DELETED .hgignore
Index: .hgignore
==================================================================
--- .hgignore
+++ .hgignore
@@ -1,8 +0,0 @@
-build/
-.lock-wscript
-.waf-*
-doc/doxygen
-data/
-doc/api
-.pyc
-.DS_Store

DELETED .hgrc
Index: .hgrc
==================================================================
--- .hgrc
+++ .hgrc
@@ -1,2 +0,0 @@
-[ui]
-username = Gavin Band <gavin.band@well.ox.ac.uk>

DELETED 3rd_party/boost_1_55_0/libs/filesystem/tools/backup.bat
Index: 3rd_party/boost_1_55_0/libs/filesystem/tools/backup.bat
==================================================================
--- 3rd_party/boost_1_55_0/libs/filesystem/tools/backup.bat
+++ 3rd_party/boost_1_55_0/libs/filesystem/tools/backup.bat
@@ -1,27 +0,0 @@
-@echo off
-
-rem  Copyright Beman Dawes 2011
-rem  Distributed under to the Boost Software License, Version 1.0 
-rem  See http://www.boost.org/LICENSE_1_0.txt
-
-if not $%1==$ goto ok
-:error
-echo Usage: backup target-directory-path
-goto done
-
-:ok
-mkdir %1\boost\filesystem 2>nul
-mkdir %1\libs\filesystem 2>nul
-
-set BOOST_CURRENT_ROOT=.
-:loop
-if exist %BOOST_CURRENT_ROOT%\boost-build.jam goto loopend
-set BOOST_CURRENT_ROOT=..\%BOOST_CURRENT_ROOT%
-goto loop
-:loopend
-
-xcopy /exclude:exclude.txt /y /d /k /r %BOOST_CURRENT_ROOT%\boost\filesystem.hpp %1\boost
-xcopy /exclude:exclude.txt /y /d /k /s /r %BOOST_CURRENT_ROOT%\boost\filesystem %1\boost\filesystem
-xcopy /exclude:exclude.txt /y /d /k /s /r %BOOST_CURRENT_ROOT%\libs\filesystem %1\libs\filesystem
-
-:done

DELETED 3rd_party/boost_1_55_0/libs/filesystem/tools/exclude.txt
Index: 3rd_party/boost_1_55_0/libs/filesystem/tools/exclude.txt
==================================================================
--- 3rd_party/boost_1_55_0/libs/filesystem/tools/exclude.txt
+++ 3rd_party/boost_1_55_0/libs/filesystem/tools/exclude.txt
@@ -1,14 +0,0 @@
-.svn
-.obj
-.exe
-.log
-.user
-.filters
-.sdf
-.ncb
-.ipch
-ipch
-Debug
-Release
-v3_operations_test
-temp_fs_test_dir

DELETED 3rd_party/boost_1_55_0/libs/regex/tools/generate/tables.cpp
Index: 3rd_party/boost_1_55_0/libs/regex/tools/generate/tables.cpp
==================================================================
--- 3rd_party/boost_1_55_0/libs/regex/tools/generate/tables.cpp
+++ 3rd_party/boost_1_55_0/libs/regex/tools/generate/tables.cpp
@@ -1,217 +0,0 @@
-/*
- *
- * Copyright (c) 2004
- * John Maddock
- *
- * Use, modification and distribution are subject to the 
- * Boost Software License, Version 1.0. (See accompanying file 
- * LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
- *
- */
-
- /*
-  *   LOCATION:    see http://www.boost.org for most recent version.
-  *   FILE         tables.cpp
-  *   VERSION      see <boost/version.hpp>
-  *   DESCRIPTION: Generates code snippets programatically, for cut-and
-  *                paste into regex source.
-  */
-
-#include <map>
-#include <vector>
-#include <string>
-#include <iostream>
-#include <algorithm>
-#include <cctype>
-#include <boost/config.hpp>
-
-std::string g_char_type;
-std::string g_data_type;
-std::map<std::string, std::string> g_table;
-std::map<std::string, std::pair<std::string, std::string> > g_help_table;
-
-void add(std::string key, std::string data)
-{
-   g_table[key] = data;
-   if(key.size() <= 2)
-      g_help_table[data].first = key;
-   else
-      g_help_table[data].second = key;
-
-   std::string::size_type i = 0;
-   while(i < key.size())
-   {
-      if(std::isspace(key[i]) || (key[i] == '-') || (key[i] == '_'))
-         key.erase(i, 1);
-      else
-      {
-         key[i] = std::tolower(key[i]);
-         ++i;
-      }
-   }
-}
-
-#define ADD(x, y) add(BOOST_STRINGIZE(x), BOOST_STRINGIZE(y))
-
-void generate_code()
-{
-   std::map<std::string, std::string>::const_iterator i, j;
-
-   // begin with the character tables:
-   std::cout << "static const " << g_char_type << " prop_name_table[] = {\n";
-   for(i = g_table.begin(), j = g_table.end(); i != j; ++i)
-   {
-      std::cout << "   /* " << i->first << " */  ";
-      for(std::string::size_type n = 0; n < i->first.size(); ++n)
-      {
-         std::cout.put('\'');
-         std::cout.put((i->first)[n]);
-         std::cout.put('\'');
-         std::cout.put(',');
-         std::cout.put(' ');
-      }
-      std::cout << std::endl;;
-   }
-   std::cout << "};\n\n";
-
-   // now the iterator table:
-   std::cout << "static const re_detail::character_pointer_range<" << g_char_type << "> range_data[] = {\n";
-   std::size_t index = 0;
-   for(i = g_table.begin(), j = g_table.end(); i != j; ++i)
-   {
-      std::cout << "   { prop_name_table+" << index << ", prop_name_table+";
-      index += i->first.size();
-      std::cout << index << ", }, // " << i->first << std::endl;
-   }
-   std::cout << "};\n\n";
-
-   // now the value table:
-   std::cout << "static const " << g_data_type << " icu_class_map[] = {\n";
-   for(i = g_table.begin(), j = g_table.end(); i != j; ++i)
-   {
-      std::cout << "   " << i->second << ", // " << i->first << std::endl;
-   }
-   std::cout << "};\n\n" << std::flush;
-   g_table.clear();
-}
-
-void generate_html()
-{
-   // start by producing a sorted list:
-   std::vector<std::pair<std::string, std::string> > v;
-   std::map<std::string, std::pair<std::string, std::string> >::const_iterator i, j;
-   i = g_help_table.begin();
-   j = g_help_table.end();
-   while(i != j)
-   {
-      v.push_back(i->second);
-      ++i;
-   }
-   std::sort(v.begin(), v.end());
-
-   std::vector<std::pair<std::string, std::string> >::const_iterator h, k;
-   h = v.begin();
-   k = v.end();
-
-   std::cout << "<table width=\"100%\"><tr><td><b>Short Name</b></td><td><b>Long Name</b></td></tr>\n";
-   while(h != k)
-   {
-      std::cout << "<tr><td>" << (h->first.size() ? h->first : std::string(" ")) << "</td><td>" << h->second << "</td></tr>\n";
-      ++h;
-   }
-   std::cout << "</table>\n\n";
-}
-
-int main()
-{
-   g_char_type = "::UChar32";
-   g_data_type = "icu_regex_traits::char_class_type";
-   ADD(L*, U_GC_L_MASK); 
-   ADD(Letter, U_GC_L_MASK); 
-   ADD(Lu, U_GC_LU_MASK); 
-   ADD(Ll, U_GC_LL_MASK); 
-   ADD(Lt, U_GC_LT_MASK); 
-   ADD(Lm, U_GC_LM_MASK); 
-   ADD(Lo, U_GC_LO_MASK); 
-   ADD(Uppercase Letter, U_GC_LU_MASK); 
-   ADD(Lowercase Letter, U_GC_LL_MASK); 
-   ADD(Titlecase Letter, U_GC_LT_MASK); 
-   ADD(Modifier Letter, U_GC_LM_MASK); 
-   ADD(Other Letter, U_GC_LO_MASK); 
-
-   ADD(M*, U_GC_M_MASK); 
-   ADD(Mn, U_GC_MN_MASK); 
-   ADD(Mc, U_GC_MC_MASK); 
-   ADD(Me, U_GC_ME_MASK); 
-   ADD(Mark, U_GC_M_MASK); 
-   ADD(Non-Spacing Mark, U_GC_MN_MASK); 
-   ADD(Spacing Combining Mark, U_GC_MC_MASK); 
-   ADD(Enclosing Mark, U_GC_ME_MASK); 
-
-   ADD(N*, U_GC_N_MASK); 
-   ADD(Nd, U_GC_ND_MASK); 
-   ADD(Nl, U_GC_NL_MASK); 
-   ADD(No, U_GC_NO_MASK);
-   ADD(Number, U_GC_N_MASK); 
-   ADD(Decimal Digit Number, U_GC_ND_MASK); 
-   ADD(Letter Number, U_GC_NL_MASK); 
-   ADD(Other Number, U_GC_NO_MASK);
-
-   ADD(S*, U_GC_S_MASK); 
-   ADD(Sm, U_GC_SM_MASK); 
-   ADD(Sc, U_GC_SC_MASK); 
-   ADD(Sk, U_GC_SK_MASK); 
-   ADD(So, U_GC_SO_MASK); 
-   ADD(Symbol, U_GC_S_MASK); 
-   ADD(Math Symbol, U_GC_SM_MASK); 
-   ADD(Currency Symbol, U_GC_SC_MASK); 
-   ADD(Modifier Symbol, U_GC_SK_MASK); 
-   ADD(Other Symbol, U_GC_SO_MASK); 
-
-   ADD(P*, U_GC_P_MASK); 
-   ADD(Pc, U_GC_PC_MASK); 
-   ADD(Pd, U_GC_PD_MASK); 
-   ADD(Ps, U_GC_PS_MASK); 
-   ADD(Pe, U_GC_PE_MASK); 
-   ADD(Pi, U_GC_PI_MASK); 
-   ADD(Pf, U_GC_PF_MASK); 
-   ADD(Po, U_GC_PO_MASK); 
-   ADD(Punctuation, U_GC_P_MASK); 
-   ADD(Connector Punctuation, U_GC_PC_MASK); 
-   ADD(Dash Punctuation, U_GC_PD_MASK); 
-   ADD(Open Punctuation, U_GC_PS_MASK); 
-   ADD(Close Punctuation, U_GC_PE_MASK); 
-   ADD(Initial Punctuation, U_GC_PI_MASK); 
-   ADD(Final Punctuation, U_GC_PF_MASK); 
-   ADD(Other Punctuation, U_GC_PO_MASK); 
-
-   ADD(Z*, U_GC_Z_MASK); 
-   ADD(Zs, U_GC_ZS_MASK); 
-   ADD(Zl, U_GC_ZL_MASK); 
-   ADD(Zp, U_GC_ZP_MASK); 
-   ADD(Separator, U_GC_Z_MASK); 
-   ADD(Space Separator, U_GC_ZS_MASK); 
-   ADD(Line Separator, U_GC_ZL_MASK); 
-   ADD(Paragraph Separator, U_GC_ZP_MASK); 
-
-   ADD(C*, U_GC_C_MASK); 
-   ADD(Cc, U_GC_CC_MASK); 
-   ADD(Cf, U_GC_CF_MASK); 
-   ADD(Cs, U_GC_CS_MASK); 
-   ADD(Co, U_GC_CO_MASK); 
-   ADD(Cn, U_GC_CN_MASK); 
-   ADD(Other, U_GC_C_MASK); 
-   ADD(Control, U_GC_CC_MASK); 
-   ADD(Format, U_GC_CF_MASK); 
-   ADD(Surrogate, U_GC_CS_MASK); 
-   ADD(Private Use, U_GC_CO_MASK); 
-   ADD(Not Assigned, U_GC_CN_MASK); 
-   ADD(Any, icu_regex_traits::mask_any); 
-   ADD(Assigned, (0x3FFFFFFFu) & ~(U_GC_CN_MASK)); 
-   ADD(ASCII, icu_regex_traits::mask_ascii); 
-   ADD(Titlecase, U_GC_LT_MASK); 
-
-   generate_code();
-   generate_html();
-   return 0;
-}

DELETED 3rd_party/boost_1_55_0/libs/test/Jamfile.v2
Index: 3rd_party/boost_1_55_0/libs/test/Jamfile.v2
==================================================================
--- 3rd_party/boost_1_55_0/libs/test/Jamfile.v2
+++ 3rd_party/boost_1_55_0/libs/test/Jamfile.v2
@@ -1,10 +0,0 @@
-#  (C) Copyright Juergen Hunold 2006.
-#  Use, modification, and distribution are subject to the 
-#  Boost Software License, Version 1.0. (See accompanying file 
-#  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-#
-#  See http://www.boost.org/libs/test for the library home page.
-
-build-project example ;
-build-project test ;
-

DELETED 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/Jamfile.v2
Index: 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/Jamfile.v2
==================================================================
--- 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/Jamfile.v2
+++ 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/Jamfile.v2
@@ -1,38 +0,0 @@
-#  (C) Copyright Gennadiy Rozental 2008-2008.
-#  Use, modification, and distribution are subject to the 
-#  Boost Software License, Version 1.0. (See accompanying file 
-#  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-#
-#  See http://www.boost.org/libs/test for the library home page.
-
-# Project
-project libs/test/tools/console_test_runner ;
-
-alias unit_test_framework
-    : # sources
-        /boost//unit_test_framework
-    ;        
-
-alias test_runner_src
-    : # sources
-      src/console_test_runner.cpp
-      unit_test_framework  
-    ;        
-
-# make aliases explicit so the libraries will only be built when requested
-explicit unit_test_framework ;
-explicit test_runner_src ;
-
-lib dl ; 
-
-lib test_runner_test : test/test_runner_test.cpp unit_test_framework ; 
-
-exe console_test_runner 
-    : test_runner_src
-      dl 
-    ;
-
-exe console_test_runner 
-    : test_runner_src
-    : <target-os>windows
-    ;

DELETED 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/src/console_test_runner.cpp
Index: 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/src/console_test_runner.cpp
==================================================================
--- 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/src/console_test_runner.cpp
+++ 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/src/console_test_runner.cpp
@@ -1,197 +0,0 @@
-//  (C) Copyright Gennadiy Rozental 2005-2007.
-//  Distributed under the Boost Software License, Version 1.0.
-//  (See accompanying file LICENSE_1_0.txt or copy at 
-//  http://www.boost.org/LICENSE_1_0.txt)
-
-//  See http://www.boost.org/libs/test for the library home page.
-
-// Boost.Test
-#ifndef BOOST_TEST_DYN_LINK
-#define BOOST_TEST_DYN_LINK
-#endif
-#include <boost/test/unit_test.hpp>
-
-// Boost.Runtime.Param
-#include <boost/test/utils/runtime/cla/named_parameter.hpp>
-#include <boost/test/utils/runtime/cla/parser.hpp>
-
-namespace rt  = boost::runtime;
-namespace cla = boost::runtime::cla;
-
-// STL
-#include <iostream>
-
-//_________________________________________________________________//
-
-// System API
-
-namespace dyn_lib {
-
-#if defined(BOOST_WINDOWS) && !defined(BOOST_DISABLE_WIN32) // WIN32 API
-
-#include <windows.h>
-
-typedef HINSTANCE handle;
-
-inline handle
-open( std::string const& file_name )
-{
-    return LoadLibrary( file_name.c_str() );
-}
-
-//_________________________________________________________________//
-
-template<typename TargType>
-inline TargType
-locate_symbol( handle h, std::string const& symbol )
-{
-    return reinterpret_cast<TargType>( GetProcAddress( h, symbol.c_str() ) );
-}
-
-//_________________________________________________________________//
-
-inline void
-close( handle h )
-{
-    if( h )
-        FreeLibrary( h );
-}
-
-//_________________________________________________________________//
-
-inline std::string
-error()
-{
-    LPTSTR msg = NULL;
-
-    FormatMessage( FORMAT_MESSAGE_ALLOCATE_BUFFER | FORMAT_MESSAGE_FROM_SYSTEM,
-                   NULL, 
-                   GetLastError(), 
-                   MAKELANGID(LANG_NEUTRAL, SUBLANG_DEFAULT),
-                   (LPTSTR)&msg, 
-                   0, NULL );
-
-    std::string res( msg );
-
-    if( msg )
-        LocalFree( msg );
-
-    return res;    
-}
-
-//_________________________________________________________________//
-
-#elif defined(BOOST_HAS_UNISTD_H) // POSIX API
-
-#include <dlfcn.h>
-
-#include <sys/types.h>
-#include <sys/stat.h>
-#include <fcntl.h>
-
-
-typedef void* handle;
-
-inline handle
-open( std::string const& file_name )
-{
-    return dlopen( file_name.c_str(), RTLD_LOCAL | RTLD_LAZY );
-}
-
-//_________________________________________________________________//
-
-template<typename TargType>
-inline TargType
-locate_symbol( handle h, std::string const& symbol )
-{
-    return reinterpret_cast<TargType>( dlsym( h, symbol.c_str() ) );
-}
-
-//_________________________________________________________________//
-
-inline void
-close( handle h )
-{
-    if( h )
-        dlclose( h );
-}
-
-//_________________________________________________________________//
-
-inline std::string
-error()
-{
-    return dlerror();
-}
-
-//_________________________________________________________________//
-
-#else
-
-#error "Dynamic library API is unknown"
-
-#endif
-
-} // namespace dyn_lib
-
-//____________________________________________________________________________//
-
-static std::string test_lib_name;
-static std::string init_func_name( "init_unit_test" );
-
-dyn_lib::handle test_lib_handle;
-
-bool load_test_lib()
-{
-    typedef bool (*init_func_ptr)();
-    init_func_ptr init_func;
-
-    test_lib_handle = dyn_lib::open( test_lib_name );
-    if( !test_lib_handle )
-        throw std::logic_error( std::string("Fail to load test library: ")
-                                    .append( dyn_lib::error() ) );
-
-    init_func =  dyn_lib::locate_symbol<init_func_ptr>( test_lib_handle, init_func_name );
-    
-    if( !init_func )
-        throw std::logic_error( std::string("Can't locate test initilization function ")
-                                    .append( init_func_name )
-                                    .append( ": " )
-                                    .append( dyn_lib::error() ) );
-   
-    return (*init_func)();
-}
-
-//____________________________________________________________________________//
-
-int main( int argc, char* argv[] )
-{
-    try {
-        cla::parser P;
-
-        P - cla::ignore_mismatch 
-            << cla::named_parameter<rt::cstring>( "test" ) - (cla::prefix = "--")
-            << cla::named_parameter<rt::cstring>( "init" ) - (cla::prefix = "--",cla::optional);
-
-        P.parse( argc, argv );
-
-        assign_op( test_lib_name, P.get( "test" ), 0 );
-        if( P["init"] )
-            assign_op( init_func_name, P.get( "init" ), 0 );
-
-        int res = ::boost::unit_test::unit_test_main( &load_test_lib, argc, argv );
-
-        ::boost::unit_test::framework::clear();
-        dyn_lib::close( test_lib_handle );
-
-        return res;
-    }
-    catch( rt::logic_error const& ex ) {
-        std::cout << "Fail to parse command line arguments: " << ex.msg() << std::endl;
-        return -1;
-    }
-}
-
-//____________________________________________________________________________//
-
-// EOF

DELETED 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/test/test_runner_test.cpp
Index: 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/test/test_runner_test.cpp
==================================================================
--- 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/test/test_runner_test.cpp
+++ 3rd_party/boost_1_55_0/libs/test/tools/console_test_runner/test/test_runner_test.cpp
@@ -1,53 +0,0 @@
-//  (C) Copyright Gennadiy Rozental 2005-2007.
-//  Distributed under the Boost Software License, Version 1.0.
-//  (See accompanying file LICENSE_1_0.txt or copy at 
-//  http://www.boost.org/LICENSE_1_0.txt)
-
-//  See http://www.boost.org/libs/test for the library home page.
-
-// Boost.Test
-#ifndef BOOST_TEST_DYN_LINK 
-#define BOOST_TEST_DYN_LINK
-#endif
-#include <boost/test/unit_test.hpp>
-using namespace boost::unit_test;
-
-//____________________________________________________________________________//
-
-BOOST_AUTO_TEST_CASE( test1 )
-{
-    int i = 0;
-
-    BOOST_CHECK_EQUAL( i, 2 );
-}
-
-//____________________________________________________________________________//
-
-BOOST_AUTO_TEST_CASE( test2 )
-{
-    BOOST_CHECKPOINT("About to force division by zero!");
-    int i = 1, j = 0;
-
-    i = i / j;
-}
-
-//____________________________________________________________________________//
-
-extern "C" {
-
-#ifdef BOOST_WINDOWS
-__declspec(dllexport)
-#endif
- bool
-init_unit_test()
-{
-    framework::master_test_suite().p_name.value = "Test runner test";
-
-    return true;
-}
-
-}
-
-//____________________________________________________________________________//
-
-// EOF

Index: 3rd_party/boost_1_55_0/wscript
==================================================================
--- 3rd_party/boost_1_55_0/wscript
+++ 3rd_party/boost_1_55_0/wscript
@@ -1,44 +1,47 @@
-import os.path
-import glob
-
 def configure( conf ):
 	pass
 
 def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld(
-		features = 'cxx cstaticlib',
-		name = 'boost',
-		target = 'boost',
-		source = [
-			'libs/iostreams/src/file_descriptor.cpp',
-			'libs/iostreams/src/gzip.cpp',
-			'libs/iostreams/src/mapped_file.cpp',
-			'libs/iostreams/src/zlib.cpp'
-			] +
-			bld.glob( 'libs/system/src/*.cpp' ) +
-			bld.glob( 'libs/regex/src/*.cpp' ) +
-			bld.glob( 'libs/thread/src/*.cpp' ) +
-			bld.glob( 'libs/thread/src/pthread/*.cpp' ) +
-			bld.glob( 'libs/filesystem/src/*.cpp' ) +
-			bld.glob( 'libs/date_time/src/posix_time/*.cpp' ) +
-			bld.glob( 'libs/timer/src/*.cpp' ) +
-			bld.glob( 'libs/chrono/src/*.cpp' ),
-		includes = './',
-		export_incdirs = './', 
-		uselib = 'ZLIB RT',
-		cxxflags = [ '-Wno-unused-function', '-Wno-keyword-macro', '-Wno-unused-const-variable' ]
-	)
-
-	bld(
-		features = 'cxx cstaticlib',
-		target = 'boost-unit_test_framework',
+	sources = (
+		[
+            'libs/iostreams/src/file_descriptor.cpp',
+            'libs/iostreams/src/gzip.cpp',
+            'libs/iostreams/src/mapped_file.cpp',
+            'libs/iostreams/src/zlib.cpp'
+		] +
+		bld.path.ant_glob( 'libs/system/src/*.cpp' ) +
+		bld.path.ant_glob( 'libs/regex/src/*.cpp' ) +
+		bld.path.ant_glob( 'libs/thread/src/*.cpp' ) +
+		bld.path.ant_glob( 'libs/thread/src/pthread/once_atomic.cpp' ) +
+		bld.path.ant_glob( 'libs/thread/src/pthread/thread.cpp' ) +
+		bld.path.ant_glob( 'libs/filesystem/src/*.cpp' ) +
+		bld.path.ant_glob( 'libs/date_time/src/posix_time/*.cpp' ) +
+		bld.path.ant_glob( 'libs/timer/src/*.cpp' ) +
+		bld.path.ant_glob( 'libs/chrono/src/*.cpp' )
+	)
+
+	bld.stlib(
+		target = 'boost',
+		source = sources,
+		includes = './',
+		export_includes = './', 
+		uselib = 'ZLIB BZIP2 rt',
+		cxxflags = [
+			'-std=c++11',
+			'-Wno-unused-local-typedefs',
+			'-Wno-c++11-long-long',
+			'-Wno-keyword-macro',
+			'-Wno-unused-const-variable',
+			'-Wno-deprecated-register',
+			'-Wno-unused-function',
+			'-Wno-redeclared-class-member'
+		]
+	)
+
+	bld.stlib(
+		target = 'boost_unit_test_framework',
 		source = [
 			'libs/test/src/compiler_log_formatter.cpp',
 			'libs/test/src/debug.cpp',
 			'libs/test/src/exception_safety.cpp',
 			'libs/test/src/execution_monitor.cpp',
@@ -57,9 +60,8 @@
 			'libs/test/src/unit_test_parameters.cpp',
 			'libs/test/src/unit_test_suite.cpp',
 			'libs/test/src/xml_log_formatter.cpp',
 			'libs/test/src/xml_report_formatter.cpp'
 		],
-		includes='./',
-		export_incdirs = './',
-		cxxflags = [ '-Wunused-function' ]
+		includes = './',
+		export_includes = './'
 	)

ADDED   3rd_party/catch/catch.hpp
Index: 3rd_party/catch/catch.hpp
==================================================================
--- 3rd_party/catch/catch.hpp
+++ 3rd_party/catch/catch.hpp
@@ -0,0 +1,17618 @@
+/*
+ *  Catch v2.11.3
+ *  Generated: 2020-03-19 13:44:21.042491
+ *  ----------------------------------------------------------
+ *  This file has been merged from multiple headers. Please don't edit it directly
+ *  Copyright (c) 2020 Two Blue Cubes Ltd. All rights reserved.
+ *
+ *  Distributed under the Boost Software License, Version 1.0. (See accompanying
+ *  file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+ */
+#ifndef TWOBLUECUBES_SINGLE_INCLUDE_CATCH_HPP_INCLUDED
+#define TWOBLUECUBES_SINGLE_INCLUDE_CATCH_HPP_INCLUDED
+// start catch.hpp
+
+
+#define CATCH_VERSION_MAJOR 2
+#define CATCH_VERSION_MINOR 11
+#define CATCH_VERSION_PATCH 3
+
+#ifdef __clang__
+#    pragma clang system_header
+#elif defined __GNUC__
+#    pragma GCC system_header
+#endif
+
+// start catch_suppress_warnings.h
+
+#ifdef __clang__
+#   ifdef __ICC // icpc defines the __clang__ macro
+#       pragma warning(push)
+#       pragma warning(disable: 161 1682)
+#   else // __ICC
+#       pragma clang diagnostic push
+#       pragma clang diagnostic ignored "-Wpadded"
+#       pragma clang diagnostic ignored "-Wswitch-enum"
+#       pragma clang diagnostic ignored "-Wcovered-switch-default"
+#    endif
+#elif defined __GNUC__
+     // Because REQUIREs trigger GCC's -Wparentheses, and because still
+     // supported version of g++ have only buggy support for _Pragmas,
+     // Wparentheses have to be suppressed globally.
+#    pragma GCC diagnostic ignored "-Wparentheses" // See #674 for details
+
+#    pragma GCC diagnostic push
+#    pragma GCC diagnostic ignored "-Wunused-variable"
+#    pragma GCC diagnostic ignored "-Wpadded"
+#endif
+// end catch_suppress_warnings.h
+#if defined(CATCH_CONFIG_MAIN) || defined(CATCH_CONFIG_RUNNER)
+#  define CATCH_IMPL
+#  define CATCH_CONFIG_ALL_PARTS
+#endif
+
+// In the impl file, we want to have access to all parts of the headers
+// Can also be used to sanely support PCHs
+#if defined(CATCH_CONFIG_ALL_PARTS)
+#  define CATCH_CONFIG_EXTERNAL_INTERFACES
+#  if defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#    undef CATCH_CONFIG_DISABLE_MATCHERS
+#  endif
+#  if !defined(CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER)
+#    define CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER
+#  endif
+#endif
+
+#if !defined(CATCH_CONFIG_IMPL_ONLY)
+// start catch_platform.h
+
+#ifdef __APPLE__
+# include <TargetConditionals.h>
+# if TARGET_OS_OSX == 1
+#  define CATCH_PLATFORM_MAC
+# elif TARGET_OS_IPHONE == 1
+#  define CATCH_PLATFORM_IPHONE
+# endif
+
+#elif defined(linux) || defined(__linux) || defined(__linux__)
+#  define CATCH_PLATFORM_LINUX
+
+#elif defined(WIN32) || defined(__WIN32__) || defined(_WIN32) || defined(_MSC_VER) || defined(__MINGW32__)
+#  define CATCH_PLATFORM_WINDOWS
+#endif
+
+// end catch_platform.h
+
+#ifdef CATCH_IMPL
+#  ifndef CLARA_CONFIG_MAIN
+#    define CLARA_CONFIG_MAIN_NOT_DEFINED
+#    define CLARA_CONFIG_MAIN
+#  endif
+#endif
+
+// start catch_user_interfaces.h
+
+namespace Catch {
+    unsigned int rngSeed();
+}
+
+// end catch_user_interfaces.h
+// start catch_tag_alias_autoregistrar.h
+
+// start catch_common.h
+
+// start catch_compiler_capabilities.h
+
+// Detect a number of compiler features - by compiler
+// The following features are defined:
+//
+// CATCH_CONFIG_COUNTER : is the __COUNTER__ macro supported?
+// CATCH_CONFIG_WINDOWS_SEH : is Windows SEH supported?
+// CATCH_CONFIG_POSIX_SIGNALS : are POSIX signals supported?
+// CATCH_CONFIG_DISABLE_EXCEPTIONS : Are exceptions enabled?
+// ****************
+// Note to maintainers: if new toggles are added please document them
+// in configuration.md, too
+// ****************
+
+// In general each macro has a _NO_<feature name> form
+// (e.g. CATCH_CONFIG_NO_POSIX_SIGNALS) which disables the feature.
+// Many features, at point of detection, define an _INTERNAL_ macro, so they
+// can be combined, en-mass, with the _NO_ forms later.
+
+#ifdef __cplusplus
+
+#  if (__cplusplus >= 201402L) || (defined(_MSVC_LANG) && _MSVC_LANG >= 201402L)
+#    define CATCH_CPP14_OR_GREATER
+#  endif
+
+#  if (__cplusplus >= 201703L) || (defined(_MSVC_LANG) && _MSVC_LANG >= 201703L)
+#    define CATCH_CPP17_OR_GREATER
+#  endif
+
+#endif
+
+#if defined(CATCH_CPP17_OR_GREATER)
+#  define CATCH_INTERNAL_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS
+#endif
+
+// We have to avoid both ICC and Clang, because they try to mask themselves
+// as gcc, and we want only GCC in this block
+#if defined(__GNUC__) && !defined(__clang__) && !defined(__ICC)
+#    define CATCH_INTERNAL_START_WARNINGS_SUPPRESSION _Pragma( "GCC diagnostic push" )
+#    define CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION  _Pragma( "GCC diagnostic pop" )
+
+#    define CATCH_INTERNAL_IGNORE_BUT_WARN(...) (void)__builtin_constant_p(__VA_ARGS__)
+
+#endif
+
+#if defined(__clang__)
+
+#    define CATCH_INTERNAL_START_WARNINGS_SUPPRESSION _Pragma( "clang diagnostic push" )
+#    define CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION  _Pragma( "clang diagnostic pop" )
+
+#    define CATCH_INTERNAL_IGNORE_BUT_WARN(...) (void)__builtin_constant_p(__VA_ARGS__)
+
+#    define CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wexit-time-destructors\"" ) \
+         _Pragma( "clang diagnostic ignored \"-Wglobal-constructors\"")
+
+#    define CATCH_INTERNAL_SUPPRESS_PARENTHESES_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wparentheses\"" )
+
+#    define CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wunused-variable\"" )
+
+#    define CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wgnu-zero-variadic-macro-arguments\"" )
+
+#    define CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wunused-template\"" )
+
+#endif // __clang__
+
+////////////////////////////////////////////////////////////////////////////////
+// Assume that non-Windows platforms support posix signals by default
+#if !defined(CATCH_PLATFORM_WINDOWS)
+    #define CATCH_INTERNAL_CONFIG_POSIX_SIGNALS
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// We know some environments not to support full POSIX signals
+#if defined(__CYGWIN__) || defined(__QNX__) || defined(__EMSCRIPTEN__) || defined(__DJGPP__)
+    #define CATCH_INTERNAL_CONFIG_NO_POSIX_SIGNALS
+#endif
+
+#ifdef __OS400__
+#       define CATCH_INTERNAL_CONFIG_NO_POSIX_SIGNALS
+#       define CATCH_CONFIG_COLOUR_NONE
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// Android somehow still does not support std::to_string
+#if defined(__ANDROID__)
+#    define CATCH_INTERNAL_CONFIG_NO_CPP11_TO_STRING
+#    define CATCH_INTERNAL_CONFIG_ANDROID_LOGWRITE
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// Not all Windows environments support SEH properly
+#if defined(__MINGW32__)
+#    define CATCH_INTERNAL_CONFIG_NO_WINDOWS_SEH
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// PS4
+#if defined(__ORBIS__)
+#    define CATCH_INTERNAL_CONFIG_NO_NEW_CAPTURE
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// Cygwin
+#ifdef __CYGWIN__
+
+// Required for some versions of Cygwin to declare gettimeofday
+// see: http://stackoverflow.com/questions/36901803/gettimeofday-not-declared-in-this-scope-cygwin
+#   define _BSD_SOURCE
+// some versions of cygwin (most) do not support std::to_string. Use the libstd check.
+// https://gcc.gnu.org/onlinedocs/gcc-4.8.2/libstdc++/api/a01053_source.html line 2812-2813
+# if !((__cplusplus >= 201103L) && defined(_GLIBCXX_USE_C99) \
+           && !defined(_GLIBCXX_HAVE_BROKEN_VSWPRINTF))
+
+#    define CATCH_INTERNAL_CONFIG_NO_CPP11_TO_STRING
+
+# endif
+#endif // __CYGWIN__
+
+////////////////////////////////////////////////////////////////////////////////
+// Visual C++
+#if defined(_MSC_VER)
+
+#  define CATCH_INTERNAL_START_WARNINGS_SUPPRESSION __pragma( warning(push) )
+#  define CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION  __pragma( warning(pop) )
+
+#  if _MSC_VER >= 1900 // Visual Studio 2015 or newer
+#    define CATCH_INTERNAL_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS
+#  endif
+
+// Universal Windows platform does not support SEH
+// Or console colours (or console at all...)
+#  if defined(WINAPI_FAMILY) && (WINAPI_FAMILY == WINAPI_FAMILY_APP)
+#    define CATCH_CONFIG_COLOUR_NONE
+#  else
+#    define CATCH_INTERNAL_CONFIG_WINDOWS_SEH
+#  endif
+
+// MSVC traditional preprocessor needs some workaround for __VA_ARGS__
+// _MSVC_TRADITIONAL == 0 means new conformant preprocessor
+// _MSVC_TRADITIONAL == 1 means old traditional non-conformant preprocessor
+#  if !defined(__clang__) // Handle Clang masquerading for msvc
+#    if !defined(_MSVC_TRADITIONAL) || (defined(_MSVC_TRADITIONAL) && _MSVC_TRADITIONAL)
+#      define CATCH_INTERNAL_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#    endif // MSVC_TRADITIONAL
+#  endif // __clang__
+
+#endif // _MSC_VER
+
+#if defined(_REENTRANT) || defined(_MSC_VER)
+// Enable async processing, as -pthread is specified or no additional linking is required
+# define CATCH_INTERNAL_CONFIG_USE_ASYNC
+#endif // _MSC_VER
+
+////////////////////////////////////////////////////////////////////////////////
+// Check if we are compiled with -fno-exceptions or equivalent
+#if defined(__EXCEPTIONS) || defined(__cpp_exceptions) || defined(_CPPUNWIND)
+#  define CATCH_INTERNAL_CONFIG_EXCEPTIONS_ENABLED
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// DJGPP
+#ifdef __DJGPP__
+#  define CATCH_INTERNAL_CONFIG_NO_WCHAR
+#endif // __DJGPP__
+
+////////////////////////////////////////////////////////////////////////////////
+// Embarcadero C++Build
+#if defined(__BORLANDC__)
+    #define CATCH_INTERNAL_CONFIG_POLYFILL_ISNAN
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+
+// Use of __COUNTER__ is suppressed during code analysis in
+// CLion/AppCode 2017.2.x and former, because __COUNTER__ is not properly
+// handled by it.
+// Otherwise all supported compilers support COUNTER macro,
+// but user still might want to turn it off
+#if ( !defined(__JETBRAINS_IDE__) || __JETBRAINS_IDE__ >= 20170300L )
+    #define CATCH_INTERNAL_CONFIG_COUNTER
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+
+// RTX is a special version of Windows that is real time.
+// This means that it is detected as Windows, but does not provide
+// the same set of capabilities as real Windows does.
+#if defined(UNDER_RTSS) || defined(RTX64_BUILD)
+    #define CATCH_INTERNAL_CONFIG_NO_WINDOWS_SEH
+    #define CATCH_INTERNAL_CONFIG_NO_ASYNC
+    #define CATCH_CONFIG_COLOUR_NONE
+#endif
+
+#if !defined(_GLIBCXX_USE_C99_MATH_TR1)
+#define CATCH_INTERNAL_CONFIG_GLOBAL_NEXTAFTER
+#endif
+
+// Various stdlib support checks that require __has_include
+#if defined(__has_include)
+  // Check if string_view is available and usable
+  #if __has_include(<string_view>) && defined(CATCH_CPP17_OR_GREATER)
+  #    define CATCH_INTERNAL_CONFIG_CPP17_STRING_VIEW
+  #endif
+
+  // Check if optional is available and usable
+  #  if __has_include(<optional>) && defined(CATCH_CPP17_OR_GREATER)
+  #    define CATCH_INTERNAL_CONFIG_CPP17_OPTIONAL
+  #  endif // __has_include(<optional>) && defined(CATCH_CPP17_OR_GREATER)
+
+  // Check if byte is available and usable
+  #  if __has_include(<cstddef>) && defined(CATCH_CPP17_OR_GREATER)
+  #    define CATCH_INTERNAL_CONFIG_CPP17_BYTE
+  #  endif // __has_include(<cstddef>) && defined(CATCH_CPP17_OR_GREATER)
+
+  // Check if variant is available and usable
+  #  if __has_include(<variant>) && defined(CATCH_CPP17_OR_GREATER)
+  #    if defined(__clang__) && (__clang_major__ < 8)
+         // work around clang bug with libstdc++ https://bugs.llvm.org/show_bug.cgi?id=31852
+         // fix should be in clang 8, workaround in libstdc++ 8.2
+  #      include <ciso646>
+  #      if defined(__GLIBCXX__) && defined(_GLIBCXX_RELEASE) && (_GLIBCXX_RELEASE < 9)
+  #        define CATCH_CONFIG_NO_CPP17_VARIANT
+  #      else
+  #        define CATCH_INTERNAL_CONFIG_CPP17_VARIANT
+  #      endif // defined(__GLIBCXX__) && defined(_GLIBCXX_RELEASE) && (_GLIBCXX_RELEASE < 9)
+  #    else
+  #      define CATCH_INTERNAL_CONFIG_CPP17_VARIANT
+  #    endif // defined(__clang__) && (__clang_major__ < 8)
+  #  endif // __has_include(<variant>) && defined(CATCH_CPP17_OR_GREATER)
+#endif // defined(__has_include)
+
+#if defined(CATCH_INTERNAL_CONFIG_COUNTER) && !defined(CATCH_CONFIG_NO_COUNTER) && !defined(CATCH_CONFIG_COUNTER)
+#   define CATCH_CONFIG_COUNTER
+#endif
+#if defined(CATCH_INTERNAL_CONFIG_WINDOWS_SEH) && !defined(CATCH_CONFIG_NO_WINDOWS_SEH) && !defined(CATCH_CONFIG_WINDOWS_SEH) && !defined(CATCH_INTERNAL_CONFIG_NO_WINDOWS_SEH)
+#   define CATCH_CONFIG_WINDOWS_SEH
+#endif
+// This is set by default, because we assume that unix compilers are posix-signal-compatible by default.
+#if defined(CATCH_INTERNAL_CONFIG_POSIX_SIGNALS) && !defined(CATCH_INTERNAL_CONFIG_NO_POSIX_SIGNALS) && !defined(CATCH_CONFIG_NO_POSIX_SIGNALS) && !defined(CATCH_CONFIG_POSIX_SIGNALS)
+#   define CATCH_CONFIG_POSIX_SIGNALS
+#endif
+// This is set by default, because we assume that compilers with no wchar_t support are just rare exceptions.
+#if !defined(CATCH_INTERNAL_CONFIG_NO_WCHAR) && !defined(CATCH_CONFIG_NO_WCHAR) && !defined(CATCH_CONFIG_WCHAR)
+#   define CATCH_CONFIG_WCHAR
+#endif
+
+#if !defined(CATCH_INTERNAL_CONFIG_NO_CPP11_TO_STRING) && !defined(CATCH_CONFIG_NO_CPP11_TO_STRING) && !defined(CATCH_CONFIG_CPP11_TO_STRING)
+#    define CATCH_CONFIG_CPP11_TO_STRING
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_OPTIONAL) && !defined(CATCH_CONFIG_NO_CPP17_OPTIONAL) && !defined(CATCH_CONFIG_CPP17_OPTIONAL)
+#  define CATCH_CONFIG_CPP17_OPTIONAL
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS) && !defined(CATCH_CONFIG_NO_CPP17_UNCAUGHT_EXCEPTIONS) && !defined(CATCH_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS)
+#  define CATCH_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_STRING_VIEW) && !defined(CATCH_CONFIG_NO_CPP17_STRING_VIEW) && !defined(CATCH_CONFIG_CPP17_STRING_VIEW)
+#  define CATCH_CONFIG_CPP17_STRING_VIEW
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_VARIANT) && !defined(CATCH_CONFIG_NO_CPP17_VARIANT) && !defined(CATCH_CONFIG_CPP17_VARIANT)
+#  define CATCH_CONFIG_CPP17_VARIANT
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_BYTE) && !defined(CATCH_CONFIG_NO_CPP17_BYTE) && !defined(CATCH_CONFIG_CPP17_BYTE)
+#  define CATCH_CONFIG_CPP17_BYTE
+#endif
+
+#if defined(CATCH_CONFIG_EXPERIMENTAL_REDIRECT)
+#  define CATCH_INTERNAL_CONFIG_NEW_CAPTURE
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_NEW_CAPTURE) && !defined(CATCH_INTERNAL_CONFIG_NO_NEW_CAPTURE) && !defined(CATCH_CONFIG_NO_NEW_CAPTURE) && !defined(CATCH_CONFIG_NEW_CAPTURE)
+#  define CATCH_CONFIG_NEW_CAPTURE
+#endif
+
+#if !defined(CATCH_INTERNAL_CONFIG_EXCEPTIONS_ENABLED) && !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+#  define CATCH_CONFIG_DISABLE_EXCEPTIONS
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_POLYFILL_ISNAN) && !defined(CATCH_CONFIG_NO_POLYFILL_ISNAN) && !defined(CATCH_CONFIG_POLYFILL_ISNAN)
+#  define CATCH_CONFIG_POLYFILL_ISNAN
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_USE_ASYNC)  && !defined(CATCH_INTERNAL_CONFIG_NO_ASYNC) && !defined(CATCH_CONFIG_NO_USE_ASYNC) && !defined(CATCH_CONFIG_USE_ASYNC)
+#  define CATCH_CONFIG_USE_ASYNC
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_ANDROID_LOGWRITE) && !defined(CATCH_CONFIG_NO_ANDROID_LOGWRITE) && !defined(CATCH_CONFIG_ANDROID_LOGWRITE)
+#  define CATCH_CONFIG_ANDROID_LOGWRITE
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_GLOBAL_NEXTAFTER) && !defined(CATCH_CONFIG_NO_GLOBAL_NEXTAFTER) && !defined(CATCH_CONFIG_GLOBAL_NEXTAFTER)
+#  define CATCH_CONFIG_GLOBAL_NEXTAFTER
+#endif
+
+// Even if we do not think the compiler has that warning, we still have
+// to provide a macro that can be used by the code.
+#if !defined(CATCH_INTERNAL_START_WARNINGS_SUPPRESSION)
+#   define CATCH_INTERNAL_START_WARNINGS_SUPPRESSION
+#endif
+#if !defined(CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION)
+#   define CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+#endif
+#if !defined(CATCH_INTERNAL_SUPPRESS_PARENTHESES_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_PARENTHESES_WARNINGS
+#endif
+#if !defined(CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS
+#endif
+#if !defined(CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS
+#endif
+#if !defined(CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS
+#endif
+
+// The goal of this macro is to avoid evaluation of the arguments, but
+// still have the compiler warn on problems inside...
+#if !defined(CATCH_INTERNAL_IGNORE_BUT_WARN)
+#   define CATCH_INTERNAL_IGNORE_BUT_WARN(...)
+#endif
+
+#if defined(__APPLE__) && defined(__apple_build_version__) && (__clang_major__ < 10)
+#   undef CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS
+#elif defined(__clang__) && (__clang_major__ < 5)
+#   undef CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS
+#endif
+
+#if !defined(CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS
+#endif
+
+#if defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+#define CATCH_TRY if ((true))
+#define CATCH_CATCH_ALL if ((false))
+#define CATCH_CATCH_ANON(type) if ((false))
+#else
+#define CATCH_TRY try
+#define CATCH_CATCH_ALL catch (...)
+#define CATCH_CATCH_ANON(type) catch (type)
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR) && !defined(CATCH_CONFIG_NO_TRADITIONAL_MSVC_PREPROCESSOR) && !defined(CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR)
+#define CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#endif
+
+// end catch_compiler_capabilities.h
+#define INTERNAL_CATCH_UNIQUE_NAME_LINE2( name, line ) name##line
+#define INTERNAL_CATCH_UNIQUE_NAME_LINE( name, line ) INTERNAL_CATCH_UNIQUE_NAME_LINE2( name, line )
+#ifdef CATCH_CONFIG_COUNTER
+#  define INTERNAL_CATCH_UNIQUE_NAME( name ) INTERNAL_CATCH_UNIQUE_NAME_LINE( name, __COUNTER__ )
+#else
+#  define INTERNAL_CATCH_UNIQUE_NAME( name ) INTERNAL_CATCH_UNIQUE_NAME_LINE( name, __LINE__ )
+#endif
+
+#include <iosfwd>
+#include <string>
+#include <cstdint>
+
+// We need a dummy global operator<< so we can bring it into Catch namespace later
+struct Catch_global_namespace_dummy {};
+std::ostream& operator<<(std::ostream&, Catch_global_namespace_dummy);
+
+namespace Catch {
+
+    struct CaseSensitive { enum Choice {
+        Yes,
+        No
+    }; };
+
+    class NonCopyable {
+        NonCopyable( NonCopyable const& )              = delete;
+        NonCopyable( NonCopyable && )                  = delete;
+        NonCopyable& operator = ( NonCopyable const& ) = delete;
+        NonCopyable& operator = ( NonCopyable && )     = delete;
+
+    protected:
+        NonCopyable();
+        virtual ~NonCopyable();
+    };
+
+    struct SourceLineInfo {
+
+        SourceLineInfo() = delete;
+        SourceLineInfo( char const* _file, std::size_t _line ) noexcept
+        :   file( _file ),
+            line( _line )
+        {}
+
+        SourceLineInfo( SourceLineInfo const& other )            = default;
+        SourceLineInfo& operator = ( SourceLineInfo const& )     = default;
+        SourceLineInfo( SourceLineInfo&& )              noexcept = default;
+        SourceLineInfo& operator = ( SourceLineInfo&& ) noexcept = default;
+
+        bool empty() const noexcept { return file[0] == '\0'; }
+        bool operator == ( SourceLineInfo const& other ) const noexcept;
+        bool operator < ( SourceLineInfo const& other ) const noexcept;
+
+        char const* file;
+        std::size_t line;
+    };
+
+    std::ostream& operator << ( std::ostream& os, SourceLineInfo const& info );
+
+    // Bring in operator<< from global namespace into Catch namespace
+    // This is necessary because the overload of operator<< above makes
+    // lookup stop at namespace Catch
+    using ::operator<<;
+
+    // Use this in variadic streaming macros to allow
+    //    >> +StreamEndStop
+    // as well as
+    //    >> stuff +StreamEndStop
+    struct StreamEndStop {
+        std::string operator+() const;
+    };
+    template<typename T>
+    T const& operator + ( T const& value, StreamEndStop ) {
+        return value;
+    }
+}
+
+#define CATCH_INTERNAL_LINEINFO \
+    ::Catch::SourceLineInfo( __FILE__, static_cast<std::size_t>( __LINE__ ) )
+
+// end catch_common.h
+namespace Catch {
+
+    struct RegistrarForTagAliases {
+        RegistrarForTagAliases( char const* alias, char const* tag, SourceLineInfo const& lineInfo );
+    };
+
+} // end namespace Catch
+
+#define CATCH_REGISTER_TAG_ALIAS( alias, spec ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+    CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+    namespace{ Catch::RegistrarForTagAliases INTERNAL_CATCH_UNIQUE_NAME( AutoRegisterTagAlias )( alias, spec, CATCH_INTERNAL_LINEINFO ); } \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+// end catch_tag_alias_autoregistrar.h
+// start catch_test_registry.h
+
+// start catch_interfaces_testcase.h
+
+#include <vector>
+
+namespace Catch {
+
+    class TestSpec;
+
+    struct ITestInvoker {
+        virtual void invoke () const = 0;
+        virtual ~ITestInvoker();
+    };
+
+    class TestCase;
+    struct IConfig;
+
+    struct ITestCaseRegistry {
+        virtual ~ITestCaseRegistry();
+        virtual std::vector<TestCase> const& getAllTests() const = 0;
+        virtual std::vector<TestCase> const& getAllTestsSorted( IConfig const& config ) const = 0;
+    };
+
+    bool isThrowSafe( TestCase const& testCase, IConfig const& config );
+    bool matchTest( TestCase const& testCase, TestSpec const& testSpec, IConfig const& config );
+    std::vector<TestCase> filterTests( std::vector<TestCase> const& testCases, TestSpec const& testSpec, IConfig const& config );
+    std::vector<TestCase> const& getAllTestCasesSorted( IConfig const& config );
+
+}
+
+// end catch_interfaces_testcase.h
+// start catch_stringref.h
+
+#include <cstddef>
+#include <string>
+#include <iosfwd>
+#include <cassert>
+
+namespace Catch {
+
+    /// A non-owning string class (similar to the forthcoming std::string_view)
+    /// Note that, because a StringRef may be a substring of another string,
+    /// it may not be null terminated.
+    class StringRef {
+    public:
+        using size_type = std::size_t;
+        using const_iterator = const char*;
+
+    private:
+        static constexpr char const* const s_empty = "";
+
+        char const* m_start = s_empty;
+        size_type m_size = 0;
+
+    public: // construction
+        constexpr StringRef() noexcept = default;
+
+        StringRef( char const* rawChars ) noexcept;
+
+        constexpr StringRef( char const* rawChars, size_type size ) noexcept
+        :   m_start( rawChars ),
+            m_size( size )
+        {}
+
+        StringRef( std::string const& stdString ) noexcept
+        :   m_start( stdString.c_str() ),
+            m_size( stdString.size() )
+        {}
+
+        explicit operator std::string() const {
+            return std::string(m_start, m_size);
+        }
+
+    public: // operators
+        auto operator == ( StringRef const& other ) const noexcept -> bool;
+        auto operator != (StringRef const& other) const noexcept -> bool {
+            return !(*this == other);
+        }
+
+        auto operator[] ( size_type index ) const noexcept -> char {
+            assert(index < m_size);
+            return m_start[index];
+        }
+
+    public: // named queries
+        constexpr auto empty() const noexcept -> bool {
+            return m_size == 0;
+        }
+        constexpr auto size() const noexcept -> size_type {
+            return m_size;
+        }
+
+        // Returns the current start pointer. If the StringRef is not
+        // null-terminated, throws std::domain_exception
+        auto c_str() const -> char const*;
+
+    public: // substrings and searches
+        // Returns a substring of [start, start + length).
+        // If start + length > size(), then the substring is [start, size()).
+        // If start > size(), then the substring is empty.
+        auto substr( size_type start, size_type length ) const noexcept -> StringRef;
+
+        // Returns the current start pointer. May not be null-terminated.
+        auto data() const noexcept -> char const*;
+
+        constexpr auto isNullTerminated() const noexcept -> bool {
+            return m_start[m_size] == '\0';
+        }
+
+    public: // iterators
+        constexpr const_iterator begin() const { return m_start; }
+        constexpr const_iterator end() const { return m_start + m_size; }
+    };
+
+    auto operator += ( std::string& lhs, StringRef const& sr ) -> std::string&;
+    auto operator << ( std::ostream& os, StringRef const& sr ) -> std::ostream&;
+
+    constexpr auto operator "" _sr( char const* rawChars, std::size_t size ) noexcept -> StringRef {
+        return StringRef( rawChars, size );
+    }
+} // namespace Catch
+
+constexpr auto operator "" _catch_sr( char const* rawChars, std::size_t size ) noexcept -> Catch::StringRef {
+    return Catch::StringRef( rawChars, size );
+}
+
+// end catch_stringref.h
+// start catch_preprocessor.hpp
+
+
+#define CATCH_RECURSION_LEVEL0(...) __VA_ARGS__
+#define CATCH_RECURSION_LEVEL1(...) CATCH_RECURSION_LEVEL0(CATCH_RECURSION_LEVEL0(CATCH_RECURSION_LEVEL0(__VA_ARGS__)))
+#define CATCH_RECURSION_LEVEL2(...) CATCH_RECURSION_LEVEL1(CATCH_RECURSION_LEVEL1(CATCH_RECURSION_LEVEL1(__VA_ARGS__)))
+#define CATCH_RECURSION_LEVEL3(...) CATCH_RECURSION_LEVEL2(CATCH_RECURSION_LEVEL2(CATCH_RECURSION_LEVEL2(__VA_ARGS__)))
+#define CATCH_RECURSION_LEVEL4(...) CATCH_RECURSION_LEVEL3(CATCH_RECURSION_LEVEL3(CATCH_RECURSION_LEVEL3(__VA_ARGS__)))
+#define CATCH_RECURSION_LEVEL5(...) CATCH_RECURSION_LEVEL4(CATCH_RECURSION_LEVEL4(CATCH_RECURSION_LEVEL4(__VA_ARGS__)))
+
+#ifdef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define INTERNAL_CATCH_EXPAND_VARGS(...) __VA_ARGS__
+// MSVC needs more evaluations
+#define CATCH_RECURSION_LEVEL6(...) CATCH_RECURSION_LEVEL5(CATCH_RECURSION_LEVEL5(CATCH_RECURSION_LEVEL5(__VA_ARGS__)))
+#define CATCH_RECURSE(...)  CATCH_RECURSION_LEVEL6(CATCH_RECURSION_LEVEL6(__VA_ARGS__))
+#else
+#define CATCH_RECURSE(...)  CATCH_RECURSION_LEVEL5(__VA_ARGS__)
+#endif
+
+#define CATCH_REC_END(...)
+#define CATCH_REC_OUT
+
+#define CATCH_EMPTY()
+#define CATCH_DEFER(id) id CATCH_EMPTY()
+
+#define CATCH_REC_GET_END2() 0, CATCH_REC_END
+#define CATCH_REC_GET_END1(...) CATCH_REC_GET_END2
+#define CATCH_REC_GET_END(...) CATCH_REC_GET_END1
+#define CATCH_REC_NEXT0(test, next, ...) next CATCH_REC_OUT
+#define CATCH_REC_NEXT1(test, next) CATCH_DEFER ( CATCH_REC_NEXT0 ) ( test, next, 0)
+#define CATCH_REC_NEXT(test, next)  CATCH_REC_NEXT1(CATCH_REC_GET_END test, next)
+
+#define CATCH_REC_LIST0(f, x, peek, ...) , f(x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST1) ) ( f, peek, __VA_ARGS__ )
+#define CATCH_REC_LIST1(f, x, peek, ...) , f(x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST0) ) ( f, peek, __VA_ARGS__ )
+#define CATCH_REC_LIST2(f, x, peek, ...)   f(x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST1) ) ( f, peek, __VA_ARGS__ )
+
+#define CATCH_REC_LIST0_UD(f, userdata, x, peek, ...) , f(userdata, x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST1_UD) ) ( f, userdata, peek, __VA_ARGS__ )
+#define CATCH_REC_LIST1_UD(f, userdata, x, peek, ...) , f(userdata, x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST0_UD) ) ( f, userdata, peek, __VA_ARGS__ )
+#define CATCH_REC_LIST2_UD(f, userdata, x, peek, ...)   f(userdata, x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST1_UD) ) ( f, userdata, peek, __VA_ARGS__ )
+
+// Applies the function macro `f` to each of the remaining parameters, inserts commas between the results,
+// and passes userdata as the first parameter to each invocation,
+// e.g. CATCH_REC_LIST_UD(f, x, a, b, c) evaluates to f(x, a), f(x, b), f(x, c)
+#define CATCH_REC_LIST_UD(f, userdata, ...) CATCH_RECURSE(CATCH_REC_LIST2_UD(f, userdata, __VA_ARGS__, ()()(), ()()(), ()()(), 0))
+
+#define CATCH_REC_LIST(f, ...) CATCH_RECURSE(CATCH_REC_LIST2(f, __VA_ARGS__, ()()(), ()()(), ()()(), 0))
+
+#define INTERNAL_CATCH_EXPAND1(param) INTERNAL_CATCH_EXPAND2(param)
+#define INTERNAL_CATCH_EXPAND2(...) INTERNAL_CATCH_NO## __VA_ARGS__
+#define INTERNAL_CATCH_DEF(...) INTERNAL_CATCH_DEF __VA_ARGS__
+#define INTERNAL_CATCH_NOINTERNAL_CATCH_DEF
+#define INTERNAL_CATCH_STRINGIZE(...) INTERNAL_CATCH_STRINGIZE2(__VA_ARGS__)
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define INTERNAL_CATCH_STRINGIZE2(...) #__VA_ARGS__
+#define INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS(param) INTERNAL_CATCH_STRINGIZE(INTERNAL_CATCH_REMOVE_PARENS(param))
+#else
+// MSVC is adding extra space and needs another indirection to expand INTERNAL_CATCH_NOINTERNAL_CATCH_DEF
+#define INTERNAL_CATCH_STRINGIZE2(...) INTERNAL_CATCH_STRINGIZE3(__VA_ARGS__)
+#define INTERNAL_CATCH_STRINGIZE3(...) #__VA_ARGS__
+#define INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS(param) (INTERNAL_CATCH_STRINGIZE(INTERNAL_CATCH_REMOVE_PARENS(param)) + 1)
+#endif
+
+#define INTERNAL_CATCH_MAKE_NAMESPACE2(...) ns_##__VA_ARGS__
+#define INTERNAL_CATCH_MAKE_NAMESPACE(name) INTERNAL_CATCH_MAKE_NAMESPACE2(name)
+
+#define INTERNAL_CATCH_REMOVE_PARENS(...) INTERNAL_CATCH_EXPAND1(INTERNAL_CATCH_DEF __VA_ARGS__)
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define INTERNAL_CATCH_MAKE_TYPE_LIST2(...) decltype(get_wrapper<INTERNAL_CATCH_REMOVE_PARENS_GEN(__VA_ARGS__)>())
+#define INTERNAL_CATCH_MAKE_TYPE_LIST(...) INTERNAL_CATCH_MAKE_TYPE_LIST2(INTERNAL_CATCH_REMOVE_PARENS(__VA_ARGS__))
+#else
+#define INTERNAL_CATCH_MAKE_TYPE_LIST2(...) INTERNAL_CATCH_EXPAND_VARGS(decltype(get_wrapper<INTERNAL_CATCH_REMOVE_PARENS_GEN(__VA_ARGS__)>()))
+#define INTERNAL_CATCH_MAKE_TYPE_LIST(...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_MAKE_TYPE_LIST2(INTERNAL_CATCH_REMOVE_PARENS(__VA_ARGS__)))
+#endif
+
+#define INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(...)\
+    CATCH_REC_LIST(INTERNAL_CATCH_MAKE_TYPE_LIST,__VA_ARGS__)
+
+#define INTERNAL_CATCH_REMOVE_PARENS_1_ARG(_0) INTERNAL_CATCH_REMOVE_PARENS(_0)
+#define INTERNAL_CATCH_REMOVE_PARENS_2_ARG(_0, _1) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_1_ARG(_1)
+#define INTERNAL_CATCH_REMOVE_PARENS_3_ARG(_0, _1, _2) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_2_ARG(_1, _2)
+#define INTERNAL_CATCH_REMOVE_PARENS_4_ARG(_0, _1, _2, _3) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_3_ARG(_1, _2, _3)
+#define INTERNAL_CATCH_REMOVE_PARENS_5_ARG(_0, _1, _2, _3, _4) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_4_ARG(_1, _2, _3, _4)
+#define INTERNAL_CATCH_REMOVE_PARENS_6_ARG(_0, _1, _2, _3, _4, _5) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_5_ARG(_1, _2, _3, _4, _5)
+#define INTERNAL_CATCH_REMOVE_PARENS_7_ARG(_0, _1, _2, _3, _4, _5, _6) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_6_ARG(_1, _2, _4, _5, _6)
+#define INTERNAL_CATCH_REMOVE_PARENS_8_ARG(_0, _1, _2, _3, _4, _5, _6, _7) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_7_ARG(_1, _2, _3, _4, _5, _6, _7)
+#define INTERNAL_CATCH_REMOVE_PARENS_9_ARG(_0, _1, _2, _3, _4, _5, _6, _7, _8) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_8_ARG(_1, _2, _3, _4, _5, _6, _7, _8)
+#define INTERNAL_CATCH_REMOVE_PARENS_10_ARG(_0, _1, _2, _3, _4, _5, _6, _7, _8, _9) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_9_ARG(_1, _2, _3, _4, _5, _6, _7, _8, _9)
+#define INTERNAL_CATCH_REMOVE_PARENS_11_ARG(_0, _1, _2, _3, _4, _5, _6, _7, _8, _9, _10) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_10_ARG(_1, _2, _3, _4, _5, _6, _7, _8, _9, _10)
+
+#define INTERNAL_CATCH_VA_NARGS_IMPL(_0, _1, _2, _3, _4, _5, _6, _7, _8, _9, _10, N, ...) N
+
+#define INTERNAL_CATCH_TYPE_GEN\
+    template<typename...> struct TypeList {};\
+    template<typename...Ts>\
+    constexpr auto get_wrapper() noexcept -> TypeList<Ts...> { return {}; }\
+    template<template<typename...> class...> struct TemplateTypeList{};\
+    template<template<typename...> class...Cs>\
+    constexpr auto get_wrapper() noexcept -> TemplateTypeList<Cs...> { return {}; }\
+    template<typename...>\
+    struct append;\
+    template<typename...>\
+    struct rewrap;\
+    template<template<typename...> class, typename...>\
+    struct create;\
+    template<template<typename...> class, typename>\
+    struct convert;\
+    \
+    template<typename T> \
+    struct append<T> { using type = T; };\
+    template< template<typename...> class L1, typename...E1, template<typename...> class L2, typename...E2, typename...Rest>\
+    struct append<L1<E1...>, L2<E2...>, Rest...> { using type = typename append<L1<E1...,E2...>, Rest...>::type; };\
+    template< template<typename...> class L1, typename...E1, typename...Rest>\
+    struct append<L1<E1...>, TypeList<mpl_::na>, Rest...> { using type = L1<E1...>; };\
+    \
+    template< template<typename...> class Container, template<typename...> class List, typename...elems>\
+    struct rewrap<TemplateTypeList<Container>, List<elems...>> { using type = TypeList<Container<elems...>>; };\
+    template< template<typename...> class Container, template<typename...> class List, class...Elems, typename...Elements>\
+    struct rewrap<TemplateTypeList<Container>, List<Elems...>, Elements...> { using type = typename append<TypeList<Container<Elems...>>, typename rewrap<TemplateTypeList<Container>, Elements...>::type>::type; };\
+    \
+    template<template <typename...> class Final, template< typename...> class...Containers, typename...Types>\
+    struct create<Final, TemplateTypeList<Containers...>, TypeList<Types...>> { using type = typename append<Final<>, typename rewrap<TemplateTypeList<Containers>, Types...>::type...>::type; };\
+    template<template <typename...> class Final, template <typename...> class List, typename...Ts>\
+    struct convert<Final, List<Ts...>> { using type = typename append<Final<>,TypeList<Ts>...>::type; };
+
+#define INTERNAL_CATCH_NTTP_1(signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)> struct Nttp{};\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    constexpr auto get_wrapper() noexcept -> Nttp<__VA_ARGS__> { return {}; } \
+    template<template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class...> struct NttpTemplateTypeList{};\
+    template<template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class...Cs>\
+    constexpr auto get_wrapper() noexcept -> NttpTemplateTypeList<Cs...> { return {}; } \
+    \
+    template< template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class Container, template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class List, INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    struct rewrap<NttpTemplateTypeList<Container>, List<__VA_ARGS__>> { using type = TypeList<Container<__VA_ARGS__>>; };\
+    template< template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class Container, template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class List, INTERNAL_CATCH_REMOVE_PARENS(signature), typename...Elements>\
+    struct rewrap<NttpTemplateTypeList<Container>, List<__VA_ARGS__>, Elements...> { using type = typename append<TypeList<Container<__VA_ARGS__>>, typename rewrap<NttpTemplateTypeList<Container>, Elements...>::type>::type; };\
+    template<template <typename...> class Final, template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class...Containers, typename...Types>\
+    struct create<Final, NttpTemplateTypeList<Containers...>, TypeList<Types...>> { using type = typename append<Final<>, typename rewrap<NttpTemplateTypeList<Containers>, Types...>::type...>::type; };
+
+#define INTERNAL_CATCH_DECLARE_SIG_TEST0(TestName)
+#define INTERNAL_CATCH_DECLARE_SIG_TEST1(TestName, signature)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    static void TestName()
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_X(TestName, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    static void TestName()
+
+#define INTERNAL_CATCH_DEFINE_SIG_TEST0(TestName)
+#define INTERNAL_CATCH_DEFINE_SIG_TEST1(TestName, signature)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    static void TestName()
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_X(TestName, signature,...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    static void TestName()
+
+#define INTERNAL_CATCH_NTTP_REGISTER0(TestFunc, signature)\
+    template<typename Type>\
+    void reg_test(TypeList<Type>, Catch::NameAndTags nameAndTags)\
+    {\
+        Catch::AutoReg( Catch::makeTestInvoker(&TestFunc<Type>), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), nameAndTags);\
+    }
+
+#define INTERNAL_CATCH_NTTP_REGISTER(TestFunc, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    void reg_test(Nttp<__VA_ARGS__>, Catch::NameAndTags nameAndTags)\
+    {\
+        Catch::AutoReg( Catch::makeTestInvoker(&TestFunc<__VA_ARGS__>), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), nameAndTags);\
+    }
+
+#define INTERNAL_CATCH_NTTP_REGISTER_METHOD0(TestName, signature, ...)\
+    template<typename Type>\
+    void reg_test(TypeList<Type>, Catch::StringRef className, Catch::NameAndTags nameAndTags)\
+    {\
+        Catch::AutoReg( Catch::makeTestInvoker(&TestName<Type>::test), CATCH_INTERNAL_LINEINFO, className, nameAndTags);\
+    }
+
+#define INTERNAL_CATCH_NTTP_REGISTER_METHOD(TestName, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    void reg_test(Nttp<__VA_ARGS__>, Catch::StringRef className, Catch::NameAndTags nameAndTags)\
+    {\
+        Catch::AutoReg( Catch::makeTestInvoker(&TestName<__VA_ARGS__>::test), CATCH_INTERNAL_LINEINFO, className, nameAndTags);\
+    }
+
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD0(TestName, ClassName)
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD1(TestName, ClassName, signature)\
+    template<typename TestType> \
+    struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName)<TestType> { \
+        void test();\
+    }
+
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X(TestName, ClassName, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)> \
+    struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName)<__VA_ARGS__> { \
+        void test();\
+    }
+
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD0(TestName)
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD1(TestName, signature)\
+    template<typename TestType> \
+    void INTERNAL_CATCH_MAKE_NAMESPACE(TestName)::TestName<TestType>::test()
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X(TestName, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)> \
+    void INTERNAL_CATCH_MAKE_NAMESPACE(TestName)::TestName<__VA_ARGS__>::test()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define INTERNAL_CATCH_NTTP_0
+#define INTERNAL_CATCH_NTTP_GEN(...) INTERNAL_CATCH_VA_NARGS_IMPL(__VA_ARGS__, INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1( __VA_ARGS__), INTERNAL_CATCH_NTTP_1( __VA_ARGS__), INTERNAL_CATCH_NTTP_1( __VA_ARGS__), INTERNAL_CATCH_NTTP_1( __VA_ARGS__),INTERNAL_CATCH_NTTP_1( __VA_ARGS__), INTERNAL_CATCH_NTTP_0)
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD(TestName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD1, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD0)(TestName, __VA_ARGS__)
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD(TestName, ClassName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD1, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD0)(TestName, ClassName, __VA_ARGS__)
+#define INTERNAL_CATCH_NTTP_REG_METHOD_GEN(TestName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD0, INTERNAL_CATCH_NTTP_REGISTER_METHOD0)(TestName, __VA_ARGS__)
+#define INTERNAL_CATCH_NTTP_REG_GEN(TestFunc, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER0, INTERNAL_CATCH_NTTP_REGISTER0)(TestFunc, __VA_ARGS__)
+#define INTERNAL_CATCH_DEFINE_SIG_TEST(TestName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DEFINE_SIG_TEST1, INTERNAL_CATCH_DEFINE_SIG_TEST0)(TestName, __VA_ARGS__)
+#define INTERNAL_CATCH_DECLARE_SIG_TEST(TestName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DECLARE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST1, INTERNAL_CATCH_DECLARE_SIG_TEST0)(TestName, __VA_ARGS__)
+#define INTERNAL_CATCH_REMOVE_PARENS_GEN(...) INTERNAL_CATCH_VA_NARGS_IMPL(__VA_ARGS__, INTERNAL_CATCH_REMOVE_PARENS_11_ARG,INTERNAL_CATCH_REMOVE_PARENS_10_ARG,INTERNAL_CATCH_REMOVE_PARENS_9_ARG,INTERNAL_CATCH_REMOVE_PARENS_8_ARG,INTERNAL_CATCH_REMOVE_PARENS_7_ARG,INTERNAL_CATCH_REMOVE_PARENS_6_ARG,INTERNAL_CATCH_REMOVE_PARENS_5_ARG,INTERNAL_CATCH_REMOVE_PARENS_4_ARG,INTERNAL_CATCH_REMOVE_PARENS_3_ARG,INTERNAL_CATCH_REMOVE_PARENS_2_ARG,INTERNAL_CATCH_REMOVE_PARENS_1_ARG)(__VA_ARGS__)
+#else
+#define INTERNAL_CATCH_NTTP_0(signature)
+#define INTERNAL_CATCH_NTTP_GEN(...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL(__VA_ARGS__, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1,INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_0)( __VA_ARGS__))
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD(TestName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD1, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD0)(TestName, __VA_ARGS__))
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD(TestName, ClassName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD1, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD0)(TestName, ClassName, __VA_ARGS__))
+#define INTERNAL_CATCH_NTTP_REG_METHOD_GEN(TestName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD0, INTERNAL_CATCH_NTTP_REGISTER_METHOD0)(TestName, __VA_ARGS__))
+#define INTERNAL_CATCH_NTTP_REG_GEN(TestFunc, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER0, INTERNAL_CATCH_NTTP_REGISTER0)(TestFunc, __VA_ARGS__))
+#define INTERNAL_CATCH_DEFINE_SIG_TEST(TestName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DEFINE_SIG_TEST1, INTERNAL_CATCH_DEFINE_SIG_TEST0)(TestName, __VA_ARGS__))
+#define INTERNAL_CATCH_DECLARE_SIG_TEST(TestName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DECLARE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST1, INTERNAL_CATCH_DECLARE_SIG_TEST0)(TestName, __VA_ARGS__))
+#define INTERNAL_CATCH_REMOVE_PARENS_GEN(...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL(__VA_ARGS__, INTERNAL_CATCH_REMOVE_PARENS_11_ARG,INTERNAL_CATCH_REMOVE_PARENS_10_ARG,INTERNAL_CATCH_REMOVE_PARENS_9_ARG,INTERNAL_CATCH_REMOVE_PARENS_8_ARG,INTERNAL_CATCH_REMOVE_PARENS_7_ARG,INTERNAL_CATCH_REMOVE_PARENS_6_ARG,INTERNAL_CATCH_REMOVE_PARENS_5_ARG,INTERNAL_CATCH_REMOVE_PARENS_4_ARG,INTERNAL_CATCH_REMOVE_PARENS_3_ARG,INTERNAL_CATCH_REMOVE_PARENS_2_ARG,INTERNAL_CATCH_REMOVE_PARENS_1_ARG)(__VA_ARGS__))
+#endif
+
+// end catch_preprocessor.hpp
+// start catch_meta.hpp
+
+
+#include <type_traits>
+
+namespace Catch {
+    template<typename T>
+    struct always_false : std::false_type {};
+
+    template <typename> struct true_given : std::true_type {};
+    struct is_callable_tester {
+        template <typename Fun, typename... Args>
+        true_given<decltype(std::declval<Fun>()(std::declval<Args>()...))> static test(int);
+        template <typename...>
+        std::false_type static test(...);
+    };
+
+    template <typename T>
+    struct is_callable;
+
+    template <typename Fun, typename... Args>
+    struct is_callable<Fun(Args...)> : decltype(is_callable_tester::test<Fun, Args...>(0)) {};
+
+#if defined(__cpp_lib_is_invocable) && __cpp_lib_is_invocable >= 201703
+    // std::result_of is deprecated in C++17 and removed in C++20. Hence, it is
+    // replaced with std::invoke_result here. Also *_t format is preferred over
+    // typename *::type format.
+    template <typename Func, typename U>
+    using FunctionReturnType = std::remove_reference_t<std::remove_cv_t<std::invoke_result_t<Func, U>>>;
+#else
+    template <typename Func, typename U>
+    using FunctionReturnType = typename std::remove_reference<typename std::remove_cv<typename std::result_of<Func(U)>::type>::type>::type;
+#endif
+
+} // namespace Catch
+
+namespace mpl_{
+    struct na;
+}
+
+// end catch_meta.hpp
+namespace Catch {
+
+template<typename C>
+class TestInvokerAsMethod : public ITestInvoker {
+    void (C::*m_testAsMethod)();
+public:
+    TestInvokerAsMethod( void (C::*testAsMethod)() ) noexcept : m_testAsMethod( testAsMethod ) {}
+
+    void invoke() const override {
+        C obj;
+        (obj.*m_testAsMethod)();
+    }
+};
+
+auto makeTestInvoker( void(*testAsFunction)() ) noexcept -> ITestInvoker*;
+
+template<typename C>
+auto makeTestInvoker( void (C::*testAsMethod)() ) noexcept -> ITestInvoker* {
+    return new(std::nothrow) TestInvokerAsMethod<C>( testAsMethod );
+}
+
+struct NameAndTags {
+    NameAndTags( StringRef const& name_ = StringRef(), StringRef const& tags_ = StringRef() ) noexcept;
+    StringRef name;
+    StringRef tags;
+};
+
+struct AutoReg : NonCopyable {
+    AutoReg( ITestInvoker* invoker, SourceLineInfo const& lineInfo, StringRef const& classOrMethod, NameAndTags const& nameAndTags ) noexcept;
+    ~AutoReg();
+};
+
+} // end namespace Catch
+
+#if defined(CATCH_CONFIG_DISABLE)
+    #define INTERNAL_CATCH_TESTCASE_NO_REGISTRATION( TestName, ... ) \
+        static void TestName()
+    #define INTERNAL_CATCH_TESTCASE_METHOD_NO_REGISTRATION( TestName, ClassName, ... ) \
+        namespace{                        \
+            struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName) { \
+                void test();              \
+            };                            \
+        }                                 \
+        void TestName::test()
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( TestName, TestFunc, Name, Tags, Signature, ... )  \
+        INTERNAL_CATCH_DEFINE_SIG_TEST(TestFunc, INTERNAL_CATCH_REMOVE_PARENS(Signature))
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( TestNameClass, TestName, ClassName, Name, Tags, Signature, ... )    \
+        namespace{                                                                                  \
+            namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName) {                                      \
+            INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD(TestName, ClassName, INTERNAL_CATCH_REMOVE_PARENS(Signature));\
+        }                                                                                           \
+        }                                                                                           \
+        INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD(TestName, INTERNAL_CATCH_REMOVE_PARENS(Signature))
+
+    #ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(Name, Tags, ...) \
+            INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, typename TestType, __VA_ARGS__ )
+    #else
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(Name, Tags, ...) \
+            INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, typename TestType, __VA_ARGS__ ) )
+    #endif
+
+    #ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(Name, Tags, Signature, ...) \
+            INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, Signature, __VA_ARGS__ )
+    #else
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(Name, Tags, Signature, ...) \
+            INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, Signature, __VA_ARGS__ ) )
+    #endif
+
+    #ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION( ClassName, Name, Tags,... ) \
+            INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____C_L_A_S_S____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ) , ClassName, Name, Tags, typename T, __VA_ARGS__ )
+    #else
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION( ClassName, Name, Tags,... ) \
+            INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____C_L_A_S_S____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ) , ClassName, Name, Tags, typename T, __VA_ARGS__ ) )
+    #endif
+
+    #ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION( ClassName, Name, Tags, Signature, ... ) \
+            INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____C_L_A_S_S____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ) , ClassName, Name, Tags, Signature, __VA_ARGS__ )
+    #else
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION( ClassName, Name, Tags, Signature, ... ) \
+            INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____C_L_A_S_S____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ) , ClassName, Name, Tags, Signature, __VA_ARGS__ ) )
+    #endif
+#endif
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_TESTCASE2( TestName, ... ) \
+        static void TestName(); \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        namespace{ Catch::AutoReg INTERNAL_CATCH_UNIQUE_NAME( autoRegistrar )( Catch::makeTestInvoker( &TestName ), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), Catch::NameAndTags{ __VA_ARGS__ } ); } /* NOLINT */ \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        static void TestName()
+    #define INTERNAL_CATCH_TESTCASE( ... ) \
+        INTERNAL_CATCH_TESTCASE2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ), __VA_ARGS__ )
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_METHOD_AS_TEST_CASE( QualifiedMethod, ... ) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        namespace{ Catch::AutoReg INTERNAL_CATCH_UNIQUE_NAME( autoRegistrar )( Catch::makeTestInvoker( &QualifiedMethod ), CATCH_INTERNAL_LINEINFO, "&" #QualifiedMethod, Catch::NameAndTags{ __VA_ARGS__ } ); } /* NOLINT */ \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_TEST_CASE_METHOD2( TestName, ClassName, ... )\
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        namespace{ \
+            struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName) { \
+                void test(); \
+            }; \
+            Catch::AutoReg INTERNAL_CATCH_UNIQUE_NAME( autoRegistrar ) ( Catch::makeTestInvoker( &TestName::test ), CATCH_INTERNAL_LINEINFO, #ClassName, Catch::NameAndTags{ __VA_ARGS__ } ); /* NOLINT */ \
+        } \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        void TestName::test()
+    #define INTERNAL_CATCH_TEST_CASE_METHOD( ClassName, ... ) \
+        INTERNAL_CATCH_TEST_CASE_METHOD2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ), ClassName, __VA_ARGS__ )
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_REGISTER_TESTCASE( Function, ... ) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        Catch::AutoReg INTERNAL_CATCH_UNIQUE_NAME( autoRegistrar )( Catch::makeTestInvoker( Function ), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), Catch::NameAndTags{ __VA_ARGS__ } ); /* NOLINT */ \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_2(TestName, TestFunc, Name, Tags, Signature, ... )\
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        INTERNAL_CATCH_DECLARE_SIG_TEST(TestFunc, INTERNAL_CATCH_REMOVE_PARENS(Signature));\
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName){\
+            INTERNAL_CATCH_TYPE_GEN\
+            INTERNAL_CATCH_NTTP_GEN(INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            INTERNAL_CATCH_NTTP_REG_GEN(TestFunc,INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            template<typename...Types> \
+            struct TestName{\
+                TestName(){\
+                    int index = 0;                                    \
+                    constexpr char const* tmpl_types[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, __VA_ARGS__)};\
+                    using expander = int[];\
+                    (void)expander{(reg_test(Types{}, Catch::NameAndTags{ Name " - " + std::string(tmpl_types[index]), Tags } ), index++, 0)... };/* NOLINT */ \
+                }\
+            };\
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){\
+            TestName<INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(__VA_ARGS__)>();\
+            return 0;\
+        }();\
+        }\
+        }\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        INTERNAL_CATCH_DEFINE_SIG_TEST(TestFunc,INTERNAL_CATCH_REMOVE_PARENS(Signature))
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE(Name, Tags, ...) \
+        INTERNAL_CATCH_TEMPLATE_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, typename TestType, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE(Name, Tags, ...) \
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, typename TestType, __VA_ARGS__ ) )
+#endif
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG(Name, Tags, Signature, ...) \
+        INTERNAL_CATCH_TEMPLATE_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, Signature, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG(Name, Tags, Signature, ...) \
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, Signature, __VA_ARGS__ ) )
+#endif
+
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2(TestName, TestFuncName, Name, Tags, Signature, TmplTypes, TypesList) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION                      \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS                      \
+        CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS                \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS              \
+        template<typename TestType> static void TestFuncName();       \
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName) {                                     \
+            INTERNAL_CATCH_TYPE_GEN                                                  \
+            INTERNAL_CATCH_NTTP_GEN(INTERNAL_CATCH_REMOVE_PARENS(Signature))         \
+            template<typename... Types>                               \
+            struct TestName {                                         \
+                void reg_tests() {                                          \
+                    int index = 0;                                    \
+                    using expander = int[];                           \
+                    constexpr char const* tmpl_types[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, INTERNAL_CATCH_REMOVE_PARENS(TmplTypes))};\
+                    constexpr char const* types_list[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, INTERNAL_CATCH_REMOVE_PARENS(TypesList))};\
+                    constexpr auto num_types = sizeof(types_list) / sizeof(types_list[0]);\
+                    (void)expander{(Catch::AutoReg( Catch::makeTestInvoker( &TestFuncName<Types> ), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), Catch::NameAndTags{ Name " - " + std::string(tmpl_types[index / num_types]) + "<" + std::string(types_list[index % num_types]) + ">", Tags } ), index++, 0)... };/* NOLINT */\
+                }                                                     \
+            };                                                        \
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){ \
+                using TestInit = typename create<TestName, decltype(get_wrapper<INTERNAL_CATCH_REMOVE_PARENS(TmplTypes)>()), TypeList<INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(INTERNAL_CATCH_REMOVE_PARENS(TypesList))>>::type; \
+                TestInit t;                                           \
+                t.reg_tests();                                        \
+                return 0;                                             \
+            }();                                                      \
+        }                                                             \
+        }                                                             \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION                       \
+        template<typename TestType>                                   \
+        static void TestFuncName()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE(Name, Tags, ...)\
+        INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, typename T,__VA_ARGS__)
+#else
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE(Name, Tags, ...)\
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, typename T, __VA_ARGS__ ) )
+#endif
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG(Name, Tags, Signature, ...)\
+        INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, Signature, __VA_ARGS__)
+#else
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG(Name, Tags, Signature, ...)\
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, Signature, __VA_ARGS__ ) )
+#endif
+
+    #define INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_2(TestName, TestFunc, Name, Tags, TmplList)\
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        template<typename TestType> static void TestFunc();       \
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName){\
+        INTERNAL_CATCH_TYPE_GEN\
+        template<typename... Types>                               \
+        struct TestName {                                         \
+            void reg_tests() {                                          \
+                int index = 0;                                    \
+                using expander = int[];                           \
+                (void)expander{(Catch::AutoReg( Catch::makeTestInvoker( &TestFunc<Types> ), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), Catch::NameAndTags{ Name " - " + std::string(INTERNAL_CATCH_STRINGIZE(TmplList)) + " - " + std::to_string(index), Tags } ), index++, 0)... };/* NOLINT */\
+            }                                                     \
+        };\
+        static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){ \
+                using TestInit = typename convert<TestName, TmplList>::type; \
+                TestInit t;                                           \
+                t.reg_tests();                                        \
+                return 0;                                             \
+            }();                                                      \
+        }}\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION                       \
+        template<typename TestType>                                   \
+        static void TestFunc()
+
+    #define INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE(Name, Tags, TmplList) \
+        INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), Name, Tags, TmplList )
+
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( TestNameClass, TestName, ClassName, Name, Tags, Signature, ... ) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName){ \
+            INTERNAL_CATCH_TYPE_GEN\
+            INTERNAL_CATCH_NTTP_GEN(INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD(TestName, ClassName, INTERNAL_CATCH_REMOVE_PARENS(Signature));\
+            INTERNAL_CATCH_NTTP_REG_METHOD_GEN(TestName, INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            template<typename...Types> \
+            struct TestNameClass{\
+                TestNameClass(){\
+                    int index = 0;                                    \
+                    constexpr char const* tmpl_types[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, __VA_ARGS__)};\
+                    using expander = int[];\
+                    (void)expander{(reg_test(Types{}, #ClassName, Catch::NameAndTags{ Name " - " + std::string(tmpl_types[index]), Tags } ), index++, 0)... };/* NOLINT */ \
+                }\
+            };\
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){\
+                TestNameClass<INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(__VA_ARGS__)>();\
+                return 0;\
+        }();\
+        }\
+        }\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD(TestName, INTERNAL_CATCH_REMOVE_PARENS(Signature))
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( ClassName, Name, Tags,... ) \
+        INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____C_L_A_S_S____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ) , ClassName, Name, Tags, typename T, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( ClassName, Name, Tags,... ) \
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____C_L_A_S_S____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ) , ClassName, Name, Tags, typename T, __VA_ARGS__ ) )
+#endif
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( ClassName, Name, Tags, Signature, ... ) \
+        INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____C_L_A_S_S____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ) , ClassName, Name, Tags, Signature, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( ClassName, Name, Tags, Signature, ... ) \
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____C_L_A_S_S____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ) , ClassName, Name, Tags, Signature, __VA_ARGS__ ) )
+#endif
+
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2(TestNameClass, TestName, ClassName, Name, Tags, Signature, TmplTypes, TypesList)\
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        template<typename TestType> \
+            struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName <TestType>) { \
+                void test();\
+            };\
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestNameClass) {\
+            INTERNAL_CATCH_TYPE_GEN                  \
+            INTERNAL_CATCH_NTTP_GEN(INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            template<typename...Types>\
+            struct TestNameClass{\
+                void reg_tests(){\
+                    int index = 0;\
+                    using expander = int[];\
+                    constexpr char const* tmpl_types[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, INTERNAL_CATCH_REMOVE_PARENS(TmplTypes))};\
+                    constexpr char const* types_list[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, INTERNAL_CATCH_REMOVE_PARENS(TypesList))};\
+                    constexpr auto num_types = sizeof(types_list) / sizeof(types_list[0]);\
+                    (void)expander{(Catch::AutoReg( Catch::makeTestInvoker( &TestName<Types>::test ), CATCH_INTERNAL_LINEINFO, #ClassName, Catch::NameAndTags{ Name " - " + std::string(tmpl_types[index / num_types]) + "<" + std::string(types_list[index % num_types]) + ">", Tags } ), index++, 0)... };/* NOLINT */ \
+                }\
+            };\
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){\
+                using TestInit = typename create<TestNameClass, decltype(get_wrapper<INTERNAL_CATCH_REMOVE_PARENS(TmplTypes)>()), TypeList<INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(INTERNAL_CATCH_REMOVE_PARENS(TypesList))>>::type;\
+                TestInit t;\
+                t.reg_tests();\
+                return 0;\
+            }(); \
+        }\
+        }\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        template<typename TestType> \
+        void TestName<TestType>::test()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( ClassName, Name, Tags, ... )\
+        INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), ClassName, Name, Tags, typename T, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( ClassName, Name, Tags, ... )\
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), ClassName, Name, Tags, typename T,__VA_ARGS__ ) )
+#endif
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( ClassName, Name, Tags, Signature, ... )\
+        INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), ClassName, Name, Tags, Signature, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( ClassName, Name, Tags, Signature, ... )\
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), ClassName, Name, Tags, Signature,__VA_ARGS__ ) )
+#endif
+
+    #define INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD_2( TestNameClass, TestName, ClassName, Name, Tags, TmplList) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        template<typename TestType> \
+        struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName <TestType>) { \
+            void test();\
+        };\
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName){ \
+            INTERNAL_CATCH_TYPE_GEN\
+            template<typename...Types>\
+            struct TestNameClass{\
+                void reg_tests(){\
+                    int index = 0;\
+                    using expander = int[];\
+                    (void)expander{(Catch::AutoReg( Catch::makeTestInvoker( &TestName<Types>::test ), CATCH_INTERNAL_LINEINFO, #ClassName, Catch::NameAndTags{ Name " - " + std::string(INTERNAL_CATCH_STRINGIZE(TmplList)) + " - " + std::to_string(index), Tags } ), index++, 0)... };/* NOLINT */ \
+                }\
+            };\
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){\
+                using TestInit = typename convert<TestNameClass, TmplList>::type;\
+                TestInit t;\
+                t.reg_tests();\
+                return 0;\
+            }(); \
+        }}\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        template<typename TestType> \
+        void TestName<TestType>::test()
+
+#define INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD(ClassName, Name, Tags, TmplList) \
+        INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____ ), INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_M_P_L_A_T_E____T_E_S_T____F_U_N_C____ ), ClassName, Name, Tags, TmplList )
+
+// end catch_test_registry.h
+// start catch_capture.hpp
+
+// start catch_assertionhandler.h
+
+// start catch_assertioninfo.h
+
+// start catch_result_type.h
+
+namespace Catch {
+
+    // ResultWas::OfType enum
+    struct ResultWas { enum OfType {
+        Unknown = -1,
+        Ok = 0,
+        Info = 1,
+        Warning = 2,
+
+        FailureBit = 0x10,
+
+        ExpressionFailed = FailureBit | 1,
+        ExplicitFailure = FailureBit | 2,
+
+        Exception = 0x100 | FailureBit,
+
+        ThrewException = Exception | 1,
+        DidntThrowException = Exception | 2,
+
+        FatalErrorCondition = 0x200 | FailureBit
+
+    }; };
+
+    bool isOk( ResultWas::OfType resultType );
+    bool isJustInfo( int flags );
+
+    // ResultDisposition::Flags enum
+    struct ResultDisposition { enum Flags {
+        Normal = 0x01,
+
+        ContinueOnFailure = 0x02,   // Failures fail test, but execution continues
+        FalseTest = 0x04,           // Prefix expression with !
+        SuppressFail = 0x08         // Failures are reported but do not fail the test
+    }; };
+
+    ResultDisposition::Flags operator | ( ResultDisposition::Flags lhs, ResultDisposition::Flags rhs );
+
+    bool shouldContinueOnFailure( int flags );
+    inline bool isFalseTest( int flags ) { return ( flags & ResultDisposition::FalseTest ) != 0; }
+    bool shouldSuppressFailure( int flags );
+
+} // end namespace Catch
+
+// end catch_result_type.h
+namespace Catch {
+
+    struct AssertionInfo
+    {
+        StringRef macroName;
+        SourceLineInfo lineInfo;
+        StringRef capturedExpression;
+        ResultDisposition::Flags resultDisposition;
+
+        // We want to delete this constructor but a compiler bug in 4.8 means
+        // the struct is then treated as non-aggregate
+        //AssertionInfo() = delete;
+    };
+
+} // end namespace Catch
+
+// end catch_assertioninfo.h
+// start catch_decomposer.h
+
+// start catch_tostring.h
+
+#include <vector>
+#include <cstddef>
+#include <type_traits>
+#include <string>
+// start catch_stream.h
+
+#include <iosfwd>
+#include <cstddef>
+#include <ostream>
+
+namespace Catch {
+
+    std::ostream& cout();
+    std::ostream& cerr();
+    std::ostream& clog();
+
+    class StringRef;
+
+    struct IStream {
+        virtual ~IStream();
+        virtual std::ostream& stream() const = 0;
+    };
+
+    auto makeStream( StringRef const &filename ) -> IStream const*;
+
+    class ReusableStringStream : NonCopyable {
+        std::size_t m_index;
+        std::ostream* m_oss;
+    public:
+        ReusableStringStream();
+        ~ReusableStringStream();
+
+        auto str() const -> std::string;
+
+        template<typename T>
+        auto operator << ( T const& value ) -> ReusableStringStream& {
+            *m_oss << value;
+            return *this;
+        }
+        auto get() -> std::ostream& { return *m_oss; }
+    };
+}
+
+// end catch_stream.h
+// start catch_interfaces_enum_values_registry.h
+
+#include <vector>
+
+namespace Catch {
+
+    namespace Detail {
+        struct EnumInfo {
+            StringRef m_name;
+            std::vector<std::pair<int, StringRef>> m_values;
+
+            ~EnumInfo();
+
+            StringRef lookup( int value ) const;
+        };
+    } // namespace Detail
+
+    struct IMutableEnumValuesRegistry {
+        virtual ~IMutableEnumValuesRegistry();
+
+        virtual Detail::EnumInfo const& registerEnum( StringRef enumName, StringRef allEnums, std::vector<int> const& values ) = 0;
+
+        template<typename E>
+        Detail::EnumInfo const& registerEnum( StringRef enumName, StringRef allEnums, std::initializer_list<E> values ) {
+            static_assert(sizeof(int) >= sizeof(E), "Cannot serialize enum to int");
+            std::vector<int> intValues;
+            intValues.reserve( values.size() );
+            for( auto enumValue : values )
+                intValues.push_back( static_cast<int>( enumValue ) );
+            return registerEnum( enumName, allEnums, intValues );
+        }
+    };
+
+} // Catch
+
+// end catch_interfaces_enum_values_registry.h
+
+#ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+#include <string_view>
+#endif
+
+#ifdef __OBJC__
+// start catch_objc_arc.hpp
+
+#import <Foundation/Foundation.h>
+
+#ifdef __has_feature
+#define CATCH_ARC_ENABLED __has_feature(objc_arc)
+#else
+#define CATCH_ARC_ENABLED 0
+#endif
+
+void arcSafeRelease( NSObject* obj );
+id performOptionalSelector( id obj, SEL sel );
+
+#if !CATCH_ARC_ENABLED
+inline void arcSafeRelease( NSObject* obj ) {
+    [obj release];
+}
+inline id performOptionalSelector( id obj, SEL sel ) {
+    if( [obj respondsToSelector: sel] )
+        return [obj performSelector: sel];
+    return nil;
+}
+#define CATCH_UNSAFE_UNRETAINED
+#define CATCH_ARC_STRONG
+#else
+inline void arcSafeRelease( NSObject* ){}
+inline id performOptionalSelector( id obj, SEL sel ) {
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Warc-performSelector-leaks"
+#endif
+    if( [obj respondsToSelector: sel] )
+        return [obj performSelector: sel];
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+    return nil;
+}
+#define CATCH_UNSAFE_UNRETAINED __unsafe_unretained
+#define CATCH_ARC_STRONG __strong
+#endif
+
+// end catch_objc_arc.hpp
+#endif
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable:4180) // We attempt to stream a function (address) by const&, which MSVC complains about but is harmless
+#endif
+
+namespace Catch {
+    namespace Detail {
+
+        extern const std::string unprintableString;
+
+        std::string rawMemoryToString( const void *object, std::size_t size );
+
+        template<typename T>
+        std::string rawMemoryToString( const T& object ) {
+          return rawMemoryToString( &object, sizeof(object) );
+        }
+
+        template<typename T>
+        class IsStreamInsertable {
+            template<typename Stream, typename U>
+            static auto test(int)
+                -> decltype(std::declval<Stream&>() << std::declval<U>(), std::true_type());
+
+            template<typename, typename>
+            static auto test(...)->std::false_type;
+
+        public:
+            static const bool value = decltype(test<std::ostream, const T&>(0))::value;
+        };
+
+        template<typename E>
+        std::string convertUnknownEnumToString( E e );
+
+        template<typename T>
+        typename std::enable_if<
+            !std::is_enum<T>::value && !std::is_base_of<std::exception, T>::value,
+        std::string>::type convertUnstreamable( T const& ) {
+            return Detail::unprintableString;
+        }
+        template<typename T>
+        typename std::enable_if<
+            !std::is_enum<T>::value && std::is_base_of<std::exception, T>::value,
+         std::string>::type convertUnstreamable(T const& ex) {
+            return ex.what();
+        }
+
+        template<typename T>
+        typename std::enable_if<
+            std::is_enum<T>::value
+        , std::string>::type convertUnstreamable( T const& value ) {
+            return convertUnknownEnumToString( value );
+        }
+
+#if defined(_MANAGED)
+        //! Convert a CLR string to a utf8 std::string
+        template<typename T>
+        std::string clrReferenceToString( T^ ref ) {
+            if (ref == nullptr)
+                return std::string("null");
+            auto bytes = System::Text::Encoding::UTF8->GetBytes(ref->ToString());
+            cli::pin_ptr<System::Byte> p = &bytes[0];
+            return std::string(reinterpret_cast<char const *>(p), bytes->Length);
+        }
+#endif
+
+    } // namespace Detail
+
+    // If we decide for C++14, change these to enable_if_ts
+    template <typename T, typename = void>
+    struct StringMaker {
+        template <typename Fake = T>
+        static
+        typename std::enable_if<::Catch::Detail::IsStreamInsertable<Fake>::value, std::string>::type
+            convert(const Fake& value) {
+                ReusableStringStream rss;
+                // NB: call using the function-like syntax to avoid ambiguity with
+                // user-defined templated operator<< under clang.
+                rss.operator<<(value);
+                return rss.str();
+        }
+
+        template <typename Fake = T>
+        static
+        typename std::enable_if<!::Catch::Detail::IsStreamInsertable<Fake>::value, std::string>::type
+            convert( const Fake& value ) {
+#if !defined(CATCH_CONFIG_FALLBACK_STRINGIFIER)
+            return Detail::convertUnstreamable(value);
+#else
+            return CATCH_CONFIG_FALLBACK_STRINGIFIER(value);
+#endif
+        }
+    };
+
+    namespace Detail {
+
+        // This function dispatches all stringification requests inside of Catch.
+        // Should be preferably called fully qualified, like ::Catch::Detail::stringify
+        template <typename T>
+        std::string stringify(const T& e) {
+            return ::Catch::StringMaker<typename std::remove_cv<typename std::remove_reference<T>::type>::type>::convert(e);
+        }
+
+        template<typename E>
+        std::string convertUnknownEnumToString( E e ) {
+            return ::Catch::Detail::stringify(static_cast<typename std::underlying_type<E>::type>(e));
+        }
+
+#if defined(_MANAGED)
+        template <typename T>
+        std::string stringify( T^ e ) {
+            return ::Catch::StringMaker<T^>::convert(e);
+        }
+#endif
+
+    } // namespace Detail
+
+    // Some predefined specializations
+
+    template<>
+    struct StringMaker<std::string> {
+        static std::string convert(const std::string& str);
+    };
+
+#ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+    template<>
+    struct StringMaker<std::string_view> {
+        static std::string convert(std::string_view str);
+    };
+#endif
+
+    template<>
+    struct StringMaker<char const *> {
+        static std::string convert(char const * str);
+    };
+    template<>
+    struct StringMaker<char *> {
+        static std::string convert(char * str);
+    };
+
+#ifdef CATCH_CONFIG_WCHAR
+    template<>
+    struct StringMaker<std::wstring> {
+        static std::string convert(const std::wstring& wstr);
+    };
+
+# ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+    template<>
+    struct StringMaker<std::wstring_view> {
+        static std::string convert(std::wstring_view str);
+    };
+# endif
+
+    template<>
+    struct StringMaker<wchar_t const *> {
+        static std::string convert(wchar_t const * str);
+    };
+    template<>
+    struct StringMaker<wchar_t *> {
+        static std::string convert(wchar_t * str);
+    };
+#endif
+
+    // TBD: Should we use `strnlen` to ensure that we don't go out of the buffer,
+    //      while keeping string semantics?
+    template<int SZ>
+    struct StringMaker<char[SZ]> {
+        static std::string convert(char const* str) {
+            return ::Catch::Detail::stringify(std::string{ str });
+        }
+    };
+    template<int SZ>
+    struct StringMaker<signed char[SZ]> {
+        static std::string convert(signed char const* str) {
+            return ::Catch::Detail::stringify(std::string{ reinterpret_cast<char const *>(str) });
+        }
+    };
+    template<int SZ>
+    struct StringMaker<unsigned char[SZ]> {
+        static std::string convert(unsigned char const* str) {
+            return ::Catch::Detail::stringify(std::string{ reinterpret_cast<char const *>(str) });
+        }
+    };
+
+#if defined(CATCH_CONFIG_CPP17_BYTE)
+    template<>
+    struct StringMaker<std::byte> {
+        static std::string convert(std::byte value);
+    };
+#endif // defined(CATCH_CONFIG_CPP17_BYTE)
+    template<>
+    struct StringMaker<int> {
+        static std::string convert(int value);
+    };
+    template<>
+    struct StringMaker<long> {
+        static std::string convert(long value);
+    };
+    template<>
+    struct StringMaker<long long> {
+        static std::string convert(long long value);
+    };
+    template<>
+    struct StringMaker<unsigned int> {
+        static std::string convert(unsigned int value);
+    };
+    template<>
+    struct StringMaker<unsigned long> {
+        static std::string convert(unsigned long value);
+    };
+    template<>
+    struct StringMaker<unsigned long long> {
+        static std::string convert(unsigned long long value);
+    };
+
+    template<>
+    struct StringMaker<bool> {
+        static std::string convert(bool b);
+    };
+
+    template<>
+    struct StringMaker<char> {
+        static std::string convert(char c);
+    };
+    template<>
+    struct StringMaker<signed char> {
+        static std::string convert(signed char c);
+    };
+    template<>
+    struct StringMaker<unsigned char> {
+        static std::string convert(unsigned char c);
+    };
+
+    template<>
+    struct StringMaker<std::nullptr_t> {
+        static std::string convert(std::nullptr_t);
+    };
+
+    template<>
+    struct StringMaker<float> {
+        static std::string convert(float value);
+        static int precision;
+    };
+
+    template<>
+    struct StringMaker<double> {
+        static std::string convert(double value);
+        static int precision;
+    };
+
+    template <typename T>
+    struct StringMaker<T*> {
+        template <typename U>
+        static std::string convert(U* p) {
+            if (p) {
+                return ::Catch::Detail::rawMemoryToString(p);
+            } else {
+                return "nullptr";
+            }
+        }
+    };
+
+    template <typename R, typename C>
+    struct StringMaker<R C::*> {
+        static std::string convert(R C::* p) {
+            if (p) {
+                return ::Catch::Detail::rawMemoryToString(p);
+            } else {
+                return "nullptr";
+            }
+        }
+    };
+
+#if defined(_MANAGED)
+    template <typename T>
+    struct StringMaker<T^> {
+        static std::string convert( T^ ref ) {
+            return ::Catch::Detail::clrReferenceToString(ref);
+        }
+    };
+#endif
+
+    namespace Detail {
+        template<typename InputIterator>
+        std::string rangeToString(InputIterator first, InputIterator last) {
+            ReusableStringStream rss;
+            rss << "{ ";
+            if (first != last) {
+                rss << ::Catch::Detail::stringify(*first);
+                for (++first; first != last; ++first)
+                    rss << ", " << ::Catch::Detail::stringify(*first);
+            }
+            rss << " }";
+            return rss.str();
+        }
+    }
+
+#ifdef __OBJC__
+    template<>
+    struct StringMaker<NSString*> {
+        static std::string convert(NSString * nsstring) {
+            if (!nsstring)
+                return "nil";
+            return std::string("@") + [nsstring UTF8String];
+        }
+    };
+    template<>
+    struct StringMaker<NSObject*> {
+        static std::string convert(NSObject* nsObject) {
+            return ::Catch::Detail::stringify([nsObject description]);
+        }
+
+    };
+    namespace Detail {
+        inline std::string stringify( NSString* nsstring ) {
+            return StringMaker<NSString*>::convert( nsstring );
+        }
+
+    } // namespace Detail
+#endif // __OBJC__
+
+} // namespace Catch
+
+//////////////////////////////////////////////////////
+// Separate std-lib types stringification, so it can be selectively enabled
+// This means that we do not bring in
+
+#if defined(CATCH_CONFIG_ENABLE_ALL_STRINGMAKERS)
+#  define CATCH_CONFIG_ENABLE_PAIR_STRINGMAKER
+#  define CATCH_CONFIG_ENABLE_TUPLE_STRINGMAKER
+#  define CATCH_CONFIG_ENABLE_VARIANT_STRINGMAKER
+#  define CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER
+#  define CATCH_CONFIG_ENABLE_OPTIONAL_STRINGMAKER
+#endif
+
+// Separate std::pair specialization
+#if defined(CATCH_CONFIG_ENABLE_PAIR_STRINGMAKER)
+#include <utility>
+namespace Catch {
+    template<typename T1, typename T2>
+    struct StringMaker<std::pair<T1, T2> > {
+        static std::string convert(const std::pair<T1, T2>& pair) {
+            ReusableStringStream rss;
+            rss << "{ "
+                << ::Catch::Detail::stringify(pair.first)
+                << ", "
+                << ::Catch::Detail::stringify(pair.second)
+                << " }";
+            return rss.str();
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_PAIR_STRINGMAKER
+
+#if defined(CATCH_CONFIG_ENABLE_OPTIONAL_STRINGMAKER) && defined(CATCH_CONFIG_CPP17_OPTIONAL)
+#include <optional>
+namespace Catch {
+    template<typename T>
+    struct StringMaker<std::optional<T> > {
+        static std::string convert(const std::optional<T>& optional) {
+            ReusableStringStream rss;
+            if (optional.has_value()) {
+                rss << ::Catch::Detail::stringify(*optional);
+            } else {
+                rss << "{ }";
+            }
+            return rss.str();
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_OPTIONAL_STRINGMAKER
+
+// Separate std::tuple specialization
+#if defined(CATCH_CONFIG_ENABLE_TUPLE_STRINGMAKER)
+#include <tuple>
+namespace Catch {
+    namespace Detail {
+        template<
+            typename Tuple,
+            std::size_t N = 0,
+            bool = (N < std::tuple_size<Tuple>::value)
+            >
+            struct TupleElementPrinter {
+            static void print(const Tuple& tuple, std::ostream& os) {
+                os << (N ? ", " : " ")
+                    << ::Catch::Detail::stringify(std::get<N>(tuple));
+                TupleElementPrinter<Tuple, N + 1>::print(tuple, os);
+            }
+        };
+
+        template<
+            typename Tuple,
+            std::size_t N
+        >
+            struct TupleElementPrinter<Tuple, N, false> {
+            static void print(const Tuple&, std::ostream&) {}
+        };
+
+    }
+
+    template<typename ...Types>
+    struct StringMaker<std::tuple<Types...>> {
+        static std::string convert(const std::tuple<Types...>& tuple) {
+            ReusableStringStream rss;
+            rss << '{';
+            Detail::TupleElementPrinter<std::tuple<Types...>>::print(tuple, rss.get());
+            rss << " }";
+            return rss.str();
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_TUPLE_STRINGMAKER
+
+#if defined(CATCH_CONFIG_ENABLE_VARIANT_STRINGMAKER) && defined(CATCH_CONFIG_CPP17_VARIANT)
+#include <variant>
+namespace Catch {
+    template<>
+    struct StringMaker<std::monostate> {
+        static std::string convert(const std::monostate&) {
+            return "{ }";
+        }
+    };
+
+    template<typename... Elements>
+    struct StringMaker<std::variant<Elements...>> {
+        static std::string convert(const std::variant<Elements...>& variant) {
+            if (variant.valueless_by_exception()) {
+                return "{valueless variant}";
+            } else {
+                return std::visit(
+                    [](const auto& value) {
+                        return ::Catch::Detail::stringify(value);
+                    },
+                    variant
+                );
+            }
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_VARIANT_STRINGMAKER
+
+namespace Catch {
+    struct not_this_one {}; // Tag type for detecting which begin/ end are being selected
+
+    // Import begin/ end from std here so they are considered alongside the fallback (...) overloads in this namespace
+    using std::begin;
+    using std::end;
+
+    not_this_one begin( ... );
+    not_this_one end( ... );
+
+    template <typename T>
+    struct is_range {
+        static const bool value =
+            !std::is_same<decltype(begin(std::declval<T>())), not_this_one>::value &&
+            !std::is_same<decltype(end(std::declval<T>())), not_this_one>::value;
+    };
+
+#if defined(_MANAGED) // Managed types are never ranges
+    template <typename T>
+    struct is_range<T^> {
+        static const bool value = false;
+    };
+#endif
+
+    template<typename Range>
+    std::string rangeToString( Range const& range ) {
+        return ::Catch::Detail::rangeToString( begin( range ), end( range ) );
+    }
+
+    // Handle vector<bool> specially
+    template<typename Allocator>
+    std::string rangeToString( std::vector<bool, Allocator> const& v ) {
+        ReusableStringStream rss;
+        rss << "{ ";
+        bool first = true;
+        for( bool b : v ) {
+            if( first )
+                first = false;
+            else
+                rss << ", ";
+            rss << ::Catch::Detail::stringify( b );
+        }
+        rss << " }";
+        return rss.str();
+    }
+
+    template<typename R>
+    struct StringMaker<R, typename std::enable_if<is_range<R>::value && !::Catch::Detail::IsStreamInsertable<R>::value>::type> {
+        static std::string convert( R const& range ) {
+            return rangeToString( range );
+        }
+    };
+
+    template <typename T, int SZ>
+    struct StringMaker<T[SZ]> {
+        static std::string convert(T const(&arr)[SZ]) {
+            return rangeToString(arr);
+        }
+    };
+
+} // namespace Catch
+
+// Separate std::chrono::duration specialization
+#if defined(CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER)
+#include <ctime>
+#include <ratio>
+#include <chrono>
+
+namespace Catch {
+
+template <class Ratio>
+struct ratio_string {
+    static std::string symbol();
+};
+
+template <class Ratio>
+std::string ratio_string<Ratio>::symbol() {
+    Catch::ReusableStringStream rss;
+    rss << '[' << Ratio::num << '/'
+        << Ratio::den << ']';
+    return rss.str();
+}
+template <>
+struct ratio_string<std::atto> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::femto> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::pico> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::nano> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::micro> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::milli> {
+    static std::string symbol();
+};
+
+    ////////////
+    // std::chrono::duration specializations
+    template<typename Value, typename Ratio>
+    struct StringMaker<std::chrono::duration<Value, Ratio>> {
+        static std::string convert(std::chrono::duration<Value, Ratio> const& duration) {
+            ReusableStringStream rss;
+            rss << duration.count() << ' ' << ratio_string<Ratio>::symbol() << 's';
+            return rss.str();
+        }
+    };
+    template<typename Value>
+    struct StringMaker<std::chrono::duration<Value, std::ratio<1>>> {
+        static std::string convert(std::chrono::duration<Value, std::ratio<1>> const& duration) {
+            ReusableStringStream rss;
+            rss << duration.count() << " s";
+            return rss.str();
+        }
+    };
+    template<typename Value>
+    struct StringMaker<std::chrono::duration<Value, std::ratio<60>>> {
+        static std::string convert(std::chrono::duration<Value, std::ratio<60>> const& duration) {
+            ReusableStringStream rss;
+            rss << duration.count() << " m";
+            return rss.str();
+        }
+    };
+    template<typename Value>
+    struct StringMaker<std::chrono::duration<Value, std::ratio<3600>>> {
+        static std::string convert(std::chrono::duration<Value, std::ratio<3600>> const& duration) {
+            ReusableStringStream rss;
+            rss << duration.count() << " h";
+            return rss.str();
+        }
+    };
+
+    ////////////
+    // std::chrono::time_point specialization
+    // Generic time_point cannot be specialized, only std::chrono::time_point<system_clock>
+    template<typename Clock, typename Duration>
+    struct StringMaker<std::chrono::time_point<Clock, Duration>> {
+        static std::string convert(std::chrono::time_point<Clock, Duration> const& time_point) {
+            return ::Catch::Detail::stringify(time_point.time_since_epoch()) + " since epoch";
+        }
+    };
+    // std::chrono::time_point<system_clock> specialization
+    template<typename Duration>
+    struct StringMaker<std::chrono::time_point<std::chrono::system_clock, Duration>> {
+        static std::string convert(std::chrono::time_point<std::chrono::system_clock, Duration> const& time_point) {
+            auto converted = std::chrono::system_clock::to_time_t(time_point);
+
+#ifdef _MSC_VER
+            std::tm timeInfo = {};
+            gmtime_s(&timeInfo, &converted);
+#else
+            std::tm* timeInfo = std::gmtime(&converted);
+#endif
+
+            auto const timeStampSize = sizeof("2017-01-16T17:06:45Z");
+            char timeStamp[timeStampSize];
+            const char * const fmt = "%Y-%m-%dT%H:%M:%SZ";
+
+#ifdef _MSC_VER
+            std::strftime(timeStamp, timeStampSize, fmt, &timeInfo);
+#else
+            std::strftime(timeStamp, timeStampSize, fmt, timeInfo);
+#endif
+            return std::string(timeStamp);
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER
+
+#define INTERNAL_CATCH_REGISTER_ENUM( enumName, ... ) \
+namespace Catch { \
+    template<> struct StringMaker<enumName> { \
+        static std::string convert( enumName value ) { \
+            static const auto& enumInfo = ::Catch::getMutableRegistryHub().getMutableEnumValuesRegistry().registerEnum( #enumName, #__VA_ARGS__, { __VA_ARGS__ } ); \
+            return static_cast<std::string>(enumInfo.lookup( static_cast<int>( value ) )); \
+        } \
+    }; \
+}
+
+#define CATCH_REGISTER_ENUM( enumName, ... ) INTERNAL_CATCH_REGISTER_ENUM( enumName, __VA_ARGS__ )
+
+#ifdef _MSC_VER
+#pragma warning(pop)
+#endif
+
+// end catch_tostring.h
+#include <iosfwd>
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable:4389) // '==' : signed/unsigned mismatch
+#pragma warning(disable:4018) // more "signed/unsigned mismatch"
+#pragma warning(disable:4312) // Converting int to T* using reinterpret_cast (issue on x64 platform)
+#pragma warning(disable:4180) // qualifier applied to function type has no meaning
+#pragma warning(disable:4800) // Forcing result to true or false
+#endif
+
+namespace Catch {
+
+    struct ITransientExpression {
+        auto isBinaryExpression() const -> bool { return m_isBinaryExpression; }
+        auto getResult() const -> bool { return m_result; }
+        virtual void streamReconstructedExpression( std::ostream &os ) const = 0;
+
+        ITransientExpression( bool isBinaryExpression, bool result )
+        :   m_isBinaryExpression( isBinaryExpression ),
+            m_result( result )
+        {}
+
+        // We don't actually need a virtual destructor, but many static analysers
+        // complain if it's not here :-(
+        virtual ~ITransientExpression();
+
+        bool m_isBinaryExpression;
+        bool m_result;
+
+    };
+
+    void formatReconstructedExpression( std::ostream &os, std::string const& lhs, StringRef op, std::string const& rhs );
+
+    template<typename LhsT, typename RhsT>
+    class BinaryExpr  : public ITransientExpression {
+        LhsT m_lhs;
+        StringRef m_op;
+        RhsT m_rhs;
+
+        void streamReconstructedExpression( std::ostream &os ) const override {
+            formatReconstructedExpression
+                    ( os, Catch::Detail::stringify( m_lhs ), m_op, Catch::Detail::stringify( m_rhs ) );
+        }
+
+    public:
+        BinaryExpr( bool comparisonResult, LhsT lhs, StringRef op, RhsT rhs )
+        :   ITransientExpression{ true, comparisonResult },
+            m_lhs( lhs ),
+            m_op( op ),
+            m_rhs( rhs )
+        {}
+
+        template<typename T>
+        auto operator && ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator || ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator == ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator != ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator > ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator < ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator >= ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator <= ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+    };
+
+    template<typename LhsT>
+    class UnaryExpr : public ITransientExpression {
+        LhsT m_lhs;
+
+        void streamReconstructedExpression( std::ostream &os ) const override {
+            os << Catch::Detail::stringify( m_lhs );
+        }
+
+    public:
+        explicit UnaryExpr( LhsT lhs )
+        :   ITransientExpression{ false, static_cast<bool>(lhs) },
+            m_lhs( lhs )
+        {}
+    };
+
+    // Specialised comparison functions to handle equality comparisons between ints and pointers (NULL deduces as an int)
+    template<typename LhsT, typename RhsT>
+    auto compareEqual( LhsT const& lhs, RhsT const& rhs ) -> bool { return static_cast<bool>(lhs == rhs); }
+    template<typename T>
+    auto compareEqual( T* const& lhs, int rhs ) -> bool { return lhs == reinterpret_cast<void const*>( rhs ); }
+    template<typename T>
+    auto compareEqual( T* const& lhs, long rhs ) -> bool { return lhs == reinterpret_cast<void const*>( rhs ); }
+    template<typename T>
+    auto compareEqual( int lhs, T* const& rhs ) -> bool { return reinterpret_cast<void const*>( lhs ) == rhs; }
+    template<typename T>
+    auto compareEqual( long lhs, T* const& rhs ) -> bool { return reinterpret_cast<void const*>( lhs ) == rhs; }
+
+    template<typename LhsT, typename RhsT>
+    auto compareNotEqual( LhsT const& lhs, RhsT&& rhs ) -> bool { return static_cast<bool>(lhs != rhs); }
+    template<typename T>
+    auto compareNotEqual( T* const& lhs, int rhs ) -> bool { return lhs != reinterpret_cast<void const*>( rhs ); }
+    template<typename T>
+    auto compareNotEqual( T* const& lhs, long rhs ) -> bool { return lhs != reinterpret_cast<void const*>( rhs ); }
+    template<typename T>
+    auto compareNotEqual( int lhs, T* const& rhs ) -> bool { return reinterpret_cast<void const*>( lhs ) != rhs; }
+    template<typename T>
+    auto compareNotEqual( long lhs, T* const& rhs ) -> bool { return reinterpret_cast<void const*>( lhs ) != rhs; }
+
+    template<typename LhsT>
+    class ExprLhs {
+        LhsT m_lhs;
+    public:
+        explicit ExprLhs( LhsT lhs ) : m_lhs( lhs ) {}
+
+        template<typename RhsT>
+        auto operator == ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { compareEqual( m_lhs, rhs ), m_lhs, "==", rhs };
+        }
+        auto operator == ( bool rhs ) -> BinaryExpr<LhsT, bool> const {
+            return { m_lhs == rhs, m_lhs, "==", rhs };
+        }
+
+        template<typename RhsT>
+        auto operator != ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { compareNotEqual( m_lhs, rhs ), m_lhs, "!=", rhs };
+        }
+        auto operator != ( bool rhs ) -> BinaryExpr<LhsT, bool> const {
+            return { m_lhs != rhs, m_lhs, "!=", rhs };
+        }
+
+        template<typename RhsT>
+        auto operator > ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs > rhs), m_lhs, ">", rhs };
+        }
+        template<typename RhsT>
+        auto operator < ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs < rhs), m_lhs, "<", rhs };
+        }
+        template<typename RhsT>
+        auto operator >= ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs >= rhs), m_lhs, ">=", rhs };
+        }
+        template<typename RhsT>
+        auto operator <= ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs <= rhs), m_lhs, "<=", rhs };
+        }
+
+        template<typename RhsT>
+        auto operator && ( RhsT const& ) -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<RhsT>::value,
+            "operator&& is not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename RhsT>
+        auto operator || ( RhsT const& ) -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<RhsT>::value,
+            "operator|| is not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        auto makeUnaryExpr() const -> UnaryExpr<LhsT> {
+            return UnaryExpr<LhsT>{ m_lhs };
+        }
+    };
+
+    void handleExpression( ITransientExpression const& expr );
+
+    template<typename T>
+    void handleExpression( ExprLhs<T> const& expr ) {
+        handleExpression( expr.makeUnaryExpr() );
+    }
+
+    struct Decomposer {
+        template<typename T>
+        auto operator <= ( T const& lhs ) -> ExprLhs<T const&> {
+            return ExprLhs<T const&>{ lhs };
+        }
+
+        auto operator <=( bool value ) -> ExprLhs<bool> {
+            return ExprLhs<bool>{ value };
+        }
+    };
+
+} // end namespace Catch
+
+#ifdef _MSC_VER
+#pragma warning(pop)
+#endif
+
+// end catch_decomposer.h
+// start catch_interfaces_capture.h
+
+#include <string>
+#include <chrono>
+
+namespace Catch {
+
+    class AssertionResult;
+    struct AssertionInfo;
+    struct SectionInfo;
+    struct SectionEndInfo;
+    struct MessageInfo;
+    struct MessageBuilder;
+    struct Counts;
+    struct AssertionReaction;
+    struct SourceLineInfo;
+
+    struct ITransientExpression;
+    struct IGeneratorTracker;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    struct BenchmarkInfo;
+    template <typename Duration = std::chrono::duration<double, std::nano>>
+    struct BenchmarkStats;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    struct IResultCapture {
+
+        virtual ~IResultCapture();
+
+        virtual bool sectionStarted(    SectionInfo const& sectionInfo,
+                                        Counts& assertions ) = 0;
+        virtual void sectionEnded( SectionEndInfo const& endInfo ) = 0;
+        virtual void sectionEndedEarly( SectionEndInfo const& endInfo ) = 0;
+
+        virtual auto acquireGeneratorTracker( SourceLineInfo const& lineInfo ) -> IGeneratorTracker& = 0;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        virtual void benchmarkPreparing( std::string const& name ) = 0;
+        virtual void benchmarkStarting( BenchmarkInfo const& info ) = 0;
+        virtual void benchmarkEnded( BenchmarkStats<> const& stats ) = 0;
+        virtual void benchmarkFailed( std::string const& error ) = 0;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        virtual void pushScopedMessage( MessageInfo const& message ) = 0;
+        virtual void popScopedMessage( MessageInfo const& message ) = 0;
+
+        virtual void emplaceUnscopedMessage( MessageBuilder const& builder ) = 0;
+
+        virtual void handleFatalErrorCondition( StringRef message ) = 0;
+
+        virtual void handleExpr
+                (   AssertionInfo const& info,
+                    ITransientExpression const& expr,
+                    AssertionReaction& reaction ) = 0;
+        virtual void handleMessage
+                (   AssertionInfo const& info,
+                    ResultWas::OfType resultType,
+                    StringRef const& message,
+                    AssertionReaction& reaction ) = 0;
+        virtual void handleUnexpectedExceptionNotThrown
+                (   AssertionInfo const& info,
+                    AssertionReaction& reaction ) = 0;
+        virtual void handleUnexpectedInflightException
+                (   AssertionInfo const& info,
+                    std::string const& message,
+                    AssertionReaction& reaction ) = 0;
+        virtual void handleIncomplete
+                (   AssertionInfo const& info ) = 0;
+        virtual void handleNonExpr
+                (   AssertionInfo const &info,
+                    ResultWas::OfType resultType,
+                    AssertionReaction &reaction ) = 0;
+
+        virtual bool lastAssertionPassed() = 0;
+        virtual void assertionPassed() = 0;
+
+        // Deprecated, do not use:
+        virtual std::string getCurrentTestName() const = 0;
+        virtual const AssertionResult* getLastResult() const = 0;
+        virtual void exceptionEarlyReported() = 0;
+    };
+
+    IResultCapture& getResultCapture();
+}
+
+// end catch_interfaces_capture.h
+namespace Catch {
+
+    struct TestFailureException{};
+    struct AssertionResultData;
+    struct IResultCapture;
+    class RunContext;
+
+    class LazyExpression {
+        friend class AssertionHandler;
+        friend struct AssertionStats;
+        friend class RunContext;
+
+        ITransientExpression const* m_transientExpression = nullptr;
+        bool m_isNegated;
+    public:
+        LazyExpression( bool isNegated );
+        LazyExpression( LazyExpression const& other );
+        LazyExpression& operator = ( LazyExpression const& ) = delete;
+
+        explicit operator bool() const;
+
+        friend auto operator << ( std::ostream& os, LazyExpression const& lazyExpr ) -> std::ostream&;
+    };
+
+    struct AssertionReaction {
+        bool shouldDebugBreak = false;
+        bool shouldThrow = false;
+    };
+
+    class AssertionHandler {
+        AssertionInfo m_assertionInfo;
+        AssertionReaction m_reaction;
+        bool m_completed = false;
+        IResultCapture& m_resultCapture;
+
+    public:
+        AssertionHandler
+            (   StringRef const& macroName,
+                SourceLineInfo const& lineInfo,
+                StringRef capturedExpression,
+                ResultDisposition::Flags resultDisposition );
+        ~AssertionHandler() {
+            if ( !m_completed ) {
+                m_resultCapture.handleIncomplete( m_assertionInfo );
+            }
+        }
+
+        template<typename T>
+        void handleExpr( ExprLhs<T> const& expr ) {
+            handleExpr( expr.makeUnaryExpr() );
+        }
+        void handleExpr( ITransientExpression const& expr );
+
+        void handleMessage(ResultWas::OfType resultType, StringRef const& message);
+
+        void handleExceptionThrownAsExpected();
+        void handleUnexpectedExceptionNotThrown();
+        void handleExceptionNotThrownAsExpected();
+        void handleThrowingCallSkipped();
+        void handleUnexpectedInflightException();
+
+        void complete();
+        void setCompleted();
+
+        // query
+        auto allowThrows() const -> bool;
+    };
+
+    void handleExceptionMatchExpr( AssertionHandler& handler, std::string const& str, StringRef const& matcherString );
+
+} // namespace Catch
+
+// end catch_assertionhandler.h
+// start catch_message.h
+
+#include <string>
+#include <vector>
+
+namespace Catch {
+
+    struct MessageInfo {
+        MessageInfo(    StringRef const& _macroName,
+                        SourceLineInfo const& _lineInfo,
+                        ResultWas::OfType _type );
+
+        StringRef macroName;
+        std::string message;
+        SourceLineInfo lineInfo;
+        ResultWas::OfType type;
+        unsigned int sequence;
+
+        bool operator == ( MessageInfo const& other ) const;
+        bool operator < ( MessageInfo const& other ) const;
+    private:
+        static unsigned int globalCount;
+    };
+
+    struct MessageStream {
+
+        template<typename T>
+        MessageStream& operator << ( T const& value ) {
+            m_stream << value;
+            return *this;
+        }
+
+        ReusableStringStream m_stream;
+    };
+
+    struct MessageBuilder : MessageStream {
+        MessageBuilder( StringRef const& macroName,
+                        SourceLineInfo const& lineInfo,
+                        ResultWas::OfType type );
+
+        template<typename T>
+        MessageBuilder& operator << ( T const& value ) {
+            m_stream << value;
+            return *this;
+        }
+
+        MessageInfo m_info;
+    };
+
+    class ScopedMessage {
+    public:
+        explicit ScopedMessage( MessageBuilder const& builder );
+        ScopedMessage( ScopedMessage& duplicate ) = delete;
+        ScopedMessage( ScopedMessage&& old );
+        ~ScopedMessage();
+
+        MessageInfo m_info;
+        bool m_moved;
+    };
+
+    class Capturer {
+        std::vector<MessageInfo> m_messages;
+        IResultCapture& m_resultCapture = getResultCapture();
+        size_t m_captured = 0;
+    public:
+        Capturer( StringRef macroName, SourceLineInfo const& lineInfo, ResultWas::OfType resultType, StringRef names );
+        ~Capturer();
+
+        void captureValue( size_t index, std::string const& value );
+
+        template<typename T>
+        void captureValues( size_t index, T const& value ) {
+            captureValue( index, Catch::Detail::stringify( value ) );
+        }
+
+        template<typename T, typename... Ts>
+        void captureValues( size_t index, T const& value, Ts const&... values ) {
+            captureValue( index, Catch::Detail::stringify(value) );
+            captureValues( index+1, values... );
+        }
+    };
+
+} // end namespace Catch
+
+// end catch_message.h
+#if !defined(CATCH_CONFIG_DISABLE)
+
+#if !defined(CATCH_CONFIG_DISABLE_STRINGIFICATION)
+  #define CATCH_INTERNAL_STRINGIFY(...) #__VA_ARGS__
+#else
+  #define CATCH_INTERNAL_STRINGIFY(...) "Disabled by CATCH_CONFIG_DISABLE_STRINGIFICATION"
+#endif
+
+#if defined(CATCH_CONFIG_FAST_COMPILE) || defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+
+///////////////////////////////////////////////////////////////////////////////
+// Another way to speed-up compilation is to omit local try-catch for REQUIRE*
+// macros.
+#define INTERNAL_CATCH_TRY
+#define INTERNAL_CATCH_CATCH( capturer )
+
+#else // CATCH_CONFIG_FAST_COMPILE
+
+#define INTERNAL_CATCH_TRY try
+#define INTERNAL_CATCH_CATCH( handler ) catch(...) { handler.handleUnexpectedInflightException(); }
+
+#endif
+
+#define INTERNAL_CATCH_REACT( handler ) handler.complete();
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_TEST( macroName, resultDisposition, ... ) \
+    do { \
+        CATCH_INTERNAL_IGNORE_BUT_WARN(__VA_ARGS__); \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__), resultDisposition ); \
+        INTERNAL_CATCH_TRY { \
+            CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+            CATCH_INTERNAL_SUPPRESS_PARENTHESES_WARNINGS \
+            catchAssertionHandler.handleExpr( Catch::Decomposer() <= __VA_ARGS__ ); \
+            CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        } INTERNAL_CATCH_CATCH( catchAssertionHandler ) \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( (void)0, (false) && static_cast<bool>( !!(__VA_ARGS__) ) )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_IF( macroName, resultDisposition, ... ) \
+    INTERNAL_CATCH_TEST( macroName, resultDisposition, __VA_ARGS__ ); \
+    if( Catch::getResultCapture().lastAssertionPassed() )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_ELSE( macroName, resultDisposition, ... ) \
+    INTERNAL_CATCH_TEST( macroName, resultDisposition, __VA_ARGS__ ); \
+    if( !Catch::getResultCapture().lastAssertionPassed() )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_NO_THROW( macroName, resultDisposition, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__), resultDisposition ); \
+        try { \
+            static_cast<void>(__VA_ARGS__); \
+            catchAssertionHandler.handleExceptionNotThrownAsExpected(); \
+        } \
+        catch( ... ) { \
+            catchAssertionHandler.handleUnexpectedInflightException(); \
+        } \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_THROWS( macroName, resultDisposition, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__), resultDisposition); \
+        if( catchAssertionHandler.allowThrows() ) \
+            try { \
+                static_cast<void>(__VA_ARGS__); \
+                catchAssertionHandler.handleUnexpectedExceptionNotThrown(); \
+            } \
+            catch( ... ) { \
+                catchAssertionHandler.handleExceptionThrownAsExpected(); \
+            } \
+        else \
+            catchAssertionHandler.handleThrowingCallSkipped(); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_THROWS_AS( macroName, exceptionType, resultDisposition, expr ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(expr) ", " CATCH_INTERNAL_STRINGIFY(exceptionType), resultDisposition ); \
+        if( catchAssertionHandler.allowThrows() ) \
+            try { \
+                static_cast<void>(expr); \
+                catchAssertionHandler.handleUnexpectedExceptionNotThrown(); \
+            } \
+            catch( exceptionType const& ) { \
+                catchAssertionHandler.handleExceptionThrownAsExpected(); \
+            } \
+            catch( ... ) { \
+                catchAssertionHandler.handleUnexpectedInflightException(); \
+            } \
+        else \
+            catchAssertionHandler.handleThrowingCallSkipped(); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_MSG( macroName, messageType, resultDisposition, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, Catch::StringRef(), resultDisposition ); \
+        catchAssertionHandler.handleMessage( messageType, ( Catch::MessageStream() << __VA_ARGS__ + ::Catch::StreamEndStop() ).m_stream.str() ); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_CAPTURE( varName, macroName, ... ) \
+    auto varName = Catch::Capturer( macroName, CATCH_INTERNAL_LINEINFO, Catch::ResultWas::Info, #__VA_ARGS__ ); \
+    varName.captureValues( 0, __VA_ARGS__ )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_INFO( macroName, log ) \
+    Catch::ScopedMessage INTERNAL_CATCH_UNIQUE_NAME( scopedMessage )( Catch::MessageBuilder( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, Catch::ResultWas::Info ) << log );
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_UNSCOPED_INFO( macroName, log ) \
+    Catch::getResultCapture().emplaceUnscopedMessage( Catch::MessageBuilder( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, Catch::ResultWas::Info ) << log )
+
+///////////////////////////////////////////////////////////////////////////////
+// Although this is matcher-based, it can be used with just a string
+#define INTERNAL_CATCH_THROWS_STR_MATCHES( macroName, resultDisposition, matcher, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__) ", " CATCH_INTERNAL_STRINGIFY(matcher), resultDisposition ); \
+        if( catchAssertionHandler.allowThrows() ) \
+            try { \
+                static_cast<void>(__VA_ARGS__); \
+                catchAssertionHandler.handleUnexpectedExceptionNotThrown(); \
+            } \
+            catch( ... ) { \
+                Catch::handleExceptionMatchExpr( catchAssertionHandler, matcher, #matcher##_catch_sr ); \
+            } \
+        else \
+            catchAssertionHandler.handleThrowingCallSkipped(); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+#endif // CATCH_CONFIG_DISABLE
+
+// end catch_capture.hpp
+// start catch_section.h
+
+// start catch_section_info.h
+
+// start catch_totals.h
+
+#include <cstddef>
+
+namespace Catch {
+
+    struct Counts {
+        Counts operator - ( Counts const& other ) const;
+        Counts& operator += ( Counts const& other );
+
+        std::size_t total() const;
+        bool allPassed() const;
+        bool allOk() const;
+
+        std::size_t passed = 0;
+        std::size_t failed = 0;
+        std::size_t failedButOk = 0;
+    };
+
+    struct Totals {
+
+        Totals operator - ( Totals const& other ) const;
+        Totals& operator += ( Totals const& other );
+
+        Totals delta( Totals const& prevTotals ) const;
+
+        int error = 0;
+        Counts assertions;
+        Counts testCases;
+    };
+}
+
+// end catch_totals.h
+#include <string>
+
+namespace Catch {
+
+    struct SectionInfo {
+        SectionInfo
+            (   SourceLineInfo const& _lineInfo,
+                std::string const& _name );
+
+        // Deprecated
+        SectionInfo
+            (   SourceLineInfo const& _lineInfo,
+                std::string const& _name,
+                std::string const& ) : SectionInfo( _lineInfo, _name ) {}
+
+        std::string name;
+        std::string description; // !Deprecated: this will always be empty
+        SourceLineInfo lineInfo;
+    };
+
+    struct SectionEndInfo {
+        SectionInfo sectionInfo;
+        Counts prevAssertions;
+        double durationInSeconds;
+    };
+
+} // end namespace Catch
+
+// end catch_section_info.h
+// start catch_timer.h
+
+#include <cstdint>
+
+namespace Catch {
+
+    auto getCurrentNanosecondsSinceEpoch() -> uint64_t;
+    auto getEstimatedClockResolution() -> uint64_t;
+
+    class Timer {
+        uint64_t m_nanoseconds = 0;
+    public:
+        void start();
+        auto getElapsedNanoseconds() const -> uint64_t;
+        auto getElapsedMicroseconds() const -> uint64_t;
+        auto getElapsedMilliseconds() const -> unsigned int;
+        auto getElapsedSeconds() const -> double;
+    };
+
+} // namespace Catch
+
+// end catch_timer.h
+#include <string>
+
+namespace Catch {
+
+    class Section : NonCopyable {
+    public:
+        Section( SectionInfo const& info );
+        ~Section();
+
+        // This indicates whether the section should be executed or not
+        explicit operator bool() const;
+
+    private:
+        SectionInfo m_info;
+
+        std::string m_name;
+        Counts m_assertions;
+        bool m_sectionIncluded;
+        Timer m_timer;
+    };
+
+} // end namespace Catch
+
+#define INTERNAL_CATCH_SECTION( ... ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+    CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS \
+    if( Catch::Section const& INTERNAL_CATCH_UNIQUE_NAME( catch_internal_Section ) = Catch::SectionInfo( CATCH_INTERNAL_LINEINFO, __VA_ARGS__ ) ) \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+#define INTERNAL_CATCH_DYNAMIC_SECTION( ... ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+    CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS \
+    if( Catch::Section const& INTERNAL_CATCH_UNIQUE_NAME( catch_internal_Section ) = Catch::SectionInfo( CATCH_INTERNAL_LINEINFO, (Catch::ReusableStringStream() << __VA_ARGS__).str() ) ) \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+// end catch_section.h
+// start catch_interfaces_exception.h
+
+// start catch_interfaces_registry_hub.h
+
+#include <string>
+#include <memory>
+
+namespace Catch {
+
+    class TestCase;
+    struct ITestCaseRegistry;
+    struct IExceptionTranslatorRegistry;
+    struct IExceptionTranslator;
+    struct IReporterRegistry;
+    struct IReporterFactory;
+    struct ITagAliasRegistry;
+    struct IMutableEnumValuesRegistry;
+
+    class StartupExceptionRegistry;
+
+    using IReporterFactoryPtr = std::shared_ptr<IReporterFactory>;
+
+    struct IRegistryHub {
+        virtual ~IRegistryHub();
+
+        virtual IReporterRegistry const& getReporterRegistry() const = 0;
+        virtual ITestCaseRegistry const& getTestCaseRegistry() const = 0;
+        virtual ITagAliasRegistry const& getTagAliasRegistry() const = 0;
+        virtual IExceptionTranslatorRegistry const& getExceptionTranslatorRegistry() const = 0;
+
+        virtual StartupExceptionRegistry const& getStartupExceptionRegistry() const = 0;
+    };
+
+    struct IMutableRegistryHub {
+        virtual ~IMutableRegistryHub();
+        virtual void registerReporter( std::string const& name, IReporterFactoryPtr const& factory ) = 0;
+        virtual void registerListener( IReporterFactoryPtr const& factory ) = 0;
+        virtual void registerTest( TestCase const& testInfo ) = 0;
+        virtual void registerTranslator( const IExceptionTranslator* translator ) = 0;
+        virtual void registerTagAlias( std::string const& alias, std::string const& tag, SourceLineInfo const& lineInfo ) = 0;
+        virtual void registerStartupException() noexcept = 0;
+        virtual IMutableEnumValuesRegistry& getMutableEnumValuesRegistry() = 0;
+    };
+
+    IRegistryHub const& getRegistryHub();
+    IMutableRegistryHub& getMutableRegistryHub();
+    void cleanUp();
+    std::string translateActiveException();
+
+}
+
+// end catch_interfaces_registry_hub.h
+#if defined(CATCH_CONFIG_DISABLE)
+    #define INTERNAL_CATCH_TRANSLATE_EXCEPTION_NO_REG( translatorName, signature) \
+        static std::string translatorName( signature )
+#endif
+
+#include <exception>
+#include <string>
+#include <vector>
+
+namespace Catch {
+    using exceptionTranslateFunction = std::string(*)();
+
+    struct IExceptionTranslator;
+    using ExceptionTranslators = std::vector<std::unique_ptr<IExceptionTranslator const>>;
+
+    struct IExceptionTranslator {
+        virtual ~IExceptionTranslator();
+        virtual std::string translate( ExceptionTranslators::const_iterator it, ExceptionTranslators::const_iterator itEnd ) const = 0;
+    };
+
+    struct IExceptionTranslatorRegistry {
+        virtual ~IExceptionTranslatorRegistry();
+
+        virtual std::string translateActiveException() const = 0;
+    };
+
+    class ExceptionTranslatorRegistrar {
+        template<typename T>
+        class ExceptionTranslator : public IExceptionTranslator {
+        public:
+
+            ExceptionTranslator( std::string(*translateFunction)( T& ) )
+            : m_translateFunction( translateFunction )
+            {}
+
+            std::string translate( ExceptionTranslators::const_iterator it, ExceptionTranslators::const_iterator itEnd ) const override {
+                try {
+                    if( it == itEnd )
+                        std::rethrow_exception(std::current_exception());
+                    else
+                        return (*it)->translate( it+1, itEnd );
+                }
+                catch( T& ex ) {
+                    return m_translateFunction( ex );
+                }
+            }
+
+        protected:
+            std::string(*m_translateFunction)( T& );
+        };
+
+    public:
+        template<typename T>
+        ExceptionTranslatorRegistrar( std::string(*translateFunction)( T& ) ) {
+            getMutableRegistryHub().registerTranslator
+                ( new ExceptionTranslator<T>( translateFunction ) );
+        }
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_TRANSLATE_EXCEPTION2( translatorName, signature ) \
+    static std::string translatorName( signature ); \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+    CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+    namespace{ Catch::ExceptionTranslatorRegistrar INTERNAL_CATCH_UNIQUE_NAME( catch_internal_ExceptionRegistrar )( &translatorName ); } \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+    static std::string translatorName( signature )
+
+#define INTERNAL_CATCH_TRANSLATE_EXCEPTION( signature ) INTERNAL_CATCH_TRANSLATE_EXCEPTION2( INTERNAL_CATCH_UNIQUE_NAME( catch_internal_ExceptionTranslator ), signature )
+
+// end catch_interfaces_exception.h
+// start catch_approx.h
+
+#include <type_traits>
+
+namespace Catch {
+namespace Detail {
+
+    class Approx {
+    private:
+        bool equalityComparisonImpl(double other) const;
+        // Validates the new margin (margin >= 0)
+        // out-of-line to avoid including stdexcept in the header
+        void setMargin(double margin);
+        // Validates the new epsilon (0 < epsilon < 1)
+        // out-of-line to avoid including stdexcept in the header
+        void setEpsilon(double epsilon);
+
+    public:
+        explicit Approx ( double value );
+
+        static Approx custom();
+
+        Approx operator-() const;
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        Approx operator()( T const& value ) {
+            Approx approx( static_cast<double>(value) );
+            approx.m_epsilon = m_epsilon;
+            approx.m_margin = m_margin;
+            approx.m_scale = m_scale;
+            return approx;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        explicit Approx( T const& value ): Approx(static_cast<double>(value))
+        {}
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator == ( const T& lhs, Approx const& rhs ) {
+            auto lhs_v = static_cast<double>(lhs);
+            return rhs.equalityComparisonImpl(lhs_v);
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator == ( Approx const& lhs, const T& rhs ) {
+            return operator==( rhs, lhs );
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator != ( T const& lhs, Approx const& rhs ) {
+            return !operator==( lhs, rhs );
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator != ( Approx const& lhs, T const& rhs ) {
+            return !operator==( rhs, lhs );
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator <= ( T const& lhs, Approx const& rhs ) {
+            return static_cast<double>(lhs) < rhs.m_value || lhs == rhs;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator <= ( Approx const& lhs, T const& rhs ) {
+            return lhs.m_value < static_cast<double>(rhs) || lhs == rhs;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator >= ( T const& lhs, Approx const& rhs ) {
+            return static_cast<double>(lhs) > rhs.m_value || lhs == rhs;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator >= ( Approx const& lhs, T const& rhs ) {
+            return lhs.m_value > static_cast<double>(rhs) || lhs == rhs;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        Approx& epsilon( T const& newEpsilon ) {
+            double epsilonAsDouble = static_cast<double>(newEpsilon);
+            setEpsilon(epsilonAsDouble);
+            return *this;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        Approx& margin( T const& newMargin ) {
+            double marginAsDouble = static_cast<double>(newMargin);
+            setMargin(marginAsDouble);
+            return *this;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        Approx& scale( T const& newScale ) {
+            m_scale = static_cast<double>(newScale);
+            return *this;
+        }
+
+        std::string toString() const;
+
+    private:
+        double m_epsilon;
+        double m_margin;
+        double m_scale;
+        double m_value;
+    };
+} // end namespace Detail
+
+namespace literals {
+    Detail::Approx operator "" _a(long double val);
+    Detail::Approx operator "" _a(unsigned long long val);
+} // end namespace literals
+
+template<>
+struct StringMaker<Catch::Detail::Approx> {
+    static std::string convert(Catch::Detail::Approx const& value);
+};
+
+} // end namespace Catch
+
+// end catch_approx.h
+// start catch_string_manip.h
+
+#include <string>
+#include <iosfwd>
+#include <vector>
+
+namespace Catch {
+
+    bool startsWith( std::string const& s, std::string const& prefix );
+    bool startsWith( std::string const& s, char prefix );
+    bool endsWith( std::string const& s, std::string const& suffix );
+    bool endsWith( std::string const& s, char suffix );
+    bool contains( std::string const& s, std::string const& infix );
+    void toLowerInPlace( std::string& s );
+    std::string toLower( std::string const& s );
+    //! Returns a new string without whitespace at the start/end
+    std::string trim( std::string const& str );
+    //! Returns a substring of the original ref without whitespace. Beware lifetimes!
+    StringRef trim(StringRef ref);
+
+    // !!! Be aware, returns refs into original string - make sure original string outlives them
+    std::vector<StringRef> splitStringRef( StringRef str, char delimiter );
+    bool replaceInPlace( std::string& str, std::string const& replaceThis, std::string const& withThis );
+
+    struct pluralise {
+        pluralise( std::size_t count, std::string const& label );
+
+        friend std::ostream& operator << ( std::ostream& os, pluralise const& pluraliser );
+
+        std::size_t m_count;
+        std::string m_label;
+    };
+}
+
+// end catch_string_manip.h
+#ifndef CATCH_CONFIG_DISABLE_MATCHERS
+// start catch_capture_matchers.h
+
+// start catch_matchers.h
+
+#include <string>
+#include <vector>
+
+namespace Catch {
+namespace Matchers {
+    namespace Impl {
+
+        template<typename ArgT> struct MatchAllOf;
+        template<typename ArgT> struct MatchAnyOf;
+        template<typename ArgT> struct MatchNotOf;
+
+        class MatcherUntypedBase {
+        public:
+            MatcherUntypedBase() = default;
+            MatcherUntypedBase ( MatcherUntypedBase const& ) = default;
+            MatcherUntypedBase& operator = ( MatcherUntypedBase const& ) = delete;
+            std::string toString() const;
+
+        protected:
+            virtual ~MatcherUntypedBase();
+            virtual std::string describe() const = 0;
+            mutable std::string m_cachedToString;
+        };
+
+#ifdef __clang__
+#    pragma clang diagnostic push
+#    pragma clang diagnostic ignored "-Wnon-virtual-dtor"
+#endif
+
+        template<typename ObjectT>
+        struct MatcherMethod {
+            virtual bool match( ObjectT const& arg ) const = 0;
+        };
+
+#if defined(__OBJC__)
+        // Hack to fix Catch GH issue #1661. Could use id for generic Object support.
+        // use of const for Object pointers is very uncommon and under ARC it causes some kind of signature mismatch that breaks compilation
+        template<>
+        struct MatcherMethod<NSString*> {
+            virtual bool match( NSString* arg ) const = 0;
+        };
+#endif
+
+#ifdef __clang__
+#    pragma clang diagnostic pop
+#endif
+
+        template<typename T>
+        struct MatcherBase : MatcherUntypedBase, MatcherMethod<T> {
+
+            MatchAllOf<T> operator && ( MatcherBase const& other ) const;
+            MatchAnyOf<T> operator || ( MatcherBase const& other ) const;
+            MatchNotOf<T> operator ! () const;
+        };
+
+        template<typename ArgT>
+        struct MatchAllOf : MatcherBase<ArgT> {
+            bool match( ArgT const& arg ) const override {
+                for( auto matcher : m_matchers ) {
+                    if (!matcher->match(arg))
+                        return false;
+                }
+                return true;
+            }
+            std::string describe() const override {
+                std::string description;
+                description.reserve( 4 + m_matchers.size()*32 );
+                description += "( ";
+                bool first = true;
+                for( auto matcher : m_matchers ) {
+                    if( first )
+                        first = false;
+                    else
+                        description += " and ";
+                    description += matcher->toString();
+                }
+                description += " )";
+                return description;
+            }
+
+            MatchAllOf<ArgT> operator && ( MatcherBase<ArgT> const& other ) {
+                auto copy(*this);
+                copy.m_matchers.push_back( &other );
+                return copy;
+            }
+
+            std::vector<MatcherBase<ArgT> const*> m_matchers;
+        };
+        template<typename ArgT>
+        struct MatchAnyOf : MatcherBase<ArgT> {
+
+            bool match( ArgT const& arg ) const override {
+                for( auto matcher : m_matchers ) {
+                    if (matcher->match(arg))
+                        return true;
+                }
+                return false;
+            }
+            std::string describe() const override {
+                std::string description;
+                description.reserve( 4 + m_matchers.size()*32 );
+                description += "( ";
+                bool first = true;
+                for( auto matcher : m_matchers ) {
+                    if( first )
+                        first = false;
+                    else
+                        description += " or ";
+                    description += matcher->toString();
+                }
+                description += " )";
+                return description;
+            }
+
+            MatchAnyOf<ArgT> operator || ( MatcherBase<ArgT> const& other ) {
+                auto copy(*this);
+                copy.m_matchers.push_back( &other );
+                return copy;
+            }
+
+            std::vector<MatcherBase<ArgT> const*> m_matchers;
+        };
+
+        template<typename ArgT>
+        struct MatchNotOf : MatcherBase<ArgT> {
+
+            MatchNotOf( MatcherBase<ArgT> const& underlyingMatcher ) : m_underlyingMatcher( underlyingMatcher ) {}
+
+            bool match( ArgT const& arg ) const override {
+                return !m_underlyingMatcher.match( arg );
+            }
+
+            std::string describe() const override {
+                return "not " + m_underlyingMatcher.toString();
+            }
+            MatcherBase<ArgT> const& m_underlyingMatcher;
+        };
+
+        template<typename T>
+        MatchAllOf<T> MatcherBase<T>::operator && ( MatcherBase const& other ) const {
+            return MatchAllOf<T>() && *this && other;
+        }
+        template<typename T>
+        MatchAnyOf<T> MatcherBase<T>::operator || ( MatcherBase const& other ) const {
+            return MatchAnyOf<T>() || *this || other;
+        }
+        template<typename T>
+        MatchNotOf<T> MatcherBase<T>::operator ! () const {
+            return MatchNotOf<T>( *this );
+        }
+
+    } // namespace Impl
+
+} // namespace Matchers
+
+using namespace Matchers;
+using Matchers::Impl::MatcherBase;
+
+} // namespace Catch
+
+// end catch_matchers.h
+// start catch_matchers_exception.hpp
+
+namespace Catch {
+namespace Matchers {
+namespace Exception {
+
+class ExceptionMessageMatcher : public MatcherBase<std::exception> {
+    std::string m_message;
+public:
+
+    ExceptionMessageMatcher(std::string const& message):
+        m_message(message)
+    {}
+
+    bool match(std::exception const& ex) const override;
+
+    std::string describe() const override;
+};
+
+} // namespace Exception
+
+Exception::ExceptionMessageMatcher Message(std::string const& message);
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_exception.hpp
+// start catch_matchers_floating.h
+
+namespace Catch {
+namespace Matchers {
+
+    namespace Floating {
+
+        enum class FloatingPointKind : uint8_t;
+
+        struct WithinAbsMatcher : MatcherBase<double> {
+            WithinAbsMatcher(double target, double margin);
+            bool match(double const& matchee) const override;
+            std::string describe() const override;
+        private:
+            double m_target;
+            double m_margin;
+        };
+
+        struct WithinUlpsMatcher : MatcherBase<double> {
+            WithinUlpsMatcher(double target, uint64_t ulps, FloatingPointKind baseType);
+            bool match(double const& matchee) const override;
+            std::string describe() const override;
+        private:
+            double m_target;
+            uint64_t m_ulps;
+            FloatingPointKind m_type;
+        };
+
+        // Given IEEE-754 format for floats and doubles, we can assume
+        // that float -> double promotion is lossless. Given this, we can
+        // assume that if we do the standard relative comparison of
+        // |lhs - rhs| <= epsilon * max(fabs(lhs), fabs(rhs)), then we get
+        // the same result if we do this for floats, as if we do this for
+        // doubles that were promoted from floats.
+        struct WithinRelMatcher : MatcherBase<double> {
+            WithinRelMatcher(double target, double epsilon);
+            bool match(double const& matchee) const override;
+            std::string describe() const override;
+        private:
+            double m_target;
+            double m_epsilon;
+        };
+
+    } // namespace Floating
+
+    // The following functions create the actual matcher objects.
+    // This allows the types to be inferred
+    Floating::WithinUlpsMatcher WithinULP(double target, uint64_t maxUlpDiff);
+    Floating::WithinUlpsMatcher WithinULP(float target, uint64_t maxUlpDiff);
+    Floating::WithinAbsMatcher WithinAbs(double target, double margin);
+    Floating::WithinRelMatcher WithinRel(double target, double eps);
+    // defaults epsilon to 100*numeric_limits<double>::epsilon()
+    Floating::WithinRelMatcher WithinRel(double target);
+    Floating::WithinRelMatcher WithinRel(float target, float eps);
+    // defaults epsilon to 100*numeric_limits<float>::epsilon()
+    Floating::WithinRelMatcher WithinRel(float target);
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_floating.h
+// start catch_matchers_generic.hpp
+
+#include <functional>
+#include <string>
+
+namespace Catch {
+namespace Matchers {
+namespace Generic {
+
+namespace Detail {
+    std::string finalizeDescription(const std::string& desc);
+}
+
+template <typename T>
+class PredicateMatcher : public MatcherBase<T> {
+    std::function<bool(T const&)> m_predicate;
+    std::string m_description;
+public:
+
+    PredicateMatcher(std::function<bool(T const&)> const& elem, std::string const& descr)
+        :m_predicate(std::move(elem)),
+        m_description(Detail::finalizeDescription(descr))
+    {}
+
+    bool match( T const& item ) const override {
+        return m_predicate(item);
+    }
+
+    std::string describe() const override {
+        return m_description;
+    }
+};
+
+} // namespace Generic
+
+    // The following functions create the actual matcher objects.
+    // The user has to explicitly specify type to the function, because
+    // inferring std::function<bool(T const&)> is hard (but possible) and
+    // requires a lot of TMP.
+    template<typename T>
+    Generic::PredicateMatcher<T> Predicate(std::function<bool(T const&)> const& predicate, std::string const& description = "") {
+        return Generic::PredicateMatcher<T>(predicate, description);
+    }
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_generic.hpp
+// start catch_matchers_string.h
+
+#include <string>
+
+namespace Catch {
+namespace Matchers {
+
+    namespace StdString {
+
+        struct CasedString
+        {
+            CasedString( std::string const& str, CaseSensitive::Choice caseSensitivity );
+            std::string adjustString( std::string const& str ) const;
+            std::string caseSensitivitySuffix() const;
+
+            CaseSensitive::Choice m_caseSensitivity;
+            std::string m_str;
+        };
+
+        struct StringMatcherBase : MatcherBase<std::string> {
+            StringMatcherBase( std::string const& operation, CasedString const& comparator );
+            std::string describe() const override;
+
+            CasedString m_comparator;
+            std::string m_operation;
+        };
+
+        struct EqualsMatcher : StringMatcherBase {
+            EqualsMatcher( CasedString const& comparator );
+            bool match( std::string const& source ) const override;
+        };
+        struct ContainsMatcher : StringMatcherBase {
+            ContainsMatcher( CasedString const& comparator );
+            bool match( std::string const& source ) const override;
+        };
+        struct StartsWithMatcher : StringMatcherBase {
+            StartsWithMatcher( CasedString const& comparator );
+            bool match( std::string const& source ) const override;
+        };
+        struct EndsWithMatcher : StringMatcherBase {
+            EndsWithMatcher( CasedString const& comparator );
+            bool match( std::string const& source ) const override;
+        };
+
+        struct RegexMatcher : MatcherBase<std::string> {
+            RegexMatcher( std::string regex, CaseSensitive::Choice caseSensitivity );
+            bool match( std::string const& matchee ) const override;
+            std::string describe() const override;
+
+        private:
+            std::string m_regex;
+            CaseSensitive::Choice m_caseSensitivity;
+        };
+
+    } // namespace StdString
+
+    // The following functions create the actual matcher objects.
+    // This allows the types to be inferred
+
+    StdString::EqualsMatcher Equals( std::string const& str, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+    StdString::ContainsMatcher Contains( std::string const& str, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+    StdString::EndsWithMatcher EndsWith( std::string const& str, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+    StdString::StartsWithMatcher StartsWith( std::string const& str, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+    StdString::RegexMatcher Matches( std::string const& regex, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_string.h
+// start catch_matchers_vector.h
+
+#include <algorithm>
+
+namespace Catch {
+namespace Matchers {
+
+    namespace Vector {
+        template<typename T>
+        struct ContainsElementMatcher : MatcherBase<std::vector<T>> {
+
+            ContainsElementMatcher(T const &comparator) : m_comparator( comparator) {}
+
+            bool match(std::vector<T> const &v) const override {
+                for (auto const& el : v) {
+                    if (el == m_comparator) {
+                        return true;
+                    }
+                }
+                return false;
+            }
+
+            std::string describe() const override {
+                return "Contains: " + ::Catch::Detail::stringify( m_comparator );
+            }
+
+            T const& m_comparator;
+        };
+
+        template<typename T>
+        struct ContainsMatcher : MatcherBase<std::vector<T>> {
+
+            ContainsMatcher(std::vector<T> const &comparator) : m_comparator( comparator ) {}
+
+            bool match(std::vector<T> const &v) const override {
+                // !TBD: see note in EqualsMatcher
+                if (m_comparator.size() > v.size())
+                    return false;
+                for (auto const& comparator : m_comparator) {
+                    auto present = false;
+                    for (const auto& el : v) {
+                        if (el == comparator) {
+                            present = true;
+                            break;
+                        }
+                    }
+                    if (!present) {
+                        return false;
+                    }
+                }
+                return true;
+            }
+            std::string describe() const override {
+                return "Contains: " + ::Catch::Detail::stringify( m_comparator );
+            }
+
+            std::vector<T> const& m_comparator;
+        };
+
+        template<typename T>
+        struct EqualsMatcher : MatcherBase<std::vector<T>> {
+
+            EqualsMatcher(std::vector<T> const &comparator) : m_comparator( comparator ) {}
+
+            bool match(std::vector<T> const &v) const override {
+                // !TBD: This currently works if all elements can be compared using !=
+                // - a more general approach would be via a compare template that defaults
+                // to using !=. but could be specialised for, e.g. std::vector<T> etc
+                // - then just call that directly
+                if (m_comparator.size() != v.size())
+                    return false;
+                for (std::size_t i = 0; i < v.size(); ++i)
+                    if (m_comparator[i] != v[i])
+                        return false;
+                return true;
+            }
+            std::string describe() const override {
+                return "Equals: " + ::Catch::Detail::stringify( m_comparator );
+            }
+            std::vector<T> const& m_comparator;
+        };
+
+        template<typename T>
+        struct ApproxMatcher : MatcherBase<std::vector<T>> {
+
+            ApproxMatcher(std::vector<T> const& comparator) : m_comparator( comparator ) {}
+
+            bool match(std::vector<T> const &v) const override {
+                if (m_comparator.size() != v.size())
+                    return false;
+                for (std::size_t i = 0; i < v.size(); ++i)
+                    if (m_comparator[i] != approx(v[i]))
+                        return false;
+                return true;
+            }
+            std::string describe() const override {
+                return "is approx: " + ::Catch::Detail::stringify( m_comparator );
+            }
+            template <typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+            ApproxMatcher& epsilon( T const& newEpsilon ) {
+                approx.epsilon(newEpsilon);
+                return *this;
+            }
+            template <typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+            ApproxMatcher& margin( T const& newMargin ) {
+                approx.margin(newMargin);
+                return *this;
+            }
+            template <typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+            ApproxMatcher& scale( T const& newScale ) {
+                approx.scale(newScale);
+                return *this;
+            }
+
+            std::vector<T> const& m_comparator;
+            mutable Catch::Detail::Approx approx = Catch::Detail::Approx::custom();
+        };
+
+        template<typename T>
+        struct UnorderedEqualsMatcher : MatcherBase<std::vector<T>> {
+            UnorderedEqualsMatcher(std::vector<T> const& target) : m_target(target) {}
+            bool match(std::vector<T> const& vec) const override {
+                // Note: This is a reimplementation of std::is_permutation,
+                //       because I don't want to include <algorithm> inside the common path
+                if (m_target.size() != vec.size()) {
+                    return false;
+                }
+                return std::is_permutation(m_target.begin(), m_target.end(), vec.begin());
+            }
+
+            std::string describe() const override {
+                return "UnorderedEquals: " + ::Catch::Detail::stringify(m_target);
+            }
+        private:
+            std::vector<T> const& m_target;
+        };
+
+    } // namespace Vector
+
+    // The following functions create the actual matcher objects.
+    // This allows the types to be inferred
+
+    template<typename T>
+    Vector::ContainsMatcher<T> Contains( std::vector<T> const& comparator ) {
+        return Vector::ContainsMatcher<T>( comparator );
+    }
+
+    template<typename T>
+    Vector::ContainsElementMatcher<T> VectorContains( T const& comparator ) {
+        return Vector::ContainsElementMatcher<T>( comparator );
+    }
+
+    template<typename T>
+    Vector::EqualsMatcher<T> Equals( std::vector<T> const& comparator ) {
+        return Vector::EqualsMatcher<T>( comparator );
+    }
+
+    template<typename T>
+    Vector::ApproxMatcher<T> Approx( std::vector<T> const& comparator ) {
+        return Vector::ApproxMatcher<T>( comparator );
+    }
+
+    template<typename T>
+    Vector::UnorderedEqualsMatcher<T> UnorderedEquals(std::vector<T> const& target) {
+        return Vector::UnorderedEqualsMatcher<T>(target);
+    }
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_vector.h
+namespace Catch {
+
+    template<typename ArgT, typename MatcherT>
+    class MatchExpr : public ITransientExpression {
+        ArgT const& m_arg;
+        MatcherT m_matcher;
+        StringRef m_matcherString;
+    public:
+        MatchExpr( ArgT const& arg, MatcherT const& matcher, StringRef const& matcherString )
+        :   ITransientExpression{ true, matcher.match( arg ) },
+            m_arg( arg ),
+            m_matcher( matcher ),
+            m_matcherString( matcherString )
+        {}
+
+        void streamReconstructedExpression( std::ostream &os ) const override {
+            auto matcherAsString = m_matcher.toString();
+            os << Catch::Detail::stringify( m_arg ) << ' ';
+            if( matcherAsString == Detail::unprintableString )
+                os << m_matcherString;
+            else
+                os << matcherAsString;
+        }
+    };
+
+    using StringMatcher = Matchers::Impl::MatcherBase<std::string>;
+
+    void handleExceptionMatchExpr( AssertionHandler& handler, StringMatcher const& matcher, StringRef const& matcherString  );
+
+    template<typename ArgT, typename MatcherT>
+    auto makeMatchExpr( ArgT const& arg, MatcherT const& matcher, StringRef const& matcherString  ) -> MatchExpr<ArgT, MatcherT> {
+        return MatchExpr<ArgT, MatcherT>( arg, matcher, matcherString );
+    }
+
+} // namespace Catch
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CHECK_THAT( macroName, matcher, resultDisposition, arg ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(arg) ", " CATCH_INTERNAL_STRINGIFY(matcher), resultDisposition ); \
+        INTERNAL_CATCH_TRY { \
+            catchAssertionHandler.handleExpr( Catch::makeMatchExpr( arg, matcher, #matcher##_catch_sr ) ); \
+        } INTERNAL_CATCH_CATCH( catchAssertionHandler ) \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_THROWS_MATCHES( macroName, exceptionType, resultDisposition, matcher, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__) ", " CATCH_INTERNAL_STRINGIFY(exceptionType) ", " CATCH_INTERNAL_STRINGIFY(matcher), resultDisposition ); \
+        if( catchAssertionHandler.allowThrows() ) \
+            try { \
+                static_cast<void>(__VA_ARGS__ ); \
+                catchAssertionHandler.handleUnexpectedExceptionNotThrown(); \
+            } \
+            catch( exceptionType const& ex ) { \
+                catchAssertionHandler.handleExpr( Catch::makeMatchExpr( ex, matcher, #matcher##_catch_sr ) ); \
+            } \
+            catch( ... ) { \
+                catchAssertionHandler.handleUnexpectedInflightException(); \
+            } \
+        else \
+            catchAssertionHandler.handleThrowingCallSkipped(); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+// end catch_capture_matchers.h
+#endif
+// start catch_generators.hpp
+
+// start catch_interfaces_generatortracker.h
+
+
+#include <memory>
+
+namespace Catch {
+
+    namespace Generators {
+        class GeneratorUntypedBase {
+        public:
+            GeneratorUntypedBase() = default;
+            virtual ~GeneratorUntypedBase();
+            // Attempts to move the generator to the next element
+             //
+             // Returns true iff the move succeeded (and a valid element
+             // can be retrieved).
+            virtual bool next() = 0;
+        };
+        using GeneratorBasePtr = std::unique_ptr<GeneratorUntypedBase>;
+
+    } // namespace Generators
+
+    struct IGeneratorTracker {
+        virtual ~IGeneratorTracker();
+        virtual auto hasGenerator() const -> bool = 0;
+        virtual auto getGenerator() const -> Generators::GeneratorBasePtr const& = 0;
+        virtual void setGenerator( Generators::GeneratorBasePtr&& generator ) = 0;
+    };
+
+} // namespace Catch
+
+// end catch_interfaces_generatortracker.h
+// start catch_enforce.h
+
+#include <exception>
+
+namespace Catch {
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+    template <typename Ex>
+    [[noreturn]]
+    void throw_exception(Ex const& e) {
+        throw e;
+    }
+#else // ^^ Exceptions are enabled //  Exceptions are disabled vv
+    [[noreturn]]
+    void throw_exception(std::exception const& e);
+#endif
+
+    [[noreturn]]
+    void throw_logic_error(std::string const& msg);
+    [[noreturn]]
+    void throw_domain_error(std::string const& msg);
+    [[noreturn]]
+    void throw_runtime_error(std::string const& msg);
+
+} // namespace Catch;
+
+#define CATCH_MAKE_MSG(...) \
+    (Catch::ReusableStringStream() << __VA_ARGS__).str()
+
+#define CATCH_INTERNAL_ERROR(...) \
+    Catch::throw_logic_error(CATCH_MAKE_MSG( CATCH_INTERNAL_LINEINFO << ": Internal Catch2 error: " << __VA_ARGS__))
+
+#define CATCH_ERROR(...) \
+    Catch::throw_domain_error(CATCH_MAKE_MSG( __VA_ARGS__ ))
+
+#define CATCH_RUNTIME_ERROR(...) \
+    Catch::throw_runtime_error(CATCH_MAKE_MSG( __VA_ARGS__ ))
+
+#define CATCH_ENFORCE( condition, ... ) \
+    do{ if( !(condition) ) CATCH_ERROR( __VA_ARGS__ ); } while(false)
+
+// end catch_enforce.h
+#include <memory>
+#include <vector>
+#include <cassert>
+
+#include <utility>
+#include <exception>
+
+namespace Catch {
+
+class GeneratorException : public std::exception {
+    const char* const m_msg = "";
+
+public:
+    GeneratorException(const char* msg):
+        m_msg(msg)
+    {}
+
+    const char* what() const noexcept override final;
+};
+
+namespace Generators {
+
+    // !TBD move this into its own location?
+    namespace pf{
+        template<typename T, typename... Args>
+        std::unique_ptr<T> make_unique( Args&&... args ) {
+            return std::unique_ptr<T>(new T(std::forward<Args>(args)...));
+        }
+    }
+
+    template<typename T>
+    struct IGenerator : GeneratorUntypedBase {
+        virtual ~IGenerator() = default;
+
+        // Returns the current element of the generator
+        //
+        // \Precondition The generator is either freshly constructed,
+        // or the last call to `next()` returned true
+        virtual T const& get() const = 0;
+        using type = T;
+    };
+
+    template<typename T>
+    class SingleValueGenerator final : public IGenerator<T> {
+        T m_value;
+    public:
+        SingleValueGenerator(T&& value) : m_value(std::move(value)) {}
+
+        T const& get() const override {
+            return m_value;
+        }
+        bool next() override {
+            return false;
+        }
+    };
+
+    template<typename T>
+    class FixedValuesGenerator final : public IGenerator<T> {
+        static_assert(!std::is_same<T, bool>::value,
+            "FixedValuesGenerator does not support bools because of std::vector<bool>"
+            "specialization, use SingleValue Generator instead.");
+        std::vector<T> m_values;
+        size_t m_idx = 0;
+    public:
+        FixedValuesGenerator( std::initializer_list<T> values ) : m_values( values ) {}
+
+        T const& get() const override {
+            return m_values[m_idx];
+        }
+        bool next() override {
+            ++m_idx;
+            return m_idx < m_values.size();
+        }
+    };
+
+    template <typename T>
+    class GeneratorWrapper final {
+        std::unique_ptr<IGenerator<T>> m_generator;
+    public:
+        GeneratorWrapper(std::unique_ptr<IGenerator<T>> generator):
+            m_generator(std::move(generator))
+        {}
+        T const& get() const {
+            return m_generator->get();
+        }
+        bool next() {
+            return m_generator->next();
+        }
+    };
+
+    template <typename T>
+    GeneratorWrapper<T> value(T&& value) {
+        return GeneratorWrapper<T>(pf::make_unique<SingleValueGenerator<T>>(std::forward<T>(value)));
+    }
+    template <typename T>
+    GeneratorWrapper<T> values(std::initializer_list<T> values) {
+        return GeneratorWrapper<T>(pf::make_unique<FixedValuesGenerator<T>>(values));
+    }
+
+    template<typename T>
+    class Generators : public IGenerator<T> {
+        std::vector<GeneratorWrapper<T>> m_generators;
+        size_t m_current = 0;
+
+        void populate(GeneratorWrapper<T>&& generator) {
+            m_generators.emplace_back(std::move(generator));
+        }
+        void populate(T&& val) {
+            m_generators.emplace_back(value(std::forward<T>(val)));
+        }
+        template<typename U>
+        void populate(U&& val) {
+            populate(T(std::forward<U>(val)));
+        }
+        template<typename U, typename... Gs>
+        void populate(U&& valueOrGenerator, Gs &&... moreGenerators) {
+            populate(std::forward<U>(valueOrGenerator));
+            populate(std::forward<Gs>(moreGenerators)...);
+        }
+
+    public:
+        template <typename... Gs>
+        Generators(Gs &&... moreGenerators) {
+            m_generators.reserve(sizeof...(Gs));
+            populate(std::forward<Gs>(moreGenerators)...);
+        }
+
+        T const& get() const override {
+            return m_generators[m_current].get();
+        }
+
+        bool next() override {
+            if (m_current >= m_generators.size()) {
+                return false;
+            }
+            const bool current_status = m_generators[m_current].next();
+            if (!current_status) {
+                ++m_current;
+            }
+            return m_current < m_generators.size();
+        }
+    };
+
+    template<typename... Ts>
+    GeneratorWrapper<std::tuple<Ts...>> table( std::initializer_list<std::tuple<typename std::decay<Ts>::type...>> tuples ) {
+        return values<std::tuple<Ts...>>( tuples );
+    }
+
+    // Tag type to signal that a generator sequence should convert arguments to a specific type
+    template <typename T>
+    struct as {};
+
+    template<typename T, typename... Gs>
+    auto makeGenerators( GeneratorWrapper<T>&& generator, Gs &&... moreGenerators ) -> Generators<T> {
+        return Generators<T>(std::move(generator), std::forward<Gs>(moreGenerators)...);
+    }
+    template<typename T>
+    auto makeGenerators( GeneratorWrapper<T>&& generator ) -> Generators<T> {
+        return Generators<T>(std::move(generator));
+    }
+    template<typename T, typename... Gs>
+    auto makeGenerators( T&& val, Gs &&... moreGenerators ) -> Generators<T> {
+        return makeGenerators( value( std::forward<T>( val ) ), std::forward<Gs>( moreGenerators )... );
+    }
+    template<typename T, typename U, typename... Gs>
+    auto makeGenerators( as<T>, U&& val, Gs &&... moreGenerators ) -> Generators<T> {
+        return makeGenerators( value( T( std::forward<U>( val ) ) ), std::forward<Gs>( moreGenerators )... );
+    }
+
+    auto acquireGeneratorTracker( SourceLineInfo const& lineInfo ) -> IGeneratorTracker&;
+
+    template<typename L>
+    // Note: The type after -> is weird, because VS2015 cannot parse
+    //       the expression used in the typedef inside, when it is in
+    //       return type. Yeah.
+    auto generate( SourceLineInfo const& lineInfo, L const& generatorExpression ) -> decltype(std::declval<decltype(generatorExpression())>().get()) {
+        using UnderlyingType = typename decltype(generatorExpression())::type;
+
+        IGeneratorTracker& tracker = acquireGeneratorTracker( lineInfo );
+        if (!tracker.hasGenerator()) {
+            tracker.setGenerator(pf::make_unique<Generators<UnderlyingType>>(generatorExpression()));
+        }
+
+        auto const& generator = static_cast<IGenerator<UnderlyingType> const&>( *tracker.getGenerator() );
+        return generator.get();
+    }
+
+} // namespace Generators
+} // namespace Catch
+
+#define GENERATE( ... ) \
+    Catch::Generators::generate( CATCH_INTERNAL_LINEINFO, [ ]{ using namespace Catch::Generators; return makeGenerators( __VA_ARGS__ ); } ) //NOLINT(google-build-using-namespace)
+#define GENERATE_COPY( ... ) \
+    Catch::Generators::generate( CATCH_INTERNAL_LINEINFO, [=]{ using namespace Catch::Generators; return makeGenerators( __VA_ARGS__ ); } ) //NOLINT(google-build-using-namespace)
+#define GENERATE_REF( ... ) \
+    Catch::Generators::generate( CATCH_INTERNAL_LINEINFO, [&]{ using namespace Catch::Generators; return makeGenerators( __VA_ARGS__ ); } ) //NOLINT(google-build-using-namespace)
+
+// end catch_generators.hpp
+// start catch_generators_generic.hpp
+
+namespace Catch {
+namespace Generators {
+
+    template <typename T>
+    class TakeGenerator : public IGenerator<T> {
+        GeneratorWrapper<T> m_generator;
+        size_t m_returned = 0;
+        size_t m_target;
+    public:
+        TakeGenerator(size_t target, GeneratorWrapper<T>&& generator):
+            m_generator(std::move(generator)),
+            m_target(target)
+        {
+            assert(target != 0 && "Empty generators are not allowed");
+        }
+        T const& get() const override {
+            return m_generator.get();
+        }
+        bool next() override {
+            ++m_returned;
+            if (m_returned >= m_target) {
+                return false;
+            }
+
+            const auto success = m_generator.next();
+            // If the underlying generator does not contain enough values
+            // then we cut short as well
+            if (!success) {
+                m_returned = m_target;
+            }
+            return success;
+        }
+    };
+
+    template <typename T>
+    GeneratorWrapper<T> take(size_t target, GeneratorWrapper<T>&& generator) {
+        return GeneratorWrapper<T>(pf::make_unique<TakeGenerator<T>>(target, std::move(generator)));
+    }
+
+    template <typename T, typename Predicate>
+    class FilterGenerator : public IGenerator<T> {
+        GeneratorWrapper<T> m_generator;
+        Predicate m_predicate;
+    public:
+        template <typename P = Predicate>
+        FilterGenerator(P&& pred, GeneratorWrapper<T>&& generator):
+            m_generator(std::move(generator)),
+            m_predicate(std::forward<P>(pred))
+        {
+            if (!m_predicate(m_generator.get())) {
+                // It might happen that there are no values that pass the
+                // filter. In that case we throw an exception.
+                auto has_initial_value = next();
+                if (!has_initial_value) {
+                    Catch::throw_exception(GeneratorException("No valid value found in filtered generator"));
+                }
+            }
+        }
+
+        T const& get() const override {
+            return m_generator.get();
+        }
+
+        bool next() override {
+            bool success = m_generator.next();
+            if (!success) {
+                return false;
+            }
+            while (!m_predicate(m_generator.get()) && (success = m_generator.next()) == true);
+            return success;
+        }
+    };
+
+    template <typename T, typename Predicate>
+    GeneratorWrapper<T> filter(Predicate&& pred, GeneratorWrapper<T>&& generator) {
+        return GeneratorWrapper<T>(std::unique_ptr<IGenerator<T>>(pf::make_unique<FilterGenerator<T, Predicate>>(std::forward<Predicate>(pred), std::move(generator))));
+    }
+
+    template <typename T>
+    class RepeatGenerator : public IGenerator<T> {
+        static_assert(!std::is_same<T, bool>::value,
+            "RepeatGenerator currently does not support bools"
+            "because of std::vector<bool> specialization");
+        GeneratorWrapper<T> m_generator;
+        mutable std::vector<T> m_returned;
+        size_t m_target_repeats;
+        size_t m_current_repeat = 0;
+        size_t m_repeat_index = 0;
+    public:
+        RepeatGenerator(size_t repeats, GeneratorWrapper<T>&& generator):
+            m_generator(std::move(generator)),
+            m_target_repeats(repeats)
+        {
+            assert(m_target_repeats > 0 && "Repeat generator must repeat at least once");
+        }
+
+        T const& get() const override {
+            if (m_current_repeat == 0) {
+                m_returned.push_back(m_generator.get());
+                return m_returned.back();
+            }
+            return m_returned[m_repeat_index];
+        }
+
+        bool next() override {
+            // There are 2 basic cases:
+            // 1) We are still reading the generator
+            // 2) We are reading our own cache
+
+            // In the first case, we need to poke the underlying generator.
+            // If it happily moves, we are left in that state, otherwise it is time to start reading from our cache
+            if (m_current_repeat == 0) {
+                const auto success = m_generator.next();
+                if (!success) {
+                    ++m_current_repeat;
+                }
+                return m_current_repeat < m_target_repeats;
+            }
+
+            // In the second case, we need to move indices forward and check that we haven't run up against the end
+            ++m_repeat_index;
+            if (m_repeat_index == m_returned.size()) {
+                m_repeat_index = 0;
+                ++m_current_repeat;
+            }
+            return m_current_repeat < m_target_repeats;
+        }
+    };
+
+    template <typename T>
+    GeneratorWrapper<T> repeat(size_t repeats, GeneratorWrapper<T>&& generator) {
+        return GeneratorWrapper<T>(pf::make_unique<RepeatGenerator<T>>(repeats, std::move(generator)));
+    }
+
+    template <typename T, typename U, typename Func>
+    class MapGenerator : public IGenerator<T> {
+        // TBD: provide static assert for mapping function, for friendly error message
+        GeneratorWrapper<U> m_generator;
+        Func m_function;
+        // To avoid returning dangling reference, we have to save the values
+        T m_cache;
+    public:
+        template <typename F2 = Func>
+        MapGenerator(F2&& function, GeneratorWrapper<U>&& generator) :
+            m_generator(std::move(generator)),
+            m_function(std::forward<F2>(function)),
+            m_cache(m_function(m_generator.get()))
+        {}
+
+        T const& get() const override {
+            return m_cache;
+        }
+        bool next() override {
+            const auto success = m_generator.next();
+            if (success) {
+                m_cache = m_function(m_generator.get());
+            }
+            return success;
+        }
+    };
+
+    template <typename Func, typename U, typename T = FunctionReturnType<Func, U>>
+    GeneratorWrapper<T> map(Func&& function, GeneratorWrapper<U>&& generator) {
+        return GeneratorWrapper<T>(
+            pf::make_unique<MapGenerator<T, U, Func>>(std::forward<Func>(function), std::move(generator))
+        );
+    }
+
+    template <typename T, typename U, typename Func>
+    GeneratorWrapper<T> map(Func&& function, GeneratorWrapper<U>&& generator) {
+        return GeneratorWrapper<T>(
+            pf::make_unique<MapGenerator<T, U, Func>>(std::forward<Func>(function), std::move(generator))
+        );
+    }
+
+    template <typename T>
+    class ChunkGenerator final : public IGenerator<std::vector<T>> {
+        std::vector<T> m_chunk;
+        size_t m_chunk_size;
+        GeneratorWrapper<T> m_generator;
+        bool m_used_up = false;
+    public:
+        ChunkGenerator(size_t size, GeneratorWrapper<T> generator) :
+            m_chunk_size(size), m_generator(std::move(generator))
+        {
+            m_chunk.reserve(m_chunk_size);
+            if (m_chunk_size != 0) {
+                m_chunk.push_back(m_generator.get());
+                for (size_t i = 1; i < m_chunk_size; ++i) {
+                    if (!m_generator.next()) {
+                        Catch::throw_exception(GeneratorException("Not enough values to initialize the first chunk"));
+                    }
+                    m_chunk.push_back(m_generator.get());
+                }
+            }
+        }
+        std::vector<T> const& get() const override {
+            return m_chunk;
+        }
+        bool next() override {
+            m_chunk.clear();
+            for (size_t idx = 0; idx < m_chunk_size; ++idx) {
+                if (!m_generator.next()) {
+                    return false;
+                }
+                m_chunk.push_back(m_generator.get());
+            }
+            return true;
+        }
+    };
+
+    template <typename T>
+    GeneratorWrapper<std::vector<T>> chunk(size_t size, GeneratorWrapper<T>&& generator) {
+        return GeneratorWrapper<std::vector<T>>(
+            pf::make_unique<ChunkGenerator<T>>(size, std::move(generator))
+        );
+    }
+
+} // namespace Generators
+} // namespace Catch
+
+// end catch_generators_generic.hpp
+// start catch_generators_specific.hpp
+
+// start catch_context.h
+
+#include <memory>
+
+namespace Catch {
+
+    struct IResultCapture;
+    struct IRunner;
+    struct IConfig;
+    struct IMutableContext;
+
+    using IConfigPtr = std::shared_ptr<IConfig const>;
+
+    struct IContext
+    {
+        virtual ~IContext();
+
+        virtual IResultCapture* getResultCapture() = 0;
+        virtual IRunner* getRunner() = 0;
+        virtual IConfigPtr const& getConfig() const = 0;
+    };
+
+    struct IMutableContext : IContext
+    {
+        virtual ~IMutableContext();
+        virtual void setResultCapture( IResultCapture* resultCapture ) = 0;
+        virtual void setRunner( IRunner* runner ) = 0;
+        virtual void setConfig( IConfigPtr const& config ) = 0;
+
+    private:
+        static IMutableContext *currentContext;
+        friend IMutableContext& getCurrentMutableContext();
+        friend void cleanUpContext();
+        static void createContext();
+    };
+
+    inline IMutableContext& getCurrentMutableContext()
+    {
+        if( !IMutableContext::currentContext )
+            IMutableContext::createContext();
+        // NOLINTNEXTLINE(clang-analyzer-core.uninitialized.UndefReturn)
+        return *IMutableContext::currentContext;
+    }
+
+    inline IContext& getCurrentContext()
+    {
+        return getCurrentMutableContext();
+    }
+
+    void cleanUpContext();
+
+    class SimplePcg32;
+    SimplePcg32& rng();
+}
+
+// end catch_context.h
+// start catch_interfaces_config.h
+
+// start catch_option.hpp
+
+namespace Catch {
+
+    // An optional type
+    template<typename T>
+    class Option {
+    public:
+        Option() : nullableValue( nullptr ) {}
+        Option( T const& _value )
+        : nullableValue( new( storage ) T( _value ) )
+        {}
+        Option( Option const& _other )
+        : nullableValue( _other ? new( storage ) T( *_other ) : nullptr )
+        {}
+
+        ~Option() {
+            reset();
+        }
+
+        Option& operator= ( Option const& _other ) {
+            if( &_other != this ) {
+                reset();
+                if( _other )
+                    nullableValue = new( storage ) T( *_other );
+            }
+            return *this;
+        }
+        Option& operator = ( T const& _value ) {
+            reset();
+            nullableValue = new( storage ) T( _value );
+            return *this;
+        }
+
+        void reset() {
+            if( nullableValue )
+                nullableValue->~T();
+            nullableValue = nullptr;
+        }
+
+        T& operator*() { return *nullableValue; }
+        T const& operator*() const { return *nullableValue; }
+        T* operator->() { return nullableValue; }
+        const T* operator->() const { return nullableValue; }
+
+        T valueOr( T const& defaultValue ) const {
+            return nullableValue ? *nullableValue : defaultValue;
+        }
+
+        bool some() const { return nullableValue != nullptr; }
+        bool none() const { return nullableValue == nullptr; }
+
+        bool operator !() const { return nullableValue == nullptr; }
+        explicit operator bool() const {
+            return some();
+        }
+
+    private:
+        T *nullableValue;
+        alignas(alignof(T)) char storage[sizeof(T)];
+    };
+
+} // end namespace Catch
+
+// end catch_option.hpp
+#include <chrono>
+#include <iosfwd>
+#include <string>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    enum class Verbosity {
+        Quiet = 0,
+        Normal,
+        High
+    };
+
+    struct WarnAbout { enum What {
+        Nothing = 0x00,
+        NoAssertions = 0x01,
+        NoTests = 0x02
+    }; };
+
+    struct ShowDurations { enum OrNot {
+        DefaultForReporter,
+        Always,
+        Never
+    }; };
+    struct RunTests { enum InWhatOrder {
+        InDeclarationOrder,
+        InLexicographicalOrder,
+        InRandomOrder
+    }; };
+    struct UseColour { enum YesOrNo {
+        Auto,
+        Yes,
+        No
+    }; };
+    struct WaitForKeypress { enum When {
+        Never,
+        BeforeStart = 1,
+        BeforeExit = 2,
+        BeforeStartAndExit = BeforeStart | BeforeExit
+    }; };
+
+    class TestSpec;
+
+    struct IConfig : NonCopyable {
+
+        virtual ~IConfig();
+
+        virtual bool allowThrows() const = 0;
+        virtual std::ostream& stream() const = 0;
+        virtual std::string name() const = 0;
+        virtual bool includeSuccessfulResults() const = 0;
+        virtual bool shouldDebugBreak() const = 0;
+        virtual bool warnAboutMissingAssertions() const = 0;
+        virtual bool warnAboutNoTests() const = 0;
+        virtual int abortAfter() const = 0;
+        virtual bool showInvisibles() const = 0;
+        virtual ShowDurations::OrNot showDurations() const = 0;
+        virtual TestSpec const& testSpec() const = 0;
+        virtual bool hasTestFilters() const = 0;
+        virtual std::vector<std::string> const& getTestsOrTags() const = 0;
+        virtual RunTests::InWhatOrder runOrder() const = 0;
+        virtual unsigned int rngSeed() const = 0;
+        virtual UseColour::YesOrNo useColour() const = 0;
+        virtual std::vector<std::string> const& getSectionsToRun() const = 0;
+        virtual Verbosity verbosity() const = 0;
+
+        virtual bool benchmarkNoAnalysis() const = 0;
+        virtual int benchmarkSamples() const = 0;
+        virtual double benchmarkConfidenceInterval() const = 0;
+        virtual unsigned int benchmarkResamples() const = 0;
+        virtual std::chrono::milliseconds benchmarkWarmupTime() const = 0;
+    };
+
+    using IConfigPtr = std::shared_ptr<IConfig const>;
+}
+
+// end catch_interfaces_config.h
+// start catch_random_number_generator.h
+
+#include <cstdint>
+
+namespace Catch {
+
+    // This is a simple implementation of C++11 Uniform Random Number
+    // Generator. It does not provide all operators, because Catch2
+    // does not use it, but it should behave as expected inside stdlib's
+    // distributions.
+    // The implementation is based on the PCG family (http://pcg-random.org)
+    class SimplePcg32 {
+        using state_type = std::uint64_t;
+    public:
+        using result_type = std::uint32_t;
+        static constexpr result_type (min)() {
+            return 0;
+        }
+        static constexpr result_type (max)() {
+            return static_cast<result_type>(-1);
+        }
+
+        // Provide some default initial state for the default constructor
+        SimplePcg32():SimplePcg32(0xed743cc4U) {}
+
+        explicit SimplePcg32(result_type seed_);
+
+        void seed(result_type seed_);
+        void discard(uint64_t skip);
+
+        result_type operator()();
+
+    private:
+        friend bool operator==(SimplePcg32 const& lhs, SimplePcg32 const& rhs);
+        friend bool operator!=(SimplePcg32 const& lhs, SimplePcg32 const& rhs);
+
+        // In theory we also need operator<< and operator>>
+        // In practice we do not use them, so we will skip them for now
+
+        std::uint64_t m_state;
+        // This part of the state determines which "stream" of the numbers
+        // is chosen -- we take it as a constant for Catch2, so we only
+        // need to deal with seeding the main state.
+        // Picked by reading 8 bytes from `/dev/random` :-)
+        static const std::uint64_t s_inc = (0x13ed0cc53f939476ULL << 1ULL) | 1ULL;
+    };
+
+} // end namespace Catch
+
+// end catch_random_number_generator.h
+#include <random>
+
+namespace Catch {
+namespace Generators {
+
+template <typename Float>
+class RandomFloatingGenerator final : public IGenerator<Float> {
+    Catch::SimplePcg32& m_rng;
+    std::uniform_real_distribution<Float> m_dist;
+    Float m_current_number;
+public:
+
+    RandomFloatingGenerator(Float a, Float b):
+        m_rng(rng()),
+        m_dist(a, b) {
+        static_cast<void>(next());
+    }
+
+    Float const& get() const override {
+        return m_current_number;
+    }
+    bool next() override {
+        m_current_number = m_dist(m_rng);
+        return true;
+    }
+};
+
+template <typename Integer>
+class RandomIntegerGenerator final : public IGenerator<Integer> {
+    Catch::SimplePcg32& m_rng;
+    std::uniform_int_distribution<Integer> m_dist;
+    Integer m_current_number;
+public:
+
+    RandomIntegerGenerator(Integer a, Integer b):
+        m_rng(rng()),
+        m_dist(a, b) {
+        static_cast<void>(next());
+    }
+
+    Integer const& get() const override {
+        return m_current_number;
+    }
+    bool next() override {
+        m_current_number = m_dist(m_rng);
+        return true;
+    }
+};
+
+// TODO: Ideally this would be also constrained against the various char types,
+//       but I don't expect users to run into that in practice.
+template <typename T>
+typename std::enable_if<std::is_integral<T>::value && !std::is_same<T, bool>::value,
+GeneratorWrapper<T>>::type
+random(T a, T b) {
+    return GeneratorWrapper<T>(
+        pf::make_unique<RandomIntegerGenerator<T>>(a, b)
+    );
+}
+
+template <typename T>
+typename std::enable_if<std::is_floating_point<T>::value,
+GeneratorWrapper<T>>::type
+random(T a, T b) {
+    return GeneratorWrapper<T>(
+        pf::make_unique<RandomFloatingGenerator<T>>(a, b)
+    );
+}
+
+template <typename T>
+class RangeGenerator final : public IGenerator<T> {
+    T m_current;
+    T m_end;
+    T m_step;
+    bool m_positive;
+
+public:
+    RangeGenerator(T const& start, T const& end, T const& step):
+        m_current(start),
+        m_end(end),
+        m_step(step),
+        m_positive(m_step > T(0))
+    {
+        assert(m_current != m_end && "Range start and end cannot be equal");
+        assert(m_step != T(0) && "Step size cannot be zero");
+        assert(((m_positive && m_current <= m_end) || (!m_positive && m_current >= m_end)) && "Step moves away from end");
+    }
+
+    RangeGenerator(T const& start, T const& end):
+        RangeGenerator(start, end, (start < end) ? T(1) : T(-1))
+    {}
+
+    T const& get() const override {
+        return m_current;
+    }
+
+    bool next() override {
+        m_current += m_step;
+        return (m_positive) ? (m_current < m_end) : (m_current > m_end);
+    }
+};
+
+template <typename T>
+GeneratorWrapper<T> range(T const& start, T const& end, T const& step) {
+    static_assert(std::is_arithmetic<T>::value && !std::is_same<T, bool>::value, "Type must be numeric");
+    return GeneratorWrapper<T>(pf::make_unique<RangeGenerator<T>>(start, end, step));
+}
+
+template <typename T>
+GeneratorWrapper<T> range(T const& start, T const& end) {
+    static_assert(std::is_integral<T>::value && !std::is_same<T, bool>::value, "Type must be an integer");
+    return GeneratorWrapper<T>(pf::make_unique<RangeGenerator<T>>(start, end));
+}
+
+template <typename T>
+class IteratorGenerator final : public IGenerator<T> {
+    static_assert(!std::is_same<T, bool>::value,
+        "IteratorGenerator currently does not support bools"
+        "because of std::vector<bool> specialization");
+
+    std::vector<T> m_elems;
+    size_t m_current = 0;
+public:
+    template <typename InputIterator, typename InputSentinel>
+    IteratorGenerator(InputIterator first, InputSentinel last):m_elems(first, last) {
+        if (m_elems.empty()) {
+            Catch::throw_exception(GeneratorException("IteratorGenerator received no valid values"));
+        }
+    }
+
+    T const& get() const override {
+        return m_elems[m_current];
+    }
+
+    bool next() override {
+        ++m_current;
+        return m_current != m_elems.size();
+    }
+};
+
+template <typename InputIterator,
+          typename InputSentinel,
+          typename ResultType = typename std::iterator_traits<InputIterator>::value_type>
+GeneratorWrapper<ResultType> from_range(InputIterator from, InputSentinel to) {
+    return GeneratorWrapper<ResultType>(pf::make_unique<IteratorGenerator<ResultType>>(from, to));
+}
+
+template <typename Container,
+          typename ResultType = typename Container::value_type>
+GeneratorWrapper<ResultType> from_range(Container const& cnt) {
+    return GeneratorWrapper<ResultType>(pf::make_unique<IteratorGenerator<ResultType>>(cnt.begin(), cnt.end()));
+}
+
+} // namespace Generators
+} // namespace Catch
+
+// end catch_generators_specific.hpp
+
+// These files are included here so the single_include script doesn't put them
+// in the conditionally compiled sections
+// start catch_test_case_info.h
+
+#include <string>
+#include <vector>
+#include <memory>
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wpadded"
+#endif
+
+namespace Catch {
+
+    struct ITestInvoker;
+
+    struct TestCaseInfo {
+        enum SpecialProperties{
+            None = 0,
+            IsHidden = 1 << 1,
+            ShouldFail = 1 << 2,
+            MayFail = 1 << 3,
+            Throws = 1 << 4,
+            NonPortable = 1 << 5,
+            Benchmark = 1 << 6
+        };
+
+        TestCaseInfo(   std::string const& _name,
+                        std::string const& _className,
+                        std::string const& _description,
+                        std::vector<std::string> const& _tags,
+                        SourceLineInfo const& _lineInfo );
+
+        friend void setTags( TestCaseInfo& testCaseInfo, std::vector<std::string> tags );
+
+        bool isHidden() const;
+        bool throws() const;
+        bool okToFail() const;
+        bool expectedToFail() const;
+
+        std::string tagsAsString() const;
+
+        std::string name;
+        std::string className;
+        std::string description;
+        std::vector<std::string> tags;
+        std::vector<std::string> lcaseTags;
+        SourceLineInfo lineInfo;
+        SpecialProperties properties;
+    };
+
+    class TestCase : public TestCaseInfo {
+    public:
+
+        TestCase( ITestInvoker* testCase, TestCaseInfo&& info );
+
+        TestCase withName( std::string const& _newName ) const;
+
+        void invoke() const;
+
+        TestCaseInfo const& getTestCaseInfo() const;
+
+        bool operator == ( TestCase const& other ) const;
+        bool operator < ( TestCase const& other ) const;
+
+    private:
+        std::shared_ptr<ITestInvoker> test;
+    };
+
+    TestCase makeTestCase(  ITestInvoker* testCase,
+                            std::string const& className,
+                            NameAndTags const& nameAndTags,
+                            SourceLineInfo const& lineInfo );
+}
+
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// end catch_test_case_info.h
+// start catch_interfaces_runner.h
+
+namespace Catch {
+
+    struct IRunner {
+        virtual ~IRunner();
+        virtual bool aborting() const = 0;
+    };
+}
+
+// end catch_interfaces_runner.h
+
+#ifdef __OBJC__
+// start catch_objc.hpp
+
+#import <objc/runtime.h>
+
+#include <string>
+
+// NB. Any general catch headers included here must be included
+// in catch.hpp first to make sure they are included by the single
+// header for non obj-usage
+
+///////////////////////////////////////////////////////////////////////////////
+// This protocol is really only here for (self) documenting purposes, since
+// all its methods are optional.
+@protocol OcFixture
+
+@optional
+
+-(void) setUp;
+-(void) tearDown;
+
+@end
+
+namespace Catch {
+
+    class OcMethod : public ITestInvoker {
+
+    public:
+        OcMethod( Class cls, SEL sel ) : m_cls( cls ), m_sel( sel ) {}
+
+        virtual void invoke() const {
+            id obj = [[m_cls alloc] init];
+
+            performOptionalSelector( obj, @selector(setUp)  );
+            performOptionalSelector( obj, m_sel );
+            performOptionalSelector( obj, @selector(tearDown)  );
+
+            arcSafeRelease( obj );
+        }
+    private:
+        virtual ~OcMethod() {}
+
+        Class m_cls;
+        SEL m_sel;
+    };
+
+    namespace Detail{
+
+        inline std::string getAnnotation(   Class cls,
+                                            std::string const& annotationName,
+                                            std::string const& testCaseName ) {
+            NSString* selStr = [[NSString alloc] initWithFormat:@"Catch_%s_%s", annotationName.c_str(), testCaseName.c_str()];
+            SEL sel = NSSelectorFromString( selStr );
+            arcSafeRelease( selStr );
+            id value = performOptionalSelector( cls, sel );
+            if( value )
+                return [(NSString*)value UTF8String];
+            return "";
+        }
+    }
+
+    inline std::size_t registerTestMethods() {
+        std::size_t noTestMethods = 0;
+        int noClasses = objc_getClassList( nullptr, 0 );
+
+        Class* classes = (CATCH_UNSAFE_UNRETAINED Class *)malloc( sizeof(Class) * noClasses);
+        objc_getClassList( classes, noClasses );
+
+        for( int c = 0; c < noClasses; c++ ) {
+            Class cls = classes[c];
+            {
+                u_int count;
+                Method* methods = class_copyMethodList( cls, &count );
+                for( u_int m = 0; m < count ; m++ ) {
+                    SEL selector = method_getName(methods[m]);
+                    std::string methodName = sel_getName(selector);
+                    if( startsWith( methodName, "Catch_TestCase_" ) ) {
+                        std::string testCaseName = methodName.substr( 15 );
+                        std::string name = Detail::getAnnotation( cls, "Name", testCaseName );
+                        std::string desc = Detail::getAnnotation( cls, "Description", testCaseName );
+                        const char* className = class_getName( cls );
+
+                        getMutableRegistryHub().registerTest( makeTestCase( new OcMethod( cls, selector ), className, NameAndTags( name.c_str(), desc.c_str() ), SourceLineInfo("",0) ) );
+                        noTestMethods++;
+                    }
+                }
+                free(methods);
+            }
+        }
+        return noTestMethods;
+    }
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+
+    namespace Matchers {
+        namespace Impl {
+        namespace NSStringMatchers {
+
+            struct StringHolder : MatcherBase<NSString*>{
+                StringHolder( NSString* substr ) : m_substr( [substr copy] ){}
+                StringHolder( StringHolder const& other ) : m_substr( [other.m_substr copy] ){}
+                StringHolder() {
+                    arcSafeRelease( m_substr );
+                }
+
+                bool match( NSString* str ) const override {
+                    return false;
+                }
+
+                NSString* CATCH_ARC_STRONG m_substr;
+            };
+
+            struct Equals : StringHolder {
+                Equals( NSString* substr ) : StringHolder( substr ){}
+
+                bool match( NSString* str ) const override {
+                    return  (str != nil || m_substr == nil ) &&
+                            [str isEqualToString:m_substr];
+                }
+
+                std::string describe() const override {
+                    return "equals string: " + Catch::Detail::stringify( m_substr );
+                }
+            };
+
+            struct Contains : StringHolder {
+                Contains( NSString* substr ) : StringHolder( substr ){}
+
+                bool match( NSString* str ) const override {
+                    return  (str != nil || m_substr == nil ) &&
+                            [str rangeOfString:m_substr].location != NSNotFound;
+                }
+
+                std::string describe() const override {
+                    return "contains string: " + Catch::Detail::stringify( m_substr );
+                }
+            };
+
+            struct StartsWith : StringHolder {
+                StartsWith( NSString* substr ) : StringHolder( substr ){}
+
+                bool match( NSString* str ) const override {
+                    return  (str != nil || m_substr == nil ) &&
+                            [str rangeOfString:m_substr].location == 0;
+                }
+
+                std::string describe() const override {
+                    return "starts with: " + Catch::Detail::stringify( m_substr );
+                }
+            };
+            struct EndsWith : StringHolder {
+                EndsWith( NSString* substr ) : StringHolder( substr ){}
+
+                bool match( NSString* str ) const override {
+                    return  (str != nil || m_substr == nil ) &&
+                            [str rangeOfString:m_substr].location == [str length] - [m_substr length];
+                }
+
+                std::string describe() const override {
+                    return "ends with: " + Catch::Detail::stringify( m_substr );
+                }
+            };
+
+        } // namespace NSStringMatchers
+        } // namespace Impl
+
+        inline Impl::NSStringMatchers::Equals
+            Equals( NSString* substr ){ return Impl::NSStringMatchers::Equals( substr ); }
+
+        inline Impl::NSStringMatchers::Contains
+            Contains( NSString* substr ){ return Impl::NSStringMatchers::Contains( substr ); }
+
+        inline Impl::NSStringMatchers::StartsWith
+            StartsWith( NSString* substr ){ return Impl::NSStringMatchers::StartsWith( substr ); }
+
+        inline Impl::NSStringMatchers::EndsWith
+            EndsWith( NSString* substr ){ return Impl::NSStringMatchers::EndsWith( substr ); }
+
+    } // namespace Matchers
+
+    using namespace Matchers;
+
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+} // namespace Catch
+
+///////////////////////////////////////////////////////////////////////////////
+#define OC_MAKE_UNIQUE_NAME( root, uniqueSuffix ) root##uniqueSuffix
+#define OC_TEST_CASE2( name, desc, uniqueSuffix ) \
++(NSString*) OC_MAKE_UNIQUE_NAME( Catch_Name_test_, uniqueSuffix ) \
+{ \
+return @ name; \
+} \
++(NSString*) OC_MAKE_UNIQUE_NAME( Catch_Description_test_, uniqueSuffix ) \
+{ \
+return @ desc; \
+} \
+-(void) OC_MAKE_UNIQUE_NAME( Catch_TestCase_test_, uniqueSuffix )
+
+#define OC_TEST_CASE( name, desc ) OC_TEST_CASE2( name, desc, __LINE__ )
+
+// end catch_objc.hpp
+#endif
+
+// Benchmarking needs the externally-facing parts of reporters to work
+#if defined(CATCH_CONFIG_EXTERNAL_INTERFACES) || defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+// start catch_external_interfaces.h
+
+// start catch_reporter_bases.hpp
+
+// start catch_interfaces_reporter.h
+
+// start catch_config.hpp
+
+// start catch_test_spec_parser.h
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wpadded"
+#endif
+
+// start catch_test_spec.h
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wpadded"
+#endif
+
+// start catch_wildcard_pattern.h
+
+namespace Catch
+{
+    class WildcardPattern {
+        enum WildcardPosition {
+            NoWildcard = 0,
+            WildcardAtStart = 1,
+            WildcardAtEnd = 2,
+            WildcardAtBothEnds = WildcardAtStart | WildcardAtEnd
+        };
+
+    public:
+
+        WildcardPattern( std::string const& pattern, CaseSensitive::Choice caseSensitivity );
+        virtual ~WildcardPattern() = default;
+        virtual bool matches( std::string const& str ) const;
+
+    private:
+        std::string normaliseString( std::string const& str ) const;
+        CaseSensitive::Choice m_caseSensitivity;
+        WildcardPosition m_wildcard = NoWildcard;
+        std::string m_pattern;
+    };
+}
+
+// end catch_wildcard_pattern.h
+#include <string>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    struct IConfig;
+
+    class TestSpec {
+        class Pattern {
+        public:
+            explicit Pattern( std::string const& name );
+            virtual ~Pattern();
+            virtual bool matches( TestCaseInfo const& testCase ) const = 0;
+            std::string const& name() const;
+        private:
+            std::string const m_name;
+        };
+        using PatternPtr = std::shared_ptr<Pattern>;
+
+        class NamePattern : public Pattern {
+        public:
+            explicit NamePattern( std::string const& name, std::string const& filterString );
+            bool matches( TestCaseInfo const& testCase ) const override;
+        private:
+            WildcardPattern m_wildcardPattern;
+        };
+
+        class TagPattern : public Pattern {
+        public:
+            explicit TagPattern( std::string const& tag, std::string const& filterString );
+            bool matches( TestCaseInfo const& testCase ) const override;
+        private:
+            std::string m_tag;
+        };
+
+        class ExcludedPattern : public Pattern {
+        public:
+            explicit ExcludedPattern( PatternPtr const& underlyingPattern );
+            bool matches( TestCaseInfo const& testCase ) const override;
+        private:
+            PatternPtr m_underlyingPattern;
+        };
+
+        struct Filter {
+            std::vector<PatternPtr> m_patterns;
+
+            bool matches( TestCaseInfo const& testCase ) const;
+            std::string name() const;
+        };
+
+    public:
+        struct FilterMatch {
+            std::string name;
+            std::vector<TestCase const*> tests;
+        };
+        using Matches = std::vector<FilterMatch>;
+        using vectorStrings = std::vector<std::string>;
+
+        bool hasFilters() const;
+        bool matches( TestCaseInfo const& testCase ) const;
+        Matches matchesByFilter( std::vector<TestCase> const& testCases, IConfig const& config ) const;
+        const vectorStrings & getInvalidArgs() const;
+
+    private:
+        std::vector<Filter> m_filters;
+        std::vector<std::string> m_invalidArgs;
+        friend class TestSpecParser;
+    };
+}
+
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// end catch_test_spec.h
+// start catch_interfaces_tag_alias_registry.h
+
+#include <string>
+
+namespace Catch {
+
+    struct TagAlias;
+
+    struct ITagAliasRegistry {
+        virtual ~ITagAliasRegistry();
+        // Nullptr if not present
+        virtual TagAlias const* find( std::string const& alias ) const = 0;
+        virtual std::string expandAliases( std::string const& unexpandedTestSpec ) const = 0;
+
+        static ITagAliasRegistry const& get();
+    };
+
+} // end namespace Catch
+
+// end catch_interfaces_tag_alias_registry.h
+namespace Catch {
+
+    class TestSpecParser {
+        enum Mode{ None, Name, QuotedName, Tag, EscapedName };
+        Mode m_mode = None;
+        Mode lastMode = None;
+        bool m_exclusion = false;
+        std::size_t m_pos = 0;
+        std::size_t m_realPatternPos = 0;
+        std::string m_arg;
+        std::string m_substring;
+        std::string m_patternName;
+        std::vector<std::size_t> m_escapeChars;
+        TestSpec::Filter m_currentFilter;
+        TestSpec m_testSpec;
+        ITagAliasRegistry const* m_tagAliases = nullptr;
+
+    public:
+        TestSpecParser( ITagAliasRegistry const& tagAliases );
+
+        TestSpecParser& parse( std::string const& arg );
+        TestSpec testSpec();
+
+    private:
+        bool visitChar( char c );
+        void startNewMode( Mode mode );
+        bool processNoneChar( char c );
+        void processNameChar( char c );
+        bool processOtherChar( char c );
+        void endMode();
+        void escape();
+        bool isControlChar( char c ) const;
+        void saveLastMode();
+        void revertBackToLastMode();
+        void addFilter();
+        bool separate();
+
+        // Handles common preprocessing of the pattern for name/tag patterns
+        std::string preprocessPattern();
+        // Adds the current pattern as a test name
+        void addNamePattern();
+        // Adds the current pattern as a tag
+        void addTagPattern();
+
+        inline void addCharToPattern(char c) {
+            m_substring += c;
+            m_patternName += c;
+            m_realPatternPos++;
+        }
+
+    };
+    TestSpec parseTestSpec( std::string const& arg );
+
+} // namespace Catch
+
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// end catch_test_spec_parser.h
+// Libstdc++ doesn't like incomplete classes for unique_ptr
+
+#include <memory>
+#include <vector>
+#include <string>
+
+#ifndef CATCH_CONFIG_CONSOLE_WIDTH
+#define CATCH_CONFIG_CONSOLE_WIDTH 80
+#endif
+
+namespace Catch {
+
+    struct IStream;
+
+    struct ConfigData {
+        bool listTests = false;
+        bool listTags = false;
+        bool listReporters = false;
+        bool listTestNamesOnly = false;
+
+        bool showSuccessfulTests = false;
+        bool shouldDebugBreak = false;
+        bool noThrow = false;
+        bool showHelp = false;
+        bool showInvisibles = false;
+        bool filenamesAsTags = false;
+        bool libIdentify = false;
+
+        int abortAfter = -1;
+        unsigned int rngSeed = 0;
+
+        bool benchmarkNoAnalysis = false;
+        unsigned int benchmarkSamples = 100;
+        double benchmarkConfidenceInterval = 0.95;
+        unsigned int benchmarkResamples = 100000;
+        std::chrono::milliseconds::rep benchmarkWarmupTime = 100;
+
+        Verbosity verbosity = Verbosity::Normal;
+        WarnAbout::What warnings = WarnAbout::Nothing;
+        ShowDurations::OrNot showDurations = ShowDurations::DefaultForReporter;
+        RunTests::InWhatOrder runOrder = RunTests::InDeclarationOrder;
+        UseColour::YesOrNo useColour = UseColour::Auto;
+        WaitForKeypress::When waitForKeypress = WaitForKeypress::Never;
+
+        std::string outputFilename;
+        std::string name;
+        std::string processName;
+#ifndef CATCH_CONFIG_DEFAULT_REPORTER
+#define CATCH_CONFIG_DEFAULT_REPORTER "console"
+#endif
+        std::string reporterName = CATCH_CONFIG_DEFAULT_REPORTER;
+#undef CATCH_CONFIG_DEFAULT_REPORTER
+
+        std::vector<std::string> testsOrTags;
+        std::vector<std::string> sectionsToRun;
+    };
+
+    class Config : public IConfig {
+    public:
+
+        Config() = default;
+        Config( ConfigData const& data );
+        virtual ~Config() = default;
+
+        std::string const& getFilename() const;
+
+        bool listTests() const;
+        bool listTestNamesOnly() const;
+        bool listTags() const;
+        bool listReporters() const;
+
+        std::string getProcessName() const;
+        std::string const& getReporterName() const;
+
+        std::vector<std::string> const& getTestsOrTags() const override;
+        std::vector<std::string> const& getSectionsToRun() const override;
+
+        TestSpec const& testSpec() const override;
+        bool hasTestFilters() const override;
+
+        bool showHelp() const;
+
+        // IConfig interface
+        bool allowThrows() const override;
+        std::ostream& stream() const override;
+        std::string name() const override;
+        bool includeSuccessfulResults() const override;
+        bool warnAboutMissingAssertions() const override;
+        bool warnAboutNoTests() const override;
+        ShowDurations::OrNot showDurations() const override;
+        RunTests::InWhatOrder runOrder() const override;
+        unsigned int rngSeed() const override;
+        UseColour::YesOrNo useColour() const override;
+        bool shouldDebugBreak() const override;
+        int abortAfter() const override;
+        bool showInvisibles() const override;
+        Verbosity verbosity() const override;
+        bool benchmarkNoAnalysis() const override;
+        int benchmarkSamples() const override;
+        double benchmarkConfidenceInterval() const override;
+        unsigned int benchmarkResamples() const override;
+        std::chrono::milliseconds benchmarkWarmupTime() const override;
+
+    private:
+
+        IStream const* openStream();
+        ConfigData m_data;
+
+        std::unique_ptr<IStream const> m_stream;
+        TestSpec m_testSpec;
+        bool m_hasTestFilters = false;
+    };
+
+} // end namespace Catch
+
+// end catch_config.hpp
+// start catch_assertionresult.h
+
+#include <string>
+
+namespace Catch {
+
+    struct AssertionResultData
+    {
+        AssertionResultData() = delete;
+
+        AssertionResultData( ResultWas::OfType _resultType, LazyExpression const& _lazyExpression );
+
+        std::string message;
+        mutable std::string reconstructedExpression;
+        LazyExpression lazyExpression;
+        ResultWas::OfType resultType;
+
+        std::string reconstructExpression() const;
+    };
+
+    class AssertionResult {
+    public:
+        AssertionResult() = delete;
+        AssertionResult( AssertionInfo const& info, AssertionResultData const& data );
+
+        bool isOk() const;
+        bool succeeded() const;
+        ResultWas::OfType getResultType() const;
+        bool hasExpression() const;
+        bool hasMessage() const;
+        std::string getExpression() const;
+        std::string getExpressionInMacro() const;
+        bool hasExpandedExpression() const;
+        std::string getExpandedExpression() const;
+        std::string getMessage() const;
+        SourceLineInfo getSourceInfo() const;
+        StringRef getTestMacroName() const;
+
+    //protected:
+        AssertionInfo m_info;
+        AssertionResultData m_resultData;
+    };
+
+} // end namespace Catch
+
+// end catch_assertionresult.h
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+// start catch_estimate.hpp
+
+ // Statistics estimates
+
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration>
+        struct Estimate {
+            Duration point;
+            Duration lower_bound;
+            Duration upper_bound;
+            double confidence_interval;
+
+            template <typename Duration2>
+            operator Estimate<Duration2>() const {
+                return { point, lower_bound, upper_bound, confidence_interval };
+            }
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_estimate.hpp
+// start catch_outlier_classification.hpp
+
+// Outlier information
+
+namespace Catch {
+    namespace Benchmark {
+        struct OutlierClassification {
+            int samples_seen = 0;
+            int low_severe = 0;     // more than 3 times IQR below Q1
+            int low_mild = 0;       // 1.5 to 3 times IQR below Q1
+            int high_mild = 0;      // 1.5 to 3 times IQR above Q3
+            int high_severe = 0;    // more than 3 times IQR above Q3
+
+            int total() const {
+                return low_severe + low_mild + high_mild + high_severe;
+            }
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_outlier_classification.hpp
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+#include <string>
+#include <iosfwd>
+#include <map>
+#include <set>
+#include <memory>
+#include <algorithm>
+
+namespace Catch {
+
+    struct ReporterConfig {
+        explicit ReporterConfig( IConfigPtr const& _fullConfig );
+
+        ReporterConfig( IConfigPtr const& _fullConfig, std::ostream& _stream );
+
+        std::ostream& stream() const;
+        IConfigPtr fullConfig() const;
+
+    private:
+        std::ostream* m_stream;
+        IConfigPtr m_fullConfig;
+    };
+
+    struct ReporterPreferences {
+        bool shouldRedirectStdOut = false;
+        bool shouldReportAllAssertions = false;
+    };
+
+    template<typename T>
+    struct LazyStat : Option<T> {
+        LazyStat& operator=( T const& _value ) {
+            Option<T>::operator=( _value );
+            used = false;
+            return *this;
+        }
+        void reset() {
+            Option<T>::reset();
+            used = false;
+        }
+        bool used = false;
+    };
+
+    struct TestRunInfo {
+        TestRunInfo( std::string const& _name );
+        std::string name;
+    };
+    struct GroupInfo {
+        GroupInfo(  std::string const& _name,
+                    std::size_t _groupIndex,
+                    std::size_t _groupsCount );
+
+        std::string name;
+        std::size_t groupIndex;
+        std::size_t groupsCounts;
+    };
+
+    struct AssertionStats {
+        AssertionStats( AssertionResult const& _assertionResult,
+                        std::vector<MessageInfo> const& _infoMessages,
+                        Totals const& _totals );
+
+        AssertionStats( AssertionStats const& )              = default;
+        AssertionStats( AssertionStats && )                  = default;
+        AssertionStats& operator = ( AssertionStats const& ) = delete;
+        AssertionStats& operator = ( AssertionStats && )     = delete;
+        virtual ~AssertionStats();
+
+        AssertionResult assertionResult;
+        std::vector<MessageInfo> infoMessages;
+        Totals totals;
+    };
+
+    struct SectionStats {
+        SectionStats(   SectionInfo const& _sectionInfo,
+                        Counts const& _assertions,
+                        double _durationInSeconds,
+                        bool _missingAssertions );
+        SectionStats( SectionStats const& )              = default;
+        SectionStats( SectionStats && )                  = default;
+        SectionStats& operator = ( SectionStats const& ) = default;
+        SectionStats& operator = ( SectionStats && )     = default;
+        virtual ~SectionStats();
+
+        SectionInfo sectionInfo;
+        Counts assertions;
+        double durationInSeconds;
+        bool missingAssertions;
+    };
+
+    struct TestCaseStats {
+        TestCaseStats(  TestCaseInfo const& _testInfo,
+                        Totals const& _totals,
+                        std::string const& _stdOut,
+                        std::string const& _stdErr,
+                        bool _aborting );
+
+        TestCaseStats( TestCaseStats const& )              = default;
+        TestCaseStats( TestCaseStats && )                  = default;
+        TestCaseStats& operator = ( TestCaseStats const& ) = default;
+        TestCaseStats& operator = ( TestCaseStats && )     = default;
+        virtual ~TestCaseStats();
+
+        TestCaseInfo testInfo;
+        Totals totals;
+        std::string stdOut;
+        std::string stdErr;
+        bool aborting;
+    };
+
+    struct TestGroupStats {
+        TestGroupStats( GroupInfo const& _groupInfo,
+                        Totals const& _totals,
+                        bool _aborting );
+        TestGroupStats( GroupInfo const& _groupInfo );
+
+        TestGroupStats( TestGroupStats const& )              = default;
+        TestGroupStats( TestGroupStats && )                  = default;
+        TestGroupStats& operator = ( TestGroupStats const& ) = default;
+        TestGroupStats& operator = ( TestGroupStats && )     = default;
+        virtual ~TestGroupStats();
+
+        GroupInfo groupInfo;
+        Totals totals;
+        bool aborting;
+    };
+
+    struct TestRunStats {
+        TestRunStats(   TestRunInfo const& _runInfo,
+                        Totals const& _totals,
+                        bool _aborting );
+
+        TestRunStats( TestRunStats const& )              = default;
+        TestRunStats( TestRunStats && )                  = default;
+        TestRunStats& operator = ( TestRunStats const& ) = default;
+        TestRunStats& operator = ( TestRunStats && )     = default;
+        virtual ~TestRunStats();
+
+        TestRunInfo runInfo;
+        Totals totals;
+        bool aborting;
+    };
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    struct BenchmarkInfo {
+        std::string name;
+        double estimatedDuration;
+        int iterations;
+        int samples;
+        unsigned int resamples;
+        double clockResolution;
+        double clockCost;
+    };
+
+    template <class Duration>
+    struct BenchmarkStats {
+        BenchmarkInfo info;
+
+        std::vector<Duration> samples;
+        Benchmark::Estimate<Duration> mean;
+        Benchmark::Estimate<Duration> standardDeviation;
+        Benchmark::OutlierClassification outliers;
+        double outlierVariance;
+
+        template <typename Duration2>
+        operator BenchmarkStats<Duration2>() const {
+            std::vector<Duration2> samples2;
+            samples2.reserve(samples.size());
+            std::transform(samples.begin(), samples.end(), std::back_inserter(samples2), [](Duration d) { return Duration2(d); });
+            return {
+                info,
+                std::move(samples2),
+                mean,
+                standardDeviation,
+                outliers,
+                outlierVariance,
+            };
+        }
+    };
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    struct IStreamingReporter {
+        virtual ~IStreamingReporter() = default;
+
+        // Implementing class must also provide the following static methods:
+        // static std::string getDescription();
+        // static std::set<Verbosity> getSupportedVerbosities()
+
+        virtual ReporterPreferences getPreferences() const = 0;
+
+        virtual void noMatchingTestCases( std::string const& spec ) = 0;
+
+        virtual void reportInvalidArguments(std::string const&) {}
+
+        virtual void testRunStarting( TestRunInfo const& testRunInfo ) = 0;
+        virtual void testGroupStarting( GroupInfo const& groupInfo ) = 0;
+
+        virtual void testCaseStarting( TestCaseInfo const& testInfo ) = 0;
+        virtual void sectionStarting( SectionInfo const& sectionInfo ) = 0;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        virtual void benchmarkPreparing( std::string const& ) {}
+        virtual void benchmarkStarting( BenchmarkInfo const& ) {}
+        virtual void benchmarkEnded( BenchmarkStats<> const& ) {}
+        virtual void benchmarkFailed( std::string const& ) {}
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        virtual void assertionStarting( AssertionInfo const& assertionInfo ) = 0;
+
+        // The return value indicates if the messages buffer should be cleared:
+        virtual bool assertionEnded( AssertionStats const& assertionStats ) = 0;
+
+        virtual void sectionEnded( SectionStats const& sectionStats ) = 0;
+        virtual void testCaseEnded( TestCaseStats const& testCaseStats ) = 0;
+        virtual void testGroupEnded( TestGroupStats const& testGroupStats ) = 0;
+        virtual void testRunEnded( TestRunStats const& testRunStats ) = 0;
+
+        virtual void skipTest( TestCaseInfo const& testInfo ) = 0;
+
+        // Default empty implementation provided
+        virtual void fatalErrorEncountered( StringRef name );
+
+        virtual bool isMulti() const;
+    };
+    using IStreamingReporterPtr = std::unique_ptr<IStreamingReporter>;
+
+    struct IReporterFactory {
+        virtual ~IReporterFactory();
+        virtual IStreamingReporterPtr create( ReporterConfig const& config ) const = 0;
+        virtual std::string getDescription() const = 0;
+    };
+    using IReporterFactoryPtr = std::shared_ptr<IReporterFactory>;
+
+    struct IReporterRegistry {
+        using FactoryMap = std::map<std::string, IReporterFactoryPtr>;
+        using Listeners = std::vector<IReporterFactoryPtr>;
+
+        virtual ~IReporterRegistry();
+        virtual IStreamingReporterPtr create( std::string const& name, IConfigPtr const& config ) const = 0;
+        virtual FactoryMap const& getFactories() const = 0;
+        virtual Listeners const& getListeners() const = 0;
+    };
+
+} // end namespace Catch
+
+// end catch_interfaces_reporter.h
+#include <algorithm>
+#include <cstring>
+#include <cfloat>
+#include <cstdio>
+#include <cassert>
+#include <memory>
+#include <ostream>
+
+namespace Catch {
+    void prepareExpandedExpression(AssertionResult& result);
+
+    // Returns double formatted as %.3f (format expected on output)
+    std::string getFormattedDuration( double duration );
+
+    std::string serializeFilters( std::vector<std::string> const& container );
+
+    template<typename DerivedT>
+    struct StreamingReporterBase : IStreamingReporter {
+
+        StreamingReporterBase( ReporterConfig const& _config )
+        :   m_config( _config.fullConfig() ),
+            stream( _config.stream() )
+        {
+            m_reporterPrefs.shouldRedirectStdOut = false;
+            if( !DerivedT::getSupportedVerbosities().count( m_config->verbosity() ) )
+                CATCH_ERROR( "Verbosity level not supported by this reporter" );
+        }
+
+        ReporterPreferences getPreferences() const override {
+            return m_reporterPrefs;
+        }
+
+        static std::set<Verbosity> getSupportedVerbosities() {
+            return { Verbosity::Normal };
+        }
+
+        ~StreamingReporterBase() override = default;
+
+        void noMatchingTestCases(std::string const&) override {}
+
+        void reportInvalidArguments(std::string const&) override {}
+
+        void testRunStarting(TestRunInfo const& _testRunInfo) override {
+            currentTestRunInfo = _testRunInfo;
+        }
+
+        void testGroupStarting(GroupInfo const& _groupInfo) override {
+            currentGroupInfo = _groupInfo;
+        }
+
+        void testCaseStarting(TestCaseInfo const& _testInfo) override  {
+            currentTestCaseInfo = _testInfo;
+        }
+        void sectionStarting(SectionInfo const& _sectionInfo) override {
+            m_sectionStack.push_back(_sectionInfo);
+        }
+
+        void sectionEnded(SectionStats const& /* _sectionStats */) override {
+            m_sectionStack.pop_back();
+        }
+        void testCaseEnded(TestCaseStats const& /* _testCaseStats */) override {
+            currentTestCaseInfo.reset();
+        }
+        void testGroupEnded(TestGroupStats const& /* _testGroupStats */) override {
+            currentGroupInfo.reset();
+        }
+        void testRunEnded(TestRunStats const& /* _testRunStats */) override {
+            currentTestCaseInfo.reset();
+            currentGroupInfo.reset();
+            currentTestRunInfo.reset();
+        }
+
+        void skipTest(TestCaseInfo const&) override {
+            // Don't do anything with this by default.
+            // It can optionally be overridden in the derived class.
+        }
+
+        IConfigPtr m_config;
+        std::ostream& stream;
+
+        LazyStat<TestRunInfo> currentTestRunInfo;
+        LazyStat<GroupInfo> currentGroupInfo;
+        LazyStat<TestCaseInfo> currentTestCaseInfo;
+
+        std::vector<SectionInfo> m_sectionStack;
+        ReporterPreferences m_reporterPrefs;
+    };
+
+    template<typename DerivedT>
+    struct CumulativeReporterBase : IStreamingReporter {
+        template<typename T, typename ChildNodeT>
+        struct Node {
+            explicit Node( T const& _value ) : value( _value ) {}
+            virtual ~Node() {}
+
+            using ChildNodes = std::vector<std::shared_ptr<ChildNodeT>>;
+            T value;
+            ChildNodes children;
+        };
+        struct SectionNode {
+            explicit SectionNode(SectionStats const& _stats) : stats(_stats) {}
+            virtual ~SectionNode() = default;
+
+            bool operator == (SectionNode const& other) const {
+                return stats.sectionInfo.lineInfo == other.stats.sectionInfo.lineInfo;
+            }
+            bool operator == (std::shared_ptr<SectionNode> const& other) const {
+                return operator==(*other);
+            }
+
+            SectionStats stats;
+            using ChildSections = std::vector<std::shared_ptr<SectionNode>>;
+            using Assertions = std::vector<AssertionStats>;
+            ChildSections childSections;
+            Assertions assertions;
+            std::string stdOut;
+            std::string stdErr;
+        };
+
+        struct BySectionInfo {
+            BySectionInfo( SectionInfo const& other ) : m_other( other ) {}
+            BySectionInfo( BySectionInfo const& other ) : m_other( other.m_other ) {}
+            bool operator() (std::shared_ptr<SectionNode> const& node) const {
+                return ((node->stats.sectionInfo.name == m_other.name) &&
+                        (node->stats.sectionInfo.lineInfo == m_other.lineInfo));
+            }
+            void operator=(BySectionInfo const&) = delete;
+
+        private:
+            SectionInfo const& m_other;
+        };
+
+        using TestCaseNode = Node<TestCaseStats, SectionNode>;
+        using TestGroupNode = Node<TestGroupStats, TestCaseNode>;
+        using TestRunNode = Node<TestRunStats, TestGroupNode>;
+
+        CumulativeReporterBase( ReporterConfig const& _config )
+        :   m_config( _config.fullConfig() ),
+            stream( _config.stream() )
+        {
+            m_reporterPrefs.shouldRedirectStdOut = false;
+            if( !DerivedT::getSupportedVerbosities().count( m_config->verbosity() ) )
+                CATCH_ERROR( "Verbosity level not supported by this reporter" );
+        }
+        ~CumulativeReporterBase() override = default;
+
+        ReporterPreferences getPreferences() const override {
+            return m_reporterPrefs;
+        }
+
+        static std::set<Verbosity> getSupportedVerbosities() {
+            return { Verbosity::Normal };
+        }
+
+        void testRunStarting( TestRunInfo const& ) override {}
+        void testGroupStarting( GroupInfo const& ) override {}
+
+        void testCaseStarting( TestCaseInfo const& ) override {}
+
+        void sectionStarting( SectionInfo const& sectionInfo ) override {
+            SectionStats incompleteStats( sectionInfo, Counts(), 0, false );
+            std::shared_ptr<SectionNode> node;
+            if( m_sectionStack.empty() ) {
+                if( !m_rootSection )
+                    m_rootSection = std::make_shared<SectionNode>( incompleteStats );
+                node = m_rootSection;
+            }
+            else {
+                SectionNode& parentNode = *m_sectionStack.back();
+                auto it =
+                    std::find_if(   parentNode.childSections.begin(),
+                                    parentNode.childSections.end(),
+                                    BySectionInfo( sectionInfo ) );
+                if( it == parentNode.childSections.end() ) {
+                    node = std::make_shared<SectionNode>( incompleteStats );
+                    parentNode.childSections.push_back( node );
+                }
+                else
+                    node = *it;
+            }
+            m_sectionStack.push_back( node );
+            m_deepestSection = std::move(node);
+        }
+
+        void assertionStarting(AssertionInfo const&) override {}
+
+        bool assertionEnded(AssertionStats const& assertionStats) override {
+            assert(!m_sectionStack.empty());
+            // AssertionResult holds a pointer to a temporary DecomposedExpression,
+            // which getExpandedExpression() calls to build the expression string.
+            // Our section stack copy of the assertionResult will likely outlive the
+            // temporary, so it must be expanded or discarded now to avoid calling
+            // a destroyed object later.
+            prepareExpandedExpression(const_cast<AssertionResult&>( assertionStats.assertionResult ) );
+            SectionNode& sectionNode = *m_sectionStack.back();
+            sectionNode.assertions.push_back(assertionStats);
+            return true;
+        }
+        void sectionEnded(SectionStats const& sectionStats) override {
+            assert(!m_sectionStack.empty());
+            SectionNode& node = *m_sectionStack.back();
+            node.stats = sectionStats;
+            m_sectionStack.pop_back();
+        }
+        void testCaseEnded(TestCaseStats const& testCaseStats) override {
+            auto node = std::make_shared<TestCaseNode>(testCaseStats);
+            assert(m_sectionStack.size() == 0);
+            node->children.push_back(m_rootSection);
+            m_testCases.push_back(node);
+            m_rootSection.reset();
+
+            assert(m_deepestSection);
+            m_deepestSection->stdOut = testCaseStats.stdOut;
+            m_deepestSection->stdErr = testCaseStats.stdErr;
+        }
+        void testGroupEnded(TestGroupStats const& testGroupStats) override {
+            auto node = std::make_shared<TestGroupNode>(testGroupStats);
+            node->children.swap(m_testCases);
+            m_testGroups.push_back(node);
+        }
+        void testRunEnded(TestRunStats const& testRunStats) override {
+            auto node = std::make_shared<TestRunNode>(testRunStats);
+            node->children.swap(m_testGroups);
+            m_testRuns.push_back(node);
+            testRunEndedCumulative();
+        }
+        virtual void testRunEndedCumulative() = 0;
+
+        void skipTest(TestCaseInfo const&) override {}
+
+        IConfigPtr m_config;
+        std::ostream& stream;
+        std::vector<AssertionStats> m_assertions;
+        std::vector<std::vector<std::shared_ptr<SectionNode>>> m_sections;
+        std::vector<std::shared_ptr<TestCaseNode>> m_testCases;
+        std::vector<std::shared_ptr<TestGroupNode>> m_testGroups;
+
+        std::vector<std::shared_ptr<TestRunNode>> m_testRuns;
+
+        std::shared_ptr<SectionNode> m_rootSection;
+        std::shared_ptr<SectionNode> m_deepestSection;
+        std::vector<std::shared_ptr<SectionNode>> m_sectionStack;
+        ReporterPreferences m_reporterPrefs;
+    };
+
+    template<char C>
+    char const* getLineOfChars() {
+        static char line[CATCH_CONFIG_CONSOLE_WIDTH] = {0};
+        if( !*line ) {
+            std::memset( line, C, CATCH_CONFIG_CONSOLE_WIDTH-1 );
+            line[CATCH_CONFIG_CONSOLE_WIDTH-1] = 0;
+        }
+        return line;
+    }
+
+    struct TestEventListenerBase : StreamingReporterBase<TestEventListenerBase> {
+        TestEventListenerBase( ReporterConfig const& _config );
+
+        static std::set<Verbosity> getSupportedVerbosities();
+
+        void assertionStarting(AssertionInfo const&) override;
+        bool assertionEnded(AssertionStats const&) override;
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_bases.hpp
+// start catch_console_colour.h
+
+namespace Catch {
+
+    struct Colour {
+        enum Code {
+            None = 0,
+
+            White,
+            Red,
+            Green,
+            Blue,
+            Cyan,
+            Yellow,
+            Grey,
+
+            Bright = 0x10,
+
+            BrightRed = Bright | Red,
+            BrightGreen = Bright | Green,
+            LightGrey = Bright | Grey,
+            BrightWhite = Bright | White,
+            BrightYellow = Bright | Yellow,
+
+            // By intention
+            FileName = LightGrey,
+            Warning = BrightYellow,
+            ResultError = BrightRed,
+            ResultSuccess = BrightGreen,
+            ResultExpectedFailure = Warning,
+
+            Error = BrightRed,
+            Success = Green,
+
+            OriginalExpression = Cyan,
+            ReconstructedExpression = BrightYellow,
+
+            SecondaryText = LightGrey,
+            Headers = White
+        };
+
+        // Use constructed object for RAII guard
+        Colour( Code _colourCode );
+        Colour( Colour&& other ) noexcept;
+        Colour& operator=( Colour&& other ) noexcept;
+        ~Colour();
+
+        // Use static method for one-shot changes
+        static void use( Code _colourCode );
+
+    private:
+        bool m_moved = false;
+    };
+
+    std::ostream& operator << ( std::ostream& os, Colour const& );
+
+} // end namespace Catch
+
+// end catch_console_colour.h
+// start catch_reporter_registrars.hpp
+
+
+namespace Catch {
+
+    template<typename T>
+    class ReporterRegistrar {
+
+        class ReporterFactory : public IReporterFactory {
+
+            IStreamingReporterPtr create( ReporterConfig const& config ) const override {
+                return std::unique_ptr<T>( new T( config ) );
+            }
+
+            std::string getDescription() const override {
+                return T::getDescription();
+            }
+        };
+
+    public:
+
+        explicit ReporterRegistrar( std::string const& name ) {
+            getMutableRegistryHub().registerReporter( name, std::make_shared<ReporterFactory>() );
+        }
+    };
+
+    template<typename T>
+    class ListenerRegistrar {
+
+        class ListenerFactory : public IReporterFactory {
+
+            IStreamingReporterPtr create( ReporterConfig const& config ) const override {
+                return std::unique_ptr<T>( new T( config ) );
+            }
+            std::string getDescription() const override {
+                return std::string();
+            }
+        };
+
+    public:
+
+        ListenerRegistrar() {
+            getMutableRegistryHub().registerListener( std::make_shared<ListenerFactory>() );
+        }
+    };
+}
+
+#if !defined(CATCH_CONFIG_DISABLE)
+
+#define CATCH_REGISTER_REPORTER( name, reporterType ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION         \
+    CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS          \
+    namespace{ Catch::ReporterRegistrar<reporterType> catch_internal_RegistrarFor##reporterType( name ); } \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+#define CATCH_REGISTER_LISTENER( listenerType ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION   \
+    CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS    \
+    namespace{ Catch::ListenerRegistrar<listenerType> catch_internal_RegistrarFor##listenerType; } \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+#else // CATCH_CONFIG_DISABLE
+
+#define CATCH_REGISTER_REPORTER(name, reporterType)
+#define CATCH_REGISTER_LISTENER(listenerType)
+
+#endif // CATCH_CONFIG_DISABLE
+
+// end catch_reporter_registrars.hpp
+// Allow users to base their work off existing reporters
+// start catch_reporter_compact.h
+
+namespace Catch {
+
+    struct CompactReporter : StreamingReporterBase<CompactReporter> {
+
+        using StreamingReporterBase::StreamingReporterBase;
+
+        ~CompactReporter() override;
+
+        static std::string getDescription();
+
+        ReporterPreferences getPreferences() const override;
+
+        void noMatchingTestCases(std::string const& spec) override;
+
+        void assertionStarting(AssertionInfo const&) override;
+
+        bool assertionEnded(AssertionStats const& _assertionStats) override;
+
+        void sectionEnded(SectionStats const& _sectionStats) override;
+
+        void testRunEnded(TestRunStats const& _testRunStats) override;
+
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_compact.h
+// start catch_reporter_console.h
+
+#if defined(_MSC_VER)
+#pragma warning(push)
+#pragma warning(disable:4061) // Not all labels are EXPLICITLY handled in switch
+                              // Note that 4062 (not all labels are handled
+                              // and default is missing) is enabled
+#endif
+
+namespace Catch {
+    // Fwd decls
+    struct SummaryColumn;
+    class TablePrinter;
+
+    struct ConsoleReporter : StreamingReporterBase<ConsoleReporter> {
+        std::unique_ptr<TablePrinter> m_tablePrinter;
+
+        ConsoleReporter(ReporterConfig const& config);
+        ~ConsoleReporter() override;
+        static std::string getDescription();
+
+        void noMatchingTestCases(std::string const& spec) override;
+
+        void reportInvalidArguments(std::string const&arg) override;
+
+        void assertionStarting(AssertionInfo const&) override;
+
+        bool assertionEnded(AssertionStats const& _assertionStats) override;
+
+        void sectionStarting(SectionInfo const& _sectionInfo) override;
+        void sectionEnded(SectionStats const& _sectionStats) override;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        void benchmarkPreparing(std::string const& name) override;
+        void benchmarkStarting(BenchmarkInfo const& info) override;
+        void benchmarkEnded(BenchmarkStats<> const& stats) override;
+        void benchmarkFailed(std::string const& error) override;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        void testCaseEnded(TestCaseStats const& _testCaseStats) override;
+        void testGroupEnded(TestGroupStats const& _testGroupStats) override;
+        void testRunEnded(TestRunStats const& _testRunStats) override;
+        void testRunStarting(TestRunInfo const& _testRunInfo) override;
+    private:
+
+        void lazyPrint();
+
+        void lazyPrintWithoutClosingBenchmarkTable();
+        void lazyPrintRunInfo();
+        void lazyPrintGroupInfo();
+        void printTestCaseAndSectionHeader();
+
+        void printClosedHeader(std::string const& _name);
+        void printOpenHeader(std::string const& _name);
+
+        // if string has a : in first line will set indent to follow it on
+        // subsequent lines
+        void printHeaderString(std::string const& _string, std::size_t indent = 0);
+
+        void printTotals(Totals const& totals);
+        void printSummaryRow(std::string const& label, std::vector<SummaryColumn> const& cols, std::size_t row);
+
+        void printTotalsDivider(Totals const& totals);
+        void printSummaryDivider();
+        void printTestFilters();
+
+    private:
+        bool m_headerPrinted = false;
+    };
+
+} // end namespace Catch
+
+#if defined(_MSC_VER)
+#pragma warning(pop)
+#endif
+
+// end catch_reporter_console.h
+// start catch_reporter_junit.h
+
+// start catch_xmlwriter.h
+
+#include <vector>
+
+namespace Catch {
+    enum class XmlFormatting {
+        None = 0x00,
+        Indent = 0x01,
+        Newline = 0x02,
+    };
+
+    XmlFormatting operator | (XmlFormatting lhs, XmlFormatting rhs);
+    XmlFormatting operator & (XmlFormatting lhs, XmlFormatting rhs);
+
+    class XmlEncode {
+    public:
+        enum ForWhat { ForTextNodes, ForAttributes };
+
+        XmlEncode( std::string const& str, ForWhat forWhat = ForTextNodes );
+
+        void encodeTo( std::ostream& os ) const;
+
+        friend std::ostream& operator << ( std::ostream& os, XmlEncode const& xmlEncode );
+
+    private:
+        std::string m_str;
+        ForWhat m_forWhat;
+    };
+
+    class XmlWriter {
+    public:
+
+        class ScopedElement {
+        public:
+            ScopedElement( XmlWriter* writer, XmlFormatting fmt );
+
+            ScopedElement( ScopedElement&& other ) noexcept;
+            ScopedElement& operator=( ScopedElement&& other ) noexcept;
+
+            ~ScopedElement();
+
+            ScopedElement& writeText( std::string const& text, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent );
+
+            template<typename T>
+            ScopedElement& writeAttribute( std::string const& name, T const& attribute ) {
+                m_writer->writeAttribute( name, attribute );
+                return *this;
+            }
+
+        private:
+            mutable XmlWriter* m_writer = nullptr;
+            XmlFormatting m_fmt;
+        };
+
+        XmlWriter( std::ostream& os = Catch::cout() );
+        ~XmlWriter();
+
+        XmlWriter( XmlWriter const& ) = delete;
+        XmlWriter& operator=( XmlWriter const& ) = delete;
+
+        XmlWriter& startElement( std::string const& name, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        ScopedElement scopedElement( std::string const& name, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        XmlWriter& endElement(XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        XmlWriter& writeAttribute( std::string const& name, std::string const& attribute );
+
+        XmlWriter& writeAttribute( std::string const& name, bool attribute );
+
+        template<typename T>
+        XmlWriter& writeAttribute( std::string const& name, T const& attribute ) {
+            ReusableStringStream rss;
+            rss << attribute;
+            return writeAttribute( name, rss.str() );
+        }
+
+        XmlWriter& writeText( std::string const& text, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        XmlWriter& writeComment(std::string const& text, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        void writeStylesheetRef( std::string const& url );
+
+        XmlWriter& writeBlankLine();
+
+        void ensureTagClosed();
+
+    private:
+
+        void applyFormatting(XmlFormatting fmt);
+
+        void writeDeclaration();
+
+        void newlineIfNecessary();
+
+        bool m_tagIsOpen = false;
+        bool m_needsNewline = false;
+        std::vector<std::string> m_tags;
+        std::string m_indent;
+        std::ostream& m_os;
+    };
+
+}
+
+// end catch_xmlwriter.h
+namespace Catch {
+
+    class JunitReporter : public CumulativeReporterBase<JunitReporter> {
+    public:
+        JunitReporter(ReporterConfig const& _config);
+
+        ~JunitReporter() override;
+
+        static std::string getDescription();
+
+        void noMatchingTestCases(std::string const& /*spec*/) override;
+
+        void testRunStarting(TestRunInfo const& runInfo) override;
+
+        void testGroupStarting(GroupInfo const& groupInfo) override;
+
+        void testCaseStarting(TestCaseInfo const& testCaseInfo) override;
+        bool assertionEnded(AssertionStats const& assertionStats) override;
+
+        void testCaseEnded(TestCaseStats const& testCaseStats) override;
+
+        void testGroupEnded(TestGroupStats const& testGroupStats) override;
+
+        void testRunEndedCumulative() override;
+
+        void writeGroup(TestGroupNode const& groupNode, double suiteTime);
+
+        void writeTestCase(TestCaseNode const& testCaseNode);
+
+        void writeSection(std::string const& className,
+                          std::string const& rootName,
+                          SectionNode const& sectionNode);
+
+        void writeAssertions(SectionNode const& sectionNode);
+        void writeAssertion(AssertionStats const& stats);
+
+        XmlWriter xml;
+        Timer suiteTimer;
+        std::string stdOutForSuite;
+        std::string stdErrForSuite;
+        unsigned int unexpectedExceptions = 0;
+        bool m_okToFail = false;
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_junit.h
+// start catch_reporter_xml.h
+
+namespace Catch {
+    class XmlReporter : public StreamingReporterBase<XmlReporter> {
+    public:
+        XmlReporter(ReporterConfig const& _config);
+
+        ~XmlReporter() override;
+
+        static std::string getDescription();
+
+        virtual std::string getStylesheetRef() const;
+
+        void writeSourceInfo(SourceLineInfo const& sourceInfo);
+
+    public: // StreamingReporterBase
+
+        void noMatchingTestCases(std::string const& s) override;
+
+        void testRunStarting(TestRunInfo const& testInfo) override;
+
+        void testGroupStarting(GroupInfo const& groupInfo) override;
+
+        void testCaseStarting(TestCaseInfo const& testInfo) override;
+
+        void sectionStarting(SectionInfo const& sectionInfo) override;
+
+        void assertionStarting(AssertionInfo const&) override;
+
+        bool assertionEnded(AssertionStats const& assertionStats) override;
+
+        void sectionEnded(SectionStats const& sectionStats) override;
+
+        void testCaseEnded(TestCaseStats const& testCaseStats) override;
+
+        void testGroupEnded(TestGroupStats const& testGroupStats) override;
+
+        void testRunEnded(TestRunStats const& testRunStats) override;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        void benchmarkPreparing(std::string const& name) override;
+        void benchmarkStarting(BenchmarkInfo const&) override;
+        void benchmarkEnded(BenchmarkStats<> const&) override;
+        void benchmarkFailed(std::string const&) override;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    private:
+        Timer m_testCaseTimer;
+        XmlWriter m_xml;
+        int m_sectionDepth = 0;
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_xml.h
+
+// end catch_external_interfaces.h
+#endif
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+// start catch_benchmarking_all.hpp
+
+// A proxy header that includes all of the benchmarking headers to allow
+// concise include of the benchmarking features. You should prefer the
+// individual includes in standard use.
+
+// start catch_benchmark.hpp
+
+ // Benchmark
+
+// start catch_chronometer.hpp
+
+// User-facing chronometer
+
+
+// start catch_clock.hpp
+
+// Clocks
+
+
+#include <chrono>
+#include <ratio>
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Clock>
+        using ClockDuration = typename Clock::duration;
+        template <typename Clock>
+        using FloatDuration = std::chrono::duration<double, typename Clock::period>;
+
+        template <typename Clock>
+        using TimePoint = typename Clock::time_point;
+
+        using default_clock = std::chrono::steady_clock;
+
+        template <typename Clock>
+        struct now {
+            TimePoint<Clock> operator()() const {
+                return Clock::now();
+            }
+        };
+
+        using fp_seconds = std::chrono::duration<double, std::ratio<1>>;
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_clock.hpp
+// start catch_optimizer.hpp
+
+ // Hinting the optimizer
+
+
+#if defined(_MSC_VER)
+#   include <atomic> // atomic_thread_fence
+#endif
+
+namespace Catch {
+    namespace Benchmark {
+#if defined(__GNUC__) || defined(__clang__)
+        template <typename T>
+        inline void keep_memory(T* p) {
+            asm volatile("" : : "g"(p) : "memory");
+        }
+        inline void keep_memory() {
+            asm volatile("" : : : "memory");
+        }
+
+        namespace Detail {
+            inline void optimizer_barrier() { keep_memory(); }
+        } // namespace Detail
+#elif defined(_MSC_VER)
+
+#pragma optimize("", off)
+        template <typename T>
+        inline void keep_memory(T* p) {
+            // thanks @milleniumbug
+            *reinterpret_cast<char volatile*>(p) = *reinterpret_cast<char const volatile*>(p);
+        }
+        // TODO equivalent keep_memory()
+#pragma optimize("", on)
+
+        namespace Detail {
+            inline void optimizer_barrier() {
+                std::atomic_thread_fence(std::memory_order_seq_cst);
+            }
+        } // namespace Detail
+
+#endif
+
+        template <typename T>
+        inline void deoptimize_value(T&& x) {
+            keep_memory(&x);
+        }
+
+        template <typename Fn, typename... Args>
+        inline auto invoke_deoptimized(Fn&& fn, Args&&... args) -> typename std::enable_if<!std::is_same<void, decltype(fn(args...))>::value>::type {
+            deoptimize_value(std::forward<Fn>(fn) (std::forward<Args...>(args...)));
+        }
+
+        template <typename Fn, typename... Args>
+        inline auto invoke_deoptimized(Fn&& fn, Args&&... args) -> typename std::enable_if<std::is_same<void, decltype(fn(args...))>::value>::type {
+            std::forward<Fn>(fn) (std::forward<Args...>(args...));
+        }
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_optimizer.hpp
+// start catch_complete_invoke.hpp
+
+// Invoke with a special case for void
+
+
+#include <type_traits>
+#include <utility>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename T>
+            struct CompleteType { using type = T; };
+            template <>
+            struct CompleteType<void> { struct type {}; };
+
+            template <typename T>
+            using CompleteType_t = typename CompleteType<T>::type;
+
+            template <typename Result>
+            struct CompleteInvoker {
+                template <typename Fun, typename... Args>
+                static Result invoke(Fun&& fun, Args&&... args) {
+                    return std::forward<Fun>(fun)(std::forward<Args>(args)...);
+                }
+            };
+            template <>
+            struct CompleteInvoker<void> {
+                template <typename Fun, typename... Args>
+                static CompleteType_t<void> invoke(Fun&& fun, Args&&... args) {
+                    std::forward<Fun>(fun)(std::forward<Args>(args)...);
+                    return {};
+                }
+            };
+            template <typename Sig>
+            using ResultOf_t = typename std::result_of<Sig>::type;
+
+            // invoke and not return void :(
+            template <typename Fun, typename... Args>
+            CompleteType_t<ResultOf_t<Fun(Args...)>> complete_invoke(Fun&& fun, Args&&... args) {
+                return CompleteInvoker<ResultOf_t<Fun(Args...)>>::invoke(std::forward<Fun>(fun), std::forward<Args>(args)...);
+            }
+
+            const std::string benchmarkErrorMsg = "a benchmark failed to run successfully";
+        } // namespace Detail
+
+        template <typename Fun>
+        Detail::CompleteType_t<Detail::ResultOf_t<Fun()>> user_code(Fun&& fun) {
+            CATCH_TRY{
+                return Detail::complete_invoke(std::forward<Fun>(fun));
+            } CATCH_CATCH_ALL{
+                getResultCapture().benchmarkFailed(translateActiveException());
+                CATCH_RUNTIME_ERROR(Detail::benchmarkErrorMsg);
+            }
+        }
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_complete_invoke.hpp
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            struct ChronometerConcept {
+                virtual void start() = 0;
+                virtual void finish() = 0;
+                virtual ~ChronometerConcept() = default;
+            };
+            template <typename Clock>
+            struct ChronometerModel final : public ChronometerConcept {
+                void start() override { started = Clock::now(); }
+                void finish() override { finished = Clock::now(); }
+
+                ClockDuration<Clock> elapsed() const { return finished - started; }
+
+                TimePoint<Clock> started;
+                TimePoint<Clock> finished;
+            };
+        } // namespace Detail
+
+        struct Chronometer {
+        public:
+            template <typename Fun>
+            void measure(Fun&& fun) { measure(std::forward<Fun>(fun), is_callable<Fun(int)>()); }
+
+            int runs() const { return k; }
+
+            Chronometer(Detail::ChronometerConcept& meter, int k)
+                : impl(&meter)
+                , k(k) {}
+
+        private:
+            template <typename Fun>
+            void measure(Fun&& fun, std::false_type) {
+                measure([&fun](int) { return fun(); }, std::true_type());
+            }
+
+            template <typename Fun>
+            void measure(Fun&& fun, std::true_type) {
+                Detail::optimizer_barrier();
+                impl->start();
+                for (int i = 0; i < k; ++i) invoke_deoptimized(fun, i);
+                impl->finish();
+                Detail::optimizer_barrier();
+            }
+
+            Detail::ChronometerConcept* impl;
+            int k;
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_chronometer.hpp
+// start catch_environment.hpp
+
+// Environment information
+
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration>
+        struct EnvironmentEstimate {
+            Duration mean;
+            OutlierClassification outliers;
+
+            template <typename Duration2>
+            operator EnvironmentEstimate<Duration2>() const {
+                return { mean, outliers };
+            }
+        };
+        template <typename Clock>
+        struct Environment {
+            using clock_type = Clock;
+            EnvironmentEstimate<FloatDuration<Clock>> clock_resolution;
+            EnvironmentEstimate<FloatDuration<Clock>> clock_cost;
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_environment.hpp
+// start catch_execution_plan.hpp
+
+ // Execution plan
+
+
+// start catch_benchmark_function.hpp
+
+ // Dumb std::function implementation for consistent call overhead
+
+
+#include <cassert>
+#include <type_traits>
+#include <utility>
+#include <memory>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename T>
+            using Decay = typename std::decay<T>::type;
+            template <typename T, typename U>
+            struct is_related
+                : std::is_same<Decay<T>, Decay<U>> {};
+
+            /// We need to reinvent std::function because every piece of code that might add overhead
+            /// in a measurement context needs to have consistent performance characteristics so that we
+            /// can account for it in the measurement.
+            /// Implementations of std::function with optimizations that aren't always applicable, like
+            /// small buffer optimizations, are not uncommon.
+            /// This is effectively an implementation of std::function without any such optimizations;
+            /// it may be slow, but it is consistently slow.
+            struct BenchmarkFunction {
+            private:
+                struct callable {
+                    virtual void call(Chronometer meter) const = 0;
+                    virtual callable* clone() const = 0;
+                    virtual ~callable() = default;
+                };
+                template <typename Fun>
+                struct model : public callable {
+                    model(Fun&& fun) : fun(std::move(fun)) {}
+                    model(Fun const& fun) : fun(fun) {}
+
+                    model<Fun>* clone() const override { return new model<Fun>(*this); }
+
+                    void call(Chronometer meter) const override {
+                        call(meter, is_callable<Fun(Chronometer)>());
+                    }
+                    void call(Chronometer meter, std::true_type) const {
+                        fun(meter);
+                    }
+                    void call(Chronometer meter, std::false_type) const {
+                        meter.measure(fun);
+                    }
+
+                    Fun fun;
+                };
+
+                struct do_nothing { void operator()() const {} };
+
+                template <typename T>
+                BenchmarkFunction(model<T>* c) : f(c) {}
+
+            public:
+                BenchmarkFunction()
+                    : f(new model<do_nothing>{ {} }) {}
+
+                template <typename Fun,
+                    typename std::enable_if<!is_related<Fun, BenchmarkFunction>::value, int>::type = 0>
+                    BenchmarkFunction(Fun&& fun)
+                    : f(new model<typename std::decay<Fun>::type>(std::forward<Fun>(fun))) {}
+
+                BenchmarkFunction(BenchmarkFunction&& that)
+                    : f(std::move(that.f)) {}
+
+                BenchmarkFunction(BenchmarkFunction const& that)
+                    : f(that.f->clone()) {}
+
+                BenchmarkFunction& operator=(BenchmarkFunction&& that) {
+                    f = std::move(that.f);
+                    return *this;
+                }
+
+                BenchmarkFunction& operator=(BenchmarkFunction const& that) {
+                    f.reset(that.f->clone());
+                    return *this;
+                }
+
+                void operator()(Chronometer meter) const { f->call(meter); }
+
+            private:
+                std::unique_ptr<callable> f;
+            };
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_benchmark_function.hpp
+// start catch_repeat.hpp
+
+// repeat algorithm
+
+
+#include <type_traits>
+#include <utility>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Fun>
+            struct repeater {
+                void operator()(int k) const {
+                    for (int i = 0; i < k; ++i) {
+                        fun();
+                    }
+                }
+                Fun fun;
+            };
+            template <typename Fun>
+            repeater<typename std::decay<Fun>::type> repeat(Fun&& fun) {
+                return { std::forward<Fun>(fun) };
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_repeat.hpp
+// start catch_run_for_at_least.hpp
+
+// Run a function for a minimum amount of time
+
+
+// start catch_measure.hpp
+
+// Measure
+
+
+// start catch_timing.hpp
+
+// Timing
+
+
+#include <tuple>
+#include <type_traits>
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration, typename Result>
+        struct Timing {
+            Duration elapsed;
+            Result result;
+            int iterations;
+        };
+        template <typename Clock, typename Sig>
+        using TimingOf = Timing<ClockDuration<Clock>, Detail::CompleteType_t<Detail::ResultOf_t<Sig>>>;
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_timing.hpp
+#include <utility>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Clock, typename Fun, typename... Args>
+            TimingOf<Clock, Fun(Args...)> measure(Fun&& fun, Args&&... args) {
+                auto start = Clock::now();
+                auto&& r = Detail::complete_invoke(fun, std::forward<Args>(args)...);
+                auto end = Clock::now();
+                auto delta = end - start;
+                return { delta, std::forward<decltype(r)>(r), 1 };
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_measure.hpp
+#include <utility>
+#include <type_traits>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Clock, typename Fun>
+            TimingOf<Clock, Fun(int)> measure_one(Fun&& fun, int iters, std::false_type) {
+                return Detail::measure<Clock>(fun, iters);
+            }
+            template <typename Clock, typename Fun>
+            TimingOf<Clock, Fun(Chronometer)> measure_one(Fun&& fun, int iters, std::true_type) {
+                Detail::ChronometerModel<Clock> meter;
+                auto&& result = Detail::complete_invoke(fun, Chronometer(meter, iters));
+
+                return { meter.elapsed(), std::move(result), iters };
+            }
+
+            template <typename Clock, typename Fun>
+            using run_for_at_least_argument_t = typename std::conditional<is_callable<Fun(Chronometer)>::value, Chronometer, int>::type;
+
+            struct optimized_away_error : std::exception {
+                const char* what() const noexcept override {
+                    return "could not measure benchmark, maybe it was optimized away";
+                }
+            };
+
+            template <typename Clock, typename Fun>
+            TimingOf<Clock, Fun(run_for_at_least_argument_t<Clock, Fun>)> run_for_at_least(ClockDuration<Clock> how_long, int seed, Fun&& fun) {
+                auto iters = seed;
+                while (iters < (1 << 30)) {
+                    auto&& Timing = measure_one<Clock>(fun, iters, is_callable<Fun(Chronometer)>());
+
+                    if (Timing.elapsed >= how_long) {
+                        return { Timing.elapsed, std::move(Timing.result), iters };
+                    }
+                    iters *= 2;
+                }
+                throw optimized_away_error{};
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_run_for_at_least.hpp
+#include <algorithm>
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration>
+        struct ExecutionPlan {
+            int iterations_per_sample;
+            Duration estimated_duration;
+            Detail::BenchmarkFunction benchmark;
+            Duration warmup_time;
+            int warmup_iterations;
+
+            template <typename Duration2>
+            operator ExecutionPlan<Duration2>() const {
+                return { iterations_per_sample, estimated_duration, benchmark, warmup_time, warmup_iterations };
+            }
+
+            template <typename Clock>
+            std::vector<FloatDuration<Clock>> run(const IConfig &cfg, Environment<FloatDuration<Clock>> env) const {
+                // warmup a bit
+                Detail::run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(warmup_time), warmup_iterations, Detail::repeat(now<Clock>{}));
+
+                std::vector<FloatDuration<Clock>> times;
+                times.reserve(cfg.benchmarkSamples());
+                std::generate_n(std::back_inserter(times), cfg.benchmarkSamples(), [this, env] {
+                    Detail::ChronometerModel<Clock> model;
+                    this->benchmark(Chronometer(model, iterations_per_sample));
+                    auto sample_time = model.elapsed() - env.clock_cost.mean;
+                    if (sample_time < FloatDuration<Clock>::zero()) sample_time = FloatDuration<Clock>::zero();
+                    return sample_time / iterations_per_sample;
+                });
+                return times;
+            }
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_execution_plan.hpp
+// start catch_estimate_clock.hpp
+
+ // Environment measurement
+
+
+// start catch_stats.hpp
+
+// Statistical analysis tools
+
+
+#include <algorithm>
+#include <functional>
+#include <vector>
+#include <iterator>
+#include <numeric>
+#include <tuple>
+#include <cmath>
+#include <utility>
+#include <cstddef>
+#include <random>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            using sample = std::vector<double>;
+
+            double weighted_average_quantile(int k, int q, std::vector<double>::iterator first, std::vector<double>::iterator last);
+
+            template <typename Iterator>
+            OutlierClassification classify_outliers(Iterator first, Iterator last) {
+                std::vector<double> copy(first, last);
+
+                auto q1 = weighted_average_quantile(1, 4, copy.begin(), copy.end());
+                auto q3 = weighted_average_quantile(3, 4, copy.begin(), copy.end());
+                auto iqr = q3 - q1;
+                auto los = q1 - (iqr * 3.);
+                auto lom = q1 - (iqr * 1.5);
+                auto him = q3 + (iqr * 1.5);
+                auto his = q3 + (iqr * 3.);
+
+                OutlierClassification o;
+                for (; first != last; ++first) {
+                    auto&& t = *first;
+                    if (t < los) ++o.low_severe;
+                    else if (t < lom) ++o.low_mild;
+                    else if (t > his) ++o.high_severe;
+                    else if (t > him) ++o.high_mild;
+                    ++o.samples_seen;
+                }
+                return o;
+            }
+
+            template <typename Iterator>
+            double mean(Iterator first, Iterator last) {
+                auto count = last - first;
+                double sum = std::accumulate(first, last, 0.);
+                return sum / count;
+            }
+
+            template <typename URng, typename Iterator, typename Estimator>
+            sample resample(URng& rng, int resamples, Iterator first, Iterator last, Estimator& estimator) {
+                auto n = last - first;
+                std::uniform_int_distribution<decltype(n)> dist(0, n - 1);
+
+                sample out;
+                out.reserve(resamples);
+                std::generate_n(std::back_inserter(out), resamples, [n, first, &estimator, &dist, &rng] {
+                    std::vector<double> resampled;
+                    resampled.reserve(n);
+                    std::generate_n(std::back_inserter(resampled), n, [first, &dist, &rng] { return first[dist(rng)]; });
+                    return estimator(resampled.begin(), resampled.end());
+                });
+                std::sort(out.begin(), out.end());
+                return out;
+            }
+
+            template <typename Estimator, typename Iterator>
+            sample jackknife(Estimator&& estimator, Iterator first, Iterator last) {
+                auto n = last - first;
+                auto second = std::next(first);
+                sample results;
+                results.reserve(n);
+
+                for (auto it = first; it != last; ++it) {
+                    std::iter_swap(it, first);
+                    results.push_back(estimator(second, last));
+                }
+
+                return results;
+            }
+
+            inline double normal_cdf(double x) {
+                return std::erfc(-x / std::sqrt(2.0)) / 2.0;
+            }
+
+            double erfc_inv(double x);
+
+            double normal_quantile(double p);
+
+            template <typename Iterator, typename Estimator>
+            Estimate<double> bootstrap(double confidence_level, Iterator first, Iterator last, sample const& resample, Estimator&& estimator) {
+                auto n_samples = last - first;
+
+                double point = estimator(first, last);
+                // Degenerate case with a single sample
+                if (n_samples == 1) return { point, point, point, confidence_level };
+
+                sample jack = jackknife(estimator, first, last);
+                double jack_mean = mean(jack.begin(), jack.end());
+                double sum_squares, sum_cubes;
+                std::tie(sum_squares, sum_cubes) = std::accumulate(jack.begin(), jack.end(), std::make_pair(0., 0.), [jack_mean](std::pair<double, double> sqcb, double x) -> std::pair<double, double> {
+                    auto d = jack_mean - x;
+                    auto d2 = d * d;
+                    auto d3 = d2 * d;
+                    return { sqcb.first + d2, sqcb.second + d3 };
+                });
+
+                double accel = sum_cubes / (6 * std::pow(sum_squares, 1.5));
+                int n = static_cast<int>(resample.size());
+                double prob_n = std::count_if(resample.begin(), resample.end(), [point](double x) { return x < point; }) / (double)n;
+                // degenerate case with uniform samples
+                if (prob_n == 0) return { point, point, point, confidence_level };
+
+                double bias = normal_quantile(prob_n);
+                double z1 = normal_quantile((1. - confidence_level) / 2.);
+
+                auto cumn = [n](double x) -> int {
+                    return std::lround(normal_cdf(x) * n); };
+                auto a = [bias, accel](double b) { return bias + b / (1. - accel * b); };
+                double b1 = bias + z1;
+                double b2 = bias - z1;
+                double a1 = a(b1);
+                double a2 = a(b2);
+                auto lo = std::max(cumn(a1), 0);
+                auto hi = std::min(cumn(a2), n - 1);
+
+                return { point, resample[lo], resample[hi], confidence_level };
+            }
+
+            double outlier_variance(Estimate<double> mean, Estimate<double> stddev, int n);
+
+            struct bootstrap_analysis {
+                Estimate<double> mean;
+                Estimate<double> standard_deviation;
+                double outlier_variance;
+            };
+
+            bootstrap_analysis analyse_samples(double confidence_level, int n_resamples, std::vector<double>::iterator first, std::vector<double>::iterator last);
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_stats.hpp
+#include <algorithm>
+#include <iterator>
+#include <tuple>
+#include <vector>
+#include <cmath>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Clock>
+            std::vector<double> resolution(int k) {
+                std::vector<TimePoint<Clock>> times;
+                times.reserve(k + 1);
+                std::generate_n(std::back_inserter(times), k + 1, now<Clock>{});
+
+                std::vector<double> deltas;
+                deltas.reserve(k);
+                std::transform(std::next(times.begin()), times.end(), times.begin(),
+                    std::back_inserter(deltas),
+                    [](TimePoint<Clock> a, TimePoint<Clock> b) { return static_cast<double>((a - b).count()); });
+
+                return deltas;
+            }
+
+            const auto warmup_iterations = 10000;
+            const auto warmup_time = std::chrono::milliseconds(100);
+            const auto minimum_ticks = 1000;
+            const auto warmup_seed = 10000;
+            const auto clock_resolution_estimation_time = std::chrono::milliseconds(500);
+            const auto clock_cost_estimation_time_limit = std::chrono::seconds(1);
+            const auto clock_cost_estimation_tick_limit = 100000;
+            const auto clock_cost_estimation_time = std::chrono::milliseconds(10);
+            const auto clock_cost_estimation_iterations = 10000;
+
+            template <typename Clock>
+            int warmup() {
+                return run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(warmup_time), warmup_seed, &resolution<Clock>)
+                    .iterations;
+            }
+            template <typename Clock>
+            EnvironmentEstimate<FloatDuration<Clock>> estimate_clock_resolution(int iterations) {
+                auto r = run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(clock_resolution_estimation_time), iterations, &resolution<Clock>)
+                    .result;
+                return {
+                    FloatDuration<Clock>(mean(r.begin(), r.end())),
+                    classify_outliers(r.begin(), r.end()),
+                };
+            }
+            template <typename Clock>
+            EnvironmentEstimate<FloatDuration<Clock>> estimate_clock_cost(FloatDuration<Clock> resolution) {
+                auto time_limit = std::min(resolution * clock_cost_estimation_tick_limit, FloatDuration<Clock>(clock_cost_estimation_time_limit));
+                auto time_clock = [](int k) {
+                    return Detail::measure<Clock>([k] {
+                        for (int i = 0; i < k; ++i) {
+                            volatile auto ignored = Clock::now();
+                            (void)ignored;
+                        }
+                    }).elapsed;
+                };
+                time_clock(1);
+                int iters = clock_cost_estimation_iterations;
+                auto&& r = run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(clock_cost_estimation_time), iters, time_clock);
+                std::vector<double> times;
+                int nsamples = static_cast<int>(std::ceil(time_limit / r.elapsed));
+                times.reserve(nsamples);
+                std::generate_n(std::back_inserter(times), nsamples, [time_clock, &r] {
+                    return static_cast<double>((time_clock(r.iterations) / r.iterations).count());
+                });
+                return {
+                    FloatDuration<Clock>(mean(times.begin(), times.end())),
+                    classify_outliers(times.begin(), times.end()),
+                };
+            }
+
+            template <typename Clock>
+            Environment<FloatDuration<Clock>> measure_environment() {
+                static Environment<FloatDuration<Clock>>* env = nullptr;
+                if (env) {
+                    return *env;
+                }
+
+                auto iters = Detail::warmup<Clock>();
+                auto resolution = Detail::estimate_clock_resolution<Clock>(iters);
+                auto cost = Detail::estimate_clock_cost<Clock>(resolution.mean);
+
+                env = new Environment<FloatDuration<Clock>>{ resolution, cost };
+                return *env;
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_estimate_clock.hpp
+// start catch_analyse.hpp
+
+ // Run and analyse one benchmark
+
+
+// start catch_sample_analysis.hpp
+
+// Benchmark results
+
+
+#include <algorithm>
+#include <vector>
+#include <string>
+#include <iterator>
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration>
+        struct SampleAnalysis {
+            std::vector<Duration> samples;
+            Estimate<Duration> mean;
+            Estimate<Duration> standard_deviation;
+            OutlierClassification outliers;
+            double outlier_variance;
+
+            template <typename Duration2>
+            operator SampleAnalysis<Duration2>() const {
+                std::vector<Duration2> samples2;
+                samples2.reserve(samples.size());
+                std::transform(samples.begin(), samples.end(), std::back_inserter(samples2), [](Duration d) { return Duration2(d); });
+                return {
+                    std::move(samples2),
+                    mean,
+                    standard_deviation,
+                    outliers,
+                    outlier_variance,
+                };
+            }
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_sample_analysis.hpp
+#include <algorithm>
+#include <iterator>
+#include <vector>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Duration, typename Iterator>
+            SampleAnalysis<Duration> analyse(const IConfig &cfg, Environment<Duration>, Iterator first, Iterator last) {
+                if (!cfg.benchmarkNoAnalysis()) {
+                    std::vector<double> samples;
+                    samples.reserve(last - first);
+                    std::transform(first, last, std::back_inserter(samples), [](Duration d) { return d.count(); });
+
+                    auto analysis = Catch::Benchmark::Detail::analyse_samples(cfg.benchmarkConfidenceInterval(), cfg.benchmarkResamples(), samples.begin(), samples.end());
+                    auto outliers = Catch::Benchmark::Detail::classify_outliers(samples.begin(), samples.end());
+
+                    auto wrap_estimate = [](Estimate<double> e) {
+                        return Estimate<Duration> {
+                            Duration(e.point),
+                                Duration(e.lower_bound),
+                                Duration(e.upper_bound),
+                                e.confidence_interval,
+                        };
+                    };
+                    std::vector<Duration> samples2;
+                    samples2.reserve(samples.size());
+                    std::transform(samples.begin(), samples.end(), std::back_inserter(samples2), [](double d) { return Duration(d); });
+                    return {
+                        std::move(samples2),
+                        wrap_estimate(analysis.mean),
+                        wrap_estimate(analysis.standard_deviation),
+                        outliers,
+                        analysis.outlier_variance,
+                    };
+                } else {
+                    std::vector<Duration> samples;
+                    samples.reserve(last - first);
+
+                    Duration mean = Duration(0);
+                    int i = 0;
+                    for (auto it = first; it < last; ++it, ++i) {
+                        samples.push_back(Duration(*it));
+                        mean += Duration(*it);
+                    }
+                    mean /= i;
+
+                    return {
+                        std::move(samples),
+                        Estimate<Duration>{mean, mean, mean, 0.0},
+                        Estimate<Duration>{Duration(0), Duration(0), Duration(0), 0.0},
+                        OutlierClassification{},
+                        0.0
+                    };
+                }
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_analyse.hpp
+#include <algorithm>
+#include <functional>
+#include <string>
+#include <vector>
+#include <cmath>
+
+namespace Catch {
+    namespace Benchmark {
+        struct Benchmark {
+            Benchmark(std::string &&name)
+                : name(std::move(name)) {}
+
+            template <class FUN>
+            Benchmark(std::string &&name, FUN &&func)
+                : fun(std::move(func)), name(std::move(name)) {}
+
+            template <typename Clock>
+            ExecutionPlan<FloatDuration<Clock>> prepare(const IConfig &cfg, Environment<FloatDuration<Clock>> env) const {
+                auto min_time = env.clock_resolution.mean * Detail::minimum_ticks;
+                auto run_time = std::max(min_time, std::chrono::duration_cast<decltype(min_time)>(cfg.benchmarkWarmupTime()));
+                auto&& test = Detail::run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(run_time), 1, fun);
+                int new_iters = static_cast<int>(std::ceil(min_time * test.iterations / test.elapsed));
+                return { new_iters, test.elapsed / test.iterations * new_iters * cfg.benchmarkSamples(), fun, std::chrono::duration_cast<FloatDuration<Clock>>(cfg.benchmarkWarmupTime()), Detail::warmup_iterations };
+            }
+
+            template <typename Clock = default_clock>
+            void run() {
+                IConfigPtr cfg = getCurrentContext().getConfig();
+
+                auto env = Detail::measure_environment<Clock>();
+
+                getResultCapture().benchmarkPreparing(name);
+                CATCH_TRY{
+                    auto plan = user_code([&] {
+                        return prepare<Clock>(*cfg, env);
+                    });
+
+                    BenchmarkInfo info {
+                        name,
+                        plan.estimated_duration.count(),
+                        plan.iterations_per_sample,
+                        cfg->benchmarkSamples(),
+                        cfg->benchmarkResamples(),
+                        env.clock_resolution.mean.count(),
+                        env.clock_cost.mean.count()
+                    };
+
+                    getResultCapture().benchmarkStarting(info);
+
+                    auto samples = user_code([&] {
+                        return plan.template run<Clock>(*cfg, env);
+                    });
+
+                    auto analysis = Detail::analyse(*cfg, env, samples.begin(), samples.end());
+                    BenchmarkStats<FloatDuration<Clock>> stats{ info, analysis.samples, analysis.mean, analysis.standard_deviation, analysis.outliers, analysis.outlier_variance };
+                    getResultCapture().benchmarkEnded(stats);
+
+                } CATCH_CATCH_ALL{
+                    if (translateActiveException() != Detail::benchmarkErrorMsg) // benchmark errors have been reported, otherwise rethrow.
+                        std::rethrow_exception(std::current_exception());
+                }
+            }
+
+            // sets lambda to be used in fun *and* executes benchmark!
+            template <typename Fun,
+                typename std::enable_if<!Detail::is_related<Fun, Benchmark>::value, int>::type = 0>
+                Benchmark & operator=(Fun func) {
+                fun = Detail::BenchmarkFunction(func);
+                run();
+                return *this;
+            }
+
+            explicit operator bool() {
+                return true;
+            }
+
+        private:
+            Detail::BenchmarkFunction fun;
+            std::string name;
+        };
+    }
+} // namespace Catch
+
+#define INTERNAL_CATCH_GET_1_ARG(arg1, arg2, ...) arg1
+#define INTERNAL_CATCH_GET_2_ARG(arg1, arg2, ...) arg2
+
+#define INTERNAL_CATCH_BENCHMARK(BenchmarkName, name, benchmarkIndex)\
+    if( Catch::Benchmark::Benchmark BenchmarkName{name} ) \
+        BenchmarkName = [&](int benchmarkIndex)
+
+#define INTERNAL_CATCH_BENCHMARK_ADVANCED(BenchmarkName, name)\
+    if( Catch::Benchmark::Benchmark BenchmarkName{name} ) \
+        BenchmarkName = [&]
+
+// end catch_benchmark.hpp
+// start catch_constructor.hpp
+
+// Constructor and destructor helpers
+
+
+#include <type_traits>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename T, bool Destruct>
+            struct ObjectStorage
+            {
+                using TStorage = typename std::aligned_storage<sizeof(T), std::alignment_of<T>::value>::type;
+
+                ObjectStorage() : data() {}
+
+                ObjectStorage(const ObjectStorage& other)
+                {
+                    new(&data) T(other.stored_object());
+                }
+
+                ObjectStorage(ObjectStorage&& other)
+                {
+                    new(&data) T(std::move(other.stored_object()));
+                }
+
+                ~ObjectStorage() { destruct_on_exit<T>(); }
+
+                template <typename... Args>
+                void construct(Args&&... args)
+                {
+                    new (&data) T(std::forward<Args>(args)...);
+                }
+
+                template <bool AllowManualDestruction = !Destruct>
+                typename std::enable_if<AllowManualDestruction>::type destruct()
+                {
+                    stored_object().~T();
+                }
+
+            private:
+                // If this is a constructor benchmark, destruct the underlying object
+                template <typename U>
+                void destruct_on_exit(typename std::enable_if<Destruct, U>::type* = 0) { destruct<true>(); }
+                // Otherwise, don't
+                template <typename U>
+                void destruct_on_exit(typename std::enable_if<!Destruct, U>::type* = 0) { }
+
+                T& stored_object() {
+                    return *static_cast<T*>(static_cast<void*>(&data));
+                }
+
+                T const& stored_object() const {
+                    return *static_cast<T*>(static_cast<void*>(&data));
+                }
+
+                TStorage data;
+            };
+        }
+
+        template <typename T>
+        using storage_for = Detail::ObjectStorage<T, true>;
+
+        template <typename T>
+        using destructable_object = Detail::ObjectStorage<T, false>;
+    }
+}
+
+// end catch_constructor.hpp
+// end catch_benchmarking_all.hpp
+#endif
+
+#endif // ! CATCH_CONFIG_IMPL_ONLY
+
+#ifdef CATCH_IMPL
+// start catch_impl.hpp
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wweak-vtables"
+#endif
+
+// Keep these here for external reporters
+// start catch_test_case_tracker.h
+
+#include <string>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+namespace TestCaseTracking {
+
+    struct NameAndLocation {
+        std::string name;
+        SourceLineInfo location;
+
+        NameAndLocation( std::string const& _name, SourceLineInfo const& _location );
+    };
+
+    struct ITracker;
+
+    using ITrackerPtr = std::shared_ptr<ITracker>;
+
+    struct ITracker {
+        virtual ~ITracker();
+
+        // static queries
+        virtual NameAndLocation const& nameAndLocation() const = 0;
+
+        // dynamic queries
+        virtual bool isComplete() const = 0; // Successfully completed or failed
+        virtual bool isSuccessfullyCompleted() const = 0;
+        virtual bool isOpen() const = 0; // Started but not complete
+        virtual bool hasChildren() const = 0;
+
+        virtual ITracker& parent() = 0;
+
+        // actions
+        virtual void close() = 0; // Successfully complete
+        virtual void fail() = 0;
+        virtual void markAsNeedingAnotherRun() = 0;
+
+        virtual void addChild( ITrackerPtr const& child ) = 0;
+        virtual ITrackerPtr findChild( NameAndLocation const& nameAndLocation ) = 0;
+        virtual void openChild() = 0;
+
+        // Debug/ checking
+        virtual bool isSectionTracker() const = 0;
+        virtual bool isGeneratorTracker() const = 0;
+    };
+
+    class TrackerContext {
+
+        enum RunState {
+            NotStarted,
+            Executing,
+            CompletedCycle
+        };
+
+        ITrackerPtr m_rootTracker;
+        ITracker* m_currentTracker = nullptr;
+        RunState m_runState = NotStarted;
+
+    public:
+
+        ITracker& startRun();
+        void endRun();
+
+        void startCycle();
+        void completeCycle();
+
+        bool completedCycle() const;
+        ITracker& currentTracker();
+        void setCurrentTracker( ITracker* tracker );
+    };
+
+    class TrackerBase : public ITracker {
+    protected:
+        enum CycleState {
+            NotStarted,
+            Executing,
+            ExecutingChildren,
+            NeedsAnotherRun,
+            CompletedSuccessfully,
+            Failed
+        };
+
+        using Children = std::vector<ITrackerPtr>;
+        NameAndLocation m_nameAndLocation;
+        TrackerContext& m_ctx;
+        ITracker* m_parent;
+        Children m_children;
+        CycleState m_runState = NotStarted;
+
+    public:
+        TrackerBase( NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent );
+
+        NameAndLocation const& nameAndLocation() const override;
+        bool isComplete() const override;
+        bool isSuccessfullyCompleted() const override;
+        bool isOpen() const override;
+        bool hasChildren() const override;
+
+        void addChild( ITrackerPtr const& child ) override;
+
+        ITrackerPtr findChild( NameAndLocation const& nameAndLocation ) override;
+        ITracker& parent() override;
+
+        void openChild() override;
+
+        bool isSectionTracker() const override;
+        bool isGeneratorTracker() const override;
+
+        void open();
+
+        void close() override;
+        void fail() override;
+        void markAsNeedingAnotherRun() override;
+
+    private:
+        void moveToParent();
+        void moveToThis();
+    };
+
+    class SectionTracker : public TrackerBase {
+        std::vector<std::string> m_filters;
+        std::string m_trimmed_name;
+    public:
+        SectionTracker( NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent );
+
+        bool isSectionTracker() const override;
+
+        bool isComplete() const override;
+
+        static SectionTracker& acquire( TrackerContext& ctx, NameAndLocation const& nameAndLocation );
+
+        void tryOpen();
+
+        void addInitialFilters( std::vector<std::string> const& filters );
+        void addNextFilters( std::vector<std::string> const& filters );
+    };
+
+} // namespace TestCaseTracking
+
+using TestCaseTracking::ITracker;
+using TestCaseTracking::TrackerContext;
+using TestCaseTracking::SectionTracker;
+
+} // namespace Catch
+
+// end catch_test_case_tracker.h
+
+// start catch_leak_detector.h
+
+namespace Catch {
+
+    struct LeakDetector {
+        LeakDetector();
+        ~LeakDetector();
+    };
+
+}
+// end catch_leak_detector.h
+// Cpp files will be included in the single-header file here
+// start catch_stats.cpp
+
+// Statistical analysis tools
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+
+#include <cassert>
+#include <random>
+
+#if defined(CATCH_CONFIG_USE_ASYNC)
+#include <future>
+#endif
+
+namespace {
+    double erf_inv(double x) {
+        // Code accompanying the article "Approximating the erfinv function" in GPU Computing Gems, Volume 2
+        double w, p;
+
+        w = -log((1.0 - x) * (1.0 + x));
+
+        if (w < 6.250000) {
+            w = w - 3.125000;
+            p = -3.6444120640178196996e-21;
+            p = -1.685059138182016589e-19 + p * w;
+            p = 1.2858480715256400167e-18 + p * w;
+            p = 1.115787767802518096e-17 + p * w;
+            p = -1.333171662854620906e-16 + p * w;
+            p = 2.0972767875968561637e-17 + p * w;
+            p = 6.6376381343583238325e-15 + p * w;
+            p = -4.0545662729752068639e-14 + p * w;
+            p = -8.1519341976054721522e-14 + p * w;
+            p = 2.6335093153082322977e-12 + p * w;
+            p = -1.2975133253453532498e-11 + p * w;
+            p = -5.4154120542946279317e-11 + p * w;
+            p = 1.051212273321532285e-09 + p * w;
+            p = -4.1126339803469836976e-09 + p * w;
+            p = -2.9070369957882005086e-08 + p * w;
+            p = 4.2347877827932403518e-07 + p * w;
+            p = -1.3654692000834678645e-06 + p * w;
+            p = -1.3882523362786468719e-05 + p * w;
+            p = 0.0001867342080340571352 + p * w;
+            p = -0.00074070253416626697512 + p * w;
+            p = -0.0060336708714301490533 + p * w;
+            p = 0.24015818242558961693 + p * w;
+            p = 1.6536545626831027356 + p * w;
+        } else if (w < 16.000000) {
+            w = sqrt(w) - 3.250000;
+            p = 2.2137376921775787049e-09;
+            p = 9.0756561938885390979e-08 + p * w;
+            p = -2.7517406297064545428e-07 + p * w;
+            p = 1.8239629214389227755e-08 + p * w;
+            p = 1.5027403968909827627e-06 + p * w;
+            p = -4.013867526981545969e-06 + p * w;
+            p = 2.9234449089955446044e-06 + p * w;
+            p = 1.2475304481671778723e-05 + p * w;
+            p = -4.7318229009055733981e-05 + p * w;
+            p = 6.8284851459573175448e-05 + p * w;
+            p = 2.4031110387097893999e-05 + p * w;
+            p = -0.0003550375203628474796 + p * w;
+            p = 0.00095328937973738049703 + p * w;
+            p = -0.0016882755560235047313 + p * w;
+            p = 0.0024914420961078508066 + p * w;
+            p = -0.0037512085075692412107 + p * w;
+            p = 0.005370914553590063617 + p * w;
+            p = 1.0052589676941592334 + p * w;
+            p = 3.0838856104922207635 + p * w;
+        } else {
+            w = sqrt(w) - 5.000000;
+            p = -2.7109920616438573243e-11;
+            p = -2.5556418169965252055e-10 + p * w;
+            p = 1.5076572693500548083e-09 + p * w;
+            p = -3.7894654401267369937e-09 + p * w;
+            p = 7.6157012080783393804e-09 + p * w;
+            p = -1.4960026627149240478e-08 + p * w;
+            p = 2.9147953450901080826e-08 + p * w;
+            p = -6.7711997758452339498e-08 + p * w;
+            p = 2.2900482228026654717e-07 + p * w;
+            p = -9.9298272942317002539e-07 + p * w;
+            p = 4.5260625972231537039e-06 + p * w;
+            p = -1.9681778105531670567e-05 + p * w;
+            p = 7.5995277030017761139e-05 + p * w;
+            p = -0.00021503011930044477347 + p * w;
+            p = -0.00013871931833623122026 + p * w;
+            p = 1.0103004648645343977 + p * w;
+            p = 4.8499064014085844221 + p * w;
+        }
+        return p * x;
+    }
+
+    double standard_deviation(std::vector<double>::iterator first, std::vector<double>::iterator last) {
+        auto m = Catch::Benchmark::Detail::mean(first, last);
+        double variance = std::accumulate(first, last, 0., [m](double a, double b) {
+            double diff = b - m;
+            return a + diff * diff;
+            }) / (last - first);
+            return std::sqrt(variance);
+    }
+
+}
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+
+            double weighted_average_quantile(int k, int q, std::vector<double>::iterator first, std::vector<double>::iterator last) {
+                auto count = last - first;
+                double idx = (count - 1) * k / static_cast<double>(q);
+                int j = static_cast<int>(idx);
+                double g = idx - j;
+                std::nth_element(first, first + j, last);
+                auto xj = first[j];
+                if (g == 0) return xj;
+
+                auto xj1 = *std::min_element(first + (j + 1), last);
+                return xj + g * (xj1 - xj);
+            }
+
+            double erfc_inv(double x) {
+                return erf_inv(1.0 - x);
+            }
+
+            double normal_quantile(double p) {
+                static const double ROOT_TWO = std::sqrt(2.0);
+
+                double result = 0.0;
+                assert(p >= 0 && p <= 1);
+                if (p < 0 || p > 1) {
+                    return result;
+                }
+
+                result = -erfc_inv(2.0 * p);
+                // result *= normal distribution standard deviation (1.0) * sqrt(2)
+                result *= /*sd * */ ROOT_TWO;
+                // result += normal disttribution mean (0)
+                return result;
+            }
+
+            double outlier_variance(Estimate<double> mean, Estimate<double> stddev, int n) {
+                double sb = stddev.point;
+                double mn = mean.point / n;
+                double mg_min = mn / 2.;
+                double sg = std::min(mg_min / 4., sb / std::sqrt(n));
+                double sg2 = sg * sg;
+                double sb2 = sb * sb;
+
+                auto c_max = [n, mn, sb2, sg2](double x) -> double {
+                    double k = mn - x;
+                    double d = k * k;
+                    double nd = n * d;
+                    double k0 = -n * nd;
+                    double k1 = sb2 - n * sg2 + nd;
+                    double det = k1 * k1 - 4 * sg2 * k0;
+                    return (int)(-2. * k0 / (k1 + std::sqrt(det)));
+                };
+
+                auto var_out = [n, sb2, sg2](double c) {
+                    double nc = n - c;
+                    return (nc / n) * (sb2 - nc * sg2);
+                };
+
+                return std::min(var_out(1), var_out(std::min(c_max(0.), c_max(mg_min)))) / sb2;
+            }
+
+            bootstrap_analysis analyse_samples(double confidence_level, int n_resamples, std::vector<double>::iterator first, std::vector<double>::iterator last) {
+                CATCH_INTERNAL_START_WARNINGS_SUPPRESSION
+                CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS
+                static std::random_device entropy;
+                CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+                auto n = static_cast<int>(last - first); // seriously, one can't use integral types without hell in C++
+
+                auto mean = &Detail::mean<std::vector<double>::iterator>;
+                auto stddev = &standard_deviation;
+
+#if defined(CATCH_CONFIG_USE_ASYNC)
+                auto Estimate = [=](double(*f)(std::vector<double>::iterator, std::vector<double>::iterator)) {
+                    auto seed = entropy();
+                    return std::async(std::launch::async, [=] {
+                        std::mt19937 rng(seed);
+                        auto resampled = resample(rng, n_resamples, first, last, f);
+                        return bootstrap(confidence_level, first, last, resampled, f);
+                    });
+                };
+
+                auto mean_future = Estimate(mean);
+                auto stddev_future = Estimate(stddev);
+
+                auto mean_estimate = mean_future.get();
+                auto stddev_estimate = stddev_future.get();
+#else
+                auto Estimate = [=](double(*f)(std::vector<double>::iterator, std::vector<double>::iterator)) {
+                    auto seed = entropy();
+                    std::mt19937 rng(seed);
+                    auto resampled = resample(rng, n_resamples, first, last, f);
+                    return bootstrap(confidence_level, first, last, resampled, f);
+                };
+
+                auto mean_estimate = Estimate(mean);
+                auto stddev_estimate = Estimate(stddev);
+#endif // CATCH_USE_ASYNC
+
+                double outlier_variance = Detail::outlier_variance(mean_estimate, stddev_estimate, n);
+
+                return { mean_estimate, stddev_estimate, outlier_variance };
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+// end catch_stats.cpp
+// start catch_approx.cpp
+
+#include <cmath>
+#include <limits>
+
+namespace {
+
+// Performs equivalent check of std::fabs(lhs - rhs) <= margin
+// But without the subtraction to allow for INFINITY in comparison
+bool marginComparison(double lhs, double rhs, double margin) {
+    return (lhs + margin >= rhs) && (rhs + margin >= lhs);
+}
+
+}
+
+namespace Catch {
+namespace Detail {
+
+    Approx::Approx ( double value )
+    :   m_epsilon( std::numeric_limits<float>::epsilon()*100 ),
+        m_margin( 0.0 ),
+        m_scale( 0.0 ),
+        m_value( value )
+    {}
+
+    Approx Approx::custom() {
+        return Approx( 0 );
+    }
+
+    Approx Approx::operator-() const {
+        auto temp(*this);
+        temp.m_value = -temp.m_value;
+        return temp;
+    }
+
+    std::string Approx::toString() const {
+        ReusableStringStream rss;
+        rss << "Approx( " << ::Catch::Detail::stringify( m_value ) << " )";
+        return rss.str();
+    }
+
+    bool Approx::equalityComparisonImpl(const double other) const {
+        // First try with fixed margin, then compute margin based on epsilon, scale and Approx's value
+        // Thanks to Richard Harris for his help refining the scaled margin value
+        return marginComparison(m_value, other, m_margin)
+            || marginComparison(m_value, other, m_epsilon * (m_scale + std::fabs(std::isinf(m_value)? 0 : m_value)));
+    }
+
+    void Approx::setMargin(double newMargin) {
+        CATCH_ENFORCE(newMargin >= 0,
+            "Invalid Approx::margin: " << newMargin << '.'
+            << " Approx::Margin has to be non-negative.");
+        m_margin = newMargin;
+    }
+
+    void Approx::setEpsilon(double newEpsilon) {
+        CATCH_ENFORCE(newEpsilon >= 0 && newEpsilon <= 1.0,
+            "Invalid Approx::epsilon: " << newEpsilon << '.'
+            << " Approx::epsilon has to be in [0, 1]");
+        m_epsilon = newEpsilon;
+    }
+
+} // end namespace Detail
+
+namespace literals {
+    Detail::Approx operator "" _a(long double val) {
+        return Detail::Approx(val);
+    }
+    Detail::Approx operator "" _a(unsigned long long val) {
+        return Detail::Approx(val);
+    }
+} // end namespace literals
+
+std::string StringMaker<Catch::Detail::Approx>::convert(Catch::Detail::Approx const& value) {
+    return value.toString();
+}
+
+} // end namespace Catch
+// end catch_approx.cpp
+// start catch_assertionhandler.cpp
+
+// start catch_debugger.h
+
+namespace Catch {
+    bool isDebuggerActive();
+}
+
+#ifdef CATCH_PLATFORM_MAC
+
+    #define CATCH_TRAP() __asm__("int $3\n" : : ) /* NOLINT */
+
+#elif defined(CATCH_PLATFORM_IPHONE)
+
+    // use inline assembler
+    #if defined(__i386__) || defined(__x86_64__)
+        #define CATCH_TRAP()  __asm__("int $3")
+    #elif defined(__aarch64__)
+        #define CATCH_TRAP()  __asm__(".inst 0xd4200000")
+    #elif defined(__arm__) && !defined(__thumb__)
+        #define CATCH_TRAP()  __asm__(".inst 0xe7f001f0")
+    #elif defined(__arm__) &&  defined(__thumb__)
+        #define CATCH_TRAP()  __asm__(".inst 0xde01")
+    #endif
+
+#elif defined(CATCH_PLATFORM_LINUX)
+    // If we can use inline assembler, do it because this allows us to break
+    // directly at the location of the failing check instead of breaking inside
+    // raise() called from it, i.e. one stack frame below.
+    #if defined(__GNUC__) && (defined(__i386) || defined(__x86_64))
+        #define CATCH_TRAP() asm volatile ("int $3") /* NOLINT */
+    #else // Fall back to the generic way.
+        #include <signal.h>
+
+        #define CATCH_TRAP() raise(SIGTRAP)
+    #endif
+#elif defined(_MSC_VER)
+    #define CATCH_TRAP() __debugbreak()
+#elif defined(__MINGW32__)
+    extern "C" __declspec(dllimport) void __stdcall DebugBreak();
+    #define CATCH_TRAP() DebugBreak()
+#endif
+
+#ifndef CATCH_BREAK_INTO_DEBUGGER
+    #ifdef CATCH_TRAP
+        #define CATCH_BREAK_INTO_DEBUGGER() []{ if( Catch::isDebuggerActive() ) { CATCH_TRAP(); } }()
+    #else
+        #define CATCH_BREAK_INTO_DEBUGGER() []{}()
+    #endif
+#endif
+
+// end catch_debugger.h
+// start catch_run_context.h
+
+// start catch_fatal_condition.h
+
+// start catch_windows_h_proxy.h
+
+
+#if defined(CATCH_PLATFORM_WINDOWS)
+
+#if !defined(NOMINMAX) && !defined(CATCH_CONFIG_NO_NOMINMAX)
+#  define CATCH_DEFINED_NOMINMAX
+#  define NOMINMAX
+#endif
+#if !defined(WIN32_LEAN_AND_MEAN) && !defined(CATCH_CONFIG_NO_WIN32_LEAN_AND_MEAN)
+#  define CATCH_DEFINED_WIN32_LEAN_AND_MEAN
+#  define WIN32_LEAN_AND_MEAN
+#endif
+
+#ifdef __AFXDLL
+#include <AfxWin.h>
+#else
+#include <windows.h>
+#endif
+
+#ifdef CATCH_DEFINED_NOMINMAX
+#  undef NOMINMAX
+#endif
+#ifdef CATCH_DEFINED_WIN32_LEAN_AND_MEAN
+#  undef WIN32_LEAN_AND_MEAN
+#endif
+
+#endif // defined(CATCH_PLATFORM_WINDOWS)
+
+// end catch_windows_h_proxy.h
+#if defined( CATCH_CONFIG_WINDOWS_SEH )
+
+namespace Catch {
+
+    struct FatalConditionHandler {
+
+        static LONG CALLBACK handleVectoredException(PEXCEPTION_POINTERS ExceptionInfo);
+        FatalConditionHandler();
+        static void reset();
+        ~FatalConditionHandler();
+
+    private:
+        static bool isSet;
+        static ULONG guaranteeSize;
+        static PVOID exceptionHandlerHandle;
+    };
+
+} // namespace Catch
+
+#elif defined ( CATCH_CONFIG_POSIX_SIGNALS )
+
+#include <signal.h>
+
+namespace Catch {
+
+    struct FatalConditionHandler {
+
+        static bool isSet;
+        static struct sigaction oldSigActions[];
+        static stack_t oldSigStack;
+        static char altStackMem[];
+
+        static void handleSignal( int sig );
+
+        FatalConditionHandler();
+        ~FatalConditionHandler();
+        static void reset();
+    };
+
+} // namespace Catch
+
+#else
+
+namespace Catch {
+    struct FatalConditionHandler {
+        void reset();
+    };
+}
+
+#endif
+
+// end catch_fatal_condition.h
+#include <string>
+
+namespace Catch {
+
+    struct IMutableContext;
+
+    ///////////////////////////////////////////////////////////////////////////
+
+    class RunContext : public IResultCapture, public IRunner {
+
+    public:
+        RunContext( RunContext const& ) = delete;
+        RunContext& operator =( RunContext const& ) = delete;
+
+        explicit RunContext( IConfigPtr const& _config, IStreamingReporterPtr&& reporter );
+
+        ~RunContext() override;
+
+        void testGroupStarting( std::string const& testSpec, std::size_t groupIndex, std::size_t groupsCount );
+        void testGroupEnded( std::string const& testSpec, Totals const& totals, std::size_t groupIndex, std::size_t groupsCount );
+
+        Totals runTest(TestCase const& testCase);
+
+        IConfigPtr config() const;
+        IStreamingReporter& reporter() const;
+
+    public: // IResultCapture
+
+        // Assertion handlers
+        void handleExpr
+                (   AssertionInfo const& info,
+                    ITransientExpression const& expr,
+                    AssertionReaction& reaction ) override;
+        void handleMessage
+                (   AssertionInfo const& info,
+                    ResultWas::OfType resultType,
+                    StringRef const& message,
+                    AssertionReaction& reaction ) override;
+        void handleUnexpectedExceptionNotThrown
+                (   AssertionInfo const& info,
+                    AssertionReaction& reaction ) override;
+        void handleUnexpectedInflightException
+                (   AssertionInfo const& info,
+                    std::string const& message,
+                    AssertionReaction& reaction ) override;
+        void handleIncomplete
+                (   AssertionInfo const& info ) override;
+        void handleNonExpr
+                (   AssertionInfo const &info,
+                    ResultWas::OfType resultType,
+                    AssertionReaction &reaction ) override;
+
+        bool sectionStarted( SectionInfo const& sectionInfo, Counts& assertions ) override;
+
+        void sectionEnded( SectionEndInfo const& endInfo ) override;
+        void sectionEndedEarly( SectionEndInfo const& endInfo ) override;
+
+        auto acquireGeneratorTracker( SourceLineInfo const& lineInfo ) -> IGeneratorTracker& override;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        void benchmarkPreparing( std::string const& name ) override;
+        void benchmarkStarting( BenchmarkInfo const& info ) override;
+        void benchmarkEnded( BenchmarkStats<> const& stats ) override;
+        void benchmarkFailed( std::string const& error ) override;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        void pushScopedMessage( MessageInfo const& message ) override;
+        void popScopedMessage( MessageInfo const& message ) override;
+
+        void emplaceUnscopedMessage( MessageBuilder const& builder ) override;
+
+        std::string getCurrentTestName() const override;
+
+        const AssertionResult* getLastResult() const override;
+
+        void exceptionEarlyReported() override;
+
+        void handleFatalErrorCondition( StringRef message ) override;
+
+        bool lastAssertionPassed() override;
+
+        void assertionPassed() override;
+
+    public:
+        // !TBD We need to do this another way!
+        bool aborting() const final;
+
+    private:
+
+        void runCurrentTest( std::string& redirectedCout, std::string& redirectedCerr );
+        void invokeActiveTestCase();
+
+        void resetAssertionInfo();
+        bool testForMissingAssertions( Counts& assertions );
+
+        void assertionEnded( AssertionResult const& result );
+        void reportExpr
+                (   AssertionInfo const &info,
+                    ResultWas::OfType resultType,
+                    ITransientExpression const *expr,
+                    bool negated );
+
+        void populateReaction( AssertionReaction& reaction );
+
+    private:
+
+        void handleUnfinishedSections();
+
+        TestRunInfo m_runInfo;
+        IMutableContext& m_context;
+        TestCase const* m_activeTestCase = nullptr;
+        ITracker* m_testCaseTracker = nullptr;
+        Option<AssertionResult> m_lastResult;
+
+        IConfigPtr m_config;
+        Totals m_totals;
+        IStreamingReporterPtr m_reporter;
+        std::vector<MessageInfo> m_messages;
+        std::vector<ScopedMessage> m_messageScopes; /* Keeps owners of so-called unscoped messages. */
+        AssertionInfo m_lastAssertionInfo;
+        std::vector<SectionEndInfo> m_unfinishedSections;
+        std::vector<ITracker*> m_activeSections;
+        TrackerContext m_trackerContext;
+        bool m_lastAssertionPassed = false;
+        bool m_shouldReportUnexpected = true;
+        bool m_includeSuccessfulResults;
+    };
+
+    void seedRng(IConfig const& config);
+    unsigned int rngSeed();
+} // end namespace Catch
+
+// end catch_run_context.h
+namespace Catch {
+
+    namespace {
+        auto operator <<( std::ostream& os, ITransientExpression const& expr ) -> std::ostream& {
+            expr.streamReconstructedExpression( os );
+            return os;
+        }
+    }
+
+    LazyExpression::LazyExpression( bool isNegated )
+    :   m_isNegated( isNegated )
+    {}
+
+    LazyExpression::LazyExpression( LazyExpression const& other ) : m_isNegated( other.m_isNegated ) {}
+
+    LazyExpression::operator bool() const {
+        return m_transientExpression != nullptr;
+    }
+
+    auto operator << ( std::ostream& os, LazyExpression const& lazyExpr ) -> std::ostream& {
+        if( lazyExpr.m_isNegated )
+            os << "!";
+
+        if( lazyExpr ) {
+            if( lazyExpr.m_isNegated && lazyExpr.m_transientExpression->isBinaryExpression() )
+                os << "(" << *lazyExpr.m_transientExpression << ")";
+            else
+                os << *lazyExpr.m_transientExpression;
+        }
+        else {
+            os << "{** error - unchecked empty expression requested **}";
+        }
+        return os;
+    }
+
+    AssertionHandler::AssertionHandler
+        (   StringRef const& macroName,
+            SourceLineInfo const& lineInfo,
+            StringRef capturedExpression,
+            ResultDisposition::Flags resultDisposition )
+    :   m_assertionInfo{ macroName, lineInfo, capturedExpression, resultDisposition },
+        m_resultCapture( getResultCapture() )
+    {}
+
+    void AssertionHandler::handleExpr( ITransientExpression const& expr ) {
+        m_resultCapture.handleExpr( m_assertionInfo, expr, m_reaction );
+    }
+    void AssertionHandler::handleMessage(ResultWas::OfType resultType, StringRef const& message) {
+        m_resultCapture.handleMessage( m_assertionInfo, resultType, message, m_reaction );
+    }
+
+    auto AssertionHandler::allowThrows() const -> bool {
+        return getCurrentContext().getConfig()->allowThrows();
+    }
+
+    void AssertionHandler::complete() {
+        setCompleted();
+        if( m_reaction.shouldDebugBreak ) {
+
+            // If you find your debugger stopping you here then go one level up on the
+            // call-stack for the code that caused it (typically a failed assertion)
+
+            // (To go back to the test and change execution, jump over the throw, next)
+            CATCH_BREAK_INTO_DEBUGGER();
+        }
+        if (m_reaction.shouldThrow) {
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+            throw Catch::TestFailureException();
+#else
+            CATCH_ERROR( "Test failure requires aborting test!" );
+#endif
+        }
+    }
+    void AssertionHandler::setCompleted() {
+        m_completed = true;
+    }
+
+    void AssertionHandler::handleUnexpectedInflightException() {
+        m_resultCapture.handleUnexpectedInflightException( m_assertionInfo, Catch::translateActiveException(), m_reaction );
+    }
+
+    void AssertionHandler::handleExceptionThrownAsExpected() {
+        m_resultCapture.handleNonExpr(m_assertionInfo, ResultWas::Ok, m_reaction);
+    }
+    void AssertionHandler::handleExceptionNotThrownAsExpected() {
+        m_resultCapture.handleNonExpr(m_assertionInfo, ResultWas::Ok, m_reaction);
+    }
+
+    void AssertionHandler::handleUnexpectedExceptionNotThrown() {
+        m_resultCapture.handleUnexpectedExceptionNotThrown( m_assertionInfo, m_reaction );
+    }
+
+    void AssertionHandler::handleThrowingCallSkipped() {
+        m_resultCapture.handleNonExpr(m_assertionInfo, ResultWas::Ok, m_reaction);
+    }
+
+    // This is the overload that takes a string and infers the Equals matcher from it
+    // The more general overload, that takes any string matcher, is in catch_capture_matchers.cpp
+    void handleExceptionMatchExpr( AssertionHandler& handler, std::string const& str, StringRef const& matcherString  ) {
+        handleExceptionMatchExpr( handler, Matchers::Equals( str ), matcherString );
+    }
+
+} // namespace Catch
+// end catch_assertionhandler.cpp
+// start catch_assertionresult.cpp
+
+namespace Catch {
+    AssertionResultData::AssertionResultData(ResultWas::OfType _resultType, LazyExpression const & _lazyExpression):
+        lazyExpression(_lazyExpression),
+        resultType(_resultType) {}
+
+    std::string AssertionResultData::reconstructExpression() const {
+
+        if( reconstructedExpression.empty() ) {
+            if( lazyExpression ) {
+                ReusableStringStream rss;
+                rss << lazyExpression;
+                reconstructedExpression = rss.str();
+            }
+        }
+        return reconstructedExpression;
+    }
+
+    AssertionResult::AssertionResult( AssertionInfo const& info, AssertionResultData const& data )
+    :   m_info( info ),
+        m_resultData( data )
+    {}
+
+    // Result was a success
+    bool AssertionResult::succeeded() const {
+        return Catch::isOk( m_resultData.resultType );
+    }
+
+    // Result was a success, or failure is suppressed
+    bool AssertionResult::isOk() const {
+        return Catch::isOk( m_resultData.resultType ) || shouldSuppressFailure( m_info.resultDisposition );
+    }
+
+    ResultWas::OfType AssertionResult::getResultType() const {
+        return m_resultData.resultType;
+    }
+
+    bool AssertionResult::hasExpression() const {
+        return !m_info.capturedExpression.empty();
+    }
+
+    bool AssertionResult::hasMessage() const {
+        return !m_resultData.message.empty();
+    }
+
+    std::string AssertionResult::getExpression() const {
+        // Possibly overallocating by 3 characters should be basically free
+        std::string expr; expr.reserve(m_info.capturedExpression.size() + 3);
+        if (isFalseTest(m_info.resultDisposition)) {
+            expr += "!(";
+        }
+        expr += m_info.capturedExpression;
+        if (isFalseTest(m_info.resultDisposition)) {
+            expr += ')';
+        }
+        return expr;
+    }
+
+    std::string AssertionResult::getExpressionInMacro() const {
+        std::string expr;
+        if( m_info.macroName.empty() )
+            expr = static_cast<std::string>(m_info.capturedExpression);
+        else {
+            expr.reserve( m_info.macroName.size() + m_info.capturedExpression.size() + 4 );
+            expr += m_info.macroName;
+            expr += "( ";
+            expr += m_info.capturedExpression;
+            expr += " )";
+        }
+        return expr;
+    }
+
+    bool AssertionResult::hasExpandedExpression() const {
+        return hasExpression() && getExpandedExpression() != getExpression();
+    }
+
+    std::string AssertionResult::getExpandedExpression() const {
+        std::string expr = m_resultData.reconstructExpression();
+        return expr.empty()
+                ? getExpression()
+                : expr;
+    }
+
+    std::string AssertionResult::getMessage() const {
+        return m_resultData.message;
+    }
+    SourceLineInfo AssertionResult::getSourceInfo() const {
+        return m_info.lineInfo;
+    }
+
+    StringRef AssertionResult::getTestMacroName() const {
+        return m_info.macroName;
+    }
+
+} // end namespace Catch
+// end catch_assertionresult.cpp
+// start catch_capture_matchers.cpp
+
+namespace Catch {
+
+    using StringMatcher = Matchers::Impl::MatcherBase<std::string>;
+
+    // This is the general overload that takes a any string matcher
+    // There is another overload, in catch_assertionhandler.h/.cpp, that only takes a string and infers
+    // the Equals matcher (so the header does not mention matchers)
+    void handleExceptionMatchExpr( AssertionHandler& handler, StringMatcher const& matcher, StringRef const& matcherString  ) {
+        std::string exceptionMessage = Catch::translateActiveException();
+        MatchExpr<std::string, StringMatcher const&> expr( exceptionMessage, matcher, matcherString );
+        handler.handleExpr( expr );
+    }
+
+} // namespace Catch
+// end catch_capture_matchers.cpp
+// start catch_commandline.cpp
+
+// start catch_commandline.h
+
+// start catch_clara.h
+
+// Use Catch's value for console width (store Clara's off to the side, if present)
+#ifdef CLARA_CONFIG_CONSOLE_WIDTH
+#define CATCH_TEMP_CLARA_CONFIG_CONSOLE_WIDTH CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH
+#undef CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH
+#endif
+#define CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH CATCH_CONFIG_CONSOLE_WIDTH-1
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wweak-vtables"
+#pragma clang diagnostic ignored "-Wexit-time-destructors"
+#pragma clang diagnostic ignored "-Wshadow"
+#endif
+
+// start clara.hpp
+// Copyright 2017 Two Blue Cubes Ltd. All rights reserved.
+//
+// Distributed under the Boost Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// See https://github.com/philsquared/Clara for more details
+
+// Clara v1.1.5
+
+
+#ifndef CATCH_CLARA_CONFIG_CONSOLE_WIDTH
+#define CATCH_CLARA_CONFIG_CONSOLE_WIDTH 80
+#endif
+
+#ifndef CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH
+#define CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH CATCH_CLARA_CONFIG_CONSOLE_WIDTH
+#endif
+
+#ifndef CLARA_CONFIG_OPTIONAL_TYPE
+#ifdef __has_include
+#if __has_include(<optional>) && __cplusplus >= 201703L
+#include <optional>
+#define CLARA_CONFIG_OPTIONAL_TYPE std::optional
+#endif
+#endif
+#endif
+
+// ----------- #included from clara_textflow.hpp -----------
+
+// TextFlowCpp
+//
+// A single-header library for wrapping and laying out basic text, by Phil Nash
+//
+// Distributed under the Boost Software License, Version 1.0. (See accompanying
+// file LICENSE.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// This project is hosted at https://github.com/philsquared/textflowcpp
+
+
+#include <cassert>
+#include <ostream>
+#include <sstream>
+#include <vector>
+
+#ifndef CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH
+#define CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH 80
+#endif
+
+namespace Catch {
+namespace clara {
+namespace TextFlow {
+
+inline auto isWhitespace(char c) -> bool {
+	static std::string chars = " \t\n\r";
+	return chars.find(c) != std::string::npos;
+}
+inline auto isBreakableBefore(char c) -> bool {
+	static std::string chars = "[({<|";
+	return chars.find(c) != std::string::npos;
+}
+inline auto isBreakableAfter(char c) -> bool {
+	static std::string chars = "])}>.,:;*+-=&/\\";
+	return chars.find(c) != std::string::npos;
+}
+
+class Columns;
+
+class Column {
+	std::vector<std::string> m_strings;
+	size_t m_width = CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH;
+	size_t m_indent = 0;
+	size_t m_initialIndent = std::string::npos;
+
+public:
+	class iterator {
+		friend Column;
+
+		Column const& m_column;
+		size_t m_stringIndex = 0;
+		size_t m_pos = 0;
+
+		size_t m_len = 0;
+		size_t m_end = 0;
+		bool m_suffix = false;
+
+		iterator(Column const& column, size_t stringIndex)
+			: m_column(column),
+			m_stringIndex(stringIndex) {}
+
+		auto line() const -> std::string const& { return m_column.m_strings[m_stringIndex]; }
+
+		auto isBoundary(size_t at) const -> bool {
+			assert(at > 0);
+			assert(at <= line().size());
+
+			return at == line().size() ||
+				(isWhitespace(line()[at]) && !isWhitespace(line()[at - 1])) ||
+				isBreakableBefore(line()[at]) ||
+				isBreakableAfter(line()[at - 1]);
+		}
+
+		void calcLength() {
+			assert(m_stringIndex < m_column.m_strings.size());
+
+			m_suffix = false;
+			auto width = m_column.m_width - indent();
+			m_end = m_pos;
+			if (line()[m_pos] == '\n') {
+				++m_end;
+			}
+			while (m_end < line().size() && line()[m_end] != '\n')
+				++m_end;
+
+			if (m_end < m_pos + width) {
+				m_len = m_end - m_pos;
+			} else {
+				size_t len = width;
+				while (len > 0 && !isBoundary(m_pos + len))
+					--len;
+				while (len > 0 && isWhitespace(line()[m_pos + len - 1]))
+					--len;
+
+				if (len > 0) {
+					m_len = len;
+				} else {
+					m_suffix = true;
+					m_len = width - 1;
+				}
+			}
+		}
+
+		auto indent() const -> size_t {
+			auto initial = m_pos == 0 && m_stringIndex == 0 ? m_column.m_initialIndent : std::string::npos;
+			return initial == std::string::npos ? m_column.m_indent : initial;
+		}
+
+		auto addIndentAndSuffix(std::string const &plain) const -> std::string {
+			return std::string(indent(), ' ') + (m_suffix ? plain + "-" : plain);
+		}
+
+	public:
+		using difference_type = std::ptrdiff_t;
+		using value_type = std::string;
+		using pointer = value_type * ;
+		using reference = value_type & ;
+		using iterator_category = std::forward_iterator_tag;
+
+		explicit iterator(Column const& column) : m_column(column) {
+			assert(m_column.m_width > m_column.m_indent);
+			assert(m_column.m_initialIndent == std::string::npos || m_column.m_width > m_column.m_initialIndent);
+			calcLength();
+			if (m_len == 0)
+				m_stringIndex++; // Empty string
+		}
+
+		auto operator *() const -> std::string {
+			assert(m_stringIndex < m_column.m_strings.size());
+			assert(m_pos <= m_end);
+			return addIndentAndSuffix(line().substr(m_pos, m_len));
+		}
+
+		auto operator ++() -> iterator& {
+			m_pos += m_len;
+			if (m_pos < line().size() && line()[m_pos] == '\n')
+				m_pos += 1;
+			else
+				while (m_pos < line().size() && isWhitespace(line()[m_pos]))
+					++m_pos;
+
+			if (m_pos == line().size()) {
+				m_pos = 0;
+				++m_stringIndex;
+			}
+			if (m_stringIndex < m_column.m_strings.size())
+				calcLength();
+			return *this;
+		}
+		auto operator ++(int) -> iterator {
+			iterator prev(*this);
+			operator++();
+			return prev;
+		}
+
+		auto operator ==(iterator const& other) const -> bool {
+			return
+				m_pos == other.m_pos &&
+				m_stringIndex == other.m_stringIndex &&
+				&m_column == &other.m_column;
+		}
+		auto operator !=(iterator const& other) const -> bool {
+			return !operator==(other);
+		}
+	};
+	using const_iterator = iterator;
+
+	explicit Column(std::string const& text) { m_strings.push_back(text); }
+
+	auto width(size_t newWidth) -> Column& {
+		assert(newWidth > 0);
+		m_width = newWidth;
+		return *this;
+	}
+	auto indent(size_t newIndent) -> Column& {
+		m_indent = newIndent;
+		return *this;
+	}
+	auto initialIndent(size_t newIndent) -> Column& {
+		m_initialIndent = newIndent;
+		return *this;
+	}
+
+	auto width() const -> size_t { return m_width; }
+	auto begin() const -> iterator { return iterator(*this); }
+	auto end() const -> iterator { return { *this, m_strings.size() }; }
+
+	inline friend std::ostream& operator << (std::ostream& os, Column const& col) {
+		bool first = true;
+		for (auto line : col) {
+			if (first)
+				first = false;
+			else
+				os << "\n";
+			os << line;
+		}
+		return os;
+	}
+
+	auto operator + (Column const& other)->Columns;
+
+	auto toString() const -> std::string {
+		std::ostringstream oss;
+		oss << *this;
+		return oss.str();
+	}
+};
+
+class Spacer : public Column {
+
+public:
+	explicit Spacer(size_t spaceWidth) : Column("") {
+		width(spaceWidth);
+	}
+};
+
+class Columns {
+	std::vector<Column> m_columns;
+
+public:
+
+	class iterator {
+		friend Columns;
+		struct EndTag {};
+
+		std::vector<Column> const& m_columns;
+		std::vector<Column::iterator> m_iterators;
+		size_t m_activeIterators;
+
+		iterator(Columns const& columns, EndTag)
+			: m_columns(columns.m_columns),
+			m_activeIterators(0) {
+			m_iterators.reserve(m_columns.size());
+
+			for (auto const& col : m_columns)
+				m_iterators.push_back(col.end());
+		}
+
+	public:
+		using difference_type = std::ptrdiff_t;
+		using value_type = std::string;
+		using pointer = value_type * ;
+		using reference = value_type & ;
+		using iterator_category = std::forward_iterator_tag;
+
+		explicit iterator(Columns const& columns)
+			: m_columns(columns.m_columns),
+			m_activeIterators(m_columns.size()) {
+			m_iterators.reserve(m_columns.size());
+
+			for (auto const& col : m_columns)
+				m_iterators.push_back(col.begin());
+		}
+
+		auto operator ==(iterator const& other) const -> bool {
+			return m_iterators == other.m_iterators;
+		}
+		auto operator !=(iterator const& other) const -> bool {
+			return m_iterators != other.m_iterators;
+		}
+		auto operator *() const -> std::string {
+			std::string row, padding;
+
+			for (size_t i = 0; i < m_columns.size(); ++i) {
+				auto width = m_columns[i].width();
+				if (m_iterators[i] != m_columns[i].end()) {
+					std::string col = *m_iterators[i];
+					row += padding + col;
+					if (col.size() < width)
+						padding = std::string(width - col.size(), ' ');
+					else
+						padding = "";
+				} else {
+					padding += std::string(width, ' ');
+				}
+			}
+			return row;
+		}
+		auto operator ++() -> iterator& {
+			for (size_t i = 0; i < m_columns.size(); ++i) {
+				if (m_iterators[i] != m_columns[i].end())
+					++m_iterators[i];
+			}
+			return *this;
+		}
+		auto operator ++(int) -> iterator {
+			iterator prev(*this);
+			operator++();
+			return prev;
+		}
+	};
+	using const_iterator = iterator;
+
+	auto begin() const -> iterator { return iterator(*this); }
+	auto end() const -> iterator { return { *this, iterator::EndTag() }; }
+
+	auto operator += (Column const& col) -> Columns& {
+		m_columns.push_back(col);
+		return *this;
+	}
+	auto operator + (Column const& col) -> Columns {
+		Columns combined = *this;
+		combined += col;
+		return combined;
+	}
+
+	inline friend std::ostream& operator << (std::ostream& os, Columns const& cols) {
+
+		bool first = true;
+		for (auto line : cols) {
+			if (first)
+				first = false;
+			else
+				os << "\n";
+			os << line;
+		}
+		return os;
+	}
+
+	auto toString() const -> std::string {
+		std::ostringstream oss;
+		oss << *this;
+		return oss.str();
+	}
+};
+
+inline auto Column::operator + (Column const& other) -> Columns {
+	Columns cols;
+	cols += *this;
+	cols += other;
+	return cols;
+}
+}
+
+}
+}
+
+// ----------- end of #include from clara_textflow.hpp -----------
+// ........... back in clara.hpp
+
+#include <cctype>
+#include <string>
+#include <memory>
+#include <set>
+#include <algorithm>
+
+#if !defined(CATCH_PLATFORM_WINDOWS) && ( defined(WIN32) || defined(__WIN32__) || defined(_WIN32) || defined(_MSC_VER) )
+#define CATCH_PLATFORM_WINDOWS
+#endif
+
+namespace Catch { namespace clara {
+namespace detail {
+
+    // Traits for extracting arg and return type of lambdas (for single argument lambdas)
+    template<typename L>
+    struct UnaryLambdaTraits : UnaryLambdaTraits<decltype( &L::operator() )> {};
+
+    template<typename ClassT, typename ReturnT, typename... Args>
+    struct UnaryLambdaTraits<ReturnT( ClassT::* )( Args... ) const> {
+        static const bool isValid = false;
+    };
+
+    template<typename ClassT, typename ReturnT, typename ArgT>
+    struct UnaryLambdaTraits<ReturnT( ClassT::* )( ArgT ) const> {
+        static const bool isValid = true;
+        using ArgType = typename std::remove_const<typename std::remove_reference<ArgT>::type>::type;
+        using ReturnType = ReturnT;
+    };
+
+    class TokenStream;
+
+    // Transport for raw args (copied from main args, or supplied via init list for testing)
+    class Args {
+        friend TokenStream;
+        std::string m_exeName;
+        std::vector<std::string> m_args;
+
+    public:
+        Args( int argc, char const* const* argv )
+            : m_exeName(argv[0]),
+              m_args(argv + 1, argv + argc) {}
+
+        Args( std::initializer_list<std::string> args )
+        :   m_exeName( *args.begin() ),
+            m_args( args.begin()+1, args.end() )
+        {}
+
+        auto exeName() const -> std::string {
+            return m_exeName;
+        }
+    };
+
+    // Wraps a token coming from a token stream. These may not directly correspond to strings as a single string
+    // may encode an option + its argument if the : or = form is used
+    enum class TokenType {
+        Option, Argument
+    };
+    struct Token {
+        TokenType type;
+        std::string token;
+    };
+
+    inline auto isOptPrefix( char c ) -> bool {
+        return c == '-'
+#ifdef CATCH_PLATFORM_WINDOWS
+            || c == '/'
+#endif
+        ;
+    }
+
+    // Abstracts iterators into args as a stream of tokens, with option arguments uniformly handled
+    class TokenStream {
+        using Iterator = std::vector<std::string>::const_iterator;
+        Iterator it;
+        Iterator itEnd;
+        std::vector<Token> m_tokenBuffer;
+
+        void loadBuffer() {
+            m_tokenBuffer.resize( 0 );
+
+            // Skip any empty strings
+            while( it != itEnd && it->empty() )
+                ++it;
+
+            if( it != itEnd ) {
+                auto const &next = *it;
+                if( isOptPrefix( next[0] ) ) {
+                    auto delimiterPos = next.find_first_of( " :=" );
+                    if( delimiterPos != std::string::npos ) {
+                        m_tokenBuffer.push_back( { TokenType::Option, next.substr( 0, delimiterPos ) } );
+                        m_tokenBuffer.push_back( { TokenType::Argument, next.substr( delimiterPos + 1 ) } );
+                    } else {
+                        if( next[1] != '-' && next.size() > 2 ) {
+                            std::string opt = "- ";
+                            for( size_t i = 1; i < next.size(); ++i ) {
+                                opt[1] = next[i];
+                                m_tokenBuffer.push_back( { TokenType::Option, opt } );
+                            }
+                        } else {
+                            m_tokenBuffer.push_back( { TokenType::Option, next } );
+                        }
+                    }
+                } else {
+                    m_tokenBuffer.push_back( { TokenType::Argument, next } );
+                }
+            }
+        }
+
+    public:
+        explicit TokenStream( Args const &args ) : TokenStream( args.m_args.begin(), args.m_args.end() ) {}
+
+        TokenStream( Iterator it, Iterator itEnd ) : it( it ), itEnd( itEnd ) {
+            loadBuffer();
+        }
+
+        explicit operator bool() const {
+            return !m_tokenBuffer.empty() || it != itEnd;
+        }
+
+        auto count() const -> size_t { return m_tokenBuffer.size() + (itEnd - it); }
+
+        auto operator*() const -> Token {
+            assert( !m_tokenBuffer.empty() );
+            return m_tokenBuffer.front();
+        }
+
+        auto operator->() const -> Token const * {
+            assert( !m_tokenBuffer.empty() );
+            return &m_tokenBuffer.front();
+        }
+
+        auto operator++() -> TokenStream & {
+            if( m_tokenBuffer.size() >= 2 ) {
+                m_tokenBuffer.erase( m_tokenBuffer.begin() );
+            } else {
+                if( it != itEnd )
+                    ++it;
+                loadBuffer();
+            }
+            return *this;
+        }
+    };
+
+    class ResultBase {
+    public:
+        enum Type {
+            Ok, LogicError, RuntimeError
+        };
+
+    protected:
+        ResultBase( Type type ) : m_type( type ) {}
+        virtual ~ResultBase() = default;
+
+        virtual void enforceOk() const = 0;
+
+        Type m_type;
+    };
+
+    template<typename T>
+    class ResultValueBase : public ResultBase {
+    public:
+        auto value() const -> T const & {
+            enforceOk();
+            return m_value;
+        }
+
+    protected:
+        ResultValueBase( Type type ) : ResultBase( type ) {}
+
+        ResultValueBase( ResultValueBase const &other ) : ResultBase( other ) {
+            if( m_type == ResultBase::Ok )
+                new( &m_value ) T( other.m_value );
+        }
+
+        ResultValueBase( Type, T const &value ) : ResultBase( Ok ) {
+            new( &m_value ) T( value );
+        }
+
+        auto operator=( ResultValueBase const &other ) -> ResultValueBase & {
+            if( m_type == ResultBase::Ok )
+                m_value.~T();
+            ResultBase::operator=(other);
+            if( m_type == ResultBase::Ok )
+                new( &m_value ) T( other.m_value );
+            return *this;
+        }
+
+        ~ResultValueBase() override {
+            if( m_type == Ok )
+                m_value.~T();
+        }
+
+        union {
+            T m_value;
+        };
+    };
+
+    template<>
+    class ResultValueBase<void> : public ResultBase {
+    protected:
+        using ResultBase::ResultBase;
+    };
+
+    template<typename T = void>
+    class BasicResult : public ResultValueBase<T> {
+    public:
+        template<typename U>
+        explicit BasicResult( BasicResult<U> const &other )
+        :   ResultValueBase<T>( other.type() ),
+            m_errorMessage( other.errorMessage() )
+        {
+            assert( type() != ResultBase::Ok );
+        }
+
+        template<typename U>
+        static auto ok( U const &value ) -> BasicResult { return { ResultBase::Ok, value }; }
+        static auto ok() -> BasicResult { return { ResultBase::Ok }; }
+        static auto logicError( std::string const &message ) -> BasicResult { return { ResultBase::LogicError, message }; }
+        static auto runtimeError( std::string const &message ) -> BasicResult { return { ResultBase::RuntimeError, message }; }
+
+        explicit operator bool() const { return m_type == ResultBase::Ok; }
+        auto type() const -> ResultBase::Type { return m_type; }
+        auto errorMessage() const -> std::string { return m_errorMessage; }
+
+    protected:
+        void enforceOk() const override {
+
+            // Errors shouldn't reach this point, but if they do
+            // the actual error message will be in m_errorMessage
+            assert( m_type != ResultBase::LogicError );
+            assert( m_type != ResultBase::RuntimeError );
+            if( m_type != ResultBase::Ok )
+                std::abort();
+        }
+
+        std::string m_errorMessage; // Only populated if resultType is an error
+
+        BasicResult( ResultBase::Type type, std::string const &message )
+        :   ResultValueBase<T>(type),
+            m_errorMessage(message)
+        {
+            assert( m_type != ResultBase::Ok );
+        }
+
+        using ResultValueBase<T>::ResultValueBase;
+        using ResultBase::m_type;
+    };
+
+    enum class ParseResultType {
+        Matched, NoMatch, ShortCircuitAll, ShortCircuitSame
+    };
+
+    class ParseState {
+    public:
+
+        ParseState( ParseResultType type, TokenStream const &remainingTokens )
+        : m_type(type),
+          m_remainingTokens( remainingTokens )
+        {}
+
+        auto type() const -> ParseResultType { return m_type; }
+        auto remainingTokens() const -> TokenStream { return m_remainingTokens; }
+
+    private:
+        ParseResultType m_type;
+        TokenStream m_remainingTokens;
+    };
+
+    using Result = BasicResult<void>;
+    using ParserResult = BasicResult<ParseResultType>;
+    using InternalParseResult = BasicResult<ParseState>;
+
+    struct HelpColumns {
+        std::string left;
+        std::string right;
+    };
+
+    template<typename T>
+    inline auto convertInto( std::string const &source, T& target ) -> ParserResult {
+        std::stringstream ss;
+        ss << source;
+        ss >> target;
+        if( ss.fail() )
+            return ParserResult::runtimeError( "Unable to convert '" + source + "' to destination type" );
+        else
+            return ParserResult::ok( ParseResultType::Matched );
+    }
+    inline auto convertInto( std::string const &source, std::string& target ) -> ParserResult {
+        target = source;
+        return ParserResult::ok( ParseResultType::Matched );
+    }
+    inline auto convertInto( std::string const &source, bool &target ) -> ParserResult {
+        std::string srcLC = source;
+        std::transform( srcLC.begin(), srcLC.end(), srcLC.begin(), []( char c ) { return static_cast<char>( std::tolower(c) ); } );
+        if (srcLC == "y" || srcLC == "1" || srcLC == "true" || srcLC == "yes" || srcLC == "on")
+            target = true;
+        else if (srcLC == "n" || srcLC == "0" || srcLC == "false" || srcLC == "no" || srcLC == "off")
+            target = false;
+        else
+            return ParserResult::runtimeError( "Expected a boolean value but did not recognise: '" + source + "'" );
+        return ParserResult::ok( ParseResultType::Matched );
+    }
+#ifdef CLARA_CONFIG_OPTIONAL_TYPE
+    template<typename T>
+    inline auto convertInto( std::string const &source, CLARA_CONFIG_OPTIONAL_TYPE<T>& target ) -> ParserResult {
+        T temp;
+        auto result = convertInto( source, temp );
+        if( result )
+            target = std::move(temp);
+        return result;
+    }
+#endif // CLARA_CONFIG_OPTIONAL_TYPE
+
+    struct NonCopyable {
+        NonCopyable() = default;
+        NonCopyable( NonCopyable const & ) = delete;
+        NonCopyable( NonCopyable && ) = delete;
+        NonCopyable &operator=( NonCopyable const & ) = delete;
+        NonCopyable &operator=( NonCopyable && ) = delete;
+    };
+
+    struct BoundRef : NonCopyable {
+        virtual ~BoundRef() = default;
+        virtual auto isContainer() const -> bool { return false; }
+        virtual auto isFlag() const -> bool { return false; }
+    };
+    struct BoundValueRefBase : BoundRef {
+        virtual auto setValue( std::string const &arg ) -> ParserResult = 0;
+    };
+    struct BoundFlagRefBase : BoundRef {
+        virtual auto setFlag( bool flag ) -> ParserResult = 0;
+        virtual auto isFlag() const -> bool { return true; }
+    };
+
+    template<typename T>
+    struct BoundValueRef : BoundValueRefBase {
+        T &m_ref;
+
+        explicit BoundValueRef( T &ref ) : m_ref( ref ) {}
+
+        auto setValue( std::string const &arg ) -> ParserResult override {
+            return convertInto( arg, m_ref );
+        }
+    };
+
+    template<typename T>
+    struct BoundValueRef<std::vector<T>> : BoundValueRefBase {
+        std::vector<T> &m_ref;
+
+        explicit BoundValueRef( std::vector<T> &ref ) : m_ref( ref ) {}
+
+        auto isContainer() const -> bool override { return true; }
+
+        auto setValue( std::string const &arg ) -> ParserResult override {
+            T temp;
+            auto result = convertInto( arg, temp );
+            if( result )
+                m_ref.push_back( temp );
+            return result;
+        }
+    };
+
+    struct BoundFlagRef : BoundFlagRefBase {
+        bool &m_ref;
+
+        explicit BoundFlagRef( bool &ref ) : m_ref( ref ) {}
+
+        auto setFlag( bool flag ) -> ParserResult override {
+            m_ref = flag;
+            return ParserResult::ok( ParseResultType::Matched );
+        }
+    };
+
+    template<typename ReturnType>
+    struct LambdaInvoker {
+        static_assert( std::is_same<ReturnType, ParserResult>::value, "Lambda must return void or clara::ParserResult" );
+
+        template<typename L, typename ArgType>
+        static auto invoke( L const &lambda, ArgType const &arg ) -> ParserResult {
+            return lambda( arg );
+        }
+    };
+
+    template<>
+    struct LambdaInvoker<void> {
+        template<typename L, typename ArgType>
+        static auto invoke( L const &lambda, ArgType const &arg ) -> ParserResult {
+            lambda( arg );
+            return ParserResult::ok( ParseResultType::Matched );
+        }
+    };
+
+    template<typename ArgType, typename L>
+    inline auto invokeLambda( L const &lambda, std::string const &arg ) -> ParserResult {
+        ArgType temp{};
+        auto result = convertInto( arg, temp );
+        return !result
+           ? result
+           : LambdaInvoker<typename UnaryLambdaTraits<L>::ReturnType>::invoke( lambda, temp );
+    }
+
+    template<typename L>
+    struct BoundLambda : BoundValueRefBase {
+        L m_lambda;
+
+        static_assert( UnaryLambdaTraits<L>::isValid, "Supplied lambda must take exactly one argument" );
+        explicit BoundLambda( L const &lambda ) : m_lambda( lambda ) {}
+
+        auto setValue( std::string const &arg ) -> ParserResult override {
+            return invokeLambda<typename UnaryLambdaTraits<L>::ArgType>( m_lambda, arg );
+        }
+    };
+
+    template<typename L>
+    struct BoundFlagLambda : BoundFlagRefBase {
+        L m_lambda;
+
+        static_assert( UnaryLambdaTraits<L>::isValid, "Supplied lambda must take exactly one argument" );
+        static_assert( std::is_same<typename UnaryLambdaTraits<L>::ArgType, bool>::value, "flags must be boolean" );
+
+        explicit BoundFlagLambda( L const &lambda ) : m_lambda( lambda ) {}
+
+        auto setFlag( bool flag ) -> ParserResult override {
+            return LambdaInvoker<typename UnaryLambdaTraits<L>::ReturnType>::invoke( m_lambda, flag );
+        }
+    };
+
+    enum class Optionality { Optional, Required };
+
+    struct Parser;
+
+    class ParserBase {
+    public:
+        virtual ~ParserBase() = default;
+        virtual auto validate() const -> Result { return Result::ok(); }
+        virtual auto parse( std::string const& exeName, TokenStream const &tokens) const -> InternalParseResult  = 0;
+        virtual auto cardinality() const -> size_t { return 1; }
+
+        auto parse( Args const &args ) const -> InternalParseResult {
+            return parse( args.exeName(), TokenStream( args ) );
+        }
+    };
+
+    template<typename DerivedT>
+    class ComposableParserImpl : public ParserBase {
+    public:
+        template<typename T>
+        auto operator|( T const &other ) const -> Parser;
+
+		template<typename T>
+        auto operator+( T const &other ) const -> Parser;
+    };
+
+    // Common code and state for Args and Opts
+    template<typename DerivedT>
+    class ParserRefImpl : public ComposableParserImpl<DerivedT> {
+    protected:
+        Optionality m_optionality = Optionality::Optional;
+        std::shared_ptr<BoundRef> m_ref;
+        std::string m_hint;
+        std::string m_description;
+
+        explicit ParserRefImpl( std::shared_ptr<BoundRef> const &ref ) : m_ref( ref ) {}
+
+    public:
+        template<typename T>
+        ParserRefImpl( T &ref, std::string const &hint )
+        :   m_ref( std::make_shared<BoundValueRef<T>>( ref ) ),
+            m_hint( hint )
+        {}
+
+        template<typename LambdaT>
+        ParserRefImpl( LambdaT const &ref, std::string const &hint )
+        :   m_ref( std::make_shared<BoundLambda<LambdaT>>( ref ) ),
+            m_hint(hint)
+        {}
+
+        auto operator()( std::string const &description ) -> DerivedT & {
+            m_description = description;
+            return static_cast<DerivedT &>( *this );
+        }
+
+        auto optional() -> DerivedT & {
+            m_optionality = Optionality::Optional;
+            return static_cast<DerivedT &>( *this );
+        };
+
+        auto required() -> DerivedT & {
+            m_optionality = Optionality::Required;
+            return static_cast<DerivedT &>( *this );
+        };
+
+        auto isOptional() const -> bool {
+            return m_optionality == Optionality::Optional;
+        }
+
+        auto cardinality() const -> size_t override {
+            if( m_ref->isContainer() )
+                return 0;
+            else
+                return 1;
+        }
+
+        auto hint() const -> std::string { return m_hint; }
+    };
+
+    class ExeName : public ComposableParserImpl<ExeName> {
+        std::shared_ptr<std::string> m_name;
+        std::shared_ptr<BoundValueRefBase> m_ref;
+
+        template<typename LambdaT>
+        static auto makeRef(LambdaT const &lambda) -> std::shared_ptr<BoundValueRefBase> {
+            return std::make_shared<BoundLambda<LambdaT>>( lambda) ;
+        }
+
+    public:
+        ExeName() : m_name( std::make_shared<std::string>( "<executable>" ) ) {}
+
+        explicit ExeName( std::string &ref ) : ExeName() {
+            m_ref = std::make_shared<BoundValueRef<std::string>>( ref );
+        }
+
+        template<typename LambdaT>
+        explicit ExeName( LambdaT const& lambda ) : ExeName() {
+            m_ref = std::make_shared<BoundLambda<LambdaT>>( lambda );
+        }
+
+        // The exe name is not parsed out of the normal tokens, but is handled specially
+        auto parse( std::string const&, TokenStream const &tokens ) const -> InternalParseResult override {
+            return InternalParseResult::ok( ParseState( ParseResultType::NoMatch, tokens ) );
+        }
+
+        auto name() const -> std::string { return *m_name; }
+        auto set( std::string const& newName ) -> ParserResult {
+
+            auto lastSlash = newName.find_last_of( "\\/" );
+            auto filename = ( lastSlash == std::string::npos )
+                    ? newName
+                    : newName.substr( lastSlash+1 );
+
+            *m_name = filename;
+            if( m_ref )
+                return m_ref->setValue( filename );
+            else
+                return ParserResult::ok( ParseResultType::Matched );
+        }
+    };
+
+    class Arg : public ParserRefImpl<Arg> {
+    public:
+        using ParserRefImpl::ParserRefImpl;
+
+        auto parse( std::string const &, TokenStream const &tokens ) const -> InternalParseResult override {
+            auto validationResult = validate();
+            if( !validationResult )
+                return InternalParseResult( validationResult );
+
+            auto remainingTokens = tokens;
+            auto const &token = *remainingTokens;
+            if( token.type != TokenType::Argument )
+                return InternalParseResult::ok( ParseState( ParseResultType::NoMatch, remainingTokens ) );
+
+            assert( !m_ref->isFlag() );
+            auto valueRef = static_cast<detail::BoundValueRefBase*>( m_ref.get() );
+
+            auto result = valueRef->setValue( remainingTokens->token );
+            if( !result )
+                return InternalParseResult( result );
+            else
+                return InternalParseResult::ok( ParseState( ParseResultType::Matched, ++remainingTokens ) );
+        }
+    };
+
+    inline auto normaliseOpt( std::string const &optName ) -> std::string {
+#ifdef CATCH_PLATFORM_WINDOWS
+        if( optName[0] == '/' )
+            return "-" + optName.substr( 1 );
+        else
+#endif
+            return optName;
+    }
+
+    class Opt : public ParserRefImpl<Opt> {
+    protected:
+        std::vector<std::string> m_optNames;
+
+    public:
+        template<typename LambdaT>
+        explicit Opt( LambdaT const &ref ) : ParserRefImpl( std::make_shared<BoundFlagLambda<LambdaT>>( ref ) ) {}
+
+        explicit Opt( bool &ref ) : ParserRefImpl( std::make_shared<BoundFlagRef>( ref ) ) {}
+
+        template<typename LambdaT>
+        Opt( LambdaT const &ref, std::string const &hint ) : ParserRefImpl( ref, hint ) {}
+
+        template<typename T>
+        Opt( T &ref, std::string const &hint ) : ParserRefImpl( ref, hint ) {}
+
+        auto operator[]( std::string const &optName ) -> Opt & {
+            m_optNames.push_back( optName );
+            return *this;
+        }
+
+        auto getHelpColumns() const -> std::vector<HelpColumns> {
+            std::ostringstream oss;
+            bool first = true;
+            for( auto const &opt : m_optNames ) {
+                if (first)
+                    first = false;
+                else
+                    oss << ", ";
+                oss << opt;
+            }
+            if( !m_hint.empty() )
+                oss << " <" << m_hint << ">";
+            return { { oss.str(), m_description } };
+        }
+
+        auto isMatch( std::string const &optToken ) const -> bool {
+            auto normalisedToken = normaliseOpt( optToken );
+            for( auto const &name : m_optNames ) {
+                if( normaliseOpt( name ) == normalisedToken )
+                    return true;
+            }
+            return false;
+        }
+
+        using ParserBase::parse;
+
+        auto parse( std::string const&, TokenStream const &tokens ) const -> InternalParseResult override {
+            auto validationResult = validate();
+            if( !validationResult )
+                return InternalParseResult( validationResult );
+
+            auto remainingTokens = tokens;
+            if( remainingTokens && remainingTokens->type == TokenType::Option ) {
+                auto const &token = *remainingTokens;
+                if( isMatch(token.token ) ) {
+                    if( m_ref->isFlag() ) {
+                        auto flagRef = static_cast<detail::BoundFlagRefBase*>( m_ref.get() );
+                        auto result = flagRef->setFlag( true );
+                        if( !result )
+                            return InternalParseResult( result );
+                        if( result.value() == ParseResultType::ShortCircuitAll )
+                            return InternalParseResult::ok( ParseState( result.value(), remainingTokens ) );
+                    } else {
+                        auto valueRef = static_cast<detail::BoundValueRefBase*>( m_ref.get() );
+                        ++remainingTokens;
+                        if( !remainingTokens )
+                            return InternalParseResult::runtimeError( "Expected argument following " + token.token );
+                        auto const &argToken = *remainingTokens;
+                        if( argToken.type != TokenType::Argument )
+                            return InternalParseResult::runtimeError( "Expected argument following " + token.token );
+                        auto result = valueRef->setValue( argToken.token );
+                        if( !result )
+                            return InternalParseResult( result );
+                        if( result.value() == ParseResultType::ShortCircuitAll )
+                            return InternalParseResult::ok( ParseState( result.value(), remainingTokens ) );
+                    }
+                    return InternalParseResult::ok( ParseState( ParseResultType::Matched, ++remainingTokens ) );
+                }
+            }
+            return InternalParseResult::ok( ParseState( ParseResultType::NoMatch, remainingTokens ) );
+        }
+
+        auto validate() const -> Result override {
+            if( m_optNames.empty() )
+                return Result::logicError( "No options supplied to Opt" );
+            for( auto const &name : m_optNames ) {
+                if( name.empty() )
+                    return Result::logicError( "Option name cannot be empty" );
+#ifdef CATCH_PLATFORM_WINDOWS
+                if( name[0] != '-' && name[0] != '/' )
+                    return Result::logicError( "Option name must begin with '-' or '/'" );
+#else
+                if( name[0] != '-' )
+                    return Result::logicError( "Option name must begin with '-'" );
+#endif
+            }
+            return ParserRefImpl::validate();
+        }
+    };
+
+    struct Help : Opt {
+        Help( bool &showHelpFlag )
+        :   Opt([&]( bool flag ) {
+                showHelpFlag = flag;
+                return ParserResult::ok( ParseResultType::ShortCircuitAll );
+            })
+        {
+            static_cast<Opt &>( *this )
+                    ("display usage information")
+                    ["-?"]["-h"]["--help"]
+                    .optional();
+        }
+    };
+
+    struct Parser : ParserBase {
+
+        mutable ExeName m_exeName;
+        std::vector<Opt> m_options;
+        std::vector<Arg> m_args;
+
+        auto operator|=( ExeName const &exeName ) -> Parser & {
+            m_exeName = exeName;
+            return *this;
+        }
+
+        auto operator|=( Arg const &arg ) -> Parser & {
+            m_args.push_back(arg);
+            return *this;
+        }
+
+        auto operator|=( Opt const &opt ) -> Parser & {
+            m_options.push_back(opt);
+            return *this;
+        }
+
+        auto operator|=( Parser const &other ) -> Parser & {
+            m_options.insert(m_options.end(), other.m_options.begin(), other.m_options.end());
+            m_args.insert(m_args.end(), other.m_args.begin(), other.m_args.end());
+            return *this;
+        }
+
+        template<typename T>
+        auto operator|( T const &other ) const -> Parser {
+            return Parser( *this ) |= other;
+        }
+
+        // Forward deprecated interface with '+' instead of '|'
+        template<typename T>
+        auto operator+=( T const &other ) -> Parser & { return operator|=( other ); }
+        template<typename T>
+        auto operator+( T const &other ) const -> Parser { return operator|( other ); }
+
+        auto getHelpColumns() const -> std::vector<HelpColumns> {
+            std::vector<HelpColumns> cols;
+            for (auto const &o : m_options) {
+                auto childCols = o.getHelpColumns();
+                cols.insert( cols.end(), childCols.begin(), childCols.end() );
+            }
+            return cols;
+        }
+
+        void writeToStream( std::ostream &os ) const {
+            if (!m_exeName.name().empty()) {
+                os << "usage:\n" << "  " << m_exeName.name() << " ";
+                bool required = true, first = true;
+                for( auto const &arg : m_args ) {
+                    if (first)
+                        first = false;
+                    else
+                        os << " ";
+                    if( arg.isOptional() && required ) {
+                        os << "[";
+                        required = false;
+                    }
+                    os << "<" << arg.hint() << ">";
+                    if( arg.cardinality() == 0 )
+                        os << " ... ";
+                }
+                if( !required )
+                    os << "]";
+                if( !m_options.empty() )
+                    os << " options";
+                os << "\n\nwhere options are:" << std::endl;
+            }
+
+            auto rows = getHelpColumns();
+            size_t consoleWidth = CATCH_CLARA_CONFIG_CONSOLE_WIDTH;
+            size_t optWidth = 0;
+            for( auto const &cols : rows )
+                optWidth = (std::max)(optWidth, cols.left.size() + 2);
+
+            optWidth = (std::min)(optWidth, consoleWidth/2);
+
+            for( auto const &cols : rows ) {
+                auto row =
+                        TextFlow::Column( cols.left ).width( optWidth ).indent( 2 ) +
+                        TextFlow::Spacer(4) +
+                        TextFlow::Column( cols.right ).width( consoleWidth - 7 - optWidth );
+                os << row << std::endl;
+            }
+        }
+
+        friend auto operator<<( std::ostream &os, Parser const &parser ) -> std::ostream& {
+            parser.writeToStream( os );
+            return os;
+        }
+
+        auto validate() const -> Result override {
+            for( auto const &opt : m_options ) {
+                auto result = opt.validate();
+                if( !result )
+                    return result;
+            }
+            for( auto const &arg : m_args ) {
+                auto result = arg.validate();
+                if( !result )
+                    return result;
+            }
+            return Result::ok();
+        }
+
+        using ParserBase::parse;
+
+        auto parse( std::string const& exeName, TokenStream const &tokens ) const -> InternalParseResult override {
+
+            struct ParserInfo {
+                ParserBase const* parser = nullptr;
+                size_t count = 0;
+            };
+            const size_t totalParsers = m_options.size() + m_args.size();
+            assert( totalParsers < 512 );
+            // ParserInfo parseInfos[totalParsers]; // <-- this is what we really want to do
+            ParserInfo parseInfos[512];
+
+            {
+                size_t i = 0;
+                for (auto const &opt : m_options) parseInfos[i++].parser = &opt;
+                for (auto const &arg : m_args) parseInfos[i++].parser = &arg;
+            }
+
+            m_exeName.set( exeName );
+
+            auto result = InternalParseResult::ok( ParseState( ParseResultType::NoMatch, tokens ) );
+            while( result.value().remainingTokens() ) {
+                bool tokenParsed = false;
+
+                for( size_t i = 0; i < totalParsers; ++i ) {
+                    auto&  parseInfo = parseInfos[i];
+                    if( parseInfo.parser->cardinality() == 0 || parseInfo.count < parseInfo.parser->cardinality() ) {
+                        result = parseInfo.parser->parse(exeName, result.value().remainingTokens());
+                        if (!result)
+                            return result;
+                        if (result.value().type() != ParseResultType::NoMatch) {
+                            tokenParsed = true;
+                            ++parseInfo.count;
+                            break;
+                        }
+                    }
+                }
+
+                if( result.value().type() == ParseResultType::ShortCircuitAll )
+                    return result;
+                if( !tokenParsed )
+                    return InternalParseResult::runtimeError( "Unrecognised token: " + result.value().remainingTokens()->token );
+            }
+            // !TBD Check missing required options
+            return result;
+        }
+    };
+
+    template<typename DerivedT>
+    template<typename T>
+    auto ComposableParserImpl<DerivedT>::operator|( T const &other ) const -> Parser {
+        return Parser() | static_cast<DerivedT const &>( *this ) | other;
+    }
+} // namespace detail
+
+// A Combined parser
+using detail::Parser;
+
+// A parser for options
+using detail::Opt;
+
+// A parser for arguments
+using detail::Arg;
+
+// Wrapper for argc, argv from main()
+using detail::Args;
+
+// Specifies the name of the executable
+using detail::ExeName;
+
+// Convenience wrapper for option parser that specifies the help option
+using detail::Help;
+
+// enum of result types from a parse
+using detail::ParseResultType;
+
+// Result type for parser operation
+using detail::ParserResult;
+
+}} // namespace Catch::clara
+
+// end clara.hpp
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// Restore Clara's value for console width, if present
+#ifdef CATCH_TEMP_CLARA_CONFIG_CONSOLE_WIDTH
+#define CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH CATCH_TEMP_CLARA_CONFIG_CONSOLE_WIDTH
+#undef CATCH_TEMP_CLARA_CONFIG_CONSOLE_WIDTH
+#endif
+
+// end catch_clara.h
+namespace Catch {
+
+    clara::Parser makeCommandLineParser( ConfigData& config );
+
+} // end namespace Catch
+
+// end catch_commandline.h
+#include <fstream>
+#include <ctime>
+
+namespace Catch {
+
+    clara::Parser makeCommandLineParser( ConfigData& config ) {
+
+        using namespace clara;
+
+        auto const setWarning = [&]( std::string const& warning ) {
+                auto warningSet = [&]() {
+                    if( warning == "NoAssertions" )
+                        return WarnAbout::NoAssertions;
+
+                    if ( warning == "NoTests" )
+                        return WarnAbout::NoTests;
+
+                    return WarnAbout::Nothing;
+                }();
+
+                if (warningSet == WarnAbout::Nothing)
+                    return ParserResult::runtimeError( "Unrecognised warning: '" + warning + "'" );
+                config.warnings = static_cast<WarnAbout::What>( config.warnings | warningSet );
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const loadTestNamesFromFile = [&]( std::string const& filename ) {
+                std::ifstream f( filename.c_str() );
+                if( !f.is_open() )
+                    return ParserResult::runtimeError( "Unable to load input file: '" + filename + "'" );
+
+                std::string line;
+                while( std::getline( f, line ) ) {
+                    line = trim(line);
+                    if( !line.empty() && !startsWith( line, '#' ) ) {
+                        if( !startsWith( line, '"' ) )
+                            line = '"' + line + '"';
+                        config.testsOrTags.push_back( line );
+                        config.testsOrTags.emplace_back( "," );
+                    }
+                }
+                //Remove comma in the end
+                if(!config.testsOrTags.empty())
+                    config.testsOrTags.erase( config.testsOrTags.end()-1 );
+
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setTestOrder = [&]( std::string const& order ) {
+                if( startsWith( "declared", order ) )
+                    config.runOrder = RunTests::InDeclarationOrder;
+                else if( startsWith( "lexical", order ) )
+                    config.runOrder = RunTests::InLexicographicalOrder;
+                else if( startsWith( "random", order ) )
+                    config.runOrder = RunTests::InRandomOrder;
+                else
+                    return clara::ParserResult::runtimeError( "Unrecognised ordering: '" + order + "'" );
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setRngSeed = [&]( std::string const& seed ) {
+                if( seed != "time" )
+                    return clara::detail::convertInto( seed, config.rngSeed );
+                config.rngSeed = static_cast<unsigned int>( std::time(nullptr) );
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setColourUsage = [&]( std::string const& useColour ) {
+                    auto mode = toLower( useColour );
+
+                    if( mode == "yes" )
+                        config.useColour = UseColour::Yes;
+                    else if( mode == "no" )
+                        config.useColour = UseColour::No;
+                    else if( mode == "auto" )
+                        config.useColour = UseColour::Auto;
+                    else
+                        return ParserResult::runtimeError( "colour mode must be one of: auto, yes or no. '" + useColour + "' not recognised" );
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setWaitForKeypress = [&]( std::string const& keypress ) {
+                auto keypressLc = toLower( keypress );
+                if (keypressLc == "never")
+                    config.waitForKeypress = WaitForKeypress::Never;
+                else if( keypressLc == "start" )
+                    config.waitForKeypress = WaitForKeypress::BeforeStart;
+                else if( keypressLc == "exit" )
+                    config.waitForKeypress = WaitForKeypress::BeforeExit;
+                else if( keypressLc == "both" )
+                    config.waitForKeypress = WaitForKeypress::BeforeStartAndExit;
+                else
+                    return ParserResult::runtimeError( "keypress argument must be one of: never, start, exit or both. '" + keypress + "' not recognised" );
+            return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setVerbosity = [&]( std::string const& verbosity ) {
+            auto lcVerbosity = toLower( verbosity );
+            if( lcVerbosity == "quiet" )
+                config.verbosity = Verbosity::Quiet;
+            else if( lcVerbosity == "normal" )
+                config.verbosity = Verbosity::Normal;
+            else if( lcVerbosity == "high" )
+                config.verbosity = Verbosity::High;
+            else
+                return ParserResult::runtimeError( "Unrecognised verbosity, '" + verbosity + "'" );
+            return ParserResult::ok( ParseResultType::Matched );
+        };
+        auto const setReporter = [&]( std::string const& reporter ) {
+            IReporterRegistry::FactoryMap const& factories = getRegistryHub().getReporterRegistry().getFactories();
+
+            auto lcReporter = toLower( reporter );
+            auto result = factories.find( lcReporter );
+
+            if( factories.end() != result )
+                config.reporterName = lcReporter;
+            else
+                return ParserResult::runtimeError( "Unrecognized reporter, '" + reporter + "'. Check available with --list-reporters" );
+            return ParserResult::ok( ParseResultType::Matched );
+        };
+
+        auto cli
+            = ExeName( config.processName )
+            | Help( config.showHelp )
+            | Opt( config.listTests )
+                ["-l"]["--list-tests"]
+                ( "list all/matching test cases" )
+            | Opt( config.listTags )
+                ["-t"]["--list-tags"]
+                ( "list all/matching tags" )
+            | Opt( config.showSuccessfulTests )
+                ["-s"]["--success"]
+                ( "include successful tests in output" )
+            | Opt( config.shouldDebugBreak )
+                ["-b"]["--break"]
+                ( "break into debugger on failure" )
+            | Opt( config.noThrow )
+                ["-e"]["--nothrow"]
+                ( "skip exception tests" )
+            | Opt( config.showInvisibles )
+                ["-i"]["--invisibles"]
+                ( "show invisibles (tabs, newlines)" )
+            | Opt( config.outputFilename, "filename" )
+                ["-o"]["--out"]
+                ( "output filename" )
+            | Opt( setReporter, "name" )
+                ["-r"]["--reporter"]
+                ( "reporter to use (defaults to console)" )
+            | Opt( config.name, "name" )
+                ["-n"]["--name"]
+                ( "suite name" )
+            | Opt( [&]( bool ){ config.abortAfter = 1; } )
+                ["-a"]["--abort"]
+                ( "abort at first failure" )
+            | Opt( [&]( int x ){ config.abortAfter = x; }, "no. failures" )
+                ["-x"]["--abortx"]
+                ( "abort after x failures" )
+            | Opt( setWarning, "warning name" )
+                ["-w"]["--warn"]
+                ( "enable warnings" )
+            | Opt( [&]( bool flag ) { config.showDurations = flag ? ShowDurations::Always : ShowDurations::Never; }, "yes|no" )
+                ["-d"]["--durations"]
+                ( "show test durations" )
+            | Opt( loadTestNamesFromFile, "filename" )
+                ["-f"]["--input-file"]
+                ( "load test names to run from a file" )
+            | Opt( config.filenamesAsTags )
+                ["-#"]["--filenames-as-tags"]
+                ( "adds a tag for the filename" )
+            | Opt( config.sectionsToRun, "section name" )
+                ["-c"]["--section"]
+                ( "specify section to run" )
+            | Opt( setVerbosity, "quiet|normal|high" )
+                ["-v"]["--verbosity"]
+                ( "set output verbosity" )
+            | Opt( config.listTestNamesOnly )
+                ["--list-test-names-only"]
+                ( "list all/matching test cases names only" )
+            | Opt( config.listReporters )
+                ["--list-reporters"]
+                ( "list all reporters" )
+            | Opt( setTestOrder, "decl|lex|rand" )
+                ["--order"]
+                ( "test case order (defaults to decl)" )
+            | Opt( setRngSeed, "'time'|number" )
+                ["--rng-seed"]
+                ( "set a specific seed for random numbers" )
+            | Opt( setColourUsage, "yes|no" )
+                ["--use-colour"]
+                ( "should output be colourised" )
+            | Opt( config.libIdentify )
+                ["--libidentify"]
+                ( "report name and version according to libidentify standard" )
+            | Opt( setWaitForKeypress, "never|start|exit|both" )
+                ["--wait-for-keypress"]
+                ( "waits for a keypress before exiting" )
+            | Opt( config.benchmarkSamples, "samples" )
+                ["--benchmark-samples"]
+                ( "number of samples to collect (default: 100)" )
+            | Opt( config.benchmarkResamples, "resamples" )
+                ["--benchmark-resamples"]
+                ( "number of resamples for the bootstrap (default: 100000)" )
+            | Opt( config.benchmarkConfidenceInterval, "confidence interval" )
+                ["--benchmark-confidence-interval"]
+                ( "confidence interval for the bootstrap (between 0 and 1, default: 0.95)" )
+            | Opt( config.benchmarkNoAnalysis )
+                ["--benchmark-no-analysis"]
+                ( "perform only measurements; do not perform any analysis" )
+            | Opt( config.benchmarkWarmupTime, "benchmarkWarmupTime" )
+                ["--benchmark-warmup-time"]
+                ( "amount of time in milliseconds spent on warming up each test (default: 100)" )
+            | Arg( config.testsOrTags, "test name|pattern|tags" )
+                ( "which test or tests to use" );
+
+        return cli;
+    }
+
+} // end namespace Catch
+// end catch_commandline.cpp
+// start catch_common.cpp
+
+#include <cstring>
+#include <ostream>
+
+namespace Catch {
+
+    bool SourceLineInfo::operator == ( SourceLineInfo const& other ) const noexcept {
+        return line == other.line && (file == other.file || std::strcmp(file, other.file) == 0);
+    }
+    bool SourceLineInfo::operator < ( SourceLineInfo const& other ) const noexcept {
+        // We can assume that the same file will usually have the same pointer.
+        // Thus, if the pointers are the same, there is no point in calling the strcmp
+        return line < other.line || ( line == other.line && file != other.file && (std::strcmp(file, other.file) < 0));
+    }
+
+    std::ostream& operator << ( std::ostream& os, SourceLineInfo const& info ) {
+#ifndef __GNUG__
+        os << info.file << '(' << info.line << ')';
+#else
+        os << info.file << ':' << info.line;
+#endif
+        return os;
+    }
+
+    std::string StreamEndStop::operator+() const {
+        return std::string();
+    }
+
+    NonCopyable::NonCopyable() = default;
+    NonCopyable::~NonCopyable() = default;
+
+}
+// end catch_common.cpp
+// start catch_config.cpp
+
+namespace Catch {
+
+    Config::Config( ConfigData const& data )
+    :   m_data( data ),
+        m_stream( openStream() )
+    {
+        // We need to trim filter specs to avoid trouble with superfluous
+        // whitespace (esp. important for bdd macros, as those are manually
+        // aligned with whitespace).
+
+        for (auto& elem : m_data.testsOrTags) {
+            elem = trim(elem);
+        }
+        for (auto& elem : m_data.sectionsToRun) {
+            elem = trim(elem);
+        }
+
+        TestSpecParser parser(ITagAliasRegistry::get());
+        if (!m_data.testsOrTags.empty()) {
+            m_hasTestFilters = true;
+            for (auto const& testOrTags : m_data.testsOrTags) {
+                parser.parse(testOrTags);
+            }
+        }
+        m_testSpec = parser.testSpec();
+    }
+
+    std::string const& Config::getFilename() const {
+        return m_data.outputFilename ;
+    }
+
+    bool Config::listTests() const          { return m_data.listTests; }
+    bool Config::listTestNamesOnly() const  { return m_data.listTestNamesOnly; }
+    bool Config::listTags() const           { return m_data.listTags; }
+    bool Config::listReporters() const      { return m_data.listReporters; }
+
+    std::string Config::getProcessName() const { return m_data.processName; }
+    std::string const& Config::getReporterName() const { return m_data.reporterName; }
+
+    std::vector<std::string> const& Config::getTestsOrTags() const { return m_data.testsOrTags; }
+    std::vector<std::string> const& Config::getSectionsToRun() const { return m_data.sectionsToRun; }
+
+    TestSpec const& Config::testSpec() const { return m_testSpec; }
+    bool Config::hasTestFilters() const { return m_hasTestFilters; }
+
+    bool Config::showHelp() const { return m_data.showHelp; }
+
+    // IConfig interface
+    bool Config::allowThrows() const                   { return !m_data.noThrow; }
+    std::ostream& Config::stream() const               { return m_stream->stream(); }
+    std::string Config::name() const                   { return m_data.name.empty() ? m_data.processName : m_data.name; }
+    bool Config::includeSuccessfulResults() const      { return m_data.showSuccessfulTests; }
+    bool Config::warnAboutMissingAssertions() const    { return !!(m_data.warnings & WarnAbout::NoAssertions); }
+    bool Config::warnAboutNoTests() const              { return !!(m_data.warnings & WarnAbout::NoTests); }
+    ShowDurations::OrNot Config::showDurations() const { return m_data.showDurations; }
+    RunTests::InWhatOrder Config::runOrder() const     { return m_data.runOrder; }
+    unsigned int Config::rngSeed() const               { return m_data.rngSeed; }
+    UseColour::YesOrNo Config::useColour() const       { return m_data.useColour; }
+    bool Config::shouldDebugBreak() const              { return m_data.shouldDebugBreak; }
+    int Config::abortAfter() const                     { return m_data.abortAfter; }
+    bool Config::showInvisibles() const                { return m_data.showInvisibles; }
+    Verbosity Config::verbosity() const                { return m_data.verbosity; }
+
+    bool Config::benchmarkNoAnalysis() const                      { return m_data.benchmarkNoAnalysis; }
+    int Config::benchmarkSamples() const                          { return m_data.benchmarkSamples; }
+    double Config::benchmarkConfidenceInterval() const            { return m_data.benchmarkConfidenceInterval; }
+    unsigned int Config::benchmarkResamples() const               { return m_data.benchmarkResamples; }
+    std::chrono::milliseconds Config::benchmarkWarmupTime() const { return std::chrono::milliseconds(m_data.benchmarkWarmupTime); }
+
+    IStream const* Config::openStream() {
+        return Catch::makeStream(m_data.outputFilename);
+    }
+
+} // end namespace Catch
+// end catch_config.cpp
+// start catch_console_colour.cpp
+
+#if defined(__clang__)
+#    pragma clang diagnostic push
+#    pragma clang diagnostic ignored "-Wexit-time-destructors"
+#endif
+
+// start catch_errno_guard.h
+
+namespace Catch {
+
+    class ErrnoGuard {
+    public:
+        ErrnoGuard();
+        ~ErrnoGuard();
+    private:
+        int m_oldErrno;
+    };
+
+}
+
+// end catch_errno_guard.h
+#include <sstream>
+
+namespace Catch {
+    namespace {
+
+        struct IColourImpl {
+            virtual ~IColourImpl() = default;
+            virtual void use( Colour::Code _colourCode ) = 0;
+        };
+
+        struct NoColourImpl : IColourImpl {
+            void use( Colour::Code ) override {}
+
+            static IColourImpl* instance() {
+                static NoColourImpl s_instance;
+                return &s_instance;
+            }
+        };
+
+    } // anon namespace
+} // namespace Catch
+
+#if !defined( CATCH_CONFIG_COLOUR_NONE ) && !defined( CATCH_CONFIG_COLOUR_WINDOWS ) && !defined( CATCH_CONFIG_COLOUR_ANSI )
+#   ifdef CATCH_PLATFORM_WINDOWS
+#       define CATCH_CONFIG_COLOUR_WINDOWS
+#   else
+#       define CATCH_CONFIG_COLOUR_ANSI
+#   endif
+#endif
+
+#if defined ( CATCH_CONFIG_COLOUR_WINDOWS ) /////////////////////////////////////////
+
+namespace Catch {
+namespace {
+
+    class Win32ColourImpl : public IColourImpl {
+    public:
+        Win32ColourImpl() : stdoutHandle( GetStdHandle(STD_OUTPUT_HANDLE) )
+        {
+            CONSOLE_SCREEN_BUFFER_INFO csbiInfo;
+            GetConsoleScreenBufferInfo( stdoutHandle, &csbiInfo );
+            originalForegroundAttributes = csbiInfo.wAttributes & ~( BACKGROUND_GREEN | BACKGROUND_RED | BACKGROUND_BLUE | BACKGROUND_INTENSITY );
+            originalBackgroundAttributes = csbiInfo.wAttributes & ~( FOREGROUND_GREEN | FOREGROUND_RED | FOREGROUND_BLUE | FOREGROUND_INTENSITY );
+        }
+
+        void use( Colour::Code _colourCode ) override {
+            switch( _colourCode ) {
+                case Colour::None:      return setTextAttribute( originalForegroundAttributes );
+                case Colour::White:     return setTextAttribute( FOREGROUND_GREEN | FOREGROUND_RED | FOREGROUND_BLUE );
+                case Colour::Red:       return setTextAttribute( FOREGROUND_RED );
+                case Colour::Green:     return setTextAttribute( FOREGROUND_GREEN );
+                case Colour::Blue:      return setTextAttribute( FOREGROUND_BLUE );
+                case Colour::Cyan:      return setTextAttribute( FOREGROUND_BLUE | FOREGROUND_GREEN );
+                case Colour::Yellow:    return setTextAttribute( FOREGROUND_RED | FOREGROUND_GREEN );
+                case Colour::Grey:      return setTextAttribute( 0 );
+
+                case Colour::LightGrey:     return setTextAttribute( FOREGROUND_INTENSITY );
+                case Colour::BrightRed:     return setTextAttribute( FOREGROUND_INTENSITY | FOREGROUND_RED );
+                case Colour::BrightGreen:   return setTextAttribute( FOREGROUND_INTENSITY | FOREGROUND_GREEN );
+                case Colour::BrightWhite:   return setTextAttribute( FOREGROUND_INTENSITY | FOREGROUND_GREEN | FOREGROUND_RED | FOREGROUND_BLUE );
+                case Colour::BrightYellow:  return setTextAttribute( FOREGROUND_INTENSITY | FOREGROUND_RED | FOREGROUND_GREEN );
+
+                case Colour::Bright: CATCH_INTERNAL_ERROR( "not a colour" );
+
+                default:
+                    CATCH_ERROR( "Unknown colour requested" );
+            }
+        }
+
+    private:
+        void setTextAttribute( WORD _textAttribute ) {
+            SetConsoleTextAttribute( stdoutHandle, _textAttribute | originalBackgroundAttributes );
+        }
+        HANDLE stdoutHandle;
+        WORD originalForegroundAttributes;
+        WORD originalBackgroundAttributes;
+    };
+
+    IColourImpl* platformColourInstance() {
+        static Win32ColourImpl s_instance;
+
+        IConfigPtr config = getCurrentContext().getConfig();
+        UseColour::YesOrNo colourMode = config
+            ? config->useColour()
+            : UseColour::Auto;
+        if( colourMode == UseColour::Auto )
+            colourMode = UseColour::Yes;
+        return colourMode == UseColour::Yes
+            ? &s_instance
+            : NoColourImpl::instance();
+    }
+
+} // end anon namespace
+} // end namespace Catch
+
+#elif defined( CATCH_CONFIG_COLOUR_ANSI ) //////////////////////////////////////
+
+#include <unistd.h>
+
+namespace Catch {
+namespace {
+
+    // use POSIX/ ANSI console terminal codes
+    // Thanks to Adam Strzelecki for original contribution
+    // (http://github.com/nanoant)
+    // https://github.com/philsquared/Catch/pull/131
+    class PosixColourImpl : public IColourImpl {
+    public:
+        void use( Colour::Code _colourCode ) override {
+            switch( _colourCode ) {
+                case Colour::None:
+                case Colour::White:     return setColour( "[0m" );
+                case Colour::Red:       return setColour( "[0;31m" );
+                case Colour::Green:     return setColour( "[0;32m" );
+                case Colour::Blue:      return setColour( "[0;34m" );
+                case Colour::Cyan:      return setColour( "[0;36m" );
+                case Colour::Yellow:    return setColour( "[0;33m" );
+                case Colour::Grey:      return setColour( "[1;30m" );
+
+                case Colour::LightGrey:     return setColour( "[0;37m" );
+                case Colour::BrightRed:     return setColour( "[1;31m" );
+                case Colour::BrightGreen:   return setColour( "[1;32m" );
+                case Colour::BrightWhite:   return setColour( "[1;37m" );
+                case Colour::BrightYellow:  return setColour( "[1;33m" );
+
+                case Colour::Bright: CATCH_INTERNAL_ERROR( "not a colour" );
+                default: CATCH_INTERNAL_ERROR( "Unknown colour requested" );
+            }
+        }
+        static IColourImpl* instance() {
+            static PosixColourImpl s_instance;
+            return &s_instance;
+        }
+
+    private:
+        void setColour( const char* _escapeCode ) {
+            getCurrentContext().getConfig()->stream()
+                << '\033' << _escapeCode;
+        }
+    };
+
+    bool useColourOnPlatform() {
+        return
+#if defined(CATCH_PLATFORM_MAC) || defined(CATCH_PLATFORM_IPHONE)
+            !isDebuggerActive() &&
+#endif
+#if !(defined(__DJGPP__) && defined(__STRICT_ANSI__))
+            isatty(STDOUT_FILENO)
+#else
+            false
+#endif
+            ;
+    }
+    IColourImpl* platformColourInstance() {
+        ErrnoGuard guard;
+        IConfigPtr config = getCurrentContext().getConfig();
+        UseColour::YesOrNo colourMode = config
+            ? config->useColour()
+            : UseColour::Auto;
+        if( colourMode == UseColour::Auto )
+            colourMode = useColourOnPlatform()
+                ? UseColour::Yes
+                : UseColour::No;
+        return colourMode == UseColour::Yes
+            ? PosixColourImpl::instance()
+            : NoColourImpl::instance();
+    }
+
+} // end anon namespace
+} // end namespace Catch
+
+#else  // not Windows or ANSI ///////////////////////////////////////////////
+
+namespace Catch {
+
+    static IColourImpl* platformColourInstance() { return NoColourImpl::instance(); }
+
+} // end namespace Catch
+
+#endif // Windows/ ANSI/ None
+
+namespace Catch {
+
+    Colour::Colour( Code _colourCode ) { use( _colourCode ); }
+    Colour::Colour( Colour&& other ) noexcept {
+        m_moved = other.m_moved;
+        other.m_moved = true;
+    }
+    Colour& Colour::operator=( Colour&& other ) noexcept {
+        m_moved = other.m_moved;
+        other.m_moved  = true;
+        return *this;
+    }
+
+    Colour::~Colour(){ if( !m_moved ) use( None ); }
+
+    void Colour::use( Code _colourCode ) {
+        static IColourImpl* impl = platformColourInstance();
+        // Strictly speaking, this cannot possibly happen.
+        // However, under some conditions it does happen (see #1626),
+        // and this change is small enough that we can let practicality
+        // triumph over purity in this case.
+        if (impl != nullptr) {
+            impl->use( _colourCode );
+        }
+    }
+
+    std::ostream& operator << ( std::ostream& os, Colour const& ) {
+        return os;
+    }
+
+} // end namespace Catch
+
+#if defined(__clang__)
+#    pragma clang diagnostic pop
+#endif
+
+// end catch_console_colour.cpp
+// start catch_context.cpp
+
+namespace Catch {
+
+    class Context : public IMutableContext, NonCopyable {
+
+    public: // IContext
+        IResultCapture* getResultCapture() override {
+            return m_resultCapture;
+        }
+        IRunner* getRunner() override {
+            return m_runner;
+        }
+
+        IConfigPtr const& getConfig() const override {
+            return m_config;
+        }
+
+        ~Context() override;
+
+    public: // IMutableContext
+        void setResultCapture( IResultCapture* resultCapture ) override {
+            m_resultCapture = resultCapture;
+        }
+        void setRunner( IRunner* runner ) override {
+            m_runner = runner;
+        }
+        void setConfig( IConfigPtr const& config ) override {
+            m_config = config;
+        }
+
+        friend IMutableContext& getCurrentMutableContext();
+
+    private:
+        IConfigPtr m_config;
+        IRunner* m_runner = nullptr;
+        IResultCapture* m_resultCapture = nullptr;
+    };
+
+    IMutableContext *IMutableContext::currentContext = nullptr;
+
+    void IMutableContext::createContext()
+    {
+        currentContext = new Context();
+    }
+
+    void cleanUpContext() {
+        delete IMutableContext::currentContext;
+        IMutableContext::currentContext = nullptr;
+    }
+    IContext::~IContext() = default;
+    IMutableContext::~IMutableContext() = default;
+    Context::~Context() = default;
+
+    SimplePcg32& rng() {
+        static SimplePcg32 s_rng;
+        return s_rng;
+    }
+
+}
+// end catch_context.cpp
+// start catch_debug_console.cpp
+
+// start catch_debug_console.h
+
+#include <string>
+
+namespace Catch {
+    void writeToDebugConsole( std::string const& text );
+}
+
+// end catch_debug_console.h
+#if defined(CATCH_CONFIG_ANDROID_LOGWRITE)
+#include <android/log.h>
+
+    namespace Catch {
+        void writeToDebugConsole( std::string const& text ) {
+            __android_log_write( ANDROID_LOG_DEBUG, "Catch", text.c_str() );
+        }
+    }
+
+#elif defined(CATCH_PLATFORM_WINDOWS)
+
+    namespace Catch {
+        void writeToDebugConsole( std::string const& text ) {
+            ::OutputDebugStringA( text.c_str() );
+        }
+    }
+
+#else
+
+    namespace Catch {
+        void writeToDebugConsole( std::string const& text ) {
+            // !TBD: Need a version for Mac/ XCode and other IDEs
+            Catch::cout() << text;
+        }
+    }
+
+#endif // Platform
+// end catch_debug_console.cpp
+// start catch_debugger.cpp
+
+#if defined(CATCH_PLATFORM_MAC) || defined(CATCH_PLATFORM_IPHONE)
+
+#  include <assert.h>
+#  include <stdbool.h>
+#  include <sys/types.h>
+#  include <unistd.h>
+#  include <cstddef>
+#  include <ostream>
+
+#ifdef __apple_build_version__
+    // These headers will only compile with AppleClang (XCode)
+    // For other compilers (Clang, GCC, ... ) we need to exclude them
+#  include <sys/sysctl.h>
+#endif
+
+    namespace Catch {
+        #ifdef __apple_build_version__
+        // The following function is taken directly from the following technical note:
+        // https://developer.apple.com/library/archive/qa/qa1361/_index.html
+
+        // Returns true if the current process is being debugged (either
+        // running under the debugger or has a debugger attached post facto).
+        bool isDebuggerActive(){
+            int                 mib[4];
+            struct kinfo_proc   info;
+            std::size_t         size;
+
+            // Initialize the flags so that, if sysctl fails for some bizarre
+            // reason, we get a predictable result.
+
+            info.kp_proc.p_flag = 0;
+
+            // Initialize mib, which tells sysctl the info we want, in this case
+            // we're looking for information about a specific process ID.
+
+            mib[0] = CTL_KERN;
+            mib[1] = KERN_PROC;
+            mib[2] = KERN_PROC_PID;
+            mib[3] = getpid();
+
+            // Call sysctl.
+
+            size = sizeof(info);
+            if( sysctl(mib, sizeof(mib) / sizeof(*mib), &info, &size, nullptr, 0) != 0 ) {
+                Catch::cerr() << "\n** Call to sysctl failed - unable to determine if debugger is active **\n" << std::endl;
+                return false;
+            }
+
+            // We're being debugged if the P_TRACED flag is set.
+
+            return ( (info.kp_proc.p_flag & P_TRACED) != 0 );
+        }
+        #else
+        bool isDebuggerActive() {
+            // We need to find another way to determine this for non-appleclang compilers on macOS
+            return false;
+        }
+        #endif
+    } // namespace Catch
+
+#elif defined(CATCH_PLATFORM_LINUX)
+    #include <fstream>
+    #include <string>
+
+    namespace Catch{
+        // The standard POSIX way of detecting a debugger is to attempt to
+        // ptrace() the process, but this needs to be done from a child and not
+        // this process itself to still allow attaching to this process later
+        // if wanted, so is rather heavy. Under Linux we have the PID of the
+        // "debugger" (which doesn't need to be gdb, of course, it could also
+        // be strace, for example) in /proc/$PID/status, so just get it from
+        // there instead.
+        bool isDebuggerActive(){
+            // Libstdc++ has a bug, where std::ifstream sets errno to 0
+            // This way our users can properly assert over errno values
+            ErrnoGuard guard;
+            std::ifstream in("/proc/self/status");
+            for( std::string line; std::getline(in, line); ) {
+                static const int PREFIX_LEN = 11;
+                if( line.compare(0, PREFIX_LEN, "TracerPid:\t") == 0 ) {
+                    // We're traced if the PID is not 0 and no other PID starts
+                    // with 0 digit, so it's enough to check for just a single
+                    // character.
+                    return line.length() > PREFIX_LEN && line[PREFIX_LEN] != '0';
+                }
+            }
+
+            return false;
+        }
+    } // namespace Catch
+#elif defined(_MSC_VER)
+    extern "C" __declspec(dllimport) int __stdcall IsDebuggerPresent();
+    namespace Catch {
+        bool isDebuggerActive() {
+            return IsDebuggerPresent() != 0;
+        }
+    }
+#elif defined(__MINGW32__)
+    extern "C" __declspec(dllimport) int __stdcall IsDebuggerPresent();
+    namespace Catch {
+        bool isDebuggerActive() {
+            return IsDebuggerPresent() != 0;
+        }
+    }
+#else
+    namespace Catch {
+       bool isDebuggerActive() { return false; }
+    }
+#endif // Platform
+// end catch_debugger.cpp
+// start catch_decomposer.cpp
+
+namespace Catch {
+
+    ITransientExpression::~ITransientExpression() = default;
+
+    void formatReconstructedExpression( std::ostream &os, std::string const& lhs, StringRef op, std::string const& rhs ) {
+        if( lhs.size() + rhs.size() < 40 &&
+                lhs.find('\n') == std::string::npos &&
+                rhs.find('\n') == std::string::npos )
+            os << lhs << " " << op << " " << rhs;
+        else
+            os << lhs << "\n" << op << "\n" << rhs;
+    }
+}
+// end catch_decomposer.cpp
+// start catch_enforce.cpp
+
+#include <stdexcept>
+
+namespace Catch {
+#if defined(CATCH_CONFIG_DISABLE_EXCEPTIONS) && !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS_CUSTOM_HANDLER)
+    [[noreturn]]
+    void throw_exception(std::exception const& e) {
+        Catch::cerr() << "Catch will terminate because it needed to throw an exception.\n"
+                      << "The message was: " << e.what() << '\n';
+        std::terminate();
+    }
+#endif
+
+    [[noreturn]]
+    void throw_logic_error(std::string const& msg) {
+        throw_exception(std::logic_error(msg));
+    }
+
+    [[noreturn]]
+    void throw_domain_error(std::string const& msg) {
+        throw_exception(std::domain_error(msg));
+    }
+
+    [[noreturn]]
+    void throw_runtime_error(std::string const& msg) {
+        throw_exception(std::runtime_error(msg));
+    }
+
+} // namespace Catch;
+// end catch_enforce.cpp
+// start catch_enum_values_registry.cpp
+// start catch_enum_values_registry.h
+
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    namespace Detail {
+
+        std::unique_ptr<EnumInfo> makeEnumInfo( StringRef enumName, StringRef allValueNames, std::vector<int> const& values );
+
+        class EnumValuesRegistry : public IMutableEnumValuesRegistry {
+
+            std::vector<std::unique_ptr<EnumInfo>> m_enumInfos;
+
+            EnumInfo const& registerEnum( StringRef enumName, StringRef allEnums, std::vector<int> const& values) override;
+        };
+
+        std::vector<StringRef> parseEnums( StringRef enums );
+
+    } // Detail
+
+} // Catch
+
+// end catch_enum_values_registry.h
+
+#include <map>
+#include <cassert>
+
+namespace Catch {
+
+    IMutableEnumValuesRegistry::~IMutableEnumValuesRegistry() {}
+
+    namespace Detail {
+
+        namespace {
+            // Extracts the actual name part of an enum instance
+            // In other words, it returns the Blue part of Bikeshed::Colour::Blue
+            StringRef extractInstanceName(StringRef enumInstance) {
+                // Find last occurence of ":"
+                size_t name_start = enumInstance.size();
+                while (name_start > 0 && enumInstance[name_start - 1] != ':') {
+                    --name_start;
+                }
+                return enumInstance.substr(name_start, enumInstance.size() - name_start);
+            }
+        }
+
+        std::vector<StringRef> parseEnums( StringRef enums ) {
+            auto enumValues = splitStringRef( enums, ',' );
+            std::vector<StringRef> parsed;
+            parsed.reserve( enumValues.size() );
+            for( auto const& enumValue : enumValues ) {
+                parsed.push_back(trim(extractInstanceName(enumValue)));
+            }
+            return parsed;
+        }
+
+        EnumInfo::~EnumInfo() {}
+
+        StringRef EnumInfo::lookup( int value ) const {
+            for( auto const& valueToName : m_values ) {
+                if( valueToName.first == value )
+                    return valueToName.second;
+            }
+            return "{** unexpected enum value **}"_sr;
+        }
+
+        std::unique_ptr<EnumInfo> makeEnumInfo( StringRef enumName, StringRef allValueNames, std::vector<int> const& values ) {
+            std::unique_ptr<EnumInfo> enumInfo( new EnumInfo );
+            enumInfo->m_name = enumName;
+            enumInfo->m_values.reserve( values.size() );
+
+            const auto valueNames = Catch::Detail::parseEnums( allValueNames );
+            assert( valueNames.size() == values.size() );
+            std::size_t i = 0;
+            for( auto value : values )
+                enumInfo->m_values.emplace_back(value, valueNames[i++]);
+
+            return enumInfo;
+        }
+
+        EnumInfo const& EnumValuesRegistry::registerEnum( StringRef enumName, StringRef allValueNames, std::vector<int> const& values ) {
+            m_enumInfos.push_back(makeEnumInfo(enumName, allValueNames, values));
+            return *m_enumInfos.back();
+        }
+
+    } // Detail
+} // Catch
+
+// end catch_enum_values_registry.cpp
+// start catch_errno_guard.cpp
+
+#include <cerrno>
+
+namespace Catch {
+        ErrnoGuard::ErrnoGuard():m_oldErrno(errno){}
+        ErrnoGuard::~ErrnoGuard() { errno = m_oldErrno; }
+}
+// end catch_errno_guard.cpp
+// start catch_exception_translator_registry.cpp
+
+// start catch_exception_translator_registry.h
+
+#include <vector>
+#include <string>
+#include <memory>
+
+namespace Catch {
+
+    class ExceptionTranslatorRegistry : public IExceptionTranslatorRegistry {
+    public:
+        ~ExceptionTranslatorRegistry();
+        virtual void registerTranslator( const IExceptionTranslator* translator );
+        std::string translateActiveException() const override;
+        std::string tryTranslators() const;
+
+    private:
+        std::vector<std::unique_ptr<IExceptionTranslator const>> m_translators;
+    };
+}
+
+// end catch_exception_translator_registry.h
+#ifdef __OBJC__
+#import "Foundation/Foundation.h"
+#endif
+
+namespace Catch {
+
+    ExceptionTranslatorRegistry::~ExceptionTranslatorRegistry() {
+    }
+
+    void ExceptionTranslatorRegistry::registerTranslator( const IExceptionTranslator* translator ) {
+        m_translators.push_back( std::unique_ptr<const IExceptionTranslator>( translator ) );
+    }
+
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+    std::string ExceptionTranslatorRegistry::translateActiveException() const {
+        try {
+#ifdef __OBJC__
+            // In Objective-C try objective-c exceptions first
+            @try {
+                return tryTranslators();
+            }
+            @catch (NSException *exception) {
+                return Catch::Detail::stringify( [exception description] );
+            }
+#else
+            // Compiling a mixed mode project with MSVC means that CLR
+            // exceptions will be caught in (...) as well. However, these
+            // do not fill-in std::current_exception and thus lead to crash
+            // when attempting rethrow.
+            // /EHa switch also causes structured exceptions to be caught
+            // here, but they fill-in current_exception properly, so
+            // at worst the output should be a little weird, instead of
+            // causing a crash.
+            if (std::current_exception() == nullptr) {
+                return "Non C++ exception. Possibly a CLR exception.";
+            }
+            return tryTranslators();
+#endif
+        }
+        catch( TestFailureException& ) {
+            std::rethrow_exception(std::current_exception());
+        }
+        catch( std::exception& ex ) {
+            return ex.what();
+        }
+        catch( std::string& msg ) {
+            return msg;
+        }
+        catch( const char* msg ) {
+            return msg;
+        }
+        catch(...) {
+            return "Unknown exception";
+        }
+    }
+
+    std::string ExceptionTranslatorRegistry::tryTranslators() const {
+        if (m_translators.empty()) {
+            std::rethrow_exception(std::current_exception());
+        } else {
+            return m_translators[0]->translate(m_translators.begin() + 1, m_translators.end());
+        }
+    }
+
+#else // ^^ Exceptions are enabled // Exceptions are disabled vv
+    std::string ExceptionTranslatorRegistry::translateActiveException() const {
+        CATCH_INTERNAL_ERROR("Attempted to translate active exception under CATCH_CONFIG_DISABLE_EXCEPTIONS!");
+    }
+
+    std::string ExceptionTranslatorRegistry::tryTranslators() const {
+        CATCH_INTERNAL_ERROR("Attempted to use exception translators under CATCH_CONFIG_DISABLE_EXCEPTIONS!");
+    }
+#endif
+
+}
+// end catch_exception_translator_registry.cpp
+// start catch_fatal_condition.cpp
+
+#if defined(__GNUC__)
+#    pragma GCC diagnostic push
+#    pragma GCC diagnostic ignored "-Wmissing-field-initializers"
+#endif
+
+#if defined( CATCH_CONFIG_WINDOWS_SEH ) || defined( CATCH_CONFIG_POSIX_SIGNALS )
+
+namespace {
+    // Report the error condition
+    void reportFatal( char const * const message ) {
+        Catch::getCurrentContext().getResultCapture()->handleFatalErrorCondition( message );
+    }
+}
+
+#endif // signals/SEH handling
+
+#if defined( CATCH_CONFIG_WINDOWS_SEH )
+
+namespace Catch {
+    struct SignalDefs { DWORD id; const char* name; };
+
+    // There is no 1-1 mapping between signals and windows exceptions.
+    // Windows can easily distinguish between SO and SigSegV,
+    // but SigInt, SigTerm, etc are handled differently.
+    static SignalDefs signalDefs[] = {
+        { static_cast<DWORD>(EXCEPTION_ILLEGAL_INSTRUCTION),  "SIGILL - Illegal instruction signal" },
+        { static_cast<DWORD>(EXCEPTION_STACK_OVERFLOW), "SIGSEGV - Stack overflow" },
+        { static_cast<DWORD>(EXCEPTION_ACCESS_VIOLATION), "SIGSEGV - Segmentation violation signal" },
+        { static_cast<DWORD>(EXCEPTION_INT_DIVIDE_BY_ZERO), "Divide by zero error" },
+    };
+
+    LONG CALLBACK FatalConditionHandler::handleVectoredException(PEXCEPTION_POINTERS ExceptionInfo) {
+        for (auto const& def : signalDefs) {
+            if (ExceptionInfo->ExceptionRecord->ExceptionCode == def.id) {
+                reportFatal(def.name);
+            }
+        }
+        // If its not an exception we care about, pass it along.
+        // This stops us from eating debugger breaks etc.
+        return EXCEPTION_CONTINUE_SEARCH;
+    }
+
+    FatalConditionHandler::FatalConditionHandler() {
+        isSet = true;
+        // 32k seems enough for Catch to handle stack overflow,
+        // but the value was found experimentally, so there is no strong guarantee
+        guaranteeSize = 32 * 1024;
+        exceptionHandlerHandle = nullptr;
+        // Register as first handler in current chain
+        exceptionHandlerHandle = AddVectoredExceptionHandler(1, handleVectoredException);
+        // Pass in guarantee size to be filled
+        SetThreadStackGuarantee(&guaranteeSize);
+    }
+
+    void FatalConditionHandler::reset() {
+        if (isSet) {
+            RemoveVectoredExceptionHandler(exceptionHandlerHandle);
+            SetThreadStackGuarantee(&guaranteeSize);
+            exceptionHandlerHandle = nullptr;
+            isSet = false;
+        }
+    }
+
+    FatalConditionHandler::~FatalConditionHandler() {
+        reset();
+    }
+
+bool FatalConditionHandler::isSet = false;
+ULONG FatalConditionHandler::guaranteeSize = 0;
+PVOID FatalConditionHandler::exceptionHandlerHandle = nullptr;
+
+} // namespace Catch
+
+#elif defined( CATCH_CONFIG_POSIX_SIGNALS )
+
+namespace Catch {
+
+    struct SignalDefs {
+        int id;
+        const char* name;
+    };
+
+    // 32kb for the alternate stack seems to be sufficient. However, this value
+    // is experimentally determined, so that's not guaranteed.
+    static constexpr std::size_t sigStackSize = 32768 >= MINSIGSTKSZ ? 32768 : MINSIGSTKSZ;
+
+    static SignalDefs signalDefs[] = {
+        { SIGINT,  "SIGINT - Terminal interrupt signal" },
+        { SIGILL,  "SIGILL - Illegal instruction signal" },
+        { SIGFPE,  "SIGFPE - Floating point error signal" },
+        { SIGSEGV, "SIGSEGV - Segmentation violation signal" },
+        { SIGTERM, "SIGTERM - Termination request signal" },
+        { SIGABRT, "SIGABRT - Abort (abnormal termination) signal" }
+    };
+
+    void FatalConditionHandler::handleSignal( int sig ) {
+        char const * name = "<unknown signal>";
+        for (auto const& def : signalDefs) {
+            if (sig == def.id) {
+                name = def.name;
+                break;
+            }
+        }
+        reset();
+        reportFatal(name);
+        raise( sig );
+    }
+
+    FatalConditionHandler::FatalConditionHandler() {
+        isSet = true;
+        stack_t sigStack;
+        sigStack.ss_sp = altStackMem;
+        sigStack.ss_size = sigStackSize;
+        sigStack.ss_flags = 0;
+        sigaltstack(&sigStack, &oldSigStack);
+        struct sigaction sa = { };
+
+        sa.sa_handler = handleSignal;
+        sa.sa_flags = SA_ONSTACK;
+        for (std::size_t i = 0; i < sizeof(signalDefs)/sizeof(SignalDefs); ++i) {
+            sigaction(signalDefs[i].id, &sa, &oldSigActions[i]);
+        }
+    }
+
+    FatalConditionHandler::~FatalConditionHandler() {
+        reset();
+    }
+
+    void FatalConditionHandler::reset() {
+        if( isSet ) {
+            // Set signals back to previous values -- hopefully nobody overwrote them in the meantime
+            for( std::size_t i = 0; i < sizeof(signalDefs)/sizeof(SignalDefs); ++i ) {
+                sigaction(signalDefs[i].id, &oldSigActions[i], nullptr);
+            }
+            // Return the old stack
+            sigaltstack(&oldSigStack, nullptr);
+            isSet = false;
+        }
+    }
+
+    bool FatalConditionHandler::isSet = false;
+    struct sigaction FatalConditionHandler::oldSigActions[sizeof(signalDefs)/sizeof(SignalDefs)] = {};
+    stack_t FatalConditionHandler::oldSigStack = {};
+    char FatalConditionHandler::altStackMem[sigStackSize] = {};
+
+} // namespace Catch
+
+#else
+
+namespace Catch {
+    void FatalConditionHandler::reset() {}
+}
+
+#endif // signals/SEH handling
+
+#if defined(__GNUC__)
+#    pragma GCC diagnostic pop
+#endif
+// end catch_fatal_condition.cpp
+// start catch_generators.cpp
+
+#include <limits>
+#include <set>
+
+namespace Catch {
+
+IGeneratorTracker::~IGeneratorTracker() {}
+
+const char* GeneratorException::what() const noexcept {
+    return m_msg;
+}
+
+namespace Generators {
+
+    GeneratorUntypedBase::~GeneratorUntypedBase() {}
+
+    auto acquireGeneratorTracker( SourceLineInfo const& lineInfo ) -> IGeneratorTracker& {
+        return getResultCapture().acquireGeneratorTracker( lineInfo );
+    }
+
+} // namespace Generators
+} // namespace Catch
+// end catch_generators.cpp
+// start catch_interfaces_capture.cpp
+
+namespace Catch {
+    IResultCapture::~IResultCapture() = default;
+}
+// end catch_interfaces_capture.cpp
+// start catch_interfaces_config.cpp
+
+namespace Catch {
+    IConfig::~IConfig() = default;
+}
+// end catch_interfaces_config.cpp
+// start catch_interfaces_exception.cpp
+
+namespace Catch {
+    IExceptionTranslator::~IExceptionTranslator() = default;
+    IExceptionTranslatorRegistry::~IExceptionTranslatorRegistry() = default;
+}
+// end catch_interfaces_exception.cpp
+// start catch_interfaces_registry_hub.cpp
+
+namespace Catch {
+    IRegistryHub::~IRegistryHub() = default;
+    IMutableRegistryHub::~IMutableRegistryHub() = default;
+}
+// end catch_interfaces_registry_hub.cpp
+// start catch_interfaces_reporter.cpp
+
+// start catch_reporter_listening.h
+
+namespace Catch {
+
+    class ListeningReporter : public IStreamingReporter {
+        using Reporters = std::vector<IStreamingReporterPtr>;
+        Reporters m_listeners;
+        IStreamingReporterPtr m_reporter = nullptr;
+        ReporterPreferences m_preferences;
+
+    public:
+        ListeningReporter();
+
+        void addListener( IStreamingReporterPtr&& listener );
+        void addReporter( IStreamingReporterPtr&& reporter );
+
+    public: // IStreamingReporter
+
+        ReporterPreferences getPreferences() const override;
+
+        void noMatchingTestCases( std::string const& spec ) override;
+
+        void reportInvalidArguments(std::string const&arg) override;
+
+        static std::set<Verbosity> getSupportedVerbosities();
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        void benchmarkPreparing(std::string const& name) override;
+        void benchmarkStarting( BenchmarkInfo const& benchmarkInfo ) override;
+        void benchmarkEnded( BenchmarkStats<> const& benchmarkStats ) override;
+        void benchmarkFailed(std::string const&) override;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        void testRunStarting( TestRunInfo const& testRunInfo ) override;
+        void testGroupStarting( GroupInfo const& groupInfo ) override;
+        void testCaseStarting( TestCaseInfo const& testInfo ) override;
+        void sectionStarting( SectionInfo const& sectionInfo ) override;
+        void assertionStarting( AssertionInfo const& assertionInfo ) override;
+
+        // The return value indicates if the messages buffer should be cleared:
+        bool assertionEnded( AssertionStats const& assertionStats ) override;
+        void sectionEnded( SectionStats const& sectionStats ) override;
+        void testCaseEnded( TestCaseStats const& testCaseStats ) override;
+        void testGroupEnded( TestGroupStats const& testGroupStats ) override;
+        void testRunEnded( TestRunStats const& testRunStats ) override;
+
+        void skipTest( TestCaseInfo const& testInfo ) override;
+        bool isMulti() const override;
+
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_listening.h
+namespace Catch {
+
+    ReporterConfig::ReporterConfig( IConfigPtr const& _fullConfig )
+    :   m_stream( &_fullConfig->stream() ), m_fullConfig( _fullConfig ) {}
+
+    ReporterConfig::ReporterConfig( IConfigPtr const& _fullConfig, std::ostream& _stream )
+    :   m_stream( &_stream ), m_fullConfig( _fullConfig ) {}
+
+    std::ostream& ReporterConfig::stream() const { return *m_stream; }
+    IConfigPtr ReporterConfig::fullConfig() const { return m_fullConfig; }
+
+    TestRunInfo::TestRunInfo( std::string const& _name ) : name( _name ) {}
+
+    GroupInfo::GroupInfo(  std::string const& _name,
+                           std::size_t _groupIndex,
+                           std::size_t _groupsCount )
+    :   name( _name ),
+        groupIndex( _groupIndex ),
+        groupsCounts( _groupsCount )
+    {}
+
+     AssertionStats::AssertionStats( AssertionResult const& _assertionResult,
+                                     std::vector<MessageInfo> const& _infoMessages,
+                                     Totals const& _totals )
+    :   assertionResult( _assertionResult ),
+        infoMessages( _infoMessages ),
+        totals( _totals )
+    {
+        assertionResult.m_resultData.lazyExpression.m_transientExpression = _assertionResult.m_resultData.lazyExpression.m_transientExpression;
+
+        if( assertionResult.hasMessage() ) {
+            // Copy message into messages list.
+            // !TBD This should have been done earlier, somewhere
+            MessageBuilder builder( assertionResult.getTestMacroName(), assertionResult.getSourceInfo(), assertionResult.getResultType() );
+            builder << assertionResult.getMessage();
+            builder.m_info.message = builder.m_stream.str();
+
+            infoMessages.push_back( builder.m_info );
+        }
+    }
+
+     AssertionStats::~AssertionStats() = default;
+
+    SectionStats::SectionStats(  SectionInfo const& _sectionInfo,
+                                 Counts const& _assertions,
+                                 double _durationInSeconds,
+                                 bool _missingAssertions )
+    :   sectionInfo( _sectionInfo ),
+        assertions( _assertions ),
+        durationInSeconds( _durationInSeconds ),
+        missingAssertions( _missingAssertions )
+    {}
+
+    SectionStats::~SectionStats() = default;
+
+    TestCaseStats::TestCaseStats(  TestCaseInfo const& _testInfo,
+                                   Totals const& _totals,
+                                   std::string const& _stdOut,
+                                   std::string const& _stdErr,
+                                   bool _aborting )
+    : testInfo( _testInfo ),
+        totals( _totals ),
+        stdOut( _stdOut ),
+        stdErr( _stdErr ),
+        aborting( _aborting )
+    {}
+
+    TestCaseStats::~TestCaseStats() = default;
+
+    TestGroupStats::TestGroupStats( GroupInfo const& _groupInfo,
+                                    Totals const& _totals,
+                                    bool _aborting )
+    :   groupInfo( _groupInfo ),
+        totals( _totals ),
+        aborting( _aborting )
+    {}
+
+    TestGroupStats::TestGroupStats( GroupInfo const& _groupInfo )
+    :   groupInfo( _groupInfo ),
+        aborting( false )
+    {}
+
+    TestGroupStats::~TestGroupStats() = default;
+
+    TestRunStats::TestRunStats(   TestRunInfo const& _runInfo,
+                    Totals const& _totals,
+                    bool _aborting )
+    :   runInfo( _runInfo ),
+        totals( _totals ),
+        aborting( _aborting )
+    {}
+
+    TestRunStats::~TestRunStats() = default;
+
+    void IStreamingReporter::fatalErrorEncountered( StringRef ) {}
+    bool IStreamingReporter::isMulti() const { return false; }
+
+    IReporterFactory::~IReporterFactory() = default;
+    IReporterRegistry::~IReporterRegistry() = default;
+
+} // end namespace Catch
+// end catch_interfaces_reporter.cpp
+// start catch_interfaces_runner.cpp
+
+namespace Catch {
+    IRunner::~IRunner() = default;
+}
+// end catch_interfaces_runner.cpp
+// start catch_interfaces_testcase.cpp
+
+namespace Catch {
+    ITestInvoker::~ITestInvoker() = default;
+    ITestCaseRegistry::~ITestCaseRegistry() = default;
+}
+// end catch_interfaces_testcase.cpp
+// start catch_leak_detector.cpp
+
+#ifdef CATCH_CONFIG_WINDOWS_CRTDBG
+#include <crtdbg.h>
+
+namespace Catch {
+
+    LeakDetector::LeakDetector() {
+        int flag = _CrtSetDbgFlag(_CRTDBG_REPORT_FLAG);
+        flag |= _CRTDBG_LEAK_CHECK_DF;
+        flag |= _CRTDBG_ALLOC_MEM_DF;
+        _CrtSetDbgFlag(flag);
+        _CrtSetReportMode(_CRT_WARN, _CRTDBG_MODE_FILE | _CRTDBG_MODE_DEBUG);
+        _CrtSetReportFile(_CRT_WARN, _CRTDBG_FILE_STDERR);
+        // Change this to leaking allocation's number to break there
+        _CrtSetBreakAlloc(-1);
+    }
+}
+
+#else
+
+    Catch::LeakDetector::LeakDetector() {}
+
+#endif
+
+Catch::LeakDetector::~LeakDetector() {
+    Catch::cleanUp();
+}
+// end catch_leak_detector.cpp
+// start catch_list.cpp
+
+// start catch_list.h
+
+#include <set>
+
+namespace Catch {
+
+    std::size_t listTests( Config const& config );
+
+    std::size_t listTestsNamesOnly( Config const& config );
+
+    struct TagInfo {
+        void add( std::string const& spelling );
+        std::string all() const;
+
+        std::set<std::string> spellings;
+        std::size_t count = 0;
+    };
+
+    std::size_t listTags( Config const& config );
+
+    std::size_t listReporters();
+
+    Option<std::size_t> list( std::shared_ptr<Config> const& config );
+
+} // end namespace Catch
+
+// end catch_list.h
+// start catch_text.h
+
+namespace Catch {
+    using namespace clara::TextFlow;
+}
+
+// end catch_text.h
+#include <limits>
+#include <algorithm>
+#include <iomanip>
+
+namespace Catch {
+
+    std::size_t listTests( Config const& config ) {
+        TestSpec const& testSpec = config.testSpec();
+        if( config.hasTestFilters() )
+            Catch::cout() << "Matching test cases:\n";
+        else {
+            Catch::cout() << "All available test cases:\n";
+        }
+
+        auto matchedTestCases = filterTests( getAllTestCasesSorted( config ), testSpec, config );
+        for( auto const& testCaseInfo : matchedTestCases ) {
+            Colour::Code colour = testCaseInfo.isHidden()
+                ? Colour::SecondaryText
+                : Colour::None;
+            Colour colourGuard( colour );
+
+            Catch::cout() << Column( testCaseInfo.name ).initialIndent( 2 ).indent( 4 ) << "\n";
+            if( config.verbosity() >= Verbosity::High ) {
+                Catch::cout() << Column( Catch::Detail::stringify( testCaseInfo.lineInfo ) ).indent(4) << std::endl;
+                std::string description = testCaseInfo.description;
+                if( description.empty() )
+                    description = "(NO DESCRIPTION)";
+                Catch::cout() << Column( description ).indent(4) << std::endl;
+            }
+            if( !testCaseInfo.tags.empty() )
+                Catch::cout() << Column( testCaseInfo.tagsAsString() ).indent( 6 ) << "\n";
+        }
+
+        if( !config.hasTestFilters() )
+            Catch::cout() << pluralise( matchedTestCases.size(), "test case" ) << '\n' << std::endl;
+        else
+            Catch::cout() << pluralise( matchedTestCases.size(), "matching test case" ) << '\n' << std::endl;
+        return matchedTestCases.size();
+    }
+
+    std::size_t listTestsNamesOnly( Config const& config ) {
+        TestSpec const& testSpec = config.testSpec();
+        std::size_t matchedTests = 0;
+        std::vector<TestCase> matchedTestCases = filterTests( getAllTestCasesSorted( config ), testSpec, config );
+        for( auto const& testCaseInfo : matchedTestCases ) {
+            matchedTests++;
+            if( startsWith( testCaseInfo.name, '#' ) )
+               Catch::cout() << '"' << testCaseInfo.name << '"';
+            else
+               Catch::cout() << testCaseInfo.name;
+            if ( config.verbosity() >= Verbosity::High )
+                Catch::cout() << "\t@" << testCaseInfo.lineInfo;
+            Catch::cout() << std::endl;
+        }
+        return matchedTests;
+    }
+
+    void TagInfo::add( std::string const& spelling ) {
+        ++count;
+        spellings.insert( spelling );
+    }
+
+    std::string TagInfo::all() const {
+        size_t size = 0;
+        for (auto const& spelling : spellings) {
+            // Add 2 for the brackes
+            size += spelling.size() + 2;
+        }
+
+        std::string out; out.reserve(size);
+        for (auto const& spelling : spellings) {
+            out += '[';
+            out += spelling;
+            out += ']';
+        }
+        return out;
+    }
+
+    std::size_t listTags( Config const& config ) {
+        TestSpec const& testSpec = config.testSpec();
+        if( config.hasTestFilters() )
+            Catch::cout() << "Tags for matching test cases:\n";
+        else {
+            Catch::cout() << "All available tags:\n";
+        }
+
+        std::map<std::string, TagInfo> tagCounts;
+
+        std::vector<TestCase> matchedTestCases = filterTests( getAllTestCasesSorted( config ), testSpec, config );
+        for( auto const& testCase : matchedTestCases ) {
+            for( auto const& tagName : testCase.getTestCaseInfo().tags ) {
+                std::string lcaseTagName = toLower( tagName );
+                auto countIt = tagCounts.find( lcaseTagName );
+                if( countIt == tagCounts.end() )
+                    countIt = tagCounts.insert( std::make_pair( lcaseTagName, TagInfo() ) ).first;
+                countIt->second.add( tagName );
+            }
+        }
+
+        for( auto const& tagCount : tagCounts ) {
+            ReusableStringStream rss;
+            rss << "  " << std::setw(2) << tagCount.second.count << "  ";
+            auto str = rss.str();
+            auto wrapper = Column( tagCount.second.all() )
+                                                    .initialIndent( 0 )
+                                                    .indent( str.size() )
+                                                    .width( CATCH_CONFIG_CONSOLE_WIDTH-10 );
+            Catch::cout() << str << wrapper << '\n';
+        }
+        Catch::cout() << pluralise( tagCounts.size(), "tag" ) << '\n' << std::endl;
+        return tagCounts.size();
+    }
+
+    std::size_t listReporters() {
+        Catch::cout() << "Available reporters:\n";
+        IReporterRegistry::FactoryMap const& factories = getRegistryHub().getReporterRegistry().getFactories();
+        std::size_t maxNameLen = 0;
+        for( auto const& factoryKvp : factories )
+            maxNameLen = (std::max)( maxNameLen, factoryKvp.first.size() );
+
+        for( auto const& factoryKvp : factories ) {
+            Catch::cout()
+                    << Column( factoryKvp.first + ":" )
+                            .indent(2)
+                            .width( 5+maxNameLen )
+                    +  Column( factoryKvp.second->getDescription() )
+                            .initialIndent(0)
+                            .indent(2)
+                            .width( CATCH_CONFIG_CONSOLE_WIDTH - maxNameLen-8 )
+                    << "\n";
+        }
+        Catch::cout() << std::endl;
+        return factories.size();
+    }
+
+    Option<std::size_t> list( std::shared_ptr<Config> const& config ) {
+        Option<std::size_t> listedCount;
+        getCurrentMutableContext().setConfig( config );
+        if( config->listTests() )
+            listedCount = listedCount.valueOr(0) + listTests( *config );
+        if( config->listTestNamesOnly() )
+            listedCount = listedCount.valueOr(0) + listTestsNamesOnly( *config );
+        if( config->listTags() )
+            listedCount = listedCount.valueOr(0) + listTags( *config );
+        if( config->listReporters() )
+            listedCount = listedCount.valueOr(0) + listReporters();
+        return listedCount;
+    }
+
+} // end namespace Catch
+// end catch_list.cpp
+// start catch_matchers.cpp
+
+namespace Catch {
+namespace Matchers {
+    namespace Impl {
+
+        std::string MatcherUntypedBase::toString() const {
+            if( m_cachedToString.empty() )
+                m_cachedToString = describe();
+            return m_cachedToString;
+        }
+
+        MatcherUntypedBase::~MatcherUntypedBase() = default;
+
+    } // namespace Impl
+} // namespace Matchers
+
+using namespace Matchers;
+using Matchers::Impl::MatcherBase;
+
+} // namespace Catch
+// end catch_matchers.cpp
+// start catch_matchers_exception.cpp
+
+namespace Catch {
+namespace Matchers {
+namespace Exception {
+
+bool ExceptionMessageMatcher::match(std::exception const& ex) const {
+    return ex.what() == m_message;
+}
+
+std::string ExceptionMessageMatcher::describe() const {
+    return "exception message matches \"" + m_message + "\"";
+}
+
+}
+Exception::ExceptionMessageMatcher Message(std::string const& message) {
+    return Exception::ExceptionMessageMatcher(message);
+}
+
+// namespace Exception
+} // namespace Matchers
+} // namespace Catch
+// end catch_matchers_exception.cpp
+// start catch_matchers_floating.cpp
+
+// start catch_polyfills.hpp
+
+namespace Catch {
+    bool isnan(float f);
+    bool isnan(double d);
+}
+
+// end catch_polyfills.hpp
+// start catch_to_string.hpp
+
+#include <string>
+
+namespace Catch {
+    template <typename T>
+    std::string to_string(T const& t) {
+#if defined(CATCH_CONFIG_CPP11_TO_STRING)
+        return std::to_string(t);
+#else
+        ReusableStringStream rss;
+        rss << t;
+        return rss.str();
+#endif
+    }
+} // end namespace Catch
+
+// end catch_to_string.hpp
+#include <algorithm>
+#include <cmath>
+#include <cstdlib>
+#include <cstdint>
+#include <cstring>
+#include <sstream>
+#include <type_traits>
+#include <iomanip>
+#include <limits>
+
+namespace Catch {
+namespace {
+
+    int32_t convert(float f) {
+        static_assert(sizeof(float) == sizeof(int32_t), "Important ULP matcher assumption violated");
+        int32_t i;
+        std::memcpy(&i, &f, sizeof(f));
+        return i;
+    }
+
+    int64_t convert(double d) {
+        static_assert(sizeof(double) == sizeof(int64_t), "Important ULP matcher assumption violated");
+        int64_t i;
+        std::memcpy(&i, &d, sizeof(d));
+        return i;
+    }
+
+    template <typename FP>
+    bool almostEqualUlps(FP lhs, FP rhs, uint64_t maxUlpDiff) {
+        // Comparison with NaN should always be false.
+        // This way we can rule it out before getting into the ugly details
+        if (Catch::isnan(lhs) || Catch::isnan(rhs)) {
+            return false;
+        }
+
+        auto lc = convert(lhs);
+        auto rc = convert(rhs);
+
+        if ((lc < 0) != (rc < 0)) {
+            // Potentially we can have +0 and -0
+            return lhs == rhs;
+        }
+
+        auto ulpDiff = std::abs(lc - rc);
+        return static_cast<uint64_t>(ulpDiff) <= maxUlpDiff;
+    }
+
+#if defined(CATCH_CONFIG_GLOBAL_NEXTAFTER)
+
+    float nextafter(float x, float y) {
+        return ::nextafterf(x, y);
+    }
+
+    double nextafter(double x, double y) {
+        return ::nextafter(x, y);
+    }
+
+#endif // ^^^ CATCH_CONFIG_GLOBAL_NEXTAFTER ^^^
+
+template <typename FP>
+FP step(FP start, FP direction, uint64_t steps) {
+    for (uint64_t i = 0; i < steps; ++i) {
+#if defined(CATCH_CONFIG_GLOBAL_NEXTAFTER)
+        start = Catch::nextafter(start, direction);
+#else
+        start = std::nextafter(start, direction);
+#endif
+    }
+    return start;
+}
+
+// Performs equivalent check of std::fabs(lhs - rhs) <= margin
+// But without the subtraction to allow for INFINITY in comparison
+bool marginComparison(double lhs, double rhs, double margin) {
+    return (lhs + margin >= rhs) && (rhs + margin >= lhs);
+}
+
+template <typename FloatingPoint>
+void write(std::ostream& out, FloatingPoint num) {
+    out << std::scientific
+        << std::setprecision(std::numeric_limits<FloatingPoint>::max_digits10 - 1)
+        << num;
+}
+
+} // end anonymous namespace
+
+namespace Matchers {
+namespace Floating {
+
+    enum class FloatingPointKind : uint8_t {
+        Float,
+        Double
+    };
+
+    WithinAbsMatcher::WithinAbsMatcher(double target, double margin)
+        :m_target{ target }, m_margin{ margin } {
+        CATCH_ENFORCE(margin >= 0, "Invalid margin: " << margin << '.'
+            << " Margin has to be non-negative.");
+    }
+
+    // Performs equivalent check of std::fabs(lhs - rhs) <= margin
+    // But without the subtraction to allow for INFINITY in comparison
+    bool WithinAbsMatcher::match(double const& matchee) const {
+        return (matchee + m_margin >= m_target) && (m_target + m_margin >= matchee);
+    }
+
+    std::string WithinAbsMatcher::describe() const {
+        return "is within " + ::Catch::Detail::stringify(m_margin) + " of " + ::Catch::Detail::stringify(m_target);
+    }
+
+    WithinUlpsMatcher::WithinUlpsMatcher(double target, uint64_t ulps, FloatingPointKind baseType)
+        :m_target{ target }, m_ulps{ ulps }, m_type{ baseType } {
+        CATCH_ENFORCE(m_type == FloatingPointKind::Double
+                   || m_ulps < (std::numeric_limits<uint32_t>::max)(),
+            "Provided ULP is impossibly large for a float comparison.");
+    }
+
+#if defined(__clang__)
+#pragma clang diagnostic push
+// Clang <3.5 reports on the default branch in the switch below
+#pragma clang diagnostic ignored "-Wunreachable-code"
+#endif
+
+    bool WithinUlpsMatcher::match(double const& matchee) const {
+        switch (m_type) {
+        case FloatingPointKind::Float:
+            return almostEqualUlps<float>(static_cast<float>(matchee), static_cast<float>(m_target), m_ulps);
+        case FloatingPointKind::Double:
+            return almostEqualUlps<double>(matchee, m_target, m_ulps);
+        default:
+            CATCH_INTERNAL_ERROR( "Unknown FloatingPointKind value" );
+        }
+    }
+
+#if defined(__clang__)
+#pragma clang diagnostic pop
+#endif
+
+    std::string WithinUlpsMatcher::describe() const {
+        std::stringstream ret;
+
+        ret << "is within " << m_ulps << " ULPs of ";
+
+        if (m_type == FloatingPointKind::Float) {
+            write(ret, static_cast<float>(m_target));
+            ret << 'f';
+        } else {
+            write(ret, m_target);
+        }
+
+        ret << " ([";
+        if (m_type == FloatingPointKind::Double) {
+            write(ret, step(m_target, static_cast<double>(-INFINITY), m_ulps));
+            ret << ", ";
+            write(ret, step(m_target, static_cast<double>( INFINITY), m_ulps));
+        } else {
+            // We have to cast INFINITY to float because of MinGW, see #1782
+            write(ret, step(static_cast<float>(m_target), static_cast<float>(-INFINITY), m_ulps));
+            ret << ", ";
+            write(ret, step(static_cast<float>(m_target), static_cast<float>( INFINITY), m_ulps));
+        }
+        ret << "])";
+
+        return ret.str();
+    }
+
+    WithinRelMatcher::WithinRelMatcher(double target, double epsilon):
+        m_target(target),
+        m_epsilon(epsilon){
+        CATCH_ENFORCE(m_epsilon >= 0., "Relative comparison with epsilon <  0 does not make sense.");
+        CATCH_ENFORCE(m_epsilon  < 1., "Relative comparison with epsilon >= 1 does not make sense.");
+    }
+
+    bool WithinRelMatcher::match(double const& matchee) const {
+        const auto relMargin = m_epsilon * (std::max)(std::fabs(matchee), std::fabs(m_target));
+        return marginComparison(matchee, m_target,
+                                std::isinf(relMargin)? 0 : relMargin);
+    }
+
+    std::string WithinRelMatcher::describe() const {
+        Catch::ReusableStringStream sstr;
+        sstr << "and " << m_target << " are within " << m_epsilon * 100. << "% of each other";
+        return sstr.str();
+    }
+
+}// namespace Floating
+
+Floating::WithinUlpsMatcher WithinULP(double target, uint64_t maxUlpDiff) {
+    return Floating::WithinUlpsMatcher(target, maxUlpDiff, Floating::FloatingPointKind::Double);
+}
+
+Floating::WithinUlpsMatcher WithinULP(float target, uint64_t maxUlpDiff) {
+    return Floating::WithinUlpsMatcher(target, maxUlpDiff, Floating::FloatingPointKind::Float);
+}
+
+Floating::WithinAbsMatcher WithinAbs(double target, double margin) {
+    return Floating::WithinAbsMatcher(target, margin);
+}
+
+Floating::WithinRelMatcher WithinRel(double target, double eps) {
+    return Floating::WithinRelMatcher(target, eps);
+}
+
+Floating::WithinRelMatcher WithinRel(double target) {
+    return Floating::WithinRelMatcher(target, std::numeric_limits<double>::epsilon() * 100);
+}
+
+Floating::WithinRelMatcher WithinRel(float target, float eps) {
+    return Floating::WithinRelMatcher(target, eps);
+}
+
+Floating::WithinRelMatcher WithinRel(float target) {
+    return Floating::WithinRelMatcher(target, std::numeric_limits<float>::epsilon() * 100);
+}
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_floating.cpp
+// start catch_matchers_generic.cpp
+
+std::string Catch::Matchers::Generic::Detail::finalizeDescription(const std::string& desc) {
+    if (desc.empty()) {
+        return "matches undescribed predicate";
+    } else {
+        return "matches predicate: \"" + desc + '"';
+    }
+}
+// end catch_matchers_generic.cpp
+// start catch_matchers_string.cpp
+
+#include <regex>
+
+namespace Catch {
+namespace Matchers {
+
+    namespace StdString {
+
+        CasedString::CasedString( std::string const& str, CaseSensitive::Choice caseSensitivity )
+        :   m_caseSensitivity( caseSensitivity ),
+            m_str( adjustString( str ) )
+        {}
+        std::string CasedString::adjustString( std::string const& str ) const {
+            return m_caseSensitivity == CaseSensitive::No
+                   ? toLower( str )
+                   : str;
+        }
+        std::string CasedString::caseSensitivitySuffix() const {
+            return m_caseSensitivity == CaseSensitive::No
+                   ? " (case insensitive)"
+                   : std::string();
+        }
+
+        StringMatcherBase::StringMatcherBase( std::string const& operation, CasedString const& comparator )
+        : m_comparator( comparator ),
+          m_operation( operation ) {
+        }
+
+        std::string StringMatcherBase::describe() const {
+            std::string description;
+            description.reserve(5 + m_operation.size() + m_comparator.m_str.size() +
+                                        m_comparator.caseSensitivitySuffix().size());
+            description += m_operation;
+            description += ": \"";
+            description += m_comparator.m_str;
+            description += "\"";
+            description += m_comparator.caseSensitivitySuffix();
+            return description;
+        }
+
+        EqualsMatcher::EqualsMatcher( CasedString const& comparator ) : StringMatcherBase( "equals", comparator ) {}
+
+        bool EqualsMatcher::match( std::string const& source ) const {
+            return m_comparator.adjustString( source ) == m_comparator.m_str;
+        }
+
+        ContainsMatcher::ContainsMatcher( CasedString const& comparator ) : StringMatcherBase( "contains", comparator ) {}
+
+        bool ContainsMatcher::match( std::string const& source ) const {
+            return contains( m_comparator.adjustString( source ), m_comparator.m_str );
+        }
+
+        StartsWithMatcher::StartsWithMatcher( CasedString const& comparator ) : StringMatcherBase( "starts with", comparator ) {}
+
+        bool StartsWithMatcher::match( std::string const& source ) const {
+            return startsWith( m_comparator.adjustString( source ), m_comparator.m_str );
+        }
+
+        EndsWithMatcher::EndsWithMatcher( CasedString const& comparator ) : StringMatcherBase( "ends with", comparator ) {}
+
+        bool EndsWithMatcher::match( std::string const& source ) const {
+            return endsWith( m_comparator.adjustString( source ), m_comparator.m_str );
+        }
+
+        RegexMatcher::RegexMatcher(std::string regex, CaseSensitive::Choice caseSensitivity): m_regex(std::move(regex)), m_caseSensitivity(caseSensitivity) {}
+
+        bool RegexMatcher::match(std::string const& matchee) const {
+            auto flags = std::regex::ECMAScript; // ECMAScript is the default syntax option anyway
+            if (m_caseSensitivity == CaseSensitive::Choice::No) {
+                flags |= std::regex::icase;
+            }
+            auto reg = std::regex(m_regex, flags);
+            return std::regex_match(matchee, reg);
+        }
+
+        std::string RegexMatcher::describe() const {
+            return "matches " + ::Catch::Detail::stringify(m_regex) + ((m_caseSensitivity == CaseSensitive::Choice::Yes)? " case sensitively" : " case insensitively");
+        }
+
+    } // namespace StdString
+
+    StdString::EqualsMatcher Equals( std::string const& str, CaseSensitive::Choice caseSensitivity ) {
+        return StdString::EqualsMatcher( StdString::CasedString( str, caseSensitivity) );
+    }
+    StdString::ContainsMatcher Contains( std::string const& str, CaseSensitive::Choice caseSensitivity ) {
+        return StdString::ContainsMatcher( StdString::CasedString( str, caseSensitivity) );
+    }
+    StdString::EndsWithMatcher EndsWith( std::string const& str, CaseSensitive::Choice caseSensitivity ) {
+        return StdString::EndsWithMatcher( StdString::CasedString( str, caseSensitivity) );
+    }
+    StdString::StartsWithMatcher StartsWith( std::string const& str, CaseSensitive::Choice caseSensitivity ) {
+        return StdString::StartsWithMatcher( StdString::CasedString( str, caseSensitivity) );
+    }
+
+    StdString::RegexMatcher Matches(std::string const& regex, CaseSensitive::Choice caseSensitivity) {
+        return StdString::RegexMatcher(regex, caseSensitivity);
+    }
+
+} // namespace Matchers
+} // namespace Catch
+// end catch_matchers_string.cpp
+// start catch_message.cpp
+
+// start catch_uncaught_exceptions.h
+
+namespace Catch {
+    bool uncaught_exceptions();
+} // end namespace Catch
+
+// end catch_uncaught_exceptions.h
+#include <cassert>
+#include <stack>
+
+namespace Catch {
+
+    MessageInfo::MessageInfo(   StringRef const& _macroName,
+                                SourceLineInfo const& _lineInfo,
+                                ResultWas::OfType _type )
+    :   macroName( _macroName ),
+        lineInfo( _lineInfo ),
+        type( _type ),
+        sequence( ++globalCount )
+    {}
+
+    bool MessageInfo::operator==( MessageInfo const& other ) const {
+        return sequence == other.sequence;
+    }
+
+    bool MessageInfo::operator<( MessageInfo const& other ) const {
+        return sequence < other.sequence;
+    }
+
+    // This may need protecting if threading support is added
+    unsigned int MessageInfo::globalCount = 0;
+
+    ////////////////////////////////////////////////////////////////////////////
+
+    Catch::MessageBuilder::MessageBuilder( StringRef const& macroName,
+                                           SourceLineInfo const& lineInfo,
+                                           ResultWas::OfType type )
+        :m_info(macroName, lineInfo, type) {}
+
+    ////////////////////////////////////////////////////////////////////////////
+
+    ScopedMessage::ScopedMessage( MessageBuilder const& builder )
+    : m_info( builder.m_info ), m_moved()
+    {
+        m_info.message = builder.m_stream.str();
+        getResultCapture().pushScopedMessage( m_info );
+    }
+
+    ScopedMessage::ScopedMessage( ScopedMessage&& old )
+    : m_info( old.m_info ), m_moved()
+    {
+        old.m_moved = true;
+    }
+
+    ScopedMessage::~ScopedMessage() {
+        if ( !uncaught_exceptions() && !m_moved ){
+            getResultCapture().popScopedMessage(m_info);
+        }
+    }
+
+    Capturer::Capturer( StringRef macroName, SourceLineInfo const& lineInfo, ResultWas::OfType resultType, StringRef names ) {
+        auto trimmed = [&] (size_t start, size_t end) {
+            while (names[start] == ',' || isspace(names[start])) {
+                ++start;
+            }
+            while (names[end] == ',' || isspace(names[end])) {
+                --end;
+            }
+            return names.substr(start, end - start + 1);
+        };
+        auto skipq = [&] (size_t start, char quote) {
+            for (auto i = start + 1; i < names.size() ; ++i) {
+                if (names[i] == quote)
+                    return i;
+                if (names[i] == '\\')
+                    ++i;
+            }
+            CATCH_INTERNAL_ERROR("CAPTURE parsing encountered unmatched quote");
+        };
+
+        size_t start = 0;
+        std::stack<char> openings;
+        for (size_t pos = 0; pos < names.size(); ++pos) {
+            char c = names[pos];
+            switch (c) {
+            case '[':
+            case '{':
+            case '(':
+            // It is basically impossible to disambiguate between
+            // comparison and start of template args in this context
+//            case '<':
+                openings.push(c);
+                break;
+            case ']':
+            case '}':
+            case ')':
+//           case '>':
+                openings.pop();
+                break;
+            case '"':
+            case '\'':
+                pos = skipq(pos, c);
+                break;
+            case ',':
+                if (start != pos && openings.empty()) {
+                    m_messages.emplace_back(macroName, lineInfo, resultType);
+                    m_messages.back().message = static_cast<std::string>(trimmed(start, pos));
+                    m_messages.back().message += " := ";
+                    start = pos;
+                }
+            }
+        }
+        assert(openings.empty() && "Mismatched openings");
+        m_messages.emplace_back(macroName, lineInfo, resultType);
+        m_messages.back().message = static_cast<std::string>(trimmed(start, names.size() - 1));
+        m_messages.back().message += " := ";
+    }
+    Capturer::~Capturer() {
+        if ( !uncaught_exceptions() ){
+            assert( m_captured == m_messages.size() );
+            for( size_t i = 0; i < m_captured; ++i  )
+                m_resultCapture.popScopedMessage( m_messages[i] );
+        }
+    }
+
+    void Capturer::captureValue( size_t index, std::string const& value ) {
+        assert( index < m_messages.size() );
+        m_messages[index].message += value;
+        m_resultCapture.pushScopedMessage( m_messages[index] );
+        m_captured++;
+    }
+
+} // end namespace Catch
+// end catch_message.cpp
+// start catch_output_redirect.cpp
+
+// start catch_output_redirect.h
+#ifndef TWOBLUECUBES_CATCH_OUTPUT_REDIRECT_H
+#define TWOBLUECUBES_CATCH_OUTPUT_REDIRECT_H
+
+#include <cstdio>
+#include <iosfwd>
+#include <string>
+
+namespace Catch {
+
+    class RedirectedStream {
+        std::ostream& m_originalStream;
+        std::ostream& m_redirectionStream;
+        std::streambuf* m_prevBuf;
+
+    public:
+        RedirectedStream( std::ostream& originalStream, std::ostream& redirectionStream );
+        ~RedirectedStream();
+    };
+
+    class RedirectedStdOut {
+        ReusableStringStream m_rss;
+        RedirectedStream m_cout;
+    public:
+        RedirectedStdOut();
+        auto str() const -> std::string;
+    };
+
+    // StdErr has two constituent streams in C++, std::cerr and std::clog
+    // This means that we need to redirect 2 streams into 1 to keep proper
+    // order of writes
+    class RedirectedStdErr {
+        ReusableStringStream m_rss;
+        RedirectedStream m_cerr;
+        RedirectedStream m_clog;
+    public:
+        RedirectedStdErr();
+        auto str() const -> std::string;
+    };
+
+    class RedirectedStreams {
+    public:
+        RedirectedStreams(RedirectedStreams const&) = delete;
+        RedirectedStreams& operator=(RedirectedStreams const&) = delete;
+        RedirectedStreams(RedirectedStreams&&) = delete;
+        RedirectedStreams& operator=(RedirectedStreams&&) = delete;
+
+        RedirectedStreams(std::string& redirectedCout, std::string& redirectedCerr);
+        ~RedirectedStreams();
+    private:
+        std::string& m_redirectedCout;
+        std::string& m_redirectedCerr;
+        RedirectedStdOut m_redirectedStdOut;
+        RedirectedStdErr m_redirectedStdErr;
+    };
+
+#if defined(CATCH_CONFIG_NEW_CAPTURE)
+
+    // Windows's implementation of std::tmpfile is terrible (it tries
+    // to create a file inside system folder, thus requiring elevated
+    // privileges for the binary), so we have to use tmpnam(_s) and
+    // create the file ourselves there.
+    class TempFile {
+    public:
+        TempFile(TempFile const&) = delete;
+        TempFile& operator=(TempFile const&) = delete;
+        TempFile(TempFile&&) = delete;
+        TempFile& operator=(TempFile&&) = delete;
+
+        TempFile();
+        ~TempFile();
+
+        std::FILE* getFile();
+        std::string getContents();
+
+    private:
+        std::FILE* m_file = nullptr;
+    #if defined(_MSC_VER)
+        char m_buffer[L_tmpnam] = { 0 };
+    #endif
+    };
+
+    class OutputRedirect {
+    public:
+        OutputRedirect(OutputRedirect const&) = delete;
+        OutputRedirect& operator=(OutputRedirect const&) = delete;
+        OutputRedirect(OutputRedirect&&) = delete;
+        OutputRedirect& operator=(OutputRedirect&&) = delete;
+
+        OutputRedirect(std::string& stdout_dest, std::string& stderr_dest);
+        ~OutputRedirect();
+
+    private:
+        int m_originalStdout = -1;
+        int m_originalStderr = -1;
+        TempFile m_stdoutFile;
+        TempFile m_stderrFile;
+        std::string& m_stdoutDest;
+        std::string& m_stderrDest;
+    };
+
+#endif
+
+} // end namespace Catch
+
+#endif // TWOBLUECUBES_CATCH_OUTPUT_REDIRECT_H
+// end catch_output_redirect.h
+#include <cstdio>
+#include <cstring>
+#include <fstream>
+#include <sstream>
+#include <stdexcept>
+
+#if defined(CATCH_CONFIG_NEW_CAPTURE)
+    #if defined(_MSC_VER)
+    #include <io.h>      //_dup and _dup2
+    #define dup _dup
+    #define dup2 _dup2
+    #define fileno _fileno
+    #else
+    #include <unistd.h>  // dup and dup2
+    #endif
+#endif
+
+namespace Catch {
+
+    RedirectedStream::RedirectedStream( std::ostream& originalStream, std::ostream& redirectionStream )
+    :   m_originalStream( originalStream ),
+        m_redirectionStream( redirectionStream ),
+        m_prevBuf( m_originalStream.rdbuf() )
+    {
+        m_originalStream.rdbuf( m_redirectionStream.rdbuf() );
+    }
+
+    RedirectedStream::~RedirectedStream() {
+        m_originalStream.rdbuf( m_prevBuf );
+    }
+
+    RedirectedStdOut::RedirectedStdOut() : m_cout( Catch::cout(), m_rss.get() ) {}
+    auto RedirectedStdOut::str() const -> std::string { return m_rss.str(); }
+
+    RedirectedStdErr::RedirectedStdErr()
+    :   m_cerr( Catch::cerr(), m_rss.get() ),
+        m_clog( Catch::clog(), m_rss.get() )
+    {}
+    auto RedirectedStdErr::str() const -> std::string { return m_rss.str(); }
+
+    RedirectedStreams::RedirectedStreams(std::string& redirectedCout, std::string& redirectedCerr)
+    :   m_redirectedCout(redirectedCout),
+        m_redirectedCerr(redirectedCerr)
+    {}
+
+    RedirectedStreams::~RedirectedStreams() {
+        m_redirectedCout += m_redirectedStdOut.str();
+        m_redirectedCerr += m_redirectedStdErr.str();
+    }
+
+#if defined(CATCH_CONFIG_NEW_CAPTURE)
+
+#if defined(_MSC_VER)
+    TempFile::TempFile() {
+        if (tmpnam_s(m_buffer)) {
+            CATCH_RUNTIME_ERROR("Could not get a temp filename");
+        }
+        if (fopen_s(&m_file, m_buffer, "w")) {
+            char buffer[100];
+            if (strerror_s(buffer, errno)) {
+                CATCH_RUNTIME_ERROR("Could not translate errno to a string");
+            }
+            CATCH_RUNTIME_ERROR("Could not open the temp file: '" << m_buffer << "' because: " << buffer);
+        }
+    }
+#else
+    TempFile::TempFile() {
+        m_file = std::tmpfile();
+        if (!m_file) {
+            CATCH_RUNTIME_ERROR("Could not create a temp file.");
+        }
+    }
+
+#endif
+
+    TempFile::~TempFile() {
+         // TBD: What to do about errors here?
+         std::fclose(m_file);
+         // We manually create the file on Windows only, on Linux
+         // it will be autodeleted
+#if defined(_MSC_VER)
+         std::remove(m_buffer);
+#endif
+    }
+
+    FILE* TempFile::getFile() {
+        return m_file;
+    }
+
+    std::string TempFile::getContents() {
+        std::stringstream sstr;
+        char buffer[100] = {};
+        std::rewind(m_file);
+        while (std::fgets(buffer, sizeof(buffer), m_file)) {
+            sstr << buffer;
+        }
+        return sstr.str();
+    }
+
+    OutputRedirect::OutputRedirect(std::string& stdout_dest, std::string& stderr_dest) :
+        m_originalStdout(dup(1)),
+        m_originalStderr(dup(2)),
+        m_stdoutDest(stdout_dest),
+        m_stderrDest(stderr_dest) {
+        dup2(fileno(m_stdoutFile.getFile()), 1);
+        dup2(fileno(m_stderrFile.getFile()), 2);
+    }
+
+    OutputRedirect::~OutputRedirect() {
+        Catch::cout() << std::flush;
+        fflush(stdout);
+        // Since we support overriding these streams, we flush cerr
+        // even though std::cerr is unbuffered
+        Catch::cerr() << std::flush;
+        Catch::clog() << std::flush;
+        fflush(stderr);
+
+        dup2(m_originalStdout, 1);
+        dup2(m_originalStderr, 2);
+
+        m_stdoutDest += m_stdoutFile.getContents();
+        m_stderrDest += m_stderrFile.getContents();
+    }
+
+#endif // CATCH_CONFIG_NEW_CAPTURE
+
+} // namespace Catch
+
+#if defined(CATCH_CONFIG_NEW_CAPTURE)
+    #if defined(_MSC_VER)
+    #undef dup
+    #undef dup2
+    #undef fileno
+    #endif
+#endif
+// end catch_output_redirect.cpp
+// start catch_polyfills.cpp
+
+#include <cmath>
+
+namespace Catch {
+
+#if !defined(CATCH_CONFIG_POLYFILL_ISNAN)
+    bool isnan(float f) {
+        return std::isnan(f);
+    }
+    bool isnan(double d) {
+        return std::isnan(d);
+    }
+#else
+    // For now we only use this for embarcadero
+    bool isnan(float f) {
+        return std::_isnan(f);
+    }
+    bool isnan(double d) {
+        return std::_isnan(d);
+    }
+#endif
+
+} // end namespace Catch
+// end catch_polyfills.cpp
+// start catch_random_number_generator.cpp
+
+namespace Catch {
+
+namespace {
+
+#if defined(_MSC_VER)
+#pragma warning(push)
+#pragma warning(disable:4146) // we negate uint32 during the rotate
+#endif
+        // Safe rotr implementation thanks to John Regehr
+        uint32_t rotate_right(uint32_t val, uint32_t count) {
+            const uint32_t mask = 31;
+            count &= mask;
+            return (val >> count) | (val << (-count & mask));
+        }
+
+#if defined(_MSC_VER)
+#pragma warning(pop)
+#endif
+
+}
+
+    SimplePcg32::SimplePcg32(result_type seed_) {
+        seed(seed_);
+    }
+
+    void SimplePcg32::seed(result_type seed_) {
+        m_state = 0;
+        (*this)();
+        m_state += seed_;
+        (*this)();
+    }
+
+    void SimplePcg32::discard(uint64_t skip) {
+        // We could implement this to run in O(log n) steps, but this
+        // should suffice for our use case.
+        for (uint64_t s = 0; s < skip; ++s) {
+            static_cast<void>((*this)());
+        }
+    }
+
+    SimplePcg32::result_type SimplePcg32::operator()() {
+        // prepare the output value
+        const uint32_t xorshifted = static_cast<uint32_t>(((m_state >> 18u) ^ m_state) >> 27u);
+        const auto output = rotate_right(xorshifted, m_state >> 59u);
+
+        // advance state
+        m_state = m_state * 6364136223846793005ULL + s_inc;
+
+        return output;
+    }
+
+    bool operator==(SimplePcg32 const& lhs, SimplePcg32 const& rhs) {
+        return lhs.m_state == rhs.m_state;
+    }
+
+    bool operator!=(SimplePcg32 const& lhs, SimplePcg32 const& rhs) {
+        return lhs.m_state != rhs.m_state;
+    }
+}
+// end catch_random_number_generator.cpp
+// start catch_registry_hub.cpp
+
+// start catch_test_case_registry_impl.h
+
+#include <vector>
+#include <set>
+#include <algorithm>
+#include <ios>
+
+namespace Catch {
+
+    class TestCase;
+    struct IConfig;
+
+    std::vector<TestCase> sortTests( IConfig const& config, std::vector<TestCase> const& unsortedTestCases );
+
+    bool isThrowSafe( TestCase const& testCase, IConfig const& config );
+    bool matchTest( TestCase const& testCase, TestSpec const& testSpec, IConfig const& config );
+
+    void enforceNoDuplicateTestCases( std::vector<TestCase> const& functions );
+
+    std::vector<TestCase> filterTests( std::vector<TestCase> const& testCases, TestSpec const& testSpec, IConfig const& config );
+    std::vector<TestCase> const& getAllTestCasesSorted( IConfig const& config );
+
+    class TestRegistry : public ITestCaseRegistry {
+    public:
+        virtual ~TestRegistry() = default;
+
+        virtual void registerTest( TestCase const& testCase );
+
+        std::vector<TestCase> const& getAllTests() const override;
+        std::vector<TestCase> const& getAllTestsSorted( IConfig const& config ) const override;
+
+    private:
+        std::vector<TestCase> m_functions;
+        mutable RunTests::InWhatOrder m_currentSortOrder = RunTests::InDeclarationOrder;
+        mutable std::vector<TestCase> m_sortedFunctions;
+        std::size_t m_unnamedCount = 0;
+        std::ios_base::Init m_ostreamInit; // Forces cout/ cerr to be initialised
+    };
+
+    ///////////////////////////////////////////////////////////////////////////
+
+    class TestInvokerAsFunction : public ITestInvoker {
+        void(*m_testAsFunction)();
+    public:
+        TestInvokerAsFunction( void(*testAsFunction)() ) noexcept;
+
+        void invoke() const override;
+    };
+
+    std::string extractClassName( StringRef const& classOrQualifiedMethodName );
+
+    ///////////////////////////////////////////////////////////////////////////
+
+} // end namespace Catch
+
+// end catch_test_case_registry_impl.h
+// start catch_reporter_registry.h
+
+#include <map>
+
+namespace Catch {
+
+    class ReporterRegistry : public IReporterRegistry {
+
+    public:
+
+        ~ReporterRegistry() override;
+
+        IStreamingReporterPtr create( std::string const& name, IConfigPtr const& config ) const override;
+
+        void registerReporter( std::string const& name, IReporterFactoryPtr const& factory );
+        void registerListener( IReporterFactoryPtr const& factory );
+
+        FactoryMap const& getFactories() const override;
+        Listeners const& getListeners() const override;
+
+    private:
+        FactoryMap m_factories;
+        Listeners m_listeners;
+    };
+}
+
+// end catch_reporter_registry.h
+// start catch_tag_alias_registry.h
+
+// start catch_tag_alias.h
+
+#include <string>
+
+namespace Catch {
+
+    struct TagAlias {
+        TagAlias(std::string const& _tag, SourceLineInfo _lineInfo);
+
+        std::string tag;
+        SourceLineInfo lineInfo;
+    };
+
+} // end namespace Catch
+
+// end catch_tag_alias.h
+#include <map>
+
+namespace Catch {
+
+    class TagAliasRegistry : public ITagAliasRegistry {
+    public:
+        ~TagAliasRegistry() override;
+        TagAlias const* find( std::string const& alias ) const override;
+        std::string expandAliases( std::string const& unexpandedTestSpec ) const override;
+        void add( std::string const& alias, std::string const& tag, SourceLineInfo const& lineInfo );
+
+    private:
+        std::map<std::string, TagAlias> m_registry;
+    };
+
+} // end namespace Catch
+
+// end catch_tag_alias_registry.h
+// start catch_startup_exception_registry.h
+
+#include <vector>
+#include <exception>
+
+namespace Catch {
+
+    class StartupExceptionRegistry {
+    public:
+        void add(std::exception_ptr const& exception) noexcept;
+        std::vector<std::exception_ptr> const& getExceptions() const noexcept;
+    private:
+        std::vector<std::exception_ptr> m_exceptions;
+    };
+
+} // end namespace Catch
+
+// end catch_startup_exception_registry.h
+// start catch_singletons.hpp
+
+namespace Catch {
+
+    struct ISingleton {
+        virtual ~ISingleton();
+    };
+
+    void addSingleton( ISingleton* singleton );
+    void cleanupSingletons();
+
+    template<typename SingletonImplT, typename InterfaceT = SingletonImplT, typename MutableInterfaceT = InterfaceT>
+    class Singleton : SingletonImplT, public ISingleton {
+
+        static auto getInternal() -> Singleton* {
+            static Singleton* s_instance = nullptr;
+            if( !s_instance ) {
+                s_instance = new Singleton;
+                addSingleton( s_instance );
+            }
+            return s_instance;
+        }
+
+    public:
+        static auto get() -> InterfaceT const& {
+            return *getInternal();
+        }
+        static auto getMutable() -> MutableInterfaceT& {
+            return *getInternal();
+        }
+    };
+
+} // namespace Catch
+
+// end catch_singletons.hpp
+namespace Catch {
+
+    namespace {
+
+        class RegistryHub : public IRegistryHub, public IMutableRegistryHub,
+                            private NonCopyable {
+
+        public: // IRegistryHub
+            RegistryHub() = default;
+            IReporterRegistry const& getReporterRegistry() const override {
+                return m_reporterRegistry;
+            }
+            ITestCaseRegistry const& getTestCaseRegistry() const override {
+                return m_testCaseRegistry;
+            }
+            IExceptionTranslatorRegistry const& getExceptionTranslatorRegistry() const override {
+                return m_exceptionTranslatorRegistry;
+            }
+            ITagAliasRegistry const& getTagAliasRegistry() const override {
+                return m_tagAliasRegistry;
+            }
+            StartupExceptionRegistry const& getStartupExceptionRegistry() const override {
+                return m_exceptionRegistry;
+            }
+
+        public: // IMutableRegistryHub
+            void registerReporter( std::string const& name, IReporterFactoryPtr const& factory ) override {
+                m_reporterRegistry.registerReporter( name, factory );
+            }
+            void registerListener( IReporterFactoryPtr const& factory ) override {
+                m_reporterRegistry.registerListener( factory );
+            }
+            void registerTest( TestCase const& testInfo ) override {
+                m_testCaseRegistry.registerTest( testInfo );
+            }
+            void registerTranslator( const IExceptionTranslator* translator ) override {
+                m_exceptionTranslatorRegistry.registerTranslator( translator );
+            }
+            void registerTagAlias( std::string const& alias, std::string const& tag, SourceLineInfo const& lineInfo ) override {
+                m_tagAliasRegistry.add( alias, tag, lineInfo );
+            }
+            void registerStartupException() noexcept override {
+                m_exceptionRegistry.add(std::current_exception());
+            }
+            IMutableEnumValuesRegistry& getMutableEnumValuesRegistry() override {
+                return m_enumValuesRegistry;
+            }
+
+        private:
+            TestRegistry m_testCaseRegistry;
+            ReporterRegistry m_reporterRegistry;
+            ExceptionTranslatorRegistry m_exceptionTranslatorRegistry;
+            TagAliasRegistry m_tagAliasRegistry;
+            StartupExceptionRegistry m_exceptionRegistry;
+            Detail::EnumValuesRegistry m_enumValuesRegistry;
+        };
+    }
+
+    using RegistryHubSingleton = Singleton<RegistryHub, IRegistryHub, IMutableRegistryHub>;
+
+    IRegistryHub const& getRegistryHub() {
+        return RegistryHubSingleton::get();
+    }
+    IMutableRegistryHub& getMutableRegistryHub() {
+        return RegistryHubSingleton::getMutable();
+    }
+    void cleanUp() {
+        cleanupSingletons();
+        cleanUpContext();
+    }
+    std::string translateActiveException() {
+        return getRegistryHub().getExceptionTranslatorRegistry().translateActiveException();
+    }
+
+} // end namespace Catch
+// end catch_registry_hub.cpp
+// start catch_reporter_registry.cpp
+
+namespace Catch {
+
+    ReporterRegistry::~ReporterRegistry() = default;
+
+    IStreamingReporterPtr ReporterRegistry::create( std::string const& name, IConfigPtr const& config ) const {
+        auto it =  m_factories.find( name );
+        if( it == m_factories.end() )
+            return nullptr;
+        return it->second->create( ReporterConfig( config ) );
+    }
+
+    void ReporterRegistry::registerReporter( std::string const& name, IReporterFactoryPtr const& factory ) {
+        m_factories.emplace(name, factory);
+    }
+    void ReporterRegistry::registerListener( IReporterFactoryPtr const& factory ) {
+        m_listeners.push_back( factory );
+    }
+
+    IReporterRegistry::FactoryMap const& ReporterRegistry::getFactories() const {
+        return m_factories;
+    }
+    IReporterRegistry::Listeners const& ReporterRegistry::getListeners() const {
+        return m_listeners;
+    }
+
+}
+// end catch_reporter_registry.cpp
+// start catch_result_type.cpp
+
+namespace Catch {
+
+    bool isOk( ResultWas::OfType resultType ) {
+        return ( resultType & ResultWas::FailureBit ) == 0;
+    }
+    bool isJustInfo( int flags ) {
+        return flags == ResultWas::Info;
+    }
+
+    ResultDisposition::Flags operator | ( ResultDisposition::Flags lhs, ResultDisposition::Flags rhs ) {
+        return static_cast<ResultDisposition::Flags>( static_cast<int>( lhs ) | static_cast<int>( rhs ) );
+    }
+
+    bool shouldContinueOnFailure( int flags )    { return ( flags & ResultDisposition::ContinueOnFailure ) != 0; }
+    bool shouldSuppressFailure( int flags )      { return ( flags & ResultDisposition::SuppressFail ) != 0; }
+
+} // end namespace Catch
+// end catch_result_type.cpp
+// start catch_run_context.cpp
+
+#include <cassert>
+#include <algorithm>
+#include <sstream>
+
+namespace Catch {
+
+    namespace Generators {
+        struct GeneratorTracker : TestCaseTracking::TrackerBase, IGeneratorTracker {
+            GeneratorBasePtr m_generator;
+
+            GeneratorTracker( TestCaseTracking::NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent )
+            :   TrackerBase( nameAndLocation, ctx, parent )
+            {}
+            ~GeneratorTracker();
+
+            static GeneratorTracker& acquire( TrackerContext& ctx, TestCaseTracking::NameAndLocation const& nameAndLocation ) {
+                std::shared_ptr<GeneratorTracker> tracker;
+
+                ITracker& currentTracker = ctx.currentTracker();
+                if( TestCaseTracking::ITrackerPtr childTracker = currentTracker.findChild( nameAndLocation ) ) {
+                    assert( childTracker );
+                    assert( childTracker->isGeneratorTracker() );
+                    tracker = std::static_pointer_cast<GeneratorTracker>( childTracker );
+                }
+                else {
+                    tracker = std::make_shared<GeneratorTracker>( nameAndLocation, ctx, &currentTracker );
+                    currentTracker.addChild( tracker );
+                }
+
+                if( !ctx.completedCycle() && !tracker->isComplete() ) {
+                    tracker->open();
+                }
+
+                return *tracker;
+            }
+
+            // TrackerBase interface
+            bool isGeneratorTracker() const override { return true; }
+            auto hasGenerator() const -> bool override {
+                return !!m_generator;
+            }
+            void close() override {
+                TrackerBase::close();
+                // Generator interface only finds out if it has another item on atual move
+                if (m_runState == CompletedSuccessfully && m_generator->next()) {
+                    m_children.clear();
+                    m_runState = Executing;
+                }
+            }
+
+            // IGeneratorTracker interface
+            auto getGenerator() const -> GeneratorBasePtr const& override {
+                return m_generator;
+            }
+            void setGenerator( GeneratorBasePtr&& generator ) override {
+                m_generator = std::move( generator );
+            }
+        };
+        GeneratorTracker::~GeneratorTracker() {}
+    }
+
+    RunContext::RunContext(IConfigPtr const& _config, IStreamingReporterPtr&& reporter)
+    :   m_runInfo(_config->name()),
+        m_context(getCurrentMutableContext()),
+        m_config(_config),
+        m_reporter(std::move(reporter)),
+        m_lastAssertionInfo{ StringRef(), SourceLineInfo("",0), StringRef(), ResultDisposition::Normal },
+        m_includeSuccessfulResults( m_config->includeSuccessfulResults() || m_reporter->getPreferences().shouldReportAllAssertions )
+    {
+        m_context.setRunner(this);
+        m_context.setConfig(m_config);
+        m_context.setResultCapture(this);
+        m_reporter->testRunStarting(m_runInfo);
+    }
+
+    RunContext::~RunContext() {
+        m_reporter->testRunEnded(TestRunStats(m_runInfo, m_totals, aborting()));
+    }
+
+    void RunContext::testGroupStarting(std::string const& testSpec, std::size_t groupIndex, std::size_t groupsCount) {
+        m_reporter->testGroupStarting(GroupInfo(testSpec, groupIndex, groupsCount));
+    }
+
+    void RunContext::testGroupEnded(std::string const& testSpec, Totals const& totals, std::size_t groupIndex, std::size_t groupsCount) {
+        m_reporter->testGroupEnded(TestGroupStats(GroupInfo(testSpec, groupIndex, groupsCount), totals, aborting()));
+    }
+
+    Totals RunContext::runTest(TestCase const& testCase) {
+        Totals prevTotals = m_totals;
+
+        std::string redirectedCout;
+        std::string redirectedCerr;
+
+        auto const& testInfo = testCase.getTestCaseInfo();
+
+        m_reporter->testCaseStarting(testInfo);
+
+        m_activeTestCase = &testCase;
+
+        ITracker& rootTracker = m_trackerContext.startRun();
+        assert(rootTracker.isSectionTracker());
+        static_cast<SectionTracker&>(rootTracker).addInitialFilters(m_config->getSectionsToRun());
+        do {
+            m_trackerContext.startCycle();
+            m_testCaseTracker = &SectionTracker::acquire(m_trackerContext, TestCaseTracking::NameAndLocation(testInfo.name, testInfo.lineInfo));
+            runCurrentTest(redirectedCout, redirectedCerr);
+        } while (!m_testCaseTracker->isSuccessfullyCompleted() && !aborting());
+
+        Totals deltaTotals = m_totals.delta(prevTotals);
+        if (testInfo.expectedToFail() && deltaTotals.testCases.passed > 0) {
+            deltaTotals.assertions.failed++;
+            deltaTotals.testCases.passed--;
+            deltaTotals.testCases.failed++;
+        }
+        m_totals.testCases += deltaTotals.testCases;
+        m_reporter->testCaseEnded(TestCaseStats(testInfo,
+                                  deltaTotals,
+                                  redirectedCout,
+                                  redirectedCerr,
+                                  aborting()));
+
+        m_activeTestCase = nullptr;
+        m_testCaseTracker = nullptr;
+
+        return deltaTotals;
+    }
+
+    IConfigPtr RunContext::config() const {
+        return m_config;
+    }
+
+    IStreamingReporter& RunContext::reporter() const {
+        return *m_reporter;
+    }
+
+    void RunContext::assertionEnded(AssertionResult const & result) {
+        if (result.getResultType() == ResultWas::Ok) {
+            m_totals.assertions.passed++;
+            m_lastAssertionPassed = true;
+        } else if (!result.isOk()) {
+            m_lastAssertionPassed = false;
+            if( m_activeTestCase->getTestCaseInfo().okToFail() )
+                m_totals.assertions.failedButOk++;
+            else
+                m_totals.assertions.failed++;
+        }
+        else {
+            m_lastAssertionPassed = true;
+        }
+
+        // We have no use for the return value (whether messages should be cleared), because messages were made scoped
+        // and should be let to clear themselves out.
+        static_cast<void>(m_reporter->assertionEnded(AssertionStats(result, m_messages, m_totals)));
+
+        if (result.getResultType() != ResultWas::Warning)
+            m_messageScopes.clear();
+
+        // Reset working state
+        resetAssertionInfo();
+        m_lastResult = result;
+    }
+    void RunContext::resetAssertionInfo() {
+        m_lastAssertionInfo.macroName = StringRef();
+        m_lastAssertionInfo.capturedExpression = "{Unknown expression after the reported line}"_sr;
+    }
+
+    bool RunContext::sectionStarted(SectionInfo const & sectionInfo, Counts & assertions) {
+        ITracker& sectionTracker = SectionTracker::acquire(m_trackerContext, TestCaseTracking::NameAndLocation(sectionInfo.name, sectionInfo.lineInfo));
+        if (!sectionTracker.isOpen())
+            return false;
+        m_activeSections.push_back(&sectionTracker);
+
+        m_lastAssertionInfo.lineInfo = sectionInfo.lineInfo;
+
+        m_reporter->sectionStarting(sectionInfo);
+
+        assertions = m_totals.assertions;
+
+        return true;
+    }
+    auto RunContext::acquireGeneratorTracker( SourceLineInfo const& lineInfo ) -> IGeneratorTracker& {
+        using namespace Generators;
+        GeneratorTracker& tracker = GeneratorTracker::acquire( m_trackerContext, TestCaseTracking::NameAndLocation( "generator", lineInfo ) );
+        assert( tracker.isOpen() );
+        m_lastAssertionInfo.lineInfo = lineInfo;
+        return tracker;
+    }
+
+    bool RunContext::testForMissingAssertions(Counts& assertions) {
+        if (assertions.total() != 0)
+            return false;
+        if (!m_config->warnAboutMissingAssertions())
+            return false;
+        if (m_trackerContext.currentTracker().hasChildren())
+            return false;
+        m_totals.assertions.failed++;
+        assertions.failed++;
+        return true;
+    }
+
+    void RunContext::sectionEnded(SectionEndInfo const & endInfo) {
+        Counts assertions = m_totals.assertions - endInfo.prevAssertions;
+        bool missingAssertions = testForMissingAssertions(assertions);
+
+        if (!m_activeSections.empty()) {
+            m_activeSections.back()->close();
+            m_activeSections.pop_back();
+        }
+
+        m_reporter->sectionEnded(SectionStats(endInfo.sectionInfo, assertions, endInfo.durationInSeconds, missingAssertions));
+        m_messages.clear();
+        m_messageScopes.clear();
+    }
+
+    void RunContext::sectionEndedEarly(SectionEndInfo const & endInfo) {
+        if (m_unfinishedSections.empty())
+            m_activeSections.back()->fail();
+        else
+            m_activeSections.back()->close();
+        m_activeSections.pop_back();
+
+        m_unfinishedSections.push_back(endInfo);
+    }
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    void RunContext::benchmarkPreparing(std::string const& name) {
+		m_reporter->benchmarkPreparing(name);
+	}
+    void RunContext::benchmarkStarting( BenchmarkInfo const& info ) {
+        m_reporter->benchmarkStarting( info );
+    }
+    void RunContext::benchmarkEnded( BenchmarkStats<> const& stats ) {
+        m_reporter->benchmarkEnded( stats );
+    }
+	void RunContext::benchmarkFailed(std::string const & error) {
+		m_reporter->benchmarkFailed(error);
+	}
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    void RunContext::pushScopedMessage(MessageInfo const & message) {
+        m_messages.push_back(message);
+    }
+
+    void RunContext::popScopedMessage(MessageInfo const & message) {
+        m_messages.erase(std::remove(m_messages.begin(), m_messages.end(), message), m_messages.end());
+    }
+
+    void RunContext::emplaceUnscopedMessage( MessageBuilder const& builder ) {
+        m_messageScopes.emplace_back( builder );
+    }
+
+    std::string RunContext::getCurrentTestName() const {
+        return m_activeTestCase
+            ? m_activeTestCase->getTestCaseInfo().name
+            : std::string();
+    }
+
+    const AssertionResult * RunContext::getLastResult() const {
+        return &(*m_lastResult);
+    }
+
+    void RunContext::exceptionEarlyReported() {
+        m_shouldReportUnexpected = false;
+    }
+
+    void RunContext::handleFatalErrorCondition( StringRef message ) {
+        // First notify reporter that bad things happened
+        m_reporter->fatalErrorEncountered(message);
+
+        // Don't rebuild the result -- the stringification itself can cause more fatal errors
+        // Instead, fake a result data.
+        AssertionResultData tempResult( ResultWas::FatalErrorCondition, { false } );
+        tempResult.message = static_cast<std::string>(message);
+        AssertionResult result(m_lastAssertionInfo, tempResult);
+
+        assertionEnded(result);
+
+        handleUnfinishedSections();
+
+        // Recreate section for test case (as we will lose the one that was in scope)
+        auto const& testCaseInfo = m_activeTestCase->getTestCaseInfo();
+        SectionInfo testCaseSection(testCaseInfo.lineInfo, testCaseInfo.name);
+
+        Counts assertions;
+        assertions.failed = 1;
+        SectionStats testCaseSectionStats(testCaseSection, assertions, 0, false);
+        m_reporter->sectionEnded(testCaseSectionStats);
+
+        auto const& testInfo = m_activeTestCase->getTestCaseInfo();
+
+        Totals deltaTotals;
+        deltaTotals.testCases.failed = 1;
+        deltaTotals.assertions.failed = 1;
+        m_reporter->testCaseEnded(TestCaseStats(testInfo,
+                                  deltaTotals,
+                                  std::string(),
+                                  std::string(),
+                                  false));
+        m_totals.testCases.failed++;
+        testGroupEnded(std::string(), m_totals, 1, 1);
+        m_reporter->testRunEnded(TestRunStats(m_runInfo, m_totals, false));
+    }
+
+    bool RunContext::lastAssertionPassed() {
+         return m_lastAssertionPassed;
+    }
+
+    void RunContext::assertionPassed() {
+        m_lastAssertionPassed = true;
+        ++m_totals.assertions.passed;
+        resetAssertionInfo();
+        m_messageScopes.clear();
+    }
+
+    bool RunContext::aborting() const {
+        return m_totals.assertions.failed >= static_cast<std::size_t>(m_config->abortAfter());
+    }
+
+    void RunContext::runCurrentTest(std::string & redirectedCout, std::string & redirectedCerr) {
+        auto const& testCaseInfo = m_activeTestCase->getTestCaseInfo();
+        SectionInfo testCaseSection(testCaseInfo.lineInfo, testCaseInfo.name);
+        m_reporter->sectionStarting(testCaseSection);
+        Counts prevAssertions = m_totals.assertions;
+        double duration = 0;
+        m_shouldReportUnexpected = true;
+        m_lastAssertionInfo = { "TEST_CASE"_sr, testCaseInfo.lineInfo, StringRef(), ResultDisposition::Normal };
+
+        seedRng(*m_config);
+
+        Timer timer;
+        CATCH_TRY {
+            if (m_reporter->getPreferences().shouldRedirectStdOut) {
+#if !defined(CATCH_CONFIG_EXPERIMENTAL_REDIRECT)
+                RedirectedStreams redirectedStreams(redirectedCout, redirectedCerr);
+
+                timer.start();
+                invokeActiveTestCase();
+#else
+                OutputRedirect r(redirectedCout, redirectedCerr);
+                timer.start();
+                invokeActiveTestCase();
+#endif
+            } else {
+                timer.start();
+                invokeActiveTestCase();
+            }
+            duration = timer.getElapsedSeconds();
+        } CATCH_CATCH_ANON (TestFailureException&) {
+            // This just means the test was aborted due to failure
+        } CATCH_CATCH_ALL {
+            // Under CATCH_CONFIG_FAST_COMPILE, unexpected exceptions under REQUIRE assertions
+            // are reported without translation at the point of origin.
+            if( m_shouldReportUnexpected ) {
+                AssertionReaction dummyReaction;
+                handleUnexpectedInflightException( m_lastAssertionInfo, translateActiveException(), dummyReaction );
+            }
+        }
+        Counts assertions = m_totals.assertions - prevAssertions;
+        bool missingAssertions = testForMissingAssertions(assertions);
+
+        m_testCaseTracker->close();
+        handleUnfinishedSections();
+        m_messages.clear();
+        m_messageScopes.clear();
+
+        SectionStats testCaseSectionStats(testCaseSection, assertions, duration, missingAssertions);
+        m_reporter->sectionEnded(testCaseSectionStats);
+    }
+
+    void RunContext::invokeActiveTestCase() {
+        FatalConditionHandler fatalConditionHandler; // Handle signals
+        m_activeTestCase->invoke();
+        fatalConditionHandler.reset();
+    }
+
+    void RunContext::handleUnfinishedSections() {
+        // If sections ended prematurely due to an exception we stored their
+        // infos here so we can tear them down outside the unwind process.
+        for (auto it = m_unfinishedSections.rbegin(),
+             itEnd = m_unfinishedSections.rend();
+             it != itEnd;
+             ++it)
+            sectionEnded(*it);
+        m_unfinishedSections.clear();
+    }
+
+    void RunContext::handleExpr(
+        AssertionInfo const& info,
+        ITransientExpression const& expr,
+        AssertionReaction& reaction
+    ) {
+        m_reporter->assertionStarting( info );
+
+        bool negated = isFalseTest( info.resultDisposition );
+        bool result = expr.getResult() != negated;
+
+        if( result ) {
+            if (!m_includeSuccessfulResults) {
+                assertionPassed();
+            }
+            else {
+                reportExpr(info, ResultWas::Ok, &expr, negated);
+            }
+        }
+        else {
+            reportExpr(info, ResultWas::ExpressionFailed, &expr, negated );
+            populateReaction( reaction );
+        }
+    }
+    void RunContext::reportExpr(
+            AssertionInfo const &info,
+            ResultWas::OfType resultType,
+            ITransientExpression const *expr,
+            bool negated ) {
+
+        m_lastAssertionInfo = info;
+        AssertionResultData data( resultType, LazyExpression( negated ) );
+
+        AssertionResult assertionResult{ info, data };
+        assertionResult.m_resultData.lazyExpression.m_transientExpression = expr;
+
+        assertionEnded( assertionResult );
+    }
+
+    void RunContext::handleMessage(
+            AssertionInfo const& info,
+            ResultWas::OfType resultType,
+            StringRef const& message,
+            AssertionReaction& reaction
+    ) {
+        m_reporter->assertionStarting( info );
+
+        m_lastAssertionInfo = info;
+
+        AssertionResultData data( resultType, LazyExpression( false ) );
+        data.message = static_cast<std::string>(message);
+        AssertionResult assertionResult{ m_lastAssertionInfo, data };
+        assertionEnded( assertionResult );
+        if( !assertionResult.isOk() )
+            populateReaction( reaction );
+    }
+    void RunContext::handleUnexpectedExceptionNotThrown(
+            AssertionInfo const& info,
+            AssertionReaction& reaction
+    ) {
+        handleNonExpr(info, Catch::ResultWas::DidntThrowException, reaction);
+    }
+
+    void RunContext::handleUnexpectedInflightException(
+            AssertionInfo const& info,
+            std::string const& message,
+            AssertionReaction& reaction
+    ) {
+        m_lastAssertionInfo = info;
+
+        AssertionResultData data( ResultWas::ThrewException, LazyExpression( false ) );
+        data.message = message;
+        AssertionResult assertionResult{ info, data };
+        assertionEnded( assertionResult );
+        populateReaction( reaction );
+    }
+
+    void RunContext::populateReaction( AssertionReaction& reaction ) {
+        reaction.shouldDebugBreak = m_config->shouldDebugBreak();
+        reaction.shouldThrow = aborting() || (m_lastAssertionInfo.resultDisposition & ResultDisposition::Normal);
+    }
+
+    void RunContext::handleIncomplete(
+            AssertionInfo const& info
+    ) {
+        m_lastAssertionInfo = info;
+
+        AssertionResultData data( ResultWas::ThrewException, LazyExpression( false ) );
+        data.message = "Exception translation was disabled by CATCH_CONFIG_FAST_COMPILE";
+        AssertionResult assertionResult{ info, data };
+        assertionEnded( assertionResult );
+    }
+    void RunContext::handleNonExpr(
+            AssertionInfo const &info,
+            ResultWas::OfType resultType,
+            AssertionReaction &reaction
+    ) {
+        m_lastAssertionInfo = info;
+
+        AssertionResultData data( resultType, LazyExpression( false ) );
+        AssertionResult assertionResult{ info, data };
+        assertionEnded( assertionResult );
+
+        if( !assertionResult.isOk() )
+            populateReaction( reaction );
+    }
+
+    IResultCapture& getResultCapture() {
+        if (auto* capture = getCurrentContext().getResultCapture())
+            return *capture;
+        else
+            CATCH_INTERNAL_ERROR("No result capture instance");
+    }
+
+    void seedRng(IConfig const& config) {
+        if (config.rngSeed() != 0) {
+            std::srand(config.rngSeed());
+            rng().seed(config.rngSeed());
+        }
+    }
+
+    unsigned int rngSeed() {
+        return getCurrentContext().getConfig()->rngSeed();
+    }
+
+}
+// end catch_run_context.cpp
+// start catch_section.cpp
+
+namespace Catch {
+
+    Section::Section( SectionInfo const& info )
+    :   m_info( info ),
+        m_sectionIncluded( getResultCapture().sectionStarted( m_info, m_assertions ) )
+    {
+        m_timer.start();
+    }
+
+    Section::~Section() {
+        if( m_sectionIncluded ) {
+            SectionEndInfo endInfo{ m_info, m_assertions, m_timer.getElapsedSeconds() };
+            if( uncaught_exceptions() )
+                getResultCapture().sectionEndedEarly( endInfo );
+            else
+                getResultCapture().sectionEnded( endInfo );
+        }
+    }
+
+    // This indicates whether the section should be executed or not
+    Section::operator bool() const {
+        return m_sectionIncluded;
+    }
+
+} // end namespace Catch
+// end catch_section.cpp
+// start catch_section_info.cpp
+
+namespace Catch {
+
+    SectionInfo::SectionInfo
+        (   SourceLineInfo const& _lineInfo,
+            std::string const& _name )
+    :   name( _name ),
+        lineInfo( _lineInfo )
+    {}
+
+} // end namespace Catch
+// end catch_section_info.cpp
+// start catch_session.cpp
+
+// start catch_session.h
+
+#include <memory>
+
+namespace Catch {
+
+    class Session : NonCopyable {
+    public:
+
+        Session();
+        ~Session() override;
+
+        void showHelp() const;
+        void libIdentify();
+
+        int applyCommandLine( int argc, char const * const * argv );
+    #if defined(CATCH_CONFIG_WCHAR) && defined(_WIN32) && defined(UNICODE)
+        int applyCommandLine( int argc, wchar_t const * const * argv );
+    #endif
+
+        void useConfigData( ConfigData const& configData );
+
+        template<typename CharT>
+        int run(int argc, CharT const * const argv[]) {
+            if (m_startupExceptions)
+                return 1;
+            int returnCode = applyCommandLine(argc, argv);
+            if (returnCode == 0)
+                returnCode = run();
+            return returnCode;
+        }
+
+        int run();
+
+        clara::Parser const& cli() const;
+        void cli( clara::Parser const& newParser );
+        ConfigData& configData();
+        Config& config();
+    private:
+        int runInternal();
+
+        clara::Parser m_cli;
+        ConfigData m_configData;
+        std::shared_ptr<Config> m_config;
+        bool m_startupExceptions = false;
+    };
+
+} // end namespace Catch
+
+// end catch_session.h
+// start catch_version.h
+
+#include <iosfwd>
+
+namespace Catch {
+
+    // Versioning information
+    struct Version {
+        Version( Version const& ) = delete;
+        Version& operator=( Version const& ) = delete;
+        Version(    unsigned int _majorVersion,
+                    unsigned int _minorVersion,
+                    unsigned int _patchNumber,
+                    char const * const _branchName,
+                    unsigned int _buildNumber );
+
+        unsigned int const majorVersion;
+        unsigned int const minorVersion;
+        unsigned int const patchNumber;
+
+        // buildNumber is only used if branchName is not null
+        char const * const branchName;
+        unsigned int const buildNumber;
+
+        friend std::ostream& operator << ( std::ostream& os, Version const& version );
+    };
+
+    Version const& libraryVersion();
+}
+
+// end catch_version.h
+#include <cstdlib>
+#include <iomanip>
+#include <set>
+#include <iterator>
+
+namespace Catch {
+
+    namespace {
+        const int MaxExitCode = 255;
+
+        IStreamingReporterPtr createReporter(std::string const& reporterName, IConfigPtr const& config) {
+            auto reporter = Catch::getRegistryHub().getReporterRegistry().create(reporterName, config);
+            CATCH_ENFORCE(reporter, "No reporter registered with name: '" << reporterName << "'");
+
+            return reporter;
+        }
+
+        IStreamingReporterPtr makeReporter(std::shared_ptr<Config> const& config) {
+            if (Catch::getRegistryHub().getReporterRegistry().getListeners().empty()) {
+                return createReporter(config->getReporterName(), config);
+            }
+
+            // On older platforms, returning std::unique_ptr<ListeningReporter>
+            // when the return type is std::unique_ptr<IStreamingReporter>
+            // doesn't compile without a std::move call. However, this causes
+            // a warning on newer platforms. Thus, we have to work around
+            // it a bit and downcast the pointer manually.
+            auto ret = std::unique_ptr<IStreamingReporter>(new ListeningReporter);
+            auto& multi = static_cast<ListeningReporter&>(*ret);
+            auto const& listeners = Catch::getRegistryHub().getReporterRegistry().getListeners();
+            for (auto const& listener : listeners) {
+                multi.addListener(listener->create(Catch::ReporterConfig(config)));
+            }
+            multi.addReporter(createReporter(config->getReporterName(), config));
+            return ret;
+        }
+
+        class TestGroup {
+        public:
+            explicit TestGroup(std::shared_ptr<Config> const& config)
+            : m_config{config}
+            , m_context{config, makeReporter(config)}
+            {
+                auto const& allTestCases = getAllTestCasesSorted(*m_config);
+                m_matches = m_config->testSpec().matchesByFilter(allTestCases, *m_config);
+                auto const& invalidArgs = m_config->testSpec().getInvalidArgs();
+
+                if (m_matches.empty() && invalidArgs.empty()) {
+                    for (auto const& test : allTestCases)
+                        if (!test.isHidden())
+                            m_tests.emplace(&test);
+                } else {
+                    for (auto const& match : m_matches)
+                        m_tests.insert(match.tests.begin(), match.tests.end());
+                }
+            }
+
+            Totals execute() {
+                auto const& invalidArgs = m_config->testSpec().getInvalidArgs();
+                Totals totals;
+                m_context.testGroupStarting(m_config->name(), 1, 1);
+                for (auto const& testCase : m_tests) {
+                    if (!m_context.aborting())
+                        totals += m_context.runTest(*testCase);
+                    else
+                        m_context.reporter().skipTest(*testCase);
+                }
+
+                for (auto const& match : m_matches) {
+                    if (match.tests.empty()) {
+                        m_context.reporter().noMatchingTestCases(match.name);
+                        totals.error = -1;
+                    }
+                }
+
+                if (!invalidArgs.empty()) {
+                    for (auto const& invalidArg: invalidArgs)
+                         m_context.reporter().reportInvalidArguments(invalidArg);
+                }
+
+                m_context.testGroupEnded(m_config->name(), totals, 1, 1);
+                return totals;
+            }
+
+        private:
+            using Tests = std::set<TestCase const*>;
+
+            std::shared_ptr<Config> m_config;
+            RunContext m_context;
+            Tests m_tests;
+            TestSpec::Matches m_matches;
+        };
+
+        void applyFilenamesAsTags(Catch::IConfig const& config) {
+            auto& tests = const_cast<std::vector<TestCase>&>(getAllTestCasesSorted(config));
+            for (auto& testCase : tests) {
+                auto tags = testCase.tags;
+
+                std::string filename = testCase.lineInfo.file;
+                auto lastSlash = filename.find_last_of("\\/");
+                if (lastSlash != std::string::npos) {
+                    filename.erase(0, lastSlash);
+                    filename[0] = '#';
+                }
+
+                auto lastDot = filename.find_last_of('.');
+                if (lastDot != std::string::npos) {
+                    filename.erase(lastDot);
+                }
+
+                tags.push_back(std::move(filename));
+                setTags(testCase, tags);
+            }
+        }
+
+    } // anon namespace
+
+    Session::Session() {
+        static bool alreadyInstantiated = false;
+        if( alreadyInstantiated ) {
+            CATCH_TRY { CATCH_INTERNAL_ERROR( "Only one instance of Catch::Session can ever be used" ); }
+            CATCH_CATCH_ALL { getMutableRegistryHub().registerStartupException(); }
+        }
+
+        // There cannot be exceptions at startup in no-exception mode.
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+        const auto& exceptions = getRegistryHub().getStartupExceptionRegistry().getExceptions();
+        if ( !exceptions.empty() ) {
+            config();
+            getCurrentMutableContext().setConfig(m_config);
+
+            m_startupExceptions = true;
+            Colour colourGuard( Colour::Red );
+            Catch::cerr() << "Errors occurred during startup!" << '\n';
+            // iterate over all exceptions and notify user
+            for ( const auto& ex_ptr : exceptions ) {
+                try {
+                    std::rethrow_exception(ex_ptr);
+                } catch ( std::exception const& ex ) {
+                    Catch::cerr() << Column( ex.what() ).indent(2) << '\n';
+                }
+            }
+        }
+#endif
+
+        alreadyInstantiated = true;
+        m_cli = makeCommandLineParser( m_configData );
+    }
+    Session::~Session() {
+        Catch::cleanUp();
+    }
+
+    void Session::showHelp() const {
+        Catch::cout()
+                << "\nCatch v" << libraryVersion() << "\n"
+                << m_cli << std::endl
+                << "For more detailed usage please see the project docs\n" << std::endl;
+    }
+    void Session::libIdentify() {
+        Catch::cout()
+                << std::left << std::setw(16) << "description: " << "A Catch2 test executable\n"
+                << std::left << std::setw(16) << "category: " << "testframework\n"
+                << std::left << std::setw(16) << "framework: " << "Catch Test\n"
+                << std::left << std::setw(16) << "version: " << libraryVersion() << std::endl;
+    }
+
+    int Session::applyCommandLine( int argc, char const * const * argv ) {
+        if( m_startupExceptions )
+            return 1;
+
+        auto result = m_cli.parse( clara::Args( argc, argv ) );
+        if( !result ) {
+            config();
+            getCurrentMutableContext().setConfig(m_config);
+            Catch::cerr()
+                << Colour( Colour::Red )
+                << "\nError(s) in input:\n"
+                << Column( result.errorMessage() ).indent( 2 )
+                << "\n\n";
+            Catch::cerr() << "Run with -? for usage\n" << std::endl;
+            return MaxExitCode;
+        }
+
+        if( m_configData.showHelp )
+            showHelp();
+        if( m_configData.libIdentify )
+            libIdentify();
+        m_config.reset();
+        return 0;
+    }
+
+#if defined(CATCH_CONFIG_WCHAR) && defined(_WIN32) && defined(UNICODE)
+    int Session::applyCommandLine( int argc, wchar_t const * const * argv ) {
+
+        char **utf8Argv = new char *[ argc ];
+
+        for ( int i = 0; i < argc; ++i ) {
+            int bufSize = WideCharToMultiByte( CP_UTF8, 0, argv[i], -1, nullptr, 0, nullptr, nullptr );
+
+            utf8Argv[ i ] = new char[ bufSize ];
+
+            WideCharToMultiByte( CP_UTF8, 0, argv[i], -1, utf8Argv[i], bufSize, nullptr, nullptr );
+        }
+
+        int returnCode = applyCommandLine( argc, utf8Argv );
+
+        for ( int i = 0; i < argc; ++i )
+            delete [] utf8Argv[ i ];
+
+        delete [] utf8Argv;
+
+        return returnCode;
+    }
+#endif
+
+    void Session::useConfigData( ConfigData const& configData ) {
+        m_configData = configData;
+        m_config.reset();
+    }
+
+    int Session::run() {
+        if( ( m_configData.waitForKeypress & WaitForKeypress::BeforeStart ) != 0 ) {
+            Catch::cout() << "...waiting for enter/ return before starting" << std::endl;
+            static_cast<void>(std::getchar());
+        }
+        int exitCode = runInternal();
+        if( ( m_configData.waitForKeypress & WaitForKeypress::BeforeExit ) != 0 ) {
+            Catch::cout() << "...waiting for enter/ return before exiting, with code: " << exitCode << std::endl;
+            static_cast<void>(std::getchar());
+        }
+        return exitCode;
+    }
+
+    clara::Parser const& Session::cli() const {
+        return m_cli;
+    }
+    void Session::cli( clara::Parser const& newParser ) {
+        m_cli = newParser;
+    }
+    ConfigData& Session::configData() {
+        return m_configData;
+    }
+    Config& Session::config() {
+        if( !m_config )
+            m_config = std::make_shared<Config>( m_configData );
+        return *m_config;
+    }
+
+    int Session::runInternal() {
+        if( m_startupExceptions )
+            return 1;
+
+        if (m_configData.showHelp || m_configData.libIdentify) {
+            return 0;
+        }
+
+        CATCH_TRY {
+            config(); // Force config to be constructed
+
+            seedRng( *m_config );
+
+            if( m_configData.filenamesAsTags )
+                applyFilenamesAsTags( *m_config );
+
+            // Handle list request
+            if( Option<std::size_t> listed = list( m_config ) )
+                return static_cast<int>( *listed );
+
+            TestGroup tests { m_config };
+            auto const totals = tests.execute();
+
+            if( m_config->warnAboutNoTests() && totals.error == -1 )
+                return 2;
+
+            // Note that on unices only the lower 8 bits are usually used, clamping
+            // the return value to 255 prevents false negative when some multiple
+            // of 256 tests has failed
+            return (std::min) (MaxExitCode, (std::max) (totals.error, static_cast<int>(totals.assertions.failed)));
+        }
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+        catch( std::exception& ex ) {
+            Catch::cerr() << ex.what() << std::endl;
+            return MaxExitCode;
+        }
+#endif
+    }
+
+} // end namespace Catch
+// end catch_session.cpp
+// start catch_singletons.cpp
+
+#include <vector>
+
+namespace Catch {
+
+    namespace {
+        static auto getSingletons() -> std::vector<ISingleton*>*& {
+            static std::vector<ISingleton*>* g_singletons = nullptr;
+            if( !g_singletons )
+                g_singletons = new std::vector<ISingleton*>();
+            return g_singletons;
+        }
+    }
+
+    ISingleton::~ISingleton() {}
+
+    void addSingleton(ISingleton* singleton ) {
+        getSingletons()->push_back( singleton );
+    }
+    void cleanupSingletons() {
+        auto& singletons = getSingletons();
+        for( auto singleton : *singletons )
+            delete singleton;
+        delete singletons;
+        singletons = nullptr;
+    }
+
+} // namespace Catch
+// end catch_singletons.cpp
+// start catch_startup_exception_registry.cpp
+
+namespace Catch {
+void StartupExceptionRegistry::add( std::exception_ptr const& exception ) noexcept {
+        CATCH_TRY {
+            m_exceptions.push_back(exception);
+        } CATCH_CATCH_ALL {
+            // If we run out of memory during start-up there's really not a lot more we can do about it
+            std::terminate();
+        }
+    }
+
+    std::vector<std::exception_ptr> const& StartupExceptionRegistry::getExceptions() const noexcept {
+        return m_exceptions;
+    }
+
+} // end namespace Catch
+// end catch_startup_exception_registry.cpp
+// start catch_stream.cpp
+
+#include <cstdio>
+#include <iostream>
+#include <fstream>
+#include <sstream>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    Catch::IStream::~IStream() = default;
+
+    namespace Detail { namespace {
+        template<typename WriterF, std::size_t bufferSize=256>
+        class StreamBufImpl : public std::streambuf {
+            char data[bufferSize];
+            WriterF m_writer;
+
+        public:
+            StreamBufImpl() {
+                setp( data, data + sizeof(data) );
+            }
+
+            ~StreamBufImpl() noexcept {
+                StreamBufImpl::sync();
+            }
+
+        private:
+            int overflow( int c ) override {
+                sync();
+
+                if( c != EOF ) {
+                    if( pbase() == epptr() )
+                        m_writer( std::string( 1, static_cast<char>( c ) ) );
+                    else
+                        sputc( static_cast<char>( c ) );
+                }
+                return 0;
+            }
+
+            int sync() override {
+                if( pbase() != pptr() ) {
+                    m_writer( std::string( pbase(), static_cast<std::string::size_type>( pptr() - pbase() ) ) );
+                    setp( pbase(), epptr() );
+                }
+                return 0;
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+
+        struct OutputDebugWriter {
+
+            void operator()( std::string const&str ) {
+                writeToDebugConsole( str );
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+
+        class FileStream : public IStream {
+            mutable std::ofstream m_ofs;
+        public:
+            FileStream( StringRef filename ) {
+                m_ofs.open( filename.c_str() );
+                CATCH_ENFORCE( !m_ofs.fail(), "Unable to open file: '" << filename << "'" );
+            }
+            ~FileStream() override = default;
+        public: // IStream
+            std::ostream& stream() const override {
+                return m_ofs;
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+
+        class CoutStream : public IStream {
+            mutable std::ostream m_os;
+        public:
+            // Store the streambuf from cout up-front because
+            // cout may get redirected when running tests
+            CoutStream() : m_os( Catch::cout().rdbuf() ) {}
+            ~CoutStream() override = default;
+
+        public: // IStream
+            std::ostream& stream() const override { return m_os; }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+
+        class DebugOutStream : public IStream {
+            std::unique_ptr<StreamBufImpl<OutputDebugWriter>> m_streamBuf;
+            mutable std::ostream m_os;
+        public:
+            DebugOutStream()
+            :   m_streamBuf( new StreamBufImpl<OutputDebugWriter>() ),
+                m_os( m_streamBuf.get() )
+            {}
+
+            ~DebugOutStream() override = default;
+
+        public: // IStream
+            std::ostream& stream() const override { return m_os; }
+        };
+
+    }} // namespace anon::detail
+
+    ///////////////////////////////////////////////////////////////////////////
+
+    auto makeStream( StringRef const &filename ) -> IStream const* {
+        if( filename.empty() )
+            return new Detail::CoutStream();
+        else if( filename[0] == '%' ) {
+            if( filename == "%debug" )
+                return new Detail::DebugOutStream();
+            else
+                CATCH_ERROR( "Unrecognised stream: '" << filename << "'" );
+        }
+        else
+            return new Detail::FileStream( filename );
+    }
+
+    // This class encapsulates the idea of a pool of ostringstreams that can be reused.
+    struct StringStreams {
+        std::vector<std::unique_ptr<std::ostringstream>> m_streams;
+        std::vector<std::size_t> m_unused;
+        std::ostringstream m_referenceStream; // Used for copy state/ flags from
+
+        auto add() -> std::size_t {
+            if( m_unused.empty() ) {
+                m_streams.push_back( std::unique_ptr<std::ostringstream>( new std::ostringstream ) );
+                return m_streams.size()-1;
+            }
+            else {
+                auto index = m_unused.back();
+                m_unused.pop_back();
+                return index;
+            }
+        }
+
+        void release( std::size_t index ) {
+            m_streams[index]->copyfmt( m_referenceStream ); // Restore initial flags and other state
+            m_unused.push_back(index);
+        }
+    };
+
+    ReusableStringStream::ReusableStringStream()
+    :   m_index( Singleton<StringStreams>::getMutable().add() ),
+        m_oss( Singleton<StringStreams>::getMutable().m_streams[m_index].get() )
+    {}
+
+    ReusableStringStream::~ReusableStringStream() {
+        static_cast<std::ostringstream*>( m_oss )->str("");
+        m_oss->clear();
+        Singleton<StringStreams>::getMutable().release( m_index );
+    }
+
+    auto ReusableStringStream::str() const -> std::string {
+        return static_cast<std::ostringstream*>( m_oss )->str();
+    }
+
+    ///////////////////////////////////////////////////////////////////////////
+
+#ifndef CATCH_CONFIG_NOSTDOUT // If you #define this you must implement these functions
+    std::ostream& cout() { return std::cout; }
+    std::ostream& cerr() { return std::cerr; }
+    std::ostream& clog() { return std::clog; }
+#endif
+}
+// end catch_stream.cpp
+// start catch_string_manip.cpp
+
+#include <algorithm>
+#include <ostream>
+#include <cstring>
+#include <cctype>
+#include <vector>
+
+namespace Catch {
+
+    namespace {
+        char toLowerCh(char c) {
+            return static_cast<char>( std::tolower( c ) );
+        }
+    }
+
+    bool startsWith( std::string const& s, std::string const& prefix ) {
+        return s.size() >= prefix.size() && std::equal(prefix.begin(), prefix.end(), s.begin());
+    }
+    bool startsWith( std::string const& s, char prefix ) {
+        return !s.empty() && s[0] == prefix;
+    }
+    bool endsWith( std::string const& s, std::string const& suffix ) {
+        return s.size() >= suffix.size() && std::equal(suffix.rbegin(), suffix.rend(), s.rbegin());
+    }
+    bool endsWith( std::string const& s, char suffix ) {
+        return !s.empty() && s[s.size()-1] == suffix;
+    }
+    bool contains( std::string const& s, std::string const& infix ) {
+        return s.find( infix ) != std::string::npos;
+    }
+    void toLowerInPlace( std::string& s ) {
+        std::transform( s.begin(), s.end(), s.begin(), toLowerCh );
+    }
+    std::string toLower( std::string const& s ) {
+        std::string lc = s;
+        toLowerInPlace( lc );
+        return lc;
+    }
+    std::string trim( std::string const& str ) {
+        static char const* whitespaceChars = "\n\r\t ";
+        std::string::size_type start = str.find_first_not_of( whitespaceChars );
+        std::string::size_type end = str.find_last_not_of( whitespaceChars );
+
+        return start != std::string::npos ? str.substr( start, 1+end-start ) : std::string();
+    }
+
+    StringRef trim(StringRef ref) {
+        const auto is_ws = [](char c) {
+            return c == ' ' || c == '\t' || c == '\n' || c == '\r';
+        };
+        size_t real_begin = 0;
+        while (real_begin < ref.size() && is_ws(ref[real_begin])) { ++real_begin; }
+        size_t real_end = ref.size();
+        while (real_end > real_begin && is_ws(ref[real_end - 1])) { --real_end; }
+
+        return ref.substr(real_begin, real_end - real_begin);
+    }
+
+    bool replaceInPlace( std::string& str, std::string const& replaceThis, std::string const& withThis ) {
+        bool replaced = false;
+        std::size_t i = str.find( replaceThis );
+        while( i != std::string::npos ) {
+            replaced = true;
+            str = str.substr( 0, i ) + withThis + str.substr( i+replaceThis.size() );
+            if( i < str.size()-withThis.size() )
+                i = str.find( replaceThis, i+withThis.size() );
+            else
+                i = std::string::npos;
+        }
+        return replaced;
+    }
+
+    std::vector<StringRef> splitStringRef( StringRef str, char delimiter ) {
+        std::vector<StringRef> subStrings;
+        std::size_t start = 0;
+        for(std::size_t pos = 0; pos < str.size(); ++pos ) {
+            if( str[pos] == delimiter ) {
+                if( pos - start > 1 )
+                    subStrings.push_back( str.substr( start, pos-start ) );
+                start = pos+1;
+            }
+        }
+        if( start < str.size() )
+            subStrings.push_back( str.substr( start, str.size()-start ) );
+        return subStrings;
+    }
+
+    pluralise::pluralise( std::size_t count, std::string const& label )
+    :   m_count( count ),
+        m_label( label )
+    {}
+
+    std::ostream& operator << ( std::ostream& os, pluralise const& pluraliser ) {
+        os << pluraliser.m_count << ' ' << pluraliser.m_label;
+        if( pluraliser.m_count != 1 )
+            os << 's';
+        return os;
+    }
+
+}
+// end catch_string_manip.cpp
+// start catch_stringref.cpp
+
+#include <algorithm>
+#include <ostream>
+#include <cstring>
+#include <cstdint>
+
+namespace Catch {
+    StringRef::StringRef( char const* rawChars ) noexcept
+    : StringRef( rawChars, static_cast<StringRef::size_type>(std::strlen(rawChars) ) )
+    {}
+
+    auto StringRef::c_str() const -> char const* {
+        CATCH_ENFORCE(isNullTerminated(), "Called StringRef::c_str() on a non-null-terminated instance");
+        return m_start;
+    }
+    auto StringRef::data() const noexcept -> char const* {
+        return m_start;
+    }
+
+    auto StringRef::substr( size_type start, size_type size ) const noexcept -> StringRef {
+        if (start < m_size) {
+            return StringRef(m_start + start, (std::min)(m_size - start, size));
+        } else {
+            return StringRef();
+        }
+    }
+    auto StringRef::operator == ( StringRef const& other ) const noexcept -> bool {
+        return m_size == other.m_size
+            && (std::memcmp( m_start, other.m_start, m_size ) == 0);
+    }
+
+    auto operator << ( std::ostream& os, StringRef const& str ) -> std::ostream& {
+        return os.write(str.data(), str.size());
+    }
+
+    auto operator+=( std::string& lhs, StringRef const& rhs ) -> std::string& {
+        lhs.append(rhs.data(), rhs.size());
+        return lhs;
+    }
+
+} // namespace Catch
+// end catch_stringref.cpp
+// start catch_tag_alias.cpp
+
+namespace Catch {
+    TagAlias::TagAlias(std::string const & _tag, SourceLineInfo _lineInfo): tag(_tag), lineInfo(_lineInfo) {}
+}
+// end catch_tag_alias.cpp
+// start catch_tag_alias_autoregistrar.cpp
+
+namespace Catch {
+
+    RegistrarForTagAliases::RegistrarForTagAliases(char const* alias, char const* tag, SourceLineInfo const& lineInfo) {
+        CATCH_TRY {
+            getMutableRegistryHub().registerTagAlias(alias, tag, lineInfo);
+        } CATCH_CATCH_ALL {
+            // Do not throw when constructing global objects, instead register the exception to be processed later
+            getMutableRegistryHub().registerStartupException();
+        }
+    }
+
+}
+// end catch_tag_alias_autoregistrar.cpp
+// start catch_tag_alias_registry.cpp
+
+#include <sstream>
+
+namespace Catch {
+
+    TagAliasRegistry::~TagAliasRegistry() {}
+
+    TagAlias const* TagAliasRegistry::find( std::string const& alias ) const {
+        auto it = m_registry.find( alias );
+        if( it != m_registry.end() )
+            return &(it->second);
+        else
+            return nullptr;
+    }
+
+    std::string TagAliasRegistry::expandAliases( std::string const& unexpandedTestSpec ) const {
+        std::string expandedTestSpec = unexpandedTestSpec;
+        for( auto const& registryKvp : m_registry ) {
+            std::size_t pos = expandedTestSpec.find( registryKvp.first );
+            if( pos != std::string::npos ) {
+                expandedTestSpec =  expandedTestSpec.substr( 0, pos ) +
+                                    registryKvp.second.tag +
+                                    expandedTestSpec.substr( pos + registryKvp.first.size() );
+            }
+        }
+        return expandedTestSpec;
+    }
+
+    void TagAliasRegistry::add( std::string const& alias, std::string const& tag, SourceLineInfo const& lineInfo ) {
+        CATCH_ENFORCE( startsWith(alias, "[@") && endsWith(alias, ']'),
+                      "error: tag alias, '" << alias << "' is not of the form [@alias name].\n" << lineInfo );
+
+        CATCH_ENFORCE( m_registry.insert(std::make_pair(alias, TagAlias(tag, lineInfo))).second,
+                      "error: tag alias, '" << alias << "' already registered.\n"
+                      << "\tFirst seen at: " << find(alias)->lineInfo << "\n"
+                      << "\tRedefined at: " << lineInfo );
+    }
+
+    ITagAliasRegistry::~ITagAliasRegistry() {}
+
+    ITagAliasRegistry const& ITagAliasRegistry::get() {
+        return getRegistryHub().getTagAliasRegistry();
+    }
+
+} // end namespace Catch
+// end catch_tag_alias_registry.cpp
+// start catch_test_case_info.cpp
+
+#include <cctype>
+#include <exception>
+#include <algorithm>
+#include <sstream>
+
+namespace Catch {
+
+    namespace {
+        TestCaseInfo::SpecialProperties parseSpecialTag( std::string const& tag ) {
+            if( startsWith( tag, '.' ) ||
+                tag == "!hide" )
+                return TestCaseInfo::IsHidden;
+            else if( tag == "!throws" )
+                return TestCaseInfo::Throws;
+            else if( tag == "!shouldfail" )
+                return TestCaseInfo::ShouldFail;
+            else if( tag == "!mayfail" )
+                return TestCaseInfo::MayFail;
+            else if( tag == "!nonportable" )
+                return TestCaseInfo::NonPortable;
+            else if( tag == "!benchmark" )
+                return static_cast<TestCaseInfo::SpecialProperties>( TestCaseInfo::Benchmark | TestCaseInfo::IsHidden );
+            else
+                return TestCaseInfo::None;
+        }
+        bool isReservedTag( std::string const& tag ) {
+            return parseSpecialTag( tag ) == TestCaseInfo::None && tag.size() > 0 && !std::isalnum( static_cast<unsigned char>(tag[0]) );
+        }
+        void enforceNotReservedTag( std::string const& tag, SourceLineInfo const& _lineInfo ) {
+            CATCH_ENFORCE( !isReservedTag(tag),
+                          "Tag name: [" << tag << "] is not allowed.\n"
+                          << "Tag names starting with non alphanumeric characters are reserved\n"
+                          << _lineInfo );
+        }
+    }
+
+    TestCase makeTestCase(  ITestInvoker* _testCase,
+                            std::string const& _className,
+                            NameAndTags const& nameAndTags,
+                            SourceLineInfo const& _lineInfo )
+    {
+        bool isHidden = false;
+
+        // Parse out tags
+        std::vector<std::string> tags;
+        std::string desc, tag;
+        bool inTag = false;
+        for (char c : nameAndTags.tags) {
+            if( !inTag ) {
+                if( c == '[' )
+                    inTag = true;
+                else
+                    desc += c;
+            }
+            else {
+                if( c == ']' ) {
+                    TestCaseInfo::SpecialProperties prop = parseSpecialTag( tag );
+                    if( ( prop & TestCaseInfo::IsHidden ) != 0 )
+                        isHidden = true;
+                    else if( prop == TestCaseInfo::None )
+                        enforceNotReservedTag( tag, _lineInfo );
+
+                    // Merged hide tags like `[.approvals]` should be added as
+                    // `[.][approvals]`. The `[.]` is added at later point, so
+                    // we only strip the prefix
+                    if (startsWith(tag, '.') && tag.size() > 1) {
+                        tag.erase(0, 1);
+                    }
+                    tags.push_back( tag );
+                    tag.clear();
+                    inTag = false;
+                }
+                else
+                    tag += c;
+            }
+        }
+        if( isHidden ) {
+            // Add all "hidden" tags to make them behave identically
+            tags.insert( tags.end(), { ".", "!hide" } );
+        }
+
+        TestCaseInfo info( static_cast<std::string>(nameAndTags.name), _className, desc, tags, _lineInfo );
+        return TestCase( _testCase, std::move(info) );
+    }
+
+    void setTags( TestCaseInfo& testCaseInfo, std::vector<std::string> tags ) {
+        std::sort(begin(tags), end(tags));
+        tags.erase(std::unique(begin(tags), end(tags)), end(tags));
+        testCaseInfo.lcaseTags.clear();
+
+        for( auto const& tag : tags ) {
+            std::string lcaseTag = toLower( tag );
+            testCaseInfo.properties = static_cast<TestCaseInfo::SpecialProperties>( testCaseInfo.properties | parseSpecialTag( lcaseTag ) );
+            testCaseInfo.lcaseTags.push_back( lcaseTag );
+        }
+        testCaseInfo.tags = std::move(tags);
+    }
+
+    TestCaseInfo::TestCaseInfo( std::string const& _name,
+                                std::string const& _className,
+                                std::string const& _description,
+                                std::vector<std::string> const& _tags,
+                                SourceLineInfo const& _lineInfo )
+    :   name( _name ),
+        className( _className ),
+        description( _description ),
+        lineInfo( _lineInfo ),
+        properties( None )
+    {
+        setTags( *this, _tags );
+    }
+
+    bool TestCaseInfo::isHidden() const {
+        return ( properties & IsHidden ) != 0;
+    }
+    bool TestCaseInfo::throws() const {
+        return ( properties & Throws ) != 0;
+    }
+    bool TestCaseInfo::okToFail() const {
+        return ( properties & (ShouldFail | MayFail ) ) != 0;
+    }
+    bool TestCaseInfo::expectedToFail() const {
+        return ( properties & (ShouldFail ) ) != 0;
+    }
+
+    std::string TestCaseInfo::tagsAsString() const {
+        std::string ret;
+        // '[' and ']' per tag
+        std::size_t full_size = 2 * tags.size();
+        for (const auto& tag : tags) {
+            full_size += tag.size();
+        }
+        ret.reserve(full_size);
+        for (const auto& tag : tags) {
+            ret.push_back('[');
+            ret.append(tag);
+            ret.push_back(']');
+        }
+
+        return ret;
+    }
+
+    TestCase::TestCase( ITestInvoker* testCase, TestCaseInfo&& info ) : TestCaseInfo( std::move(info) ), test( testCase ) {}
+
+    TestCase TestCase::withName( std::string const& _newName ) const {
+        TestCase other( *this );
+        other.name = _newName;
+        return other;
+    }
+
+    void TestCase::invoke() const {
+        test->invoke();
+    }
+
+    bool TestCase::operator == ( TestCase const& other ) const {
+        return  test.get() == other.test.get() &&
+                name == other.name &&
+                className == other.className;
+    }
+
+    bool TestCase::operator < ( TestCase const& other ) const {
+        return name < other.name;
+    }
+
+    TestCaseInfo const& TestCase::getTestCaseInfo() const
+    {
+        return *this;
+    }
+
+} // end namespace Catch
+// end catch_test_case_info.cpp
+// start catch_test_case_registry_impl.cpp
+
+#include <sstream>
+
+namespace Catch {
+
+    std::vector<TestCase> sortTests( IConfig const& config, std::vector<TestCase> const& unsortedTestCases ) {
+
+        std::vector<TestCase> sorted = unsortedTestCases;
+
+        switch( config.runOrder() ) {
+            case RunTests::InLexicographicalOrder:
+                std::sort( sorted.begin(), sorted.end() );
+                break;
+            case RunTests::InRandomOrder:
+                seedRng( config );
+                std::shuffle( sorted.begin(), sorted.end(), rng() );
+                break;
+            case RunTests::InDeclarationOrder:
+                // already in declaration order
+                break;
+        }
+        return sorted;
+    }
+
+    bool isThrowSafe( TestCase const& testCase, IConfig const& config ) {
+        return !testCase.throws() || config.allowThrows();
+    }
+
+    bool matchTest( TestCase const& testCase, TestSpec const& testSpec, IConfig const& config ) {
+        return testSpec.matches( testCase ) && isThrowSafe( testCase, config );
+    }
+
+    void enforceNoDuplicateTestCases( std::vector<TestCase> const& functions ) {
+        std::set<TestCase> seenFunctions;
+        for( auto const& function : functions ) {
+            auto prev = seenFunctions.insert( function );
+            CATCH_ENFORCE( prev.second,
+                    "error: TEST_CASE( \"" << function.name << "\" ) already defined.\n"
+                    << "\tFirst seen at " << prev.first->getTestCaseInfo().lineInfo << "\n"
+                    << "\tRedefined at " << function.getTestCaseInfo().lineInfo );
+        }
+    }
+
+    std::vector<TestCase> filterTests( std::vector<TestCase> const& testCases, TestSpec const& testSpec, IConfig const& config ) {
+        std::vector<TestCase> filtered;
+        filtered.reserve( testCases.size() );
+        for (auto const& testCase : testCases) {
+            if ((!testSpec.hasFilters() && !testCase.isHidden()) ||
+                (testSpec.hasFilters() && matchTest(testCase, testSpec, config))) {
+                filtered.push_back(testCase);
+            }
+        }
+        return filtered;
+    }
+    std::vector<TestCase> const& getAllTestCasesSorted( IConfig const& config ) {
+        return getRegistryHub().getTestCaseRegistry().getAllTestsSorted( config );
+    }
+
+    void TestRegistry::registerTest( TestCase const& testCase ) {
+        std::string name = testCase.getTestCaseInfo().name;
+        if( name.empty() ) {
+            ReusableStringStream rss;
+            rss << "Anonymous test case " << ++m_unnamedCount;
+            return registerTest( testCase.withName( rss.str() ) );
+        }
+        m_functions.push_back( testCase );
+    }
+
+    std::vector<TestCase> const& TestRegistry::getAllTests() const {
+        return m_functions;
+    }
+    std::vector<TestCase> const& TestRegistry::getAllTestsSorted( IConfig const& config ) const {
+        if( m_sortedFunctions.empty() )
+            enforceNoDuplicateTestCases( m_functions );
+
+        if(  m_currentSortOrder != config.runOrder() || m_sortedFunctions.empty() ) {
+            m_sortedFunctions = sortTests( config, m_functions );
+            m_currentSortOrder = config.runOrder();
+        }
+        return m_sortedFunctions;
+    }
+
+    ///////////////////////////////////////////////////////////////////////////
+    TestInvokerAsFunction::TestInvokerAsFunction( void(*testAsFunction)() ) noexcept : m_testAsFunction( testAsFunction ) {}
+
+    void TestInvokerAsFunction::invoke() const {
+        m_testAsFunction();
+    }
+
+    std::string extractClassName( StringRef const& classOrQualifiedMethodName ) {
+        std::string className(classOrQualifiedMethodName);
+        if( startsWith( className, '&' ) )
+        {
+            std::size_t lastColons = className.rfind( "::" );
+            std::size_t penultimateColons = className.rfind( "::", lastColons-1 );
+            if( penultimateColons == std::string::npos )
+                penultimateColons = 1;
+            className = className.substr( penultimateColons, lastColons-penultimateColons );
+        }
+        return className;
+    }
+
+} // end namespace Catch
+// end catch_test_case_registry_impl.cpp
+// start catch_test_case_tracker.cpp
+
+#include <algorithm>
+#include <cassert>
+#include <stdexcept>
+#include <memory>
+#include <sstream>
+
+#if defined(__clang__)
+#    pragma clang diagnostic push
+#    pragma clang diagnostic ignored "-Wexit-time-destructors"
+#endif
+
+namespace Catch {
+namespace TestCaseTracking {
+
+    NameAndLocation::NameAndLocation( std::string const& _name, SourceLineInfo const& _location )
+    :   name( _name ),
+        location( _location )
+    {}
+
+    ITracker::~ITracker() = default;
+
+    ITracker& TrackerContext::startRun() {
+        m_rootTracker = std::make_shared<SectionTracker>( NameAndLocation( "{root}", CATCH_INTERNAL_LINEINFO ), *this, nullptr );
+        m_currentTracker = nullptr;
+        m_runState = Executing;
+        return *m_rootTracker;
+    }
+
+    void TrackerContext::endRun() {
+        m_rootTracker.reset();
+        m_currentTracker = nullptr;
+        m_runState = NotStarted;
+    }
+
+    void TrackerContext::startCycle() {
+        m_currentTracker = m_rootTracker.get();
+        m_runState = Executing;
+    }
+    void TrackerContext::completeCycle() {
+        m_runState = CompletedCycle;
+    }
+
+    bool TrackerContext::completedCycle() const {
+        return m_runState == CompletedCycle;
+    }
+    ITracker& TrackerContext::currentTracker() {
+        return *m_currentTracker;
+    }
+    void TrackerContext::setCurrentTracker( ITracker* tracker ) {
+        m_currentTracker = tracker;
+    }
+
+    TrackerBase::TrackerBase( NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent )
+    :   m_nameAndLocation( nameAndLocation ),
+        m_ctx( ctx ),
+        m_parent( parent )
+    {}
+
+    NameAndLocation const& TrackerBase::nameAndLocation() const {
+        return m_nameAndLocation;
+    }
+    bool TrackerBase::isComplete() const {
+        return m_runState == CompletedSuccessfully || m_runState == Failed;
+    }
+    bool TrackerBase::isSuccessfullyCompleted() const {
+        return m_runState == CompletedSuccessfully;
+    }
+    bool TrackerBase::isOpen() const {
+        return m_runState != NotStarted && !isComplete();
+    }
+    bool TrackerBase::hasChildren() const {
+        return !m_children.empty();
+    }
+
+    void TrackerBase::addChild( ITrackerPtr const& child ) {
+        m_children.push_back( child );
+    }
+
+    ITrackerPtr TrackerBase::findChild( NameAndLocation const& nameAndLocation ) {
+        auto it = std::find_if( m_children.begin(), m_children.end(),
+            [&nameAndLocation]( ITrackerPtr const& tracker ){
+                return
+                    tracker->nameAndLocation().location == nameAndLocation.location &&
+                    tracker->nameAndLocation().name == nameAndLocation.name;
+            } );
+        return( it != m_children.end() )
+            ? *it
+            : nullptr;
+    }
+    ITracker& TrackerBase::parent() {
+        assert( m_parent ); // Should always be non-null except for root
+        return *m_parent;
+    }
+
+    void TrackerBase::openChild() {
+        if( m_runState != ExecutingChildren ) {
+            m_runState = ExecutingChildren;
+            if( m_parent )
+                m_parent->openChild();
+        }
+    }
+
+    bool TrackerBase::isSectionTracker() const { return false; }
+    bool TrackerBase::isGeneratorTracker() const { return false; }
+
+    void TrackerBase::open() {
+        m_runState = Executing;
+        moveToThis();
+        if( m_parent )
+            m_parent->openChild();
+    }
+
+    void TrackerBase::close() {
+
+        // Close any still open children (e.g. generators)
+        while( &m_ctx.currentTracker() != this )
+            m_ctx.currentTracker().close();
+
+        switch( m_runState ) {
+            case NeedsAnotherRun:
+                break;
+
+            case Executing:
+                m_runState = CompletedSuccessfully;
+                break;
+            case ExecutingChildren:
+                if( std::all_of(m_children.begin(), m_children.end(), [](ITrackerPtr const& t){ return t->isComplete(); }) )
+                    m_runState = CompletedSuccessfully;
+                break;
+
+            case NotStarted:
+            case CompletedSuccessfully:
+            case Failed:
+                CATCH_INTERNAL_ERROR( "Illogical state: " << m_runState );
+
+            default:
+                CATCH_INTERNAL_ERROR( "Unknown state: " << m_runState );
+        }
+        moveToParent();
+        m_ctx.completeCycle();
+    }
+    void TrackerBase::fail() {
+        m_runState = Failed;
+        if( m_parent )
+            m_parent->markAsNeedingAnotherRun();
+        moveToParent();
+        m_ctx.completeCycle();
+    }
+    void TrackerBase::markAsNeedingAnotherRun() {
+        m_runState = NeedsAnotherRun;
+    }
+
+    void TrackerBase::moveToParent() {
+        assert( m_parent );
+        m_ctx.setCurrentTracker( m_parent );
+    }
+    void TrackerBase::moveToThis() {
+        m_ctx.setCurrentTracker( this );
+    }
+
+    SectionTracker::SectionTracker( NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent )
+    :   TrackerBase( nameAndLocation, ctx, parent ),
+        m_trimmed_name(trim(nameAndLocation.name))
+    {
+        if( parent ) {
+            while( !parent->isSectionTracker() )
+                parent = &parent->parent();
+
+            SectionTracker& parentSection = static_cast<SectionTracker&>( *parent );
+            addNextFilters( parentSection.m_filters );
+        }
+    }
+
+    bool SectionTracker::isComplete() const {
+        bool complete = true;
+
+        if ((m_filters.empty() || m_filters[0] == "")
+            || std::find(m_filters.begin(), m_filters.end(), m_trimmed_name) != m_filters.end()) {
+            complete = TrackerBase::isComplete();
+        }
+        return complete;
+    }
+
+    bool SectionTracker::isSectionTracker() const { return true; }
+
+    SectionTracker& SectionTracker::acquire( TrackerContext& ctx, NameAndLocation const& nameAndLocation ) {
+        std::shared_ptr<SectionTracker> section;
+
+        ITracker& currentTracker = ctx.currentTracker();
+        if( ITrackerPtr childTracker = currentTracker.findChild( nameAndLocation ) ) {
+            assert( childTracker );
+            assert( childTracker->isSectionTracker() );
+            section = std::static_pointer_cast<SectionTracker>( childTracker );
+        }
+        else {
+            section = std::make_shared<SectionTracker>( nameAndLocation, ctx, &currentTracker );
+            currentTracker.addChild( section );
+        }
+        if( !ctx.completedCycle() )
+            section->tryOpen();
+        return *section;
+    }
+
+    void SectionTracker::tryOpen() {
+        if( !isComplete() )
+            open();
+    }
+
+    void SectionTracker::addInitialFilters( std::vector<std::string> const& filters ) {
+        if( !filters.empty() ) {
+            m_filters.reserve( m_filters.size() + filters.size() + 2 );
+            m_filters.emplace_back(""); // Root - should never be consulted
+            m_filters.emplace_back(""); // Test Case - not a section filter
+            m_filters.insert( m_filters.end(), filters.begin(), filters.end() );
+        }
+    }
+    void SectionTracker::addNextFilters( std::vector<std::string> const& filters ) {
+        if( filters.size() > 1 )
+            m_filters.insert( m_filters.end(), filters.begin()+1, filters.end() );
+    }
+
+} // namespace TestCaseTracking
+
+using TestCaseTracking::ITracker;
+using TestCaseTracking::TrackerContext;
+using TestCaseTracking::SectionTracker;
+
+} // namespace Catch
+
+#if defined(__clang__)
+#    pragma clang diagnostic pop
+#endif
+// end catch_test_case_tracker.cpp
+// start catch_test_registry.cpp
+
+namespace Catch {
+
+    auto makeTestInvoker( void(*testAsFunction)() ) noexcept -> ITestInvoker* {
+        return new(std::nothrow) TestInvokerAsFunction( testAsFunction );
+    }
+
+    NameAndTags::NameAndTags( StringRef const& name_ , StringRef const& tags_ ) noexcept : name( name_ ), tags( tags_ ) {}
+
+    AutoReg::AutoReg( ITestInvoker* invoker, SourceLineInfo const& lineInfo, StringRef const& classOrMethod, NameAndTags const& nameAndTags ) noexcept {
+        CATCH_TRY {
+            getMutableRegistryHub()
+                    .registerTest(
+                        makeTestCase(
+                            invoker,
+                            extractClassName( classOrMethod ),
+                            nameAndTags,
+                            lineInfo));
+        } CATCH_CATCH_ALL {
+            // Do not throw when constructing global objects, instead register the exception to be processed later
+            getMutableRegistryHub().registerStartupException();
+        }
+    }
+
+    AutoReg::~AutoReg() = default;
+}
+// end catch_test_registry.cpp
+// start catch_test_spec.cpp
+
+#include <algorithm>
+#include <string>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    TestSpec::Pattern::Pattern( std::string const& name )
+    : m_name( name )
+    {}
+
+    TestSpec::Pattern::~Pattern() = default;
+
+    std::string const& TestSpec::Pattern::name() const {
+        return m_name;
+    }
+
+    TestSpec::NamePattern::NamePattern( std::string const& name, std::string const& filterString )
+    : Pattern( filterString )
+    , m_wildcardPattern( toLower( name ), CaseSensitive::No )
+    {}
+
+    bool TestSpec::NamePattern::matches( TestCaseInfo const& testCase ) const {
+        return m_wildcardPattern.matches( testCase.name );
+    }
+
+    TestSpec::TagPattern::TagPattern( std::string const& tag, std::string const& filterString )
+    : Pattern( filterString )
+    , m_tag( toLower( tag ) )
+    {}
+
+    bool TestSpec::TagPattern::matches( TestCaseInfo const& testCase ) const {
+        return std::find(begin(testCase.lcaseTags),
+                         end(testCase.lcaseTags),
+                         m_tag) != end(testCase.lcaseTags);
+    }
+
+    TestSpec::ExcludedPattern::ExcludedPattern( PatternPtr const& underlyingPattern )
+    : Pattern( underlyingPattern->name() )
+    , m_underlyingPattern( underlyingPattern )
+    {}
+
+    bool TestSpec::ExcludedPattern::matches( TestCaseInfo const& testCase ) const {
+        return !m_underlyingPattern->matches( testCase );
+    }
+
+    bool TestSpec::Filter::matches( TestCaseInfo const& testCase ) const {
+        return std::all_of( m_patterns.begin(), m_patterns.end(), [&]( PatternPtr const& p ){ return p->matches( testCase ); } );
+    }
+
+    std::string TestSpec::Filter::name() const {
+        std::string name;
+        for( auto const& p : m_patterns )
+            name += p->name();
+        return name;
+    }
+
+    bool TestSpec::hasFilters() const {
+        return !m_filters.empty();
+    }
+
+    bool TestSpec::matches( TestCaseInfo const& testCase ) const {
+        return std::any_of( m_filters.begin(), m_filters.end(), [&]( Filter const& f ){ return f.matches( testCase ); } );
+    }
+
+    TestSpec::Matches TestSpec::matchesByFilter( std::vector<TestCase> const& testCases, IConfig const& config ) const
+    {
+        Matches matches( m_filters.size() );
+        std::transform( m_filters.begin(), m_filters.end(), matches.begin(), [&]( Filter const& filter ){
+            std::vector<TestCase const*> currentMatches;
+            for( auto const& test : testCases )
+                if( isThrowSafe( test, config ) && filter.matches( test ) )
+                    currentMatches.emplace_back( &test );
+            return FilterMatch{ filter.name(), currentMatches };
+        } );
+        return matches;
+    }
+
+    const TestSpec::vectorStrings& TestSpec::getInvalidArgs() const{
+        return  (m_invalidArgs);
+    }
+
+}
+// end catch_test_spec.cpp
+// start catch_test_spec_parser.cpp
+
+namespace Catch {
+
+    TestSpecParser::TestSpecParser( ITagAliasRegistry const& tagAliases ) : m_tagAliases( &tagAliases ) {}
+
+    TestSpecParser& TestSpecParser::parse( std::string const& arg ) {
+        m_mode = None;
+        m_exclusion = false;
+        m_arg = m_tagAliases->expandAliases( arg );
+        m_escapeChars.clear();
+        m_substring.reserve(m_arg.size());
+        m_patternName.reserve(m_arg.size());
+        m_realPatternPos = 0;
+
+        for( m_pos = 0; m_pos < m_arg.size(); ++m_pos )
+          //if visitChar fails
+           if( !visitChar( m_arg[m_pos] ) ){
+               m_testSpec.m_invalidArgs.push_back(arg);
+               break;
+           }
+        endMode();
+        return *this;
+    }
+    TestSpec TestSpecParser::testSpec() {
+        addFilter();
+        return m_testSpec;
+    }
+    bool TestSpecParser::visitChar( char c ) {
+        if( (m_mode != EscapedName) && (c == '\\') ) {
+            escape();
+            addCharToPattern(c);
+            return true;
+        }else if((m_mode != EscapedName) && (c == ',') )  {
+            return separate();
+        }
+
+        switch( m_mode ) {
+        case None:
+            if( processNoneChar( c ) )
+                return true;
+            break;
+        case Name:
+            processNameChar( c );
+            break;
+        case EscapedName:
+            endMode();
+            addCharToPattern(c);
+            return true;
+        default:
+        case Tag:
+        case QuotedName:
+            if( processOtherChar( c ) )
+                return true;
+            break;
+        }
+
+        m_substring += c;
+        if( !isControlChar( c ) ) {
+            m_patternName += c;
+            m_realPatternPos++;
+        }
+        return true;
+    }
+    // Two of the processing methods return true to signal the caller to return
+    // without adding the given character to the current pattern strings
+    bool TestSpecParser::processNoneChar( char c ) {
+        switch( c ) {
+        case ' ':
+            return true;
+        case '~':
+            m_exclusion = true;
+            return false;
+        case '[':
+            startNewMode( Tag );
+            return false;
+        case '"':
+            startNewMode( QuotedName );
+            return false;
+        default:
+            startNewMode( Name );
+            return false;
+        }
+    }
+    void TestSpecParser::processNameChar( char c ) {
+        if( c == '[' ) {
+            if( m_substring == "exclude:" )
+                m_exclusion = true;
+            else
+                endMode();
+            startNewMode( Tag );
+        }
+    }
+    bool TestSpecParser::processOtherChar( char c ) {
+        if( !isControlChar( c ) )
+            return false;
+        m_substring += c;
+        endMode();
+        return true;
+    }
+    void TestSpecParser::startNewMode( Mode mode ) {
+        m_mode = mode;
+    }
+    void TestSpecParser::endMode() {
+        switch( m_mode ) {
+        case Name:
+        case QuotedName:
+            return addNamePattern();
+        case Tag:
+            return addTagPattern();
+        case EscapedName:
+            revertBackToLastMode();
+            return;
+        case None:
+        default:
+            return startNewMode( None );
+        }
+    }
+    void TestSpecParser::escape() {
+        saveLastMode();
+        m_mode = EscapedName;
+        m_escapeChars.push_back(m_realPatternPos);
+    }
+    bool TestSpecParser::isControlChar( char c ) const {
+        switch( m_mode ) {
+            default:
+                return false;
+            case None:
+                return c == '~';
+            case Name:
+                return c == '[';
+            case EscapedName:
+                return true;
+            case QuotedName:
+                return c == '"';
+            case Tag:
+                return c == '[' || c == ']';
+        }
+    }
+
+    void TestSpecParser::addFilter() {
+        if( !m_currentFilter.m_patterns.empty() ) {
+            m_testSpec.m_filters.push_back( m_currentFilter );
+            m_currentFilter = TestSpec::Filter();
+        }
+    }
+
+    void TestSpecParser::saveLastMode() {
+      lastMode = m_mode;
+    }
+
+    void TestSpecParser::revertBackToLastMode() {
+      m_mode = lastMode;
+    }
+
+    bool TestSpecParser::separate() {
+      if( (m_mode==QuotedName) || (m_mode==Tag) ){
+         //invalid argument, signal failure to previous scope.
+         m_mode = None;
+         m_pos = m_arg.size();
+         m_substring.clear();
+         m_patternName.clear();
+         return false;
+      }
+      endMode();
+      addFilter();
+      return true; //success
+    }
+
+    std::string TestSpecParser::preprocessPattern() {
+        std::string token = m_patternName;
+        for (std::size_t i = 0; i < m_escapeChars.size(); ++i)
+            token = token.substr(0, m_escapeChars[i] - i) + token.substr(m_escapeChars[i] - i + 1);
+        m_escapeChars.clear();
+        if (startsWith(token, "exclude:")) {
+            m_exclusion = true;
+            token = token.substr(8);
+        }
+
+        m_patternName.clear();
+
+        return token;
+    }
+
+    void TestSpecParser::addNamePattern() {
+        auto token = preprocessPattern();
+
+        if (!token.empty()) {
+            TestSpec::PatternPtr pattern = std::make_shared<TestSpec::NamePattern>(token, m_substring);
+            if (m_exclusion)
+                pattern = std::make_shared<TestSpec::ExcludedPattern>(pattern);
+            m_currentFilter.m_patterns.push_back(pattern);
+        }
+        m_substring.clear();
+        m_exclusion = false;
+        m_mode = None;
+    }
+
+    void TestSpecParser::addTagPattern() {
+        auto token = preprocessPattern();
+
+        if (!token.empty()) {
+            // If the tag pattern is the "hide and tag" shorthand (e.g. [.foo])
+            // we have to create a separate hide tag and shorten the real one
+            if (token.size() > 1 && token[0] == '.') {
+                token.erase(token.begin());
+                TestSpec::PatternPtr pattern = std::make_shared<TestSpec::TagPattern>(".", m_substring);
+                if (m_exclusion) {
+                    pattern = std::make_shared<TestSpec::ExcludedPattern>(pattern);
+                }
+                m_currentFilter.m_patterns.push_back(pattern);
+            }
+
+            TestSpec::PatternPtr pattern = std::make_shared<TestSpec::TagPattern>(token, m_substring);
+
+            if (m_exclusion) {
+                pattern = std::make_shared<TestSpec::ExcludedPattern>(pattern);
+            }
+            m_currentFilter.m_patterns.push_back(pattern);
+        }
+        m_substring.clear();
+        m_exclusion = false;
+        m_mode = None;
+    }
+
+    TestSpec parseTestSpec( std::string const& arg ) {
+        return TestSpecParser( ITagAliasRegistry::get() ).parse( arg ).testSpec();
+    }
+
+} // namespace Catch
+// end catch_test_spec_parser.cpp
+// start catch_timer.cpp
+
+#include <chrono>
+
+static const uint64_t nanosecondsInSecond = 1000000000;
+
+namespace Catch {
+
+    auto getCurrentNanosecondsSinceEpoch() -> uint64_t {
+        return std::chrono::duration_cast<std::chrono::nanoseconds>( std::chrono::high_resolution_clock::now().time_since_epoch() ).count();
+    }
+
+    namespace {
+        auto estimateClockResolution() -> uint64_t {
+            uint64_t sum = 0;
+            static const uint64_t iterations = 1000000;
+
+            auto startTime = getCurrentNanosecondsSinceEpoch();
+
+            for( std::size_t i = 0; i < iterations; ++i ) {
+
+                uint64_t ticks;
+                uint64_t baseTicks = getCurrentNanosecondsSinceEpoch();
+                do {
+                    ticks = getCurrentNanosecondsSinceEpoch();
+                } while( ticks == baseTicks );
+
+                auto delta = ticks - baseTicks;
+                sum += delta;
+
+                // If we have been calibrating for over 3 seconds -- the clock
+                // is terrible and we should move on.
+                // TBD: How to signal that the measured resolution is probably wrong?
+                if (ticks > startTime + 3 * nanosecondsInSecond) {
+                    return sum / ( i + 1u );
+                }
+            }
+
+            // We're just taking the mean, here. To do better we could take the std. dev and exclude outliers
+            // - and potentially do more iterations if there's a high variance.
+            return sum/iterations;
+        }
+    }
+    auto getEstimatedClockResolution() -> uint64_t {
+        static auto s_resolution = estimateClockResolution();
+        return s_resolution;
+    }
+
+    void Timer::start() {
+       m_nanoseconds = getCurrentNanosecondsSinceEpoch();
+    }
+    auto Timer::getElapsedNanoseconds() const -> uint64_t {
+        return getCurrentNanosecondsSinceEpoch() - m_nanoseconds;
+    }
+    auto Timer::getElapsedMicroseconds() const -> uint64_t {
+        return getElapsedNanoseconds()/1000;
+    }
+    auto Timer::getElapsedMilliseconds() const -> unsigned int {
+        return static_cast<unsigned int>(getElapsedMicroseconds()/1000);
+    }
+    auto Timer::getElapsedSeconds() const -> double {
+        return getElapsedMicroseconds()/1000000.0;
+    }
+
+} // namespace Catch
+// end catch_timer.cpp
+// start catch_tostring.cpp
+
+#if defined(__clang__)
+#    pragma clang diagnostic push
+#    pragma clang diagnostic ignored "-Wexit-time-destructors"
+#    pragma clang diagnostic ignored "-Wglobal-constructors"
+#endif
+
+// Enable specific decls locally
+#if !defined(CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER)
+#define CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER
+#endif
+
+#include <cmath>
+#include <iomanip>
+
+namespace Catch {
+
+namespace Detail {
+
+    const std::string unprintableString = "{?}";
+
+    namespace {
+        const int hexThreshold = 255;
+
+        struct Endianness {
+            enum Arch { Big, Little };
+
+            static Arch which() {
+                int one = 1;
+                // If the lowest byte we read is non-zero, we can assume
+                // that little endian format is used.
+                auto value = *reinterpret_cast<char*>(&one);
+                return value ? Little : Big;
+            }
+        };
+    }
+
+    std::string rawMemoryToString( const void *object, std::size_t size ) {
+        // Reverse order for little endian architectures
+        int i = 0, end = static_cast<int>( size ), inc = 1;
+        if( Endianness::which() == Endianness::Little ) {
+            i = end-1;
+            end = inc = -1;
+        }
+
+        unsigned char const *bytes = static_cast<unsigned char const *>(object);
+        ReusableStringStream rss;
+        rss << "0x" << std::setfill('0') << std::hex;
+        for( ; i != end; i += inc )
+             rss << std::setw(2) << static_cast<unsigned>(bytes[i]);
+       return rss.str();
+    }
+}
+
+template<typename T>
+std::string fpToString( T value, int precision ) {
+    if (Catch::isnan(value)) {
+        return "nan";
+    }
+
+    ReusableStringStream rss;
+    rss << std::setprecision( precision )
+        << std::fixed
+        << value;
+    std::string d = rss.str();
+    std::size_t i = d.find_last_not_of( '0' );
+    if( i != std::string::npos && i != d.size()-1 ) {
+        if( d[i] == '.' )
+            i++;
+        d = d.substr( 0, i+1 );
+    }
+    return d;
+}
+
+//// ======================================================= ////
+//
+//   Out-of-line defs for full specialization of StringMaker
+//
+//// ======================================================= ////
+
+std::string StringMaker<std::string>::convert(const std::string& str) {
+    if (!getCurrentContext().getConfig()->showInvisibles()) {
+        return '"' + str + '"';
+    }
+
+    std::string s("\"");
+    for (char c : str) {
+        switch (c) {
+        case '\n':
+            s.append("\\n");
+            break;
+        case '\t':
+            s.append("\\t");
+            break;
+        default:
+            s.push_back(c);
+            break;
+        }
+    }
+    s.append("\"");
+    return s;
+}
+
+#ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+std::string StringMaker<std::string_view>::convert(std::string_view str) {
+    return ::Catch::Detail::stringify(std::string{ str });
+}
+#endif
+
+std::string StringMaker<char const*>::convert(char const* str) {
+    if (str) {
+        return ::Catch::Detail::stringify(std::string{ str });
+    } else {
+        return{ "{null string}" };
+    }
+}
+std::string StringMaker<char*>::convert(char* str) {
+    if (str) {
+        return ::Catch::Detail::stringify(std::string{ str });
+    } else {
+        return{ "{null string}" };
+    }
+}
+
+#ifdef CATCH_CONFIG_WCHAR
+std::string StringMaker<std::wstring>::convert(const std::wstring& wstr) {
+    std::string s;
+    s.reserve(wstr.size());
+    for (auto c : wstr) {
+        s += (c <= 0xff) ? static_cast<char>(c) : '?';
+    }
+    return ::Catch::Detail::stringify(s);
+}
+
+# ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+std::string StringMaker<std::wstring_view>::convert(std::wstring_view str) {
+    return StringMaker<std::wstring>::convert(std::wstring(str));
+}
+# endif
+
+std::string StringMaker<wchar_t const*>::convert(wchar_t const * str) {
+    if (str) {
+        return ::Catch::Detail::stringify(std::wstring{ str });
+    } else {
+        return{ "{null string}" };
+    }
+}
+std::string StringMaker<wchar_t *>::convert(wchar_t * str) {
+    if (str) {
+        return ::Catch::Detail::stringify(std::wstring{ str });
+    } else {
+        return{ "{null string}" };
+    }
+}
+#endif
+
+#if defined(CATCH_CONFIG_CPP17_BYTE)
+#include <cstddef>
+std::string StringMaker<std::byte>::convert(std::byte value) {
+    return ::Catch::Detail::stringify(std::to_integer<unsigned long long>(value));
+}
+#endif // defined(CATCH_CONFIG_CPP17_BYTE)
+
+std::string StringMaker<int>::convert(int value) {
+    return ::Catch::Detail::stringify(static_cast<long long>(value));
+}
+std::string StringMaker<long>::convert(long value) {
+    return ::Catch::Detail::stringify(static_cast<long long>(value));
+}
+std::string StringMaker<long long>::convert(long long value) {
+    ReusableStringStream rss;
+    rss << value;
+    if (value > Detail::hexThreshold) {
+        rss << " (0x" << std::hex << value << ')';
+    }
+    return rss.str();
+}
+
+std::string StringMaker<unsigned int>::convert(unsigned int value) {
+    return ::Catch::Detail::stringify(static_cast<unsigned long long>(value));
+}
+std::string StringMaker<unsigned long>::convert(unsigned long value) {
+    return ::Catch::Detail::stringify(static_cast<unsigned long long>(value));
+}
+std::string StringMaker<unsigned long long>::convert(unsigned long long value) {
+    ReusableStringStream rss;
+    rss << value;
+    if (value > Detail::hexThreshold) {
+        rss << " (0x" << std::hex << value << ')';
+    }
+    return rss.str();
+}
+
+std::string StringMaker<bool>::convert(bool b) {
+    return b ? "true" : "false";
+}
+
+std::string StringMaker<signed char>::convert(signed char value) {
+    if (value == '\r') {
+        return "'\\r'";
+    } else if (value == '\f') {
+        return "'\\f'";
+    } else if (value == '\n') {
+        return "'\\n'";
+    } else if (value == '\t') {
+        return "'\\t'";
+    } else if ('\0' <= value && value < ' ') {
+        return ::Catch::Detail::stringify(static_cast<unsigned int>(value));
+    } else {
+        char chstr[] = "' '";
+        chstr[1] = value;
+        return chstr;
+    }
+}
+std::string StringMaker<char>::convert(char c) {
+    return ::Catch::Detail::stringify(static_cast<signed char>(c));
+}
+std::string StringMaker<unsigned char>::convert(unsigned char c) {
+    return ::Catch::Detail::stringify(static_cast<char>(c));
+}
+
+std::string StringMaker<std::nullptr_t>::convert(std::nullptr_t) {
+    return "nullptr";
+}
+
+int StringMaker<float>::precision = 5;
+
+std::string StringMaker<float>::convert(float value) {
+    return fpToString(value, precision) + 'f';
+}
+
+int StringMaker<double>::precision = 10;
+
+std::string StringMaker<double>::convert(double value) {
+    return fpToString(value, precision);
+}
+
+std::string ratio_string<std::atto>::symbol() { return "a"; }
+std::string ratio_string<std::femto>::symbol() { return "f"; }
+std::string ratio_string<std::pico>::symbol() { return "p"; }
+std::string ratio_string<std::nano>::symbol() { return "n"; }
+std::string ratio_string<std::micro>::symbol() { return "u"; }
+std::string ratio_string<std::milli>::symbol() { return "m"; }
+
+} // end namespace Catch
+
+#if defined(__clang__)
+#    pragma clang diagnostic pop
+#endif
+
+// end catch_tostring.cpp
+// start catch_totals.cpp
+
+namespace Catch {
+
+    Counts Counts::operator - ( Counts const& other ) const {
+        Counts diff;
+        diff.passed = passed - other.passed;
+        diff.failed = failed - other.failed;
+        diff.failedButOk = failedButOk - other.failedButOk;
+        return diff;
+    }
+
+    Counts& Counts::operator += ( Counts const& other ) {
+        passed += other.passed;
+        failed += other.failed;
+        failedButOk += other.failedButOk;
+        return *this;
+    }
+
+    std::size_t Counts::total() const {
+        return passed + failed + failedButOk;
+    }
+    bool Counts::allPassed() const {
+        return failed == 0 && failedButOk == 0;
+    }
+    bool Counts::allOk() const {
+        return failed == 0;
+    }
+
+    Totals Totals::operator - ( Totals const& other ) const {
+        Totals diff;
+        diff.assertions = assertions - other.assertions;
+        diff.testCases = testCases - other.testCases;
+        return diff;
+    }
+
+    Totals& Totals::operator += ( Totals const& other ) {
+        assertions += other.assertions;
+        testCases += other.testCases;
+        return *this;
+    }
+
+    Totals Totals::delta( Totals const& prevTotals ) const {
+        Totals diff = *this - prevTotals;
+        if( diff.assertions.failed > 0 )
+            ++diff.testCases.failed;
+        else if( diff.assertions.failedButOk > 0 )
+            ++diff.testCases.failedButOk;
+        else
+            ++diff.testCases.passed;
+        return diff;
+    }
+
+}
+// end catch_totals.cpp
+// start catch_uncaught_exceptions.cpp
+
+#include <exception>
+
+namespace Catch {
+    bool uncaught_exceptions() {
+#if defined(CATCH_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS)
+        return std::uncaught_exceptions() > 0;
+#else
+        return std::uncaught_exception();
+#endif
+  }
+} // end namespace Catch
+// end catch_uncaught_exceptions.cpp
+// start catch_version.cpp
+
+#include <ostream>
+
+namespace Catch {
+
+    Version::Version
+        (   unsigned int _majorVersion,
+            unsigned int _minorVersion,
+            unsigned int _patchNumber,
+            char const * const _branchName,
+            unsigned int _buildNumber )
+    :   majorVersion( _majorVersion ),
+        minorVersion( _minorVersion ),
+        patchNumber( _patchNumber ),
+        branchName( _branchName ),
+        buildNumber( _buildNumber )
+    {}
+
+    std::ostream& operator << ( std::ostream& os, Version const& version ) {
+        os  << version.majorVersion << '.'
+            << version.minorVersion << '.'
+            << version.patchNumber;
+        // branchName is never null -> 0th char is \0 if it is empty
+        if (version.branchName[0]) {
+            os << '-' << version.branchName
+               << '.' << version.buildNumber;
+        }
+        return os;
+    }
+
+    Version const& libraryVersion() {
+        static Version version( 2, 11, 3, "", 0 );
+        return version;
+    }
+
+}
+// end catch_version.cpp
+// start catch_wildcard_pattern.cpp
+
+namespace Catch {
+
+    WildcardPattern::WildcardPattern( std::string const& pattern,
+                                      CaseSensitive::Choice caseSensitivity )
+    :   m_caseSensitivity( caseSensitivity ),
+        m_pattern( normaliseString( pattern ) )
+    {
+        if( startsWith( m_pattern, '*' ) ) {
+            m_pattern = m_pattern.substr( 1 );
+            m_wildcard = WildcardAtStart;
+        }
+        if( endsWith( m_pattern, '*' ) ) {
+            m_pattern = m_pattern.substr( 0, m_pattern.size()-1 );
+            m_wildcard = static_cast<WildcardPosition>( m_wildcard | WildcardAtEnd );
+        }
+    }
+
+    bool WildcardPattern::matches( std::string const& str ) const {
+        switch( m_wildcard ) {
+            case NoWildcard:
+                return m_pattern == normaliseString( str );
+            case WildcardAtStart:
+                return endsWith( normaliseString( str ), m_pattern );
+            case WildcardAtEnd:
+                return startsWith( normaliseString( str ), m_pattern );
+            case WildcardAtBothEnds:
+                return contains( normaliseString( str ), m_pattern );
+            default:
+                CATCH_INTERNAL_ERROR( "Unknown enum" );
+        }
+    }
+
+    std::string WildcardPattern::normaliseString( std::string const& str ) const {
+        return trim( m_caseSensitivity == CaseSensitive::No ? toLower( str ) : str );
+    }
+}
+// end catch_wildcard_pattern.cpp
+// start catch_xmlwriter.cpp
+
+#include <iomanip>
+#include <type_traits>
+
+namespace Catch {
+
+namespace {
+
+    size_t trailingBytes(unsigned char c) {
+        if ((c & 0xE0) == 0xC0) {
+            return 2;
+        }
+        if ((c & 0xF0) == 0xE0) {
+            return 3;
+        }
+        if ((c & 0xF8) == 0xF0) {
+            return 4;
+        }
+        CATCH_INTERNAL_ERROR("Invalid multibyte utf-8 start byte encountered");
+    }
+
+    uint32_t headerValue(unsigned char c) {
+        if ((c & 0xE0) == 0xC0) {
+            return c & 0x1F;
+        }
+        if ((c & 0xF0) == 0xE0) {
+            return c & 0x0F;
+        }
+        if ((c & 0xF8) == 0xF0) {
+            return c & 0x07;
+        }
+        CATCH_INTERNAL_ERROR("Invalid multibyte utf-8 start byte encountered");
+    }
+
+    void hexEscapeChar(std::ostream& os, unsigned char c) {
+        std::ios_base::fmtflags f(os.flags());
+        os << "\\x"
+            << std::uppercase << std::hex << std::setfill('0') << std::setw(2)
+            << static_cast<int>(c);
+        os.flags(f);
+    }
+
+    bool shouldNewline(XmlFormatting fmt) {
+        return !!(static_cast<std::underlying_type<XmlFormatting>::type>(fmt & XmlFormatting::Newline));
+    }
+
+    bool shouldIndent(XmlFormatting fmt) {
+        return !!(static_cast<std::underlying_type<XmlFormatting>::type>(fmt & XmlFormatting::Indent));
+    }
+
+} // anonymous namespace
+
+    XmlFormatting operator | (XmlFormatting lhs, XmlFormatting rhs) {
+        return static_cast<XmlFormatting>(
+            static_cast<std::underlying_type<XmlFormatting>::type>(lhs) |
+            static_cast<std::underlying_type<XmlFormatting>::type>(rhs)
+        );
+    }
+
+    XmlFormatting operator & (XmlFormatting lhs, XmlFormatting rhs) {
+        return static_cast<XmlFormatting>(
+            static_cast<std::underlying_type<XmlFormatting>::type>(lhs) &
+            static_cast<std::underlying_type<XmlFormatting>::type>(rhs)
+        );
+    }
+
+    XmlEncode::XmlEncode( std::string const& str, ForWhat forWhat )
+    :   m_str( str ),
+        m_forWhat( forWhat )
+    {}
+
+    void XmlEncode::encodeTo( std::ostream& os ) const {
+        // Apostrophe escaping not necessary if we always use " to write attributes
+        // (see: http://www.w3.org/TR/xml/#syntax)
+
+        for( std::size_t idx = 0; idx < m_str.size(); ++ idx ) {
+            unsigned char c = m_str[idx];
+            switch (c) {
+            case '<':   os << "&lt;"; break;
+            case '&':   os << "&amp;"; break;
+
+            case '>':
+                // See: http://www.w3.org/TR/xml/#syntax
+                if (idx > 2 && m_str[idx - 1] == ']' && m_str[idx - 2] == ']')
+                    os << "&gt;";
+                else
+                    os << c;
+                break;
+
+            case '\"':
+                if (m_forWhat == ForAttributes)
+                    os << "&quot;";
+                else
+                    os << c;
+                break;
+
+            default:
+                // Check for control characters and invalid utf-8
+
+                // Escape control characters in standard ascii
+                // see http://stackoverflow.com/questions/404107/why-are-control-characters-illegal-in-xml-1-0
+                if (c < 0x09 || (c > 0x0D && c < 0x20) || c == 0x7F) {
+                    hexEscapeChar(os, c);
+                    break;
+                }
+
+                // Plain ASCII: Write it to stream
+                if (c < 0x7F) {
+                    os << c;
+                    break;
+                }
+
+                // UTF-8 territory
+                // Check if the encoding is valid and if it is not, hex escape bytes.
+                // Important: We do not check the exact decoded values for validity, only the encoding format
+                // First check that this bytes is a valid lead byte:
+                // This means that it is not encoded as 1111 1XXX
+                // Or as 10XX XXXX
+                if (c <  0xC0 ||
+                    c >= 0xF8) {
+                    hexEscapeChar(os, c);
+                    break;
+                }
+
+                auto encBytes = trailingBytes(c);
+                // Are there enough bytes left to avoid accessing out-of-bounds memory?
+                if (idx + encBytes - 1 >= m_str.size()) {
+                    hexEscapeChar(os, c);
+                    break;
+                }
+                // The header is valid, check data
+                // The next encBytes bytes must together be a valid utf-8
+                // This means: bitpattern 10XX XXXX and the extracted value is sane (ish)
+                bool valid = true;
+                uint32_t value = headerValue(c);
+                for (std::size_t n = 1; n < encBytes; ++n) {
+                    unsigned char nc = m_str[idx + n];
+                    valid &= ((nc & 0xC0) == 0x80);
+                    value = (value << 6) | (nc & 0x3F);
+                }
+
+                if (
+                    // Wrong bit pattern of following bytes
+                    (!valid) ||
+                    // Overlong encodings
+                    (value < 0x80) ||
+                    (0x80 <= value && value < 0x800   && encBytes > 2) ||
+                    (0x800 < value && value < 0x10000 && encBytes > 3) ||
+                    // Encoded value out of range
+                    (value >= 0x110000)
+                    ) {
+                    hexEscapeChar(os, c);
+                    break;
+                }
+
+                // If we got here, this is in fact a valid(ish) utf-8 sequence
+                for (std::size_t n = 0; n < encBytes; ++n) {
+                    os << m_str[idx + n];
+                }
+                idx += encBytes - 1;
+                break;
+            }
+        }
+    }
+
+    std::ostream& operator << ( std::ostream& os, XmlEncode const& xmlEncode ) {
+        xmlEncode.encodeTo( os );
+        return os;
+    }
+
+    XmlWriter::ScopedElement::ScopedElement( XmlWriter* writer, XmlFormatting fmt )
+    :   m_writer( writer ),
+        m_fmt(fmt)
+    {}
+
+    XmlWriter::ScopedElement::ScopedElement( ScopedElement&& other ) noexcept
+    :   m_writer( other.m_writer ),
+        m_fmt(other.m_fmt)
+    {
+        other.m_writer = nullptr;
+        other.m_fmt = XmlFormatting::None;
+    }
+    XmlWriter::ScopedElement& XmlWriter::ScopedElement::operator=( ScopedElement&& other ) noexcept {
+        if ( m_writer ) {
+            m_writer->endElement();
+        }
+        m_writer = other.m_writer;
+        other.m_writer = nullptr;
+        m_fmt = other.m_fmt;
+        other.m_fmt = XmlFormatting::None;
+        return *this;
+    }
+
+    XmlWriter::ScopedElement::~ScopedElement() {
+        if (m_writer) {
+            m_writer->endElement(m_fmt);
+        }
+    }
+
+    XmlWriter::ScopedElement& XmlWriter::ScopedElement::writeText( std::string const& text, XmlFormatting fmt ) {
+        m_writer->writeText( text, fmt );
+        return *this;
+    }
+
+    XmlWriter::XmlWriter( std::ostream& os ) : m_os( os )
+    {
+        writeDeclaration();
+    }
+
+    XmlWriter::~XmlWriter() {
+        while (!m_tags.empty()) {
+            endElement();
+        }
+        newlineIfNecessary();
+    }
+
+    XmlWriter& XmlWriter::startElement( std::string const& name, XmlFormatting fmt ) {
+        ensureTagClosed();
+        newlineIfNecessary();
+        if (shouldIndent(fmt)) {
+            m_os << m_indent;
+            m_indent += "  ";
+        }
+        m_os << '<' << name;
+        m_tags.push_back( name );
+        m_tagIsOpen = true;
+        applyFormatting(fmt);
+        return *this;
+    }
+
+    XmlWriter::ScopedElement XmlWriter::scopedElement( std::string const& name, XmlFormatting fmt ) {
+        ScopedElement scoped( this, fmt );
+        startElement( name, fmt );
+        return scoped;
+    }
+
+    XmlWriter& XmlWriter::endElement(XmlFormatting fmt) {
+        m_indent = m_indent.substr(0, m_indent.size() - 2);
+
+        if( m_tagIsOpen ) {
+            m_os << "/>";
+            m_tagIsOpen = false;
+        } else {
+            newlineIfNecessary();
+            if (shouldIndent(fmt)) {
+                m_os << m_indent;
+            }
+            m_os << "</" << m_tags.back() << ">";
+        }
+        m_os << std::flush;
+        applyFormatting(fmt);
+        m_tags.pop_back();
+        return *this;
+    }
+
+    XmlWriter& XmlWriter::writeAttribute( std::string const& name, std::string const& attribute ) {
+        if( !name.empty() && !attribute.empty() )
+            m_os << ' ' << name << "=\"" << XmlEncode( attribute, XmlEncode::ForAttributes ) << '"';
+        return *this;
+    }
+
+    XmlWriter& XmlWriter::writeAttribute( std::string const& name, bool attribute ) {
+        m_os << ' ' << name << "=\"" << ( attribute ? "true" : "false" ) << '"';
+        return *this;
+    }
+
+    XmlWriter& XmlWriter::writeText( std::string const& text, XmlFormatting fmt) {
+        if( !text.empty() ){
+            bool tagWasOpen = m_tagIsOpen;
+            ensureTagClosed();
+            if (tagWasOpen && shouldIndent(fmt)) {
+                m_os << m_indent;
+            }
+            m_os << XmlEncode( text );
+            applyFormatting(fmt);
+        }
+        return *this;
+    }
+
+    XmlWriter& XmlWriter::writeComment( std::string const& text, XmlFormatting fmt) {
+        ensureTagClosed();
+        if (shouldIndent(fmt)) {
+            m_os << m_indent;
+        }
+        m_os << "<!--" << text << "-->";
+        applyFormatting(fmt);
+        return *this;
+    }
+
+    void XmlWriter::writeStylesheetRef( std::string const& url ) {
+        m_os << "<?xml-stylesheet type=\"text/xsl\" href=\"" << url << "\"?>\n";
+    }
+
+    XmlWriter& XmlWriter::writeBlankLine() {
+        ensureTagClosed();
+        m_os << '\n';
+        return *this;
+    }
+
+    void XmlWriter::ensureTagClosed() {
+        if( m_tagIsOpen ) {
+            m_os << '>' << std::flush;
+            newlineIfNecessary();
+            m_tagIsOpen = false;
+        }
+    }
+
+    void XmlWriter::applyFormatting(XmlFormatting fmt) {
+        m_needsNewline = shouldNewline(fmt);
+    }
+
+    void XmlWriter::writeDeclaration() {
+        m_os << "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n";
+    }
+
+    void XmlWriter::newlineIfNecessary() {
+        if( m_needsNewline ) {
+            m_os << std::endl;
+            m_needsNewline = false;
+        }
+    }
+}
+// end catch_xmlwriter.cpp
+// start catch_reporter_bases.cpp
+
+#include <cstring>
+#include <cfloat>
+#include <cstdio>
+#include <cassert>
+#include <memory>
+
+namespace Catch {
+    void prepareExpandedExpression(AssertionResult& result) {
+        result.getExpandedExpression();
+    }
+
+    // Because formatting using c++ streams is stateful, drop down to C is required
+    // Alternatively we could use stringstream, but its performance is... not good.
+    std::string getFormattedDuration( double duration ) {
+        // Max exponent + 1 is required to represent the whole part
+        // + 1 for decimal point
+        // + 3 for the 3 decimal places
+        // + 1 for null terminator
+        const std::size_t maxDoubleSize = DBL_MAX_10_EXP + 1 + 1 + 3 + 1;
+        char buffer[maxDoubleSize];
+
+        // Save previous errno, to prevent sprintf from overwriting it
+        ErrnoGuard guard;
+#ifdef _MSC_VER
+        sprintf_s(buffer, "%.3f", duration);
+#else
+        std::sprintf(buffer, "%.3f", duration);
+#endif
+        return std::string(buffer);
+    }
+
+    std::string serializeFilters( std::vector<std::string> const& container ) {
+        ReusableStringStream oss;
+        bool first = true;
+        for (auto&& filter : container)
+        {
+            if (!first)
+                oss << ' ';
+            else
+                first = false;
+
+            oss << filter;
+        }
+        return oss.str();
+    }
+
+    TestEventListenerBase::TestEventListenerBase(ReporterConfig const & _config)
+        :StreamingReporterBase(_config) {}
+
+    std::set<Verbosity> TestEventListenerBase::getSupportedVerbosities() {
+        return { Verbosity::Quiet, Verbosity::Normal, Verbosity::High };
+    }
+
+    void TestEventListenerBase::assertionStarting(AssertionInfo const &) {}
+
+    bool TestEventListenerBase::assertionEnded(AssertionStats const &) {
+        return false;
+    }
+
+} // end namespace Catch
+// end catch_reporter_bases.cpp
+// start catch_reporter_compact.cpp
+
+namespace {
+
+#ifdef CATCH_PLATFORM_MAC
+    const char* failedString() { return "FAILED"; }
+    const char* passedString() { return "PASSED"; }
+#else
+    const char* failedString() { return "failed"; }
+    const char* passedString() { return "passed"; }
+#endif
+
+    // Colour::LightGrey
+    Catch::Colour::Code dimColour() { return Catch::Colour::FileName; }
+
+    std::string bothOrAll( std::size_t count ) {
+        return count == 1 ? std::string() :
+               count == 2 ? "both " : "all " ;
+    }
+
+} // anon namespace
+
+namespace Catch {
+namespace {
+// Colour, message variants:
+// - white: No tests ran.
+// -   red: Failed [both/all] N test cases, failed [both/all] M assertions.
+// - white: Passed [both/all] N test cases (no assertions).
+// -   red: Failed N tests cases, failed M assertions.
+// - green: Passed [both/all] N tests cases with M assertions.
+void printTotals(std::ostream& out, const Totals& totals) {
+    if (totals.testCases.total() == 0) {
+        out << "No tests ran.";
+    } else if (totals.testCases.failed == totals.testCases.total()) {
+        Colour colour(Colour::ResultError);
+        const std::string qualify_assertions_failed =
+            totals.assertions.failed == totals.assertions.total() ?
+            bothOrAll(totals.assertions.failed) : std::string();
+        out <<
+            "Failed " << bothOrAll(totals.testCases.failed)
+            << pluralise(totals.testCases.failed, "test case") << ", "
+            "failed " << qualify_assertions_failed <<
+            pluralise(totals.assertions.failed, "assertion") << '.';
+    } else if (totals.assertions.total() == 0) {
+        out <<
+            "Passed " << bothOrAll(totals.testCases.total())
+            << pluralise(totals.testCases.total(), "test case")
+            << " (no assertions).";
+    } else if (totals.assertions.failed) {
+        Colour colour(Colour::ResultError);
+        out <<
+            "Failed " << pluralise(totals.testCases.failed, "test case") << ", "
+            "failed " << pluralise(totals.assertions.failed, "assertion") << '.';
+    } else {
+        Colour colour(Colour::ResultSuccess);
+        out <<
+            "Passed " << bothOrAll(totals.testCases.passed)
+            << pluralise(totals.testCases.passed, "test case") <<
+            " with " << pluralise(totals.assertions.passed, "assertion") << '.';
+    }
+}
+
+// Implementation of CompactReporter formatting
+class AssertionPrinter {
+public:
+    AssertionPrinter& operator= (AssertionPrinter const&) = delete;
+    AssertionPrinter(AssertionPrinter const&) = delete;
+    AssertionPrinter(std::ostream& _stream, AssertionStats const& _stats, bool _printInfoMessages)
+        : stream(_stream)
+        , result(_stats.assertionResult)
+        , messages(_stats.infoMessages)
+        , itMessage(_stats.infoMessages.begin())
+        , printInfoMessages(_printInfoMessages) {}
+
+    void print() {
+        printSourceInfo();
+
+        itMessage = messages.begin();
+
+        switch (result.getResultType()) {
+        case ResultWas::Ok:
+            printResultType(Colour::ResultSuccess, passedString());
+            printOriginalExpression();
+            printReconstructedExpression();
+            if (!result.hasExpression())
+                printRemainingMessages(Colour::None);
+            else
+                printRemainingMessages();
+            break;
+        case ResultWas::ExpressionFailed:
+            if (result.isOk())
+                printResultType(Colour::ResultSuccess, failedString() + std::string(" - but was ok"));
+            else
+                printResultType(Colour::Error, failedString());
+            printOriginalExpression();
+            printReconstructedExpression();
+            printRemainingMessages();
+            break;
+        case ResultWas::ThrewException:
+            printResultType(Colour::Error, failedString());
+            printIssue("unexpected exception with message:");
+            printMessage();
+            printExpressionWas();
+            printRemainingMessages();
+            break;
+        case ResultWas::FatalErrorCondition:
+            printResultType(Colour::Error, failedString());
+            printIssue("fatal error condition with message:");
+            printMessage();
+            printExpressionWas();
+            printRemainingMessages();
+            break;
+        case ResultWas::DidntThrowException:
+            printResultType(Colour::Error, failedString());
+            printIssue("expected exception, got none");
+            printExpressionWas();
+            printRemainingMessages();
+            break;
+        case ResultWas::Info:
+            printResultType(Colour::None, "info");
+            printMessage();
+            printRemainingMessages();
+            break;
+        case ResultWas::Warning:
+            printResultType(Colour::None, "warning");
+            printMessage();
+            printRemainingMessages();
+            break;
+        case ResultWas::ExplicitFailure:
+            printResultType(Colour::Error, failedString());
+            printIssue("explicitly");
+            printRemainingMessages(Colour::None);
+            break;
+            // These cases are here to prevent compiler warnings
+        case ResultWas::Unknown:
+        case ResultWas::FailureBit:
+        case ResultWas::Exception:
+            printResultType(Colour::Error, "** internal error **");
+            break;
+        }
+    }
+
+private:
+    void printSourceInfo() const {
+        Colour colourGuard(Colour::FileName);
+        stream << result.getSourceInfo() << ':';
+    }
+
+    void printResultType(Colour::Code colour, std::string const& passOrFail) const {
+        if (!passOrFail.empty()) {
+            {
+                Colour colourGuard(colour);
+                stream << ' ' << passOrFail;
+            }
+            stream << ':';
+        }
+    }
+
+    void printIssue(std::string const& issue) const {
+        stream << ' ' << issue;
+    }
+
+    void printExpressionWas() {
+        if (result.hasExpression()) {
+            stream << ';';
+            {
+                Colour colour(dimColour());
+                stream << " expression was:";
+            }
+            printOriginalExpression();
+        }
+    }
+
+    void printOriginalExpression() const {
+        if (result.hasExpression()) {
+            stream << ' ' << result.getExpression();
+        }
+    }
+
+    void printReconstructedExpression() const {
+        if (result.hasExpandedExpression()) {
+            {
+                Colour colour(dimColour());
+                stream << " for: ";
+            }
+            stream << result.getExpandedExpression();
+        }
+    }
+
+    void printMessage() {
+        if (itMessage != messages.end()) {
+            stream << " '" << itMessage->message << '\'';
+            ++itMessage;
+        }
+    }
+
+    void printRemainingMessages(Colour::Code colour = dimColour()) {
+        if (itMessage == messages.end())
+            return;
+
+        const auto itEnd = messages.cend();
+        const auto N = static_cast<std::size_t>(std::distance(itMessage, itEnd));
+
+        {
+            Colour colourGuard(colour);
+            stream << " with " << pluralise(N, "message") << ':';
+        }
+
+        while (itMessage != itEnd) {
+            // If this assertion is a warning ignore any INFO messages
+            if (printInfoMessages || itMessage->type != ResultWas::Info) {
+                printMessage();
+                if (itMessage != itEnd) {
+                    Colour colourGuard(dimColour());
+                    stream << " and";
+                }
+                continue;
+            }
+            ++itMessage;
+        }
+    }
+
+private:
+    std::ostream& stream;
+    AssertionResult const& result;
+    std::vector<MessageInfo> messages;
+    std::vector<MessageInfo>::const_iterator itMessage;
+    bool printInfoMessages;
+};
+
+} // anon namespace
+
+        std::string CompactReporter::getDescription() {
+            return "Reports test results on a single line, suitable for IDEs";
+        }
+
+        ReporterPreferences CompactReporter::getPreferences() const {
+            return m_reporterPrefs;
+        }
+
+        void CompactReporter::noMatchingTestCases( std::string const& spec ) {
+            stream << "No test cases matched '" << spec << '\'' << std::endl;
+        }
+
+        void CompactReporter::assertionStarting( AssertionInfo const& ) {}
+
+        bool CompactReporter::assertionEnded( AssertionStats const& _assertionStats ) {
+            AssertionResult const& result = _assertionStats.assertionResult;
+
+            bool printInfoMessages = true;
+
+            // Drop out if result was successful and we're not printing those
+            if( !m_config->includeSuccessfulResults() && result.isOk() ) {
+                if( result.getResultType() != ResultWas::Warning )
+                    return false;
+                printInfoMessages = false;
+            }
+
+            AssertionPrinter printer( stream, _assertionStats, printInfoMessages );
+            printer.print();
+
+            stream << std::endl;
+            return true;
+        }
+
+        void CompactReporter::sectionEnded(SectionStats const& _sectionStats) {
+            if (m_config->showDurations() == ShowDurations::Always) {
+                stream << getFormattedDuration(_sectionStats.durationInSeconds) << " s: " << _sectionStats.sectionInfo.name << std::endl;
+            }
+        }
+
+        void CompactReporter::testRunEnded( TestRunStats const& _testRunStats ) {
+            printTotals( stream, _testRunStats.totals );
+            stream << '\n' << std::endl;
+            StreamingReporterBase::testRunEnded( _testRunStats );
+        }
+
+        CompactReporter::~CompactReporter() {}
+
+    CATCH_REGISTER_REPORTER( "compact", CompactReporter )
+
+} // end namespace Catch
+// end catch_reporter_compact.cpp
+// start catch_reporter_console.cpp
+
+#include <cfloat>
+#include <cstdio>
+
+#if defined(_MSC_VER)
+#pragma warning(push)
+#pragma warning(disable:4061) // Not all labels are EXPLICITLY handled in switch
+ // Note that 4062 (not all labels are handled and default is missing) is enabled
+#endif
+
+#if defined(__clang__)
+#  pragma clang diagnostic push
+// For simplicity, benchmarking-only helpers are always enabled
+#  pragma clang diagnostic ignored "-Wunused-function"
+#endif
+
+namespace Catch {
+
+namespace {
+
+// Formatter impl for ConsoleReporter
+class ConsoleAssertionPrinter {
+public:
+    ConsoleAssertionPrinter& operator= (ConsoleAssertionPrinter const&) = delete;
+    ConsoleAssertionPrinter(ConsoleAssertionPrinter const&) = delete;
+    ConsoleAssertionPrinter(std::ostream& _stream, AssertionStats const& _stats, bool _printInfoMessages)
+        : stream(_stream),
+        stats(_stats),
+        result(_stats.assertionResult),
+        colour(Colour::None),
+        message(result.getMessage()),
+        messages(_stats.infoMessages),
+        printInfoMessages(_printInfoMessages) {
+        switch (result.getResultType()) {
+        case ResultWas::Ok:
+            colour = Colour::Success;
+            passOrFail = "PASSED";
+            //if( result.hasMessage() )
+            if (_stats.infoMessages.size() == 1)
+                messageLabel = "with message";
+            if (_stats.infoMessages.size() > 1)
+                messageLabel = "with messages";
+            break;
+        case ResultWas::ExpressionFailed:
+            if (result.isOk()) {
+                colour = Colour::Success;
+                passOrFail = "FAILED - but was ok";
+            } else {
+                colour = Colour::Error;
+                passOrFail = "FAILED";
+            }
+            if (_stats.infoMessages.size() == 1)
+                messageLabel = "with message";
+            if (_stats.infoMessages.size() > 1)
+                messageLabel = "with messages";
+            break;
+        case ResultWas::ThrewException:
+            colour = Colour::Error;
+            passOrFail = "FAILED";
+            messageLabel = "due to unexpected exception with ";
+            if (_stats.infoMessages.size() == 1)
+                messageLabel += "message";
+            if (_stats.infoMessages.size() > 1)
+                messageLabel += "messages";
+            break;
+        case ResultWas::FatalErrorCondition:
+            colour = Colour::Error;
+            passOrFail = "FAILED";
+            messageLabel = "due to a fatal error condition";
+            break;
+        case ResultWas::DidntThrowException:
+            colour = Colour::Error;
+            passOrFail = "FAILED";
+            messageLabel = "because no exception was thrown where one was expected";
+            break;
+        case ResultWas::Info:
+            messageLabel = "info";
+            break;
+        case ResultWas::Warning:
+            messageLabel = "warning";
+            break;
+        case ResultWas::ExplicitFailure:
+            passOrFail = "FAILED";
+            colour = Colour::Error;
+            if (_stats.infoMessages.size() == 1)
+                messageLabel = "explicitly with message";
+            if (_stats.infoMessages.size() > 1)
+                messageLabel = "explicitly with messages";
+            break;
+            // These cases are here to prevent compiler warnings
+        case ResultWas::Unknown:
+        case ResultWas::FailureBit:
+        case ResultWas::Exception:
+            passOrFail = "** internal error **";
+            colour = Colour::Error;
+            break;
+        }
+    }
+
+    void print() const {
+        printSourceInfo();
+        if (stats.totals.assertions.total() > 0) {
+            printResultType();
+            printOriginalExpression();
+            printReconstructedExpression();
+        } else {
+            stream << '\n';
+        }
+        printMessage();
+    }
+
+private:
+    void printResultType() const {
+        if (!passOrFail.empty()) {
+            Colour colourGuard(colour);
+            stream << passOrFail << ":\n";
+        }
+    }
+    void printOriginalExpression() const {
+        if (result.hasExpression()) {
+            Colour colourGuard(Colour::OriginalExpression);
+            stream << "  ";
+            stream << result.getExpressionInMacro();
+            stream << '\n';
+        }
+    }
+    void printReconstructedExpression() const {
+        if (result.hasExpandedExpression()) {
+            stream << "with expansion:\n";
+            Colour colourGuard(Colour::ReconstructedExpression);
+            stream << Column(result.getExpandedExpression()).indent(2) << '\n';
+        }
+    }
+    void printMessage() const {
+        if (!messageLabel.empty())
+            stream << messageLabel << ':' << '\n';
+        for (auto const& msg : messages) {
+            // If this assertion is a warning ignore any INFO messages
+            if (printInfoMessages || msg.type != ResultWas::Info)
+                stream << Column(msg.message).indent(2) << '\n';
+        }
+    }
+    void printSourceInfo() const {
+        Colour colourGuard(Colour::FileName);
+        stream << result.getSourceInfo() << ": ";
+    }
+
+    std::ostream& stream;
+    AssertionStats const& stats;
+    AssertionResult const& result;
+    Colour::Code colour;
+    std::string passOrFail;
+    std::string messageLabel;
+    std::string message;
+    std::vector<MessageInfo> messages;
+    bool printInfoMessages;
+};
+
+std::size_t makeRatio(std::size_t number, std::size_t total) {
+    std::size_t ratio = total > 0 ? CATCH_CONFIG_CONSOLE_WIDTH * number / total : 0;
+    return (ratio == 0 && number > 0) ? 1 : ratio;
+}
+
+std::size_t& findMax(std::size_t& i, std::size_t& j, std::size_t& k) {
+    if (i > j && i > k)
+        return i;
+    else if (j > k)
+        return j;
+    else
+        return k;
+}
+
+struct ColumnInfo {
+    enum Justification { Left, Right };
+    std::string name;
+    int width;
+    Justification justification;
+};
+struct ColumnBreak {};
+struct RowBreak {};
+
+class Duration {
+    enum class Unit {
+        Auto,
+        Nanoseconds,
+        Microseconds,
+        Milliseconds,
+        Seconds,
+        Minutes
+    };
+    static const uint64_t s_nanosecondsInAMicrosecond = 1000;
+    static const uint64_t s_nanosecondsInAMillisecond = 1000 * s_nanosecondsInAMicrosecond;
+    static const uint64_t s_nanosecondsInASecond = 1000 * s_nanosecondsInAMillisecond;
+    static const uint64_t s_nanosecondsInAMinute = 60 * s_nanosecondsInASecond;
+
+    double m_inNanoseconds;
+    Unit m_units;
+
+public:
+    explicit Duration(double inNanoseconds, Unit units = Unit::Auto)
+        : m_inNanoseconds(inNanoseconds),
+        m_units(units) {
+        if (m_units == Unit::Auto) {
+            if (m_inNanoseconds < s_nanosecondsInAMicrosecond)
+                m_units = Unit::Nanoseconds;
+            else if (m_inNanoseconds < s_nanosecondsInAMillisecond)
+                m_units = Unit::Microseconds;
+            else if (m_inNanoseconds < s_nanosecondsInASecond)
+                m_units = Unit::Milliseconds;
+            else if (m_inNanoseconds < s_nanosecondsInAMinute)
+                m_units = Unit::Seconds;
+            else
+                m_units = Unit::Minutes;
+        }
+
+    }
+
+    auto value() const -> double {
+        switch (m_units) {
+        case Unit::Microseconds:
+            return m_inNanoseconds / static_cast<double>(s_nanosecondsInAMicrosecond);
+        case Unit::Milliseconds:
+            return m_inNanoseconds / static_cast<double>(s_nanosecondsInAMillisecond);
+        case Unit::Seconds:
+            return m_inNanoseconds / static_cast<double>(s_nanosecondsInASecond);
+        case Unit::Minutes:
+            return m_inNanoseconds / static_cast<double>(s_nanosecondsInAMinute);
+        default:
+            return m_inNanoseconds;
+        }
+    }
+    auto unitsAsString() const -> std::string {
+        switch (m_units) {
+        case Unit::Nanoseconds:
+            return "ns";
+        case Unit::Microseconds:
+            return "us";
+        case Unit::Milliseconds:
+            return "ms";
+        case Unit::Seconds:
+            return "s";
+        case Unit::Minutes:
+            return "m";
+        default:
+            return "** internal error **";
+        }
+
+    }
+    friend auto operator << (std::ostream& os, Duration const& duration) -> std::ostream& {
+        return os << duration.value() << ' ' << duration.unitsAsString();
+    }
+};
+} // end anon namespace
+
+class TablePrinter {
+    std::ostream& m_os;
+    std::vector<ColumnInfo> m_columnInfos;
+    std::ostringstream m_oss;
+    int m_currentColumn = -1;
+    bool m_isOpen = false;
+
+public:
+    TablePrinter( std::ostream& os, std::vector<ColumnInfo> columnInfos )
+    :   m_os( os ),
+        m_columnInfos( std::move( columnInfos ) ) {}
+
+    auto columnInfos() const -> std::vector<ColumnInfo> const& {
+        return m_columnInfos;
+    }
+
+    void open() {
+        if (!m_isOpen) {
+            m_isOpen = true;
+            *this << RowBreak();
+
+			Columns headerCols;
+			Spacer spacer(2);
+			for (auto const& info : m_columnInfos) {
+				headerCols += Column(info.name).width(static_cast<std::size_t>(info.width - 2));
+				headerCols += spacer;
+			}
+			m_os << headerCols << '\n';
+
+            m_os << Catch::getLineOfChars<'-'>() << '\n';
+        }
+    }
+    void close() {
+        if (m_isOpen) {
+            *this << RowBreak();
+            m_os << std::endl;
+            m_isOpen = false;
+        }
+    }
+
+    template<typename T>
+    friend TablePrinter& operator << (TablePrinter& tp, T const& value) {
+        tp.m_oss << value;
+        return tp;
+    }
+
+    friend TablePrinter& operator << (TablePrinter& tp, ColumnBreak) {
+        auto colStr = tp.m_oss.str();
+        const auto strSize = colStr.size();
+        tp.m_oss.str("");
+        tp.open();
+        if (tp.m_currentColumn == static_cast<int>(tp.m_columnInfos.size() - 1)) {
+            tp.m_currentColumn = -1;
+            tp.m_os << '\n';
+        }
+        tp.m_currentColumn++;
+
+        auto colInfo = tp.m_columnInfos[tp.m_currentColumn];
+        auto padding = (strSize + 1 < static_cast<std::size_t>(colInfo.width))
+            ? std::string(colInfo.width - (strSize + 1), ' ')
+            : std::string();
+        if (colInfo.justification == ColumnInfo::Left)
+            tp.m_os << colStr << padding << ' ';
+        else
+            tp.m_os << padding << colStr << ' ';
+        return tp;
+    }
+
+    friend TablePrinter& operator << (TablePrinter& tp, RowBreak) {
+        if (tp.m_currentColumn > 0) {
+            tp.m_os << '\n';
+            tp.m_currentColumn = -1;
+        }
+        return tp;
+    }
+};
+
+ConsoleReporter::ConsoleReporter(ReporterConfig const& config)
+    : StreamingReporterBase(config),
+    m_tablePrinter(new TablePrinter(config.stream(),
+        [&config]() -> std::vector<ColumnInfo> {
+        if (config.fullConfig()->benchmarkNoAnalysis())
+        {
+            return{
+                { "benchmark name", CATCH_CONFIG_CONSOLE_WIDTH - 43, ColumnInfo::Left },
+                { "     samples", 14, ColumnInfo::Right },
+                { "  iterations", 14, ColumnInfo::Right },
+                { "        mean", 14, ColumnInfo::Right }
+            };
+        }
+        else
+        {
+            return{
+                { "benchmark name", CATCH_CONFIG_CONSOLE_WIDTH - 32, ColumnInfo::Left },
+                { "samples      mean       std dev", 14, ColumnInfo::Right },
+                { "iterations   low mean   low std dev", 14, ColumnInfo::Right },
+                { "estimated    high mean  high std dev", 14, ColumnInfo::Right }
+            };
+        }
+    }())) {}
+ConsoleReporter::~ConsoleReporter() = default;
+
+std::string ConsoleReporter::getDescription() {
+    return "Reports test results as plain lines of text";
+}
+
+void ConsoleReporter::noMatchingTestCases(std::string const& spec) {
+    stream << "No test cases matched '" << spec << '\'' << std::endl;
+}
+
+void ConsoleReporter::reportInvalidArguments(std::string const&arg){
+    stream << "Invalid Filter: " << arg << std::endl;
+}
+
+void ConsoleReporter::assertionStarting(AssertionInfo const&) {}
+
+bool ConsoleReporter::assertionEnded(AssertionStats const& _assertionStats) {
+    AssertionResult const& result = _assertionStats.assertionResult;
+
+    bool includeResults = m_config->includeSuccessfulResults() || !result.isOk();
+
+    // Drop out if result was successful but we're not printing them.
+    if (!includeResults && result.getResultType() != ResultWas::Warning)
+        return false;
+
+    lazyPrint();
+
+    ConsoleAssertionPrinter printer(stream, _assertionStats, includeResults);
+    printer.print();
+    stream << std::endl;
+    return true;
+}
+
+void ConsoleReporter::sectionStarting(SectionInfo const& _sectionInfo) {
+    m_tablePrinter->close();
+    m_headerPrinted = false;
+    StreamingReporterBase::sectionStarting(_sectionInfo);
+}
+void ConsoleReporter::sectionEnded(SectionStats const& _sectionStats) {
+    m_tablePrinter->close();
+    if (_sectionStats.missingAssertions) {
+        lazyPrint();
+        Colour colour(Colour::ResultError);
+        if (m_sectionStack.size() > 1)
+            stream << "\nNo assertions in section";
+        else
+            stream << "\nNo assertions in test case";
+        stream << " '" << _sectionStats.sectionInfo.name << "'\n" << std::endl;
+    }
+    if (m_config->showDurations() == ShowDurations::Always) {
+        stream << getFormattedDuration(_sectionStats.durationInSeconds) << " s: " << _sectionStats.sectionInfo.name << std::endl;
+    }
+    if (m_headerPrinted) {
+        m_headerPrinted = false;
+    }
+    StreamingReporterBase::sectionEnded(_sectionStats);
+}
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+void ConsoleReporter::benchmarkPreparing(std::string const& name) {
+	lazyPrintWithoutClosingBenchmarkTable();
+
+	auto nameCol = Column(name).width(static_cast<std::size_t>(m_tablePrinter->columnInfos()[0].width - 2));
+
+	bool firstLine = true;
+	for (auto line : nameCol) {
+		if (!firstLine)
+			(*m_tablePrinter) << ColumnBreak() << ColumnBreak() << ColumnBreak();
+		else
+			firstLine = false;
+
+		(*m_tablePrinter) << line << ColumnBreak();
+	}
+}
+
+void ConsoleReporter::benchmarkStarting(BenchmarkInfo const& info) {
+    (*m_tablePrinter) << info.samples << ColumnBreak()
+        << info.iterations << ColumnBreak();
+    if (!m_config->benchmarkNoAnalysis())
+        (*m_tablePrinter) << Duration(info.estimatedDuration) << ColumnBreak();
+}
+void ConsoleReporter::benchmarkEnded(BenchmarkStats<> const& stats) {
+    if (m_config->benchmarkNoAnalysis())
+    {
+        (*m_tablePrinter) << Duration(stats.mean.point.count()) << ColumnBreak();
+    }
+    else
+    {
+        (*m_tablePrinter) << ColumnBreak()
+            << Duration(stats.mean.point.count()) << ColumnBreak()
+            << Duration(stats.mean.lower_bound.count()) << ColumnBreak()
+            << Duration(stats.mean.upper_bound.count()) << ColumnBreak() << ColumnBreak()
+            << Duration(stats.standardDeviation.point.count()) << ColumnBreak()
+            << Duration(stats.standardDeviation.lower_bound.count()) << ColumnBreak()
+            << Duration(stats.standardDeviation.upper_bound.count()) << ColumnBreak() << ColumnBreak() << ColumnBreak() << ColumnBreak() << ColumnBreak();
+    }
+}
+
+void ConsoleReporter::benchmarkFailed(std::string const& error) {
+	Colour colour(Colour::Red);
+    (*m_tablePrinter)
+        << "Benchmark failed (" << error << ')'
+        << ColumnBreak() << RowBreak();
+}
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+void ConsoleReporter::testCaseEnded(TestCaseStats const& _testCaseStats) {
+    m_tablePrinter->close();
+    StreamingReporterBase::testCaseEnded(_testCaseStats);
+    m_headerPrinted = false;
+}
+void ConsoleReporter::testGroupEnded(TestGroupStats const& _testGroupStats) {
+    if (currentGroupInfo.used) {
+        printSummaryDivider();
+        stream << "Summary for group '" << _testGroupStats.groupInfo.name << "':\n";
+        printTotals(_testGroupStats.totals);
+        stream << '\n' << std::endl;
+    }
+    StreamingReporterBase::testGroupEnded(_testGroupStats);
+}
+void ConsoleReporter::testRunEnded(TestRunStats const& _testRunStats) {
+    printTotalsDivider(_testRunStats.totals);
+    printTotals(_testRunStats.totals);
+    stream << std::endl;
+    StreamingReporterBase::testRunEnded(_testRunStats);
+}
+void ConsoleReporter::testRunStarting(TestRunInfo const& _testInfo) {
+    StreamingReporterBase::testRunStarting(_testInfo);
+    printTestFilters();
+}
+
+void ConsoleReporter::lazyPrint() {
+
+    m_tablePrinter->close();
+    lazyPrintWithoutClosingBenchmarkTable();
+}
+
+void ConsoleReporter::lazyPrintWithoutClosingBenchmarkTable() {
+
+    if (!currentTestRunInfo.used)
+        lazyPrintRunInfo();
+    if (!currentGroupInfo.used)
+        lazyPrintGroupInfo();
+
+    if (!m_headerPrinted) {
+        printTestCaseAndSectionHeader();
+        m_headerPrinted = true;
+    }
+}
+void ConsoleReporter::lazyPrintRunInfo() {
+    stream << '\n' << getLineOfChars<'~'>() << '\n';
+    Colour colour(Colour::SecondaryText);
+    stream << currentTestRunInfo->name
+        << " is a Catch v" << libraryVersion() << " host application.\n"
+        << "Run with -? for options\n\n";
+
+    if (m_config->rngSeed() != 0)
+        stream << "Randomness seeded to: " << m_config->rngSeed() << "\n\n";
+
+    currentTestRunInfo.used = true;
+}
+void ConsoleReporter::lazyPrintGroupInfo() {
+    if (!currentGroupInfo->name.empty() && currentGroupInfo->groupsCounts > 1) {
+        printClosedHeader("Group: " + currentGroupInfo->name);
+        currentGroupInfo.used = true;
+    }
+}
+void ConsoleReporter::printTestCaseAndSectionHeader() {
+    assert(!m_sectionStack.empty());
+    printOpenHeader(currentTestCaseInfo->name);
+
+    if (m_sectionStack.size() > 1) {
+        Colour colourGuard(Colour::Headers);
+
+        auto
+            it = m_sectionStack.begin() + 1, // Skip first section (test case)
+            itEnd = m_sectionStack.end();
+        for (; it != itEnd; ++it)
+            printHeaderString(it->name, 2);
+    }
+
+    SourceLineInfo lineInfo = m_sectionStack.back().lineInfo;
+
+    stream << getLineOfChars<'-'>() << '\n';
+    Colour colourGuard(Colour::FileName);
+    stream << lineInfo << '\n';
+    stream << getLineOfChars<'.'>() << '\n' << std::endl;
+}
+
+void ConsoleReporter::printClosedHeader(std::string const& _name) {
+    printOpenHeader(_name);
+    stream << getLineOfChars<'.'>() << '\n';
+}
+void ConsoleReporter::printOpenHeader(std::string const& _name) {
+    stream << getLineOfChars<'-'>() << '\n';
+    {
+        Colour colourGuard(Colour::Headers);
+        printHeaderString(_name);
+    }
+}
+
+// if string has a : in first line will set indent to follow it on
+// subsequent lines
+void ConsoleReporter::printHeaderString(std::string const& _string, std::size_t indent) {
+    std::size_t i = _string.find(": ");
+    if (i != std::string::npos)
+        i += 2;
+    else
+        i = 0;
+    stream << Column(_string).indent(indent + i).initialIndent(indent) << '\n';
+}
+
+struct SummaryColumn {
+
+    SummaryColumn( std::string _label, Colour::Code _colour )
+    :   label( std::move( _label ) ),
+        colour( _colour ) {}
+    SummaryColumn addRow( std::size_t count ) {
+        ReusableStringStream rss;
+        rss << count;
+        std::string row = rss.str();
+        for (auto& oldRow : rows) {
+            while (oldRow.size() < row.size())
+                oldRow = ' ' + oldRow;
+            while (oldRow.size() > row.size())
+                row = ' ' + row;
+        }
+        rows.push_back(row);
+        return *this;
+    }
+
+    std::string label;
+    Colour::Code colour;
+    std::vector<std::string> rows;
+
+};
+
+void ConsoleReporter::printTotals( Totals const& totals ) {
+    if (totals.testCases.total() == 0) {
+        stream << Colour(Colour::Warning) << "No tests ran\n";
+    } else if (totals.assertions.total() > 0 && totals.testCases.allPassed()) {
+        stream << Colour(Colour::ResultSuccess) << "All tests passed";
+        stream << " ("
+            << pluralise(totals.assertions.passed, "assertion") << " in "
+            << pluralise(totals.testCases.passed, "test case") << ')'
+            << '\n';
+    } else {
+
+        std::vector<SummaryColumn> columns;
+        columns.push_back(SummaryColumn("", Colour::None)
+                          .addRow(totals.testCases.total())
+                          .addRow(totals.assertions.total()));
+        columns.push_back(SummaryColumn("passed", Colour::Success)
+                          .addRow(totals.testCases.passed)
+                          .addRow(totals.assertions.passed));
+        columns.push_back(SummaryColumn("failed", Colour::ResultError)
+                          .addRow(totals.testCases.failed)
+                          .addRow(totals.assertions.failed));
+        columns.push_back(SummaryColumn("failed as expected", Colour::ResultExpectedFailure)
+                          .addRow(totals.testCases.failedButOk)
+                          .addRow(totals.assertions.failedButOk));
+
+        printSummaryRow("test cases", columns, 0);
+        printSummaryRow("assertions", columns, 1);
+    }
+}
+void ConsoleReporter::printSummaryRow(std::string const& label, std::vector<SummaryColumn> const& cols, std::size_t row) {
+    for (auto col : cols) {
+        std::string value = col.rows[row];
+        if (col.label.empty()) {
+            stream << label << ": ";
+            if (value != "0")
+                stream << value;
+            else
+                stream << Colour(Colour::Warning) << "- none -";
+        } else if (value != "0") {
+            stream << Colour(Colour::LightGrey) << " | ";
+            stream << Colour(col.colour)
+                << value << ' ' << col.label;
+        }
+    }
+    stream << '\n';
+}
+
+void ConsoleReporter::printTotalsDivider(Totals const& totals) {
+    if (totals.testCases.total() > 0) {
+        std::size_t failedRatio = makeRatio(totals.testCases.failed, totals.testCases.total());
+        std::size_t failedButOkRatio = makeRatio(totals.testCases.failedButOk, totals.testCases.total());
+        std::size_t passedRatio = makeRatio(totals.testCases.passed, totals.testCases.total());
+        while (failedRatio + failedButOkRatio + passedRatio < CATCH_CONFIG_CONSOLE_WIDTH - 1)
+            findMax(failedRatio, failedButOkRatio, passedRatio)++;
+        while (failedRatio + failedButOkRatio + passedRatio > CATCH_CONFIG_CONSOLE_WIDTH - 1)
+            findMax(failedRatio, failedButOkRatio, passedRatio)--;
+
+        stream << Colour(Colour::Error) << std::string(failedRatio, '=');
+        stream << Colour(Colour::ResultExpectedFailure) << std::string(failedButOkRatio, '=');
+        if (totals.testCases.allPassed())
+            stream << Colour(Colour::ResultSuccess) << std::string(passedRatio, '=');
+        else
+            stream << Colour(Colour::Success) << std::string(passedRatio, '=');
+    } else {
+        stream << Colour(Colour::Warning) << std::string(CATCH_CONFIG_CONSOLE_WIDTH - 1, '=');
+    }
+    stream << '\n';
+}
+void ConsoleReporter::printSummaryDivider() {
+    stream << getLineOfChars<'-'>() << '\n';
+}
+
+void ConsoleReporter::printTestFilters() {
+    if (m_config->testSpec().hasFilters()) {
+        Colour guard(Colour::BrightYellow);
+        stream << "Filters: " << serializeFilters(m_config->getTestsOrTags()) << '\n';
+    }
+}
+
+CATCH_REGISTER_REPORTER("console", ConsoleReporter)
+
+} // end namespace Catch
+
+#if defined(_MSC_VER)
+#pragma warning(pop)
+#endif
+
+#if defined(__clang__)
+#  pragma clang diagnostic pop
+#endif
+// end catch_reporter_console.cpp
+// start catch_reporter_junit.cpp
+
+#include <cassert>
+#include <sstream>
+#include <ctime>
+#include <algorithm>
+
+namespace Catch {
+
+    namespace {
+        std::string getCurrentTimestamp() {
+            // Beware, this is not reentrant because of backward compatibility issues
+            // Also, UTC only, again because of backward compatibility (%z is C++11)
+            time_t rawtime;
+            std::time(&rawtime);
+            auto const timeStampSize = sizeof("2017-01-16T17:06:45Z");
+
+#ifdef _MSC_VER
+            std::tm timeInfo = {};
+            gmtime_s(&timeInfo, &rawtime);
+#else
+            std::tm* timeInfo;
+            timeInfo = std::gmtime(&rawtime);
+#endif
+
+            char timeStamp[timeStampSize];
+            const char * const fmt = "%Y-%m-%dT%H:%M:%SZ";
+
+#ifdef _MSC_VER
+            std::strftime(timeStamp, timeStampSize, fmt, &timeInfo);
+#else
+            std::strftime(timeStamp, timeStampSize, fmt, timeInfo);
+#endif
+            return std::string(timeStamp);
+        }
+
+        std::string fileNameTag(const std::vector<std::string> &tags) {
+            auto it = std::find_if(begin(tags),
+                                   end(tags),
+                                   [] (std::string const& tag) {return tag.front() == '#'; });
+            if (it != tags.end())
+                return it->substr(1);
+            return std::string();
+        }
+    } // anonymous namespace
+
+    JunitReporter::JunitReporter( ReporterConfig const& _config )
+        :   CumulativeReporterBase( _config ),
+            xml( _config.stream() )
+        {
+            m_reporterPrefs.shouldRedirectStdOut = true;
+            m_reporterPrefs.shouldReportAllAssertions = true;
+        }
+
+    JunitReporter::~JunitReporter() {}
+
+    std::string JunitReporter::getDescription() {
+        return "Reports test results in an XML format that looks like Ant's junitreport target";
+    }
+
+    void JunitReporter::noMatchingTestCases( std::string const& /*spec*/ ) {}
+
+    void JunitReporter::testRunStarting( TestRunInfo const& runInfo )  {
+        CumulativeReporterBase::testRunStarting( runInfo );
+        xml.startElement( "testsuites" );
+    }
+
+    void JunitReporter::testGroupStarting( GroupInfo const& groupInfo ) {
+        suiteTimer.start();
+        stdOutForSuite.clear();
+        stdErrForSuite.clear();
+        unexpectedExceptions = 0;
+        CumulativeReporterBase::testGroupStarting( groupInfo );
+    }
+
+    void JunitReporter::testCaseStarting( TestCaseInfo const& testCaseInfo ) {
+        m_okToFail = testCaseInfo.okToFail();
+    }
+
+    bool JunitReporter::assertionEnded( AssertionStats const& assertionStats ) {
+        if( assertionStats.assertionResult.getResultType() == ResultWas::ThrewException && !m_okToFail )
+            unexpectedExceptions++;
+        return CumulativeReporterBase::assertionEnded( assertionStats );
+    }
+
+    void JunitReporter::testCaseEnded( TestCaseStats const& testCaseStats ) {
+        stdOutForSuite += testCaseStats.stdOut;
+        stdErrForSuite += testCaseStats.stdErr;
+        CumulativeReporterBase::testCaseEnded( testCaseStats );
+    }
+
+    void JunitReporter::testGroupEnded( TestGroupStats const& testGroupStats ) {
+        double suiteTime = suiteTimer.getElapsedSeconds();
+        CumulativeReporterBase::testGroupEnded( testGroupStats );
+        writeGroup( *m_testGroups.back(), suiteTime );
+    }
+
+    void JunitReporter::testRunEndedCumulative() {
+        xml.endElement();
+    }
+
+    void JunitReporter::writeGroup( TestGroupNode const& groupNode, double suiteTime ) {
+        XmlWriter::ScopedElement e = xml.scopedElement( "testsuite" );
+
+        TestGroupStats const& stats = groupNode.value;
+        xml.writeAttribute( "name", stats.groupInfo.name );
+        xml.writeAttribute( "errors", unexpectedExceptions );
+        xml.writeAttribute( "failures", stats.totals.assertions.failed-unexpectedExceptions );
+        xml.writeAttribute( "tests", stats.totals.assertions.total() );
+        xml.writeAttribute( "hostname", "tbd" ); // !TBD
+        if( m_config->showDurations() == ShowDurations::Never )
+            xml.writeAttribute( "time", "" );
+        else
+            xml.writeAttribute( "time", suiteTime );
+        xml.writeAttribute( "timestamp", getCurrentTimestamp() );
+
+        // Write properties if there are any
+        if (m_config->hasTestFilters() || m_config->rngSeed() != 0) {
+            auto properties = xml.scopedElement("properties");
+            if (m_config->hasTestFilters()) {
+                xml.scopedElement("property")
+                    .writeAttribute("name", "filters")
+                    .writeAttribute("value", serializeFilters(m_config->getTestsOrTags()));
+            }
+            if (m_config->rngSeed() != 0) {
+                xml.scopedElement("property")
+                    .writeAttribute("name", "random-seed")
+                    .writeAttribute("value", m_config->rngSeed());
+            }
+        }
+
+        // Write test cases
+        for( auto const& child : groupNode.children )
+            writeTestCase( *child );
+
+        xml.scopedElement( "system-out" ).writeText( trim( stdOutForSuite ), XmlFormatting::Newline );
+        xml.scopedElement( "system-err" ).writeText( trim( stdErrForSuite ), XmlFormatting::Newline );
+    }
+
+    void JunitReporter::writeTestCase( TestCaseNode const& testCaseNode ) {
+        TestCaseStats const& stats = testCaseNode.value;
+
+        // All test cases have exactly one section - which represents the
+        // test case itself. That section may have 0-n nested sections
+        assert( testCaseNode.children.size() == 1 );
+        SectionNode const& rootSection = *testCaseNode.children.front();
+
+        std::string className = stats.testInfo.className;
+
+        if( className.empty() ) {
+            className = fileNameTag(stats.testInfo.tags);
+            if ( className.empty() )
+                className = "global";
+        }
+
+        if ( !m_config->name().empty() )
+            className = m_config->name() + "." + className;
+
+        writeSection( className, "", rootSection );
+    }
+
+    void JunitReporter::writeSection(  std::string const& className,
+                        std::string const& rootName,
+                        SectionNode const& sectionNode ) {
+        std::string name = trim( sectionNode.stats.sectionInfo.name );
+        if( !rootName.empty() )
+            name = rootName + '/' + name;
+
+        if( !sectionNode.assertions.empty() ||
+            !sectionNode.stdOut.empty() ||
+            !sectionNode.stdErr.empty() ) {
+            XmlWriter::ScopedElement e = xml.scopedElement( "testcase" );
+            if( className.empty() ) {
+                xml.writeAttribute( "classname", name );
+                xml.writeAttribute( "name", "root" );
+            }
+            else {
+                xml.writeAttribute( "classname", className );
+                xml.writeAttribute( "name", name );
+            }
+            xml.writeAttribute( "time", ::Catch::Detail::stringify( sectionNode.stats.durationInSeconds ) );
+
+            writeAssertions( sectionNode );
+
+            if( !sectionNode.stdOut.empty() )
+                xml.scopedElement( "system-out" ).writeText( trim( sectionNode.stdOut ), XmlFormatting::Newline );
+            if( !sectionNode.stdErr.empty() )
+                xml.scopedElement( "system-err" ).writeText( trim( sectionNode.stdErr ), XmlFormatting::Newline );
+        }
+        for( auto const& childNode : sectionNode.childSections )
+            if( className.empty() )
+                writeSection( name, "", *childNode );
+            else
+                writeSection( className, name, *childNode );
+    }
+
+    void JunitReporter::writeAssertions( SectionNode const& sectionNode ) {
+        for( auto const& assertion : sectionNode.assertions )
+            writeAssertion( assertion );
+    }
+
+    void JunitReporter::writeAssertion( AssertionStats const& stats ) {
+        AssertionResult const& result = stats.assertionResult;
+        if( !result.isOk() ) {
+            std::string elementName;
+            switch( result.getResultType() ) {
+                case ResultWas::ThrewException:
+                case ResultWas::FatalErrorCondition:
+                    elementName = "error";
+                    break;
+                case ResultWas::ExplicitFailure:
+                case ResultWas::ExpressionFailed:
+                case ResultWas::DidntThrowException:
+                    elementName = "failure";
+                    break;
+
+                // We should never see these here:
+                case ResultWas::Info:
+                case ResultWas::Warning:
+                case ResultWas::Ok:
+                case ResultWas::Unknown:
+                case ResultWas::FailureBit:
+                case ResultWas::Exception:
+                    elementName = "internalError";
+                    break;
+            }
+
+            XmlWriter::ScopedElement e = xml.scopedElement( elementName );
+
+            xml.writeAttribute( "message", result.getExpression() );
+            xml.writeAttribute( "type", result.getTestMacroName() );
+
+            ReusableStringStream rss;
+            if (stats.totals.assertions.total() > 0) {
+                rss << "FAILED" << ":\n";
+                if (result.hasExpression()) {
+                    rss << "  ";
+                    rss << result.getExpressionInMacro();
+                    rss << '\n';
+                }
+                if (result.hasExpandedExpression()) {
+                    rss << "with expansion:\n";
+                    rss << Column(result.getExpandedExpression()).indent(2) << '\n';
+                }
+            } else {
+                rss << '\n';
+            }
+
+            if( !result.getMessage().empty() )
+                rss << result.getMessage() << '\n';
+            for( auto const& msg : stats.infoMessages )
+                if( msg.type == ResultWas::Info )
+                    rss << msg.message << '\n';
+
+            rss << "at " << result.getSourceInfo();
+            xml.writeText( rss.str(), XmlFormatting::Newline );
+        }
+    }
+
+    CATCH_REGISTER_REPORTER( "junit", JunitReporter )
+
+} // end namespace Catch
+// end catch_reporter_junit.cpp
+// start catch_reporter_listening.cpp
+
+#include <cassert>
+
+namespace Catch {
+
+    ListeningReporter::ListeningReporter() {
+        // We will assume that listeners will always want all assertions
+        m_preferences.shouldReportAllAssertions = true;
+    }
+
+    void ListeningReporter::addListener( IStreamingReporterPtr&& listener ) {
+        m_listeners.push_back( std::move( listener ) );
+    }
+
+    void ListeningReporter::addReporter(IStreamingReporterPtr&& reporter) {
+        assert(!m_reporter && "Listening reporter can wrap only 1 real reporter");
+        m_reporter = std::move( reporter );
+        m_preferences.shouldRedirectStdOut = m_reporter->getPreferences().shouldRedirectStdOut;
+    }
+
+    ReporterPreferences ListeningReporter::getPreferences() const {
+        return m_preferences;
+    }
+
+    std::set<Verbosity> ListeningReporter::getSupportedVerbosities() {
+        return std::set<Verbosity>{ };
+    }
+
+    void ListeningReporter::noMatchingTestCases( std::string const& spec ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->noMatchingTestCases( spec );
+        }
+        m_reporter->noMatchingTestCases( spec );
+    }
+
+    void ListeningReporter::reportInvalidArguments(std::string const&arg){
+        for ( auto const& listener : m_listeners ) {
+            listener->reportInvalidArguments( arg );
+        }
+        m_reporter->reportInvalidArguments( arg );
+    }
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    void ListeningReporter::benchmarkPreparing( std::string const& name ) {
+		for (auto const& listener : m_listeners) {
+			listener->benchmarkPreparing(name);
+		}
+		m_reporter->benchmarkPreparing(name);
+	}
+    void ListeningReporter::benchmarkStarting( BenchmarkInfo const& benchmarkInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->benchmarkStarting( benchmarkInfo );
+        }
+        m_reporter->benchmarkStarting( benchmarkInfo );
+    }
+    void ListeningReporter::benchmarkEnded( BenchmarkStats<> const& benchmarkStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->benchmarkEnded( benchmarkStats );
+        }
+        m_reporter->benchmarkEnded( benchmarkStats );
+    }
+
+	void ListeningReporter::benchmarkFailed( std::string const& error ) {
+		for (auto const& listener : m_listeners) {
+			listener->benchmarkFailed(error);
+		}
+		m_reporter->benchmarkFailed(error);
+	}
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    void ListeningReporter::testRunStarting( TestRunInfo const& testRunInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testRunStarting( testRunInfo );
+        }
+        m_reporter->testRunStarting( testRunInfo );
+    }
+
+    void ListeningReporter::testGroupStarting( GroupInfo const& groupInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testGroupStarting( groupInfo );
+        }
+        m_reporter->testGroupStarting( groupInfo );
+    }
+
+    void ListeningReporter::testCaseStarting( TestCaseInfo const& testInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testCaseStarting( testInfo );
+        }
+        m_reporter->testCaseStarting( testInfo );
+    }
+
+    void ListeningReporter::sectionStarting( SectionInfo const& sectionInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->sectionStarting( sectionInfo );
+        }
+        m_reporter->sectionStarting( sectionInfo );
+    }
+
+    void ListeningReporter::assertionStarting( AssertionInfo const& assertionInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->assertionStarting( assertionInfo );
+        }
+        m_reporter->assertionStarting( assertionInfo );
+    }
+
+    // The return value indicates if the messages buffer should be cleared:
+    bool ListeningReporter::assertionEnded( AssertionStats const& assertionStats ) {
+        for( auto const& listener : m_listeners ) {
+            static_cast<void>( listener->assertionEnded( assertionStats ) );
+        }
+        return m_reporter->assertionEnded( assertionStats );
+    }
+
+    void ListeningReporter::sectionEnded( SectionStats const& sectionStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->sectionEnded( sectionStats );
+        }
+        m_reporter->sectionEnded( sectionStats );
+    }
+
+    void ListeningReporter::testCaseEnded( TestCaseStats const& testCaseStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testCaseEnded( testCaseStats );
+        }
+        m_reporter->testCaseEnded( testCaseStats );
+    }
+
+    void ListeningReporter::testGroupEnded( TestGroupStats const& testGroupStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testGroupEnded( testGroupStats );
+        }
+        m_reporter->testGroupEnded( testGroupStats );
+    }
+
+    void ListeningReporter::testRunEnded( TestRunStats const& testRunStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testRunEnded( testRunStats );
+        }
+        m_reporter->testRunEnded( testRunStats );
+    }
+
+    void ListeningReporter::skipTest( TestCaseInfo const& testInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->skipTest( testInfo );
+        }
+        m_reporter->skipTest( testInfo );
+    }
+
+    bool ListeningReporter::isMulti() const {
+        return true;
+    }
+
+} // end namespace Catch
+// end catch_reporter_listening.cpp
+// start catch_reporter_xml.cpp
+
+#if defined(_MSC_VER)
+#pragma warning(push)
+#pragma warning(disable:4061) // Not all labels are EXPLICITLY handled in switch
+                              // Note that 4062 (not all labels are handled
+                              // and default is missing) is enabled
+#endif
+
+namespace Catch {
+    XmlReporter::XmlReporter( ReporterConfig const& _config )
+    :   StreamingReporterBase( _config ),
+        m_xml(_config.stream())
+    {
+        m_reporterPrefs.shouldRedirectStdOut = true;
+        m_reporterPrefs.shouldReportAllAssertions = true;
+    }
+
+    XmlReporter::~XmlReporter() = default;
+
+    std::string XmlReporter::getDescription() {
+        return "Reports test results as an XML document";
+    }
+
+    std::string XmlReporter::getStylesheetRef() const {
+        return std::string();
+    }
+
+    void XmlReporter::writeSourceInfo( SourceLineInfo const& sourceInfo ) {
+        m_xml
+            .writeAttribute( "filename", sourceInfo.file )
+            .writeAttribute( "line", sourceInfo.line );
+    }
+
+    void XmlReporter::noMatchingTestCases( std::string const& s ) {
+        StreamingReporterBase::noMatchingTestCases( s );
+    }
+
+    void XmlReporter::testRunStarting( TestRunInfo const& testInfo ) {
+        StreamingReporterBase::testRunStarting( testInfo );
+        std::string stylesheetRef = getStylesheetRef();
+        if( !stylesheetRef.empty() )
+            m_xml.writeStylesheetRef( stylesheetRef );
+        m_xml.startElement( "Catch" );
+        if( !m_config->name().empty() )
+            m_xml.writeAttribute( "name", m_config->name() );
+        if (m_config->testSpec().hasFilters())
+            m_xml.writeAttribute( "filters", serializeFilters( m_config->getTestsOrTags() ) );
+        if( m_config->rngSeed() != 0 )
+            m_xml.scopedElement( "Randomness" )
+                .writeAttribute( "seed", m_config->rngSeed() );
+    }
+
+    void XmlReporter::testGroupStarting( GroupInfo const& groupInfo ) {
+        StreamingReporterBase::testGroupStarting( groupInfo );
+        m_xml.startElement( "Group" )
+            .writeAttribute( "name", groupInfo.name );
+    }
+
+    void XmlReporter::testCaseStarting( TestCaseInfo const& testInfo ) {
+        StreamingReporterBase::testCaseStarting(testInfo);
+        m_xml.startElement( "TestCase" )
+            .writeAttribute( "name", trim( testInfo.name ) )
+            .writeAttribute( "description", testInfo.description )
+            .writeAttribute( "tags", testInfo.tagsAsString() );
+
+        writeSourceInfo( testInfo.lineInfo );
+
+        if ( m_config->showDurations() == ShowDurations::Always )
+            m_testCaseTimer.start();
+        m_xml.ensureTagClosed();
+    }
+
+    void XmlReporter::sectionStarting( SectionInfo const& sectionInfo ) {
+        StreamingReporterBase::sectionStarting( sectionInfo );
+        if( m_sectionDepth++ > 0 ) {
+            m_xml.startElement( "Section" )
+                .writeAttribute( "name", trim( sectionInfo.name ) );
+            writeSourceInfo( sectionInfo.lineInfo );
+            m_xml.ensureTagClosed();
+        }
+    }
+
+    void XmlReporter::assertionStarting( AssertionInfo const& ) { }
+
+    bool XmlReporter::assertionEnded( AssertionStats const& assertionStats ) {
+
+        AssertionResult const& result = assertionStats.assertionResult;
+
+        bool includeResults = m_config->includeSuccessfulResults() || !result.isOk();
+
+        if( includeResults || result.getResultType() == ResultWas::Warning ) {
+            // Print any info messages in <Info> tags.
+            for( auto const& msg : assertionStats.infoMessages ) {
+                if( msg.type == ResultWas::Info && includeResults ) {
+                    m_xml.scopedElement( "Info" )
+                            .writeText( msg.message );
+                } else if ( msg.type == ResultWas::Warning ) {
+                    m_xml.scopedElement( "Warning" )
+                            .writeText( msg.message );
+                }
+            }
+        }
+
+        // Drop out if result was successful but we're not printing them.
+        if( !includeResults && result.getResultType() != ResultWas::Warning )
+            return true;
+
+        // Print the expression if there is one.
+        if( result.hasExpression() ) {
+            m_xml.startElement( "Expression" )
+                .writeAttribute( "success", result.succeeded() )
+                .writeAttribute( "type", result.getTestMacroName() );
+
+            writeSourceInfo( result.getSourceInfo() );
+
+            m_xml.scopedElement( "Original" )
+                .writeText( result.getExpression() );
+            m_xml.scopedElement( "Expanded" )
+                .writeText( result.getExpandedExpression() );
+        }
+
+        // And... Print a result applicable to each result type.
+        switch( result.getResultType() ) {
+            case ResultWas::ThrewException:
+                m_xml.startElement( "Exception" );
+                writeSourceInfo( result.getSourceInfo() );
+                m_xml.writeText( result.getMessage() );
+                m_xml.endElement();
+                break;
+            case ResultWas::FatalErrorCondition:
+                m_xml.startElement( "FatalErrorCondition" );
+                writeSourceInfo( result.getSourceInfo() );
+                m_xml.writeText( result.getMessage() );
+                m_xml.endElement();
+                break;
+            case ResultWas::Info:
+                m_xml.scopedElement( "Info" )
+                    .writeText( result.getMessage() );
+                break;
+            case ResultWas::Warning:
+                // Warning will already have been written
+                break;
+            case ResultWas::ExplicitFailure:
+                m_xml.startElement( "Failure" );
+                writeSourceInfo( result.getSourceInfo() );
+                m_xml.writeText( result.getMessage() );
+                m_xml.endElement();
+                break;
+            default:
+                break;
+        }
+
+        if( result.hasExpression() )
+            m_xml.endElement();
+
+        return true;
+    }
+
+    void XmlReporter::sectionEnded( SectionStats const& sectionStats ) {
+        StreamingReporterBase::sectionEnded( sectionStats );
+        if( --m_sectionDepth > 0 ) {
+            XmlWriter::ScopedElement e = m_xml.scopedElement( "OverallResults" );
+            e.writeAttribute( "successes", sectionStats.assertions.passed );
+            e.writeAttribute( "failures", sectionStats.assertions.failed );
+            e.writeAttribute( "expectedFailures", sectionStats.assertions.failedButOk );
+
+            if ( m_config->showDurations() == ShowDurations::Always )
+                e.writeAttribute( "durationInSeconds", sectionStats.durationInSeconds );
+
+            m_xml.endElement();
+        }
+    }
+
+    void XmlReporter::testCaseEnded( TestCaseStats const& testCaseStats ) {
+        StreamingReporterBase::testCaseEnded( testCaseStats );
+        XmlWriter::ScopedElement e = m_xml.scopedElement( "OverallResult" );
+        e.writeAttribute( "success", testCaseStats.totals.assertions.allOk() );
+
+        if ( m_config->showDurations() == ShowDurations::Always )
+            e.writeAttribute( "durationInSeconds", m_testCaseTimer.getElapsedSeconds() );
+
+        if( !testCaseStats.stdOut.empty() )
+            m_xml.scopedElement( "StdOut" ).writeText( trim( testCaseStats.stdOut ), XmlFormatting::Newline );
+        if( !testCaseStats.stdErr.empty() )
+            m_xml.scopedElement( "StdErr" ).writeText( trim( testCaseStats.stdErr ), XmlFormatting::Newline );
+
+        m_xml.endElement();
+    }
+
+    void XmlReporter::testGroupEnded( TestGroupStats const& testGroupStats ) {
+        StreamingReporterBase::testGroupEnded( testGroupStats );
+        // TODO: Check testGroupStats.aborting and act accordingly.
+        m_xml.scopedElement( "OverallResults" )
+            .writeAttribute( "successes", testGroupStats.totals.assertions.passed )
+            .writeAttribute( "failures", testGroupStats.totals.assertions.failed )
+            .writeAttribute( "expectedFailures", testGroupStats.totals.assertions.failedButOk );
+        m_xml.endElement();
+    }
+
+    void XmlReporter::testRunEnded( TestRunStats const& testRunStats ) {
+        StreamingReporterBase::testRunEnded( testRunStats );
+        m_xml.scopedElement( "OverallResults" )
+            .writeAttribute( "successes", testRunStats.totals.assertions.passed )
+            .writeAttribute( "failures", testRunStats.totals.assertions.failed )
+            .writeAttribute( "expectedFailures", testRunStats.totals.assertions.failedButOk );
+        m_xml.endElement();
+    }
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    void XmlReporter::benchmarkPreparing(std::string const& name) {
+        m_xml.startElement("BenchmarkResults")
+            .writeAttribute("name", name);
+    }
+
+    void XmlReporter::benchmarkStarting(BenchmarkInfo const &info) {
+        m_xml.writeAttribute("samples", info.samples)
+            .writeAttribute("resamples", info.resamples)
+            .writeAttribute("iterations", info.iterations)
+            .writeAttribute("clockResolution", info.clockResolution)
+            .writeAttribute("estimatedDuration", info.estimatedDuration)
+            .writeComment("All values in nano seconds");
+    }
+
+    void XmlReporter::benchmarkEnded(BenchmarkStats<> const& benchmarkStats) {
+        m_xml.startElement("mean")
+            .writeAttribute("value", benchmarkStats.mean.point.count())
+            .writeAttribute("lowerBound", benchmarkStats.mean.lower_bound.count())
+            .writeAttribute("upperBound", benchmarkStats.mean.upper_bound.count())
+            .writeAttribute("ci", benchmarkStats.mean.confidence_interval);
+        m_xml.endElement();
+        m_xml.startElement("standardDeviation")
+            .writeAttribute("value", benchmarkStats.standardDeviation.point.count())
+            .writeAttribute("lowerBound", benchmarkStats.standardDeviation.lower_bound.count())
+            .writeAttribute("upperBound", benchmarkStats.standardDeviation.upper_bound.count())
+            .writeAttribute("ci", benchmarkStats.standardDeviation.confidence_interval);
+        m_xml.endElement();
+        m_xml.startElement("outliers")
+            .writeAttribute("variance", benchmarkStats.outlierVariance)
+            .writeAttribute("lowMild", benchmarkStats.outliers.low_mild)
+            .writeAttribute("lowSevere", benchmarkStats.outliers.low_severe)
+            .writeAttribute("highMild", benchmarkStats.outliers.high_mild)
+            .writeAttribute("highSevere", benchmarkStats.outliers.high_severe);
+        m_xml.endElement();
+        m_xml.endElement();
+    }
+
+    void XmlReporter::benchmarkFailed(std::string const &error) {
+        m_xml.scopedElement("failed").
+            writeAttribute("message", error);
+        m_xml.endElement();
+    }
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    CATCH_REGISTER_REPORTER( "xml", XmlReporter )
+
+} // end namespace Catch
+
+#if defined(_MSC_VER)
+#pragma warning(pop)
+#endif
+// end catch_reporter_xml.cpp
+
+namespace Catch {
+    LeakDetector leakDetector;
+}
+
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// end catch_impl.hpp
+#endif
+
+#ifdef CATCH_CONFIG_MAIN
+// start catch_default_main.hpp
+
+#ifndef __OBJC__
+
+#if defined(CATCH_CONFIG_WCHAR) && defined(CATCH_PLATFORM_WINDOWS) && defined(_UNICODE) && !defined(DO_NOT_USE_WMAIN)
+// Standard C/C++ Win32 Unicode wmain entry point
+extern "C" int wmain (int argc, wchar_t * argv[], wchar_t * []) {
+#else
+// Standard C/C++ main entry point
+int main (int argc, char * argv[]) {
+#endif
+
+    return Catch::Session().run( argc, argv );
+}
+
+#else // __OBJC__
+
+// Objective-C entry point
+int main (int argc, char * const argv[]) {
+#if !CATCH_ARC_ENABLED
+    NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
+#endif
+
+    Catch::registerTestMethods();
+    int result = Catch::Session().run( argc, (char**)argv );
+
+#if !CATCH_ARC_ENABLED
+    [pool drain];
+#endif
+
+    return result;
+}
+
+#endif // __OBJC__
+
+// end catch_default_main.hpp
+#endif
+
+#if !defined(CATCH_CONFIG_IMPL_ONLY)
+
+#ifdef CLARA_CONFIG_MAIN_NOT_DEFINED
+#  undef CLARA_CONFIG_MAIN
+#endif
+
+#if !defined(CATCH_CONFIG_DISABLE)
+//////
+// If this config identifier is defined then all CATCH macros are prefixed with CATCH_
+#ifdef CATCH_CONFIG_PREFIX_ALL
+
+#define CATCH_REQUIRE( ... ) INTERNAL_CATCH_TEST( "CATCH_REQUIRE", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define CATCH_REQUIRE_FALSE( ... ) INTERNAL_CATCH_TEST( "CATCH_REQUIRE_FALSE", Catch::ResultDisposition::Normal | Catch::ResultDisposition::FalseTest, __VA_ARGS__ )
+
+#define CATCH_REQUIRE_THROWS( ... ) INTERNAL_CATCH_THROWS( "CATCH_REQUIRE_THROWS", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define CATCH_REQUIRE_THROWS_AS( expr, exceptionType ) INTERNAL_CATCH_THROWS_AS( "CATCH_REQUIRE_THROWS_AS", exceptionType, Catch::ResultDisposition::Normal, expr )
+#define CATCH_REQUIRE_THROWS_WITH( expr, matcher ) INTERNAL_CATCH_THROWS_STR_MATCHES( "CATCH_REQUIRE_THROWS_WITH", Catch::ResultDisposition::Normal, matcher, expr )
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_REQUIRE_THROWS_MATCHES( expr, exceptionType, matcher ) INTERNAL_CATCH_THROWS_MATCHES( "CATCH_REQUIRE_THROWS_MATCHES", exceptionType, Catch::ResultDisposition::Normal, matcher, expr )
+#endif// CATCH_CONFIG_DISABLE_MATCHERS
+#define CATCH_REQUIRE_NOTHROW( ... ) INTERNAL_CATCH_NO_THROW( "CATCH_REQUIRE_NOTHROW", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+
+#define CATCH_CHECK( ... ) INTERNAL_CATCH_TEST( "CATCH_CHECK", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_CHECK_FALSE( ... ) INTERNAL_CATCH_TEST( "CATCH_CHECK_FALSE", Catch::ResultDisposition::ContinueOnFailure | Catch::ResultDisposition::FalseTest, __VA_ARGS__ )
+#define CATCH_CHECKED_IF( ... ) INTERNAL_CATCH_IF( "CATCH_CHECKED_IF", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_CHECKED_ELSE( ... ) INTERNAL_CATCH_ELSE( "CATCH_CHECKED_ELSE", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_CHECK_NOFAIL( ... ) INTERNAL_CATCH_TEST( "CATCH_CHECK_NOFAIL", Catch::ResultDisposition::ContinueOnFailure | Catch::ResultDisposition::SuppressFail, __VA_ARGS__ )
+
+#define CATCH_CHECK_THROWS( ... )  INTERNAL_CATCH_THROWS( "CATCH_CHECK_THROWS", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_CHECK_THROWS_AS( expr, exceptionType ) INTERNAL_CATCH_THROWS_AS( "CATCH_CHECK_THROWS_AS", exceptionType, Catch::ResultDisposition::ContinueOnFailure, expr )
+#define CATCH_CHECK_THROWS_WITH( expr, matcher ) INTERNAL_CATCH_THROWS_STR_MATCHES( "CATCH_CHECK_THROWS_WITH", Catch::ResultDisposition::ContinueOnFailure, matcher, expr )
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_CHECK_THROWS_MATCHES( expr, exceptionType, matcher ) INTERNAL_CATCH_THROWS_MATCHES( "CATCH_CHECK_THROWS_MATCHES", exceptionType, Catch::ResultDisposition::ContinueOnFailure, matcher, expr )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define CATCH_CHECK_NOTHROW( ... ) INTERNAL_CATCH_NO_THROW( "CATCH_CHECK_NOTHROW", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_CHECK_THAT( arg, matcher ) INTERNAL_CHECK_THAT( "CATCH_CHECK_THAT", matcher, Catch::ResultDisposition::ContinueOnFailure, arg )
+
+#define CATCH_REQUIRE_THAT( arg, matcher ) INTERNAL_CHECK_THAT( "CATCH_REQUIRE_THAT", matcher, Catch::ResultDisposition::Normal, arg )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+#define CATCH_INFO( msg ) INTERNAL_CATCH_INFO( "CATCH_INFO", msg )
+#define CATCH_UNSCOPED_INFO( msg ) INTERNAL_CATCH_UNSCOPED_INFO( "CATCH_UNSCOPED_INFO", msg )
+#define CATCH_WARN( msg ) INTERNAL_CATCH_MSG( "CATCH_WARN", Catch::ResultWas::Warning, Catch::ResultDisposition::ContinueOnFailure, msg )
+#define CATCH_CAPTURE( ... ) INTERNAL_CATCH_CAPTURE( INTERNAL_CATCH_UNIQUE_NAME(capturer), "CATCH_CAPTURE",__VA_ARGS__ )
+
+#define CATCH_TEST_CASE( ... ) INTERNAL_CATCH_TESTCASE( __VA_ARGS__ )
+#define CATCH_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_METHOD_AS_TEST_CASE( method, ... ) INTERNAL_CATCH_METHOD_AS_TEST_CASE( method, __VA_ARGS__ )
+#define CATCH_REGISTER_TEST_CASE( Function, ... ) INTERNAL_CATCH_REGISTER_TESTCASE( Function, __VA_ARGS__ )
+#define CATCH_SECTION( ... ) INTERNAL_CATCH_SECTION( __VA_ARGS__ )
+#define CATCH_DYNAMIC_SECTION( ... ) INTERNAL_CATCH_DYNAMIC_SECTION( __VA_ARGS__ )
+#define CATCH_FAIL( ... ) INTERNAL_CATCH_MSG( "CATCH_FAIL", Catch::ResultWas::ExplicitFailure, Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define CATCH_FAIL_CHECK( ... ) INTERNAL_CATCH_MSG( "CATCH_FAIL_CHECK", Catch::ResultWas::ExplicitFailure, Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_SUCCEED( ... ) INTERNAL_CATCH_MSG( "CATCH_SUCCEED", Catch::ResultWas::Ok, Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+
+#define CATCH_ANON_TEST_CASE() INTERNAL_CATCH_TESTCASE()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define CATCH_TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG( __VA_ARGS__ )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ )
+#else
+#define CATCH_TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG( __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE( __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ ) )
+#endif
+
+#if !defined(CATCH_CONFIG_RUNTIME_STATIC_REQUIRE)
+#define CATCH_STATIC_REQUIRE( ... )       static_assert(   __VA_ARGS__ ,      #__VA_ARGS__ );     CATCH_SUCCEED( #__VA_ARGS__ )
+#define CATCH_STATIC_REQUIRE_FALSE( ... ) static_assert( !(__VA_ARGS__), "!(" #__VA_ARGS__ ")" ); CATCH_SUCCEED( #__VA_ARGS__ )
+#else
+#define CATCH_STATIC_REQUIRE( ... )       CATCH_REQUIRE( __VA_ARGS__ )
+#define CATCH_STATIC_REQUIRE_FALSE( ... ) CATCH_REQUIRE_FALSE( __VA_ARGS__ )
+#endif
+
+// "BDD-style" convenience wrappers
+#define CATCH_SCENARIO( ... ) CATCH_TEST_CASE( "Scenario: " __VA_ARGS__ )
+#define CATCH_SCENARIO_METHOD( className, ... ) INTERNAL_CATCH_TEST_CASE_METHOD( className, "Scenario: " __VA_ARGS__ )
+#define CATCH_GIVEN( desc )     INTERNAL_CATCH_DYNAMIC_SECTION( "    Given: " << desc )
+#define CATCH_AND_GIVEN( desc ) INTERNAL_CATCH_DYNAMIC_SECTION( "And given: " << desc )
+#define CATCH_WHEN( desc )      INTERNAL_CATCH_DYNAMIC_SECTION( "     When: " << desc )
+#define CATCH_AND_WHEN( desc )  INTERNAL_CATCH_DYNAMIC_SECTION( " And when: " << desc )
+#define CATCH_THEN( desc )      INTERNAL_CATCH_DYNAMIC_SECTION( "     Then: " << desc )
+#define CATCH_AND_THEN( desc )  INTERNAL_CATCH_DYNAMIC_SECTION( "      And: " << desc )
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+#define CATCH_BENCHMARK(...) \
+    INTERNAL_CATCH_BENCHMARK(INTERNAL_CATCH_UNIQUE_NAME(____C_A_T_C_H____B_E_N_C_H____), INTERNAL_CATCH_GET_1_ARG(__VA_ARGS__,,), INTERNAL_CATCH_GET_2_ARG(__VA_ARGS__,,))
+#define CATCH_BENCHMARK_ADVANCED(name) \
+    INTERNAL_CATCH_BENCHMARK_ADVANCED(INTERNAL_CATCH_UNIQUE_NAME(____C_A_T_C_H____B_E_N_C_H____), name)
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+// If CATCH_CONFIG_PREFIX_ALL is not defined then the CATCH_ prefix is not required
+#else
+
+#define REQUIRE( ... ) INTERNAL_CATCH_TEST( "REQUIRE", Catch::ResultDisposition::Normal, __VA_ARGS__  )
+#define REQUIRE_FALSE( ... ) INTERNAL_CATCH_TEST( "REQUIRE_FALSE", Catch::ResultDisposition::Normal | Catch::ResultDisposition::FalseTest, __VA_ARGS__ )
+
+#define REQUIRE_THROWS( ... ) INTERNAL_CATCH_THROWS( "REQUIRE_THROWS", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define REQUIRE_THROWS_AS( expr, exceptionType ) INTERNAL_CATCH_THROWS_AS( "REQUIRE_THROWS_AS", exceptionType, Catch::ResultDisposition::Normal, expr )
+#define REQUIRE_THROWS_WITH( expr, matcher ) INTERNAL_CATCH_THROWS_STR_MATCHES( "REQUIRE_THROWS_WITH", Catch::ResultDisposition::Normal, matcher, expr )
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define REQUIRE_THROWS_MATCHES( expr, exceptionType, matcher ) INTERNAL_CATCH_THROWS_MATCHES( "REQUIRE_THROWS_MATCHES", exceptionType, Catch::ResultDisposition::Normal, matcher, expr )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define REQUIRE_NOTHROW( ... ) INTERNAL_CATCH_NO_THROW( "REQUIRE_NOTHROW", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+
+#define CHECK( ... ) INTERNAL_CATCH_TEST( "CHECK", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CHECK_FALSE( ... ) INTERNAL_CATCH_TEST( "CHECK_FALSE", Catch::ResultDisposition::ContinueOnFailure | Catch::ResultDisposition::FalseTest, __VA_ARGS__ )
+#define CHECKED_IF( ... ) INTERNAL_CATCH_IF( "CHECKED_IF", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CHECKED_ELSE( ... ) INTERNAL_CATCH_ELSE( "CHECKED_ELSE", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CHECK_NOFAIL( ... ) INTERNAL_CATCH_TEST( "CHECK_NOFAIL", Catch::ResultDisposition::ContinueOnFailure | Catch::ResultDisposition::SuppressFail, __VA_ARGS__ )
+
+#define CHECK_THROWS( ... )  INTERNAL_CATCH_THROWS( "CHECK_THROWS", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CHECK_THROWS_AS( expr, exceptionType ) INTERNAL_CATCH_THROWS_AS( "CHECK_THROWS_AS", exceptionType, Catch::ResultDisposition::ContinueOnFailure, expr )
+#define CHECK_THROWS_WITH( expr, matcher ) INTERNAL_CATCH_THROWS_STR_MATCHES( "CHECK_THROWS_WITH", Catch::ResultDisposition::ContinueOnFailure, matcher, expr )
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CHECK_THROWS_MATCHES( expr, exceptionType, matcher ) INTERNAL_CATCH_THROWS_MATCHES( "CHECK_THROWS_MATCHES", exceptionType, Catch::ResultDisposition::ContinueOnFailure, matcher, expr )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define CHECK_NOTHROW( ... ) INTERNAL_CATCH_NO_THROW( "CHECK_NOTHROW", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CHECK_THAT( arg, matcher ) INTERNAL_CHECK_THAT( "CHECK_THAT", matcher, Catch::ResultDisposition::ContinueOnFailure, arg )
+
+#define REQUIRE_THAT( arg, matcher ) INTERNAL_CHECK_THAT( "REQUIRE_THAT", matcher, Catch::ResultDisposition::Normal, arg )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+#define INFO( msg ) INTERNAL_CATCH_INFO( "INFO", msg )
+#define UNSCOPED_INFO( msg ) INTERNAL_CATCH_UNSCOPED_INFO( "UNSCOPED_INFO", msg )
+#define WARN( msg ) INTERNAL_CATCH_MSG( "WARN", Catch::ResultWas::Warning, Catch::ResultDisposition::ContinueOnFailure, msg )
+#define CAPTURE( ... ) INTERNAL_CATCH_CAPTURE( INTERNAL_CATCH_UNIQUE_NAME(capturer), "CAPTURE",__VA_ARGS__ )
+
+#define TEST_CASE( ... ) INTERNAL_CATCH_TESTCASE( __VA_ARGS__ )
+#define TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define METHOD_AS_TEST_CASE( method, ... ) INTERNAL_CATCH_METHOD_AS_TEST_CASE( method, __VA_ARGS__ )
+#define REGISTER_TEST_CASE( Function, ... ) INTERNAL_CATCH_REGISTER_TESTCASE( Function, __VA_ARGS__ )
+#define SECTION( ... ) INTERNAL_CATCH_SECTION( __VA_ARGS__ )
+#define DYNAMIC_SECTION( ... ) INTERNAL_CATCH_DYNAMIC_SECTION( __VA_ARGS__ )
+#define FAIL( ... ) INTERNAL_CATCH_MSG( "FAIL", Catch::ResultWas::ExplicitFailure, Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define FAIL_CHECK( ... ) INTERNAL_CATCH_MSG( "FAIL_CHECK", Catch::ResultWas::ExplicitFailure, Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define SUCCEED( ... ) INTERNAL_CATCH_MSG( "SUCCEED", Catch::ResultWas::Ok, Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define ANON_TEST_CASE() INTERNAL_CATCH_TESTCASE()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG( __VA_ARGS__ )
+#define TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ )
+#define TEMPLATE_LIST_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE(__VA_ARGS__)
+#define TEMPLATE_LIST_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#else
+#define TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ ) )
+#define TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG( __VA_ARGS__ ) )
+#define TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#define TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE( __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ ) )
+#define TEMPLATE_LIST_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE( __VA_ARGS__ ) )
+#define TEMPLATE_LIST_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#endif
+
+#if !defined(CATCH_CONFIG_RUNTIME_STATIC_REQUIRE)
+#define STATIC_REQUIRE( ... )       static_assert(   __VA_ARGS__,  #__VA_ARGS__ ); SUCCEED( #__VA_ARGS__ )
+#define STATIC_REQUIRE_FALSE( ... ) static_assert( !(__VA_ARGS__), "!(" #__VA_ARGS__ ")" ); SUCCEED( "!(" #__VA_ARGS__ ")" )
+#else
+#define STATIC_REQUIRE( ... )       REQUIRE( __VA_ARGS__ )
+#define STATIC_REQUIRE_FALSE( ... ) REQUIRE_FALSE( __VA_ARGS__ )
+#endif
+
+#endif
+
+#define CATCH_TRANSLATE_EXCEPTION( signature ) INTERNAL_CATCH_TRANSLATE_EXCEPTION( signature )
+
+// "BDD-style" convenience wrappers
+#define SCENARIO( ... ) TEST_CASE( "Scenario: " __VA_ARGS__ )
+#define SCENARIO_METHOD( className, ... ) INTERNAL_CATCH_TEST_CASE_METHOD( className, "Scenario: " __VA_ARGS__ )
+
+#define GIVEN( desc )     INTERNAL_CATCH_DYNAMIC_SECTION( "    Given: " << desc )
+#define AND_GIVEN( desc ) INTERNAL_CATCH_DYNAMIC_SECTION( "And given: " << desc )
+#define WHEN( desc )      INTERNAL_CATCH_DYNAMIC_SECTION( "     When: " << desc )
+#define AND_WHEN( desc )  INTERNAL_CATCH_DYNAMIC_SECTION( " And when: " << desc )
+#define THEN( desc )      INTERNAL_CATCH_DYNAMIC_SECTION( "     Then: " << desc )
+#define AND_THEN( desc )  INTERNAL_CATCH_DYNAMIC_SECTION( "      And: " << desc )
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+#define BENCHMARK(...) \
+    INTERNAL_CATCH_BENCHMARK(INTERNAL_CATCH_UNIQUE_NAME(____C_A_T_C_H____B_E_N_C_H____), INTERNAL_CATCH_GET_1_ARG(__VA_ARGS__,,), INTERNAL_CATCH_GET_2_ARG(__VA_ARGS__,,))
+#define BENCHMARK_ADVANCED(name) \
+    INTERNAL_CATCH_BENCHMARK_ADVANCED(INTERNAL_CATCH_UNIQUE_NAME(____C_A_T_C_H____B_E_N_C_H____), name)
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+using Catch::Detail::Approx;
+
+#else // CATCH_CONFIG_DISABLE
+
+//////
+// If this config identifier is defined then all CATCH macros are prefixed with CATCH_
+#ifdef CATCH_CONFIG_PREFIX_ALL
+
+#define CATCH_REQUIRE( ... )        (void)(0)
+#define CATCH_REQUIRE_FALSE( ... )  (void)(0)
+
+#define CATCH_REQUIRE_THROWS( ... ) (void)(0)
+#define CATCH_REQUIRE_THROWS_AS( expr, exceptionType ) (void)(0)
+#define CATCH_REQUIRE_THROWS_WITH( expr, matcher )     (void)(0)
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_REQUIRE_THROWS_MATCHES( expr, exceptionType, matcher ) (void)(0)
+#endif// CATCH_CONFIG_DISABLE_MATCHERS
+#define CATCH_REQUIRE_NOTHROW( ... ) (void)(0)
+
+#define CATCH_CHECK( ... )         (void)(0)
+#define CATCH_CHECK_FALSE( ... )   (void)(0)
+#define CATCH_CHECKED_IF( ... )    if (__VA_ARGS__)
+#define CATCH_CHECKED_ELSE( ... )  if (!(__VA_ARGS__))
+#define CATCH_CHECK_NOFAIL( ... )  (void)(0)
+
+#define CATCH_CHECK_THROWS( ... )  (void)(0)
+#define CATCH_CHECK_THROWS_AS( expr, exceptionType ) (void)(0)
+#define CATCH_CHECK_THROWS_WITH( expr, matcher )     (void)(0)
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_CHECK_THROWS_MATCHES( expr, exceptionType, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define CATCH_CHECK_NOTHROW( ... ) (void)(0)
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_CHECK_THAT( arg, matcher )   (void)(0)
+
+#define CATCH_REQUIRE_THAT( arg, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+#define CATCH_INFO( msg )          (void)(0)
+#define CATCH_UNSCOPED_INFO( msg ) (void)(0)
+#define CATCH_WARN( msg )          (void)(0)
+#define CATCH_CAPTURE( msg )       (void)(0)
+
+#define CATCH_TEST_CASE( ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ))
+#define CATCH_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ))
+#define CATCH_METHOD_AS_TEST_CASE( method, ... )
+#define CATCH_REGISTER_TEST_CASE( Function, ... ) (void)(0)
+#define CATCH_SECTION( ... )
+#define CATCH_DYNAMIC_SECTION( ... )
+#define CATCH_FAIL( ... ) (void)(0)
+#define CATCH_FAIL_CHECK( ... ) (void)(0)
+#define CATCH_SUCCEED( ... ) (void)(0)
+
+#define CATCH_ANON_TEST_CASE() INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ))
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define CATCH_TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(__VA_ARGS__)
+#define CATCH_TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(__VA_ARGS__)
+#define CATCH_TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION(className, __VA_ARGS__)
+#define CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION(className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE( ... ) CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#else
+#define CATCH_TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(__VA_ARGS__) )
+#define CATCH_TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(__VA_ARGS__) )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION(className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION(className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE( ... ) CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#endif
+
+// "BDD-style" convenience wrappers
+#define CATCH_SCENARIO( ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ))
+#define CATCH_SCENARIO_METHOD( className, ... ) INTERNAL_CATCH_TESTCASE_METHOD_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ), className )
+#define CATCH_GIVEN( desc )
+#define CATCH_AND_GIVEN( desc )
+#define CATCH_WHEN( desc )
+#define CATCH_AND_WHEN( desc )
+#define CATCH_THEN( desc )
+#define CATCH_AND_THEN( desc )
+
+#define CATCH_STATIC_REQUIRE( ... )       (void)(0)
+#define CATCH_STATIC_REQUIRE_FALSE( ... ) (void)(0)
+
+// If CATCH_CONFIG_PREFIX_ALL is not defined then the CATCH_ prefix is not required
+#else
+
+#define REQUIRE( ... )       (void)(0)
+#define REQUIRE_FALSE( ... ) (void)(0)
+
+#define REQUIRE_THROWS( ... ) (void)(0)
+#define REQUIRE_THROWS_AS( expr, exceptionType ) (void)(0)
+#define REQUIRE_THROWS_WITH( expr, matcher ) (void)(0)
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define REQUIRE_THROWS_MATCHES( expr, exceptionType, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define REQUIRE_NOTHROW( ... ) (void)(0)
+
+#define CHECK( ... ) (void)(0)
+#define CHECK_FALSE( ... ) (void)(0)
+#define CHECKED_IF( ... ) if (__VA_ARGS__)
+#define CHECKED_ELSE( ... ) if (!(__VA_ARGS__))
+#define CHECK_NOFAIL( ... ) (void)(0)
+
+#define CHECK_THROWS( ... )  (void)(0)
+#define CHECK_THROWS_AS( expr, exceptionType ) (void)(0)
+#define CHECK_THROWS_WITH( expr, matcher ) (void)(0)
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CHECK_THROWS_MATCHES( expr, exceptionType, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define CHECK_NOTHROW( ... ) (void)(0)
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CHECK_THAT( arg, matcher ) (void)(0)
+
+#define REQUIRE_THAT( arg, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+#define INFO( msg ) (void)(0)
+#define UNSCOPED_INFO( msg ) (void)(0)
+#define WARN( msg ) (void)(0)
+#define CAPTURE( msg ) (void)(0)
+
+#define TEST_CASE( ... )  INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ))
+#define TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ))
+#define METHOD_AS_TEST_CASE( method, ... )
+#define REGISTER_TEST_CASE( Function, ... ) (void)(0)
+#define SECTION( ... )
+#define DYNAMIC_SECTION( ... )
+#define FAIL( ... ) (void)(0)
+#define FAIL_CHECK( ... ) (void)(0)
+#define SUCCEED( ... ) (void)(0)
+#define ANON_TEST_CASE() INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ))
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(__VA_ARGS__)
+#define TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(__VA_ARGS__)
+#define TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION(className, __VA_ARGS__)
+#define TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION(className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE( ... ) TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#else
+#define TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(__VA_ARGS__) )
+#define TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(__VA_ARGS__) )
+#define TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION(className, __VA_ARGS__ ) )
+#define TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION(className, __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE( ... ) TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#endif
+
+#define STATIC_REQUIRE( ... )       (void)(0)
+#define STATIC_REQUIRE_FALSE( ... ) (void)(0)
+
+#endif
+
+#define CATCH_TRANSLATE_EXCEPTION( signature ) INTERNAL_CATCH_TRANSLATE_EXCEPTION_NO_REG( INTERNAL_CATCH_UNIQUE_NAME( catch_internal_ExceptionTranslator ), signature )
+
+// "BDD-style" convenience wrappers
+#define SCENARIO( ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ) )
+#define SCENARIO_METHOD( className, ... ) INTERNAL_CATCH_TESTCASE_METHOD_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( ____C_A_T_C_H____T_E_S_T____ ), className )
+
+#define GIVEN( desc )
+#define AND_GIVEN( desc )
+#define WHEN( desc )
+#define AND_WHEN( desc )
+#define THEN( desc )
+#define AND_THEN( desc )
+
+using Catch::Detail::Approx;
+
+#endif
+
+#endif // ! CATCH_CONFIG_IMPL_ONLY
+
+// start catch_reenable_warnings.h
+
+
+#ifdef __clang__
+#    ifdef __ICC // icpc defines the __clang__ macro
+#        pragma warning(pop)
+#    else
+#        pragma clang diagnostic pop
+#    endif
+#elif defined __GNUC__
+#    pragma GCC diagnostic pop
+#endif
+
+// end catch_reenable_warnings.h
+// end catch.hpp
+#endif // TWOBLUECUBES_SINGLE_INCLUDE_CATCH_HPP_INCLUDED
+

ADDED   3rd_party/catch/wscript
Index: 3rd_party/catch/wscript
==================================================================
--- 3rd_party/catch/wscript
+++ 3rd_party/catch/wscript
@@ -0,0 +1,7 @@
+def build( bld ):
+        bld(
+                target = 'catch',
+                includes = './',
+                export_includes = './'
+        )
+

Index: 3rd_party/eigen/.hg_archival.txt
==================================================================
--- 3rd_party/eigen/.hg_archival.txt
+++ 3rd_party/eigen/.hg_archival.txt
@@ -1,4 +1,4 @@
 repo: 8a21fd850624c931e448cbcfb38168cb2717c790
-node: 10219c95fe653d4962aa9db4946f6fbea96dd740
-branch: 3.2
-tag: 3.2.4
+node: 5a0156e40feb7c4136680b493c6e433d91a6f355
+branch: 3.3
+tag: 3.3.4

Index: 3rd_party/eigen/.hgeol
==================================================================
--- 3rd_party/eigen/.hgeol
+++ 3rd_party/eigen/.hgeol
@@ -1,8 +1,11 @@
 [patterns]
+*.sh = LF
+*.MINPACK = CRLF
 scripts/*.in = LF
 debug/msvc/*.dat = CRLF
+debug/msvc/*.natvis = CRLF
 unsupported/test/mpreal/*.* = CRLF
 ** = native
 
 [repository]
 native = LF

Index: 3rd_party/eigen/.hgignore
==================================================================
--- 3rd_party/eigen/.hgignore
+++ 3rd_party/eigen/.hgignore
@@ -28,5 +28,7 @@
 *.rej
 log
 patch
 a
 a.*
+lapack/testing
+lapack/reference

Index: 3rd_party/eigen/.hgtags
==================================================================
--- 3rd_party/eigen/.hgtags
+++ 3rd_party/eigen/.hgtags
@@ -19,11 +19,15 @@
 304c88ca3affc16dd0b008b1104873986edd77af 3.1.0-alpha2
 920fc730b5930daae0a6dbe296d60ce2e3808215 3.1.0-beta1
 8383e883ebcc6f14695ff0b5e20bb631abab43fb 3.1.0-rc1
 bf4cb8c934fa3a79f45f1e629610f0225e93e493 3.1.0-rc2
 da195914abcc1d739027cbee7c52077aab30b336 3.2-beta1
-4b687cad1d23066f66863f4f87298447298443df 3.2-rc1
-1eeda7b1258bcd306018c0738e2b6a8543661141 3.2-rc2
-ffa86ffb557094721ca71dcea6aed2651b9fd610 3.2.0
-6b38706d90a9fe182e66ab88477b3dbde34b9f66 3.2.1
-1306d75b4a21891e59ff9bd96678882cf831e39f 3.2.2
-36fd1ba04c120cfdd90f3e4cede47f43b21d19ad 3.2.3
+a8e0d153fc5e239ef8b06e3665f1f9e8cb8d49c8 before-evaluators
+09a8e21866106b49c5dec1d6d543e5794e82efa0 3.3-alpha1
+ce5a455b34c0a0ac3545a1497cb4a16c38ed90e8 3.3-beta1
+69d418c0699907bcd0bf9e0b3ba0a112ed091d85 3.3-beta2
+bef509908b9da05d0d07ffc0da105e2c8c6d3996 3.3-rc1
+04ab5fa4b241754afcf631117572276444c67239 3.3-rc2
+26667be4f70baf4f0d39e96f330714c87b399090 3.3.0
+f562a193118d4f40514e2f4a0ace6e974926ef06 3.3.1
+da9b4e14c2550e0d11078a3c39e6d56eba9905df 3.3.2
+67e894c6cd8f5f1f604b27d37ed47fdf012674ff 3.3.3

Index: 3rd_party/eigen/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/CMakeLists.txt
+++ 3rd_party/eigen/CMakeLists.txt
@@ -1,15 +1,20 @@
-project(Eigen)
+project(Eigen3)
 
-cmake_minimum_required(VERSION 2.8.2)
+cmake_minimum_required(VERSION 2.8.5)
 
 # guard against in-source builds
 
 if(${CMAKE_SOURCE_DIR} STREQUAL ${CMAKE_BINARY_DIR})
   message(FATAL_ERROR "In-source builds not allowed. Please make a new directory (called a build directory) and run CMake from there. You may need to remove CMakeCache.txt. ")
 endif()
 
+# Alias Eigen_*_DIR to Eigen3_*_DIR:
+
+set(Eigen_SOURCE_DIR ${Eigen3_SOURCE_DIR})
+set(Eigen_BINARY_DIR ${Eigen3_BINARY_DIR})
+
 # guard against bad build-type strings
 
 if (NOT CMAKE_BUILD_TYPE)
   set(CMAKE_BUILD_TYPE "Release")
 endif()
@@ -53,10 +58,11 @@
   set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER}")
 endif(EIGEN_HG_CHANGESET)
 
 
 include(CheckCXXCompilerFlag)
+include(GNUInstallDirs)
 
 set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
 
 #############################################################################
 # find how to link to the standard libraries                                #
@@ -90,13 +96,15 @@
 else()
   message(STATUS "Standard libraries to link to explicitly: none")
 endif()
 
 option(EIGEN_BUILD_BTL "Build benchmark suite" OFF)
-if(NOT WIN32)
+
+# Disable pkgconfig only for native Windows builds
+if(NOT WIN32 OR NOT CMAKE_HOST_SYSTEM_NAME MATCHES Windows)
   option(EIGEN_BUILD_PKGCONFIG "Build pkg-config .pc file for Eigen" ON)
-endif(NOT WIN32)
+endif()
 
 set(CMAKE_INCLUDE_CURRENT_DIR ON)
 
 option(EIGEN_SPLIT_LARGE_TESTS "Split large tests into smaller executables" ON)
 
@@ -106,31 +114,27 @@
 endif()
 
 set(EIGEN_TEST_MAX_SIZE "320" CACHE STRING "Maximal matrix/vector size, default is 320")
 
 macro(ei_add_cxx_compiler_flag FLAG)
-  string(REGEX REPLACE "-" "" SFLAG ${FLAG})
+  string(REGEX REPLACE "-" "" SFLAG1 ${FLAG})
+  string(REGEX REPLACE "\\+" "p" SFLAG ${SFLAG1})
   check_cxx_compiler_flag(${FLAG} COMPILER_SUPPORT_${SFLAG})
   if(COMPILER_SUPPORT_${SFLAG})
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${FLAG}")
   endif()
 endmacro(ei_add_cxx_compiler_flag)
 
 if(NOT MSVC)
   # We assume that other compilers are partly compatible with GNUCC
-  
-  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fexceptions")
-  set(CMAKE_CXX_FLAGS_DEBUG "-g3")
-  set(CMAKE_CXX_FLAGS_RELEASE "-g0 -O2")
-  
-  # clang outputs some warnings for unknwon flags that are not caught by check_cxx_compiler_flag
+
+  # clang outputs some warnings for unknown flags that are not caught by check_cxx_compiler_flag
   # adding -Werror turns such warnings into errors
   check_cxx_compiler_flag("-Werror" COMPILER_SUPPORT_WERROR)
   if(COMPILER_SUPPORT_WERROR)
     set(CMAKE_REQUIRED_FLAGS "-Werror")
   endif()
-  
   ei_add_cxx_compiler_flag("-pedantic")
   ei_add_cxx_compiler_flag("-Wall")
   ei_add_cxx_compiler_flag("-Wextra")
   #ei_add_cxx_compiler_flag("-Weverything")              # clang
   
@@ -140,20 +144,33 @@
   ei_add_cxx_compiler_flag("-Wnon-virtual-dtor")
   ei_add_cxx_compiler_flag("-Wunused-local-typedefs")
   ei_add_cxx_compiler_flag("-Wpointer-arith")
   ei_add_cxx_compiler_flag("-Wwrite-strings")
   ei_add_cxx_compiler_flag("-Wformat-security")
+  ei_add_cxx_compiler_flag("-Wshorten-64-to-32")
+  ei_add_cxx_compiler_flag("-Wlogical-op")
+  ei_add_cxx_compiler_flag("-Wenum-conversion")
+  ei_add_cxx_compiler_flag("-Wc++11-extensions")
+  ei_add_cxx_compiler_flag("-Wdouble-promotion")
+#  ei_add_cxx_compiler_flag("-Wconversion")
+  
+  # -Wshadow is insanely too strict with gcc, hopefully it will become usable with gcc 6
+  # if(NOT CMAKE_COMPILER_IS_GNUCXX OR (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER "5.0.0"))
+  if(NOT CMAKE_COMPILER_IS_GNUCXX)
+    ei_add_cxx_compiler_flag("-Wshadow")
+  endif()
   
   ei_add_cxx_compiler_flag("-Wno-psabi")
   ei_add_cxx_compiler_flag("-Wno-variadic-macros")
   ei_add_cxx_compiler_flag("-Wno-long-long")
   
   ei_add_cxx_compiler_flag("-fno-check-new")
   ei_add_cxx_compiler_flag("-fno-common")
   ei_add_cxx_compiler_flag("-fstrict-aliasing")
   ei_add_cxx_compiler_flag("-wd981")                    # disable ICC's "operands are evaluated in unspecified order" remark
-  ei_add_cxx_compiler_flag("-wd2304")                   # disbale ICC's "warning #2304: non-explicit constructor with single argument may cause implicit type conversion" produced by -Wnon-virtual-dtor
+  ei_add_cxx_compiler_flag("-wd2304")                   # disable ICC's "warning #2304: non-explicit constructor with single argument may cause implicit type conversion" produced by -Wnon-virtual-dtor
+  
   
   # The -ansi flag must be added last, otherwise it is also used as a linker flag by check_cxx_compiler_flag making it fails
   # Moreover we should not set both -strict-ansi and -ansi
   check_cxx_compiler_flag("-strict-ansi" COMPILER_SUPPORT_STRICTANSI)
   ei_add_cxx_compiler_flag("-Qunused-arguments")        # disable clang warning: argument unused during compilation: '-ansi'
@@ -161,10 +178,15 @@
   if(COMPILER_SUPPORT_STRICTANSI)
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -strict-ansi")
   else()
     ei_add_cxx_compiler_flag("-ansi")
   endif()
+
+  if(ANDROID_NDK)
+    ei_add_cxx_compiler_flag("-pie")
+    ei_add_cxx_compiler_flag("-fPIE")
+  endif()
   
   set(CMAKE_REQUIRED_FLAGS "")
 
   option(EIGEN_TEST_SSE2 "Enable/Disable SSE2 in tests/examples" OFF)
   if(EIGEN_TEST_SSE2)
@@ -193,22 +215,69 @@
   option(EIGEN_TEST_SSE4_2 "Enable/Disable SSE4.2 in tests/examples" OFF)
   if(EIGEN_TEST_SSE4_2)
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse4.2")
     message(STATUS "Enabling SSE4.2 in tests/examples")
   endif()
+
+  option(EIGEN_TEST_AVX "Enable/Disable AVX in tests/examples" OFF)
+  if(EIGEN_TEST_AVX)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx")
+    message(STATUS "Enabling AVX in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_FMA "Enable/Disable FMA in tests/examples" OFF)
+  if(EIGEN_TEST_FMA AND NOT EIGEN_TEST_NEON)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfma")
+    message(STATUS "Enabling FMA in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_AVX512 "Enable/Disable AVX512 in tests/examples" OFF)
+  if(EIGEN_TEST_AVX512)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx512f -fabi-version=6 -DEIGEN_ENABLE_AVX512")
+    message(STATUS "Enabling AVX512 in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_F16C "Enable/Disable F16C in tests/examples" OFF)
+  if(EIGEN_TEST_F16C)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mf16c")
+    message(STATUS "Enabling F16C in tests/examples")
+  endif()
 
   option(EIGEN_TEST_ALTIVEC "Enable/Disable AltiVec in tests/examples" OFF)
   if(EIGEN_TEST_ALTIVEC)
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -maltivec -mabi=altivec")
     message(STATUS "Enabling AltiVec in tests/examples")
   endif()
+
+  option(EIGEN_TEST_VSX "Enable/Disable VSX in tests/examples" OFF)
+  if(EIGEN_TEST_VSX)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -m64 -mvsx")
+    message(STATUS "Enabling VSX in tests/examples")
+  endif()
 
   option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF)
   if(EIGEN_TEST_NEON)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon -mcpu=cortex-a8")
+    if(EIGEN_TEST_FMA)
+      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon-vfpv4")
+    else()
+      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon")
+    endif()
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfloat-abi=hard")
+    message(STATUS "Enabling NEON in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_NEON64 "Enable/Disable Neon in tests/examples" OFF)
+  if(EIGEN_TEST_NEON64)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
     message(STATUS "Enabling NEON in tests/examples")
   endif()
+
+  option(EIGEN_TEST_ZVECTOR "Enable/Disable S390X(zEC13) ZVECTOR in tests/examples" OFF)
+  if(EIGEN_TEST_ZVECTOR)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -march=z13 -mzvector")
+    message(STATUS "Enabling S390X(zEC13) ZVECTOR in tests/examples")
+  endif()
 
   check_cxx_compiler_flag("-fopenmp" COMPILER_SUPPORT_OPENMP)
   if(COMPILER_SUPPORT_OPENMP)
     option(EIGEN_TEST_OPENMP "Enable/Disable OpenMP in tests/examples" OFF)
     if(EIGEN_TEST_OPENMP)
@@ -282,32 +351,45 @@
 if(EIGEN_TEST_NO_EXPLICIT_ALIGNMENT)
   add_definitions(-DEIGEN_DONT_ALIGN=1)
   message(STATUS "Disabling alignment in tests/examples")
 endif()
 
-option(EIGEN_TEST_C++0x "Enables all C++0x features." OFF)
+option(EIGEN_TEST_NO_EXCEPTIONS "Disables C++ exceptions" OFF)
+if(EIGEN_TEST_NO_EXCEPTIONS)
+  ei_add_cxx_compiler_flag("-fno-exceptions")
+  message(STATUS "Disabling exceptions in tests/examples")
+endif()
+
+option(EIGEN_TEST_CXX11 "Enable testing with C++11 and C++11 features (e.g. Tensor module)." OFF)
+
+set(EIGEN_CUDA_COMPUTE_ARCH 30 CACHE STRING "The CUDA compute architecture level to target when compiling CUDA code")
 
 include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
 
-# the user modifiable install path for header files
-set(EIGEN_INCLUDE_INSTALL_DIR ${EIGEN_INCLUDE_INSTALL_DIR} CACHE PATH "The directory where we install the header files (optional)")
-
-# set the internal install path for header files which depends on wether the user modifiable
-# EIGEN_INCLUDE_INSTALL_DIR has been set by the user or not.
+# Backward compatibility support for EIGEN_INCLUDE_INSTALL_DIR
 if(EIGEN_INCLUDE_INSTALL_DIR)
-  set(INCLUDE_INSTALL_DIR
-    ${EIGEN_INCLUDE_INSTALL_DIR}
-    CACHE INTERNAL
-    "The directory where we install the header files (internal)"
-  )
+  message(WARNING "EIGEN_INCLUDE_INSTALL_DIR is deprecated. Use INCLUDE_INSTALL_DIR instead.")
+endif()
+
+if(EIGEN_INCLUDE_INSTALL_DIR AND NOT INCLUDE_INSTALL_DIR)
+  set(INCLUDE_INSTALL_DIR ${EIGEN_INCLUDE_INSTALL_DIR}
+      CACHE PATH "The directory relative to CMAKE_PREFIX_PATH where Eigen header files are installed")
 else()
   set(INCLUDE_INSTALL_DIR
-    "${CMAKE_INSTALL_PREFIX}/include/eigen3"
-    CACHE INTERNAL
-    "The directory where we install the header files (internal)"
-  )
+      "${CMAKE_INSTALL_INCLUDEDIR}/eigen3"
+      CACHE PATH "The directory relative to CMAKE_PREFIX_PATH where Eigen header files are installed"
+      )
 endif()
+set(CMAKEPACKAGE_INSTALL_DIR
+    "${CMAKE_INSTALL_DATADIR}/eigen3/cmake"
+    CACHE PATH "The directory relative to CMAKE_PREFIX_PATH where Eigen3Config.cmake is installed"
+    )
+set(PKGCONFIG_INSTALL_DIR
+    "${CMAKE_INSTALL_DATADIR}/pkgconfig"
+    CACHE PATH "The directory relative to CMAKE_PREFIX_PATH where eigen3.pc is installed"
+    )
+
 
 # similar to set_target_properties but append the property instead of overwriting it
 macro(ei_add_target_property target prop value)
 
   get_target_property(previous ${target} ${prop})
@@ -322,27 +404,15 @@
   signature_of_eigen3_matrix_library
   DESTINATION ${INCLUDE_INSTALL_DIR} COMPONENT Devel
   )
 
 if(EIGEN_BUILD_PKGCONFIG)
-    SET(path_separator ":")
-    STRING(REPLACE ${path_separator} ";" pkg_config_libdir_search "$ENV{PKG_CONFIG_LIBDIR}")
-    message(STATUS "searching for 'pkgconfig' directory in PKG_CONFIG_LIBDIR ( $ENV{PKG_CONFIG_LIBDIR} ), ${CMAKE_INSTALL_PREFIX}/share, and ${CMAKE_INSTALL_PREFIX}/lib")
-    FIND_PATH(pkg_config_libdir pkgconfig ${pkg_config_libdir_search} ${CMAKE_INSTALL_PREFIX}/share ${CMAKE_INSTALL_PREFIX}/lib ${pkg_config_libdir_search})
-    if(pkg_config_libdir)
-        SET(pkg_config_install_dir ${pkg_config_libdir})
-        message(STATUS "found ${pkg_config_libdir}/pkgconfig" )
-    else(pkg_config_libdir)
-        SET(pkg_config_install_dir ${CMAKE_INSTALL_PREFIX}/share)
-        message(STATUS "pkgconfig not found; installing in ${pkg_config_install_dir}" )
-    endif(pkg_config_libdir)
-
-    configure_file(eigen3.pc.in eigen3.pc)
+    configure_file(eigen3.pc.in eigen3.pc @ONLY)
     install(FILES ${CMAKE_CURRENT_BINARY_DIR}/eigen3.pc
-        DESTINATION ${pkg_config_install_dir}/pkgconfig
+        DESTINATION ${PKGCONFIG_INSTALL_DIR}
         )
-endif(EIGEN_BUILD_PKGCONFIG)
+endif()
 
 add_subdirectory(Eigen)
 
 add_subdirectory(doc EXCLUDE_FROM_ALL)
 
@@ -363,10 +433,17 @@
   add_subdirectory(lapack)
 else()
   add_subdirectory(blas EXCLUDE_FROM_ALL)
   add_subdirectory(lapack EXCLUDE_FROM_ALL)
 endif()
+
+# add SYCL
+option(EIGEN_TEST_SYCL "Add Sycl support." OFF)
+if(EIGEN_TEST_SYCL)
+  set (CMAKE_MODULE_PATH "${CMAKE_ROOT}/Modules" "cmake/Modules/" "${CMAKE_MODULE_PATH}")
+  include(FindComputeCpp)
+endif()
 
 add_subdirectory(unsupported)
 
 add_subdirectory(demos EXCLUDE_FROM_ALL)
 
@@ -399,22 +476,121 @@
 if(cmake_generator_tolower MATCHES "makefile")
   message(STATUS "Some things you can do now:")
   message(STATUS "--------------+--------------------------------------------------------------")
   message(STATUS "Command       |   Description")
   message(STATUS "--------------+--------------------------------------------------------------")
-  message(STATUS "make install  | Install to ${CMAKE_INSTALL_PREFIX}. To change that:")
-  message(STATUS "              |     cmake . -DCMAKE_INSTALL_PREFIX=yourpath")
-  message(STATUS "              |   Eigen headers will then be installed to:")
-  message(STATUS "              |     ${INCLUDE_INSTALL_DIR}")
-  message(STATUS "              |   To install Eigen headers to a separate location, do:")
-  message(STATUS "              |     cmake . -DEIGEN_INCLUDE_INSTALL_DIR=yourpath")
+  message(STATUS "make install  | Install Eigen. Headers will be installed to:")
+  message(STATUS "              |     <CMAKE_INSTALL_PREFIX>/<INCLUDE_INSTALL_DIR>")
+  message(STATUS "              |   Using the following values:")
+  message(STATUS "              |     CMAKE_INSTALL_PREFIX: ${CMAKE_INSTALL_PREFIX}")
+  message(STATUS "              |     INCLUDE_INSTALL_DIR:  ${INCLUDE_INSTALL_DIR}")
+  message(STATUS "              |   Change the install location of Eigen headers using:")
+  message(STATUS "              |     cmake . -DCMAKE_INSTALL_PREFIX=yourprefix")
+  message(STATUS "              |   Or:")
+  message(STATUS "              |     cmake . -DINCLUDE_INSTALL_DIR=yourdir")
   message(STATUS "make doc      | Generate the API documentation, requires Doxygen & LaTeX")
   message(STATUS "make check    | Build and run the unit-tests. Read this page:")
   message(STATUS "              |   http://eigen.tuxfamily.org/index.php?title=Tests")
   message(STATUS "make blas     | Build BLAS library (not the same thing as Eigen)")
+  message(STATUS "make uninstall| Removes files installed by make install")
   message(STATUS "--------------+--------------------------------------------------------------")
 else()
   message(STATUS "To build/run the unit tests, read this page:")
   message(STATUS "  http://eigen.tuxfamily.org/index.php?title=Tests")
 endif()
 
 message(STATUS "")
+
+
+set ( EIGEN_VERSION_STRING ${EIGEN_VERSION_NUMBER} )
+set ( EIGEN_VERSION_MAJOR  ${EIGEN_WORLD_VERSION} )
+set ( EIGEN_VERSION_MINOR  ${EIGEN_MAJOR_VERSION} )
+set ( EIGEN_VERSION_PATCH  ${EIGEN_MINOR_VERSION} )
+set ( EIGEN_DEFINITIONS "")
+set ( EIGEN_INCLUDE_DIR "${CMAKE_INSTALL_PREFIX}/${INCLUDE_INSTALL_DIR}" )
+set ( EIGEN_ROOT_DIR ${CMAKE_INSTALL_PREFIX} )
+
+# Interface libraries require at least CMake 3.0
+if (NOT CMAKE_VERSION VERSION_LESS 3.0)
+  include (CMakePackageConfigHelpers)
+
+  # Imported target support
+  add_library (eigen INTERFACE)
+
+  target_compile_definitions (eigen INTERFACE ${EIGEN_DEFINITIONS})
+  target_include_directories (eigen INTERFACE
+    $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>
+    $<INSTALL_INTERFACE:${INCLUDE_INSTALL_DIR}>
+  )
+
+  # Export as title case Eigen
+  set_target_properties (eigen PROPERTIES EXPORT_NAME Eigen)
+
+  install (TARGETS eigen EXPORT Eigen3Targets)
+
+  configure_package_config_file (
+    ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3Config.cmake.in
+    ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
+    PATH_VARS EIGEN_INCLUDE_DIR EIGEN_ROOT_DIR
+    INSTALL_DESTINATION ${CMAKEPACKAGE_INSTALL_DIR}
+    NO_CHECK_REQUIRED_COMPONENTS_MACRO # Eigen does not provide components
+  )
+  # Remove CMAKE_SIZEOF_VOID_P from Eigen3ConfigVersion.cmake since Eigen does
+  # not depend on architecture specific settings or libraries. More
+  # specifically, an Eigen3Config.cmake generated from a 64 bit target can be
+  # used for 32 bit targets as well (and vice versa).
+  set (_Eigen3_CMAKE_SIZEOF_VOID_P ${CMAKE_SIZEOF_VOID_P})
+  unset (CMAKE_SIZEOF_VOID_P)
+  write_basic_package_version_file (Eigen3ConfigVersion.cmake
+                                    VERSION ${EIGEN_VERSION_NUMBER}
+                                    COMPATIBILITY SameMajorVersion)
+  set (CMAKE_SIZEOF_VOID_P ${_Eigen3_CMAKE_SIZEOF_VOID_P})
+
+  # The Eigen target will be located in the Eigen3 namespace. Other CMake
+  # targets can refer to it using Eigen3::Eigen.
+  export (TARGETS eigen NAMESPACE Eigen3:: FILE Eigen3Targets.cmake)
+  # Export Eigen3 package to CMake registry such that it can be easily found by
+  # CMake even if it has not been installed to a standard directory.
+  export (PACKAGE Eigen3)
+
+  install (EXPORT Eigen3Targets NAMESPACE Eigen3:: DESTINATION ${CMAKEPACKAGE_INSTALL_DIR})
+
+else (NOT CMAKE_VERSION VERSION_LESS 3.0)
+  # Fallback to legacy Eigen3Config.cmake without the imported target
+  
+  # If CMakePackageConfigHelpers module is available (CMake >= 2.8.8)
+  # create a relocatable Config file, otherwise leave the hardcoded paths       
+  include(CMakePackageConfigHelpers OPTIONAL RESULT_VARIABLE CPCH_PATH)
+  
+  if(CPCH_PATH)
+    configure_package_config_file (
+      ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3ConfigLegacy.cmake.in
+      ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
+      PATH_VARS EIGEN_INCLUDE_DIR EIGEN_ROOT_DIR
+      INSTALL_DESTINATION ${CMAKEPACKAGE_INSTALL_DIR}
+      NO_CHECK_REQUIRED_COMPONENTS_MACRO # Eigen does not provide components
+    )
+  else() 
+    # The PACKAGE_* variables are defined by the configure_package_config_file
+    # but without it we define them manually to the hardcoded paths
+    set(PACKAGE_INIT "")
+    set(PACKAGE_EIGEN_INCLUDE_DIR ${EIGEN_INCLUDE_DIR})
+    set(PACKAGE_EIGEN_ROOT_DIR ${EIGEN_ROOT_DIR})
+    configure_file ( ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3ConfigLegacy.cmake.in
+                     ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
+                     @ONLY ESCAPE_QUOTES )
+  endif()
+
+  write_basic_package_version_file( Eigen3ConfigVersion.cmake
+                                    VERSION ${EIGEN_VERSION_NUMBER}
+                                    COMPATIBILITY SameMajorVersion )
+
+endif (NOT CMAKE_VERSION VERSION_LESS 3.0)
+
+install ( FILES ${CMAKE_CURRENT_SOURCE_DIR}/cmake/UseEigen3.cmake
+                ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
+                ${CMAKE_CURRENT_BINARY_DIR}/Eigen3ConfigVersion.cmake
+          DESTINATION ${CMAKEPACKAGE_INSTALL_DIR} )
+
+# Add uninstall target
+add_custom_target ( uninstall
+    COMMAND ${CMAKE_COMMAND} -P ${CMAKE_CURRENT_SOURCE_DIR}/cmake/EigenUninstall.cmake)

Index: 3rd_party/eigen/CTestConfig.cmake
==================================================================
--- 3rd_party/eigen/CTestConfig.cmake
+++ 3rd_party/eigen/CTestConfig.cmake
@@ -2,12 +2,12 @@
 ## Then modify the CMakeLists.txt file in the root directory of your
 ## project to incorporate the testing dashboard.
 ## # The following are required to uses Dart and the Cdash dashboard
 ##   ENABLE_TESTING()
 ##   INCLUDE(CTest)
-set(CTEST_PROJECT_NAME "Eigen3.2")
+set(CTEST_PROJECT_NAME "Eigen3.3")
 set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
 
 set(CTEST_DROP_METHOD "http")
 set(CTEST_DROP_SITE "manao.inria.fr")
-set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen3.2")
+set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen3.3")
 set(CTEST_DROP_SITE_CDASH TRUE)

DELETED 3rd_party/eigen/Eigen/Array
Index: 3rd_party/eigen/Eigen/Array
==================================================================
--- 3rd_party/eigen/Eigen/Array
+++ 3rd_party/eigen/Eigen/Array
@@ -1,11 +0,0 @@
-#ifndef EIGEN_ARRAY_MODULE_H
-#define EIGEN_ARRAY_MODULE_H
-
-// include Core first to handle Eigen2 support macros
-#include "Core"
-
-#ifndef EIGEN2_SUPPORT
-  #error The Eigen/Array header does no longer exist in Eigen3. All that functionality has moved to Eigen/Core.
-#endif
-
-#endif // EIGEN_ARRAY_MODULE_H

Index: 3rd_party/eigen/Eigen/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/CMakeLists.txt
@@ -14,6 +14,6 @@
 install(FILES
   ${Eigen_directory_files_to_install}
   DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen COMPONENT Devel
   )
 
-add_subdirectory(src)
+install(DIRECTORY src DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen COMPONENT Devel FILES_MATCHING PATTERN "*.h")

Index: 3rd_party/eigen/Eigen/Cholesky
==================================================================
--- 3rd_party/eigen/Eigen/Cholesky
+++ 3rd_party/eigen/Eigen/Cholesky
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_CHOLESKY_MODULE_H
 #define EIGEN_CHOLESKY_MODULE_H
 
 #include "Core"
 
@@ -8,25 +15,27 @@
 /** \defgroup Cholesky_Module Cholesky module
   *
   *
   *
   * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
-  * Those decompositions are accessible via the following MatrixBase methods:
-  *  - MatrixBase::llt(),
+  * Those decompositions are also accessible via the following methods:
+  *  - MatrixBase::llt()
   *  - MatrixBase::ldlt()
+  *  - SelfAdjointView::llt()
+  *  - SelfAdjointView::ldlt()
   *
   * \code
   * #include <Eigen/Cholesky>
   * \endcode
   */
 
-#include "src/misc/Solve.h"
 #include "src/Cholesky/LLT.h"
 #include "src/Cholesky/LDLT.h"
 #ifdef EIGEN_USE_LAPACKE
-#include "src/Cholesky/LLT_MKL.h"
+#include "src/misc/lapacke.h"
+#include "src/Cholesky/LLT_LAPACKE.h"
 #endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_CHOLESKY_MODULE_H
 /* vim: set filetype=cpp et sw=2 ts=2 ai: */

Index: 3rd_party/eigen/Eigen/CholmodSupport
==================================================================
--- 3rd_party/eigen/Eigen/CholmodSupport
+++ 3rd_party/eigen/Eigen/CholmodSupport
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_CHOLMODSUPPORT_MODULE_H
 #define EIGEN_CHOLMODSUPPORT_MODULE_H
 
 #include "SparseCore"
 
@@ -10,11 +17,11 @@
 }
 
 /** \ingroup Support_modules
   * \defgroup CholmodSupport_Module CholmodSupport module
   *
-  * This module provides an interface to the Cholmod library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  * This module provides an interface to the Cholmod library which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
   * It provides the two following main factorization classes:
   * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
   * - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial).
   *
   * For the sake of completeness, this module also propose the two following classes:
@@ -31,15 +38,11 @@
   * The dependencies depend on how cholmod has been compiled.
   * For a cmake based project, you can use our FindCholmod.cmake module to help you in this task.
   *
   */
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
 #include "src/CholmodSupport/CholmodSupport.h"
-
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_CHOLMODSUPPORT_MODULE_H
 

Index: 3rd_party/eigen/Eigen/Core
==================================================================
--- 3rd_party/eigen/Eigen/Core
+++ 3rd_party/eigen/Eigen/Core
@@ -11,48 +11,100 @@
 #ifndef EIGEN_CORE_H
 #define EIGEN_CORE_H
 
 // first thing Eigen does: stop the compiler from committing suicide
 #include "src/Core/util/DisableStupidWarnings.h"
+
+// Handle NVCC/CUDA/SYCL
+#if defined(__CUDACC__) || defined(__SYCL_DEVICE_ONLY__)
+  // Do not try asserts on CUDA and SYCL!
+  #ifndef EIGEN_NO_DEBUG
+  #define EIGEN_NO_DEBUG
+  #endif
+
+  #ifdef EIGEN_INTERNAL_DEBUGGING
+  #undef EIGEN_INTERNAL_DEBUGGING
+  #endif
+
+  #ifdef EIGEN_EXCEPTIONS
+  #undef EIGEN_EXCEPTIONS
+  #endif
+
+  // All functions callable from CUDA code must be qualified with __device__
+  #ifdef __CUDACC__
+    // Do not try to vectorize on CUDA and SYCL!
+    #ifndef EIGEN_DONT_VECTORIZE
+    #define EIGEN_DONT_VECTORIZE
+    #endif
+
+    #define EIGEN_DEVICE_FUNC __host__ __device__
+    // We need math_functions.hpp to ensure that that EIGEN_USING_STD_MATH macro
+    // works properly on the device side
+    #include <math_functions.hpp>
+  #else
+    #define EIGEN_DEVICE_FUNC
+  #endif
+
+#else
+  #define EIGEN_DEVICE_FUNC
+
+#endif
+
+// When compiling CUDA device code with NVCC, pull in math functions from the
+// global namespace.  In host mode, and when device doee with clang, use the
+// std versions.
+#if defined(__CUDA_ARCH__) && defined(__NVCC__)
+  #define EIGEN_USING_STD_MATH(FUNC) using ::FUNC;
+#else
+  #define EIGEN_USING_STD_MATH(FUNC) using std::FUNC;
+#endif
+
+#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__) && !defined(EIGEN_EXCEPTIONS) && !defined(EIGEN_USE_SYCL)
+  #define EIGEN_EXCEPTIONS
+#endif
+
+#ifdef EIGEN_EXCEPTIONS
+  #include <new>
+#endif
 
 // then include this file where all our macros are defined. It's really important to do it first because
 // it's where we do all the alignment settings (platform detection and honoring the user's will if he
 // defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization.
 #include "src/Core/util/Macros.h"
 
 // Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3)
 // See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
-#if defined(__MINGW32__) && EIGEN_GNUC_AT_LEAST(4,6)
+#if EIGEN_COMP_MINGW && EIGEN_GNUC_AT_LEAST(4,6)
   #pragma GCC optimize ("-fno-ipa-cp-clone")
 #endif
 
 #include <complex>
 
 // this include file manages BLAS and MKL related macros
 // and inclusion of their respective header files
 #include "src/Core/util/MKL_support.h"
 
-// if alignment is disabled, then disable vectorization. Note: EIGEN_ALIGN is the proper check, it takes into
-// account both the user's will (EIGEN_DONT_ALIGN) and our own platform checks
-#if !EIGEN_ALIGN
+// if alignment is disabled, then disable vectorization. Note: EIGEN_MAX_ALIGN_BYTES is the proper check, it takes into
+// account both the user's will (EIGEN_MAX_ALIGN_BYTES,EIGEN_DONT_ALIGN) and our own platform checks
+#if EIGEN_MAX_ALIGN_BYTES==0
   #ifndef EIGEN_DONT_VECTORIZE
     #define EIGEN_DONT_VECTORIZE
   #endif
 #endif
 
-#ifdef _MSC_VER
+#if EIGEN_COMP_MSVC
   #include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled
-  #if (_MSC_VER >= 1500) // 2008 or later
+  #if (EIGEN_COMP_MSVC >= 1500) // 2008 or later
     // Remember that usage of defined() in a #define is undefined by the standard.
     // a user reported that in 64-bit mode, MSVC doesn't care to define _M_IX86_FP.
-    #if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(_M_X64)
+    #if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || EIGEN_ARCH_x86_64
       #define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
     #endif
   #endif
 #else
   // Remember that usage of defined() in a #define is undefined by the standard
-  #if (defined __SSE2__) && ( (!defined __GNUC__) || (defined __INTEL_COMPILER) || EIGEN_GNUC_AT_LEAST(4,2) )
+  #if (defined __SSE2__) && ( (!EIGEN_COMP_GNUC) || EIGEN_COMP_ICC || EIGEN_GNUC_AT_LEAST(4,2) )
     #define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
   #endif
 #endif
 
 #ifndef EIGEN_DONT_VECTORIZE
@@ -80,10 +132,32 @@
       #define EIGEN_VECTORIZE_SSE4_1
     #endif
     #ifdef __SSE4_2__
       #define EIGEN_VECTORIZE_SSE4_2
     #endif
+    #ifdef __AVX__
+      #define EIGEN_VECTORIZE_AVX
+      #define EIGEN_VECTORIZE_SSE3
+      #define EIGEN_VECTORIZE_SSSE3
+      #define EIGEN_VECTORIZE_SSE4_1
+      #define EIGEN_VECTORIZE_SSE4_2
+    #endif
+    #ifdef __AVX2__
+      #define EIGEN_VECTORIZE_AVX2
+    #endif
+    #ifdef __FMA__
+      #define EIGEN_VECTORIZE_FMA
+    #endif
+    #if defined(__AVX512F__) && defined(EIGEN_ENABLE_AVX512)
+      #define EIGEN_VECTORIZE_AVX512
+      #define EIGEN_VECTORIZE_AVX2
+      #define EIGEN_VECTORIZE_AVX
+      #define EIGEN_VECTORIZE_FMA
+      #ifdef __AVX512DQ__
+        #define EIGEN_VECTORIZE_AVX512DQ
+      #endif
+    #endif
 
     // include files
 
     // This extern "C" works around a MINGW-w64 compilation issue
     // https://sourceforge.net/tracker/index.php?func=detail&aid=3018394&group_id=202880&atid=983354
@@ -93,13 +167,14 @@
     // so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too.
     // notice that since these are C headers, the extern "C" is theoretically needed anyways.
     extern "C" {
       // In theory we should only include immintrin.h and not the other *mmintrin.h header files directly.
       // Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus:
-      #if defined(__INTEL_COMPILER) && __INTEL_COMPILER >= 1110
+      #if EIGEN_COMP_ICC >= 1110
         #include <immintrin.h>
       #else
+        #include <mmintrin.h>
         #include <emmintrin.h>
         #include <xmmintrin.h>
         #ifdef  EIGEN_VECTORIZE_SSE3
         #include <pmmintrin.h>
         #endif
@@ -110,27 +185,61 @@
         #include <smmintrin.h>
         #endif
         #ifdef EIGEN_VECTORIZE_SSE4_2
         #include <nmmintrin.h>
         #endif
+        #if defined(EIGEN_VECTORIZE_AVX) || defined(EIGEN_VECTORIZE_AVX512)
+        #include <immintrin.h>
+        #endif
       #endif
     } // end extern "C"
+  #elif defined __VSX__
+    #define EIGEN_VECTORIZE
+    #define EIGEN_VECTORIZE_VSX
+    #include <altivec.h>
+    // We need to #undef all these ugly tokens defined in <altivec.h>
+    // => use __vector instead of vector
+    #undef bool
+    #undef vector
+    #undef pixel
   #elif defined __ALTIVEC__
     #define EIGEN_VECTORIZE
     #define EIGEN_VECTORIZE_ALTIVEC
     #include <altivec.h>
     // We need to #undef all these ugly tokens defined in <altivec.h>
     // => use __vector instead of vector
     #undef bool
     #undef vector
     #undef pixel
-  #elif defined  __ARM_NEON__
+  #elif (defined  __ARM_NEON) || (defined __ARM_NEON__)
     #define EIGEN_VECTORIZE
     #define EIGEN_VECTORIZE_NEON
     #include <arm_neon.h>
+  #elif (defined __s390x__ && defined __VEC__)
+    #define EIGEN_VECTORIZE
+    #define EIGEN_VECTORIZE_ZVECTOR
+    #include <vecintrin.h>
+  #endif
+#endif
+
+#if defined(__F16C__) && !defined(EIGEN_COMP_CLANG)
+  // We can use the optimized fp16 to float and float to fp16 conversion routines
+  #define EIGEN_HAS_FP16_C
+#endif
+
+#if defined __CUDACC__
+  #define EIGEN_VECTORIZE_CUDA
+  #include <vector_types.h>
+  #if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+    #define EIGEN_HAS_CUDA_FP16
   #endif
 #endif
+
+#if defined EIGEN_HAS_CUDA_FP16
+  #include <host_defines.h>
+  #include <cuda_fp16.h>
+#endif
 
 #if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE)
   #define EIGEN_HAS_OPENMP
 #endif
 
@@ -137,11 +246,11 @@
 #ifdef EIGEN_HAS_OPENMP
 #include <omp.h>
 #endif
 
 // MSVC for windows mobile does not have the errno.h file
-#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
+#if !(EIGEN_COMP_MSVC && EIGEN_OS_WINCE) && !EIGEN_COMP_ARM
 #define EIGEN_HAS_ERRNO
 #endif
 
 #ifdef EIGEN_HAS_ERRNO
 #include <cerrno>
@@ -156,34 +265,35 @@
 #include <string>
 #include <limits>
 #include <climits> // for CHAR_BIT
 // for min/max:
 #include <algorithm>
+
+// for std::is_nothrow_move_assignable
+#ifdef EIGEN_INCLUDE_TYPE_TRAITS
+#include <type_traits>
+#endif
 
 // for outputting debug info
 #ifdef EIGEN_DEBUG_ASSIGN
 #include <iostream>
 #endif
 
 // required for __cpuid, needs to be included after cmath
-#if defined(_MSC_VER) && (defined(_M_IX86)||defined(_M_X64)) && (!defined(_WIN32_WCE))
+#if EIGEN_COMP_MSVC && EIGEN_ARCH_i386_OR_x86_64 && !EIGEN_OS_WINCE
   #include <intrin.h>
 #endif
 
-#if defined(_CPPUNWIND) || defined(__EXCEPTIONS)
-  #define EIGEN_EXCEPTIONS
-#endif
-
-#ifdef EIGEN_EXCEPTIONS
-  #include <new>
-#endif
-
 /** \brief Namespace containing all symbols from the %Eigen library. */
 namespace Eigen {
 
 inline static const char *SimdInstructionSetsInUse(void) {
-#if defined(EIGEN_VECTORIZE_SSE4_2)
+#if defined(EIGEN_VECTORIZE_AVX512)
+  return "AVX512, FMA, AVX2, AVX, SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
+#elif defined(EIGEN_VECTORIZE_AVX)
+  return "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
+#elif defined(EIGEN_VECTORIZE_SSE4_2)
   return "SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
 #elif defined(EIGEN_VECTORIZE_SSE4_1)
   return "SSE, SSE2, SSE3, SSSE3, SSE4.1";
 #elif defined(EIGEN_VECTORIZE_SSSE3)
   return "SSE, SSE2, SSE3, SSSE3";
@@ -191,54 +301,37 @@
   return "SSE, SSE2, SSE3";
 #elif defined(EIGEN_VECTORIZE_SSE2)
   return "SSE, SSE2";
 #elif defined(EIGEN_VECTORIZE_ALTIVEC)
   return "AltiVec";
+#elif defined(EIGEN_VECTORIZE_VSX)
+  return "VSX";
 #elif defined(EIGEN_VECTORIZE_NEON)
   return "ARM NEON";
+#elif defined(EIGEN_VECTORIZE_ZVECTOR)
+  return "S390X ZVECTOR";
 #else
   return "None";
 #endif
 }
 
 } // end namespace Eigen
 
-#define STAGE10_FULL_EIGEN2_API             10
-#define STAGE20_RESOLVE_API_CONFLICTS       20
-#define STAGE30_FULL_EIGEN3_API             30
-#define STAGE40_FULL_EIGEN3_STRICTNESS      40
-#define STAGE99_NO_EIGEN2_SUPPORT           99
-
-#if   defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS
-  #define EIGEN2_SUPPORT
-  #define EIGEN2_SUPPORT_STAGE STAGE40_FULL_EIGEN3_STRICTNESS
-#elif defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
-  #define EIGEN2_SUPPORT
-  #define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API
-#elif defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS
-  #define EIGEN2_SUPPORT
-  #define EIGEN2_SUPPORT_STAGE STAGE20_RESOLVE_API_CONFLICTS
-#elif defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API
-  #define EIGEN2_SUPPORT
-  #define EIGEN2_SUPPORT_STAGE STAGE10_FULL_EIGEN2_API
-#elif defined EIGEN2_SUPPORT
-  // default to stage 3, that's what it's always meant
-  #define EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
-  #define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API
-#else
-  #define EIGEN2_SUPPORT_STAGE STAGE99_NO_EIGEN2_SUPPORT
-#endif
-
-#ifdef EIGEN2_SUPPORT
-#undef minor
-#endif
+#if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS || defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API || defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS || defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API || defined EIGEN2_SUPPORT
+// This will generate an error message:
+#error Eigen2-support is only available up to version 3.2. Please go to "http://eigen.tuxfamily.org/index.php?title=Eigen2" for further information
+#endif
+
+namespace Eigen {
 
 // we use size_t frequently and we'll never remember to prepend it with std:: everytime just to
 // ensure QNX/QCC support
 using std::size_t;
-// gcc 4.6.0 wants std:: for ptrdiff_t 
+// gcc 4.6.0 wants std:: for ptrdiff_t
 using std::ptrdiff_t;
+
+}
 
 /** \defgroup Core_Module Core module
   * This is the main module of Eigen providing dense matrix and vector support
   * (both fixed and dynamic size) with all the features corresponding to a BLAS library
   * and much more...
@@ -247,87 +340,138 @@
   * #include <Eigen/Core>
   * \endcode
   */
 
 #include "src/Core/util/Constants.h"
-#include "src/Core/util/ForwardDeclarations.h"
 #include "src/Core/util/Meta.h"
+#include "src/Core/util/ForwardDeclarations.h"
 #include "src/Core/util/StaticAssert.h"
 #include "src/Core/util/XprHelper.h"
 #include "src/Core/util/Memory.h"
 
 #include "src/Core/NumTraits.h"
 #include "src/Core/MathFunctions.h"
 #include "src/Core/GenericPacketMath.h"
+#include "src/Core/MathFunctionsImpl.h"
 
-#if defined EIGEN_VECTORIZE_SSE
+#if defined EIGEN_VECTORIZE_AVX512
+  #include "src/Core/arch/SSE/PacketMath.h"
+  #include "src/Core/arch/AVX/PacketMath.h"
+  #include "src/Core/arch/AVX512/PacketMath.h"
+  #include "src/Core/arch/AVX512/MathFunctions.h"
+#elif defined EIGEN_VECTORIZE_AVX
+  // Use AVX for floats and doubles, SSE for integers
+  #include "src/Core/arch/SSE/PacketMath.h"
+  #include "src/Core/arch/SSE/Complex.h"
+  #include "src/Core/arch/SSE/MathFunctions.h"
+  #include "src/Core/arch/AVX/PacketMath.h"
+  #include "src/Core/arch/AVX/MathFunctions.h"
+  #include "src/Core/arch/AVX/Complex.h"
+  #include "src/Core/arch/AVX/TypeCasting.h"
+#elif defined EIGEN_VECTORIZE_SSE
   #include "src/Core/arch/SSE/PacketMath.h"
   #include "src/Core/arch/SSE/MathFunctions.h"
   #include "src/Core/arch/SSE/Complex.h"
-#elif defined EIGEN_VECTORIZE_ALTIVEC
+  #include "src/Core/arch/SSE/TypeCasting.h"
+#elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
   #include "src/Core/arch/AltiVec/PacketMath.h"
+  #include "src/Core/arch/AltiVec/MathFunctions.h"
   #include "src/Core/arch/AltiVec/Complex.h"
 #elif defined EIGEN_VECTORIZE_NEON
   #include "src/Core/arch/NEON/PacketMath.h"
+  #include "src/Core/arch/NEON/MathFunctions.h"
   #include "src/Core/arch/NEON/Complex.h"
+#elif defined EIGEN_VECTORIZE_ZVECTOR
+  #include "src/Core/arch/ZVector/PacketMath.h"
+  #include "src/Core/arch/ZVector/MathFunctions.h"
+  #include "src/Core/arch/ZVector/Complex.h"
+#endif
+
+// Half float support
+#include "src/Core/arch/CUDA/Half.h"
+#include "src/Core/arch/CUDA/PacketMathHalf.h"
+#include "src/Core/arch/CUDA/TypeCasting.h"
+
+#if defined EIGEN_VECTORIZE_CUDA
+  #include "src/Core/arch/CUDA/PacketMath.h"
+  #include "src/Core/arch/CUDA/MathFunctions.h"
 #endif
 
 #include "src/Core/arch/Default/Settings.h"
 
-#include "src/Core/Functors.h"
+#include "src/Core/functors/TernaryFunctors.h"
+#include "src/Core/functors/BinaryFunctors.h"
+#include "src/Core/functors/UnaryFunctors.h"
+#include "src/Core/functors/NullaryFunctors.h"
+#include "src/Core/functors/StlFunctors.h"
+#include "src/Core/functors/AssignmentFunctors.h"
+
+// Specialized functors to enable the processing of complex numbers
+// on CUDA devices
+#include "src/Core/arch/CUDA/Complex.h"
+
+#include "src/Core/IO.h"
 #include "src/Core/DenseCoeffsBase.h"
 #include "src/Core/DenseBase.h"
 #include "src/Core/MatrixBase.h"
 #include "src/Core/EigenBase.h"
 
+#include "src/Core/Product.h"
+#include "src/Core/CoreEvaluators.h"
+#include "src/Core/AssignEvaluator.h"
+
 #ifndef EIGEN_PARSED_BY_DOXYGEN // work around Doxygen bug triggered by Assign.h r814874
                                 // at least confirmed with Doxygen 1.5.5 and 1.5.6
   #include "src/Core/Assign.h"
 #endif
 
+#include "src/Core/ArrayBase.h"
 #include "src/Core/util/BlasUtil.h"
 #include "src/Core/DenseStorage.h"
 #include "src/Core/NestByValue.h"
-#include "src/Core/ForceAlignedAccess.h"
+
+// #include "src/Core/ForceAlignedAccess.h"
+
 #include "src/Core/ReturnByValue.h"
 #include "src/Core/NoAlias.h"
 #include "src/Core/PlainObjectBase.h"
 #include "src/Core/Matrix.h"
 #include "src/Core/Array.h"
+#include "src/Core/CwiseTernaryOp.h"
 #include "src/Core/CwiseBinaryOp.h"
 #include "src/Core/CwiseUnaryOp.h"
 #include "src/Core/CwiseNullaryOp.h"
 #include "src/Core/CwiseUnaryView.h"
 #include "src/Core/SelfCwiseBinaryOp.h"
 #include "src/Core/Dot.h"
 #include "src/Core/StableNorm.h"
-#include "src/Core/MapBase.h"
 #include "src/Core/Stride.h"
+#include "src/Core/MapBase.h"
 #include "src/Core/Map.h"
+#include "src/Core/Ref.h"
 #include "src/Core/Block.h"
 #include "src/Core/VectorBlock.h"
-#include "src/Core/Ref.h"
 #include "src/Core/Transpose.h"
 #include "src/Core/DiagonalMatrix.h"
 #include "src/Core/Diagonal.h"
 #include "src/Core/DiagonalProduct.h"
-#include "src/Core/PermutationMatrix.h"
-#include "src/Core/Transpositions.h"
 #include "src/Core/Redux.h"
 #include "src/Core/Visitor.h"
 #include "src/Core/Fuzzy.h"
-#include "src/Core/IO.h"
 #include "src/Core/Swap.h"
 #include "src/Core/CommaInitializer.h"
-#include "src/Core/Flagged.h"
-#include "src/Core/ProductBase.h"
 #include "src/Core/GeneralProduct.h"
+#include "src/Core/Solve.h"
+#include "src/Core/Inverse.h"
+#include "src/Core/SolverBase.h"
+#include "src/Core/PermutationMatrix.h"
+#include "src/Core/Transpositions.h"
 #include "src/Core/TriangularMatrix.h"
 #include "src/Core/SelfAdjointView.h"
 #include "src/Core/products/GeneralBlockPanelKernel.h"
 #include "src/Core/products/Parallelizer.h"
-#include "src/Core/products/CoeffBasedProduct.h"
+#include "src/Core/ProductEvaluators.h"
 #include "src/Core/products/GeneralMatrixVector.h"
 #include "src/Core/products/GeneralMatrixMatrix.h"
 #include "src/Core/SolveTriangular.h"
 #include "src/Core/products/GeneralMatrixMatrixTriangular.h"
 #include "src/Core/products/SelfadjointMatrixVector.h"
@@ -338,29 +482,29 @@
 #include "src/Core/products/TriangularMatrixMatrix.h"
 #include "src/Core/products/TriangularSolverMatrix.h"
 #include "src/Core/products/TriangularSolverVector.h"
 #include "src/Core/BandMatrix.h"
 #include "src/Core/CoreIterators.h"
+#include "src/Core/ConditionEstimator.h"
 
 #include "src/Core/BooleanRedux.h"
 #include "src/Core/Select.h"
 #include "src/Core/VectorwiseOp.h"
 #include "src/Core/Random.h"
 #include "src/Core/Replicate.h"
 #include "src/Core/Reverse.h"
-#include "src/Core/ArrayBase.h"
 #include "src/Core/ArrayWrapper.h"
 
 #ifdef EIGEN_USE_BLAS
-#include "src/Core/products/GeneralMatrixMatrix_MKL.h"
-#include "src/Core/products/GeneralMatrixVector_MKL.h"
-#include "src/Core/products/GeneralMatrixMatrixTriangular_MKL.h"
-#include "src/Core/products/SelfadjointMatrixMatrix_MKL.h"
-#include "src/Core/products/SelfadjointMatrixVector_MKL.h"
-#include "src/Core/products/TriangularMatrixMatrix_MKL.h"
-#include "src/Core/products/TriangularMatrixVector_MKL.h"
-#include "src/Core/products/TriangularSolverMatrix_MKL.h"
+#include "src/Core/products/GeneralMatrixMatrix_BLAS.h"
+#include "src/Core/products/GeneralMatrixVector_BLAS.h"
+#include "src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h"
+#include "src/Core/products/SelfadjointMatrixMatrix_BLAS.h"
+#include "src/Core/products/SelfadjointMatrixVector_BLAS.h"
+#include "src/Core/products/TriangularMatrixMatrix_BLAS.h"
+#include "src/Core/products/TriangularMatrixVector_BLAS.h"
+#include "src/Core/products/TriangularSolverMatrix_BLAS.h"
 #endif // EIGEN_USE_BLAS
 
 #ifdef EIGEN_USE_MKL_VML
 #include "src/Core/Assign_MKL.h"
 #endif
@@ -367,10 +511,6 @@
 
 #include "src/Core/GlobalFunctions.h"
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#ifdef EIGEN2_SUPPORT
-#include "Eigen2Support"
-#endif
-
 #endif // EIGEN_CORE_H

Index: 3rd_party/eigen/Eigen/Eigen
==================================================================
--- 3rd_party/eigen/Eigen/Eigen
+++ 3rd_party/eigen/Eigen/Eigen
@@ -1,2 +1,2 @@
 #include "Dense"
-//#include "Sparse"
+#include "Sparse"

DELETED 3rd_party/eigen/Eigen/Eigen2Support
Index: 3rd_party/eigen/Eigen/Eigen2Support
==================================================================
--- 3rd_party/eigen/Eigen/Eigen2Support
+++ 3rd_party/eigen/Eigen/Eigen2Support
@@ -1,95 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2SUPPORT_H
-#define EIGEN2SUPPORT_H
-
-#if (!defined(EIGEN2_SUPPORT)) || (!defined(EIGEN_CORE_H))
-#error Eigen2 support must be enabled by defining EIGEN2_SUPPORT before including any Eigen header
-#endif
-
-#ifndef EIGEN_NO_EIGEN2_DEPRECATED_WARNING
-
-#if defined(__GNUC__) || defined(__INTEL_COMPILER) || defined(__clang__)
-#warning "Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3. (Define EIGEN_NO_EIGEN2_DEPRECATED_WARNING to disable this warning)"
-#else
-#pragma message ("Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3. (Define EIGEN_NO_EIGEN2_DEPRECATED_WARNING to disable this warning)")
-#endif
-
-#endif // EIGEN_NO_EIGEN2_DEPRECATED_WARNING
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \ingroup Support_modules
-  * \defgroup Eigen2Support_Module Eigen2 support module
-  *
-  * \warning Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3.
-  *
-  * This module provides a couple of deprecated functions improving the compatibility with Eigen2.
-  * 
-  * To use it, define EIGEN2_SUPPORT before including any Eigen header
-  * \code
-  * #define EIGEN2_SUPPORT
-  * \endcode
-  *
-  */
-
-#include "src/Eigen2Support/Macros.h"
-#include "src/Eigen2Support/Memory.h"
-#include "src/Eigen2Support/Meta.h"
-#include "src/Eigen2Support/Lazy.h"
-#include "src/Eigen2Support/Cwise.h"
-#include "src/Eigen2Support/CwiseOperators.h"
-#include "src/Eigen2Support/TriangularSolver.h"
-#include "src/Eigen2Support/Block.h"
-#include "src/Eigen2Support/VectorBlock.h"
-#include "src/Eigen2Support/Minor.h"
-#include "src/Eigen2Support/MathFunctions.h"
-
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-// Eigen2 used to include iostream
-#include<iostream>
-
-#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
-using Eigen::Matrix##SizeSuffix##TypeSuffix; \
-using Eigen::Vector##SizeSuffix##TypeSuffix; \
-using Eigen::RowVector##SizeSuffix##TypeSuffix;
-
-#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(TypeSuffix) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
-
-#define EIGEN_USING_MATRIX_TYPEDEFS \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd)
-
-#define USING_PART_OF_NAMESPACE_EIGEN \
-EIGEN_USING_MATRIX_TYPEDEFS \
-using Eigen::Matrix; \
-using Eigen::MatrixBase; \
-using Eigen::ei_random; \
-using Eigen::ei_real; \
-using Eigen::ei_imag; \
-using Eigen::ei_conj; \
-using Eigen::ei_abs; \
-using Eigen::ei_abs2; \
-using Eigen::ei_sqrt; \
-using Eigen::ei_exp; \
-using Eigen::ei_log; \
-using Eigen::ei_sin; \
-using Eigen::ei_cos;
-
-#endif // EIGEN2SUPPORT_H

Index: 3rd_party/eigen/Eigen/Eigenvalues
==================================================================
--- 3rd_party/eigen/Eigen/Eigenvalues
+++ 3rd_party/eigen/Eigen/Eigenvalues
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_EIGENVALUES_MODULE_H
 #define EIGEN_EIGENVALUES_MODULE_H
 
 #include "Core"
 
@@ -23,10 +30,11 @@
   * \code
   * #include <Eigen/Eigenvalues>
   * \endcode
   */
 
+#include "src/misc/RealSvd2x2.h"
 #include "src/Eigenvalues/Tridiagonalization.h"
 #include "src/Eigenvalues/RealSchur.h"
 #include "src/Eigenvalues/EigenSolver.h"
 #include "src/Eigenvalues/SelfAdjointEigenSolver.h"
 #include "src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h"
@@ -35,14 +43,15 @@
 #include "src/Eigenvalues/ComplexEigenSolver.h"
 #include "src/Eigenvalues/RealQZ.h"
 #include "src/Eigenvalues/GeneralizedEigenSolver.h"
 #include "src/Eigenvalues/MatrixBaseEigenvalues.h"
 #ifdef EIGEN_USE_LAPACKE
-#include "src/Eigenvalues/RealSchur_MKL.h"
-#include "src/Eigenvalues/ComplexSchur_MKL.h"
-#include "src/Eigenvalues/SelfAdjointEigenSolver_MKL.h"
+#include "src/misc/lapacke.h"
+#include "src/Eigenvalues/RealSchur_LAPACKE.h"
+#include "src/Eigenvalues/ComplexSchur_LAPACKE.h"
+#include "src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h"
 #endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_EIGENVALUES_MODULE_H
 /* vim: set filetype=cpp et sw=2 ts=2 ai: */

Index: 3rd_party/eigen/Eigen/Geometry
==================================================================
--- 3rd_party/eigen/Eigen/Geometry
+++ 3rd_party/eigen/Eigen/Geometry
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_GEOMETRY_MODULE_H
 #define EIGEN_GEOMETRY_MODULE_H
 
 #include "Core"
 
@@ -7,57 +14,49 @@
 
 #include "SVD"
 #include "LU"
 #include <limits>
 
-#ifndef M_PI
-#define M_PI 3.14159265358979323846
-#endif
-
 /** \defgroup Geometry_Module Geometry module
-  *
-  *
   *
   * This module provides support for:
   *  - fixed-size homogeneous transformations
   *  - translation, scaling, 2D and 3D rotations
-  *  - quaternions
-  *  - \ref MatrixBase::cross() "cross product"
-  *  - \ref MatrixBase::unitOrthogonal() "orthognal vector generation"
-  *  - some linear components: parametrized-lines and hyperplanes
+  *  - \link Quaternion quaternions \endlink
+  *  - cross products (\ref MatrixBase::cross, \ref MatrixBase::cross3)
+  *  - orthognal vector generation (\ref MatrixBase::unitOrthogonal)
+  *  - some linear components: \link ParametrizedLine parametrized-lines \endlink and \link Hyperplane hyperplanes \endlink
+  *  - \link AlignedBox axis aligned bounding boxes \endlink
+  *  - \link umeyama least-square transformation fitting \endlink
   *
   * \code
   * #include <Eigen/Geometry>
   * \endcode
   */
 
 #include "src/Geometry/OrthoMethods.h"
 #include "src/Geometry/EulerAngles.h"
 
-#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
-  #include "src/Geometry/Homogeneous.h"
-  #include "src/Geometry/RotationBase.h"
-  #include "src/Geometry/Rotation2D.h"
-  #include "src/Geometry/Quaternion.h"
-  #include "src/Geometry/AngleAxis.h"
-  #include "src/Geometry/Transform.h"
-  #include "src/Geometry/Translation.h"
-  #include "src/Geometry/Scaling.h"
-  #include "src/Geometry/Hyperplane.h"
-  #include "src/Geometry/ParametrizedLine.h"
-  #include "src/Geometry/AlignedBox.h"
-  #include "src/Geometry/Umeyama.h"
-
-  #if defined EIGEN_VECTORIZE_SSE
-    #include "src/Geometry/arch/Geometry_SSE.h"
-  #endif
-#endif
-
-#ifdef EIGEN2_SUPPORT
-#include "src/Eigen2Support/Geometry/All.h"
+#include "src/Geometry/Homogeneous.h"
+#include "src/Geometry/RotationBase.h"
+#include "src/Geometry/Rotation2D.h"
+#include "src/Geometry/Quaternion.h"
+#include "src/Geometry/AngleAxis.h"
+#include "src/Geometry/Transform.h"
+#include "src/Geometry/Translation.h"
+#include "src/Geometry/Scaling.h"
+#include "src/Geometry/Hyperplane.h"
+#include "src/Geometry/ParametrizedLine.h"
+#include "src/Geometry/AlignedBox.h"
+#include "src/Geometry/Umeyama.h"
+
+// Use the SSE optimized version whenever possible. At the moment the
+// SSE version doesn't compile when AVX is enabled
+#if defined EIGEN_VECTORIZE_SSE && !defined EIGEN_VECTORIZE_AVX
+#include "src/Geometry/arch/Geometry_SSE.h"
 #endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_GEOMETRY_MODULE_H
 /* vim: set filetype=cpp et sw=2 ts=2 ai: */
 

Index: 3rd_party/eigen/Eigen/Householder
==================================================================
--- 3rd_party/eigen/Eigen/Householder
+++ 3rd_party/eigen/Eigen/Householder
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_HOUSEHOLDER_MODULE_H
 #define EIGEN_HOUSEHOLDER_MODULE_H
 
 #include "Core"
 

Index: 3rd_party/eigen/Eigen/IterativeLinearSolvers
==================================================================
--- 3rd_party/eigen/Eigen/IterativeLinearSolvers
+++ 3rd_party/eigen/Eigen/IterativeLinearSolvers
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
 #define EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
 
 #include "SparseCore"
 #include "OrderingMethods"
@@ -10,31 +17,32 @@
   * \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module
   *
   * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse.
   * Those solvers are accessible via the following classes:
   *  - ConjugateGradient for selfadjoint (hermitian) matrices,
+  *  - LeastSquaresConjugateGradient for rectangular least-square problems,
   *  - BiCGSTAB for general square matrices.
   *
   * These iterative solvers are associated with some preconditioners:
   *  - IdentityPreconditioner - not really useful
-  *  - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices.
-  *  - IncompleteILUT - incomplete LU factorization with dual thresholding
+  *  - DiagonalPreconditioner - also called Jacobi preconditioner, work very well on diagonal dominant matrices.
+  *  - IncompleteLUT - incomplete LU factorization with dual thresholding
   *
   * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport.
   *
-  * \code
-  * #include <Eigen/IterativeLinearSolvers>
-  * \endcode
+    \code
+    #include <Eigen/IterativeLinearSolvers>
+    \endcode
   */
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
+#include "src/IterativeLinearSolvers/SolveWithGuess.h"
 #include "src/IterativeLinearSolvers/IterativeSolverBase.h"
 #include "src/IterativeLinearSolvers/BasicPreconditioners.h"
 #include "src/IterativeLinearSolvers/ConjugateGradient.h"
+#include "src/IterativeLinearSolvers/LeastSquareConjugateGradient.h"
 #include "src/IterativeLinearSolvers/BiCGSTAB.h"
 #include "src/IterativeLinearSolvers/IncompleteLUT.h"
+#include "src/IterativeLinearSolvers/IncompleteCholesky.h"
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H

Index: 3rd_party/eigen/Eigen/Jacobi
==================================================================
--- 3rd_party/eigen/Eigen/Jacobi
+++ 3rd_party/eigen/Eigen/Jacobi
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_JACOBI_MODULE_H
 #define EIGEN_JACOBI_MODULE_H
 
 #include "Core"
 

Index: 3rd_party/eigen/Eigen/LU
==================================================================
--- 3rd_party/eigen/Eigen/LU
+++ 3rd_party/eigen/Eigen/LU
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_LU_MODULE_H
 #define EIGEN_LU_MODULE_H
 
 #include "Core"
 
@@ -14,28 +21,26 @@
   * \code
   * #include <Eigen/LU>
   * \endcode
   */
 
-#include "src/misc/Solve.h"
 #include "src/misc/Kernel.h"
 #include "src/misc/Image.h"
 #include "src/LU/FullPivLU.h"
 #include "src/LU/PartialPivLU.h"
 #ifdef EIGEN_USE_LAPACKE
-#include "src/LU/PartialPivLU_MKL.h"
+#include "src/misc/lapacke.h"
+#include "src/LU/PartialPivLU_LAPACKE.h"
 #endif
 #include "src/LU/Determinant.h"
-#include "src/LU/Inverse.h"
-
-#if defined EIGEN_VECTORIZE_SSE
-  #include "src/LU/arch/Inverse_SSE.h"
-#endif
-
-#ifdef EIGEN2_SUPPORT
-  #include "src/Eigen2Support/LU.h"
+#include "src/LU/InverseImpl.h"
+
+// Use the SSE optimized version whenever possible. At the moment the
+// SSE version doesn't compile when AVX is enabled
+#if defined EIGEN_VECTORIZE_SSE && !defined EIGEN_VECTORIZE_AVX
+  #include "src/LU/arch/Inverse_SSE.h"
 #endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_LU_MODULE_H
 /* vim: set filetype=cpp et sw=2 ts=2 ai: */

DELETED 3rd_party/eigen/Eigen/LeastSquares
Index: 3rd_party/eigen/Eigen/LeastSquares
==================================================================
--- 3rd_party/eigen/Eigen/LeastSquares
+++ 3rd_party/eigen/Eigen/LeastSquares
@@ -1,32 +0,0 @@
-#ifndef EIGEN_REGRESSION_MODULE_H
-#define EIGEN_REGRESSION_MODULE_H
-
-#ifndef EIGEN2_SUPPORT
-#error LeastSquares is only available in Eigen2 support mode (define EIGEN2_SUPPORT)
-#endif
-
-// exclude from normal eigen3-only documentation
-#ifdef EIGEN2_SUPPORT
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include "Eigenvalues"
-#include "Geometry"
-
-/** \defgroup LeastSquares_Module LeastSquares module
-  * This module provides linear regression and related features.
-  *
-  * \code
-  * #include <Eigen/LeastSquares>
-  * \endcode
-  */
-
-#include "src/Eigen2Support/LeastSquares.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN2_SUPPORT
-
-#endif // EIGEN_REGRESSION_MODULE_H

Index: 3rd_party/eigen/Eigen/MetisSupport
==================================================================
--- 3rd_party/eigen/Eigen/MetisSupport
+++ 3rd_party/eigen/Eigen/MetisSupport
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_METISSUPPORT_MODULE_H
 #define EIGEN_METISSUPPORT_MODULE_H
 
 #include "SparseCore"
 

Index: 3rd_party/eigen/Eigen/OrderingMethods
==================================================================
--- 3rd_party/eigen/Eigen/OrderingMethods
+++ 3rd_party/eigen/Eigen/OrderingMethods
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_ORDERINGMETHODS_MODULE_H
 #define EIGEN_ORDERINGMETHODS_MODULE_H
 
 #include "SparseCore"
 

Index: 3rd_party/eigen/Eigen/PaStiXSupport
==================================================================
--- 3rd_party/eigen/Eigen/PaStiXSupport
+++ 3rd_party/eigen/Eigen/PaStiXSupport
@@ -1,13 +1,19 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_PASTIXSUPPORT_MODULE_H
 #define EIGEN_PASTIXSUPPORT_MODULE_H
 
 #include "SparseCore"
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-#include <complex.h>
 extern "C" {
 #include <pastix_nompi.h>
 #include <pastix.h>
 }
 
@@ -33,14 +39,10 @@
   * The dependencies depend on how PaSTiX has been compiled.
   * For a cmake based project, you can use our FindPaSTiX.cmake module to help you in this task.
   *
   */
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
 #include "src/PaStiXSupport/PaStiXSupport.h"
-
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_PASTIXSUPPORT_MODULE_H

Index: 3rd_party/eigen/Eigen/PardisoSupport
==================================================================
--- 3rd_party/eigen/Eigen/PardisoSupport
+++ 3rd_party/eigen/Eigen/PardisoSupport
@@ -1,16 +1,21 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_PARDISOSUPPORT_MODULE_H
 #define EIGEN_PARDISOSUPPORT_MODULE_H
 
 #include "SparseCore"
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
 #include <mkl_pardiso.h>
 
-#include <unsupported/Eigen/SparseExtra>
-
 /** \ingroup Support_modules
   * \defgroup PardisoSupport_Module PardisoSupport module
   *
   * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers.
   *

Index: 3rd_party/eigen/Eigen/QR
==================================================================
--- 3rd_party/eigen/Eigen/QR
+++ 3rd_party/eigen/Eigen/QR
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_QR_MODULE_H
 #define EIGEN_QR_MODULE_H
 
 #include "Core"
 
@@ -13,33 +20,28 @@
   *
   *
   *
   * This module provides various QR decompositions
   * This module also provides some MatrixBase methods, including:
-  *  - MatrixBase::qr(),
+  *  - MatrixBase::householderQr()
+  *  - MatrixBase::colPivHouseholderQr()
+  *  - MatrixBase::fullPivHouseholderQr()
   *
   * \code
   * #include <Eigen/QR>
   * \endcode
   */
 
-#include "src/misc/Solve.h"
 #include "src/QR/HouseholderQR.h"
 #include "src/QR/FullPivHouseholderQR.h"
 #include "src/QR/ColPivHouseholderQR.h"
+#include "src/QR/CompleteOrthogonalDecomposition.h"
 #ifdef EIGEN_USE_LAPACKE
-#include "src/QR/HouseholderQR_MKL.h"
-#include "src/QR/ColPivHouseholderQR_MKL.h"
-#endif
-
-#ifdef EIGEN2_SUPPORT
-#include "src/Eigen2Support/QR.h"
+#include "src/misc/lapacke.h"
+#include "src/QR/HouseholderQR_LAPACKE.h"
+#include "src/QR/ColPivHouseholderQR_LAPACKE.h"
 #endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#ifdef EIGEN2_SUPPORT
-#include "Eigenvalues"
-#endif
-
 #endif // EIGEN_QR_MODULE_H
 /* vim: set filetype=cpp et sw=2 ts=2 ai: */

Index: 3rd_party/eigen/Eigen/QtAlignedMalloc
==================================================================
--- 3rd_party/eigen/Eigen/QtAlignedMalloc
+++ 3rd_party/eigen/Eigen/QtAlignedMalloc
@@ -1,5 +1,11 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_QTMALLOC_MODULE_H
 #define EIGEN_QTMALLOC_MODULE_H
 
 #include "Core"
@@ -6,21 +12,21 @@
 
 #if (!EIGEN_MALLOC_ALREADY_ALIGNED)
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-void *qMalloc(size_t size)
+void *qMalloc(std::size_t size)
 {
   return Eigen::internal::aligned_malloc(size);
 }
 
 void qFree(void *ptr)
 {
   Eigen::internal::aligned_free(ptr);
 }
 
-void *qRealloc(void *ptr, size_t size)
+void *qRealloc(void *ptr, std::size_t size)
 {
   void* newPtr = Eigen::internal::aligned_malloc(size);
   memcpy(newPtr, ptr, size);
   Eigen::internal::aligned_free(ptr);
   return newPtr;

Index: 3rd_party/eigen/Eigen/SPQRSupport
==================================================================
--- 3rd_party/eigen/Eigen/SPQRSupport
+++ 3rd_party/eigen/Eigen/SPQRSupport
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_SPQRSUPPORT_MODULE_H
 #define EIGEN_SPQRSUPPORT_MODULE_H
 
 #include "SparseCore"
 
@@ -8,11 +15,11 @@
 #include "SuiteSparseQR.hpp"
 
 /** \ingroup Support_modules
   * \defgroup SPQRSupport_Module SuiteSparseQR module
   * 
-  * This module provides an interface to the SPQR library, which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  * This module provides an interface to the SPQR library, which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
   *
   * \code
   * #include <Eigen/SPQRSupport>
   * \endcode
   *
@@ -19,11 +26,9 @@
   * In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...).
   * For a cmake based project, you can use our FindSPQR.cmake and FindCholmod.Cmake modules
   *
   */
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
 #include "src/CholmodSupport/CholmodSupport.h"
 #include "src/SPQRSupport/SuiteSparseQRSupport.h"
 
 #endif

Index: 3rd_party/eigen/Eigen/SVD
==================================================================
--- 3rd_party/eigen/Eigen/SVD
+++ 3rd_party/eigen/Eigen/SVD
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_SVD_MODULE_H
 #define EIGEN_SVD_MODULE_H
 
 #include "QR"
 #include "Householder"
@@ -10,28 +17,31 @@
 /** \defgroup SVD_Module SVD module
   *
   *
   *
   * This module provides SVD decomposition for matrices (both real and complex).
-  * This decomposition is accessible via the following MatrixBase method:
+  * Two decomposition algorithms are provided:
+  *  - JacobiSVD implementing two-sided Jacobi iterations is numerically very accurate, fast for small matrices, but very slow for larger ones.
+  *  - BDCSVD implementing a recursive divide & conquer strategy on top of an upper-bidiagonalization which remains fast for large problems.
+  * These decompositions are accessible via the respective classes and following MatrixBase methods:
   *  - MatrixBase::jacobiSvd()
+  *  - MatrixBase::bdcSvd()
   *
   * \code
   * #include <Eigen/SVD>
   * \endcode
   */
 
-#include "src/misc/Solve.h"
+#include "src/misc/RealSvd2x2.h"
+#include "src/SVD/UpperBidiagonalization.h"
+#include "src/SVD/SVDBase.h"
 #include "src/SVD/JacobiSVD.h"
+#include "src/SVD/BDCSVD.h"
 #if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
-#include "src/SVD/JacobiSVD_MKL.h"
-#endif
-#include "src/SVD/UpperBidiagonalization.h"
-
-#ifdef EIGEN2_SUPPORT
-#include "src/Eigen2Support/SVD.h"
+#include "src/misc/lapacke.h"
+#include "src/SVD/JacobiSVD_LAPACKE.h"
 #endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_SVD_MODULE_H
 /* vim: set filetype=cpp et sw=2 ts=2 ai: */

Index: 3rd_party/eigen/Eigen/Sparse
==================================================================
--- 3rd_party/eigen/Eigen/Sparse
+++ 3rd_party/eigen/Eigen/Sparse
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_SPARSE_MODULE_H
 #define EIGEN_SPARSE_MODULE_H
 
 /** \defgroup Sparse_Module Sparse meta-module
   *
@@ -9,19 +16,21 @@
   * - \ref SparseCholesky_Module
   * - \ref SparseLU_Module
   * - \ref SparseQR_Module
   * - \ref IterativeLinearSolvers_Module
   *
-  * \code
-  * #include <Eigen/Sparse>
-  * \endcode
+    \code
+    #include <Eigen/Sparse>
+    \endcode
   */
 
 #include "SparseCore"
 #include "OrderingMethods"
+#ifndef EIGEN_MPL2_ONLY
 #include "SparseCholesky"
+#endif
 #include "SparseLU"
 #include "SparseQR"
 #include "IterativeLinearSolvers"
 
 #endif // EIGEN_SPARSE_MODULE_H
 

Index: 3rd_party/eigen/Eigen/SparseCholesky
==================================================================
--- 3rd_party/eigen/Eigen/SparseCholesky
+++ 3rd_party/eigen/Eigen/SparseCholesky
@@ -32,16 +32,14 @@
 
 #ifdef EIGEN_MPL2_ONLY
 #error The SparseCholesky module has nothing to offer in MPL2 only mode
 #endif
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
 #include "src/SparseCholesky/SimplicialCholesky.h"
 
 #ifndef EIGEN_MPL2_ONLY
 #include "src/SparseCholesky/SimplicialCholesky_impl.h"
 #endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_SPARSECHOLESKY_MODULE_H

Index: 3rd_party/eigen/Eigen/SparseCore
==================================================================
--- 3rd_party/eigen/Eigen/SparseCore
+++ 3rd_party/eigen/Eigen/SparseCore
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_SPARSECORE_MODULE_H
 #define EIGEN_SPARSECORE_MODULE_H
 
 #include "Core"
 
@@ -12,11 +19,11 @@
 #include <algorithm>
 
 /** 
   * \defgroup SparseCore_Module SparseCore module
   *
-  * This module provides a sparse matrix representation, and basic associatd matrix manipulations
+  * This module provides a sparse matrix representation, and basic associated matrix manipulations
   * and operations.
   *
   * See the \ref TutorialSparse "Sparse tutorial"
   *
   * \code
@@ -24,41 +31,39 @@
   * \endcode
   *
   * This module depends on: Core.
   */
 
-namespace Eigen {
-
-/** The type used to identify a general sparse storage. */
-struct Sparse {};
-
-}
-
 #include "src/SparseCore/SparseUtil.h"
 #include "src/SparseCore/SparseMatrixBase.h"
+#include "src/SparseCore/SparseAssign.h"
 #include "src/SparseCore/CompressedStorage.h"
 #include "src/SparseCore/AmbiVector.h"
+#include "src/SparseCore/SparseCompressedBase.h"
 #include "src/SparseCore/SparseMatrix.h"
+#include "src/SparseCore/SparseMap.h"
 #include "src/SparseCore/MappedSparseMatrix.h"
 #include "src/SparseCore/SparseVector.h"
-#include "src/SparseCore/SparseBlock.h"
-#include "src/SparseCore/SparseTranspose.h"
+#include "src/SparseCore/SparseRef.h"
 #include "src/SparseCore/SparseCwiseUnaryOp.h"
 #include "src/SparseCore/SparseCwiseBinaryOp.h"
+#include "src/SparseCore/SparseTranspose.h"
+#include "src/SparseCore/SparseBlock.h"
 #include "src/SparseCore/SparseDot.h"
-#include "src/SparseCore/SparsePermutation.h"
 #include "src/SparseCore/SparseRedux.h"
-#include "src/SparseCore/SparseFuzzy.h"
+#include "src/SparseCore/SparseView.h"
+#include "src/SparseCore/SparseDiagonalProduct.h"
 #include "src/SparseCore/ConservativeSparseSparseProduct.h"
 #include "src/SparseCore/SparseSparseProductWithPruning.h"
 #include "src/SparseCore/SparseProduct.h"
 #include "src/SparseCore/SparseDenseProduct.h"
-#include "src/SparseCore/SparseDiagonalProduct.h"
+#include "src/SparseCore/SparseSelfAdjointView.h"
 #include "src/SparseCore/SparseTriangularView.h"
-#include "src/SparseCore/SparseSelfAdjointView.h"
 #include "src/SparseCore/TriangularSolver.h"
-#include "src/SparseCore/SparseView.h"
+#include "src/SparseCore/SparsePermutation.h"
+#include "src/SparseCore/SparseFuzzy.h"
+#include "src/SparseCore/SparseSolverBase.h"
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_SPARSECORE_MODULE_H
 

Index: 3rd_party/eigen/Eigen/SparseLU
==================================================================
--- 3rd_party/eigen/Eigen/SparseLU
+++ 3rd_party/eigen/Eigen/SparseLU
@@ -18,13 +18,10 @@
   * This module defines a supernodal factorization of general sparse matrices.
   * The code is fully optimized for supernode-panel updates with specialized kernels.
   * Please, see the documentation of the SparseLU class for more details.
   */
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
 // Ordering interface
 #include "OrderingMethods"
 
 #include "src/SparseLU/SparseLU_gemm_kernel.h"
 

Index: 3rd_party/eigen/Eigen/SparseQR
==================================================================
--- 3rd_party/eigen/Eigen/SparseQR
+++ 3rd_party/eigen/Eigen/SparseQR
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_SPARSEQR_MODULE_H
 #define EIGEN_SPARSEQR_MODULE_H
 
 #include "SparseCore"
 #include "OrderingMethods"
@@ -19,15 +26,12 @@
   * \endcode
   * 
   * 
   */
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
 #include "OrderingMethods"
 #include "src/SparseCore/SparseColEtree.h"
 #include "src/SparseQR/SparseQR.h"
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif

Index: 3rd_party/eigen/Eigen/StdDeque
==================================================================
--- 3rd_party/eigen/Eigen/StdDeque
+++ 3rd_party/eigen/Eigen/StdDeque
@@ -12,11 +12,11 @@
 #define EIGEN_STDDEQUE_MODULE_H
 
 #include "Core"
 #include <deque>
 
-#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
+#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
 
 #define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)
 
 #else
 

Index: 3rd_party/eigen/Eigen/StdList
==================================================================
--- 3rd_party/eigen/Eigen/StdList
+++ 3rd_party/eigen/Eigen/StdList
@@ -11,11 +11,11 @@
 #define EIGEN_STDLIST_MODULE_H
 
 #include "Core"
 #include <list>
 
-#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */    
+#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
 
 #define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)
 
 #else
 

Index: 3rd_party/eigen/Eigen/StdVector
==================================================================
--- 3rd_party/eigen/Eigen/StdVector
+++ 3rd_party/eigen/Eigen/StdVector
@@ -12,11 +12,11 @@
 #define EIGEN_STDVECTOR_MODULE_H
 
 #include "Core"
 #include <vector>
 
-#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
+#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
 
 #define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)
 
 #else
 

Index: 3rd_party/eigen/Eigen/SuperLUSupport
==================================================================
--- 3rd_party/eigen/Eigen/SuperLUSupport
+++ 3rd_party/eigen/Eigen/SuperLUSupport
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_SUPERLUSUPPORT_MODULE_H
 #define EIGEN_SUPERLUSUPPORT_MODULE_H
 
 #include "SparseCore"
 
@@ -33,10 +40,12 @@
   *
   * This module provides an interface to the <a href="http://crd-legacy.lbl.gov/~xiaoye/SuperLU/">SuperLU</a> library.
   * It provides the following factorization class:
   * - class SuperLU: a supernodal sequential LU factorization.
   * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative methods).
+  *
+  * \warning This wrapper requires at least versions 4.0 of SuperLU. The 3.x versions are not supported.
   *
   * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting.
   *
   * \code
   * #include <Eigen/SuperLUSupport>
@@ -46,14 +55,10 @@
   * The dependencies depend on how superlu has been compiled.
   * For a cmake based project, you can use our FindSuperLU.cmake module to help you in this task.
   *
   */
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
 #include "src/SuperLUSupport/SuperLUSupport.h"
-
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_SUPERLUSUPPORT_MODULE_H

Index: 3rd_party/eigen/Eigen/UmfPackSupport
==================================================================
--- 3rd_party/eigen/Eigen/UmfPackSupport
+++ 3rd_party/eigen/Eigen/UmfPackSupport
@@ -1,5 +1,12 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_UMFPACKSUPPORT_MODULE_H
 #define EIGEN_UMFPACKSUPPORT_MODULE_H
 
 #include "SparseCore"
 
@@ -10,11 +17,11 @@
 }
 
 /** \ingroup Support_modules
   * \defgroup UmfPackSupport_Module UmfPackSupport module
   *
-  * This module provides an interface to the UmfPack library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  * This module provides an interface to the UmfPack library which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
   * It provides the following factorization class:
   * - class UmfPackLU: a multifrontal sequential LU factorization.
   *
   * \code
   * #include <Eigen/UmfPackSupport>
@@ -24,13 +31,10 @@
   * The dependencies depend on how umfpack has been compiled.
   * For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task.
   *
   */
 
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
 #include "src/UmfPackSupport/UmfPackSupport.h"
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_UMFPACKSUPPORT_MODULE_H

DELETED 3rd_party/eigen/Eigen/src/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/CMakeLists.txt
@@ -1,7 +0,0 @@
-file(GLOB Eigen_src_subdirectories "*")
-escape_string_as_regex(ESCAPED_CMAKE_CURRENT_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
-foreach(f ${Eigen_src_subdirectories})
-  if(NOT f MATCHES "\\.txt" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/[.].+" )
-    add_subdirectory(${f})
-  endif()
-endforeach()

DELETED 3rd_party/eigen/Eigen/src/Cholesky/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Cholesky/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Cholesky/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Cholesky/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Cholesky_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Cholesky_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Cholesky COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/Cholesky/LDLT.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Cholesky/LDLT.h
+++ 3rd_party/eigen/Eigen/src/Cholesky/LDLT.h
@@ -11,11 +11,11 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_LDLT_H
 #define EIGEN_LDLT_H
 
-namespace Eigen { 
+namespace Eigen {
 
 namespace internal {
   template<typename MatrixType, int UpLo> struct LDLT_Traits;
 
   // PositiveSemiDef means positive semi-definite and non-zero; same for NegativeSemiDef
@@ -26,12 +26,12 @@
   *
   * \class LDLT
   *
   * \brief Robust Cholesky decomposition of a matrix with pivoting
   *
-  * \param MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition
-  * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
+  * \tparam _MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition
+  * \tparam _UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
   *             The other triangular part won't be read.
   *
   * Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite
   * matrix \f$ A \f$ such that \f$ A =  P^TLDL^*P \f$, where P is a permutation matrix, L
   * is lower triangular with a unit diagonal and D is a diagonal matrix.
@@ -41,28 +41,30 @@
   * on D also stabilizes the computation.
   *
   * Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky
   * decomposition to determine whether a system of equations has a solution.
   *
-  * \sa MatrixBase::ldlt(), class LLT
+  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
+  * 
+  * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt(), class LLT
   */
 template<typename _MatrixType, int _UpLo> class LDLT
 {
   public:
     typedef _MatrixType MatrixType;
     enum {
       RowsAtCompileTime = MatrixType::RowsAtCompileTime,
       ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      Options = MatrixType::Options & ~RowMajorBit, // these are the options for the TmpMatrixType, we need a ColMajor matrix here!
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
       UpLo = _UpLo
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
-    typedef Matrix<Scalar, RowsAtCompileTime, 1, Options, MaxRowsAtCompileTime, 1> TmpMatrixType;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    typedef Matrix<Scalar, RowsAtCompileTime, 1, 0, MaxRowsAtCompileTime, 1> TmpMatrixType;
 
     typedef Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> TranspositionType;
     typedef PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> PermutationType;
 
     typedef internal::LDLT_Traits<MatrixType,UpLo> Traits;
@@ -70,24 +72,24 @@
     /** \brief Default Constructor.
       *
       * The default constructor is useful in cases in which the user intends to
       * perform decompositions via LDLT::compute(const MatrixType&).
       */
-    LDLT() 
-      : m_matrix(), 
-        m_transpositions(), 
+    LDLT()
+      : m_matrix(),
+        m_transpositions(),
         m_sign(internal::ZeroSign),
-        m_isInitialized(false) 
+        m_isInitialized(false)
     {}
 
     /** \brief Default Constructor with memory preallocation
       *
       * Like the default constructor but with preallocation of the internal data
       * according to the specified problem \a size.
       * \sa LDLT()
       */
-    LDLT(Index size)
+    explicit LDLT(Index size)
       : m_matrix(size, size),
         m_transpositions(size),
         m_temporary(size),
         m_sign(internal::ZeroSign),
         m_isInitialized(false)
@@ -94,20 +96,39 @@
     {}
 
     /** \brief Constructor with decomposition
       *
       * This calculates the decomposition for the input \a matrix.
+      *
       * \sa LDLT(Index size)
       */
-    LDLT(const MatrixType& matrix)
+    template<typename InputType>
+    explicit LDLT(const EigenBase<InputType>& matrix)
       : m_matrix(matrix.rows(), matrix.cols()),
         m_transpositions(matrix.rows()),
         m_temporary(matrix.rows()),
         m_sign(internal::ZeroSign),
         m_isInitialized(false)
     {
-      compute(matrix);
+      compute(matrix.derived());
+    }
+
+    /** \brief Constructs a LDLT factorization from a given matrix
+      *
+      * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when \c MatrixType is a Eigen::Ref.
+      *
+      * \sa LDLT(const EigenBase&)
+      */
+    template<typename InputType>
+    explicit LDLT(EigenBase<InputType>& matrix)
+      : m_matrix(matrix.derived()),
+        m_transpositions(matrix.rows()),
+        m_temporary(matrix.rows()),
+        m_sign(internal::ZeroSign),
+        m_isInitialized(false)
+    {
+      compute(matrix.derived());
     }
 
     /** Clear any existing decomposition
      * \sa rankUpdate(w,sigma)
      */
@@ -149,17 +170,10 @@
     inline bool isPositive() const
     {
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
       return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign;
     }
-    
-    #ifdef EIGEN2_SUPPORT
-    inline bool isPositiveDefinite() const
-    {
-      return isPositive();
-    }
-    #endif
 
     /** \returns true if the matrix is negative (semidefinite) */
     inline bool isNegative(void) const
     {
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
@@ -171,41 +185,42 @@
       * This function also supports in-place solves using the syntax <tt>x = decompositionObject.solve(x)</tt> .
       *
       * \note_about_checking_solutions
       *
       * More precisely, this method solves \f$ A x = b \f$ using the decomposition \f$ A = P^T L D L^* P \f$
-      * by solving the systems \f$ P^T y_1 = b \f$, \f$ L y_2 = y_1 \f$, \f$ D y_3 = y_2 \f$, 
+      * by solving the systems \f$ P^T y_1 = b \f$, \f$ L y_2 = y_1 \f$, \f$ D y_3 = y_2 \f$,
       * \f$ L^* y_4 = y_3 \f$ and \f$ P x = y_4 \f$ in succession. If the matrix \f$ A \f$ is singular, then
       * \f$ D \f$ will also be singular (all the other matrices are invertible). In that case, the
       * least-square solution of \f$ D y_3 = y_2 \f$ is computed. This does not mean that this function
       * computes the least-square solution of \f$ A x = b \f$ is \f$ A \f$ is singular.
       *
-      * \sa MatrixBase::ldlt()
+      * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt()
       */
     template<typename Rhs>
-    inline const internal::solve_retval<LDLT, Rhs>
+    inline const Solve<LDLT, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
       eigen_assert(m_matrix.rows()==b.rows()
                 && "LDLT::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<LDLT, Rhs>(*this, b.derived());
-    }
-
-    #ifdef EIGEN2_SUPPORT
-    template<typename OtherDerived, typename ResultType>
-    bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
-    {
-      *result = this->solve(b);
-      return true;
-    }
-    #endif
+      return Solve<LDLT, Rhs>(*this, b.derived());
+    }
 
     template<typename Derived>
     bool solveInPlace(MatrixBase<Derived> &bAndX) const;
 
-    LDLT& compute(const MatrixType& matrix);
+    template<typename InputType>
+    LDLT& compute(const EigenBase<InputType>& matrix);
+
+    /** \returns an estimate of the reciprocal condition number of the matrix of
+     *  which \c *this is the LDLT decomposition.
+     */
+    RealScalar rcond() const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return internal::rcond_estimate_helper(m_l1_norm, *this);
+    }
 
     template <typename Derived>
     LDLT& rankUpdate(const MatrixBase<Derived>& w, const RealScalar& alpha=1);
 
     /** \returns the internal LDLT decomposition matrix
@@ -217,10 +232,17 @@
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
       return m_matrix;
     }
 
     MatrixType reconstructedMatrix() const;
+
+    /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix is self-adjoint.
+      *
+      * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as:
+      * \code x = decomposition.adjoint().solve(b) \endcode
+      */
+    const LDLT& adjoint() const { return *this; };
 
     inline Index rows() const { return m_matrix.rows(); }
     inline Index cols() const { return m_matrix.cols(); }
 
     /** \brief Reports whether previous computation was successful.
@@ -229,26 +251,39 @@
       *          \c NumericalIssue if the matrix.appears to be negative.
       */
     ComputationInfo info() const
     {
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return Success;
+      return m_info;
     }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl(const RhsType &rhs, DstType &dst) const;
+    #endif
 
   protected:
+
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
 
     /** \internal
       * Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U.
       * The strict upper part is used during the decomposition, the strict lower
       * part correspond to the coefficients of L (its diagonal is equal to 1 and
       * is not stored), and the diagonal entries correspond to D.
       */
     MatrixType m_matrix;
+    RealScalar m_l1_norm;
     TranspositionType m_transpositions;
     TmpMatrixType m_temporary;
     internal::SignMatrix m_sign;
     bool m_isInitialized;
+    ComputationInfo m_info;
 };
 
 namespace internal {
 
 template<int UpLo> struct ldlt_inplace;
@@ -259,19 +294,21 @@
   static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign)
   {
     using std::abs;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef typename TranspositionType::StorageIndex IndexType;
     eigen_assert(mat.rows()==mat.cols());
     const Index size = mat.rows();
+    bool found_zero_pivot = false;
+    bool ret = true;
 
     if (size <= 1)
     {
       transpositions.setIdentity();
-      if (numext::real(mat.coeff(0,0)) > 0) sign = PositiveSemiDef;
-      else if (numext::real(mat.coeff(0,0)) < 0) sign = NegativeSemiDef;
+      if (numext::real(mat.coeff(0,0)) > static_cast<RealScalar>(0) ) sign = PositiveSemiDef;
+      else if (numext::real(mat.coeff(0,0)) < static_cast<RealScalar>(0)) sign = NegativeSemiDef;
       else sign = ZeroSign;
       return true;
     }
 
     for (Index k = 0; k < size; ++k)
@@ -279,20 +316,20 @@
       // Find largest diagonal element
       Index index_of_biggest_in_corner;
       mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
       index_of_biggest_in_corner += k;
 
-      transpositions.coeffRef(k) = index_of_biggest_in_corner;
+      transpositions.coeffRef(k) = IndexType(index_of_biggest_in_corner);
       if(k != index_of_biggest_in_corner)
       {
         // apply the transposition while taking care to consider only
         // the lower triangular part
         Index s = size-index_of_biggest_in_corner-1; // trailing size after the biggest element
         mat.row(k).head(k).swap(mat.row(index_of_biggest_in_corner).head(k));
         mat.col(k).tail(s).swap(mat.col(index_of_biggest_in_corner).tail(s));
         std::swap(mat.coeffRef(k,k),mat.coeffRef(index_of_biggest_in_corner,index_of_biggest_in_corner));
-        for(int i=k+1;i<index_of_biggest_in_corner;++i)
+        for(Index i=k+1;i<index_of_biggest_in_corner;++i)
         {
           Scalar tmp = mat.coeffRef(i,k);
           mat.coeffRef(i,k) = numext::conj(mat.coeffRef(index_of_biggest_in_corner,i));
           mat.coeffRef(index_of_biggest_in_corner,i) = numext::conj(tmp);
         }
@@ -314,30 +351,48 @@
         temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint();
         mat.coeffRef(k,k) -= (A10 * temp.head(k)).value();
         if(rs>0)
           A21.noalias() -= A20 * temp.head(k);
       }
-      
+
       // In some previous versions of Eigen (e.g., 3.2.1), the scaling was omitted if the pivot
-      // was smaller than the cutoff value. However, soince LDLT is not rank-revealing
-      // we should only make sure we do not introduce INF or NaN values.
-      // LAPACK also uses 0 as the cutoff value.
+      // was smaller than the cutoff value. However, since LDLT is not rank-revealing
+      // we should only make sure that we do not introduce INF or NaN values.
+      // Remark that LAPACK also uses 0 as the cutoff value.
       RealScalar realAkk = numext::real(mat.coeffRef(k,k));
-      if((rs>0) && (abs(realAkk) > RealScalar(0)))
+      bool pivot_is_valid = (abs(realAkk) > RealScalar(0));
+
+      if(k==0 && !pivot_is_valid)
+      {
+        // The entire diagonal is zero, there is nothing more to do
+        // except filling the transpositions, and checking whether the matrix is zero.
+        sign = ZeroSign;
+        for(Index j = 0; j<size; ++j)
+        {
+          transpositions.coeffRef(j) = IndexType(j);
+          ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all();
+        }
+        return ret;
+      }
+
+      if((rs>0) && pivot_is_valid)
         A21 /= realAkk;
 
+      if(found_zero_pivot && pivot_is_valid) ret = false; // factorization failed
+      else if(!pivot_is_valid) found_zero_pivot = true;
+
       if (sign == PositiveSemiDef) {
-        if (realAkk < 0) sign = Indefinite;
+        if (realAkk < static_cast<RealScalar>(0)) sign = Indefinite;
       } else if (sign == NegativeSemiDef) {
-        if (realAkk > 0) sign = Indefinite;
+        if (realAkk > static_cast<RealScalar>(0)) sign = Indefinite;
       } else if (sign == ZeroSign) {
-        if (realAkk > 0) sign = PositiveSemiDef;
-        else if (realAkk < 0) sign = NegativeSemiDef;
+        if (realAkk > static_cast<RealScalar>(0)) sign = PositiveSemiDef;
+        else if (realAkk < static_cast<RealScalar>(0)) sign = NegativeSemiDef;
       }
     }
 
-    return true;
+    return ret;
   }
 
   // Reference for the algorithm: Davis and Hager, "Multiple Rank
   // Modifications of a Sparse Cholesky Factorization" (Algorithm 1)
   // Trivial rearrangements of their computations (Timothy E. Holy)
@@ -349,11 +404,10 @@
   static bool updateInPlace(MatrixType& mat, MatrixBase<WDerived>& w, const typename MatrixType::RealScalar& sigma=1)
   {
     using numext::isfinite;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
 
     const Index size = mat.rows();
     eigen_assert(mat.cols() == size && w.size()==size);
 
     RealScalar alpha = 1;
@@ -413,40 +467,56 @@
 
 template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower>
 {
   typedef const TriangularView<const MatrixType, UnitLower> MatrixL;
   typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m; }
-  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
+  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
 };
 
 template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
 {
   typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
   typedef const TriangularView<const MatrixType, UnitUpper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
-  static inline MatrixU getU(const MatrixType& m) { return m; }
+  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
+  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
 };
 
 } // end namespace internal
 
 /** Compute / recompute the LDLT decomposition A = L D L^* = U^* D U of \a matrix
   */
 template<typename MatrixType, int _UpLo>
-LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
+template<typename InputType>
+LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>& a)
 {
+  check_template_parameters();
+
   eigen_assert(a.rows()==a.cols());
   const Index size = a.rows();
 
-  m_matrix = a;
+  m_matrix = a.derived();
+
+  // Compute matrix L1 norm = max abs column sum.
+  m_l1_norm = RealScalar(0);
+  // TODO move this code to SelfAdjointView
+  for (Index col = 0; col < size; ++col) {
+    RealScalar abs_col_sum;
+    if (_UpLo == Lower)
+      abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
+    else
+      abs_col_sum = m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>();
+    if (abs_col_sum > m_l1_norm)
+      m_l1_norm = abs_col_sum;
+  }
 
   m_transpositions.resize(size);
   m_isInitialized = false;
   m_temporary.resize(size);
   m_sign = internal::ZeroSign;
 
-  internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign);
+  m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
 
   m_isInitialized = true;
   return *this;
 }
 
@@ -455,24 +525,25 @@
  * \param sigma a scalar, +1 for updates and -1 for "downdates," which correspond to removing previously-added column vectors. Optional; default value is +1.
  * \sa setZero()
   */
 template<typename MatrixType, int _UpLo>
 template<typename Derived>
-LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename NumTraits<typename MatrixType::Scalar>::Real& sigma)
+LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename LDLT<MatrixType,_UpLo>::RealScalar& sigma)
 {
+  typedef typename TranspositionType::StorageIndex IndexType;
   const Index size = w.rows();
   if (m_isInitialized)
   {
     eigen_assert(m_matrix.rows()==size);
   }
   else
-  {    
+  {
     m_matrix.resize(size,size);
     m_matrix.setZero();
     m_transpositions.resize(size);
     for (Index i = 0; i < size; i++)
-      m_transpositions.coeffRef(i) = i;
+      m_transpositions.coeffRef(i) = IndexType(i);
     m_temporary.resize(size);
     m_sign = sigma>=0 ? internal::PositiveSemiDef : internal::NegativeSemiDef;
     m_isInitialized = true;
   }
 
@@ -479,57 +550,49 @@
   internal::ldlt_inplace<UpLo>::update(m_matrix, m_transpositions, m_temporary, w, sigma);
 
   return *this;
 }
 
-namespace internal {
-template<typename _MatrixType, int _UpLo, typename Rhs>
-struct solve_retval<LDLT<_MatrixType,_UpLo>, Rhs>
-  : solve_retval_base<LDLT<_MatrixType,_UpLo>, Rhs>
-{
-  typedef LDLT<_MatrixType,_UpLo> LDLTType;
-  EIGEN_MAKE_SOLVE_HELPERS(LDLTType,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    eigen_assert(rhs().rows() == dec().matrixLDLT().rows());
-    // dst = P b
-    dst = dec().transpositionsP() * rhs();
-
-    // dst = L^-1 (P b)
-    dec().matrixL().solveInPlace(dst);
-
-    // dst = D^-1 (L^-1 P b)
-    // more precisely, use pseudo-inverse of D (see bug 241)
-    using std::abs;
-    using std::max;
-    typedef typename LDLTType::MatrixType MatrixType;
-    typedef typename LDLTType::RealScalar RealScalar;
-    const typename Diagonal<const MatrixType>::RealReturnType vectorD(dec().vectorD());
-    // In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
-    // as motivated by LAPACK's xGELSS:
-    // RealScalar tolerance = (max)(vectorD.array().abs().maxCoeff() *NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
-    // However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
-    // diagonal element is not well justified and to numerical issues in some cases.
-    // Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
-    RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
-    
-    for (Index i = 0; i < vectorD.size(); ++i) {
-      if(abs(vectorD(i)) > tolerance)
-        dst.row(i) /= vectorD(i);
-      else
-        dst.row(i).setZero();
-    }
-
-    // dst = L^-T (D^-1 L^-1 P b)
-    dec().matrixU().solveInPlace(dst);
-
-    // dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b
-    dst = dec().transpositionsP().transpose() * dst;
-  }
-};
-}
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename _MatrixType, int _UpLo>
+template<typename RhsType, typename DstType>
+void LDLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
+{
+  eigen_assert(rhs.rows() == rows());
+  // dst = P b
+  dst = m_transpositions * rhs;
+
+  // dst = L^-1 (P b)
+  matrixL().solveInPlace(dst);
+
+  // dst = D^-1 (L^-1 P b)
+  // more precisely, use pseudo-inverse of D (see bug 241)
+  using std::abs;
+  const typename Diagonal<const MatrixType>::RealReturnType vecD(vectorD());
+  // In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
+  // as motivated by LAPACK's xGELSS:
+  // RealScalar tolerance = numext::maxi(vecD.array().abs().maxCoeff() * NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
+  // However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
+  // diagonal element is not well justified and leads to numerical issues in some cases.
+  // Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
+  RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
+
+  for (Index i = 0; i < vecD.size(); ++i)
+  {
+    if(abs(vecD(i)) > tolerance)
+      dst.row(i) /= vecD(i);
+    else
+      dst.row(i).setZero();
+  }
+
+  // dst = L^-T (D^-1 L^-1 P b)
+  matrixU().solveInPlace(dst);
+
+  // dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b
+  dst = m_transpositions.transpose() * dst;
+}
+#endif
 
 /** \internal use x = ldlt_object.solve(x);
   *
   * This is the \em in-place version of solve().
   *
@@ -579,10 +642,11 @@
   return res;
 }
 
 /** \cholesky_module
   * \returns the Cholesky decomposition with full pivoting without square root of \c *this
+  * \sa MatrixBase::ldlt()
   */
 template<typename MatrixType, unsigned int UpLo>
 inline const LDLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
 SelfAdjointView<MatrixType, UpLo>::ldlt() const
 {
@@ -589,10 +653,11 @@
   return LDLT<PlainObject,UpLo>(m_matrix);
 }
 
 /** \cholesky_module
   * \returns the Cholesky decomposition with full pivoting without square root of \c *this
+  * \sa SelfAdjointView::ldlt()
   */
 template<typename Derived>
 inline const LDLT<typename MatrixBase<Derived>::PlainObject>
 MatrixBase<Derived>::ldlt() const
 {

Index: 3rd_party/eigen/Eigen/src/Cholesky/LLT.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Cholesky/LLT.h
+++ 3rd_party/eigen/Eigen/src/Cholesky/LLT.h
@@ -8,11 +8,11 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_LLT_H
 #define EIGEN_LLT_H
 
-namespace Eigen { 
+namespace Eigen {
 
 namespace internal{
 template<typename MatrixType, int UpLo> struct LLT_Traits;
 }
 
@@ -20,12 +20,12 @@
   *
   * \class LLT
   *
   * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features
   *
-  * \param MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition
-  * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
+  * \tparam _MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition
+  * \tparam _UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
   *             The other triangular part won't be read.
   *
   * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite
   * matrix A such that A = LL^* = U^*U, where L is lower triangular.
   *
@@ -38,12 +38,14 @@
   * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations
   * has a solution.
   *
   * Example: \include LLT_example.cpp
   * Output: \verbinclude LLT_example.out
-  *    
-  * \sa MatrixBase::llt(), class LDLT
+  *
+  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
+  *
+  * \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT
   */
  /* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH)
   * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
   * the strict lower part does not have to store correct values.
   */
@@ -52,16 +54,16 @@
   public:
     typedef _MatrixType MatrixType;
     enum {
       RowsAtCompileTime = MatrixType::RowsAtCompileTime,
       ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      Options = MatrixType::Options,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
+    typedef typename MatrixType::StorageIndex StorageIndex;
 
     enum {
       PacketSize = internal::packet_traits<Scalar>::size,
       AlignmentMask = int(PacketSize)-1,
       UpLo = _UpLo
@@ -81,18 +83,34 @@
       *
       * Like the default constructor but with preallocation of the internal data
       * according to the specified problem \a size.
       * \sa LLT()
       */
-    LLT(Index size) : m_matrix(size, size),
+    explicit LLT(Index size) : m_matrix(size, size),
                     m_isInitialized(false) {}
 
-    LLT(const MatrixType& matrix)
+    template<typename InputType>
+    explicit LLT(const EigenBase<InputType>& matrix)
       : m_matrix(matrix.rows(), matrix.cols()),
         m_isInitialized(false)
     {
-      compute(matrix);
+      compute(matrix.derived());
+    }
+
+    /** \brief Constructs a LDLT factorization from a given matrix
+      *
+      * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when
+      * \c MatrixType is a Eigen::Ref.
+      *
+      * \sa LLT(const EigenBase&)
+      */
+    template<typename InputType>
+    explicit LLT(EigenBase<InputType>& matrix)
+      : m_matrix(matrix.derived()),
+        m_isInitialized(false)
+    {
+      compute(matrix.derived());
     }
 
     /** \returns a view of the upper triangular matrix U */
     inline typename Traits::MatrixU matrixU() const
     {
@@ -113,37 +131,37 @@
       * theoretically exists and is unique regardless of b.
       *
       * Example: \include LLT_solve.cpp
       * Output: \verbinclude LLT_solve.out
       *
-      * \sa solveInPlace(), MatrixBase::llt()
+      * \sa solveInPlace(), MatrixBase::llt(), SelfAdjointView::llt()
       */
     template<typename Rhs>
-    inline const internal::solve_retval<LLT, Rhs>
+    inline const Solve<LLT, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
       eigen_assert(m_isInitialized && "LLT is not initialized.");
       eigen_assert(m_matrix.rows()==b.rows()
                 && "LLT::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<LLT, Rhs>(*this, b.derived());
-    }
-
-    #ifdef EIGEN2_SUPPORT
-    template<typename OtherDerived, typename ResultType>
-    bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
-    {
-      *result = this->solve(b);
-      return true;
-    }
-    
-    bool isPositiveDefinite() const { return true; }
-    #endif
+      return Solve<LLT, Rhs>(*this, b.derived());
+    }
 
     template<typename Derived>
     void solveInPlace(MatrixBase<Derived> &bAndX) const;
 
-    LLT& compute(const MatrixType& matrix);
+    template<typename InputType>
+    LLT& compute(const EigenBase<InputType>& matrix);
+
+    /** \returns an estimate of the reciprocal condition number of the matrix of
+      *  which \c *this is the Cholesky decomposition.
+      */
+    RealScalar rcond() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      eigen_assert(m_info == Success && "LLT failed because matrix appears to be negative");
+      return internal::rcond_estimate_helper(m_l1_norm, *this);
+    }
 
     /** \returns the LLT decomposition matrix
       *
       * TODO: document the storage layout
       */
@@ -164,38 +182,57 @@
     ComputationInfo info() const
     {
       eigen_assert(m_isInitialized && "LLT is not initialized.");
       return m_info;
     }
+
+    /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix is self-adjoint.
+      *
+      * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as:
+      * \code x = decomposition.adjoint().solve(b) \endcode
+      */
+    const LLT& adjoint() const { return *this; };
 
     inline Index rows() const { return m_matrix.rows(); }
     inline Index cols() const { return m_matrix.cols(); }
 
     template<typename VectorType>
     LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl(const RhsType &rhs, DstType &dst) const;
+    #endif
 
   protected:
+
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+
     /** \internal
       * Used to compute and store L
       * The strict upper part is not used and even not initialized.
       */
     MatrixType m_matrix;
+    RealScalar m_l1_norm;
     bool m_isInitialized;
     ComputationInfo m_info;
 };
 
 namespace internal {
 
 template<typename Scalar, int UpLo> struct llt_inplace;
 
 template<typename MatrixType, typename VectorType>
-static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
+static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
 {
   using std::sqrt;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::ColXpr ColXpr;
   typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
   typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
   typedef Matrix<Scalar,Dynamic,1> TempVectorType;
   typedef typename TempVectorType::SegmentReturnType TempVecSegment;
@@ -260,15 +297,14 @@
 
 template<typename Scalar> struct llt_inplace<Scalar, Lower>
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
   template<typename MatrixType>
-  static typename MatrixType::Index unblocked(MatrixType& mat)
+  static Index unblocked(MatrixType& mat)
   {
     using std::sqrt;
-    typedef typename MatrixType::Index Index;
-    
+
     eigen_assert(mat.rows()==mat.cols());
     const Index size = mat.rows();
     for(Index k = 0; k < size; ++k)
     {
       Index rs = size-k-1; // remaining size
@@ -281,19 +317,18 @@
       if (k>0) x -= A10.squaredNorm();
       if (x<=RealScalar(0))
         return k;
       mat.coeffRef(k,k) = x = sqrt(x);
       if (k>0 && rs>0) A21.noalias() -= A20 * A10.adjoint();
-      if (rs>0) A21 *= RealScalar(1)/x;
+      if (rs>0) A21 /= x;
     }
     return -1;
   }
 
   template<typename MatrixType>
-  static typename MatrixType::Index blocked(MatrixType& m)
+  static Index blocked(MatrixType& m)
   {
-    typedef typename MatrixType::Index Index;
     eigen_assert(m.rows()==m.cols());
     Index size = m.rows();
     if(size<32)
       return unblocked(m);
 
@@ -314,40 +349,40 @@
       Block<MatrixType,Dynamic,Dynamic> A22(m,k+bs,k+bs,rs,rs);
 
       Index ret;
       if((ret=unblocked(A11))>=0) return k+ret;
       if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
-      if(rs>0) A22.template selfadjointView<Lower>().rankUpdate(A21,-1); // bottleneck
+      if(rs>0) A22.template selfadjointView<Lower>().rankUpdate(A21,typename NumTraits<RealScalar>::Literal(-1)); // bottleneck
     }
     return -1;
   }
 
   template<typename MatrixType, typename VectorType>
-  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
+  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
   {
     return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
   }
 };
-  
+
 template<typename Scalar> struct llt_inplace<Scalar, Upper>
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
 
   template<typename MatrixType>
-  static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat)
+  static EIGEN_STRONG_INLINE Index unblocked(MatrixType& mat)
   {
     Transpose<MatrixType> matt(mat);
     return llt_inplace<Scalar, Lower>::unblocked(matt);
   }
   template<typename MatrixType>
-  static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat)
+  static EIGEN_STRONG_INLINE Index blocked(MatrixType& mat)
   {
     Transpose<MatrixType> matt(mat);
     return llt_inplace<Scalar, Lower>::blocked(matt);
   }
   template<typename MatrixType, typename VectorType>
-  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
+  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
   {
     Transpose<MatrixType> matt(mat);
     return llt_inplace<Scalar, Lower>::rankUpdate(matt, vec.conjugate(), sigma);
   }
 };
@@ -354,22 +389,22 @@
 
 template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
 {
   typedef const TriangularView<const MatrixType, Lower> MatrixL;
   typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m; }
-  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
+  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
   static bool inplace_decomposition(MatrixType& m)
   { return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
 };
 
 template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
 {
   typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
   typedef const TriangularView<const MatrixType, Upper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
-  static inline MatrixU getU(const MatrixType& m) { return m; }
+  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
+  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
   static bool inplace_decomposition(MatrixType& m)
   { return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m)==-1; }
 };
 
 } // end namespace internal
@@ -380,16 +415,32 @@
   *
   * Example: \include TutorialLinAlgComputeTwice.cpp
   * Output: \verbinclude TutorialLinAlgComputeTwice.out
   */
 template<typename MatrixType, int _UpLo>
-LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
+template<typename InputType>
+LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>& a)
 {
+  check_template_parameters();
+
   eigen_assert(a.rows()==a.cols());
   const Index size = a.rows();
   m_matrix.resize(size, size);
-  m_matrix = a;
+  m_matrix = a.derived();
+
+  // Compute matrix L1 norm = max abs column sum.
+  m_l1_norm = RealScalar(0);
+  // TODO move this code to SelfAdjointView
+  for (Index col = 0; col < size; ++col) {
+    RealScalar abs_col_sum;
+    if (_UpLo == Lower)
+      abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
+    else
+      abs_col_sum = m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>();
+    if (abs_col_sum > m_l1_norm)
+      m_l1_norm = abs_col_sum;
+  }
 
   m_isInitialized = true;
   bool ok = Traits::inplace_decomposition(m_matrix);
   m_info = ok ? Success : NumericalIssue;
 
@@ -413,37 +464,28 @@
   else
     m_info = Success;
 
   return *this;
 }
-    
-namespace internal {
-template<typename _MatrixType, int UpLo, typename Rhs>
-struct solve_retval<LLT<_MatrixType, UpLo>, Rhs>
-  : solve_retval_base<LLT<_MatrixType, UpLo>, Rhs>
-{
-  typedef LLT<_MatrixType,UpLo> LLTType;
-  EIGEN_MAKE_SOLVE_HELPERS(LLTType,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dst = rhs();
-    dec().solveInPlace(dst);
-  }
-};
-}
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename _MatrixType,int _UpLo>
+template<typename RhsType, typename DstType>
+void LLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
+{
+  dst = rhs;
+  solveInPlace(dst);
+}
+#endif
 
 /** \internal use x = llt_object.solve(x);
-  * 
+  *
   * This is the \em in-place version of solve().
   *
   * \param bAndX represents both the right-hand side matrix b and result x.
   *
-  * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD.
-  *
-  * This version avoids a copy when the right hand side matrix b is not
-  * needed anymore.
+  * This version avoids a copy when the right hand side matrix b is not needed anymore.
   *
   * \sa LLT::solve(), MatrixBase::llt()
   */
 template<typename MatrixType, int _UpLo>
 template<typename Derived>
@@ -465,10 +507,11 @@
   return matrixL() * matrixL().adjoint().toDenseMatrix();
 }
 
 /** \cholesky_module
   * \returns the LLT decomposition of \c *this
+  * \sa SelfAdjointView::llt()
   */
 template<typename Derived>
 inline const LLT<typename MatrixBase<Derived>::PlainObject>
 MatrixBase<Derived>::llt() const
 {
@@ -475,10 +518,11 @@
   return LLT<PlainObject>(derived());
 }
 
 /** \cholesky_module
   * \returns the LLT decomposition of \c *this
+  * \sa SelfAdjointView::llt()
   */
 template<typename MatrixType, unsigned int UpLo>
 inline const LLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
 SelfAdjointView<MatrixType, UpLo>::llt() const
 {

ADDED   3rd_party/eigen/Eigen/src/Cholesky/LLT_LAPACKE.h
Index: 3rd_party/eigen/Eigen/src/Cholesky/LLT_LAPACKE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Cholesky/LLT_LAPACKE.h
+++ 3rd_party/eigen/Eigen/src/Cholesky/LLT_LAPACKE.h
@@ -0,0 +1,99 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to LAPACKe
+ *     LLt decomposition based on LAPACKE_?potrf function.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_LLT_LAPACKE_H
+#define EIGEN_LLT_LAPACKE_H
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename Scalar> struct lapacke_llt;
+
+#define EIGEN_LAPACKE_LLT(EIGTYPE, BLASTYPE, LAPACKE_PREFIX) \
+template<> struct lapacke_llt<EIGTYPE> \
+{ \
+  template<typename MatrixType> \
+  static inline Index potrf(MatrixType& m, char uplo) \
+  { \
+    lapack_int matrix_order; \
+    lapack_int size, lda, info, StorageOrder; \
+    EIGTYPE* a; \
+    eigen_assert(m.rows()==m.cols()); \
+    /* Set up parameters for ?potrf */ \
+    size = convert_index<lapack_int>(m.rows()); \
+    StorageOrder = MatrixType::Flags&RowMajorBit?RowMajor:ColMajor; \
+    matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
+    a = &(m.coeffRef(0,0)); \
+    lda = convert_index<lapack_int>(m.outerStride()); \
+\
+    info = LAPACKE_##LAPACKE_PREFIX##potrf( matrix_order, uplo, size, (BLASTYPE*)a, lda ); \
+    info = (info==0) ? -1 : info>0 ? info-1 : size; \
+    return info; \
+  } \
+}; \
+template<> struct llt_inplace<EIGTYPE, Lower> \
+{ \
+  template<typename MatrixType> \
+  static Index blocked(MatrixType& m) \
+  { \
+    return lapacke_llt<EIGTYPE>::potrf(m, 'L'); \
+  } \
+  template<typename MatrixType, typename VectorType> \
+  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
+  { return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \
+}; \
+template<> struct llt_inplace<EIGTYPE, Upper> \
+{ \
+  template<typename MatrixType> \
+  static Index blocked(MatrixType& m) \
+  { \
+    return lapacke_llt<EIGTYPE>::potrf(m, 'U'); \
+  } \
+  template<typename MatrixType, typename VectorType> \
+  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
+  { \
+    Transpose<MatrixType> matt(mat); \
+    return llt_inplace<EIGTYPE, Lower>::rankUpdate(matt, vec.conjugate(), sigma); \
+  } \
+};
+
+EIGEN_LAPACKE_LLT(double, double, d)
+EIGEN_LAPACKE_LLT(float, float, s)
+EIGEN_LAPACKE_LLT(dcomplex, lapack_complex_double, z)
+EIGEN_LAPACKE_LLT(scomplex, lapack_complex_float, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_LLT_LAPACKE_H

DELETED 3rd_party/eigen/Eigen/src/Cholesky/LLT_MKL.h
Index: 3rd_party/eigen/Eigen/src/Cholesky/LLT_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Cholesky/LLT_MKL.h
+++ 3rd_party/eigen/Eigen/src/Cholesky/LLT_MKL.h
@@ -1,102 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *     LLt decomposition based on LAPACKE_?potrf function.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_LLT_MKL_H
-#define EIGEN_LLT_MKL_H
-
-#include "Eigen/src/Core/util/MKL_support.h"
-#include <iostream>
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename Scalar> struct mkl_llt;
-
-#define EIGEN_MKL_LLT(EIGTYPE, MKLTYPE, MKLPREFIX) \
-template<> struct mkl_llt<EIGTYPE> \
-{ \
-  template<typename MatrixType> \
-  static inline typename MatrixType::Index potrf(MatrixType& m, char uplo) \
-  { \
-    lapack_int matrix_order; \
-    lapack_int size, lda, info, StorageOrder; \
-    EIGTYPE* a; \
-    eigen_assert(m.rows()==m.cols()); \
-    /* Set up parameters for ?potrf */ \
-    size = m.rows(); \
-    StorageOrder = MatrixType::Flags&RowMajorBit?RowMajor:ColMajor; \
-    matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
-    a = &(m.coeffRef(0,0)); \
-    lda = m.outerStride(); \
-\
-    info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \
-    info = (info==0) ? Success : NumericalIssue; \
-    return info; \
-  } \
-}; \
-template<> struct llt_inplace<EIGTYPE, Lower> \
-{ \
-  template<typename MatrixType> \
-  static typename MatrixType::Index blocked(MatrixType& m) \
-  { \
-    return mkl_llt<EIGTYPE>::potrf(m, 'L'); \
-  } \
-  template<typename MatrixType, typename VectorType> \
-  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
-  { return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \
-}; \
-template<> struct llt_inplace<EIGTYPE, Upper> \
-{ \
-  template<typename MatrixType> \
-  static typename MatrixType::Index blocked(MatrixType& m) \
-  { \
-    return mkl_llt<EIGTYPE>::potrf(m, 'U'); \
-  } \
-  template<typename MatrixType, typename VectorType> \
-  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
-  { \
-    Transpose<MatrixType> matt(mat); \
-    return llt_inplace<EIGTYPE, Lower>::rankUpdate(matt, vec.conjugate(), sigma); \
-  } \
-};
-
-EIGEN_MKL_LLT(double, double, d)
-EIGEN_MKL_LLT(float, float, s)
-EIGEN_MKL_LLT(dcomplex, MKL_Complex16, z)
-EIGEN_MKL_LLT(scomplex, MKL_Complex8, c)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_LLT_MKL_H

DELETED 3rd_party/eigen/Eigen/src/CholmodSupport/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/CholmodSupport/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/CholmodSupport/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/CholmodSupport/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_CholmodSupport_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_CholmodSupport_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/CholmodSupport COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/CholmodSupport/CholmodSupport.h
==================================================================
--- 3rd_party/eigen/Eigen/src/CholmodSupport/CholmodSupport.h
+++ 3rd_party/eigen/Eigen/src/CholmodSupport/CholmodSupport.h
@@ -12,50 +12,56 @@
 
 namespace Eigen { 
 
 namespace internal {
 
-template<typename Scalar, typename CholmodType>
-void cholmod_configure_matrix(CholmodType& mat)
-{
-  if (internal::is_same<Scalar,float>::value)
-  {
-    mat.xtype = CHOLMOD_REAL;
-    mat.dtype = CHOLMOD_SINGLE;
-  }
-  else if (internal::is_same<Scalar,double>::value)
-  {
-    mat.xtype = CHOLMOD_REAL;
-    mat.dtype = CHOLMOD_DOUBLE;
-  }
-  else if (internal::is_same<Scalar,std::complex<float> >::value)
-  {
-    mat.xtype = CHOLMOD_COMPLEX;
-    mat.dtype = CHOLMOD_SINGLE;
-  }
-  else if (internal::is_same<Scalar,std::complex<double> >::value)
-  {
-    mat.xtype = CHOLMOD_COMPLEX;
-    mat.dtype = CHOLMOD_DOUBLE;
-  }
-  else
-  {
-    eigen_assert(false && "Scalar type not supported by CHOLMOD");
-  }
-}
+template<typename Scalar> struct cholmod_configure_matrix;
+
+template<> struct cholmod_configure_matrix<double> {
+  template<typename CholmodType>
+  static void run(CholmodType& mat) {
+    mat.xtype = CHOLMOD_REAL;
+    mat.dtype = CHOLMOD_DOUBLE;
+  }
+};
+
+template<> struct cholmod_configure_matrix<std::complex<double> > {
+  template<typename CholmodType>
+  static void run(CholmodType& mat) {
+    mat.xtype = CHOLMOD_COMPLEX;
+    mat.dtype = CHOLMOD_DOUBLE;
+  }
+};
+
+// Other scalar types are not yet suppotred by Cholmod
+// template<> struct cholmod_configure_matrix<float> {
+//   template<typename CholmodType>
+//   static void run(CholmodType& mat) {
+//     mat.xtype = CHOLMOD_REAL;
+//     mat.dtype = CHOLMOD_SINGLE;
+//   }
+// };
+//
+// template<> struct cholmod_configure_matrix<std::complex<float> > {
+//   template<typename CholmodType>
+//   static void run(CholmodType& mat) {
+//     mat.xtype = CHOLMOD_COMPLEX;
+//     mat.dtype = CHOLMOD_SINGLE;
+//   }
+// };
 
 } // namespace internal
 
 /** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object.
   * Note that the data are shared.
   */
-template<typename _Scalar, int _Options, typename _Index>
-cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat)
+template<typename _Scalar, int _Options, typename _StorageIndex>
+cholmod_sparse viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_StorageIndex> > mat)
 {
   cholmod_sparse res;
   res.nzmax   = mat.nonZeros();
-  res.nrow    = mat.rows();;
+  res.nrow    = mat.rows();
   res.ncol    = mat.cols();
   res.p       = mat.outerIndexPtr();
   res.i       = mat.innerIndexPtr();
   res.x       = mat.valuePtr();
   res.z       = 0;
@@ -72,44 +78,51 @@
   }
 
   res.dtype   = 0;
   res.stype   = -1;
   
-  if (internal::is_same<_Index,int>::value)
+  if (internal::is_same<_StorageIndex,int>::value)
   {
     res.itype = CHOLMOD_INT;
   }
-  else if (internal::is_same<_Index,UF_long>::value)
+  else if (internal::is_same<_StorageIndex,long>::value)
   {
     res.itype = CHOLMOD_LONG;
   }
   else
   {
     eigen_assert(false && "Index type not supported yet");
   }
 
   // setup res.xtype
-  internal::cholmod_configure_matrix<_Scalar>(res);
+  internal::cholmod_configure_matrix<_Scalar>::run(res);
   
   res.stype = 0;
   
   return res;
 }
 
 template<typename _Scalar, int _Options, typename _Index>
 const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>& mat)
 {
-  cholmod_sparse res = viewAsCholmod(mat.const_cast_derived());
+  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_Index> >(mat.const_cast_derived()));
+  return res;
+}
+
+template<typename _Scalar, int _Options, typename _Index>
+const cholmod_sparse viewAsCholmod(const SparseVector<_Scalar,_Options,_Index>& mat)
+{
+  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_Index> >(mat.const_cast_derived()));
   return res;
 }
 
 /** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix.
   * The data are not copied but shared. */
 template<typename _Scalar, int _Options, typename _Index, unsigned int UpLo>
-cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
+cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<const SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
 {
-  cholmod_sparse res = viewAsCholmod(mat.matrix().const_cast_derived());
+  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_Index> >(mat.matrix().const_cast_derived()));
   
   if(UpLo==Upper) res.stype =  1;
   if(UpLo==Lower) res.stype = -1;
 
   return res;
@@ -129,23 +142,23 @@
   res.nzmax  = res.nrow * res.ncol;
   res.d      = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride();
   res.x      = (void*)(mat.derived().data());
   res.z      = 0;
 
-  internal::cholmod_configure_matrix<Scalar>(res);
+  internal::cholmod_configure_matrix<Scalar>::run(res);
 
   return res;
 }
 
 /** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
   * The data are not copied but shared. */
-template<typename Scalar, int Flags, typename Index>
-MappedSparseMatrix<Scalar,Flags,Index> viewAsEigen(cholmod_sparse& cm)
+template<typename Scalar, int Flags, typename StorageIndex>
+MappedSparseMatrix<Scalar,Flags,StorageIndex> viewAsEigen(cholmod_sparse& cm)
 {
-  return MappedSparseMatrix<Scalar,Flags,Index>
-         (cm.nrow, cm.ncol, static_cast<Index*>(cm.p)[cm.ncol],
-          static_cast<Index*>(cm.p), static_cast<Index*>(cm.i),static_cast<Scalar*>(cm.x) );
+  return MappedSparseMatrix<Scalar,Flags,StorageIndex>
+         (cm.nrow, cm.ncol, static_cast<StorageIndex*>(cm.p)[cm.ncol],
+          static_cast<StorageIndex*>(cm.p), static_cast<StorageIndex*>(cm.i),static_cast<Scalar*>(cm.x) );
 }
 
 enum CholmodMode {
   CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt
 };
@@ -155,33 +168,43 @@
   * \class CholmodBase
   * \brief The base class for the direct Cholesky factorization of Cholmod
   * \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
   */
 template<typename _MatrixType, int _UpLo, typename Derived>
-class CholmodBase : internal::noncopyable
+class CholmodBase : public SparseSolverBase<Derived>
 {
+  protected:
+    typedef SparseSolverBase<Derived> Base;
+    using Base::derived;
+    using Base::m_isInitialized;
   public:
     typedef _MatrixType MatrixType;
     enum { UpLo = _UpLo };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
     typedef MatrixType CholMatrixType;
-    typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    enum {
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
 
   public:
 
     CholmodBase()
-      : m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
+      : m_cholmodFactor(0), m_info(Success), m_factorizationIsOk(false), m_analysisIsOk(false)
     {
-      m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
+      EIGEN_STATIC_ASSERT((internal::is_same<double,RealScalar>::value), CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY);
+      m_shiftOffset[0] = m_shiftOffset[1] = 0.0;
       cholmod_start(&m_cholmod);
     }
 
-    CholmodBase(const MatrixType& matrix)
-      : m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
+    explicit CholmodBase(const MatrixType& matrix)
+      : m_cholmodFactor(0), m_info(Success), m_factorizationIsOk(false), m_analysisIsOk(false)
     {
-      m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
+      EIGEN_STATIC_ASSERT((internal::is_same<double,RealScalar>::value), CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY);
+      m_shiftOffset[0] = m_shiftOffset[1] = 0.0;
       cholmod_start(&m_cholmod);
       compute(matrix);
     }
 
     ~CholmodBase()
@@ -189,15 +212,12 @@
       if(m_cholmodFactor)
         cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
       cholmod_finish(&m_cholmod);
     }
     
-    inline Index cols() const { return m_cholmodFactor->n; }
-    inline Index rows() const { return m_cholmodFactor->n; }
-    
-    Derived& derived() { return *static_cast<Derived*>(this); }
-    const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    inline StorageIndex cols() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
+    inline StorageIndex rows() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
     
     /** \brief Reports whether previous computation was successful.
       *
       * \returns \c Success if computation was succesful,
       *          \c NumericalIssue if the matrix.appears to be negative.
@@ -214,38 +234,10 @@
       analyzePattern(matrix);
       factorize(matrix);
       return derived();
     }
     
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<CholmodBase, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "LLT is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<CholmodBase, Rhs>(*this, b.derived());
-    }
-    
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::sparse_solve_retval<CholmodBase, Rhs>
-    solve(const SparseMatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "LLT is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::sparse_solve_retval<CholmodBase, Rhs>(*this, b.derived());
-    }
-    
     /** Performs a symbolic decomposition on the sparsity pattern of \a matrix.
       *
       * This function is particularly useful when solving for several problems having the same structure.
       * 
       * \sa factorize()
@@ -275,11 +267,11 @@
     void factorize(const MatrixType& matrix)
     {
       eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
       cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
       cholmod_factorize_p(&A, m_shiftOffset, 0, 0, m_cholmodFactor, &m_cholmod);
-      
+
       // If the factorization failed, minor is the column at which it did. On success minor == n.
       this->m_info = (m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue);
       m_factorizationIsOk = true;
     }
     
@@ -288,48 +280,52 @@
     cholmod_common& cholmod() { return m_cholmod; }
     
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** \internal */
     template<typename Rhs,typename Dest>
-    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
+    void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
     {
       eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
       const Index size = m_cholmodFactor->n;
       EIGEN_UNUSED_VARIABLE(size);
       eigen_assert(size==b.rows());
+      
+      // Cholmod needs column-major stoarge without inner-stride, which corresponds to the default behavior of Ref.
+      Ref<const Matrix<typename Rhs::Scalar,Dynamic,Dynamic,ColMajor> > b_ref(b.derived());
 
-      // note: cd stands for Cholmod Dense
-      Rhs& b_ref(b.const_cast_derived());
       cholmod_dense b_cd = viewAsCholmod(b_ref);
       cholmod_dense* x_cd = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &b_cd, &m_cholmod);
       if(!x_cd)
       {
         this->m_info = NumericalIssue;
+        return;
       }
       // TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
       dest = Matrix<Scalar,Dest::RowsAtCompileTime,Dest::ColsAtCompileTime>::Map(reinterpret_cast<Scalar*>(x_cd->x),b.rows(),b.cols());
       cholmod_free_dense(&x_cd, &m_cholmod);
     }
     
     /** \internal */
-    template<typename RhsScalar, int RhsOptions, typename RhsIndex, typename DestScalar, int DestOptions, typename DestIndex>
-    void _solve(const SparseMatrix<RhsScalar,RhsOptions,RhsIndex> &b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
+    template<typename RhsDerived, typename DestDerived>
+    void _solve_impl(const SparseMatrixBase<RhsDerived> &b, SparseMatrixBase<DestDerived> &dest) const
     {
       eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
       const Index size = m_cholmodFactor->n;
       EIGEN_UNUSED_VARIABLE(size);
       eigen_assert(size==b.rows());
 
       // note: cs stands for Cholmod Sparse
-      cholmod_sparse b_cs = viewAsCholmod(b);
+      Ref<SparseMatrix<typename RhsDerived::Scalar,ColMajor,typename RhsDerived::StorageIndex> > b_ref(b.const_cast_derived());
+      cholmod_sparse b_cs = viewAsCholmod(b_ref);
       cholmod_sparse* x_cs = cholmod_spsolve(CHOLMOD_A, m_cholmodFactor, &b_cs, &m_cholmod);
       if(!x_cs)
       {
         this->m_info = NumericalIssue;
+        return;
       }
       // TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
-      dest = viewAsEigen<DestScalar,DestOptions,DestIndex>(*x_cs);
+      dest.derived() = viewAsEigen<typename DestDerived::Scalar,ColMajor,typename DestDerived::StorageIndex>(*x_cs);
       cholmod_free_sparse(&x_cs, &m_cholmod);
     }
     #endif // EIGEN_PARSED_BY_DOXYGEN
     
     
@@ -342,24 +338,74 @@
       *
       * \returns a reference to \c *this.
       */
     Derived& setShift(const RealScalar& offset)
     {
-      m_shiftOffset[0] = offset;
+      m_shiftOffset[0] = double(offset);
       return derived();
     }
     
+    /** \returns the determinant of the underlying matrix from the current factorization */
+    Scalar determinant() const
+    {
+      using std::exp;
+      return exp(logDeterminant());
+    }
+
+    /** \returns the log determinant of the underlying matrix from the current factorization */
+    Scalar logDeterminant() const
+    {
+      using std::log;
+      using numext::real;
+      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+
+      RealScalar logDet = 0;
+      Scalar *x = static_cast<Scalar*>(m_cholmodFactor->x);
+      if (m_cholmodFactor->is_super)
+      {
+        // Supernodal factorization stored as a packed list of dense column-major blocs,
+        // as described by the following structure:
+
+        // super[k] == index of the first column of the j-th super node
+        StorageIndex *super = static_cast<StorageIndex*>(m_cholmodFactor->super);
+        // pi[k] == offset to the description of row indices
+        StorageIndex *pi = static_cast<StorageIndex*>(m_cholmodFactor->pi);
+        // px[k] == offset to the respective dense block
+        StorageIndex *px = static_cast<StorageIndex*>(m_cholmodFactor->px);
+
+        Index nb_super_nodes = m_cholmodFactor->nsuper;
+        for (Index k=0; k < nb_super_nodes; ++k)
+        {
+          StorageIndex ncols = super[k + 1] - super[k];
+          StorageIndex nrows = pi[k + 1] - pi[k];
+
+          Map<const Array<Scalar,1,Dynamic>, 0, InnerStride<> > sk(x + px[k], ncols, InnerStride<>(nrows+1));
+          logDet += sk.real().log().sum();
+        }
+      }
+      else
+      {
+        // Simplicial factorization stored as standard CSC matrix.
+        StorageIndex *p = static_cast<StorageIndex*>(m_cholmodFactor->p);
+        Index size = m_cholmodFactor->n;
+        for (Index k=0; k<size; ++k)
+          logDet += log(real( x[p[k]] ));
+      }
+      if (m_cholmodFactor->is_ll)
+        logDet *= 2.0;
+      return logDet;
+    };
+
     template<typename Stream>
     void dumpMemory(Stream& /*s*/)
     {}
     
   protected:
     mutable cholmod_common m_cholmod;
     cholmod_factor* m_cholmodFactor;
-    RealScalar m_shiftOffset[2];
+    double m_shiftOffset[2];
     mutable ComputationInfo m_info;
-    bool m_isInitialized;
     int m_factorizationIsOk;
     int m_analysisIsOk;
 };
 
 /** \ingroup CholmodSupport_Module
@@ -373,14 +419,18 @@
   * X and B can be either dense or sparse.
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
+  *
+  * \implsparsesolverconcept
   *
   * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
   *
-  * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLLT
+  * \warning Only double precision real and complex scalar types are supported by Cholmod.
+  *
+  * \sa \ref TutorialSparseSolverConcept, class CholmodSupernodalLLT, class SimplicialLLT
   */
 template<typename _MatrixType, int _UpLo = Lower>
 class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT<_MatrixType, _UpLo> >
 {
     typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT> Base;
@@ -393,11 +443,11 @@
     CholmodSimplicialLLT() : Base() { init(); }
 
     CholmodSimplicialLLT(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      this->compute(matrix);
     }
 
     ~CholmodSimplicialLLT() {}
   protected:
     void init()
@@ -420,14 +470,18 @@
   * X and B can be either dense or sparse.
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
+  *
+  * \implsparsesolverconcept
   *
   * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
   *
-  * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLDLT
+  * \warning Only double precision real and complex scalar types are supported by Cholmod.
+  *
+  * \sa \ref TutorialSparseSolverConcept, class CholmodSupernodalLLT, class SimplicialLDLT
   */
 template<typename _MatrixType, int _UpLo = Lower>
 class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT<_MatrixType, _UpLo> >
 {
     typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT> Base;
@@ -440,11 +494,11 @@
     CholmodSimplicialLDLT() : Base() { init(); }
 
     CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      this->compute(matrix);
     }
 
     ~CholmodSimplicialLDLT() {}
   protected:
     void init()
@@ -465,14 +519,18 @@
   * X and B can be either dense or sparse.
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
+  *
+  * \implsparsesolverconcept
   *
   * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
   *
-  * \sa \ref TutorialSparseDirectSolvers
+  * \warning Only double precision real and complex scalar types are supported by Cholmod.
+  *
+  * \sa \ref TutorialSparseSolverConcept
   */
 template<typename _MatrixType, int _UpLo = Lower>
 class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT<_MatrixType, _UpLo> >
 {
     typedef CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT> Base;
@@ -485,11 +543,11 @@
     CholmodSupernodalLLT() : Base() { init(); }
 
     CholmodSupernodalLLT(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      this->compute(matrix);
     }
 
     ~CholmodSupernodalLLT() {}
   protected:
     void init()
@@ -512,14 +570,18 @@
   * The default is to let Cholmod automatically choose between a simplicial and supernodal factorization.
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
+  *
+  * \implsparsesolverconcept
   *
   * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
   *
-  * \sa \ref TutorialSparseDirectSolvers
+  * \warning Only double precision real and complex scalar types are supported by Cholmod.
+  *
+  * \sa \ref TutorialSparseSolverConcept
   */
 template<typename _MatrixType, int _UpLo = Lower>
 class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecomposition<_MatrixType, _UpLo> >
 {
     typedef CholmodBase<_MatrixType, _UpLo, CholmodDecomposition> Base;
@@ -532,11 +594,11 @@
     CholmodDecomposition() : Base() { init(); }
 
     CholmodDecomposition(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      this->compute(matrix);
     }
 
     ~CholmodDecomposition() {}
     
     void setMode(CholmodMode mode)
@@ -570,38 +632,8 @@
       m_cholmod.final_asis = 1;
       m_cholmod.supernodal = CHOLMOD_AUTO;
     }
 };
 
-namespace internal {
-  
-template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
-struct solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
-  : solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
-{
-  typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
-struct sparse_solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
-  : sparse_solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
-{
-  typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-} // end namespace internal
-
 } // end namespace Eigen
 
 #endif // EIGEN_CHOLMODSUPPORT_H

Index: 3rd_party/eigen/Eigen/src/Core/Array.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Array.h
+++ 3rd_party/eigen/Eigen/src/Core/Array.h
@@ -10,11 +10,20 @@
 #ifndef EIGEN_ARRAY_H
 #define EIGEN_ARRAY_H
 
 namespace Eigen {
 
-/** \class Array 
+namespace internal {
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+struct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+{
+  typedef ArrayXpr XprKind;
+  typedef ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > XprBase;
+};
+}
+
+/** \class Array
   * \ingroup Core_Module
   *
   * \brief General-purpose arrays with easy API for coefficient-wise operations
   *
   * The %Array class is very similar to the Matrix class. It provides
@@ -21,25 +30,19 @@
   * general-purpose one- and two-dimensional arrays. The difference between the
   * %Array and the %Matrix class is primarily in the API: the API for the
   * %Array class provides easy access to coefficient-wise operations, while the
   * API for the %Matrix class provides easy access to linear-algebra
   * operations.
+  *
+  * See documentation of class Matrix for detailed information on the template parameters
+  * storage layout.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
-  *
-  * \sa \ref TutorialArrayClass, \ref TopicClassHierarchy
-  */
-namespace internal {
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-{
-  typedef ArrayXpr XprKind;
-  typedef ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > XprBase;
-};
-}
-
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
+  *
+  * \sa \blank \ref TutorialArrayClass, \ref TopicClassHierarchy
+  */
 template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
 class Array
   : public PlainObjectBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
 {
   public:
@@ -67,14 +70,30 @@
       *   using Base::operator=;
       * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
       * the usage of 'using'. This should be done only for operator=.
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived> &other)
     {
       return Base::operator=(other);
     }
+
+    /** Set all the entries to \a value.
+      * \sa DenseBase::setConstant(), DenseBase::fill()
+      */
+    /* This overload is needed because the usage of
+      *   using Base::operator=;
+      * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
+      * the usage of 'using'. This should be done only for operator=.
+      */
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Array& operator=(const Scalar &value)
+    {
+      Base::setConstant(value);
+      return *this;
+    }
 
     /** Copies the value of the expression \a other into \c *this with automatic resizing.
       *
       * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
       * it will be initialized.
@@ -82,23 +101,25 @@
       * Note that copying a row-vector into a vector (and conversely) is allowed.
       * The resizing, if any, is then done in the appropriate way so that row-vectors
       * remain row-vectors and vectors remain vectors.
       */
     template<typename OtherDerived>
-    EIGEN_STRONG_INLINE Array& operator=(const ArrayBase<OtherDerived>& other)
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Array& operator=(const DenseBase<OtherDerived>& other)
     {
       return Base::_set(other);
     }
 
     /** This is a special case of the templated operator=. Its purpose is to
       * prevent a default operator= from hiding the templated operator=.
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array& operator=(const Array& other)
     {
       return Base::_set(other);
     }
-
+    
     /** Default constructor.
       *
       * For fixed-size matrices, does nothing.
       *
       * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix
@@ -105,71 +126,97 @@
       * is called a null matrix. This constructor is the unique way to create null matrices: resizing
       * a matrix to 0 is not supported.
       *
       * \sa resize(Index,Index)
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array() : Base()
     {
       Base::_check_template_params();
       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     // FIXME is it still needed ??
     /** \internal */
+    EIGEN_DEVICE_FUNC
     Array(internal::constructor_without_unaligned_array_assert)
       : Base(internal::constructor_without_unaligned_array_assert())
     {
       Base::_check_template_params();
       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 #endif
 
-    /** Constructs a vector or row-vector with given dimension. \only_for_vectors
-      *
-      * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
-      * it is redundant to pass the dimension here, so it makes more sense to use the default
-      * constructor Matrix() instead.
-      */
-    EIGEN_STRONG_INLINE explicit Array(Index dim)
-      : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
+#if EIGEN_HAS_RVALUE_REFERENCES
+    EIGEN_DEVICE_FUNC
+    Array(Array&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_constructible<Scalar>::value)
+      : Base(std::move(other))
     {
       Base::_check_template_params();
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Array)
-      eigen_assert(dim >= 0);
-      eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
-      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+      if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
+        Base::_set_noalias(other);
+    }
+    EIGEN_DEVICE_FUNC
+    Array& operator=(Array&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_assignable<Scalar>::value)
+    {
+      other.swap(*this);
+      return *this;
     }
+#endif
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE explicit Array(const T& x)
+    {
+      Base::_check_template_params();
+      Base::template _init1<T>(x);
+    }
+
     template<typename T0, typename T1>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
     {
       Base::_check_template_params();
       this->template _init2<T0,T1>(val0, val1);
     }
     #else
-    /** constructs an uninitialized matrix with \a rows rows and \a cols columns.
+    /** \brief Constructs a fixed-sized array initialized with coefficients starting at \a data */
+    EIGEN_DEVICE_FUNC explicit Array(const Scalar *data);
+    /** Constructs a vector or row-vector with given dimension. \only_for_vectors
+      *
+      * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
+      * it is redundant to pass the dimension here, so it makes more sense to use the default
+      * constructor Array() instead.
+      */
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE explicit Array(Index dim);
+    /** constructs an initialized 1x1 Array with the given coefficient */
+    Array(const Scalar& value);
+    /** constructs an uninitialized array with \a rows rows and \a cols columns.
       *
-      * This is useful for dynamic-size matrices. For fixed-size matrices,
+      * This is useful for dynamic-size arrays. For fixed-size arrays,
       * it is redundant to pass these parameters, so one should use the default constructor
-      * Matrix() instead. */
+      * Array() instead. */
     Array(Index rows, Index cols);
     /** constructs an initialized 2D vector with given coefficients */
     Array(const Scalar& val0, const Scalar& val1);
     #endif
 
     /** constructs an initialized 3D vector with given coefficients */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
     {
       Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
       m_storage.data()[0] = val0;
       m_storage.data()[1] = val1;
       m_storage.data()[2] = val2;
     }
     /** constructs an initialized 4D vector with given coefficients */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
     {
       Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
       m_storage.data()[0] = val0;
@@ -176,55 +223,31 @@
       m_storage.data()[1] = val1;
       m_storage.data()[2] = val2;
       m_storage.data()[3] = val3;
     }
 
-    explicit Array(const Scalar *data);
-
-    /** Constructor copying the value of the expression \a other */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE Array(const ArrayBase<OtherDerived>& other)
-             : Base(other.rows() * other.cols(), other.rows(), other.cols())
-    {
-      Base::_check_template_params();
-      Base::_set_noalias(other);
-    }
     /** Copy constructor */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array(const Array& other)
-            : Base(other.rows() * other.cols(), other.rows(), other.cols())
-    {
-      Base::_check_template_params();
-      Base::_set_noalias(other);
-    }
-    /** Copy constructor with in-place evaluation */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE Array(const ReturnByValue<OtherDerived>& other)
-    {
-      Base::_check_template_params();
-      Base::resize(other.rows(), other.cols());
-      other.evalTo(*this);
-    }
+            : Base(other)
+    { }
+
+  private:
+    struct PrivateType {};
+  public:
 
     /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
     template<typename OtherDerived>
-    EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other)
-      : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
-    {
-      Base::_check_template_params();
-      Base::_resize_to_match(other);
-      *this = other;
-    }
-
-    /** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
-      * data pointers.
-      */
-    template<typename OtherDerived>
-    void swap(ArrayBase<OtherDerived> const & other)
-    { this->_swap(other.derived()); }
-
-    inline Index innerStride() const { return 1; }
-    inline Index outerStride() const { return this->innerSize(); }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other,
+                              typename internal::enable_if<internal::is_convertible<typename OtherDerived::Scalar,Scalar>::value,
+                                                           PrivateType>::type = PrivateType())
+      : Base(other.derived())
+    { }
+
+    EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; }
+    EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); }
 
     #ifdef EIGEN_ARRAY_PLUGIN
     #include EIGEN_ARRAY_PLUGIN
     #endif
 

Index: 3rd_party/eigen/Eigen/src/Core/ArrayBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/ArrayBase.h
+++ 3rd_party/eigen/Eigen/src/Core/ArrayBase.h
@@ -30,11 +30,11 @@
   * This class is the base that is inherited by all array expression types.
   *
   * \tparam Derived is the derived type, e.g., an array or an expression type.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAYBASE_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAYBASE_PLUGIN.
   *
   * \sa class MatrixBase, \ref TopicClassHierarchy
   */
 template<typename Derived> class ArrayBase
   : public DenseBase<Derived>
@@ -44,15 +44,11 @@
     /** The base class for a given storage type. */
     typedef ArrayBase StorageBaseType;
 
     typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl;
 
-    using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
-                typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
-
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
     typedef DenseBase<Derived> Base;
@@ -62,12 +58,11 @@
     using Base::MaxRowsAtCompileTime;
     using Base::MaxColsAtCompileTime;
     using Base::MaxSizeAtCompileTime;
     using Base::IsVectorAtCompileTime;
     using Base::Flags;
-    using Base::CoeffReadCost;
-
+    
     using Base::derived;
     using Base::const_cast_derived;
     using Base::rows;
     using Base::cols;
     using Base::size;
@@ -83,29 +78,18 @@
     typedef typename Base::CoeffReturnType CoeffReturnType;
 
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** \internal the plain matrix type corresponding to this expression. Note that is not necessarily
-      * exactly the return type of eval(): in the case of plain matrices, the return type of eval() is a const
-      * reference to a matrix, not a matrix! It is however guaranteed that the return type of eval() is either
-      * PlainObject or const PlainObject&.
-      */
-    typedef Array<typename internal::traits<Derived>::Scalar,
-                internal::traits<Derived>::RowsAtCompileTime,
-                internal::traits<Derived>::ColsAtCompileTime,
-                AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
-                internal::traits<Derived>::MaxRowsAtCompileTime,
-                internal::traits<Derived>::MaxColsAtCompileTime
-          > PlainObject;
-
+    typedef typename Base::PlainObject PlainObject;
 
     /** \internal Represents a matrix with all coefficients equal to one another*/
-    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
+    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
 #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase
+#define EIGEN_DOC_UNARY_ADDONS(X,Y)
 #   include "../plugins/CommonCwiseUnaryOps.h"
 #   include "../plugins/MatrixCwiseUnaryOps.h"
 #   include "../plugins/ArrayCwiseUnaryOps.h"
 #   include "../plugins/CommonCwiseBinaryOps.h"
 #   include "../plugins/MatrixCwiseBinaryOps.h"
@@ -112,48 +96,66 @@
 #   include "../plugins/ArrayCwiseBinaryOps.h"
 #   ifdef EIGEN_ARRAYBASE_PLUGIN
 #     include EIGEN_ARRAYBASE_PLUGIN
 #   endif
 #undef EIGEN_CURRENT_STORAGE_BASE_CLASS
+#undef EIGEN_DOC_UNARY_ADDONS
 
     /** Special case of the template operator=, in order to prevent the compiler
       * from generating a default operator= (issue hit with g++ 4.1)
       */
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator=(const ArrayBase& other)
     {
-      return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
+      internal::call_assignment(derived(), other.derived());
+      return derived();
     }
+    
+    /** Set all the entries to \a value.
+      * \sa DenseBase::setConstant(), DenseBase::fill() */
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator=(const Scalar &value)
+    { Base::setConstant(value); return derived(); }
 
-    Derived& operator+=(const Scalar& scalar)
-    { return *this = derived() + scalar; }
-    Derived& operator-=(const Scalar& scalar)
-    { return *this = derived() - scalar; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator+=(const Scalar& scalar);
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator-=(const Scalar& scalar);
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator+=(const ArrayBase<OtherDerived>& other);
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator-=(const ArrayBase<OtherDerived>& other);
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator*=(const ArrayBase<OtherDerived>& other);
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator/=(const ArrayBase<OtherDerived>& other);
 
   public:
+    EIGEN_DEVICE_FUNC
     ArrayBase<Derived>& array() { return *this; }
+    EIGEN_DEVICE_FUNC
     const ArrayBase<Derived>& array() const { return *this; }
 
     /** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array
       * \sa MatrixBase::array() */
-    MatrixWrapper<Derived> matrix() { return derived(); }
-    const MatrixWrapper<const Derived> matrix() const { return derived(); }
+    EIGEN_DEVICE_FUNC
+    MatrixWrapper<Derived> matrix() { return MatrixWrapper<Derived>(derived()); }
+    EIGEN_DEVICE_FUNC
+    const MatrixWrapper<const Derived> matrix() const { return MatrixWrapper<const Derived>(derived()); }
 
 //     template<typename Dest>
 //     inline void evalTo(Dest& dst) const { dst = matrix(); }
 
   protected:
+    EIGEN_DEVICE_FUNC
     ArrayBase() : Base() {}
 
   private:
     explicit ArrayBase(Index);
     ArrayBase(Index,Index);
@@ -171,58 +173,54 @@
   *
   * \returns a reference to \c *this
   */
 template<typename Derived>
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived &
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
 ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other)
 {
-  SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
-  tmp = other.derived();
+  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }
 
 /** replaces \c *this by \c *this + \a other.
   *
   * \returns a reference to \c *this
   */
 template<typename Derived>
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived &
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
 ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other)
 {
-  SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
-  tmp = other.derived();
+  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }
 
 /** replaces \c *this by \c *this * \a other coefficient wise.
   *
   * \returns a reference to \c *this
   */
 template<typename Derived>
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived &
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
 ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other)
 {
-  SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, Derived, OtherDerived> tmp(derived());
-  tmp = other.derived();
+  call_assignment(derived(), other.derived(), internal::mul_assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }
 
 /** replaces \c *this by \c *this / \a other coefficient wise.
   *
   * \returns a reference to \c *this
   */
 template<typename Derived>
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived &
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
 ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
 {
-  SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, Derived, OtherDerived> tmp(derived());
-  tmp = other.derived();
+  call_assignment(derived(), other.derived(), internal::div_assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_ARRAYBASE_H

Index: 3rd_party/eigen/Eigen/src/Core/ArrayWrapper.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/ArrayWrapper.h
+++ 3rd_party/eigen/Eigen/src/Core/ArrayWrapper.h
@@ -30,11 +30,12 @@
 {
   typedef ArrayXpr XprKind;
   // Let's remove NestByRefBit
   enum {
     Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
-    Flags = Flags0 & ~NestByRefBit
+    LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
+    Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
   };
 };
 }
 
 template<typename ExpressionType>
@@ -42,98 +43,70 @@
 {
   public:
     typedef ArrayBase<ArrayWrapper> Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
+    typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
 
     typedef typename internal::conditional<
                        internal::is_lvalue<ExpressionType>::value,
                        Scalar,
                        const Scalar
                      >::type ScalarWithConstIfNotLvalue;
 
-    typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
-
-    inline ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
-
-    inline Index rows() const { return m_expression.rows(); }
-    inline Index cols() const { return m_expression.cols(); }
-    inline Index outerStride() const { return m_expression.outerStride(); }
-    inline Index innerStride() const { return m_expression.innerStride(); }
-
-    inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
-    inline const Scalar* data() const { return m_expression.data(); }
-
-    inline CoeffReturnType coeff(Index rowId, Index colId) const
-    {
-      return m_expression.coeff(rowId, colId);
-    }
-
-    inline Scalar& coeffRef(Index rowId, Index colId)
-    {
-      return m_expression.const_cast_derived().coeffRef(rowId, colId);
-    }
-
-    inline const Scalar& coeffRef(Index rowId, Index colId) const
-    {
-      return m_expression.const_cast_derived().coeffRef(rowId, colId);
-    }
-
-    inline CoeffReturnType coeff(Index index) const
-    {
-      return m_expression.coeff(index);
-    }
-
-    inline Scalar& coeffRef(Index index)
-    {
-      return m_expression.const_cast_derived().coeffRef(index);
-    }
-
-    inline const Scalar& coeffRef(Index index) const
-    {
-      return m_expression.const_cast_derived().coeffRef(index);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index rowId, Index colId) const
-    {
-      return m_expression.template packet<LoadMode>(rowId, colId);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
-    {
-      m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index index) const
-    {
-      return m_expression.template packet<LoadMode>(index);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& val)
-    {
-      m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
+    typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
+
+    using Base::coeffRef;
+
+    EIGEN_DEVICE_FUNC
+    explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
+
+    EIGEN_DEVICE_FUNC
+    inline Index rows() const { return m_expression.rows(); }
+    EIGEN_DEVICE_FUNC
+    inline Index cols() const { return m_expression.cols(); }
+    EIGEN_DEVICE_FUNC
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    EIGEN_DEVICE_FUNC
+    inline Index innerStride() const { return m_expression.innerStride(); }
+
+    EIGEN_DEVICE_FUNC
+    inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
+    EIGEN_DEVICE_FUNC
+    inline const Scalar* data() const { return m_expression.data(); }
+
+    EIGEN_DEVICE_FUNC
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
+    {
+      return m_expression.coeffRef(rowId, colId);
+    }
+
+    EIGEN_DEVICE_FUNC
+    inline const Scalar& coeffRef(Index index) const
+    {
+      return m_expression.coeffRef(index);
     }
 
     template<typename Dest>
+    EIGEN_DEVICE_FUNC
     inline void evalTo(Dest& dst) const { dst = m_expression; }
 
     const typename internal::remove_all<NestedExpressionType>::type& 
+    EIGEN_DEVICE_FUNC
     nestedExpression() const 
     {
       return m_expression;
     }
 
     /** Forwards the resizing request to the nested expression
       * \sa DenseBase::resize(Index)  */
-    void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+    EIGEN_DEVICE_FUNC
+    void resize(Index newSize) { m_expression.resize(newSize); }
     /** Forwards the resizing request to the nested expression
       * \sa DenseBase::resize(Index,Index)*/
-    void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+    EIGEN_DEVICE_FUNC
+    void resize(Index rows, Index cols) { m_expression.resize(rows,cols); }
 
   protected:
     NestedExpressionType m_expression;
 };
 
@@ -155,11 +128,12 @@
 {
   typedef MatrixXpr XprKind;
   // Let's remove NestByRefBit
   enum {
     Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
-    Flags = Flags0 & ~NestByRefBit
+    LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
+    Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
   };
 };
 }
 
 template<typename ExpressionType>
@@ -167,98 +141,69 @@
 {
   public:
     typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
+    typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
 
     typedef typename internal::conditional<
                        internal::is_lvalue<ExpressionType>::value,
                        Scalar,
                        const Scalar
                      >::type ScalarWithConstIfNotLvalue;
 
-    typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
+    typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
+
+    using Base::coeffRef;
 
-    inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {}
+    EIGEN_DEVICE_FUNC
+    explicit inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
 
+    EIGEN_DEVICE_FUNC
     inline Index rows() const { return m_expression.rows(); }
+    EIGEN_DEVICE_FUNC
     inline Index cols() const { return m_expression.cols(); }
+    EIGEN_DEVICE_FUNC
     inline Index outerStride() const { return m_expression.outerStride(); }
+    EIGEN_DEVICE_FUNC
     inline Index innerStride() const { return m_expression.innerStride(); }
 
-    inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
+    EIGEN_DEVICE_FUNC
+    inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
+    EIGEN_DEVICE_FUNC
     inline const Scalar* data() const { return m_expression.data(); }
 
-    inline CoeffReturnType coeff(Index rowId, Index colId) const
-    {
-      return m_expression.coeff(rowId, colId);
-    }
-
-    inline Scalar& coeffRef(Index rowId, Index colId)
-    {
-      return m_expression.const_cast_derived().coeffRef(rowId, colId);
-    }
-
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
       return m_expression.derived().coeffRef(rowId, colId);
     }
 
-    inline CoeffReturnType coeff(Index index) const
-    {
-      return m_expression.coeff(index);
-    }
-
-    inline Scalar& coeffRef(Index index)
-    {
-      return m_expression.const_cast_derived().coeffRef(index);
-    }
-
-    inline const Scalar& coeffRef(Index index) const
-    {
-      return m_expression.const_cast_derived().coeffRef(index);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index rowId, Index colId) const
-    {
-      return m_expression.template packet<LoadMode>(rowId, colId);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
-    {
-      m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index index) const
-    {
-      return m_expression.template packet<LoadMode>(index);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& val)
-    {
-      m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
-    }
-
+    EIGEN_DEVICE_FUNC
+    inline const Scalar& coeffRef(Index index) const
+    {
+      return m_expression.coeffRef(index);
+    }
+
+    EIGEN_DEVICE_FUNC
     const typename internal::remove_all<NestedExpressionType>::type& 
     nestedExpression() const 
     {
       return m_expression;
     }
 
     /** Forwards the resizing request to the nested expression
       * \sa DenseBase::resize(Index)  */
-    void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+    EIGEN_DEVICE_FUNC
+    void resize(Index newSize) { m_expression.resize(newSize); }
     /** Forwards the resizing request to the nested expression
       * \sa DenseBase::resize(Index,Index)*/
-    void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+    EIGEN_DEVICE_FUNC
+    void resize(Index rows, Index cols) { m_expression.resize(rows,cols); }
 
   protected:
     NestedExpressionType m_expression;
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_ARRAYWRAPPER_H

Index: 3rd_party/eigen/Eigen/src/Core/Assign.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Assign.h
+++ 3rd_party/eigen/Eigen/src/Core/Assign.h
@@ -12,475 +12,10 @@
 #ifndef EIGEN_ASSIGN_H
 #define EIGEN_ASSIGN_H
 
 namespace Eigen {
 
-namespace internal {
-
-/***************************************************************************
-* Part 1 : the logic deciding a strategy for traversal and unrolling       *
-***************************************************************************/
-
-template <typename Derived, typename OtherDerived>
-struct assign_traits
-{
-public:
-  enum {
-    DstIsAligned = Derived::Flags & AlignedBit,
-    DstHasDirectAccess = Derived::Flags & DirectAccessBit,
-    SrcIsAligned = OtherDerived::Flags & AlignedBit,
-    JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned
-  };
-
-private:
-  enum {
-    InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime)
-              : int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime)
-              : int(Derived::RowsAtCompileTime),
-    InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime)
-              : int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime)
-              : int(Derived::MaxRowsAtCompileTime),
-    MaxSizeAtCompileTime = Derived::SizeAtCompileTime,
-    PacketSize = packet_traits<typename Derived::Scalar>::size
-  };
-
-  enum {
-    StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)),
-    MightVectorize = StorageOrdersAgree
-                  && (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit),
-    MayInnerVectorize  = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
-                       && int(DstIsAligned) && int(SrcIsAligned),
-    MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
-    MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
-                       && (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
-      /* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
-         so it's only good for large enough sizes. */
-    MaySliceVectorize  = MightVectorize && DstHasDirectAccess
-                       && (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize)
-      /* slice vectorization can be slow, so we only want it if the slices are big, which is
-         indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
-         in a fixed-size matrix */
-  };
-
-public:
-  enum {
-    Traversal = int(MayInnerVectorize)  ? int(InnerVectorizedTraversal)
-              : int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
-              : int(MaySliceVectorize)  ? int(SliceVectorizedTraversal)
-              : int(MayLinearize)       ? int(LinearTraversal)
-                                        : int(DefaultTraversal),
-    Vectorized = int(Traversal) == InnerVectorizedTraversal
-              || int(Traversal) == LinearVectorizedTraversal
-              || int(Traversal) == SliceVectorizedTraversal
-  };
-
-private:
-  enum {
-    UnrollingLimit      = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
-    MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic
-                       && int(OtherDerived::CoeffReadCost) != Dynamic
-                       && int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
-    MayUnrollInner      = int(InnerSize) != Dynamic
-                       && int(OtherDerived::CoeffReadCost) != Dynamic
-                       && int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
-  };
-
-public:
-  enum {
-    Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
-                ? (
-                    int(MayUnrollCompletely) ? int(CompleteUnrolling)
-                  : int(MayUnrollInner)      ? int(InnerUnrolling)
-                                             : int(NoUnrolling)
-                  )
-              : int(Traversal) == int(LinearVectorizedTraversal)
-                ? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling) : int(NoUnrolling) )
-              : int(Traversal) == int(LinearTraversal)
-                ? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) : int(NoUnrolling) )
-              : int(NoUnrolling)
-  };
-
-#ifdef EIGEN_DEBUG_ASSIGN
-  static void debug()
-  {
-    EIGEN_DEBUG_VAR(DstIsAligned)
-    EIGEN_DEBUG_VAR(SrcIsAligned)
-    EIGEN_DEBUG_VAR(JointAlignment)
-    EIGEN_DEBUG_VAR(InnerSize)
-    EIGEN_DEBUG_VAR(InnerMaxSize)
-    EIGEN_DEBUG_VAR(PacketSize)
-    EIGEN_DEBUG_VAR(StorageOrdersAgree)
-    EIGEN_DEBUG_VAR(MightVectorize)
-    EIGEN_DEBUG_VAR(MayLinearize)
-    EIGEN_DEBUG_VAR(MayInnerVectorize)
-    EIGEN_DEBUG_VAR(MayLinearVectorize)
-    EIGEN_DEBUG_VAR(MaySliceVectorize)
-    EIGEN_DEBUG_VAR(Traversal)
-    EIGEN_DEBUG_VAR(UnrollingLimit)
-    EIGEN_DEBUG_VAR(MayUnrollCompletely)
-    EIGEN_DEBUG_VAR(MayUnrollInner)
-    EIGEN_DEBUG_VAR(Unrolling)
-  }
-#endif
-};
-
-/***************************************************************************
-* Part 2 : meta-unrollers
-***************************************************************************/
-
-/************************
-*** Default traversal ***
-************************/
-
-template<typename Derived1, typename Derived2, int Index, int Stop>
-struct assign_DefaultTraversal_CompleteUnrolling
-{
-  enum {
-    outer = Index / Derived1::InnerSizeAtCompileTime,
-    inner = Index % Derived1::InnerSizeAtCompileTime
-  };
-
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    dst.copyCoeffByOuterInner(outer, inner, src);
-    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Stop>
-struct assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
-};
-
-template<typename Derived1, typename Derived2, int Index, int Stop>
-struct assign_DefaultTraversal_InnerUnrolling
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
-  {
-    dst.copyCoeffByOuterInner(outer, Index, src);
-    assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src, outer);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Stop>
-struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
-};
-
-/***********************
-*** Linear traversal ***
-***********************/
-
-template<typename Derived1, typename Derived2, int Index, int Stop>
-struct assign_LinearTraversal_CompleteUnrolling
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    dst.copyCoeff(Index, src);
-    assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Stop>
-struct assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
-};
-
-/**************************
-*** Inner vectorization ***
-**************************/
-
-template<typename Derived1, typename Derived2, int Index, int Stop>
-struct assign_innervec_CompleteUnrolling
-{
-  enum {
-    outer = Index / Derived1::InnerSizeAtCompileTime,
-    inner = Index % Derived1::InnerSizeAtCompileTime,
-    JointAlignment = assign_traits<Derived1,Derived2>::JointAlignment
-  };
-
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    dst.template copyPacketByOuterInner<Derived2, Aligned, JointAlignment>(outer, inner, src);
-    assign_innervec_CompleteUnrolling<Derived1, Derived2,
-      Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Stop>
-struct assign_innervec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
-};
-
-template<typename Derived1, typename Derived2, int Index, int Stop>
-struct assign_innervec_InnerUnrolling
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
-  {
-    dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, Index, src);
-    assign_innervec_InnerUnrolling<Derived1, Derived2,
-      Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src, outer);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Stop>
-struct assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
-};
-
-/***************************************************************************
-* Part 3 : implementation of all cases
-***************************************************************************/
-
-template<typename Derived1, typename Derived2,
-         int Traversal = assign_traits<Derived1, Derived2>::Traversal,
-         int Unrolling = assign_traits<Derived1, Derived2>::Unrolling,
-         int Version = Specialized>
-struct assign_impl;
-
-/************************
-*** Default traversal ***
-************************/
-
-template<typename Derived1, typename Derived2, int Unrolling, int Version>
-struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling, Version>
-{
-  static inline void run(Derived1 &, const Derived2 &) { }
-};
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling, Version>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    const Index innerSize = dst.innerSize();
-    const Index outerSize = dst.outerSize();
-    for(Index outer = 0; outer < outerSize; ++outer)
-      for(Index inner = 0; inner < innerSize; ++inner)
-        dst.copyCoeffByOuterInner(outer, inner, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling, Version>
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
-      ::run(dst, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling, Version>
-{
-  typedef typename Derived1::Index Index;
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    const Index outerSize = dst.outerSize();
-    for(Index outer = 0; outer < outerSize; ++outer)
-      assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
-        ::run(dst, src, outer);
-  }
-};
-
-/***********************
-*** Linear traversal ***
-***********************/
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling, Version>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    const Index size = dst.size();
-    for(Index i = 0; i < size; ++i)
-      dst.copyCoeff(i, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling, Version>
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
-      ::run(dst, src);
-  }
-};
-
-/**************************
-*** Inner vectorization ***
-**************************/
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling, Version>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    const Index innerSize = dst.innerSize();
-    const Index outerSize = dst.outerSize();
-    const Index packetSize = packet_traits<typename Derived1::Scalar>::size;
-    for(Index outer = 0; outer < outerSize; ++outer)
-      for(Index inner = 0; inner < innerSize; inner+=packetSize)
-        dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, inner, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling, Version>
-{
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
-      ::run(dst, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling, Version>
-{
-  typedef typename Derived1::Index Index;
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    const Index outerSize = dst.outerSize();
-    for(Index outer = 0; outer < outerSize; ++outer)
-      assign_innervec_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
-        ::run(dst, src, outer);
-  }
-};
-
-/***************************
-*** Linear vectorization ***
-***************************/
-
-template <bool IsAligned = false>
-struct unaligned_assign_impl
-{
-  template <typename Derived, typename OtherDerived>
-  static EIGEN_STRONG_INLINE void run(const Derived&, OtherDerived&, typename Derived::Index, typename Derived::Index) {}
-};
-
-template <>
-struct unaligned_assign_impl<false>
-{
-  // MSVC must not inline this functions. If it does, it fails to optimize the
-  // packet access path.
-#ifdef _MSC_VER
-  template <typename Derived, typename OtherDerived>
-  static EIGEN_DONT_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
-#else
-  template <typename Derived, typename OtherDerived>
-  static EIGEN_STRONG_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
-#endif
-  {
-    for (typename Derived::Index index = start; index < end; ++index)
-      dst.copyCoeff(index, src);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, Version>
-{
-  typedef typename Derived1::Index Index;
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    const Index size = dst.size();
-    typedef packet_traits<typename Derived1::Scalar> PacketTraits;
-    enum {
-      packetSize = PacketTraits::size,
-      dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
-      srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
-    };
-    const Index alignedStart = assign_traits<Derived1,Derived2>::DstIsAligned ? 0
-                             : internal::first_aligned(&dst.coeffRef(0), size);
-    const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
-
-    unaligned_assign_impl<assign_traits<Derived1,Derived2>::DstIsAligned!=0>::run(src,dst,0,alignedStart);
-
-    for(Index index = alignedStart; index < alignedEnd; index += packetSize)
-    {
-      dst.template copyPacket<Derived2, dstAlignment, srcAlignment>(index, src);
-    }
-
-    unaligned_assign_impl<>::run(src,dst,alignedEnd,size);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling, Version>
-{
-  typedef typename Derived1::Index Index;
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
-  {
-    enum { size = Derived1::SizeAtCompileTime,
-           packetSize = packet_traits<typename Derived1::Scalar>::size,
-           alignedSize = (size/packetSize)*packetSize };
-
-    assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
-    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, alignedSize, size>::run(dst, src);
-  }
-};
-
-/**************************
-*** Slice vectorization ***
-***************************/
-
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Version>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    typedef packet_traits<typename Derived1::Scalar> PacketTraits;
-    enum {
-      packetSize = PacketTraits::size,
-      alignable = PacketTraits::AlignedOnScalar,
-      dstAlignment = alignable ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
-      srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
-    };
-    const Index packetAlignedMask = packetSize - 1;
-    const Index innerSize = dst.innerSize();
-    const Index outerSize = dst.outerSize();
-    const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
-    Index alignedStart = ((!alignable) || assign_traits<Derived1,Derived2>::DstIsAligned) ? 0
-                       : internal::first_aligned(&dst.coeffRef(0,0), innerSize);
-
-    for(Index outer = 0; outer < outerSize; ++outer)
-    {
-      const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
-      // do the non-vectorizable part of the assignment
-      for(Index inner = 0; inner<alignedStart ; ++inner)
-        dst.copyCoeffByOuterInner(outer, inner, src);
-
-      // do the vectorizable part of the assignment
-      for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
-        dst.template copyPacketByOuterInner<Derived2, dstAlignment, Unaligned>(outer, inner, src);
-
-      // do the non-vectorizable part of the assignment
-      for(Index inner = alignedEnd; inner<innerSize ; ++inner)
-        dst.copyCoeffByOuterInner(outer, inner, src);
-
-      alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
-    }
-  }
-};
-
-} // end namespace internal
-
-/***************************************************************************
-* Part 4 : implementation of DenseBase methods
-***************************************************************************/
-
 template<typename Derived>
 template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
   ::lazyAssign(const DenseBase<OtherDerived>& other)
 {
@@ -490,94 +25,66 @@
 
   EIGEN_STATIC_ASSERT_LVALUE(Derived)
   EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
   EIGEN_STATIC_ASSERT(SameType,YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
-#ifdef EIGEN_DEBUG_ASSIGN
-  internal::assign_traits<Derived, OtherDerived>::debug();
-#endif
-  eigen_assert(rows() == other.rows() && cols() == other.cols());
-  internal::assign_impl<Derived, OtherDerived, int(SameType) ? int(internal::assign_traits<Derived, OtherDerived>::Traversal)
-                                                       : int(InvalidTraversal)>::run(derived(),other.derived());
-#ifndef EIGEN_NO_DEBUG
-  checkTransposeAliasing(other.derived());
-#endif
-  return derived();
-}
-
-namespace internal {
-
-template<typename Derived, typename OtherDerived,
-         bool EvalBeforeAssigning = (int(internal::traits<OtherDerived>::Flags) & EvalBeforeAssigningBit) != 0,
-         bool NeedToTranspose = ((int(Derived::RowsAtCompileTime) == 1 && int(OtherDerived::ColsAtCompileTime) == 1)
-                              |   // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
-                                  // revert to || as soon as not needed anymore.
-                                  (int(Derived::ColsAtCompileTime) == 1 && int(OtherDerived::RowsAtCompileTime) == 1))
-                              && int(Derived::SizeAtCompileTime) != 1>
-struct assign_selector;
-
-template<typename Derived, typename OtherDerived>
-struct assign_selector<Derived,OtherDerived,false,false> {
-  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
-  template<typename ActualDerived, typename ActualOtherDerived>
-  static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { other.evalTo(dst); return dst; }
-};
-template<typename Derived, typename OtherDerived>
-struct assign_selector<Derived,OtherDerived,true,false> {
-  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
-};
-template<typename Derived, typename OtherDerived>
-struct assign_selector<Derived,OtherDerived,false,true> {
-  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
-  template<typename ActualDerived, typename ActualOtherDerived>
-  static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { Transpose<ActualDerived> dstTrans(dst); other.evalTo(dstTrans); return dst; }
-};
-template<typename Derived, typename OtherDerived>
-struct assign_selector<Derived,OtherDerived,true,true> {
-  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
-};
-
-} // end namespace internal
-
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
-{
-  return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
-}
-
-template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other)
-{
-  return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
-}
-
-template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other)
-{
-  return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
-}
-
-template<typename Derived>
-template <typename OtherDerived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
-{
-  return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
-}
-
-template<typename Derived>
-template <typename OtherDerived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
-{
-  return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
-}
-
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
-{
-  return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
+  eigen_assert(rows() == other.rows() && cols() == other.cols());
+  internal::call_assignment_no_alias(derived(),other.derived());
+  
+  return derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
+{
+  internal::call_assignment(derived(), other.derived());
+  return derived();
+}
+
+template<typename Derived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other)
+{
+  internal::call_assignment(derived(), other.derived());
+  return derived();
+}
+
+template<typename Derived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other)
+{
+  internal::call_assignment(derived(), other.derived());
+  return derived();
+}
+
+template<typename Derived>
+template <typename OtherDerived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
+{
+  internal::call_assignment(derived(), other.derived());
+  return derived();
+}
+
+template<typename Derived>
+template <typename OtherDerived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
+{
+  internal::call_assignment(derived(), other.derived());
+  return derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
+{
+  other.derived().evalTo(derived());
+  return derived();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_ASSIGN_H

ADDED   3rd_party/eigen/Eigen/src/Core/AssignEvaluator.h
Index: 3rd_party/eigen/Eigen/src/Core/AssignEvaluator.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/AssignEvaluator.h
+++ 3rd_party/eigen/Eigen/src/Core/AssignEvaluator.h
@@ -0,0 +1,935 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_ASSIGN_EVALUATOR_H
+#define EIGEN_ASSIGN_EVALUATOR_H
+
+namespace Eigen {
+
+// This implementation is based on Assign.h
+
+namespace internal {
+  
+/***************************************************************************
+* Part 1 : the logic deciding a strategy for traversal and unrolling       *
+***************************************************************************/
+
+// copy_using_evaluator_traits is based on assign_traits
+
+template <typename DstEvaluator, typename SrcEvaluator, typename AssignFunc>
+struct copy_using_evaluator_traits
+{
+  typedef typename DstEvaluator::XprType Dst;
+  typedef typename Dst::Scalar DstScalar;
+  
+  enum {
+    DstFlags = DstEvaluator::Flags,
+    SrcFlags = SrcEvaluator::Flags
+  };
+  
+public:
+  enum {
+    DstAlignment = DstEvaluator::Alignment,
+    SrcAlignment = SrcEvaluator::Alignment,
+    DstHasDirectAccess = DstFlags & DirectAccessBit,
+    JointAlignment = EIGEN_PLAIN_ENUM_MIN(DstAlignment,SrcAlignment)
+  };
+
+private:
+  enum {
+    InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
+              : int(DstFlags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
+              : int(Dst::RowsAtCompileTime),
+    InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
+              : int(DstFlags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
+              : int(Dst::MaxRowsAtCompileTime),
+    OuterStride = int(outer_stride_at_compile_time<Dst>::ret),
+    MaxSizeAtCompileTime = Dst::SizeAtCompileTime
+  };
+
+  // TODO distinguish between linear traversal and inner-traversals
+  typedef typename find_best_packet<DstScalar,Dst::SizeAtCompileTime>::type LinearPacketType;
+  typedef typename find_best_packet<DstScalar,InnerSize>::type InnerPacketType;
+
+  enum {
+    LinearPacketSize = unpacket_traits<LinearPacketType>::size,
+    InnerPacketSize = unpacket_traits<InnerPacketType>::size
+  };
+
+public:
+  enum {
+    LinearRequiredAlignment = unpacket_traits<LinearPacketType>::alignment,
+    InnerRequiredAlignment = unpacket_traits<InnerPacketType>::alignment
+  };
+
+private:
+  enum {
+    DstIsRowMajor = DstFlags&RowMajorBit,
+    SrcIsRowMajor = SrcFlags&RowMajorBit,
+    StorageOrdersAgree = (int(DstIsRowMajor) == int(SrcIsRowMajor)),
+    MightVectorize = bool(StorageOrdersAgree)
+                  && (int(DstFlags) & int(SrcFlags) & ActualPacketAccessBit)
+                  && bool(functor_traits<AssignFunc>::PacketAccess),
+    MayInnerVectorize  = MightVectorize
+                       && int(InnerSize)!=Dynamic && int(InnerSize)%int(InnerPacketSize)==0
+                       && int(OuterStride)!=Dynamic && int(OuterStride)%int(InnerPacketSize)==0
+                       && (EIGEN_UNALIGNED_VECTORIZE  || int(JointAlignment)>=int(InnerRequiredAlignment)),
+    MayLinearize = bool(StorageOrdersAgree) && (int(DstFlags) & int(SrcFlags) & LinearAccessBit),
+    MayLinearVectorize = bool(MightVectorize) && MayLinearize && DstHasDirectAccess
+                       && (EIGEN_UNALIGNED_VECTORIZE || (int(DstAlignment)>=int(LinearRequiredAlignment)) || MaxSizeAtCompileTime == Dynamic),
+      /* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
+         so it's only good for large enough sizes. */
+    MaySliceVectorize  = bool(MightVectorize) && bool(DstHasDirectAccess)
+                       && (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=(EIGEN_UNALIGNED_VECTORIZE?InnerPacketSize:(3*InnerPacketSize)))
+      /* slice vectorization can be slow, so we only want it if the slices are big, which is
+         indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
+         in a fixed-size matrix
+         However, with EIGEN_UNALIGNED_VECTORIZE and unrolling, slice vectorization is still worth it */
+  };
+
+public:
+  enum {
+    Traversal = int(MayLinearVectorize) && (LinearPacketSize>InnerPacketSize) ? int(LinearVectorizedTraversal)
+              : int(MayInnerVectorize)   ? int(InnerVectorizedTraversal)
+              : int(MayLinearVectorize)  ? int(LinearVectorizedTraversal)
+              : int(MaySliceVectorize)   ? int(SliceVectorizedTraversal)
+              : int(MayLinearize)        ? int(LinearTraversal)
+                                         : int(DefaultTraversal),
+    Vectorized = int(Traversal) == InnerVectorizedTraversal
+              || int(Traversal) == LinearVectorizedTraversal
+              || int(Traversal) == SliceVectorizedTraversal
+  };
+
+  typedef typename conditional<int(Traversal)==LinearVectorizedTraversal, LinearPacketType, InnerPacketType>::type PacketType;
+
+private:
+  enum {
+    ActualPacketSize    = int(Traversal)==LinearVectorizedTraversal ? LinearPacketSize
+                        : Vectorized ? InnerPacketSize
+                        : 1,
+    UnrollingLimit      = EIGEN_UNROLLING_LIMIT * ActualPacketSize,
+    MayUnrollCompletely = int(Dst::SizeAtCompileTime) != Dynamic
+                       && int(Dst::SizeAtCompileTime) * (int(DstEvaluator::CoeffReadCost)+int(SrcEvaluator::CoeffReadCost)) <= int(UnrollingLimit),
+    MayUnrollInner      = int(InnerSize) != Dynamic
+                       && int(InnerSize) * (int(DstEvaluator::CoeffReadCost)+int(SrcEvaluator::CoeffReadCost)) <= int(UnrollingLimit)
+  };
+
+public:
+  enum {
+    Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
+                ? (
+                    int(MayUnrollCompletely) ? int(CompleteUnrolling)
+                  : int(MayUnrollInner)      ? int(InnerUnrolling)
+                                             : int(NoUnrolling)
+                  )
+              : int(Traversal) == int(LinearVectorizedTraversal)
+                ? ( bool(MayUnrollCompletely) && ( EIGEN_UNALIGNED_VECTORIZE || (int(DstAlignment)>=int(LinearRequiredAlignment)))
+                          ? int(CompleteUnrolling)
+                          : int(NoUnrolling) )
+              : int(Traversal) == int(LinearTraversal)
+                ? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) 
+                                              : int(NoUnrolling) )
+#if EIGEN_UNALIGNED_VECTORIZE
+              : int(Traversal) == int(SliceVectorizedTraversal)
+                ? ( bool(MayUnrollInner) ? int(InnerUnrolling)
+                                         : int(NoUnrolling) )
+#endif
+              : int(NoUnrolling)
+  };
+
+#ifdef EIGEN_DEBUG_ASSIGN
+  static void debug()
+  {
+    std::cerr << "DstXpr: " << typeid(typename DstEvaluator::XprType).name() << std::endl;
+    std::cerr << "SrcXpr: " << typeid(typename SrcEvaluator::XprType).name() << std::endl;
+    std::cerr.setf(std::ios::hex, std::ios::basefield);
+    std::cerr << "DstFlags" << " = " << DstFlags << " (" << demangle_flags(DstFlags) << " )" << std::endl;
+    std::cerr << "SrcFlags" << " = " << SrcFlags << " (" << demangle_flags(SrcFlags) << " )" << std::endl;
+    std::cerr.unsetf(std::ios::hex);
+    EIGEN_DEBUG_VAR(DstAlignment)
+    EIGEN_DEBUG_VAR(SrcAlignment)
+    EIGEN_DEBUG_VAR(LinearRequiredAlignment)
+    EIGEN_DEBUG_VAR(InnerRequiredAlignment)
+    EIGEN_DEBUG_VAR(JointAlignment)
+    EIGEN_DEBUG_VAR(InnerSize)
+    EIGEN_DEBUG_VAR(InnerMaxSize)
+    EIGEN_DEBUG_VAR(LinearPacketSize)
+    EIGEN_DEBUG_VAR(InnerPacketSize)
+    EIGEN_DEBUG_VAR(ActualPacketSize)
+    EIGEN_DEBUG_VAR(StorageOrdersAgree)
+    EIGEN_DEBUG_VAR(MightVectorize)
+    EIGEN_DEBUG_VAR(MayLinearize)
+    EIGEN_DEBUG_VAR(MayInnerVectorize)
+    EIGEN_DEBUG_VAR(MayLinearVectorize)
+    EIGEN_DEBUG_VAR(MaySliceVectorize)
+    std::cerr << "Traversal" << " = " << Traversal << " (" << demangle_traversal(Traversal) << ")" << std::endl;
+    EIGEN_DEBUG_VAR(SrcEvaluator::CoeffReadCost)
+    EIGEN_DEBUG_VAR(UnrollingLimit)
+    EIGEN_DEBUG_VAR(MayUnrollCompletely)
+    EIGEN_DEBUG_VAR(MayUnrollInner)
+    std::cerr << "Unrolling" << " = " << Unrolling << " (" << demangle_unrolling(Unrolling) << ")" << std::endl;
+    std::cerr << std::endl;
+  }
+#endif
+};
+
+/***************************************************************************
+* Part 2 : meta-unrollers
+***************************************************************************/
+
+/************************
+*** Default traversal ***
+************************/
+
+template<typename Kernel, int Index, int Stop>
+struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
+{
+  // FIXME: this is not very clean, perhaps this information should be provided by the kernel?
+  typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
+  typedef typename DstEvaluatorType::XprType DstXprType;
+  
+  enum {
+    outer = Index / DstXprType::InnerSizeAtCompileTime,
+    inner = Index % DstXprType::InnerSizeAtCompileTime
+  };
+
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    kernel.assignCoeffByOuterInner(outer, inner);
+    copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Index+1, Stop>::run(kernel);
+  }
+};
+
+template<typename Kernel, int Stop>
+struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Stop, Stop>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
+};
+
+template<typename Kernel, int Index_, int Stop>
+struct copy_using_evaluator_DefaultTraversal_InnerUnrolling
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
+  {
+    kernel.assignCoeffByOuterInner(outer, Index_);
+    copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Index_+1, Stop>::run(kernel, outer);
+  }
+};
+
+template<typename Kernel, int Stop>
+struct copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Stop, Stop>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index) { }
+};
+
+/***********************
+*** Linear traversal ***
+***********************/
+
+template<typename Kernel, int Index, int Stop>
+struct copy_using_evaluator_LinearTraversal_CompleteUnrolling
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel)
+  {
+    kernel.assignCoeff(Index);
+    copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Index+1, Stop>::run(kernel);
+  }
+};
+
+template<typename Kernel, int Stop>
+struct copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Stop, Stop>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
+};
+
+/**************************
+*** Inner vectorization ***
+**************************/
+
+template<typename Kernel, int Index, int Stop>
+struct copy_using_evaluator_innervec_CompleteUnrolling
+{
+  // FIXME: this is not very clean, perhaps this information should be provided by the kernel?
+  typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
+  typedef typename DstEvaluatorType::XprType DstXprType;
+  typedef typename Kernel::PacketType PacketType;
+  
+  enum {
+    outer = Index / DstXprType::InnerSizeAtCompileTime,
+    inner = Index % DstXprType::InnerSizeAtCompileTime,
+    SrcAlignment = Kernel::AssignmentTraits::SrcAlignment,
+    DstAlignment = Kernel::AssignmentTraits::DstAlignment
+  };
+
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, inner);
+    enum { NextIndex = Index + unpacket_traits<PacketType>::size };
+    copy_using_evaluator_innervec_CompleteUnrolling<Kernel, NextIndex, Stop>::run(kernel);
+  }
+};
+
+template<typename Kernel, int Stop>
+struct copy_using_evaluator_innervec_CompleteUnrolling<Kernel, Stop, Stop>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
+};
+
+template<typename Kernel, int Index_, int Stop, int SrcAlignment, int DstAlignment>
+struct copy_using_evaluator_innervec_InnerUnrolling
+{
+  typedef typename Kernel::PacketType PacketType;
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
+  {
+    kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, Index_);
+    enum { NextIndex = Index_ + unpacket_traits<PacketType>::size };
+    copy_using_evaluator_innervec_InnerUnrolling<Kernel, NextIndex, Stop, SrcAlignment, DstAlignment>::run(kernel, outer);
+  }
+};
+
+template<typename Kernel, int Stop, int SrcAlignment, int DstAlignment>
+struct copy_using_evaluator_innervec_InnerUnrolling<Kernel, Stop, Stop, SrcAlignment, DstAlignment>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &, Index) { }
+};
+
+/***************************************************************************
+* Part 3 : implementation of all cases
+***************************************************************************/
+
+// dense_assignment_loop is based on assign_impl
+
+template<typename Kernel,
+         int Traversal = Kernel::AssignmentTraits::Traversal,
+         int Unrolling = Kernel::AssignmentTraits::Unrolling>
+struct dense_assignment_loop;
+
+/************************
+*** Default traversal ***
+************************/
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, DefaultTraversal, NoUnrolling>
+{
+  EIGEN_DEVICE_FUNC static void EIGEN_STRONG_INLINE run(Kernel &kernel)
+  {
+    for(Index outer = 0; outer < kernel.outerSize(); ++outer) {
+      for(Index inner = 0; inner < kernel.innerSize(); ++inner) {
+        kernel.assignCoeffByOuterInner(outer, inner);
+      }
+    }
+  }
+};
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, DefaultTraversal, CompleteUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
+    copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
+  }
+};
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, DefaultTraversal, InnerUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
+
+    const Index outerSize = kernel.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, 0, DstXprType::InnerSizeAtCompileTime>::run(kernel, outer);
+  }
+};
+
+/***************************
+*** Linear vectorization ***
+***************************/
+
+
+// The goal of unaligned_dense_assignment_loop is simply to factorize the handling
+// of the non vectorizable beginning and ending parts
+
+template <bool IsAligned = false>
+struct unaligned_dense_assignment_loop
+{
+  // if IsAligned = true, then do nothing
+  template <typename Kernel>
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index, Index) {}
+};
+
+template <>
+struct unaligned_dense_assignment_loop<false>
+{
+  // MSVC must not inline this functions. If it does, it fails to optimize the
+  // packet access path.
+  // FIXME check which version exhibits this issue
+#if EIGEN_COMP_MSVC
+  template <typename Kernel>
+  static EIGEN_DONT_INLINE void run(Kernel &kernel,
+                                    Index start,
+                                    Index end)
+#else
+  template <typename Kernel>
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel,
+                                      Index start,
+                                      Index end)
+#endif
+  {
+    for (Index index = start; index < end; ++index)
+      kernel.assignCoeff(index);
+  }
+};
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, NoUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    const Index size = kernel.size();
+    typedef typename Kernel::Scalar Scalar;
+    typedef typename Kernel::PacketType PacketType;
+    enum {
+      requestedAlignment = Kernel::AssignmentTraits::LinearRequiredAlignment,
+      packetSize = unpacket_traits<PacketType>::size,
+      dstIsAligned = int(Kernel::AssignmentTraits::DstAlignment)>=int(requestedAlignment),
+      dstAlignment = packet_traits<Scalar>::AlignedOnScalar ? int(requestedAlignment)
+                                                            : int(Kernel::AssignmentTraits::DstAlignment),
+      srcAlignment = Kernel::AssignmentTraits::JointAlignment
+    };
+    const Index alignedStart = dstIsAligned ? 0 : internal::first_aligned<requestedAlignment>(kernel.dstDataPtr(), size);
+    const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
+
+    unaligned_dense_assignment_loop<dstIsAligned!=0>::run(kernel, 0, alignedStart);
+
+    for(Index index = alignedStart; index < alignedEnd; index += packetSize)
+      kernel.template assignPacket<dstAlignment, srcAlignment, PacketType>(index);
+
+    unaligned_dense_assignment_loop<>::run(kernel, alignedEnd, size);
+  }
+};
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, CompleteUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
+    typedef typename Kernel::PacketType PacketType;
+    
+    enum { size = DstXprType::SizeAtCompileTime,
+           packetSize =unpacket_traits<PacketType>::size,
+           alignedSize = (size/packetSize)*packetSize };
+
+    copy_using_evaluator_innervec_CompleteUnrolling<Kernel, 0, alignedSize>::run(kernel);
+    copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, alignedSize, size>::run(kernel);
+  }
+};
+
+/**************************
+*** Inner vectorization ***
+**************************/
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, NoUnrolling>
+{
+  typedef typename Kernel::PacketType PacketType;
+  enum {
+    SrcAlignment = Kernel::AssignmentTraits::SrcAlignment,
+    DstAlignment = Kernel::AssignmentTraits::DstAlignment
+  };
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    const Index innerSize = kernel.innerSize();
+    const Index outerSize = kernel.outerSize();
+    const Index packetSize = unpacket_traits<PacketType>::size;
+    for(Index outer = 0; outer < outerSize; ++outer)
+      for(Index inner = 0; inner < innerSize; inner+=packetSize)
+        kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, inner);
+  }
+};
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, CompleteUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
+    copy_using_evaluator_innervec_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
+  }
+};
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, InnerUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
+    typedef typename Kernel::AssignmentTraits Traits;
+    const Index outerSize = kernel.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      copy_using_evaluator_innervec_InnerUnrolling<Kernel, 0, DstXprType::InnerSizeAtCompileTime,
+                                                   Traits::SrcAlignment, Traits::DstAlignment>::run(kernel, outer);
+  }
+};
+
+/***********************
+*** Linear traversal ***
+***********************/
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, LinearTraversal, NoUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    const Index size = kernel.size();
+    for(Index i = 0; i < size; ++i)
+      kernel.assignCoeff(i);
+  }
+};
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, LinearTraversal, CompleteUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
+    copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
+  }
+};
+
+/**************************
+*** Slice vectorization ***
+***************************/
+
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    typedef typename Kernel::Scalar Scalar;
+    typedef typename Kernel::PacketType PacketType;
+    enum {
+      packetSize = unpacket_traits<PacketType>::size,
+      requestedAlignment = int(Kernel::AssignmentTraits::InnerRequiredAlignment),
+      alignable = packet_traits<Scalar>::AlignedOnScalar || int(Kernel::AssignmentTraits::DstAlignment)>=sizeof(Scalar),
+      dstIsAligned = int(Kernel::AssignmentTraits::DstAlignment)>=int(requestedAlignment),
+      dstAlignment = alignable ? int(requestedAlignment)
+                               : int(Kernel::AssignmentTraits::DstAlignment)
+    };
+    const Scalar *dst_ptr = kernel.dstDataPtr();
+    if((!bool(dstIsAligned)) && (UIntPtr(dst_ptr) % sizeof(Scalar))>0)
+    {
+      // the pointer is not aligend-on scalar, so alignment is not possible
+      return dense_assignment_loop<Kernel,DefaultTraversal,NoUnrolling>::run(kernel);
+    }
+    const Index packetAlignedMask = packetSize - 1;
+    const Index innerSize = kernel.innerSize();
+    const Index outerSize = kernel.outerSize();
+    const Index alignedStep = alignable ? (packetSize - kernel.outerStride() % packetSize) & packetAlignedMask : 0;
+    Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned<requestedAlignment>(dst_ptr, innerSize);
+
+    for(Index outer = 0; outer < outerSize; ++outer)
+    {
+      const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
+      // do the non-vectorizable part of the assignment
+      for(Index inner = 0; inner<alignedStart ; ++inner)
+        kernel.assignCoeffByOuterInner(outer, inner);
+
+      // do the vectorizable part of the assignment
+      for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
+        kernel.template assignPacketByOuterInner<dstAlignment, Unaligned, PacketType>(outer, inner);
+
+      // do the non-vectorizable part of the assignment
+      for(Index inner = alignedEnd; inner<innerSize ; ++inner)
+        kernel.assignCoeffByOuterInner(outer, inner);
+
+      alignedStart = numext::mini((alignedStart+alignedStep)%packetSize, innerSize);
+    }
+  }
+};
+
+#if EIGEN_UNALIGNED_VECTORIZE
+template<typename Kernel>
+struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, InnerUnrolling>
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  {
+    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
+    typedef typename Kernel::PacketType PacketType;
+
+    enum { size = DstXprType::InnerSizeAtCompileTime,
+           packetSize =unpacket_traits<PacketType>::size,
+           vectorizableSize = (size/packetSize)*packetSize };
+
+    for(Index outer = 0; outer < kernel.outerSize(); ++outer)
+    {
+      copy_using_evaluator_innervec_InnerUnrolling<Kernel, 0, vectorizableSize, 0, 0>::run(kernel, outer);
+      copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, vectorizableSize, size>::run(kernel, outer);
+    }
+  }
+};
+#endif
+
+
+/***************************************************************************
+* Part 4 : Generic dense assignment kernel
+***************************************************************************/
+
+// This class generalize the assignment of a coefficient (or packet) from one dense evaluator
+// to another dense writable evaluator.
+// It is parametrized by the two evaluators, and the actual assignment functor.
+// This abstraction level permits to keep the evaluation loops as simple and as generic as possible.
+// One can customize the assignment using this generic dense_assignment_kernel with different
+// functors, or by completely overloading it, by-passing a functor.
+template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version = Specialized>
+class generic_dense_assignment_kernel
+{
+protected:
+  typedef typename DstEvaluatorTypeT::XprType DstXprType;
+  typedef typename SrcEvaluatorTypeT::XprType SrcXprType;
+public:
+  
+  typedef DstEvaluatorTypeT DstEvaluatorType;
+  typedef SrcEvaluatorTypeT SrcEvaluatorType;
+  typedef typename DstEvaluatorType::Scalar Scalar;
+  typedef copy_using_evaluator_traits<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor> AssignmentTraits;
+  typedef typename AssignmentTraits::PacketType PacketType;
+  
+  
+  EIGEN_DEVICE_FUNC generic_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
+    : m_dst(dst), m_src(src), m_functor(func), m_dstExpr(dstExpr)
+  {
+    #ifdef EIGEN_DEBUG_ASSIGN
+    AssignmentTraits::debug();
+    #endif
+  }
+  
+  EIGEN_DEVICE_FUNC Index size() const        { return m_dstExpr.size(); }
+  EIGEN_DEVICE_FUNC Index innerSize() const   { return m_dstExpr.innerSize(); }
+  EIGEN_DEVICE_FUNC Index outerSize() const   { return m_dstExpr.outerSize(); }
+  EIGEN_DEVICE_FUNC Index rows() const        { return m_dstExpr.rows(); }
+  EIGEN_DEVICE_FUNC Index cols() const        { return m_dstExpr.cols(); }
+  EIGEN_DEVICE_FUNC Index outerStride() const { return m_dstExpr.outerStride(); }
+  
+  EIGEN_DEVICE_FUNC DstEvaluatorType& dstEvaluator() { return m_dst; }
+  EIGEN_DEVICE_FUNC const SrcEvaluatorType& srcEvaluator() const { return m_src; }
+  
+  /// Assign src(row,col) to dst(row,col) through the assignment functor.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Index row, Index col)
+  {
+    m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
+  }
+  
+  /// \sa assignCoeff(Index,Index)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Index index)
+  {
+    m_functor.assignCoeff(m_dst.coeffRef(index), m_src.coeff(index));
+  }
+  
+  /// \sa assignCoeff(Index,Index)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeffByOuterInner(Index outer, Index inner)
+  {
+    Index row = rowIndexByOuterInner(outer, inner); 
+    Index col = colIndexByOuterInner(outer, inner); 
+    assignCoeff(row, col);
+  }
+  
+  
+  template<int StoreMode, int LoadMode, typename PacketType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index row, Index col)
+  {
+    m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(row,col), m_src.template packet<LoadMode,PacketType>(row,col));
+  }
+  
+  template<int StoreMode, int LoadMode, typename PacketType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index index)
+  {
+    m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode,PacketType>(index));
+  }
+  
+  template<int StoreMode, int LoadMode, typename PacketType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketByOuterInner(Index outer, Index inner)
+  {
+    Index row = rowIndexByOuterInner(outer, inner); 
+    Index col = colIndexByOuterInner(outer, inner);
+    assignPacket<StoreMode,LoadMode,PacketType>(row, col);
+  }
+  
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner)
+  {
+    typedef typename DstEvaluatorType::ExpressionTraits Traits;
+    return int(Traits::RowsAtCompileTime) == 1 ? 0
+      : int(Traits::ColsAtCompileTime) == 1 ? inner
+      : int(DstEvaluatorType::Flags)&RowMajorBit ? outer
+      : inner;
+  }
+
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner)
+  {
+    typedef typename DstEvaluatorType::ExpressionTraits Traits;
+    return int(Traits::ColsAtCompileTime) == 1 ? 0
+      : int(Traits::RowsAtCompileTime) == 1 ? inner
+      : int(DstEvaluatorType::Flags)&RowMajorBit ? inner
+      : outer;
+  }
+
+  EIGEN_DEVICE_FUNC const Scalar* dstDataPtr() const
+  {
+    return m_dstExpr.data();
+  }
+  
+protected:
+  DstEvaluatorType& m_dst;
+  const SrcEvaluatorType& m_src;
+  const Functor &m_functor;
+  // TODO find a way to avoid the needs of the original expression
+  DstXprType& m_dstExpr;
+};
+
+/***************************************************************************
+* Part 5 : Entry point for dense rectangular assignment
+***************************************************************************/
+
+template<typename DstXprType,typename SrcXprType, typename Functor>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void resize_if_allowed(DstXprType &dst, const SrcXprType& src, const Functor &/*func*/)
+{
+  EIGEN_ONLY_USED_FOR_DEBUG(dst);
+  EIGEN_ONLY_USED_FOR_DEBUG(src);
+  eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
+}
+
+template<typename DstXprType,typename SrcXprType, typename T1, typename T2>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void resize_if_allowed(DstXprType &dst, const SrcXprType& src, const internal::assign_op<T1,T2> &/*func*/)
+{
+  Index dstRows = src.rows();
+  Index dstCols = src.cols();
+  if(((dst.rows()!=dstRows) || (dst.cols()!=dstCols)))
+    dst.resize(dstRows, dstCols);
+  eigen_assert(dst.rows() == dstRows && dst.cols() == dstCols);
+}
+
+template<typename DstXprType, typename SrcXprType, typename Functor>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src, const Functor &func)
+{
+  typedef evaluator<DstXprType> DstEvaluatorType;
+  typedef evaluator<SrcXprType> SrcEvaluatorType;
+
+  SrcEvaluatorType srcEvaluator(src);
+
+  // NOTE To properly handle A = (A*A.transpose())/s with A rectangular,
+  // we need to resize the destination after the source evaluator has been created.
+  resize_if_allowed(dst, src, func);
+
+  DstEvaluatorType dstEvaluator(dst);
+    
+  typedef generic_dense_assignment_kernel<DstEvaluatorType,SrcEvaluatorType,Functor> Kernel;
+  Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
+
+  dense_assignment_loop<Kernel>::run(kernel);
+}
+
+template<typename DstXprType, typename SrcXprType>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src)
+{
+  call_dense_assignment_loop(dst, src, internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>());
+}
+
+/***************************************************************************
+* Part 6 : Generic assignment
+***************************************************************************/
+
+// Based on the respective shapes of the destination and source,
+// the class AssignmentKind determine the kind of assignment mechanism.
+// AssignmentKind must define a Kind typedef.
+template<typename DstShape, typename SrcShape> struct AssignmentKind;
+
+// Assignement kind defined in this file:
+struct Dense2Dense {};
+struct EigenBase2EigenBase {};
+
+template<typename,typename> struct AssignmentKind { typedef EigenBase2EigenBase Kind; };
+template<> struct AssignmentKind<DenseShape,DenseShape> { typedef Dense2Dense Kind; };
+    
+// This is the main assignment class
+template< typename DstXprType, typename SrcXprType, typename Functor,
+          typename Kind = typename AssignmentKind< typename evaluator_traits<DstXprType>::Shape , typename evaluator_traits<SrcXprType>::Shape >::Kind,
+          typename EnableIf = void>
+struct Assignment;
+
+
+// The only purpose of this call_assignment() function is to deal with noalias() / "assume-aliasing" and automatic transposition.
+// Indeed, I (Gael) think that this concept of "assume-aliasing" was a mistake, and it makes thing quite complicated.
+// So this intermediate function removes everything related to "assume-aliasing" such that Assignment
+// does not has to bother about these annoying details.
+
+template<typename Dst, typename Src>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment(Dst& dst, const Src& src)
+{
+  call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
+}
+template<typename Dst, typename Src>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment(const Dst& dst, const Src& src)
+{
+  call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
+}
+                     
+// Deal with "assume-aliasing"
+template<typename Dst, typename Src, typename Func>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if< evaluator_assume_aliasing<Src>::value, void*>::type = 0)
+{
+  typename plain_matrix_type<Src>::type tmp(src);
+  call_assignment_no_alias(dst, tmp, func);
+}
+
+template<typename Dst, typename Src, typename Func>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if<!evaluator_assume_aliasing<Src>::value, void*>::type = 0)
+{
+  call_assignment_no_alias(dst, src, func);
+}
+
+// by-pass "assume-aliasing"
+// When there is no aliasing, we require that 'dst' has been properly resized
+template<typename Dst, template <typename> class StorageBase, typename Src, typename Func>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment(NoAlias<Dst,StorageBase>& dst, const Src& src, const Func& func)
+{
+  call_assignment_no_alias(dst.expression(), src, func);
+}
+
+
+template<typename Dst, typename Src, typename Func>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment_no_alias(Dst& dst, const Src& src, const Func& func)
+{
+  enum {
+    NeedToTranspose = (    (int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1)
+                        || (int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1)
+                      ) && int(Dst::SizeAtCompileTime) != 1
+  };
+
+  typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst>::type ActualDstTypeCleaned;
+  typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst&>::type ActualDstType;
+  ActualDstType actualDst(dst);
+  
+  // TODO check whether this is the right place to perform these checks:
+  EIGEN_STATIC_ASSERT_LVALUE(Dst)
+  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned,Src)
+  EIGEN_CHECK_BINARY_COMPATIBILIY(Func,typename ActualDstTypeCleaned::Scalar,typename Src::Scalar);
+  
+  Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
+}
+template<typename Dst, typename Src>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment_no_alias(Dst& dst, const Src& src)
+{
+  call_assignment_no_alias(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
+}
+
+template<typename Dst, typename Src, typename Func>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src, const Func& func)
+{
+  // TODO check whether this is the right place to perform these checks:
+  EIGEN_STATIC_ASSERT_LVALUE(Dst)
+  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Dst,Src)
+  EIGEN_CHECK_BINARY_COMPATIBILIY(Func,typename Dst::Scalar,typename Src::Scalar);
+
+  Assignment<Dst,Src,Func>::run(dst, src, func);
+}
+template<typename Dst, typename Src>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src)
+{
+  call_assignment_no_alias_no_transpose(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
+}
+
+// forward declaration
+template<typename Dst, typename Src> void check_for_aliasing(const Dst &dst, const Src &src);
+
+// Generic Dense to Dense assignment
+// Note that the last template argument "Weak" is needed to make it possible to perform
+// both partial specialization+SFINAE without ambiguous specialization
+template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
+struct Assignment<DstXprType, SrcXprType, Functor, Dense2Dense, Weak>
+{
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
+  {
+#ifndef EIGEN_NO_DEBUG
+    internal::check_for_aliasing(dst, src);
+#endif
+    
+    call_dense_assignment_loop(dst, src, func);
+  }
+};
+
+// Generic assignment through evalTo.
+// TODO: not sure we have to keep that one, but it helps porting current code to new evaluator mechanism.
+// Note that the last template argument "Weak" is needed to make it possible to perform
+// both partial specialization+SFINAE without ambiguous specialization
+template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
+struct Assignment<DstXprType, SrcXprType, Functor, EigenBase2EigenBase, Weak>
+{
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
+    src.evalTo(dst);
+  }
+
+  // NOTE The following two functions are templated to avoid their instanciation if not needed
+  //      This is needed because some expressions supports evalTo only and/or have 'void' as scalar type.
+  template<typename SrcScalarType>
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,SrcScalarType> &/*func*/)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
+    src.addTo(dst);
+  }
+
+  template<typename SrcScalarType>
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,SrcScalarType> &/*func*/)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
+    src.subTo(dst);
+  }
+};
+
+} // namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_ASSIGN_EVALUATOR_H

Index: 3rd_party/eigen/Eigen/src/Core/Assign_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Assign_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/Assign_MKL.h
@@ -1,8 +1,9 @@
 /*
  Copyright (c) 2011, Intel Corporation. All rights reserved.
-
+ Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+ 
  Redistribution and use in source and binary forms, with or without modification,
  are permitted provided that the following conditions are met:
 
  * Redistributions of source code must retain the above copyright notice, this
    list of conditions and the following disclaimer.
@@ -35,190 +36,141 @@
 
 namespace Eigen { 
 
 namespace internal {
 
-template<typename Op> struct vml_call
-{ enum { IsSupported = 0 }; };
-
-template<typename Dst, typename Src, typename UnaryOp>
+template<typename Dst, typename Src>
 class vml_assign_traits
 {
   private:
     enum {
       DstHasDirectAccess = Dst::Flags & DirectAccessBit,
       SrcHasDirectAccess = Src::Flags & DirectAccessBit,
-
       StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
       InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
                 : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
                 : int(Dst::RowsAtCompileTime),
       InnerMaxSize  = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
                     : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
                     : int(Dst::MaxRowsAtCompileTime),
       MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
 
-      MightEnableVml =  vml_call<UnaryOp>::IsSupported && StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess
-                     && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
-      MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
-      VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
-      LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD,
-      MayEnableVml = MightEnableVml && LargeEnough,
-      MayLinearize = MayEnableVml && MightLinearize
-    };
-  public:
-    enum {
-      Traversal = MayLinearize ? LinearVectorizedTraversal
-                : MayEnableVml ? InnerVectorizedTraversal
-                : DefaultTraversal
-    };
-};
-
-template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling,
-         int VmlTraversal = vml_assign_traits<Derived1, Derived2, UnaryOp>::Traversal >
-struct vml_assign_impl
-  : assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>
-{
-};
-
-template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
-struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, InnerVectorizedTraversal>
-{
-  typedef typename Derived1::Scalar Scalar;
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
-  {
-    // in case we want to (or have to) skip VML at runtime we can call:
-    // assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
-    const Index innerSize = dst.innerSize();
-    const Index outerSize = dst.outerSize();
-    for(Index outer = 0; outer < outerSize; ++outer) {
-      const Scalar *src_ptr = src.IsRowMajor ?  &(src.nestedExpression().coeffRef(outer,0)) :
-                                                &(src.nestedExpression().coeffRef(0, outer));
-      Scalar *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));
-      vml_call<UnaryOp>::run(src.functor(), innerSize, src_ptr, dst_ptr );
-    }
-  }
-};
-
-template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
-struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, LinearVectorizedTraversal>
-{
-  static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
-  {
-    // in case we want to (or have to) skip VML at runtime we can call:
-    // assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
-    vml_call<UnaryOp>::run(src.functor(), dst.size(), src.nestedExpression().data(), dst.data() );
-  }
-};
-
-// Macroses
-
-#define EIGEN_MKL_VML_SPECIALIZE_ASSIGN(TRAVERSAL,UNROLLING) \
-  template<typename Derived1, typename Derived2, typename UnaryOp> \
-  struct assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>, TRAVERSAL, UNROLLING, Specialized>  {  \
-    static inline void run(Derived1 &dst, const Eigen::CwiseUnaryOp<UnaryOp, Derived2> &src) { \
-      vml_assign_impl<Derived1,Derived2,UnaryOp,TRAVERSAL,UNROLLING>::run(dst, src); \
-    } \
-  };
-
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,NoUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,CompleteUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,InnerUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,NoUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,CompleteUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,NoUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,CompleteUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,InnerUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,CompleteUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,NoUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(SliceVectorizedTraversal,NoUnrolling)
-
-
-#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
-#define  EIGEN_MKL_VML_MODE VML_HA
-#else
-#define  EIGEN_MKL_VML_MODE VML_LA
-#endif
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)     \
-  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
-    enum { IsSupported = 1 };                                                    \
-    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/,        \
-                            int size, const EIGENTYPE* src, EIGENTYPE* dst) {    \
-      VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst);                           \
-    }                                                                            \
-  };
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)  \
-  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
-    enum { IsSupported = 1 };                                                    \
-    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/,        \
-                            int size, const EIGENTYPE* src, EIGENTYPE* dst) {    \
-      MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE;                                    \
-      VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst, vmlMode);                  \
-    }                                                                            \
-  };
-
-#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)       \
-  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
-    enum { IsSupported = 1 };                                                    \
-    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& func,        \
-                          int size, const EIGENTYPE* src, EIGENTYPE* dst) {      \
-      EIGENTYPE exponent = func.m_exponent;                                      \
-      MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE;                                    \
-      VMLOP(&size, (const VMLTYPE*)src, (const VMLTYPE*)&exponent,               \
-                        (VMLTYPE*)dst, &vmlMode);                                \
-    }                                                                            \
-  };
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP)                   \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vs##VMLOP, float, float)             \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vd##VMLOP, double, double)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)                \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vc##VMLOP, scomplex, MKL_Complex8)   \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vz##VMLOP, dcomplex, MKL_Complex16)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP)                        \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP)                         \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)
-
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP)                \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vms##VMLOP, float, float)         \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmd##VMLOP, double, double)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)             \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmc##VMLOP, scomplex, MKL_Complex8)  \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmz##VMLOP, dcomplex, MKL_Complex16)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(EIGENOP, VMLOP)                     \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP)                      \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)
-
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sin,  Sin)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(asin, Asin)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(cos,  Cos)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(acos, Acos)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(tan,  Tan)
-//EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs,  Abs)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(exp,  Exp)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(log,  Ln)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sqrt, Sqrt)
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr)
-
-// The vm*powx functions are not avaibale in the windows version of MKL.
-#ifndef _WIN32
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzpowx_, dcomplex, MKL_Complex16)
-#endif
+      MightEnableVml = StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
+      MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
+      VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
+      LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD
+    };
+  public:
+    enum {
+      EnableVml = MightEnableVml && LargeEnough,
+      Traversal = MightLinearize ? LinearTraversal : DefaultTraversal
+    };
+};
+
+#define EIGEN_PP_EXPAND(ARG) ARG
+#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
+#define EIGEN_VMLMODE_EXPAND_LA , VML_HA
+#else
+#define EIGEN_VMLMODE_EXPAND_LA , VML_LA
+#endif
+
+#define EIGEN_VMLMODE_EXPAND__ 
+
+#define EIGEN_VMLMODE_PREFIX_LA vm
+#define EIGEN_VMLMODE_PREFIX__  v
+#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_,VMLMODE)
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE)                                           \
+  template< typename DstXprType, typename SrcXprNested>                                                                         \
+  struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE,EIGENTYPE>,   \
+                   Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> {              \
+    typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType;                                            \
+    static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &/*func*/) {                   \
+      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());                                                       \
+      if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) {                                              \
+        VMLOP(dst.size(), (const VMLTYPE*)src.nestedExpression().data(),                                                        \
+              (VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE) );                                           \
+      } else {                                                                                                                  \
+        const Index outerSize = dst.outerSize();                                                                                \
+        for(Index outer = 0; outer < outerSize; ++outer) {                                                                      \
+          const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) :                             \
+                                                      &(src.nestedExpression().coeffRef(0, outer));                             \
+          EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));                           \
+          VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr,                                                                      \
+                (VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE));                                             \
+        }                                                                                                                       \
+      }                                                                                                                         \
+    }                                                                                                                           \
+  };                                                                                                                            \
+
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE)                                                         \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),s##VMLOP), float, float, VMLMODE)           \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),d##VMLOP), double, double, VMLMODE)
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)                                                         \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),c##VMLOP), scomplex, MKL_Complex8, VMLMODE) \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),z##VMLOP), dcomplex, MKL_Complex16, VMLMODE)
+  
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE)                                                              \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE)                                                               \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)
+
+  
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin,   Sin,   LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin,  Asin,  LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh,  Sinh,  LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos,   Cos,   LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos,  Acos,  LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh,  Cosh,  LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan,   Tan,   LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan,  Atan,  LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh,  Tanh,  LA)
+// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs,   Abs,    _)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp,   Exp,   LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log,   Ln,    LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt,  Sqrt,  _)
+
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr,   _)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg,      _)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round,  _)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor,  _)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil,  Ceil,   _)
+
+#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE)                                           \
+  template< typename DstXprType, typename SrcXprNested, typename Plain>                                                       \
+  struct Assignment<DstXprType, CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested,                       \
+                    const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> >, assign_op<EIGENTYPE,EIGENTYPE>,    \
+                   Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> {            \
+    typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested,                                           \
+                    const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> > SrcXprType;                         \
+    static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &/*func*/) {                 \
+      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());                                                     \
+      VMLTYPE exponent = reinterpret_cast<const VMLTYPE&>(src.rhs().functor().m_other);                                       \
+      if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal)                                              \
+      {                                                                                                                       \
+        VMLOP( dst.size(), (const VMLTYPE*)src.lhs().data(), exponent,                                                        \
+              (VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE) );                                         \
+      } else {                                                                                                                \
+        const Index outerSize = dst.outerSize();                                                                              \
+        for(Index outer = 0; outer < outerSize; ++outer) {                                                                    \
+          const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.lhs().coeffRef(outer,0)) :                                        \
+                                                      &(src.lhs().coeffRef(0, outer));                                        \
+          EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));                         \
+          VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, exponent,                                                          \
+                 (VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE));                                          \
+        }                                                                                                                     \
+      }                                                                                                                       \
+    }                                                                                                                         \
+  };
+  
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float,    float,         LA)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double,   double,        LA)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8,  LA)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA)
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_ASSIGN_VML_H

Index: 3rd_party/eigen/Eigen/src/Core/BandMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/BandMatrix.h
+++ 3rd_party/eigen/Eigen/src/Core/BandMatrix.h
@@ -30,11 +30,11 @@
       Subs   = internal::traits<Derived>::Subs,
       Options = internal::traits<Derived>::Options
     };
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
-    typedef typename DenseMatrixType::Index Index;
+    typedef typename DenseMatrixType::StorageIndex StorageIndex;
     typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
     typedef EigenBase<Derived> Base;
 
   protected:
     enum {
@@ -159,29 +159,29 @@
   * \class BandMatrix
   * \ingroup Core_Module
   *
   * \brief Represents a rectangular matrix with a banded storage
   *
-  * \param _Scalar Numeric type, i.e. float, double, int
-  * \param Rows Number of rows, or \b Dynamic
-  * \param Cols Number of columns, or \b Dynamic
-  * \param Supers Number of super diagonal
-  * \param Subs Number of sub diagonal
-  * \param _Options A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
-  *                 The former controls \ref TopicStorageOrders "storage order", and defaults to
-  *                 column-major. The latter controls whether the matrix represents a selfadjoint 
-  *                 matrix in which case either Supers of Subs have to be null.
+  * \tparam _Scalar Numeric type, i.e. float, double, int
+  * \tparam _Rows Number of rows, or \b Dynamic
+  * \tparam _Cols Number of columns, or \b Dynamic
+  * \tparam _Supers Number of super diagonal
+  * \tparam _Subs Number of sub diagonal
+  * \tparam _Options A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
+  *                  The former controls \ref TopicStorageOrders "storage order", and defaults to
+  *                  column-major. The latter controls whether the matrix represents a selfadjoint
+  *                  matrix in which case either Supers of Subs have to be null.
   *
   * \sa class TridiagonalMatrix
   */
 
 template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
 struct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
 {
   typedef _Scalar Scalar;
   typedef Dense StorageKind;
-  typedef DenseIndex Index;
+  typedef Eigen::Index StorageIndex;
   enum {
     CoeffReadCost = NumTraits<Scalar>::ReadCost,
     RowsAtCompileTime = _Rows,
     ColsAtCompileTime = _Cols,
     MaxRowsAtCompileTime = _Rows,
@@ -199,14 +199,14 @@
 class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Subs,Options> >
 {
   public:
 
     typedef typename internal::traits<BandMatrix>::Scalar Scalar;
-    typedef typename internal::traits<BandMatrix>::Index Index;
+    typedef typename internal::traits<BandMatrix>::StorageIndex StorageIndex;
     typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
 
-    inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
+    explicit inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
       : m_coeffs(1+supers+subs,cols),
         m_rows(rows), m_supers(supers), m_subs(subs)
     {
     }
 
@@ -239,11 +239,11 @@
 template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
 struct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
 {
   typedef typename _CoefficientsType::Scalar Scalar;
   typedef typename _CoefficientsType::StorageKind StorageKind;
-  typedef typename _CoefficientsType::Index Index;
+  typedef typename _CoefficientsType::StorageIndex StorageIndex;
   enum {
     CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
     RowsAtCompileTime = _Rows,
     ColsAtCompileTime = _Cols,
     MaxRowsAtCompileTime = _Rows,
@@ -262,13 +262,13 @@
 {
   public:
 
     typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
     typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
-    typedef typename internal::traits<BandMatrixWrapper>::Index Index;
+    typedef typename internal::traits<BandMatrixWrapper>::StorageIndex StorageIndex;
 
-    inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
+    explicit inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
       : m_coeffs(coeffs),
         m_rows(rows), m_supers(supers), m_subs(subs)
     {
       EIGEN_UNUSED_VARIABLE(cols);
       //internal::assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
@@ -300,23 +300,23 @@
   * \class TridiagonalMatrix
   * \ingroup Core_Module
   *
   * \brief Represents a tridiagonal matrix with a compact banded storage
   *
-  * \param _Scalar Numeric type, i.e. float, double, int
-  * \param Size Number of rows and cols, or \b Dynamic
-  * \param _Options Can be 0 or \b SelfAdjoint
+  * \tparam Scalar Numeric type, i.e. float, double, int
+  * \tparam Size Number of rows and cols, or \b Dynamic
+  * \tparam Options Can be 0 or \b SelfAdjoint
   *
   * \sa class BandMatrix
   */
 template<typename Scalar, int Size, int Options>
 class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor>
 {
     typedef BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> Base;
-    typedef typename Base::Index Index;
+    typedef typename Base::StorageIndex StorageIndex;
   public:
-    TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
+    explicit TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
 
     inline typename Base::template DiagonalIntReturnType<1>::Type super()
     { return Base::template diagonal<1>(); }
     inline const typename Base::template DiagonalIntReturnType<1>::Type super() const
     { return Base::template diagonal<1>(); }
@@ -325,10 +325,29 @@
     inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const
     { return Base::template diagonal<-1>(); }
   protected:
 };
 
+
+struct BandShape {};
+
+template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
+struct evaluator_traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
+  : public evaluator_traits_base<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
+{
+  typedef BandShape Shape;
+};
+
+template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
+struct evaluator_traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+  : public evaluator_traits_base<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+{
+  typedef BandShape Shape;
+};
+
+template<> struct AssignmentKind<DenseShape,BandShape> { typedef EigenBase2EigenBase Kind; };
+
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_BANDMATRIX_H

Index: 3rd_party/eigen/Eigen/src/Core/Block.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Block.h
+++ 3rd_party/eigen/Eigen/src/Core/Block.h
@@ -11,18 +11,74 @@
 #ifndef EIGEN_BLOCK_H
 #define EIGEN_BLOCK_H
 
 namespace Eigen { 
 
+namespace internal {
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
+struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprType>
+{
+  typedef typename traits<XprType>::Scalar Scalar;
+  typedef typename traits<XprType>::StorageKind StorageKind;
+  typedef typename traits<XprType>::XprKind XprKind;
+  typedef typename ref_selector<XprType>::type XprTypeNested;
+  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
+  enum{
+    MatrixRows = traits<XprType>::RowsAtCompileTime,
+    MatrixCols = traits<XprType>::ColsAtCompileTime,
+    RowsAtCompileTime = MatrixRows == 0 ? 0 : BlockRows,
+    ColsAtCompileTime = MatrixCols == 0 ? 0 : BlockCols,
+    MaxRowsAtCompileTime = BlockRows==0 ? 0
+                         : RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime)
+                         : int(traits<XprType>::MaxRowsAtCompileTime),
+    MaxColsAtCompileTime = BlockCols==0 ? 0
+                         : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
+                         : int(traits<XprType>::MaxColsAtCompileTime),
+
+    XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
+    IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
+               : (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
+               : XprTypeIsRowMajor,
+    HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor),
+    InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
+    InnerStrideAtCompileTime = HasSameStorageOrderAsXprType
+                             ? int(inner_stride_at_compile_time<XprType>::ret)
+                             : int(outer_stride_at_compile_time<XprType>::ret),
+    OuterStrideAtCompileTime = HasSameStorageOrderAsXprType
+                             ? int(outer_stride_at_compile_time<XprType>::ret)
+                             : int(inner_stride_at_compile_time<XprType>::ret),
+
+    // FIXME, this traits is rather specialized for dense object and it needs to be cleaned further
+    FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
+    FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
+    Flags = (traits<XprType>::Flags & (DirectAccessBit | (InnerPanel?CompressedAccessBit:0))) | FlagsLvalueBit | FlagsRowMajorBit,
+    // FIXME DirectAccessBit should not be handled by expressions
+    // 
+    // Alignment is needed by MapBase's assertions
+    // We can sefely set it to false here. Internal alignment errors will be detected by an eigen_internal_assert in the respective evaluator
+    Alignment = 0
+  };
+};
+
+template<typename XprType, int BlockRows=Dynamic, int BlockCols=Dynamic, bool InnerPanel = false,
+         bool HasDirectAccess = internal::has_direct_access<XprType>::ret> class BlockImpl_dense;
+         
+} // end namespace internal
+
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, typename StorageKind> class BlockImpl;
+
 /** \class Block
   * \ingroup Core_Module
   *
   * \brief Expression of a fixed-size or dynamic-size block
   *
-  * \param XprType the type of the expression in which we are taking a block
-  * \param BlockRows the number of rows of the block we are taking at compile time (optional)
-  * \param BlockCols the number of columns of the block we are taking at compile time (optional)
+  * \tparam XprType the type of the expression in which we are taking a block
+  * \tparam BlockRows the number of rows of the block we are taking at compile time (optional)
+  * \tparam BlockCols the number of columns of the block we are taking at compile time (optional)
+  * \tparam InnerPanel is true, if the block maps to a set of rows of a row major matrix or
+  *         to set of columns of a column major matrix (optional). The parameter allows to determine
+  *         at compile time whether aligned access is possible on the block expression.
   *
   * This class represents an expression of either a fixed-size or dynamic-size block. It is the return
   * type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block<int,int>(Index,Index) and
   * most of the time this is the only way it is used.
   *
@@ -42,105 +98,55 @@
   * \include class_FixedBlock.cpp
   * Output: \verbinclude class_FixedBlock.out
   *
   * \sa DenseBase::block(Index,Index,Index,Index), DenseBase::block(Index,Index), class VectorBlock
   */
-
-namespace internal {
-template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
-struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprType>
-{
-  typedef typename traits<XprType>::Scalar Scalar;
-  typedef typename traits<XprType>::StorageKind StorageKind;
-  typedef typename traits<XprType>::XprKind XprKind;
-  typedef typename nested<XprType>::type XprTypeNested;
-  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
-  enum{
-    MatrixRows = traits<XprType>::RowsAtCompileTime,
-    MatrixCols = traits<XprType>::ColsAtCompileTime,
-    RowsAtCompileTime = MatrixRows == 0 ? 0 : BlockRows,
-    ColsAtCompileTime = MatrixCols == 0 ? 0 : BlockCols,
-    MaxRowsAtCompileTime = BlockRows==0 ? 0
-                         : RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime)
-                         : int(traits<XprType>::MaxRowsAtCompileTime),
-    MaxColsAtCompileTime = BlockCols==0 ? 0
-                         : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
-                         : int(traits<XprType>::MaxColsAtCompileTime),
-    XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
-    IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
-               : (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
-               : XprTypeIsRowMajor,
-    HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor),
-    InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
-    InnerStrideAtCompileTime = HasSameStorageOrderAsXprType
-                             ? int(inner_stride_at_compile_time<XprType>::ret)
-                             : int(outer_stride_at_compile_time<XprType>::ret),
-    OuterStrideAtCompileTime = HasSameStorageOrderAsXprType
-                             ? int(outer_stride_at_compile_time<XprType>::ret)
-                             : int(inner_stride_at_compile_time<XprType>::ret),
-    MaskPacketAccessBit = (InnerSize == Dynamic || (InnerSize % packet_traits<Scalar>::size) == 0)
-                       && (InnerStrideAtCompileTime == 1)
-                        ? PacketAccessBit : 0,
-    MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % 16) == 0)) ? AlignedBit : 0,
-    FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || (InnerPanel && (traits<XprType>::Flags&LinearAccessBit))) ? LinearAccessBit : 0,
-    FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
-    FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
-    Flags0 = traits<XprType>::Flags & ( (HereditaryBits & ~RowMajorBit) |
-                                        DirectAccessBit |
-                                        MaskPacketAccessBit |
-                                        MaskAlignedBit),
-    Flags = Flags0 | FlagsLinearAccessBit | FlagsLvalueBit | FlagsRowMajorBit
-  };
-};
-
-template<typename XprType, int BlockRows=Dynamic, int BlockCols=Dynamic, bool InnerPanel = false,
-         bool HasDirectAccess = internal::has_direct_access<XprType>::ret> class BlockImpl_dense;
-         
-} // end namespace internal
-
-template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, typename StorageKind> class BlockImpl;
-
 template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
   : public BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind>
 {
     typedef BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind> Impl;
   public:
     //typedef typename Impl::Base Base;
     typedef Impl Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(Block)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
+    
+    typedef typename internal::remove_all<XprType>::type NestedExpression;
   
     /** Column or Row constructor
       */
+    EIGEN_DEVICE_FUNC
     inline Block(XprType& xpr, Index i) : Impl(xpr,i)
     {
       eigen_assert( (i>=0) && (
           ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i<xpr.rows())
         ||((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && i<xpr.cols())));
     }
 
     /** Fixed-size constructor
       */
-    inline Block(XprType& xpr, Index a_startRow, Index a_startCol)
-      : Impl(xpr, a_startRow, a_startCol)
+    EIGEN_DEVICE_FUNC
+    inline Block(XprType& xpr, Index startRow, Index startCol)
+      : Impl(xpr, startRow, startCol)
     {
       EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
-      eigen_assert(a_startRow >= 0 && BlockRows >= 1 && a_startRow + BlockRows <= xpr.rows()
-             && a_startCol >= 0 && BlockCols >= 1 && a_startCol + BlockCols <= xpr.cols());
+      eigen_assert(startRow >= 0 && BlockRows >= 0 && startRow + BlockRows <= xpr.rows()
+             && startCol >= 0 && BlockCols >= 0 && startCol + BlockCols <= xpr.cols());
     }
 
     /** Dynamic-size constructor
       */
+    EIGEN_DEVICE_FUNC
     inline Block(XprType& xpr,
-          Index a_startRow, Index a_startCol,
+          Index startRow, Index startCol,
           Index blockRows, Index blockCols)
-      : Impl(xpr, a_startRow, a_startCol, blockRows, blockCols)
+      : Impl(xpr, startRow, startCol, blockRows, blockCols)
     {
       eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
           && (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
-      eigen_assert(a_startRow >= 0 && blockRows >= 0 && a_startRow  <= xpr.rows() - blockRows
-          && a_startCol >= 0 && blockCols >= 0 && a_startCol <= xpr.cols() - blockCols);
+      eigen_assert(startRow >= 0 && blockRows >= 0 && startRow  <= xpr.rows() - blockRows
+          && startCol >= 0 && blockCols >= 0 && startCol <= xpr.cols() - blockCols);
     }
 };
          
 // The generic default implementation for dense block simplu forward to the internal::BlockImpl_dense
 // that must be specialized for direct and non-direct access...
@@ -147,37 +153,40 @@
 template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
 class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
   : public internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel>
 {
     typedef internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> Impl;
-    typedef typename XprType::Index Index;
+    typedef typename XprType::StorageIndex StorageIndex;
   public:
     typedef Impl Base;
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
-    inline BlockImpl(XprType& xpr, Index i) : Impl(xpr,i) {}
-    inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol) : Impl(xpr, a_startRow, a_startCol) {}
-    inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol, Index blockRows, Index blockCols)
-      : Impl(xpr, a_startRow, a_startCol, blockRows, blockCols) {}
+    EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index i) : Impl(xpr,i) {}
+    EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index startRow, Index startCol) : Impl(xpr, startRow, startCol) {}
+    EIGEN_DEVICE_FUNC
+    inline BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
+      : Impl(xpr, startRow, startCol, blockRows, blockCols) {}
 };
 
 namespace internal {
 
 /** \internal Internal implementation of dense Blocks in the general case. */
 template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
   : public internal::dense_xpr_base<Block<XprType, BlockRows, BlockCols, InnerPanel> >::type
 {
     typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
+    typedef typename internal::ref_selector<XprType>::non_const_type XprTypeNested;
   public:
 
     typedef typename internal::dense_xpr_base<BlockType>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
 
-    class InnerIterator;
+    // class InnerIterator; // FIXME apparently never used
 
     /** Column or Row constructor
       */
+    EIGEN_DEVICE_FUNC
     inline BlockImpl_dense(XprType& xpr, Index i)
       : m_xpr(xpr),
         // It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime,
         // and it is a column if and only if BlockRows==XprType::RowsAtCompileTime and BlockCols==1,
         // all other cases are invalid.
@@ -188,79 +197,80 @@
         m_blockCols(BlockCols==1 ? 1 : xpr.cols())
     {}
 
     /** Fixed-size constructor
       */
-    inline BlockImpl_dense(XprType& xpr, Index a_startRow, Index a_startCol)
-      : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
+    EIGEN_DEVICE_FUNC
+    inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
+      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
                     m_blockRows(BlockRows), m_blockCols(BlockCols)
     {}
 
     /** Dynamic-size constructor
       */
+    EIGEN_DEVICE_FUNC
     inline BlockImpl_dense(XprType& xpr,
-          Index a_startRow, Index a_startCol,
+          Index startRow, Index startCol,
           Index blockRows, Index blockCols)
-      : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
+      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
                     m_blockRows(blockRows), m_blockCols(blockCols)
     {}
 
-    inline Index rows() const { return m_blockRows.value(); }
-    inline Index cols() const { return m_blockCols.value(); }
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_blockRows.value(); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_blockCols.value(); }
 
+    EIGEN_DEVICE_FUNC
     inline Scalar& coeffRef(Index rowId, Index colId)
     {
       EIGEN_STATIC_ASSERT_LVALUE(XprType)
-      return m_xpr.const_cast_derived()
-               .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
+      return m_xpr.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
-      return m_xpr.derived()
-               .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
+      return m_xpr.derived().coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const
     {
       return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
+    EIGEN_DEVICE_FUNC
     inline Scalar& coeffRef(Index index)
     {
       EIGEN_STATIC_ASSERT_LVALUE(XprType)
-      return m_xpr.const_cast_derived()
-             .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                       m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
+      return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+                            m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
     }
 
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index index) const
     {
-      return m_xpr.const_cast_derived()
-             .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                       m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
+      return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+                            m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
     }
 
+    EIGEN_DEVICE_FUNC
     inline const CoeffReturnType coeff(Index index) const
     {
-      return m_xpr
-             .coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                    m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
+      return m_xpr.coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+                         m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
     }
 
     template<int LoadMode>
     inline PacketScalar packet(Index rowId, Index colId) const
     {
-      return m_xpr.template packet<Unaligned>
-              (rowId + m_startRow.value(), colId + m_startCol.value());
+      return m_xpr.template packet<Unaligned>(rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
     template<int LoadMode>
     inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
     {
-      m_xpr.const_cast_derived().template writePacket<Unaligned>
-              (rowId + m_startRow.value(), colId + m_startCol.value(), val);
+      m_xpr.template writePacket<Unaligned>(rowId + m_startRow.value(), colId + m_startCol.value(), val);
     }
 
     template<int LoadMode>
     inline PacketScalar packet(Index index) const
     {
@@ -270,136 +280,173 @@
     }
 
     template<int LoadMode>
     inline void writePacket(Index index, const PacketScalar& val)
     {
-      m_xpr.const_cast_derived().template writePacket<Unaligned>
+      m_xpr.template writePacket<Unaligned>
          (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
           m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val);
     }
 
     #ifdef EIGEN_PARSED_BY_DOXYGEN
     /** \sa MapBase::data() */
-    inline const Scalar* data() const;
-    inline Index innerStride() const;
-    inline Index outerStride() const;
+    EIGEN_DEVICE_FUNC inline const Scalar* data() const;
+    EIGEN_DEVICE_FUNC inline Index innerStride() const;
+    EIGEN_DEVICE_FUNC inline Index outerStride() const;
     #endif
 
-    const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const 
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<XprTypeNested>::type& nestedExpression() const
     { 
       return m_xpr; 
     }
+
+    EIGEN_DEVICE_FUNC
+    XprType& nestedExpression() { return m_xpr; }
       
-    Index startRow() const 
+    EIGEN_DEVICE_FUNC
+    StorageIndex startRow() const
     { 
       return m_startRow.value(); 
     }
       
-    Index startCol() const 
+    EIGEN_DEVICE_FUNC
+    StorageIndex startCol() const
     { 
       return m_startCol.value(); 
     }
 
   protected:
 
-    const typename XprType::Nested m_xpr;
-    const internal::variable_if_dynamic<Index, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
-    const internal::variable_if_dynamic<Index, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
-    const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_blockRows;
-    const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_blockCols;
+    XprTypeNested m_xpr;
+    const internal::variable_if_dynamic<StorageIndex, (XprType::RowsAtCompileTime == 1 && BlockRows==1) ? 0 : Dynamic> m_startRow;
+    const internal::variable_if_dynamic<StorageIndex, (XprType::ColsAtCompileTime == 1 && BlockCols==1) ? 0 : Dynamic> m_startCol;
+    const internal::variable_if_dynamic<StorageIndex, RowsAtCompileTime> m_blockRows;
+    const internal::variable_if_dynamic<StorageIndex, ColsAtCompileTime> m_blockCols;
 };
 
 /** \internal Internal implementation of dense Blocks in the direct access case.*/
 template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
 class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
   : public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel> >
 {
     typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
+    typedef typename internal::ref_selector<XprType>::non_const_type XprTypeNested;
+    enum {
+      XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0
+    };
   public:
 
     typedef MapBase<BlockType> Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
 
     /** Column or Row constructor
       */
+    EIGEN_DEVICE_FUNC
     inline BlockImpl_dense(XprType& xpr, Index i)
-      : Base(internal::const_cast_ptr(&xpr.coeffRef(
-              (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0,
-              (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0)),
+      : Base(xpr.data() + i * (    ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && (!XprTypeIsRowMajor)) 
+                                || ((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && ( XprTypeIsRowMajor)) ? xpr.innerStride() : xpr.outerStride()),
              BlockRows==1 ? 1 : xpr.rows(),
              BlockCols==1 ? 1 : xpr.cols()),
-        m_xpr(xpr)
+        m_xpr(xpr),
+        m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0),
+        m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0)
     {
       init();
     }
 
     /** Fixed-size constructor
       */
+    EIGEN_DEVICE_FUNC
     inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
-      : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol))), m_xpr(xpr)
+      : Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol)),
+        m_xpr(xpr), m_startRow(startRow), m_startCol(startCol)
     {
       init();
     }
 
     /** Dynamic-size constructor
       */
+    EIGEN_DEVICE_FUNC
     inline BlockImpl_dense(XprType& xpr,
           Index startRow, Index startCol,
           Index blockRows, Index blockCols)
-      : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol)), blockRows, blockCols),
-        m_xpr(xpr)
+      : Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol), blockRows, blockCols),
+        m_xpr(xpr), m_startRow(startRow), m_startCol(startCol)
     {
       init();
     }
 
-    const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const 
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<XprTypeNested>::type& nestedExpression() const
     { 
       return m_xpr; 
     }
+
+    EIGEN_DEVICE_FUNC
+    XprType& nestedExpression() { return m_xpr; }
       
     /** \sa MapBase::innerStride() */
+    EIGEN_DEVICE_FUNC
     inline Index innerStride() const
     {
       return internal::traits<BlockType>::HasSameStorageOrderAsXprType
              ? m_xpr.innerStride()
              : m_xpr.outerStride();
     }
 
     /** \sa MapBase::outerStride() */
+    EIGEN_DEVICE_FUNC
     inline Index outerStride() const
     {
       return m_outerStride;
     }
+
+    EIGEN_DEVICE_FUNC
+    StorageIndex startRow() const
+    {
+      return m_startRow.value();
+    }
+
+    EIGEN_DEVICE_FUNC
+    StorageIndex startCol() const
+    {
+      return m_startCol.value();
+    }
 
   #ifndef __SUNPRO_CC
   // FIXME sunstudio is not friendly with the above friend...
   // META-FIXME there is no 'friend' keyword around here. Is this obsolete?
   protected:
   #endif
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** \internal used by allowAligned() */
+    EIGEN_DEVICE_FUNC
     inline BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows, Index blockCols)
       : Base(data, blockRows, blockCols), m_xpr(xpr)
     {
       init();
     }
     #endif
 
   protected:
+    EIGEN_DEVICE_FUNC
     void init()
     {
       m_outerStride = internal::traits<BlockType>::HasSameStorageOrderAsXprType
                     ? m_xpr.outerStride()
                     : m_xpr.innerStride();
     }
 
-    typename XprType::Nested m_xpr;
+    XprTypeNested m_xpr;
+    const internal::variable_if_dynamic<StorageIndex, (XprType::RowsAtCompileTime == 1 && BlockRows==1) ? 0 : Dynamic> m_startRow;
+    const internal::variable_if_dynamic<StorageIndex, (XprType::ColsAtCompileTime == 1 && BlockCols==1) ? 0 : Dynamic> m_startCol;
     Index m_outerStride;
 };
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_BLOCK_H

Index: 3rd_party/eigen/Eigen/src/Core/BooleanRedux.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/BooleanRedux.h
+++ 3rd_party/eigen/Eigen/src/Core/BooleanRedux.h
@@ -15,13 +15,14 @@
 namespace internal {
 
 template<typename Derived, int UnrollCount>
 struct all_unroller
 {
+  typedef typename Derived::ExpressionTraits Traits;
   enum {
-    col = (UnrollCount-1) / Derived::RowsAtCompileTime,
-    row = (UnrollCount-1) % Derived::RowsAtCompileTime
+    col = (UnrollCount-1) / Traits::RowsAtCompileTime,
+    row = (UnrollCount-1) % Traits::RowsAtCompileTime
   };
 
   static inline bool run(const Derived &mat)
   {
     return all_unroller<Derived, UnrollCount-1>::run(mat) && mat.coeff(row, col);
@@ -41,15 +42,16 @@
 };
 
 template<typename Derived, int UnrollCount>
 struct any_unroller
 {
+  typedef typename Derived::ExpressionTraits Traits;
   enum {
-    col = (UnrollCount-1) / Derived::RowsAtCompileTime,
-    row = (UnrollCount-1) % Derived::RowsAtCompileTime
+    col = (UnrollCount-1) / Traits::RowsAtCompileTime,
+    row = (UnrollCount-1) % Traits::RowsAtCompileTime
   };
-
+  
   static inline bool run(const Derived &mat)
   {
     return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
   }
 };
@@ -76,23 +78,23 @@
   * \sa any(), Cwise::operator<()
   */
 template<typename Derived>
 inline bool DenseBase<Derived>::all() const
 {
+  typedef internal::evaluator<Derived> Evaluator;
   enum {
     unroll = SizeAtCompileTime != Dynamic
-          && CoeffReadCost != Dynamic
-          && NumTraits<Scalar>::AddCost != Dynamic
-          && SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
+          && SizeAtCompileTime * (Evaluator::CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
   };
+  Evaluator evaluator(derived());
   if(unroll)
-    return internal::all_unroller<Derived, unroll ? int(SizeAtCompileTime) : Dynamic>::run(derived());
+    return internal::all_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(evaluator);
   else
   {
     for(Index j = 0; j < cols(); ++j)
       for(Index i = 0; i < rows(); ++i)
-        if (!coeff(i, j)) return false;
+        if (!evaluator.coeff(i, j)) return false;
     return true;
   }
 }
 
 /** \returns true if at least one coefficient is true
@@ -100,33 +102,33 @@
   * \sa all()
   */
 template<typename Derived>
 inline bool DenseBase<Derived>::any() const
 {
+  typedef internal::evaluator<Derived> Evaluator;
   enum {
     unroll = SizeAtCompileTime != Dynamic
-          && CoeffReadCost != Dynamic
-          && NumTraits<Scalar>::AddCost != Dynamic
-          && SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
+          && SizeAtCompileTime * (Evaluator::CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
   };
+  Evaluator evaluator(derived());
   if(unroll)
-    return internal::any_unroller<Derived, unroll ? int(SizeAtCompileTime) : Dynamic>::run(derived());
+    return internal::any_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(evaluator);
   else
   {
     for(Index j = 0; j < cols(); ++j)
       for(Index i = 0; i < rows(); ++i)
-        if (coeff(i, j)) return true;
+        if (evaluator.coeff(i, j)) return true;
     return false;
   }
 }
 
 /** \returns the number of coefficients which evaluate to true
   *
   * \sa all(), any()
   */
 template<typename Derived>
-inline typename DenseBase<Derived>::Index DenseBase<Derived>::count() const
+inline Eigen::Index DenseBase<Derived>::count() const
 {
   return derived().template cast<bool>().template cast<Index>().sum();
 }
 
 /** \returns true is \c *this contains at least one Not A Number (NaN).
@@ -134,21 +136,29 @@
   * \sa allFinite()
   */
 template<typename Derived>
 inline bool DenseBase<Derived>::hasNaN() const
 {
+#if EIGEN_COMP_MSVC || (defined __FAST_MATH__)
+  return derived().array().isNaN().any();
+#else
   return !((derived().array()==derived().array()).all());
+#endif
 }
 
 /** \returns true if \c *this contains only finite numbers, i.e., no NaN and no +/-INF values.
   *
   * \sa hasNaN()
   */
 template<typename Derived>
 inline bool DenseBase<Derived>::allFinite() const
 {
+#if EIGEN_COMP_MSVC || (defined __FAST_MATH__)
+  return derived().array().isFinite().all();
+#else
   return !((derived()-derived()).hasNaN());
+#endif
 }
     
 } // end namespace Eigen
 
 #endif // EIGEN_ALLANDANY_H

DELETED 3rd_party/eigen/Eigen/src/Core/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Core/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Core/CMakeLists.txt
@@ -1,10 +0,0 @@
-FILE(GLOB Eigen_Core_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Core_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core COMPONENT Devel
-  )
-
-ADD_SUBDIRECTORY(products)
-ADD_SUBDIRECTORY(util)
-ADD_SUBDIRECTORY(arch)

Index: 3rd_party/eigen/Eigen/src/Core/CommaInitializer.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CommaInitializer.h
+++ 3rd_party/eigen/Eigen/src/Core/CommaInitializer.h
@@ -20,43 +20,46 @@
   *
   * This class is internally used to implement the comma initializer feature. It is
   * the return type of MatrixBase::operator<<, and most of the time this is the only
   * way it is used.
   *
-  * \sa \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
+  * \sa \blank \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
   */
 template<typename XprType>
 struct CommaInitializer
 {
   typedef typename XprType::Scalar Scalar;
-  typedef typename XprType::Index Index;
 
+  EIGEN_DEVICE_FUNC
   inline CommaInitializer(XprType& xpr, const Scalar& s)
     : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1)
   {
     m_xpr.coeffRef(0,0) = s;
   }
 
   template<typename OtherDerived>
+  EIGEN_DEVICE_FUNC
   inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
     : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows())
   {
     m_xpr.block(0, 0, other.rows(), other.cols()) = other;
   }
 
   /* Copy/Move constructor which transfers ownership. This is crucial in 
    * absence of return value optimization to avoid assertions during destruction. */
   // FIXME in C++11 mode this could be replaced by a proper RValue constructor
+  EIGEN_DEVICE_FUNC
   inline CommaInitializer(const CommaInitializer& o)
   : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
     // Mark original object as finished. In absence of R-value references we need to const_cast:
     const_cast<CommaInitializer&>(o).m_row = m_xpr.rows();
     const_cast<CommaInitializer&>(o).m_col = m_xpr.cols();
     const_cast<CommaInitializer&>(o).m_currentBlockRows = 0;
   }
 
   /* inserts a scalar value in the target matrix */
+  EIGEN_DEVICE_FUNC
   CommaInitializer& operator,(const Scalar& s)
   {
     if (m_col==m_xpr.cols())
     {
       m_row+=m_currentBlockRows;
@@ -72,52 +75,55 @@
     return *this;
   }
 
   /* inserts a matrix expression in the target matrix */
   template<typename OtherDerived>
+  EIGEN_DEVICE_FUNC
   CommaInitializer& operator,(const DenseBase<OtherDerived>& other)
   {
-    if(other.cols()==0 || other.rows()==0)
-      return *this;
-    if (m_col==m_xpr.cols())
+    if (m_col==m_xpr.cols() && (other.cols()!=0 || other.rows()!=m_currentBlockRows))
     {
       m_row+=m_currentBlockRows;
       m_col = 0;
       m_currentBlockRows = other.rows();
       eigen_assert(m_row+m_currentBlockRows<=m_xpr.rows()
         && "Too many rows passed to comma initializer (operator<<)");
     }
-    eigen_assert(m_col<m_xpr.cols()
+    eigen_assert((m_col + other.cols() <= m_xpr.cols())
       && "Too many coefficients passed to comma initializer (operator<<)");
     eigen_assert(m_currentBlockRows==other.rows());
-    if (OtherDerived::SizeAtCompileTime != Dynamic)
-      m_xpr.template block<OtherDerived::RowsAtCompileTime != Dynamic ? OtherDerived::RowsAtCompileTime : 1,
-                              OtherDerived::ColsAtCompileTime != Dynamic ? OtherDerived::ColsAtCompileTime : 1>
-                    (m_row, m_col) = other;
-    else
-      m_xpr.block(m_row, m_col, other.rows(), other.cols()) = other;
+    m_xpr.template block<OtherDerived::RowsAtCompileTime, OtherDerived::ColsAtCompileTime>
+                    (m_row, m_col, other.rows(), other.cols()) = other;
     m_col += other.cols();
     return *this;
   }
 
+  EIGEN_DEVICE_FUNC
   inline ~CommaInitializer()
+#if defined VERIFY_RAISES_ASSERT && (!defined EIGEN_NO_ASSERTION_CHECKING) && defined EIGEN_EXCEPTIONS
+  EIGEN_EXCEPTION_SPEC(Eigen::eigen_assert_exception)
+#endif
   {
-    eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows()
-         && m_col == m_xpr.cols()
-         && "Too few coefficients passed to comma initializer (operator<<)");
+      finished();
   }
 
   /** \returns the built matrix once all its coefficients have been set.
     * Calling finished is 100% optional. Its purpose is to write expressions
     * like this:
     * \code
     * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
     * \endcode
     */
-  inline XprType& finished() { return m_xpr; }
+  EIGEN_DEVICE_FUNC
+  inline XprType& finished() {
+      eigen_assert(((m_row+m_currentBlockRows) == m_xpr.rows() || m_xpr.cols() == 0)
+           && m_col == m_xpr.cols()
+           && "Too few coefficients passed to comma initializer (operator<<)");
+      return m_xpr;
+  }
 
-  XprType& m_xpr;   // target expression
+  XprType& m_xpr;           // target expression
   Index m_row;              // current row id
   Index m_col;              // current col id
   Index m_currentBlockRows; // current block height
 };
 

ADDED   3rd_party/eigen/Eigen/src/Core/ConditionEstimator.h
Index: 3rd_party/eigen/Eigen/src/Core/ConditionEstimator.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/ConditionEstimator.h
+++ 3rd_party/eigen/Eigen/src/Core/ConditionEstimator.h
@@ -0,0 +1,175 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Rasmus Munk Larsen (rmlarsen@google.com)
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CONDITIONESTIMATOR_H
+#define EIGEN_CONDITIONESTIMATOR_H
+
+namespace Eigen {
+
+namespace internal {
+
+template <typename Vector, typename RealVector, bool IsComplex>
+struct rcond_compute_sign {
+  static inline Vector run(const Vector& v) {
+    const RealVector v_abs = v.cwiseAbs();
+    return (v_abs.array() == static_cast<typename Vector::RealScalar>(0))
+            .select(Vector::Ones(v.size()), v.cwiseQuotient(v_abs));
+  }
+};
+
+// Partial specialization to avoid elementwise division for real vectors.
+template <typename Vector>
+struct rcond_compute_sign<Vector, Vector, false> {
+  static inline Vector run(const Vector& v) {
+    return (v.array() < static_cast<typename Vector::RealScalar>(0))
+           .select(-Vector::Ones(v.size()), Vector::Ones(v.size()));
+  }
+};
+
+/**
+  * \returns an estimate of ||inv(matrix)||_1 given a decomposition of
+  * \a matrix that implements .solve() and .adjoint().solve() methods.
+  *
+  * This function implements Algorithms 4.1 and 5.1 from
+  *   http://www.maths.manchester.ac.uk/~higham/narep/narep135.pdf
+  * which also forms the basis for the condition number estimators in
+  * LAPACK. Since at most 10 calls to the solve method of dec are
+  * performed, the total cost is O(dims^2), as opposed to O(dims^3)
+  * needed to compute the inverse matrix explicitly.
+  *
+  * The most common usage is in estimating the condition number
+  * ||matrix||_1 * ||inv(matrix)||_1. The first term ||matrix||_1 can be
+  * computed directly in O(n^2) operations.
+  *
+  * Supports the following decompositions: FullPivLU, PartialPivLU, LDLT, and
+  * LLT.
+  *
+  * \sa FullPivLU, PartialPivLU, LDLT, LLT.
+  */
+template <typename Decomposition>
+typename Decomposition::RealScalar rcond_invmatrix_L1_norm_estimate(const Decomposition& dec)
+{
+  typedef typename Decomposition::MatrixType MatrixType;
+  typedef typename Decomposition::Scalar Scalar;
+  typedef typename Decomposition::RealScalar RealScalar;
+  typedef typename internal::plain_col_type<MatrixType>::type Vector;
+  typedef typename internal::plain_col_type<MatrixType, RealScalar>::type RealVector;
+  const bool is_complex = (NumTraits<Scalar>::IsComplex != 0);
+
+  eigen_assert(dec.rows() == dec.cols());
+  const Index n = dec.rows();
+  if (n == 0)
+    return 0;
+
+  // Disable Index to float conversion warning
+#ifdef __INTEL_COMPILER
+  #pragma warning push
+  #pragma warning ( disable : 2259 )
+#endif
+  Vector v = dec.solve(Vector::Ones(n) / Scalar(n));
+#ifdef __INTEL_COMPILER
+  #pragma warning pop
+#endif
+
+  // lower_bound is a lower bound on
+  //   ||inv(matrix)||_1  = sup_v ||inv(matrix) v||_1 / ||v||_1
+  // and is the objective maximized by the ("super-") gradient ascent
+  // algorithm below.
+  RealScalar lower_bound = v.template lpNorm<1>();
+  if (n == 1)
+    return lower_bound;
+
+  // Gradient ascent algorithm follows: We know that the optimum is achieved at
+  // one of the simplices v = e_i, so in each iteration we follow a
+  // super-gradient to move towards the optimal one.
+  RealScalar old_lower_bound = lower_bound;
+  Vector sign_vector(n);
+  Vector old_sign_vector;
+  Index v_max_abs_index = -1;
+  Index old_v_max_abs_index = v_max_abs_index;
+  for (int k = 0; k < 4; ++k)
+  {
+    sign_vector = internal::rcond_compute_sign<Vector, RealVector, is_complex>::run(v);
+    if (k > 0 && !is_complex && sign_vector == old_sign_vector) {
+      // Break if the solution stagnated.
+      break;
+    }
+    // v_max_abs_index = argmax |real( inv(matrix)^T * sign_vector )|
+    v = dec.adjoint().solve(sign_vector);
+    v.real().cwiseAbs().maxCoeff(&v_max_abs_index);
+    if (v_max_abs_index == old_v_max_abs_index) {
+      // Break if the solution stagnated.
+      break;
+    }
+    // Move to the new simplex e_j, where j = v_max_abs_index.
+    v = dec.solve(Vector::Unit(n, v_max_abs_index));  // v = inv(matrix) * e_j.
+    lower_bound = v.template lpNorm<1>();
+    if (lower_bound <= old_lower_bound) {
+      // Break if the gradient step did not increase the lower_bound.
+      break;
+    }
+    if (!is_complex) {
+      old_sign_vector = sign_vector;
+    }
+    old_v_max_abs_index = v_max_abs_index;
+    old_lower_bound = lower_bound;
+  }
+  // The following calculates an independent estimate of ||matrix||_1 by
+  // multiplying matrix by a vector with entries of slowly increasing
+  // magnitude and alternating sign:
+  //   v_i = (-1)^{i} (1 + (i / (dim-1))), i = 0,...,dim-1.
+  // This improvement to Hager's algorithm above is due to Higham. It was
+  // added to make the algorithm more robust in certain corner cases where
+  // large elements in the matrix might otherwise escape detection due to
+  // exact cancellation (especially when op and op_adjoint correspond to a
+  // sequence of backsubstitutions and permutations), which could cause
+  // Hager's algorithm to vastly underestimate ||matrix||_1.
+  Scalar alternating_sign(RealScalar(1));
+  for (Index i = 0; i < n; ++i) {
+    // The static_cast is needed when Scalar is a complex and RealScalar implements expression templates
+    v[i] = alternating_sign * static_cast<RealScalar>(RealScalar(1) + (RealScalar(i) / (RealScalar(n - 1))));
+    alternating_sign = -alternating_sign;
+  }
+  v = dec.solve(v);
+  const RealScalar alternate_lower_bound = (2 * v.template lpNorm<1>()) / (3 * RealScalar(n));
+  return numext::maxi(lower_bound, alternate_lower_bound);
+}
+
+/** \brief Reciprocal condition number estimator.
+  *
+  * Computing a decomposition of a dense matrix takes O(n^3) operations, while
+  * this method estimates the condition number quickly and reliably in O(n^2)
+  * operations.
+  *
+  * \returns an estimate of the reciprocal condition number
+  * (1 / (||matrix||_1 * ||inv(matrix)||_1)) of matrix, given ||matrix||_1 and
+  * its decomposition. Supports the following decompositions: FullPivLU,
+  * PartialPivLU, LDLT, and LLT.
+  *
+  * \sa FullPivLU, PartialPivLU, LDLT, LLT.
+  */
+template <typename Decomposition>
+typename Decomposition::RealScalar
+rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm, const Decomposition& dec)
+{
+  typedef typename Decomposition::RealScalar RealScalar;
+  eigen_assert(dec.rows() == dec.cols());
+  if (dec.rows() == 0)              return RealScalar(1);
+  if (matrix_norm == RealScalar(0)) return RealScalar(0);
+  if (dec.rows() == 1)              return RealScalar(1);
+  const RealScalar inverse_matrix_norm = rcond_invmatrix_L1_norm_estimate(dec);
+  return (inverse_matrix_norm == RealScalar(0) ? RealScalar(0)
+                                               : (RealScalar(1) / inverse_matrix_norm) / matrix_norm);
+}
+
+}  // namespace internal
+
+}  // namespace Eigen
+
+#endif

ADDED   3rd_party/eigen/Eigen/src/Core/CoreEvaluators.h
Index: 3rd_party/eigen/Eigen/src/Core/CoreEvaluators.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CoreEvaluators.h
+++ 3rd_party/eigen/Eigen/src/Core/CoreEvaluators.h
@@ -0,0 +1,1671 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+
+#ifndef EIGEN_COREEVALUATORS_H
+#define EIGEN_COREEVALUATORS_H
+
+namespace Eigen {
+  
+namespace internal {
+
+// This class returns the evaluator kind from the expression storage kind.
+// Default assumes index based accessors
+template<typename StorageKind>
+struct storage_kind_to_evaluator_kind {
+  typedef IndexBased Kind;
+};
+
+// This class returns the evaluator shape from the expression storage kind.
+// It can be Dense, Sparse, Triangular, Diagonal, SelfAdjoint, Band, etc.
+template<typename StorageKind> struct storage_kind_to_shape;
+
+template<> struct storage_kind_to_shape<Dense>                  { typedef DenseShape Shape;           };
+template<> struct storage_kind_to_shape<SolverStorage>          { typedef SolverShape Shape;           };
+template<> struct storage_kind_to_shape<PermutationStorage>     { typedef PermutationShape Shape;     };
+template<> struct storage_kind_to_shape<TranspositionsStorage>  { typedef TranspositionsShape Shape;  };
+
+// Evaluators have to be specialized with respect to various criteria such as:
+//  - storage/structure/shape
+//  - scalar type
+//  - etc.
+// Therefore, we need specialization of evaluator providing additional template arguments for each kind of evaluators.
+// We currently distinguish the following kind of evaluators:
+// - unary_evaluator    for expressions taking only one arguments (CwiseUnaryOp, CwiseUnaryView, Transpose, MatrixWrapper, ArrayWrapper, Reverse, Replicate)
+// - binary_evaluator   for expression taking two arguments (CwiseBinaryOp)
+// - ternary_evaluator   for expression taking three arguments (CwiseTernaryOp)
+// - product_evaluator  for linear algebra products (Product); special case of binary_evaluator because it requires additional tags for dispatching.
+// - mapbase_evaluator  for Map, Block, Ref
+// - block_evaluator    for Block (special dispatching to a mapbase_evaluator or unary_evaluator)
+
+template< typename T,
+          typename Arg1Kind   = typename evaluator_traits<typename T::Arg1>::Kind,
+          typename Arg2Kind   = typename evaluator_traits<typename T::Arg2>::Kind,
+          typename Arg3Kind   = typename evaluator_traits<typename T::Arg3>::Kind,
+          typename Arg1Scalar = typename traits<typename T::Arg1>::Scalar,
+          typename Arg2Scalar = typename traits<typename T::Arg2>::Scalar,
+          typename Arg3Scalar = typename traits<typename T::Arg3>::Scalar> struct ternary_evaluator;
+
+template< typename T,
+          typename LhsKind   = typename evaluator_traits<typename T::Lhs>::Kind,
+          typename RhsKind   = typename evaluator_traits<typename T::Rhs>::Kind,
+          typename LhsScalar = typename traits<typename T::Lhs>::Scalar,
+          typename RhsScalar = typename traits<typename T::Rhs>::Scalar> struct binary_evaluator;
+
+template< typename T,
+          typename Kind   = typename evaluator_traits<typename T::NestedExpression>::Kind,
+          typename Scalar = typename T::Scalar> struct unary_evaluator;
+          
+// evaluator_traits<T> contains traits for evaluator<T> 
+
+template<typename T>
+struct evaluator_traits_base
+{
+  // by default, get evaluator kind and shape from storage
+  typedef typename storage_kind_to_evaluator_kind<typename traits<T>::StorageKind>::Kind Kind;
+  typedef typename storage_kind_to_shape<typename traits<T>::StorageKind>::Shape Shape;
+};
+
+// Default evaluator traits
+template<typename T>
+struct evaluator_traits : public evaluator_traits_base<T>
+{
+};
+
+template<typename T, typename Shape = typename evaluator_traits<T>::Shape >
+struct evaluator_assume_aliasing {
+  static const bool value = false;
+};
+
+// By default, we assume a unary expression:
+template<typename T>
+struct evaluator : public unary_evaluator<T>
+{
+  typedef unary_evaluator<T> Base;
+  EIGEN_DEVICE_FUNC explicit evaluator(const T& xpr) : Base(xpr) {}
+};
+
+
+// TODO: Think about const-correctness
+template<typename T>
+struct evaluator<const T>
+  : evaluator<T>
+{
+  EIGEN_DEVICE_FUNC
+  explicit evaluator(const T& xpr) : evaluator<T>(xpr) {}
+};
+
+// ---------- base class for all evaluators ----------
+
+template<typename ExpressionType>
+struct evaluator_base : public noncopyable
+{
+  // TODO that's not very nice to have to propagate all these traits. They are currently only needed to handle outer,inner indices.
+  typedef traits<ExpressionType> ExpressionTraits;
+  
+  enum {
+    Alignment = 0
+  };
+};
+
+// -------------------- Matrix and Array --------------------
+//
+// evaluator<PlainObjectBase> is a common base class for the
+// Matrix and Array evaluators.
+// Here we directly specialize evaluator. This is not really a unary expression, and it is, by definition, dense,
+// so no need for more sophisticated dispatching.
+
+template<typename Derived>
+struct evaluator<PlainObjectBase<Derived> >
+  : evaluator_base<Derived>
+{
+  typedef PlainObjectBase<Derived> PlainObjectType;
+  typedef typename PlainObjectType::Scalar Scalar;
+  typedef typename PlainObjectType::CoeffReturnType CoeffReturnType;
+
+  enum {
+    IsRowMajor = PlainObjectType::IsRowMajor,
+    IsVectorAtCompileTime = PlainObjectType::IsVectorAtCompileTime,
+    RowsAtCompileTime = PlainObjectType::RowsAtCompileTime,
+    ColsAtCompileTime = PlainObjectType::ColsAtCompileTime,
+    
+    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    Flags = traits<Derived>::EvaluatorFlags,
+    Alignment = traits<Derived>::Alignment
+  };
+  
+  EIGEN_DEVICE_FUNC evaluator()
+    : m_data(0),
+      m_outerStride(IsVectorAtCompileTime  ? 0 
+                                           : int(IsRowMajor) ? ColsAtCompileTime 
+                                           : RowsAtCompileTime)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const PlainObjectType& m)
+    : m_data(m.data()), m_outerStride(IsVectorAtCompileTime ? 0 : m.outerStride()) 
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    if (IsRowMajor)
+      return m_data[row * m_outerStride.value() + col];
+    else
+      return m_data[row + col * m_outerStride.value()];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_data[index];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index row, Index col)
+  {
+    if (IsRowMajor)
+      return const_cast<Scalar*>(m_data)[row * m_outerStride.value() + col];
+    else
+      return const_cast<Scalar*>(m_data)[row + col * m_outerStride.value()];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index index)
+  {
+    return const_cast<Scalar*>(m_data)[index];
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    if (IsRowMajor)
+      return ploadt<PacketType, LoadMode>(m_data + row * m_outerStride.value() + col);
+    else
+      return ploadt<PacketType, LoadMode>(m_data + row + col * m_outerStride.value());
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    return ploadt<PacketType, LoadMode>(m_data + index);
+  }
+
+  template<int StoreMode,typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index row, Index col, const PacketType& x)
+  {
+    if (IsRowMajor)
+      return pstoret<Scalar, PacketType, StoreMode>
+	            (const_cast<Scalar*>(m_data) + row * m_outerStride.value() + col, x);
+    else
+      return pstoret<Scalar, PacketType, StoreMode>
+                    (const_cast<Scalar*>(m_data) + row + col * m_outerStride.value(), x);
+  }
+
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketType& x)
+  {
+    return pstoret<Scalar, PacketType, StoreMode>(const_cast<Scalar*>(m_data) + index, x);
+  }
+
+protected:
+  const Scalar *m_data;
+
+  // We do not need to know the outer stride for vectors
+  variable_if_dynamic<Index, IsVectorAtCompileTime  ? 0 
+                                                    : int(IsRowMajor) ? ColsAtCompileTime 
+                                                    : RowsAtCompileTime> m_outerStride;
+};
+
+template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
+struct evaluator<Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
+  : evaluator<PlainObjectBase<Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols> > >
+{
+  typedef Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols> XprType;
+  
+  EIGEN_DEVICE_FUNC evaluator() {}
+
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& m)
+    : evaluator<PlainObjectBase<XprType> >(m) 
+  { }
+};
+
+template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
+struct evaluator<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
+  : evaluator<PlainObjectBase<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> > >
+{
+  typedef Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> XprType;
+
+  EIGEN_DEVICE_FUNC evaluator() {}
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& m)
+    : evaluator<PlainObjectBase<XprType> >(m) 
+  { }
+};
+
+// -------------------- Transpose --------------------
+
+template<typename ArgType>
+struct unary_evaluator<Transpose<ArgType>, IndexBased>
+  : evaluator_base<Transpose<ArgType> >
+{
+  typedef Transpose<ArgType> XprType;
+  
+  enum {
+    CoeffReadCost = evaluator<ArgType>::CoeffReadCost,    
+    Flags = evaluator<ArgType>::Flags ^ RowMajorBit,
+    Alignment = evaluator<ArgType>::Alignment
+  };
+
+  EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& t) : m_argImpl(t.nestedExpression()) {}
+
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    return m_argImpl.coeff(col, row);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_argImpl.coeff(index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index row, Index col)
+  {
+    return m_argImpl.coeffRef(col, row);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  typename XprType::Scalar& coeffRef(Index index)
+  {
+    return m_argImpl.coeffRef(index);
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    return m_argImpl.template packet<LoadMode,PacketType>(col, row);
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    return m_argImpl.template packet<LoadMode,PacketType>(index);
+  }
+
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index row, Index col, const PacketType& x)
+  {
+    m_argImpl.template writePacket<StoreMode,PacketType>(col, row, x);
+  }
+
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketType& x)
+  {
+    m_argImpl.template writePacket<StoreMode,PacketType>(index, x);
+  }
+
+protected:
+  evaluator<ArgType> m_argImpl;
+};
+
+// -------------------- CwiseNullaryOp --------------------
+// Like Matrix and Array, this is not really a unary expression, so we directly specialize evaluator.
+// Likewise, there is not need to more sophisticated dispatching here.
+
+template<typename Scalar,typename NullaryOp,
+         bool has_nullary = has_nullary_operator<NullaryOp>::value,
+         bool has_unary   = has_unary_operator<NullaryOp>::value,
+         bool has_binary  = has_binary_operator<NullaryOp>::value>
+struct nullary_wrapper
+{
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const { return op(i,j); }
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const { return op(i); }
+
+  template <typename T, typename IndexType> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const { return op.template packetOp<T>(i,j); }
+  template <typename T, typename IndexType> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const { return op.template packetOp<T>(i); }
+};
+
+template<typename Scalar,typename NullaryOp>
+struct nullary_wrapper<Scalar,NullaryOp,true,false,false>
+{
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType=0, IndexType=0) const { return op(); }
+  template <typename T, typename IndexType> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType=0, IndexType=0) const { return op.template packetOp<T>(); }
+};
+
+template<typename Scalar,typename NullaryOp>
+struct nullary_wrapper<Scalar,NullaryOp,false,false,true>
+{
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j=0) const { return op(i,j); }
+  template <typename T, typename IndexType> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j=0) const { return op.template packetOp<T>(i,j); }
+};
+
+// We need the following specialization for vector-only functors assigned to a runtime vector,
+// for instance, using linspace and assigning a RowVectorXd to a MatrixXd or even a row of a MatrixXd.
+// In this case, i==0 and j is used for the actual iteration.
+template<typename Scalar,typename NullaryOp>
+struct nullary_wrapper<Scalar,NullaryOp,false,true,false>
+{
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const {
+    eigen_assert(i==0 || j==0);
+    return op(i+j);
+  }
+  template <typename T, typename IndexType> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const {
+    eigen_assert(i==0 || j==0);
+    return op.template packetOp<T>(i+j);
+  }
+
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const { return op(i); }
+  template <typename T, typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const { return op.template packetOp<T>(i); }
+};
+
+template<typename Scalar,typename NullaryOp>
+struct nullary_wrapper<Scalar,NullaryOp,false,false,false> {};
+
+#if 0 && EIGEN_COMP_MSVC>0
+// Disable this ugly workaround. This is now handled in traits<Ref>::match,
+// but this piece of code might still become handly if some other weird compilation
+// erros pop up again.
+
+// MSVC exhibits a weird compilation error when
+// compiling:
+//    Eigen::MatrixXf A = MatrixXf::Random(3,3);
+//    Ref<const MatrixXf> R = 2.f*A;
+// and that has_*ary_operator<scalar_constant_op<float>> have not been instantiated yet.
+// The "problem" is that evaluator<2.f*A> is instantiated by traits<Ref>::match<2.f*A>
+// and at that time has_*ary_operator<T> returns true regardless of T.
+// Then nullary_wrapper is badly instantiated as nullary_wrapper<.,.,true,true,true>.
+// The trick is thus to defer the proper instantiation of nullary_wrapper when coeff(),
+// and packet() are really instantiated as implemented below:
+
+// This is a simple wrapper around Index to enforce the re-instantiation of
+// has_*ary_operator when needed.
+template<typename T> struct nullary_wrapper_workaround_msvc {
+  nullary_wrapper_workaround_msvc(const T&);
+  operator T()const;
+};
+
+template<typename Scalar,typename NullaryOp>
+struct nullary_wrapper<Scalar,NullaryOp,true,true,true>
+{
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const {
+    return nullary_wrapper<Scalar,NullaryOp,
+    has_nullary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
+    has_unary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
+    has_binary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value>().operator()(op,i,j);
+  }
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const {
+    return nullary_wrapper<Scalar,NullaryOp,
+    has_nullary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
+    has_unary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
+    has_binary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value>().operator()(op,i);
+  }
+
+  template <typename T, typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const {
+    return nullary_wrapper<Scalar,NullaryOp,
+    has_nullary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
+    has_unary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
+    has_binary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value>().template packetOp<T>(op,i,j);
+  }
+  template <typename T, typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const {
+    return nullary_wrapper<Scalar,NullaryOp,
+    has_nullary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
+    has_unary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
+    has_binary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value>().template packetOp<T>(op,i);
+  }
+};
+#endif // MSVC workaround
+
+template<typename NullaryOp, typename PlainObjectType>
+struct evaluator<CwiseNullaryOp<NullaryOp,PlainObjectType> >
+  : evaluator_base<CwiseNullaryOp<NullaryOp,PlainObjectType> >
+{
+  typedef CwiseNullaryOp<NullaryOp,PlainObjectType> XprType;
+  typedef typename internal::remove_all<PlainObjectType>::type PlainObjectTypeCleaned;
+  
+  enum {
+    CoeffReadCost = internal::functor_traits<NullaryOp>::Cost,
+    
+    Flags = (evaluator<PlainObjectTypeCleaned>::Flags
+          &  (  HereditaryBits
+              | (functor_has_linear_access<NullaryOp>::ret  ? LinearAccessBit : 0)
+              | (functor_traits<NullaryOp>::PacketAccess    ? PacketAccessBit : 0)))
+          | (functor_traits<NullaryOp>::IsRepeatable ? 0 : EvalBeforeNestingBit),
+    Alignment = AlignedMax
+  };
+
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& n)
+    : m_functor(n.functor()), m_wrapper()
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(IndexType row, IndexType col) const
+  {
+    return m_wrapper(m_functor, row, col);
+  }
+
+  template <typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(IndexType index) const
+  {
+    return m_wrapper(m_functor,index);
+  }
+
+  template<int LoadMode, typename PacketType, typename IndexType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(IndexType row, IndexType col) const
+  {
+    return m_wrapper.template packetOp<PacketType>(m_functor, row, col);
+  }
+
+  template<int LoadMode, typename PacketType, typename IndexType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(IndexType index) const
+  {
+    return m_wrapper.template packetOp<PacketType>(m_functor, index);
+  }
+
+protected:
+  const NullaryOp m_functor;
+  const internal::nullary_wrapper<CoeffReturnType,NullaryOp> m_wrapper;
+};
+
+// -------------------- CwiseUnaryOp --------------------
+
+template<typename UnaryOp, typename ArgType>
+struct unary_evaluator<CwiseUnaryOp<UnaryOp, ArgType>, IndexBased >
+  : evaluator_base<CwiseUnaryOp<UnaryOp, ArgType> >
+{
+  typedef CwiseUnaryOp<UnaryOp, ArgType> XprType;
+  
+  enum {
+    CoeffReadCost = evaluator<ArgType>::CoeffReadCost + functor_traits<UnaryOp>::Cost,
+    
+    Flags = evaluator<ArgType>::Flags
+          & (HereditaryBits | LinearAccessBit | (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
+    Alignment = evaluator<ArgType>::Alignment
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  explicit unary_evaluator(const XprType& op)
+    : m_functor(op.functor()), 
+      m_argImpl(op.nestedExpression()) 
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<UnaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    return m_functor(m_argImpl.coeff(row, col));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_functor(m_argImpl.coeff(index));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    return m_functor.packetOp(m_argImpl.template packet<LoadMode, PacketType>(row, col));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    return m_functor.packetOp(m_argImpl.template packet<LoadMode, PacketType>(index));
+  }
+
+protected:
+  const UnaryOp m_functor;
+  evaluator<ArgType> m_argImpl;
+};
+
+// -------------------- CwiseTernaryOp --------------------
+
+// this is a ternary expression
+template<typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
+struct evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> >
+  : public ternary_evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> >
+{
+  typedef CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> XprType;
+  typedef ternary_evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> > Base;
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {}
+};
+
+template<typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
+struct ternary_evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>, IndexBased, IndexBased>
+  : evaluator_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> >
+{
+  typedef CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> XprType;
+  
+  enum {
+    CoeffReadCost = evaluator<Arg1>::CoeffReadCost + evaluator<Arg2>::CoeffReadCost + evaluator<Arg3>::CoeffReadCost + functor_traits<TernaryOp>::Cost,
+    
+    Arg1Flags = evaluator<Arg1>::Flags,
+    Arg2Flags = evaluator<Arg2>::Flags,
+    Arg3Flags = evaluator<Arg3>::Flags,
+    SameType = is_same<typename Arg1::Scalar,typename Arg2::Scalar>::value && is_same<typename Arg1::Scalar,typename Arg3::Scalar>::value,
+    StorageOrdersAgree = (int(Arg1Flags)&RowMajorBit)==(int(Arg2Flags)&RowMajorBit) && (int(Arg1Flags)&RowMajorBit)==(int(Arg3Flags)&RowMajorBit),
+    Flags0 = (int(Arg1Flags) | int(Arg2Flags) | int(Arg3Flags)) & (
+        HereditaryBits
+        | (int(Arg1Flags) & int(Arg2Flags) & int(Arg3Flags) &
+           ( (StorageOrdersAgree ? LinearAccessBit : 0)
+           | (functor_traits<TernaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)
+           )
+        )
+     ),
+    Flags = (Flags0 & ~RowMajorBit) | (Arg1Flags & RowMajorBit),
+    Alignment = EIGEN_PLAIN_ENUM_MIN(
+        EIGEN_PLAIN_ENUM_MIN(evaluator<Arg1>::Alignment, evaluator<Arg2>::Alignment),
+        evaluator<Arg3>::Alignment)
+  };
+
+  EIGEN_DEVICE_FUNC explicit ternary_evaluator(const XprType& xpr)
+    : m_functor(xpr.functor()),
+      m_arg1Impl(xpr.arg1()), 
+      m_arg2Impl(xpr.arg2()), 
+      m_arg3Impl(xpr.arg3())  
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<TernaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    return m_functor(m_arg1Impl.coeff(row, col), m_arg2Impl.coeff(row, col), m_arg3Impl.coeff(row, col));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_functor(m_arg1Impl.coeff(index), m_arg2Impl.coeff(index), m_arg3Impl.coeff(index));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    return m_functor.packetOp(m_arg1Impl.template packet<LoadMode,PacketType>(row, col),
+                              m_arg2Impl.template packet<LoadMode,PacketType>(row, col),
+                              m_arg3Impl.template packet<LoadMode,PacketType>(row, col));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    return m_functor.packetOp(m_arg1Impl.template packet<LoadMode,PacketType>(index),
+                              m_arg2Impl.template packet<LoadMode,PacketType>(index),
+                              m_arg3Impl.template packet<LoadMode,PacketType>(index));
+  }
+
+protected:
+  const TernaryOp m_functor;
+  evaluator<Arg1> m_arg1Impl;
+  evaluator<Arg2> m_arg2Impl;
+  evaluator<Arg3> m_arg3Impl;
+};
+
+// -------------------- CwiseBinaryOp --------------------
+
+// this is a binary expression
+template<typename BinaryOp, typename Lhs, typename Rhs>
+struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+  : public binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> XprType;
+  typedef binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> > Base;
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {}
+};
+
+template<typename BinaryOp, typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>, IndexBased, IndexBased>
+  : evaluator_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> XprType;
+  
+  enum {
+    CoeffReadCost = evaluator<Lhs>::CoeffReadCost + evaluator<Rhs>::CoeffReadCost + functor_traits<BinaryOp>::Cost,
+    
+    LhsFlags = evaluator<Lhs>::Flags,
+    RhsFlags = evaluator<Rhs>::Flags,
+    SameType = is_same<typename Lhs::Scalar,typename Rhs::Scalar>::value,
+    StorageOrdersAgree = (int(LhsFlags)&RowMajorBit)==(int(RhsFlags)&RowMajorBit),
+    Flags0 = (int(LhsFlags) | int(RhsFlags)) & (
+        HereditaryBits
+      | (int(LhsFlags) & int(RhsFlags) &
+           ( (StorageOrdersAgree ? LinearAccessBit : 0)
+           | (functor_traits<BinaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)
+           )
+        )
+     ),
+    Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
+    Alignment = EIGEN_PLAIN_ENUM_MIN(evaluator<Lhs>::Alignment,evaluator<Rhs>::Alignment)
+  };
+
+  EIGEN_DEVICE_FUNC explicit binary_evaluator(const XprType& xpr)
+    : m_functor(xpr.functor()),
+      m_lhsImpl(xpr.lhs()), 
+      m_rhsImpl(xpr.rhs())  
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<BinaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    return m_functor(m_lhsImpl.coeff(row, col), m_rhsImpl.coeff(row, col));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_functor(m_lhsImpl.coeff(index), m_rhsImpl.coeff(index));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    return m_functor.packetOp(m_lhsImpl.template packet<LoadMode,PacketType>(row, col),
+                              m_rhsImpl.template packet<LoadMode,PacketType>(row, col));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    return m_functor.packetOp(m_lhsImpl.template packet<LoadMode,PacketType>(index),
+                              m_rhsImpl.template packet<LoadMode,PacketType>(index));
+  }
+
+protected:
+  const BinaryOp m_functor;
+  evaluator<Lhs> m_lhsImpl;
+  evaluator<Rhs> m_rhsImpl;
+};
+
+// -------------------- CwiseUnaryView --------------------
+
+template<typename UnaryOp, typename ArgType>
+struct unary_evaluator<CwiseUnaryView<UnaryOp, ArgType>, IndexBased>
+  : evaluator_base<CwiseUnaryView<UnaryOp, ArgType> >
+{
+  typedef CwiseUnaryView<UnaryOp, ArgType> XprType;
+  
+  enum {
+    CoeffReadCost = evaluator<ArgType>::CoeffReadCost + functor_traits<UnaryOp>::Cost,
+    
+    Flags = (evaluator<ArgType>::Flags & (HereditaryBits | LinearAccessBit | DirectAccessBit)),
+    
+    Alignment = 0 // FIXME it is not very clear why alignment is necessarily lost...
+  };
+
+  EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& op)
+    : m_unaryOp(op.functor()), 
+      m_argImpl(op.nestedExpression()) 
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<UnaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    return m_unaryOp(m_argImpl.coeff(row, col));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_unaryOp(m_argImpl.coeff(index));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index row, Index col)
+  {
+    return m_unaryOp(m_argImpl.coeffRef(row, col));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index index)
+  {
+    return m_unaryOp(m_argImpl.coeffRef(index));
+  }
+
+protected:
+  const UnaryOp m_unaryOp;
+  evaluator<ArgType> m_argImpl;
+};
+
+// -------------------- Map --------------------
+
+// FIXME perhaps the PlainObjectType could be provided by Derived::PlainObject ?
+// but that might complicate template specialization
+template<typename Derived, typename PlainObjectType>
+struct mapbase_evaluator;
+
+template<typename Derived, typename PlainObjectType>
+struct mapbase_evaluator : evaluator_base<Derived>
+{
+  typedef Derived  XprType;
+  typedef typename XprType::PointerType PointerType;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  
+  enum {
+    IsRowMajor = XprType::RowsAtCompileTime,
+    ColsAtCompileTime = XprType::ColsAtCompileTime,
+    CoeffReadCost = NumTraits<Scalar>::ReadCost
+  };
+
+  EIGEN_DEVICE_FUNC explicit mapbase_evaluator(const XprType& map)
+    : m_data(const_cast<PointerType>(map.data())),
+      m_innerStride(map.innerStride()),
+      m_outerStride(map.outerStride())
+  {
+    EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(evaluator<Derived>::Flags&PacketAccessBit, internal::inner_stride_at_compile_time<Derived>::ret==1),
+                        PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    return m_data[col * colStride() + row * rowStride()];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_data[index * m_innerStride.value()];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index row, Index col)
+  {
+    return m_data[col * colStride() + row * rowStride()];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index index)
+  {
+    return m_data[index * m_innerStride.value()];
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    PointerType ptr = m_data + row * rowStride() + col * colStride();
+    return internal::ploadt<PacketType, LoadMode>(ptr);
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    return internal::ploadt<PacketType, LoadMode>(m_data + index * m_innerStride.value());
+  }
+
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index row, Index col, const PacketType& x)
+  {
+    PointerType ptr = m_data + row * rowStride() + col * colStride();
+    return internal::pstoret<Scalar, PacketType, StoreMode>(ptr, x);
+  }
+
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketType& x)
+  {
+    internal::pstoret<Scalar, PacketType, StoreMode>(m_data + index * m_innerStride.value(), x);
+  }
+protected:
+  EIGEN_DEVICE_FUNC
+  inline Index rowStride() const { return XprType::IsRowMajor ? m_outerStride.value() : m_innerStride.value(); }
+  EIGEN_DEVICE_FUNC
+  inline Index colStride() const { return XprType::IsRowMajor ? m_innerStride.value() : m_outerStride.value(); }
+
+  PointerType m_data;
+  const internal::variable_if_dynamic<Index, XprType::InnerStrideAtCompileTime> m_innerStride;
+  const internal::variable_if_dynamic<Index, XprType::OuterStrideAtCompileTime> m_outerStride;
+};
+
+template<typename PlainObjectType, int MapOptions, typename StrideType> 
+struct evaluator<Map<PlainObjectType, MapOptions, StrideType> >
+  : public mapbase_evaluator<Map<PlainObjectType, MapOptions, StrideType>, PlainObjectType>
+{
+  typedef Map<PlainObjectType, MapOptions, StrideType> XprType;
+  typedef typename XprType::Scalar Scalar;
+  // TODO: should check for smaller packet types once we can handle multi-sized packet types
+  typedef typename packet_traits<Scalar>::type PacketScalar;
+  
+  enum {
+    InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
+                             ? int(PlainObjectType::InnerStrideAtCompileTime)
+                             : int(StrideType::InnerStrideAtCompileTime),
+    OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
+                             ? int(PlainObjectType::OuterStrideAtCompileTime)
+                             : int(StrideType::OuterStrideAtCompileTime),
+    HasNoInnerStride = InnerStrideAtCompileTime == 1,
+    HasNoOuterStride = StrideType::OuterStrideAtCompileTime == 0,
+    HasNoStride = HasNoInnerStride && HasNoOuterStride,
+    IsDynamicSize = PlainObjectType::SizeAtCompileTime==Dynamic,
+    
+    PacketAccessMask = bool(HasNoInnerStride) ? ~int(0) : ~int(PacketAccessBit),
+    LinearAccessMask = bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime) ? ~int(0) : ~int(LinearAccessBit),
+    Flags = int( evaluator<PlainObjectType>::Flags) & (LinearAccessMask&PacketAccessMask),
+    
+    Alignment = int(MapOptions)&int(AlignedMask)
+  };
+
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& map)
+    : mapbase_evaluator<XprType, PlainObjectType>(map) 
+  { }
+};
+
+// -------------------- Ref --------------------
+
+template<typename PlainObjectType, int RefOptions, typename StrideType> 
+struct evaluator<Ref<PlainObjectType, RefOptions, StrideType> >
+  : public mapbase_evaluator<Ref<PlainObjectType, RefOptions, StrideType>, PlainObjectType>
+{
+  typedef Ref<PlainObjectType, RefOptions, StrideType> XprType;
+  
+  enum {
+    Flags = evaluator<Map<PlainObjectType, RefOptions, StrideType> >::Flags,
+    Alignment = evaluator<Map<PlainObjectType, RefOptions, StrideType> >::Alignment
+  };
+
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& ref)
+    : mapbase_evaluator<XprType, PlainObjectType>(ref) 
+  { }
+};
+
+// -------------------- Block --------------------
+
+template<typename ArgType, int BlockRows, int BlockCols, bool InnerPanel,
+         bool HasDirectAccess = internal::has_direct_access<ArgType>::ret> struct block_evaluator;
+         
+template<typename ArgType, int BlockRows, int BlockCols, bool InnerPanel> 
+struct evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel> >
+  : block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel>
+{
+  typedef Block<ArgType, BlockRows, BlockCols, InnerPanel> XprType;
+  typedef typename XprType::Scalar Scalar;
+  // TODO: should check for smaller packet types once we can handle multi-sized packet types
+  typedef typename packet_traits<Scalar>::type PacketScalar;
+  
+  enum {
+    CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+    
+    RowsAtCompileTime = traits<XprType>::RowsAtCompileTime,
+    ColsAtCompileTime = traits<XprType>::ColsAtCompileTime,
+    MaxRowsAtCompileTime = traits<XprType>::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = traits<XprType>::MaxColsAtCompileTime,
+    
+    ArgTypeIsRowMajor = (int(evaluator<ArgType>::Flags)&RowMajorBit) != 0,
+    IsRowMajor = (MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1) ? 1
+               : (MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1) ? 0
+               : ArgTypeIsRowMajor,
+    HasSameStorageOrderAsArgType = (IsRowMajor == ArgTypeIsRowMajor),
+    InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
+    InnerStrideAtCompileTime = HasSameStorageOrderAsArgType
+                             ? int(inner_stride_at_compile_time<ArgType>::ret)
+                             : int(outer_stride_at_compile_time<ArgType>::ret),
+    OuterStrideAtCompileTime = HasSameStorageOrderAsArgType
+                             ? int(outer_stride_at_compile_time<ArgType>::ret)
+                             : int(inner_stride_at_compile_time<ArgType>::ret),
+    MaskPacketAccessBit = (InnerStrideAtCompileTime == 1) ? PacketAccessBit : 0,
+    
+    FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || (InnerPanel && (evaluator<ArgType>::Flags&LinearAccessBit))) ? LinearAccessBit : 0,    
+    FlagsRowMajorBit = XprType::Flags&RowMajorBit,
+    Flags0 = evaluator<ArgType>::Flags & ( (HereditaryBits & ~RowMajorBit) |
+                                           DirectAccessBit |
+                                           MaskPacketAccessBit),
+    Flags = Flags0 | FlagsLinearAccessBit | FlagsRowMajorBit,
+    
+    PacketAlignment = unpacket_traits<PacketScalar>::alignment,
+    Alignment0 = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % int(PacketAlignment)) == 0)) ? int(PacketAlignment) : 0,
+    Alignment = EIGEN_PLAIN_ENUM_MIN(evaluator<ArgType>::Alignment, Alignment0)
+  };
+  typedef block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel> block_evaluator_type;
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& block) : block_evaluator_type(block)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+};
+
+// no direct-access => dispatch to a unary evaluator
+template<typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
+struct block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel, /*HasDirectAccess*/ false>
+  : unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel> >
+{
+  typedef Block<ArgType, BlockRows, BlockCols, InnerPanel> XprType;
+
+  EIGEN_DEVICE_FUNC explicit block_evaluator(const XprType& block)
+    : unary_evaluator<XprType>(block) 
+  {}
+};
+
+template<typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
+struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBased>
+  : evaluator_base<Block<ArgType, BlockRows, BlockCols, InnerPanel> >
+{
+  typedef Block<ArgType, BlockRows, BlockCols, InnerPanel> XprType;
+
+  EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& block)
+    : m_argImpl(block.nestedExpression()), 
+      m_startRow(block.startRow()), 
+      m_startCol(block.startCol()) 
+  { }
+ 
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  enum {
+    RowsAtCompileTime = XprType::RowsAtCompileTime
+  };
+ 
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  { 
+    return m_argImpl.coeff(m_startRow.value() + row, m_startCol.value() + col); 
+  }
+  
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  { 
+    return coeff(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index row, Index col)
+  { 
+    return m_argImpl.coeffRef(m_startRow.value() + row, m_startCol.value() + col); 
+  }
+  
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index index)
+  { 
+    return coeffRef(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
+  }
+ 
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const 
+  { 
+    return m_argImpl.template packet<LoadMode,PacketType>(m_startRow.value() + row, m_startCol.value() + col); 
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const 
+  { 
+    return packet<LoadMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index,
+                                       RowsAtCompileTime == 1 ? index : 0);
+  }
+  
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index row, Index col, const PacketType& x) 
+  {
+    return m_argImpl.template writePacket<StoreMode,PacketType>(m_startRow.value() + row, m_startCol.value() + col, x); 
+  }
+  
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketType& x) 
+  {
+    return writePacket<StoreMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index,
+                                             RowsAtCompileTime == 1 ? index : 0,
+                                             x);
+  }
+ 
+protected:
+  evaluator<ArgType> m_argImpl;
+  const variable_if_dynamic<Index, (ArgType::RowsAtCompileTime == 1 && BlockRows==1) ? 0 : Dynamic> m_startRow;
+  const variable_if_dynamic<Index, (ArgType::ColsAtCompileTime == 1 && BlockCols==1) ? 0 : Dynamic> m_startCol;
+};
+
+// TODO: This evaluator does not actually use the child evaluator; 
+// all action is via the data() as returned by the Block expression.
+
+template<typename ArgType, int BlockRows, int BlockCols, bool InnerPanel> 
+struct block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel, /* HasDirectAccess */ true>
+  : mapbase_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>,
+                      typename Block<ArgType, BlockRows, BlockCols, InnerPanel>::PlainObject>
+{
+  typedef Block<ArgType, BlockRows, BlockCols, InnerPanel> XprType;
+  typedef typename XprType::Scalar Scalar;
+
+  EIGEN_DEVICE_FUNC explicit block_evaluator(const XprType& block)
+    : mapbase_evaluator<XprType, typename XprType::PlainObject>(block) 
+  {
+    // TODO: for the 3.3 release, this should be turned to an internal assertion, but let's keep it as is for the beta lifetime
+    eigen_assert(((internal::UIntPtr(block.data()) % EIGEN_PLAIN_ENUM_MAX(1,evaluator<XprType>::Alignment)) == 0) && "data is not aligned");
+  }
+};
+
+
+// -------------------- Select --------------------
+// NOTE shall we introduce a ternary_evaluator?
+
+// TODO enable vectorization for Select
+template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType>
+struct evaluator<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
+  : evaluator_base<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
+{
+  typedef Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> XprType;
+  enum {
+    CoeffReadCost = evaluator<ConditionMatrixType>::CoeffReadCost
+                  + EIGEN_PLAIN_ENUM_MAX(evaluator<ThenMatrixType>::CoeffReadCost,
+                                         evaluator<ElseMatrixType>::CoeffReadCost),
+
+    Flags = (unsigned int)evaluator<ThenMatrixType>::Flags & evaluator<ElseMatrixType>::Flags & HereditaryBits,
+    
+    Alignment = EIGEN_PLAIN_ENUM_MIN(evaluator<ThenMatrixType>::Alignment, evaluator<ElseMatrixType>::Alignment)
+  };
+
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& select)
+    : m_conditionImpl(select.conditionMatrix()),
+      m_thenImpl(select.thenMatrix()),
+      m_elseImpl(select.elseMatrix())
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+ 
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    if (m_conditionImpl.coeff(row, col))
+      return m_thenImpl.coeff(row, col);
+    else
+      return m_elseImpl.coeff(row, col);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    if (m_conditionImpl.coeff(index))
+      return m_thenImpl.coeff(index);
+    else
+      return m_elseImpl.coeff(index);
+  }
+ 
+protected:
+  evaluator<ConditionMatrixType> m_conditionImpl;
+  evaluator<ThenMatrixType> m_thenImpl;
+  evaluator<ElseMatrixType> m_elseImpl;
+};
+
+
+// -------------------- Replicate --------------------
+
+template<typename ArgType, int RowFactor, int ColFactor> 
+struct unary_evaluator<Replicate<ArgType, RowFactor, ColFactor> >
+  : evaluator_base<Replicate<ArgType, RowFactor, ColFactor> >
+{
+  typedef Replicate<ArgType, RowFactor, ColFactor> XprType;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  enum {
+    Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor
+  };
+  typedef typename internal::nested_eval<ArgType,Factor>::type ArgTypeNested;
+  typedef typename internal::remove_all<ArgTypeNested>::type ArgTypeNestedCleaned;
+  
+  enum {
+    CoeffReadCost = evaluator<ArgTypeNestedCleaned>::CoeffReadCost,
+    LinearAccessMask = XprType::IsVectorAtCompileTime ? LinearAccessBit : 0,
+    Flags = (evaluator<ArgTypeNestedCleaned>::Flags & (HereditaryBits|LinearAccessMask) & ~RowMajorBit) | (traits<XprType>::Flags & RowMajorBit),
+    
+    Alignment = evaluator<ArgTypeNestedCleaned>::Alignment
+  };
+
+  EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& replicate)
+    : m_arg(replicate.nestedExpression()),
+      m_argImpl(m_arg),
+      m_rows(replicate.nestedExpression().rows()),
+      m_cols(replicate.nestedExpression().cols())
+  {}
+ 
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    // try to avoid using modulo; this is a pure optimization strategy
+    const Index actual_row = internal::traits<XprType>::RowsAtCompileTime==1 ? 0
+                           : RowFactor==1 ? row
+                           : row % m_rows.value();
+    const Index actual_col = internal::traits<XprType>::ColsAtCompileTime==1 ? 0
+                           : ColFactor==1 ? col
+                           : col % m_cols.value();
+    
+    return m_argImpl.coeff(actual_row, actual_col);
+  }
+  
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    // try to avoid using modulo; this is a pure optimization strategy
+    const Index actual_index = internal::traits<XprType>::RowsAtCompileTime==1
+                                  ? (ColFactor==1 ?  index : index%m_cols.value())
+                                  : (RowFactor==1 ?  index : index%m_rows.value());
+    
+    return m_argImpl.coeff(actual_index);
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    const Index actual_row = internal::traits<XprType>::RowsAtCompileTime==1 ? 0
+                           : RowFactor==1 ? row
+                           : row % m_rows.value();
+    const Index actual_col = internal::traits<XprType>::ColsAtCompileTime==1 ? 0
+                           : ColFactor==1 ? col
+                           : col % m_cols.value();
+
+    return m_argImpl.template packet<LoadMode,PacketType>(actual_row, actual_col);
+  }
+  
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    const Index actual_index = internal::traits<XprType>::RowsAtCompileTime==1
+                                  ? (ColFactor==1 ?  index : index%m_cols.value())
+                                  : (RowFactor==1 ?  index : index%m_rows.value());
+
+    return m_argImpl.template packet<LoadMode,PacketType>(actual_index);
+  }
+ 
+protected:
+  const ArgTypeNested m_arg;
+  evaluator<ArgTypeNestedCleaned> m_argImpl;
+  const variable_if_dynamic<Index, ArgType::RowsAtCompileTime> m_rows;
+  const variable_if_dynamic<Index, ArgType::ColsAtCompileTime> m_cols;
+};
+
+
+// -------------------- PartialReduxExpr --------------------
+
+template< typename ArgType, typename MemberOp, int Direction>
+struct evaluator<PartialReduxExpr<ArgType, MemberOp, Direction> >
+  : evaluator_base<PartialReduxExpr<ArgType, MemberOp, Direction> >
+{
+  typedef PartialReduxExpr<ArgType, MemberOp, Direction> XprType;
+  typedef typename internal::nested_eval<ArgType,1>::type ArgTypeNested;
+  typedef typename internal::remove_all<ArgTypeNested>::type ArgTypeNestedCleaned;
+  typedef typename ArgType::Scalar InputScalar;
+  typedef typename XprType::Scalar Scalar;
+  enum {
+    TraversalSize = Direction==int(Vertical) ? int(ArgType::RowsAtCompileTime) :  int(ArgType::ColsAtCompileTime)
+  };
+  typedef typename MemberOp::template Cost<InputScalar,int(TraversalSize)> CostOpType;
+  enum {
+    CoeffReadCost = TraversalSize==Dynamic ? HugeCost
+                  : TraversalSize * evaluator<ArgType>::CoeffReadCost + int(CostOpType::value),
+    
+    Flags = (traits<XprType>::Flags&RowMajorBit) | (evaluator<ArgType>::Flags&(HereditaryBits&(~RowMajorBit))) | LinearAccessBit,
+    
+    Alignment = 0 // FIXME this will need to be improved once PartialReduxExpr is vectorized
+  };
+
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType xpr)
+    : m_arg(xpr.nestedExpression()), m_functor(xpr.functor())
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(TraversalSize==Dynamic ? HugeCost : int(CostOpType::value));
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const Scalar coeff(Index i, Index j) const
+  {
+    if (Direction==Vertical)
+      return m_functor(m_arg.col(j));
+    else
+      return m_functor(m_arg.row(i));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const Scalar coeff(Index index) const
+  {
+    if (Direction==Vertical)
+      return m_functor(m_arg.col(index));
+    else
+      return m_functor(m_arg.row(index));
+  }
+
+protected:
+  typename internal::add_const_on_value_type<ArgTypeNested>::type m_arg;
+  const MemberOp m_functor;
+};
+
+
+// -------------------- MatrixWrapper and ArrayWrapper --------------------
+//
+// evaluator_wrapper_base<T> is a common base class for the
+// MatrixWrapper and ArrayWrapper evaluators.
+
+template<typename XprType>
+struct evaluator_wrapper_base
+  : evaluator_base<XprType>
+{
+  typedef typename remove_all<typename XprType::NestedExpressionType>::type ArgType;
+  enum {
+    CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+    Flags = evaluator<ArgType>::Flags,
+    Alignment = evaluator<ArgType>::Alignment
+  };
+
+  EIGEN_DEVICE_FUNC explicit evaluator_wrapper_base(const ArgType& arg) : m_argImpl(arg) {}
+
+  typedef typename ArgType::Scalar Scalar;
+  typedef typename ArgType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    return m_argImpl.coeff(row, col);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_argImpl.coeff(index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index row, Index col)
+  {
+    return m_argImpl.coeffRef(row, col);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index index)
+  {
+    return m_argImpl.coeffRef(index);
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    return m_argImpl.template packet<LoadMode,PacketType>(row, col);
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    return m_argImpl.template packet<LoadMode,PacketType>(index);
+  }
+
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index row, Index col, const PacketType& x)
+  {
+    m_argImpl.template writePacket<StoreMode>(row, col, x);
+  }
+
+  template<int StoreMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketType& x)
+  {
+    m_argImpl.template writePacket<StoreMode>(index, x);
+  }
+
+protected:
+  evaluator<ArgType> m_argImpl;
+};
+
+template<typename TArgType>
+struct unary_evaluator<MatrixWrapper<TArgType> >
+  : evaluator_wrapper_base<MatrixWrapper<TArgType> >
+{
+  typedef MatrixWrapper<TArgType> XprType;
+
+  EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& wrapper)
+    : evaluator_wrapper_base<MatrixWrapper<TArgType> >(wrapper.nestedExpression())
+  { }
+};
+
+template<typename TArgType>
+struct unary_evaluator<ArrayWrapper<TArgType> >
+  : evaluator_wrapper_base<ArrayWrapper<TArgType> >
+{
+  typedef ArrayWrapper<TArgType> XprType;
+
+  EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& wrapper)
+    : evaluator_wrapper_base<ArrayWrapper<TArgType> >(wrapper.nestedExpression())
+  { }
+};
+
+
+// -------------------- Reverse --------------------
+
+// defined in Reverse.h:
+template<typename PacketType, bool ReversePacket> struct reverse_packet_cond;
+
+template<typename ArgType, int Direction>
+struct unary_evaluator<Reverse<ArgType, Direction> >
+  : evaluator_base<Reverse<ArgType, Direction> >
+{
+  typedef Reverse<ArgType, Direction> XprType;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  enum {
+    IsRowMajor = XprType::IsRowMajor,
+    IsColMajor = !IsRowMajor,
+    ReverseRow = (Direction == Vertical)   || (Direction == BothDirections),
+    ReverseCol = (Direction == Horizontal) || (Direction == BothDirections),
+    ReversePacket = (Direction == BothDirections)
+                    || ((Direction == Vertical)   && IsColMajor)
+                    || ((Direction == Horizontal) && IsRowMajor),
+                    
+    CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+    
+    // let's enable LinearAccess only with vectorization because of the product overhead
+    // FIXME enable DirectAccess with negative strides?
+    Flags0 = evaluator<ArgType>::Flags,
+    LinearAccess = ( (Direction==BothDirections) && (int(Flags0)&PacketAccessBit) )
+                  || ((ReverseRow && XprType::ColsAtCompileTime==1) || (ReverseCol && XprType::RowsAtCompileTime==1))
+                 ? LinearAccessBit : 0,
+
+    Flags = int(Flags0) & (HereditaryBits | PacketAccessBit | LinearAccess),
+    
+    Alignment = 0 // FIXME in some rare cases, Alignment could be preserved, like a Vector4f.
+  };
+
+  EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& reverse)
+    : m_argImpl(reverse.nestedExpression()),
+      m_rows(ReverseRow ? reverse.nestedExpression().rows() : 1),
+      m_cols(ReverseCol ? reverse.nestedExpression().cols() : 1)
+  { }
+ 
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index col) const
+  {
+    return m_argImpl.coeff(ReverseRow ? m_rows.value() - row - 1 : row,
+                           ReverseCol ? m_cols.value() - col - 1 : col);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_argImpl.coeff(m_rows.value() * m_cols.value() - index - 1);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index row, Index col)
+  {
+    return m_argImpl.coeffRef(ReverseRow ? m_rows.value() - row - 1 : row,
+                              ReverseCol ? m_cols.value() - col - 1 : col);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index index)
+  {
+    return m_argImpl.coeffRef(m_rows.value() * m_cols.value() - index - 1);
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index row, Index col) const
+  {
+    enum {
+      PacketSize = unpacket_traits<PacketType>::size,
+      OffsetRow  = ReverseRow && IsColMajor ? PacketSize : 1,
+      OffsetCol  = ReverseCol && IsRowMajor ? PacketSize : 1
+    };
+    typedef internal::reverse_packet_cond<PacketType,ReversePacket> reverse_packet;
+    return reverse_packet::run(m_argImpl.template packet<LoadMode,PacketType>(
+                                  ReverseRow ? m_rows.value() - row - OffsetRow : row,
+                                  ReverseCol ? m_cols.value() - col - OffsetCol : col));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  PacketType packet(Index index) const
+  {
+    enum { PacketSize = unpacket_traits<PacketType>::size };
+    return preverse(m_argImpl.template packet<LoadMode,PacketType>(m_rows.value() * m_cols.value() - index - PacketSize));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index row, Index col, const PacketType& x)
+  {
+    // FIXME we could factorize some code with packet(i,j)
+    enum {
+      PacketSize = unpacket_traits<PacketType>::size,
+      OffsetRow  = ReverseRow && IsColMajor ? PacketSize : 1,
+      OffsetCol  = ReverseCol && IsRowMajor ? PacketSize : 1
+    };
+    typedef internal::reverse_packet_cond<PacketType,ReversePacket> reverse_packet;
+    m_argImpl.template writePacket<LoadMode>(
+                                  ReverseRow ? m_rows.value() - row - OffsetRow : row,
+                                  ReverseCol ? m_cols.value() - col - OffsetCol : col,
+                                  reverse_packet::run(x));
+  }
+
+  template<int LoadMode, typename PacketType>
+  EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketType& x)
+  {
+    enum { PacketSize = unpacket_traits<PacketType>::size };
+    m_argImpl.template writePacket<LoadMode>
+      (m_rows.value() * m_cols.value() - index - PacketSize, preverse(x));
+  }
+ 
+protected:
+  evaluator<ArgType> m_argImpl;
+
+  // If we do not reverse rows, then we do not need to know the number of rows; same for columns
+  // Nonetheless, in this case it is important to set to 1 such that the coeff(index) method works fine for vectors.
+  const variable_if_dynamic<Index, ReverseRow ? ArgType::RowsAtCompileTime : 1> m_rows;
+  const variable_if_dynamic<Index, ReverseCol ? ArgType::ColsAtCompileTime : 1> m_cols;
+};
+
+
+// -------------------- Diagonal --------------------
+
+template<typename ArgType, int DiagIndex>
+struct evaluator<Diagonal<ArgType, DiagIndex> >
+  : evaluator_base<Diagonal<ArgType, DiagIndex> >
+{
+  typedef Diagonal<ArgType, DiagIndex> XprType;
+  
+  enum {
+    CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+    
+    Flags = (unsigned int)(evaluator<ArgType>::Flags & (HereditaryBits | DirectAccessBit) & ~RowMajorBit) | LinearAccessBit,
+    
+    Alignment = 0
+  };
+
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& diagonal)
+    : m_argImpl(diagonal.nestedExpression()),
+      m_index(diagonal.index())
+  { }
+ 
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index row, Index) const
+  {
+    return m_argImpl.coeff(row + rowOffset(), row + colOffset());
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  CoeffReturnType coeff(Index index) const
+  {
+    return m_argImpl.coeff(index + rowOffset(), index + colOffset());
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index row, Index)
+  {
+    return m_argImpl.coeffRef(row + rowOffset(), row + colOffset());
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Scalar& coeffRef(Index index)
+  {
+    return m_argImpl.coeffRef(index + rowOffset(), index + colOffset());
+  }
+
+protected:
+  evaluator<ArgType> m_argImpl;
+  const internal::variable_if_dynamicindex<Index, XprType::DiagIndex> m_index;
+
+private:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value() > 0 ? 0 : -m_index.value(); }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value() > 0 ? m_index.value() : 0; }
+};
+
+
+//----------------------------------------------------------------------
+// deprecated code
+//----------------------------------------------------------------------
+
+// -------------------- EvalToTemp --------------------
+
+// expression class for evaluating nested expression to a temporary
+
+template<typename ArgType> class EvalToTemp;
+
+template<typename ArgType>
+struct traits<EvalToTemp<ArgType> >
+  : public traits<ArgType>
+{ };
+
+template<typename ArgType>
+class EvalToTemp
+  : public dense_xpr_base<EvalToTemp<ArgType> >::type
+{
+ public:
+ 
+  typedef typename dense_xpr_base<EvalToTemp>::type Base;
+  EIGEN_GENERIC_PUBLIC_INTERFACE(EvalToTemp)
+ 
+  explicit EvalToTemp(const ArgType& arg)
+    : m_arg(arg)
+  { }
+ 
+  const ArgType& arg() const
+  {
+    return m_arg;
+  }
+
+  Index rows() const 
+  {
+    return m_arg.rows();
+  }
+
+  Index cols() const 
+  {
+    return m_arg.cols();
+  }
+
+ private:
+  const ArgType& m_arg;
+};
+ 
+template<typename ArgType>
+struct evaluator<EvalToTemp<ArgType> >
+  : public evaluator<typename ArgType::PlainObject>
+{
+  typedef EvalToTemp<ArgType>                   XprType;
+  typedef typename ArgType::PlainObject         PlainObject;
+  typedef evaluator<PlainObject> Base;
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
+    : m_result(xpr.arg())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+  }
+
+  // This constructor is used when nesting an EvalTo evaluator in another evaluator
+  EIGEN_DEVICE_FUNC evaluator(const ArgType& arg)
+    : m_result(arg)
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+  }
+
+protected:
+  PlainObject m_result;
+};
+
+} // namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_COREEVALUATORS_H

Index: 3rd_party/eigen/Eigen/src/Core/CoreIterators.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CoreIterators.h
+++ 3rd_party/eigen/Eigen/src/Core/CoreIterators.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -13,49 +13,115 @@
 namespace Eigen { 
 
 /* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
  */
 
-/** \ingroup SparseCore_Module
-  * \class InnerIterator
-  * \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression
-  *
-  * todo
+namespace internal {
+
+template<typename XprType, typename EvaluatorKind>
+class inner_iterator_selector;
+
+}
+
+/** \class InnerIterator
+  * \brief An InnerIterator allows to loop over the element of any matrix expression.
+  * 
+  * \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is constructed.
+  * 
+  * TODO: add a usage example
   */
-
-// generic version for dense matrix and expressions
-template<typename Derived> class DenseBase<Derived>::InnerIterator
-{
-  protected:
-    typedef typename Derived::Scalar Scalar;
-    typedef typename Derived::Index Index;
-
-    enum { IsRowMajor = (Derived::Flags&RowMajorBit)==RowMajorBit };
-  public:
-    EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, Index outer)
-      : m_expression(expr), m_inner(0), m_outer(outer), m_end(expr.innerSize())
-    {}
-
-    EIGEN_STRONG_INLINE Scalar value() const
-    {
-      return (IsRowMajor) ? m_expression.coeff(m_outer, m_inner)
-                          : m_expression.coeff(m_inner, m_outer);
-    }
-
-    EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; }
-
-    EIGEN_STRONG_INLINE Index index() const { return m_inner; }
-    inline Index row() const { return IsRowMajor ? m_outer : index(); }
-    inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-    EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
-
-  protected:
-    const Derived& m_expression;
-    Index m_inner;
-    const Index m_outer;
-    const Index m_end;
+template<typename XprType>
+class InnerIterator
+{
+protected:
+  typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
+  typedef internal::evaluator<XprType> EvaluatorType;
+  typedef typename internal::traits<XprType>::Scalar Scalar;
+public:
+  /** Construct an iterator over the \a outerId -th row or column of \a xpr */
+  InnerIterator(const XprType &xpr, const Index &outerId)
+    : m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize())
+  {}
+  
+  /// \returns the value of the current coefficient.
+  EIGEN_STRONG_INLINE Scalar value() const          { return m_iter.value(); }
+  /** Increment the iterator \c *this to the next non-zero coefficient.
+    * Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView
+    */
+  EIGEN_STRONG_INLINE InnerIterator& operator++()   { m_iter.operator++(); return *this; }
+  /// \returns the column or row index of the current coefficient.
+  EIGEN_STRONG_INLINE Index index() const           { return m_iter.index(); }
+  /// \returns the row index of the current coefficient.
+  EIGEN_STRONG_INLINE Index row() const             { return m_iter.row(); }
+  /// \returns the column index of the current coefficient.
+  EIGEN_STRONG_INLINE Index col() const             { return m_iter.col(); }
+  /// \returns \c true if the iterator \c *this still references a valid coefficient.
+  EIGEN_STRONG_INLINE operator bool() const         { return m_iter; }
+  
+protected:
+  EvaluatorType m_eval;
+  IteratorType m_iter;
+private:
+  // If you get here, then you're not using the right InnerIterator type, e.g.:
+  //   SparseMatrix<double,RowMajor> A;
+  //   SparseMatrix<double>::InnerIterator it(A,0);
+  template<typename T> InnerIterator(const EigenBase<T>&,Index outer);
+};
+
+namespace internal {
+
+// Generic inner iterator implementation for dense objects
+template<typename XprType>
+class inner_iterator_selector<XprType, IndexBased>
+{
+protected:
+  typedef evaluator<XprType> EvaluatorType;
+  typedef typename traits<XprType>::Scalar Scalar;
+  enum { IsRowMajor = (XprType::Flags&RowMajorBit)==RowMajorBit };
+  
+public:
+  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize)
+    : m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize)
+  {}
+
+  EIGEN_STRONG_INLINE Scalar value() const
+  {
+    return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner)
+                        : m_eval.coeff(m_inner, m_outer);
+  }
+
+  EIGEN_STRONG_INLINE inner_iterator_selector& operator++() { m_inner++; return *this; }
+
+  EIGEN_STRONG_INLINE Index index() const { return m_inner; }
+  inline Index row() const { return IsRowMajor ? m_outer : index(); }
+  inline Index col() const { return IsRowMajor ? index() : m_outer; }
+
+  EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
+
+protected:
+  const EvaluatorType& m_eval;
+  Index m_inner;
+  const Index m_outer;
+  const Index m_end;
+};
+
+// For iterator-based evaluator, inner-iterator is already implemented as
+// evaluator<>::InnerIterator
+template<typename XprType>
+class inner_iterator_selector<XprType, IteratorBased>
+ : public evaluator<XprType>::InnerIterator
+{
+protected:
+  typedef typename evaluator<XprType>::InnerIterator Base;
+  typedef evaluator<XprType> EvaluatorType;
+  
+public:
+  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &/*innerSize*/)
+    : Base(eval, outerId)
+  {}  
 };
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_COREITERATORS_H

Index: 3rd_party/eigen/Eigen/src/Core/CwiseBinaryOp.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CwiseBinaryOp.h
+++ 3rd_party/eigen/Eigen/src/Core/CwiseBinaryOp.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -11,30 +11,10 @@
 #ifndef EIGEN_CWISE_BINARY_OP_H
 #define EIGEN_CWISE_BINARY_OP_H
 
 namespace Eigen {
 
-/** \class CwiseBinaryOp
-  * \ingroup Core_Module
-  *
-  * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions
-  *
-  * \param BinaryOp template functor implementing the operator
-  * \param Lhs the type of the left-hand side
-  * \param Rhs the type of the right-hand side
-  *
-  * This class represents an expression  where a coefficient-wise binary operator is applied to two expressions.
-  * It is the return type of binary operators, by which we mean only those binary operators where
-  * both the left-hand side and the right-hand side are Eigen expressions.
-  * For example, the return type of matrix1+matrix2 is a CwiseBinaryOp.
-  *
-  * Most of the time, this is the only way that it is used, so you typically don't have to name
-  * CwiseBinaryOp types explicitly.
-  *
-  * \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp
-  */
-
 namespace internal {
 template<typename BinaryOp, typename Lhs, typename Rhs>
 struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
 {
   // we must not inherit from traits<Lhs> since it has
@@ -50,152 +30,128 @@
 
   // even though we require Lhs and Rhs to have the same scalar type (see CwiseBinaryOp constructor),
   // we still want to handle the case when the result type is different.
   typedef typename result_of<
                      BinaryOp(
-                       typename Lhs::Scalar,
-                       typename Rhs::Scalar
+                       const typename Lhs::Scalar&,
+                       const typename Rhs::Scalar&
                      )
                    >::type Scalar;
-  typedef typename promote_storage_type<typename traits<Lhs>::StorageKind,
-                                           typename traits<Rhs>::StorageKind>::ret StorageKind;
-  typedef typename promote_index_type<typename traits<Lhs>::Index,
-                                         typename traits<Rhs>::Index>::type Index;
+  typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind,
+                                              typename traits<Rhs>::StorageKind,
+                                              BinaryOp>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<Lhs>::StorageIndex,
+                                      typename traits<Rhs>::StorageIndex>::type StorageIndex;
   typedef typename Lhs::Nested LhsNested;
   typedef typename Rhs::Nested RhsNested;
   typedef typename remove_reference<LhsNested>::type _LhsNested;
   typedef typename remove_reference<RhsNested>::type _RhsNested;
   enum {
-    LhsCoeffReadCost = _LhsNested::CoeffReadCost,
-    RhsCoeffReadCost = _RhsNested::CoeffReadCost,
-    LhsFlags = _LhsNested::Flags,
-    RhsFlags = _RhsNested::Flags,
-    SameType = is_same<typename _LhsNested::Scalar,typename _RhsNested::Scalar>::value,
-    StorageOrdersAgree = (int(Lhs::Flags)&RowMajorBit)==(int(Rhs::Flags)&RowMajorBit),
-    Flags0 = (int(LhsFlags) | int(RhsFlags)) & (
-        HereditaryBits
-      | (int(LhsFlags) & int(RhsFlags) &
-           ( AlignedBit
-           | (StorageOrdersAgree ? LinearAccessBit : 0)
-           | (functor_traits<BinaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)
-           )
-        )
-     ),
-    Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
-    CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + functor_traits<BinaryOp>::Cost
+    Flags = cwise_promote_storage_order<typename traits<Lhs>::StorageKind,typename traits<Rhs>::StorageKind,_LhsNested::Flags & RowMajorBit,_RhsNested::Flags & RowMajorBit>::value
   };
 };
 } // end namespace internal
 
-// we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor
-// that would take two operands of different types. If there were such an example, then this check should be
-// moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as
-// currently they take only one typename Scalar template parameter.
-// It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths.
-// So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
-// add together a float matrix and a double matrix.
-#define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \
-  EIGEN_STATIC_ASSERT((internal::functor_is_product_like<BINOP>::ret \
-                        ? int(internal::scalar_product_traits<LHS, RHS>::Defined) \
-                        : int(internal::is_same<LHS, RHS>::value)), \
-    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-
 template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
 class CwiseBinaryOpImpl;
 
-template<typename BinaryOp, typename Lhs, typename Rhs>
-class CwiseBinaryOp : internal::no_assignment_operator,
+/** \class CwiseBinaryOp
+  * \ingroup Core_Module
+  *
+  * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions
+  *
+  * \tparam BinaryOp template functor implementing the operator
+  * \tparam LhsType the type of the left-hand side
+  * \tparam RhsType the type of the right-hand side
+  *
+  * This class represents an expression  where a coefficient-wise binary operator is applied to two expressions.
+  * It is the return type of binary operators, by which we mean only those binary operators where
+  * both the left-hand side and the right-hand side are Eigen expressions.
+  * For example, the return type of matrix1+matrix2 is a CwiseBinaryOp.
+  *
+  * Most of the time, this is the only way that it is used, so you typically don't have to name
+  * CwiseBinaryOp types explicitly.
+  *
+  * \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp
+  */
+template<typename BinaryOp, typename LhsType, typename RhsType>
+class CwiseBinaryOp : 
   public CwiseBinaryOpImpl<
-          BinaryOp, Lhs, Rhs,
-          typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
-                                           typename internal::traits<Rhs>::StorageKind>::ret>
+          BinaryOp, LhsType, RhsType,
+          typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
+                                                        typename internal::traits<RhsType>::StorageKind,
+                                                        BinaryOp>::ret>,
+  internal::no_assignment_operator
 {
   public:
+    
+    typedef typename internal::remove_all<BinaryOp>::type Functor;
+    typedef typename internal::remove_all<LhsType>::type Lhs;
+    typedef typename internal::remove_all<RhsType>::type Rhs;
 
     typedef typename CwiseBinaryOpImpl<
-        BinaryOp, Lhs, Rhs,
-        typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
-                                         typename internal::traits<Rhs>::StorageKind>::ret>::Base Base;
+        BinaryOp, LhsType, RhsType,
+        typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
+                                                      typename internal::traits<Rhs>::StorageKind,
+                                                      BinaryOp>::ret>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
 
-    typedef typename internal::nested<Lhs>::type LhsNested;
-    typedef typename internal::nested<Rhs>::type RhsNested;
+    typedef typename internal::ref_selector<LhsType>::type LhsNested;
+    typedef typename internal::ref_selector<RhsType>::type RhsNested;
     typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
     typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp())
       : m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
     {
       EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar);
       // require the sizes to match
       EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
       eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
     }
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index rows() const {
       // return the fixed size type if available to enable compile time optimizations
       if (internal::traits<typename internal::remove_all<LhsNested>::type>::RowsAtCompileTime==Dynamic)
         return m_rhs.rows();
       else
         return m_lhs.rows();
     }
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index cols() const {
       // return the fixed size type if available to enable compile time optimizations
       if (internal::traits<typename internal::remove_all<LhsNested>::type>::ColsAtCompileTime==Dynamic)
         return m_rhs.cols();
       else
         return m_lhs.cols();
     }
 
     /** \returns the left hand side nested expression */
+    EIGEN_DEVICE_FUNC
     const _LhsNested& lhs() const { return m_lhs; }
     /** \returns the right hand side nested expression */
+    EIGEN_DEVICE_FUNC
     const _RhsNested& rhs() const { return m_rhs; }
     /** \returns the functor representing the binary operation */
+    EIGEN_DEVICE_FUNC
     const BinaryOp& functor() const { return m_functor; }
 
   protected:
     LhsNested m_lhs;
     RhsNested m_rhs;
     const BinaryOp m_functor;
 };
 
-template<typename BinaryOp, typename Lhs, typename Rhs>
-class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
-  : public internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
-{
-    typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived;
-  public:
-
-    typedef typename internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
-
-    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
-    {
-      return derived().functor()(derived().lhs().coeff(rowId, colId),
-                                 derived().rhs().coeff(rowId, colId));
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
-    {
-      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(rowId, colId),
-                                          derived().rhs().template packet<LoadMode>(rowId, colId));
-    }
-
-    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
-    {
-      return derived().functor()(derived().lhs().coeff(index),
-                                 derived().rhs().coeff(index));
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
-    {
-      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(index),
-                                          derived().rhs().template packet<LoadMode>(index));
-    }
+// Generic API dispatcher
+template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
+class CwiseBinaryOpImpl
+  : public internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
+{
+public:
+  typedef typename internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
 };
 
 /** replaces \c *this by \c *this - \a other.
   *
   * \returns a reference to \c *this
@@ -203,12 +159,11 @@
 template<typename Derived>
 template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived &
 MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other)
 {
-  SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
-  tmp = other.derived();
+  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }
 
 /** replaces \c *this by \c *this + \a other.
   *
@@ -217,13 +172,13 @@
 template<typename Derived>
 template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived &
 MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
 {
-  SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
-  tmp = other.derived();
+  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_CWISE_BINARY_OP_H
+

Index: 3rd_party/eigen/Eigen/src/Core/CwiseNullaryOp.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CwiseNullaryOp.h
+++ 3rd_party/eigen/Eigen/src/Core/CwiseNullaryOp.h
@@ -10,87 +10,79 @@
 #ifndef EIGEN_CWISE_NULLARY_OP_H
 #define EIGEN_CWISE_NULLARY_OP_H
 
 namespace Eigen {
 
+namespace internal {
+template<typename NullaryOp, typename PlainObjectType>
+struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType>
+{
+  enum {
+    Flags = traits<PlainObjectType>::Flags & RowMajorBit
+  };
+};
+
+} // namespace internal
+
 /** \class CwiseNullaryOp
   * \ingroup Core_Module
   *
   * \brief Generic expression of a matrix where all coefficients are defined by a functor
   *
-  * \param NullaryOp template functor implementing the operator
-  * \param PlainObjectType the underlying plain matrix/array type
+  * \tparam NullaryOp template functor implementing the operator
+  * \tparam PlainObjectType the underlying plain matrix/array type
   *
   * This class represents an expression of a generic nullary operator.
   * It is the return type of the Ones(), Zero(), Constant(), Identity() and Random() methods,
   * and most of the time this is the only way it is used.
   *
   * However, if you want to write a function returning such an expression, you
   * will need to use this class.
   *
-  * \sa class CwiseUnaryOp, class CwiseBinaryOp, DenseBase::NullaryExpr()
-  */
-
-namespace internal {
-template<typename NullaryOp, typename PlainObjectType>
-struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType>
-{
-  enum {
-    Flags = (traits<PlainObjectType>::Flags
-      & (  HereditaryBits
-         | (functor_has_linear_access<NullaryOp>::ret ? LinearAccessBit : 0)
-         | (functor_traits<NullaryOp>::PacketAccess ? PacketAccessBit : 0)))
-      | (functor_traits<NullaryOp>::IsRepeatable ? 0 : EvalBeforeNestingBit),
-    CoeffReadCost = functor_traits<NullaryOp>::Cost
-  };
-};
-}
-
-template<typename NullaryOp, typename PlainObjectType>
-class CwiseNullaryOp : internal::no_assignment_operator,
-  public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type
+  * The functor NullaryOp must expose one of the following method:
+    <table class="manual">
+    <tr            ><td>\c operator()() </td><td>if the procedural generation does not depend on the coefficient entries (e.g., random numbers)</td></tr>
+    <tr class="alt"><td>\c operator()(Index i)</td><td>if the procedural generation makes sense for vectors only and that it depends on the coefficient index \c i (e.g., linspace) </td></tr>
+    <tr            ><td>\c operator()(Index i,Index j)</td><td>if the procedural generation depends on the matrix coordinates \c i, \c j (e.g., to generate a checkerboard with 0 and 1)</td></tr>
+    </table>
+  * It is also possible to expose the last two operators if the generation makes sense for matrices but can be optimized for vectors.
+  *
+  * See DenseBase::NullaryExpr(Index,const CustomNullaryOp&) for an example binding
+  * C++11 random number generators.
+  *
+  * A nullary expression can also be used to implement custom sophisticated matrix manipulations
+  * that cannot be covered by the existing set of natively supported matrix manipulations.
+  * See this \ref TopicCustomizing_NullaryExpr "page" for some examples and additional explanations
+  * on the behavior of CwiseNullaryOp.
+  *
+  * \sa class CwiseUnaryOp, class CwiseBinaryOp, DenseBase::NullaryExpr
+  */
+template<typename NullaryOp, typename PlainObjectType>
+class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
 {
   public:
 
     typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
 
-    CwiseNullaryOp(Index nbRows, Index nbCols, const NullaryOp& func = NullaryOp())
-      : m_rows(nbRows), m_cols(nbCols), m_functor(func)
-    {
-      eigen_assert(nbRows >= 0
-            && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
-            &&  nbCols >= 0
-            && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols));
-    }
-
-    EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
-    EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
-
-    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
-    {
-      return m_functor(rowId, colId);
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
-    {
-      return m_functor.packetOp(rowId, colId);
-    }
-
-    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
-    {
-      return m_functor(index);
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
-    {
-      return m_functor.packetOp(index);
-    }
-
-    /** \returns the functor representing the nullary operation */
+    EIGEN_DEVICE_FUNC
+    CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
+      : m_rows(rows), m_cols(cols), m_functor(func)
+    {
+      eigen_assert(rows >= 0
+            && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
+            &&  cols >= 0
+            && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
+
+    /** \returns the functor representing the nullary operation */
+    EIGEN_DEVICE_FUNC
     const NullaryOp& functor() const { return m_functor; }
 
   protected:
     const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
     const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
@@ -111,14 +103,14 @@
   *
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
 template<typename CustomNullaryOp>
-EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
 DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func)
 {
-  return CwiseNullaryOp<CustomNullaryOp, Derived>(rows, cols, func);
+  return CwiseNullaryOp<CustomNullaryOp, PlainObject>(rows, cols, func);
 }
 
 /** \returns an expression of a matrix defined by a custom functor \a func
   *
   * The parameter \a size is the size of the returned vector.
@@ -130,20 +122,23 @@
   * it is redundant to pass \a size as argument, so Zero() should be used
   * instead.
   *
   * The template parameter \a CustomNullaryOp is the type of the functor.
   *
+  * Here is an example with C++11 random generators: \include random_cpp11.cpp
+  * Output: \verbinclude random_cpp11.out
+  * 
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
 template<typename CustomNullaryOp>
-EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
+EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
 DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, Derived>(1, size, func);
-  else return CwiseNullaryOp<CustomNullaryOp, Derived>(size, 1, func);
+  if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, PlainObject>(1, size, func);
+  else return CwiseNullaryOp<CustomNullaryOp, PlainObject>(size, 1, func);
 }
 
 /** \returns an expression of a matrix defined by a custom functor \a func
   *
   * This variant is only for fixed-size DenseBase types. For dynamic-size types, you
@@ -153,34 +148,34 @@
   *
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
 template<typename CustomNullaryOp>
-EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
 DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
 {
-  return CwiseNullaryOp<CustomNullaryOp, Derived>(RowsAtCompileTime, ColsAtCompileTime, func);
+  return CwiseNullaryOp<CustomNullaryOp, PlainObject>(RowsAtCompileTime, ColsAtCompileTime, func);
 }
 
 /** \returns an expression of a constant matrix of value \a value
   *
-  * The parameters \a nbRows and \a nbCols are the number of rows and of columns of
+  * The parameters \a rows and \a cols are the number of rows and of columns of
   * the returned matrix. Must be compatible with this DenseBase type.
   *
   * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
-  * it is redundant to pass \a nbRows and \a nbCols as arguments, so Zero() should be used
+  * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
   * instead.
   *
   * The template parameter \a CustomNullaryOp is the type of the functor.
   *
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Constant(Index nbRows, Index nbCols, const Scalar& value)
+DenseBase<Derived>::Constant(Index rows, Index cols, const Scalar& value)
 {
-  return DenseBase<Derived>::NullaryExpr(nbRows, nbCols, internal::scalar_constant_op<Scalar>(value));
+  return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_constant_op<Scalar>(value));
 }
 
 /** \returns an expression of a constant matrix of value \a value
   *
   * The parameter \a size is the size of the returned vector.
@@ -195,11 +190,11 @@
   * The template parameter \a CustomNullaryOp is the type of the functor.
   *
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
 DenseBase<Derived>::Constant(Index size, const Scalar& value)
 {
   return DenseBase<Derived>::NullaryExpr(size, internal::scalar_constant_op<Scalar>(value));
 }
 
@@ -211,106 +206,104 @@
   * The template parameter \a CustomNullaryOp is the type of the functor.
   *
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
 DenseBase<Derived>::Constant(const Scalar& value)
 {
   EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
   return DenseBase<Derived>::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_constant_op<Scalar>(value));
 }
 
-/**
-  * \brief Sets a linearly space vector.
-  *
-  * The function generates 'size' equally spaced values in the closed interval [low,high].
-  * This particular version of LinSpaced() uses sequential access, i.e. vector access is
-  * assumed to be a(0), a(1), ..., a(size). This assumption allows for better vectorization
-  * and yields faster code than the random access version.
-  *
-  * When size is set to 1, a vector of length 1 containing 'high' is returned.
-  *
-  * \only_for_vectors
-  *
-  * Example: \include DenseBase_LinSpaced_seq.cpp
-  * Output: \verbinclude DenseBase_LinSpaced_seq.out
-  *
-  * \sa setLinSpaced(Index,const Scalar&,const Scalar&), LinSpaced(Index,Scalar,Scalar), CwiseNullaryOp
+/** \deprecated because of accuracy loss. In Eigen 3.3, it is an alias for LinSpaced(Index,const Scalar&,const Scalar&)
+  *
+  * \sa LinSpaced(Index,Scalar,Scalar), setLinSpaced(Index,const Scalar&,const Scalar&)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::SequentialLinSpacedReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
 DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,false>(low,high,size));
+  return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,PacketScalar>(low,high,size));
 }
 
-/**
-  * \copydoc DenseBase::LinSpaced(Sequential_t, Index, const Scalar&, const Scalar&)
-  * Special version for fixed size types which does not require the size parameter.
+/** \deprecated because of accuracy loss. In Eigen 3.3, it is an alias for LinSpaced(const Scalar&,const Scalar&)
+  *
+  * \sa LinSpaced(Scalar,Scalar)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::SequentialLinSpacedReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
 DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,false>(low,high,Derived::SizeAtCompileTime));
+  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,PacketScalar>(low,high,Derived::SizeAtCompileTime));
 }
 
 /**
-  * \brief Sets a linearly space vector.
+  * \brief Sets a linearly spaced vector.
   *
   * The function generates 'size' equally spaced values in the closed interval [low,high].
   * When size is set to 1, a vector of length 1 containing 'high' is returned.
   *
   * \only_for_vectors
   *
   * Example: \include DenseBase_LinSpaced.cpp
   * Output: \verbinclude DenseBase_LinSpaced.out
   *
-  * \sa setLinSpaced(Index,const Scalar&,const Scalar&), LinSpaced(Sequential_t,Index,const Scalar&,const Scalar&,Index), CwiseNullaryOp
+  * For integer scalar types, an even spacing is possible if and only if the length of the range,
+  * i.e., \c high-low is a scalar multiple of \c size-1, or if \c size is a scalar multiple of the
+  * number of values \c high-low+1 (meaning each value can be repeated the same number of time).
+  * If one of these two considions is not satisfied, then \c high is lowered to the largest value
+  * satisfying one of this constraint.
+  * Here are some examples:
+  *
+  * Example: \include DenseBase_LinSpacedInt.cpp
+  * Output: \verbinclude DenseBase_LinSpacedInt.out
+  *
+  * \sa setLinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
 DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,true>(low,high,size));
+  return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,PacketScalar>(low,high,size));
 }
 
 /**
   * \copydoc DenseBase::LinSpaced(Index, const Scalar&, const Scalar&)
   * Special version for fixed size types which does not require the size parameter.
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
 DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,true>(low,high,Derived::SizeAtCompileTime));
+  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,PacketScalar>(low,high,Derived::SizeAtCompileTime));
 }
 
 /** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */
 template<typename Derived>
-bool DenseBase<Derived>::isApproxToConstant
+EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isApproxToConstant
 (const Scalar& val, const RealScalar& prec) const
 {
+  typename internal::nested_eval<Derived,1>::type self(derived());
   for(Index j = 0; j < cols(); ++j)
     for(Index i = 0; i < rows(); ++i)
-      if(!internal::isApprox(this->coeff(i, j), val, prec))
+      if(!internal::isApprox(self.coeff(i, j), val, prec))
         return false;
   return true;
 }
 
 /** This is just an alias for isApproxToConstant().
   *
   * \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
 template<typename Derived>
-bool DenseBase<Derived>::isConstant
+EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isConstant
 (const Scalar& val, const RealScalar& prec) const
 {
   return isApproxToConstant(val, prec);
 }
 
@@ -317,93 +310,99 @@
 /** Alias for setConstant(): sets all coefficients in this expression to \a val.
   *
   * \sa setConstant(), Constant(), class CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
 {
   setConstant(val);
 }
 
-/** Sets all coefficients in this expression to \a value.
+/** Sets all coefficients in this expression to value \a val.
   *
   * \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
 {
   return derived() = Constant(rows(), cols(), val);
 }
 
-/** Resizes to the given \a size, and sets all coefficients in this expression to the given \a value.
+/** Resizes to the given \a size, and sets all coefficients in this expression to the given value \a val.
   *
   * \only_for_vectors
   *
   * Example: \include Matrix_setConstant_int.cpp
   * Output: \verbinclude Matrix_setConstant_int.out
   *
   * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
 PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
 {
   resize(size);
   return setConstant(val);
 }
 
-/** Resizes to the given size, and sets all coefficients in this expression to the given \a value.
+/** Resizes to the given size, and sets all coefficients in this expression to the given value \a val.
   *
-  * \param nbRows the new number of rows
-  * \param nbCols the new number of columns
+  * \param rows the new number of rows
+  * \param cols the new number of columns
   * \param val the value to which all coefficients are set
   *
   * Example: \include Matrix_setConstant_int_int.cpp
   * Output: \verbinclude Matrix_setConstant_int_int.out
   *
   * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setConstant(Index nbRows, Index nbCols, const Scalar& val)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& val)
 {
-  resize(nbRows, nbCols);
+  resize(rows, cols);
   return setConstant(val);
 }
 
 /**
-  * \brief Sets a linearly space vector.
+  * \brief Sets a linearly spaced vector.
   *
   * The function generates 'size' equally spaced values in the closed interval [low,high].
   * When size is set to 1, a vector of length 1 containing 'high' is returned.
   *
   * \only_for_vectors
   *
   * Example: \include DenseBase_setLinSpaced.cpp
   * Output: \verbinclude DenseBase_setLinSpaced.out
   *
-  * \sa CwiseNullaryOp
+  * For integer scalar types, do not miss the explanations on the definition
+  * of \link LinSpaced(Index,const Scalar&,const Scalar&) even spacing \endlink.
+  *
+  * \sa LinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,false>(low,high,newSize));
+  return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,PacketScalar>(low,high,newSize));
 }
 
 /**
-  * \brief Sets a linearly space vector.
+  * \brief Sets a linearly spaced vector.
   *
-  * The function fill *this with equally spaced values in the closed interval [low,high].
+  * The function fills \c *this with equally spaced values in the closed interval [low,high].
   * When size is set to 1, a vector of length 1 containing 'high' is returned.
   *
   * \only_for_vectors
   *
-  * \sa setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp
+  * For integer scalar types, do not miss the explanations on the definition
+  * of \link LinSpaced(Index,const Scalar&,const Scalar&) even spacing \endlink.
+  *
+  * \sa LinSpaced(Index,const Scalar&,const Scalar&), setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return setLinSpaced(size(), low, high);
 }
 
@@ -422,14 +421,14 @@
   * Output: \verbinclude MatrixBase_zero_int_int.out
   *
   * \sa Zero(), Zero(Index)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Zero(Index nbRows, Index nbCols)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Zero(Index rows, Index cols)
 {
-  return Constant(nbRows, nbCols, Scalar(0));
+  return Constant(rows, cols, Scalar(0));
 }
 
 /** \returns an expression of a zero vector.
   *
   * The parameter \a size is the size of the returned vector.
@@ -445,11 +444,11 @@
   * Output: \verbinclude MatrixBase_zero_int.out
   *
   * \sa Zero(), Zero(Index,Index)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
 DenseBase<Derived>::Zero(Index size)
 {
   return Constant(size, Scalar(0));
 }
 
@@ -462,11 +461,11 @@
   * Output: \verbinclude MatrixBase_zero.out
   *
   * \sa Zero(Index), Zero(Index,Index)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
 DenseBase<Derived>::Zero()
 {
   return Constant(Scalar(0));
 }
 
@@ -477,15 +476,16 @@
   * Output: \verbinclude MatrixBase_isZero.out
   *
   * \sa class CwiseNullaryOp, Zero()
   */
 template<typename Derived>
-bool DenseBase<Derived>::isZero(const RealScalar& prec) const
+EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isZero(const RealScalar& prec) const
 {
+  typename internal::nested_eval<Derived,1>::type self(derived());
   for(Index j = 0; j < cols(); ++j)
     for(Index i = 0; i < rows(); ++i)
-      if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast<Scalar>(1), prec))
+      if(!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<Scalar>(1), prec))
         return false;
   return true;
 }
 
 /** Sets all coefficients in this expression to zero.
@@ -494,11 +494,11 @@
   * Output: \verbinclude MatrixBase_setZero.out
   *
   * \sa class CwiseNullaryOp, Zero()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
 {
   return setConstant(Scalar(0));
 }
 
 /** Resizes to the given \a size, and sets all coefficients in this expression to zero.
@@ -509,40 +509,40 @@
   * Output: \verbinclude Matrix_setZero_int.out
   *
   * \sa DenseBase::setZero(), setZero(Index,Index), class CwiseNullaryOp, DenseBase::Zero()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
 PlainObjectBase<Derived>::setZero(Index newSize)
 {
   resize(newSize);
   return setConstant(Scalar(0));
 }
 
 /** Resizes to the given size, and sets all coefficients in this expression to zero.
   *
-  * \param nbRows the new number of rows
-  * \param nbCols the new number of columns
+  * \param rows the new number of rows
+  * \param cols the new number of columns
   *
   * Example: \include Matrix_setZero_int_int.cpp
   * Output: \verbinclude Matrix_setZero_int_int.out
   *
   * \sa DenseBase::setZero(), setZero(Index), class CwiseNullaryOp, DenseBase::Zero()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setZero(Index nbRows, Index nbCols)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setZero(Index rows, Index cols)
 {
-  resize(nbRows, nbCols);
+  resize(rows, cols);
   return setConstant(Scalar(0));
 }
 
 // ones:
 
 /** \returns an expression of a matrix where all coefficients equal one.
   *
-  * The parameters \a nbRows and \a nbCols are the number of rows and of columns of
+  * The parameters \a rows and \a cols are the number of rows and of columns of
   * the returned matrix. Must be compatible with this MatrixBase type.
   *
   * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
   * it is redundant to pass \a rows and \a cols as arguments, so Ones() should be used
   * instead.
@@ -551,14 +551,14 @@
   * Output: \verbinclude MatrixBase_ones_int_int.out
   *
   * \sa Ones(), Ones(Index), isOnes(), class Ones
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(Index nbRows, Index nbCols)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Ones(Index rows, Index cols)
 {
-  return Constant(nbRows, nbCols, Scalar(1));
+  return Constant(rows, cols, Scalar(1));
 }
 
 /** \returns an expression of a vector where all coefficients equal one.
   *
   * The parameter \a newSize is the size of the returned vector.
@@ -574,11 +574,11 @@
   * Output: \verbinclude MatrixBase_ones_int.out
   *
   * \sa Ones(), Ones(Index,Index), isOnes(), class Ones
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
 DenseBase<Derived>::Ones(Index newSize)
 {
   return Constant(newSize, Scalar(1));
 }
 
@@ -591,11 +591,11 @@
   * Output: \verbinclude MatrixBase_ones.out
   *
   * \sa Ones(Index), Ones(Index,Index), isOnes(), class Ones
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
 DenseBase<Derived>::Ones()
 {
   return Constant(Scalar(1));
 }
 
@@ -606,11 +606,11 @@
   * Output: \verbinclude MatrixBase_isOnes.out
   *
   * \sa class CwiseNullaryOp, Ones()
   */
 template<typename Derived>
-bool DenseBase<Derived>::isOnes
+EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isOnes
 (const RealScalar& prec) const
 {
   return isApproxToConstant(Scalar(1), prec);
 }
 
@@ -620,11 +620,11 @@
   * Output: \verbinclude MatrixBase_setOnes.out
   *
   * \sa class CwiseNullaryOp, Ones()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
 {
   return setConstant(Scalar(1));
 }
 
 /** Resizes to the given \a newSize, and sets all coefficients in this expression to one.
@@ -635,40 +635,40 @@
   * Output: \verbinclude Matrix_setOnes_int.out
   *
   * \sa MatrixBase::setOnes(), setOnes(Index,Index), class CwiseNullaryOp, MatrixBase::Ones()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
 PlainObjectBase<Derived>::setOnes(Index newSize)
 {
   resize(newSize);
   return setConstant(Scalar(1));
 }
 
 /** Resizes to the given size, and sets all coefficients in this expression to one.
   *
-  * \param nbRows the new number of rows
-  * \param nbCols the new number of columns
+  * \param rows the new number of rows
+  * \param cols the new number of columns
   *
   * Example: \include Matrix_setOnes_int_int.cpp
   * Output: \verbinclude Matrix_setOnes_int_int.out
   *
   * \sa MatrixBase::setOnes(), setOnes(Index), class CwiseNullaryOp, MatrixBase::Ones()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setOnes(Index nbRows, Index nbCols)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
 {
-  resize(nbRows, nbCols);
+  resize(rows, cols);
   return setConstant(Scalar(1));
 }
 
 // Identity:
 
 /** \returns an expression of the identity matrix (not necessarily square).
   *
-  * The parameters \a nbRows and \a nbCols are the number of rows and of columns of
+  * The parameters \a rows and \a cols are the number of rows and of columns of
   * the returned matrix. Must be compatible with this MatrixBase type.
   *
   * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
   * it is redundant to pass \a rows and \a cols as arguments, so Identity() should be used
   * instead.
@@ -677,14 +677,14 @@
   * Output: \verbinclude MatrixBase_identity_int_int.out
   *
   * \sa Identity(), setIdentity(), isIdentity()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
-MatrixBase<Derived>::Identity(Index nbRows, Index nbCols)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
+MatrixBase<Derived>::Identity(Index rows, Index cols)
 {
-  return DenseBase<Derived>::NullaryExpr(nbRows, nbCols, internal::scalar_identity_op<Scalar>());
+  return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_identity_op<Scalar>());
 }
 
 /** \returns an expression of the identity matrix (not necessarily square).
   *
   * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
@@ -694,11 +694,11 @@
   * Output: \verbinclude MatrixBase_identity.out
   *
   * \sa Identity(Index,Index), setIdentity(), isIdentity()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
 MatrixBase<Derived>::Identity()
 {
   EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
   return MatrixBase<Derived>::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_identity_op<Scalar>());
 }
@@ -714,22 +714,23 @@
   */
 template<typename Derived>
 bool MatrixBase<Derived>::isIdentity
 (const RealScalar& prec) const
 {
+  typename internal::nested_eval<Derived,1>::type self(derived());
   for(Index j = 0; j < cols(); ++j)
   {
     for(Index i = 0; i < rows(); ++i)
     {
       if(i == j)
       {
-        if(!internal::isApprox(this->coeff(i, j), static_cast<Scalar>(1), prec))
+        if(!internal::isApprox(self.coeff(i, j), static_cast<Scalar>(1), prec))
           return false;
       }
       else
       {
-        if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast<RealScalar>(1), prec))
+        if(!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<RealScalar>(1), prec))
           return false;
       }
     }
   }
   return true;
@@ -738,24 +739,25 @@
 namespace internal {
 
 template<typename Derived, bool Big = (Derived::SizeAtCompileTime>=16)>
 struct setIdentity_impl
 {
+  EIGEN_DEVICE_FUNC
   static EIGEN_STRONG_INLINE Derived& run(Derived& m)
   {
     return m = Derived::Identity(m.rows(), m.cols());
   }
 };
 
 template<typename Derived>
 struct setIdentity_impl<Derived, true>
 {
-  typedef typename Derived::Index Index;
+  EIGEN_DEVICE_FUNC
   static EIGEN_STRONG_INLINE Derived& run(Derived& m)
   {
     m.setZero();
-    const Index size = (std::min)(m.rows(), m.cols());
+    const Index size = numext::mini(m.rows(), m.cols());
     for(Index i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
     return m;
   }
 };
 
@@ -767,29 +769,29 @@
   * Output: \verbinclude MatrixBase_setIdentity.out
   *
   * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
 {
   return internal::setIdentity_impl<Derived>::run(derived());
 }
 
 /** \brief Resizes to the given size, and writes the identity expression (not necessarily square) into *this.
   *
-  * \param nbRows the new number of rows
-  * \param nbCols the new number of columns
+  * \param rows the new number of rows
+  * \param cols the new number of columns
   *
   * Example: \include Matrix_setIdentity_int_int.cpp
   * Output: \verbinclude Matrix_setIdentity_int_int.out
   *
   * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index nbRows, Index nbCols)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols)
 {
-  derived().resize(nbRows, nbCols);
+  derived().resize(rows, cols);
   return setIdentity();
 }
 
 /** \returns an expression of the i-th unit (basis) vector.
   *
@@ -796,11 +798,11 @@
   * \only_for_vectors
   *
   * \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return BasisReturnType(SquareMatrixType::Identity(newSize,newSize), i);
 }
 
@@ -811,11 +813,11 @@
   * This variant is for fixed-size vector only.
   *
   * \sa MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index i)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index i)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return BasisReturnType(SquareMatrixType::Identity(),i);
 }
 
@@ -824,41 +826,41 @@
   * \only_for_vectors
   *
   * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitX()
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitX()
 { return Derived::Unit(0); }
 
 /** \returns an expression of the Y axis unit vector (0,1{,0}^*)
   *
   * \only_for_vectors
   *
   * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitY()
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitY()
 { return Derived::Unit(1); }
 
 /** \returns an expression of the Z axis unit vector (0,0,1{,0}^*)
   *
   * \only_for_vectors
   *
   * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitZ()
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitZ()
 { return Derived::Unit(2); }
 
 /** \returns an expression of the W axis unit vector (0,0,0,1)
   *
   * \only_for_vectors
   *
   * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
 { return Derived::Unit(3); }
 
 } // end namespace Eigen
 
 #endif // EIGEN_CWISE_NULLARY_OP_H

ADDED   3rd_party/eigen/Eigen/src/Core/CwiseTernaryOp.h
Index: 3rd_party/eigen/Eigen/src/Core/CwiseTernaryOp.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CwiseTernaryOp.h
+++ 3rd_party/eigen/Eigen/src/Core/CwiseTernaryOp.h
@@ -0,0 +1,197 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2016 Eugene Brevdo <ebrevdo@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CWISE_TERNARY_OP_H
+#define EIGEN_CWISE_TERNARY_OP_H
+
+namespace Eigen {
+
+namespace internal {
+template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
+struct traits<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> > {
+  // we must not inherit from traits<Arg1> since it has
+  // the potential to cause problems with MSVC
+  typedef typename remove_all<Arg1>::type Ancestor;
+  typedef typename traits<Ancestor>::XprKind XprKind;
+  enum {
+    RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
+    ColsAtCompileTime = traits<Ancestor>::ColsAtCompileTime,
+    MaxRowsAtCompileTime = traits<Ancestor>::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = traits<Ancestor>::MaxColsAtCompileTime
+  };
+
+  // even though we require Arg1, Arg2, and Arg3 to have the same scalar type
+  // (see CwiseTernaryOp constructor),
+  // we still want to handle the case when the result type is different.
+  typedef typename result_of<TernaryOp(
+      const typename Arg1::Scalar&, const typename Arg2::Scalar&,
+      const typename Arg3::Scalar&)>::type Scalar;
+
+  typedef typename internal::traits<Arg1>::StorageKind StorageKind;
+  typedef typename internal::traits<Arg1>::StorageIndex StorageIndex;
+
+  typedef typename Arg1::Nested Arg1Nested;
+  typedef typename Arg2::Nested Arg2Nested;
+  typedef typename Arg3::Nested Arg3Nested;
+  typedef typename remove_reference<Arg1Nested>::type _Arg1Nested;
+  typedef typename remove_reference<Arg2Nested>::type _Arg2Nested;
+  typedef typename remove_reference<Arg3Nested>::type _Arg3Nested;
+  enum { Flags = _Arg1Nested::Flags & RowMajorBit };
+};
+}  // end namespace internal
+
+template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3,
+          typename StorageKind>
+class CwiseTernaryOpImpl;
+
+/** \class CwiseTernaryOp
+  * \ingroup Core_Module
+  *
+  * \brief Generic expression where a coefficient-wise ternary operator is
+ * applied to two expressions
+  *
+  * \tparam TernaryOp template functor implementing the operator
+  * \tparam Arg1Type the type of the first argument
+  * \tparam Arg2Type the type of the second argument
+  * \tparam Arg3Type the type of the third argument
+  *
+  * This class represents an expression where a coefficient-wise ternary
+ * operator is applied to three expressions.
+  * It is the return type of ternary operators, by which we mean only those
+ * ternary operators where
+  * all three arguments are Eigen expressions.
+  * For example, the return type of betainc(matrix1, matrix2, matrix3) is a
+ * CwiseTernaryOp.
+  *
+  * Most of the time, this is the only way that it is used, so you typically
+ * don't have to name
+  * CwiseTernaryOp types explicitly.
+  *
+  * \sa MatrixBase::ternaryExpr(const MatrixBase<Argument2> &, const
+ * MatrixBase<Argument3> &, const CustomTernaryOp &) const, class CwiseBinaryOp,
+ * class CwiseUnaryOp, class CwiseNullaryOp
+  */
+template <typename TernaryOp, typename Arg1Type, typename Arg2Type,
+          typename Arg3Type>
+class CwiseTernaryOp : public CwiseTernaryOpImpl<
+                           TernaryOp, Arg1Type, Arg2Type, Arg3Type,
+                           typename internal::traits<Arg1Type>::StorageKind>,
+                       internal::no_assignment_operator
+{
+ public:
+  typedef typename internal::remove_all<Arg1Type>::type Arg1;
+  typedef typename internal::remove_all<Arg2Type>::type Arg2;
+  typedef typename internal::remove_all<Arg3Type>::type Arg3;
+
+  typedef typename CwiseTernaryOpImpl<
+      TernaryOp, Arg1Type, Arg2Type, Arg3Type,
+      typename internal::traits<Arg1Type>::StorageKind>::Base Base;
+  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseTernaryOp)
+
+  typedef typename internal::ref_selector<Arg1Type>::type Arg1Nested;
+  typedef typename internal::ref_selector<Arg2Type>::type Arg2Nested;
+  typedef typename internal::ref_selector<Arg3Type>::type Arg3Nested;
+  typedef typename internal::remove_reference<Arg1Nested>::type _Arg1Nested;
+  typedef typename internal::remove_reference<Arg2Nested>::type _Arg2Nested;
+  typedef typename internal::remove_reference<Arg3Nested>::type _Arg3Nested;
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE CwiseTernaryOp(const Arg1& a1, const Arg2& a2,
+                                     const Arg3& a3,
+                                     const TernaryOp& func = TernaryOp())
+      : m_arg1(a1), m_arg2(a2), m_arg3(a3), m_functor(func) {
+    // require the sizes to match
+    EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg2)
+    EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg3)
+
+    // The index types should match
+    EIGEN_STATIC_ASSERT((internal::is_same<
+                         typename internal::traits<Arg1Type>::StorageKind,
+                         typename internal::traits<Arg2Type>::StorageKind>::value),
+                        STORAGE_KIND_MUST_MATCH)
+    EIGEN_STATIC_ASSERT((internal::is_same<
+                         typename internal::traits<Arg1Type>::StorageKind,
+                         typename internal::traits<Arg3Type>::StorageKind>::value),
+                        STORAGE_KIND_MUST_MATCH)
+
+    eigen_assert(a1.rows() == a2.rows() && a1.cols() == a2.cols() &&
+                 a1.rows() == a3.rows() && a1.cols() == a3.cols());
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE Index rows() const {
+    // return the fixed size type if available to enable compile time
+    // optimizations
+    if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
+                RowsAtCompileTime == Dynamic &&
+        internal::traits<typename internal::remove_all<Arg2Nested>::type>::
+                RowsAtCompileTime == Dynamic)
+      return m_arg3.rows();
+    else if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
+                     RowsAtCompileTime == Dynamic &&
+             internal::traits<typename internal::remove_all<Arg3Nested>::type>::
+                     RowsAtCompileTime == Dynamic)
+      return m_arg2.rows();
+    else
+      return m_arg1.rows();
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE Index cols() const {
+    // return the fixed size type if available to enable compile time
+    // optimizations
+    if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
+                ColsAtCompileTime == Dynamic &&
+        internal::traits<typename internal::remove_all<Arg2Nested>::type>::
+                ColsAtCompileTime == Dynamic)
+      return m_arg3.cols();
+    else if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
+                     ColsAtCompileTime == Dynamic &&
+             internal::traits<typename internal::remove_all<Arg3Nested>::type>::
+                     ColsAtCompileTime == Dynamic)
+      return m_arg2.cols();
+    else
+      return m_arg1.cols();
+  }
+
+  /** \returns the first argument nested expression */
+  EIGEN_DEVICE_FUNC
+  const _Arg1Nested& arg1() const { return m_arg1; }
+  /** \returns the first argument nested expression */
+  EIGEN_DEVICE_FUNC
+  const _Arg2Nested& arg2() const { return m_arg2; }
+  /** \returns the third argument nested expression */
+  EIGEN_DEVICE_FUNC
+  const _Arg3Nested& arg3() const { return m_arg3; }
+  /** \returns the functor representing the ternary operation */
+  EIGEN_DEVICE_FUNC
+  const TernaryOp& functor() const { return m_functor; }
+
+ protected:
+  Arg1Nested m_arg1;
+  Arg2Nested m_arg2;
+  Arg3Nested m_arg3;
+  const TernaryOp m_functor;
+};
+
+// Generic API dispatcher
+template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3,
+          typename StorageKind>
+class CwiseTernaryOpImpl
+    : public internal::generic_xpr_base<
+          CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> >::type {
+ public:
+  typedef typename internal::generic_xpr_base<
+      CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> >::type Base;
+};
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_CWISE_TERNARY_OP_H

Index: 3rd_party/eigen/Eigen/src/Core/CwiseUnaryOp.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CwiseUnaryOp.h
+++ 3rd_party/eigen/Eigen/src/Core/CwiseUnaryOp.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -11,17 +11,36 @@
 #ifndef EIGEN_CWISE_UNARY_OP_H
 #define EIGEN_CWISE_UNARY_OP_H
 
 namespace Eigen { 
 
+namespace internal {
+template<typename UnaryOp, typename XprType>
+struct traits<CwiseUnaryOp<UnaryOp, XprType> >
+ : traits<XprType>
+{
+  typedef typename result_of<
+                     UnaryOp(const typename XprType::Scalar&)
+                   >::type Scalar;
+  typedef typename XprType::Nested XprTypeNested;
+  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
+  enum {
+    Flags = _XprTypeNested::Flags & RowMajorBit 
+  };
+};
+}
+
+template<typename UnaryOp, typename XprType, typename StorageKind>
+class CwiseUnaryOpImpl;
+
 /** \class CwiseUnaryOp
   * \ingroup Core_Module
   *
   * \brief Generic expression where a coefficient-wise unary operator is applied to an expression
   *
-  * \param UnaryOp template functor implementing the operator
-  * \param XprType the type of the expression to which we are applying the unary operator
+  * \tparam UnaryOp template functor implementing the operator
+  * \tparam XprType the type of the expression to which we are applying the unary operator
   *
   * This class represents an expression where a unary operator is applied to an expression.
   * It is the return type of all operations taking exactly 1 input expression, regardless of the
   * presence of other inputs such as scalars. For example, the operator* in the expression 3*matrix
   * is considered unary, because only the right-hand side is an expression, and its
@@ -30,97 +49,55 @@
   * Most of the time, this is the only way that it is used, so you typically don't have to name
   * CwiseUnaryOp types explicitly.
   *
   * \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp
   */
-
-namespace internal {
-template<typename UnaryOp, typename XprType>
-struct traits<CwiseUnaryOp<UnaryOp, XprType> >
- : traits<XprType>
-{
-  typedef typename result_of<
-                     UnaryOp(typename XprType::Scalar)
-                   >::type Scalar;
-  typedef typename XprType::Nested XprTypeNested;
-  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
-  enum {
-    Flags = _XprTypeNested::Flags & (
-      HereditaryBits | LinearAccessBit | AlignedBit
-      | (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
-    CoeffReadCost = _XprTypeNested::CoeffReadCost + functor_traits<UnaryOp>::Cost
-  };
-};
-}
-
-template<typename UnaryOp, typename XprType, typename StorageKind>
-class CwiseUnaryOpImpl;
-
-template<typename UnaryOp, typename XprType>
-class CwiseUnaryOp : internal::no_assignment_operator,
-  public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>
+template<typename UnaryOp, typename XprType>
+class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
 {
   public:
 
     typedef typename CwiseUnaryOpImpl<UnaryOp, XprType,typename internal::traits<XprType>::StorageKind>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
+    typedef typename internal::ref_selector<XprType>::type XprTypeNested;
+    typedef typename internal::remove_all<XprType>::type NestedExpression;
 
-    inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    explicit CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
       : m_xpr(xpr), m_functor(func) {}
 
-    EIGEN_STRONG_INLINE Index rows() const { return m_xpr.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return m_xpr.cols(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Index rows() const { return m_xpr.rows(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Index cols() const { return m_xpr.cols(); }
 
     /** \returns the functor representing the unary operation */
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     const UnaryOp& functor() const { return m_functor; }
 
     /** \returns the nested expression */
-    const typename internal::remove_all<typename XprType::Nested>::type&
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const typename internal::remove_all<XprTypeNested>::type&
     nestedExpression() const { return m_xpr; }
 
     /** \returns the nested expression */
-    typename internal::remove_all<typename XprType::Nested>::type&
-    nestedExpression() { return m_xpr.const_cast_derived(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    typename internal::remove_all<XprTypeNested>::type&
+    nestedExpression() { return m_xpr; }
 
   protected:
-    typename XprType::Nested m_xpr;
+    XprTypeNested m_xpr;
     const UnaryOp m_functor;
 };
 
-// This is the generic implementation for dense storage.
-// It can be used for any expression types implementing the dense concept.
-template<typename UnaryOp, typename XprType>
-class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
-  : public internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
-{
-  public:
-
-    typedef CwiseUnaryOp<UnaryOp, XprType> Derived;
-    typedef typename internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
-
-    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
-    {
-      return derived().functor()(derived().nestedExpression().coeff(rowId, colId));
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
-    {
-      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(rowId, colId));
-    }
-
-    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
-    {
-      return derived().functor()(derived().nestedExpression().coeff(index));
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
-    {
-      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(index));
-    }
+// Generic API dispatcher
+template<typename UnaryOp, typename XprType, typename StorageKind>
+class CwiseUnaryOpImpl
+  : public internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
+{
+public:
+  typedef typename internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_CWISE_UNARY_OP_H

Index: 3rd_party/eigen/Eigen/src/Core/CwiseUnaryView.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/CwiseUnaryView.h
+++ 3rd_party/eigen/Eigen/src/Core/CwiseUnaryView.h
@@ -10,37 +10,23 @@
 #ifndef EIGEN_CWISE_UNARY_VIEW_H
 #define EIGEN_CWISE_UNARY_VIEW_H
 
 namespace Eigen {
 
-/** \class CwiseUnaryView
-  * \ingroup Core_Module
-  *
-  * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector
-  *
-  * \param ViewOp template functor implementing the view
-  * \param MatrixType the type of the matrix we are applying the unary operator
-  *
-  * This class represents a lvalue expression of a generic unary view operator of a matrix or a vector.
-  * It is the return type of real() and imag(), and most of the time this is the only way it is used.
-  *
-  * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp
-  */
-
 namespace internal {
 template<typename ViewOp, typename MatrixType>
 struct traits<CwiseUnaryView<ViewOp, MatrixType> >
  : traits<MatrixType>
 {
   typedef typename result_of<
-                     ViewOp(typename traits<MatrixType>::Scalar)
+                     ViewOp(const typename traits<MatrixType>::Scalar&)
                    >::type Scalar;
   typedef typename MatrixType::Nested MatrixTypeNested;
   typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
-    Flags = (traits<_MatrixTypeNested>::Flags & (HereditaryBits | LvalueBit | LinearAccessBit | DirectAccessBit)),
-    CoeffReadCost = traits<_MatrixTypeNested>::CoeffReadCost + functor_traits<ViewOp>::Cost,
+    FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
+    Flags = traits<_MatrixTypeNested>::Flags & (RowMajorBit | FlagsLvalueBit | DirectAccessBit), // FIXME DirectAccessBit should not be handled by expressions
     MatrixTypeInnerStride =  inner_stride_at_compile_time<MatrixType>::ret,
     // need to cast the sizeof's from size_t to int explicitly, otherwise:
     // "error: no integral type can represent all of the enumerator values
     InnerStrideAtCompileTime = MatrixTypeInnerStride == Dynamic
                              ? int(Dynamic)
@@ -53,19 +39,34 @@
 }
 
 template<typename ViewOp, typename MatrixType, typename StorageKind>
 class CwiseUnaryViewImpl;
 
+/** \class CwiseUnaryView
+  * \ingroup Core_Module
+  *
+  * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector
+  *
+  * \tparam ViewOp template functor implementing the view
+  * \tparam MatrixType the type of the matrix we are applying the unary operator
+  *
+  * This class represents a lvalue expression of a generic unary view operator of a matrix or a vector.
+  * It is the return type of real() and imag(), and most of the time this is the only way it is used.
+  *
+  * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp
+  */
 template<typename ViewOp, typename MatrixType>
 class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
 {
   public:
 
     typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
+    typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;
+    typedef typename internal::remove_all<MatrixType>::type NestedExpression;
 
-    inline CwiseUnaryView(const MatrixType& mat, const ViewOp& func = ViewOp())
+    explicit inline CwiseUnaryView(MatrixType& mat, const ViewOp& func = ViewOp())
       : m_matrix(mat), m_functor(func) {}
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
 
     EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
@@ -73,22 +74,30 @@
 
     /** \returns the functor representing unary operation */
     const ViewOp& functor() const { return m_functor; }
 
     /** \returns the nested expression */
-    const typename internal::remove_all<typename MatrixType::Nested>::type&
+    const typename internal::remove_all<MatrixTypeNested>::type&
     nestedExpression() const { return m_matrix; }
 
     /** \returns the nested expression */
-    typename internal::remove_all<typename MatrixType::Nested>::type&
+    typename internal::remove_reference<MatrixTypeNested>::type&
     nestedExpression() { return m_matrix.const_cast_derived(); }
 
   protected:
-    // FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC
-    typename internal::nested<MatrixType>::type m_matrix;
+    MatrixTypeNested m_matrix;
     ViewOp m_functor;
 };
+
+// Generic API dispatcher
+template<typename ViewOp, typename XprType, typename StorageKind>
+class CwiseUnaryViewImpl
+  : public internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type
+{
+public:
+  typedef typename internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type Base;
+};
 
 template<typename ViewOp, typename MatrixType>
 class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
   : public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
 {
@@ -98,42 +107,22 @@
     typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base;
 
     EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
     
-    inline Scalar* data() { return &coeffRef(0); }
-    inline const Scalar* data() const { return &coeff(0); }
+    EIGEN_DEVICE_FUNC inline Scalar* data() { return &(this->coeffRef(0)); }
+    EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(this->coeff(0)); }
 
-    inline Index innerStride() const
+    EIGEN_DEVICE_FUNC inline Index innerStride() const
     {
       return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
     }
 
-    inline Index outerStride() const
+    EIGEN_DEVICE_FUNC inline Index outerStride() const
     {
       return derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
     }
-
-    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
-    {
-      return derived().functor()(derived().nestedExpression().coeff(row, col));
-    }
-
-    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
-    {
-      return derived().functor()(derived().nestedExpression().coeff(index));
-    }
-
-    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
-    {
-      return derived().functor()(const_cast_derived().nestedExpression().coeffRef(row, col));
-    }
-
-    EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
-    {
-      return derived().functor()(const_cast_derived().nestedExpression().coeffRef(index));
-    }
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_CWISE_UNARY_VIEW_H

Index: 3rd_party/eigen/Eigen/src/Core/DenseBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/DenseBase.h
+++ 3rd_party/eigen/Eigen/src/Core/DenseBase.h
@@ -32,60 +32,58 @@
   * and related expression types). The common Eigen API for dense objects is contained in this class.
   *
   * \tparam Derived is the derived type, e.g., a matrix type or an expression.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_DENSEBASE_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_DENSEBASE_PLUGIN.
   *
-  * \sa \ref TopicClassHierarchy
+  * \sa \blank \ref TopicClassHierarchy
   */
 template<typename Derived> class DenseBase
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-  : public internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
-                                     typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>
+  : public DenseCoeffsBase<Derived>
 #else
-  : public DenseCoeffsBase<Derived>
+  : public DenseCoeffsBase<Derived,DirectWriteAccessors>
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 {
   public:
-    using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
-                typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
 
-    class InnerIterator;
+    /** Inner iterator type to iterate over the coefficients of a row or column.
+      * \sa class InnerIterator
+      */
+    typedef Eigen::InnerIterator<Derived> InnerIterator;
 
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
 
-    /** \brief The type of indices 
-      * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
-      * \sa \ref TopicPreprocessorDirectives.
-      */
-    typedef typename internal::traits<Derived>::Index Index; 
+    /**
+      * \brief The type used to store indices
+      * \details This typedef is relevant for types that store multiple indices such as
+      *          PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index
+      * \sa \blank \ref TopicPreprocessorDirectives, Eigen::Index, SparseMatrixBase.
+     */
+    typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
 
+    /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc. */
     typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
+    
+    /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
+      *
+      * It is an alias for the Scalar type */
+    typedef Scalar value_type;
+    
     typedef typename NumTraits<Scalar>::Real RealScalar;
-
     typedef DenseCoeffsBase<Derived> Base;
+
     using Base::derived;
     using Base::const_cast_derived;
     using Base::rows;
     using Base::cols;
     using Base::size;
     using Base::rowIndexByOuterInner;
     using Base::colIndexByOuterInner;
     using Base::coeff;
     using Base::coeffByOuterInner;
-    using Base::packet;
-    using Base::packetByOuterInner;
-    using Base::writePacket;
-    using Base::writePacketByOuterInner;
-    using Base::coeffRef;
-    using Base::coeffRefByOuterInner;
-    using Base::copyCoeff;
-    using Base::copyCoeffByOuterInner;
-    using Base::copyPacket;
-    using Base::copyPacketByOuterInner;
     using Base::operator();
     using Base::operator[];
     using Base::x;
     using Base::y;
     using Base::z;
@@ -167,34 +165,58 @@
       IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */
 
       InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
                              : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
 
-      CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
-        /**< This is a rough measure of how expensive it is to read one coefficient from
-          * this expression.
-          */
-
       InnerStrideAtCompileTime = internal::inner_stride_at_compile_time<Derived>::ret,
       OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret
     };
+    
+    typedef typename internal::find_best_packet<Scalar,SizeAtCompileTime>::type PacketScalar;
+
+    enum { IsPlainObjectBase = 0 };
+    
+    /** The plain matrix type corresponding to this expression.
+      * \sa PlainObject */
+    typedef Matrix<typename internal::traits<Derived>::Scalar,
+                internal::traits<Derived>::RowsAtCompileTime,
+                internal::traits<Derived>::ColsAtCompileTime,
+                AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
+                internal::traits<Derived>::MaxRowsAtCompileTime,
+                internal::traits<Derived>::MaxColsAtCompileTime
+          > PlainMatrix;
+    
+    /** The plain array type corresponding to this expression.
+      * \sa PlainObject */
+    typedef Array<typename internal::traits<Derived>::Scalar,
+                internal::traits<Derived>::RowsAtCompileTime,
+                internal::traits<Derived>::ColsAtCompileTime,
+                AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
+                internal::traits<Derived>::MaxRowsAtCompileTime,
+                internal::traits<Derived>::MaxColsAtCompileTime
+          > PlainArray;
 
-    enum { ThisConstantIsPrivateInPlainObjectBase };
+    /** \brief The plain matrix or array type corresponding to this expression.
+      *
+      * This is not necessarily exactly the return type of eval(). In the case of plain matrices,
+      * the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed
+      * that the return type of eval() is either PlainObject or const PlainObject&.
+      */
+    typedef typename internal::conditional<internal::is_same<typename internal::traits<Derived>::XprKind,MatrixXpr >::value,
+                                 PlainMatrix, PlainArray>::type PlainObject;
 
     /** \returns the number of nonzero coefficients which is in practice the number
       * of stored coefficients. */
+    EIGEN_DEVICE_FUNC
     inline Index nonZeros() const { return size(); }
-    /** \returns true if either the number of rows or the number of columns is equal to 1.
-      * In other words, this function returns
-      * \code rows()==1 || cols()==1 \endcode
-      * \sa rows(), cols(), IsVectorAtCompileTime. */
 
     /** \returns the outer size.
       *
       * \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension
       * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of columns for a
       * column-major matrix, and the number of rows for a row-major matrix. */
+    EIGEN_DEVICE_FUNC
     Index outerSize() const
     {
       return IsVectorAtCompileTime ? 1
            : int(IsRowMajor) ? this->rows() : this->cols();
     }
@@ -202,10 +224,11 @@
     /** \returns the inner size.
       *
       * \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension
       * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of rows for a 
       * column-major matrix, and the number of columns for a row-major matrix. */
+    EIGEN_DEVICE_FUNC
     Index innerSize() const
     {
       return IsVectorAtCompileTime ? this->size()
            : int(IsRowMajor) ? this->cols() : this->rows();
     }
@@ -212,10 +235,11 @@
 
     /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
       * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
       * nothing else.
       */
+    EIGEN_DEVICE_FUNC
     void resize(Index newSize)
     {
       EIGEN_ONLY_USED_FOR_DEBUG(newSize);
       eigen_assert(newSize == this->size()
                 && "DenseBase::resize() does not actually allow to resize.");
@@ -222,231 +246,284 @@
     }
     /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
       * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
       * nothing else.
       */
-    void resize(Index nbRows, Index nbCols)
+    EIGEN_DEVICE_FUNC
+    void resize(Index rows, Index cols)
     {
-      EIGEN_ONLY_USED_FOR_DEBUG(nbRows);
-      EIGEN_ONLY_USED_FOR_DEBUG(nbCols);
-      eigen_assert(nbRows == this->rows() && nbCols == this->cols()
+      EIGEN_ONLY_USED_FOR_DEBUG(rows);
+      EIGEN_ONLY_USED_FOR_DEBUG(cols);
+      eigen_assert(rows == this->rows() && cols == this->cols()
                 && "DenseBase::resize() does not actually allow to resize.");
     }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-
     /** \internal Represents a matrix with all coefficients equal to one another*/
-    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
-    /** \internal Represents a vector with linearly spaced coefficients that allows sequential access only. */
-    typedef CwiseNullaryOp<internal::linspaced_op<Scalar,false>,Derived> SequentialLinSpacedReturnType;
+    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
+    /** \internal \deprecated Represents a vector with linearly spaced coefficients that allows sequential access only. */
+    typedef CwiseNullaryOp<internal::linspaced_op<Scalar,PacketScalar>,PlainObject> SequentialLinSpacedReturnType;
     /** \internal Represents a vector with linearly spaced coefficients that allows random access. */
-    typedef CwiseNullaryOp<internal::linspaced_op<Scalar,true>,Derived> RandomAccessLinSpacedReturnType;
+    typedef CwiseNullaryOp<internal::linspaced_op<Scalar,PacketScalar>,PlainObject> RandomAccessLinSpacedReturnType;
     /** \internal the return type of MatrixBase::eigenvalues() */
     typedef Matrix<typename NumTraits<typename internal::traits<Derived>::Scalar>::Real, internal::traits<Derived>::ColsAtCompileTime, 1> EigenvaluesReturnType;
 
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
     /** Copies \a other into *this. \returns a reference to *this. */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator=(const DenseBase<OtherDerived>& other);
 
     /** Special case of the template operator=, in order to prevent the compiler
       * from generating a default operator= (issue hit with g++ 4.1)
       */
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator=(const DenseBase& other);
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     Derived& operator=(const EigenBase<OtherDerived> &other);
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     Derived& operator+=(const EigenBase<OtherDerived> &other);
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     Derived& operator-=(const EigenBase<OtherDerived> &other);
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     Derived& operator=(const ReturnByValue<OtherDerived>& func);
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** Copies \a other into *this without evaluating other. \returns a reference to *this. */
+    /** \internal
+      * Copies \a other into *this without evaluating other. \returns a reference to *this.
+      * \deprecated */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     Derived& lazyAssign(const DenseBase<OtherDerived>& other);
-#endif // not EIGEN_PARSED_BY_DOXYGEN
 
+    EIGEN_DEVICE_FUNC
     CommaInitializer<Derived> operator<< (const Scalar& s);
 
+    /** \deprecated it now returns \c *this */
     template<unsigned int Added,unsigned int Removed>
-    const Flagged<Derived, Added, Removed> flagged() const;
+    EIGEN_DEPRECATED
+    const Derived& flagged() const
+    { return derived(); }
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     CommaInitializer<Derived> operator<< (const DenseBase<OtherDerived>& other);
 
-    Eigen::Transpose<Derived> transpose();
-	typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
+    typedef Transpose<Derived> TransposeReturnType;
+    EIGEN_DEVICE_FUNC
+    TransposeReturnType transpose();
+    typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
+    EIGEN_DEVICE_FUNC
     ConstTransposeReturnType transpose() const;
+    EIGEN_DEVICE_FUNC
     void transposeInPlace();
-#ifndef EIGEN_NO_DEBUG
-  protected:
-    template<typename OtherDerived>
-    void checkTransposeAliasing(const OtherDerived& other) const;
-  public:
-#endif
-
-
-    static const ConstantReturnType
+
+    EIGEN_DEVICE_FUNC static const ConstantReturnType
     Constant(Index rows, Index cols, const Scalar& value);
-    static const ConstantReturnType
+    EIGEN_DEVICE_FUNC static const ConstantReturnType
     Constant(Index size, const Scalar& value);
-    static const ConstantReturnType
+    EIGEN_DEVICE_FUNC static const ConstantReturnType
     Constant(const Scalar& value);
 
-    static const SequentialLinSpacedReturnType
+    EIGEN_DEVICE_FUNC static const SequentialLinSpacedReturnType
     LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high);
-    static const RandomAccessLinSpacedReturnType
+    EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType
     LinSpaced(Index size, const Scalar& low, const Scalar& high);
-    static const SequentialLinSpacedReturnType
+    EIGEN_DEVICE_FUNC static const SequentialLinSpacedReturnType
     LinSpaced(Sequential_t, const Scalar& low, const Scalar& high);
-    static const RandomAccessLinSpacedReturnType
+    EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType
     LinSpaced(const Scalar& low, const Scalar& high);
 
-    template<typename CustomNullaryOp>
-    static const CwiseNullaryOp<CustomNullaryOp, Derived>
+    template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
+    static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
     NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func);
-    template<typename CustomNullaryOp>
-    static const CwiseNullaryOp<CustomNullaryOp, Derived>
+    template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
+    static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
     NullaryExpr(Index size, const CustomNullaryOp& func);
-    template<typename CustomNullaryOp>
-    static const CwiseNullaryOp<CustomNullaryOp, Derived>
+    template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
+    static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
     NullaryExpr(const CustomNullaryOp& func);
 
-    static const ConstantReturnType Zero(Index rows, Index cols);
-    static const ConstantReturnType Zero(Index size);
-    static const ConstantReturnType Zero();
-    static const ConstantReturnType Ones(Index rows, Index cols);
-    static const ConstantReturnType Ones(Index size);
-    static const ConstantReturnType Ones();
-
-    void fill(const Scalar& value);
-    Derived& setConstant(const Scalar& value);
-    Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
-    Derived& setLinSpaced(const Scalar& low, const Scalar& high);
-    Derived& setZero();
-    Derived& setOnes();
-    Derived& setRandom();
-
-    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index rows, Index cols);
+    EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index size);
+    EIGEN_DEVICE_FUNC static const ConstantReturnType Zero();
+    EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index rows, Index cols);
+    EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index size);
+    EIGEN_DEVICE_FUNC static const ConstantReturnType Ones();
+
+    EIGEN_DEVICE_FUNC void fill(const Scalar& value);
+    EIGEN_DEVICE_FUNC Derived& setConstant(const Scalar& value);
+    EIGEN_DEVICE_FUNC Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
+    EIGEN_DEVICE_FUNC Derived& setLinSpaced(const Scalar& low, const Scalar& high);
+    EIGEN_DEVICE_FUNC Derived& setZero();
+    EIGEN_DEVICE_FUNC Derived& setOnes();
+    EIGEN_DEVICE_FUNC Derived& setRandom();
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC
     bool isApprox(const DenseBase<OtherDerived>& other,
                   const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    EIGEN_DEVICE_FUNC 
     bool isMuchSmallerThan(const RealScalar& other,
                            const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    template<typename OtherDerived>
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC
     bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
                            const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
-    bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    EIGEN_DEVICE_FUNC bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    EIGEN_DEVICE_FUNC bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    EIGEN_DEVICE_FUNC bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    EIGEN_DEVICE_FUNC bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
     
     inline bool hasNaN() const;
     inline bool allFinite() const;
 
-    inline Derived& operator*=(const Scalar& other);
-    inline Derived& operator/=(const Scalar& other);
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator*=(const Scalar& other);
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator/=(const Scalar& other);
 
     typedef typename internal::add_const_on_value_type<typename internal::eval<Derived>::type>::type EvalReturnType;
     /** \returns the matrix or vector obtained by evaluating this expression.
       *
       * Notice that in the case of a plain matrix or vector (not an expression) this function just returns
       * a const reference, in order to avoid a useless copy.
+      * 
+      * \warning Be carefull with eval() and the auto C++ keyword, as detailed in this \link TopicPitfalls_auto_keyword page \endlink.
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE EvalReturnType eval() const
     {
       // Even though MSVC does not honor strong inlining when the return type
       // is a dynamic matrix, we desperately need strong inlining for fixed
       // size types on MSVC.
       return typename internal::eval<Derived>::type(derived());
     }
-
+    
     /** swaps *this with the expression \a other.
       *
       */
     template<typename OtherDerived>
-    void swap(const DenseBase<OtherDerived>& other,
-              int = OtherDerived::ThisConstantIsPrivateInPlainObjectBase)
+    EIGEN_DEVICE_FUNC
+    void swap(const DenseBase<OtherDerived>& other)
     {
-      SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
+      EIGEN_STATIC_ASSERT(!OtherDerived::IsPlainObjectBase,THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
+      eigen_assert(rows()==other.rows() && cols()==other.cols());
+      call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
     }
 
     /** swaps *this with the matrix or array \a other.
       *
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     void swap(PlainObjectBase<OtherDerived>& other)
     {
-      SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
-    }
-
-
-    inline const NestByValue<Derived> nestByValue() const;
-    inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
-    inline ForceAlignedAccess<Derived> forceAlignedAccess();
-    template<bool Enable> inline const typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf() const;
-    template<bool Enable> inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
-
-    Scalar sum() const;
-    Scalar mean() const;
-    Scalar trace() const;
-
-    Scalar prod() const;
-
-    typename internal::traits<Derived>::Scalar minCoeff() const;
-    typename internal::traits<Derived>::Scalar maxCoeff() const;
-
-    template<typename IndexType>
+      eigen_assert(rows()==other.rows() && cols()==other.cols());
+      call_assignment(derived(), other.derived(), internal::swap_assign_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC inline const NestByValue<Derived> nestByValue() const;
+    EIGEN_DEVICE_FUNC inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
+    EIGEN_DEVICE_FUNC inline ForceAlignedAccess<Derived> forceAlignedAccess();
+    template<bool Enable> EIGEN_DEVICE_FUNC
+    inline const typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf() const;
+    template<bool Enable> EIGEN_DEVICE_FUNC
+    inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
+
+    EIGEN_DEVICE_FUNC Scalar sum() const;
+    EIGEN_DEVICE_FUNC Scalar mean() const;
+    EIGEN_DEVICE_FUNC Scalar trace() const;
+
+    EIGEN_DEVICE_FUNC Scalar prod() const;
+
+    EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff() const;
+    EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff() const;
+
+    template<typename IndexType> EIGEN_DEVICE_FUNC
     typename internal::traits<Derived>::Scalar minCoeff(IndexType* row, IndexType* col) const;
-    template<typename IndexType>
+    template<typename IndexType> EIGEN_DEVICE_FUNC
     typename internal::traits<Derived>::Scalar maxCoeff(IndexType* row, IndexType* col) const;
-    template<typename IndexType>
+    template<typename IndexType> EIGEN_DEVICE_FUNC
     typename internal::traits<Derived>::Scalar minCoeff(IndexType* index) const;
-    template<typename IndexType>
+    template<typename IndexType> EIGEN_DEVICE_FUNC
     typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const;
 
     template<typename BinaryOp>
-    typename internal::result_of<BinaryOp(typename internal::traits<Derived>::Scalar)>::type
-    redux(const BinaryOp& func) const;
+    EIGEN_DEVICE_FUNC
+    Scalar redux(const BinaryOp& func) const;
 
     template<typename Visitor>
+    EIGEN_DEVICE_FUNC
     void visit(Visitor& func) const;
 
-    inline const WithFormat<Derived> format(const IOFormat& fmt) const;
+    /** \returns a WithFormat proxy object allowing to print a matrix the with given
+      * format \a fmt.
+      *
+      * See class IOFormat for some examples.
+      *
+      * \sa class IOFormat, class WithFormat
+      */
+    inline const WithFormat<Derived> format(const IOFormat& fmt) const
+    {
+      return WithFormat<Derived>(derived(), fmt);
+    }
 
     /** \returns the unique coefficient of a 1x1 expression */
+    EIGEN_DEVICE_FUNC
     CoeffReturnType value() const
     {
       EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
       eigen_assert(this->rows() == 1 && this->cols() == 1);
       return derived().coeff(0,0);
     }
 
-    bool all(void) const;
-    bool any(void) const;
-    Index count() const;
+    EIGEN_DEVICE_FUNC bool all() const;
+    EIGEN_DEVICE_FUNC bool any() const;
+    EIGEN_DEVICE_FUNC Index count() const;
 
     typedef VectorwiseOp<Derived, Horizontal> RowwiseReturnType;
     typedef const VectorwiseOp<const Derived, Horizontal> ConstRowwiseReturnType;
     typedef VectorwiseOp<Derived, Vertical> ColwiseReturnType;
     typedef const VectorwiseOp<const Derived, Vertical> ConstColwiseReturnType;
 
-    ConstRowwiseReturnType rowwise() const;
-    RowwiseReturnType rowwise();
-    ConstColwiseReturnType colwise() const;
-    ColwiseReturnType colwise();
-
-    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(Index rows, Index cols);
-    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(Index size);
-    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random();
+    /** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
+    *
+    * Example: \include MatrixBase_rowwise.cpp
+    * Output: \verbinclude MatrixBase_rowwise.out
+    *
+    * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
+    */
+    //Code moved here due to a CUDA compiler bug
+    EIGEN_DEVICE_FUNC inline ConstRowwiseReturnType rowwise() const {
+      return ConstRowwiseReturnType(derived());
+    }
+    EIGEN_DEVICE_FUNC RowwiseReturnType rowwise();
+
+    /** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
+    *
+    * Example: \include MatrixBase_colwise.cpp
+    * Output: \verbinclude MatrixBase_colwise.out
+    *
+    * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
+    */
+    EIGEN_DEVICE_FUNC inline ConstColwiseReturnType colwise() const {
+      return ConstColwiseReturnType(derived());
+    }
+    EIGEN_DEVICE_FUNC ColwiseReturnType colwise();
+
+    typedef CwiseNullaryOp<internal::scalar_random_op<Scalar>,PlainObject> RandomReturnType;
+    static const RandomReturnType Random(Index rows, Index cols);
+    static const RandomReturnType Random(Index size);
+    static const RandomReturnType Random();
 
     template<typename ThenDerived,typename ElseDerived>
     const Select<Derived,ThenDerived,ElseDerived>
     select(const DenseBase<ThenDerived>& thenMatrix,
            const DenseBase<ElseDerived>& elseMatrix) const;
@@ -460,49 +537,60 @@
     select(const typename ElseDerived::Scalar& thenScalar, const DenseBase<ElseDerived>& elseMatrix) const;
 
     template<int p> RealScalar lpNorm() const;
 
     template<int RowFactor, int ColFactor>
-    inline const Replicate<Derived,RowFactor,ColFactor> replicate() const;
-    
-    typedef Replicate<Derived,Dynamic,Dynamic> ReplicateReturnType;
-    inline const ReplicateReturnType replicate(Index rowFacor,Index colFactor) const;
+    EIGEN_DEVICE_FUNC
+    const Replicate<Derived,RowFactor,ColFactor> replicate() const;
+    /**
+    * \return an expression of the replication of \c *this
+    *
+    * Example: \include MatrixBase_replicate_int_int.cpp
+    * Output: \verbinclude MatrixBase_replicate_int_int.out
+    *
+    * \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
+    */
+    //Code moved here due to a CUDA compiler bug
+    EIGEN_DEVICE_FUNC
+    const Replicate<Derived, Dynamic, Dynamic> replicate(Index rowFactor, Index colFactor) const
+    {
+      return Replicate<Derived, Dynamic, Dynamic>(derived(), rowFactor, colFactor);
+    }
 
     typedef Reverse<Derived, BothDirections> ReverseReturnType;
     typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;
-    ReverseReturnType reverse();
-    ConstReverseReturnType reverse() const;
-    void reverseInPlace();
+    EIGEN_DEVICE_FUNC ReverseReturnType reverse();
+    /** This is the const version of reverse(). */
+    //Code moved here due to a CUDA compiler bug
+    EIGEN_DEVICE_FUNC ConstReverseReturnType reverse() const
+    {
+      return ConstReverseReturnType(derived());
+    }
+    EIGEN_DEVICE_FUNC void reverseInPlace();
 
 #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase
+#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND)
 #   include "../plugins/BlockMethods.h"
 #   ifdef EIGEN_DENSEBASE_PLUGIN
 #     include EIGEN_DENSEBASE_PLUGIN
 #   endif
 #undef EIGEN_CURRENT_STORAGE_BASE_CLASS
-
-#ifdef EIGEN2_SUPPORT
-
-    Block<Derived> corner(CornerType type, Index cRows, Index cCols);
-    const Block<Derived> corner(CornerType type, Index cRows, Index cCols) const;
-    template<int CRows, int CCols>
-    Block<Derived, CRows, CCols> corner(CornerType type);
-    template<int CRows, int CCols>
-    const Block<Derived, CRows, CCols> corner(CornerType type) const;
-
-#endif // EIGEN2_SUPPORT
-
+#undef EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+#undef EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF
 
     // disable the use of evalTo for dense objects with a nice compilation error
-    template<typename Dest> inline void evalTo(Dest& ) const
+    template<typename Dest>
+    EIGEN_DEVICE_FUNC
+    inline void evalTo(Dest& ) const
     {
       EIGEN_STATIC_ASSERT((internal::is_same<Dest,void>::value),THE_EVAL_EVALTO_FUNCTION_SHOULD_NEVER_BE_CALLED_FOR_DENSE_OBJECTS);
     }
 
   protected:
     /** Default constructor. Do nothing. */
-    DenseBase()
+    EIGEN_DEVICE_FUNC DenseBase()
     {
       /* Just checks for self-consistency of the flags.
        * Only do it when debugging Eigen, as this borders on paranoiac and could slow compilation down
        */
 #ifdef EIGEN_INTERNAL_DEBUGGING
@@ -511,13 +599,13 @@
                           INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION)
 #endif
     }
 
   private:
-    explicit DenseBase(int);
-    DenseBase(int,int);
-    template<typename OtherDerived> explicit DenseBase(const DenseBase<OtherDerived>&);
+    EIGEN_DEVICE_FUNC explicit DenseBase(int);
+    EIGEN_DEVICE_FUNC DenseBase(int,int);
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC explicit DenseBase(const DenseBase<OtherDerived>&);
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_DENSEBASE_H

Index: 3rd_party/eigen/Eigen/src/Core/DenseCoeffsBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/DenseCoeffsBase.h
+++ 3rd_party/eigen/Eigen/src/Core/DenseCoeffsBase.h
@@ -33,11 +33,10 @@
 template<typename Derived>
 class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
 {
   public:
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
 
     // Explanation for this CoeffReturnType typedef.
     // - This is the return type of the coeff() method.
@@ -59,18 +58,20 @@
     using Base::rows;
     using Base::cols;
     using Base::size;
     using Base::derived;
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const
     {
       return int(Derived::RowsAtCompileTime) == 1 ? 0
           : int(Derived::ColsAtCompileTime) == 1 ? inner
           : int(Derived::Flags)&RowMajorBit ? outer
           : inner;
     }
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const
     {
       return int(Derived::ColsAtCompileTime) == 1 ? 0
           : int(Derived::RowsAtCompileTime) == 1 ? inner
           : int(Derived::Flags)&RowMajorBit ? inner
@@ -89,17 +90,19 @@
       * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
       * function equivalent to \link operator()(Index,Index) const \endlink.
       *
       * \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
     {
       eigen_internal_assert(row >= 0 && row < rows()
-                        && col >= 0 && col < cols());
-      return derived().coeff(row, col);
+                         && col >= 0 && col < cols());
+      return internal::evaluator<Derived>(derived()).coeff(row,col);
     }
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
     {
       return coeff(rowIndexByOuterInner(outer, inner),
                    colIndexByOuterInner(outer, inner));
     }
@@ -106,15 +109,16 @@
 
     /** \returns the coefficient at given the given row and column.
       *
       * \sa operator()(Index,Index), operator[](Index)
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType operator()(Index row, Index col) const
     {
       eigen_assert(row >= 0 && row < rows()
           && col >= 0 && col < cols());
-      return derived().coeff(row, col);
+      return coeff(row, col);
     }
 
     /** Short version: don't use this function, use
       * \link operator[](Index) const \endlink instead.
       *
@@ -128,15 +132,18 @@
       * function equivalent to \link operator[](Index) const \endlink.
       *
       * \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const
       */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType
     coeff(Index index) const
     {
+      EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
+                          THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
       eigen_internal_assert(index >= 0 && index < size());
-      return derived().coeff(index);
+      return internal::evaluator<Derived>(derived()).coeff(index);
     }
 
 
     /** \returns the coefficient at given index.
       *
@@ -144,19 +151,18 @@
       *
       * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
       * z() const, w() const
       */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType
     operator[](Index index) const
     {
-      #ifndef EIGEN2_SUPPORT
       EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
                           THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
-      #endif
       eigen_assert(index >= 0 && index < size());
-      return derived().coeff(index);
+      return coeff(index);
     }
 
     /** \returns the coefficient at given index.
       *
       * This is synonymous to operator[](Index) const.
@@ -165,36 +171,53 @@
       *
       * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
       * z() const, w() const
       */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType
     operator()(Index index) const
     {
       eigen_assert(index >= 0 && index < size());
-      return derived().coeff(index);
+      return coeff(index);
     }
 
     /** equivalent to operator[](0).  */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType
     x() const { return (*this)[0]; }
 
     /** equivalent to operator[](1).  */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType
-    y() const { return (*this)[1]; }
+    y() const
+    {
+      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=2, OUT_OF_RANGE_ACCESS);
+      return (*this)[1];
+    }
 
     /** equivalent to operator[](2).  */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType
-    z() const { return (*this)[2]; }
+    z() const
+    {
+      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=3, OUT_OF_RANGE_ACCESS);
+      return (*this)[2];
+    }
 
     /** equivalent to operator[](3).  */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE CoeffReturnType
-    w() const { return (*this)[3]; }
+    w() const
+    {
+      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=4, OUT_OF_RANGE_ACCESS);
+      return (*this)[3];
+    }
 
     /** \internal
       * \returns the packet of coefficients starting at the given row and column. It is your responsibility
       * to ensure that a packet really starts there. This method is only available on expressions having the
       * PacketAccessBit.
@@ -205,13 +228,13 @@
       */
 
     template<int LoadMode>
     EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const
     {
-      eigen_internal_assert(row >= 0 && row < rows()
-                      && col >= 0 && col < cols());
-      return derived().template packet<LoadMode>(row,col);
+      typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
+      eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
+      return internal::evaluator<Derived>(derived()).template packet<LoadMode,DefaultPacketType>(row,col);
     }
 
 
     /** \internal */
     template<int LoadMode>
@@ -232,12 +255,15 @@
       */
 
     template<int LoadMode>
     EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
     {
+      EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
+                          THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
+      typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
       eigen_internal_assert(index >= 0 && index < size());
-      return derived().template packet<LoadMode>(index);
+      return internal::evaluator<Derived>(derived()).template packet<LoadMode,DefaultPacketType>(index);
     }
 
   protected:
     // explanation: DenseBase is doing "using ..." on the methods from DenseCoeffsBase.
     // But some methods are only available in the DirectAccess case.
@@ -276,11 +302,10 @@
   public:
 
     typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
 
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
     using Base::coeff;
@@ -309,17 +334,19 @@
       * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
       * function equivalent to \link operator()(Index,Index) \endlink.
       *
       * \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index)
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
     {
       eigen_internal_assert(row >= 0 && row < rows()
-                        && col >= 0 && col < cols());
-      return derived().coeffRef(row, col);
+                         && col >= 0 && col < cols());
+      return internal::evaluator<Derived>(derived()).coeffRef(row,col);
     }
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
     coeffRefByOuterInner(Index outer, Index inner)
     {
       return coeffRef(rowIndexByOuterInner(outer, inner),
                       colIndexByOuterInner(outer, inner));
@@ -328,16 +355,17 @@
     /** \returns a reference to the coefficient at given the given row and column.
       *
       * \sa operator[](Index)
       */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
     operator()(Index row, Index col)
     {
       eigen_assert(row >= 0 && row < rows()
           && col >= 0 && col < cols());
-      return derived().coeffRef(row, col);
+      return coeffRef(row, col);
     }
 
 
     /** Short version: don't use this function, use
       * \link operator[](Index) \endlink instead.
@@ -352,33 +380,35 @@
       * function equivalent to \link operator[](Index) \endlink.
       *
       * \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index)
       */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
     coeffRef(Index index)
     {
+      EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
+                          THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
       eigen_internal_assert(index >= 0 && index < size());
-      return derived().coeffRef(index);
+      return internal::evaluator<Derived>(derived()).coeffRef(index);
     }
 
     /** \returns a reference to the coefficient at given index.
       *
       * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
       *
       * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
       */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
     operator[](Index index)
     {
-      #ifndef EIGEN2_SUPPORT
       EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
                           THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
-      #endif
       eigen_assert(index >= 0 && index < size());
-      return derived().coeffRef(index);
+      return coeffRef(index);
     }
 
     /** \returns a reference to the coefficient at given index.
       *
       * This is synonymous to operator[](Index).
@@ -386,171 +416,53 @@
       * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
       *
       * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
       */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
     operator()(Index index)
     {
       eigen_assert(index >= 0 && index < size());
-      return derived().coeffRef(index);
+      return coeffRef(index);
     }
 
     /** equivalent to operator[](0).  */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
     x() { return (*this)[0]; }
 
     /** equivalent to operator[](1).  */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
-    y() { return (*this)[1]; }
+    y()
+    {
+      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=2, OUT_OF_RANGE_ACCESS);
+      return (*this)[1];
+    }
 
     /** equivalent to operator[](2).  */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
-    z() { return (*this)[2]; }
+    z()
+    {
+      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=3, OUT_OF_RANGE_ACCESS);
+      return (*this)[2];
+    }
 
     /** equivalent to operator[](3).  */
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar&
-    w() { return (*this)[3]; }
-
-    /** \internal
-      * Stores the given packet of coefficients, at the given row and column of this expression. It is your responsibility
-      * to ensure that a packet really starts there. This method is only available on expressions having the
-      * PacketAccessBit.
-      *
-      * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
-      * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
-      * starting at an address which is a multiple of the packet size.
-      */
-
-    template<int StoreMode>
-    EIGEN_STRONG_INLINE void writePacket
-    (Index row, Index col, const typename internal::packet_traits<Scalar>::type& val)
-    {
-      eigen_internal_assert(row >= 0 && row < rows()
-                        && col >= 0 && col < cols());
-      derived().template writePacket<StoreMode>(row,col,val);
-    }
-
-
-    /** \internal */
-    template<int StoreMode>
-    EIGEN_STRONG_INLINE void writePacketByOuterInner
-    (Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& val)
-    {
-      writePacket<StoreMode>(rowIndexByOuterInner(outer, inner),
-                            colIndexByOuterInner(outer, inner),
-                            val);
-    }
-
-    /** \internal
-      * Stores the given packet of coefficients, at the given index in this expression. It is your responsibility
-      * to ensure that a packet really starts there. This method is only available on expressions having the
-      * PacketAccessBit and the LinearAccessBit.
-      *
-      * The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select
-      * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
-      * starting at an address which is a multiple of the packet size.
-      */
-    template<int StoreMode>
-    EIGEN_STRONG_INLINE void writePacket
-    (Index index, const typename internal::packet_traits<Scalar>::type& val)
-    {
-      eigen_internal_assert(index >= 0 && index < size());
-      derived().template writePacket<StoreMode>(index,val);
-    }
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-
-    /** \internal Copies the coefficient at position (row,col) of other into *this.
-      *
-      * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
-      * with usual assignments.
-      *
-      * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
-      */
-
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
-    {
-      eigen_internal_assert(row >= 0 && row < rows()
-                        && col >= 0 && col < cols());
-      derived().coeffRef(row, col) = other.derived().coeff(row, col);
-    }
-
-    /** \internal Copies the coefficient at the given index of other into *this.
-      *
-      * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
-      * with usual assignments.
-      *
-      * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
-      */
-
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
-    {
-      eigen_internal_assert(index >= 0 && index < size());
-      derived().coeffRef(index) = other.derived().coeff(index);
-    }
-
-
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE void copyCoeffByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
-    {
-      const Index row = rowIndexByOuterInner(outer,inner);
-      const Index col = colIndexByOuterInner(outer,inner);
-      // derived() is important here: copyCoeff() may be reimplemented in Derived!
-      derived().copyCoeff(row, col, other);
-    }
-
-    /** \internal Copies the packet at position (row,col) of other into *this.
-      *
-      * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
-      * with usual assignments.
-      *
-      * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
-      */
-
-    template<typename OtherDerived, int StoreMode, int LoadMode>
-    EIGEN_STRONG_INLINE void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
-    {
-      eigen_internal_assert(row >= 0 && row < rows()
-                        && col >= 0 && col < cols());
-      derived().template writePacket<StoreMode>(row, col,
-        other.derived().template packet<LoadMode>(row, col));
-    }
-
-    /** \internal Copies the packet at the given index of other into *this.
-      *
-      * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
-      * with usual assignments.
-      *
-      * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
-      */
-
-    template<typename OtherDerived, int StoreMode, int LoadMode>
-    EIGEN_STRONG_INLINE void copyPacket(Index index, const DenseBase<OtherDerived>& other)
-    {
-      eigen_internal_assert(index >= 0 && index < size());
-      derived().template writePacket<StoreMode>(index,
-        other.derived().template packet<LoadMode>(index));
-    }
-
-    /** \internal */
-    template<typename OtherDerived, int StoreMode, int LoadMode>
-    EIGEN_STRONG_INLINE void copyPacketByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
-    {
-      const Index row = rowIndexByOuterInner(outer,inner);
-      const Index col = colIndexByOuterInner(outer,inner);
-      // derived() is important here: copyCoeff() may be reimplemented in Derived!
-      derived().template copyPacket< OtherDerived, StoreMode, LoadMode>(row, col, other);
-    }
-#endif
-
+    w()
+    {
+      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=4, OUT_OF_RANGE_ACCESS);
+      return (*this)[3];
+    }
 };
 
 /** \brief Base class providing direct read-only coefficient access to matrices and arrays.
   * \ingroup Core_Module
   * \tparam Derived Type of the derived class
@@ -558,19 +470,92 @@
   *
   * This class defines functions to work with strides which can be used to access entries directly. This class
   * inherits DenseCoeffsBase<Derived, ReadOnlyAccessors> which defines functions to access entries read-only using
   * \c operator() .
   *
-  * \sa \ref TopicClassHierarchy
+  * \sa \blank \ref TopicClassHierarchy
   */
 template<typename Derived>
 class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
 {
   public:
 
     typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
-    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::derived;
+
+    /** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
+      *
+      * \sa outerStride(), rowStride(), colStride()
+      */
+    EIGEN_DEVICE_FUNC
+    inline Index innerStride() const
+    {
+      return derived().innerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
+      *          in a column-major matrix).
+      *
+      * \sa innerStride(), rowStride(), colStride()
+      */
+    EIGEN_DEVICE_FUNC
+    inline Index outerStride() const
+    {
+      return derived().outerStride();
+    }
+
+    // FIXME shall we remove it ?
+    inline Index stride() const
+    {
+      return Derived::IsVectorAtCompileTime ? innerStride() : outerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive rows.
+      *
+      * \sa innerStride(), outerStride(), colStride()
+      */
+    EIGEN_DEVICE_FUNC
+    inline Index rowStride() const
+    {
+      return Derived::IsRowMajor ? outerStride() : innerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive columns.
+      *
+      * \sa innerStride(), outerStride(), rowStride()
+      */
+    EIGEN_DEVICE_FUNC
+    inline Index colStride() const
+    {
+      return Derived::IsRowMajor ? innerStride() : outerStride();
+    }
+};
+
+/** \brief Base class providing direct read/write coefficient access to matrices and arrays.
+  * \ingroup Core_Module
+  * \tparam Derived Type of the derived class
+  * \tparam #DirectWriteAccessors Constant indicating direct access
+  *
+  * This class defines functions to work with strides which can be used to access entries directly. This class
+  * inherits DenseCoeffsBase<Derived, WriteAccessors> which defines functions to access entries read/write using
+  * \c operator().
+  *
+  * \sa \blank \ref TopicClassHierarchy
+  */
+template<typename Derived>
+class DenseCoeffsBase<Derived, DirectWriteAccessors>
+  : public DenseCoeffsBase<Derived, WriteAccessors>
+{
+  public:
+
+    typedef DenseCoeffsBase<Derived, WriteAccessors> Base;
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
     using Base::rows;
     using Base::cols;
@@ -579,10 +564,11 @@
 
     /** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
       *
       * \sa outerStride(), rowStride(), colStride()
       */
+    EIGEN_DEVICE_FUNC
     inline Index innerStride() const
     {
       return derived().innerStride();
     }
 
@@ -589,10 +575,11 @@
     /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
       *          in a column-major matrix).
       *
       * \sa innerStride(), rowStride(), colStride()
       */
+    EIGEN_DEVICE_FUNC
     inline Index outerStride() const
     {
       return derived().outerStride();
     }
 
@@ -604,125 +591,65 @@
 
     /** \returns the pointer increment between two consecutive rows.
       *
       * \sa innerStride(), outerStride(), colStride()
       */
+    EIGEN_DEVICE_FUNC
     inline Index rowStride() const
     {
       return Derived::IsRowMajor ? outerStride() : innerStride();
     }
 
     /** \returns the pointer increment between two consecutive columns.
       *
       * \sa innerStride(), outerStride(), rowStride()
       */
-    inline Index colStride() const
-    {
-      return Derived::IsRowMajor ? innerStride() : outerStride();
-    }
-};
-
-/** \brief Base class providing direct read/write coefficient access to matrices and arrays.
-  * \ingroup Core_Module
-  * \tparam Derived Type of the derived class
-  * \tparam #DirectWriteAccessors Constant indicating direct access
-  *
-  * This class defines functions to work with strides which can be used to access entries directly. This class
-  * inherits DenseCoeffsBase<Derived, WriteAccessors> which defines functions to access entries read/write using
-  * \c operator().
-  *
-  * \sa \ref TopicClassHierarchy
-  */
-template<typename Derived>
-class DenseCoeffsBase<Derived, DirectWriteAccessors>
-  : public DenseCoeffsBase<Derived, WriteAccessors>
-{
-  public:
-
-    typedef DenseCoeffsBase<Derived, WriteAccessors> Base;
-    typedef typename internal::traits<Derived>::Index Index;
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::derived;
-
-    /** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
-      *
-      * \sa outerStride(), rowStride(), colStride()
-      */
-    inline Index innerStride() const
-    {
-      return derived().innerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
-      *          in a column-major matrix).
-      *
-      * \sa innerStride(), rowStride(), colStride()
-      */
-    inline Index outerStride() const
-    {
-      return derived().outerStride();
-    }
-
-    // FIXME shall we remove it ?
-    inline Index stride() const
-    {
-      return Derived::IsVectorAtCompileTime ? innerStride() : outerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive rows.
-      *
-      * \sa innerStride(), outerStride(), colStride()
-      */
-    inline Index rowStride() const
-    {
-      return Derived::IsRowMajor ? outerStride() : innerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive columns.
-      *
-      * \sa innerStride(), outerStride(), rowStride()
-      */
+    EIGEN_DEVICE_FUNC
     inline Index colStride() const
     {
       return Derived::IsRowMajor ? innerStride() : outerStride();
     }
 };
 
 namespace internal {
 
-template<typename Derived, bool JustReturnZero>
+template<int Alignment, typename Derived, bool JustReturnZero>
 struct first_aligned_impl
 {
-  static inline typename Derived::Index run(const Derived&)
+  static inline Index run(const Derived&)
   { return 0; }
 };
 
-template<typename Derived>
-struct first_aligned_impl<Derived, false>
+template<int Alignment, typename Derived>
+struct first_aligned_impl<Alignment, Derived, false>
 {
-  static inline typename Derived::Index run(const Derived& m)
+  static inline Index run(const Derived& m)
   {
-    return internal::first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
+    return internal::first_aligned<Alignment>(m.data(), m.size());
   }
 };
 
-/** \internal \returns the index of the first element of the array that is well aligned for vectorization.
+/** \internal \returns the index of the first element of the array stored by \a m that is properly aligned with respect to \a Alignment for vectorization.
+  *
+  * \tparam Alignment requested alignment in Bytes.
   *
   * There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more
   * documentation.
   */
+template<int Alignment, typename Derived>
+static inline Index first_aligned(const DenseBase<Derived>& m)
+{
+  enum { ReturnZero = (int(evaluator<Derived>::Alignment) >= Alignment) || !(Derived::Flags & DirectAccessBit) };
+  return first_aligned_impl<Alignment, Derived, ReturnZero>::run(m.derived());
+}
+
 template<typename Derived>
-static inline typename Derived::Index first_aligned(const Derived& m)
+static inline Index first_default_aligned(const DenseBase<Derived>& m)
 {
-  return first_aligned_impl
-          <Derived, (Derived::Flags & AlignedBit) || !(Derived::Flags & DirectAccessBit)>
-          ::run(m);
+  typedef typename Derived::Scalar Scalar;
+  typedef typename packet_traits<Scalar>::type DefaultPacketType;
+  return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
 }
 
 template<typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
 struct inner_stride_at_compile_time
 {

Index: 3rd_party/eigen/Eigen/src/Core/DenseStorage.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/DenseStorage.h
+++ 3rd_party/eigen/Eigen/src/Core/DenseStorage.h
@@ -1,32 +1,34 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
+// Copyright (C) 2010-2013 Hauke Heibel <hauke.heibel@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATRIXSTORAGE_H
 #define EIGEN_MATRIXSTORAGE_H
 
 #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
+  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X) X; EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
 #else
-  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X)
 #endif
 
 namespace Eigen {
 
 namespace internal {
 
 struct constructor_without_unaligned_array_assert {};
 
-template<typename T, int Size> void check_static_allocation_size()
+template<typename T, int Size>
+EIGEN_DEVICE_FUNC
+void check_static_allocation_size()
 {
   // if EIGEN_STACK_ALLOCATION_LIMIT is defined to 0, then no limit
   #if EIGEN_STACK_ALLOCATION_LIMIT
   EIGEN_STATIC_ASSERT(Size * sizeof(T) <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
   #endif
@@ -36,22 +38,23 @@
   * Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned:
   * to 16 bytes boundary if the total size is a multiple of 16 bytes.
   */
 template <typename T, int Size, int MatrixOrArrayOptions,
           int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0
-                        : (((Size*sizeof(T))%16)==0) ? 16
-                        : 0 >
+                        : compute_default_alignment<T,Size>::value >
 struct plain_array
 {
   T array[Size];
 
-  plain_array() 
+  EIGEN_DEVICE_FUNC
+  plain_array()
   { 
     check_static_allocation_size<T,Size>();
   }
 
-  plain_array(constructor_without_unaligned_array_assert) 
+  EIGEN_DEVICE_FUNC
+  plain_array(constructor_without_unaligned_array_assert)
   { 
     check_static_allocation_size<T,Size>();
   }
 };
 
@@ -62,45 +65,104 @@
   // See this bug report: http://gcc.gnu.org/bugzilla/show_bug.cgi?id=53900
   // Hiding the origin of the array pointer behind a function argument seems to do the trick even if the function is inlined:
   template<typename PtrType>
   EIGEN_ALWAYS_INLINE PtrType eigen_unaligned_array_assert_workaround_gcc47(PtrType array) { return array; }
   #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
-    eigen_assert((reinterpret_cast<size_t>(eigen_unaligned_array_assert_workaround_gcc47(array)) & sizemask) == 0 \
+    eigen_assert((internal::UIntPtr(eigen_unaligned_array_assert_workaround_gcc47(array)) & (sizemask)) == 0 \
               && "this assertion is explained here: " \
               "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
               " **** READ THIS WEB PAGE !!! ****");
 #else
   #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
-    eigen_assert((reinterpret_cast<size_t>(array) & sizemask) == 0 \
+    eigen_assert((internal::UIntPtr(array) & (sizemask)) == 0 \
               && "this assertion is explained here: " \
               "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
               " **** READ THIS WEB PAGE !!! ****");
 #endif
+
+template <typename T, int Size, int MatrixOrArrayOptions>
+struct plain_array<T, Size, MatrixOrArrayOptions, 8>
+{
+  EIGEN_ALIGN_TO_BOUNDARY(8) T array[Size];
+
+  EIGEN_DEVICE_FUNC
+  plain_array() 
+  {
+    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(7);
+    check_static_allocation_size<T,Size>();
+  }
+
+  EIGEN_DEVICE_FUNC
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    check_static_allocation_size<T,Size>();
+  }
+};
 
 template <typename T, int Size, int MatrixOrArrayOptions>
 struct plain_array<T, Size, MatrixOrArrayOptions, 16>
 {
-  EIGEN_USER_ALIGN16 T array[Size];
+  EIGEN_ALIGN_TO_BOUNDARY(16) T array[Size];
+
+  EIGEN_DEVICE_FUNC
+  plain_array() 
+  { 
+    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(15);
+    check_static_allocation_size<T,Size>();
+  }
+
+  EIGEN_DEVICE_FUNC
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    check_static_allocation_size<T,Size>();
+  }
+};
+
+template <typename T, int Size, int MatrixOrArrayOptions>
+struct plain_array<T, Size, MatrixOrArrayOptions, 32>
+{
+  EIGEN_ALIGN_TO_BOUNDARY(32) T array[Size];
+
+  EIGEN_DEVICE_FUNC
+  plain_array() 
+  {
+    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(31);
+    check_static_allocation_size<T,Size>();
+  }
+
+  EIGEN_DEVICE_FUNC
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    check_static_allocation_size<T,Size>();
+  }
+};
+
+template <typename T, int Size, int MatrixOrArrayOptions>
+struct plain_array<T, Size, MatrixOrArrayOptions, 64>
+{
+  EIGEN_ALIGN_TO_BOUNDARY(64) T array[Size];
 
+  EIGEN_DEVICE_FUNC
   plain_array() 
   { 
-    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf);
+    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(63);
     check_static_allocation_size<T,Size>();
   }
 
+  EIGEN_DEVICE_FUNC
   plain_array(constructor_without_unaligned_array_assert) 
   { 
     check_static_allocation_size<T,Size>();
   }
 };
 
 template <typename T, int MatrixOrArrayOptions, int Alignment>
 struct plain_array<T, 0, MatrixOrArrayOptions, Alignment>
 {
-  EIGEN_USER_ALIGN16 T array[1];
-  plain_array() {}
-  plain_array(constructor_without_unaligned_array_assert) {}
+  T array[1];
+  EIGEN_DEVICE_FUNC plain_array() {}
+  EIGEN_DEVICE_FUNC plain_array(constructor_without_unaligned_array_assert) {}
 };
 
 } // end namespace internal
 
 /** \internal
@@ -120,37 +182,58 @@
 // purely fixed-size matrix
 template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage
 {
     internal::plain_array<T,Size,_Options> m_data;
   public:
-    inline DenseStorage() {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    EIGEN_DEVICE_FUNC DenseStorage() {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
+    }
+    EIGEN_DEVICE_FUNC
+    explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()) {}
-    inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
-    static inline DenseIndex rows(void) {return _Rows;}
-    static inline DenseIndex cols(void) {return _Cols;}
-    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
-    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
-    inline const T *data() const { return m_data.array; }
-    inline T *data() { return m_data.array; }
+    EIGEN_DEVICE_FUNC 
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data) {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
+    }
+    EIGEN_DEVICE_FUNC 
+    DenseStorage& operator=(const DenseStorage& other)
+    { 
+      if (this != &other) m_data = other.m_data;
+      return *this; 
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
+      eigen_internal_assert(size==rows*cols && rows==_Rows && cols==_Cols);
+      EIGEN_UNUSED_VARIABLE(size);
+      EIGEN_UNUSED_VARIABLE(rows);
+      EIGEN_UNUSED_VARIABLE(cols);
+    }
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
+    EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
+    EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
+    EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
+    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
 };
 
 // null matrix
 template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
 {
   public:
-    inline DenseStorage() {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert) {}
-    inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
-    inline void swap(DenseStorage& ) {}
-    static inline DenseIndex rows(void) {return _Rows;}
-    static inline DenseIndex cols(void) {return _Cols;}
-    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
-    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
-    inline const T *data() const { return 0; }
-    inline T *data() { return 0; }
+    EIGEN_DEVICE_FUNC DenseStorage() {}
+    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) {}
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage&) {}
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage&) { return *this; }
+    EIGEN_DEVICE_FUNC DenseStorage(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& ) {}
+    EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
+    EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
+    EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC const T *data() const { return 0; }
+    EIGEN_DEVICE_FUNC T *data() { return 0; }
 };
 
 // more specializations for null matrices; these are necessary to resolve ambiguities
 template<typename T, int _Options> class DenseStorage<T, 0, Dynamic, Dynamic, _Options>
 : public DenseStorage<T, 0, 0, 0, _Options> { };
@@ -163,177 +246,325 @@
 
 // dynamic-size matrix with fixed-size storage
 template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
 {
     internal::plain_array<T,Size,_Options> m_data;
-    DenseIndex m_rows;
-    DenseIndex m_cols;
+    Index m_rows;
+    Index m_cols;
   public:
-    inline DenseStorage() : m_rows(0), m_cols(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0), m_cols(0) {}
+    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
-    inline void swap(DenseStorage& other)
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {}
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) 
+    { 
+      if (this != &other)
+      {
+        m_data = other.m_data;
+        m_rows = other.m_rows;
+        m_cols = other.m_cols;
+      }
+      return *this; 
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index cols) : m_rows(rows), m_cols(cols) {}
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    inline DenseIndex rows() const {return m_rows;}
-    inline DenseIndex cols() const {return m_cols;}
-    inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
-    inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
-    inline const T *data() const { return m_data.array; }
-    inline T *data() { return m_data.array; }
+    EIGEN_DEVICE_FUNC Index rows() const {return m_rows;}
+    EIGEN_DEVICE_FUNC Index cols() const {return m_cols;}
+    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; }
+    EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; }
+    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
+    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
 };
 
 // dynamic-size matrix with fixed-size storage and fixed width
 template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
 {
     internal::plain_array<T,Size,_Options> m_data;
-    DenseIndex m_rows;
+    Index m_rows;
   public:
-    inline DenseStorage() : m_rows(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0) {}
+    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
-    inline DenseIndex rows(void) const {return m_rows;}
-    inline DenseIndex cols(void) const {return _Cols;}
-    inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
-    inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
-    inline const T *data() const { return m_data.array; }
-    inline T *data() { return m_data.array; }
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {}
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) 
+    {
+      if (this != &other)
+      {
+        m_data = other.m_data;
+        m_rows = other.m_rows;
+      }
+      return *this; 
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index) : m_rows(rows) {}
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
+    EIGEN_DEVICE_FUNC Index cols(void) const {return _Cols;}
+    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index) { m_rows = rows; }
+    EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index) { m_rows = rows; }
+    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
+    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
 };
 
 // dynamic-size matrix with fixed-size storage and fixed height
 template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
 {
     internal::plain_array<T,Size,_Options> m_data;
-    DenseIndex m_cols;
+    Index m_cols;
   public:
-    inline DenseStorage() : m_cols(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    EIGEN_DEVICE_FUNC DenseStorage() : m_cols(0) {}
+    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
-    inline DenseIndex rows(void) const {return _Rows;}
-    inline DenseIndex cols(void) const {return m_cols;}
-    inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
-    inline void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
-    inline const T *data() const { return m_data.array; }
-    inline T *data() { return m_data.array; }
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {}
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other)
+      {
+        m_data = other.m_data;
+        m_cols = other.m_cols;
+      }
+      return *this;
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(Index, Index, Index cols) : m_cols(cols) {}
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    EIGEN_DEVICE_FUNC Index rows(void) const {return _Rows;}
+    EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
+    void conservativeResize(Index, Index, Index cols) { m_cols = cols; }
+    void resize(Index, Index, Index cols) { m_cols = cols; }
+    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
+    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
 };
 
 // purely dynamic matrix.
 template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
 {
     T *m_data;
-    DenseIndex m_rows;
-    DenseIndex m_cols;
+    Index m_rows;
+    Index m_cols;
   public:
-    inline DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
+    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
        : m_data(0), m_rows(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows), m_cols(nbCols)
-    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
-    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
-    inline void swap(DenseStorage& other)
+    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols)
+      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols)
+    {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
+      eigen_internal_assert(size==rows*cols && rows>=0 && cols >=0);
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
+      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*other.m_cols))
+      , m_rows(other.m_rows)
+      , m_cols(other.m_cols)
+    {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*m_cols)
+      internal::smart_copy(other.m_data, other.m_data+other.m_rows*other.m_cols, m_data);
+    }
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other)
+      {
+        DenseStorage tmp(other);
+        this->swap(tmp);
+      }
+      return *this;
+    }
+#if EIGEN_HAS_RVALUE_REFERENCES
+    EIGEN_DEVICE_FUNC
+    DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
+      : m_data(std::move(other.m_data))
+      , m_rows(std::move(other.m_rows))
+      , m_cols(std::move(other.m_cols))
+    {
+      other.m_data = nullptr;
+      other.m_rows = 0;
+      other.m_cols = 0;
+    }
+    EIGEN_DEVICE_FUNC
+    DenseStorage& operator=(DenseStorage&& other) EIGEN_NOEXCEPT
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_rows, other.m_rows);
+      swap(m_cols, other.m_cols);
+      return *this;
+    }
+#endif
+    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    inline DenseIndex rows(void) const {return m_rows;}
-    inline DenseIndex cols(void) const {return m_cols;}
-    inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+    EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
+    EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
+    void conservativeResize(Index size, Index rows, Index cols)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
-      m_rows = nbRows;
-      m_cols = nbCols;
+      m_rows = rows;
+      m_cols = cols;
     }
-    void resize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+    EIGEN_DEVICE_FUNC void resize(Index size, Index rows, Index cols)
     {
       if(size != m_rows*m_cols)
       {
         internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols);
         if (size)
           m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
         else
           m_data = 0;
-        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
       }
-      m_rows = nbRows;
-      m_cols = nbCols;
+      m_rows = rows;
+      m_cols = cols;
     }
-    inline const T *data() const { return m_data; }
-    inline T *data() { return m_data; }
+    EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
+    EIGEN_DEVICE_FUNC T *data() { return m_data; }
 };
 
 // matrix with dynamic width and fixed height (so that matrix has dynamic size).
 template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
 {
     T *m_data;
-    DenseIndex m_cols;
+    Index m_cols;
   public:
-    inline DenseStorage() : m_data(0), m_cols(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
-    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
-    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
-    static inline DenseIndex rows(void) {return _Rows;}
-    inline DenseIndex cols(void) const {return m_cols;}
-    inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
+    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_cols(0) {}
+    explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
+    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
+    {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
+      eigen_internal_assert(size==rows*cols && rows==_Rows && cols >=0);
+      EIGEN_UNUSED_VARIABLE(rows);
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
+      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(_Rows*other.m_cols))
+      , m_cols(other.m_cols)
+    {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_cols*_Rows)
+      internal::smart_copy(other.m_data, other.m_data+_Rows*m_cols, m_data);
+    }
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other)
+      {
+        DenseStorage tmp(other);
+        this->swap(tmp);
+      }
+      return *this;
+    }    
+#if EIGEN_HAS_RVALUE_REFERENCES
+    EIGEN_DEVICE_FUNC
+    DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
+      : m_data(std::move(other.m_data))
+      , m_cols(std::move(other.m_cols))
+    {
+      other.m_data = nullptr;
+      other.m_cols = 0;
+    }
+    EIGEN_DEVICE_FUNC
+    DenseStorage& operator=(DenseStorage&& other) EIGEN_NOEXCEPT
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_cols, other.m_cols);
+      return *this;
+    }
+#endif
+    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
+    EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
+    EIGEN_DEVICE_FUNC void conservativeResize(Index size, Index, Index cols)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
-      m_cols = nbCols;
+      m_cols = cols;
     }
-    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex nbCols)
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index, Index cols)
     {
       if(size != _Rows*m_cols)
       {
         internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols);
         if (size)
           m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
         else
           m_data = 0;
-        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
       }
-      m_cols = nbCols;
+      m_cols = cols;
     }
-    inline const T *data() const { return m_data; }
-    inline T *data() { return m_data; }
+    EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
+    EIGEN_DEVICE_FUNC T *data() { return m_data; }
 };
 
 // matrix with dynamic height and fixed width (so that matrix has dynamic size).
 template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
 {
     T *m_data;
-    DenseIndex m_rows;
+    Index m_rows;
   public:
-    inline DenseStorage() : m_data(0), m_rows(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
-    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
-    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
-    inline DenseIndex rows(void) const {return m_rows;}
-    static inline DenseIndex cols(void) {return _Cols;}
-    inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
+    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0) {}
+    explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
+    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
+    {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
+      eigen_internal_assert(size==rows*cols && rows>=0 && cols == _Cols);
+      EIGEN_UNUSED_VARIABLE(cols);
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
+      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*_Cols))
+      , m_rows(other.m_rows)
+    {
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*_Cols)
+      internal::smart_copy(other.m_data, other.m_data+other.m_rows*_Cols, m_data);
+    }
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other)
+      {
+        DenseStorage tmp(other);
+        this->swap(tmp);
+      }
+      return *this;
+    }    
+#if EIGEN_HAS_RVALUE_REFERENCES
+    EIGEN_DEVICE_FUNC
+    DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
+      : m_data(std::move(other.m_data))
+      , m_rows(std::move(other.m_rows))
+    {
+      other.m_data = nullptr;
+      other.m_rows = 0;
+    }
+    EIGEN_DEVICE_FUNC
+    DenseStorage& operator=(DenseStorage&& other) EIGEN_NOEXCEPT
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_rows, other.m_rows);
+      return *this;
+    }
+#endif
+    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
+    EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
+    void conservativeResize(Index size, Index rows, Index)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
-      m_rows = nbRows;
+      m_rows = rows;
     }
-    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex nbRows, DenseIndex)
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index rows, Index)
     {
       if(size != m_rows*_Cols)
       {
         internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows);
         if (size)
           m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
         else
           m_data = 0;
-        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
       }
-      m_rows = nbRows;
+      m_rows = rows;
     }
-    inline const T *data() const { return m_data; }
-    inline T *data() { return m_data; }
+    EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
+    EIGEN_DEVICE_FUNC T *data() { return m_data; }
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_MATRIX_H

Index: 3rd_party/eigen/Eigen/src/Core/Diagonal.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Diagonal.h
+++ 3rd_party/eigen/Eigen/src/Core/Diagonal.h
@@ -19,11 +19,11 @@
   * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix
   *
   * \param MatrixType the type of the object in which we are taking a sub/main/super diagonal
   * \param DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
   *              A positive value means a superdiagonal, a negative value means a subdiagonal.
-  *              You can also use Dynamic so the index can be set at runtime.
+  *              You can also use DynamicIndex so the index can be set at runtime.
   *
   * The matrix is not required to be square.
   *
   * This class represents an expression of the main diagonal, or any sub/super diagonal
   * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the
@@ -35,11 +35,11 @@
 namespace internal {
 template<typename MatrixType, int DiagIndex>
 struct traits<Diagonal<MatrixType,DiagIndex> >
  : traits<MatrixType>
 {
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
   typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
   typedef typename MatrixType::StorageKind StorageKind;
   enum {
     RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
                       : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
@@ -50,12 +50,11 @@
                                                                               MatrixType::MaxColsAtCompileTime)
                          : (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
                                                  MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
     MaxColsAtCompileTime = 1,
     MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
-    Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit,
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost,
+    Flags = (unsigned int)_MatrixTypeNested::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit, // FIXME DirectAccessBit should not be handled by expressions
     MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
     InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1,
     OuterStrideAtCompileTime = 0
   };
 };
@@ -68,24 +67,32 @@
 
     enum { DiagIndex = _DiagIndex };
     typedef typename internal::dense_xpr_base<Diagonal>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
 
-    inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
+    EIGEN_DEVICE_FUNC
+    explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
 
+    EIGEN_DEVICE_FUNC
     inline Index rows() const
-    { return m_index.value()<0 ? (std::min<Index>)(m_matrix.cols(),m_matrix.rows()+m_index.value()) : (std::min<Index>)(m_matrix.rows(),m_matrix.cols()-m_index.value()); }
+    {
+      return m_index.value()<0 ? numext::mini<Index>(m_matrix.cols(),m_matrix.rows()+m_index.value())
+                               : numext::mini<Index>(m_matrix.rows(),m_matrix.cols()-m_index.value());
+    }
 
+    EIGEN_DEVICE_FUNC
     inline Index cols() const { return 1; }
 
+    EIGEN_DEVICE_FUNC
     inline Index innerStride() const
     {
       return m_matrix.outerStride() + 1;
     }
 
+    EIGEN_DEVICE_FUNC
     inline Index outerStride() const
     {
       return 0;
     }
 
@@ -93,66 +100,79 @@
                        internal::is_lvalue<MatrixType>::value,
                        Scalar,
                        const Scalar
                      >::type ScalarWithConstIfNotLvalue;
 
-    inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
-    inline const Scalar* data() const { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
+    EIGEN_DEVICE_FUNC
+    inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.coeffRef(rowOffset(), colOffset())); }
+    EIGEN_DEVICE_FUNC
+    inline const Scalar* data() const { return &(m_matrix.coeffRef(rowOffset(), colOffset())); }
 
+    EIGEN_DEVICE_FUNC
     inline Scalar& coeffRef(Index row, Index)
     {
       EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
+      return m_matrix.coeffRef(row+rowOffset(), row+colOffset());
     }
 
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index row, Index) const
     {
-      return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
+      return m_matrix.coeffRef(row+rowOffset(), row+colOffset());
     }
 
+    EIGEN_DEVICE_FUNC
     inline CoeffReturnType coeff(Index row, Index) const
     {
       return m_matrix.coeff(row+rowOffset(), row+colOffset());
     }
 
+    EIGEN_DEVICE_FUNC
     inline Scalar& coeffRef(Index idx)
     {
       EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
+      return m_matrix.coeffRef(idx+rowOffset(), idx+colOffset());
     }
 
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index idx) const
     {
-      return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
+      return m_matrix.coeffRef(idx+rowOffset(), idx+colOffset());
     }
 
+    EIGEN_DEVICE_FUNC
     inline CoeffReturnType coeff(Index idx) const
     {
       return m_matrix.coeff(idx+rowOffset(), idx+colOffset());
     }
 
-    const typename internal::remove_all<typename MatrixType::Nested>::type& 
+    EIGEN_DEVICE_FUNC
+    inline const typename internal::remove_all<typename MatrixType::Nested>::type& 
     nestedExpression() const 
     {
       return m_matrix;
     }
 
-    int index() const
+    EIGEN_DEVICE_FUNC
+    inline Index index() const
     {
       return m_index.value();
     }
 
   protected:
-    typename MatrixType::Nested m_matrix;
+    typename internal::ref_selector<MatrixType>::non_const_type m_matrix;
     const internal::variable_if_dynamicindex<Index, DiagIndex> m_index;
 
   private:
     // some compilers may fail to optimize std::max etc in case of compile-time constants...
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index absDiagIndex() const { return m_index.value()>0 ? m_index.value() : -m_index.value(); }
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); }
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
-    // triger a compile time error is someone try to call packet
+    // trigger a compile-time error if someone try to call packet
     template<int LoadMode> typename MatrixType::PacketReturnType packet(Index) const;
     template<int LoadMode> typename MatrixType::PacketReturnType packet(Index,Index) const;
 };
 
 /** \returns an expression of the main diagonal of the matrix \c *this
@@ -165,11 +185,11 @@
   * \sa class Diagonal */
 template<typename Derived>
 inline typename MatrixBase<Derived>::DiagonalReturnType
 MatrixBase<Derived>::diagonal()
 {
-  return derived();
+  return DiagonalReturnType(derived());
 }
 
 /** This is the const version of diagonal(). */
 template<typename Derived>
 inline typename MatrixBase<Derived>::ConstDiagonalReturnType
@@ -214,24 +234,24 @@
   * Example: \include MatrixBase_diagonal_template_int.cpp
   * Output: \verbinclude MatrixBase_diagonal_template_int.out
   *
   * \sa MatrixBase::diagonal(), class Diagonal */
 template<typename Derived>
-template<int Index>
-inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index>::Type
+template<int Index_>
+inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index_>::Type
 MatrixBase<Derived>::diagonal()
 {
-  return derived();
+  return typename DiagonalIndexReturnType<Index_>::Type(derived());
 }
 
 /** This is the const version of diagonal<int>(). */
 template<typename Derived>
-template<int Index>
-inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index>::Type
+template<int Index_>
+inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index_>::Type
 MatrixBase<Derived>::diagonal() const
 {
-  return derived();
+  return typename ConstDiagonalIndexReturnType<Index_>::Type(derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_DIAGONAL_H

Index: 3rd_party/eigen/Eigen/src/Core/DiagonalMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/DiagonalMatrix.h
+++ 3rd_party/eigen/Eigen/src/Core/DiagonalMatrix.h
@@ -20,91 +20,73 @@
   public:
     typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType;
     typedef typename DiagonalVectorType::Scalar Scalar;
     typedef typename DiagonalVectorType::RealScalar RealScalar;
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
 
     enum {
       RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
       ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
       MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
       MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
       IsVectorAtCompileTime = 0,
-      Flags = 0
+      Flags = NoPreferredStorageOrderBit
     };
 
     typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType;
     typedef DenseMatrixType DenseType;
     typedef DiagonalMatrix<Scalar,DiagonalVectorType::SizeAtCompileTime,DiagonalVectorType::MaxSizeAtCompileTime> PlainObject;
 
-    inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
-    inline Derived& derived() { return *static_cast<Derived*>(this); }
-
-    DenseMatrixType toDenseMatrix() const { return derived(); }
-    template<typename DenseDerived>
-    void evalTo(MatrixBase<DenseDerived> &other) const;
-    template<typename DenseDerived>
-    void addTo(MatrixBase<DenseDerived> &other) const
-    { other.diagonal() += diagonal(); }
-    template<typename DenseDerived>
-    void subTo(MatrixBase<DenseDerived> &other) const
-    { other.diagonal() -= diagonal(); }
-
-    inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
-    inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
-
-    inline Index rows() const { return diagonal().size(); }
-    inline Index cols() const { return diagonal().size(); }
-
-    /** \returns the diagonal matrix product of \c *this by the matrix \a matrix.
-      */
-    template<typename MatrixDerived>
-    const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
-    operator*(const MatrixBase<MatrixDerived> &matrix) const
-    {
-      return DiagonalProduct<MatrixDerived, Derived, OnTheLeft>(matrix.derived(), derived());
-    }
-
-    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
-    inverse() const
-    {
-      return diagonal().cwiseInverse();
-    }
-    
-    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
-    operator*(const Scalar& scalar) const
-    {
-      return diagonal() * scalar;
-    }
-    friend inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
-    operator*(const Scalar& scalar, const DiagonalBase& other)
-    {
-      return other.diagonal() * scalar;
-    }
-    
-    #ifdef EIGEN2_SUPPORT
-    template<typename OtherDerived>
-    bool isApprox(const DiagonalBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
-    {
-      return diagonal().isApprox(other.diagonal(), precision);
-    }
-    template<typename OtherDerived>
-    bool isApprox(const MatrixBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
-    {
-      return toDenseMatrix().isApprox(other, precision);
-    }
-    #endif
-};
-
-template<typename Derived>
-template<typename DenseDerived>
-void DiagonalBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
-{
-  other.setZero();
-  other.diagonal() = diagonal();
-}
+    EIGEN_DEVICE_FUNC
+    inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    EIGEN_DEVICE_FUNC
+    inline Derived& derived() { return *static_cast<Derived*>(this); }
+
+    EIGEN_DEVICE_FUNC
+    DenseMatrixType toDenseMatrix() const { return derived(); }
+    
+    EIGEN_DEVICE_FUNC
+    inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
+    EIGEN_DEVICE_FUNC
+    inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
+
+    EIGEN_DEVICE_FUNC
+    inline Index rows() const { return diagonal().size(); }
+    EIGEN_DEVICE_FUNC
+    inline Index cols() const { return diagonal().size(); }
+
+    template<typename MatrixDerived>
+    EIGEN_DEVICE_FUNC
+    const Product<Derived,MatrixDerived,LazyProduct>
+    operator*(const MatrixBase<MatrixDerived> &matrix) const
+    {
+      return Product<Derived, MatrixDerived, LazyProduct>(derived(),matrix.derived());
+    }
+
+    typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> > InverseReturnType;
+    EIGEN_DEVICE_FUNC
+    inline const InverseReturnType
+    inverse() const
+    {
+      return InverseReturnType(diagonal().cwiseInverse());
+    }
+    
+    EIGEN_DEVICE_FUNC
+    inline const DiagonalWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DiagonalVectorType,Scalar,product) >
+    operator*(const Scalar& scalar) const
+    {
+      return DiagonalWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DiagonalVectorType,Scalar,product) >(diagonal() * scalar);
+    }
+    EIGEN_DEVICE_FUNC
+    friend inline const DiagonalWrapper<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,DiagonalVectorType,product) >
+    operator*(const Scalar& scalar, const DiagonalBase& other)
+    {
+      return DiagonalWrapper<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,DiagonalVectorType,product) >(scalar * other.diagonal());
+    }
+};
+
 #endif
 
 /** \class DiagonalMatrix
   * \ingroup Core_Module
   *
@@ -122,14 +104,13 @@
 template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
 struct traits<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
  : traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
 {
   typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
-  typedef Dense StorageKind;
-  typedef DenseIndex Index;
+  typedef DiagonalShape StorageKind;
   enum {
-    Flags = LvalueBit
+    Flags = LvalueBit | NoPreferredStorageOrderBit
   };
 };
 }
 template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
 class DiagonalMatrix
@@ -139,52 +120,61 @@
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     typedef typename internal::traits<DiagonalMatrix>::DiagonalVectorType DiagonalVectorType;
     typedef const DiagonalMatrix& Nested;
     typedef _Scalar Scalar;
     typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
-    typedef typename internal::traits<DiagonalMatrix>::Index Index;
+    typedef typename internal::traits<DiagonalMatrix>::StorageIndex StorageIndex;
     #endif
 
   protected:
 
     DiagonalVectorType m_diagonal;
 
   public:
 
     /** const version of diagonal(). */
+    EIGEN_DEVICE_FUNC
     inline const DiagonalVectorType& diagonal() const { return m_diagonal; }
     /** \returns a reference to the stored vector of diagonal coefficients. */
+    EIGEN_DEVICE_FUNC
     inline DiagonalVectorType& diagonal() { return m_diagonal; }
 
     /** Default constructor without initialization */
+    EIGEN_DEVICE_FUNC
     inline DiagonalMatrix() {}
 
     /** Constructs a diagonal matrix with given dimension  */
-    inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
+    EIGEN_DEVICE_FUNC
+    explicit inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
 
     /** 2D constructor. */
+    EIGEN_DEVICE_FUNC
     inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {}
 
     /** 3D constructor. */
+    EIGEN_DEVICE_FUNC
     inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {}
 
     /** Copy constructor. */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     inline DiagonalMatrix(const DiagonalBase<OtherDerived>& other) : m_diagonal(other.diagonal()) {}
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** copy constructor. prevent a default copy constructor from hiding the other templated constructor */
     inline DiagonalMatrix(const DiagonalMatrix& other) : m_diagonal(other.diagonal()) {}
     #endif
 
     /** generic constructor from expression of the diagonal coefficients */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     explicit inline DiagonalMatrix(const MatrixBase<OtherDerived>& other) : m_diagonal(other)
     {}
 
     /** Copy operator. */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     DiagonalMatrix& operator=(const DiagonalBase<OtherDerived>& other)
     {
       m_diagonal = other.diagonal();
       return *this;
     }
@@ -191,26 +181,32 @@
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** This is a special case of the templated operator=. Its purpose is to
       * prevent a default operator= from hiding the templated operator=.
       */
+    EIGEN_DEVICE_FUNC
     DiagonalMatrix& operator=(const DiagonalMatrix& other)
     {
       m_diagonal = other.diagonal();
       return *this;
     }
     #endif
 
     /** Resizes to given size. */
+    EIGEN_DEVICE_FUNC
     inline void resize(Index size) { m_diagonal.resize(size); }
     /** Sets all coefficients to zero. */
+    EIGEN_DEVICE_FUNC
     inline void setZero() { m_diagonal.setZero(); }
     /** Resizes and sets all coefficients to zero. */
+    EIGEN_DEVICE_FUNC
     inline void setZero(Index size) { m_diagonal.setZero(size); }
     /** Sets this matrix to be the identity matrix of the current size. */
+    EIGEN_DEVICE_FUNC
     inline void setIdentity() { m_diagonal.setOnes(); }
     /** Sets this matrix to be the identity matrix of the given size. */
+    EIGEN_DEVICE_FUNC
     inline void setIdentity(Index size) { m_diagonal.setOnes(size); }
 };
 
 /** \class DiagonalWrapper
   * \ingroup Core_Module
@@ -230,18 +226,19 @@
 template<typename _DiagonalVectorType>
 struct traits<DiagonalWrapper<_DiagonalVectorType> >
 {
   typedef _DiagonalVectorType DiagonalVectorType;
   typedef typename DiagonalVectorType::Scalar Scalar;
-  typedef typename DiagonalVectorType::Index Index;
-  typedef typename DiagonalVectorType::StorageKind StorageKind;
+  typedef typename DiagonalVectorType::StorageIndex StorageIndex;
+  typedef DiagonalShape StorageKind;
+  typedef typename traits<DiagonalVectorType>::XprKind XprKind;
   enum {
     RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
     ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-    MaxRowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-    MaxColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-    Flags =  traits<DiagonalVectorType>::Flags & LvalueBit
+    MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
+    MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
+    Flags =  (traits<DiagonalVectorType>::Flags & LvalueBit) | NoPreferredStorageOrderBit
   };
 };
 }
 
 template<typename _DiagonalVectorType>
@@ -253,13 +250,15 @@
     typedef _DiagonalVectorType DiagonalVectorType;
     typedef DiagonalWrapper Nested;
     #endif
 
     /** Constructor from expression of diagonal coefficients to wrap. */
-    inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
+    EIGEN_DEVICE_FUNC
+    explicit inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
 
     /** \returns a const reference to the wrapped expression of diagonal coefficients. */
+    EIGEN_DEVICE_FUNC
     const DiagonalVectorType& diagonal() const { return m_diagonal; }
 
   protected:
     typename DiagonalVectorType::Nested m_diagonal;
 };
@@ -275,11 +274,11 @@
   **/
 template<typename Derived>
 inline const DiagonalWrapper<const Derived>
 MatrixBase<Derived>::asDiagonal() const
 {
-  return derived();
+  return DiagonalWrapper<const Derived>(derived());
 }
 
 /** \returns true if *this is approximately equal to a diagonal matrix,
   *          within the precision given by \a prec.
   *
@@ -289,16 +288,15 @@
   * \sa asDiagonal()
   */
 template<typename Derived>
 bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
 {
-  using std::abs;
   if(cols() != rows()) return false;
   RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
   for(Index j = 0; j < cols(); ++j)
   {
-    RealScalar absOnDiagonal = abs(coeff(j,j));
+    RealScalar absOnDiagonal = numext::abs(coeff(j,j));
     if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
   }
   for(Index j = 0; j < cols(); ++j)
     for(Index i = 0; i < j; ++i)
     {
@@ -306,8 +304,40 @@
       if(!internal::isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false;
     }
   return true;
 }
 
+namespace internal {
+
+template<> struct storage_kind_to_shape<DiagonalShape> { typedef DiagonalShape Shape; };
+
+struct Diagonal2Dense {};
+
+template<> struct AssignmentKind<DenseShape,DiagonalShape> { typedef Diagonal2Dense Kind; };
+
+// Diagonal matrix to Dense assignment
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Dense>
+{
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+    
+    dst.setZero();
+    dst.diagonal() = src.diagonal();
+  }
+  
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  { dst.diagonal() += src.diagonal(); }
+  
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  { dst.diagonal() -= src.diagonal(); }
+};
+
+} // namespace internal
+
 } // end namespace Eigen
 
 #endif // EIGEN_DIAGONALMATRIX_H

Index: 3rd_party/eigen/Eigen/src/Core/DiagonalProduct.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/DiagonalProduct.h
+++ 3rd_party/eigen/Eigen/src/Core/DiagonalProduct.h
@@ -11,120 +11,18 @@
 #ifndef EIGEN_DIAGONALPRODUCT_H
 #define EIGEN_DIAGONALPRODUCT_H
 
 namespace Eigen { 
 
-namespace internal {
-template<typename MatrixType, typename DiagonalType, int ProductOrder>
-struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
- : traits<MatrixType>
-{
-  typedef typename scalar_product_traits<typename MatrixType::Scalar, typename DiagonalType::Scalar>::ReturnType Scalar;
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-
-    _StorageOrder = MatrixType::Flags & RowMajorBit ? RowMajor : ColMajor,
-    _ScalarAccessOnDiag =  !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft)
-                          ||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)),
-    _SameTypes = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
-    // FIXME currently we need same types, but in the future the next rule should be the one
-    //_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
-    _Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
-    _LinearAccessMask = (RowsAtCompileTime==1 || ColsAtCompileTime==1) ? LinearAccessBit : 0,
-
-    Flags = ((HereditaryBits|_LinearAccessMask) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0) | AlignedBit,//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
-    CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + DiagonalType::DiagonalVectorType::CoeffReadCost
-  };
-};
-}
-
-template<typename MatrixType, typename DiagonalType, int ProductOrder>
-class DiagonalProduct : internal::no_assignment_operator,
-                        public MatrixBase<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
-{
-  public:
-
-    typedef MatrixBase<DiagonalProduct> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(DiagonalProduct)
-
-    inline DiagonalProduct(const MatrixType& matrix, const DiagonalType& diagonal)
-      : m_matrix(matrix), m_diagonal(diagonal)
-    {
-      eigen_assert(diagonal.diagonal().size() == (ProductOrder == OnTheLeft ? matrix.rows() : matrix.cols()));
-    }
-
-    EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
-
-    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
-    {
-      return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col);
-    }
-    
-    EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
-    {
-      enum {
-        StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
-      };
-      return coeff(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
-    {
-      enum {
-        StorageOrder = Flags & RowMajorBit ? RowMajor : ColMajor
-      };
-      const Index indexInDiagonalVector = ProductOrder == OnTheLeft ? row : col;
-      return packet_impl<LoadMode>(row,col,indexInDiagonalVector,typename internal::conditional<
-        ((int(StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft)
-       ||(int(StorageOrder) == ColMajor && int(ProductOrder) == OnTheRight)), internal::true_type, internal::false_type>::type());
-    }
-    
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index idx) const
-    {
-      enum {
-        StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
-      };
-      return packet<LoadMode>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
-    }
-
-  protected:
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::true_type) const
-    {
-      return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
-                     internal::pset1<PacketScalar>(m_diagonal.diagonal().coeff(id)));
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::false_type) const
-    {
-      enum {
-        InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
-        DiagonalVectorPacketLoadMode = (LoadMode == Aligned && (((InnerSize%16) == 0) || (int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit)==AlignedBit) ? Aligned : Unaligned)
-      };
-      return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
-                     m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(id));
-    }
-
-    typename MatrixType::Nested m_matrix;
-    typename DiagonalType::Nested m_diagonal;
-};
-
 /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
   */
 template<typename Derived>
 template<typename DiagonalDerived>
-inline const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
+inline const Product<Derived, DiagonalDerived, LazyProduct>
 MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const
 {
-  return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), a_diagonal.derived());
+  return Product<Derived, DiagonalDerived, LazyProduct>(derived(),a_diagonal.derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_DIAGONALPRODUCT_H

Index: 3rd_party/eigen/Eigen/src/Core/Dot.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Dot.h
+++ 3rd_party/eigen/Eigen/src/Core/Dot.h
@@ -26,30 +26,35 @@
                          // revert to || as soon as not needed anymore.
                     (int(T::ColsAtCompileTime) == 1 && int(U::RowsAtCompileTime) == 1))
 >
 struct dot_nocheck
 {
-  typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar;
+  typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
+  typedef typename conj_prod::result_type ResScalar;
+  EIGEN_DEVICE_FUNC
   static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
   {
-    return a.template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
+    return a.template binaryExpr<conj_prod>(b).sum();
   }
 };
 
 template<typename T, typename U>
 struct dot_nocheck<T, U, true>
 {
-  typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar;
+  typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
+  typedef typename conj_prod::result_type ResScalar;
+  EIGEN_DEVICE_FUNC
   static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
   {
-    return a.transpose().template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
+    return a.transpose().template binaryExpr<conj_prod>(b).sum();
   }
 };
 
 } // end namespace internal
 
-/** \returns the dot product of *this with other.
+/** \fn MatrixBase::dot
+  * \returns the dot product of *this with other.
   *
   * \only_for_vectors
   *
   * \note If the scalar type is complex numbers, then this function returns the hermitian
   * (sesquilinear) dot product, conjugate-linear in the first variable and linear in the
@@ -57,59 +62,34 @@
   *
   * \sa squaredNorm(), norm()
   */
 template<typename Derived>
 template<typename OtherDerived>
-typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
+EIGEN_DEVICE_FUNC
+typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
 MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
   EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
+#if !(defined(EIGEN_NO_STATIC_ASSERT) && defined(EIGEN_NO_DEBUG))
   typedef internal::scalar_conj_product_op<Scalar,typename OtherDerived::Scalar> func;
   EIGEN_CHECK_BINARY_COMPATIBILIY(func,Scalar,typename OtherDerived::Scalar);
-
+#endif
+  
   eigen_assert(size() == other.size());
 
   return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
 }
-
-#ifdef EIGEN2_SUPPORT
-/** \returns the dot product of *this with other, with the Eigen2 convention that the dot product is linear in the first variable
-  * (conjugating the second variable). Of course this only makes a difference in the complex case.
-  *
-  * This method is only available in EIGEN2_SUPPORT mode.
-  *
-  * \only_for_vectors
-  *
-  * \sa dot()
-  */
-template<typename Derived>
-template<typename OtherDerived>
-typename internal::traits<Derived>::Scalar
-MatrixBase<Derived>::eigen2_dot(const MatrixBase<OtherDerived>& other) const
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
-  EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
-    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-
-  eigen_assert(size() == other.size());
-
-  return internal::dot_nocheck<OtherDerived,Derived>::run(other,*this);
-}
-#endif
-
 
 //---------- implementation of L2 norm and related functions ----------
 
 /** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm.
   * In both cases, it consists in the sum of the square of all the matrix entries.
   * For vectors, this is also equals to the dot product of \c *this with itself.
   *
-  * \sa dot(), norm()
+  * \sa dot(), norm(), lpNorm()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
 {
   return numext::real((*this).cwiseAbs2().sum());
@@ -117,45 +97,102 @@
 
 /** \returns, for vectors, the \em l2 norm of \c *this, and for matrices the Frobenius norm.
   * In both cases, it consists in the square root of the sum of the square of all the matrix entries.
   * For vectors, this is also equals to the square root of the dot product of \c *this with itself.
   *
-  * \sa dot(), squaredNorm()
+  * \sa lpNorm(), dot(), squaredNorm()
   */
 template<typename Derived>
 inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
 {
-  using std::sqrt;
-  return sqrt(squaredNorm());
+  return numext::sqrt(squaredNorm());
 }
 
-/** \returns an expression of the quotient of *this by its own norm.
+/** \returns an expression of the quotient of \c *this by its own norm.
+  *
+  * \warning If the input vector is too small (i.e., this->norm()==0),
+  *          then this function returns a copy of the input.
   *
   * \only_for_vectors
   *
   * \sa norm(), normalize()
   */
 template<typename Derived>
 inline const typename MatrixBase<Derived>::PlainObject
 MatrixBase<Derived>::normalized() const
 {
-  typedef typename internal::nested<Derived>::type Nested;
-  typedef typename internal::remove_reference<Nested>::type _Nested;
+  typedef typename internal::nested_eval<Derived,2>::type _Nested;
   _Nested n(derived());
-  return n / n.norm();
+  RealScalar z = n.squaredNorm();
+  // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
+  if(z>RealScalar(0))
+    return n / numext::sqrt(z);
+  else
+    return n;
 }
 
 /** Normalizes the vector, i.e. divides it by its own norm.
   *
   * \only_for_vectors
   *
+  * \warning If the input vector is too small (i.e., this->norm()==0), then \c *this is left unchanged.
+  *
   * \sa norm(), normalized()
   */
 template<typename Derived>
 inline void MatrixBase<Derived>::normalize()
 {
-  *this /= norm();
+  RealScalar z = squaredNorm();
+  // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
+  if(z>RealScalar(0))
+    derived() /= numext::sqrt(z);
+}
+
+/** \returns an expression of the quotient of \c *this by its own norm while avoiding underflow and overflow.
+  *
+  * \only_for_vectors
+  *
+  * This method is analogue to the normalized() method, but it reduces the risk of
+  * underflow and overflow when computing the norm.
+  *
+  * \warning If the input vector is too small (i.e., this->norm()==0),
+  *          then this function returns a copy of the input.
+  *
+  * \sa stableNorm(), stableNormalize(), normalized()
+  */
+template<typename Derived>
+inline const typename MatrixBase<Derived>::PlainObject
+MatrixBase<Derived>::stableNormalized() const
+{
+  typedef typename internal::nested_eval<Derived,3>::type _Nested;
+  _Nested n(derived());
+  RealScalar w = n.cwiseAbs().maxCoeff();
+  RealScalar z = (n/w).squaredNorm();
+  if(z>RealScalar(0))
+    return n / (numext::sqrt(z)*w);
+  else
+    return n;
+}
+
+/** Normalizes the vector while avoid underflow and overflow
+  *
+  * \only_for_vectors
+  *
+  * This method is analogue to the normalize() method, but it reduces the risk of
+  * underflow and overflow when computing the norm.
+  *
+  * \warning If the input vector is too small (i.e., this->norm()==0), then \c *this is left unchanged.
+  *
+  * \sa stableNorm(), stableNormalized(), normalize()
+  */
+template<typename Derived>
+inline void MatrixBase<Derived>::stableNormalize()
+{
+  RealScalar w = cwiseAbs().maxCoeff();
+  RealScalar z = (derived()/w).squaredNorm();
+  if(z>RealScalar(0))
+    derived() /= numext::sqrt(z)*w;
 }
 
 //---------- implementation of other norms ----------
 
 namespace internal {
@@ -162,55 +199,70 @@
 
 template<typename Derived, int p>
 struct lpNorm_selector
 {
   typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar run(const MatrixBase<Derived>& m)
   {
-    using std::pow;
+    EIGEN_USING_STD_MATH(pow)
     return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p);
   }
 };
 
 template<typename Derived>
 struct lpNorm_selector<Derived, 1>
 {
+  EIGEN_DEVICE_FUNC
   static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
   {
     return m.cwiseAbs().sum();
   }
 };
 
 template<typename Derived>
 struct lpNorm_selector<Derived, 2>
 {
+  EIGEN_DEVICE_FUNC
   static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
   {
     return m.norm();
   }
 };
 
 template<typename Derived>
 struct lpNorm_selector<Derived, Infinity>
 {
-  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
+  static inline RealScalar run(const MatrixBase<Derived>& m)
   {
+    if(Derived::SizeAtCompileTime==0 || (Derived::SizeAtCompileTime==Dynamic && m.size()==0))
+      return RealScalar(0);
     return m.cwiseAbs().maxCoeff();
   }
 };
 
 } // end namespace internal
 
-/** \returns the \f$ \ell^p \f$ norm of *this, that is, returns the p-th root of the sum of the p-th powers of the absolute values
-  *          of the coefficients of *this. If \a p is the special value \a Eigen::Infinity, this function returns the \f$ \ell^\infty \f$
-  *          norm, that is the maximum of the absolute values of the coefficients of *this.
+/** \returns the \b coefficient-wise \f$ \ell^p \f$ norm of \c *this, that is, returns the p-th root of the sum of the p-th powers of the absolute values
+  *          of the coefficients of \c *this. If \a p is the special value \a Eigen::Infinity, this function returns the \f$ \ell^\infty \f$
+  *          norm, that is the maximum of the absolute values of the coefficients of \c *this.
+  *
+  * In all cases, if \c *this is empty, then the value 0 is returned.
+  *
+  * \note For matrices, this function does not compute the <a href="https://en.wikipedia.org/wiki/Operator_norm">operator-norm</a>. That is, if \c *this is a matrix, then its coefficients are interpreted as a 1D vector. Nonetheless, you can easily compute the 1-norm and \f$\infty\f$-norm matrix operator norms using \link TutorialReductionsVisitorsBroadcastingReductionsNorm partial reductions \endlink.
   *
   * \sa norm()
   */
 template<typename Derived>
 template<int p>
+#ifndef EIGEN_PARSED_BY_DOXYGEN
 inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
+#else
+MatrixBase<Derived>::RealScalar
+#endif
 MatrixBase<Derived>::lpNorm() const
 {
   return internal::lpNorm_selector<Derived, p>::run(*this);
 }
 
@@ -225,12 +277,12 @@
 template<typename Derived>
 template<typename OtherDerived>
 bool MatrixBase<Derived>::isOrthogonal
 (const MatrixBase<OtherDerived>& other, const RealScalar& prec) const
 {
-  typename internal::nested<Derived,2>::type nested(derived());
-  typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
+  typename internal::nested_eval<Derived,2>::type nested(derived());
+  typename internal::nested_eval<OtherDerived,2>::type otherNested(other.derived());
   return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
 }
 
 /** \returns true if *this is approximately an unitary matrix,
   *          within the precision given by \a prec. In the case where the \a Scalar
@@ -244,20 +296,20 @@
   * Output: \verbinclude MatrixBase_isUnitary.out
   */
 template<typename Derived>
 bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const
 {
-  typename Derived::Nested nested(derived());
+  typename internal::nested_eval<Derived,1>::type self(derived());
   for(Index i = 0; i < cols(); ++i)
   {
-    if(!internal::isApprox(nested.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
+    if(!internal::isApprox(self.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
       return false;
     for(Index j = 0; j < i; ++j)
-      if(!internal::isMuchSmallerThan(nested.col(i).dot(nested.col(j)), static_cast<Scalar>(1), prec))
+      if(!internal::isMuchSmallerThan(self.col(i).dot(self.col(j)), static_cast<Scalar>(1), prec))
         return false;
   }
   return true;
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_DOT_H

Index: 3rd_party/eigen/Eigen/src/Core/EigenBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/EigenBase.h
+++ 3rd_party/eigen/Eigen/src/Core/EigenBase.h
@@ -11,79 +11,104 @@
 #ifndef EIGEN_EIGENBASE_H
 #define EIGEN_EIGENBASE_H
 
 namespace Eigen {
 
-/** Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
+/** \class EigenBase
+  * \ingroup Core_Module
+  * 
+  * Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
   *
   * In other words, an EigenBase object is an object that can be copied into a MatrixBase.
   *
   * Besides MatrixBase-derived classes, this also includes special matrix classes such as diagonal matrices, etc.
   *
   * Notice that this class is trivial, it is only used to disambiguate overloaded functions.
   *
-  * \sa \ref TopicClassHierarchy
+  * \sa \blank \ref TopicClassHierarchy
   */
 template<typename Derived> struct EigenBase
 {
 //   typedef typename internal::plain_matrix_type<Derived>::type PlainObject;
+  
+  /** \brief The interface type of indices
+    * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
+    * \deprecated Since Eigen 3.3, its usage is deprecated. Use Eigen::Index instead.
+    * \sa StorageIndex, \ref TopicPreprocessorDirectives.
+    */
+  typedef Eigen::Index Index;
 
+  // FIXME is it needed?
   typedef typename internal::traits<Derived>::StorageKind StorageKind;
-  typedef typename internal::traits<Derived>::Index Index;
 
   /** \returns a reference to the derived object */
+  EIGEN_DEVICE_FUNC
   Derived& derived() { return *static_cast<Derived*>(this); }
   /** \returns a const reference to the derived object */
+  EIGEN_DEVICE_FUNC
   const Derived& derived() const { return *static_cast<const Derived*>(this); }
 
+  EIGEN_DEVICE_FUNC
   inline Derived& const_cast_derived() const
   { return *static_cast<Derived*>(const_cast<EigenBase*>(this)); }
+  EIGEN_DEVICE_FUNC
   inline const Derived& const_derived() const
   { return *static_cast<const Derived*>(this); }
 
   /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
+  EIGEN_DEVICE_FUNC
   inline Index rows() const { return derived().rows(); }
   /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
+  EIGEN_DEVICE_FUNC
   inline Index cols() const { return derived().cols(); }
   /** \returns the number of coefficients, which is rows()*cols().
     * \sa rows(), cols(), SizeAtCompileTime. */
+  EIGEN_DEVICE_FUNC
   inline Index size() const { return rows() * cols(); }
 
   /** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */
-  template<typename Dest> inline void evalTo(Dest& dst) const
+  template<typename Dest>
+  EIGEN_DEVICE_FUNC
+  inline void evalTo(Dest& dst) const
   { derived().evalTo(dst); }
 
   /** \internal Don't use it, but do the equivalent: \code dst += *this; \endcode */
-  template<typename Dest> inline void addTo(Dest& dst) const
+  template<typename Dest>
+  EIGEN_DEVICE_FUNC
+  inline void addTo(Dest& dst) const
   {
     // This is the default implementation,
     // derived class can reimplement it in a more optimized way.
     typename Dest::PlainObject res(rows(),cols());
     evalTo(res);
     dst += res;
   }
 
   /** \internal Don't use it, but do the equivalent: \code dst -= *this; \endcode */
-  template<typename Dest> inline void subTo(Dest& dst) const
+  template<typename Dest>
+  EIGEN_DEVICE_FUNC
+  inline void subTo(Dest& dst) const
   {
     // This is the default implementation,
     // derived class can reimplement it in a more optimized way.
     typename Dest::PlainObject res(rows(),cols());
     evalTo(res);
     dst -= res;
   }
 
   /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheRight(*this); \endcode */
-  template<typename Dest> inline void applyThisOnTheRight(Dest& dst) const
+  template<typename Dest>
+  EIGEN_DEVICE_FUNC inline void applyThisOnTheRight(Dest& dst) const
   {
     // This is the default implementation,
     // derived class can reimplement it in a more optimized way.
     dst = dst * this->derived();
   }
 
   /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheLeft(*this); \endcode */
-  template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
+  template<typename Dest>
+  EIGEN_DEVICE_FUNC inline void applyThisOnTheLeft(Dest& dst) const
   {
     // This is the default implementation,
     // derived class can reimplement it in a more optimized way.
     dst = this->derived() * dst;
   }
@@ -102,30 +127,33 @@
   *
   * \returns a reference to *this.
   */
 template<typename Derived>
 template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
 Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
 {
-  other.derived().evalTo(derived());
+  call_assignment(derived(), other.derived());
   return derived();
 }
 
 template<typename Derived>
 template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
 Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
 {
-  other.derived().addTo(derived());
+  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }
 
 template<typename Derived>
 template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
 Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
 {
-  other.derived().subTo(derived());
+  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_EIGENBASE_H

DELETED 3rd_party/eigen/Eigen/src/Core/Flagged.h
Index: 3rd_party/eigen/Eigen/src/Core/Flagged.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Flagged.h
+++ 3rd_party/eigen/Eigen/src/Core/Flagged.h
@@ -1,140 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_FLAGGED_H
-#define EIGEN_FLAGGED_H
-
-namespace Eigen { 
-
-/** \class Flagged
-  * \ingroup Core_Module
-  *
-  * \brief Expression with modified flags
-  *
-  * \param ExpressionType the type of the object of which we are modifying the flags
-  * \param Added the flags added to the expression
-  * \param Removed the flags removed from the expression (has priority over Added).
-  *
-  * This class represents an expression whose flags have been modified.
-  * It is the return type of MatrixBase::flagged()
-  * and most of the time this is the only way it is used.
-  *
-  * \sa MatrixBase::flagged()
-  */
-
-namespace internal {
-template<typename ExpressionType, unsigned int Added, unsigned int Removed>
-struct traits<Flagged<ExpressionType, Added, Removed> > : traits<ExpressionType>
-{
-  enum { Flags = (ExpressionType::Flags | Added) & ~Removed };
-};
-}
-
-template<typename ExpressionType, unsigned int Added, unsigned int Removed> class Flagged
-  : public MatrixBase<Flagged<ExpressionType, Added, Removed> >
-{
-  public:
-
-    typedef MatrixBase<Flagged> Base;
-    
-    EIGEN_DENSE_PUBLIC_INTERFACE(Flagged)
-    typedef typename internal::conditional<internal::must_nest_by_value<ExpressionType>::ret,
-        ExpressionType, const ExpressionType&>::type ExpressionTypeNested;
-    typedef typename ExpressionType::InnerIterator InnerIterator;
-
-    inline Flagged(const ExpressionType& matrix) : m_matrix(matrix) {}
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-    inline Index outerStride() const { return m_matrix.outerStride(); }
-    inline Index innerStride() const { return m_matrix.innerStride(); }
-
-    inline CoeffReturnType coeff(Index row, Index col) const
-    {
-      return m_matrix.coeff(row, col);
-    }
-
-    inline CoeffReturnType coeff(Index index) const
-    {
-      return m_matrix.coeff(index);
-    }
-    
-    inline const Scalar& coeffRef(Index row, Index col) const
-    {
-      return m_matrix.const_cast_derived().coeffRef(row, col);
-    }
-
-    inline const Scalar& coeffRef(Index index) const
-    {
-      return m_matrix.const_cast_derived().coeffRef(index);
-    }
-
-    inline Scalar& coeffRef(Index row, Index col)
-    {
-      return m_matrix.const_cast_derived().coeffRef(row, col);
-    }
-
-    inline Scalar& coeffRef(Index index)
-    {
-      return m_matrix.const_cast_derived().coeffRef(index);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index row, Index col) const
-    {
-      return m_matrix.template packet<LoadMode>(row, col);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& x)
-    {
-      m_matrix.const_cast_derived().template writePacket<LoadMode>(row, col, x);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index index) const
-    {
-      return m_matrix.template packet<LoadMode>(index);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& x)
-    {
-      m_matrix.const_cast_derived().template writePacket<LoadMode>(index, x);
-    }
-
-    const ExpressionType& _expression() const { return m_matrix; }
-
-    template<typename OtherDerived>
-    typename ExpressionType::PlainObject solveTriangular(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename OtherDerived>
-    void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
-
-  protected:
-    ExpressionTypeNested m_matrix;
-};
-
-/** \returns an expression of *this with added and removed flags
-  *
-  * This is mostly for internal use.
-  *
-  * \sa class Flagged
-  */
-template<typename Derived>
-template<unsigned int Added,unsigned int Removed>
-inline const Flagged<Derived, Added, Removed>
-DenseBase<Derived>::flagged() const
-{
-  return derived();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_FLAGGED_H

Index: 3rd_party/eigen/Eigen/src/Core/ForceAlignedAccess.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/ForceAlignedAccess.h
+++ 3rd_party/eigen/Eigen/src/Core/ForceAlignedAccess.h
@@ -37,33 +37,33 @@
   public:
 
     typedef typename internal::dense_xpr_base<ForceAlignedAccess>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(ForceAlignedAccess)
 
-    inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
-
-    inline Index rows() const { return m_expression.rows(); }
-    inline Index cols() const { return m_expression.cols(); }
-    inline Index outerStride() const { return m_expression.outerStride(); }
-    inline Index innerStride() const { return m_expression.innerStride(); }
-
-    inline const CoeffReturnType coeff(Index row, Index col) const
+    EIGEN_DEVICE_FUNC explicit inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
+
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_expression.rows(); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); }
+    EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); }
+    EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); }
+
+    EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
 
-    inline Scalar& coeffRef(Index row, Index col)
+    EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
     {
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const CoeffReturnType coeff(Index index) const
+    EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
 
-    inline Scalar& coeffRef(Index index)
+    EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
     {
       return m_expression.const_cast_derived().coeffRef(index);
     }
 
     template<int LoadMode>
@@ -88,11 +88,11 @@
     inline void writePacket(Index index, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<Aligned>(index, x);
     }
 
-    operator const ExpressionType&() const { return m_expression; }
+    EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; }
 
   protected:
     const ExpressionType& m_expression;
 
   private:
@@ -125,11 +125,11 @@
 template<typename Derived>
 template<bool Enable>
 inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type
 MatrixBase<Derived>::forceAlignedAccessIf() const
 {
-  return derived();
+  return derived();  // FIXME This should not work but apparently is never used
 }
 
 /** \returns an expression of *this with forced aligned access if \a Enable is true.
   * \sa forceAlignedAccess(), class ForceAlignedAccess
   */
@@ -136,11 +136,11 @@
 template<typename Derived>
 template<bool Enable>
 inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type
 MatrixBase<Derived>::forceAlignedAccessIf()
 {
-  return derived();
+  return derived();  // FIXME This should not work but apparently is never used
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_FORCEALIGNEDACCESS_H

DELETED 3rd_party/eigen/Eigen/src/Core/Functors.h
Index: 3rd_party/eigen/Eigen/src/Core/Functors.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Functors.h
+++ 3rd_party/eigen/Eigen/src/Core/Functors.h
@@ -1,985 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_FUNCTORS_H
-#define EIGEN_FUNCTORS_H
-
-namespace Eigen {
-
-namespace internal {
-
-// associative functors:
-
-/** \internal
-  * \brief Template functor to compute the sum of two scalars
-  *
-  * \sa class CwiseBinaryOp, MatrixBase::operator+, class VectorwiseOp, MatrixBase::sum()
-  */
-template<typename Scalar> struct scalar_sum_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_sum_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a + b; }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
-  { return internal::padd(a,b); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
-  { return internal::predux(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_sum_op<Scalar> > {
-  enum {
-    Cost = NumTraits<Scalar>::AddCost,
-    PacketAccess = packet_traits<Scalar>::HasAdd
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the product of two scalars
-  *
-  * \sa class CwiseBinaryOp, Cwise::operator*(), class VectorwiseOp, MatrixBase::redux()
-  */
-template<typename LhsScalar,typename RhsScalar> struct scalar_product_op {
-  enum {
-    // TODO vectorize mixed product
-    Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasMul && packet_traits<RhsScalar>::HasMul
-  };
-  typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_product_op)
-  EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a * b; }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
-  { return internal::pmul(a,b); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
-  { return internal::predux_mul(a); }
-};
-template<typename LhsScalar,typename RhsScalar>
-struct functor_traits<scalar_product_op<LhsScalar,RhsScalar> > {
-  enum {
-    Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost)/2, // rough estimate!
-    PacketAccess = scalar_product_op<LhsScalar,RhsScalar>::Vectorizable
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the conjugate product of two scalars
-  *
-  * This is a short cut for conj(x) * y which is needed for optimization purpose; in Eigen2 support mode, this becomes x * conj(y)
-  */
-template<typename LhsScalar,typename RhsScalar> struct scalar_conj_product_op {
-
-  enum {
-    Conj = NumTraits<LhsScalar>::IsComplex
-  };
-  
-  typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
-  
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_conj_product_op)
-  EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const
-  { return conj_helper<LhsScalar,RhsScalar,Conj,false>().pmul(a,b); }
-  
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
-  { return conj_helper<Packet,Packet,Conj,false>().pmul(a,b); }
-};
-template<typename LhsScalar,typename RhsScalar>
-struct functor_traits<scalar_conj_product_op<LhsScalar,RhsScalar> > {
-  enum {
-    Cost = NumTraits<LhsScalar>::MulCost,
-    PacketAccess = internal::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMul
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the min of two scalars
-  *
-  * \sa class CwiseBinaryOp, MatrixBase::cwiseMin, class VectorwiseOp, MatrixBase::minCoeff()
-  */
-template<typename Scalar> struct scalar_min_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_min_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::min; return (min)(a, b); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
-  { return internal::pmin(a,b); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
-  { return internal::predux_min(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_min_op<Scalar> > {
-  enum {
-    Cost = NumTraits<Scalar>::AddCost,
-    PacketAccess = packet_traits<Scalar>::HasMin
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the max of two scalars
-  *
-  * \sa class CwiseBinaryOp, MatrixBase::cwiseMax, class VectorwiseOp, MatrixBase::maxCoeff()
-  */
-template<typename Scalar> struct scalar_max_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_max_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::max; return (max)(a, b); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
-  { return internal::pmax(a,b); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
-  { return internal::predux_max(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_max_op<Scalar> > {
-  enum {
-    Cost = NumTraits<Scalar>::AddCost,
-    PacketAccess = packet_traits<Scalar>::HasMax
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the hypot of two scalars
-  *
-  * \sa MatrixBase::stableNorm(), class Redux
-  */
-template<typename Scalar> struct scalar_hypot_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op)
-//   typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
-  {
-    using std::max;
-    using std::min;
-    using std::sqrt;
-    Scalar p = (max)(_x, _y);
-    Scalar q = (min)(_x, _y);
-    Scalar qp = q/p;
-    return p * sqrt(Scalar(1) + qp*qp);
-  }
-};
-template<typename Scalar>
-struct functor_traits<scalar_hypot_op<Scalar> > {
-  enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess=0 };
-};
-
-/** \internal
-  * \brief Template functor to compute the pow of two scalars
-  */
-template<typename Scalar, typename OtherScalar> struct scalar_binary_pow_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_binary_pow_op)
-  inline Scalar operator() (const Scalar& a, const OtherScalar& b) const { return numext::pow(a, b); }
-};
-template<typename Scalar, typename OtherScalar>
-struct functor_traits<scalar_binary_pow_op<Scalar,OtherScalar> > {
-  enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false };
-};
-
-// other binary functors:
-
-/** \internal
-  * \brief Template functor to compute the difference of two scalars
-  *
-  * \sa class CwiseBinaryOp, MatrixBase::operator-
-  */
-template<typename Scalar> struct scalar_difference_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_difference_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a - b; }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
-  { return internal::psub(a,b); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_difference_op<Scalar> > {
-  enum {
-    Cost = NumTraits<Scalar>::AddCost,
-    PacketAccess = packet_traits<Scalar>::HasSub
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the quotient of two scalars
-  *
-  * \sa class CwiseBinaryOp, Cwise::operator/()
-  */
-template<typename LhsScalar,typename RhsScalar> struct scalar_quotient_op {
-  enum {
-    // TODO vectorize mixed product
-    Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasDiv && packet_traits<RhsScalar>::HasDiv
-  };
-  typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
-  EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a / b; }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
-  { return internal::pdiv(a,b); }
-};
-template<typename LhsScalar,typename RhsScalar>
-struct functor_traits<scalar_quotient_op<LhsScalar,RhsScalar> > {
-  enum {
-    Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost), // rough estimate!
-    PacketAccess = scalar_quotient_op<LhsScalar,RhsScalar>::Vectorizable
-  };
-};
-
-
-
-/** \internal
-  * \brief Template functor to compute the and of two booleans
-  *
-  * \sa class CwiseBinaryOp, ArrayBase::operator&&
-  */
-struct scalar_boolean_and_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_and_op)
-  EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a && b; }
-};
-template<> struct functor_traits<scalar_boolean_and_op> {
-  enum {
-    Cost = NumTraits<bool>::AddCost,
-    PacketAccess = false
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the or of two booleans
-  *
-  * \sa class CwiseBinaryOp, ArrayBase::operator||
-  */
-struct scalar_boolean_or_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_or_op)
-  EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a || b; }
-};
-template<> struct functor_traits<scalar_boolean_or_op> {
-  enum {
-    Cost = NumTraits<bool>::AddCost,
-    PacketAccess = false
-  };
-};
-
-// unary functors:
-
-/** \internal
-  * \brief Template functor to compute the opposite of a scalar
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::operator-
-  */
-template<typename Scalar> struct scalar_opposite_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_opposite_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return -a; }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
-  { return internal::pnegate(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_opposite_op<Scalar> >
-{ enum {
-    Cost = NumTraits<Scalar>::AddCost,
-    PacketAccess = packet_traits<Scalar>::HasNegate };
-};
-
-/** \internal
-  * \brief Template functor to compute the absolute value of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::abs
-  */
-template<typename Scalar> struct scalar_abs_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op)
-  typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { using std::abs; return abs(a); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
-  { return internal::pabs(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_abs_op<Scalar> >
-{
-  enum {
-    Cost = NumTraits<Scalar>::AddCost,
-    PacketAccess = packet_traits<Scalar>::HasAbs
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the squared absolute value of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::abs2
-  */
-template<typename Scalar> struct scalar_abs2_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op)
-  typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::abs2(a); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
-  { return internal::pmul(a,a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_abs2_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasAbs2 }; };
-
-/** \internal
-  * \brief Template functor to compute the conjugate of a complex value
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::conjugate()
-  */
-template<typename Scalar> struct scalar_conjugate_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { using numext::conj; return conj(a); }
-  template<typename Packet>
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_conjugate_op<Scalar> >
-{
-  enum {
-    Cost = NumTraits<Scalar>::IsComplex ? NumTraits<Scalar>::AddCost : 0,
-    PacketAccess = packet_traits<Scalar>::HasConj
-  };
-};
-
-/** \internal
-  * \brief Template functor to cast a scalar to another type
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::cast()
-  */
-template<typename Scalar, typename NewType>
-struct scalar_cast_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
-  typedef NewType result_type;
-  EIGEN_STRONG_INLINE const NewType operator() (const Scalar& a) const { return cast<Scalar, NewType>(a); }
-};
-template<typename Scalar, typename NewType>
-struct functor_traits<scalar_cast_op<Scalar,NewType> >
-{ enum { Cost = is_same<Scalar, NewType>::value ? 0 : NumTraits<NewType>::AddCost, PacketAccess = false }; };
-
-/** \internal
-  * \brief Template functor to extract the real part of a complex
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::real()
-  */
-template<typename Scalar>
-struct scalar_real_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op)
-  typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::real(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_real_op<Scalar> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-/** \internal
-  * \brief Template functor to extract the imaginary part of a complex
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::imag()
-  */
-template<typename Scalar>
-struct scalar_imag_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op)
-  typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::imag(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_imag_op<Scalar> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-/** \internal
-  * \brief Template functor to extract the real part of a complex as a reference
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::real()
-  */
-template<typename Scalar>
-struct scalar_real_ref_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op)
-  typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::real_ref(*const_cast<Scalar*>(&a)); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_real_ref_op<Scalar> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-/** \internal
-  * \brief Template functor to extract the imaginary part of a complex as a reference
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::imag()
-  */
-template<typename Scalar>
-struct scalar_imag_ref_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op)
-  typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::imag_ref(*const_cast<Scalar*>(&a)); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_imag_ref_op<Scalar> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-/** \internal
-  *
-  * \brief Template functor to compute the exponential of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::exp()
-  */
-template<typename Scalar> struct scalar_exp_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op)
-  inline const Scalar operator() (const Scalar& a) const { using std::exp; return exp(a); }
-  typedef typename packet_traits<Scalar>::type Packet;
-  inline Packet packetOp(const Packet& a) const { return internal::pexp(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_exp_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasExp }; };
-
-/** \internal
-  *
-  * \brief Template functor to compute the logarithm of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::log()
-  */
-template<typename Scalar> struct scalar_log_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op)
-  inline const Scalar operator() (const Scalar& a) const { using std::log; return log(a); }
-  typedef typename packet_traits<Scalar>::type Packet;
-  inline Packet packetOp(const Packet& a) const { return internal::plog(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_log_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasLog }; };
-
-/** \internal
-  * \brief Template functor to multiply a scalar by a fixed other one
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::operator*, MatrixBase::operator/
-  */
-/* NOTE why doing the pset1() in packetOp *is* an optimization ?
- * indeed it seems better to declare m_other as a Packet and do the pset1() once
- * in the constructor. However, in practice:
- *  - GCC does not like m_other as a Packet and generate a load every time it needs it
- *  - on the other hand GCC is able to moves the pset1() outside the loop :)
- *  - simpler code ;)
- * (ICC and gcc 4.4 seems to perform well in both cases, the issue is visible with y = a*x + b*y)
- */
-template<typename Scalar>
-struct scalar_multiple_op {
-  typedef typename packet_traits<Scalar>::type Packet;
-  // FIXME default copy constructors seems bugged with std::complex<>
-  EIGEN_STRONG_INLINE scalar_multiple_op(const scalar_multiple_op& other) : m_other(other.m_other) { }
-  EIGEN_STRONG_INLINE scalar_multiple_op(const Scalar& other) : m_other(other) { }
-  EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
-  { return internal::pmul(a, pset1<Packet>(m_other)); }
-  typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_multiple_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
-
-template<typename Scalar1, typename Scalar2>
-struct scalar_multiple2_op {
-  typedef typename scalar_product_traits<Scalar1,Scalar2>::ReturnType result_type;
-  EIGEN_STRONG_INLINE scalar_multiple2_op(const scalar_multiple2_op& other) : m_other(other.m_other) { }
-  EIGEN_STRONG_INLINE scalar_multiple2_op(const Scalar2& other) : m_other(other) { }
-  EIGEN_STRONG_INLINE result_type operator() (const Scalar1& a) const { return a * m_other; }
-  typename add_const_on_value_type<typename NumTraits<Scalar2>::Nested>::type m_other;
-};
-template<typename Scalar1,typename Scalar2>
-struct functor_traits<scalar_multiple2_op<Scalar1,Scalar2> >
-{ enum { Cost = NumTraits<Scalar1>::MulCost, PacketAccess = false }; };
-
-/** \internal
-  * \brief Template functor to divide a scalar by a fixed other one
-  *
-  * This functor is used to implement the quotient of a matrix by
-  * a scalar where the scalar type is not necessarily a floating point type.
-  *
-  * \sa class CwiseUnaryOp, MatrixBase::operator/
-  */
-template<typename Scalar>
-struct scalar_quotient1_op {
-  typedef typename packet_traits<Scalar>::type Packet;
-  // FIXME default copy constructors seems bugged with std::complex<>
-  EIGEN_STRONG_INLINE scalar_quotient1_op(const scalar_quotient1_op& other) : m_other(other.m_other) { }
-  EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other) : m_other(other) {}
-  EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
-  { return internal::pdiv(a, pset1<Packet>(m_other)); }
-  typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_quotient1_op<Scalar> >
-{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
-
-// nullary functors
-
-template<typename Scalar>
-struct scalar_constant_op {
-  typedef typename packet_traits<Scalar>::type Packet;
-  EIGEN_STRONG_INLINE scalar_constant_op(const scalar_constant_op& other) : m_other(other.m_other) { }
-  EIGEN_STRONG_INLINE scalar_constant_op(const Scalar& other) : m_other(other) { }
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Scalar operator() (Index, Index = 0) const { return m_other; }
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Packet packetOp(Index, Index = 0) const { return internal::pset1<Packet>(m_other); }
-  const Scalar m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_constant_op<Scalar> >
-// FIXME replace this packet test by a safe one
-{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::Vectorizable, IsRepeatable = true }; };
-
-template<typename Scalar> struct scalar_identity_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_identity_op)
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const { return row==col ? Scalar(1) : Scalar(0); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_identity_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = false, IsRepeatable = true }; };
-
-template <typename Scalar, bool RandomAccess> struct linspaced_op_impl;
-
-// linear access for packet ops:
-// 1) initialization
-//   base = [low, ..., low] + ([step, ..., step] * [-size, ..., 0])
-// 2) each step (where size is 1 for coeff access or PacketSize for packet access)
-//   base += [size*step, ..., size*step]
-//
-// TODO: Perhaps it's better to initialize lazily (so not in the constructor but in packetOp)
-//       in order to avoid the padd() in operator() ?
-template <typename Scalar>
-struct linspaced_op_impl<Scalar,false>
-{
-  typedef typename packet_traits<Scalar>::type Packet;
-
-  linspaced_op_impl(const Scalar& low, const Scalar& step) :
-  m_low(low), m_step(step),
-  m_packetStep(pset1<Packet>(packet_traits<Scalar>::size*step)),
-  m_base(padd(pset1<Packet>(low), pmul(pset1<Packet>(step),plset<Scalar>(-packet_traits<Scalar>::size)))) {}
-
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const 
-  { 
-    m_base = padd(m_base, pset1<Packet>(m_step));
-    return m_low+Scalar(i)*m_step; 
-  }
-
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Packet packetOp(Index) const { return m_base = padd(m_base,m_packetStep); }
-
-  const Scalar m_low;
-  const Scalar m_step;
-  const Packet m_packetStep;
-  mutable Packet m_base;
-};
-
-// random access for packet ops:
-// 1) each step
-//   [low, ..., low] + ( [step, ..., step] * ( [i, ..., i] + [0, ..., size] ) )
-template <typename Scalar>
-struct linspaced_op_impl<Scalar,true>
-{
-  typedef typename packet_traits<Scalar>::type Packet;
-
-  linspaced_op_impl(const Scalar& low, const Scalar& step) :
-  m_low(low), m_step(step),
-  m_lowPacket(pset1<Packet>(m_low)), m_stepPacket(pset1<Packet>(m_step)), m_interPacket(plset<Scalar>(0)) {}
-
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
-
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Packet packetOp(Index i) const
-  { return internal::padd(m_lowPacket, pmul(m_stepPacket, padd(pset1<Packet>(Scalar(i)),m_interPacket))); }
-
-  const Scalar m_low;
-  const Scalar m_step;
-  const Packet m_lowPacket;
-  const Packet m_stepPacket;
-  const Packet m_interPacket;
-};
-
-// ----- Linspace functor ----------------------------------------------------------------
-
-// Forward declaration (we default to random access which does not really give
-// us a speed gain when using packet access but it allows to use the functor in
-// nested expressions).
-template <typename Scalar, bool RandomAccess = true> struct linspaced_op;
-template <typename Scalar, bool RandomAccess> struct functor_traits< linspaced_op<Scalar,RandomAccess> >
-{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::HasSetLinear, IsRepeatable = true }; };
-template <typename Scalar, bool RandomAccess> struct linspaced_op
-{
-  typedef typename packet_traits<Scalar>::type Packet;
-  linspaced_op(const Scalar& low, const Scalar& high, DenseIndex num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/Scalar(num_steps-1))) {}
-
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); }
-
-  // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
-  // there row==0 and col is used for the actual iteration.
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const 
-  {
-    eigen_assert(col==0 || row==0);
-    return impl(col + row);
-  }
-
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Packet packetOp(Index i) const { return impl.packetOp(i); }
-
-  // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
-  // there row==0 and col is used for the actual iteration.
-  template<typename Index>
-  EIGEN_STRONG_INLINE const Packet packetOp(Index row, Index col) const
-  {
-    eigen_assert(col==0 || row==0);
-    return impl.packetOp(col + row);
-  }
-
-  // This proxy object handles the actual required temporaries, the different
-  // implementations (random vs. sequential access) as well as the
-  // correct piping to size 2/4 packet operations.
-  const linspaced_op_impl<Scalar,RandomAccess> impl;
-};
-
-// all functors allow linear access, except scalar_identity_op. So we fix here a quick meta
-// to indicate whether a functor allows linear access, just always answering 'yes' except for
-// scalar_identity_op.
-// FIXME move this to functor_traits adding a functor_default
-template<typename Functor> struct functor_has_linear_access { enum { ret = 1 }; };
-template<typename Scalar> struct functor_has_linear_access<scalar_identity_op<Scalar> > { enum { ret = 0 }; };
-
-// In Eigen, any binary op (Product, CwiseBinaryOp) require the Lhs and Rhs to have the same scalar type, except for multiplication
-// where the mixing of different types is handled by scalar_product_traits
-// In particular, real * complex<real> is allowed.
-// FIXME move this to functor_traits adding a functor_default
-template<typename Functor> struct functor_is_product_like { enum { ret = 0 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_quotient_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
-
-
-/** \internal
-  * \brief Template functor to add a scalar to a fixed other one
-  * \sa class CwiseUnaryOp, Array::operator+
-  */
-/* If you wonder why doing the pset1() in packetOp() is an optimization check scalar_multiple_op */
-template<typename Scalar>
-struct scalar_add_op {
-  typedef typename packet_traits<Scalar>::type Packet;
-  // FIXME default copy constructors seems bugged with std::complex<>
-  inline scalar_add_op(const scalar_add_op& other) : m_other(other.m_other) { }
-  inline scalar_add_op(const Scalar& other) : m_other(other) { }
-  inline Scalar operator() (const Scalar& a) const { return a + m_other; }
-  inline const Packet packetOp(const Packet& a) const
-  { return internal::padd(a, pset1<Packet>(m_other)); }
-  const Scalar m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_add_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
-
-/** \internal
-  * \brief Template functor to compute the square root of a scalar
-  * \sa class CwiseUnaryOp, Cwise::sqrt()
-  */
-template<typename Scalar> struct scalar_sqrt_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op)
-  inline const Scalar operator() (const Scalar& a) const { using std::sqrt; return sqrt(a); }
-  typedef typename packet_traits<Scalar>::type Packet;
-  inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_sqrt_op<Scalar> >
-{ enum {
-    Cost = 5 * NumTraits<Scalar>::MulCost,
-    PacketAccess = packet_traits<Scalar>::HasSqrt
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the cosine of a scalar
-  * \sa class CwiseUnaryOp, ArrayBase::cos()
-  */
-template<typename Scalar> struct scalar_cos_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op)
-  inline Scalar operator() (const Scalar& a) const { using std::cos; return cos(a); }
-  typedef typename packet_traits<Scalar>::type Packet;
-  inline Packet packetOp(const Packet& a) const { return internal::pcos(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_cos_op<Scalar> >
-{
-  enum {
-    Cost = 5 * NumTraits<Scalar>::MulCost,
-    PacketAccess = packet_traits<Scalar>::HasCos
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the sine of a scalar
-  * \sa class CwiseUnaryOp, ArrayBase::sin()
-  */
-template<typename Scalar> struct scalar_sin_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op)
-  inline const Scalar operator() (const Scalar& a) const { using std::sin; return sin(a); }
-  typedef typename packet_traits<Scalar>::type Packet;
-  inline Packet packetOp(const Packet& a) const { return internal::psin(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_sin_op<Scalar> >
-{
-  enum {
-    Cost = 5 * NumTraits<Scalar>::MulCost,
-    PacketAccess = packet_traits<Scalar>::HasSin
-  };
-};
-
-
-/** \internal
-  * \brief Template functor to compute the tan of a scalar
-  * \sa class CwiseUnaryOp, ArrayBase::tan()
-  */
-template<typename Scalar> struct scalar_tan_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op)
-  inline const Scalar operator() (const Scalar& a) const { using std::tan; return tan(a); }
-  typedef typename packet_traits<Scalar>::type Packet;
-  inline Packet packetOp(const Packet& a) const { return internal::ptan(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_tan_op<Scalar> >
-{
-  enum {
-    Cost = 5 * NumTraits<Scalar>::MulCost,
-    PacketAccess = packet_traits<Scalar>::HasTan
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the arc cosine of a scalar
-  * \sa class CwiseUnaryOp, ArrayBase::acos()
-  */
-template<typename Scalar> struct scalar_acos_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op)
-  inline const Scalar operator() (const Scalar& a) const { using std::acos; return acos(a); }
-  typedef typename packet_traits<Scalar>::type Packet;
-  inline Packet packetOp(const Packet& a) const { return internal::pacos(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_acos_op<Scalar> >
-{
-  enum {
-    Cost = 5 * NumTraits<Scalar>::MulCost,
-    PacketAccess = packet_traits<Scalar>::HasACos
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the arc sine of a scalar
-  * \sa class CwiseUnaryOp, ArrayBase::asin()
-  */
-template<typename Scalar> struct scalar_asin_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op)
-  inline const Scalar operator() (const Scalar& a) const { using std::asin; return asin(a); }
-  typedef typename packet_traits<Scalar>::type Packet;
-  inline Packet packetOp(const Packet& a) const { return internal::pasin(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_asin_op<Scalar> >
-{
-  enum {
-    Cost = 5 * NumTraits<Scalar>::MulCost,
-    PacketAccess = packet_traits<Scalar>::HasASin
-  };
-};
-
-/** \internal
-  * \brief Template functor to raise a scalar to a power
-  * \sa class CwiseUnaryOp, Cwise::pow
-  */
-template<typename Scalar>
-struct scalar_pow_op {
-  // FIXME default copy constructors seems bugged with std::complex<>
-  inline scalar_pow_op(const scalar_pow_op& other) : m_exponent(other.m_exponent) { }
-  inline scalar_pow_op(const Scalar& exponent) : m_exponent(exponent) {}
-  inline Scalar operator() (const Scalar& a) const { return numext::pow(a, m_exponent); }
-  const Scalar m_exponent;
-};
-template<typename Scalar>
-struct functor_traits<scalar_pow_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
-/** \internal
-  * \brief Template functor to compute the quotient between a scalar and array entries.
-  * \sa class CwiseUnaryOp, Cwise::inverse()
-  */
-template<typename Scalar>
-struct scalar_inverse_mult_op {
-  scalar_inverse_mult_op(const Scalar& other) : m_other(other) {}
-  inline Scalar operator() (const Scalar& a) const { return m_other / a; }
-  template<typename Packet>
-  inline const Packet packetOp(const Packet& a) const
-  { return internal::pdiv(pset1<Packet>(m_other),a); }
-  Scalar m_other;
-};
-
-/** \internal
-  * \brief Template functor to compute the inverse of a scalar
-  * \sa class CwiseUnaryOp, Cwise::inverse()
-  */
-template<typename Scalar>
-struct scalar_inverse_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_inverse_op)
-  inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; }
-  template<typename Packet>
-  inline const Packet packetOp(const Packet& a) const
-  { return internal::pdiv(pset1<Packet>(Scalar(1)),a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_inverse_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
-
-/** \internal
-  * \brief Template functor to compute the square of a scalar
-  * \sa class CwiseUnaryOp, Cwise::square()
-  */
-template<typename Scalar>
-struct scalar_square_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op)
-  inline Scalar operator() (const Scalar& a) const { return a*a; }
-  template<typename Packet>
-  inline const Packet packetOp(const Packet& a) const
-  { return internal::pmul(a,a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_square_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
-
-/** \internal
-  * \brief Template functor to compute the cube of a scalar
-  * \sa class CwiseUnaryOp, Cwise::cube()
-  */
-template<typename Scalar>
-struct scalar_cube_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op)
-  inline Scalar operator() (const Scalar& a) const { return a*a*a; }
-  template<typename Packet>
-  inline const Packet packetOp(const Packet& a) const
-  { return internal::pmul(a,pmul(a,a)); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_cube_op<Scalar> >
-{ enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
-
-// default functor traits for STL functors:
-
-template<typename T>
-struct functor_traits<std::multiplies<T> >
-{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::divides<T> >
-{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::plus<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::minus<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::negate<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::logical_or<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::logical_and<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::logical_not<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::greater<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::less<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::greater_equal<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::less_equal<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::equal_to<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::not_equal_to<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::binder2nd<T> >
-{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::binder1st<T> >
-{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::unary_negate<T> >
-{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::binary_negate<T> >
-{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
-
-#ifdef EIGEN_STDEXT_SUPPORT
-
-template<typename T0,typename T1>
-struct functor_traits<std::project1st<T0,T1> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct functor_traits<std::project2nd<T0,T1> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct functor_traits<std::select2nd<std::pair<T0,T1> > >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct functor_traits<std::select1st<std::pair<T0,T1> > >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct functor_traits<std::unary_compose<T0,T1> >
-{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost, PacketAccess = false }; };
-
-template<typename T0,typename T1,typename T2>
-struct functor_traits<std::binary_compose<T0,T1,T2> >
-{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost + functor_traits<T2>::Cost, PacketAccess = false }; };
-
-#endif // EIGEN_STDEXT_SUPPORT
-
-// allow to add new functors and specializations of functor_traits from outside Eigen.
-// this macro is really needed because functor_traits must be specialized after it is declared but before it is used...
-#ifdef EIGEN_FUNCTORS_PLUGIN
-#include EIGEN_FUNCTORS_PLUGIN
-#endif
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_FUNCTORS_H

Index: 3rd_party/eigen/Eigen/src/Core/Fuzzy.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Fuzzy.h
+++ 3rd_party/eigen/Eigen/src/Core/Fuzzy.h
@@ -17,58 +17,63 @@
 {
 
 template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
 struct isApprox_selector
 {
+  EIGEN_DEVICE_FUNC
   static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
   {
-    using std::min;
-    typename internal::nested<Derived,2>::type nested(x);
-    typename internal::nested<OtherDerived,2>::type otherNested(y);
-    return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
+    typename internal::nested_eval<Derived,2>::type nested(x);
+    typename internal::nested_eval<OtherDerived,2>::type otherNested(y);
+    return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * numext::mini(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
   }
 };
 
 template<typename Derived, typename OtherDerived>
 struct isApprox_selector<Derived, OtherDerived, true>
 {
+  EIGEN_DEVICE_FUNC
   static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&)
   {
     return x.matrix() == y.matrix();
   }
 };
 
 template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
 struct isMuchSmallerThan_object_selector
 {
+  EIGEN_DEVICE_FUNC
   static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
   {
     return x.cwiseAbs2().sum() <= numext::abs2(prec) * y.cwiseAbs2().sum();
   }
 };
 
 template<typename Derived, typename OtherDerived>
 struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
 {
+  EIGEN_DEVICE_FUNC
   static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&)
   {
     return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
   }
 };
 
 template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
 struct isMuchSmallerThan_scalar_selector
 {
+  EIGEN_DEVICE_FUNC
   static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec)
   {
     return x.cwiseAbs2().sum() <= numext::abs2(prec * y);
   }
 };
 
 template<typename Derived>
 struct isMuchSmallerThan_scalar_selector<Derived, true>
 {
+  EIGEN_DEVICE_FUNC
   static bool run(const Derived& x, const typename Derived::RealScalar&, const typename Derived::RealScalar&)
   {
     return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
   }
 };

Index: 3rd_party/eigen/Eigen/src/Core/GeneralProduct.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/GeneralProduct.h
+++ 3rd_party/eigen/Eigen/src/Core/GeneralProduct.h
@@ -9,33 +9,11 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERAL_PRODUCT_H
 #define EIGEN_GENERAL_PRODUCT_H
 
-namespace Eigen { 
-
-/** \class GeneralProduct
-  * \ingroup Core_Module
-  *
-  * \brief Expression of the product of two general matrices or vectors
-  *
-  * \param LhsNested the type used to store the left-hand side
-  * \param RhsNested the type used to store the right-hand side
-  * \param ProductMode the type of the product
-  *
-  * This class represents an expression of the product of two general matrices.
-  * We call a general matrix, a dense matrix with full storage. For instance,
-  * This excludes triangular, selfadjoint, and sparse matrices.
-  * It is the return type of the operator* between general matrices. Its template
-  * arguments are determined automatically by ProductReturnType. Therefore,
-  * GeneralProduct should never be used direclty. To determine the result type of a
-  * function which involves a matrix product, use ProductReturnType::Type.
-  *
-  * \sa ProductReturnType, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
-  */
-template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
-class GeneralProduct;
+namespace Eigen {
 
 enum {
   Large = 2,
   Small = 3
 };
@@ -45,11 +23,12 @@
 template<int Rows, int Cols, int Depth> struct product_type_selector;
 
 template<int Size, int MaxSize> struct product_size_category
 {
   enum { is_large = MaxSize == Dynamic ||
-                    Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
+                    Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD ||
+                    (Size==Dynamic && MaxSize>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD),
          value = is_large  ? Large
                : Size == 1 ? 1
                            : Small
   };
 };
@@ -57,19 +36,18 @@
 template<typename Lhs, typename Rhs> struct product_type
 {
   typedef typename remove_all<Lhs>::type _Lhs;
   typedef typename remove_all<Rhs>::type _Rhs;
   enum {
-    MaxRows  = _Lhs::MaxRowsAtCompileTime,
-    Rows  = _Lhs::RowsAtCompileTime,
-    MaxCols  = _Rhs::MaxColsAtCompileTime,
-    Cols  = _Rhs::ColsAtCompileTime,
-    MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
-                                           _Rhs::MaxRowsAtCompileTime),
-    Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
-                                        _Rhs::RowsAtCompileTime),
-    LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
+    MaxRows = traits<_Lhs>::MaxRowsAtCompileTime,
+    Rows    = traits<_Lhs>::RowsAtCompileTime,
+    MaxCols = traits<_Rhs>::MaxColsAtCompileTime,
+    Cols    = traits<_Rhs>::ColsAtCompileTime,
+    MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::MaxColsAtCompileTime,
+                                           traits<_Rhs>::MaxRowsAtCompileTime),
+    Depth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::ColsAtCompileTime,
+                                        traits<_Rhs>::RowsAtCompileTime)
   };
 
   // the splitting into different lines of code here, introducing the _select enums and the typedef below,
   // is to work around an internal compiler error with gcc 4.1 and 4.2.
 private:
@@ -80,11 +58,12 @@
   };
   typedef product_type_selector<rows_select, cols_select, depth_select> selector;
 
 public:
   enum {
-    value = selector::ret
+    value = selector::ret,
+    ret = selector::ret
   };
 #ifdef EIGEN_DEBUG_PRODUCT
   static void debug()
   {
       EIGEN_DEBUG_VAR(Rows);
@@ -96,16 +75,17 @@
       EIGEN_DEBUG_VAR(value);
   }
 #endif
 };
 
-
 /* The following allows to select the kind of product at compile time
  * based on the three dimensions of the product.
  * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
 // FIXME I'm not sure the current mapping is the ideal one.
 template<int M, int N>  struct product_type_selector<M,N,1>              { enum { ret = OuterProduct }; };
+template<int M>         struct product_type_selector<M, 1, 1>            { enum { ret = LazyCoeffBasedProductMode }; };
+template<int N>         struct product_type_selector<1, N, 1>            { enum { ret = LazyCoeffBasedProductMode }; };
 template<int Depth>     struct product_type_selector<1,    1,    Depth>  { enum { ret = InnerProduct }; };
 template<>              struct product_type_selector<1,    1,    1>      { enum { ret = InnerProduct }; };
 template<>              struct product_type_selector<Small,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
 template<>              struct product_type_selector<1,    Small,Small>  { enum { ret = CoeffBasedProductMode }; };
 template<>              struct product_type_selector<Small,Small,Small>  { enum { ret = CoeffBasedProductMode }; };
@@ -120,64 +100,16 @@
 template<>              struct product_type_selector<Small,1,    Large>  { enum { ret = CoeffBasedProductMode }; };
 template<>              struct product_type_selector<Small,Small,Large>  { enum { ret = GemmProduct }; };
 template<>              struct product_type_selector<Large,Small,Large>  { enum { ret = GemmProduct }; };
 template<>              struct product_type_selector<Small,Large,Large>  { enum { ret = GemmProduct }; };
 template<>              struct product_type_selector<Large,Large,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Large,Small,Small>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Small,Large,Small>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Small,Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small,Large,Small>  { enum { ret = CoeffBasedProductMode }; };
 template<>              struct product_type_selector<Large,Large,Small>  { enum { ret = GemmProduct }; };
 
 } // end namespace internal
 
-/** \class ProductReturnType
-  * \ingroup Core_Module
-  *
-  * \brief Helper class to get the correct and optimized returned type of operator*
-  *
-  * \param Lhs the type of the left-hand side
-  * \param Rhs the type of the right-hand side
-  * \param ProductMode the type of the product (determined automatically by internal::product_mode)
-  *
-  * This class defines the typename Type representing the optimized product expression
-  * between two matrix expressions. In practice, using ProductReturnType<Lhs,Rhs>::Type
-  * is the recommended way to define the result type of a function returning an expression
-  * which involve a matrix product. The class Product should never be
-  * used directly.
-  *
-  * \sa class Product, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
-  */
-template<typename Lhs, typename Rhs, int ProductType>
-struct ProductReturnType
-{
-  // TODO use the nested type to reduce instanciations ????
-//   typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
-//   typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
-
-  typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
-};
-
-template<typename Lhs, typename Rhs>
-struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
-{
-  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
-  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
-  typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
-};
-
-template<typename Lhs, typename Rhs>
-struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
-{
-  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
-  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
-  typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
-};
-
-// this is a workaround for sun CC
-template<typename Lhs, typename Rhs>
-struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
-{};
-
 /***********************************************************************
 *  Implementation of Inner Vector Vector Product
 ***********************************************************************/
 
 // FIXME : maybe the "inner product" could return a Scalar
@@ -185,123 +117,14 @@
 // Pro: more natural for the user
 // Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
 // product ends up to a row-vector times col-vector product... To tackle this use
 // case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
 
-namespace internal {
-
-template<typename Lhs, typename Rhs>
-struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
- : traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
-{};
-
-}
-
-template<typename Lhs, typename Rhs>
-class GeneralProduct<Lhs, Rhs, InnerProduct>
-  : internal::no_assignment_operator,
-    public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
-{
-    typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
-  public:
-    GeneralProduct(const Lhs& lhs, const Rhs& rhs)
-    {
-      EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
-        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-
-      Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
-    }
-
-    /** Convertion to scalar */
-    operator const typename Base::Scalar() const {
-      return Base::coeff(0,0);
-    }
-};
-
 /***********************************************************************
 *  Implementation of Outer Vector Vector Product
 ***********************************************************************/
 
-namespace internal {
-
-// Column major
-template<typename ProductType, typename Dest, typename Func>
-EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const false_type&)
-{
-  typedef typename Dest::Index Index;
-  // FIXME make sure lhs is sequentially stored
-  // FIXME not very good if rhs is real and lhs complex while alpha is real too
-  const Index cols = dest.cols();
-  for (Index j=0; j<cols; ++j)
-    func(dest.col(j), prod.rhs().coeff(0,j) * prod.lhs());
-}
-
-// Row major
-template<typename ProductType, typename Dest, typename Func>
-EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const true_type&) {
-  typedef typename Dest::Index Index;
-  // FIXME make sure rhs is sequentially stored
-  // FIXME not very good if lhs is real and rhs complex while alpha is real too
-  const Index rows = dest.rows();
-  for (Index i=0; i<rows; ++i)
-    func(dest.row(i), prod.lhs().coeff(i,0) * prod.rhs());
-}
-
-template<typename Lhs, typename Rhs>
-struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
- : traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
-{};
-
-}
-
-template<typename Lhs, typename Rhs>
-class GeneralProduct<Lhs, Rhs, OuterProduct>
-  : public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
-{
-    template<typename T> struct IsRowMajor : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
-    
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
-
-    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
-    {
-      EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
-        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-    }
-    
-    struct set  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived()  = src; } };
-    struct add  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } };
-    struct sub  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } };
-    struct adds {
-      Scalar m_scale;
-      adds(const Scalar& s) : m_scale(s) {}
-      template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const {
-        dst.const_cast_derived() += m_scale * src;
-      }
-    };
-    
-    template<typename Dest>
-    inline void evalTo(Dest& dest) const {
-      internal::outer_product_selector_run(*this, dest, set(), IsRowMajor<Dest>());
-    }
-    
-    template<typename Dest>
-    inline void addTo(Dest& dest) const {
-      internal::outer_product_selector_run(*this, dest, add(), IsRowMajor<Dest>());
-    }
-
-    template<typename Dest>
-    inline void subTo(Dest& dest) const {
-      internal::outer_product_selector_run(*this, dest, sub(), IsRowMajor<Dest>());
-    }
-
-    template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
-    {
-      internal::outer_product_selector_run(*this, dest, adds(alpha), IsRowMajor<Dest>());
-    }
-};
-
 /***********************************************************************
 *  Implementation of General Matrix Vector Product
 ***********************************************************************/
 
 /*  According to the shape/flags of the matrix we have to distinghish 3 different cases:
@@ -311,64 +134,17 @@
  *  Therefore we need a lower level meta selector.
  *  Furthermore, if the matrix is the rhs, then the product has to be transposed.
  */
 namespace internal {
 
-template<typename Lhs, typename Rhs>
-struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
- : traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
-{};
-
 template<int Side, int StorageOrder, bool BlasCompatible>
-struct gemv_selector;
+struct gemv_dense_selector;
 
 } // end namespace internal
 
-template<typename Lhs, typename Rhs>
-class GeneralProduct<Lhs, Rhs, GemvProduct>
-  : public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
-{
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
-
-    typedef typename Lhs::Scalar LhsScalar;
-    typedef typename Rhs::Scalar RhsScalar;
-
-    GeneralProduct(const Lhs& a_lhs, const Rhs& a_rhs) : Base(a_lhs,a_rhs)
-    {
-//       EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
-//         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-    }
-
-    enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
-    typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
-
-    template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
-    {
-      eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
-      internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
-                       bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
-    }
-};
-
 namespace internal {
 
-// The vector is on the left => transposition
-template<int StorageOrder, bool BlasCompatible>
-struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
-{
-  template<typename ProductType, typename Dest>
-  static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
-  {
-    Transpose<Dest> destT(dest);
-    enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
-    gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
-      ::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
-        (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
-  }
-};
-
 template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
 
 template<typename Scalar,int Size,int MaxSize>
 struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
 {
@@ -382,176 +158,214 @@
 };
 
 template<typename Scalar,int Size,int MaxSize>
 struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
 {
-  #if EIGEN_ALIGN_STATICALLY
-  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
+  enum {
+    ForceAlignment  = internal::packet_traits<Scalar>::Vectorizable,
+    PacketSize      = internal::packet_traits<Scalar>::size
+  };
+  #if EIGEN_MAX_STATIC_ALIGN_BYTES!=0
+  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0,EIGEN_PLAIN_ENUM_MIN(AlignedMax,PacketSize)> m_data;
   EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
   #else
   // Some architectures cannot align on the stack,
   // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
-  enum {
-    ForceAlignment  = internal::packet_traits<Scalar>::Vectorizable,
-    PacketSize      = internal::packet_traits<Scalar>::size
-  };
-  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
+  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?EIGEN_MAX_ALIGN_BYTES:0),0> m_data;
   EIGEN_STRONG_INLINE Scalar* data() {
     return ForceAlignment
-            ? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(15))) + 16)
+            ? reinterpret_cast<Scalar*>((internal::UIntPtr(m_data.array) & ~(std::size_t(EIGEN_MAX_ALIGN_BYTES-1))) + EIGEN_MAX_ALIGN_BYTES)
             : m_data.array;
   }
   #endif
 };
 
-template<> struct gemv_selector<OnTheRight,ColMajor,true>
-{
-  template<typename ProductType, typename Dest>
-  static inline void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
-  {
-    typedef typename ProductType::Index Index;
-    typedef typename ProductType::LhsScalar   LhsScalar;
-    typedef typename ProductType::RhsScalar   RhsScalar;
-    typedef typename ProductType::Scalar      ResScalar;
-    typedef typename ProductType::RealScalar  RealScalar;
-    typedef typename ProductType::ActualLhsType ActualLhsType;
-    typedef typename ProductType::ActualRhsType ActualRhsType;
-    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
-    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
-    typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
-
-    ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
-    ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
-
-    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
-                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
-
-    enum {
-      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
-      // on, the other hand it is good for the cache to pack the vector anyways...
-      EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
-      ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
-      MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
-    };
-
-    gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
-
-    bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
-    bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
-    
-    RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
-
-    ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
-                                                  evalToDest ? dest.data() : static_dest.data());
-    
-    if(!evalToDest)
-    {
-      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      int size = dest.size();
-      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      #endif
-      if(!alphaIsCompatible)
-      {
-        MappedDest(actualDestPtr, dest.size()).setZero();
-        compatibleAlpha = RhsScalar(1);
-      }
-      else
-        MappedDest(actualDestPtr, dest.size()) = dest;
-    }
-
-    general_matrix_vector_product
-      <Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
-        actualLhs.rows(), actualLhs.cols(),
-        actualLhs.data(), actualLhs.outerStride(),
-        actualRhs.data(), actualRhs.innerStride(),
-        actualDestPtr, 1,
-        compatibleAlpha);
-
-    if (!evalToDest)
-    {
-      if(!alphaIsCompatible)
-        dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
-      else
-        dest = MappedDest(actualDestPtr, dest.size());
-    }
-  }
-};
-
-template<> struct gemv_selector<OnTheRight,RowMajor,true>
-{
-  template<typename ProductType, typename Dest>
-  static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
-  {
-    typedef typename ProductType::LhsScalar LhsScalar;
-    typedef typename ProductType::RhsScalar RhsScalar;
-    typedef typename ProductType::Scalar    ResScalar;
-    typedef typename ProductType::Index Index;
-    typedef typename ProductType::ActualLhsType ActualLhsType;
-    typedef typename ProductType::ActualRhsType ActualRhsType;
-    typedef typename ProductType::_ActualRhsType _ActualRhsType;
-    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
-    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
-
-    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
-    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
-
-    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
-                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
-
-    enum {
-      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
-      // on, the other hand it is good for the cache to pack the vector anyways...
-      DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
-    };
-
-    gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
+// The vector is on the left => transposition
+template<int StorageOrder, bool BlasCompatible>
+struct gemv_dense_selector<OnTheLeft,StorageOrder,BlasCompatible>
+{
+  template<typename Lhs, typename Rhs, typename Dest>
+  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
+  {
+    Transpose<Dest> destT(dest);
+    enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
+    gemv_dense_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
+      ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
+  }
+};
+
+template<> struct gemv_dense_selector<OnTheRight,ColMajor,true>
+{
+  template<typename Lhs, typename Rhs, typename Dest>
+  static inline void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
+  {
+    typedef typename Lhs::Scalar   LhsScalar;
+    typedef typename Rhs::Scalar   RhsScalar;
+    typedef typename Dest::Scalar  ResScalar;
+    typedef typename Dest::RealScalar  RealScalar;
+    
+    typedef internal::blas_traits<Lhs> LhsBlasTraits;
+    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+    typedef internal::blas_traits<Rhs> RhsBlasTraits;
+    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+  
+    typedef Map<Matrix<ResScalar,Dynamic,1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax,internal::packet_traits<ResScalar>::size)> MappedDest;
+
+    ActualLhsType actualLhs = LhsBlasTraits::extract(lhs);
+    ActualRhsType actualRhs = RhsBlasTraits::extract(rhs);
+
+    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
+                                  * RhsBlasTraits::extractScalarFactor(rhs);
+
+    // make sure Dest is a compile-time vector type (bug 1166)
+    typedef typename conditional<Dest::IsVectorAtCompileTime, Dest, typename Dest::ColXpr>::type ActualDest;
+
+    enum {
+      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
+      // on, the other hand it is good for the cache to pack the vector anyways...
+      EvalToDestAtCompileTime = (ActualDest::InnerStrideAtCompileTime==1),
+      ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
+      MightCannotUseDest = (!EvalToDestAtCompileTime) || ComplexByReal
+    };
+
+    typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper;
+    typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
+    RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
+
+    if(!MightCannotUseDest)
+    {
+      // shortcut if we are sure to be able to use dest directly,
+      // this ease the compiler to generate cleaner and more optimzized code for most common cases
+      general_matrix_vector_product
+          <Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
+          actualLhs.rows(), actualLhs.cols(),
+          LhsMapper(actualLhs.data(), actualLhs.outerStride()),
+          RhsMapper(actualRhs.data(), actualRhs.innerStride()),
+          dest.data(), 1,
+          compatibleAlpha);
+    }
+    else
+    {
+      gemv_static_vector_if<ResScalar,ActualDest::SizeAtCompileTime,ActualDest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
+
+      const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
+      const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
+
+      ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
+                                                    evalToDest ? dest.data() : static_dest.data());
+
+      if(!evalToDest)
+      {
+        #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+        Index size = dest.size();
+        EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+        #endif
+        if(!alphaIsCompatible)
+        {
+          MappedDest(actualDestPtr, dest.size()).setZero();
+          compatibleAlpha = RhsScalar(1);
+        }
+        else
+          MappedDest(actualDestPtr, dest.size()) = dest;
+      }
+
+      general_matrix_vector_product
+          <Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
+          actualLhs.rows(), actualLhs.cols(),
+          LhsMapper(actualLhs.data(), actualLhs.outerStride()),
+          RhsMapper(actualRhs.data(), actualRhs.innerStride()),
+          actualDestPtr, 1,
+          compatibleAlpha);
+
+      if (!evalToDest)
+      {
+        if(!alphaIsCompatible)
+          dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size());
+        else
+          dest = MappedDest(actualDestPtr, dest.size());
+      }
+    }
+  }
+};
+
+template<> struct gemv_dense_selector<OnTheRight,RowMajor,true>
+{
+  template<typename Lhs, typename Rhs, typename Dest>
+  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
+  {
+    typedef typename Lhs::Scalar   LhsScalar;
+    typedef typename Rhs::Scalar   RhsScalar;
+    typedef typename Dest::Scalar  ResScalar;
+    
+    typedef internal::blas_traits<Lhs> LhsBlasTraits;
+    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+    typedef internal::blas_traits<Rhs> RhsBlasTraits;
+    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+    typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
+
+    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
+    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
+
+    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
+                                  * RhsBlasTraits::extractScalarFactor(rhs);
+
+    enum {
+      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
+      // on, the other hand it is good for the cache to pack the vector anyways...
+      DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1
+    };
+
+    gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
 
     ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
         DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
 
     if(!DirectlyUseRhs)
     {
       #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      int size = actualRhs.size();
+      Index size = actualRhs.size();
       EIGEN_DENSE_STORAGE_CTOR_PLUGIN
       #endif
-      Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
+      Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
     }
 
+    typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper;
+    typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper;
     general_matrix_vector_product
-      <Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
+        <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
         actualLhs.rows(), actualLhs.cols(),
-        actualLhs.data(), actualLhs.outerStride(),
-        actualRhsPtr, 1,
-        dest.data(), dest.innerStride(),
+        LhsMapper(actualLhs.data(), actualLhs.outerStride()),
+        RhsMapper(actualRhsPtr, 1),
+        dest.data(), dest.col(0).innerStride(), //NOTE  if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166)
         actualAlpha);
   }
 };
 
-template<> struct gemv_selector<OnTheRight,ColMajor,false>
-{
-  template<typename ProductType, typename Dest>
-  static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
-  {
-    typedef typename Dest::Index Index;
-    // TODO makes sure dest is sequentially stored in memory, otherwise use a temp
-    const Index size = prod.rhs().rows();
-    for(Index k=0; k<size; ++k)
-      dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
+template<> struct gemv_dense_selector<OnTheRight,ColMajor,false>
+{
+  template<typename Lhs, typename Rhs, typename Dest>
+  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
+  {
+    EIGEN_STATIC_ASSERT((!nested_eval<Lhs,1>::Evaluate),EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE);
+    // TODO if rhs is large enough it might be beneficial to make sure that dest is sequentially stored in memory, otherwise use a temp
+    typename nested_eval<Rhs,1>::type actual_rhs(rhs);
+    const Index size = rhs.rows();
+    for(Index k=0; k<size; ++k)
+      dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k);
   }
 };
 
-template<> struct gemv_selector<OnTheRight,RowMajor,false>
-{
-  template<typename ProductType, typename Dest>
-  static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
-  {
-    typedef typename Dest::Index Index;
-    // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
-    const Index rows = prod.rows();
-    for(Index i=0; i<rows; ++i)
-      dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
+template<> struct gemv_dense_selector<OnTheRight,RowMajor,false>
+{
+  template<typename Lhs, typename Rhs, typename Dest>
+  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
+  {
+    EIGEN_STATIC_ASSERT((!nested_eval<Lhs,1>::Evaluate),EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE);
+    typename nested_eval<Rhs,Lhs::RowsAtCompileTime>::type actual_rhs(rhs);
+    const Index rows = dest.rows();
+    for(Index i=0; i<rows; ++i)
+      dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum();
   }
 };
 
 } // end namespace internal
 
@@ -563,13 +377,15 @@
   *
   * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
   *
   * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
   */
+#ifndef __CUDACC__
+
 template<typename Derived>
 template<typename OtherDerived>
-inline const typename ProductReturnType<Derived, OtherDerived>::Type
+inline const Product<Derived, OtherDerived>
 MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
 {
   // A note regarding the function declaration: In MSVC, this function will sometimes
   // not be inlined since DenseStorage is an unwindable object for dynamic
   // matrices and product types are holding a member to store the result.
@@ -590,12 +406,15 @@
     INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
   EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
 #ifdef EIGEN_DEBUG_PRODUCT
   internal::product_type<Derived,OtherDerived>::debug();
 #endif
-  return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
+
+  return Product<Derived, OtherDerived>(derived(), other.derived());
 }
+
+#endif // __CUDACC__
 
 /** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
   *
   * The returned product will behave like any other expressions: the coefficients of the product will be
   * computed once at a time as requested. This might be useful in some extremely rare cases when only
@@ -606,11 +425,11 @@
   *
   * \sa operator*(const MatrixBase&)
   */
 template<typename Derived>
 template<typename OtherDerived>
-const typename LazyProductReturnType<Derived,OtherDerived>::Type
+const Product<Derived,OtherDerived,LazyProduct>
 MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
 {
   enum {
     ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
                    || OtherDerived::RowsAtCompileTime==Dynamic
@@ -625,11 +444,11 @@
     INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
   EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
     INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
   EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
 
-  return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
+  return Product<Derived,OtherDerived,LazyProduct>(derived(), other.derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_PRODUCT_H

Index: 3rd_party/eigen/Eigen/src/Core/GenericPacketMath.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/GenericPacketMath.h
+++ 3rd_party/eigen/Eigen/src/Core/GenericPacketMath.h
@@ -40,43 +40,70 @@
 #endif
 
 struct default_packet_traits
 {
   enum {
+    HasHalfPacket = 0,
+
     HasAdd    = 1,
     HasSub    = 1,
     HasMul    = 1,
     HasNegate = 1,
     HasAbs    = 1,
+    HasArg    = 0,
     HasAbs2   = 1,
     HasMin    = 1,
     HasMax    = 1,
     HasConj   = 1,
     HasSetLinear = 1,
+    HasBlend  = 0,
 
     HasDiv    = 0,
     HasSqrt   = 0,
+    HasRsqrt  = 0,
     HasExp    = 0,
     HasLog    = 0,
+    HasLog1p  = 0,
+    HasLog10  = 0,
     HasPow    = 0,
 
     HasSin    = 0,
     HasCos    = 0,
     HasTan    = 0,
     HasASin   = 0,
     HasACos   = 0,
-    HasATan   = 0
+    HasATan   = 0,
+    HasSinh   = 0,
+    HasCosh   = 0,
+    HasTanh   = 0,
+    HasLGamma = 0,
+    HasDiGamma = 0,
+    HasZeta = 0,
+    HasPolygamma = 0,
+    HasErf = 0,
+    HasErfc = 0,
+    HasIGamma = 0,
+    HasIGammac = 0,
+    HasBetaInc = 0,
+
+    HasRound  = 0,
+    HasFloor  = 0,
+    HasCeil   = 0,
+
+    HasSign   = 0
   };
 };
 
 template<typename T> struct packet_traits : default_packet_traits
 {
   typedef T type;
+  typedef T half;
   enum {
     Vectorizable = 0,
     size = 1,
-    AlignedOnScalar = 0
+    AlignedOnScalar = 0,
+    HasHalfPacket = 0
   };
   enum {
     HasAdd    = 0,
     HasSub    = 0,
     HasMul    = 0,
@@ -87,140 +114,244 @@
     HasMax    = 0,
     HasConj   = 0,
     HasSetLinear = 0
   };
 };
+
+template<typename T> struct packet_traits<const T> : packet_traits<T> { };
+
+template <typename Src, typename Tgt> struct type_casting_traits {
+  enum {
+    VectorizedCast = 0,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+
+/** \internal \returns static_cast<TgtType>(a) (coeff-wise) */
+template <typename SrcPacket, typename TgtPacket>
+EIGEN_DEVICE_FUNC inline TgtPacket
+pcast(const SrcPacket& a) {
+  return static_cast<TgtPacket>(a);
+}
+template <typename SrcPacket, typename TgtPacket>
+EIGEN_DEVICE_FUNC inline TgtPacket
+pcast(const SrcPacket& a, const SrcPacket& /*b*/) {
+  return static_cast<TgtPacket>(a);
+}
+
+template <typename SrcPacket, typename TgtPacket>
+EIGEN_DEVICE_FUNC inline TgtPacket
+pcast(const SrcPacket& a, const SrcPacket& /*b*/, const SrcPacket& /*c*/, const SrcPacket& /*d*/) {
+  return static_cast<TgtPacket>(a);
+}
 
 /** \internal \returns a + b (coeff-wise) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 padd(const Packet& a,
         const Packet& b) { return a+b; }
 
 /** \internal \returns a - b (coeff-wise) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 psub(const Packet& a,
         const Packet& b) { return a-b; }
 
 /** \internal \returns -a (coeff-wise) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pnegate(const Packet& a) { return -a; }
 
 /** \internal \returns conj(a) (coeff-wise) */
-template<typename Packet> inline Packet
+
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pconj(const Packet& a) { return numext::conj(a); }
 
 /** \internal \returns a * b (coeff-wise) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pmul(const Packet& a,
         const Packet& b) { return a*b; }
 
 /** \internal \returns a / b (coeff-wise) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pdiv(const Packet& a,
         const Packet& b) { return a/b; }
 
 /** \internal \returns the min of \a a and \a b  (coeff-wise) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pmin(const Packet& a,
-        const Packet& b) { using std::min; return (min)(a, b); }
+        const Packet& b) { return numext::mini(a, b); }
 
 /** \internal \returns the max of \a a and \a b  (coeff-wise) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pmax(const Packet& a,
-        const Packet& b) { using std::max; return (max)(a, b); }
+        const Packet& b) { return numext::maxi(a, b); }
 
 /** \internal \returns the absolute value of \a a */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pabs(const Packet& a) { using std::abs; return abs(a); }
 
+/** \internal \returns the phase angle of \a a */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+parg(const Packet& a) { using numext::arg; return arg(a); }
+
 /** \internal \returns the bitwise and of \a a and \a b */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pand(const Packet& a, const Packet& b) { return a & b; }
 
 /** \internal \returns the bitwise or of \a a and \a b */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 por(const Packet& a, const Packet& b) { return a | b; }
 
 /** \internal \returns the bitwise xor of \a a and \a b */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pxor(const Packet& a, const Packet& b) { return a ^ b; }
 
 /** \internal \returns the bitwise andnot of \a a and \a b */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pandnot(const Packet& a, const Packet& b) { return a & (!b); }
 
 /** \internal \returns a packet version of \a *from, from must be 16 bytes aligned */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pload(const typename unpacket_traits<Packet>::type* from) { return *from; }
 
 /** \internal \returns a packet version of \a *from, (un-aligned load) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 ploadu(const typename unpacket_traits<Packet>::type* from) { return *from; }
 
+/** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+pset1(const typename unpacket_traits<Packet>::type& a) { return a; }
+
+/** \internal \returns a packet with constant coefficients \a a[0], e.g.: (a[0],a[0],a[0],a[0]) */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+pload1(const typename unpacket_traits<Packet>::type  *a) { return pset1<Packet>(*a); }
+
 /** \internal \returns a packet with elements of \a *from duplicated.
-  * For instance, for a packet of 8 elements, 4 scalar will be read from \a *from and
-  * duplicated to form: {from[0],from[0],from[1],from[1],,from[2],from[2],,from[3],from[3]}
+  * For instance, for a packet of 8 elements, 4 scalars will be read from \a *from and
+  * duplicated to form: {from[0],from[0],from[1],from[1],from[2],from[2],from[3],from[3]}
   * Currently, this function is only used for scalar * complex products.
- */
-template<typename Packet> inline Packet
+  */
+template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet
 ploaddup(const typename unpacket_traits<Packet>::type* from) { return *from; }
 
-/** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */
-template<typename Packet> inline Packet
-pset1(const typename unpacket_traits<Packet>::type& a) { return a; }
+/** \internal \returns a packet with elements of \a *from quadrupled.
+  * For instance, for a packet of 8 elements, 2 scalars will be read from \a *from and
+  * replicated to form: {from[0],from[0],from[0],from[0],from[1],from[1],from[1],from[1]}
+  * Currently, this function is only used in matrix products.
+  * For packet-size smaller or equal to 4, this function is equivalent to pload1 
+  */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+ploadquad(const typename unpacket_traits<Packet>::type* from)
+{ return pload1<Packet>(from); }
+
+/** \internal equivalent to
+  * \code
+  * a0 = pload1(a+0);
+  * a1 = pload1(a+1);
+  * a2 = pload1(a+2);
+  * a3 = pload1(a+3);
+  * \endcode
+  * \sa pset1, pload1, ploaddup, pbroadcast2
+  */
+template<typename Packet> EIGEN_DEVICE_FUNC
+inline void pbroadcast4(const typename unpacket_traits<Packet>::type *a,
+                        Packet& a0, Packet& a1, Packet& a2, Packet& a3)
+{
+  a0 = pload1<Packet>(a+0);
+  a1 = pload1<Packet>(a+1);
+  a2 = pload1<Packet>(a+2);
+  a3 = pload1<Packet>(a+3);
+}
+
+/** \internal equivalent to
+  * \code
+  * a0 = pload1(a+0);
+  * a1 = pload1(a+1);
+  * \endcode
+  * \sa pset1, pload1, ploaddup, pbroadcast4
+  */
+template<typename Packet> EIGEN_DEVICE_FUNC
+inline void pbroadcast2(const typename unpacket_traits<Packet>::type *a,
+                        Packet& a0, Packet& a1)
+{
+  a0 = pload1<Packet>(a+0);
+  a1 = pload1<Packet>(a+1);
+}
 
 /** \internal \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */
-template<typename Scalar> inline typename packet_traits<Scalar>::type
-plset(const Scalar& a) { return a; }
+template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet
+plset(const typename unpacket_traits<Packet>::type& a) { return a; }
 
 /** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */
-template<typename Scalar, typename Packet> inline void pstore(Scalar* to, const Packet& from)
+template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstore(Scalar* to, const Packet& from)
 { (*to) = from; }
 
 /** \internal copy the packet \a from to \a *to, (un-aligned store) */
-template<typename Scalar, typename Packet> inline void pstoreu(Scalar* to, const Packet& from)
-{ (*to) = from; }
+template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstoreu(Scalar* to, const Packet& from)
+{  (*to) = from; }
+
+ template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, Index /*stride*/)
+ { return ploadu<Packet>(from); }
+
+ template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, Index /*stride*/)
+ { pstore(to, from); }
 
 /** \internal tries to do cache prefetching of \a addr */
-template<typename Scalar> inline void prefetch(const Scalar* addr)
+template<typename Scalar> EIGEN_DEVICE_FUNC inline void prefetch(const Scalar* addr)
 {
-#if !defined(_MSC_VER)
-__builtin_prefetch(addr);
+#ifdef __CUDA_ARCH__
+#if defined(__LP64__)
+  // 64-bit pointer operand constraint for inlined asm
+  asm(" prefetch.L1 [ %1 ];" : "=l"(addr) : "l"(addr));
+#else
+  // 32-bit pointer operand constraint for inlined asm
+  asm(" prefetch.L1 [ %1 ];" : "=r"(addr) : "r"(addr));
+#endif
+#elif (!EIGEN_COMP_MSVC) && (EIGEN_COMP_GNUC || EIGEN_COMP_CLANG || EIGEN_COMP_ICC)
+  __builtin_prefetch(addr);
 #endif
 }
 
 /** \internal \returns the first element of a packet */
-template<typename Packet> inline typename unpacket_traits<Packet>::type pfirst(const Packet& a)
+template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type pfirst(const Packet& a)
 { return a; }
 
 /** \internal \returns a packet where the element i contains the sum of the packet of \a vec[i] */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 preduxp(const Packet* vecs) { return vecs[0]; }
 
 /** \internal \returns the sum of the elements of \a a*/
-template<typename Packet> inline typename unpacket_traits<Packet>::type predux(const Packet& a)
+template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux(const Packet& a)
+{ return a; }
+
+/** \internal \returns the sum of the elements of \a a by block of 4 elements.
+  * For a packet {a0, a1, a2, a3, a4, a5, a6, a7}, it returns a half packet {a0+a4, a1+a5, a2+a6, a3+a7}
+  * For packet-size smaller or equal to 4, this boils down to a noop.
+  */
+template<typename Packet> EIGEN_DEVICE_FUNC inline
+typename conditional<(unpacket_traits<Packet>::size%8)==0,typename unpacket_traits<Packet>::half,Packet>::type
+predux_downto4(const Packet& a)
 { return a; }
 
 /** \internal \returns the product of the elements of \a a*/
-template<typename Packet> inline typename unpacket_traits<Packet>::type predux_mul(const Packet& a)
+template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_mul(const Packet& a)
 { return a; }
 
 /** \internal \returns the min of the elements of \a a*/
-template<typename Packet> inline typename unpacket_traits<Packet>::type predux_min(const Packet& a)
+template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_min(const Packet& a)
 { return a; }
 
 /** \internal \returns the max of the elements of \a a*/
-template<typename Packet> inline typename unpacket_traits<Packet>::type predux_max(const Packet& a)
+template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_max(const Packet& a)
 { return a; }
 
 /** \internal \returns the reversed elements of \a a*/
-template<typename Packet> inline Packet preverse(const Packet& a)
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet preverse(const Packet& a)
 { return a; }
 
-
 /** \internal \returns \a a with real and imaginary part flipped (for complex type only) */
-template<typename Packet> inline Packet pcplxflip(const Packet& a)
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet pcplxflip(const Packet& a)
 {
   // FIXME: uncomment the following in case we drop the internal imag and real functions.
 //   using std::imag;
 //   using std::real;
   return Packet(imag(a),real(a));
@@ -248,21 +379,63 @@
 
 /** \internal \returns the arc cosine of \a a (coeff-wise) */
 template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet pacos(const Packet& a) { using std::acos; return acos(a); }
 
+/** \internal \returns the arc tangent of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet patan(const Packet& a) { using std::atan; return atan(a); }
+
+/** \internal \returns the hyperbolic sine of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet psinh(const Packet& a) { using std::sinh; return sinh(a); }
+
+/** \internal \returns the hyperbolic cosine of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pcosh(const Packet& a) { using std::cosh; return cosh(a); }
+
+/** \internal \returns the hyperbolic tan of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet ptanh(const Packet& a) { using std::tanh; return tanh(a); }
+
 /** \internal \returns the exp of \a a (coeff-wise) */
 template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet pexp(const Packet& a) { using std::exp; return exp(a); }
 
 /** \internal \returns the log of \a a (coeff-wise) */
 template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet plog(const Packet& a) { using std::log; return log(a); }
 
+/** \internal \returns the log1p of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet plog1p(const Packet& a) { return numext::log1p(a); }
+
+/** \internal \returns the log10 of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet plog10(const Packet& a) { using std::log10; return log10(a); }
+
 /** \internal \returns the square-root of \a a (coeff-wise) */
 template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet psqrt(const Packet& a) { using std::sqrt; return sqrt(a); }
+
+/** \internal \returns the reciprocal square-root of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet prsqrt(const Packet& a) {
+  return pdiv(pset1<Packet>(1), psqrt(a));
+}
+
+/** \internal \returns the rounded value of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pround(const Packet& a) { using numext::round; return round(a); }
+
+/** \internal \returns the floor of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pfloor(const Packet& a) { using numext::floor; return floor(a); }
+
+/** \internal \returns the ceil of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pceil(const Packet& a) { using numext::ceil; return ceil(a); }
 
 /***************************************************************************
 * The following functions might not have to be overwritten for vectorized types
 ***************************************************************************/
 
@@ -273,37 +446,48 @@
 {
   pstore(to, pset1<Packet>(a));
 }
 
 /** \internal \returns a * b + c (coeff-wise) */
-template<typename Packet> inline Packet
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pmadd(const Packet&  a,
          const Packet&  b,
          const Packet&  c)
 { return padd(pmul(a, b),c); }
 
 /** \internal \returns a packet version of \a *from.
-  * If LoadMode equals #Aligned, \a from must be 16 bytes aligned */
-template<typename Packet, int LoadMode>
-inline Packet ploadt(const typename unpacket_traits<Packet>::type* from)
+  * The pointer \a from must be aligned on a \a Alignment bytes boundary. */
+template<typename Packet, int Alignment>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt(const typename unpacket_traits<Packet>::type* from)
 {
-  if(LoadMode == Aligned)
+  if(Alignment >= unpacket_traits<Packet>::alignment)
     return pload<Packet>(from);
   else
     return ploadu<Packet>(from);
 }
 
 /** \internal copy the packet \a from to \a *to.
-  * If StoreMode equals #Aligned, \a to must be 16 bytes aligned */
-template<typename Scalar, typename Packet, int LoadMode>
-inline void pstoret(Scalar* to, const Packet& from)
+  * The pointer \a from must be aligned on a \a Alignment bytes boundary. */
+template<typename Scalar, typename Packet, int Alignment>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret(Scalar* to, const Packet& from)
 {
-  if(LoadMode == Aligned)
+  if(Alignment >= unpacket_traits<Packet>::alignment)
     pstore(to, from);
   else
     pstoreu(to, from);
 }
+
+/** \internal \returns a packet version of \a *from.
+  * Unlike ploadt, ploadt_ro takes advantage of the read-only memory path on the
+  * hardware if available to speedup the loading of data that won't be modified
+  * by the current computation.
+  */
+template<typename Packet, int LoadMode>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt_ro(const typename unpacket_traits<Packet>::type* from)
+{
+  return ploadt<Packet, LoadMode>(from);
+}
 
 /** \internal default implementation of palign() allowing partial specialization */
 template<int Offset,typename PacketType>
 struct palign_impl
 {
@@ -333,18 +517,77 @@
 }
 
 /***************************************************************************
 * Fast complex products (GCC generates a function call which is very slow)
 ***************************************************************************/
+
+// Eigen+CUDA does not support complexes.
+#ifndef __CUDACC__
 
 template<> inline std::complex<float> pmul(const std::complex<float>& a, const std::complex<float>& b)
 { return std::complex<float>(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); }
 
 template<> inline std::complex<double> pmul(const std::complex<double>& a, const std::complex<double>& b)
 { return std::complex<double>(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); }
+
+#endif
+
+
+/***************************************************************************
+ * PacketBlock, that is a collection of N packets where the number of words
+ * in the packet is a multiple of N.
+***************************************************************************/
+template <typename Packet,int N=unpacket_traits<Packet>::size> struct PacketBlock {
+  Packet packet[N];
+};
+
+template<typename Packet> EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet,1>& /*kernel*/) {
+  // Nothing to do in the scalar case, i.e. a 1x1 matrix.
+}
+
+/***************************************************************************
+ * Selector, i.e. vector of N boolean values used to select (i.e. blend)
+ * words from 2 packets.
+***************************************************************************/
+template <size_t N> struct Selector {
+  bool select[N];
+};
+
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+pblend(const Selector<unpacket_traits<Packet>::size>& ifPacket, const Packet& thenPacket, const Packet& elsePacket) {
+  return ifPacket.select[0] ? thenPacket : elsePacket;
+}
+
+/** \internal \returns \a a with the first coefficient replaced by the scalar b */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+pinsertfirst(const Packet& a, typename unpacket_traits<Packet>::type b)
+{
+  // Default implementation based on pblend.
+  // It must be specialized for higher performance.
+  Selector<unpacket_traits<Packet>::size> mask;
+  mask.select[0] = true;
+  // This for loop should be optimized away by the compiler.
+  for(Index i=1; i<unpacket_traits<Packet>::size; ++i)
+    mask.select[i] = false;
+  return pblend(mask, pset1<Packet>(b), a);
+}
+
+/** \internal \returns \a a with the last coefficient replaced by the scalar b */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+pinsertlast(const Packet& a, typename unpacket_traits<Packet>::type b)
+{
+  // Default implementation based on pblend.
+  // It must be specialized for higher performance.
+  Selector<unpacket_traits<Packet>::size> mask;
+  // This for loop should be optimized away by the compiler.
+  for(Index i=0; i<unpacket_traits<Packet>::size-1; ++i)
+    mask.select[i] = false;
+  mask.select[unpacket_traits<Packet>::size-1] = true;
+  return pblend(mask, pset1<Packet>(b), a);
+}
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_GENERIC_PACKET_MATH_H
-

Index: 3rd_party/eigen/Eigen/src/Core/GlobalFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/GlobalFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/GlobalFunctions.h
@@ -1,24 +1,41 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2010-2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GLOBAL_FUNCTIONS_H
 #define EIGEN_GLOBAL_FUNCTIONS_H
 
-#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR) \
+#ifdef EIGEN_PARSED_BY_DOXYGEN
+
+#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR,DOC_OP,DOC_DETAILS) \
+  /** \returns an expression of the coefficient-wise DOC_OP of \a x
+
+    DOC_DETAILS
+
+    \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_##NAME">Math functions</a>, class CwiseUnaryOp
+    */ \
+  template<typename Derived> \
+  inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \
+  NAME(const Eigen::ArrayBase<Derived>& x);
+
+#else
+
+#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR,DOC_OP,DOC_DETAILS) \
   template<typename Derived> \
   inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \
-  NAME(const Eigen::ArrayBase<Derived>& x) { \
-    return x.derived(); \
+  (NAME)(const Eigen::ArrayBase<Derived>& x) { \
+    return Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived>(x.derived()); \
   }
+
+#endif // EIGEN_PARSED_BY_DOXYGEN
 
 #define EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(NAME,FUNCTOR) \
   \
   template<typename Derived> \
   struct NAME##_retval<ArrayBase<Derived> > \
@@ -28,58 +45,136 @@
   template<typename Derived> \
   struct NAME##_impl<ArrayBase<Derived> > \
   { \
     static inline typename NAME##_retval<ArrayBase<Derived> >::type run(const Eigen::ArrayBase<Derived>& x) \
     { \
-      return x.derived(); \
+      return typename NAME##_retval<ArrayBase<Derived> >::type(x.derived()); \
     } \
   };
-
 
 namespace Eigen
 {
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real,scalar_real_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(imag,scalar_imag_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(conj,scalar_conjugate_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sin,scalar_sin_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cos,scalar_cos_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan,scalar_tan_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp,scalar_exp_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log,scalar_log_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs,scalar_abs_op)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sqrt,scalar_sqrt_op)
-  
-  template<typename Derived>
-  inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar>, const Derived>
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real,scalar_real_op,real part,\sa ArrayBase::real)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(imag,scalar_imag_op,imaginary part,\sa ArrayBase::imag)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(conj,scalar_conjugate_op,complex conjugate,\sa ArrayBase::conjugate)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(inverse,scalar_inverse_op,inverse,\sa ArrayBase::inverse)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sin,scalar_sin_op,sine,\sa ArrayBase::sin)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cos,scalar_cos_op,cosine,\sa ArrayBase::cos)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan,scalar_tan_op,tangent,\sa ArrayBase::tan)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(atan,scalar_atan_op,arc-tangent,\sa ArrayBase::atan)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op,arc-sine,\sa ArrayBase::asin)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op,arc-consine,\sa ArrayBase::acos)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sinh,scalar_sinh_op,hyperbolic sine,\sa ArrayBase::sinh)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cosh,scalar_cosh_op,hyperbolic cosine,\sa ArrayBase::cosh)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tanh,scalar_tanh_op,hyperbolic tangent,\sa ArrayBase::tanh)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(lgamma,scalar_lgamma_op,natural logarithm of the gamma function,\sa ArrayBase::lgamma)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(digamma,scalar_digamma_op,derivative of lgamma,\sa ArrayBase::digamma)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(erf,scalar_erf_op,error function,\sa ArrayBase::erf)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(erfc,scalar_erfc_op,complement error function,\sa ArrayBase::erfc)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp,scalar_exp_op,exponential,\sa ArrayBase::exp)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log,scalar_log_op,natural logarithm,\sa Eigen::log10 DOXCOMMA ArrayBase::log)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log1p,scalar_log1p_op,natural logarithm of 1 plus the value,\sa ArrayBase::log1p)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log10,scalar_log10_op,base 10 logarithm,\sa Eigen::log DOXCOMMA ArrayBase::log)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs,scalar_abs_op,absolute value,\sa ArrayBase::abs DOXCOMMA MatrixBase::cwiseAbs)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs2,scalar_abs2_op,squared absolute value,\sa ArrayBase::abs2 DOXCOMMA MatrixBase::cwiseAbs2)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(arg,scalar_arg_op,complex argument,\sa ArrayBase::arg)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sqrt,scalar_sqrt_op,square root,\sa ArrayBase::sqrt DOXCOMMA MatrixBase::cwiseSqrt)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(rsqrt,scalar_rsqrt_op,reciprocal square root,\sa ArrayBase::rsqrt)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(square,scalar_square_op,square (power 2),\sa Eigen::abs2 DOXCOMMA Eigen::pow DOXCOMMA ArrayBase::square)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cube,scalar_cube_op,cube (power 3),\sa Eigen::pow DOXCOMMA ArrayBase::cube)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(round,scalar_round_op,nearest integer,\sa Eigen::floor DOXCOMMA Eigen::ceil DOXCOMMA ArrayBase::round)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(floor,scalar_floor_op,nearest integer not greater than the giben value,\sa Eigen::ceil DOXCOMMA ArrayBase::floor)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(ceil,scalar_ceil_op,nearest integer not less than the giben value,\sa Eigen::floor DOXCOMMA ArrayBase::ceil)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isnan,scalar_isnan_op,not-a-number test,\sa Eigen::isinf DOXCOMMA Eigen::isfinite DOXCOMMA ArrayBase::isnan)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isinf,scalar_isinf_op,infinite value test,\sa Eigen::isnan DOXCOMMA Eigen::isfinite DOXCOMMA ArrayBase::isinf)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isfinite,scalar_isfinite_op,finite value test,\sa Eigen::isinf DOXCOMMA Eigen::isnan DOXCOMMA ArrayBase::isfinite)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sign,scalar_sign_op,sign (or 0),\sa ArrayBase::sign)
+  
+  /** \returns an expression of the coefficient-wise power of \a x to the given constant \a exponent.
+    *
+    * \tparam ScalarExponent is the scalar type of \a exponent. It must be compatible with the scalar type of the given expression (\c Derived::Scalar).
+    *
+    * \sa ArrayBase::pow()
+    *
+    * \relates ArrayBase
+    */
+#ifdef EIGEN_PARSED_BY_DOXYGEN
+  template<typename Derived,typename ScalarExponent>
+  inline const CwiseBinaryOp<internal::scalar_pow_op<Derived::Scalar,ScalarExponent>,Derived,Constant<ScalarExponent> >
+  pow(const Eigen::ArrayBase<Derived>& x, const ScalarExponent& exponent);
+#else
+  template<typename Derived,typename ScalarExponent>
+  inline typename internal::enable_if<   !(internal::is_same<typename Derived::Scalar,ScalarExponent>::value) && EIGEN_SCALAR_BINARY_SUPPORTED(pow,typename Derived::Scalar,ScalarExponent),
+          const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,ScalarExponent,pow) >::type
+  pow(const Eigen::ArrayBase<Derived>& x, const ScalarExponent& exponent) {
+    return x.derived().pow(exponent);
+  }
+
+  template<typename Derived>
+  inline const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,typename Derived::Scalar,pow)
   pow(const Eigen::ArrayBase<Derived>& x, const typename Derived::Scalar& exponent) {
     return x.derived().pow(exponent);
   }
+#endif
 
-  template<typename Derived>
-  inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived>
-  pow(const Eigen::ArrayBase<Derived>& x, const Eigen::ArrayBase<Derived>& exponents) 
+  /** \returns an expression of the coefficient-wise power of \a x to the given array of \a exponents.
+    *
+    * This function computes the coefficient-wise power.
+    *
+    * Example: \include Cwise_array_power_array.cpp
+    * Output: \verbinclude Cwise_array_power_array.out
+    * 
+    * \sa ArrayBase::pow()
+    *
+    * \relates ArrayBase
+    */
+  template<typename Derived,typename ExponentDerived>
+  inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar, typename ExponentDerived::Scalar>, const Derived, const ExponentDerived>
+  pow(const Eigen::ArrayBase<Derived>& x, const Eigen::ArrayBase<ExponentDerived>& exponents) 
   {
-    return Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived>(
+    return Eigen::CwiseBinaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar, typename ExponentDerived::Scalar>, const Derived, const ExponentDerived>(
       x.derived(),
       exponents.derived()
     );
   }
   
-  /**
-  * \brief Component-wise division of a scalar by array elements.
-  **/
-  template <typename Derived>
-  inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived>
-    operator/(const typename Derived::Scalar& s, const Eigen::ArrayBase<Derived>& a)
-  {
-    return Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived>(
-      a.derived(),
-      Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>(s)  
-    );
-  }
+  /** \returns an expression of the coefficient-wise power of the scalar \a x to the given array of \a exponents.
+    *
+    * This function computes the coefficient-wise power between a scalar and an array of exponents.
+    *
+    * \tparam Scalar is the scalar type of \a x. It must be compatible with the scalar type of the given array expression (\c Derived::Scalar).
+    *
+    * Example: \include Cwise_scalar_power_array.cpp
+    * Output: \verbinclude Cwise_scalar_power_array.out
+    * 
+    * \sa ArrayBase::pow()
+    *
+    * \relates ArrayBase
+    */
+#ifdef EIGEN_PARSED_BY_DOXYGEN
+  template<typename Scalar,typename Derived>
+  inline const CwiseBinaryOp<internal::scalar_pow_op<Scalar,Derived::Scalar>,Constant<Scalar>,Derived>
+  pow(const Scalar& x,const Eigen::ArrayBase<Derived>& x);
+#else
+  template<typename Scalar, typename Derived>
+  inline typename internal::enable_if<   !(internal::is_same<typename Derived::Scalar,Scalar>::value) && EIGEN_SCALAR_BINARY_SUPPORTED(pow,Scalar,typename Derived::Scalar),
+          const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,Derived,pow) >::type
+  pow(const Scalar& x, const Eigen::ArrayBase<Derived>& exponents)
+  {
+    return EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,Derived,pow)(
+            typename internal::plain_constant_type<Derived,Scalar>::type(exponents.rows(), exponents.cols(), x), exponents.derived() );
+  }
+
+  template<typename Derived>
+  inline const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(typename Derived::Scalar,Derived,pow)
+  pow(const typename Derived::Scalar& x, const Eigen::ArrayBase<Derived>& exponents)
+  {
+    return EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(typename Derived::Scalar,Derived,pow)(
+      typename internal::plain_constant_type<Derived,typename Derived::Scalar>::type(exponents.rows(), exponents.cols(), x), exponents.derived() );
+  }
+#endif
+
 
   namespace internal
   {
     EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real,scalar_real_op)
     EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(imag,scalar_imag_op)

Index: 3rd_party/eigen/Eigen/src/Core/IO.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/IO.h
+++ 3rd_party/eigen/Eigen/src/Core/IO.h
@@ -47,18 +47,22 @@
   *
   * \sa DenseBase::format(), class WithFormat
   */
 struct IOFormat
 {
-  /** Default contructor, see class IOFormat for the meaning of the parameters */
+  /** Default constructor, see class IOFormat for the meaning of the parameters */
   IOFormat(int _precision = StreamPrecision, int _flags = 0,
     const std::string& _coeffSeparator = " ",
     const std::string& _rowSeparator = "\n", const std::string& _rowPrefix="", const std::string& _rowSuffix="",
     const std::string& _matPrefix="", const std::string& _matSuffix="")
   : matPrefix(_matPrefix), matSuffix(_matSuffix), rowPrefix(_rowPrefix), rowSuffix(_rowSuffix), rowSeparator(_rowSeparator),
     rowSpacer(""), coeffSeparator(_coeffSeparator), precision(_precision), flags(_flags)
   {
+    // TODO check if rowPrefix, rowSuffix or rowSeparator contains a newline
+    // don't add rowSpacer if columns are not to be aligned
+    if((flags & DontAlignCols))
+      return;
     int i = int(matSuffix.length())-1;
     while (i>=0 && matSuffix[i]!='\n')
     {
       rowSpacer += ' ';
       i--;
@@ -74,11 +78,11 @@
 /** \class WithFormat
   * \ingroup Core_Module
   *
   * \brief Pseudo expression providing matrix output with given format
   *
-  * \param ExpressionType the type of the object on which IO stream operations are performed
+  * \tparam ExpressionType the type of the object on which IO stream operations are performed
   *
   * This class represents an expression with stream operators controlled by a given IOFormat.
   * It is the return type of DenseBase::format()
   * and most of the time this is the only way it is used.
   *
@@ -99,55 +103,27 @@
     {
       return internal::print_matrix(s, wf.m_matrix.eval(), wf.m_format);
     }
 
   protected:
-    const typename ExpressionType::Nested m_matrix;
+    typename ExpressionType::Nested m_matrix;
     IOFormat m_format;
 };
 
-/** \returns a WithFormat proxy object allowing to print a matrix the with given
-  * format \a fmt.
-  *
-  * See class IOFormat for some examples.
-  *
-  * \sa class IOFormat, class WithFormat
-  */
-template<typename Derived>
-inline const WithFormat<Derived>
-DenseBase<Derived>::format(const IOFormat& fmt) const
-{
-  return WithFormat<Derived>(derived(), fmt);
-}
-
 namespace internal {
 
-template<typename Scalar, bool IsInteger>
-struct significant_decimals_default_impl
-{
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  static inline int run()
-  {
-    using std::ceil;
-    using std::log;
-    return cast<RealScalar,int>(ceil(-log(NumTraits<RealScalar>::epsilon())/log(RealScalar(10))));
-  }
-};
-
-template<typename Scalar>
-struct significant_decimals_default_impl<Scalar, true>
-{
-  static inline int run()
-  {
-    return 0;
-  }
-};
-
-template<typename Scalar>
-struct significant_decimals_impl
-  : significant_decimals_default_impl<Scalar, NumTraits<Scalar>::IsInteger>
-{};
+// NOTE: This helper is kept for backward compatibility with previous code specializing
+//       this internal::significant_decimals_impl structure. In the future we should directly
+//       call digits10() which has been introduced in July 2016 in 3.3.
+template<typename Scalar>
+struct significant_decimals_impl
+{
+  static inline int run()
+  {
+    return NumTraits<Scalar>::digits10();
+  }
+};
 
 /** \internal
   * print the matrix \a _m to the output stream \a s using the output format \a fmt */
 template<typename Derived>
 std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt)
@@ -158,11 +134,10 @@
     return s;
   }
   
   typename Derived::Nested m = _m;
   typedef typename Derived::Scalar Scalar;
-  typedef typename Derived::Index Index;
 
   Index width = 0;
 
   std::streamsize explicit_precision;
   if(fmt.precision == StreamPrecision)

ADDED   3rd_party/eigen/Eigen/src/Core/Inverse.h
Index: 3rd_party/eigen/Eigen/src/Core/Inverse.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Inverse.h
+++ 3rd_party/eigen/Eigen/src/Core/Inverse.h
@@ -0,0 +1,118 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_INVERSE_H
+#define EIGEN_INVERSE_H
+
+namespace Eigen { 
+
+template<typename XprType,typename StorageKind> class InverseImpl;
+
+namespace internal {
+
+template<typename XprType>
+struct traits<Inverse<XprType> >
+  : traits<typename XprType::PlainObject>
+{
+  typedef typename XprType::PlainObject PlainObject;
+  typedef traits<PlainObject> BaseTraits;
+  enum {
+    Flags = BaseTraits::Flags & RowMajorBit
+  };
+};
+
+} // end namespace internal
+
+/** \class Inverse
+  *
+  * \brief Expression of the inverse of another expression
+  *
+  * \tparam XprType the type of the expression we are taking the inverse
+  *
+  * This class represents an abstract expression of A.inverse()
+  * and most of the time this is the only way it is used.
+  *
+  */
+template<typename XprType>
+class Inverse : public InverseImpl<XprType,typename internal::traits<XprType>::StorageKind>
+{
+public:
+  typedef typename XprType::StorageIndex StorageIndex;
+  typedef typename XprType::PlainObject                       PlainObject;
+  typedef typename XprType::Scalar                            Scalar;
+  typedef typename internal::ref_selector<XprType>::type      XprTypeNested;
+  typedef typename internal::remove_all<XprTypeNested>::type  XprTypeNestedCleaned;
+  typedef typename internal::ref_selector<Inverse>::type Nested;
+  typedef typename internal::remove_all<XprType>::type NestedExpression;
+  
+  explicit EIGEN_DEVICE_FUNC Inverse(const XprType &xpr)
+    : m_xpr(xpr)
+  {}
+
+  EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
+  EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
+
+  EIGEN_DEVICE_FUNC const XprTypeNestedCleaned& nestedExpression() const { return m_xpr; }
+
+protected:
+  XprTypeNested m_xpr;
+};
+
+// Generic API dispatcher
+template<typename XprType, typename StorageKind>
+class InverseImpl
+  : public internal::generic_xpr_base<Inverse<XprType> >::type
+{
+public:
+  typedef typename internal::generic_xpr_base<Inverse<XprType> >::type Base;
+  typedef typename XprType::Scalar Scalar;
+private:
+
+  Scalar coeff(Index row, Index col) const;
+  Scalar coeff(Index i) const;
+};
+
+namespace internal {
+
+/** \internal
+  * \brief Default evaluator for Inverse expression.
+  * 
+  * This default evaluator for Inverse expression simply evaluate the inverse into a temporary
+  * by a call to internal::call_assignment_no_alias.
+  * Therefore, inverse implementers only have to specialize Assignment<Dst,Inverse<...>, ...> for
+  * there own nested expression.
+  *
+  * \sa class Inverse
+  */
+template<typename ArgType>
+struct unary_evaluator<Inverse<ArgType> >
+  : public evaluator<typename Inverse<ArgType>::PlainObject>
+{
+  typedef Inverse<ArgType> InverseType;
+  typedef typename InverseType::PlainObject PlainObject;
+  typedef evaluator<PlainObject> Base;
+  
+  enum { Flags = Base::Flags | EvalBeforeNestingBit };
+
+  unary_evaluator(const InverseType& inv_xpr)
+    : m_result(inv_xpr.rows(), inv_xpr.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    internal::call_assignment_no_alias(m_result, inv_xpr);
+  }
+  
+protected:
+  PlainObject m_result;
+};
+  
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_INVERSE_H

Index: 3rd_party/eigen/Eigen/src/Core/Map.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Map.h
+++ 3rd_party/eigen/Eigen/src/Core/Map.h
@@ -10,18 +10,40 @@
 
 #ifndef EIGEN_MAP_H
 #define EIGEN_MAP_H
 
 namespace Eigen { 
+
+namespace internal {
+template<typename PlainObjectType, int MapOptions, typename StrideType>
+struct traits<Map<PlainObjectType, MapOptions, StrideType> >
+  : public traits<PlainObjectType>
+{
+  typedef traits<PlainObjectType> TraitsBase;
+  enum {
+    InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
+                             ? int(PlainObjectType::InnerStrideAtCompileTime)
+                             : int(StrideType::InnerStrideAtCompileTime),
+    OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
+                             ? int(PlainObjectType::OuterStrideAtCompileTime)
+                             : int(StrideType::OuterStrideAtCompileTime),
+    Alignment = int(MapOptions)&int(AlignedMask),
+    Flags0 = TraitsBase::Flags & (~NestByRefBit),
+    Flags = is_lvalue<PlainObjectType>::value ? int(Flags0) : (int(Flags0) & ~LvalueBit)
+  };
+private:
+  enum { Options }; // Expressions don't have Options
+};
+}
 
 /** \class Map
   * \ingroup Core_Module
   *
   * \brief A matrix or vector expression mapping an existing array of data.
   *
   * \tparam PlainObjectType the equivalent matrix type of the mapped data
-  * \tparam MapOptions specifies whether the pointer is \c #Aligned, or \c #Unaligned.
+  * \tparam MapOptions specifies the pointer alignment in bytes. It can be: \c #Aligned128, , \c #Aligned64, \c #Aligned32, \c #Aligned16, \c #Aligned8 or \c #Unaligned.
   *                The default is \c #Unaligned.
   * \tparam StrideType optionally specifies strides. By default, Map assumes the memory layout
   *                   of an ordinary, contiguous array. This can be overridden by specifying strides.
   *                   The type passed here must be a specialization of the Stride template, see examples below.
   *
@@ -61,70 +83,30 @@
   *
   * This class is the return type of PlainObjectBase::Map() but can also be used directly.
   *
   * \sa PlainObjectBase::Map(), \ref TopicStorageOrders
   */
-
-namespace internal {
-template<typename PlainObjectType, int MapOptions, typename StrideType>
-struct traits<Map<PlainObjectType, MapOptions, StrideType> >
-  : public traits<PlainObjectType>
-{
-  typedef traits<PlainObjectType> TraitsBase;
-  typedef typename PlainObjectType::Index Index;
-  typedef typename PlainObjectType::Scalar Scalar;
-  enum {
-    InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
-                             ? int(PlainObjectType::InnerStrideAtCompileTime)
-                             : int(StrideType::InnerStrideAtCompileTime),
-    OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
-                             ? int(PlainObjectType::OuterStrideAtCompileTime)
-                             : int(StrideType::OuterStrideAtCompileTime),
-    HasNoInnerStride = InnerStrideAtCompileTime == 1,
-    HasNoOuterStride = StrideType::OuterStrideAtCompileTime == 0,
-    HasNoStride = HasNoInnerStride && HasNoOuterStride,
-    IsAligned = bool(EIGEN_ALIGN) && ((int(MapOptions)&Aligned)==Aligned),
-    IsDynamicSize = PlainObjectType::SizeAtCompileTime==Dynamic,
-    KeepsPacketAccess = bool(HasNoInnerStride)
-                        && ( bool(IsDynamicSize)
-                           || HasNoOuterStride
-                           || ( OuterStrideAtCompileTime!=Dynamic
-                           && ((static_cast<int>(sizeof(Scalar))*OuterStrideAtCompileTime)%16)==0 ) ),
-    Flags0 = TraitsBase::Flags & (~NestByRefBit),
-    Flags1 = IsAligned ? (int(Flags0) | AlignedBit) : (int(Flags0) & ~AlignedBit),
-    Flags2 = (bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime))
-           ? int(Flags1) : int(Flags1 & ~LinearAccessBit),
-    Flags3 = is_lvalue<PlainObjectType>::value ? int(Flags2) : (int(Flags2) & ~LvalueBit),
-    Flags = KeepsPacketAccess ? int(Flags3) : (int(Flags3) & ~PacketAccessBit)
-  };
-private:
-  enum { Options }; // Expressions don't have Options
-};
-}
-
 template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
   : public MapBase<Map<PlainObjectType, MapOptions, StrideType> >
 {
   public:
 
     typedef MapBase<Map> Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Map)
 
     typedef typename Base::PointerType PointerType;
-#if EIGEN2_SUPPORT_STAGE <= STAGE30_FULL_EIGEN3_API
-    typedef const Scalar* PointerArgType;
-    inline PointerType cast_to_pointer_type(PointerArgType ptr) { return const_cast<PointerType>(ptr); }
-#else
     typedef PointerType PointerArgType;
+    EIGEN_DEVICE_FUNC
     inline PointerType cast_to_pointer_type(PointerArgType ptr) { return ptr; }
-#endif
 
+    EIGEN_DEVICE_FUNC
     inline Index innerStride() const
     {
       return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
     }
 
+    EIGEN_DEVICE_FUNC
     inline Index outerStride() const
     {
       return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
            : IsVectorAtCompileTime ? this->size()
            : int(Flags)&RowMajorBit ? this->cols()
@@ -132,39 +114,42 @@
     }
 
     /** Constructor in the fixed-size case.
       *
       * \param dataPtr pointer to the array to map
-      * \param a_stride optional Stride object, passing the strides.
+      * \param stride optional Stride object, passing the strides.
       */
-    inline Map(PointerArgType dataPtr, const StrideType& a_stride = StrideType())
-      : Base(cast_to_pointer_type(dataPtr)), m_stride(a_stride)
+    EIGEN_DEVICE_FUNC
+    explicit inline Map(PointerArgType dataPtr, const StrideType& stride = StrideType())
+      : Base(cast_to_pointer_type(dataPtr)), m_stride(stride)
     {
       PlainObjectType::Base::_check_template_params();
     }
 
     /** Constructor in the dynamic-size vector case.
       *
       * \param dataPtr pointer to the array to map
-      * \param a_size the size of the vector expression
-      * \param a_stride optional Stride object, passing the strides.
+      * \param size the size of the vector expression
+      * \param stride optional Stride object, passing the strides.
       */
-    inline Map(PointerArgType dataPtr, Index a_size, const StrideType& a_stride = StrideType())
-      : Base(cast_to_pointer_type(dataPtr), a_size), m_stride(a_stride)
+    EIGEN_DEVICE_FUNC
+    inline Map(PointerArgType dataPtr, Index size, const StrideType& stride = StrideType())
+      : Base(cast_to_pointer_type(dataPtr), size), m_stride(stride)
     {
       PlainObjectType::Base::_check_template_params();
     }
 
     /** Constructor in the dynamic-size matrix case.
       *
       * \param dataPtr pointer to the array to map
-      * \param nbRows the number of rows of the matrix expression
-      * \param nbCols the number of columns of the matrix expression
-      * \param a_stride optional Stride object, passing the strides.
+      * \param rows the number of rows of the matrix expression
+      * \param cols the number of columns of the matrix expression
+      * \param stride optional Stride object, passing the strides.
       */
-    inline Map(PointerArgType dataPtr, Index nbRows, Index nbCols, const StrideType& a_stride = StrideType())
-      : Base(cast_to_pointer_type(dataPtr), nbRows, nbCols), m_stride(a_stride)
+    EIGEN_DEVICE_FUNC
+    inline Map(PointerArgType dataPtr, Index rows, Index cols, const StrideType& stride = StrideType())
+      : Base(cast_to_pointer_type(dataPtr), rows, cols), m_stride(stride)
     {
       PlainObjectType::Base::_check_template_params();
     }
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
@@ -171,22 +156,9 @@
 
   protected:
     StrideType m_stride;
 };
 
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-inline Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>
-  ::Array(const Scalar *data)
-{
-  this->_set_noalias(Eigen::Map<const Array>(data));
-}
-
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-inline Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>
-  ::Matrix(const Scalar *data)
-{
-  this->_set_noalias(Eigen::Map<const Matrix>(data));
-}
 
 } // end namespace Eigen
 
 #endif // EIGEN_MAP_H

Index: 3rd_party/eigen/Eigen/src/Core/MapBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/MapBase.h
+++ 3rd_party/eigen/Eigen/src/Core/MapBase.h
@@ -10,19 +10,29 @@
 
 #ifndef EIGEN_MAPBASE_H
 #define EIGEN_MAPBASE_H
 
 #define EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) \
-      EIGEN_STATIC_ASSERT((int(internal::traits<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
+      EIGEN_STATIC_ASSERT((int(internal::evaluator<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
                           YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT)
 
 namespace Eigen { 
 
-/** \class MapBase
-  * \ingroup Core_Module
+/** \ingroup Core_Module
+  *
+  * \brief Base class for dense Map and Block expression with direct access
+  *
+  * This base class provides the const low-level accessors (e.g. coeff, coeffRef) of dense
+  * Map and Block objects with direct access.
+  * Typical users do not have to directly deal with this class.
+  *
+  * This class can be extended by through the macro plugin \c EIGEN_MAPBASE_PLUGIN.
+  * See \link TopicCustomizing_Plugins customizing Eigen \endlink for details.
   *
-  * \brief Base class for Map and Block expression with direct access
+  * The \c Derived class has to provide the following two methods describing the memory layout:
+  *  \code Index innerStride() const; \endcode
+  *  \code Index outerStride() const; \endcode
   *
   * \sa class Map, class Block
   */
 template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
   : public internal::dense_xpr_base<Derived>::type
@@ -35,11 +45,10 @@
       ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
       SizeAtCompileTime = Base::SizeAtCompileTime
     };
 
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
     typedef typename internal::conditional<
                          bool(internal::is_lvalue<Derived>::value),
@@ -74,99 +83,137 @@
     // bug 217 - compile error on ICC 11.1
     using Base::operator=;
 
     typedef typename Base::CoeffReturnType CoeffReturnType;
 
-    inline Index rows() const { return m_rows.value(); }
-    inline Index cols() const { return m_cols.value(); }
+    /** \copydoc DenseBase::rows() */
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_rows.value(); }
+    /** \copydoc DenseBase::cols() */
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_cols.value(); }
 
     /** Returns a pointer to the first coefficient of the matrix or vector.
       *
       * \note When addressing this data, make sure to honor the strides returned by innerStride() and outerStride().
       *
       * \sa innerStride(), outerStride()
       */
-    inline const Scalar* data() const { return m_data; }
+    EIGEN_DEVICE_FUNC inline const Scalar* data() const { return m_data; }
 
+    /** \copydoc PlainObjectBase::coeff(Index,Index) const */
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeff(Index rowId, Index colId) const
     {
       return m_data[colId * colStride() + rowId * rowStride()];
     }
 
+    /** \copydoc PlainObjectBase::coeff(Index) const */
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeff(Index index) const
     {
       EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
       return m_data[index * innerStride()];
     }
 
+    /** \copydoc PlainObjectBase::coeffRef(Index,Index) const */
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
       return this->m_data[colId * colStride() + rowId * rowStride()];
     }
 
+    /** \copydoc PlainObjectBase::coeffRef(Index) const */
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index index) const
     {
       EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
       return this->m_data[index * innerStride()];
     }
 
+    /** \internal */
     template<int LoadMode>
     inline PacketScalar packet(Index rowId, Index colId) const
     {
       return internal::ploadt<PacketScalar, LoadMode>
                (m_data + (colId * colStride() + rowId * rowStride()));
     }
 
+    /** \internal */
     template<int LoadMode>
     inline PacketScalar packet(Index index) const
     {
       EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
       return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
     }
 
-    inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
+    /** \internal Constructor for fixed size matrices or vectors */
+    EIGEN_DEVICE_FUNC
+    explicit inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
     {
       EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-      checkSanity();
+      checkSanity<Derived>();
     }
 
+    /** \internal Constructor for dynamically sized vectors */
+    EIGEN_DEVICE_FUNC
     inline MapBase(PointerType dataPtr, Index vecSize)
             : m_data(dataPtr),
               m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)),
               m_cols(ColsAtCompileTime == Dynamic ? vecSize : Index(ColsAtCompileTime))
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
       eigen_assert(vecSize >= 0);
       eigen_assert(dataPtr == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == vecSize);
-      checkSanity();
+      checkSanity<Derived>();
     }
 
-    inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols)
-            : m_data(dataPtr), m_rows(nbRows), m_cols(nbCols)
+    /** \internal Constructor for dynamically sized matrices */
+    EIGEN_DEVICE_FUNC
+    inline MapBase(PointerType dataPtr, Index rows, Index cols)
+            : m_data(dataPtr), m_rows(rows), m_cols(cols)
     {
       eigen_assert( (dataPtr == 0)
-              || (   nbRows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
-                  && nbCols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols)));
-      checkSanity();
+              || (   rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
+                  && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)));
+      checkSanity<Derived>();
     }
+
+    #ifdef EIGEN_MAPBASE_PLUGIN
+    #include EIGEN_MAPBASE_PLUGIN
+    #endif
 
   protected:
 
-    void checkSanity() const
-    {
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(internal::traits<Derived>::Flags&PacketAccessBit,
-                                        internal::inner_stride_at_compile_time<Derived>::ret==1),
-                          PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
-      eigen_assert(EIGEN_IMPLIES(internal::traits<Derived>::Flags&AlignedBit, (size_t(m_data) % 16) == 0)
-                   && "data is not aligned");
-    }
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    void checkSanity(typename internal::enable_if<(internal::traits<T>::Alignment>0),void*>::type = 0) const
+    {
+#if EIGEN_MAX_ALIGN_BYTES>0
+      eigen_assert((   ((internal::UIntPtr(m_data) % internal::traits<Derived>::Alignment) == 0)
+                    || (cols() * rows() * innerStride() * sizeof(Scalar)) < internal::traits<Derived>::Alignment ) && "data is not aligned");
+#endif
+    }
+
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    void checkSanity(typename internal::enable_if<internal::traits<T>::Alignment==0,void*>::type = 0) const
+    {}
 
     PointerType m_data;
     const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
     const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
 };
 
+/** \ingroup Core_Module
+  *
+  * \brief Base class for non-const dense Map and Block expression with direct access
+  *
+  * This base class provides the non-const low-level accessors (e.g. coeff and coeffRef) of
+  * dense Map and Block objects with direct access.
+  * It inherits MapBase<Derived, ReadOnlyAccessors> which defines the const variant for reading specific entries.
+  *
+  * \sa class Map, class Block
+  */
 template<typename Derived> class MapBase<Derived, WriteAccessors>
   : public MapBase<Derived, ReadOnlyAccessors>
 {
     typedef MapBase<Derived, ReadOnlyAccessors> ReadOnlyMapBase;
   public:
@@ -173,11 +220,11 @@
 
     typedef MapBase<Derived, ReadOnlyAccessors> Base;
 
     typedef typename Base::Scalar Scalar;
     typedef typename Base::PacketScalar PacketScalar;
-    typedef typename Base::Index Index;
+    typedef typename Base::StorageIndex StorageIndex;
     typedef typename Base::PointerType PointerType;
 
     using Base::derived;
     using Base::rows;
     using Base::cols;
@@ -194,18 +241,22 @@
                     internal::is_lvalue<Derived>::value,
                     Scalar,
                     const Scalar
                   >::type ScalarWithConstIfNotLvalue;
 
+    EIGEN_DEVICE_FUNC
     inline const Scalar* data() const { return this->m_data; }
+    EIGEN_DEVICE_FUNC
     inline ScalarWithConstIfNotLvalue* data() { return this->m_data; } // no const-cast here so non-const-correct code will give a compile error
 
+    EIGEN_DEVICE_FUNC
     inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col)
     {
       return this->m_data[col * colStride() + row * rowStride()];
     }
 
+    EIGEN_DEVICE_FUNC
     inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
     {
       EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
       return this->m_data[index * innerStride()];
     }
@@ -223,14 +274,15 @@
       EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
       internal::pstoret<Scalar, PacketScalar, StoreMode>
                 (this->m_data + index * innerStride(), val);
     }
 
-    explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
-    inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
-    inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) : Base(dataPtr, nbRows, nbCols) {}
+    EIGEN_DEVICE_FUNC explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
+    EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
+    EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index rows, Index cols) : Base(dataPtr, rows, cols) {}
 
+    EIGEN_DEVICE_FUNC
     Derived& operator=(const MapBase& other)
     {
       ReadOnlyMapBase::Base::operator=(other);
       return derived();
     }

Index: 3rd_party/eigen/Eigen/src/Core/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/MathFunctions.h
@@ -7,16 +7,30 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATHFUNCTIONS_H
 #define EIGEN_MATHFUNCTIONS_H
+
+// source: http://www.geom.uiuc.edu/~huberty/math5337/groupe/digits.html
+// TODO this should better be moved to NumTraits
+#define EIGEN_PI 3.141592653589793238462643383279502884197169399375105820974944592307816406L
+
 
 namespace Eigen {
+
+// On WINCE, std::abs is defined for int only, so let's defined our own overloads:
+// This issue has been confirmed with MSVC 2008 only, but the issue might exist for more recent versions too.
+#if EIGEN_OS_WINCE && EIGEN_COMP_MSVC && EIGEN_COMP_MSVC<=1500
+long        abs(long        x) { return (labs(x));  }
+double      abs(double      x) { return (fabs(x));  }
+float       abs(float       x) { return (fabsf(x)); }
+long double abs(long double x) { return (fabsl(x)); }
+#endif
 
 namespace internal {
 
-/** \internal \struct global_math_functions_filtering_base
+/** \internal \class global_math_functions_filtering_base
   *
   * What it does:
   * Defines a typedef 'type' as follows:
   * - if type T has a member typedef Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl, then
   *   global_math_functions_filtering_base<T>::type is a typedef for it.
@@ -60,10 +74,11 @@
 
 template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
 struct real_default_impl
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar run(const Scalar& x)
   {
     return x;
   }
 };
@@ -70,34 +85,48 @@
 
 template<typename Scalar>
 struct real_default_impl<Scalar,true>
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar run(const Scalar& x)
   {
     using std::real;
     return real(x);
   }
 };
 
 template<typename Scalar> struct real_impl : real_default_impl<Scalar> {};
+
+#ifdef __CUDA_ARCH__
+template<typename T>
+struct real_impl<std::complex<T> >
+{
+  typedef T RealScalar;
+  EIGEN_DEVICE_FUNC
+  static inline T run(const std::complex<T>& x)
+  {
+    return x.real();
+  }
+};
+#endif
 
 template<typename Scalar>
 struct real_retval
 {
   typedef typename NumTraits<Scalar>::Real type;
 };
-
 
 /****************************************************************************
 * Implementation of imag                                                 *
 ****************************************************************************/
 
 template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
 struct imag_default_impl
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar run(const Scalar&)
   {
     return RealScalar(0);
   }
 };
@@ -104,18 +133,32 @@
 
 template<typename Scalar>
 struct imag_default_impl<Scalar,true>
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar run(const Scalar& x)
   {
     using std::imag;
     return imag(x);
   }
 };
 
 template<typename Scalar> struct imag_impl : imag_default_impl<Scalar> {};
+
+#ifdef __CUDA_ARCH__
+template<typename T>
+struct imag_impl<std::complex<T> >
+{
+  typedef T RealScalar;
+  EIGEN_DEVICE_FUNC
+  static inline T run(const std::complex<T>& x)
+  {
+    return x.imag();
+  }
+};
+#endif
 
 template<typename Scalar>
 struct imag_retval
 {
   typedef typename NumTraits<Scalar>::Real type;
@@ -127,14 +170,16 @@
 
 template<typename Scalar>
 struct real_ref_impl
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar& run(Scalar& x)
   {
     return reinterpret_cast<RealScalar*>(&x)[0];
   }
+  EIGEN_DEVICE_FUNC
   static inline const RealScalar& run(const Scalar& x)
   {
     return reinterpret_cast<const RealScalar*>(&x)[0];
   }
 };
@@ -151,27 +196,31 @@
 
 template<typename Scalar, bool IsComplex>
 struct imag_ref_default_impl
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar& run(Scalar& x)
   {
     return reinterpret_cast<RealScalar*>(&x)[1];
   }
+  EIGEN_DEVICE_FUNC
   static inline const RealScalar& run(const Scalar& x)
   {
     return reinterpret_cast<RealScalar*>(&x)[1];
   }
 };
 
 template<typename Scalar>
 struct imag_ref_default_impl<Scalar, false>
 {
+  EIGEN_DEVICE_FUNC
   static inline Scalar run(Scalar&)
   {
     return Scalar(0);
   }
+  EIGEN_DEVICE_FUNC
   static inline const Scalar run(const Scalar&)
   {
     return Scalar(0);
   }
 };
@@ -190,19 +239,21 @@
 ****************************************************************************/
 
 template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
 struct conj_impl
 {
+  EIGEN_DEVICE_FUNC
   static inline Scalar run(const Scalar& x)
   {
     return x;
   }
 };
 
 template<typename Scalar>
 struct conj_impl<Scalar,true>
 {
+  EIGEN_DEVICE_FUNC
   static inline Scalar run(const Scalar& x)
   {
     using std::conj;
     return conj(x);
   }
@@ -216,28 +267,42 @@
 
 /****************************************************************************
 * Implementation of abs2                                                 *
 ****************************************************************************/
 
-template<typename Scalar>
-struct abs2_impl
+template<typename Scalar,bool IsComplex>
+struct abs2_impl_default
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar run(const Scalar& x)
   {
     return x*x;
   }
 };
 
-template<typename RealScalar>
-struct abs2_impl<std::complex<RealScalar> >
+template<typename Scalar>
+struct abs2_impl_default<Scalar, true> // IsComplex
 {
-  static inline RealScalar run(const std::complex<RealScalar>& x)
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
+  static inline RealScalar run(const Scalar& x)
   {
     return real(x)*real(x) + imag(x)*imag(x);
   }
 };
+
+template<typename Scalar>
+struct abs2_impl
+{
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
+  static inline RealScalar run(const Scalar& x)
+  {
+    return abs2_impl_default<Scalar,NumTraits<Scalar>::IsComplex>::run(x);
+  }
+};
 
 template<typename Scalar>
 struct abs2_retval
 {
   typedef typename NumTraits<Scalar>::Real type;
@@ -249,23 +314,25 @@
 
 template<typename Scalar, bool IsComplex>
 struct norm1_default_impl
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline RealScalar run(const Scalar& x)
   {
-    using std::abs;
+    EIGEN_USING_STD_MATH(abs);
     return abs(real(x)) + abs(imag(x));
   }
 };
 
 template<typename Scalar>
 struct norm1_default_impl<Scalar, false>
 {
+  EIGEN_DEVICE_FUNC
   static inline Scalar run(const Scalar& x)
   {
-    using std::abs;
+    EIGEN_USING_STD_MATH(abs);
     return abs(x);
   }
 };
 
 template<typename Scalar>
@@ -285,20 +352,26 @@
 struct hypot_impl
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
   static inline RealScalar run(const Scalar& x, const Scalar& y)
   {
-    using std::max;
-    using std::min;
-    using std::abs;
-    using std::sqrt;
+    EIGEN_USING_STD_MATH(abs);
+    EIGEN_USING_STD_MATH(sqrt);
     RealScalar _x = abs(x);
     RealScalar _y = abs(y);
-    RealScalar p = (max)(_x, _y);
-    if(p==RealScalar(0)) return 0;
-    RealScalar q = (min)(_x, _y);
-    RealScalar qp = q/p;
+    Scalar p, qp;
+    if(_x>_y)
+    {
+      p = _x;
+      qp = _y / p;
+    }
+    else
+    {
+      p = _y;
+      qp = _x / p;
+    }
+    if(p==RealScalar(0)) return RealScalar(0);
     return p * sqrt(RealScalar(1) + qp*qp);
   }
 };
 
 template<typename Scalar>
@@ -312,87 +385,166 @@
 ****************************************************************************/
 
 template<typename OldType, typename NewType>
 struct cast_impl
 {
+  EIGEN_DEVICE_FUNC
   static inline NewType run(const OldType& x)
   {
     return static_cast<NewType>(x);
   }
 };
 
 // here, for once, we're plainly returning NewType: we don't want cast to do weird things.
 
 template<typename OldType, typename NewType>
+EIGEN_DEVICE_FUNC
 inline NewType cast(const OldType& x)
 {
   return cast_impl<OldType, NewType>::run(x);
 }
 
 /****************************************************************************
-* Implementation of atanh2                                                *
+* Implementation of round                                                   *
+****************************************************************************/
+
+#if EIGEN_HAS_CXX11_MATH
+  template<typename Scalar>
+  struct round_impl {
+    static inline Scalar run(const Scalar& x)
+    {
+      EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
+      using std::round;
+      return round(x);
+    }
+  };
+#else
+  template<typename Scalar>
+  struct round_impl
+  {
+    static inline Scalar run(const Scalar& x)
+    {
+      EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
+      EIGEN_USING_STD_MATH(floor);
+      EIGEN_USING_STD_MATH(ceil);
+      return (x > Scalar(0)) ? floor(x + Scalar(0.5)) : ceil(x - Scalar(0.5));
+    }
+  };
+#endif
+
+template<typename Scalar>
+struct round_retval
+{
+  typedef Scalar type;
+};
+
+/****************************************************************************
+* Implementation of arg                                                     *
+****************************************************************************/
+
+#if EIGEN_HAS_CXX11_MATH
+  template<typename Scalar>
+  struct arg_impl {
+    static inline Scalar run(const Scalar& x)
+    {
+      EIGEN_USING_STD_MATH(arg);
+      return arg(x);
+    }
+  };
+#else
+  template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
+  struct arg_default_impl
+  {
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    EIGEN_DEVICE_FUNC
+    static inline RealScalar run(const Scalar& x)
+    {
+      return (x < Scalar(0)) ? Scalar(EIGEN_PI) : Scalar(0); }
+  };
+
+  template<typename Scalar>
+  struct arg_default_impl<Scalar,true>
+  {
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    EIGEN_DEVICE_FUNC
+    static inline RealScalar run(const Scalar& x)
+    {
+      EIGEN_USING_STD_MATH(arg);
+      return arg(x);
+    }
+  };
+
+  template<typename Scalar> struct arg_impl : arg_default_impl<Scalar> {};
+#endif
+
+template<typename Scalar>
+struct arg_retval
+{
+  typedef typename NumTraits<Scalar>::Real type;
+};
+
+/****************************************************************************
+* Implementation of log1p                                                   *
 ****************************************************************************/
 
-template<typename Scalar, bool IsInteger>
-struct atanh2_default_impl
-{
-  typedef Scalar retval;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  static inline Scalar run(const Scalar& x, const Scalar& y)
-  {
-    using std::abs;
-    using std::log;
-    using std::sqrt;
-    Scalar z = x / y;
-    if (y == Scalar(0) || abs(z) > sqrt(NumTraits<RealScalar>::epsilon()))
-      return RealScalar(0.5) * log((y + x) / (y - x));
-    else
-      return z + z*z*z / RealScalar(3);
-  }
-};
+namespace std_fallback {
+  // fallback log1p implementation in case there is no log1p(Scalar) function in namespace of Scalar,
+  // or that there is no suitable std::log1p function available
+  template<typename Scalar>
+  EIGEN_DEVICE_FUNC inline Scalar log1p(const Scalar& x) {
+    EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    EIGEN_USING_STD_MATH(log);
+    Scalar x1p = RealScalar(1) + x;
+    return ( x1p == Scalar(1) ) ? x : x * ( log(x1p) / (x1p - RealScalar(1)) );
+  }
+}
 
 template<typename Scalar>
-struct atanh2_default_impl<Scalar, true>
-{
-  static inline Scalar run(const Scalar&, const Scalar&)
+struct log1p_impl {
+  static inline Scalar run(const Scalar& x)
   {
     EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
-    return Scalar(0);
+    #if EIGEN_HAS_CXX11_MATH
+    using std::log1p;
+    #endif
+    using std_fallback::log1p;
+    return log1p(x);
   }
 };
 
-template<typename Scalar>
-struct atanh2_impl : atanh2_default_impl<Scalar, NumTraits<Scalar>::IsInteger> {};
 
 template<typename Scalar>
-struct atanh2_retval
+struct log1p_retval
 {
   typedef Scalar type;
 };
 
 /****************************************************************************
 * Implementation of pow                                                  *
 ****************************************************************************/
 
-template<typename Scalar, bool IsInteger>
-struct pow_default_impl
+template<typename ScalarX,typename ScalarY, bool IsInteger = NumTraits<ScalarX>::IsInteger&&NumTraits<ScalarY>::IsInteger>
+struct pow_impl
 {
-  typedef Scalar retval;
-  static inline Scalar run(const Scalar& x, const Scalar& y)
+  //typedef Scalar retval;
+  typedef typename ScalarBinaryOpTraits<ScalarX,ScalarY,internal::scalar_pow_op<ScalarX,ScalarY> >::ReturnType result_type;
+  static EIGEN_DEVICE_FUNC inline result_type run(const ScalarX& x, const ScalarY& y)
   {
-    using std::pow;
+    EIGEN_USING_STD_MATH(pow);
     return pow(x, y);
   }
 };
 
-template<typename Scalar>
-struct pow_default_impl<Scalar, true>
+template<typename ScalarX,typename ScalarY>
+struct pow_impl<ScalarX,ScalarY, true>
 {
-  static inline Scalar run(Scalar x, Scalar y)
+  typedef ScalarX result_type;
+  static EIGEN_DEVICE_FUNC inline ScalarX run(ScalarX x, ScalarY y)
   {
-    Scalar res(1);
-    eigen_assert(!NumTraits<Scalar>::IsSigned || y >= 0);
+    ScalarX res(1);
+    eigen_assert(!NumTraits<ScalarY>::IsSigned || y >= 0);
     if(y & 1) res *= x;
     y >>= 1;
     while(y)
     {
       x *= x;
@@ -401,19 +553,10 @@
     }
     return res;
   }
 };
 
-template<typename Scalar>
-struct pow_impl : pow_default_impl<Scalar, NumTraits<Scalar>::IsInteger> {};
-
-template<typename Scalar>
-struct pow_retval
-{
-  typedef Scalar type;
-};
-
 /****************************************************************************
 * Implementation of random                                               *
 ****************************************************************************/
 
 template<typename Scalar,
@@ -445,72 +588,85 @@
     return run(Scalar(NumTraits<Scalar>::IsSigned ? -1 : 0), Scalar(1));
   }
 };
 
 enum {
-  floor_log2_terminate,
-  floor_log2_move_up,
-  floor_log2_move_down,
-  floor_log2_bogus
+  meta_floor_log2_terminate,
+  meta_floor_log2_move_up,
+  meta_floor_log2_move_down,
+  meta_floor_log2_bogus
 };
 
-template<unsigned int n, int lower, int upper> struct floor_log2_selector
+template<unsigned int n, int lower, int upper> struct meta_floor_log2_selector
 {
   enum { middle = (lower + upper) / 2,
-         value = (upper <= lower + 1) ? int(floor_log2_terminate)
-               : (n < (1 << middle)) ? int(floor_log2_move_down)
-               : (n==0) ? int(floor_log2_bogus)
-               : int(floor_log2_move_up)
+         value = (upper <= lower + 1) ? int(meta_floor_log2_terminate)
+               : (n < (1 << middle)) ? int(meta_floor_log2_move_down)
+               : (n==0) ? int(meta_floor_log2_bogus)
+               : int(meta_floor_log2_move_up)
   };
 };
 
 template<unsigned int n,
          int lower = 0,
          int upper = sizeof(unsigned int) * CHAR_BIT - 1,
-         int selector = floor_log2_selector<n, lower, upper>::value>
-struct floor_log2 {};
+         int selector = meta_floor_log2_selector<n, lower, upper>::value>
+struct meta_floor_log2 {};
+
+template<unsigned int n, int lower, int upper>
+struct meta_floor_log2<n, lower, upper, meta_floor_log2_move_down>
+{
+  enum { value = meta_floor_log2<n, lower, meta_floor_log2_selector<n, lower, upper>::middle>::value };
+};
 
 template<unsigned int n, int lower, int upper>
-struct floor_log2<n, lower, upper, floor_log2_move_down>
+struct meta_floor_log2<n, lower, upper, meta_floor_log2_move_up>
 {
-  enum { value = floor_log2<n, lower, floor_log2_selector<n, lower, upper>::middle>::value };
+  enum { value = meta_floor_log2<n, meta_floor_log2_selector<n, lower, upper>::middle, upper>::value };
 };
 
 template<unsigned int n, int lower, int upper>
-struct floor_log2<n, lower, upper, floor_log2_move_up>
-{
-  enum { value = floor_log2<n, floor_log2_selector<n, lower, upper>::middle, upper>::value };
-};
-
-template<unsigned int n, int lower, int upper>
-struct floor_log2<n, lower, upper, floor_log2_terminate>
+struct meta_floor_log2<n, lower, upper, meta_floor_log2_terminate>
 {
   enum { value = (n >= ((unsigned int)(1) << (lower+1))) ? lower+1 : lower };
 };
 
 template<unsigned int n, int lower, int upper>
-struct floor_log2<n, lower, upper, floor_log2_bogus>
+struct meta_floor_log2<n, lower, upper, meta_floor_log2_bogus>
 {
   // no value, error at compile time
 };
 
 template<typename Scalar>
 struct random_default_impl<Scalar, false, true>
 {
-  typedef typename NumTraits<Scalar>::NonInteger NonInteger;
-
   static inline Scalar run(const Scalar& x, const Scalar& y)
-  {
-    return x + Scalar((NonInteger(y)-x+1) * std::rand() / (RAND_MAX + NonInteger(1)));
+  { 
+    typedef typename conditional<NumTraits<Scalar>::IsSigned,std::ptrdiff_t,std::size_t>::type ScalarX;
+    if(y<x)
+      return x;
+    // the following difference might overflow on a 32 bits system,
+    // but since y>=x the result converted to an unsigned long is still correct.
+    std::size_t range = ScalarX(y)-ScalarX(x);
+    std::size_t offset = 0;
+    // rejection sampling
+    std::size_t divisor = 1;
+    std::size_t multiplier = 1;
+    if(range<RAND_MAX) divisor = (std::size_t(RAND_MAX)+1)/(range+1);
+    else               multiplier = 1 + range/(std::size_t(RAND_MAX)+1);
+    do {
+      offset = (std::size_t(std::rand()) * multiplier) / divisor;
+    } while (offset > range);
+    return Scalar(ScalarX(x) + offset);
   }
 
   static inline Scalar run()
   {
 #ifdef EIGEN_MAKING_DOCS
     return run(Scalar(NumTraits<Scalar>::IsSigned ? -10 : 0), Scalar(10));
 #else
-    enum { rand_bits = floor_log2<(unsigned int)(RAND_MAX)+1>::value,
+    enum { rand_bits = meta_floor_log2<(unsigned int)(RAND_MAX)+1>::value,
            scalar_bits = sizeof(Scalar) * CHAR_BIT,
            shift = EIGEN_PLAIN_ENUM_MAX(0, int(rand_bits) - int(scalar_bits)),
            offset = NumTraits<Scalar>::IsSigned ? (1 << (EIGEN_PLAIN_ENUM_MIN(rand_bits,scalar_bits)-1)) : 0
     };
     return Scalar((std::rand() >> shift) - offset);
@@ -543,100 +699,604 @@
 inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random()
 {
   return EIGEN_MATHFUNC_IMPL(random, Scalar)::run();
 }
 
+// Implementatin of is* functions
+
+// std::is* do not work with fast-math and gcc, std::is* are available on MSVC 2013 and newer, as well as in clang.
+#if (EIGEN_HAS_CXX11_MATH && !(EIGEN_COMP_GNUC_STRICT && __FINITE_MATH_ONLY__)) || (EIGEN_COMP_MSVC>=1800) || (EIGEN_COMP_CLANG)
+#define EIGEN_USE_STD_FPCLASSIFY 1
+#else
+#define EIGEN_USE_STD_FPCLASSIFY 0
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+typename internal::enable_if<internal::is_integral<T>::value,bool>::type
+isnan_impl(const T&) { return false; }
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+typename internal::enable_if<internal::is_integral<T>::value,bool>::type
+isinf_impl(const T&) { return false; }
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+typename internal::enable_if<internal::is_integral<T>::value,bool>::type
+isfinite_impl(const T&) { return true; }
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+typename internal::enable_if<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>::type
+isfinite_impl(const T& x)
+{
+  #ifdef __CUDA_ARCH__
+    return (::isfinite)(x);
+  #elif EIGEN_USE_STD_FPCLASSIFY
+    using std::isfinite;
+    return isfinite EIGEN_NOT_A_MACRO (x);
+  #else
+    return x<=NumTraits<T>::highest() && x>=NumTraits<T>::lowest();
+  #endif
+}
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+typename internal::enable_if<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>::type
+isinf_impl(const T& x)
+{
+  #ifdef __CUDA_ARCH__
+    return (::isinf)(x);
+  #elif EIGEN_USE_STD_FPCLASSIFY
+    using std::isinf;
+    return isinf EIGEN_NOT_A_MACRO (x);
+  #else
+    return x>NumTraits<T>::highest() || x<NumTraits<T>::lowest();
+  #endif
+}
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+typename internal::enable_if<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>::type
+isnan_impl(const T& x)
+{
+  #ifdef __CUDA_ARCH__
+    return (::isnan)(x);
+  #elif EIGEN_USE_STD_FPCLASSIFY
+    using std::isnan;
+    return isnan EIGEN_NOT_A_MACRO (x);
+  #else
+    return x != x;
+  #endif
+}
+
+#if (!EIGEN_USE_STD_FPCLASSIFY)
+
+#if EIGEN_COMP_MSVC
+
+template<typename T> EIGEN_DEVICE_FUNC bool isinf_msvc_helper(T x)
+{
+  return _fpclass(x)==_FPCLASS_NINF || _fpclass(x)==_FPCLASS_PINF;
+}
+
+//MSVC defines a _isnan builtin function, but for double only
+EIGEN_DEVICE_FUNC inline bool isnan_impl(const long double& x) { return _isnan(x)!=0; }
+EIGEN_DEVICE_FUNC inline bool isnan_impl(const double& x)      { return _isnan(x)!=0; }
+EIGEN_DEVICE_FUNC inline bool isnan_impl(const float& x)       { return _isnan(x)!=0; }
+
+EIGEN_DEVICE_FUNC inline bool isinf_impl(const long double& x) { return isinf_msvc_helper(x); }
+EIGEN_DEVICE_FUNC inline bool isinf_impl(const double& x)      { return isinf_msvc_helper(x); }
+EIGEN_DEVICE_FUNC inline bool isinf_impl(const float& x)       { return isinf_msvc_helper(x); }
+
+#elif (defined __FINITE_MATH_ONLY__ && __FINITE_MATH_ONLY__ && EIGEN_COMP_GNUC)
+
+#if EIGEN_GNUC_AT_LEAST(5,0)
+  #define EIGEN_TMP_NOOPT_ATTRIB EIGEN_DEVICE_FUNC inline __attribute__((optimize("no-finite-math-only")))
+#else
+  // NOTE the inline qualifier and noinline attribute are both needed: the former is to avoid linking issue (duplicate symbol),
+  //      while the second prevent too aggressive optimizations in fast-math mode:
+  #define EIGEN_TMP_NOOPT_ATTRIB EIGEN_DEVICE_FUNC inline __attribute__((noinline,optimize("no-finite-math-only")))
+#endif
+
+template<> EIGEN_TMP_NOOPT_ATTRIB bool isnan_impl(const long double& x) { return __builtin_isnan(x); }
+template<> EIGEN_TMP_NOOPT_ATTRIB bool isnan_impl(const double& x)      { return __builtin_isnan(x); }
+template<> EIGEN_TMP_NOOPT_ATTRIB bool isnan_impl(const float& x)       { return __builtin_isnan(x); }
+template<> EIGEN_TMP_NOOPT_ATTRIB bool isinf_impl(const double& x)      { return __builtin_isinf(x); }
+template<> EIGEN_TMP_NOOPT_ATTRIB bool isinf_impl(const float& x)       { return __builtin_isinf(x); }
+template<> EIGEN_TMP_NOOPT_ATTRIB bool isinf_impl(const long double& x) { return __builtin_isinf(x); }
+
+#undef EIGEN_TMP_NOOPT_ATTRIB
+
+#endif
+
+#endif
+
+// The following overload are defined at the end of this file
+template<typename T> EIGEN_DEVICE_FUNC bool isfinite_impl(const std::complex<T>& x);
+template<typename T> EIGEN_DEVICE_FUNC bool isnan_impl(const std::complex<T>& x);
+template<typename T> EIGEN_DEVICE_FUNC bool isinf_impl(const std::complex<T>& x);
+
+template<typename T> T generic_fast_tanh_float(const T& a_x);
+
 } // end namespace internal
 
 /****************************************************************************
-* Generic math function                                                    *
+* Generic math functions                                                    *
 ****************************************************************************/
 
 namespace numext {
+
+#ifndef __CUDA_ARCH__
+template<typename T>
+EIGEN_DEVICE_FUNC
+EIGEN_ALWAYS_INLINE T mini(const T& x, const T& y)
+{
+  EIGEN_USING_STD_MATH(min);
+  return min EIGEN_NOT_A_MACRO (x,y);
+}
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y)
+{
+  EIGEN_USING_STD_MATH(max);
+  return max EIGEN_NOT_A_MACRO (x,y);
+}
+#else
+template<typename T>
+EIGEN_DEVICE_FUNC
+EIGEN_ALWAYS_INLINE T mini(const T& x, const T& y)
+{
+  return y < x ? y : x;
+}
+template<>
+EIGEN_DEVICE_FUNC
+EIGEN_ALWAYS_INLINE float mini(const float& x, const float& y)
+{
+  return fminf(x, y);
+}
+template<typename T>
+EIGEN_DEVICE_FUNC
+EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y)
+{
+  return x < y ? y : x;
+}
+template<>
+EIGEN_DEVICE_FUNC
+EIGEN_ALWAYS_INLINE float maxi(const float& x, const float& y)
+{
+  return fmaxf(x, y);
+}
+#endif
+
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(real, Scalar) real(const Scalar& x)
 {
   return EIGEN_MATHFUNC_IMPL(real, Scalar)::run(x);
-}  
+}
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) >::type real_ref(const Scalar& x)
 {
   return internal::real_ref_impl<Scalar>::run(x);
 }
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) real_ref(Scalar& x)
 {
   return EIGEN_MATHFUNC_IMPL(real_ref, Scalar)::run(x);
 }
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(imag, Scalar) imag(const Scalar& x)
 {
   return EIGEN_MATHFUNC_IMPL(imag, Scalar)::run(x);
 }
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
+inline EIGEN_MATHFUNC_RETVAL(arg, Scalar) arg(const Scalar& x)
+{
+  return EIGEN_MATHFUNC_IMPL(arg, Scalar)::run(x);
+}
+
+template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) >::type imag_ref(const Scalar& x)
 {
   return internal::imag_ref_impl<Scalar>::run(x);
 }
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) imag_ref(Scalar& x)
 {
   return EIGEN_MATHFUNC_IMPL(imag_ref, Scalar)::run(x);
 }
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(conj, Scalar) conj(const Scalar& x)
 {
   return EIGEN_MATHFUNC_IMPL(conj, Scalar)::run(x);
 }
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(abs2, Scalar) abs2(const Scalar& x)
 {
   return EIGEN_MATHFUNC_IMPL(abs2, Scalar)::run(x);
 }
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(norm1, Scalar) norm1(const Scalar& x)
 {
   return EIGEN_MATHFUNC_IMPL(norm1, Scalar)::run(x);
 }
 
 template<typename Scalar>
+EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(hypot, Scalar) hypot(const Scalar& x, const Scalar& y)
 {
   return EIGEN_MATHFUNC_IMPL(hypot, Scalar)::run(x, y);
 }
 
 template<typename Scalar>
-inline EIGEN_MATHFUNC_RETVAL(atanh2, Scalar) atanh2(const Scalar& x, const Scalar& y)
+EIGEN_DEVICE_FUNC
+inline EIGEN_MATHFUNC_RETVAL(log1p, Scalar) log1p(const Scalar& x)
+{
+  return EIGEN_MATHFUNC_IMPL(log1p, Scalar)::run(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float log1p(const float &x) { return ::log1pf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double log1p(const double &x) { return ::log1p(x); }
+#endif
+
+template<typename ScalarX,typename ScalarY>
+EIGEN_DEVICE_FUNC
+inline typename internal::pow_impl<ScalarX,ScalarY>::result_type pow(const ScalarX& x, const ScalarY& y)
 {
-  return EIGEN_MATHFUNC_IMPL(atanh2, Scalar)::run(x, y);
+  return internal::pow_impl<ScalarX,ScalarY>::run(x, y);
 }
 
+template<typename T> EIGEN_DEVICE_FUNC bool (isnan)   (const T &x) { return internal::isnan_impl(x); }
+template<typename T> EIGEN_DEVICE_FUNC bool (isinf)   (const T &x) { return internal::isinf_impl(x); }
+template<typename T> EIGEN_DEVICE_FUNC bool (isfinite)(const T &x) { return internal::isfinite_impl(x); }
+
 template<typename Scalar>
-inline EIGEN_MATHFUNC_RETVAL(pow, Scalar) pow(const Scalar& x, const Scalar& y)
-{
-  return EIGEN_MATHFUNC_IMPL(pow, Scalar)::run(x, y);
-}
-
-// std::isfinite is non standard, so let's define our own version,
-// even though it is not very efficient.
-template<typename T> bool (isfinite)(const T& x)
-{
-  return x<NumTraits<T>::highest() && x>NumTraits<T>::lowest();
-}
+EIGEN_DEVICE_FUNC
+inline EIGEN_MATHFUNC_RETVAL(round, Scalar) round(const Scalar& x)
+{
+  return EIGEN_MATHFUNC_IMPL(round, Scalar)::run(x);
+}
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+T (floor)(const T& x)
+{
+  EIGEN_USING_STD_MATH(floor);
+  return floor(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float floor(const float &x) { return ::floorf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double floor(const double &x) { return ::floor(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC
+T (ceil)(const T& x)
+{
+  EIGEN_USING_STD_MATH(ceil);
+  return ceil(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float ceil(const float &x) { return ::ceilf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double ceil(const double &x) { return ::ceil(x); }
+#endif
+
+
+/** Log base 2 for 32 bits positive integers.
+  * Conveniently returns 0 for x==0. */
+inline int log2(int x)
+{
+  eigen_assert(x>=0);
+  unsigned int v(x);
+  static const int table[32] = { 0, 9, 1, 10, 13, 21, 2, 29, 11, 14, 16, 18, 22, 25, 3, 30, 8, 12, 20, 28, 15, 17, 24, 7, 19, 27, 23, 6, 26, 5, 4, 31 };
+  v |= v >> 1;
+  v |= v >> 2;
+  v |= v >> 4;
+  v |= v >> 8;
+  v |= v >> 16;
+  return table[(v * 0x07C4ACDDU) >> 27];
+}
+
+/** \returns the square root of \a x.
+  *
+  * It is essentially equivalent to \code using std::sqrt; return sqrt(x); \endcode,
+  * but slightly faster for float/double and some compilers (e.g., gcc), thanks to
+  * specializations when SSE is enabled.
+  *
+  * It's usage is justified in performance critical functions, like norm/normalize.
+  */
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T sqrt(const T &x)
+{
+  EIGEN_USING_STD_MATH(sqrt);
+  return sqrt(x);
+}
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T log(const T &x) {
+  EIGEN_USING_STD_MATH(log);
+  return log(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float log(const float &x) { return ::logf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double log(const double &x) { return ::log(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+typename internal::enable_if<NumTraits<T>::IsSigned || NumTraits<T>::IsComplex,typename NumTraits<T>::Real>::type
+abs(const T &x) {
+  EIGEN_USING_STD_MATH(abs);
+  return abs(x);
+}
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+typename internal::enable_if<!(NumTraits<T>::IsSigned || NumTraits<T>::IsComplex),typename NumTraits<T>::Real>::type
+abs(const T &x) {
+  return x;
+}
+
+#if defined(__SYCL_DEVICE_ONLY__)
+EIGEN_ALWAYS_INLINE float   abs(float x) { return cl::sycl::fabs(x); }
+EIGEN_ALWAYS_INLINE double  abs(double x) { return cl::sycl::fabs(x); }
+#endif // defined(__SYCL_DEVICE_ONLY__)
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float abs(const float &x) { return ::fabsf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double abs(const double &x) { return ::fabs(x); }
+
+template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float abs(const std::complex<float>& x) {
+  return ::hypotf(x.real(), x.imag());
+}
+
+template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double abs(const std::complex<double>& x) {
+  return ::hypot(x.real(), x.imag());
+}
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T exp(const T &x) {
+  EIGEN_USING_STD_MATH(exp);
+  return exp(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float exp(const float &x) { return ::expf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double exp(const double &x) { return ::exp(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T cos(const T &x) {
+  EIGEN_USING_STD_MATH(cos);
+  return cos(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float cos(const float &x) { return ::cosf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double cos(const double &x) { return ::cos(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T sin(const T &x) {
+  EIGEN_USING_STD_MATH(sin);
+  return sin(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float sin(const float &x) { return ::sinf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double sin(const double &x) { return ::sin(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T tan(const T &x) {
+  EIGEN_USING_STD_MATH(tan);
+  return tan(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float tan(const float &x) { return ::tanf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double tan(const double &x) { return ::tan(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T acos(const T &x) {
+  EIGEN_USING_STD_MATH(acos);
+  return acos(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float acos(const float &x) { return ::acosf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double acos(const double &x) { return ::acos(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T asin(const T &x) {
+  EIGEN_USING_STD_MATH(asin);
+  return asin(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float asin(const float &x) { return ::asinf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double asin(const double &x) { return ::asin(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T atan(const T &x) {
+  EIGEN_USING_STD_MATH(atan);
+  return atan(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float atan(const float &x) { return ::atanf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double atan(const double &x) { return ::atan(x); }
+#endif
+
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T cosh(const T &x) {
+  EIGEN_USING_STD_MATH(cosh);
+  return cosh(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float cosh(const float &x) { return ::coshf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double cosh(const double &x) { return ::cosh(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T sinh(const T &x) {
+  EIGEN_USING_STD_MATH(sinh);
+  return sinh(x);
+}
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float sinh(const float &x) { return ::sinhf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double sinh(const double &x) { return ::sinh(x); }
+#endif
+
+template<typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T tanh(const T &x) {
+  EIGEN_USING_STD_MATH(tanh);
+  return tanh(x);
+}
+
+#if (!defined(__CUDACC__)) && EIGEN_FAST_MATH
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float tanh(float x) { return internal::generic_fast_tanh_float(x); }
+#endif
+
+#ifdef __CUDACC__
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float tanh(const float &x) { return ::tanhf(x); }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double tanh(const double &x) { return ::tanh(x); }
+#endif
+
+template <typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T fmod(const T& a, const T& b) {
+  EIGEN_USING_STD_MATH(fmod);
+  return fmod(a, b);
+}
+
+#ifdef __CUDACC__
+template <>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float fmod(const float& a, const float& b) {
+  return ::fmodf(a, b);
+}
+
+template <>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double fmod(const double& a, const double& b) {
+  return ::fmod(a, b);
+}
+#endif
 
 } // end namespace numext
 
 namespace internal {
+
+template<typename T>
+EIGEN_DEVICE_FUNC bool isfinite_impl(const std::complex<T>& x)
+{
+  return (numext::isfinite)(numext::real(x)) && (numext::isfinite)(numext::imag(x));
+}
+
+template<typename T>
+EIGEN_DEVICE_FUNC bool isnan_impl(const std::complex<T>& x)
+{
+  return (numext::isnan)(numext::real(x)) || (numext::isnan)(numext::imag(x));
+}
+
+template<typename T>
+EIGEN_DEVICE_FUNC bool isinf_impl(const std::complex<T>& x)
+{
+  return ((numext::isinf)(numext::real(x)) || (numext::isinf)(numext::imag(x))) && (!(numext::isnan)(x));
+}
 
 /****************************************************************************
 * Implementation of fuzzy comparisons                                       *
 ****************************************************************************/
 
@@ -647,22 +1307,21 @@
 
 template<typename Scalar>
 struct scalar_fuzzy_default_impl<Scalar, false, false>
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  template<typename OtherScalar>
+  template<typename OtherScalar> EIGEN_DEVICE_FUNC
   static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, const RealScalar& prec)
   {
-    using std::abs;
-    return abs(x) <= abs(y) * prec;
+    return numext::abs(x) <= numext::abs(y) * prec;
   }
+  EIGEN_DEVICE_FUNC
   static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec)
   {
-    using std::min;
-    using std::abs;
-    return abs(x - y) <= (min)(abs(x), abs(y)) * prec;
+    return numext::abs(x - y) <= numext::mini(numext::abs(x), numext::abs(y)) * prec;
   }
+  EIGEN_DEVICE_FUNC
   static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar& prec)
   {
     return x <= y || isApprox(x, y, prec);
   }
 };
@@ -669,19 +1328,21 @@
 
 template<typename Scalar>
 struct scalar_fuzzy_default_impl<Scalar, false, true>
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  template<typename OtherScalar>
+  template<typename OtherScalar> EIGEN_DEVICE_FUNC
   static inline bool isMuchSmallerThan(const Scalar& x, const Scalar&, const RealScalar&)
   {
     return x == Scalar(0);
   }
+  EIGEN_DEVICE_FUNC
   static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar&)
   {
     return x == y;
   }
+  EIGEN_DEVICE_FUNC
   static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar&)
   {
     return x <= y;
   }
 };
@@ -688,42 +1349,42 @@
 
 template<typename Scalar>
 struct scalar_fuzzy_default_impl<Scalar, true, false>
 {
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  template<typename OtherScalar>
+  template<typename OtherScalar> EIGEN_DEVICE_FUNC
   static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, const RealScalar& prec)
   {
     return numext::abs2(x) <= numext::abs2(y) * prec * prec;
   }
+  EIGEN_DEVICE_FUNC
   static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec)
   {
-    using std::min;
-    return numext::abs2(x - y) <= (min)(numext::abs2(x), numext::abs2(y)) * prec * prec;
+    return numext::abs2(x - y) <= numext::mini(numext::abs2(x), numext::abs2(y)) * prec * prec;
   }
 };
 
 template<typename Scalar>
 struct scalar_fuzzy_impl : scalar_fuzzy_default_impl<Scalar, NumTraits<Scalar>::IsComplex, NumTraits<Scalar>::IsInteger> {};
 
-template<typename Scalar, typename OtherScalar>
+template<typename Scalar, typename OtherScalar> EIGEN_DEVICE_FUNC
 inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y,
-                                   typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
+                              const typename NumTraits<Scalar>::Real &precision = NumTraits<Scalar>::dummy_precision())
 {
   return scalar_fuzzy_impl<Scalar>::template isMuchSmallerThan<OtherScalar>(x, y, precision);
 }
 
-template<typename Scalar>
+template<typename Scalar> EIGEN_DEVICE_FUNC
 inline bool isApprox(const Scalar& x, const Scalar& y,
-                          typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
+                     const typename NumTraits<Scalar>::Real &precision = NumTraits<Scalar>::dummy_precision())
 {
   return scalar_fuzzy_impl<Scalar>::isApprox(x, y, precision);
 }
 
-template<typename Scalar>
+template<typename Scalar> EIGEN_DEVICE_FUNC
 inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y,
-                                    typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
+                               const typename NumTraits<Scalar>::Real &precision = NumTraits<Scalar>::dummy_precision())
 {
   return scalar_fuzzy_impl<Scalar>::isApproxOrLessThan(x, y, precision);
 }
 
 /******************************************
@@ -740,21 +1401,23 @@
 
 template<> struct scalar_fuzzy_impl<bool>
 {
   typedef bool RealScalar;
   
-  template<typename OtherScalar>
+  template<typename OtherScalar> EIGEN_DEVICE_FUNC
   static inline bool isMuchSmallerThan(const bool& x, const bool&, const bool&)
   {
     return !x;
   }
   
+  EIGEN_DEVICE_FUNC
   static inline bool isApprox(bool x, bool y, bool)
   {
     return x == y;
   }
 
+  EIGEN_DEVICE_FUNC
   static inline bool isApproxOrLessThan(const bool& x, const bool& y, const bool&)
   {
     return (!x) || y;
   }
   

ADDED   3rd_party/eigen/Eigen/src/Core/MathFunctionsImpl.h
Index: 3rd_party/eigen/Eigen/src/Core/MathFunctionsImpl.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/MathFunctionsImpl.h
+++ 3rd_party/eigen/Eigen/src/Core/MathFunctionsImpl.h
@@ -0,0 +1,78 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Pedro Gonnet (pedro.gonnet@gmail.com)
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_MATHFUNCTIONSIMPL_H
+#define EIGEN_MATHFUNCTIONSIMPL_H
+
+namespace Eigen {
+
+namespace internal {
+
+/** \internal \returns the hyperbolic tan of \a a (coeff-wise)
+    Doesn't do anything fancy, just a 13/6-degree rational interpolant which
+    is accurate up to a couple of ulp in the range [-9, 9], outside of which
+    the tanh(x) = +/-1.
+
+    This implementation works on both scalars and packets.
+*/
+template<typename T>
+T generic_fast_tanh_float(const T& a_x)
+{
+  // Clamp the inputs to the range [-9, 9] since anything outside
+  // this range is +/-1.0f in single-precision.
+  const T plus_9 = pset1<T>(9.f);
+  const T minus_9 = pset1<T>(-9.f);
+  // NOTE GCC prior to 6.3 might improperly optimize this max/min
+  //      step such that if a_x is nan, x will be either 9 or -9,
+  //      and tanh will return 1 or -1 instead of nan.
+  //      This is supposed to be fixed in gcc6.3,
+  //      see: https://gcc.gnu.org/bugzilla/show_bug.cgi?id=72867
+  const T x = pmax(minus_9,pmin(plus_9,a_x));
+  // The monomial coefficients of the numerator polynomial (odd).
+  const T alpha_1 = pset1<T>(4.89352455891786e-03f);
+  const T alpha_3 = pset1<T>(6.37261928875436e-04f);
+  const T alpha_5 = pset1<T>(1.48572235717979e-05f);
+  const T alpha_7 = pset1<T>(5.12229709037114e-08f);
+  const T alpha_9 = pset1<T>(-8.60467152213735e-11f);
+  const T alpha_11 = pset1<T>(2.00018790482477e-13f);
+  const T alpha_13 = pset1<T>(-2.76076847742355e-16f);
+
+  // The monomial coefficients of the denominator polynomial (even).
+  const T beta_0 = pset1<T>(4.89352518554385e-03f);
+  const T beta_2 = pset1<T>(2.26843463243900e-03f);
+  const T beta_4 = pset1<T>(1.18534705686654e-04f);
+  const T beta_6 = pset1<T>(1.19825839466702e-06f);
+
+  // Since the polynomials are odd/even, we need x^2.
+  const T x2 = pmul(x, x);
+
+  // Evaluate the numerator polynomial p.
+  T p = pmadd(x2, alpha_13, alpha_11);
+  p = pmadd(x2, p, alpha_9);
+  p = pmadd(x2, p, alpha_7);
+  p = pmadd(x2, p, alpha_5);
+  p = pmadd(x2, p, alpha_3);
+  p = pmadd(x2, p, alpha_1);
+  p = pmul(x, p);
+
+  // Evaluate the denominator polynomial p.
+  T q = pmadd(x2, beta_6, beta_4);
+  q = pmadd(x2, q, beta_2);
+  q = pmadd(x2, q, beta_0);
+
+  // Divide the numerator by the denominator.
+  return pdiv(p, q);
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_MATHFUNCTIONSIMPL_H

Index: 3rd_party/eigen/Eigen/src/Core/Matrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Matrix.h
+++ 3rd_party/eigen/Eigen/src/Core/Matrix.h
@@ -10,10 +10,49 @@
 
 #ifndef EIGEN_MATRIX_H
 #define EIGEN_MATRIX_H
 
 namespace Eigen {
+
+namespace internal {
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+{
+private:
+  enum { size = internal::size_at_compile_time<_Rows,_Cols>::ret };
+  typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
+  enum {
+      row_major_bit = _Options&RowMajor ? RowMajorBit : 0,
+      is_dynamic_size_storage = _MaxRows==Dynamic || _MaxCols==Dynamic,
+      max_size = is_dynamic_size_storage ? Dynamic : _MaxRows*_MaxCols,
+      default_alignment = compute_default_alignment<_Scalar,max_size>::value,
+      actual_alignment = ((_Options&DontAlign)==0) ? default_alignment : 0,
+      required_alignment = unpacket_traits<PacketScalar>::alignment,
+      packet_access_bit = (packet_traits<_Scalar>::Vectorizable && (EIGEN_UNALIGNED_VECTORIZE || (actual_alignment>=required_alignment))) ? PacketAccessBit : 0
+    };
+    
+public:
+  typedef _Scalar Scalar;
+  typedef Dense StorageKind;
+  typedef Eigen::Index StorageIndex;
+  typedef MatrixXpr XprKind;
+  enum {
+    RowsAtCompileTime = _Rows,
+    ColsAtCompileTime = _Cols,
+    MaxRowsAtCompileTime = _MaxRows,
+    MaxColsAtCompileTime = _MaxCols,
+    Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
+    Options = _Options,
+    InnerStrideAtCompileTime = 1,
+    OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime,
+    
+    // FIXME, the following flag in only used to define NeedsToAlign in PlainObjectBase
+    EvaluatorFlags = LinearAccessBit | DirectAccessBit | packet_access_bit | row_major_bit,
+    Alignment = actual_alignment
+  };
+};
+}
 
 /** \class Matrix
   * \ingroup Core_Module
   *
   * \brief The matrix class, also used for vectors and row-vectors
@@ -22,17 +61,17 @@
   * Vectors are matrices with one column, and row-vectors are matrices with one row.
   *
   * The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note").
   *
   * The first three template parameters are required:
-  * \tparam _Scalar \anchor matrix_tparam_scalar Numeric type, e.g. float, double, int or std::complex<float>.
-  *                 User defined sclar types are supported as well (see \ref user_defined_scalars "here").
+  * \tparam _Scalar Numeric type, e.g. float, double, int or std::complex<float>.
+  *                 User defined scalar types are supported as well (see \ref user_defined_scalars "here").
   * \tparam _Rows Number of rows, or \b Dynamic
   * \tparam _Cols Number of columns, or \b Dynamic
   *
   * The remaining template parameters are optional -- in most cases you don't have to worry about them.
-  * \tparam _Options \anchor matrix_tparam_options A combination of either \b #RowMajor or \b #ColMajor, and of either
+  * \tparam _Options A combination of either \b #RowMajor or \b #ColMajor, and of either
   *                 \b #AutoAlign or \b #DontAlign.
   *                 The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required
   *                 for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size.
   * \tparam _MaxRows Maximum number of rows. Defaults to \a _Rows (\ref maxrows "note").
   * \tparam _MaxCols Maximum number of columns. Defaults to \a _Cols (\ref maxrows "note").
@@ -65,11 +104,11 @@
   * m(0, 2) = 2;
   * m(0, 3) = 3;
   * \endcode
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_MATRIX_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_MATRIX_PLUGIN.
   *
   * <i><b>Some notes:</b></i>
   *
   * <dl>
   * <dt><b>\anchor dense Dense versus sparse:</b></dt>
@@ -95,36 +134,48 @@
   * when the exact numbers of rows and columns are not known are compile-time, but it is known at compile-time that they cannot
   * exceed a certain value. This happens when taking dynamic-size blocks inside fixed-size matrices: in this case _MaxRows and _MaxCols
   * are the dimensions of the original matrix, while _Rows and _Cols are Dynamic.</dd>
   * </dl>
   *
-  * \see MatrixBase for the majority of the API methods for matrices, \ref TopicClassHierarchy, 
-  * \ref TopicStorageOrders 
+  * <i><b>ABI and storage layout</b></i>
+  *
+  * The table below summarizes the ABI of some possible Matrix instances which is fixed thorough the lifetime of Eigen 3.
+  * <table  class="manual">
+  * <tr><th>Matrix type</th><th>Equivalent C structure</th></tr>
+  * <tr><td>\code Matrix<T,Dynamic,Dynamic> \endcode</td><td>\code
+  * struct {
+  *   T *data;                  // with (size_t(data)%EIGEN_MAX_ALIGN_BYTES)==0
+  *   Eigen::Index rows, cols;
+  *  };
+  * \endcode</td></tr>
+  * <tr class="alt"><td>\code
+  * Matrix<T,Dynamic,1>
+  * Matrix<T,1,Dynamic> \endcode</td><td>\code
+  * struct {
+  *   T *data;                  // with (size_t(data)%EIGEN_MAX_ALIGN_BYTES)==0
+  *   Eigen::Index size;
+  *  };
+  * \endcode</td></tr>
+  * <tr><td>\code Matrix<T,Rows,Cols> \endcode</td><td>\code
+  * struct {
+  *   T data[Rows*Cols];        // with (size_t(data)%A(Rows*Cols*sizeof(T)))==0
+  *  };
+  * \endcode</td></tr>
+  * <tr class="alt"><td>\code Matrix<T,Dynamic,Dynamic,0,MaxRows,MaxCols> \endcode</td><td>\code
+  * struct {
+  *   T data[MaxRows*MaxCols];  // with (size_t(data)%A(MaxRows*MaxCols*sizeof(T)))==0
+  *   Eigen::Index rows, cols;
+  *  };
+  * \endcode</td></tr>
+  * </table>
+  * Note that in this table Rows, Cols, MaxRows and MaxCols are all positive integers. A(S) is defined to the largest possible power-of-two
+  * smaller to EIGEN_MAX_STATIC_ALIGN_BYTES.
+  *
+  * \see MatrixBase for the majority of the API methods for matrices, \ref TopicClassHierarchy,
+  * \ref TopicStorageOrders
   */
 
-namespace internal {
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-{
-  typedef _Scalar Scalar;
-  typedef Dense StorageKind;
-  typedef DenseIndex Index;
-  typedef MatrixXpr XprKind;
-  enum {
-    RowsAtCompileTime = _Rows,
-    ColsAtCompileTime = _Cols,
-    MaxRowsAtCompileTime = _MaxRows,
-    MaxColsAtCompileTime = _MaxCols,
-    Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
-    CoeffReadCost = NumTraits<Scalar>::ReadCost,
-    Options = _Options,
-    InnerStrideAtCompileTime = 1,
-    OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime
-  };
-};
-}
-
 template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
 class Matrix
   : public PlainObjectBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
 {
   public:
@@ -149,10 +200,11 @@
       * \note This is a special case of the templated operator=. Its purpose is
       * to prevent a default operator= from hiding the templated operator=.
       *
       * \callgraph
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix& operator=(const Matrix& other)
     {
       return Base::_set(other);
     }
 
@@ -165,11 +217,12 @@
       * Note that copying a row-vector into a vector (and conversely) is allowed.
       * The resizing, if any, is then done in the appropriate way so that row-vectors
       * remain row-vectors and vectors remain vectors.
       */
     template<typename OtherDerived>
-    EIGEN_STRONG_INLINE Matrix& operator=(const MatrixBase<OtherDerived>& other)
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Matrix& operator=(const DenseBase<OtherDerived>& other)
     {
       return Base::_set(other);
     }
 
     /* Here, doxygen failed to copy the brief information when using \copydoc */
@@ -177,16 +230,18 @@
     /**
       * \brief Copies the generic expression \a other into *this.
       * \copydetails DenseBase::operator=(const EigenBase<OtherDerived> &other)
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix& operator=(const EigenBase<OtherDerived> &other)
     {
       return Base::operator=(other);
     }
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix& operator=(const ReturnByValue<OtherDerived>& func)
     {
       return Base::operator=(func);
     }
 
@@ -198,65 +253,109 @@
       * is called a null matrix. This constructor is the unique way to create null matrices: resizing
       * a matrix to 0 is not supported.
       *
       * \sa resize(Index,Index)
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix() : Base()
     {
       Base::_check_template_params();
       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 
     // FIXME is it still needed
-    Matrix(internal::constructor_without_unaligned_array_assert)
+    EIGEN_DEVICE_FUNC
+    explicit Matrix(internal::constructor_without_unaligned_array_assert)
       : Base(internal::constructor_without_unaligned_array_assert())
     { Base::_check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
 
-    /** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors
-      *
-      * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
-      * it is redundant to pass the dimension here, so it makes more sense to use the default
-      * constructor Matrix() instead.
-      */
-    EIGEN_STRONG_INLINE explicit Matrix(Index dim)
-      : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
+#if EIGEN_HAS_RVALUE_REFERENCES
+    EIGEN_DEVICE_FUNC
+    Matrix(Matrix&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_constructible<Scalar>::value)
+      : Base(std::move(other))
     {
       Base::_check_template_params();
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix)
-      eigen_assert(dim >= 0);
-      eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
-      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+      if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
+        Base::_set_noalias(other);
+    }
+    EIGEN_DEVICE_FUNC
+    Matrix& operator=(Matrix&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_assignable<Scalar>::value)
+    {
+      other.swap(*this);
+      return *this;
     }
+#endif
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
+
+    // This constructor is for both 1x1 matrices and dynamic vectors
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE explicit Matrix(const T& x)
+    {
+      Base::_check_template_params();
+      Base::template _init1<T>(x);
+    }
+
     template<typename T0, typename T1>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix(const T0& x, const T1& y)
     {
       Base::_check_template_params();
       Base::template _init2<T0,T1>(x, y);
     }
     #else
+    /** \brief Constructs a fixed-sized matrix initialized with coefficients starting at \a data */
+    EIGEN_DEVICE_FUNC
+    explicit Matrix(const Scalar *data);
+
+    /** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors
+      *
+      * This is useful for dynamic-size vectors. For fixed-size vectors,
+      * it is redundant to pass these parameters, so one should use the default constructor
+      * Matrix() instead.
+      * 
+      * \warning This constructor is disabled for fixed-size \c 1x1 matrices. For instance,
+      * calling Matrix<double,1,1>(1) will call the initialization constructor: Matrix(const Scalar&).
+      * For fixed-size \c 1x1 matrices it is therefore recommended to use the default
+      * constructor Matrix() instead, especially when using one of the non standard
+      * \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives).
+      */
+    EIGEN_STRONG_INLINE explicit Matrix(Index dim);
+    /** \brief Constructs an initialized 1x1 matrix with the given coefficient */
+    Matrix(const Scalar& x);
     /** \brief Constructs an uninitialized matrix with \a rows rows and \a cols columns.
       *
       * This is useful for dynamic-size matrices. For fixed-size matrices,
       * it is redundant to pass these parameters, so one should use the default constructor
-      * Matrix() instead. */
+      * Matrix() instead.
+      * 
+      * \warning This constructor is disabled for fixed-size \c 1x2 and \c 2x1 vectors. For instance,
+      * calling Matrix2f(2,1) will call the initialization constructor: Matrix(const Scalar& x, const Scalar& y).
+      * For fixed-size \c 1x2 or \c 2x1 vectors it is therefore recommended to use the default
+      * constructor Matrix() instead, especially when using one of the non standard
+      * \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives).
+      */
+    EIGEN_DEVICE_FUNC
     Matrix(Index rows, Index cols);
+    
     /** \brief Constructs an initialized 2D vector with given coefficients */
     Matrix(const Scalar& x, const Scalar& y);
     #endif
 
     /** \brief Constructs an initialized 3D vector with given coefficients */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z)
     {
       Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 3)
       m_storage.data()[0] = x;
       m_storage.data()[1] = y;
       m_storage.data()[2] = z;
     }
     /** \brief Constructs an initialized 4D vector with given coefficients */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
     {
       Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 4)
       m_storage.data()[0] = x;
@@ -263,80 +362,37 @@
       m_storage.data()[1] = y;
       m_storage.data()[2] = z;
       m_storage.data()[3] = w;
     }
 
-    explicit Matrix(const Scalar *data);
-
-    /** \brief Constructor copying the value of the expression \a other */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE Matrix(const MatrixBase<OtherDerived>& other)
-             : Base(other.rows() * other.cols(), other.rows(), other.cols())
-    {
-      // This test resides here, to bring the error messages closer to the user. Normally, these checks
-      // are performed deeply within the library, thus causing long and scary error traces.
-      EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
-        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-
-      Base::_check_template_params();
-      Base::_set_noalias(other);
-    }
+
     /** \brief Copy constructor */
-    EIGEN_STRONG_INLINE Matrix(const Matrix& other)
-            : Base(other.rows() * other.cols(), other.rows(), other.cols())
-    {
-      Base::_check_template_params();
-      Base::_set_noalias(other);
-    }
-    /** \brief Copy constructor with in-place evaluation */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE Matrix(const ReturnByValue<OtherDerived>& other)
-    {
-      Base::_check_template_params();
-      Base::resize(other.rows(), other.cols());
-      other.evalTo(*this);
-    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Matrix(const Matrix& other) : Base(other)
+    { }
 
     /** \brief Copy constructor for generic expressions.
       * \sa MatrixBase::operator=(const EigenBase<OtherDerived>&)
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix(const EigenBase<OtherDerived> &other)
-      : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
-    {
-      Base::_check_template_params();
-      Base::_resize_to_match(other);
-      // FIXME/CHECK: isn't *this = other.derived() more efficient. it allows to
-      //              go for pure _set() implementations, right?
-      *this = other;
-    }
-
-    /** \internal
-      * \brief Override MatrixBase::swap() since for dynamic-sized matrices
-      * of same type it is enough to swap the data pointers.
-      */
-    template<typename OtherDerived>
-    void swap(MatrixBase<OtherDerived> const & other)
-    { this->_swap(other.derived()); }
-
-    inline Index innerStride() const { return 1; }
-    inline Index outerStride() const { return this->innerSize(); }
+      : Base(other.derived())
+    { }
+
+    EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; }
+    EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); }
 
     /////////// Geometry module ///////////
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     explicit Matrix(const RotationBase<OtherDerived,ColsAtCompileTime>& r);
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     Matrix& operator=(const RotationBase<OtherDerived,ColsAtCompileTime>& r);
 
-    #ifdef EIGEN2_SUPPORT
-    template<typename OtherDerived>
-    explicit Matrix(const eigen2_RotationBase<OtherDerived,ColsAtCompileTime>& r);
-    template<typename OtherDerived>
-    Matrix& operator=(const eigen2_RotationBase<OtherDerived,ColsAtCompileTime>& r);
-    #endif
-
     // allow to extend Matrix outside Eigen
     #ifdef EIGEN_MATRIX_PLUGIN
     #include EIGEN_MATRIX_PLUGIN
     #endif
 

Index: 3rd_party/eigen/Eigen/src/Core/MatrixBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/MatrixBase.h
+++ 3rd_party/eigen/Eigen/src/Core/MatrixBase.h
@@ -39,22 +39,22 @@
       cout << x.row(0) << endl;
     }
   * \endcode
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_MATRIXBASE_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_MATRIXBASE_PLUGIN.
   *
-  * \sa \ref TopicClassHierarchy
+  * \sa \blank \ref TopicClassHierarchy
   */
 template<typename Derived> class MatrixBase
   : public DenseBase<Derived>
 {
   public:
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     typedef MatrixBase StorageBaseType;
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
     typedef DenseBase<Derived> Base;
@@ -64,11 +64,10 @@
     using Base::MaxRowsAtCompileTime;
     using Base::MaxColsAtCompileTime;
     using Base::MaxSizeAtCompileTime;
     using Base::IsVectorAtCompileTime;
     using Base::Flags;
-    using Base::CoeffReadCost;
 
     using Base::derived;
     using Base::const_cast_derived;
     using Base::rows;
     using Base::cols;
@@ -96,90 +95,90 @@
                           EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime)> SquareMatrixType;
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
     /** \returns the size of the main diagonal, which is min(rows(),cols()).
       * \sa rows(), cols(), SizeAtCompileTime. */
-    inline Index diagonalSize() const { return (std::min)(rows(),cols()); }
-
-    /** \brief The plain matrix type corresponding to this expression.
-      *
-      * This is not necessarily exactly the return type of eval(). In the case of plain matrices,
-      * the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed
-      * that the return type of eval() is either PlainObject or const PlainObject&.
-      */
-    typedef Matrix<typename internal::traits<Derived>::Scalar,
-                internal::traits<Derived>::RowsAtCompileTime,
-                internal::traits<Derived>::ColsAtCompileTime,
-                AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
-                internal::traits<Derived>::MaxRowsAtCompileTime,
-                internal::traits<Derived>::MaxColsAtCompileTime
-          > PlainObject;
+    EIGEN_DEVICE_FUNC
+    inline Index diagonalSize() const { return (numext::mini)(rows(),cols()); }
+
+    typedef typename Base::PlainObject PlainObject;
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** \internal Represents a matrix with all coefficients equal to one another*/
-    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
+    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
     /** \internal the return type of MatrixBase::adjoint() */
     typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
                         CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, ConstTransposeReturnType>,
                         ConstTransposeReturnType
                      >::type AdjointReturnType;
     /** \internal Return type of eigenvalues() */
     typedef Matrix<std::complex<RealScalar>, internal::traits<Derived>::ColsAtCompileTime, 1, ColMajor> EigenvaluesReturnType;
     /** \internal the return type of identity */
-    typedef CwiseNullaryOp<internal::scalar_identity_op<Scalar>,Derived> IdentityReturnType;
+    typedef CwiseNullaryOp<internal::scalar_identity_op<Scalar>,PlainObject> IdentityReturnType;
     /** \internal the return type of unit vectors */
     typedef Block<const CwiseNullaryOp<internal::scalar_identity_op<Scalar>, SquareMatrixType>,
                   internal::traits<Derived>::RowsAtCompileTime,
                   internal::traits<Derived>::ColsAtCompileTime> BasisReturnType;
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
 #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::MatrixBase
+#define EIGEN_DOC_UNARY_ADDONS(X,Y)
 #   include "../plugins/CommonCwiseUnaryOps.h"
 #   include "../plugins/CommonCwiseBinaryOps.h"
 #   include "../plugins/MatrixCwiseUnaryOps.h"
 #   include "../plugins/MatrixCwiseBinaryOps.h"
 #   ifdef EIGEN_MATRIXBASE_PLUGIN
 #     include EIGEN_MATRIXBASE_PLUGIN
 #   endif
 #undef EIGEN_CURRENT_STORAGE_BASE_CLASS
+#undef EIGEN_DOC_UNARY_ADDONS
 
     /** Special case of the template operator=, in order to prevent the compiler
       * from generating a default operator= (issue hit with g++ 4.1)
       */
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator=(const MatrixBase& other);
 
     // We cannot inherit here via Base::operator= since it is causing
     // trouble with MSVC.
 
     template <typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator=(const DenseBase<OtherDerived>& other);
 
     template <typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     Derived& operator=(const EigenBase<OtherDerived>& other);
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     Derived& operator=(const ReturnByValue<OtherDerived>& other);
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    Derived& lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other);
-
-    template<typename MatrixPower, typename Lhs, typename Rhs>
-    Derived& lazyAssign(const MatrixPowerProduct<MatrixPower, Lhs,Rhs>& other);
-#endif // not EIGEN_PARSED_BY_DOXYGEN
-
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator+=(const MatrixBase<OtherDerived>& other);
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator-=(const MatrixBase<OtherDerived>& other);
+
+#ifdef __CUDACC__
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    const Product<Derived,OtherDerived,LazyProduct>
+    operator*(const MatrixBase<OtherDerived> &other) const
+    { return this->lazyProduct(other); }
+#else
 
     template<typename OtherDerived>
-    const typename ProductReturnType<Derived,OtherDerived>::Type
+    const Product<Derived,OtherDerived>
     operator*(const MatrixBase<OtherDerived> &other) const;
+
+#endif
 
     template<typename OtherDerived>
-    const typename LazyProductReturnType<Derived,OtherDerived>::Type
+    EIGEN_DEVICE_FUNC
+    const Product<Derived,OtherDerived,LazyProduct>
     lazyProduct(const MatrixBase<OtherDerived> &other) const;
 
     template<typename OtherDerived>
     Derived& operator*=(const EigenBase<OtherDerived>& other);
 
@@ -188,88 +187,97 @@
 
     template<typename OtherDerived>
     void applyOnTheRight(const EigenBase<OtherDerived>& other);
 
     template<typename DiagonalDerived>
-    const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
+    EIGEN_DEVICE_FUNC
+    const Product<Derived, DiagonalDerived, LazyProduct>
     operator*(const DiagonalBase<DiagonalDerived> &diagonal) const;
 
     template<typename OtherDerived>
-    typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
+    EIGEN_DEVICE_FUNC
+    typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
     dot(const MatrixBase<OtherDerived>& other) const;
 
-    #ifdef EIGEN2_SUPPORT
-      template<typename OtherDerived>
-      Scalar eigen2_dot(const MatrixBase<OtherDerived>& other) const;
-    #endif
-
-    RealScalar squaredNorm() const;
-    RealScalar norm() const;
+    EIGEN_DEVICE_FUNC RealScalar squaredNorm() const;
+    EIGEN_DEVICE_FUNC RealScalar norm() const;
     RealScalar stableNorm() const;
     RealScalar blueNorm() const;
     RealScalar hypotNorm() const;
-    const PlainObject normalized() const;
-    void normalize();
+    EIGEN_DEVICE_FUNC const PlainObject normalized() const;
+    EIGEN_DEVICE_FUNC const PlainObject stableNormalized() const;
+    EIGEN_DEVICE_FUNC void normalize();
+    EIGEN_DEVICE_FUNC void stableNormalize();
 
-    const AdjointReturnType adjoint() const;
-    void adjointInPlace();
+    EIGEN_DEVICE_FUNC const AdjointReturnType adjoint() const;
+    EIGEN_DEVICE_FUNC void adjointInPlace();
 
     typedef Diagonal<Derived> DiagonalReturnType;
+    EIGEN_DEVICE_FUNC
     DiagonalReturnType diagonal();
+
     typedef typename internal::add_const<Diagonal<const Derived> >::type ConstDiagonalReturnType;
+    EIGEN_DEVICE_FUNC
     ConstDiagonalReturnType diagonal() const;
 
     template<int Index> struct DiagonalIndexReturnType { typedef Diagonal<Derived,Index> Type; };
     template<int Index> struct ConstDiagonalIndexReturnType { typedef const Diagonal<const Derived,Index> Type; };
 
-    template<int Index> typename DiagonalIndexReturnType<Index>::Type diagonal();
-    template<int Index> typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const;
-    
+    template<int Index>
+    EIGEN_DEVICE_FUNC
+    typename DiagonalIndexReturnType<Index>::Type diagonal();
+
+    template<int Index>
+    EIGEN_DEVICE_FUNC
+    typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const;
+
     typedef Diagonal<Derived,DynamicIndex> DiagonalDynamicIndexReturnType;
     typedef typename internal::add_const<Diagonal<const Derived,DynamicIndex> >::type ConstDiagonalDynamicIndexReturnType;
 
+    EIGEN_DEVICE_FUNC
     DiagonalDynamicIndexReturnType diagonal(Index index);
+    EIGEN_DEVICE_FUNC
     ConstDiagonalDynamicIndexReturnType diagonal(Index index) const;
 
-    #ifdef EIGEN2_SUPPORT
-    template<unsigned int Mode> typename internal::eigen2_part_return_type<Derived, Mode>::type part();
-    template<unsigned int Mode> const typename internal::eigen2_part_return_type<Derived, Mode>::type part() const;
-    
-    // huuuge hack. make Eigen2's matrix.part<Diagonal>() work in eigen3. Problem: Diagonal is now a class template instead
-    // of an integer constant. Solution: overload the part() method template wrt template parameters list.
-    template<template<typename T, int N> class U>
-    const DiagonalWrapper<ConstDiagonalReturnType> part() const
-    { return diagonal().asDiagonal(); }
-    #endif // EIGEN2_SUPPORT
-
     template<unsigned int Mode> struct TriangularViewReturnType { typedef TriangularView<Derived, Mode> Type; };
     template<unsigned int Mode> struct ConstTriangularViewReturnType { typedef const TriangularView<const Derived, Mode> Type; };
 
-    template<unsigned int Mode> typename TriangularViewReturnType<Mode>::Type triangularView();
-    template<unsigned int Mode> typename ConstTriangularViewReturnType<Mode>::Type triangularView() const;
+    template<unsigned int Mode>
+    EIGEN_DEVICE_FUNC
+    typename TriangularViewReturnType<Mode>::Type triangularView();
+    template<unsigned int Mode>
+    EIGEN_DEVICE_FUNC
+    typename ConstTriangularViewReturnType<Mode>::Type triangularView() const;
 
     template<unsigned int UpLo> struct SelfAdjointViewReturnType { typedef SelfAdjointView<Derived, UpLo> Type; };
     template<unsigned int UpLo> struct ConstSelfAdjointViewReturnType { typedef const SelfAdjointView<const Derived, UpLo> Type; };
 
-    template<unsigned int UpLo> typename SelfAdjointViewReturnType<UpLo>::Type selfadjointView();
-    template<unsigned int UpLo> typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
+    template<unsigned int UpLo>
+    EIGEN_DEVICE_FUNC
+    typename SelfAdjointViewReturnType<UpLo>::Type selfadjointView();
+    template<unsigned int UpLo>
+    EIGEN_DEVICE_FUNC
+    typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
 
     const SparseView<Derived> sparseView(const Scalar& m_reference = Scalar(0),
                                          const typename NumTraits<Scalar>::Real& m_epsilon = NumTraits<Scalar>::dummy_precision()) const;
-    static const IdentityReturnType Identity();
-    static const IdentityReturnType Identity(Index rows, Index cols);
-    static const BasisReturnType Unit(Index size, Index i);
-    static const BasisReturnType Unit(Index i);
-    static const BasisReturnType UnitX();
-    static const BasisReturnType UnitY();
-    static const BasisReturnType UnitZ();
-    static const BasisReturnType UnitW();
-
+    EIGEN_DEVICE_FUNC static const IdentityReturnType Identity();
+    EIGEN_DEVICE_FUNC static const IdentityReturnType Identity(Index rows, Index cols);
+    EIGEN_DEVICE_FUNC static const BasisReturnType Unit(Index size, Index i);
+    EIGEN_DEVICE_FUNC static const BasisReturnType Unit(Index i);
+    EIGEN_DEVICE_FUNC static const BasisReturnType UnitX();
+    EIGEN_DEVICE_FUNC static const BasisReturnType UnitY();
+    EIGEN_DEVICE_FUNC static const BasisReturnType UnitZ();
+    EIGEN_DEVICE_FUNC static const BasisReturnType UnitW();
+
+    EIGEN_DEVICE_FUNC
     const DiagonalWrapper<const Derived> asDiagonal() const;
     const PermutationWrapper<const Derived> asPermutation() const;
 
+    EIGEN_DEVICE_FUNC
     Derived& setIdentity();
+    EIGEN_DEVICE_FUNC
     Derived& setIdentity(Index rows, Index cols);
 
     bool isIdentity(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
     bool isDiagonal(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
@@ -284,143 +292,134 @@
     /** \returns true if each coefficients of \c *this and \a other are all exactly equal.
       * \warning When using floating point scalar values you probably should rather use a
       *          fuzzy comparison such as isApprox()
       * \sa isApprox(), operator!= */
     template<typename OtherDerived>
-    inline bool operator==(const MatrixBase<OtherDerived>& other) const
+    EIGEN_DEVICE_FUNC inline bool operator==(const MatrixBase<OtherDerived>& other) const
     { return cwiseEqual(other).all(); }
 
     /** \returns true if at least one pair of coefficients of \c *this and \a other are not exactly equal to each other.
       * \warning When using floating point scalar values you probably should rather use a
       *          fuzzy comparison such as isApprox()
       * \sa isApprox(), operator== */
     template<typename OtherDerived>
-    inline bool operator!=(const MatrixBase<OtherDerived>& other) const
+    EIGEN_DEVICE_FUNC inline bool operator!=(const MatrixBase<OtherDerived>& other) const
     { return cwiseNotEqual(other).any(); }
 
     NoAlias<Derived,Eigen::MatrixBase > noalias();
 
-    inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
-    inline ForceAlignedAccess<Derived> forceAlignedAccess();
-    template<bool Enable> inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type forceAlignedAccessIf() const;
-    template<bool Enable> inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
-
-    Scalar trace() const;
-
-/////////// Array module ///////////
-
-    template<int p> RealScalar lpNorm() const;
-
-    MatrixBase<Derived>& matrix() { return *this; }
-    const MatrixBase<Derived>& matrix() const { return *this; }
+    // TODO forceAlignedAccess is temporarily disabled
+    // Need to find a nicer workaround.
+    inline const Derived& forceAlignedAccess() const { return derived(); }
+    inline Derived& forceAlignedAccess() { return derived(); }
+    template<bool Enable> inline const Derived& forceAlignedAccessIf() const { return derived(); }
+    template<bool Enable> inline Derived& forceAlignedAccessIf() { return derived(); }
+
+    EIGEN_DEVICE_FUNC Scalar trace() const;
+
+    template<int p> EIGEN_DEVICE_FUNC RealScalar lpNorm() const;
+
+    EIGEN_DEVICE_FUNC MatrixBase<Derived>& matrix() { return *this; }
+    EIGEN_DEVICE_FUNC const MatrixBase<Derived>& matrix() const { return *this; }
 
     /** \returns an \link Eigen::ArrayBase Array \endlink expression of this matrix
       * \sa ArrayBase::matrix() */
-    ArrayWrapper<Derived> array() { return derived(); }
-    const ArrayWrapper<const Derived> array() const { return derived(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ArrayWrapper<Derived> array() { return ArrayWrapper<Derived>(derived()); }
+    /** \returns a const \link Eigen::ArrayBase Array \endlink expression of this matrix
+      * \sa ArrayBase::matrix() */
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const ArrayWrapper<const Derived> array() const { return ArrayWrapper<const Derived>(derived()); }
 
 /////////// LU module ///////////
 
-    const FullPivLU<PlainObject> fullPivLu() const;
-    const PartialPivLU<PlainObject> partialPivLu() const;
-
-    #if EIGEN2_SUPPORT_STAGE < STAGE20_RESOLVE_API_CONFLICTS
-    const LU<PlainObject> lu() const;
-    #endif
-
-    #ifdef EIGEN2_SUPPORT
-    const LU<PlainObject> eigen2_lu() const;
-    #endif
-
-    #if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
-    const PartialPivLU<PlainObject> lu() const;
-    #endif
-    
-    #ifdef EIGEN2_SUPPORT
-    template<typename ResultType>
-    void computeInverse(MatrixBase<ResultType> *result) const {
-      *result = this->inverse();
-    }
-    #endif
-
-    const internal::inverse_impl<Derived> inverse() const;
-    template<typename ResultType>
-    void computeInverseAndDetWithCheck(
+    inline const FullPivLU<PlainObject> fullPivLu() const;
+    inline const PartialPivLU<PlainObject> partialPivLu() const;
+
+    inline const PartialPivLU<PlainObject> lu() const;
+
+    inline const Inverse<Derived> inverse() const;
+
+    template<typename ResultType>
+    inline void computeInverseAndDetWithCheck(
       ResultType& inverse,
       typename ResultType::Scalar& determinant,
       bool& invertible,
       const RealScalar& absDeterminantThreshold = NumTraits<Scalar>::dummy_precision()
     ) const;
     template<typename ResultType>
-    void computeInverseWithCheck(
+    inline void computeInverseWithCheck(
       ResultType& inverse,
       bool& invertible,
       const RealScalar& absDeterminantThreshold = NumTraits<Scalar>::dummy_precision()
     ) const;
     Scalar determinant() const;
 
 /////////// Cholesky module ///////////
 
-    const LLT<PlainObject>  llt() const;
-    const LDLT<PlainObject> ldlt() const;
+    inline const LLT<PlainObject>  llt() const;
+    inline const LDLT<PlainObject> ldlt() const;
 
 /////////// QR module ///////////
 
-    const HouseholderQR<PlainObject> householderQr() const;
-    const ColPivHouseholderQR<PlainObject> colPivHouseholderQr() const;
-    const FullPivHouseholderQR<PlainObject> fullPivHouseholderQr() const;
-    
-    #ifdef EIGEN2_SUPPORT
-    const QR<PlainObject> qr() const;
-    #endif
-
-    EigenvaluesReturnType eigenvalues() const;
-    RealScalar operatorNorm() const;
+    inline const HouseholderQR<PlainObject> householderQr() const;
+    inline const ColPivHouseholderQR<PlainObject> colPivHouseholderQr() const;
+    inline const FullPivHouseholderQR<PlainObject> fullPivHouseholderQr() const;
+    inline const CompleteOrthogonalDecomposition<PlainObject> completeOrthogonalDecomposition() const;
+
+/////////// Eigenvalues module ///////////
+
+    inline EigenvaluesReturnType eigenvalues() const;
+    inline RealScalar operatorNorm() const;
 
 /////////// SVD module ///////////
 
-    JacobiSVD<PlainObject> jacobiSvd(unsigned int computationOptions = 0) const;
-
-    #ifdef EIGEN2_SUPPORT
-    SVD<PlainObject> svd() const;
-    #endif
+    inline JacobiSVD<PlainObject> jacobiSvd(unsigned int computationOptions = 0) const;
+    inline BDCSVD<PlainObject>    bdcSvd(unsigned int computationOptions = 0) const;
 
 /////////// Geometry module ///////////
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     /// \internal helper struct to form the return type of the cross product
     template<typename OtherDerived> struct cross_product_return_type {
-      typedef typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType Scalar;
+      typedef typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType Scalar;
       typedef Matrix<Scalar,MatrixBase::RowsAtCompileTime,MatrixBase::ColsAtCompileTime> type;
     };
     #endif // EIGEN_PARSED_BY_DOXYGEN
     template<typename OtherDerived>
-    typename cross_product_return_type<OtherDerived>::type
+    EIGEN_DEVICE_FUNC
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    inline typename cross_product_return_type<OtherDerived>::type
+#else
+    inline PlainObject
+#endif
     cross(const MatrixBase<OtherDerived>& other) const;
+
     template<typename OtherDerived>
-    PlainObject cross3(const MatrixBase<OtherDerived>& other) const;
-    PlainObject unitOrthogonal(void) const;
-    Matrix<Scalar,3,1> eulerAngles(Index a0, Index a1, Index a2) const;
-    
-    #if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
-    ScalarMultipleReturnType operator*(const UniformScaling<Scalar>& s) const;
+    EIGEN_DEVICE_FUNC
+    inline PlainObject cross3(const MatrixBase<OtherDerived>& other) const;
+
+    EIGEN_DEVICE_FUNC
+    inline PlainObject unitOrthogonal(void) const;
+
+    EIGEN_DEVICE_FUNC
+    inline Matrix<Scalar,3,1> eulerAngles(Index a0, Index a1, Index a2) const;
+
     // put this as separate enum value to work around possible GCC 4.3 bug (?)
-    enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1?Vertical:Horizontal };
+    enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1&&RowsAtCompileTime==1 ? ((internal::traits<Derived>::Flags&RowMajorBit)==RowMajorBit ? Horizontal : Vertical)
+                                          : ColsAtCompileTime==1 ? Vertical : Horizontal };
     typedef Homogeneous<Derived, HomogeneousReturnTypeDirection> HomogeneousReturnType;
-    HomogeneousReturnType homogeneous() const;
-    #endif
-    
+    EIGEN_DEVICE_FUNC
+    inline HomogeneousReturnType homogeneous() const;
+
     enum {
       SizeMinusOne = SizeAtCompileTime==Dynamic ? Dynamic : SizeAtCompileTime-1
     };
     typedef Block<const Derived,
                   internal::traits<Derived>::ColsAtCompileTime==1 ? SizeMinusOne : 1,
                   internal::traits<Derived>::ColsAtCompileTime==1 ? 1 : SizeMinusOne> ConstStartMinusOne;
-    typedef CwiseUnaryOp<internal::scalar_quotient1_op<typename internal::traits<Derived>::Scalar>,
-                const ConstStartMinusOne > HNormalizedReturnType;
-
-    const HNormalizedReturnType hnormalized() const;
+    typedef EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(ConstStartMinusOne,Scalar,quotient) HNormalizedReturnType;
+    EIGEN_DEVICE_FUNC
+    inline const HNormalizedReturnType hnormalized() const;
 
 ////////// Householder module ///////////
 
     void makeHouseholderInPlace(Scalar& tau, RealScalar& beta);
     template<typename EssentialPart>
@@ -439,10 +438,19 @@
 
     template<typename OtherScalar>
     void applyOnTheLeft(Index p, Index q, const JacobiRotation<OtherScalar>& j);
     template<typename OtherScalar>
     void applyOnTheRight(Index p, Index q, const JacobiRotation<OtherScalar>& j);
+
+///////// SparseCore module /////////
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE const typename SparseMatrixBase<OtherDerived>::template CwiseProductDenseReturnType<Derived>::Type
+    cwiseProduct(const SparseMatrixBase<OtherDerived> &other) const
+    {
+      return other.cwiseProduct(derived());
+    }
 
 ///////// MatrixFunctions module /////////
 
     typedef typename internal::stem_function<Scalar>::type StemFunction;
     const MatrixExponentialReturnValue<Derived> exp() const;
@@ -452,53 +460,19 @@
     const MatrixFunctionReturnValue<Derived> cos() const;
     const MatrixFunctionReturnValue<Derived> sin() const;
     const MatrixSquareRootReturnValue<Derived> sqrt() const;
     const MatrixLogarithmReturnValue<Derived> log() const;
     const MatrixPowerReturnValue<Derived> pow(const RealScalar& p) const;
-
-#ifdef EIGEN2_SUPPORT
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    Derived& operator+=(const Flagged<ProductBase<ProductDerived, Lhs,Rhs>, 0,
-                                      EvalBeforeAssigningBit>& other);
-
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    Derived& operator-=(const Flagged<ProductBase<ProductDerived, Lhs,Rhs>, 0,
-                                      EvalBeforeAssigningBit>& other);
-
-    /** \deprecated because .lazy() is deprecated
-      * Overloaded for cache friendly product evaluation */
-    template<typename OtherDerived>
-    Derived& lazyAssign(const Flagged<OtherDerived, 0, EvalBeforeAssigningBit>& other)
-    { return lazyAssign(other._expression()); }
-
-    template<unsigned int Added>
-    const Flagged<Derived, Added, 0> marked() const;
-    const Flagged<Derived, 0, EvalBeforeAssigningBit> lazy() const;
-
-    inline const Cwise<Derived> cwise() const;
-    inline Cwise<Derived> cwise();
-
-    VectorBlock<Derived> start(Index size);
-    const VectorBlock<const Derived> start(Index size) const;
-    VectorBlock<Derived> end(Index size);
-    const VectorBlock<const Derived> end(Index size) const;
-    template<int Size> VectorBlock<Derived,Size> start();
-    template<int Size> const VectorBlock<const Derived,Size> start() const;
-    template<int Size> VectorBlock<Derived,Size> end();
-    template<int Size> const VectorBlock<const Derived,Size> end() const;
-
-    Minor<Derived> minor(Index row, Index col);
-    const Minor<Derived> minor(Index row, Index col) const;
-#endif
+    const MatrixComplexPowerReturnValue<Derived> pow(const std::complex<RealScalar>& p) const;
 
   protected:
-    MatrixBase() : Base() {}
+    EIGEN_DEVICE_FUNC MatrixBase() : Base() {}
 
   private:
-    explicit MatrixBase(int);
-    MatrixBase(int,int);
-    template<typename OtherDerived> explicit MatrixBase(const MatrixBase<OtherDerived>&);
+    EIGEN_DEVICE_FUNC explicit MatrixBase(int);
+    EIGEN_DEVICE_FUNC MatrixBase(int,int);
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC explicit MatrixBase(const MatrixBase<OtherDerived>&);
   protected:
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator+=(const ArrayBase<OtherDerived>& )
     {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
     // mixing arrays and matrices is not legal

Index: 3rd_party/eigen/Eigen/src/Core/NestByValue.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/NestByValue.h
+++ 3rd_party/eigen/Eigen/src/Core/NestByValue.h
@@ -10,61 +10,60 @@
 
 #ifndef EIGEN_NESTBYVALUE_H
 #define EIGEN_NESTBYVALUE_H
 
 namespace Eigen {
+
+namespace internal {
+template<typename ExpressionType>
+struct traits<NestByValue<ExpressionType> > : public traits<ExpressionType>
+{};
+}
 
 /** \class NestByValue
   * \ingroup Core_Module
   *
   * \brief Expression which must be nested by value
   *
-  * \param ExpressionType the type of the object of which we are requiring nesting-by-value
+  * \tparam ExpressionType the type of the object of which we are requiring nesting-by-value
   *
   * This class is the return type of MatrixBase::nestByValue()
   * and most of the time this is the only way it is used.
   *
   * \sa MatrixBase::nestByValue()
   */
-
-namespace internal {
-template<typename ExpressionType>
-struct traits<NestByValue<ExpressionType> > : public traits<ExpressionType>
-{};
-}
-
 template<typename ExpressionType> class NestByValue
   : public internal::dense_xpr_base< NestByValue<ExpressionType> >::type
 {
   public:
 
     typedef typename internal::dense_xpr_base<NestByValue>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(NestByValue)
 
-    inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
-
-    inline Index rows() const { return m_expression.rows(); }
-    inline Index cols() const { return m_expression.cols(); }
-    inline Index outerStride() const { return m_expression.outerStride(); }
-    inline Index innerStride() const { return m_expression.innerStride(); }
-
-    inline const CoeffReturnType coeff(Index row, Index col) const
+    EIGEN_DEVICE_FUNC explicit inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
+
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_expression.rows(); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); }
+    EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); }
+    EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); }
+
+    EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
 
-    inline Scalar& coeffRef(Index row, Index col)
+    EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
     {
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const CoeffReturnType coeff(Index index) const
+    EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
 
-    inline Scalar& coeffRef(Index index)
+    EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
     {
       return m_expression.const_cast_derived().coeffRef(index);
     }
 
     template<int LoadMode>
@@ -89,11 +88,11 @@
     inline void writePacket(Index index, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
     }
 
-    operator const ExpressionType&() const { return m_expression; }
+    EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; }
 
   protected:
     const ExpressionType m_expression;
 };
 

Index: 3rd_party/eigen/Eigen/src/Core/NoAlias.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/NoAlias.h
+++ 3rd_party/eigen/Eigen/src/Core/NoAlias.h
@@ -15,11 +15,11 @@
 /** \class NoAlias
   * \ingroup Core_Module
   *
   * \brief Pseudo expression providing an operator = assuming no aliasing
   *
-  * \param ExpressionType the type of the object on which to do the lazy assignment
+  * \tparam ExpressionType the type of the object on which to do the lazy assignment
   *
   * This class represents an expression with special assignment operators
   * assuming no aliasing between the target expression and the source expression.
   * More precisely it alloas to bypass the EvalBeforeAssignBit flag of the source expression.
   * It is the return type of MatrixBase::noalias()
@@ -28,66 +28,40 @@
   * \sa MatrixBase::noalias()
   */
 template<typename ExpressionType, template <typename> class StorageBase>
 class NoAlias
 {
-    typedef typename ExpressionType::Scalar Scalar;
-  public:
-    NoAlias(ExpressionType& expression) : m_expression(expression) {}
-
-    /** Behaves like MatrixBase::lazyAssign(other)
-      * \sa MatrixBase::lazyAssign() */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE ExpressionType& operator=(const StorageBase<OtherDerived>& other)
-    { return internal::assign_selector<ExpressionType,OtherDerived,false>::run(m_expression,other.derived()); }
-
-    /** \sa MatrixBase::operator+= */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE ExpressionType& operator+=(const StorageBase<OtherDerived>& other)
-    {
-      typedef SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, ExpressionType, OtherDerived> SelfAdder;
-      SelfAdder tmp(m_expression);
-      typedef typename internal::nested<OtherDerived>::type OtherDerivedNested;
-      typedef typename internal::remove_all<OtherDerivedNested>::type _OtherDerivedNested;
-      internal::assign_selector<SelfAdder,_OtherDerivedNested,false>::run(tmp,OtherDerivedNested(other.derived()));
-      return m_expression;
-    }
-
-    /** \sa MatrixBase::operator-= */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE ExpressionType& operator-=(const StorageBase<OtherDerived>& other)
-    {
-      typedef SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, ExpressionType, OtherDerived> SelfAdder;
-      SelfAdder tmp(m_expression);
-      typedef typename internal::nested<OtherDerived>::type OtherDerivedNested;
-      typedef typename internal::remove_all<OtherDerivedNested>::type _OtherDerivedNested;
-      internal::assign_selector<SelfAdder,_OtherDerivedNested,false>::run(tmp,OtherDerivedNested(other.derived()));
-      return m_expression;
-    }
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    EIGEN_STRONG_INLINE ExpressionType& operator+=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
-    { other.derived().addTo(m_expression); return m_expression; }
-
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    EIGEN_STRONG_INLINE ExpressionType& operator-=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
-    { other.derived().subTo(m_expression); return m_expression; }
-
-    template<typename Lhs, typename Rhs, int NestingFlags>
-    EIGEN_STRONG_INLINE ExpressionType& operator+=(const CoeffBasedProduct<Lhs,Rhs,NestingFlags>& other)
-    { return m_expression.derived() += CoeffBasedProduct<Lhs,Rhs,NestByRefBit>(other.lhs(), other.rhs()); }
-
-    template<typename Lhs, typename Rhs, int NestingFlags>
-    EIGEN_STRONG_INLINE ExpressionType& operator-=(const CoeffBasedProduct<Lhs,Rhs,NestingFlags>& other)
-    { return m_expression.derived() -= CoeffBasedProduct<Lhs,Rhs,NestByRefBit>(other.lhs(), other.rhs()); }
-    
-    template<typename OtherDerived>
-    ExpressionType& operator=(const ReturnByValue<OtherDerived>& func)
-    { return m_expression = func; }
-#endif
-
+  public:
+    typedef typename ExpressionType::Scalar Scalar;
+    
+    explicit NoAlias(ExpressionType& expression) : m_expression(expression) {}
+    
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE ExpressionType& operator=(const StorageBase<OtherDerived>& other)
+    {
+      call_assignment_no_alias(m_expression, other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
+      return m_expression;
+    }
+    
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE ExpressionType& operator+=(const StorageBase<OtherDerived>& other)
+    {
+      call_assignment_no_alias(m_expression, other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
+      return m_expression;
+    }
+    
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE ExpressionType& operator-=(const StorageBase<OtherDerived>& other)
+    {
+      call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
+      return m_expression;
+    }
+
+    EIGEN_DEVICE_FUNC
     ExpressionType& expression() const
     {
       return m_expression;
     }
 
@@ -124,11 +98,11 @@
   * \sa class NoAlias
   */
 template<typename Derived>
 NoAlias<Derived,MatrixBase> MatrixBase<Derived>::noalias()
 {
-  return derived();
+  return NoAlias<Derived, Eigen::MatrixBase >(derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_NOALIAS_H

Index: 3rd_party/eigen/Eigen/src/Core/NumTraits.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/NumTraits.h
+++ 3rd_party/eigen/Eigen/src/Core/NumTraits.h
@@ -10,28 +10,61 @@
 #ifndef EIGEN_NUMTRAITS_H
 #define EIGEN_NUMTRAITS_H
 
 namespace Eigen {
 
+namespace internal {
+
+// default implementation of digits10(), based on numeric_limits if specialized,
+// 0 for integer types, and log10(epsilon()) otherwise.
+template< typename T,
+          bool use_numeric_limits = std::numeric_limits<T>::is_specialized,
+          bool is_integer = NumTraits<T>::IsInteger>
+struct default_digits10_impl
+{
+  static int run() { return std::numeric_limits<T>::digits10; }
+};
+
+template<typename T>
+struct default_digits10_impl<T,false,false> // Floating point
+{
+  static int run() {
+    using std::log10;
+    using std::ceil;
+    typedef typename NumTraits<T>::Real Real;
+    return int(ceil(-log10(NumTraits<Real>::epsilon())));
+  }
+};
+
+template<typename T>
+struct default_digits10_impl<T,false,true> // Integer
+{
+  static int run() { return 0; }
+};
+
+} // end namespace internal
+
 /** \class NumTraits
   * \ingroup Core_Module
   *
   * \brief Holds information about the various numeric (i.e. scalar) types allowed by Eigen.
   *
-  * \param T the numeric type at hand
+  * \tparam T the numeric type at hand
   *
   * This class stores enums, typedefs and static methods giving information about a numeric type.
   *
   * The provided data consists of:
-  * \li A typedef \a Real, giving the "real part" type of \a T. If \a T is already real,
-  *     then \a Real is just a typedef to \a T. If \a T is \c std::complex<U> then \a Real
+  * \li A typedef \c Real, giving the "real part" type of \a T. If \a T is already real,
+  *     then \c Real is just a typedef to \a T. If \a T is \c std::complex<U> then \c Real
   *     is a typedef to \a U.
-  * \li A typedef \a NonInteger, giving the type that should be used for operations producing non-integral values,
+  * \li A typedef \c NonInteger, giving the type that should be used for operations producing non-integral values,
   *     such as quotients, square roots, etc. If \a T is a floating-point type, then this typedef just gives
   *     \a T again. Note however that many Eigen functions such as internal::sqrt simply refuse to
   *     take integers. Outside of a few cases, Eigen doesn't do automatic type promotion. Thus, this typedef is
   *     only intended as a helper for code that needs to explicitly promote types.
+  * \li A typedef \c Literal giving the type to use for numeric literals such as "2" or "0.5". For instance, for \c std::complex<U>, Literal is defined as \c U.
+  *     Of course, this type must be fully compatible with \a T. In doubt, just use \a T here.
   * \li A typedef \a Nested giving the type to use to nest a value inside of the expression tree. If you don't know what
   *     this means, just use \a T here.
   * \li An enum value \a IsComplex. It is equal to 1 if \a T is a \c std::complex
   *     type, and to 0 otherwise.
   * \li An enum value \a IsInteger. It is equal to \c 1 if \a T is an integer type such as \c int,
@@ -40,14 +73,18 @@
   *     to by move / add / mul instructions respectively, assuming the data is already stored in CPU registers.
   *     Stay vague here. No need to do architecture-specific stuff.
   * \li An enum value \a IsSigned. It is equal to \c 1 if \a T is a signed type and to 0 if \a T is unsigned.
   * \li An enum value \a RequireInitialization. It is equal to \c 1 if the constructor of the numeric type \a T must
   *     be called, and to 0 if it is safe not to call it. Default is 0 if \a T is an arithmetic type, and 1 otherwise.
-  * \li An epsilon() function which, unlike std::numeric_limits::epsilon(), returns a \a Real instead of a \a T.
+  * \li An epsilon() function which, unlike <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/epsilon">std::numeric_limits::epsilon()</a>,
+  *     it returns a \a Real instead of a \a T.
   * \li A dummy_precision() function returning a weak epsilon value. It is mainly used as a default
   *     value by the fuzzy comparison operators.
   * \li highest() and lowest() functions returning the highest and lowest possible values respectively.
+  * \li digits10() function returning the number of decimal digits that can be represented without change. This is
+  *     the analogue of <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/digits10">std::numeric_limits<T>::digits10</a>
+  *     which is used as the default implementation if specialized.
   */
 
 template<typename T> struct GenericNumTraits
 {
   enum {
@@ -65,39 +102,66 @@
                      IsInteger,
                      typename internal::conditional<sizeof(T)<=2, float, double>::type,
                      T
                    >::type NonInteger;
   typedef T Nested;
+  typedef T Literal;
+
+  EIGEN_DEVICE_FUNC
+  static inline Real epsilon()
+  {
+    return numext::numeric_limits<T>::epsilon();
+  }
+
+  EIGEN_DEVICE_FUNC
+  static inline int digits10()
+  {
+    return internal::default_digits10_impl<T>::run();
+  }
 
-  static inline Real epsilon() { return std::numeric_limits<T>::epsilon(); }
+  EIGEN_DEVICE_FUNC
   static inline Real dummy_precision()
   {
     // make sure to override this for floating-point types
     return Real(0);
   }
-  static inline T highest() { return (std::numeric_limits<T>::max)(); }
-  static inline T lowest()  { return IsInteger ? (std::numeric_limits<T>::min)() : (-(std::numeric_limits<T>::max)()); }
-  
-#ifdef EIGEN2_SUPPORT
-  enum {
-    HasFloatingPoint = !IsInteger
-  };
-  typedef NonInteger FloatingPoint;
-#endif
+
+
+  EIGEN_DEVICE_FUNC
+  static inline T highest() {
+    return (numext::numeric_limits<T>::max)();
+  }
+
+  EIGEN_DEVICE_FUNC
+  static inline T lowest()  {
+    return IsInteger ? (numext::numeric_limits<T>::min)() : (-(numext::numeric_limits<T>::max)());
+  }
+
+  EIGEN_DEVICE_FUNC
+  static inline T infinity() {
+    return numext::numeric_limits<T>::infinity();
+  }
+
+  EIGEN_DEVICE_FUNC
+  static inline T quiet_NaN() {
+    return numext::numeric_limits<T>::quiet_NaN();
+  }
 };
 
 template<typename T> struct NumTraits : GenericNumTraits<T>
 {};
 
 template<> struct NumTraits<float>
   : GenericNumTraits<float>
 {
+  EIGEN_DEVICE_FUNC
   static inline float dummy_precision() { return 1e-5f; }
 };
 
 template<> struct NumTraits<double> : GenericNumTraits<double>
 {
+  EIGEN_DEVICE_FUNC
   static inline double dummy_precision() { return 1e-12; }
 };
 
 template<> struct NumTraits<long double>
   : GenericNumTraits<long double>
@@ -107,20 +171,25 @@
 
 template<typename _Real> struct NumTraits<std::complex<_Real> >
   : GenericNumTraits<std::complex<_Real> >
 {
   typedef _Real Real;
+  typedef typename NumTraits<_Real>::Literal Literal;
   enum {
     IsComplex = 1,
     RequireInitialization = NumTraits<_Real>::RequireInitialization,
     ReadCost = 2 * NumTraits<_Real>::ReadCost,
     AddCost = 2 * NumTraits<Real>::AddCost,
     MulCost = 4 * NumTraits<Real>::MulCost + 2 * NumTraits<Real>::AddCost
   };
 
+  EIGEN_DEVICE_FUNC
   static inline Real epsilon() { return NumTraits<Real>::epsilon(); }
+  EIGEN_DEVICE_FUNC
   static inline Real dummy_precision() { return NumTraits<Real>::dummy_precision(); }
+  EIGEN_DEVICE_FUNC
+  static inline int digits10() { return NumTraits<Real>::digits10(); }
 };
 
 template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
 struct NumTraits<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
 {
@@ -128,23 +197,52 @@
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef Array<RealScalar, Rows, Cols, Options, MaxRows, MaxCols> Real;
   typedef typename NumTraits<Scalar>::NonInteger NonIntegerScalar;
   typedef Array<NonIntegerScalar, Rows, Cols, Options, MaxRows, MaxCols> NonInteger;
   typedef ArrayType & Nested;
-  
+  typedef typename NumTraits<Scalar>::Literal Literal;
+
   enum {
     IsComplex = NumTraits<Scalar>::IsComplex,
     IsInteger = NumTraits<Scalar>::IsInteger,
     IsSigned  = NumTraits<Scalar>::IsSigned,
     RequireInitialization = 1,
-    ReadCost = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::ReadCost,
-    AddCost  = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::AddCost,
-    MulCost  = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::MulCost
+    ReadCost = ArrayType::SizeAtCompileTime==Dynamic ? HugeCost : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::ReadCost,
+    AddCost  = ArrayType::SizeAtCompileTime==Dynamic ? HugeCost : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::AddCost,
+    MulCost  = ArrayType::SizeAtCompileTime==Dynamic ? HugeCost : ArrayType::SizeAtCompileTime * NumTraits<Scalar>::MulCost
   };
-  
+
+  EIGEN_DEVICE_FUNC
   static inline RealScalar epsilon() { return NumTraits<RealScalar>::epsilon(); }
+  EIGEN_DEVICE_FUNC
   static inline RealScalar dummy_precision() { return NumTraits<RealScalar>::dummy_precision(); }
+
+  static inline int digits10() { return NumTraits<Scalar>::digits10(); }
+};
+
+template<> struct NumTraits<std::string>
+  : GenericNumTraits<std::string>
+{
+  enum {
+    RequireInitialization = 1,
+    ReadCost = HugeCost,
+    AddCost  = HugeCost,
+    MulCost  = HugeCost
+  };
+
+  static inline int digits10() { return 0; }
+
+private:
+  static inline std::string epsilon();
+  static inline std::string dummy_precision();
+  static inline std::string lowest();
+  static inline std::string highest();
+  static inline std::string infinity();
+  static inline std::string quiet_NaN();
 };
+
+// Empty specialization for void to allow template specialization based on NumTraits<T>::Real with T==void and SFINAE.
+template<> struct NumTraits<void> {};
 
 } // end namespace Eigen
 
 #endif // EIGEN_NUMTRAITS_H

Index: 3rd_party/eigen/Eigen/src/Core/PermutationMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/PermutationMatrix.h
+++ 3rd_party/eigen/Eigen/src/Core/PermutationMatrix.h
@@ -1,10 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2009-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -11,18 +11,22 @@
 #ifndef EIGEN_PERMUTATIONMATRIX_H
 #define EIGEN_PERMUTATIONMATRIX_H
 
 namespace Eigen { 
 
-template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
+namespace internal {
+
+enum PermPermProduct_t {PermPermProduct};
+
+} // end namespace internal
 
 /** \class PermutationBase
   * \ingroup Core_Module
   *
   * \brief Base class for permutations
   *
-  * \param Derived the derived class
+  * \tparam Derived the derived class
   *
   * This class is the base class for all expressions representing a permutation matrix,
   * internally stored as a vector of integers.
   * The convention followed here is that if \f$ \sigma \f$ is a permutation, the corresponding permutation matrix
   * \f$ P_\sigma \f$ is such that if \f$ (e_1,\ldots,e_p) \f$ is the canonical basis, we have:
@@ -36,21 +40,10 @@
   * operator* to multiply any kind of permutation object with any kind of matrix expression (MatrixBase)
   * on either side.
   *
   * \sa class PermutationMatrix, class PermutationWrapper
   */
-
-namespace internal {
-
-template<typename PermutationType, typename MatrixType, int Side, bool Transposed=false>
-struct permut_matrix_product_retval;
-template<typename PermutationType, typename MatrixType, int Side, bool Transposed=false>
-struct permut_sparsematrix_product_retval;
-enum PermPermProduct_t {PermPermProduct};
-
-} // end namespace internal
-
 template<typename Derived>
 class PermutationBase : public EigenBase<Derived>
 {
     typedef internal::traits<Derived> Traits;
     typedef EigenBase<Derived> Base;
@@ -58,23 +51,24 @@
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     typedef typename Traits::IndicesType IndicesType;
     enum {
       Flags = Traits::Flags,
-      CoeffReadCost = Traits::CoeffReadCost,
       RowsAtCompileTime = Traits::RowsAtCompileTime,
       ColsAtCompileTime = Traits::ColsAtCompileTime,
       MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = Traits::MaxColsAtCompileTime
     };
-    typedef typename Traits::Scalar Scalar;
-    typedef typename Traits::Index Index;
-    typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime,0,MaxRowsAtCompileTime,MaxColsAtCompileTime>
+    typedef typename Traits::StorageIndex StorageIndex;
+    typedef Matrix<StorageIndex,RowsAtCompileTime,ColsAtCompileTime,0,MaxRowsAtCompileTime,MaxColsAtCompileTime>
             DenseMatrixType;
-    typedef PermutationMatrix<IndicesType::SizeAtCompileTime,IndicesType::MaxSizeAtCompileTime,Index>
+    typedef PermutationMatrix<IndicesType::SizeAtCompileTime,IndicesType::MaxSizeAtCompileTime,StorageIndex>
             PlainPermutationType;
+    typedef PlainPermutationType PlainObject;
     using Base::derived;
+    typedef Inverse<Derived> InverseReturnType;
+    typedef void Scalar;
     #endif
 
     /** Copies the other permutation into *this */
     template<typename OtherDerived>
     Derived& operator=(const PermutationBase<OtherDerived>& other)
@@ -116,11 +110,11 @@
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename DenseDerived>
     void evalTo(MatrixBase<DenseDerived>& other) const
     {
       other.setZero();
-      for (int i=0; i<rows();++i)
+      for (Index i=0; i<rows(); ++i)
         other.coeffRef(indices().coeff(i),i) = typename DenseDerived::Scalar(1);
     }
     #endif
 
     /** \returns a Matrix object initialized from this permutation matrix. Notice that it
@@ -145,11 +139,12 @@
     }
 
     /** Sets *this to be the identity permutation matrix */
     void setIdentity()
     {
-      for(Index i = 0; i < size(); ++i)
+      StorageIndex n = StorageIndex(size());
+      for(StorageIndex i = 0; i < n; ++i)
         indices().coeffRef(i) = i;
     }
 
     /** Sets *this to be the identity permutation matrix of given size.
       */
@@ -161,22 +156,22 @@
 
     /** Multiplies *this by the transposition \f$(ij)\f$ on the left.
       *
       * \returns a reference to *this.
       *
-      * \warning This is much slower than applyTranspositionOnTheRight(int,int):
+      * \warning This is much slower than applyTranspositionOnTheRight(Index,Index):
       * this has linear complexity and requires a lot of branching.
       *
-      * \sa applyTranspositionOnTheRight(int,int)
+      * \sa applyTranspositionOnTheRight(Index,Index)
       */
     Derived& applyTranspositionOnTheLeft(Index i, Index j)
     {
       eigen_assert(i>=0 && j>=0 && i<size() && j<size());
       for(Index k = 0; k < size(); ++k)
       {
-        if(indices().coeff(k) == i) indices().coeffRef(k) = j;
-        else if(indices().coeff(k) == j) indices().coeffRef(k) = i;
+        if(indices().coeff(k) == i) indices().coeffRef(k) = StorageIndex(j);
+        else if(indices().coeff(k) == j) indices().coeffRef(k) = StorageIndex(i);
       }
       return derived();
     }
 
     /** Multiplies *this by the transposition \f$(ij)\f$ on the right.
@@ -183,11 +178,11 @@
       *
       * \returns a reference to *this.
       *
       * This is a fast operation, it only consists in swapping two indices.
       *
-      * \sa applyTranspositionOnTheLeft(int,int)
+      * \sa applyTranspositionOnTheLeft(Index,Index)
       */
     Derived& applyTranspositionOnTheRight(Index i, Index j)
     {
       eigen_assert(i>=0 && j>=0 && i<size() && j<size());
       std::swap(indices().coeffRef(i), indices().coeffRef(j));
@@ -194,111 +189,146 @@
       return derived();
     }
 
     /** \returns the inverse permutation matrix.
       *
-      * \note \note_try_to_help_rvo
+      * \note \blank \note_try_to_help_rvo
       */
-    inline Transpose<PermutationBase> inverse() const
-    { return derived(); }
+    inline InverseReturnType inverse() const
+    { return InverseReturnType(derived()); }
     /** \returns the tranpose permutation matrix.
       *
-      * \note \note_try_to_help_rvo
+      * \note \blank \note_try_to_help_rvo
       */
-    inline Transpose<PermutationBase> transpose() const
-    { return derived(); }
+    inline InverseReturnType transpose() const
+    { return InverseReturnType(derived()); }
 
     /**** multiplication helpers to hopefully get RVO ****/
 
   
 #ifndef EIGEN_PARSED_BY_DOXYGEN
   protected:
     template<typename OtherDerived>
     void assignTranspose(const PermutationBase<OtherDerived>& other)
     {
-      for (int i=0; i<rows();++i) indices().coeffRef(other.indices().coeff(i)) = i;
+      for (Index i=0; i<rows();++i) indices().coeffRef(other.indices().coeff(i)) = i;
     }
     template<typename Lhs,typename Rhs>
     void assignProduct(const Lhs& lhs, const Rhs& rhs)
     {
       eigen_assert(lhs.cols() == rhs.rows());
-      for (int i=0; i<rows();++i) indices().coeffRef(i) = lhs.indices().coeff(rhs.indices().coeff(i));
+      for (Index i=0; i<rows();++i) indices().coeffRef(i) = lhs.indices().coeff(rhs.indices().coeff(i));
     }
 #endif
 
   public:
 
     /** \returns the product permutation matrix.
       *
-      * \note \note_try_to_help_rvo
+      * \note \blank \note_try_to_help_rvo
       */
     template<typename Other>
     inline PlainPermutationType operator*(const PermutationBase<Other>& other) const
     { return PlainPermutationType(internal::PermPermProduct, derived(), other.derived()); }
 
     /** \returns the product of a permutation with another inverse permutation.
       *
-      * \note \note_try_to_help_rvo
+      * \note \blank \note_try_to_help_rvo
       */
     template<typename Other>
-    inline PlainPermutationType operator*(const Transpose<PermutationBase<Other> >& other) const
+    inline PlainPermutationType operator*(const InverseImpl<Other,PermutationStorage>& other) const
     { return PlainPermutationType(internal::PermPermProduct, *this, other.eval()); }
 
     /** \returns the product of an inverse permutation with another permutation.
       *
-      * \note \note_try_to_help_rvo
+      * \note \blank \note_try_to_help_rvo
       */
     template<typename Other> friend
-    inline PlainPermutationType operator*(const Transpose<PermutationBase<Other> >& other, const PermutationBase& perm)
+    inline PlainPermutationType operator*(const InverseImpl<Other, PermutationStorage>& other, const PermutationBase& perm)
     { return PlainPermutationType(internal::PermPermProduct, other.eval(), perm); }
+    
+    /** \returns the determinant of the permutation matrix, which is either 1 or -1 depending on the parity of the permutation.
+      *
+      * This function is O(\c n) procedure allocating a buffer of \c n booleans.
+      */
+    Index determinant() const
+    {
+      Index res = 1;
+      Index n = size();
+      Matrix<bool,RowsAtCompileTime,1,0,MaxRowsAtCompileTime> mask(n);
+      mask.fill(false);
+      Index r = 0;
+      while(r < n)
+      {
+        // search for the next seed
+        while(r<n && mask[r]) r++;
+        if(r>=n)
+          break;
+        // we got one, let's follow it until we are back to the seed
+        Index k0 = r++;
+        mask.coeffRef(k0) = true;
+        for(Index k=indices().coeff(k0); k!=k0; k=indices().coeff(k))
+        {
+          mask.coeffRef(k) = true;
+          res = -res;
+        }
+      }
+      return res;
+    }
 
   protected:
 
 };
+
+namespace internal {
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
+struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> >
+ : traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
+{
+  typedef PermutationStorage StorageKind;
+  typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
+  typedef _StorageIndex StorageIndex;
+  typedef void Scalar;
+};
+}
 
 /** \class PermutationMatrix
   * \ingroup Core_Module
   *
   * \brief Permutation matrix
   *
-  * \param SizeAtCompileTime the number of rows/cols, or Dynamic
-  * \param MaxSizeAtCompileTime the maximum number of rows/cols, or Dynamic. This optional parameter defaults to SizeAtCompileTime. Most of the time, you should not have to specify it.
-  * \param IndexType the interger type of the indices
+  * \tparam SizeAtCompileTime the number of rows/cols, or Dynamic
+  * \tparam MaxSizeAtCompileTime the maximum number of rows/cols, or Dynamic. This optional parameter defaults to SizeAtCompileTime. Most of the time, you should not have to specify it.
+  * \tparam _StorageIndex the integer type of the indices
   *
   * This class represents a permutation matrix, internally stored as a vector of integers.
   *
   * \sa class PermutationBase, class PermutationWrapper, class DiagonalMatrix
   */
-
-namespace internal {
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
-struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType> >
- : traits<Matrix<IndexType,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
-{
-  typedef IndexType Index;
-  typedef Matrix<IndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
-};
-}
-
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
-class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType> >
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
+class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> >
 {
     typedef PermutationBase<PermutationMatrix> Base;
     typedef internal::traits<PermutationMatrix> Traits;
   public:
 
+    typedef const PermutationMatrix& Nested;
+
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     typedef typename Traits::IndicesType IndicesType;
+    typedef typename Traits::StorageIndex StorageIndex;
     #endif
 
     inline PermutationMatrix()
     {}
 
     /** Constructs an uninitialized permutation matrix of given size.
       */
-    inline PermutationMatrix(int size) : m_indices(size)
-    {}
+    explicit inline PermutationMatrix(Index size) : m_indices(size)
+    {
+      eigen_internal_assert(size <= NumTraits<StorageIndex>::highest());
+    }
 
     /** Copy constructor. */
     template<typename OtherDerived>
     inline PermutationMatrix(const PermutationBase<OtherDerived>& other)
       : m_indices(other.indices()) {}
@@ -315,11 +345,11 @@
       * \warning It is your responsibility to check that the indices array that you passes actually
       * describes a permutation, i.e., each value between 0 and n-1 occurs exactly once, where n is the
       * array's size.
       */
     template<typename Other>
-    explicit inline PermutationMatrix(const MatrixBase<Other>& a_indices) : m_indices(a_indices)
+    explicit inline PermutationMatrix(const MatrixBase<Other>& indices) : m_indices(indices)
     {}
 
     /** Convert the Transpositions \a tr to a permutation matrix */
     template<typename Other>
     explicit PermutationMatrix(const TranspositionsBase<Other>& tr)
@@ -362,14 +392,17 @@
 
     /**** multiplication helpers to hopefully get RVO ****/
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename Other>
-    PermutationMatrix(const Transpose<PermutationBase<Other> >& other)
-      : m_indices(other.nestedPermutation().size())
+    PermutationMatrix(const InverseImpl<Other,PermutationStorage>& other)
+      : m_indices(other.derived().nestedExpression().size())
     {
-      for (int i=0; i<m_indices.size();++i) m_indices.coeffRef(other.nestedPermutation().indices().coeff(i)) = i;
+      eigen_internal_assert(m_indices.size() <= NumTraits<StorageIndex>::highest());
+      StorageIndex end = StorageIndex(m_indices.size());
+      for (StorageIndex i=0; i<end;++i)
+        m_indices.coeffRef(other.derived().nestedExpression().indices().coeff(i)) = i;
     }
     template<typename Lhs,typename Rhs>
     PermutationMatrix(internal::PermPermProduct_t, const Lhs& lhs, const Rhs& rhs)
       : m_indices(lhs.indices().size())
     {
@@ -382,37 +415,39 @@
     IndicesType m_indices;
 };
 
 
 namespace internal {
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int _PacketAccess>
-struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess> >
- : traits<Matrix<IndexType,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
+struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> >
+ : traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
 {
-  typedef IndexType Index;
-  typedef Map<const Matrix<IndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType;
+  typedef PermutationStorage StorageKind;
+  typedef Map<const Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType;
+  typedef _StorageIndex StorageIndex;
+  typedef void Scalar;
 };
 }
 
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int _PacketAccess>
-class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess>
-  : public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,_PacketAccess> >
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
+class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess>
+  : public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> >
 {
     typedef PermutationBase<Map> Base;
     typedef internal::traits<Map> Traits;
   public:
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     typedef typename Traits::IndicesType IndicesType;
-    typedef typename IndicesType::Scalar Index;
+    typedef typename IndicesType::Scalar StorageIndex;
     #endif
 
-    inline Map(const Index* indicesPtr)
+    inline Map(const StorageIndex* indicesPtr)
       : m_indices(indicesPtr)
     {}
 
-    inline Map(const Index* indicesPtr, Index size)
+    inline Map(const StorageIndex* indicesPtr, Index size)
       : m_indices(indicesPtr,size)
     {}
 
     /** Copies the other permutation into *this */
     template<typename Other>
@@ -443,44 +478,40 @@
   protected:
 
     IndicesType m_indices;
 };
 
-/** \class PermutationWrapper
-  * \ingroup Core_Module
-  *
-  * \brief Class to view a vector of integers as a permutation matrix
-  *
-  * \param _IndicesType the type of the vector of integer (can be any compatible expression)
-  *
-  * This class allows to view any vector expression of integers as a permutation matrix.
-  *
-  * \sa class PermutationBase, class PermutationMatrix
-  */
-
-struct PermutationStorage {};
-
 template<typename _IndicesType> class TranspositionsWrapper;
 namespace internal {
 template<typename _IndicesType>
 struct traits<PermutationWrapper<_IndicesType> >
 {
   typedef PermutationStorage StorageKind;
-  typedef typename _IndicesType::Scalar Scalar;
-  typedef typename _IndicesType::Scalar Index;
+  typedef void Scalar;
+  typedef typename _IndicesType::Scalar StorageIndex;
   typedef _IndicesType IndicesType;
   enum {
     RowsAtCompileTime = _IndicesType::SizeAtCompileTime,
     ColsAtCompileTime = _IndicesType::SizeAtCompileTime,
-    MaxRowsAtCompileTime = IndicesType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = IndicesType::MaxColsAtCompileTime,
-    Flags = 0,
-    CoeffReadCost = _IndicesType::CoeffReadCost
+    MaxRowsAtCompileTime = IndicesType::MaxSizeAtCompileTime,
+    MaxColsAtCompileTime = IndicesType::MaxSizeAtCompileTime,
+    Flags = 0
   };
 };
 }
 
+/** \class PermutationWrapper
+  * \ingroup Core_Module
+  *
+  * \brief Class to view a vector of integers as a permutation matrix
+  *
+  * \tparam _IndicesType the type of the vector of integer (can be any compatible expression)
+  *
+  * This class allows to view any vector expression of integers as a permutation matrix.
+  *
+  * \sa class PermutationBase, class PermutationMatrix
+  */
 template<typename _IndicesType>
 class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesType> >
 {
     typedef PermutationBase<PermutationWrapper> Base;
     typedef internal::traits<PermutationWrapper> Traits;
@@ -488,12 +519,12 @@
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     typedef typename Traits::IndicesType IndicesType;
     #endif
 
-    inline PermutationWrapper(const IndicesType& a_indices)
-      : m_indices(a_indices)
+    inline PermutationWrapper(const IndicesType& indices)
+      : m_indices(indices)
     {}
 
     /** const version of indices(). */
     const typename internal::remove_all<typename IndicesType::Nested>::type&
     indices() const { return m_indices; }
@@ -500,193 +531,103 @@
 
   protected:
 
     typename IndicesType::Nested m_indices;
 };
+
 
 /** \returns the matrix with the permutation applied to the columns.
   */
-template<typename Derived, typename PermutationDerived>
-inline const internal::permut_matrix_product_retval<PermutationDerived, Derived, OnTheRight>
-operator*(const MatrixBase<Derived>& matrix,
-          const PermutationBase<PermutationDerived> &permutation)
-{
-  return internal::permut_matrix_product_retval
-           <PermutationDerived, Derived, OnTheRight>
-           (permutation.derived(), matrix.derived());
+template<typename MatrixDerived, typename PermutationDerived>
+EIGEN_DEVICE_FUNC
+const Product<MatrixDerived, PermutationDerived, AliasFreeProduct>
+operator*(const MatrixBase<MatrixDerived> &matrix,
+          const PermutationBase<PermutationDerived>& permutation)
+{
+  return Product<MatrixDerived, PermutationDerived, AliasFreeProduct>
+            (matrix.derived(), permutation.derived());
 }
 
 /** \returns the matrix with the permutation applied to the rows.
   */
-template<typename Derived, typename PermutationDerived>
-inline const internal::permut_matrix_product_retval
-               <PermutationDerived, Derived, OnTheLeft>
-operator*(const PermutationBase<PermutationDerived> &permutation,
-          const MatrixBase<Derived>& matrix)
-{
-  return internal::permut_matrix_product_retval
-           <PermutationDerived, Derived, OnTheLeft>
-           (permutation.derived(), matrix.derived());
-}
-
-namespace internal {
-
-template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
-struct traits<permut_matrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
-{
-  typedef typename MatrixType::PlainObject ReturnType;
-};
-
-template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
-struct permut_matrix_product_retval
- : public ReturnByValue<permut_matrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
-{
-    typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
-    typedef typename MatrixType::Index Index;
-
-    permut_matrix_product_retval(const PermutationType& perm, const MatrixType& matrix)
-      : m_permutation(perm), m_matrix(matrix)
-    {}
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-
-    template<typename Dest> inline void evalTo(Dest& dst) const
-    {
-      const Index n = Side==OnTheLeft ? rows() : cols();
-      // FIXME we need an is_same for expression that is not sensitive to constness. For instance
-      // is_same_xpr<Block<const Matrix>, Block<Matrix> >::value should be true.
-      if(    is_same<MatrixTypeNestedCleaned,Dest>::value
-          && blas_traits<MatrixTypeNestedCleaned>::HasUsableDirectAccess
-          && blas_traits<Dest>::HasUsableDirectAccess
-          && extract_data(dst) == extract_data(m_matrix))
-      {
-        // apply the permutation inplace
-        Matrix<bool,PermutationType::RowsAtCompileTime,1,0,PermutationType::MaxRowsAtCompileTime> mask(m_permutation.size());
-        mask.fill(false);
-        Index r = 0;
-        while(r < m_permutation.size())
-        {
-          // search for the next seed
-          while(r<m_permutation.size() && mask[r]) r++;
-          if(r>=m_permutation.size())
-            break;
-          // we got one, let's follow it until we are back to the seed
-          Index k0 = r++;
-          Index kPrev = k0;
-          mask.coeffRef(k0) = true;
-          for(Index k=m_permutation.indices().coeff(k0); k!=k0; k=m_permutation.indices().coeff(k))
-          {
-                  Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>(dst, k)
-            .swap(Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>
-                       (dst,((Side==OnTheLeft) ^ Transposed) ? k0 : kPrev));
-
-            mask.coeffRef(k) = true;
-            kPrev = k;
-          }
-        }
-      }
-      else
-      {
-        for(int i = 0; i < n; ++i)
-        {
-          Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>
-               (dst, ((Side==OnTheLeft) ^ Transposed) ? m_permutation.indices().coeff(i) : i)
-
-          =
-
-          Block<const MatrixTypeNestedCleaned,Side==OnTheLeft ? 1 : MatrixType::RowsAtCompileTime,Side==OnTheRight ? 1 : MatrixType::ColsAtCompileTime>
-               (m_matrix, ((Side==OnTheRight) ^ Transposed) ? m_permutation.indices().coeff(i) : i);
-        }
-      }
-    }
-
-  protected:
-    const PermutationType& m_permutation;
-    typename MatrixType::Nested m_matrix;
-};
-
-/* Template partial specialization for transposed/inverse permutations */
-
-template<typename Derived>
-struct traits<Transpose<PermutationBase<Derived> > >
- : traits<Derived>
-{};
-
-} // end namespace internal
-
-template<typename Derived>
-class Transpose<PermutationBase<Derived> >
-  : public EigenBase<Transpose<PermutationBase<Derived> > >
-{
-    typedef Derived PermutationType;
-    typedef typename PermutationType::IndicesType IndicesType;
-    typedef typename PermutationType::PlainPermutationType PlainPermutationType;
-  public:
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    typedef internal::traits<PermutationType> Traits;
-    typedef typename Derived::DenseMatrixType DenseMatrixType;
-    enum {
-      Flags = Traits::Flags,
-      CoeffReadCost = Traits::CoeffReadCost,
-      RowsAtCompileTime = Traits::RowsAtCompileTime,
-      ColsAtCompileTime = Traits::ColsAtCompileTime,
-      MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime,
-      MaxColsAtCompileTime = Traits::MaxColsAtCompileTime
-    };
-    typedef typename Traits::Scalar Scalar;
-    #endif
-
-    Transpose(const PermutationType& p) : m_permutation(p) {}
-
-    inline int rows() const { return m_permutation.rows(); }
-    inline int cols() const { return m_permutation.cols(); }
+template<typename PermutationDerived, typename MatrixDerived>
+EIGEN_DEVICE_FUNC
+const Product<PermutationDerived, MatrixDerived, AliasFreeProduct>
+operator*(const PermutationBase<PermutationDerived> &permutation,
+          const MatrixBase<MatrixDerived>& matrix)
+{
+  return Product<PermutationDerived, MatrixDerived, AliasFreeProduct>
+            (permutation.derived(), matrix.derived());
+}
+
+
+template<typename PermutationType>
+class InverseImpl<PermutationType, PermutationStorage>
+  : public EigenBase<Inverse<PermutationType> >
+{
+    typedef typename PermutationType::PlainPermutationType PlainPermutationType;
+    typedef internal::traits<PermutationType> PermTraits;
+  protected:
+    InverseImpl() {}
+  public:
+    typedef Inverse<PermutationType> InverseType;
+    using EigenBase<Inverse<PermutationType> >::derived;
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    typedef typename PermutationType::DenseMatrixType DenseMatrixType;
+    enum {
+      RowsAtCompileTime = PermTraits::RowsAtCompileTime,
+      ColsAtCompileTime = PermTraits::ColsAtCompileTime,
+      MaxRowsAtCompileTime = PermTraits::MaxRowsAtCompileTime,
+      MaxColsAtCompileTime = PermTraits::MaxColsAtCompileTime
+    };
+    #endif
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename DenseDerived>
     void evalTo(MatrixBase<DenseDerived>& other) const
     {
       other.setZero();
-      for (int i=0; i<rows();++i)
-        other.coeffRef(i, m_permutation.indices().coeff(i)) = typename DenseDerived::Scalar(1);
+      for (Index i=0; i<derived().rows();++i)
+        other.coeffRef(i, derived().nestedExpression().indices().coeff(i)) = typename DenseDerived::Scalar(1);
     }
     #endif
 
     /** \return the equivalent permutation matrix */
-    PlainPermutationType eval() const { return *this; }
+    PlainPermutationType eval() const { return derived(); }
 
-    DenseMatrixType toDenseMatrix() const { return *this; }
+    DenseMatrixType toDenseMatrix() const { return derived(); }
 
     /** \returns the matrix with the inverse permutation applied to the columns.
       */
     template<typename OtherDerived> friend
-    inline const internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheRight, true>
-    operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trPerm)
+    const Product<OtherDerived, InverseType, AliasFreeProduct>
+    operator*(const MatrixBase<OtherDerived>& matrix, const InverseType& trPerm)
     {
-      return internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheRight, true>(trPerm.m_permutation, matrix.derived());
+      return Product<OtherDerived, InverseType, AliasFreeProduct>(matrix.derived(), trPerm.derived());
     }
 
     /** \returns the matrix with the inverse permutation applied to the rows.
       */
     template<typename OtherDerived>
-    inline const internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheLeft, true>
+    const Product<InverseType, OtherDerived, AliasFreeProduct>
     operator*(const MatrixBase<OtherDerived>& matrix) const
     {
-      return internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheLeft, true>(m_permutation, matrix.derived());
+      return Product<InverseType, OtherDerived, AliasFreeProduct>(derived(), matrix.derived());
     }
-
-    const PermutationType& nestedPermutation() const { return m_permutation; }
-
-  protected:
-    const PermutationType& m_permutation;
 };
 
 template<typename Derived>
 const PermutationWrapper<const Derived> MatrixBase<Derived>::asPermutation() const
 {
   return derived();
 }
 
+namespace internal {
+
+template<> struct AssignmentKind<DenseShape,PermutationShape> { typedef EigenBase2EigenBase Kind; };
+
+} // end namespace internal
+
 } // end namespace Eigen
 
 #endif // EIGEN_PERMUTATIONMATRIX_H

Index: 3rd_party/eigen/Eigen/src/Core/PlainObjectBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/PlainObjectBase.h
+++ 3rd_party/eigen/Eigen/src/Core/PlainObjectBase.h
@@ -26,22 +26,24 @@
 
 namespace internal {
 
 template<int MaxSizeAtCompileTime> struct check_rows_cols_for_overflow {
   template<typename Index>
+  EIGEN_DEVICE_FUNC
   static EIGEN_ALWAYS_INLINE void run(Index, Index)
   {
   }
 };
 
 template<> struct check_rows_cols_for_overflow<Dynamic> {
   template<typename Index>
+  EIGEN_DEVICE_FUNC
   static EIGEN_ALWAYS_INLINE void run(Index rows, Index cols)
   {
     // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
     // we assume Index is signed
-    Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
+    Index max_index = (std::size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
     bool error = (rows == 0 || cols == 0) ? false
                : (rows > max_index / cols);
     if (error)
       throw_std_bad_alloc();
   }
@@ -53,38 +55,46 @@
 struct conservative_resize_like_impl;
 
 template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct matrix_swap_impl;
 
 } // end namespace internal
+
+#ifdef EIGEN_PARSED_BY_DOXYGEN
+namespace doxygen {
+
+// This is a workaround to doxygen not being able to understand the inheritance logic
+// when it is hidden by the dense_xpr_base helper struct.
+// Moreover, doxygen fails to include members that are not documented in the declaration body of
+// MatrixBase if we inherits MatrixBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >,
+// this is why we simply inherits MatrixBase, though this does not make sense.
+
+/** This class is just a workaround for Doxygen and it does not not actually exist. */
+template<typename Derived> struct dense_xpr_base_dispatcher;
+/** This class is just a workaround for Doxygen and it does not not actually exist. */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+struct dense_xpr_base_dispatcher<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+    : public MatrixBase {};
+/** This class is just a workaround for Doxygen and it does not not actually exist. */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+struct dense_xpr_base_dispatcher<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+    : public ArrayBase {};
+
+} // namespace doxygen
 
 /** \class PlainObjectBase
+  * \ingroup Core_Module
   * \brief %Dense storage base class for matrices and arrays.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_PLAINOBJECTBASE_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_PLAINOBJECTBASE_PLUGIN.
+  *
+  * \tparam Derived is the derived type, e.g., a Matrix or Array
   *
   * \sa \ref TopicClassHierarchy
   */
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-namespace internal {
-
-// this is a warkaround to doxygen not being able to understand the inheritence logic
-// when it is hidden by the dense_xpr_base helper struct.
-template<typename Derived> struct dense_xpr_base_dispatcher_for_doxygen;// : public MatrixBase<Derived> {};
-/** This class is just a workaround for Doxygen and it does not not actually exist. */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct dense_xpr_base_dispatcher_for_doxygen<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-    : public MatrixBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > {};
-/** This class is just a workaround for Doxygen and it does not not actually exist. */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct dense_xpr_base_dispatcher_for_doxygen<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-    : public ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > {};
-
-} // namespace internal
-
 template<typename Derived>
-class PlainObjectBase : public internal::dense_xpr_base_dispatcher_for_doxygen<Derived>
+class PlainObjectBase : public doxygen::dense_xpr_base_dispatcher<Derived>
 #else
 template<typename Derived>
 class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
 #endif
 {
@@ -91,12 +101,12 @@
   public:
     enum { Options = internal::traits<Derived>::Options };
     typedef typename internal::dense_xpr_base<Derived>::type Base;
 
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
     typedef typename internal::traits<Derived>::Scalar Scalar;
+    
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
     typedef Derived DenseType;
 
     using Base::RowsAtCompileTime;
@@ -111,66 +121,99 @@
     template<typename PlainObjectType, int MapOptions, typename StrideType> friend class Eigen::Map;
     friend  class Eigen::Map<Derived, Unaligned>;
     typedef Eigen::Map<Derived, Unaligned>  MapType;
     friend  class Eigen::Map<const Derived, Unaligned>;
     typedef const Eigen::Map<const Derived, Unaligned> ConstMapType;
-    friend  class Eigen::Map<Derived, Aligned>;
-    typedef Eigen::Map<Derived, Aligned> AlignedMapType;
-    friend  class Eigen::Map<const Derived, Aligned>;
-    typedef const Eigen::Map<const Derived, Aligned> ConstAlignedMapType;
+#if EIGEN_MAX_ALIGN_BYTES>0
+    // for EIGEN_MAX_ALIGN_BYTES==0, AlignedMax==Unaligned, and many compilers generate warnings for friend-ing a class twice.
+    friend  class Eigen::Map<Derived, AlignedMax>;
+    friend  class Eigen::Map<const Derived, AlignedMax>;
+#endif
+    typedef Eigen::Map<Derived, AlignedMax> AlignedMapType;
+    typedef const Eigen::Map<const Derived, AlignedMax> ConstAlignedMapType;
     template<typename StrideType> struct StridedMapType { typedef Eigen::Map<Derived, Unaligned, StrideType> type; };
     template<typename StrideType> struct StridedConstMapType { typedef Eigen::Map<const Derived, Unaligned, StrideType> type; };
-    template<typename StrideType> struct StridedAlignedMapType { typedef Eigen::Map<Derived, Aligned, StrideType> type; };
-    template<typename StrideType> struct StridedConstAlignedMapType { typedef Eigen::Map<const Derived, Aligned, StrideType> type; };
+    template<typename StrideType> struct StridedAlignedMapType { typedef Eigen::Map<Derived, AlignedMax, StrideType> type; };
+    template<typename StrideType> struct StridedConstAlignedMapType { typedef Eigen::Map<const Derived, AlignedMax, StrideType> type; };
 
   protected:
     DenseStorage<Scalar, Base::MaxSizeAtCompileTime, Base::RowsAtCompileTime, Base::ColsAtCompileTime, Options> m_storage;
 
   public:
-    enum { NeedsToAlign = SizeAtCompileTime != Dynamic && (internal::traits<Derived>::Flags & AlignedBit) != 0 };
+    enum { NeedsToAlign = (SizeAtCompileTime != Dynamic) && (internal::traits<Derived>::Alignment>0) };
     EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
 
+    EIGEN_DEVICE_FUNC
     Base& base() { return *static_cast<Base*>(this); }
+    EIGEN_DEVICE_FUNC
     const Base& base() const { return *static_cast<const Base*>(this); }
 
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); }
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); }
 
+    /** This is an overloaded version of DenseCoeffsBase<Derived,ReadOnlyAccessors>::coeff(Index,Index) const
+      * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts.
+      *
+      * See DenseCoeffsBase<Derived,ReadOnlyAccessors>::coeff(Index) const for details. */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE const Scalar& coeff(Index rowId, Index colId) const
     {
       if(Flags & RowMajorBit)
         return m_storage.data()[colId + rowId * m_storage.cols()];
       else // column-major
         return m_storage.data()[rowId + colId * m_storage.rows()];
     }
 
+    /** This is an overloaded version of DenseCoeffsBase<Derived,ReadOnlyAccessors>::coeff(Index) const
+      * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts.
+      *
+      * See DenseCoeffsBase<Derived,ReadOnlyAccessors>::coeff(Index) const for details. */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const
     {
       return m_storage.data()[index];
     }
 
+    /** This is an overloaded version of DenseCoeffsBase<Derived,WriteAccessors>::coeffRef(Index,Index) const
+      * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts.
+      *
+      * See DenseCoeffsBase<Derived,WriteAccessors>::coeffRef(Index,Index) const for details. */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar& coeffRef(Index rowId, Index colId)
     {
       if(Flags & RowMajorBit)
         return m_storage.data()[colId + rowId * m_storage.cols()];
       else // column-major
         return m_storage.data()[rowId + colId * m_storage.rows()];
     }
 
+    /** This is an overloaded version of DenseCoeffsBase<Derived,WriteAccessors>::coeffRef(Index) const
+      * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts.
+      *
+      * See DenseCoeffsBase<Derived,WriteAccessors>::coeffRef(Index) const for details. */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
     {
       return m_storage.data()[index];
     }
 
+    /** This is the const version of coeffRef(Index,Index) which is thus synonym of coeff(Index,Index).
+      * It is provided for convenience. */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const
     {
       if(Flags & RowMajorBit)
         return m_storage.data()[colId + rowId * m_storage.cols()];
       else // column-major
         return m_storage.data()[rowId + colId * m_storage.rows()];
     }
 
+    /** This is the const version of coeffRef(Index) which is thus synonym of coeff(Index).
+      * It is provided for convenience. */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const
     {
       return m_storage.data()[index];
     }
 
@@ -207,15 +250,15 @@
     {
       internal::pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, val);
     }
 
     /** \returns a const pointer to the data array of this matrix */
-    EIGEN_STRONG_INLINE const Scalar *data() const
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar *data() const
     { return m_storage.data(); }
 
     /** \returns a pointer to the data array of this matrix */
-    EIGEN_STRONG_INLINE Scalar *data()
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar *data()
     { return m_storage.data(); }
 
     /** Resizes \c *this to a \a rows x \a cols matrix.
       *
       * This method is intended for dynamic-size matrices, although it is legal to call it on any
@@ -230,26 +273,26 @@
       * Example: \include Matrix_resize_int_int.cpp
       * Output: \verbinclude Matrix_resize_int_int.out
       *
       * \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t)
       */
-    EIGEN_STRONG_INLINE void resize(Index nbRows, Index nbCols)
-    {
-      eigen_assert(   EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,nbRows==RowsAtCompileTime)
-                   && EIGEN_IMPLIES(ColsAtCompileTime!=Dynamic,nbCols==ColsAtCompileTime)
-                   && EIGEN_IMPLIES(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic,nbRows<=MaxRowsAtCompileTime)
-                   && EIGEN_IMPLIES(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic,nbCols<=MaxColsAtCompileTime)
-                   && nbRows>=0 && nbCols>=0 && "Invalid sizes when resizing a matrix or array.");
-      internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(nbRows, nbCols);
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void resize(Index rows, Index cols)
+    {
+      eigen_assert(   EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,rows==RowsAtCompileTime)
+                   && EIGEN_IMPLIES(ColsAtCompileTime!=Dynamic,cols==ColsAtCompileTime)
+                   && EIGEN_IMPLIES(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic,rows<=MaxRowsAtCompileTime)
+                   && EIGEN_IMPLIES(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic,cols<=MaxColsAtCompileTime)
+                   && rows>=0 && cols>=0 && "Invalid sizes when resizing a matrix or array.");
+      internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(rows, cols);
       #ifdef EIGEN_INITIALIZE_COEFFS
-        Index size = nbRows*nbCols;
+        Index size = rows*cols;
         bool size_changed = size != this->size();
-        m_storage.resize(size, nbRows, nbCols);
+        m_storage.resize(size, rows, cols);
         if(size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
       #else
-        internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(nbRows, nbCols);
-        m_storage.resize(nbRows*nbCols, nbRows, nbCols);
+        m_storage.resize(rows*cols, rows, cols);
       #endif
     }
 
     /** Resizes \c *this to a vector of length \a size
       *
@@ -260,10 +303,11 @@
       * Example: \include Matrix_resize_int.cpp
       * Output: \verbinclude Matrix_resize_int.out
       *
       * \sa resize(Index,Index), resize(NoChange_t, Index), resize(Index, NoChange_t)
       */
+    EIGEN_DEVICE_FUNC
     inline void resize(Index size)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase)
       eigen_assert(((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime==Dynamic || size<=MaxSizeAtCompileTime)) || SizeAtCompileTime == size) && size>=0);
       #ifdef EIGEN_INITIALIZE_COEFFS
@@ -284,13 +328,14 @@
       * Example: \include Matrix_resize_NoChange_int.cpp
       * Output: \verbinclude Matrix_resize_NoChange_int.out
       *
       * \sa resize(Index,Index)
       */
-    inline void resize(NoChange_t, Index nbCols)
+    EIGEN_DEVICE_FUNC
+    inline void resize(NoChange_t, Index cols)
     {
-      resize(rows(), nbCols);
+      resize(rows(), cols);
     }
 
     /** Resizes the matrix, changing only the number of rows. For the parameter of type NoChange_t, just pass the special value \c NoChange
       * as in the example below.
       *
@@ -297,13 +342,14 @@
       * Example: \include Matrix_resize_int_NoChange.cpp
       * Output: \verbinclude Matrix_resize_int_NoChange.out
       *
       * \sa resize(Index,Index)
       */
-    inline void resize(Index nbRows, NoChange_t)
+    EIGEN_DEVICE_FUNC
+    inline void resize(Index rows, NoChange_t)
     {
-      resize(nbRows, cols());
+      resize(rows, cols());
     }
 
     /** Resizes \c *this to have the same dimensions as \a other.
       * Takes care of doing all the checking that's needed.
       *
@@ -310,10 +356,11 @@
       * Note that copying a row-vector into a vector (and conversely) is allowed.
       * The resizing, if any, is then done in the appropriate way so that row-vectors
       * remain row-vectors and vectors remain vectors.
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC 
     EIGEN_STRONG_INLINE void resizeLike(const EigenBase<OtherDerived>& _other)
     {
       const OtherDerived& other = _other.derived();
       internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(other.rows(), other.cols());
       const Index othersize = other.rows()*other.cols();
@@ -337,39 +384,42 @@
       * conservativeResize(Index, NoChange_t).
       *
       * Matrices are resized relative to the top-left element. In case values need to be 
       * appended to the matrix they will be uninitialized.
       */
-    EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, Index nbCols)
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void conservativeResize(Index rows, Index cols)
     {
-      internal::conservative_resize_like_impl<Derived>::run(*this, nbRows, nbCols);
+      internal::conservative_resize_like_impl<Derived>::run(*this, rows, cols);
     }
 
     /** Resizes the matrix to \a rows x \a cols while leaving old values untouched.
       *
       * As opposed to conservativeResize(Index rows, Index cols), this version leaves
       * the number of columns unchanged.
       *
       * In case the matrix is growing, new rows will be uninitialized.
       */
-    EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, NoChange_t)
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void conservativeResize(Index rows, NoChange_t)
     {
       // Note: see the comment in conservativeResize(Index,Index)
-      conservativeResize(nbRows, cols());
+      conservativeResize(rows, cols());
     }
 
     /** Resizes the matrix to \a rows x \a cols while leaving old values untouched.
       *
       * As opposed to conservativeResize(Index rows, Index cols), this version leaves
       * the number of rows unchanged.
       *
       * In case the matrix is growing, new columns will be uninitialized.
       */
-    EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index nbCols)
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index cols)
     {
       // Note: see the comment in conservativeResize(Index,Index)
-      conservativeResize(rows(), nbCols);
+      conservativeResize(rows(), cols);
     }
 
     /** Resizes the vector to \a size while retaining old values.
       *
       * \only_for_vectors. This method does not work for
@@ -376,10 +426,11 @@
       * partially dynamic matrices when the static dimension is anything other
       * than 1. For example it will not work with Matrix<double, 2, Dynamic>.
       *
       * When values are appended, they will be uninitialized.
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE void conservativeResize(Index size)
     {
       internal::conservative_resize_like_impl<Derived>::run(*this, size);
     }
 
@@ -391,81 +442,138 @@
       *
       * Matrices are resized relative to the top-left element. In case values need to be 
       * appended to the matrix they will copied from \c other.
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE void conservativeResizeLike(const DenseBase<OtherDerived>& other)
     {
       internal::conservative_resize_like_impl<Derived,OtherDerived>::run(*this, other);
     }
 
     /** This is a special case of the templated operator=. Its purpose is to
       * prevent a default operator= from hiding the templated operator=.
       */
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Derived& operator=(const PlainObjectBase& other)
     {
       return _set(other);
     }
 
     /** \sa MatrixBase::lazyAssign() */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Derived& lazyAssign(const DenseBase<OtherDerived>& other)
     {
       _resize_to_match(other);
       return Base::lazyAssign(other.derived());
     }
 
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Derived& operator=(const ReturnByValue<OtherDerived>& func)
     {
       resize(func.rows(), func.cols());
       return Base::operator=(func);
     }
 
+    // Prevent user from trying to instantiate PlainObjectBase objects
+    // by making all its constructor protected. See bug 1074.
+  protected:
+
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE PlainObjectBase() : m_storage()
     {
 //       _check_template_params();
 //       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     // FIXME is it still needed ?
     /** \internal */
-    PlainObjectBase(internal::constructor_without_unaligned_array_assert)
+    EIGEN_DEVICE_FUNC
+    explicit PlainObjectBase(internal::constructor_without_unaligned_array_assert)
       : m_storage(internal::constructor_without_unaligned_array_assert())
     {
 //       _check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 #endif
 
-    EIGEN_STRONG_INLINE PlainObjectBase(Index a_size, Index nbRows, Index nbCols)
-      : m_storage(a_size, nbRows, nbCols)
+#if EIGEN_HAS_RVALUE_REFERENCES
+    EIGEN_DEVICE_FUNC
+    PlainObjectBase(PlainObjectBase&& other) EIGEN_NOEXCEPT
+      : m_storage( std::move(other.m_storage) )
+    {
+    }
+
+    EIGEN_DEVICE_FUNC
+    PlainObjectBase& operator=(PlainObjectBase&& other) EIGEN_NOEXCEPT
+    {
+      using std::swap;
+      swap(m_storage, other.m_storage);
+      return *this;
+    }
+#endif
+
+    /** Copy constructor */
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE PlainObjectBase(const PlainObjectBase& other)
+      : Base(), m_storage(other.m_storage) { }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE PlainObjectBase(Index size, Index rows, Index cols)
+      : m_storage(size, rows, cols)
     {
 //       _check_template_params();
 //       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 
-    /** \copydoc MatrixBase::operator=(const EigenBase<OtherDerived>&)
+    /** \sa PlainObjectBase::operator=(const EigenBase<OtherDerived>&) */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE PlainObjectBase(const DenseBase<OtherDerived> &other)
+      : m_storage()
+    {
+      _check_template_params();
+      resizeLike(other);
+      _set_noalias(other);
+    }
+
+    /** \sa PlainObjectBase::operator=(const EigenBase<OtherDerived>&) */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase<OtherDerived> &other)
+      : m_storage()
+    {
+      _check_template_params();
+      resizeLike(other);
+      *this = other.derived();
+    }
+    /** \brief Copy constructor with in-place evaluation */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE PlainObjectBase(const ReturnByValue<OtherDerived>& other)
+    {
+      _check_template_params();
+      // FIXME this does not automatically transpose vectors if necessary
+      resize(other.rows(), other.cols());
+      other.evalTo(this->derived());
+    }
+
+  public:
+
+    /** \brief Copies the generic expression \a other into *this.
+      * \copydetails DenseBase::operator=(const EigenBase<OtherDerived> &other)
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC 
     EIGEN_STRONG_INLINE Derived& operator=(const EigenBase<OtherDerived> &other)
     {
       _resize_to_match(other);
       Base::operator=(other.derived());
       return this->derived();
     }
 
-    /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase<OtherDerived> &other)
-      : m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
-    {
-      _check_template_params();
-      internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(other.derived().rows(), other.derived().cols());
-      Base::operator=(other.derived());
-    }
-
     /** \name Map
       * These are convenience functions returning Map objects. The Map() static functions return unaligned Map objects,
       * while the AlignedMap() functions return aligned Map objects and thus should be called only with 16-byte-aligned
       * \a data pointers.
       *
@@ -536,20 +644,20 @@
     static inline typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
     { return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
     //@}
 
     using Base::setConstant;
-    Derived& setConstant(Index size, const Scalar& value);
-    Derived& setConstant(Index rows, Index cols, const Scalar& value);
+    EIGEN_DEVICE_FUNC Derived& setConstant(Index size, const Scalar& val);
+    EIGEN_DEVICE_FUNC Derived& setConstant(Index rows, Index cols, const Scalar& val);
 
     using Base::setZero;
-    Derived& setZero(Index size);
-    Derived& setZero(Index rows, Index cols);
+    EIGEN_DEVICE_FUNC Derived& setZero(Index size);
+    EIGEN_DEVICE_FUNC Derived& setZero(Index rows, Index cols);
 
     using Base::setOnes;
-    Derived& setOnes(Index size);
-    Derived& setOnes(Index rows, Index cols);
+    EIGEN_DEVICE_FUNC Derived& setOnes(Index size);
+    EIGEN_DEVICE_FUNC Derived& setOnes(Index rows, Index cols);
 
     using Base::setRandom;
     Derived& setRandom(Index size);
     Derived& setRandom(Index rows, Index cols);
 
@@ -564,10 +672,11 @@
       * Note that copying a row-vector into a vector (and conversely) is allowed.
       * The resizing, if any, is then done in the appropriate way so that row-vectors
       * remain row-vectors and vectors remain vectors.
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC 
     EIGEN_STRONG_INLINE void _resize_to_match(const EigenBase<OtherDerived>& other)
     {
       #ifdef EIGEN_NO_AUTOMATIC_RESIZING
       eigen_assert((this->size()==0 || (IsVectorAtCompileTime ? (this->size() == other.size())
                  : (rows() == other.rows() && cols() == other.cols())))
@@ -590,70 +699,203 @@
       *
       * \sa operator=(const MatrixBase<OtherDerived>&), _set_noalias()
       *
       * \internal
       */
+    // aliasing is dealt once in internall::call_assignment
+    // so at this stage we have to assume aliasing... and resising has to be done later.
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC 
     EIGEN_STRONG_INLINE Derived& _set(const DenseBase<OtherDerived>& other)
     {
-      _set_selector(other.derived(), typename internal::conditional<static_cast<bool>(int(OtherDerived::Flags) & EvalBeforeAssigningBit), internal::true_type, internal::false_type>::type());
+      internal::call_assignment(this->derived(), other.derived());
       return this->derived();
     }
 
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const internal::true_type&) { _set_noalias(other.eval()); }
-
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const internal::false_type&) { _set_noalias(other); }
-
     /** \internal Like _set() but additionally makes the assumption that no aliasing effect can happen (which
       * is the case when creating a new matrix) so one can enforce lazy evaluation.
       *
       * \sa operator=(const MatrixBase<OtherDerived>&), _set()
       */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC 
     EIGEN_STRONG_INLINE Derived& _set_noalias(const DenseBase<OtherDerived>& other)
     {
       // I don't think we need this resize call since the lazyAssign will anyways resize
       // and lazyAssign will be called by the assign selector.
       //_resize_to_match(other);
       // the 'false' below means to enforce lazy evaluation. We don't use lazyAssign() because
       // it wouldn't allow to copy a row-vector into a column-vector.
-      return internal::assign_selector<Derived,OtherDerived,false>::run(this->derived(), other.derived());
+      internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
+      return this->derived();
     }
 
     template<typename T0, typename T1>
-    EIGEN_STRONG_INLINE void _init2(Index nbRows, Index nbCols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
     {
       EIGEN_STATIC_ASSERT(bool(NumTraits<T0>::IsInteger) &&
                           bool(NumTraits<T1>::IsInteger),
                           FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
-      resize(nbRows,nbCols);
+      resize(rows,cols);
+    }
+    
+    template<typename T0, typename T1>
+    EIGEN_DEVICE_FUNC 
+    EIGEN_STRONG_INLINE void _init2(const T0& val0, const T1& val1, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
+    {
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
+      m_storage.data()[0] = Scalar(val0);
+      m_storage.data()[1] = Scalar(val1);
     }
+    
     template<typename T0, typename T1>
-    EIGEN_STRONG_INLINE void _init2(const Scalar& val0, const Scalar& val1, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
+    EIGEN_DEVICE_FUNC 
+    EIGEN_STRONG_INLINE void _init2(const Index& val0, const Index& val1,
+                                    typename internal::enable_if<    (!internal::is_same<Index,Scalar>::value)
+                                                                  && (internal::is_same<T0,Index>::value)
+                                                                  && (internal::is_same<T1,Index>::value)
+                                                                  && Base::SizeAtCompileTime==2,T1>::type* = 0)
     {
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
+      m_storage.data()[0] = Scalar(val0);
+      m_storage.data()[1] = Scalar(val1);
+    }
+
+    // The argument is convertible to the Index type and we either have a non 1x1 Matrix, or a dynamic-sized Array,
+    // then the argument is meant to be the size of the object.
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(Index size, typename internal::enable_if<    (Base::SizeAtCompileTime!=1 || !internal::is_convertible<T, Scalar>::value)
+                                                                              && ((!internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value || Base::SizeAtCompileTime==Dynamic)),T>::type* = 0)
+    {
+      // NOTE MSVC 2008 complains if we directly put bool(NumTraits<T>::IsInteger) as the EIGEN_STATIC_ASSERT argument.
+      const bool is_integer = NumTraits<T>::IsInteger;
+      EIGEN_UNUSED_VARIABLE(is_integer);
+      EIGEN_STATIC_ASSERT(is_integer,
+                          FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
+      resize(size);
+    }
+    
+    // We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar type can be implicitely converted)
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const Scalar& val0, typename internal::enable_if<Base::SizeAtCompileTime==1 && internal::is_convertible<T, Scalar>::value,T>::type* = 0)
+    {
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1)
       m_storage.data()[0] = val0;
-      m_storage.data()[1] = val1;
+    }
+    
+    // We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar type match the index type)
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const Index& val0,
+                                    typename internal::enable_if<    (!internal::is_same<Index,Scalar>::value)
+                                                                  && (internal::is_same<Index,T>::value)
+                                                                  && Base::SizeAtCompileTime==1
+                                                                  && internal::is_convertible<T, Scalar>::value,T*>::type* = 0)
+    {
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1)
+      m_storage.data()[0] = Scalar(val0);
+    }
+
+    // Initialize a fixed size matrix from a pointer to raw data
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const Scalar* data){
+      this->_set_noalias(ConstMapType(data));
+    }
+
+    // Initialize an arbitrary matrix from a dense expression
+    template<typename T, typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const DenseBase<OtherDerived>& other){
+      this->_set_noalias(other);
+    }
+
+    // Initialize an arbitrary matrix from an object convertible to the Derived type.
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const Derived& other){
+      this->_set_noalias(other);
+    }
+
+    // Initialize an arbitrary matrix from a generic Eigen expression
+    template<typename T, typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const EigenBase<OtherDerived>& other){
+      this->derived() = other;
+    }
+
+    template<typename T, typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const ReturnByValue<OtherDerived>& other)
+    {
+      resize(other.rows(), other.cols());
+      other.evalTo(this->derived());
+    }
+
+    template<typename T, typename OtherDerived, int ColsAtCompileTime>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const RotationBase<OtherDerived,ColsAtCompileTime>& r)
+    {
+      this->derived() = r;
+    }
+    
+    // For fixed-size Array<Scalar,...>
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const Scalar& val0,
+                                    typename internal::enable_if<    Base::SizeAtCompileTime!=Dynamic
+                                                                  && Base::SizeAtCompileTime!=1
+                                                                  && internal::is_convertible<T, Scalar>::value
+                                                                  && internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T>::type* = 0)
+    {
+      Base::setConstant(val0);
+    }
+    
+    // For fixed-size Array<Index,...>
+    template<typename T>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _init1(const Index& val0,
+                                    typename internal::enable_if<    (!internal::is_same<Index,Scalar>::value)
+                                                                  && (internal::is_same<Index,T>::value)
+                                                                  && Base::SizeAtCompileTime!=Dynamic
+                                                                  && Base::SizeAtCompileTime!=1
+                                                                  && internal::is_convertible<T, Scalar>::value
+                                                                  && internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T*>::type* = 0)
+    {
+      Base::setConstant(val0);
     }
-
+    
     template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
     friend struct internal::matrix_swap_impl;
 
-    /** \internal generic implementation of swap for dense storage since for dynamic-sized matrices of same type it is enough to swap the
-      * data pointers.
+  public:
+    
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal
+      * \brief Override DenseBase::swap() since for dynamic-sized matrices
+      * of same type it is enough to swap the data pointers.
       */
     template<typename OtherDerived>
-    void _swap(DenseBase<OtherDerived> const & other)
+    EIGEN_DEVICE_FUNC
+    void swap(DenseBase<OtherDerived> & other)
     {
       enum { SwapPointers = internal::is_same<Derived, OtherDerived>::value && Base::SizeAtCompileTime==Dynamic };
-      internal::matrix_swap_impl<Derived, OtherDerived, bool(SwapPointers)>::run(this->derived(), other.const_cast_derived());
+      internal::matrix_swap_impl<Derived, OtherDerived, bool(SwapPointers)>::run(this->derived(), other.derived());
     }
-
-  public:
-#ifndef EIGEN_PARSED_BY_DOXYGEN
+    
+    /** \internal
+      * \brief const version forwarded to DenseBase::swap
+      */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    void swap(DenseBase<OtherDerived> const & other)
+    { Base::swap(other.derived()); }
+    
+    EIGEN_DEVICE_FUNC 
     static EIGEN_STRONG_INLINE void _check_template_params()
     {
       EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (Options&RowMajor)==RowMajor)
                         && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, (Options&RowMajor)==0)
                         && ((RowsAtCompileTime == Dynamic) || (RowsAtCompileTime >= 0))
@@ -663,22 +905,20 @@
                         && (MaxRowsAtCompileTime == RowsAtCompileTime || RowsAtCompileTime==Dynamic)
                         && (MaxColsAtCompileTime == ColsAtCompileTime || ColsAtCompileTime==Dynamic)
                         && (Options & (DontAlign|RowMajor)) == Options),
         INVALID_MATRIX_TEMPLATE_PARAMETERS)
     }
-#endif
 
-private:
-    enum { ThisConstantIsPrivateInPlainObjectBase };
+    enum { IsPlainObjectBase = 1 };
+#endif
 };
 
 namespace internal {
 
 template <typename Derived, typename OtherDerived, bool IsVector>
 struct conservative_resize_like_impl
 {
-  typedef typename Derived::Index Index;
   static void run(DenseBase<Derived>& _this, Index rows, Index cols)
   {
     if (_this.rows() == rows && _this.cols() == cols) return;
     EIGEN_STATIC_ASSERT_DYNAMIC_SIZE(Derived)
 
@@ -690,12 +930,12 @@
     }
     else
     {
       // The storage order does not allow us to use reallocation.
       typename Derived::PlainObject tmp(rows,cols);
-      const Index common_rows = (std::min)(rows, _this.rows());
-      const Index common_cols = (std::min)(cols, _this.cols());
+      const Index common_rows = numext::mini(rows, _this.rows());
+      const Index common_cols = numext::mini(cols, _this.cols());
       tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
       _this.derived().swap(tmp);
     }
   }
 
@@ -724,12 +964,12 @@
     }
     else
     {
       // The storage order does not allow us to use reallocation.
       typename Derived::PlainObject tmp(other);
-      const Index common_rows = (std::min)(tmp.rows(), _this.rows());
-      const Index common_cols = (std::min)(tmp.cols(), _this.cols());
+      const Index common_rows = numext::mini(tmp.rows(), _this.rows());
+      const Index common_cols = numext::mini(tmp.cols(), _this.cols());
       tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
       _this.derived().swap(tmp);
     }
   }
 };
@@ -740,11 +980,10 @@
 struct conservative_resize_like_impl<Derived,OtherDerived,true>
   : conservative_resize_like_impl<Derived,OtherDerived,false>
 {
   using conservative_resize_like_impl<Derived,OtherDerived,false>::run;
   
-  typedef typename Derived::Index Index;
   static void run(DenseBase<Derived>& _this, Index size)
   {
     const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : size;
     const Index new_cols = Derived::RowsAtCompileTime==1 ? size : 1;
     _this.derived().m_storage.conservativeResize(size,new_rows,new_cols);
@@ -766,19 +1005,21 @@
 };
 
 template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
 struct matrix_swap_impl
 {
+  EIGEN_DEVICE_FUNC
   static inline void run(MatrixTypeA& a, MatrixTypeB& b)
   {
     a.base().swap(b);
   }
 };
 
 template<typename MatrixTypeA, typename MatrixTypeB>
 struct matrix_swap_impl<MatrixTypeA, MatrixTypeB, true>
 {
+  EIGEN_DEVICE_FUNC
   static inline void run(MatrixTypeA& a, MatrixTypeB& b)
   {
     static_cast<typename MatrixTypeA::Base&>(a).m_storage.swap(static_cast<typename MatrixTypeB::Base&>(b).m_storage);
   }
 };

ADDED   3rd_party/eigen/Eigen/src/Core/Product.h
Index: 3rd_party/eigen/Eigen/src/Core/Product.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Product.h
+++ 3rd_party/eigen/Eigen/src/Core/Product.h
@@ -0,0 +1,186 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_PRODUCT_H
+#define EIGEN_PRODUCT_H
+
+namespace Eigen {
+
+template<typename Lhs, typename Rhs, int Option, typename StorageKind> class ProductImpl;
+
+namespace internal {
+
+template<typename Lhs, typename Rhs, int Option>
+struct traits<Product<Lhs, Rhs, Option> >
+{
+  typedef typename remove_all<Lhs>::type LhsCleaned;
+  typedef typename remove_all<Rhs>::type RhsCleaned;
+  typedef traits<LhsCleaned> LhsTraits;
+  typedef traits<RhsCleaned> RhsTraits;
+  
+  typedef MatrixXpr XprKind;
+  
+  typedef typename ScalarBinaryOpTraits<typename traits<LhsCleaned>::Scalar, typename traits<RhsCleaned>::Scalar>::ReturnType Scalar;
+  typedef typename product_promote_storage_type<typename LhsTraits::StorageKind,
+                                                typename RhsTraits::StorageKind,
+                                                internal::product_type<Lhs,Rhs>::ret>::ret StorageKind;
+  typedef typename promote_index_type<typename LhsTraits::StorageIndex,
+                                      typename RhsTraits::StorageIndex>::type StorageIndex;
+  
+  enum {
+    RowsAtCompileTime    = LhsTraits::RowsAtCompileTime,
+    ColsAtCompileTime    = RhsTraits::ColsAtCompileTime,
+    MaxRowsAtCompileTime = LhsTraits::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = RhsTraits::MaxColsAtCompileTime,
+    
+    // FIXME: only needed by GeneralMatrixMatrixTriangular
+    InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(LhsTraits::ColsAtCompileTime, RhsTraits::RowsAtCompileTime),
+    
+    // The storage order is somewhat arbitrary here. The correct one will be determined through the evaluator.
+    Flags = (MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1) ? RowMajorBit
+          : (MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1) ? 0
+          : (   ((LhsTraits::Flags&NoPreferredStorageOrderBit) && (RhsTraits::Flags&RowMajorBit))
+             || ((RhsTraits::Flags&NoPreferredStorageOrderBit) && (LhsTraits::Flags&RowMajorBit)) ) ? RowMajorBit
+          : NoPreferredStorageOrderBit
+  };
+};
+
+} // end namespace internal
+
+/** \class Product
+  * \ingroup Core_Module
+  *
+  * \brief Expression of the product of two arbitrary matrices or vectors
+  *
+  * \tparam _Lhs the type of the left-hand side expression
+  * \tparam _Rhs the type of the right-hand side expression
+  *
+  * This class represents an expression of the product of two arbitrary matrices.
+  *
+  * The other template parameters are:
+  * \tparam Option     can be DefaultProduct, AliasFreeProduct, or LazyProduct
+  *
+  */
+template<typename _Lhs, typename _Rhs, int Option>
+class Product : public ProductImpl<_Lhs,_Rhs,Option,
+                                   typename internal::product_promote_storage_type<typename internal::traits<_Lhs>::StorageKind,
+                                                                                   typename internal::traits<_Rhs>::StorageKind,
+                                                                                   internal::product_type<_Lhs,_Rhs>::ret>::ret>
+{
+  public:
+    
+    typedef _Lhs Lhs;
+    typedef _Rhs Rhs;
+    
+    typedef typename ProductImpl<
+        Lhs, Rhs, Option,
+        typename internal::product_promote_storage_type<typename internal::traits<Lhs>::StorageKind,
+                                                        typename internal::traits<Rhs>::StorageKind,
+                                                        internal::product_type<Lhs,Rhs>::ret>::ret>::Base Base;
+    EIGEN_GENERIC_PUBLIC_INTERFACE(Product)
+
+    typedef typename internal::ref_selector<Lhs>::type LhsNested;
+    typedef typename internal::ref_selector<Rhs>::type RhsNested;
+    typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
+    typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
+
+    EIGEN_DEVICE_FUNC Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs)
+    {
+      eigen_assert(lhs.cols() == rhs.rows()
+        && "invalid matrix product"
+        && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
+    }
+
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_lhs.rows(); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); }
+
+    EIGEN_DEVICE_FUNC const LhsNestedCleaned& lhs() const { return m_lhs; }
+    EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; }
+
+  protected:
+
+    LhsNested m_lhs;
+    RhsNested m_rhs;
+};
+
+namespace internal {
+  
+template<typename Lhs, typename Rhs, int Option, int ProductTag = internal::product_type<Lhs,Rhs>::ret>
+class dense_product_base
+ : public internal::dense_xpr_base<Product<Lhs,Rhs,Option> >::type
+{};
+
+/** Convertion to scalar for inner-products */
+template<typename Lhs, typename Rhs, int Option>
+class dense_product_base<Lhs, Rhs, Option, InnerProduct>
+ : public internal::dense_xpr_base<Product<Lhs,Rhs,Option> >::type
+{
+  typedef Product<Lhs,Rhs,Option> ProductXpr;
+  typedef typename internal::dense_xpr_base<ProductXpr>::type Base;
+public:
+  using Base::derived;
+  typedef typename Base::Scalar Scalar;
+  
+  operator const Scalar() const
+  {
+    return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
+  }
+};
+
+} // namespace internal
+
+// Generic API dispatcher
+template<typename Lhs, typename Rhs, int Option, typename StorageKind>
+class ProductImpl : public internal::generic_xpr_base<Product<Lhs,Rhs,Option>, MatrixXpr, StorageKind>::type
+{
+  public:
+    typedef typename internal::generic_xpr_base<Product<Lhs,Rhs,Option>, MatrixXpr, StorageKind>::type Base;
+};
+
+template<typename Lhs, typename Rhs, int Option>
+class ProductImpl<Lhs,Rhs,Option,Dense>
+  : public internal::dense_product_base<Lhs,Rhs,Option>
+{
+    typedef Product<Lhs, Rhs, Option> Derived;
+    
+  public:
+    
+    typedef typename internal::dense_product_base<Lhs, Rhs, Option> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+  protected:
+    enum {
+      IsOneByOne = (RowsAtCompileTime == 1 || RowsAtCompileTime == Dynamic) && 
+                   (ColsAtCompileTime == 1 || ColsAtCompileTime == Dynamic),
+      EnableCoeff = IsOneByOne || Option==LazyProduct
+    };
+    
+  public:
+  
+    EIGEN_DEVICE_FUNC Scalar coeff(Index row, Index col) const
+    {
+      EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
+      eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );
+      
+      return internal::evaluator<Derived>(derived()).coeff(row,col);
+    }
+
+    EIGEN_DEVICE_FUNC Scalar coeff(Index i) const
+    {
+      EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
+      eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );
+      
+      return internal::evaluator<Derived>(derived()).coeff(i);
+    }
+    
+  
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_PRODUCT_H

DELETED 3rd_party/eigen/Eigen/src/Core/ProductBase.h
Index: 3rd_party/eigen/Eigen/src/Core/ProductBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/ProductBase.h
+++ 3rd_party/eigen/Eigen/src/Core/ProductBase.h
@@ -1,290 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_PRODUCTBASE_H
-#define EIGEN_PRODUCTBASE_H
-
-namespace Eigen { 
-
-/** \class ProductBase
-  * \ingroup Core_Module
-  *
-  */
-
-namespace internal {
-template<typename Derived, typename _Lhs, typename _Rhs>
-struct traits<ProductBase<Derived,_Lhs,_Rhs> >
-{
-  typedef MatrixXpr XprKind;
-  typedef typename remove_all<_Lhs>::type Lhs;
-  typedef typename remove_all<_Rhs>::type Rhs;
-  typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
-  typedef typename promote_storage_type<typename traits<Lhs>::StorageKind,
-                                           typename traits<Rhs>::StorageKind>::ret StorageKind;
-  typedef typename promote_index_type<typename traits<Lhs>::Index,
-                                         typename traits<Rhs>::Index>::type Index;
-  enum {
-    RowsAtCompileTime = traits<Lhs>::RowsAtCompileTime,
-    ColsAtCompileTime = traits<Rhs>::ColsAtCompileTime,
-    MaxRowsAtCompileTime = traits<Lhs>::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = traits<Rhs>::MaxColsAtCompileTime,
-    Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0)
-          | EvalBeforeNestingBit | EvalBeforeAssigningBit | NestByRefBit,
-                  // Note that EvalBeforeNestingBit and NestByRefBit
-                  // are not used in practice because nested is overloaded for products
-    CoeffReadCost = 0 // FIXME why is it needed ?
-  };
-};
-}
-
-#define EIGEN_PRODUCT_PUBLIC_INTERFACE(Derived) \
-  typedef ProductBase<Derived, Lhs, Rhs > Base; \
-  EIGEN_DENSE_PUBLIC_INTERFACE(Derived) \
-  typedef typename Base::LhsNested LhsNested; \
-  typedef typename Base::_LhsNested _LhsNested; \
-  typedef typename Base::LhsBlasTraits LhsBlasTraits; \
-  typedef typename Base::ActualLhsType ActualLhsType; \
-  typedef typename Base::_ActualLhsType _ActualLhsType; \
-  typedef typename Base::RhsNested RhsNested; \
-  typedef typename Base::_RhsNested _RhsNested; \
-  typedef typename Base::RhsBlasTraits RhsBlasTraits; \
-  typedef typename Base::ActualRhsType ActualRhsType; \
-  typedef typename Base::_ActualRhsType _ActualRhsType; \
-  using Base::m_lhs; \
-  using Base::m_rhs;
-
-template<typename Derived, typename Lhs, typename Rhs>
-class ProductBase : public MatrixBase<Derived>
-{
-  public:
-    typedef MatrixBase<Derived> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(ProductBase)
-    
-    typedef typename Lhs::Nested LhsNested;
-    typedef typename internal::remove_all<LhsNested>::type _LhsNested;
-    typedef internal::blas_traits<_LhsNested> LhsBlasTraits;
-    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
-    typedef typename internal::remove_all<ActualLhsType>::type _ActualLhsType;
-    typedef typename internal::traits<Lhs>::Scalar LhsScalar;
-
-    typedef typename Rhs::Nested RhsNested;
-    typedef typename internal::remove_all<RhsNested>::type _RhsNested;
-    typedef internal::blas_traits<_RhsNested> RhsBlasTraits;
-    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
-    typedef typename internal::remove_all<ActualRhsType>::type _ActualRhsType;
-    typedef typename internal::traits<Rhs>::Scalar RhsScalar;
-
-    // Diagonal of a product: no need to evaluate the arguments because they are going to be evaluated only once
-    typedef CoeffBasedProduct<LhsNested, RhsNested, 0> FullyLazyCoeffBaseProductType;
-
-  public:
-
-#ifndef EIGEN_NO_MALLOC
-    typedef typename Base::PlainObject BasePlainObject;
-    typedef Matrix<Scalar,RowsAtCompileTime==1?1:Dynamic,ColsAtCompileTime==1?1:Dynamic,BasePlainObject::Options> DynPlainObject;
-    typedef typename internal::conditional<(BasePlainObject::SizeAtCompileTime==Dynamic) || (BasePlainObject::SizeAtCompileTime*int(sizeof(Scalar)) < int(EIGEN_STACK_ALLOCATION_LIMIT)),
-                                           BasePlainObject, DynPlainObject>::type PlainObject;
-#else
-    typedef typename Base::PlainObject PlainObject;
-#endif
-
-    ProductBase(const Lhs& a_lhs, const Rhs& a_rhs)
-      : m_lhs(a_lhs), m_rhs(a_rhs)
-    {
-      eigen_assert(a_lhs.cols() == a_rhs.rows()
-        && "invalid matrix product"
-        && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
-    }
-
-    inline Index rows() const { return m_lhs.rows(); }
-    inline Index cols() const { return m_rhs.cols(); }
-
-    template<typename Dest>
-    inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst,Scalar(1)); }
-
-    template<typename Dest>
-    inline void addTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(1)); }
-
-    template<typename Dest>
-    inline void subTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(-1)); }
-
-    template<typename Dest>
-    inline void scaleAndAddTo(Dest& dst, const Scalar& alpha) const { derived().scaleAndAddTo(dst,alpha); }
-
-    const _LhsNested& lhs() const { return m_lhs; }
-    const _RhsNested& rhs() const { return m_rhs; }
-
-    // Implicit conversion to the nested type (trigger the evaluation of the product)
-    operator const PlainObject& () const
-    {
-      m_result.resize(m_lhs.rows(), m_rhs.cols());
-      derived().evalTo(m_result);
-      return m_result;
-    }
-
-    const Diagonal<const FullyLazyCoeffBaseProductType,0> diagonal() const
-    { return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); }
-
-    template<int Index>
-    const Diagonal<FullyLazyCoeffBaseProductType,Index> diagonal() const
-    { return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); }
-
-    const Diagonal<FullyLazyCoeffBaseProductType,Dynamic> diagonal(Index index) const
-    { return FullyLazyCoeffBaseProductType(m_lhs, m_rhs).diagonal(index); }
-
-    // restrict coeff accessors to 1x1 expressions. No need to care about mutators here since this isnt a Lvalue expression
-    typename Base::CoeffReturnType coeff(Index row, Index col) const
-    {
-#ifdef EIGEN2_SUPPORT
-      return lhs().row(row).cwiseProduct(rhs().col(col).transpose()).sum();
-#else
-      EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
-      eigen_assert(this->rows() == 1 && this->cols() == 1);
-      Matrix<Scalar,1,1> result = *this;
-      return result.coeff(row,col);
-#endif
-    }
-
-    typename Base::CoeffReturnType coeff(Index i) const
-    {
-      EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
-      eigen_assert(this->rows() == 1 && this->cols() == 1);
-      Matrix<Scalar,1,1> result = *this;
-      return result.coeff(i);
-    }
-
-    const Scalar& coeffRef(Index row, Index col) const
-    {
-      EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
-      eigen_assert(this->rows() == 1 && this->cols() == 1);
-      return derived().coeffRef(row,col);
-    }
-
-    const Scalar& coeffRef(Index i) const
-    {
-      EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
-      eigen_assert(this->rows() == 1 && this->cols() == 1);
-      return derived().coeffRef(i);
-    }
-
-  protected:
-
-    LhsNested m_lhs;
-    RhsNested m_rhs;
-
-    mutable PlainObject m_result;
-};
-
-// here we need to overload the nested rule for products
-// such that the nested type is a const reference to a plain matrix
-namespace internal {
-template<typename Lhs, typename Rhs, int Mode, int N, typename PlainObject>
-struct nested<GeneralProduct<Lhs,Rhs,Mode>, N, PlainObject>
-{
-  typedef typename GeneralProduct<Lhs,Rhs,Mode>::PlainObject const& type;
-};
-template<typename Lhs, typename Rhs, int Mode, int N, typename PlainObject>
-struct nested<const GeneralProduct<Lhs,Rhs,Mode>, N, PlainObject>
-{
-  typedef typename GeneralProduct<Lhs,Rhs,Mode>::PlainObject const& type;
-};
-}
-
-template<typename NestedProduct>
-class ScaledProduct;
-
-// Note that these two operator* functions are not defined as member
-// functions of ProductBase, because, otherwise we would have to
-// define all overloads defined in MatrixBase. Furthermore, Using
-// "using Base::operator*" would not work with MSVC.
-//
-// Also note that here we accept any compatible scalar types
-template<typename Derived,typename Lhs,typename Rhs>
-const ScaledProduct<Derived>
-operator*(const ProductBase<Derived,Lhs,Rhs>& prod, const typename Derived::Scalar& x)
-{ return ScaledProduct<Derived>(prod.derived(), x); }
-
-template<typename Derived,typename Lhs,typename Rhs>
-typename internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value,
-                      const ScaledProduct<Derived> >::type
-operator*(const ProductBase<Derived,Lhs,Rhs>& prod, const typename Derived::RealScalar& x)
-{ return ScaledProduct<Derived>(prod.derived(), x); }
-
-
-template<typename Derived,typename Lhs,typename Rhs>
-const ScaledProduct<Derived>
-operator*(const typename Derived::Scalar& x,const ProductBase<Derived,Lhs,Rhs>& prod)
-{ return ScaledProduct<Derived>(prod.derived(), x); }
-
-template<typename Derived,typename Lhs,typename Rhs>
-typename internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value,
-                      const ScaledProduct<Derived> >::type
-operator*(const typename Derived::RealScalar& x,const ProductBase<Derived,Lhs,Rhs>& prod)
-{ return ScaledProduct<Derived>(prod.derived(), x); }
-
-namespace internal {
-template<typename NestedProduct>
-struct traits<ScaledProduct<NestedProduct> >
- : traits<ProductBase<ScaledProduct<NestedProduct>,
-                         typename NestedProduct::_LhsNested,
-                         typename NestedProduct::_RhsNested> >
-{
-  typedef typename traits<NestedProduct>::StorageKind StorageKind;
-};
-}
-
-template<typename NestedProduct>
-class ScaledProduct
-  : public ProductBase<ScaledProduct<NestedProduct>,
-                       typename NestedProduct::_LhsNested,
-                       typename NestedProduct::_RhsNested>
-{
-  public:
-    typedef ProductBase<ScaledProduct<NestedProduct>,
-                       typename NestedProduct::_LhsNested,
-                       typename NestedProduct::_RhsNested> Base;
-    typedef typename Base::Scalar Scalar;
-    typedef typename Base::PlainObject PlainObject;
-//     EIGEN_PRODUCT_PUBLIC_INTERFACE(ScaledProduct)
-
-    ScaledProduct(const NestedProduct& prod, const Scalar& x)
-    : Base(prod.lhs(),prod.rhs()), m_prod(prod), m_alpha(x) {}
-
-    template<typename Dest>
-    inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst, Scalar(1)); }
-
-    template<typename Dest>
-    inline void addTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(1)); }
-
-    template<typename Dest>
-    inline void subTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(-1)); }
-
-    template<typename Dest>
-    inline void scaleAndAddTo(Dest& dst, const Scalar& a_alpha) const { m_prod.derived().scaleAndAddTo(dst,a_alpha * m_alpha); }
-
-    const Scalar& alpha() const { return m_alpha; }
-    
-  protected:
-    const NestedProduct& m_prod;
-    Scalar m_alpha;
-};
-
-/** \internal
-  * Overloaded to perform an efficient C = (A*B).lazy() */
-template<typename Derived>
-template<typename ProductDerived, typename Lhs, typename Rhs>
-Derived& MatrixBase<Derived>::lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other)
-{
-  other.derived().evalTo(derived());
-  return derived();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_PRODUCTBASE_H

ADDED   3rd_party/eigen/Eigen/src/Core/ProductEvaluators.h
Index: 3rd_party/eigen/Eigen/src/Core/ProductEvaluators.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/ProductEvaluators.h
+++ 3rd_party/eigen/Eigen/src/Core/ProductEvaluators.h
@@ -0,0 +1,1105 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+
+#ifndef EIGEN_PRODUCTEVALUATORS_H
+#define EIGEN_PRODUCTEVALUATORS_H
+
+namespace Eigen {
+  
+namespace internal {
+
+/** \internal
+  * Evaluator of a product expression.
+  * Since products require special treatments to handle all possible cases,
+  * we simply deffer the evaluation logic to a product_evaluator class
+  * which offers more partial specialization possibilities.
+  * 
+  * \sa class product_evaluator
+  */
+template<typename Lhs, typename Rhs, int Options>
+struct evaluator<Product<Lhs, Rhs, Options> > 
+ : public product_evaluator<Product<Lhs, Rhs, Options> >
+{
+  typedef Product<Lhs, Rhs, Options> XprType;
+  typedef product_evaluator<XprType> Base;
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {}
+};
+ 
+// Catch "scalar * ( A * B )" and transform it to "(A*scalar) * B"
+// TODO we should apply that rule only if that's really helpful
+template<typename Lhs, typename Rhs, typename Scalar1, typename Scalar2, typename Plain1>
+struct evaluator_assume_aliasing<CwiseBinaryOp<internal::scalar_product_op<Scalar1,Scalar2>,
+                                               const CwiseNullaryOp<internal::scalar_constant_op<Scalar1>, Plain1>,
+                                               const Product<Lhs, Rhs, DefaultProduct> > >
+{
+  static const bool value = true;
+};
+template<typename Lhs, typename Rhs, typename Scalar1, typename Scalar2, typename Plain1>
+struct evaluator<CwiseBinaryOp<internal::scalar_product_op<Scalar1,Scalar2>,
+                               const CwiseNullaryOp<internal::scalar_constant_op<Scalar1>, Plain1>,
+                               const Product<Lhs, Rhs, DefaultProduct> > >
+ : public evaluator<Product<EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar1,Lhs,product), Rhs, DefaultProduct> >
+{
+  typedef CwiseBinaryOp<internal::scalar_product_op<Scalar1,Scalar2>,
+                               const CwiseNullaryOp<internal::scalar_constant_op<Scalar1>, Plain1>,
+                               const Product<Lhs, Rhs, DefaultProduct> > XprType;
+  typedef evaluator<Product<EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar1,Lhs,product), Rhs, DefaultProduct> > Base;
+
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
+    : Base(xpr.lhs().functor().m_other * xpr.rhs().lhs() * xpr.rhs().rhs())
+  {}
+};
+
+
+template<typename Lhs, typename Rhs, int DiagIndex>
+struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> > 
+ : public evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> >
+{
+  typedef Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> XprType;
+  typedef evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> > Base;
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
+    : Base(Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex>(
+        Product<Lhs, Rhs, LazyProduct>(xpr.nestedExpression().lhs(), xpr.nestedExpression().rhs()),
+        xpr.index() ))
+  {}
+};
+
+
+// Helper class to perform a matrix product with the destination at hand.
+// Depending on the sizes of the factors, there are different evaluation strategies
+// as controlled by internal::product_type.
+template< typename Lhs, typename Rhs,
+          typename LhsShape = typename evaluator_traits<Lhs>::Shape,
+          typename RhsShape = typename evaluator_traits<Rhs>::Shape,
+          int ProductType = internal::product_type<Lhs,Rhs>::value>
+struct generic_product_impl;
+
+template<typename Lhs, typename Rhs>
+struct evaluator_assume_aliasing<Product<Lhs, Rhs, DefaultProduct> > {
+  static const bool value = true;
+};
+
+// This is the default evaluator implementation for products:
+// It creates a temporary and call generic_product_impl
+template<typename Lhs, typename Rhs, int Options, int ProductTag, typename LhsShape, typename RhsShape>
+struct product_evaluator<Product<Lhs, Rhs, Options>, ProductTag, LhsShape, RhsShape>
+  : public evaluator<typename Product<Lhs, Rhs, Options>::PlainObject>
+{
+  typedef Product<Lhs, Rhs, Options> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  typedef evaluator<PlainObject> Base;
+  enum {
+    Flags = Base::Flags | EvalBeforeNestingBit
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  explicit product_evaluator(const XprType& xpr)
+    : m_result(xpr.rows(), xpr.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    
+// FIXME shall we handle nested_eval here?,
+// if so, then we must take care at removing the call to nested_eval in the specializations (e.g., in permutation_matrix_product, transposition_matrix_product, etc.)
+//     typedef typename internal::nested_eval<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
+//     typedef typename internal::nested_eval<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
+//     typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
+//     typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
+//     
+//     const LhsNested lhs(xpr.lhs());
+//     const RhsNested rhs(xpr.rhs());
+//   
+//     generic_product_impl<LhsNestedCleaned, RhsNestedCleaned>::evalTo(m_result, lhs, rhs);
+
+    generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
+  }
+  
+protected:  
+  PlainObject m_result;
+};
+
+// The following three shortcuts are enabled only if the scalar types match excatly.
+// TODO: we could enable them for different scalar types when the product is not vectorized.
+
+// Dense = Product
+template< typename DstXprType, typename Lhs, typename Rhs, int Options, typename Scalar>
+struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::assign_op<Scalar,Scalar>, Dense2Dense,
+  typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
+{
+  typedef Product<Lhs,Rhs,Options> SrcXprType;
+  static EIGEN_STRONG_INLINE
+  void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+    // FIXME shall we handle nested_eval here?
+    generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
+  }
+};
+
+// Dense += Product
+template< typename DstXprType, typename Lhs, typename Rhs, int Options, typename Scalar>
+struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::add_assign_op<Scalar,Scalar>, Dense2Dense,
+  typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
+{
+  typedef Product<Lhs,Rhs,Options> SrcXprType;
+  static EIGEN_STRONG_INLINE
+  void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<Scalar,Scalar> &)
+  {
+    eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
+    // FIXME shall we handle nested_eval here?
+    generic_product_impl<Lhs, Rhs>::addTo(dst, src.lhs(), src.rhs());
+  }
+};
+
+// Dense -= Product
+template< typename DstXprType, typename Lhs, typename Rhs, int Options, typename Scalar>
+struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::sub_assign_op<Scalar,Scalar>, Dense2Dense,
+  typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
+{
+  typedef Product<Lhs,Rhs,Options> SrcXprType;
+  static EIGEN_STRONG_INLINE
+  void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<Scalar,Scalar> &)
+  {
+    eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
+    // FIXME shall we handle nested_eval here?
+    generic_product_impl<Lhs, Rhs>::subTo(dst, src.lhs(), src.rhs());
+  }
+};
+
+
+// Dense ?= scalar * Product
+// TODO we should apply that rule if that's really helpful
+// for instance, this is not good for inner products
+template< typename DstXprType, typename Lhs, typename Rhs, typename AssignFunc, typename Scalar, typename ScalarBis, typename Plain>
+struct Assignment<DstXprType, CwiseBinaryOp<internal::scalar_product_op<ScalarBis,Scalar>, const CwiseNullaryOp<internal::scalar_constant_op<ScalarBis>,Plain>,
+                                           const Product<Lhs,Rhs,DefaultProduct> >, AssignFunc, Dense2Dense>
+{
+  typedef CwiseBinaryOp<internal::scalar_product_op<ScalarBis,Scalar>,
+                        const CwiseNullaryOp<internal::scalar_constant_op<ScalarBis>,Plain>,
+                        const Product<Lhs,Rhs,DefaultProduct> > SrcXprType;
+  static EIGEN_STRONG_INLINE
+  void run(DstXprType &dst, const SrcXprType &src, const AssignFunc& func)
+  {
+    call_assignment_no_alias(dst, (src.lhs().functor().m_other * src.rhs().lhs())*src.rhs().rhs(), func);
+  }
+};
+
+//----------------------------------------
+// Catch "Dense ?= xpr + Product<>" expression to save one temporary
+// FIXME we could probably enable these rules for any product, i.e., not only Dense and DefaultProduct
+
+template<typename OtherXpr, typename Lhs, typename Rhs>
+struct evaluator_assume_aliasing<CwiseBinaryOp<internal::scalar_sum_op<typename OtherXpr::Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, const OtherXpr,
+                                               const Product<Lhs,Rhs,DefaultProduct> >, DenseShape > {
+  static const bool value = true;
+};
+
+template<typename OtherXpr, typename Lhs, typename Rhs>
+struct evaluator_assume_aliasing<CwiseBinaryOp<internal::scalar_difference_op<typename OtherXpr::Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, const OtherXpr,
+                                               const Product<Lhs,Rhs,DefaultProduct> >, DenseShape > {
+  static const bool value = true;
+};
+
+template<typename DstXprType, typename OtherXpr, typename ProductType, typename Func1, typename Func2>
+struct assignment_from_xpr_op_product
+{
+  template<typename SrcXprType, typename InitialFunc>
+  static EIGEN_STRONG_INLINE
+  void run(DstXprType &dst, const SrcXprType &src, const InitialFunc& /*func*/)
+  {
+    call_assignment_no_alias(dst, src.lhs(), Func1());
+    call_assignment_no_alias(dst, src.rhs(), Func2());
+  }
+};
+
+#define EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(ASSIGN_OP,BINOP,ASSIGN_OP2) \
+  template< typename DstXprType, typename OtherXpr, typename Lhs, typename Rhs, typename DstScalar, typename SrcScalar, typename OtherScalar,typename ProdScalar> \
+  struct Assignment<DstXprType, CwiseBinaryOp<internal::BINOP<OtherScalar,ProdScalar>, const OtherXpr, \
+                                            const Product<Lhs,Rhs,DefaultProduct> >, internal::ASSIGN_OP<DstScalar,SrcScalar>, Dense2Dense> \
+    : assignment_from_xpr_op_product<DstXprType, OtherXpr, Product<Lhs,Rhs,DefaultProduct>, internal::ASSIGN_OP<DstScalar,OtherScalar>, internal::ASSIGN_OP2<DstScalar,ProdScalar> > \
+  {}
+
+EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(assign_op,    scalar_sum_op,add_assign_op);
+EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(add_assign_op,scalar_sum_op,add_assign_op);
+EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(sub_assign_op,scalar_sum_op,sub_assign_op);
+
+EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(assign_op,    scalar_difference_op,sub_assign_op);
+EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(add_assign_op,scalar_difference_op,sub_assign_op);
+EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(sub_assign_op,scalar_difference_op,add_assign_op);
+
+//----------------------------------------
+
+template<typename Lhs, typename Rhs>
+struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,InnerProduct>
+{
+  template<typename Dst>
+  static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
+  }
+  
+  template<typename Dst>
+  static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    dst.coeffRef(0,0) += (lhs.transpose().cwiseProduct(rhs)).sum();
+  }
+  
+  template<typename Dst>
+  static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  { dst.coeffRef(0,0) -= (lhs.transpose().cwiseProduct(rhs)).sum(); }
+};
+
+
+/***********************************************************************
+*  Implementation of outer dense * dense vector product
+***********************************************************************/
+
+// Column major result
+template<typename Dst, typename Lhs, typename Rhs, typename Func>
+void outer_product_selector_run(Dst& dst, const Lhs &lhs, const Rhs &rhs, const Func& func, const false_type&)
+{
+  evaluator<Rhs> rhsEval(rhs);
+  typename nested_eval<Lhs,Rhs::SizeAtCompileTime>::type actual_lhs(lhs);
+  // FIXME if cols is large enough, then it might be useful to make sure that lhs is sequentially stored
+  // FIXME not very good if rhs is real and lhs complex while alpha is real too
+  const Index cols = dst.cols();
+  for (Index j=0; j<cols; ++j)
+    func(dst.col(j), rhsEval.coeff(Index(0),j) * actual_lhs);
+}
+
+// Row major result
+template<typename Dst, typename Lhs, typename Rhs, typename Func>
+void outer_product_selector_run(Dst& dst, const Lhs &lhs, const Rhs &rhs, const Func& func, const true_type&)
+{
+  evaluator<Lhs> lhsEval(lhs);
+  typename nested_eval<Rhs,Lhs::SizeAtCompileTime>::type actual_rhs(rhs);
+  // FIXME if rows is large enough, then it might be useful to make sure that rhs is sequentially stored
+  // FIXME not very good if lhs is real and rhs complex while alpha is real too
+  const Index rows = dst.rows();
+  for (Index i=0; i<rows; ++i)
+    func(dst.row(i), lhsEval.coeff(i,Index(0)) * actual_rhs);
+}
+
+template<typename Lhs, typename Rhs>
+struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,OuterProduct>
+{
+  template<typename T> struct is_row_major : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  // TODO it would be nice to be able to exploit our *_assign_op functors for that purpose
+  struct set  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived()  = src; } };
+  struct add  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } };
+  struct sub  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } };
+  struct adds {
+    Scalar m_scale;
+    explicit adds(const Scalar& s) : m_scale(s) {}
+    template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const {
+      dst.const_cast_derived() += m_scale * src;
+    }
+  };
+  
+  template<typename Dst>
+  static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    internal::outer_product_selector_run(dst, lhs, rhs, set(), is_row_major<Dst>());
+  }
+  
+  template<typename Dst>
+  static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    internal::outer_product_selector_run(dst, lhs, rhs, add(), is_row_major<Dst>());
+  }
+  
+  template<typename Dst>
+  static inline void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    internal::outer_product_selector_run(dst, lhs, rhs, sub(), is_row_major<Dst>());
+  }
+  
+  template<typename Dst>
+  static inline void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  {
+    internal::outer_product_selector_run(dst, lhs, rhs, adds(alpha), is_row_major<Dst>());
+  }
+  
+};
+
+
+// This base class provides default implementations for evalTo, addTo, subTo, in terms of scaleAndAddTo
+template<typename Lhs, typename Rhs, typename Derived>
+struct generic_product_impl_base
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  template<typename Dst>
+  static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
+
+  template<typename Dst>
+  static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  { scaleAndAddTo(dst,lhs, rhs, Scalar(1)); }
+
+  template<typename Dst>
+  static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  { scaleAndAddTo(dst, lhs, rhs, Scalar(-1)); }
+  
+  template<typename Dst>
+  static EIGEN_STRONG_INLINE void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
+
+};
+
+template<typename Lhs, typename Rhs>
+struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemvProduct>
+  : generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemvProduct> >
+{
+  typedef typename nested_eval<Lhs,1>::type LhsNested;
+  typedef typename nested_eval<Rhs,1>::type RhsNested;
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
+  typedef typename internal::remove_all<typename internal::conditional<int(Side)==OnTheRight,LhsNested,RhsNested>::type>::type MatrixType;
+
+  template<typename Dest>
+  static EIGEN_STRONG_INLINE void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  {
+    LhsNested actual_lhs(lhs);
+    RhsNested actual_rhs(rhs);
+    internal::gemv_dense_selector<Side,
+                            (int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
+                            bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)
+                           >::run(actual_lhs, actual_rhs, dst, alpha);
+  }
+};
+
+template<typename Lhs, typename Rhs>
+struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode> 
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  template<typename Dst>
+  static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    // Same as: dst.noalias() = lhs.lazyProduct(rhs);
+    // but easier on the compiler side
+    call_assignment_no_alias(dst, lhs.lazyProduct(rhs), internal::assign_op<typename Dst::Scalar,Scalar>());
+  }
+  
+  template<typename Dst>
+  static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    // dst.noalias() += lhs.lazyProduct(rhs);
+    call_assignment_no_alias(dst, lhs.lazyProduct(rhs), internal::add_assign_op<typename Dst::Scalar,Scalar>());
+  }
+  
+  template<typename Dst>
+  static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    // dst.noalias() -= lhs.lazyProduct(rhs);
+    call_assignment_no_alias(dst, lhs.lazyProduct(rhs), internal::sub_assign_op<typename Dst::Scalar,Scalar>());
+  }
+  
+//   template<typename Dst>
+//   static inline void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+//   { dst.noalias() += alpha * lhs.lazyProduct(rhs); }
+};
+
+// This specialization enforces the use of a coefficient-based evaluation strategy
+template<typename Lhs, typename Rhs>
+struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,LazyCoeffBasedProductMode>
+  : generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode> {};
+
+// Case 2: Evaluate coeff by coeff
+//
+// This is mostly taken from CoeffBasedProduct.h
+// The main difference is that we add an extra argument to the etor_product_*_impl::run() function
+// for the inner dimension of the product, because evaluator object do not know their size.
+
+template<int Traversal, int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
+struct etor_product_coeff_impl;
+
+template<int StorageOrder, int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl;
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape, DenseShape>
+    : evaluator_base<Product<Lhs, Rhs, LazyProduct> >
+{
+  typedef Product<Lhs, Rhs, LazyProduct> XprType;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  explicit product_evaluator(const XprType& xpr)
+    : m_lhs(xpr.lhs()),
+      m_rhs(xpr.rhs()),
+      m_lhsImpl(m_lhs),     // FIXME the creation of the evaluator objects should result in a no-op, but check that!
+      m_rhsImpl(m_rhs),     //       Moreover, they are only useful for the packet path, so we could completely disable them when not needed,
+                            //       or perhaps declare them on the fly on the packet method... We have experiment to check what's best.
+      m_innerDim(xpr.lhs().cols())
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(NumTraits<Scalar>::MulCost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(NumTraits<Scalar>::AddCost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+#if 0
+    std::cerr << "LhsOuterStrideBytes=  " << LhsOuterStrideBytes << "\n";
+    std::cerr << "RhsOuterStrideBytes=  " << RhsOuterStrideBytes << "\n";
+    std::cerr << "LhsAlignment=         " << LhsAlignment << "\n";
+    std::cerr << "RhsAlignment=         " << RhsAlignment << "\n";
+    std::cerr << "CanVectorizeLhs=      " << CanVectorizeLhs << "\n";
+    std::cerr << "CanVectorizeRhs=      " << CanVectorizeRhs << "\n";
+    std::cerr << "CanVectorizeInner=    " << CanVectorizeInner << "\n";
+    std::cerr << "EvalToRowMajor=       " << EvalToRowMajor << "\n";
+    std::cerr << "Alignment=            " << Alignment << "\n";
+    std::cerr << "Flags=                " << Flags << "\n";
+#endif
+  }
+
+  // Everything below here is taken from CoeffBasedProduct.h
+
+  typedef typename internal::nested_eval<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
+  typedef typename internal::nested_eval<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
+  
+  typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
+  typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
+
+  typedef evaluator<LhsNestedCleaned> LhsEtorType;
+  typedef evaluator<RhsNestedCleaned> RhsEtorType;
+
+  enum {
+    RowsAtCompileTime = LhsNestedCleaned::RowsAtCompileTime,
+    ColsAtCompileTime = RhsNestedCleaned::ColsAtCompileTime,
+    InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(LhsNestedCleaned::ColsAtCompileTime, RhsNestedCleaned::RowsAtCompileTime),
+    MaxRowsAtCompileTime = LhsNestedCleaned::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = RhsNestedCleaned::MaxColsAtCompileTime
+  };
+
+  typedef typename find_best_packet<Scalar,RowsAtCompileTime>::type LhsVecPacketType;
+  typedef typename find_best_packet<Scalar,ColsAtCompileTime>::type RhsVecPacketType;
+
+  enum {
+      
+    LhsCoeffReadCost = LhsEtorType::CoeffReadCost,
+    RhsCoeffReadCost = RhsEtorType::CoeffReadCost,
+    CoeffReadCost = InnerSize==0 ? NumTraits<Scalar>::ReadCost
+                  : InnerSize == Dynamic ? HugeCost
+                  : InnerSize * (NumTraits<Scalar>::MulCost + LhsCoeffReadCost + RhsCoeffReadCost)
+                    + (InnerSize - 1) * NumTraits<Scalar>::AddCost,
+
+    Unroll = CoeffReadCost <= EIGEN_UNROLLING_LIMIT,
+    
+    LhsFlags = LhsEtorType::Flags,
+    RhsFlags = RhsEtorType::Flags,
+    
+    LhsRowMajor = LhsFlags & RowMajorBit,
+    RhsRowMajor = RhsFlags & RowMajorBit,
+
+    LhsVecPacketSize = unpacket_traits<LhsVecPacketType>::size,
+    RhsVecPacketSize = unpacket_traits<RhsVecPacketType>::size,
+
+    // Here, we don't care about alignment larger than the usable packet size.
+    LhsAlignment = EIGEN_PLAIN_ENUM_MIN(LhsEtorType::Alignment,LhsVecPacketSize*int(sizeof(typename LhsNestedCleaned::Scalar))),
+    RhsAlignment = EIGEN_PLAIN_ENUM_MIN(RhsEtorType::Alignment,RhsVecPacketSize*int(sizeof(typename RhsNestedCleaned::Scalar))),
+      
+    SameType = is_same<typename LhsNestedCleaned::Scalar,typename RhsNestedCleaned::Scalar>::value,
+
+    CanVectorizeRhs = bool(RhsRowMajor) && (RhsFlags & PacketAccessBit) && (ColsAtCompileTime!=1),
+    CanVectorizeLhs = (!LhsRowMajor) && (LhsFlags & PacketAccessBit) && (RowsAtCompileTime!=1),
+
+    EvalToRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
+                    : (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
+                    : (bool(RhsRowMajor) && !CanVectorizeLhs),
+
+    Flags = ((unsigned int)(LhsFlags | RhsFlags) & HereditaryBits & ~RowMajorBit)
+          | (EvalToRowMajor ? RowMajorBit : 0)
+          // TODO enable vectorization for mixed types
+          | (SameType && (CanVectorizeLhs || CanVectorizeRhs) ? PacketAccessBit : 0)
+          | (XprType::IsVectorAtCompileTime ? LinearAccessBit : 0),
+          
+    LhsOuterStrideBytes = int(LhsNestedCleaned::OuterStrideAtCompileTime) * int(sizeof(typename LhsNestedCleaned::Scalar)),
+    RhsOuterStrideBytes = int(RhsNestedCleaned::OuterStrideAtCompileTime) * int(sizeof(typename RhsNestedCleaned::Scalar)),
+
+    Alignment = bool(CanVectorizeLhs) ? (LhsOuterStrideBytes<=0 || (int(LhsOuterStrideBytes) % EIGEN_PLAIN_ENUM_MAX(1,LhsAlignment))!=0 ? 0 : LhsAlignment)
+              : bool(CanVectorizeRhs) ? (RhsOuterStrideBytes<=0 || (int(RhsOuterStrideBytes) % EIGEN_PLAIN_ENUM_MAX(1,RhsAlignment))!=0 ? 0 : RhsAlignment)
+              : 0,
+
+    /* CanVectorizeInner deserves special explanation. It does not affect the product flags. It is not used outside
+     * of Product. If the Product itself is not a packet-access expression, there is still a chance that the inner
+     * loop of the product might be vectorized. This is the meaning of CanVectorizeInner. Since it doesn't affect
+     * the Flags, it is safe to make this value depend on ActualPacketAccessBit, that doesn't affect the ABI.
+     */
+    CanVectorizeInner =    SameType
+                        && LhsRowMajor
+                        && (!RhsRowMajor)
+                        && (LhsFlags & RhsFlags & ActualPacketAccessBit)
+                        && (InnerSize % packet_traits<Scalar>::size == 0)
+  };
+  
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index row, Index col) const
+  {
+    return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
+  }
+
+  /* Allow index-based non-packet access. It is impossible though to allow index-based packed access,
+   * which is why we don't set the LinearAccessBit.
+   * TODO: this seems possible when the result is a vector
+   */
+  EIGEN_DEVICE_FUNC const CoeffReturnType coeff(Index index) const
+  {
+    const Index row = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime==1) ? 0 : index;
+    const Index col = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime==1) ? index : 0;
+    return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
+  }
+
+  template<int LoadMode, typename PacketType>
+  const PacketType packet(Index row, Index col) const
+  {
+    PacketType res;
+    typedef etor_product_packet_impl<bool(int(Flags)&RowMajorBit) ? RowMajor : ColMajor,
+                                     Unroll ? int(InnerSize) : Dynamic,
+                                     LhsEtorType, RhsEtorType, PacketType, LoadMode> PacketImpl;
+    PacketImpl::run(row, col, m_lhsImpl, m_rhsImpl, m_innerDim, res);
+    return res;
+  }
+
+  template<int LoadMode, typename PacketType>
+  const PacketType packet(Index index) const
+  {
+    const Index row = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime==1) ? 0 : index;
+    const Index col = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime==1) ? index : 0;
+    return packet<LoadMode,PacketType>(row,col);
+  }
+
+protected:
+  typename internal::add_const_on_value_type<LhsNested>::type m_lhs;
+  typename internal::add_const_on_value_type<RhsNested>::type m_rhs;
+  
+  LhsEtorType m_lhsImpl;
+  RhsEtorType m_rhsImpl;
+
+  // TODO: Get rid of m_innerDim if known at compile time
+  Index m_innerDim;
+};
+
+template<typename Lhs, typename Rhs>
+struct product_evaluator<Product<Lhs, Rhs, DefaultProduct>, LazyCoeffBasedProductMode, DenseShape, DenseShape>
+  : product_evaluator<Product<Lhs, Rhs, LazyProduct>, CoeffBasedProductMode, DenseShape, DenseShape>
+{
+  typedef Product<Lhs, Rhs, DefaultProduct> XprType;
+  typedef Product<Lhs, Rhs, LazyProduct> BaseProduct;
+  typedef product_evaluator<BaseProduct, CoeffBasedProductMode, DenseShape, DenseShape> Base;
+  enum {
+    Flags = Base::Flags | EvalBeforeNestingBit
+  };
+  EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
+    : Base(BaseProduct(xpr.lhs(),xpr.rhs()))
+  {}
+};
+
+/****************************************
+*** Coeff based product, Packet path  ***
+****************************************/
+
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<RowMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
+{
+  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet &res)
+  {
+    etor_product_packet_impl<RowMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, innerDim, res);
+    res =  pmadd(pset1<Packet>(lhs.coeff(row, Index(UnrollingIndex-1))), rhs.template packet<LoadMode,Packet>(Index(UnrollingIndex-1), col), res);
+  }
+};
+
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<ColMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
+{
+  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet &res)
+  {
+    etor_product_packet_impl<ColMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, innerDim, res);
+    res =  pmadd(lhs.template packet<LoadMode,Packet>(row, Index(UnrollingIndex-1)), pset1<Packet>(rhs.coeff(Index(UnrollingIndex-1), col)), res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<RowMajor, 1, Lhs, Rhs, Packet, LoadMode>
+{
+  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, Packet &res)
+  {
+    res = pmul(pset1<Packet>(lhs.coeff(row, Index(0))),rhs.template packet<LoadMode,Packet>(Index(0), col));
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<ColMajor, 1, Lhs, Rhs, Packet, LoadMode>
+{
+  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, Packet &res)
+  {
+    res = pmul(lhs.template packet<LoadMode,Packet>(row, Index(0)), pset1<Packet>(rhs.coeff(Index(0), col)));
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
+{
+  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, Index /*innerDim*/, Packet &res)
+  {
+    res = pset1<Packet>(typename unpacket_traits<Packet>::type(0));
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
+{
+  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, Index /*innerDim*/, Packet &res)
+  {
+    res = pset1<Packet>(typename unpacket_traits<Packet>::type(0));
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
+{
+  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet& res)
+  {
+    res = pset1<Packet>(typename unpacket_traits<Packet>::type(0));
+    for(Index i = 0; i < innerDim; ++i)
+      res =  pmadd(pset1<Packet>(lhs.coeff(row, i)), rhs.template packet<LoadMode,Packet>(i, col), res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
+{
+  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet& res)
+  {
+    res = pset1<Packet>(typename unpacket_traits<Packet>::type(0));
+    for(Index i = 0; i < innerDim; ++i)
+      res =  pmadd(lhs.template packet<LoadMode,Packet>(row, i), pset1<Packet>(rhs.coeff(i, col)), res);
+  }
+};
+
+
+/***************************************************************************
+* Triangular products
+***************************************************************************/
+template<int Mode, bool LhsIsTriangular,
+         typename Lhs, bool LhsIsVector,
+         typename Rhs, bool RhsIsVector>
+struct triangular_product_impl;
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct generic_product_impl<Lhs,Rhs,TriangularShape,DenseShape,ProductTag>
+  : generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,TriangularShape,DenseShape,ProductTag> >
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  template<typename Dest>
+  static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  {
+    triangular_product_impl<Lhs::Mode,true,typename Lhs::MatrixType,false,Rhs, Rhs::ColsAtCompileTime==1>
+        ::run(dst, lhs.nestedExpression(), rhs, alpha);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct generic_product_impl<Lhs,Rhs,DenseShape,TriangularShape,ProductTag>
+: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,TriangularShape,ProductTag> >
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  template<typename Dest>
+  static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  {
+    triangular_product_impl<Rhs::Mode,false,Lhs,Lhs::RowsAtCompileTime==1, typename Rhs::MatrixType, false>::run(dst, lhs, rhs.nestedExpression(), alpha);
+  }
+};
+
+
+/***************************************************************************
+* SelfAdjoint products
+***************************************************************************/
+template <typename Lhs, int LhsMode, bool LhsIsVector,
+          typename Rhs, int RhsMode, bool RhsIsVector>
+struct selfadjoint_product_impl;
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct generic_product_impl<Lhs,Rhs,SelfAdjointShape,DenseShape,ProductTag>
+  : generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,SelfAdjointShape,DenseShape,ProductTag> >
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  template<typename Dest>
+  static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  {
+    selfadjoint_product_impl<typename Lhs::MatrixType,Lhs::Mode,false,Rhs,0,Rhs::IsVectorAtCompileTime>::run(dst, lhs.nestedExpression(), rhs, alpha);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct generic_product_impl<Lhs,Rhs,DenseShape,SelfAdjointShape,ProductTag>
+: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,SelfAdjointShape,ProductTag> >
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  template<typename Dest>
+  static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  {
+    selfadjoint_product_impl<Lhs,0,Lhs::IsVectorAtCompileTime,typename Rhs::MatrixType,Rhs::Mode,false>::run(dst, lhs, rhs.nestedExpression(), alpha);
+  }
+};
+
+
+/***************************************************************************
+* Diagonal products
+***************************************************************************/
+  
+template<typename MatrixType, typename DiagonalType, typename Derived, int ProductOrder>
+struct diagonal_product_evaluator_base
+  : evaluator_base<Derived>
+{
+   typedef typename ScalarBinaryOpTraits<typename MatrixType::Scalar, typename DiagonalType::Scalar>::ReturnType Scalar;
+public:
+  enum {
+    CoeffReadCost = NumTraits<Scalar>::MulCost + evaluator<MatrixType>::CoeffReadCost + evaluator<DiagonalType>::CoeffReadCost,
+    
+    MatrixFlags = evaluator<MatrixType>::Flags,
+    DiagFlags = evaluator<DiagonalType>::Flags,
+    _StorageOrder = MatrixFlags & RowMajorBit ? RowMajor : ColMajor,
+    _ScalarAccessOnDiag =  !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft)
+                           ||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)),
+    _SameTypes = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
+    // FIXME currently we need same types, but in the future the next rule should be the one
+    //_Vectorizable = bool(int(MatrixFlags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagFlags)&PacketAccessBit))),
+    _Vectorizable = bool(int(MatrixFlags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagFlags)&PacketAccessBit))),
+    _LinearAccessMask = (MatrixType::RowsAtCompileTime==1 || MatrixType::ColsAtCompileTime==1) ? LinearAccessBit : 0,
+    Flags = ((HereditaryBits|_LinearAccessMask) & (unsigned int)(MatrixFlags)) | (_Vectorizable ? PacketAccessBit : 0),
+    Alignment = evaluator<MatrixType>::Alignment
+  };
+  
+  diagonal_product_evaluator_base(const MatrixType &mat, const DiagonalType &diag)
+    : m_diagImpl(diag), m_matImpl(mat)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(NumTraits<Scalar>::MulCost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
+  {
+    return m_diagImpl.coeff(idx) * m_matImpl.coeff(idx);
+  }
+  
+protected:
+  template<int LoadMode,typename PacketType>
+  EIGEN_STRONG_INLINE PacketType packet_impl(Index row, Index col, Index id, internal::true_type) const
+  {
+    return internal::pmul(m_matImpl.template packet<LoadMode,PacketType>(row, col),
+                          internal::pset1<PacketType>(m_diagImpl.coeff(id)));
+  }
+  
+  template<int LoadMode,typename PacketType>
+  EIGEN_STRONG_INLINE PacketType packet_impl(Index row, Index col, Index id, internal::false_type) const
+  {
+    enum {
+      InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
+      DiagonalPacketLoadMode = EIGEN_PLAIN_ENUM_MIN(LoadMode,((InnerSize%16) == 0) ? int(Aligned16) : int(evaluator<DiagonalType>::Alignment)) // FIXME hardcoded 16!!
+    };
+    return internal::pmul(m_matImpl.template packet<LoadMode,PacketType>(row, col),
+                          m_diagImpl.template packet<DiagonalPacketLoadMode,PacketType>(id));
+  }
+  
+  evaluator<DiagonalType> m_diagImpl;
+  evaluator<MatrixType>   m_matImpl;
+};
+
+// diagonal * dense
+template<typename Lhs, typename Rhs, int ProductKind, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DiagonalShape, DenseShape>
+  : diagonal_product_evaluator_base<Rhs, typename Lhs::DiagonalVectorType, Product<Lhs, Rhs, LazyProduct>, OnTheLeft>
+{
+  typedef diagonal_product_evaluator_base<Rhs, typename Lhs::DiagonalVectorType, Product<Lhs, Rhs, LazyProduct>, OnTheLeft> Base;
+  using Base::m_diagImpl;
+  using Base::m_matImpl;
+  using Base::coeff;
+  typedef typename Base::Scalar Scalar;
+  
+  typedef Product<Lhs, Rhs, ProductKind> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  
+  enum {
+    StorageOrder = int(Rhs::Flags) & RowMajorBit ? RowMajor : ColMajor
+  };
+
+  EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
+    : Base(xpr.rhs(), xpr.lhs().diagonal())
+  {
+  }
+  
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
+  {
+    return m_diagImpl.coeff(row) * m_matImpl.coeff(row, col);
+  }
+  
+#ifndef __CUDACC__
+  template<int LoadMode,typename PacketType>
+  EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const
+  {
+    // FIXME: NVCC used to complain about the template keyword, but we have to check whether this is still the case.
+    // See also similar calls below.
+    return this->template packet_impl<LoadMode,PacketType>(row,col, row,
+                                 typename internal::conditional<int(StorageOrder)==RowMajor, internal::true_type, internal::false_type>::type());
+  }
+  
+  template<int LoadMode,typename PacketType>
+  EIGEN_STRONG_INLINE PacketType packet(Index idx) const
+  {
+    return packet<LoadMode,PacketType>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
+  }
+#endif
+};
+
+// dense * diagonal
+template<typename Lhs, typename Rhs, int ProductKind, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DenseShape, DiagonalShape>
+  : diagonal_product_evaluator_base<Lhs, typename Rhs::DiagonalVectorType, Product<Lhs, Rhs, LazyProduct>, OnTheRight>
+{
+  typedef diagonal_product_evaluator_base<Lhs, typename Rhs::DiagonalVectorType, Product<Lhs, Rhs, LazyProduct>, OnTheRight> Base;
+  using Base::m_diagImpl;
+  using Base::m_matImpl;
+  using Base::coeff;
+  typedef typename Base::Scalar Scalar;
+  
+  typedef Product<Lhs, Rhs, ProductKind> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  
+  enum { StorageOrder = int(Lhs::Flags) & RowMajorBit ? RowMajor : ColMajor };
+
+  EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
+    : Base(xpr.lhs(), xpr.rhs().diagonal())
+  {
+  }
+  
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
+  {
+    return m_matImpl.coeff(row, col) * m_diagImpl.coeff(col);
+  }
+  
+#ifndef __CUDACC__
+  template<int LoadMode,typename PacketType>
+  EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const
+  {
+    return this->template packet_impl<LoadMode,PacketType>(row,col, col,
+                                 typename internal::conditional<int(StorageOrder)==ColMajor, internal::true_type, internal::false_type>::type());
+  }
+  
+  template<int LoadMode,typename PacketType>
+  EIGEN_STRONG_INLINE PacketType packet(Index idx) const
+  {
+    return packet<LoadMode,PacketType>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
+  }
+#endif
+};
+
+/***************************************************************************
+* Products with permutation matrices
+***************************************************************************/
+
+/** \internal
+  * \class permutation_matrix_product
+  * Internal helper class implementing the product between a permutation matrix and a matrix.
+  * This class is specialized for DenseShape below and for SparseShape in SparseCore/SparsePermutation.h
+  */
+template<typename ExpressionType, int Side, bool Transposed, typename ExpressionShape>
+struct permutation_matrix_product;
+
+template<typename ExpressionType, int Side, bool Transposed>
+struct permutation_matrix_product<ExpressionType, Side, Transposed, DenseShape>
+{
+    typedef typename nested_eval<ExpressionType, 1>::type MatrixType;
+    typedef typename remove_all<MatrixType>::type MatrixTypeCleaned;
+
+    template<typename Dest, typename PermutationType>
+    static inline void run(Dest& dst, const PermutationType& perm, const ExpressionType& xpr)
+    {
+      MatrixType mat(xpr);
+      const Index n = Side==OnTheLeft ? mat.rows() : mat.cols();
+      // FIXME we need an is_same for expression that is not sensitive to constness. For instance
+      // is_same_xpr<Block<const Matrix>, Block<Matrix> >::value should be true.
+      //if(is_same<MatrixTypeCleaned,Dest>::value && extract_data(dst) == extract_data(mat))
+      if(is_same_dense(dst, mat))
+      {
+        // apply the permutation inplace
+        Matrix<bool,PermutationType::RowsAtCompileTime,1,0,PermutationType::MaxRowsAtCompileTime> mask(perm.size());
+        mask.fill(false);
+        Index r = 0;
+        while(r < perm.size())
+        {
+          // search for the next seed
+          while(r<perm.size() && mask[r]) r++;
+          if(r>=perm.size())
+            break;
+          // we got one, let's follow it until we are back to the seed
+          Index k0 = r++;
+          Index kPrev = k0;
+          mask.coeffRef(k0) = true;
+          for(Index k=perm.indices().coeff(k0); k!=k0; k=perm.indices().coeff(k))
+          {
+                  Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>(dst, k)
+            .swap(Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>
+                       (dst,((Side==OnTheLeft) ^ Transposed) ? k0 : kPrev));
+
+            mask.coeffRef(k) = true;
+            kPrev = k;
+          }
+        }
+      }
+      else
+      {
+        for(Index i = 0; i < n; ++i)
+        {
+          Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>
+               (dst, ((Side==OnTheLeft) ^ Transposed) ? perm.indices().coeff(i) : i)
+
+          =
+
+          Block<const MatrixTypeCleaned,Side==OnTheLeft ? 1 : MatrixTypeCleaned::RowsAtCompileTime,Side==OnTheRight ? 1 : MatrixTypeCleaned::ColsAtCompileTime>
+               (mat, ((Side==OnTheRight) ^ Transposed) ? perm.indices().coeff(i) : i);
+        }
+      }
+    }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Lhs, Rhs, PermutationShape, MatrixShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    permutation_matrix_product<Rhs, OnTheLeft, false, MatrixShape>::run(dst, lhs, rhs);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Lhs, Rhs, MatrixShape, PermutationShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    permutation_matrix_product<Lhs, OnTheRight, false, MatrixShape>::run(dst, rhs, lhs);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Inverse<Lhs>, Rhs, PermutationShape, MatrixShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Inverse<Lhs>& lhs, const Rhs& rhs)
+  {
+    permutation_matrix_product<Rhs, OnTheLeft, true, MatrixShape>::run(dst, lhs.nestedExpression(), rhs);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Lhs, Inverse<Rhs>, MatrixShape, PermutationShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Inverse<Rhs>& rhs)
+  {
+    permutation_matrix_product<Lhs, OnTheRight, true, MatrixShape>::run(dst, rhs.nestedExpression(), lhs);
+  }
+};
+
+
+/***************************************************************************
+* Products with transpositions matrices
+***************************************************************************/
+
+// FIXME could we unify Transpositions and Permutation into a single "shape"??
+
+/** \internal
+  * \class transposition_matrix_product
+  * Internal helper class implementing the product between a permutation matrix and a matrix.
+  */
+template<typename ExpressionType, int Side, bool Transposed, typename ExpressionShape>
+struct transposition_matrix_product
+{
+  typedef typename nested_eval<ExpressionType, 1>::type MatrixType;
+  typedef typename remove_all<MatrixType>::type MatrixTypeCleaned;
+  
+  template<typename Dest, typename TranspositionType>
+  static inline void run(Dest& dst, const TranspositionType& tr, const ExpressionType& xpr)
+  {
+    MatrixType mat(xpr);
+    typedef typename TranspositionType::StorageIndex StorageIndex;
+    const Index size = tr.size();
+    StorageIndex j = 0;
+
+    if(!is_same_dense(dst,mat))
+      dst = mat;
+
+    for(Index k=(Transposed?size-1:0) ; Transposed?k>=0:k<size ; Transposed?--k:++k)
+      if(Index(j=tr.coeff(k))!=k)
+      {
+        if(Side==OnTheLeft)        dst.row(k).swap(dst.row(j));
+        else if(Side==OnTheRight)  dst.col(k).swap(dst.col(j));
+      }
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Lhs, Rhs, TranspositionsShape, MatrixShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    transposition_matrix_product<Rhs, OnTheLeft, false, MatrixShape>::run(dst, lhs, rhs);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Lhs, Rhs, MatrixShape, TranspositionsShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    transposition_matrix_product<Lhs, OnTheRight, false, MatrixShape>::run(dst, rhs, lhs);
+  }
+};
+
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Transpose<Lhs>, Rhs, TranspositionsShape, MatrixShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Transpose<Lhs>& lhs, const Rhs& rhs)
+  {
+    transposition_matrix_product<Rhs, OnTheLeft, true, MatrixShape>::run(dst, lhs.nestedExpression(), rhs);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Lhs, Transpose<Rhs>, MatrixShape, TranspositionsShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Transpose<Rhs>& rhs)
+  {
+    transposition_matrix_product<Lhs, OnTheRight, true, MatrixShape>::run(dst, rhs.nestedExpression(), lhs);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_PRODUCT_EVALUATORS_H

Index: 3rd_party/eigen/Eigen/src/Core/Random.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Random.h
+++ 3rd_party/eigen/Eigen/src/Core/Random.h
@@ -14,12 +14,11 @@
 
 namespace internal {
 
 template<typename Scalar> struct scalar_random_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_random_op)
-  template<typename Index>
-  inline const Scalar operator() (Index, Index = 0) const { return random<Scalar>(); }
+  inline const Scalar operator() () const { return random<Scalar>(); }
 };
 
 template<typename Scalar>
 struct functor_traits<scalar_random_op<Scalar> >
 { enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false, IsRepeatable = false }; };
@@ -26,39 +25,51 @@
 
 } // end namespace internal
 
 /** \returns a random matrix expression
   *
+  * Numbers are uniformly spread through their whole definition range for integer types,
+  * and in the [-1:1] range for floating point scalar types.
+  * 
   * The parameters \a rows and \a cols are the number of rows and of columns of
   * the returned matrix. Must be compatible with this MatrixBase type.
   *
+  * \not_reentrant
+  * 
   * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
   * it is redundant to pass \a rows and \a cols as arguments, so Random() should be used
   * instead.
+  * 
   *
   * Example: \include MatrixBase_random_int_int.cpp
   * Output: \verbinclude MatrixBase_random_int_int.out
   *
   * This expression has the "evaluate before nesting" flag so that it will be evaluated into
   * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
   * behavior with expressions involving random matrices.
+  * 
+  * See DenseBase::NullaryExpr(Index, const CustomNullaryOp&) for an example using C++11 random generators.
   *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(Index), MatrixBase::Random()
+  * \sa DenseBase::setRandom(), DenseBase::Random(Index), DenseBase::Random()
   */
 template<typename Derived>
-inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
+inline const typename DenseBase<Derived>::RandomReturnType
 DenseBase<Derived>::Random(Index rows, Index cols)
 {
   return NullaryExpr(rows, cols, internal::scalar_random_op<Scalar>());
 }
 
 /** \returns a random vector expression
+  *
+  * Numbers are uniformly spread through their whole definition range for integer types,
+  * and in the [-1:1] range for floating point scalar types.
   *
   * The parameter \a size is the size of the returned vector.
   * Must be compatible with this MatrixBase type.
   *
   * \only_for_vectors
+  * \not_reentrant
   *
   * This variant is meant to be used for dynamic-size vector types. For fixed-size types,
   * it is redundant to pass \a size as argument, so Random() should be used
   * instead.
   *
@@ -67,42 +78,52 @@
   *
   * This expression has the "evaluate before nesting" flag so that it will be evaluated into
   * a temporary vector whenever it is nested in a larger expression. This prevents unexpected
   * behavior with expressions involving random matrices.
   *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(Index,Index), MatrixBase::Random()
+  * \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random()
   */
 template<typename Derived>
-inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
+inline const typename DenseBase<Derived>::RandomReturnType
 DenseBase<Derived>::Random(Index size)
 {
   return NullaryExpr(size, internal::scalar_random_op<Scalar>());
 }
 
 /** \returns a fixed-size random matrix or vector expression
   *
+  * Numbers are uniformly spread through their whole definition range for integer types,
+  * and in the [-1:1] range for floating point scalar types.
+  * 
   * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
   * need to use the variants taking size arguments.
   *
   * Example: \include MatrixBase_random.cpp
   * Output: \verbinclude MatrixBase_random.out
   *
   * This expression has the "evaluate before nesting" flag so that it will be evaluated into
   * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
   * behavior with expressions involving random matrices.
+  * 
+  * \not_reentrant
   *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(Index,Index), MatrixBase::Random(Index)
+  * \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random(Index)
   */
 template<typename Derived>
-inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
+inline const typename DenseBase<Derived>::RandomReturnType
 DenseBase<Derived>::Random()
 {
   return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_random_op<Scalar>());
 }
 
 /** Sets all coefficients in this expression to random values.
   *
+  * Numbers are uniformly spread through their whole definition range for integer types,
+  * and in the [-1:1] range for floating point scalar types.
+  * 
+  * \not_reentrant
+  * 
   * Example: \include MatrixBase_setRandom.cpp
   * Output: \verbinclude MatrixBase_setRandom.out
   *
   * \sa class CwiseNullaryOp, setRandom(Index), setRandom(Index,Index)
   */
@@ -112,16 +133,20 @@
   return *this = Random(rows(), cols());
 }
 
 /** Resizes to the given \a newSize, and sets all coefficients in this expression to random values.
   *
+  * Numbers are uniformly spread through their whole definition range for integer types,
+  * and in the [-1:1] range for floating point scalar types.
+  * 
   * \only_for_vectors
+  * \not_reentrant
   *
   * Example: \include Matrix_setRandom_int.cpp
   * Output: \verbinclude Matrix_setRandom_int.out
   *
-  * \sa MatrixBase::setRandom(), setRandom(Index,Index), class CwiseNullaryOp, MatrixBase::Random()
+  * \sa DenseBase::setRandom(), setRandom(Index,Index), class CwiseNullaryOp, DenseBase::Random()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
 PlainObjectBase<Derived>::setRandom(Index newSize)
 {
@@ -129,24 +154,29 @@
   return setRandom();
 }
 
 /** Resizes to the given size, and sets all coefficients in this expression to random values.
   *
-  * \param nbRows the new number of rows
-  * \param nbCols the new number of columns
+  * Numbers are uniformly spread through their whole definition range for integer types,
+  * and in the [-1:1] range for floating point scalar types.
+  *
+  * \not_reentrant
+  * 
+  * \param rows the new number of rows
+  * \param cols the new number of columns
   *
   * Example: \include Matrix_setRandom_int_int.cpp
   * Output: \verbinclude Matrix_setRandom_int_int.out
   *
-  * \sa MatrixBase::setRandom(), setRandom(Index), class CwiseNullaryOp, MatrixBase::Random()
+  * \sa DenseBase::setRandom(), setRandom(Index), class CwiseNullaryOp, DenseBase::Random()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setRandom(Index nbRows, Index nbCols)
+PlainObjectBase<Derived>::setRandom(Index rows, Index cols)
 {
-  resize(nbRows, nbCols);
+  resize(rows, cols);
   return setRandom();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_RANDOM_H

Index: 3rd_party/eigen/Eigen/src/Core/Redux.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Redux.h
+++ 3rd_party/eigen/Eigen/src/Core/Redux.h
@@ -25,22 +25,23 @@
 
 template<typename Func, typename Derived>
 struct redux_traits
 {
 public:
+    typedef typename find_best_packet<typename Derived::Scalar,Derived::SizeAtCompileTime>::type PacketType;
   enum {
-    PacketSize = packet_traits<typename Derived::Scalar>::size,
+    PacketSize = unpacket_traits<PacketType>::size,
     InnerMaxSize = int(Derived::IsRowMajor)
                  ? Derived::MaxColsAtCompileTime
                  : Derived::MaxRowsAtCompileTime
   };
 
   enum {
     MightVectorize = (int(Derived::Flags)&ActualPacketAccessBit)
                   && (functor_traits<Func>::PacketAccess),
-    MayLinearVectorize = MightVectorize && (int(Derived::Flags)&LinearAccessBit),
-    MaySliceVectorize  = MightVectorize && int(InnerMaxSize)>=3*PacketSize
+    MayLinearVectorize = bool(MightVectorize) && (int(Derived::Flags)&LinearAccessBit),
+    MaySliceVectorize  = bool(MightVectorize) && int(InnerMaxSize)>=3*PacketSize
   };
 
 public:
   enum {
     Traversal = int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
@@ -48,25 +49,38 @@
                                         : int(DefaultTraversal)
   };
 
 public:
   enum {
-    Cost = (  Derived::SizeAtCompileTime == Dynamic
-           || Derived::CoeffReadCost == Dynamic
-           || (Derived::SizeAtCompileTime!=1 && functor_traits<Func>::Cost == Dynamic)
-           ) ? Dynamic
-           : Derived::SizeAtCompileTime * Derived::CoeffReadCost
-               + (Derived::SizeAtCompileTime-1) * functor_traits<Func>::Cost,
+    Cost = Derived::SizeAtCompileTime == Dynamic ? HugeCost
+         : Derived::SizeAtCompileTime * Derived::CoeffReadCost + (Derived::SizeAtCompileTime-1) * functor_traits<Func>::Cost,
     UnrollingLimit = EIGEN_UNROLLING_LIMIT * (int(Traversal) == int(DefaultTraversal) ? 1 : int(PacketSize))
   };
 
 public:
   enum {
-    Unrolling = Cost != Dynamic && Cost <= UnrollingLimit
-              ? CompleteUnrolling
-              : NoUnrolling
+    Unrolling = Cost <= UnrollingLimit ? CompleteUnrolling : NoUnrolling
   };
+  
+#ifdef EIGEN_DEBUG_ASSIGN
+  static void debug()
+  {
+    std::cerr << "Xpr: " << typeid(typename Derived::XprType).name() << std::endl;
+    std::cerr.setf(std::ios::hex, std::ios::basefield);
+    EIGEN_DEBUG_VAR(Derived::Flags)
+    std::cerr.unsetf(std::ios::hex);
+    EIGEN_DEBUG_VAR(InnerMaxSize)
+    EIGEN_DEBUG_VAR(PacketSize)
+    EIGEN_DEBUG_VAR(MightVectorize)
+    EIGEN_DEBUG_VAR(MayLinearVectorize)
+    EIGEN_DEBUG_VAR(MaySliceVectorize)
+    EIGEN_DEBUG_VAR(Traversal)
+    EIGEN_DEBUG_VAR(UnrollingLimit)
+    EIGEN_DEBUG_VAR(Unrolling)
+    std::cerr << std::endl;
+  }
+#endif
 };
 
 /***************************************************************************
 * Part 2 : unrollers
 ***************************************************************************/
@@ -80,10 +94,11 @@
     HalfLength = Length/2
   };
 
   typedef typename Derived::Scalar Scalar;
 
+  EIGEN_DEVICE_FUNC
   static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
   {
     return func(redux_novec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),
                 redux_novec_unroller<Func, Derived, Start+HalfLength, Length-HalfLength>::run(mat,func));
   }
@@ -97,10 +112,11 @@
     inner = Start % Derived::InnerSizeAtCompileTime
   };
 
   typedef typename Derived::Scalar Scalar;
 
+  EIGEN_DEVICE_FUNC
   static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func&)
   {
     return mat.coeffByOuterInner(outer, inner);
   }
 };
@@ -110,25 +126,26 @@
 // for 0 length run() will never be called at all.
 template<typename Func, typename Derived, int Start>
 struct redux_novec_unroller<Func, Derived, Start, 0>
 {
   typedef typename Derived::Scalar Scalar;
+  EIGEN_DEVICE_FUNC 
   static EIGEN_STRONG_INLINE Scalar run(const Derived&, const Func&) { return Scalar(); }
 };
 
 /*** vectorization ***/
 
 template<typename Func, typename Derived, int Start, int Length>
 struct redux_vec_unroller
 {
   enum {
-    PacketSize = packet_traits<typename Derived::Scalar>::size,
+    PacketSize = redux_traits<Func, Derived>::PacketSize,
     HalfLength = Length/2
   };
 
   typedef typename Derived::Scalar Scalar;
-  typedef typename packet_traits<Scalar>::type PacketScalar;
+  typedef typename redux_traits<Func, Derived>::PacketType PacketScalar;
 
   static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func& func)
   {
     return func.packetOp(
             redux_vec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),
@@ -138,22 +155,22 @@
 
 template<typename Func, typename Derived, int Start>
 struct redux_vec_unroller<Func, Derived, Start, 1>
 {
   enum {
-    index = Start * packet_traits<typename Derived::Scalar>::size,
+    index = Start * redux_traits<Func, Derived>::PacketSize,
     outer = index / int(Derived::InnerSizeAtCompileTime),
     inner = index % int(Derived::InnerSizeAtCompileTime),
-    alignment = (Derived::Flags & AlignedBit) ? Aligned : Unaligned
+    alignment = Derived::Alignment
   };
 
   typedef typename Derived::Scalar Scalar;
-  typedef typename packet_traits<Scalar>::type PacketScalar;
+  typedef typename redux_traits<Func, Derived>::PacketType PacketScalar;
 
   static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func&)
   {
-    return mat.template packetByOuterInner<alignment>(outer, inner);
+    return mat.template packetByOuterInner<alignment,PacketScalar>(outer, inner);
   }
 };
 
 /***************************************************************************
 * Part 3 : implementation of all cases
@@ -167,12 +184,12 @@
 
 template<typename Func, typename Derived>
 struct redux_impl<Func, Derived, DefaultTraversal, NoUnrolling>
 {
   typedef typename Derived::Scalar Scalar;
-  typedef typename Derived::Index Index;
-  static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func)
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
   {
     eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
     Scalar res;
     res = mat.coeffByOuterInner(0, 0);
     for(Index i = 1; i < mat.innerSize(); ++i)
@@ -191,43 +208,43 @@
 
 template<typename Func, typename Derived>
 struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
 {
   typedef typename Derived::Scalar Scalar;
-  typedef typename packet_traits<Scalar>::type PacketScalar;
-  typedef typename Derived::Index Index;
+  typedef typename redux_traits<Func, Derived>::PacketType PacketScalar;
 
-  static Scalar run(const Derived& mat, const Func& func)
+  static Scalar run(const Derived &mat, const Func& func)
   {
     const Index size = mat.size();
-    eigen_assert(size && "you are using an empty matrix");
-    const Index packetSize = packet_traits<Scalar>::size;
-    const Index alignedStart = internal::first_aligned(mat);
+    
+    const Index packetSize = redux_traits<Func, Derived>::PacketSize;
+    const int packetAlignment = unpacket_traits<PacketScalar>::alignment;
     enum {
-      alignment = bool(Derived::Flags & DirectAccessBit) || bool(Derived::Flags & AlignedBit)
-                ? Aligned : Unaligned
+      alignment0 = (bool(Derived::Flags & DirectAccessBit) && bool(packet_traits<Scalar>::AlignedOnScalar)) ? int(packetAlignment) : int(Unaligned),
+      alignment = EIGEN_PLAIN_ENUM_MAX(alignment0, Derived::Alignment)
     };
+    const Index alignedStart = internal::first_default_aligned(mat.nestedExpression());
     const Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize);
     const Index alignedSize = ((size-alignedStart)/(packetSize))*(packetSize);
     const Index alignedEnd2 = alignedStart + alignedSize2;
     const Index alignedEnd  = alignedStart + alignedSize;
     Scalar res;
     if(alignedSize)
     {
-      PacketScalar packet_res0 = mat.template packet<alignment>(alignedStart);
+      PacketScalar packet_res0 = mat.template packet<alignment,PacketScalar>(alignedStart);
       if(alignedSize>packetSize) // we have at least two packets to partly unroll the loop
       {
-        PacketScalar packet_res1 = mat.template packet<alignment>(alignedStart+packetSize);
+        PacketScalar packet_res1 = mat.template packet<alignment,PacketScalar>(alignedStart+packetSize);
         for(Index index = alignedStart + 2*packetSize; index < alignedEnd2; index += 2*packetSize)
         {
-          packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment>(index));
-          packet_res1 = func.packetOp(packet_res1, mat.template packet<alignment>(index+packetSize));
+          packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment,PacketScalar>(index));
+          packet_res1 = func.packetOp(packet_res1, mat.template packet<alignment,PacketScalar>(index+packetSize));
         }
 
         packet_res0 = func.packetOp(packet_res0,packet_res1);
         if(alignedEnd>alignedEnd2)
-          packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment>(alignedEnd2));
+          packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment,PacketScalar>(alignedEnd2));
       }
       res = func.predux(packet_res0);
 
       for(Index index = 0; index < alignedStart; ++index)
         res = func(res,mat.coeff(index));
@@ -245,33 +262,33 @@
 
     return res;
   }
 };
 
-template<typename Func, typename Derived>
-struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
+// NOTE: for SliceVectorizedTraversal we simply bypass unrolling
+template<typename Func, typename Derived, int Unrolling>
+struct redux_impl<Func, Derived, SliceVectorizedTraversal, Unrolling>
 {
   typedef typename Derived::Scalar Scalar;
-  typedef typename packet_traits<Scalar>::type PacketScalar;
-  typedef typename Derived::Index Index;
+  typedef typename redux_traits<Func, Derived>::PacketType PacketType;
 
-  static Scalar run(const Derived& mat, const Func& func)
+  EIGEN_DEVICE_FUNC static Scalar run(const Derived &mat, const Func& func)
   {
     eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
     const Index innerSize = mat.innerSize();
     const Index outerSize = mat.outerSize();
     enum {
-      packetSize = packet_traits<Scalar>::size
+      packetSize = redux_traits<Func, Derived>::PacketSize
     };
     const Index packetedInnerSize = ((innerSize)/packetSize)*packetSize;
     Scalar res;
     if(packetedInnerSize)
     {
-      PacketScalar packet_res = mat.template packet<Unaligned>(0,0);
+      PacketType packet_res = mat.template packet<Unaligned,PacketType>(0,0);
       for(Index j=0; j<outerSize; ++j)
         for(Index i=(j==0?packetSize:0); i<packetedInnerSize; i+=Index(packetSize))
-          packet_res = func.packetOp(packet_res, mat.template packetByOuterInner<Unaligned>(j,i));
+          packet_res = func.packetOp(packet_res, mat.template packetByOuterInner<Unaligned,PacketType>(j,i));
 
       res = func.predux(packet_res);
       for(Index j=0; j<outerSize; ++j)
         for(Index i=packetedInnerSize; i<innerSize; ++i)
           res = func(res, mat.coeffByOuterInner(j,i));
@@ -288,25 +305,93 @@
 
 template<typename Func, typename Derived>
 struct redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
 {
   typedef typename Derived::Scalar Scalar;
-  typedef typename packet_traits<Scalar>::type PacketScalar;
+
+  typedef typename redux_traits<Func, Derived>::PacketType PacketScalar;
   enum {
-    PacketSize = packet_traits<Scalar>::size,
+    PacketSize = redux_traits<Func, Derived>::PacketSize,
     Size = Derived::SizeAtCompileTime,
     VectorizedSize = (Size / PacketSize) * PacketSize
   };
-  static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
   {
     eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
-    Scalar res = func.predux(redux_vec_unroller<Func, Derived, 0, Size / PacketSize>::run(mat,func));
-    if (VectorizedSize != Size)
-      res = func(res,redux_novec_unroller<Func, Derived, VectorizedSize, Size-VectorizedSize>::run(mat,func));
-    return res;
+    if (VectorizedSize > 0) {
+      Scalar res = func.predux(redux_vec_unroller<Func, Derived, 0, Size / PacketSize>::run(mat,func));
+      if (VectorizedSize != Size)
+        res = func(res,redux_novec_unroller<Func, Derived, VectorizedSize, Size-VectorizedSize>::run(mat,func));
+      return res;
+    }
+    else {
+      return redux_novec_unroller<Func, Derived, 0, Size>::run(mat,func);
+    }
   }
 };
+
+// evaluator adaptor
+template<typename _XprType>
+class redux_evaluator
+{
+public:
+  typedef _XprType XprType;
+  EIGEN_DEVICE_FUNC explicit redux_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) {}
+  
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename XprType::PacketScalar PacketScalar;
+  typedef typename XprType::PacketReturnType PacketReturnType;
+  
+  enum {
+    MaxRowsAtCompileTime = XprType::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = XprType::MaxColsAtCompileTime,
+    // TODO we should not remove DirectAccessBit and rather find an elegant way to query the alignment offset at runtime from the evaluator
+    Flags = evaluator<XprType>::Flags & ~DirectAccessBit,
+    IsRowMajor = XprType::IsRowMajor,
+    SizeAtCompileTime = XprType::SizeAtCompileTime,
+    InnerSizeAtCompileTime = XprType::InnerSizeAtCompileTime,
+    CoeffReadCost = evaluator<XprType>::CoeffReadCost,
+    Alignment = evaluator<XprType>::Alignment
+  };
+  
+  EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
+  EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
+  EIGEN_DEVICE_FUNC Index size() const { return m_xpr.size(); }
+  EIGEN_DEVICE_FUNC Index innerSize() const { return m_xpr.innerSize(); }
+  EIGEN_DEVICE_FUNC Index outerSize() const { return m_xpr.outerSize(); }
+
+  EIGEN_DEVICE_FUNC
+  CoeffReturnType coeff(Index row, Index col) const
+  { return m_evaluator.coeff(row, col); }
+
+  EIGEN_DEVICE_FUNC
+  CoeffReturnType coeff(Index index) const
+  { return m_evaluator.coeff(index); }
+
+  template<int LoadMode, typename PacketType>
+  PacketType packet(Index row, Index col) const
+  { return m_evaluator.template packet<LoadMode,PacketType>(row, col); }
+
+  template<int LoadMode, typename PacketType>
+  PacketType packet(Index index) const
+  { return m_evaluator.template packet<LoadMode,PacketType>(index); }
+  
+  EIGEN_DEVICE_FUNC
+  CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
+  { return m_evaluator.coeff(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
+  
+  template<int LoadMode, typename PacketType>
+  PacketType packetByOuterInner(Index outer, Index inner) const
+  { return m_evaluator.template packet<LoadMode,PacketType>(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
+  
+  const XprType & nestedExpression() const { return m_xpr; }
+  
+protected:
+  internal::evaluator<XprType> m_evaluator;
+  const XprType &m_xpr;
+};
 
 } // end namespace internal
 
 /***************************************************************************
 * Part 4 : public API
@@ -314,55 +399,60 @@
 
 
 /** \returns the result of a full redux operation on the whole matrix or vector using \a func
   *
   * The template parameter \a BinaryOp is the type of the functor \a func which must be
-  * an associative operator. Both current STL and TR1 functor styles are handled.
+  * an associative operator. Both current C++98 and C++11 functor styles are handled.
   *
   * \sa DenseBase::sum(), DenseBase::minCoeff(), DenseBase::maxCoeff(), MatrixBase::colwise(), MatrixBase::rowwise()
   */
 template<typename Derived>
 template<typename Func>
-EIGEN_STRONG_INLINE typename internal::result_of<Func(typename internal::traits<Derived>::Scalar)>::type
+typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::redux(const Func& func) const
 {
-  typedef typename internal::remove_all<typename Derived::Nested>::type ThisNested;
-  return internal::redux_impl<Func, ThisNested>
-            ::run(derived(), func);
+  eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");
+
+  typedef typename internal::redux_evaluator<Derived> ThisEvaluator;
+  ThisEvaluator thisEval(derived());
+  
+  return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func);
 }
 
 /** \returns the minimum of all coefficients of \c *this.
   * \warning the result is undefined if \c *this contains NaN.
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::minCoeff() const
 {
-  return this->redux(Eigen::internal::scalar_min_op<Scalar>());
+  return derived().redux(Eigen::internal::scalar_min_op<Scalar,Scalar>());
 }
 
 /** \returns the maximum of all coefficients of \c *this.
   * \warning the result is undefined if \c *this contains NaN.
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::maxCoeff() const
 {
-  return this->redux(Eigen::internal::scalar_max_op<Scalar>());
+  return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar>());
 }
 
-/** \returns the sum of all coefficients of *this
+/** \returns the sum of all coefficients of \c *this
+  *
+  * If \c *this is empty, then the value 0 is returned.
   *
   * \sa trace(), prod(), mean()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::sum() const
 {
   if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
     return Scalar(0);
-  return this->redux(Eigen::internal::scalar_sum_op<Scalar>());
+  return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
 }
 
 /** \returns the mean of all coefficients of *this
 *
 * \sa trace(), prod(), sum()
@@ -369,11 +459,18 @@
 */
 template<typename Derived>
 EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::mean() const
 {
-  return Scalar(this->redux(Eigen::internal::scalar_sum_op<Scalar>())) / Scalar(this->size());
+#ifdef __INTEL_COMPILER
+  #pragma warning push
+  #pragma warning ( disable : 2259 )
+#endif
+  return Scalar(derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>())) / Scalar(this->size());
+#ifdef __INTEL_COMPILER
+  #pragma warning pop
+#endif
 }
 
 /** \returns the product of all coefficients of *this
   *
   * Example: \include MatrixBase_prod.cpp
@@ -385,11 +482,11 @@
 EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::prod() const
 {
   if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
     return Scalar(1);
-  return this->redux(Eigen::internal::scalar_product_op<Scalar>());
+  return derived().redux(Eigen::internal::scalar_product_op<Scalar>());
 }
 
 /** \returns the trace of \c *this, i.e. the sum of the coefficients on the main diagonal.
   *
   * \c *this can be any matrix, not necessarily square.

Index: 3rd_party/eigen/Eigen/src/Core/Ref.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Ref.h
+++ 3rd_party/eigen/Eigen/src/Core/Ref.h
@@ -10,83 +10,10 @@
 #ifndef EIGEN_REF_H
 #define EIGEN_REF_H
 
 namespace Eigen { 
 
-template<typename Derived> class RefBase;
-template<typename PlainObjectType, int Options = 0,
-         typename StrideType = typename internal::conditional<PlainObjectType::IsVectorAtCompileTime,InnerStride<1>,OuterStride<> >::type > class Ref;
-
-/** \class Ref
-  * \ingroup Core_Module
-  *
-  * \brief A matrix or vector expression mapping an existing expressions
-  *
-  * \tparam PlainObjectType the equivalent matrix type of the mapped data
-  * \tparam Options specifies whether the pointer is \c #Aligned, or \c #Unaligned.
-  *                The default is \c #Unaligned.
-  * \tparam StrideType optionally specifies strides. By default, Ref implies a contiguous storage along the inner dimension (inner stride==1),
-  *                   but accept a variable outer stride (leading dimension).
-  *                   This can be overridden by specifying strides.
-  *                   The type passed here must be a specialization of the Stride template, see examples below.
-  *
-  * This class permits to write non template functions taking Eigen's object as parameters while limiting the number of copies.
-  * A Ref<> object can represent either a const expression or a l-value:
-  * \code
-  * // in-out argument:
-  * void foo1(Ref<VectorXf> x);
-  *
-  * // read-only const argument:
-  * void foo2(const Ref<const VectorXf>& x);
-  * \endcode
-  *
-  * In the in-out case, the input argument must satisfies the constraints of the actual Ref<> type, otherwise a compilation issue will be triggered.
-  * By default, a Ref<VectorXf> can reference any dense vector expression of float having a contiguous memory layout.
-  * Likewise, a Ref<MatrixXf> can reference any column major dense matrix expression of float whose column's elements are contiguously stored with
-  * the possibility to have a constant space inbetween each column, i.e.: the inner stride mmust be equal to 1, but the outer-stride (or leading dimension),
-  * can be greater than the number of rows.
-  *
-  * In the const case, if the input expression does not match the above requirement, then it is evaluated into a temporary before being passed to the function.
-  * Here are some examples:
-  * \code
-  * MatrixXf A;
-  * VectorXf a;
-  * foo1(a.head());             // OK
-  * foo1(A.col());              // OK
-  * foo1(A.row());              // compilation error because here innerstride!=1
-  * foo2(A.row());              // The row is copied into a contiguous temporary
-  * foo2(2*a);                  // The expression is evaluated into a temporary
-  * foo2(A.col().segment(2,4)); // No temporary
-  * \endcode
-  *
-  * The range of inputs that can be referenced without temporary can be enlarged using the last two template parameter.
-  * Here is an example accepting an innerstride!=1:
-  * \code
-  * // in-out argument:
-  * void foo3(Ref<VectorXf,0,InnerStride<> > x);
-  * foo3(A.row());              // OK
-  * \endcode
-  * The downside here is that the function foo3 might be significantly slower than foo1 because it won't be able to exploit vectorization, and will involved more
-  * expensive address computations even if the input is contiguously stored in memory. To overcome this issue, one might propose to overloads internally calling a
-  * template function, e.g.:
-  * \code
-  * // in the .h:
-  * void foo(const Ref<MatrixXf>& A);
-  * void foo(const Ref<MatrixXf,0,Stride<> >& A);
-  *
-  * // in the .cpp:
-  * template<typename TypeOfA> void foo_impl(const TypeOfA& A) {
-  *     ... // crazy code goes here
-  * }
-  * void foo(const Ref<MatrixXf>& A) { foo_impl(A); }
-  * void foo(const Ref<MatrixXf,0,Stride<> >& A) { foo_impl(A); }
-  * \endcode
-  *
-  *
-  * \sa PlainObjectBase::Map(), \ref TopicStorageOrders
-  */
-
 namespace internal {
 
 template<typename _PlainObjectType, int _Options, typename _StrideType>
 struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
   : public traits<Map<_PlainObjectType, _Options, _StrideType> >
@@ -93,11 +20,12 @@
 {
   typedef _PlainObjectType PlainObjectType;
   typedef _StrideType StrideType;
   enum {
     Options = _Options,
-    Flags = traits<Map<_PlainObjectType, _Options, _StrideType> >::Flags | NestByRefBit
+    Flags = traits<Map<_PlainObjectType, _Options, _StrideType> >::Flags | NestByRefBit,
+    Alignment = traits<Map<_PlainObjectType, _Options, _StrideType> >::Alignment
   };
 
   template<typename Derived> struct match {
     enum {
       HasDirectAccess = internal::has_direct_access<Derived>::ret,
@@ -105,12 +33,19 @@
       InnerStrideMatch = int(StrideType::InnerStrideAtCompileTime)==int(Dynamic)
                       || int(StrideType::InnerStrideAtCompileTime)==int(Derived::InnerStrideAtCompileTime)
                       || (int(StrideType::InnerStrideAtCompileTime)==0 && int(Derived::InnerStrideAtCompileTime)==1),
       OuterStrideMatch = Derived::IsVectorAtCompileTime
                       || int(StrideType::OuterStrideAtCompileTime)==int(Dynamic) || int(StrideType::OuterStrideAtCompileTime)==int(Derived::OuterStrideAtCompileTime),
-      AlignmentMatch = (_Options!=Aligned) || ((PlainObjectType::Flags&AlignedBit)==0) || ((traits<Derived>::Flags&AlignedBit)==AlignedBit),
-      MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch
+      // NOTE, this indirection of evaluator<Derived>::Alignment is needed
+      // to workaround a very strange bug in MSVC related to the instantiation
+      // of has_*ary_operator in evaluator<CwiseNullaryOp>.
+      // This line is surprisingly very sensitive. For instance, simply adding parenthesis
+      // as "DerivedAlignment = (int(evaluator<Derived>::Alignment))," will make MSVC fail...
+      DerivedAlignment = int(evaluator<Derived>::Alignment),
+      AlignmentMatch = (int(traits<PlainObjectType>::Alignment)==int(Unaligned)) || (DerivedAlignment >= int(Alignment)), // FIXME the first condition is not very clear, it should be replaced by the required alignment
+      ScalarTypeMatch = internal::is_same<typename PlainObjectType::Scalar, typename Derived::Scalar>::value,
+      MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch && ScalarTypeMatch
     };
     typedef typename internal::conditional<MatchAtCompileTime,internal::true_type,internal::false_type>::type type;
   };
   
 };
@@ -129,24 +64,24 @@
 public:
 
   typedef MapBase<Derived> Base;
   EIGEN_DENSE_PUBLIC_INTERFACE(RefBase)
 
-  inline Index innerStride() const
+  EIGEN_DEVICE_FUNC inline Index innerStride() const
   {
     return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
   }
 
-  inline Index outerStride() const
+  EIGEN_DEVICE_FUNC inline Index outerStride() const
   {
     return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
          : IsVectorAtCompileTime ? this->size()
          : int(Flags)&RowMajorBit ? this->cols()
          : this->rows();
   }
 
-  RefBase()
+  EIGEN_DEVICE_FUNC RefBase()
     : Base(0,RowsAtCompileTime==Dynamic?0:RowsAtCompileTime,ColsAtCompileTime==Dynamic?0:ColsAtCompileTime),
       // Stride<> does not allow default ctor for Dynamic strides, so let' initialize it with dummy values:
       m_stride(StrideType::OuterStrideAtCompileTime==Dynamic?0:StrideType::OuterStrideAtCompileTime,
                StrideType::InnerStrideAtCompileTime==Dynamic?0:StrideType::InnerStrideAtCompileTime)
   {}
@@ -156,11 +91,11 @@
 protected:
 
   typedef Stride<StrideType::OuterStrideAtCompileTime,StrideType::InnerStrideAtCompileTime> StrideBase;
 
   template<typename Expression>
-  void construct(Expression& expr)
+  EIGEN_DEVICE_FUNC void construct(Expression& expr)
   {
     if(PlainObjectType::RowsAtCompileTime==1)
     {
       eigen_assert(expr.rows()==1 || expr.cols()==1);
       ::new (static_cast<Base*>(this)) Base(expr.data(), 1, expr.size());
@@ -181,40 +116,113 @@
   }
 
   StrideBase m_stride;
 };
 
-
+/** \class Ref
+  * \ingroup Core_Module
+  *
+  * \brief A matrix or vector expression mapping an existing expression
+  *
+  * \tparam PlainObjectType the equivalent matrix type of the mapped data
+  * \tparam Options specifies the pointer alignment in bytes. It can be: \c #Aligned128, , \c #Aligned64, \c #Aligned32, \c #Aligned16, \c #Aligned8 or \c #Unaligned.
+  *                 The default is \c #Unaligned.
+  * \tparam StrideType optionally specifies strides. By default, Ref implies a contiguous storage along the inner dimension (inner stride==1),
+  *                   but accepts a variable outer stride (leading dimension).
+  *                   This can be overridden by specifying strides.
+  *                   The type passed here must be a specialization of the Stride template, see examples below.
+  *
+  * This class provides a way to write non-template functions taking Eigen objects as parameters while limiting the number of copies.
+  * A Ref<> object can represent either a const expression or a l-value:
+  * \code
+  * // in-out argument:
+  * void foo1(Ref<VectorXf> x);
+  *
+  * // read-only const argument:
+  * void foo2(const Ref<const VectorXf>& x);
+  * \endcode
+  *
+  * In the in-out case, the input argument must satisfy the constraints of the actual Ref<> type, otherwise a compilation issue will be triggered.
+  * By default, a Ref<VectorXf> can reference any dense vector expression of float having a contiguous memory layout.
+  * Likewise, a Ref<MatrixXf> can reference any column-major dense matrix expression of float whose column's elements are contiguously stored with
+  * the possibility to have a constant space in-between each column, i.e. the inner stride must be equal to 1, but the outer stride (or leading dimension)
+  * can be greater than the number of rows.
+  *
+  * In the const case, if the input expression does not match the above requirement, then it is evaluated into a temporary before being passed to the function.
+  * Here are some examples:
+  * \code
+  * MatrixXf A;
+  * VectorXf a;
+  * foo1(a.head());             // OK
+  * foo1(A.col());              // OK
+  * foo1(A.row());              // Compilation error because here innerstride!=1
+  * foo2(A.row());              // Compilation error because A.row() is a 1xN object while foo2 is expecting a Nx1 object
+  * foo2(A.row().transpose());  // The row is copied into a contiguous temporary
+  * foo2(2*a);                  // The expression is evaluated into a temporary
+  * foo2(A.col().segment(2,4)); // No temporary
+  * \endcode
+  *
+  * The range of inputs that can be referenced without temporary can be enlarged using the last two template parameters.
+  * Here is an example accepting an innerstride!=1:
+  * \code
+  * // in-out argument:
+  * void foo3(Ref<VectorXf,0,InnerStride<> > x);
+  * foo3(A.row());              // OK
+  * \endcode
+  * The downside here is that the function foo3 might be significantly slower than foo1 because it won't be able to exploit vectorization, and will involve more
+  * expensive address computations even if the input is contiguously stored in memory. To overcome this issue, one might propose to overload internally calling a
+  * template function, e.g.:
+  * \code
+  * // in the .h:
+  * void foo(const Ref<MatrixXf>& A);
+  * void foo(const Ref<MatrixXf,0,Stride<> >& A);
+  *
+  * // in the .cpp:
+  * template<typename TypeOfA> void foo_impl(const TypeOfA& A) {
+  *     ... // crazy code goes here
+  * }
+  * void foo(const Ref<MatrixXf>& A) { foo_impl(A); }
+  * void foo(const Ref<MatrixXf,0,Stride<> >& A) { foo_impl(A); }
+  * \endcode
+  *
+  *
+  * \sa PlainObjectBase::Map(), \ref TopicStorageOrders
+  */
 template<typename PlainObjectType, int Options, typename StrideType> class Ref
   : public RefBase<Ref<PlainObjectType, Options, StrideType> >
 {
+  private:
     typedef internal::traits<Ref> Traits;
     template<typename Derived>
-    inline Ref(const PlainObjectBase<Derived>& expr);
+    EIGEN_DEVICE_FUNC inline Ref(const PlainObjectBase<Derived>& expr,
+                                 typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0);
   public:
 
     typedef RefBase<Ref> Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
 
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename Derived>
-    inline Ref(PlainObjectBase<Derived>& expr)
+    EIGEN_DEVICE_FUNC inline Ref(PlainObjectBase<Derived>& expr,
+                                 typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
     {
-      EIGEN_STATIC_ASSERT(static_cast<bool>(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
+      EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
       Base::construct(expr.derived());
     }
     template<typename Derived>
-    inline Ref(const DenseBase<Derived>& expr)
+    EIGEN_DEVICE_FUNC inline Ref(const DenseBase<Derived>& expr,
+                                 typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
     #else
+    /** Implicit constructor from any dense expression */
     template<typename Derived>
     inline Ref(DenseBase<Derived>& expr)
     #endif
     {
-      EIGEN_STATIC_ASSERT(static_cast<bool>(internal::is_lvalue<Derived>::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
-      EIGEN_STATIC_ASSERT(static_cast<bool>(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
-      enum { THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY = Derived::ThisConstantIsPrivateInPlainObjectBase};
+      EIGEN_STATIC_ASSERT(bool(internal::is_lvalue<Derived>::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
+      EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
+      EIGEN_STATIC_ASSERT(!Derived::IsPlainObjectBase,THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
       Base::construct(expr.const_cast_derived());
     }
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Ref)
 
@@ -229,30 +237,40 @@
 
     typedef RefBase<Ref> Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
 
     template<typename Derived>
-    inline Ref(const DenseBase<Derived>& expr)
+    EIGEN_DEVICE_FUNC inline Ref(const DenseBase<Derived>& expr,
+                                 typename internal::enable_if<bool(Traits::template match<Derived>::ScalarTypeMatch),Derived>::type* = 0)
     {
 //      std::cout << match_helper<Derived>::HasDirectAccess << "," << match_helper<Derived>::OuterStrideMatch << "," << match_helper<Derived>::InnerStrideMatch << "\n";
 //      std::cout << int(StrideType::OuterStrideAtCompileTime) << " - " << int(Derived::OuterStrideAtCompileTime) << "\n";
 //      std::cout << int(StrideType::InnerStrideAtCompileTime) << " - " << int(Derived::InnerStrideAtCompileTime) << "\n";
       construct(expr.derived(), typename Traits::template match<Derived>::type());
     }
+
+    EIGEN_DEVICE_FUNC inline Ref(const Ref& other) : Base(other) {
+      // copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy
+    }
+
+    template<typename OtherRef>
+    EIGEN_DEVICE_FUNC inline Ref(const RefBase<OtherRef>& other) {
+      construct(other.derived(), typename Traits::template match<OtherRef>::type());
+    }
 
   protected:
 
     template<typename Expression>
-    void construct(const Expression& expr,internal::true_type)
+    EIGEN_DEVICE_FUNC void construct(const Expression& expr,internal::true_type)
     {
       Base::construct(expr);
     }
 
     template<typename Expression>
-    void construct(const Expression& expr, internal::false_type)
+    EIGEN_DEVICE_FUNC void construct(const Expression& expr, internal::false_type)
     {
-      m_object.lazyAssign(expr);
+      internal::call_assignment_no_alias(m_object,expr,internal::assign_op<Scalar,Scalar>());
       Base::construct(m_object);
     }
 
   protected:
     TPlainObjectType m_object;

Index: 3rd_party/eigen/Eigen/src/Core/Replicate.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Replicate.h
+++ 3rd_party/eigen/Eigen/src/Core/Replicate.h
@@ -10,37 +10,19 @@
 #ifndef EIGEN_REPLICATE_H
 #define EIGEN_REPLICATE_H
 
 namespace Eigen { 
 
-/**
-  * \class Replicate
-  * \ingroup Core_Module
-  *
-  * \brief Expression of the multiple replication of a matrix or vector
-  *
-  * \param MatrixType the type of the object we are replicating
-  *
-  * This class represents an expression of the multiple replication of a matrix or vector.
-  * It is the return type of DenseBase::replicate() and most of the time
-  * this is the only way it is used.
-  *
-  * \sa DenseBase::replicate()
-  */
-
 namespace internal {
 template<typename MatrixType,int RowFactor,int ColFactor>
 struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
  : traits<MatrixType>
 {
   typedef typename MatrixType::Scalar Scalar;
   typedef typename traits<MatrixType>::StorageKind StorageKind;
   typedef typename traits<MatrixType>::XprKind XprKind;
-  enum {
-    Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor
-  };
-  typedef typename nested<MatrixType,Factor>::type MatrixTypeNested;
+  typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
   typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
     RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic
                       ? Dynamic
                       : RowFactor * MatrixType::RowsAtCompileTime,
@@ -51,71 +33,69 @@
     MaxRowsAtCompileTime = RowsAtCompileTime,
     MaxColsAtCompileTime = ColsAtCompileTime,
     IsRowMajor = MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1 ? 1
                : MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1 ? 0
                : (MatrixType::Flags & RowMajorBit) ? 1 : 0,
-    Flags = (_MatrixTypeNested::Flags & HereditaryBits & ~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0),
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost
+    
+    // FIXME enable DirectAccess with negative strides?
+    Flags = IsRowMajor ? RowMajorBit : 0
   };
 };
 }
 
+/**
+  * \class Replicate
+  * \ingroup Core_Module
+  *
+  * \brief Expression of the multiple replication of a matrix or vector
+  *
+  * \tparam MatrixType the type of the object we are replicating
+  * \tparam RowFactor number of repetitions at compile time along the vertical direction, can be Dynamic.
+  * \tparam ColFactor number of repetitions at compile time along the horizontal direction, can be Dynamic.
+  *
+  * This class represents an expression of the multiple replication of a matrix or vector.
+  * It is the return type of DenseBase::replicate() and most of the time
+  * this is the only way it is used.
+  *
+  * \sa DenseBase::replicate()
+  */
 template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
   : public internal::dense_xpr_base< Replicate<MatrixType,RowFactor,ColFactor> >::type
 {
     typedef typename internal::traits<Replicate>::MatrixTypeNested MatrixTypeNested;
     typedef typename internal::traits<Replicate>::_MatrixTypeNested _MatrixTypeNested;
   public:
 
     typedef typename internal::dense_xpr_base<Replicate>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Replicate)
+    typedef typename internal::remove_all<MatrixType>::type NestedExpression;
 
     template<typename OriginalMatrixType>
-    inline explicit Replicate(const OriginalMatrixType& a_matrix)
-      : m_matrix(a_matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
+    EIGEN_DEVICE_FUNC
+    inline explicit Replicate(const OriginalMatrixType& matrix)
+      : m_matrix(matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
     {
       EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
                           THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
       eigen_assert(RowFactor!=Dynamic && ColFactor!=Dynamic);
     }
 
     template<typename OriginalMatrixType>
-    inline Replicate(const OriginalMatrixType& a_matrix, Index rowFactor, Index colFactor)
-      : m_matrix(a_matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
+    EIGEN_DEVICE_FUNC
+    inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor)
+      : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
     {
       EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
                           THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
     }
 
+    EIGEN_DEVICE_FUNC
     inline Index rows() const { return m_matrix.rows() * m_rowFactor.value(); }
+    EIGEN_DEVICE_FUNC
     inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); }
 
-    inline Scalar coeff(Index rowId, Index colId) const
-    {
-      // try to avoid using modulo; this is a pure optimization strategy
-      const Index actual_row  = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
-                            : RowFactor==1 ? rowId
-                            : rowId%m_matrix.rows();
-      const Index actual_col  = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
-                            : ColFactor==1 ? colId
-                            : colId%m_matrix.cols();
-
-      return m_matrix.coeff(actual_row, actual_col);
-    }
-    template<int LoadMode>
-    inline PacketScalar packet(Index rowId, Index colId) const
-    {
-      const Index actual_row  = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
-                            : RowFactor==1 ? rowId
-                            : rowId%m_matrix.rows();
-      const Index actual_col  = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
-                            : ColFactor==1 ? colId
-                            : colId%m_matrix.cols();
-
-      return m_matrix.template packet<LoadMode>(actual_row, actual_col);
-    }
-
+    EIGEN_DEVICE_FUNC
     const _MatrixTypeNested& nestedExpression() const
     { 
       return m_matrix; 
     }
 
@@ -139,25 +119,10 @@
 DenseBase<Derived>::replicate() const
 {
   return Replicate<Derived,RowFactor,ColFactor>(derived());
 }
 
-/**
-  * \return an expression of the replication of \c *this
-  *
-  * Example: \include MatrixBase_replicate_int_int.cpp
-  * Output: \verbinclude MatrixBase_replicate_int_int.out
-  *
-  * \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
-  */
-template<typename Derived>
-const typename DenseBase<Derived>::ReplicateReturnType
-DenseBase<Derived>::replicate(Index rowFactor,Index colFactor) const
-{
-  return Replicate<Derived,Dynamic,Dynamic>(derived(),rowFactor,colFactor);
-}
-
 /**
   * \return an expression of the replication of each column (or row) of \c *this
   *
   * Example: \include DirectionWise_replicate_int.cpp
   * Output: \verbinclude DirectionWise_replicate_int.out

Index: 3rd_party/eigen/Eigen/src/Core/ReturnByValue.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/ReturnByValue.h
+++ 3rd_party/eigen/Eigen/src/Core/ReturnByValue.h
@@ -11,15 +11,10 @@
 #ifndef EIGEN_RETURNBYVALUE_H
 #define EIGEN_RETURNBYVALUE_H
 
 namespace Eigen {
 
-/** \class ReturnByValue
-  * \ingroup Core_Module
-  *
-  */
-
 namespace internal {
 
 template<typename Derived>
 struct traits<ReturnByValue<Derived> >
   : public traits<typename traits<Derived>::ReturnType>
@@ -36,33 +31,39 @@
 /* The ReturnByValue object doesn't even have a coeff() method.
  * So the only way that nesting it in an expression can work, is by evaluating it into a plain matrix.
  * So internal::nested always gives the plain return matrix type.
  *
  * FIXME: I don't understand why we need this specialization: isn't this taken care of by the EvalBeforeNestingBit ??
+ * Answer: EvalBeforeNestingBit should be deprecated since we have the evaluators
  */
 template<typename Derived,int n,typename PlainObject>
-struct nested<ReturnByValue<Derived>, n, PlainObject>
+struct nested_eval<ReturnByValue<Derived>, n, PlainObject>
 {
   typedef typename traits<Derived>::ReturnType type;
 };
 
 } // end namespace internal
 
+/** \class ReturnByValue
+  * \ingroup Core_Module
+  *
+  */
 template<typename Derived> class ReturnByValue
-  : internal::no_assignment_operator, public internal::dense_xpr_base< ReturnByValue<Derived> >::type
+  : public internal::dense_xpr_base< ReturnByValue<Derived> >::type, internal::no_assignment_operator
 {
   public:
     typedef typename internal::traits<Derived>::ReturnType ReturnType;
 
     typedef typename internal::dense_xpr_base<ReturnByValue>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(ReturnByValue)
 
     template<typename Dest>
+    EIGEN_DEVICE_FUNC
     inline void evalTo(Dest& dst) const
     { static_cast<const Derived*>(this)->evalTo(dst); }
-    inline Index rows() const { return static_cast<const Derived*>(this)->rows(); }
-    inline Index cols() const { return static_cast<const Derived*>(this)->cols(); }
+    EIGEN_DEVICE_FUNC inline Index rows() const { return static_cast<const Derived*>(this)->rows(); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return static_cast<const Derived*>(this)->cols(); }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
 #define Unusable YOU_ARE_TRYING_TO_ACCESS_A_SINGLE_COEFFICIENT_IN_A_SPECIAL_EXPRESSION_WHERE_THAT_IS_NOT_ALLOWED_BECAUSE_THAT_WOULD_BE_INEFFICIENT
     class Unusable{
       Unusable(const Unusable&) {}
@@ -70,10 +71,11 @@
     };
     const Unusable& coeff(Index) const { return *reinterpret_cast<const Unusable*>(this); }
     const Unusable& coeff(Index,Index) const { return *reinterpret_cast<const Unusable*>(this); }
     Unusable& coeffRef(Index) { return *reinterpret_cast<Unusable*>(this); }
     Unusable& coeffRef(Index,Index) { return *reinterpret_cast<Unusable*>(this); }
+#undef Unusable
 #endif
 };
 
 template<typename Derived>
 template<typename OtherDerived>
@@ -81,8 +83,35 @@
 {
   other.evalTo(derived());
   return derived();
 }
 
+namespace internal {
+
+// Expression is evaluated in a temporary; default implementation of Assignment is bypassed so that
+// when a ReturnByValue expression is assigned, the evaluator is not constructed.
+// TODO: Finalize port to new regime; ReturnByValue should not exist in the expression world
+  
+template<typename Derived>
+struct evaluator<ReturnByValue<Derived> >
+  : public evaluator<typename internal::traits<Derived>::ReturnType>
+{
+  typedef ReturnByValue<Derived> XprType;
+  typedef typename internal::traits<Derived>::ReturnType PlainObject;
+  typedef evaluator<PlainObject> Base;
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
+    : m_result(xpr.rows(), xpr.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    xpr.evalTo(m_result);
+  }
+
+protected:
+  PlainObject m_result;
+};
+
+} // end namespace internal
+
 } // end namespace Eigen
 
 #endif // EIGEN_RETURNBYVALUE_H

Index: 3rd_party/eigen/Eigen/src/Core/Reverse.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Reverse.h
+++ 3rd_party/eigen/Eigen/src/Core/Reverse.h
@@ -12,76 +12,66 @@
 #ifndef EIGEN_REVERSE_H
 #define EIGEN_REVERSE_H
 
 namespace Eigen { 
 
-/** \class Reverse
-  * \ingroup Core_Module
-  *
-  * \brief Expression of the reverse of a vector or matrix
-  *
-  * \param MatrixType the type of the object of which we are taking the reverse
-  *
-  * This class represents an expression of the reverse of a vector.
-  * It is the return type of MatrixBase::reverse() and VectorwiseOp::reverse()
-  * and most of the time this is the only way it is used.
-  *
-  * \sa MatrixBase::reverse(), VectorwiseOp::reverse()
-  */
-
 namespace internal {
 
 template<typename MatrixType, int Direction>
 struct traits<Reverse<MatrixType, Direction> >
  : traits<MatrixType>
 {
   typedef typename MatrixType::Scalar Scalar;
   typedef typename traits<MatrixType>::StorageKind StorageKind;
   typedef typename traits<MatrixType>::XprKind XprKind;
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
   typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
     RowsAtCompileTime = MatrixType::RowsAtCompileTime,
     ColsAtCompileTime = MatrixType::ColsAtCompileTime,
     MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-
-    // let's enable LinearAccess only with vectorization because of the product overhead
-    LinearAccess = ( (Direction==BothDirections) && (int(_MatrixTypeNested::Flags)&PacketAccessBit) )
-                 ? LinearAccessBit : 0,
-
-    Flags = int(_MatrixTypeNested::Flags) & (HereditaryBits | LvalueBit | PacketAccessBit | LinearAccess),
-
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost
+    Flags = _MatrixTypeNested::Flags & (RowMajorBit | LvalueBit)
   };
 };
 
-template<typename PacketScalar, bool ReversePacket> struct reverse_packet_cond
+template<typename PacketType, bool ReversePacket> struct reverse_packet_cond
 {
-  static inline PacketScalar run(const PacketScalar& x) { return preverse(x); }
+  static inline PacketType run(const PacketType& x) { return preverse(x); }
 };
 
-template<typename PacketScalar> struct reverse_packet_cond<PacketScalar,false>
+template<typename PacketType> struct reverse_packet_cond<PacketType,false>
 {
-  static inline PacketScalar run(const PacketScalar& x) { return x; }
+  static inline PacketType run(const PacketType& x) { return x; }
 };
 
 } // end namespace internal 
 
+/** \class Reverse
+  * \ingroup Core_Module
+  *
+  * \brief Expression of the reverse of a vector or matrix
+  *
+  * \tparam MatrixType the type of the object of which we are taking the reverse
+  * \tparam Direction defines the direction of the reverse operation, can be Vertical, Horizontal, or BothDirections
+  *
+  * This class represents an expression of the reverse of a vector.
+  * It is the return type of MatrixBase::reverse() and VectorwiseOp::reverse()
+  * and most of the time this is the only way it is used.
+  *
+  * \sa MatrixBase::reverse(), VectorwiseOp::reverse()
+  */
 template<typename MatrixType, int Direction> class Reverse
   : public internal::dense_xpr_base< Reverse<MatrixType, Direction> >::type
 {
   public:
 
     typedef typename internal::dense_xpr_base<Reverse>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Reverse)
+    typedef typename internal::remove_all<MatrixType>::type NestedExpression;
     using Base::IsRowMajor;
 
-    // next line is necessary because otherwise const version of operator()
-    // is hidden by non-const version defined in this file
-    using Base::operator(); 
-
   protected:
     enum {
       PacketSize = internal::packet_traits<Scalar>::size,
       IsColMajor = !IsRowMajor,
       ReverseRow = (Direction == Vertical)   || (Direction == BothDirections),
@@ -93,86 +83,23 @@
                     || ((Direction == Horizontal) && IsRowMajor)
     };
     typedef internal::reverse_packet_cond<PacketScalar,ReversePacket> reverse_packet;
   public:
 
-    inline Reverse(const MatrixType& matrix) : m_matrix(matrix) { }
+    EIGEN_DEVICE_FUNC explicit inline Reverse(const MatrixType& matrix) : m_matrix(matrix) { }
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Reverse)
 
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.rows(); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.cols(); }
 
-    inline Index innerStride() const
+    EIGEN_DEVICE_FUNC inline Index innerStride() const
     {
       return -m_matrix.innerStride();
     }
 
-    inline Scalar& operator()(Index row, Index col)
-    {
-      eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
-      return coeffRef(row, col);
-    }
-
-    inline Scalar& coeffRef(Index row, Index col)
-    {
-      return m_matrix.const_cast_derived().coeffRef(ReverseRow ? m_matrix.rows() - row - 1 : row,
-                                                    ReverseCol ? m_matrix.cols() - col - 1 : col);
-    }
-
-    inline CoeffReturnType coeff(Index row, Index col) const
-    {
-      return m_matrix.coeff(ReverseRow ? m_matrix.rows() - row - 1 : row,
-                            ReverseCol ? m_matrix.cols() - col - 1 : col);
-    }
-
-    inline CoeffReturnType coeff(Index index) const
-    {
-      return m_matrix.coeff(m_matrix.size() - index - 1);
-    }
-
-    inline Scalar& coeffRef(Index index)
-    {
-      return m_matrix.const_cast_derived().coeffRef(m_matrix.size() - index - 1);
-    }
-
-    inline Scalar& operator()(Index index)
-    {
-      eigen_assert(index >= 0 && index < m_matrix.size());
-      return coeffRef(index);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index row, Index col) const
-    {
-      return reverse_packet::run(m_matrix.template packet<LoadMode>(
-                                    ReverseRow ? m_matrix.rows() - row - OffsetRow : row,
-                                    ReverseCol ? m_matrix.cols() - col - OffsetCol : col));
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& x)
-    {
-      m_matrix.const_cast_derived().template writePacket<LoadMode>(
-                                      ReverseRow ? m_matrix.rows() - row - OffsetRow : row,
-                                      ReverseCol ? m_matrix.cols() - col - OffsetCol : col,
-                                      reverse_packet::run(x));
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index index) const
-    {
-      return internal::preverse(m_matrix.template packet<LoadMode>( m_matrix.size() - index - PacketSize ));
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& x)
-    {
-      m_matrix.const_cast_derived().template writePacket<LoadMode>(m_matrix.size() - index - PacketSize, internal::preverse(x));
-    }
-
-    const typename internal::remove_all<typename MatrixType::Nested>::type& 
+    EIGEN_DEVICE_FUNC const typename internal::remove_all<typename MatrixType::Nested>::type&
     nestedExpression() const 
     {
       return m_matrix;
     }
 
@@ -188,37 +115,97 @@
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::ReverseReturnType
 DenseBase<Derived>::reverse()
 {
-  return derived();
+  return ReverseReturnType(derived());
 }
 
-/** This is the const version of reverse(). */
-template<typename Derived>
-inline const typename DenseBase<Derived>::ConstReverseReturnType
-DenseBase<Derived>::reverse() const
-{
-  return derived();
-}
+
+//reverse const overload moved DenseBase.h due to a CUDA compiler bug
 
 /** This is the "in place" version of reverse: it reverses \c *this.
   *
   * In most cases it is probably better to simply use the reversed expression
   * of a matrix. However, when reversing the matrix data itself is really needed,
   * then this "in-place" version is probably the right choice because it provides
-  * the following additional features:
+  * the following additional benefits:
   *  - less error prone: doing the same operation with .reverse() requires special care:
   *    \code m = m.reverse().eval(); \endcode
-  *  - this API allows to avoid creating a temporary (the current implementation creates a temporary, but that could be avoided using swap)
+  *  - this API enables reverse operations without the need for a temporary
   *  - it allows future optimizations (cache friendliness, etc.)
   *
-  * \sa reverse() */
+  * \sa VectorwiseOp::reverseInPlace(), reverse() */
 template<typename Derived>
 inline void DenseBase<Derived>::reverseInPlace()
 {
-  derived() = derived().reverse().eval();
+  if(cols()>rows())
+  {
+    Index half = cols()/2;
+    leftCols(half).swap(rightCols(half).reverse());
+    if((cols()%2)==1)
+    {
+      Index half2 = rows()/2;
+      col(half).head(half2).swap(col(half).tail(half2).reverse());
+    }
+  }
+  else
+  {
+    Index half = rows()/2;
+    topRows(half).swap(bottomRows(half).reverse());
+    if((rows()%2)==1)
+    {
+      Index half2 = cols()/2;
+      row(half).head(half2).swap(row(half).tail(half2).reverse());
+    }
+  }
+}
+
+namespace internal {
+  
+template<int Direction>
+struct vectorwise_reverse_inplace_impl;
+
+template<>
+struct vectorwise_reverse_inplace_impl<Vertical>
+{
+  template<typename ExpressionType>
+  static void run(ExpressionType &xpr)
+  {
+    Index half = xpr.rows()/2;
+    xpr.topRows(half).swap(xpr.bottomRows(half).colwise().reverse());
+  }
+};
+
+template<>
+struct vectorwise_reverse_inplace_impl<Horizontal>
+{
+  template<typename ExpressionType>
+  static void run(ExpressionType &xpr)
+  {
+    Index half = xpr.cols()/2;
+    xpr.leftCols(half).swap(xpr.rightCols(half).rowwise().reverse());
+  }
+};
+
+} // end namespace internal
+
+/** This is the "in place" version of VectorwiseOp::reverse: it reverses each column or row of \c *this.
+  *
+  * In most cases it is probably better to simply use the reversed expression
+  * of a matrix. However, when reversing the matrix data itself is really needed,
+  * then this "in-place" version is probably the right choice because it provides
+  * the following additional benefits:
+  *  - less error prone: doing the same operation with .reverse() requires special care:
+  *    \code m = m.reverse().eval(); \endcode
+  *  - this API enables reverse operations without the need for a temporary
+  *
+  * \sa DenseBase::reverseInPlace(), reverse() */
+template<typename ExpressionType, int Direction>
+void VectorwiseOp<ExpressionType,Direction>::reverseInPlace()
+{
+  internal::vectorwise_reverse_inplace_impl<Direction>::run(_expression().const_cast_derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_REVERSE_H

Index: 3rd_party/eigen/Eigen/src/Core/Select.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Select.h
+++ 3rd_party/eigen/Eigen/src/Core/Select.h
@@ -41,66 +41,66 @@
   enum {
     RowsAtCompileTime = ConditionMatrixType::RowsAtCompileTime,
     ColsAtCompileTime = ConditionMatrixType::ColsAtCompileTime,
     MaxRowsAtCompileTime = ConditionMatrixType::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = ConditionMatrixType::MaxColsAtCompileTime,
-    Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & HereditaryBits,
-    CoeffReadCost = traits<typename remove_all<ConditionMatrixNested>::type>::CoeffReadCost
-                  + EIGEN_SIZE_MAX(traits<typename remove_all<ThenMatrixNested>::type>::CoeffReadCost,
-                                   traits<typename remove_all<ElseMatrixNested>::type>::CoeffReadCost)
+    Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & RowMajorBit
   };
 };
 }
 
 template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType>
-class Select : internal::no_assignment_operator,
-  public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type
+class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type,
+               internal::no_assignment_operator
 {
   public:
 
     typedef typename internal::dense_xpr_base<Select>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Select)
 
+    inline EIGEN_DEVICE_FUNC
     Select(const ConditionMatrixType& a_conditionMatrix,
            const ThenMatrixType& a_thenMatrix,
            const ElseMatrixType& a_elseMatrix)
       : m_condition(a_conditionMatrix), m_then(a_thenMatrix), m_else(a_elseMatrix)
     {
       eigen_assert(m_condition.rows() == m_then.rows() && m_condition.rows() == m_else.rows());
       eigen_assert(m_condition.cols() == m_then.cols() && m_condition.cols() == m_else.cols());
     }
 
-    Index rows() const { return m_condition.rows(); }
-    Index cols() const { return m_condition.cols(); }
+    inline EIGEN_DEVICE_FUNC Index rows() const { return m_condition.rows(); }
+    inline EIGEN_DEVICE_FUNC Index cols() const { return m_condition.cols(); }
 
+    inline EIGEN_DEVICE_FUNC
     const Scalar coeff(Index i, Index j) const
     {
       if (m_condition.coeff(i,j))
         return m_then.coeff(i,j);
       else
         return m_else.coeff(i,j);
     }
 
+    inline EIGEN_DEVICE_FUNC
     const Scalar coeff(Index i) const
     {
       if (m_condition.coeff(i))
         return m_then.coeff(i);
       else
         return m_else.coeff(i);
     }
 
-    const ConditionMatrixType& conditionMatrix() const
+    inline EIGEN_DEVICE_FUNC const ConditionMatrixType& conditionMatrix() const
     {
       return m_condition;
     }
 
-    const ThenMatrixType& thenMatrix() const
+    inline EIGEN_DEVICE_FUNC const ThenMatrixType& thenMatrix() const
     {
       return m_then;
     }
 
-    const ElseMatrixType& elseMatrix() const
+    inline EIGEN_DEVICE_FUNC const ElseMatrixType& elseMatrix() const
     {
       return m_else;
     }
 
   protected:

Index: 3rd_party/eigen/Eigen/src/Core/SelfAdjointView.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/SelfAdjointView.h
+++ 3rd_party/eigen/Eigen/src/Core/SelfAdjointView.h
@@ -30,97 +30,113 @@
 
 namespace internal {
 template<typename MatrixType, unsigned int UpLo>
 struct traits<SelfAdjointView<MatrixType, UpLo> > : traits<MatrixType>
 {
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
-  typedef MatrixType ExpressionType;
-  typedef typename MatrixType::PlainObject DenseMatrixType;
-  enum {
-    Mode = UpLo | SelfAdjoint,
-    Flags =  MatrixTypeNestedCleaned::Flags & (HereditaryBits)
-           & (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)), // FIXME these flags should be preserved
-    CoeffReadCost = MatrixTypeNestedCleaned::CoeffReadCost
-  };
-};
-}
-
-template <typename Lhs, int LhsMode, bool LhsIsVector,
-          typename Rhs, int RhsMode, bool RhsIsVector>
-struct SelfadjointProductMatrix;
-
-// FIXME could also be called SelfAdjointWrapper to be consistent with DiagonalWrapper ??
-template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
-  : public TriangularBase<SelfAdjointView<MatrixType, UpLo> >
-{
-  public:
-
-    typedef TriangularBase<SelfAdjointView> Base;
-    typedef typename internal::traits<SelfAdjointView>::MatrixTypeNested MatrixTypeNested;
-    typedef typename internal::traits<SelfAdjointView>::MatrixTypeNestedCleaned MatrixTypeNestedCleaned;
-
-    /** \brief The type of coefficients in this matrix */
-    typedef typename internal::traits<SelfAdjointView>::Scalar Scalar; 
-
-    typedef typename MatrixType::Index Index;
-
-    enum {
-      Mode = internal::traits<SelfAdjointView>::Mode
-    };
-    typedef typename MatrixType::PlainObject PlainObject;
-
-    inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
-    {}
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-    inline Index outerStride() const { return m_matrix.outerStride(); }
+  typedef typename ref_selector<MatrixType>::non_const_type MatrixTypeNested;
+  typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
+  typedef MatrixType ExpressionType;
+  typedef typename MatrixType::PlainObject FullMatrixType;
+  enum {
+    Mode = UpLo | SelfAdjoint,
+    FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
+    Flags =  MatrixTypeNestedCleaned::Flags & (HereditaryBits|FlagsLvalueBit)
+           & (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)) // FIXME these flags should be preserved
+  };
+};
+}
+
+
+template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
+  : public TriangularBase<SelfAdjointView<_MatrixType, UpLo> >
+{
+  public:
+
+    typedef _MatrixType MatrixType;
+    typedef TriangularBase<SelfAdjointView> Base;
+    typedef typename internal::traits<SelfAdjointView>::MatrixTypeNested MatrixTypeNested;
+    typedef typename internal::traits<SelfAdjointView>::MatrixTypeNestedCleaned MatrixTypeNestedCleaned;
+    typedef MatrixTypeNestedCleaned NestedExpression;
+
+    /** \brief The type of coefficients in this matrix */
+    typedef typename internal::traits<SelfAdjointView>::Scalar Scalar; 
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    typedef typename internal::remove_all<typename MatrixType::ConjugateReturnType>::type MatrixConjugateReturnType;
+
+    enum {
+      Mode = internal::traits<SelfAdjointView>::Mode,
+      Flags = internal::traits<SelfAdjointView>::Flags,
+      TransposeMode = ((Mode & Upper) ? Lower : 0) | ((Mode & Lower) ? Upper : 0)
+    };
+    typedef typename MatrixType::PlainObject PlainObject;
+
+    EIGEN_DEVICE_FUNC
+    explicit inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
+    {}
+
+    EIGEN_DEVICE_FUNC
+    inline Index rows() const { return m_matrix.rows(); }
+    EIGEN_DEVICE_FUNC
+    inline Index cols() const { return m_matrix.cols(); }
+    EIGEN_DEVICE_FUNC
+    inline Index outerStride() const { return m_matrix.outerStride(); }
+    EIGEN_DEVICE_FUNC
     inline Index innerStride() const { return m_matrix.innerStride(); }
 
     /** \sa MatrixBase::coeff()
       * \warning the coordinates must fit into the referenced triangular part
       */
+    EIGEN_DEVICE_FUNC
     inline Scalar coeff(Index row, Index col) const
     {
       Base::check_coordinates_internal(row, col);
       return m_matrix.coeff(row, col);
     }
 
     /** \sa MatrixBase::coeffRef()
       * \warning the coordinates must fit into the referenced triangular part
       */
+    EIGEN_DEVICE_FUNC
     inline Scalar& coeffRef(Index row, Index col)
     {
+      EIGEN_STATIC_ASSERT_LVALUE(SelfAdjointView);
       Base::check_coordinates_internal(row, col);
-      return m_matrix.const_cast_derived().coeffRef(row, col);
+      return m_matrix.coeffRef(row, col);
     }
 
     /** \internal */
+    EIGEN_DEVICE_FUNC
     const MatrixTypeNestedCleaned& _expression() const { return m_matrix; }
 
+    EIGEN_DEVICE_FUNC
     const MatrixTypeNestedCleaned& nestedExpression() const { return m_matrix; }
-    MatrixTypeNestedCleaned& nestedExpression() { return *const_cast<MatrixTypeNestedCleaned*>(&m_matrix); }
+    EIGEN_DEVICE_FUNC
+    MatrixTypeNestedCleaned& nestedExpression() { return m_matrix; }
 
-    /** Efficient self-adjoint matrix times vector/matrix product */
+    /** Efficient triangular matrix times vector/matrix product */
     template<typename OtherDerived>
-    SelfadjointProductMatrix<MatrixType,Mode,false,OtherDerived,0,OtherDerived::IsVectorAtCompileTime>
+    EIGEN_DEVICE_FUNC
+    const Product<SelfAdjointView,OtherDerived>
     operator*(const MatrixBase<OtherDerived>& rhs) const
     {
-      return SelfadjointProductMatrix
-              <MatrixType,Mode,false,OtherDerived,0,OtherDerived::IsVectorAtCompileTime>
-              (m_matrix, rhs.derived());
+      return Product<SelfAdjointView,OtherDerived>(*this, rhs.derived());
     }
 
-    /** Efficient vector/matrix times self-adjoint matrix product */
+    /** Efficient vector/matrix times triangular matrix product */
     template<typename OtherDerived> friend
-    SelfadjointProductMatrix<OtherDerived,0,OtherDerived::IsVectorAtCompileTime,MatrixType,Mode,false>
+    EIGEN_DEVICE_FUNC
+    const Product<OtherDerived,SelfAdjointView>
     operator*(const MatrixBase<OtherDerived>& lhs, const SelfAdjointView& rhs)
     {
-      return SelfadjointProductMatrix
-              <OtherDerived,0,OtherDerived::IsVectorAtCompileTime,MatrixType,Mode,false>
-              (lhs.derived(),rhs.m_matrix);
+      return Product<OtherDerived,SelfAdjointView>(lhs.derived(),rhs);
+    }
+    
+    friend EIGEN_DEVICE_FUNC
+    const SelfAdjointView<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,MatrixType,product),UpLo>
+    operator*(const Scalar& s, const SelfAdjointView& mat)
+    {
+      return (s*mat.nestedExpression()).template selfadjointView<UpLo>();
     }
 
     /** Perform a symmetric rank 2 update of the selfadjoint matrix \c *this:
       * \f$ this = this + \alpha u v^* + conj(\alpha) v u^* \f$
       * \returns a reference to \c *this
@@ -130,10 +146,11 @@
       * part of the matrix is updated, the rest is left unchanged.
       *
       * \sa rankUpdate(const MatrixBase<DerivedU>&, Scalar)
       */
     template<typename DerivedU, typename DerivedV>
+    EIGEN_DEVICE_FUNC
     SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, const Scalar& alpha = Scalar(1));
 
     /** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
       * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix.
       *
@@ -143,11 +160,77 @@
       * call this function with u.adjoint().
       *
       * \sa rankUpdate(const MatrixBase<DerivedU>&, const MatrixBase<DerivedV>&, Scalar)
       */
     template<typename DerivedU>
+    EIGEN_DEVICE_FUNC
     SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, const Scalar& alpha = Scalar(1));
+
+    /** \returns an expression of a triangular view extracted from the current selfadjoint view of a given triangular part
+      *
+      * The parameter \a TriMode can have the following values: \c #Upper, \c #StrictlyUpper, \c #UnitUpper,
+      * \c #Lower, \c #StrictlyLower, \c #UnitLower.
+      *
+      * If \c TriMode references the same triangular part than \c *this, then this method simply return a \c TriangularView of the nested expression,
+      * otherwise, the nested expression is first transposed, thus returning a \c TriangularView<Transpose<MatrixType>> object.
+      *
+      * \sa MatrixBase::triangularView(), class TriangularView
+      */
+    template<unsigned int TriMode>
+    EIGEN_DEVICE_FUNC
+    typename internal::conditional<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)),
+                                   TriangularView<MatrixType,TriMode>,
+                                   TriangularView<typename MatrixType::AdjointReturnType,TriMode> >::type
+    triangularView() const
+    {
+      typename internal::conditional<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)), MatrixType&, typename MatrixType::ConstTransposeReturnType>::type tmp1(m_matrix);
+      typename internal::conditional<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)), MatrixType&, typename MatrixType::AdjointReturnType>::type tmp2(tmp1);
+      return typename internal::conditional<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)),
+                                   TriangularView<MatrixType,TriMode>,
+                                   TriangularView<typename MatrixType::AdjointReturnType,TriMode> >::type(tmp2);
+    }
+
+    typedef SelfAdjointView<const MatrixConjugateReturnType,Mode> ConjugateReturnType;
+    /** \sa MatrixBase::conjugate() const */
+    EIGEN_DEVICE_FUNC
+    inline const ConjugateReturnType conjugate() const
+    { return ConjugateReturnType(m_matrix.conjugate()); }
+
+    typedef SelfAdjointView<const typename MatrixType::AdjointReturnType,TransposeMode> AdjointReturnType;
+    /** \sa MatrixBase::adjoint() const */
+    EIGEN_DEVICE_FUNC
+    inline const AdjointReturnType adjoint() const
+    { return AdjointReturnType(m_matrix.adjoint()); }
+
+    typedef SelfAdjointView<typename MatrixType::TransposeReturnType,TransposeMode> TransposeReturnType;
+     /** \sa MatrixBase::transpose() */
+    EIGEN_DEVICE_FUNC
+    inline TransposeReturnType transpose()
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
+      typename MatrixType::TransposeReturnType tmp(m_matrix);
+      return TransposeReturnType(tmp);
+    }
+
+    typedef SelfAdjointView<const typename MatrixType::ConstTransposeReturnType,TransposeMode> ConstTransposeReturnType;
+    /** \sa MatrixBase::transpose() const */
+    EIGEN_DEVICE_FUNC
+    inline const ConstTransposeReturnType transpose() const
+    {
+      return ConstTransposeReturnType(m_matrix.transpose());
+    }
+
+    /** \returns a const expression of the main diagonal of the matrix \c *this
+      *
+      * This method simply returns the diagonal of the nested expression, thus by-passing the SelfAdjointView decorator.
+      *
+      * \sa MatrixBase::diagonal(), class Diagonal */
+    EIGEN_DEVICE_FUNC
+    typename MatrixType::ConstDiagonalReturnType diagonal() const
+    {
+      return typename MatrixType::ConstDiagonalReturnType(m_matrix);
+    }
 
 /////////// Cholesky module ///////////
 
     const LLT<PlainObject, UpLo> llt() const;
     const LDLT<PlainObject, UpLo> ldlt() const;
@@ -157,35 +240,14 @@
     /** Real part of #Scalar */
     typedef typename NumTraits<Scalar>::Real RealScalar;
     /** Return type of eigenvalues() */
     typedef Matrix<RealScalar, internal::traits<MatrixType>::ColsAtCompileTime, 1> EigenvaluesReturnType;
 
+    EIGEN_DEVICE_FUNC
     EigenvaluesReturnType eigenvalues() const;
+    EIGEN_DEVICE_FUNC
     RealScalar operatorNorm() const;
-    
-    #ifdef EIGEN2_SUPPORT
-    template<typename OtherDerived>
-    SelfAdjointView& operator=(const MatrixBase<OtherDerived>& other)
-    {
-      enum {
-        OtherPart = UpLo == Upper ? StrictlyLower : StrictlyUpper
-      };
-      m_matrix.const_cast_derived().template triangularView<UpLo>() = other;
-      m_matrix.const_cast_derived().template triangularView<OtherPart>() = other.adjoint();
-      return *this;
-    }
-    template<typename OtherMatrixType, unsigned int OtherMode>
-    SelfAdjointView& operator=(const TriangularView<OtherMatrixType, OtherMode>& other)
-    {
-      enum {
-        OtherPart = UpLo == Upper ? StrictlyLower : StrictlyUpper
-      };
-      m_matrix.const_cast_derived().template triangularView<UpLo>() = other.toDenseMatrix();
-      m_matrix.const_cast_derived().template triangularView<OtherPart>() = other.toDenseMatrix().adjoint();
-      return *this;
-    }
-    #endif
 
   protected:
     MatrixTypeNested m_matrix;
 };
 
@@ -199,116 +261,90 @@
 
 // selfadjoint to dense matrix
 
 namespace internal {
 
-template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), UnrollCount, ClearOpposite>
-{
-  enum {
-    col = (UnrollCount-1) / Derived1::RowsAtCompileTime,
-    row = (UnrollCount-1) % Derived1::RowsAtCompileTime
-  };
-
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), UnrollCount-1, ClearOpposite>::run(dst, src);
-
-    if(row == col)
-      dst.coeffRef(row, col) = numext::real(src.coeff(row, col));
-    else if(row < col)
-      dst.coeffRef(col, row) = numext::conj(dst.coeffRef(row, col) = src.coeff(row, col));
-  }
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, 0, ClearOpposite>
-{
-  static inline void run(Derived1 &, const Derived2 &) {}
-};
-
-template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), UnrollCount, ClearOpposite>
-{
-  enum {
-    col = (UnrollCount-1) / Derived1::RowsAtCompileTime,
-    row = (UnrollCount-1) % Derived1::RowsAtCompileTime
-  };
-
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), UnrollCount-1, ClearOpposite>::run(dst, src);
-
-    if(row == col)
-      dst.coeffRef(row, col) = numext::real(src.coeff(row, col));
-    else if(row > col)
-      dst.coeffRef(col, row) = numext::conj(dst.coeffRef(row, col) = src.coeff(row, col));
-  }
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Lower, 0, ClearOpposite>
-{
-  static inline void run(Derived1 &, const Derived2 &) {}
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, Dynamic, ClearOpposite>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    for(Index j = 0; j < dst.cols(); ++j)
-    {
-      for(Index i = 0; i < j; ++i)
-      {
-        dst.copyCoeff(i, j, src);
-        dst.coeffRef(j,i) = numext::conj(dst.coeff(i,j));
-      }
-      dst.copyCoeff(j, j, src);
-    }
-  }
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Lower, Dynamic, ClearOpposite>
-{
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-  typedef typename Derived1::Index Index;
-    for(Index i = 0; i < dst.rows(); ++i)
-    {
-      for(Index j = 0; j < i; ++j)
-      {
-        dst.copyCoeff(i, j, src);
-        dst.coeffRef(j,i) = numext::conj(dst.coeff(i,j));
-      }
-      dst.copyCoeff(i, i, src);
-    }
-  }
+// TODO currently a selfadjoint expression has the form SelfAdjointView<.,.>
+//      in the future selfadjoint-ness should be defined by the expression traits
+//      such that Transpose<SelfAdjointView<.,.> > is valid. (currently TriangularBase::transpose() is overloaded to make it work)
+template<typename MatrixType, unsigned int Mode>
+struct evaluator_traits<SelfAdjointView<MatrixType,Mode> >
+{
+  typedef typename storage_kind_to_evaluator_kind<typename MatrixType::StorageKind>::Kind Kind;
+  typedef SelfAdjointShape Shape;
+};
+
+template<int UpLo, int SetOpposite, typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version>
+class triangular_dense_assignment_kernel<UpLo,SelfAdjoint,SetOpposite,DstEvaluatorTypeT,SrcEvaluatorTypeT,Functor,Version>
+  : public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>
+{
+protected:
+  typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version> Base;
+  typedef typename Base::DstXprType DstXprType;
+  typedef typename Base::SrcXprType SrcXprType;
+  using Base::m_dst;
+  using Base::m_src;
+  using Base::m_functor;
+public:
+  
+  typedef typename Base::DstEvaluatorType DstEvaluatorType;
+  typedef typename Base::SrcEvaluatorType SrcEvaluatorType;
+  typedef typename Base::Scalar Scalar;
+  typedef typename Base::AssignmentTraits AssignmentTraits;
+  
+  
+  EIGEN_DEVICE_FUNC triangular_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
+    : Base(dst, src, func, dstExpr)
+  {}
+  
+  EIGEN_DEVICE_FUNC void assignCoeff(Index row, Index col)
+  {
+    eigen_internal_assert(row!=col);
+    Scalar tmp = m_src.coeff(row,col);
+    m_functor.assignCoeff(m_dst.coeffRef(row,col), tmp);
+    m_functor.assignCoeff(m_dst.coeffRef(col,row), numext::conj(tmp));
+  }
+  
+  EIGEN_DEVICE_FUNC void assignDiagonalCoeff(Index id)
+  {
+    Base::assignCoeff(id,id);
+  }
+  
+  EIGEN_DEVICE_FUNC void assignOppositeCoeff(Index, Index)
+  { eigen_internal_assert(false && "should never be called"); }
 };
 
 } // end namespace internal
 
 /***************************************************************************
 * Implementation of MatrixBase methods
 ***************************************************************************/
 
+/** This is the const version of MatrixBase::selfadjointView() */
 template<typename Derived>
 template<unsigned int UpLo>
 typename MatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type
 MatrixBase<Derived>::selfadjointView() const
 {
-  return derived();
+  return typename ConstSelfAdjointViewReturnType<UpLo>::Type(derived());
 }
 
+/** \returns an expression of a symmetric/self-adjoint view extracted from the upper or lower triangular part of the current matrix
+  *
+  * The parameter \a UpLo can be either \c #Upper or \c #Lower
+  *
+  * Example: \include MatrixBase_selfadjointView.cpp
+  * Output: \verbinclude MatrixBase_selfadjointView.out
+  *
+  * \sa class SelfAdjointView
+  */
 template<typename Derived>
 template<unsigned int UpLo>
 typename MatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type
 MatrixBase<Derived>::selfadjointView()
 {
-  return derived();
+  return typename SelfAdjointViewReturnType<UpLo>::Type(derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SELFADJOINTMATRIX_H

Index: 3rd_party/eigen/Eigen/src/Core/SelfCwiseBinaryOp.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/SelfCwiseBinaryOp.h
+++ 3rd_party/eigen/Eigen/src/Core/SelfCwiseBinaryOp.h
@@ -10,188 +10,42 @@
 #ifndef EIGEN_SELFCWISEBINARYOP_H
 #define EIGEN_SELFCWISEBINARYOP_H
 
 namespace Eigen { 
 
-/** \class SelfCwiseBinaryOp
-  * \ingroup Core_Module
-  *
-  * \internal
-  *
-  * \brief Internal helper class for optimizing operators like +=, -=
-  *
-  * This is a pseudo expression class re-implementing the copyCoeff/copyPacket
-  * method to directly performs a +=/-= operations in an optimal way. In particular,
-  * this allows to make sure that the input/output data are loaded only once using
-  * aligned packet loads.
-  *
-  * \sa class SwapWrapper for a similar trick.
-  */
-
-namespace internal {
-template<typename BinaryOp, typename Lhs, typename Rhs>
-struct traits<SelfCwiseBinaryOp<BinaryOp,Lhs,Rhs> >
-  : traits<CwiseBinaryOp<BinaryOp,Lhs,Rhs> >
-{
-  enum {
-    // Note that it is still a good idea to preserve the DirectAccessBit
-    // so that assign can correctly align the data.
-    Flags = traits<CwiseBinaryOp<BinaryOp,Lhs,Rhs> >::Flags | (Lhs::Flags&DirectAccessBit) | (Lhs::Flags&LvalueBit),
-    OuterStrideAtCompileTime = Lhs::OuterStrideAtCompileTime,
-    InnerStrideAtCompileTime = Lhs::InnerStrideAtCompileTime
-  };
-};
-}
-
-template<typename BinaryOp, typename Lhs, typename Rhs> class SelfCwiseBinaryOp
-  : public internal::dense_xpr_base< SelfCwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
-{
-  public:
-
-    typedef typename internal::dense_xpr_base<SelfCwiseBinaryOp>::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(SelfCwiseBinaryOp)
-
-    typedef typename internal::packet_traits<Scalar>::type Packet;
-
-    inline SelfCwiseBinaryOp(Lhs& xpr, const BinaryOp& func = BinaryOp()) : m_matrix(xpr), m_functor(func) {}
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-    inline Index outerStride() const { return m_matrix.outerStride(); }
-    inline Index innerStride() const { return m_matrix.innerStride(); }
-    inline const Scalar* data() const { return m_matrix.data(); }
-
-    // note that this function is needed by assign to correctly align loads/stores
-    // TODO make Assign use .data()
-    inline Scalar& coeffRef(Index row, Index col)
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(Lhs)
-      return m_matrix.const_cast_derived().coeffRef(row, col);
-    }
-    inline const Scalar& coeffRef(Index row, Index col) const
-    {
-      return m_matrix.coeffRef(row, col);
-    }
-
-    // note that this function is needed by assign to correctly align loads/stores
-    // TODO make Assign use .data()
-    inline Scalar& coeffRef(Index index)
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(Lhs)
-      return m_matrix.const_cast_derived().coeffRef(index);
-    }
-    inline const Scalar& coeffRef(Index index) const
-    {
-      return m_matrix.const_cast_derived().coeffRef(index);
-    }
-
-    template<typename OtherDerived>
-    void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
-    {
-      OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(row >= 0 && row < rows()
-                         && col >= 0 && col < cols());
-      Scalar& tmp = m_matrix.coeffRef(row,col);
-      tmp = m_functor(tmp, _other.coeff(row,col));
-    }
-
-    template<typename OtherDerived>
-    void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
-    {
-      OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(index >= 0 && index < m_matrix.size());
-      Scalar& tmp = m_matrix.coeffRef(index);
-      tmp = m_functor(tmp, _other.coeff(index));
-    }
-
-    template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
-    {
-      OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(row >= 0 && row < rows()
-                        && col >= 0 && col < cols());
-      m_matrix.template writePacket<StoreMode>(row, col,
-        m_functor.packetOp(m_matrix.template packet<StoreMode>(row, col),_other.template packet<LoadMode>(row, col)) );
-    }
-
-    template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(Index index, const DenseBase<OtherDerived>& other)
-    {
-      OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(index >= 0 && index < m_matrix.size());
-      m_matrix.template writePacket<StoreMode>(index,
-        m_functor.packetOp(m_matrix.template packet<StoreMode>(index),_other.template packet<LoadMode>(index)) );
-    }
-
-    // reimplement lazyAssign to handle complex *= real
-    // see CwiseBinaryOp ctor for details
-    template<typename RhsDerived>
-    EIGEN_STRONG_INLINE SelfCwiseBinaryOp& lazyAssign(const DenseBase<RhsDerived>& rhs)
-    {
-      EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs,RhsDerived)
-      EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename RhsDerived::Scalar);
-      
-    #ifdef EIGEN_DEBUG_ASSIGN
-      internal::assign_traits<SelfCwiseBinaryOp, RhsDerived>::debug();
-    #endif
-      eigen_assert(rows() == rhs.rows() && cols() == rhs.cols());
-      internal::assign_impl<SelfCwiseBinaryOp, RhsDerived>::run(*this,rhs.derived());
-    #ifndef EIGEN_NO_DEBUG
-      this->checkTransposeAliasing(rhs.derived());
-    #endif
-      return *this;
-    }
-    
-    // overloaded to honor evaluation of special matrices
-    // maybe another solution would be to not use SelfCwiseBinaryOp
-    // at first...
-    SelfCwiseBinaryOp& operator=(const Rhs& _rhs)
-    {
-      typename internal::nested<Rhs>::type rhs(_rhs);
-      return Base::operator=(rhs);
-    }
-
-    Lhs& expression() const 
-    { 
-      return m_matrix;
-    }
-
-    const BinaryOp& functor() const 
-    { 
-      return m_functor;
-    }
-
-  protected:
-    Lhs& m_matrix;
-    const BinaryOp& m_functor;
-
-  private:
-    SelfCwiseBinaryOp& operator=(const SelfCwiseBinaryOp&);
-};
-
-template<typename Derived>
-inline Derived& DenseBase<Derived>::operator*=(const Scalar& other)
-{
-  typedef typename Derived::PlainObject PlainObject;
-  SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
-  tmp = PlainObject::Constant(rows(),cols(),other);
+// TODO generalize the scalar type of 'other'
+
+template<typename Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator*=(const Scalar& other)
+{
+  typedef typename Derived::PlainObject PlainObject;
+  internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::mul_assign_op<Scalar,Scalar>());
+  return derived();
+}
+
+template<typename Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator+=(const Scalar& other)
+{
+  typedef typename Derived::PlainObject PlainObject;
+  internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar,Scalar>());
+  return derived();
+}
+
+template<typename Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator-=(const Scalar& other)
+{
+  typedef typename Derived::PlainObject PlainObject;
+  internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::sub_assign_op<Scalar,Scalar>());
   return derived();
 }
 
 template<typename Derived>
-inline Derived& DenseBase<Derived>::operator/=(const Scalar& other)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator/=(const Scalar& other)
 {
-  typedef typename internal::conditional<NumTraits<Scalar>::IsInteger,
-                                        internal::scalar_quotient_op<Scalar>,
-                                        internal::scalar_product_op<Scalar> >::type BinOp;
   typedef typename Derived::PlainObject PlainObject;
-  SelfCwiseBinaryOp<BinOp, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
-  Scalar actual_other;
-  if(NumTraits<Scalar>::IsInteger)  actual_other = other;
-  else                              actual_other = Scalar(1)/other;
-  tmp = PlainObject::Constant(rows(),cols(), actual_other);
+  internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>());
   return derived();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SELFCWISEBINARYOP_H

ADDED   3rd_party/eigen/Eigen/src/Core/Solve.h
Index: 3rd_party/eigen/Eigen/src/Core/Solve.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Solve.h
+++ 3rd_party/eigen/Eigen/src/Core/Solve.h
@@ -0,0 +1,188 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SOLVE_H
+#define EIGEN_SOLVE_H
+
+namespace Eigen {
+
+template<typename Decomposition, typename RhsType, typename StorageKind> class SolveImpl;
+  
+/** \class Solve
+  * \ingroup Core_Module
+  *
+  * \brief Pseudo expression representing a solving operation
+  *
+  * \tparam Decomposition the type of the matrix or decomposion object
+  * \tparam Rhstype the type of the right-hand side
+  *
+  * This class represents an expression of A.solve(B)
+  * and most of the time this is the only way it is used.
+  *
+  */
+namespace internal {
+
+// this solve_traits class permits to determine the evaluation type with respect to storage kind (Dense vs Sparse)
+template<typename Decomposition, typename RhsType,typename StorageKind> struct solve_traits;
+
+template<typename Decomposition, typename RhsType>
+struct solve_traits<Decomposition,RhsType,Dense>
+{
+  typedef typename make_proper_matrix_type<typename RhsType::Scalar,
+                 Decomposition::ColsAtCompileTime,
+                 RhsType::ColsAtCompileTime,
+                 RhsType::PlainObject::Options,
+                 Decomposition::MaxColsAtCompileTime,
+                 RhsType::MaxColsAtCompileTime>::type PlainObject;
+};
+
+template<typename Decomposition, typename RhsType>
+struct traits<Solve<Decomposition, RhsType> >
+  : traits<typename solve_traits<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>::PlainObject>
+{
+  typedef typename solve_traits<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>::PlainObject PlainObject;
+  typedef typename promote_index_type<typename Decomposition::StorageIndex, typename RhsType::StorageIndex>::type StorageIndex;
+  typedef traits<PlainObject> BaseTraits;
+  enum {
+    Flags = BaseTraits::Flags & RowMajorBit,
+    CoeffReadCost = HugeCost
+  };
+};
+
+}
+
+
+template<typename Decomposition, typename RhsType>
+class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
+{
+public:
+  typedef typename internal::traits<Solve>::PlainObject PlainObject;
+  typedef typename internal::traits<Solve>::StorageIndex StorageIndex;
+  
+  Solve(const Decomposition &dec, const RhsType &rhs)
+    : m_dec(dec), m_rhs(rhs)
+  {}
+  
+  EIGEN_DEVICE_FUNC Index rows() const { return m_dec.cols(); }
+  EIGEN_DEVICE_FUNC Index cols() const { return m_rhs.cols(); }
+
+  EIGEN_DEVICE_FUNC const Decomposition& dec() const { return m_dec; }
+  EIGEN_DEVICE_FUNC const RhsType&       rhs() const { return m_rhs; }
+
+protected:
+  const Decomposition &m_dec;
+  const RhsType       &m_rhs;
+};
+
+
+// Specialization of the Solve expression for dense results
+template<typename Decomposition, typename RhsType>
+class SolveImpl<Decomposition,RhsType,Dense>
+  : public MatrixBase<Solve<Decomposition,RhsType> >
+{
+  typedef Solve<Decomposition,RhsType> Derived;
+  
+public:
+  
+  typedef MatrixBase<Solve<Decomposition,RhsType> > Base;
+  EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+
+private:
+  
+  Scalar coeff(Index row, Index col) const;
+  Scalar coeff(Index i) const;
+};
+
+// Generic API dispatcher
+template<typename Decomposition, typename RhsType, typename StorageKind>
+class SolveImpl : public internal::generic_xpr_base<Solve<Decomposition,RhsType>, MatrixXpr, StorageKind>::type
+{
+  public:
+    typedef typename internal::generic_xpr_base<Solve<Decomposition,RhsType>, MatrixXpr, StorageKind>::type Base;
+};
+
+namespace internal {
+
+// Evaluator of Solve -> eval into a temporary
+template<typename Decomposition, typename RhsType>
+struct evaluator<Solve<Decomposition,RhsType> >
+  : public evaluator<typename Solve<Decomposition,RhsType>::PlainObject>
+{
+  typedef Solve<Decomposition,RhsType> SolveType;
+  typedef typename SolveType::PlainObject PlainObject;
+  typedef evaluator<PlainObject> Base;
+
+  enum { Flags = Base::Flags | EvalBeforeNestingBit };
+  
+  EIGEN_DEVICE_FUNC explicit evaluator(const SolveType& solve)
+    : m_result(solve.rows(), solve.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    solve.dec()._solve_impl(solve.rhs(), m_result);
+  }
+  
+protected:  
+  PlainObject m_result;
+};
+
+// Specialization for "dst = dec.solve(rhs)"
+// NOTE we need to specialize it for Dense2Dense to avoid ambiguous specialization error and a Sparse2Sparse specialization must exist somewhere
+template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
+struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar,Scalar>, Dense2Dense>
+{
+  typedef Solve<DecType,RhsType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    src.dec()._solve_impl(src.rhs(), dst);
+  }
+};
+
+// Specialization for "dst = dec.transpose().solve(rhs)"
+template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
+struct Assignment<DstXprType, Solve<Transpose<const DecType>,RhsType>, internal::assign_op<Scalar,Scalar>, Dense2Dense>
+{
+  typedef Solve<Transpose<const DecType>,RhsType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    src.dec().nestedExpression().template _solve_impl_transposed<false>(src.rhs(), dst);
+  }
+};
+
+// Specialization for "dst = dec.adjoint().solve(rhs)"
+template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
+struct Assignment<DstXprType, Solve<CwiseUnaryOp<internal::scalar_conjugate_op<typename DecType::Scalar>, const Transpose<const DecType> >,RhsType>,
+                  internal::assign_op<Scalar,Scalar>, Dense2Dense>
+{
+  typedef Solve<CwiseUnaryOp<internal::scalar_conjugate_op<typename DecType::Scalar>, const Transpose<const DecType> >,RhsType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+    
+    src.dec().nestedExpression().nestedExpression().template _solve_impl_transposed<true>(src.rhs(), dst);
+  }
+};
+
+} // end namepsace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SOLVE_H

Index: 3rd_party/eigen/Eigen/src/Core/SolveTriangular.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/SolveTriangular.h
+++ 3rd_party/eigen/Eigen/src/Core/SolveTriangular.h
@@ -66,11 +66,11 @@
                                                   (useRhsDirectly ? rhs.data() : 0));
                                                   
     if(!useRhsDirectly)
       MappedRhs(actualRhs,rhs.size()) = rhs;
 
-    triangular_solve_vector<LhsScalar, RhsScalar, typename Lhs::Index, Side, Mode, LhsProductTraits::NeedToConjugate,
+    triangular_solve_vector<LhsScalar, RhsScalar, Index, Side, Mode, LhsProductTraits::NeedToConjugate,
                             (int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor>
       ::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs);
 
     if(!useRhsDirectly)
       rhs = MappedRhs(actualRhs, rhs.size());
@@ -80,11 +80,10 @@
 // the rhs is a matrix
 template<typename Lhs, typename Rhs, int Side, int Mode>
 struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,Dynamic>
 {
   typedef typename Rhs::Scalar Scalar;
-  typedef typename Rhs::Index Index;
   typedef blas_traits<Lhs> LhsProductTraits;
   typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType;
 
   static void run(const Lhs& lhs, Rhs& rhs)
   {
@@ -94,11 +93,11 @@
     const Index othersize = Side==OnTheLeft? rhs.cols() : rhs.rows();
 
     typedef internal::gemm_blocking_space<(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
               Rhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxRowsAtCompileTime,4> BlockingType;
 
-    BlockingType blocking(rhs.rows(), rhs.cols(), size);
+    BlockingType blocking(rhs.rows(), rhs.cols(), size, 1, false);
 
     triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
                                (Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor>
       ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.outerStride(), blocking);
   }
@@ -106,36 +105,36 @@
 
 /***************************************************************************
 * meta-unrolling implementation
 ***************************************************************************/
 
-template<typename Lhs, typename Rhs, int Mode, int Index, int Size,
-         bool Stop = Index==Size>
+template<typename Lhs, typename Rhs, int Mode, int LoopIndex, int Size,
+         bool Stop = LoopIndex==Size>
 struct triangular_solver_unroller;
 
-template<typename Lhs, typename Rhs, int Mode, int Index, int Size>
-struct triangular_solver_unroller<Lhs,Rhs,Mode,Index,Size,false> {
+template<typename Lhs, typename Rhs, int Mode, int LoopIndex, int Size>
+struct triangular_solver_unroller<Lhs,Rhs,Mode,LoopIndex,Size,false> {
   enum {
     IsLower = ((Mode&Lower)==Lower),
-    I = IsLower ? Index : Size - Index - 1,
-    S = IsLower ? 0     : I+1
+    DiagIndex  = IsLower ? LoopIndex : Size - LoopIndex - 1,
+    StartIndex = IsLower ? 0         : DiagIndex+1
   };
   static void run(const Lhs& lhs, Rhs& rhs)
   {
-    if (Index>0)
-      rhs.coeffRef(I) -= lhs.row(I).template segment<Index>(S).transpose()
-                         .cwiseProduct(rhs.template segment<Index>(S)).sum();
+    if (LoopIndex>0)
+      rhs.coeffRef(DiagIndex) -= lhs.row(DiagIndex).template segment<LoopIndex>(StartIndex).transpose()
+                                .cwiseProduct(rhs.template segment<LoopIndex>(StartIndex)).sum();
 
     if(!(Mode & UnitDiag))
-      rhs.coeffRef(I) /= lhs.coeff(I,I);
+      rhs.coeffRef(DiagIndex) /= lhs.coeff(DiagIndex,DiagIndex);
 
-    triangular_solver_unroller<Lhs,Rhs,Mode,Index+1,Size>::run(lhs,rhs);
+    triangular_solver_unroller<Lhs,Rhs,Mode,LoopIndex+1,Size>::run(lhs,rhs);
   }
 };
 
-template<typename Lhs, typename Rhs, int Mode, int Index, int Size>
-struct triangular_solver_unroller<Lhs,Rhs,Mode,Index,Size,true> {
+template<typename Lhs, typename Rhs, int Mode, int LoopIndex, int Size>
+struct triangular_solver_unroller<Lhs,Rhs,Mode,LoopIndex,Size,true> {
   static void run(const Lhs&, Rhs&) {}
 };
 
 template<typename Lhs, typename Rhs, int Mode>
 struct triangular_solver_selector<Lhs,Rhs,OnTheLeft,Mode,CompleteUnrolling,1> {
@@ -160,65 +159,39 @@
 
 /***************************************************************************
 * TriangularView methods
 ***************************************************************************/
 
-/** "in-place" version of TriangularView::solve() where the result is written in \a other
-  *
-  * \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
-  * This function will const_cast it, so constness isn't honored here.
-  *
-  * See TriangularView:solve() for the details.
-  */
+#ifndef EIGEN_PARSED_BY_DOXYGEN
 template<typename MatrixType, unsigned int Mode>
 template<int Side, typename OtherDerived>
-void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
+void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
 {
   OtherDerived& other = _other.const_cast_derived();
-  eigen_assert( cols() == rows() && ((Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols())) );
+  eigen_assert( derived().cols() == derived().rows() && ((Side==OnTheLeft && derived().cols() == other.rows()) || (Side==OnTheRight && derived().cols() == other.cols())) );
   eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
 
-  enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit  && OtherDerived::IsVectorAtCompileTime };
+  enum { copy = (internal::traits<OtherDerived>::Flags & RowMajorBit)  && OtherDerived::IsVectorAtCompileTime && OtherDerived::SizeAtCompileTime!=1};
   typedef typename internal::conditional<copy,
     typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::type OtherCopy;
   OtherCopy otherCopy(other);
 
   internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::type,
-    Side, Mode>::run(nestedExpression(), otherCopy);
+    Side, Mode>::run(derived().nestedExpression(), otherCopy);
 
   if (copy)
     other = otherCopy;
 }
 
-/** \returns the product of the inverse of \c *this with \a other, \a *this being triangular.
-  *
-  * This function computes the inverse-matrix matrix product inverse(\c *this) * \a other if
-  * \a Side==OnTheLeft (the default), or the right-inverse-multiply  \a other * inverse(\c *this) if
-  * \a Side==OnTheRight.
-  *
-  * The matrix \c *this must be triangular and invertible (i.e., all the coefficients of the
-  * diagonal must be non zero). It works as a forward (resp. backward) substitution if \c *this
-  * is an upper (resp. lower) triangular matrix.
-  *
-  * Example: \include MatrixBase_marked.cpp
-  * Output: \verbinclude MatrixBase_marked.out
-  *
-  * This function returns an expression of the inverse-multiply and can works in-place if it is assigned
-  * to the same matrix or vector \a other.
-  *
-  * For users coming from BLAS, this function (and more specifically solveInPlace()) offer
-  * all the operations supported by the \c *TRSV and \c *TRSM BLAS routines.
-  *
-  * \sa TriangularView::solveInPlace()
-  */
 template<typename Derived, unsigned int Mode>
 template<int Side, typename Other>
 const internal::triangular_solve_retval<Side,TriangularView<Derived,Mode>,Other>
-TriangularView<Derived,Mode>::solve(const MatrixBase<Other>& other) const
+TriangularViewImpl<Derived,Mode,Dense>::solve(const MatrixBase<Other>& other) const
 {
-  return internal::triangular_solve_retval<Side,TriangularView,Other>(*this, other.derived());
+  return internal::triangular_solve_retval<Side,TriangularViewType,Other>(derived(), other.derived());
 }
+#endif
 
 namespace internal {
 
 
 template<int Side, typename TriangularType, typename Rhs>
@@ -230,11 +203,10 @@
 template<int Side, typename TriangularType, typename Rhs> struct triangular_solve_retval
  : public ReturnByValue<triangular_solve_retval<Side, TriangularType, Rhs> >
 {
   typedef typename remove_all<typename Rhs::Nested>::type RhsNestedCleaned;
   typedef ReturnByValue<triangular_solve_retval> Base;
-  typedef typename Base::Index Index;
 
   triangular_solve_retval(const TriangularType& tri, const Rhs& rhs)
     : m_triangularMatrix(tri), m_rhs(rhs)
   {}
 
@@ -241,11 +213,11 @@
   inline Index rows() const { return m_rhs.rows(); }
   inline Index cols() const { return m_rhs.cols(); }
 
   template<typename Dest> inline void evalTo(Dest& dst) const
   {
-    if(!(is_same<RhsNestedCleaned,Dest>::value && extract_data(dst) == extract_data(m_rhs)))
+    if(!is_same_dense(dst,m_rhs))
       dst = m_rhs;
     m_triangularMatrix.template solveInPlace<Side>(dst);
   }
 
   protected:

ADDED   3rd_party/eigen/Eigen/src/Core/SolverBase.h
Index: 3rd_party/eigen/Eigen/src/Core/SolverBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/SolverBase.h
+++ 3rd_party/eigen/Eigen/src/Core/SolverBase.h
@@ -0,0 +1,130 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SOLVERBASE_H
+#define EIGEN_SOLVERBASE_H
+
+namespace Eigen {
+
+namespace internal {
+
+
+
+} // end namespace internal
+
+/** \class SolverBase
+  * \brief A base class for matrix decomposition and solvers
+  *
+  * \tparam Derived the actual type of the decomposition/solver.
+  *
+  * Any matrix decomposition inheriting this base class provide the following API:
+  *
+  * \code
+  * MatrixType A, b, x;
+  * DecompositionType dec(A);
+  * x = dec.solve(b);             // solve A   * x = b
+  * x = dec.transpose().solve(b); // solve A^T * x = b
+  * x = dec.adjoint().solve(b);   // solve A'  * x = b
+  * \endcode
+  *
+  * \warning Currently, any other usage of transpose() and adjoint() are not supported and will produce compilation errors.
+  *
+  * \sa class PartialPivLU, class FullPivLU
+  */
+template<typename Derived>
+class SolverBase : public EigenBase<Derived>
+{
+  public:
+
+    typedef EigenBase<Derived> Base;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef Scalar CoeffReturnType;
+
+    enum {
+      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
+      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
+      SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
+                                                          internal::traits<Derived>::ColsAtCompileTime>::ret),
+      MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
+      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
+      MaxSizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::MaxRowsAtCompileTime,
+                                                             internal::traits<Derived>::MaxColsAtCompileTime>::ret),
+      IsVectorAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime == 1
+                           || internal::traits<Derived>::MaxColsAtCompileTime == 1
+    };
+
+    /** Default constructor */
+    SolverBase()
+    {}
+
+    ~SolverBase()
+    {}
+
+    using Base::derived;
+
+    /** \returns an expression of the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      */
+    template<typename Rhs>
+    inline const Solve<Derived, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(derived().rows()==b.rows() && "solve(): invalid number of rows of the right hand side matrix b");
+      return Solve<Derived, Rhs>(derived(), b.derived());
+    }
+
+    /** \internal the return type of transpose() */
+    typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
+    /** \returns an expression of the transposed of the factored matrix.
+      *
+      * A typical usage is to solve for the transposed problem A^T x = b:
+      * \code x = dec.transpose().solve(b); \endcode
+      *
+      * \sa adjoint(), solve()
+      */
+    inline ConstTransposeReturnType transpose() const
+    {
+      return ConstTransposeReturnType(derived());
+    }
+
+    /** \internal the return type of adjoint() */
+    typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
+                        CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, ConstTransposeReturnType>,
+                        ConstTransposeReturnType
+                     >::type AdjointReturnType;
+    /** \returns an expression of the adjoint of the factored matrix
+      *
+      * A typical usage is to solve for the adjoint problem A' x = b:
+      * \code x = dec.adjoint().solve(b); \endcode
+      *
+      * For real scalar types, this function is equivalent to transpose().
+      *
+      * \sa transpose(), solve()
+      */
+    inline AdjointReturnType adjoint() const
+    {
+      return AdjointReturnType(derived().transpose());
+    }
+
+  protected:
+};
+
+namespace internal {
+
+template<typename Derived>
+struct generic_xpr_base<Derived, MatrixXpr, SolverStorage>
+{
+  typedef SolverBase<Derived> type;
+
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SOLVERBASE_H

Index: 3rd_party/eigen/Eigen/src/Core/StableNorm.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/StableNorm.h
+++ 3rd_party/eigen/Eigen/src/Core/StableNorm.h
@@ -15,27 +15,35 @@
 namespace internal {
 
 template<typename ExpressionType, typename Scalar>
 inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& scale, Scalar& invScale)
 {
-  using std::max;
   Scalar maxCoeff = bl.cwiseAbs().maxCoeff();
   
-  if (maxCoeff>scale)
+  if(maxCoeff>scale)
   {
     ssq = ssq * numext::abs2(scale/maxCoeff);
     Scalar tmp = Scalar(1)/maxCoeff;
     if(tmp > NumTraits<Scalar>::highest())
     {
       invScale = NumTraits<Scalar>::highest();
       scale = Scalar(1)/invScale;
     }
+    else if(maxCoeff>NumTraits<Scalar>::highest()) // we got a INF
+    {
+      invScale = Scalar(1);
+      scale = maxCoeff;
+    }
     else
     {
       scale = maxCoeff;
       invScale = tmp;
     }
+  }
+  else if(maxCoeff!=maxCoeff) // we got a NaN
+  {
+    scale = maxCoeff;
   }
   
   // TODO if the maxCoeff is much much smaller than the current scale,
   // then we can neglect this sub vector
   if(scale>Scalar(0)) // if scale==0, then bl is 0 
@@ -45,19 +53,16 @@
 template<typename Derived>
 inline typename NumTraits<typename traits<Derived>::Scalar>::Real
 blueNorm_impl(const EigenBase<Derived>& _vec)
 {
   typedef typename Derived::RealScalar RealScalar;  
-  typedef typename Derived::Index Index;
   using std::pow;
-  using std::min;
-  using std::max;
   using std::sqrt;
   using std::abs;
   const Derived& vec(_vec.derived());
   static bool initialized = false;
-  static RealScalar b1, b2, s1m, s2m, overfl, rbig, relerr;
+  static RealScalar b1, b2, s1m, s2m, rbig, relerr;
   if(!initialized)
   {
     int ibeta, it, iemin, iemax, iexp;
     RealScalar eps;
     // This program calculates the machine-dependent constants
@@ -82,11 +87,10 @@
     iexp  = (2-iemin)/2;
     s1m   = RealScalar(pow(RealScalar(ibeta),RealScalar(iexp)));    // scaling factor for lower range
     iexp  = - ((iemax+it)/2);
     s2m   = RealScalar(pow(RealScalar(ibeta),RealScalar(iexp)));    // scaling factor for upper range
 
-    overfl  = rbig*s2m;                                             // overflow boundary for abig
     eps     = RealScalar(pow(double(ibeta), 1-it));
     relerr  = sqrt(eps);                                            // tolerance for neglecting asml
     initialized = true;
   }
   Index n = vec.size();
@@ -99,17 +103,17 @@
     RealScalar ax = abs(it.value());
     if(ax > ab2)     abig += numext::abs2(ax*s2m);
     else if(ax < b1) asml += numext::abs2(ax*s1m);
     else             amed += numext::abs2(ax);
   }
+  if(amed!=amed)
+    return amed;  // we got a NaN
   if(abig > RealScalar(0))
   {
     abig = sqrt(abig);
-    if(abig > overfl)
-    {
-      return rbig;
-    }
+    if(abig > rbig) // overflow, or *this contains INF values
+      return abig;  // return INF
     if(amed > RealScalar(0))
     {
       abig = abig/s2m;
       amed = sqrt(amed);
     }
@@ -126,12 +130,12 @@
     else
       return sqrt(asml)/s1m;
   }
   else
     return sqrt(amed);
-  asml = (min)(abig, amed);
-  abig = (max)(abig, amed);
+  asml = numext::mini(abig, amed);
+  abig = numext::maxi(abig, amed);
   if(asml <= abig*relerr)
     return abig;
   else
     return abig * sqrt(RealScalar(1) + numext::abs2(asml/abig));
 }
@@ -150,25 +154,39 @@
   */
 template<typename Derived>
 inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
 MatrixBase<Derived>::stableNorm() const
 {
-  using std::min;
   using std::sqrt;
+  using std::abs;
   const Index blockSize = 4096;
   RealScalar scale(0);
   RealScalar invScale(1);
   RealScalar ssq(0); // sum of square
+  
+  typedef typename internal::nested_eval<Derived,2>::type DerivedCopy;
+  typedef typename internal::remove_all<DerivedCopy>::type DerivedCopyClean;
+  DerivedCopy copy(derived());
+  
   enum {
-    Alignment = (int(Flags)&DirectAccessBit) || (int(Flags)&AlignedBit) ? 1 : 0
+    CanAlign = (   (int(DerivedCopyClean::Flags)&DirectAccessBit)
+                || (int(internal::evaluator<DerivedCopyClean>::Alignment)>0) // FIXME Alignment)>0 might not be enough
+               ) && (blockSize*sizeof(Scalar)*2<EIGEN_STACK_ALLOCATION_LIMIT)
+                 && (EIGEN_MAX_STATIC_ALIGN_BYTES>0) // if we cannot allocate on the stack, then let's not bother about this optimization
   };
+  typedef typename internal::conditional<CanAlign, Ref<const Matrix<Scalar,Dynamic,1,0,blockSize,1>, internal::evaluator<DerivedCopyClean>::Alignment>,
+                                                   typename DerivedCopyClean::ConstSegmentReturnType>::type SegmentWrapper;
   Index n = size();
-  Index bi = internal::first_aligned(derived());
+  
+  if(n==1)
+    return abs(this->coeff(0));
+  
+  Index bi = internal::first_default_aligned(copy);
   if (bi>0)
-    internal::stable_norm_kernel(this->head(bi), ssq, scale, invScale);
+    internal::stable_norm_kernel(copy.head(bi), ssq, scale, invScale);
   for (; bi<n; bi+=blockSize)
-    internal::stable_norm_kernel(this->segment(bi,(min)(blockSize, n - bi)).template forceAlignedAccessIf<Alignment>(), ssq, scale, invScale);
+    internal::stable_norm_kernel(SegmentWrapper(copy.segment(bi,numext::mini(blockSize, n - bi))), ssq, scale, invScale);
   return scale * sqrt(ssq);
 }
 
 /** \returns the \em l2 norm of \c *this using the Blue's algorithm.
   * A Portable Fortran Program to Find the Euclidean Norm of a Vector,

Index: 3rd_party/eigen/Eigen/src/Core/Stride.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Stride.h
+++ 3rd_party/eigen/Eigen/src/Core/Stride.h
@@ -29,12 +29,12 @@
   *
   * These two values can be passed either at compile-time as template parameters, or at runtime as
   * arguments to the constructor.
   *
   * Indeed, this class takes two template parameters:
-  *  \param _OuterStrideAtCompileTime the outer stride, or Dynamic if you want to specify it at runtime.
-  *  \param _InnerStrideAtCompileTime the inner stride, or Dynamic if you want to specify it at runtime.
+  *  \tparam _OuterStrideAtCompileTime the outer stride, or Dynamic if you want to specify it at runtime.
+  *  \tparam _InnerStrideAtCompileTime the inner stride, or Dynamic if you want to specify it at runtime.
   *
   * Here is an example:
   * \include Map_general_stride.cpp
   * Output: \verbinclude Map_general_stride.out
   *
@@ -42,67 +42,70 @@
   */
 template<int _OuterStrideAtCompileTime, int _InnerStrideAtCompileTime>
 class Stride
 {
   public:
-    typedef DenseIndex Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
     enum {
       InnerStrideAtCompileTime = _InnerStrideAtCompileTime,
       OuterStrideAtCompileTime = _OuterStrideAtCompileTime
     };
 
     /** Default constructor, for use when strides are fixed at compile time */
+    EIGEN_DEVICE_FUNC
     Stride()
       : m_outer(OuterStrideAtCompileTime), m_inner(InnerStrideAtCompileTime)
     {
       eigen_assert(InnerStrideAtCompileTime != Dynamic && OuterStrideAtCompileTime != Dynamic);
     }
 
     /** Constructor allowing to pass the strides at runtime */
+    EIGEN_DEVICE_FUNC
     Stride(Index outerStride, Index innerStride)
       : m_outer(outerStride), m_inner(innerStride)
     {
       eigen_assert(innerStride>=0 && outerStride>=0);
     }
 
     /** Copy constructor */
+    EIGEN_DEVICE_FUNC
     Stride(const Stride& other)
       : m_outer(other.outer()), m_inner(other.inner())
     {}
 
     /** \returns the outer stride */
+    EIGEN_DEVICE_FUNC
     inline Index outer() const { return m_outer.value(); }
     /** \returns the inner stride */
+    EIGEN_DEVICE_FUNC
     inline Index inner() const { return m_inner.value(); }
 
   protected:
     internal::variable_if_dynamic<Index, OuterStrideAtCompileTime> m_outer;
     internal::variable_if_dynamic<Index, InnerStrideAtCompileTime> m_inner;
 };
 
 /** \brief Convenience specialization of Stride to specify only an inner stride
   * See class Map for some examples */
-template<int Value = Dynamic>
+template<int Value>
 class InnerStride : public Stride<0, Value>
 {
     typedef Stride<0, Value> Base;
   public:
-    typedef DenseIndex Index;
-    InnerStride() : Base() {}
-    InnerStride(Index v) : Base(0, v) {}
+    EIGEN_DEVICE_FUNC InnerStride() : Base() {}
+    EIGEN_DEVICE_FUNC InnerStride(Index v) : Base(0, v) {} // FIXME making this explicit could break valid code
 };
 
 /** \brief Convenience specialization of Stride to specify only an outer stride
   * See class Map for some examples */
-template<int Value = Dynamic>
+template<int Value>
 class OuterStride : public Stride<Value, 0>
 {
     typedef Stride<Value, 0> Base;
   public:
-    typedef DenseIndex Index;
-    OuterStride() : Base() {}
-    OuterStride(Index v) : Base(v,0) {}
+    EIGEN_DEVICE_FUNC OuterStride() : Base() {}
+    EIGEN_DEVICE_FUNC OuterStride(Index v) : Base(v,0) {} // FIXME making this explicit could break valid code
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_STRIDE_H

Index: 3rd_party/eigen/Eigen/src/Core/Swap.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Swap.h
+++ 3rd_party/eigen/Eigen/src/Core/Swap.h
@@ -10,117 +10,58 @@
 #ifndef EIGEN_SWAP_H
 #define EIGEN_SWAP_H
 
 namespace Eigen { 
 
-/** \class SwapWrapper
-  * \ingroup Core_Module
-  *
-  * \internal
-  *
-  * \brief Internal helper class for swapping two expressions
-  */
-namespace internal {
-template<typename ExpressionType>
-struct traits<SwapWrapper<ExpressionType> > : traits<ExpressionType> {};
-}
-
-template<typename ExpressionType> class SwapWrapper
-  : public internal::dense_xpr_base<SwapWrapper<ExpressionType> >::type
-{
-  public:
-
-    typedef typename internal::dense_xpr_base<SwapWrapper>::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(SwapWrapper)
-    typedef typename internal::packet_traits<Scalar>::type Packet;
-
-    inline SwapWrapper(ExpressionType& xpr) : m_expression(xpr) {}
-
-    inline Index rows() const { return m_expression.rows(); }
-    inline Index cols() const { return m_expression.cols(); }
-    inline Index outerStride() const { return m_expression.outerStride(); }
-    inline Index innerStride() const { return m_expression.innerStride(); }
-    
-    typedef typename internal::conditional<
-                       internal::is_lvalue<ExpressionType>::value,
-                       Scalar,
-                       const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
-                     
-    inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
-    inline const Scalar* data() const { return m_expression.data(); }
-
-    inline Scalar& coeffRef(Index rowId, Index colId)
-    {
-      return m_expression.const_cast_derived().coeffRef(rowId, colId);
-    }
-
-    inline Scalar& coeffRef(Index index)
-    {
-      return m_expression.const_cast_derived().coeffRef(index);
-    }
-
-    inline Scalar& coeffRef(Index rowId, Index colId) const
-    {
-      return m_expression.coeffRef(rowId, colId);
-    }
-
-    inline Scalar& coeffRef(Index index) const
-    {
-      return m_expression.coeffRef(index);
-    }
-
-    template<typename OtherDerived>
-    void copyCoeff(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
-    {
-      OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(rowId >= 0 && rowId < rows()
-                         && colId >= 0 && colId < cols());
-      Scalar tmp = m_expression.coeff(rowId, colId);
-      m_expression.coeffRef(rowId, colId) = _other.coeff(rowId, colId);
-      _other.coeffRef(rowId, colId) = tmp;
-    }
-
-    template<typename OtherDerived>
-    void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
-    {
-      OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(index >= 0 && index < m_expression.size());
-      Scalar tmp = m_expression.coeff(index);
-      m_expression.coeffRef(index) = _other.coeff(index);
-      _other.coeffRef(index) = tmp;
-    }
-
-    template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
-    {
-      OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(rowId >= 0 && rowId < rows()
-                        && colId >= 0 && colId < cols());
-      Packet tmp = m_expression.template packet<StoreMode>(rowId, colId);
-      m_expression.template writePacket<StoreMode>(rowId, colId,
-        _other.template packet<LoadMode>(rowId, colId)
-      );
-      _other.template writePacket<LoadMode>(rowId, colId, tmp);
-    }
-
-    template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(Index index, const DenseBase<OtherDerived>& other)
-    {
-      OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(index >= 0 && index < m_expression.size());
-      Packet tmp = m_expression.template packet<StoreMode>(index);
-      m_expression.template writePacket<StoreMode>(index,
-        _other.template packet<LoadMode>(index)
-      );
-      _other.template writePacket<LoadMode>(index, tmp);
-    }
-
-    ExpressionType& expression() const { return m_expression; }
-
-  protected:
-    ExpressionType& m_expression;
-};
+namespace internal {
+
+// Overload default assignPacket behavior for swapping them
+template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT>
+class generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, Specialized>
+ : public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, BuiltIn>
+{
+protected:
+  typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, BuiltIn> Base;
+  using Base::m_dst;
+  using Base::m_src;
+  using Base::m_functor;
+  
+public:
+  typedef typename Base::Scalar Scalar;
+  typedef typename Base::DstXprType DstXprType;
+  typedef swap_assign_op<Scalar> Functor;
+  
+  EIGEN_DEVICE_FUNC generic_dense_assignment_kernel(DstEvaluatorTypeT &dst, const SrcEvaluatorTypeT &src, const Functor &func, DstXprType& dstExpr)
+    : Base(dst, src, func, dstExpr)
+  {}
+  
+  template<int StoreMode, int LoadMode, typename PacketType>
+  void assignPacket(Index row, Index col)
+  {
+    PacketType tmp = m_src.template packet<LoadMode,PacketType>(row,col);
+    const_cast<SrcEvaluatorTypeT&>(m_src).template writePacket<LoadMode>(row,col, m_dst.template packet<StoreMode,PacketType>(row,col));
+    m_dst.template writePacket<StoreMode>(row,col,tmp);
+  }
+  
+  template<int StoreMode, int LoadMode, typename PacketType>
+  void assignPacket(Index index)
+  {
+    PacketType tmp = m_src.template packet<LoadMode,PacketType>(index);
+    const_cast<SrcEvaluatorTypeT&>(m_src).template writePacket<LoadMode>(index, m_dst.template packet<StoreMode,PacketType>(index));
+    m_dst.template writePacket<StoreMode>(index,tmp);
+  }
+  
+  // TODO find a simple way not to have to copy/paste this function from generic_dense_assignment_kernel, by simple I mean no CRTP (Gael)
+  template<int StoreMode, int LoadMode, typename PacketType>
+  void assignPacketByOuterInner(Index outer, Index inner)
+  {
+    Index row = Base::rowIndexByOuterInner(outer, inner); 
+    Index col = Base::colIndexByOuterInner(outer, inner);
+    assignPacket<StoreMode,LoadMode,PacketType>(row, col);
+  }
+};
+
+} // namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_SWAP_H

Index: 3rd_party/eigen/Eigen/src/Core/Transpose.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Transpose.h
+++ 3rd_party/eigen/Eigen/src/Core/Transpose.h
@@ -1,10 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -11,76 +11,82 @@
 #ifndef EIGEN_TRANSPOSE_H
 #define EIGEN_TRANSPOSE_H
 
 namespace Eigen { 
 
-/** \class Transpose
-  * \ingroup Core_Module
-  *
-  * \brief Expression of the transpose of a matrix
-  *
-  * \param MatrixType the type of the object of which we are taking the transpose
-  *
-  * This class represents an expression of the transpose of a matrix.
-  * It is the return type of MatrixBase::transpose() and MatrixBase::adjoint()
-  * and most of the time this is the only way it is used.
-  *
-  * \sa MatrixBase::transpose(), MatrixBase::adjoint()
-  */
-
 namespace internal {
 template<typename MatrixType>
-struct traits<Transpose<MatrixType> > : traits<MatrixType>
+struct traits<Transpose<MatrixType> > : public traits<MatrixType>
 {
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
   typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain;
-  typedef typename traits<MatrixType>::StorageKind StorageKind;
-  typedef typename traits<MatrixType>::XprKind XprKind;
   enum {
     RowsAtCompileTime = MatrixType::ColsAtCompileTime,
     ColsAtCompileTime = MatrixType::RowsAtCompileTime,
     MaxRowsAtCompileTime = MatrixType::MaxColsAtCompileTime,
     MaxColsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
     FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
-    Flags0 = MatrixTypeNestedPlain::Flags & ~(LvalueBit | NestByRefBit),
+    Flags0 = traits<MatrixTypeNestedPlain>::Flags & ~(LvalueBit | NestByRefBit),
     Flags1 = Flags0 | FlagsLvalueBit,
     Flags = Flags1 ^ RowMajorBit,
-    CoeffReadCost = MatrixTypeNestedPlain::CoeffReadCost,
     InnerStrideAtCompileTime = inner_stride_at_compile_time<MatrixType>::ret,
     OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret
   };
 };
 }
 
 template<typename MatrixType, typename StorageKind> class TransposeImpl;
 
+/** \class Transpose
+  * \ingroup Core_Module
+  *
+  * \brief Expression of the transpose of a matrix
+  *
+  * \tparam MatrixType the type of the object of which we are taking the transpose
+  *
+  * This class represents an expression of the transpose of a matrix.
+  * It is the return type of MatrixBase::transpose() and MatrixBase::adjoint()
+  * and most of the time this is the only way it is used.
+  *
+  * \sa MatrixBase::transpose(), MatrixBase::adjoint()
+  */
 template<typename MatrixType> class Transpose
   : public TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>
 {
   public:
+
+    typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;
 
     typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
+    typedef typename internal::remove_all<MatrixType>::type NestedExpression;
 
-    inline Transpose(MatrixType& a_matrix) : m_matrix(a_matrix) {}
+    EIGEN_DEVICE_FUNC
+    explicit inline Transpose(MatrixType& matrix) : m_matrix(matrix) {}
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)
 
-    inline Index rows() const { return m_matrix.cols(); }
-    inline Index cols() const { return m_matrix.rows(); }
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.cols(); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.rows(); }
 
     /** \returns the nested expression */
-    const typename internal::remove_all<typename MatrixType::Nested>::type&
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<MatrixTypeNested>::type&
     nestedExpression() const { return m_matrix; }
 
     /** \returns the nested expression */
-    typename internal::remove_all<typename MatrixType::Nested>::type&
-    nestedExpression() { return m_matrix.const_cast_derived(); }
+    EIGEN_DEVICE_FUNC
+    typename internal::remove_reference<MatrixTypeNested>::type&
+    nestedExpression() { return m_matrix; }
+
+    /** \internal */
+    void resize(Index nrows, Index ncols) {
+      m_matrix.resize(ncols,nrows);
+    }
 
   protected:
-    typename MatrixType::Nested m_matrix;
+    typename internal::ref_selector<MatrixType>::non_const_type m_matrix;
 };
 
 namespace internal {
 
 template<typename MatrixType, bool HasDirectAccess = has_direct_access<MatrixType>::ret>
@@ -94,87 +100,54 @@
 {
   typedef typename dense_xpr_base<Transpose<MatrixType> >::type type;
 };
 
 } // end namespace internal
+
+// Generic API dispatcher
+template<typename XprType, typename StorageKind>
+class TransposeImpl
+  : public internal::generic_xpr_base<Transpose<XprType> >::type
+{
+public:
+  typedef typename internal::generic_xpr_base<Transpose<XprType> >::type Base;
+};
 
 template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
   : public internal::TransposeImpl_base<MatrixType>::type
 {
   public:
 
     typedef typename internal::TransposeImpl_base<MatrixType>::type Base;
+    using Base::coeffRef;
     EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl)
 
-    inline Index innerStride() const { return derived().nestedExpression().innerStride(); }
-    inline Index outerStride() const { return derived().nestedExpression().outerStride(); }
+    EIGEN_DEVICE_FUNC inline Index innerStride() const { return derived().nestedExpression().innerStride(); }
+    EIGEN_DEVICE_FUNC inline Index outerStride() const { return derived().nestedExpression().outerStride(); }
 
     typedef typename internal::conditional<
                        internal::is_lvalue<MatrixType>::value,
                        Scalar,
                        const Scalar
                      >::type ScalarWithConstIfNotLvalue;
 
-    inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
-    inline const Scalar* data() const { return derived().nestedExpression().data(); }
-
-    inline ScalarWithConstIfNotLvalue& coeffRef(Index rowId, Index colId)
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return derived().nestedExpression().const_cast_derived().coeffRef(colId, rowId);
-    }
-
-    inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return derived().nestedExpression().const_cast_derived().coeffRef(index);
-    }
-
+    EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
+    EIGEN_DEVICE_FUNC inline const Scalar* data() const { return derived().nestedExpression().data(); }
+
+    // FIXME: shall we keep the const version of coeffRef?
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
       return derived().nestedExpression().coeffRef(colId, rowId);
     }
 
+    EIGEN_DEVICE_FUNC
     inline const Scalar& coeffRef(Index index) const
     {
       return derived().nestedExpression().coeffRef(index);
     }
-
-    inline CoeffReturnType coeff(Index rowId, Index colId) const
-    {
-      return derived().nestedExpression().coeff(colId, rowId);
-    }
-
-    inline CoeffReturnType coeff(Index index) const
-    {
-      return derived().nestedExpression().coeff(index);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index rowId, Index colId) const
-    {
-      return derived().nestedExpression().template packet<LoadMode>(colId, rowId);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index rowId, Index colId, const PacketScalar& x)
-    {
-      derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(colId, rowId, x);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index index) const
-    {
-      return derived().nestedExpression().template packet<LoadMode>(index);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& x)
-    {
-      derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(index, x);
-    }
 };
 
 /** \returns an expression of the transpose of *this.
   *
   * Example: \include MatrixBase_transpose.cpp
@@ -196,11 +169,11 @@
   * \sa transposeInPlace(), adjoint() */
 template<typename Derived>
 inline Transpose<Derived>
 DenseBase<Derived>::transpose()
 {
-  return derived();
+  return TransposeReturnType(derived());
 }
 
 /** This is the const version of transpose().
   *
   * Make sure you read the warning for transpose() !
@@ -234,33 +207,52 @@
   * \sa adjointInPlace(), transpose(), conjugate(), class Transpose, class internal::scalar_conjugate_op */
 template<typename Derived>
 inline const typename MatrixBase<Derived>::AdjointReturnType
 MatrixBase<Derived>::adjoint() const
 {
-  return this->transpose(); // in the complex case, the .conjugate() is be implicit here
-                            // due to implicit conversion to return type
+  return AdjointReturnType(this->transpose());
 }
 
 /***************************************************************************
 * "in place" transpose implementation
 ***************************************************************************/
 
 namespace internal {
 
 template<typename MatrixType,
-  bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic>
+  bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic,
+  bool MatchPacketSize =
+        (int(MatrixType::RowsAtCompileTime) == int(internal::packet_traits<typename MatrixType::Scalar>::size))
+    &&  (internal::evaluator<MatrixType>::Flags&PacketAccessBit) >
 struct inplace_transpose_selector;
 
 template<typename MatrixType>
-struct inplace_transpose_selector<MatrixType,true> { // square matrix
+struct inplace_transpose_selector<MatrixType,true,false> { // square matrix
   static void run(MatrixType& m) {
     m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
   }
 };
 
+// TODO: vectorized path is currently limited to LargestPacketSize x LargestPacketSize cases only.
 template<typename MatrixType>
-struct inplace_transpose_selector<MatrixType,false> { // non square matrix
+struct inplace_transpose_selector<MatrixType,true,true> { // PacketSize x PacketSize
+  static void run(MatrixType& m) {
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet;
+    const Index PacketSize = internal::packet_traits<Scalar>::size;
+    const Index Alignment = internal::evaluator<MatrixType>::Alignment;
+    PacketBlock<Packet> A;
+    for (Index i=0; i<PacketSize; ++i)
+      A.packet[i] = m.template packetByOuterInner<Alignment>(i,0);
+    internal::ptranspose(A);
+    for (Index i=0; i<PacketSize; ++i)
+      m.template writePacket<Alignment>(m.rowIndexByOuterInner(i,0), m.colIndexByOuterInner(i,0), A.packet[i]);
+  }
+};
+
+template<typename MatrixType,bool MatchPacketSize>
+struct inplace_transpose_selector<MatrixType,false,MatchPacketSize> { // non square matrix
   static void run(MatrixType& m) {
     if (m.rows()==m.cols())
       m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
     else
       m = m.transpose().eval();
@@ -329,18 +321,10 @@
 
 // The following is to detect aliasing problems in most common cases.
 
 namespace internal {
 
-template<typename BinOp,typename NestedXpr,typename Rhs>
-struct blas_traits<SelfCwiseBinaryOp<BinOp,NestedXpr,Rhs> >
- : blas_traits<NestedXpr>
-{
-  typedef SelfCwiseBinaryOp<BinOp,NestedXpr,Rhs> XprType;
-  static inline const XprType extract(const XprType& x) { return x; }
-};
-
 template<bool DestIsTransposed, typename OtherDerived>
 struct check_transpose_aliasing_compile_time_selector
 {
   enum { ret = bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed };
 };
@@ -401,19 +385,19 @@
 {
     static void run(const Derived&, const OtherDerived&)
     {
     }
 };
+
+template<typename Dst, typename Src>
+void check_for_aliasing(const Dst &dst, const Src &src)
+{
+  internal::checkTransposeAliasing_impl<Dst, Src>::run(dst, src);
+}
 
 } // end namespace internal
 
-template<typename Derived>
-template<typename OtherDerived>
-void DenseBase<Derived>::checkTransposeAliasing(const OtherDerived& other) const
-{
-    internal::checkTransposeAliasing_impl<Derived, OtherDerived>::run(derived(), other);
-}
-#endif
+#endif // EIGEN_NO_DEBUG
 
 } // end namespace Eigen
 
 #endif // EIGEN_TRANSPOSE_H

Index: 3rd_party/eigen/Eigen/src/Core/Transpositions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Transpositions.h
+++ 3rd_party/eigen/Eigen/src/Core/Transpositions.h
@@ -10,52 +10,20 @@
 #ifndef EIGEN_TRANSPOSITIONS_H
 #define EIGEN_TRANSPOSITIONS_H
 
 namespace Eigen { 
 
-/** \class Transpositions
-  * \ingroup Core_Module
-  *
-  * \brief Represents a sequence of transpositions (row/column interchange)
-  *
-  * \param SizeAtCompileTime the number of transpositions, or Dynamic
-  * \param MaxSizeAtCompileTime the maximum number of transpositions, or Dynamic. This optional parameter defaults to SizeAtCompileTime. Most of the time, you should not have to specify it.
-  *
-  * This class represents a permutation transformation as a sequence of \em n transpositions
-  * \f$[T_{n-1} \ldots T_{i} \ldots T_{0}]\f$. It is internally stored as a vector of integers \c indices.
-  * Each transposition \f$ T_{i} \f$ applied on the left of a matrix (\f$ T_{i} M\f$) interchanges
-  * the rows \c i and \c indices[i] of the matrix \c M.
-  * A transposition applied on the right (e.g., \f$ M T_{i}\f$) yields a column interchange.
-  *
-  * Compared to the class PermutationMatrix, such a sequence of transpositions is what is
-  * computed during a decomposition with pivoting, and it is faster when applying the permutation in-place.
-  * 
-  * To apply a sequence of transpositions to a matrix, simply use the operator * as in the following example:
-  * \code
-  * Transpositions tr;
-  * MatrixXf mat;
-  * mat = tr * mat;
-  * \endcode
-  * In this example, we detect that the matrix appears on both side, and so the transpositions
-  * are applied in-place without any temporary or extra copy.
-  *
-  * \sa class PermutationMatrix
-  */
-
-namespace internal {
-template<typename TranspositionType, typename MatrixType, int Side, bool Transposed=false> struct transposition_matrix_product_retval;
-}
-
 template<typename Derived>
 class TranspositionsBase
 {
     typedef internal::traits<Derived> Traits;
     
   public:
 
     typedef typename Traits::IndicesType IndicesType;
-    typedef typename IndicesType::Scalar Index;
+    typedef typename IndicesType::Scalar StorageIndex;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     Derived& derived() { return *static_cast<Derived*>(this); }
     const Derived& derived() const { return *static_cast<const Derived*>(this); }
 
     /** Copies the \a other transpositions into \c *this */
@@ -63,11 +31,11 @@
     Derived& operator=(const TranspositionsBase<OtherDerived>& other)
     {
       indices() = other.indices();
       return derived();
     }
-
+    
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** This is a special case of the templated operator=. Its purpose is to
       * prevent a default operator= from hiding the templated operator=.
       */
     Derived& operator=(const TranspositionsBase& other)
@@ -76,40 +44,44 @@
       return derived();
     }
     #endif
 
     /** \returns the number of transpositions */
-    inline Index size() const { return indices().size(); }
-
-    /** Direct access to the underlying index vector */
-    inline const Index& coeff(Index i) const { return indices().coeff(i); }
-    /** Direct access to the underlying index vector */
-    inline Index& coeffRef(Index i) { return indices().coeffRef(i); }
-    /** Direct access to the underlying index vector */
-    inline const Index& operator()(Index i) const { return indices()(i); }
-    /** Direct access to the underlying index vector */
-    inline Index& operator()(Index i) { return indices()(i); }
-    /** Direct access to the underlying index vector */
-    inline const Index& operator[](Index i) const { return indices()(i); }
-    /** Direct access to the underlying index vector */
-    inline Index& operator[](Index i) { return indices()(i); }
+    Index size() const { return indices().size(); }
+    /** \returns the number of rows of the equivalent permutation matrix */
+    Index rows() const { return indices().size(); }
+    /** \returns the number of columns of the equivalent permutation matrix */
+    Index cols() const { return indices().size(); }
+
+    /** Direct access to the underlying index vector */
+    inline const StorageIndex& coeff(Index i) const { return indices().coeff(i); }
+    /** Direct access to the underlying index vector */
+    inline StorageIndex& coeffRef(Index i) { return indices().coeffRef(i); }
+    /** Direct access to the underlying index vector */
+    inline const StorageIndex& operator()(Index i) const { return indices()(i); }
+    /** Direct access to the underlying index vector */
+    inline StorageIndex& operator()(Index i) { return indices()(i); }
+    /** Direct access to the underlying index vector */
+    inline const StorageIndex& operator[](Index i) const { return indices()(i); }
+    /** Direct access to the underlying index vector */
+    inline StorageIndex& operator[](Index i) { return indices()(i); }
 
     /** const version of indices(). */
     const IndicesType& indices() const { return derived().indices(); }
     /** \returns a reference to the stored array representing the transpositions. */
     IndicesType& indices() { return derived().indices(); }
 
     /** Resizes to given size. */
-    inline void resize(int newSize)
+    inline void resize(Index newSize)
     {
       indices().resize(newSize);
     }
 
     /** Sets \c *this to represents an identity transformation */
     void setIdentity()
     {
-      for(int i = 0; i < indices().size(); ++i)
+      for(StorageIndex i = 0; i < indices().size(); ++i)
         coeffRef(i) = i;
     }
 
     // FIXME: do we want such methods ?
     // might be usefull when the target matrix expression is complex, e.g.:
@@ -142,27 +114,57 @@
 
   protected:
 };
 
 namespace internal {
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
-struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType> >
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
+struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
+ : traits<PermutationMatrix<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
 {
-  typedef IndexType Index;
-  typedef Matrix<Index, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
+  typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
+  typedef TranspositionsStorage StorageKind;
 };
 }
 
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType>
-class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType> >
+/** \class Transpositions
+  * \ingroup Core_Module
+  *
+  * \brief Represents a sequence of transpositions (row/column interchange)
+  *
+  * \tparam SizeAtCompileTime the number of transpositions, or Dynamic
+  * \tparam MaxSizeAtCompileTime the maximum number of transpositions, or Dynamic. This optional parameter defaults to SizeAtCompileTime. Most of the time, you should not have to specify it.
+  *
+  * This class represents a permutation transformation as a sequence of \em n transpositions
+  * \f$[T_{n-1} \ldots T_{i} \ldots T_{0}]\f$. It is internally stored as a vector of integers \c indices.
+  * Each transposition \f$ T_{i} \f$ applied on the left of a matrix (\f$ T_{i} M\f$) interchanges
+  * the rows \c i and \c indices[i] of the matrix \c M.
+  * A transposition applied on the right (e.g., \f$ M T_{i}\f$) yields a column interchange.
+  *
+  * Compared to the class PermutationMatrix, such a sequence of transpositions is what is
+  * computed during a decomposition with pivoting, and it is faster when applying the permutation in-place.
+  *
+  * To apply a sequence of transpositions to a matrix, simply use the operator * as in the following example:
+  * \code
+  * Transpositions tr;
+  * MatrixXf mat;
+  * mat = tr * mat;
+  * \endcode
+  * In this example, we detect that the matrix appears on both side, and so the transpositions
+  * are applied in-place without any temporary or extra copy.
+  *
+  * \sa class PermutationMatrix
+  */
+
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
+class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
 {
     typedef internal::traits<Transpositions> Traits;
   public:
 
     typedef TranspositionsBase<Transpositions> Base;
     typedef typename Traits::IndicesType IndicesType;
-    typedef typename IndicesType::Scalar Index;
+    typedef typename IndicesType::Scalar StorageIndex;
 
     inline Transpositions() {}
 
     /** Copy constructor. */
     template<typename OtherDerived>
@@ -175,11 +177,11 @@
     inline Transpositions(const Transpositions& other) : m_indices(other.indices()) {}
     #endif
 
     /** Generic constructor from expression of the transposition indices. */
     template<typename Other>
-    explicit inline Transpositions(const MatrixBase<Other>& a_indices) : m_indices(a_indices)
+    explicit inline Transpositions(const MatrixBase<Other>& indices) : m_indices(indices)
     {}
 
     /** Copies the \a other transpositions into \c *this */
     template<typename OtherDerived>
     Transpositions& operator=(const TranspositionsBase<OtherDerived>& other)
@@ -213,34 +215,36 @@
     IndicesType m_indices;
 };
 
 
 namespace internal {
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int _PacketAccess>
-struct traits<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType>,_PacketAccess> >
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
+struct traits<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,_PacketAccess> >
+ : traits<PermutationMatrix<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
 {
-  typedef IndexType Index;
-  typedef Map<const Matrix<Index,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1>, _PacketAccess> IndicesType;
+  typedef Map<const Matrix<_StorageIndex,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1>, _PacketAccess> IndicesType;
+  typedef _StorageIndex StorageIndex;
+  typedef TranspositionsStorage StorageKind;
 };
 }
 
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename IndexType, int PacketAccess>
-class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType>,PacketAccess>
- : public TranspositionsBase<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType>,PacketAccess> >
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int PacketAccess>
+class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,PacketAccess>
+ : public TranspositionsBase<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,PacketAccess> >
 {
     typedef internal::traits<Map> Traits;
   public:
 
     typedef TranspositionsBase<Map> Base;
     typedef typename Traits::IndicesType IndicesType;
-    typedef typename IndicesType::Scalar Index;
+    typedef typename IndicesType::Scalar StorageIndex;
 
-    inline Map(const Index* indicesPtr)
+    explicit inline Map(const StorageIndex* indicesPtr)
       : m_indices(indicesPtr)
     {}
 
-    inline Map(const Index* indicesPtr, Index size)
+    inline Map(const StorageIndex* indicesPtr, Index size)
       : m_indices(indicesPtr,size)
     {}
 
     /** Copies the \a other transpositions into \c *this */
     template<typename OtherDerived>
@@ -272,13 +276,13 @@
 };
 
 namespace internal {
 template<typename _IndicesType>
 struct traits<TranspositionsWrapper<_IndicesType> >
+ : traits<PermutationWrapper<_IndicesType> >
 {
-  typedef typename _IndicesType::Scalar Index;
-  typedef _IndicesType IndicesType;
+  typedef TranspositionsStorage StorageKind;
 };
 }
 
 template<typename _IndicesType>
 class TranspositionsWrapper
@@ -287,14 +291,14 @@
     typedef internal::traits<TranspositionsWrapper> Traits;
   public:
 
     typedef TranspositionsBase<TranspositionsWrapper> Base;
     typedef typename Traits::IndicesType IndicesType;
-    typedef typename IndicesType::Scalar Index;
+    typedef typename IndicesType::Scalar StorageIndex;
 
-    inline TranspositionsWrapper(IndicesType& a_indices)
-      : m_indices(a_indices)
+    explicit inline TranspositionsWrapper(IndicesType& indices)
+      : m_indices(indices)
     {}
 
     /** Copies the \a other transpositions into \c *this */
     template<typename OtherDerived>
     TranspositionsWrapper& operator=(const TranspositionsBase<OtherDerived>& other)
@@ -319,118 +323,85 @@
     /** \returns a reference to the stored array representing the transpositions. */
     IndicesType& indices() { return m_indices; }
 
   protected:
 
-    const typename IndicesType::Nested m_indices;
+    typename IndicesType::Nested m_indices;
 };
+
+
 
 /** \returns the \a matrix with the \a transpositions applied to the columns.
   */
-template<typename Derived, typename TranspositionsDerived>
-inline const internal::transposition_matrix_product_retval<TranspositionsDerived, Derived, OnTheRight>
-operator*(const MatrixBase<Derived>& matrix,
-          const TranspositionsBase<TranspositionsDerived> &transpositions)
-{
-  return internal::transposition_matrix_product_retval
-           <TranspositionsDerived, Derived, OnTheRight>
-           (transpositions.derived(), matrix.derived());
+template<typename MatrixDerived, typename TranspositionsDerived>
+EIGEN_DEVICE_FUNC
+const Product<MatrixDerived, TranspositionsDerived, AliasFreeProduct>
+operator*(const MatrixBase<MatrixDerived> &matrix,
+          const TranspositionsBase<TranspositionsDerived>& transpositions)
+{
+  return Product<MatrixDerived, TranspositionsDerived, AliasFreeProduct>
+            (matrix.derived(), transpositions.derived());
 }
 
 /** \returns the \a matrix with the \a transpositions applied to the rows.
   */
-template<typename Derived, typename TranspositionDerived>
-inline const internal::transposition_matrix_product_retval
-               <TranspositionDerived, Derived, OnTheLeft>
-operator*(const TranspositionsBase<TranspositionDerived> &transpositions,
-          const MatrixBase<Derived>& matrix)
-{
-  return internal::transposition_matrix_product_retval
-           <TranspositionDerived, Derived, OnTheLeft>
-           (transpositions.derived(), matrix.derived());
-}
+template<typename TranspositionsDerived, typename MatrixDerived>
+EIGEN_DEVICE_FUNC
+const Product<TranspositionsDerived, MatrixDerived, AliasFreeProduct>
+operator*(const TranspositionsBase<TranspositionsDerived> &transpositions,
+          const MatrixBase<MatrixDerived>& matrix)
+{
+  return Product<TranspositionsDerived, MatrixDerived, AliasFreeProduct>
+            (transpositions.derived(), matrix.derived());
+}
+
+// Template partial specialization for transposed/inverse transpositions
 
 namespace internal {
 
-template<typename TranspositionType, typename MatrixType, int Side, bool Transposed>
-struct traits<transposition_matrix_product_retval<TranspositionType, MatrixType, Side, Transposed> >
-{
-  typedef typename MatrixType::PlainObject ReturnType;
-};
-
-template<typename TranspositionType, typename MatrixType, int Side, bool Transposed>
-struct transposition_matrix_product_retval
- : public ReturnByValue<transposition_matrix_product_retval<TranspositionType, MatrixType, Side, Transposed> >
-{
-    typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
-    typedef typename TranspositionType::Index Index;
-
-    transposition_matrix_product_retval(const TranspositionType& tr, const MatrixType& matrix)
-      : m_transpositions(tr), m_matrix(matrix)
-    {}
-
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
-
-    template<typename Dest> inline void evalTo(Dest& dst) const
-    {
-      const int size = m_transpositions.size();
-      Index j = 0;
-
-      if(!(is_same<MatrixTypeNestedCleaned,Dest>::value && extract_data(dst) == extract_data(m_matrix)))
-        dst = m_matrix;
-
-      for(int k=(Transposed?size-1:0) ; Transposed?k>=0:k<size ; Transposed?--k:++k)
-        if((j=m_transpositions.coeff(k))!=k)
-        {
-          if(Side==OnTheLeft)
-            dst.row(k).swap(dst.row(j));
-          else if(Side==OnTheRight)
-            dst.col(k).swap(dst.col(j));
-        }
-    }
-
-  protected:
-    const TranspositionType& m_transpositions;
-    typename MatrixType::Nested m_matrix;
-};
+template<typename Derived>
+struct traits<Transpose<TranspositionsBase<Derived> > >
+ : traits<Derived>
+{};
 
 } // end namespace internal
 
-/* Template partial specialization for transposed/inverse transpositions */
-
 template<typename TranspositionsDerived>
 class Transpose<TranspositionsBase<TranspositionsDerived> >
 {
     typedef TranspositionsDerived TranspositionType;
     typedef typename TranspositionType::IndicesType IndicesType;
   public:
 
-    Transpose(const TranspositionType& t) : m_transpositions(t) {}
+    explicit Transpose(const TranspositionType& t) : m_transpositions(t) {}
 
-    inline int size() const { return m_transpositions.size(); }
+    Index size() const { return m_transpositions.size(); }
+    Index rows() const { return m_transpositions.size(); }
+    Index cols() const { return m_transpositions.size(); }
 
     /** \returns the \a matrix with the inverse transpositions applied to the columns.
       */
-    template<typename Derived> friend
-    inline const internal::transposition_matrix_product_retval<TranspositionType, Derived, OnTheRight, true>
-    operator*(const MatrixBase<Derived>& matrix, const Transpose& trt)
+    template<typename OtherDerived> friend
+    const Product<OtherDerived, Transpose, AliasFreeProduct>
+    operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trt)
     {
-      return internal::transposition_matrix_product_retval<TranspositionType, Derived, OnTheRight, true>(trt.m_transpositions, matrix.derived());
+      return Product<OtherDerived, Transpose, AliasFreeProduct>(matrix.derived(), trt.derived());
     }
 
     /** \returns the \a matrix with the inverse transpositions applied to the rows.
       */
-    template<typename Derived>
-    inline const internal::transposition_matrix_product_retval<TranspositionType, Derived, OnTheLeft, true>
-    operator*(const MatrixBase<Derived>& matrix) const
+    template<typename OtherDerived>
+    const Product<Transpose, OtherDerived, AliasFreeProduct>
+    operator*(const MatrixBase<OtherDerived>& matrix) const
     {
-      return internal::transposition_matrix_product_retval<TranspositionType, Derived, OnTheLeft, true>(m_transpositions, matrix.derived());
+      return Product<Transpose, OtherDerived, AliasFreeProduct>(*this, matrix.derived());
     }
+    
+    const TranspositionType& nestedExpression() const { return m_transpositions; }
 
   protected:
     const TranspositionType& m_transpositions;
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_TRANSPOSITIONS_H

Index: 3rd_party/eigen/Eigen/src/Core/TriangularMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/TriangularMatrix.h
+++ 3rd_party/eigen/Eigen/src/Core/TriangularMatrix.h
@@ -17,13 +17,11 @@
   
 template<int Side, typename TriangularType, typename Rhs> struct triangular_solve_retval;
   
 }
 
-/** \internal
-  *
-  * \class TriangularBase
+/** \class TriangularBase
   * \ingroup Core_Module
   *
   * \brief Base class for triangular part in a matrix
   */
 template<typename Derived> class TriangularBase : public EigenBase<Derived>
@@ -30,61 +28,94 @@
 {
   public:
 
     enum {
       Mode = internal::traits<Derived>::Mode,
-      CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
       RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
       ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
       MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
-      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime
+      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
+      
+      SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
+                                                   internal::traits<Derived>::ColsAtCompileTime>::ret),
+      /**< This is equal to the number of coefficients, i.e. the number of
+          * rows times the number of columns, or to \a Dynamic if this is not
+          * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
+      
+      MaxSizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::MaxRowsAtCompileTime,
+                                                   internal::traits<Derived>::MaxColsAtCompileTime>::ret)
+        
     };
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
-    typedef typename internal::traits<Derived>::DenseMatrixType DenseMatrixType;
+    typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
+    typedef typename internal::traits<Derived>::FullMatrixType DenseMatrixType;
     typedef DenseMatrixType DenseType;
+    typedef Derived const& Nested;
 
+    EIGEN_DEVICE_FUNC
     inline TriangularBase() { eigen_assert(!((Mode&UnitDiag) && (Mode&ZeroDiag))); }
 
+    EIGEN_DEVICE_FUNC
     inline Index rows() const { return derived().rows(); }
+    EIGEN_DEVICE_FUNC
     inline Index cols() const { return derived().cols(); }
+    EIGEN_DEVICE_FUNC
     inline Index outerStride() const { return derived().outerStride(); }
+    EIGEN_DEVICE_FUNC
     inline Index innerStride() const { return derived().innerStride(); }
+    
+    // dummy resize function
+    void resize(Index rows, Index cols)
+    {
+      EIGEN_UNUSED_VARIABLE(rows);
+      EIGEN_UNUSED_VARIABLE(cols);
+      eigen_assert(rows==this->rows() && cols==this->cols());
+    }
 
+    EIGEN_DEVICE_FUNC
     inline Scalar coeff(Index row, Index col) const  { return derived().coeff(row,col); }
+    EIGEN_DEVICE_FUNC
     inline Scalar& coeffRef(Index row, Index col) { return derived().coeffRef(row,col); }
 
     /** \see MatrixBase::copyCoeff(row,col)
       */
     template<typename Other>
+    EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE void copyCoeff(Index row, Index col, Other& other)
     {
       derived().coeffRef(row, col) = other.coeff(row, col);
     }
 
+    EIGEN_DEVICE_FUNC
     inline Scalar operator()(Index row, Index col) const
     {
       check_coordinates(row, col);
       return coeff(row,col);
     }
+    EIGEN_DEVICE_FUNC
     inline Scalar& operator()(Index row, Index col)
     {
       check_coordinates(row, col);
       return coeffRef(row,col);
     }
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
+    EIGEN_DEVICE_FUNC
     inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    EIGEN_DEVICE_FUNC
     inline Derived& derived() { return *static_cast<Derived*>(this); }
     #endif // not EIGEN_PARSED_BY_DOXYGEN
 
     template<typename DenseDerived>
+    EIGEN_DEVICE_FUNC
     void evalTo(MatrixBase<DenseDerived> &other) const;
     template<typename DenseDerived>
+    EIGEN_DEVICE_FUNC
     void evalToLazy(MatrixBase<DenseDerived> &other) const;
 
+    EIGEN_DEVICE_FUNC
     DenseMatrixType toDenseMatrix() const
     {
       DenseMatrixType res(rows(), cols());
       evalToLazy(res);
       return res;
@@ -117,560 +148,449 @@
 };
 
 /** \class TriangularView
   * \ingroup Core_Module
   *
-  * \brief Base class for triangular part in a matrix
+  * \brief Expression of a triangular part in a matrix
   *
   * \param MatrixType the type of the object in which we are taking the triangular part
   * \param Mode the kind of triangular matrix expression to construct. Can be #Upper,
   *             #Lower, #UnitUpper, #UnitLower, #StrictlyUpper, or #StrictlyLower.
   *             This is in fact a bit field; it must have either #Upper or #Lower, 
-  *             and additionnaly it may have #UnitDiag or #ZeroDiag or neither.
+  *             and additionally it may have #UnitDiag or #ZeroDiag or neither.
   *
   * This class represents a triangular part of a matrix, not necessarily square. Strictly speaking, for rectangular
   * matrices one should speak of "trapezoid" parts. This class is the return type
-  * of MatrixBase::triangularView() and most of the time this is the only way it is used.
+  * of MatrixBase::triangularView() and SparseMatrixBase::triangularView(), and most of the time this is the only way it is used.
   *
   * \sa MatrixBase::triangularView()
   */
 namespace internal {
 template<typename MatrixType, unsigned int _Mode>
 struct traits<TriangularView<MatrixType, _Mode> > : traits<MatrixType>
 {
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef typename ref_selector<MatrixType>::non_const_type MatrixTypeNested;
   typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedNonRef;
   typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
+  typedef typename MatrixType::PlainObject FullMatrixType;
   typedef MatrixType ExpressionType;
-  typedef typename MatrixType::PlainObject DenseMatrixType;
   enum {
     Mode = _Mode,
-    Flags = (MatrixTypeNestedCleaned::Flags & (HereditaryBits) & (~(PacketAccessBit | DirectAccessBit | LinearAccessBit))) | Mode,
-    CoeffReadCost = MatrixTypeNestedCleaned::CoeffReadCost
+    FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
+    Flags = (MatrixTypeNestedCleaned::Flags & (HereditaryBits | FlagsLvalueBit) & (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)))
   };
 };
 }
 
-template<int Mode, bool LhsIsTriangular,
-         typename Lhs, bool LhsIsVector,
-         typename Rhs, bool RhsIsVector>
-struct TriangularProduct;
+template<typename _MatrixType, unsigned int _Mode, typename StorageKind> class TriangularViewImpl;
 
 template<typename _MatrixType, unsigned int _Mode> class TriangularView
-  : public TriangularBase<TriangularView<_MatrixType, _Mode> >
+  : public TriangularViewImpl<_MatrixType, _Mode, typename internal::traits<_MatrixType>::StorageKind >
 {
   public:
 
-    typedef TriangularBase<TriangularView> Base;
+    typedef TriangularViewImpl<_MatrixType, _Mode, typename internal::traits<_MatrixType>::StorageKind > Base;
     typedef typename internal::traits<TriangularView>::Scalar Scalar;
-
     typedef _MatrixType MatrixType;
-    typedef typename internal::traits<TriangularView>::DenseMatrixType DenseMatrixType;
-    typedef DenseMatrixType PlainObject;
 
   protected:
     typedef typename internal::traits<TriangularView>::MatrixTypeNested MatrixTypeNested;
     typedef typename internal::traits<TriangularView>::MatrixTypeNestedNonRef MatrixTypeNestedNonRef;
-    typedef typename internal::traits<TriangularView>::MatrixTypeNestedCleaned MatrixTypeNestedCleaned;
 
     typedef typename internal::remove_all<typename MatrixType::ConjugateReturnType>::type MatrixConjugateReturnType;
     
   public:
-    using Base::evalToLazy;
-  
 
     typedef typename internal::traits<TriangularView>::StorageKind StorageKind;
-    typedef typename internal::traits<TriangularView>::Index Index;
+    typedef typename internal::traits<TriangularView>::MatrixTypeNestedCleaned NestedExpression;
 
     enum {
       Mode = _Mode,
+      Flags = internal::traits<TriangularView>::Flags,
       TransposeMode = (Mode & Upper ? Lower : 0)
                     | (Mode & Lower ? Upper : 0)
                     | (Mode & (UnitDiag))
-                    | (Mode & (ZeroDiag))
-    };
-
-    inline TriangularView(const MatrixType& matrix) : m_matrix(matrix)
-    {}
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-    inline Index outerStride() const { return m_matrix.outerStride(); }
-    inline Index innerStride() const { return m_matrix.innerStride(); }
-
-    /** \sa MatrixBase::operator+=() */
-    template<typename Other> TriangularView&  operator+=(const DenseBase<Other>& other) { return *this = m_matrix + other.derived(); }
-    /** \sa MatrixBase::operator-=() */
-    template<typename Other> TriangularView&  operator-=(const DenseBase<Other>& other) { return *this = m_matrix - other.derived(); }
-    /** \sa MatrixBase::operator*=() */
-    TriangularView&  operator*=(const typename internal::traits<MatrixType>::Scalar& other) { return *this = m_matrix * other; }
-    /** \sa MatrixBase::operator/=() */
-    TriangularView&  operator/=(const typename internal::traits<MatrixType>::Scalar& other) { return *this = m_matrix / other; }
-
-    /** \sa MatrixBase::fill() */
-    void fill(const Scalar& value) { setConstant(value); }
-    /** \sa MatrixBase::setConstant() */
-    TriangularView& setConstant(const Scalar& value)
-    { return *this = MatrixType::Constant(rows(), cols(), value); }
-    /** \sa MatrixBase::setZero() */
-    TriangularView& setZero() { return setConstant(Scalar(0)); }
-    /** \sa MatrixBase::setOnes() */
-    TriangularView& setOnes() { return setConstant(Scalar(1)); }
-
-    /** \sa MatrixBase::coeff()
-      * \warning the coordinates must fit into the referenced triangular part
-      */
-    inline Scalar coeff(Index row, Index col) const
-    {
-      Base::check_coordinates_internal(row, col);
-      return m_matrix.coeff(row, col);
-    }
-
-    /** \sa MatrixBase::coeffRef()
-      * \warning the coordinates must fit into the referenced triangular part
-      */
-    inline Scalar& coeffRef(Index row, Index col)
-    {
-      Base::check_coordinates_internal(row, col);
-      return m_matrix.const_cast_derived().coeffRef(row, col);
-    }
-
-    const MatrixTypeNestedCleaned& nestedExpression() const { return m_matrix; }
-    MatrixTypeNestedCleaned& nestedExpression() { return *const_cast<MatrixTypeNestedCleaned*>(&m_matrix); }
-
-    /** Assigns a triangular matrix to a triangular part of a dense matrix */
-    template<typename OtherDerived>
-    TriangularView& operator=(const TriangularBase<OtherDerived>& other);
-
-    template<typename OtherDerived>
-    TriangularView& operator=(const MatrixBase<OtherDerived>& other);
-
-    TriangularView& operator=(const TriangularView& other)
-    { return *this = other.nestedExpression(); }
-
-    template<typename OtherDerived>
-    void lazyAssign(const TriangularBase<OtherDerived>& other);
-
-    template<typename OtherDerived>
-    void lazyAssign(const MatrixBase<OtherDerived>& other);
-
-    /** \sa MatrixBase::conjugate() */
-    inline TriangularView<MatrixConjugateReturnType,Mode> conjugate()
-    { return m_matrix.conjugate(); }
-    /** \sa MatrixBase::conjugate() const */
-    inline const TriangularView<MatrixConjugateReturnType,Mode> conjugate() const
-    { return m_matrix.conjugate(); }
-
-    /** \sa MatrixBase::adjoint() const */
-    inline const TriangularView<const typename MatrixType::AdjointReturnType,TransposeMode> adjoint() const
-    { return m_matrix.adjoint(); }
-
-    /** \sa MatrixBase::transpose() */
-    inline TriangularView<Transpose<MatrixType>,TransposeMode> transpose()
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return m_matrix.const_cast_derived().transpose();
-    }
-    /** \sa MatrixBase::transpose() const */
-    inline const TriangularView<Transpose<MatrixType>,TransposeMode> transpose() const
-    {
-      return m_matrix.transpose();
-    }
-
-    /** Efficient triangular matrix times vector/matrix product */
-    template<typename OtherDerived>
-    TriangularProduct<Mode, true, MatrixType, false, OtherDerived, OtherDerived::ColsAtCompileTime==1>
-    operator*(const MatrixBase<OtherDerived>& rhs) const
-    {
-      return TriangularProduct
-              <Mode, true, MatrixType, false, OtherDerived, OtherDerived::ColsAtCompileTime==1>
-              (m_matrix, rhs.derived());
-    }
-
-    /** Efficient vector/matrix times triangular matrix product */
-    template<typename OtherDerived> friend
-    TriangularProduct<Mode, false, OtherDerived, OtherDerived::RowsAtCompileTime==1, MatrixType, false>
-    operator*(const MatrixBase<OtherDerived>& lhs, const TriangularView& rhs)
-    {
-      return TriangularProduct
-              <Mode, false, OtherDerived, OtherDerived::RowsAtCompileTime==1, MatrixType, false>
-              (lhs.derived(),rhs.m_matrix);
-    }
-
-    #ifdef EIGEN2_SUPPORT
-    template<typename OtherDerived>
-    struct eigen2_product_return_type
-    {
-      typedef typename TriangularView<MatrixType,Mode>::DenseMatrixType DenseMatrixType;
-      typedef typename OtherDerived::PlainObject::DenseType OtherPlainObject;
-      typedef typename ProductReturnType<DenseMatrixType, OtherPlainObject>::Type ProdRetType;
-      typedef typename ProdRetType::PlainObject type;
-    };
-    template<typename OtherDerived>
-    const typename eigen2_product_return_type<OtherDerived>::type
-    operator*(const EigenBase<OtherDerived>& rhs) const
-    {
-      typename OtherDerived::PlainObject::DenseType rhsPlainObject;
-      rhs.evalTo(rhsPlainObject);
-      return this->toDenseMatrix() * rhsPlainObject;
-    }
-    template<typename OtherMatrixType>
-    bool isApprox(const TriangularView<OtherMatrixType, Mode>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
-    {
-      return this->toDenseMatrix().isApprox(other.toDenseMatrix(), precision);
-    }
-    template<typename OtherDerived>
-    bool isApprox(const MatrixBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
-    {
-      return this->toDenseMatrix().isApprox(other, precision);
-    }
-    #endif // EIGEN2_SUPPORT
-
-    template<int Side, typename Other>
-    inline const internal::triangular_solve_retval<Side,TriangularView, Other>
-    solve(const MatrixBase<Other>& other) const;
-
-    template<int Side, typename OtherDerived>
-    void solveInPlace(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename Other>
-    inline const internal::triangular_solve_retval<OnTheLeft,TriangularView, Other> 
-    solve(const MatrixBase<Other>& other) const
-    { return solve<OnTheLeft>(other); }
-
-    template<typename OtherDerived>
-    void solveInPlace(const MatrixBase<OtherDerived>& other) const
-    { return solveInPlace<OnTheLeft>(other); }
-
-    const SelfAdjointView<MatrixTypeNestedNonRef,Mode> selfadjointView() const
-    {
-      EIGEN_STATIC_ASSERT((Mode&UnitDiag)==0,PROGRAMMING_ERROR);
-      return SelfAdjointView<MatrixTypeNestedNonRef,Mode>(m_matrix);
-    }
-    SelfAdjointView<MatrixTypeNestedNonRef,Mode> selfadjointView()
-    {
-      EIGEN_STATIC_ASSERT((Mode&UnitDiag)==0,PROGRAMMING_ERROR);
-      return SelfAdjointView<MatrixTypeNestedNonRef,Mode>(m_matrix);
-    }
-
-    template<typename OtherDerived>
-    void swap(TriangularBase<OtherDerived> const & other)
-    {
-      TriangularView<SwapWrapper<MatrixType>,Mode>(const_cast<MatrixType&>(m_matrix)).lazyAssign(other.derived());
-    }
-
-    template<typename OtherDerived>
-    void swap(MatrixBase<OtherDerived> const & other)
-    {
-      SwapWrapper<MatrixType> swaper(const_cast<MatrixType&>(m_matrix));
-      TriangularView<SwapWrapper<MatrixType>,Mode>(swaper).lazyAssign(other.derived());
-    }
-
+                    | (Mode & (ZeroDiag)),
+      IsVectorAtCompileTime = false
+    };
+
+    EIGEN_DEVICE_FUNC
+    explicit inline TriangularView(MatrixType& matrix) : m_matrix(matrix)
+    {}
+    
+    using Base::operator=;
+    TriangularView& operator=(const TriangularView &other)
+    { return Base::operator=(other); }
+
+    /** \copydoc EigenBase::rows() */
+    EIGEN_DEVICE_FUNC
+    inline Index rows() const { return m_matrix.rows(); }
+    /** \copydoc EigenBase::cols() */
+    EIGEN_DEVICE_FUNC
+    inline Index cols() const { return m_matrix.cols(); }
+
+    /** \returns a const reference to the nested expression */
+    EIGEN_DEVICE_FUNC
+    const NestedExpression& nestedExpression() const { return m_matrix; }
+
+    /** \returns a reference to the nested expression */
+    EIGEN_DEVICE_FUNC
+    NestedExpression& nestedExpression() { return m_matrix; }
+    
+    typedef TriangularView<const MatrixConjugateReturnType,Mode> ConjugateReturnType;
+    /** \sa MatrixBase::conjugate() const */
+    EIGEN_DEVICE_FUNC
+    inline const ConjugateReturnType conjugate() const
+    { return ConjugateReturnType(m_matrix.conjugate()); }
+
+    typedef TriangularView<const typename MatrixType::AdjointReturnType,TransposeMode> AdjointReturnType;
+    /** \sa MatrixBase::adjoint() const */
+    EIGEN_DEVICE_FUNC
+    inline const AdjointReturnType adjoint() const
+    { return AdjointReturnType(m_matrix.adjoint()); }
+
+    typedef TriangularView<typename MatrixType::TransposeReturnType,TransposeMode> TransposeReturnType;
+     /** \sa MatrixBase::transpose() */
+    EIGEN_DEVICE_FUNC
+    inline TransposeReturnType transpose()
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
+      typename MatrixType::TransposeReturnType tmp(m_matrix);
+      return TransposeReturnType(tmp);
+    }
+    
+    typedef TriangularView<const typename MatrixType::ConstTransposeReturnType,TransposeMode> ConstTransposeReturnType;
+    /** \sa MatrixBase::transpose() const */
+    EIGEN_DEVICE_FUNC
+    inline const ConstTransposeReturnType transpose() const
+    {
+      return ConstTransposeReturnType(m_matrix.transpose());
+    }
+
+    template<typename Other>
+    EIGEN_DEVICE_FUNC
+    inline const Solve<TriangularView, Other> 
+    solve(const MatrixBase<Other>& other) const
+    { return Solve<TriangularView, Other>(*this, other.derived()); }
+    
+  // workaround MSVC ICE
+  #if EIGEN_COMP_MSVC
+    template<int Side, typename Other>
+    EIGEN_DEVICE_FUNC
+    inline const internal::triangular_solve_retval<Side,TriangularView, Other>
+    solve(const MatrixBase<Other>& other) const
+    { return Base::template solve<Side>(other); }
+  #else
+    using Base::solve;
+  #endif
+
+    /** \returns a selfadjoint view of the referenced triangular part which must be either \c #Upper or \c #Lower.
+      *
+      * This is a shortcut for \code this->nestedExpression().selfadjointView<(*this)::Mode>() \endcode
+      * \sa MatrixBase::selfadjointView() */
+    EIGEN_DEVICE_FUNC
+    SelfAdjointView<MatrixTypeNestedNonRef,Mode> selfadjointView()
+    {
+      EIGEN_STATIC_ASSERT((Mode&(UnitDiag|ZeroDiag))==0,PROGRAMMING_ERROR);
+      return SelfAdjointView<MatrixTypeNestedNonRef,Mode>(m_matrix);
+    }
+
+    /** This is the const version of selfadjointView() */
+    EIGEN_DEVICE_FUNC
+    const SelfAdjointView<MatrixTypeNestedNonRef,Mode> selfadjointView() const
+    {
+      EIGEN_STATIC_ASSERT((Mode&(UnitDiag|ZeroDiag))==0,PROGRAMMING_ERROR);
+      return SelfAdjointView<MatrixTypeNestedNonRef,Mode>(m_matrix);
+    }
+
+
+    /** \returns the determinant of the triangular matrix
+      * \sa MatrixBase::determinant() */
+    EIGEN_DEVICE_FUNC
     Scalar determinant() const
     {
       if (Mode & UnitDiag)
         return 1;
       else if (Mode & ZeroDiag)
         return 0;
       else
         return m_matrix.diagonal().prod();
     }
-    
-    // TODO simplify the following:
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    EIGEN_STRONG_INLINE TriangularView& operator=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
-    {
-      setZero();
-      return assignProduct(other.derived(),1);
-    }
-    
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    EIGEN_STRONG_INLINE TriangularView& operator+=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
-    {
-      return assignProduct(other.derived(),1);
-    }
-    
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    EIGEN_STRONG_INLINE TriangularView& operator-=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
-    {
-      return assignProduct(other.derived(),-1);
-    }
-    
-    
-    template<typename ProductDerived>
-    EIGEN_STRONG_INLINE TriangularView& operator=(const ScaledProduct<ProductDerived>& other)
-    {
-      setZero();
-      return assignProduct(other.derived(),other.alpha());
-    }
-    
-    template<typename ProductDerived>
-    EIGEN_STRONG_INLINE TriangularView& operator+=(const ScaledProduct<ProductDerived>& other)
-    {
-      return assignProduct(other.derived(),other.alpha());
-    }
-    
-    template<typename ProductDerived>
-    EIGEN_STRONG_INLINE TriangularView& operator-=(const ScaledProduct<ProductDerived>& other)
-    {
-      return assignProduct(other.derived(),-other.alpha());
-    }
-    
-  protected:
-    
-    template<typename ProductDerived, typename Lhs, typename Rhs>
-    EIGEN_STRONG_INLINE TriangularView& assignProduct(const ProductBase<ProductDerived, Lhs,Rhs>& prod, const Scalar& alpha);
-    
-    template<int Mode, bool LhsIsTriangular,
-         typename Lhs, bool LhsIsVector,
-         typename Rhs, bool RhsIsVector>
-    EIGEN_STRONG_INLINE TriangularView& assignProduct(const TriangularProduct<Mode, LhsIsTriangular, Lhs, LhsIsVector, Rhs, RhsIsVector>& prod, const Scalar& alpha)
-    {
-      lazyAssign(alpha*prod.eval());
-      return *this;
-    }
-
-    MatrixTypeNested m_matrix;
+      
+  protected:
+
+    MatrixTypeNested m_matrix;
+};
+
+/** \ingroup Core_Module
+  *
+  * \brief Base class for a triangular part in a \b dense matrix
+  *
+  * This class is an abstract base class of class TriangularView, and objects of type TriangularViewImpl cannot be instantiated.
+  * It extends class TriangularView with additional methods which available for dense expressions only.
+  *
+  * \sa class TriangularView, MatrixBase::triangularView()
+  */
+template<typename _MatrixType, unsigned int _Mode> class TriangularViewImpl<_MatrixType,_Mode,Dense>
+  : public TriangularBase<TriangularView<_MatrixType, _Mode> >
+{
+  public:
+
+    typedef TriangularView<_MatrixType, _Mode> TriangularViewType;
+    typedef TriangularBase<TriangularViewType> Base;
+    typedef typename internal::traits<TriangularViewType>::Scalar Scalar;
+
+    typedef _MatrixType MatrixType;
+    typedef typename MatrixType::PlainObject DenseMatrixType;
+    typedef DenseMatrixType PlainObject;
+
+  public:
+    using Base::evalToLazy;
+    using Base::derived;
+
+    typedef typename internal::traits<TriangularViewType>::StorageKind StorageKind;
+
+    enum {
+      Mode = _Mode,
+      Flags = internal::traits<TriangularViewType>::Flags
+    };
+
+    /** \returns the outer-stride of the underlying dense matrix
+      * \sa DenseCoeffsBase::outerStride() */
+    EIGEN_DEVICE_FUNC
+    inline Index outerStride() const { return derived().nestedExpression().outerStride(); }
+    /** \returns the inner-stride of the underlying dense matrix
+      * \sa DenseCoeffsBase::innerStride() */
+    EIGEN_DEVICE_FUNC
+    inline Index innerStride() const { return derived().nestedExpression().innerStride(); }
+
+    /** \sa MatrixBase::operator+=() */
+    template<typename Other>
+    EIGEN_DEVICE_FUNC
+    TriangularViewType&  operator+=(const DenseBase<Other>& other) {
+      internal::call_assignment_no_alias(derived(), other.derived(), internal::add_assign_op<Scalar,typename Other::Scalar>());
+      return derived();
+    }
+    /** \sa MatrixBase::operator-=() */
+    template<typename Other>
+    EIGEN_DEVICE_FUNC
+    TriangularViewType&  operator-=(const DenseBase<Other>& other) {
+      internal::call_assignment_no_alias(derived(), other.derived(), internal::sub_assign_op<Scalar,typename Other::Scalar>());
+      return derived();
+    }
+    
+    /** \sa MatrixBase::operator*=() */
+    EIGEN_DEVICE_FUNC
+    TriangularViewType&  operator*=(const typename internal::traits<MatrixType>::Scalar& other) { return *this = derived().nestedExpression() * other; }
+    /** \sa DenseBase::operator/=() */
+    EIGEN_DEVICE_FUNC
+    TriangularViewType&  operator/=(const typename internal::traits<MatrixType>::Scalar& other) { return *this = derived().nestedExpression() / other; }
+
+    /** \sa MatrixBase::fill() */
+    EIGEN_DEVICE_FUNC
+    void fill(const Scalar& value) { setConstant(value); }
+    /** \sa MatrixBase::setConstant() */
+    EIGEN_DEVICE_FUNC
+    TriangularViewType& setConstant(const Scalar& value)
+    { return *this = MatrixType::Constant(derived().rows(), derived().cols(), value); }
+    /** \sa MatrixBase::setZero() */
+    EIGEN_DEVICE_FUNC
+    TriangularViewType& setZero() { return setConstant(Scalar(0)); }
+    /** \sa MatrixBase::setOnes() */
+    EIGEN_DEVICE_FUNC
+    TriangularViewType& setOnes() { return setConstant(Scalar(1)); }
+
+    /** \sa MatrixBase::coeff()
+      * \warning the coordinates must fit into the referenced triangular part
+      */
+    EIGEN_DEVICE_FUNC
+    inline Scalar coeff(Index row, Index col) const
+    {
+      Base::check_coordinates_internal(row, col);
+      return derived().nestedExpression().coeff(row, col);
+    }
+
+    /** \sa MatrixBase::coeffRef()
+      * \warning the coordinates must fit into the referenced triangular part
+      */
+    EIGEN_DEVICE_FUNC
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(TriangularViewType);
+      Base::check_coordinates_internal(row, col);
+      return derived().nestedExpression().coeffRef(row, col);
+    }
+
+    /** Assigns a triangular matrix to a triangular part of a dense matrix */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    TriangularViewType& operator=(const TriangularBase<OtherDerived>& other);
+
+    /** Shortcut for\code *this = other.other.triangularView<(*this)::Mode>() \endcode */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    TriangularViewType& operator=(const MatrixBase<OtherDerived>& other);
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    EIGEN_DEVICE_FUNC
+    TriangularViewType& operator=(const TriangularViewImpl& other)
+    { return *this = other.derived().nestedExpression(); }
+
+    /** \deprecated */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    void lazyAssign(const TriangularBase<OtherDerived>& other);
+
+    /** \deprecated */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    void lazyAssign(const MatrixBase<OtherDerived>& other);
+#endif
+
+    /** Efficient triangular matrix times vector/matrix product */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    const Product<TriangularViewType,OtherDerived>
+    operator*(const MatrixBase<OtherDerived>& rhs) const
+    {
+      return Product<TriangularViewType,OtherDerived>(derived(), rhs.derived());
+    }
+
+    /** Efficient vector/matrix times triangular matrix product */
+    template<typename OtherDerived> friend
+    EIGEN_DEVICE_FUNC
+    const Product<OtherDerived,TriangularViewType>
+    operator*(const MatrixBase<OtherDerived>& lhs, const TriangularViewImpl& rhs)
+    {
+      return Product<OtherDerived,TriangularViewType>(lhs.derived(),rhs.derived());
+    }
+
+    /** \returns the product of the inverse of \c *this with \a other, \a *this being triangular.
+      *
+      * This function computes the inverse-matrix matrix product inverse(\c *this) * \a other if
+      * \a Side==OnTheLeft (the default), or the right-inverse-multiply  \a other * inverse(\c *this) if
+      * \a Side==OnTheRight.
+      *
+      * Note that the template parameter \c Side can be ommitted, in which case \c Side==OnTheLeft
+      *
+      * The matrix \c *this must be triangular and invertible (i.e., all the coefficients of the
+      * diagonal must be non zero). It works as a forward (resp. backward) substitution if \c *this
+      * is an upper (resp. lower) triangular matrix.
+      *
+      * Example: \include Triangular_solve.cpp
+      * Output: \verbinclude Triangular_solve.out
+      *
+      * This function returns an expression of the inverse-multiply and can works in-place if it is assigned
+      * to the same matrix or vector \a other.
+      *
+      * For users coming from BLAS, this function (and more specifically solveInPlace()) offer
+      * all the operations supported by the \c *TRSV and \c *TRSM BLAS routines.
+      *
+      * \sa TriangularView::solveInPlace()
+      */
+    template<int Side, typename Other>
+    EIGEN_DEVICE_FUNC
+    inline const internal::triangular_solve_retval<Side,TriangularViewType, Other>
+    solve(const MatrixBase<Other>& other) const;
+
+    /** "in-place" version of TriangularView::solve() where the result is written in \a other
+      *
+      * \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
+      * This function will const_cast it, so constness isn't honored here.
+      *
+      * Note that the template parameter \c Side can be ommitted, in which case \c Side==OnTheLeft
+      *
+      * See TriangularView:solve() for the details.
+      */
+    template<int Side, typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    void solveInPlace(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    void solveInPlace(const MatrixBase<OtherDerived>& other) const
+    { return solveInPlace<OnTheLeft>(other); }
+
+    /** Swaps the coefficients of the common triangular parts of two matrices */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+#ifdef EIGEN_PARSED_BY_DOXYGEN
+    void swap(TriangularBase<OtherDerived> &other)
+#else
+    void swap(TriangularBase<OtherDerived> const & other)
+#endif
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(OtherDerived);
+      call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
+    }
+
+    /** \deprecated
+      * Shortcut for \code (*this).swap(other.triangularView<(*this)::Mode>()) \endcode */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    void swap(MatrixBase<OtherDerived> const & other)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(OtherDerived);
+      call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
+    }
+
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _solve_impl(const RhsType &rhs, DstType &dst) const {
+      if(!internal::is_same_dense(dst,rhs))
+        dst = rhs;
+      this->solveInPlace(dst);
+    }
+
+    template<typename ProductType>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TriangularViewType& _assignProduct(const ProductType& prod, const Scalar& alpha, bool beta);
 };
 
 /***************************************************************************
 * Implementation of triangular evaluation/assignment
 ***************************************************************************/
 
-namespace internal {
-
-template<typename Derived1, typename Derived2, unsigned int Mode, int UnrollCount, bool ClearOpposite>
-struct triangular_assignment_selector
-{
-  enum {
-    col = (UnrollCount-1) / Derived1::RowsAtCompileTime,
-    row = (UnrollCount-1) % Derived1::RowsAtCompileTime
-  };
-  
-  typedef typename Derived1::Scalar Scalar;
-
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    triangular_assignment_selector<Derived1, Derived2, Mode, UnrollCount-1, ClearOpposite>::run(dst, src);
-
-    eigen_assert( Mode == Upper || Mode == Lower
-            || Mode == StrictlyUpper || Mode == StrictlyLower
-            || Mode == UnitUpper || Mode == UnitLower);
-    if((Mode == Upper && row <= col)
-    || (Mode == Lower && row >= col)
-    || (Mode == StrictlyUpper && row < col)
-    || (Mode == StrictlyLower && row > col)
-    || (Mode == UnitUpper && row < col)
-    || (Mode == UnitLower && row > col))
-      dst.copyCoeff(row, col, src);
-    else if(ClearOpposite)
-    {
-      if (Mode&UnitDiag && row==col)
-        dst.coeffRef(row, col) = Scalar(1);
-      else
-        dst.coeffRef(row, col) = Scalar(0);
-    }
-  }
-};
-
-// prevent buggy user code from causing an infinite recursion
-template<typename Derived1, typename Derived2, unsigned int Mode, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, Mode, 0, ClearOpposite>
-{
-  static inline void run(Derived1 &, const Derived2 &) {}
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, Upper, Dynamic, ClearOpposite>
-{
-  typedef typename Derived1::Index Index;
-  typedef typename Derived1::Scalar Scalar;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    for(Index j = 0; j < dst.cols(); ++j)
-    {
-      Index maxi = (std::min)(j, dst.rows()-1);
-      for(Index i = 0; i <= maxi; ++i)
-        dst.copyCoeff(i, j, src);
-      if (ClearOpposite)
-        for(Index i = maxi+1; i < dst.rows(); ++i)
-          dst.coeffRef(i, j) = Scalar(0);
-    }
-  }
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, Lower, Dynamic, ClearOpposite>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    for(Index j = 0; j < dst.cols(); ++j)
-    {
-      for(Index i = j; i < dst.rows(); ++i)
-        dst.copyCoeff(i, j, src);
-      Index maxi = (std::min)(j, dst.rows());
-      if (ClearOpposite)
-        for(Index i = 0; i < maxi; ++i)
-          dst.coeffRef(i, j) = static_cast<typename Derived1::Scalar>(0);
-    }
-  }
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic, ClearOpposite>
-{
-  typedef typename Derived1::Index Index;
-  typedef typename Derived1::Scalar Scalar;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    for(Index j = 0; j < dst.cols(); ++j)
-    {
-      Index maxi = (std::min)(j, dst.rows());
-      for(Index i = 0; i < maxi; ++i)
-        dst.copyCoeff(i, j, src);
-      if (ClearOpposite)
-        for(Index i = maxi; i < dst.rows(); ++i)
-          dst.coeffRef(i, j) = Scalar(0);
-    }
-  }
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, StrictlyLower, Dynamic, ClearOpposite>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    for(Index j = 0; j < dst.cols(); ++j)
-    {
-      for(Index i = j+1; i < dst.rows(); ++i)
-        dst.copyCoeff(i, j, src);
-      Index maxi = (std::min)(j, dst.rows()-1);
-      if (ClearOpposite)
-        for(Index i = 0; i <= maxi; ++i)
-          dst.coeffRef(i, j) = static_cast<typename Derived1::Scalar>(0);
-    }
-  }
-};
-
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, UnitUpper, Dynamic, ClearOpposite>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    for(Index j = 0; j < dst.cols(); ++j)
-    {
-      Index maxi = (std::min)(j, dst.rows());
-      for(Index i = 0; i < maxi; ++i)
-        dst.copyCoeff(i, j, src);
-      if (ClearOpposite)
-      {
-        for(Index i = maxi+1; i < dst.rows(); ++i)
-          dst.coeffRef(i, j) = 0;
-      }
-    }
-    dst.diagonal().setOnes();
-  }
-};
-template<typename Derived1, typename Derived2, bool ClearOpposite>
-struct triangular_assignment_selector<Derived1, Derived2, UnitLower, Dynamic, ClearOpposite>
-{
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
-  {
-    for(Index j = 0; j < dst.cols(); ++j)
-    {
-      Index maxi = (std::min)(j, dst.rows());
-      for(Index i = maxi+1; i < dst.rows(); ++i)
-        dst.copyCoeff(i, j, src);
-      if (ClearOpposite)
-      {
-        for(Index i = 0; i < maxi; ++i)
-          dst.coeffRef(i, j) = 0;
-      }
-    }
-    dst.diagonal().setOnes();
-  }
-};
-
-} // end namespace internal
-
-// FIXME should we keep that possibility
-template<typename MatrixType, unsigned int Mode>
-template<typename OtherDerived>
-inline TriangularView<MatrixType, Mode>&
-TriangularView<MatrixType, Mode>::operator=(const MatrixBase<OtherDerived>& other)
-{
-  if(OtherDerived::Flags & EvalBeforeAssigningBit)
-  {
-    typename internal::plain_matrix_type<OtherDerived>::type other_evaluated(other.rows(), other.cols());
-    other_evaluated.template triangularView<Mode>().lazyAssign(other.derived());
-    lazyAssign(other_evaluated);
-  }
-  else
-    lazyAssign(other.derived());
-  return *this;
-}
-
-// FIXME should we keep that possibility
-template<typename MatrixType, unsigned int Mode>
-template<typename OtherDerived>
-void TriangularView<MatrixType, Mode>::lazyAssign(const MatrixBase<OtherDerived>& other)
-{
-  enum {
-    unroll = MatrixType::SizeAtCompileTime != Dynamic
-          && internal::traits<OtherDerived>::CoeffReadCost != Dynamic
-          && MatrixType::SizeAtCompileTime*internal::traits<OtherDerived>::CoeffReadCost/2 <= EIGEN_UNROLLING_LIMIT
-  };
-  eigen_assert(m_matrix.rows() == other.rows() && m_matrix.cols() == other.cols());
-
-  internal::triangular_assignment_selector
-    <MatrixType, OtherDerived, int(Mode),
-    unroll ? int(MatrixType::SizeAtCompileTime) : Dynamic,
-    false // do not change the opposite triangular part
-    >::run(m_matrix.const_cast_derived(), other.derived());
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+// FIXME should we keep that possibility
+template<typename MatrixType, unsigned int Mode>
+template<typename OtherDerived>
+inline TriangularView<MatrixType, Mode>&
+TriangularViewImpl<MatrixType, Mode, Dense>::operator=(const MatrixBase<OtherDerived>& other)
+{
+  internal::call_assignment_no_alias(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
+  return derived();
+}
+
+// FIXME should we keep that possibility
+template<typename MatrixType, unsigned int Mode>
+template<typename OtherDerived>
+void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const MatrixBase<OtherDerived>& other)
+{
+  internal::call_assignment_no_alias(derived(), other.template triangularView<Mode>());
 }
 
 
 
 template<typename MatrixType, unsigned int Mode>
 template<typename OtherDerived>
 inline TriangularView<MatrixType, Mode>&
-TriangularView<MatrixType, Mode>::operator=(const TriangularBase<OtherDerived>& other)
+TriangularViewImpl<MatrixType, Mode, Dense>::operator=(const TriangularBase<OtherDerived>& other)
 {
   eigen_assert(Mode == int(OtherDerived::Mode));
-  if(internal::traits<OtherDerived>::Flags & EvalBeforeAssigningBit)
-  {
-    typename OtherDerived::DenseMatrixType other_evaluated(other.rows(), other.cols());
-    other_evaluated.template triangularView<Mode>().lazyAssign(other.derived().nestedExpression());
-    lazyAssign(other_evaluated);
-  }
-  else
-    lazyAssign(other.derived().nestedExpression());
-  return *this;
+  internal::call_assignment(derived(), other.derived());
+  return derived();
 }
 
 template<typename MatrixType, unsigned int Mode>
 template<typename OtherDerived>
-void TriangularView<MatrixType, Mode>::lazyAssign(const TriangularBase<OtherDerived>& other)
-{
-  enum {
-    unroll = MatrixType::SizeAtCompileTime != Dynamic
-                   && internal::traits<OtherDerived>::CoeffReadCost != Dynamic
-                   && MatrixType::SizeAtCompileTime * internal::traits<OtherDerived>::CoeffReadCost / 2
-                        <= EIGEN_UNROLLING_LIMIT
-  };
-  eigen_assert(m_matrix.rows() == other.rows() && m_matrix.cols() == other.cols());
-
-  internal::triangular_assignment_selector
-    <MatrixType, OtherDerived, int(Mode),
-    unroll ? int(MatrixType::SizeAtCompileTime) : Dynamic,
-    false // preserve the opposite triangular part
-    >::run(m_matrix.const_cast_derived(), other.derived().nestedExpression());
-}
+void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const TriangularBase<OtherDerived>& other)
+{
+  eigen_assert(Mode == int(OtherDerived::Mode));
+  internal::call_assignment_no_alias(derived(), other.derived());
+}
+#endif
 
 /***************************************************************************
 * Implementation of TriangularBase methods
 ***************************************************************************/
 
@@ -678,39 +598,11 @@
   * If the matrix is triangular, the opposite part is set to zero. */
 template<typename Derived>
 template<typename DenseDerived>
 void TriangularBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
 {
-  if(internal::traits<Derived>::Flags & EvalBeforeAssigningBit)
-  {
-    typename internal::plain_matrix_type<Derived>::type other_evaluated(rows(), cols());
-    evalToLazy(other_evaluated);
-    other.derived().swap(other_evaluated);
-  }
-  else
-    evalToLazy(other.derived());
-}
-
-/** Assigns a triangular or selfadjoint matrix to a dense matrix.
-  * If the matrix is triangular, the opposite part is set to zero. */
-template<typename Derived>
-template<typename DenseDerived>
-void TriangularBase<Derived>::evalToLazy(MatrixBase<DenseDerived> &other) const
-{
-  enum {
-    unroll = DenseDerived::SizeAtCompileTime != Dynamic
-                   && internal::traits<Derived>::CoeffReadCost != Dynamic
-                   && DenseDerived::SizeAtCompileTime * internal::traits<Derived>::CoeffReadCost / 2
-                        <= EIGEN_UNROLLING_LIMIT
-  };
-  other.derived().resize(this->rows(), this->cols());
-
-  internal::triangular_assignment_selector
-    <DenseDerived, typename internal::traits<Derived>::MatrixTypeNestedCleaned, Derived::Mode,
-    unroll ? int(DenseDerived::SizeAtCompileTime) : Dynamic,
-    true // clear the opposite triangular part
-    >::run(other.derived(), derived().nestedExpression());
+  evalToLazy(other.derived());
 }
 
 /***************************************************************************
 * Implementation of TriangularView methods
 ***************************************************************************/
@@ -717,71 +609,36 @@
 
 /***************************************************************************
 * Implementation of MatrixBase methods
 ***************************************************************************/
 
-#ifdef EIGEN2_SUPPORT
-
-// implementation of part<>(), including the SelfAdjoint case.
-
-namespace internal {
-template<typename MatrixType, unsigned int Mode>
-struct eigen2_part_return_type
-{
-  typedef TriangularView<MatrixType, Mode> type;
-};
-
-template<typename MatrixType>
-struct eigen2_part_return_type<MatrixType, SelfAdjoint>
-{
-  typedef SelfAdjointView<MatrixType, Upper> type;
-};
-}
-
-/** \deprecated use MatrixBase::triangularView() */
-template<typename Derived>
-template<unsigned int Mode>
-const typename internal::eigen2_part_return_type<Derived, Mode>::type MatrixBase<Derived>::part() const
-{
-  return derived();
-}
-
-/** \deprecated use MatrixBase::triangularView() */
-template<typename Derived>
-template<unsigned int Mode>
-typename internal::eigen2_part_return_type<Derived, Mode>::type MatrixBase<Derived>::part()
-{
-  return derived();
-}
-#endif
-
 /**
   * \returns an expression of a triangular view extracted from the current matrix
   *
   * The parameter \a Mode can have the following values: \c #Upper, \c #StrictlyUpper, \c #UnitUpper,
   * \c #Lower, \c #StrictlyLower, \c #UnitLower.
   *
-  * Example: \include MatrixBase_extract.cpp
-  * Output: \verbinclude MatrixBase_extract.out
+  * Example: \include MatrixBase_triangularView.cpp
+  * Output: \verbinclude MatrixBase_triangularView.out
   *
   * \sa class TriangularView
   */
 template<typename Derived>
 template<unsigned int Mode>
 typename MatrixBase<Derived>::template TriangularViewReturnType<Mode>::Type
 MatrixBase<Derived>::triangularView()
 {
-  return derived();
+  return typename TriangularViewReturnType<Mode>::Type(derived());
 }
 
 /** This is the const version of MatrixBase::triangularView() */
 template<typename Derived>
 template<unsigned int Mode>
 typename MatrixBase<Derived>::template ConstTriangularViewReturnType<Mode>::Type
 MatrixBase<Derived>::triangularView() const
 {
-  return derived();
+  return typename ConstTriangularViewReturnType<Mode>::Type(derived());
 }
 
 /** \returns true if *this is approximately equal to an upper triangular matrix,
   *          within the precision given by \a prec.
   *
@@ -788,25 +645,24 @@
   * \sa isLowerTriangular()
   */
 template<typename Derived>
 bool MatrixBase<Derived>::isUpperTriangular(const RealScalar& prec) const
 {
-  using std::abs;
   RealScalar maxAbsOnUpperPart = static_cast<RealScalar>(-1);
   for(Index j = 0; j < cols(); ++j)
   {
-    Index maxi = (std::min)(j, rows()-1);
+    Index maxi = numext::mini(j, rows()-1);
     for(Index i = 0; i <= maxi; ++i)
     {
-      RealScalar absValue = abs(coeff(i,j));
+      RealScalar absValue = numext::abs(coeff(i,j));
       if(absValue > maxAbsOnUpperPart) maxAbsOnUpperPart = absValue;
     }
   }
   RealScalar threshold = maxAbsOnUpperPart * prec;
   for(Index j = 0; j < cols(); ++j)
     for(Index i = j+1; i < rows(); ++i)
-      if(abs(coeff(i, j)) > threshold) return false;
+      if(numext::abs(coeff(i, j)) > threshold) return false;
   return true;
 }
 
 /** \returns true if *this is approximately equal to a lower triangular matrix,
   *          within the precision given by \a prec.
@@ -814,26 +670,314 @@
   * \sa isUpperTriangular()
   */
 template<typename Derived>
 bool MatrixBase<Derived>::isLowerTriangular(const RealScalar& prec) const
 {
-  using std::abs;
   RealScalar maxAbsOnLowerPart = static_cast<RealScalar>(-1);
   for(Index j = 0; j < cols(); ++j)
     for(Index i = j; i < rows(); ++i)
     {
-      RealScalar absValue = abs(coeff(i,j));
+      RealScalar absValue = numext::abs(coeff(i,j));
       if(absValue > maxAbsOnLowerPart) maxAbsOnLowerPart = absValue;
     }
   RealScalar threshold = maxAbsOnLowerPart * prec;
   for(Index j = 1; j < cols(); ++j)
   {
-    Index maxi = (std::min)(j, rows()-1);
+    Index maxi = numext::mini(j, rows()-1);
     for(Index i = 0; i < maxi; ++i)
-      if(abs(coeff(i, j)) > threshold) return false;
+      if(numext::abs(coeff(i, j)) > threshold) return false;
   }
   return true;
 }
 
+
+/***************************************************************************
+****************************************************************************
+* Evaluators and Assignment of triangular expressions
+***************************************************************************
+***************************************************************************/
+
+namespace internal {
+
+  
+// TODO currently a triangular expression has the form TriangularView<.,.>
+//      in the future triangular-ness should be defined by the expression traits
+//      such that Transpose<TriangularView<.,.> > is valid. (currently TriangularBase::transpose() is overloaded to make it work)
+template<typename MatrixType, unsigned int Mode>
+struct evaluator_traits<TriangularView<MatrixType,Mode> >
+{
+  typedef typename storage_kind_to_evaluator_kind<typename MatrixType::StorageKind>::Kind Kind;
+  typedef typename glue_shapes<typename evaluator_traits<MatrixType>::Shape, TriangularShape>::type Shape;
+};
+
+template<typename MatrixType, unsigned int Mode>
+struct unary_evaluator<TriangularView<MatrixType,Mode>, IndexBased>
+ : evaluator<typename internal::remove_all<MatrixType>::type>
+{
+  typedef TriangularView<MatrixType,Mode> XprType;
+  typedef evaluator<typename internal::remove_all<MatrixType>::type> Base;
+  unary_evaluator(const XprType &xpr) : Base(xpr.nestedExpression()) {}
+};
+
+// Additional assignment kinds:
+struct Triangular2Triangular    {};
+struct Triangular2Dense         {};
+struct Dense2Triangular         {};
+
+
+template<typename Kernel, unsigned int Mode, int UnrollCount, bool ClearOpposite> struct triangular_assignment_loop;
+
+ 
+/** \internal Specialization of the dense assignment kernel for triangular matrices.
+  * The main difference is that the triangular, diagonal, and opposite parts are processed through three different functions.
+  * \tparam UpLo must be either Lower or Upper
+  * \tparam Mode must be either 0, UnitDiag, ZeroDiag, or SelfAdjoint
+  */
+template<int UpLo, int Mode, int SetOpposite, typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version = Specialized>
+class triangular_dense_assignment_kernel : public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>
+{
+protected:
+  typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version> Base;
+  typedef typename Base::DstXprType DstXprType;
+  typedef typename Base::SrcXprType SrcXprType;
+  using Base::m_dst;
+  using Base::m_src;
+  using Base::m_functor;
+public:
+  
+  typedef typename Base::DstEvaluatorType DstEvaluatorType;
+  typedef typename Base::SrcEvaluatorType SrcEvaluatorType;
+  typedef typename Base::Scalar Scalar;
+  typedef typename Base::AssignmentTraits AssignmentTraits;
+  
+  
+  EIGEN_DEVICE_FUNC triangular_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
+    : Base(dst, src, func, dstExpr)
+  {}
+  
+#ifdef EIGEN_INTERNAL_DEBUGGING
+  EIGEN_DEVICE_FUNC void assignCoeff(Index row, Index col)
+  {
+    eigen_internal_assert(row!=col);
+    Base::assignCoeff(row,col);
+  }
+#else
+  using Base::assignCoeff;
+#endif
+  
+  EIGEN_DEVICE_FUNC void assignDiagonalCoeff(Index id)
+  {
+         if(Mode==UnitDiag && SetOpposite) m_functor.assignCoeff(m_dst.coeffRef(id,id), Scalar(1));
+    else if(Mode==ZeroDiag && SetOpposite) m_functor.assignCoeff(m_dst.coeffRef(id,id), Scalar(0));
+    else if(Mode==0)                       Base::assignCoeff(id,id);
+  }
+  
+  EIGEN_DEVICE_FUNC void assignOppositeCoeff(Index row, Index col)
+  { 
+    eigen_internal_assert(row!=col);
+    if(SetOpposite)
+      m_functor.assignCoeff(m_dst.coeffRef(row,col), Scalar(0));
+  }
+};
+
+template<int Mode, bool SetOpposite, typename DstXprType, typename SrcXprType, typename Functor>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_triangular_assignment_loop(DstXprType& dst, const SrcXprType& src, const Functor &func)
+{
+  typedef evaluator<DstXprType> DstEvaluatorType;
+  typedef evaluator<SrcXprType> SrcEvaluatorType;
+
+  SrcEvaluatorType srcEvaluator(src);
+
+  Index dstRows = src.rows();
+  Index dstCols = src.cols();
+  if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+    dst.resize(dstRows, dstCols);
+  DstEvaluatorType dstEvaluator(dst);
+    
+  typedef triangular_dense_assignment_kernel< Mode&(Lower|Upper),Mode&(UnitDiag|ZeroDiag|SelfAdjoint),SetOpposite,
+                                              DstEvaluatorType,SrcEvaluatorType,Functor> Kernel;
+  Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
+  
+  enum {
+      unroll = DstXprType::SizeAtCompileTime != Dynamic
+            && SrcEvaluatorType::CoeffReadCost < HugeCost
+            && DstXprType::SizeAtCompileTime * (DstEvaluatorType::CoeffReadCost+SrcEvaluatorType::CoeffReadCost) / 2 <= EIGEN_UNROLLING_LIMIT
+    };
+  
+  triangular_assignment_loop<Kernel, Mode, unroll ? int(DstXprType::SizeAtCompileTime) : Dynamic, SetOpposite>::run(kernel);
+}
+
+template<int Mode, bool SetOpposite, typename DstXprType, typename SrcXprType>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+void call_triangular_assignment_loop(DstXprType& dst, const SrcXprType& src)
+{
+  call_triangular_assignment_loop<Mode,SetOpposite>(dst, src, internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>());
+}
+
+template<> struct AssignmentKind<TriangularShape,TriangularShape> { typedef Triangular2Triangular Kind; };
+template<> struct AssignmentKind<DenseShape,TriangularShape>      { typedef Triangular2Dense      Kind; };
+template<> struct AssignmentKind<TriangularShape,DenseShape>      { typedef Dense2Triangular      Kind; };
+
+
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, Triangular2Triangular>
+{
+  EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
+  {
+    eigen_assert(int(DstXprType::Mode) == int(SrcXprType::Mode));
+    
+    call_triangular_assignment_loop<DstXprType::Mode, false>(dst, src, func);  
+  }
+};
+
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, Triangular2Dense>
+{
+  EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
+  {
+    call_triangular_assignment_loop<SrcXprType::Mode, (SrcXprType::Mode&SelfAdjoint)==0>(dst, src, func);  
+  }
+};
+
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, Dense2Triangular>
+{
+  EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
+  {
+    call_triangular_assignment_loop<DstXprType::Mode, false>(dst, src, func);  
+  }
+};
+
+
+template<typename Kernel, unsigned int Mode, int UnrollCount, bool SetOpposite>
+struct triangular_assignment_loop
+{
+  // FIXME: this is not very clean, perhaps this information should be provided by the kernel?
+  typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
+  typedef typename DstEvaluatorType::XprType DstXprType;
+  
+  enum {
+    col = (UnrollCount-1) / DstXprType::RowsAtCompileTime,
+    row = (UnrollCount-1) % DstXprType::RowsAtCompileTime
+  };
+  
+  typedef typename Kernel::Scalar Scalar;
+
+  EIGEN_DEVICE_FUNC
+  static inline void run(Kernel &kernel)
+  {
+    triangular_assignment_loop<Kernel, Mode, UnrollCount-1, SetOpposite>::run(kernel);
+    
+    if(row==col)
+      kernel.assignDiagonalCoeff(row);
+    else if( ((Mode&Lower) && row>col) || ((Mode&Upper) && row<col) )
+      kernel.assignCoeff(row,col);
+    else if(SetOpposite)
+      kernel.assignOppositeCoeff(row,col);
+  }
+};
+
+// prevent buggy user code from causing an infinite recursion
+template<typename Kernel, unsigned int Mode, bool SetOpposite>
+struct triangular_assignment_loop<Kernel, Mode, 0, SetOpposite>
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(Kernel &) {}
+};
+
+
+
+// TODO: experiment with a recursive assignment procedure splitting the current
+//       triangular part into one rectangular and two triangular parts.
+
+
+template<typename Kernel, unsigned int Mode, bool SetOpposite>
+struct triangular_assignment_loop<Kernel, Mode, Dynamic, SetOpposite>
+{
+  typedef typename Kernel::Scalar Scalar;
+  EIGEN_DEVICE_FUNC
+  static inline void run(Kernel &kernel)
+  {
+    for(Index j = 0; j < kernel.cols(); ++j)
+    {
+      Index maxi = numext::mini(j, kernel.rows());
+      Index i = 0;
+      if (((Mode&Lower) && SetOpposite) || (Mode&Upper))
+      {
+        for(; i < maxi; ++i)
+          if(Mode&Upper) kernel.assignCoeff(i, j);
+          else           kernel.assignOppositeCoeff(i, j);
+      }
+      else
+        i = maxi;
+      
+      if(i<kernel.rows()) // then i==j
+        kernel.assignDiagonalCoeff(i++);
+      
+      if (((Mode&Upper) && SetOpposite) || (Mode&Lower))
+      {
+        for(; i < kernel.rows(); ++i)
+          if(Mode&Lower) kernel.assignCoeff(i, j);
+          else           kernel.assignOppositeCoeff(i, j);
+      }
+    }
+  }
+};
+
+} // end namespace internal
+
+/** Assigns a triangular or selfadjoint matrix to a dense matrix.
+  * If the matrix is triangular, the opposite part is set to zero. */
+template<typename Derived>
+template<typename DenseDerived>
+void TriangularBase<Derived>::evalToLazy(MatrixBase<DenseDerived> &other) const
+{
+  other.derived().resize(this->rows(), this->cols());
+  internal::call_triangular_assignment_loop<Derived::Mode,(Derived::Mode&SelfAdjoint)==0 /* SetOpposite */>(other.derived(), derived().nestedExpression());
+}
+
+namespace internal {
+  
+// Triangular = Product
+template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
+struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::assign_op<Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, Dense2Triangular>
+{
+  typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,typename SrcXprType::Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    dst._assignProduct(src, 1, 0);
+  }
+};
+
+// Triangular += Product
+template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
+struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::add_assign_op<Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, Dense2Triangular>
+{
+  typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<Scalar,typename SrcXprType::Scalar> &)
+  {
+    dst._assignProduct(src, 1, 1);
+  }
+};
+
+// Triangular -= Product
+template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
+struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::sub_assign_op<Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, Dense2Triangular>
+{
+  typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<Scalar,typename SrcXprType::Scalar> &)
+  {
+    dst._assignProduct(src, -1, 1);
+  }
+};
+
+} // end namespace internal
+
 } // end namespace Eigen
 
 #endif // EIGEN_TRIANGULARMATRIX_H

Index: 3rd_party/eigen/Eigen/src/Core/VectorBlock.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/VectorBlock.h
+++ 3rd_party/eigen/Eigen/src/Core/VectorBlock.h
@@ -10,18 +10,28 @@
 
 #ifndef EIGEN_VECTORBLOCK_H
 #define EIGEN_VECTORBLOCK_H
 
 namespace Eigen { 
+
+namespace internal {
+template<typename VectorType, int Size>
+struct traits<VectorBlock<VectorType, Size> >
+  : public traits<Block<VectorType,
+                     traits<VectorType>::Flags & RowMajorBit ? 1 : Size,
+                     traits<VectorType>::Flags & RowMajorBit ? Size : 1> >
+{
+};
+}
 
 /** \class VectorBlock
   * \ingroup Core_Module
   *
   * \brief Expression of a fixed-size or dynamic-size sub-vector
   *
-  * \param VectorType the type of the object in which we are taking a sub-vector
-  * \param Size size of the sub-vector we are taking at compile time (optional)
+  * \tparam VectorType the type of the object in which we are taking a sub-vector
+  * \tparam Size size of the sub-vector we are taking at compile time (optional)
   *
   * This class represents an expression of either a fixed-size or dynamic-size sub-vector.
   * It is the return type of DenseBase::segment(Index,Index) and DenseBase::segment<int>(Index) and
   * most of the time this is the only way it is used.
   *
@@ -41,21 +51,10 @@
   * \include class_FixedVectorBlock.cpp
   * Output: \verbinclude class_FixedVectorBlock.out
   *
   * \sa class Block, DenseBase::segment(Index,Index,Index,Index), DenseBase::segment(Index,Index)
   */
-
-namespace internal {
-template<typename VectorType, int Size>
-struct traits<VectorBlock<VectorType, Size> >
-  : public traits<Block<VectorType,
-                     traits<VectorType>::Flags & RowMajorBit ? 1 : Size,
-                     traits<VectorType>::Flags & RowMajorBit ? Size : 1> >
-{
-};
-}
-
 template<typename VectorType, int Size> class VectorBlock
   : public Block<VectorType,
                      internal::traits<VectorType>::Flags & RowMajorBit ? 1 : Size,
                      internal::traits<VectorType>::Flags & RowMajorBit ? Size : 1>
 {
@@ -70,10 +69,11 @@
 
     using Base::operator=;
 
     /** Dynamic-size constructor
       */
+    EIGEN_DEVICE_FUNC
     inline VectorBlock(VectorType& vector, Index start, Index size)
       : Base(vector,
              IsColVector ? start : 0, IsColVector ? 0 : start,
              IsColVector ? size  : 1, IsColVector ? 1 : size)
     {
@@ -80,10 +80,11 @@
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorBlock);
     }
 
     /** Fixed-size constructor
       */
+    EIGEN_DEVICE_FUNC
     inline VectorBlock(VectorType& vector, Index start)
       : Base(vector, IsColVector ? start : 0, IsColVector ? 0 : start)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorBlock);
     }

Index: 3rd_party/eigen/Eigen/src/Core/VectorwiseOp.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/VectorwiseOp.h
+++ 3rd_party/eigen/Eigen/src/Core/VectorwiseOp.h
@@ -9,11 +9,11 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PARTIAL_REDUX_H
 #define EIGEN_PARTIAL_REDUX_H
 
-namespace Eigen { 
+namespace Eigen {
 
 /** \class PartialReduxExpr
   * \ingroup Core_Module
   *
   * \brief Generic expression of a partially reduxed matrix
@@ -39,68 +39,47 @@
 {
   typedef typename MemberOp::result_type Scalar;
   typedef typename traits<MatrixType>::StorageKind StorageKind;
   typedef typename traits<MatrixType>::XprKind XprKind;
   typedef typename MatrixType::Scalar InputScalar;
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
     RowsAtCompileTime = Direction==Vertical   ? 1 : MatrixType::RowsAtCompileTime,
     ColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::ColsAtCompileTime,
     MaxRowsAtCompileTime = Direction==Vertical   ? 1 : MatrixType::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::MaxColsAtCompileTime,
-    Flags0 = (unsigned int)_MatrixTypeNested::Flags & HereditaryBits,
-    Flags = (Flags0 & ~RowMajorBit) | (RowsAtCompileTime == 1 ? RowMajorBit : 0),
+    Flags = RowsAtCompileTime == 1 ? RowMajorBit : 0,
     TraversalSize = Direction==Vertical ? MatrixType::RowsAtCompileTime :  MatrixType::ColsAtCompileTime
   };
-  #if EIGEN_GNUC_AT_LEAST(3,4)
-  typedef typename MemberOp::template Cost<InputScalar,int(TraversalSize)> CostOpType;
-  #else
-  typedef typename MemberOp::template Cost<InputScalar,TraversalSize> CostOpType;
-  #endif
-  enum {
-    CoeffReadCost = TraversalSize==Dynamic ? Dynamic
-                  : TraversalSize * traits<_MatrixTypeNested>::CoeffReadCost + int(CostOpType::value)
-  };
 };
 }
 
 template< typename MatrixType, typename MemberOp, int Direction>
-class PartialReduxExpr : internal::no_assignment_operator,
-  public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type
+class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type,
+                         internal::no_assignment_operator
 {
   public:
 
     typedef typename internal::dense_xpr_base<PartialReduxExpr>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(PartialReduxExpr)
-    typedef typename internal::traits<PartialReduxExpr>::MatrixTypeNested MatrixTypeNested;
-    typedef typename internal::traits<PartialReduxExpr>::_MatrixTypeNested _MatrixTypeNested;
 
-    PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp())
+    EIGEN_DEVICE_FUNC
+    explicit PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp())
       : m_matrix(mat), m_functor(func) {}
 
+    EIGEN_DEVICE_FUNC
     Index rows() const { return (Direction==Vertical   ? 1 : m_matrix.rows()); }
+    EIGEN_DEVICE_FUNC
     Index cols() const { return (Direction==Horizontal ? 1 : m_matrix.cols()); }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(Index i, Index j) const
-    {
-      if (Direction==Vertical)
-        return m_functor(m_matrix.col(j));
-      else
-        return m_functor(m_matrix.row(i));
-    }
-
-    const Scalar coeff(Index index) const
-    {
-      if (Direction==Vertical)
-        return m_functor(m_matrix.col(index));
-      else
-        return m_functor(m_matrix.row(index));
-    }
+    EIGEN_DEVICE_FUNC
+    typename MatrixType::Nested nestedExpression() const { return m_matrix; }
+
+    EIGEN_DEVICE_FUNC
+    const MemberOp& functor() const { return m_functor; }
 
   protected:
-    MatrixTypeNested m_matrix;
+    typename MatrixType::Nested m_matrix;
     const MemberOp m_functor;
 };
 
 #define EIGEN_MEMBER_FUNCTOR(MEMBER,COST)                               \
   template <typename ResultType>                                        \
@@ -108,11 +87,12 @@
     EIGEN_EMPTY_STRUCT_CTOR(member_##MEMBER)                            \
     typedef ResultType result_type;                                     \
     template<typename Scalar, int Size> struct Cost                     \
     { enum { value = COST }; };                                         \
     template<typename XprType>                                          \
-    EIGEN_STRONG_INLINE ResultType operator()(const XprType& mat) const \
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE                               \
+    ResultType operator()(const XprType& mat) const                     \
     { return mat.MEMBER(); } \
   }
 
 namespace internal {
 
@@ -128,21 +108,31 @@
 EIGEN_MEMBER_FUNCTOR(all, (Size-1)*NumTraits<Scalar>::AddCost);
 EIGEN_MEMBER_FUNCTOR(any, (Size-1)*NumTraits<Scalar>::AddCost);
 EIGEN_MEMBER_FUNCTOR(count, (Size-1)*NumTraits<Scalar>::AddCost);
 EIGEN_MEMBER_FUNCTOR(prod, (Size-1)*NumTraits<Scalar>::MulCost);
 
+template <int p, typename ResultType>
+struct member_lpnorm {
+  typedef ResultType result_type;
+  template<typename Scalar, int Size> struct Cost
+  { enum { value = (Size+5) * NumTraits<Scalar>::MulCost + (Size-1)*NumTraits<Scalar>::AddCost }; };
+  EIGEN_DEVICE_FUNC member_lpnorm() {}
+  template<typename XprType>
+  EIGEN_DEVICE_FUNC inline ResultType operator()(const XprType& mat) const
+  { return mat.template lpNorm<p>(); }
+};
 
 template <typename BinaryOp, typename Scalar>
 struct member_redux {
   typedef typename result_of<
-                     BinaryOp(Scalar)
+                     BinaryOp(const Scalar&,const Scalar&)
                    >::type  result_type;
   template<typename _Scalar, int Size> struct Cost
   { enum { value = (Size-1) * functor_traits<BinaryOp>::Cost }; };
-  member_redux(const BinaryOp func) : m_functor(func) {}
+  EIGEN_DEVICE_FUNC explicit member_redux(const BinaryOp func) : m_functor(func) {}
   template<typename Derived>
-  inline result_type operator()(const DenseBase<Derived>& mat) const
+  EIGEN_DEVICE_FUNC inline result_type operator()(const DenseBase<Derived>& mat) const
   { return mat.redux(m_functor); }
   const BinaryOp m_functor;
 };
 }
 
@@ -149,12 +139,12 @@
 /** \class VectorwiseOp
   * \ingroup Core_Module
   *
   * \brief Pseudo expression providing partial reduction operations
   *
-  * \param ExpressionType the type of the object on which to do partial reductions
-  * \param Direction indicates the direction of the redux (#Vertical or #Horizontal)
+  * \tparam ExpressionType the type of the object on which to do partial reductions
+  * \tparam Direction indicates the direction of the redux (#Vertical or #Horizontal)
   *
   * This class represents a pseudo expression with partial reduction features.
   * It is the return type of DenseBase::colwise() and DenseBase::rowwise()
   * and most of the time this is the only way it is used.
   *
@@ -167,103 +157,107 @@
 {
   public:
 
     typedef typename ExpressionType::Scalar Scalar;
     typedef typename ExpressionType::RealScalar RealScalar;
-    typedef typename ExpressionType::Index Index;
-    typedef typename internal::conditional<internal::must_nest_by_value<ExpressionType>::ret,
-        ExpressionType, ExpressionType&>::type ExpressionTypeNested;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
+    typedef typename internal::ref_selector<ExpressionType>::non_const_type ExpressionTypeNested;
     typedef typename internal::remove_all<ExpressionTypeNested>::type ExpressionTypeNestedCleaned;
 
     template<template<typename _Scalar> class Functor,
-                      typename Scalar=typename internal::traits<ExpressionType>::Scalar> struct ReturnType
+                      typename Scalar_=Scalar> struct ReturnType
     {
       typedef PartialReduxExpr<ExpressionType,
-                               Functor<Scalar>,
+                               Functor<Scalar_>,
                                Direction
                               > Type;
     };
 
     template<typename BinaryOp> struct ReduxReturnType
     {
       typedef PartialReduxExpr<ExpressionType,
-                               internal::member_redux<BinaryOp,typename internal::traits<ExpressionType>::Scalar>,
+                               internal::member_redux<BinaryOp,Scalar>,
                                Direction
                               > Type;
     };
 
     enum {
-      IsVertical   = (Direction==Vertical) ? 1 : 0,
-      IsHorizontal = (Direction==Horizontal) ? 1 : 0
+      isVertical   = (Direction==Vertical) ? 1 : 0,
+      isHorizontal = (Direction==Horizontal) ? 1 : 0
     };
 
   protected:
 
+    typedef typename internal::conditional<isVertical,
+                               typename ExpressionType::ColXpr,
+                               typename ExpressionType::RowXpr>::type SubVector;
     /** \internal
       * \returns the i-th subvector according to the \c Direction */
-    typedef typename internal::conditional<Direction==Vertical,
-                               typename ExpressionType::ColXpr,
-                               typename ExpressionType::RowXpr>::type SubVector;
+    EIGEN_DEVICE_FUNC
     SubVector subVector(Index i)
     {
       return SubVector(m_matrix.derived(),i);
     }
 
     /** \internal
       * \returns the number of subvectors in the direction \c Direction */
+    EIGEN_DEVICE_FUNC
     Index subVectors() const
-    { return Direction==Vertical?m_matrix.cols():m_matrix.rows(); }
+    { return isVertical?m_matrix.cols():m_matrix.rows(); }
 
     template<typename OtherDerived> struct ExtendedType {
       typedef Replicate<OtherDerived,
-                        Direction==Vertical   ? 1 : ExpressionType::RowsAtCompileTime,
-                        Direction==Horizontal ? 1 : ExpressionType::ColsAtCompileTime> Type;
+                        isVertical   ? 1 : ExpressionType::RowsAtCompileTime,
+                        isHorizontal ? 1 : ExpressionType::ColsAtCompileTime> Type;
     };
 
     /** \internal
       * Replicates a vector to match the size of \c *this */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     typename ExtendedType<OtherDerived>::Type
     extendedTo(const DenseBase<OtherDerived>& other) const
     {
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Vertical, OtherDerived::MaxColsAtCompileTime==1),
+      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isVertical, OtherDerived::MaxColsAtCompileTime==1),
                           YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED)
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Horizontal, OtherDerived::MaxRowsAtCompileTime==1),
+      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isHorizontal, OtherDerived::MaxRowsAtCompileTime==1),
                           YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED)
       return typename ExtendedType<OtherDerived>::Type
                       (other.derived(),
-                       Direction==Vertical   ? 1 : m_matrix.rows(),
-                       Direction==Horizontal ? 1 : m_matrix.cols());
+                       isVertical   ? 1 : m_matrix.rows(),
+                       isHorizontal ? 1 : m_matrix.cols());
     }
-    
+
     template<typename OtherDerived> struct OppositeExtendedType {
       typedef Replicate<OtherDerived,
-                        Direction==Horizontal ? 1 : ExpressionType::RowsAtCompileTime,
-                        Direction==Vertical   ? 1 : ExpressionType::ColsAtCompileTime> Type;
+                        isHorizontal ? 1 : ExpressionType::RowsAtCompileTime,
+                        isVertical   ? 1 : ExpressionType::ColsAtCompileTime> Type;
     };
 
     /** \internal
       * Replicates a vector in the opposite direction to match the size of \c *this */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     typename OppositeExtendedType<OtherDerived>::Type
     extendedToOpposite(const DenseBase<OtherDerived>& other) const
     {
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Horizontal, OtherDerived::MaxColsAtCompileTime==1),
+      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isHorizontal, OtherDerived::MaxColsAtCompileTime==1),
                           YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED)
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Vertical, OtherDerived::MaxRowsAtCompileTime==1),
+      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isVertical, OtherDerived::MaxRowsAtCompileTime==1),
                           YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED)
       return typename OppositeExtendedType<OtherDerived>::Type
                       (other.derived(),
-                       Direction==Horizontal  ? 1 : m_matrix.rows(),
-                       Direction==Vertical    ? 1 : m_matrix.cols());
+                       isHorizontal  ? 1 : m_matrix.rows(),
+                       isVertical    ? 1 : m_matrix.cols());
     }
 
   public:
-
-    inline VectorwiseOp(ExpressionType& matrix) : m_matrix(matrix) {}
+    EIGEN_DEVICE_FUNC
+    explicit inline VectorwiseOp(ExpressionType& matrix) : m_matrix(matrix) {}
 
     /** \internal */
+    EIGEN_DEVICE_FUNC
     inline const ExpressionType& _expression() const { return m_matrix; }
 
     /** \returns a row or column vector expression of \c *this reduxed by \a func
       *
       * The template parameter \a BinaryOp is the type of the functor
@@ -270,148 +264,214 @@
       * of the custom redux operator. Note that func must be an associative operator.
       *
       * \sa class VectorwiseOp, DenseBase::colwise(), DenseBase::rowwise()
       */
     template<typename BinaryOp>
+    EIGEN_DEVICE_FUNC
     const typename ReduxReturnType<BinaryOp>::Type
     redux(const BinaryOp& func = BinaryOp()) const
-    { return typename ReduxReturnType<BinaryOp>::Type(_expression(), func); }
+    { return typename ReduxReturnType<BinaryOp>::Type(_expression(), internal::member_redux<BinaryOp,Scalar>(func)); }
+
+    typedef typename ReturnType<internal::member_minCoeff>::Type MinCoeffReturnType;
+    typedef typename ReturnType<internal::member_maxCoeff>::Type MaxCoeffReturnType;
+    typedef typename ReturnType<internal::member_squaredNorm,RealScalar>::Type SquaredNormReturnType;
+    typedef typename ReturnType<internal::member_norm,RealScalar>::Type NormReturnType;
+    typedef typename ReturnType<internal::member_blueNorm,RealScalar>::Type BlueNormReturnType;
+    typedef typename ReturnType<internal::member_stableNorm,RealScalar>::Type StableNormReturnType;
+    typedef typename ReturnType<internal::member_hypotNorm,RealScalar>::Type HypotNormReturnType;
+    typedef typename ReturnType<internal::member_sum>::Type SumReturnType;
+    typedef typename ReturnType<internal::member_mean>::Type MeanReturnType;
+    typedef typename ReturnType<internal::member_all>::Type AllReturnType;
+    typedef typename ReturnType<internal::member_any>::Type AnyReturnType;
+    typedef PartialReduxExpr<ExpressionType, internal::member_count<Index>, Direction> CountReturnType;
+    typedef typename ReturnType<internal::member_prod>::Type ProdReturnType;
+    typedef Reverse<const ExpressionType, Direction> ConstReverseReturnType;
+    typedef Reverse<ExpressionType, Direction> ReverseReturnType;
+
+    template<int p> struct LpNormReturnType {
+      typedef PartialReduxExpr<ExpressionType, internal::member_lpnorm<p,RealScalar>,Direction> Type;
+    };
 
     /** \returns a row (or column) vector expression of the smallest coefficient
       * of each column (or row) of the referenced expression.
-      * 
+      *
       * \warning the result is undefined if \c *this contains NaN.
       *
       * Example: \include PartialRedux_minCoeff.cpp
       * Output: \verbinclude PartialRedux_minCoeff.out
       *
       * \sa DenseBase::minCoeff() */
-    const typename ReturnType<internal::member_minCoeff>::Type minCoeff() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const MinCoeffReturnType minCoeff() const
+    { return MinCoeffReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression of the largest coefficient
       * of each column (or row) of the referenced expression.
-      * 
+      *
       * \warning the result is undefined if \c *this contains NaN.
       *
       * Example: \include PartialRedux_maxCoeff.cpp
       * Output: \verbinclude PartialRedux_maxCoeff.out
       *
       * \sa DenseBase::maxCoeff() */
-    const typename ReturnType<internal::member_maxCoeff>::Type maxCoeff() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const MaxCoeffReturnType maxCoeff() const
+    { return MaxCoeffReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression of the squared norm
       * of each column (or row) of the referenced expression.
+      * This is a vector with real entries, even if the original matrix has complex entries.
       *
       * Example: \include PartialRedux_squaredNorm.cpp
       * Output: \verbinclude PartialRedux_squaredNorm.out
       *
       * \sa DenseBase::squaredNorm() */
-    const typename ReturnType<internal::member_squaredNorm,RealScalar>::Type squaredNorm() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const SquaredNormReturnType squaredNorm() const
+    { return SquaredNormReturnType(_expression()); }
+
+    /** \returns a row (or column) vector expression of the norm
+      * of each column (or row) of the referenced expression.
+      * This is a vector with real entries, even if the original matrix has complex entries.
+      *
+      * Example: \include PartialRedux_norm.cpp
+      * Output: \verbinclude PartialRedux_norm.out
+      *
+      * \sa DenseBase::norm() */
+    EIGEN_DEVICE_FUNC
+    const NormReturnType norm() const
+    { return NormReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression of the norm
       * of each column (or row) of the referenced expression.
+      * This is a vector with real entries, even if the original matrix has complex entries.
       *
       * Example: \include PartialRedux_norm.cpp
       * Output: \verbinclude PartialRedux_norm.out
       *
       * \sa DenseBase::norm() */
-    const typename ReturnType<internal::member_norm,RealScalar>::Type norm() const
-    { return _expression(); }
+    template<int p>
+    EIGEN_DEVICE_FUNC
+    const typename LpNormReturnType<p>::Type lpNorm() const
+    { return typename LpNormReturnType<p>::Type(_expression()); }
 
 
     /** \returns a row (or column) vector expression of the norm
       * of each column (or row) of the referenced expression, using
-      * blue's algorithm.
+      * Blue's algorithm.
+      * This is a vector with real entries, even if the original matrix has complex entries.
       *
       * \sa DenseBase::blueNorm() */
-    const typename ReturnType<internal::member_blueNorm,RealScalar>::Type blueNorm() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const BlueNormReturnType blueNorm() const
+    { return BlueNormReturnType(_expression()); }
 
 
     /** \returns a row (or column) vector expression of the norm
       * of each column (or row) of the referenced expression, avoiding
       * underflow and overflow.
+      * This is a vector with real entries, even if the original matrix has complex entries.
       *
       * \sa DenseBase::stableNorm() */
-    const typename ReturnType<internal::member_stableNorm,RealScalar>::Type stableNorm() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const StableNormReturnType stableNorm() const
+    { return StableNormReturnType(_expression()); }
 
 
     /** \returns a row (or column) vector expression of the norm
       * of each column (or row) of the referenced expression, avoiding
       * underflow and overflow using a concatenation of hypot() calls.
+      * This is a vector with real entries, even if the original matrix has complex entries.
       *
       * \sa DenseBase::hypotNorm() */
-    const typename ReturnType<internal::member_hypotNorm,RealScalar>::Type hypotNorm() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const HypotNormReturnType hypotNorm() const
+    { return HypotNormReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression of the sum
       * of each column (or row) of the referenced expression.
       *
       * Example: \include PartialRedux_sum.cpp
       * Output: \verbinclude PartialRedux_sum.out
       *
       * \sa DenseBase::sum() */
-    const typename ReturnType<internal::member_sum>::Type sum() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const SumReturnType sum() const
+    { return SumReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression of the mean
     * of each column (or row) of the referenced expression.
     *
     * \sa DenseBase::mean() */
-    const typename ReturnType<internal::member_mean>::Type mean() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const MeanReturnType mean() const
+    { return MeanReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression representing
       * whether \b all coefficients of each respective column (or row) are \c true.
+      * This expression can be assigned to a vector with entries of type \c bool.
       *
       * \sa DenseBase::all() */
-    const typename ReturnType<internal::member_all>::Type all() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const AllReturnType all() const
+    { return AllReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression representing
       * whether \b at \b least one coefficient of each respective column (or row) is \c true.
+      * This expression can be assigned to a vector with entries of type \c bool.
       *
       * \sa DenseBase::any() */
-    const typename ReturnType<internal::member_any>::Type any() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const AnyReturnType any() const
+    { return AnyReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression representing
       * the number of \c true coefficients of each respective column (or row).
+      * This expression can be assigned to a vector whose entries have the same type as is used to
+      * index entries of the original matrix; for dense matrices, this is \c std::ptrdiff_t .
       *
       * Example: \include PartialRedux_count.cpp
       * Output: \verbinclude PartialRedux_count.out
       *
       * \sa DenseBase::count() */
-    const PartialReduxExpr<ExpressionType, internal::member_count<Index>, Direction> count() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const CountReturnType count() const
+    { return CountReturnType(_expression()); }
 
     /** \returns a row (or column) vector expression of the product
       * of each column (or row) of the referenced expression.
       *
       * Example: \include PartialRedux_prod.cpp
       * Output: \verbinclude PartialRedux_prod.out
       *
       * \sa DenseBase::prod() */
-    const typename ReturnType<internal::member_prod>::Type prod() const
-    { return _expression(); }
+    EIGEN_DEVICE_FUNC
+    const ProdReturnType prod() const
+    { return ProdReturnType(_expression()); }
 
 
     /** \returns a matrix expression
       * where each column (or row) are reversed.
       *
       * Example: \include Vectorwise_reverse.cpp
       * Output: \verbinclude Vectorwise_reverse.out
       *
       * \sa DenseBase::reverse() */
-    const Reverse<ExpressionType, Direction> reverse() const
-    { return Reverse<ExpressionType, Direction>( _expression() ); }
+    EIGEN_DEVICE_FUNC
+    const ConstReverseReturnType reverse() const
+    { return ConstReverseReturnType( _expression() ); }
+
+    /** \returns a writable matrix expression
+      * where each column (or row) are reversed.
+      *
+      * \sa reverse() const */
+    EIGEN_DEVICE_FUNC
+    ReverseReturnType reverse()
+    { return ReverseReturnType( _expression() ); }
 
-    typedef Replicate<ExpressionType,Direction==Vertical?Dynamic:1,Direction==Horizontal?Dynamic:1> ReplicateReturnType;
+    typedef Replicate<ExpressionType,(isVertical?Dynamic:1),(isHorizontal?Dynamic:1)> ReplicateReturnType;
+    EIGEN_DEVICE_FUNC
     const ReplicateReturnType replicate(Index factor) const;
 
     /**
       * \return an expression of the replication of each column (or row) of \c *this
       *
@@ -419,21 +479,24 @@
       * Output: \verbinclude DirectionWise_replicate.out
       *
       * \sa VectorwiseOp::replicate(Index), DenseBase::replicate(), class Replicate
       */
     // NOTE implemented here because of sunstudio's compilation errors
-    template<int Factor> const Replicate<ExpressionType,(IsVertical?Factor:1),(IsHorizontal?Factor:1)>
+    // isVertical*Factor+isHorizontal instead of (isVertical?Factor:1) to handle CUDA bug with ternary operator
+    template<int Factor> const Replicate<ExpressionType,isVertical*Factor+isHorizontal,isHorizontal*Factor+isVertical>
+    EIGEN_DEVICE_FUNC
     replicate(Index factor = Factor) const
     {
-      return Replicate<ExpressionType,Direction==Vertical?Factor:1,Direction==Horizontal?Factor:1>
-          (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
+      return Replicate<ExpressionType,(isVertical?Factor:1),(isHorizontal?Factor:1)>
+          (_expression(),isVertical?factor:1,isHorizontal?factor:1);
     }
 
 /////////// Artithmetic operators ///////////
 
     /** Copies the vector \a other to each subvector of \c *this */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     ExpressionType& operator=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
       EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
       //eigen_assert((m_matrix.isNull()) == (other.isNull())); FIXME
@@ -440,28 +503,31 @@
       return const_cast<ExpressionType&>(m_matrix = extendedTo(other.derived()));
     }
 
     /** Adds the vector \a other to each subvector of \c *this */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     ExpressionType& operator+=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
       EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
       return const_cast<ExpressionType&>(m_matrix += extendedTo(other.derived()));
     }
 
     /** Substracts the vector \a other to each subvector of \c *this */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     ExpressionType& operator-=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
       EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
       return const_cast<ExpressionType&>(m_matrix -= extendedTo(other.derived()));
     }
 
     /** Multiples each subvector of \c *this by the vector \a other */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     ExpressionType& operator*=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
       EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType)
       EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
@@ -469,10 +535,11 @@
       return const_cast<ExpressionType&>(m_matrix);
     }
 
     /** Divides each subvector of \c *this by the vector \a other */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     ExpressionType& operator/=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
       EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType)
       EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
@@ -479,12 +546,12 @@
       m_matrix /= extendedTo(other.derived());
       return const_cast<ExpressionType&>(m_matrix);
     }
 
     /** Returns the expression of the sum of the vector \a other to each subvector of \c *this */
-    template<typename OtherDerived> EIGEN_STRONG_INLINE
-    CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
+    template<typename OtherDerived> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC
+    CwiseBinaryOp<internal::scalar_sum_op<Scalar,typename OtherDerived::Scalar>,
                   const ExpressionTypeNestedCleaned,
                   const typename ExtendedType<OtherDerived>::Type>
     operator+(const DenseBase<OtherDerived>& other) const
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
@@ -492,11 +559,12 @@
       return m_matrix + extendedTo(other.derived());
     }
 
     /** Returns the expression of the difference between each subvector of \c *this and the vector \a other */
     template<typename OtherDerived>
-    CwiseBinaryOp<internal::scalar_difference_op<Scalar>,
+    EIGEN_DEVICE_FUNC
+    CwiseBinaryOp<internal::scalar_difference_op<Scalar,typename OtherDerived::Scalar>,
                   const ExpressionTypeNestedCleaned,
                   const typename ExtendedType<OtherDerived>::Type>
     operator-(const DenseBase<OtherDerived>& other) const
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
@@ -504,14 +572,15 @@
       return m_matrix - extendedTo(other.derived());
     }
 
     /** Returns the expression where each subvector is the product of the vector \a other
       * by the corresponding subvector of \c *this */
-    template<typename OtherDerived> EIGEN_STRONG_INLINE
+    template<typename OtherDerived> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC
     CwiseBinaryOp<internal::scalar_product_op<Scalar>,
                   const ExpressionTypeNestedCleaned,
                   const typename ExtendedType<OtherDerived>::Type>
+    EIGEN_DEVICE_FUNC
     operator*(const DenseBase<OtherDerived>& other) const
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
       EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType)
       EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
@@ -519,10 +588,11 @@
     }
 
     /** Returns the expression where each subvector is the quotient of the corresponding
       * subvector of \c *this by the vector \a other */
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     CwiseBinaryOp<internal::scalar_quotient_op<Scalar>,
                   const ExpressionTypeNestedCleaned,
                   const typename ExtendedType<OtherDerived>::Type>
     operator/(const DenseBase<OtherDerived>& other) const
     {
@@ -529,36 +599,40 @@
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
       EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType)
       EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
       return m_matrix / extendedTo(other.derived());
     }
-    
-    /** \returns an expression where each column of row of the referenced matrix are normalized.
+
+    /** \returns an expression where each column (or row) of the referenced matrix are normalized.
       * The referenced matrix is \b not modified.
       * \sa MatrixBase::normalized(), normalize()
       */
+    EIGEN_DEVICE_FUNC
     CwiseBinaryOp<internal::scalar_quotient_op<Scalar>,
                   const ExpressionTypeNestedCleaned,
                   const typename OppositeExtendedType<typename ReturnType<internal::member_norm,RealScalar>::Type>::Type>
     normalized() const { return m_matrix.cwiseQuotient(extendedToOpposite(this->norm())); }
-    
-    
+
+
     /** Normalize in-place each row or columns of the referenced matrix.
       * \sa MatrixBase::normalize(), normalized()
       */
-    void normalize() {
+    EIGEN_DEVICE_FUNC void normalize() {
       m_matrix = this->normalized();
     }
 
+    EIGEN_DEVICE_FUNC inline void reverseInPlace();
+
 /////////// Geometry module ///////////
 
-    #if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
-    Homogeneous<ExpressionType,Direction> homogeneous() const;
-    #endif
+    typedef Homogeneous<ExpressionType,Direction> HomogeneousReturnType;
+    EIGEN_DEVICE_FUNC
+    HomogeneousReturnType homogeneous() const;
 
     typedef typename ExpressionType::PlainObject CrossReturnType;
     template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
     const CrossReturnType cross(const MatrixBase<OtherDerived>& other) const;
 
     enum {
       HNormalized_Size = Direction==Vertical ? internal::traits<ExpressionType>::RowsAtCompileTime
                                              : internal::traits<ExpressionType>::ColsAtCompileTime,
@@ -579,64 +653,43 @@
                 const Replicate<HNormalized_Factors,
                   Direction==Vertical   ? HNormalized_SizeMinusOne : 1,
                   Direction==Horizontal ? HNormalized_SizeMinusOne : 1> >
             HNormalizedReturnType;
 
+    EIGEN_DEVICE_FUNC
     const HNormalizedReturnType hnormalized() const;
 
   protected:
     ExpressionTypeNested m_matrix;
 };
 
-/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
-  *
-  * Example: \include MatrixBase_colwise.cpp
-  * Output: \verbinclude MatrixBase_colwise.out
-  *
-  * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
-  */
-template<typename Derived>
-inline const typename DenseBase<Derived>::ConstColwiseReturnType
-DenseBase<Derived>::colwise() const
-{
-  return derived();
-}
+//const colwise moved to DenseBase.h due to CUDA compiler bug
+
 
 /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
   *
   * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::ColwiseReturnType
 DenseBase<Derived>::colwise()
 {
-  return derived();
-}
-
-/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
-  *
-  * Example: \include MatrixBase_rowwise.cpp
-  * Output: \verbinclude MatrixBase_rowwise.out
-  *
-  * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
-  */
-template<typename Derived>
-inline const typename DenseBase<Derived>::ConstRowwiseReturnType
-DenseBase<Derived>::rowwise() const
-{
-  return derived();
-}
+  return ColwiseReturnType(derived());
+}
+
+//const rowwise moved to DenseBase.h due to CUDA compiler bug
+
 
 /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
   *
   * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::RowwiseReturnType
 DenseBase<Derived>::rowwise()
 {
-  return derived();
+  return RowwiseReturnType(derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_PARTIAL_REDUX_H

Index: 3rd_party/eigen/Eigen/src/Core/Visitor.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/Visitor.h
+++ 3rd_party/eigen/Eigen/src/Core/Visitor.h
@@ -20,10 +20,11 @@
   enum {
     col = (UnrollCount-1) / Derived::RowsAtCompileTime,
     row = (UnrollCount-1) % Derived::RowsAtCompileTime
   };
 
+  EIGEN_DEVICE_FUNC
   static inline void run(const Derived &mat, Visitor& visitor)
   {
     visitor_impl<Visitor, Derived, UnrollCount-1>::run(mat, visitor);
     visitor(mat.coeff(row, col), row, col);
   }
@@ -30,20 +31,21 @@
 };
 
 template<typename Visitor, typename Derived>
 struct visitor_impl<Visitor, Derived, 1>
 {
+  EIGEN_DEVICE_FUNC
   static inline void run(const Derived &mat, Visitor& visitor)
   {
     return visitor.init(mat.coeff(0, 0), 0, 0);
   }
 };
 
 template<typename Visitor, typename Derived>
 struct visitor_impl<Visitor, Derived, Dynamic>
 {
-  typedef typename Derived::Index Index;
+  EIGEN_DEVICE_FUNC
   static inline void run(const Derived& mat, Visitor& visitor)
   {
     visitor.init(mat.coeff(0,0), 0, 0);
     for(Index i = 1; i < mat.rows(); ++i)
       visitor(mat.coeff(i, 0), i, 0);
@@ -51,10 +53,37 @@
       for(Index i = 0; i < mat.rows(); ++i)
         visitor(mat.coeff(i, j), i, j);
   }
 };
 
+// evaluator adaptor
+template<typename XprType>
+class visitor_evaluator
+{
+public:
+  EIGEN_DEVICE_FUNC
+  explicit visitor_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) {}
+  
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  
+  enum {
+    RowsAtCompileTime = XprType::RowsAtCompileTime,
+    CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
+  };
+  
+  EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
+  EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
+  EIGEN_DEVICE_FUNC Index size() const { return m_xpr.size(); }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index row, Index col) const
+  { return m_evaluator.coeff(row, col); }
+  
+protected:
+  internal::evaluator<XprType> m_evaluator;
+  const XprType &m_xpr;
+};
 } // end namespace internal
 
 /** Applies the visitor \a visitor to the whole coefficients of the matrix or vector.
   *
   * The template parameter \a Visitor is the type of the visitor and provides the following interface:
@@ -72,20 +101,21 @@
   *
   * \sa minCoeff(Index*,Index*), maxCoeff(Index*,Index*), DenseBase::redux()
   */
 template<typename Derived>
 template<typename Visitor>
+EIGEN_DEVICE_FUNC
 void DenseBase<Derived>::visit(Visitor& visitor) const
 {
-  enum { unroll = SizeAtCompileTime != Dynamic
-                   && CoeffReadCost != Dynamic
-                   && (SizeAtCompileTime == 1 || internal::functor_traits<Visitor>::Cost != Dynamic)
-                   && SizeAtCompileTime * CoeffReadCost + (SizeAtCompileTime-1) * internal::functor_traits<Visitor>::Cost
-                      <= EIGEN_UNROLLING_LIMIT };
-  return internal::visitor_impl<Visitor, Derived,
-      unroll ? int(SizeAtCompileTime) : Dynamic
-    >::run(derived(), visitor);
+  typedef typename internal::visitor_evaluator<Derived> ThisEvaluator;
+  ThisEvaluator thisEval(derived());
+  
+  enum {
+    unroll =  SizeAtCompileTime != Dynamic
+           && SizeAtCompileTime * ThisEvaluator::CoeffReadCost + (SizeAtCompileTime-1) * internal::functor_traits<Visitor>::Cost <= EIGEN_UNROLLING_LIMIT
+  };
+  return internal::visitor_impl<Visitor, ThisEvaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(thisEval, visitor);
 }
 
 namespace internal {
 
 /** \internal
@@ -92,14 +122,14 @@
   * \brief Base class to implement min and max visitors
   */
 template <typename Derived>
 struct coeff_visitor
 {
-  typedef typename Derived::Index Index;
   typedef typename Derived::Scalar Scalar;
   Index row, col;
   Scalar res;
+  EIGEN_DEVICE_FUNC
   inline void init(const Scalar& value, Index i, Index j)
   {
     res = value;
     row = i;
     col = j;
@@ -112,12 +142,12 @@
   * \sa DenseBase::minCoeff(Index*, Index*)
   */
 template <typename Derived>
 struct min_coeff_visitor : coeff_visitor<Derived>
 {
-  typedef typename Derived::Index Index;
   typedef typename Derived::Scalar Scalar;
+  EIGEN_DEVICE_FUNC
   void operator() (const Scalar& value, Index i, Index j)
   {
     if(value < this->res)
     {
       this->res = value;
@@ -140,12 +170,12 @@
   * \sa DenseBase::maxCoeff(Index*, Index*)
   */
 template <typename Derived>
 struct max_coeff_visitor : coeff_visitor<Derived>
 {
-  typedef typename Derived::Index Index;
-  typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::Scalar Scalar; 
+  EIGEN_DEVICE_FUNC
   void operator() (const Scalar& value, Index i, Index j)
   {
     if(value > this->res)
     {
       this->res = value;
@@ -162,17 +192,19 @@
   };
 };
 
 } // end namespace internal
 
-/** \returns the minimum of all coefficients of *this and puts in *row and *col its location.
+/** \fn DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
+  * \returns the minimum of all coefficients of *this and puts in *row and *col its location.
   * \warning the result is undefined if \c *this contains NaN.
   *
-  * \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visitor(), DenseBase::minCoeff()
+  * \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visit(), DenseBase::minCoeff()
   */
 template<typename Derived>
 template<typename IndexType>
+EIGEN_DEVICE_FUNC
 typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
 {
   internal::min_coeff_visitor<Derived> minVisitor;
   this->visit(minVisitor);
@@ -182,31 +214,34 @@
 }
 
 /** \returns the minimum of all coefficients of *this and puts in *index its location.
   * \warning the result is undefined if \c *this contains NaN. 
   *
-  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::visitor(), DenseBase::minCoeff()
+  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::minCoeff()
   */
 template<typename Derived>
 template<typename IndexType>
+EIGEN_DEVICE_FUNC
 typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::minCoeff(IndexType* index) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   internal::min_coeff_visitor<Derived> minVisitor;
   this->visit(minVisitor);
-  *index = (RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row;
+  *index = IndexType((RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row);
   return minVisitor.res;
 }
 
-/** \returns the maximum of all coefficients of *this and puts in *row and *col its location.
+/** \fn DenseBase<Derived>::maxCoeff(IndexType* rowId, IndexType* colId) const
+  * \returns the maximum of all coefficients of *this and puts in *row and *col its location.
   * \warning the result is undefined if \c *this contains NaN. 
   *
-  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visitor(), DenseBase::maxCoeff()
+  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::maxCoeff()
   */
 template<typename Derived>
 template<typename IndexType>
+EIGEN_DEVICE_FUNC
 typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::maxCoeff(IndexType* rowPtr, IndexType* colPtr) const
 {
   internal::max_coeff_visitor<Derived> maxVisitor;
   this->visit(maxVisitor);
@@ -220,10 +255,11 @@
   *
   * \sa DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visitor(), DenseBase::maxCoeff()
   */
 template<typename Derived>
 template<typename IndexType>
+EIGEN_DEVICE_FUNC
 typename internal::traits<Derived>::Scalar
 DenseBase<Derived>::maxCoeff(IndexType* index) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   internal::max_coeff_visitor<Derived> maxVisitor;

ADDED   3rd_party/eigen/Eigen/src/Core/arch/AVX/Complex.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/AVX/Complex.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AVX/Complex.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AVX/Complex.h
@@ -0,0 +1,483 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner (benoit.steiner.goog@gmail.com)
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_COMPLEX_AVX_H
+#define EIGEN_COMPLEX_AVX_H
+
+namespace Eigen {
+
+namespace internal {
+
+//---------- float ----------
+struct Packet4cf
+{
+  EIGEN_STRONG_INLINE Packet4cf() {}
+  EIGEN_STRONG_INLINE explicit Packet4cf(const __m256& a) : v(a) {}
+  __m256  v;
+};
+
+template<> struct packet_traits<std::complex<float> >  : default_packet_traits
+{
+  typedef Packet4cf type;
+  typedef Packet2cf half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 4,
+    HasHalfPacket = 1,
+
+    HasAdd    = 1,
+    HasSub    = 1,
+    HasMul    = 1,
+    HasDiv    = 1,
+    HasNegate = 1,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasSetLinear = 0
+  };
+};
+
+template<> struct unpacket_traits<Packet4cf> { typedef std::complex<float> type; enum {size=4, alignment=Aligned32}; typedef Packet2cf half; };
+
+template<> EIGEN_STRONG_INLINE Packet4cf padd<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_add_ps(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet4cf psub<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_sub_ps(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet4cf pnegate(const Packet4cf& a)
+{
+  return Packet4cf(pnegate(a.v));
+}
+template<> EIGEN_STRONG_INLINE Packet4cf pconj(const Packet4cf& a)
+{
+  const __m256 mask = _mm256_castsi256_ps(_mm256_setr_epi32(0x00000000,0x80000000,0x00000000,0x80000000,0x00000000,0x80000000,0x00000000,0x80000000));
+  return Packet4cf(_mm256_xor_ps(a.v,mask));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4cf pmul<Packet4cf>(const Packet4cf& a, const Packet4cf& b)
+{
+  __m256 tmp1 = _mm256_mul_ps(_mm256_moveldup_ps(a.v), b.v);
+  __m256 tmp2 = _mm256_mul_ps(_mm256_movehdup_ps(a.v), _mm256_permute_ps(b.v, _MM_SHUFFLE(2,3,0,1)));
+  __m256 result = _mm256_addsub_ps(tmp1, tmp2);
+  return Packet4cf(result);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4cf pand   <Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_and_ps(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet4cf por    <Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_or_ps(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet4cf pxor   <Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_xor_ps(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet4cf pandnot<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_andnot_ps(a.v,b.v)); }
+
+template<> EIGEN_STRONG_INLINE Packet4cf pload <Packet4cf>(const std::complex<float>* from) { EIGEN_DEBUG_ALIGNED_LOAD return Packet4cf(pload<Packet8f>(&numext::real_ref(*from))); }
+template<> EIGEN_STRONG_INLINE Packet4cf ploadu<Packet4cf>(const std::complex<float>* from) { EIGEN_DEBUG_UNALIGNED_LOAD return Packet4cf(ploadu<Packet8f>(&numext::real_ref(*from))); }
+
+
+template<> EIGEN_STRONG_INLINE Packet4cf pset1<Packet4cf>(const std::complex<float>& from)
+{
+  return Packet4cf(_mm256_castpd_ps(_mm256_broadcast_sd((const double*)(const void*)&from)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4cf ploaddup<Packet4cf>(const std::complex<float>* from)
+{
+  // FIXME The following might be optimized using _mm256_movedup_pd
+  Packet2cf a = ploaddup<Packet2cf>(from);
+  Packet2cf b = ploaddup<Packet2cf>(from+1);
+  return  Packet4cf(_mm256_insertf128_ps(_mm256_castps128_ps256(a.v), b.v, 1));
+}
+
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float>* to, const Packet4cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore(&numext::real_ref(*to), from.v); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float>* to, const Packet4cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(&numext::real_ref(*to), from.v); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet4cf pgather<std::complex<float>, Packet4cf>(const std::complex<float>* from, Index stride)
+{
+  return Packet4cf(_mm256_set_ps(std::imag(from[3*stride]), std::real(from[3*stride]),
+                                 std::imag(from[2*stride]), std::real(from[2*stride]),
+                                 std::imag(from[1*stride]), std::real(from[1*stride]),
+                                 std::imag(from[0*stride]), std::real(from[0*stride])));
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet4cf>(std::complex<float>* to, const Packet4cf& from, Index stride)
+{
+  __m128 low = _mm256_extractf128_ps(from.v, 0);
+  to[stride*0] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(low, low, 0)),
+                                     _mm_cvtss_f32(_mm_shuffle_ps(low, low, 1)));
+  to[stride*1] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(low, low, 2)),
+                                     _mm_cvtss_f32(_mm_shuffle_ps(low, low, 3)));
+
+  __m128 high = _mm256_extractf128_ps(from.v, 1);
+  to[stride*2] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(high, high, 0)),
+                                     _mm_cvtss_f32(_mm_shuffle_ps(high, high, 1)));
+  to[stride*3] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(high, high, 2)),
+                                     _mm_cvtss_f32(_mm_shuffle_ps(high, high, 3)));
+
+}
+
+template<> EIGEN_STRONG_INLINE std::complex<float>  pfirst<Packet4cf>(const Packet4cf& a)
+{
+  return pfirst(Packet2cf(_mm256_castps256_ps128(a.v)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4cf preverse(const Packet4cf& a) {
+  __m128 low  = _mm256_extractf128_ps(a.v, 0);
+  __m128 high = _mm256_extractf128_ps(a.v, 1);
+  __m128d lowd  = _mm_castps_pd(low);
+  __m128d highd = _mm_castps_pd(high);
+  low  = _mm_castpd_ps(_mm_shuffle_pd(lowd,lowd,0x1));
+  high = _mm_castpd_ps(_mm_shuffle_pd(highd,highd,0x1));
+  __m256 result = _mm256_setzero_ps();
+  result = _mm256_insertf128_ps(result, low, 1);
+  result = _mm256_insertf128_ps(result, high, 0);
+  return Packet4cf(result);
+}
+
+template<> EIGEN_STRONG_INLINE std::complex<float> predux<Packet4cf>(const Packet4cf& a)
+{
+  return predux(padd(Packet2cf(_mm256_extractf128_ps(a.v,0)),
+                     Packet2cf(_mm256_extractf128_ps(a.v,1))));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4cf preduxp<Packet4cf>(const Packet4cf* vecs)
+{
+  Packet8f t0 = _mm256_shuffle_ps(vecs[0].v, vecs[0].v, _MM_SHUFFLE(3, 1, 2 ,0));
+  Packet8f t1 = _mm256_shuffle_ps(vecs[1].v, vecs[1].v, _MM_SHUFFLE(3, 1, 2 ,0));
+  t0 = _mm256_hadd_ps(t0,t1);
+  Packet8f t2 = _mm256_shuffle_ps(vecs[2].v, vecs[2].v, _MM_SHUFFLE(3, 1, 2 ,0));
+  Packet8f t3 = _mm256_shuffle_ps(vecs[3].v, vecs[3].v, _MM_SHUFFLE(3, 1, 2 ,0));
+  t2 = _mm256_hadd_ps(t2,t3);
+  
+  t1 = _mm256_permute2f128_ps(t0,t2, 0 + (2<<4));
+  t3 = _mm256_permute2f128_ps(t0,t2, 1 + (3<<4));
+
+  return Packet4cf(_mm256_add_ps(t1,t3));
+}
+
+template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet4cf>(const Packet4cf& a)
+{
+  return predux_mul(pmul(Packet2cf(_mm256_extractf128_ps(a.v, 0)),
+                         Packet2cf(_mm256_extractf128_ps(a.v, 1))));
+}
+
+template<int Offset>
+struct palign_impl<Offset,Packet4cf>
+{
+  static EIGEN_STRONG_INLINE void run(Packet4cf& first, const Packet4cf& second)
+  {
+    if (Offset==0) return;
+    palign_impl<Offset*2,Packet8f>::run(first.v, second.v);
+  }
+};
+
+template<> struct conj_helper<Packet4cf, Packet4cf, false,true>
+{
+  EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet4cf& y, const Packet4cf& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& a, const Packet4cf& b) const
+  {
+    return internal::pmul(a, pconj(b));
+  }
+};
+
+template<> struct conj_helper<Packet4cf, Packet4cf, true,false>
+{
+  EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet4cf& y, const Packet4cf& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& a, const Packet4cf& b) const
+  {
+    return internal::pmul(pconj(a), b);
+  }
+};
+
+template<> struct conj_helper<Packet4cf, Packet4cf, true,true>
+{
+  EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet4cf& y, const Packet4cf& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& a, const Packet4cf& b) const
+  {
+    return pconj(internal::pmul(a, b));
+  }
+};
+
+template<> struct conj_helper<Packet8f, Packet4cf, false,false>
+{
+  EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet8f& x, const Packet4cf& y, const Packet4cf& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Packet4cf pmul(const Packet8f& x, const Packet4cf& y) const
+  { return Packet4cf(Eigen::internal::pmul(x, y.v)); }
+};
+
+template<> struct conj_helper<Packet4cf, Packet8f, false,false>
+{
+  EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet8f& y, const Packet4cf& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& x, const Packet8f& y) const
+  { return Packet4cf(Eigen::internal::pmul(x.v, y)); }
+};
+
+template<> EIGEN_STRONG_INLINE Packet4cf pdiv<Packet4cf>(const Packet4cf& a, const Packet4cf& b)
+{
+  Packet4cf num = pmul(a, pconj(b));
+  __m256 tmp = _mm256_mul_ps(b.v, b.v);
+  __m256 tmp2    = _mm256_shuffle_ps(tmp,tmp,0xB1);
+  __m256 denom = _mm256_add_ps(tmp, tmp2);
+  return Packet4cf(_mm256_div_ps(num.v, denom));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4cf pcplxflip<Packet4cf>(const Packet4cf& x)
+{
+  return Packet4cf(_mm256_shuffle_ps(x.v, x.v, _MM_SHUFFLE(2, 3, 0 ,1)));
+}
+
+//---------- double ----------
+struct Packet2cd
+{
+  EIGEN_STRONG_INLINE Packet2cd() {}
+  EIGEN_STRONG_INLINE explicit Packet2cd(const __m256d& a) : v(a) {}
+  __m256d  v;
+};
+
+template<> struct packet_traits<std::complex<double> >  : default_packet_traits
+{
+  typedef Packet2cd type;
+  typedef Packet1cd half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 0,
+    size = 2,
+    HasHalfPacket = 1,
+
+    HasAdd    = 1,
+    HasSub    = 1,
+    HasMul    = 1,
+    HasDiv    = 1,
+    HasNegate = 1,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasSetLinear = 0
+  };
+};
+
+template<> struct unpacket_traits<Packet2cd> { typedef std::complex<double> type; enum {size=2, alignment=Aligned32}; typedef Packet1cd half; };
+
+template<> EIGEN_STRONG_INLINE Packet2cd padd<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_add_pd(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cd psub<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_sub_pd(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cd pnegate(const Packet2cd& a) { return Packet2cd(pnegate(a.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cd pconj(const Packet2cd& a)
+{
+  const __m256d mask = _mm256_castsi256_pd(_mm256_set_epi32(0x80000000,0x0,0x0,0x0,0x80000000,0x0,0x0,0x0));
+  return Packet2cd(_mm256_xor_pd(a.v,mask));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cd pmul<Packet2cd>(const Packet2cd& a, const Packet2cd& b)
+{
+  __m256d tmp1 = _mm256_shuffle_pd(a.v,a.v,0x0);
+  __m256d even = _mm256_mul_pd(tmp1, b.v);
+  __m256d tmp2 = _mm256_shuffle_pd(a.v,a.v,0xF);
+  __m256d tmp3 = _mm256_shuffle_pd(b.v,b.v,0x5);
+  __m256d odd  = _mm256_mul_pd(tmp2, tmp3);
+  return Packet2cd(_mm256_addsub_pd(even, odd));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cd pand   <Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_and_pd(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cd por    <Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_or_pd(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cd pxor   <Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_xor_pd(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cd pandnot<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_andnot_pd(a.v,b.v)); }
+
+template<> EIGEN_STRONG_INLINE Packet2cd pload <Packet2cd>(const std::complex<double>* from)
+{ EIGEN_DEBUG_ALIGNED_LOAD return Packet2cd(pload<Packet4d>((const double*)from)); }
+template<> EIGEN_STRONG_INLINE Packet2cd ploadu<Packet2cd>(const std::complex<double>* from)
+{ EIGEN_DEBUG_UNALIGNED_LOAD return Packet2cd(ploadu<Packet4d>((const double*)from)); }
+
+template<> EIGEN_STRONG_INLINE Packet2cd pset1<Packet2cd>(const std::complex<double>& from)
+{
+  // in case casting to a __m128d* is really not safe, then we can still fallback to this version: (much slower though)
+//   return Packet2cd(_mm256_loadu2_m128d((const double*)&from,(const double*)&from));
+    return Packet2cd(_mm256_broadcast_pd((const __m128d*)(const void*)&from));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cd ploaddup<Packet2cd>(const std::complex<double>* from) { return pset1<Packet2cd>(*from); }
+
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> *   to, const Packet2cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> *   to, const Packet2cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet2cd pgather<std::complex<double>, Packet2cd>(const std::complex<double>* from, Index stride)
+{
+  return Packet2cd(_mm256_set_pd(std::imag(from[1*stride]), std::real(from[1*stride]),
+				 std::imag(from[0*stride]), std::real(from[0*stride])));
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet2cd>(std::complex<double>* to, const Packet2cd& from, Index stride)
+{
+  __m128d low = _mm256_extractf128_pd(from.v, 0);
+  to[stride*0] = std::complex<double>(_mm_cvtsd_f64(low), _mm_cvtsd_f64(_mm_shuffle_pd(low, low, 1)));
+  __m128d high = _mm256_extractf128_pd(from.v, 1);
+  to[stride*1] = std::complex<double>(_mm_cvtsd_f64(high), _mm_cvtsd_f64(_mm_shuffle_pd(high, high, 1)));
+}
+
+template<> EIGEN_STRONG_INLINE std::complex<double> pfirst<Packet2cd>(const Packet2cd& a)
+{
+  __m128d low = _mm256_extractf128_pd(a.v, 0);
+  EIGEN_ALIGN16 double res[2];
+  _mm_store_pd(res, low);
+  return std::complex<double>(res[0],res[1]);
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cd preverse(const Packet2cd& a) {
+  __m256d result = _mm256_permute2f128_pd(a.v, a.v, 1);
+  return Packet2cd(result);
+}
+
+template<> EIGEN_STRONG_INLINE std::complex<double> predux<Packet2cd>(const Packet2cd& a)
+{
+  return predux(padd(Packet1cd(_mm256_extractf128_pd(a.v,0)),
+                     Packet1cd(_mm256_extractf128_pd(a.v,1))));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cd preduxp<Packet2cd>(const Packet2cd* vecs)
+{
+  Packet4d t0 = _mm256_permute2f128_pd(vecs[0].v,vecs[1].v, 0 + (2<<4));
+  Packet4d t1 = _mm256_permute2f128_pd(vecs[0].v,vecs[1].v, 1 + (3<<4));
+
+  return Packet2cd(_mm256_add_pd(t0,t1));
+}
+
+template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet2cd>(const Packet2cd& a)
+{
+  return predux(pmul(Packet1cd(_mm256_extractf128_pd(a.v,0)),
+                     Packet1cd(_mm256_extractf128_pd(a.v,1))));
+}
+
+template<int Offset>
+struct palign_impl<Offset,Packet2cd>
+{
+  static EIGEN_STRONG_INLINE void run(Packet2cd& first, const Packet2cd& second)
+  {
+    if (Offset==0) return;
+    palign_impl<Offset*2,Packet4d>::run(first.v, second.v);
+  }
+};
+
+template<> struct conj_helper<Packet2cd, Packet2cd, false,true>
+{
+  EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet2cd& y, const Packet2cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& a, const Packet2cd& b) const
+  {
+    return internal::pmul(a, pconj(b));
+  }
+};
+
+template<> struct conj_helper<Packet2cd, Packet2cd, true,false>
+{
+  EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet2cd& y, const Packet2cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& a, const Packet2cd& b) const
+  {
+    return internal::pmul(pconj(a), b);
+  }
+};
+
+template<> struct conj_helper<Packet2cd, Packet2cd, true,true>
+{
+  EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet2cd& y, const Packet2cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& a, const Packet2cd& b) const
+  {
+    return pconj(internal::pmul(a, b));
+  }
+};
+
+template<> struct conj_helper<Packet4d, Packet2cd, false,false>
+{
+  EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet4d& x, const Packet2cd& y, const Packet2cd& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Packet2cd pmul(const Packet4d& x, const Packet2cd& y) const
+  { return Packet2cd(Eigen::internal::pmul(x, y.v)); }
+};
+
+template<> struct conj_helper<Packet2cd, Packet4d, false,false>
+{
+  EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet4d& y, const Packet2cd& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& x, const Packet4d& y) const
+  { return Packet2cd(Eigen::internal::pmul(x.v, y)); }
+};
+
+template<> EIGEN_STRONG_INLINE Packet2cd pdiv<Packet2cd>(const Packet2cd& a, const Packet2cd& b)
+{
+  Packet2cd num = pmul(a, pconj(b));
+  __m256d tmp = _mm256_mul_pd(b.v, b.v);
+  __m256d denom = _mm256_hadd_pd(tmp, tmp);
+  return Packet2cd(_mm256_div_pd(num.v, denom));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cd pcplxflip<Packet2cd>(const Packet2cd& x)
+{
+  return Packet2cd(_mm256_shuffle_pd(x.v, x.v, 0x5));
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4cf,4>& kernel) {
+  __m256d P0 = _mm256_castps_pd(kernel.packet[0].v);
+  __m256d P1 = _mm256_castps_pd(kernel.packet[1].v);
+  __m256d P2 = _mm256_castps_pd(kernel.packet[2].v);
+  __m256d P3 = _mm256_castps_pd(kernel.packet[3].v);
+
+  __m256d T0 = _mm256_shuffle_pd(P0, P1, 15);
+  __m256d T1 = _mm256_shuffle_pd(P0, P1, 0);
+  __m256d T2 = _mm256_shuffle_pd(P2, P3, 15);
+  __m256d T3 = _mm256_shuffle_pd(P2, P3, 0);
+
+  kernel.packet[1].v = _mm256_castpd_ps(_mm256_permute2f128_pd(T0, T2, 32));
+  kernel.packet[3].v = _mm256_castpd_ps(_mm256_permute2f128_pd(T0, T2, 49));
+  kernel.packet[0].v = _mm256_castpd_ps(_mm256_permute2f128_pd(T1, T3, 32));
+  kernel.packet[2].v = _mm256_castpd_ps(_mm256_permute2f128_pd(T1, T3, 49));
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet2cd,2>& kernel) {
+  __m256d tmp = _mm256_permute2f128_pd(kernel.packet[0].v, kernel.packet[1].v, 0+(2<<4));
+  kernel.packet[1].v = _mm256_permute2f128_pd(kernel.packet[0].v, kernel.packet[1].v, 1+(3<<4));
+ kernel.packet[0].v = tmp;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4cf pinsertfirst(const Packet4cf& a, std::complex<float> b)
+{
+  return Packet4cf(_mm256_blend_ps(a.v,pset1<Packet4cf>(b).v,1|2));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cd pinsertfirst(const Packet2cd& a, std::complex<double> b)
+{
+  return Packet2cd(_mm256_blend_pd(a.v,pset1<Packet2cd>(b).v,1|2));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4cf pinsertlast(const Packet4cf& a, std::complex<float> b)
+{
+  return Packet4cf(_mm256_blend_ps(a.v,pset1<Packet4cf>(b).v,(1<<7)|(1<<6)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cd pinsertlast(const Packet2cd& a, std::complex<double> b)
+{
+  return Packet2cd(_mm256_blend_pd(a.v,pset1<Packet2cd>(b).v,(1<<3)|(1<<2)));
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_COMPLEX_AVX_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/AVX/MathFunctions.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/AVX/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AVX/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AVX/MathFunctions.h
@@ -0,0 +1,439 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Pedro Gonnet (pedro.gonnet@gmail.com)
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_MATH_FUNCTIONS_AVX_H
+#define EIGEN_MATH_FUNCTIONS_AVX_H
+
+/* The sin, cos, exp, and log functions of this file are loosely derived from
+ * Julien Pommier's sse math library: http://gruntthepeon.free.fr/ssemath/
+ */
+
+namespace Eigen {
+
+namespace internal {
+
+inline Packet8i pshiftleft(Packet8i v, int n)
+{
+#ifdef EIGEN_VECTORIZE_AVX2
+  return _mm256_slli_epi32(v, n);
+#else
+  __m128i lo = _mm_slli_epi32(_mm256_extractf128_si256(v, 0), n);
+  __m128i hi = _mm_slli_epi32(_mm256_extractf128_si256(v, 1), n);
+  return _mm256_insertf128_si256(_mm256_castsi128_si256(lo), (hi), 1);
+#endif
+}
+
+inline Packet8f pshiftright(Packet8f v, int n)
+{
+#ifdef EIGEN_VECTORIZE_AVX2
+  return _mm256_cvtepi32_ps(_mm256_srli_epi32(_mm256_castps_si256(v), n));
+#else
+  __m128i lo = _mm_srli_epi32(_mm256_extractf128_si256(_mm256_castps_si256(v), 0), n);
+  __m128i hi = _mm_srli_epi32(_mm256_extractf128_si256(_mm256_castps_si256(v), 1), n);
+  return _mm256_cvtepi32_ps(_mm256_insertf128_si256(_mm256_castsi128_si256(lo), (hi), 1));
+#endif
+}
+
+// Sine function
+// Computes sin(x) by wrapping x to the interval [-Pi/4,3*Pi/4] and
+// evaluating interpolants in [-Pi/4,Pi/4] or [Pi/4,3*Pi/4]. The interpolants
+// are (anti-)symmetric and thus have only odd/even coefficients
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+psin<Packet8f>(const Packet8f& _x) {
+  Packet8f x = _x;
+
+  // Some useful values.
+  _EIGEN_DECLARE_CONST_Packet8i(one, 1);
+  _EIGEN_DECLARE_CONST_Packet8f(one, 1.0f);
+  _EIGEN_DECLARE_CONST_Packet8f(two, 2.0f);
+  _EIGEN_DECLARE_CONST_Packet8f(one_over_four, 0.25f);
+  _EIGEN_DECLARE_CONST_Packet8f(one_over_pi, 3.183098861837907e-01f);
+  _EIGEN_DECLARE_CONST_Packet8f(neg_pi_first, -3.140625000000000e+00f);
+  _EIGEN_DECLARE_CONST_Packet8f(neg_pi_second, -9.670257568359375e-04f);
+  _EIGEN_DECLARE_CONST_Packet8f(neg_pi_third, -6.278329571784980e-07f);
+  _EIGEN_DECLARE_CONST_Packet8f(four_over_pi, 1.273239544735163e+00f);
+
+  // Map x from [-Pi/4,3*Pi/4] to z in [-1,3] and subtract the shifted period.
+  Packet8f z = pmul(x, p8f_one_over_pi);
+  Packet8f shift = _mm256_floor_ps(padd(z, p8f_one_over_four));
+  x = pmadd(shift, p8f_neg_pi_first, x);
+  x = pmadd(shift, p8f_neg_pi_second, x);
+  x = pmadd(shift, p8f_neg_pi_third, x);
+  z = pmul(x, p8f_four_over_pi);
+
+  // Make a mask for the entries that need flipping, i.e. wherever the shift
+  // is odd.
+  Packet8i shift_ints = _mm256_cvtps_epi32(shift);
+  Packet8i shift_isodd = _mm256_castps_si256(_mm256_and_ps(_mm256_castsi256_ps(shift_ints), _mm256_castsi256_ps(p8i_one)));
+  Packet8i sign_flip_mask = pshiftleft(shift_isodd, 31);
+
+  // Create a mask for which interpolant to use, i.e. if z > 1, then the mask
+  // is set to ones for that entry.
+  Packet8f ival_mask = _mm256_cmp_ps(z, p8f_one, _CMP_GT_OQ);
+
+  // Evaluate the polynomial for the interval [1,3] in z.
+  _EIGEN_DECLARE_CONST_Packet8f(coeff_right_0, 9.999999724233232e-01f);
+  _EIGEN_DECLARE_CONST_Packet8f(coeff_right_2, -3.084242535619928e-01f);
+  _EIGEN_DECLARE_CONST_Packet8f(coeff_right_4, 1.584991525700324e-02f);
+  _EIGEN_DECLARE_CONST_Packet8f(coeff_right_6, -3.188805084631342e-04f);
+  Packet8f z_minus_two = psub(z, p8f_two);
+  Packet8f z_minus_two2 = pmul(z_minus_two, z_minus_two);
+  Packet8f right = pmadd(p8f_coeff_right_6, z_minus_two2, p8f_coeff_right_4);
+  right = pmadd(right, z_minus_two2, p8f_coeff_right_2);
+  right = pmadd(right, z_minus_two2, p8f_coeff_right_0);
+
+  // Evaluate the polynomial for the interval [-1,1] in z.
+  _EIGEN_DECLARE_CONST_Packet8f(coeff_left_1, 7.853981525427295e-01f);
+  _EIGEN_DECLARE_CONST_Packet8f(coeff_left_3, -8.074536727092352e-02f);
+  _EIGEN_DECLARE_CONST_Packet8f(coeff_left_5, 2.489871967827018e-03f);
+  _EIGEN_DECLARE_CONST_Packet8f(coeff_left_7, -3.587725841214251e-05f);
+  Packet8f z2 = pmul(z, z);
+  Packet8f left = pmadd(p8f_coeff_left_7, z2, p8f_coeff_left_5);
+  left = pmadd(left, z2, p8f_coeff_left_3);
+  left = pmadd(left, z2, p8f_coeff_left_1);
+  left = pmul(left, z);
+
+  // Assemble the results, i.e. select the left and right polynomials.
+  left = _mm256_andnot_ps(ival_mask, left);
+  right = _mm256_and_ps(ival_mask, right);
+  Packet8f res = _mm256_or_ps(left, right);
+
+  // Flip the sign on the odd intervals and return the result.
+  res = _mm256_xor_ps(res, _mm256_castsi256_ps(sign_flip_mask));
+  return res;
+}
+
+// Natural logarithm
+// Computes log(x) as log(2^e * m) = C*e + log(m), where the constant C =log(2)
+// and m is in the range [sqrt(1/2),sqrt(2)). In this range, the logarithm can
+// be easily approximated by a polynomial centered on m=1 for stability.
+// TODO(gonnet): Further reduce the interval allowing for lower-degree
+//               polynomial interpolants -> ... -> profit!
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+plog<Packet8f>(const Packet8f& _x) {
+  Packet8f x = _x;
+  _EIGEN_DECLARE_CONST_Packet8f(1, 1.0f);
+  _EIGEN_DECLARE_CONST_Packet8f(half, 0.5f);
+  _EIGEN_DECLARE_CONST_Packet8f(126f, 126.0f);
+
+  _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(inv_mant_mask, ~0x7f800000);
+
+  // The smallest non denormalized float number.
+  _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(min_norm_pos, 0x00800000);
+  _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(minus_inf, 0xff800000);
+
+  // Polynomial coefficients.
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_SQRTHF, 0.707106781186547524f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p0, 7.0376836292E-2f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p1, -1.1514610310E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p2, 1.1676998740E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p3, -1.2420140846E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p4, +1.4249322787E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p5, -1.6668057665E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p6, +2.0000714765E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p7, -2.4999993993E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_p8, +3.3333331174E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_q1, -2.12194440e-4f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_log_q2, 0.693359375f);
+
+  Packet8f invalid_mask = _mm256_cmp_ps(x, _mm256_setzero_ps(), _CMP_NGE_UQ); // not greater equal is true if x is NaN
+  Packet8f iszero_mask = _mm256_cmp_ps(x, _mm256_setzero_ps(), _CMP_EQ_OQ);
+
+  // Truncate input values to the minimum positive normal.
+  x = pmax(x, p8f_min_norm_pos);
+
+  Packet8f emm0 = pshiftright(x,23);
+  Packet8f e = _mm256_sub_ps(emm0, p8f_126f);
+
+  // Set the exponents to -1, i.e. x are in the range [0.5,1).
+  x = _mm256_and_ps(x, p8f_inv_mant_mask);
+  x = _mm256_or_ps(x, p8f_half);
+
+  // part2: Shift the inputs from the range [0.5,1) to [sqrt(1/2),sqrt(2))
+  // and shift by -1. The values are then centered around 0, which improves
+  // the stability of the polynomial evaluation.
+  //   if( x < SQRTHF ) {
+  //     e -= 1;
+  //     x = x + x - 1.0;
+  //   } else { x = x - 1.0; }
+  Packet8f mask = _mm256_cmp_ps(x, p8f_cephes_SQRTHF, _CMP_LT_OQ);
+  Packet8f tmp = _mm256_and_ps(x, mask);
+  x = psub(x, p8f_1);
+  e = psub(e, _mm256_and_ps(p8f_1, mask));
+  x = padd(x, tmp);
+
+  Packet8f x2 = pmul(x, x);
+  Packet8f x3 = pmul(x2, x);
+
+  // Evaluate the polynomial approximant of degree 8 in three parts, probably
+  // to improve instruction-level parallelism.
+  Packet8f y, y1, y2;
+  y = pmadd(p8f_cephes_log_p0, x, p8f_cephes_log_p1);
+  y1 = pmadd(p8f_cephes_log_p3, x, p8f_cephes_log_p4);
+  y2 = pmadd(p8f_cephes_log_p6, x, p8f_cephes_log_p7);
+  y = pmadd(y, x, p8f_cephes_log_p2);
+  y1 = pmadd(y1, x, p8f_cephes_log_p5);
+  y2 = pmadd(y2, x, p8f_cephes_log_p8);
+  y = pmadd(y, x3, y1);
+  y = pmadd(y, x3, y2);
+  y = pmul(y, x3);
+
+  // Add the logarithm of the exponent back to the result of the interpolation.
+  y1 = pmul(e, p8f_cephes_log_q1);
+  tmp = pmul(x2, p8f_half);
+  y = padd(y, y1);
+  x = psub(x, tmp);
+  y2 = pmul(e, p8f_cephes_log_q2);
+  x = padd(x, y);
+  x = padd(x, y2);
+
+  // Filter out invalid inputs, i.e. negative arg will be NAN, 0 will be -INF.
+  return _mm256_or_ps(
+      _mm256_andnot_ps(iszero_mask, _mm256_or_ps(x, invalid_mask)),
+      _mm256_and_ps(iszero_mask, p8f_minus_inf));
+}
+
+// Exponential function. Works by writing "x = m*log(2) + r" where
+// "m = floor(x/log(2)+1/2)" and "r" is the remainder. The result is then
+// "exp(x) = 2^m*exp(r)" where exp(r) is in the range [-1,1).
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+pexp<Packet8f>(const Packet8f& _x) {
+  _EIGEN_DECLARE_CONST_Packet8f(1, 1.0f);
+  _EIGEN_DECLARE_CONST_Packet8f(half, 0.5f);
+  _EIGEN_DECLARE_CONST_Packet8f(127, 127.0f);
+
+  _EIGEN_DECLARE_CONST_Packet8f(exp_hi, 88.3762626647950f);
+  _EIGEN_DECLARE_CONST_Packet8f(exp_lo, -88.3762626647949f);
+
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_LOG2EF, 1.44269504088896341f);
+
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p0, 1.9875691500E-4f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p1, 1.3981999507E-3f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p2, 8.3334519073E-3f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p3, 4.1665795894E-2f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p4, 1.6666665459E-1f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p5, 5.0000001201E-1f);
+
+  // Clamp x.
+  Packet8f x = pmax(pmin(_x, p8f_exp_hi), p8f_exp_lo);
+
+  // Express exp(x) as exp(m*ln(2) + r), start by extracting
+  // m = floor(x/ln(2) + 0.5).
+  Packet8f m = _mm256_floor_ps(pmadd(x, p8f_cephes_LOG2EF, p8f_half));
+
+// Get r = x - m*ln(2). If no FMA instructions are available, m*ln(2) is
+// subtracted out in two parts, m*C1+m*C2 = m*ln(2), to avoid accumulating
+// truncation errors. Note that we don't use the "pmadd" function here to
+// ensure that a precision-preserving FMA instruction is used.
+#ifdef EIGEN_VECTORIZE_FMA
+  _EIGEN_DECLARE_CONST_Packet8f(nln2, -0.6931471805599453f);
+  Packet8f r = _mm256_fmadd_ps(m, p8f_nln2, x);
+#else
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_exp_C1, 0.693359375f);
+  _EIGEN_DECLARE_CONST_Packet8f(cephes_exp_C2, -2.12194440e-4f);
+  Packet8f r = psub(x, pmul(m, p8f_cephes_exp_C1));
+  r = psub(r, pmul(m, p8f_cephes_exp_C2));
+#endif
+
+  Packet8f r2 = pmul(r, r);
+
+  // TODO(gonnet): Split into odd/even polynomials and try to exploit
+  //               instruction-level parallelism.
+  Packet8f y = p8f_cephes_exp_p0;
+  y = pmadd(y, r, p8f_cephes_exp_p1);
+  y = pmadd(y, r, p8f_cephes_exp_p2);
+  y = pmadd(y, r, p8f_cephes_exp_p3);
+  y = pmadd(y, r, p8f_cephes_exp_p4);
+  y = pmadd(y, r, p8f_cephes_exp_p5);
+  y = pmadd(y, r2, r);
+  y = padd(y, p8f_1);
+
+  // Build emm0 = 2^m.
+  Packet8i emm0 = _mm256_cvttps_epi32(padd(m, p8f_127));
+  emm0 = pshiftleft(emm0, 23);
+
+  // Return 2^m * exp(r).
+  return pmax(pmul(y, _mm256_castsi256_ps(emm0)), _x);
+}
+
+// Hyperbolic Tangent function.
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+ptanh<Packet8f>(const Packet8f& x) {
+  return internal::generic_fast_tanh_float(x);
+}
+
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet4d
+pexp<Packet4d>(const Packet4d& _x) {
+  Packet4d x = _x;
+
+  _EIGEN_DECLARE_CONST_Packet4d(1, 1.0);
+  _EIGEN_DECLARE_CONST_Packet4d(2, 2.0);
+  _EIGEN_DECLARE_CONST_Packet4d(half, 0.5);
+
+  _EIGEN_DECLARE_CONST_Packet4d(exp_hi, 709.437);
+  _EIGEN_DECLARE_CONST_Packet4d(exp_lo, -709.436139303);
+
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_LOG2EF, 1.4426950408889634073599);
+
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_p0, 1.26177193074810590878e-4);
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_p1, 3.02994407707441961300e-2);
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_p2, 9.99999999999999999910e-1);
+
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_q0, 3.00198505138664455042e-6);
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_q1, 2.52448340349684104192e-3);
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_q2, 2.27265548208155028766e-1);
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_q3, 2.00000000000000000009e0);
+
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_C1, 0.693145751953125);
+  _EIGEN_DECLARE_CONST_Packet4d(cephes_exp_C2, 1.42860682030941723212e-6);
+  _EIGEN_DECLARE_CONST_Packet4i(1023, 1023);
+
+  Packet4d tmp, fx;
+
+  // clamp x
+  x = pmax(pmin(x, p4d_exp_hi), p4d_exp_lo);
+  // Express exp(x) as exp(g + n*log(2)).
+  fx = pmadd(p4d_cephes_LOG2EF, x, p4d_half);
+
+  // Get the integer modulus of log(2), i.e. the "n" described above.
+  fx = _mm256_floor_pd(fx);
+
+  // Get the remainder modulo log(2), i.e. the "g" described above. Subtract
+  // n*log(2) out in two steps, i.e. n*C1 + n*C2, C1+C2=log2 to get the last
+  // digits right.
+  tmp = pmul(fx, p4d_cephes_exp_C1);
+  Packet4d z = pmul(fx, p4d_cephes_exp_C2);
+  x = psub(x, tmp);
+  x = psub(x, z);
+
+  Packet4d x2 = pmul(x, x);
+
+  // Evaluate the numerator polynomial of the rational interpolant.
+  Packet4d px = p4d_cephes_exp_p0;
+  px = pmadd(px, x2, p4d_cephes_exp_p1);
+  px = pmadd(px, x2, p4d_cephes_exp_p2);
+  px = pmul(px, x);
+
+  // Evaluate the denominator polynomial of the rational interpolant.
+  Packet4d qx = p4d_cephes_exp_q0;
+  qx = pmadd(qx, x2, p4d_cephes_exp_q1);
+  qx = pmadd(qx, x2, p4d_cephes_exp_q2);
+  qx = pmadd(qx, x2, p4d_cephes_exp_q3);
+
+  // I don't really get this bit, copied from the SSE2 routines, so...
+  // TODO(gonnet): Figure out what is going on here, perhaps find a better
+  // rational interpolant?
+  x = _mm256_div_pd(px, psub(qx, px));
+  x = pmadd(p4d_2, x, p4d_1);
+
+  // Build e=2^n by constructing the exponents in a 128-bit vector and
+  // shifting them to where they belong in double-precision values.
+  __m128i emm0 = _mm256_cvtpd_epi32(fx);
+  emm0 = _mm_add_epi32(emm0, p4i_1023);
+  emm0 = _mm_shuffle_epi32(emm0, _MM_SHUFFLE(3, 1, 2, 0));
+  __m128i lo = _mm_slli_epi64(emm0, 52);
+  __m128i hi = _mm_slli_epi64(_mm_srli_epi64(emm0, 32), 52);
+  __m256i e = _mm256_insertf128_si256(_mm256_setzero_si256(), lo, 0);
+  e = _mm256_insertf128_si256(e, hi, 1);
+
+  // Construct the result 2^n * exp(g) = e * x. The max is used to catch
+  // non-finite values in the input.
+  return pmax(pmul(x, _mm256_castsi256_pd(e)), _x);
+}
+
+// Functions for sqrt.
+// The EIGEN_FAST_MATH version uses the _mm_rsqrt_ps approximation and one step
+// of Newton's method, at a cost of 1-2 bits of precision as opposed to the
+// exact solution. It does not handle +inf, or denormalized numbers correctly.
+// The main advantage of this approach is not just speed, but also the fact that
+// it can be inlined and pipelined with other computations, further reducing its
+// effective latency. This is similar to Quake3's fast inverse square root.
+// For detail see here: http://www.beyond3d.com/content/articles/8/
+#if EIGEN_FAST_MATH
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+psqrt<Packet8f>(const Packet8f& _x) {
+  Packet8f half = pmul(_x, pset1<Packet8f>(.5f));
+  Packet8f denormal_mask = _mm256_and_ps(
+      _mm256_cmp_ps(_x, pset1<Packet8f>((std::numeric_limits<float>::min)()),
+                    _CMP_LT_OQ),
+      _mm256_cmp_ps(_x, _mm256_setzero_ps(), _CMP_GE_OQ));
+
+  // Compute approximate reciprocal sqrt.
+  Packet8f x = _mm256_rsqrt_ps(_x);
+  // Do a single step of Newton's iteration.
+  x = pmul(x, psub(pset1<Packet8f>(1.5f), pmul(half, pmul(x,x))));
+  // Flush results for denormals to zero.
+  return _mm256_andnot_ps(denormal_mask, pmul(_x,x));
+}
+#else
+template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet8f psqrt<Packet8f>(const Packet8f& x) {
+  return _mm256_sqrt_ps(x);
+}
+#endif
+template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4d psqrt<Packet4d>(const Packet4d& x) {
+  return _mm256_sqrt_pd(x);
+}
+#if EIGEN_FAST_MATH
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet8f prsqrt<Packet8f>(const Packet8f& _x) {
+  _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(inf, 0x7f800000);
+  _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(nan, 0x7fc00000);
+  _EIGEN_DECLARE_CONST_Packet8f(one_point_five, 1.5f);
+  _EIGEN_DECLARE_CONST_Packet8f(minus_half, -0.5f);
+  _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(flt_min, 0x00800000);
+
+  Packet8f neg_half = pmul(_x, p8f_minus_half);
+
+  // select only the inverse sqrt of positive normal inputs (denormals are
+  // flushed to zero and cause infs as well).
+  Packet8f le_zero_mask = _mm256_cmp_ps(_x, p8f_flt_min, _CMP_LT_OQ);
+  Packet8f x = _mm256_andnot_ps(le_zero_mask, _mm256_rsqrt_ps(_x));
+
+  // Fill in NaNs and Infs for the negative/zero entries.
+  Packet8f neg_mask = _mm256_cmp_ps(_x, _mm256_setzero_ps(), _CMP_LT_OQ);
+  Packet8f zero_mask = _mm256_andnot_ps(neg_mask, le_zero_mask);
+  Packet8f infs_and_nans = _mm256_or_ps(_mm256_and_ps(neg_mask, p8f_nan),
+                                        _mm256_and_ps(zero_mask, p8f_inf));
+
+  // Do a single step of Newton's iteration.
+  x = pmul(x, pmadd(neg_half, pmul(x, x), p8f_one_point_five));
+
+  // Insert NaNs and Infs in all the right places.
+  return _mm256_or_ps(x, infs_and_nans);
+}
+
+#else
+template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet8f prsqrt<Packet8f>(const Packet8f& x) {
+  _EIGEN_DECLARE_CONST_Packet8f(one, 1.0f);
+  return _mm256_div_ps(p8f_one, _mm256_sqrt_ps(x));
+}
+#endif
+
+template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4d prsqrt<Packet4d>(const Packet4d& x) {
+  _EIGEN_DECLARE_CONST_Packet4d(one, 1.0);
+  return _mm256_div_pd(p4d_one, _mm256_sqrt_pd(x));
+}
+
+
+}  // end namespace internal
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_MATH_FUNCTIONS_AVX_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/AVX/PacketMath.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/AVX/PacketMath.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AVX/PacketMath.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AVX/PacketMath.h
@@ -0,0 +1,633 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner (benoit.steiner.goog@gmail.com)
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_PACKET_MATH_AVX_H
+#define EIGEN_PACKET_MATH_AVX_H
+
+namespace Eigen {
+
+namespace internal {
+
+#ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
+#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 8
+#endif
+
+#ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
+#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS (2*sizeof(void*))
+#endif
+
+#ifdef __FMA__
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#endif
+#endif
+
+typedef __m256  Packet8f;
+typedef __m256i Packet8i;
+typedef __m256d Packet4d;
+
+template<> struct is_arithmetic<__m256>  { enum { value = true }; };
+template<> struct is_arithmetic<__m256i> { enum { value = true }; };
+template<> struct is_arithmetic<__m256d> { enum { value = true }; };
+
+#define _EIGEN_DECLARE_CONST_Packet8f(NAME,X) \
+  const Packet8f p8f_##NAME = pset1<Packet8f>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet4d(NAME,X) \
+  const Packet4d p4d_##NAME = pset1<Packet4d>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(NAME,X) \
+  const Packet8f p8f_##NAME = _mm256_castsi256_ps(pset1<Packet8i>(X))
+
+#define _EIGEN_DECLARE_CONST_Packet8i(NAME,X) \
+  const Packet8i p8i_##NAME = pset1<Packet8i>(X)
+
+// Use the packet_traits defined in AVX512/PacketMath.h instead if we're going
+// to leverage AVX512 instructions.
+#ifndef EIGEN_VECTORIZE_AVX512
+template<> struct packet_traits<float>  : default_packet_traits
+{
+  typedef Packet8f type;
+  typedef Packet4f half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=8,
+    HasHalfPacket = 1,
+
+    HasDiv  = 1,
+    HasSin  = EIGEN_FAST_MATH,
+    HasCos  = 0,
+    HasLog  = 1,
+    HasExp  = 1,
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasTanh  = EIGEN_FAST_MATH,
+    HasBlend = 1,
+    HasRound = 1,
+    HasFloor = 1,
+    HasCeil = 1
+  };
+};
+template<> struct packet_traits<double> : default_packet_traits
+{
+  typedef Packet4d type;
+  typedef Packet2d half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=4,
+    HasHalfPacket = 1,
+
+    HasDiv  = 1,
+    HasExp  = 1,
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasBlend = 1,
+    HasRound = 1,
+    HasFloor = 1,
+    HasCeil = 1
+  };
+};
+#endif
+
+template<> struct scalar_div_cost<float,true> { enum { value = 14 }; };
+template<> struct scalar_div_cost<double,true> { enum { value = 16 }; };
+
+/* Proper support for integers is only provided by AVX2. In the meantime, we'll
+   use SSE instructions and packets to deal with integers.
+template<> struct packet_traits<int>    : default_packet_traits
+{
+  typedef Packet8i type;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=8
+  };
+};
+*/
+
+template<> struct unpacket_traits<Packet8f> { typedef float  type; typedef Packet4f half; enum {size=8, alignment=Aligned32}; };
+template<> struct unpacket_traits<Packet4d> { typedef double type; typedef Packet2d half; enum {size=4, alignment=Aligned32}; };
+template<> struct unpacket_traits<Packet8i> { typedef int    type; typedef Packet4i half; enum {size=8, alignment=Aligned32}; };
+
+template<> EIGEN_STRONG_INLINE Packet8f pset1<Packet8f>(const float&  from) { return _mm256_set1_ps(from); }
+template<> EIGEN_STRONG_INLINE Packet4d pset1<Packet4d>(const double& from) { return _mm256_set1_pd(from); }
+template<> EIGEN_STRONG_INLINE Packet8i pset1<Packet8i>(const int&    from) { return _mm256_set1_epi32(from); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pload1<Packet8f>(const float*  from) { return _mm256_broadcast_ss(from); }
+template<> EIGEN_STRONG_INLINE Packet4d pload1<Packet4d>(const double* from) { return _mm256_broadcast_sd(from); }
+
+template<> EIGEN_STRONG_INLINE Packet8f plset<Packet8f>(const float& a) { return _mm256_add_ps(_mm256_set1_ps(a), _mm256_set_ps(7.0,6.0,5.0,4.0,3.0,2.0,1.0,0.0)); }
+template<> EIGEN_STRONG_INLINE Packet4d plset<Packet4d>(const double& a) { return _mm256_add_pd(_mm256_set1_pd(a), _mm256_set_pd(3.0,2.0,1.0,0.0)); }
+
+template<> EIGEN_STRONG_INLINE Packet8f padd<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_add_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d padd<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_add_pd(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet8f psub<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_sub_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d psub<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_sub_pd(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pnegate(const Packet8f& a)
+{
+  return _mm256_sub_ps(_mm256_set1_ps(0.0),a);
+}
+template<> EIGEN_STRONG_INLINE Packet4d pnegate(const Packet4d& a)
+{
+  return _mm256_sub_pd(_mm256_set1_pd(0.0),a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8f pconj(const Packet8f& a) { return a; }
+template<> EIGEN_STRONG_INLINE Packet4d pconj(const Packet4d& a) { return a; }
+template<> EIGEN_STRONG_INLINE Packet8i pconj(const Packet8i& a) { return a; }
+
+template<> EIGEN_STRONG_INLINE Packet8f pmul<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_mul_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d pmul<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_mul_pd(a,b); }
+
+
+template<> EIGEN_STRONG_INLINE Packet8f pdiv<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_div_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d pdiv<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_div_pd(a,b); }
+template<> EIGEN_STRONG_INLINE Packet8i pdiv<Packet8i>(const Packet8i& /*a*/, const Packet8i& /*b*/)
+{ eigen_assert(false && "packet integer division are not supported by AVX");
+  return pset1<Packet8i>(0);
+}
+
+#ifdef __FMA__
+template<> EIGEN_STRONG_INLINE Packet8f pmadd(const Packet8f& a, const Packet8f& b, const Packet8f& c) {
+#if ( EIGEN_COMP_GNUC_STRICT || (EIGEN_COMP_CLANG && (EIGEN_COMP_CLANG<308)) )
+  // clang stupidly generates a vfmadd213ps instruction plus some vmovaps on registers,
+  // and gcc stupidly generates a vfmadd132ps instruction,
+  // so let's enforce it to generate a vfmadd231ps instruction since the most common use case is to accumulate
+  // the result of the product.
+  Packet8f res = c;
+  __asm__("vfmadd231ps %[a], %[b], %[c]" : [c] "+x" (res) : [a] "x" (a), [b] "x" (b));
+  return res;
+#else
+  return _mm256_fmadd_ps(a,b,c);
+#endif
+}
+template<> EIGEN_STRONG_INLINE Packet4d pmadd(const Packet4d& a, const Packet4d& b, const Packet4d& c) {
+#if ( EIGEN_COMP_GNUC_STRICT || (EIGEN_COMP_CLANG && (EIGEN_COMP_CLANG<308)) )
+  // see above
+  Packet4d res = c;
+  __asm__("vfmadd231pd %[a], %[b], %[c]" : [c] "+x" (res) : [a] "x" (a), [b] "x" (b));
+  return res;
+#else
+  return _mm256_fmadd_pd(a,b,c);
+#endif
+}
+#endif
+
+template<> EIGEN_STRONG_INLINE Packet8f pmin<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_min_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d pmin<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_min_pd(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pmax<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_max_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d pmax<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_max_pd(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pround<Packet8f>(const Packet8f& a) { return _mm256_round_ps(a, _MM_FROUND_CUR_DIRECTION); }
+template<> EIGEN_STRONG_INLINE Packet4d pround<Packet4d>(const Packet4d& a) { return _mm256_round_pd(a, _MM_FROUND_CUR_DIRECTION); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pceil<Packet8f>(const Packet8f& a) { return _mm256_ceil_ps(a); }
+template<> EIGEN_STRONG_INLINE Packet4d pceil<Packet4d>(const Packet4d& a) { return _mm256_ceil_pd(a); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pfloor<Packet8f>(const Packet8f& a) { return _mm256_floor_ps(a); }
+template<> EIGEN_STRONG_INLINE Packet4d pfloor<Packet4d>(const Packet4d& a) { return _mm256_floor_pd(a); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pand<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_and_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d pand<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_and_pd(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet8f por<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_or_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d por<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_or_pd(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pxor<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_xor_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d pxor<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_xor_pd(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pandnot<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_andnot_ps(a,b); }
+template<> EIGEN_STRONG_INLINE Packet4d pandnot<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_andnot_pd(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet8f pload<Packet8f>(const float*   from) { EIGEN_DEBUG_ALIGNED_LOAD return _mm256_load_ps(from); }
+template<> EIGEN_STRONG_INLINE Packet4d pload<Packet4d>(const double*  from) { EIGEN_DEBUG_ALIGNED_LOAD return _mm256_load_pd(from); }
+template<> EIGEN_STRONG_INLINE Packet8i pload<Packet8i>(const int*     from) { EIGEN_DEBUG_ALIGNED_LOAD return _mm256_load_si256(reinterpret_cast<const __m256i*>(from)); }
+
+template<> EIGEN_STRONG_INLINE Packet8f ploadu<Packet8f>(const float* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm256_loadu_ps(from); }
+template<> EIGEN_STRONG_INLINE Packet4d ploadu<Packet4d>(const double* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm256_loadu_pd(from); }
+template<> EIGEN_STRONG_INLINE Packet8i ploadu<Packet8i>(const int* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm256_loadu_si256(reinterpret_cast<const __m256i*>(from)); }
+
+// Loads 4 floats from memory a returns the packet {a0, a0  a1, a1, a2, a2, a3, a3}
+template<> EIGEN_STRONG_INLINE Packet8f ploaddup<Packet8f>(const float* from)
+{
+  // TODO try to find a way to avoid the need of a temporary register
+//   Packet8f tmp  = _mm256_castps128_ps256(_mm_loadu_ps(from));
+//   tmp = _mm256_insertf128_ps(tmp, _mm_movehl_ps(_mm256_castps256_ps128(tmp),_mm256_castps256_ps128(tmp)), 1);
+//   return _mm256_unpacklo_ps(tmp,tmp);
+  
+  // _mm256_insertf128_ps is very slow on Haswell, thus:
+  Packet8f tmp = _mm256_broadcast_ps((const __m128*)(const void*)from);
+  // mimic an "inplace" permutation of the lower 128bits using a blend
+  tmp = _mm256_blend_ps(tmp,_mm256_castps128_ps256(_mm_permute_ps( _mm256_castps256_ps128(tmp), _MM_SHUFFLE(1,0,1,0))), 15);
+  // then we can perform a consistent permutation on the global register to get everything in shape:
+  return  _mm256_permute_ps(tmp, _MM_SHUFFLE(3,3,2,2));
+}
+// Loads 2 doubles from memory a returns the packet {a0, a0  a1, a1}
+template<> EIGEN_STRONG_INLINE Packet4d ploaddup<Packet4d>(const double* from)
+{
+  Packet4d tmp = _mm256_broadcast_pd((const __m128d*)(const void*)from);
+  return  _mm256_permute_pd(tmp, 3<<2);
+}
+
+// Loads 2 floats from memory a returns the packet {a0, a0  a0, a0, a1, a1, a1, a1}
+template<> EIGEN_STRONG_INLINE Packet8f ploadquad<Packet8f>(const float* from)
+{
+  Packet8f tmp = _mm256_castps128_ps256(_mm_broadcast_ss(from));
+  return _mm256_insertf128_ps(tmp, _mm_broadcast_ss(from+1), 1);
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<float>(float*   to, const Packet8f& from) { EIGEN_DEBUG_ALIGNED_STORE _mm256_store_ps(to, from); }
+template<> EIGEN_STRONG_INLINE void pstore<double>(double* to, const Packet4d& from) { EIGEN_DEBUG_ALIGNED_STORE _mm256_store_pd(to, from); }
+template<> EIGEN_STRONG_INLINE void pstore<int>(int*       to, const Packet8i& from) { EIGEN_DEBUG_ALIGNED_STORE _mm256_storeu_si256(reinterpret_cast<__m256i*>(to), from); }
+
+template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*   to, const Packet8f& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm256_storeu_ps(to, from); }
+template<> EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet4d& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm256_storeu_pd(to, from); }
+template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*       to, const Packet8i& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm256_storeu_si256(reinterpret_cast<__m256i*>(to), from); }
+
+// NOTE: leverage _mm256_i32gather_ps and _mm256_i32gather_pd if AVX2 instructions are available
+// NOTE: for the record the following seems to be slower: return _mm256_i32gather_ps(from, _mm256_set1_epi32(stride), 4);
+template<> EIGEN_DEVICE_FUNC inline Packet8f pgather<float, Packet8f>(const float* from, Index stride)
+{
+  return _mm256_set_ps(from[7*stride], from[6*stride], from[5*stride], from[4*stride],
+                       from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
+}
+template<> EIGEN_DEVICE_FUNC inline Packet4d pgather<double, Packet4d>(const double* from, Index stride)
+{
+  return _mm256_set_pd(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet8f>(float* to, const Packet8f& from, Index stride)
+{
+  __m128 low = _mm256_extractf128_ps(from, 0);
+  to[stride*0] = _mm_cvtss_f32(low);
+  to[stride*1] = _mm_cvtss_f32(_mm_shuffle_ps(low, low, 1));
+  to[stride*2] = _mm_cvtss_f32(_mm_shuffle_ps(low, low, 2));
+  to[stride*3] = _mm_cvtss_f32(_mm_shuffle_ps(low, low, 3));
+
+  __m128 high = _mm256_extractf128_ps(from, 1);
+  to[stride*4] = _mm_cvtss_f32(high);
+  to[stride*5] = _mm_cvtss_f32(_mm_shuffle_ps(high, high, 1));
+  to[stride*6] = _mm_cvtss_f32(_mm_shuffle_ps(high, high, 2));
+  to[stride*7] = _mm_cvtss_f32(_mm_shuffle_ps(high, high, 3));
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet4d>(double* to, const Packet4d& from, Index stride)
+{
+  __m128d low = _mm256_extractf128_pd(from, 0);
+  to[stride*0] = _mm_cvtsd_f64(low);
+  to[stride*1] = _mm_cvtsd_f64(_mm_shuffle_pd(low, low, 1));
+  __m128d high = _mm256_extractf128_pd(from, 1);
+  to[stride*2] = _mm_cvtsd_f64(high);
+  to[stride*3] = _mm_cvtsd_f64(_mm_shuffle_pd(high, high, 1));
+}
+
+template<> EIGEN_STRONG_INLINE void pstore1<Packet8f>(float* to, const float& a)
+{
+  Packet8f pa = pset1<Packet8f>(a);
+  pstore(to, pa);
+}
+template<> EIGEN_STRONG_INLINE void pstore1<Packet4d>(double* to, const double& a)
+{
+  Packet4d pa = pset1<Packet4d>(a);
+  pstore(to, pa);
+}
+template<> EIGEN_STRONG_INLINE void pstore1<Packet8i>(int* to, const int& a)
+{
+  Packet8i pa = pset1<Packet8i>(a);
+  pstore(to, pa);
+}
+
+#ifndef EIGEN_VECTORIZE_AVX512
+template<> EIGEN_STRONG_INLINE void prefetch<float>(const float*   addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
+template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
+template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*       addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
+#endif
+
+template<> EIGEN_STRONG_INLINE float  pfirst<Packet8f>(const Packet8f& a) {
+  return _mm_cvtss_f32(_mm256_castps256_ps128(a));
+}
+template<> EIGEN_STRONG_INLINE double pfirst<Packet4d>(const Packet4d& a) {
+  return _mm_cvtsd_f64(_mm256_castpd256_pd128(a));
+}
+template<> EIGEN_STRONG_INLINE int    pfirst<Packet8i>(const Packet8i& a) {
+  return _mm_cvtsi128_si32(_mm256_castsi256_si128(a));
+}
+
+
+template<> EIGEN_STRONG_INLINE Packet8f preverse(const Packet8f& a)
+{
+  __m256 tmp = _mm256_shuffle_ps(a,a,0x1b);
+  return _mm256_permute2f128_ps(tmp, tmp, 1);
+}
+template<> EIGEN_STRONG_INLINE Packet4d preverse(const Packet4d& a)
+{
+   __m256d tmp = _mm256_shuffle_pd(a,a,5);
+  return _mm256_permute2f128_pd(tmp, tmp, 1);
+
+  __m256d swap_halves = _mm256_permute2f128_pd(a,a,1);
+    return _mm256_permute_pd(swap_halves,5);
+}
+
+// pabs should be ok
+template<> EIGEN_STRONG_INLINE Packet8f pabs(const Packet8f& a)
+{
+  const Packet8f mask = _mm256_castsi256_ps(_mm256_setr_epi32(0x7FFFFFFF,0x7FFFFFFF,0x7FFFFFFF,0x7FFFFFFF,0x7FFFFFFF,0x7FFFFFFF,0x7FFFFFFF,0x7FFFFFFF));
+  return _mm256_and_ps(a,mask);
+}
+template<> EIGEN_STRONG_INLINE Packet4d pabs(const Packet4d& a)
+{
+  const Packet4d mask = _mm256_castsi256_pd(_mm256_setr_epi32(0xFFFFFFFF,0x7FFFFFFF,0xFFFFFFFF,0x7FFFFFFF,0xFFFFFFFF,0x7FFFFFFF,0xFFFFFFFF,0x7FFFFFFF));
+  return _mm256_and_pd(a,mask);
+}
+
+// preduxp should be ok
+// FIXME: why is this ok? why isn't the simply implementation working as expected?
+template<> EIGEN_STRONG_INLINE Packet8f preduxp<Packet8f>(const Packet8f* vecs)
+{
+    __m256 hsum1 = _mm256_hadd_ps(vecs[0], vecs[1]);
+    __m256 hsum2 = _mm256_hadd_ps(vecs[2], vecs[3]);
+    __m256 hsum3 = _mm256_hadd_ps(vecs[4], vecs[5]);
+    __m256 hsum4 = _mm256_hadd_ps(vecs[6], vecs[7]);
+
+    __m256 hsum5 = _mm256_hadd_ps(hsum1, hsum1);
+    __m256 hsum6 = _mm256_hadd_ps(hsum2, hsum2);
+    __m256 hsum7 = _mm256_hadd_ps(hsum3, hsum3);
+    __m256 hsum8 = _mm256_hadd_ps(hsum4, hsum4);
+
+    __m256 perm1 =  _mm256_permute2f128_ps(hsum5, hsum5, 0x23);
+    __m256 perm2 =  _mm256_permute2f128_ps(hsum6, hsum6, 0x23);
+    __m256 perm3 =  _mm256_permute2f128_ps(hsum7, hsum7, 0x23);
+    __m256 perm4 =  _mm256_permute2f128_ps(hsum8, hsum8, 0x23);
+
+    __m256 sum1 = _mm256_add_ps(perm1, hsum5);
+    __m256 sum2 = _mm256_add_ps(perm2, hsum6);
+    __m256 sum3 = _mm256_add_ps(perm3, hsum7);
+    __m256 sum4 = _mm256_add_ps(perm4, hsum8);
+
+    __m256 blend1 = _mm256_blend_ps(sum1, sum2, 0xcc);
+    __m256 blend2 = _mm256_blend_ps(sum3, sum4, 0xcc);
+
+    __m256 final = _mm256_blend_ps(blend1, blend2, 0xf0);
+    return final;
+}
+template<> EIGEN_STRONG_INLINE Packet4d preduxp<Packet4d>(const Packet4d* vecs)
+{
+ Packet4d tmp0, tmp1;
+
+  tmp0 = _mm256_hadd_pd(vecs[0], vecs[1]);
+  tmp0 = _mm256_add_pd(tmp0, _mm256_permute2f128_pd(tmp0, tmp0, 1));
+
+  tmp1 = _mm256_hadd_pd(vecs[2], vecs[3]);
+  tmp1 = _mm256_add_pd(tmp1, _mm256_permute2f128_pd(tmp1, tmp1, 1));
+
+  return _mm256_blend_pd(tmp0, tmp1, 0xC);
+}
+
+template<> EIGEN_STRONG_INLINE float predux<Packet8f>(const Packet8f& a)
+{
+  return predux(Packet4f(_mm_add_ps(_mm256_castps256_ps128(a),_mm256_extractf128_ps(a,1))));
+}
+template<> EIGEN_STRONG_INLINE double predux<Packet4d>(const Packet4d& a)
+{
+  return predux(Packet2d(_mm_add_pd(_mm256_castpd256_pd128(a),_mm256_extractf128_pd(a,1))));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f predux_downto4<Packet8f>(const Packet8f& a)
+{
+  return _mm_add_ps(_mm256_castps256_ps128(a),_mm256_extractf128_ps(a,1));
+}
+
+template<> EIGEN_STRONG_INLINE float predux_mul<Packet8f>(const Packet8f& a)
+{
+  Packet8f tmp;
+  tmp = _mm256_mul_ps(a, _mm256_permute2f128_ps(a,a,1));
+  tmp = _mm256_mul_ps(tmp, _mm256_shuffle_ps(tmp,tmp,_MM_SHUFFLE(1,0,3,2)));
+  return pfirst(_mm256_mul_ps(tmp, _mm256_shuffle_ps(tmp,tmp,1)));
+}
+template<> EIGEN_STRONG_INLINE double predux_mul<Packet4d>(const Packet4d& a)
+{
+  Packet4d tmp;
+  tmp = _mm256_mul_pd(a, _mm256_permute2f128_pd(a,a,1));
+  return pfirst(_mm256_mul_pd(tmp, _mm256_shuffle_pd(tmp,tmp,1)));
+}
+
+template<> EIGEN_STRONG_INLINE float predux_min<Packet8f>(const Packet8f& a)
+{
+  Packet8f tmp = _mm256_min_ps(a, _mm256_permute2f128_ps(a,a,1));
+  tmp = _mm256_min_ps(tmp, _mm256_shuffle_ps(tmp,tmp,_MM_SHUFFLE(1,0,3,2)));
+  return pfirst(_mm256_min_ps(tmp, _mm256_shuffle_ps(tmp,tmp,1)));
+}
+template<> EIGEN_STRONG_INLINE double predux_min<Packet4d>(const Packet4d& a)
+{
+  Packet4d tmp = _mm256_min_pd(a, _mm256_permute2f128_pd(a,a,1));
+  return pfirst(_mm256_min_pd(tmp, _mm256_shuffle_pd(tmp, tmp, 1)));
+}
+
+template<> EIGEN_STRONG_INLINE float predux_max<Packet8f>(const Packet8f& a)
+{
+  Packet8f tmp = _mm256_max_ps(a, _mm256_permute2f128_ps(a,a,1));
+  tmp = _mm256_max_ps(tmp, _mm256_shuffle_ps(tmp,tmp,_MM_SHUFFLE(1,0,3,2)));
+  return pfirst(_mm256_max_ps(tmp, _mm256_shuffle_ps(tmp,tmp,1)));
+}
+
+template<> EIGEN_STRONG_INLINE double predux_max<Packet4d>(const Packet4d& a)
+{
+  Packet4d tmp = _mm256_max_pd(a, _mm256_permute2f128_pd(a,a,1));
+  return pfirst(_mm256_max_pd(tmp, _mm256_shuffle_pd(tmp, tmp, 1)));
+}
+
+
+template<int Offset>
+struct palign_impl<Offset,Packet8f>
+{
+  static EIGEN_STRONG_INLINE void run(Packet8f& first, const Packet8f& second)
+  {
+    if (Offset==1)
+    {
+      first = _mm256_blend_ps(first, second, 1);
+      Packet8f tmp1 = _mm256_permute_ps (first, _MM_SHUFFLE(0,3,2,1));
+      Packet8f tmp2 = _mm256_permute2f128_ps (tmp1, tmp1, 1);
+      first = _mm256_blend_ps(tmp1, tmp2, 0x88);
+    }
+    else if (Offset==2)
+    {
+      first = _mm256_blend_ps(first, second, 3);
+      Packet8f tmp1 = _mm256_permute_ps (first, _MM_SHUFFLE(1,0,3,2));
+      Packet8f tmp2 = _mm256_permute2f128_ps (tmp1, tmp1, 1);
+      first = _mm256_blend_ps(tmp1, tmp2, 0xcc);
+    }
+    else if (Offset==3)
+    {
+      first = _mm256_blend_ps(first, second, 7);
+      Packet8f tmp1 = _mm256_permute_ps (first, _MM_SHUFFLE(2,1,0,3));
+      Packet8f tmp2 = _mm256_permute2f128_ps (tmp1, tmp1, 1);
+      first = _mm256_blend_ps(tmp1, tmp2, 0xee);
+    }
+    else if (Offset==4)
+    {
+      first = _mm256_blend_ps(first, second, 15);
+      Packet8f tmp1 = _mm256_permute_ps (first, _MM_SHUFFLE(3,2,1,0));
+      Packet8f tmp2 = _mm256_permute2f128_ps (tmp1, tmp1, 1);
+      first = _mm256_permute_ps(tmp2, _MM_SHUFFLE(3,2,1,0));
+    }
+    else if (Offset==5)
+    {
+      first = _mm256_blend_ps(first, second, 31);
+      first = _mm256_permute2f128_ps(first, first, 1);
+      Packet8f tmp = _mm256_permute_ps (first, _MM_SHUFFLE(0,3,2,1));
+      first = _mm256_permute2f128_ps(tmp, tmp, 1);
+      first = _mm256_blend_ps(tmp, first, 0x88);
+    }
+    else if (Offset==6)
+    {
+      first = _mm256_blend_ps(first, second, 63);
+      first = _mm256_permute2f128_ps(first, first, 1);
+      Packet8f tmp = _mm256_permute_ps (first, _MM_SHUFFLE(1,0,3,2));
+      first = _mm256_permute2f128_ps(tmp, tmp, 1);
+      first = _mm256_blend_ps(tmp, first, 0xcc);
+    }
+    else if (Offset==7)
+    {
+      first = _mm256_blend_ps(first, second, 127);
+      first = _mm256_permute2f128_ps(first, first, 1);
+      Packet8f tmp = _mm256_permute_ps (first, _MM_SHUFFLE(2,1,0,3));
+      first = _mm256_permute2f128_ps(tmp, tmp, 1);
+      first = _mm256_blend_ps(tmp, first, 0xee);
+    }
+  }
+};
+
+template<int Offset>
+struct palign_impl<Offset,Packet4d>
+{
+  static EIGEN_STRONG_INLINE void run(Packet4d& first, const Packet4d& second)
+  {
+    if (Offset==1)
+    {
+      first = _mm256_blend_pd(first, second, 1);
+      __m256d tmp = _mm256_permute_pd(first, 5);
+      first = _mm256_permute2f128_pd(tmp, tmp, 1);
+      first = _mm256_blend_pd(tmp, first, 0xA);
+    }
+    else if (Offset==2)
+    {
+      first = _mm256_blend_pd(first, second, 3);
+      first = _mm256_permute2f128_pd(first, first, 1);
+    }
+    else if (Offset==3)
+    {
+      first = _mm256_blend_pd(first, second, 7);
+      __m256d tmp = _mm256_permute_pd(first, 5);
+      first = _mm256_permute2f128_pd(tmp, tmp, 1);
+      first = _mm256_blend_pd(tmp, first, 5);
+    }
+  }
+};
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet8f,8>& kernel) {
+  __m256 T0 = _mm256_unpacklo_ps(kernel.packet[0], kernel.packet[1]);
+  __m256 T1 = _mm256_unpackhi_ps(kernel.packet[0], kernel.packet[1]);
+  __m256 T2 = _mm256_unpacklo_ps(kernel.packet[2], kernel.packet[3]);
+  __m256 T3 = _mm256_unpackhi_ps(kernel.packet[2], kernel.packet[3]);
+  __m256 T4 = _mm256_unpacklo_ps(kernel.packet[4], kernel.packet[5]);
+  __m256 T5 = _mm256_unpackhi_ps(kernel.packet[4], kernel.packet[5]);
+  __m256 T6 = _mm256_unpacklo_ps(kernel.packet[6], kernel.packet[7]);
+  __m256 T7 = _mm256_unpackhi_ps(kernel.packet[6], kernel.packet[7]);
+  __m256 S0 = _mm256_shuffle_ps(T0,T2,_MM_SHUFFLE(1,0,1,0));
+  __m256 S1 = _mm256_shuffle_ps(T0,T2,_MM_SHUFFLE(3,2,3,2));
+  __m256 S2 = _mm256_shuffle_ps(T1,T3,_MM_SHUFFLE(1,0,1,0));
+  __m256 S3 = _mm256_shuffle_ps(T1,T3,_MM_SHUFFLE(3,2,3,2));
+  __m256 S4 = _mm256_shuffle_ps(T4,T6,_MM_SHUFFLE(1,0,1,0));
+  __m256 S5 = _mm256_shuffle_ps(T4,T6,_MM_SHUFFLE(3,2,3,2));
+  __m256 S6 = _mm256_shuffle_ps(T5,T7,_MM_SHUFFLE(1,0,1,0));
+  __m256 S7 = _mm256_shuffle_ps(T5,T7,_MM_SHUFFLE(3,2,3,2));
+  kernel.packet[0] = _mm256_permute2f128_ps(S0, S4, 0x20);
+  kernel.packet[1] = _mm256_permute2f128_ps(S1, S5, 0x20);
+  kernel.packet[2] = _mm256_permute2f128_ps(S2, S6, 0x20);
+  kernel.packet[3] = _mm256_permute2f128_ps(S3, S7, 0x20);
+  kernel.packet[4] = _mm256_permute2f128_ps(S0, S4, 0x31);
+  kernel.packet[5] = _mm256_permute2f128_ps(S1, S5, 0x31);
+  kernel.packet[6] = _mm256_permute2f128_ps(S2, S6, 0x31);
+  kernel.packet[7] = _mm256_permute2f128_ps(S3, S7, 0x31);
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet8f,4>& kernel) {
+  __m256 T0 = _mm256_unpacklo_ps(kernel.packet[0], kernel.packet[1]);
+  __m256 T1 = _mm256_unpackhi_ps(kernel.packet[0], kernel.packet[1]);
+  __m256 T2 = _mm256_unpacklo_ps(kernel.packet[2], kernel.packet[3]);
+  __m256 T3 = _mm256_unpackhi_ps(kernel.packet[2], kernel.packet[3]);
+
+  __m256 S0 = _mm256_shuffle_ps(T0,T2,_MM_SHUFFLE(1,0,1,0));
+  __m256 S1 = _mm256_shuffle_ps(T0,T2,_MM_SHUFFLE(3,2,3,2));
+  __m256 S2 = _mm256_shuffle_ps(T1,T3,_MM_SHUFFLE(1,0,1,0));
+  __m256 S3 = _mm256_shuffle_ps(T1,T3,_MM_SHUFFLE(3,2,3,2));
+
+  kernel.packet[0] = _mm256_permute2f128_ps(S0, S1, 0x20);
+  kernel.packet[1] = _mm256_permute2f128_ps(S2, S3, 0x20);
+  kernel.packet[2] = _mm256_permute2f128_ps(S0, S1, 0x31);
+  kernel.packet[3] = _mm256_permute2f128_ps(S2, S3, 0x31);
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4d,4>& kernel) {
+  __m256d T0 = _mm256_shuffle_pd(kernel.packet[0], kernel.packet[1], 15);
+  __m256d T1 = _mm256_shuffle_pd(kernel.packet[0], kernel.packet[1], 0);
+  __m256d T2 = _mm256_shuffle_pd(kernel.packet[2], kernel.packet[3], 15);
+  __m256d T3 = _mm256_shuffle_pd(kernel.packet[2], kernel.packet[3], 0);
+
+  kernel.packet[1] = _mm256_permute2f128_pd(T0, T2, 32);
+  kernel.packet[3] = _mm256_permute2f128_pd(T0, T2, 49);
+  kernel.packet[0] = _mm256_permute2f128_pd(T1, T3, 32);
+  kernel.packet[2] = _mm256_permute2f128_pd(T1, T3, 49);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8f pblend(const Selector<8>& ifPacket, const Packet8f& thenPacket, const Packet8f& elsePacket) {
+  const __m256 zero = _mm256_setzero_ps();
+  const __m256 select = _mm256_set_ps(ifPacket.select[7], ifPacket.select[6], ifPacket.select[5], ifPacket.select[4], ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
+  __m256 false_mask = _mm256_cmp_ps(select, zero, _CMP_EQ_UQ);
+  return _mm256_blendv_ps(thenPacket, elsePacket, false_mask);
+}
+template<> EIGEN_STRONG_INLINE Packet4d pblend(const Selector<4>& ifPacket, const Packet4d& thenPacket, const Packet4d& elsePacket) {
+  const __m256d zero = _mm256_setzero_pd();
+  const __m256d select = _mm256_set_pd(ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
+  __m256d false_mask = _mm256_cmp_pd(select, zero, _CMP_EQ_UQ);
+  return _mm256_blendv_pd(thenPacket, elsePacket, false_mask);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8f pinsertfirst(const Packet8f& a, float b)
+{
+  return _mm256_blend_ps(a,pset1<Packet8f>(b),1);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4d pinsertfirst(const Packet4d& a, double b)
+{
+  return _mm256_blend_pd(a,pset1<Packet4d>(b),1);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8f pinsertlast(const Packet8f& a, float b)
+{
+  return _mm256_blend_ps(a,pset1<Packet8f>(b),(1<<7));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4d pinsertlast(const Packet4d& a, double b)
+{
+  return _mm256_blend_pd(a,pset1<Packet4d>(b),(1<<3));
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_PACKET_MATH_AVX_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/AVX/TypeCasting.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/AVX/TypeCasting.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AVX/TypeCasting.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AVX/TypeCasting.h
@@ -0,0 +1,51 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_TYPE_CASTING_AVX_H
+#define EIGEN_TYPE_CASTING_AVX_H
+
+namespace Eigen {
+
+namespace internal {
+
+// For now we use SSE to handle integers, so we can't use AVX instructions to cast
+// from int to float
+template <>
+struct type_casting_traits<float, int> {
+  enum {
+    VectorizedCast = 0,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template <>
+struct type_casting_traits<int, float> {
+  enum {
+    VectorizedCast = 0,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+
+
+template<> EIGEN_STRONG_INLINE Packet8i pcast<Packet8f, Packet8i>(const Packet8f& a) {
+  return _mm256_cvtps_epi32(a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8f pcast<Packet8i, Packet8f>(const Packet8i& a) {
+  return _mm256_cvtepi32_ps(a);
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TYPE_CASTING_AVX_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/AVX512/MathFunctions.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/AVX512/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AVX512/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AVX512/MathFunctions.h
@@ -0,0 +1,396 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Pedro Gonnet (pedro.gonnet@gmail.com)
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef THIRD_PARTY_EIGEN3_EIGEN_SRC_CORE_ARCH_AVX512_MATHFUNCTIONS_H_
+#define THIRD_PARTY_EIGEN3_EIGEN_SRC_CORE_ARCH_AVX512_MATHFUNCTIONS_H_
+
+namespace Eigen {
+
+namespace internal {
+
+// Disable the code for older versions of gcc that don't support many of the required avx512 instrinsics.
+#if EIGEN_GNUC_AT_LEAST(5, 3)
+
+#define _EIGEN_DECLARE_CONST_Packet16f(NAME, X) \
+  const Packet16f p16f_##NAME = pset1<Packet16f>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(NAME, X) \
+  const Packet16f p16f_##NAME = (__m512)pset1<Packet16i>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet8d(NAME, X) \
+  const Packet8d p8d_##NAME = pset1<Packet8d>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet8d_FROM_INT64(NAME, X) \
+  const Packet8d p8d_##NAME = _mm512_castsi512_pd(_mm512_set1_epi64(X))
+
+// Natural logarithm
+// Computes log(x) as log(2^e * m) = C*e + log(m), where the constant C =log(2)
+// and m is in the range [sqrt(1/2),sqrt(2)). In this range, the logarithm can
+// be easily approximated by a polynomial centered on m=1 for stability.
+#if defined(EIGEN_VECTORIZE_AVX512DQ)
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet16f
+plog<Packet16f>(const Packet16f& _x) {
+  Packet16f x = _x;
+  _EIGEN_DECLARE_CONST_Packet16f(1, 1.0f);
+  _EIGEN_DECLARE_CONST_Packet16f(half, 0.5f);
+  _EIGEN_DECLARE_CONST_Packet16f(126f, 126.0f);
+
+  _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(inv_mant_mask, ~0x7f800000);
+
+  // The smallest non denormalized float number.
+  _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(min_norm_pos, 0x00800000);
+  _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(minus_inf, 0xff800000);
+  _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(nan, 0x7fc00000);
+
+  // Polynomial coefficients.
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_SQRTHF, 0.707106781186547524f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p0, 7.0376836292E-2f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p1, -1.1514610310E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p2, 1.1676998740E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p3, -1.2420140846E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p4, +1.4249322787E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p5, -1.6668057665E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p6, +2.0000714765E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p7, -2.4999993993E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_p8, +3.3333331174E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_q1, -2.12194440e-4f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_log_q2, 0.693359375f);
+
+  // invalid_mask is set to true when x is NaN
+  __mmask16 invalid_mask =
+      _mm512_cmp_ps_mask(x, _mm512_setzero_ps(), _CMP_NGE_UQ);
+  __mmask16 iszero_mask =
+      _mm512_cmp_ps_mask(x, _mm512_setzero_ps(), _CMP_EQ_UQ);
+
+  // Truncate input values to the minimum positive normal.
+  x = pmax(x, p16f_min_norm_pos);
+
+  // Extract the shifted exponents.
+  Packet16f emm0 = _mm512_cvtepi32_ps(_mm512_srli_epi32((__m512i)x, 23));
+  Packet16f e = _mm512_sub_ps(emm0, p16f_126f);
+
+  // Set the exponents to -1, i.e. x are in the range [0.5,1).
+  x = _mm512_and_ps(x, p16f_inv_mant_mask);
+  x = _mm512_or_ps(x, p16f_half);
+
+  // part2: Shift the inputs from the range [0.5,1) to [sqrt(1/2),sqrt(2))
+  // and shift by -1. The values are then centered around 0, which improves
+  // the stability of the polynomial evaluation.
+  //   if( x < SQRTHF ) {
+  //     e -= 1;
+  //     x = x + x - 1.0;
+  //   } else { x = x - 1.0; }
+  __mmask16 mask = _mm512_cmp_ps_mask(x, p16f_cephes_SQRTHF, _CMP_LT_OQ);
+  Packet16f tmp = _mm512_mask_blend_ps(mask, x, _mm512_setzero_ps());
+  x = psub(x, p16f_1);
+  e = psub(e, _mm512_mask_blend_ps(mask, p16f_1, _mm512_setzero_ps()));
+  x = padd(x, tmp);
+
+  Packet16f x2 = pmul(x, x);
+  Packet16f x3 = pmul(x2, x);
+
+  // Evaluate the polynomial approximant of degree 8 in three parts, probably
+  // to improve instruction-level parallelism.
+  Packet16f y, y1, y2;
+  y = pmadd(p16f_cephes_log_p0, x, p16f_cephes_log_p1);
+  y1 = pmadd(p16f_cephes_log_p3, x, p16f_cephes_log_p4);
+  y2 = pmadd(p16f_cephes_log_p6, x, p16f_cephes_log_p7);
+  y = pmadd(y, x, p16f_cephes_log_p2);
+  y1 = pmadd(y1, x, p16f_cephes_log_p5);
+  y2 = pmadd(y2, x, p16f_cephes_log_p8);
+  y = pmadd(y, x3, y1);
+  y = pmadd(y, x3, y2);
+  y = pmul(y, x3);
+
+  // Add the logarithm of the exponent back to the result of the interpolation.
+  y1 = pmul(e, p16f_cephes_log_q1);
+  tmp = pmul(x2, p16f_half);
+  y = padd(y, y1);
+  x = psub(x, tmp);
+  y2 = pmul(e, p16f_cephes_log_q2);
+  x = padd(x, y);
+  x = padd(x, y2);
+
+  // Filter out invalid inputs, i.e. negative arg will be NAN, 0 will be -INF.
+  return _mm512_mask_blend_ps(iszero_mask, p16f_minus_inf,
+                              _mm512_mask_blend_ps(invalid_mask, p16f_nan, x));
+}
+#endif
+
+// Exponential function. Works by writing "x = m*log(2) + r" where
+// "m = floor(x/log(2)+1/2)" and "r" is the remainder. The result is then
+// "exp(x) = 2^m*exp(r)" where exp(r) is in the range [-1,1).
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet16f
+pexp<Packet16f>(const Packet16f& _x) {
+  _EIGEN_DECLARE_CONST_Packet16f(1, 1.0f);
+  _EIGEN_DECLARE_CONST_Packet16f(half, 0.5f);
+  _EIGEN_DECLARE_CONST_Packet16f(127, 127.0f);
+
+  _EIGEN_DECLARE_CONST_Packet16f(exp_hi, 88.3762626647950f);
+  _EIGEN_DECLARE_CONST_Packet16f(exp_lo, -88.3762626647949f);
+
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_LOG2EF, 1.44269504088896341f);
+
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_exp_p0, 1.9875691500E-4f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_exp_p1, 1.3981999507E-3f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_exp_p2, 8.3334519073E-3f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_exp_p3, 4.1665795894E-2f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_exp_p4, 1.6666665459E-1f);
+  _EIGEN_DECLARE_CONST_Packet16f(cephes_exp_p5, 5.0000001201E-1f);
+
+  // Clamp x.
+  Packet16f x = pmax(pmin(_x, p16f_exp_hi), p16f_exp_lo);
+
+  // Express exp(x) as exp(m*ln(2) + r), start by extracting
+  // m = floor(x/ln(2) + 0.5).
+  Packet16f m = _mm512_floor_ps(pmadd(x, p16f_cephes_LOG2EF, p16f_half));
+
+  // Get r = x - m*ln(2). Note that we can do this without losing more than one
+  // ulp precision due to the FMA instruction.
+  _EIGEN_DECLARE_CONST_Packet16f(nln2, -0.6931471805599453f);
+  Packet16f r = _mm512_fmadd_ps(m, p16f_nln2, x);
+  Packet16f r2 = pmul(r, r);
+
+  // TODO(gonnet): Split into odd/even polynomials and try to exploit
+  //               instruction-level parallelism.
+  Packet16f y = p16f_cephes_exp_p0;
+  y = pmadd(y, r, p16f_cephes_exp_p1);
+  y = pmadd(y, r, p16f_cephes_exp_p2);
+  y = pmadd(y, r, p16f_cephes_exp_p3);
+  y = pmadd(y, r, p16f_cephes_exp_p4);
+  y = pmadd(y, r, p16f_cephes_exp_p5);
+  y = pmadd(y, r2, r);
+  y = padd(y, p16f_1);
+
+  // Build emm0 = 2^m.
+  Packet16i emm0 = _mm512_cvttps_epi32(padd(m, p16f_127));
+  emm0 = _mm512_slli_epi32(emm0, 23);
+
+  // Return 2^m * exp(r).
+  return pmax(pmul(y, _mm512_castsi512_ps(emm0)), _x);
+}
+
+/*template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8d
+pexp<Packet8d>(const Packet8d& _x) {
+  Packet8d x = _x;
+
+  _EIGEN_DECLARE_CONST_Packet8d(1, 1.0);
+  _EIGEN_DECLARE_CONST_Packet8d(2, 2.0);
+
+  _EIGEN_DECLARE_CONST_Packet8d(exp_hi, 709.437);
+  _EIGEN_DECLARE_CONST_Packet8d(exp_lo, -709.436139303);
+
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_LOG2EF, 1.4426950408889634073599);
+
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_p0, 1.26177193074810590878e-4);
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_p1, 3.02994407707441961300e-2);
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_p2, 9.99999999999999999910e-1);
+
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_q0, 3.00198505138664455042e-6);
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_q1, 2.52448340349684104192e-3);
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_q2, 2.27265548208155028766e-1);
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_q3, 2.00000000000000000009e0);
+
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_C1, 0.693145751953125);
+  _EIGEN_DECLARE_CONST_Packet8d(cephes_exp_C2, 1.42860682030941723212e-6);
+
+  // clamp x
+  x = pmax(pmin(x, p8d_exp_hi), p8d_exp_lo);
+
+  // Express exp(x) as exp(g + n*log(2)).
+  const Packet8d n =
+      _mm512_mul_round_pd(p8d_cephes_LOG2EF, x, _MM_FROUND_TO_NEAREST_INT);
+
+  // Get the remainder modulo log(2), i.e. the "g" described above. Subtract
+  // n*log(2) out in two steps, i.e. n*C1 + n*C2, C1+C2=log2 to get the last
+  // digits right.
+  const Packet8d nC1 = pmul(n, p8d_cephes_exp_C1);
+  const Packet8d nC2 = pmul(n, p8d_cephes_exp_C2);
+  x = psub(x, nC1);
+  x = psub(x, nC2);
+
+  const Packet8d x2 = pmul(x, x);
+
+  // Evaluate the numerator polynomial of the rational interpolant.
+  Packet8d px = p8d_cephes_exp_p0;
+  px = pmadd(px, x2, p8d_cephes_exp_p1);
+  px = pmadd(px, x2, p8d_cephes_exp_p2);
+  px = pmul(px, x);
+
+  // Evaluate the denominator polynomial of the rational interpolant.
+  Packet8d qx = p8d_cephes_exp_q0;
+  qx = pmadd(qx, x2, p8d_cephes_exp_q1);
+  qx = pmadd(qx, x2, p8d_cephes_exp_q2);
+  qx = pmadd(qx, x2, p8d_cephes_exp_q3);
+
+  // I don't really get this bit, copied from the SSE2 routines, so...
+  // TODO(gonnet): Figure out what is going on here, perhaps find a better
+  // rational interpolant?
+  x = _mm512_div_pd(px, psub(qx, px));
+  x = pmadd(p8d_2, x, p8d_1);
+
+  // Build e=2^n.
+  const Packet8d e = _mm512_castsi512_pd(_mm512_slli_epi64(
+      _mm512_add_epi64(_mm512_cvtpd_epi64(n), _mm512_set1_epi64(1023)), 52));
+
+  // Construct the result 2^n * exp(g) = e * x. The max is used to catch
+  // non-finite values in the input.
+  return pmax(pmul(x, e), _x);
+  }*/
+
+// Functions for sqrt.
+// The EIGEN_FAST_MATH version uses the _mm_rsqrt_ps approximation and one step
+// of Newton's method, at a cost of 1-2 bits of precision as opposed to the
+// exact solution. The main advantage of this approach is not just speed, but
+// also the fact that it can be inlined and pipelined with other computations,
+// further reducing its effective latency.
+#if EIGEN_FAST_MATH
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet16f
+psqrt<Packet16f>(const Packet16f& _x) {
+  _EIGEN_DECLARE_CONST_Packet16f(one_point_five, 1.5f);
+  _EIGEN_DECLARE_CONST_Packet16f(minus_half, -0.5f);
+  _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(flt_min, 0x00800000);
+
+  Packet16f neg_half = pmul(_x, p16f_minus_half);
+
+  // select only the inverse sqrt of positive normal inputs (denormals are
+  // flushed to zero and cause infs as well).
+  __mmask16 non_zero_mask = _mm512_cmp_ps_mask(_x, p16f_flt_min, _CMP_GE_OQ);
+  Packet16f x = _mm512_mask_blend_ps(non_zero_mask, _mm512_rsqrt14_ps(_x),
+                                     _mm512_setzero_ps());
+
+  // Do a single step of Newton's iteration.
+  x = pmul(x, pmadd(neg_half, pmul(x, x), p16f_one_point_five));
+
+  // Multiply the original _x by it's reciprocal square root to extract the
+  // square root.
+  return pmul(_x, x);
+}
+
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8d
+psqrt<Packet8d>(const Packet8d& _x) {
+  _EIGEN_DECLARE_CONST_Packet8d(one_point_five, 1.5);
+  _EIGEN_DECLARE_CONST_Packet8d(minus_half, -0.5);
+  _EIGEN_DECLARE_CONST_Packet8d_FROM_INT64(dbl_min, 0x0010000000000000LL);
+
+  Packet8d neg_half = pmul(_x, p8d_minus_half);
+
+  // select only the inverse sqrt of positive normal inputs (denormals are
+  // flushed to zero and cause infs as well).
+  __mmask8 non_zero_mask = _mm512_cmp_pd_mask(_x, p8d_dbl_min, _CMP_GE_OQ);
+  Packet8d x = _mm512_mask_blend_pd(non_zero_mask, _mm512_rsqrt14_pd(_x),
+                                    _mm512_setzero_pd());
+
+  // Do a first step of Newton's iteration.
+  x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five));
+
+  // Do a second step of Newton's iteration.
+  x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five));
+
+  // Multiply the original _x by it's reciprocal square root to extract the
+  // square root.
+  return pmul(_x, x);
+}
+#else
+template <>
+EIGEN_STRONG_INLINE Packet16f psqrt<Packet16f>(const Packet16f& x) {
+  return _mm512_sqrt_ps(x);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d psqrt<Packet8d>(const Packet8d& x) {
+  return _mm512_sqrt_pd(x);
+}
+#endif
+
+// Functions for rsqrt.
+// Almost identical to the sqrt routine, just leave out the last multiplication
+// and fill in NaN/Inf where needed. Note that this function only exists as an
+// iterative version for doubles since there is no instruction for diretly
+// computing the reciprocal square root in AVX-512.
+#ifdef EIGEN_FAST_MATH
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet16f
+prsqrt<Packet16f>(const Packet16f& _x) {
+  _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(inf, 0x7f800000);
+  _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(nan, 0x7fc00000);
+  _EIGEN_DECLARE_CONST_Packet16f(one_point_five, 1.5f);
+  _EIGEN_DECLARE_CONST_Packet16f(minus_half, -0.5f);
+  _EIGEN_DECLARE_CONST_Packet16f_FROM_INT(flt_min, 0x00800000);
+
+  Packet16f neg_half = pmul(_x, p16f_minus_half);
+
+  // select only the inverse sqrt of positive normal inputs (denormals are
+  // flushed to zero and cause infs as well).
+  __mmask16 le_zero_mask = _mm512_cmp_ps_mask(_x, p16f_flt_min, _CMP_LT_OQ);
+  Packet16f x = _mm512_mask_blend_ps(le_zero_mask, _mm512_setzero_ps(),
+                                     _mm512_rsqrt14_ps(_x));
+
+  // Fill in NaNs and Infs for the negative/zero entries.
+  __mmask16 neg_mask = _mm512_cmp_ps_mask(_x, _mm512_setzero_ps(), _CMP_LT_OQ);
+  Packet16f infs_and_nans = _mm512_mask_blend_ps(
+      neg_mask, p16f_nan,
+      _mm512_mask_blend_ps(le_zero_mask, p16f_inf, _mm512_setzero_ps()));
+
+  // Do a single step of Newton's iteration.
+  x = pmul(x, pmadd(neg_half, pmul(x, x), p16f_one_point_five));
+
+  // Insert NaNs and Infs in all the right places.
+  return _mm512_mask_blend_ps(le_zero_mask, infs_and_nans, x);
+}
+
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8d
+prsqrt<Packet8d>(const Packet8d& _x) {
+  _EIGEN_DECLARE_CONST_Packet8d_FROM_INT64(inf, 0x7ff0000000000000LL);
+  _EIGEN_DECLARE_CONST_Packet8d_FROM_INT64(nan, 0x7ff1000000000000LL);
+  _EIGEN_DECLARE_CONST_Packet8d(one_point_five, 1.5);
+  _EIGEN_DECLARE_CONST_Packet8d(minus_half, -0.5);
+  _EIGEN_DECLARE_CONST_Packet8d_FROM_INT64(dbl_min, 0x0010000000000000LL);
+
+  Packet8d neg_half = pmul(_x, p8d_minus_half);
+
+  // select only the inverse sqrt of positive normal inputs (denormals are
+  // flushed to zero and cause infs as well).
+  __mmask8 le_zero_mask = _mm512_cmp_pd_mask(_x, p8d_dbl_min, _CMP_LT_OQ);
+  Packet8d x = _mm512_mask_blend_pd(le_zero_mask, _mm512_setzero_pd(),
+                                    _mm512_rsqrt14_pd(_x));
+
+  // Fill in NaNs and Infs for the negative/zero entries.
+  __mmask8 neg_mask = _mm512_cmp_pd_mask(_x, _mm512_setzero_pd(), _CMP_LT_OQ);
+  Packet8d infs_and_nans = _mm512_mask_blend_pd(
+      neg_mask, p8d_nan,
+      _mm512_mask_blend_pd(le_zero_mask, p8d_inf, _mm512_setzero_pd()));
+
+  // Do a first step of Newton's iteration.
+  x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five));
+
+  // Do a second step of Newton's iteration.
+  x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five));
+
+  // Insert NaNs and Infs in all the right places.
+  return _mm512_mask_blend_pd(le_zero_mask, infs_and_nans, x);
+}
+#else
+template <>
+EIGEN_STRONG_INLINE Packet16f prsqrt<Packet16f>(const Packet16f& x) {
+  return _mm512_rsqrt28_ps(x);
+}
+#endif
+#endif
+
+}  // end namespace internal
+
+}  // end namespace Eigen
+
+#endif  // THIRD_PARTY_EIGEN3_EIGEN_SRC_CORE_ARCH_AVX512_MATHFUNCTIONS_H_

ADDED   3rd_party/eigen/Eigen/src/Core/arch/AVX512/PacketMath.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/AVX512/PacketMath.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AVX512/PacketMath.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AVX512/PacketMath.h
@@ -0,0 +1,1316 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner (benoit.steiner.goog@gmail.com)
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_PACKET_MATH_AVX512_H
+#define EIGEN_PACKET_MATH_AVX512_H
+
+namespace Eigen {
+
+namespace internal {
+
+#ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
+#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 8
+#endif
+
+#ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
+#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS (2*sizeof(void*))
+#endif
+
+#ifdef __FMA__
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#endif
+#endif
+
+typedef __m512 Packet16f;
+typedef __m512i Packet16i;
+typedef __m512d Packet8d;
+
+template <>
+struct is_arithmetic<__m512> {
+  enum { value = true };
+};
+template <>
+struct is_arithmetic<__m512i> {
+  enum { value = true };
+};
+template <>
+struct is_arithmetic<__m512d> {
+  enum { value = true };
+};
+
+template<> struct packet_traits<float>  : default_packet_traits
+{
+  typedef Packet16f type;
+  typedef Packet8f half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 16,
+    HasHalfPacket = 1,
+#if EIGEN_GNUC_AT_LEAST(5, 3)
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+    HasLog = 1,
+#endif
+    HasExp = 1,
+    HasSqrt = 1,
+    HasRsqrt = 1,
+#endif
+    HasDiv = 1
+  };
+ };
+template<> struct packet_traits<double> : default_packet_traits
+{
+  typedef Packet8d type;
+  typedef Packet4d half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 8,
+    HasHalfPacket = 1,
+#if EIGEN_GNUC_AT_LEAST(5, 3)
+    HasSqrt = 1,
+    HasRsqrt = EIGEN_FAST_MATH,
+#endif
+    HasDiv = 1
+  };
+};
+
+/* TODO Implement AVX512 for integers
+template<> struct packet_traits<int>    : default_packet_traits
+{
+  typedef Packet16i type;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=8
+  };
+};
+*/
+
+template <>
+struct unpacket_traits<Packet16f> {
+  typedef float type;
+  typedef Packet8f half;
+  enum { size = 16, alignment=Aligned64 };
+};
+template <>
+struct unpacket_traits<Packet8d> {
+  typedef double type;
+  typedef Packet4d half;
+  enum { size = 8, alignment=Aligned64 };
+};
+template <>
+struct unpacket_traits<Packet16i> {
+  typedef int type;
+  typedef Packet8i half;
+  enum { size = 16, alignment=Aligned64 };
+};
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pset1<Packet16f>(const float& from) {
+  return _mm512_set1_ps(from);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pset1<Packet8d>(const double& from) {
+  return _mm512_set1_pd(from);
+}
+template <>
+EIGEN_STRONG_INLINE Packet16i pset1<Packet16i>(const int& from) {
+  return _mm512_set1_epi32(from);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pload1<Packet16f>(const float* from) {
+  return _mm512_broadcastss_ps(_mm_load_ps1(from));
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pload1<Packet8d>(const double* from) {
+  return _mm512_broadcastsd_pd(_mm_load_pd1(from));
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f plset<Packet16f>(const float& a) {
+  return _mm512_add_ps(
+      _mm512_set1_ps(a),
+      _mm512_set_ps(15.0f, 14.0f, 13.0f, 12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f,
+                    4.0f, 3.0f, 2.0f, 1.0f, 0.0f));
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d plset<Packet8d>(const double& a) {
+  return _mm512_add_pd(_mm512_set1_pd(a),
+                       _mm512_set_pd(7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 0.0));
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f padd<Packet16f>(const Packet16f& a,
+                                              const Packet16f& b) {
+  return _mm512_add_ps(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d padd<Packet8d>(const Packet8d& a,
+                                            const Packet8d& b) {
+  return _mm512_add_pd(a, b);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f psub<Packet16f>(const Packet16f& a,
+                                              const Packet16f& b) {
+  return _mm512_sub_ps(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d psub<Packet8d>(const Packet8d& a,
+                                            const Packet8d& b) {
+  return _mm512_sub_pd(a, b);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pnegate(const Packet16f& a) {
+  return _mm512_sub_ps(_mm512_set1_ps(0.0), a);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pnegate(const Packet8d& a) {
+  return _mm512_sub_pd(_mm512_set1_pd(0.0), a);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pconj(const Packet16f& a) {
+  return a;
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pconj(const Packet8d& a) {
+  return a;
+}
+template <>
+EIGEN_STRONG_INLINE Packet16i pconj(const Packet16i& a) {
+  return a;
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pmul<Packet16f>(const Packet16f& a,
+                                              const Packet16f& b) {
+  return _mm512_mul_ps(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pmul<Packet8d>(const Packet8d& a,
+                                            const Packet8d& b) {
+  return _mm512_mul_pd(a, b);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pdiv<Packet16f>(const Packet16f& a,
+                                              const Packet16f& b) {
+  return _mm512_div_ps(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pdiv<Packet8d>(const Packet8d& a,
+                                            const Packet8d& b) {
+  return _mm512_div_pd(a, b);
+}
+
+#ifdef __FMA__
+template <>
+EIGEN_STRONG_INLINE Packet16f pmadd(const Packet16f& a, const Packet16f& b,
+                                    const Packet16f& c) {
+  return _mm512_fmadd_ps(a, b, c);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pmadd(const Packet8d& a, const Packet8d& b,
+                                   const Packet8d& c) {
+  return _mm512_fmadd_pd(a, b, c);
+}
+#endif
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pmin<Packet16f>(const Packet16f& a,
+                                              const Packet16f& b) {
+  return _mm512_min_ps(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pmin<Packet8d>(const Packet8d& a,
+                                            const Packet8d& b) {
+  return _mm512_min_pd(a, b);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pmax<Packet16f>(const Packet16f& a,
+                                              const Packet16f& b) {
+  return _mm512_max_ps(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pmax<Packet8d>(const Packet8d& a,
+                                            const Packet8d& b) {
+  return _mm512_max_pd(a, b);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pand<Packet16f>(const Packet16f& a,
+                                              const Packet16f& b) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  return _mm512_and_ps(a, b);
+#else
+  Packet16f res = _mm512_undefined_ps();
+  Packet4f lane0_a = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane0_b = _mm512_extractf32x4_ps(b, 0);
+  res = _mm512_insertf32x4(res, _mm_and_ps(lane0_a, lane0_b), 0);
+
+  Packet4f lane1_a = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane1_b = _mm512_extractf32x4_ps(b, 1);
+  res = _mm512_insertf32x4(res, _mm_and_ps(lane1_a, lane1_b), 1);
+
+  Packet4f lane2_a = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane2_b = _mm512_extractf32x4_ps(b, 2);
+  res = _mm512_insertf32x4(res, _mm_and_ps(lane2_a, lane2_b), 2);
+
+  Packet4f lane3_a = _mm512_extractf32x4_ps(a, 3);
+  Packet4f lane3_b = _mm512_extractf32x4_ps(b, 3);
+  res = _mm512_insertf32x4(res, _mm_and_ps(lane3_a, lane3_b), 3);
+
+  return res;
+#endif
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pand<Packet8d>(const Packet8d& a,
+                                            const Packet8d& b) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  return _mm512_and_pd(a, b);
+#else
+  Packet8d res = _mm512_undefined_pd();
+  Packet4d lane0_a = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane0_b = _mm512_extractf64x4_pd(b, 0);
+  res = _mm512_insertf64x4(res, _mm256_and_pd(lane0_a, lane0_b), 0);
+
+  Packet4d lane1_a = _mm512_extractf64x4_pd(a, 1);
+  Packet4d lane1_b = _mm512_extractf64x4_pd(b, 1);
+  res = _mm512_insertf64x4(res, _mm256_and_pd(lane1_a, lane1_b), 1);
+
+  return res;
+#endif
+}
+template <>
+EIGEN_STRONG_INLINE Packet16f por<Packet16f>(const Packet16f& a,
+                                             const Packet16f& b) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  return _mm512_or_ps(a, b);
+#else
+  Packet16f res = _mm512_undefined_ps();
+  Packet4f lane0_a = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane0_b = _mm512_extractf32x4_ps(b, 0);
+  res = _mm512_insertf32x4(res, _mm_or_ps(lane0_a, lane0_b), 0);
+
+  Packet4f lane1_a = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane1_b = _mm512_extractf32x4_ps(b, 1);
+  res = _mm512_insertf32x4(res, _mm_or_ps(lane1_a, lane1_b), 1);
+
+  Packet4f lane2_a = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane2_b = _mm512_extractf32x4_ps(b, 2);
+  res = _mm512_insertf32x4(res, _mm_or_ps(lane2_a, lane2_b), 2);
+
+  Packet4f lane3_a = _mm512_extractf32x4_ps(a, 3);
+  Packet4f lane3_b = _mm512_extractf32x4_ps(b, 3);
+  res = _mm512_insertf32x4(res, _mm_or_ps(lane3_a, lane3_b), 3);
+
+  return res;
+#endif
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet8d por<Packet8d>(const Packet8d& a,
+                                           const Packet8d& b) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  return _mm512_or_pd(a, b);
+#else
+  Packet8d res = _mm512_undefined_pd();
+  Packet4d lane0_a = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane0_b = _mm512_extractf64x4_pd(b, 0);
+  res = _mm512_insertf64x4(res, _mm256_or_pd(lane0_a, lane0_b), 0);
+
+  Packet4d lane1_a = _mm512_extractf64x4_pd(a, 1);
+  Packet4d lane1_b = _mm512_extractf64x4_pd(b, 1);
+  res = _mm512_insertf64x4(res, _mm256_or_pd(lane1_a, lane1_b), 1);
+
+  return res;
+#endif
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pxor<Packet16f>(const Packet16f& a,
+                                              const Packet16f& b) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  return _mm512_xor_ps(a, b);
+#else
+  Packet16f res = _mm512_undefined_ps();
+  Packet4f lane0_a = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane0_b = _mm512_extractf32x4_ps(b, 0);
+  res = _mm512_insertf32x4(res, _mm_xor_ps(lane0_a, lane0_b), 0);
+
+  Packet4f lane1_a = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane1_b = _mm512_extractf32x4_ps(b, 1);
+  res = _mm512_insertf32x4(res, _mm_xor_ps(lane1_a, lane1_b), 1);
+
+  Packet4f lane2_a = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane2_b = _mm512_extractf32x4_ps(b, 2);
+  res = _mm512_insertf32x4(res, _mm_xor_ps(lane2_a, lane2_b), 2);
+
+  Packet4f lane3_a = _mm512_extractf32x4_ps(a, 3);
+  Packet4f lane3_b = _mm512_extractf32x4_ps(b, 3);
+  res = _mm512_insertf32x4(res, _mm_xor_ps(lane3_a, lane3_b), 3);
+
+  return res;
+#endif
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pxor<Packet8d>(const Packet8d& a,
+                                            const Packet8d& b) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  return _mm512_xor_pd(a, b);
+#else
+  Packet8d res = _mm512_undefined_pd();
+  Packet4d lane0_a = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane0_b = _mm512_extractf64x4_pd(b, 0);
+  res = _mm512_insertf64x4(res, _mm256_xor_pd(lane0_a, lane0_b), 0);
+
+  Packet4d lane1_a = _mm512_extractf64x4_pd(a, 1);
+  Packet4d lane1_b = _mm512_extractf64x4_pd(b, 1);
+  res = _mm512_insertf64x4(res, _mm256_xor_pd(lane1_a, lane1_b), 1);
+
+  return res;
+#endif
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pandnot<Packet16f>(const Packet16f& a,
+                                                 const Packet16f& b) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  return _mm512_andnot_ps(a, b);
+#else
+  Packet16f res = _mm512_undefined_ps();
+  Packet4f lane0_a = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane0_b = _mm512_extractf32x4_ps(b, 0);
+  res = _mm512_insertf32x4(res, _mm_andnot_ps(lane0_a, lane0_b), 0);
+
+  Packet4f lane1_a = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane1_b = _mm512_extractf32x4_ps(b, 1);
+  res = _mm512_insertf32x4(res, _mm_andnot_ps(lane1_a, lane1_b), 1);
+
+  Packet4f lane2_a = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane2_b = _mm512_extractf32x4_ps(b, 2);
+  res = _mm512_insertf32x4(res, _mm_andnot_ps(lane2_a, lane2_b), 2);
+
+  Packet4f lane3_a = _mm512_extractf32x4_ps(a, 3);
+  Packet4f lane3_b = _mm512_extractf32x4_ps(b, 3);
+  res = _mm512_insertf32x4(res, _mm_andnot_ps(lane3_a, lane3_b), 3);
+
+  return res;
+#endif
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pandnot<Packet8d>(const Packet8d& a,
+                                               const Packet8d& b) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  return _mm512_andnot_pd(a, b);
+#else
+  Packet8d res = _mm512_undefined_pd();
+  Packet4d lane0_a = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane0_b = _mm512_extractf64x4_pd(b, 0);
+  res = _mm512_insertf64x4(res, _mm256_andnot_pd(lane0_a, lane0_b), 0);
+
+  Packet4d lane1_a = _mm512_extractf64x4_pd(a, 1);
+  Packet4d lane1_b = _mm512_extractf64x4_pd(b, 1);
+  res = _mm512_insertf64x4(res, _mm256_andnot_pd(lane1_a, lane1_b), 1);
+
+  return res;
+#endif
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f pload<Packet16f>(const float* from) {
+  EIGEN_DEBUG_ALIGNED_LOAD return _mm512_load_ps(from);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pload<Packet8d>(const double* from) {
+  EIGEN_DEBUG_ALIGNED_LOAD return _mm512_load_pd(from);
+}
+template <>
+EIGEN_STRONG_INLINE Packet16i pload<Packet16i>(const int* from) {
+  EIGEN_DEBUG_ALIGNED_LOAD return _mm512_load_si512(
+      reinterpret_cast<const __m512i*>(from));
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet16f ploadu<Packet16f>(const float* from) {
+  EIGEN_DEBUG_UNALIGNED_LOAD return _mm512_loadu_ps(from);
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d ploadu<Packet8d>(const double* from) {
+  EIGEN_DEBUG_UNALIGNED_LOAD return _mm512_loadu_pd(from);
+}
+template <>
+EIGEN_STRONG_INLINE Packet16i ploadu<Packet16i>(const int* from) {
+  EIGEN_DEBUG_UNALIGNED_LOAD return _mm512_loadu_si512(
+      reinterpret_cast<const __m512i*>(from));
+}
+
+// Loads 8 floats from memory a returns the packet
+// {a0, a0  a1, a1, a2, a2, a3, a3, a4, a4, a5, a5, a6, a6, a7, a7}
+template <>
+EIGEN_STRONG_INLINE Packet16f ploaddup<Packet16f>(const float* from) {
+  Packet8f lane0 = _mm256_broadcast_ps((const __m128*)(const void*)from);
+  // mimic an "inplace" permutation of the lower 128bits using a blend
+  lane0 = _mm256_blend_ps(
+      lane0, _mm256_castps128_ps256(_mm_permute_ps(
+                 _mm256_castps256_ps128(lane0), _MM_SHUFFLE(1, 0, 1, 0))),
+      15);
+  // then we can perform a consistent permutation on the global register to get
+  // everything in shape:
+  lane0 = _mm256_permute_ps(lane0, _MM_SHUFFLE(3, 3, 2, 2));
+
+  Packet8f lane1 = _mm256_broadcast_ps((const __m128*)(const void*)(from + 4));
+  // mimic an "inplace" permutation of the lower 128bits using a blend
+  lane1 = _mm256_blend_ps(
+      lane1, _mm256_castps128_ps256(_mm_permute_ps(
+                 _mm256_castps256_ps128(lane1), _MM_SHUFFLE(1, 0, 1, 0))),
+      15);
+  // then we can perform a consistent permutation on the global register to get
+  // everything in shape:
+  lane1 = _mm256_permute_ps(lane1, _MM_SHUFFLE(3, 3, 2, 2));
+
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  Packet16f res = _mm512_undefined_ps();
+  return _mm512_insertf32x8(res, lane0, 0);
+  return _mm512_insertf32x8(res, lane1, 1);
+  return res;
+#else
+  Packet16f res = _mm512_undefined_ps();
+  res = _mm512_insertf32x4(res, _mm256_extractf128_ps(lane0, 0), 0);
+  res = _mm512_insertf32x4(res, _mm256_extractf128_ps(lane0, 1), 1);
+  res = _mm512_insertf32x4(res, _mm256_extractf128_ps(lane1, 0), 2);
+  res = _mm512_insertf32x4(res, _mm256_extractf128_ps(lane1, 1), 3);
+  return res;
+#endif
+}
+// Loads 4 doubles from memory a returns the packet {a0, a0  a1, a1, a2, a2, a3,
+// a3}
+template <>
+EIGEN_STRONG_INLINE Packet8d ploaddup<Packet8d>(const double* from) {
+  Packet4d lane0 = _mm256_broadcast_pd((const __m128d*)(const void*)from);
+  lane0 = _mm256_permute_pd(lane0, 3 << 2);
+
+  Packet4d lane1 = _mm256_broadcast_pd((const __m128d*)(const void*)(from + 2));
+  lane1 = _mm256_permute_pd(lane1, 3 << 2);
+
+  Packet8d res = _mm512_undefined_pd();
+  res = _mm512_insertf64x4(res, lane0, 0);
+  return _mm512_insertf64x4(res, lane1, 1);
+}
+
+// Loads 4 floats from memory a returns the packet
+// {a0, a0  a0, a0, a1, a1, a1, a1, a2, a2, a2, a2, a3, a3, a3, a3}
+template <>
+EIGEN_STRONG_INLINE Packet16f ploadquad<Packet16f>(const float* from) {
+  Packet16f tmp = _mm512_undefined_ps();
+  tmp = _mm512_insertf32x4(tmp, _mm_load_ps1(from), 0);
+  tmp = _mm512_insertf32x4(tmp, _mm_load_ps1(from + 1), 1);
+  tmp = _mm512_insertf32x4(tmp, _mm_load_ps1(from + 2), 2);
+  tmp = _mm512_insertf32x4(tmp, _mm_load_ps1(from + 3), 3);
+  return tmp;
+}
+// Loads 2 doubles from memory a returns the packet
+// {a0, a0  a0, a0, a1, a1, a1, a1}
+template <>
+EIGEN_STRONG_INLINE Packet8d ploadquad<Packet8d>(const double* from) {
+  Packet8d tmp = _mm512_undefined_pd();
+  Packet2d tmp0 = _mm_load_pd1(from);
+  Packet2d tmp1 = _mm_load_pd1(from + 1);
+  Packet4d lane0 = _mm256_broadcastsd_pd(tmp0);
+  Packet4d lane1 = _mm256_broadcastsd_pd(tmp1);
+  tmp = _mm512_insertf64x4(tmp, lane0, 0);
+  return _mm512_insertf64x4(tmp, lane1, 1);
+}
+
+template <>
+EIGEN_STRONG_INLINE void pstore<float>(float* to, const Packet16f& from) {
+  EIGEN_DEBUG_ALIGNED_STORE _mm512_store_ps(to, from);
+}
+template <>
+EIGEN_STRONG_INLINE void pstore<double>(double* to, const Packet8d& from) {
+  EIGEN_DEBUG_ALIGNED_STORE _mm512_store_pd(to, from);
+}
+template <>
+EIGEN_STRONG_INLINE void pstore<int>(int* to, const Packet16i& from) {
+  EIGEN_DEBUG_ALIGNED_STORE _mm512_storeu_si512(reinterpret_cast<__m512i*>(to),
+                                                from);
+}
+
+template <>
+EIGEN_STRONG_INLINE void pstoreu<float>(float* to, const Packet16f& from) {
+  EIGEN_DEBUG_UNALIGNED_STORE _mm512_storeu_ps(to, from);
+}
+template <>
+EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet8d& from) {
+  EIGEN_DEBUG_UNALIGNED_STORE _mm512_storeu_pd(to, from);
+}
+template <>
+EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet16i& from) {
+  EIGEN_DEBUG_UNALIGNED_STORE _mm512_storeu_si512(
+      reinterpret_cast<__m512i*>(to), from);
+}
+
+template <>
+EIGEN_DEVICE_FUNC inline Packet16f pgather<float, Packet16f>(const float* from,
+                                                             Index stride) {
+  Packet16i stride_vector = _mm512_set1_epi32(stride);
+  Packet16i stride_multiplier =
+      _mm512_set_epi32(15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0);
+  Packet16i indices = _mm512_mullo_epi32(stride_vector, stride_multiplier);
+
+  return _mm512_i32gather_ps(indices, from, 4);
+}
+template <>
+EIGEN_DEVICE_FUNC inline Packet8d pgather<double, Packet8d>(const double* from,
+                                                            Index stride) {
+  Packet8i stride_vector = _mm256_set1_epi32(stride);
+  Packet8i stride_multiplier = _mm256_set_epi32(7, 6, 5, 4, 3, 2, 1, 0);
+  Packet8i indices = _mm256_mullo_epi32(stride_vector, stride_multiplier);
+
+  return _mm512_i32gather_pd(indices, from, 8);
+}
+
+template <>
+EIGEN_DEVICE_FUNC inline void pscatter<float, Packet16f>(float* to,
+                                                         const Packet16f& from,
+                                                         Index stride) {
+  Packet16i stride_vector = _mm512_set1_epi32(stride);
+  Packet16i stride_multiplier =
+      _mm512_set_epi32(15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0);
+  Packet16i indices = _mm512_mullo_epi32(stride_vector, stride_multiplier);
+  _mm512_i32scatter_ps(to, indices, from, 4);
+}
+template <>
+EIGEN_DEVICE_FUNC inline void pscatter<double, Packet8d>(double* to,
+                                                         const Packet8d& from,
+                                                         Index stride) {
+  Packet8i stride_vector = _mm256_set1_epi32(stride);
+  Packet8i stride_multiplier = _mm256_set_epi32(7, 6, 5, 4, 3, 2, 1, 0);
+  Packet8i indices = _mm256_mullo_epi32(stride_vector, stride_multiplier);
+  _mm512_i32scatter_pd(to, indices, from, 8);
+}
+
+template <>
+EIGEN_STRONG_INLINE void pstore1<Packet16f>(float* to, const float& a) {
+  Packet16f pa = pset1<Packet16f>(a);
+  pstore(to, pa);
+}
+template <>
+EIGEN_STRONG_INLINE void pstore1<Packet8d>(double* to, const double& a) {
+  Packet8d pa = pset1<Packet8d>(a);
+  pstore(to, pa);
+}
+template <>
+EIGEN_STRONG_INLINE void pstore1<Packet16i>(int* to, const int& a) {
+  Packet16i pa = pset1<Packet16i>(a);
+  pstore(to, pa);
+}
+
+template<> EIGEN_STRONG_INLINE void prefetch<float>(const float*   addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
+template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
+template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*       addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
+
+template <>
+EIGEN_STRONG_INLINE float pfirst<Packet16f>(const Packet16f& a) {
+  return _mm_cvtss_f32(_mm512_extractf32x4_ps(a, 0));
+}
+template <>
+EIGEN_STRONG_INLINE double pfirst<Packet8d>(const Packet8d& a) {
+  return _mm_cvtsd_f64(_mm256_extractf128_pd(_mm512_extractf64x4_pd(a, 0), 0));
+}
+template <>
+EIGEN_STRONG_INLINE int pfirst<Packet16i>(const Packet16i& a) {
+  return _mm_extract_epi32(_mm512_extracti32x4_epi32(a, 0), 0);
+}
+
+template<> EIGEN_STRONG_INLINE Packet16f preverse(const Packet16f& a)
+{
+  return _mm512_permutexvar_ps(_mm512_set_epi32(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15), a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8d preverse(const Packet8d& a)
+{
+  return _mm512_permutexvar_pd(_mm512_set_epi32(0, 0, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7), a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet16f pabs(const Packet16f& a)
+{
+  // _mm512_abs_ps intrinsic not found, so hack around it
+  return (__m512)_mm512_and_si512((__m512i)a, _mm512_set1_epi32(0x7fffffff));
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pabs(const Packet8d& a) {
+  // _mm512_abs_ps intrinsic not found, so hack around it
+  return (__m512d)_mm512_and_si512((__m512i)a,
+                                   _mm512_set1_epi64(0x7fffffffffffffff));
+}
+
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+// AVX512F does not define _mm512_extractf32x8_ps to extract _m256 from _m512
+#define EIGEN_EXTRACT_8f_FROM_16f(INPUT, OUTPUT)                           \
+  __m256 OUTPUT##_0 = _mm512_extractf32x8_ps(INPUT, 0) __m256 OUTPUT##_1 = \
+      _mm512_extractf32x8_ps(INPUT, 1)
+#else
+#define EIGEN_EXTRACT_8f_FROM_16f(INPUT, OUTPUT)                \
+  __m256 OUTPUT##_0 = _mm256_insertf128_ps(                     \
+      _mm256_castps128_ps256(_mm512_extractf32x4_ps(INPUT, 0)), \
+      _mm512_extractf32x4_ps(INPUT, 1), 1);                     \
+  __m256 OUTPUT##_1 = _mm256_insertf128_ps(                     \
+      _mm256_castps128_ps256(_mm512_extractf32x4_ps(INPUT, 2)), \
+      _mm512_extractf32x4_ps(INPUT, 3), 1);
+#endif
+
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+#define EIGEN_INSERT_8f_INTO_16f(OUTPUT, INPUTA, INPUTB) \
+  OUTPUT = _mm512_insertf32x8(OUTPUT, INPUTA, 0);        \
+  OUTPUT = _mm512_insertf32x8(OUTPUT, INPUTB, 1);
+#else
+#define EIGEN_INSERT_8f_INTO_16f(OUTPUT, INPUTA, INPUTB)                    \
+  OUTPUT = _mm512_insertf32x4(OUTPUT, _mm256_extractf128_ps(INPUTA, 0), 0); \
+  OUTPUT = _mm512_insertf32x4(OUTPUT, _mm256_extractf128_ps(INPUTA, 1), 1); \
+  OUTPUT = _mm512_insertf32x4(OUTPUT, _mm256_extractf128_ps(INPUTB, 0), 2); \
+  OUTPUT = _mm512_insertf32x4(OUTPUT, _mm256_extractf128_ps(INPUTB, 1), 3);
+#endif
+template<> EIGEN_STRONG_INLINE Packet16f preduxp<Packet16f>(const Packet16f*
+vecs)
+{
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[0], vecs0);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[1], vecs1);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[2], vecs2);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[3], vecs3);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[4], vecs4);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[5], vecs5);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[6], vecs6);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[7], vecs7);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[8], vecs8);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[9], vecs9);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[10], vecs10);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[11], vecs11);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[12], vecs12);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[13], vecs13);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[14], vecs14);
+  EIGEN_EXTRACT_8f_FROM_16f(vecs[15], vecs15);
+
+  __m256 hsum1 = _mm256_hadd_ps(vecs0_0, vecs1_0);
+  __m256 hsum2 = _mm256_hadd_ps(vecs2_0, vecs3_0);
+  __m256 hsum3 = _mm256_hadd_ps(vecs4_0, vecs5_0);
+  __m256 hsum4 = _mm256_hadd_ps(vecs6_0, vecs7_0);
+
+  __m256 hsum5 = _mm256_hadd_ps(hsum1, hsum1);
+  __m256 hsum6 = _mm256_hadd_ps(hsum2, hsum2);
+  __m256 hsum7 = _mm256_hadd_ps(hsum3, hsum3);
+  __m256 hsum8 = _mm256_hadd_ps(hsum4, hsum4);
+
+  __m256 perm1 = _mm256_permute2f128_ps(hsum5, hsum5, 0x23);
+  __m256 perm2 = _mm256_permute2f128_ps(hsum6, hsum6, 0x23);
+  __m256 perm3 = _mm256_permute2f128_ps(hsum7, hsum7, 0x23);
+  __m256 perm4 = _mm256_permute2f128_ps(hsum8, hsum8, 0x23);
+
+  __m256 sum1 = _mm256_add_ps(perm1, hsum5);
+  __m256 sum2 = _mm256_add_ps(perm2, hsum6);
+  __m256 sum3 = _mm256_add_ps(perm3, hsum7);
+  __m256 sum4 = _mm256_add_ps(perm4, hsum8);
+
+  __m256 blend1 = _mm256_blend_ps(sum1, sum2, 0xcc);
+  __m256 blend2 = _mm256_blend_ps(sum3, sum4, 0xcc);
+
+  __m256 final = _mm256_blend_ps(blend1, blend2, 0xf0);
+
+  hsum1 = _mm256_hadd_ps(vecs0_1, vecs1_1);
+  hsum2 = _mm256_hadd_ps(vecs2_1, vecs3_1);
+  hsum3 = _mm256_hadd_ps(vecs4_1, vecs5_1);
+  hsum4 = _mm256_hadd_ps(vecs6_1, vecs7_1);
+
+  hsum5 = _mm256_hadd_ps(hsum1, hsum1);
+  hsum6 = _mm256_hadd_ps(hsum2, hsum2);
+  hsum7 = _mm256_hadd_ps(hsum3, hsum3);
+  hsum8 = _mm256_hadd_ps(hsum4, hsum4);
+
+  perm1 = _mm256_permute2f128_ps(hsum5, hsum5, 0x23);
+  perm2 = _mm256_permute2f128_ps(hsum6, hsum6, 0x23);
+  perm3 = _mm256_permute2f128_ps(hsum7, hsum7, 0x23);
+  perm4 = _mm256_permute2f128_ps(hsum8, hsum8, 0x23);
+
+  sum1 = _mm256_add_ps(perm1, hsum5);
+  sum2 = _mm256_add_ps(perm2, hsum6);
+  sum3 = _mm256_add_ps(perm3, hsum7);
+  sum4 = _mm256_add_ps(perm4, hsum8);
+
+  blend1 = _mm256_blend_ps(sum1, sum2, 0xcc);
+  blend2 = _mm256_blend_ps(sum3, sum4, 0xcc);
+
+  final = padd(final, _mm256_blend_ps(blend1, blend2, 0xf0));
+
+  hsum1 = _mm256_hadd_ps(vecs8_0, vecs9_0);
+  hsum2 = _mm256_hadd_ps(vecs10_0, vecs11_0);
+  hsum3 = _mm256_hadd_ps(vecs12_0, vecs13_0);
+  hsum4 = _mm256_hadd_ps(vecs14_0, vecs15_0);
+
+  hsum5 = _mm256_hadd_ps(hsum1, hsum1);
+  hsum6 = _mm256_hadd_ps(hsum2, hsum2);
+  hsum7 = _mm256_hadd_ps(hsum3, hsum3);
+  hsum8 = _mm256_hadd_ps(hsum4, hsum4);
+
+  perm1 = _mm256_permute2f128_ps(hsum5, hsum5, 0x23);
+  perm2 = _mm256_permute2f128_ps(hsum6, hsum6, 0x23);
+  perm3 = _mm256_permute2f128_ps(hsum7, hsum7, 0x23);
+  perm4 = _mm256_permute2f128_ps(hsum8, hsum8, 0x23);
+
+  sum1 = _mm256_add_ps(perm1, hsum5);
+  sum2 = _mm256_add_ps(perm2, hsum6);
+  sum3 = _mm256_add_ps(perm3, hsum7);
+  sum4 = _mm256_add_ps(perm4, hsum8);
+
+  blend1 = _mm256_blend_ps(sum1, sum2, 0xcc);
+  blend2 = _mm256_blend_ps(sum3, sum4, 0xcc);
+
+  __m256 final_1 = _mm256_blend_ps(blend1, blend2, 0xf0);
+
+  hsum1 = _mm256_hadd_ps(vecs8_1, vecs9_1);
+  hsum2 = _mm256_hadd_ps(vecs10_1, vecs11_1);
+  hsum3 = _mm256_hadd_ps(vecs12_1, vecs13_1);
+  hsum4 = _mm256_hadd_ps(vecs14_1, vecs15_1);
+
+  hsum5 = _mm256_hadd_ps(hsum1, hsum1);
+  hsum6 = _mm256_hadd_ps(hsum2, hsum2);
+  hsum7 = _mm256_hadd_ps(hsum3, hsum3);
+  hsum8 = _mm256_hadd_ps(hsum4, hsum4);
+
+  perm1 = _mm256_permute2f128_ps(hsum5, hsum5, 0x23);
+  perm2 = _mm256_permute2f128_ps(hsum6, hsum6, 0x23);
+  perm3 = _mm256_permute2f128_ps(hsum7, hsum7, 0x23);
+  perm4 = _mm256_permute2f128_ps(hsum8, hsum8, 0x23);
+
+  sum1 = _mm256_add_ps(perm1, hsum5);
+  sum2 = _mm256_add_ps(perm2, hsum6);
+  sum3 = _mm256_add_ps(perm3, hsum7);
+  sum4 = _mm256_add_ps(perm4, hsum8);
+
+  blend1 = _mm256_blend_ps(sum1, sum2, 0xcc);
+  blend2 = _mm256_blend_ps(sum3, sum4, 0xcc);
+
+  final_1 = padd(final_1, _mm256_blend_ps(blend1, blend2, 0xf0));
+
+  __m512 final_output;
+
+  EIGEN_INSERT_8f_INTO_16f(final_output, final, final_1);
+  return final_output;
+}
+
+template<> EIGEN_STRONG_INLINE Packet8d preduxp<Packet8d>(const Packet8d* vecs)
+{
+  Packet4d vecs0_0 = _mm512_extractf64x4_pd(vecs[0], 0);
+  Packet4d vecs0_1 = _mm512_extractf64x4_pd(vecs[0], 1);
+
+  Packet4d vecs1_0 = _mm512_extractf64x4_pd(vecs[1], 0);
+  Packet4d vecs1_1 = _mm512_extractf64x4_pd(vecs[1], 1);
+
+  Packet4d vecs2_0 = _mm512_extractf64x4_pd(vecs[2], 0);
+  Packet4d vecs2_1 = _mm512_extractf64x4_pd(vecs[2], 1);
+
+  Packet4d vecs3_0 = _mm512_extractf64x4_pd(vecs[3], 0);
+  Packet4d vecs3_1 = _mm512_extractf64x4_pd(vecs[3], 1);
+
+  Packet4d vecs4_0 = _mm512_extractf64x4_pd(vecs[4], 0);
+  Packet4d vecs4_1 = _mm512_extractf64x4_pd(vecs[4], 1);
+
+  Packet4d vecs5_0 = _mm512_extractf64x4_pd(vecs[5], 0);
+  Packet4d vecs5_1 = _mm512_extractf64x4_pd(vecs[5], 1);
+
+  Packet4d vecs6_0 = _mm512_extractf64x4_pd(vecs[6], 0);
+  Packet4d vecs6_1 = _mm512_extractf64x4_pd(vecs[6], 1);
+
+  Packet4d vecs7_0 = _mm512_extractf64x4_pd(vecs[7], 0);
+  Packet4d vecs7_1 = _mm512_extractf64x4_pd(vecs[7], 1);
+
+  Packet4d tmp0, tmp1;
+
+  tmp0 = _mm256_hadd_pd(vecs0_0, vecs1_0);
+  tmp0 = _mm256_add_pd(tmp0, _mm256_permute2f128_pd(tmp0, tmp0, 1));
+
+  tmp1 = _mm256_hadd_pd(vecs2_0, vecs3_0);
+  tmp1 = _mm256_add_pd(tmp1, _mm256_permute2f128_pd(tmp1, tmp1, 1));
+
+  __m256d final_0 = _mm256_blend_pd(tmp0, tmp1, 0xC);
+
+  tmp0 = _mm256_hadd_pd(vecs0_1, vecs1_1);
+  tmp0 = _mm256_add_pd(tmp0, _mm256_permute2f128_pd(tmp0, tmp0, 1));
+
+  tmp1 = _mm256_hadd_pd(vecs2_1, vecs3_1);
+  tmp1 = _mm256_add_pd(tmp1, _mm256_permute2f128_pd(tmp1, tmp1, 1));
+
+  final_0 = padd(final_0, _mm256_blend_pd(tmp0, tmp1, 0xC));
+
+  tmp0 = _mm256_hadd_pd(vecs4_0, vecs5_0);
+  tmp0 = _mm256_add_pd(tmp0, _mm256_permute2f128_pd(tmp0, tmp0, 1));
+
+  tmp1 = _mm256_hadd_pd(vecs6_0, vecs7_0);
+  tmp1 = _mm256_add_pd(tmp1, _mm256_permute2f128_pd(tmp1, tmp1, 1));
+
+  __m256d final_1 = _mm256_blend_pd(tmp0, tmp1, 0xC);
+
+  tmp0 = _mm256_hadd_pd(vecs4_1, vecs5_1);
+  tmp0 = _mm256_add_pd(tmp0, _mm256_permute2f128_pd(tmp0, tmp0, 1));
+
+  tmp1 = _mm256_hadd_pd(vecs6_1, vecs7_1);
+  tmp1 = _mm256_add_pd(tmp1, _mm256_permute2f128_pd(tmp1, tmp1, 1));
+
+  final_1 = padd(final_1, _mm256_blend_pd(tmp0, tmp1, 0xC));
+
+  __m512d final_output = _mm512_insertf64x4(final_output, final_0, 0);
+
+  return _mm512_insertf64x4(final_output, final_1, 1);
+}
+
+template <>
+EIGEN_STRONG_INLINE float predux<Packet16f>(const Packet16f& a) {
+  //#ifdef EIGEN_VECTORIZE_AVX512DQ
+#if 0
+  Packet8f lane0 = _mm512_extractf32x8_ps(a, 0);
+  Packet8f lane1 = _mm512_extractf32x8_ps(a, 1);
+  Packet8f sum = padd(lane0, lane1);
+  Packet8f tmp0 = _mm256_hadd_ps(sum, _mm256_permute2f128_ps(a, a, 1));
+  tmp0 = _mm256_hadd_ps(tmp0, tmp0);
+  return pfirst(_mm256_hadd_ps(tmp0, tmp0));
+#else
+  Packet4f lane0 = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane1 = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane2 = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane3 = _mm512_extractf32x4_ps(a, 3);
+  Packet4f sum = padd(padd(lane0, lane1), padd(lane2, lane3));
+  sum = _mm_hadd_ps(sum, sum);
+  sum = _mm_hadd_ps(sum, _mm_permute_ps(sum, 1));
+  return pfirst(sum);
+#endif
+}
+template <>
+EIGEN_STRONG_INLINE double predux<Packet8d>(const Packet8d& a) {
+  Packet4d lane0 = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane1 = _mm512_extractf64x4_pd(a, 1);
+  Packet4d sum = padd(lane0, lane1);
+  Packet4d tmp0 = _mm256_hadd_pd(sum, _mm256_permute2f128_pd(sum, sum, 1));
+  return pfirst(_mm256_hadd_pd(tmp0, tmp0));
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet8f predux_downto4<Packet16f>(const Packet16f& a) {
+#ifdef EIGEN_VECTORIZE_AVX512DQ
+  Packet8f lane0 = _mm512_extractf32x8_ps(a, 0);
+  Packet8f lane1 = _mm512_extractf32x8_ps(a, 1);
+  return padd(lane0, lane1);
+#else
+  Packet4f lane0 = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane1 = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane2 = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane3 = _mm512_extractf32x4_ps(a, 3);
+  Packet4f sum0 = padd(lane0, lane2);
+  Packet4f sum1 = padd(lane1, lane3);
+  return _mm256_insertf128_ps(_mm256_castps128_ps256(sum0), sum1, 1);
+#endif
+}
+template <>
+EIGEN_STRONG_INLINE Packet4d predux_downto4<Packet8d>(const Packet8d& a) {
+  Packet4d lane0 = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane1 = _mm512_extractf64x4_pd(a, 1);
+  Packet4d res = padd(lane0, lane1);
+  return res;
+}
+
+template <>
+EIGEN_STRONG_INLINE float predux_mul<Packet16f>(const Packet16f& a) {
+//#ifdef EIGEN_VECTORIZE_AVX512DQ
+#if 0
+  Packet8f lane0 = _mm512_extractf32x8_ps(a, 0);
+  Packet8f lane1 = _mm512_extractf32x8_ps(a, 1);
+  Packet8f res = pmul(lane0, lane1);
+  res = pmul(res, _mm256_permute2f128_ps(res, res, 1));
+  res = pmul(res, _mm_permute_ps(res, _MM_SHUFFLE(0, 0, 3, 2)));
+  return pfirst(pmul(res, _mm_permute_ps(res, _MM_SHUFFLE(0, 0, 0, 1))));
+#else
+  Packet4f lane0 = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane1 = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane2 = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane3 = _mm512_extractf32x4_ps(a, 3);
+  Packet4f res = pmul(pmul(lane0, lane1), pmul(lane2, lane3));
+  res = pmul(res, _mm_permute_ps(res, _MM_SHUFFLE(0, 0, 3, 2)));
+  return pfirst(pmul(res, _mm_permute_ps(res, _MM_SHUFFLE(0, 0, 0, 1))));
+#endif
+}
+template <>
+EIGEN_STRONG_INLINE double predux_mul<Packet8d>(const Packet8d& a) {
+  Packet4d lane0 = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane1 = _mm512_extractf64x4_pd(a, 1);
+  Packet4d res = pmul(lane0, lane1);
+  res = pmul(res, _mm256_permute2f128_pd(res, res, 1));
+  return pfirst(pmul(res, _mm256_shuffle_pd(res, res, 1)));
+}
+
+template <>
+EIGEN_STRONG_INLINE float predux_min<Packet16f>(const Packet16f& a) {
+  Packet4f lane0 = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane1 = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane2 = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane3 = _mm512_extractf32x4_ps(a, 3);
+  Packet4f res = _mm_min_ps(_mm_min_ps(lane0, lane1), _mm_min_ps(lane2, lane3));
+  res = _mm_min_ps(res, _mm_permute_ps(res, _MM_SHUFFLE(0, 0, 3, 2)));
+  return pfirst(_mm_min_ps(res, _mm_permute_ps(res, _MM_SHUFFLE(0, 0, 0, 1))));
+}
+template <>
+EIGEN_STRONG_INLINE double predux_min<Packet8d>(const Packet8d& a) {
+  Packet4d lane0 = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane1 = _mm512_extractf64x4_pd(a, 1);
+  Packet4d res = _mm256_min_pd(lane0, lane1);
+  res = _mm256_min_pd(res, _mm256_permute2f128_pd(res, res, 1));
+  return pfirst(_mm256_min_pd(res, _mm256_shuffle_pd(res, res, 1)));
+}
+
+template <>
+EIGEN_STRONG_INLINE float predux_max<Packet16f>(const Packet16f& a) {
+  Packet4f lane0 = _mm512_extractf32x4_ps(a, 0);
+  Packet4f lane1 = _mm512_extractf32x4_ps(a, 1);
+  Packet4f lane2 = _mm512_extractf32x4_ps(a, 2);
+  Packet4f lane3 = _mm512_extractf32x4_ps(a, 3);
+  Packet4f res = _mm_max_ps(_mm_max_ps(lane0, lane1), _mm_max_ps(lane2, lane3));
+  res = _mm_max_ps(res, _mm_permute_ps(res, _MM_SHUFFLE(0, 0, 3, 2)));
+  return pfirst(_mm_max_ps(res, _mm_permute_ps(res, _MM_SHUFFLE(0, 0, 0, 1))));
+}
+template <>
+EIGEN_STRONG_INLINE double predux_max<Packet8d>(const Packet8d& a) {
+  Packet4d lane0 = _mm512_extractf64x4_pd(a, 0);
+  Packet4d lane1 = _mm512_extractf64x4_pd(a, 1);
+  Packet4d res = _mm256_max_pd(lane0, lane1);
+  res = _mm256_max_pd(res, _mm256_permute2f128_pd(res, res, 1));
+  return pfirst(_mm256_max_pd(res, _mm256_shuffle_pd(res, res, 1)));
+}
+
+template <int Offset>
+struct palign_impl<Offset, Packet16f> {
+  static EIGEN_STRONG_INLINE void run(Packet16f& first,
+                                      const Packet16f& second) {
+    if (Offset != 0) {
+      __m512i first_idx = _mm512_set_epi32(
+          Offset + 15, Offset + 14, Offset + 13, Offset + 12, Offset + 11,
+          Offset + 10, Offset + 9, Offset + 8, Offset + 7, Offset + 6,
+          Offset + 5, Offset + 4, Offset + 3, Offset + 2, Offset + 1, Offset);
+
+      __m512i second_idx =
+          _mm512_set_epi32(Offset - 1, Offset - 2, Offset - 3, Offset - 4,
+                           Offset - 5, Offset - 6, Offset - 7, Offset - 8,
+                           Offset - 9, Offset - 10, Offset - 11, Offset - 12,
+                           Offset - 13, Offset - 14, Offset - 15, Offset - 16);
+
+      unsigned short mask = 0xFFFF;
+      mask <<= (16 - Offset);
+
+      first = _mm512_permutexvar_ps(first_idx, first);
+      Packet16f tmp = _mm512_permutexvar_ps(second_idx, second);
+      first = _mm512_mask_blend_ps(mask, first, tmp);
+    }
+  }
+};
+template <int Offset>
+struct palign_impl<Offset, Packet8d> {
+  static EIGEN_STRONG_INLINE void run(Packet8d& first, const Packet8d& second) {
+    if (Offset != 0) {
+      __m512i first_idx = _mm512_set_epi32(
+          0, Offset + 7, 0, Offset + 6, 0, Offset + 5, 0, Offset + 4, 0,
+          Offset + 3, 0, Offset + 2, 0, Offset + 1, 0, Offset);
+
+      __m512i second_idx = _mm512_set_epi32(
+          0, Offset - 1, 0, Offset - 2, 0, Offset - 3, 0, Offset - 4, 0,
+          Offset - 5, 0, Offset - 6, 0, Offset - 7, 0, Offset - 8);
+
+      unsigned char mask = 0xFF;
+      mask <<= (8 - Offset);
+
+      first = _mm512_permutexvar_pd(first_idx, first);
+      Packet8d tmp = _mm512_permutexvar_pd(second_idx, second);
+      first = _mm512_mask_blend_pd(mask, first, tmp);
+    }
+  }
+};
+
+
+#define PACK_OUTPUT(OUTPUT, INPUT, INDEX, STRIDE) \
+  EIGEN_INSERT_8f_INTO_16f(OUTPUT[INDEX], INPUT[INDEX], INPUT[INDEX + STRIDE]);
+
+EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet16f, 16>& kernel) {
+  __m512 T0 = _mm512_unpacklo_ps(kernel.packet[0], kernel.packet[1]);
+  __m512 T1 = _mm512_unpackhi_ps(kernel.packet[0], kernel.packet[1]);
+  __m512 T2 = _mm512_unpacklo_ps(kernel.packet[2], kernel.packet[3]);
+  __m512 T3 = _mm512_unpackhi_ps(kernel.packet[2], kernel.packet[3]);
+  __m512 T4 = _mm512_unpacklo_ps(kernel.packet[4], kernel.packet[5]);
+  __m512 T5 = _mm512_unpackhi_ps(kernel.packet[4], kernel.packet[5]);
+  __m512 T6 = _mm512_unpacklo_ps(kernel.packet[6], kernel.packet[7]);
+  __m512 T7 = _mm512_unpackhi_ps(kernel.packet[6], kernel.packet[7]);
+  __m512 T8 = _mm512_unpacklo_ps(kernel.packet[8], kernel.packet[9]);
+  __m512 T9 = _mm512_unpackhi_ps(kernel.packet[8], kernel.packet[9]);
+  __m512 T10 = _mm512_unpacklo_ps(kernel.packet[10], kernel.packet[11]);
+  __m512 T11 = _mm512_unpackhi_ps(kernel.packet[10], kernel.packet[11]);
+  __m512 T12 = _mm512_unpacklo_ps(kernel.packet[12], kernel.packet[13]);
+  __m512 T13 = _mm512_unpackhi_ps(kernel.packet[12], kernel.packet[13]);
+  __m512 T14 = _mm512_unpacklo_ps(kernel.packet[14], kernel.packet[15]);
+  __m512 T15 = _mm512_unpackhi_ps(kernel.packet[14], kernel.packet[15]);
+  __m512 S0 = _mm512_shuffle_ps(T0, T2, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S1 = _mm512_shuffle_ps(T0, T2, _MM_SHUFFLE(3, 2, 3, 2));
+  __m512 S2 = _mm512_shuffle_ps(T1, T3, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S3 = _mm512_shuffle_ps(T1, T3, _MM_SHUFFLE(3, 2, 3, 2));
+  __m512 S4 = _mm512_shuffle_ps(T4, T6, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S5 = _mm512_shuffle_ps(T4, T6, _MM_SHUFFLE(3, 2, 3, 2));
+  __m512 S6 = _mm512_shuffle_ps(T5, T7, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S7 = _mm512_shuffle_ps(T5, T7, _MM_SHUFFLE(3, 2, 3, 2));
+  __m512 S8 = _mm512_shuffle_ps(T8, T10, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S9 = _mm512_shuffle_ps(T8, T10, _MM_SHUFFLE(3, 2, 3, 2));
+  __m512 S10 = _mm512_shuffle_ps(T9, T11, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S11 = _mm512_shuffle_ps(T9, T11, _MM_SHUFFLE(3, 2, 3, 2));
+  __m512 S12 = _mm512_shuffle_ps(T12, T14, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S13 = _mm512_shuffle_ps(T12, T14, _MM_SHUFFLE(3, 2, 3, 2));
+  __m512 S14 = _mm512_shuffle_ps(T13, T15, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S15 = _mm512_shuffle_ps(T13, T15, _MM_SHUFFLE(3, 2, 3, 2));
+
+  EIGEN_EXTRACT_8f_FROM_16f(S0, S0);
+  EIGEN_EXTRACT_8f_FROM_16f(S1, S1);
+  EIGEN_EXTRACT_8f_FROM_16f(S2, S2);
+  EIGEN_EXTRACT_8f_FROM_16f(S3, S3);
+  EIGEN_EXTRACT_8f_FROM_16f(S4, S4);
+  EIGEN_EXTRACT_8f_FROM_16f(S5, S5);
+  EIGEN_EXTRACT_8f_FROM_16f(S6, S6);
+  EIGEN_EXTRACT_8f_FROM_16f(S7, S7);
+  EIGEN_EXTRACT_8f_FROM_16f(S8, S8);
+  EIGEN_EXTRACT_8f_FROM_16f(S9, S9);
+  EIGEN_EXTRACT_8f_FROM_16f(S10, S10);
+  EIGEN_EXTRACT_8f_FROM_16f(S11, S11);
+  EIGEN_EXTRACT_8f_FROM_16f(S12, S12);
+  EIGEN_EXTRACT_8f_FROM_16f(S13, S13);
+  EIGEN_EXTRACT_8f_FROM_16f(S14, S14);
+  EIGEN_EXTRACT_8f_FROM_16f(S15, S15);
+
+  PacketBlock<Packet8f, 32> tmp;
+
+  tmp.packet[0] = _mm256_permute2f128_ps(S0_0, S4_0, 0x20);
+  tmp.packet[1] = _mm256_permute2f128_ps(S1_0, S5_0, 0x20);
+  tmp.packet[2] = _mm256_permute2f128_ps(S2_0, S6_0, 0x20);
+  tmp.packet[3] = _mm256_permute2f128_ps(S3_0, S7_0, 0x20);
+  tmp.packet[4] = _mm256_permute2f128_ps(S0_0, S4_0, 0x31);
+  tmp.packet[5] = _mm256_permute2f128_ps(S1_0, S5_0, 0x31);
+  tmp.packet[6] = _mm256_permute2f128_ps(S2_0, S6_0, 0x31);
+  tmp.packet[7] = _mm256_permute2f128_ps(S3_0, S7_0, 0x31);
+
+  tmp.packet[8] = _mm256_permute2f128_ps(S0_1, S4_1, 0x20);
+  tmp.packet[9] = _mm256_permute2f128_ps(S1_1, S5_1, 0x20);
+  tmp.packet[10] = _mm256_permute2f128_ps(S2_1, S6_1, 0x20);
+  tmp.packet[11] = _mm256_permute2f128_ps(S3_1, S7_1, 0x20);
+  tmp.packet[12] = _mm256_permute2f128_ps(S0_1, S4_1, 0x31);
+  tmp.packet[13] = _mm256_permute2f128_ps(S1_1, S5_1, 0x31);
+  tmp.packet[14] = _mm256_permute2f128_ps(S2_1, S6_1, 0x31);
+  tmp.packet[15] = _mm256_permute2f128_ps(S3_1, S7_1, 0x31);
+
+  // Second set of _m256 outputs
+  tmp.packet[16] = _mm256_permute2f128_ps(S8_0, S12_0, 0x20);
+  tmp.packet[17] = _mm256_permute2f128_ps(S9_0, S13_0, 0x20);
+  tmp.packet[18] = _mm256_permute2f128_ps(S10_0, S14_0, 0x20);
+  tmp.packet[19] = _mm256_permute2f128_ps(S11_0, S15_0, 0x20);
+  tmp.packet[20] = _mm256_permute2f128_ps(S8_0, S12_0, 0x31);
+  tmp.packet[21] = _mm256_permute2f128_ps(S9_0, S13_0, 0x31);
+  tmp.packet[22] = _mm256_permute2f128_ps(S10_0, S14_0, 0x31);
+  tmp.packet[23] = _mm256_permute2f128_ps(S11_0, S15_0, 0x31);
+
+  tmp.packet[24] = _mm256_permute2f128_ps(S8_1, S12_1, 0x20);
+  tmp.packet[25] = _mm256_permute2f128_ps(S9_1, S13_1, 0x20);
+  tmp.packet[26] = _mm256_permute2f128_ps(S10_1, S14_1, 0x20);
+  tmp.packet[27] = _mm256_permute2f128_ps(S11_1, S15_1, 0x20);
+  tmp.packet[28] = _mm256_permute2f128_ps(S8_1, S12_1, 0x31);
+  tmp.packet[29] = _mm256_permute2f128_ps(S9_1, S13_1, 0x31);
+  tmp.packet[30] = _mm256_permute2f128_ps(S10_1, S14_1, 0x31);
+  tmp.packet[31] = _mm256_permute2f128_ps(S11_1, S15_1, 0x31);
+
+  // Pack them into the output
+  PACK_OUTPUT(kernel.packet, tmp.packet, 0, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 1, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 2, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 3, 16);
+
+  PACK_OUTPUT(kernel.packet, tmp.packet, 4, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 5, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 6, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 7, 16);
+
+  PACK_OUTPUT(kernel.packet, tmp.packet, 8, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 9, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 10, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 11, 16);
+
+  PACK_OUTPUT(kernel.packet, tmp.packet, 12, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 13, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 14, 16);
+  PACK_OUTPUT(kernel.packet, tmp.packet, 15, 16);
+}
+#define PACK_OUTPUT_2(OUTPUT, INPUT, INDEX, STRIDE)         \
+  EIGEN_INSERT_8f_INTO_16f(OUTPUT[INDEX], INPUT[2 * INDEX], \
+                           INPUT[2 * INDEX + STRIDE]);
+
+EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet16f, 4>& kernel) {
+  __m512 T0 = _mm512_unpacklo_ps(kernel.packet[0], kernel.packet[1]);
+  __m512 T1 = _mm512_unpackhi_ps(kernel.packet[0], kernel.packet[1]);
+  __m512 T2 = _mm512_unpacklo_ps(kernel.packet[2], kernel.packet[3]);
+  __m512 T3 = _mm512_unpackhi_ps(kernel.packet[2], kernel.packet[3]);
+
+  __m512 S0 = _mm512_shuffle_ps(T0, T2, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S1 = _mm512_shuffle_ps(T0, T2, _MM_SHUFFLE(3, 2, 3, 2));
+  __m512 S2 = _mm512_shuffle_ps(T1, T3, _MM_SHUFFLE(1, 0, 1, 0));
+  __m512 S3 = _mm512_shuffle_ps(T1, T3, _MM_SHUFFLE(3, 2, 3, 2));
+
+  EIGEN_EXTRACT_8f_FROM_16f(S0, S0);
+  EIGEN_EXTRACT_8f_FROM_16f(S1, S1);
+  EIGEN_EXTRACT_8f_FROM_16f(S2, S2);
+  EIGEN_EXTRACT_8f_FROM_16f(S3, S3);
+
+  PacketBlock<Packet8f, 8> tmp;
+
+  tmp.packet[0] = _mm256_permute2f128_ps(S0_0, S1_0, 0x20);
+  tmp.packet[1] = _mm256_permute2f128_ps(S2_0, S3_0, 0x20);
+  tmp.packet[2] = _mm256_permute2f128_ps(S0_0, S1_0, 0x31);
+  tmp.packet[3] = _mm256_permute2f128_ps(S2_0, S3_0, 0x31);
+
+  tmp.packet[4] = _mm256_permute2f128_ps(S0_1, S1_1, 0x20);
+  tmp.packet[5] = _mm256_permute2f128_ps(S2_1, S3_1, 0x20);
+  tmp.packet[6] = _mm256_permute2f128_ps(S0_1, S1_1, 0x31);
+  tmp.packet[7] = _mm256_permute2f128_ps(S2_1, S3_1, 0x31);
+
+  PACK_OUTPUT_2(kernel.packet, tmp.packet, 0, 1);
+  PACK_OUTPUT_2(kernel.packet, tmp.packet, 1, 1);
+  PACK_OUTPUT_2(kernel.packet, tmp.packet, 2, 1);
+  PACK_OUTPUT_2(kernel.packet, tmp.packet, 3, 1);
+}
+
+#define PACK_OUTPUT_SQ_D(OUTPUT, INPUT, INDEX, STRIDE)                \
+  OUTPUT[INDEX] = _mm512_insertf64x4(OUTPUT[INDEX], INPUT[INDEX], 0); \
+  OUTPUT[INDEX] = _mm512_insertf64x4(OUTPUT[INDEX], INPUT[INDEX + STRIDE], 1);
+
+#define PACK_OUTPUT_D(OUTPUT, INPUT, INDEX, STRIDE)                         \
+  OUTPUT[INDEX] = _mm512_insertf64x4(OUTPUT[INDEX], INPUT[(2 * INDEX)], 0); \
+  OUTPUT[INDEX] =                                                           \
+      _mm512_insertf64x4(OUTPUT[INDEX], INPUT[(2 * INDEX) + STRIDE], 1);
+
+EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet8d, 4>& kernel) {
+  __m512d T0 = _mm512_shuffle_pd(kernel.packet[0], kernel.packet[1], 0);
+  __m512d T1 = _mm512_shuffle_pd(kernel.packet[0], kernel.packet[1], 0xff);
+  __m512d T2 = _mm512_shuffle_pd(kernel.packet[2], kernel.packet[3], 0);
+  __m512d T3 = _mm512_shuffle_pd(kernel.packet[2], kernel.packet[3], 0xff);
+
+  PacketBlock<Packet4d, 8> tmp;
+
+  tmp.packet[0] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T0, 0),
+                                         _mm512_extractf64x4_pd(T2, 0), 0x20);
+  tmp.packet[1] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T1, 0),
+                                         _mm512_extractf64x4_pd(T3, 0), 0x20);
+  tmp.packet[2] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T0, 0),
+                                         _mm512_extractf64x4_pd(T2, 0), 0x31);
+  tmp.packet[3] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T1, 0),
+                                         _mm512_extractf64x4_pd(T3, 0), 0x31);
+
+  tmp.packet[4] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T0, 1),
+                                         _mm512_extractf64x4_pd(T2, 1), 0x20);
+  tmp.packet[5] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T1, 1),
+                                         _mm512_extractf64x4_pd(T3, 1), 0x20);
+  tmp.packet[6] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T0, 1),
+                                         _mm512_extractf64x4_pd(T2, 1), 0x31);
+  tmp.packet[7] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T1, 1),
+                                         _mm512_extractf64x4_pd(T3, 1), 0x31);
+
+  PACK_OUTPUT_D(kernel.packet, tmp.packet, 0, 1);
+  PACK_OUTPUT_D(kernel.packet, tmp.packet, 1, 1);
+  PACK_OUTPUT_D(kernel.packet, tmp.packet, 2, 1);
+  PACK_OUTPUT_D(kernel.packet, tmp.packet, 3, 1);
+}
+
+EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet8d, 8>& kernel) {
+  __m512d T0 = _mm512_unpacklo_pd(kernel.packet[0], kernel.packet[1]);
+  __m512d T1 = _mm512_unpackhi_pd(kernel.packet[0], kernel.packet[1]);
+  __m512d T2 = _mm512_unpacklo_pd(kernel.packet[2], kernel.packet[3]);
+  __m512d T3 = _mm512_unpackhi_pd(kernel.packet[2], kernel.packet[3]);
+  __m512d T4 = _mm512_unpacklo_pd(kernel.packet[4], kernel.packet[5]);
+  __m512d T5 = _mm512_unpackhi_pd(kernel.packet[4], kernel.packet[5]);
+  __m512d T6 = _mm512_unpacklo_pd(kernel.packet[6], kernel.packet[7]);
+  __m512d T7 = _mm512_unpackhi_pd(kernel.packet[6], kernel.packet[7]);
+
+  PacketBlock<Packet4d, 16> tmp;
+
+  tmp.packet[0] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T0, 0),
+                                         _mm512_extractf64x4_pd(T2, 0), 0x20);
+  tmp.packet[1] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T1, 0),
+                                         _mm512_extractf64x4_pd(T3, 0), 0x20);
+  tmp.packet[2] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T0, 0),
+                                         _mm512_extractf64x4_pd(T2, 0), 0x31);
+  tmp.packet[3] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T1, 0),
+                                         _mm512_extractf64x4_pd(T3, 0), 0x31);
+
+  tmp.packet[4] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T0, 1),
+                                         _mm512_extractf64x4_pd(T2, 1), 0x20);
+  tmp.packet[5] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T1, 1),
+                                         _mm512_extractf64x4_pd(T3, 1), 0x20);
+  tmp.packet[6] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T0, 1),
+                                         _mm512_extractf64x4_pd(T2, 1), 0x31);
+  tmp.packet[7] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T1, 1),
+                                         _mm512_extractf64x4_pd(T3, 1), 0x31);
+
+  tmp.packet[8] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T4, 0),
+                                         _mm512_extractf64x4_pd(T6, 0), 0x20);
+  tmp.packet[9] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T5, 0),
+                                         _mm512_extractf64x4_pd(T7, 0), 0x20);
+  tmp.packet[10] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T4, 0),
+                                          _mm512_extractf64x4_pd(T6, 0), 0x31);
+  tmp.packet[11] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T5, 0),
+                                          _mm512_extractf64x4_pd(T7, 0), 0x31);
+
+  tmp.packet[12] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T4, 1),
+                                          _mm512_extractf64x4_pd(T6, 1), 0x20);
+  tmp.packet[13] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T5, 1),
+                                          _mm512_extractf64x4_pd(T7, 1), 0x20);
+  tmp.packet[14] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T4, 1),
+                                          _mm512_extractf64x4_pd(T6, 1), 0x31);
+  tmp.packet[15] = _mm256_permute2f128_pd(_mm512_extractf64x4_pd(T5, 1),
+                                          _mm512_extractf64x4_pd(T7, 1), 0x31);
+
+  PACK_OUTPUT_SQ_D(kernel.packet, tmp.packet, 0, 8);
+  PACK_OUTPUT_SQ_D(kernel.packet, tmp.packet, 1, 8);
+  PACK_OUTPUT_SQ_D(kernel.packet, tmp.packet, 2, 8);
+  PACK_OUTPUT_SQ_D(kernel.packet, tmp.packet, 3, 8);
+
+  PACK_OUTPUT_SQ_D(kernel.packet, tmp.packet, 4, 8);
+  PACK_OUTPUT_SQ_D(kernel.packet, tmp.packet, 5, 8);
+  PACK_OUTPUT_SQ_D(kernel.packet, tmp.packet, 6, 8);
+  PACK_OUTPUT_SQ_D(kernel.packet, tmp.packet, 7, 8);
+}
+template <>
+EIGEN_STRONG_INLINE Packet16f pblend(const Selector<16>& /*ifPacket*/,
+                                     const Packet16f& /*thenPacket*/,
+                                     const Packet16f& /*elsePacket*/) {
+  assert(false && "To be implemented");
+  return Packet16f();
+}
+template <>
+EIGEN_STRONG_INLINE Packet8d pblend(const Selector<8>& /*ifPacket*/,
+                                    const Packet8d& /*thenPacket*/,
+                                    const Packet8d& /*elsePacket*/) {
+  assert(false && "To be implemented");
+  return Packet8d();
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_PACKET_MATH_AVX512_H

DELETED 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Core_arch_AltiVec_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Core_arch_AltiVec_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/AltiVec COMPONENT Devel
-)

Index: 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/Complex.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/Complex.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/Complex.h
@@ -1,44 +1,50 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010-2016 Konstantinos Margaritis <markos@freevec.org>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
-#ifndef EIGEN_COMPLEX_ALTIVEC_H
-#define EIGEN_COMPLEX_ALTIVEC_H
+#ifndef EIGEN_COMPLEX32_ALTIVEC_H
+#define EIGEN_COMPLEX32_ALTIVEC_H
 
 namespace Eigen {
 
 namespace internal {
 
-static Packet4ui  p4ui_CONJ_XOR = vec_mergeh((Packet4ui)p4i_ZERO, (Packet4ui)p4f_ZERO_);//{ 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
-static Packet16uc p16uc_COMPLEX_RE   = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 };
-static Packet16uc p16uc_COMPLEX_IM   = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 1), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
-static Packet16uc p16uc_COMPLEX_REV  = vec_sld(p16uc_REVERSE, p16uc_REVERSE, 8);//{ 4,5,6,7, 0,1,2,3, 12,13,14,15, 8,9,10,11 };
-static Packet16uc p16uc_COMPLEX_REV2 = vec_sld(p16uc_FORWARD, p16uc_FORWARD, 8);//{ 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
-static Packet16uc p16uc_PSET_HI = (Packet16uc) vec_mergeh((Packet4ui) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet4ui) vec_splat((Packet4ui)p16uc_FORWARD, 1));//{ 0,1,2,3, 4,5,6,7, 0,1,2,3, 4,5,6,7 };
-static Packet16uc p16uc_PSET_LO = (Packet16uc) vec_mergeh((Packet4ui) vec_splat((Packet4ui)p16uc_FORWARD, 2), (Packet4ui) vec_splat((Packet4ui)p16uc_FORWARD, 3));//{ 8,9,10,11, 12,13,14,15, 8,9,10,11, 12,13,14,15 };
+static Packet4ui  p4ui_CONJ_XOR = vec_mergeh((Packet4ui)p4i_ZERO, (Packet4ui)p4f_MZERO);//{ 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
+#ifdef __VSX__
+#if defined(_BIG_ENDIAN)
+static Packet2ul  p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2d_MZERO, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
+static Packet2ul  p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO,  (Packet4ui) p2d_MZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
+#else
+static Packet2ul  p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO,  (Packet4ui) p2d_MZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
+static Packet2ul  p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2d_MZERO, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
+#endif
+#endif
 
 //---------- float ----------
 struct Packet2cf
 {
-  EIGEN_STRONG_INLINE Packet2cf() {}
+  EIGEN_STRONG_INLINE explicit Packet2cf() : v(p4f_ZERO) {}
   EIGEN_STRONG_INLINE explicit Packet2cf(const Packet4f& a) : v(a) {}
   Packet4f  v;
 };
 
 template<> struct packet_traits<std::complex<float> >  : default_packet_traits
 {
   typedef Packet2cf type;
+  typedef Packet2cf half;
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 1,
     size = 2,
+    HasHalfPacket = 0,
 
     HasAdd    = 1,
     HasSub    = 1,
     HasMul    = 1,
     HasDiv    = 1,
@@ -45,69 +51,82 @@
     HasNegate = 1,
     HasAbs    = 0,
     HasAbs2   = 0,
     HasMin    = 0,
     HasMax    = 0,
+#ifdef __VSX__
+    HasBlend  = 1,
+#endif
     HasSetLinear = 0
   };
 };
 
-template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2}; };
+template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2, alignment=Aligned16}; typedef Packet2cf half; };
 
 template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>&  from)
 {
   Packet2cf res;
-  /* On AltiVec we cannot load 64-bit registers, so wa have to take care of alignment */
-  if((ptrdiff_t(&from) % 16) == 0)
+  if((std::ptrdiff_t(&from) % 16) == 0)
     res.v = pload<Packet4f>((const float *)&from);
   else
     res.v = ploadu<Packet4f>((const float *)&from);
-  res.v = vec_perm(res.v, res.v, p16uc_PSET_HI);
+  res.v = vec_perm(res.v, res.v, p16uc_PSET64_HI);
   return res;
 }
 
-template<> EIGEN_STRONG_INLINE Packet2cf padd<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(vec_add(a.v,b.v)); }
-template<> EIGEN_STRONG_INLINE Packet2cf psub<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(vec_sub(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cf pload<Packet2cf>(const std::complex<float>*        from) { return Packet2cf(pload<Packet4f>((const float *) from)); }
+template<> EIGEN_STRONG_INLINE Packet2cf ploadu<Packet2cf>(const std::complex<float>*       from) { return Packet2cf(ploadu<Packet4f>((const float*) from)); }
+template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<float>*     from) { return pset1<Packet2cf>(*from); }
+
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { pstore((float*)to, from.v); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { pstoreu((float*)to, from.v); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, Index stride)
+{
+  std::complex<float> EIGEN_ALIGN16 af[2];
+  af[0] = from[0*stride];
+  af[1] = from[1*stride];
+  return pload<Packet2cf>(af);
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, Index stride)
+{
+  std::complex<float> EIGEN_ALIGN16 af[2];
+  pstore<std::complex<float> >((std::complex<float> *) af, from);
+  to[0*stride] = af[0];
+  to[1*stride] = af[1];
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cf padd<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(a.v + b.v); }
+template<> EIGEN_STRONG_INLINE Packet2cf psub<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(a.v - b.v); }
 template<> EIGEN_STRONG_INLINE Packet2cf pnegate(const Packet2cf& a) { return Packet2cf(pnegate(a.v)); }
-template<> EIGEN_STRONG_INLINE Packet2cf pconj(const Packet2cf& a) { return Packet2cf((Packet4f)vec_xor((Packet4ui)a.v, p4ui_CONJ_XOR)); }
+template<> EIGEN_STRONG_INLINE Packet2cf pconj(const Packet2cf& a) { return Packet2cf(pxor<Packet4f>(a.v, reinterpret_cast<Packet4f>(p4ui_CONJ_XOR))); }
 
 template<> EIGEN_STRONG_INLINE Packet2cf pmul<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
 {
   Packet4f v1, v2;
 
   // Permute and multiply the real parts of a and b
-  v1 = vec_perm(a.v, a.v, p16uc_COMPLEX_RE);
+  v1 = vec_perm(a.v, a.v, p16uc_PSET32_WODD);
   // Get the imaginary parts of a
-  v2 = vec_perm(a.v, a.v, p16uc_COMPLEX_IM);
+  v2 = vec_perm(a.v, a.v, p16uc_PSET32_WEVEN);
   // multiply a_re * b 
   v1 = vec_madd(v1, b.v, p4f_ZERO);
   // multiply a_im * b and get the conjugate result
   v2 = vec_madd(v2, b.v, p4f_ZERO);
-  v2 = (Packet4f) vec_xor((Packet4ui)v2, p4ui_CONJ_XOR);
-  // permute back to a proper order
-  v2 = vec_perm(v2, v2, p16uc_COMPLEX_REV);
-  
-  return Packet2cf(vec_add(v1, v2));
-}
-
-template<> EIGEN_STRONG_INLINE Packet2cf pand   <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(vec_and(a.v,b.v)); }
-template<> EIGEN_STRONG_INLINE Packet2cf por    <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(vec_or(a.v,b.v)); }
-template<> EIGEN_STRONG_INLINE Packet2cf pxor   <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(vec_xor(a.v,b.v)); }
-template<> EIGEN_STRONG_INLINE Packet2cf pandnot<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(vec_and(a.v, vec_nor(b.v,b.v))); }
-
-template<> EIGEN_STRONG_INLINE Packet2cf pload <Packet2cf>(const std::complex<float>* from) { EIGEN_DEBUG_ALIGNED_LOAD return Packet2cf(pload<Packet4f>((const float*)from)); }
-template<> EIGEN_STRONG_INLINE Packet2cf ploadu<Packet2cf>(const std::complex<float>* from) { EIGEN_DEBUG_UNALIGNED_LOAD return Packet2cf(ploadu<Packet4f>((const float*)from)); }
-
-template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<float>*     from)
-{
-  return pset1<Packet2cf>(*from);
-}
-
-template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((float*)to, from.v); }
-template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((float*)to, from.v); }
-
-template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> *   addr) { vec_dstt((float *)addr, DST_CTRL(2,2,32), DST_CHAN); }
+  v2 = reinterpret_cast<Packet4f>(pxor(v2, reinterpret_cast<Packet4f>(p4ui_CONJ_XOR)));
+  // permute back to a proper order
+  v2 = vec_perm(v2, v2, p16uc_COMPLEX32_REV);
+  
+  return Packet2cf(padd<Packet4f>(v1, v2));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cf pand   <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pand<Packet4f>(a.v, b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cf por    <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(por<Packet4f>(a.v, b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cf pxor   <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pxor<Packet4f>(a.v, b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cf pandnot<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pandnot<Packet4f>(a.v, b.v)); }
+
+template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr)    { EIGEN_PPC_PREFETCH(addr); }
 
 template<> EIGEN_STRONG_INLINE std::complex<float>  pfirst<Packet2cf>(const Packet2cf& a)
 {
   std::complex<float> EIGEN_ALIGN16 res[2];
   pstore((float *)&res, a.v);
@@ -116,52 +135,60 @@
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cf preverse(const Packet2cf& a)
 {
   Packet4f rev_a;
-  rev_a = vec_perm(a.v, a.v, p16uc_COMPLEX_REV2);
+  rev_a = vec_perm(a.v, a.v, p16uc_COMPLEX32_REV2);
   return Packet2cf(rev_a);
 }
 
 template<> EIGEN_STRONG_INLINE std::complex<float> predux<Packet2cf>(const Packet2cf& a)
 {
   Packet4f b;
-  b = (Packet4f) vec_sld(a.v, a.v, 8);
-  b = padd(a.v, b);
-  return pfirst(Packet2cf(b));
+  b = vec_sld(a.v, a.v, 8);
+  b = padd<Packet4f>(a.v, b);
+  return pfirst<Packet2cf>(Packet2cf(b));
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cf preduxp<Packet2cf>(const Packet2cf* vecs)
 {
   Packet4f b1, b2;
-  
-  b1 = (Packet4f) vec_sld(vecs[0].v, vecs[1].v, 8);
-  b2 = (Packet4f) vec_sld(vecs[1].v, vecs[0].v, 8);
-  b2 = (Packet4f) vec_sld(b2, b2, 8);
-  b2 = padd(b1, b2);
+#ifdef _BIG_ENDIAN  
+  b1 = vec_sld(vecs[0].v, vecs[1].v, 8);
+  b2 = vec_sld(vecs[1].v, vecs[0].v, 8);
+#else
+  b1 = vec_sld(vecs[1].v, vecs[0].v, 8);
+  b2 = vec_sld(vecs[0].v, vecs[1].v, 8);
+#endif
+  b2 = vec_sld(b2, b2, 8);
+  b2 = padd<Packet4f>(b1, b2);
 
   return Packet2cf(b2);
 }
 
 template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet2cf>(const Packet2cf& a)
 {
   Packet4f b;
   Packet2cf prod;
-  b = (Packet4f) vec_sld(a.v, a.v, 8);
-  prod = pmul(a, Packet2cf(b));
+  b = vec_sld(a.v, a.v, 8);
+  prod = pmul<Packet2cf>(a, Packet2cf(b));
 
-  return pfirst(prod);
+  return pfirst<Packet2cf>(prod);
 }
 
 template<int Offset>
 struct palign_impl<Offset,Packet2cf>
 {
   static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second)
   {
     if (Offset==1)
     {
+#ifdef _BIG_ENDIAN
       first.v = vec_sld(first.v, second.v, 8);
+#else
+      first.v = vec_sld(second.v, first.v, 8);
+#endif
     }
   }
 };
 
 template<> struct conj_helper<Packet2cf, Packet2cf, false,true>
@@ -194,24 +221,241 @@
   EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& a, const Packet2cf& b) const
   {
     return pconj(internal::pmul(a, b));
   }
 };
+
+template<> struct conj_helper<Packet4f, Packet2cf, false,false>
+{
+  EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet4f& x, const Packet2cf& y, const Packet2cf& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Packet2cf pmul(const Packet4f& x, const Packet2cf& y) const
+  { return Packet2cf(internal::pmul<Packet4f>(x, y.v)); }
+};
+
+template<> struct conj_helper<Packet2cf, Packet4f, false,false>
+{
+  EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet4f& y, const Packet2cf& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& x, const Packet4f& y) const
+  { return Packet2cf(internal::pmul<Packet4f>(x.v, y)); }
+};
 
 template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
 {
   // TODO optimize it for AltiVec
-  Packet2cf res = conj_helper<Packet2cf,Packet2cf,false,true>().pmul(a,b);
-  Packet4f s = vec_madd(b.v, b.v, p4f_ZERO);
-  return Packet2cf(pdiv(res.v, vec_add(s,vec_perm(s, s, p16uc_COMPLEX_REV))));
+  Packet2cf res = conj_helper<Packet2cf,Packet2cf,false,true>().pmul(a, b);
+  Packet4f s = pmul<Packet4f>(b.v, b.v);
+  return Packet2cf(pdiv(res.v, padd<Packet4f>(s, vec_perm(s, s, p16uc_COMPLEX32_REV))));
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cf pcplxflip<Packet2cf>(const Packet2cf& x)
 {
-  return Packet2cf(vec_perm(x.v, x.v, p16uc_COMPLEX_REV));
+  return Packet2cf(vec_perm(x.v, x.v, p16uc_COMPLEX32_REV));
+}
+
+EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet2cf,2>& kernel)
+{
+  Packet4f tmp = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_HI);
+  kernel.packet[1].v = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_LO);
+  kernel.packet[0].v = tmp;
+}
+
+#ifdef __VSX__
+template<> EIGEN_STRONG_INLINE Packet2cf pblend(const Selector<2>& ifPacket, const Packet2cf& thenPacket, const Packet2cf& elsePacket) {
+  Packet2cf result;
+  result.v = reinterpret_cast<Packet4f>(pblend<Packet2d>(ifPacket, reinterpret_cast<Packet2d>(thenPacket.v), reinterpret_cast<Packet2d>(elsePacket.v)));
+  return result;
+}
+#endif
+
+//---------- double ----------
+#ifdef __VSX__
+struct Packet1cd
+{
+  EIGEN_STRONG_INLINE Packet1cd() {}
+  EIGEN_STRONG_INLINE explicit Packet1cd(const Packet2d& a) : v(a) {}
+  Packet2d v;
+};
+
+template<> struct packet_traits<std::complex<double> >  : default_packet_traits
+{
+  typedef Packet1cd type;
+  typedef Packet1cd half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 0,
+    size = 1,
+    HasHalfPacket = 0,
+
+    HasAdd    = 1,
+    HasSub    = 1,
+    HasMul    = 1,
+    HasDiv    = 1,
+    HasNegate = 1,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasSetLinear = 0
+  };
+};
+
+template<> struct unpacket_traits<Packet1cd> { typedef std::complex<double> type; enum {size=1, alignment=Aligned16}; typedef Packet1cd half; };
+
+template<> EIGEN_STRONG_INLINE Packet1cd pload <Packet1cd>(const std::complex<double>* from) { return Packet1cd(pload<Packet2d>((const double*)from)); }
+template<> EIGEN_STRONG_INLINE Packet1cd ploadu<Packet1cd>(const std::complex<double>* from) { return Packet1cd(ploadu<Packet2d>((const double*)from)); }
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { pstore((double*)to, from.v); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { pstoreu((double*)to, from.v); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd pset1<Packet1cd>(const std::complex<double>&  from)
+{ /* here we really have to use unaligned loads :( */ return ploadu<Packet1cd>(&from); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet1cd pgather<std::complex<double>, Packet1cd>(const std::complex<double>* from, Index stride)
+{
+  std::complex<double> EIGEN_ALIGN16 af[2];
+  af[0] = from[0*stride];
+  af[1] = from[1*stride];
+  return pload<Packet1cd>(af);
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet1cd>(std::complex<double>* to, const Packet1cd& from, Index stride)
+{
+  std::complex<double> EIGEN_ALIGN16 af[2];
+  pstore<std::complex<double> >(af, from);
+  to[0*stride] = af[0];
+  to[1*stride] = af[1];
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd padd<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(a.v + b.v); }
+template<> EIGEN_STRONG_INLINE Packet1cd psub<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(a.v - b.v); }
+template<> EIGEN_STRONG_INLINE Packet1cd pnegate(const Packet1cd& a) { return Packet1cd(pnegate(Packet2d(a.v))); }
+template<> EIGEN_STRONG_INLINE Packet1cd pconj(const Packet1cd& a) { return Packet1cd(pxor(a.v, reinterpret_cast<Packet2d>(p2ul_CONJ_XOR2))); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd pmul<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  Packet2d a_re, a_im, v1, v2;
+
+  // Permute and multiply the real parts of a and b
+  a_re = vec_perm(a.v, a.v, p16uc_PSET64_HI);
+  // Get the imaginary parts of a
+  a_im = vec_perm(a.v, a.v, p16uc_PSET64_LO);
+  // multiply a_re * b
+  v1 = vec_madd(a_re, b.v, p2d_ZERO);
+  // multiply a_im * b and get the conjugate result
+  v2 = vec_madd(a_im, b.v, p2d_ZERO);
+  v2 = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(v2), reinterpret_cast<Packet4ui>(v2), 8));
+  v2 = pxor(v2, reinterpret_cast<Packet2d>(p2ul_CONJ_XOR1));
+
+  return Packet1cd(padd<Packet2d>(v1, v2));
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd pand   <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(pand(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd por    <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(por(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd pxor   <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(pxor(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd pandnot<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(pandnot(a.v, b.v)); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<double>*     from)  { return pset1<Packet1cd>(*from); }
+
+template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr)    { EIGEN_PPC_PREFETCH(addr); }
+
+template<> EIGEN_STRONG_INLINE std::complex<double>  pfirst<Packet1cd>(const Packet1cd& a)
+{
+  std::complex<double> EIGEN_ALIGN16 res[2];
+  pstore<std::complex<double> >(res, a);
+
+  return res[0];
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd preverse(const Packet1cd& a) { return a; }
+
+template<> EIGEN_STRONG_INLINE std::complex<double> predux<Packet1cd>(const Packet1cd& a) { return pfirst(a); }
+template<> EIGEN_STRONG_INLINE Packet1cd preduxp<Packet1cd>(const Packet1cd* vecs)        { return vecs[0]; }
+
+template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet1cd>(const Packet1cd& a) { return pfirst(a); }
+
+template<int Offset>
+struct palign_impl<Offset,Packet1cd>
+{
+  static EIGEN_STRONG_INLINE void run(Packet1cd& /*first*/, const Packet1cd& /*second*/)
+  {
+    // FIXME is it sure we never have to align a Packet1cd?
+    // Even though a std::complex<double> has 16 bytes, it is not necessarily aligned on a 16 bytes boundary...
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, false,true>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return internal::pmul(a, pconj(b));
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, true,false>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return internal::pmul(pconj(a), b);
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, true,true>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return pconj(internal::pmul(a, b));
+  }
+};
+template<> struct conj_helper<Packet2d, Packet1cd, false,false>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet2d& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet2d& x, const Packet1cd& y) const
+  { return Packet1cd(internal::pmul<Packet2d>(x, y.v)); }
+};
+
+template<> struct conj_helper<Packet1cd, Packet2d, false,false>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet2d& y, const Packet1cd& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& x, const Packet2d& y) const
+  { return Packet1cd(internal::pmul<Packet2d>(x.v, y)); }
+};
+
+template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  // TODO optimize it for AltiVec
+  Packet1cd res = conj_helper<Packet1cd,Packet1cd,false,true>().pmul(a,b);
+  Packet2d s = pmul<Packet2d>(b.v, b.v);
+  return Packet1cd(pdiv(res.v, padd<Packet2d>(s, vec_perm(s, s, p16uc_REVERSE64))));
+}
+
+EIGEN_STRONG_INLINE Packet1cd pcplxflip/*<Packet1cd>*/(const Packet1cd& x)
+{
+  return Packet1cd(preverse(Packet2d(x.v)));
 }
 
+EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet1cd,2>& kernel)
+{
+  Packet2d tmp = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_HI);
+  kernel.packet[1].v = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_LO);
+  kernel.packet[0].v = tmp;
+}
+#endif // __VSX__
 } // end namespace internal
 
 } // end namespace Eigen
 
-#endif // EIGEN_COMPLEX_ALTIVEC_H
+#endif // EIGEN_COMPLEX32_ALTIVEC_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/AltiVec/MathFunctions.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/MathFunctions.h
@@ -0,0 +1,322 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2007 Julien Pommier
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2016 Konstantinos Margaritis <markos@freevec.org>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/* The sin, cos, exp, and log functions of this file come from
+ * Julien Pommier's sse math library: http://gruntthepeon.free.fr/ssemath/
+ */
+
+#ifndef EIGEN_MATH_FUNCTIONS_ALTIVEC_H
+#define EIGEN_MATH_FUNCTIONS_ALTIVEC_H
+
+namespace Eigen {
+
+namespace internal {
+
+static _EIGEN_DECLARE_CONST_Packet4f(1 , 1.0f);
+static _EIGEN_DECLARE_CONST_Packet4f(half, 0.5f);
+static _EIGEN_DECLARE_CONST_Packet4i(0x7f, 0x7f);
+static _EIGEN_DECLARE_CONST_Packet4i(23, 23);
+
+static _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(inv_mant_mask, ~0x7f800000);
+
+/* the smallest non denormalized float number */
+static _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(min_norm_pos,  0x00800000);
+static _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(minus_inf,     0xff800000); // -1.f/0.f
+static _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(minus_nan,     0xffffffff);
+  
+/* natural logarithm computed for 4 simultaneous float
+  return NaN for x <= 0
+*/
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_SQRTHF, 0.707106781186547524f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p0, 7.0376836292E-2f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p1, - 1.1514610310E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p2, 1.1676998740E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p3, - 1.2420140846E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p4, + 1.4249322787E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p5, - 1.6668057665E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p6, + 2.0000714765E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p7, - 2.4999993993E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p8, + 3.3333331174E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_q1, -2.12194440e-4f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_log_q2, 0.693359375f);
+
+static _EIGEN_DECLARE_CONST_Packet4f(exp_hi,  88.3762626647950f);
+static _EIGEN_DECLARE_CONST_Packet4f(exp_lo, -88.3762626647949f);
+
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_LOG2EF, 1.44269504088896341f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_C1, 0.693359375f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_C2, -2.12194440e-4f);
+
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p0, 1.9875691500E-4f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p1, 1.3981999507E-3f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p2, 8.3334519073E-3f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p3, 4.1665795894E-2f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p4, 1.6666665459E-1f);
+static _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p5, 5.0000001201E-1f);
+
+#ifdef __VSX__
+static _EIGEN_DECLARE_CONST_Packet2d(1 , 1.0);
+static _EIGEN_DECLARE_CONST_Packet2d(2 , 2.0);
+static _EIGEN_DECLARE_CONST_Packet2d(half, 0.5);
+
+static _EIGEN_DECLARE_CONST_Packet2d(exp_hi,  709.437);
+static _EIGEN_DECLARE_CONST_Packet2d(exp_lo, -709.436139303);
+
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_LOG2EF, 1.4426950408889634073599);
+
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p0, 1.26177193074810590878e-4);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p1, 3.02994407707441961300e-2);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p2, 9.99999999999999999910e-1);
+
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q0, 3.00198505138664455042e-6);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q1, 2.52448340349684104192e-3);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q2, 2.27265548208155028766e-1);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q3, 2.00000000000000000009e0);
+
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C1, 0.693145751953125);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
+
+#ifdef __POWER8_VECTOR__
+static Packet2l p2l_1023 = { 1023, 1023 };
+static Packet2ul p2ul_52 = { 52, 52 };
+#endif
+
+#endif
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f plog<Packet4f>(const Packet4f& _x)
+{
+  Packet4f x = _x;
+
+  Packet4i emm0;
+
+  /* isvalid_mask is 0 if x < 0 or x is NaN. */
+  Packet4ui isvalid_mask = reinterpret_cast<Packet4ui>(vec_cmpge(x, p4f_ZERO));
+  Packet4ui iszero_mask = reinterpret_cast<Packet4ui>(vec_cmpeq(x, p4f_ZERO));
+
+  x = pmax(x, p4f_min_norm_pos);  /* cut off denormalized stuff */
+  emm0 = vec_sr(reinterpret_cast<Packet4i>(x),
+                reinterpret_cast<Packet4ui>(p4i_23));
+
+  /* keep only the fractional part */
+  x = pand(x, p4f_inv_mant_mask);
+  x = por(x, p4f_half);
+
+  emm0 = psub(emm0, p4i_0x7f);
+  Packet4f e = padd(vec_ctf(emm0, 0), p4f_1);
+
+  /* part2:
+     if( x < SQRTHF ) {
+       e -= 1;
+       x = x + x - 1.0;
+     } else { x = x - 1.0; }
+  */
+  Packet4f mask = reinterpret_cast<Packet4f>(vec_cmplt(x, p4f_cephes_SQRTHF));
+  Packet4f tmp = pand(x, mask);
+  x = psub(x, p4f_1);
+  e = psub(e, pand(p4f_1, mask));
+  x = padd(x, tmp);
+
+  Packet4f x2 = pmul(x,x);
+  Packet4f x3 = pmul(x2,x);
+
+  Packet4f y, y1, y2;
+  y  = pmadd(p4f_cephes_log_p0, x, p4f_cephes_log_p1);
+  y1 = pmadd(p4f_cephes_log_p3, x, p4f_cephes_log_p4);
+  y2 = pmadd(p4f_cephes_log_p6, x, p4f_cephes_log_p7);
+  y  = pmadd(y , x, p4f_cephes_log_p2);
+  y1 = pmadd(y1, x, p4f_cephes_log_p5);
+  y2 = pmadd(y2, x, p4f_cephes_log_p8);
+  y = pmadd(y, x3, y1);
+  y = pmadd(y, x3, y2);
+  y = pmul(y, x3);
+
+  y1 = pmul(e, p4f_cephes_log_q1);
+  tmp = pmul(x2, p4f_half);
+  y = padd(y, y1);
+  x = psub(x, tmp);
+  y2 = pmul(e, p4f_cephes_log_q2);
+  x = padd(x, y);
+  x = padd(x, y2);
+  // negative arg will be NAN, 0 will be -INF
+  x = vec_sel(x, p4f_minus_inf, iszero_mask);
+  x = vec_sel(p4f_minus_nan, x, isvalid_mask);
+  return x;
+}
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f pexp<Packet4f>(const Packet4f& _x)
+{
+  Packet4f x = _x;
+
+  Packet4f tmp, fx;
+  Packet4i emm0;
+
+  // clamp x
+  x = pmax(pmin(x, p4f_exp_hi), p4f_exp_lo);
+
+  // express exp(x) as exp(g + n*log(2))
+  fx = pmadd(x, p4f_cephes_LOG2EF, p4f_half);
+
+  fx = pfloor(fx);
+
+  tmp = pmul(fx, p4f_cephes_exp_C1);
+  Packet4f z = pmul(fx, p4f_cephes_exp_C2);
+  x = psub(x, tmp);
+  x = psub(x, z);
+
+  z = pmul(x,x);
+
+  Packet4f y = p4f_cephes_exp_p0;
+  y = pmadd(y, x, p4f_cephes_exp_p1);
+  y = pmadd(y, x, p4f_cephes_exp_p2);
+  y = pmadd(y, x, p4f_cephes_exp_p3);
+  y = pmadd(y, x, p4f_cephes_exp_p4);
+  y = pmadd(y, x, p4f_cephes_exp_p5);
+  y = pmadd(y, z, x);
+  y = padd(y, p4f_1);
+
+  // build 2^n
+  emm0 = vec_cts(fx, 0);
+  emm0 = vec_add(emm0, p4i_0x7f);
+  emm0 = vec_sl(emm0, reinterpret_cast<Packet4ui>(p4i_23));
+
+  // Altivec's max & min operators just drop silent NaNs. Check NaNs in 
+  // inputs and return them unmodified.
+  Packet4ui isnumber_mask = reinterpret_cast<Packet4ui>(vec_cmpeq(_x, _x));
+  return vec_sel(_x, pmax(pmul(y, reinterpret_cast<Packet4f>(emm0)), _x),
+                 isnumber_mask);
+}
+
+#ifndef EIGEN_COMP_CLANG
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f prsqrt<Packet4f>(const Packet4f& x)
+{
+  return  vec_rsqrt(x);
+}
+#endif
+
+#ifdef __VSX__
+#ifndef EIGEN_COMP_CLANG
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d prsqrt<Packet2d>(const Packet2d& x)
+{
+  return  vec_rsqrt(x);
+}
+#endif
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f psqrt<Packet4f>(const Packet4f& x)
+{
+  return  vec_sqrt(x);
+}
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d psqrt<Packet2d>(const Packet2d& x)
+{
+  return  vec_sqrt(x);
+}
+
+// VSX support varies between different compilers and even different
+// versions of the same compiler.  For gcc version >= 4.9.3, we can use
+// vec_cts to efficiently convert Packet2d to Packet2l.  Otherwise, use
+// a slow version that works with older compilers. 
+// Update: apparently vec_cts/vec_ctf intrinsics for 64-bit doubles
+// are buggy, https://gcc.gnu.org/bugzilla/show_bug.cgi?id=70963
+static inline Packet2l ConvertToPacket2l(const Packet2d& x) {
+#if EIGEN_GNUC_AT_LEAST(5, 4) || \
+    (EIGEN_GNUC_AT(6, 1) && __GNUC_PATCHLEVEL__ >= 1)
+  return vec_cts(x, 0);    // TODO: check clang version.
+#else
+  double tmp[2];
+  memcpy(tmp, &x, sizeof(tmp));
+  Packet2l l = { static_cast<long long>(tmp[0]),
+                 static_cast<long long>(tmp[1]) };
+  return l;
+#endif
+}
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d pexp<Packet2d>(const Packet2d& _x)
+{
+  Packet2d x = _x;
+
+  Packet2d tmp, fx;
+  Packet2l emm0;
+
+  // clamp x
+  x = pmax(pmin(x, p2d_exp_hi), p2d_exp_lo);
+
+  /* express exp(x) as exp(g + n*log(2)) */
+  fx = pmadd(x, p2d_cephes_LOG2EF, p2d_half);
+
+  fx = pfloor(fx);
+
+  tmp = pmul(fx, p2d_cephes_exp_C1);
+  Packet2d z = pmul(fx, p2d_cephes_exp_C2);
+  x = psub(x, tmp);
+  x = psub(x, z);
+
+  Packet2d x2 = pmul(x,x);
+
+  Packet2d px = p2d_cephes_exp_p0;
+  px = pmadd(px, x2, p2d_cephes_exp_p1);
+  px = pmadd(px, x2, p2d_cephes_exp_p2);
+  px = pmul (px, x);
+
+  Packet2d qx = p2d_cephes_exp_q0;
+  qx = pmadd(qx, x2, p2d_cephes_exp_q1);
+  qx = pmadd(qx, x2, p2d_cephes_exp_q2);
+  qx = pmadd(qx, x2, p2d_cephes_exp_q3);
+
+  x = pdiv(px,psub(qx,px));
+  x = pmadd(p2d_2,x,p2d_1);
+
+  // build 2^n
+  emm0 = ConvertToPacket2l(fx);
+
+#ifdef __POWER8_VECTOR__ 
+  emm0 = vec_add(emm0, p2l_1023);
+  emm0 = vec_sl(emm0, p2ul_52);
+#else
+  // Code is a bit complex for POWER7.  There is actually a
+  // vec_xxsldi intrinsic but it is not supported by some gcc versions.
+  // So we shift (52-32) bits and do a word swap with zeros.
+  _EIGEN_DECLARE_CONST_Packet4i(1023, 1023);
+  _EIGEN_DECLARE_CONST_Packet4i(20, 20);    // 52 - 32
+
+  Packet4i emm04i = reinterpret_cast<Packet4i>(emm0);
+  emm04i = vec_add(emm04i, p4i_1023);
+  emm04i = vec_sl(emm04i, reinterpret_cast<Packet4ui>(p4i_20));
+  static const Packet16uc perm = {
+    0x14, 0x15, 0x16, 0x17, 0x00, 0x01, 0x02, 0x03, 
+    0x1c, 0x1d, 0x1e, 0x1f, 0x08, 0x09, 0x0a, 0x0b };
+#ifdef  _BIG_ENDIAN
+  emm0 = reinterpret_cast<Packet2l>(vec_perm(p4i_ZERO, emm04i, perm));
+#else
+  emm0 = reinterpret_cast<Packet2l>(vec_perm(emm04i, p4i_ZERO, perm));
+#endif
+
+#endif
+
+  // Altivec's max & min operators just drop silent NaNs. Check NaNs in 
+  // inputs and return them unmodified.
+  Packet2ul isnumber_mask = reinterpret_cast<Packet2ul>(vec_cmpeq(_x, _x));
+  return vec_sel(_x, pmax(pmul(x, reinterpret_cast<Packet2d>(emm0)), _x),
+                 isnumber_mask);
+}
+#endif
+
+}  // end namespace internal
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_MATH_FUNCTIONS_ALTIVEC_H

Index: 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Konstantinos Margaritis <markos@codex.gr>
+// Copyright (C) 2008-2016 Konstantinos Margaritis <markos@freevec.org>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -16,17 +16,21 @@
 
 #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
 #define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 4
 #endif
 
-#ifndef EIGEN_HAS_FUSE_CJMADD
-#define EIGEN_HAS_FUSE_CJMADD 1
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#endif
+
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
 #endif
 
 // NOTE Altivec has 32 registers, but Eigen only accepts a value of 8 or 16
 #ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
-#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 16
+#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS  32
 #endif
 
 typedef __vector float          Packet4f;
 typedef __vector int            Packet4i;
 typedef __vector unsigned int   Packet4ui;
@@ -36,72 +40,170 @@
 
 // We don't want to write the same code all the time, but we need to reuse the constants
 // and it doesn't really work to declare them global, so we define macros instead
 
 #define _EIGEN_DECLARE_CONST_FAST_Packet4f(NAME,X) \
-  Packet4f p4f_##NAME = (Packet4f) vec_splat_s32(X)
+  Packet4f p4f_##NAME = reinterpret_cast<Packet4f>(vec_splat_s32(X))
 
 #define _EIGEN_DECLARE_CONST_FAST_Packet4i(NAME,X) \
   Packet4i p4i_##NAME = vec_splat_s32(X)
 
 #define _EIGEN_DECLARE_CONST_Packet4f(NAME,X) \
   Packet4f p4f_##NAME = pset1<Packet4f>(X)
 
-#define _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(NAME,X) \
-  Packet4f p4f_##NAME = vreinterpretq_f32_u32(pset1<int>(X))
-
 #define _EIGEN_DECLARE_CONST_Packet4i(NAME,X) \
   Packet4i p4i_##NAME = pset1<Packet4i>(X)
 
+#define _EIGEN_DECLARE_CONST_Packet2d(NAME,X) \
+  Packet2d p2d_##NAME = pset1<Packet2d>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet2l(NAME,X) \
+  Packet2l p2l_##NAME = pset1<Packet2l>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(NAME,X) \
+  const Packet4f p4f_##NAME = reinterpret_cast<Packet4f>(pset1<Packet4i>(X))
+
 #define DST_CHAN 1
 #define DST_CTRL(size, count, stride) (((size) << 24) | ((count) << 16) | (stride))
 
+
+// These constants are endian-agnostic
+static _EIGEN_DECLARE_CONST_FAST_Packet4f(ZERO, 0); //{ 0.0, 0.0, 0.0, 0.0}
+static _EIGEN_DECLARE_CONST_FAST_Packet4i(ZERO, 0); //{ 0, 0, 0, 0,}
+static _EIGEN_DECLARE_CONST_FAST_Packet4i(ONE,1); //{ 1, 1, 1, 1}
+static _EIGEN_DECLARE_CONST_FAST_Packet4i(MINUS16,-16); //{ -16, -16, -16, -16}
+static _EIGEN_DECLARE_CONST_FAST_Packet4i(MINUS1,-1); //{ -1, -1, -1, -1}
+static Packet4f p4f_MZERO = (Packet4f) vec_sl((Packet4ui)p4i_MINUS1, (Packet4ui)p4i_MINUS1); //{ 0x80000000, 0x80000000, 0x80000000, 0x80000000}
+#ifndef __VSX__
+static Packet4f p4f_ONE = vec_ctf(p4i_ONE, 0); //{ 1.0, 1.0, 1.0, 1.0}
+#endif
+
+static Packet4f p4f_COUNTDOWN = { 0.0, 1.0, 2.0, 3.0 };
+static Packet4i p4i_COUNTDOWN = { 0, 1, 2, 3 };
+
+static Packet16uc p16uc_REVERSE32 = { 12,13,14,15, 8,9,10,11, 4,5,6,7, 0,1,2,3 };
+static Packet16uc p16uc_DUPLICATE32_HI = { 0,1,2,3, 0,1,2,3, 4,5,6,7, 4,5,6,7 };
+
+// Mask alignment
+#ifdef __PPC64__
+#define _EIGEN_MASK_ALIGNMENT	0xfffffffffffffff0
+#else
+#define _EIGEN_MASK_ALIGNMENT	0xfffffff0
+#endif
+
+#define _EIGEN_ALIGNED_PTR(x)	((std::ptrdiff_t)(x) & _EIGEN_MASK_ALIGNMENT)
+
+// Handle endianness properly while loading constants
 // Define global static constants:
-static Packet4f p4f_COUNTDOWN = { 3.0, 2.0, 1.0, 0.0 };
-static Packet4i p4i_COUNTDOWN = { 3, 2, 1, 0 };
-static Packet16uc p16uc_REVERSE = {12,13,14,15, 8,9,10,11, 4,5,6,7, 0,1,2,3};
+#ifdef _BIG_ENDIAN
 static Packet16uc p16uc_FORWARD = vec_lvsl(0, (float*)0);
-static Packet16uc p16uc_DUPLICATE = {0,1,2,3, 0,1,2,3, 4,5,6,7, 4,5,6,7};
-
-static _EIGEN_DECLARE_CONST_FAST_Packet4f(ZERO, 0);
-static _EIGEN_DECLARE_CONST_FAST_Packet4i(ZERO, 0);
-static _EIGEN_DECLARE_CONST_FAST_Packet4i(ONE,1);
-static _EIGEN_DECLARE_CONST_FAST_Packet4i(MINUS16,-16);
-static _EIGEN_DECLARE_CONST_FAST_Packet4i(MINUS1,-1);
-static Packet4f p4f_ONE = vec_ctf(p4i_ONE, 0);
-static Packet4f p4f_ZERO_ = (Packet4f) vec_sl((Packet4ui)p4i_MINUS1, (Packet4ui)p4i_MINUS1);
+#ifdef __VSX__
+static Packet16uc p16uc_REVERSE64 = { 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
+#endif
+static Packet16uc p16uc_PSET32_WODD   = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 };
+static Packet16uc p16uc_PSET32_WEVEN  = vec_sld(p16uc_DUPLICATE32_HI, (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
+static Packet16uc p16uc_HALF64_0_16 = vec_sld((Packet16uc)p4i_ZERO, vec_splat((Packet16uc) vec_abs(p4i_MINUS16), 3), 8);      //{ 0,0,0,0, 0,0,0,0, 16,16,16,16, 16,16,16,16};
+#else
+static Packet16uc p16uc_FORWARD = p16uc_REVERSE32; 
+static Packet16uc p16uc_REVERSE64 = { 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
+static Packet16uc p16uc_PSET32_WODD = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 1), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 };
+static Packet16uc p16uc_PSET32_WEVEN = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
+static Packet16uc p16uc_HALF64_0_16 = vec_sld(vec_splat((Packet16uc) vec_abs(p4i_MINUS16), 0), (Packet16uc)p4i_ZERO, 8);      //{ 0,0,0,0, 0,0,0,0, 16,16,16,16, 16,16,16,16};
+#endif // _BIG_ENDIAN
+
+static Packet16uc p16uc_PSET64_HI = (Packet16uc) vec_mergeh((Packet4ui)p16uc_PSET32_WODD, (Packet4ui)p16uc_PSET32_WEVEN);     //{ 0,1,2,3, 4,5,6,7, 0,1,2,3, 4,5,6,7 };
+static Packet16uc p16uc_PSET64_LO = (Packet16uc) vec_mergel((Packet4ui)p16uc_PSET32_WODD, (Packet4ui)p16uc_PSET32_WEVEN);     //{ 8,9,10,11, 12,13,14,15, 8,9,10,11, 12,13,14,15 };
+static Packet16uc p16uc_TRANSPOSE64_HI = p16uc_PSET64_HI + p16uc_HALF64_0_16;                                         //{ 0,1,2,3, 4,5,6,7, 16,17,18,19, 20,21,22,23};
+static Packet16uc p16uc_TRANSPOSE64_LO = p16uc_PSET64_LO + p16uc_HALF64_0_16;                                         //{ 8,9,10,11, 12,13,14,15, 24,25,26,27, 28,29,30,31};
+
+static Packet16uc p16uc_COMPLEX32_REV = vec_sld(p16uc_REVERSE32, p16uc_REVERSE32, 8);                                         //{ 4,5,6,7, 0,1,2,3, 12,13,14,15, 8,9,10,11 };
+
+#ifdef _BIG_ENDIAN
+static Packet16uc p16uc_COMPLEX32_REV2 = vec_sld(p16uc_FORWARD, p16uc_FORWARD, 8);                                            //{ 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
+#else
+static Packet16uc p16uc_COMPLEX32_REV2 = vec_sld(p16uc_PSET64_HI, p16uc_PSET64_LO, 8);                                            //{ 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
+#endif // _BIG_ENDIAN
+
+#if EIGEN_HAS_BUILTIN(__builtin_prefetch) || EIGEN_COMP_GNUC
+  #define EIGEN_PPC_PREFETCH(ADDR) __builtin_prefetch(ADDR);
+#else
+  #define EIGEN_PPC_PREFETCH(ADDR) asm( "   dcbt [%[addr]]\n" :: [addr] "r" (ADDR) : "cc" );
+#endif
 
 template<> struct packet_traits<float>  : default_packet_traits
 {
   typedef Packet4f type;
+  typedef Packet4f half;
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 1,
     size=4,
+    HasHalfPacket = 1,
 
-    // FIXME check the Has*
+    HasAdd  = 1,
+    HasSub  = 1,
+    HasMul  = 1,
+    HasDiv  = 1,
+    HasMin  = 1,
+    HasMax  = 1,
+    HasAbs  = 1,
     HasSin  = 0,
     HasCos  = 0,
     HasLog  = 0,
-    HasExp  = 0,
-    HasSqrt = 0
+    HasExp  = 1,
+#ifdef __VSX__
+    HasSqrt = 1,
+#if !EIGEN_COMP_CLANG
+    HasRsqrt = 1,
+#else
+    HasRsqrt = 0,
+#endif
+#else
+    HasSqrt = 0,
+    HasRsqrt = 0,
+#endif
+    HasRound = 1,
+    HasFloor = 1,
+    HasCeil = 1,
+    HasNegate = 1,
+    HasBlend = 1
   };
 };
 template<> struct packet_traits<int>    : default_packet_traits
 {
   typedef Packet4i type;
+  typedef Packet4i half;
   enum {
-    // FIXME check the Has*
     Vectorizable = 1,
     AlignedOnScalar = 1,
-    size=4
+    size = 4,
+    HasHalfPacket = 0,
+
+    HasAdd  = 1,
+    HasSub  = 1,
+    HasMul  = 1,
+    HasDiv  = 0,
+    HasBlend = 1
   };
 };
 
-template<> struct unpacket_traits<Packet4f> { typedef float  type; enum {size=4}; };
-template<> struct unpacket_traits<Packet4i> { typedef int    type; enum {size=4}; };
-/*
+
+template<> struct unpacket_traits<Packet4f> { typedef float  type; enum {size=4, alignment=Aligned16}; typedef Packet4f half; };
+template<> struct unpacket_traits<Packet4i> { typedef int    type; enum {size=4, alignment=Aligned16}; typedef Packet4i half; };
+
+inline std::ostream & operator <<(std::ostream & s, const Packet16uc & v)
+{
+  union {
+    Packet16uc   v;
+    unsigned char n[16];
+  } vt;
+  vt.v = v;
+  for (int i=0; i< 16; i++)
+    s << (int)vt.n[i] << ", ";
+  return s;
+}
+
 inline std::ostream & operator <<(std::ostream & s, const Packet4f & v)
 {
   union {
     Packet4f   v;
     float n[4];
@@ -131,121 +233,169 @@
   vt.v = v;
   s << vt.n[0] << ", " << vt.n[1] << ", " << vt.n[2] << ", " << vt.n[3];
   return s;
 }
 
-inline std::ostream & operator <<(std::ostream & s, const Packetbi & v)
-{
-  union {
-    Packet4bi v;
-    unsigned int n[4];
-  } vt;
-  vt.v = v;
-  s << vt.n[0] << ", " << vt.n[1] << ", " << vt.n[2] << ", " << vt.n[3];
-  return s;
-}
-*/
+// Need to define them first or we get specialization after instantiation errors
+template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float* from)
+{
+  EIGEN_DEBUG_ALIGNED_LOAD
+#ifdef __VSX__
+  return vec_vsx_ld(0, from);
+#else
+  return vec_ld(0, from);
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int*     from)
+{
+  EIGEN_DEBUG_ALIGNED_LOAD
+#ifdef __VSX__
+  return vec_vsx_ld(0, from);
+#else
+  return vec_ld(0, from);
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<float>(float*   to, const Packet4f& from)
+{
+  EIGEN_DEBUG_ALIGNED_STORE
+#ifdef __VSX__
+  vec_vsx_st(from, 0, to);
+#else
+  vec_st(from, 0, to);
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<int>(int*       to, const Packet4i& from)
+{
+  EIGEN_DEBUG_ALIGNED_STORE
+#ifdef __VSX__
+  vec_vsx_st(from, 0, to);
+#else
+  vec_st(from, 0, to);
+#endif
+}
+
 template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float&  from) {
-  // Taken from http://developer.apple.com/hardwaredrivers/ve/alignment.html
-  float EIGEN_ALIGN16 af[4];
-  af[0] = from;
-  Packet4f vc = vec_ld(0, af);
-  vc = vec_splat(vc, 0);
-  return vc;
+  Packet4f v = {from, from, from, from};
+  return v;
 }
 
 template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int&    from)   {
+  Packet4i v = {from, from, from, from};
+  return v;
+}
+template<> EIGEN_STRONG_INLINE void
+pbroadcast4<Packet4f>(const float *a,
+                      Packet4f& a0, Packet4f& a1, Packet4f& a2, Packet4f& a3)
+{
+  a3 = pload<Packet4f>(a);
+  a0 = vec_splat(a3, 0);
+  a1 = vec_splat(a3, 1);
+  a2 = vec_splat(a3, 2);
+  a3 = vec_splat(a3, 3);
+}
+template<> EIGEN_STRONG_INLINE void
+pbroadcast4<Packet4i>(const int *a,
+                      Packet4i& a0, Packet4i& a1, Packet4i& a2, Packet4i& a3)
+{
+  a3 = pload<Packet4i>(a);
+  a0 = vec_splat(a3, 0);
+  a1 = vec_splat(a3, 1);
+  a2 = vec_splat(a3, 2);
+  a3 = vec_splat(a3, 3);
+}
+
+template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, Index stride)
+{
+  float EIGEN_ALIGN16 af[4];
+  af[0] = from[0*stride];
+  af[1] = from[1*stride];
+  af[2] = from[2*stride];
+  af[3] = from[3*stride];
+ return pload<Packet4f>(af);
+}
+template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, Index stride)
+{
+  int EIGEN_ALIGN16 ai[4];
+  ai[0] = from[0*stride];
+  ai[1] = from[1*stride];
+  ai[2] = from[2*stride];
+  ai[3] = from[3*stride];
+ return pload<Packet4i>(ai);
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, Index stride)
+{
+  float EIGEN_ALIGN16 af[4];
+  pstore<float>(af, from);
+  to[0*stride] = af[0];
+  to[1*stride] = af[1];
+  to[2*stride] = af[2];
+  to[3*stride] = af[3];
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, Index stride)
+{
   int EIGEN_ALIGN16 ai[4];
-  ai[0] = from;
-  Packet4i vc = vec_ld(0, ai);
-  vc = vec_splat(vc, 0);
-  return vc;
-}
-
-template<> EIGEN_STRONG_INLINE Packet4f plset<float>(const float& a) { return vec_add(pset1<Packet4f>(a), p4f_COUNTDOWN); }
-template<> EIGEN_STRONG_INLINE Packet4i plset<int>(const int& a)     { return vec_add(pset1<Packet4i>(a), p4i_COUNTDOWN); }
-
-template<> EIGEN_STRONG_INLINE Packet4f padd<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_add(a,b); }
-template<> EIGEN_STRONG_INLINE Packet4i padd<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_add(a,b); }
-
-template<> EIGEN_STRONG_INLINE Packet4f psub<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_sub(a,b); }
-template<> EIGEN_STRONG_INLINE Packet4i psub<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_sub(a,b); }
-
-template<> EIGEN_STRONG_INLINE Packet4f pnegate(const Packet4f& a) { return psub<Packet4f>(p4f_ZERO, a); }
-template<> EIGEN_STRONG_INLINE Packet4i pnegate(const Packet4i& a) { return psub<Packet4i>(p4i_ZERO, a); }
+  pstore<int>((int *)ai, from);
+  to[0*stride] = ai[0];
+  to[1*stride] = ai[1];
+  to[2*stride] = ai[2];
+  to[3*stride] = ai[3];
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f plset<Packet4f>(const float& a) { return pset1<Packet4f>(a) + p4f_COUNTDOWN; }
+template<> EIGEN_STRONG_INLINE Packet4i plset<Packet4i>(const int& a)   { return pset1<Packet4i>(a) + p4i_COUNTDOWN; }
+
+template<> EIGEN_STRONG_INLINE Packet4f padd<Packet4f>(const Packet4f& a, const Packet4f& b) { return a + b; }
+template<> EIGEN_STRONG_INLINE Packet4i padd<Packet4i>(const Packet4i& a, const Packet4i& b) { return a + b; }
+
+template<> EIGEN_STRONG_INLINE Packet4f psub<Packet4f>(const Packet4f& a, const Packet4f& b) { return a - b; }
+template<> EIGEN_STRONG_INLINE Packet4i psub<Packet4i>(const Packet4i& a, const Packet4i& b) { return a - b; }
+
+template<> EIGEN_STRONG_INLINE Packet4f pnegate(const Packet4f& a) { return p4f_ZERO - a; }
+template<> EIGEN_STRONG_INLINE Packet4i pnegate(const Packet4i& a) { return p4i_ZERO - a; }
 
 template<> EIGEN_STRONG_INLINE Packet4f pconj(const Packet4f& a) { return a; }
 template<> EIGEN_STRONG_INLINE Packet4i pconj(const Packet4i& a) { return a; }
 
-template<> EIGEN_STRONG_INLINE Packet4f pmul<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_madd(a,b,p4f_ZERO); }
-/* Commented out: it's actually slower than processing it scalar
- *
-template<> EIGEN_STRONG_INLINE Packet4i pmul<Packet4i>(const Packet4i& a, const Packet4i& b)
-{
-  // Detailed in: http://freevec.org/content/32bit_signed_integer_multiplication_altivec
-  //Set up constants, variables
-  Packet4i a1, b1, bswap, low_prod, high_prod, prod, prod_, v1sel;
-
-  // Get the absolute values
-  a1  = vec_abs(a);
-  b1  = vec_abs(b);
-
-  // Get the signs using xor
-  Packet4bi sgn = (Packet4bi) vec_cmplt(vec_xor(a, b), p4i_ZERO);
-
-  // Do the multiplication for the asbolute values.
-  bswap = (Packet4i) vec_rl((Packet4ui) b1, (Packet4ui) p4i_MINUS16 );
-  low_prod = vec_mulo((Packet8i) a1, (Packet8i)b1);
-  high_prod = vec_msum((Packet8i) a1, (Packet8i) bswap, p4i_ZERO);
-  high_prod = (Packet4i) vec_sl((Packet4ui) high_prod, (Packet4ui) p4i_MINUS16);
-  prod = vec_add( low_prod, high_prod );
-
-  // NOR the product and select only the negative elements according to the sign mask
-  prod_ = vec_nor(prod, prod);
-  prod_ = vec_sel(p4i_ZERO, prod_, sgn);
-
-  // Add 1 to the result to get the negative numbers
-  v1sel = vec_sel(p4i_ZERO, p4i_ONE, sgn);
-  prod_ = vec_add(prod_, v1sel);
-
-  // Merge the results back to the final vector.
-  prod = vec_sel(prod, prod_, sgn);
-
-  return prod;
-}
-*/
+template<> EIGEN_STRONG_INLINE Packet4f pmul<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_madd(a,b, p4f_MZERO); }
+template<> EIGEN_STRONG_INLINE Packet4i pmul<Packet4i>(const Packet4i& a, const Packet4i& b) { return a * b; }
+
 template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b)
 {
-  Packet4f t, y_0, y_1, res;
+#ifndef __VSX__  // VSX actually provides a div instruction
+  Packet4f t, y_0, y_1;
 
   // Altivec does not offer a divide instruction, we have to do a reciprocal approximation
   y_0 = vec_re(b);
 
   // Do one Newton-Raphson iteration to get the needed accuracy
   t   = vec_nmsub(y_0, b, p4f_ONE);
   y_1 = vec_madd(y_0, t, y_0);
 
-  res = vec_madd(a, y_1, p4f_ZERO);
-  return res;
+  return vec_madd(a, y_1, p4f_MZERO);
+#else
+  return vec_div(a, b);
+#endif
 }
 
 template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& /*a*/, const Packet4i& /*b*/)
 { eigen_assert(false && "packet integer division are not supported by AltiVec");
   return pset1<Packet4i>(0);
 }
 
 // for some weird raisons, it has to be overloaded for packet of integers
-template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return vec_madd(a, b, c); }
-template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return padd(pmul(a,b), c); }
+template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return vec_madd(a,b,c); }
+template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return a*b + c; }
 
 template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_min(a, b); }
 template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_min(a, b); }
 
 template<> EIGEN_STRONG_INLINE Packet4f pmax<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_max(a, b); }
 template<> EIGEN_STRONG_INLINE Packet4i pmax<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_max(a, b); }
 
-// Logical Operations are not supported for float, so we have to reinterpret casts using NEON intrinsics
 template<> EIGEN_STRONG_INLINE Packet4f pand<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_and(a, b); }
 template<> EIGEN_STRONG_INLINE Packet4i pand<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_and(a, b); }
 
 template<> EIGEN_STRONG_INLINE Packet4f por<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_or(a, b); }
 template<> EIGEN_STRONG_INLINE Packet4i por<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_or(a, b); }
@@ -254,17 +404,18 @@
 template<> EIGEN_STRONG_INLINE Packet4i pxor<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_xor(a, b); }
 
 template<> EIGEN_STRONG_INLINE Packet4f pandnot<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_and(a, vec_nor(b, b)); }
 template<> EIGEN_STRONG_INLINE Packet4i pandnot<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_and(a, vec_nor(b, b)); }
 
-template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float* from) { EIGEN_DEBUG_ALIGNED_LOAD return vec_ld(0, from); }
-template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int*     from) { EIGEN_DEBUG_ALIGNED_LOAD return vec_ld(0, from); }
+template<> EIGEN_STRONG_INLINE Packet4f pround<Packet4f>(const Packet4f& a) { return vec_round(a); }
+template<> EIGEN_STRONG_INLINE Packet4f pceil<Packet4f>(const  Packet4f& a) { return vec_ceil(a); }
+template<> EIGEN_STRONG_INLINE Packet4f pfloor<Packet4f>(const Packet4f& a) { return vec_floor(a); }
 
+#ifdef _BIG_ENDIAN
 template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from)
 {
   EIGEN_DEBUG_ALIGNED_LOAD
-  // Taken from http://developer.apple.com/hardwaredrivers/ve/alignment.html
   Packet16uc MSQ, LSQ;
   Packet16uc mask;
   MSQ = vec_ld(0, (unsigned char *)from);          // most significant quadword
   LSQ = vec_ld(15, (unsigned char *)from);         // least significant quadword
   mask = vec_lvsl(0, from);                        // create the permute mask
@@ -280,29 +431,40 @@
   MSQ = vec_ld(0, (unsigned char *)from);          // most significant quadword
   LSQ = vec_ld(15, (unsigned char *)from);         // least significant quadword
   mask = vec_lvsl(0, from);                        // create the permute mask
   return (Packet4i) vec_perm(MSQ, LSQ, mask);    // align the data
 }
+#else
+// We also need ot redefine little endian loading of Packet4i/Packet4f using VSX
+template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int* from)
+{
+  EIGEN_DEBUG_UNALIGNED_LOAD
+  return (Packet4i) vec_vsx_ld((long)from & 15, (const int*) _EIGEN_ALIGNED_PTR(from));
+}
+template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from)
+{
+  EIGEN_DEBUG_UNALIGNED_LOAD
+  return (Packet4f) vec_vsx_ld((long)from & 15, (const float*) _EIGEN_ALIGNED_PTR(from));
+}
+#endif
 
 template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float*   from)
 {
   Packet4f p;
-  if((ptrdiff_t(&from) % 16) == 0)  p = pload<Packet4f>(from);
-  else                              p = ploadu<Packet4f>(from);
-  return vec_perm(p, p, p16uc_DUPLICATE);
+  if((std::ptrdiff_t(from) % 16) == 0)  p = pload<Packet4f>(from);
+  else                                  p = ploadu<Packet4f>(from);
+  return vec_perm(p, p, p16uc_DUPLICATE32_HI);
 }
 template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int*     from)
 {
   Packet4i p;
-  if((ptrdiff_t(&from) % 16) == 0)  p = pload<Packet4i>(from);
-  else                              p = ploadu<Packet4i>(from);
-  return vec_perm(p, p, p16uc_DUPLICATE);
+  if((std::ptrdiff_t(from) % 16) == 0)  p = pload<Packet4i>(from);
+  else                                  p = ploadu<Packet4i>(from);
+  return vec_perm(p, p, p16uc_DUPLICATE32_HI);
 }
 
-template<> EIGEN_STRONG_INLINE void pstore<float>(float*   to, const Packet4f& from) { EIGEN_DEBUG_ALIGNED_STORE vec_st(from, 0, to); }
-template<> EIGEN_STRONG_INLINE void pstore<int>(int*       to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE vec_st(from, 0, to); }
-
+#ifdef _BIG_ENDIAN
 template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*  to, const Packet4f& from)
 {
   EIGEN_DEBUG_UNALIGNED_STORE
   // Taken from http://developer.apple.com/hardwaredrivers/ve/alignment.html
   // Warning: not thread safe!
@@ -335,30 +497,48 @@
   MSQ = vec_perm(edges, (Packet16uc) from, align);          // misalign the data (MSQ)
   LSQ = vec_perm((Packet16uc) from, edges, align);          // misalign the data (LSQ)
   vec_st( LSQ, 15, (unsigned char *)to );                   // Store the LSQ part first
   vec_st( MSQ, 0, (unsigned char *)to );                    // Store the MSQ part
 }
-
-template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { vec_dstt(addr, DST_CTRL(2,2,32), DST_CHAN); }
-template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*     addr) { vec_dstt(addr, DST_CTRL(2,2,32), DST_CHAN); }
-
-template<> EIGEN_STRONG_INLINE float  pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x[4]; vec_st(a, 0, x); return x[0]; }
-template<> EIGEN_STRONG_INLINE int    pfirst<Packet4i>(const Packet4i& a) { int   EIGEN_ALIGN16 x[4]; vec_st(a, 0, x); return x[0]; }
-
-template<> EIGEN_STRONG_INLINE Packet4f preverse(const Packet4f& a) { return (Packet4f)vec_perm((Packet16uc)a,(Packet16uc)a, p16uc_REVERSE); }
-template<> EIGEN_STRONG_INLINE Packet4i preverse(const Packet4i& a) { return (Packet4i)vec_perm((Packet16uc)a,(Packet16uc)a, p16uc_REVERSE); }
+#else
+// We also need ot redefine little endian loading of Packet4i/Packet4f using VSX
+template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*       to, const Packet4i& from)
+{
+  EIGEN_DEBUG_ALIGNED_STORE
+  vec_vsx_st(from, (long)to & 15, (int*) _EIGEN_ALIGNED_PTR(to));
+}
+template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*   to, const Packet4f& from)
+{
+  EIGEN_DEBUG_ALIGNED_STORE
+  vec_vsx_st(from, (long)to & 15, (float*) _EIGEN_ALIGNED_PTR(to));
+}
+#endif
+
+template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr)    { EIGEN_PPC_PREFETCH(addr); }
+template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*     addr)    { EIGEN_PPC_PREFETCH(addr); }
+
+template<> EIGEN_STRONG_INLINE float  pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x; vec_ste(a, 0, &x); return x; }
+template<> EIGEN_STRONG_INLINE int    pfirst<Packet4i>(const Packet4i& a) { int   EIGEN_ALIGN16 x; vec_ste(a, 0, &x); return x; }
+
+template<> EIGEN_STRONG_INLINE Packet4f preverse(const Packet4f& a)
+{
+  return reinterpret_cast<Packet4f>(vec_perm(reinterpret_cast<Packet16uc>(a), reinterpret_cast<Packet16uc>(a), p16uc_REVERSE32));
+}
+template<> EIGEN_STRONG_INLINE Packet4i preverse(const Packet4i& a)
+{
+  return reinterpret_cast<Packet4i>(vec_perm(reinterpret_cast<Packet16uc>(a), reinterpret_cast<Packet16uc>(a), p16uc_REVERSE32)); }
 
 template<> EIGEN_STRONG_INLINE Packet4f pabs(const Packet4f& a) { return vec_abs(a); }
 template<> EIGEN_STRONG_INLINE Packet4i pabs(const Packet4i& a) { return vec_abs(a); }
 
 template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
 {
   Packet4f b, sum;
-  b   = (Packet4f) vec_sld(a, a, 8);
-  sum = vec_add(a, b);
-  b   = (Packet4f) vec_sld(sum, sum, 4);
-  sum = vec_add(sum, b);
+  b   = vec_sld(a, a, 8);
+  sum = a + b;
+  b   = vec_sld(sum, sum, 4);
+  sum += b;
   return pfirst(sum);
 }
 
 template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
 {
@@ -377,24 +557,28 @@
   sum[2] = vec_mergeh(v[1], v[3]);
   sum[3] = vec_mergel(v[1], v[3]);
 
   // Now do the summation:
   // Lines 0+1
-  sum[0] = vec_add(sum[0], sum[1]);
+  sum[0] = sum[0] + sum[1];
   // Lines 2+3
-  sum[1] = vec_add(sum[2], sum[3]);
+  sum[1] = sum[2] + sum[3];
   // Add the results
-  sum[0] = vec_add(sum[0], sum[1]);
+  sum[0] = sum[0] + sum[1];
 
   return sum[0];
 }
 
 template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
 {
   Packet4i sum;
   sum = vec_sums(a, p4i_ZERO);
+#ifdef _BIG_ENDIAN
   sum = vec_sld(sum, p4i_ZERO, 12);
+#else
+  sum = vec_sld(p4i_ZERO, sum, 4);
+#endif
   return pfirst(sum);
 }
 
 template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
 {
@@ -413,26 +597,26 @@
   sum[2] = vec_mergeh(v[1], v[3]);
   sum[3] = vec_mergel(v[1], v[3]);
 
   // Now do the summation:
   // Lines 0+1
-  sum[0] = vec_add(sum[0], sum[1]);
+  sum[0] = sum[0] + sum[1];
   // Lines 2+3
-  sum[1] = vec_add(sum[2], sum[3]);
+  sum[1] = sum[2] + sum[3];
   // Add the results
-  sum[0] = vec_add(sum[0], sum[1]);
+  sum[0] = sum[0] + sum[1];
 
   return sum[0];
 }
 
 // Other reduction functions:
 // mul
 template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
 {
   Packet4f prod;
-  prod = pmul(a, (Packet4f)vec_sld(a, a, 8));
-  return pfirst(pmul(prod, (Packet4f)vec_sld(prod, prod, 4)));
+  prod = pmul(a, vec_sld(a, a, 8));
+  return pfirst(pmul(prod, vec_sld(prod, prod, 4)));
 }
 
 template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
 {
   EIGEN_ALIGN16 int aux[4];
@@ -477,25 +661,373 @@
 template<int Offset>
 struct palign_impl<Offset,Packet4f>
 {
   static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
   {
-    if (Offset!=0)
-      first = vec_sld(first, second, Offset*4);
+#ifdef _BIG_ENDIAN
+    switch (Offset % 4) {
+    case 1:
+      first = vec_sld(first, second, 4); break;
+    case 2:
+      first = vec_sld(first, second, 8); break;
+    case 3:
+      first = vec_sld(first, second, 12); break;
+    }
+#else
+    switch (Offset % 4) {
+    case 1:
+      first = vec_sld(second, first, 12); break;
+    case 2:
+      first = vec_sld(second, first, 8); break;
+    case 3:
+      first = vec_sld(second, first, 4); break;
+    }
+#endif
   }
 };
 
 template<int Offset>
 struct palign_impl<Offset,Packet4i>
 {
   static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
   {
-    if (Offset!=0)
-      first = vec_sld(first, second, Offset*4);
+#ifdef _BIG_ENDIAN
+    switch (Offset % 4) {
+    case 1:
+      first = vec_sld(first, second, 4); break;
+    case 2:
+      first = vec_sld(first, second, 8); break;
+    case 3:
+      first = vec_sld(first, second, 12); break;
+    }
+#else
+    switch (Offset % 4) {
+    case 1:
+      first = vec_sld(second, first, 12); break;
+    case 2:
+      first = vec_sld(second, first, 8); break;
+    case 3:
+      first = vec_sld(second, first, 4); break;
+    }
+#endif
+  }
+};
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4f,4>& kernel) {
+  Packet4f t0, t1, t2, t3;
+  t0 = vec_mergeh(kernel.packet[0], kernel.packet[2]);
+  t1 = vec_mergel(kernel.packet[0], kernel.packet[2]);
+  t2 = vec_mergeh(kernel.packet[1], kernel.packet[3]);
+  t3 = vec_mergel(kernel.packet[1], kernel.packet[3]);
+  kernel.packet[0] = vec_mergeh(t0, t2);
+  kernel.packet[1] = vec_mergel(t0, t2);
+  kernel.packet[2] = vec_mergeh(t1, t3);
+  kernel.packet[3] = vec_mergel(t1, t3);
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4i,4>& kernel) {
+  Packet4i t0, t1, t2, t3;
+  t0 = vec_mergeh(kernel.packet[0], kernel.packet[2]);
+  t1 = vec_mergel(kernel.packet[0], kernel.packet[2]);
+  t2 = vec_mergeh(kernel.packet[1], kernel.packet[3]);
+  t3 = vec_mergel(kernel.packet[1], kernel.packet[3]);
+  kernel.packet[0] = vec_mergeh(t0, t2);
+  kernel.packet[1] = vec_mergel(t0, t2);
+  kernel.packet[2] = vec_mergeh(t1, t3);
+  kernel.packet[3] = vec_mergel(t1, t3);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pblend(const Selector<4>& ifPacket, const Packet4i& thenPacket, const Packet4i& elsePacket) {
+  Packet4ui select = { ifPacket.select[0], ifPacket.select[1], ifPacket.select[2], ifPacket.select[3] };
+  Packet4ui mask = reinterpret_cast<Packet4ui>(vec_cmpeq(reinterpret_cast<Packet4ui>(select), reinterpret_cast<Packet4ui>(p4i_ONE)));
+  return vec_sel(elsePacket, thenPacket, mask);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f pblend(const Selector<4>& ifPacket, const Packet4f& thenPacket, const Packet4f& elsePacket) {
+  Packet4ui select = { ifPacket.select[0], ifPacket.select[1], ifPacket.select[2], ifPacket.select[3] };
+  Packet4ui mask = reinterpret_cast<Packet4ui>(vec_cmpeq(reinterpret_cast<Packet4ui>(select), reinterpret_cast<Packet4ui>(p4i_ONE)));
+  return vec_sel(elsePacket, thenPacket, mask);
+}
+
+
+//---------- double ----------
+#ifdef __VSX__
+typedef __vector double              Packet2d;
+typedef __vector unsigned long long  Packet2ul;
+typedef __vector long long           Packet2l;
+#if EIGEN_COMP_CLANG
+typedef Packet2ul                    Packet2bl;
+#else
+typedef __vector __bool long         Packet2bl;
+#endif
+
+static Packet2l  p2l_ONE  = { 1, 1 };
+static Packet2l  p2l_ZERO = reinterpret_cast<Packet2l>(p4i_ZERO);
+static Packet2d  p2d_ONE  = { 1.0, 1.0 }; 
+static Packet2d  p2d_ZERO = reinterpret_cast<Packet2d>(p4f_ZERO);
+static Packet2d  p2d_MZERO = { -0.0, -0.0 };
+
+#ifdef _BIG_ENDIAN
+static Packet2d p2d_COUNTDOWN = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(p2d_ZERO), reinterpret_cast<Packet4f>(p2d_ONE), 8));
+#else
+static Packet2d p2d_COUNTDOWN = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(p2d_ONE), reinterpret_cast<Packet4f>(p2d_ZERO), 8));
+#endif
+
+template<int index> Packet2d vec_splat_dbl(Packet2d& a);
+
+template<> EIGEN_STRONG_INLINE Packet2d vec_splat_dbl<0>(Packet2d& a)
+{
+  return reinterpret_cast<Packet2d>(vec_perm(a, a, p16uc_PSET64_HI));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d vec_splat_dbl<1>(Packet2d& a)
+{
+  return reinterpret_cast<Packet2d>(vec_perm(a, a, p16uc_PSET64_LO));
+}
+
+template<> struct packet_traits<double> : default_packet_traits
+{
+  typedef Packet2d type;
+  typedef Packet2d half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=2,
+    HasHalfPacket = 1,
+
+    HasAdd  = 1,
+    HasSub  = 1,
+    HasMul  = 1,
+    HasDiv  = 1,
+    HasMin  = 1,
+    HasMax  = 1,
+    HasAbs  = 1,
+    HasSin  = 0,
+    HasCos  = 0,
+    HasLog  = 0,
+    HasExp  = 1,
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasRound = 1,
+    HasFloor = 1,
+    HasCeil = 1,
+    HasNegate = 1,
+    HasBlend = 1
+  };
+};
+
+template<> struct unpacket_traits<Packet2d> { typedef double type; enum {size=2, alignment=Aligned16}; typedef Packet2d half; };
+
+inline std::ostream & operator <<(std::ostream & s, const Packet2l & v)
+{
+  union {
+    Packet2l   v;
+    int64_t n[2];
+  } vt;
+  vt.v = v;
+  s << vt.n[0] << ", " << vt.n[1];
+  return s;
+}
+
+inline std::ostream & operator <<(std::ostream & s, const Packet2d & v)
+{
+  union {
+    Packet2d   v;
+    double n[2];
+  } vt;
+  vt.v = v;
+  s << vt.n[0] << ", " << vt.n[1];
+  return s;
+}
+
+// Need to define them first or we get specialization after instantiation errors
+template<> EIGEN_STRONG_INLINE Packet2d pload<Packet2d>(const double* from)
+{
+  EIGEN_DEBUG_ALIGNED_LOAD
+#ifdef __VSX__
+  return vec_vsx_ld(0, from);
+#else
+  return vec_ld(0, from);
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<double>(double*   to, const Packet2d& from)
+{
+  EIGEN_DEBUG_ALIGNED_STORE
+#ifdef __VSX__
+  vec_vsx_st(from, 0, to);
+#else
+  vec_st(from, 0, to);
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double&  from) {
+  Packet2d v = {from, from};
+  return v;
+}
+
+template<> EIGEN_STRONG_INLINE void
+pbroadcast4<Packet2d>(const double *a,
+                      Packet2d& a0, Packet2d& a1, Packet2d& a2, Packet2d& a3)
+{
+  a1 = pload<Packet2d>(a);
+  a0 = vec_splat_dbl<0>(a1);
+  a1 = vec_splat_dbl<1>(a1);
+  a3 = pload<Packet2d>(a+2);
+  a2 = vec_splat_dbl<0>(a3);
+  a3 = vec_splat_dbl<1>(a3);
+}
+
+template<> EIGEN_DEVICE_FUNC inline Packet2d pgather<double, Packet2d>(const double* from, Index stride)
+{
+  double EIGEN_ALIGN16 af[2];
+  af[0] = from[0*stride];
+  af[1] = from[1*stride];
+ return pload<Packet2d>(af);
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to, const Packet2d& from, Index stride)
+{
+  double EIGEN_ALIGN16 af[2];
+  pstore<double>(af, from);
+  to[0*stride] = af[0];
+  to[1*stride] = af[1];
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d plset<Packet2d>(const double& a) { return pset1<Packet2d>(a) + p2d_COUNTDOWN; }
+
+template<> EIGEN_STRONG_INLINE Packet2d padd<Packet2d>(const Packet2d& a, const Packet2d& b) { return a + b; }
+
+template<> EIGEN_STRONG_INLINE Packet2d psub<Packet2d>(const Packet2d& a, const Packet2d& b) { return a - b; }
+
+template<> EIGEN_STRONG_INLINE Packet2d pnegate(const Packet2d& a) { return p2d_ZERO - a; }
+
+template<> EIGEN_STRONG_INLINE Packet2d pconj(const Packet2d& a) { return a; }
+
+template<> EIGEN_STRONG_INLINE Packet2d pmul<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_madd(a,b,p2d_MZERO); }
+template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_div(a,b); }
+
+// for some weird raisons, it has to be overloaded for packet of integers
+template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return vec_madd(a, b, c); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_min(a, b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_max(a, b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pand<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d por<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_or(a, b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pxor<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_xor(a, b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pandnot<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, vec_nor(b, b)); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pround<Packet2d>(const Packet2d& a) { return vec_round(a); }
+template<> EIGEN_STRONG_INLINE Packet2d pceil<Packet2d>(const  Packet2d& a) { return vec_ceil(a); }
+template<> EIGEN_STRONG_INLINE Packet2d pfloor<Packet2d>(const Packet2d& a) { return vec_floor(a); }
+
+template<> EIGEN_STRONG_INLINE Packet2d ploadu<Packet2d>(const double* from)
+{
+  EIGEN_DEBUG_ALIGNED_LOAD
+  return (Packet2d) vec_vsx_ld((long)from & 15, (const double*) _EIGEN_ALIGNED_PTR(from));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double*   from)
+{
+  Packet2d p;
+  if((std::ptrdiff_t(from) % 16) == 0)  p = pload<Packet2d>(from);
+  else                                  p = ploadu<Packet2d>(from);
+  return vec_splat_dbl<0>(p);
+}
+
+template<> EIGEN_STRONG_INLINE void pstoreu<double>(double*  to, const Packet2d& from)
+{
+  EIGEN_DEBUG_ALIGNED_STORE
+  vec_vsx_st((Packet4f)from, (long)to & 15, (float*) _EIGEN_ALIGNED_PTR(to));
+}
+
+template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { EIGEN_PPC_PREFETCH(addr); }
+
+template<> EIGEN_STRONG_INLINE double  pfirst<Packet2d>(const Packet2d& a) { double EIGEN_ALIGN16 x[2]; pstore<double>(x, a); return x[0]; }
+
+template<> EIGEN_STRONG_INLINE Packet2d preverse(const Packet2d& a)
+{
+  return reinterpret_cast<Packet2d>(vec_perm(reinterpret_cast<Packet16uc>(a), reinterpret_cast<Packet16uc>(a), p16uc_REVERSE64));
+}
+template<> EIGEN_STRONG_INLINE Packet2d pabs(const Packet2d& a) { return vec_abs(a); }
+
+template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a)
+{
+  Packet2d b, sum;
+  b   = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(a), reinterpret_cast<Packet4f>(a), 8));
+  sum = a + b;
+  return pfirst<Packet2d>(sum);
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
+{
+  Packet2d v[2], sum;
+  v[0] = vecs[0] + reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(vecs[0]), reinterpret_cast<Packet4f>(vecs[0]), 8));
+  v[1] = vecs[1] + reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(vecs[1]), reinterpret_cast<Packet4f>(vecs[1]), 8));
+ 
+#ifdef _BIG_ENDIAN
+  sum = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(v[0]), reinterpret_cast<Packet4f>(v[1]), 8));
+#else
+  sum = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(v[1]), reinterpret_cast<Packet4f>(v[0]), 8));
+#endif
+
+  return sum;
+}
+// Other reduction functions:
+// mul
+template<> EIGEN_STRONG_INLINE double predux_mul<Packet2d>(const Packet2d& a)
+{
+  return pfirst(pmul(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(a), reinterpret_cast<Packet4ui>(a), 8))));
+}
+
+// min
+template<> EIGEN_STRONG_INLINE double predux_min<Packet2d>(const Packet2d& a)
+{
+  return pfirst(pmin(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(a), reinterpret_cast<Packet4ui>(a), 8))));
+}
+
+// max
+template<> EIGEN_STRONG_INLINE double predux_max<Packet2d>(const Packet2d& a)
+{
+  return pfirst(pmax(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(a), reinterpret_cast<Packet4ui>(a), 8))));
+}
+
+template<int Offset>
+struct palign_impl<Offset,Packet2d>
+{
+  static EIGEN_STRONG_INLINE void run(Packet2d& first, const Packet2d& second)
+  {
+    if (Offset == 1)
+#ifdef _BIG_ENDIAN
+      first = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(first), reinterpret_cast<Packet4ui>(second), 8));
+#else
+      first = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(second), reinterpret_cast<Packet4ui>(first), 8));
+#endif
   }
 };
 
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet2d,2>& kernel) {
+  Packet2d t0, t1;
+  t0 = vec_perm(kernel.packet[0], kernel.packet[1], p16uc_TRANSPOSE64_HI);
+  t1 = vec_perm(kernel.packet[0], kernel.packet[1], p16uc_TRANSPOSE64_LO);
+  kernel.packet[0] = t0;
+  kernel.packet[1] = t1;
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pblend(const Selector<2>& ifPacket, const Packet2d& thenPacket, const Packet2d& elsePacket) {
+  Packet2l select = { ifPacket.select[0], ifPacket.select[1] };
+  Packet2bl mask = vec_cmpeq(reinterpret_cast<Packet2d>(select), reinterpret_cast<Packet2d>(p2l_ONE));
+  return vec_sel(elsePacket, thenPacket, mask);
+}
+#endif // __VSX__
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_PACKET_MATH_ALTIVEC_H

DELETED 3rd_party/eigen/Eigen/src/Core/arch/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Core/arch/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Core/arch/CMakeLists.txt
@@ -1,4 +0,0 @@
-ADD_SUBDIRECTORY(SSE)
-ADD_SUBDIRECTORY(AltiVec)
-ADD_SUBDIRECTORY(NEON)
-ADD_SUBDIRECTORY(Default)

ADDED   3rd_party/eigen/Eigen/src/Core/arch/CUDA/Complex.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/CUDA/Complex.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/CUDA/Complex.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/CUDA/Complex.h
@@ -0,0 +1,103 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_COMPLEX_CUDA_H
+#define EIGEN_COMPLEX_CUDA_H
+
+// clang-format off
+
+namespace Eigen {
+
+namespace internal {
+
+#if defined(__CUDACC__) && defined(EIGEN_USE_GPU)
+
+// Many std::complex methods such as operator+, operator-, operator* and
+// operator/ are not constexpr. Due to this, clang does not treat them as device
+// functions and thus Eigen functors making use of these operators fail to
+// compile. Here, we manually specialize these functors for complex types when
+// building for CUDA to avoid non-constexpr methods.
+
+// Sum
+template<typename T> struct scalar_sum_op<const std::complex<T>, const std::complex<T> > : binary_op_base<const std::complex<T>, const std::complex<T> > {
+  typedef typename std::complex<T> result_type;
+
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_sum_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::complex<T> operator() (const std::complex<T>& a, const std::complex<T>& b) const {
+    return std::complex<T>(numext::real(a) + numext::real(b),
+                           numext::imag(a) + numext::imag(b));
+  }
+};
+
+template<typename T> struct scalar_sum_op<std::complex<T>, std::complex<T> > : scalar_sum_op<const std::complex<T>, const std::complex<T> > {};
+
+
+// Difference
+template<typename T> struct scalar_difference_op<const std::complex<T>, const std::complex<T> >  : binary_op_base<const std::complex<T>, const std::complex<T> > {
+  typedef typename std::complex<T> result_type;
+
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_difference_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::complex<T> operator() (const std::complex<T>& a, const std::complex<T>& b) const {
+    return std::complex<T>(numext::real(a) - numext::real(b),
+                           numext::imag(a) - numext::imag(b));
+  }
+};
+
+template<typename T> struct scalar_difference_op<std::complex<T>, std::complex<T> > : scalar_difference_op<const std::complex<T>, const std::complex<T> > {};
+
+
+// Product
+template<typename T> struct scalar_product_op<const std::complex<T>, const std::complex<T> >  : binary_op_base<const std::complex<T>, const std::complex<T> > {
+  enum {
+    Vectorizable = packet_traits<std::complex<T>>::HasMul
+  };
+  typedef typename std::complex<T> result_type;
+
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_product_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::complex<T> operator() (const std::complex<T>& a, const std::complex<T>& b) const {
+    const T a_real = numext::real(a);
+    const T a_imag = numext::imag(a);
+    const T b_real = numext::real(b);
+    const T b_imag = numext::imag(b);
+    return std::complex<T>(a_real * b_real - a_imag * b_imag,
+                           a_real * b_imag + a_imag * b_real);
+  }
+};
+
+template<typename T> struct scalar_product_op<std::complex<T>, std::complex<T> > : scalar_product_op<const std::complex<T>, const std::complex<T> > {};
+
+
+// Quotient
+template<typename T> struct scalar_quotient_op<const std::complex<T>, const std::complex<T> > : binary_op_base<const std::complex<T>, const std::complex<T> > {
+  enum {
+    Vectorizable = packet_traits<std::complex<T>>::HasDiv
+  };
+  typedef typename std::complex<T> result_type;
+
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::complex<T> operator() (const std::complex<T>& a, const std::complex<T>& b) const {
+    const T a_real = numext::real(a);
+    const T a_imag = numext::imag(a);
+    const T b_real = numext::real(b);
+    const T b_imag = numext::imag(b);
+    const T norm = T(1) / (b_real * b_real + b_imag * b_imag);
+    return std::complex<T>((a_real * b_real + a_imag * b_imag) * norm,
+                           (a_imag * b_real - a_real * b_imag) * norm);
+  }
+};
+
+template<typename T> struct scalar_quotient_op<std::complex<T>, std::complex<T> > : scalar_quotient_op<const std::complex<T>, const std::complex<T> > {};
+
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_COMPLEX_CUDA_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/CUDA/Half.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/CUDA/Half.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/CUDA/Half.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/CUDA/Half.h
@@ -0,0 +1,635 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+//
+// The conversion routines are Copyright (c) Fabian Giesen, 2016.
+// The original license follows:
+//
+// Copyright (c) Fabian Giesen, 2016
+// All rights reserved.
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted.
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+// A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+// LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+// Standard 16-bit float type, mostly useful for GPUs. Defines a new
+// type Eigen::half (inheriting from CUDA's __half struct) with
+// operator overloads such that it behaves basically as an arithmetic
+// type. It will be quite slow on CPUs (so it is recommended to stay
+// in fp32 for CPUs, except for simple parameter conversions, I/O
+// to disk and the likes), but fast on GPUs.
+
+
+#ifndef EIGEN_HALF_CUDA_H
+#define EIGEN_HALF_CUDA_H
+
+#if __cplusplus > 199711L
+#define EIGEN_EXPLICIT_CAST(tgt_type) explicit operator tgt_type()
+#else
+#define EIGEN_EXPLICIT_CAST(tgt_type) operator tgt_type()
+#endif
+
+
+namespace Eigen {
+
+struct half;
+
+namespace half_impl {
+
+#if !defined(EIGEN_HAS_CUDA_FP16)
+
+// Make our own __half definition that is similar to CUDA's.
+struct __half {
+  EIGEN_DEVICE_FUNC __half() {}
+  explicit EIGEN_DEVICE_FUNC __half(unsigned short raw) : x(raw) {}
+  unsigned short x;
+};
+
+#endif
+
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half raw_uint16_to_half(unsigned short x);
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half float_to_half_rtne(float ff);
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC float half_to_float(__half h);
+
+struct half_base : public __half {
+  EIGEN_DEVICE_FUNC half_base() {}
+  EIGEN_DEVICE_FUNC half_base(const half_base& h) : __half(h) {}
+  EIGEN_DEVICE_FUNC half_base(const __half& h) : __half(h) {}
+};
+
+} // namespace half_impl
+
+// Class definition.
+struct half : public half_impl::half_base {
+  #if !defined(EIGEN_HAS_CUDA_FP16)
+    typedef half_impl::__half __half;
+  #endif
+
+  EIGEN_DEVICE_FUNC half() {}
+
+  EIGEN_DEVICE_FUNC half(const __half& h) : half_impl::half_base(h) {}
+  EIGEN_DEVICE_FUNC half(const half& h) : half_impl::half_base(h) {}
+
+  explicit EIGEN_DEVICE_FUNC half(bool b)
+      : half_impl::half_base(half_impl::raw_uint16_to_half(b ? 0x3c00 : 0)) {}
+  template<class T>
+  explicit EIGEN_DEVICE_FUNC half(const T& val)
+      : half_impl::half_base(half_impl::float_to_half_rtne(static_cast<float>(val))) {}
+  explicit EIGEN_DEVICE_FUNC half(float f)
+      : half_impl::half_base(half_impl::float_to_half_rtne(f)) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(bool) const {
+    // +0.0 and -0.0 become false, everything else becomes true.
+    return (x & 0x7fff) != 0;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(signed char) const {
+    return static_cast<signed char>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned char) const {
+    return static_cast<unsigned char>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(short) const {
+    return static_cast<short>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned short) const {
+    return static_cast<unsigned short>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(int) const {
+    return static_cast<int>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned int) const {
+    return static_cast<unsigned int>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(long) const {
+    return static_cast<long>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned long) const {
+    return static_cast<unsigned long>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(long long) const {
+    return static_cast<long long>(half_impl::half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(unsigned long long) const {
+    return static_cast<unsigned long long>(half_to_float(*this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(float) const {
+    return half_impl::half_to_float(*this);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_EXPLICIT_CAST(double) const {
+    return static_cast<double>(half_impl::half_to_float(*this));
+  }
+
+  EIGEN_DEVICE_FUNC half& operator=(const half& other) {
+    x = other.x;
+    return *this;
+  }
+};
+
+namespace half_impl {
+
+#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+
+// Intrinsics for native fp16 support. Note that on current hardware,
+// these are no faster than fp32 arithmetic (you need to use the half2
+// versions to get the ALU speed increased), but you do save the
+// conversion steps back and forth.
+
+__device__ half operator + (const half& a, const half& b) {
+  return __hadd(a, b);
+}
+__device__ half operator * (const half& a, const half& b) {
+  return __hmul(a, b);
+}
+__device__ half operator - (const half& a, const half& b) {
+  return __hsub(a, b);
+}
+__device__ half operator / (const half& a, const half& b) {
+  float num = __half2float(a);
+  float denom = __half2float(b);
+  return __float2half(num / denom);
+}
+__device__ half operator - (const half& a) {
+  return __hneg(a);
+}
+__device__ half& operator += (half& a, const half& b) {
+  a = a + b;
+  return a;
+}
+__device__ half& operator *= (half& a, const half& b) {
+  a = a * b;
+  return a;
+}
+__device__ half& operator -= (half& a, const half& b) {
+  a = a - b;
+  return a;
+}
+__device__ half& operator /= (half& a, const half& b) {
+  a = a / b;
+  return a;
+}
+__device__ bool operator == (const half& a, const half& b) {
+  return __heq(a, b);
+}
+__device__ bool operator != (const half& a, const half& b) {
+  return __hne(a, b);
+}
+__device__ bool operator < (const half& a, const half& b) {
+  return __hlt(a, b);
+}
+__device__ bool operator <= (const half& a, const half& b) {
+  return __hle(a, b);
+}
+__device__ bool operator > (const half& a, const half& b) {
+  return __hgt(a, b);
+}
+__device__ bool operator >= (const half& a, const half& b) {
+  return __hge(a, b);
+}
+
+#else  // Emulate support for half floats
+
+// Definitions for CPUs and older CUDA, mostly working through conversion
+// to/from fp32.
+
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator + (const half& a, const half& b) {
+  return half(float(a) + float(b));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator * (const half& a, const half& b) {
+  return half(float(a) * float(b));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator - (const half& a, const half& b) {
+  return half(float(a) - float(b));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator / (const half& a, const half& b) {
+  return half(float(a) / float(b));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator - (const half& a) {
+  half result;
+  result.x = a.x ^ 0x8000;
+  return result;
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator += (half& a, const half& b) {
+  a = half(float(a) + float(b));
+  return a;
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator *= (half& a, const half& b) {
+  a = half(float(a) * float(b));
+  return a;
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator -= (half& a, const half& b) {
+  a = half(float(a) - float(b));
+  return a;
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator /= (half& a, const half& b) {
+  a = half(float(a) / float(b));
+  return a;
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator == (const half& a, const half& b) {
+  return float(a) == float(b);
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator != (const half& a, const half& b) {
+  return float(a) != float(b);
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator < (const half& a, const half& b) {
+  return float(a) < float(b);
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator <= (const half& a, const half& b) {
+  return float(a) <= float(b);
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator > (const half& a, const half& b) {
+  return float(a) > float(b);
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator >= (const half& a, const half& b) {
+  return float(a) >= float(b);
+}
+
+#endif  // Emulate support for half floats
+
+// Division by an index. Do it in full float precision to avoid accuracy
+// issues in converting the denominator to half.
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half operator / (const half& a, Index b) {
+  return half(static_cast<float>(a) / static_cast<float>(b));
+}
+
+// Conversion routines, including fallbacks for the host or older CUDA.
+// Note that newer Intel CPUs (Haswell or newer) have vectorized versions of
+// these in hardware. If we need more performance on older/other CPUs, they are
+// also possible to vectorize directly.
+
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half raw_uint16_to_half(unsigned short x) {
+  __half h;
+  h.x = x;
+  return h;
+}
+
+union FP32 {
+  unsigned int u;
+  float f;
+};
+
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half float_to_half_rtne(float ff) {
+#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
+  return __float2half(ff);
+
+#elif defined(EIGEN_HAS_FP16_C)
+  __half h;
+  h.x = _cvtss_sh(ff, 0);
+  return h;
+
+#else
+  FP32 f; f.f = ff;
+
+  const FP32 f32infty = { 255 << 23 };
+  const FP32 f16max = { (127 + 16) << 23 };
+  const FP32 denorm_magic = { ((127 - 15) + (23 - 10) + 1) << 23 };
+  unsigned int sign_mask = 0x80000000u;
+  __half o;
+  o.x = static_cast<unsigned short>(0x0u);
+
+  unsigned int sign = f.u & sign_mask;
+  f.u ^= sign;
+
+  // NOTE all the integer compares in this function can be safely
+  // compiled into signed compares since all operands are below
+  // 0x80000000. Important if you want fast straight SSE2 code
+  // (since there's no unsigned PCMPGTD).
+
+  if (f.u >= f16max.u) {  // result is Inf or NaN (all exponent bits set)
+    o.x = (f.u > f32infty.u) ? 0x7e00 : 0x7c00; // NaN->qNaN and Inf->Inf
+  } else {  // (De)normalized number or zero
+    if (f.u < (113 << 23)) {  // resulting FP16 is subnormal or zero
+      // use a magic value to align our 10 mantissa bits at the bottom of
+      // the float. as long as FP addition is round-to-nearest-even this
+      // just works.
+      f.f += denorm_magic.f;
+
+      // and one integer subtract of the bias later, we have our final float!
+      o.x = static_cast<unsigned short>(f.u - denorm_magic.u);
+    } else {
+      unsigned int mant_odd = (f.u >> 13) & 1; // resulting mantissa is odd
+
+      // update exponent, rounding bias part 1
+      f.u += ((unsigned int)(15 - 127) << 23) + 0xfff;
+      // rounding bias part 2
+      f.u += mant_odd;
+      // take the bits!
+      o.x = static_cast<unsigned short>(f.u >> 13);
+    }
+  }
+
+  o.x |= static_cast<unsigned short>(sign >> 16);
+  return o;
+#endif
+}
+
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC float half_to_float(__half h) {
+#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
+  return __half2float(h);
+
+#elif defined(EIGEN_HAS_FP16_C)
+  return _cvtsh_ss(h.x);
+
+#else
+  const FP32 magic = { 113 << 23 };
+  const unsigned int shifted_exp = 0x7c00 << 13; // exponent mask after shift
+  FP32 o;
+
+  o.u = (h.x & 0x7fff) << 13;             // exponent/mantissa bits
+  unsigned int exp = shifted_exp & o.u;   // just the exponent
+  o.u += (127 - 15) << 23;                // exponent adjust
+
+  // handle exponent special cases
+  if (exp == shifted_exp) {     // Inf/NaN?
+    o.u += (128 - 16) << 23;    // extra exp adjust
+  } else if (exp == 0) {        // Zero/Denormal?
+    o.u += 1 << 23;             // extra exp adjust
+    o.f -= magic.f;             // renormalize
+  }
+
+  o.u |= (h.x & 0x8000) << 16;    // sign bit
+  return o.f;
+#endif
+}
+
+// --- standard functions ---
+
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool (isinf)(const half& a) {
+  return (a.x & 0x7fff) == 0x7c00;
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool (isnan)(const half& a) {
+#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return __hisnan(a);
+#else
+  return (a.x & 0x7fff) > 0x7c00;
+#endif
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool (isfinite)(const half& a) {
+  return !(isinf EIGEN_NOT_A_MACRO (a)) && !(isnan EIGEN_NOT_A_MACRO (a));
+}
+
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half abs(const half& a) {
+  half result;
+  result.x = a.x & 0x7FFF;
+  return result;
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half exp(const half& a) {
+  return half(::expf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half log(const half& a) {
+#if defined(EIGEN_HAS_CUDA_FP16) && defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return Eigen::half(::hlog(a));
+#else
+  return half(::logf(float(a)));
+#endif
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half log1p(const half& a) {
+  return half(numext::log1p(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half log10(const half& a) {
+  return half(::log10f(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half sqrt(const half& a) {
+  return half(::sqrtf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half pow(const half& a, const half& b) {
+  return half(::powf(float(a), float(b)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half sin(const half& a) {
+  return half(::sinf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half cos(const half& a) {
+  return half(::cosf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half tan(const half& a) {
+  return half(::tanf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half tanh(const half& a) {
+  return half(::tanhf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half floor(const half& a) {
+  return half(::floorf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half ceil(const half& a) {
+  return half(::ceilf(float(a)));
+}
+
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half (min)(const half& a, const half& b) {
+#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return __hlt(b, a) ? b : a;
+#else
+  const float f1 = static_cast<float>(a);
+  const float f2 = static_cast<float>(b);
+  return f2 < f1 ? b : a;
+#endif
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half (max)(const half& a, const half& b) {
+#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return __hlt(a, b) ? b : a;
+#else
+  const float f1 = static_cast<float>(a);
+  const float f2 = static_cast<float>(b);
+  return f1 < f2 ? b : a;
+#endif
+}
+
+EIGEN_ALWAYS_INLINE std::ostream& operator << (std::ostream& os, const half& v) {
+  os << static_cast<float>(v);
+  return os;
+}
+
+} // end namespace half_impl
+
+// import Eigen::half_impl::half into Eigen namespace
+// using half_impl::half;
+
+namespace internal {
+
+template<>
+struct random_default_impl<half, false, false>
+{
+  static inline half run(const half& x, const half& y)
+  {
+    return x + (y-x) * half(float(std::rand()) / float(RAND_MAX));
+  }
+  static inline half run()
+  {
+    return run(half(-1.f), half(1.f));
+  }
+};
+
+template<> struct is_arithmetic<half> { enum { value = true }; };
+
+} // end namespace internal
+
+}  // end namespace Eigen
+
+namespace std {
+template<>
+struct numeric_limits<Eigen::half> {
+  static const bool is_specialized = true;
+  static const bool is_signed = true;
+  static const bool is_integer = false;
+  static const bool is_exact = false;
+  static const bool has_infinity = true;
+  static const bool has_quiet_NaN = true;
+  static const bool has_signaling_NaN = true;
+  static const float_denorm_style has_denorm = denorm_present;
+  static const bool has_denorm_loss = false;
+  static const std::float_round_style round_style = std::round_to_nearest;
+  static const bool is_iec559 = false;
+  static const bool is_bounded = false;
+  static const bool is_modulo = false;
+  static const int digits = 11;
+  static const int digits10 = 2;
+  //static const int max_digits10 = ;
+  static const int radix = 2;
+  static const int min_exponent = -13;
+  static const int min_exponent10 = -4;
+  static const int max_exponent = 16;
+  static const int max_exponent10 = 4;
+  static const bool traps = true;
+  static const bool tinyness_before = false;
+
+  static Eigen::half (min)() { return Eigen::half_impl::raw_uint16_to_half(0x400); }
+  static Eigen::half lowest() { return Eigen::half_impl::raw_uint16_to_half(0xfbff); }
+  static Eigen::half (max)() { return Eigen::half_impl::raw_uint16_to_half(0x7bff); }
+  static Eigen::half epsilon() { return Eigen::half_impl::raw_uint16_to_half(0x0800); }
+  static Eigen::half round_error() { return Eigen::half(0.5); }
+  static Eigen::half infinity() { return Eigen::half_impl::raw_uint16_to_half(0x7c00); }
+  static Eigen::half quiet_NaN() { return Eigen::half_impl::raw_uint16_to_half(0x7e00); }
+  static Eigen::half signaling_NaN() { return Eigen::half_impl::raw_uint16_to_half(0x7e00); }
+  static Eigen::half denorm_min() { return Eigen::half_impl::raw_uint16_to_half(0x1); }
+};
+}
+
+namespace Eigen {
+
+template<> struct NumTraits<Eigen::half>
+    : GenericNumTraits<Eigen::half>
+{
+  enum {
+    IsSigned = true,
+    IsInteger = false,
+    IsComplex = false,
+    RequireInitialization = false
+  };
+
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half epsilon() {
+    return half_impl::raw_uint16_to_half(0x0800);
+  }
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half dummy_precision() { return Eigen::half(1e-2f); }
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half highest() {
+    return half_impl::raw_uint16_to_half(0x7bff);
+  }
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half lowest() {
+    return half_impl::raw_uint16_to_half(0xfbff);
+  }
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half infinity() {
+    return half_impl::raw_uint16_to_half(0x7c00);
+  }
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Eigen::half quiet_NaN() {
+    return half_impl::raw_uint16_to_half(0x7c01);
+  }
+};
+
+} // end namespace Eigen
+
+// C-like standard mathematical functions and trancendentals.
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half fabsh(const Eigen::half& a) {
+  Eigen::half result;
+  result.x = a.x & 0x7FFF;
+  return result;
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half exph(const Eigen::half& a) {
+  return Eigen::half(::expf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half logh(const Eigen::half& a) {
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
+  return Eigen::half(::hlog(a));
+#else
+  return Eigen::half(::logf(float(a)));
+#endif
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half sqrth(const Eigen::half& a) {
+  return Eigen::half(::sqrtf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half powh(const Eigen::half& a, const Eigen::half& b) {
+  return Eigen::half(::powf(float(a), float(b)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half floorh(const Eigen::half& a) {
+  return Eigen::half(::floorf(float(a)));
+}
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half ceilh(const Eigen::half& a) {
+  return Eigen::half(::ceilf(float(a)));
+}
+
+namespace std {
+
+#if __cplusplus > 199711L
+template <>
+struct hash<Eigen::half> {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t operator()(const Eigen::half& a) const {
+    return static_cast<std::size_t>(a.x);
+  }
+};
+#endif
+
+} // end namespace std
+
+
+// Add the missing shfl_xor intrinsic
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
+__device__ EIGEN_STRONG_INLINE Eigen::half __shfl_xor(Eigen::half var, int laneMask, int width=warpSize) {
+  return static_cast<Eigen::half>(__shfl_xor(static_cast<float>(var), laneMask, width));
+}
+#endif
+
+// ldg() has an overload for __half, but we also need one for Eigen::half.
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 350
+EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half __ldg(const Eigen::half* ptr) {
+  return Eigen::half_impl::raw_uint16_to_half(
+      __ldg(reinterpret_cast<const unsigned short*>(ptr)));
+}
+#endif
+
+
+#if defined(__CUDA_ARCH__)
+namespace Eigen {
+namespace numext {
+
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+bool (isnan)(const Eigen::half& h) {
+  return (half_impl::isnan)(h);
+}
+
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+bool (isinf)(const Eigen::half& h) {
+  return (half_impl::isinf)(h);
+}
+
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+bool (isfinite)(const Eigen::half& h) {
+  return (half_impl::isfinite)(h);
+}
+
+} // namespace Eigen
+}  // namespace numext
+#endif
+
+#endif // EIGEN_HALF_CUDA_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/CUDA/MathFunctions.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/CUDA/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/CUDA/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/CUDA/MathFunctions.h
@@ -0,0 +1,91 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_MATH_FUNCTIONS_CUDA_H
+#define EIGEN_MATH_FUNCTIONS_CUDA_H
+
+namespace Eigen {
+
+namespace internal {
+
+// Make sure this is only available when targeting a GPU: we don't want to
+// introduce conflicts between these packet_traits definitions and the ones
+// we'll use on the host side (SSE, AVX, ...)
+#if defined(__CUDACC__) && defined(EIGEN_USE_GPU)
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 plog<float4>(const float4& a)
+{
+  return make_float4(logf(a.x), logf(a.y), logf(a.z), logf(a.w));
+}
+
+template<>  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 plog<double2>(const double2& a)
+{
+  using ::log;
+  return make_double2(log(a.x), log(a.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 plog1p<float4>(const float4& a)
+{
+  return make_float4(log1pf(a.x), log1pf(a.y), log1pf(a.z), log1pf(a.w));
+}
+
+template<>  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 plog1p<double2>(const double2& a)
+{
+  return make_double2(log1p(a.x), log1p(a.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 pexp<float4>(const float4& a)
+{
+  return make_float4(expf(a.x), expf(a.y), expf(a.z), expf(a.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 pexp<double2>(const double2& a)
+{
+  using ::exp;
+  return make_double2(exp(a.x), exp(a.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 psqrt<float4>(const float4& a)
+{
+  return make_float4(sqrtf(a.x), sqrtf(a.y), sqrtf(a.z), sqrtf(a.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 psqrt<double2>(const double2& a)
+{
+  using ::sqrt;
+  return make_double2(sqrt(a.x), sqrt(a.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 prsqrt<float4>(const float4& a)
+{
+  return make_float4(rsqrtf(a.x), rsqrtf(a.y), rsqrtf(a.z), rsqrtf(a.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 prsqrt<double2>(const double2& a)
+{
+  return make_double2(rsqrt(a.x), rsqrt(a.y));
+}
+
+
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_MATH_FUNCTIONS_CUDA_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/CUDA/PacketMath.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/CUDA/PacketMath.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/CUDA/PacketMath.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/CUDA/PacketMath.h
@@ -0,0 +1,333 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_PACKET_MATH_CUDA_H
+#define EIGEN_PACKET_MATH_CUDA_H
+
+namespace Eigen {
+
+namespace internal {
+
+// Make sure this is only available when targeting a GPU: we don't want to
+// introduce conflicts between these packet_traits definitions and the ones
+// we'll use on the host side (SSE, AVX, ...)
+#if defined(__CUDACC__) && defined(EIGEN_USE_GPU)
+template<> struct is_arithmetic<float4>  { enum { value = true }; };
+template<> struct is_arithmetic<double2> { enum { value = true }; };
+
+template<> struct packet_traits<float> : default_packet_traits
+{
+  typedef float4 type;
+  typedef float4 half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=4,
+    HasHalfPacket = 0,
+
+    HasDiv  = 1,
+    HasSin  = 0,
+    HasCos  = 0,
+    HasLog  = 1,
+    HasExp  = 1,
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasLGamma = 1,
+    HasDiGamma = 1,
+    HasZeta = 1,
+    HasPolygamma = 1,
+    HasErf = 1,
+    HasErfc = 1,
+    HasIGamma = 1,
+    HasIGammac = 1,
+    HasBetaInc = 1,
+
+    HasBlend = 0,
+  };
+};
+
+template<> struct packet_traits<double> : default_packet_traits
+{
+  typedef double2 type;
+  typedef double2 half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=2,
+    HasHalfPacket = 0,
+
+    HasDiv  = 1,
+    HasLog  = 1,
+    HasExp  = 1,
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasLGamma = 1,
+    HasDiGamma = 1,
+    HasZeta = 1,
+    HasPolygamma = 1,
+    HasErf = 1,
+    HasErfc = 1,
+    HasIGamma = 1,
+    HasIGammac = 1,
+    HasBetaInc = 1,
+
+    HasBlend = 0,
+  };
+};
+
+
+template<> struct unpacket_traits<float4>  { typedef float  type; enum {size=4, alignment=Aligned16}; typedef float4 half; };
+template<> struct unpacket_traits<double2> { typedef double type; enum {size=2, alignment=Aligned16}; typedef double2 half; };
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pset1<float4>(const float&  from) {
+  return make_float4(from, from, from, from);
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 pset1<double2>(const double& from) {
+  return make_double2(from, from);
+}
+
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 plset<float4>(const float& a) {
+  return make_float4(a, a+1, a+2, a+3);
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 plset<double2>(const double& a) {
+  return make_double2(a, a+1);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 padd<float4>(const float4& a, const float4& b) {
+  return make_float4(a.x+b.x, a.y+b.y, a.z+b.z, a.w+b.w);
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 padd<double2>(const double2& a, const double2& b) {
+  return make_double2(a.x+b.x, a.y+b.y);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 psub<float4>(const float4& a, const float4& b) {
+  return make_float4(a.x-b.x, a.y-b.y, a.z-b.z, a.w-b.w);
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 psub<double2>(const double2& a, const double2& b) {
+  return make_double2(a.x-b.x, a.y-b.y);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pnegate(const float4& a) {
+  return make_float4(-a.x, -a.y, -a.z, -a.w);
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 pnegate(const double2& a) {
+  return make_double2(-a.x, -a.y);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pconj(const float4& a) { return a; }
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 pconj(const double2& a) { return a; }
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pmul<float4>(const float4& a, const float4& b) {
+  return make_float4(a.x*b.x, a.y*b.y, a.z*b.z, a.w*b.w);
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 pmul<double2>(const double2& a, const double2& b) {
+  return make_double2(a.x*b.x, a.y*b.y);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pdiv<float4>(const float4& a, const float4& b) {
+  return make_float4(a.x/b.x, a.y/b.y, a.z/b.z, a.w/b.w);
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 pdiv<double2>(const double2& a, const double2& b) {
+  return make_double2(a.x/b.x, a.y/b.y);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pmin<float4>(const float4& a, const float4& b) {
+  return make_float4(fminf(a.x, b.x), fminf(a.y, b.y), fminf(a.z, b.z), fminf(a.w, b.w));
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 pmin<double2>(const double2& a, const double2& b) {
+  return make_double2(fmin(a.x, b.x), fmin(a.y, b.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pmax<float4>(const float4& a, const float4& b) {
+  return make_float4(fmaxf(a.x, b.x), fmaxf(a.y, b.y), fmaxf(a.z, b.z), fmaxf(a.w, b.w));
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 pmax<double2>(const double2& a, const double2& b) {
+  return make_double2(fmax(a.x, b.x), fmax(a.y, b.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pload<float4>(const float* from) {
+  return *reinterpret_cast<const float4*>(from);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 pload<double2>(const double* from) {
+  return *reinterpret_cast<const double2*>(from);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 ploadu<float4>(const float* from) {
+  return make_float4(from[0], from[1], from[2], from[3]);
+}
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 ploadu<double2>(const double* from) {
+  return make_double2(from[0], from[1]);
+}
+
+template<> EIGEN_STRONG_INLINE float4 ploaddup<float4>(const float*   from) {
+  return make_float4(from[0], from[0], from[1], from[1]);
+}
+template<> EIGEN_STRONG_INLINE double2 ploaddup<double2>(const double*  from) {
+  return make_double2(from[0], from[0]);
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void pstore<float>(float*   to, const float4& from) {
+  *reinterpret_cast<float4*>(to) = from;
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void pstore<double>(double* to, const double2& from) {
+  *reinterpret_cast<double2*>(to) = from;
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void pstoreu<float>(float*  to, const float4& from) {
+  to[0] = from.x;
+  to[1] = from.y;
+  to[2] = from.z;
+  to[3] = from.w;
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const double2& from) {
+  to[0] = from.x;
+  to[1] = from.y;
+}
+
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float4 ploadt_ro<float4, Aligned>(const float* from) {
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 350
+  return __ldg((const float4*)from);
+#else
+  return make_float4(from[0], from[1], from[2], from[3]);
+#endif
+}
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double2 ploadt_ro<double2, Aligned>(const double* from) {
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 350
+  return __ldg((const double2*)from);
+#else
+  return make_double2(from[0], from[1]);
+#endif
+}
+
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float4 ploadt_ro<float4, Unaligned>(const float* from) {
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 350
+  return make_float4(__ldg(from+0), __ldg(from+1), __ldg(from+2), __ldg(from+3));
+#else
+  return make_float4(from[0], from[1], from[2], from[3]);
+#endif
+}
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double2 ploadt_ro<double2, Unaligned>(const double* from) {
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 350
+  return make_double2(__ldg(from+0), __ldg(from+1));
+#else
+  return make_double2(from[0], from[1]);
+#endif
+}
+
+template<> EIGEN_DEVICE_FUNC inline float4 pgather<float, float4>(const float* from, Index stride) {
+  return make_float4(from[0*stride], from[1*stride], from[2*stride], from[3*stride]);
+}
+
+template<> EIGEN_DEVICE_FUNC inline double2 pgather<double, double2>(const double* from, Index stride) {
+  return make_double2(from[0*stride], from[1*stride]);
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<float, float4>(float* to, const float4& from, Index stride) {
+  to[stride*0] = from.x;
+  to[stride*1] = from.y;
+  to[stride*2] = from.z;
+  to[stride*3] = from.w;
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<double, double2>(double* to, const double2& from, Index stride) {
+  to[stride*0] = from.x;
+  to[stride*1] = from.y;
+}
+
+template<> EIGEN_DEVICE_FUNC inline float  pfirst<float4>(const float4& a) {
+  return a.x;
+}
+template<> EIGEN_DEVICE_FUNC inline double pfirst<double2>(const double2& a) {
+  return a.x;
+}
+
+template<> EIGEN_DEVICE_FUNC inline float  predux<float4>(const float4& a) {
+  return a.x + a.y + a.z + a.w;
+}
+template<> EIGEN_DEVICE_FUNC inline double predux<double2>(const double2& a) {
+  return a.x + a.y;
+}
+
+template<> EIGEN_DEVICE_FUNC inline float  predux_max<float4>(const float4& a) {
+  return fmaxf(fmaxf(a.x, a.y), fmaxf(a.z, a.w));
+}
+template<> EIGEN_DEVICE_FUNC inline double predux_max<double2>(const double2& a) {
+  return fmax(a.x, a.y);
+}
+
+template<> EIGEN_DEVICE_FUNC inline float  predux_min<float4>(const float4& a) {
+  return fminf(fminf(a.x, a.y), fminf(a.z, a.w));
+}
+template<> EIGEN_DEVICE_FUNC inline double predux_min<double2>(const double2& a) {
+  return fmin(a.x, a.y);
+}
+
+template<> EIGEN_DEVICE_FUNC inline float  predux_mul<float4>(const float4& a) {
+  return a.x * a.y * a.z * a.w;
+}
+template<> EIGEN_DEVICE_FUNC inline double predux_mul<double2>(const double2& a) {
+  return a.x * a.y;
+}
+
+template<> EIGEN_DEVICE_FUNC inline float4  pabs<float4>(const float4& a) {
+  return make_float4(fabsf(a.x), fabsf(a.y), fabsf(a.z), fabsf(a.w));
+}
+template<> EIGEN_DEVICE_FUNC inline double2 pabs<double2>(const double2& a) {
+  return make_double2(fabs(a.x), fabs(a.y));
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<float4,4>& kernel) {
+  float tmp = kernel.packet[0].y;
+  kernel.packet[0].y = kernel.packet[1].x;
+  kernel.packet[1].x = tmp;
+
+  tmp = kernel.packet[0].z;
+  kernel.packet[0].z = kernel.packet[2].x;
+  kernel.packet[2].x = tmp;
+
+  tmp = kernel.packet[0].w;
+  kernel.packet[0].w = kernel.packet[3].x;
+  kernel.packet[3].x = tmp;
+
+  tmp = kernel.packet[1].z;
+  kernel.packet[1].z = kernel.packet[2].y;
+  kernel.packet[2].y = tmp;
+
+  tmp = kernel.packet[1].w;
+  kernel.packet[1].w = kernel.packet[3].y;
+  kernel.packet[3].y = tmp;
+
+  tmp = kernel.packet[2].w;
+  kernel.packet[2].w = kernel.packet[3].z;
+  kernel.packet[3].z = tmp;
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<double2,2>& kernel) {
+  double tmp = kernel.packet[0].y;
+  kernel.packet[0].y = kernel.packet[1].x;
+  kernel.packet[1].x = tmp;
+}
+
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+
+#endif // EIGEN_PACKET_MATH_CUDA_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/CUDA/PacketMathHalf.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/CUDA/PacketMathHalf.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/CUDA/PacketMathHalf.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/CUDA/PacketMathHalf.h
@@ -0,0 +1,1123 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_PACKET_MATH_HALF_CUDA_H
+#define EIGEN_PACKET_MATH_HALF_CUDA_H
+
+
+namespace Eigen {
+namespace internal {
+
+// Most of the following operations require arch >= 3.0
+#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDACC__) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
+
+template<> struct is_arithmetic<half2> { enum { value = true }; };
+
+template<> struct packet_traits<Eigen::half> : default_packet_traits
+{
+  typedef half2 type;
+  typedef half2 half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=2,
+    HasHalfPacket = 0,
+    HasAdd    = 1,
+    HasMul    = 1,
+    HasDiv    = 1,
+    HasSqrt   = 1,
+    HasRsqrt  = 1,
+    HasExp    = 1,
+    HasLog    = 1,
+    HasLog1p  = 1
+  };
+};
+
+template<> struct unpacket_traits<half2> { typedef Eigen::half type; enum {size=2, alignment=Aligned16}; typedef half2 half; };
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pset1<half2>(const Eigen::half& from) {
+  return __half2half2(from);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pload<half2>(const Eigen::half* from) {
+  return *reinterpret_cast<const half2*>(from);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 ploadu<half2>(const Eigen::half* from) {
+  return __halves2half2(from[0], from[1]);
+}
+
+template<> EIGEN_STRONG_INLINE half2 ploaddup<half2>(const Eigen::half*  from) {
+  return __halves2half2(from[0], from[0]);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE void pstore<Eigen::half>(Eigen::half* to, const half2& from) {
+  *reinterpret_cast<half2*>(to) = from;
+}
+
+template<> __device__ EIGEN_STRONG_INLINE void pstoreu<Eigen::half>(Eigen::half* to, const half2& from) {
+  to[0] = __low2half(from);
+  to[1] = __high2half(from);
+}
+
+template<>
+ __device__ EIGEN_ALWAYS_INLINE half2 ploadt_ro<half2, Aligned>(const Eigen::half* from) {
+#if __CUDA_ARCH__ >= 350
+   return __ldg((const half2*)from);
+#else
+  return __halves2half2(*(from+0), *(from+1));
+#endif
+}
+
+template<>
+__device__ EIGEN_ALWAYS_INLINE half2 ploadt_ro<half2, Unaligned>(const Eigen::half* from) {
+#if __CUDA_ARCH__ >= 350
+   return __halves2half2(__ldg(from+0), __ldg(from+1));
+#else
+  return __halves2half2(*(from+0), *(from+1));
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pgather<Eigen::half, half2>(const Eigen::half* from, Index stride) {
+  return __halves2half2(from[0*stride], from[1*stride]);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE void pscatter<Eigen::half, half2>(Eigen::half* to, const half2& from, Index stride) {
+  to[stride*0] = __low2half(from);
+  to[stride*1] = __high2half(from);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE Eigen::half pfirst<half2>(const half2& a) {
+  return __low2half(a);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pabs<half2>(const half2& a) {
+  half2 result;
+  result.x = a.x & 0x7FFF7FFF;
+  return result;
+}
+
+
+__device__ EIGEN_STRONG_INLINE void
+ptranspose(PacketBlock<half2,2>& kernel) {
+  __half a1 = __low2half(kernel.packet[0]);
+  __half a2 = __high2half(kernel.packet[0]);
+  __half b1 = __low2half(kernel.packet[1]);
+  __half b2 = __high2half(kernel.packet[1]);
+  kernel.packet[0] = __halves2half2(a1, b1);
+  kernel.packet[1] = __halves2half2(a2, b2);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 plset<half2>(const Eigen::half& a) {
+#if __CUDA_ARCH__ >= 530
+  return __halves2half2(a, __hadd(a, __float2half(1.0f)));
+#else
+  float f = __half2float(a) + 1.0f;
+  return __halves2half2(a, __float2half(f));
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 padd<half2>(const half2& a, const half2& b) {
+#if __CUDA_ARCH__ >= 530
+  return __hadd2(a, b);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float r1 = a1 + b1;
+  float r2 = a2 + b2;
+  return __floats2half2_rn(r1, r2);
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 psub<half2>(const half2& a, const half2& b) {
+#if __CUDA_ARCH__ >= 530
+  return __hsub2(a, b);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float r1 = a1 - b1;
+  float r2 = a2 - b2;
+  return __floats2half2_rn(r1, r2);
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pnegate(const half2& a) {
+#if __CUDA_ARCH__ >= 530
+  return __hneg2(a);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  return __floats2half2_rn(-a1, -a2);
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pconj(const half2& a) { return a; }
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pmul<half2>(const half2& a, const half2& b) {
+#if __CUDA_ARCH__ >= 530
+  return __hmul2(a, b);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float r1 = a1 * b1;
+  float r2 = a2 * b2;
+  return __floats2half2_rn(r1, r2);
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pmadd<half2>(const half2& a, const half2& b, const half2& c) {
+#if __CUDA_ARCH__ >= 530
+   return __hfma2(a, b, c);
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float c1 = __low2float(c);
+  float c2 = __high2float(c);
+  float r1 = a1 * b1 + c1;
+  float r2 = a2 * b2 + c2;
+  return __floats2half2_rn(r1, r2);
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pdiv<half2>(const half2& a, const half2& b) {
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  float r1 = a1 / b1;
+  float r2 = a2 / b2;
+  return __floats2half2_rn(r1, r2);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pmin<half2>(const half2& a, const half2& b) {
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  __half r1 = a1 < b1 ? __low2half(a) : __low2half(b);
+  __half r2 = a2 < b2 ? __high2half(a) : __high2half(b);
+  return __halves2half2(r1, r2);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pmax<half2>(const half2& a, const half2& b) {
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float b1 = __low2float(b);
+  float b2 = __high2float(b);
+  __half r1 = a1 > b1 ? __low2half(a) : __low2half(b);
+  __half r2 = a2 > b2 ? __high2half(a) : __high2half(b);
+  return __halves2half2(r1, r2);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE Eigen::half predux<half2>(const half2& a) {
+#if __CUDA_ARCH__ >= 530
+  return __hadd(__low2half(a), __high2half(a));
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  return Eigen::half(half_impl::raw_uint16_to_half(__float2half_rn(a1 + a2)));
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE Eigen::half predux_max<half2>(const half2& a) {
+#if __CUDA_ARCH__ >= 530
+  __half first = __low2half(a);
+  __half second = __high2half(a);
+  return __hgt(first, second) ? first : second;
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  return a1 > a2 ? __low2half(a) : __high2half(a);
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE Eigen::half predux_min<half2>(const half2& a) {
+#if __CUDA_ARCH__ >= 530
+  __half first = __low2half(a);
+  __half second = __high2half(a);
+  return __hlt(first, second) ? first : second;
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  return a1 < a2 ? __low2half(a) : __high2half(a);
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE Eigen::half predux_mul<half2>(const half2& a) {
+#if __CUDA_ARCH__ >= 530
+  return __hmul(__low2half(a), __high2half(a));
+#else
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  return Eigen::half(half_impl::raw_uint16_to_half(__float2half_rn(a1 * a2)));
+#endif
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 plog1p<half2>(const half2& a) {
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float r1 = log1pf(a1);
+  float r2 = log1pf(a2);
+  return __floats2half2_rn(r1, r2);
+}
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 530
+
+template<>  __device__ EIGEN_STRONG_INLINE
+half2 plog<half2>(const half2& a) {
+  return h2log(a);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE
+half2 pexp<half2>(const half2& a) {
+  return h2exp(a);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE
+half2 psqrt<half2>(const half2& a) {
+  return h2sqrt(a);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE
+half2 prsqrt<half2>(const half2& a) {
+  return h2rsqrt(a);
+}
+
+#else
+
+template<> __device__ EIGEN_STRONG_INLINE half2 plog<half2>(const half2& a) {
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float r1 = logf(a1);
+  float r2 = logf(a2);
+  return __floats2half2_rn(r1, r2);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 pexp<half2>(const half2& a) {
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float r1 = expf(a1);
+  float r2 = expf(a2);
+  return __floats2half2_rn(r1, r2);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 psqrt<half2>(const half2& a) {
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float r1 = sqrtf(a1);
+  float r2 = sqrtf(a2);
+  return __floats2half2_rn(r1, r2);
+}
+
+template<> __device__ EIGEN_STRONG_INLINE half2 prsqrt<half2>(const half2& a) {
+  float a1 = __low2float(a);
+  float a2 = __high2float(a);
+  float r1 = rsqrtf(a1);
+  float r2 = rsqrtf(a2);
+  return __floats2half2_rn(r1, r2);
+}
+
+#endif
+
+#elif defined EIGEN_VECTORIZE_AVX512
+
+typedef struct {
+  __m256i x;
+} Packet16h;
+
+
+template<> struct is_arithmetic<Packet16h> { enum { value = true }; };
+
+template <>
+struct packet_traits<half> : default_packet_traits {
+  typedef Packet16h type;
+  // There is no half-size packet for Packet16h.
+  typedef Packet16h half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 16,
+    HasHalfPacket = 0,
+    HasAdd    = 0,
+    HasSub    = 0,
+    HasMul    = 0,
+    HasNegate = 0,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasConj   = 0,
+    HasSetLinear = 0,
+    HasDiv = 0,
+    HasSqrt = 0,
+    HasRsqrt = 0,
+    HasExp = 0,
+    HasLog = 0,
+    HasBlend = 0
+  };
+};
+
+
+template<> struct unpacket_traits<Packet16h> { typedef Eigen::half type; enum {size=16, alignment=Aligned32}; typedef Packet16h half; };
+
+template<> EIGEN_STRONG_INLINE Packet16h pset1<Packet16h>(const Eigen::half& from) {
+  Packet16h result;
+  result.x = _mm256_set1_epi16(from.x);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Eigen::half pfirst<Packet16h>(const Packet16h& from) {
+  return half_impl::raw_uint16_to_half(static_cast<unsigned short>(_mm256_extract_epi16(from.x, 0)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet16h pload<Packet16h>(const Eigen::half* from) {
+  Packet16h result;
+  result.x = _mm256_load_si256(reinterpret_cast<const __m256i*>(from));
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Packet16h ploadu<Packet16h>(const Eigen::half* from) {
+  Packet16h result;
+  result.x = _mm256_loadu_si256(reinterpret_cast<const __m256i*>(from));
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<half>(Eigen::half* to, const Packet16h& from) {
+  _mm256_store_si256((__m256i*)to, from.x);
+}
+
+template<> EIGEN_STRONG_INLINE void pstoreu<half>(Eigen::half* to, const Packet16h& from) {
+  _mm256_storeu_si256((__m256i*)to, from.x);
+}
+
+template<> EIGEN_STRONG_INLINE Packet16h
+ploadquad(const Eigen::half* from) {
+  Packet16h result;
+  unsigned short a = from[0].x;
+  unsigned short b = from[1].x;
+  unsigned short c = from[2].x;
+  unsigned short d = from[3].x;
+  result.x = _mm256_set_epi16(d, d, d, d, c, c, c, c, b, b, b, b, a, a, a, a);
+  return result;
+}
+
+EIGEN_STRONG_INLINE Packet16f half2float(const Packet16h& a) {
+#ifdef EIGEN_HAS_FP16_C
+  return _mm512_cvtph_ps(a.x);
+#else
+  EIGEN_ALIGN64 half aux[16];
+  pstore(aux, a);
+  float f0(aux[0]);
+  float f1(aux[1]);
+  float f2(aux[2]);
+  float f3(aux[3]);
+  float f4(aux[4]);
+  float f5(aux[5]);
+  float f6(aux[6]);
+  float f7(aux[7]);
+  float f8(aux[8]);
+  float f9(aux[9]);
+  float fa(aux[10]);
+  float fb(aux[11]);
+  float fc(aux[12]);
+  float fd(aux[13]);
+  float fe(aux[14]);
+  float ff(aux[15]);
+
+  return _mm512_set_ps(
+      ff, fe, fd, fc, fb, fa, f9, f8, f7, f6, f5, f4, f3, f2, f1, f0);
+#endif
+}
+
+EIGEN_STRONG_INLINE Packet16h float2half(const Packet16f& a) {
+#ifdef EIGEN_HAS_FP16_C
+  Packet16h result;
+  result.x = _mm512_cvtps_ph(a, _MM_FROUND_TO_NEAREST_INT|_MM_FROUND_NO_EXC);
+  return result;
+#else
+  EIGEN_ALIGN64 float aux[16];
+  pstore(aux, a);
+  half h0(aux[0]);
+  half h1(aux[1]);
+  half h2(aux[2]);
+  half h3(aux[3]);
+  half h4(aux[4]);
+  half h5(aux[5]);
+  half h6(aux[6]);
+  half h7(aux[7]);
+  half h8(aux[8]);
+  half h9(aux[9]);
+  half ha(aux[10]);
+  half hb(aux[11]);
+  half hc(aux[12]);
+  half hd(aux[13]);
+  half he(aux[14]);
+  half hf(aux[15]);
+
+  Packet16h result;
+  result.x = _mm256_set_epi16(
+      hf.x, he.x, hd.x, hc.x, hb.x, ha.x, h9.x, h8.x,
+      h7.x, h6.x, h5.x, h4.x, h3.x, h2.x, h1.x, h0.x);
+  return result;
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet16h padd<Packet16h>(const Packet16h& a, const Packet16h& b) {
+  Packet16f af = half2float(a);
+  Packet16f bf = half2float(b);
+  Packet16f rf = padd(af, bf);
+  return float2half(rf);
+}
+
+template<> EIGEN_STRONG_INLINE Packet16h pmul<Packet16h>(const Packet16h& a, const Packet16h& b) {
+  Packet16f af = half2float(a);
+  Packet16f bf = half2float(b);
+  Packet16f rf = pmul(af, bf);
+  return float2half(rf);
+}
+
+template<> EIGEN_STRONG_INLINE half predux<Packet16h>(const Packet16h& from) {
+  Packet16f from_float = half2float(from);
+  return half(predux(from_float));
+}
+
+template<> EIGEN_STRONG_INLINE Packet16h pgather<Eigen::half, Packet16h>(const Eigen::half* from, Index stride)
+{
+  Packet16h result;
+  result.x = _mm256_set_epi16(
+      from[15*stride].x, from[14*stride].x, from[13*stride].x, from[12*stride].x,
+      from[11*stride].x, from[10*stride].x, from[9*stride].x, from[8*stride].x,
+      from[7*stride].x, from[6*stride].x, from[5*stride].x, from[4*stride].x,
+      from[3*stride].x, from[2*stride].x, from[1*stride].x, from[0*stride].x);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE void pscatter<half, Packet16h>(half* to, const Packet16h& from, Index stride)
+{
+  EIGEN_ALIGN64 half aux[16];
+  pstore(aux, from);
+  to[stride*0].x = aux[0].x;
+  to[stride*1].x = aux[1].x;
+  to[stride*2].x = aux[2].x;
+  to[stride*3].x = aux[3].x;
+  to[stride*4].x = aux[4].x;
+  to[stride*5].x = aux[5].x;
+  to[stride*6].x = aux[6].x;
+  to[stride*7].x = aux[7].x;
+  to[stride*8].x = aux[8].x;
+  to[stride*9].x = aux[9].x;
+  to[stride*10].x = aux[10].x;
+  to[stride*11].x = aux[11].x;
+  to[stride*12].x = aux[12].x;
+  to[stride*13].x = aux[13].x;
+  to[stride*14].x = aux[14].x;
+  to[stride*15].x = aux[15].x;
+}
+
+EIGEN_STRONG_INLINE void
+ptranspose(PacketBlock<Packet16h,16>& kernel) {
+  __m256i a = kernel.packet[0].x;
+  __m256i b = kernel.packet[1].x;
+  __m256i c = kernel.packet[2].x;
+  __m256i d = kernel.packet[3].x;
+  __m256i e = kernel.packet[4].x;
+  __m256i f = kernel.packet[5].x;
+  __m256i g = kernel.packet[6].x;
+  __m256i h = kernel.packet[7].x;
+  __m256i i = kernel.packet[8].x;
+  __m256i j = kernel.packet[9].x;
+  __m256i k = kernel.packet[10].x;
+  __m256i l = kernel.packet[11].x;
+  __m256i m = kernel.packet[12].x;
+  __m256i n = kernel.packet[13].x;
+  __m256i o = kernel.packet[14].x;
+  __m256i p = kernel.packet[15].x;
+
+  __m256i ab_07 = _mm256_unpacklo_epi16(a, b);
+  __m256i cd_07 = _mm256_unpacklo_epi16(c, d);
+  __m256i ef_07 = _mm256_unpacklo_epi16(e, f);
+  __m256i gh_07 = _mm256_unpacklo_epi16(g, h);
+  __m256i ij_07 = _mm256_unpacklo_epi16(i, j);
+  __m256i kl_07 = _mm256_unpacklo_epi16(k, l);
+  __m256i mn_07 = _mm256_unpacklo_epi16(m, n);
+  __m256i op_07 = _mm256_unpacklo_epi16(o, p);
+
+  __m256i ab_8f = _mm256_unpackhi_epi16(a, b);
+  __m256i cd_8f = _mm256_unpackhi_epi16(c, d);
+  __m256i ef_8f = _mm256_unpackhi_epi16(e, f);
+  __m256i gh_8f = _mm256_unpackhi_epi16(g, h);
+  __m256i ij_8f = _mm256_unpackhi_epi16(i, j);
+  __m256i kl_8f = _mm256_unpackhi_epi16(k, l);
+  __m256i mn_8f = _mm256_unpackhi_epi16(m, n);
+  __m256i op_8f = _mm256_unpackhi_epi16(o, p);
+
+  __m256i abcd_03 = _mm256_unpacklo_epi32(ab_07, cd_07);
+  __m256i abcd_47 = _mm256_unpackhi_epi32(ab_07, cd_07);
+  __m256i efgh_03 = _mm256_unpacklo_epi32(ef_07, gh_07);
+  __m256i efgh_47 = _mm256_unpackhi_epi32(ef_07, gh_07);
+  __m256i ijkl_03 = _mm256_unpacklo_epi32(ij_07, kl_07);
+  __m256i ijkl_47 = _mm256_unpackhi_epi32(ij_07, kl_07);
+  __m256i mnop_03 = _mm256_unpacklo_epi32(mn_07, op_07);
+  __m256i mnop_47 = _mm256_unpackhi_epi32(mn_07, op_07);
+
+  __m256i abcd_8b = _mm256_unpacklo_epi32(ab_8f, cd_8f);
+  __m256i abcd_cf = _mm256_unpackhi_epi32(ab_8f, cd_8f);
+  __m256i efgh_8b = _mm256_unpacklo_epi32(ef_8f, gh_8f);
+  __m256i efgh_cf = _mm256_unpackhi_epi32(ef_8f, gh_8f);
+  __m256i ijkl_8b = _mm256_unpacklo_epi32(ij_8f, kl_8f);
+  __m256i ijkl_cf = _mm256_unpackhi_epi32(ij_8f, kl_8f);
+  __m256i mnop_8b = _mm256_unpacklo_epi32(mn_8f, op_8f);
+  __m256i mnop_cf = _mm256_unpackhi_epi32(mn_8f, op_8f);
+
+  __m256i abcdefgh_01 = _mm256_unpacklo_epi64(abcd_03, efgh_03);
+  __m256i abcdefgh_23 = _mm256_unpackhi_epi64(abcd_03, efgh_03);
+  __m256i ijklmnop_01 = _mm256_unpacklo_epi64(ijkl_03, mnop_03);
+  __m256i ijklmnop_23 = _mm256_unpackhi_epi64(ijkl_03, mnop_03);
+  __m256i abcdefgh_45 = _mm256_unpacklo_epi64(abcd_47, efgh_47);
+  __m256i abcdefgh_67 = _mm256_unpackhi_epi64(abcd_47, efgh_47);
+  __m256i ijklmnop_45 = _mm256_unpacklo_epi64(ijkl_47, mnop_47);
+  __m256i ijklmnop_67 = _mm256_unpackhi_epi64(ijkl_47, mnop_47);
+  __m256i abcdefgh_89 = _mm256_unpacklo_epi64(abcd_8b, efgh_8b);
+  __m256i abcdefgh_ab = _mm256_unpackhi_epi64(abcd_8b, efgh_8b);
+  __m256i ijklmnop_89 = _mm256_unpacklo_epi64(ijkl_8b, mnop_8b);
+  __m256i ijklmnop_ab = _mm256_unpackhi_epi64(ijkl_8b, mnop_8b);
+  __m256i abcdefgh_cd = _mm256_unpacklo_epi64(abcd_cf, efgh_cf);
+  __m256i abcdefgh_ef = _mm256_unpackhi_epi64(abcd_cf, efgh_cf);
+  __m256i ijklmnop_cd = _mm256_unpacklo_epi64(ijkl_cf, mnop_cf);
+  __m256i ijklmnop_ef = _mm256_unpackhi_epi64(ijkl_cf, mnop_cf);
+
+  // NOTE: no unpacklo/hi instr in this case, so using permute instr.
+  __m256i a_p_0 = _mm256_permute2x128_si256(abcdefgh_01, ijklmnop_01, 0x20);
+  __m256i a_p_1 = _mm256_permute2x128_si256(abcdefgh_01, ijklmnop_01, 0x31);
+  __m256i a_p_2 = _mm256_permute2x128_si256(abcdefgh_23, ijklmnop_23, 0x20);
+  __m256i a_p_3 = _mm256_permute2x128_si256(abcdefgh_23, ijklmnop_23, 0x31);
+  __m256i a_p_4 = _mm256_permute2x128_si256(abcdefgh_45, ijklmnop_45, 0x20);
+  __m256i a_p_5 = _mm256_permute2x128_si256(abcdefgh_45, ijklmnop_45, 0x31);
+  __m256i a_p_6 = _mm256_permute2x128_si256(abcdefgh_67, ijklmnop_67, 0x20);
+  __m256i a_p_7 = _mm256_permute2x128_si256(abcdefgh_67, ijklmnop_67, 0x31);
+  __m256i a_p_8 = _mm256_permute2x128_si256(abcdefgh_89, ijklmnop_89, 0x20);
+  __m256i a_p_9 = _mm256_permute2x128_si256(abcdefgh_89, ijklmnop_89, 0x31);
+  __m256i a_p_a = _mm256_permute2x128_si256(abcdefgh_ab, ijklmnop_ab, 0x20);
+  __m256i a_p_b = _mm256_permute2x128_si256(abcdefgh_ab, ijklmnop_ab, 0x31);
+  __m256i a_p_c = _mm256_permute2x128_si256(abcdefgh_cd, ijklmnop_cd, 0x20);
+  __m256i a_p_d = _mm256_permute2x128_si256(abcdefgh_cd, ijklmnop_cd, 0x31);
+  __m256i a_p_e = _mm256_permute2x128_si256(abcdefgh_ef, ijklmnop_ef, 0x20);
+  __m256i a_p_f = _mm256_permute2x128_si256(abcdefgh_ef, ijklmnop_ef, 0x31);
+
+  kernel.packet[0].x = a_p_0;
+  kernel.packet[1].x = a_p_1;
+  kernel.packet[2].x = a_p_2;
+  kernel.packet[3].x = a_p_3;
+  kernel.packet[4].x = a_p_4;
+  kernel.packet[5].x = a_p_5;
+  kernel.packet[6].x = a_p_6;
+  kernel.packet[7].x = a_p_7;
+  kernel.packet[8].x = a_p_8;
+  kernel.packet[9].x = a_p_9;
+  kernel.packet[10].x = a_p_a;
+  kernel.packet[11].x = a_p_b;
+  kernel.packet[12].x = a_p_c;
+  kernel.packet[13].x = a_p_d;
+  kernel.packet[14].x = a_p_e;
+  kernel.packet[15].x = a_p_f;
+}
+
+EIGEN_STRONG_INLINE void
+ptranspose(PacketBlock<Packet16h,8>& kernel) {
+  EIGEN_ALIGN64 half in[8][16];
+  pstore<half>(in[0], kernel.packet[0]);
+  pstore<half>(in[1], kernel.packet[1]);
+  pstore<half>(in[2], kernel.packet[2]);
+  pstore<half>(in[3], kernel.packet[3]);
+  pstore<half>(in[4], kernel.packet[4]);
+  pstore<half>(in[5], kernel.packet[5]);
+  pstore<half>(in[6], kernel.packet[6]);
+  pstore<half>(in[7], kernel.packet[7]);
+
+  EIGEN_ALIGN64 half out[8][16];
+
+  for (int i = 0; i < 8; ++i) {
+    for (int j = 0; j < 8; ++j) {
+      out[i][j] = in[j][2*i];
+    }
+    for (int j = 0; j < 8; ++j) {
+      out[i][j+8] = in[j][2*i+1];
+    }
+  }
+
+  kernel.packet[0] = pload<Packet16h>(out[0]);
+  kernel.packet[1] = pload<Packet16h>(out[1]);
+  kernel.packet[2] = pload<Packet16h>(out[2]);
+  kernel.packet[3] = pload<Packet16h>(out[3]);
+  kernel.packet[4] = pload<Packet16h>(out[4]);
+  kernel.packet[5] = pload<Packet16h>(out[5]);
+  kernel.packet[6] = pload<Packet16h>(out[6]);
+  kernel.packet[7] = pload<Packet16h>(out[7]);
+}
+
+EIGEN_STRONG_INLINE void
+ptranspose(PacketBlock<Packet16h,4>& kernel) {
+  EIGEN_ALIGN64 half in[4][16];
+  pstore<half>(in[0], kernel.packet[0]);
+  pstore<half>(in[1], kernel.packet[1]);
+  pstore<half>(in[2], kernel.packet[2]);
+  pstore<half>(in[3], kernel.packet[3]);
+
+  EIGEN_ALIGN64 half out[4][16];
+
+  for (int i = 0; i < 4; ++i) {
+    for (int j = 0; j < 4; ++j) {
+      out[i][j] = in[j][4*i];
+    }
+    for (int j = 0; j < 4; ++j) {
+      out[i][j+4] = in[j][4*i+1];
+    }
+    for (int j = 0; j < 4; ++j) {
+      out[i][j+8] = in[j][4*i+2];
+    }
+    for (int j = 0; j < 4; ++j) {
+      out[i][j+12] = in[j][4*i+3];
+    }
+  }
+
+  kernel.packet[0] = pload<Packet16h>(out[0]);
+  kernel.packet[1] = pload<Packet16h>(out[1]);
+  kernel.packet[2] = pload<Packet16h>(out[2]);
+  kernel.packet[3] = pload<Packet16h>(out[3]);
+}
+
+
+#elif defined EIGEN_VECTORIZE_AVX
+
+typedef struct {
+  __m128i x;
+} Packet8h;
+
+
+template<> struct is_arithmetic<Packet8h> { enum { value = true }; };
+
+template <>
+struct packet_traits<Eigen::half> : default_packet_traits {
+  typedef Packet8h type;
+  // There is no half-size packet for Packet8h.
+  typedef Packet8h half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 8,
+    HasHalfPacket = 0,
+    HasAdd    = 0,
+    HasSub    = 0,
+    HasMul    = 0,
+    HasNegate = 0,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasConj   = 0,
+    HasSetLinear = 0,
+    HasDiv = 0,
+    HasSqrt = 0,
+    HasRsqrt = 0,
+    HasExp = 0,
+    HasLog = 0,
+    HasBlend = 0
+  };
+};
+
+
+template<> struct unpacket_traits<Packet8h> { typedef Eigen::half type; enum {size=8, alignment=Aligned16}; typedef Packet8h half; };
+
+template<> EIGEN_STRONG_INLINE Packet8h pset1<Packet8h>(const Eigen::half& from) {
+  Packet8h result;
+  result.x = _mm_set1_epi16(from.x);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Eigen::half pfirst<Packet8h>(const Packet8h& from) {
+  return half_impl::raw_uint16_to_half(static_cast<unsigned short>(_mm_extract_epi16(from.x, 0)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet8h pload<Packet8h>(const Eigen::half* from) {
+  Packet8h result;
+  result.x = _mm_load_si128(reinterpret_cast<const __m128i*>(from));
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Packet8h ploadu<Packet8h>(const Eigen::half* from) {
+  Packet8h result;
+  result.x = _mm_loadu_si128(reinterpret_cast<const __m128i*>(from));
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<Eigen::half>(Eigen::half* to, const Packet8h& from) {
+  _mm_store_si128(reinterpret_cast<__m128i*>(to), from.x);
+}
+
+template<> EIGEN_STRONG_INLINE void pstoreu<Eigen::half>(Eigen::half* to, const Packet8h& from) {
+  _mm_storeu_si128(reinterpret_cast<__m128i*>(to), from.x);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8h
+ploadquad<Packet8h>(const Eigen::half* from) {
+  Packet8h result;
+  unsigned short a = from[0].x;
+  unsigned short b = from[1].x;
+  result.x = _mm_set_epi16(b, b, b, b, a, a, a, a);
+  return result;
+}
+
+EIGEN_STRONG_INLINE Packet8f half2float(const Packet8h& a) {
+#ifdef EIGEN_HAS_FP16_C
+  return _mm256_cvtph_ps(a.x);
+#else
+  EIGEN_ALIGN32 Eigen::half aux[8];
+  pstore(aux, a);
+  float f0(aux[0]);
+  float f1(aux[1]);
+  float f2(aux[2]);
+  float f3(aux[3]);
+  float f4(aux[4]);
+  float f5(aux[5]);
+  float f6(aux[6]);
+  float f7(aux[7]);
+
+  return _mm256_set_ps(f7, f6, f5, f4, f3, f2, f1, f0);
+#endif
+}
+
+EIGEN_STRONG_INLINE Packet8h float2half(const Packet8f& a) {
+#ifdef EIGEN_HAS_FP16_C
+  Packet8h result;
+  result.x = _mm256_cvtps_ph(a, _MM_FROUND_TO_NEAREST_INT|_MM_FROUND_NO_EXC);
+  return result;
+#else
+  EIGEN_ALIGN32 float aux[8];
+  pstore(aux, a);
+  Eigen::half h0(aux[0]);
+  Eigen::half h1(aux[1]);
+  Eigen::half h2(aux[2]);
+  Eigen::half h3(aux[3]);
+  Eigen::half h4(aux[4]);
+  Eigen::half h5(aux[5]);
+  Eigen::half h6(aux[6]);
+  Eigen::half h7(aux[7]);
+
+  Packet8h result;
+  result.x = _mm_set_epi16(h7.x, h6.x, h5.x, h4.x, h3.x, h2.x, h1.x, h0.x);
+  return result;
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet8h pconj(const Packet8h& a) { return a; }
+
+template<> EIGEN_STRONG_INLINE Packet8h padd<Packet8h>(const Packet8h& a, const Packet8h& b) {
+  Packet8f af = half2float(a);
+  Packet8f bf = half2float(b);
+  Packet8f rf = padd(af, bf);
+  return float2half(rf);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8h pmul<Packet8h>(const Packet8h& a, const Packet8h& b) {
+  Packet8f af = half2float(a);
+  Packet8f bf = half2float(b);
+  Packet8f rf = pmul(af, bf);
+  return float2half(rf);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8h pgather<Eigen::half, Packet8h>(const Eigen::half* from, Index stride)
+{
+  Packet8h result;
+  result.x = _mm_set_epi16(from[7*stride].x, from[6*stride].x, from[5*stride].x, from[4*stride].x, from[3*stride].x, from[2*stride].x, from[1*stride].x, from[0*stride].x);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE void pscatter<Eigen::half, Packet8h>(Eigen::half* to, const Packet8h& from, Index stride)
+{
+  EIGEN_ALIGN32 Eigen::half aux[8];
+  pstore(aux, from);
+  to[stride*0].x = aux[0].x;
+  to[stride*1].x = aux[1].x;
+  to[stride*2].x = aux[2].x;
+  to[stride*3].x = aux[3].x;
+  to[stride*4].x = aux[4].x;
+  to[stride*5].x = aux[5].x;
+  to[stride*6].x = aux[6].x;
+  to[stride*7].x = aux[7].x;
+}
+
+template<> EIGEN_STRONG_INLINE Eigen::half predux<Packet8h>(const Packet8h& a) {
+  Packet8f af = half2float(a);
+  float reduced = predux<Packet8f>(af);
+  return Eigen::half(reduced);
+}
+
+template<> EIGEN_STRONG_INLINE Eigen::half predux_max<Packet8h>(const Packet8h& a) {
+  Packet8f af = half2float(a);
+  float reduced = predux_max<Packet8f>(af);
+  return Eigen::half(reduced);
+}
+
+template<> EIGEN_STRONG_INLINE Eigen::half predux_min<Packet8h>(const Packet8h& a) {
+  Packet8f af = half2float(a);
+  float reduced = predux_min<Packet8f>(af);
+  return Eigen::half(reduced);
+}
+
+template<> EIGEN_STRONG_INLINE Eigen::half predux_mul<Packet8h>(const Packet8h& a) {
+  Packet8f af = half2float(a);
+  float reduced = predux_mul<Packet8f>(af);
+  return Eigen::half(reduced);
+}
+
+EIGEN_STRONG_INLINE void
+ptranspose(PacketBlock<Packet8h,8>& kernel) {
+  __m128i a = kernel.packet[0].x;
+  __m128i b = kernel.packet[1].x;
+  __m128i c = kernel.packet[2].x;
+  __m128i d = kernel.packet[3].x;
+  __m128i e = kernel.packet[4].x;
+  __m128i f = kernel.packet[5].x;
+  __m128i g = kernel.packet[6].x;
+  __m128i h = kernel.packet[7].x;
+
+  __m128i a03b03 = _mm_unpacklo_epi16(a, b);
+  __m128i c03d03 = _mm_unpacklo_epi16(c, d);
+  __m128i e03f03 = _mm_unpacklo_epi16(e, f);
+  __m128i g03h03 = _mm_unpacklo_epi16(g, h);
+  __m128i a47b47 = _mm_unpackhi_epi16(a, b);
+  __m128i c47d47 = _mm_unpackhi_epi16(c, d);
+  __m128i e47f47 = _mm_unpackhi_epi16(e, f);
+  __m128i g47h47 = _mm_unpackhi_epi16(g, h);
+
+  __m128i a01b01c01d01 = _mm_unpacklo_epi32(a03b03, c03d03);
+  __m128i a23b23c23d23 = _mm_unpackhi_epi32(a03b03, c03d03);
+  __m128i e01f01g01h01 = _mm_unpacklo_epi32(e03f03, g03h03);
+  __m128i e23f23g23h23 = _mm_unpackhi_epi32(e03f03, g03h03);
+  __m128i a45b45c45d45 = _mm_unpacklo_epi32(a47b47, c47d47);
+  __m128i a67b67c67d67 = _mm_unpackhi_epi32(a47b47, c47d47);
+  __m128i e45f45g45h45 = _mm_unpacklo_epi32(e47f47, g47h47);
+  __m128i e67f67g67h67 = _mm_unpackhi_epi32(e47f47, g47h47);
+
+  __m128i a0b0c0d0e0f0g0h0 = _mm_unpacklo_epi64(a01b01c01d01, e01f01g01h01);
+  __m128i a1b1c1d1e1f1g1h1 = _mm_unpackhi_epi64(a01b01c01d01, e01f01g01h01);
+  __m128i a2b2c2d2e2f2g2h2 = _mm_unpacklo_epi64(a23b23c23d23, e23f23g23h23);
+  __m128i a3b3c3d3e3f3g3h3 = _mm_unpackhi_epi64(a23b23c23d23, e23f23g23h23);
+  __m128i a4b4c4d4e4f4g4h4 = _mm_unpacklo_epi64(a45b45c45d45, e45f45g45h45);
+  __m128i a5b5c5d5e5f5g5h5 = _mm_unpackhi_epi64(a45b45c45d45, e45f45g45h45);
+  __m128i a6b6c6d6e6f6g6h6 = _mm_unpacklo_epi64(a67b67c67d67, e67f67g67h67);
+  __m128i a7b7c7d7e7f7g7h7 = _mm_unpackhi_epi64(a67b67c67d67, e67f67g67h67);
+
+  kernel.packet[0].x = a0b0c0d0e0f0g0h0;
+  kernel.packet[1].x = a1b1c1d1e1f1g1h1;
+  kernel.packet[2].x = a2b2c2d2e2f2g2h2;
+  kernel.packet[3].x = a3b3c3d3e3f3g3h3;
+  kernel.packet[4].x = a4b4c4d4e4f4g4h4;
+  kernel.packet[5].x = a5b5c5d5e5f5g5h5;
+  kernel.packet[6].x = a6b6c6d6e6f6g6h6;
+  kernel.packet[7].x = a7b7c7d7e7f7g7h7;
+}
+
+EIGEN_STRONG_INLINE void
+ptranspose(PacketBlock<Packet8h,4>& kernel) {
+  EIGEN_ALIGN32 Eigen::half in[4][8];
+  pstore<Eigen::half>(in[0], kernel.packet[0]);
+  pstore<Eigen::half>(in[1], kernel.packet[1]);
+  pstore<Eigen::half>(in[2], kernel.packet[2]);
+  pstore<Eigen::half>(in[3], kernel.packet[3]);
+
+  EIGEN_ALIGN32 Eigen::half out[4][8];
+
+  for (int i = 0; i < 4; ++i) {
+    for (int j = 0; j < 4; ++j) {
+      out[i][j] = in[j][2*i];
+    }
+    for (int j = 0; j < 4; ++j) {
+      out[i][j+4] = in[j][2*i+1];
+    }
+  }
+
+  kernel.packet[0] = pload<Packet8h>(out[0]);
+  kernel.packet[1] = pload<Packet8h>(out[1]);
+  kernel.packet[2] = pload<Packet8h>(out[2]);
+  kernel.packet[3] = pload<Packet8h>(out[3]);
+}
+
+
+// Disable the following code since it's broken on too many platforms / compilers.
+//#elif defined(EIGEN_VECTORIZE_SSE) && (!EIGEN_ARCH_x86_64) && (!EIGEN_COMP_MSVC)
+#elif 0
+
+typedef struct {
+  __m64 x;
+} Packet4h;
+
+
+template<> struct is_arithmetic<Packet4h> { enum { value = true }; };
+
+template <>
+struct packet_traits<Eigen::half> : default_packet_traits {
+  typedef Packet4h type;
+  // There is no half-size packet for Packet4h.
+  typedef Packet4h half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 4,
+    HasHalfPacket = 0,
+    HasAdd    = 0,
+    HasSub    = 0,
+    HasMul    = 0,
+    HasNegate = 0,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasConj   = 0,
+    HasSetLinear = 0,
+    HasDiv = 0,
+    HasSqrt = 0,
+    HasRsqrt = 0,
+    HasExp = 0,
+    HasLog = 0,
+    HasBlend = 0
+  };
+};
+
+
+template<> struct unpacket_traits<Packet4h> { typedef Eigen::half type; enum {size=4, alignment=Aligned16}; typedef Packet4h half; };
+
+template<> EIGEN_STRONG_INLINE Packet4h pset1<Packet4h>(const Eigen::half& from) {
+  Packet4h result;
+  result.x = _mm_set1_pi16(from.x);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Eigen::half pfirst<Packet4h>(const Packet4h& from) {
+  return half_impl::raw_uint16_to_half(static_cast<unsigned short>(_mm_cvtsi64_si32(from.x)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4h pconj(const Packet4h& a) { return a; }
+
+template<> EIGEN_STRONG_INLINE Packet4h padd<Packet4h>(const Packet4h& a, const Packet4h& b) {
+  __int64_t a64 = _mm_cvtm64_si64(a.x);
+  __int64_t b64 = _mm_cvtm64_si64(b.x);
+
+  Eigen::half h[4];
+
+  Eigen::half ha = half_impl::raw_uint16_to_half(static_cast<unsigned short>(a64));
+  Eigen::half hb = half_impl::raw_uint16_to_half(static_cast<unsigned short>(b64));
+  h[0] = ha + hb;
+  ha = half_impl::raw_uint16_to_half(static_cast<unsigned short>(a64 >> 16));
+  hb = half_impl::raw_uint16_to_half(static_cast<unsigned short>(b64 >> 16));
+  h[1] = ha + hb;
+  ha = half_impl::raw_uint16_to_half(static_cast<unsigned short>(a64 >> 32));
+  hb = half_impl::raw_uint16_to_half(static_cast<unsigned short>(b64 >> 32));
+  h[2] = ha + hb;
+  ha = half_impl::raw_uint16_to_half(static_cast<unsigned short>(a64 >> 48));
+  hb = half_impl::raw_uint16_to_half(static_cast<unsigned short>(b64 >> 48));
+  h[3] = ha + hb;
+  Packet4h result;
+  result.x = _mm_set_pi16(h[3].x, h[2].x, h[1].x, h[0].x);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4h pmul<Packet4h>(const Packet4h& a, const Packet4h& b) {
+  __int64_t a64 = _mm_cvtm64_si64(a.x);
+  __int64_t b64 = _mm_cvtm64_si64(b.x);
+
+  Eigen::half h[4];
+
+  Eigen::half ha = half_impl::raw_uint16_to_half(static_cast<unsigned short>(a64));
+  Eigen::half hb = half_impl::raw_uint16_to_half(static_cast<unsigned short>(b64));
+  h[0] = ha * hb;
+  ha = half_impl::raw_uint16_to_half(static_cast<unsigned short>(a64 >> 16));
+  hb = half_impl::raw_uint16_to_half(static_cast<unsigned short>(b64 >> 16));
+  h[1] = ha * hb;
+  ha = half_impl::raw_uint16_to_half(static_cast<unsigned short>(a64 >> 32));
+  hb = half_impl::raw_uint16_to_half(static_cast<unsigned short>(b64 >> 32));
+  h[2] = ha * hb;
+  ha = half_impl::raw_uint16_to_half(static_cast<unsigned short>(a64 >> 48));
+  hb = half_impl::raw_uint16_to_half(static_cast<unsigned short>(b64 >> 48));
+  h[3] = ha * hb;
+  Packet4h result;
+  result.x = _mm_set_pi16(h[3].x, h[2].x, h[1].x, h[0].x);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4h pload<Packet4h>(const Eigen::half* from) {
+  Packet4h result;
+  result.x = _mm_cvtsi64_m64(*reinterpret_cast<const __int64_t*>(from));
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4h ploadu<Packet4h>(const Eigen::half* from) {
+  Packet4h result;
+  result.x = _mm_cvtsi64_m64(*reinterpret_cast<const __int64_t*>(from));
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<Eigen::half>(Eigen::half* to, const Packet4h& from) {
+  __int64_t r = _mm_cvtm64_si64(from.x);
+  *(reinterpret_cast<__int64_t*>(to)) = r;
+}
+
+template<> EIGEN_STRONG_INLINE void pstoreu<Eigen::half>(Eigen::half* to, const Packet4h& from) {
+  __int64_t r = _mm_cvtm64_si64(from.x);
+  *(reinterpret_cast<__int64_t*>(to)) = r;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4h
+ploadquad<Packet4h>(const Eigen::half* from) {
+  return pset1<Packet4h>(*from);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4h pgather<Eigen::half, Packet4h>(const Eigen::half* from, Index stride)
+{
+  Packet4h result;
+  result.x = _mm_set_pi16(from[3*stride].x, from[2*stride].x, from[1*stride].x, from[0*stride].x);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE void pscatter<Eigen::half, Packet4h>(Eigen::half* to, const Packet4h& from, Index stride)
+{
+  __int64_t a = _mm_cvtm64_si64(from.x);
+  to[stride*0].x = static_cast<unsigned short>(a);
+  to[stride*1].x = static_cast<unsigned short>(a >> 16);
+  to[stride*2].x = static_cast<unsigned short>(a >> 32);
+  to[stride*3].x = static_cast<unsigned short>(a >> 48);
+}
+
+EIGEN_STRONG_INLINE void
+ptranspose(PacketBlock<Packet4h,4>& kernel) {
+  __m64 T0 = _mm_unpacklo_pi16(kernel.packet[0].x, kernel.packet[1].x);
+  __m64 T1 = _mm_unpacklo_pi16(kernel.packet[2].x, kernel.packet[3].x);
+  __m64 T2 = _mm_unpackhi_pi16(kernel.packet[0].x, kernel.packet[1].x);
+  __m64 T3 = _mm_unpackhi_pi16(kernel.packet[2].x, kernel.packet[3].x);
+
+  kernel.packet[0].x = _mm_unpacklo_pi32(T0, T1);
+  kernel.packet[1].x = _mm_unpackhi_pi32(T0, T1);
+  kernel.packet[2].x = _mm_unpacklo_pi32(T2, T3);
+  kernel.packet[3].x = _mm_unpackhi_pi32(T2, T3);
+}
+
+#endif
+
+}
+}
+
+#endif // EIGEN_PACKET_MATH_HALF_CUDA_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/CUDA/TypeCasting.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/CUDA/TypeCasting.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/CUDA/TypeCasting.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/CUDA/TypeCasting.h
@@ -0,0 +1,212 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_TYPE_CASTING_CUDA_H
+#define EIGEN_TYPE_CASTING_CUDA_H
+
+namespace Eigen {
+
+namespace internal {
+
+template<>
+struct scalar_cast_op<float, Eigen::half> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
+  typedef Eigen::half result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Eigen::half operator() (const float& a) const {
+    #if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
+      return __float2half(a);
+    #else
+      return Eigen::half(a);
+    #endif
+  }
+};
+
+template<>
+struct functor_traits<scalar_cast_op<float, Eigen::half> >
+{ enum { Cost = NumTraits<float>::AddCost, PacketAccess = false }; };
+
+
+template<>
+struct scalar_cast_op<int, Eigen::half> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
+  typedef Eigen::half result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Eigen::half operator() (const int& a) const {
+    #if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
+      return __float2half(static_cast<float>(a));
+    #else
+      return Eigen::half(static_cast<float>(a));
+    #endif
+  }
+};
+
+template<>
+struct functor_traits<scalar_cast_op<int, Eigen::half> >
+{ enum { Cost = NumTraits<float>::AddCost, PacketAccess = false }; };
+
+
+template<>
+struct scalar_cast_op<Eigen::half, float> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
+  typedef float result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float operator() (const Eigen::half& a) const {
+    #if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
+      return __half2float(a);
+    #else
+      return static_cast<float>(a);
+    #endif
+  }
+};
+
+template<>
+struct functor_traits<scalar_cast_op<Eigen::half, float> >
+{ enum { Cost = NumTraits<float>::AddCost, PacketAccess = false }; };
+
+
+
+#if defined(EIGEN_HAS_CUDA_FP16) && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 300
+
+template <>
+struct type_casting_traits<Eigen::half, float> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 2,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 pcast<half2, float4>(const half2& a, const half2& b) {
+  float2 r1 = __half22float2(a);
+  float2 r2 = __half22float2(b);
+  return make_float4(r1.x, r1.y, r2.x, r2.y);
+}
+
+template <>
+struct type_casting_traits<float, Eigen::half> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 2
+  };
+};
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE half2 pcast<float4, half2>(const float4& a) {
+  // Simply discard the second half of the input
+  return __floats2half2_rn(a.x, a.y);
+}
+
+#elif defined EIGEN_VECTORIZE_AVX512
+template <>
+struct type_casting_traits<half, float> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet16f pcast<Packet16h, Packet16f>(const Packet16h& a) {
+  return half2float(a);
+}
+
+template <>
+struct type_casting_traits<float, half> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet16h pcast<Packet16f, Packet16h>(const Packet16f& a) {
+  return float2half(a);
+}
+
+#elif defined EIGEN_VECTORIZE_AVX
+
+template <>
+struct type_casting_traits<Eigen::half, float> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet8f pcast<Packet8h, Packet8f>(const Packet8h& a) {
+  return half2float(a);
+}
+
+template <>
+struct type_casting_traits<float, Eigen::half> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet8h pcast<Packet8f, Packet8h>(const Packet8f& a) {
+  return float2half(a);
+}
+
+// Disable the following code since it's broken on too many platforms / compilers.
+//#elif defined(EIGEN_VECTORIZE_SSE) && (!EIGEN_ARCH_x86_64) && (!EIGEN_COMP_MSVC)
+#elif 0
+
+template <>
+struct type_casting_traits<Eigen::half, float> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet4h, Packet4f>(const Packet4h& a) {
+  __int64_t a64 = _mm_cvtm64_si64(a.x);
+  Eigen::half h = raw_uint16_to_half(static_cast<unsigned short>(a64));
+  float f1 = static_cast<float>(h);
+  h = raw_uint16_to_half(static_cast<unsigned short>(a64 >> 16));
+  float f2 = static_cast<float>(h);
+  h = raw_uint16_to_half(static_cast<unsigned short>(a64 >> 32));
+  float f3 = static_cast<float>(h);
+  h = raw_uint16_to_half(static_cast<unsigned short>(a64 >> 48));
+  float f4 = static_cast<float>(h);
+  return _mm_set_ps(f4, f3, f2, f1);
+}
+
+template <>
+struct type_casting_traits<float, Eigen::half> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet4h pcast<Packet4f, Packet4h>(const Packet4f& a) {
+  EIGEN_ALIGN16 float aux[4];
+  pstore(aux, a);
+  Eigen::half h0(aux[0]);
+  Eigen::half h1(aux[1]);
+  Eigen::half h2(aux[2]);
+  Eigen::half h3(aux[3]);
+
+  Packet4h result;
+  result.x = _mm_set_pi16(h3.x, h2.x, h1.x, h0.x);
+  return result;
+}
+
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TYPE_CASTING_CUDA_H

DELETED 3rd_party/eigen/Eigen/src/Core/arch/Default/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Core/arch/Default/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/Default/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Core/arch/Default/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Core_arch_Default_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Core_arch_Default_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/Default COMPONENT Devel
-)

DELETED 3rd_party/eigen/Eigen/src/Core/arch/NEON/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Core/arch/NEON/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/NEON/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Core/arch/NEON/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Core_arch_NEON_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Core_arch_NEON_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/NEON COMPONENT Devel
-)

Index: 3rd_party/eigen/Eigen/src/Core/arch/NEON/Complex.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/NEON/Complex.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/NEON/Complex.h
@@ -1,9 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010 Konstantinos Margaritis <markos@freevec.org>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -12,12 +13,25 @@
 
 namespace Eigen {
 
 namespace internal {
 
-static uint32x4_t p4ui_CONJ_XOR = EIGEN_INIT_NEON_PACKET4(0x00000000, 0x80000000, 0x00000000, 0x80000000);
-static uint32x2_t p2ui_CONJ_XOR = EIGEN_INIT_NEON_PACKET2(0x00000000, 0x80000000);
+inline uint32x4_t p4ui_CONJ_XOR() {
+// See bug 1325, clang fails to call vld1q_u64.
+#if EIGEN_COMP_CLANG
+  uint32x4_t ret = { 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
+  return ret;
+#else
+  static const uint32_t conj_XOR_DATA[] = { 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
+  return vld1q_u32( conj_XOR_DATA );
+#endif
+}
+
+inline uint32x2_t p2ui_CONJ_XOR() {
+  static const uint32_t conj_XOR_DATA[] = { 0x00000000, 0x80000000 };
+  return vld1_u32( conj_XOR_DATA );
+}
 
 //---------- float ----------
 struct Packet2cf
 {
   EIGEN_STRONG_INLINE Packet2cf() {}
@@ -26,14 +40,16 @@
 };
 
 template<> struct packet_traits<std::complex<float> >  : default_packet_traits
 {
   typedef Packet2cf type;
+  typedef Packet2cf half;
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 1,
     size = 2,
+    HasHalfPacket = 0,
 
     HasAdd    = 1,
     HasSub    = 1,
     HasMul    = 1,
     HasDiv    = 1,
@@ -44,11 +60,11 @@
     HasMax    = 0,
     HasSetLinear = 0
   };
 };
 
-template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2}; };
+template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2, alignment=Aligned16}; typedef Packet2cf half; };
 
 template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>&  from)
 {
   float32x2_t r64;
   r64 = vld1_f32((float *)&from);
@@ -60,36 +76,36 @@
 template<> EIGEN_STRONG_INLINE Packet2cf psub<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(psub<Packet4f>(a.v,b.v)); }
 template<> EIGEN_STRONG_INLINE Packet2cf pnegate(const Packet2cf& a) { return Packet2cf(pnegate<Packet4f>(a.v)); }
 template<> EIGEN_STRONG_INLINE Packet2cf pconj(const Packet2cf& a)
 {
   Packet4ui b = vreinterpretq_u32_f32(a.v);
-  return Packet2cf(vreinterpretq_f32_u32(veorq_u32(b, p4ui_CONJ_XOR)));
+  return Packet2cf(vreinterpretq_f32_u32(veorq_u32(b, p4ui_CONJ_XOR())));
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cf pmul<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
 {
   Packet4f v1, v2;
 
   // Get the real values of a | a1_re | a1_re | a2_re | a2_re |
   v1 = vcombine_f32(vdup_lane_f32(vget_low_f32(a.v), 0), vdup_lane_f32(vget_high_f32(a.v), 0));
-  // Get the real values of a | a1_im | a1_im | a2_im | a2_im |
+  // Get the imag values of a | a1_im | a1_im | a2_im | a2_im |
   v2 = vcombine_f32(vdup_lane_f32(vget_low_f32(a.v), 1), vdup_lane_f32(vget_high_f32(a.v), 1));
   // Multiply the real a with b
   v1 = vmulq_f32(v1, b.v);
   // Multiply the imag a with b
   v2 = vmulq_f32(v2, b.v);
   // Conjugate v2 
-  v2 = vreinterpretq_f32_u32(veorq_u32(vreinterpretq_u32_f32(v2), p4ui_CONJ_XOR));
+  v2 = vreinterpretq_f32_u32(veorq_u32(vreinterpretq_u32_f32(v2), p4ui_CONJ_XOR()));
   // Swap real/imag elements in v2.
   v2 = vrev64q_f32(v2);
   // Add and return the result
   return Packet2cf(vaddq_f32(v1, v2));
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cf pand   <Packet2cf>(const Packet2cf& a, const Packet2cf& b)
 {
-  return Packet2cf(vreinterpretq_f32_u32(vorrq_u32(vreinterpretq_u32_f32(a.v),vreinterpretq_u32_f32(b.v))));
+  return Packet2cf(vreinterpretq_f32_u32(vandq_u32(vreinterpretq_u32_f32(a.v),vreinterpretq_u32_f32(b.v))));
 }
 template<> EIGEN_STRONG_INLINE Packet2cf por    <Packet2cf>(const Packet2cf& a, const Packet2cf& b)
 {
   return Packet2cf(vreinterpretq_f32_u32(vorrq_u32(vreinterpretq_u32_f32(a.v),vreinterpretq_u32_f32(b.v))));
 }
@@ -107,10 +123,26 @@
 
 template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<float>* from) { return pset1<Packet2cf>(*from); }
 
 template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((float*)to, from.v); }
 template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((float*)to, from.v); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, Index stride)
+{
+  Packet4f res = pset1<Packet4f>(0.f);
+  res = vsetq_lane_f32(std::real(from[0*stride]), res, 0);
+  res = vsetq_lane_f32(std::imag(from[0*stride]), res, 1);
+  res = vsetq_lane_f32(std::real(from[1*stride]), res, 2);
+  res = vsetq_lane_f32(std::imag(from[1*stride]), res, 3);
+  return Packet2cf(res);
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, Index stride)
+{
+  to[stride*0] = std::complex<float>(vgetq_lane_f32(from.v, 0), vgetq_lane_f32(from.v, 1));
+  to[stride*1] = std::complex<float>(vgetq_lane_f32(from.v, 2), vgetq_lane_f32(from.v, 3));
+}
 
 template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> *   addr) { EIGEN_ARM_PREFETCH((float *)addr); }
 
 template<> EIGEN_STRONG_INLINE std::complex<float>  pfirst<Packet2cf>(const Packet2cf& a)
 {
@@ -175,11 +207,11 @@
   // Multiply the real a with b
   v1 = vmul_f32(v1, a2);
   // Multiply the imag a with b
   v2 = vmul_f32(v2, a2);
   // Conjugate v2 
-  v2 = vreinterpret_f32_u32(veor_u32(vreinterpret_u32_f32(v2), p2ui_CONJ_XOR));
+  v2 = vreinterpret_f32_u32(veor_u32(vreinterpret_u32_f32(v2), p2ui_CONJ_XOR()));
   // Swap real/imag elements in v2.
   v2 = vrev64_f32(v2);
   // Add v1, v2
   prod = vadd_f32(v1, v2);
 
@@ -233,21 +265,222 @@
   }
 };
 
 template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
 {
-  // TODO optimize it for AltiVec
+  // TODO optimize it for NEON
   Packet2cf res = conj_helper<Packet2cf,Packet2cf,false,true>().pmul(a,b);
   Packet4f s, rev_s;
 
   // this computes the norm
   s = vmulq_f32(b.v, b.v);
   rev_s = vrev64q_f32(s);
 
   return Packet2cf(pdiv(res.v, vaddq_f32(s,rev_s)));
 }
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet2cf,2>& kernel) {
+  Packet4f tmp = vcombine_f32(vget_high_f32(kernel.packet[0].v), vget_high_f32(kernel.packet[1].v));
+  kernel.packet[0].v = vcombine_f32(vget_low_f32(kernel.packet[0].v), vget_low_f32(kernel.packet[1].v));
+  kernel.packet[1].v = tmp;
+}
+
+//---------- double ----------
+#if EIGEN_ARCH_ARM64 && !EIGEN_APPLE_DOUBLE_NEON_BUG
+
+// See bug 1325, clang fails to call vld1q_u64.
+#if EIGEN_COMP_CLANG
+  static uint64x2_t p2ul_CONJ_XOR = {0x0, 0x8000000000000000};
+#else
+  const uint64_t  p2ul_conj_XOR_DATA[] = { 0x0, 0x8000000000000000 };
+  static uint64x2_t p2ul_CONJ_XOR = vld1q_u64( p2ul_conj_XOR_DATA );
+#endif
+
+struct Packet1cd
+{
+  EIGEN_STRONG_INLINE Packet1cd() {}
+  EIGEN_STRONG_INLINE explicit Packet1cd(const Packet2d& a) : v(a) {}
+  Packet2d v;
+};
+
+template<> struct packet_traits<std::complex<double> >  : default_packet_traits
+{
+  typedef Packet1cd type;
+  typedef Packet1cd half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 0,
+    size = 1,
+    HasHalfPacket = 0,
+
+    HasAdd    = 1,
+    HasSub    = 1,
+    HasMul    = 1,
+    HasDiv    = 1,
+    HasNegate = 1,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasSetLinear = 0
+  };
+};
+
+template<> struct unpacket_traits<Packet1cd> { typedef std::complex<double> type; enum {size=1, alignment=Aligned16}; typedef Packet1cd half; };
+
+template<> EIGEN_STRONG_INLINE Packet1cd pload<Packet1cd>(const std::complex<double>* from) { EIGEN_DEBUG_ALIGNED_LOAD return Packet1cd(pload<Packet2d>((const double*)from)); }
+template<> EIGEN_STRONG_INLINE Packet1cd ploadu<Packet1cd>(const std::complex<double>* from) { EIGEN_DEBUG_UNALIGNED_LOAD return Packet1cd(ploadu<Packet2d>((const double*)from)); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd pset1<Packet1cd>(const std::complex<double>&  from)
+{ /* here we really have to use unaligned loads :( */ return ploadu<Packet1cd>(&from); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd padd<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(padd<Packet2d>(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd psub<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(psub<Packet2d>(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd pnegate(const Packet1cd& a) { return Packet1cd(pnegate<Packet2d>(a.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd pconj(const Packet1cd& a) { return Packet1cd(vreinterpretq_f64_u64(veorq_u64(vreinterpretq_u64_f64(a.v), p2ul_CONJ_XOR))); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd pmul<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  Packet2d v1, v2;
+
+  // Get the real values of a 
+  v1 = vdupq_lane_f64(vget_low_f64(a.v), 0);
+  // Get the imag values of a
+  v2 = vdupq_lane_f64(vget_high_f64(a.v), 0);
+  // Multiply the real a with b
+  v1 = vmulq_f64(v1, b.v);
+  // Multiply the imag a with b
+  v2 = vmulq_f64(v2, b.v);
+  // Conjugate v2 
+  v2 = vreinterpretq_f64_u64(veorq_u64(vreinterpretq_u64_f64(v2), p2ul_CONJ_XOR));
+  // Swap real/imag elements in v2.
+  v2 = preverse<Packet2d>(v2);
+  // Add and return the result
+  return Packet1cd(vaddq_f64(v1, v2));
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd pand   <Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  return Packet1cd(vreinterpretq_f64_u64(vandq_u64(vreinterpretq_u64_f64(a.v),vreinterpretq_u64_f64(b.v))));
+}
+template<> EIGEN_STRONG_INLINE Packet1cd por    <Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  return Packet1cd(vreinterpretq_f64_u64(vorrq_u64(vreinterpretq_u64_f64(a.v),vreinterpretq_u64_f64(b.v))));
+}
+template<> EIGEN_STRONG_INLINE Packet1cd pxor   <Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  return Packet1cd(vreinterpretq_f64_u64(veorq_u64(vreinterpretq_u64_f64(a.v),vreinterpretq_u64_f64(b.v))));
+}
+template<> EIGEN_STRONG_INLINE Packet1cd pandnot<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  return Packet1cd(vreinterpretq_f64_u64(vbicq_u64(vreinterpretq_u64_f64(a.v),vreinterpretq_u64_f64(b.v))));
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<double>* from) { return pset1<Packet1cd>(*from); }
+
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
+
+template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> *   addr) { EIGEN_ARM_PREFETCH((double *)addr); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet1cd pgather<std::complex<double>, Packet1cd>(const std::complex<double>* from, Index stride)
+{
+  Packet2d res = pset1<Packet2d>(0.0);
+  res = vsetq_lane_f64(std::real(from[0*stride]), res, 0);
+  res = vsetq_lane_f64(std::imag(from[0*stride]), res, 1);
+  return Packet1cd(res);
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet1cd>(std::complex<double>* to, const Packet1cd& from, Index stride)
+{
+  to[stride*0] = std::complex<double>(vgetq_lane_f64(from.v, 0), vgetq_lane_f64(from.v, 1));
+}
+
+
+template<> EIGEN_STRONG_INLINE std::complex<double>  pfirst<Packet1cd>(const Packet1cd& a)
+{
+  std::complex<double> EIGEN_ALIGN16 res;
+  pstore<std::complex<double> >(&res, a);
+
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd preverse(const Packet1cd& a) { return a; }
+
+template<> EIGEN_STRONG_INLINE std::complex<double> predux<Packet1cd>(const Packet1cd& a) { return pfirst(a); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd preduxp<Packet1cd>(const Packet1cd* vecs) { return vecs[0]; }
+
+template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet1cd>(const Packet1cd& a) { return pfirst(a); }
+
+template<int Offset>
+struct palign_impl<Offset,Packet1cd>
+{
+  static EIGEN_STRONG_INLINE void run(Packet1cd& /*first*/, const Packet1cd& /*second*/)
+  {
+    // FIXME is it sure we never have to align a Packet1cd?
+    // Even though a std::complex<double> has 16 bytes, it is not necessarily aligned on a 16 bytes boundary...
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, false,true>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return internal::pmul(a, pconj(b));
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, true,false>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return internal::pmul(pconj(a), b);
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, true,true>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return pconj(internal::pmul(a, b));
+  }
+};
+
+template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  // TODO optimize it for NEON
+  Packet1cd res = conj_helper<Packet1cd,Packet1cd,false,true>().pmul(a,b);
+  Packet2d s = pmul<Packet2d>(b.v, b.v);
+  Packet2d rev_s = preverse<Packet2d>(s);
+
+  return Packet1cd(pdiv(res.v, padd<Packet2d>(s,rev_s)));
+}
+
+EIGEN_STRONG_INLINE Packet1cd pcplxflip/*<Packet1cd>*/(const Packet1cd& x)
+{
+  return Packet1cd(preverse(Packet2d(x.v)));
+}
+
+EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet1cd,2>& kernel)
+{
+  Packet2d tmp = vcombine_f64(vget_high_f64(kernel.packet[0].v), vget_high_f64(kernel.packet[1].v));
+  kernel.packet[0].v = vcombine_f64(vget_low_f64(kernel.packet[0].v), vget_low_f64(kernel.packet[1].v));
+  kernel.packet[1].v = tmp;
+}
+#endif // EIGEN_ARCH_ARM64
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_COMPLEX_NEON_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/NEON/MathFunctions.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/NEON/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/NEON/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/NEON/MathFunctions.h
@@ -0,0 +1,91 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/* The sin, cos, exp, and log functions of this file come from
+ * Julien Pommier's sse math library: http://gruntthepeon.free.fr/ssemath/
+ */
+
+#ifndef EIGEN_MATH_FUNCTIONS_NEON_H
+#define EIGEN_MATH_FUNCTIONS_NEON_H
+
+namespace Eigen {
+
+namespace internal {
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f pexp<Packet4f>(const Packet4f& _x)
+{
+  Packet4f x = _x;
+  Packet4f tmp, fx;
+
+  _EIGEN_DECLARE_CONST_Packet4f(1 , 1.0f);
+  _EIGEN_DECLARE_CONST_Packet4f(half, 0.5f);
+  _EIGEN_DECLARE_CONST_Packet4i(0x7f, 0x7f);
+  _EIGEN_DECLARE_CONST_Packet4f(exp_hi,  88.3762626647950f);
+  _EIGEN_DECLARE_CONST_Packet4f(exp_lo, -88.3762626647949f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_LOG2EF, 1.44269504088896341f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_C1, 0.693359375f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_C2, -2.12194440e-4f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p0, 1.9875691500E-4f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p1, 1.3981999507E-3f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p2, 8.3334519073E-3f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p3, 4.1665795894E-2f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p4, 1.6666665459E-1f);
+  _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p5, 5.0000001201E-1f);
+
+  x = vminq_f32(x, p4f_exp_hi);
+  x = vmaxq_f32(x, p4f_exp_lo);
+
+  /* express exp(x) as exp(g + n*log(2)) */
+  fx = vmlaq_f32(p4f_half, x, p4f_cephes_LOG2EF);
+
+  /* perform a floorf */
+  tmp = vcvtq_f32_s32(vcvtq_s32_f32(fx));
+
+  /* if greater, substract 1 */
+  Packet4ui mask = vcgtq_f32(tmp, fx);
+  mask = vandq_u32(mask, vreinterpretq_u32_f32(p4f_1));
+
+  fx = vsubq_f32(tmp, vreinterpretq_f32_u32(mask));
+
+  tmp = vmulq_f32(fx, p4f_cephes_exp_C1);
+  Packet4f z = vmulq_f32(fx, p4f_cephes_exp_C2);
+  x = vsubq_f32(x, tmp);
+  x = vsubq_f32(x, z);
+
+  Packet4f y = vmulq_f32(p4f_cephes_exp_p0, x);
+  z = vmulq_f32(x, x);
+  y = vaddq_f32(y, p4f_cephes_exp_p1);
+  y = vmulq_f32(y, x);
+  y = vaddq_f32(y, p4f_cephes_exp_p2);
+  y = vmulq_f32(y, x);
+  y = vaddq_f32(y, p4f_cephes_exp_p3);
+  y = vmulq_f32(y, x);
+  y = vaddq_f32(y, p4f_cephes_exp_p4);
+  y = vmulq_f32(y, x);
+  y = vaddq_f32(y, p4f_cephes_exp_p5);
+
+  y = vmulq_f32(y, z);
+  y = vaddq_f32(y, x);
+  y = vaddq_f32(y, p4f_1);
+
+  /* build 2^n */
+  int32x4_t mm;
+  mm = vcvtq_s32_f32(fx);
+  mm = vaddq_s32(mm, p4i_0x7f);
+  mm = vshlq_n_s32(mm, 23);
+  Packet4f pow2n = vreinterpretq_f32_s32(mm);
+
+  y = vmulq_f32(y, pow2n);
+  return y;
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_MATH_FUNCTIONS_NEON_H

Index: 3rd_party/eigen/Eigen/src/Core/arch/NEON/PacketMath.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/NEON/PacketMath.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/NEON/PacketMath.h
@@ -1,10 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Konstantinos Margaritis <markos@codex.gr>
+// Copyright (C) 2010 Konstantinos Margaritis <markos@freevec.org>
 // Heavily based on Gael's SSE version.
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -18,102 +18,114 @@
 
 #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
 #define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 8
 #endif
 
-// FIXME NEON has 16 quad registers, but since the current register allocator
-// is so bad, it is much better to reduce it to 8
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#endif
+
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
+#endif
+
 #ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
-#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 8
+#if EIGEN_ARCH_ARM64
+#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 32
+#else
+#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 16 
+#endif
 #endif
 
+typedef float32x2_t Packet2f;
 typedef float32x4_t Packet4f;
 typedef int32x4_t   Packet4i;
+typedef int32x2_t   Packet2i;
 typedef uint32x4_t  Packet4ui;
 
 #define _EIGEN_DECLARE_CONST_Packet4f(NAME,X) \
   const Packet4f p4f_##NAME = pset1<Packet4f>(X)
 
 #define _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(NAME,X) \
-  const Packet4f p4f_##NAME = vreinterpretq_f32_u32(pset1<int>(X))
+  const Packet4f p4f_##NAME = vreinterpretq_f32_u32(pset1<int32_t>(X))
 
 #define _EIGEN_DECLARE_CONST_Packet4i(NAME,X) \
   const Packet4i p4i_##NAME = pset1<Packet4i>(X)
 
-#if defined(__llvm__) && !defined(__clang__)
-  //Special treatment for Apple's llvm-gcc, its NEON packet types are unions
-  #define EIGEN_INIT_NEON_PACKET2(X, Y)       {{X, Y}}
-  #define EIGEN_INIT_NEON_PACKET4(X, Y, Z, W) {{X, Y, Z, W}}
-#else
-  //Default initializer for packets
-  #define EIGEN_INIT_NEON_PACKET2(X, Y)       {X, Y}
-  #define EIGEN_INIT_NEON_PACKET4(X, Y, Z, W) {X, Y, Z, W}
-#endif
-
-// arm64 does have the pld instruction. If available, let's trust the __builtin_prefetch built-in function
-// which available on LLVM and GCC (at least)
-#if EIGEN_HAS_BUILTIN(__builtin_prefetch) || defined(__GNUC__)
+#if EIGEN_ARCH_ARM64
+  // __builtin_prefetch tends to do nothing on ARM64 compilers because the
+  // prefetch instructions there are too detailed for __builtin_prefetch to map
+  // meaningfully to them.
+  #define EIGEN_ARM_PREFETCH(ADDR)  __asm__ __volatile__("prfm pldl1keep, [%[addr]]\n" ::[addr] "r"(ADDR) : );
+#elif EIGEN_HAS_BUILTIN(__builtin_prefetch) || EIGEN_COMP_GNUC
   #define EIGEN_ARM_PREFETCH(ADDR) __builtin_prefetch(ADDR);
 #elif defined __pld
   #define EIGEN_ARM_PREFETCH(ADDR) __pld(ADDR)
-#elif !defined(__aarch64__)
-  #define EIGEN_ARM_PREFETCH(ADDR) __asm__ __volatile__ ( "   pld [%[addr]]\n" :: [addr] "r" (ADDR) : "cc" );
+#elif EIGEN_ARCH_ARM32
+  #define EIGEN_ARM_PREFETCH(ADDR) __asm__ __volatile__ ("pld [%[addr]]\n" :: [addr] "r" (ADDR) : );
 #else
   // by default no explicit prefetching
   #define EIGEN_ARM_PREFETCH(ADDR)
 #endif
 
 template<> struct packet_traits<float>  : default_packet_traits
 {
   typedef Packet4f type;
+  typedef Packet4f half; // Packet2f intrinsics not implemented yet
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 1,
     size = 4,
+    HasHalfPacket=0, // Packet2f intrinsics not implemented yet
    
     HasDiv  = 1,
     // FIXME check the Has*
     HasSin  = 0,
     HasCos  = 0,
     HasLog  = 0,
-    HasExp  = 0,
+    HasExp  = 1,
     HasSqrt = 0
   };
 };
-template<> struct packet_traits<int>    : default_packet_traits
+template<> struct packet_traits<int32_t>    : default_packet_traits
 {
   typedef Packet4i type;
+  typedef Packet4i half; // Packet2i intrinsics not implemented yet
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 1,
-    size=4
+    size=4,
+    HasHalfPacket=0 // Packet2i intrinsics not implemented yet
     // FIXME check the Has*
   };
 };
 
-#if EIGEN_GNUC_AT_MOST(4,4) && !defined(__llvm__)
+#if EIGEN_GNUC_AT_MOST(4,4) && !EIGEN_COMP_LLVM
 // workaround gcc 4.2, 4.3 and 4.4 compilatin issue
 EIGEN_STRONG_INLINE float32x4_t vld1q_f32(const float* x) { return ::vld1q_f32((const float32_t*)x); }
 EIGEN_STRONG_INLINE float32x2_t vld1_f32 (const float* x) { return ::vld1_f32 ((const float32_t*)x); }
+EIGEN_STRONG_INLINE float32x2_t vld1_dup_f32 (const float* x) { return ::vld1_dup_f32 ((const float32_t*)x); }
 EIGEN_STRONG_INLINE void        vst1q_f32(float* to, float32x4_t from) { ::vst1q_f32((float32_t*)to,from); }
 EIGEN_STRONG_INLINE void        vst1_f32 (float* to, float32x2_t from) { ::vst1_f32 ((float32_t*)to,from); }
 #endif
 
-template<> struct unpacket_traits<Packet4f> { typedef float  type; enum {size=4}; };
-template<> struct unpacket_traits<Packet4i> { typedef int    type; enum {size=4}; };
+template<> struct unpacket_traits<Packet4f> { typedef float   type; enum {size=4, alignment=Aligned16}; typedef Packet4f half; };
+template<> struct unpacket_traits<Packet4i> { typedef int32_t type; enum {size=4, alignment=Aligned16}; typedef Packet4i half; };
 
 template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float&  from) { return vdupq_n_f32(from); }
-template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int&    from)   { return vdupq_n_s32(from); }
+template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int32_t&    from)   { return vdupq_n_s32(from); }
 
-template<> EIGEN_STRONG_INLINE Packet4f plset<float>(const float& a)
+template<> EIGEN_STRONG_INLINE Packet4f plset<Packet4f>(const float& a)
 {
-  Packet4f countdown = EIGEN_INIT_NEON_PACKET4(0, 1, 2, 3);
+  const float f[] = {0, 1, 2, 3};
+  Packet4f countdown = vld1q_f32(f);
   return vaddq_f32(pset1<Packet4f>(a), countdown);
 }
-template<> EIGEN_STRONG_INLINE Packet4i plset<int>(const int& a)
+template<> EIGEN_STRONG_INLINE Packet4i plset<Packet4i>(const int32_t& a)
 {
-  Packet4i countdown = EIGEN_INIT_NEON_PACKET4(0, 1, 2, 3);
+  const int32_t i[] = {0, 1, 2, 3};
+  Packet4i countdown = vld1q_s32(i);
   return vaddq_s32(pset1<Packet4i>(a), countdown);
 }
 
 template<> EIGEN_STRONG_INLINE Packet4f padd<Packet4f>(const Packet4f& a, const Packet4f& b) { return vaddq_f32(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4i padd<Packet4i>(const Packet4i& a, const Packet4i& b) { return vaddq_s32(a,b); }
@@ -130,10 +142,13 @@
 template<> EIGEN_STRONG_INLINE Packet4f pmul<Packet4f>(const Packet4f& a, const Packet4f& b) { return vmulq_f32(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4i pmul<Packet4i>(const Packet4i& a, const Packet4i& b) { return vmulq_s32(a,b); }
 
 template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b)
 {
+#if EIGEN_ARCH_ARM64
+  return vdivq_f32(a,b);
+#else
   Packet4f inv, restep, div;
 
   // NEON does not offer a divide instruction, we have to do a reciprocal approximation
   // However NEON in contrast to other SIMD engines (AltiVec/SSE), offers
   // a reciprocal estimate AND a reciprocal step -which saves a few instructions
@@ -148,18 +163,55 @@
 
   // Finally, multiply a by 1/b and get the wanted result of the division.
   div = vmulq_f32(a, inv);
 
   return div;
+#endif
 }
+
 template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& /*a*/, const Packet4i& /*b*/)
 { eigen_assert(false && "packet integer division are not supported by NEON");
   return pset1<Packet4i>(0);
 }
 
-// for some weird raisons, it has to be overloaded for packet of integers
-template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return vmlaq_f32(c,a,b); }
+// Clang/ARM wrongly advertises __ARM_FEATURE_FMA even when it's not available,
+// then implements a slow software scalar fallback calling fmaf()!
+// Filed LLVM bug:
+//     https://llvm.org/bugs/show_bug.cgi?id=27216
+#if (defined __ARM_FEATURE_FMA) && !(EIGEN_COMP_CLANG && EIGEN_ARCH_ARM)
+// See bug 936.
+// FMA is available on VFPv4 i.e. when compiling with -mfpu=neon-vfpv4.
+// FMA is a true fused multiply-add i.e. only 1 rounding at the end, no intermediate rounding.
+// MLA is not fused i.e. does 2 roundings.
+// In addition to giving better accuracy, FMA also gives better performance here on a Krait (Nexus 4):
+// MLA: 10 GFlop/s ; FMA: 12 GFlops/s.
+template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return vfmaq_f32(c,a,b); }
+#else
+template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) {
+#if EIGEN_COMP_CLANG && EIGEN_ARCH_ARM
+  // Clang/ARM will replace VMLA by VMUL+VADD at least for some values of -mcpu,
+  // at least -mcpu=cortex-a8 and -mcpu=cortex-a7. Since the former is the default on
+  // -march=armv7-a, that is a very common case.
+  // See e.g. this thread:
+  //     http://lists.llvm.org/pipermail/llvm-dev/2013-December/068806.html
+  // Filed LLVM bug:
+  //     https://llvm.org/bugs/show_bug.cgi?id=27219
+  Packet4f r = c;
+  asm volatile(
+    "vmla.f32 %q[r], %q[a], %q[b]"
+    : [r] "+w" (r)
+    : [a] "w" (a),
+      [b] "w" (b)
+    : );
+  return r;
+#else
+  return vmlaq_f32(c,a,b);
+#endif
+}
+#endif
+
+// No FMA instruction for int, so use MLA unconditionally.
 template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return vmlaq_s32(c,a,b); }
 
 template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b) { return vminq_f32(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const Packet4i& b) { return vminq_s32(a,b); }
 
@@ -189,43 +241,77 @@
 {
   return vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(a),vreinterpretq_u32_f32(b)));
 }
 template<> EIGEN_STRONG_INLINE Packet4i pandnot<Packet4i>(const Packet4i& a, const Packet4i& b) { return vbicq_s32(a,b); }
 
-template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float* from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_f32(from); }
-template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int*   from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_s32(from); }
+template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float*    from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_f32(from); }
+template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int32_t*  from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_s32(from); }
 
-template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from) { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_f32(from); }
-template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int* from)   { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_s32(from); }
+template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float*   from) { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_f32(from); }
+template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int32_t* from) { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_s32(from); }
 
-template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float*   from)
+template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float* from)
 {
   float32x2_t lo, hi;
   lo = vld1_dup_f32(from);
   hi = vld1_dup_f32(from+1);
   return vcombine_f32(lo, hi);
 }
-template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int*     from)
+template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int32_t* from)
 {
   int32x2_t lo, hi;
   lo = vld1_dup_s32(from);
   hi = vld1_dup_s32(from+1);
   return vcombine_s32(lo, hi);
 }
 
-template<> EIGEN_STRONG_INLINE void pstore<float>(float*   to, const Packet4f& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_f32(to, from); }
-template<> EIGEN_STRONG_INLINE void pstore<int>(int*       to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_s32(to, from); }
-
-template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*  to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_f32(to, from); }
-template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*      to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_s32(to, from); }
-
-template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { EIGEN_ARM_PREFETCH(addr); }
-template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*     addr) { EIGEN_ARM_PREFETCH(addr); }
+template<> EIGEN_STRONG_INLINE void pstore<float>  (float*    to, const Packet4f& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_f32(to, from); }
+template<> EIGEN_STRONG_INLINE void pstore<int32_t>(int32_t*  to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_s32(to, from); }
+
+template<> EIGEN_STRONG_INLINE void pstoreu<float>  (float*   to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_f32(to, from); }
+template<> EIGEN_STRONG_INLINE void pstoreu<int32_t>(int32_t* to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_s32(to, from); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, Index stride)
+{
+  Packet4f res = pset1<Packet4f>(0.f);
+  res = vsetq_lane_f32(from[0*stride], res, 0);
+  res = vsetq_lane_f32(from[1*stride], res, 1);
+  res = vsetq_lane_f32(from[2*stride], res, 2);
+  res = vsetq_lane_f32(from[3*stride], res, 3);
+  return res;
+}
+template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int32_t, Packet4i>(const int32_t* from, Index stride)
+{
+  Packet4i res = pset1<Packet4i>(0);
+  res = vsetq_lane_s32(from[0*stride], res, 0);
+  res = vsetq_lane_s32(from[1*stride], res, 1);
+  res = vsetq_lane_s32(from[2*stride], res, 2);
+  res = vsetq_lane_s32(from[3*stride], res, 3);
+  return res;
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, Index stride)
+{
+  to[stride*0] = vgetq_lane_f32(from, 0);
+  to[stride*1] = vgetq_lane_f32(from, 1);
+  to[stride*2] = vgetq_lane_f32(from, 2);
+  to[stride*3] = vgetq_lane_f32(from, 3);
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<int32_t, Packet4i>(int32_t* to, const Packet4i& from, Index stride)
+{
+  to[stride*0] = vgetq_lane_s32(from, 0);
+  to[stride*1] = vgetq_lane_s32(from, 1);
+  to[stride*2] = vgetq_lane_s32(from, 2);
+  to[stride*3] = vgetq_lane_s32(from, 3);
+}
+
+template<> EIGEN_STRONG_INLINE void prefetch<float>  (const float*    addr) { EIGEN_ARM_PREFETCH(addr); }
+template<> EIGEN_STRONG_INLINE void prefetch<int32_t>(const int32_t*  addr) { EIGEN_ARM_PREFETCH(addr); }
 
 // FIXME only store the 2 first elements ?
-template<> EIGEN_STRONG_INLINE float  pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x[4]; vst1q_f32(x, a); return x[0]; }
-template<> EIGEN_STRONG_INLINE int    pfirst<Packet4i>(const Packet4i& a) { int   EIGEN_ALIGN16 x[4]; vst1q_s32(x, a); return x[0]; }
+template<> EIGEN_STRONG_INLINE float   pfirst<Packet4f>(const Packet4f& a) { float   EIGEN_ALIGN16 x[4]; vst1q_f32(x, a); return x[0]; }
+template<> EIGEN_STRONG_INLINE int32_t pfirst<Packet4i>(const Packet4i& a) { int32_t EIGEN_ALIGN16 x[4]; vst1q_s32(x, a); return x[0]; }
 
 template<> EIGEN_STRONG_INLINE Packet4f preverse(const Packet4f& a) {
   float32x2_t a_lo, a_hi;
   Packet4f a_r64;
 
@@ -241,10 +327,11 @@
   a_r64 = vrev64q_s32(a);
   a_lo = vget_low_s32(a_r64);
   a_hi = vget_high_s32(a_r64);
   return vcombine_s32(a_hi, a_lo);
 }
+
 template<> EIGEN_STRONG_INLINE Packet4f pabs(const Packet4f& a) { return vabsq_f32(a); }
 template<> EIGEN_STRONG_INLINE Packet4i pabs(const Packet4i& a) { return vabsq_s32(a); }
 
 template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
 {
@@ -275,11 +362,11 @@
   sum = vaddq_f32(sum1, sum2);
 
   return sum;
 }
 
-template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
+template<> EIGEN_STRONG_INLINE int32_t predux<Packet4i>(const Packet4i& a)
 {
   int32x2_t a_lo, a_hi, sum;
 
   a_lo = vget_low_s32(a);
   a_hi = vget_high_s32(a);
@@ -322,11 +409,11 @@
   // Multiply prod with its swapped value |a2*a4|a1*a3|
   prod = vmul_f32(prod, vrev64_f32(prod));
 
   return vget_lane_f32(prod, 0);
 }
-template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
+template<> EIGEN_STRONG_INLINE int32_t predux_mul<Packet4i>(const Packet4i& a)
 {
   int32x2_t a_lo, a_hi, prod;
 
   // Get a_lo = |a1|a2| and a_hi = |a3|a4|
   a_lo = vget_low_s32(a);
@@ -350,11 +437,11 @@
   min = vpmin_f32(min, min);
 
   return vget_lane_f32(min, 0);
 }
 
-template<> EIGEN_STRONG_INLINE int predux_min<Packet4i>(const Packet4i& a)
+template<> EIGEN_STRONG_INLINE int32_t predux_min<Packet4i>(const Packet4i& a)
 {
   int32x2_t a_lo, a_hi, min;
 
   a_lo = vget_low_s32(a);
   a_hi = vget_high_s32(a);
@@ -375,17 +462,18 @@
   max = vpmax_f32(max, max);
 
   return vget_lane_f32(max, 0);
 }
 
-template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
+template<> EIGEN_STRONG_INLINE int32_t predux_max<Packet4i>(const Packet4i& a)
 {
   int32x2_t a_lo, a_hi, max;
 
   a_lo = vget_low_s32(a);
   a_hi = vget_high_s32(a);
   max = vpmax_s32(a_lo, a_hi);
+  max = vpmax_s32(max, max);
 
   return vget_lane_s32(max, 0);
 }
 
 // this PALIGN_NEON business is to work around a bug in LLVM Clang 3.0 causing incorrect compilation errors,
@@ -407,13 +495,235 @@
 PALIGN_NEON(3,Packet4f,vextq_f32)
 PALIGN_NEON(0,Packet4i,vextq_s32)
 PALIGN_NEON(1,Packet4i,vextq_s32)
 PALIGN_NEON(2,Packet4i,vextq_s32)
 PALIGN_NEON(3,Packet4i,vextq_s32)
-    
+
+#undef PALIGN_NEON
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4f,4>& kernel) {
+  float32x4x2_t tmp1 = vzipq_f32(kernel.packet[0], kernel.packet[1]);
+  float32x4x2_t tmp2 = vzipq_f32(kernel.packet[2], kernel.packet[3]);
+
+  kernel.packet[0] = vcombine_f32(vget_low_f32(tmp1.val[0]), vget_low_f32(tmp2.val[0]));
+  kernel.packet[1] = vcombine_f32(vget_high_f32(tmp1.val[0]), vget_high_f32(tmp2.val[0]));
+  kernel.packet[2] = vcombine_f32(vget_low_f32(tmp1.val[1]), vget_low_f32(tmp2.val[1]));
+  kernel.packet[3] = vcombine_f32(vget_high_f32(tmp1.val[1]), vget_high_f32(tmp2.val[1]));
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4i,4>& kernel) {
+  int32x4x2_t tmp1 = vzipq_s32(kernel.packet[0], kernel.packet[1]);
+  int32x4x2_t tmp2 = vzipq_s32(kernel.packet[2], kernel.packet[3]);
+  kernel.packet[0] = vcombine_s32(vget_low_s32(tmp1.val[0]), vget_low_s32(tmp2.val[0]));
+  kernel.packet[1] = vcombine_s32(vget_high_s32(tmp1.val[0]), vget_high_s32(tmp2.val[0]));
+  kernel.packet[2] = vcombine_s32(vget_low_s32(tmp1.val[1]), vget_low_s32(tmp2.val[1]));
+  kernel.packet[3] = vcombine_s32(vget_high_s32(tmp1.val[1]), vget_high_s32(tmp2.val[1]));
+}
+
+//---------- double ----------
+
+// Clang 3.5 in the iOS toolchain has an ICE triggered by NEON intrisics for double.
+// Confirmed at least with __apple_build_version__ = 6000054.
+#ifdef __apple_build_version__
+// Let's hope that by the time __apple_build_version__ hits the 601* range, the bug will be fixed.
+// https://gist.github.com/yamaya/2924292 suggests that the 3 first digits are only updated with
+// major toolchain updates.
+#define EIGEN_APPLE_DOUBLE_NEON_BUG (__apple_build_version__ < 6010000)
+#else
+#define EIGEN_APPLE_DOUBLE_NEON_BUG 0
+#endif
+
+#if EIGEN_ARCH_ARM64 && !EIGEN_APPLE_DOUBLE_NEON_BUG
+
+// Bug 907: workaround missing declarations of the following two functions in the ADK
+// Defining these functions as templates ensures that if these intrinsics are
+// already defined in arm_neon.h, then our workaround doesn't cause a conflict
+// and has lower priority in overload resolution.
+template <typename T>
+uint64x2_t vreinterpretq_u64_f64(T a)
+{
+  return (uint64x2_t) a;
+}
+
+template <typename T>
+float64x2_t vreinterpretq_f64_u64(T a)
+{
+  return (float64x2_t) a;
+}
+
+typedef float64x2_t Packet2d;
+typedef float64x1_t Packet1d;
+
+template<> struct packet_traits<double>  : default_packet_traits
+{
+  typedef Packet2d type;
+  typedef Packet2d half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 2,
+    HasHalfPacket=0,
+   
+    HasDiv  = 1,
+    // FIXME check the Has*
+    HasSin  = 0,
+    HasCos  = 0,
+    HasLog  = 0,
+    HasExp  = 0,
+    HasSqrt = 0
+  };
+};
+
+template<> struct unpacket_traits<Packet2d> { typedef double  type; enum {size=2, alignment=Aligned16}; typedef Packet2d half; };
+
+template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double&  from) { return vdupq_n_f64(from); }
+
+template<> EIGEN_STRONG_INLINE Packet2d plset<Packet2d>(const double& a)
+{
+  const double countdown_raw[] = {0.0,1.0};
+  const Packet2d countdown = vld1q_f64(countdown_raw);
+  return vaddq_f64(pset1<Packet2d>(a), countdown);
+}
+template<> EIGEN_STRONG_INLINE Packet2d padd<Packet2d>(const Packet2d& a, const Packet2d& b) { return vaddq_f64(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d psub<Packet2d>(const Packet2d& a, const Packet2d& b) { return vsubq_f64(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pnegate(const Packet2d& a) { return vnegq_f64(a); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pconj(const Packet2d& a) { return a; }
+
+template<> EIGEN_STRONG_INLINE Packet2d pmul<Packet2d>(const Packet2d& a, const Packet2d& b) { return vmulq_f64(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return vdivq_f64(a,b); }
+
+#ifdef __ARM_FEATURE_FMA
+// See bug 936. See above comment about FMA for float.
+template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return vfmaq_f64(c,a,b); }
+#else
+template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return vmlaq_f64(c,a,b); }
+#endif
+
+template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) { return vminq_f64(a,b); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b) { return vmaxq_f64(a,b); }
+
+// Logical Operations are not supported for float, so we have to reinterpret casts using NEON intrinsics
+template<> EIGEN_STRONG_INLINE Packet2d pand<Packet2d>(const Packet2d& a, const Packet2d& b)
+{
+  return vreinterpretq_f64_u64(vandq_u64(vreinterpretq_u64_f64(a),vreinterpretq_u64_f64(b)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d por<Packet2d>(const Packet2d& a, const Packet2d& b)
+{
+  return vreinterpretq_f64_u64(vorrq_u64(vreinterpretq_u64_f64(a),vreinterpretq_u64_f64(b)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pxor<Packet2d>(const Packet2d& a, const Packet2d& b)
+{
+  return vreinterpretq_f64_u64(veorq_u64(vreinterpretq_u64_f64(a),vreinterpretq_u64_f64(b)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pandnot<Packet2d>(const Packet2d& a, const Packet2d& b)
+{
+  return vreinterpretq_f64_u64(vbicq_u64(vreinterpretq_u64_f64(a),vreinterpretq_u64_f64(b)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pload<Packet2d>(const double* from) { EIGEN_DEBUG_ALIGNED_LOAD return vld1q_f64(from); }
+
+template<> EIGEN_STRONG_INLINE Packet2d ploadu<Packet2d>(const double* from) { EIGEN_DEBUG_UNALIGNED_LOAD return vld1q_f64(from); }
+
+template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double*   from)
+{
+  return vld1q_dup_f64(from);
+}
+template<> EIGEN_STRONG_INLINE void pstore<double>(double*   to, const Packet2d& from) { EIGEN_DEBUG_ALIGNED_STORE vst1q_f64(to, from); }
+
+template<> EIGEN_STRONG_INLINE void pstoreu<double>(double*  to, const Packet2d& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_f64(to, from); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet2d pgather<double, Packet2d>(const double* from, Index stride)
+{
+  Packet2d res = pset1<Packet2d>(0.0);
+  res = vsetq_lane_f64(from[0*stride], res, 0);
+  res = vsetq_lane_f64(from[1*stride], res, 1);
+  return res;
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to, const Packet2d& from, Index stride)
+{
+  to[stride*0] = vgetq_lane_f64(from, 0);
+  to[stride*1] = vgetq_lane_f64(from, 1);
+}
+template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { EIGEN_ARM_PREFETCH(addr); }
+
+// FIXME only store the 2 first elements ?
+template<> EIGEN_STRONG_INLINE double pfirst<Packet2d>(const Packet2d& a) { return vgetq_lane_f64(a, 0); }
+
+template<> EIGEN_STRONG_INLINE Packet2d preverse(const Packet2d& a) { return vcombine_f64(vget_high_f64(a), vget_low_f64(a)); }
+
+template<> EIGEN_STRONG_INLINE Packet2d pabs(const Packet2d& a) { return vabsq_f64(a); }
+
+#if EIGEN_COMP_CLANG && defined(__apple_build_version__)
+// workaround ICE, see bug 907
+template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a) { return (vget_low_f64(a) + vget_high_f64(a))[0]; }
+#else
+template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a) { return vget_lane_f64(vget_low_f64(a) + vget_high_f64(a), 0); }
+#endif
+
+template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
+{
+  float64x2_t trn1, trn2;
+
+  // NEON zip performs interleaving of the supplied vectors.
+  // We perform two interleaves in a row to acquire the transposed vector
+  trn1 = vzip1q_f64(vecs[0], vecs[1]);
+  trn2 = vzip2q_f64(vecs[0], vecs[1]);
+
+  // Do the addition of the resulting vectors
+  return vaddq_f64(trn1, trn2);
+}
+// Other reduction functions:
+// mul
+#if EIGEN_COMP_CLANG && defined(__apple_build_version__)
+template<> EIGEN_STRONG_INLINE double predux_mul<Packet2d>(const Packet2d& a) { return (vget_low_f64(a) * vget_high_f64(a))[0]; }
+#else
+template<> EIGEN_STRONG_INLINE double predux_mul<Packet2d>(const Packet2d& a) { return vget_lane_f64(vget_low_f64(a) * vget_high_f64(a), 0); }
+#endif
+
+// min
+template<> EIGEN_STRONG_INLINE double predux_min<Packet2d>(const Packet2d& a) { return vgetq_lane_f64(vpminq_f64(a, a), 0); }
+
+// max
+template<> EIGEN_STRONG_INLINE double predux_max<Packet2d>(const Packet2d& a) { return vgetq_lane_f64(vpmaxq_f64(a, a), 0); }
+
+// this PALIGN_NEON business is to work around a bug in LLVM Clang 3.0 causing incorrect compilation errors,
+// see bug 347 and this LLVM bug: http://llvm.org/bugs/show_bug.cgi?id=11074
+#define PALIGN_NEON(Offset,Type,Command) \
+template<>\
+struct palign_impl<Offset,Type>\
+{\
+    EIGEN_STRONG_INLINE static void run(Type& first, const Type& second)\
+    {\
+        if (Offset!=0)\
+            first = Command(first, second, Offset);\
+    }\
+};\
+
+PALIGN_NEON(0,Packet2d,vextq_f64)
+PALIGN_NEON(1,Packet2d,vextq_f64)
 #undef PALIGN_NEON
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet2d,2>& kernel) {
+  float64x2_t trn1 = vzip1q_f64(kernel.packet[0], kernel.packet[1]);
+  float64x2_t trn2 = vzip2q_f64(kernel.packet[0], kernel.packet[1]);
+
+  kernel.packet[0] = trn1;
+  kernel.packet[1] = trn2;
+}
+#endif // EIGEN_ARCH_ARM64 
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_PACKET_MATH_NEON_H

DELETED 3rd_party/eigen/Eigen/src/Core/arch/SSE/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Core/arch/SSE/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/SSE/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Core/arch/SSE/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Core_arch_SSE_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Core_arch_SSE_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/SSE COMPONENT Devel
-)

Index: 3rd_party/eigen/Eigen/src/Core/arch/SSE/Complex.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/SSE/Complex.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/SSE/Complex.h
@@ -20,17 +20,22 @@
   EIGEN_STRONG_INLINE Packet2cf() {}
   EIGEN_STRONG_INLINE explicit Packet2cf(const __m128& a) : v(a) {}
   __m128  v;
 };
 
+// Use the packet_traits defined in AVX/PacketMath.h instead if we're going
+// to leverage AVX instructions.
+#ifndef EIGEN_VECTORIZE_AVX
 template<> struct packet_traits<std::complex<float> >  : default_packet_traits
 {
   typedef Packet2cf type;
+  typedef Packet2cf half;
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 1,
     size = 2,
+    HasHalfPacket = 0,
 
     HasAdd    = 1,
     HasSub    = 1,
     HasMul    = 1,
     HasDiv    = 1,
@@ -37,15 +42,17 @@
     HasNegate = 1,
     HasAbs    = 0,
     HasAbs2   = 0,
     HasMin    = 0,
     HasMax    = 0,
-    HasSetLinear = 0
+    HasSetLinear = 0,
+    HasBlend = 1
   };
 };
+#endif
 
-template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2}; };
+template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2, alignment=Aligned16}; typedef Packet2cf half; };
 
 template<> EIGEN_STRONG_INLINE Packet2cf padd<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(_mm_add_ps(a.v,b.v)); }
 template<> EIGEN_STRONG_INLINE Packet2cf psub<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(_mm_sub_ps(a.v,b.v)); }
 template<> EIGEN_STRONG_INLINE Packet2cf pnegate(const Packet2cf& a)
 {
@@ -58,11 +65,10 @@
   return Packet2cf(_mm_xor_ps(a.v,mask));
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cf pmul<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
 {
-  // TODO optimize it for SSE3 and 4
   #ifdef EIGEN_VECTORIZE_SSE3
   return Packet2cf(_mm_addsub_ps(_mm_mul_ps(_mm_moveldup_ps(a.v), b.v),
                                  _mm_mul_ps(_mm_movehdup_ps(a.v),
                                             vec4f_swizzle1(b.v, 1, 0, 3, 2))));
 //   return Packet2cf(_mm_addsub_ps(_mm_mul_ps(vec4f_swizzle1(a.v, 0, 0, 2, 2), b.v),
@@ -102,12 +108,27 @@
   return Packet2cf(_mm_movelh_ps(res.v,res.v));
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<float>* from) { return pset1<Packet2cf>(*from); }
 
-template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore(&numext::real_ref(*to), from.v); }
-template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(&numext::real_ref(*to), from.v); }
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore(&numext::real_ref(*to), Packet4f(from.v)); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(&numext::real_ref(*to), Packet4f(from.v)); }
+
+
+template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, Index stride)
+{
+  return Packet2cf(_mm_set_ps(std::imag(from[1*stride]), std::real(from[1*stride]),
+                              std::imag(from[0*stride]), std::real(from[0*stride])));
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, Index stride)
+{
+  to[stride*0] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(from.v, from.v, 0)),
+                                     _mm_cvtss_f32(_mm_shuffle_ps(from.v, from.v, 1)));
+  to[stride*1] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(from.v, from.v, 2)),
+                                     _mm_cvtss_f32(_mm_shuffle_ps(from.v, from.v, 3)));
+}
 
 template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> *   addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
 
 template<> EIGEN_STRONG_INLINE std::complex<float>  pfirst<Packet2cf>(const Packet2cf& a)
 {
@@ -122,11 +143,11 @@
   _mm_storel_pi((__m64*)&res, a.v);
   return res;
   #endif
 }
 
-template<> EIGEN_STRONG_INLINE Packet2cf preverse(const Packet2cf& a) { return Packet2cf(_mm_castpd_ps(preverse(_mm_castps_pd(a.v)))); }
+template<> EIGEN_STRONG_INLINE Packet2cf preverse(const Packet2cf& a) { return Packet2cf(_mm_castpd_ps(preverse(Packet2d(_mm_castps_pd(a.v))))); }
 
 template<> EIGEN_STRONG_INLINE std::complex<float> predux<Packet2cf>(const Packet2cf& a)
 {
   return pfirst(Packet2cf(_mm_add_ps(a.v, _mm_movehl_ps(a.v,a.v))));
 }
@@ -212,20 +233,20 @@
 {
   EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet4f& x, const Packet2cf& y, const Packet2cf& c) const
   { return padd(c, pmul(x,y)); }
 
   EIGEN_STRONG_INLINE Packet2cf pmul(const Packet4f& x, const Packet2cf& y) const
-  { return Packet2cf(Eigen::internal::pmul(x, y.v)); }
+  { return Packet2cf(Eigen::internal::pmul<Packet4f>(x, y.v)); }
 };
 
 template<> struct conj_helper<Packet2cf, Packet4f, false,false>
 {
   EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet4f& y, const Packet2cf& c) const
   { return padd(c, pmul(x,y)); }
 
   EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& x, const Packet4f& y) const
-  { return Packet2cf(Eigen::internal::pmul(x.v, y)); }
+  { return Packet2cf(Eigen::internal::pmul<Packet4f>(x.v, y)); }
 };
 
 template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
 {
   // TODO optimize it for SSE3 and 4
@@ -232,11 +253,11 @@
   Packet2cf res = conj_helper<Packet2cf,Packet2cf,false,true>().pmul(a,b);
   __m128 s = _mm_mul_ps(b.v,b.v);
   return Packet2cf(_mm_div_ps(res.v,_mm_add_ps(s,_mm_castsi128_ps(_mm_shuffle_epi32(_mm_castps_si128(s), 0xb1)))));
 }
 
-EIGEN_STRONG_INLINE Packet2cf pcplxflip/*<Packet2cf>*/(const Packet2cf& x)
+EIGEN_STRONG_INLINE Packet2cf pcplxflip/* <Packet2cf> */(const Packet2cf& x)
 {
   return Packet2cf(vec4f_swizzle1(x.v, 1, 0, 3, 2));
 }
 
 
@@ -246,17 +267,22 @@
   EIGEN_STRONG_INLINE Packet1cd() {}
   EIGEN_STRONG_INLINE explicit Packet1cd(const __m128d& a) : v(a) {}
   __m128d  v;
 };
 
+// Use the packet_traits defined in AVX/PacketMath.h instead if we're going
+// to leverage AVX instructions.
+#ifndef EIGEN_VECTORIZE_AVX
 template<> struct packet_traits<std::complex<double> >  : default_packet_traits
 {
   typedef Packet1cd type;
+  typedef Packet1cd half;
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 0,
     size = 1,
+    HasHalfPacket = 0,
 
     HasAdd    = 1,
     HasSub    = 1,
     HasMul    = 1,
     HasDiv    = 1,
@@ -266,27 +292,27 @@
     HasMin    = 0,
     HasMax    = 0,
     HasSetLinear = 0
   };
 };
+#endif
 
-template<> struct unpacket_traits<Packet1cd> { typedef std::complex<double> type; enum {size=1}; };
+template<> struct unpacket_traits<Packet1cd> { typedef std::complex<double> type; enum {size=1, alignment=Aligned16}; typedef Packet1cd half; };
 
 template<> EIGEN_STRONG_INLINE Packet1cd padd<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(_mm_add_pd(a.v,b.v)); }
 template<> EIGEN_STRONG_INLINE Packet1cd psub<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(_mm_sub_pd(a.v,b.v)); }
-template<> EIGEN_STRONG_INLINE Packet1cd pnegate(const Packet1cd& a) { return Packet1cd(pnegate(a.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd pnegate(const Packet1cd& a) { return Packet1cd(pnegate(Packet2d(a.v))); }
 template<> EIGEN_STRONG_INLINE Packet1cd pconj(const Packet1cd& a)
 {
   const __m128d mask = _mm_castsi128_pd(_mm_set_epi32(0x80000000,0x0,0x0,0x0));
   return Packet1cd(_mm_xor_pd(a.v,mask));
 }
 
 template<> EIGEN_STRONG_INLINE Packet1cd pmul<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
 {
-  // TODO optimize it for SSE3 and 4
   #ifdef EIGEN_VECTORIZE_SSE3
-  return Packet1cd(_mm_addsub_pd(_mm_mul_pd(vec2d_swizzle1(a.v, 0, 0), b.v),
+  return Packet1cd(_mm_addsub_pd(_mm_mul_pd(_mm_movedup_pd(a.v), b.v),
                                  _mm_mul_pd(vec2d_swizzle1(a.v, 1, 1),
                                             vec2d_swizzle1(b.v, 1, 0))));
   #else
   const __m128d mask = _mm_castsi128_pd(_mm_set_epi32(0x0,0x0,0x80000000,0x0));
   return Packet1cd(_mm_add_pd(_mm_mul_pd(vec2d_swizzle1(a.v, 0, 0), b.v),
@@ -309,12 +335,12 @@
 { /* here we really have to use unaligned loads :( */ return ploadu<Packet1cd>(&from); }
 
 template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<double>* from) { return pset1<Packet1cd>(*from); }
 
 // FIXME force unaligned store, this is a temporary fix
-template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
-template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, Packet2d(from.v)); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, Packet2d(from.v)); }
 
 template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> *   addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
 
 template<> EIGEN_STRONG_INLINE std::complex<double>  pfirst<Packet1cd>(const Packet1cd& a)
 {
@@ -408,20 +434,20 @@
 {
   EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet2d& x, const Packet1cd& y, const Packet1cd& c) const
   { return padd(c, pmul(x,y)); }
 
   EIGEN_STRONG_INLINE Packet1cd pmul(const Packet2d& x, const Packet1cd& y) const
-  { return Packet1cd(Eigen::internal::pmul(x, y.v)); }
+  { return Packet1cd(Eigen::internal::pmul<Packet2d>(x, y.v)); }
 };
 
 template<> struct conj_helper<Packet1cd, Packet2d, false,false>
 {
   EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet2d& y, const Packet1cd& c) const
   { return padd(c, pmul(x,y)); }
 
   EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& x, const Packet2d& y) const
-  { return Packet1cd(Eigen::internal::pmul(x.v, y)); }
+  { return Packet1cd(Eigen::internal::pmul<Packet2d>(x.v, y)); }
 };
 
 template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
 {
   // TODO optimize it for SSE3 and 4
@@ -428,15 +454,50 @@
   Packet1cd res = conj_helper<Packet1cd,Packet1cd,false,true>().pmul(a,b);
   __m128d s = _mm_mul_pd(b.v,b.v);
   return Packet1cd(_mm_div_pd(res.v, _mm_add_pd(s,_mm_shuffle_pd(s, s, 0x1))));
 }
 
-EIGEN_STRONG_INLINE Packet1cd pcplxflip/*<Packet1cd>*/(const Packet1cd& x)
+EIGEN_STRONG_INLINE Packet1cd pcplxflip/* <Packet1cd> */(const Packet1cd& x)
+{
+  return Packet1cd(preverse(Packet2d(x.v)));
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet2cf,2>& kernel) {
+  __m128d w1 = _mm_castps_pd(kernel.packet[0].v);
+  __m128d w2 = _mm_castps_pd(kernel.packet[1].v);
+
+  __m128 tmp = _mm_castpd_ps(_mm_unpackhi_pd(w1, w2));
+  kernel.packet[0].v = _mm_castpd_ps(_mm_unpacklo_pd(w1, w2));
+  kernel.packet[1].v = tmp;
+}
+
+template<>  EIGEN_STRONG_INLINE Packet2cf pblend(const Selector<2>& ifPacket, const Packet2cf& thenPacket, const Packet2cf& elsePacket) {
+  __m128d result = pblend<Packet2d>(ifPacket, _mm_castps_pd(thenPacket.v), _mm_castps_pd(elsePacket.v));
+  return Packet2cf(_mm_castpd_ps(result));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cf pinsertfirst(const Packet2cf& a, std::complex<float> b)
+{
+  return Packet2cf(_mm_loadl_pi(a.v, reinterpret_cast<const __m64*>(&b)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd pinsertfirst(const Packet1cd&, std::complex<double> b)
+{
+  return pset1<Packet1cd>(b);
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cf pinsertlast(const Packet2cf& a, std::complex<float> b)
+{
+  return Packet2cf(_mm_loadh_pi(a.v, reinterpret_cast<const __m64*>(&b)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd pinsertlast(const Packet1cd&, std::complex<double> b)
 {
-  return Packet1cd(preverse(x.v));
+  return pset1<Packet1cd>(b);
 }
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_COMPLEX_SSE_H

Index: 3rd_party/eigen/Eigen/src/Core/arch/SSE/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/SSE/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/SSE/MathFunctions.h
@@ -30,11 +30,11 @@
   _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(inv_mant_mask, ~0x7f800000);
 
   /* the smallest non denormalized float number */
   _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(min_norm_pos,  0x00800000);
   _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(minus_inf,     0xff800000);//-1.f/0.f);
-  
+
   /* natural logarithm computed for 4 simultaneous float
     return NaN for x <= 0
   */
   _EIGEN_DECLARE_CONST_Packet4f(cephes_SQRTHF, 0.707106781186547524f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_log_p0, 7.0376836292E-2f);
@@ -61,22 +61,22 @@
   /* keep only the fractional part */
   x = _mm_and_ps(x, p4f_inv_mant_mask);
   x = _mm_or_ps(x, p4f_half);
 
   emm0 = _mm_sub_epi32(emm0, p4i_0x7f);
-  Packet4f e = padd(_mm_cvtepi32_ps(emm0), p4f_1);
+  Packet4f e = padd(Packet4f(_mm_cvtepi32_ps(emm0)), p4f_1);
 
   /* part2:
      if( x < SQRTHF ) {
        e -= 1;
        x = x + x - 1.0;
      } else { x = x - 1.0; }
   */
   Packet4f mask = _mm_cmplt_ps(x, p4f_cephes_SQRTHF);
-  Packet4f tmp = _mm_and_ps(x, mask);
+  Packet4f tmp = pand(x, mask);
   x = psub(x, p4f_1);
-  e = psub(e, _mm_and_ps(p4f_1, mask));
+  e = psub(e, pand(p4f_1, mask));
   x = padd(x, tmp);
 
   Packet4f x2 = pmul(x,x);
   Packet4f x3 = pmul(x2,x);
 
@@ -124,11 +124,11 @@
   _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p2, 8.3334519073E-3f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p3, 4.1665795894E-2f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p4, 1.6666665459E-1f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p5, 5.0000001201E-1f);
 
-  Packet4f tmp = _mm_setzero_ps(), fx;
+  Packet4f tmp, fx;
   Packet4i emm0;
 
   // clamp x
   x = pmax(pmin(x, p4f_exp_hi), p4f_exp_lo);
 
@@ -193,11 +193,11 @@
 
   _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C1, 0.693145751953125);
   _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
   static const __m128i p4i_1023_0 = _mm_setr_epi32(1023, 1023, 0, 0);
 
-  Packet2d tmp = _mm_setzero_pd(), fx;
+  Packet2d tmp, fx;
   Packet4i emm0;
 
   // clamp x
   x = pmax(pmin(x, p2d_exp_hi), p2d_exp_lo);
   /* express exp(x) as exp(g + n*log(2)) */
@@ -277,11 +277,11 @@
   _EIGEN_DECLARE_CONST_Packet4f(coscof_p0,  2.443315711809948E-005f);
   _EIGEN_DECLARE_CONST_Packet4f(coscof_p1, -1.388731625493765E-003f);
   _EIGEN_DECLARE_CONST_Packet4f(coscof_p2,  4.166664568298827E-002f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_FOPI, 1.27323954473516f); // 4 / M_PI
 
-  Packet4f xmm1, xmm2 = _mm_setzero_ps(), xmm3, sign_bit, y;
+  Packet4f xmm1, xmm2, xmm3, sign_bit, y;
 
   Packet4i emm0, emm2;
   sign_bit = x;
   /* take the absolute value */
   x = pabs(x);
@@ -376,11 +376,11 @@
   _EIGEN_DECLARE_CONST_Packet4f(coscof_p0,  2.443315711809948E-005f);
   _EIGEN_DECLARE_CONST_Packet4f(coscof_p1, -1.388731625493765E-003f);
   _EIGEN_DECLARE_CONST_Packet4f(coscof_p2,  4.166664568298827E-002f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_FOPI, 1.27323954473516f); // 4 / M_PI
 
-  Packet4f xmm1, xmm2 = _mm_setzero_ps(), xmm3, y;
+  Packet4f xmm1, xmm2, xmm3, y;
   Packet4i emm0, emm2;
 
   x = pabs(x);
 
   /* scale by 4/Pi */
@@ -442,34 +442,121 @@
   return _mm_xor_ps(y, sign_bit);
 }
 
 #if EIGEN_FAST_MATH
 
-// This is based on Quake3's fast inverse square root.
+// Functions for sqrt.
+// The EIGEN_FAST_MATH version uses the _mm_rsqrt_ps approximation and one step
+// of Newton's method, at a cost of 1-2 bits of precision as opposed to the
+// exact solution. It does not handle +inf, or denormalized numbers correctly.
+// The main advantage of this approach is not just speed, but also the fact that
+// it can be inlined and pipelined with other computations, further reducing its
+// effective latency. This is similar to Quake3's fast inverse square root.
 // For detail see here: http://www.beyond3d.com/content/articles/8/
-// It lacks 1 (or 2 bits in some rare cases) of precision, and does not handle negative, +inf, or denormalized numbers correctly.
 template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
 Packet4f psqrt<Packet4f>(const Packet4f& _x)
 {
   Packet4f half = pmul(_x, pset1<Packet4f>(.5f));
-
-  /* select only the inverse sqrt of non-zero inputs */
-  Packet4f non_zero_mask = _mm_cmpge_ps(_x, pset1<Packet4f>((std::numeric_limits<float>::min)()));
-  Packet4f x = _mm_and_ps(non_zero_mask, _mm_rsqrt_ps(_x));
+  Packet4f denormal_mask = _mm_and_ps(
+      _mm_cmpge_ps(_x, _mm_setzero_ps()),
+      _mm_cmplt_ps(_x, pset1<Packet4f>((std::numeric_limits<float>::min)())));
 
+  // Compute approximate reciprocal sqrt.
+  Packet4f x = _mm_rsqrt_ps(_x);
+  // Do a single step of Newton's iteration.
   x = pmul(x, psub(pset1<Packet4f>(1.5f), pmul(half, pmul(x,x))));
-  return pmul(_x,x);
+  // Flush results for denormals to zero.
+  return _mm_andnot_ps(denormal_mask, pmul(_x,x));
+}
+
+#else
+
+template<>EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f psqrt<Packet4f>(const Packet4f& x) { return _mm_sqrt_ps(x); }
+
+#endif
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d psqrt<Packet2d>(const Packet2d& x) { return _mm_sqrt_pd(x); }
+
+#if EIGEN_FAST_MATH
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f prsqrt<Packet4f>(const Packet4f& _x) {
+  _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(inf, 0x7f800000);
+  _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(nan, 0x7fc00000);
+  _EIGEN_DECLARE_CONST_Packet4f(one_point_five, 1.5f);
+  _EIGEN_DECLARE_CONST_Packet4f(minus_half, -0.5f);
+  _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(flt_min, 0x00800000);
+
+  Packet4f neg_half = pmul(_x, p4f_minus_half);
+
+  // select only the inverse sqrt of positive normal inputs (denormals are
+  // flushed to zero and cause infs as well).
+  Packet4f le_zero_mask = _mm_cmple_ps(_x, p4f_flt_min);
+  Packet4f x = _mm_andnot_ps(le_zero_mask, _mm_rsqrt_ps(_x));
+
+  // Fill in NaNs and Infs for the negative/zero entries.
+  Packet4f neg_mask = _mm_cmplt_ps(_x, _mm_setzero_ps());
+  Packet4f zero_mask = _mm_andnot_ps(neg_mask, le_zero_mask);
+  Packet4f infs_and_nans = _mm_or_ps(_mm_and_ps(neg_mask, p4f_nan),
+                                     _mm_and_ps(zero_mask, p4f_inf));
+
+  // Do a single step of Newton's iteration.
+  x = pmul(x, pmadd(neg_half, pmul(x, x), p4f_one_point_five));
+
+  // Insert NaNs and Infs in all the right places.
+  return _mm_or_ps(x, infs_and_nans);
 }
 
 #else
 
-template<> EIGEN_STRONG_INLINE Packet4f psqrt<Packet4f>(const Packet4f& x) { return _mm_sqrt_ps(x); }
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f prsqrt<Packet4f>(const Packet4f& x) {
+  // Unfortunately we can't use the much faster mm_rqsrt_ps since it only provides an approximation.
+  return _mm_div_ps(pset1<Packet4f>(1.0f), _mm_sqrt_ps(x));
+}
 
 #endif
 
-template<> EIGEN_STRONG_INLINE Packet2d psqrt<Packet2d>(const Packet2d& x) { return _mm_sqrt_pd(x); }
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d prsqrt<Packet2d>(const Packet2d& x) {
+  // Unfortunately we can't use the much faster mm_rqsrt_pd since it only provides an approximation.
+  return _mm_div_pd(pset1<Packet2d>(1.0), _mm_sqrt_pd(x));
+}
+
+// Hyperbolic Tangent function.
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet4f
+ptanh<Packet4f>(const Packet4f& x) {
+  return internal::generic_fast_tanh_float(x);
+}
 
 } // end namespace internal
 
+namespace numext {
+
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float sqrt(const float &x)
+{
+  return internal::pfirst(internal::Packet4f(_mm_sqrt_ss(_mm_set_ss(x))));
+}
+
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double sqrt(const double &x)
+{
+#if EIGEN_COMP_GNUC_STRICT
+  // This works around a GCC bug generating poor code for _mm_sqrt_pd
+  // See https://bitbucket.org/eigen/eigen/commits/14f468dba4d350d7c19c9b93072e19f7b3df563b
+  return internal::pfirst(internal::Packet2d(__builtin_ia32_sqrtsd(_mm_set_sd(x))));
+#else
+  return internal::pfirst(internal::Packet2d(_mm_sqrt_pd(_mm_set_sd(x))));
+#endif
+}
+
+} // end namespace numex
+
 } // end namespace Eigen
 
 #endif // EIGEN_MATH_FUNCTIONS_SSE_H

Index: 3rd_party/eigen/Eigen/src/Core/arch/SSE/PacketMath.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/SSE/PacketMath.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/SSE/PacketMath.h
@@ -20,13 +20,44 @@
 
 #ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
 #define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS (2*sizeof(void*))
 #endif
 
+#ifdef __FMA__
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_MADD 1
+#endif
+#endif
+
+#if (defined EIGEN_VECTORIZE_AVX) && (EIGEN_COMP_GNUC_STRICT || EIGEN_COMP_MINGW) && (__GXX_ABI_VERSION < 1004)
+// With GCC's default ABI version, a __m128 or __m256 are the same types and therefore we cannot
+// have overloads for both types without linking error.
+// One solution is to increase ABI version using -fabi-version=4 (or greater).
+// Otherwise, we workaround this inconvenience by wrapping 128bit types into the following helper
+// structure:
+template<typename T>
+struct eigen_packet_wrapper
+{
+  EIGEN_ALWAYS_INLINE operator T&() { return m_val; }
+  EIGEN_ALWAYS_INLINE operator const T&() const { return m_val; }
+  EIGEN_ALWAYS_INLINE eigen_packet_wrapper() {}
+  EIGEN_ALWAYS_INLINE eigen_packet_wrapper(const T &v) : m_val(v) {}
+  EIGEN_ALWAYS_INLINE eigen_packet_wrapper& operator=(const T &v) {
+    m_val = v;
+    return *this;
+  }
+  
+  T m_val;
+};
+typedef eigen_packet_wrapper<__m128>  Packet4f;
+typedef eigen_packet_wrapper<__m128i> Packet4i;
+typedef eigen_packet_wrapper<__m128d> Packet2d;
+#else
 typedef __m128  Packet4f;
 typedef __m128i Packet4i;
 typedef __m128d Packet2d;
+#endif
 
 template<> struct is_arithmetic<__m128>  { enum { value = true }; };
 template<> struct is_arithmetic<__m128i> { enum { value = true }; };
 template<> struct is_arithmetic<__m128d> { enum { value = true }; };
 
@@ -56,70 +87,115 @@
 
 #define _EIGEN_DECLARE_CONST_Packet4i(NAME,X) \
   const Packet4i p4i_##NAME = pset1<Packet4i>(X)
 
 
+// Use the packet_traits defined in AVX/PacketMath.h instead if we're going
+// to leverage AVX instructions.
+#ifndef EIGEN_VECTORIZE_AVX
 template<> struct packet_traits<float>  : default_packet_traits
 {
   typedef Packet4f type;
+  typedef Packet4f half;
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 1,
     size=4,
+    HasHalfPacket = 0,
 
     HasDiv  = 1,
     HasSin  = EIGEN_FAST_MATH,
     HasCos  = EIGEN_FAST_MATH,
     HasLog  = 1,
     HasExp  = 1,
-    HasSqrt = 1
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasTanh  = EIGEN_FAST_MATH,
+    HasBlend = 1
+
+#ifdef EIGEN_VECTORIZE_SSE4_1
+    ,
+    HasRound = 1,
+    HasFloor = 1,
+    HasCeil = 1
+#endif
   };
 };
 template<> struct packet_traits<double> : default_packet_traits
 {
   typedef Packet2d type;
+  typedef Packet2d half;
   enum {
     Vectorizable = 1,
     AlignedOnScalar = 1,
     size=2,
+    HasHalfPacket = 0,
 
     HasDiv  = 1,
     HasExp  = 1,
-    HasSqrt = 1
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasBlend = 1
+
+#ifdef EIGEN_VECTORIZE_SSE4_1
+    ,
+    HasRound = 1,
+    HasFloor = 1,
+    HasCeil = 1
+#endif
   };
 };
+#endif
 template<> struct packet_traits<int>    : default_packet_traits
 {
   typedef Packet4i type;
+  typedef Packet4i half;
   enum {
-    // FIXME check the Has*
     Vectorizable = 1,
     AlignedOnScalar = 1,
-    size=4
+    size=4,
+
+    HasBlend = 1
   };
 };
 
-template<> struct unpacket_traits<Packet4f> { typedef float  type; enum {size=4}; };
-template<> struct unpacket_traits<Packet2d> { typedef double type; enum {size=2}; };
-template<> struct unpacket_traits<Packet4i> { typedef int    type; enum {size=4}; };
+template<> struct unpacket_traits<Packet4f> { typedef float  type; enum {size=4, alignment=Aligned16}; typedef Packet4f half; };
+template<> struct unpacket_traits<Packet2d> { typedef double type; enum {size=2, alignment=Aligned16}; typedef Packet2d half; };
+template<> struct unpacket_traits<Packet4i> { typedef int    type; enum {size=4, alignment=Aligned16}; typedef Packet4i half; };
+
+#ifndef EIGEN_VECTORIZE_AVX
+template<> struct scalar_div_cost<float,true> { enum { value = 7 }; };
+template<> struct scalar_div_cost<double,true> { enum { value = 8 }; };
+#endif
 
-#if defined(_MSC_VER) && (_MSC_VER==1500)
+#if EIGEN_COMP_MSVC==1500
 // Workaround MSVC 9 internal compiler error.
 // TODO: It has been detected with win64 builds (amd64), so let's check whether it also happens in 32bits+SSE mode
 // TODO: let's check whether there does not exist a better fix, like adding a pset0() function. (it crashed on pset1(0)).
 template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float&  from) { return _mm_set_ps(from,from,from,from); }
 template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double& from) { return _mm_set_pd(from,from); }
 template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int&    from) { return _mm_set_epi32(from,from,from,from); }
 #else
-template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float&  from) { return _mm_set1_ps(from); }
+template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float&  from) { return _mm_set_ps1(from); }
 template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double& from) { return _mm_set1_pd(from); }
 template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int&    from) { return _mm_set1_epi32(from); }
 #endif
 
-template<> EIGEN_STRONG_INLINE Packet4f plset<float>(const float& a) { return _mm_add_ps(pset1<Packet4f>(a), _mm_set_ps(3,2,1,0)); }
-template<> EIGEN_STRONG_INLINE Packet2d plset<double>(const double& a) { return _mm_add_pd(pset1<Packet2d>(a),_mm_set_pd(1,0)); }
-template<> EIGEN_STRONG_INLINE Packet4i plset<int>(const int& a) { return _mm_add_epi32(pset1<Packet4i>(a),_mm_set_epi32(3,2,1,0)); }
+// GCC generates a shufps instruction for _mm_set1_ps/_mm_load1_ps instead of the more efficient pshufd instruction.
+// However, using inrinsics for pset1 makes gcc to generate crappy code in some cases (see bug 203)
+// Using inline assembly is also not an option because then gcc fails to reorder properly the instructions.
+// Therefore, we introduced the pload1 functions to be used in product kernels for which bug 203 does not apply.
+// Also note that with AVX, we want it to generate a vbroadcastss.
+#if EIGEN_COMP_GNUC_STRICT && (!defined __AVX__)
+template<> EIGEN_STRONG_INLINE Packet4f pload1<Packet4f>(const float *from) {
+  return vec4f_swizzle1(_mm_load_ss(from),0,0,0,0);
+}
+#endif
+  
+template<> EIGEN_STRONG_INLINE Packet4f plset<Packet4f>(const float& a) { return _mm_add_ps(pset1<Packet4f>(a), _mm_set_ps(3,2,1,0)); }
+template<> EIGEN_STRONG_INLINE Packet2d plset<Packet2d>(const double& a) { return _mm_add_pd(pset1<Packet2d>(a),_mm_set_pd(1,0)); }
+template<> EIGEN_STRONG_INLINE Packet4i plset<Packet4i>(const int& a) { return _mm_add_epi32(pset1<Packet4i>(a),_mm_set_epi32(3,2,1,0)); }
 
 template<> EIGEN_STRONG_INLINE Packet4f padd<Packet4f>(const Packet4f& a, const Packet4f& b) { return _mm_add_ps(a,b); }
 template<> EIGEN_STRONG_INLINE Packet2d padd<Packet2d>(const Packet2d& a, const Packet2d& b) { return _mm_add_pd(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4i padd<Packet4i>(const Packet4i& a, const Packet4i& b) { return _mm_add_epi32(a,b); }
 
@@ -137,11 +213,11 @@
   const Packet2d mask = _mm_castsi128_pd(_mm_setr_epi32(0x0,0x80000000,0x0,0x80000000));
   return _mm_xor_pd(a,mask);
 }
 template<> EIGEN_STRONG_INLINE Packet4i pnegate(const Packet4i& a)
 {
-  return psub(_mm_setr_epi32(0,0,0,0), a);
+  return psub(Packet4i(_mm_setr_epi32(0,0,0,0)), a);
 }
 
 template<> EIGEN_STRONG_INLINE Packet4f pconj(const Packet4f& a) { return a; }
 template<> EIGEN_STRONG_INLINE Packet2d pconj(const Packet2d& a) { return a; }
 template<> EIGEN_STRONG_INLINE Packet4i pconj(const Packet4i& a) { return a; }
@@ -164,17 +240,17 @@
 #endif
 }
 
 template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b) { return _mm_div_ps(a,b); }
 template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return _mm_div_pd(a,b); }
-template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& /*a*/, const Packet4i& /*b*/)
-{ eigen_assert(false && "packet integer division are not supported by SSE");
-  return pset1<Packet4i>(0);
-}
 
 // for some weird raisons, it has to be overloaded for packet of integers
 template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return padd(pmul(a,b), c); }
+#ifdef __FMA__
+template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return _mm_fmadd_ps(a,b,c); }
+template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return _mm_fmadd_pd(a,b,c); }
+#endif
 
 template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b) { return _mm_min_ps(a,b); }
 template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) { return _mm_min_pd(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const Packet4i& b)
 {
@@ -197,10 +273,21 @@
   // after some bench, this version *is* faster than a scalar implementation
   Packet4i mask = _mm_cmpgt_epi32(a,b);
   return _mm_or_si128(_mm_and_si128(mask,a),_mm_andnot_si128(mask,b));
 #endif
 }
+
+#ifdef EIGEN_VECTORIZE_SSE4_1
+template<> EIGEN_STRONG_INLINE Packet4f pround<Packet4f>(const Packet4f& a) { return _mm_round_ps(a, 0); }
+template<> EIGEN_STRONG_INLINE Packet2d pround<Packet2d>(const Packet2d& a) { return _mm_round_pd(a, 0); }
+
+template<> EIGEN_STRONG_INLINE Packet4f pceil<Packet4f>(const Packet4f& a) { return _mm_ceil_ps(a); }
+template<> EIGEN_STRONG_INLINE Packet2d pceil<Packet2d>(const Packet2d& a) { return _mm_ceil_pd(a); }
+
+template<> EIGEN_STRONG_INLINE Packet4f pfloor<Packet4f>(const Packet4f& a) { return _mm_floor_ps(a); }
+template<> EIGEN_STRONG_INLINE Packet2d pfloor<Packet2d>(const Packet2d& a) { return _mm_floor_pd(a); }
+#endif
 
 template<> EIGEN_STRONG_INLINE Packet4f pand<Packet4f>(const Packet4f& a, const Packet4f& b) { return _mm_and_ps(a,b); }
 template<> EIGEN_STRONG_INLINE Packet2d pand<Packet2d>(const Packet2d& a, const Packet2d& b) { return _mm_and_pd(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4i pand<Packet4i>(const Packet4i& a, const Packet4i& b) { return _mm_and_si128(a,b); }
 
@@ -216,84 +303,46 @@
 template<> EIGEN_STRONG_INLINE Packet2d pandnot<Packet2d>(const Packet2d& a, const Packet2d& b) { return _mm_andnot_pd(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4i pandnot<Packet4i>(const Packet4i& a, const Packet4i& b) { return _mm_andnot_si128(a,b); }
 
 template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float*   from) { EIGEN_DEBUG_ALIGNED_LOAD return _mm_load_ps(from); }
 template<> EIGEN_STRONG_INLINE Packet2d pload<Packet2d>(const double*  from) { EIGEN_DEBUG_ALIGNED_LOAD return _mm_load_pd(from); }
-template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int*     from) { EIGEN_DEBUG_ALIGNED_LOAD return _mm_load_si128(reinterpret_cast<const Packet4i*>(from)); }
+template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int*     from) { EIGEN_DEBUG_ALIGNED_LOAD return _mm_load_si128(reinterpret_cast<const __m128i*>(from)); }
 
-#if defined(_MSC_VER)
+#if EIGEN_COMP_MSVC
   template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float*  from) {
     EIGEN_DEBUG_UNALIGNED_LOAD
-    #if (_MSC_VER==1600)
+    #if (EIGEN_COMP_MSVC==1600)
     // NOTE Some version of MSVC10 generates bad code when using _mm_loadu_ps
     // (i.e., it does not generate an unaligned load!!
-    // TODO On most architectures this version should also be faster than a single _mm_loadu_ps
-    // so we could also enable it for MSVC08 but first we have to make this later does not generate crap when doing so...
     __m128 res = _mm_loadl_pi(_mm_set1_ps(0.0f), (const __m64*)(from));
     res = _mm_loadh_pi(res, (const __m64*)(from+2));
     return res;
     #else
     return _mm_loadu_ps(from);
     #endif
   }
-  template<> EIGEN_STRONG_INLINE Packet2d ploadu<Packet2d>(const double* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm_loadu_pd(from); }
-  template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int*    from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm_loadu_si128(reinterpret_cast<const Packet4i*>(from)); }
-#else
-// Fast unaligned loads. Note that here we cannot directly use intrinsics: this would
-// require pointer casting to incompatible pointer types and leads to invalid code
-// because of the strict aliasing rule. The "dummy" stuff are required to enforce
-// a correct instruction dependency.
-// TODO: do the same for MSVC (ICC is compatible)
-// NOTE: with the code below, MSVC's compiler crashes!
-
-#if defined(__GNUC__) && defined(__i386__)
-  // bug 195: gcc/i386 emits weird x87 fldl/fstpl instructions for _mm_load_sd
-  #define EIGEN_AVOID_CUSTOM_UNALIGNED_LOADS 1
-#elif defined(__clang__)
-  // bug 201: Segfaults in __mm_loadh_pd with clang 2.8
-  #define EIGEN_AVOID_CUSTOM_UNALIGNED_LOADS 1
-#else
-  #define EIGEN_AVOID_CUSTOM_UNALIGNED_LOADS 0
-#endif
+#else
+// NOTE: with the code below, MSVC's compiler crashes!
 
 template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from)
 {
   EIGEN_DEBUG_UNALIGNED_LOAD
-#if EIGEN_AVOID_CUSTOM_UNALIGNED_LOADS
   return _mm_loadu_ps(from);
-#else
-  __m128d res;
-  res =  _mm_load_sd((const double*)(from)) ;
-  res =  _mm_loadh_pd(res, (const double*)(from+2)) ;
-  return _mm_castpd_ps(res);
+}
 #endif
-}
+
 template<> EIGEN_STRONG_INLINE Packet2d ploadu<Packet2d>(const double* from)
 {
   EIGEN_DEBUG_UNALIGNED_LOAD
-#if EIGEN_AVOID_CUSTOM_UNALIGNED_LOADS
   return _mm_loadu_pd(from);
-#else
-  __m128d res;
-  res = _mm_load_sd(from) ;
-  res = _mm_loadh_pd(res,from+1);
-  return res;
-#endif
 }
 template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int* from)
 {
   EIGEN_DEBUG_UNALIGNED_LOAD
-#if EIGEN_AVOID_CUSTOM_UNALIGNED_LOADS
-  return _mm_loadu_si128(reinterpret_cast<const Packet4i*>(from));
-#else
-  __m128d res;
-  res =  _mm_load_sd((const double*)(from)) ;
-  res =  _mm_loadh_pd(res, (const double*)(from+2)) ;
-  return _mm_castpd_si128(res);
-#endif
-}
-#endif
+  return _mm_loadu_si128(reinterpret_cast<const __m128i*>(from));
+}
+
 
 template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float*   from)
 {
   return vec4f_swizzle1(_mm_castpd_ps(_mm_load_sd(reinterpret_cast<const double*>(from))), 0, 0, 1, 1);
 }
@@ -300,50 +349,81 @@
 template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double*  from)
 { return pset1<Packet2d>(from[0]); }
 template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int*     from)
 {
   Packet4i tmp;
-  tmp = _mm_loadl_epi64(reinterpret_cast<const Packet4i*>(from));
+  tmp = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(from));
   return vec4i_swizzle1(tmp, 0, 0, 1, 1);
 }
 
 template<> EIGEN_STRONG_INLINE void pstore<float>(float*   to, const Packet4f& from) { EIGEN_DEBUG_ALIGNED_STORE _mm_store_ps(to, from); }
 template<> EIGEN_STRONG_INLINE void pstore<double>(double* to, const Packet2d& from) { EIGEN_DEBUG_ALIGNED_STORE _mm_store_pd(to, from); }
-template<> EIGEN_STRONG_INLINE void pstore<int>(int*       to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE _mm_store_si128(reinterpret_cast<Packet4i*>(to), from); }
-
-template<> EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet2d& from) {
-  EIGEN_DEBUG_UNALIGNED_STORE
-  _mm_storel_pd((to), from);
-  _mm_storeh_pd((to+1), from);
-}
-template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*  to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(reinterpret_cast<double*>(to), _mm_castps_pd(from)); }
-template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*      to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(reinterpret_cast<double*>(to), _mm_castsi128_pd(from)); }
+template<> EIGEN_STRONG_INLINE void pstore<int>(int*       to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE _mm_store_si128(reinterpret_cast<__m128i*>(to), from); }
+
+template<> EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet2d& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm_storeu_pd(to, from); }
+template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*   to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm_storeu_ps(to, from); }
+template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*       to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm_storeu_si128(reinterpret_cast<__m128i*>(to), from); }
+
+template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, Index stride)
+{
+ return _mm_set_ps(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
+}
+template<> EIGEN_DEVICE_FUNC inline Packet2d pgather<double, Packet2d>(const double* from, Index stride)
+{
+ return _mm_set_pd(from[1*stride], from[0*stride]);
+}
+template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, Index stride)
+{
+ return _mm_set_epi32(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
+ }
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, Index stride)
+{
+  to[stride*0] = _mm_cvtss_f32(from);
+  to[stride*1] = _mm_cvtss_f32(_mm_shuffle_ps(from, from, 1));
+  to[stride*2] = _mm_cvtss_f32(_mm_shuffle_ps(from, from, 2));
+  to[stride*3] = _mm_cvtss_f32(_mm_shuffle_ps(from, from, 3));
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to, const Packet2d& from, Index stride)
+{
+  to[stride*0] = _mm_cvtsd_f64(from);
+  to[stride*1] = _mm_cvtsd_f64(_mm_shuffle_pd(from, from, 1));
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, Index stride)
+{
+  to[stride*0] = _mm_cvtsi128_si32(from);
+  to[stride*1] = _mm_cvtsi128_si32(_mm_shuffle_epi32(from, 1));
+  to[stride*2] = _mm_cvtsi128_si32(_mm_shuffle_epi32(from, 2));
+  to[stride*3] = _mm_cvtsi128_si32(_mm_shuffle_epi32(from, 3));
+}
 
 // some compilers might be tempted to perform multiple moves instead of using a vector path.
 template<> EIGEN_STRONG_INLINE void pstore1<Packet4f>(float* to, const float& a)
 {
   Packet4f pa = _mm_set_ss(a);
-  pstore(to, vec4f_swizzle1(pa,0,0,0,0));
+  pstore(to, Packet4f(vec4f_swizzle1(pa,0,0,0,0)));
 }
 // some compilers might be tempted to perform multiple moves instead of using a vector path.
 template<> EIGEN_STRONG_INLINE void pstore1<Packet2d>(double* to, const double& a)
 {
   Packet2d pa = _mm_set_sd(a);
-  pstore(to, vec2d_swizzle1(pa,0,0));
+  pstore(to, Packet2d(vec2d_swizzle1(pa,0,0)));
 }
 
+#ifndef EIGEN_VECTORIZE_AVX
 template<> EIGEN_STRONG_INLINE void prefetch<float>(const float*   addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
 template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
 template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*       addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); }
+#endif
 
-#if defined(_MSC_VER) && defined(_WIN64) && !defined(__INTEL_COMPILER)
+#if EIGEN_COMP_MSVC_STRICT && EIGEN_OS_WIN64
 // The temporary variable fixes an internal compilation error in vs <= 2008 and a wrong-result bug in vs 2010
 // Direct of the struct members fixed bug #62.
 template<> EIGEN_STRONG_INLINE float  pfirst<Packet4f>(const Packet4f& a) { return a.m128_f32[0]; }
 template<> EIGEN_STRONG_INLINE double pfirst<Packet2d>(const Packet2d& a) { return a.m128d_f64[0]; }
 template<> EIGEN_STRONG_INLINE int    pfirst<Packet4i>(const Packet4i& a) { int x = _mm_cvtsi128_si32(a); return x; }
-#elif defined(_MSC_VER) && !defined(__INTEL_COMPILER)
+#elif EIGEN_COMP_MSVC_STRICT
 // The temporary variable fixes an internal compilation error in vs <= 2008 and a wrong-result bug in vs 2010
 template<> EIGEN_STRONG_INLINE float  pfirst<Packet4f>(const Packet4f& a) { float x = _mm_cvtss_f32(a); return x; }
 template<> EIGEN_STRONG_INLINE double pfirst<Packet2d>(const Packet2d& a) { double x = _mm_cvtsd_f64(a); return x; }
 template<> EIGEN_STRONG_INLINE int    pfirst<Packet4i>(const Packet4i& a) { int x = _mm_cvtsi128_si32(a); return x; }
 #else
@@ -356,11 +436,10 @@
 { return _mm_shuffle_ps(a,a,0x1B); }
 template<> EIGEN_STRONG_INLINE Packet2d preverse(const Packet2d& a)
 { return _mm_shuffle_pd(a,a,0x1); }
 template<> EIGEN_STRONG_INLINE Packet4i preverse(const Packet4i& a)
 { return _mm_shuffle_epi32(a,0x1B); }
-
 
 template<> EIGEN_STRONG_INLINE Packet4f pabs(const Packet4f& a)
 {
   const Packet4f mask = _mm_castsi128_ps(_mm_setr_epi32(0x7FFFFFFF,0x7FFFFFFF,0x7FFFFFFF,0x7FFFFFFF));
   return _mm_and_ps(a,mask);
@@ -377,10 +456,42 @@
   #else
   Packet4i aux = _mm_srai_epi32(a,31);
   return _mm_sub_epi32(_mm_xor_si128(a,aux),aux);
   #endif
 }
+
+// with AVX, the default implementations based on pload1 are faster
+#ifndef __AVX__
+template<> EIGEN_STRONG_INLINE void
+pbroadcast4<Packet4f>(const float *a,
+                      Packet4f& a0, Packet4f& a1, Packet4f& a2, Packet4f& a3)
+{
+  a3 = pload<Packet4f>(a);
+  a0 = vec4f_swizzle1(a3, 0,0,0,0);
+  a1 = vec4f_swizzle1(a3, 1,1,1,1);
+  a2 = vec4f_swizzle1(a3, 2,2,2,2);
+  a3 = vec4f_swizzle1(a3, 3,3,3,3);
+}
+template<> EIGEN_STRONG_INLINE void
+pbroadcast4<Packet2d>(const double *a,
+                      Packet2d& a0, Packet2d& a1, Packet2d& a2, Packet2d& a3)
+{
+#ifdef EIGEN_VECTORIZE_SSE3
+  a0 = _mm_loaddup_pd(a+0);
+  a1 = _mm_loaddup_pd(a+1);
+  a2 = _mm_loaddup_pd(a+2);
+  a3 = _mm_loaddup_pd(a+3);
+#else
+  a1 = pload<Packet2d>(a);
+  a0 = vec2d_swizzle1(a1, 0,0);
+  a1 = vec2d_swizzle1(a1, 1,1);
+  a3 = pload<Packet2d>(a+2);
+  a2 = vec2d_swizzle1(a3, 0,0);
+  a3 = vec2d_swizzle1(a3, 1,1);
+#endif
+}
+#endif
 
 EIGEN_STRONG_INLINE void punpackp(Packet4f* vecs)
 {
   vecs[1] = _mm_castsi128_ps(_mm_shuffle_epi32(_mm_castps_si128(vecs[0]), 0x55));
   vecs[2] = _mm_castsi128_ps(_mm_shuffle_epi32(_mm_castps_si128(vecs[0]), 0xAA));
@@ -387,51 +498,21 @@
   vecs[3] = _mm_castsi128_ps(_mm_shuffle_epi32(_mm_castps_si128(vecs[0]), 0xFF));
   vecs[0] = _mm_castsi128_ps(_mm_shuffle_epi32(_mm_castps_si128(vecs[0]), 0x00));
 }
 
 #ifdef EIGEN_VECTORIZE_SSE3
-// TODO implement SSE2 versions as well as integer versions
 template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
 {
   return _mm_hadd_ps(_mm_hadd_ps(vecs[0], vecs[1]),_mm_hadd_ps(vecs[2], vecs[3]));
 }
+
 template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
 {
   return _mm_hadd_pd(vecs[0], vecs[1]);
 }
-// SSSE3 version:
-// EIGEN_STRONG_INLINE Packet4i preduxp(const Packet4i* vecs)
-// {
-//   return _mm_hadd_epi32(_mm_hadd_epi32(vecs[0], vecs[1]),_mm_hadd_epi32(vecs[2], vecs[3]));
-// }
-
-template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
-{
-  Packet4f tmp0 = _mm_hadd_ps(a,a);
-  return pfirst(_mm_hadd_ps(tmp0, tmp0));
-}
-
-template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a) { return pfirst(_mm_hadd_pd(a, a)); }
-
-// SSSE3 version:
-// EIGEN_STRONG_INLINE float predux(const Packet4i& a)
-// {
-//   Packet4i tmp0 = _mm_hadd_epi32(a,a);
-//   return pfirst(_mm_hadd_epi32(tmp0, tmp0));
-// }
-#else
-// SSE2 versions
-template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
-{
-  Packet4f tmp = _mm_add_ps(a, _mm_movehl_ps(a,a));
-  return pfirst(_mm_add_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
-}
-template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a)
-{
-  return pfirst(_mm_add_sd(a, _mm_unpackhi_pd(a,a)));
-}
-
+
+#else
 template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
 {
   Packet4f tmp0, tmp1, tmp2;
   tmp0 = _mm_unpacklo_ps(vecs[0], vecs[1]);
   tmp1 = _mm_unpackhi_ps(vecs[0], vecs[1]);
@@ -448,14 +529,49 @@
 {
   return _mm_add_pd(_mm_unpacklo_pd(vecs[0], vecs[1]), _mm_unpackhi_pd(vecs[0], vecs[1]));
 }
 #endif  // SSE3
 
+template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
+{
+  // Disable SSE3 _mm_hadd_pd that is extremely slow on all existing Intel's architectures
+  // (from Nehalem to Haswell)
+// #ifdef EIGEN_VECTORIZE_SSE3
+//   Packet4f tmp = _mm_add_ps(a, vec4f_swizzle1(a,2,3,2,3));
+//   return pfirst<Packet4f>(_mm_hadd_ps(tmp, tmp));
+// #else
+  Packet4f tmp = _mm_add_ps(a, _mm_movehl_ps(a,a));
+  return pfirst<Packet4f>(_mm_add_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
+// #endif
+}
+
+template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a)
+{
+  // Disable SSE3 _mm_hadd_pd that is extremely slow on all existing Intel's architectures
+  // (from Nehalem to Haswell)
+// #ifdef EIGEN_VECTORIZE_SSE3
+//   return pfirst<Packet2d>(_mm_hadd_pd(a, a));
+// #else
+  return pfirst<Packet2d>(_mm_add_sd(a, _mm_unpackhi_pd(a,a)));
+// #endif
+}
+
+#ifdef EIGEN_VECTORIZE_SSSE3
+template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
+{
+  return _mm_hadd_epi32(_mm_hadd_epi32(vecs[0], vecs[1]),_mm_hadd_epi32(vecs[2], vecs[3]));
+}
+template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
+{
+  Packet4i tmp0 = _mm_hadd_epi32(a,a);
+  return pfirst<Packet4i>(_mm_hadd_epi32(tmp0,tmp0));
+}
+#else
 template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
 {
   Packet4i tmp = _mm_add_epi32(a, _mm_unpackhi_epi64(a,a));
-  return pfirst(tmp) + pfirst(_mm_shuffle_epi32(tmp, 1));
+  return pfirst(tmp) + pfirst<Packet4i>(_mm_shuffle_epi32(tmp, 1));
 }
 
 template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
 {
   Packet4i tmp0, tmp1, tmp2;
@@ -467,22 +583,22 @@
   tmp1 = _mm_add_epi32(tmp1, tmp2);
   tmp2 = _mm_unpacklo_epi64(tmp0, tmp1);
   tmp0 = _mm_unpackhi_epi64(tmp0, tmp1);
   return _mm_add_epi32(tmp0, tmp2);
 }
-
+#endif
 // Other reduction functions:
 
 // mul
 template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
 {
   Packet4f tmp = _mm_mul_ps(a, _mm_movehl_ps(a,a));
-  return pfirst(_mm_mul_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
+  return pfirst<Packet4f>(_mm_mul_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
 }
 template<> EIGEN_STRONG_INLINE double predux_mul<Packet2d>(const Packet2d& a)
 {
-  return pfirst(_mm_mul_sd(a, _mm_unpackhi_pd(a,a)));
+  return pfirst<Packet2d>(_mm_mul_sd(a, _mm_unpackhi_pd(a,a)));
 }
 template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
 {
   // after some experiments, it is seems this is the fastest way to implement it
   // for GCC (eg., reusing pmul is very slow !)
@@ -494,49 +610,59 @@
 
 // min
 template<> EIGEN_STRONG_INLINE float predux_min<Packet4f>(const Packet4f& a)
 {
   Packet4f tmp = _mm_min_ps(a, _mm_movehl_ps(a,a));
-  return pfirst(_mm_min_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
+  return pfirst<Packet4f>(_mm_min_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
 }
 template<> EIGEN_STRONG_INLINE double predux_min<Packet2d>(const Packet2d& a)
 {
-  return pfirst(_mm_min_sd(a, _mm_unpackhi_pd(a,a)));
+  return pfirst<Packet2d>(_mm_min_sd(a, _mm_unpackhi_pd(a,a)));
 }
 template<> EIGEN_STRONG_INLINE int predux_min<Packet4i>(const Packet4i& a)
 {
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  Packet4i tmp = _mm_min_epi32(a, _mm_shuffle_epi32(a, _MM_SHUFFLE(0,0,3,2)));
+  return pfirst<Packet4i>(_mm_min_epi32(tmp,_mm_shuffle_epi32(tmp, 1)));
+#else
   // after some experiments, it is seems this is the fastest way to implement it
   // for GCC (eg., it does not like using std::min after the pstore !!)
   EIGEN_ALIGN16 int aux[4];
   pstore(aux, a);
   int aux0 = aux[0]<aux[1] ? aux[0] : aux[1];
   int aux2 = aux[2]<aux[3] ? aux[2] : aux[3];
   return aux0<aux2 ? aux0 : aux2;
+#endif // EIGEN_VECTORIZE_SSE4_1
 }
 
 // max
 template<> EIGEN_STRONG_INLINE float predux_max<Packet4f>(const Packet4f& a)
 {
   Packet4f tmp = _mm_max_ps(a, _mm_movehl_ps(a,a));
-  return pfirst(_mm_max_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
+  return pfirst<Packet4f>(_mm_max_ss(tmp, _mm_shuffle_ps(tmp,tmp, 1)));
 }
 template<> EIGEN_STRONG_INLINE double predux_max<Packet2d>(const Packet2d& a)
 {
-  return pfirst(_mm_max_sd(a, _mm_unpackhi_pd(a,a)));
+  return pfirst<Packet2d>(_mm_max_sd(a, _mm_unpackhi_pd(a,a)));
 }
 template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
 {
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  Packet4i tmp = _mm_max_epi32(a, _mm_shuffle_epi32(a, _MM_SHUFFLE(0,0,3,2)));
+  return pfirst<Packet4i>(_mm_max_epi32(tmp,_mm_shuffle_epi32(tmp, 1)));
+#else
   // after some experiments, it is seems this is the fastest way to implement it
   // for GCC (eg., it does not like using std::min after the pstore !!)
   EIGEN_ALIGN16 int aux[4];
   pstore(aux, a);
   int aux0 = aux[0]>aux[1] ? aux[0] : aux[1];
   int aux2 = aux[2]>aux[3] ? aux[2] : aux[3];
   return aux0>aux2 ? aux0 : aux2;
+#endif // EIGEN_VECTORIZE_SSE4_1
 }
 
-#if (defined __GNUC__)
+#if EIGEN_COMP_GNUC
 // template <> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f&  a, const Packet4f&  b, const Packet4f&  c)
 // {
 //   Packet4f res = b;
 //   asm("mulps %[a], %[b] \n\taddps %[c], %[b]" : [b] "+x" (res) : [a] "x" (a), [c] "x" (c));
 //   return res;
@@ -639,11 +765,115 @@
       first = _mm_castps_pd(_mm_movelh_ps(_mm_castpd_ps(first),_mm_castpd_ps(second)));
     }
   }
 };
 #endif
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4f,4>& kernel) {
+  _MM_TRANSPOSE4_PS(kernel.packet[0], kernel.packet[1], kernel.packet[2], kernel.packet[3]);
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet2d,2>& kernel) {
+  __m128d tmp = _mm_unpackhi_pd(kernel.packet[0], kernel.packet[1]);
+  kernel.packet[0] = _mm_unpacklo_pd(kernel.packet[0], kernel.packet[1]);
+  kernel.packet[1] = tmp;
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4i,4>& kernel) {
+  __m128i T0 = _mm_unpacklo_epi32(kernel.packet[0], kernel.packet[1]);
+  __m128i T1 = _mm_unpacklo_epi32(kernel.packet[2], kernel.packet[3]);
+  __m128i T2 = _mm_unpackhi_epi32(kernel.packet[0], kernel.packet[1]);
+  __m128i T3 = _mm_unpackhi_epi32(kernel.packet[2], kernel.packet[3]);
+
+  kernel.packet[0] = _mm_unpacklo_epi64(T0, T1);
+  kernel.packet[1] = _mm_unpackhi_epi64(T0, T1);
+  kernel.packet[2] = _mm_unpacklo_epi64(T2, T3);
+  kernel.packet[3] = _mm_unpackhi_epi64(T2, T3);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pblend(const Selector<4>& ifPacket, const Packet4i& thenPacket, const Packet4i& elsePacket) {
+  const __m128i zero = _mm_setzero_si128();
+  const __m128i select = _mm_set_epi32(ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
+  __m128i false_mask = _mm_cmpeq_epi32(select, zero);
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  return _mm_blendv_epi8(thenPacket, elsePacket, false_mask);
+#else
+  return _mm_or_si128(_mm_andnot_si128(false_mask, thenPacket), _mm_and_si128(false_mask, elsePacket));
+#endif
+}
+template<> EIGEN_STRONG_INLINE Packet4f pblend(const Selector<4>& ifPacket, const Packet4f& thenPacket, const Packet4f& elsePacket) {
+  const __m128 zero = _mm_setzero_ps();
+  const __m128 select = _mm_set_ps(ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
+  __m128 false_mask = _mm_cmpeq_ps(select, zero);
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  return _mm_blendv_ps(thenPacket, elsePacket, false_mask);
+#else
+  return _mm_or_ps(_mm_andnot_ps(false_mask, thenPacket), _mm_and_ps(false_mask, elsePacket));
+#endif
+}
+template<> EIGEN_STRONG_INLINE Packet2d pblend(const Selector<2>& ifPacket, const Packet2d& thenPacket, const Packet2d& elsePacket) {
+  const __m128d zero = _mm_setzero_pd();
+  const __m128d select = _mm_set_pd(ifPacket.select[1], ifPacket.select[0]);
+  __m128d false_mask = _mm_cmpeq_pd(select, zero);
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  return _mm_blendv_pd(thenPacket, elsePacket, false_mask);
+#else
+  return _mm_or_pd(_mm_andnot_pd(false_mask, thenPacket), _mm_and_pd(false_mask, elsePacket));
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f pinsertfirst(const Packet4f& a, float b)
+{
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  return _mm_blend_ps(a,pset1<Packet4f>(b),1);
+#else
+  return _mm_move_ss(a, _mm_load_ss(&b));
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pinsertfirst(const Packet2d& a, double b)
+{
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  return _mm_blend_pd(a,pset1<Packet2d>(b),1);
+#else
+  return _mm_move_sd(a, _mm_load_sd(&b));
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f pinsertlast(const Packet4f& a, float b)
+{
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  return _mm_blend_ps(a,pset1<Packet4f>(b),(1<<3));
+#else
+  const Packet4f mask = _mm_castsi128_ps(_mm_setr_epi32(0x0,0x0,0x0,0xFFFFFFFF));
+  return _mm_or_ps(_mm_andnot_ps(mask, a), _mm_and_ps(mask, pset1<Packet4f>(b)));
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pinsertlast(const Packet2d& a, double b)
+{
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  return _mm_blend_pd(a,pset1<Packet2d>(b),(1<<1));
+#else
+  const Packet2d mask = _mm_castsi128_pd(_mm_setr_epi32(0x0,0x0,0xFFFFFFFF,0xFFFFFFFF));
+  return _mm_or_pd(_mm_andnot_pd(mask, a), _mm_and_pd(mask, pset1<Packet2d>(b)));
+#endif
+}
+
+// Scalar path for pmadd with FMA to ensure consistency with vectorized path.
+#ifdef __FMA__
+template<> EIGEN_STRONG_INLINE float pmadd(const float& a, const float& b, const float& c) {
+  return ::fmaf(a,b,c);
+}
+template<> EIGEN_STRONG_INLINE double pmadd(const double& a, const double& b, const double& c) {
+  return ::fma(a,b,c);
+}
+#endif
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_PACKET_MATH_SSE_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/SSE/TypeCasting.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/SSE/TypeCasting.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/SSE/TypeCasting.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/SSE/TypeCasting.h
@@ -0,0 +1,77 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_TYPE_CASTING_SSE_H
+#define EIGEN_TYPE_CASTING_SSE_H
+
+namespace Eigen {
+
+namespace internal {
+
+template <>
+struct type_casting_traits<float, int> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet4i pcast<Packet4f, Packet4i>(const Packet4f& a) {
+  return _mm_cvttps_epi32(a);
+}
+
+
+template <>
+struct type_casting_traits<int, float> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet4i, Packet4f>(const Packet4i& a) {
+  return _mm_cvtepi32_ps(a);
+}
+
+
+template <>
+struct type_casting_traits<double, float> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 2,
+    TgtCoeffRatio = 1
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet2d, Packet4f>(const Packet2d& a, const Packet2d& b) {
+  return _mm_shuffle_ps(_mm_cvtpd_ps(a), _mm_cvtpd_ps(b), (1 << 2) | (1 << 6));
+}
+
+template <>
+struct type_casting_traits<float, double> {
+  enum {
+    VectorizedCast = 1,
+    SrcCoeffRatio = 1,
+    TgtCoeffRatio = 2
+  };
+};
+
+template<> EIGEN_STRONG_INLINE Packet2d pcast<Packet4f, Packet2d>(const Packet4f& a) {
+  // Simply discard the second half of the input
+  return _mm_cvtps_pd(a);
+}
+
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TYPE_CASTING_SSE_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/ZVector/Complex.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/ZVector/Complex.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/ZVector/Complex.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/ZVector/Complex.h
@@ -0,0 +1,394 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2016 Konstantinos Margaritis <markos@freevec.org>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_COMPLEX32_ALTIVEC_H
+#define EIGEN_COMPLEX32_ALTIVEC_H
+
+namespace Eigen {
+
+namespace internal {
+
+static Packet2ul  p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2d_ZERO_, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
+static Packet2ul  p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO,  (Packet4ui) p2d_ZERO_, 8);//{ 0x8000000000000000, 0x0000000000000000 };
+
+struct Packet1cd
+{
+  EIGEN_STRONG_INLINE Packet1cd() {}
+  EIGEN_STRONG_INLINE explicit Packet1cd(const Packet2d& a) : v(a) {}
+  Packet2d v;
+};
+
+struct Packet2cf
+{
+  EIGEN_STRONG_INLINE Packet2cf() {}
+  EIGEN_STRONG_INLINE explicit Packet2cf(const Packet4f& a) : v(a) {}
+  union {
+    Packet4f v;
+    Packet1cd cd[2];
+  };
+};
+
+template<> struct packet_traits<std::complex<float> >  : default_packet_traits
+{
+  typedef Packet2cf type;
+  typedef Packet2cf half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 2,
+    HasHalfPacket = 0,
+
+    HasAdd    = 1,
+    HasSub    = 1,
+    HasMul    = 1,
+    HasDiv    = 1,
+    HasNegate = 1,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasBlend  = 1,
+    HasSetLinear = 0
+  };
+};
+
+
+template<> struct packet_traits<std::complex<double> >  : default_packet_traits
+{
+  typedef Packet1cd type;
+  typedef Packet1cd half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 1,
+    HasHalfPacket = 0,
+
+    HasAdd    = 1,
+    HasSub    = 1,
+    HasMul    = 1,
+    HasDiv    = 1,
+    HasNegate = 1,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasSetLinear = 0
+  };
+};
+
+template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float>  type; enum {size=2, alignment=Aligned16}; typedef Packet2cf half; };
+template<> struct unpacket_traits<Packet1cd> { typedef std::complex<double> type; enum {size=1, alignment=Aligned16}; typedef Packet1cd half; };
+
+/* Forward declaration */
+EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet2cf,2>& kernel);
+
+template<> EIGEN_STRONG_INLINE Packet2cf pload <Packet2cf>(const std::complex<float>* from)  { EIGEN_DEBUG_ALIGNED_LOAD return Packet2cf(pload<Packet4f>((const float*)from)); }
+template<> EIGEN_STRONG_INLINE Packet1cd pload <Packet1cd>(const std::complex<double>* from) { EIGEN_DEBUG_ALIGNED_LOAD return Packet1cd(pload<Packet2d>((const double*)from)); }
+template<> EIGEN_STRONG_INLINE Packet2cf ploadu<Packet2cf>(const std::complex<float>* from)  { EIGEN_DEBUG_UNALIGNED_LOAD return Packet2cf(ploadu<Packet4f>((const float*)from)); }
+template<> EIGEN_STRONG_INLINE Packet1cd ploadu<Packet1cd>(const std::complex<double>* from) { EIGEN_DEBUG_UNALIGNED_LOAD return Packet1cd(ploadu<Packet2d>((const double*)from)); }
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> *     to, const Packet2cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((float*)to, from.v); }
+template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> *     to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((float*)to, from.v); }
+template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> *   to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd pset1<Packet1cd>(const std::complex<double>&  from)
+{ /* here we really have to use unaligned loads :( */ return ploadu<Packet1cd>(&from); }
+
+template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>&  from)
+{
+  Packet2cf res;
+  res.cd[0] = Packet1cd(vec_ld2f((const float *)&from));
+  res.cd[1] = res.cd[0];
+  return res;
+}
+template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, Index stride)
+{
+  std::complex<float> EIGEN_ALIGN16 af[2];
+  af[0] = from[0*stride];
+  af[1] = from[1*stride];
+  return pload<Packet2cf>(af);
+}
+template<> EIGEN_DEVICE_FUNC inline Packet1cd pgather<std::complex<double>, Packet1cd>(const std::complex<double>* from, Index stride EIGEN_UNUSED)
+{
+  return pload<Packet1cd>(from);
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, Index stride)
+{
+  std::complex<float> EIGEN_ALIGN16 af[2];
+  pstore<std::complex<float> >((std::complex<float> *) af, from);
+  to[0*stride] = af[0];
+  to[1*stride] = af[1];
+}
+template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet1cd>(std::complex<double>* to, const Packet1cd& from, Index stride EIGEN_UNUSED)
+{
+  pstore<std::complex<double> >(to, from);
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cf padd<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(padd<Packet4f>(a.v, b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd padd<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(a.v + b.v); }
+template<> EIGEN_STRONG_INLINE Packet2cf psub<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(psub<Packet4f>(a.v, b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd psub<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(a.v - b.v); }
+template<> EIGEN_STRONG_INLINE Packet1cd pnegate(const Packet1cd& a) { return Packet1cd(pnegate(Packet2d(a.v))); }
+template<> EIGEN_STRONG_INLINE Packet2cf pnegate(const Packet2cf& a) { return Packet2cf(pnegate(Packet4f(a.v))); }
+template<> EIGEN_STRONG_INLINE Packet1cd pconj(const Packet1cd& a) { return Packet1cd((Packet2d)vec_xor((Packet2d)a.v, (Packet2d)p2ul_CONJ_XOR2)); }
+template<> EIGEN_STRONG_INLINE Packet2cf pconj(const Packet2cf& a)
+{
+  Packet2cf res;
+  res.v.v4f[0] = pconj(Packet1cd(reinterpret_cast<Packet2d>(a.v.v4f[0]))).v;
+  res.v.v4f[1] = pconj(Packet1cd(reinterpret_cast<Packet2d>(a.v.v4f[1]))).v;
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd pmul<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  Packet2d a_re, a_im, v1, v2;
+
+  // Permute and multiply the real parts of a and b
+  a_re = vec_perm(a.v, a.v, p16uc_PSET64_HI);
+  // Get the imaginary parts of a
+  a_im = vec_perm(a.v, a.v, p16uc_PSET64_LO);
+  // multiply a_re * b
+  v1 = vec_madd(a_re, b.v, p2d_ZERO);
+  // multiply a_im * b and get the conjugate result
+  v2 = vec_madd(a_im, b.v, p2d_ZERO);
+  v2 = (Packet2d) vec_sld((Packet4ui)v2, (Packet4ui)v2, 8);
+  v2 = (Packet2d) vec_xor((Packet2d)v2, (Packet2d) p2ul_CONJ_XOR1);
+
+  return Packet1cd(v1 + v2);
+}
+template<> EIGEN_STRONG_INLINE Packet2cf pmul<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
+{
+  Packet2cf res;
+  res.v.v4f[0] = pmul(Packet1cd(reinterpret_cast<Packet2d>(a.v.v4f[0])), Packet1cd(reinterpret_cast<Packet2d>(b.v.v4f[0]))).v;
+  res.v.v4f[1] = pmul(Packet1cd(reinterpret_cast<Packet2d>(a.v.v4f[1])), Packet1cd(reinterpret_cast<Packet2d>(b.v.v4f[1]))).v;
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd pand   <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_and(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cf pand   <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pand<Packet4f>(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd por    <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_or(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cf por    <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(por<Packet4f>(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd pxor   <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_xor(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet2cf pxor   <Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pxor<Packet4f>(a.v,b.v)); }
+template<> EIGEN_STRONG_INLINE Packet1cd pandnot<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_and(a.v, vec_nor(b.v,b.v))); }
+template<> EIGEN_STRONG_INLINE Packet2cf pandnot<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { return Packet2cf(pandnot<Packet4f>(a.v,b.v)); }
+
+template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<double>*     from) {  return pset1<Packet1cd>(*from); }
+template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<float>*      from) {  return pset1<Packet2cf>(*from); }
+
+template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> *     addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
+template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> *   addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
+
+template<> EIGEN_STRONG_INLINE std::complex<double>  pfirst<Packet1cd>(const Packet1cd& a)
+{
+  std::complex<double> EIGEN_ALIGN16 res;
+  pstore<std::complex<double> >(&res, a);
+
+  return res;
+}
+template<> EIGEN_STRONG_INLINE std::complex<float>  pfirst<Packet2cf>(const Packet2cf& a)
+{
+  std::complex<float> EIGEN_ALIGN16 res[2];
+  pstore<std::complex<float> >(res, a);
+
+  return res[0];
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd preverse(const Packet1cd& a) { return a; }
+template<> EIGEN_STRONG_INLINE Packet2cf preverse(const Packet2cf& a)
+{
+  Packet2cf res;
+  res.cd[0] = a.cd[1];
+  res.cd[1] = a.cd[0];
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE std::complex<double> predux<Packet1cd>(const Packet1cd& a)
+{
+  return pfirst(a);
+}
+template<> EIGEN_STRONG_INLINE std::complex<float> predux<Packet2cf>(const Packet2cf& a)
+{
+  std::complex<float> res;
+  Packet1cd b = padd<Packet1cd>(a.cd[0], a.cd[1]);
+  vec_st2f(b.v, (float*)&res);
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet1cd preduxp<Packet1cd>(const Packet1cd* vecs)
+{
+  return vecs[0];
+}
+template<> EIGEN_STRONG_INLINE Packet2cf preduxp<Packet2cf>(const Packet2cf* vecs)
+{
+  PacketBlock<Packet2cf,2> transpose;
+  transpose.packet[0] = vecs[0];
+  transpose.packet[1] = vecs[1];
+  ptranspose(transpose);
+
+  return padd<Packet2cf>(transpose.packet[0], transpose.packet[1]);
+} 
+
+template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet1cd>(const Packet1cd& a)
+{
+  return pfirst(a);
+}
+template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet2cf>(const Packet2cf& a)
+{
+  std::complex<float> res;
+  Packet1cd b = pmul<Packet1cd>(a.cd[0], a.cd[1]);
+  vec_st2f(b.v, (float*)&res);
+  return res;
+}
+
+template<int Offset>
+struct palign_impl<Offset,Packet1cd>
+{
+  static EIGEN_STRONG_INLINE void run(Packet1cd& /*first*/, const Packet1cd& /*second*/)
+  {
+    // FIXME is it sure we never have to align a Packet1cd?
+    // Even though a std::complex<double> has 16 bytes, it is not necessarily aligned on a 16 bytes boundary...
+  }
+};
+
+template<int Offset>
+struct palign_impl<Offset,Packet2cf>
+{
+  static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second)
+  {
+    if (Offset == 1) {
+      first.cd[0] = first.cd[1];
+      first.cd[1] = second.cd[0];
+    }
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, false,true>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return internal::pmul(a, pconj(b));
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, true,false>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return internal::pmul(pconj(a), b);
+  }
+};
+
+template<> struct conj_helper<Packet1cd, Packet1cd, true,true>
+{
+  EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
+  {
+    return pconj(internal::pmul(a, b));
+  }
+};
+
+template<> struct conj_helper<Packet2cf, Packet2cf, false,true>
+{
+  EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet2cf& y, const Packet2cf& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& a, const Packet2cf& b) const
+  {
+    return internal::pmul(a, pconj(b));
+  }
+};
+
+template<> struct conj_helper<Packet2cf, Packet2cf, true,false>
+{
+  EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet2cf& y, const Packet2cf& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& a, const Packet2cf& b) const
+  {
+    return internal::pmul(pconj(a), b);
+  }
+};
+
+template<> struct conj_helper<Packet2cf, Packet2cf, true,true>
+{
+  EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet2cf& y, const Packet2cf& c) const
+  { return padd(pmul(x,y),c); }
+
+  EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& a, const Packet2cf& b) const
+  {
+    return pconj(internal::pmul(a, b));
+  }
+};
+
+template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
+{
+  // TODO optimize it for AltiVec
+  Packet1cd res = conj_helper<Packet1cd,Packet1cd,false,true>().pmul(a,b);
+  Packet2d s = vec_madd(b.v, b.v, p2d_ZERO_);
+  return Packet1cd(pdiv(res.v, s + vec_perm(s, s, p16uc_REVERSE64)));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b)
+{
+  // TODO optimize it for AltiVec
+  Packet2cf res;
+  res.cd[0] = pdiv<Packet1cd>(a.cd[0], b.cd[0]);
+  res.cd[1] = pdiv<Packet1cd>(a.cd[1], b.cd[1]);
+  return res;
+}
+
+EIGEN_STRONG_INLINE Packet1cd pcplxflip/*<Packet1cd>*/(const Packet1cd& x)
+{
+  return Packet1cd(preverse(Packet2d(x.v)));
+}
+
+EIGEN_STRONG_INLINE Packet2cf pcplxflip/*<Packet2cf>*/(const Packet2cf& x)
+{
+  Packet2cf res;
+  res.cd[0] = pcplxflip(x.cd[0]);
+  res.cd[1] = pcplxflip(x.cd[1]);
+  return res;
+}
+
+EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet1cd,2>& kernel)
+{
+  Packet2d tmp = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_HI);
+  kernel.packet[1].v = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_LO);
+  kernel.packet[0].v = tmp;
+}
+
+EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet2cf,2>& kernel)
+{
+  Packet1cd tmp = kernel.packet[0].cd[1];
+  kernel.packet[0].cd[1] = kernel.packet[1].cd[0];
+  kernel.packet[1].cd[0] = tmp;
+}
+
+template<> EIGEN_STRONG_INLINE Packet2cf pblend(const Selector<2>& ifPacket, const Packet2cf& thenPacket, const Packet2cf& elsePacket) {
+  Packet2cf result;
+  const Selector<4> ifPacket4 = { ifPacket.select[0], ifPacket.select[0], ifPacket.select[1], ifPacket.select[1] };
+  result.v = pblend<Packet4f>(ifPacket4, thenPacket.v, elsePacket.v);
+  return result;
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_COMPLEX32_ALTIVEC_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/ZVector/MathFunctions.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/ZVector/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/ZVector/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/ZVector/MathFunctions.h
@@ -0,0 +1,137 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2007 Julien Pommier
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2016 Konstantinos Margaritis <markos@freevec.org>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/* The sin, cos, exp, and log functions of this file come from
+ * Julien Pommier's sse math library: http://gruntthepeon.free.fr/ssemath/
+ */
+
+#ifndef EIGEN_MATH_FUNCTIONS_ALTIVEC_H
+#define EIGEN_MATH_FUNCTIONS_ALTIVEC_H
+
+namespace Eigen {
+
+namespace internal {
+
+static _EIGEN_DECLARE_CONST_Packet2d(1 , 1.0);
+static _EIGEN_DECLARE_CONST_Packet2d(2 , 2.0);
+static _EIGEN_DECLARE_CONST_Packet2d(half, 0.5);
+
+static _EIGEN_DECLARE_CONST_Packet2d(exp_hi,  709.437);
+static _EIGEN_DECLARE_CONST_Packet2d(exp_lo, -709.436139303);
+
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_LOG2EF, 1.4426950408889634073599);
+
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p0, 1.26177193074810590878e-4);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p1, 3.02994407707441961300e-2);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p2, 9.99999999999999999910e-1);
+
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q0, 3.00198505138664455042e-6);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q1, 2.52448340349684104192e-3);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q2, 2.27265548208155028766e-1);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q3, 2.00000000000000000009e0);
+
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C1, 0.693145751953125);
+static _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d pexp<Packet2d>(const Packet2d& _x)
+{
+  Packet2d x = _x;
+
+  Packet2d tmp, fx;
+  Packet2l emm0;
+
+  // clamp x
+  x = pmax(pmin(x, p2d_exp_hi), p2d_exp_lo);
+  /* express exp(x) as exp(g + n*log(2)) */
+  fx = pmadd(p2d_cephes_LOG2EF, x, p2d_half);
+
+  fx = vec_floor(fx);
+
+  tmp = pmul(fx, p2d_cephes_exp_C1);
+  Packet2d z = pmul(fx, p2d_cephes_exp_C2);
+  x = psub(x, tmp);
+  x = psub(x, z);
+
+  Packet2d x2 = pmul(x,x);
+
+  Packet2d px = p2d_cephes_exp_p0;
+  px = pmadd(px, x2, p2d_cephes_exp_p1);
+  px = pmadd(px, x2, p2d_cephes_exp_p2);
+  px = pmul (px, x);
+
+  Packet2d qx = p2d_cephes_exp_q0;
+  qx = pmadd(qx, x2, p2d_cephes_exp_q1);
+  qx = pmadd(qx, x2, p2d_cephes_exp_q2);
+  qx = pmadd(qx, x2, p2d_cephes_exp_q3);
+
+  x = pdiv(px,psub(qx,px));
+  x = pmadd(p2d_2,x,p2d_1);
+
+  // build 2^n
+  emm0 = vec_ctsl(fx, 0);
+
+  static const Packet2l p2l_1023 = { 1023, 1023 };
+  static const Packet2ul p2ul_52 = { 52, 52 };
+
+  emm0 = emm0 + p2l_1023;
+  emm0 = emm0 << reinterpret_cast<Packet2l>(p2ul_52);
+
+  // Altivec's max & min operators just drop silent NaNs. Check NaNs in 
+  // inputs and return them unmodified.
+  Packet2ul isnumber_mask = reinterpret_cast<Packet2ul>(vec_cmpeq(_x, _x));
+  return vec_sel(_x, pmax(pmul(x, reinterpret_cast<Packet2d>(emm0)), _x),
+                 isnumber_mask);
+}
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f pexp<Packet4f>(const Packet4f& x)
+{
+  Packet4f res;
+  res.v4f[0] = pexp<Packet2d>(x.v4f[0]);
+  res.v4f[1] = pexp<Packet2d>(x.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d psqrt<Packet2d>(const Packet2d& x)
+{
+  return  __builtin_s390_vfsqdb(x);
+}
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f psqrt<Packet4f>(const Packet4f& x)
+{
+  Packet4f res;
+  res.v4f[0] = psqrt<Packet2d>(x.v4f[0]);
+  res.v4f[1] = psqrt<Packet2d>(x.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d prsqrt<Packet2d>(const Packet2d& x) {
+  // Unfortunately we can't use the much faster mm_rqsrt_pd since it only provides an approximation.
+  return pset1<Packet2d>(1.0) / psqrt<Packet2d>(x);
+}
+
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet4f prsqrt<Packet4f>(const Packet4f& x) {
+  Packet4f res;
+  res.v4f[0] = prsqrt<Packet2d>(x.v4f[0]);
+  res.v4f[1] = prsqrt<Packet2d>(x.v4f[1]);
+  return res;
+}
+
+}  // end namespace internal
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_MATH_FUNCTIONS_ALTIVEC_H

ADDED   3rd_party/eigen/Eigen/src/Core/arch/ZVector/PacketMath.h
Index: 3rd_party/eigen/Eigen/src/Core/arch/ZVector/PacketMath.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/arch/ZVector/PacketMath.h
+++ 3rd_party/eigen/Eigen/src/Core/arch/ZVector/PacketMath.h
@@ -0,0 +1,945 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Konstantinos Margaritis <markos@freevec.org>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_PACKET_MATH_ZVECTOR_H
+#define EIGEN_PACKET_MATH_ZVECTOR_H
+
+#include <stdint.h>
+
+namespace Eigen {
+
+namespace internal {
+
+#ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
+#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 4
+#endif
+
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+#endif
+
+#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
+#define EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
+#endif
+
+#ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
+#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS  16
+#endif
+
+typedef __vector int                 Packet4i;
+typedef __vector unsigned int        Packet4ui;
+typedef __vector __bool int          Packet4bi;
+typedef __vector short int           Packet8i;
+typedef __vector unsigned char       Packet16uc;
+typedef __vector double              Packet2d;
+typedef __vector unsigned long long  Packet2ul;
+typedef __vector long long           Packet2l;
+
+typedef struct {
+	Packet2d  v4f[2];
+} Packet4f;
+
+typedef union {
+  int32_t   i[4];
+  uint32_t ui[4];
+  int64_t   l[2];
+  uint64_t ul[2];
+  double    d[2];
+  Packet4i  v4i;
+  Packet4ui v4ui;
+  Packet2l  v2l;
+  Packet2ul v2ul;
+  Packet2d  v2d;
+} Packet;
+
+// We don't want to write the same code all the time, but we need to reuse the constants
+// and it doesn't really work to declare them global, so we define macros instead
+
+#define _EIGEN_DECLARE_CONST_FAST_Packet4i(NAME,X) \
+  Packet4i p4i_##NAME = reinterpret_cast<Packet4i>(vec_splat_s32(X))
+
+#define _EIGEN_DECLARE_CONST_FAST_Packet2d(NAME,X) \
+  Packet2d p2d_##NAME = reinterpret_cast<Packet2d>(vec_splat_s64(X))
+
+#define _EIGEN_DECLARE_CONST_FAST_Packet2l(NAME,X) \
+  Packet2l p2l_##NAME = reinterpret_cast<Packet2l>(vec_splat_s64(X))
+
+#define _EIGEN_DECLARE_CONST_Packet4i(NAME,X) \
+  Packet4i p4i_##NAME = pset1<Packet4i>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet2d(NAME,X) \
+  Packet2d p2d_##NAME = pset1<Packet2d>(X)
+
+#define _EIGEN_DECLARE_CONST_Packet2l(NAME,X) \
+  Packet2l p2l_##NAME = pset1<Packet2l>(X)
+
+// These constants are endian-agnostic
+//static _EIGEN_DECLARE_CONST_FAST_Packet4i(ZERO, 0); //{ 0, 0, 0, 0,}
+static _EIGEN_DECLARE_CONST_FAST_Packet4i(ONE, 1); //{ 1, 1, 1, 1}
+
+static _EIGEN_DECLARE_CONST_FAST_Packet2d(ZERO, 0);
+static _EIGEN_DECLARE_CONST_FAST_Packet2l(ZERO, 0);
+static _EIGEN_DECLARE_CONST_FAST_Packet2l(ONE, 1);
+
+static Packet2d p2d_ONE = { 1.0, 1.0 }; 
+static Packet2d p2d_ZERO_ = { -0.0, -0.0 };
+
+static Packet4i p4i_COUNTDOWN = { 0, 1, 2, 3 };
+static Packet4f p4f_COUNTDOWN = { 0.0, 1.0, 2.0, 3.0 };
+static Packet2d p2d_COUNTDOWN = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet16uc>(p2d_ZERO), reinterpret_cast<Packet16uc>(p2d_ONE), 8));
+
+static Packet16uc p16uc_PSET64_HI = { 0,1,2,3, 4,5,6,7, 0,1,2,3, 4,5,6,7 };
+static Packet16uc p16uc_DUPLICATE32_HI = { 0,1,2,3, 0,1,2,3, 4,5,6,7, 4,5,6,7 };
+
+// Mask alignment
+#define _EIGEN_MASK_ALIGNMENT	0xfffffffffffffff0
+
+#define _EIGEN_ALIGNED_PTR(x)	((std::ptrdiff_t)(x) & _EIGEN_MASK_ALIGNMENT)
+
+// Handle endianness properly while loading constants
+// Define global static constants:
+
+static Packet16uc p16uc_FORWARD =   { 0,1,2,3, 4,5,6,7, 8,9,10,11, 12,13,14,15 };
+static Packet16uc p16uc_REVERSE32 = { 12,13,14,15, 8,9,10,11, 4,5,6,7, 0,1,2,3 };
+static Packet16uc p16uc_REVERSE64 = { 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
+
+static Packet16uc p16uc_PSET32_WODD   = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 };
+static Packet16uc p16uc_PSET32_WEVEN  = vec_sld(p16uc_DUPLICATE32_HI, (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
+/*static Packet16uc p16uc_HALF64_0_16 = vec_sld((Packet16uc)p4i_ZERO, vec_splat((Packet16uc) vec_abs(p4i_MINUS16), 3), 8);      //{ 0,0,0,0, 0,0,0,0, 16,16,16,16, 16,16,16,16};
+
+static Packet16uc p16uc_PSET64_HI = (Packet16uc) vec_mergeh((Packet4ui)p16uc_PSET32_WODD, (Packet4ui)p16uc_PSET32_WEVEN);     //{ 0,1,2,3, 4,5,6,7, 0,1,2,3, 4,5,6,7 };*/
+static Packet16uc p16uc_PSET64_LO = (Packet16uc) vec_mergel((Packet4ui)p16uc_PSET32_WODD, (Packet4ui)p16uc_PSET32_WEVEN);     //{ 8,9,10,11, 12,13,14,15, 8,9,10,11, 12,13,14,15 };
+/*static Packet16uc p16uc_TRANSPOSE64_HI = vec_add(p16uc_PSET64_HI, p16uc_HALF64_0_16);                                         //{ 0,1,2,3, 4,5,6,7, 16,17,18,19, 20,21,22,23};
+static Packet16uc p16uc_TRANSPOSE64_LO = vec_add(p16uc_PSET64_LO, p16uc_HALF64_0_16);                                         //{ 8,9,10,11, 12,13,14,15, 24,25,26,27, 28,29,30,31};*/
+static Packet16uc p16uc_TRANSPOSE64_HI = { 0,1,2,3, 4,5,6,7, 16,17,18,19, 20,21,22,23};
+static Packet16uc p16uc_TRANSPOSE64_LO = { 8,9,10,11, 12,13,14,15, 24,25,26,27, 28,29,30,31};
+
+//static Packet16uc p16uc_COMPLEX32_REV = vec_sld(p16uc_REVERSE32, p16uc_REVERSE32, 8);                                         //{ 4,5,6,7, 0,1,2,3, 12,13,14,15, 8,9,10,11 };
+
+//static Packet16uc p16uc_COMPLEX32_REV2 = vec_sld(p16uc_FORWARD, p16uc_FORWARD, 8);                                            //{ 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
+
+
+#if EIGEN_HAS_BUILTIN(__builtin_prefetch) || EIGEN_COMP_GNUC
+  #define EIGEN_ZVECTOR_PREFETCH(ADDR) __builtin_prefetch(ADDR);
+#else
+  #define EIGEN_ZVECTOR_PREFETCH(ADDR) asm( "   pfd [%[addr]]\n" :: [addr] "r" (ADDR) : "cc" );
+#endif
+
+template<> struct packet_traits<int>    : default_packet_traits
+{
+  typedef Packet4i type;
+  typedef Packet4i half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size = 4,
+    HasHalfPacket = 0,
+
+    HasAdd  = 1,
+    HasSub  = 1,
+    HasMul  = 1,
+    HasDiv  = 1,
+    HasBlend = 1
+  };
+};
+
+template<> struct packet_traits<float> : default_packet_traits
+{
+  typedef Packet4f type;
+  typedef Packet4f half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=4,
+    HasHalfPacket = 0,
+
+    HasAdd  = 1,
+    HasSub  = 1,
+    HasMul  = 1,
+    HasDiv  = 1,
+    HasMin  = 1,
+    HasMax  = 1,
+    HasAbs  = 1,
+    HasSin  = 0,
+    HasCos  = 0,
+    HasLog  = 0,
+    HasExp  = 1,
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasRound = 1,
+    HasFloor = 1,
+    HasCeil = 1,
+    HasNegate = 1,
+    HasBlend = 1
+  };
+};
+
+template<> struct packet_traits<double> : default_packet_traits
+{
+  typedef Packet2d type;
+  typedef Packet2d half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    size=2,
+    HasHalfPacket = 1,
+
+    HasAdd  = 1,
+    HasSub  = 1,
+    HasMul  = 1,
+    HasDiv  = 1,
+    HasMin  = 1,
+    HasMax  = 1,
+    HasAbs  = 1,
+    HasSin  = 0,
+    HasCos  = 0,
+    HasLog  = 0,
+    HasExp  = 1,
+    HasSqrt = 1,
+    HasRsqrt = 1,
+    HasRound = 1,
+    HasFloor = 1,
+    HasCeil = 1,
+    HasNegate = 1,
+    HasBlend = 1
+  };
+};
+
+template<> struct unpacket_traits<Packet4i> { typedef int    type; enum {size=4, alignment=Aligned16}; typedef Packet4i half; };
+template<> struct unpacket_traits<Packet4f> { typedef float  type; enum {size=4, alignment=Aligned16}; typedef Packet4f half; };
+template<> struct unpacket_traits<Packet2d> { typedef double type; enum {size=2, alignment=Aligned16}; typedef Packet2d half; };
+
+/* Forward declaration */
+EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet4f,4>& kernel);
+ 
+inline std::ostream & operator <<(std::ostream & s, const Packet4i & v)
+{
+  Packet vt;
+  vt.v4i = v;
+  s << vt.i[0] << ", " << vt.i[1] << ", " << vt.i[2] << ", " << vt.i[3];
+  return s;
+}
+
+inline std::ostream & operator <<(std::ostream & s, const Packet4ui & v)
+{
+  Packet vt;
+  vt.v4ui = v;
+  s << vt.ui[0] << ", " << vt.ui[1] << ", " << vt.ui[2] << ", " << vt.ui[3];
+  return s;
+}
+
+inline std::ostream & operator <<(std::ostream & s, const Packet2l & v)
+{
+  Packet vt;
+  vt.v2l = v;
+  s << vt.l[0] << ", " << vt.l[1];
+  return s;
+}
+
+inline std::ostream & operator <<(std::ostream & s, const Packet2ul & v)
+{
+  Packet vt;
+  vt.v2ul = v;
+  s << vt.ul[0] << ", " << vt.ul[1] ;
+  return s;
+}
+
+inline std::ostream & operator <<(std::ostream & s, const Packet2d & v)
+{
+  Packet vt;
+  vt.v2d = v;
+  s << vt.d[0] << ", " << vt.d[1];
+  return s;
+}
+
+/* Helper function to simulate a vec_splat_packet4f
+ */
+template<int element> EIGEN_STRONG_INLINE Packet4f vec_splat_packet4f(const Packet4f&   from)
+{
+  Packet4f splat;
+  switch (element) {
+  case 0:
+    splat.v4f[0] = vec_splat(from.v4f[0], 0);
+    splat.v4f[1] = splat.v4f[0];
+    break;
+  case 1:
+    splat.v4f[0] = vec_splat(from.v4f[0], 1);
+    splat.v4f[1] = splat.v4f[0];
+    break;
+  case 2:
+    splat.v4f[0] = vec_splat(from.v4f[1], 0);
+    splat.v4f[1] = splat.v4f[0];
+    break;
+  case 3:
+    splat.v4f[0] = vec_splat(from.v4f[1], 1);
+    splat.v4f[1] = splat.v4f[0];
+    break;
+  }
+  return splat;
+}
+
+template<int Offset>
+struct palign_impl<Offset,Packet4i>
+{
+  static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
+  {
+    switch (Offset % 4) {
+    case 1:
+      first = vec_sld(first, second, 4); break;
+    case 2:
+      first = vec_sld(first, second, 8); break;
+    case 3:
+      first = vec_sld(first, second, 12); break;
+    }
+  }
+};
+
+/* This is a tricky one, we have to translate float alignment to vector elements of sizeof double
+ */
+template<int Offset>
+struct palign_impl<Offset,Packet4f>
+{
+  static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
+  {
+    switch (Offset % 4) {
+    case 1:
+      first.v4f[0] = vec_sld(first.v4f[0], first.v4f[1], 8);
+      first.v4f[1] = vec_sld(first.v4f[1], second.v4f[0], 8);
+      break;
+    case 2:
+      first.v4f[0] = first.v4f[1];
+      first.v4f[1] = second.v4f[0];
+      break;
+    case 3:
+      first.v4f[0] = vec_sld(first.v4f[1],  second.v4f[0], 8);
+      first.v4f[1] = vec_sld(second.v4f[0], second.v4f[1], 8);
+      break;
+    }
+  }
+};
+
+
+template<int Offset>
+struct palign_impl<Offset,Packet2d>
+{
+  static EIGEN_STRONG_INLINE void run(Packet2d& first, const Packet2d& second)
+  {
+    if (Offset == 1)
+      first = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(first), reinterpret_cast<Packet4i>(second), 8));
+  }
+};
+
+template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int*     from)
+{
+  // FIXME: No intrinsic yet
+  EIGEN_DEBUG_ALIGNED_LOAD
+  Packet *vfrom;
+  vfrom = (Packet *) from;
+  return vfrom->v4i;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float*   from)
+{
+  // FIXME: No intrinsic yet
+  EIGEN_DEBUG_ALIGNED_LOAD
+  Packet4f vfrom;
+  vfrom.v4f[0] = vec_ld2f(&from[0]);
+  vfrom.v4f[1] = vec_ld2f(&from[2]);
+  return vfrom;
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pload<Packet2d>(const double* from)
+{
+  // FIXME: No intrinsic yet
+  EIGEN_DEBUG_ALIGNED_LOAD
+  Packet *vfrom;
+  vfrom = (Packet *) from;
+  return vfrom->v2d;
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<int>(int*       to, const Packet4i& from)
+{
+  // FIXME: No intrinsic yet
+  EIGEN_DEBUG_ALIGNED_STORE
+  Packet *vto;
+  vto = (Packet *) to;
+  vto->v4i = from;
+}
+
+template<> EIGEN_STRONG_INLINE void pstore<float>(float*   to, const Packet4f& from)
+{
+  // FIXME: No intrinsic yet
+  EIGEN_DEBUG_ALIGNED_STORE
+  vec_st2f(from.v4f[0], &to[0]);
+  vec_st2f(from.v4f[1], &to[2]);
+}
+
+
+template<> EIGEN_STRONG_INLINE void pstore<double>(double*   to, const Packet2d& from)
+{
+  // FIXME: No intrinsic yet
+  EIGEN_DEBUG_ALIGNED_STORE
+  Packet *vto;
+  vto = (Packet *) to;
+  vto->v2d = from;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int&    from)
+{
+  return vec_splats(from);
+}
+template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double& from) {
+  return vec_splats(from);
+}
+template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float&    from)
+{
+  Packet4f to;
+  to.v4f[0] = pset1<Packet2d>(static_cast<const double&>(from));
+  to.v4f[1] = to.v4f[0];
+  return to;
+}
+
+template<> EIGEN_STRONG_INLINE void
+pbroadcast4<Packet4i>(const int *a,
+                      Packet4i& a0, Packet4i& a1, Packet4i& a2, Packet4i& a3)
+{
+  a3 = pload<Packet4i>(a);
+  a0 = vec_splat(a3, 0);
+  a1 = vec_splat(a3, 1);
+  a2 = vec_splat(a3, 2);
+  a3 = vec_splat(a3, 3);
+}
+
+template<> EIGEN_STRONG_INLINE void
+pbroadcast4<Packet4f>(const float *a,
+                      Packet4f& a0, Packet4f& a1, Packet4f& a2, Packet4f& a3)
+{
+  a3 = pload<Packet4f>(a);
+  a0 = vec_splat_packet4f<0>(a3);
+  a1 = vec_splat_packet4f<1>(a3);
+  a2 = vec_splat_packet4f<2>(a3);
+  a3 = vec_splat_packet4f<3>(a3);
+}
+
+template<> EIGEN_STRONG_INLINE void
+pbroadcast4<Packet2d>(const double *a,
+                      Packet2d& a0, Packet2d& a1, Packet2d& a2, Packet2d& a3)
+{
+  a1 = pload<Packet2d>(a);
+  a0 = vec_splat(a1, 0);
+  a1 = vec_splat(a1, 1);
+  a3 = pload<Packet2d>(a+2);
+  a2 = vec_splat(a3, 0);
+  a3 = vec_splat(a3, 1);
+}
+
+template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, Index stride)
+{
+  int EIGEN_ALIGN16 ai[4];
+  ai[0] = from[0*stride];
+  ai[1] = from[1*stride];
+  ai[2] = from[2*stride];
+  ai[3] = from[3*stride];
+ return pload<Packet4i>(ai);
+}
+
+template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, Index stride)
+{
+  float EIGEN_ALIGN16 ai[4];
+  ai[0] = from[0*stride];
+  ai[1] = from[1*stride];
+  ai[2] = from[2*stride];
+  ai[3] = from[3*stride];
+ return pload<Packet4f>(ai);
+}
+
+template<> EIGEN_DEVICE_FUNC inline Packet2d pgather<double, Packet2d>(const double* from, Index stride)
+{
+  double EIGEN_ALIGN16 af[2];
+  af[0] = from[0*stride];
+  af[1] = from[1*stride];
+ return pload<Packet2d>(af);
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, Index stride)
+{
+  int EIGEN_ALIGN16 ai[4];
+  pstore<int>((int *)ai, from);
+  to[0*stride] = ai[0];
+  to[1*stride] = ai[1];
+  to[2*stride] = ai[2];
+  to[3*stride] = ai[3];
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, Index stride)
+{
+  float EIGEN_ALIGN16 ai[4];
+  pstore<float>((float *)ai, from);
+  to[0*stride] = ai[0];
+  to[1*stride] = ai[1];
+  to[2*stride] = ai[2];
+  to[3*stride] = ai[3];
+}
+
+template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to, const Packet2d& from, Index stride)
+{
+  double EIGEN_ALIGN16 af[2];
+  pstore<double>(af, from);
+  to[0*stride] = af[0];
+  to[1*stride] = af[1];
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i padd<Packet4i>(const Packet4i& a, const Packet4i& b) { return (a + b); }
+template<> EIGEN_STRONG_INLINE Packet4f padd<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f c;
+  c.v4f[0] = a.v4f[0] + b.v4f[0];
+  c.v4f[1] = a.v4f[1] + b.v4f[1];
+  return c;
+}
+template<> EIGEN_STRONG_INLINE Packet2d padd<Packet2d>(const Packet2d& a, const Packet2d& b) { return (a + b); }
+
+template<> EIGEN_STRONG_INLINE Packet4i psub<Packet4i>(const Packet4i& a, const Packet4i& b) { return (a - b); }
+template<> EIGEN_STRONG_INLINE Packet4f psub<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f c;
+  c.v4f[0] = a.v4f[0] - b.v4f[0];
+  c.v4f[1] = a.v4f[1] - b.v4f[1];
+  return c;
+}
+template<> EIGEN_STRONG_INLINE Packet2d psub<Packet2d>(const Packet2d& a, const Packet2d& b) { return (a - b); }
+
+template<> EIGEN_STRONG_INLINE Packet4i pmul<Packet4i>(const Packet4i& a, const Packet4i& b) { return (a * b); }
+template<> EIGEN_STRONG_INLINE Packet4f pmul<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f c;
+  c.v4f[0] = a.v4f[0] * b.v4f[0];
+  c.v4f[1] = a.v4f[1] * b.v4f[1];
+  return c;
+}
+template<> EIGEN_STRONG_INLINE Packet2d pmul<Packet2d>(const Packet2d& a, const Packet2d& b) { return (a * b); }
+
+template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& a, const Packet4i& b) { return (a / b); }
+template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f c;
+  c.v4f[0] = a.v4f[0] / b.v4f[0];
+  c.v4f[1] = a.v4f[1] / b.v4f[1];
+  return c;
+}
+template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return (a / b); }
+
+template<> EIGEN_STRONG_INLINE Packet4i pnegate(const Packet4i& a) { return (-a); }
+template<> EIGEN_STRONG_INLINE Packet4f pnegate(const Packet4f& a)
+{
+  Packet4f c;
+  c.v4f[0] = -a.v4f[0];
+  c.v4f[1] = -a.v4f[1];
+  return c;
+}
+template<> EIGEN_STRONG_INLINE Packet2d pnegate(const Packet2d& a) { return (-a); }
+
+template<> EIGEN_STRONG_INLINE Packet4i pconj(const Packet4i& a) { return a; }
+template<> EIGEN_STRONG_INLINE Packet4f pconj(const Packet4f& a) { return a; }
+template<> EIGEN_STRONG_INLINE Packet2d pconj(const Packet2d& a) { return a; }
+
+template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return padd<Packet4i>(pmul<Packet4i>(a, b), c); }
+template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c)
+{
+  Packet4f res;
+  res.v4f[0] = vec_madd(a.v4f[0], b.v4f[0], c.v4f[0]);
+  res.v4f[1] = vec_madd(a.v4f[1], b.v4f[1], c.v4f[1]);
+  return res;
+}
+template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return vec_madd(a, b, c); }
+
+template<> EIGEN_STRONG_INLINE Packet4i plset<Packet4i>(const int& a)    { return padd<Packet4i>(pset1<Packet4i>(a), p4i_COUNTDOWN); }
+template<> EIGEN_STRONG_INLINE Packet4f plset<Packet4f>(const float& a)  { return padd<Packet4f>(pset1<Packet4f>(a), p4f_COUNTDOWN); }
+template<> EIGEN_STRONG_INLINE Packet2d plset<Packet2d>(const double& a) { return padd<Packet2d>(pset1<Packet2d>(a), p2d_COUNTDOWN); }
+
+template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_min(a, b); }
+template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_min(a, b); }
+template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f res;
+  res.v4f[0] = pmin(a.v4f[0], b.v4f[0]);
+  res.v4f[1] = pmin(a.v4f[1], b.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pmax<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_max(a, b); }
+template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_max(a, b); }
+template<> EIGEN_STRONG_INLINE Packet4f pmax<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f res;
+  res.v4f[0] = pmax(a.v4f[0], b.v4f[0]);
+  res.v4f[1] = pmax(a.v4f[1], b.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pand<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_and(a, b); }
+template<> EIGEN_STRONG_INLINE Packet2d pand<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, b); }
+template<> EIGEN_STRONG_INLINE Packet4f pand<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f res;
+  res.v4f[0] = pand(a.v4f[0], b.v4f[0]);
+  res.v4f[1] = pand(a.v4f[1], b.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i por<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_or(a, b); }
+template<> EIGEN_STRONG_INLINE Packet2d por<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_or(a, b); }
+template<> EIGEN_STRONG_INLINE Packet4f por<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f res;
+  res.v4f[0] = pand(a.v4f[0], b.v4f[0]);
+  res.v4f[1] = pand(a.v4f[1], b.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pxor<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_xor(a, b); }
+template<> EIGEN_STRONG_INLINE Packet2d pxor<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_xor(a, b); }
+template<> EIGEN_STRONG_INLINE Packet4f pxor<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f res;
+  res.v4f[0] = pand(a.v4f[0], b.v4f[0]);
+  res.v4f[1] = pand(a.v4f[1], b.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pandnot<Packet4i>(const Packet4i& a, const Packet4i& b) { return pand<Packet4i>(a, vec_nor(b, b)); }
+template<> EIGEN_STRONG_INLINE Packet2d pandnot<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, vec_nor(b, b)); }
+template<> EIGEN_STRONG_INLINE Packet4f pandnot<Packet4f>(const Packet4f& a, const Packet4f& b)
+{
+  Packet4f res;
+  res.v4f[0] = pandnot(a.v4f[0], b.v4f[0]);
+  res.v4f[1] = pandnot(a.v4f[1], b.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f pround<Packet4f>(const Packet4f& a)
+{
+  Packet4f res;
+  res.v4f[0] = vec_round(a.v4f[0]);
+  res.v4f[1] = vec_round(a.v4f[1]);
+  return res;
+}
+template<> EIGEN_STRONG_INLINE Packet2d pround<Packet2d>(const Packet2d& a) { return vec_round(a); }
+template<> EIGEN_STRONG_INLINE Packet4f pceil<Packet4f>(const  Packet4f& a)
+{
+  Packet4f res;
+  res.v4f[0] = vec_ceil(a.v4f[0]);
+  res.v4f[1] = vec_ceil(a.v4f[1]);
+  return res;
+}
+template<> EIGEN_STRONG_INLINE Packet2d pceil<Packet2d>(const  Packet2d& a) { return vec_ceil(a); }
+template<> EIGEN_STRONG_INLINE Packet4f pfloor<Packet4f>(const Packet4f& a)
+{
+  Packet4f res;
+  res.v4f[0] = vec_floor(a.v4f[0]);
+  res.v4f[1] = vec_floor(a.v4f[1]);
+  return res;
+}
+template<> EIGEN_STRONG_INLINE Packet2d pfloor<Packet2d>(const Packet2d& a) { return vec_floor(a); }
+
+template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int*       from) { return pload<Packet4i>(from); }
+template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float*     from) { return pload<Packet4f>(from); }
+template<> EIGEN_STRONG_INLINE Packet2d ploadu<Packet2d>(const double*    from) { return pload<Packet2d>(from); }
+
+
+template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int*     from)
+{
+  Packet4i p = pload<Packet4i>(from);
+  return vec_perm(p, p, p16uc_DUPLICATE32_HI);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float*    from)
+{
+  Packet4f p = pload<Packet4f>(from);
+  p.v4f[1] = vec_splat(p.v4f[0], 1);
+  p.v4f[0] = vec_splat(p.v4f[0], 0);
+  return p;
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double*   from)
+{
+  Packet2d p = pload<Packet2d>(from);
+  return vec_perm(p, p, p16uc_PSET64_HI);
+}
+
+template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*        to, const Packet4i& from) { pstore<int>(to, from); }
+template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*    to, const Packet4f& from) { pstore<float>(to, from); }
+template<> EIGEN_STRONG_INLINE void pstoreu<double>(double*  to, const Packet2d& from) { pstore<double>(to, from); }
+
+template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*       addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
+template<> EIGEN_STRONG_INLINE void prefetch<float>(const float*   addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
+template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { EIGEN_ZVECTOR_PREFETCH(addr); }
+
+template<> EIGEN_STRONG_INLINE int    pfirst<Packet4i>(const Packet4i& a) { int    EIGEN_ALIGN16 x[4]; pstore(x, a); return x[0]; }
+template<> EIGEN_STRONG_INLINE float  pfirst<Packet4f>(const Packet4f& a) { float  EIGEN_ALIGN16 x[2]; vec_st2f(a.v4f[0], &x[0]); return x[0]; }
+template<> EIGEN_STRONG_INLINE double pfirst<Packet2d>(const Packet2d& a) { double EIGEN_ALIGN16 x[2]; pstore(x, a); return x[0]; }
+
+template<> EIGEN_STRONG_INLINE Packet4i preverse(const Packet4i& a)
+{
+  return reinterpret_cast<Packet4i>(vec_perm(reinterpret_cast<Packet16uc>(a), reinterpret_cast<Packet16uc>(a), p16uc_REVERSE32));
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d preverse(const Packet2d& a)
+{
+  return reinterpret_cast<Packet2d>(vec_perm(reinterpret_cast<Packet16uc>(a), reinterpret_cast<Packet16uc>(a), p16uc_REVERSE64));
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f preverse(const Packet4f& a)
+{
+  Packet4f rev;
+  rev.v4f[0] = preverse<Packet2d>(a.v4f[1]);
+  rev.v4f[1] = preverse<Packet2d>(a.v4f[0]);
+  return rev;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pabs<Packet4i>(const Packet4i& a) { return vec_abs(a); }
+template<> EIGEN_STRONG_INLINE Packet2d pabs<Packet2d>(const Packet2d& a) { return vec_abs(a); }
+template<> EIGEN_STRONG_INLINE Packet4f pabs<Packet4f>(const Packet4f& a)
+{
+  Packet4f res;
+  res.v4f[0] = pabs(a.v4f[0]);
+  res.v4f[1] = pabs(a.v4f[1]);
+  return res;
+}
+
+template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
+{
+  Packet4i b, sum;
+  b   = vec_sld(a, a, 8);
+  sum = padd<Packet4i>(a, b);
+  b   = vec_sld(sum, sum, 4);
+  sum = padd<Packet4i>(sum, b);
+  return pfirst(sum);
+}
+
+template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a)
+{
+  Packet2d b, sum;
+  b   = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(a), reinterpret_cast<Packet4i>(a), 8));
+  sum = padd<Packet2d>(a, b);
+  return pfirst(sum);
+}
+template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
+{
+  Packet2d sum;
+  sum = padd<Packet2d>(a.v4f[0], a.v4f[1]);
+  double first = predux<Packet2d>(sum);
+  return static_cast<float>(first);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
+{
+  Packet4i v[4], sum[4];
+
+  // It's easier and faster to transpose then add as columns
+  // Check: http://www.freevec.org/function/matrix_4x4_transpose_floats for explanation
+  // Do the transpose, first set of moves
+  v[0] = vec_mergeh(vecs[0], vecs[2]);
+  v[1] = vec_mergel(vecs[0], vecs[2]);
+  v[2] = vec_mergeh(vecs[1], vecs[3]);
+  v[3] = vec_mergel(vecs[1], vecs[3]);
+  // Get the resulting vectors
+  sum[0] = vec_mergeh(v[0], v[2]);
+  sum[1] = vec_mergel(v[0], v[2]);
+  sum[2] = vec_mergeh(v[1], v[3]);
+  sum[3] = vec_mergel(v[1], v[3]);
+
+  // Now do the summation:
+  // Lines 0+1
+  sum[0] = padd<Packet4i>(sum[0], sum[1]);
+  // Lines 2+3
+  sum[1] = padd<Packet4i>(sum[2], sum[3]);
+  // Add the results
+  sum[0] = padd<Packet4i>(sum[0], sum[1]);
+
+  return sum[0];
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
+{
+  Packet2d v[2], sum;
+  v[0] = padd<Packet2d>(vecs[0], reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(vecs[0]), reinterpret_cast<Packet4ui>(vecs[0]), 8)));
+  v[1] = padd<Packet2d>(vecs[1], reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(vecs[1]), reinterpret_cast<Packet4ui>(vecs[1]), 8)));
+ 
+  sum = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4ui>(v[0]), reinterpret_cast<Packet4ui>(v[1]), 8));
+
+  return sum;
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
+{
+  PacketBlock<Packet4f,4> transpose;
+  transpose.packet[0] = vecs[0];
+  transpose.packet[1] = vecs[1];
+  transpose.packet[2] = vecs[2];
+  transpose.packet[3] = vecs[3];
+  ptranspose(transpose);
+
+  Packet4f sum = padd(transpose.packet[0], transpose.packet[1]);
+  sum = padd(sum, transpose.packet[2]);
+  sum = padd(sum, transpose.packet[3]);
+  return sum;
+}
+
+// Other reduction functions:
+// mul
+template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
+{
+  EIGEN_ALIGN16 int aux[4];
+  pstore(aux, a);
+  return aux[0] * aux[1] * aux[2] * aux[3];
+}
+
+template<> EIGEN_STRONG_INLINE double predux_mul<Packet2d>(const Packet2d& a)
+{
+  return pfirst(pmul(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(a), reinterpret_cast<Packet4i>(a), 8))));
+}
+
+template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
+{
+  // Return predux_mul<Packet2d> of the subvectors product
+  return static_cast<float>(pfirst(predux_mul(pmul(a.v4f[0], a.v4f[1]))));
+}
+
+// min
+template<> EIGEN_STRONG_INLINE int predux_min<Packet4i>(const Packet4i& a)
+{
+  Packet4i b, res;
+  b   = pmin<Packet4i>(a, vec_sld(a, a, 8));
+  res = pmin<Packet4i>(b, vec_sld(b, b, 4));
+  return pfirst(res);
+}
+
+template<> EIGEN_STRONG_INLINE double predux_min<Packet2d>(const Packet2d& a)
+{
+  return pfirst(pmin<Packet2d>(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(a), reinterpret_cast<Packet4i>(a), 8))));
+}
+
+template<> EIGEN_STRONG_INLINE float predux_min<Packet4f>(const Packet4f& a)
+{
+  Packet2d b, res;
+  b   = pmin<Packet2d>(a.v4f[0], a.v4f[1]);
+  res = pmin<Packet2d>(b, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(b), reinterpret_cast<Packet4i>(b), 8)));
+  return static_cast<float>(pfirst(res));
+}
+
+// max
+template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
+{
+  Packet4i b, res;
+  b = pmax<Packet4i>(a, vec_sld(a, a, 8));
+  res = pmax<Packet4i>(b, vec_sld(b, b, 4));
+  return pfirst(res);
+}
+
+// max
+template<> EIGEN_STRONG_INLINE double predux_max<Packet2d>(const Packet2d& a)
+{
+  return pfirst(pmax<Packet2d>(a, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(a), reinterpret_cast<Packet4i>(a), 8))));
+}
+
+template<> EIGEN_STRONG_INLINE float predux_max<Packet4f>(const Packet4f& a)
+{
+  Packet2d b, res;
+  b   = pmax<Packet2d>(a.v4f[0], a.v4f[1]);
+  res = pmax<Packet2d>(b, reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4i>(b), reinterpret_cast<Packet4i>(b), 8)));
+  return static_cast<float>(pfirst(res));
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4i,4>& kernel) {
+  Packet4i t0 = vec_mergeh(kernel.packet[0], kernel.packet[2]);
+  Packet4i t1 = vec_mergel(kernel.packet[0], kernel.packet[2]);
+  Packet4i t2 = vec_mergeh(kernel.packet[1], kernel.packet[3]);
+  Packet4i t3 = vec_mergel(kernel.packet[1], kernel.packet[3]);
+  kernel.packet[0] = vec_mergeh(t0, t2);
+  kernel.packet[1] = vec_mergel(t0, t2);
+  kernel.packet[2] = vec_mergeh(t1, t3);
+  kernel.packet[3] = vec_mergel(t1, t3);
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet2d,2>& kernel) {
+  Packet2d t0 = vec_perm(kernel.packet[0], kernel.packet[1], p16uc_TRANSPOSE64_HI);
+  Packet2d t1 = vec_perm(kernel.packet[0], kernel.packet[1], p16uc_TRANSPOSE64_LO);
+  kernel.packet[0] = t0;
+  kernel.packet[1] = t1;
+}
+
+/* Split the Packet4f PacketBlock into 4 Packet2d PacketBlocks and transpose each one
+ */
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet4f,4>& kernel) {
+  PacketBlock<Packet2d,2> t0,t1,t2,t3;
+  // copy top-left 2x2 Packet2d block
+  t0.packet[0] = kernel.packet[0].v4f[0];
+  t0.packet[1] = kernel.packet[1].v4f[0];
+
+  // copy top-right 2x2 Packet2d block
+  t1.packet[0] = kernel.packet[0].v4f[1];
+  t1.packet[1] = kernel.packet[1].v4f[1];
+
+  // copy bottom-left 2x2 Packet2d block
+  t2.packet[0] = kernel.packet[2].v4f[0];
+  t2.packet[1] = kernel.packet[3].v4f[0];
+
+  // copy bottom-right 2x2 Packet2d block
+  t3.packet[0] = kernel.packet[2].v4f[1];
+  t3.packet[1] = kernel.packet[3].v4f[1];
+
+  // Transpose all 2x2 blocks
+  ptranspose(t0);
+  ptranspose(t1);
+  ptranspose(t2);
+  ptranspose(t3);
+
+  // Copy back transposed blocks, but exchange t1 and t2 due to transposition
+  kernel.packet[0].v4f[0] = t0.packet[0];
+  kernel.packet[0].v4f[1] = t2.packet[0];
+  kernel.packet[1].v4f[0] = t0.packet[1];
+  kernel.packet[1].v4f[1] = t2.packet[1];
+  kernel.packet[2].v4f[0] = t1.packet[0];
+  kernel.packet[2].v4f[1] = t3.packet[0];
+  kernel.packet[3].v4f[0] = t1.packet[1];
+  kernel.packet[3].v4f[1] = t3.packet[1];
+}
+
+template<> EIGEN_STRONG_INLINE Packet4i pblend(const Selector<4>& ifPacket, const Packet4i& thenPacket, const Packet4i& elsePacket) {
+  Packet4ui select = { ifPacket.select[0], ifPacket.select[1], ifPacket.select[2], ifPacket.select[3] };
+  Packet4ui mask = vec_cmpeq(select, reinterpret_cast<Packet4ui>(p4i_ONE));
+  return vec_sel(elsePacket, thenPacket, mask);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f pblend(const Selector<4>& ifPacket, const Packet4f& thenPacket, const Packet4f& elsePacket) {
+  Packet2ul select_hi = { ifPacket.select[0], ifPacket.select[1] };
+  Packet2ul select_lo = { ifPacket.select[2], ifPacket.select[3] };
+  Packet2ul mask_hi = vec_cmpeq(select_hi, reinterpret_cast<Packet2ul>(p2l_ONE));
+  Packet2ul mask_lo = vec_cmpeq(select_lo, reinterpret_cast<Packet2ul>(p2l_ONE));
+  Packet4f result;
+  result.v4f[0] = vec_sel(elsePacket.v4f[0], thenPacket.v4f[0], mask_hi);
+  result.v4f[1] = vec_sel(elsePacket.v4f[1], thenPacket.v4f[1], mask_lo);
+  return result;
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d pblend(const Selector<2>& ifPacket, const Packet2d& thenPacket, const Packet2d& elsePacket) {
+  Packet2ul select = { ifPacket.select[0], ifPacket.select[1] };
+  Packet2ul mask = vec_cmpeq(select, reinterpret_cast<Packet2ul>(p2l_ONE));
+  return vec_sel(elsePacket, thenPacket, mask);
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_PACKET_MATH_ZVECTOR_H

ADDED   3rd_party/eigen/Eigen/src/Core/functors/AssignmentFunctors.h
Index: 3rd_party/eigen/Eigen/src/Core/functors/AssignmentFunctors.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/functors/AssignmentFunctors.h
+++ 3rd_party/eigen/Eigen/src/Core/functors/AssignmentFunctors.h
@@ -0,0 +1,168 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_ASSIGNMENT_FUNCTORS_H
+#define EIGEN_ASSIGNMENT_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+  
+/** \internal
+  * \brief Template functor for scalar/packet assignment
+  *
+  */
+template<typename DstScalar,typename SrcScalar> struct assign_op {
+
+  EIGEN_EMPTY_STRUCT_CTOR(assign_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(DstScalar& a, const SrcScalar& b) const { a = b; }
+  
+  template<int Alignment, typename Packet>
+  EIGEN_STRONG_INLINE void assignPacket(DstScalar* a, const Packet& b) const
+  { internal::pstoret<DstScalar,Packet,Alignment>(a,b); }
+};
+
+// Empty overload for void type (used by PermutationMatrix)
+template<typename DstScalar> struct assign_op<DstScalar,void> {};
+
+template<typename DstScalar,typename SrcScalar>
+struct functor_traits<assign_op<DstScalar,SrcScalar> > {
+  enum {
+    Cost = NumTraits<DstScalar>::ReadCost,
+    PacketAccess = is_same<DstScalar,SrcScalar>::value && packet_traits<DstScalar>::Vectorizable && packet_traits<SrcScalar>::Vectorizable
+  };
+};
+
+/** \internal
+  * \brief Template functor for scalar/packet assignment with addition
+  *
+  */
+template<typename DstScalar,typename SrcScalar> struct add_assign_op {
+
+  EIGEN_EMPTY_STRUCT_CTOR(add_assign_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(DstScalar& a, const SrcScalar& b) const { a += b; }
+  
+  template<int Alignment, typename Packet>
+  EIGEN_STRONG_INLINE void assignPacket(DstScalar* a, const Packet& b) const
+  { internal::pstoret<DstScalar,Packet,Alignment>(a,internal::padd(internal::ploadt<Packet,Alignment>(a),b)); }
+};
+template<typename DstScalar,typename SrcScalar>
+struct functor_traits<add_assign_op<DstScalar,SrcScalar> > {
+  enum {
+    Cost = NumTraits<DstScalar>::ReadCost + NumTraits<DstScalar>::AddCost,
+    PacketAccess = is_same<DstScalar,SrcScalar>::value && packet_traits<DstScalar>::HasAdd
+  };
+};
+
+/** \internal
+  * \brief Template functor for scalar/packet assignment with subtraction
+  *
+  */
+template<typename DstScalar,typename SrcScalar> struct sub_assign_op {
+
+  EIGEN_EMPTY_STRUCT_CTOR(sub_assign_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(DstScalar& a, const SrcScalar& b) const { a -= b; }
+  
+  template<int Alignment, typename Packet>
+  EIGEN_STRONG_INLINE void assignPacket(DstScalar* a, const Packet& b) const
+  { internal::pstoret<DstScalar,Packet,Alignment>(a,internal::psub(internal::ploadt<Packet,Alignment>(a),b)); }
+};
+template<typename DstScalar,typename SrcScalar>
+struct functor_traits<sub_assign_op<DstScalar,SrcScalar> > {
+  enum {
+    Cost = NumTraits<DstScalar>::ReadCost + NumTraits<DstScalar>::AddCost,
+    PacketAccess = is_same<DstScalar,SrcScalar>::value && packet_traits<DstScalar>::HasSub
+  };
+};
+
+/** \internal
+  * \brief Template functor for scalar/packet assignment with multiplication
+  *
+  */
+template<typename DstScalar, typename SrcScalar=DstScalar>
+struct mul_assign_op {
+
+  EIGEN_EMPTY_STRUCT_CTOR(mul_assign_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(DstScalar& a, const SrcScalar& b) const { a *= b; }
+  
+  template<int Alignment, typename Packet>
+  EIGEN_STRONG_INLINE void assignPacket(DstScalar* a, const Packet& b) const
+  { internal::pstoret<DstScalar,Packet,Alignment>(a,internal::pmul(internal::ploadt<Packet,Alignment>(a),b)); }
+};
+template<typename DstScalar, typename SrcScalar>
+struct functor_traits<mul_assign_op<DstScalar,SrcScalar> > {
+  enum {
+    Cost = NumTraits<DstScalar>::ReadCost + NumTraits<DstScalar>::MulCost,
+    PacketAccess = is_same<DstScalar,SrcScalar>::value && packet_traits<DstScalar>::HasMul
+  };
+};
+
+/** \internal
+  * \brief Template functor for scalar/packet assignment with diviving
+  *
+  */
+template<typename DstScalar, typename SrcScalar=DstScalar> struct div_assign_op {
+
+  EIGEN_EMPTY_STRUCT_CTOR(div_assign_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(DstScalar& a, const SrcScalar& b) const { a /= b; }
+  
+  template<int Alignment, typename Packet>
+  EIGEN_STRONG_INLINE void assignPacket(DstScalar* a, const Packet& b) const
+  { internal::pstoret<DstScalar,Packet,Alignment>(a,internal::pdiv(internal::ploadt<Packet,Alignment>(a),b)); }
+};
+template<typename DstScalar, typename SrcScalar>
+struct functor_traits<div_assign_op<DstScalar,SrcScalar> > {
+  enum {
+    Cost = NumTraits<DstScalar>::ReadCost + NumTraits<DstScalar>::MulCost,
+    PacketAccess = is_same<DstScalar,SrcScalar>::value && packet_traits<DstScalar>::HasDiv
+  };
+};
+
+/** \internal
+  * \brief Template functor for scalar/packet assignment with swapping
+  *
+  * It works as follow. For a non-vectorized evaluation loop, we have:
+  *   for(i) func(A.coeffRef(i), B.coeff(i));
+  * where B is a SwapWrapper expression. The trick is to make SwapWrapper::coeff behaves like a non-const coeffRef.
+  * Actually, SwapWrapper might not even be needed since even if B is a plain expression, since it has to be writable
+  * B.coeff already returns a const reference to the underlying scalar value.
+  * 
+  * The case of a vectorized loop is more tricky:
+  *   for(i,j) func.assignPacket<A_Align>(&A.coeffRef(i,j), B.packet<B_Align>(i,j));
+  * Here, B must be a SwapWrapper whose packet function actually returns a proxy object holding a Scalar*,
+  * the actual alignment and Packet type.
+  *
+  */
+template<typename Scalar> struct swap_assign_op {
+
+  EIGEN_EMPTY_STRUCT_CTOR(swap_assign_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Scalar& a, const Scalar& b) const
+  {
+#ifdef __CUDACC__
+    // FIXME is there some kind of cuda::swap?
+    Scalar t=b; const_cast<Scalar&>(b)=a; a=t;
+#else
+    using std::swap;
+    swap(a,const_cast<Scalar&>(b));
+#endif
+  }
+};
+template<typename Scalar>
+struct functor_traits<swap_assign_op<Scalar> > {
+  enum {
+    Cost = 3 * NumTraits<Scalar>::ReadCost,
+    PacketAccess = packet_traits<Scalar>::Vectorizable
+  };
+};
+
+} // namespace internal
+
+} // namespace Eigen
+
+#endif // EIGEN_ASSIGNMENT_FUNCTORS_H

ADDED   3rd_party/eigen/Eigen/src/Core/functors/BinaryFunctors.h
Index: 3rd_party/eigen/Eigen/src/Core/functors/BinaryFunctors.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/functors/BinaryFunctors.h
+++ 3rd_party/eigen/Eigen/src/Core/functors/BinaryFunctors.h
@@ -0,0 +1,482 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_BINARY_FUNCTORS_H
+#define EIGEN_BINARY_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+//---------- associative binary functors ----------
+
+template<typename Arg1, typename Arg2>
+struct binary_op_base
+{
+  typedef Arg1 first_argument_type;
+  typedef Arg2 second_argument_type;
+};
+
+/** \internal
+  * \brief Template functor to compute the sum of two scalars
+  *
+  * \sa class CwiseBinaryOp, MatrixBase::operator+, class VectorwiseOp, DenseBase::sum()
+  */
+template<typename LhsScalar,typename RhsScalar>
+struct scalar_sum_op : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef typename ScalarBinaryOpTraits<LhsScalar,RhsScalar,scalar_sum_op>::ReturnType result_type;
+#ifndef EIGEN_SCALAR_BINARY_OP_PLUGIN
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_sum_op)
+#else
+  scalar_sum_op() {
+    EIGEN_SCALAR_BINARY_OP_PLUGIN
+  }
+#endif
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a + b; }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+  { return internal::padd(a,b); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
+  { return internal::predux(a); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_sum_op<LhsScalar,RhsScalar> > {
+  enum {
+    Cost = (NumTraits<LhsScalar>::AddCost+NumTraits<RhsScalar>::AddCost)/2, // rough estimate!
+    PacketAccess = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasAdd && packet_traits<RhsScalar>::HasAdd
+    // TODO vectorize mixed sum
+  };
+};
+
+/** \internal
+  * \brief Template specialization to deprecate the summation of boolean expressions.
+  * This is required to solve Bug 426.
+  * \sa DenseBase::count(), DenseBase::any(), ArrayBase::cast(), MatrixBase::cast()
+  */
+template<> struct scalar_sum_op<bool,bool> : scalar_sum_op<int,int> {
+  EIGEN_DEPRECATED
+  scalar_sum_op() {}
+};
+
+
+/** \internal
+  * \brief Template functor to compute the product of two scalars
+  *
+  * \sa class CwiseBinaryOp, Cwise::operator*(), class VectorwiseOp, MatrixBase::redux()
+  */
+template<typename LhsScalar,typename RhsScalar>
+struct scalar_product_op  : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef typename ScalarBinaryOpTraits<LhsScalar,RhsScalar,scalar_product_op>::ReturnType result_type;
+#ifndef EIGEN_SCALAR_BINARY_OP_PLUGIN
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_product_op)
+#else
+  scalar_product_op() {
+    EIGEN_SCALAR_BINARY_OP_PLUGIN
+  }
+#endif
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a * b; }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+  { return internal::pmul(a,b); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
+  { return internal::predux_mul(a); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_product_op<LhsScalar,RhsScalar> > {
+  enum {
+    Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost)/2, // rough estimate!
+    PacketAccess = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasMul && packet_traits<RhsScalar>::HasMul
+    // TODO vectorize mixed product
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the conjugate product of two scalars
+  *
+  * This is a short cut for conj(x) * y which is needed for optimization purpose; in Eigen2 support mode, this becomes x * conj(y)
+  */
+template<typename LhsScalar,typename RhsScalar>
+struct scalar_conj_product_op  : binary_op_base<LhsScalar,RhsScalar>
+{
+
+  enum {
+    Conj = NumTraits<LhsScalar>::IsComplex
+  };
+  
+  typedef typename ScalarBinaryOpTraits<LhsScalar,RhsScalar,scalar_conj_product_op>::ReturnType result_type;
+  
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_conj_product_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const
+  { return conj_helper<LhsScalar,RhsScalar,Conj,false>().pmul(a,b); }
+  
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+  { return conj_helper<Packet,Packet,Conj,false>().pmul(a,b); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_conj_product_op<LhsScalar,RhsScalar> > {
+  enum {
+    Cost = NumTraits<LhsScalar>::MulCost,
+    PacketAccess = internal::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMul
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the min of two scalars
+  *
+  * \sa class CwiseBinaryOp, MatrixBase::cwiseMin, class VectorwiseOp, MatrixBase::minCoeff()
+  */
+template<typename LhsScalar,typename RhsScalar>
+struct scalar_min_op : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef typename ScalarBinaryOpTraits<LhsScalar,RhsScalar,scalar_min_op>::ReturnType result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_min_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return numext::mini(a, b); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+  { return internal::pmin(a,b); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
+  { return internal::predux_min(a); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_min_op<LhsScalar,RhsScalar> > {
+  enum {
+    Cost = (NumTraits<LhsScalar>::AddCost+NumTraits<RhsScalar>::AddCost)/2,
+    PacketAccess = internal::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMin
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the max of two scalars
+  *
+  * \sa class CwiseBinaryOp, MatrixBase::cwiseMax, class VectorwiseOp, MatrixBase::maxCoeff()
+  */
+template<typename LhsScalar,typename RhsScalar>
+struct scalar_max_op  : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef typename ScalarBinaryOpTraits<LhsScalar,RhsScalar,scalar_max_op>::ReturnType result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_max_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return numext::maxi(a, b); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+  { return internal::pmax(a,b); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
+  { return internal::predux_max(a); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_max_op<LhsScalar,RhsScalar> > {
+  enum {
+    Cost = (NumTraits<LhsScalar>::AddCost+NumTraits<RhsScalar>::AddCost)/2,
+    PacketAccess = internal::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMax
+  };
+};
+
+/** \internal
+  * \brief Template functors for comparison of two scalars
+  * \todo Implement packet-comparisons
+  */
+template<typename LhsScalar, typename RhsScalar, ComparisonName cmp> struct scalar_cmp_op;
+
+template<typename LhsScalar, typename RhsScalar, ComparisonName cmp>
+struct functor_traits<scalar_cmp_op<LhsScalar,RhsScalar, cmp> > {
+  enum {
+    Cost = (NumTraits<LhsScalar>::AddCost+NumTraits<RhsScalar>::AddCost)/2,
+    PacketAccess = false
+  };
+};
+
+template<ComparisonName Cmp, typename LhsScalar, typename RhsScalar>
+struct result_of<scalar_cmp_op<LhsScalar, RhsScalar, Cmp>(LhsScalar,RhsScalar)> {
+  typedef bool type;
+};
+
+
+template<typename LhsScalar, typename RhsScalar>
+struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_EQ> : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef bool result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator()(const LhsScalar& a, const RhsScalar& b) const {return a==b;}
+};
+template<typename LhsScalar, typename RhsScalar>
+struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_LT> : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef bool result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator()(const LhsScalar& a, const RhsScalar& b) const {return a<b;}
+};
+template<typename LhsScalar, typename RhsScalar>
+struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_LE> : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef bool result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator()(const LhsScalar& a, const RhsScalar& b) const {return a<=b;}
+};
+template<typename LhsScalar, typename RhsScalar>
+struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_GT> : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef bool result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator()(const LhsScalar& a, const RhsScalar& b) const {return a>b;}
+};
+template<typename LhsScalar, typename RhsScalar>
+struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_GE> : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef bool result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator()(const LhsScalar& a, const RhsScalar& b) const {return a>=b;}
+};
+template<typename LhsScalar, typename RhsScalar>
+struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_UNORD> : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef bool result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator()(const LhsScalar& a, const RhsScalar& b) const {return !(a<=b || b<=a);}
+};
+template<typename LhsScalar, typename RhsScalar>
+struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_NEQ> : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef bool result_type;
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator()(const LhsScalar& a, const RhsScalar& b) const {return a!=b;}
+};
+
+
+/** \internal
+  * \brief Template functor to compute the hypot of two scalars
+  *
+  * \sa MatrixBase::stableNorm(), class Redux
+  */
+template<typename Scalar>
+struct scalar_hypot_op<Scalar,Scalar> : binary_op_base<Scalar,Scalar>
+{
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op)
+//   typedef typename NumTraits<Scalar>::Real result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
+  {
+    EIGEN_USING_STD_MATH(sqrt)
+    Scalar p, qp;
+    if(_x>_y)
+    {
+      p = _x;
+      qp = _y / p;
+    }
+    else
+    {
+      p = _y;
+      qp = _x / p;
+    }
+    return p * sqrt(Scalar(1) + qp*qp);
+  }
+};
+template<typename Scalar>
+struct functor_traits<scalar_hypot_op<Scalar,Scalar> > {
+  enum
+  {
+    Cost = 3 * NumTraits<Scalar>::AddCost +
+           2 * NumTraits<Scalar>::MulCost +
+           2 * scalar_div_cost<Scalar,false>::value,
+    PacketAccess = false
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the pow of two scalars
+  */
+template<typename Scalar, typename Exponent>
+struct scalar_pow_op  : binary_op_base<Scalar,Exponent>
+{
+  typedef typename ScalarBinaryOpTraits<Scalar,Exponent,scalar_pow_op>::ReturnType result_type;
+#ifndef EIGEN_SCALAR_BINARY_OP_PLUGIN
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_pow_op)
+#else
+  scalar_pow_op() {
+    typedef Scalar LhsScalar;
+    typedef Exponent RhsScalar;
+    EIGEN_SCALAR_BINARY_OP_PLUGIN
+  }
+#endif
+  EIGEN_DEVICE_FUNC
+  inline result_type operator() (const Scalar& a, const Exponent& b) const { return numext::pow(a, b); }
+};
+template<typename Scalar, typename Exponent>
+struct functor_traits<scalar_pow_op<Scalar,Exponent> > {
+  enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false };
+};
+
+
+
+//---------- non associative binary functors ----------
+
+/** \internal
+  * \brief Template functor to compute the difference of two scalars
+  *
+  * \sa class CwiseBinaryOp, MatrixBase::operator-
+  */
+template<typename LhsScalar,typename RhsScalar>
+struct scalar_difference_op : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef typename ScalarBinaryOpTraits<LhsScalar,RhsScalar,scalar_difference_op>::ReturnType result_type;
+#ifndef EIGEN_SCALAR_BINARY_OP_PLUGIN
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_difference_op)
+#else
+  scalar_difference_op() {
+    EIGEN_SCALAR_BINARY_OP_PLUGIN
+  }
+#endif
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a - b; }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+  { return internal::psub(a,b); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_difference_op<LhsScalar,RhsScalar> > {
+  enum {
+    Cost = (NumTraits<LhsScalar>::AddCost+NumTraits<RhsScalar>::AddCost)/2,
+    PacketAccess = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasSub && packet_traits<RhsScalar>::HasSub
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the quotient of two scalars
+  *
+  * \sa class CwiseBinaryOp, Cwise::operator/()
+  */
+template<typename LhsScalar,typename RhsScalar>
+struct scalar_quotient_op  : binary_op_base<LhsScalar,RhsScalar>
+{
+  typedef typename ScalarBinaryOpTraits<LhsScalar,RhsScalar,scalar_quotient_op>::ReturnType result_type;
+#ifndef EIGEN_SCALAR_BINARY_OP_PLUGIN
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
+#else
+  scalar_quotient_op() {
+    EIGEN_SCALAR_BINARY_OP_PLUGIN
+  }
+#endif
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a / b; }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+  { return internal::pdiv(a,b); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_quotient_op<LhsScalar,RhsScalar> > {
+  typedef typename scalar_quotient_op<LhsScalar,RhsScalar>::result_type result_type;
+  enum {
+    PacketAccess = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasDiv && packet_traits<RhsScalar>::HasDiv,
+    Cost = scalar_div_cost<result_type,PacketAccess>::value
+  };
+};
+
+
+
+/** \internal
+  * \brief Template functor to compute the and of two booleans
+  *
+  * \sa class CwiseBinaryOp, ArrayBase::operator&&
+  */
+struct scalar_boolean_and_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_and_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a && b; }
+};
+template<> struct functor_traits<scalar_boolean_and_op> {
+  enum {
+    Cost = NumTraits<bool>::AddCost,
+    PacketAccess = false
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the or of two booleans
+  *
+  * \sa class CwiseBinaryOp, ArrayBase::operator||
+  */
+struct scalar_boolean_or_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_or_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a || b; }
+};
+template<> struct functor_traits<scalar_boolean_or_op> {
+  enum {
+    Cost = NumTraits<bool>::AddCost,
+    PacketAccess = false
+  };
+};
+
+/** \internal
+ * \brief Template functor to compute the xor of two booleans
+ *
+ * \sa class CwiseBinaryOp, ArrayBase::operator^
+ */
+struct scalar_boolean_xor_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_xor_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a ^ b; }
+};
+template<> struct functor_traits<scalar_boolean_xor_op> {
+  enum {
+    Cost = NumTraits<bool>::AddCost,
+    PacketAccess = false
+  };
+};
+
+
+
+//---------- binary functors bound to a constant, thus appearing as a unary functor ----------
+
+// The following two classes permits to turn any binary functor into a unary one with one argument bound to a constant value.
+// They are analogues to std::binder1st/binder2nd but with the following differences:
+//  - they are compatible with packetOp
+//  - they are portable across C++ versions (the std::binder* are deprecated in C++11)
+template<typename BinaryOp> struct bind1st_op : BinaryOp {
+
+  typedef typename BinaryOp::first_argument_type  first_argument_type;
+  typedef typename BinaryOp::second_argument_type second_argument_type;
+  typedef typename BinaryOp::result_type          result_type;
+
+  bind1st_op(const first_argument_type &val) : m_value(val) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const second_argument_type& b) const { return BinaryOp::operator()(m_value,b); }
+
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& b) const
+  { return BinaryOp::packetOp(internal::pset1<Packet>(m_value), b); }
+
+  first_argument_type m_value;
+};
+template<typename BinaryOp> struct functor_traits<bind1st_op<BinaryOp> > : functor_traits<BinaryOp> {};
+
+
+template<typename BinaryOp> struct bind2nd_op : BinaryOp {
+
+  typedef typename BinaryOp::first_argument_type  first_argument_type;
+  typedef typename BinaryOp::second_argument_type second_argument_type;
+  typedef typename BinaryOp::result_type          result_type;
+
+  bind2nd_op(const second_argument_type &val) : m_value(val) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const first_argument_type& a) const { return BinaryOp::operator()(a,m_value); }
+
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+  { return BinaryOp::packetOp(a,internal::pset1<Packet>(m_value)); }
+
+  second_argument_type m_value;
+};
+template<typename BinaryOp> struct functor_traits<bind2nd_op<BinaryOp> > : functor_traits<BinaryOp> {};
+
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_BINARY_FUNCTORS_H

ADDED   3rd_party/eigen/Eigen/src/Core/functors/NullaryFunctors.h
Index: 3rd_party/eigen/Eigen/src/Core/functors/NullaryFunctors.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/functors/NullaryFunctors.h
+++ 3rd_party/eigen/Eigen/src/Core/functors/NullaryFunctors.h
@@ -0,0 +1,188 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_NULLARY_FUNCTORS_H
+#define EIGEN_NULLARY_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+template<typename Scalar>
+struct scalar_constant_op {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_constant_op(const scalar_constant_op& other) : m_other(other.m_other) { }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_constant_op(const Scalar& other) : m_other(other) { }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() () const { return m_other; }
+  template<typename PacketType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const PacketType packetOp() const { return internal::pset1<PacketType>(m_other); }
+  const Scalar m_other;
+};
+template<typename Scalar>
+struct functor_traits<scalar_constant_op<Scalar> >
+{ enum { Cost = 0 /* as the constant value should be loaded in register only once for the whole expression */,
+         PacketAccess = packet_traits<Scalar>::Vectorizable, IsRepeatable = true }; };
+
+template<typename Scalar> struct scalar_identity_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_identity_op)
+  template<typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (IndexType row, IndexType col) const { return row==col ? Scalar(1) : Scalar(0); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_identity_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = false, IsRepeatable = true }; };
+
+template <typename Scalar, typename Packet, bool IsInteger> struct linspaced_op_impl;
+
+template <typename Scalar, typename Packet>
+struct linspaced_op_impl<Scalar,Packet,/*IsInteger*/false>
+{
+  linspaced_op_impl(const Scalar& low, const Scalar& high, Index num_steps) :
+    m_low(low), m_high(high), m_size1(num_steps==1 ? 1 : num_steps-1), m_step(num_steps==1 ? Scalar() : (high-low)/Scalar(num_steps-1)),
+    m_flip(numext::abs(high)<numext::abs(low))
+  {}
+
+  template<typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (IndexType i) const {
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    if(m_flip)
+      return (i==0)? m_low : (m_high - RealScalar(m_size1-i)*m_step);
+    else
+      return (i==m_size1)? m_high : (m_low + RealScalar(i)*m_step);
+  }
+
+  template<typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(IndexType i) const
+  {
+    // Principle:
+    // [low, ..., low] + ( [step, ..., step] * ( [i, ..., i] + [0, ..., size] ) )
+    if(m_flip)
+    {
+      Packet pi = plset<Packet>(Scalar(i-m_size1));
+      Packet res = padd(pset1<Packet>(m_high), pmul(pset1<Packet>(m_step), pi));
+      if(i==0)
+        res = pinsertfirst(res, m_low);
+      return res;
+    }
+    else
+    {
+      Packet pi = plset<Packet>(Scalar(i));
+      Packet res = padd(pset1<Packet>(m_low), pmul(pset1<Packet>(m_step), pi));
+      if(i==m_size1-unpacket_traits<Packet>::size+1)
+        res = pinsertlast(res, m_high);
+      return res;
+    }
+  }
+
+  const Scalar m_low;
+  const Scalar m_high;
+  const Index m_size1;
+  const Scalar m_step;
+  const bool m_flip;
+};
+
+template <typename Scalar, typename Packet>
+struct linspaced_op_impl<Scalar,Packet,/*IsInteger*/true>
+{
+  linspaced_op_impl(const Scalar& low, const Scalar& high, Index num_steps) :
+    m_low(low),
+    m_multiplier((high-low)/convert_index<Scalar>(num_steps<=1 ? 1 : num_steps-1)),
+    m_divisor(convert_index<Scalar>((high>=low?num_steps:-num_steps)+(high-low))/((numext::abs(high-low)+1)==0?1:(numext::abs(high-low)+1))),
+    m_use_divisor(num_steps>1 && (numext::abs(high-low)+1)<num_steps)
+  {}
+
+  template<typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const Scalar operator() (IndexType i) const
+  {
+    if(m_use_divisor) return m_low + convert_index<Scalar>(i)/m_divisor;
+    else              return m_low + convert_index<Scalar>(i)*m_multiplier;
+  }
+
+  const Scalar m_low;
+  const Scalar m_multiplier;
+  const Scalar m_divisor;
+  const bool m_use_divisor;
+};
+
+// ----- Linspace functor ----------------------------------------------------------------
+
+// Forward declaration (we default to random access which does not really give
+// us a speed gain when using packet access but it allows to use the functor in
+// nested expressions).
+template <typename Scalar, typename PacketType> struct linspaced_op;
+template <typename Scalar, typename PacketType> struct functor_traits< linspaced_op<Scalar,PacketType> >
+{
+  enum
+  {
+    Cost = 1,
+    PacketAccess =   (!NumTraits<Scalar>::IsInteger) && packet_traits<Scalar>::HasSetLinear && packet_traits<Scalar>::HasBlend,
+                  /*&& ((!NumTraits<Scalar>::IsInteger) || packet_traits<Scalar>::HasDiv),*/ // <- vectorization for integer is currently disabled
+    IsRepeatable = true
+  };
+};
+template <typename Scalar, typename PacketType> struct linspaced_op
+{
+  linspaced_op(const Scalar& low, const Scalar& high, Index num_steps)
+    : impl((num_steps==1 ? high : low),high,num_steps)
+  {}
+
+  template<typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (IndexType i) const { return impl(i); }
+
+  template<typename Packet,typename IndexType>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(IndexType i) const { return impl.packetOp(i); }
+
+  // This proxy object handles the actual required temporaries and the different
+  // implementations (integer vs. floating point).
+  const linspaced_op_impl<Scalar,PacketType,NumTraits<Scalar>::IsInteger> impl;
+};
+
+// Linear access is automatically determined from the operator() prototypes available for the given functor.
+// If it exposes an operator()(i,j), then we assume the i and j coefficients are required independently
+// and linear access is not possible. In all other cases, linear access is enabled.
+// Users should not have to deal with this structure.
+template<typename Functor> struct functor_has_linear_access { enum { ret = !has_binary_operator<Functor>::value }; };
+
+// For unreliable compilers, let's specialize the has_*ary_operator
+// helpers so that at least built-in nullary functors work fine.
+#if !( (EIGEN_COMP_MSVC>1600) || (EIGEN_GNUC_AT_LEAST(4,8)) || (EIGEN_COMP_ICC>=1600))
+template<typename Scalar,typename IndexType>
+struct has_nullary_operator<scalar_constant_op<Scalar>,IndexType> { enum { value = 1}; };
+template<typename Scalar,typename IndexType>
+struct has_unary_operator<scalar_constant_op<Scalar>,IndexType> { enum { value = 0}; };
+template<typename Scalar,typename IndexType>
+struct has_binary_operator<scalar_constant_op<Scalar>,IndexType> { enum { value = 0}; };
+
+template<typename Scalar,typename IndexType>
+struct has_nullary_operator<scalar_identity_op<Scalar>,IndexType> { enum { value = 0}; };
+template<typename Scalar,typename IndexType>
+struct has_unary_operator<scalar_identity_op<Scalar>,IndexType> { enum { value = 0}; };
+template<typename Scalar,typename IndexType>
+struct has_binary_operator<scalar_identity_op<Scalar>,IndexType> { enum { value = 1}; };
+
+template<typename Scalar, typename PacketType,typename IndexType>
+struct has_nullary_operator<linspaced_op<Scalar,PacketType>,IndexType> { enum { value = 0}; };
+template<typename Scalar, typename PacketType,typename IndexType>
+struct has_unary_operator<linspaced_op<Scalar,PacketType>,IndexType> { enum { value = 1}; };
+template<typename Scalar, typename PacketType,typename IndexType>
+struct has_binary_operator<linspaced_op<Scalar,PacketType>,IndexType> { enum { value = 0}; };
+
+template<typename Scalar,typename IndexType>
+struct has_nullary_operator<scalar_random_op<Scalar>,IndexType> { enum { value = 1}; };
+template<typename Scalar,typename IndexType>
+struct has_unary_operator<scalar_random_op<Scalar>,IndexType> { enum { value = 0}; };
+template<typename Scalar,typename IndexType>
+struct has_binary_operator<scalar_random_op<Scalar>,IndexType> { enum { value = 0}; };
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_NULLARY_FUNCTORS_H

ADDED   3rd_party/eigen/Eigen/src/Core/functors/StlFunctors.h
Index: 3rd_party/eigen/Eigen/src/Core/functors/StlFunctors.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/functors/StlFunctors.h
+++ 3rd_party/eigen/Eigen/src/Core/functors/StlFunctors.h
@@ -0,0 +1,132 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_STL_FUNCTORS_H
+#define EIGEN_STL_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+// default functor traits for STL functors:
+
+template<typename T>
+struct functor_traits<std::multiplies<T> >
+{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::divides<T> >
+{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::plus<T> >
+{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::minus<T> >
+{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::negate<T> >
+{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::logical_or<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::logical_and<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::logical_not<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::greater<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::less<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::greater_equal<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::less_equal<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::equal_to<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::not_equal_to<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+#if (__cplusplus < 201103L) && (EIGEN_COMP_MSVC <= 1900)
+// std::binder* are deprecated since c++11 and will be removed in c++17
+template<typename T>
+struct functor_traits<std::binder2nd<T> >
+{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::binder1st<T> >
+{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
+#endif
+
+template<typename T>
+struct functor_traits<std::unary_negate<T> >
+{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::binary_negate<T> >
+{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
+
+#ifdef EIGEN_STDEXT_SUPPORT
+
+template<typename T0,typename T1>
+struct functor_traits<std::project1st<T0,T1> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+template<typename T0,typename T1>
+struct functor_traits<std::project2nd<T0,T1> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+template<typename T0,typename T1>
+struct functor_traits<std::select2nd<std::pair<T0,T1> > >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+template<typename T0,typename T1>
+struct functor_traits<std::select1st<std::pair<T0,T1> > >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+template<typename T0,typename T1>
+struct functor_traits<std::unary_compose<T0,T1> >
+{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost, PacketAccess = false }; };
+
+template<typename T0,typename T1,typename T2>
+struct functor_traits<std::binary_compose<T0,T1,T2> >
+{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost + functor_traits<T2>::Cost, PacketAccess = false }; };
+
+#endif // EIGEN_STDEXT_SUPPORT
+
+// allow to add new functors and specializations of functor_traits from outside Eigen.
+// this macro is really needed because functor_traits must be specialized after it is declared but before it is used...
+#ifdef EIGEN_FUNCTORS_PLUGIN
+#include EIGEN_FUNCTORS_PLUGIN
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_STL_FUNCTORS_H

ADDED   3rd_party/eigen/Eigen/src/Core/functors/TernaryFunctors.h
Index: 3rd_party/eigen/Eigen/src/Core/functors/TernaryFunctors.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/functors/TernaryFunctors.h
+++ 3rd_party/eigen/Eigen/src/Core/functors/TernaryFunctors.h
@@ -0,0 +1,25 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Eugene Brevdo <ebrevdo@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_TERNARY_FUNCTORS_H
+#define EIGEN_TERNARY_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+//---------- associative ternary functors ----------
+
+
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TERNARY_FUNCTORS_H

ADDED   3rd_party/eigen/Eigen/src/Core/functors/UnaryFunctors.h
Index: 3rd_party/eigen/Eigen/src/Core/functors/UnaryFunctors.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/functors/UnaryFunctors.h
+++ 3rd_party/eigen/Eigen/src/Core/functors/UnaryFunctors.h
@@ -0,0 +1,792 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_UNARY_FUNCTORS_H
+#define EIGEN_UNARY_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+/** \internal
+  * \brief Template functor to compute the opposite of a scalar
+  *
+  * \sa class CwiseUnaryOp, MatrixBase::operator-
+  */
+template<typename Scalar> struct scalar_opposite_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_opposite_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return -a; }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+  { return internal::pnegate(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_opposite_op<Scalar> >
+{ enum {
+    Cost = NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasNegate };
+};
+
+/** \internal
+  * \brief Template functor to compute the absolute value of a scalar
+  *
+  * \sa class CwiseUnaryOp, Cwise::abs
+  */
+template<typename Scalar> struct scalar_abs_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::abs(a); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+  { return internal::pabs(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_abs_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasAbs
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the score of a scalar, to chose a pivot
+  *
+  * \sa class CwiseUnaryOp
+  */
+template<typename Scalar> struct scalar_score_coeff_op : scalar_abs_op<Scalar>
+{
+  typedef void Score_is_abs;
+};
+template<typename Scalar>
+struct functor_traits<scalar_score_coeff_op<Scalar> > : functor_traits<scalar_abs_op<Scalar> > {};
+
+/* Avoid recomputing abs when we know the score and they are the same. Not a true Eigen functor.  */
+template<typename Scalar, typename=void> struct abs_knowing_score
+{
+  EIGEN_EMPTY_STRUCT_CTOR(abs_knowing_score)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  template<typename Score>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a, const Score&) const { return numext::abs(a); }
+};
+template<typename Scalar> struct abs_knowing_score<Scalar, typename scalar_score_coeff_op<Scalar>::Score_is_abs>
+{
+  EIGEN_EMPTY_STRUCT_CTOR(abs_knowing_score)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  template<typename Scal>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scal&, const result_type& a) const { return a; }
+};
+
+/** \internal
+  * \brief Template functor to compute the squared absolute value of a scalar
+  *
+  * \sa class CwiseUnaryOp, Cwise::abs2
+  */
+template<typename Scalar> struct scalar_abs2_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::abs2(a); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+  { return internal::pmul(a,a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_abs2_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasAbs2 }; };
+
+/** \internal
+  * \brief Template functor to compute the conjugate of a complex value
+  *
+  * \sa class CwiseUnaryOp, MatrixBase::conjugate()
+  */
+template<typename Scalar> struct scalar_conjugate_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op)
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { using numext::conj; return conj(a); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_conjugate_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::IsComplex ? NumTraits<Scalar>::AddCost : 0,
+    PacketAccess = packet_traits<Scalar>::HasConj
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the phase angle of a complex
+  *
+  * \sa class CwiseUnaryOp, Cwise::arg
+  */
+template<typename Scalar> struct scalar_arg_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_arg_op)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { using numext::arg; return arg(a); }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+  { return internal::parg(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_arg_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::IsComplex ? 5 * NumTraits<Scalar>::MulCost : NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasArg
+  };
+};
+/** \internal
+  * \brief Template functor to cast a scalar to another type
+  *
+  * \sa class CwiseUnaryOp, MatrixBase::cast()
+  */
+template<typename Scalar, typename NewType>
+struct scalar_cast_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
+  typedef NewType result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const NewType operator() (const Scalar& a) const { return cast<Scalar, NewType>(a); }
+};
+template<typename Scalar, typename NewType>
+struct functor_traits<scalar_cast_op<Scalar,NewType> >
+{ enum { Cost = is_same<Scalar, NewType>::value ? 0 : NumTraits<NewType>::AddCost, PacketAccess = false }; };
+
+/** \internal
+  * \brief Template functor to extract the real part of a complex
+  *
+  * \sa class CwiseUnaryOp, MatrixBase::real()
+  */
+template<typename Scalar>
+struct scalar_real_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::real(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_real_op<Scalar> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+/** \internal
+  * \brief Template functor to extract the imaginary part of a complex
+  *
+  * \sa class CwiseUnaryOp, MatrixBase::imag()
+  */
+template<typename Scalar>
+struct scalar_imag_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::imag(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_imag_op<Scalar> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+/** \internal
+  * \brief Template functor to extract the real part of a complex as a reference
+  *
+  * \sa class CwiseUnaryOp, MatrixBase::real()
+  */
+template<typename Scalar>
+struct scalar_real_ref_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::real_ref(*const_cast<Scalar*>(&a)); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_real_ref_op<Scalar> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+/** \internal
+  * \brief Template functor to extract the imaginary part of a complex as a reference
+  *
+  * \sa class CwiseUnaryOp, MatrixBase::imag()
+  */
+template<typename Scalar>
+struct scalar_imag_ref_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op)
+  typedef typename NumTraits<Scalar>::Real result_type;
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::imag_ref(*const_cast<Scalar*>(&a)); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_imag_ref_op<Scalar> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+/** \internal
+  *
+  * \brief Template functor to compute the exponential of a scalar
+  *
+  * \sa class CwiseUnaryOp, Cwise::exp()
+  */
+template<typename Scalar> struct scalar_exp_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::exp(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pexp(a); }
+};
+template <typename Scalar>
+struct functor_traits<scalar_exp_op<Scalar> > {
+  enum {
+    PacketAccess = packet_traits<Scalar>::HasExp,
+    // The following numbers are based on the AVX implementation.
+#ifdef EIGEN_VECTORIZE_FMA
+    // Haswell can issue 2 add/mul/madd per cycle.
+    Cost =
+    (sizeof(Scalar) == 4
+     // float: 8 pmadd, 4 pmul, 2 padd/psub, 6 other
+     ? (8 * NumTraits<Scalar>::AddCost + 6 * NumTraits<Scalar>::MulCost)
+     // double: 7 pmadd, 5 pmul, 3 padd/psub, 1 div,  13 other
+     : (14 * NumTraits<Scalar>::AddCost +
+        6 * NumTraits<Scalar>::MulCost +
+        scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value))
+#else
+    Cost =
+    (sizeof(Scalar) == 4
+     // float: 7 pmadd, 6 pmul, 4 padd/psub, 10 other
+     ? (21 * NumTraits<Scalar>::AddCost + 13 * NumTraits<Scalar>::MulCost)
+     // double: 7 pmadd, 5 pmul, 3 padd/psub, 1 div,  13 other
+     : (23 * NumTraits<Scalar>::AddCost +
+        12 * NumTraits<Scalar>::MulCost +
+        scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value))
+#endif
+  };
+};
+
+/** \internal
+  *
+  * \brief Template functor to compute the logarithm of a scalar
+  *
+  * \sa class CwiseUnaryOp, ArrayBase::log()
+  */
+template<typename Scalar> struct scalar_log_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::log(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog(a); }
+};
+template <typename Scalar>
+struct functor_traits<scalar_log_op<Scalar> > {
+  enum {
+    PacketAccess = packet_traits<Scalar>::HasLog,
+    Cost =
+    (PacketAccess
+     // The following numbers are based on the AVX implementation.
+#ifdef EIGEN_VECTORIZE_FMA
+     // 8 pmadd, 6 pmul, 8 padd/psub, 16 other, can issue 2 add/mul/madd per cycle.
+     ? (20 * NumTraits<Scalar>::AddCost + 7 * NumTraits<Scalar>::MulCost)
+#else
+     // 8 pmadd, 6 pmul, 8 padd/psub, 20 other
+     ? (36 * NumTraits<Scalar>::AddCost + 14 * NumTraits<Scalar>::MulCost)
+#endif
+     // Measured cost of std::log.
+     : sizeof(Scalar)==4 ? 40 : 85)
+  };
+};
+
+/** \internal
+  *
+  * \brief Template functor to compute the logarithm of 1 plus a scalar value
+  *
+  * \sa class CwiseUnaryOp, ArrayBase::log1p()
+  */
+template<typename Scalar> struct scalar_log1p_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_log1p_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::log1p(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog1p(a); }
+};
+template <typename Scalar>
+struct functor_traits<scalar_log1p_op<Scalar> > {
+  enum {
+    PacketAccess = packet_traits<Scalar>::HasLog1p,
+    Cost = functor_traits<scalar_log_op<Scalar> >::Cost // TODO measure cost of log1p
+  };
+};
+
+/** \internal
+  *
+  * \brief Template functor to compute the base-10 logarithm of a scalar
+  *
+  * \sa class CwiseUnaryOp, Cwise::log10()
+  */
+template<typename Scalar> struct scalar_log10_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_log10_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { EIGEN_USING_STD_MATH(log10) return log10(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog10(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_log10_op<Scalar> >
+{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasLog10 }; };
+
+/** \internal
+  * \brief Template functor to compute the square root of a scalar
+  * \sa class CwiseUnaryOp, Cwise::sqrt()
+  */
+template<typename Scalar> struct scalar_sqrt_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::sqrt(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); }
+};
+template <typename Scalar>
+struct functor_traits<scalar_sqrt_op<Scalar> > {
+  enum {
+#if EIGEN_FAST_MATH
+    // The following numbers are based on the AVX implementation.
+    Cost = (sizeof(Scalar) == 8 ? 28
+                                // 4 pmul, 1 pmadd, 3 other
+                                : (3 * NumTraits<Scalar>::AddCost +
+                                   5 * NumTraits<Scalar>::MulCost)),
+#else
+    // The following numbers are based on min VSQRT throughput on Haswell.
+    Cost = (sizeof(Scalar) == 8 ? 28 : 14),
+#endif
+    PacketAccess = packet_traits<Scalar>::HasSqrt
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the reciprocal square root of a scalar
+  * \sa class CwiseUnaryOp, Cwise::rsqrt()
+  */
+template<typename Scalar> struct scalar_rsqrt_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_rsqrt_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return Scalar(1)/numext::sqrt(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::prsqrt(a); }
+};
+
+template<typename Scalar>
+struct functor_traits<scalar_rsqrt_op<Scalar> >
+{ enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasRsqrt
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the cosine of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::cos()
+  */
+template<typename Scalar> struct scalar_cos_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op)
+  EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return numext::cos(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pcos(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_cos_op<Scalar> >
+{
+  enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasCos
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the sine of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::sin()
+  */
+template<typename Scalar> struct scalar_sin_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::sin(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psin(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_sin_op<Scalar> >
+{
+  enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasSin
+  };
+};
+
+
+/** \internal
+  * \brief Template functor to compute the tan of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::tan()
+  */
+template<typename Scalar> struct scalar_tan_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::tan(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::ptan(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_tan_op<Scalar> >
+{
+  enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasTan
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the arc cosine of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::acos()
+  */
+template<typename Scalar> struct scalar_acos_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::acos(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pacos(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_acos_op<Scalar> >
+{
+  enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasACos
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the arc sine of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::asin()
+  */
+template<typename Scalar> struct scalar_asin_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::asin(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pasin(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_asin_op<Scalar> >
+{
+  enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasASin
+  };
+};
+
+
+/** \internal
+  * \brief Template functor to compute the atan of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::atan()
+  */
+template<typename Scalar> struct scalar_atan_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_atan_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::atan(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::patan(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_atan_op<Scalar> >
+{
+  enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasATan
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the tanh of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::tanh()
+  */
+template <typename Scalar>
+struct scalar_tanh_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_tanh_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator()(const Scalar& a) const { return numext::tanh(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& x) const { return ptanh(x); }
+};
+
+template <typename Scalar>
+struct functor_traits<scalar_tanh_op<Scalar> > {
+  enum {
+    PacketAccess = packet_traits<Scalar>::HasTanh,
+    Cost = ( (EIGEN_FAST_MATH && is_same<Scalar,float>::value)
+// The following numbers are based on the AVX implementation,
+#ifdef EIGEN_VECTORIZE_FMA
+                // Haswell can issue 2 add/mul/madd per cycle.
+                // 9 pmadd, 2 pmul, 1 div, 2 other
+                ? (2 * NumTraits<Scalar>::AddCost +
+                   6 * NumTraits<Scalar>::MulCost +
+                   scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value)
+#else
+                ? (11 * NumTraits<Scalar>::AddCost +
+                   11 * NumTraits<Scalar>::MulCost +
+                   scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value)
+#endif
+                // This number assumes a naive implementation of tanh
+                : (6 * NumTraits<Scalar>::AddCost +
+                   3 * NumTraits<Scalar>::MulCost +
+                   2 * scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value +
+                   functor_traits<scalar_exp_op<Scalar> >::Cost))
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the sinh of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::sinh()
+  */
+template<typename Scalar> struct scalar_sinh_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_sinh_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::sinh(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psinh(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_sinh_op<Scalar> >
+{
+  enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasSinh
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the cosh of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::cosh()
+  */
+template<typename Scalar> struct scalar_cosh_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cosh_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::cosh(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pcosh(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_cosh_op<Scalar> >
+{
+  enum {
+    Cost = 5 * NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasCosh
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the inverse of a scalar
+  * \sa class CwiseUnaryOp, Cwise::inverse()
+  */
+template<typename Scalar>
+struct scalar_inverse_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_inverse_op)
+  EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC inline const Packet packetOp(const Packet& a) const
+  { return internal::pdiv(pset1<Packet>(Scalar(1)),a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_inverse_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
+
+/** \internal
+  * \brief Template functor to compute the square of a scalar
+  * \sa class CwiseUnaryOp, Cwise::square()
+  */
+template<typename Scalar>
+struct scalar_square_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op)
+  EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a*a; }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC inline const Packet packetOp(const Packet& a) const
+  { return internal::pmul(a,a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_square_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
+
+/** \internal
+  * \brief Template functor to compute the cube of a scalar
+  * \sa class CwiseUnaryOp, Cwise::cube()
+  */
+template<typename Scalar>
+struct scalar_cube_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op)
+  EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a*a*a; }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC inline const Packet packetOp(const Packet& a) const
+  { return internal::pmul(a,pmul(a,a)); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_cube_op<Scalar> >
+{ enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
+
+/** \internal
+  * \brief Template functor to compute the rounded value of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::round()
+  */
+template<typename Scalar> struct scalar_round_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_round_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return numext::round(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pround(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_round_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasRound
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the floor of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::floor()
+  */
+template<typename Scalar> struct scalar_floor_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_floor_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return numext::floor(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pfloor(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_floor_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasFloor
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the ceil of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::ceil()
+  */
+template<typename Scalar> struct scalar_ceil_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_ceil_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return numext::ceil(a); }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pceil(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_ceil_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::MulCost,
+    PacketAccess = packet_traits<Scalar>::HasCeil
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute whether a scalar is NaN
+  * \sa class CwiseUnaryOp, ArrayBase::isnan()
+  */
+template<typename Scalar> struct scalar_isnan_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_isnan_op)
+  typedef bool result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return (numext::isnan)(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_isnan_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::MulCost,
+    PacketAccess = false
+  };
+};
+
+/** \internal
+  * \brief Template functor to check whether a scalar is +/-inf
+  * \sa class CwiseUnaryOp, ArrayBase::isinf()
+  */
+template<typename Scalar> struct scalar_isinf_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_isinf_op)
+  typedef bool result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return (numext::isinf)(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_isinf_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::MulCost,
+    PacketAccess = false
+  };
+};
+
+/** \internal
+  * \brief Template functor to check whether a scalar has a finite value
+  * \sa class CwiseUnaryOp, ArrayBase::isfinite()
+  */
+template<typename Scalar> struct scalar_isfinite_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_isfinite_op)
+  typedef bool result_type;
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return (numext::isfinite)(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_isfinite_op<Scalar> >
+{
+  enum {
+    Cost = NumTraits<Scalar>::MulCost,
+    PacketAccess = false
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the logical not of a boolean
+  *
+  * \sa class CwiseUnaryOp, ArrayBase::operator!
+  */
+template<typename Scalar> struct scalar_boolean_not_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_not_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a) const { return !a; }
+};
+template<typename Scalar>
+struct functor_traits<scalar_boolean_not_op<Scalar> > {
+  enum {
+    Cost = NumTraits<bool>::AddCost,
+    PacketAccess = false
+  };
+};
+
+/** \internal
+  * \brief Template functor to compute the signum of a scalar
+  * \sa class CwiseUnaryOp, Cwise::sign()
+  */
+template<typename Scalar,bool iscpx=(NumTraits<Scalar>::IsComplex!=0) > struct scalar_sign_op;
+template<typename Scalar>
+struct scalar_sign_op<Scalar,false> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_sign_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const
+  {
+      return Scalar( (a>Scalar(0)) - (a<Scalar(0)) );
+  }
+  //TODO
+  //template <typename Packet>
+  //EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psign(a); }
+};
+template<typename Scalar>
+struct scalar_sign_op<Scalar,true> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_sign_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const
+  {
+    typedef typename NumTraits<Scalar>::Real real_type;
+    real_type aa = numext::abs(a);
+    if (aa==real_type(0))
+      return Scalar(0);
+    aa = real_type(1)/aa;
+    return Scalar(real(a)*aa, imag(a)*aa );
+  }
+  //TODO
+  //template <typename Packet>
+  //EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psign(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_sign_op<Scalar> >
+{ enum {
+    Cost = 
+        NumTraits<Scalar>::IsComplex
+        ? ( 8*NumTraits<Scalar>::MulCost  ) // roughly
+        : ( 3*NumTraits<Scalar>::AddCost),
+    PacketAccess = packet_traits<Scalar>::HasSign
+  };
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_FUNCTORS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Core/products/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Core/products/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Core_Product_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Core_Product_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/products COMPONENT Devel
-  )

DELETED 3rd_party/eigen/Eigen/src/Core/products/CoeffBasedProduct.h
Index: 3rd_party/eigen/Eigen/src/Core/products/CoeffBasedProduct.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/CoeffBasedProduct.h
+++ 3rd_party/eigen/Eigen/src/Core/products/CoeffBasedProduct.h
@@ -1,439 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_COEFFBASED_PRODUCT_H
-#define EIGEN_COEFFBASED_PRODUCT_H
-
-namespace Eigen { 
-
-namespace internal {
-
-/*********************************************************************************
-*  Coefficient based product implementation.
-*  It is designed for the following use cases:
-*  - small fixed sizes
-*  - lazy products
-*********************************************************************************/
-
-/* Since the all the dimensions of the product are small, here we can rely
- * on the generic Assign mechanism to evaluate the product per coeff (or packet).
- *
- * Note that here the inner-loops should always be unrolled.
- */
-
-template<int Traversal, int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
-struct product_coeff_impl;
-
-template<int StorageOrder, int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl;
-
-template<typename LhsNested, typename RhsNested, int NestingFlags>
-struct traits<CoeffBasedProduct<LhsNested,RhsNested,NestingFlags> >
-{
-  typedef MatrixXpr XprKind;
-  typedef typename remove_all<LhsNested>::type _LhsNested;
-  typedef typename remove_all<RhsNested>::type _RhsNested;
-  typedef typename scalar_product_traits<typename _LhsNested::Scalar, typename _RhsNested::Scalar>::ReturnType Scalar;
-  typedef typename promote_storage_type<typename traits<_LhsNested>::StorageKind,
-                                           typename traits<_RhsNested>::StorageKind>::ret StorageKind;
-  typedef typename promote_index_type<typename traits<_LhsNested>::Index,
-                                         typename traits<_RhsNested>::Index>::type Index;
-
-  enum {
-      LhsCoeffReadCost = _LhsNested::CoeffReadCost,
-      RhsCoeffReadCost = _RhsNested::CoeffReadCost,
-      LhsFlags = _LhsNested::Flags,
-      RhsFlags = _RhsNested::Flags,
-
-      RowsAtCompileTime = _LhsNested::RowsAtCompileTime,
-      ColsAtCompileTime = _RhsNested::ColsAtCompileTime,
-      InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(_LhsNested::ColsAtCompileTime, _RhsNested::RowsAtCompileTime),
-
-      MaxRowsAtCompileTime = _LhsNested::MaxRowsAtCompileTime,
-      MaxColsAtCompileTime = _RhsNested::MaxColsAtCompileTime,
-
-      LhsRowMajor = LhsFlags & RowMajorBit,
-      RhsRowMajor = RhsFlags & RowMajorBit,
-
-      SameType = is_same<typename _LhsNested::Scalar,typename _RhsNested::Scalar>::value,
-
-      CanVectorizeRhs = RhsRowMajor && (RhsFlags & PacketAccessBit)
-                      && (ColsAtCompileTime == Dynamic
-                          || ( (ColsAtCompileTime % packet_traits<Scalar>::size) == 0
-                              && (RhsFlags&AlignedBit)
-                             )
-                         ),
-
-      CanVectorizeLhs = (!LhsRowMajor) && (LhsFlags & PacketAccessBit)
-                      && (RowsAtCompileTime == Dynamic
-                          || ( (RowsAtCompileTime % packet_traits<Scalar>::size) == 0
-                              && (LhsFlags&AlignedBit)
-                             )
-                         ),
-
-      EvalToRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
-                     : (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
-                     : (RhsRowMajor && !CanVectorizeLhs),
-
-      Flags = ((unsigned int)(LhsFlags | RhsFlags) & HereditaryBits & ~RowMajorBit)
-            | (EvalToRowMajor ? RowMajorBit : 0)
-            | NestingFlags
-            | (LhsFlags & RhsFlags & AlignedBit)
-            // TODO enable vectorization for mixed types
-            | (SameType && (CanVectorizeLhs || CanVectorizeRhs) ? PacketAccessBit : 0),
-
-      CoeffReadCost = InnerSize == Dynamic ? Dynamic
-                    : InnerSize == 0 ? 0
-                    : InnerSize * (NumTraits<Scalar>::MulCost + LhsCoeffReadCost + RhsCoeffReadCost)
-                      + (InnerSize - 1) * NumTraits<Scalar>::AddCost,
-
-      /* CanVectorizeInner deserves special explanation. It does not affect the product flags. It is not used outside
-      * of Product. If the Product itself is not a packet-access expression, there is still a chance that the inner
-      * loop of the product might be vectorized. This is the meaning of CanVectorizeInner. Since it doesn't affect
-      * the Flags, it is safe to make this value depend on ActualPacketAccessBit, that doesn't affect the ABI.
-      */
-      CanVectorizeInner =    SameType
-                          && LhsRowMajor
-                          && (!RhsRowMajor)
-                          && (LhsFlags & RhsFlags & ActualPacketAccessBit)
-                          && (LhsFlags & RhsFlags & AlignedBit)
-                          && (InnerSize % packet_traits<Scalar>::size == 0)
-    };
-};
-
-} // end namespace internal
-
-template<typename LhsNested, typename RhsNested, int NestingFlags>
-class CoeffBasedProduct
-  : internal::no_assignment_operator,
-    public MatrixBase<CoeffBasedProduct<LhsNested, RhsNested, NestingFlags> >
-{
-  public:
-
-    typedef MatrixBase<CoeffBasedProduct> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(CoeffBasedProduct)
-    typedef typename Base::PlainObject PlainObject;
-
-  private:
-
-    typedef typename internal::traits<CoeffBasedProduct>::_LhsNested _LhsNested;
-    typedef typename internal::traits<CoeffBasedProduct>::_RhsNested _RhsNested;
-
-    enum {
-      PacketSize = internal::packet_traits<Scalar>::size,
-      InnerSize  = internal::traits<CoeffBasedProduct>::InnerSize,
-      Unroll = CoeffReadCost != Dynamic && CoeffReadCost <= EIGEN_UNROLLING_LIMIT,
-      CanVectorizeInner = internal::traits<CoeffBasedProduct>::CanVectorizeInner
-    };
-
-    typedef internal::product_coeff_impl<CanVectorizeInner ? InnerVectorizedTraversal : DefaultTraversal,
-                                   Unroll ? (InnerSize==0 ? 0 : InnerSize-1) : Dynamic,
-                                   _LhsNested, _RhsNested, Scalar> ScalarCoeffImpl;
-
-    typedef CoeffBasedProduct<LhsNested,RhsNested,NestByRefBit> LazyCoeffBasedProductType;
-
-  public:
-
-    inline CoeffBasedProduct(const CoeffBasedProduct& other)
-      : Base(), m_lhs(other.m_lhs), m_rhs(other.m_rhs)
-    {}
-
-    template<typename Lhs, typename Rhs>
-    inline CoeffBasedProduct(const Lhs& lhs, const Rhs& rhs)
-      : m_lhs(lhs), m_rhs(rhs)
-    {
-      // we don't allow taking products of matrices of different real types, as that wouldn't be vectorizable.
-      // We still allow to mix T and complex<T>.
-      EIGEN_STATIC_ASSERT((internal::scalar_product_traits<typename Lhs::RealScalar, typename Rhs::RealScalar>::Defined),
-        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-      eigen_assert(lhs.cols() == rhs.rows()
-        && "invalid matrix product"
-        && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
-    }
-
-    EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
-
-    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
-    {
-      Scalar res;
-      ScalarCoeffImpl::run(row, col, m_lhs, m_rhs, res);
-      return res;
-    }
-
-    /* Allow index-based non-packet access. It is impossible though to allow index-based packed access,
-     * which is why we don't set the LinearAccessBit.
-     */
-    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
-    {
-      Scalar res;
-      const Index row = RowsAtCompileTime == 1 ? 0 : index;
-      const Index col = RowsAtCompileTime == 1 ? index : 0;
-      ScalarCoeffImpl::run(row, col, m_lhs, m_rhs, res);
-      return res;
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE const PacketScalar packet(Index row, Index col) const
-    {
-      PacketScalar res;
-      internal::product_packet_impl<Flags&RowMajorBit ? RowMajor : ColMajor,
-                              Unroll ? (InnerSize==0 ? 0 : InnerSize-1) : Dynamic,
-                              _LhsNested, _RhsNested, PacketScalar, LoadMode>
-        ::run(row, col, m_lhs, m_rhs, res);
-      return res;
-    }
-
-    // Implicit conversion to the nested type (trigger the evaluation of the product)
-    EIGEN_STRONG_INLINE operator const PlainObject& () const
-    {
-      m_result.lazyAssign(*this);
-      return m_result;
-    }
-
-    const _LhsNested& lhs() const { return m_lhs; }
-    const _RhsNested& rhs() const { return m_rhs; }
-
-    const Diagonal<const LazyCoeffBasedProductType,0> diagonal() const
-    { return reinterpret_cast<const LazyCoeffBasedProductType&>(*this); }
-
-    template<int DiagonalIndex>
-    const Diagonal<const LazyCoeffBasedProductType,DiagonalIndex> diagonal() const
-    { return reinterpret_cast<const LazyCoeffBasedProductType&>(*this); }
-
-    const Diagonal<const LazyCoeffBasedProductType,Dynamic> diagonal(Index index) const
-    { return reinterpret_cast<const LazyCoeffBasedProductType&>(*this).diagonal(index); }
-
-  protected:
-    typename internal::add_const_on_value_type<LhsNested>::type m_lhs;
-    typename internal::add_const_on_value_type<RhsNested>::type m_rhs;
-
-    mutable PlainObject m_result;
-};
-
-namespace internal {
-
-// here we need to overload the nested rule for products
-// such that the nested type is a const reference to a plain matrix
-template<typename Lhs, typename Rhs, int N, typename PlainObject>
-struct nested<CoeffBasedProduct<Lhs,Rhs,EvalBeforeNestingBit|EvalBeforeAssigningBit>, N, PlainObject>
-{
-  typedef PlainObject const& type;
-};
-
-/***************************************************************************
-* Normal product .coeff() implementation (with meta-unrolling)
-***************************************************************************/
-
-/**************************************
-*** Scalar path  - no vectorization ***
-**************************************/
-
-template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
-struct product_coeff_impl<DefaultTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
-  {
-    product_coeff_impl<DefaultTraversal, UnrollingIndex-1, Lhs, Rhs, RetScalar>::run(row, col, lhs, rhs, res);
-    res += lhs.coeff(row, UnrollingIndex) * rhs.coeff(UnrollingIndex, col);
-  }
-};
-
-template<typename Lhs, typename Rhs, typename RetScalar>
-struct product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
-  {
-    res = lhs.coeff(row, 0) * rhs.coeff(0, col);
-  }
-};
-
-template<typename Lhs, typename Rhs, typename RetScalar>
-struct product_coeff_impl<DefaultTraversal, Dynamic, Lhs, Rhs, RetScalar>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar& res)
-  {
-    res = (lhs.row(row).transpose().cwiseProduct( rhs.col(col) )).sum();
-  }
-};
-
-/*******************************************
-*** Scalar path with inner vectorization ***
-*******************************************/
-
-template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet>
-struct product_coeff_vectorized_unroller
-{
-  typedef typename Lhs::Index Index;
-  enum { PacketSize = packet_traits<typename Lhs::Scalar>::size };
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
-  {
-    product_coeff_vectorized_unroller<UnrollingIndex-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, pres);
-    pres = padd(pres, pmul( lhs.template packet<Aligned>(row, UnrollingIndex) , rhs.template packet<Aligned>(UnrollingIndex, col) ));
-  }
-};
-
-template<typename Lhs, typename Rhs, typename Packet>
-struct product_coeff_vectorized_unroller<0, Lhs, Rhs, Packet>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
-  {
-    pres = pmul(lhs.template packet<Aligned>(row, 0) , rhs.template packet<Aligned>(0, col));
-  }
-};
-
-template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
-struct product_coeff_impl<InnerVectorizedTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
-{
-  typedef typename Lhs::PacketScalar Packet;
-  typedef typename Lhs::Index Index;
-  enum { PacketSize = packet_traits<typename Lhs::Scalar>::size };
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
-  {
-    Packet pres;
-    product_coeff_vectorized_unroller<UnrollingIndex+1-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, pres);
-    product_coeff_impl<DefaultTraversal,UnrollingIndex,Lhs,Rhs,RetScalar>::run(row, col, lhs, rhs, res);
-    res = predux(pres);
-  }
-};
-
-template<typename Lhs, typename Rhs, int LhsRows = Lhs::RowsAtCompileTime, int RhsCols = Rhs::ColsAtCompileTime>
-struct product_coeff_vectorized_dyn_selector
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
-  {
-    res = lhs.row(row).transpose().cwiseProduct(rhs.col(col)).sum();
-  }
-};
-
-// NOTE the 3 following specializations are because taking .col(0) on a vector is a bit slower
-// NOTE maybe they are now useless since we have a specialization for Block<Matrix>
-template<typename Lhs, typename Rhs, int RhsCols>
-struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,RhsCols>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
-  {
-    res = lhs.transpose().cwiseProduct(rhs.col(col)).sum();
-  }
-};
-
-template<typename Lhs, typename Rhs, int LhsRows>
-struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,LhsRows,1>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
-  {
-    res = lhs.row(row).transpose().cwiseProduct(rhs).sum();
-  }
-};
-
-template<typename Lhs, typename Rhs>
-struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,1>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
-  {
-    res = lhs.transpose().cwiseProduct(rhs).sum();
-  }
-};
-
-template<typename Lhs, typename Rhs, typename RetScalar>
-struct product_coeff_impl<InnerVectorizedTraversal, Dynamic, Lhs, Rhs, RetScalar>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
-  {
-    product_coeff_vectorized_dyn_selector<Lhs,Rhs>::run(row, col, lhs, rhs, res);
-  }
-};
-
-/*******************
-*** Packet path  ***
-*******************/
-
-template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl<RowMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
-  {
-    product_packet_impl<RowMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, res);
-    res =  pmadd(pset1<Packet>(lhs.coeff(row, UnrollingIndex)), rhs.template packet<LoadMode>(UnrollingIndex, col), res);
-  }
-};
-
-template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl<ColMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
-  {
-    product_packet_impl<ColMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, res);
-    res =  pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex), pset1<Packet>(rhs.coeff(UnrollingIndex, col)), res);
-  }
-};
-
-template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
-  {
-    res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
-  }
-};
-
-template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
-  {
-    res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
-  }
-};
-
-template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
-  {
-    eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
-    res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
-      for(Index i = 1; i < lhs.cols(); ++i)
-        res =  pmadd(pset1<Packet>(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res);
-  }
-};
-
-template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
-{
-  typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
-  {
-    eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
-    res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
-      for(Index i = 1; i < lhs.cols(); ++i)
-        res =  pmadd(lhs.template packet<LoadMode>(row, i), pset1<Packet>(rhs.coeff(i, col)), res);
-  }
-};
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_COEFFBASED_PRODUCT_H

Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h
@@ -8,12 +8,13 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERAL_BLOCK_PANEL_H
 #define EIGEN_GENERAL_BLOCK_PANEL_H
 
-namespace Eigen { 
-  
+
+namespace Eigen {
+
 namespace internal {
 
 template<typename _LhsScalar, typename _RhsScalar, bool _ConjLhs=false, bool _ConjRhs=false>
 class gebp_traits;
 
@@ -21,91 +22,295 @@
 /** \internal \returns b if a<=0, and returns a otherwise. */
 inline std::ptrdiff_t manage_caching_sizes_helper(std::ptrdiff_t a, std::ptrdiff_t b)
 {
   return a<=0 ? b : a;
 }
+
+#if EIGEN_ARCH_i386_OR_x86_64
+const std::ptrdiff_t defaultL1CacheSize = 32*1024;
+const std::ptrdiff_t defaultL2CacheSize = 256*1024;
+const std::ptrdiff_t defaultL3CacheSize = 2*1024*1024;
+#else
+const std::ptrdiff_t defaultL1CacheSize = 16*1024;
+const std::ptrdiff_t defaultL2CacheSize = 512*1024;
+const std::ptrdiff_t defaultL3CacheSize = 512*1024;
+#endif
+
+/** \internal */
+struct CacheSizes {
+  CacheSizes(): m_l1(-1),m_l2(-1),m_l3(-1) {
+    int l1CacheSize, l2CacheSize, l3CacheSize;
+    queryCacheSizes(l1CacheSize, l2CacheSize, l3CacheSize);
+    m_l1 = manage_caching_sizes_helper(l1CacheSize, defaultL1CacheSize);
+    m_l2 = manage_caching_sizes_helper(l2CacheSize, defaultL2CacheSize);
+    m_l3 = manage_caching_sizes_helper(l3CacheSize, defaultL3CacheSize);
+  }
+
+  std::ptrdiff_t m_l1;
+  std::ptrdiff_t m_l2;
+  std::ptrdiff_t m_l3;
+};
+
 
 /** \internal */
-inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1=0, std::ptrdiff_t* l2=0)
-{
-  static std::ptrdiff_t m_l1CacheSize = 0;
-  static std::ptrdiff_t m_l2CacheSize = 0;
-  if(m_l2CacheSize==0)
-  {
-    m_l1CacheSize = manage_caching_sizes_helper(queryL1CacheSize(),8 * 1024);
-    m_l2CacheSize = manage_caching_sizes_helper(queryTopLevelCacheSize(),1*1024*1024);
-  }
-  
+inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1, std::ptrdiff_t* l2, std::ptrdiff_t* l3)
+{
+  static CacheSizes m_cacheSizes;
+
   if(action==SetAction)
   {
     // set the cpu cache size and cache all block sizes from a global cache size in byte
     eigen_internal_assert(l1!=0 && l2!=0);
-    m_l1CacheSize = *l1;
-    m_l2CacheSize = *l2;
+    m_cacheSizes.m_l1 = *l1;
+    m_cacheSizes.m_l2 = *l2;
+    m_cacheSizes.m_l3 = *l3;
   }
   else if(action==GetAction)
   {
     eigen_internal_assert(l1!=0 && l2!=0);
-    *l1 = m_l1CacheSize;
-    *l2 = m_l2CacheSize;
+    *l1 = m_cacheSizes.m_l1;
+    *l2 = m_cacheSizes.m_l2;
+    *l3 = m_cacheSizes.m_l3;
   }
   else
   {
     eigen_internal_assert(false);
   }
 }
+
+/* Helper for computeProductBlockingSizes.
+ *
+ * Given a m x k times k x n matrix product of scalar types \c LhsScalar and \c RhsScalar,
+ * this function computes the blocking size parameters along the respective dimensions
+ * for matrix products and related algorithms. The blocking sizes depends on various
+ * parameters:
+ * - the L1 and L2 cache sizes,
+ * - the register level blocking sizes defined by gebp_traits,
+ * - the number of scalars that fit into a packet (when vectorization is enabled).
+ *
+ * \sa setCpuCacheSizes */
+
+template<typename LhsScalar, typename RhsScalar, int KcFactor, typename Index>
+void evaluateProductBlockingSizesHeuristic(Index& k, Index& m, Index& n, Index num_threads = 1)
+{
+  typedef gebp_traits<LhsScalar,RhsScalar> Traits;
+
+  // Explanations:
+  // Let's recall that the product algorithms form mc x kc vertical panels A' on the lhs and
+  // kc x nc blocks B' on the rhs. B' has to fit into L2/L3 cache. Moreover, A' is processed
+  // per mr x kc horizontal small panels where mr is the blocking size along the m dimension
+  // at the register level. This small horizontal panel has to stay within L1 cache.
+  std::ptrdiff_t l1, l2, l3;
+  manage_caching_sizes(GetAction, &l1, &l2, &l3);
+
+  if (num_threads > 1) {
+    typedef typename Traits::ResScalar ResScalar;
+    enum {
+      kdiv = KcFactor * (Traits::mr * sizeof(LhsScalar) + Traits::nr * sizeof(RhsScalar)),
+      ksub = Traits::mr * Traits::nr * sizeof(ResScalar),
+      kr = 8,
+      mr = Traits::mr,
+      nr = Traits::nr
+    };
+    // Increasing k gives us more time to prefetch the content of the "C"
+    // registers. However once the latency is hidden there is no point in
+    // increasing the value of k, so we'll cap it at 320 (value determined
+    // experimentally).
+    const Index k_cache = (numext::mini<Index>)((l1-ksub)/kdiv, 320);
+    if (k_cache < k) {
+      k = k_cache - (k_cache % kr);
+      eigen_internal_assert(k > 0);
+    }
+
+    const Index n_cache = (l2-l1) / (nr * sizeof(RhsScalar) * k);
+    const Index n_per_thread = numext::div_ceil(n, num_threads);
+    if (n_cache <= n_per_thread) {
+      // Don't exceed the capacity of the l2 cache.
+      eigen_internal_assert(n_cache >= static_cast<Index>(nr));
+      n = n_cache - (n_cache % nr);
+      eigen_internal_assert(n > 0);
+    } else {
+      n = (numext::mini<Index>)(n, (n_per_thread + nr - 1) - ((n_per_thread + nr - 1) % nr));
+    }
+
+    if (l3 > l2) {
+      // l3 is shared between all cores, so we'll give each thread its own chunk of l3.
+      const Index m_cache = (l3-l2) / (sizeof(LhsScalar) * k * num_threads);
+      const Index m_per_thread = numext::div_ceil(m, num_threads);
+      if(m_cache < m_per_thread && m_cache >= static_cast<Index>(mr)) {
+        m = m_cache - (m_cache % mr);
+        eigen_internal_assert(m > 0);
+      } else {
+        m = (numext::mini<Index>)(m, (m_per_thread + mr - 1) - ((m_per_thread + mr - 1) % mr));
+      }
+    }
+  }
+  else {
+    // In unit tests we do not want to use extra large matrices,
+    // so we reduce the cache size to check the blocking strategy is not flawed
+#ifdef EIGEN_DEBUG_SMALL_PRODUCT_BLOCKS
+    l1 = 9*1024;
+    l2 = 32*1024;
+    l3 = 512*1024;
+#endif
+
+    // Early return for small problems because the computation below are time consuming for small problems.
+    // Perhaps it would make more sense to consider k*n*m??
+    // Note that for very tiny problem, this function should be bypassed anyway
+    // because we use the coefficient-based implementation for them.
+    if((numext::maxi)(k,(numext::maxi)(m,n))<48)
+      return;
+
+    typedef typename Traits::ResScalar ResScalar;
+    enum {
+      k_peeling = 8,
+      k_div = KcFactor * (Traits::mr * sizeof(LhsScalar) + Traits::nr * sizeof(RhsScalar)),
+      k_sub = Traits::mr * Traits::nr * sizeof(ResScalar)
+    };
+
+    // ---- 1st level of blocking on L1, yields kc ----
+
+    // Blocking on the third dimension (i.e., k) is chosen so that an horizontal panel
+    // of size mr x kc of the lhs plus a vertical panel of kc x nr of the rhs both fits within L1 cache.
+    // We also include a register-level block of the result (mx x nr).
+    // (In an ideal world only the lhs panel would stay in L1)
+    // Moreover, kc has to be a multiple of 8 to be compatible with loop peeling, leading to a maximum blocking size of:
+    const Index max_kc = numext::maxi<Index>(((l1-k_sub)/k_div) & (~(k_peeling-1)),1);
+    const Index old_k = k;
+    if(k>max_kc)
+    {
+      // We are really blocking on the third dimension:
+      // -> reduce blocking size to make sure the last block is as large as possible
+      //    while keeping the same number of sweeps over the result.
+      k = (k%max_kc)==0 ? max_kc
+                        : max_kc - k_peeling * ((max_kc-1-(k%max_kc))/(k_peeling*(k/max_kc+1)));
+
+      eigen_internal_assert(((old_k/k) == (old_k/max_kc)) && "the number of sweeps has to remain the same");
+    }
+
+    // ---- 2nd level of blocking on max(L2,L3), yields nc ----
+
+    // TODO find a reliable way to get the actual amount of cache per core to use for 2nd level blocking, that is:
+    //      actual_l2 = max(l2, l3/nb_core_sharing_l3)
+    // The number below is quite conservative: it is better to underestimate the cache size rather than overestimating it)
+    // For instance, it corresponds to 6MB of L3 shared among 4 cores.
+    #ifdef EIGEN_DEBUG_SMALL_PRODUCT_BLOCKS
+    const Index actual_l2 = l3;
+    #else
+    const Index actual_l2 = 1572864; // == 1.5 MB
+    #endif
+
+    // Here, nc is chosen such that a block of kc x nc of the rhs fit within half of L2.
+    // The second half is implicitly reserved to access the result and lhs coefficients.
+    // When k<max_kc, then nc can arbitrarily growth. In practice, it seems to be fruitful
+    // to limit this growth: we bound nc to growth by a factor x1.5.
+    // However, if the entire lhs block fit within L1, then we are not going to block on the rows at all,
+    // and it becomes fruitful to keep the packed rhs blocks in L1 if there is enough remaining space.
+    Index max_nc;
+    const Index lhs_bytes = m * k * sizeof(LhsScalar);
+    const Index remaining_l1 = l1- k_sub - lhs_bytes;
+    if(remaining_l1 >= Index(Traits::nr*sizeof(RhsScalar))*k)
+    {
+      // L1 blocking
+      max_nc = remaining_l1 / (k*sizeof(RhsScalar));
+    }
+    else
+    {
+      // L2 blocking
+      max_nc = (3*actual_l2)/(2*2*max_kc*sizeof(RhsScalar));
+    }
+    // WARNING Below, we assume that Traits::nr is a power of two.
+    Index nc = numext::mini<Index>(actual_l2/(2*k*sizeof(RhsScalar)), max_nc) & (~(Traits::nr-1));
+    if(n>nc)
+    {
+      // We are really blocking over the columns:
+      // -> reduce blocking size to make sure the last block is as large as possible
+      //    while keeping the same number of sweeps over the packed lhs.
+      //    Here we allow one more sweep if this gives us a perfect match, thus the commented "-1"
+      n = (n%nc)==0 ? nc
+                    : (nc - Traits::nr * ((nc/*-1*/-(n%nc))/(Traits::nr*(n/nc+1))));
+    }
+    else if(old_k==k)
+    {
+      // So far, no blocking at all, i.e., kc==k, and nc==n.
+      // In this case, let's perform a blocking over the rows such that the packed lhs data is kept in cache L1/L2
+      // TODO: part of this blocking strategy is now implemented within the kernel itself, so the L1-based heuristic here should be obsolete.
+      Index problem_size = k*n*sizeof(LhsScalar);
+      Index actual_lm = actual_l2;
+      Index max_mc = m;
+      if(problem_size<=1024)
+      {
+        // problem is small enough to keep in L1
+        // Let's choose m such that lhs's block fit in 1/3 of L1
+        actual_lm = l1;
+      }
+      else if(l3!=0 && problem_size<=32768)
+      {
+        // we have both L2 and L3, and problem is small enough to be kept in L2
+        // Let's choose m such that lhs's block fit in 1/3 of L2
+        actual_lm = l2;
+        max_mc = (numext::mini<Index>)(576,max_mc);
+      }
+      Index mc = (numext::mini<Index>)(actual_lm/(3*k*sizeof(LhsScalar)), max_mc);
+      if (mc > Traits::mr) mc -= mc % Traits::mr;
+      else if (mc==0) return;
+      m = (m%mc)==0 ? mc
+                    : (mc - Traits::mr * ((mc/*-1*/-(m%mc))/(Traits::mr*(m/mc+1))));
+    }
+  }
+}
+
+template <typename Index>
+inline bool useSpecificBlockingSizes(Index& k, Index& m, Index& n)
+{
+#ifdef EIGEN_TEST_SPECIFIC_BLOCKING_SIZES
+  if (EIGEN_TEST_SPECIFIC_BLOCKING_SIZES) {
+    k = numext::mini<Index>(k, EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_K);
+    m = numext::mini<Index>(m, EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_M);
+    n = numext::mini<Index>(n, EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_N);
+    return true;
+  }
+#else
+  EIGEN_UNUSED_VARIABLE(k)
+  EIGEN_UNUSED_VARIABLE(m)
+  EIGEN_UNUSED_VARIABLE(n)
+#endif
+  return false;
+}
 
 /** \brief Computes the blocking parameters for a m x k times k x n matrix product
   *
   * \param[in,out] k Input: the third dimension of the product. Output: the blocking size along the same dimension.
   * \param[in,out] m Input: the number of rows of the left hand side. Output: the blocking size along the same dimension.
   * \param[in,out] n Input: the number of columns of the right hand side. Output: the blocking size along the same dimension.
   *
   * Given a m x k times k x n matrix product of scalar types \c LhsScalar and \c RhsScalar,
   * this function computes the blocking size parameters along the respective dimensions
-  * for matrix products and related algorithms. The blocking sizes depends on various
-  * parameters:
-  * - the L1 and L2 cache sizes,
-  * - the register level blocking sizes defined by gebp_traits,
-  * - the number of scalars that fit into a packet (when vectorization is enabled).
+  * for matrix products and related algorithms.
+  *
+  * The blocking size parameters may be evaluated:
+  *   - either by a heuristic based on cache sizes;
+  *   - or using fixed prescribed values (for testing purposes).
   *
   * \sa setCpuCacheSizes */
-template<typename LhsScalar, typename RhsScalar, int KcFactor, typename SizeType>
-void computeProductBlockingSizes(SizeType& k, SizeType& m, SizeType& n)
-{
-  EIGEN_UNUSED_VARIABLE(n);
-  // Explanations:
-  // Let's recall the product algorithms form kc x nc horizontal panels B' on the rhs and
-  // mc x kc blocks A' on the lhs. A' has to fit into L2 cache. Moreover, B' is processed
-  // per kc x nr vertical small panels where nr is the blocking size along the n dimension
-  // at the register level. For vectorization purpose, these small vertical panels are unpacked,
-  // e.g., each coefficient is replicated to fit a packet. This small vertical panel has to
-  // stay in L1 cache.
-  std::ptrdiff_t l1, l2;
-
-  typedef gebp_traits<LhsScalar,RhsScalar> Traits;
-  enum {
-    kdiv = KcFactor * 2 * Traits::nr
-         * Traits::RhsProgress * sizeof(RhsScalar),
-    mr = gebp_traits<LhsScalar,RhsScalar>::mr,
-    mr_mask = (0xffffffff/mr)*mr
-  };
-
-  manage_caching_sizes(GetAction, &l1, &l2);
-  k = std::min<SizeType>(k, l1/kdiv);
-  SizeType _m = k>0 ? l2/(4 * sizeof(LhsScalar) * k) : 0;
-  if(_m<m) m = _m & mr_mask;
-}
-
-template<typename LhsScalar, typename RhsScalar, typename SizeType>
-inline void computeProductBlockingSizes(SizeType& k, SizeType& m, SizeType& n)
-{
-  computeProductBlockingSizes<LhsScalar,RhsScalar,1>(k, m, n);
-}
-
-#ifdef EIGEN_HAS_FUSE_CJMADD
-  #define MADD(CJ,A,B,C,T)  C = CJ.pmadd(A,B,C);
+
+template<typename LhsScalar, typename RhsScalar, int KcFactor, typename Index>
+void computeProductBlockingSizes(Index& k, Index& m, Index& n, Index num_threads = 1)
+{
+  if (!useSpecificBlockingSizes(k, m, n)) {
+    evaluateProductBlockingSizesHeuristic<LhsScalar, RhsScalar, KcFactor, Index>(k, m, n, num_threads);
+  }
+}
+
+template<typename LhsScalar, typename RhsScalar, typename Index>
+inline void computeProductBlockingSizes(Index& k, Index& m, Index& n, Index num_threads = 1)
+{
+  computeProductBlockingSizes<LhsScalar,RhsScalar,1,Index>(k, m, n, num_threads);
+}
+
+#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
+  #define CJMADD(CJ,A,B,C,T)  C = CJ.pmadd(A,B,C);
 #else
 
   // FIXME (a bit overkill maybe ?)
 
   template<typename CJ, typename A, typename B, typename C, typename T> struct gebp_madd_selector {
@@ -126,12 +331,12 @@
   EIGEN_STRONG_INLINE void gebp_madd(const CJ& cj, A& a, B& b, C& c, T& t)
   {
     gebp_madd_selector<CJ,A,B,C,T>::run(cj,a,b,c,t);
   }
 
-  #define MADD(CJ,A,B,C,T)  gebp_madd(CJ,A,B,C,T);
-//   #define MADD(CJ,A,B,C,T)  T = B; T = CJ.pmul(A,T); C = padd(C,T);
+  #define CJMADD(CJ,A,B,C,T)  gebp_madd(CJ,A,B,C,T);
+//   #define CJMADD(CJ,A,B,C,T)  T = B; T = CJ.pmul(A,T); C = padd(C,T);
 #endif
 
 /* Vectorization logic
  *  real*real: unpack rhs to constant packets, ...
  * 
@@ -146,11 +351,11 @@
 class gebp_traits
 {
 public:
   typedef _LhsScalar LhsScalar;
   typedef _RhsScalar RhsScalar;
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
 
   enum {
     ConjLhs = _ConjLhs,
     ConjRhs = _ConjRhs,
     Vectorizable = packet_traits<LhsScalar>::Vectorizable && packet_traits<RhsScalar>::Vectorizable,
@@ -158,20 +363,26 @@
     RhsPacketSize = Vectorizable ? packet_traits<RhsScalar>::size : 1,
     ResPacketSize = Vectorizable ? packet_traits<ResScalar>::size : 1,
     
     NumberOfRegisters = EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS,
 
-    // register block size along the N direction (must be either 2 or 4)
-    nr = NumberOfRegisters/4,
+    // register block size along the N direction must be 1 or 4
+    nr = 4,
 
     // register block size along the M direction (currently, this one cannot be modified)
-    mr = 2 * LhsPacketSize,
+    default_mr = (EIGEN_PLAIN_ENUM_MIN(16,NumberOfRegisters)/2/nr)*LhsPacketSize,
+#if defined(EIGEN_HAS_SINGLE_INSTRUCTION_MADD) && !defined(EIGEN_VECTORIZE_ALTIVEC) && !defined(EIGEN_VECTORIZE_VSX)
+    // we assume 16 registers
+    // See bug 992, if the scalar type is not vectorizable but that EIGEN_HAS_SINGLE_INSTRUCTION_MADD is defined,
+    // then using 3*LhsPacketSize triggers non-implemented paths in syrk.
+    mr = Vectorizable ? 3*LhsPacketSize : default_mr,
+#else
+    mr = default_mr,
+#endif
     
-    WorkSpaceFactor = nr * RhsPacketSize,
-
     LhsProgress = LhsPacketSize,
-    RhsProgress = RhsPacketSize
+    RhsProgress = 1
   };
 
   typedef typename packet_traits<LhsScalar>::type  _LhsPacket;
   typedef typename packet_traits<RhsScalar>::type  _RhsPacket;
   typedef typename packet_traits<ResScalar>::type  _ResPacket;
@@ -184,49 +395,80 @@
   
   EIGEN_STRONG_INLINE void initAcc(AccPacket& p)
   {
     p = pset1<ResPacket>(ResScalar(0));
   }
-
-  EIGEN_STRONG_INLINE void unpackRhs(DenseIndex n, const RhsScalar* rhs, RhsScalar* b)
-  {
-    for(DenseIndex k=0; k<n; k++)
-      pstore1<RhsPacket>(&b[k*RhsPacketSize], rhs[k]);
-  }
-
-  EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, RhsPacket& dest) const
-  {
-    dest = pload<RhsPacket>(b);
-  }
-
-  EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacket& dest) const
-  {
-    dest = pload<LhsPacket>(a);
-  }
-
-  EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, AccPacket& c, AccPacket& tmp) const
-  {
-    tmp = b; tmp = pmul(a,tmp); c = padd(c,tmp);
+  
+  EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1, RhsPacket& b2, RhsPacket& b3)
+  {
+    pbroadcast4(b, b0, b1, b2, b3);
+  }
+  
+//   EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1)
+//   {
+//     pbroadcast2(b, b0, b1);
+//   }
+  
+  template<typename RhsPacketType>
+  EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, RhsPacketType& dest) const
+  {
+    dest = pset1<RhsPacketType>(*b);
+  }
+  
+  EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, RhsPacket& dest) const
+  {
+    dest = ploadquad<RhsPacket>(b);
+  }
+
+  template<typename LhsPacketType>
+  EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacketType& dest) const
+  {
+    dest = pload<LhsPacketType>(a);
+  }
+
+  template<typename LhsPacketType>
+  EIGEN_STRONG_INLINE void loadLhsUnaligned(const LhsScalar* a, LhsPacketType& dest) const
+  {
+    dest = ploadu<LhsPacketType>(a);
+  }
+
+  template<typename LhsPacketType, typename RhsPacketType, typename AccPacketType>
+  EIGEN_STRONG_INLINE void madd(const LhsPacketType& a, const RhsPacketType& b, AccPacketType& c, AccPacketType& tmp) const
+  {
+    conj_helper<LhsPacketType,RhsPacketType,ConjLhs,ConjRhs> cj;
+    // It would be a lot cleaner to call pmadd all the time. Unfortunately if we
+    // let gcc allocate the register in which to store the result of the pmul
+    // (in the case where there is no FMA) gcc fails to figure out how to avoid
+    // spilling register.
+#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+    EIGEN_UNUSED_VARIABLE(tmp);
+    c = cj.pmadd(a,b,c);
+#else
+    tmp = b; tmp = cj.pmul(a,tmp); c = padd(c,tmp);
+#endif
   }
 
   EIGEN_STRONG_INLINE void acc(const AccPacket& c, const ResPacket& alpha, ResPacket& r) const
   {
     r = pmadd(c,alpha,r);
   }
+  
+  template<typename ResPacketHalf>
+  EIGEN_STRONG_INLINE void acc(const ResPacketHalf& c, const ResPacketHalf& alpha, ResPacketHalf& r) const
+  {
+    r = pmadd(c,alpha,r);
+  }
 
-protected:
-//   conj_helper<LhsScalar,RhsScalar,ConjLhs,ConjRhs> cj;
-//   conj_helper<LhsPacket,RhsPacket,ConjLhs,ConjRhs> pcj;
 };
 
 template<typename RealScalar, bool _ConjLhs>
 class gebp_traits<std::complex<RealScalar>, RealScalar, _ConjLhs, false>
 {
 public:
   typedef std::complex<RealScalar> LhsScalar;
   typedef RealScalar RhsScalar;
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
 
   enum {
     ConjLhs = _ConjLhs,
     ConjRhs = false,
     Vectorizable = packet_traits<LhsScalar>::Vectorizable && packet_traits<RhsScalar>::Vectorizable,
@@ -233,16 +475,20 @@
     LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1,
     RhsPacketSize = Vectorizable ? packet_traits<RhsScalar>::size : 1,
     ResPacketSize = Vectorizable ? packet_traits<ResScalar>::size : 1,
     
     NumberOfRegisters = EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS,
-    nr = NumberOfRegisters/4,
-    mr = 2 * LhsPacketSize,
-    WorkSpaceFactor = nr*RhsPacketSize,
+    nr = 4,
+#if defined(EIGEN_HAS_SINGLE_INSTRUCTION_MADD) && !defined(EIGEN_VECTORIZE_ALTIVEC) && !defined(EIGEN_VECTORIZE_VSX)
+    // we assume 16 registers
+    mr = 3*LhsPacketSize,
+#else
+    mr = (EIGEN_PLAIN_ENUM_MIN(16,NumberOfRegisters)/2/nr)*LhsPacketSize,
+#endif
 
     LhsProgress = LhsPacketSize,
-    RhsProgress = RhsPacketSize
+    RhsProgress = 1
   };
 
   typedef typename packet_traits<LhsScalar>::type  _LhsPacket;
   typedef typename packet_traits<RhsScalar>::type  _RhsPacket;
   typedef typename packet_traits<ResScalar>::type  _ResPacket;
@@ -256,34 +502,53 @@
   EIGEN_STRONG_INLINE void initAcc(AccPacket& p)
   {
     p = pset1<ResPacket>(ResScalar(0));
   }
 
-  EIGEN_STRONG_INLINE void unpackRhs(DenseIndex n, const RhsScalar* rhs, RhsScalar* b)
-  {
-    for(DenseIndex k=0; k<n; k++)
-      pstore1<RhsPacket>(&b[k*RhsPacketSize], rhs[k]);
-  }
-
   EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, RhsPacket& dest) const
   {
-    dest = pload<RhsPacket>(b);
+    dest = pset1<RhsPacket>(*b);
+  }
+  
+  EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, RhsPacket& dest) const
+  {
+    dest = pset1<RhsPacket>(*b);
   }
 
   EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacket& dest) const
   {
     dest = pload<LhsPacket>(a);
   }
+
+  EIGEN_STRONG_INLINE void loadLhsUnaligned(const LhsScalar* a, LhsPacket& dest) const
+  {
+    dest = ploadu<LhsPacket>(a);
+  }
+
+  EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1, RhsPacket& b2, RhsPacket& b3)
+  {
+    pbroadcast4(b, b0, b1, b2, b3);
+  }
+  
+//   EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1)
+//   {
+//     pbroadcast2(b, b0, b1);
+//   }
 
   EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, AccPacket& c, RhsPacket& tmp) const
   {
     madd_impl(a, b, c, tmp, typename conditional<Vectorizable,true_type,false_type>::type());
   }
 
   EIGEN_STRONG_INLINE void madd_impl(const LhsPacket& a, const RhsPacket& b, AccPacket& c, RhsPacket& tmp, const true_type&) const
   {
+#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+    EIGEN_UNUSED_VARIABLE(tmp);
+    c.v = pmadd(a.v,b,c.v);
+#else
     tmp = b; tmp = pmul(a.v,tmp); c.v = padd(c.v,tmp);
+#endif
   }
 
   EIGEN_STRONG_INLINE void madd_impl(const LhsScalar& a, const RhsScalar& b, ResScalar& c, RhsScalar& /*tmp*/, const false_type&) const
   {
     c += a * b;
@@ -295,10 +560,42 @@
   }
 
 protected:
   conj_helper<ResPacket,ResPacket,ConjLhs,false> cj;
 };
+
+template<typename Packet>
+struct DoublePacket
+{
+  Packet first;
+  Packet second;
+};
+
+template<typename Packet>
+DoublePacket<Packet> padd(const DoublePacket<Packet> &a, const DoublePacket<Packet> &b)
+{
+  DoublePacket<Packet> res;
+  res.first  = padd(a.first, b.first);
+  res.second = padd(a.second,b.second);
+  return res;
+}
+
+template<typename Packet>
+const DoublePacket<Packet>& predux_downto4(const DoublePacket<Packet> &a)
+{
+  return a;
+}
+
+template<typename Packet> struct unpacket_traits<DoublePacket<Packet> > { typedef DoublePacket<Packet> half; };
+// template<typename Packet>
+// DoublePacket<Packet> pmadd(const DoublePacket<Packet> &a, const DoublePacket<Packet> &b)
+// {
+//   DoublePacket<Packet> res;
+//   res.first  = padd(a.first, b.first);
+//   res.second = padd(a.second,b.second);
+//   return res;
+// }
 
 template<typename RealScalar, bool _ConjLhs, bool _ConjRhs>
 class gebp_traits<std::complex<RealScalar>, std::complex<RealScalar>, _ConjLhs, _ConjRhs >
 {
 public:
@@ -312,73 +609,98 @@
     ConjRhs = _ConjRhs,
     Vectorizable = packet_traits<RealScalar>::Vectorizable
                 && packet_traits<Scalar>::Vectorizable,
     RealPacketSize  = Vectorizable ? packet_traits<RealScalar>::size : 1,
     ResPacketSize   = Vectorizable ? packet_traits<ResScalar>::size : 1,
-    
-    nr = 2,
-    mr = 2 * ResPacketSize,
-    WorkSpaceFactor = Vectorizable ? 2*nr*RealPacketSize : nr,
+    LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1,
+    RhsPacketSize = Vectorizable ? packet_traits<RhsScalar>::size : 1,
+
+    // FIXME: should depend on NumberOfRegisters
+    nr = 4,
+    mr = ResPacketSize,
 
     LhsProgress = ResPacketSize,
-    RhsProgress = Vectorizable ? 2*ResPacketSize : 1
+    RhsProgress = 1
   };
   
   typedef typename packet_traits<RealScalar>::type RealPacket;
   typedef typename packet_traits<Scalar>::type     ScalarPacket;
-  struct DoublePacket
-  {
-    RealPacket first;
-    RealPacket second;
-  };
+  typedef DoublePacket<RealPacket> DoublePacketType;
 
   typedef typename conditional<Vectorizable,RealPacket,  Scalar>::type LhsPacket;
-  typedef typename conditional<Vectorizable,DoublePacket,Scalar>::type RhsPacket;
+  typedef typename conditional<Vectorizable,DoublePacketType,Scalar>::type RhsPacket;
   typedef typename conditional<Vectorizable,ScalarPacket,Scalar>::type ResPacket;
-  typedef typename conditional<Vectorizable,DoublePacket,Scalar>::type AccPacket;
+  typedef typename conditional<Vectorizable,DoublePacketType,Scalar>::type AccPacket;
   
   EIGEN_STRONG_INLINE void initAcc(Scalar& p) { p = Scalar(0); }
 
-  EIGEN_STRONG_INLINE void initAcc(DoublePacket& p)
+  EIGEN_STRONG_INLINE void initAcc(DoublePacketType& p)
   {
     p.first   = pset1<RealPacket>(RealScalar(0));
     p.second  = pset1<RealPacket>(RealScalar(0));
   }
 
-  /* Unpack the rhs coeff such that each complex coefficient is spread into
-   * two packects containing respectively the real and imaginary coefficient
-   * duplicated as many time as needed: (x+iy) => [x, ..., x] [y, ..., y]
-   */
-  EIGEN_STRONG_INLINE void unpackRhs(DenseIndex n, const Scalar* rhs, Scalar* b)
-  {
-    for(DenseIndex k=0; k<n; k++)
-    {
-      if(Vectorizable)
-      {
-        pstore1<RealPacket>((RealScalar*)&b[k*ResPacketSize*2+0],             real(rhs[k]));
-        pstore1<RealPacket>((RealScalar*)&b[k*ResPacketSize*2+ResPacketSize], imag(rhs[k]));
-      }
-      else
-        b[k] = rhs[k];
-    }
-  }
-
-  EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, ResPacket& dest) const { dest = *b; }
-
-  EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, DoublePacket& dest) const
-  {
-    dest.first  = pload<RealPacket>((const RealScalar*)b);
-    dest.second = pload<RealPacket>((const RealScalar*)(b+ResPacketSize));
+  // Scalar path
+  EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, ResPacket& dest) const
+  {
+    dest = pset1<ResPacket>(*b);
+  }
+
+  // Vectorized path
+  EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, DoublePacketType& dest) const
+  {
+    dest.first  = pset1<RealPacket>(real(*b));
+    dest.second = pset1<RealPacket>(imag(*b));
+  }
+  
+  EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, ResPacket& dest) const
+  {
+    loadRhs(b,dest);
+  }
+  EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, DoublePacketType& dest) const
+  {
+    eigen_internal_assert(unpacket_traits<ScalarPacket>::size<=4);
+    loadRhs(b,dest);
+  }
+  
+  EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1, RhsPacket& b2, RhsPacket& b3)
+  {
+    // FIXME not sure that's the best way to implement it!
+    loadRhs(b+0, b0);
+    loadRhs(b+1, b1);
+    loadRhs(b+2, b2);
+    loadRhs(b+3, b3);
+  }
+  
+  // Vectorized path
+  EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, DoublePacketType& b0, DoublePacketType& b1)
+  {
+    // FIXME not sure that's the best way to implement it!
+    loadRhs(b+0, b0);
+    loadRhs(b+1, b1);
+  }
+  
+  // Scalar path
+  EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsScalar& b0, RhsScalar& b1)
+  {
+    // FIXME not sure that's the best way to implement it!
+    loadRhs(b+0, b0);
+    loadRhs(b+1, b1);
   }
 
   // nothing special here
   EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacket& dest) const
   {
     dest = pload<LhsPacket>((const typename unpacket_traits<LhsPacket>::type*)(a));
   }
 
-  EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, DoublePacket& c, RhsPacket& /*tmp*/) const
+  EIGEN_STRONG_INLINE void loadLhsUnaligned(const LhsScalar* a, LhsPacket& dest) const
+  {
+    dest = ploadu<LhsPacket>((const typename unpacket_traits<LhsPacket>::type*)(a));
+  }
+
+  EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, DoublePacketType& c, RhsPacket& /*tmp*/) const
   {
     c.first   = padd(pmul(a,b.first), c.first);
     c.second  = padd(pmul(a,b.second),c.second);
   }
 
@@ -387,11 +709,11 @@
     c = cj.pmadd(a,b,c);
   }
   
   EIGEN_STRONG_INLINE void acc(const Scalar& c, const Scalar& alpha, Scalar& r) const { r += alpha * c; }
   
-  EIGEN_STRONG_INLINE void acc(const DoublePacket& c, const ResPacket& alpha, ResPacket& r) const
+  EIGEN_STRONG_INLINE void acc(const DoublePacketType& c, const ResPacket& alpha, ResPacket& r) const
   {
     // assemble c
     ResPacket tmp;
     if((!ConjLhs)&&(!ConjRhs))
     {
@@ -438,16 +760,16 @@
     LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1,
     RhsPacketSize = Vectorizable ? packet_traits<RhsScalar>::size : 1,
     ResPacketSize = Vectorizable ? packet_traits<ResScalar>::size : 1,
     
     NumberOfRegisters = EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS,
+    // FIXME: should depend on NumberOfRegisters
     nr = 4,
-    mr = 2*ResPacketSize,
-    WorkSpaceFactor = nr*RhsPacketSize,
+    mr = (EIGEN_PLAIN_ENUM_MIN(16,NumberOfRegisters)/2/nr)*ResPacketSize,
 
     LhsProgress = ResPacketSize,
-    RhsProgress = ResPacketSize
+    RhsProgress = 1
   };
 
   typedef typename packet_traits<LhsScalar>::type  _LhsPacket;
   typedef typename packet_traits<RhsScalar>::type  _RhsPacket;
   typedef typename packet_traits<ResScalar>::type  _ResPacket;
@@ -461,23 +783,40 @@
   EIGEN_STRONG_INLINE void initAcc(AccPacket& p)
   {
     p = pset1<ResPacket>(ResScalar(0));
   }
 
-  EIGEN_STRONG_INLINE void unpackRhs(DenseIndex n, const RhsScalar* rhs, RhsScalar* b)
-  {
-    for(DenseIndex k=0; k<n; k++)
-      pstore1<RhsPacket>(&b[k*RhsPacketSize], rhs[k]);
-  }
-
   EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, RhsPacket& dest) const
   {
-    dest = pload<RhsPacket>(b);
+    dest = pset1<RhsPacket>(*b);
+  }
+  
+  void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1, RhsPacket& b2, RhsPacket& b3)
+  {
+    pbroadcast4(b, b0, b1, b2, b3);
   }
+  
+//   EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1)
+//   {
+//     // FIXME not sure that's the best way to implement it!
+//     b0 = pload1<RhsPacket>(b+0);
+//     b1 = pload1<RhsPacket>(b+1);
+//   }
 
   EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacket& dest) const
   {
+    dest = ploaddup<LhsPacket>(a);
+  }
+  
+  EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, RhsPacket& dest) const
+  {
+    eigen_internal_assert(unpacket_traits<RhsPacket>::size<=4);
+    loadRhs(b,dest);
+  }
+
+  EIGEN_STRONG_INLINE void loadLhsUnaligned(const LhsScalar* a, LhsPacket& dest) const
+  {
     dest = ploaddup<LhsPacket>(a);
   }
 
   EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, AccPacket& c, RhsPacket& tmp) const
   {
@@ -484,11 +823,17 @@
     madd_impl(a, b, c, tmp, typename conditional<Vectorizable,true_type,false_type>::type());
   }
 
   EIGEN_STRONG_INLINE void madd_impl(const LhsPacket& a, const RhsPacket& b, AccPacket& c, RhsPacket& tmp, const true_type&) const
   {
+#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
+    EIGEN_UNUSED_VARIABLE(tmp);
+    c.v = pmadd(a,b.v,c.v);
+#else
     tmp = b; tmp.v = pmul(a,tmp.v); c = padd(c,tmp);
+#endif
+    
   }
 
   EIGEN_STRONG_INLINE void madd_impl(const LhsScalar& a, const RhsScalar& b, ResScalar& c, RhsScalar& /*tmp*/, const false_type&) const
   {
     c += a * b;
@@ -508,593 +853,819 @@
  * Mixing type logic: C += A * B
  *  |  A  |  B  | comments
  *  |real |cplx | no vectorization yet, would require to pack A with duplication
  *  |cplx |real | easy vectorization
  */
-template<typename LhsScalar, typename RhsScalar, typename Index, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs>
+template<typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs>
 struct gebp_kernel
 {
   typedef gebp_traits<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> Traits;
   typedef typename Traits::ResScalar ResScalar;
   typedef typename Traits::LhsPacket LhsPacket;
   typedef typename Traits::RhsPacket RhsPacket;
   typedef typename Traits::ResPacket ResPacket;
   typedef typename Traits::AccPacket AccPacket;
 
+  typedef gebp_traits<RhsScalar,LhsScalar,ConjugateRhs,ConjugateLhs> SwappedTraits;
+  typedef typename SwappedTraits::ResScalar SResScalar;
+  typedef typename SwappedTraits::LhsPacket SLhsPacket;
+  typedef typename SwappedTraits::RhsPacket SRhsPacket;
+  typedef typename SwappedTraits::ResPacket SResPacket;
+  typedef typename SwappedTraits::AccPacket SAccPacket;
+
+  typedef typename DataMapper::LinearMapper LinearMapper;
+
   enum {
     Vectorizable  = Traits::Vectorizable,
     LhsProgress   = Traits::LhsProgress,
     RhsProgress   = Traits::RhsProgress,
     ResPacketSize = Traits::ResPacketSize
   };
 
   EIGEN_DONT_INLINE
-  void operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index rows, Index depth, Index cols, ResScalar alpha,
-                  Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, RhsScalar* unpackedB=0);
+  void operator()(const DataMapper& res, const LhsScalar* blockA, const RhsScalar* blockB,
+                  Index rows, Index depth, Index cols, ResScalar alpha,
+                  Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0);
 };
 
-template<typename LhsScalar, typename RhsScalar, typename Index, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs>
+template<typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs>
 EIGEN_DONT_INLINE
-void gebp_kernel<LhsScalar,RhsScalar,Index,mr,nr,ConjugateLhs,ConjugateRhs>
-  ::operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index rows, Index depth, Index cols, ResScalar alpha,
-               Index strideA, Index strideB, Index offsetA, Index offsetB, RhsScalar* unpackedB)
+void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,ConjugateRhs>
+  ::operator()(const DataMapper& res, const LhsScalar* blockA, const RhsScalar* blockB,
+               Index rows, Index depth, Index cols, ResScalar alpha,
+               Index strideA, Index strideB, Index offsetA, Index offsetB)
   {
     Traits traits;
+    SwappedTraits straits;
     
     if(strideA==-1) strideA = depth;
     if(strideB==-1) strideB = depth;
     conj_helper<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> cj;
-//     conj_helper<LhsPacket,RhsPacket,ConjugateLhs,ConjugateRhs> pcj;
-    Index packet_cols = (cols/nr) * nr;
-    const Index peeled_mc = (rows/mr)*mr;
-    // FIXME:
-    const Index peeled_mc2 = peeled_mc + (rows-peeled_mc >= LhsProgress ? LhsProgress : 0);
-    const Index peeled_kc = (depth/4)*4;
-
-    if(unpackedB==0)
-      unpackedB = const_cast<RhsScalar*>(blockB - strideB * nr * RhsProgress);
-
-    // loops on each micro vertical panel of rhs (depth x nr)
-    for(Index j2=0; j2<packet_cols; j2+=nr)
-    {
-      traits.unpackRhs(depth*nr,&blockB[j2*strideB+offsetB*nr],unpackedB); 
-
-      // loops on each largest micro horizontal panel of lhs (mr x depth)
-      // => we select a mr x nr micro block of res which is entirely
-      //    stored into mr/packet_size x nr registers.
-      for(Index i=0; i<peeled_mc; i+=mr)
-      {
-        const LhsScalar* blA = &blockA[i*strideA+offsetA*mr];
-        prefetch(&blA[0]);
-
-        // gets res block as register
-        AccPacket C0, C1, C2, C3, C4, C5, C6, C7;
-                  traits.initAcc(C0);
-                  traits.initAcc(C1);
-        if(nr==4) traits.initAcc(C2);
-        if(nr==4) traits.initAcc(C3);
-                  traits.initAcc(C4);
-                  traits.initAcc(C5);
-        if(nr==4) traits.initAcc(C6);
-        if(nr==4) traits.initAcc(C7);
-
-        ResScalar* r0 = &res[(j2+0)*resStride + i];
-        ResScalar* r1 = r0 + resStride;
-        ResScalar* r2 = r1 + resStride;
-        ResScalar* r3 = r2 + resStride;
-
-        prefetch(r0+16);
-        prefetch(r1+16);
-        prefetch(r2+16);
-        prefetch(r3+16);
-
-        // performs "inner" product
-        // TODO let's check wether the folowing peeled loop could not be
-        //      optimized via optimal prefetching from one loop to the other
-        const RhsScalar* blB = unpackedB;
-        for(Index k=0; k<peeled_kc; k+=4)
-        {
-          if(nr==2)
-          {
-            LhsPacket A0, A1;
-            RhsPacket B_0;
-            RhsPacket T0;
-            
-EIGEN_ASM_COMMENT("mybegin2");
-            traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
-
-            traits.loadLhs(&blA[2*LhsProgress], A0);
-            traits.loadLhs(&blA[3*LhsProgress], A1);
-            traits.loadRhs(&blB[2*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[3*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
-
-            traits.loadLhs(&blA[4*LhsProgress], A0);
-            traits.loadLhs(&blA[5*LhsProgress], A1);
-            traits.loadRhs(&blB[4*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[5*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
-
-            traits.loadLhs(&blA[6*LhsProgress], A0);
-            traits.loadLhs(&blA[7*LhsProgress], A1);
-            traits.loadRhs(&blB[6*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[7*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
-EIGEN_ASM_COMMENT("myend");
-          }
-          else
-          {
-EIGEN_ASM_COMMENT("mybegin4");
-            LhsPacket A0, A1;
-            RhsPacket B_0, B1, B2, B3;
-            RhsPacket T0;
-            
-            traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B1);
-
-            traits.madd(A0,B_0,C0,T0);
-            traits.loadRhs(&blB[2*RhsProgress], B2);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[3*RhsProgress], B3);
-            traits.loadRhs(&blB[4*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,T0);
-            traits.madd(A1,B1,C5,B1);
-            traits.loadRhs(&blB[5*RhsProgress], B1);
-            traits.madd(A0,B2,C2,T0);
-            traits.madd(A1,B2,C6,B2);
-            traits.loadRhs(&blB[6*RhsProgress], B2);
-            traits.madd(A0,B3,C3,T0);
-            traits.loadLhs(&blA[2*LhsProgress], A0);
-            traits.madd(A1,B3,C7,B3);
-            traits.loadLhs(&blA[3*LhsProgress], A1);
-            traits.loadRhs(&blB[7*RhsProgress], B3);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[8*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,T0);
-            traits.madd(A1,B1,C5,B1);
-            traits.loadRhs(&blB[9*RhsProgress], B1);
-            traits.madd(A0,B2,C2,T0);
-            traits.madd(A1,B2,C6,B2);
-            traits.loadRhs(&blB[10*RhsProgress], B2);
-            traits.madd(A0,B3,C3,T0);
-            traits.loadLhs(&blA[4*LhsProgress], A0);
-            traits.madd(A1,B3,C7,B3);
-            traits.loadLhs(&blA[5*LhsProgress], A1);
-            traits.loadRhs(&blB[11*RhsProgress], B3);
-
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[12*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,T0);
-            traits.madd(A1,B1,C5,B1);
-            traits.loadRhs(&blB[13*RhsProgress], B1);
-            traits.madd(A0,B2,C2,T0);
-            traits.madd(A1,B2,C6,B2);
-            traits.loadRhs(&blB[14*RhsProgress], B2);
-            traits.madd(A0,B3,C3,T0);
-            traits.loadLhs(&blA[6*LhsProgress], A0);
-            traits.madd(A1,B3,C7,B3);
-            traits.loadLhs(&blA[7*LhsProgress], A1);
-            traits.loadRhs(&blB[15*RhsProgress], B3);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.madd(A0,B1,C1,T0);
-            traits.madd(A1,B1,C5,B1);
-            traits.madd(A0,B2,C2,T0);
-            traits.madd(A1,B2,C6,B2);
-            traits.madd(A0,B3,C3,T0);
-            traits.madd(A1,B3,C7,B3);
-          }
-
-          blB += 4*nr*RhsProgress;
-          blA += 4*mr;
-        }
-        // process remaining peeled loop
-        for(Index k=peeled_kc; k<depth; k++)
-        {
-          if(nr==2)
-          {
-            LhsPacket A0, A1;
-            RhsPacket B_0;
-            RhsPacket T0;
-
-            traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
-          }
-          else
-          {
-            LhsPacket A0, A1;
-            RhsPacket B_0, B1, B2, B3;
-            RhsPacket T0;
-
-            traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B1);
-
-            traits.madd(A0,B_0,C0,T0);
-            traits.loadRhs(&blB[2*RhsProgress], B2);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[3*RhsProgress], B3);
-            traits.madd(A0,B1,C1,T0);
-            traits.madd(A1,B1,C5,B1);
-            traits.madd(A0,B2,C2,T0);
-            traits.madd(A1,B2,C6,B2);
-            traits.madd(A0,B3,C3,T0);
-            traits.madd(A1,B3,C7,B3);
-          }
-
-          blB += nr*RhsProgress;
-          blA += mr;
-        }
-
-        if(nr==4)
-        {
-          ResPacket R0, R1, R2, R3, R4, R5, R6;
-          ResPacket alphav = pset1<ResPacket>(alpha);
-
-          R0 = ploadu<ResPacket>(r0);
-          R1 = ploadu<ResPacket>(r1);
-          R2 = ploadu<ResPacket>(r2);
-          R3 = ploadu<ResPacket>(r3);
-          R4 = ploadu<ResPacket>(r0 + ResPacketSize);
-          R5 = ploadu<ResPacket>(r1 + ResPacketSize);
-          R6 = ploadu<ResPacket>(r2 + ResPacketSize);
-          traits.acc(C0, alphav, R0);
-          pstoreu(r0, R0);
-          R0 = ploadu<ResPacket>(r3 + ResPacketSize);
-
-          traits.acc(C1, alphav, R1);
-          traits.acc(C2, alphav, R2);
-          traits.acc(C3, alphav, R3);
-          traits.acc(C4, alphav, R4);
-          traits.acc(C5, alphav, R5);
-          traits.acc(C6, alphav, R6);
-          traits.acc(C7, alphav, R0);
-          
-          pstoreu(r1, R1);
-          pstoreu(r2, R2);
-          pstoreu(r3, R3);
-          pstoreu(r0 + ResPacketSize, R4);
-          pstoreu(r1 + ResPacketSize, R5);
-          pstoreu(r2 + ResPacketSize, R6);
-          pstoreu(r3 + ResPacketSize, R0);
-        }
-        else
-        {
-          ResPacket R0, R1, R4;
-          ResPacket alphav = pset1<ResPacket>(alpha);
-
-          R0 = ploadu<ResPacket>(r0);
-          R1 = ploadu<ResPacket>(r1);
-          R4 = ploadu<ResPacket>(r0 + ResPacketSize);
-          traits.acc(C0, alphav, R0);
-          pstoreu(r0, R0);
-          R0 = ploadu<ResPacket>(r1 + ResPacketSize);
-          traits.acc(C1, alphav, R1);
-          traits.acc(C4, alphav, R4);
-          traits.acc(C5, alphav, R0);
-          pstoreu(r1, R1);
-          pstoreu(r0 + ResPacketSize, R4);
-          pstoreu(r1 + ResPacketSize, R0);
-        }
-        
-      }
-      
-      if(rows-peeled_mc>=LhsProgress)
-      {
-        Index i = peeled_mc;
-        const LhsScalar* blA = &blockA[i*strideA+offsetA*LhsProgress];
-        prefetch(&blA[0]);
-
-        // gets res block as register
-        AccPacket C0, C1, C2, C3;
-                  traits.initAcc(C0);
-                  traits.initAcc(C1);
-        if(nr==4) traits.initAcc(C2);
-        if(nr==4) traits.initAcc(C3);
-
-        // performs "inner" product
-        const RhsScalar* blB = unpackedB;
-        for(Index k=0; k<peeled_kc; k+=4)
-        {
-          if(nr==2)
-          {
-            LhsPacket A0;
-            RhsPacket B_0, B1;
-
-            traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[2*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,B1);
-            traits.loadLhs(&blA[1*LhsProgress], A0);
-            traits.loadRhs(&blB[3*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[4*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,B1);
-            traits.loadLhs(&blA[2*LhsProgress], A0);
-            traits.loadRhs(&blB[5*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[6*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,B1);
-            traits.loadLhs(&blA[3*LhsProgress], A0);
-            traits.loadRhs(&blB[7*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.madd(A0,B1,C1,B1);
-          }
-          else
-          {
-            LhsPacket A0;
-            RhsPacket B_0, B1, B2, B3;
-
-            traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B1);
-
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[2*RhsProgress], B2);
-            traits.loadRhs(&blB[3*RhsProgress], B3);
-            traits.loadRhs(&blB[4*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,B1);
-            traits.loadRhs(&blB[5*RhsProgress], B1);
-            traits.madd(A0,B2,C2,B2);
-            traits.loadRhs(&blB[6*RhsProgress], B2);
-            traits.madd(A0,B3,C3,B3);
-            traits.loadLhs(&blA[1*LhsProgress], A0);
-            traits.loadRhs(&blB[7*RhsProgress], B3);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[8*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,B1);
-            traits.loadRhs(&blB[9*RhsProgress], B1);
-            traits.madd(A0,B2,C2,B2);
-            traits.loadRhs(&blB[10*RhsProgress], B2);
-            traits.madd(A0,B3,C3,B3);
-            traits.loadLhs(&blA[2*LhsProgress], A0);
-            traits.loadRhs(&blB[11*RhsProgress], B3);
-
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[12*RhsProgress], B_0);
-            traits.madd(A0,B1,C1,B1);
-            traits.loadRhs(&blB[13*RhsProgress], B1);
-            traits.madd(A0,B2,C2,B2);
-            traits.loadRhs(&blB[14*RhsProgress], B2);
-            traits.madd(A0,B3,C3,B3);
-
-            traits.loadLhs(&blA[3*LhsProgress], A0);
-            traits.loadRhs(&blB[15*RhsProgress], B3);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.madd(A0,B1,C1,B1);
-            traits.madd(A0,B2,C2,B2);
-            traits.madd(A0,B3,C3,B3);
-          }
-
-          blB += nr*4*RhsProgress;
-          blA += 4*LhsProgress;
-        }
-        // process remaining peeled loop
-        for(Index k=peeled_kc; k<depth; k++)
-        {
-          if(nr==2)
-          {
-            LhsPacket A0;
-            RhsPacket B_0, B1;
-
-            traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.madd(A0,B1,C1,B1);
-          }
-          else
-          {
-            LhsPacket A0;
-            RhsPacket B_0, B1, B2, B3;
-
-            traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B1);
-            traits.loadRhs(&blB[2*RhsProgress], B2);
-            traits.loadRhs(&blB[3*RhsProgress], B3);
-
-            traits.madd(A0,B_0,C0,B_0);
-            traits.madd(A0,B1,C1,B1);
-            traits.madd(A0,B2,C2,B2);
-            traits.madd(A0,B3,C3,B3);
-          }
-
-          blB += nr*RhsProgress;
-          blA += LhsProgress;
-        }
-
-        ResPacket R0, R1, R2, R3;
-        ResPacket alphav = pset1<ResPacket>(alpha);
-
-        ResScalar* r0 = &res[(j2+0)*resStride + i];
-        ResScalar* r1 = r0 + resStride;
-        ResScalar* r2 = r1 + resStride;
-        ResScalar* r3 = r2 + resStride;
-
-                  R0 = ploadu<ResPacket>(r0);
-                  R1 = ploadu<ResPacket>(r1);
-        if(nr==4) R2 = ploadu<ResPacket>(r2);
-        if(nr==4) R3 = ploadu<ResPacket>(r3);
-
-                  traits.acc(C0, alphav, R0);
-                  traits.acc(C1, alphav, R1);
-        if(nr==4) traits.acc(C2, alphav, R2);
-        if(nr==4) traits.acc(C3, alphav, R3);
-
-                  pstoreu(r0, R0);
-                  pstoreu(r1, R1);
-        if(nr==4) pstoreu(r2, R2);
-        if(nr==4) pstoreu(r3, R3);
-      }
-      for(Index i=peeled_mc2; i<rows; i++)
-      {
-        const LhsScalar* blA = &blockA[i*strideA+offsetA];
-        prefetch(&blA[0]);
-
-        // gets a 1 x nr res block as registers
-        ResScalar C0(0), C1(0), C2(0), C3(0);
-        // TODO directly use blockB ???
-        const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr];
-        for(Index k=0; k<depth; k++)
-        {
-          if(nr==2)
-          {
-            LhsScalar A0;
-            RhsScalar B_0, B1;
-
-            A0 = blA[k];
-            B_0 = blB[0];
-            B1 = blB[1];
-            MADD(cj,A0,B_0,C0,B_0);
-            MADD(cj,A0,B1,C1,B1);
-          }
-          else
-          {
-            LhsScalar A0;
-            RhsScalar B_0, B1, B2, B3;
-
-            A0 = blA[k];
-            B_0 = blB[0];
-            B1 = blB[1];
-            B2 = blB[2];
-            B3 = blB[3];
-
-            MADD(cj,A0,B_0,C0,B_0);
-            MADD(cj,A0,B1,C1,B1);
-            MADD(cj,A0,B2,C2,B2);
-            MADD(cj,A0,B3,C3,B3);
-          }
-
-          blB += nr;
-        }
-                  res[(j2+0)*resStride + i] += alpha*C0;
-                  res[(j2+1)*resStride + i] += alpha*C1;
-        if(nr==4) res[(j2+2)*resStride + i] += alpha*C2;
-        if(nr==4) res[(j2+3)*resStride + i] += alpha*C3;
-      }
-    }
-    // process remaining rhs/res columns one at a time
-    // => do the same but with nr==1
-    for(Index j2=packet_cols; j2<cols; j2++)
-    {
-      // unpack B
-      traits.unpackRhs(depth, &blockB[j2*strideB+offsetB], unpackedB);
-
-      for(Index i=0; i<peeled_mc; i+=mr)
-      {
-        const LhsScalar* blA = &blockA[i*strideA+offsetA*mr];
-        prefetch(&blA[0]);
-
-        // TODO move the res loads to the stores
-
-        // get res block as registers
-        AccPacket C0, C4;
-        traits.initAcc(C0);
-        traits.initAcc(C4);
-
-        const RhsScalar* blB = unpackedB;
-        for(Index k=0; k<depth; k++)
-        {
-          LhsPacket A0, A1;
-          RhsPacket B_0;
-          RhsPacket T0;
-
-          traits.loadLhs(&blA[0*LhsProgress], A0);
-          traits.loadLhs(&blA[1*LhsProgress], A1);
-          traits.loadRhs(&blB[0*RhsProgress], B_0);
-          traits.madd(A0,B_0,C0,T0);
-          traits.madd(A1,B_0,C4,B_0);
-
-          blB += RhsProgress;
-          blA += 2*LhsProgress;
-        }
-        ResPacket R0, R4;
-        ResPacket alphav = pset1<ResPacket>(alpha);
-
-        ResScalar* r0 = &res[(j2+0)*resStride + i];
-
-        R0 = ploadu<ResPacket>(r0);
-        R4 = ploadu<ResPacket>(r0+ResPacketSize);
-
-        traits.acc(C0, alphav, R0);
-        traits.acc(C4, alphav, R4);
-
-        pstoreu(r0,               R0);
-        pstoreu(r0+ResPacketSize, R4);
-      }
-      if(rows-peeled_mc>=LhsProgress)
-      {
-        Index i = peeled_mc;
-        const LhsScalar* blA = &blockA[i*strideA+offsetA*LhsProgress];
-        prefetch(&blA[0]);
-
-        AccPacket C0;
-        traits.initAcc(C0);
-
-        const RhsScalar* blB = unpackedB;
-        for(Index k=0; k<depth; k++)
-        {
-          LhsPacket A0;
-          RhsPacket B_0;
-          traits.loadLhs(blA, A0);
-          traits.loadRhs(blB, B_0);
-          traits.madd(A0, B_0, C0, B_0);
-          blB += RhsProgress;
-          blA += LhsProgress;
-        }
-
-        ResPacket alphav = pset1<ResPacket>(alpha);
-        ResPacket R0 = ploadu<ResPacket>(&res[(j2+0)*resStride + i]);
-        traits.acc(C0, alphav, R0);
-        pstoreu(&res[(j2+0)*resStride + i], R0);
-      }
-      for(Index i=peeled_mc2; i<rows; i++)
-      {
-        const LhsScalar* blA = &blockA[i*strideA+offsetA];
-        prefetch(&blA[0]);
-
-        // gets a 1 x 1 res block as registers
-        ResScalar C0(0);
-        // FIXME directly use blockB ??
-        const RhsScalar* blB = &blockB[j2*strideB+offsetB];
-        for(Index k=0; k<depth; k++)
-        {
-          LhsScalar A0 = blA[k];
-          RhsScalar B_0 = blB[k];
-          MADD(cj, A0, B_0, C0, B_0);
-        }
-        res[(j2+0)*resStride + i] += alpha*C0;
+    Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
+    const Index peeled_mc3 = mr>=3*Traits::LhsProgress ? (rows/(3*LhsProgress))*(3*LhsProgress) : 0;
+    const Index peeled_mc2 = mr>=2*Traits::LhsProgress ? peeled_mc3+((rows-peeled_mc3)/(2*LhsProgress))*(2*LhsProgress) : 0;
+    const Index peeled_mc1 = mr>=1*Traits::LhsProgress ? (rows/(1*LhsProgress))*(1*LhsProgress) : 0;
+    enum { pk = 8 }; // NOTE Such a large peeling factor is important for large matrices (~ +5% when >1000 on Haswell)
+    const Index peeled_kc  = depth & ~(pk-1);
+    const Index prefetch_res_offset = 32/sizeof(ResScalar);    
+//     const Index depth2     = depth & ~1;
+
+    //---------- Process 3 * LhsProgress rows at once ----------
+    // This corresponds to 3*LhsProgress x nr register blocks.
+    // Usually, make sense only with FMA
+    if(mr>=3*Traits::LhsProgress)
+    {
+      // Here, the general idea is to loop on each largest micro horizontal panel of the lhs (3*Traits::LhsProgress x depth)
+      // and on each largest micro vertical panel of the rhs (depth * nr).
+      // Blocking sizes, i.e., 'depth' has been computed so that the micro horizontal panel of the lhs fit in L1.
+      // However, if depth is too small, we can extend the number of rows of these horizontal panels.
+      // This actual number of rows is computed as follow:
+      const Index l1 = defaultL1CacheSize; // in Bytes, TODO, l1 should be passed to this function.
+      // The max(1, ...) here is needed because we may be using blocking params larger than what our known l1 cache size
+      // suggests we should be using: either because our known l1 cache size is inaccurate (e.g. on Android, we can only guess),
+      // or because we are testing specific blocking sizes.
+      const Index actual_panel_rows = (3*LhsProgress) * std::max<Index>(1,( (l1 - sizeof(ResScalar)*mr*nr - depth*nr*sizeof(RhsScalar)) / (depth * sizeof(LhsScalar) * 3*LhsProgress) ));
+      for(Index i1=0; i1<peeled_mc3; i1+=actual_panel_rows)
+      {
+        const Index actual_panel_end = (std::min)(i1+actual_panel_rows, peeled_mc3);
+        for(Index j2=0; j2<packet_cols4; j2+=nr)
+        {
+          for(Index i=i1; i<actual_panel_end; i+=3*LhsProgress)
+          {
+          
+          // We selected a 3*Traits::LhsProgress x nr micro block of res which is entirely
+          // stored into 3 x nr registers.
+          
+          const LhsScalar* blA = &blockA[i*strideA+offsetA*(3*LhsProgress)];
+          prefetch(&blA[0]);
+
+          // gets res block as register
+          AccPacket C0, C1, C2,  C3,
+                    C4, C5, C6,  C7,
+                    C8, C9, C10, C11;
+          traits.initAcc(C0);  traits.initAcc(C1);  traits.initAcc(C2);  traits.initAcc(C3);
+          traits.initAcc(C4);  traits.initAcc(C5);  traits.initAcc(C6);  traits.initAcc(C7);
+          traits.initAcc(C8);  traits.initAcc(C9);  traits.initAcc(C10); traits.initAcc(C11);
+
+          LinearMapper r0 = res.getLinearMapper(i, j2 + 0);
+          LinearMapper r1 = res.getLinearMapper(i, j2 + 1);
+          LinearMapper r2 = res.getLinearMapper(i, j2 + 2);
+          LinearMapper r3 = res.getLinearMapper(i, j2 + 3);
+
+          r0.prefetch(0);
+          r1.prefetch(0);
+          r2.prefetch(0);
+          r3.prefetch(0);
+
+          // performs "inner" products
+          const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr];
+          prefetch(&blB[0]);
+          LhsPacket A0, A1;
+
+          for(Index k=0; k<peeled_kc; k+=pk)
+          {
+            EIGEN_ASM_COMMENT("begin gebp micro kernel 3pX4");
+            RhsPacket B_0, T0;
+            LhsPacket A2;
+
+#define EIGEN_GEBP_ONESTEP(K) \
+            do { \
+              EIGEN_ASM_COMMENT("begin step of gebp micro kernel 3pX4"); \
+              EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \
+              internal::prefetch(blA+(3*K+16)*LhsProgress); \
+              if (EIGEN_ARCH_ARM) { internal::prefetch(blB+(4*K+16)*RhsProgress); } /* Bug 953 */ \
+              traits.loadLhs(&blA[(0+3*K)*LhsProgress], A0);  \
+              traits.loadLhs(&blA[(1+3*K)*LhsProgress], A1);  \
+              traits.loadLhs(&blA[(2+3*K)*LhsProgress], A2);  \
+              traits.loadRhs(blB + (0+4*K)*Traits::RhsProgress, B_0); \
+              traits.madd(A0, B_0, C0, T0); \
+              traits.madd(A1, B_0, C4, T0); \
+              traits.madd(A2, B_0, C8, B_0); \
+              traits.loadRhs(blB + (1+4*K)*Traits::RhsProgress, B_0); \
+              traits.madd(A0, B_0, C1, T0); \
+              traits.madd(A1, B_0, C5, T0); \
+              traits.madd(A2, B_0, C9, B_0); \
+              traits.loadRhs(blB + (2+4*K)*Traits::RhsProgress, B_0); \
+              traits.madd(A0, B_0, C2,  T0); \
+              traits.madd(A1, B_0, C6,  T0); \
+              traits.madd(A2, B_0, C10, B_0); \
+              traits.loadRhs(blB + (3+4*K)*Traits::RhsProgress, B_0); \
+              traits.madd(A0, B_0, C3 , T0); \
+              traits.madd(A1, B_0, C7,  T0); \
+              traits.madd(A2, B_0, C11, B_0); \
+              EIGEN_ASM_COMMENT("end step of gebp micro kernel 3pX4"); \
+            } while(false)
+
+            internal::prefetch(blB);
+            EIGEN_GEBP_ONESTEP(0);
+            EIGEN_GEBP_ONESTEP(1);
+            EIGEN_GEBP_ONESTEP(2);
+            EIGEN_GEBP_ONESTEP(3);
+            EIGEN_GEBP_ONESTEP(4);
+            EIGEN_GEBP_ONESTEP(5);
+            EIGEN_GEBP_ONESTEP(6);
+            EIGEN_GEBP_ONESTEP(7);
+
+            blB += pk*4*RhsProgress;
+            blA += pk*3*Traits::LhsProgress;
+
+            EIGEN_ASM_COMMENT("end gebp micro kernel 3pX4");
+          }
+          // process remaining peeled loop
+          for(Index k=peeled_kc; k<depth; k++)
+          {
+            RhsPacket B_0, T0;
+            LhsPacket A2;
+            EIGEN_GEBP_ONESTEP(0);
+            blB += 4*RhsProgress;
+            blA += 3*Traits::LhsProgress;
+          }
+
+#undef EIGEN_GEBP_ONESTEP
+
+          ResPacket R0, R1, R2;
+          ResPacket alphav = pset1<ResPacket>(alpha);
+
+          R0 = r0.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r0.loadPacket(1 * Traits::ResPacketSize);
+          R2 = r0.loadPacket(2 * Traits::ResPacketSize);
+          traits.acc(C0, alphav, R0);
+          traits.acc(C4, alphav, R1);
+          traits.acc(C8, alphav, R2);
+          r0.storePacket(0 * Traits::ResPacketSize, R0);
+          r0.storePacket(1 * Traits::ResPacketSize, R1);
+          r0.storePacket(2 * Traits::ResPacketSize, R2);
+
+          R0 = r1.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r1.loadPacket(1 * Traits::ResPacketSize);
+          R2 = r1.loadPacket(2 * Traits::ResPacketSize);
+          traits.acc(C1, alphav, R0);
+          traits.acc(C5, alphav, R1);
+          traits.acc(C9, alphav, R2);
+          r1.storePacket(0 * Traits::ResPacketSize, R0);
+          r1.storePacket(1 * Traits::ResPacketSize, R1);
+          r1.storePacket(2 * Traits::ResPacketSize, R2);
+
+          R0 = r2.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r2.loadPacket(1 * Traits::ResPacketSize);
+          R2 = r2.loadPacket(2 * Traits::ResPacketSize);
+          traits.acc(C2, alphav, R0);
+          traits.acc(C6, alphav, R1);
+          traits.acc(C10, alphav, R2);
+          r2.storePacket(0 * Traits::ResPacketSize, R0);
+          r2.storePacket(1 * Traits::ResPacketSize, R1);
+          r2.storePacket(2 * Traits::ResPacketSize, R2);
+
+          R0 = r3.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r3.loadPacket(1 * Traits::ResPacketSize);
+          R2 = r3.loadPacket(2 * Traits::ResPacketSize);
+          traits.acc(C3, alphav, R0);
+          traits.acc(C7, alphav, R1);
+          traits.acc(C11, alphav, R2);
+          r3.storePacket(0 * Traits::ResPacketSize, R0);
+          r3.storePacket(1 * Traits::ResPacketSize, R1);
+          r3.storePacket(2 * Traits::ResPacketSize, R2);          
+          }
+        }
+
+        // Deal with remaining columns of the rhs
+        for(Index j2=packet_cols4; j2<cols; j2++)
+        {
+          for(Index i=i1; i<actual_panel_end; i+=3*LhsProgress)
+          {
+          // One column at a time
+          const LhsScalar* blA = &blockA[i*strideA+offsetA*(3*Traits::LhsProgress)];
+          prefetch(&blA[0]);
+
+          // gets res block as register
+          AccPacket C0, C4, C8;
+          traits.initAcc(C0);
+          traits.initAcc(C4);
+          traits.initAcc(C8);
+
+          LinearMapper r0 = res.getLinearMapper(i, j2);
+          r0.prefetch(0);
+
+          // performs "inner" products
+          const RhsScalar* blB = &blockB[j2*strideB+offsetB];
+          LhsPacket A0, A1, A2;
+          
+          for(Index k=0; k<peeled_kc; k+=pk)
+          {
+            EIGEN_ASM_COMMENT("begin gebp micro kernel 3pX1");
+            RhsPacket B_0;
+#define EIGEN_GEBGP_ONESTEP(K) \
+            do { \
+              EIGEN_ASM_COMMENT("begin step of gebp micro kernel 3pX1"); \
+              EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \
+              traits.loadLhs(&blA[(0+3*K)*LhsProgress], A0);  \
+              traits.loadLhs(&blA[(1+3*K)*LhsProgress], A1);  \
+              traits.loadLhs(&blA[(2+3*K)*LhsProgress], A2);  \
+              traits.loadRhs(&blB[(0+K)*RhsProgress], B_0);   \
+              traits.madd(A0, B_0, C0, B_0); \
+              traits.madd(A1, B_0, C4, B_0); \
+              traits.madd(A2, B_0, C8, B_0); \
+              EIGEN_ASM_COMMENT("end step of gebp micro kernel 3pX1"); \
+            } while(false)
+        
+            EIGEN_GEBGP_ONESTEP(0);
+            EIGEN_GEBGP_ONESTEP(1);
+            EIGEN_GEBGP_ONESTEP(2);
+            EIGEN_GEBGP_ONESTEP(3);
+            EIGEN_GEBGP_ONESTEP(4);
+            EIGEN_GEBGP_ONESTEP(5);
+            EIGEN_GEBGP_ONESTEP(6);
+            EIGEN_GEBGP_ONESTEP(7);
+
+            blB += pk*RhsProgress;
+            blA += pk*3*Traits::LhsProgress;
+
+            EIGEN_ASM_COMMENT("end gebp micro kernel 3pX1");
+          }
+
+          // process remaining peeled loop
+          for(Index k=peeled_kc; k<depth; k++)
+          {
+            RhsPacket B_0;
+            EIGEN_GEBGP_ONESTEP(0);
+            blB += RhsProgress;
+            blA += 3*Traits::LhsProgress;
+          }
+#undef EIGEN_GEBGP_ONESTEP
+          ResPacket R0, R1, R2;
+          ResPacket alphav = pset1<ResPacket>(alpha);
+
+          R0 = r0.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r0.loadPacket(1 * Traits::ResPacketSize);
+          R2 = r0.loadPacket(2 * Traits::ResPacketSize);
+          traits.acc(C0, alphav, R0);
+          traits.acc(C4, alphav, R1);
+          traits.acc(C8, alphav, R2);
+          r0.storePacket(0 * Traits::ResPacketSize, R0);
+          r0.storePacket(1 * Traits::ResPacketSize, R1);
+          r0.storePacket(2 * Traits::ResPacketSize, R2);          
+          }
+        }
+      }
+    }
+
+    //---------- Process 2 * LhsProgress rows at once ----------
+    if(mr>=2*Traits::LhsProgress)
+    {
+      const Index l1 = defaultL1CacheSize; // in Bytes, TODO, l1 should be passed to this function.
+      // The max(1, ...) here is needed because we may be using blocking params larger than what our known l1 cache size
+      // suggests we should be using: either because our known l1 cache size is inaccurate (e.g. on Android, we can only guess),
+      // or because we are testing specific blocking sizes.
+      Index actual_panel_rows = (2*LhsProgress) * std::max<Index>(1,( (l1 - sizeof(ResScalar)*mr*nr - depth*nr*sizeof(RhsScalar)) / (depth * sizeof(LhsScalar) * 2*LhsProgress) ));
+
+      for(Index i1=peeled_mc3; i1<peeled_mc2; i1+=actual_panel_rows)
+      {
+        Index actual_panel_end = (std::min)(i1+actual_panel_rows, peeled_mc2);
+        for(Index j2=0; j2<packet_cols4; j2+=nr)
+        {
+          for(Index i=i1; i<actual_panel_end; i+=2*LhsProgress)
+          {
+          
+          // We selected a 2*Traits::LhsProgress x nr micro block of res which is entirely
+          // stored into 2 x nr registers.
+          
+          const LhsScalar* blA = &blockA[i*strideA+offsetA*(2*Traits::LhsProgress)];
+          prefetch(&blA[0]);
+
+          // gets res block as register
+          AccPacket C0, C1, C2, C3,
+                    C4, C5, C6, C7;
+          traits.initAcc(C0); traits.initAcc(C1); traits.initAcc(C2); traits.initAcc(C3);
+          traits.initAcc(C4); traits.initAcc(C5); traits.initAcc(C6); traits.initAcc(C7);
+
+          LinearMapper r0 = res.getLinearMapper(i, j2 + 0);
+          LinearMapper r1 = res.getLinearMapper(i, j2 + 1);
+          LinearMapper r2 = res.getLinearMapper(i, j2 + 2);
+          LinearMapper r3 = res.getLinearMapper(i, j2 + 3);
+
+          r0.prefetch(prefetch_res_offset);
+          r1.prefetch(prefetch_res_offset);
+          r2.prefetch(prefetch_res_offset);
+          r3.prefetch(prefetch_res_offset);
+
+          // performs "inner" products
+          const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr];
+          prefetch(&blB[0]);
+          LhsPacket A0, A1;
+
+          for(Index k=0; k<peeled_kc; k+=pk)
+          {
+            EIGEN_ASM_COMMENT("begin gebp micro kernel 2pX4");
+            RhsPacket B_0, B1, B2, B3, T0;
+
+   #define EIGEN_GEBGP_ONESTEP(K) \
+            do {                                                                \
+              EIGEN_ASM_COMMENT("begin step of gebp micro kernel 2pX4");        \
+              EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \
+              traits.loadLhs(&blA[(0+2*K)*LhsProgress], A0);                    \
+              traits.loadLhs(&blA[(1+2*K)*LhsProgress], A1);                    \
+              traits.broadcastRhs(&blB[(0+4*K)*RhsProgress], B_0, B1, B2, B3);  \
+              traits.madd(A0, B_0, C0, T0);                                     \
+              traits.madd(A1, B_0, C4, B_0);                                    \
+              traits.madd(A0, B1,  C1, T0);                                     \
+              traits.madd(A1, B1,  C5, B1);                                     \
+              traits.madd(A0, B2,  C2, T0);                                     \
+              traits.madd(A1, B2,  C6, B2);                                     \
+              traits.madd(A0, B3,  C3, T0);                                     \
+              traits.madd(A1, B3,  C7, B3);                                     \
+              EIGEN_ASM_COMMENT("end step of gebp micro kernel 2pX4");          \
+            } while(false)
+            
+            internal::prefetch(blB+(48+0));
+            EIGEN_GEBGP_ONESTEP(0);
+            EIGEN_GEBGP_ONESTEP(1);
+            EIGEN_GEBGP_ONESTEP(2);
+            EIGEN_GEBGP_ONESTEP(3);
+            internal::prefetch(blB+(48+16));
+            EIGEN_GEBGP_ONESTEP(4);
+            EIGEN_GEBGP_ONESTEP(5);
+            EIGEN_GEBGP_ONESTEP(6);
+            EIGEN_GEBGP_ONESTEP(7);
+
+            blB += pk*4*RhsProgress;
+            blA += pk*(2*Traits::LhsProgress);
+
+            EIGEN_ASM_COMMENT("end gebp micro kernel 2pX4");
+          }
+          // process remaining peeled loop
+          for(Index k=peeled_kc; k<depth; k++)
+          {
+            RhsPacket B_0, B1, B2, B3, T0;
+            EIGEN_GEBGP_ONESTEP(0);
+            blB += 4*RhsProgress;
+            blA += 2*Traits::LhsProgress;
+          }
+#undef EIGEN_GEBGP_ONESTEP
+
+          ResPacket R0, R1, R2, R3;
+          ResPacket alphav = pset1<ResPacket>(alpha);
+
+          R0 = r0.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r0.loadPacket(1 * Traits::ResPacketSize);
+          R2 = r1.loadPacket(0 * Traits::ResPacketSize);
+          R3 = r1.loadPacket(1 * Traits::ResPacketSize);
+          traits.acc(C0, alphav, R0);
+          traits.acc(C4, alphav, R1);
+          traits.acc(C1, alphav, R2);
+          traits.acc(C5, alphav, R3);
+          r0.storePacket(0 * Traits::ResPacketSize, R0);
+          r0.storePacket(1 * Traits::ResPacketSize, R1);
+          r1.storePacket(0 * Traits::ResPacketSize, R2);
+          r1.storePacket(1 * Traits::ResPacketSize, R3);
+
+          R0 = r2.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r2.loadPacket(1 * Traits::ResPacketSize);
+          R2 = r3.loadPacket(0 * Traits::ResPacketSize);
+          R3 = r3.loadPacket(1 * Traits::ResPacketSize);
+          traits.acc(C2,  alphav, R0);
+          traits.acc(C6,  alphav, R1);
+          traits.acc(C3,  alphav, R2);
+          traits.acc(C7,  alphav, R3);
+          r2.storePacket(0 * Traits::ResPacketSize, R0);
+          r2.storePacket(1 * Traits::ResPacketSize, R1);
+          r3.storePacket(0 * Traits::ResPacketSize, R2);
+          r3.storePacket(1 * Traits::ResPacketSize, R3);
+          }
+        }
+      
+        // Deal with remaining columns of the rhs
+        for(Index j2=packet_cols4; j2<cols; j2++)
+        {
+          for(Index i=i1; i<actual_panel_end; i+=2*LhsProgress)
+          {
+          // One column at a time
+          const LhsScalar* blA = &blockA[i*strideA+offsetA*(2*Traits::LhsProgress)];
+          prefetch(&blA[0]);
+
+          // gets res block as register
+          AccPacket C0, C4;
+          traits.initAcc(C0);
+          traits.initAcc(C4);
+
+          LinearMapper r0 = res.getLinearMapper(i, j2);
+          r0.prefetch(prefetch_res_offset);
+
+          // performs "inner" products
+          const RhsScalar* blB = &blockB[j2*strideB+offsetB];
+          LhsPacket A0, A1;
+
+          for(Index k=0; k<peeled_kc; k+=pk)
+          {
+            EIGEN_ASM_COMMENT("begin gebp micro kernel 2pX1");
+            RhsPacket B_0, B1;
+        
+#define EIGEN_GEBGP_ONESTEP(K) \
+            do {                                                                  \
+              EIGEN_ASM_COMMENT("begin step of gebp micro kernel 2pX1");          \
+              EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \
+              traits.loadLhs(&blA[(0+2*K)*LhsProgress], A0);                      \
+              traits.loadLhs(&blA[(1+2*K)*LhsProgress], A1);                      \
+              traits.loadRhs(&blB[(0+K)*RhsProgress], B_0);                       \
+              traits.madd(A0, B_0, C0, B1);                                       \
+              traits.madd(A1, B_0, C4, B_0);                                      \
+              EIGEN_ASM_COMMENT("end step of gebp micro kernel 2pX1");            \
+            } while(false)
+        
+            EIGEN_GEBGP_ONESTEP(0);
+            EIGEN_GEBGP_ONESTEP(1);
+            EIGEN_GEBGP_ONESTEP(2);
+            EIGEN_GEBGP_ONESTEP(3);
+            EIGEN_GEBGP_ONESTEP(4);
+            EIGEN_GEBGP_ONESTEP(5);
+            EIGEN_GEBGP_ONESTEP(6);
+            EIGEN_GEBGP_ONESTEP(7);
+
+            blB += pk*RhsProgress;
+            blA += pk*2*Traits::LhsProgress;
+
+            EIGEN_ASM_COMMENT("end gebp micro kernel 2pX1");
+          }
+
+          // process remaining peeled loop
+          for(Index k=peeled_kc; k<depth; k++)
+          {
+            RhsPacket B_0, B1;
+            EIGEN_GEBGP_ONESTEP(0);
+            blB += RhsProgress;
+            blA += 2*Traits::LhsProgress;
+          }
+#undef EIGEN_GEBGP_ONESTEP
+          ResPacket R0, R1;
+          ResPacket alphav = pset1<ResPacket>(alpha);
+
+          R0 = r0.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r0.loadPacket(1 * Traits::ResPacketSize);
+          traits.acc(C0, alphav, R0);
+          traits.acc(C4, alphav, R1);
+          r0.storePacket(0 * Traits::ResPacketSize, R0);
+          r0.storePacket(1 * Traits::ResPacketSize, R1);
+          }
+        }
+      }
+    }
+    //---------- Process 1 * LhsProgress rows at once ----------
+    if(mr>=1*Traits::LhsProgress)
+    {
+      // loops on each largest micro horizontal panel of lhs (1*LhsProgress x depth)
+      for(Index i=peeled_mc2; i<peeled_mc1; i+=1*LhsProgress)
+      {
+        // loops on each largest micro vertical panel of rhs (depth * nr)
+        for(Index j2=0; j2<packet_cols4; j2+=nr)
+        {
+          // We select a 1*Traits::LhsProgress x nr micro block of res which is entirely
+          // stored into 1 x nr registers.
+          
+          const LhsScalar* blA = &blockA[i*strideA+offsetA*(1*Traits::LhsProgress)];
+          prefetch(&blA[0]);
+
+          // gets res block as register
+          AccPacket C0, C1, C2, C3;
+          traits.initAcc(C0);
+          traits.initAcc(C1);
+          traits.initAcc(C2);
+          traits.initAcc(C3);
+
+          LinearMapper r0 = res.getLinearMapper(i, j2 + 0);
+          LinearMapper r1 = res.getLinearMapper(i, j2 + 1);
+          LinearMapper r2 = res.getLinearMapper(i, j2 + 2);
+          LinearMapper r3 = res.getLinearMapper(i, j2 + 3);
+
+          r0.prefetch(prefetch_res_offset);
+          r1.prefetch(prefetch_res_offset);
+          r2.prefetch(prefetch_res_offset);
+          r3.prefetch(prefetch_res_offset);
+
+          // performs "inner" products
+          const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr];
+          prefetch(&blB[0]);
+          LhsPacket A0;
+
+          for(Index k=0; k<peeled_kc; k+=pk)
+          {
+            EIGEN_ASM_COMMENT("begin gebp micro kernel 1pX4");
+            RhsPacket B_0, B1, B2, B3;
+               
+#define EIGEN_GEBGP_ONESTEP(K) \
+            do {                                                                \
+              EIGEN_ASM_COMMENT("begin step of gebp micro kernel 1pX4");        \
+              EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \
+              traits.loadLhs(&blA[(0+1*K)*LhsProgress], A0);                    \
+              traits.broadcastRhs(&blB[(0+4*K)*RhsProgress], B_0, B1, B2, B3);  \
+              traits.madd(A0, B_0, C0, B_0);                                    \
+              traits.madd(A0, B1,  C1, B1);                                     \
+              traits.madd(A0, B2,  C2, B2);                                     \
+              traits.madd(A0, B3,  C3, B3);                                     \
+              EIGEN_ASM_COMMENT("end step of gebp micro kernel 1pX4");          \
+            } while(false)
+            
+            internal::prefetch(blB+(48+0));
+            EIGEN_GEBGP_ONESTEP(0);
+            EIGEN_GEBGP_ONESTEP(1);
+            EIGEN_GEBGP_ONESTEP(2);
+            EIGEN_GEBGP_ONESTEP(3);
+            internal::prefetch(blB+(48+16));
+            EIGEN_GEBGP_ONESTEP(4);
+            EIGEN_GEBGP_ONESTEP(5);
+            EIGEN_GEBGP_ONESTEP(6);
+            EIGEN_GEBGP_ONESTEP(7);
+
+            blB += pk*4*RhsProgress;
+            blA += pk*1*LhsProgress;
+
+            EIGEN_ASM_COMMENT("end gebp micro kernel 1pX4");
+          }
+          // process remaining peeled loop
+          for(Index k=peeled_kc; k<depth; k++)
+          {
+            RhsPacket B_0, B1, B2, B3;
+            EIGEN_GEBGP_ONESTEP(0);
+            blB += 4*RhsProgress;
+            blA += 1*LhsProgress;
+          }
+#undef EIGEN_GEBGP_ONESTEP
+
+          ResPacket R0, R1;
+          ResPacket alphav = pset1<ResPacket>(alpha);
+
+          R0 = r0.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r1.loadPacket(0 * Traits::ResPacketSize);
+          traits.acc(C0, alphav, R0);
+          traits.acc(C1,  alphav, R1);
+          r0.storePacket(0 * Traits::ResPacketSize, R0);
+          r1.storePacket(0 * Traits::ResPacketSize, R1);
+
+          R0 = r2.loadPacket(0 * Traits::ResPacketSize);
+          R1 = r3.loadPacket(0 * Traits::ResPacketSize);
+          traits.acc(C2,  alphav, R0);
+          traits.acc(C3,  alphav, R1);
+          r2.storePacket(0 * Traits::ResPacketSize, R0);
+          r3.storePacket(0 * Traits::ResPacketSize, R1);
+        }
+
+        // Deal with remaining columns of the rhs
+        for(Index j2=packet_cols4; j2<cols; j2++)
+        {
+          // One column at a time
+          const LhsScalar* blA = &blockA[i*strideA+offsetA*(1*Traits::LhsProgress)];
+          prefetch(&blA[0]);
+
+          // gets res block as register
+          AccPacket C0;
+          traits.initAcc(C0);
+
+          LinearMapper r0 = res.getLinearMapper(i, j2);
+
+          // performs "inner" products
+          const RhsScalar* blB = &blockB[j2*strideB+offsetB];
+          LhsPacket A0;
+
+          for(Index k=0; k<peeled_kc; k+=pk)
+          {
+            EIGEN_ASM_COMMENT("begin gebp micro kernel 1pX1");
+            RhsPacket B_0;
+        
+#define EIGEN_GEBGP_ONESTEP(K) \
+            do {                                                                \
+              EIGEN_ASM_COMMENT("begin step of gebp micro kernel 1pX1");        \
+              EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \
+              traits.loadLhs(&blA[(0+1*K)*LhsProgress], A0);                    \
+              traits.loadRhs(&blB[(0+K)*RhsProgress], B_0);                     \
+              traits.madd(A0, B_0, C0, B_0);                                    \
+              EIGEN_ASM_COMMENT("end step of gebp micro kernel 1pX1");          \
+            } while(false);
+
+            EIGEN_GEBGP_ONESTEP(0);
+            EIGEN_GEBGP_ONESTEP(1);
+            EIGEN_GEBGP_ONESTEP(2);
+            EIGEN_GEBGP_ONESTEP(3);
+            EIGEN_GEBGP_ONESTEP(4);
+            EIGEN_GEBGP_ONESTEP(5);
+            EIGEN_GEBGP_ONESTEP(6);
+            EIGEN_GEBGP_ONESTEP(7);
+
+            blB += pk*RhsProgress;
+            blA += pk*1*Traits::LhsProgress;
+
+            EIGEN_ASM_COMMENT("end gebp micro kernel 1pX1");
+          }
+
+          // process remaining peeled loop
+          for(Index k=peeled_kc; k<depth; k++)
+          {
+            RhsPacket B_0;
+            EIGEN_GEBGP_ONESTEP(0);
+            blB += RhsProgress;
+            blA += 1*Traits::LhsProgress;
+          }
+#undef EIGEN_GEBGP_ONESTEP
+          ResPacket R0;
+          ResPacket alphav = pset1<ResPacket>(alpha);
+          R0 = r0.loadPacket(0 * Traits::ResPacketSize);
+          traits.acc(C0, alphav, R0);
+          r0.storePacket(0 * Traits::ResPacketSize, R0);
+        }
+      }
+    }
+    //---------- Process remaining rows, 1 at once ----------
+    if(peeled_mc1<rows)
+    {
+      // loop on each panel of the rhs
+      for(Index j2=0; j2<packet_cols4; j2+=nr)
+      {
+        // loop on each row of the lhs (1*LhsProgress x depth)
+        for(Index i=peeled_mc1; i<rows; i+=1)
+        {
+          const LhsScalar* blA = &blockA[i*strideA+offsetA];
+          prefetch(&blA[0]);
+          const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr];
+
+          // The following piece of code wont work for 512 bit registers
+          // Moreover, if LhsProgress==8 it assumes that there is a half packet of the same size
+          // as nr (which is currently 4) for the return type.
+          typedef typename unpacket_traits<SResPacket>::half SResPacketHalf;
+          if ((SwappedTraits::LhsProgress % 4) == 0 &&
+              (SwappedTraits::LhsProgress <= 8) &&
+              (SwappedTraits::LhsProgress!=8 || unpacket_traits<SResPacketHalf>::size==nr))
+          {
+            SAccPacket C0, C1, C2, C3;
+            straits.initAcc(C0);
+            straits.initAcc(C1);
+            straits.initAcc(C2);
+            straits.initAcc(C3);
+
+            const Index spk   = (std::max)(1,SwappedTraits::LhsProgress/4);
+            const Index endk  = (depth/spk)*spk;
+            const Index endk4 = (depth/(spk*4))*(spk*4);
+
+            Index k=0;
+            for(; k<endk4; k+=4*spk)
+            {
+              SLhsPacket A0,A1;
+              SRhsPacket B_0,B_1;
+
+              straits.loadLhsUnaligned(blB+0*SwappedTraits::LhsProgress, A0);
+              straits.loadLhsUnaligned(blB+1*SwappedTraits::LhsProgress, A1);
+
+              straits.loadRhsQuad(blA+0*spk, B_0);
+              straits.loadRhsQuad(blA+1*spk, B_1);
+              straits.madd(A0,B_0,C0,B_0);
+              straits.madd(A1,B_1,C1,B_1);
+
+              straits.loadLhsUnaligned(blB+2*SwappedTraits::LhsProgress, A0);
+              straits.loadLhsUnaligned(blB+3*SwappedTraits::LhsProgress, A1);
+              straits.loadRhsQuad(blA+2*spk, B_0);
+              straits.loadRhsQuad(blA+3*spk, B_1);
+              straits.madd(A0,B_0,C2,B_0);
+              straits.madd(A1,B_1,C3,B_1);
+
+              blB += 4*SwappedTraits::LhsProgress;
+              blA += 4*spk;
+            }
+            C0 = padd(padd(C0,C1),padd(C2,C3));
+            for(; k<endk; k+=spk)
+            {
+              SLhsPacket A0;
+              SRhsPacket B_0;
+
+              straits.loadLhsUnaligned(blB, A0);
+              straits.loadRhsQuad(blA, B_0);
+              straits.madd(A0,B_0,C0,B_0);
+
+              blB += SwappedTraits::LhsProgress;
+              blA += spk;
+            }
+            if(SwappedTraits::LhsProgress==8)
+            {
+              // Special case where we have to first reduce the accumulation register C0
+              typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SResPacket>::half,SResPacket>::type SResPacketHalf;
+              typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SLhsPacket>::half,SLhsPacket>::type SLhsPacketHalf;
+              typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SLhsPacket>::half,SRhsPacket>::type SRhsPacketHalf;
+              typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SAccPacket>::half,SAccPacket>::type SAccPacketHalf;
+
+              SResPacketHalf R = res.template gatherPacket<SResPacketHalf>(i, j2);
+              SResPacketHalf alphav = pset1<SResPacketHalf>(alpha);
+
+              if(depth-endk>0)
+              {
+                // We have to handle the last row of the rhs which corresponds to a half-packet
+                SLhsPacketHalf a0;
+                SRhsPacketHalf b0;
+                straits.loadLhsUnaligned(blB, a0);
+                straits.loadRhs(blA, b0);
+                SAccPacketHalf c0 = predux_downto4(C0);
+                straits.madd(a0,b0,c0,b0);
+                straits.acc(c0, alphav, R);
+              }
+              else
+              {
+                straits.acc(predux_downto4(C0), alphav, R);
+              }
+              res.scatterPacket(i, j2, R);
+            }
+            else
+            {
+              SResPacket R = res.template gatherPacket<SResPacket>(i, j2);
+              SResPacket alphav = pset1<SResPacket>(alpha);
+              straits.acc(C0, alphav, R);
+              res.scatterPacket(i, j2, R);
+            }
+          }
+          else // scalar path
+          {
+            // get a 1 x 4 res block as registers
+            ResScalar C0(0), C1(0), C2(0), C3(0);
+
+            for(Index k=0; k<depth; k++)
+            {
+              LhsScalar A0;
+              RhsScalar B_0, B_1;
+
+              A0 = blA[k];
+
+              B_0 = blB[0];
+              B_1 = blB[1];
+              CJMADD(cj,A0,B_0,C0,  B_0);
+              CJMADD(cj,A0,B_1,C1,  B_1);
+              
+              B_0 = blB[2];
+              B_1 = blB[3];
+              CJMADD(cj,A0,B_0,C2,  B_0);
+              CJMADD(cj,A0,B_1,C3,  B_1);
+              
+              blB += 4;
+            }
+            res(i, j2 + 0) += alpha * C0;
+            res(i, j2 + 1) += alpha * C1;
+            res(i, j2 + 2) += alpha * C2;
+            res(i, j2 + 3) += alpha * C3;
+          }
+        }
+      }
+      // remaining columns
+      for(Index j2=packet_cols4; j2<cols; j2++)
+      {
+        // loop on each row of the lhs (1*LhsProgress x depth)
+        for(Index i=peeled_mc1; i<rows; i+=1)
+        {
+          const LhsScalar* blA = &blockA[i*strideA+offsetA];
+          prefetch(&blA[0]);
+          // gets a 1 x 1 res block as registers
+          ResScalar C0(0);
+          const RhsScalar* blB = &blockB[j2*strideB+offsetB];
+          for(Index k=0; k<depth; k++)
+          {
+            LhsScalar A0 = blA[k];
+            RhsScalar B_0 = blB[k];
+            CJMADD(cj, A0, B_0, C0, B_0);
+          }
+          res(i, j2) += alpha * C0;
+        }
       }
     }
   }
 
 
@@ -1112,85 +1683,197 @@
 //  18 22 26 30 ...
 //  19 23 27 31 ...
 //
 //  32 33 34 35 ...
 //  36 36 38 39 ...
-template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder, bool Conjugate, bool PanelMode>
-struct gemm_pack_lhs
+template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, bool Conjugate, bool PanelMode>
+struct gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, ColMajor, Conjugate, PanelMode>
+{
+  typedef typename DataMapper::LinearMapper LinearMapper;
+  EIGEN_DONT_INLINE void operator()(Scalar* blockA, const DataMapper& lhs, Index depth, Index rows, Index stride=0, Index offset=0);
+};
+
+template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, bool Conjugate, bool PanelMode>
+EIGEN_DONT_INLINE void gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, ColMajor, Conjugate, PanelMode>
+  ::operator()(Scalar* blockA, const DataMapper& lhs, Index depth, Index rows, Index stride, Index offset)
+{
+  typedef typename packet_traits<Scalar>::type Packet;
+  enum { PacketSize = packet_traits<Scalar>::size };
+
+  EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK LHS");
+  EIGEN_UNUSED_VARIABLE(stride);
+  EIGEN_UNUSED_VARIABLE(offset);
+  eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
+  eigen_assert( ((Pack1%PacketSize)==0 && Pack1<=4*PacketSize) || (Pack1<=4) );
+  conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
+  Index count = 0;
+
+  const Index peeled_mc3 = Pack1>=3*PacketSize ? (rows/(3*PacketSize))*(3*PacketSize) : 0;
+  const Index peeled_mc2 = Pack1>=2*PacketSize ? peeled_mc3+((rows-peeled_mc3)/(2*PacketSize))*(2*PacketSize) : 0;
+  const Index peeled_mc1 = Pack1>=1*PacketSize ? (rows/(1*PacketSize))*(1*PacketSize) : 0;
+  const Index peeled_mc0 = Pack2>=1*PacketSize ? peeled_mc1
+                         : Pack2>1             ? (rows/Pack2)*Pack2 : 0;
+
+  Index i=0;
+
+  // Pack 3 packets
+  if(Pack1>=3*PacketSize)
+  {
+    for(; i<peeled_mc3; i+=3*PacketSize)
+    {
+      if(PanelMode) count += (3*PacketSize) * offset;
+
+      for(Index k=0; k<depth; k++)
+      {
+        Packet A, B, C;
+        A = lhs.loadPacket(i+0*PacketSize, k);
+        B = lhs.loadPacket(i+1*PacketSize, k);
+        C = lhs.loadPacket(i+2*PacketSize, k);
+        pstore(blockA+count, cj.pconj(A)); count+=PacketSize;
+        pstore(blockA+count, cj.pconj(B)); count+=PacketSize;
+        pstore(blockA+count, cj.pconj(C)); count+=PacketSize;
+      }
+      if(PanelMode) count += (3*PacketSize) * (stride-offset-depth);
+    }
+  }
+  // Pack 2 packets
+  if(Pack1>=2*PacketSize)
+  {
+    for(; i<peeled_mc2; i+=2*PacketSize)
+    {
+      if(PanelMode) count += (2*PacketSize) * offset;
+
+      for(Index k=0; k<depth; k++)
+      {
+        Packet A, B;
+        A = lhs.loadPacket(i+0*PacketSize, k);
+        B = lhs.loadPacket(i+1*PacketSize, k);
+        pstore(blockA+count, cj.pconj(A)); count+=PacketSize;
+        pstore(blockA+count, cj.pconj(B)); count+=PacketSize;
+      }
+      if(PanelMode) count += (2*PacketSize) * (stride-offset-depth);
+    }
+  }
+  // Pack 1 packets
+  if(Pack1>=1*PacketSize)
+  {
+    for(; i<peeled_mc1; i+=1*PacketSize)
+    {
+      if(PanelMode) count += (1*PacketSize) * offset;
+
+      for(Index k=0; k<depth; k++)
+      {
+        Packet A;
+        A = lhs.loadPacket(i+0*PacketSize, k);
+        pstore(blockA+count, cj.pconj(A));
+        count+=PacketSize;
+      }
+      if(PanelMode) count += (1*PacketSize) * (stride-offset-depth);
+    }
+  }
+  // Pack scalars
+  if(Pack2<PacketSize && Pack2>1)
+  {
+    for(; i<peeled_mc0; i+=Pack2)
+    {
+      if(PanelMode) count += Pack2 * offset;
+
+      for(Index k=0; k<depth; k++)
+        for(Index w=0; w<Pack2; w++)
+          blockA[count++] = cj(lhs(i+w, k));
+
+      if(PanelMode) count += Pack2 * (stride-offset-depth);
+    }
+  }
+  for(; i<rows; i++)
+  {
+    if(PanelMode) count += offset;
+    for(Index k=0; k<depth; k++)
+      blockA[count++] = cj(lhs(i, k));
+    if(PanelMode) count += (stride-offset-depth);
+  }
+}
+
+template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, bool Conjugate, bool PanelMode>
+struct gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, RowMajor, Conjugate, PanelMode>
 {
-  EIGEN_DONT_INLINE void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows, Index stride=0, Index offset=0);
+  typedef typename DataMapper::LinearMapper LinearMapper;
+  EIGEN_DONT_INLINE void operator()(Scalar* blockA, const DataMapper& lhs, Index depth, Index rows, Index stride=0, Index offset=0);
 };
 
-template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder, bool Conjugate, bool PanelMode>
-EIGEN_DONT_INLINE void gemm_pack_lhs<Scalar, Index, Pack1, Pack2, StorageOrder, Conjugate, PanelMode>
-  ::operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows, Index stride, Index offset)
+template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, bool Conjugate, bool PanelMode>
+EIGEN_DONT_INLINE void gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, RowMajor, Conjugate, PanelMode>
+  ::operator()(Scalar* blockA, const DataMapper& lhs, Index depth, Index rows, Index stride, Index offset)
 {
   typedef typename packet_traits<Scalar>::type Packet;
   enum { PacketSize = packet_traits<Scalar>::size };
 
   EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK LHS");
-  EIGEN_UNUSED_VARIABLE(stride)
-  EIGEN_UNUSED_VARIABLE(offset)
-  eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
-  eigen_assert( (StorageOrder==RowMajor) || ((Pack1%PacketSize)==0 && Pack1<=4*PacketSize) );
-  conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
-  const_blas_data_mapper<Scalar, Index, StorageOrder> lhs(_lhs,lhsStride);
-  Index count = 0;
-  Index peeled_mc = (rows/Pack1)*Pack1;
-  for(Index i=0; i<peeled_mc; i+=Pack1)
-  {
-    if(PanelMode) count += Pack1 * offset;
-
-    if(StorageOrder==ColMajor)
-    {
-      for(Index k=0; k<depth; k++)
-      {
-        Packet A, B, C, D;
-        if(Pack1>=1*PacketSize) A = ploadu<Packet>(&lhs(i+0*PacketSize, k));
-        if(Pack1>=2*PacketSize) B = ploadu<Packet>(&lhs(i+1*PacketSize, k));
-        if(Pack1>=3*PacketSize) C = ploadu<Packet>(&lhs(i+2*PacketSize, k));
-        if(Pack1>=4*PacketSize) D = ploadu<Packet>(&lhs(i+3*PacketSize, k));
-        if(Pack1>=1*PacketSize) { pstore(blockA+count, cj.pconj(A)); count+=PacketSize; }
-        if(Pack1>=2*PacketSize) { pstore(blockA+count, cj.pconj(B)); count+=PacketSize; }
-        if(Pack1>=3*PacketSize) { pstore(blockA+count, cj.pconj(C)); count+=PacketSize; }
-        if(Pack1>=4*PacketSize) { pstore(blockA+count, cj.pconj(D)); count+=PacketSize; }
-      }
-    }
-    else
-    {
-      for(Index k=0; k<depth; k++)
-      {
-        // TODO add a vectorized transpose here
-        Index w=0;
-        for(; w<Pack1-3; w+=4)
+  EIGEN_UNUSED_VARIABLE(stride);
+  EIGEN_UNUSED_VARIABLE(offset);
+  eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
+  conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
+  Index count = 0;
+
+//   const Index peeled_mc3 = Pack1>=3*PacketSize ? (rows/(3*PacketSize))*(3*PacketSize) : 0;
+//   const Index peeled_mc2 = Pack1>=2*PacketSize ? peeled_mc3+((rows-peeled_mc3)/(2*PacketSize))*(2*PacketSize) : 0;
+//   const Index peeled_mc1 = Pack1>=1*PacketSize ? (rows/(1*PacketSize))*(1*PacketSize) : 0;
+
+  int pack = Pack1;
+  Index i = 0;
+  while(pack>0)
+  {
+    Index remaining_rows = rows-i;
+    Index peeled_mc = i+(remaining_rows/pack)*pack;
+    for(; i<peeled_mc; i+=pack)
+    {
+      if(PanelMode) count += pack * offset;
+
+      const Index peeled_k = (depth/PacketSize)*PacketSize;
+      Index k=0;
+      if(pack>=PacketSize)
+      {
+        for(; k<peeled_k; k+=PacketSize)
+        {
+          for (Index m = 0; m < pack; m += PacketSize)
+          {
+            PacketBlock<Packet> kernel;
+            for (int p = 0; p < PacketSize; ++p) kernel.packet[p] = lhs.loadPacket(i+p+m, k);
+            ptranspose(kernel);
+            for (int p = 0; p < PacketSize; ++p) pstore(blockA+count+m+(pack)*p, cj.pconj(kernel.packet[p]));
+          }
+          count += PacketSize*pack;
+        }
+      }
+      for(; k<depth; k++)
+      {
+        Index w=0;
+        for(; w<pack-3; w+=4)
         {
           Scalar a(cj(lhs(i+w+0, k))),
-                  b(cj(lhs(i+w+1, k))),
-                  c(cj(lhs(i+w+2, k))),
-                  d(cj(lhs(i+w+3, k)));
+                 b(cj(lhs(i+w+1, k))),
+                 c(cj(lhs(i+w+2, k))),
+                 d(cj(lhs(i+w+3, k)));
           blockA[count++] = a;
           blockA[count++] = b;
           blockA[count++] = c;
           blockA[count++] = d;
         }
-        if(Pack1%4)
-          for(;w<Pack1;++w)
+        if(pack%4)
+          for(;w<pack;++w)
             blockA[count++] = cj(lhs(i+w, k));
       }
-    }
-    if(PanelMode) count += Pack1 * (stride-offset-depth);
-  }
-  if(rows-peeled_mc>=Pack2)
-  {
-    if(PanelMode) count += Pack2*offset;
-    for(Index k=0; k<depth; k++)
-      for(Index w=0; w<Pack2; w++)
-        blockA[count++] = cj(lhs(peeled_mc+w, k));
-    if(PanelMode) count += Pack2 * (stride-offset-depth);
-    peeled_mc += Pack2;
-  }
-  for(Index i=peeled_mc; i<rows; i++)
+
+      if(PanelMode) count += pack * (stride-offset-depth);
+    }
+
+    pack -= PacketSize;
+    if(pack<Pack2 && (pack+PacketSize)!=Pack2)
+      pack = Pack2;
+  }
+
+  for(; i<rows; i++)
   {
     if(PanelMode) count += offset;
     for(Index k=0; k<depth; k++)
       blockA[count++] = cj(lhs(i, k));
     if(PanelMode) count += (stride-offset-depth);
@@ -1202,106 +1885,221 @@
 // The traversal order is as follow: (nr==4):
 //  0  1  2  3   12 13 14 15   24 27
 //  4  5  6  7   16 17 18 19   25 28
 //  8  9 10 11   20 21 22 23   26 29
 //  .  .  .  .    .  .  .  .    .  .
-template<typename Scalar, typename Index, int nr, bool Conjugate, bool PanelMode>
-struct gemm_pack_rhs<Scalar, Index, nr, ColMajor, Conjugate, PanelMode>
+template<typename Scalar, typename Index, typename DataMapper, int nr, bool Conjugate, bool PanelMode>
+struct gemm_pack_rhs<Scalar, Index, DataMapper, nr, ColMajor, Conjugate, PanelMode>
 {
   typedef typename packet_traits<Scalar>::type Packet;
+  typedef typename DataMapper::LinearMapper LinearMapper;
   enum { PacketSize = packet_traits<Scalar>::size };
-  EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride=0, Index offset=0);
+  EIGEN_DONT_INLINE void operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride=0, Index offset=0);
 };
 
-template<typename Scalar, typename Index, int nr, bool Conjugate, bool PanelMode>
-EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, nr, ColMajor, Conjugate, PanelMode>
-  ::operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride, Index offset)
+template<typename Scalar, typename Index, typename DataMapper, int nr, bool Conjugate, bool PanelMode>
+EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, DataMapper, nr, ColMajor, Conjugate, PanelMode>
+  ::operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride, Index offset)
 {
   EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS COLMAJOR");
-  EIGEN_UNUSED_VARIABLE(stride)
-  EIGEN_UNUSED_VARIABLE(offset)
+  EIGEN_UNUSED_VARIABLE(stride);
+  EIGEN_UNUSED_VARIABLE(offset);
   eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
   conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
-  Index packet_cols = (cols/nr) * nr;
+  Index packet_cols8 = nr>=8 ? (cols/8) * 8 : 0;
+  Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
   Index count = 0;
-  for(Index j2=0; j2<packet_cols; j2+=nr)
-  {
-    // skip what we have before
-    if(PanelMode) count += nr * offset;
-    const Scalar* b0 = &rhs[(j2+0)*rhsStride];
-    const Scalar* b1 = &rhs[(j2+1)*rhsStride];
-    const Scalar* b2 = &rhs[(j2+2)*rhsStride];
-    const Scalar* b3 = &rhs[(j2+3)*rhsStride];
-    for(Index k=0; k<depth; k++)
-    {
-                blockB[count+0] = cj(b0[k]);
-                blockB[count+1] = cj(b1[k]);
-      if(nr==4) blockB[count+2] = cj(b2[k]);
-      if(nr==4) blockB[count+3] = cj(b3[k]);
-      count += nr;
-    }
-    // skip what we have after
-    if(PanelMode) count += nr * (stride-offset-depth);
+  const Index peeled_k = (depth/PacketSize)*PacketSize;
+//   if(nr>=8)
+//   {
+//     for(Index j2=0; j2<packet_cols8; j2+=8)
+//     {
+//       // skip what we have before
+//       if(PanelMode) count += 8 * offset;
+//       const Scalar* b0 = &rhs[(j2+0)*rhsStride];
+//       const Scalar* b1 = &rhs[(j2+1)*rhsStride];
+//       const Scalar* b2 = &rhs[(j2+2)*rhsStride];
+//       const Scalar* b3 = &rhs[(j2+3)*rhsStride];
+//       const Scalar* b4 = &rhs[(j2+4)*rhsStride];
+//       const Scalar* b5 = &rhs[(j2+5)*rhsStride];
+//       const Scalar* b6 = &rhs[(j2+6)*rhsStride];
+//       const Scalar* b7 = &rhs[(j2+7)*rhsStride];
+//       Index k=0;
+//       if(PacketSize==8) // TODO enbale vectorized transposition for PacketSize==4
+//       {
+//         for(; k<peeled_k; k+=PacketSize) {
+//           PacketBlock<Packet> kernel;
+//           for (int p = 0; p < PacketSize; ++p) {
+//             kernel.packet[p] = ploadu<Packet>(&rhs[(j2+p)*rhsStride+k]);
+//           }
+//           ptranspose(kernel);
+//           for (int p = 0; p < PacketSize; ++p) {
+//             pstoreu(blockB+count, cj.pconj(kernel.packet[p]));
+//             count+=PacketSize;
+//           }
+//         }
+//       }
+//       for(; k<depth; k++)
+//       {
+//         blockB[count+0] = cj(b0[k]);
+//         blockB[count+1] = cj(b1[k]);
+//         blockB[count+2] = cj(b2[k]);
+//         blockB[count+3] = cj(b3[k]);
+//         blockB[count+4] = cj(b4[k]);
+//         blockB[count+5] = cj(b5[k]);
+//         blockB[count+6] = cj(b6[k]);
+//         blockB[count+7] = cj(b7[k]);
+//         count += 8;
+//       }
+//       // skip what we have after
+//       if(PanelMode) count += 8 * (stride-offset-depth);
+//     }
+//   }
+
+  if(nr>=4)
+  {
+    for(Index j2=packet_cols8; j2<packet_cols4; j2+=4)
+    {
+      // skip what we have before
+      if(PanelMode) count += 4 * offset;
+      const LinearMapper dm0 = rhs.getLinearMapper(0, j2 + 0);
+      const LinearMapper dm1 = rhs.getLinearMapper(0, j2 + 1);
+      const LinearMapper dm2 = rhs.getLinearMapper(0, j2 + 2);
+      const LinearMapper dm3 = rhs.getLinearMapper(0, j2 + 3);
+
+      Index k=0;
+      if((PacketSize%4)==0) // TODO enable vectorized transposition for PacketSize==2 ??
+      {
+        for(; k<peeled_k; k+=PacketSize) {
+          PacketBlock<Packet,(PacketSize%4)==0?4:PacketSize> kernel;
+          kernel.packet[0] = dm0.loadPacket(k);
+          kernel.packet[1%PacketSize] = dm1.loadPacket(k);
+          kernel.packet[2%PacketSize] = dm2.loadPacket(k);
+          kernel.packet[3%PacketSize] = dm3.loadPacket(k);
+          ptranspose(kernel);
+          pstoreu(blockB+count+0*PacketSize, cj.pconj(kernel.packet[0]));
+          pstoreu(blockB+count+1*PacketSize, cj.pconj(kernel.packet[1%PacketSize]));
+          pstoreu(blockB+count+2*PacketSize, cj.pconj(kernel.packet[2%PacketSize]));
+          pstoreu(blockB+count+3*PacketSize, cj.pconj(kernel.packet[3%PacketSize]));
+          count+=4*PacketSize;
+        }
+      }
+      for(; k<depth; k++)
+      {
+        blockB[count+0] = cj(dm0(k));
+        blockB[count+1] = cj(dm1(k));
+        blockB[count+2] = cj(dm2(k));
+        blockB[count+3] = cj(dm3(k));
+        count += 4;
+      }
+      // skip what we have after
+      if(PanelMode) count += 4 * (stride-offset-depth);
+    }
   }
 
   // copy the remaining columns one at a time (nr==1)
-  for(Index j2=packet_cols; j2<cols; ++j2)
+  for(Index j2=packet_cols4; j2<cols; ++j2)
   {
     if(PanelMode) count += offset;
-    const Scalar* b0 = &rhs[(j2+0)*rhsStride];
+    const LinearMapper dm0 = rhs.getLinearMapper(0, j2);
     for(Index k=0; k<depth; k++)
     {
-      blockB[count] = cj(b0[k]);
+      blockB[count] = cj(dm0(k));
       count += 1;
     }
     if(PanelMode) count += (stride-offset-depth);
   }
 }
 
 // this version is optimized for row major matrices
-template<typename Scalar, typename Index, int nr, bool Conjugate, bool PanelMode>
-struct gemm_pack_rhs<Scalar, Index, nr, RowMajor, Conjugate, PanelMode>
+template<typename Scalar, typename Index, typename DataMapper, int nr, bool Conjugate, bool PanelMode>
+struct gemm_pack_rhs<Scalar, Index, DataMapper, nr, RowMajor, Conjugate, PanelMode>
 {
+  typedef typename packet_traits<Scalar>::type Packet;
+  typedef typename DataMapper::LinearMapper LinearMapper;
   enum { PacketSize = packet_traits<Scalar>::size };
-  EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride=0, Index offset=0);
+  EIGEN_DONT_INLINE void operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride=0, Index offset=0);
 };
 
-template<typename Scalar, typename Index, int nr, bool Conjugate, bool PanelMode>
-EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, nr, RowMajor, Conjugate, PanelMode>
-  ::operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride, Index offset)
+template<typename Scalar, typename Index, typename DataMapper, int nr, bool Conjugate, bool PanelMode>
+EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, DataMapper, nr, RowMajor, Conjugate, PanelMode>
+  ::operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride, Index offset)
 {
   EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS ROWMAJOR");
-  EIGEN_UNUSED_VARIABLE(stride)
-  EIGEN_UNUSED_VARIABLE(offset)
+  EIGEN_UNUSED_VARIABLE(stride);
+  EIGEN_UNUSED_VARIABLE(offset);
   eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
   conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
-  Index packet_cols = (cols/nr) * nr;
+  Index packet_cols8 = nr>=8 ? (cols/8) * 8 : 0;
+  Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
   Index count = 0;
-  for(Index j2=0; j2<packet_cols; j2+=nr)
-  {
-    // skip what we have before
-    if(PanelMode) count += nr * offset;
-    for(Index k=0; k<depth; k++)
-    {
-      const Scalar* b0 = &rhs[k*rhsStride + j2];
-                blockB[count+0] = cj(b0[0]);
-                blockB[count+1] = cj(b0[1]);
-      if(nr==4) blockB[count+2] = cj(b0[2]);
-      if(nr==4) blockB[count+3] = cj(b0[3]);
-      count += nr;
-    }
-    // skip what we have after
-    if(PanelMode) count += nr * (stride-offset-depth);
+
+//   if(nr>=8)
+//   {
+//     for(Index j2=0; j2<packet_cols8; j2+=8)
+//     {
+//       // skip what we have before
+//       if(PanelMode) count += 8 * offset;
+//       for(Index k=0; k<depth; k++)
+//       {
+//         if (PacketSize==8) {
+//           Packet A = ploadu<Packet>(&rhs[k*rhsStride + j2]);
+//           pstoreu(blockB+count, cj.pconj(A));
+//         } else if (PacketSize==4) {
+//           Packet A = ploadu<Packet>(&rhs[k*rhsStride + j2]);
+//           Packet B = ploadu<Packet>(&rhs[k*rhsStride + j2 + PacketSize]);
+//           pstoreu(blockB+count, cj.pconj(A));
+//           pstoreu(blockB+count+PacketSize, cj.pconj(B));
+//         } else {
+//           const Scalar* b0 = &rhs[k*rhsStride + j2];
+//           blockB[count+0] = cj(b0[0]);
+//           blockB[count+1] = cj(b0[1]);
+//           blockB[count+2] = cj(b0[2]);
+//           blockB[count+3] = cj(b0[3]);
+//           blockB[count+4] = cj(b0[4]);
+//           blockB[count+5] = cj(b0[5]);
+//           blockB[count+6] = cj(b0[6]);
+//           blockB[count+7] = cj(b0[7]);
+//         }
+//         count += 8;
+//       }
+//       // skip what we have after
+//       if(PanelMode) count += 8 * (stride-offset-depth);
+//     }
+//   }
+  if(nr>=4)
+  {
+    for(Index j2=packet_cols8; j2<packet_cols4; j2+=4)
+    {
+      // skip what we have before
+      if(PanelMode) count += 4 * offset;
+      for(Index k=0; k<depth; k++)
+      {
+        if (PacketSize==4) {
+          Packet A = rhs.loadPacket(k, j2);
+          pstoreu(blockB+count, cj.pconj(A));
+          count += PacketSize;
+        } else {
+          const LinearMapper dm0 = rhs.getLinearMapper(k, j2);
+          blockB[count+0] = cj(dm0(0));
+          blockB[count+1] = cj(dm0(1));
+          blockB[count+2] = cj(dm0(2));
+          blockB[count+3] = cj(dm0(3));
+          count += 4;
+        }
+      }
+      // skip what we have after
+      if(PanelMode) count += 4 * (stride-offset-depth);
+    }
   }
   // copy the remaining columns one at a time (nr==1)
-  for(Index j2=packet_cols; j2<cols; ++j2)
+  for(Index j2=packet_cols4; j2<cols; ++j2)
   {
     if(PanelMode) count += offset;
-    const Scalar* b0 = &rhs[j2];
     for(Index k=0; k<depth; k++)
     {
-      blockB[count] = cj(b0[k*rhsStride]);
+      blockB[count] = cj(rhs(k, j2));
       count += 1;
     }
     if(PanelMode) count += stride-offset-depth;
   }
 }
@@ -1310,32 +2108,42 @@
 
 /** \returns the currently set level 1 cpu cache size (in bytes) used to estimate the ideal blocking size parameters.
   * \sa setCpuCacheSize */
 inline std::ptrdiff_t l1CacheSize()
 {
-  std::ptrdiff_t l1, l2;
-  internal::manage_caching_sizes(GetAction, &l1, &l2);
+  std::ptrdiff_t l1, l2, l3;
+  internal::manage_caching_sizes(GetAction, &l1, &l2, &l3);
   return l1;
 }
 
 /** \returns the currently set level 2 cpu cache size (in bytes) used to estimate the ideal blocking size parameters.
   * \sa setCpuCacheSize */
 inline std::ptrdiff_t l2CacheSize()
 {
-  std::ptrdiff_t l1, l2;
-  internal::manage_caching_sizes(GetAction, &l1, &l2);
+  std::ptrdiff_t l1, l2, l3;
+  internal::manage_caching_sizes(GetAction, &l1, &l2, &l3);
   return l2;
 }
+
+/** \returns the currently set level 3 cpu cache size (in bytes) used to estimate the ideal blocking size paramete\
+rs.                                                                                                                
+* \sa setCpuCacheSize */
+inline std::ptrdiff_t l3CacheSize()
+{
+  std::ptrdiff_t l1, l2, l3;
+  internal::manage_caching_sizes(GetAction, &l1, &l2, &l3);
+  return l3;
+}
 
 /** Set the cpu L1 and L2 cache sizes (in bytes).
   * These values are use to adjust the size of the blocks
   * for the algorithms working per blocks.
   *
   * \sa computeProductBlockingSizes */
-inline void setCpuCacheSizes(std::ptrdiff_t l1, std::ptrdiff_t l2)
+inline void setCpuCacheSizes(std::ptrdiff_t l1, std::ptrdiff_t l2, std::ptrdiff_t l3)
 {
-  internal::manage_caching_sizes(SetAction, &l1, &l2);
+  internal::manage_caching_sizes(SetAction, &l1, &l2, &l3);
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_GENERAL_BLOCK_PANEL_H

Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h
@@ -8,11 +8,11 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERAL_MATRIX_MATRIX_H
 #define EIGEN_GENERAL_MATRIX_MATRIX_H
 
-namespace Eigen { 
+namespace Eigen {
 
 namespace internal {
 
 template<typename _LhsScalar, typename _RhsScalar> class level3_blocking;
 
@@ -21,11 +21,13 @@
   typename Index,
   typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
   typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs>
 struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,RowMajor>
 {
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef gebp_traits<RhsScalar,LhsScalar> Traits;
+
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   static EIGEN_STRONG_INLINE void run(
     Index rows, Index cols, Index depth,
     const LhsScalar* lhs, Index lhsStride,
     const RhsScalar* rhs, Index rhsStride,
     ResScalar* res, Index resStride,
@@ -49,183 +51,188 @@
   typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
   typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs>
 struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor>
 {
 
-typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+typedef gebp_traits<LhsScalar,RhsScalar> Traits;
+
+typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
 static void run(Index rows, Index cols, Index depth,
   const LhsScalar* _lhs, Index lhsStride,
   const RhsScalar* _rhs, Index rhsStride,
-  ResScalar* res, Index resStride,
+  ResScalar* _res, Index resStride,
   ResScalar alpha,
   level3_blocking<LhsScalar,RhsScalar>& blocking,
   GemmParallelInfo<Index>* info = 0)
 {
-  const_blas_data_mapper<LhsScalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
-  const_blas_data_mapper<RhsScalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
-
-  typedef gebp_traits<LhsScalar,RhsScalar> Traits;
+  typedef const_blas_data_mapper<LhsScalar, Index, LhsStorageOrder> LhsMapper;
+  typedef const_blas_data_mapper<RhsScalar, Index, RhsStorageOrder> RhsMapper;
+  typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
+  LhsMapper lhs(_lhs,lhsStride);
+  RhsMapper rhs(_rhs,rhsStride);
+  ResMapper res(_res, resStride);
 
   Index kc = blocking.kc();                   // cache block size along the K direction
   Index mc = (std::min)(rows,blocking.mc());  // cache block size along the M direction
-  //Index nc = blocking.nc(); // cache block size along the N direction
+  Index nc = (std::min)(cols,blocking.nc());  // cache block size along the N direction
 
-  gemm_pack_lhs<LhsScalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
-  gemm_pack_rhs<RhsScalar, Index, Traits::nr, RhsStorageOrder> pack_rhs;
-  gebp_kernel<LhsScalar, RhsScalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
+  gemm_pack_lhs<LhsScalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+  gemm_pack_rhs<RhsScalar, Index, RhsMapper, Traits::nr, RhsStorageOrder> pack_rhs;
+  gebp_kernel<LhsScalar, RhsScalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
 
 #ifdef EIGEN_HAS_OPENMP
   if(info)
   {
     // this is the parallel version!
-    Index tid = omp_get_thread_num();
-    Index threads = omp_get_num_threads();
-    
-    std::size_t sizeA = kc*mc;
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
-    ei_declare_aligned_stack_constructed_variable(LhsScalar, blockA, sizeA, 0);
-    ei_declare_aligned_stack_constructed_variable(RhsScalar, w, sizeW, 0);
-    
-    RhsScalar* blockB = blocking.blockB();
-    eigen_internal_assert(blockB!=0);
+    int tid = omp_get_thread_num();
+    int threads = omp_get_num_threads();
+
+    LhsScalar* blockA = blocking.blockA();
+    eigen_internal_assert(blockA!=0);
+
+    std::size_t sizeB = kc*nc;
+    ei_declare_aligned_stack_constructed_variable(RhsScalar, blockB, sizeB, 0);
 
     // For each horizontal panel of the rhs, and corresponding vertical panel of the lhs...
     for(Index k=0; k<depth; k+=kc)
     {
       const Index actual_kc = (std::min)(k+kc,depth)-k; // => rows of B', and cols of the A'
 
       // In order to reduce the chance that a thread has to wait for the other,
-      // let's start by packing A'.
-      pack_lhs(blockA, &lhs(0,k), lhsStride, actual_kc, mc);
+      // let's start by packing B'.
+      pack_rhs(blockB, rhs.getSubMapper(k,0), actual_kc, nc);
 
-      // Pack B_k to B' in a parallel fashion:
-      // each thread packs the sub block B_k,j to B'_j where j is the thread id.
+      // Pack A_k to A' in a parallel fashion:
+      // each thread packs the sub block A_k,i to A'_i where i is the thread id.
 
-      // However, before copying to B'_j, we have to make sure that no other thread is still using it,
+      // However, before copying to A'_i, we have to make sure that no other thread is still using it,
       // i.e., we test that info[tid].users equals 0.
       // Then, we set info[tid].users to the number of threads to mark that all other threads are going to use it.
       while(info[tid].users!=0) {}
       info[tid].users += threads;
 
-      pack_rhs(blockB+info[tid].rhs_start*actual_kc, &rhs(k,info[tid].rhs_start), rhsStride, actual_kc, info[tid].rhs_length);
+      pack_lhs(blockA+info[tid].lhs_start*actual_kc, lhs.getSubMapper(info[tid].lhs_start,k), actual_kc, info[tid].lhs_length);
 
-      // Notify the other threads that the part B'_j is ready to go.
+      // Notify the other threads that the part A'_i is ready to go.
       info[tid].sync = k;
 
-      // Computes C_i += A' * B' per B'_j
-      for(Index shift=0; shift<threads; ++shift)
+      // Computes C_i += A' * B' per A'_i
+      for(int shift=0; shift<threads; ++shift)
       {
-        Index j = (tid+shift)%threads;
+        int i = (tid+shift)%threads;
 
-        // At this point we have to make sure that B'_j has been updated by the thread j,
+        // At this point we have to make sure that A'_i has been updated by the thread i,
         // we use testAndSetOrdered to mimic a volatile access.
         // However, no need to wait for the B' part which has been updated by the current thread!
-        if(shift>0)
-          while(info[j].sync!=k) {}
-
-        gebp(res+info[j].rhs_start*resStride, resStride, blockA, blockB+info[j].rhs_start*actual_kc, mc, actual_kc, info[j].rhs_length, alpha, -1,-1,0,0, w);
-      }
-
-      // Then keep going as usual with the remaining A'
-      for(Index i=mc; i<rows; i+=mc)
-      {
-        const Index actual_mc = (std::min)(i+mc,rows)-i;
-
-        // pack A_i,k to A'
-        pack_lhs(blockA, &lhs(i,k), lhsStride, actual_kc, actual_mc);
-
-        // C_i += A' * B'
-        gebp(res+i, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha, -1,-1,0,0, w);
-      }
-
-      // Release all the sub blocks B'_j of B' for the current thread,
-      // i.e., we simply decrement the number of users by 1
-      for(Index j=0; j<threads; ++j)
-        #pragma omp atomic
-        --(info[j].users);
+        if (shift>0) {
+          while(info[i].sync!=k) {
+          }
+        }
+
+        gebp(res.getSubMapper(info[i].lhs_start, 0), blockA+info[i].lhs_start*actual_kc, blockB, info[i].lhs_length, actual_kc, nc, alpha);
+      }
+
+      // Then keep going as usual with the remaining B'
+      for(Index j=nc; j<cols; j+=nc)
+      {
+        const Index actual_nc = (std::min)(j+nc,cols)-j;
+
+        // pack B_k,j to B'
+        pack_rhs(blockB, rhs.getSubMapper(k,j), actual_kc, actual_nc);
+
+        // C_j += A' * B'
+        gebp(res.getSubMapper(0, j), blockA, blockB, rows, actual_kc, actual_nc, alpha);
+      }
+
+      // Release all the sub blocks A'_i of A' for the current thread,
+      // i.e., we simply decrement the number of users by 1
+      for(Index i=0; i<threads; ++i)
+        #pragma omp atomic
+        info[i].users -= 1;
     }
   }
   else
 #endif // EIGEN_HAS_OPENMP
   {
     EIGEN_UNUSED_VARIABLE(info);
 
     // this is the sequential version!
     std::size_t sizeA = kc*mc;
-    std::size_t sizeB = kc*cols;
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
+    std::size_t sizeB = kc*nc;
 
     ei_declare_aligned_stack_constructed_variable(LhsScalar, blockA, sizeA, blocking.blockA());
     ei_declare_aligned_stack_constructed_variable(RhsScalar, blockB, sizeB, blocking.blockB());
-    ei_declare_aligned_stack_constructed_variable(RhsScalar, blockW, sizeW, blocking.blockW());
+
+    const bool pack_rhs_once = mc!=rows && kc==depth && nc==cols;
 
     // For each horizontal panel of the rhs, and corresponding panel of the lhs...
-    // (==GEMM_VAR1)
-    for(Index k2=0; k2<depth; k2+=kc)
-    {
-      const Index actual_kc = (std::min)(k2+kc,depth)-k2;
-
-      // OK, here we have selected one horizontal panel of rhs and one vertical panel of lhs.
-      // => Pack rhs's panel into a sequential chunk of memory (L2 caching)
-      // Note that this panel will be read as many times as the number of blocks in the lhs's
-      // vertical panel which is, in practice, a very low number.
-      pack_rhs(blockB, &rhs(k2,0), rhsStride, actual_kc, cols);
-
-      // For each mc x kc block of the lhs's vertical panel...
-      // (==GEPP_VAR1)
-      for(Index i2=0; i2<rows; i2+=mc)
-      {
-        const Index actual_mc = (std::min)(i2+mc,rows)-i2;
-
-        // We pack the lhs's block into a sequential chunk of memory (L1 caching)
-        // Note that this block will be read a very high number of times, which is equal to the number of
-        // micro vertical panel of the large rhs's panel (e.g., cols/4 times).
-        pack_lhs(blockA, &lhs(i2,k2), lhsStride, actual_kc, actual_mc);
-
-        // Everything is packed, we can now call the block * panel kernel:
-        gebp(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha, -1, -1, 0, 0, blockW);
+    for(Index i2=0; i2<rows; i2+=mc)
+    {
+      const Index actual_mc = (std::min)(i2+mc,rows)-i2;
+
+      for(Index k2=0; k2<depth; k2+=kc)
+      {
+        const Index actual_kc = (std::min)(k2+kc,depth)-k2;
+
+        // OK, here we have selected one horizontal panel of rhs and one vertical panel of lhs.
+        // => Pack lhs's panel into a sequential chunk of memory (L2/L3 caching)
+        // Note that this panel will be read as many times as the number of blocks in the rhs's
+        // horizontal panel which is, in practice, a very low number.
+        pack_lhs(blockA, lhs.getSubMapper(i2,k2), actual_kc, actual_mc);
+
+        // For each kc x nc block of the rhs's horizontal panel...
+        for(Index j2=0; j2<cols; j2+=nc)
+        {
+          const Index actual_nc = (std::min)(j2+nc,cols)-j2;
+
+          // We pack the rhs's block into a sequential chunk of memory (L2 caching)
+          // Note that this block will be read a very high number of times, which is equal to the number of
+          // micro horizontal panel of the large rhs's panel (e.g., rows/12 times).
+          if((!pack_rhs_once) || i2==0)
+            pack_rhs(blockB, rhs.getSubMapper(k2,j2), actual_kc, actual_nc);
+
+          // Everything is packed, we can now call the panel * block kernel:
+          gebp(res.getSubMapper(i2, j2), blockA, blockB, actual_mc, actual_kc, actual_nc, alpha);
+        }
       }
     }
   }
 }
 
 };
 
 /*********************************************************************************
-*  Specialization of GeneralProduct<> for "large" GEMM, i.e.,
+*  Specialization of generic_product_impl for "large" GEMM, i.e.,
 *  implementation of the high level wrapper to general_matrix_matrix_product
 **********************************************************************************/
 
-template<typename Lhs, typename Rhs>
-struct traits<GeneralProduct<Lhs,Rhs,GemmProduct> >
- : traits<ProductBase<GeneralProduct<Lhs,Rhs,GemmProduct>, Lhs, Rhs> >
-{};
-
 template<typename Scalar, typename Index, typename Gemm, typename Lhs, typename Rhs, typename Dest, typename BlockingType>
 struct gemm_functor
 {
-  gemm_functor(const Lhs& lhs, const Rhs& rhs, Dest& dest, const Scalar& actualAlpha,
-                  BlockingType& blocking)
+  gemm_functor(const Lhs& lhs, const Rhs& rhs, Dest& dest, const Scalar& actualAlpha, BlockingType& blocking)
     : m_lhs(lhs), m_rhs(rhs), m_dest(dest), m_actualAlpha(actualAlpha), m_blocking(blocking)
   {}
 
-  void initParallelSession() const
+  void initParallelSession(Index num_threads) const
   {
-    m_blocking.allocateB();
+    m_blocking.initParallel(m_lhs.rows(), m_rhs.cols(), m_lhs.cols(), num_threads);
+    m_blocking.allocateA();
   }
 
   void operator() (Index row, Index rows, Index col=0, Index cols=-1, GemmParallelInfo<Index>* info=0) const
   {
     if(cols==-1)
       cols = m_rhs.cols();
 
     Gemm::run(rows, cols, m_lhs.cols(),
-              /*(const Scalar*)*/&m_lhs.coeffRef(row,0), m_lhs.outerStride(),
-              /*(const Scalar*)*/&m_rhs.coeffRef(0,col), m_rhs.outerStride(),
+              &m_lhs.coeffRef(row,0), m_lhs.outerStride(),
+              &m_rhs.coeffRef(0,col), m_rhs.outerStride(),
               (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.outerStride(),
               m_actualAlpha, m_blocking, info);
   }
+
+  typedef typename Gemm::Traits Traits;
 
   protected:
     const Lhs& m_lhs;
     const Rhs& m_rhs;
     Dest& m_dest;
@@ -243,33 +250,31 @@
     typedef _RhsScalar RhsScalar;
 
   protected:
     LhsScalar* m_blockA;
     RhsScalar* m_blockB;
-    RhsScalar* m_blockW;
 
-    DenseIndex m_mc;
-    DenseIndex m_nc;
-    DenseIndex m_kc;
+    Index m_mc;
+    Index m_nc;
+    Index m_kc;
 
   public:
 
     level3_blocking()
-      : m_blockA(0), m_blockB(0), m_blockW(0), m_mc(0), m_nc(0), m_kc(0)
+      : m_blockA(0), m_blockB(0), m_mc(0), m_nc(0), m_kc(0)
     {}
 
-    inline DenseIndex mc() const { return m_mc; }
-    inline DenseIndex nc() const { return m_nc; }
-    inline DenseIndex kc() const { return m_kc; }
+    inline Index mc() const { return m_mc; }
+    inline Index nc() const { return m_nc; }
+    inline Index kc() const { return m_kc; }
 
     inline LhsScalar* blockA() { return m_blockA; }
     inline RhsScalar* blockB() { return m_blockB; }
-    inline RhsScalar* blockW() { return m_blockW; }
 };
 
 template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor>
-class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, true>
+class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, true /* == FiniteAtCompileTime */>
   : public level3_blocking<
       typename conditional<StorageOrder==RowMajor,_RhsScalar,_LhsScalar>::type,
       typename conditional<StorageOrder==RowMajor,_LhsScalar,_RhsScalar>::type>
 {
     enum {
@@ -280,33 +285,42 @@
     typedef typename conditional<Transpose,_RhsScalar,_LhsScalar>::type LhsScalar;
     typedef typename conditional<Transpose,_LhsScalar,_RhsScalar>::type RhsScalar;
     typedef gebp_traits<LhsScalar,RhsScalar> Traits;
     enum {
       SizeA = ActualRows * MaxDepth,
-      SizeB = ActualCols * MaxDepth,
-      SizeW = MaxDepth * Traits::WorkSpaceFactor
+      SizeB = ActualCols * MaxDepth
     };
 
-    EIGEN_ALIGN16 LhsScalar m_staticA[SizeA];
-    EIGEN_ALIGN16 RhsScalar m_staticB[SizeB];
-    EIGEN_ALIGN16 RhsScalar m_staticW[SizeW];
+#if EIGEN_MAX_STATIC_ALIGN_BYTES >= EIGEN_DEFAULT_ALIGN_BYTES
+    EIGEN_ALIGN_MAX LhsScalar m_staticA[SizeA];
+    EIGEN_ALIGN_MAX RhsScalar m_staticB[SizeB];
+#else
+    EIGEN_ALIGN_MAX char m_staticA[SizeA * sizeof(LhsScalar) + EIGEN_DEFAULT_ALIGN_BYTES-1];
+    EIGEN_ALIGN_MAX char m_staticB[SizeB * sizeof(RhsScalar) + EIGEN_DEFAULT_ALIGN_BYTES-1];
+#endif
 
   public:
 
-    gemm_blocking_space(DenseIndex /*rows*/, DenseIndex /*cols*/, DenseIndex /*depth*/)
+    gemm_blocking_space(Index /*rows*/, Index /*cols*/, Index /*depth*/, Index /*num_threads*/, bool /*full_rows = false*/)
     {
       this->m_mc = ActualRows;
       this->m_nc = ActualCols;
       this->m_kc = MaxDepth;
+#if EIGEN_MAX_STATIC_ALIGN_BYTES >= EIGEN_DEFAULT_ALIGN_BYTES
       this->m_blockA = m_staticA;
       this->m_blockB = m_staticB;
-      this->m_blockW = m_staticW;
+#else
+      this->m_blockA = reinterpret_cast<LhsScalar*>((internal::UIntPtr(m_staticA) + (EIGEN_DEFAULT_ALIGN_BYTES-1)) & ~std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1));
+      this->m_blockB = reinterpret_cast<RhsScalar*>((internal::UIntPtr(m_staticB) + (EIGEN_DEFAULT_ALIGN_BYTES-1)) & ~std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1));
+#endif
     }
+
+    void initParallel(Index, Index, Index, Index)
+    {}
 
     inline void allocateA() {}
     inline void allocateB() {}
-    inline void allocateW() {}
     inline void allocateAll() {}
 };
 
 template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor>
 class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, false>
@@ -319,26 +333,46 @@
     };
     typedef typename conditional<Transpose,_RhsScalar,_LhsScalar>::type LhsScalar;
     typedef typename conditional<Transpose,_LhsScalar,_RhsScalar>::type RhsScalar;
     typedef gebp_traits<LhsScalar,RhsScalar> Traits;
 
-    DenseIndex m_sizeA;
-    DenseIndex m_sizeB;
-    DenseIndex m_sizeW;
+    Index m_sizeA;
+    Index m_sizeB;
 
   public:
 
-    gemm_blocking_space(DenseIndex rows, DenseIndex cols, DenseIndex depth)
+    gemm_blocking_space(Index rows, Index cols, Index depth, Index num_threads, bool l3_blocking)
+    {
+      this->m_mc = Transpose ? cols : rows;
+      this->m_nc = Transpose ? rows : cols;
+      this->m_kc = depth;
+
+      if(l3_blocking)
+      {
+        computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, this->m_mc, this->m_nc, num_threads);
+      }
+      else  // no l3 blocking
+      {
+        Index n = this->m_nc;
+        computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, this->m_mc, n, num_threads);
+      }
+
+      m_sizeA = this->m_mc * this->m_kc;
+      m_sizeB = this->m_kc * this->m_nc;
+    }
+
+    void initParallel(Index rows, Index cols, Index depth, Index num_threads)
     {
       this->m_mc = Transpose ? cols : rows;
       this->m_nc = Transpose ? rows : cols;
       this->m_kc = depth;
 
-      computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, this->m_mc, this->m_nc);
+      eigen_internal_assert(this->m_blockA==0 && this->m_blockB==0);
+      Index m = this->m_mc;
+      computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, m, this->m_nc, num_threads);
       m_sizeA = this->m_mc * this->m_kc;
       m_sizeB = this->m_kc * this->m_nc;
-      m_sizeW = this->m_kc*Traits::WorkSpaceFactor;
     }
 
     void allocateA()
     {
       if(this->m_blockA==0)
@@ -349,79 +383,110 @@
     {
       if(this->m_blockB==0)
         this->m_blockB = aligned_new<RhsScalar>(m_sizeB);
     }
 
-    void allocateW()
-    {
-      if(this->m_blockW==0)
-        this->m_blockW = aligned_new<RhsScalar>(m_sizeW);
-    }
-
     void allocateAll()
     {
       allocateA();
       allocateB();
-      allocateW();
     }
 
     ~gemm_blocking_space()
     {
       aligned_delete(this->m_blockA, m_sizeA);
       aligned_delete(this->m_blockB, m_sizeB);
-      aligned_delete(this->m_blockW, m_sizeW);
     }
 };
 
 } // end namespace internal
 
-template<typename Lhs, typename Rhs>
-class GeneralProduct<Lhs, Rhs, GemmProduct>
-  : public ProductBase<GeneralProduct<Lhs,Rhs,GemmProduct>, Lhs, Rhs>
-{
-    enum {
-      MaxDepthAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(Lhs::MaxColsAtCompileTime,Rhs::MaxRowsAtCompileTime)
-    };
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
-    
-    typedef typename  Lhs::Scalar LhsScalar;
-    typedef typename  Rhs::Scalar RhsScalar;
-    typedef           Scalar      ResScalar;
-
-    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
-    {
-      typedef internal::scalar_product_op<LhsScalar,RhsScalar> BinOp;
-      EIGEN_CHECK_BINARY_COMPATIBILIY(BinOp,LhsScalar,RhsScalar);
-    }
-
-    template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
-    {
-      eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
-
-      typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(m_lhs);
-      typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(m_rhs);
-
-      Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
-                                 * RhsBlasTraits::extractScalarFactor(m_rhs);
-
-      typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,LhsScalar,RhsScalar,
-              Dest::MaxRowsAtCompileTime,Dest::MaxColsAtCompileTime,MaxDepthAtCompileTime> BlockingType;
-
-      typedef internal::gemm_functor<
-        Scalar, Index,
-        internal::general_matrix_matrix_product<
-          Index,
-          LhsScalar, (_ActualLhsType::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(LhsBlasTraits::NeedToConjugate),
-          RhsScalar, (_ActualRhsType::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(RhsBlasTraits::NeedToConjugate),
-          (Dest::Flags&RowMajorBit) ? RowMajor : ColMajor>,
-        _ActualLhsType, _ActualRhsType, Dest, BlockingType> GemmFunctor;
-
-      BlockingType blocking(dst.rows(), dst.cols(), lhs.cols());
-
-      internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)>(GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), this->rows(), this->cols(), Dest::Flags&RowMajorBit);
-    }
-};
+namespace internal {
+
+template<typename Lhs, typename Rhs>
+struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemmProduct>
+  : generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemmProduct> >
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  typedef typename Lhs::Scalar LhsScalar;
+  typedef typename Rhs::Scalar RhsScalar;
+
+  typedef internal::blas_traits<Lhs> LhsBlasTraits;
+  typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+  typedef typename internal::remove_all<ActualLhsType>::type ActualLhsTypeCleaned;
+
+  typedef internal::blas_traits<Rhs> RhsBlasTraits;
+  typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+  typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
+
+  enum {
+    MaxDepthAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(Lhs::MaxColsAtCompileTime,Rhs::MaxRowsAtCompileTime)
+  };
+
+  typedef generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode> lazyproduct;
+
+  template<typename Dst>
+  static void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    if((rhs.rows()+dst.rows()+dst.cols())<20 && rhs.rows()>0)
+      lazyproduct::evalTo(dst, lhs, rhs);
+    else
+    {
+      dst.setZero();
+      scaleAndAddTo(dst, lhs, rhs, Scalar(1));
+    }
+  }
+
+  template<typename Dst>
+  static void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    if((rhs.rows()+dst.rows()+dst.cols())<20 && rhs.rows()>0)
+      lazyproduct::addTo(dst, lhs, rhs);
+    else
+      scaleAndAddTo(dst,lhs, rhs, Scalar(1));
+  }
+
+  template<typename Dst>
+  static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    if((rhs.rows()+dst.rows()+dst.cols())<20 && rhs.rows()>0)
+      lazyproduct::subTo(dst, lhs, rhs);
+    else
+      scaleAndAddTo(dst, lhs, rhs, Scalar(-1));
+  }
+
+  template<typename Dest>
+  static void scaleAndAddTo(Dest& dst, const Lhs& a_lhs, const Rhs& a_rhs, const Scalar& alpha)
+  {
+    eigen_assert(dst.rows()==a_lhs.rows() && dst.cols()==a_rhs.cols());
+    if(a_lhs.cols()==0 || a_lhs.rows()==0 || a_rhs.cols()==0)
+      return;
+
+    typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs);
+    typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs);
+
+    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs)
+                               * RhsBlasTraits::extractScalarFactor(a_rhs);
+
+    typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,LhsScalar,RhsScalar,
+            Dest::MaxRowsAtCompileTime,Dest::MaxColsAtCompileTime,MaxDepthAtCompileTime> BlockingType;
+
+    typedef internal::gemm_functor<
+      Scalar, Index,
+      internal::general_matrix_matrix_product<
+        Index,
+        LhsScalar, (ActualLhsTypeCleaned::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(LhsBlasTraits::NeedToConjugate),
+        RhsScalar, (ActualRhsTypeCleaned::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(RhsBlasTraits::NeedToConjugate),
+        (Dest::Flags&RowMajorBit) ? RowMajor : ColMajor>,
+      ActualLhsTypeCleaned, ActualRhsTypeCleaned, Dest, BlockingType> GemmFunctor;
+
+    BlockingType blocking(dst.rows(), dst.cols(), lhs.cols(), 1, true);
+    internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)>
+        (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit);
+  }
+};
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_GENERAL_MATRIX_MATRIX_H

Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
@@ -18,11 +18,11 @@
 namespace internal {
 
 /**********************************************************************
 * This file implements a general A * B product while
 * evaluating only one triangular part of the product.
-* This is more general version of self adjoint product (C += A A^T)
+* This is a more general version of self adjoint product (C += A A^T)
 * as the level 3 SYRK Blas routine.
 **********************************************************************/
 
 // forward declarations (defined at the end of this file)
 template<typename LhsScalar, typename RhsScalar, typename Index, int mr, int nr, bool ConjLhs, bool ConjRhs, int UpLo>
@@ -38,82 +38,88 @@
 // as usual if the result is row major => we transpose the product
 template <typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
                           typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, int  UpLo, int Version>
 struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,RowMajor,UpLo,Version>
 {
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   static EIGEN_STRONG_INLINE void run(Index size, Index depth,const LhsScalar* lhs, Index lhsStride,
-                                      const RhsScalar* rhs, Index rhsStride, ResScalar* res, Index resStride, const ResScalar& alpha)
+                                      const RhsScalar* rhs, Index rhsStride, ResScalar* res, Index resStride,
+                                      const ResScalar& alpha, level3_blocking<RhsScalar,LhsScalar>& blocking)
   {
     general_matrix_matrix_triangular_product<Index,
         RhsScalar, RhsStorageOrder==RowMajor ? ColMajor : RowMajor, ConjugateRhs,
         LhsScalar, LhsStorageOrder==RowMajor ? ColMajor : RowMajor, ConjugateLhs,
         ColMajor, UpLo==Lower?Upper:Lower>
-      ::run(size,depth,rhs,rhsStride,lhs,lhsStride,res,resStride,alpha);
+      ::run(size,depth,rhs,rhsStride,lhs,lhsStride,res,resStride,alpha,blocking);
   }
 };
 
 template <typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
                           typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, int  UpLo, int Version>
 struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor,UpLo,Version>
 {
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   static EIGEN_STRONG_INLINE void run(Index size, Index depth,const LhsScalar* _lhs, Index lhsStride,
-                                      const RhsScalar* _rhs, Index rhsStride, ResScalar* res, Index resStride, const ResScalar& alpha)
+                                      const RhsScalar* _rhs, Index rhsStride, ResScalar* _res, Index resStride,
+                                      const ResScalar& alpha, level3_blocking<LhsScalar,RhsScalar>& blocking)
   {
-    const_blas_data_mapper<LhsScalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
-    const_blas_data_mapper<RhsScalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
-
     typedef gebp_traits<LhsScalar,RhsScalar> Traits;
 
-    Index kc = depth; // cache block size along the K direction
-    Index mc = size;  // cache block size along the M direction
-    Index nc = size;  // cache block size along the N direction
-    computeProductBlockingSizes<LhsScalar,RhsScalar>(kc, mc, nc);
+    typedef const_blas_data_mapper<LhsScalar, Index, LhsStorageOrder> LhsMapper;
+    typedef const_blas_data_mapper<RhsScalar, Index, RhsStorageOrder> RhsMapper;
+    typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
+    LhsMapper lhs(_lhs,lhsStride);
+    RhsMapper rhs(_rhs,rhsStride);
+    ResMapper res(_res, resStride);
+
+    Index kc = blocking.kc();
+    Index mc = (std::min)(size,blocking.mc());
+
     // !!! mc must be a multiple of nr:
     if(mc > Traits::nr)
       mc = (mc/Traits::nr)*Traits::nr;
 
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
-    std::size_t sizeB = sizeW + kc*size;
-    ei_declare_aligned_stack_constructed_variable(LhsScalar, blockA, kc*mc, 0);
-    ei_declare_aligned_stack_constructed_variable(RhsScalar, allocatedBlockB, sizeB, 0);
-    RhsScalar* blockB = allocatedBlockB + sizeW;
-    
-    gemm_pack_lhs<LhsScalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
-    gemm_pack_rhs<RhsScalar, Index, Traits::nr, RhsStorageOrder> pack_rhs;
-    gebp_kernel <LhsScalar, RhsScalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
+    std::size_t sizeA = kc*mc;
+    std::size_t sizeB = kc*size;
+
+    ei_declare_aligned_stack_constructed_variable(LhsScalar, blockA, sizeA, blocking.blockA());
+    ei_declare_aligned_stack_constructed_variable(RhsScalar, blockB, sizeB, blocking.blockB());
+
+    gemm_pack_lhs<LhsScalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+    gemm_pack_rhs<RhsScalar, Index, RhsMapper, Traits::nr, RhsStorageOrder> pack_rhs;
+    gebp_kernel<LhsScalar, RhsScalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
     tribb_kernel<LhsScalar, RhsScalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs, UpLo> sybb;
 
     for(Index k2=0; k2<depth; k2+=kc)
     {
       const Index actual_kc = (std::min)(k2+kc,depth)-k2;
 
       // note that the actual rhs is the transpose/adjoint of mat
-      pack_rhs(blockB, &rhs(k2,0), rhsStride, actual_kc, size);
+      pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, size);
 
       for(Index i2=0; i2<size; i2+=mc)
       {
         const Index actual_mc = (std::min)(i2+mc,size)-i2;
 
-        pack_lhs(blockA, &lhs(i2, k2), lhsStride, actual_kc, actual_mc);
+        pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
 
         // the selected actual_mc * size panel of res is split into three different part:
         //  1 - before the diagonal => processed with gebp or skipped
         //  2 - the actual_mc x actual_mc symmetric block => processed with a special kernel
         //  3 - after the diagonal => processed with gebp or skipped
         if (UpLo==Lower)
-          gebp(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, (std::min)(size,i2), alpha,
-               -1, -1, 0, 0, allocatedBlockB);
+          gebp(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc,
+               (std::min)(size,i2), alpha, -1, -1, 0, 0);
+
 
-        sybb(res+resStride*i2 + i2, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha, allocatedBlockB);
+        sybb(_res+resStride*i2 + i2, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha);
 
         if (UpLo==Upper)
         {
           Index j2 = i2+actual_mc;
-          gebp(res+resStride*j2+i2, resStride, blockA, blockB+actual_kc*j2, actual_mc, actual_kc, (std::max)(Index(0), size-j2), alpha,
-               -1, -1, 0, 0, allocatedBlockB);
+          gebp(res.getSubMapper(i2, j2), blockA, blockB+actual_kc*j2, actual_mc,
+               actual_kc, (std::max)(Index(0), size-j2), alpha, -1, -1, 0, 0);
         }
       }
     }
   }
 };
@@ -130,52 +136,55 @@
 template<typename LhsScalar, typename RhsScalar, typename Index, int mr, int nr, bool ConjLhs, bool ConjRhs, int UpLo>
 struct tribb_kernel
 {
   typedef gebp_traits<LhsScalar,RhsScalar,ConjLhs,ConjRhs> Traits;
   typedef typename Traits::ResScalar ResScalar;
-  
+
   enum {
-    BlockSize  = EIGEN_PLAIN_ENUM_MAX(mr,nr)
+    BlockSize  = meta_least_common_multiple<EIGEN_PLAIN_ENUM_MAX(mr,nr),EIGEN_PLAIN_ENUM_MIN(mr,nr)>::ret
   };
-  void operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index size, Index depth, const ResScalar& alpha, RhsScalar* workspace)
+  void operator()(ResScalar* _res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index size, Index depth, const ResScalar& alpha)
   {
-    gebp_kernel<LhsScalar, RhsScalar, Index, mr, nr, ConjLhs, ConjRhs> gebp_kernel;
-    Matrix<ResScalar,BlockSize,BlockSize,ColMajor> buffer;
+    typedef blas_data_mapper<ResScalar, Index, ColMajor> ResMapper;
+    ResMapper res(_res, resStride);
+    gebp_kernel<LhsScalar, RhsScalar, Index, ResMapper, mr, nr, ConjLhs, ConjRhs> gebp_kernel;
+
+    Matrix<ResScalar,BlockSize,BlockSize,ColMajor> buffer((internal::constructor_without_unaligned_array_assert()));
 
     // let's process the block per panel of actual_mc x BlockSize,
     // again, each is split into three parts, etc.
     for (Index j=0; j<size; j+=BlockSize)
     {
       Index actualBlockSize = std::min<Index>(BlockSize,size - j);
       const RhsScalar* actual_b = blockB+j*depth;
 
       if(UpLo==Upper)
-        gebp_kernel(res+j*resStride, resStride, blockA, actual_b, j, depth, actualBlockSize, alpha,
-                    -1, -1, 0, 0, workspace);
+        gebp_kernel(res.getSubMapper(0, j), blockA, actual_b, j, depth, actualBlockSize, alpha,
+                    -1, -1, 0, 0);
 
       // selfadjoint micro block
       {
         Index i = j;
         buffer.setZero();
         // 1 - apply the kernel on the temporary buffer
-        gebp_kernel(buffer.data(), BlockSize, blockA+depth*i, actual_b, actualBlockSize, depth, actualBlockSize, alpha,
-                    -1, -1, 0, 0, workspace);
+        gebp_kernel(ResMapper(buffer.data(), BlockSize), blockA+depth*i, actual_b, actualBlockSize, depth, actualBlockSize, alpha,
+                    -1, -1, 0, 0);
         // 2 - triangular accumulation
         for(Index j1=0; j1<actualBlockSize; ++j1)
         {
-          ResScalar* r = res + (j+j1)*resStride + i;
+          ResScalar* r = &res(i, j + j1);
           for(Index i1=UpLo==Lower ? j1 : 0;
               UpLo==Lower ? i1<actualBlockSize : i1<=j1; ++i1)
             r[i1] += buffer(i1,j1);
         }
       }
 
       if(UpLo==Lower)
       {
         Index i = j+actualBlockSize;
-        gebp_kernel(res+j*resStride+i, resStride, blockA+depth*i, actual_b, size-i, depth, actualBlockSize, alpha,
-                    -1, -1, 0, 0, workspace);
+        gebp_kernel(res.getSubMapper(i, j), blockA+depth*i, actual_b, size-i, 
+                    depth, actualBlockSize, alpha, -1, -1, 0, 0);
       }
     }
   }
 };
 
@@ -188,14 +197,13 @@
 
 
 template<typename MatrixType, typename ProductType, int UpLo>
 struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,true>
 {
-  static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha)
+  static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha, bool beta)
   {
     typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
     
     typedef typename internal::remove_all<typename ProductType::LhsNested>::type Lhs;
     typedef internal::blas_traits<Lhs> LhsBlasTraits;
     typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhs;
     typedef typename internal::remove_all<ActualLhs>::type _ActualLhs;
@@ -207,10 +215,13 @@
     typedef typename internal::remove_all<ActualRhs>::type _ActualRhs;
     typename internal::add_const_on_value_type<ActualRhs>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
 
     Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs().derived()) * RhsBlasTraits::extractScalarFactor(prod.rhs().derived());
 
+    if(!beta)
+      mat.template triangularView<UpLo>().setZero();
+
     enum {
       StorageOrder = (internal::traits<MatrixType>::Flags&RowMajorBit) ? RowMajor : ColMajor,
       UseLhsDirectly = _ActualLhs::InnerStrideAtCompileTime==1,
       UseRhsDirectly = _ActualRhs::InnerStrideAtCompileTime==1
     };
@@ -234,14 +245,12 @@
 };
 
 template<typename MatrixType, typename ProductType, int UpLo>
 struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,false>
 {
-  static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha)
+  static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha, bool beta)
   {
-    typedef typename MatrixType::Index Index;
-    
     typedef typename internal::remove_all<typename ProductType::LhsNested>::type Lhs;
     typedef internal::blas_traits<Lhs> LhsBlasTraits;
     typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhs;
     typedef typename internal::remove_all<ActualLhs>::type _ActualLhs;
     typename internal::add_const_on_value_type<ActualLhs>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
@@ -252,27 +261,51 @@
     typedef typename internal::remove_all<ActualRhs>::type _ActualRhs;
     typename internal::add_const_on_value_type<ActualRhs>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
 
     typename ProductType::Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs().derived()) * RhsBlasTraits::extractScalarFactor(prod.rhs().derived());
 
+    if(!beta)
+      mat.template triangularView<UpLo>().setZero();
+
+    enum {
+      IsRowMajor = (internal::traits<MatrixType>::Flags&RowMajorBit) ? 1 : 0,
+      LhsIsRowMajor = _ActualLhs::Flags&RowMajorBit ? 1 : 0,
+      RhsIsRowMajor = _ActualRhs::Flags&RowMajorBit ? 1 : 0,
+      SkipDiag = (UpLo&(UnitDiag|ZeroDiag))!=0
+    };
+
+    Index size = mat.cols();
+    if(SkipDiag)
+      size--;
+    Index depth = actualLhs.cols();
+
+    typedef internal::gemm_blocking_space<IsRowMajor ? RowMajor : ColMajor,typename Lhs::Scalar,typename Rhs::Scalar,
+          MatrixType::MaxColsAtCompileTime, MatrixType::MaxColsAtCompileTime, _ActualRhs::MaxColsAtCompileTime> BlockingType;
+
+    BlockingType blocking(size, size, depth, 1, false);
+
     internal::general_matrix_matrix_triangular_product<Index,
-      typename Lhs::Scalar, _ActualLhs::Flags&RowMajorBit ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
-      typename Rhs::Scalar, _ActualRhs::Flags&RowMajorBit ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
-      MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor, UpLo>
-      ::run(mat.cols(), actualLhs.cols(),
-            &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &actualRhs.coeffRef(0,0), actualRhs.outerStride(),
-            mat.data(), mat.outerStride(), actualAlpha);
+      typename Lhs::Scalar, LhsIsRowMajor ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
+      typename Rhs::Scalar, RhsIsRowMajor ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
+      IsRowMajor ? RowMajor : ColMajor, UpLo&(Lower|Upper)>
+      ::run(size, depth,
+            &actualLhs.coeffRef(SkipDiag&&(UpLo&Lower)==Lower ? 1 : 0,0), actualLhs.outerStride(),
+            &actualRhs.coeffRef(0,SkipDiag&&(UpLo&Upper)==Upper ? 1 : 0), actualRhs.outerStride(),
+            mat.data() + (SkipDiag ? (bool(IsRowMajor) != ((UpLo&Lower)==Lower) ? 1 : mat.outerStride() ) : 0), mat.outerStride(), actualAlpha, blocking);
   }
 };
 
 template<typename MatrixType, unsigned int UpLo>
-template<typename ProductDerived, typename _Lhs, typename _Rhs>
-TriangularView<MatrixType,UpLo>& TriangularView<MatrixType,UpLo>::assignProduct(const ProductBase<ProductDerived, _Lhs,_Rhs>& prod, const Scalar& alpha)
+template<typename ProductType>
+TriangularView<MatrixType,UpLo>& TriangularViewImpl<MatrixType,UpLo,Dense>::_assignProduct(const ProductType& prod, const Scalar& alpha, bool beta)
 {
-  general_product_to_triangular_selector<MatrixType, ProductDerived, UpLo, (_Lhs::ColsAtCompileTime==1) || (_Rhs::RowsAtCompileTime==1)>::run(m_matrix.const_cast_derived(), prod.derived(), alpha);
+  EIGEN_STATIC_ASSERT((UpLo&UnitDiag)==0, WRITING_TO_TRIANGULAR_PART_WITH_UNIT_DIAGONAL_IS_NOT_SUPPORTED);
+  eigen_assert(derived().nestedExpression().rows() == prod.rows() && derived().cols() == prod.cols());
+  
+  general_product_to_triangular_selector<MatrixType, ProductType, UpLo, internal::traits<ProductType>::InnerSize==1>::run(derived().nestedExpression().const_cast_derived(), prod, alpha, beta);
   
-  return *this;
+  return derived();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H

ADDED   3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h
Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h
@@ -0,0 +1,141 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to BLAS F77
+ *   Level 3 BLAS SYRK/HERK implementation.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_BLAS_H
+#define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_BLAS_H
+
+namespace Eigen {
+
+namespace internal {
+
+template <typename Index, typename Scalar, int AStorageOrder, bool ConjugateA, int ResStorageOrder, int  UpLo>
+struct general_matrix_matrix_rankupdate :
+       general_matrix_matrix_triangular_product<
+         Index,Scalar,AStorageOrder,ConjugateA,Scalar,AStorageOrder,ConjugateA,ResStorageOrder,UpLo,BuiltIn> {};
+
+
+// try to go to BLAS specialization
+#define EIGEN_BLAS_RANKUPDATE_SPECIALIZE(Scalar) \
+template <typename Index, int LhsStorageOrder, bool ConjugateLhs, \
+                          int RhsStorageOrder, bool ConjugateRhs, int  UpLo> \
+struct general_matrix_matrix_triangular_product<Index,Scalar,LhsStorageOrder,ConjugateLhs, \
+               Scalar,RhsStorageOrder,ConjugateRhs,ColMajor,UpLo,Specialized> { \
+  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const Scalar* lhs, Index lhsStride, \
+                          const Scalar* rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha, level3_blocking<Scalar, Scalar>& blocking) \
+  { \
+    if ( lhs==rhs && ((UpLo&(Lower|Upper)==UpLo)) ) { \
+      general_matrix_matrix_rankupdate<Index,Scalar,LhsStorageOrder,ConjugateLhs,ColMajor,UpLo> \
+      ::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha,blocking); \
+    } else { \
+      general_matrix_matrix_triangular_product<Index, \
+        Scalar, LhsStorageOrder, ConjugateLhs, \
+        Scalar, RhsStorageOrder, ConjugateRhs, \
+        ColMajor, UpLo, BuiltIn> \
+      ::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha,blocking); \
+    } \
+  } \
+};
+
+EIGEN_BLAS_RANKUPDATE_SPECIALIZE(double)
+EIGEN_BLAS_RANKUPDATE_SPECIALIZE(float)
+// TODO handle complex cases
+// EIGEN_BLAS_RANKUPDATE_SPECIALIZE(dcomplex)
+// EIGEN_BLAS_RANKUPDATE_SPECIALIZE(scomplex)
+
+// SYRK for float/double
+#define EIGEN_BLAS_RANKUPDATE_R(EIGTYPE, BLASTYPE, BLASFUNC) \
+template <typename Index, int AStorageOrder, bool ConjugateA, int  UpLo> \
+struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,ColMajor,UpLo> { \
+  enum { \
+    IsLower = (UpLo&Lower) == Lower, \
+    LowUp = IsLower ? Lower : Upper, \
+    conjA = ((AStorageOrder==ColMajor) && ConjugateA) ? 1 : 0 \
+  }; \
+  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const EIGTYPE* lhs, Index lhsStride, \
+                          const EIGTYPE* /*rhs*/, Index /*rhsStride*/, EIGTYPE* res, Index resStride, EIGTYPE alpha, level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/) \
+  { \
+  /* typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs;*/ \
+\
+   BlasIndex lda=convert_index<BlasIndex>(lhsStride), ldc=convert_index<BlasIndex>(resStride), n=convert_index<BlasIndex>(size), k=convert_index<BlasIndex>(depth); \
+   char uplo=((IsLower) ? 'L' : 'U'), trans=((AStorageOrder==RowMajor) ? 'T':'N'); \
+   EIGTYPE beta(1); \
+   BLASFUNC(&uplo, &trans, &n, &k, &numext::real_ref(alpha), lhs, &lda, &numext::real_ref(beta), res, &ldc); \
+  } \
+};
+
+// HERK for complex data
+#define EIGEN_BLAS_RANKUPDATE_C(EIGTYPE, BLASTYPE, RTYPE, BLASFUNC) \
+template <typename Index, int AStorageOrder, bool ConjugateA, int  UpLo> \
+struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,ColMajor,UpLo> { \
+  enum { \
+    IsLower = (UpLo&Lower) == Lower, \
+    LowUp = IsLower ? Lower : Upper, \
+    conjA = (((AStorageOrder==ColMajor) && ConjugateA) || ((AStorageOrder==RowMajor) && !ConjugateA)) ? 1 : 0 \
+  }; \
+  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const EIGTYPE* lhs, Index lhsStride, \
+                          const EIGTYPE* /*rhs*/, Index /*rhsStride*/, EIGTYPE* res, Index resStride, EIGTYPE alpha, level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/) \
+  { \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, AStorageOrder> MatrixType; \
+\
+   BlasIndex lda=convert_index<BlasIndex>(lhsStride), ldc=convert_index<BlasIndex>(resStride), n=convert_index<BlasIndex>(size), k=convert_index<BlasIndex>(depth); \
+   char uplo=((IsLower) ? 'L' : 'U'), trans=((AStorageOrder==RowMajor) ? 'C':'N'); \
+   RTYPE alpha_, beta_; \
+   const EIGTYPE* a_ptr; \
+\
+   alpha_ = alpha.real(); \
+   beta_ = 1.0; \
+/* Copy with conjugation in some cases*/ \
+   MatrixType a; \
+   if (conjA) { \
+     Map<const MatrixType, 0, OuterStride<> > mapA(lhs,n,k,OuterStride<>(lhsStride)); \
+     a = mapA.conjugate(); \
+     lda = a.outerStride(); \
+     a_ptr = a.data(); \
+   } else a_ptr=lhs; \
+   BLASFUNC(&uplo, &trans, &n, &k, &alpha_, (BLASTYPE*)a_ptr, &lda, &beta_, (BLASTYPE*)res, &ldc); \
+  } \
+};
+
+
+EIGEN_BLAS_RANKUPDATE_R(double, double, dsyrk_)
+EIGEN_BLAS_RANKUPDATE_R(float,  float,  ssyrk_)
+
+// TODO hanlde complex cases
+// EIGEN_BLAS_RANKUPDATE_C(dcomplex, double, double, zherk_)
+// EIGEN_BLAS_RANKUPDATE_C(scomplex, float,  float, cherk_)
+
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_BLAS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h
Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h
@@ -1,146 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   Level 3 BLAS SYRK/HERK implementation.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H
-#define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template <typename Index, typename Scalar, int AStorageOrder, bool ConjugateA, int ResStorageOrder, int  UpLo>
-struct general_matrix_matrix_rankupdate :
-       general_matrix_matrix_triangular_product<
-         Index,Scalar,AStorageOrder,ConjugateA,Scalar,AStorageOrder,ConjugateA,ResStorageOrder,UpLo,BuiltIn> {};
-
-
-// try to go to BLAS specialization
-#define EIGEN_MKL_RANKUPDATE_SPECIALIZE(Scalar) \
-template <typename Index, int LhsStorageOrder, bool ConjugateLhs, \
-                          int RhsStorageOrder, bool ConjugateRhs, int  UpLo> \
-struct general_matrix_matrix_triangular_product<Index,Scalar,LhsStorageOrder,ConjugateLhs, \
-               Scalar,RhsStorageOrder,ConjugateRhs,ColMajor,UpLo,Specialized> { \
-  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const Scalar* lhs, Index lhsStride, \
-                          const Scalar* rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha) \
-  { \
-    if (lhs==rhs) { \
-      general_matrix_matrix_rankupdate<Index,Scalar,LhsStorageOrder,ConjugateLhs,ColMajor,UpLo> \
-      ::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha); \
-    } else { \
-      general_matrix_matrix_triangular_product<Index, \
-        Scalar, LhsStorageOrder, ConjugateLhs, \
-        Scalar, RhsStorageOrder, ConjugateRhs, \
-        ColMajor, UpLo, BuiltIn> \
-      ::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha); \
-    } \
-  } \
-};
-
-EIGEN_MKL_RANKUPDATE_SPECIALIZE(double)
-//EIGEN_MKL_RANKUPDATE_SPECIALIZE(dcomplex)
-EIGEN_MKL_RANKUPDATE_SPECIALIZE(float)
-//EIGEN_MKL_RANKUPDATE_SPECIALIZE(scomplex)
-
-// SYRK for float/double
-#define EIGEN_MKL_RANKUPDATE_R(EIGTYPE, MKLTYPE, MKLFUNC) \
-template <typename Index, int AStorageOrder, bool ConjugateA, int  UpLo> \
-struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,ColMajor,UpLo> { \
-  enum { \
-    IsLower = (UpLo&Lower) == Lower, \
-    LowUp = IsLower ? Lower : Upper, \
-    conjA = ((AStorageOrder==ColMajor) && ConjugateA) ? 1 : 0 \
-  }; \
-  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const EIGTYPE* lhs, Index lhsStride, \
-                          const EIGTYPE* rhs, Index rhsStride, EIGTYPE* res, Index resStride, EIGTYPE alpha) \
-  { \
-  /* typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs;*/ \
-\
-   MKL_INT lda=lhsStride, ldc=resStride, n=size, k=depth; \
-   char uplo=(IsLower) ? 'L' : 'U', trans=(AStorageOrder==RowMajor) ? 'T':'N'; \
-   MKLTYPE alpha_, beta_; \
-\
-/* Set alpha_ & beta_ */ \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
-   MKLFUNC(&uplo, &trans, &n, &k, &alpha_, lhs, &lda, &beta_, res, &ldc); \
-  } \
-};
-
-// HERK for complex data
-#define EIGEN_MKL_RANKUPDATE_C(EIGTYPE, MKLTYPE, RTYPE, MKLFUNC) \
-template <typename Index, int AStorageOrder, bool ConjugateA, int  UpLo> \
-struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,ColMajor,UpLo> { \
-  enum { \
-    IsLower = (UpLo&Lower) == Lower, \
-    LowUp = IsLower ? Lower : Upper, \
-    conjA = (((AStorageOrder==ColMajor) && ConjugateA) || ((AStorageOrder==RowMajor) && !ConjugateA)) ? 1 : 0 \
-  }; \
-  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const EIGTYPE* lhs, Index lhsStride, \
-                          const EIGTYPE* rhs, Index rhsStride, EIGTYPE* res, Index resStride, EIGTYPE alpha) \
-  { \
-   typedef Matrix<EIGTYPE, Dynamic, Dynamic, AStorageOrder> MatrixType; \
-\
-   MKL_INT lda=lhsStride, ldc=resStride, n=size, k=depth; \
-   char uplo=(IsLower) ? 'L' : 'U', trans=(AStorageOrder==RowMajor) ? 'C':'N'; \
-   RTYPE alpha_, beta_; \
-   const EIGTYPE* a_ptr; \
-\
-/* Set alpha_ & beta_ */ \
-/*   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); */\
-/*   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1));*/ \
-   alpha_ = alpha.real(); \
-   beta_ = 1.0; \
-/* Copy with conjugation in some cases*/ \
-   MatrixType a; \
-   if (conjA) { \
-     Map<const MatrixType, 0, OuterStride<> > mapA(lhs,n,k,OuterStride<>(lhsStride)); \
-     a = mapA.conjugate(); \
-     lda = a.outerStride(); \
-     a_ptr = a.data(); \
-   } else a_ptr=lhs; \
-   MKLFUNC(&uplo, &trans, &n, &k, &alpha_, (MKLTYPE*)a_ptr, &lda, &beta_, (MKLTYPE*)res, &ldc); \
-  } \
-};
-
-
-EIGEN_MKL_RANKUPDATE_R(double, double, dsyrk)
-EIGEN_MKL_RANKUPDATE_R(float,  float,  ssyrk)
-
-//EIGEN_MKL_RANKUPDATE_C(dcomplex, MKL_Complex16, double, zherk)
-//EIGEN_MKL_RANKUPDATE_C(scomplex, MKL_Complex8,  double, cherk)
-
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H

ADDED   3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h
Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h
@@ -0,0 +1,115 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to BLAS F77
+ *   General matrix-matrix product functionality based on ?GEMM.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_GENERAL_MATRIX_MATRIX_BLAS_H
+#define EIGEN_GENERAL_MATRIX_MATRIX_BLAS_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************************************************
+* This file implements general matrix-matrix multiplication using BLAS
+* gemm function via partial specialization of
+* general_matrix_matrix_product::run(..) method for float, double,
+* std::complex<float> and std::complex<double> types
+**********************************************************************/
+
+// gemm specialization
+
+#define GEMM_SPECIALIZATION(EIGTYPE, EIGPREFIX, BLASTYPE, BLASPREFIX) \
+template< \
+  typename Index, \
+  int LhsStorageOrder, bool ConjugateLhs, \
+  int RhsStorageOrder, bool ConjugateRhs> \
+struct general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor> \
+{ \
+typedef gebp_traits<EIGTYPE,EIGTYPE> Traits; \
+\
+static void run(Index rows, Index cols, Index depth, \
+  const EIGTYPE* _lhs, Index lhsStride, \
+  const EIGTYPE* _rhs, Index rhsStride, \
+  EIGTYPE* res, Index resStride, \
+  EIGTYPE alpha, \
+  level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/, \
+  GemmParallelInfo<Index>* /*info = 0*/) \
+{ \
+  using std::conj; \
+\
+  char transa, transb; \
+  BlasIndex m, n, k, lda, ldb, ldc; \
+  const EIGTYPE *a, *b; \
+  EIGTYPE beta(1); \
+  MatrixX##EIGPREFIX a_tmp, b_tmp; \
+\
+/* Set transpose options */ \
+  transa = (LhsStorageOrder==RowMajor) ? ((ConjugateLhs) ? 'C' : 'T') : 'N'; \
+  transb = (RhsStorageOrder==RowMajor) ? ((ConjugateRhs) ? 'C' : 'T') : 'N'; \
+\
+/* Set m, n, k */ \
+  m = convert_index<BlasIndex>(rows);  \
+  n = convert_index<BlasIndex>(cols);  \
+  k = convert_index<BlasIndex>(depth); \
+\
+/* Set lda, ldb, ldc */ \
+  lda = convert_index<BlasIndex>(lhsStride); \
+  ldb = convert_index<BlasIndex>(rhsStride); \
+  ldc = convert_index<BlasIndex>(resStride); \
+\
+/* Set a, b, c */ \
+  if ((LhsStorageOrder==ColMajor) && (ConjugateLhs)) { \
+    Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,m,k,OuterStride<>(lhsStride)); \
+    a_tmp = lhs.conjugate(); \
+    a = a_tmp.data(); \
+    lda = convert_index<BlasIndex>(a_tmp.outerStride()); \
+  } else a = _lhs; \
+\
+  if ((RhsStorageOrder==ColMajor) && (ConjugateRhs)) { \
+    Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,k,n,OuterStride<>(rhsStride)); \
+    b_tmp = rhs.conjugate(); \
+    b = b_tmp.data(); \
+    ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
+  } else b = _rhs; \
+\
+  BLASPREFIX##gemm_(&transa, &transb, &m, &n, &k, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
+}};
+
+GEMM_SPECIALIZATION(double,   d,  double, d)
+GEMM_SPECIALIZATION(float,    f,  float,  s)
+GEMM_SPECIALIZATION(dcomplex, cd, double, z)
+GEMM_SPECIALIZATION(scomplex, cf, float,  c)
+
+} // end namespase internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_GENERAL_MATRIX_MATRIX_BLAS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h
Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h
@@ -1,118 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   General matrix-matrix product functionality based on ?GEMM.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_GENERAL_MATRIX_MATRIX_MKL_H
-#define EIGEN_GENERAL_MATRIX_MATRIX_MKL_H
-
-namespace Eigen { 
-
-namespace internal {
-
-/**********************************************************************
-* This file implements general matrix-matrix multiplication using BLAS
-* gemm function via partial specialization of
-* general_matrix_matrix_product::run(..) method for float, double,
-* std::complex<float> and std::complex<double> types
-**********************************************************************/
-
-// gemm specialization
-
-#define GEMM_SPECIALIZATION(EIGTYPE, EIGPREFIX, MKLTYPE, MKLPREFIX) \
-template< \
-  typename Index, \
-  int LhsStorageOrder, bool ConjugateLhs, \
-  int RhsStorageOrder, bool ConjugateRhs> \
-struct general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor> \
-{ \
-static void run(Index rows, Index cols, Index depth, \
-  const EIGTYPE* _lhs, Index lhsStride, \
-  const EIGTYPE* _rhs, Index rhsStride, \
-  EIGTYPE* res, Index resStride, \
-  EIGTYPE alpha, \
-  level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/, \
-  GemmParallelInfo<Index>* /*info = 0*/) \
-{ \
-  using std::conj; \
-\
-  char transa, transb; \
-  MKL_INT m, n, k, lda, ldb, ldc; \
-  const EIGTYPE *a, *b; \
-  MKLTYPE alpha_, beta_; \
-  MatrixX##EIGPREFIX a_tmp, b_tmp; \
-  EIGTYPE myone(1);\
-\
-/* Set transpose options */ \
-  transa = (LhsStorageOrder==RowMajor) ? ((ConjugateLhs) ? 'C' : 'T') : 'N'; \
-  transb = (RhsStorageOrder==RowMajor) ? ((ConjugateRhs) ? 'C' : 'T') : 'N'; \
-\
-/* Set m, n, k */ \
-  m = (MKL_INT)rows;  \
-  n = (MKL_INT)cols;  \
-  k = (MKL_INT)depth; \
-\
-/* Set alpha_ & beta_ */ \
-  assign_scalar_eig2mkl(alpha_, alpha); \
-  assign_scalar_eig2mkl(beta_, myone); \
-\
-/* Set lda, ldb, ldc */ \
-  lda = (MKL_INT)lhsStride; \
-  ldb = (MKL_INT)rhsStride; \
-  ldc = (MKL_INT)resStride; \
-\
-/* Set a, b, c */ \
-  if ((LhsStorageOrder==ColMajor) && (ConjugateLhs)) { \
-    Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,m,k,OuterStride<>(lhsStride)); \
-    a_tmp = lhs.conjugate(); \
-    a = a_tmp.data(); \
-    lda = a_tmp.outerStride(); \
-  } else a = _lhs; \
-\
-  if ((RhsStorageOrder==ColMajor) && (ConjugateRhs)) { \
-    Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,k,n,OuterStride<>(rhsStride)); \
-    b_tmp = rhs.conjugate(); \
-    b = b_tmp.data(); \
-    ldb = b_tmp.outerStride(); \
-  } else b = _rhs; \
-\
-  MKLPREFIX##gemm(&transa, &transb, &m, &n, &k, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
-}};
-
-GEMM_SPECIALIZATION(double,   d,  double,        d)
-GEMM_SPECIALIZATION(float,    f,  float,         s)
-GEMM_SPECIALIZATION(dcomplex, cd, MKL_Complex16, z)
-GEMM_SPECIALIZATION(scomplex, cf, MKL_Complex8,  c)
-
-} // end namespase internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_GENERAL_MATRIX_MATRIX_MKL_H

Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector.h
@@ -8,11 +8,11 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERAL_MATRIX_VECTOR_H
 #define EIGEN_GENERAL_MATRIX_VECTOR_H
 
-namespace Eigen { 
+namespace Eigen {
 
 namespace internal {
 
 /* Optimized col-major matrix * vector product:
  * This algorithm processes 4 columns at onces that allows to both reduce
@@ -24,15 +24,43 @@
  *  |  A  |  B  |alpha| comments
  *  |real |cplx |cplx | no vectorization
  *  |real |cplx |real | alpha is converted to a cplx when calling the run function, no vectorization
  *  |cplx |real |cplx | invalid, the caller has to do tmp: = A * B; C += alpha*tmp
  *  |cplx |real |real | optimal case, vectorization possible via real-cplx mul
+ *
+ * Accesses to the matrix coefficients follow the following logic:
+ *
+ * - if all columns have the same alignment then
+ *   - if the columns have the same alignment as the result vector, then easy! (-> AllAligned case)
+ *   - otherwise perform unaligned loads only (-> NoneAligned case)
+ * - otherwise
+ *   - if even columns have the same alignment then
+ *     // odd columns are guaranteed to have the same alignment too
+ *     - if even or odd columns have the same alignment as the result, then
+ *       // for a register size of 2 scalars, this is guarantee to be the case (e.g., SSE with double)
+ *       - perform half aligned and half unaligned loads (-> EvenAligned case)
+ *     - otherwise perform unaligned loads only (-> NoneAligned case)
+ *   - otherwise, if the register size is 4 scalars (e.g., SSE with float) then
+ *     - one over 4 consecutive columns is guaranteed to be aligned with the result vector,
+ *       perform simple aligned loads for this column and aligned loads plus re-alignment for the other. (-> FirstAligned case)
+ *       // this re-alignment is done by the palign function implemented for SSE in Eigen/src/Core/arch/SSE/PacketMath.h
+ *   - otherwise,
+ *     // if we get here, this means the register size is greater than 4 (e.g., AVX with floats),
+ *     // we currently fall back to the NoneAligned case
+ *
+ * The same reasoning apply for the transposed case.
+ *
+ * The last case (PacketSize>4) could probably be improved by generalizing the FirstAligned case, but since we do not support AVX yet...
+ * One might also wonder why in the EvenAligned case we perform unaligned loads instead of using the aligned-loads plus re-alignment
+ * strategy as in the FirstAligned case. The reason is that we observed that unaligned loads on a 8 byte boundary are not too slow
+ * compared to unaligned loads on a 4 byte boundary.
+ *
  */
-template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
-struct general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>
+template<typename Index, typename LhsScalar, typename LhsMapper, bool ConjugateLhs, typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version>
+struct general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjugateLhs,RhsScalar,RhsMapper,ConjugateRhs,Version>
 {
-typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
 
 enum {
   Vectorizable = packet_traits<LhsScalar>::Vectorizable && packet_traits<RhsScalar>::Vectorizable
               && int(packet_traits<LhsScalar>::size)==int(packet_traits<RhsScalar>::size),
   LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1,
@@ -48,35 +76,39 @@
 typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
 typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
 
 EIGEN_DONT_INLINE static void run(
   Index rows, Index cols,
-  const LhsScalar* lhs, Index lhsStride,
-  const RhsScalar* rhs, Index rhsIncr,
-  ResScalar* res, Index resIncr, RhsScalar alpha);
+  const LhsMapper& lhs,
+  const RhsMapper& rhs,
+        ResScalar* res, Index resIncr,
+  RhsScalar alpha);
 };
 
-template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
-EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>::run(
+template<typename Index, typename LhsScalar, typename LhsMapper, bool ConjugateLhs, typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version>
+EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjugateLhs,RhsScalar,RhsMapper,ConjugateRhs,Version>::run(
   Index rows, Index cols,
-  const LhsScalar* lhs, Index lhsStride,
-  const RhsScalar* rhs, Index rhsIncr,
-  ResScalar* res, Index resIncr, RhsScalar alpha)
+  const LhsMapper& lhs,
+  const RhsMapper& rhs,
+        ResScalar* res, Index resIncr,
+  RhsScalar alpha)
 {
-  EIGEN_UNUSED_VARIABLE(resIncr)
+  EIGEN_UNUSED_VARIABLE(resIncr);
   eigen_internal_assert(resIncr==1);
   #ifdef _EIGEN_ACCUMULATE_PACKETS
   #error _EIGEN_ACCUMULATE_PACKETS has already been defined
   #endif
-  #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2) \
+  #define _EIGEN_ACCUMULATE_PACKETS(Alignment0,Alignment13,Alignment2) \
     pstore(&res[j], \
       padd(pload<ResPacket>(&res[j]), \
         padd( \
-          padd(pcj.pmul(EIGEN_CAT(ploa , A0)<LhsPacket>(&lhs0[j]),    ptmp0), \
-                  pcj.pmul(EIGEN_CAT(ploa , A13)<LhsPacket>(&lhs1[j]),   ptmp1)), \
-          padd(pcj.pmul(EIGEN_CAT(ploa , A2)<LhsPacket>(&lhs2[j]),    ptmp2), \
-                  pcj.pmul(EIGEN_CAT(ploa , A13)<LhsPacket>(&lhs3[j]),   ptmp3)) )))
+      padd(pcj.pmul(lhs0.template load<LhsPacket, Alignment0>(j),    ptmp0), \
+      pcj.pmul(lhs1.template load<LhsPacket, Alignment13>(j),   ptmp1)),   \
+      padd(pcj.pmul(lhs2.template load<LhsPacket, Alignment2>(j),    ptmp2), \
+      pcj.pmul(lhs3.template load<LhsPacket, Alignment13>(j),   ptmp3)) )))
+
+  typedef typename LhsMapper::VectorMapper LhsScalars;
 
   conj_helper<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> cj;
   conj_helper<LhsPacket,RhsPacket,ConjugateLhs,ConjugateRhs> pcj;
   if(ConjugateRhs)
     alpha = numext::conj(alpha);
@@ -86,36 +118,45 @@
   const Index peels = 2;
   const Index LhsPacketAlignedMask = LhsPacketSize-1;
   const Index ResPacketAlignedMask = ResPacketSize-1;
 //  const Index PeelAlignedMask = ResPacketSize*peels-1;
   const Index size = rows;
-  
+
+  const Index lhsStride = lhs.stride();
+
   // How many coeffs of the result do we have to skip to be aligned.
   // Here we assume data are at least aligned on the base scalar type.
-  Index alignedStart = internal::first_aligned(res,size);
+  Index alignedStart = internal::first_default_aligned(res,size);
   Index alignedSize = ResPacketSize>1 ? alignedStart + ((size-alignedStart) & ~ResPacketAlignedMask) : 0;
   const Index peeledSize = alignedSize - RhsPacketSize*peels - RhsPacketSize + 1;
 
   const Index alignmentStep = LhsPacketSize>1 ? (LhsPacketSize - lhsStride % LhsPacketSize) & LhsPacketAlignedMask : 0;
   Index alignmentPattern = alignmentStep==0 ? AllAligned
                        : alignmentStep==(LhsPacketSize/2) ? EvenAligned
                        : FirstAligned;
 
   // we cannot assume the first element is aligned because of sub-matrices
-  const Index lhsAlignmentOffset = internal::first_aligned(lhs,size);
+  const Index lhsAlignmentOffset = lhs.firstAligned(size);
 
   // find how many columns do we have to skip to be aligned with the result (if possible)
   Index skipColumns = 0;
   // if the data cannot be aligned (TODO add some compile time tests when possible, e.g. for floats)
-  if( (size_t(lhs)%sizeof(LhsScalar)) || (size_t(res)%sizeof(ResScalar)) )
+  if( (lhsAlignmentOffset < 0) || (lhsAlignmentOffset == size) || (UIntPtr(res)%sizeof(ResScalar)) )
   {
     alignedSize = 0;
     alignedStart = 0;
+    alignmentPattern = NoneAligned;
+  }
+  else if(LhsPacketSize > 4)
+  {
+    // TODO: extend the code to support aligned loads whenever possible when LhsPacketSize > 4.
+    // Currently, it seems to be better to perform unaligned loads anyway
+    alignmentPattern = NoneAligned;
   }
   else if (LhsPacketSize>1)
   {
-    eigen_internal_assert(size_t(lhs+lhsAlignmentOffset)%sizeof(LhsPacket)==0 || size<LhsPacketSize);
+  //    eigen_internal_assert(size_t(firstLhs+lhsAlignmentOffset)%sizeof(LhsPacket)==0 || size<LhsPacketSize);
 
     while (skipColumns<LhsPacketSize &&
           alignedStart != ((lhsAlignmentOffset + alignmentStep*skipColumns)%LhsPacketSize))
       ++skipColumns;
     if (skipColumns==LhsPacketSize)
@@ -128,116 +169,116 @@
     {
       skipColumns = (std::min)(skipColumns,cols);
       // note that the skiped columns are processed later.
     }
 
-    eigen_internal_assert(  (alignmentPattern==NoneAligned)
+    /*    eigen_internal_assert(  (alignmentPattern==NoneAligned)
                       || (skipColumns + columnsAtOnce >= cols)
                       || LhsPacketSize > size
-                      || (size_t(lhs+alignedStart+lhsStride*skipColumns)%sizeof(LhsPacket))==0);
+                      || (size_t(firstLhs+alignedStart+lhsStride*skipColumns)%sizeof(LhsPacket))==0);*/
   }
   else if(Vectorizable)
   {
     alignedStart = 0;
     alignedSize = size;
     alignmentPattern = AllAligned;
   }
 
-  Index offset1 = (FirstAligned && alignmentStep==1?3:1);
-  Index offset3 = (FirstAligned && alignmentStep==1?1:3);
+  const Index offset1 = (FirstAligned && alignmentStep==1)?3:1;
+  const Index offset3 = (FirstAligned && alignmentStep==1)?1:3;
 
   Index columnBound = ((cols-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns;
   for (Index i=skipColumns; i<columnBound; i+=columnsAtOnce)
   {
-    RhsPacket ptmp0 = pset1<RhsPacket>(alpha*rhs[i*rhsIncr]),
-              ptmp1 = pset1<RhsPacket>(alpha*rhs[(i+offset1)*rhsIncr]),
-              ptmp2 = pset1<RhsPacket>(alpha*rhs[(i+2)*rhsIncr]),
-              ptmp3 = pset1<RhsPacket>(alpha*rhs[(i+offset3)*rhsIncr]);
+    RhsPacket ptmp0 = pset1<RhsPacket>(alpha*rhs(i, 0)),
+              ptmp1 = pset1<RhsPacket>(alpha*rhs(i+offset1, 0)),
+              ptmp2 = pset1<RhsPacket>(alpha*rhs(i+2, 0)),
+              ptmp3 = pset1<RhsPacket>(alpha*rhs(i+offset3, 0));
 
     // this helps a lot generating better binary code
-    const LhsScalar *lhs0 = lhs + i*lhsStride,     *lhs1 = lhs + (i+offset1)*lhsStride,
-                    *lhs2 = lhs + (i+2)*lhsStride, *lhs3 = lhs + (i+offset3)*lhsStride;
+    const LhsScalars lhs0 = lhs.getVectorMapper(0, i+0),   lhs1 = lhs.getVectorMapper(0, i+offset1),
+                     lhs2 = lhs.getVectorMapper(0, i+2),   lhs3 = lhs.getVectorMapper(0, i+offset3);
 
     if (Vectorizable)
     {
       /* explicit vectorization */
       // process initial unaligned coeffs
       for (Index j=0; j<alignedStart; ++j)
       {
-        res[j] = cj.pmadd(lhs0[j], pfirst(ptmp0), res[j]);
-        res[j] = cj.pmadd(lhs1[j], pfirst(ptmp1), res[j]);
-        res[j] = cj.pmadd(lhs2[j], pfirst(ptmp2), res[j]);
-        res[j] = cj.pmadd(lhs3[j], pfirst(ptmp3), res[j]);
+        res[j] = cj.pmadd(lhs0(j), pfirst(ptmp0), res[j]);
+        res[j] = cj.pmadd(lhs1(j), pfirst(ptmp1), res[j]);
+        res[j] = cj.pmadd(lhs2(j), pfirst(ptmp2), res[j]);
+        res[j] = cj.pmadd(lhs3(j), pfirst(ptmp3), res[j]);
       }
 
       if (alignedSize>alignedStart)
       {
         switch(alignmentPattern)
         {
           case AllAligned:
             for (Index j = alignedStart; j<alignedSize; j+=ResPacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,d,d);
+              _EIGEN_ACCUMULATE_PACKETS(Aligned,Aligned,Aligned);
             break;
           case EvenAligned:
             for (Index j = alignedStart; j<alignedSize; j+=ResPacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,du,d);
+              _EIGEN_ACCUMULATE_PACKETS(Aligned,Unaligned,Aligned);
             break;
           case FirstAligned:
           {
             Index j = alignedStart;
             if(peels>1)
             {
               LhsPacket A00, A01, A02, A03, A10, A11, A12, A13;
               ResPacket T0, T1;
 
-              A01 = pload<LhsPacket>(&lhs1[alignedStart-1]);
-              A02 = pload<LhsPacket>(&lhs2[alignedStart-2]);
-              A03 = pload<LhsPacket>(&lhs3[alignedStart-3]);
+              A01 = lhs1.template load<LhsPacket, Aligned>(alignedStart-1);
+              A02 = lhs2.template load<LhsPacket, Aligned>(alignedStart-2);
+              A03 = lhs3.template load<LhsPacket, Aligned>(alignedStart-3);
 
               for (; j<peeledSize; j+=peels*ResPacketSize)
               {
-                A11 = pload<LhsPacket>(&lhs1[j-1+LhsPacketSize]);  palign<1>(A01,A11);
-                A12 = pload<LhsPacket>(&lhs2[j-2+LhsPacketSize]);  palign<2>(A02,A12);
-                A13 = pload<LhsPacket>(&lhs3[j-3+LhsPacketSize]);  palign<3>(A03,A13);
+                A11 = lhs1.template load<LhsPacket, Aligned>(j-1+LhsPacketSize);  palign<1>(A01,A11);
+                A12 = lhs2.template load<LhsPacket, Aligned>(j-2+LhsPacketSize);  palign<2>(A02,A12);
+                A13 = lhs3.template load<LhsPacket, Aligned>(j-3+LhsPacketSize);  palign<3>(A03,A13);
 
-                A00 = pload<LhsPacket>(&lhs0[j]);
-                A10 = pload<LhsPacket>(&lhs0[j+LhsPacketSize]);
+                A00 = lhs0.template load<LhsPacket, Aligned>(j);
+                A10 = lhs0.template load<LhsPacket, Aligned>(j+LhsPacketSize);
                 T0  = pcj.pmadd(A00, ptmp0, pload<ResPacket>(&res[j]));
                 T1  = pcj.pmadd(A10, ptmp0, pload<ResPacket>(&res[j+ResPacketSize]));
 
                 T0  = pcj.pmadd(A01, ptmp1, T0);
-                A01 = pload<LhsPacket>(&lhs1[j-1+2*LhsPacketSize]);  palign<1>(A11,A01);
+                A01 = lhs1.template load<LhsPacket, Aligned>(j-1+2*LhsPacketSize);  palign<1>(A11,A01);
                 T0  = pcj.pmadd(A02, ptmp2, T0);
-                A02 = pload<LhsPacket>(&lhs2[j-2+2*LhsPacketSize]);  palign<2>(A12,A02);
+                A02 = lhs2.template load<LhsPacket, Aligned>(j-2+2*LhsPacketSize);  palign<2>(A12,A02);
                 T0  = pcj.pmadd(A03, ptmp3, T0);
                 pstore(&res[j],T0);
-                A03 = pload<LhsPacket>(&lhs3[j-3+2*LhsPacketSize]);  palign<3>(A13,A03);
+                A03 = lhs3.template load<LhsPacket, Aligned>(j-3+2*LhsPacketSize);  palign<3>(A13,A03);
                 T1  = pcj.pmadd(A11, ptmp1, T1);
                 T1  = pcj.pmadd(A12, ptmp2, T1);
                 T1  = pcj.pmadd(A13, ptmp3, T1);
                 pstore(&res[j+ResPacketSize],T1);
               }
             }
             for (; j<alignedSize; j+=ResPacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,du,du);
+              _EIGEN_ACCUMULATE_PACKETS(Aligned,Unaligned,Unaligned);
             break;
           }
           default:
             for (Index j = alignedStart; j<alignedSize; j+=ResPacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(du,du,du);
+              _EIGEN_ACCUMULATE_PACKETS(Unaligned,Unaligned,Unaligned);
             break;
         }
       }
     } // end explicit vectorization
 
     /* process remaining coeffs (or all if there is no explicit vectorization) */
     for (Index j=alignedSize; j<size; ++j)
     {
-      res[j] = cj.pmadd(lhs0[j], pfirst(ptmp0), res[j]);
-      res[j] = cj.pmadd(lhs1[j], pfirst(ptmp1), res[j]);
-      res[j] = cj.pmadd(lhs2[j], pfirst(ptmp2), res[j]);
-      res[j] = cj.pmadd(lhs3[j], pfirst(ptmp3), res[j]);
+      res[j] = cj.pmadd(lhs0(j), pfirst(ptmp0), res[j]);
+      res[j] = cj.pmadd(lhs1(j), pfirst(ptmp1), res[j]);
+      res[j] = cj.pmadd(lhs2(j), pfirst(ptmp2), res[j]);
+      res[j] = cj.pmadd(lhs3(j), pfirst(ptmp3), res[j]);
     }
   }
 
   // process remaining first and last columns (at most columnsAtOnce-1)
   Index end = cols;
@@ -244,31 +285,31 @@
   Index start = columnBound;
   do
   {
     for (Index k=start; k<end; ++k)
     {
-      RhsPacket ptmp0 = pset1<RhsPacket>(alpha*rhs[k*rhsIncr]);
-      const LhsScalar* lhs0 = lhs + k*lhsStride;
+      RhsPacket ptmp0 = pset1<RhsPacket>(alpha*rhs(k, 0));
+      const LhsScalars lhs0 = lhs.getVectorMapper(0, k);
 
       if (Vectorizable)
       {
         /* explicit vectorization */
         // process first unaligned result's coeffs
         for (Index j=0; j<alignedStart; ++j)
-          res[j] += cj.pmul(lhs0[j], pfirst(ptmp0));
+          res[j] += cj.pmul(lhs0(j), pfirst(ptmp0));
         // process aligned result's coeffs
-        if ((size_t(lhs0+alignedStart)%sizeof(LhsPacket))==0)
+        if (lhs0.template aligned<LhsPacket>(alignedStart))
           for (Index i = alignedStart;i<alignedSize;i+=ResPacketSize)
-            pstore(&res[i], pcj.pmadd(pload<LhsPacket>(&lhs0[i]), ptmp0, pload<ResPacket>(&res[i])));
+            pstore(&res[i], pcj.pmadd(lhs0.template load<LhsPacket, Aligned>(i), ptmp0, pload<ResPacket>(&res[i])));
         else
           for (Index i = alignedStart;i<alignedSize;i+=ResPacketSize)
-            pstore(&res[i], pcj.pmadd(ploadu<LhsPacket>(&lhs0[i]), ptmp0, pload<ResPacket>(&res[i])));
+            pstore(&res[i], pcj.pmadd(lhs0.template load<LhsPacket, Unaligned>(i), ptmp0, pload<ResPacket>(&res[i])));
       }
 
       // process remaining scalars (or all if no explicit vectorization)
       for (Index i=alignedSize; i<size; ++i)
-        res[i] += cj.pmul(lhs0[i], pfirst(ptmp0));
+        res[i] += cj.pmul(lhs0(i), pfirst(ptmp0));
     }
     if (skipColumns)
     {
       start = 0;
       end = skipColumns;
@@ -288,14 +329,14 @@
  *
  * Mixing type logic:
  *  - alpha is always a complex (or converted to a complex)
  *  - no vectorization
  */
-template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
-struct general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>
+template<typename Index, typename LhsScalar, typename LhsMapper, bool ConjugateLhs, typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version>
+struct general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjugateLhs,RhsScalar,RhsMapper,ConjugateRhs,Version>
 {
-typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
 
 enum {
   Vectorizable = packet_traits<LhsScalar>::Vectorizable && packet_traits<RhsScalar>::Vectorizable
               && int(packet_traits<LhsScalar>::size)==int(packet_traits<RhsScalar>::size),
   LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1,
@@ -308,77 +349,88 @@
 typedef typename packet_traits<ResScalar>::type  _ResPacket;
 
 typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket;
 typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
 typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
-  
+
 EIGEN_DONT_INLINE static void run(
   Index rows, Index cols,
-  const LhsScalar* lhs, Index lhsStride,
-  const RhsScalar* rhs, Index rhsIncr,
-  ResScalar* res, Index resIncr,
+  const LhsMapper& lhs,
+  const RhsMapper& rhs,
+        ResScalar* res, Index resIncr,
   ResScalar alpha);
 };
 
-template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
-EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>::run(
+template<typename Index, typename LhsScalar, typename LhsMapper, bool ConjugateLhs, typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version>
+EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjugateLhs,RhsScalar,RhsMapper,ConjugateRhs,Version>::run(
   Index rows, Index cols,
-  const LhsScalar* lhs, Index lhsStride,
-  const RhsScalar* rhs, Index rhsIncr,
+  const LhsMapper& lhs,
+  const RhsMapper& rhs,
   ResScalar* res, Index resIncr,
   ResScalar alpha)
 {
-  EIGEN_UNUSED_VARIABLE(rhsIncr);
-  eigen_internal_assert(rhsIncr==1);
+  eigen_internal_assert(rhs.stride()==1);
+
   #ifdef _EIGEN_ACCUMULATE_PACKETS
   #error _EIGEN_ACCUMULATE_PACKETS has already been defined
   #endif
 
-  #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2) {\
-    RhsPacket b = pload<RhsPacket>(&rhs[j]); \
-    ptmp0 = pcj.pmadd(EIGEN_CAT(ploa,A0) <LhsPacket>(&lhs0[j]), b, ptmp0); \
-    ptmp1 = pcj.pmadd(EIGEN_CAT(ploa,A13)<LhsPacket>(&lhs1[j]), b, ptmp1); \
-    ptmp2 = pcj.pmadd(EIGEN_CAT(ploa,A2) <LhsPacket>(&lhs2[j]), b, ptmp2); \
-    ptmp3 = pcj.pmadd(EIGEN_CAT(ploa,A13)<LhsPacket>(&lhs3[j]), b, ptmp3); }
+  #define _EIGEN_ACCUMULATE_PACKETS(Alignment0,Alignment13,Alignment2) {\
+    RhsPacket b = rhs.getVectorMapper(j, 0).template load<RhsPacket, Aligned>(0);  \
+    ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Alignment0>(j), b, ptmp0); \
+    ptmp1 = pcj.pmadd(lhs1.template load<LhsPacket, Alignment13>(j), b, ptmp1); \
+    ptmp2 = pcj.pmadd(lhs2.template load<LhsPacket, Alignment2>(j), b, ptmp2); \
+    ptmp3 = pcj.pmadd(lhs3.template load<LhsPacket, Alignment13>(j), b, ptmp3); }
 
   conj_helper<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> cj;
   conj_helper<LhsPacket,RhsPacket,ConjugateLhs,ConjugateRhs> pcj;
+
+  typedef typename LhsMapper::VectorMapper LhsScalars;
 
   enum { AllAligned=0, EvenAligned=1, FirstAligned=2, NoneAligned=3 };
   const Index rowsAtOnce = 4;
   const Index peels = 2;
   const Index RhsPacketAlignedMask = RhsPacketSize-1;
   const Index LhsPacketAlignedMask = LhsPacketSize-1;
-//   const Index PeelAlignedMask = RhsPacketSize*peels-1;
   const Index depth = cols;
+  const Index lhsStride = lhs.stride();
 
   // How many coeffs of the result do we have to skip to be aligned.
   // Here we assume data are at least aligned on the base scalar type
   // if that's not the case then vectorization is discarded, see below.
-  Index alignedStart = internal::first_aligned(rhs, depth);
+  Index alignedStart = rhs.firstAligned(depth);
   Index alignedSize = RhsPacketSize>1 ? alignedStart + ((depth-alignedStart) & ~RhsPacketAlignedMask) : 0;
   const Index peeledSize = alignedSize - RhsPacketSize*peels - RhsPacketSize + 1;
 
   const Index alignmentStep = LhsPacketSize>1 ? (LhsPacketSize - lhsStride % LhsPacketSize) & LhsPacketAlignedMask : 0;
   Index alignmentPattern = alignmentStep==0 ? AllAligned
-                         : alignmentStep==(LhsPacketSize/2) ? EvenAligned
-                         : FirstAligned;
+                           : alignmentStep==(LhsPacketSize/2) ? EvenAligned
+                           : FirstAligned;
 
   // we cannot assume the first element is aligned because of sub-matrices
-  const Index lhsAlignmentOffset = internal::first_aligned(lhs,depth);
+  const Index lhsAlignmentOffset = lhs.firstAligned(depth);
+  const Index rhsAlignmentOffset = rhs.firstAligned(rows);
 
   // find how many rows do we have to skip to be aligned with rhs (if possible)
   Index skipRows = 0;
   // if the data cannot be aligned (TODO add some compile time tests when possible, e.g. for floats)
-  if( (sizeof(LhsScalar)!=sizeof(RhsScalar)) || (size_t(lhs)%sizeof(LhsScalar)) || (size_t(rhs)%sizeof(RhsScalar)) )
+  if( (sizeof(LhsScalar)!=sizeof(RhsScalar)) ||
+      (lhsAlignmentOffset < 0) || (lhsAlignmentOffset == depth) ||
+      (rhsAlignmentOffset < 0) || (rhsAlignmentOffset == rows) )
   {
     alignedSize = 0;
     alignedStart = 0;
+    alignmentPattern = NoneAligned;
+  }
+  else if(LhsPacketSize > 4)
+  {
+    // TODO: extend the code to support aligned loads whenever possible when LhsPacketSize > 4.
+    alignmentPattern = NoneAligned;
   }
   else if (LhsPacketSize>1)
   {
-    eigen_internal_assert(size_t(lhs+lhsAlignmentOffset)%sizeof(LhsPacket)==0  || depth<LhsPacketSize);
+  //    eigen_internal_assert(size_t(firstLhs+lhsAlignmentOffset)%sizeof(LhsPacket)==0  || depth<LhsPacketSize);
 
     while (skipRows<LhsPacketSize &&
            alignedStart != ((lhsAlignmentOffset + alignmentStep*skipRows)%LhsPacketSize))
       ++skipRows;
     if (skipRows==LhsPacketSize)
@@ -390,35 +442,36 @@
     else
     {
       skipRows = (std::min)(skipRows,Index(rows));
       // note that the skiped columns are processed later.
     }
-    eigen_internal_assert(  alignmentPattern==NoneAligned
+    /*    eigen_internal_assert(  alignmentPattern==NoneAligned
                       || LhsPacketSize==1
                       || (skipRows + rowsAtOnce >= rows)
                       || LhsPacketSize > depth
-                      || (size_t(lhs+alignedStart+lhsStride*skipRows)%sizeof(LhsPacket))==0);
+                      || (size_t(firstLhs+alignedStart+lhsStride*skipRows)%sizeof(LhsPacket))==0);*/
   }
   else if(Vectorizable)
   {
     alignedStart = 0;
     alignedSize = depth;
     alignmentPattern = AllAligned;
   }
 
-  Index offset1 = (FirstAligned && alignmentStep==1?3:1);
-  Index offset3 = (FirstAligned && alignmentStep==1?1:3);
+  const Index offset1 = (FirstAligned && alignmentStep==1)?3:1;
+  const Index offset3 = (FirstAligned && alignmentStep==1)?1:3;
 
   Index rowBound = ((rows-skipRows)/rowsAtOnce)*rowsAtOnce + skipRows;
   for (Index i=skipRows; i<rowBound; i+=rowsAtOnce)
   {
-    EIGEN_ALIGN16 ResScalar tmp0 = ResScalar(0);
+    // FIXME: what is the purpose of this EIGEN_ALIGN_DEFAULT ??
+    EIGEN_ALIGN_MAX ResScalar tmp0 = ResScalar(0);
     ResScalar tmp1 = ResScalar(0), tmp2 = ResScalar(0), tmp3 = ResScalar(0);
 
     // this helps the compiler generating good binary code
-    const LhsScalar *lhs0 = lhs + i*lhsStride,     *lhs1 = lhs + (i+offset1)*lhsStride,
-                    *lhs2 = lhs + (i+2)*lhsStride, *lhs3 = lhs + (i+offset3)*lhsStride;
+    const LhsScalars lhs0 = lhs.getVectorMapper(i+0, 0),    lhs1 = lhs.getVectorMapper(i+offset1, 0),
+                     lhs2 = lhs.getVectorMapper(i+2, 0),    lhs3 = lhs.getVectorMapper(i+offset3, 0);
 
     if (Vectorizable)
     {
       /* explicit vectorization */
       ResPacket ptmp0 = pset1<ResPacket>(ResScalar(0)), ptmp1 = pset1<ResPacket>(ResScalar(0)),
@@ -426,26 +479,26 @@
 
       // process initial unaligned coeffs
       // FIXME this loop get vectorized by the compiler !
       for (Index j=0; j<alignedStart; ++j)
       {
-        RhsScalar b = rhs[j];
-        tmp0 += cj.pmul(lhs0[j],b); tmp1 += cj.pmul(lhs1[j],b);
-        tmp2 += cj.pmul(lhs2[j],b); tmp3 += cj.pmul(lhs3[j],b);
+        RhsScalar b = rhs(j, 0);
+        tmp0 += cj.pmul(lhs0(j),b); tmp1 += cj.pmul(lhs1(j),b);
+        tmp2 += cj.pmul(lhs2(j),b); tmp3 += cj.pmul(lhs3(j),b);
       }
 
       if (alignedSize>alignedStart)
       {
         switch(alignmentPattern)
         {
           case AllAligned:
             for (Index j = alignedStart; j<alignedSize; j+=RhsPacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,d,d);
+              _EIGEN_ACCUMULATE_PACKETS(Aligned,Aligned,Aligned);
             break;
           case EvenAligned:
             for (Index j = alignedStart; j<alignedSize; j+=RhsPacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,du,d);
+              _EIGEN_ACCUMULATE_PACKETS(Aligned,Unaligned,Aligned);
             break;
           case FirstAligned:
           {
             Index j = alignedStart;
             if (peels>1)
@@ -455,43 +508,43 @@
                * using special shift/move operations between the two aligned packets
                * overlaping the desired unaligned packet. This is *much* more efficient
                * than basic unaligned loads.
                */
               LhsPacket A01, A02, A03, A11, A12, A13;
-              A01 = pload<LhsPacket>(&lhs1[alignedStart-1]);
-              A02 = pload<LhsPacket>(&lhs2[alignedStart-2]);
-              A03 = pload<LhsPacket>(&lhs3[alignedStart-3]);
+              A01 = lhs1.template load<LhsPacket, Aligned>(alignedStart-1);
+              A02 = lhs2.template load<LhsPacket, Aligned>(alignedStart-2);
+              A03 = lhs3.template load<LhsPacket, Aligned>(alignedStart-3);
 
               for (; j<peeledSize; j+=peels*RhsPacketSize)
               {
-                RhsPacket b = pload<RhsPacket>(&rhs[j]);
-                A11 = pload<LhsPacket>(&lhs1[j-1+LhsPacketSize]);  palign<1>(A01,A11);
-                A12 = pload<LhsPacket>(&lhs2[j-2+LhsPacketSize]);  palign<2>(A02,A12);
-                A13 = pload<LhsPacket>(&lhs3[j-3+LhsPacketSize]);  palign<3>(A03,A13);
+                RhsPacket b = rhs.getVectorMapper(j, 0).template load<RhsPacket, Aligned>(0);
+                A11 = lhs1.template load<LhsPacket, Aligned>(j-1+LhsPacketSize);  palign<1>(A01,A11);
+                A12 = lhs2.template load<LhsPacket, Aligned>(j-2+LhsPacketSize);  palign<2>(A02,A12);
+                A13 = lhs3.template load<LhsPacket, Aligned>(j-3+LhsPacketSize);  palign<3>(A03,A13);
 
-                ptmp0 = pcj.pmadd(pload<LhsPacket>(&lhs0[j]), b, ptmp0);
+                ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Aligned>(j), b, ptmp0);
                 ptmp1 = pcj.pmadd(A01, b, ptmp1);
-                A01 = pload<LhsPacket>(&lhs1[j-1+2*LhsPacketSize]);  palign<1>(A11,A01);
+                A01 = lhs1.template load<LhsPacket, Aligned>(j-1+2*LhsPacketSize);  palign<1>(A11,A01);
                 ptmp2 = pcj.pmadd(A02, b, ptmp2);
-                A02 = pload<LhsPacket>(&lhs2[j-2+2*LhsPacketSize]);  palign<2>(A12,A02);
+                A02 = lhs2.template load<LhsPacket, Aligned>(j-2+2*LhsPacketSize);  palign<2>(A12,A02);
                 ptmp3 = pcj.pmadd(A03, b, ptmp3);
-                A03 = pload<LhsPacket>(&lhs3[j-3+2*LhsPacketSize]);  palign<3>(A13,A03);
+                A03 = lhs3.template load<LhsPacket, Aligned>(j-3+2*LhsPacketSize);  palign<3>(A13,A03);
 
-                b = pload<RhsPacket>(&rhs[j+RhsPacketSize]);
-                ptmp0 = pcj.pmadd(pload<LhsPacket>(&lhs0[j+LhsPacketSize]), b, ptmp0);
+                b = rhs.getVectorMapper(j+RhsPacketSize, 0).template load<RhsPacket, Aligned>(0);
+                ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Aligned>(j+LhsPacketSize), b, ptmp0);
                 ptmp1 = pcj.pmadd(A11, b, ptmp1);
                 ptmp2 = pcj.pmadd(A12, b, ptmp2);
                 ptmp3 = pcj.pmadd(A13, b, ptmp3);
               }
             }
             for (; j<alignedSize; j+=RhsPacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,du,du);
+              _EIGEN_ACCUMULATE_PACKETS(Aligned,Unaligned,Unaligned);
             break;
           }
           default:
             for (Index j = alignedStart; j<alignedSize; j+=RhsPacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(du,du,du);
+              _EIGEN_ACCUMULATE_PACKETS(Unaligned,Unaligned,Unaligned);
             break;
         }
         tmp0 += predux(ptmp0);
         tmp1 += predux(ptmp1);
         tmp2 += predux(ptmp2);
@@ -501,13 +554,13 @@
 
     // process remaining coeffs (or all if no explicit vectorization)
     // FIXME this loop get vectorized by the compiler !
     for (Index j=alignedSize; j<depth; ++j)
     {
-      RhsScalar b = rhs[j];
-      tmp0 += cj.pmul(lhs0[j],b); tmp1 += cj.pmul(lhs1[j],b);
-      tmp2 += cj.pmul(lhs2[j],b); tmp3 += cj.pmul(lhs3[j],b);
+      RhsScalar b = rhs(j, 0);
+      tmp0 += cj.pmul(lhs0(j),b); tmp1 += cj.pmul(lhs1(j),b);
+      tmp2 += cj.pmul(lhs2(j),b); tmp3 += cj.pmul(lhs3(j),b);
     }
     res[i*resIncr]            += alpha*tmp0;
     res[(i+offset1)*resIncr]  += alpha*tmp1;
     res[(i+2)*resIncr]        += alpha*tmp2;
     res[(i+offset3)*resIncr]  += alpha*tmp3;
@@ -518,34 +571,34 @@
   Index start = rowBound;
   do
   {
     for (Index i=start; i<end; ++i)
     {
-      EIGEN_ALIGN16 ResScalar tmp0 = ResScalar(0);
+      EIGEN_ALIGN_MAX ResScalar tmp0 = ResScalar(0);
       ResPacket ptmp0 = pset1<ResPacket>(tmp0);
-      const LhsScalar* lhs0 = lhs + i*lhsStride;
+      const LhsScalars lhs0 = lhs.getVectorMapper(i, 0);
       // process first unaligned result's coeffs
       // FIXME this loop get vectorized by the compiler !
       for (Index j=0; j<alignedStart; ++j)
-        tmp0 += cj.pmul(lhs0[j], rhs[j]);
+        tmp0 += cj.pmul(lhs0(j), rhs(j, 0));
 
       if (alignedSize>alignedStart)
       {
         // process aligned rhs coeffs
-        if ((size_t(lhs0+alignedStart)%sizeof(LhsPacket))==0)
+        if (lhs0.template aligned<LhsPacket>(alignedStart))
           for (Index j = alignedStart;j<alignedSize;j+=RhsPacketSize)
-            ptmp0 = pcj.pmadd(pload<LhsPacket>(&lhs0[j]), pload<RhsPacket>(&rhs[j]), ptmp0);
+            ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Aligned>(j), rhs.getVectorMapper(j, 0).template load<RhsPacket, Aligned>(0), ptmp0);
         else
           for (Index j = alignedStart;j<alignedSize;j+=RhsPacketSize)
-            ptmp0 = pcj.pmadd(ploadu<LhsPacket>(&lhs0[j]), pload<RhsPacket>(&rhs[j]), ptmp0);
+            ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Unaligned>(j), rhs.getVectorMapper(j, 0).template load<RhsPacket, Aligned>(0), ptmp0);
         tmp0 += predux(ptmp0);
       }
 
       // process remaining scalars
       // FIXME this loop get vectorized by the compiler !
       for (Index j=alignedSize; j<depth; ++j)
-        tmp0 += cj.pmul(lhs0[j], rhs[j]);
+        tmp0 += cj.pmul(lhs0(j), rhs(j, 0));
       res[i*resIncr] += alpha*tmp0;
     }
     if (skipRows)
     {
       start = 0;

ADDED   3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector_BLAS.h
Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector_BLAS.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector_BLAS.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector_BLAS.h
@@ -0,0 +1,129 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to BLAS F77
+ *   General matrix-vector product functionality based on ?GEMV.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_GENERAL_MATRIX_VECTOR_BLAS_H
+#define EIGEN_GENERAL_MATRIX_VECTOR_BLAS_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************************************************
+* This file implements general matrix-vector multiplication using BLAS
+* gemv function via partial specialization of
+* general_matrix_vector_product::run(..) method for float, double,
+* std::complex<float> and std::complex<double> types
+**********************************************************************/
+
+// gemv specialization
+
+template<typename Index, typename LhsScalar, int StorageOrder, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs>
+struct general_matrix_vector_product_gemv;
+
+#define EIGEN_BLAS_GEMV_SPECIALIZE(Scalar) \
+template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
+struct general_matrix_vector_product<Index,Scalar,const_blas_data_mapper<Scalar,Index,ColMajor>,ColMajor,ConjugateLhs,Scalar,const_blas_data_mapper<Scalar,Index,RowMajor>,ConjugateRhs,Specialized> { \
+static void run( \
+  Index rows, Index cols, \
+  const const_blas_data_mapper<Scalar,Index,ColMajor> &lhs, \
+  const const_blas_data_mapper<Scalar,Index,RowMajor> &rhs, \
+  Scalar* res, Index resIncr, Scalar alpha) \
+{ \
+  if (ConjugateLhs) { \
+    general_matrix_vector_product<Index,Scalar,const_blas_data_mapper<Scalar,Index,ColMajor>,ColMajor,ConjugateLhs,Scalar,const_blas_data_mapper<Scalar,Index,RowMajor>,ConjugateRhs,BuiltIn>::run( \
+      rows, cols, lhs, rhs, res, resIncr, alpha); \
+  } else { \
+    general_matrix_vector_product_gemv<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs>::run( \
+      rows, cols, lhs.data(), lhs.stride(), rhs.data(), rhs.stride(), res, resIncr, alpha); \
+  } \
+} \
+}; \
+template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
+struct general_matrix_vector_product<Index,Scalar,const_blas_data_mapper<Scalar,Index,RowMajor>,RowMajor,ConjugateLhs,Scalar,const_blas_data_mapper<Scalar,Index,ColMajor>,ConjugateRhs,Specialized> { \
+static void run( \
+  Index rows, Index cols, \
+  const const_blas_data_mapper<Scalar,Index,RowMajor> &lhs, \
+  const const_blas_data_mapper<Scalar,Index,ColMajor> &rhs, \
+  Scalar* res, Index resIncr, Scalar alpha) \
+{ \
+    general_matrix_vector_product_gemv<Index,Scalar,RowMajor,ConjugateLhs,Scalar,ConjugateRhs>::run( \
+      rows, cols, lhs.data(), lhs.stride(), rhs.data(), rhs.stride(), res, resIncr, alpha); \
+} \
+}; \
+
+EIGEN_BLAS_GEMV_SPECIALIZE(double)
+EIGEN_BLAS_GEMV_SPECIALIZE(float)
+EIGEN_BLAS_GEMV_SPECIALIZE(dcomplex)
+EIGEN_BLAS_GEMV_SPECIALIZE(scomplex)
+
+#define EIGEN_BLAS_GEMV_SPECIALIZATION(EIGTYPE,BLASTYPE,BLASPREFIX) \
+template<typename Index, int LhsStorageOrder, bool ConjugateLhs, bool ConjugateRhs> \
+struct general_matrix_vector_product_gemv<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,ConjugateRhs> \
+{ \
+typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> GEMVVector;\
+\
+static void run( \
+  Index rows, Index cols, \
+  const EIGTYPE* lhs, Index lhsStride, \
+  const EIGTYPE* rhs, Index rhsIncr, \
+  EIGTYPE* res, Index resIncr, EIGTYPE alpha) \
+{ \
+  BlasIndex m=convert_index<BlasIndex>(rows), n=convert_index<BlasIndex>(cols), \
+            lda=convert_index<BlasIndex>(lhsStride), incx=convert_index<BlasIndex>(rhsIncr), incy=convert_index<BlasIndex>(resIncr); \
+  const EIGTYPE beta(1); \
+  const EIGTYPE *x_ptr; \
+  char trans=(LhsStorageOrder==ColMajor) ? 'N' : (ConjugateLhs) ? 'C' : 'T'; \
+  if (LhsStorageOrder==RowMajor) { \
+    m = convert_index<BlasIndex>(cols); \
+    n = convert_index<BlasIndex>(rows); \
+  }\
+  GEMVVector x_tmp; \
+  if (ConjugateRhs) { \
+    Map<const GEMVVector, 0, InnerStride<> > map_x(rhs,cols,1,InnerStride<>(incx)); \
+    x_tmp=map_x.conjugate(); \
+    x_ptr=x_tmp.data(); \
+    incx=1; \
+  } else x_ptr=rhs; \
+  BLASPREFIX##gemv_(&trans, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, &numext::real_ref(beta), (BLASTYPE*)res, &incy); \
+}\
+};
+
+EIGEN_BLAS_GEMV_SPECIALIZATION(double,   double, d)
+EIGEN_BLAS_GEMV_SPECIALIZATION(float,    float,  s)
+EIGEN_BLAS_GEMV_SPECIALIZATION(dcomplex, double, z)
+EIGEN_BLAS_GEMV_SPECIALIZATION(scomplex, float,  c)
+
+} // end namespase internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_GENERAL_MATRIX_VECTOR_BLAS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector_MKL.h
Index: 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/products/GeneralMatrixVector_MKL.h
@@ -1,131 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   General matrix-vector product functionality based on ?GEMV.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_GENERAL_MATRIX_VECTOR_MKL_H
-#define EIGEN_GENERAL_MATRIX_VECTOR_MKL_H
-
-namespace Eigen { 
-
-namespace internal {
-
-/**********************************************************************
-* This file implements general matrix-vector multiplication using BLAS
-* gemv function via partial specialization of
-* general_matrix_vector_product::run(..) method for float, double,
-* std::complex<float> and std::complex<double> types
-**********************************************************************/
-
-// gemv specialization
-
-template<typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs>
-struct general_matrix_vector_product_gemv :
-  general_matrix_vector_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,ConjugateRhs,BuiltIn> {};
-
-#define EIGEN_MKL_GEMV_SPECIALIZE(Scalar) \
-template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
-struct general_matrix_vector_product<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs,Specialized> { \
-static void run( \
-  Index rows, Index cols, \
-  const Scalar* lhs, Index lhsStride, \
-  const Scalar* rhs, Index rhsIncr, \
-  Scalar* res, Index resIncr, Scalar alpha) \
-{ \
-  if (ConjugateLhs) { \
-    general_matrix_vector_product<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs,BuiltIn>::run( \
-      rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
-  } else { \
-    general_matrix_vector_product_gemv<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs>::run( \
-      rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
-  } \
-} \
-}; \
-template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
-struct general_matrix_vector_product<Index,Scalar,RowMajor,ConjugateLhs,Scalar,ConjugateRhs,Specialized> { \
-static void run( \
-  Index rows, Index cols, \
-  const Scalar* lhs, Index lhsStride, \
-  const Scalar* rhs, Index rhsIncr, \
-  Scalar* res, Index resIncr, Scalar alpha) \
-{ \
-    general_matrix_vector_product_gemv<Index,Scalar,RowMajor,ConjugateLhs,Scalar,ConjugateRhs>::run( \
-      rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
-} \
-}; \
-
-EIGEN_MKL_GEMV_SPECIALIZE(double)
-EIGEN_MKL_GEMV_SPECIALIZE(float)
-EIGEN_MKL_GEMV_SPECIALIZE(dcomplex)
-EIGEN_MKL_GEMV_SPECIALIZE(scomplex)
-
-#define EIGEN_MKL_GEMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLPREFIX) \
-template<typename Index, int LhsStorageOrder, bool ConjugateLhs, bool ConjugateRhs> \
-struct general_matrix_vector_product_gemv<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,ConjugateRhs> \
-{ \
-typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> GEMVVector;\
-\
-static void run( \
-  Index rows, Index cols, \
-  const EIGTYPE* lhs, Index lhsStride, \
-  const EIGTYPE* rhs, Index rhsIncr, \
-  EIGTYPE* res, Index resIncr, EIGTYPE alpha) \
-{ \
-  MKL_INT m=rows, n=cols, lda=lhsStride, incx=rhsIncr, incy=resIncr; \
-  MKLTYPE alpha_, beta_; \
-  const EIGTYPE *x_ptr, myone(1); \
-  char trans=(LhsStorageOrder==ColMajor) ? 'N' : (ConjugateLhs) ? 'C' : 'T'; \
-  if (LhsStorageOrder==RowMajor) { \
-    m=cols; \
-    n=rows; \
-  }\
-  assign_scalar_eig2mkl(alpha_, alpha); \
-  assign_scalar_eig2mkl(beta_, myone); \
-  GEMVVector x_tmp; \
-  if (ConjugateRhs) { \
-    Map<const GEMVVector, 0, InnerStride<> > map_x(rhs,cols,1,InnerStride<>(incx)); \
-    x_tmp=map_x.conjugate(); \
-    x_ptr=x_tmp.data(); \
-    incx=1; \
-  } else x_ptr=rhs; \
-  MKLPREFIX##gemv(&trans, &m, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \
-}\
-};
-
-EIGEN_MKL_GEMV_SPECIALIZATION(double,   double,        d)
-EIGEN_MKL_GEMV_SPECIALIZATION(float,    float,         s)
-EIGEN_MKL_GEMV_SPECIALIZATION(dcomplex, MKL_Complex16, z)
-EIGEN_MKL_GEMV_SPECIALIZATION(scomplex, MKL_Complex8,  c)
-
-} // end namespase internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_GENERAL_MATRIX_VECTOR_MKL_H

Index: 3rd_party/eigen/Eigen/src/Core/products/Parallelizer.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/Parallelizer.h
+++ 3rd_party/eigen/Eigen/src/Core/products/Parallelizer.h
@@ -8,11 +8,11 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PARALLELIZER_H
 #define EIGEN_PARALLELIZER_H
 
-namespace Eigen { 
+namespace Eigen {
 
 namespace internal {
 
 /** \internal */
 inline void manage_multi_threading(Action action, int* v)
@@ -47,12 +47,12 @@
 /** Must be call first when calling Eigen from multiple threads */
 inline void initParallel()
 {
   int nbt;
   internal::manage_multi_threading(GetAction, &nbt);
-  std::ptrdiff_t l1, l2;
-  internal::manage_caching_sizes(GetAction, &l1, &l2);
+  std::ptrdiff_t l1, l2, l3;
+  internal::manage_caching_sizes(GetAction, &l1, &l2, &l3);
 }
 
 /** \returns the max number of threads reserved for Eigen
   * \sa setNbThreads */
 inline int nbThreads()
@@ -71,29 +71,30 @@
 
 namespace internal {
 
 template<typename Index> struct GemmParallelInfo
 {
-  GemmParallelInfo() : sync(-1), users(0), rhs_start(0), rhs_length(0) {}
+  GemmParallelInfo() : sync(-1), users(0), lhs_start(0), lhs_length(0) {}
 
-  int volatile sync;
+  Index volatile sync;
   int volatile users;
 
-  Index rhs_start;
-  Index rhs_length;
+  Index lhs_start;
+  Index lhs_length;
 };
 
 template<bool Condition, typename Functor, typename Index>
-void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpose)
+void parallelize_gemm(const Functor& func, Index rows, Index cols, Index depth, bool transpose)
 {
   // TODO when EIGEN_USE_BLAS is defined,
   // we should still enable OMP for other scalar types
 #if !(defined (EIGEN_HAS_OPENMP)) || defined (EIGEN_USE_BLAS)
   // FIXME the transpose variable is only needed to properly split
   // the matrix product when multithreading is enabled. This is a temporary
   // fix to support row-major destination matrices. This whole
   // parallelizer mechanism has to be redisigned anyway.
+  EIGEN_UNUSED_VARIABLE(depth);
   EIGEN_UNUSED_VARIABLE(transpose);
   func(0,rows, 0,cols);
 #else
 
   // Dynamically check whether we should enable or disable OpenMP.
@@ -100,60 +101,63 @@
   // The conditions are:
   // - the max number of threads we can create is greater than 1
   // - we are not already in a parallel code
   // - the sizes are large enough
 
-  // 1- are we already in a parallel session?
+  // compute the maximal number of threads from the size of the product:
+  // This first heuristic takes into account that the product kernel is fully optimized when working with nr columns at once.
+  Index size = transpose ? rows : cols;
+  Index pb_max_threads = std::max<Index>(1,size / Functor::Traits::nr);
+
+  // compute the maximal number of threads from the total amount of work:
+  double work = static_cast<double>(rows) * static_cast<double>(cols) *
+      static_cast<double>(depth);
+  double kMinTaskSize = 50000;  // FIXME improve this heuristic.
+  pb_max_threads = std::max<Index>(1, std::min<Index>(pb_max_threads, work / kMinTaskSize));
+
+  // compute the number of threads we are going to use
+  Index threads = std::min<Index>(nbThreads(), pb_max_threads);
+
+  // if multi-threading is explicitely disabled, not useful, or if we already are in a parallel session,
+  // then abort multi-threading
   // FIXME omp_get_num_threads()>1 only works for openmp, what if the user does not use openmp?
-  if((!Condition) || (omp_get_num_threads()>1))
-    return func(0,rows, 0,cols);
-
-  Index size = transpose ? cols : rows;
-
-  // 2- compute the maximal number of threads from the size of the product:
-  // FIXME this has to be fine tuned
-  Index max_threads = std::max<Index>(1,size / 32);
-
-  // 3 - compute the number of threads we are going to use
-  Index threads = std::min<Index>(nbThreads(), max_threads);
-
-  if(threads==1)
+  if((!Condition) || (threads==1) || (omp_get_num_threads()>1))
     return func(0,rows, 0,cols);
 
   Eigen::initParallel();
-  func.initParallelSession();
+  func.initParallelSession(threads);
 
   if(transpose)
     std::swap(rows,cols);
 
-  Index blockCols = (cols / threads) & ~Index(0x3);
-  Index blockRows = (rows / threads) & ~Index(0x7);
-  
-  GemmParallelInfo<Index>* info = new GemmParallelInfo<Index>[threads];
-
-  #pragma omp parallel for schedule(static,1) num_threads(threads)
-  for(Index i=0; i<threads; ++i)
-  {
-    Index r0 = i*blockRows;
-    Index actualBlockRows = (i+1==threads) ? rows-r0 : blockRows;
+  ei_declare_aligned_stack_constructed_variable(GemmParallelInfo<Index>,info,threads,0);
+
+  #pragma omp parallel num_threads(threads)
+  {
+    Index i = omp_get_thread_num();
+    // Note that the actual number of threads might be lower than the number of request ones.
+    Index actual_threads = omp_get_num_threads();
+
+    Index blockCols = (cols / actual_threads) & ~Index(0x3);
+    Index blockRows = (rows / actual_threads);
+    blockRows = (blockRows/Functor::Traits::mr)*Functor::Traits::mr;
+
+    Index r0 = i*blockRows;
+    Index actualBlockRows = (i+1==actual_threads) ? rows-r0 : blockRows;
 
     Index c0 = i*blockCols;
-    Index actualBlockCols = (i+1==threads) ? cols-c0 : blockCols;
-
-    info[i].rhs_start = c0;
-    info[i].rhs_length = actualBlockCols;
-
-    if(transpose)
-      func(0, cols, r0, actualBlockRows, info);
-    else
-      func(r0, actualBlockRows, 0,cols, info);
-  }
-
-  delete[] info;
+    Index actualBlockCols = (i+1==actual_threads) ? cols-c0 : blockCols;
+
+    info[i].lhs_start = r0;
+    info[i].lhs_length = actualBlockRows;
+
+    if(transpose) func(c0, actualBlockCols, 0, rows, info);
+    else          func(0, rows, c0, actualBlockCols, info);
+  }
 #endif
 }
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_PARALLELIZER_H

Index: 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
+++ 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
@@ -13,11 +13,11 @@
 namespace Eigen { 
 
 namespace internal {
 
 // pack a selfadjoint block diagonal for use with the gebp_kernel
-template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder>
+template<typename Scalar, typename Index, int Pack1, int Pack2_dummy, int StorageOrder>
 struct symm_pack_lhs
 {
   template<int BlockRows> inline
   void pack(Scalar* blockA, const const_blas_data_mapper<Scalar,Index,StorageOrder>& lhs, Index cols, Index i, Index& count)
   {
@@ -43,29 +43,36 @@
       for(Index w=0; w<BlockRows; w++)
         blockA[count++] = numext::conj(lhs(k, i+w)); // transposed
   }
   void operator()(Scalar* blockA, const Scalar* _lhs, Index lhsStride, Index cols, Index rows)
   {
+    enum { PacketSize = packet_traits<Scalar>::size };
     const_blas_data_mapper<Scalar,Index,StorageOrder> lhs(_lhs,lhsStride);
     Index count = 0;
-    Index peeled_mc = (rows/Pack1)*Pack1;
-    for(Index i=0; i<peeled_mc; i+=Pack1)
-    {
-      pack<Pack1>(blockA, lhs, cols, i, count);
-    }
-
-    if(rows-peeled_mc>=Pack2)
-    {
-      pack<Pack2>(blockA, lhs, cols, peeled_mc, count);
-      peeled_mc += Pack2;
-    }
+    //Index peeled_mc3 = (rows/Pack1)*Pack1;
+    
+    const Index peeled_mc3 = Pack1>=3*PacketSize ? (rows/(3*PacketSize))*(3*PacketSize) : 0;
+    const Index peeled_mc2 = Pack1>=2*PacketSize ? peeled_mc3+((rows-peeled_mc3)/(2*PacketSize))*(2*PacketSize) : 0;
+    const Index peeled_mc1 = Pack1>=1*PacketSize ? (rows/(1*PacketSize))*(1*PacketSize) : 0;
+    
+    if(Pack1>=3*PacketSize)
+      for(Index i=0; i<peeled_mc3; i+=3*PacketSize)
+        pack<3*PacketSize>(blockA, lhs, cols, i, count);
+    
+    if(Pack1>=2*PacketSize)
+      for(Index i=peeled_mc3; i<peeled_mc2; i+=2*PacketSize)
+        pack<2*PacketSize>(blockA, lhs, cols, i, count);
+    
+    if(Pack1>=1*PacketSize)
+      for(Index i=peeled_mc2; i<peeled_mc1; i+=1*PacketSize)
+        pack<1*PacketSize>(blockA, lhs, cols, i, count);
 
     // do the same with mr==1
-    for(Index i=peeled_mc; i<rows; i++)
+    for(Index i=peeled_mc1; i<rows; i++)
     {
       for(Index k=0; k<i; k++)
-        blockA[count++] = lhs(i, k);              // normal
+        blockA[count++] = lhs(i, k);                   // normal
 
       blockA[count++] = numext::real(lhs(i, i));       // real (diagonal)
 
       for(Index k=i+1; k<cols; k++)
         blockA[count++] = numext::conj(lhs(k, i));     // transposed
@@ -80,92 +87,165 @@
   void operator()(Scalar* blockB, const Scalar* _rhs, Index rhsStride, Index rows, Index cols, Index k2)
   {
     Index end_k = k2 + rows;
     Index count = 0;
     const_blas_data_mapper<Scalar,Index,StorageOrder> rhs(_rhs,rhsStride);
-    Index packet_cols = (cols/nr)*nr;
+    Index packet_cols8 = nr>=8 ? (cols/8) * 8 : 0;
+    Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
 
     // first part: normal case
     for(Index j2=0; j2<k2; j2+=nr)
     {
       for(Index k=k2; k<end_k; k++)
       {
         blockB[count+0] = rhs(k,j2+0);
         blockB[count+1] = rhs(k,j2+1);
-        if (nr==4)
+        if (nr>=4)
         {
           blockB[count+2] = rhs(k,j2+2);
           blockB[count+3] = rhs(k,j2+3);
         }
+        if (nr>=8)
+        {
+          blockB[count+4] = rhs(k,j2+4);
+          blockB[count+5] = rhs(k,j2+5);
+          blockB[count+6] = rhs(k,j2+6);
+          blockB[count+7] = rhs(k,j2+7);
+        }
         count += nr;
       }
     }
 
     // second part: diagonal block
-    for(Index j2=k2; j2<(std::min)(k2+rows,packet_cols); j2+=nr)
-    {
-      // again we can split vertically in three different parts (transpose, symmetric, normal)
-      // transpose
-      for(Index k=k2; k<j2; k++)
-      {
-        blockB[count+0] = numext::conj(rhs(j2+0,k));
-        blockB[count+1] = numext::conj(rhs(j2+1,k));
-        if (nr==4)
-        {
+    Index end8 = nr>=8 ? (std::min)(k2+rows,packet_cols8) : k2;
+    if(nr>=8)
+    {
+      for(Index j2=k2; j2<end8; j2+=8)
+      {
+        // again we can split vertically in three different parts (transpose, symmetric, normal)
+        // transpose
+        for(Index k=k2; k<j2; k++)
+        {
+          blockB[count+0] = numext::conj(rhs(j2+0,k));
+          blockB[count+1] = numext::conj(rhs(j2+1,k));
+          blockB[count+2] = numext::conj(rhs(j2+2,k));
+          blockB[count+3] = numext::conj(rhs(j2+3,k));
+          blockB[count+4] = numext::conj(rhs(j2+4,k));
+          blockB[count+5] = numext::conj(rhs(j2+5,k));
+          blockB[count+6] = numext::conj(rhs(j2+6,k));
+          blockB[count+7] = numext::conj(rhs(j2+7,k));
+          count += 8;
+        }
+        // symmetric
+        Index h = 0;
+        for(Index k=j2; k<j2+8; k++)
+        {
+          // normal
+          for (Index w=0 ; w<h; ++w)
+            blockB[count+w] = rhs(k,j2+w);
+
+          blockB[count+h] = numext::real(rhs(k,k));
+
+          // transpose
+          for (Index w=h+1 ; w<8; ++w)
+            blockB[count+w] = numext::conj(rhs(j2+w,k));
+          count += 8;
+          ++h;
+        }
+        // normal
+        for(Index k=j2+8; k<end_k; k++)
+        {
+          blockB[count+0] = rhs(k,j2+0);
+          blockB[count+1] = rhs(k,j2+1);
+          blockB[count+2] = rhs(k,j2+2);
+          blockB[count+3] = rhs(k,j2+3);
+          blockB[count+4] = rhs(k,j2+4);
+          blockB[count+5] = rhs(k,j2+5);
+          blockB[count+6] = rhs(k,j2+6);
+          blockB[count+7] = rhs(k,j2+7);
+          count += 8;
+        }
+      }
+    }
+    if(nr>=4)
+    {
+      for(Index j2=end8; j2<(std::min)(k2+rows,packet_cols4); j2+=4)
+      {
+        // again we can split vertically in three different parts (transpose, symmetric, normal)
+        // transpose
+        for(Index k=k2; k<j2; k++)
+        {
+          blockB[count+0] = numext::conj(rhs(j2+0,k));
+          blockB[count+1] = numext::conj(rhs(j2+1,k));
           blockB[count+2] = numext::conj(rhs(j2+2,k));
           blockB[count+3] = numext::conj(rhs(j2+3,k));
-        }
-        count += nr;
-      }
-      // symmetric
-      Index h = 0;
-      for(Index k=j2; k<j2+nr; k++)
-      {
-        // normal
-        for (Index w=0 ; w<h; ++w)
-          blockB[count+w] = rhs(k,j2+w);
-
-        blockB[count+h] = numext::real(rhs(k,k));
-
-        // transpose
-        for (Index w=h+1 ; w<nr; ++w)
-          blockB[count+w] = numext::conj(rhs(j2+w,k));
-        count += nr;
-        ++h;
-      }
-      // normal
-      for(Index k=j2+nr; k<end_k; k++)
-      {
-        blockB[count+0] = rhs(k,j2+0);
-        blockB[count+1] = rhs(k,j2+1);
-        if (nr==4)
-        {
+          count += 4;
+        }
+        // symmetric
+        Index h = 0;
+        for(Index k=j2; k<j2+4; k++)
+        {
+          // normal
+          for (Index w=0 ; w<h; ++w)
+            blockB[count+w] = rhs(k,j2+w);
+
+          blockB[count+h] = numext::real(rhs(k,k));
+
+          // transpose
+          for (Index w=h+1 ; w<4; ++w)
+            blockB[count+w] = numext::conj(rhs(j2+w,k));
+          count += 4;
+          ++h;
+        }
+        // normal
+        for(Index k=j2+4; k<end_k; k++)
+        {
+          blockB[count+0] = rhs(k,j2+0);
+          blockB[count+1] = rhs(k,j2+1);
           blockB[count+2] = rhs(k,j2+2);
           blockB[count+3] = rhs(k,j2+3);
+          count += 4;
         }
-        count += nr;
       }
     }
 
     // third part: transposed
-    for(Index j2=k2+rows; j2<packet_cols; j2+=nr)
-    {
-      for(Index k=k2; k<end_k; k++)
-      {
-        blockB[count+0] = numext::conj(rhs(j2+0,k));
-        blockB[count+1] = numext::conj(rhs(j2+1,k));
-        if (nr==4)
-        {
+    if(nr>=8)
+    {
+      for(Index j2=k2+rows; j2<packet_cols8; j2+=8)
+      {
+        for(Index k=k2; k<end_k; k++)
+        {
+          blockB[count+0] = numext::conj(rhs(j2+0,k));
+          blockB[count+1] = numext::conj(rhs(j2+1,k));
+          blockB[count+2] = numext::conj(rhs(j2+2,k));
+          blockB[count+3] = numext::conj(rhs(j2+3,k));
+          blockB[count+4] = numext::conj(rhs(j2+4,k));
+          blockB[count+5] = numext::conj(rhs(j2+5,k));
+          blockB[count+6] = numext::conj(rhs(j2+6,k));
+          blockB[count+7] = numext::conj(rhs(j2+7,k));
+          count += 8;
+        }
+      }
+    }
+    if(nr>=4)
+    {
+      for(Index j2=(std::max)(packet_cols8,k2+rows); j2<packet_cols4; j2+=4)
+      {
+        for(Index k=k2; k<end_k; k++)
+        {
+          blockB[count+0] = numext::conj(rhs(j2+0,k));
+          blockB[count+1] = numext::conj(rhs(j2+1,k));
           blockB[count+2] = numext::conj(rhs(j2+2,k));
           blockB[count+3] = numext::conj(rhs(j2+3,k));
+          count += 4;
         }
-        count += nr;
       }
     }
 
     // copy the remaining columns one at a time (=> the same with nr==1)
-    for(Index j2=packet_cols; j2<cols; ++j2)
+    for(Index j2=packet_cols4; j2<cols; ++j2)
     {
       // transpose
       Index half = (std::min)(end_k,j2);
       for(Index k=k2; k<half; k++)
       {
@@ -209,19 +289,19 @@
   static EIGEN_STRONG_INLINE void run(
     Index rows, Index cols,
     const Scalar* lhs, Index lhsStride,
     const Scalar* rhs, Index rhsStride,
     Scalar* res,       Index resStride,
-    const Scalar& alpha)
+    const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
   {
     product_selfadjoint_matrix<Scalar, Index,
       EIGEN_LOGICAL_XOR(RhsSelfAdjoint,RhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
       RhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsSelfAdjoint,ConjugateRhs),
       EIGEN_LOGICAL_XOR(LhsSelfAdjoint,LhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
       LhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsSelfAdjoint,ConjugateLhs),
       ColMajor>
-      ::run(cols, rows,  rhs, rhsStride,  lhs, lhsStride,  res, resStride,  alpha);
+      ::run(cols, rows,  rhs, rhsStride,  lhs, lhsStride,  res, resStride,  alpha, blocking);
   }
 };
 
 template <typename Scalar, typename Index,
           int LhsStorageOrder, bool ConjugateLhs,
@@ -232,85 +312,87 @@
   static EIGEN_DONT_INLINE void run(
     Index rows, Index cols,
     const Scalar* _lhs, Index lhsStride,
     const Scalar* _rhs, Index rhsStride,
     Scalar* res,        Index resStride,
-    const Scalar& alpha);
+    const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking);
 };
 
 template <typename Scalar, typename Index,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs>
 EIGEN_DONT_INLINE void product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor>::run(
     Index rows, Index cols,
     const Scalar* _lhs, Index lhsStride,
     const Scalar* _rhs, Index rhsStride,
-    Scalar* res,        Index resStride,
-    const Scalar& alpha)
+    Scalar* _res,        Index resStride,
+    const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
   {
     Index size = rows;
 
-    const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
-    const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
-
     typedef gebp_traits<Scalar,Scalar> Traits;
 
-    Index kc = size;  // cache block size along the K direction
-    Index mc = rows;  // cache block size along the M direction
-    Index nc = cols;  // cache block size along the N direction
-    computeProductBlockingSizes<Scalar,Scalar>(kc, mc, nc);
-    // kc must smaller than mc
+    typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
+    typedef const_blas_data_mapper<Scalar, Index, (LhsStorageOrder == RowMajor) ? ColMajor : RowMajor> LhsTransposeMapper;
+    typedef const_blas_data_mapper<Scalar, Index, RhsStorageOrder> RhsMapper;
+    typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
+    LhsMapper lhs(_lhs,lhsStride);
+    LhsTransposeMapper lhs_transpose(_lhs,lhsStride);
+    RhsMapper rhs(_rhs,rhsStride);
+    ResMapper res(_res, resStride);
+
+    Index kc = blocking.kc();                   // cache block size along the K direction
+    Index mc = (std::min)(rows,blocking.mc());  // cache block size along the M direction
+    // kc must be smaller than mc
     kc = (std::min)(kc,mc);
-
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
-    std::size_t sizeB = sizeW + kc*cols;
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0);
-    ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0);
-    Scalar* blockB = allocatedBlockB + sizeW;
-
-    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
+    std::size_t sizeA = kc*mc;
+    std::size_t sizeB = kc*cols;
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
+
+    gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
     symm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
-    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
-    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder==RowMajor?ColMajor:RowMajor, true> pack_lhs_transposed;
+    gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr,RhsStorageOrder> pack_rhs;
+    gemm_pack_lhs<Scalar, Index, LhsTransposeMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder==RowMajor?ColMajor:RowMajor, true> pack_lhs_transposed;
 
     for(Index k2=0; k2<size; k2+=kc)
     {
       const Index actual_kc = (std::min)(k2+kc,size)-k2;
 
       // we have selected one row panel of rhs and one column panel of lhs
       // pack rhs's panel into a sequential chunk of memory
       // and expand each coeff to a constant packet for further reuse
-      pack_rhs(blockB, &rhs(k2,0), rhsStride, actual_kc, cols);
+      pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, cols);
 
       // the select lhs's panel has to be split in three different parts:
       //  1 - the transposed panel above the diagonal block => transposed packed copy
       //  2 - the diagonal block => special packed copy
       //  3 - the panel below the diagonal block => generic packed copy
       for(Index i2=0; i2<k2; i2+=mc)
       {
         const Index actual_mc = (std::min)(i2+mc,k2)-i2;
         // transposed packed copy
-        pack_lhs_transposed(blockA, &lhs(k2, i2), lhsStride, actual_kc, actual_mc);
+        pack_lhs_transposed(blockA, lhs_transpose.getSubMapper(i2, k2), actual_kc, actual_mc);
 
-        gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+        gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
       }
       // the block diagonal
       {
         const Index actual_mc = (std::min)(k2+kc,size)-k2;
         // symmetric packed copy
         pack_lhs(blockA, &lhs(k2,k2), lhsStride, actual_kc, actual_mc);
 
-        gebp_kernel(res+k2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+        gebp_kernel(res.getSubMapper(k2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
       }
 
       for(Index i2=k2+kc; i2<size; i2+=mc)
       {
         const Index actual_mc = (std::min)(i2+mc,size)-i2;
-        gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder,false>()
-          (blockA, &lhs(i2, k2), lhsStride, actual_kc, actual_mc);
+        gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder,false>()
+          (blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
 
-        gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+        gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
       }
     }
   }
 
 // matrix * selfadjoint product
@@ -323,41 +405,41 @@
   static EIGEN_DONT_INLINE void run(
     Index rows, Index cols,
     const Scalar* _lhs, Index lhsStride,
     const Scalar* _rhs, Index rhsStride,
     Scalar* res,        Index resStride,
-    const Scalar& alpha);
+    const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking);
 };
 
 template <typename Scalar, typename Index,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs>
 EIGEN_DONT_INLINE void product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor>::run(
     Index rows, Index cols,
     const Scalar* _lhs, Index lhsStride,
     const Scalar* _rhs, Index rhsStride,
-    Scalar* res,        Index resStride,
-    const Scalar& alpha)
+    Scalar* _res,        Index resStride,
+    const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
   {
     Index size = cols;
 
-    const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
-
     typedef gebp_traits<Scalar,Scalar> Traits;
 
-    Index kc = size; // cache block size along the K direction
-    Index mc = rows;  // cache block size along the M direction
-    Index nc = cols;  // cache block size along the N direction
-    computeProductBlockingSizes<Scalar,Scalar>(kc, mc, nc);
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
-    std::size_t sizeB = sizeW + kc*cols;
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0);
-    ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0);
-    Scalar* blockB = allocatedBlockB + sizeW;
-
-    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
-    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+    typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
+    typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
+    LhsMapper lhs(_lhs,lhsStride);
+    ResMapper res(_res,resStride);
+
+    Index kc = blocking.kc();                   // cache block size along the K direction
+    Index mc = (std::min)(rows,blocking.mc());  // cache block size along the M direction
+    std::size_t sizeA = kc*mc;
+    std::size_t sizeB = kc*cols;
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
+
+    gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
+    gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
     symm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
 
     for(Index k2=0; k2<size; k2+=kc)
     {
       const Index actual_kc = (std::min)(k2+kc,size)-k2;
@@ -366,13 +448,13 @@
 
       // => GEPP
       for(Index i2=0; i2<rows; i2+=mc)
       {
         const Index actual_mc = (std::min)(i2+mc,rows)-i2;
-        pack_lhs(blockA, &lhs(i2, k2), lhsStride, actual_kc, actual_mc);
+        pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
 
-        gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+        gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
       }
     }
   }
 
 } // end namespace internal
@@ -380,57 +462,60 @@
 /***************************************************************************
 * Wrapper to product_selfadjoint_matrix
 ***************************************************************************/
 
 namespace internal {
-template<typename Lhs, int LhsMode, typename Rhs, int RhsMode>
-struct traits<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false> >
-  : traits<ProductBase<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>, Lhs, Rhs> >
-{};
-}
-
-template<typename Lhs, int LhsMode, typename Rhs, int RhsMode>
-struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>
-  : public ProductBase<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>, Lhs, Rhs >
-{
-  EIGEN_PRODUCT_PUBLIC_INTERFACE(SelfadjointProductMatrix)
-
-  SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
-
+  
+template<typename Lhs, int LhsMode, typename Rhs, int RhsMode>
+struct selfadjoint_product_impl<Lhs,LhsMode,false,Rhs,RhsMode,false>
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  typedef internal::blas_traits<Lhs> LhsBlasTraits;
+  typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+  typedef internal::blas_traits<Rhs> RhsBlasTraits;
+  typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+  
   enum {
     LhsIsUpper = (LhsMode&(Upper|Lower))==Upper,
     LhsIsSelfAdjoint = (LhsMode&SelfAdjoint)==SelfAdjoint,
     RhsIsUpper = (RhsMode&(Upper|Lower))==Upper,
     RhsIsSelfAdjoint = (RhsMode&SelfAdjoint)==SelfAdjoint
   };
-
-  template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
-  {
-    eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
-
-    typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(m_lhs);
-    typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(m_rhs);
-
-    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
-                               * RhsBlasTraits::extractScalarFactor(m_rhs);
+  
+  template<typename Dest>
+  static void run(Dest &dst, const Lhs &a_lhs, const Rhs &a_rhs, const Scalar& alpha)
+  {
+    eigen_assert(dst.rows()==a_lhs.rows() && dst.cols()==a_rhs.cols());
+
+    typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs);
+    typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs);
+
+    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs)
+                               * RhsBlasTraits::extractScalarFactor(a_rhs);
+
+    typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
+              Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxColsAtCompileTime,1> BlockingType;
+
+    BlockingType blocking(lhs.rows(), rhs.cols(), lhs.cols(), 1, false);
 
     internal::product_selfadjoint_matrix<Scalar, Index,
-      EIGEN_LOGICAL_XOR(LhsIsUpper,
-                        internal::traits<Lhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, LhsIsSelfAdjoint,
+      EIGEN_LOGICAL_XOR(LhsIsUpper,internal::traits<Lhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, LhsIsSelfAdjoint,
       NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsIsUpper,bool(LhsBlasTraits::NeedToConjugate)),
-      EIGEN_LOGICAL_XOR(RhsIsUpper,
-                        internal::traits<Rhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, RhsIsSelfAdjoint,
+      EIGEN_LOGICAL_XOR(RhsIsUpper,internal::traits<Rhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, RhsIsSelfAdjoint,
       NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsIsUpper,bool(RhsBlasTraits::NeedToConjugate)),
       internal::traits<Dest>::Flags&RowMajorBit  ? RowMajor : ColMajor>
       ::run(
         lhs.rows(), rhs.cols(),                 // sizes
-        &lhs.coeffRef(0,0),    lhs.outerStride(),  // lhs info
-        &rhs.coeffRef(0,0),    rhs.outerStride(),  // rhs info
+        &lhs.coeffRef(0,0), lhs.outerStride(),  // lhs info
+        &rhs.coeffRef(0,0), rhs.outerStride(),  // rhs info
         &dst.coeffRef(0,0), dst.outerStride(),  // result info
-        actualAlpha                             // alpha
+        actualAlpha, blocking                   // alpha
       );
   }
 };
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_H

ADDED   3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_BLAS.h
Index: 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_BLAS.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_BLAS.h
+++ 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_BLAS.h
@@ -0,0 +1,275 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+//
+ ********************************************************************************
+ *   Content : Eigen bindings to BLAS F77
+ *   Self adjoint matrix * matrix product functionality based on ?SYMM/?HEMM.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_BLAS_H
+#define EIGEN_SELFADJOINT_MATRIX_MATRIX_BLAS_H
+
+namespace Eigen { 
+
+namespace internal {
+
+
+/* Optimized selfadjoint matrix * matrix (?SYMM/?HEMM) product */
+
+#define EIGEN_BLAS_SYMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
+template <typename Index, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLhs,RhsStorageOrder,false,ConjugateRhs,ColMajor> \
+{\
+\
+  static void run( \
+    Index rows, Index cols, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha, level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/) \
+  { \
+    char side='L', uplo='L'; \
+    BlasIndex m, n, lda, ldb, ldc; \
+    const EIGTYPE *a, *b; \
+    EIGTYPE beta(1); \
+    MatrixX##EIGPREFIX b_tmp; \
+\
+/* Set transpose options */ \
+/* Set m, n, k */ \
+    m = convert_index<BlasIndex>(rows);  \
+    n = convert_index<BlasIndex>(cols);  \
+\
+/* Set lda, ldb, ldc */ \
+    lda = convert_index<BlasIndex>(lhsStride); \
+    ldb = convert_index<BlasIndex>(rhsStride); \
+    ldc = convert_index<BlasIndex>(resStride); \
+\
+/* Set a, b, c */ \
+    if (LhsStorageOrder==RowMajor) uplo='U'; \
+    a = _lhs; \
+\
+    if (RhsStorageOrder==RowMajor) { \
+      Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
+      b_tmp = rhs.adjoint(); \
+      b = b_tmp.data(); \
+      ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
+    } else b = _rhs; \
+\
+    BLASPREFIX##symm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
+\
+  } \
+};
+
+
+#define EIGEN_BLAS_HEMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
+template <typename Index, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLhs,RhsStorageOrder,false,ConjugateRhs,ColMajor> \
+{\
+  static void run( \
+    Index rows, Index cols, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha, level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/) \
+  { \
+    char side='L', uplo='L'; \
+    BlasIndex m, n, lda, ldb, ldc; \
+    const EIGTYPE *a, *b; \
+    EIGTYPE beta(1); \
+    MatrixX##EIGPREFIX b_tmp; \
+    Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> a_tmp; \
+\
+/* Set transpose options */ \
+/* Set m, n, k */ \
+    m = convert_index<BlasIndex>(rows); \
+    n = convert_index<BlasIndex>(cols); \
+\
+/* Set lda, ldb, ldc */ \
+    lda = convert_index<BlasIndex>(lhsStride); \
+    ldb = convert_index<BlasIndex>(rhsStride); \
+    ldc = convert_index<BlasIndex>(resStride); \
+\
+/* Set a, b, c */ \
+    if (((LhsStorageOrder==ColMajor) && ConjugateLhs) || ((LhsStorageOrder==RowMajor) && (!ConjugateLhs))) { \
+      Map<const Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder>, 0, OuterStride<> > lhs(_lhs,m,m,OuterStride<>(lhsStride)); \
+      a_tmp = lhs.conjugate(); \
+      a = a_tmp.data(); \
+      lda = convert_index<BlasIndex>(a_tmp.outerStride()); \
+    } else a = _lhs; \
+    if (LhsStorageOrder==RowMajor) uplo='U'; \
+\
+    if (RhsStorageOrder==ColMajor && (!ConjugateRhs)) { \
+       b = _rhs; } \
+    else { \
+      if (RhsStorageOrder==ColMajor && ConjugateRhs) { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,m,n,OuterStride<>(rhsStride)); \
+        b_tmp = rhs.conjugate(); \
+      } else \
+      if (ConjugateRhs) { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
+        b_tmp = rhs.adjoint(); \
+      } else { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
+        b_tmp = rhs.transpose(); \
+      } \
+      b = b_tmp.data(); \
+      ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
+    } \
+\
+    BLASPREFIX##hemm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
+\
+  } \
+};
+
+EIGEN_BLAS_SYMM_L(double, double, d, d)
+EIGEN_BLAS_SYMM_L(float, float, f, s)
+EIGEN_BLAS_HEMM_L(dcomplex, double, cd, z)
+EIGEN_BLAS_HEMM_L(scomplex, float, cf, c)
+
+
+/* Optimized matrix * selfadjoint matrix (?SYMM/?HEMM) product */
+
+#define EIGEN_BLAS_SYMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
+template <typename Index, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateLhs,RhsStorageOrder,true,ConjugateRhs,ColMajor> \
+{\
+\
+  static void run( \
+    Index rows, Index cols, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha, level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/) \
+  { \
+    char side='R', uplo='L'; \
+    BlasIndex m, n, lda, ldb, ldc; \
+    const EIGTYPE *a, *b; \
+    EIGTYPE beta(1); \
+    MatrixX##EIGPREFIX b_tmp; \
+\
+/* Set m, n, k */ \
+    m = convert_index<BlasIndex>(rows);  \
+    n = convert_index<BlasIndex>(cols);  \
+\
+/* Set lda, ldb, ldc */ \
+    lda = convert_index<BlasIndex>(rhsStride); \
+    ldb = convert_index<BlasIndex>(lhsStride); \
+    ldc = convert_index<BlasIndex>(resStride); \
+\
+/* Set a, b, c */ \
+    if (RhsStorageOrder==RowMajor) uplo='U'; \
+    a = _rhs; \
+\
+    if (LhsStorageOrder==RowMajor) { \
+      Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(rhsStride)); \
+      b_tmp = lhs.adjoint(); \
+      b = b_tmp.data(); \
+      ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
+    } else b = _lhs; \
+\
+    BLASPREFIX##symm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
+\
+  } \
+};
+
+
+#define EIGEN_BLAS_HEMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
+template <typename Index, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateLhs,RhsStorageOrder,true,ConjugateRhs,ColMajor> \
+{\
+  static void run( \
+    Index rows, Index cols, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha, level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/) \
+  { \
+    char side='R', uplo='L'; \
+    BlasIndex m, n, lda, ldb, ldc; \
+    const EIGTYPE *a, *b; \
+    EIGTYPE beta(1); \
+    MatrixX##EIGPREFIX b_tmp; \
+    Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> a_tmp; \
+\
+/* Set m, n, k */ \
+    m = convert_index<BlasIndex>(rows); \
+    n = convert_index<BlasIndex>(cols); \
+\
+/* Set lda, ldb, ldc */ \
+    lda = convert_index<BlasIndex>(rhsStride); \
+    ldb = convert_index<BlasIndex>(lhsStride); \
+    ldc = convert_index<BlasIndex>(resStride); \
+\
+/* Set a, b, c */ \
+    if (((RhsStorageOrder==ColMajor) && ConjugateRhs) || ((RhsStorageOrder==RowMajor) && (!ConjugateRhs))) { \
+      Map<const Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder>, 0, OuterStride<> > rhs(_rhs,n,n,OuterStride<>(rhsStride)); \
+      a_tmp = rhs.conjugate(); \
+      a = a_tmp.data(); \
+      lda = convert_index<BlasIndex>(a_tmp.outerStride()); \
+    } else a = _rhs; \
+    if (RhsStorageOrder==RowMajor) uplo='U'; \
+\
+    if (LhsStorageOrder==ColMajor && (!ConjugateLhs)) { \
+       b = _lhs; } \
+    else { \
+      if (LhsStorageOrder==ColMajor && ConjugateLhs) { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,m,n,OuterStride<>(lhsStride)); \
+        b_tmp = lhs.conjugate(); \
+      } else \
+      if (ConjugateLhs) { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(lhsStride)); \
+        b_tmp = lhs.adjoint(); \
+      } else { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(lhsStride)); \
+        b_tmp = lhs.transpose(); \
+      } \
+      b = b_tmp.data(); \
+      ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
+    } \
+\
+    BLASPREFIX##hemm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
+  } \
+};
+
+EIGEN_BLAS_SYMM_R(double, double, d, d)
+EIGEN_BLAS_SYMM_R(float, float, f, s)
+EIGEN_BLAS_HEMM_R(dcomplex, double, cd, z)
+EIGEN_BLAS_HEMM_R(scomplex, float, cf, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_BLAS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h
Index: 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h
@@ -1,295 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-//
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   Self adjoint matrix * matrix product functionality based on ?SYMM/?HEMM.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H
-#define EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H
-
-namespace Eigen { 
-
-namespace internal {
-
-
-/* Optimized selfadjoint matrix * matrix (?SYMM/?HEMM) product */
-
-#define EIGEN_MKL_SYMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
-template <typename Index, \
-          int LhsStorageOrder, bool ConjugateLhs, \
-          int RhsStorageOrder, bool ConjugateRhs> \
-struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLhs,RhsStorageOrder,false,ConjugateRhs,ColMajor> \
-{\
-\
-  static void run( \
-    Index rows, Index cols, \
-    const EIGTYPE* _lhs, Index lhsStride, \
-    const EIGTYPE* _rhs, Index rhsStride, \
-    EIGTYPE* res,        Index resStride, \
-    EIGTYPE alpha) \
-  { \
-    char side='L', uplo='L'; \
-    MKL_INT m, n, lda, ldb, ldc; \
-    const EIGTYPE *a, *b; \
-    MKLTYPE alpha_, beta_; \
-    MatrixX##EIGPREFIX b_tmp; \
-    EIGTYPE myone(1);\
-\
-/* Set transpose options */ \
-/* Set m, n, k */ \
-    m = (MKL_INT)rows;  \
-    n = (MKL_INT)cols;  \
-\
-/* Set alpha_ & beta_ */ \
-    assign_scalar_eig2mkl(alpha_, alpha); \
-    assign_scalar_eig2mkl(beta_, myone); \
-\
-/* Set lda, ldb, ldc */ \
-    lda = (MKL_INT)lhsStride; \
-    ldb = (MKL_INT)rhsStride; \
-    ldc = (MKL_INT)resStride; \
-\
-/* Set a, b, c */ \
-    if (LhsStorageOrder==RowMajor) uplo='U'; \
-    a = _lhs; \
-\
-    if (RhsStorageOrder==RowMajor) { \
-      Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
-      b_tmp = rhs.adjoint(); \
-      b = b_tmp.data(); \
-      ldb = b_tmp.outerStride(); \
-    } else b = _rhs; \
-\
-    MKLPREFIX##symm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
-\
-  } \
-};
-
-
-#define EIGEN_MKL_HEMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
-template <typename Index, \
-          int LhsStorageOrder, bool ConjugateLhs, \
-          int RhsStorageOrder, bool ConjugateRhs> \
-struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLhs,RhsStorageOrder,false,ConjugateRhs,ColMajor> \
-{\
-  static void run( \
-    Index rows, Index cols, \
-    const EIGTYPE* _lhs, Index lhsStride, \
-    const EIGTYPE* _rhs, Index rhsStride, \
-    EIGTYPE* res,        Index resStride, \
-    EIGTYPE alpha) \
-  { \
-    char side='L', uplo='L'; \
-    MKL_INT m, n, lda, ldb, ldc; \
-    const EIGTYPE *a, *b; \
-    MKLTYPE alpha_, beta_; \
-    MatrixX##EIGPREFIX b_tmp; \
-    Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> a_tmp; \
-    EIGTYPE myone(1); \
-\
-/* Set transpose options */ \
-/* Set m, n, k */ \
-    m = (MKL_INT)rows; \
-    n = (MKL_INT)cols; \
-\
-/* Set alpha_ & beta_ */ \
-    assign_scalar_eig2mkl(alpha_, alpha); \
-    assign_scalar_eig2mkl(beta_, myone); \
-\
-/* Set lda, ldb, ldc */ \
-    lda = (MKL_INT)lhsStride; \
-    ldb = (MKL_INT)rhsStride; \
-    ldc = (MKL_INT)resStride; \
-\
-/* Set a, b, c */ \
-    if (((LhsStorageOrder==ColMajor) && ConjugateLhs) || ((LhsStorageOrder==RowMajor) && (!ConjugateLhs))) { \
-      Map<const Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder>, 0, OuterStride<> > lhs(_lhs,m,m,OuterStride<>(lhsStride)); \
-      a_tmp = lhs.conjugate(); \
-      a = a_tmp.data(); \
-      lda = a_tmp.outerStride(); \
-    } else a = _lhs; \
-    if (LhsStorageOrder==RowMajor) uplo='U'; \
-\
-    if (RhsStorageOrder==ColMajor && (!ConjugateRhs)) { \
-       b = _rhs; } \
-    else { \
-      if (RhsStorageOrder==ColMajor && ConjugateRhs) { \
-        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,m,n,OuterStride<>(rhsStride)); \
-        b_tmp = rhs.conjugate(); \
-      } else \
-      if (ConjugateRhs) { \
-        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
-        b_tmp = rhs.adjoint(); \
-      } else { \
-        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
-        b_tmp = rhs.transpose(); \
-      } \
-      b = b_tmp.data(); \
-      ldb = b_tmp.outerStride(); \
-    } \
-\
-    MKLPREFIX##hemm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
-\
-  } \
-};
-
-EIGEN_MKL_SYMM_L(double, double, d, d)
-EIGEN_MKL_SYMM_L(float, float, f, s)
-EIGEN_MKL_HEMM_L(dcomplex, MKL_Complex16, cd, z)
-EIGEN_MKL_HEMM_L(scomplex, MKL_Complex8, cf, c)
-
-
-/* Optimized matrix * selfadjoint matrix (?SYMM/?HEMM) product */
-
-#define EIGEN_MKL_SYMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
-template <typename Index, \
-          int LhsStorageOrder, bool ConjugateLhs, \
-          int RhsStorageOrder, bool ConjugateRhs> \
-struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateLhs,RhsStorageOrder,true,ConjugateRhs,ColMajor> \
-{\
-\
-  static void run( \
-    Index rows, Index cols, \
-    const EIGTYPE* _lhs, Index lhsStride, \
-    const EIGTYPE* _rhs, Index rhsStride, \
-    EIGTYPE* res,        Index resStride, \
-    EIGTYPE alpha) \
-  { \
-    char side='R', uplo='L'; \
-    MKL_INT m, n, lda, ldb, ldc; \
-    const EIGTYPE *a, *b; \
-    MKLTYPE alpha_, beta_; \
-    MatrixX##EIGPREFIX b_tmp; \
-    EIGTYPE myone(1);\
-\
-/* Set m, n, k */ \
-    m = (MKL_INT)rows;  \
-    n = (MKL_INT)cols;  \
-\
-/* Set alpha_ & beta_ */ \
-    assign_scalar_eig2mkl(alpha_, alpha); \
-    assign_scalar_eig2mkl(beta_, myone); \
-\
-/* Set lda, ldb, ldc */ \
-    lda = (MKL_INT)rhsStride; \
-    ldb = (MKL_INT)lhsStride; \
-    ldc = (MKL_INT)resStride; \
-\
-/* Set a, b, c */ \
-    if (RhsStorageOrder==RowMajor) uplo='U'; \
-    a = _rhs; \
-\
-    if (LhsStorageOrder==RowMajor) { \
-      Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(rhsStride)); \
-      b_tmp = lhs.adjoint(); \
-      b = b_tmp.data(); \
-      ldb = b_tmp.outerStride(); \
-    } else b = _lhs; \
-\
-    MKLPREFIX##symm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
-\
-  } \
-};
-
-
-#define EIGEN_MKL_HEMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
-template <typename Index, \
-          int LhsStorageOrder, bool ConjugateLhs, \
-          int RhsStorageOrder, bool ConjugateRhs> \
-struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateLhs,RhsStorageOrder,true,ConjugateRhs,ColMajor> \
-{\
-  static void run( \
-    Index rows, Index cols, \
-    const EIGTYPE* _lhs, Index lhsStride, \
-    const EIGTYPE* _rhs, Index rhsStride, \
-    EIGTYPE* res,        Index resStride, \
-    EIGTYPE alpha) \
-  { \
-    char side='R', uplo='L'; \
-    MKL_INT m, n, lda, ldb, ldc; \
-    const EIGTYPE *a, *b; \
-    MKLTYPE alpha_, beta_; \
-    MatrixX##EIGPREFIX b_tmp; \
-    Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> a_tmp; \
-    EIGTYPE myone(1); \
-\
-/* Set m, n, k */ \
-    m = (MKL_INT)rows; \
-    n = (MKL_INT)cols; \
-\
-/* Set alpha_ & beta_ */ \
-    assign_scalar_eig2mkl(alpha_, alpha); \
-    assign_scalar_eig2mkl(beta_, myone); \
-\
-/* Set lda, ldb, ldc */ \
-    lda = (MKL_INT)rhsStride; \
-    ldb = (MKL_INT)lhsStride; \
-    ldc = (MKL_INT)resStride; \
-\
-/* Set a, b, c */ \
-    if (((RhsStorageOrder==ColMajor) && ConjugateRhs) || ((RhsStorageOrder==RowMajor) && (!ConjugateRhs))) { \
-      Map<const Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder>, 0, OuterStride<> > rhs(_rhs,n,n,OuterStride<>(rhsStride)); \
-      a_tmp = rhs.conjugate(); \
-      a = a_tmp.data(); \
-      lda = a_tmp.outerStride(); \
-    } else a = _rhs; \
-    if (RhsStorageOrder==RowMajor) uplo='U'; \
-\
-    if (LhsStorageOrder==ColMajor && (!ConjugateLhs)) { \
-       b = _lhs; } \
-    else { \
-      if (LhsStorageOrder==ColMajor && ConjugateLhs) { \
-        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,m,n,OuterStride<>(lhsStride)); \
-        b_tmp = lhs.conjugate(); \
-      } else \
-      if (ConjugateLhs) { \
-        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(lhsStride)); \
-        b_tmp = lhs.adjoint(); \
-      } else { \
-        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(lhsStride)); \
-        b_tmp = lhs.transpose(); \
-      } \
-      b = b_tmp.data(); \
-      ldb = b_tmp.outerStride(); \
-    } \
-\
-    MKLPREFIX##hemm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
-  } \
-};
-
-EIGEN_MKL_SYMM_R(double, double, d, d)
-EIGEN_MKL_SYMM_R(float, float, f, s)
-EIGEN_MKL_HEMM_R(dcomplex, MKL_Complex16, cd, z)
-EIGEN_MKL_HEMM_R(scomplex, MKL_Complex8, cf, c)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H

Index: 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector.h
+++ 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector.h
@@ -28,24 +28,25 @@
 
 {
 static EIGEN_DONT_INLINE void run(
   Index size,
   const Scalar*  lhs, Index lhsStride,
-  const Scalar* _rhs, Index rhsIncr,
+  const Scalar*  rhs,
   Scalar* res,
   Scalar alpha);
 };
 
 template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs, int Version>
 EIGEN_DONT_INLINE void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Version>::run(
   Index size,
   const Scalar*  lhs, Index lhsStride,
-  const Scalar* _rhs, Index rhsIncr,
+  const Scalar*  rhs,
   Scalar* res,
   Scalar alpha)
 {
   typedef typename packet_traits<Scalar>::type Packet;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
   const Index PacketSize = sizeof(Packet)/sizeof(Scalar);
 
   enum {
     IsRowMajor = StorageOrder==RowMajor ? 1 : 0,
     IsLower = UpLo == Lower ? 1 : 0,
@@ -52,27 +53,17 @@
     FirstTriangular = IsRowMajor == IsLower
   };
 
   conj_helper<Scalar,Scalar,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs,  IsRowMajor), ConjugateRhs> cj0;
   conj_helper<Scalar,Scalar,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> cj1;
-  conj_helper<Scalar,Scalar,NumTraits<Scalar>::IsComplex, ConjugateRhs> cjd;
+  conj_helper<RealScalar,Scalar,false, ConjugateRhs> cjd;
 
   conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs,  IsRowMajor), ConjugateRhs> pcj0;
   conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1;
 
   Scalar cjAlpha = ConjugateRhs ? numext::conj(alpha) : alpha;
 
-  // FIXME this copy is now handled outside product_selfadjoint_vector, so it could probably be removed.
-  // if the rhs is not sequentially stored in memory we copy it to a temporary buffer,
-  // this is because we need to extract packets
-  ei_declare_aligned_stack_constructed_variable(Scalar,rhs,size,rhsIncr==1 ? const_cast<Scalar*>(_rhs) : 0);  
-  if (rhsIncr!=1)
-  {
-    const Scalar* it = _rhs;
-    for (Index i=0; i<size; ++i, it+=rhsIncr)
-      rhs[i] = *it;
-  }
 
   Index bound = (std::max)(Index(0),size-8) & 0xfffffffe;
   if (FirstTriangular)
     bound = size - bound;
 
@@ -90,16 +81,15 @@
     Scalar t2(0);
     Packet ptmp2 = pset1<Packet>(t2);
     Scalar t3(0);
     Packet ptmp3 = pset1<Packet>(t3);
 
-    size_t starti = FirstTriangular ? 0 : j+2;
-    size_t endi   = FirstTriangular ? j : size;
-    size_t alignedStart = (starti) + internal::first_aligned(&res[starti], endi-starti);
-    size_t alignedEnd = alignedStart + ((endi-alignedStart)/(PacketSize))*(PacketSize);
+    Index starti = FirstTriangular ? 0 : j+2;
+    Index endi   = FirstTriangular ? j : size;
+    Index alignedStart = (starti) + internal::first_default_aligned(&res[starti], endi-starti);
+    Index alignedEnd = alignedStart + ((endi-alignedStart)/(PacketSize))*(PacketSize);
 
-    // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed
     res[j]   += cjd.pmul(numext::real(A0[j]), t0);
     res[j+1] += cjd.pmul(numext::real(A1[j+1]), t1);
     if(FirstTriangular)
     {
       res[j]   += cj0.pmul(A1[j],   t1);
@@ -109,23 +99,23 @@
     {
       res[j+1] += cj0.pmul(A0[j+1],t0);
       t2 += cj1.pmul(A0[j+1], rhs[j+1]);
     }
 
-    for (size_t i=starti; i<alignedStart; ++i)
+    for (Index i=starti; i<alignedStart; ++i)
     {
-      res[i] += t0 * A0[i] + t1 * A1[i];
-      t2 += numext::conj(A0[i]) * rhs[i];
-      t3 += numext::conj(A1[i]) * rhs[i];
+      res[i] += cj0.pmul(A0[i], t0) + cj0.pmul(A1[i],t1);
+      t2 += cj1.pmul(A0[i], rhs[i]);
+      t3 += cj1.pmul(A1[i], rhs[i]);
     }
     // Yes this an optimization for gcc 4.3 and 4.4 (=> huge speed up)
     // gcc 4.2 does this optimization automatically.
     const Scalar* EIGEN_RESTRICT a0It  = A0  + alignedStart;
     const Scalar* EIGEN_RESTRICT a1It  = A1  + alignedStart;
     const Scalar* EIGEN_RESTRICT rhsIt = rhs + alignedStart;
           Scalar* EIGEN_RESTRICT resIt = res + alignedStart;
-    for (size_t i=alignedStart; i<alignedEnd; i+=PacketSize)
+    for (Index i=alignedStart; i<alignedEnd; i+=PacketSize)
     {
       Packet A0i = ploadu<Packet>(a0It);  a0It  += PacketSize;
       Packet A1i = ploadu<Packet>(a1It);  a1It  += PacketSize;
       Packet Bi  = ploadu<Packet>(rhsIt); rhsIt += PacketSize; // FIXME should be aligned in most cases
       Packet Xi  = pload <Packet>(resIt);
@@ -133,11 +123,11 @@
       Xi    = pcj0.pmadd(A0i,ptmp0, pcj0.pmadd(A1i,ptmp1,Xi));
       ptmp2 = pcj1.pmadd(A0i,  Bi, ptmp2);
       ptmp3 = pcj1.pmadd(A1i,  Bi, ptmp3);
       pstore(resIt,Xi); resIt += PacketSize;
     }
-    for (size_t i=alignedEnd; i<endi; i++)
+    for (Index i=alignedEnd; i<endi; i++)
     {
       res[i] += cj0.pmul(A0[i], t0) + cj0.pmul(A1[i],t1);
       t2 += cj1.pmul(A0[i], rhs[i]);
       t3 += cj1.pmul(A1[i], rhs[i]);
     }
@@ -149,11 +139,10 @@
   {
     const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride;
 
     Scalar t1 = cjAlpha * rhs[j];
     Scalar t2(0);
-    // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed
     res[j] += cjd.pmul(numext::real(A0[j]), t1);
     for (Index i=FirstTriangular ? 0 : j+1; i<(FirstTriangular ? j : size); i++)
     {
       res[i] += cj0.pmul(A0[i], t1);
       t2 += cj1.pmul(A0[i], rhs[i]);
@@ -167,49 +156,48 @@
 /***************************************************************************
 * Wrapper to product_selfadjoint_vector
 ***************************************************************************/
 
 namespace internal {
-template<typename Lhs, int LhsMode, typename Rhs>
-struct traits<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true> >
-  : traits<ProductBase<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>, Lhs, Rhs> >
-{};
-}
-
-template<typename Lhs, int LhsMode, typename Rhs>
-struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>
-  : public ProductBase<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>, Lhs, Rhs >
-{
-  EIGEN_PRODUCT_PUBLIC_INTERFACE(SelfadjointProductMatrix)
-
-  enum {
-    LhsUpLo = LhsMode&(Upper|Lower)
-  };
-
-  SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
-
-  template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
+
+template<typename Lhs, int LhsMode, typename Rhs>
+struct selfadjoint_product_impl<Lhs,LhsMode,false,Rhs,0,true>
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  typedef internal::blas_traits<Lhs> LhsBlasTraits;
+  typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+  typedef typename internal::remove_all<ActualLhsType>::type ActualLhsTypeCleaned;
+  
+  typedef internal::blas_traits<Rhs> RhsBlasTraits;
+  typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+  typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
+
+  enum { LhsUpLo = LhsMode&(Upper|Lower) };
+
+  template<typename Dest>
+  static void run(Dest& dest, const Lhs &a_lhs, const Rhs &a_rhs, const Scalar& alpha)
   {
     typedef typename Dest::Scalar ResScalar;
-    typedef typename Base::RhsScalar RhsScalar;
-    typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
-    
-    eigen_assert(dest.rows()==m_lhs.rows() && dest.cols()==m_rhs.cols());
-
-    typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(m_lhs);
-    typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(m_rhs);
-
-    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
-                               * RhsBlasTraits::extractScalarFactor(m_rhs);
+    typedef typename Rhs::Scalar RhsScalar;
+    typedef Map<Matrix<ResScalar,Dynamic,1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax,internal::packet_traits<ResScalar>::size)> MappedDest;
+    
+    eigen_assert(dest.rows()==a_lhs.rows() && dest.cols()==a_rhs.cols());
+
+    typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs);
+    typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs);
+
+    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs)
+                               * RhsBlasTraits::extractScalarFactor(a_rhs);
 
     enum {
       EvalToDest = (Dest::InnerStrideAtCompileTime==1),
-      UseRhs = (_ActualRhsType::InnerStrideAtCompileTime==1)
+      UseRhs = (ActualRhsTypeCleaned::InnerStrideAtCompileTime==1)
     };
     
     internal::gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,!EvalToDest> static_dest;
-    internal::gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!UseRhs> static_rhs;
+    internal::gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!UseRhs> static_rhs;
 
     ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
                                                   EvalToDest ? dest.data() : static_dest.data());
                                                   
     ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,rhs.size(),
@@ -216,66 +204,57 @@
         UseRhs ? const_cast<RhsScalar*>(rhs.data()) : static_rhs.data());
     
     if(!EvalToDest)
     {
       #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      int size = dest.size();
+      Index size = dest.size();
       EIGEN_DENSE_STORAGE_CTOR_PLUGIN
       #endif
       MappedDest(actualDestPtr, dest.size()) = dest;
     }
       
     if(!UseRhs)
     {
       #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      int size = rhs.size();
+      Index size = rhs.size();
       EIGEN_DENSE_STORAGE_CTOR_PLUGIN
       #endif
-      Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, rhs.size()) = rhs;
+      Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, rhs.size()) = rhs;
     }
       
       
-    internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run
+    internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor,
+                                                int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run
       (
         lhs.rows(),                             // size
         &lhs.coeffRef(0,0),  lhs.outerStride(), // lhs info
-        actualRhsPtr, 1,                        // rhs info
+        actualRhsPtr,                           // rhs info
         actualDestPtr,                          // result info
         actualAlpha                             // scale factor
       );
     
     if(!EvalToDest)
       dest = MappedDest(actualDestPtr, dest.size());
   }
 };
 
-namespace internal {
-template<typename Lhs, typename Rhs, int RhsMode>
-struct traits<SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false> >
-  : traits<ProductBase<SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false>, Lhs, Rhs> >
-{};
-}
-
-template<typename Lhs, typename Rhs, int RhsMode>
-struct SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false>
-  : public ProductBase<SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false>, Lhs, Rhs >
-{
-  EIGEN_PRODUCT_PUBLIC_INTERFACE(SelfadjointProductMatrix)
-
-  enum {
-    RhsUpLo = RhsMode&(Upper|Lower)
-  };
-
-  SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
-
-  template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
+template<typename Lhs, typename Rhs, int RhsMode>
+struct selfadjoint_product_impl<Lhs,0,true,Rhs,RhsMode,false>
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  enum { RhsUpLo = RhsMode&(Upper|Lower)  };
+
+  template<typename Dest>
+  static void run(Dest& dest, const Lhs &a_lhs, const Rhs &a_rhs, const Scalar& alpha)
   {
     // let's simply transpose the product
     Transpose<Dest> destT(dest);
-    SelfadjointProductMatrix<Transpose<const Rhs>, int(RhsUpLo)==Upper ? Lower : Upper, false,
-                             Transpose<const Lhs>, 0, true>(m_rhs.transpose(), m_lhs.transpose()).scaleAndAddTo(destT, alpha);
+    selfadjoint_product_impl<Transpose<const Rhs>, int(RhsUpLo)==Upper ? Lower : Upper, false,
+                             Transpose<const Lhs>, 0, true>::run(destT, a_rhs.transpose(), a_lhs.transpose(), alpha);
   }
 };
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_H

ADDED   3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_BLAS.h
Index: 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_BLAS.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_BLAS.h
+++ 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_BLAS.h
@@ -0,0 +1,111 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to BLAS F77
+ *   Selfadjoint matrix-vector product functionality based on ?SYMV/HEMV.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_BLAS_H
+#define EIGEN_SELFADJOINT_MATRIX_VECTOR_BLAS_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************************************************
+* This file implements selfadjoint matrix-vector multiplication using BLAS
+**********************************************************************/
+
+// symv/hemv specialization
+
+template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs>
+struct selfadjoint_matrix_vector_product_symv :
+  selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn> {};
+
+#define EIGEN_BLAS_SYMV_SPECIALIZE(Scalar) \
+template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
+struct selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Specialized> { \
+static void run( \
+  Index size, const Scalar*  lhs, Index lhsStride, \
+  const Scalar* _rhs, Scalar* res, Scalar alpha) { \
+    enum {\
+      IsColMajor = StorageOrder==ColMajor \
+    }; \
+    if (IsColMajor == ConjugateLhs) {\
+      selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn>::run( \
+        size, lhs, lhsStride, _rhs, res, alpha);  \
+    } else {\
+      selfadjoint_matrix_vector_product_symv<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs>::run( \
+        size, lhs, lhsStride, _rhs, res, alpha);  \
+    }\
+  } \
+}; \
+
+EIGEN_BLAS_SYMV_SPECIALIZE(double)
+EIGEN_BLAS_SYMV_SPECIALIZE(float)
+EIGEN_BLAS_SYMV_SPECIALIZE(dcomplex)
+EIGEN_BLAS_SYMV_SPECIALIZE(scomplex)
+
+#define EIGEN_BLAS_SYMV_SPECIALIZATION(EIGTYPE,BLASTYPE,BLASFUNC) \
+template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
+struct selfadjoint_matrix_vector_product_symv<EIGTYPE,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs> \
+{ \
+typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> SYMVVector;\
+\
+static void run( \
+Index size, const EIGTYPE*  lhs, Index lhsStride, \
+const EIGTYPE* _rhs, EIGTYPE* res, EIGTYPE alpha) \
+{ \
+  enum {\
+    IsRowMajor = StorageOrder==RowMajor ? 1 : 0, \
+    IsLower = UpLo == Lower ? 1 : 0 \
+  }; \
+  BlasIndex n=convert_index<BlasIndex>(size), lda=convert_index<BlasIndex>(lhsStride), incx=1, incy=1; \
+  EIGTYPE beta(1); \
+  const EIGTYPE *x_ptr; \
+  char uplo=(IsRowMajor) ? (IsLower ? 'U' : 'L') : (IsLower ? 'L' : 'U'); \
+  SYMVVector x_tmp; \
+  if (ConjugateRhs) { \
+    Map<const SYMVVector, 0 > map_x(_rhs,size,1); \
+    x_tmp=map_x.conjugate(); \
+    x_ptr=x_tmp.data(); \
+  } else x_ptr=_rhs; \
+  BLASFUNC(&uplo, &n, &numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, &numext::real_ref(beta), (BLASTYPE*)res, &incy); \
+}\
+};
+
+EIGEN_BLAS_SYMV_SPECIALIZATION(double,   double, dsymv_)
+EIGEN_BLAS_SYMV_SPECIALIZATION(float,    float,  ssymv_)
+EIGEN_BLAS_SYMV_SPECIALIZATION(dcomplex, double, zhemv_)
+EIGEN_BLAS_SYMV_SPECIALIZATION(scomplex, float,  chemv_)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_BLAS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h
Index: 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h
@@ -1,114 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   Selfadjoint matrix-vector product functionality based on ?SYMV/HEMV.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
-#define EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
-
-namespace Eigen { 
-
-namespace internal {
-
-/**********************************************************************
-* This file implements selfadjoint matrix-vector multiplication using BLAS
-**********************************************************************/
-
-// symv/hemv specialization
-
-template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs>
-struct selfadjoint_matrix_vector_product_symv :
-  selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn> {};
-
-#define EIGEN_MKL_SYMV_SPECIALIZE(Scalar) \
-template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
-struct selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Specialized> { \
-static void run( \
-  Index size, const Scalar*  lhs, Index lhsStride, \
-  const Scalar* _rhs, Index rhsIncr, Scalar* res, Scalar alpha) { \
-    enum {\
-      IsColMajor = StorageOrder==ColMajor \
-    }; \
-    if (IsColMajor == ConjugateLhs) {\
-      selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn>::run( \
-        size, lhs, lhsStride, _rhs, rhsIncr, res, alpha);  \
-    } else {\
-      selfadjoint_matrix_vector_product_symv<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs>::run( \
-        size, lhs, lhsStride, _rhs, rhsIncr, res, alpha);  \
-    }\
-  } \
-}; \
-
-EIGEN_MKL_SYMV_SPECIALIZE(double)
-EIGEN_MKL_SYMV_SPECIALIZE(float)
-EIGEN_MKL_SYMV_SPECIALIZE(dcomplex)
-EIGEN_MKL_SYMV_SPECIALIZE(scomplex)
-
-#define EIGEN_MKL_SYMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLFUNC) \
-template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
-struct selfadjoint_matrix_vector_product_symv<EIGTYPE,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs> \
-{ \
-typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> SYMVVector;\
-\
-static void run( \
-Index size, const EIGTYPE*  lhs, Index lhsStride, \
-const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* res, EIGTYPE alpha) \
-{ \
-  enum {\
-    IsRowMajor = StorageOrder==RowMajor ? 1 : 0, \
-    IsLower = UpLo == Lower ? 1 : 0 \
-  }; \
-  MKL_INT n=size, lda=lhsStride, incx=rhsIncr, incy=1; \
-  MKLTYPE alpha_, beta_; \
-  const EIGTYPE *x_ptr, myone(1); \
-  char uplo=(IsRowMajor) ? (IsLower ? 'U' : 'L') : (IsLower ? 'L' : 'U'); \
-  assign_scalar_eig2mkl(alpha_, alpha); \
-  assign_scalar_eig2mkl(beta_, myone); \
-  SYMVVector x_tmp; \
-  if (ConjugateRhs) { \
-    Map<const SYMVVector, 0, InnerStride<> > map_x(_rhs,size,1,InnerStride<>(incx)); \
-    x_tmp=map_x.conjugate(); \
-    x_ptr=x_tmp.data(); \
-    incx=1; \
-  } else x_ptr=_rhs; \
-  MKLFUNC(&uplo, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \
-}\
-};
-
-EIGEN_MKL_SYMV_SPECIALIZATION(double,   double,        dsymv)
-EIGEN_MKL_SYMV_SPECIALIZATION(float,    float,         ssymv)
-EIGEN_MKL_SYMV_SPECIALIZATION(dcomplex, MKL_Complex16, zhemv)
-EIGEN_MKL_SYMV_SPECIALIZATION(scomplex, MKL_Complex8,  chemv)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H

Index: 3rd_party/eigen/Eigen/src/Core/products/SelfadjointProduct.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/SelfadjointProduct.h
+++ 3rd_party/eigen/Eigen/src/Core/products/SelfadjointProduct.h
@@ -51,11 +51,10 @@
 struct selfadjoint_product_selector<MatrixType,OtherType,UpLo,true>
 {
   static void run(MatrixType& mat, const OtherType& other, const typename MatrixType::Scalar& alpha)
   {
     typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
     typedef internal::blas_traits<OtherType> OtherBlasTraits;
     typedef typename OtherBlasTraits::DirectLinearAccessType ActualOtherType;
     typedef typename internal::remove_all<ActualOtherType>::type _ActualOtherType;
     typename internal::add_const_on_value_type<ActualOtherType>::type actualOther = OtherBlasTraits::extract(other.derived());
 
@@ -84,27 +83,38 @@
 struct selfadjoint_product_selector<MatrixType,OtherType,UpLo,false>
 {
   static void run(MatrixType& mat, const OtherType& other, const typename MatrixType::Scalar& alpha)
   {
     typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
     typedef internal::blas_traits<OtherType> OtherBlasTraits;
     typedef typename OtherBlasTraits::DirectLinearAccessType ActualOtherType;
     typedef typename internal::remove_all<ActualOtherType>::type _ActualOtherType;
     typename internal::add_const_on_value_type<ActualOtherType>::type actualOther = OtherBlasTraits::extract(other.derived());
 
     Scalar actualAlpha = alpha * OtherBlasTraits::extractScalarFactor(other.derived());
 
-    enum { IsRowMajor = (internal::traits<MatrixType>::Flags&RowMajorBit) ? 1 : 0 };
+    enum {
+      IsRowMajor = (internal::traits<MatrixType>::Flags&RowMajorBit) ? 1 : 0,
+      OtherIsRowMajor = _ActualOtherType::Flags&RowMajorBit ? 1 : 0
+    };
+
+    Index size = mat.cols();
+    Index depth = actualOther.cols();
+
+    typedef internal::gemm_blocking_space<IsRowMajor ? RowMajor : ColMajor,Scalar,Scalar,
+              MatrixType::MaxColsAtCompileTime, MatrixType::MaxColsAtCompileTime, _ActualOtherType::MaxColsAtCompileTime> BlockingType;
+
+    BlockingType blocking(size, size, depth, 1, false);
+
 
     internal::general_matrix_matrix_triangular_product<Index,
-      Scalar, _ActualOtherType::Flags&RowMajorBit ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
-      Scalar, _ActualOtherType::Flags&RowMajorBit ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
-      MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor, UpLo>
-      ::run(mat.cols(), actualOther.cols(),
+      Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
+      Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
+      IsRowMajor ? RowMajor : ColMajor, UpLo>
+      ::run(size, depth,
             &actualOther.coeffRef(0,0), actualOther.outerStride(), &actualOther.coeffRef(0,0), actualOther.outerStride(),
-            mat.data(), mat.outerStride(), actualAlpha);
+            mat.data(), mat.outerStride(), actualAlpha, blocking);
   }
 };
 
 // high level API
 

Index: 3rd_party/eigen/Eigen/src/Core/products/SelfadjointRank2Update.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/SelfadjointRank2Update.h
+++ 3rd_party/eigen/Eigen/src/Core/products/SelfadjointRank2Update.h
@@ -77,17 +77,17 @@
   Scalar actualAlpha = alpha * UBlasTraits::extractScalarFactor(u.derived())
                              * numext::conj(VBlasTraits::extractScalarFactor(v.derived()));
   if (IsRowMajor)
     actualAlpha = numext::conj(actualAlpha);
 
-  internal::selfadjoint_rank2_update_selector<Scalar, Index,
-    typename internal::remove_all<typename internal::conj_expr_if<IsRowMajor ^ UBlasTraits::NeedToConjugate,_ActualUType>::type>::type,
-    typename internal::remove_all<typename internal::conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::type>::type,
+  typedef typename internal::remove_all<typename internal::conj_expr_if<IsRowMajor ^ UBlasTraits::NeedToConjugate,_ActualUType>::type>::type UType;
+  typedef typename internal::remove_all<typename internal::conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::type>::type VType;
+  internal::selfadjoint_rank2_update_selector<Scalar, Index, UType, VType,
     (IsRowMajor ? int(UpLo==Upper ? Lower : Upper) : UpLo)>
-    ::run(_expression().const_cast_derived().data(),_expression().outerStride(),actualU,actualV,actualAlpha);
+    ::run(_expression().const_cast_derived().data(),_expression().outerStride(),UType(actualU),VType(actualV),actualAlpha);
 
   return *this;
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SELFADJOINTRANK2UPTADE_H

Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h
@@ -106,43 +106,49 @@
                                                         LhsStorageOrder,ConjugateLhs,
                                                         RhsStorageOrder,ConjugateRhs,ColMajor,Version>::run(
     Index _rows, Index _cols, Index _depth,
     const Scalar* _lhs, Index lhsStride,
     const Scalar* _rhs, Index rhsStride,
-    Scalar* res,        Index resStride,
+    Scalar* _res,        Index resStride,
     const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
   {
     // strip zeros
     Index diagSize  = (std::min)(_rows,_depth);
     Index rows      = IsLower ? _rows : diagSize;
     Index depth     = IsLower ? diagSize : _depth;
     Index cols      = _cols;
     
-    const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
-    const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
+    typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
+    typedef const_blas_data_mapper<Scalar, Index, RhsStorageOrder> RhsMapper;
+    typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
+    LhsMapper lhs(_lhs,lhsStride);
+    RhsMapper rhs(_rhs,rhsStride);
+    ResMapper res(_res, resStride);
 
     Index kc = blocking.kc();                   // cache block size along the K direction
     Index mc = (std::min)(rows,blocking.mc());  // cache block size along the M direction
+    // The small panel size must not be larger than blocking size.
+    // Usually this should never be the case because SmallPanelWidth^2 is very small
+    // compared to L2 cache size, but let's be safe:
+    Index panelWidth = (std::min)(Index(SmallPanelWidth),(std::min)(kc,mc));
 
     std::size_t sizeA = kc*mc;
     std::size_t sizeB = kc*cols;
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
 
     ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
     ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW());
 
-    Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer;
+    Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer((internal::constructor_without_unaligned_array_assert()));
     triangularBuffer.setZero();
     if((Mode&ZeroDiag)==ZeroDiag)
       triangularBuffer.diagonal().setZero();
     else
       triangularBuffer.diagonal().setOnes();
 
-    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
-    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
-    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
+    gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
+    gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+    gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr,RhsStorageOrder> pack_rhs;
 
     for(Index k2=IsLower ? depth : 0;
         IsLower ? k2>0 : k2<depth;
         IsLower ? k2-=kc : k2+=kc)
     {
@@ -154,11 +160,11 @@
       {
         actual_kc = rows-k2;
         k2 = k2+actual_kc-kc;
       }
 
-      pack_rhs(blockB, &rhs(actual_k2,0), rhsStride, actual_kc, cols);
+      pack_rhs(blockB, rhs.getSubMapper(actual_k2,0), actual_kc, cols);
 
       // the selected lhs's panel has to be split in three different parts:
       //  1 - the part which is zero => skip it
       //  2 - the diagonal block => special kernel
       //  3 - the dense panel below (lower case) or above (upper case) the diagonal block => GEPP
@@ -165,13 +171,13 @@
 
       // the block diagonal, if any:
       if(IsLower || actual_k2<rows)
       {
         // for each small vertical panels of lhs
-        for (Index k1=0; k1<actual_kc; k1+=SmallPanelWidth)
+        for (Index k1=0; k1<actual_kc; k1+=panelWidth)
         {
-          Index actualPanelWidth = std::min<Index>(actual_kc-k1, SmallPanelWidth);
+          Index actualPanelWidth = std::min<Index>(actual_kc-k1, panelWidth);
           Index lengthTarget = IsLower ? actual_kc-k1-actualPanelWidth : k1;
           Index startBlock   = actual_k2+k1;
           Index blockBOffset = k1;
 
           // => GEBP with the micro triangular block
@@ -182,24 +188,26 @@
             if (SetDiag)
               triangularBuffer.coeffRef(k,k) = lhs(startBlock+k,startBlock+k);
             for (Index i=IsLower ? k+1 : 0; IsLower ? i<actualPanelWidth : i<k; ++i)
               triangularBuffer.coeffRef(i,k) = lhs(startBlock+i,startBlock+k);
           }
-          pack_lhs(blockA, triangularBuffer.data(), triangularBuffer.outerStride(), actualPanelWidth, actualPanelWidth);
+          pack_lhs(blockA, LhsMapper(triangularBuffer.data(), triangularBuffer.outerStride()), actualPanelWidth, actualPanelWidth);
 
-          gebp_kernel(res+startBlock, resStride, blockA, blockB, actualPanelWidth, actualPanelWidth, cols, alpha,
-                      actualPanelWidth, actual_kc, 0, blockBOffset, blockW);
+          gebp_kernel(res.getSubMapper(startBlock, 0), blockA, blockB,
+                      actualPanelWidth, actualPanelWidth, cols, alpha,
+                      actualPanelWidth, actual_kc, 0, blockBOffset);
 
           // GEBP with remaining micro panel
           if (lengthTarget>0)
           {
             Index startTarget  = IsLower ? actual_k2+k1+actualPanelWidth : actual_k2;
 
-            pack_lhs(blockA, &lhs(startTarget,startBlock), lhsStride, actualPanelWidth, lengthTarget);
+            pack_lhs(blockA, lhs.getSubMapper(startTarget,startBlock), actualPanelWidth, lengthTarget);
 
-            gebp_kernel(res+startTarget, resStride, blockA, blockB, lengthTarget, actualPanelWidth, cols, alpha,
-                        actualPanelWidth, actual_kc, 0, blockBOffset, blockW);
+            gebp_kernel(res.getSubMapper(startTarget, 0), blockA, blockB,
+                        lengthTarget, actualPanelWidth, cols, alpha,
+                        actualPanelWidth, actual_kc, 0, blockBOffset);
           }
         }
       }
       // the part below (lower case) or above (upper case) the diagonal => GEPP
       {
@@ -206,14 +214,15 @@
         Index start = IsLower ? k2 : 0;
         Index end   = IsLower ? rows : (std::min)(actual_k2,rows);
         for(Index i2=start; i2<end; i2+=mc)
         {
           const Index actual_mc = (std::min)(i2+mc,end)-i2;
-          gemm_pack_lhs<Scalar, Index, Traits::mr,Traits::LhsProgress, LhsStorageOrder,false>()
-            (blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc);
+          gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr,Traits::LhsProgress, LhsStorageOrder,false>()
+            (blockA, lhs.getSubMapper(i2, actual_k2), actual_kc, actual_mc);
 
-          gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha, -1, -1, 0, 0, blockW);
+          gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc,
+                      actual_kc, cols, alpha, -1, -1, 0, 0);
         }
       }
     }
   }
 
@@ -247,44 +256,47 @@
                                                         LhsStorageOrder,ConjugateLhs,
                                                         RhsStorageOrder,ConjugateRhs,ColMajor,Version>::run(
     Index _rows, Index _cols, Index _depth,
     const Scalar* _lhs, Index lhsStride,
     const Scalar* _rhs, Index rhsStride,
-    Scalar* res,        Index resStride,
+    Scalar* _res,        Index resStride,
     const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
   {
+    const Index PacketBytes = packet_traits<Scalar>::size*sizeof(Scalar);
     // strip zeros
     Index diagSize  = (std::min)(_cols,_depth);
     Index rows      = _rows;
     Index depth     = IsLower ? _depth : diagSize;
     Index cols      = IsLower ? diagSize : _cols;
     
-    const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
-    const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
+    typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
+    typedef const_blas_data_mapper<Scalar, Index, RhsStorageOrder> RhsMapper;
+    typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
+    LhsMapper lhs(_lhs,lhsStride);
+    RhsMapper rhs(_rhs,rhsStride);
+    ResMapper res(_res, resStride);
 
     Index kc = blocking.kc();                   // cache block size along the K direction
     Index mc = (std::min)(rows,blocking.mc());  // cache block size along the M direction
 
     std::size_t sizeA = kc*mc;
-    std::size_t sizeB = kc*cols;
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
+    std::size_t sizeB = kc*cols+EIGEN_MAX_ALIGN_BYTES/sizeof(Scalar);
 
     ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
     ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW());
 
-    Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer;
+    Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer((internal::constructor_without_unaligned_array_assert()));
     triangularBuffer.setZero();
     if((Mode&ZeroDiag)==ZeroDiag)
       triangularBuffer.diagonal().setZero();
     else
       triangularBuffer.diagonal().setOnes();
 
-    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
-    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
-    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
-    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder,false,true> pack_rhs_panel;
+    gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
+    gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+    gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr,RhsStorageOrder> pack_rhs;
+    gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr,RhsStorageOrder,false,true> pack_rhs_panel;
 
     for(Index k2=IsLower ? 0 : depth;
         IsLower ? k2<depth  : k2>0;
         IsLower ? k2+=kc   : k2-=kc)
     {
@@ -302,12 +314,13 @@
       Index rs = IsLower ? (std::min)(cols,actual_k2) : cols - k2;
       // size of the triangular part
       Index ts = (IsLower && actual_k2>=cols) ? 0 : actual_kc;
 
       Scalar* geb = blockB+ts*ts;
+      geb = geb + internal::first_aligned<PacketBytes>(geb,PacketBytes/sizeof(Scalar));
 
-      pack_rhs(geb, &rhs(actual_k2,IsLower ? 0 : k2), rhsStride, actual_kc, rs);
+      pack_rhs(geb, rhs.getSubMapper(actual_k2,IsLower ? 0 : k2), actual_kc, rs);
 
       // pack the triangular part of the rhs padding the unrolled blocks with zeros
       if(ts>0)
       {
         for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth)
@@ -316,11 +329,11 @@
           Index actual_j2 = actual_k2 + j2;
           Index panelOffset = IsLower ? j2+actualPanelWidth : 0;
           Index panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
           // general part
           pack_rhs_panel(blockB+j2*actual_kc,
-                         &rhs(actual_k2+panelOffset, actual_j2), rhsStride,
+                         rhs.getSubMapper(actual_k2+panelOffset, actual_j2),
                          panelLength, actualPanelWidth,
                          actual_kc, panelOffset);
 
           // append the triangular part via a temporary buffer
           for (Index j=0;j<actualPanelWidth;++j)
@@ -330,20 +343,20 @@
             for (Index k=IsLower ? j+1 : 0; IsLower ? k<actualPanelWidth : k<j; ++k)
               triangularBuffer.coeffRef(k,j) = rhs(actual_j2+k,actual_j2+j);
           }
 
           pack_rhs_panel(blockB+j2*actual_kc,
-                         triangularBuffer.data(), triangularBuffer.outerStride(),
+                         RhsMapper(triangularBuffer.data(), triangularBuffer.outerStride()),
                          actualPanelWidth, actualPanelWidth,
                          actual_kc, j2);
         }
       }
 
       for (Index i2=0; i2<rows; i2+=mc)
       {
         const Index actual_mc = (std::min)(mc,rows-i2);
-        pack_lhs(blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc);
+        pack_lhs(blockA, lhs.getSubMapper(i2, actual_k2), actual_kc, actual_mc);
 
         // triangular kernel
         if(ts>0)
         {
           for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth)
@@ -350,53 +363,52 @@
           {
             Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth);
             Index panelLength = IsLower ? actual_kc-j2 : j2+actualPanelWidth;
             Index blockOffset = IsLower ? j2 : 0;
 
-            gebp_kernel(res+i2+(actual_k2+j2)*resStride, resStride,
+            gebp_kernel(res.getSubMapper(i2, actual_k2 + j2),
                         blockA, blockB+j2*actual_kc,
                         actual_mc, panelLength, actualPanelWidth,
                         alpha,
                         actual_kc, actual_kc,  // strides
-                        blockOffset, blockOffset,// offsets
-                        blockW); // workspace
+                        blockOffset, blockOffset);// offsets
           }
         }
-        gebp_kernel(res+i2+(IsLower ? 0 : k2)*resStride, resStride,
+        gebp_kernel(res.getSubMapper(i2, IsLower ? 0 : k2),
                     blockA, geb, actual_mc, actual_kc, rs,
                     alpha,
-                    -1, -1, 0, 0, blockW);
+                    -1, -1, 0, 0);
       }
     }
   }
 
 /***************************************************************************
 * Wrapper to product_triangular_matrix_matrix
 ***************************************************************************/
 
-template<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs>
-struct traits<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false> >
-  : traits<ProductBase<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>, Lhs, Rhs> >
-{};
-
 } // end namespace internal
 
-template<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs>
-struct TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>
-  : public ProductBase<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>, Lhs, Rhs >
-{
-  EIGEN_PRODUCT_PUBLIC_INTERFACE(TriangularProduct)
-
-  TriangularProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
-
-  template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
-  {
-    typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(m_lhs);
-    typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(m_rhs);
-
-    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
-                               * RhsBlasTraits::extractScalarFactor(m_rhs);
+namespace internal {
+template<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs>
+struct triangular_product_impl<Mode,LhsIsTriangular,Lhs,false,Rhs,false>
+{
+  template<typename Dest> static void run(Dest& dst, const Lhs &a_lhs, const Rhs &a_rhs, const typename Dest::Scalar& alpha)
+  {
+    typedef typename Dest::Scalar     Scalar;
+    
+    typedef internal::blas_traits<Lhs> LhsBlasTraits;
+    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+    typedef typename internal::remove_all<ActualLhsType>::type ActualLhsTypeCleaned;
+    typedef internal::blas_traits<Rhs> RhsBlasTraits;
+    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+    typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
+    
+    typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs);
+    typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs);
+
+    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs)
+                               * RhsBlasTraits::extractScalarFactor(a_rhs);
 
     typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
               Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxColsAtCompileTime,4> BlockingType;
 
     enum { IsLower = (Mode&Lower) == Lower };
@@ -403,25 +415,27 @@
     Index stripedRows  = ((!LhsIsTriangular) || (IsLower))  ? lhs.rows() : (std::min)(lhs.rows(),lhs.cols());
     Index stripedCols  = ((LhsIsTriangular)  || (!IsLower)) ? rhs.cols() : (std::min)(rhs.cols(),rhs.rows());
     Index stripedDepth = LhsIsTriangular ? ((!IsLower) ? lhs.cols() : (std::min)(lhs.cols(),lhs.rows()))
                                          : ((IsLower)  ? rhs.rows() : (std::min)(rhs.rows(),rhs.cols()));
 
-    BlockingType blocking(stripedRows, stripedCols, stripedDepth);
+    BlockingType blocking(stripedRows, stripedCols, stripedDepth, 1, false);
 
     internal::product_triangular_matrix_matrix<Scalar, Index,
       Mode, LhsIsTriangular,
-      (internal::traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
-      (internal::traits<_ActualRhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
+      (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
+      (internal::traits<ActualRhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
       (internal::traits<Dest          >::Flags&RowMajorBit) ? RowMajor : ColMajor>
       ::run(
         stripedRows, stripedCols, stripedDepth,   // sizes
-        &lhs.coeffRef(0,0),    lhs.outerStride(), // lhs info
-        &rhs.coeffRef(0,0),    rhs.outerStride(), // rhs info
+        &lhs.coeffRef(0,0), lhs.outerStride(),    // lhs info
+        &rhs.coeffRef(0,0), rhs.outerStride(),    // rhs info
         &dst.coeffRef(0,0), dst.outerStride(),    // result info
         actualAlpha, blocking
       );
   }
 };
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_H

ADDED   3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_BLAS.h
Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_BLAS.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_BLAS.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_BLAS.h
@@ -0,0 +1,302 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to BLAS F77
+ *   Triangular matrix * matrix product functionality based on ?TRMM.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_TRIANGULAR_MATRIX_MATRIX_BLAS_H
+#define EIGEN_TRIANGULAR_MATRIX_MATRIX_BLAS_H
+
+namespace Eigen { 
+
+namespace internal {
+
+
+template <typename Scalar, typename Index,
+          int Mode, bool LhsIsTriangular,
+          int LhsStorageOrder, bool ConjugateLhs,
+          int RhsStorageOrder, bool ConjugateRhs,
+          int ResStorageOrder>
+struct product_triangular_matrix_matrix_trmm :
+       product_triangular_matrix_matrix<Scalar,Index,Mode,
+          LhsIsTriangular,LhsStorageOrder,ConjugateLhs,
+          RhsStorageOrder, ConjugateRhs, ResStorageOrder, BuiltIn> {};
+
+
+// try to go to BLAS specialization
+#define EIGEN_BLAS_TRMM_SPECIALIZE(Scalar, LhsIsTriangular) \
+template <typename Index, int Mode, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_triangular_matrix_matrix<Scalar,Index, Mode, LhsIsTriangular, \
+           LhsStorageOrder,ConjugateLhs, RhsStorageOrder,ConjugateRhs,ColMajor,Specialized> { \
+  static inline void run(Index _rows, Index _cols, Index _depth, const Scalar* _lhs, Index lhsStride,\
+    const Scalar* _rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha, level3_blocking<Scalar,Scalar>& blocking) { \
+      product_triangular_matrix_matrix_trmm<Scalar,Index,Mode, \
+        LhsIsTriangular,LhsStorageOrder,ConjugateLhs, \
+        RhsStorageOrder, ConjugateRhs, ColMajor>::run( \
+        _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
+  } \
+};
+
+EIGEN_BLAS_TRMM_SPECIALIZE(double, true)
+EIGEN_BLAS_TRMM_SPECIALIZE(double, false)
+EIGEN_BLAS_TRMM_SPECIALIZE(dcomplex, true)
+EIGEN_BLAS_TRMM_SPECIALIZE(dcomplex, false)
+EIGEN_BLAS_TRMM_SPECIALIZE(float, true)
+EIGEN_BLAS_TRMM_SPECIALIZE(float, false)
+EIGEN_BLAS_TRMM_SPECIALIZE(scomplex, true)
+EIGEN_BLAS_TRMM_SPECIALIZE(scomplex, false)
+
+// implements col-major += alpha * op(triangular) * op(general)
+#define EIGEN_BLAS_TRMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
+template <typename Index, int Mode, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
+         LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor> \
+{ \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    LowUp = IsLower ? Lower : Upper, \
+    conjA = ((LhsStorageOrder==ColMajor) && ConjugateLhs) ? 1 : 0 \
+  }; \
+\
+  static void run( \
+    Index _rows, Index _cols, Index _depth, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+  { \
+   Index diagSize  = (std::min)(_rows,_depth); \
+   Index rows      = IsLower ? _rows : diagSize; \
+   Index depth     = IsLower ? diagSize : _depth; \
+   Index cols      = _cols; \
+\
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> MatrixLhs; \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs; \
+\
+/* Non-square case - doesn't fit to BLAS ?TRMM. Fall to default triangular product or call BLAS ?GEMM*/ \
+   if (rows != depth) { \
+\
+     /* FIXME handle mkl_domain_get_max_threads */ \
+     /*int nthr = mkl_domain_get_max_threads(EIGEN_BLAS_DOMAIN_BLAS);*/ int nthr = 1;\
+\
+     if (((nthr==1) && (((std::max)(rows,depth)-diagSize)/(double)diagSize < 0.5))) { \
+     /* Most likely no benefit to call TRMM or GEMM from BLAS */ \
+       product_triangular_matrix_matrix<EIGTYPE,Index,Mode,true, \
+       LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
+           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
+     /*std::cout << "TRMM_L: A is not square! Go to Eigen TRMM implementation!\n";*/ \
+     } else { \
+     /* Make sense to call GEMM */ \
+       Map<const MatrixLhs, 0, OuterStride<> > lhsMap(_lhs,rows,depth,OuterStride<>(lhsStride)); \
+       MatrixLhs aa_tmp=lhsMap.template triangularView<Mode>(); \
+       BlasIndex aStride = convert_index<BlasIndex>(aa_tmp.outerStride()); \
+       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> gemm_blocking(_rows,_cols,_depth, 1, true); \
+       general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
+       rows, cols, depth, aa_tmp.data(), aStride, _rhs, rhsStride, res, resStride, alpha, gemm_blocking, 0); \
+\
+     /*std::cout << "TRMM_L: A is not square! Go to BLAS GEMM implementation! " << nthr<<" \n";*/ \
+     } \
+     return; \
+   } \
+   char side = 'L', transa, uplo, diag = 'N'; \
+   EIGTYPE *b; \
+   const EIGTYPE *a; \
+   BlasIndex m, n, lda, ldb; \
+\
+/* Set m, n */ \
+   m = convert_index<BlasIndex>(diagSize); \
+   n = convert_index<BlasIndex>(cols); \
+\
+/* Set trans */ \
+   transa = (LhsStorageOrder==RowMajor) ? ((ConjugateLhs) ? 'C' : 'T') : 'N'; \
+\
+/* Set b, ldb */ \
+   Map<const MatrixRhs, 0, OuterStride<> > rhs(_rhs,depth,cols,OuterStride<>(rhsStride)); \
+   MatrixX##EIGPREFIX b_tmp; \
+\
+   if (ConjugateRhs) b_tmp = rhs.conjugate(); else b_tmp = rhs; \
+   b = b_tmp.data(); \
+   ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
+\
+/* Set uplo */ \
+   uplo = IsLower ? 'L' : 'U'; \
+   if (LhsStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
+/* Set a, lda */ \
+   Map<const MatrixLhs, 0, OuterStride<> > lhs(_lhs,rows,depth,OuterStride<>(lhsStride)); \
+   MatrixLhs a_tmp; \
+\
+   if ((conjA!=0) || (SetDiag==0)) { \
+     if (conjA) a_tmp = lhs.conjugate(); else a_tmp = lhs; \
+     if (IsZeroDiag) \
+       a_tmp.diagonal().setZero(); \
+     else if (IsUnitDiag) \
+       a_tmp.diagonal().setOnes();\
+     a = a_tmp.data(); \
+     lda = convert_index<BlasIndex>(a_tmp.outerStride()); \
+   } else { \
+     a = _lhs; \
+     lda = convert_index<BlasIndex>(lhsStride); \
+   } \
+   /*std::cout << "TRMM_L: A is square! Go to BLAS TRMM implementation! \n";*/ \
+/* call ?trmm*/ \
+   BLASPREFIX##trmm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \
+\
+/* Add op(a_triangular)*b into res*/ \
+   Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \
+   res_tmp=res_tmp+b_tmp; \
+  } \
+};
+
+EIGEN_BLAS_TRMM_L(double, double, d, d)
+EIGEN_BLAS_TRMM_L(dcomplex, double, cd, z)
+EIGEN_BLAS_TRMM_L(float, float, f, s)
+EIGEN_BLAS_TRMM_L(scomplex, float, cf, c)
+
+// implements col-major += alpha * op(general) * op(triangular)
+#define EIGEN_BLAS_TRMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
+template <typename Index, int Mode, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
+         LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor> \
+{ \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    LowUp = IsLower ? Lower : Upper, \
+    conjA = ((RhsStorageOrder==ColMajor) && ConjugateRhs) ? 1 : 0 \
+  }; \
+\
+  static void run( \
+    Index _rows, Index _cols, Index _depth, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+  { \
+   Index diagSize  = (std::min)(_cols,_depth); \
+   Index rows      = _rows; \
+   Index depth     = IsLower ? _depth : diagSize; \
+   Index cols      = IsLower ? diagSize : _cols; \
+\
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> MatrixLhs; \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs; \
+\
+/* Non-square case - doesn't fit to BLAS ?TRMM. Fall to default triangular product or call BLAS ?GEMM*/ \
+   if (cols != depth) { \
+\
+     int nthr = 1 /*mkl_domain_get_max_threads(EIGEN_BLAS_DOMAIN_BLAS)*/; \
+\
+     if ((nthr==1) && (((std::max)(cols,depth)-diagSize)/(double)diagSize < 0.5)) { \
+     /* Most likely no benefit to call TRMM or GEMM from BLAS*/ \
+       product_triangular_matrix_matrix<EIGTYPE,Index,Mode,false, \
+       LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
+           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
+       /*std::cout << "TRMM_R: A is not square! Go to Eigen TRMM implementation!\n";*/ \
+     } else { \
+     /* Make sense to call GEMM */ \
+       Map<const MatrixRhs, 0, OuterStride<> > rhsMap(_rhs,depth,cols, OuterStride<>(rhsStride)); \
+       MatrixRhs aa_tmp=rhsMap.template triangularView<Mode>(); \
+       BlasIndex aStride = convert_index<BlasIndex>(aa_tmp.outerStride()); \
+       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> gemm_blocking(_rows,_cols,_depth, 1, true); \
+       general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
+       rows, cols, depth, _lhs, lhsStride, aa_tmp.data(), aStride, res, resStride, alpha, gemm_blocking, 0); \
+\
+     /*std::cout << "TRMM_R: A is not square! Go to BLAS GEMM implementation! " << nthr<<" \n";*/ \
+     } \
+     return; \
+   } \
+   char side = 'R', transa, uplo, diag = 'N'; \
+   EIGTYPE *b; \
+   const EIGTYPE *a; \
+   BlasIndex m, n, lda, ldb; \
+\
+/* Set m, n */ \
+   m = convert_index<BlasIndex>(rows); \
+   n = convert_index<BlasIndex>(diagSize); \
+\
+/* Set trans */ \
+   transa = (RhsStorageOrder==RowMajor) ? ((ConjugateRhs) ? 'C' : 'T') : 'N'; \
+\
+/* Set b, ldb */ \
+   Map<const MatrixLhs, 0, OuterStride<> > lhs(_lhs,rows,depth,OuterStride<>(lhsStride)); \
+   MatrixX##EIGPREFIX b_tmp; \
+\
+   if (ConjugateLhs) b_tmp = lhs.conjugate(); else b_tmp = lhs; \
+   b = b_tmp.data(); \
+   ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \
+\
+/* Set uplo */ \
+   uplo = IsLower ? 'L' : 'U'; \
+   if (RhsStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
+/* Set a, lda */ \
+   Map<const MatrixRhs, 0, OuterStride<> > rhs(_rhs,depth,cols, OuterStride<>(rhsStride)); \
+   MatrixRhs a_tmp; \
+\
+   if ((conjA!=0) || (SetDiag==0)) { \
+     if (conjA) a_tmp = rhs.conjugate(); else a_tmp = rhs; \
+     if (IsZeroDiag) \
+       a_tmp.diagonal().setZero(); \
+     else if (IsUnitDiag) \
+       a_tmp.diagonal().setOnes();\
+     a = a_tmp.data(); \
+     lda = convert_index<BlasIndex>(a_tmp.outerStride()); \
+   } else { \
+     a = _rhs; \
+     lda = convert_index<BlasIndex>(rhsStride); \
+   } \
+   /*std::cout << "TRMM_R: A is square! Go to BLAS TRMM implementation! \n";*/ \
+/* call ?trmm*/ \
+   BLASPREFIX##trmm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \
+\
+/* Add op(a_triangular)*b into res*/ \
+   Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \
+   res_tmp=res_tmp+b_tmp; \
+  } \
+};
+
+EIGEN_BLAS_TRMM_R(double, double, d, d)
+EIGEN_BLAS_TRMM_R(dcomplex, double, cd, z)
+EIGEN_BLAS_TRMM_R(float, float, f, s)
+EIGEN_BLAS_TRMM_R(scomplex, float, cf, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_BLAS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
@@ -1,309 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   Triangular matrix * matrix product functionality based on ?TRMM.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H
-#define EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H
-
-namespace Eigen { 
-
-namespace internal {
-
-
-template <typename Scalar, typename Index,
-          int Mode, bool LhsIsTriangular,
-          int LhsStorageOrder, bool ConjugateLhs,
-          int RhsStorageOrder, bool ConjugateRhs,
-          int ResStorageOrder>
-struct product_triangular_matrix_matrix_trmm :
-       product_triangular_matrix_matrix<Scalar,Index,Mode,
-          LhsIsTriangular,LhsStorageOrder,ConjugateLhs,
-          RhsStorageOrder, ConjugateRhs, ResStorageOrder, BuiltIn> {};
-
-
-// try to go to BLAS specialization
-#define EIGEN_MKL_TRMM_SPECIALIZE(Scalar, LhsIsTriangular) \
-template <typename Index, int Mode, \
-          int LhsStorageOrder, bool ConjugateLhs, \
-          int RhsStorageOrder, bool ConjugateRhs> \
-struct product_triangular_matrix_matrix<Scalar,Index, Mode, LhsIsTriangular, \
-           LhsStorageOrder,ConjugateLhs, RhsStorageOrder,ConjugateRhs,ColMajor,Specialized> { \
-  static inline void run(Index _rows, Index _cols, Index _depth, const Scalar* _lhs, Index lhsStride,\
-    const Scalar* _rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha, level3_blocking<Scalar,Scalar>& blocking) { \
-      product_triangular_matrix_matrix_trmm<Scalar,Index,Mode, \
-        LhsIsTriangular,LhsStorageOrder,ConjugateLhs, \
-        RhsStorageOrder, ConjugateRhs, ColMajor>::run( \
-        _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
-  } \
-};
-
-EIGEN_MKL_TRMM_SPECIALIZE(double, true)
-EIGEN_MKL_TRMM_SPECIALIZE(double, false)
-EIGEN_MKL_TRMM_SPECIALIZE(dcomplex, true)
-EIGEN_MKL_TRMM_SPECIALIZE(dcomplex, false)
-EIGEN_MKL_TRMM_SPECIALIZE(float, true)
-EIGEN_MKL_TRMM_SPECIALIZE(float, false)
-EIGEN_MKL_TRMM_SPECIALIZE(scomplex, true)
-EIGEN_MKL_TRMM_SPECIALIZE(scomplex, false)
-
-// implements col-major += alpha * op(triangular) * op(general)
-#define EIGEN_MKL_TRMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
-template <typename Index, int Mode, \
-          int LhsStorageOrder, bool ConjugateLhs, \
-          int RhsStorageOrder, bool ConjugateRhs> \
-struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
-         LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor> \
-{ \
-  enum { \
-    IsLower = (Mode&Lower) == Lower, \
-    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
-    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
-    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
-    LowUp = IsLower ? Lower : Upper, \
-    conjA = ((LhsStorageOrder==ColMajor) && ConjugateLhs) ? 1 : 0 \
-  }; \
-\
-  static void run( \
-    Index _rows, Index _cols, Index _depth, \
-    const EIGTYPE* _lhs, Index lhsStride, \
-    const EIGTYPE* _rhs, Index rhsStride, \
-    EIGTYPE* res,        Index resStride, \
-    EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
-  { \
-   Index diagSize  = (std::min)(_rows,_depth); \
-   Index rows      = IsLower ? _rows : diagSize; \
-   Index depth     = IsLower ? diagSize : _depth; \
-   Index cols      = _cols; \
-\
-   typedef Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> MatrixLhs; \
-   typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs; \
-\
-/* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \
-   if (rows != depth) { \
-\
-     int nthr = mkl_domain_get_max_threads(MKL_BLAS); \
-\
-     if (((nthr==1) && (((std::max)(rows,depth)-diagSize)/(double)diagSize < 0.5))) { \
-     /* Most likely no benefit to call TRMM or GEMM from MKL*/ \
-       product_triangular_matrix_matrix<EIGTYPE,Index,Mode,true, \
-       LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
-           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
-     /*std::cout << "TRMM_L: A is not square! Go to Eigen TRMM implementation!\n";*/ \
-     } else { \
-     /* Make sense to call GEMM */ \
-       Map<const MatrixLhs, 0, OuterStride<> > lhsMap(_lhs,rows,depth,OuterStride<>(lhsStride)); \
-       MatrixLhs aa_tmp=lhsMap.template triangularView<Mode>(); \
-       MKL_INT aStride = aa_tmp.outerStride(); \
-       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> gemm_blocking(_rows,_cols,_depth); \
-       general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
-       rows, cols, depth, aa_tmp.data(), aStride, _rhs, rhsStride, res, resStride, alpha, gemm_blocking, 0); \
-\
-     /*std::cout << "TRMM_L: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \
-     } \
-     return; \
-   } \
-   char side = 'L', transa, uplo, diag = 'N'; \
-   EIGTYPE *b; \
-   const EIGTYPE *a; \
-   MKL_INT m, n, lda, ldb; \
-   MKLTYPE alpha_; \
-\
-/* Set alpha_*/ \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
-\
-/* Set m, n */ \
-   m = (MKL_INT)diagSize; \
-   n = (MKL_INT)cols; \
-\
-/* Set trans */ \
-   transa = (LhsStorageOrder==RowMajor) ? ((ConjugateLhs) ? 'C' : 'T') : 'N'; \
-\
-/* Set b, ldb */ \
-   Map<const MatrixRhs, 0, OuterStride<> > rhs(_rhs,depth,cols,OuterStride<>(rhsStride)); \
-   MatrixX##EIGPREFIX b_tmp; \
-\
-   if (ConjugateRhs) b_tmp = rhs.conjugate(); else b_tmp = rhs; \
-   b = b_tmp.data(); \
-   ldb = b_tmp.outerStride(); \
-\
-/* Set uplo */ \
-   uplo = IsLower ? 'L' : 'U'; \
-   if (LhsStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
-/* Set a, lda */ \
-   Map<const MatrixLhs, 0, OuterStride<> > lhs(_lhs,rows,depth,OuterStride<>(lhsStride)); \
-   MatrixLhs a_tmp; \
-\
-   if ((conjA!=0) || (SetDiag==0)) { \
-     if (conjA) a_tmp = lhs.conjugate(); else a_tmp = lhs; \
-     if (IsZeroDiag) \
-       a_tmp.diagonal().setZero(); \
-     else if (IsUnitDiag) \
-       a_tmp.diagonal().setOnes();\
-     a = a_tmp.data(); \
-     lda = a_tmp.outerStride(); \
-   } else { \
-     a = _lhs; \
-     lda = lhsStride; \
-   } \
-   /*std::cout << "TRMM_L: A is square! Go to MKL TRMM implementation! \n";*/ \
-/* call ?trmm*/ \
-   MKLPREFIX##trmm(&side, &uplo, &transa, &diag, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (MKLTYPE*)b, &ldb); \
-\
-/* Add op(a_triangular)*b into res*/ \
-   Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \
-   res_tmp=res_tmp+b_tmp; \
-  } \
-};
-
-EIGEN_MKL_TRMM_L(double, double, d, d)
-EIGEN_MKL_TRMM_L(dcomplex, MKL_Complex16, cd, z)
-EIGEN_MKL_TRMM_L(float, float, f, s)
-EIGEN_MKL_TRMM_L(scomplex, MKL_Complex8, cf, c)
-
-// implements col-major += alpha * op(general) * op(triangular)
-#define EIGEN_MKL_TRMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
-template <typename Index, int Mode, \
-          int LhsStorageOrder, bool ConjugateLhs, \
-          int RhsStorageOrder, bool ConjugateRhs> \
-struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
-         LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor> \
-{ \
-  enum { \
-    IsLower = (Mode&Lower) == Lower, \
-    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
-    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
-    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
-    LowUp = IsLower ? Lower : Upper, \
-    conjA = ((RhsStorageOrder==ColMajor) && ConjugateRhs) ? 1 : 0 \
-  }; \
-\
-  static void run( \
-    Index _rows, Index _cols, Index _depth, \
-    const EIGTYPE* _lhs, Index lhsStride, \
-    const EIGTYPE* _rhs, Index rhsStride, \
-    EIGTYPE* res,        Index resStride, \
-    EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
-  { \
-   Index diagSize  = (std::min)(_cols,_depth); \
-   Index rows      = _rows; \
-   Index depth     = IsLower ? _depth : diagSize; \
-   Index cols      = IsLower ? diagSize : _cols; \
-\
-   typedef Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> MatrixLhs; \
-   typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs; \
-\
-/* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \
-   if (cols != depth) { \
-\
-     int nthr = mkl_domain_get_max_threads(MKL_BLAS); \
-\
-     if ((nthr==1) && (((std::max)(cols,depth)-diagSize)/(double)diagSize < 0.5)) { \
-     /* Most likely no benefit to call TRMM or GEMM from MKL*/ \
-       product_triangular_matrix_matrix<EIGTYPE,Index,Mode,false, \
-       LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
-           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
-       /*std::cout << "TRMM_R: A is not square! Go to Eigen TRMM implementation!\n";*/ \
-     } else { \
-     /* Make sense to call GEMM */ \
-       Map<const MatrixRhs, 0, OuterStride<> > rhsMap(_rhs,depth,cols, OuterStride<>(rhsStride)); \
-       MatrixRhs aa_tmp=rhsMap.template triangularView<Mode>(); \
-       MKL_INT aStride = aa_tmp.outerStride(); \
-       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> gemm_blocking(_rows,_cols,_depth); \
-       general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
-       rows, cols, depth, _lhs, lhsStride, aa_tmp.data(), aStride, res, resStride, alpha, gemm_blocking, 0); \
-\
-     /*std::cout << "TRMM_R: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \
-     } \
-     return; \
-   } \
-   char side = 'R', transa, uplo, diag = 'N'; \
-   EIGTYPE *b; \
-   const EIGTYPE *a; \
-   MKL_INT m, n, lda, ldb; \
-   MKLTYPE alpha_; \
-\
-/* Set alpha_*/ \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
-\
-/* Set m, n */ \
-   m = (MKL_INT)rows; \
-   n = (MKL_INT)diagSize; \
-\
-/* Set trans */ \
-   transa = (RhsStorageOrder==RowMajor) ? ((ConjugateRhs) ? 'C' : 'T') : 'N'; \
-\
-/* Set b, ldb */ \
-   Map<const MatrixLhs, 0, OuterStride<> > lhs(_lhs,rows,depth,OuterStride<>(lhsStride)); \
-   MatrixX##EIGPREFIX b_tmp; \
-\
-   if (ConjugateLhs) b_tmp = lhs.conjugate(); else b_tmp = lhs; \
-   b = b_tmp.data(); \
-   ldb = b_tmp.outerStride(); \
-\
-/* Set uplo */ \
-   uplo = IsLower ? 'L' : 'U'; \
-   if (RhsStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
-/* Set a, lda */ \
-   Map<const MatrixRhs, 0, OuterStride<> > rhs(_rhs,depth,cols, OuterStride<>(rhsStride)); \
-   MatrixRhs a_tmp; \
-\
-   if ((conjA!=0) || (SetDiag==0)) { \
-     if (conjA) a_tmp = rhs.conjugate(); else a_tmp = rhs; \
-     if (IsZeroDiag) \
-       a_tmp.diagonal().setZero(); \
-     else if (IsUnitDiag) \
-       a_tmp.diagonal().setOnes();\
-     a = a_tmp.data(); \
-     lda = a_tmp.outerStride(); \
-   } else { \
-     a = _rhs; \
-     lda = rhsStride; \
-   } \
-   /*std::cout << "TRMM_R: A is square! Go to MKL TRMM implementation! \n";*/ \
-/* call ?trmm*/ \
-   MKLPREFIX##trmm(&side, &uplo, &transa, &diag, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (MKLTYPE*)b, &ldb); \
-\
-/* Add op(a_triangular)*b into res*/ \
-   Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \
-   res_tmp=res_tmp+b_tmp; \
-  } \
-};
-
-EIGEN_MKL_TRMM_R(double, double, d, d)
-EIGEN_MKL_TRMM_R(dcomplex, MKL_Complex16, cd, z)
-EIGEN_MKL_TRMM_R(float, float, f, s)
-EIGEN_MKL_TRMM_R(scomplex, MKL_Complex8, cf, c)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H

Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector.h
@@ -8,50 +8,53 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIANGULARMATRIXVECTOR_H
 #define EIGEN_TRIANGULARMATRIXVECTOR_H
 
-namespace Eigen { 
+namespace Eigen {
 
 namespace internal {
 
 template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder, int Version=Specialized>
 struct triangular_matrix_vector_product;
 
 template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int Version>
 struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor,Version>
 {
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   enum {
     IsLower = ((Mode&Lower)==Lower),
     HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
     HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
   };
   static EIGEN_DONT_INLINE  void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
-                                     const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const ResScalar& alpha);
+                                     const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const RhsScalar& alpha);
 };
 
 template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int Version>
 EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor,Version>
   ::run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
-        const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const ResScalar& alpha)
+        const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, const RhsScalar& alpha)
   {
     static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
     Index size = (std::min)(_rows,_cols);
     Index rows = IsLower ? _rows : (std::min)(_rows,_cols);
     Index cols = IsLower ? (std::min)(_rows,_cols) : _cols;
 
     typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > LhsMap;
     const LhsMap lhs(_lhs,rows,cols,OuterStride<>(lhsStride));
     typename conj_expr_if<ConjLhs,LhsMap>::type cjLhs(lhs);
-    
+
     typedef Map<const Matrix<RhsScalar,Dynamic,1>, 0, InnerStride<> > RhsMap;
     const RhsMap rhs(_rhs,cols,InnerStride<>(rhsIncr));
     typename conj_expr_if<ConjRhs,RhsMap>::type cjRhs(rhs);
 
     typedef Map<Matrix<ResScalar,Dynamic,1> > ResMap;
     ResMap res(_res,rows);
+
+    typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper;
+    typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
 
     for (Index pi=0; pi<size; pi+=PanelWidth)
     {
       Index actualPanelWidth = (std::min)(PanelWidth, size-pi);
       for (Index k=0; k<actualPanelWidth; ++k)
@@ -66,31 +69,31 @@
       }
       Index r = IsLower ? rows - pi - actualPanelWidth : pi;
       if (r>0)
       {
         Index s = IsLower ? pi+actualPanelWidth : 0;
-        general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjLhs,RhsScalar,ConjRhs,BuiltIn>::run(
+        general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs,BuiltIn>::run(
             r, actualPanelWidth,
-            &lhs.coeffRef(s,pi), lhsStride,
-            &rhs.coeffRef(pi), rhsIncr,
+            LhsMapper(&lhs.coeffRef(s,pi), lhsStride),
+            RhsMapper(&rhs.coeffRef(pi), rhsIncr),
             &res.coeffRef(s), resIncr, alpha);
       }
     }
     if((!IsLower) && cols>size)
     {
-      general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjLhs,RhsScalar,ConjRhs>::run(
+      general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs>::run(
           rows, cols-size,
-          &lhs.coeffRef(0,size), lhsStride,
-          &rhs.coeffRef(size), rhsIncr,
+          LhsMapper(&lhs.coeffRef(0,size), lhsStride),
+          RhsMapper(&rhs.coeffRef(size), rhsIncr),
           _res, resIncr, alpha);
     }
   }
 
 template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs,int Version>
 struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor,Version>
 {
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   enum {
     IsLower = ((Mode&Lower)==Lower),
     HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
     HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
   };
@@ -116,11 +119,14 @@
     const RhsMap rhs(_rhs,cols);
     typename conj_expr_if<ConjRhs,RhsMap>::type cjRhs(rhs);
 
     typedef Map<Matrix<ResScalar,Dynamic,1>, 0, InnerStride<> > ResMap;
     ResMap res(_res,rows,InnerStride<>(resIncr));
-    
+
+    typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper;
+    typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
+
     for (Index pi=0; pi<diagSize; pi+=PanelWidth)
     {
       Index actualPanelWidth = (std::min)(PanelWidth, diagSize-pi);
       for (Index k=0; k<actualPanelWidth; ++k)
       {
@@ -134,108 +140,91 @@
       }
       Index r = IsLower ? pi : cols - pi - actualPanelWidth;
       if (r>0)
       {
         Index s = IsLower ? 0 : pi + actualPanelWidth;
-        general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjLhs,RhsScalar,ConjRhs,BuiltIn>::run(
+        general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs,BuiltIn>::run(
             actualPanelWidth, r,
-            &lhs.coeffRef(pi,s), lhsStride,
-            &rhs.coeffRef(s), rhsIncr,
+            LhsMapper(&lhs.coeffRef(pi,s), lhsStride),
+            RhsMapper(&rhs.coeffRef(s), rhsIncr),
             &res.coeffRef(pi), resIncr, alpha);
       }
     }
     if(IsLower && rows>diagSize)
     {
-      general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjLhs,RhsScalar,ConjRhs>::run(
+      general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs>::run(
             rows-diagSize, cols,
-            &lhs.coeffRef(diagSize,0), lhsStride,
-            &rhs.coeffRef(0), rhsIncr,
+            LhsMapper(&lhs.coeffRef(diagSize,0), lhsStride),
+            RhsMapper(&rhs.coeffRef(0), rhsIncr),
             &res.coeffRef(diagSize), resIncr, alpha);
     }
   }
 
 /***************************************************************************
 * Wrapper to product_triangular_vector
 ***************************************************************************/
 
-template<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs>
-struct traits<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,true> >
- : traits<ProductBase<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,true>, Lhs, Rhs> >
-{};
-
-template<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs>
-struct traits<TriangularProduct<Mode,LhsIsTriangular,Lhs,true,Rhs,false> >
- : traits<ProductBase<TriangularProduct<Mode,LhsIsTriangular,Lhs,true,Rhs,false>, Lhs, Rhs> >
-{};
-
-
-template<int StorageOrder>
-struct trmv_selector;
-
-} // end namespace internal
-
-template<int Mode, typename Lhs, typename Rhs>
-struct TriangularProduct<Mode,true,Lhs,false,Rhs,true>
-  : public ProductBase<TriangularProduct<Mode,true,Lhs,false,Rhs,true>, Lhs, Rhs >
-{
-  EIGEN_PRODUCT_PUBLIC_INTERFACE(TriangularProduct)
-
-  TriangularProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
-
-  template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
-  {
-    eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
-  
-    internal::trmv_selector<(int(internal::traits<Lhs>::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dst, alpha);
-  }
-};
-
-template<int Mode, typename Lhs, typename Rhs>
-struct TriangularProduct<Mode,false,Lhs,true,Rhs,false>
-  : public ProductBase<TriangularProduct<Mode,false,Lhs,true,Rhs,false>, Lhs, Rhs >
-{
-  EIGEN_PRODUCT_PUBLIC_INTERFACE(TriangularProduct)
-
-  TriangularProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
-
-  template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
-  {
-    eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
-
-    typedef TriangularProduct<(Mode & (UnitDiag|ZeroDiag)) | ((Mode & Lower) ? Upper : Lower),true,Transpose<const Rhs>,false,Transpose<const Lhs>,true> TriangularProductTranspose;
-    Transpose<Dest> dstT(dst);
-    internal::trmv_selector<(int(internal::traits<Rhs>::Flags)&RowMajorBit) ? ColMajor : RowMajor>::run(
-      TriangularProductTranspose(m_rhs.transpose(),m_lhs.transpose()), dstT, alpha);
-  }
-};
+template<int Mode,int StorageOrder>
+struct trmv_selector;
+
+} // end namespace internal
+
+namespace internal {
+
+template<int Mode, typename Lhs, typename Rhs>
+struct triangular_product_impl<Mode,true,Lhs,false,Rhs,true>
+{
+  template<typename Dest> static void run(Dest& dst, const Lhs &lhs, const Rhs &rhs, const typename Dest::Scalar& alpha)
+  {
+    eigen_assert(dst.rows()==lhs.rows() && dst.cols()==rhs.cols());
+  
+    internal::trmv_selector<Mode,(int(internal::traits<Lhs>::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(lhs, rhs, dst, alpha);
+  }
+};
+
+template<int Mode, typename Lhs, typename Rhs>
+struct triangular_product_impl<Mode,false,Lhs,true,Rhs,false>
+{
+  template<typename Dest> static void run(Dest& dst, const Lhs &lhs, const Rhs &rhs, const typename Dest::Scalar& alpha)
+  {
+    eigen_assert(dst.rows()==lhs.rows() && dst.cols()==rhs.cols());
+
+    Transpose<Dest> dstT(dst);
+    internal::trmv_selector<(Mode & (UnitDiag|ZeroDiag)) | ((Mode & Lower) ? Upper : Lower),
+                            (int(internal::traits<Rhs>::Flags)&RowMajorBit) ? ColMajor : RowMajor>
+            ::run(rhs.transpose(),lhs.transpose(), dstT, alpha);
+  }
+};
+
+} // end namespace internal
 
 namespace internal {
 
 // TODO: find a way to factorize this piece of code with gemv_selector since the logic is exactly the same.
   
-template<> struct trmv_selector<ColMajor>
-{
-  template<int Mode, typename Lhs, typename Rhs, typename Dest>
-  static void run(const TriangularProduct<Mode,true,Lhs,false,Rhs,true>& prod, Dest& dest, const typename TriangularProduct<Mode,true,Lhs,false,Rhs,true>::Scalar& alpha)
-  {
-    typedef TriangularProduct<Mode,true,Lhs,false,Rhs,true> ProductType;
-    typedef typename ProductType::Index Index;
-    typedef typename ProductType::LhsScalar   LhsScalar;
-    typedef typename ProductType::RhsScalar   RhsScalar;
-    typedef typename ProductType::Scalar      ResScalar;
-    typedef typename ProductType::RealScalar  RealScalar;
-    typedef typename ProductType::ActualLhsType ActualLhsType;
-    typedef typename ProductType::ActualRhsType ActualRhsType;
-    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
-    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
-    typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
-
-    typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
-    typename internal::add_const_on_value_type<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
-
-    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
-                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
+template<int Mode> struct trmv_selector<Mode,ColMajor>
+{
+  template<typename Lhs, typename Rhs, typename Dest>
+  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
+  {
+    typedef typename Lhs::Scalar      LhsScalar;
+    typedef typename Rhs::Scalar      RhsScalar;
+    typedef typename Dest::Scalar     ResScalar;
+    typedef typename Dest::RealScalar RealScalar;
+    
+    typedef internal::blas_traits<Lhs> LhsBlasTraits;
+    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+    typedef internal::blas_traits<Rhs> RhsBlasTraits;
+    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+    
+    typedef Map<Matrix<ResScalar,Dynamic,1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax,internal::packet_traits<ResScalar>::size)> MappedDest;
+
+    typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
+    typename internal::add_const_on_value_type<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
+
+    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
+                                  * RhsBlasTraits::extractScalarFactor(rhs);
 
     enum {
       // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
       // on, the other hand it is good for the cache to pack the vector anyways...
       EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
@@ -245,11 +234,11 @@
 
     gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
 
     bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
     bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
-    
+
     RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
 
     ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
                                                   evalToDest ? dest.data() : static_dest.data());
 
@@ -265,11 +254,11 @@
         compatibleAlpha = RhsScalar(1);
       }
       else
         MappedDest(actualDestPtr, dest.size()) = dest;
     }
-    
+
     internal::triangular_matrix_vector_product
       <Index,Mode,
        LhsScalar, LhsBlasTraits::NeedToConjugate,
        RhsScalar, RhsBlasTraits::NeedToConjugate,
        ColMajor>
@@ -286,50 +275,49 @@
         dest = MappedDest(actualDestPtr, dest.size());
     }
   }
 };
 
-template<> struct trmv_selector<RowMajor>
-{
-  template<int Mode, typename Lhs, typename Rhs, typename Dest>
-  static void run(const TriangularProduct<Mode,true,Lhs,false,Rhs,true>& prod, Dest& dest, const typename TriangularProduct<Mode,true,Lhs,false,Rhs,true>::Scalar& alpha)
-  {
-    typedef TriangularProduct<Mode,true,Lhs,false,Rhs,true> ProductType;
-    typedef typename ProductType::LhsScalar LhsScalar;
-    typedef typename ProductType::RhsScalar RhsScalar;
-    typedef typename ProductType::Scalar    ResScalar;
-    typedef typename ProductType::Index Index;
-    typedef typename ProductType::ActualLhsType ActualLhsType;
-    typedef typename ProductType::ActualRhsType ActualRhsType;
-    typedef typename ProductType::_ActualRhsType _ActualRhsType;
-    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
-    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
-
-    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
-    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
-
-    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
-                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
+template<int Mode> struct trmv_selector<Mode,RowMajor>
+{
+  template<typename Lhs, typename Rhs, typename Dest>
+  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
+  {
+    typedef typename Lhs::Scalar      LhsScalar;
+    typedef typename Rhs::Scalar      RhsScalar;
+    typedef typename Dest::Scalar     ResScalar;
+    
+    typedef internal::blas_traits<Lhs> LhsBlasTraits;
+    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+    typedef internal::blas_traits<Rhs> RhsBlasTraits;
+    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+    typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
+
+    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
+    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
+
+    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
+                                  * RhsBlasTraits::extractScalarFactor(rhs);
 
     enum {
-      DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
+      DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1
     };
 
-    gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
+    gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
 
     ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
         DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
 
     if(!DirectlyUseRhs)
     {
       #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      int size = actualRhs.size();
+      Index size = actualRhs.size();
       EIGEN_DENSE_STORAGE_CTOR_PLUGIN
       #endif
-      Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
+      Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
     }
-    
+
     internal::triangular_matrix_vector_product
       <Index,Mode,
        LhsScalar, LhsBlasTraits::NeedToConjugate,
        RhsScalar, RhsBlasTraits::NeedToConjugate,
        RowMajor>

ADDED   3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector_BLAS.h
Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector_BLAS.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector_BLAS.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector_BLAS.h
@@ -0,0 +1,241 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to BLAS F77
+ *   Triangular matrix-vector product functionality based on ?TRMV.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_TRIANGULAR_MATRIX_VECTOR_BLAS_H
+#define EIGEN_TRIANGULAR_MATRIX_VECTOR_BLAS_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************************************************
+* This file implements triangular matrix-vector multiplication using BLAS
+**********************************************************************/
+
+// trmv/hemv specialization
+
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder>
+struct triangular_matrix_vector_product_trmv :
+  triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,StorageOrder,BuiltIn> {};
+
+#define EIGEN_BLAS_TRMV_SPECIALIZE(Scalar) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor,Specialized> { \
+ static void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
+                                     const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
+      triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor>::run( \
+        _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
+  } \
+}; \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor,Specialized> { \
+ static void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
+                                     const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
+      triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor>::run( \
+        _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
+  } \
+};
+
+EIGEN_BLAS_TRMV_SPECIALIZE(double)
+EIGEN_BLAS_TRMV_SPECIALIZE(float)
+EIGEN_BLAS_TRMV_SPECIALIZE(dcomplex)
+EIGEN_BLAS_TRMV_SPECIALIZE(scomplex)
+
+// implements col-major: res += alpha * op(triangular) * vector
+#define EIGEN_BLAS_TRMV_CM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor> { \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    LowUp = IsLower ? Lower : Upper \
+  }; \
+ static void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
+                 const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
+ { \
+   if (ConjLhs || IsZeroDiag) { \
+     triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor,BuiltIn>::run( \
+       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
+     return; \
+   }\
+   Index size = (std::min)(_rows,_cols); \
+   Index rows = IsLower ? _rows : size; \
+   Index cols = IsLower ? size : _cols; \
+\
+   typedef VectorX##EIGPREFIX VectorRhs; \
+   EIGTYPE *x, *y;\
+\
+/* Set x*/ \
+   Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
+   VectorRhs x_tmp; \
+   if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+   x = x_tmp.data(); \
+\
+/* Square part handling */\
+\
+   char trans, uplo, diag; \
+   BlasIndex m, n, lda, incx, incy; \
+   EIGTYPE const *a; \
+   EIGTYPE beta(1); \
+\
+/* Set m, n */ \
+   n = convert_index<BlasIndex>(size); \
+   lda = convert_index<BlasIndex>(lhsStride); \
+   incx = 1; \
+   incy = convert_index<BlasIndex>(resIncr); \
+\
+/* Set uplo, trans and diag*/ \
+   trans = 'N'; \
+   uplo = IsLower ? 'L' : 'U'; \
+   diag = IsUnitDiag ? 'U' : 'N'; \
+\
+/* call ?TRMV*/ \
+   BLASPREFIX##trmv_(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \
+\
+/* Add op(a_tr)rhs into res*/ \
+   BLASPREFIX##axpy_(&n, &numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \
+/* Non-square case - doesn't fit to BLAS ?TRMV. Fall to default triangular product*/ \
+   if (size<(std::max)(rows,cols)) { \
+     if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+     x = x_tmp.data(); \
+     if (size<rows) { \
+       y = _res + size*resIncr; \
+       a = _lhs + size; \
+       m = convert_index<BlasIndex>(rows-size); \
+       n = convert_index<BlasIndex>(size); \
+     } \
+     else { \
+       x += size; \
+       y = _res; \
+       a = _lhs + size*lda; \
+       m = convert_index<BlasIndex>(size); \
+       n = convert_index<BlasIndex>(cols-size); \
+     } \
+     BLASPREFIX##gemv_(&trans, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, &numext::real_ref(beta), (BLASTYPE*)y, &incy); \
+   } \
+  } \
+};
+
+EIGEN_BLAS_TRMV_CM(double,   double, d,  d)
+EIGEN_BLAS_TRMV_CM(dcomplex, double, cd, z)
+EIGEN_BLAS_TRMV_CM(float,    float,  f,  s)
+EIGEN_BLAS_TRMV_CM(scomplex, float,  cf, c)
+
+// implements row-major: res += alpha * op(triangular) * vector
+#define EIGEN_BLAS_TRMV_RM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor> { \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    LowUp = IsLower ? Lower : Upper \
+  }; \
+ static void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
+                 const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
+ { \
+   if (IsZeroDiag) { \
+     triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor,BuiltIn>::run( \
+       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
+     return; \
+   }\
+   Index size = (std::min)(_rows,_cols); \
+   Index rows = IsLower ? _rows : size; \
+   Index cols = IsLower ? size : _cols; \
+\
+   typedef VectorX##EIGPREFIX VectorRhs; \
+   EIGTYPE *x, *y;\
+\
+/* Set x*/ \
+   Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
+   VectorRhs x_tmp; \
+   if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+   x = x_tmp.data(); \
+\
+/* Square part handling */\
+\
+   char trans, uplo, diag; \
+   BlasIndex m, n, lda, incx, incy; \
+   EIGTYPE const *a; \
+   EIGTYPE beta(1); \
+\
+/* Set m, n */ \
+   n = convert_index<BlasIndex>(size); \
+   lda = convert_index<BlasIndex>(lhsStride); \
+   incx = 1; \
+   incy = convert_index<BlasIndex>(resIncr); \
+\
+/* Set uplo, trans and diag*/ \
+   trans = ConjLhs ? 'C' : 'T'; \
+   uplo = IsLower ? 'U' : 'L'; \
+   diag = IsUnitDiag ? 'U' : 'N'; \
+\
+/* call ?TRMV*/ \
+   BLASPREFIX##trmv_(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \
+\
+/* Add op(a_tr)rhs into res*/ \
+   BLASPREFIX##axpy_(&n, &numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \
+/* Non-square case - doesn't fit to BLAS ?TRMV. Fall to default triangular product*/ \
+   if (size<(std::max)(rows,cols)) { \
+     if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+     x = x_tmp.data(); \
+     if (size<rows) { \
+       y = _res + size*resIncr; \
+       a = _lhs + size*lda; \
+       m = convert_index<BlasIndex>(rows-size); \
+       n = convert_index<BlasIndex>(size); \
+     } \
+     else { \
+       x += size; \
+       y = _res; \
+       a = _lhs + size; \
+       m = convert_index<BlasIndex>(size); \
+       n = convert_index<BlasIndex>(cols-size); \
+     } \
+     BLASPREFIX##gemv_(&trans, &n, &m, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, &numext::real_ref(beta), (BLASTYPE*)y, &incy); \
+   } \
+  } \
+};
+
+EIGEN_BLAS_TRMV_RM(double,   double, d,  d)
+EIGEN_BLAS_TRMV_RM(dcomplex, double, cd, z)
+EIGEN_BLAS_TRMV_RM(float,    float,  f,  s)
+EIGEN_BLAS_TRMV_RM(scomplex, float,  cf, c)
+
+} // end namespase internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TRIANGULAR_MATRIX_VECTOR_BLAS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
@@ -1,247 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   Triangular matrix-vector product functionality based on ?TRMV.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
-#define EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
-
-namespace Eigen { 
-
-namespace internal {
-
-/**********************************************************************
-* This file implements triangular matrix-vector multiplication using BLAS
-**********************************************************************/
-
-// trmv/hemv specialization
-
-template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder>
-struct triangular_matrix_vector_product_trmv :
-  triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,StorageOrder,BuiltIn> {};
-
-#define EIGEN_MKL_TRMV_SPECIALIZE(Scalar) \
-template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
-struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor,Specialized> { \
- static void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
-                                     const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
-      triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor>::run( \
-        _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
-  } \
-}; \
-template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
-struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor,Specialized> { \
- static void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
-                                     const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
-      triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor>::run( \
-        _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
-  } \
-};
-
-EIGEN_MKL_TRMV_SPECIALIZE(double)
-EIGEN_MKL_TRMV_SPECIALIZE(float)
-EIGEN_MKL_TRMV_SPECIALIZE(dcomplex)
-EIGEN_MKL_TRMV_SPECIALIZE(scomplex)
-
-// implements col-major: res += alpha * op(triangular) * vector
-#define EIGEN_MKL_TRMV_CM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
-template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
-struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor> { \
-  enum { \
-    IsLower = (Mode&Lower) == Lower, \
-    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
-    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
-    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
-    LowUp = IsLower ? Lower : Upper \
-  }; \
- static void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
-                 const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
- { \
-   if (ConjLhs || IsZeroDiag) { \
-     triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor,BuiltIn>::run( \
-       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
-     return; \
-   }\
-   Index size = (std::min)(_rows,_cols); \
-   Index rows = IsLower ? _rows : size; \
-   Index cols = IsLower ? size : _cols; \
-\
-   typedef VectorX##EIGPREFIX VectorRhs; \
-   EIGTYPE *x, *y;\
-\
-/* Set x*/ \
-   Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
-   VectorRhs x_tmp; \
-   if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
-   x = x_tmp.data(); \
-\
-/* Square part handling */\
-\
-   char trans, uplo, diag; \
-   MKL_INT m, n, lda, incx, incy; \
-   EIGTYPE const *a; \
-   MKLTYPE alpha_, beta_; \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
-\
-/* Set m, n */ \
-   n = (MKL_INT)size; \
-   lda = lhsStride; \
-   incx = 1; \
-   incy = resIncr; \
-\
-/* Set uplo, trans and diag*/ \
-   trans = 'N'; \
-   uplo = IsLower ? 'L' : 'U'; \
-   diag = IsUnitDiag ? 'U' : 'N'; \
-\
-/* call ?TRMV*/ \
-   MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \
-\
-/* Add op(a_tr)rhs into res*/ \
-   MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \
-/* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \
-   if (size<(std::max)(rows,cols)) { \
-     typedef Matrix<EIGTYPE, Dynamic, Dynamic> MatrixLhs; \
-     if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
-     x = x_tmp.data(); \
-     if (size<rows) { \
-       y = _res + size*resIncr; \
-       a = _lhs + size; \
-       m = rows-size; \
-       n = size; \
-     } \
-     else { \
-       x += size; \
-       y = _res; \
-       a = _lhs + size*lda; \
-       m = size; \
-       n = cols-size; \
-     } \
-     MKLPREFIX##gemv(&trans, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)x, &incx, &beta_, (MKLTYPE*)y, &incy); \
-   } \
-  } \
-};
-
-EIGEN_MKL_TRMV_CM(double, double, d, d)
-EIGEN_MKL_TRMV_CM(dcomplex, MKL_Complex16, cd, z)
-EIGEN_MKL_TRMV_CM(float, float, f, s)
-EIGEN_MKL_TRMV_CM(scomplex, MKL_Complex8, cf, c)
-
-// implements row-major: res += alpha * op(triangular) * vector
-#define EIGEN_MKL_TRMV_RM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
-template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
-struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor> { \
-  enum { \
-    IsLower = (Mode&Lower) == Lower, \
-    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
-    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
-    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
-    LowUp = IsLower ? Lower : Upper \
-  }; \
- static void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
-                 const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
- { \
-   if (IsZeroDiag) { \
-     triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor,BuiltIn>::run( \
-       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
-     return; \
-   }\
-   Index size = (std::min)(_rows,_cols); \
-   Index rows = IsLower ? _rows : size; \
-   Index cols = IsLower ? size : _cols; \
-\
-   typedef VectorX##EIGPREFIX VectorRhs; \
-   EIGTYPE *x, *y;\
-\
-/* Set x*/ \
-   Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
-   VectorRhs x_tmp; \
-   if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
-   x = x_tmp.data(); \
-\
-/* Square part handling */\
-\
-   char trans, uplo, diag; \
-   MKL_INT m, n, lda, incx, incy; \
-   EIGTYPE const *a; \
-   MKLTYPE alpha_, beta_; \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
-\
-/* Set m, n */ \
-   n = (MKL_INT)size; \
-   lda = lhsStride; \
-   incx = 1; \
-   incy = resIncr; \
-\
-/* Set uplo, trans and diag*/ \
-   trans = ConjLhs ? 'C' : 'T'; \
-   uplo = IsLower ? 'U' : 'L'; \
-   diag = IsUnitDiag ? 'U' : 'N'; \
-\
-/* call ?TRMV*/ \
-   MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \
-\
-/* Add op(a_tr)rhs into res*/ \
-   MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \
-/* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \
-   if (size<(std::max)(rows,cols)) { \
-     typedef Matrix<EIGTYPE, Dynamic, Dynamic> MatrixLhs; \
-     if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
-     x = x_tmp.data(); \
-     if (size<rows) { \
-       y = _res + size*resIncr; \
-       a = _lhs + size*lda; \
-       m = rows-size; \
-       n = size; \
-     } \
-     else { \
-       x += size; \
-       y = _res; \
-       a = _lhs + size; \
-       m = size; \
-       n = cols-size; \
-     } \
-     MKLPREFIX##gemv(&trans, &n, &m, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)x, &incx, &beta_, (MKLTYPE*)y, &incy); \
-   } \
-  } \
-};
-
-EIGEN_MKL_TRMV_RM(double, double, d, d)
-EIGEN_MKL_TRMV_RM(dcomplex, MKL_Complex16, cd, z)
-EIGEN_MKL_TRMV_RM(float, float, f, s)
-EIGEN_MKL_TRMV_RM(scomplex, MKL_Complex8, cf, c)
-
-} // end namespase internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H

Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix.h
@@ -50,14 +50,18 @@
     const Scalar* _tri, Index triStride,
     Scalar* _other, Index otherStride,
     level3_blocking<Scalar,Scalar>& blocking)
   {
     Index cols = otherSize;
-    const_blas_data_mapper<Scalar, Index, TriStorageOrder> tri(_tri,triStride);
-    blas_data_mapper<Scalar, Index, ColMajor> other(_other,otherStride);
+
+    typedef const_blas_data_mapper<Scalar, Index, TriStorageOrder> TriMapper;
+    typedef blas_data_mapper<Scalar, Index, ColMajor> OtherMapper;
+    TriMapper tri(_tri, triStride);
+    OtherMapper other(_other, otherStride);
 
     typedef gebp_traits<Scalar,Scalar> Traits;
+
     enum {
       SmallPanelWidth   = EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr),
       IsLower = (Mode&Lower) == Lower
     };
 
@@ -64,26 +68,24 @@
     Index kc = blocking.kc();                   // cache block size along the K direction
     Index mc = (std::min)(size,blocking.mc());  // cache block size along the M direction
 
     std::size_t sizeA = kc*mc;
     std::size_t sizeB = kc*cols;
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
 
     ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
     ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW());
 
     conj_if<Conjugate> conj;
-    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, Conjugate, false> gebp_kernel;
-    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, TriStorageOrder> pack_lhs;
-    gemm_pack_rhs<Scalar, Index, Traits::nr, ColMajor, false, true> pack_rhs;
+    gebp_kernel<Scalar, Scalar, Index, OtherMapper, Traits::mr, Traits::nr, Conjugate, false> gebp_kernel;
+    gemm_pack_lhs<Scalar, Index, TriMapper, Traits::mr, Traits::LhsProgress, TriStorageOrder> pack_lhs;
+    gemm_pack_rhs<Scalar, Index, OtherMapper, Traits::nr, ColMajor, false, true> pack_rhs;
 
     // the goal here is to subdivise the Rhs panels such that we keep some cache
     // coherence when accessing the rhs elements
-    std::ptrdiff_t l1, l2;
-    manage_caching_sizes(GetAction, &l1, &l2);
-    Index subcols = cols>0 ? l2/(4 * sizeof(Scalar) * otherStride) : 0;
+    std::ptrdiff_t l1, l2, l3;
+    manage_caching_sizes(GetAction, &l1, &l2, &l3);
+    Index subcols = cols>0 ? l2/(4 * sizeof(Scalar) * std::max<Index>(otherStride,size)) : 0;
     subcols = std::max<Index>((subcols/Traits::nr)*Traits::nr, Traits::nr);
 
     for(Index k2=IsLower ? 0 : size;
         IsLower ? k2<size : k2>0;
         IsLower ? k2+=kc : k2-=kc)
@@ -113,12 +115,13 @@
           // tr solve
           for (Index k=0; k<actualPanelWidth; ++k)
           {
             // TODO write a small kernel handling this (can be shared with trsv)
             Index i  = IsLower ? k2+k1+k : k2-k1-k-1;
-            Index s  = IsLower ? k2+k1 : i+1;
             Index rs = actualPanelWidth - k - 1; // remaining size
+            Index s  = TriStorageOrder==RowMajor ? (IsLower ? k2+k1 : i+1)
+                                                 :  IsLower ? i+1 : i-rs;
 
             Scalar a = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(tri(i,i));
             for (Index j=j2; j<j2+actual_cols; ++j)
             {
               if (TriStorageOrder==RowMajor)
@@ -131,11 +134,10 @@
 
                 other(i,j) = (other(i,j) - b)*a;
               }
               else
               {
-                Index s = IsLower ? i+1 : i-rs;
                 Scalar b = (other(i,j) *= a);
                 Scalar* r = &other(s,j);
                 const Scalar* l = &tri(s,i);
                 for (Index i3=0;i3<rs;++i3)
                   r[i3] -= b * conj(l[i3]);
@@ -146,21 +148,21 @@
           Index lengthTarget = actual_kc-k1-actualPanelWidth;
           Index startBlock   = IsLower ? k2+k1 : k2-k1-actualPanelWidth;
           Index blockBOffset = IsLower ? k1 : lengthTarget;
 
           // update the respective rows of B from other
-          pack_rhs(blockB+actual_kc*j2, &other(startBlock,j2), otherStride, actualPanelWidth, actual_cols, actual_kc, blockBOffset);
+          pack_rhs(blockB+actual_kc*j2, other.getSubMapper(startBlock,j2), actualPanelWidth, actual_cols, actual_kc, blockBOffset);
 
           // GEBP
           if (lengthTarget>0)
           {
             Index startTarget  = IsLower ? k2+k1+actualPanelWidth : k2-actual_kc;
 
-            pack_lhs(blockA, &tri(startTarget,startBlock), triStride, actualPanelWidth, lengthTarget);
+            pack_lhs(blockA, tri.getSubMapper(startTarget,startBlock), actualPanelWidth, lengthTarget);
 
-            gebp_kernel(&other(startTarget,j2), otherStride, blockA, blockB+actual_kc*j2, lengthTarget, actualPanelWidth, actual_cols, Scalar(-1),
-                        actualPanelWidth, actual_kc, 0, blockBOffset, blockW);
+            gebp_kernel(other.getSubMapper(startTarget,j2), blockA, blockB+actual_kc*j2, lengthTarget, actualPanelWidth, actual_cols, Scalar(-1),
+                        actualPanelWidth, actual_kc, 0, blockBOffset);
           }
         }
       }
       
       // R2 -= A21 * B => GEPP
@@ -170,20 +172,20 @@
         for(Index i2=start; i2<end; i2+=mc)
         {
           const Index actual_mc = (std::min)(mc,end-i2);
           if (actual_mc>0)
           {
-            pack_lhs(blockA, &tri(i2, IsLower ? k2 : k2-kc), triStride, actual_kc, actual_mc);
+            pack_lhs(blockA, tri.getSubMapper(i2, IsLower ? k2 : k2-kc), actual_kc, actual_mc);
 
-            gebp_kernel(_other+i2, otherStride, blockA, blockB, actual_mc, actual_kc, cols, Scalar(-1), -1, -1, 0, 0, blockW);
+            gebp_kernel(other.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, Scalar(-1), -1, -1, 0, 0);
           }
         }
       }
     }
   }
 
-/* Optimized triangular solver with multiple left hand sides and the trinagular matrix on the right
+/* Optimized triangular solver with multiple left hand sides and the triangular matrix on the right
  */
 template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStorageOrder>
 struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor>
 {
   static EIGEN_DONT_INLINE void run(
@@ -198,12 +200,16 @@
     const Scalar* _tri, Index triStride,
     Scalar* _other, Index otherStride,
     level3_blocking<Scalar,Scalar>& blocking)
   {
     Index rows = otherSize;
-    const_blas_data_mapper<Scalar, Index, TriStorageOrder> rhs(_tri,triStride);
-    blas_data_mapper<Scalar, Index, ColMajor> lhs(_other,otherStride);
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    typedef blas_data_mapper<Scalar, Index, ColMajor> LhsMapper;
+    typedef const_blas_data_mapper<Scalar, Index, TriStorageOrder> RhsMapper;
+    LhsMapper lhs(_other, otherStride);
+    RhsMapper rhs(_tri, triStride);
 
     typedef gebp_traits<Scalar,Scalar> Traits;
     enum {
       RhsStorageOrder   = TriStorageOrder,
       SmallPanelWidth   = EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr),
@@ -213,21 +219,19 @@
     Index kc = blocking.kc();                   // cache block size along the K direction
     Index mc = (std::min)(rows,blocking.mc());  // cache block size along the M direction
 
     std::size_t sizeA = kc*mc;
     std::size_t sizeB = kc*size;
-    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
 
     ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
     ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW());
 
     conj_if<Conjugate> conj;
-    gebp_kernel<Scalar,Scalar, Index, Traits::mr, Traits::nr, false, Conjugate> gebp_kernel;
-    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
-    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder,false,true> pack_rhs_panel;
-    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, ColMajor, false, true> pack_lhs_panel;
+    gebp_kernel<Scalar, Scalar, Index, LhsMapper, Traits::mr, Traits::nr, false, Conjugate> gebp_kernel;
+    gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr, RhsStorageOrder> pack_rhs;
+    gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr, RhsStorageOrder,false,true> pack_rhs_panel;
+    gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, ColMajor, false, true> pack_lhs_panel;
 
     for(Index k2=IsLower ? size : 0;
         IsLower ? k2>0 : k2<size;
         IsLower ? k2-=kc : k2+=kc)
     {
@@ -236,11 +240,11 @@
 
       Index startPanel = IsLower ? 0 : k2+actual_kc;
       Index rs = IsLower ? actual_k2 : size - actual_k2 - actual_kc;
       Scalar* geb = blockB+actual_kc*actual_kc;
 
-      if (rs>0) pack_rhs(geb, &rhs(actual_k2,startPanel), triStride, actual_kc, rs);
+      if (rs>0) pack_rhs(geb, rhs.getSubMapper(actual_k2,startPanel), actual_kc, rs);
 
       // triangular packing (we only pack the panels off the diagonal,
       // neglecting the blocks overlapping the diagonal
       {
         for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth)
@@ -250,11 +254,11 @@
           Index panelOffset = IsLower ? j2+actualPanelWidth : 0;
           Index panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
 
           if (panelLength>0)
           pack_rhs_panel(blockB+j2*actual_kc,
-                         &rhs(actual_k2+panelOffset, actual_j2), triStride,
+                         rhs.getSubMapper(actual_k2+panelOffset, actual_j2),
                          panelLength, actualPanelWidth,
                          actual_kc, panelOffset);
         }
       }
 
@@ -278,17 +282,16 @@
             Index panelLength = IsLower ? actual_kc - j2 - actualPanelWidth : j2;
 
             // GEBP
             if(panelLength>0)
             {
-              gebp_kernel(&lhs(i2,absolute_j2), otherStride,
+              gebp_kernel(lhs.getSubMapper(i2,absolute_j2),
                           blockA, blockB+j2*actual_kc,
                           actual_mc, panelLength, actualPanelWidth,
                           Scalar(-1),
                           actual_kc, actual_kc, // strides
-                          panelOffset, panelOffset, // offsets
-                          blockW);  // workspace
+                          panelOffset, panelOffset); // offsets
             }
 
             // unblocked triangular solve
             for (Index k=0; k<actualPanelWidth; ++k)
             {
@@ -300,30 +303,33 @@
                 Scalar b = conj(rhs(IsLower ? j+1+k3 : absolute_j2+k3,j));
                 Scalar* a = &lhs(i2,IsLower ? j+1+k3 : absolute_j2+k3);
                 for (Index i=0; i<actual_mc; ++i)
                   r[i] -= a[i] * b;
               }
-              Scalar b = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(rhs(j,j));
-              for (Index i=0; i<actual_mc; ++i)
-                r[i] *= b;
+              if((Mode & UnitDiag)==0)
+              {
+                Scalar inv_rjj = RealScalar(1)/conj(rhs(j,j));
+                for (Index i=0; i<actual_mc; ++i)
+                  r[i] *= inv_rjj;
+              }
             }
 
             // pack the just computed part of lhs to A
-            pack_lhs_panel(blockA, _other+absolute_j2*otherStride+i2, otherStride,
+            pack_lhs_panel(blockA, LhsMapper(_other+absolute_j2*otherStride+i2, otherStride),
                            actualPanelWidth, actual_mc,
                            actual_kc, j2);
           }
         }
 
         if (rs>0)
-          gebp_kernel(_other+i2+startPanel*otherStride, otherStride, blockA, geb,
+          gebp_kernel(lhs.getSubMapper(i2, startPanel), blockA, geb,
                       actual_mc, actual_kc, rs, Scalar(-1),
-                      -1, -1, 0, 0, blockW);
+                      -1, -1, 0, 0);
       }
     }
   }
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_TRIANGULAR_SOLVER_MATRIX_H

ADDED   3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix_BLAS.h
Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix_BLAS.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix_BLAS.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix_BLAS.h
@@ -0,0 +1,151 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to BLAS F77
+ *   Triangular matrix * matrix product functionality based on ?TRMM.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_TRIANGULAR_SOLVER_MATRIX_BLAS_H
+#define EIGEN_TRIANGULAR_SOLVER_MATRIX_BLAS_H
+
+namespace Eigen {
+
+namespace internal {
+
+// implements LeftSide op(triangular)^-1 * general
+#define EIGEN_BLAS_TRSM_L(EIGTYPE, BLASTYPE, BLASPREFIX) \
+template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
+struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor> \
+{ \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
+  }; \
+  static void run( \
+      Index size, Index otherSize, \
+      const EIGTYPE* _tri, Index triStride, \
+      EIGTYPE* _other, Index otherStride, level3_blocking<EIGTYPE,EIGTYPE>& /*blocking*/) \
+  { \
+   BlasIndex m = convert_index<BlasIndex>(size), n = convert_index<BlasIndex>(otherSize), lda, ldb; \
+   char side = 'L', uplo, diag='N', transa; \
+   /* Set alpha_ */ \
+   EIGTYPE alpha(1); \
+   ldb = convert_index<BlasIndex>(otherStride);\
+\
+   const EIGTYPE *a; \
+/* Set trans */ \
+   transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \
+/* Set uplo */ \
+   uplo = IsLower ? 'L' : 'U'; \
+   if (TriStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
+/* Set a, lda */ \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, TriStorageOrder> MatrixTri; \
+   Map<const MatrixTri, 0, OuterStride<> > tri(_tri,size,size,OuterStride<>(triStride)); \
+   MatrixTri a_tmp; \
+\
+   if (conjA) { \
+     a_tmp = tri.conjugate(); \
+     a = a_tmp.data(); \
+     lda = convert_index<BlasIndex>(a_tmp.outerStride()); \
+   } else { \
+     a = _tri; \
+     lda = convert_index<BlasIndex>(triStride); \
+   } \
+   if (IsUnitDiag) diag='U'; \
+/* call ?trsm*/ \
+   BLASPREFIX##trsm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \
+ } \
+};
+
+EIGEN_BLAS_TRSM_L(double,   double, d)
+EIGEN_BLAS_TRSM_L(dcomplex, double, z)
+EIGEN_BLAS_TRSM_L(float,    float,  s)
+EIGEN_BLAS_TRSM_L(scomplex, float,  c)
+
+
+// implements RightSide general * op(triangular)^-1
+#define EIGEN_BLAS_TRSM_R(EIGTYPE, BLASTYPE, BLASPREFIX) \
+template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
+struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor> \
+{ \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
+  }; \
+  static void run( \
+      Index size, Index otherSize, \
+      const EIGTYPE* _tri, Index triStride, \
+      EIGTYPE* _other, Index otherStride, level3_blocking<EIGTYPE,EIGTYPE>& /*blocking*/) \
+  { \
+   BlasIndex m = convert_index<BlasIndex>(otherSize), n = convert_index<BlasIndex>(size), lda, ldb; \
+   char side = 'R', uplo, diag='N', transa; \
+   /* Set alpha_ */ \
+   EIGTYPE alpha(1); \
+   ldb = convert_index<BlasIndex>(otherStride);\
+\
+   const EIGTYPE *a; \
+/* Set trans */ \
+   transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \
+/* Set uplo */ \
+   uplo = IsLower ? 'L' : 'U'; \
+   if (TriStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
+/* Set a, lda */ \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, TriStorageOrder> MatrixTri; \
+   Map<const MatrixTri, 0, OuterStride<> > tri(_tri,size,size,OuterStride<>(triStride)); \
+   MatrixTri a_tmp; \
+\
+   if (conjA) { \
+     a_tmp = tri.conjugate(); \
+     a = a_tmp.data(); \
+     lda = convert_index<BlasIndex>(a_tmp.outerStride()); \
+   } else { \
+     a = _tri; \
+     lda = convert_index<BlasIndex>(triStride); \
+   } \
+   if (IsUnitDiag) diag='U'; \
+/* call ?trsm*/ \
+   BLASPREFIX##trsm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \
+   /*std::cout << "TRMS_L specialization!\n";*/ \
+ } \
+};
+
+EIGEN_BLAS_TRSM_R(double,   double, d)
+EIGEN_BLAS_TRSM_R(dcomplex, double, z)
+EIGEN_BLAS_TRSM_R(float,    float,  s)
+EIGEN_BLAS_TRSM_R(scomplex, float,  c)
+
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TRIANGULAR_SOLVER_MATRIX_BLAS_H

DELETED 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix_MKL.h
Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix_MKL.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverMatrix_MKL.h
@@ -1,155 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   Triangular matrix * matrix product functionality based on ?TRMM.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_TRIANGULAR_SOLVER_MATRIX_MKL_H
-#define EIGEN_TRIANGULAR_SOLVER_MATRIX_MKL_H
-
-namespace Eigen {
-
-namespace internal {
-
-// implements LeftSide op(triangular)^-1 * general
-#define EIGEN_MKL_TRSM_L(EIGTYPE, MKLTYPE, MKLPREFIX) \
-template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
-struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor> \
-{ \
-  enum { \
-    IsLower = (Mode&Lower) == Lower, \
-    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
-    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
-    conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
-  }; \
-  static void run( \
-      Index size, Index otherSize, \
-      const EIGTYPE* _tri, Index triStride, \
-      EIGTYPE* _other, Index otherStride, level3_blocking<EIGTYPE,EIGTYPE>& /*blocking*/) \
-  { \
-   MKL_INT m = size, n = otherSize, lda, ldb; \
-   char side = 'L', uplo, diag='N', transa; \
-   /* Set alpha_ */ \
-   MKLTYPE alpha; \
-   EIGTYPE myone(1); \
-   assign_scalar_eig2mkl(alpha, myone); \
-   ldb = otherStride;\
-\
-   const EIGTYPE *a; \
-/* Set trans */ \
-   transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \
-/* Set uplo */ \
-   uplo = IsLower ? 'L' : 'U'; \
-   if (TriStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
-/* Set a, lda */ \
-   typedef Matrix<EIGTYPE, Dynamic, Dynamic, TriStorageOrder> MatrixTri; \
-   Map<const MatrixTri, 0, OuterStride<> > tri(_tri,size,size,OuterStride<>(triStride)); \
-   MatrixTri a_tmp; \
-\
-   if (conjA) { \
-     a_tmp = tri.conjugate(); \
-     a = a_tmp.data(); \
-     lda = a_tmp.outerStride(); \
-   } else { \
-     a = _tri; \
-     lda = triStride; \
-   } \
-   if (IsUnitDiag) diag='U'; \
-/* call ?trsm*/ \
-   MKLPREFIX##trsm(&side, &uplo, &transa, &diag, &m, &n, &alpha, (const MKLTYPE*)a, &lda, (MKLTYPE*)_other, &ldb); \
- } \
-};
-
-EIGEN_MKL_TRSM_L(double, double, d)
-EIGEN_MKL_TRSM_L(dcomplex, MKL_Complex16, z)
-EIGEN_MKL_TRSM_L(float, float, s)
-EIGEN_MKL_TRSM_L(scomplex, MKL_Complex8, c)
-
-
-// implements RightSide general * op(triangular)^-1
-#define EIGEN_MKL_TRSM_R(EIGTYPE, MKLTYPE, MKLPREFIX) \
-template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
-struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor> \
-{ \
-  enum { \
-    IsLower = (Mode&Lower) == Lower, \
-    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
-    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
-    conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
-  }; \
-  static void run( \
-      Index size, Index otherSize, \
-      const EIGTYPE* _tri, Index triStride, \
-      EIGTYPE* _other, Index otherStride, level3_blocking<EIGTYPE,EIGTYPE>& /*blocking*/) \
-  { \
-   MKL_INT m = otherSize, n = size, lda, ldb; \
-   char side = 'R', uplo, diag='N', transa; \
-   /* Set alpha_ */ \
-   MKLTYPE alpha; \
-   EIGTYPE myone(1); \
-   assign_scalar_eig2mkl(alpha, myone); \
-   ldb = otherStride;\
-\
-   const EIGTYPE *a; \
-/* Set trans */ \
-   transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \
-/* Set uplo */ \
-   uplo = IsLower ? 'L' : 'U'; \
-   if (TriStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
-/* Set a, lda */ \
-   typedef Matrix<EIGTYPE, Dynamic, Dynamic, TriStorageOrder> MatrixTri; \
-   Map<const MatrixTri, 0, OuterStride<> > tri(_tri,size,size,OuterStride<>(triStride)); \
-   MatrixTri a_tmp; \
-\
-   if (conjA) { \
-     a_tmp = tri.conjugate(); \
-     a = a_tmp.data(); \
-     lda = a_tmp.outerStride(); \
-   } else { \
-     a = _tri; \
-     lda = triStride; \
-   } \
-   if (IsUnitDiag) diag='U'; \
-/* call ?trsm*/ \
-   MKLPREFIX##trsm(&side, &uplo, &transa, &diag, &m, &n, &alpha, (const MKLTYPE*)a, &lda, (MKLTYPE*)_other, &ldb); \
-   /*std::cout << "TRMS_L specialization!\n";*/ \
- } \
-};
-
-EIGEN_MKL_TRSM_R(double, double, d)
-EIGEN_MKL_TRSM_R(dcomplex, MKL_Complex16, z)
-EIGEN_MKL_TRSM_R(float, float, s)
-EIGEN_MKL_TRSM_R(scomplex, MKL_Complex8, c)
-
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_TRIANGULAR_SOLVER_MATRIX_MKL_H

Index: 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverVector.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverVector.h
+++ 3rd_party/eigen/Eigen/src/Core/products/TriangularSolverVector.h
@@ -8,11 +8,11 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIANGULAR_SOLVER_VECTOR_H
 #define EIGEN_TRIANGULAR_SOLVER_VECTOR_H
 
-namespace Eigen { 
+namespace Eigen {
 
 namespace internal {
 
 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate, int StorageOrder>
 struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheRight, Mode, Conjugate, StorageOrder>
@@ -23,11 +23,11 @@
         ((Mode&Upper)==Upper ? Lower : Upper) | (Mode&UnitDiag),
         Conjugate,StorageOrder==RowMajor?ColMajor:RowMajor
       >::run(size, _lhs, lhsStride, rhs);
   }
 };
-    
+
 // forward and backward substitution, row-major, rhs is a vector
 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate>
 struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Conjugate, RowMajor>
 {
   enum {
@@ -35,10 +35,14 @@
   };
   static void run(Index size, const LhsScalar* _lhs, Index lhsStride, RhsScalar* rhs)
   {
     typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,RowMajor>, 0, OuterStride<> > LhsMap;
     const LhsMap lhs(_lhs,size,size,OuterStride<>(lhsStride));
+
+    typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper;
+    typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper;
+
     typename internal::conditional<
                           Conjugate,
                           const CwiseUnaryOp<typename internal::scalar_conjugate_op<LhsScalar>,LhsMap>,
                           const LhsMap&>
                         ::type cjLhs(lhs);
@@ -56,14 +60,14 @@
         // 1 - it is faster to compile
         // 2 - it is slighlty faster at runtime
         Index startRow = IsLower ? pi : pi-actualPanelWidth;
         Index startCol = IsLower ? 0 : pi;
 
-        general_matrix_vector_product<Index,LhsScalar,RowMajor,Conjugate,RhsScalar,false>::run(
+        general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,Conjugate,RhsScalar,RhsMapper,false>::run(
           actualPanelWidth, r,
-          &lhs.coeffRef(startRow,startCol), lhsStride,
-          rhs + startCol, 1,
+          LhsMapper(&lhs.coeffRef(startRow,startCol), lhsStride),
+          RhsMapper(rhs + startCol, 1),
           rhs + startRow, 1,
           RhsScalar(-1));
       }
 
       for(Index k=0; k<actualPanelWidth; ++k)
@@ -70,11 +74,11 @@
       {
         Index i = IsLower ? pi+k : pi-k-1;
         Index s = IsLower ? pi   : i+1;
         if (k>0)
           rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map<const Matrix<RhsScalar,Dynamic,1> >(rhs+s,k))).sum();
-        
+
         if(!(Mode & UnitDiag))
           rhs[i] /= cjLhs(i,i);
       }
     }
   }
@@ -89,10 +93,12 @@
   };
   static void run(Index size, const LhsScalar* _lhs, Index lhsStride, RhsScalar* rhs)
   {
     typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > LhsMap;
     const LhsMap lhs(_lhs,size,size,OuterStride<>(lhsStride));
+    typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper;
+    typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper;
     typename internal::conditional<Conjugate,
                                    const CwiseUnaryOp<typename internal::scalar_conjugate_op<LhsScalar>,LhsMap>,
                                    const LhsMap&
                                   >::type cjLhs(lhs);
     static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
@@ -120,14 +126,14 @@
       if (r > 0)
       {
         // let's directly call the low level product function because:
         // 1 - it is faster to compile
         // 2 - it is slighlty faster at runtime
-        general_matrix_vector_product<Index,LhsScalar,ColMajor,Conjugate,RhsScalar,false>::run(
+        general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,Conjugate,RhsScalar,RhsMapper,false>::run(
             r, actualPanelWidth,
-            &lhs.coeffRef(endBlock,startBlock), lhsStride,
-            rhs+startBlock, 1,
+            LhsMapper(&lhs.coeffRef(endBlock,startBlock), lhsStride),
+            RhsMapper(rhs+startBlock, 1),
             rhs+endBlock, 1, RhsScalar(-1));
       }
     }
   }
 };

Index: 3rd_party/eigen/Eigen/src/Core/util/BlasUtil.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/BlasUtil.h
+++ 3rd_party/eigen/Eigen/src/Core/util/BlasUtil.h
@@ -16,50 +16,65 @@
 namespace Eigen {
 
 namespace internal {
 
 // forward declarations
-template<typename LhsScalar, typename RhsScalar, typename Index, int mr, int nr, bool ConjugateLhs=false, bool ConjugateRhs=false>
+template<typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr, bool ConjugateLhs=false, bool ConjugateRhs=false>
 struct gebp_kernel;
 
-template<typename Scalar, typename Index, int nr, int StorageOrder, bool Conjugate = false, bool PanelMode=false>
+template<typename Scalar, typename Index, typename DataMapper, int nr, int StorageOrder, bool Conjugate = false, bool PanelMode=false>
 struct gemm_pack_rhs;
 
-template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder, bool Conjugate = false, bool PanelMode = false>
+template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, int StorageOrder, bool Conjugate = false, bool PanelMode = false>
 struct gemm_pack_lhs;
 
 template<
   typename Index,
   typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
   typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs,
   int ResStorageOrder>
 struct general_matrix_matrix_product;
 
-template<typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version=Specialized>
+template<typename Index,
+         typename LhsScalar, typename LhsMapper, int LhsStorageOrder, bool ConjugateLhs,
+         typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version=Specialized>
 struct general_matrix_vector_product;
 
 
 template<bool Conjugate> struct conj_if;
 
 template<> struct conj_if<true> {
   template<typename T>
-  inline T operator()(const T& x) { return numext::conj(x); }
+  inline T operator()(const T& x) const { return numext::conj(x); }
   template<typename T>
-  inline T pconj(const T& x) { return internal::pconj(x); }
+  inline T pconj(const T& x) const { return internal::pconj(x); }
 };
 
 template<> struct conj_if<false> {
   template<typename T>
-  inline const T& operator()(const T& x) { return x; }
+  inline const T& operator()(const T& x) const { return x; }
   template<typename T>
-  inline const T& pconj(const T& x) { return x; }
+  inline const T& pconj(const T& x) const { return x; }
+};
+
+// Generic implementation for custom complex types.
+template<typename LhsScalar, typename RhsScalar, bool ConjLhs, bool ConjRhs>
+struct conj_helper
+{
+  typedef typename ScalarBinaryOpTraits<LhsScalar,RhsScalar>::ReturnType Scalar;
+
+  EIGEN_STRONG_INLINE Scalar pmadd(const LhsScalar& x, const RhsScalar& y, const Scalar& c) const
+  { return padd(c, pmul(x,y)); }
+
+  EIGEN_STRONG_INLINE Scalar pmul(const LhsScalar& x, const RhsScalar& y) const
+  { return conj_if<ConjLhs>()(x) *  conj_if<ConjRhs>()(y); }
 };
 
 template<typename Scalar> struct conj_helper<Scalar,Scalar,false,false>
 {
-  EIGEN_STRONG_INLINE Scalar pmadd(const Scalar& x, const Scalar& y, const Scalar& c) const { return internal::pmadd(x,y,c); }
-  EIGEN_STRONG_INLINE Scalar pmul(const Scalar& x, const Scalar& y) const { return internal::pmul(x,y); }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar pmadd(const Scalar& x, const Scalar& y, const Scalar& c) const { return internal::pmadd(x,y,c); }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar pmul(const Scalar& x, const Scalar& y) const { return internal::pmul(x,y); }
 };
 
 template<typename RealScalar> struct conj_helper<std::complex<RealScalar>, std::complex<RealScalar>, false,true>
 {
   typedef std::complex<RealScalar> Scalar;
@@ -107,43 +122,146 @@
   EIGEN_STRONG_INLINE Scalar pmul(const RealScalar& x, const Scalar& y) const
   { return x*conj_if<Conj>()(y); }
 };
 
 template<typename From,typename To> struct get_factor {
-  static EIGEN_STRONG_INLINE To run(const From& x) { return x; }
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE To run(const From& x) { return To(x); }
 };
 
 template<typename Scalar> struct get_factor<Scalar,typename NumTraits<Scalar>::Real> {
+  EIGEN_DEVICE_FUNC
   static EIGEN_STRONG_INLINE typename NumTraits<Scalar>::Real run(const Scalar& x) { return numext::real(x); }
 };
 
+
+template<typename Scalar, typename Index>
+class BlasVectorMapper {
+  public:
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE BlasVectorMapper(Scalar *data) : m_data(data) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar operator()(Index i) const {
+    return m_data[i];
+  }
+  template <typename Packet, int AlignmentType>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet load(Index i) const {
+    return ploadt<Packet, AlignmentType>(m_data + i);
+  }
+
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC bool aligned(Index i) const {
+    return (UIntPtr(m_data+i)%sizeof(Packet))==0;
+  }
+
+  protected:
+  Scalar* m_data;
+};
+
+template<typename Scalar, typename Index, int AlignmentType>
+class BlasLinearMapper {
+  public:
+  typedef typename packet_traits<Scalar>::type Packet;
+  typedef typename packet_traits<Scalar>::half HalfPacket;
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE BlasLinearMapper(Scalar *data) : m_data(data) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void prefetch(int i) const {
+    internal::prefetch(&operator()(i));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar& operator()(Index i) const {
+    return m_data[i];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet loadPacket(Index i) const {
+    return ploadt<Packet, AlignmentType>(m_data + i);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE HalfPacket loadHalfPacket(Index i) const {
+    return ploadt<HalfPacket, AlignmentType>(m_data + i);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacket(Index i, const Packet &p) const {
+    pstoret<Scalar, Packet, AlignmentType>(m_data + i, p);
+  }
+
+  protected:
+  Scalar *m_data;
+};
+
 // Lightweight helper class to access matrix coefficients.
-// Yes, this is somehow redundant with Map<>, but this version is much much lighter,
-// and so I hope better compilation performance (time and code quality).
-template<typename Scalar, typename Index, int StorageOrder>
-class blas_data_mapper
-{
+template<typename Scalar, typename Index, int StorageOrder, int AlignmentType = Unaligned>
+class blas_data_mapper {
   public:
-    blas_data_mapper(Scalar* data, Index stride) : m_data(data), m_stride(stride) {}
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i, Index j)
-    { return m_data[StorageOrder==RowMajor ? j + i*m_stride : i + j*m_stride]; }
+  typedef typename packet_traits<Scalar>::type Packet;
+  typedef typename packet_traits<Scalar>::half HalfPacket;
+
+  typedef BlasLinearMapper<Scalar, Index, AlignmentType> LinearMapper;
+  typedef BlasVectorMapper<Scalar, Index> VectorMapper;
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE blas_data_mapper(Scalar* data, Index stride) : m_data(data), m_stride(stride) {}
+
+  EIGEN_DEVICE_FUNC  EIGEN_ALWAYS_INLINE blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType>
+  getSubMapper(Index i, Index j) const {
+    return blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType>(&operator()(i, j), m_stride);
+  }
+
+  EIGEN_DEVICE_FUNC  EIGEN_ALWAYS_INLINE LinearMapper getLinearMapper(Index i, Index j) const {
+    return LinearMapper(&operator()(i, j));
+  }
+
+  EIGEN_DEVICE_FUNC  EIGEN_ALWAYS_INLINE VectorMapper getVectorMapper(Index i, Index j) const {
+    return VectorMapper(&operator()(i, j));
+  }
+
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_ALWAYS_INLINE Scalar& operator()(Index i, Index j) const {
+    return m_data[StorageOrder==RowMajor ? j + i*m_stride : i + j*m_stride];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet loadPacket(Index i, Index j) const {
+    return ploadt<Packet, AlignmentType>(&operator()(i, j));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE HalfPacket loadHalfPacket(Index i, Index j) const {
+    return ploadt<HalfPacket, AlignmentType>(&operator()(i, j));
+  }
+
+  template<typename SubPacket>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void scatterPacket(Index i, Index j, const SubPacket &p) const {
+    pscatter<Scalar, SubPacket>(&operator()(i, j), p, m_stride);
+  }
+
+  template<typename SubPacket>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE SubPacket gatherPacket(Index i, Index j) const {
+    return pgather<Scalar, SubPacket>(&operator()(i, j), m_stride);
+  }
+
+  EIGEN_DEVICE_FUNC const Index stride() const { return m_stride; }
+  EIGEN_DEVICE_FUNC const Scalar* data() const { return m_data; }
+
+  EIGEN_DEVICE_FUNC Index firstAligned(Index size) const {
+    if (UIntPtr(m_data)%sizeof(Scalar)) {
+      return -1;
+    }
+    return internal::first_default_aligned(m_data, size);
+  }
+
   protected:
-    Scalar* EIGEN_RESTRICT m_data;
-    Index m_stride;
+  Scalar* EIGEN_RESTRICT m_data;
+  const Index m_stride;
 };
 
 // lightweight helper class to access matrix coefficients (const version)
 template<typename Scalar, typename Index, int StorageOrder>
-class const_blas_data_mapper
-{
+class const_blas_data_mapper : public blas_data_mapper<const Scalar, Index, StorageOrder> {
   public:
-    const_blas_data_mapper(const Scalar* data, Index stride) : m_data(data), m_stride(stride) {}
-    EIGEN_STRONG_INLINE const Scalar& operator()(Index i, Index j) const
-    { return m_data[StorageOrder==RowMajor ? j + i*m_stride : i + j*m_stride]; }
-  protected:
-    const Scalar* EIGEN_RESTRICT m_data;
-    Index m_stride;
+  EIGEN_ALWAYS_INLINE const_blas_data_mapper(const Scalar *data, Index stride) : blas_data_mapper<const Scalar, Index, StorageOrder>(data, stride) {}
+
+  EIGEN_ALWAYS_INLINE const_blas_data_mapper<Scalar, Index, StorageOrder> getSubMapper(Index i, Index j) const {
+    return const_blas_data_mapper<Scalar, Index, StorageOrder>(&(this->operator()(i, j)), this->m_stride);
+  }
 };
 
 
 /* Helper class to analyze the factors of a Product expression.
  * In particular it allows to pop out operator-, scalar multiples,
@@ -186,21 +304,37 @@
   static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
   static inline Scalar extractScalarFactor(const XprType& x) { return conj(Base::extractScalarFactor(x.nestedExpression())); }
 };
 
 // pop scalar multiple
-template<typename Scalar, typename NestedXpr>
-struct blas_traits<CwiseUnaryOp<scalar_multiple_op<Scalar>, NestedXpr> >
+template<typename Scalar, typename NestedXpr, typename Plain>
+struct blas_traits<CwiseBinaryOp<scalar_product_op<Scalar>, const CwiseNullaryOp<scalar_constant_op<Scalar>,Plain>, NestedXpr> >
+ : blas_traits<NestedXpr>
+{
+  typedef blas_traits<NestedXpr> Base;
+  typedef CwiseBinaryOp<scalar_product_op<Scalar>, const CwiseNullaryOp<scalar_constant_op<Scalar>,Plain>, NestedXpr> XprType;
+  typedef typename Base::ExtractType ExtractType;
+  static inline ExtractType extract(const XprType& x) { return Base::extract(x.rhs()); }
+  static inline Scalar extractScalarFactor(const XprType& x)
+  { return x.lhs().functor().m_other * Base::extractScalarFactor(x.rhs()); }
+};
+template<typename Scalar, typename NestedXpr, typename Plain>
+struct blas_traits<CwiseBinaryOp<scalar_product_op<Scalar>, NestedXpr, const CwiseNullaryOp<scalar_constant_op<Scalar>,Plain> > >
  : blas_traits<NestedXpr>
 {
   typedef blas_traits<NestedXpr> Base;
-  typedef CwiseUnaryOp<scalar_multiple_op<Scalar>, NestedXpr> XprType;
+  typedef CwiseBinaryOp<scalar_product_op<Scalar>, NestedXpr, const CwiseNullaryOp<scalar_constant_op<Scalar>,Plain> > XprType;
   typedef typename Base::ExtractType ExtractType;
-  static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
+  static inline ExtractType extract(const XprType& x) { return Base::extract(x.lhs()); }
   static inline Scalar extractScalarFactor(const XprType& x)
-  { return x.functor().m_other * Base::extractScalarFactor(x.nestedExpression()); }
+  { return Base::extractScalarFactor(x.lhs()) * x.rhs().functor().m_other; }
 };
+template<typename Scalar, typename Plain1, typename Plain2>
+struct blas_traits<CwiseBinaryOp<scalar_product_op<Scalar>, const CwiseNullaryOp<scalar_constant_op<Scalar>,Plain1>,
+                                                            const CwiseNullaryOp<scalar_constant_op<Scalar>,Plain2> > >
+ : blas_traits<CwiseNullaryOp<scalar_constant_op<Scalar>,Plain1> >
+{};
 
 // pop opposite
 template<typename Scalar, typename NestedXpr>
 struct blas_traits<CwiseUnaryOp<scalar_opposite_op<Scalar>, NestedXpr> >
  : blas_traits<NestedXpr>
@@ -228,11 +362,11 @@
     typename ExtractType::PlainObject
     >::type DirectLinearAccessType;
   enum {
     IsTransposed = Base::IsTransposed ? 0 : 1
   };
-  static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
+  static inline ExtractType extract(const XprType& x) { return ExtractType(Base::extract(x.nestedExpression())); }
   static inline Scalar extractScalarFactor(const XprType& x) { return Base::extractScalarFactor(x.nestedExpression()); }
 };
 
 template<typename T>
 struct blas_traits<const T>

DELETED 3rd_party/eigen/Eigen/src/Core/util/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Core/util/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Core/util/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Core_util_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_Core_util_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/util COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/Core/util/Constants.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/Constants.h
+++ 3rd_party/eigen/Eigen/src/Core/util/Constants.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -28,10 +28,18 @@
 /** This value means +Infinity; it is currently used only as the p parameter to MatrixBase::lpNorm<int>().
   * The value Infinity there means the L-infinity norm.
   */
 const int Infinity = -1;
 
+/** This value means that the cost to evaluate an expression coefficient is either very expensive or
+  * cannot be known at compile time.
+  *
+  * This value has to be positive to (1) simplify cost computation, and (2) allow to distinguish between a very expensive and very very expensive expressions.
+  * It thus must also be large enough to make sure unrolling won't happen and that sub expressions will be evaluated, but not too large to avoid overflow.
+  */
+const int HugeCost = 10000;
+
 /** \defgroup flags Flags
   * \ingroup Core_Module
   *
   * These are the possible bits which can be OR'ed to constitute the flags of a matrix or
   * expression.
@@ -46,23 +54,23 @@
 /** \ingroup flags
   *
   * for a matrix, this means that the storage order is row-major.
   * If this bit is not set, the storage order is column-major.
   * For an expression, this determines the storage order of
-  * the matrix created by evaluation of that expression. 
-  * \sa \ref TopicStorageOrders */
+  * the matrix created by evaluation of that expression.
+  * \sa \blank  \ref TopicStorageOrders */
 const unsigned int RowMajorBit = 0x1;
 
 /** \ingroup flags
-  *
   * means the expression should be evaluated by the calling expression */
 const unsigned int EvalBeforeNestingBit = 0x2;
 
 /** \ingroup flags
-  *
+  * \deprecated
   * means the expression should be evaluated before any assignment */
-const unsigned int EvalBeforeAssigningBit = 0x4;
+EIGEN_DEPRECATED
+const unsigned int EvalBeforeAssigningBit = 0x4; // FIXME deprecated
 
 /** \ingroup flags
   *
   * Short version: means the expression might be vectorized
   *
@@ -139,32 +147,61 @@
   *
   * See the comment on LvalueBit for an explanation of how LvalueBit and DirectAccessBit are mutually orthogonal.
   */
 const unsigned int DirectAccessBit = 0x40;
 
-/** \ingroup flags
+/** \deprecated \ingroup flags
   *
-  * means the first coefficient packet is guaranteed to be aligned */
-const unsigned int AlignedBit = 0x80;
+  * means the first coefficient packet is guaranteed to be aligned.
+  * An expression cannot has the AlignedBit without the PacketAccessBit flag.
+  * In other words, this means we are allow to perform an aligned packet access to the first element regardless
+  * of the expression kind:
+  * \code
+  * expression.packet<Aligned>(0);
+  * \endcode
+  */
+EIGEN_DEPRECATED const unsigned int AlignedBit = 0x80;
 
 const unsigned int NestByRefBit = 0x100;
+
+/** \ingroup flags
+  *
+  * for an expression, this means that the storage order
+  * can be either row-major or column-major.
+  * The precise choice will be decided at evaluation time or when
+  * combined with other expressions.
+  * \sa \blank  \ref RowMajorBit, \ref TopicStorageOrders */
+const unsigned int NoPreferredStorageOrderBit = 0x200;
+
+/** \ingroup flags
+  *
+  * Means that the underlying coefficients can be accessed through pointers to the sparse (un)compressed storage format,
+  * that is, the expression provides:
+  * \code
+    inline const Scalar* valuePtr() const;
+    inline const Index* innerIndexPtr() const;
+    inline const Index* outerIndexPtr() const;
+    inline const Index* innerNonZeroPtr() const;
+    \endcode
+  */
+const unsigned int CompressedAccessBit = 0x400;
+
 
 // list of flags that are inherited by default
 const unsigned int HereditaryBits = RowMajorBit
-                                  | EvalBeforeNestingBit
-                                  | EvalBeforeAssigningBit;
+                                  | EvalBeforeNestingBit;
 
 /** \defgroup enums Enumerations
   * \ingroup Core_Module
   *
   * Various enumerations used in %Eigen. Many of these are used as template parameters.
   */
 
 /** \ingroup enums
-  * Enum containing possible values for the \p Mode parameter of 
-  * MatrixBase::selfadjointView() and MatrixBase::triangularView(). */
-enum {
+  * Enum containing possible values for the \c Mode or \c UpLo parameter of
+  * MatrixBase::selfadjointView() and MatrixBase::triangularView(), and selfadjoint solvers. */
+enum UpLoType {
   /** View matrix as a lower triangular matrix. */
   Lower=0x1,                      
   /** View matrix as an upper triangular matrix. */
   Upper=0x2,                      
   /** %Matrix has ones on the diagonal; to be used in combination with #Lower or #Upper. */
@@ -184,16 +221,35 @@
   /** Used to support symmetric, non-selfadjoint, complex matrices. */
   Symmetric=0x20
 };
 
 /** \ingroup enums
-  * Enum for indicating whether an object is aligned or not. */
-enum { 
-  /** Object is not correctly aligned for vectorization. */
-  Unaligned=0, 
-  /** Object is aligned for vectorization. */
-  Aligned=1 
+  * Enum for indicating whether a buffer is aligned or not. */
+enum AlignmentType {
+  Unaligned=0,        /**< Data pointer has no specific alignment. */
+  Aligned8=8,         /**< Data pointer is aligned on a 8 bytes boundary. */
+  Aligned16=16,       /**< Data pointer is aligned on a 16 bytes boundary. */
+  Aligned32=32,       /**< Data pointer is aligned on a 32 bytes boundary. */
+  Aligned64=64,       /**< Data pointer is aligned on a 64 bytes boundary. */
+  Aligned128=128,     /**< Data pointer is aligned on a 128 bytes boundary. */
+  AlignedMask=255,
+  Aligned=16,         /**< \deprecated Synonym for Aligned16. */
+#if EIGEN_MAX_ALIGN_BYTES==128
+  AlignedMax = Aligned128
+#elif EIGEN_MAX_ALIGN_BYTES==64
+  AlignedMax = Aligned64
+#elif EIGEN_MAX_ALIGN_BYTES==32
+  AlignedMax = Aligned32
+#elif EIGEN_MAX_ALIGN_BYTES==16
+  AlignedMax = Aligned16
+#elif EIGEN_MAX_ALIGN_BYTES==8
+  AlignedMax = Aligned8
+#elif EIGEN_MAX_ALIGN_BYTES==0
+  AlignedMax = Unaligned
+#else
+#error Invalid value for EIGEN_MAX_ALIGN_BYTES
+#endif
 };
 
 /** \ingroup enums
  * Enum used by DenseBase::corner() in Eigen2 compatibility mode. */
 // FIXME after the corner() API change, this was not needed anymore, except by AlignedBox
@@ -215,11 +271,11 @@
   BothDirections 
 };
 
 /** \internal \ingroup enums
   * Enum to specify how to traverse the entries of a matrix. */
-enum {
+enum TraversalType {
   /** \internal Default traversal, no vectorization, no index-based access */
   DefaultTraversal,
   /** \internal No vectorization, use index-based access to have only one for loop instead of 2 nested loops */
   LinearTraversal,
   /** \internal Equivalent to a slice vectorization for fixed-size matrices having good alignment
@@ -237,11 +293,11 @@
   AllAtOnceTraversal
 };
 
 /** \internal \ingroup enums
   * Enum to specify whether to unroll loops when traversing over the entries of a matrix. */
-enum {
+enum UnrollingType {
   /** \internal Do not unroll loops. */
   NoUnrolling,
   /** \internal Unroll only the inner loop, but not the outer loop. */
   InnerUnrolling,
   /** \internal Unroll both the inner and the outer loop. If there is only one loop, 
@@ -249,19 +305,19 @@
   CompleteUnrolling
 };
 
 /** \internal \ingroup enums
   * Enum to specify whether to use the default (built-in) implementation or the specialization. */
-enum {
+enum SpecializedType {
   Specialized,
   BuiltIn
 };
 
 /** \ingroup enums
   * Enum containing possible values for the \p _Options template parameter of
   * Matrix, Array and BandMatrix. */
-enum {
+enum StorageOptions {
   /** Storage order is column major (see \ref TopicStorageOrders). */
   ColMajor = 0,
   /** Storage order is row major (see \ref TopicStorageOrders). */
   RowMajor = 0x1,  // it is only a coincidence that this is equal to RowMajorBit -- don't rely on that
   /** Align the matrix itself if it is vectorizable fixed-size */
@@ -270,11 +326,11 @@
   DontAlign = 0x2
 };
 
 /** \ingroup enums
   * Enum for specifying whether to apply or solve on the left or right. */
-enum {
+enum SideType {
   /** Apply transformation on the left. */
   OnTheLeft = 1,  
   /** Apply transformation on the right. */
   OnTheRight = 2  
 };
@@ -295,11 +351,11 @@
 enum Sequential_t { Sequential };
 enum Default_t    { Default };
 
 /** \internal \ingroup enums
   * Used in AmbiVector. */
-enum {
+enum AmbiVectorMode {
   IsDense         = 0,
   IsSparse
 };
 
 /** \ingroup enums
@@ -404,35 +460,88 @@
 {
   enum Type {
     Generic = 0x0,
     SSE = 0x1,
     AltiVec = 0x2,
+    VSX = 0x3,
+    NEON = 0x4,
 #if defined EIGEN_VECTORIZE_SSE
     Target = SSE
 #elif defined EIGEN_VECTORIZE_ALTIVEC
     Target = AltiVec
+#elif defined EIGEN_VECTORIZE_VSX
+    Target = VSX
+#elif defined EIGEN_VECTORIZE_NEON
+    Target = NEON
 #else
     Target = Generic
 #endif
   };
 }
 
 /** \internal \ingroup enums
-  * Enum used as template parameter in GeneralProduct. */
-enum { CoeffBasedProductMode, LazyCoeffBasedProductMode, OuterProduct, InnerProduct, GemvProduct, GemmProduct };
+  * Enum used as template parameter in Product and product evaluators. */
+enum ProductImplType
+{ DefaultProduct=0, LazyProduct, AliasFreeProduct, CoeffBasedProductMode, LazyCoeffBasedProductMode, OuterProduct, InnerProduct, GemvProduct, GemmProduct };
 
 /** \internal \ingroup enums
   * Enum used in experimental parallel implementation. */
 enum Action {GetAction, SetAction};
 
 /** The type used to identify a dense storage. */
 struct Dense {};
+
+/** The type used to identify a general sparse storage. */
+struct Sparse {};
+
+/** The type used to identify a general solver (factored) storage. */
+struct SolverStorage {};
+
+/** The type used to identify a permutation storage. */
+struct PermutationStorage {};
+
+/** The type used to identify a permutation storage. */
+struct TranspositionsStorage {};
 
 /** The type used to identify a matrix expression */
 struct MatrixXpr {};
 
 /** The type used to identify an array expression */
 struct ArrayXpr {};
+
+// An evaluator must define its shape. By default, it can be one of the following:
+struct DenseShape             { static std::string debugName() { return "DenseShape"; } };
+struct SolverShape            { static std::string debugName() { return "SolverShape"; } };
+struct HomogeneousShape       { static std::string debugName() { return "HomogeneousShape"; } };
+struct DiagonalShape          { static std::string debugName() { return "DiagonalShape"; } };
+struct BandShape              { static std::string debugName() { return "BandShape"; } };
+struct TriangularShape        { static std::string debugName() { return "TriangularShape"; } };
+struct SelfAdjointShape       { static std::string debugName() { return "SelfAdjointShape"; } };
+struct PermutationShape       { static std::string debugName() { return "PermutationShape"; } };
+struct TranspositionsShape    { static std::string debugName() { return "TranspositionsShape"; } };
+struct SparseShape            { static std::string debugName() { return "SparseShape"; } };
+
+namespace internal {
+
+  // random access iterators based on coeff*() accessors.
+struct IndexBased {};
+
+// evaluator based on iterators to access coefficients. 
+struct IteratorBased {};
+
+/** \internal
+ * Constants for comparison functors
+ */
+enum ComparisonName {
+  cmp_EQ = 0,
+  cmp_LT = 1,
+  cmp_LE = 2,
+  cmp_UNORD = 3,
+  cmp_NEQ = 4,
+  cmp_GT = 5,
+  cmp_GE = 6
+};
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_CONSTANTS_H

Index: 3rd_party/eigen/Eigen/src/Core/util/DisableStupidWarnings.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/DisableStupidWarnings.h
+++ 3rd_party/eigen/Eigen/src/Core/util/DisableStupidWarnings.h
@@ -8,33 +8,68 @@
   // 4181 - qualifier applied to reference type ignored
   // 4211 - nonstandard extension used : redefined extern to static
   // 4244 - 'argument' : conversion from 'type1' to 'type2', possible loss of data
   // 4273 - QtAlignedMalloc, inconsistent DLL linkage
   // 4324 - structure was padded due to declspec(align())
+  // 4503 - decorated name length exceeded, name was truncated
   // 4512 - assignment operator could not be generated
   // 4522 - 'class' : multiple assignment operators specified
   // 4700 - uninitialized local variable 'xyz' used
+  // 4714 - function marked as __forceinline not inlined
   // 4717 - 'function' : recursive on all control paths, function will cause runtime stack overflow
+  // 4800 - 'type' : forcing value to bool 'true' or 'false' (performance warning)
   #ifndef EIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS
     #pragma warning( push )
   #endif
-  #pragma warning( disable : 4100 4101 4127 4181 4211 4244 4273 4324 4512 4522 4700 4717 )
+  #pragma warning( disable : 4100 4101 4127 4181 4211 4244 4273 4324 4503 4512 4522 4700 4714 4717 4800)
+
 #elif defined __INTEL_COMPILER
   // 2196 - routine is both "inline" and "noinline" ("noinline" assumed)
   //        ICC 12 generates this warning even without any inline keyword, when defining class methods 'inline' i.e. inside of class body
   //        typedef that may be a reference type.
   // 279  - controlling expression is constant
   //        ICC 12 generates this warning on assert(constant_expression_depending_on_template_params) and frankly this is a legitimate use case.
+  // 1684 - conversion from pointer to same-sized integral type (potential portability problem)
+  // 2259 - non-pointer conversion from "Eigen::Index={ptrdiff_t={long}}" to "int" may lose significant bits
   #ifndef EIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS
     #pragma warning push
   #endif
-  #pragma warning disable 2196 279
+  #pragma warning disable 2196 279 1684 2259
+
 #elif defined __clang__
   // -Wconstant-logical-operand - warning: use of logical && with constant operand; switch to bitwise & or remove constant
   //     this is really a stupid warning as it warns on compile-time expressions involving enums
   #ifndef EIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS
     #pragma clang diagnostic push
   #endif
   #pragma clang diagnostic ignored "-Wconstant-logical-operand"
+
+#elif defined __GNUC__ && __GNUC__>=6
+
+  #ifndef EIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS
+    #pragma GCC diagnostic push
+  #endif
+  #pragma GCC diagnostic ignored "-Wignored-attributes"
+
+#endif
+
+#if defined __NVCC__
+  // Disable the "statement is unreachable" message
+  #pragma diag_suppress code_is_unreachable
+  // Disable the "dynamic initialization in unreachable code" message
+  #pragma diag_suppress initialization_not_reachable
+  // Disable the "invalid error number" message that we get with older versions of nvcc
+  #pragma diag_suppress 1222
+  // Disable the "calling a __host__ function from a __host__ __device__ function is not allowed" messages (yes, there are many of them and they seem to change with every version of the compiler)
+  #pragma diag_suppress 2527
+  #pragma diag_suppress 2529
+  #pragma diag_suppress 2651
+  #pragma diag_suppress 2653
+  #pragma diag_suppress 2668
+  #pragma diag_suppress 2669
+  #pragma diag_suppress 2670
+  #pragma diag_suppress 2671
+  #pragma diag_suppress 2735
+  #pragma diag_suppress 2737
 #endif
 
 #endif // not EIGEN_WARNINGS_DISABLED

Index: 3rd_party/eigen/Eigen/src/Core/util/ForwardDeclarations.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/ForwardDeclarations.h
+++ 3rd_party/eigen/Eigen/src/Core/util/ForwardDeclarations.h
@@ -34,10 +34,14 @@
          value = has_direct_access ? (has_write_access ? DirectWriteAccessors : DirectAccessors)
                                    : (has_write_access ? WriteAccessors       : ReadOnlyAccessors)
   };
 };
 
+template<typename T> struct evaluator_traits;
+
+template< typename T> struct evaluator;
+
 } // end namespace internal
 
 template<typename T> struct NumTraits;
 
 template<typename Derived> struct EigenBase;
@@ -49,22 +53,22 @@
          int Level = internal::accessors_level<Derived>::value >
 class DenseCoeffsBase;
 
 template<typename _Scalar, int _Rows, int _Cols,
          int _Options = AutoAlign |
-#if defined(__GNUC__) && __GNUC__==3 && __GNUC_MINOR__==4
+#if EIGEN_GNUC_AT(3,4)
     // workaround a bug in at least gcc 3.4.6
     // the innermost ?: ternary operator is misparsed. We write it slightly
     // differently and this makes gcc 3.4.6 happy, but it's ugly.
     // The error would only show up with EIGEN_DEFAULT_TO_ROW_MAJOR is defined
     // (when EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION is RowMajor)
-                          ( (_Rows==1 && _Cols!=1) ? RowMajor
+                          ( (_Rows==1 && _Cols!=1) ? Eigen::RowMajor
                           : !(_Cols==1 && _Rows!=1) ?  EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION
-                          : ColMajor ),
+                          : Eigen::ColMajor ),
 #else
-                          ( (_Rows==1 && _Cols!=1) ? RowMajor
-                          : (_Cols==1 && _Rows!=1) ? ColMajor
+                          ( (_Rows==1 && _Cols!=1) ? Eigen::RowMajor
+                          : (_Cols==1 && _Rows!=1) ? Eigen::ColMajor
                           : EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ),
 #endif
          int _MaxRows = _Rows,
          int _MaxCols = _Cols
 > class Matrix;
@@ -85,14 +89,15 @@
 template<typename MatrixType> class Conjugate;
 template<typename NullaryOp, typename MatrixType>         class CwiseNullaryOp;
 template<typename UnaryOp,   typename MatrixType>         class CwiseUnaryOp;
 template<typename ViewOp,    typename MatrixType>         class CwiseUnaryView;
 template<typename BinaryOp,  typename Lhs, typename Rhs>  class CwiseBinaryOp;
-template<typename BinOp,     typename Lhs, typename Rhs>  class SelfCwiseBinaryOp;
-template<typename Derived,   typename Lhs, typename Rhs>  class ProductBase;
-template<typename Lhs, typename Rhs, int Mode>            class GeneralProduct;
-template<typename Lhs, typename Rhs, int NestingFlags>    class CoeffBasedProduct;
+template<typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>  class CwiseTernaryOp;
+template<typename Decomposition, typename Rhstype>        class Solve;
+template<typename XprType>                                class Inverse;
+
+template<typename Lhs, typename Rhs, int Option = DefaultProduct> class Product;
 
 template<typename Derived> class DiagonalBase;
 template<typename _DiagonalVectorType> class DiagonalWrapper;
 template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime=SizeAtCompileTime> class DiagonalMatrix;
 template<typename MatrixType, typename DiagonalType, int ProductOrder> class DiagonalProduct;
@@ -106,11 +111,16 @@
 
 template<typename Derived,
          int Level = internal::accessors_level<Derived>::has_write_access ? WriteAccessors : ReadOnlyAccessors
 > class MapBase;
 template<int InnerStrideAtCompileTime, int OuterStrideAtCompileTime> class Stride;
+template<int Value = Dynamic> class InnerStride;
+template<int Value = Dynamic> class OuterStride;
 template<typename MatrixType, int MapOptions=Unaligned, typename StrideType = Stride<0,0> > class Map;
+template<typename Derived> class RefBase;
+template<typename PlainObjectType, int Options = 0,
+         typename StrideType = typename internal::conditional<PlainObjectType::IsVectorAtCompileTime,InnerStride<1>,OuterStride<> >::type > class Ref;
 
 template<typename Derived> class TriangularBase;
 template<typename MatrixType, unsigned int Mode> class TriangularView;
 template<typename MatrixType, unsigned int Mode> class SelfAdjointView;
 template<typename MatrixType> class SparseView;
@@ -117,14 +127,14 @@
 template<typename ExpressionType> class WithFormat;
 template<typename MatrixType> struct CommaInitializer;
 template<typename Derived> class ReturnByValue;
 template<typename ExpressionType> class ArrayWrapper;
 template<typename ExpressionType> class MatrixWrapper;
+template<typename Derived> class SolverBase;
+template<typename XprType> class InnerIterator;
 
 namespace internal {
-template<typename DecompositionType, typename Rhs> struct solve_retval_base;
-template<typename DecompositionType, typename Rhs> struct solve_retval;
 template<typename DecompositionType> struct kernel_retval_base;
 template<typename DecompositionType> struct kernel_retval;
 template<typename DecompositionType> struct image_retval_base;
 template<typename DecompositionType> struct image_retval;
 } // end namespace internal
@@ -133,10 +143,25 @@
 template<typename _Scalar, int Rows=Dynamic, int Cols=Dynamic, int Supers=Dynamic, int Subs=Dynamic, int Options=0> class BandMatrix;
 }
 
 namespace internal {
 template<typename Lhs, typename Rhs> struct product_type;
+
+template<bool> struct EnableIf;
+
+/** \internal
+  * \class product_evaluator
+  * Products need their own evaluator with more template arguments allowing for
+  * easier partial template specializations.
+  */
+template< typename T,
+          int ProductTag = internal::product_type<typename T::Lhs,typename T::Rhs>::ret,
+          typename LhsShape = typename evaluator_traits<typename T::Lhs>::Shape,
+          typename RhsShape = typename evaluator_traits<typename T::Rhs>::Shape,
+          typename LhsScalar = typename traits<typename T::Lhs>::Scalar,
+          typename RhsScalar = typename traits<typename T::Rhs>::Scalar
+        > struct product_evaluator;
 }
 
 template<typename Lhs, typename Rhs,
          int ProductType = internal::product_type<Lhs,Rhs>::value>
 struct ProductReturnType;
@@ -148,64 +173,72 @@
 
 // Provides scalar/packet-wise product and product with accumulation
 // with optional conjugation of the arguments.
 template<typename LhsScalar, typename RhsScalar, bool ConjLhs=false, bool ConjRhs=false> struct conj_helper;
 
-template<typename Scalar> struct scalar_sum_op;
-template<typename Scalar> struct scalar_difference_op;
-template<typename LhsScalar,typename RhsScalar> struct scalar_conj_product_op;
+template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_sum_op;
+template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_difference_op;
+template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_conj_product_op;
+template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_min_op;
+template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_max_op;
 template<typename Scalar> struct scalar_opposite_op;
 template<typename Scalar> struct scalar_conjugate_op;
 template<typename Scalar> struct scalar_real_op;
 template<typename Scalar> struct scalar_imag_op;
 template<typename Scalar> struct scalar_abs_op;
 template<typename Scalar> struct scalar_abs2_op;
 template<typename Scalar> struct scalar_sqrt_op;
+template<typename Scalar> struct scalar_rsqrt_op;
 template<typename Scalar> struct scalar_exp_op;
 template<typename Scalar> struct scalar_log_op;
 template<typename Scalar> struct scalar_cos_op;
 template<typename Scalar> struct scalar_sin_op;
 template<typename Scalar> struct scalar_acos_op;
 template<typename Scalar> struct scalar_asin_op;
 template<typename Scalar> struct scalar_tan_op;
-template<typename Scalar> struct scalar_pow_op;
 template<typename Scalar> struct scalar_inverse_op;
 template<typename Scalar> struct scalar_square_op;
 template<typename Scalar> struct scalar_cube_op;
 template<typename Scalar, typename NewType> struct scalar_cast_op;
-template<typename Scalar> struct scalar_multiple_op;
-template<typename Scalar> struct scalar_quotient1_op;
-template<typename Scalar> struct scalar_min_op;
-template<typename Scalar> struct scalar_max_op;
 template<typename Scalar> struct scalar_random_op;
-template<typename Scalar> struct scalar_add_op;
 template<typename Scalar> struct scalar_constant_op;
 template<typename Scalar> struct scalar_identity_op;
-
+template<typename Scalar,bool iscpx> struct scalar_sign_op;
+template<typename Scalar,typename ScalarExponent> struct scalar_pow_op;
+template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_hypot_op;
 template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_product_op;
-template<typename LhsScalar,typename RhsScalar> struct scalar_multiple2_op;
 template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_quotient_op;
 
+// SpecialFunctions module
+template<typename Scalar> struct scalar_lgamma_op;
+template<typename Scalar> struct scalar_digamma_op;
+template<typename Scalar> struct scalar_erf_op;
+template<typename Scalar> struct scalar_erfc_op;
+template<typename Scalar> struct scalar_igamma_op;
+template<typename Scalar> struct scalar_igammac_op;
+template<typename Scalar> struct scalar_zeta_op;
+template<typename Scalar> struct scalar_betainc_op;
+
 } // end namespace internal
 
 struct IOFormat;
 
 // Array module
 template<typename _Scalar, int _Rows, int _Cols,
          int _Options = AutoAlign |
-#if defined(__GNUC__) && __GNUC__==3 && __GNUC_MINOR__==4
+#if EIGEN_GNUC_AT(3,4)
     // workaround a bug in at least gcc 3.4.6
     // the innermost ?: ternary operator is misparsed. We write it slightly
     // differently and this makes gcc 3.4.6 happy, but it's ugly.
     // The error would only show up with EIGEN_DEFAULT_TO_ROW_MAJOR is defined
     // (when EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION is RowMajor)
-                          ( (_Rows==1 && _Cols!=1) ? RowMajor
+                          ( (_Rows==1 && _Cols!=1) ? Eigen::RowMajor
                           : !(_Cols==1 && _Rows!=1) ?  EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION
-                          : ColMajor ),
+                          : Eigen::ColMajor ),
 #else
-                          ( (_Rows==1 && _Cols!=1) ? RowMajor
-                          : (_Cols==1 && _Rows!=1) ? ColMajor
+                          ( (_Rows==1 && _Cols!=1) ? Eigen::RowMajor
+                          : (_Cols==1 && _Rows!=1) ? Eigen::ColMajor
                           : EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ),
 #endif
          int _MaxRows = _Rows, int _MaxCols = _Cols> class Array;
 template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType> class Select;
 template<typename MatrixType, typename BinaryOp, int Direction> class PartialReduxExpr;
@@ -219,11 +252,13 @@
 template<typename MatrixType> struct inverse_impl;
 }
 template<typename MatrixType> class HouseholderQR;
 template<typename MatrixType> class ColPivHouseholderQR;
 template<typename MatrixType> class FullPivHouseholderQR;
+template<typename MatrixType> class CompleteOrthogonalDecomposition;
 template<typename MatrixType, int QRPreconditioner = ColPivHouseholderQRPreconditioner> class JacobiSVD;
+template<typename MatrixType> class BDCSVD;
 template<typename MatrixType, int UpLo = Lower> class LLT;
 template<typename MatrixType, int UpLo = Lower> class LDLT;
 template<typename VectorsType, typename CoeffsType, int Side=OnTheLeft> class HouseholderSequence;
 template<typename Scalar>     class JacobiRotation;
 
@@ -232,48 +267,28 @@
 template<typename Lhs, typename Rhs> class Cross;
 template<typename Derived> class QuaternionBase;
 template<typename Scalar> class Rotation2D;
 template<typename Scalar> class AngleAxis;
 template<typename Scalar,int Dim> class Translation;
-
-#ifdef EIGEN2_SUPPORT
-template<typename Derived, int _Dim> class eigen2_RotationBase;
-template<typename Lhs, typename Rhs> class eigen2_Cross;
-template<typename Scalar> class eigen2_Quaternion;
-template<typename Scalar> class eigen2_Rotation2D;
-template<typename Scalar> class eigen2_AngleAxis;
-template<typename Scalar,int Dim> class eigen2_Transform;
-template <typename _Scalar, int _AmbientDim> class eigen2_ParametrizedLine;
-template <typename _Scalar, int _AmbientDim> class eigen2_Hyperplane;
-template<typename Scalar,int Dim> class eigen2_Translation;
-template<typename Scalar,int Dim> class eigen2_Scaling;
-#endif
-
-#if EIGEN2_SUPPORT_STAGE < STAGE20_RESOLVE_API_CONFLICTS
-template<typename Scalar> class Quaternion;
-template<typename Scalar,int Dim> class Transform;
-template <typename _Scalar, int _AmbientDim> class ParametrizedLine;
-template <typename _Scalar, int _AmbientDim> class Hyperplane;
-template<typename Scalar,int Dim> class Scaling;
-#endif
-
-#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
+template<typename Scalar,int Dim> class AlignedBox;
 template<typename Scalar, int Options = AutoAlign> class Quaternion;
 template<typename Scalar,int Dim,int Mode,int _Options=AutoAlign> class Transform;
 template <typename _Scalar, int _AmbientDim, int Options=AutoAlign> class ParametrizedLine;
 template <typename _Scalar, int _AmbientDim, int Options=AutoAlign> class Hyperplane;
 template<typename Scalar> class UniformScaling;
 template<typename MatrixType,int Direction> class Homogeneous;
-#endif
+
+// Sparse module:
+template<typename Derived> class SparseMatrixBase;
 
 // MatrixFunctions module
 template<typename Derived> struct MatrixExponentialReturnValue;
 template<typename Derived> class MatrixFunctionReturnValue;
 template<typename Derived> class MatrixSquareRootReturnValue;
 template<typename Derived> class MatrixLogarithmReturnValue;
 template<typename Derived> class MatrixPowerReturnValue;
-template<typename Derived, typename Lhs, typename Rhs> class MatrixPowerProduct;
+template<typename Derived> class MatrixComplexPowerReturnValue;
 
 namespace internal {
 template <typename Scalar>
 struct stem_function
 {
@@ -280,20 +295,8 @@
   typedef std::complex<typename NumTraits<Scalar>::Real> ComplexScalar;
   typedef ComplexScalar type(ComplexScalar, int);
 };
 }
 
-
-#ifdef EIGEN2_SUPPORT
-template<typename ExpressionType> class Cwise;
-template<typename MatrixType> class Minor;
-template<typename MatrixType> class LU;
-template<typename MatrixType> class QR;
-template<typename MatrixType> class SVD;
-namespace internal {
-template<typename MatrixType, unsigned int Mode> struct eigen2_part_return_type;
-}
-#endif
-
 } // end namespace Eigen
 
 #endif // EIGEN_FORWARDDECLARATIONS_H

Index: 3rd_party/eigen/Eigen/src/Core/util/MKL_support.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/MKL_support.h
+++ 3rd_party/eigen/Eigen/src/Core/util/MKL_support.h
@@ -47,11 +47,11 @@
 
 #ifdef EIGEN_USE_LAPACKE_STRICT
   #define EIGEN_USE_LAPACKE
 #endif
 
-#if defined(EIGEN_USE_BLAS) || defined(EIGEN_USE_LAPACKE) || defined(EIGEN_USE_MKL_VML)
+#if defined(EIGEN_USE_MKL_VML)
   #define EIGEN_USE_MKL
 #endif
 
 #if defined EIGEN_USE_MKL
 #   include <mkl.h> 
@@ -62,65 +62,67 @@
 #       undef EIGEN_USE_MKL
 #   endif
 #   ifndef EIGEN_USE_MKL
     /*If the MKL version is too old, undef everything*/
 #       undef   EIGEN_USE_MKL_ALL
-#       undef   EIGEN_USE_BLAS
 #       undef   EIGEN_USE_LAPACKE
 #       undef   EIGEN_USE_MKL_VML
 #       undef   EIGEN_USE_LAPACKE_STRICT
 #       undef   EIGEN_USE_LAPACKE
 #   endif
 #endif
 
 #if defined EIGEN_USE_MKL
-#include <mkl_lapacke.h>
+
 #define EIGEN_MKL_VML_THRESHOLD 128
+
+/* MKL_DOMAIN_BLAS, etc are defined only in 10.3 update 7 */
+/* MKL_BLAS, etc are not defined in 11.2 */
+#ifdef MKL_DOMAIN_ALL
+#define EIGEN_MKL_DOMAIN_ALL MKL_DOMAIN_ALL
+#else
+#define EIGEN_MKL_DOMAIN_ALL MKL_ALL
+#endif
+
+#ifdef MKL_DOMAIN_BLAS
+#define EIGEN_MKL_DOMAIN_BLAS MKL_DOMAIN_BLAS
+#else
+#define EIGEN_MKL_DOMAIN_BLAS MKL_BLAS
+#endif
+
+#ifdef MKL_DOMAIN_FFT
+#define EIGEN_MKL_DOMAIN_FFT MKL_DOMAIN_FFT
+#else
+#define EIGEN_MKL_DOMAIN_FFT MKL_FFT
+#endif
+
+#ifdef MKL_DOMAIN_VML
+#define EIGEN_MKL_DOMAIN_VML MKL_DOMAIN_VML
+#else
+#define EIGEN_MKL_DOMAIN_VML MKL_VML
+#endif
+
+#ifdef MKL_DOMAIN_PARDISO
+#define EIGEN_MKL_DOMAIN_PARDISO MKL_DOMAIN_PARDISO
+#else
+#define EIGEN_MKL_DOMAIN_PARDISO MKL_PARDISO
+#endif
+#endif
 
 namespace Eigen {
 
 typedef std::complex<double> dcomplex;
 typedef std::complex<float>  scomplex;
 
-namespace internal {
-
-template<typename MKLType, typename EigenType>
-static inline void assign_scalar_eig2mkl(MKLType& mklScalar, const EigenType& eigenScalar) {
-  mklScalar=eigenScalar;
-}
-
-template<typename MKLType, typename EigenType>
-static inline void assign_conj_scalar_eig2mkl(MKLType& mklScalar, const EigenType& eigenScalar) {
-  mklScalar=eigenScalar;
-}
-
-template <>
-inline void assign_scalar_eig2mkl<MKL_Complex16,dcomplex>(MKL_Complex16& mklScalar, const dcomplex& eigenScalar) {
-  mklScalar.real=eigenScalar.real();
-  mklScalar.imag=eigenScalar.imag();
-}
-
-template <>
-inline void assign_scalar_eig2mkl<MKL_Complex8,scomplex>(MKL_Complex8& mklScalar, const scomplex& eigenScalar) {
-  mklScalar.real=eigenScalar.real();
-  mklScalar.imag=eigenScalar.imag();
-}
-
-template <>
-inline void assign_conj_scalar_eig2mkl<MKL_Complex16,dcomplex>(MKL_Complex16& mklScalar, const dcomplex& eigenScalar) {
-  mklScalar.real=eigenScalar.real();
-  mklScalar.imag=-eigenScalar.imag();
-}
-
-template <>
-inline void assign_conj_scalar_eig2mkl<MKL_Complex8,scomplex>(MKL_Complex8& mklScalar, const scomplex& eigenScalar) {
-  mklScalar.real=eigenScalar.real();
-  mklScalar.imag=-eigenScalar.imag();
-}
-
-} // end namespace internal
+#if defined(EIGEN_USE_MKL)
+typedef MKL_INT BlasIndex;
+#else
+typedef int BlasIndex;
+#endif
 
 } // end namespace Eigen
 
+#if defined(EIGEN_USE_BLAS)
+#include "../../misc/blas.h"
 #endif
 
 #endif // EIGEN_MKL_SUPPORT_H

Index: 3rd_party/eigen/Eigen/src/Core/util/Macros.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/Macros.h
+++ 3rd_party/eigen/Eigen/src/Core/util/Macros.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -10,88 +10,328 @@
 
 #ifndef EIGEN_MACROS_H
 #define EIGEN_MACROS_H
 
 #define EIGEN_WORLD_VERSION 3
-#define EIGEN_MAJOR_VERSION 2
+#define EIGEN_MAJOR_VERSION 3
 #define EIGEN_MINOR_VERSION 4
 
 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
                                       (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
                                                                  EIGEN_MINOR_VERSION>=z))))
+
+// Compiler identification, EIGEN_COMP_*
+
+/// \internal EIGEN_COMP_GNUC set to 1 for all compilers compatible with GCC
 #ifdef __GNUC__
+  #define EIGEN_COMP_GNUC 1
+#else
+  #define EIGEN_COMP_GNUC 0
+#endif
+
+/// \internal EIGEN_COMP_CLANG set to major+minor version (e.g., 307 for clang 3.7) if the compiler is clang
+#if defined(__clang__)
+  #define EIGEN_COMP_CLANG (__clang_major__*100+__clang_minor__)
+#else
+  #define EIGEN_COMP_CLANG 0
+#endif
+
+
+/// \internal EIGEN_COMP_LLVM set to 1 if the compiler backend is llvm
+#if defined(__llvm__)
+  #define EIGEN_COMP_LLVM 1
+#else
+  #define EIGEN_COMP_LLVM 0
+#endif
+
+/// \internal EIGEN_COMP_ICC set to __INTEL_COMPILER if the compiler is Intel compiler, 0 otherwise
+#if defined(__INTEL_COMPILER)
+  #define EIGEN_COMP_ICC __INTEL_COMPILER
+#else
+  #define EIGEN_COMP_ICC 0
+#endif
+
+/// \internal EIGEN_COMP_MINGW set to 1 if the compiler is mingw
+#if defined(__MINGW32__)
+  #define EIGEN_COMP_MINGW 1
+#else
+  #define EIGEN_COMP_MINGW 0
+#endif
+
+/// \internal EIGEN_COMP_SUNCC set to 1 if the compiler is Solaris Studio
+#if defined(__SUNPRO_CC)
+  #define EIGEN_COMP_SUNCC 1
+#else
+  #define EIGEN_COMP_SUNCC 0
+#endif
+
+/// \internal EIGEN_COMP_MSVC set to _MSC_VER if the compiler is Microsoft Visual C++, 0 otherwise.
+#if defined(_MSC_VER)
+  #define EIGEN_COMP_MSVC _MSC_VER
+#else
+  #define EIGEN_COMP_MSVC 0
+#endif
+
+// For the record, here is a table summarizing the possible values for EIGEN_COMP_MSVC:
+//  name  ver   MSC_VER
+//  2008    9      1500
+//  2010   10      1600
+//  2012   11      1700
+//  2013   12      1800
+//  2015   14      1900
+//  "15"   15      1900
+
+/// \internal EIGEN_COMP_MSVC_STRICT set to 1 if the compiler is really Microsoft Visual C++ and not ,e.g., ICC or clang-cl
+#if EIGEN_COMP_MSVC && !(EIGEN_COMP_ICC || EIGEN_COMP_LLVM || EIGEN_COMP_CLANG)
+  #define EIGEN_COMP_MSVC_STRICT _MSC_VER
+#else
+  #define EIGEN_COMP_MSVC_STRICT 0
+#endif
+
+/// \internal EIGEN_COMP_IBM set to 1 if the compiler is IBM XL C++
+#if defined(__IBMCPP__) || defined(__xlc__)
+  #define EIGEN_COMP_IBM 1
+#else
+  #define EIGEN_COMP_IBM 0
+#endif
+
+/// \internal EIGEN_COMP_PGI set to 1 if the compiler is Portland Group Compiler
+#if defined(__PGI)
+  #define EIGEN_COMP_PGI 1
+#else
+  #define EIGEN_COMP_PGI 0
+#endif
+
+/// \internal EIGEN_COMP_ARM set to 1 if the compiler is ARM Compiler
+#if defined(__CC_ARM) || defined(__ARMCC_VERSION)
+  #define EIGEN_COMP_ARM 1
+#else
+  #define EIGEN_COMP_ARM 0
+#endif
+
+/// \internal EIGEN_COMP_ARM set to 1 if the compiler is ARM Compiler
+#if defined(__EMSCRIPTEN__)
+  #define EIGEN_COMP_EMSCRIPTEN 1
+#else
+  #define EIGEN_COMP_EMSCRIPTEN 0
+#endif
+
+
+/// \internal EIGEN_GNUC_STRICT set to 1 if the compiler is really GCC and not a compatible compiler (e.g., ICC, clang, mingw, etc.)
+#if EIGEN_COMP_GNUC && !(EIGEN_COMP_CLANG || EIGEN_COMP_ICC || EIGEN_COMP_MINGW || EIGEN_COMP_PGI || EIGEN_COMP_IBM || EIGEN_COMP_ARM || EIGEN_COMP_EMSCRIPTEN)
+  #define EIGEN_COMP_GNUC_STRICT 1
+#else
+  #define EIGEN_COMP_GNUC_STRICT 0
+#endif
+
+
+#if EIGEN_COMP_GNUC
   #define EIGEN_GNUC_AT_LEAST(x,y) ((__GNUC__==x && __GNUC_MINOR__>=y) || __GNUC__>x)
+  #define EIGEN_GNUC_AT_MOST(x,y)  ((__GNUC__==x && __GNUC_MINOR__<=y) || __GNUC__<x)
+  #define EIGEN_GNUC_AT(x,y)       ( __GNUC__==x && __GNUC_MINOR__==y )
 #else
   #define EIGEN_GNUC_AT_LEAST(x,y) 0
+  #define EIGEN_GNUC_AT_MOST(x,y)  0
+  #define EIGEN_GNUC_AT(x,y)       0
+#endif
+
+// FIXME: could probably be removed as we do not support gcc 3.x anymore
+#if EIGEN_COMP_GNUC && (__GNUC__ <= 3)
+#define EIGEN_GCC3_OR_OLDER 1
+#else
+#define EIGEN_GCC3_OR_OLDER 0
+#endif
+
+
+// Architecture identification, EIGEN_ARCH_*
+
+#if defined(__x86_64__) || defined(_M_X64) || defined(__amd64)
+  #define EIGEN_ARCH_x86_64 1
+#else
+  #define EIGEN_ARCH_x86_64 0
+#endif
+
+#if defined(__i386__) || defined(_M_IX86) || defined(_X86_) || defined(__i386)
+  #define EIGEN_ARCH_i386 1
+#else
+  #define EIGEN_ARCH_i386 0
+#endif
+
+#if EIGEN_ARCH_x86_64 || EIGEN_ARCH_i386
+  #define EIGEN_ARCH_i386_OR_x86_64 1
+#else
+  #define EIGEN_ARCH_i386_OR_x86_64 0
+#endif
+
+/// \internal EIGEN_ARCH_ARM set to 1 if the architecture is ARM
+#if defined(__arm__)
+  #define EIGEN_ARCH_ARM 1
+#else
+  #define EIGEN_ARCH_ARM 0
+#endif
+
+/// \internal EIGEN_ARCH_ARM64 set to 1 if the architecture is ARM64
+#if defined(__aarch64__)
+  #define EIGEN_ARCH_ARM64 1
+#else
+  #define EIGEN_ARCH_ARM64 0
+#endif
+
+#if EIGEN_ARCH_ARM || EIGEN_ARCH_ARM64
+  #define EIGEN_ARCH_ARM_OR_ARM64 1
+#else
+  #define EIGEN_ARCH_ARM_OR_ARM64 0
+#endif
+
+/// \internal EIGEN_ARCH_MIPS set to 1 if the architecture is MIPS
+#if defined(__mips__) || defined(__mips)
+  #define EIGEN_ARCH_MIPS 1
+#else
+  #define EIGEN_ARCH_MIPS 0
+#endif
+
+/// \internal EIGEN_ARCH_SPARC set to 1 if the architecture is SPARC
+#if defined(__sparc__) || defined(__sparc)
+  #define EIGEN_ARCH_SPARC 1
+#else
+  #define EIGEN_ARCH_SPARC 0
+#endif
+
+/// \internal EIGEN_ARCH_IA64 set to 1 if the architecture is Intel Itanium
+#if defined(__ia64__)
+  #define EIGEN_ARCH_IA64 1
+#else
+  #define EIGEN_ARCH_IA64 0
+#endif
+
+/// \internal EIGEN_ARCH_PPC set to 1 if the architecture is PowerPC
+#if defined(__powerpc__) || defined(__ppc__) || defined(_M_PPC)
+  #define EIGEN_ARCH_PPC 1
+#else
+  #define EIGEN_ARCH_PPC 0
+#endif
+
+
+
+// Operating system identification, EIGEN_OS_*
+
+/// \internal EIGEN_OS_UNIX set to 1 if the OS is a unix variant
+#if defined(__unix__) || defined(__unix)
+  #define EIGEN_OS_UNIX 1
+#else
+  #define EIGEN_OS_UNIX 0
+#endif
+
+/// \internal EIGEN_OS_LINUX set to 1 if the OS is based on Linux kernel
+#if defined(__linux__)
+  #define EIGEN_OS_LINUX 1
+#else
+  #define EIGEN_OS_LINUX 0
+#endif
+
+/// \internal EIGEN_OS_ANDROID set to 1 if the OS is Android
+// note: ANDROID is defined when using ndk_build, __ANDROID__ is defined when using a standalone toolchain.
+#if defined(__ANDROID__) || defined(ANDROID)
+  #define EIGEN_OS_ANDROID 1
+#else
+  #define EIGEN_OS_ANDROID 0
+#endif
+
+/// \internal EIGEN_OS_GNULINUX set to 1 if the OS is GNU Linux and not Linux-based OS (e.g., not android)
+#if defined(__gnu_linux__) && !(EIGEN_OS_ANDROID)
+  #define EIGEN_OS_GNULINUX 1
+#else
+  #define EIGEN_OS_GNULINUX 0
+#endif
+
+/// \internal EIGEN_OS_BSD set to 1 if the OS is a BSD variant
+#if defined(__FreeBSD__) || defined(__NetBSD__) || defined(__OpenBSD__) || defined(__bsdi__) || defined(__DragonFly__)
+  #define EIGEN_OS_BSD 1
+#else
+  #define EIGEN_OS_BSD 0
+#endif
+
+/// \internal EIGEN_OS_MAC set to 1 if the OS is MacOS
+#if defined(__APPLE__)
+  #define EIGEN_OS_MAC 1
+#else
+  #define EIGEN_OS_MAC 0
+#endif
+
+/// \internal EIGEN_OS_QNX set to 1 if the OS is QNX
+#if defined(__QNX__)
+  #define EIGEN_OS_QNX 1
+#else
+  #define EIGEN_OS_QNX 0
+#endif
+
+/// \internal EIGEN_OS_WIN set to 1 if the OS is Windows based
+#if defined(_WIN32)
+  #define EIGEN_OS_WIN 1
+#else
+  #define EIGEN_OS_WIN 0
+#endif
+
+/// \internal EIGEN_OS_WIN64 set to 1 if the OS is Windows 64bits
+#if defined(_WIN64)
+  #define EIGEN_OS_WIN64 1
+#else
+  #define EIGEN_OS_WIN64 0
+#endif
+
+/// \internal EIGEN_OS_WINCE set to 1 if the OS is Windows CE
+#if defined(_WIN32_WCE)
+  #define EIGEN_OS_WINCE 1
+#else
+  #define EIGEN_OS_WINCE 0
+#endif
+
+/// \internal EIGEN_OS_CYGWIN set to 1 if the OS is Windows/Cygwin
+#if defined(__CYGWIN__)
+  #define EIGEN_OS_CYGWIN 1
+#else
+  #define EIGEN_OS_CYGWIN 0
+#endif
+
+/// \internal EIGEN_OS_WIN_STRICT set to 1 if the OS is really Windows and not some variants
+#if EIGEN_OS_WIN && !( EIGEN_OS_WINCE || EIGEN_OS_CYGWIN )
+  #define EIGEN_OS_WIN_STRICT 1
+#else
+  #define EIGEN_OS_WIN_STRICT 0
+#endif
+
+/// \internal EIGEN_OS_SUN set to 1 if the OS is SUN
+#if (defined(sun) || defined(__sun)) && !(defined(__SVR4) || defined(__svr4__))
+  #define EIGEN_OS_SUN 1
+#else
+  #define EIGEN_OS_SUN 0
 #endif
- 
-#ifdef __GNUC__
-  #define EIGEN_GNUC_AT_MOST(x,y) ((__GNUC__==x && __GNUC_MINOR__<=y) || __GNUC__<x)
+
+/// \internal EIGEN_OS_SOLARIS set to 1 if the OS is Solaris
+#if (defined(sun) || defined(__sun)) && (defined(__SVR4) || defined(__svr4__))
+  #define EIGEN_OS_SOLARIS 1
 #else
-  #define EIGEN_GNUC_AT_MOST(x,y) 0
+  #define EIGEN_OS_SOLARIS 0
 #endif
 
-#if EIGEN_GNUC_AT_MOST(4,3) && !defined(__clang__)
+
+
+#if EIGEN_GNUC_AT_MOST(4,3) && !EIGEN_COMP_CLANG
   // see bug 89
   #define EIGEN_SAFE_TO_USE_STANDARD_ASSERT_MACRO 0
 #else
   #define EIGEN_SAFE_TO_USE_STANDARD_ASSERT_MACRO 1
 #endif
 
-#if defined(__GNUC__) && (__GNUC__ <= 3)
-#define EIGEN_GCC3_OR_OLDER 1
-#else
-#define EIGEN_GCC3_OR_OLDER 0
-#endif
-
-// 16 byte alignment is only useful for vectorization. Since it affects the ABI, we need to enable
-// 16 byte alignment on all platforms where vectorization might be enabled. In theory we could always
-// enable alignment, but it can be a cause of problems on some platforms, so we just disable it in
-// certain common platform (compiler+architecture combinations) to avoid these problems.
-// Only static alignment is really problematic (relies on nonstandard compiler extensions that don't
-// work everywhere, for example don't work on GCC/ARM), try to keep heap alignment even
-// when we have to disable static alignment.
-#if defined(__GNUC__) && !(defined(__i386__) || defined(__x86_64__) || defined(__powerpc__) || defined(__ppc__) || defined(__ia64__))
-#define EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT 1
-#else
-#define EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT 0
-#endif
-
-// static alignment is completely disabled with GCC 3, Sun Studio, and QCC/QNX
-#if !EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT \
- && !EIGEN_GCC3_OR_OLDER \
- && !defined(__SUNPRO_CC) \
- && !defined(__QNXNTO__)
-  #define EIGEN_ARCH_WANTS_STACK_ALIGNMENT 1
-#else
-  #define EIGEN_ARCH_WANTS_STACK_ALIGNMENT 0
-#endif
-
-#ifdef EIGEN_DONT_ALIGN
-  #ifndef EIGEN_DONT_ALIGN_STATICALLY
-    #define EIGEN_DONT_ALIGN_STATICALLY
-  #endif
-  #define EIGEN_ALIGN 0
-#else
-  #define EIGEN_ALIGN 1
-#endif
-
-// EIGEN_ALIGN_STATICALLY is the true test whether we want to align arrays on the stack or not. It takes into account both the user choice to explicitly disable
-// alignment (EIGEN_DONT_ALIGN_STATICALLY) and the architecture config (EIGEN_ARCH_WANTS_STACK_ALIGNMENT). Henceforth, only EIGEN_ALIGN_STATICALLY should be used.
-#if EIGEN_ARCH_WANTS_STACK_ALIGNMENT && !defined(EIGEN_DONT_ALIGN_STATICALLY)
-  #define EIGEN_ALIGN_STATICALLY 1
-#else
-  #define EIGEN_ALIGN_STATICALLY 0
-  #ifndef EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
-    #define EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
-  #endif
-#endif
+// This macro can be used to prevent from macro expansion, e.g.:
+//   std::max EIGEN_NOT_A_MACRO(a,b)
+#define EIGEN_NOT_A_MACRO
 
 #ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
-#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION RowMajor
+#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION Eigen::RowMajor
 #else
-#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ColMajor
+#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION Eigen::ColMajor
 #endif
 
 #ifndef EIGEN_DEFAULT_DENSE_INDEX_TYPE
 #define EIGEN_DEFAULT_DENSE_INDEX_TYPE std::ptrdiff_t
 #endif
@@ -100,15 +340,135 @@
 #ifdef __has_builtin
 #  define EIGEN_HAS_BUILTIN(x) __has_builtin(x)
 #else
 #  define EIGEN_HAS_BUILTIN(x) 0
 #endif
+
+// A Clang feature extension to determine compiler features.
+// We use it to determine 'cxx_rvalue_references'
+#ifndef __has_feature
+# define __has_feature(x) 0
+#endif
+
+// Upperbound on the C++ version to use.
+// Expected values are 03, 11, 14, 17, etc.
+// By default, let's use an arbitrarily large C++ version.
+#ifndef EIGEN_MAX_CPP_VER
+#define EIGEN_MAX_CPP_VER 99
+#endif
+
+#if EIGEN_MAX_CPP_VER>=11 && (defined(__cplusplus) && (__cplusplus >= 201103L) || EIGEN_COMP_MSVC >= 1900)
+#define EIGEN_HAS_CXX11 1
+#else
+#define EIGEN_HAS_CXX11 0
+#endif
+
+
+// Do we support r-value references?
+#ifndef EIGEN_HAS_RVALUE_REFERENCES
+#if EIGEN_MAX_CPP_VER>=11 && \
+    (__has_feature(cxx_rvalue_references) || \
+    (defined(__cplusplus) && __cplusplus >= 201103L) || \
+    (EIGEN_COMP_MSVC >= 1600))
+  #define EIGEN_HAS_RVALUE_REFERENCES 1
+#else
+  #define EIGEN_HAS_RVALUE_REFERENCES 0
+#endif
+#endif
+
+// Does the compiler support C99?
+#ifndef EIGEN_HAS_C99_MATH
+#if EIGEN_MAX_CPP_VER>=11 && \
+    ((defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901))       \
+  || (defined(__GNUC__) && defined(_GLIBCXX_USE_C99)) \
+  || (defined(_LIBCPP_VERSION) && !defined(_MSC_VER)))
+  #define EIGEN_HAS_C99_MATH 1
+#else
+  #define EIGEN_HAS_C99_MATH 0
+#endif
+#endif
+
+// Does the compiler support result_of?
+#ifndef EIGEN_HAS_STD_RESULT_OF
+#if EIGEN_MAX_CPP_VER>=11 && ((__has_feature(cxx_lambdas) || (defined(__cplusplus) && __cplusplus >= 201103L)))
+#define EIGEN_HAS_STD_RESULT_OF 1
+#else
+#define EIGEN_HAS_STD_RESULT_OF 0
+#endif
+#endif
+
+// Does the compiler support variadic templates?
+#ifndef EIGEN_HAS_VARIADIC_TEMPLATES
+#if EIGEN_MAX_CPP_VER>=11 && (__cplusplus > 199711L || EIGEN_COMP_MSVC >= 1900) \
+  && ( !defined(__NVCC__) || !EIGEN_ARCH_ARM_OR_ARM64 || (defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000) )
+    // ^^ Disable the use of variadic templates when compiling with versions of nvcc older than 8.0 on ARM devices:
+    //    this prevents nvcc from crashing when compiling Eigen on Tegra X1
+#define EIGEN_HAS_VARIADIC_TEMPLATES 1
+#else
+#define EIGEN_HAS_VARIADIC_TEMPLATES 0
+#endif
+#endif
+
+// Does the compiler fully support const expressions? (as in c++14)
+#ifndef EIGEN_HAS_CONSTEXPR
+
+#ifdef __CUDACC__
+// Const expressions are supported provided that c++11 is enabled and we're using either clang or nvcc 7.5 or above
+#if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && defined(__CUDACC_VER__) && (EIGEN_COMP_CLANG || __CUDACC_VER__ >= 70500))
+  #define EIGEN_HAS_CONSTEXPR 1
+#endif
+#elif EIGEN_MAX_CPP_VER>=14 && (__has_feature(cxx_relaxed_constexpr) || (defined(__cplusplus) && __cplusplus >= 201402L) || \
+  (EIGEN_GNUC_AT_LEAST(4,8) && (__cplusplus > 199711L)))
+#define EIGEN_HAS_CONSTEXPR 1
+#endif
+
+#ifndef EIGEN_HAS_CONSTEXPR
+#define EIGEN_HAS_CONSTEXPR 0
+#endif
+
+#endif
+
+// Does the compiler support C++11 math?
+// Let's be conservative and enable the default C++11 implementation only if we are sure it exists
+#ifndef EIGEN_HAS_CXX11_MATH
+  #if EIGEN_MAX_CPP_VER>=11 && ((__cplusplus > 201103L) || (__cplusplus >= 201103L) && (EIGEN_COMP_GNUC_STRICT || EIGEN_COMP_CLANG || EIGEN_COMP_MSVC || EIGEN_COMP_ICC)  \
+      && (EIGEN_ARCH_i386_OR_x86_64) && (EIGEN_OS_GNULINUX || EIGEN_OS_WIN_STRICT || EIGEN_OS_MAC))
+    #define EIGEN_HAS_CXX11_MATH 1
+  #else
+    #define EIGEN_HAS_CXX11_MATH 0
+  #endif
+#endif
+
+// Does the compiler support proper C++11 containers?
+#ifndef EIGEN_HAS_CXX11_CONTAINERS
+  #if    EIGEN_MAX_CPP_VER>=11 && \
+         ((__cplusplus > 201103L) \
+      || ((__cplusplus >= 201103L) && (EIGEN_COMP_GNUC_STRICT || EIGEN_COMP_CLANG || EIGEN_COMP_ICC>=1400)) \
+      || EIGEN_COMP_MSVC >= 1900)
+    #define EIGEN_HAS_CXX11_CONTAINERS 1
+  #else
+    #define EIGEN_HAS_CXX11_CONTAINERS 0
+  #endif
+#endif
+
+// Does the compiler support C++11 noexcept?
+#ifndef EIGEN_HAS_CXX11_NOEXCEPT
+  #if    EIGEN_MAX_CPP_VER>=11 && \
+         (__has_feature(cxx_noexcept) \
+      || (__cplusplus > 201103L) \
+      || ((__cplusplus >= 201103L) && (EIGEN_COMP_GNUC_STRICT || EIGEN_COMP_CLANG || EIGEN_COMP_ICC>=1400)) \
+      || EIGEN_COMP_MSVC >= 1900)
+    #define EIGEN_HAS_CXX11_NOEXCEPT 1
+  #else
+    #define EIGEN_HAS_CXX11_NOEXCEPT 0
+  #endif
+#endif
 
 /** Allows to disable some optimizations which might affect the accuracy of the result.
   * Such optimization are enabled by default, and set EIGEN_FAST_MATH to 0 to disable them.
   * They currently include:
-  *   - single precision Cwise::sin() and Cwise::cos() when SSE vectorization is enabled.
+  *   - single precision ArrayBase::sin() and ArrayBase::cos() for SSE and AVX vectorization.
   */
 #ifndef EIGEN_FAST_MATH
 #define EIGEN_FAST_MATH 1
 #endif
 
@@ -115,46 +475,49 @@
 #define EIGEN_DEBUG_VAR(x) std::cerr << #x << " = " << x << std::endl;
 
 // concatenate two tokens
 #define EIGEN_CAT2(a,b) a ## b
 #define EIGEN_CAT(a,b) EIGEN_CAT2(a,b)
+
+#define EIGEN_COMMA ,
 
 // convert a token to a string
 #define EIGEN_MAKESTRING2(a) #a
 #define EIGEN_MAKESTRING(a) EIGEN_MAKESTRING2(a)
 
 // EIGEN_STRONG_INLINE is a stronger version of the inline, using __forceinline on MSVC,
 // but it still doesn't use GCC's always_inline. This is useful in (common) situations where MSVC needs forceinline
 // but GCC is still doing fine with just inline.
-#if (defined _MSC_VER) || (defined __INTEL_COMPILER)
+#if EIGEN_COMP_MSVC || EIGEN_COMP_ICC
 #define EIGEN_STRONG_INLINE __forceinline
 #else
 #define EIGEN_STRONG_INLINE inline
 #endif
 
 // EIGEN_ALWAYS_INLINE is the stronget, it has the effect of making the function inline and adding every possible
 // attribute to maximize inlining. This should only be used when really necessary: in particular,
 // it uses __attribute__((always_inline)) on GCC, which most of the time is useless and can severely harm compile times.
 // FIXME with the always_inline attribute,
-// gcc 3.4.x reports the following compilation error:
+// gcc 3.4.x and 4.1 reports the following compilation error:
 //   Eval.h:91: sorry, unimplemented: inlining failed in call to 'const Eigen::Eval<Derived> Eigen::MatrixBase<Scalar, Derived>::eval() const'
 //    : function body not available
-#if EIGEN_GNUC_AT_LEAST(4,0)
+//   See also bug 1367
+#if EIGEN_GNUC_AT_LEAST(4,2)
 #define EIGEN_ALWAYS_INLINE __attribute__((always_inline)) inline
 #else
 #define EIGEN_ALWAYS_INLINE EIGEN_STRONG_INLINE
 #endif
 
-#if (defined __GNUC__)
+#if EIGEN_COMP_GNUC
 #define EIGEN_DONT_INLINE __attribute__((noinline))
-#elif (defined _MSC_VER)
+#elif EIGEN_COMP_MSVC
 #define EIGEN_DONT_INLINE __declspec(noinline)
 #else
 #define EIGEN_DONT_INLINE
 #endif
 
-#if (defined __GNUC__)
+#if EIGEN_COMP_GNUC
 #define EIGEN_PERMISSIVE_EXPR __extension__
 #else
 #define EIGEN_PERMISSIVE_EXPR
 #endif
 
@@ -219,76 +582,212 @@
 #else
 #define eigen_internal_assert(x)
 #endif
 
 #ifdef EIGEN_NO_DEBUG
-#define EIGEN_ONLY_USED_FOR_DEBUG(x) (void)x
+#define EIGEN_ONLY_USED_FOR_DEBUG(x) EIGEN_UNUSED_VARIABLE(x)
 #else
 #define EIGEN_ONLY_USED_FOR_DEBUG(x)
 #endif
 
 #ifndef EIGEN_NO_DEPRECATED_WARNING
-  #if (defined __GNUC__)
+  #if EIGEN_COMP_GNUC
     #define EIGEN_DEPRECATED __attribute__((deprecated))
-  #elif (defined _MSC_VER)
+  #elif EIGEN_COMP_MSVC
     #define EIGEN_DEPRECATED __declspec(deprecated)
   #else
     #define EIGEN_DEPRECATED
   #endif
 #else
   #define EIGEN_DEPRECATED
 #endif
 
-#if (defined __GNUC__)
+#if EIGEN_COMP_GNUC
 #define EIGEN_UNUSED __attribute__((unused))
 #else
 #define EIGEN_UNUSED
 #endif
 
 // Suppresses 'unused variable' warnings.
 namespace Eigen {
   namespace internal {
-    template<typename T> void ignore_unused_variable(const T&) {}
+    template<typename T> EIGEN_DEVICE_FUNC void ignore_unused_variable(const T&) {}
   }
 }
 #define EIGEN_UNUSED_VARIABLE(var) Eigen::internal::ignore_unused_variable(var);
 
 #if !defined(EIGEN_ASM_COMMENT)
-  #if (defined __GNUC__) && ( defined(__i386__) || defined(__x86_64__) )
+  #if EIGEN_COMP_GNUC && (EIGEN_ARCH_i386_OR_x86_64 || EIGEN_ARCH_ARM_OR_ARM64)
     #define EIGEN_ASM_COMMENT(X)  __asm__("#" X)
   #else
     #define EIGEN_ASM_COMMENT(X)
   #endif
 #endif
+
+
+//------------------------------------------------------------------------------------------
+// Static and dynamic alignment control
+//
+// The main purpose of this section is to define EIGEN_MAX_ALIGN_BYTES and EIGEN_MAX_STATIC_ALIGN_BYTES
+// as the maximal boundary in bytes on which dynamically and statically allocated data may be alignment respectively.
+// The values of EIGEN_MAX_ALIGN_BYTES and EIGEN_MAX_STATIC_ALIGN_BYTES can be specified by the user. If not,
+// a default value is automatically computed based on architecture, compiler, and OS.
+//
+// This section also defines macros EIGEN_ALIGN_TO_BOUNDARY(N) and the shortcuts EIGEN_ALIGN{8,16,32,_MAX}
+// to be used to declare statically aligned buffers.
+//------------------------------------------------------------------------------------------
+
 
 /* EIGEN_ALIGN_TO_BOUNDARY(n) forces data to be n-byte aligned. This is used to satisfy SIMD requirements.
  * However, we do that EVEN if vectorization (EIGEN_VECTORIZE) is disabled,
  * so that vectorization doesn't affect binary compatibility.
  *
  * If we made alignment depend on whether or not EIGEN_VECTORIZE is defined, it would be impossible to link
  * vectorized and non-vectorized code.
  */
-#if (defined __GNUC__) || (defined __PGI) || (defined __IBMCPP__) || (defined __ARMCC_VERSION)
+#if (defined __CUDACC__)
+  #define EIGEN_ALIGN_TO_BOUNDARY(n) __align__(n)
+#elif EIGEN_COMP_GNUC || EIGEN_COMP_PGI || EIGEN_COMP_IBM || EIGEN_COMP_ARM
   #define EIGEN_ALIGN_TO_BOUNDARY(n) __attribute__((aligned(n)))
-#elif (defined _MSC_VER)
+#elif EIGEN_COMP_MSVC
   #define EIGEN_ALIGN_TO_BOUNDARY(n) __declspec(align(n))
-#elif (defined __SUNPRO_CC)
+#elif EIGEN_COMP_SUNCC
   // FIXME not sure about this one:
   #define EIGEN_ALIGN_TO_BOUNDARY(n) __attribute__((aligned(n)))
 #else
   #error Please tell me what is the equivalent of __attribute__((aligned(n))) for your compiler
 #endif
 
+// If the user explicitly disable vectorization, then we also disable alignment
+#if defined(EIGEN_DONT_VECTORIZE)
+  #define EIGEN_IDEAL_MAX_ALIGN_BYTES 0
+#elif defined(EIGEN_VECTORIZE_AVX512)
+  // 64 bytes static alignmeent is preferred only if really required
+  #define EIGEN_IDEAL_MAX_ALIGN_BYTES 64
+#elif defined(__AVX__)
+  // 32 bytes static alignmeent is preferred only if really required
+  #define EIGEN_IDEAL_MAX_ALIGN_BYTES 32
+#else
+  #define EIGEN_IDEAL_MAX_ALIGN_BYTES 16
+#endif
+
+
+// EIGEN_MIN_ALIGN_BYTES defines the minimal value for which the notion of explicit alignment makes sense
+#define EIGEN_MIN_ALIGN_BYTES 16
+
+// Defined the boundary (in bytes) on which the data needs to be aligned. Note
+// that unless EIGEN_ALIGN is defined and not equal to 0, the data may not be
+// aligned at all regardless of the value of this #define.
+
+#if (defined(EIGEN_DONT_ALIGN_STATICALLY) || defined(EIGEN_DONT_ALIGN))  && defined(EIGEN_MAX_STATIC_ALIGN_BYTES) && EIGEN_MAX_STATIC_ALIGN_BYTES>0
+#error EIGEN_MAX_STATIC_ALIGN_BYTES and EIGEN_DONT_ALIGN[_STATICALLY] are both defined with EIGEN_MAX_STATIC_ALIGN_BYTES!=0. Use EIGEN_MAX_STATIC_ALIGN_BYTES=0 as a synonym of EIGEN_DONT_ALIGN_STATICALLY.
+#endif
+
+// EIGEN_DONT_ALIGN_STATICALLY and EIGEN_DONT_ALIGN are deprectated
+// They imply EIGEN_MAX_STATIC_ALIGN_BYTES=0
+#if defined(EIGEN_DONT_ALIGN_STATICALLY) || defined(EIGEN_DONT_ALIGN)
+  #ifdef EIGEN_MAX_STATIC_ALIGN_BYTES
+    #undef EIGEN_MAX_STATIC_ALIGN_BYTES
+  #endif
+  #define EIGEN_MAX_STATIC_ALIGN_BYTES 0
+#endif
+
+#ifndef EIGEN_MAX_STATIC_ALIGN_BYTES
+
+  // Try to automatically guess what is the best default value for EIGEN_MAX_STATIC_ALIGN_BYTES
+
+  // 16 byte alignment is only useful for vectorization. Since it affects the ABI, we need to enable
+  // 16 byte alignment on all platforms where vectorization might be enabled. In theory we could always
+  // enable alignment, but it can be a cause of problems on some platforms, so we just disable it in
+  // certain common platform (compiler+architecture combinations) to avoid these problems.
+  // Only static alignment is really problematic (relies on nonstandard compiler extensions),
+  // try to keep heap alignment even when we have to disable static alignment.
+  #if EIGEN_COMP_GNUC && !(EIGEN_ARCH_i386_OR_x86_64 || EIGEN_ARCH_ARM_OR_ARM64 || EIGEN_ARCH_PPC || EIGEN_ARCH_IA64)
+  #define EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT 1
+  #elif EIGEN_ARCH_ARM_OR_ARM64 && EIGEN_COMP_GNUC_STRICT && EIGEN_GNUC_AT_MOST(4, 6)
+  // Old versions of GCC on ARM, at least 4.4, were once seen to have buggy static alignment support.
+  // Not sure which version fixed it, hopefully it doesn't affect 4.7, which is still somewhat in use.
+  // 4.8 and newer seem definitely unaffected.
+  #define EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT 1
+  #else
+  #define EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT 0
+  #endif
+
+  // static alignment is completely disabled with GCC 3, Sun Studio, and QCC/QNX
+  #if !EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT \
+  && !EIGEN_GCC3_OR_OLDER \
+  && !EIGEN_COMP_SUNCC \
+  && !EIGEN_OS_QNX
+    #define EIGEN_ARCH_WANTS_STACK_ALIGNMENT 1
+  #else
+    #define EIGEN_ARCH_WANTS_STACK_ALIGNMENT 0
+  #endif
+
+  #if EIGEN_ARCH_WANTS_STACK_ALIGNMENT
+    #define EIGEN_MAX_STATIC_ALIGN_BYTES EIGEN_IDEAL_MAX_ALIGN_BYTES
+  #else
+    #define EIGEN_MAX_STATIC_ALIGN_BYTES 0
+  #endif
+
+#endif
+
+// If EIGEN_MAX_ALIGN_BYTES is defined, then it is considered as an upper bound for EIGEN_MAX_ALIGN_BYTES
+#if defined(EIGEN_MAX_ALIGN_BYTES) && EIGEN_MAX_ALIGN_BYTES<EIGEN_MAX_STATIC_ALIGN_BYTES
+#undef EIGEN_MAX_STATIC_ALIGN_BYTES
+#define EIGEN_MAX_STATIC_ALIGN_BYTES EIGEN_MAX_ALIGN_BYTES
+#endif
+
+#if EIGEN_MAX_STATIC_ALIGN_BYTES==0 && !defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT)
+  #define EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
+#endif
+
+// At this stage, EIGEN_MAX_STATIC_ALIGN_BYTES>0 is the true test whether we want to align arrays on the stack or not.
+// It takes into account both the user choice to explicitly enable/disable alignment (by settting EIGEN_MAX_STATIC_ALIGN_BYTES)
+// and the architecture config (EIGEN_ARCH_WANTS_STACK_ALIGNMENT).
+// Henceforth, only EIGEN_MAX_STATIC_ALIGN_BYTES should be used.
+
+
+// Shortcuts to EIGEN_ALIGN_TO_BOUNDARY
+#define EIGEN_ALIGN8  EIGEN_ALIGN_TO_BOUNDARY(8)
 #define EIGEN_ALIGN16 EIGEN_ALIGN_TO_BOUNDARY(16)
+#define EIGEN_ALIGN32 EIGEN_ALIGN_TO_BOUNDARY(32)
+#define EIGEN_ALIGN64 EIGEN_ALIGN_TO_BOUNDARY(64)
+#if EIGEN_MAX_STATIC_ALIGN_BYTES>0
+#define EIGEN_ALIGN_MAX EIGEN_ALIGN_TO_BOUNDARY(EIGEN_MAX_STATIC_ALIGN_BYTES)
+#else
+#define EIGEN_ALIGN_MAX
+#endif
+
+
+// Dynamic alignment control
+
+#if defined(EIGEN_DONT_ALIGN) && defined(EIGEN_MAX_ALIGN_BYTES) && EIGEN_MAX_ALIGN_BYTES>0
+#error EIGEN_MAX_ALIGN_BYTES and EIGEN_DONT_ALIGN are both defined with EIGEN_MAX_ALIGN_BYTES!=0. Use EIGEN_MAX_ALIGN_BYTES=0 as a synonym of EIGEN_DONT_ALIGN.
+#endif
+
+#ifdef EIGEN_DONT_ALIGN
+  #ifdef EIGEN_MAX_ALIGN_BYTES
+    #undef EIGEN_MAX_ALIGN_BYTES
+  #endif
+  #define EIGEN_MAX_ALIGN_BYTES 0
+#elif !defined(EIGEN_MAX_ALIGN_BYTES)
+  #define EIGEN_MAX_ALIGN_BYTES EIGEN_IDEAL_MAX_ALIGN_BYTES
+#endif
 
-#if EIGEN_ALIGN_STATICALLY
-#define EIGEN_USER_ALIGN_TO_BOUNDARY(n) EIGEN_ALIGN_TO_BOUNDARY(n)
-#define EIGEN_USER_ALIGN16 EIGEN_ALIGN16
+#if EIGEN_IDEAL_MAX_ALIGN_BYTES > EIGEN_MAX_ALIGN_BYTES
+#define EIGEN_DEFAULT_ALIGN_BYTES EIGEN_IDEAL_MAX_ALIGN_BYTES
 #else
-#define EIGEN_USER_ALIGN_TO_BOUNDARY(n)
-#define EIGEN_USER_ALIGN16
+#define EIGEN_DEFAULT_ALIGN_BYTES EIGEN_MAX_ALIGN_BYTES
+#endif
+
+
+#ifndef EIGEN_UNALIGNED_VECTORIZE
+#define EIGEN_UNALIGNED_VECTORIZE 1
 #endif
+
+//----------------------------------------------------------------------
+
 
 #ifdef EIGEN_DONT_USE_RESTRICT_KEYWORD
   #define EIGEN_RESTRICT
 #endif
 #ifndef EIGEN_RESTRICT
@@ -311,31 +810,35 @@
 #endif
 
 // just an empty macro !
 #define EIGEN_EMPTY
 
-#if defined(_MSC_VER) && (_MSC_VER < 1900) && (!defined(__INTEL_COMPILER))
-#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
-  using Base::operator =;
-#elif defined(__clang__) // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653)
-#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
-  using Base::operator =; \
-  EIGEN_STRONG_INLINE Derived& operator=(const Derived& other) { Base::operator=(other); return *this; } \
-  template <typename OtherDerived> \
-  EIGEN_STRONG_INLINE Derived& operator=(const DenseBase<OtherDerived>& other) { Base::operator=(other.derived()); return *this; }
+#if EIGEN_COMP_MSVC_STRICT && (EIGEN_COMP_MSVC < 1900 ||  defined(__CUDACC_VER__)) // for older MSVC versions, as well as 1900 && CUDA 8, using the base operator is sufficient (cf Bugs 1000, 1324)
+  #define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
+    using Base::operator =;
+#elif EIGEN_COMP_CLANG // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653)
+  #define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
+    using Base::operator =; \
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const Derived& other) { Base::operator=(other); return *this; } \
+    template <typename OtherDerived> \
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const DenseBase<OtherDerived>& other) { Base::operator=(other.derived()); return *this; }
 #else
-#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
-  using Base::operator =; \
-  EIGEN_STRONG_INLINE Derived& operator=(const Derived& other) \
-  { \
-    Base::operator=(other); \
-    return *this; \
-  }
+  #define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
+    using Base::operator =; \
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const Derived& other) \
+    { \
+      Base::operator=(other); \
+      return *this; \
+    }
 #endif
 
-#define EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Derived) \
-  EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived)
+
+/** \internal
+ * \brief Macro to manually inherit assignment operators.
+ * This is necessary, because the implicitly defined assignment operator gets deleted when a custom operator= is defined.
+ */
+#define EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Derived) EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived)
 
 /**
 * Just a side note. Commenting within defines works only by documenting
 * behind the object (via '!<'). Comments cannot be multi-line and thus
 * we have these extra long lines. What is confusing doxygen over here is
@@ -345,42 +848,28 @@
 
 #define EIGEN_GENERIC_PUBLIC_INTERFACE(Derived) \
   typedef typename Eigen::internal::traits<Derived>::Scalar Scalar; /*!< \brief Numeric type, e.g. float, double, int or std::complex<float>. */ \
   typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; /*!< \brief The underlying numeric type for composed scalar types. \details In cases where Scalar is e.g. std::complex<T>, T were corresponding to RealScalar. */ \
   typedef typename Base::CoeffReturnType CoeffReturnType; /*!< \brief The return type for coefficient access. \details Depending on whether the object allows direct coefficient access (e.g. for a MatrixXd), this type is either 'const Scalar&' or simply 'Scalar' for objects that do not allow direct coefficient access. */ \
-  typedef typename Eigen::internal::nested<Derived>::type Nested; \
-  typedef typename Eigen::internal::traits<Derived>::StorageKind StorageKind; \
-  typedef typename Eigen::internal::traits<Derived>::Index Index; \
-  enum { RowsAtCompileTime = Eigen::internal::traits<Derived>::RowsAtCompileTime, \
-        ColsAtCompileTime = Eigen::internal::traits<Derived>::ColsAtCompileTime, \
-        Flags = Eigen::internal::traits<Derived>::Flags, \
-        CoeffReadCost = Eigen::internal::traits<Derived>::CoeffReadCost, \
-        SizeAtCompileTime = Base::SizeAtCompileTime, \
-        MaxSizeAtCompileTime = Base::MaxSizeAtCompileTime, \
-        IsVectorAtCompileTime = Base::IsVectorAtCompileTime };
-
-
-#define EIGEN_DENSE_PUBLIC_INTERFACE(Derived) \
-  typedef typename Eigen::internal::traits<Derived>::Scalar Scalar; /*!< \brief Numeric type, e.g. float, double, int or std::complex<float>. */ \
-  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; /*!< \brief The underlying numeric type for composed scalar types. \details In cases where Scalar is e.g. std::complex<T>, T were corresponding to RealScalar. */ \
-  typedef typename Base::PacketScalar PacketScalar; \
-  typedef typename Base::CoeffReturnType CoeffReturnType; /*!< \brief The return type for coefficient access. \details Depending on whether the object allows direct coefficient access (e.g. for a MatrixXd), this type is either 'const Scalar&' or simply 'Scalar' for objects that do not allow direct coefficient access. */ \
-  typedef typename Eigen::internal::nested<Derived>::type Nested; \
-  typedef typename Eigen::internal::traits<Derived>::StorageKind StorageKind; \
-  typedef typename Eigen::internal::traits<Derived>::Index Index; \
-  enum { RowsAtCompileTime = Eigen::internal::traits<Derived>::RowsAtCompileTime, \
-        ColsAtCompileTime = Eigen::internal::traits<Derived>::ColsAtCompileTime, \
-        MaxRowsAtCompileTime = Eigen::internal::traits<Derived>::MaxRowsAtCompileTime, \
-        MaxColsAtCompileTime = Eigen::internal::traits<Derived>::MaxColsAtCompileTime, \
-        Flags = Eigen::internal::traits<Derived>::Flags, \
-        CoeffReadCost = Eigen::internal::traits<Derived>::CoeffReadCost, \
+  typedef typename Eigen::internal::ref_selector<Derived>::type Nested; \
+  typedef typename Eigen::internal::traits<Derived>::StorageKind StorageKind; \
+  typedef typename Eigen::internal::traits<Derived>::StorageIndex StorageIndex; \
+  enum { RowsAtCompileTime = Eigen::internal::traits<Derived>::RowsAtCompileTime, \
+        ColsAtCompileTime = Eigen::internal::traits<Derived>::ColsAtCompileTime, \
+        Flags = Eigen::internal::traits<Derived>::Flags, \
         SizeAtCompileTime = Base::SizeAtCompileTime, \
         MaxSizeAtCompileTime = Base::MaxSizeAtCompileTime, \
         IsVectorAtCompileTime = Base::IsVectorAtCompileTime }; \
   using Base::derived; \
   using Base::const_cast_derived;
 
+
+// FIXME Maybe the EIGEN_DENSE_PUBLIC_INTERFACE could be removed as importing PacketScalar is rarely needed
+#define EIGEN_DENSE_PUBLIC_INTERFACE(Derived) \
+  EIGEN_GENERIC_PUBLIC_INTERFACE(Derived) \
+  typedef typename Base::PacketScalar PacketScalar;
+
 
 #define EIGEN_PLAIN_ENUM_MIN(a,b) (((int)a <= (int)b) ? (int)a : (int)b)
 #define EIGEN_PLAIN_ENUM_MAX(a,b) (((int)a >= (int)b) ? (int)a : (int)b)
 
 // EIGEN_SIZE_MIN_PREFER_DYNAMIC gives the min between compile-time sizes. 0 has absolute priority, followed by 1,
@@ -407,25 +896,97 @@
 
 #define EIGEN_LOGICAL_XOR(a,b) (((a) || (b)) && !((a) && (b)))
 
 #define EIGEN_IMPLIES(a,b) (!(a) || (b))
 
-#define EIGEN_MAKE_CWISE_BINARY_OP(METHOD,FUNCTOR) \
-  template<typename OtherDerived> \
-  EIGEN_STRONG_INLINE const CwiseBinaryOp<FUNCTOR<Scalar>, const Derived, const OtherDerived> \
-  (METHOD)(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const \
-  { \
-    return CwiseBinaryOp<FUNCTOR<Scalar>, const Derived, const OtherDerived>(derived(), other.derived()); \
-  }
-
-// the expression type of a cwise product
-#define EIGEN_CWISE_PRODUCT_RETURN_TYPE(LHS,RHS) \
+// the expression type of a standard coefficient wise binary operation
+#define EIGEN_CWISE_BINARY_RETURN_TYPE(LHS,RHS,OPNAME) \
     CwiseBinaryOp< \
-      internal::scalar_product_op< \
+      EIGEN_CAT(EIGEN_CAT(internal::scalar_,OPNAME),_op)< \
           typename internal::traits<LHS>::Scalar, \
           typename internal::traits<RHS>::Scalar \
       >, \
       const LHS, \
       const RHS \
     >
+
+#define EIGEN_MAKE_CWISE_BINARY_OP(METHOD,OPNAME) \
+  template<typename OtherDerived> \
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const EIGEN_CWISE_BINARY_RETURN_TYPE(Derived,OtherDerived,OPNAME) \
+  (METHOD)(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const \
+  { \
+    return EIGEN_CWISE_BINARY_RETURN_TYPE(Derived,OtherDerived,OPNAME)(derived(), other.derived()); \
+  }
+
+#define EIGEN_SCALAR_BINARY_SUPPORTED(OPNAME,TYPEA,TYPEB) \
+  (Eigen::internal::has_ReturnType<Eigen::ScalarBinaryOpTraits<TYPEA,TYPEB,EIGEN_CAT(EIGEN_CAT(Eigen::internal::scalar_,OPNAME),_op)<TYPEA,TYPEB>  > >::value)
+
+#define EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(EXPR,SCALAR,OPNAME) \
+  CwiseBinaryOp<EIGEN_CAT(EIGEN_CAT(internal::scalar_,OPNAME),_op)<typename internal::traits<EXPR>::Scalar,SCALAR>, const EXPR, \
+                const typename internal::plain_constant_type<EXPR,SCALAR>::type>
+
+#define EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(SCALAR,EXPR,OPNAME) \
+  CwiseBinaryOp<EIGEN_CAT(EIGEN_CAT(internal::scalar_,OPNAME),_op)<SCALAR,typename internal::traits<EXPR>::Scalar>, \
+                const typename internal::plain_constant_type<EXPR,SCALAR>::type, const EXPR>
+
+// Workaround for MSVC 2010 (see ML thread "patch with compile for for MSVC 2010")
+#if EIGEN_COMP_MSVC_STRICT<=1600
+#define EIGEN_MSVC10_WORKAROUND_BINARYOP_RETURN_TYPE(X) typename internal::enable_if<true,X>::type
+#else
+#define EIGEN_MSVC10_WORKAROUND_BINARYOP_RETURN_TYPE(X) X
+#endif
+
+#define EIGEN_MAKE_SCALAR_BINARY_OP_ONTHERIGHT(METHOD,OPNAME) \
+  template <typename T> EIGEN_DEVICE_FUNC inline \
+  EIGEN_MSVC10_WORKAROUND_BINARYOP_RETURN_TYPE(const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,typename internal::promote_scalar_arg<Scalar EIGEN_COMMA T EIGEN_COMMA EIGEN_SCALAR_BINARY_SUPPORTED(OPNAME,Scalar,T)>::type,OPNAME))\
+  (METHOD)(const T& scalar) const { \
+    typedef typename internal::promote_scalar_arg<Scalar,T,EIGEN_SCALAR_BINARY_SUPPORTED(OPNAME,Scalar,T)>::type PromotedT; \
+    return EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,PromotedT,OPNAME)(derived(), \
+           typename internal::plain_constant_type<Derived,PromotedT>::type(derived().rows(), derived().cols(), internal::scalar_constant_op<PromotedT>(scalar))); \
+  }
+
+#define EIGEN_MAKE_SCALAR_BINARY_OP_ONTHELEFT(METHOD,OPNAME) \
+  template <typename T> EIGEN_DEVICE_FUNC inline friend \
+  EIGEN_MSVC10_WORKAROUND_BINARYOP_RETURN_TYPE(const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(typename internal::promote_scalar_arg<Scalar EIGEN_COMMA T EIGEN_COMMA EIGEN_SCALAR_BINARY_SUPPORTED(OPNAME,T,Scalar)>::type,Derived,OPNAME)) \
+  (METHOD)(const T& scalar, const StorageBaseType& matrix) { \
+    typedef typename internal::promote_scalar_arg<Scalar,T,EIGEN_SCALAR_BINARY_SUPPORTED(OPNAME,T,Scalar)>::type PromotedT; \
+    return EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(PromotedT,Derived,OPNAME)( \
+           typename internal::plain_constant_type<Derived,PromotedT>::type(matrix.derived().rows(), matrix.derived().cols(), internal::scalar_constant_op<PromotedT>(scalar)), matrix.derived()); \
+  }
+
+#define EIGEN_MAKE_SCALAR_BINARY_OP(METHOD,OPNAME) \
+  EIGEN_MAKE_SCALAR_BINARY_OP_ONTHELEFT(METHOD,OPNAME) \
+  EIGEN_MAKE_SCALAR_BINARY_OP_ONTHERIGHT(METHOD,OPNAME)
+
+
+#ifdef EIGEN_EXCEPTIONS
+#  define EIGEN_THROW_X(X) throw X
+#  define EIGEN_THROW throw
+#  define EIGEN_TRY try
+#  define EIGEN_CATCH(X) catch (X)
+#else
+#  ifdef __CUDA_ARCH__
+#    define EIGEN_THROW_X(X) asm("trap;")
+#    define EIGEN_THROW asm("trap;")
+#  else
+#    define EIGEN_THROW_X(X) std::abort()
+#    define EIGEN_THROW std::abort()
+#  endif
+#  define EIGEN_TRY if (true)
+#  define EIGEN_CATCH(X) else
+#endif
+
+
+#if EIGEN_HAS_CXX11_NOEXCEPT
+#   define EIGEN_INCLUDE_TYPE_TRAITS
+#   define EIGEN_NOEXCEPT noexcept
+#   define EIGEN_NOEXCEPT_IF(x) noexcept(x)
+#   define EIGEN_NO_THROW noexcept(true)
+#   define EIGEN_EXCEPTION_SPEC(X) noexcept(false)
+#else
+#   define EIGEN_NOEXCEPT
+#   define EIGEN_NOEXCEPT_IF(x)
+#   define EIGEN_NO_THROW throw()
+#   define EIGEN_EXCEPTION_SPEC(X) throw(X)
+#endif
 
 #endif // EIGEN_MACROS_H

Index: 3rd_party/eigen/Eigen/src/Core/util/Memory.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/Memory.h
+++ 3rd_party/eigen/Eigen/src/Core/util/Memory.h
@@ -1,13 +1,14 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2008-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2009 Kenneth Riddile <kfriddile@yahoo.com>
 // Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
 // Copyright (C) 2010 Thomas Capricelli <orzel@freehackers.org>
+// Copyright (C) 2013 Pavel Holoborodko <pavel@holoborodko.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -29,67 +30,48 @@
 // This leaves the question how to detect 64-bit. According to this document,
 //   http://gcc.fyxm.net/summit/2003/Porting%20to%2064%20bit.pdf
 // page 114, "[The] LP64 model [...] is used by all 64-bit UNIX ports" so it's indeed
 // quite safe, at least within the context of glibc, to equate 64-bit with LP64.
 #if defined(__GLIBC__) && ((__GLIBC__>=2 && __GLIBC_MINOR__ >= 8) || __GLIBC__>2) \
- && defined(__LP64__) && ! defined( __SANITIZE_ADDRESS__ )
+ && defined(__LP64__) && ! defined( __SANITIZE_ADDRESS__ ) && (EIGEN_DEFAULT_ALIGN_BYTES == 16)
   #define EIGEN_GLIBC_MALLOC_ALREADY_ALIGNED 1
 #else
   #define EIGEN_GLIBC_MALLOC_ALREADY_ALIGNED 0
 #endif
 
 // FreeBSD 6 seems to have 16-byte aligned malloc
 //   See http://svn.freebsd.org/viewvc/base/stable/6/lib/libc/stdlib/malloc.c?view=markup
 // FreeBSD 7 seems to have 16-byte aligned malloc except on ARM and MIPS architectures
 //   See http://svn.freebsd.org/viewvc/base/stable/7/lib/libc/stdlib/malloc.c?view=markup
-#if defined(__FreeBSD__) && !defined(__arm__) && !defined(__mips__)
+#if defined(__FreeBSD__) && !(EIGEN_ARCH_ARM || EIGEN_ARCH_MIPS) && (EIGEN_DEFAULT_ALIGN_BYTES == 16)
   #define EIGEN_FREEBSD_MALLOC_ALREADY_ALIGNED 1
 #else
   #define EIGEN_FREEBSD_MALLOC_ALREADY_ALIGNED 0
 #endif
 
-#if defined(__APPLE__) \
- || defined(_WIN64) \
- || EIGEN_GLIBC_MALLOC_ALREADY_ALIGNED \
+#if (EIGEN_OS_MAC && (EIGEN_DEFAULT_ALIGN_BYTES == 16))     \
+ || (EIGEN_OS_WIN64 && (EIGEN_DEFAULT_ALIGN_BYTES == 16))   \
+ || EIGEN_GLIBC_MALLOC_ALREADY_ALIGNED              \
  || EIGEN_FREEBSD_MALLOC_ALREADY_ALIGNED
   #define EIGEN_MALLOC_ALREADY_ALIGNED 1
 #else
   #define EIGEN_MALLOC_ALREADY_ALIGNED 0
 #endif
 
 #endif
 
-// See bug 554 (http://eigen.tuxfamily.org/bz/show_bug.cgi?id=554)
-// It seems to be unsafe to check _POSIX_ADVISORY_INFO without including unistd.h first.
-// Currently, let's include it only on unix systems:
-#if defined(__unix__) || defined(__unix)
-  #include <unistd.h>
-  #if ((defined __QNXNTO__) || (defined _GNU_SOURCE) || (defined __PGI) || ((defined _XOPEN_SOURCE) && (_XOPEN_SOURCE >= 600))) && (defined _POSIX_ADVISORY_INFO) && (_POSIX_ADVISORY_INFO > 0)
-    #define EIGEN_HAS_POSIX_MEMALIGN 1
-  #endif
-#endif
-
-#ifndef EIGEN_HAS_POSIX_MEMALIGN
-  #define EIGEN_HAS_POSIX_MEMALIGN 0
-#endif
-
-#ifdef EIGEN_VECTORIZE_SSE
-  #define EIGEN_HAS_MM_MALLOC 1
-#else
-  #define EIGEN_HAS_MM_MALLOC 0
-#endif
-
 namespace Eigen {
 
 namespace internal {
 
+EIGEN_DEVICE_FUNC 
 inline void throw_std_bad_alloc()
 {
   #ifdef EIGEN_EXCEPTIONS
     throw std::bad_alloc();
   #else
-    std::size_t huge = -1;
+    std::size_t huge = static_cast<std::size_t>(-1);
     new int[huge];
   #endif
 }
 
 /*****************************************************************************
@@ -101,13 +83,13 @@
 /** \internal Like malloc, but the returned pointer is guaranteed to be 16-byte aligned.
   * Fast, but wastes 16 additional bytes of memory. Does not throw any exception.
   */
 inline void* handmade_aligned_malloc(std::size_t size)
 {
-  void *original = std::malloc(size+16);
+  void *original = std::malloc(size+EIGEN_DEFAULT_ALIGN_BYTES);
   if (original == 0) return 0;
-  void *aligned = reinterpret_cast<void*>((reinterpret_cast<std::size_t>(original) & ~(std::size_t(15))) + 16);
+  void *aligned = reinterpret_cast<void*>((reinterpret_cast<std::size_t>(original) & ~(std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1))) + EIGEN_DEFAULT_ALIGN_BYTES);
   *(reinterpret_cast<void**>(aligned) - 1) = original;
   return aligned;
 }
 
 /** \internal Frees memory allocated with handmade_aligned_malloc */
@@ -116,116 +98,70 @@
   if (ptr) std::free(*(reinterpret_cast<void**>(ptr) - 1));
 }
 
 /** \internal
   * \brief Reallocates aligned memory.
-  * Since we know that our handmade version is based on std::realloc
+  * Since we know that our handmade version is based on std::malloc
   * we can use std::realloc to implement efficient reallocation.
   */
 inline void* handmade_aligned_realloc(void* ptr, std::size_t size, std::size_t = 0)
 {
   if (ptr == 0) return handmade_aligned_malloc(size);
   void *original = *(reinterpret_cast<void**>(ptr) - 1);
   std::ptrdiff_t previous_offset = static_cast<char *>(ptr)-static_cast<char *>(original);
-  original = std::realloc(original,size+16);
+  original = std::realloc(original,size+EIGEN_DEFAULT_ALIGN_BYTES);
   if (original == 0) return 0;
-  void *aligned = reinterpret_cast<void*>((reinterpret_cast<std::size_t>(original) & ~(std::size_t(15))) + 16);
+  void *aligned = reinterpret_cast<void*>((reinterpret_cast<std::size_t>(original) & ~(std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1))) + EIGEN_DEFAULT_ALIGN_BYTES);
   void *previous_aligned = static_cast<char *>(original)+previous_offset;
   if(aligned!=previous_aligned)
     std::memmove(aligned, previous_aligned, size);
   
   *(reinterpret_cast<void**>(aligned) - 1) = original;
   return aligned;
 }
 
-/*****************************************************************************
-*** Implementation of generic aligned realloc (when no realloc can be used)***
-*****************************************************************************/
-
-void* aligned_malloc(std::size_t size);
-void  aligned_free(void *ptr);
-
-/** \internal
-  * \brief Reallocates aligned memory.
-  * Allows reallocation with aligned ptr types. This implementation will
-  * always create a new memory chunk and copy the old data.
-  */
-inline void* generic_aligned_realloc(void* ptr, size_t size, size_t old_size)
-{
-  if (ptr==0)
-    return aligned_malloc(size);
-
-  if (size==0)
-  {
-    aligned_free(ptr);
-    return 0;
-  }
-
-  void* newptr = aligned_malloc(size);
-  if (newptr == 0)
-  {
-    #ifdef EIGEN_HAS_ERRNO
-    errno = ENOMEM; // according to the standard
-    #endif
-    return 0;
-  }
-
-  if (ptr != 0)
-  {
-    std::memcpy(newptr, ptr, (std::min)(size,old_size));
-    aligned_free(ptr);
-  }
-
-  return newptr;
-}
-
 /*****************************************************************************
 *** Implementation of portable aligned versions of malloc/free/realloc     ***
 *****************************************************************************/
 
 #ifdef EIGEN_NO_MALLOC
-inline void check_that_malloc_is_allowed()
+EIGEN_DEVICE_FUNC inline void check_that_malloc_is_allowed()
 {
   eigen_assert(false && "heap allocation is forbidden (EIGEN_NO_MALLOC is defined)");
 }
 #elif defined EIGEN_RUNTIME_NO_MALLOC
-inline bool is_malloc_allowed_impl(bool update, bool new_value = false)
+EIGEN_DEVICE_FUNC inline bool is_malloc_allowed_impl(bool update, bool new_value = false)
 {
   static bool value = true;
   if (update == 1)
     value = new_value;
   return value;
 }
-inline bool is_malloc_allowed() { return is_malloc_allowed_impl(false); }
-inline bool set_is_malloc_allowed(bool new_value) { return is_malloc_allowed_impl(true, new_value); }
-inline void check_that_malloc_is_allowed()
+EIGEN_DEVICE_FUNC inline bool is_malloc_allowed() { return is_malloc_allowed_impl(false); }
+EIGEN_DEVICE_FUNC inline bool set_is_malloc_allowed(bool new_value) { return is_malloc_allowed_impl(true, new_value); }
+EIGEN_DEVICE_FUNC inline void check_that_malloc_is_allowed()
 {
   eigen_assert(is_malloc_allowed() && "heap allocation is forbidden (EIGEN_RUNTIME_NO_MALLOC is defined and g_is_malloc_allowed is false)");
 }
 #else 
-inline void check_that_malloc_is_allowed()
+EIGEN_DEVICE_FUNC inline void check_that_malloc_is_allowed()
 {}
 #endif
 
-/** \internal Allocates \a size bytes. The returned pointer is guaranteed to have 16 bytes alignment.
+/** \internal Allocates \a size bytes. The returned pointer is guaranteed to have 16 or 32 bytes alignment depending on the requirements.
   * On allocation error, the returned pointer is null, and std::bad_alloc is thrown.
   */
-inline void* aligned_malloc(size_t size)
+EIGEN_DEVICE_FUNC inline void* aligned_malloc(std::size_t size)
 {
   check_that_malloc_is_allowed();
 
   void *result;
-  #if !EIGEN_ALIGN
-    result = std::malloc(size);
-  #elif EIGEN_MALLOC_ALREADY_ALIGNED
-    result = std::malloc(size);
-  #elif EIGEN_HAS_POSIX_MEMALIGN
-    if(posix_memalign(&result, 16, size)) result = 0;
-  #elif EIGEN_HAS_MM_MALLOC
-    result = _mm_malloc(size, 16);
-  #elif defined(_MSC_VER) && (!defined(_WIN32_WCE))
-    result = _aligned_malloc(size, 16);
+  #if (EIGEN_DEFAULT_ALIGN_BYTES==0) || EIGEN_MALLOC_ALREADY_ALIGNED
+    result = std::malloc(size);
+    #if EIGEN_DEFAULT_ALIGN_BYTES==16
+    eigen_assert((size<16 || (std::size_t(result)%16)==0) && "System's malloc returned an unaligned pointer. Compile with EIGEN_MALLOC_ALREADY_ALIGNED=0 to fallback to handmade alignd memory allocator.");
+    #endif
   #else
     result = handmade_aligned_malloc(size);
   #endif
 
   if(!result && size)
@@ -233,54 +169,31 @@
 
   return result;
 }
 
 /** \internal Frees memory allocated with aligned_malloc. */
-inline void aligned_free(void *ptr)
-{
-  #if !EIGEN_ALIGN
-    std::free(ptr);
-  #elif EIGEN_MALLOC_ALREADY_ALIGNED
-    std::free(ptr);
-  #elif EIGEN_HAS_POSIX_MEMALIGN
-    std::free(ptr);
-  #elif EIGEN_HAS_MM_MALLOC
-    _mm_free(ptr);
-  #elif defined(_MSC_VER) && (!defined(_WIN32_WCE))
-    _aligned_free(ptr);
+EIGEN_DEVICE_FUNC inline void aligned_free(void *ptr)
+{
+  #if (EIGEN_DEFAULT_ALIGN_BYTES==0) || EIGEN_MALLOC_ALREADY_ALIGNED
+    std::free(ptr);
   #else
     handmade_aligned_free(ptr);
   #endif
 }
 
 /**
-* \internal
-* \brief Reallocates an aligned block of memory.
-* \throws std::bad_alloc on allocation failure
-**/
-inline void* aligned_realloc(void *ptr, size_t new_size, size_t old_size)
+  * \internal
+  * \brief Reallocates an aligned block of memory.
+  * \throws std::bad_alloc on allocation failure
+  */
+inline void* aligned_realloc(void *ptr, std::size_t new_size, std::size_t old_size)
 {
   EIGEN_UNUSED_VARIABLE(old_size);
 
   void *result;
-#if !EIGEN_ALIGN
-  result = std::realloc(ptr,new_size);
-#elif EIGEN_MALLOC_ALREADY_ALIGNED
-  result = std::realloc(ptr,new_size);
-#elif EIGEN_HAS_POSIX_MEMALIGN
-  result = generic_aligned_realloc(ptr,new_size,old_size);
-#elif EIGEN_HAS_MM_MALLOC
-  // The defined(_mm_free) is just here to verify that this MSVC version
-  // implements _mm_malloc/_mm_free based on the corresponding _aligned_
-  // functions. This may not always be the case and we just try to be safe.
-  #if defined(_MSC_VER) && (!defined(_WIN32_WCE)) && defined(_mm_free)
-    result = _aligned_realloc(ptr,new_size,16);
-  #else
-    result = generic_aligned_realloc(ptr,new_size,old_size);
-  #endif
-#elif defined(_MSC_VER) && (!defined(_WIN32_WCE))
-  result = _aligned_realloc(ptr,new_size,16);
+#if (EIGEN_DEFAULT_ALIGN_BYTES==0) || EIGEN_MALLOC_ALREADY_ALIGNED
+  result = std::realloc(ptr,new_size);
 #else
   result = handmade_aligned_realloc(ptr,new_size,old_size);
 #endif
 
   if (!result && new_size)
@@ -294,16 +207,16 @@
 *****************************************************************************/
 
 /** \internal Allocates \a size bytes. If Align is true, then the returned ptr is 16-byte-aligned.
   * On allocation error, the returned pointer is null, and a std::bad_alloc is thrown.
   */
-template<bool Align> inline void* conditional_aligned_malloc(size_t size)
+template<bool Align> EIGEN_DEVICE_FUNC inline void* conditional_aligned_malloc(std::size_t size)
 {
   return aligned_malloc(size);
 }
 
-template<> inline void* conditional_aligned_malloc<false>(size_t size)
+template<> EIGEN_DEVICE_FUNC inline void* conditional_aligned_malloc<false>(std::size_t size)
 {
   check_that_malloc_is_allowed();
 
   void *result = std::malloc(size);
   if(!result && size)
@@ -310,240 +223,347 @@
     throw_std_bad_alloc();
   return result;
 }
 
 /** \internal Frees memory allocated with conditional_aligned_malloc */
-template<bool Align> inline void conditional_aligned_free(void *ptr)
+template<bool Align> EIGEN_DEVICE_FUNC inline void conditional_aligned_free(void *ptr)
 {
   aligned_free(ptr);
 }
 
-template<> inline void conditional_aligned_free<false>(void *ptr)
+template<> EIGEN_DEVICE_FUNC inline void conditional_aligned_free<false>(void *ptr)
 {
   std::free(ptr);
 }
 
-template<bool Align> inline void* conditional_aligned_realloc(void* ptr, size_t new_size, size_t old_size)
+template<bool Align> inline void* conditional_aligned_realloc(void* ptr, std::size_t new_size, std::size_t old_size)
 {
   return aligned_realloc(ptr, new_size, old_size);
 }
 
-template<> inline void* conditional_aligned_realloc<false>(void* ptr, size_t new_size, size_t)
+template<> inline void* conditional_aligned_realloc<false>(void* ptr, std::size_t new_size, std::size_t)
 {
   return std::realloc(ptr, new_size);
 }
 
 /*****************************************************************************
 *** Construction/destruction of array elements                             ***
 *****************************************************************************/
 
-/** \internal Constructs the elements of an array.
-  * The \a size parameter tells on how many objects to call the constructor of T.
-  */
-template<typename T> inline T* construct_elements_of_array(T *ptr, size_t size)
-{
-  for (size_t i=0; i < size; ++i) ::new (ptr + i) T;
-  return ptr;
-}
-
 /** \internal Destructs the elements of an array.
   * The \a size parameters tells on how many objects to call the destructor of T.
   */
-template<typename T> inline void destruct_elements_of_array(T *ptr, size_t size)
+template<typename T> EIGEN_DEVICE_FUNC inline void destruct_elements_of_array(T *ptr, std::size_t size)
 {
   // always destruct an array starting from the end.
   if(ptr)
     while(size) ptr[--size].~T();
 }
+
+/** \internal Constructs the elements of an array.
+  * The \a size parameter tells on how many objects to call the constructor of T.
+  */
+template<typename T> EIGEN_DEVICE_FUNC inline T* construct_elements_of_array(T *ptr, std::size_t size)
+{
+  std::size_t i;
+  EIGEN_TRY
+  {
+      for (i = 0; i < size; ++i) ::new (ptr + i) T;
+      return ptr;
+  }
+  EIGEN_CATCH(...)
+  {
+    destruct_elements_of_array(ptr, i);
+    EIGEN_THROW;
+  }
+  return NULL;
+}
 
 /*****************************************************************************
 *** Implementation of aligned new/delete-like functions                    ***
 *****************************************************************************/
 
 template<typename T>
-EIGEN_ALWAYS_INLINE void check_size_for_overflow(size_t size)
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void check_size_for_overflow(std::size_t size)
 {
-  if(size > size_t(-1) / sizeof(T))
+  if(size > std::size_t(-1) / sizeof(T))
     throw_std_bad_alloc();
 }
 
 /** \internal Allocates \a size objects of type T. The returned pointer is guaranteed to have 16 bytes alignment.
   * On allocation error, the returned pointer is undefined, but a std::bad_alloc is thrown.
   * The default constructor of T is called.
   */
-template<typename T> inline T* aligned_new(size_t size)
+template<typename T> EIGEN_DEVICE_FUNC inline T* aligned_new(std::size_t size)
 {
   check_size_for_overflow<T>(size);
   T *result = reinterpret_cast<T*>(aligned_malloc(sizeof(T)*size));
-  return construct_elements_of_array(result, size);
+  EIGEN_TRY
+  {
+    return construct_elements_of_array(result, size);
+  }
+  EIGEN_CATCH(...)
+  {
+    aligned_free(result);
+    EIGEN_THROW;
+  }
+  return result;
 }
 
-template<typename T, bool Align> inline T* conditional_aligned_new(size_t size)
+template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_new(std::size_t size)
 {
   check_size_for_overflow<T>(size);
   T *result = reinterpret_cast<T*>(conditional_aligned_malloc<Align>(sizeof(T)*size));
-  return construct_elements_of_array(result, size);
+  EIGEN_TRY
+  {
+    return construct_elements_of_array(result, size);
+  }
+  EIGEN_CATCH(...)
+  {
+    conditional_aligned_free<Align>(result);
+    EIGEN_THROW;
+  }
+  return result;
 }
 
 /** \internal Deletes objects constructed with aligned_new
   * The \a size parameters tells on how many objects to call the destructor of T.
   */
-template<typename T> inline void aligned_delete(T *ptr, size_t size)
+template<typename T> EIGEN_DEVICE_FUNC inline void aligned_delete(T *ptr, std::size_t size)
 {
   destruct_elements_of_array<T>(ptr, size);
   aligned_free(ptr);
 }
 
 /** \internal Deletes objects constructed with conditional_aligned_new
   * The \a size parameters tells on how many objects to call the destructor of T.
   */
-template<typename T, bool Align> inline void conditional_aligned_delete(T *ptr, size_t size)
+template<typename T, bool Align> EIGEN_DEVICE_FUNC inline void conditional_aligned_delete(T *ptr, std::size_t size)
 {
   destruct_elements_of_array<T>(ptr, size);
   conditional_aligned_free<Align>(ptr);
 }
 
-template<typename T, bool Align> inline T* conditional_aligned_realloc_new(T* pts, size_t new_size, size_t old_size)
+template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_realloc_new(T* pts, std::size_t new_size, std::size_t old_size)
 {
   check_size_for_overflow<T>(new_size);
   check_size_for_overflow<T>(old_size);
   if(new_size < old_size)
     destruct_elements_of_array(pts+new_size, old_size-new_size);
   T *result = reinterpret_cast<T*>(conditional_aligned_realloc<Align>(reinterpret_cast<void*>(pts), sizeof(T)*new_size, sizeof(T)*old_size));
   if(new_size > old_size)
-    construct_elements_of_array(result+old_size, new_size-old_size);
+  {
+    EIGEN_TRY
+    {
+      construct_elements_of_array(result+old_size, new_size-old_size);
+    }
+    EIGEN_CATCH(...)
+    {
+      conditional_aligned_free<Align>(result);
+      EIGEN_THROW;
+    }
+  }
   return result;
 }
 
 
-template<typename T, bool Align> inline T* conditional_aligned_new_auto(size_t size)
+template<typename T, bool Align> EIGEN_DEVICE_FUNC inline T* conditional_aligned_new_auto(std::size_t size)
 {
   if(size==0)
     return 0; // short-cut. Also fixes Bug 884
   check_size_for_overflow<T>(size);
   T *result = reinterpret_cast<T*>(conditional_aligned_malloc<Align>(sizeof(T)*size));
   if(NumTraits<T>::RequireInitialization)
-    construct_elements_of_array(result, size);
+  {
+    EIGEN_TRY
+    {
+      construct_elements_of_array(result, size);
+    }
+    EIGEN_CATCH(...)
+    {
+      conditional_aligned_free<Align>(result);
+      EIGEN_THROW;
+    }
+  }
   return result;
 }
 
-template<typename T, bool Align> inline T* conditional_aligned_realloc_new_auto(T* pts, size_t new_size, size_t old_size)
+template<typename T, bool Align> inline T* conditional_aligned_realloc_new_auto(T* pts, std::size_t new_size, std::size_t old_size)
 {
   check_size_for_overflow<T>(new_size);
   check_size_for_overflow<T>(old_size);
   if(NumTraits<T>::RequireInitialization && (new_size < old_size))
     destruct_elements_of_array(pts+new_size, old_size-new_size);
   T *result = reinterpret_cast<T*>(conditional_aligned_realloc<Align>(reinterpret_cast<void*>(pts), sizeof(T)*new_size, sizeof(T)*old_size));
   if(NumTraits<T>::RequireInitialization && (new_size > old_size))
-    construct_elements_of_array(result+old_size, new_size-old_size);
+  {
+    EIGEN_TRY
+    {
+      construct_elements_of_array(result+old_size, new_size-old_size);
+    }
+    EIGEN_CATCH(...)
+    {
+      conditional_aligned_free<Align>(result);
+      EIGEN_THROW;
+    }
+  }
   return result;
 }
 
-template<typename T, bool Align> inline void conditional_aligned_delete_auto(T *ptr, size_t size)
+template<typename T, bool Align> EIGEN_DEVICE_FUNC inline void conditional_aligned_delete_auto(T *ptr, std::size_t size)
 {
   if(NumTraits<T>::RequireInitialization)
     destruct_elements_of_array<T>(ptr, size);
   conditional_aligned_free<Align>(ptr);
 }
 
 /****************************************************************************/
 
-/** \internal Returns the index of the first element of the array that is well aligned for vectorization.
+/** \internal Returns the index of the first element of the array that is well aligned with respect to the requested \a Alignment.
   *
+  * \tparam Alignment requested alignment in Bytes.
   * \param array the address of the start of the array
   * \param size the size of the array
   *
-  * \note If no element of the array is well aligned, the size of the array is returned. Typically,
-  * for example with SSE, "well aligned" means 16-byte-aligned. If vectorization is disabled or if the
+  * \note If no element of the array is well aligned or the requested alignment is not a multiple of a scalar,
+  * the size of the array is returned. For example with SSE, the requested alignment is typically 16-bytes. If
   * packet size for the given scalar type is 1, then everything is considered well-aligned.
   *
-  * \note If the scalar type is vectorizable, we rely on the following assumptions: sizeof(Scalar) is a
-  * power of 2, the packet size in bytes is also a power of 2, and is a multiple of sizeof(Scalar). On the
-  * other hand, we do not assume that the array address is a multiple of sizeof(Scalar), as that fails for
+  * \note Otherwise, if the Alignment is larger that the scalar size, we rely on the assumptions that sizeof(Scalar) is a
+  * power of 2. On the other hand, we do not assume that the array address is a multiple of sizeof(Scalar), as that fails for
   * example with Scalar=double on certain 32-bit platforms, see bug #79.
   *
   * There is also the variant first_aligned(const MatrixBase&) defined in DenseCoeffsBase.h.
+  * \sa first_default_aligned()
   */
-template<typename Scalar, typename Index>
-static inline Index first_aligned(const Scalar* array, Index size)
-{
-  static const Index PacketSize = packet_traits<Scalar>::size;
-  static const Index PacketAlignedMask = PacketSize-1;
-
-  if(PacketSize==1)
-  {
-    // Either there is no vectorization, or a packet consists of exactly 1 scalar so that all elements
-    // of the array have the same alignment.
+template<int Alignment, typename Scalar, typename Index>
+EIGEN_DEVICE_FUNC inline Index first_aligned(const Scalar* array, Index size)
+{
+  const Index ScalarSize = sizeof(Scalar);
+  const Index AlignmentSize = Alignment / ScalarSize;
+  const Index AlignmentMask = AlignmentSize-1;
+
+  if(AlignmentSize<=1)
+  {
+    // Either the requested alignment if smaller than a scalar, or it exactly match a 1 scalar
+    // so that all elements of the array have the same alignment.
     return 0;
   }
-  else if(size_t(array) & (sizeof(Scalar)-1))
+  else if( (UIntPtr(array) & (sizeof(Scalar)-1)) || (Alignment%ScalarSize)!=0)
   {
-    // There is vectorization for this scalar type, but the array is not aligned to the size of a single scalar.
+    // The array is not aligned to the size of a single scalar, or the requested alignment is not a multiple of the scalar size.
     // Consequently, no element of the array is well aligned.
     return size;
   }
   else
   {
-    return std::min<Index>( (PacketSize - (Index((size_t(array)/sizeof(Scalar))) & PacketAlignedMask))
-                           & PacketAlignedMask, size);
+    Index first = (AlignmentSize - (Index((UIntPtr(array)/sizeof(Scalar))) & AlignmentMask)) & AlignmentMask;
+    return (first < size) ? first : size;
   }
 }
+
+/** \internal Returns the index of the first element of the array that is well aligned with respect the largest packet requirement.
+   * \sa first_aligned(Scalar*,Index) and first_default_aligned(DenseBase<Derived>) */
+template<typename Scalar, typename Index>
+EIGEN_DEVICE_FUNC inline Index first_default_aligned(const Scalar* array, Index size)
+{
+  typedef typename packet_traits<Scalar>::type DefaultPacketType;
+  return first_aligned<unpacket_traits<DefaultPacketType>::alignment>(array, size);
+}
 
 /** \internal Returns the smallest integer multiple of \a base and greater or equal to \a size
   */ 
 template<typename Index> 
-inline static Index first_multiple(Index size, Index base)
+inline Index first_multiple(Index size, Index base)
 {
   return ((size+base-1)/base)*base;
 }
 
 // std::copy is much slower than memcpy, so let's introduce a smart_copy which
 // use memcpy on trivial types, i.e., on types that does not require an initialization ctor.
 template<typename T, bool UseMemcpy> struct smart_copy_helper;
 
-template<typename T> void smart_copy(const T* start, const T* end, T* target)
+template<typename T> EIGEN_DEVICE_FUNC void smart_copy(const T* start, const T* end, T* target)
 {
   smart_copy_helper<T,!NumTraits<T>::RequireInitialization>::run(start, end, target);
 }
 
 template<typename T> struct smart_copy_helper<T,true> {
-  static inline void run(const T* start, const T* end, T* target)
-  { memcpy(target, start, std::ptrdiff_t(end)-std::ptrdiff_t(start)); }
+  EIGEN_DEVICE_FUNC static inline void run(const T* start, const T* end, T* target)
+  {
+    IntPtr size = IntPtr(end)-IntPtr(start);
+    if(size==0) return;
+    eigen_internal_assert(start!=0 && end!=0 && target!=0);
+    memcpy(target, start, size);
+  }
 };
 
 template<typename T> struct smart_copy_helper<T,false> {
-  static inline void run(const T* start, const T* end, T* target)
+  EIGEN_DEVICE_FUNC static inline void run(const T* start, const T* end, T* target)
   { std::copy(start, end, target); }
 };
+
+// intelligent memmove. falls back to std::memmove for POD types, uses std::copy otherwise. 
+template<typename T, bool UseMemmove> struct smart_memmove_helper;
+
+template<typename T> void smart_memmove(const T* start, const T* end, T* target)
+{
+  smart_memmove_helper<T,!NumTraits<T>::RequireInitialization>::run(start, end, target);
+}
+
+template<typename T> struct smart_memmove_helper<T,true> {
+  static inline void run(const T* start, const T* end, T* target)
+  {
+    IntPtr size = IntPtr(end)-IntPtr(start);
+    if(size==0) return;
+    eigen_internal_assert(start!=0 && end!=0 && target!=0);
+    std::memmove(target, start, size);
+  }
+};
+
+template<typename T> struct smart_memmove_helper<T,false> {
+  static inline void run(const T* start, const T* end, T* target)
+  { 
+    if (UIntPtr(target) < UIntPtr(start))
+    {
+      std::copy(start, end, target);
+    }
+    else                                 
+    {
+      std::ptrdiff_t count = (std::ptrdiff_t(end)-std::ptrdiff_t(start)) / sizeof(T);
+      std::copy_backward(start, end, target + count); 
+    }
+  }
+};
 
 
 /*****************************************************************************
 *** Implementation of runtime stack allocation (falling back to malloc)    ***
 *****************************************************************************/
 
 // you can overwrite Eigen's default behavior regarding alloca by defining EIGEN_ALLOCA
 // to the appropriate stack allocation function
 #ifndef EIGEN_ALLOCA
-  #if (defined __linux__)
+  #if EIGEN_OS_LINUX || EIGEN_OS_MAC || (defined alloca)
     #define EIGEN_ALLOCA alloca
-  #elif defined(_MSC_VER)
+  #elif EIGEN_COMP_MSVC
     #define EIGEN_ALLOCA _alloca
   #endif
 #endif
 
 // This helper class construct the allocated memory, and takes care of destructing and freeing the handled data
 // at destruction time. In practice this helper class is mainly useful to avoid memory leak in case of exceptions.
-template<typename T> class aligned_stack_memory_handler
+template<typename T> class aligned_stack_memory_handler : noncopyable
 {
   public:
     /* Creates a stack_memory_handler responsible for the buffer \a ptr of size \a size.
      * Note that \a ptr can be 0 regardless of the other parameters.
      * This constructor takes care of constructing/initializing the elements of the buffer if required by the scalar type T (see NumTraits<T>::RequireInitialization).
      * In this case, the buffer elements will also be destructed when this handler will be destructed.
      * Finally, if \a dealloc is true, then the pointer \a ptr is freed.
      **/
-    aligned_stack_memory_handler(T* ptr, size_t size, bool dealloc)
+    aligned_stack_memory_handler(T* ptr, std::size_t size, bool dealloc)
       : m_ptr(ptr), m_size(size), m_deallocate(dealloc)
     {
       if(NumTraits<T>::RequireInitialization && m_ptr)
         Eigen::internal::construct_elements_of_array(m_ptr, size);
     }
@@ -554,14 +574,38 @@
       if(m_deallocate)
         Eigen::internal::aligned_free(m_ptr);
     }
   protected:
     T* m_ptr;
-    size_t m_size;
+    std::size_t m_size;
     bool m_deallocate;
 };
 
+template<typename T> class scoped_array : noncopyable
+{
+  T* m_ptr;
+public:
+  explicit scoped_array(std::ptrdiff_t size)
+  {
+    m_ptr = new T[size];
+  }
+  ~scoped_array()
+  {
+    delete[] m_ptr;
+  }
+  T& operator[](std::ptrdiff_t i) { return m_ptr[i]; }
+  const T& operator[](std::ptrdiff_t i) const { return m_ptr[i]; }
+  T* &ptr() { return m_ptr; }
+  const T* ptr() const { return m_ptr; }
+  operator const T*() const { return m_ptr; }
+};
+
+template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b)
+{
+  std::swap(a.ptr(),b.ptr());
+}
+    
 } // end namespace internal
 
 /** \internal
   * Declares, allocates and construct an aligned buffer named NAME of SIZE elements of type TYPE on the stack
   * if SIZE is smaller than EIGEN_STACK_ALLOCATION_LIMIT, and if stack allocation is supported by the platform
@@ -576,15 +620,17 @@
   * }
   * \endcode
   * The underlying stack allocation function can controlled with the EIGEN_ALLOCA preprocessor token.
   */
 #ifdef EIGEN_ALLOCA
-
-  #if defined(__arm__) || defined(_WIN32)
-    #define EIGEN_ALIGNED_ALLOCA(SIZE) reinterpret_cast<void*>((reinterpret_cast<size_t>(EIGEN_ALLOCA(SIZE+16)) & ~(size_t(15))) + 16)
+  
+  #if EIGEN_DEFAULT_ALIGN_BYTES>0
+    // We always manually re-align the result of EIGEN_ALLOCA.
+    // If alloca is already aligned, the compiler should be smart enough to optimize away the re-alignment.
+    #define EIGEN_ALIGNED_ALLOCA(SIZE) reinterpret_cast<void*>((internal::UIntPtr(EIGEN_ALLOCA(SIZE+EIGEN_DEFAULT_ALIGN_BYTES-1)) + EIGEN_DEFAULT_ALIGN_BYTES-1) & ~(std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1)))
   #else
-    #define EIGEN_ALIGNED_ALLOCA EIGEN_ALLOCA
+    #define EIGEN_ALIGNED_ALLOCA(SIZE) EIGEN_ALLOCA(SIZE)
   #endif
 
   #define ei_declare_aligned_stack_constructed_variable(TYPE,NAME,SIZE,BUFFER) \
     Eigen::internal::check_size_for_overflow<TYPE>(SIZE); \
     TYPE* NAME = (BUFFER)!=0 ? (BUFFER) \
@@ -605,53 +651,47 @@
 
 /*****************************************************************************
 *** Implementation of EIGEN_MAKE_ALIGNED_OPERATOR_NEW [_IF]                ***
 *****************************************************************************/
 
-#if EIGEN_ALIGN
-  #ifdef EIGEN_EXCEPTIONS
-    #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \
-      void* operator new(size_t size, const std::nothrow_t&) throw() { \
-        try { return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); } \
-        catch (...) { return 0; } \
-      }
-  #else
-    #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \
-      void* operator new(size_t size, const std::nothrow_t&) throw() { \
-        return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); \
-      }
-  #endif
-
-  #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign) \
-      void *operator new(size_t size) { \
-        return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); \
-      } \
-      void *operator new[](size_t size) { \
-        return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); \
-      } \
-      void operator delete(void * ptr) throw() { Eigen::internal::conditional_aligned_free<NeedsToAlign>(ptr); } \
-      void operator delete[](void * ptr) throw() { Eigen::internal::conditional_aligned_free<NeedsToAlign>(ptr); } \
+#if EIGEN_MAX_ALIGN_BYTES!=0
+  #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \
+      void* operator new(std::size_t size, const std::nothrow_t&) EIGEN_NO_THROW { \
+        EIGEN_TRY { return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); } \
+        EIGEN_CATCH (...) { return 0; } \
+      }
+  #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign) \
+      void *operator new(std::size_t size) { \
+        return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); \
+      } \
+      void *operator new[](std::size_t size) { \
+        return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); \
+      } \
+      void operator delete(void * ptr) EIGEN_NO_THROW { Eigen::internal::conditional_aligned_free<NeedsToAlign>(ptr); } \
+      void operator delete[](void * ptr) EIGEN_NO_THROW { Eigen::internal::conditional_aligned_free<NeedsToAlign>(ptr); } \
+      void operator delete(void * ptr, std::size_t /* sz */) EIGEN_NO_THROW { Eigen::internal::conditional_aligned_free<NeedsToAlign>(ptr); } \
+      void operator delete[](void * ptr, std::size_t /* sz */) EIGEN_NO_THROW { Eigen::internal::conditional_aligned_free<NeedsToAlign>(ptr); } \
       /* in-place new and delete. since (at least afaik) there is no actual   */ \
       /* memory allocated we can safely let the default implementation handle */ \
       /* this particular case. */ \
-      static void *operator new(size_t size, void *ptr) { return ::operator new(size,ptr); } \
-      static void *operator new[](size_t size, void* ptr) { return ::operator new[](size,ptr); } \
-      void operator delete(void * memory, void *ptr) throw() { return ::operator delete(memory,ptr); } \
-      void operator delete[](void * memory, void *ptr) throw() { return ::operator delete[](memory,ptr); } \
+      static void *operator new(std::size_t size, void *ptr) { return ::operator new(size,ptr); } \
+      static void *operator new[](std::size_t size, void* ptr) { return ::operator new[](size,ptr); } \
+      void operator delete(void * memory, void *ptr) EIGEN_NO_THROW { return ::operator delete(memory,ptr); } \
+      void operator delete[](void * memory, void *ptr) EIGEN_NO_THROW { return ::operator delete[](memory,ptr); } \
       /* nothrow-new (returns zero instead of std::bad_alloc) */ \
       EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \
-      void operator delete(void *ptr, const std::nothrow_t&) throw() { \
+      void operator delete(void *ptr, const std::nothrow_t&) EIGEN_NO_THROW { \
         Eigen::internal::conditional_aligned_free<NeedsToAlign>(ptr); \
       } \
       typedef void eigen_aligned_operator_new_marker_type;
 #else
   #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
 #endif
 
 #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(true)
 #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(Scalar,Size) \
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(bool(((Size)!=Eigen::Dynamic) && ((sizeof(Scalar)*(Size))%16==0)))
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(bool(((Size)!=Eigen::Dynamic) && ((sizeof(Scalar)*(Size))%EIGEN_MAX_ALIGN_BYTES==0)))
 
 /****************************************************************************/
 
 /** \class aligned_allocator
 * \ingroup Core_Module
@@ -665,111 +705,71 @@
 *           aligned_allocator<std::pair<const int, Matrix4f> > > my_map_mat4;
 * // Vector3f does not require 16 bytes alignment, no need to use Eigen's allocator:
 * std::map< int, Vector3f > my_map_vec3;
 * \endcode
 *
-* \sa \ref TopicStlContainers.
+* \sa \blank \ref TopicStlContainers.
 */
 template<class T>
-class aligned_allocator
+class aligned_allocator : public std::allocator<T>
 {
 public:
-    typedef size_t    size_type;
-    typedef std::ptrdiff_t difference_type;
-    typedef T*        pointer;
-    typedef const T*  const_pointer;
-    typedef T&        reference;
-    typedef const T&  const_reference;
-    typedef T         value_type;
-
-    template<class U>
-    struct rebind
-    {
-        typedef aligned_allocator<U> other;
-    };
-
-    pointer address( reference value ) const
-    {
-        return &value;
-    }
-
-    const_pointer address( const_reference value ) const
-    {
-        return &value;
-    }
-
-    aligned_allocator()
-    {
-    }
-
-    aligned_allocator( const aligned_allocator& )
-    {
-    }
-
-    template<class U>
-    aligned_allocator( const aligned_allocator<U>& )
-    {
-    }
-
-    ~aligned_allocator()
-    {
-    }
-
-    size_type max_size() const
-    {
-        return (std::numeric_limits<size_type>::max)();
-    }
-
-    pointer allocate( size_type num, const void* hint = 0 )
-    {
-        EIGEN_UNUSED_VARIABLE(hint);
-        internal::check_size_for_overflow<T>(num);
-        return static_cast<pointer>( internal::aligned_malloc( num * sizeof(T) ) );
-    }
-
-    void construct( pointer p, const T& value )
-    {
-        ::new( p ) T( value );
-    }
-
-    void destroy( pointer p )
-    {
-        p->~T();
-    }
-
-    void deallocate( pointer p, size_type /*num*/ )
-    {
-        internal::aligned_free( p );
-    }
-
-    bool operator!=(const aligned_allocator<T>& ) const
-    { return false; }
-
-    bool operator==(const aligned_allocator<T>& ) const
-    { return true; }
+  typedef std::size_t     size_type;
+  typedef std::ptrdiff_t  difference_type;
+  typedef T*              pointer;
+  typedef const T*        const_pointer;
+  typedef T&              reference;
+  typedef const T&        const_reference;
+  typedef T               value_type;
+
+  template<class U>
+  struct rebind
+  {
+    typedef aligned_allocator<U> other;
+  };
+
+  aligned_allocator() : std::allocator<T>() {}
+
+  aligned_allocator(const aligned_allocator& other) : std::allocator<T>(other) {}
+
+  template<class U>
+  aligned_allocator(const aligned_allocator<U>& other) : std::allocator<T>(other) {}
+
+  ~aligned_allocator() {}
+
+  pointer allocate(size_type num, const void* /*hint*/ = 0)
+  {
+    internal::check_size_for_overflow<T>(num);
+    return static_cast<pointer>( internal::aligned_malloc(num * sizeof(T)) );
+  }
+
+  void deallocate(pointer p, size_type /*num*/)
+  {
+    internal::aligned_free(p);
+  }
 };
 
 //---------- Cache sizes ----------
 
 #if !defined(EIGEN_NO_CPUID)
-#  if defined(__GNUC__) && ( defined(__i386__) || defined(__x86_64__) )
-#    if defined(__PIC__) && defined(__i386__)
+#  if EIGEN_COMP_GNUC && EIGEN_ARCH_i386_OR_x86_64
+#    if defined(__PIC__) && EIGEN_ARCH_i386
        // Case for x86 with PIC
 #      define EIGEN_CPUID(abcd,func,id) \
          __asm__ __volatile__ ("xchgl %%ebx, %k1;cpuid; xchgl %%ebx,%k1": "=a" (abcd[0]), "=&r" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id));
-#    elif defined(__PIC__) && defined(__x86_64__)
+#    elif defined(__PIC__) && EIGEN_ARCH_x86_64
        // Case for x64 with PIC. In theory this is only a problem with recent gcc and with medium or large code model, not with the default small code model.
        // However, we cannot detect which code model is used, and the xchg overhead is negligible anyway.
 #      define EIGEN_CPUID(abcd,func,id) \
         __asm__ __volatile__ ("xchg{q}\t{%%}rbx, %q1; cpuid; xchg{q}\t{%%}rbx, %q1": "=a" (abcd[0]), "=&r" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "0" (func), "2" (id));
 #    else
        // Case for x86_64 or x86 w/o PIC
 #      define EIGEN_CPUID(abcd,func,id) \
          __asm__ __volatile__ ("cpuid": "=a" (abcd[0]), "=b" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "0" (func), "2" (id) );
 #    endif
-#  elif defined(_MSC_VER)
-#    if (_MSC_VER > 1500) && ( defined(_M_IX86) || defined(_M_X64) )
+#  elif EIGEN_COMP_MSVC
+#    if (EIGEN_COMP_MSVC > 1500) && EIGEN_ARCH_i386_OR_x86_64
 #      define EIGEN_CPUID(abcd,func,id) __cpuidex((int*)abcd,func,id)
 #    endif
 #  endif
 #endif
 

Index: 3rd_party/eigen/Eigen/src/Core/util/Meta.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/Meta.h
+++ 3rd_party/eigen/Eigen/src/Core/util/Meta.h
@@ -1,28 +1,57 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_META_H
 #define EIGEN_META_H
+
+#if defined(__CUDA_ARCH__)
+#include <cfloat>
+#include <math_constants.h>
+#endif
+
+#if EIGEN_COMP_ICC>=1600 &&  __cplusplus >= 201103L
+#include <cstdint>
+#endif
 
 namespace Eigen {
+
+typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE DenseIndex;
+
+/**
+ * \brief The Index type as used for the API.
+ * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
+ * \sa \blank \ref TopicPreprocessorDirectives, StorageIndex.
+ */
+
+typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE Index;
 
 namespace internal {
 
 /** \internal
   * \file Meta.h
   * This file contains generic metaprogramming classes which are not specifically related to Eigen.
   * \note In case you wonder, yes we're aware that Boost already provides all these features,
   * we however don't want to add a dependency to Boost.
   */
+
+// Only recent versions of ICC complain about using ptrdiff_t to hold pointers,
+// and older versions do not provide *intptr_t types.
+#if EIGEN_COMP_ICC>=1600 &&  __cplusplus >= 201103L
+typedef std::intptr_t  IntPtr;
+typedef std::uintptr_t UIntPtr;
+#else
+typedef std::ptrdiff_t IntPtr;
+typedef std::size_t UIntPtr;
+#endif
 
 struct true_type {  enum { value = 1 }; };
 struct false_type { enum { value = 0 }; };
 
 template<bool Condition, typename Then, typename Else>
@@ -66,10 +95,22 @@
 template<> struct is_arithmetic<signed int>    { enum { value = true }; };
 template<> struct is_arithmetic<unsigned int>  { enum { value = true }; };
 template<> struct is_arithmetic<signed long>   { enum { value = true }; };
 template<> struct is_arithmetic<unsigned long> { enum { value = true }; };
 
+template<typename T> struct is_integral        { enum { value = false }; };
+template<> struct is_integral<bool>            { enum { value = true }; };
+template<> struct is_integral<char>            { enum { value = true }; };
+template<> struct is_integral<signed char>     { enum { value = true }; };
+template<> struct is_integral<unsigned char>   { enum { value = true }; };
+template<> struct is_integral<signed short>    { enum { value = true }; };
+template<> struct is_integral<unsigned short>  { enum { value = true }; };
+template<> struct is_integral<signed int>      { enum { value = true }; };
+template<> struct is_integral<unsigned int>    { enum { value = true }; };
+template<> struct is_integral<signed long>     { enum { value = true }; };
+template<> struct is_integral<unsigned long>   { enum { value = true }; };
+
 template <typename T> struct add_const { typedef const T type; };
 template <typename T> struct add_const<T&> { typedef T& type; };
 
 template <typename T> struct is_const { enum { value = 0 }; };
 template <typename T> struct is_const<T const> { enum { value = 1 }; };
@@ -78,48 +119,188 @@
 template<typename T> struct add_const_on_value_type<T&>        { typedef T const& type; };
 template<typename T> struct add_const_on_value_type<T*>        { typedef T const* type; };
 template<typename T> struct add_const_on_value_type<T* const>  { typedef T const* const type; };
 template<typename T> struct add_const_on_value_type<T const* const>  { typedef T const* const type; };
 
+
+template<typename From, typename To>
+struct is_convertible_impl
+{
+private:
+  struct any_conversion
+  {
+    template <typename T> any_conversion(const volatile T&);
+    template <typename T> any_conversion(T&);
+  };
+  struct yes {int a[1];};
+  struct no  {int a[2];};
+
+  static yes test(const To&, int);
+  static no  test(any_conversion, ...);
+
+public:
+  static From ms_from;
+#ifdef __INTEL_COMPILER
+  #pragma warning push
+  #pragma warning ( disable : 2259 )
+#endif
+  enum { value = sizeof(test(ms_from, 0))==sizeof(yes) };
+#ifdef __INTEL_COMPILER
+  #pragma warning pop
+#endif
+};
+
+template<typename From, typename To>
+struct is_convertible
+{
+  enum { value = is_convertible_impl<typename remove_all<From>::type,
+                                     typename remove_all<To  >::type>::value };
+};
+
 /** \internal Allows to enable/disable an overload
   * according to a compile time condition.
   */
-template<bool Condition, typename T> struct enable_if;
+template<bool Condition, typename T=void> struct enable_if;
 
 template<typename T> struct enable_if<true,T>
 { typedef T type; };
 
+#if defined(__CUDA_ARCH__)
+#if !defined(__FLT_EPSILON__)
+#define __FLT_EPSILON__ FLT_EPSILON
+#define __DBL_EPSILON__ DBL_EPSILON
+#endif
+
+namespace device {
+
+template<typename T> struct numeric_limits
+{
+  EIGEN_DEVICE_FUNC
+  static T epsilon() { return 0; }
+  static T (max)() { assert(false && "Highest not supported for this type"); }
+  static T (min)() { assert(false && "Lowest not supported for this type"); }
+  static T infinity() { assert(false && "Infinity not supported for this type"); }
+  static T quiet_NaN() { assert(false && "quiet_NaN not supported for this type"); }
+};
+template<> struct numeric_limits<float>
+{
+  EIGEN_DEVICE_FUNC
+  static float epsilon() { return __FLT_EPSILON__; }
+  EIGEN_DEVICE_FUNC
+  static float (max)() { return CUDART_MAX_NORMAL_F; }
+  EIGEN_DEVICE_FUNC
+  static float (min)() { return FLT_MIN; }
+  EIGEN_DEVICE_FUNC
+  static float infinity() { return CUDART_INF_F; }
+  EIGEN_DEVICE_FUNC
+  static float quiet_NaN() { return CUDART_NAN_F; }
+};
+template<> struct numeric_limits<double>
+{
+  EIGEN_DEVICE_FUNC
+  static double epsilon() { return __DBL_EPSILON__; }
+  EIGEN_DEVICE_FUNC
+  static double (max)() { return DBL_MAX; }
+  EIGEN_DEVICE_FUNC
+  static double (min)() { return DBL_MIN; }
+  EIGEN_DEVICE_FUNC
+  static double infinity() { return CUDART_INF; }
+  EIGEN_DEVICE_FUNC
+  static double quiet_NaN() { return CUDART_NAN; }
+};
+template<> struct numeric_limits<int>
+{
+  EIGEN_DEVICE_FUNC
+  static int epsilon() { return 0; }
+  EIGEN_DEVICE_FUNC
+  static int (max)() { return INT_MAX; }
+  EIGEN_DEVICE_FUNC
+  static int (min)() { return INT_MIN; }
+};
+template<> struct numeric_limits<unsigned int>
+{
+  EIGEN_DEVICE_FUNC
+  static unsigned int epsilon() { return 0; }
+  EIGEN_DEVICE_FUNC
+  static unsigned int (max)() { return UINT_MAX; }
+  EIGEN_DEVICE_FUNC
+  static unsigned int (min)() { return 0; }
+};
+template<> struct numeric_limits<long>
+{
+  EIGEN_DEVICE_FUNC
+  static long epsilon() { return 0; }
+  EIGEN_DEVICE_FUNC
+  static long (max)() { return LONG_MAX; }
+  EIGEN_DEVICE_FUNC
+  static long (min)() { return LONG_MIN; }
+};
+template<> struct numeric_limits<unsigned long>
+{
+  EIGEN_DEVICE_FUNC
+  static unsigned long epsilon() { return 0; }
+  EIGEN_DEVICE_FUNC
+  static unsigned long (max)() { return ULONG_MAX; }
+  EIGEN_DEVICE_FUNC
+  static unsigned long (min)() { return 0; }
+};
+template<> struct numeric_limits<long long>
+{
+  EIGEN_DEVICE_FUNC
+  static long long epsilon() { return 0; }
+  EIGEN_DEVICE_FUNC
+  static long long (max)() { return LLONG_MAX; }
+  EIGEN_DEVICE_FUNC
+  static long long (min)() { return LLONG_MIN; }
+};
+template<> struct numeric_limits<unsigned long long>
+{
+  EIGEN_DEVICE_FUNC
+  static unsigned long long epsilon() { return 0; }
+  EIGEN_DEVICE_FUNC
+  static unsigned long long (max)() { return ULLONG_MAX; }
+  EIGEN_DEVICE_FUNC
+  static unsigned long long (min)() { return 0; }
+};
+
+}
 
+#endif
 
 /** \internal
   * A base class do disable default copy ctor and copy assignement operator.
   */
 class noncopyable
 {
-  noncopyable(const noncopyable&);
-  const noncopyable& operator=(const noncopyable&);
+  EIGEN_DEVICE_FUNC noncopyable(const noncopyable&);
+  EIGEN_DEVICE_FUNC const noncopyable& operator=(const noncopyable&);
 protected:
-  noncopyable() {}
-  ~noncopyable() {}
+  EIGEN_DEVICE_FUNC noncopyable() {}
+  EIGEN_DEVICE_FUNC ~noncopyable() {}
 };
-
 
 /** \internal
   * Convenient struct to get the result type of a unary or binary functor.
   *
   * It supports both the current STL mechanism (using the result_type member) as well as
   * upcoming next STL generation (using a templated result member).
   * If none of these members is provided, then the type of the first argument is returned. FIXME, that behavior is a pretty bad hack.
   */
-template<typename T> struct result_of {};
+#if EIGEN_HAS_STD_RESULT_OF
+template<typename T> struct result_of {
+  typedef typename std::result_of<T>::type type1;
+  typedef typename remove_all<type1>::type type;
+};
+#else
+template<typename T> struct result_of { };
 
 struct has_none {int a[1];};
 struct has_std_result_type {int a[2];};
 struct has_tr1_result {int a[3];};
 
 template<typename Func, typename ArgType, int SizeOf=sizeof(has_none)>
-struct unary_result_of_select {typedef ArgType type;};
+struct unary_result_of_select {typedef typename internal::remove_all<ArgType>::type type;};
 
 template<typename Func, typename ArgType>
 struct unary_result_of_select<Func, ArgType, sizeof(has_std_result_type)> {typedef typename Func::result_type type;};
 
 template<typename Func, typename ArgType>
@@ -126,22 +307,22 @@
 struct unary_result_of_select<Func, ArgType, sizeof(has_tr1_result)> {typedef typename Func::template result<Func(ArgType)>::type type;};
 
 template<typename Func, typename ArgType>
 struct result_of<Func(ArgType)> {
     template<typename T>
-    static has_std_result_type testFunctor(T const *, typename T::result_type const * = 0);
+    static has_std_result_type    testFunctor(T const *, typename T::result_type const * = 0);
     template<typename T>
-    static has_tr1_result      testFunctor(T const *, typename T::template result<T(ArgType)>::type const * = 0);
-    static has_none            testFunctor(...);
+    static has_tr1_result         testFunctor(T const *, typename T::template result<T(ArgType)>::type const * = 0);
+    static has_none               testFunctor(...);
 
     // note that the following indirection is needed for gcc-3.3
     enum {FunctorType = sizeof(testFunctor(static_cast<Func*>(0)))};
     typedef typename unary_result_of_select<Func, ArgType, FunctorType>::type type;
 };
 
 template<typename Func, typename ArgType0, typename ArgType1, int SizeOf=sizeof(has_none)>
-struct binary_result_of_select {typedef ArgType0 type;};
+struct binary_result_of_select {typedef typename internal::remove_all<ArgType0>::type type;};
 
 template<typename Func, typename ArgType0, typename ArgType1>
 struct binary_result_of_select<Func, ArgType0, ArgType1, sizeof(has_std_result_type)>
 {typedef typename Func::result_type type;};
 
@@ -150,19 +331,86 @@
 {typedef typename Func::template result<Func(ArgType0,ArgType1)>::type type;};
 
 template<typename Func, typename ArgType0, typename ArgType1>
 struct result_of<Func(ArgType0,ArgType1)> {
     template<typename T>
-    static has_std_result_type testFunctor(T const *, typename T::result_type const * = 0);
+    static has_std_result_type    testFunctor(T const *, typename T::result_type const * = 0);
     template<typename T>
-    static has_tr1_result      testFunctor(T const *, typename T::template result<T(ArgType0,ArgType1)>::type const * = 0);
-    static has_none            testFunctor(...);
+    static has_tr1_result         testFunctor(T const *, typename T::template result<T(ArgType0,ArgType1)>::type const * = 0);
+    static has_none               testFunctor(...);
 
     // note that the following indirection is needed for gcc-3.3
     enum {FunctorType = sizeof(testFunctor(static_cast<Func*>(0)))};
     typedef typename binary_result_of_select<Func, ArgType0, ArgType1, FunctorType>::type type;
 };
+
+template<typename Func, typename ArgType0, typename ArgType1, typename ArgType2, int SizeOf=sizeof(has_none)>
+struct ternary_result_of_select {typedef typename internal::remove_all<ArgType0>::type type;};
+
+template<typename Func, typename ArgType0, typename ArgType1, typename ArgType2>
+struct ternary_result_of_select<Func, ArgType0, ArgType1, ArgType2, sizeof(has_std_result_type)>
+{typedef typename Func::result_type type;};
+
+template<typename Func, typename ArgType0, typename ArgType1, typename ArgType2>
+struct ternary_result_of_select<Func, ArgType0, ArgType1, ArgType2, sizeof(has_tr1_result)>
+{typedef typename Func::template result<Func(ArgType0,ArgType1,ArgType2)>::type type;};
+
+template<typename Func, typename ArgType0, typename ArgType1, typename ArgType2>
+struct result_of<Func(ArgType0,ArgType1,ArgType2)> {
+    template<typename T>
+    static has_std_result_type    testFunctor(T const *, typename T::result_type const * = 0);
+    template<typename T>
+    static has_tr1_result         testFunctor(T const *, typename T::template result<T(ArgType0,ArgType1,ArgType2)>::type const * = 0);
+    static has_none               testFunctor(...);
+
+    // note that the following indirection is needed for gcc-3.3
+    enum {FunctorType = sizeof(testFunctor(static_cast<Func*>(0)))};
+    typedef typename ternary_result_of_select<Func, ArgType0, ArgType1, ArgType2, FunctorType>::type type;
+};
+#endif
+
+struct meta_yes { char a[1]; };
+struct meta_no  { char a[2]; };
+
+// Check whether T::ReturnType does exist
+template <typename T>
+struct has_ReturnType
+{
+  template <typename C> static meta_yes testFunctor(typename C::ReturnType const *);
+  template <typename C> static meta_no testFunctor(...);
+
+  enum { value = sizeof(testFunctor<T>(0)) == sizeof(meta_yes) };
+};
+
+template<typename T> const T* return_ptr();
+
+template <typename T, typename IndexType=Index>
+struct has_nullary_operator
+{
+  template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ptr<C>()->operator()())>0)>::type * = 0);
+  static meta_no testFunctor(...);
+
+  enum { value = sizeof(testFunctor(static_cast<T*>(0))) == sizeof(meta_yes) };
+};
+
+template <typename T, typename IndexType=Index>
+struct has_unary_operator
+{
+  template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ptr<C>()->operator()(IndexType(0)))>0)>::type * = 0);
+  static meta_no testFunctor(...);
+
+  enum { value = sizeof(testFunctor(static_cast<T*>(0))) == sizeof(meta_yes) };
+};
+
+template <typename T, typename IndexType=Index>
+struct has_binary_operator
+{
+  template <typename C> static meta_yes testFunctor(C const *,typename enable_if<(sizeof(return_ptr<C>()->operator()(IndexType(0),IndexType(0)))>0)>::type * = 0);
+  static meta_no testFunctor(...);
+
+  enum { value = sizeof(testFunctor(static_cast<T*>(0))) == sizeof(meta_yes) };
+};
 
 /** \internal In short, it computes int(sqrt(\a Y)) with \a Y an integer.
   * Usage example: \code meta_sqrt<1023>::ret \endcode
   */
 template<int Y,
@@ -183,61 +431,62 @@
 };
 
 template<int Y, int InfX, int SupX>
 class meta_sqrt<Y, InfX, SupX, true> { public:  enum { ret = (SupX*SupX <= Y) ? SupX : InfX }; };
 
+
+/** \internal Computes the least common multiple of two positive integer A and B
+  * at compile-time. It implements a naive algorithm testing all multiples of A.
+  * It thus works better if A>=B.
+  */
+template<int A, int B, int K=1, bool Done = ((A*K)%B)==0>
+struct meta_least_common_multiple
+{
+  enum { ret = meta_least_common_multiple<A,B,K+1>::ret };
+};
+template<int A, int B, int K>
+struct meta_least_common_multiple<A,B,K,true>
+{
+  enum { ret = A*K };
+};
+
 /** \internal determines whether the product of two numeric types is allowed and what the return type is */
 template<typename T, typename U> struct scalar_product_traits
 {
   enum { Defined = 0 };
 };
 
-template<typename T> struct scalar_product_traits<T,T>
-{
-  enum {
-    // Cost = NumTraits<T>::MulCost,
-    Defined = 1
-  };
-  typedef T ReturnType;
-};
-
-template<typename T> struct scalar_product_traits<T,std::complex<T> >
-{
-  enum {
-    // Cost = 2*NumTraits<T>::MulCost,
-    Defined = 1
-  };
-  typedef std::complex<T> ReturnType;
-};
-
-template<typename T> struct scalar_product_traits<std::complex<T>, T>
-{
-  enum {
-    // Cost = 2*NumTraits<T>::MulCost,
-    Defined = 1
-  };
-  typedef std::complex<T> ReturnType;
-};
-
 // FIXME quick workaround around current limitation of result_of
 // template<typename Scalar, typename ArgType0, typename ArgType1>
 // struct result_of<scalar_product_op<Scalar>(ArgType0,ArgType1)> {
 // typedef typename scalar_product_traits<typename remove_all<ArgType0>::type, typename remove_all<ArgType1>::type>::ReturnType type;
 // };
 
-template<typename T> struct is_diagonal
-{ enum { ret = false }; };
-
-template<typename T> struct is_diagonal<DiagonalBase<T> >
-{ enum { ret = true }; };
-
-template<typename T> struct is_diagonal<DiagonalWrapper<T> >
-{ enum { ret = true }; };
-
-template<typename T, int S> struct is_diagonal<DiagonalMatrix<T,S> >
-{ enum { ret = true }; };
-
-} // end namespace internal
+} // end namespace internal
+
+namespace numext {
+  
+#if defined(__CUDA_ARCH__)
+template<typename T> EIGEN_DEVICE_FUNC   void swap(T &a, T &b) { T tmp = b; b = a; a = tmp; }
+#else
+template<typename T> EIGEN_STRONG_INLINE void swap(T &a, T &b) { std::swap(a,b); }
+#endif
+
+#if defined(__CUDA_ARCH__)
+using internal::device::numeric_limits;
+#else
+using std::numeric_limits;
+#endif
+
+// Integer division with rounding up.
+// T is assumed to be an integer type with a>=0, and b>0
+template<typename T>
+T div_ceil(const T &a, const T &b)
+{
+  return (a+b-1) / b;
+}
+
+} // end namespace numext
 
 } // end namespace Eigen
 
 #endif // EIGEN_META_H

Index: 3rd_party/eigen/Eigen/src/Core/util/ReenableStupidWarnings.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/ReenableStupidWarnings.h
+++ 3rd_party/eigen/Eigen/src/Core/util/ReenableStupidWarnings.h
@@ -6,9 +6,22 @@
     #pragma warning( pop )
   #elif defined __INTEL_COMPILER
     #pragma warning pop
   #elif defined __clang__
     #pragma clang diagnostic pop
+  #elif defined __GNUC__ && __GNUC__>=6
+    #pragma GCC diagnostic pop
+  #endif
+
+  #if defined __NVCC__
+//    Don't reenable the diagnostic messages, as it turns out these messages need
+//    to be disabled at the point of the template instantiation (i.e the user code)
+//    otherwise they'll be triggered by nvcc.
+//    #pragma diag_default code_is_unreachable
+//    #pragma diag_default initialization_not_reachable
+//    #pragma diag_default 2651
+//    #pragma diag_default 2653
   #endif
+
 #endif
 
 #endif // EIGEN_WARNINGS_DISABLED

Index: 3rd_party/eigen/Eigen/src/Core/util/StaticAssert.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/StaticAssert.h
+++ 3rd_party/eigen/Eigen/src/Core/util/StaticAssert.h
@@ -24,11 +24,11 @@
  *
  */
 
 #ifndef EIGEN_NO_STATIC_ASSERT
 
-  #if defined(__GXX_EXPERIMENTAL_CXX0X__) || (defined(_MSC_VER) && (_MSC_VER >= 1600))
+  #if EIGEN_MAX_CPP_VER>=11 && (__has_feature(cxx_static_assert) || (defined(__cplusplus) && __cplusplus >= 201103L) || (EIGEN_COMP_MSVC >= 1600))
 
     // if native static_assert is enabled, let's use it
     #define EIGEN_STATIC_ASSERT(X,MSG) static_assert(X,#MSG);
 
   #else // not CXX0X
@@ -48,10 +48,11 @@
         YOU_MIXED_VECTORS_OF_DIFFERENT_SIZES,
         YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES,
         THIS_METHOD_IS_ONLY_FOR_VECTORS_OF_A_SPECIFIC_SIZE,
         THIS_METHOD_IS_ONLY_FOR_MATRICES_OF_A_SPECIFIC_SIZE,
         THIS_METHOD_IS_ONLY_FOR_OBJECTS_OF_A_SPECIFIC_SIZE,
+        OUT_OF_RANGE_ACCESS,
         YOU_MADE_A_PROGRAMMING_MISTAKE,
         EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT,
         EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE,
         YOU_CALLED_A_FIXED_SIZE_METHOD_ON_A_DYNAMIC_SIZE_MATRIX_OR_VECTOR,
         YOU_CALLED_A_DYNAMIC_SIZE_METHOD_ON_A_FIXED_SIZE_MATRIX_OR_VECTOR,
@@ -82,19 +83,27 @@
         YOU_CANNOT_MIX_ARRAYS_AND_MATRICES,
         YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION,
         THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY,
         YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT,
         THIS_METHOD_IS_ONLY_FOR_1x1_EXPRESSIONS,
+        THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS,
         THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL,
         THIS_METHOD_IS_ONLY_FOR_ARRAYS_NOT_MATRICES,
         YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED,
         YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED,
         THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE,
         THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH,
         OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG,
         IMPLICIT_CONVERSION_TO_SCALAR_IS_FOR_INNER_PRODUCT_ONLY,
-        STORAGE_LAYOUT_DOES_NOT_MATCH
+        STORAGE_LAYOUT_DOES_NOT_MATCH,
+        EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT__INVALID_COST_VALUE,
+        THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS,
+        MATRIX_FREE_CONJUGATE_GRADIENT_IS_COMPATIBLE_WITH_UPPER_UNION_LOWER_MODE_ONLY,
+        THIS_TYPE_IS_NOT_SUPPORTED,
+        STORAGE_KIND_MUST_MATCH,
+        STORAGE_INDEX_MUST_MATCH,
+        CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY
       };
     };
 
     } // end namespace internal
 
@@ -101,19 +110,19 @@
     } // end namespace Eigen
 
     // Specialized implementation for MSVC to avoid "conditional
     // expression is constant" warnings.  This implementation doesn't
     // appear to work under GCC, hence the multiple implementations.
-    #ifdef _MSC_VER
+    #if EIGEN_COMP_MSVC
 
       #define EIGEN_STATIC_ASSERT(CONDITION,MSG) \
         {Eigen::internal::static_assertion<bool(CONDITION)>::MSG;}
 
     #else
-
+      // In some cases clang interprets bool(CONDITION) as function declaration
       #define EIGEN_STATIC_ASSERT(CONDITION,MSG) \
-        if (Eigen::internal::static_assertion<bool(CONDITION)>::MSG) {}
+        if (Eigen::internal::static_assertion<static_cast<bool>(CONDITION)>::MSG) {}
 
     #endif
 
   #endif // not CXX0X
 
@@ -157,11 +166,11 @@
     || int(TYPE0::SizeAtCompileTime)==int(TYPE1::SizeAtCompileTime)),\
     YOU_MIXED_VECTORS_OF_DIFFERENT_SIZES)
 
 #define EIGEN_PREDICATE_SAME_MATRIX_SIZE(TYPE0,TYPE1) \
      ( \
-        (int(TYPE0::SizeAtCompileTime)==0 && int(TYPE1::SizeAtCompileTime)==0) \
+        (int(Eigen::internal::size_of_xpr_at_compile_time<TYPE0>::ret)==0 && int(Eigen::internal::size_of_xpr_at_compile_time<TYPE1>::ret)==0) \
     || (\
           (int(TYPE0::RowsAtCompileTime)==Eigen::Dynamic \
         || int(TYPE1::RowsAtCompileTime)==Eigen::Dynamic \
         || int(TYPE0::RowsAtCompileTime)==int(TYPE1::RowsAtCompileTime)) \
       &&  (int(TYPE0::ColsAtCompileTime)==Eigen::Dynamic \
@@ -168,17 +177,12 @@
         || int(TYPE1::ColsAtCompileTime)==Eigen::Dynamic \
         || int(TYPE0::ColsAtCompileTime)==int(TYPE1::ColsAtCompileTime))\
        ) \
      )
 
-#ifdef EIGEN2_SUPPORT
-  #define EIGEN_STATIC_ASSERT_NON_INTEGER(TYPE) \
-    eigen_assert(!NumTraits<Scalar>::IsInteger);
-#else
-  #define EIGEN_STATIC_ASSERT_NON_INTEGER(TYPE) \
+#define EIGEN_STATIC_ASSERT_NON_INTEGER(TYPE) \
     EIGEN_STATIC_ASSERT(!NumTraits<TYPE>::IsInteger, THIS_FUNCTION_IS_NOT_FOR_INTEGER_NUMERIC_TYPES)
-#endif
 
 
 // static assertion failing if it is guaranteed at compile-time that the two matrix expression types have different sizes
 #define EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(TYPE0,TYPE1) \
   EIGEN_STATIC_ASSERT( \
@@ -189,20 +193,24 @@
       EIGEN_STATIC_ASSERT((TYPE::RowsAtCompileTime == 1 || TYPE::RowsAtCompileTime == Dynamic) && \
                           (TYPE::ColsAtCompileTime == 1 || TYPE::ColsAtCompileTime == Dynamic), \
                           THIS_METHOD_IS_ONLY_FOR_1x1_EXPRESSIONS)
 
 #define EIGEN_STATIC_ASSERT_LVALUE(Derived) \
-      EIGEN_STATIC_ASSERT(internal::is_lvalue<Derived>::value, \
+      EIGEN_STATIC_ASSERT(Eigen::internal::is_lvalue<Derived>::value, \
                           THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY)
 
 #define EIGEN_STATIC_ASSERT_ARRAYXPR(Derived) \
-      EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Derived>::XprKind, ArrayXpr>::value), \
+      EIGEN_STATIC_ASSERT((Eigen::internal::is_same<typename Eigen::internal::traits<Derived>::XprKind, ArrayXpr>::value), \
                           THIS_METHOD_IS_ONLY_FOR_ARRAYS_NOT_MATRICES)
 
 #define EIGEN_STATIC_ASSERT_SAME_XPR_KIND(Derived1, Derived2) \
-      EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Derived1>::XprKind, \
-                                             typename internal::traits<Derived2>::XprKind \
+      EIGEN_STATIC_ASSERT((Eigen::internal::is_same<typename Eigen::internal::traits<Derived1>::XprKind, \
+                                             typename Eigen::internal::traits<Derived2>::XprKind \
                                             >::value), \
                           YOU_CANNOT_MIX_ARRAYS_AND_MATRICES)
 
+// Check that a cost value is positive, and that is stay within a reasonable range
+// TODO this check could be enabled for internal debugging only
+#define EIGEN_INTERNAL_CHECK_COST_VALUE(C) \
+      EIGEN_STATIC_ASSERT((C)>=0 && (C)<=HugeCost*HugeCost, EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT__INVALID_COST_VALUE);
 
 #endif // EIGEN_STATIC_ASSERT_H

Index: 3rd_party/eigen/Eigen/src/Core/util/XprHelper.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Core/util/XprHelper.h
+++ 3rd_party/eigen/Eigen/src/Core/util/XprHelper.h
@@ -12,24 +12,81 @@
 #define EIGEN_XPRHELPER_H
 
 // just a workaround because GCC seems to not really like empty structs
 // FIXME: gcc 4.3 generates bad code when strict-aliasing is enabled
 // so currently we simply disable this optimization for gcc 4.3
-#if (defined __GNUG__) && !((__GNUC__==4) && (__GNUC_MINOR__==3))
+#if EIGEN_COMP_GNUC && !EIGEN_GNUC_AT(4,3)
   #define EIGEN_EMPTY_STRUCT_CTOR(X) \
-    EIGEN_STRONG_INLINE X() {} \
-    EIGEN_STRONG_INLINE X(const X& ) {}
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE X() {} \
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE X(const X& ) {}
 #else
   #define EIGEN_EMPTY_STRUCT_CTOR(X)
 #endif
 
 namespace Eigen {
 
-typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE DenseIndex;
-
 namespace internal {
 
+template<typename IndexDest, typename IndexSrc>
+EIGEN_DEVICE_FUNC
+inline IndexDest convert_index(const IndexSrc& idx) {
+  // for sizeof(IndexDest)>=sizeof(IndexSrc) compilers should be able to optimize this away:
+  eigen_internal_assert(idx <= NumTraits<IndexDest>::highest() && "Index value to big for target type");
+  return IndexDest(idx);
+}
+
+
+// promote_scalar_arg is an helper used in operation between an expression and a scalar, like:
+//    expression * scalar
+// Its role is to determine how the type T of the scalar operand should be promoted given the scalar type ExprScalar of the given expression.
+// The IsSupported template parameter must be provided by the caller as: internal::has_ReturnType<ScalarBinaryOpTraits<ExprScalar,T,op> >::value using the proper order for ExprScalar and T.
+// Then the logic is as follows:
+//  - if the operation is natively supported as defined by IsSupported, then the scalar type is not promoted, and T is returned.
+//  - otherwise, NumTraits<ExprScalar>::Literal is returned if T is implicitly convertible to NumTraits<ExprScalar>::Literal AND that this does not imply a float to integer conversion.
+//  - otherwise, ExprScalar is returned if T is implicitly convertible to ExprScalar AND that this does not imply a float to integer conversion.
+//  - In all other cases, the promoted type is not defined, and the respective operation is thus invalid and not available (SFINAE).
+template<typename ExprScalar,typename T, bool IsSupported>
+struct promote_scalar_arg;
+
+template<typename S,typename T>
+struct promote_scalar_arg<S,T,true>
+{
+  typedef T type;
+};
+
+// Recursively check safe conversion to PromotedType, and then ExprScalar if they are different.
+template<typename ExprScalar,typename T,typename PromotedType,
+  bool ConvertibleToLiteral = internal::is_convertible<T,PromotedType>::value,
+  bool IsSafe = NumTraits<T>::IsInteger || !NumTraits<PromotedType>::IsInteger>
+struct promote_scalar_arg_unsupported;
+
+// Start recursion with NumTraits<ExprScalar>::Literal
+template<typename S,typename T>
+struct promote_scalar_arg<S,T,false> : promote_scalar_arg_unsupported<S,T,typename NumTraits<S>::Literal> {};
+
+// We found a match!
+template<typename S,typename T, typename PromotedType>
+struct promote_scalar_arg_unsupported<S,T,PromotedType,true,true>
+{
+  typedef PromotedType type;
+};
+
+// No match, but no real-to-integer issues, and ExprScalar and current PromotedType are different,
+// so let's try to promote to ExprScalar
+template<typename ExprScalar,typename T, typename PromotedType>
+struct promote_scalar_arg_unsupported<ExprScalar,T,PromotedType,false,true>
+   : promote_scalar_arg_unsupported<ExprScalar,T,ExprScalar>
+{};
+
+// Unsafe real-to-integer, let's stop.
+template<typename S,typename T, typename PromotedType, bool ConvertibleToLiteral>
+struct promote_scalar_arg_unsupported<S,T,PromotedType,ConvertibleToLiteral,false> {};
+
+// T is not even convertible to ExprScalar, let's stop.
+template<typename S,typename T>
+struct promote_scalar_arg_unsupported<S,T,S,false,true> {};
+
 //classes inheriting no_assignment_operator don't generate a default operator=.
 class no_assignment_operator
 {
   private:
     no_assignment_operator& operator=(const no_assignment_operator&);
@@ -48,44 +105,44 @@
   */
 template<typename T, int Value> class variable_if_dynamic
 {
   public:
     EIGEN_EMPTY_STRUCT_CTOR(variable_if_dynamic)
-    explicit variable_if_dynamic(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); assert(v == T(Value)); }
-    static T value() { return T(Value); }
-    void setValue(T) {}
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamic(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); eigen_assert(v == T(Value)); }
+    EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE T value() { return T(Value); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T) {}
 };
 
 template<typename T> class variable_if_dynamic<T, Dynamic>
 {
     T m_value;
-    variable_if_dynamic() { assert(false); }
+    EIGEN_DEVICE_FUNC variable_if_dynamic() { eigen_assert(false); }
   public:
-    explicit variable_if_dynamic(T value) : m_value(value) {}
-    T value() const { return m_value; }
-    void setValue(T value) { m_value = value; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamic(T value) : m_value(value) {}
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T value() const { return m_value; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T value) { m_value = value; }
 };
 
 /** \internal like variable_if_dynamic but for DynamicIndex
   */
 template<typename T, int Value> class variable_if_dynamicindex
 {
   public:
     EIGEN_EMPTY_STRUCT_CTOR(variable_if_dynamicindex)
-    explicit variable_if_dynamicindex(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); assert(v == T(Value)); }
-    static T value() { return T(Value); }
-    void setValue(T) {}
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamicindex(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); eigen_assert(v == T(Value)); }
+    EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE T value() { return T(Value); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T) {}
 };
 
 template<typename T> class variable_if_dynamicindex<T, DynamicIndex>
 {
     T m_value;
-    variable_if_dynamicindex() { assert(false); }
+    EIGEN_DEVICE_FUNC variable_if_dynamicindex() { eigen_assert(false); }
   public:
-    explicit variable_if_dynamicindex(T value) : m_value(value) {}
-    T value() const { return m_value; }
-    void setValue(T value) { m_value = value; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamicindex(T value) : m_value(value) {}
+    EIGEN_DEVICE_FUNC T EIGEN_STRONG_INLINE value() const { return m_value; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T value) { m_value = value; }
 };
 
 template<typename T> struct functor_traits
 {
   enum
@@ -99,11 +156,77 @@
 template<typename T> struct packet_traits;
 
 template<typename T> struct unpacket_traits
 {
   typedef T type;
-  enum {size=1};
+  typedef T half;
+  enum
+  {
+    size = 1,
+    alignment = 1
+  };
+};
+
+template<int Size, typename PacketType,
+         bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
+struct find_best_packet_helper;
+
+template< int Size, typename PacketType>
+struct find_best_packet_helper<Size,PacketType,true>
+{
+  typedef PacketType type;
+};
+
+template<int Size, typename PacketType>
+struct find_best_packet_helper<Size,PacketType,false>
+{
+  typedef typename find_best_packet_helper<Size,typename unpacket_traits<PacketType>::half>::type type;
+};
+
+template<typename T, int Size>
+struct find_best_packet
+{
+  typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
+};
+
+#if EIGEN_MAX_STATIC_ALIGN_BYTES>0
+template<int ArrayBytes, int AlignmentBytes,
+         bool Match     =  bool((ArrayBytes%AlignmentBytes)==0),
+         bool TryHalf   =  bool(EIGEN_MIN_ALIGN_BYTES<AlignmentBytes) >
+struct compute_default_alignment_helper
+{
+  enum { value = 0 };
+};
+
+template<int ArrayBytes, int AlignmentBytes, bool TryHalf>
+struct compute_default_alignment_helper<ArrayBytes, AlignmentBytes, true, TryHalf> // Match
+{
+  enum { value = AlignmentBytes };
+};
+
+template<int ArrayBytes, int AlignmentBytes>
+struct compute_default_alignment_helper<ArrayBytes, AlignmentBytes, false, true> // Try-half
+{
+  // current packet too large, try with an half-packet
+  enum { value = compute_default_alignment_helper<ArrayBytes, AlignmentBytes/2>::value };
+};
+#else
+// If static alignment is disabled, no need to bother.
+// This also avoids a division by zero in "bool Match =  bool((ArrayBytes%AlignmentBytes)==0)"
+template<int ArrayBytes, int AlignmentBytes>
+struct compute_default_alignment_helper
+{
+  enum { value = 0 };
+};
+#endif
+
+template<typename T, int Size> struct compute_default_alignment {
+  enum { value = compute_default_alignment_helper<Size*sizeof(T),EIGEN_MAX_STATIC_ALIGN_BYTES>::value };
+};
+
+template<typename T> struct compute_default_alignment<T,Dynamic> {
+  enum { value = EIGEN_MAX_ALIGN_BYTES };
 };
 
 template<typename _Scalar, int _Rows, int _Cols,
          int _Options = AutoAlign |
                           ( (_Rows==1 && _Cols!=1) ? RowMajor
@@ -125,74 +248,60 @@
 };
 
 template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
 class compute_matrix_flags
 {
-    enum {
-      row_major_bit = Options&RowMajor ? RowMajorBit : 0,
-      is_dynamic_size_storage = MaxRows==Dynamic || MaxCols==Dynamic,
-
-      aligned_bit =
-      (
-            ((Options&DontAlign)==0)
-        && (
-#if EIGEN_ALIGN_STATICALLY
-             ((!is_dynamic_size_storage) && (((MaxCols*MaxRows*int(sizeof(Scalar))) % 16) == 0))
-#else
-             0
-#endif
-
-          ||
-
-#if EIGEN_ALIGN
-             is_dynamic_size_storage
-#else
-             0
-#endif
-
-          )
-      ) ? AlignedBit : 0,
-      packet_access_bit = packet_traits<Scalar>::Vectorizable && aligned_bit ? PacketAccessBit : 0
-    };
-
+    enum { row_major_bit = Options&RowMajor ? RowMajorBit : 0 };
   public:
-    enum { ret = LinearAccessBit | LvalueBit | DirectAccessBit | NestByRefBit | packet_access_bit | row_major_bit | aligned_bit };
+    // FIXME currently we still have to handle DirectAccessBit at the expression level to handle DenseCoeffsBase<>
+    // and then propagate this information to the evaluator's flags.
+    // However, I (Gael) think that DirectAccessBit should only matter at the evaluation stage.
+    enum { ret = DirectAccessBit | LvalueBit | NestByRefBit | row_major_bit };
 };
 
 template<int _Rows, int _Cols> struct size_at_compile_time
 {
   enum { ret = (_Rows==Dynamic || _Cols==Dynamic) ? Dynamic : _Rows * _Cols };
 };
+
+template<typename XprType> struct size_of_xpr_at_compile_time
+{
+  enum { ret = size_at_compile_time<traits<XprType>::RowsAtCompileTime,traits<XprType>::ColsAtCompileTime>::ret };
+};
 
 /* plain_matrix_type : the difference from eval is that plain_matrix_type is always a plain matrix type,
  * whereas eval is a const reference in the case of a matrix
  */
 
 template<typename T, typename StorageKind = typename traits<T>::StorageKind> struct plain_matrix_type;
-template<typename T, typename BaseClassType> struct plain_matrix_type_dense;
+template<typename T, typename BaseClassType, int Flags> struct plain_matrix_type_dense;
 template<typename T> struct plain_matrix_type<T,Dense>
 {
-  typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind>::type type;
+  typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, traits<T>::Flags>::type type;
+};
+template<typename T> struct plain_matrix_type<T,DiagonalShape>
+{
+  typedef typename T::PlainObject type;
 };
 
-template<typename T> struct plain_matrix_type_dense<T,MatrixXpr>
+template<typename T, int Flags> struct plain_matrix_type_dense<T,MatrixXpr,Flags>
 {
   typedef Matrix<typename traits<T>::Scalar,
                 traits<T>::RowsAtCompileTime,
                 traits<T>::ColsAtCompileTime,
-                AutoAlign | (traits<T>::Flags&RowMajorBit ? RowMajor : ColMajor),
+                AutoAlign | (Flags&RowMajorBit ? RowMajor : ColMajor),
                 traits<T>::MaxRowsAtCompileTime,
                 traits<T>::MaxColsAtCompileTime
           > type;
 };
 
-template<typename T> struct plain_matrix_type_dense<T,ArrayXpr>
+template<typename T, int Flags> struct plain_matrix_type_dense<T,ArrayXpr,Flags>
 {
   typedef Array<typename traits<T>::Scalar,
                 traits<T>::RowsAtCompileTime,
                 traits<T>::ColsAtCompileTime,
-                AutoAlign | (traits<T>::Flags&RowMajorBit ? RowMajor : ColMajor),
+                AutoAlign | (Flags&RowMajorBit ? RowMajor : ColMajor),
                 traits<T>::MaxRowsAtCompileTime,
                 traits<T>::MaxColsAtCompileTime
           > type;
 };
 
@@ -212,10 +321,15 @@
 //                 AutoAlign | (traits<T>::Flags&RowMajorBit ? RowMajor : ColMajor),
 //                 traits<T>::MaxRowsAtCompileTime,
 //                 traits<T>::MaxColsAtCompileTime
 //           > type;
 };
+
+template<typename T> struct eval<T,DiagonalShape>
+{
+  typedef typename plain_matrix_type<T>::type type;
+};
 
 // for matrices, no need to evaluate, just use a const reference to avoid a useless copy
 template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
 struct eval<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>, Dense>
 {
@@ -226,10 +340,19 @@
 struct eval<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>, Dense>
 {
   typedef const Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& type;
 };
 
+
+/* similar to plain_matrix_type, but using the evaluator's Flags */
+template<typename T, typename StorageKind = typename traits<T>::StorageKind> struct plain_object_eval;
+
+template<typename T>
+struct plain_object_eval<T,Dense>
+{
+  typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
+};
 
 
 /* plain_matrix_type_column_major : same as plain_matrix_type but guaranteed to be column-major
  */
 template<typename T> struct plain_matrix_type_column_major
@@ -264,13 +387,10 @@
                 MaxRows,
                 MaxCols
           > type;
 };
 
-// we should be able to get rid of this one too
-template<typename T> struct must_nest_by_value { enum { ret = false }; };
-
 /** \internal The reference selector for template expressions. The idea is that we don't
   * need to use references for expressions since they are light weight proxy
   * objects which should generate no copying overhead. */
 template <typename T>
 struct ref_selector
@@ -278,10 +398,16 @@
   typedef typename conditional<
     bool(traits<T>::Flags & NestByRefBit),
     T const&,
     const T
   >::type type;
+  
+  typedef typename conditional<
+    bool(traits<T>::Flags & NestByRefBit),
+    T &,
+    T
+  >::type non_const_type;
 };
 
 /** \internal Adds the const qualifier on the value-type of T2 if and only if T1 is a const type */
 template<typename T1, typename T2>
 struct transfer_constness
@@ -291,58 +417,45 @@
     typename internal::add_const_on_value_type<T2>::type,
     T2
   >::type type;
 };
 
-/** \internal Determines how a given expression should be nested into another one.
+
+// However, we still need a mechanism to detect whether an expression which is evaluated multiple time
+// has to be evaluated into a temporary.
+// That's the purpose of this new nested_eval helper:
+/** \internal Determines how a given expression should be nested when evaluated multiple times.
   * For example, when you do a * (b+c), Eigen will determine how the expression b+c should be
-  * nested into the bigger product expression. The choice is between nesting the expression b+c as-is, or
+  * evaluated into the bigger product expression. The choice is between nesting the expression b+c as-is, or
   * evaluating that expression b+c into a temporary variable d, and nest d so that the resulting expression is
   * a*d. Evaluating can be beneficial for example if every coefficient access in the resulting expression causes
   * many coefficient accesses in the nested expressions -- as is the case with matrix product for example.
   *
-  * \param T the type of the expression being nested
-  * \param n the number of coefficient accesses in the nested expression for each coefficient access in the bigger expression.
-  *
-  * Note that if no evaluation occur, then the constness of T is preserved.
-  *
-  * Example. Suppose that a, b, and c are of type Matrix3d. The user forms the expression a*(b+c).
-  * b+c is an expression "sum of matrices", which we will denote by S. In order to determine how to nest it,
-  * the Product expression uses: nested<S, 3>::ret, which turns out to be Matrix3d because the internal logic of
-  * nested determined that in this case it was better to evaluate the expression b+c into a temporary. On the other hand,
-  * since a is of type Matrix3d, the Product expression nests it as nested<Matrix3d, 3>::ret, which turns out to be
-  * const Matrix3d&, because the internal logic of nested determined that since a was already a matrix, there was no point
-  * in copying it into another matrix.
+  * \tparam T the type of the expression being nested.
+  * \tparam n the number of coefficient accesses in the nested expression for each coefficient access in the bigger expression.
+  * \tparam PlainObject the type of the temporary if needed.
   */
-template<typename T, int n=1, typename PlainObject = typename eval<T>::type> struct nested
+template<typename T, int n, typename PlainObject = typename plain_object_eval<T>::type> struct nested_eval
 {
   enum {
-    // for the purpose of this test, to keep it reasonably simple, we arbitrarily choose a value of Dynamic values.
-    // the choice of 10000 makes it larger than any practical fixed value and even most dynamic values.
-    // in extreme cases where these assumptions would be wrong, we would still at worst suffer performance issues
-    // (poor choice of temporaries).
-    // it's important that this value can still be squared without integer overflowing.
-    DynamicAsInteger = 10000,
     ScalarReadCost = NumTraits<typename traits<T>::Scalar>::ReadCost,
-    ScalarReadCostAsInteger = ScalarReadCost == Dynamic ? int(DynamicAsInteger) : int(ScalarReadCost),
-    CoeffReadCost = traits<T>::CoeffReadCost,
-    CoeffReadCostAsInteger = CoeffReadCost == Dynamic ? int(DynamicAsInteger) : int(CoeffReadCost),
-    NAsInteger = n == Dynamic ? int(DynamicAsInteger) : n,
-    CostEvalAsInteger   = (NAsInteger+1) * ScalarReadCostAsInteger + CoeffReadCostAsInteger,
-    CostNoEvalAsInteger = NAsInteger * CoeffReadCostAsInteger
+    CoeffReadCost = evaluator<T>::CoeffReadCost,  // NOTE What if an evaluator evaluate itself into a tempory?
+                                                  //      Then CoeffReadCost will be small (e.g., 1) but we still have to evaluate, especially if n>1.
+                                                  //      This situation is already taken care by the EvalBeforeNestingBit flag, which is turned ON
+                                                  //      for all evaluator creating a temporary. This flag is then propagated by the parent evaluators.
+                                                  //      Another solution could be to count the number of temps?
+    NAsInteger = n == Dynamic ? HugeCost : n,
+    CostEval   = (NAsInteger+1) * ScalarReadCost + CoeffReadCost,
+    CostNoEval = NAsInteger * CoeffReadCost,
+    Evaluate = (int(evaluator<T>::Flags) & EvalBeforeNestingBit) || (int(CostEval) < int(CostNoEval))
   };
 
-  typedef typename conditional<
-      ( (int(traits<T>::Flags) & EvalBeforeNestingBit) ||
-        int(CostEvalAsInteger) < int(CostNoEvalAsInteger)
-      ),
-      PlainObject,
-      typename ref_selector<T>::type
-  >::type type;
+  typedef typename conditional<Evaluate, PlainObject, typename ref_selector<T>::type>::type type;
 };
 
 template<typename T>
+EIGEN_DEVICE_FUNC
 inline T* const_cast_ptr(const T* ptr)
 {
   return const_cast<T*>(ptr);
 }
 
@@ -362,34 +475,17 @@
 struct dense_xpr_base<Derived, ArrayXpr>
 {
   typedef ArrayBase<Derived> type;
 };
 
-/** \internal Helper base class to add a scalar multiple operator
-  * overloads for complex types */
-template<typename Derived,typename Scalar,typename OtherScalar,
-         bool EnableIt = !is_same<Scalar,OtherScalar>::value >
-struct special_scalar_op_base : public DenseCoeffsBase<Derived>
-{
-  // dummy operator* so that the
-  // "using special_scalar_op_base::operator*" compiles
-  void operator*() const;
-};
-
-template<typename Derived,typename Scalar,typename OtherScalar>
-struct special_scalar_op_base<Derived,Scalar,OtherScalar,true>  : public DenseCoeffsBase<Derived>
-{
-  const CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, Derived>
-  operator*(const OtherScalar& scalar) const
-  {
-    return CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, Derived>
-      (*static_cast<const Derived*>(this), scalar_multiple2_op<Scalar,OtherScalar>(scalar));
-  }
-
-  inline friend const CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, Derived>
-  operator*(const OtherScalar& scalar, const Derived& matrix)
-  { return static_cast<const special_scalar_op_base&>(matrix).operator*(scalar); }
+template<typename Derived, typename XprKind = typename traits<Derived>::XprKind, typename StorageKind = typename traits<Derived>::StorageKind>
+struct generic_xpr_base;
+
+template<typename Derived, typename XprKind>
+struct generic_xpr_base<Derived, XprKind, Dense>
+{
+  typedef typename dense_xpr_base<Derived,XprKind>::type type;
 };
 
 template<typename XprType, typename CastType> struct cast_return_type
 {
   typedef typename XprType::Scalar CurrentScalarType;
@@ -403,13 +499,83 @@
 
 template <typename A> struct promote_storage_type<A,A>
 {
   typedef A ret;
 };
+template <typename A> struct promote_storage_type<A, const A>
+{
+  typedef A ret;
+};
+template <typename A> struct promote_storage_type<const A, A>
+{
+  typedef A ret;
+};
+
+/** \internal Specify the "storage kind" of applying a coefficient-wise
+  * binary operations between two expressions of kinds A and B respectively.
+  * The template parameter Functor permits to specialize the resulting storage kind wrt to
+  * the functor.
+  * The default rules are as follows:
+  * \code
+  * A      op A      -> A
+  * A      op dense  -> dense
+  * dense  op B      -> dense
+  * sparse op dense  -> sparse
+  * dense  op sparse -> sparse
+  * \endcode
+  */
+template <typename A, typename B, typename Functor> struct cwise_promote_storage_type;
+
+template <typename A, typename Functor>                   struct cwise_promote_storage_type<A,A,Functor>                                      { typedef A      ret; };
+template <typename Functor>                               struct cwise_promote_storage_type<Dense,Dense,Functor>                              { typedef Dense  ret; };
+template <typename A, typename Functor>                   struct cwise_promote_storage_type<A,Dense,Functor>                                  { typedef Dense  ret; };
+template <typename B, typename Functor>                   struct cwise_promote_storage_type<Dense,B,Functor>                                  { typedef Dense  ret; };
+template <typename Functor>                               struct cwise_promote_storage_type<Sparse,Dense,Functor>                             { typedef Sparse ret; };
+template <typename Functor>                               struct cwise_promote_storage_type<Dense,Sparse,Functor>                             { typedef Sparse ret; };
+
+template <typename LhsKind, typename RhsKind, int LhsOrder, int RhsOrder> struct cwise_promote_storage_order {
+  enum { value = LhsOrder };
+};
+
+template <typename LhsKind, int LhsOrder, int RhsOrder>   struct cwise_promote_storage_order<LhsKind,Sparse,LhsOrder,RhsOrder>                { enum { value = RhsOrder }; };
+template <typename RhsKind, int LhsOrder, int RhsOrder>   struct cwise_promote_storage_order<Sparse,RhsKind,LhsOrder,RhsOrder>                { enum { value = LhsOrder }; };
+template <int Order>                                      struct cwise_promote_storage_order<Sparse,Sparse,Order,Order>                       { enum { value = Order }; };
+
+
+/** \internal Specify the "storage kind" of multiplying an expression of kind A with kind B.
+  * The template parameter ProductTag permits to specialize the resulting storage kind wrt to
+  * some compile-time properties of the product: GemmProduct, GemvProduct, OuterProduct, InnerProduct.
+  * The default rules are as follows:
+  * \code
+  *  K * K            -> K
+  *  dense * K        -> dense
+  *  K * dense        -> dense
+  *  diag * K         -> K
+  *  K * diag         -> K
+  *  Perm * K         -> K
+  * K * Perm          -> K
+  * \endcode
+  */
+template <typename A, typename B, int ProductTag> struct product_promote_storage_type;
+
+template <typename A, int ProductTag> struct product_promote_storage_type<A,                  A,                  ProductTag> { typedef A     ret;};
+template <int ProductTag>             struct product_promote_storage_type<Dense,              Dense,              ProductTag> { typedef Dense ret;};
+template <typename A, int ProductTag> struct product_promote_storage_type<A,                  Dense,              ProductTag> { typedef Dense ret; };
+template <typename B, int ProductTag> struct product_promote_storage_type<Dense,              B,                  ProductTag> { typedef Dense ret; };
+
+template <typename A, int ProductTag> struct product_promote_storage_type<A,                  DiagonalShape,      ProductTag> { typedef A ret; };
+template <typename B, int ProductTag> struct product_promote_storage_type<DiagonalShape,      B,                  ProductTag> { typedef B ret; };
+template <int ProductTag>             struct product_promote_storage_type<Dense,              DiagonalShape,      ProductTag> { typedef Dense ret; };
+template <int ProductTag>             struct product_promote_storage_type<DiagonalShape,      Dense,              ProductTag> { typedef Dense ret; };
+
+template <typename A, int ProductTag> struct product_promote_storage_type<A,                  PermutationStorage, ProductTag> { typedef A ret; };
+template <typename B, int ProductTag> struct product_promote_storage_type<PermutationStorage, B,                  ProductTag> { typedef B ret; };
+template <int ProductTag>             struct product_promote_storage_type<Dense,              PermutationStorage, ProductTag> { typedef Dense ret; };
+template <int ProductTag>             struct product_promote_storage_type<PermutationStorage, Dense,              ProductTag> { typedef Dense ret; };
 
 /** \internal gives the plain matrix or array type to store a row/column/diagonal of a matrix type.
-  * \param Scalar optional parameter allowing to pass a different scalar type than the one of the MatrixType.
+  * \tparam Scalar optional parameter allowing to pass a different scalar type than the one of the MatrixType.
   */
 template<typename ExpressionType, typename Scalar = typename ExpressionType::Scalar>
 struct plain_row_type
 {
   typedef Matrix<Scalar, 1, ExpressionType::ColsAtCompileTime,
@@ -452,18 +618,204 @@
     is_same< typename traits<ExpressionType>::XprKind, MatrixXpr >::value,
     MatrixDiagType,
     ArrayDiagType 
   >::type type;
 };
+
+template<typename Expr,typename Scalar = typename Expr::Scalar>
+struct plain_constant_type
+{
+  enum { Options = (traits<Expr>::Flags&RowMajorBit)?RowMajor:0 };
+
+  typedef Array<Scalar,  traits<Expr>::RowsAtCompileTime,   traits<Expr>::ColsAtCompileTime,
+                Options, traits<Expr>::MaxRowsAtCompileTime,traits<Expr>::MaxColsAtCompileTime> array_type;
+
+  typedef Matrix<Scalar,  traits<Expr>::RowsAtCompileTime,   traits<Expr>::ColsAtCompileTime,
+                 Options, traits<Expr>::MaxRowsAtCompileTime,traits<Expr>::MaxColsAtCompileTime> matrix_type;
+
+  typedef CwiseNullaryOp<scalar_constant_op<Scalar>, const typename conditional<is_same< typename traits<Expr>::XprKind, MatrixXpr >::value, matrix_type, array_type>::type > type;
+};
 
 template<typename ExpressionType>
 struct is_lvalue
 {
-  enum { value = !bool(is_const<ExpressionType>::value) &&
+  enum { value = (!bool(is_const<ExpressionType>::value)) &&
                  bool(traits<ExpressionType>::Flags & LvalueBit) };
 };
+
+template<typename T> struct is_diagonal
+{ enum { ret = false }; };
+
+template<typename T> struct is_diagonal<DiagonalBase<T> >
+{ enum { ret = true }; };
+
+template<typename T> struct is_diagonal<DiagonalWrapper<T> >
+{ enum { ret = true }; };
+
+template<typename T, int S> struct is_diagonal<DiagonalMatrix<T,S> >
+{ enum { ret = true }; };
+
+template<typename S1, typename S2> struct glue_shapes;
+template<> struct glue_shapes<DenseShape,TriangularShape> { typedef TriangularShape type;  };
+
+template<typename T1, typename T2>
+bool is_same_dense(const T1 &mat1, const T2 &mat2, typename enable_if<has_direct_access<T1>::ret&&has_direct_access<T2>::ret, T1>::type * = 0)
+{
+  return (mat1.data()==mat2.data()) && (mat1.innerStride()==mat2.innerStride()) && (mat1.outerStride()==mat2.outerStride());
+}
+
+template<typename T1, typename T2>
+bool is_same_dense(const T1 &, const T2 &, typename enable_if<!(has_direct_access<T1>::ret&&has_direct_access<T2>::ret), T1>::type * = 0)
+{
+  return false;
+}
+
+// Internal helper defining the cost of a scalar division for the type T.
+// The default heuristic can be specialized for each scalar type and architecture.
+template<typename T,bool Vectorized=false,typename EnaleIf = void>
+struct scalar_div_cost {
+  enum { value = 8*NumTraits<T>::MulCost };
+};
+
+template<typename T,bool Vectorized>
+struct scalar_div_cost<std::complex<T>, Vectorized> {
+  enum { value = 2*scalar_div_cost<T>::value
+               + 6*NumTraits<T>::MulCost
+               + 3*NumTraits<T>::AddCost
+  };
+};
+
+
+template<bool Vectorized>
+struct scalar_div_cost<signed long,Vectorized,typename conditional<sizeof(long)==8,void,false_type>::type> { enum { value = 24 }; };
+template<bool Vectorized>
+struct scalar_div_cost<unsigned long,Vectorized,typename conditional<sizeof(long)==8,void,false_type>::type> { enum { value = 21 }; };
+
+
+#ifdef EIGEN_DEBUG_ASSIGN
+std::string demangle_traversal(int t)
+{
+  if(t==DefaultTraversal) return "DefaultTraversal";
+  if(t==LinearTraversal) return "LinearTraversal";
+  if(t==InnerVectorizedTraversal) return "InnerVectorizedTraversal";
+  if(t==LinearVectorizedTraversal) return "LinearVectorizedTraversal";
+  if(t==SliceVectorizedTraversal) return "SliceVectorizedTraversal";
+  return "?";
+}
+std::string demangle_unrolling(int t)
+{
+  if(t==NoUnrolling) return "NoUnrolling";
+  if(t==InnerUnrolling) return "InnerUnrolling";
+  if(t==CompleteUnrolling) return "CompleteUnrolling";
+  return "?";
+}
+std::string demangle_flags(int f)
+{
+  std::string res;
+  if(f&RowMajorBit)                 res += " | RowMajor";
+  if(f&PacketAccessBit)             res += " | Packet";
+  if(f&LinearAccessBit)             res += " | Linear";
+  if(f&LvalueBit)                   res += " | Lvalue";
+  if(f&DirectAccessBit)             res += " | Direct";
+  if(f&NestByRefBit)                res += " | NestByRef";
+  if(f&NoPreferredStorageOrderBit)  res += " | NoPreferredStorageOrderBit";
+  
+  return res;
+}
+#endif
 
 } // end namespace internal
 
+
+/** \class ScalarBinaryOpTraits
+  * \ingroup Core_Module
+  *
+  * \brief Determines whether the given binary operation of two numeric types is allowed and what the scalar return type is.
+  *
+  * This class permits to control the scalar return type of any binary operation performed on two different scalar types through (partial) template specializations.
+  *
+  * For instance, let \c U1, \c U2 and \c U3 be three user defined scalar types for which most operations between instances of \c U1 and \c U2 returns an \c U3.
+  * You can let %Eigen knows that by defining:
+    \code
+    template<typename BinaryOp>
+    struct ScalarBinaryOpTraits<U1,U2,BinaryOp> { typedef U3 ReturnType;  };
+    template<typename BinaryOp>
+    struct ScalarBinaryOpTraits<U2,U1,BinaryOp> { typedef U3 ReturnType;  };
+    \endcode
+  * You can then explicitly disable some particular operations to get more explicit error messages:
+    \code
+    template<>
+    struct ScalarBinaryOpTraits<U1,U2,internal::scalar_max_op<U1,U2> > {};
+    \endcode
+  * Or customize the return type for individual operation:
+    \code
+    template<>
+    struct ScalarBinaryOpTraits<U1,U2,internal::scalar_sum_op<U1,U2> > { typedef U1 ReturnType; };
+    \endcode
+  *
+  * By default, the following generic combinations are supported:
+  <table class="manual">
+  <tr><th>ScalarA</th><th>ScalarB</th><th>BinaryOp</th><th>ReturnType</th><th>Note</th></tr>
+  <tr            ><td>\c T </td><td>\c T </td><td>\c * </td><td>\c T </td><td></td></tr>
+  <tr class="alt"><td>\c NumTraits<T>::Real </td><td>\c T </td><td>\c * </td><td>\c T </td><td>Only if \c NumTraits<T>::IsComplex </td></tr>
+  <tr            ><td>\c T </td><td>\c NumTraits<T>::Real </td><td>\c * </td><td>\c T </td><td>Only if \c NumTraits<T>::IsComplex </td></tr>
+  </table>
+  *
+  * \sa CwiseBinaryOp
+  */
+template<typename ScalarA, typename ScalarB, typename BinaryOp=internal::scalar_product_op<ScalarA,ScalarB> >
+struct ScalarBinaryOpTraits
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+  // for backward compatibility, use the hints given by the (deprecated) internal::scalar_product_traits class.
+  : internal::scalar_product_traits<ScalarA,ScalarB>
+#endif // EIGEN_PARSED_BY_DOXYGEN
+{};
+
+template<typename T, typename BinaryOp>
+struct ScalarBinaryOpTraits<T,T,BinaryOp>
+{
+  typedef T ReturnType;
+};
+
+template <typename T, typename BinaryOp>
+struct ScalarBinaryOpTraits<T, typename NumTraits<typename internal::enable_if<NumTraits<T>::IsComplex,T>::type>::Real, BinaryOp>
+{
+  typedef T ReturnType;
+};
+template <typename T, typename BinaryOp>
+struct ScalarBinaryOpTraits<typename NumTraits<typename internal::enable_if<NumTraits<T>::IsComplex,T>::type>::Real, T, BinaryOp>
+{
+  typedef T ReturnType;
+};
+
+// For Matrix * Permutation
+template<typename T, typename BinaryOp>
+struct ScalarBinaryOpTraits<T,void,BinaryOp>
+{
+  typedef T ReturnType;
+};
+
+// For Permutation * Matrix
+template<typename T, typename BinaryOp>
+struct ScalarBinaryOpTraits<void,T,BinaryOp>
+{
+  typedef T ReturnType;
+};
+
+// for Permutation*Permutation
+template<typename BinaryOp>
+struct ScalarBinaryOpTraits<void,void,BinaryOp>
+{
+  typedef void ReturnType;
+};
+
+// We require Lhs and Rhs to have "compatible" scalar types.
+// It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths.
+// So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
+// add together a float matrix and a double matrix.
+#define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \
+  EIGEN_STATIC_ASSERT((Eigen::internal::has_ReturnType<ScalarBinaryOpTraits<LHS, RHS,BINOP> >::value), \
+    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+    
 } // end namespace Eigen
 
 #endif // EIGEN_XPRHELPER_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Block.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Block.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Block.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Block.h
@@ -1,126 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_BLOCK2_H
-#define EIGEN_BLOCK2_H
-
-namespace Eigen { 
-
-/** \returns a dynamic-size expression of a corner of *this.
-  *
-  * \param type the type of corner. Can be \a Eigen::TopLeft, \a Eigen::TopRight,
-  * \a Eigen::BottomLeft, \a Eigen::BottomRight.
-  * \param cRows the number of rows in the corner
-  * \param cCols the number of columns in the corner
-  *
-  * Example: \include MatrixBase_corner_enum_int_int.cpp
-  * Output: \verbinclude MatrixBase_corner_enum_int_int.out
-  *
-  * \note Even though the returned expression has dynamic size, in the case
-  * when it is applied to a fixed-size matrix, it inherits a fixed maximal size,
-  * which means that evaluating it does not cause a dynamic memory allocation.
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-template<typename Derived>
-inline Block<Derived> DenseBase<Derived>
-  ::corner(CornerType type, Index cRows, Index cCols)
-{
-  switch(type)
-  {
-    default:
-      eigen_assert(false && "Bad corner type.");
-    case TopLeft:
-      return Block<Derived>(derived(), 0, 0, cRows, cCols);
-    case TopRight:
-      return Block<Derived>(derived(), 0, cols() - cCols, cRows, cCols);
-    case BottomLeft:
-      return Block<Derived>(derived(), rows() - cRows, 0, cRows, cCols);
-    case BottomRight:
-      return Block<Derived>(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
-  }
-}
-
-/** This is the const version of corner(CornerType, Index, Index).*/
-template<typename Derived>
-inline const Block<Derived>
-DenseBase<Derived>::corner(CornerType type, Index cRows, Index cCols) const
-{
-  switch(type)
-  {
-    default:
-      eigen_assert(false && "Bad corner type.");
-    case TopLeft:
-      return Block<Derived>(derived(), 0, 0, cRows, cCols);
-    case TopRight:
-      return Block<Derived>(derived(), 0, cols() - cCols, cRows, cCols);
-    case BottomLeft:
-      return Block<Derived>(derived(), rows() - cRows, 0, cRows, cCols);
-    case BottomRight:
-      return Block<Derived>(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
-  }
-}
-
-/** \returns a fixed-size expression of a corner of *this.
-  *
-  * \param type the type of corner. Can be \a Eigen::TopLeft, \a Eigen::TopRight,
-  * \a Eigen::BottomLeft, \a Eigen::BottomRight.
-  *
-  * The template parameters CRows and CCols arethe number of rows and columns in the corner.
-  *
-  * Example: \include MatrixBase_template_int_int_corner_enum.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_corner_enum.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-template<typename Derived>
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols>
-DenseBase<Derived>::corner(CornerType type)
-{
-  switch(type)
-  {
-    default:
-      eigen_assert(false && "Bad corner type.");
-    case TopLeft:
-      return Block<Derived, CRows, CCols>(derived(), 0, 0);
-    case TopRight:
-      return Block<Derived, CRows, CCols>(derived(), 0, cols() - CCols);
-    case BottomLeft:
-      return Block<Derived, CRows, CCols>(derived(), rows() - CRows, 0);
-    case BottomRight:
-      return Block<Derived, CRows, CCols>(derived(), rows() - CRows, cols() - CCols);
-  }
-}
-
-/** This is the const version of corner<int, int>(CornerType).*/
-template<typename Derived>
-template<int CRows, int CCols>
-inline const Block<Derived, CRows, CCols>
-DenseBase<Derived>::corner(CornerType type) const
-{
-  switch(type)
-  {
-    default:
-      eigen_assert(false && "Bad corner type.");
-    case TopLeft:
-      return Block<Derived, CRows, CCols>(derived(), 0, 0);
-    case TopRight:
-      return Block<Derived, CRows, CCols>(derived(), 0, cols() - CCols);
-    case BottomLeft:
-      return Block<Derived, CRows, CCols>(derived(), rows() - CRows, 0);
-    case BottomRight:
-      return Block<Derived, CRows, CCols>(derived(), rows() - CRows, cols() - CCols);
-  }
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_BLOCK2_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/CMakeLists.txt
@@ -1,8 +0,0 @@
-FILE(GLOB Eigen_Eigen2Support_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Eigen2Support_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Eigen2Support COMPONENT Devel
-  )
-
-ADD_SUBDIRECTORY(Geometry)

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Cwise.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Cwise.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Cwise.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Cwise.h
@@ -1,192 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CWISE_H
-#define EIGEN_CWISE_H
-
-namespace Eigen { 
-
-/** \internal
-  * convenient macro to defined the return type of a cwise binary operation */
-#define EIGEN_CWISE_BINOP_RETURN_TYPE(OP) \
-    CwiseBinaryOp<OP<typename internal::traits<ExpressionType>::Scalar>, ExpressionType, OtherDerived>
-
-/** \internal
-  * convenient macro to defined the return type of a cwise unary operation */
-#define EIGEN_CWISE_UNOP_RETURN_TYPE(OP) \
-    CwiseUnaryOp<OP<typename internal::traits<ExpressionType>::Scalar>, ExpressionType>
-
-/** \internal
-  * convenient macro to defined the return type of a cwise comparison to a scalar */
-#define EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(OP) \
-    CwiseBinaryOp<OP<typename internal::traits<ExpressionType>::Scalar>, ExpressionType, \
-        typename ExpressionType::ConstantReturnType >
-
-/** \class Cwise
-  *
-  * \brief Pseudo expression providing additional coefficient-wise operations
-  *
-  * \param ExpressionType the type of the object on which to do coefficient-wise operations
-  *
-  * This class represents an expression with additional coefficient-wise features.
-  * It is the return type of MatrixBase::cwise()
-  * and most of the time this is the only way it is used.
-  *
-  * Example: \include MatrixBase_cwise_const.cpp
-  * Output: \verbinclude MatrixBase_cwise_const.out
-  *
-  * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_CWISE_PLUGIN.
-  *
-  * \sa MatrixBase::cwise() const, MatrixBase::cwise()
-  */
-template<typename ExpressionType> class Cwise
-{
-  public:
-
-    typedef typename internal::traits<ExpressionType>::Scalar Scalar;
-    typedef typename internal::conditional<internal::must_nest_by_value<ExpressionType>::ret,
-        ExpressionType, const ExpressionType&>::type ExpressionTypeNested;
-    typedef CwiseUnaryOp<internal::scalar_add_op<Scalar>, ExpressionType> ScalarAddReturnType;
-
-    inline Cwise(const ExpressionType& matrix) : m_matrix(matrix) {}
-
-    /** \internal */
-    inline const ExpressionType& _expression() const { return m_matrix; }
-
-    template<typename OtherDerived>
-    const EIGEN_CWISE_PRODUCT_RETURN_TYPE(ExpressionType,OtherDerived)
-    operator*(const MatrixBase<OtherDerived> &other) const;
-
-    template<typename OtherDerived>
-    const EIGEN_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)
-    operator/(const MatrixBase<OtherDerived> &other) const;
-
-    /** \deprecated ArrayBase::min() */
-    template<typename OtherDerived>
-    const EIGEN_CWISE_BINOP_RETURN_TYPE(internal::scalar_min_op)
-    (min)(const MatrixBase<OtherDerived> &other) const
-    { return EIGEN_CWISE_BINOP_RETURN_TYPE(internal::scalar_min_op)(_expression(), other.derived()); }
-
-    /** \deprecated ArrayBase::max() */
-    template<typename OtherDerived>
-    const EIGEN_CWISE_BINOP_RETURN_TYPE(internal::scalar_max_op)
-    (max)(const MatrixBase<OtherDerived> &other) const
-    { return EIGEN_CWISE_BINOP_RETURN_TYPE(internal::scalar_max_op)(_expression(), other.derived()); }
-
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_abs_op)      abs() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_abs2_op)     abs2() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_square_op)   square() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_cube_op)     cube() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_inverse_op)  inverse() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_sqrt_op)     sqrt() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_exp_op)      exp() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_log_op)      log() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_cos_op)      cos() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_sin_op)      sin() const;
-    const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_pow_op)      pow(const Scalar& exponent) const;
-
-    const ScalarAddReturnType
-    operator+(const Scalar& scalar) const;
-
-    /** \relates Cwise */
-    friend const ScalarAddReturnType
-    operator+(const Scalar& scalar, const Cwise& mat)
-    { return mat + scalar; }
-
-    ExpressionType& operator+=(const Scalar& scalar);
-
-    const ScalarAddReturnType
-    operator-(const Scalar& scalar) const;
-
-    ExpressionType& operator-=(const Scalar& scalar);
-
-    template<typename OtherDerived>
-    inline ExpressionType& operator*=(const MatrixBase<OtherDerived> &other);
-
-    template<typename OtherDerived>
-    inline ExpressionType& operator/=(const MatrixBase<OtherDerived> &other);
-
-    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)
-    operator<(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)
-    operator<=(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)
-    operator>(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)
-    operator>=(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)
-    operator==(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::not_equal_to)
-    operator!=(const MatrixBase<OtherDerived>& other) const;
-
-    // comparisons to a scalar value
-    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less)
-    operator<(Scalar s) const;
-
-    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less_equal)
-    operator<=(Scalar s) const;
-
-    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater)
-    operator>(Scalar s) const;
-
-    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater_equal)
-    operator>=(Scalar s) const;
-
-    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::equal_to)
-    operator==(Scalar s) const;
-
-    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)
-    operator!=(Scalar s) const;
-
-    // allow to extend Cwise outside Eigen
-    #ifdef EIGEN_CWISE_PLUGIN
-    #include EIGEN_CWISE_PLUGIN
-    #endif
-
-  protected:
-    ExpressionTypeNested m_matrix;
-};
-
-
-/** \returns a Cwise wrapper of *this providing additional coefficient-wise operations
-  *
-  * Example: \include MatrixBase_cwise_const.cpp
-  * Output: \verbinclude MatrixBase_cwise_const.out
-  *
-  * \sa class Cwise, cwise()
-  */
-template<typename Derived>
-inline const Cwise<Derived> MatrixBase<Derived>::cwise() const
-{
-  return derived();
-}
-
-/** \returns a Cwise wrapper of *this providing additional coefficient-wise operations
-  *
-  * Example: \include MatrixBase_cwise.cpp
-  * Output: \verbinclude MatrixBase_cwise.out
-  *
-  * \sa class Cwise, cwise() const
-  */
-template<typename Derived>
-inline Cwise<Derived> MatrixBase<Derived>::cwise()
-{
-  return derived();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_CWISE_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/CwiseOperators.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/CwiseOperators.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/CwiseOperators.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/CwiseOperators.h
@@ -1,298 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ARRAY_CWISE_OPERATORS_H
-#define EIGEN_ARRAY_CWISE_OPERATORS_H
-
-namespace Eigen { 
-
-/***************************************************************************
-* The following functions were defined in Core
-***************************************************************************/
-
-
-/** \deprecated ArrayBase::abs() */
-template<typename ExpressionType>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_abs_op)
-Cwise<ExpressionType>::abs() const
-{
-  return _expression();
-}
-
-/** \deprecated ArrayBase::abs2() */
-template<typename ExpressionType>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_abs2_op)
-Cwise<ExpressionType>::abs2() const
-{
-  return _expression();
-}
-
-/** \deprecated ArrayBase::exp() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_exp_op)
-Cwise<ExpressionType>::exp() const
-{
-  return _expression();
-}
-
-/** \deprecated ArrayBase::log() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_log_op)
-Cwise<ExpressionType>::log() const
-{
-  return _expression();
-}
-
-/** \deprecated ArrayBase::operator*() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_PRODUCT_RETURN_TYPE(ExpressionType,OtherDerived)
-Cwise<ExpressionType>::operator*(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_PRODUCT_RETURN_TYPE(ExpressionType,OtherDerived)(_expression(), other.derived());
-}
-
-/** \deprecated ArrayBase::operator/() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)
-Cwise<ExpressionType>::operator/(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)(_expression(), other.derived());
-}
-
-/** \deprecated ArrayBase::operator*=() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline ExpressionType& Cwise<ExpressionType>::operator*=(const MatrixBase<OtherDerived> &other)
-{
-  return m_matrix.const_cast_derived() = *this * other;
-}
-
-/** \deprecated ArrayBase::operator/=() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline ExpressionType& Cwise<ExpressionType>::operator/=(const MatrixBase<OtherDerived> &other)
-{
-  return m_matrix.const_cast_derived() = *this / other;
-}
-
-/***************************************************************************
-* The following functions were defined in Array
-***************************************************************************/
-
-// -- unary operators --
-
-/** \deprecated ArrayBase::sqrt() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_sqrt_op)
-Cwise<ExpressionType>::sqrt() const
-{
-  return _expression();
-}
-
-/** \deprecated ArrayBase::cos() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_cos_op)
-Cwise<ExpressionType>::cos() const
-{
-  return _expression();
-}
-
-
-/** \deprecated ArrayBase::sin() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_sin_op)
-Cwise<ExpressionType>::sin() const
-{
-  return _expression();
-}
-
-
-/** \deprecated ArrayBase::log() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_pow_op)
-Cwise<ExpressionType>::pow(const Scalar& exponent) const
-{
-  return EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_pow_op)(_expression(), internal::scalar_pow_op<Scalar>(exponent));
-}
-
-
-/** \deprecated ArrayBase::inverse() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_inverse_op)
-Cwise<ExpressionType>::inverse() const
-{
-  return _expression();
-}
-
-/** \deprecated ArrayBase::square() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_square_op)
-Cwise<ExpressionType>::square() const
-{
-  return _expression();
-}
-
-/** \deprecated ArrayBase::cube() */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(internal::scalar_cube_op)
-Cwise<ExpressionType>::cube() const
-{
-  return _expression();
-}
-
-
-// -- binary operators --
-
-/** \deprecated ArrayBase::operator<() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)
-Cwise<ExpressionType>::operator<(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)(_expression(), other.derived());
-}
-
-/** \deprecated ArrayBase::<=() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)
-Cwise<ExpressionType>::operator<=(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)(_expression(), other.derived());
-}
-
-/** \deprecated ArrayBase::operator>() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)
-Cwise<ExpressionType>::operator>(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)(_expression(), other.derived());
-}
-
-/** \deprecated ArrayBase::operator>=() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)
-Cwise<ExpressionType>::operator>=(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)(_expression(), other.derived());
-}
-
-/** \deprecated ArrayBase::operator==() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)
-Cwise<ExpressionType>::operator==(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)(_expression(), other.derived());
-}
-
-/** \deprecated ArrayBase::operator!=() */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::not_equal_to)
-Cwise<ExpressionType>::operator!=(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::not_equal_to)(_expression(), other.derived());
-}
-
-// comparisons to scalar value
-
-/** \deprecated ArrayBase::operator<(Scalar) */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less)
-Cwise<ExpressionType>::operator<(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \deprecated ArrayBase::operator<=(Scalar) */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less_equal)
-Cwise<ExpressionType>::operator<=(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less_equal)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \deprecated ArrayBase::operator>(Scalar) */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater)
-Cwise<ExpressionType>::operator>(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \deprecated ArrayBase::operator>=(Scalar) */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater_equal)
-Cwise<ExpressionType>::operator>=(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater_equal)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \deprecated ArrayBase::operator==(Scalar) */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::equal_to)
-Cwise<ExpressionType>::operator==(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::equal_to)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \deprecated ArrayBase::operator!=(Scalar) */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)
-Cwise<ExpressionType>::operator!=(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-// scalar addition
-
-/** \deprecated ArrayBase::operator+(Scalar) */
-template<typename ExpressionType>
-inline const typename Cwise<ExpressionType>::ScalarAddReturnType
-Cwise<ExpressionType>::operator+(const Scalar& scalar) const
-{
-  return typename Cwise<ExpressionType>::ScalarAddReturnType(m_matrix, internal::scalar_add_op<Scalar>(scalar));
-}
-
-/** \deprecated ArrayBase::operator+=(Scalar) */
-template<typename ExpressionType>
-inline ExpressionType& Cwise<ExpressionType>::operator+=(const Scalar& scalar)
-{
-  return m_matrix.const_cast_derived() = *this + scalar;
-}
-
-/** \deprecated ArrayBase::operator-(Scalar) */
-template<typename ExpressionType>
-inline const typename Cwise<ExpressionType>::ScalarAddReturnType
-Cwise<ExpressionType>::operator-(const Scalar& scalar) const
-{
-  return *this + (-scalar);
-}
-
-/** \deprecated ArrayBase::operator-=(Scalar) */
-template<typename ExpressionType>
-inline ExpressionType& Cwise<ExpressionType>::operator-=(const Scalar& scalar)
-{
-  return m_matrix.const_cast_derived() = *this - scalar;
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_ARRAY_CWISE_OPERATORS_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
@@ -1,159 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-/** \geometry_module \ingroup Geometry_Module
-  * \nonstableyet
-  *
-  * \class AlignedBox
-  *
-  * \brief An axis aligned box
-  *
-  * \param _Scalar the type of the scalar coefficients
-  * \param _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
-  *
-  * This class represents an axis aligned box as a pair of the minimal and maximal corners.
-  */
-template <typename _Scalar, int _AmbientDim>
-class AlignedBox
-{
-public:
-EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim==Dynamic ? Dynamic : _AmbientDim+1)
-  enum { AmbientDimAtCompileTime = _AmbientDim };
-  typedef _Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar,AmbientDimAtCompileTime,1> VectorType;
-
-  /** Default constructor initializing a null box. */
-  inline AlignedBox()
-  { if (AmbientDimAtCompileTime!=Dynamic) setNull(); }
-
-  /** Constructs a null box with \a _dim the dimension of the ambient space. */
-  inline explicit AlignedBox(int _dim) : m_min(_dim), m_max(_dim)
-  { setNull(); }
-
-  /** Constructs a box with extremities \a _min and \a _max. */
-  inline AlignedBox(const VectorType& _min, const VectorType& _max) : m_min(_min), m_max(_max) {}
-
-  /** Constructs a box containing a single point \a p. */
-  inline explicit AlignedBox(const VectorType& p) : m_min(p), m_max(p) {}
-
-  ~AlignedBox() {}
-
-  /** \returns the dimension in which the box holds */
-  inline int dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size()-1 : AmbientDimAtCompileTime; }
-
-  /** \returns true if the box is null, i.e, empty. */
-  inline bool isNull() const { return (m_min.cwise() > m_max).any(); }
-
-  /** Makes \c *this a null/empty box. */
-  inline void setNull()
-  {
-    m_min.setConstant( (std::numeric_limits<Scalar>::max)());
-    m_max.setConstant(-(std::numeric_limits<Scalar>::max)());
-  }
-
-  /** \returns the minimal corner */
-  inline const VectorType& (min)() const { return m_min; }
-  /** \returns a non const reference to the minimal corner */
-  inline VectorType& (min)() { return m_min; }
-  /** \returns the maximal corner */
-  inline const VectorType& (max)() const { return m_max; }
-  /** \returns a non const reference to the maximal corner */
-  inline VectorType& (max)() { return m_max; }
-
-  /** \returns true if the point \a p is inside the box \c *this. */
-  inline bool contains(const VectorType& p) const
-  { return (m_min.cwise()<=p).all() && (p.cwise()<=m_max).all(); }
-
-  /** \returns true if the box \a b is entirely inside the box \c *this. */
-  inline bool contains(const AlignedBox& b) const
-  { return (m_min.cwise()<=(b.min)()).all() && ((b.max)().cwise()<=m_max).all(); }
-
-  /** Extends \c *this such that it contains the point \a p and returns a reference to \c *this. */
-  inline AlignedBox& extend(const VectorType& p)
-  { m_min = (m_min.cwise().min)(p); m_max = (m_max.cwise().max)(p); return *this; }
-
-  /** Extends \c *this such that it contains the box \a b and returns a reference to \c *this. */
-  inline AlignedBox& extend(const AlignedBox& b)
-  { m_min = (m_min.cwise().min)(b.m_min); m_max = (m_max.cwise().max)(b.m_max); return *this; }
-
-  /** Clamps \c *this by the box \a b and returns a reference to \c *this. */
-  inline AlignedBox& clamp(const AlignedBox& b)
-  { m_min = (m_min.cwise().max)(b.m_min); m_max = (m_max.cwise().min)(b.m_max); return *this; }
-
-  /** Translate \c *this by the vector \a t and returns a reference to \c *this. */
-  inline AlignedBox& translate(const VectorType& t)
-  { m_min += t; m_max += t; return *this; }
-
-  /** \returns the squared distance between the point \a p and the box \c *this,
-    * and zero if \a p is inside the box.
-    * \sa exteriorDistance()
-    */
-  inline Scalar squaredExteriorDistance(const VectorType& p) const;
-
-  /** \returns the distance between the point \a p and the box \c *this,
-    * and zero if \a p is inside the box.
-    * \sa squaredExteriorDistance()
-    */
-  inline Scalar exteriorDistance(const VectorType& p) const
-  { return ei_sqrt(squaredExteriorDistance(p)); }
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<AlignedBox,
-           AlignedBox<NewScalarType,AmbientDimAtCompileTime> >::type cast() const
-  {
-    return typename internal::cast_return_type<AlignedBox,
-                    AlignedBox<NewScalarType,AmbientDimAtCompileTime> >::type(*this);
-  }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit AlignedBox(const AlignedBox<OtherScalarType,AmbientDimAtCompileTime>& other)
-  {
-    m_min = (other.min)().template cast<Scalar>();
-    m_max = (other.max)().template cast<Scalar>();
-  }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const AlignedBox& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return m_min.isApprox(other.m_min, prec) && m_max.isApprox(other.m_max, prec); }
-
-protected:
-
-  VectorType m_min, m_max;
-};
-
-template<typename Scalar,int AmbiantDim>
-inline Scalar AlignedBox<Scalar,AmbiantDim>::squaredExteriorDistance(const VectorType& p) const
-{
-  Scalar dist2(0);
-  Scalar aux;
-  for (int k=0; k<dim(); ++k)
-  {
-    if ((aux = (p[k]-m_min[k]))<Scalar(0))
-      dist2 += aux*aux;
-    else if ( (aux = (m_max[k]-p[k]))<Scalar(0))
-      dist2 += aux*aux;
-  }
-  return dist2;
-}
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/All.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/All.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/All.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/All.h
@@ -1,115 +0,0 @@
-#ifndef EIGEN2_GEOMETRY_MODULE_H
-#define EIGEN2_GEOMETRY_MODULE_H
-
-#include <limits>
-
-#ifndef M_PI
-#define M_PI 3.14159265358979323846
-#endif
-
-#if EIGEN2_SUPPORT_STAGE < STAGE20_RESOLVE_API_CONFLICTS
-#include "RotationBase.h"
-#include "Rotation2D.h"
-#include "Quaternion.h"
-#include "AngleAxis.h"
-#include "Transform.h"
-#include "Translation.h"
-#include "Scaling.h"
-#include "AlignedBox.h"
-#include "Hyperplane.h"
-#include "ParametrizedLine.h"
-#endif
-
-
-#define RotationBase eigen2_RotationBase
-#define Rotation2D eigen2_Rotation2D
-#define Rotation2Df eigen2_Rotation2Df
-#define Rotation2Dd eigen2_Rotation2Dd
-
-#define Quaternion  eigen2_Quaternion
-#define Quaternionf eigen2_Quaternionf
-#define Quaterniond eigen2_Quaterniond
-
-#define AngleAxis eigen2_AngleAxis
-#define AngleAxisf eigen2_AngleAxisf
-#define AngleAxisd eigen2_AngleAxisd
-
-#define Transform   eigen2_Transform
-#define Transform2f eigen2_Transform2f
-#define Transform2d eigen2_Transform2d
-#define Transform3f eigen2_Transform3f
-#define Transform3d eigen2_Transform3d
-
-#define Translation eigen2_Translation
-#define Translation2f eigen2_Translation2f
-#define Translation2d eigen2_Translation2d
-#define Translation3f eigen2_Translation3f
-#define Translation3d eigen2_Translation3d
-
-#define Scaling eigen2_Scaling
-#define Scaling2f eigen2_Scaling2f
-#define Scaling2d eigen2_Scaling2d
-#define Scaling3f eigen2_Scaling3f
-#define Scaling3d eigen2_Scaling3d
-
-#define AlignedBox eigen2_AlignedBox
-
-#define Hyperplane eigen2_Hyperplane
-#define ParametrizedLine eigen2_ParametrizedLine
-
-#define ei_toRotationMatrix eigen2_ei_toRotationMatrix
-#define ei_quaternion_assign_impl eigen2_ei_quaternion_assign_impl
-#define ei_transform_product_impl eigen2_ei_transform_product_impl
-
-#include "RotationBase.h"
-#include "Rotation2D.h"
-#include "Quaternion.h"
-#include "AngleAxis.h"
-#include "Transform.h"
-#include "Translation.h"
-#include "Scaling.h"
-#include "AlignedBox.h"
-#include "Hyperplane.h"
-#include "ParametrizedLine.h"
-
-#undef ei_toRotationMatrix
-#undef ei_quaternion_assign_impl
-#undef ei_transform_product_impl
-
-#undef RotationBase
-#undef Rotation2D
-#undef Rotation2Df
-#undef Rotation2Dd
-
-#undef Quaternion
-#undef Quaternionf
-#undef Quaterniond
-
-#undef AngleAxis
-#undef AngleAxisf
-#undef AngleAxisd
-
-#undef Transform
-#undef Transform2f
-#undef Transform2d
-#undef Transform3f
-#undef Transform3d
-
-#undef Translation
-#undef Translation2f
-#undef Translation2d
-#undef Translation3f
-#undef Translation3d
-
-#undef Scaling
-#undef Scaling2f
-#undef Scaling2d
-#undef Scaling3f
-#undef Scaling3d
-
-#undef AlignedBox
-
-#undef Hyperplane
-#undef ParametrizedLine
-
-#endif // EIGEN2_GEOMETRY_MODULE_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
@@ -1,214 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-/** \geometry_module \ingroup Geometry_Module
-  *
-  * \class AngleAxis
-  *
-  * \brief Represents a 3D rotation as a rotation angle around an arbitrary 3D axis
-  *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients.
-  *
-  * The following two typedefs are provided for convenience:
-  * \li \c AngleAxisf for \c float
-  * \li \c AngleAxisd for \c double
-  *
-  * \addexample AngleAxisForEuler \label How to define a rotation from Euler-angles
-  *
-  * Combined with MatrixBase::Unit{X,Y,Z}, AngleAxis can be used to easily
-  * mimic Euler-angles. Here is an example:
-  * \include AngleAxis_mimic_euler.cpp
-  * Output: \verbinclude AngleAxis_mimic_euler.out
-  *
-  * \note This class is not aimed to be used to store a rotation transformation,
-  * but rather to make easier the creation of other rotation (Quaternion, rotation Matrix)
-  * and transformation objects.
-  *
-  * \sa class Quaternion, class Transform, MatrixBase::UnitX()
-  */
-
-template<typename _Scalar> struct ei_traits<AngleAxis<_Scalar> >
-{
-  typedef _Scalar Scalar;
-};
-
-template<typename _Scalar>
-class AngleAxis : public RotationBase<AngleAxis<_Scalar>,3>
-{
-  typedef RotationBase<AngleAxis<_Scalar>,3> Base;
-
-public:
-
-  using Base::operator*;
-
-  enum { Dim = 3 };
-  /** the scalar type of the coefficients */
-  typedef _Scalar Scalar;
-  typedef Matrix<Scalar,3,3> Matrix3;
-  typedef Matrix<Scalar,3,1> Vector3;
-  typedef Quaternion<Scalar> QuaternionType;
-
-protected:
-
-  Vector3 m_axis;
-  Scalar m_angle;
-
-public:
-
-  /** Default constructor without initialization. */
-  AngleAxis() {}
-  /** Constructs and initialize the angle-axis rotation from an \a angle in radian
-    * and an \a axis which must be normalized. */
-  template<typename Derived>
-  inline AngleAxis(Scalar angle, const MatrixBase<Derived>& axis) : m_axis(axis), m_angle(angle) {}
-  /** Constructs and initialize the angle-axis rotation from a quaternion \a q. */
-  inline AngleAxis(const QuaternionType& q) { *this = q; }
-  /** Constructs and initialize the angle-axis rotation from a 3x3 rotation matrix. */
-  template<typename Derived>
-  inline explicit AngleAxis(const MatrixBase<Derived>& m) { *this = m; }
-
-  Scalar angle() const { return m_angle; }
-  Scalar& angle() { return m_angle; }
-
-  const Vector3& axis() const { return m_axis; }
-  Vector3& axis() { return m_axis; }
-
-  /** Concatenates two rotations */
-  inline QuaternionType operator* (const AngleAxis& other) const
-  { return QuaternionType(*this) * QuaternionType(other); }
-
-  /** Concatenates two rotations */
-  inline QuaternionType operator* (const QuaternionType& other) const
-  { return QuaternionType(*this) * other; }
-
-  /** Concatenates two rotations */
-  friend inline QuaternionType operator* (const QuaternionType& a, const AngleAxis& b)
-  { return a * QuaternionType(b); }
-
-  /** Concatenates two rotations */
-  inline Matrix3 operator* (const Matrix3& other) const
-  { return toRotationMatrix() * other; }
-
-  /** Concatenates two rotations */
-  inline friend Matrix3 operator* (const Matrix3& a, const AngleAxis& b)
-  { return a * b.toRotationMatrix(); }
-
-  /** Applies rotation to vector */
-  inline Vector3 operator* (const Vector3& other) const
-  { return toRotationMatrix() * other; }
-
-  /** \returns the inverse rotation, i.e., an angle-axis with opposite rotation angle */
-  AngleAxis inverse() const
-  { return AngleAxis(-m_angle, m_axis); }
-
-  AngleAxis& operator=(const QuaternionType& q);
-  template<typename Derived>
-  AngleAxis& operator=(const MatrixBase<Derived>& m);
-
-  template<typename Derived>
-  AngleAxis& fromRotationMatrix(const MatrixBase<Derived>& m);
-  Matrix3 toRotationMatrix(void) const;
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<AngleAxis,AngleAxis<NewScalarType> >::type cast() const
-  { return typename internal::cast_return_type<AngleAxis,AngleAxis<NewScalarType> >::type(*this); }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit AngleAxis(const AngleAxis<OtherScalarType>& other)
-  {
-    m_axis = other.axis().template cast<Scalar>();
-    m_angle = Scalar(other.angle());
-  }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const AngleAxis& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return m_axis.isApprox(other.m_axis, prec) && ei_isApprox(m_angle,other.m_angle, prec); }
-};
-
-/** \ingroup Geometry_Module
-  * single precision angle-axis type */
-typedef AngleAxis<float> AngleAxisf;
-/** \ingroup Geometry_Module
-  * double precision angle-axis type */
-typedef AngleAxis<double> AngleAxisd;
-
-/** Set \c *this from a quaternion.
-  * The axis is normalized.
-  */
-template<typename Scalar>
-AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const QuaternionType& q)
-{
-  Scalar n2 = q.vec().squaredNorm();
-  if (n2 < precision<Scalar>()*precision<Scalar>())
-  {
-    m_angle = 0;
-    m_axis << 1, 0, 0;
-  }
-  else
-  {
-    m_angle = 2*std::acos(q.w());
-    m_axis = q.vec() / ei_sqrt(n2);
-  }
-  return *this;
-}
-
-/** Set \c *this from a 3x3 rotation matrix \a mat.
-  */
-template<typename Scalar>
-template<typename Derived>
-AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const MatrixBase<Derived>& mat)
-{
-  // Since a direct conversion would not be really faster,
-  // let's use the robust Quaternion implementation:
-  return *this = QuaternionType(mat);
-}
-
-/** Constructs and \returns an equivalent 3x3 rotation matrix.
-  */
-template<typename Scalar>
-typename AngleAxis<Scalar>::Matrix3
-AngleAxis<Scalar>::toRotationMatrix(void) const
-{
-  Matrix3 res;
-  Vector3 sin_axis  = ei_sin(m_angle) * m_axis;
-  Scalar c = ei_cos(m_angle);
-  Vector3 cos1_axis = (Scalar(1)-c) * m_axis;
-
-  Scalar tmp;
-  tmp = cos1_axis.x() * m_axis.y();
-  res.coeffRef(0,1) = tmp - sin_axis.z();
-  res.coeffRef(1,0) = tmp + sin_axis.z();
-
-  tmp = cos1_axis.x() * m_axis.z();
-  res.coeffRef(0,2) = tmp + sin_axis.y();
-  res.coeffRef(2,0) = tmp - sin_axis.y();
-
-  tmp = cos1_axis.y() * m_axis.z();
-  res.coeffRef(1,2) = tmp - sin_axis.x();
-  res.coeffRef(2,1) = tmp + sin_axis.x();
-
-  res.diagonal() = (cos1_axis.cwise() * m_axis).cwise() + c;
-
-  return res;
-}
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Eigen2Support_Geometry_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Eigen2Support_Geometry_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Eigen2Support/Geometry
-  )

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
@@ -1,254 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-/** \geometry_module \ingroup Geometry_Module
-  *
-  * \class Hyperplane
-  *
-  * \brief A hyperplane
-  *
-  * A hyperplane is an affine subspace of dimension n-1 in a space of dimension n.
-  * For example, a hyperplane in a plane is a line; a hyperplane in 3-space is a plane.
-  *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
-  * \param _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
-  *             Notice that the dimension of the hyperplane is _AmbientDim-1.
-  *
-  * This class represents an hyperplane as the zero set of the implicit equation
-  * \f$ n \cdot x + d = 0 \f$ where \f$ n \f$ is a unit normal vector of the plane (linear part)
-  * and \f$ d \f$ is the distance (offset) to the origin.
-  */
-template <typename _Scalar, int _AmbientDim>
-class Hyperplane
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim==Dynamic ? Dynamic : _AmbientDim+1)
-  enum { AmbientDimAtCompileTime = _AmbientDim };
-  typedef _Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar,AmbientDimAtCompileTime,1> VectorType;
-  typedef Matrix<Scalar,int(AmbientDimAtCompileTime)==Dynamic
-                        ? Dynamic
-                        : int(AmbientDimAtCompileTime)+1,1> Coefficients;
-  typedef Block<Coefficients,AmbientDimAtCompileTime,1> NormalReturnType;
-
-  /** Default constructor without initialization */
-  inline Hyperplane() {}
-
-  /** Constructs a dynamic-size hyperplane with \a _dim the dimension
-    * of the ambient space */
-  inline explicit Hyperplane(int _dim) : m_coeffs(_dim+1) {}
-
-  /** Construct a plane from its normal \a n and a point \a e onto the plane.
-    * \warning the vector normal is assumed to be normalized.
-    */
-  inline Hyperplane(const VectorType& n, const VectorType& e)
-    : m_coeffs(n.size()+1)
-  {
-    normal() = n;
-    offset() = -e.eigen2_dot(n);
-  }
-
-  /** Constructs a plane from its normal \a n and distance to the origin \a d
-    * such that the algebraic equation of the plane is \f$ n \cdot x + d = 0 \f$.
-    * \warning the vector normal is assumed to be normalized.
-    */
-  inline Hyperplane(const VectorType& n, Scalar d)
-    : m_coeffs(n.size()+1)
-  {
-    normal() = n;
-    offset() = d;
-  }
-
-  /** Constructs a hyperplane passing through the two points. If the dimension of the ambient space
-    * is greater than 2, then there isn't uniqueness, so an arbitrary choice is made.
-    */
-  static inline Hyperplane Through(const VectorType& p0, const VectorType& p1)
-  {
-    Hyperplane result(p0.size());
-    result.normal() = (p1 - p0).unitOrthogonal();
-    result.offset() = -result.normal().eigen2_dot(p0);
-    return result;
-  }
-
-  /** Constructs a hyperplane passing through the three points. The dimension of the ambient space
-    * is required to be exactly 3.
-    */
-  static inline Hyperplane Through(const VectorType& p0, const VectorType& p1, const VectorType& p2)
-  {
-    EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(VectorType, 3)
-    Hyperplane result(p0.size());
-    result.normal() = (p2 - p0).cross(p1 - p0).normalized();
-    result.offset() = -result.normal().eigen2_dot(p0);
-    return result;
-  }
-
-  /** Constructs a hyperplane passing through the parametrized line \a parametrized.
-    * If the dimension of the ambient space is greater than 2, then there isn't uniqueness,
-    * so an arbitrary choice is made.
-    */
-  // FIXME to be consitent with the rest this could be implemented as a static Through function ??
-  explicit Hyperplane(const ParametrizedLine<Scalar, AmbientDimAtCompileTime>& parametrized)
-  {
-    normal() = parametrized.direction().unitOrthogonal();
-    offset() = -normal().eigen2_dot(parametrized.origin());
-  }
-
-  ~Hyperplane() {}
-
-  /** \returns the dimension in which the plane holds */
-  inline int dim() const { return int(AmbientDimAtCompileTime)==Dynamic ? m_coeffs.size()-1 : int(AmbientDimAtCompileTime); }
-
-  /** normalizes \c *this */
-  void normalize(void)
-  {
-    m_coeffs /= normal().norm();
-  }
-
-  /** \returns the signed distance between the plane \c *this and a point \a p.
-    * \sa absDistance()
-    */
-  inline Scalar signedDistance(const VectorType& p) const { return p.eigen2_dot(normal()) + offset(); }
-
-  /** \returns the absolute distance between the plane \c *this and a point \a p.
-    * \sa signedDistance()
-    */
-  inline Scalar absDistance(const VectorType& p) const { return ei_abs(signedDistance(p)); }
-
-  /** \returns the projection of a point \a p onto the plane \c *this.
-    */
-  inline VectorType projection(const VectorType& p) const { return p - signedDistance(p) * normal(); }
-
-  /** \returns a constant reference to the unit normal vector of the plane, which corresponds
-    * to the linear part of the implicit equation.
-    */
-  inline const NormalReturnType normal() const { return NormalReturnType(*const_cast<Coefficients*>(&m_coeffs),0,0,dim(),1); }
-
-  /** \returns a non-constant reference to the unit normal vector of the plane, which corresponds
-    * to the linear part of the implicit equation.
-    */
-  inline NormalReturnType normal() { return NormalReturnType(m_coeffs,0,0,dim(),1); }
-
-  /** \returns the distance to the origin, which is also the "constant term" of the implicit equation
-    * \warning the vector normal is assumed to be normalized.
-    */
-  inline const Scalar& offset() const { return m_coeffs.coeff(dim()); }
-
-  /** \returns a non-constant reference to the distance to the origin, which is also the constant part
-    * of the implicit equation */
-  inline Scalar& offset() { return m_coeffs(dim()); }
-
-  /** \returns a constant reference to the coefficients c_i of the plane equation:
-    * \f$ c_0*x_0 + ... + c_{d-1}*x_{d-1} + c_d = 0 \f$
-    */
-  inline const Coefficients& coeffs() const { return m_coeffs; }
-
-  /** \returns a non-constant reference to the coefficients c_i of the plane equation:
-    * \f$ c_0*x_0 + ... + c_{d-1}*x_{d-1} + c_d = 0 \f$
-    */
-  inline Coefficients& coeffs() { return m_coeffs; }
-
-  /** \returns the intersection of *this with \a other.
-    *
-    * \warning The ambient space must be a plane, i.e. have dimension 2, so that \c *this and \a other are lines.
-    *
-    * \note If \a other is approximately parallel to *this, this method will return any point on *this.
-    */
-  VectorType intersection(const Hyperplane& other)
-  {
-    EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(VectorType, 2)
-    Scalar det = coeffs().coeff(0) * other.coeffs().coeff(1) - coeffs().coeff(1) * other.coeffs().coeff(0);
-    // since the line equations ax+by=c are normalized with a^2+b^2=1, the following tests
-    // whether the two lines are approximately parallel.
-    if(ei_isMuchSmallerThan(det, Scalar(1)))
-    {   // special case where the two lines are approximately parallel. Pick any point on the first line.
-        if(ei_abs(coeffs().coeff(1))>ei_abs(coeffs().coeff(0)))
-            return VectorType(coeffs().coeff(1), -coeffs().coeff(2)/coeffs().coeff(1)-coeffs().coeff(0));
-        else
-            return VectorType(-coeffs().coeff(2)/coeffs().coeff(0)-coeffs().coeff(1), coeffs().coeff(0));
-    }
-    else
-    {   // general case
-        Scalar invdet = Scalar(1) / det;
-        return VectorType(invdet*(coeffs().coeff(1)*other.coeffs().coeff(2)-other.coeffs().coeff(1)*coeffs().coeff(2)),
-                          invdet*(other.coeffs().coeff(0)*coeffs().coeff(2)-coeffs().coeff(0)*other.coeffs().coeff(2)));
-    }
-  }
-
-  /** Applies the transformation matrix \a mat to \c *this and returns a reference to \c *this.
-    *
-    * \param mat the Dim x Dim transformation matrix
-    * \param traits specifies whether the matrix \a mat represents an Isometry
-    *               or a more generic Affine transformation. The default is Affine.
-    */
-  template<typename XprType>
-  inline Hyperplane& transform(const MatrixBase<XprType>& mat, TransformTraits traits = Affine)
-  {
-    if (traits==Affine)
-      normal() = mat.inverse().transpose() * normal();
-    else if (traits==Isometry)
-      normal() = mat * normal();
-    else
-    {
-      ei_assert("invalid traits value in Hyperplane::transform()");
-    }
-    return *this;
-  }
-
-  /** Applies the transformation \a t to \c *this and returns a reference to \c *this.
-    *
-    * \param t the transformation of dimension Dim
-    * \param traits specifies whether the transformation \a t represents an Isometry
-    *               or a more generic Affine transformation. The default is Affine.
-    *               Other kind of transformations are not supported.
-    */
-  inline Hyperplane& transform(const Transform<Scalar,AmbientDimAtCompileTime>& t,
-                                TransformTraits traits = Affine)
-  {
-    transform(t.linear(), traits);
-    offset() -= t.translation().eigen2_dot(normal());
-    return *this;
-  }
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<Hyperplane,
-           Hyperplane<NewScalarType,AmbientDimAtCompileTime> >::type cast() const
-  {
-    return typename internal::cast_return_type<Hyperplane,
-                    Hyperplane<NewScalarType,AmbientDimAtCompileTime> >::type(*this);
-  }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit Hyperplane(const Hyperplane<OtherScalarType,AmbientDimAtCompileTime>& other)
-  { m_coeffs = other.coeffs().template cast<Scalar>(); }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const Hyperplane& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return m_coeffs.isApprox(other.m_coeffs, prec); }
-
-protected:
-
-  Coefficients m_coeffs;
-};
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
@@ -1,141 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-/** \geometry_module \ingroup Geometry_Module
-  *
-  * \class ParametrizedLine
-  *
-  * \brief A parametrized line
-  *
-  * A parametrized line is defined by an origin point \f$ \mathbf{o} \f$ and a unit
-  * direction vector \f$ \mathbf{d} \f$ such that the line corresponds to
-  * the set \f$ l(t) = \mathbf{o} + t \mathbf{d} \f$, \f$ l \in \mathbf{R} \f$.
-  *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
-  * \param _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
-  */
-template <typename _Scalar, int _AmbientDim>
-class ParametrizedLine
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
-  enum { AmbientDimAtCompileTime = _AmbientDim };
-  typedef _Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar,AmbientDimAtCompileTime,1> VectorType;
-
-  /** Default constructor without initialization */
-  inline ParametrizedLine() {}
-
-  /** Constructs a dynamic-size line with \a _dim the dimension
-    * of the ambient space */
-  inline explicit ParametrizedLine(int _dim) : m_origin(_dim), m_direction(_dim) {}
-
-  /** Initializes a parametrized line of direction \a direction and origin \a origin.
-    * \warning the vector direction is assumed to be normalized.
-    */
-  ParametrizedLine(const VectorType& origin, const VectorType& direction)
-    : m_origin(origin), m_direction(direction) {}
-
-  explicit ParametrizedLine(const Hyperplane<_Scalar, _AmbientDim>& hyperplane);
-
-  /** Constructs a parametrized line going from \a p0 to \a p1. */
-  static inline ParametrizedLine Through(const VectorType& p0, const VectorType& p1)
-  { return ParametrizedLine(p0, (p1-p0).normalized()); }
-
-  ~ParametrizedLine() {}
-
-  /** \returns the dimension in which the line holds */
-  inline int dim() const { return m_direction.size(); }
-
-  const VectorType& origin() const { return m_origin; }
-  VectorType& origin() { return m_origin; }
-
-  const VectorType& direction() const { return m_direction; }
-  VectorType& direction() { return m_direction; }
-
-  /** \returns the squared distance of a point \a p to its projection onto the line \c *this.
-    * \sa distance()
-    */
-  RealScalar squaredDistance(const VectorType& p) const
-  {
-    VectorType diff = p-origin();
-    return (diff - diff.eigen2_dot(direction())* direction()).squaredNorm();
-  }
-  /** \returns the distance of a point \a p to its projection onto the line \c *this.
-    * \sa squaredDistance()
-    */
-  RealScalar distance(const VectorType& p) const { return ei_sqrt(squaredDistance(p)); }
-
-  /** \returns the projection of a point \a p onto the line \c *this. */
-  VectorType projection(const VectorType& p) const
-  { return origin() + (p-origin()).eigen2_dot(direction()) * direction(); }
-
-  Scalar intersection(const Hyperplane<_Scalar, _AmbientDim>& hyperplane);
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<ParametrizedLine,
-           ParametrizedLine<NewScalarType,AmbientDimAtCompileTime> >::type cast() const
-  {
-    return typename internal::cast_return_type<ParametrizedLine,
-                    ParametrizedLine<NewScalarType,AmbientDimAtCompileTime> >::type(*this);
-  }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit ParametrizedLine(const ParametrizedLine<OtherScalarType,AmbientDimAtCompileTime>& other)
-  {
-    m_origin = other.origin().template cast<Scalar>();
-    m_direction = other.direction().template cast<Scalar>();
-  }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const ParametrizedLine& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return m_origin.isApprox(other.m_origin, prec) && m_direction.isApprox(other.m_direction, prec); }
-
-protected:
-
-  VectorType m_origin, m_direction;
-};
-
-/** Constructs a parametrized line from a 2D hyperplane
-  *
-  * \warning the ambient space must have dimension 2 such that the hyperplane actually describes a line
-  */
-template <typename _Scalar, int _AmbientDim>
-inline ParametrizedLine<_Scalar, _AmbientDim>::ParametrizedLine(const Hyperplane<_Scalar, _AmbientDim>& hyperplane)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(VectorType, 2)
-  direction() = hyperplane.normal().unitOrthogonal();
-  origin() = -hyperplane.normal()*hyperplane.offset();
-}
-
-/** \returns the parameter value of the intersection between \c *this and the given hyperplane
-  */
-template <typename _Scalar, int _AmbientDim>
-inline _Scalar ParametrizedLine<_Scalar, _AmbientDim>::intersection(const Hyperplane<_Scalar, _AmbientDim>& hyperplane)
-{
-  return -(hyperplane.offset()+origin().eigen2_dot(hyperplane.normal()))
-          /(direction().eigen2_dot(hyperplane.normal()));
-}
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h
@@ -1,495 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-template<typename Other,
-         int OtherRows=Other::RowsAtCompileTime,
-         int OtherCols=Other::ColsAtCompileTime>
-struct ei_quaternion_assign_impl;
-
-/** \geometry_module \ingroup Geometry_Module
-  *
-  * \class Quaternion
-  *
-  * \brief The quaternion class used to represent 3D orientations and rotations
-  *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
-  *
-  * This class represents a quaternion \f$ w+xi+yj+zk \f$ that is a convenient representation of
-  * orientations and rotations of objects in three dimensions. Compared to other representations
-  * like Euler angles or 3x3 matrices, quatertions offer the following advantages:
-  * \li \b compact storage (4 scalars)
-  * \li \b efficient to compose (28 flops),
-  * \li \b stable spherical interpolation
-  *
-  * The following two typedefs are provided for convenience:
-  * \li \c Quaternionf for \c float
-  * \li \c Quaterniond for \c double
-  *
-  * \sa  class AngleAxis, class Transform
-  */
-
-template<typename _Scalar> struct ei_traits<Quaternion<_Scalar> >
-{
-  typedef _Scalar Scalar;
-};
-
-template<typename _Scalar>
-class Quaternion : public RotationBase<Quaternion<_Scalar>,3>
-{
-  typedef RotationBase<Quaternion<_Scalar>,3> Base;
-
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,4)
-
-  using Base::operator*;
-
-  /** the scalar type of the coefficients */
-  typedef _Scalar Scalar;
-
-  /** the type of the Coefficients 4-vector */
-  typedef Matrix<Scalar, 4, 1> Coefficients;
-  /** the type of a 3D vector */
-  typedef Matrix<Scalar,3,1> Vector3;
-  /** the equivalent rotation matrix type */
-  typedef Matrix<Scalar,3,3> Matrix3;
-  /** the equivalent angle-axis type */
-  typedef AngleAxis<Scalar> AngleAxisType;
-
-  /** \returns the \c x coefficient */
-  inline Scalar x() const { return m_coeffs.coeff(0); }
-  /** \returns the \c y coefficient */
-  inline Scalar y() const { return m_coeffs.coeff(1); }
-  /** \returns the \c z coefficient */
-  inline Scalar z() const { return m_coeffs.coeff(2); }
-  /** \returns the \c w coefficient */
-  inline Scalar w() const { return m_coeffs.coeff(3); }
-
-  /** \returns a reference to the \c x coefficient */
-  inline Scalar& x() { return m_coeffs.coeffRef(0); }
-  /** \returns a reference to the \c y coefficient */
-  inline Scalar& y() { return m_coeffs.coeffRef(1); }
-  /** \returns a reference to the \c z coefficient */
-  inline Scalar& z() { return m_coeffs.coeffRef(2); }
-  /** \returns a reference to the \c w coefficient */
-  inline Scalar& w() { return m_coeffs.coeffRef(3); }
-
-  /** \returns a read-only vector expression of the imaginary part (x,y,z) */
-  inline const Block<const Coefficients,3,1> vec() const { return m_coeffs.template start<3>(); }
-
-  /** \returns a vector expression of the imaginary part (x,y,z) */
-  inline Block<Coefficients,3,1> vec() { return m_coeffs.template start<3>(); }
-
-  /** \returns a read-only vector expression of the coefficients (x,y,z,w) */
-  inline const Coefficients& coeffs() const { return m_coeffs; }
-
-  /** \returns a vector expression of the coefficients (x,y,z,w) */
-  inline Coefficients& coeffs() { return m_coeffs; }
-
-  /** Default constructor leaving the quaternion uninitialized. */
-  inline Quaternion() {}
-
-  /** Constructs and initializes the quaternion \f$ w+xi+yj+zk \f$ from
-    * its four coefficients \a w, \a x, \a y and \a z.
-    *
-    * \warning Note the order of the arguments: the real \a w coefficient first,
-    * while internally the coefficients are stored in the following order:
-    * [\c x, \c y, \c z, \c w]
-    */
-  inline Quaternion(Scalar w, Scalar x, Scalar y, Scalar z)
-  { m_coeffs << x, y, z, w; }
-
-  /** Copy constructor */
-  inline Quaternion(const Quaternion& other) { m_coeffs = other.m_coeffs; }
-
-  /** Constructs and initializes a quaternion from the angle-axis \a aa */
-  explicit inline Quaternion(const AngleAxisType& aa) { *this = aa; }
-
-  /** Constructs and initializes a quaternion from either:
-    *  - a rotation matrix expression,
-    *  - a 4D vector expression representing quaternion coefficients.
-    * \sa operator=(MatrixBase<Derived>)
-    */
-  template<typename Derived>
-  explicit inline Quaternion(const MatrixBase<Derived>& other) { *this = other; }
-
-  Quaternion& operator=(const Quaternion& other);
-  Quaternion& operator=(const AngleAxisType& aa);
-  template<typename Derived>
-  Quaternion& operator=(const MatrixBase<Derived>& m);
-
-  /** \returns a quaternion representing an identity rotation
-    * \sa MatrixBase::Identity()
-    */
-  static inline Quaternion Identity() { return Quaternion(1, 0, 0, 0); }
-
-  /** \sa Quaternion::Identity(), MatrixBase::setIdentity()
-    */
-  inline Quaternion& setIdentity() { m_coeffs << 0, 0, 0, 1; return *this; }
-
-  /** \returns the squared norm of the quaternion's coefficients
-    * \sa Quaternion::norm(), MatrixBase::squaredNorm()
-    */
-  inline Scalar squaredNorm() const { return m_coeffs.squaredNorm(); }
-
-  /** \returns the norm of the quaternion's coefficients
-    * \sa Quaternion::squaredNorm(), MatrixBase::norm()
-    */
-  inline Scalar norm() const { return m_coeffs.norm(); }
-
-  /** Normalizes the quaternion \c *this
-    * \sa normalized(), MatrixBase::normalize() */
-  inline void normalize() { m_coeffs.normalize(); }
-  /** \returns a normalized version of \c *this
-    * \sa normalize(), MatrixBase::normalized() */
-  inline Quaternion normalized() const { return Quaternion(m_coeffs.normalized()); }
-
-  /** \returns the dot product of \c *this and \a other
-    * Geometrically speaking, the dot product of two unit quaternions
-    * corresponds to the cosine of half the angle between the two rotations.
-    * \sa angularDistance()
-    */
-  inline Scalar eigen2_dot(const Quaternion& other) const { return m_coeffs.eigen2_dot(other.m_coeffs); }
-
-  inline Scalar angularDistance(const Quaternion& other) const;
-
-  Matrix3 toRotationMatrix(void) const;
-
-  template<typename Derived1, typename Derived2>
-  Quaternion& setFromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b);
-
-  inline Quaternion operator* (const Quaternion& q) const;
-  inline Quaternion& operator*= (const Quaternion& q);
-
-  Quaternion inverse(void) const;
-  Quaternion conjugate(void) const;
-
-  Quaternion slerp(Scalar t, const Quaternion& other) const;
-
-  template<typename Derived>
-  Vector3 operator* (const MatrixBase<Derived>& vec) const;
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<Quaternion,Quaternion<NewScalarType> >::type cast() const
-  { return typename internal::cast_return_type<Quaternion,Quaternion<NewScalarType> >::type(*this); }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit Quaternion(const Quaternion<OtherScalarType>& other)
-  { m_coeffs = other.coeffs().template cast<Scalar>(); }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const Quaternion& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return m_coeffs.isApprox(other.m_coeffs, prec); }
-
-protected:
-  Coefficients m_coeffs;
-};
-
-/** \ingroup Geometry_Module
-  * single precision quaternion type */
-typedef Quaternion<float> Quaternionf;
-/** \ingroup Geometry_Module
-  * double precision quaternion type */
-typedef Quaternion<double> Quaterniond;
-
-// Generic Quaternion * Quaternion product
-template<typename Scalar> inline Quaternion<Scalar>
-ei_quaternion_product(const Quaternion<Scalar>& a, const Quaternion<Scalar>& b)
-{
-  return Quaternion<Scalar>
-  (
-    a.w() * b.w() - a.x() * b.x() - a.y() * b.y() - a.z() * b.z(),
-    a.w() * b.x() + a.x() * b.w() + a.y() * b.z() - a.z() * b.y(),
-    a.w() * b.y() + a.y() * b.w() + a.z() * b.x() - a.x() * b.z(),
-    a.w() * b.z() + a.z() * b.w() + a.x() * b.y() - a.y() * b.x()
-  );
-}
-
-/** \returns the concatenation of two rotations as a quaternion-quaternion product */
-template <typename Scalar>
-inline Quaternion<Scalar> Quaternion<Scalar>::operator* (const Quaternion& other) const
-{
-  return ei_quaternion_product(*this,other);
-}
-
-/** \sa operator*(Quaternion) */
-template <typename Scalar>
-inline Quaternion<Scalar>& Quaternion<Scalar>::operator*= (const Quaternion& other)
-{
-  return (*this = *this * other);
-}
-
-/** Rotation of a vector by a quaternion.
-  * \remarks If the quaternion is used to rotate several points (>1)
-  * then it is much more efficient to first convert it to a 3x3 Matrix.
-  * Comparison of the operation cost for n transformations:
-  *   - Quaternion:    30n
-  *   - Via a Matrix3: 24 + 15n
-  */
-template <typename Scalar>
-template<typename Derived>
-inline typename Quaternion<Scalar>::Vector3
-Quaternion<Scalar>::operator* (const MatrixBase<Derived>& v) const
-{
-    // Note that this algorithm comes from the optimization by hand
-    // of the conversion to a Matrix followed by a Matrix/Vector product.
-    // It appears to be much faster than the common algorithm found
-    // in the litterature (30 versus 39 flops). It also requires two
-    // Vector3 as temporaries.
-    Vector3 uv;
-    uv = 2 * this->vec().cross(v);
-    return v + this->w() * uv + this->vec().cross(uv);
-}
-
-template<typename Scalar>
-inline Quaternion<Scalar>& Quaternion<Scalar>::operator=(const Quaternion& other)
-{
-  m_coeffs = other.m_coeffs;
-  return *this;
-}
-
-/** Set \c *this from an angle-axis \a aa and returns a reference to \c *this
-  */
-template<typename Scalar>
-inline Quaternion<Scalar>& Quaternion<Scalar>::operator=(const AngleAxisType& aa)
-{
-  Scalar ha = Scalar(0.5)*aa.angle(); // Scalar(0.5) to suppress precision loss warnings
-  this->w() = ei_cos(ha);
-  this->vec() = ei_sin(ha) * aa.axis();
-  return *this;
-}
-
-/** Set \c *this from the expression \a xpr:
-  *   - if \a xpr is a 4x1 vector, then \a xpr is assumed to be a quaternion
-  *   - if \a xpr is a 3x3 matrix, then \a xpr is assumed to be rotation matrix
-  *     and \a xpr is converted to a quaternion
-  */
-template<typename Scalar>
-template<typename Derived>
-inline Quaternion<Scalar>& Quaternion<Scalar>::operator=(const MatrixBase<Derived>& xpr)
-{
-  ei_quaternion_assign_impl<Derived>::run(*this, xpr.derived());
-  return *this;
-}
-
-/** Convert the quaternion to a 3x3 rotation matrix */
-template<typename Scalar>
-inline typename Quaternion<Scalar>::Matrix3
-Quaternion<Scalar>::toRotationMatrix(void) const
-{
-  // NOTE if inlined, then gcc 4.2 and 4.4 get rid of the temporary (not gcc 4.3 !!)
-  // if not inlined then the cost of the return by value is huge ~ +35%,
-  // however, not inlining this function is an order of magnitude slower, so
-  // it has to be inlined, and so the return by value is not an issue
-  Matrix3 res;
-
-  const Scalar tx  = Scalar(2)*this->x();
-  const Scalar ty  = Scalar(2)*this->y();
-  const Scalar tz  = Scalar(2)*this->z();
-  const Scalar twx = tx*this->w();
-  const Scalar twy = ty*this->w();
-  const Scalar twz = tz*this->w();
-  const Scalar txx = tx*this->x();
-  const Scalar txy = ty*this->x();
-  const Scalar txz = tz*this->x();
-  const Scalar tyy = ty*this->y();
-  const Scalar tyz = tz*this->y();
-  const Scalar tzz = tz*this->z();
-
-  res.coeffRef(0,0) = Scalar(1)-(tyy+tzz);
-  res.coeffRef(0,1) = txy-twz;
-  res.coeffRef(0,2) = txz+twy;
-  res.coeffRef(1,0) = txy+twz;
-  res.coeffRef(1,1) = Scalar(1)-(txx+tzz);
-  res.coeffRef(1,2) = tyz-twx;
-  res.coeffRef(2,0) = txz-twy;
-  res.coeffRef(2,1) = tyz+twx;
-  res.coeffRef(2,2) = Scalar(1)-(txx+tyy);
-
-  return res;
-}
-
-/** Sets *this to be a quaternion representing a rotation sending the vector \a a to the vector \a b.
-  *
-  * \returns a reference to *this.
-  *
-  * Note that the two input vectors do \b not have to be normalized.
-  */
-template<typename Scalar>
-template<typename Derived1, typename Derived2>
-inline Quaternion<Scalar>& Quaternion<Scalar>::setFromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b)
-{
-  Vector3 v0 = a.normalized();
-  Vector3 v1 = b.normalized();
-  Scalar c = v0.eigen2_dot(v1);
-
-  // if dot == 1, vectors are the same
-  if (ei_isApprox(c,Scalar(1)))
-  {
-    // set to identity
-    this->w() = 1; this->vec().setZero();
-    return *this;
-  }
-  // if dot == -1, vectors are opposites
-  if (ei_isApprox(c,Scalar(-1)))
-  {
-    this->vec() = v0.unitOrthogonal();
-    this->w() = 0;
-    return *this;
-  }
-
-  Vector3 axis = v0.cross(v1);
-  Scalar s = ei_sqrt((Scalar(1)+c)*Scalar(2));
-  Scalar invs = Scalar(1)/s;
-  this->vec() = axis * invs;
-  this->w() = s * Scalar(0.5);
-
-  return *this;
-}
-
-/** \returns the multiplicative inverse of \c *this
-  * Note that in most cases, i.e., if you simply want the opposite rotation,
-  * and/or the quaternion is normalized, then it is enough to use the conjugate.
-  *
-  * \sa Quaternion::conjugate()
-  */
-template <typename Scalar>
-inline Quaternion<Scalar> Quaternion<Scalar>::inverse() const
-{
-  // FIXME should this function be called multiplicativeInverse and conjugate() be called inverse() or opposite()  ??
-  Scalar n2 = this->squaredNorm();
-  if (n2 > 0)
-    return Quaternion(conjugate().coeffs() / n2);
-  else
-  {
-    // return an invalid result to flag the error
-    return Quaternion(Coefficients::Zero());
-  }
-}
-
-/** \returns the conjugate of the \c *this which is equal to the multiplicative inverse
-  * if the quaternion is normalized.
-  * The conjugate of a quaternion represents the opposite rotation.
-  *
-  * \sa Quaternion::inverse()
-  */
-template <typename Scalar>
-inline Quaternion<Scalar> Quaternion<Scalar>::conjugate() const
-{
-  return Quaternion(this->w(),-this->x(),-this->y(),-this->z());
-}
-
-/** \returns the angle (in radian) between two rotations
-  * \sa eigen2_dot()
-  */
-template <typename Scalar>
-inline Scalar Quaternion<Scalar>::angularDistance(const Quaternion& other) const
-{
-  double d = ei_abs(this->eigen2_dot(other));
-  if (d>=1.0)
-    return 0;
-  return Scalar(2) * std::acos(d);
-}
-
-/** \returns the spherical linear interpolation between the two quaternions
-  * \c *this and \a other at the parameter \a t
-  */
-template <typename Scalar>
-Quaternion<Scalar> Quaternion<Scalar>::slerp(Scalar t, const Quaternion& other) const
-{
-  static const Scalar one = Scalar(1) - machine_epsilon<Scalar>();
-  Scalar d = this->eigen2_dot(other);
-  Scalar absD = ei_abs(d);
-
-  Scalar scale0;
-  Scalar scale1;
-
-  if (absD>=one)
-  {
-    scale0 = Scalar(1) - t;
-    scale1 = t;
-  }
-  else
-  {
-    // theta is the angle between the 2 quaternions
-    Scalar theta = std::acos(absD);
-    Scalar sinTheta = ei_sin(theta);
-
-    scale0 = ei_sin( ( Scalar(1) - t ) * theta) / sinTheta;
-    scale1 = ei_sin( ( t * theta) ) / sinTheta;
-    if (d<0)
-      scale1 = -scale1;
-  }
-
-  return Quaternion<Scalar>(scale0 * coeffs() + scale1 * other.coeffs());
-}
-
-// set from a rotation matrix
-template<typename Other>
-struct ei_quaternion_assign_impl<Other,3,3>
-{
-  typedef typename Other::Scalar Scalar;
-  static inline void run(Quaternion<Scalar>& q, const Other& mat)
-  {
-    // This algorithm comes from  "Quaternion Calculus and Fast Animation",
-    // Ken Shoemake, 1987 SIGGRAPH course notes
-    Scalar t = mat.trace();
-    if (t > 0)
-    {
-      t = ei_sqrt(t + Scalar(1.0));
-      q.w() = Scalar(0.5)*t;
-      t = Scalar(0.5)/t;
-      q.x() = (mat.coeff(2,1) - mat.coeff(1,2)) * t;
-      q.y() = (mat.coeff(0,2) - mat.coeff(2,0)) * t;
-      q.z() = (mat.coeff(1,0) - mat.coeff(0,1)) * t;
-    }
-    else
-    {
-      int i = 0;
-      if (mat.coeff(1,1) > mat.coeff(0,0))
-        i = 1;
-      if (mat.coeff(2,2) > mat.coeff(i,i))
-        i = 2;
-      int j = (i+1)%3;
-      int k = (j+1)%3;
-
-      t = ei_sqrt(mat.coeff(i,i)-mat.coeff(j,j)-mat.coeff(k,k) + Scalar(1.0));
-      q.coeffs().coeffRef(i) = Scalar(0.5) * t;
-      t = Scalar(0.5)/t;
-      q.w() = (mat.coeff(k,j)-mat.coeff(j,k))*t;
-      q.coeffs().coeffRef(j) = (mat.coeff(j,i)+mat.coeff(i,j))*t;
-      q.coeffs().coeffRef(k) = (mat.coeff(k,i)+mat.coeff(i,k))*t;
-    }
-  }
-};
-
-// set from a vector of coefficients assumed to be a quaternion
-template<typename Other>
-struct ei_quaternion_assign_impl<Other,4,1>
-{
-  typedef typename Other::Scalar Scalar;
-  static inline void run(Quaternion<Scalar>& q, const Other& vec)
-  {
-    q.coeffs() = vec;
-  }
-};
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
@@ -1,145 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-/** \geometry_module \ingroup Geometry_Module
-  *
-  * \class Rotation2D
-  *
-  * \brief Represents a rotation/orientation in a 2 dimensional space.
-  *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
-  *
-  * This class is equivalent to a single scalar representing a counter clock wise rotation
-  * as a single angle in radian. It provides some additional features such as the automatic
-  * conversion from/to a 2x2 rotation matrix. Moreover this class aims to provide a similar
-  * interface to Quaternion in order to facilitate the writing of generic algorithms
-  * dealing with rotations.
-  *
-  * \sa class Quaternion, class Transform
-  */
-template<typename _Scalar> struct ei_traits<Rotation2D<_Scalar> >
-{
-  typedef _Scalar Scalar;
-};
-
-template<typename _Scalar>
-class Rotation2D : public RotationBase<Rotation2D<_Scalar>,2>
-{
-  typedef RotationBase<Rotation2D<_Scalar>,2> Base;
-
-public:
-
-  using Base::operator*;
-
-  enum { Dim = 2 };
-  /** the scalar type of the coefficients */
-  typedef _Scalar Scalar;
-  typedef Matrix<Scalar,2,1> Vector2;
-  typedef Matrix<Scalar,2,2> Matrix2;
-
-protected:
-
-  Scalar m_angle;
-
-public:
-
-  /** Construct a 2D counter clock wise rotation from the angle \a a in radian. */
-  inline Rotation2D(Scalar a) : m_angle(a) {}
-
-  /** \returns the rotation angle */
-  inline Scalar angle() const { return m_angle; }
-
-  /** \returns a read-write reference to the rotation angle */
-  inline Scalar& angle() { return m_angle; }
-
-  /** \returns the inverse rotation */
-  inline Rotation2D inverse() const { return -m_angle; }
-
-  /** Concatenates two rotations */
-  inline Rotation2D operator*(const Rotation2D& other) const
-  { return m_angle + other.m_angle; }
-
-  /** Concatenates two rotations */
-  inline Rotation2D& operator*=(const Rotation2D& other)
-  { return m_angle += other.m_angle; return *this; }
-
-  /** Applies the rotation to a 2D vector */
-  Vector2 operator* (const Vector2& vec) const
-  { return toRotationMatrix() * vec; }
-
-  template<typename Derived>
-  Rotation2D& fromRotationMatrix(const MatrixBase<Derived>& m);
-  Matrix2 toRotationMatrix(void) const;
-
-  /** \returns the spherical interpolation between \c *this and \a other using
-    * parameter \a t. It is in fact equivalent to a linear interpolation.
-    */
-  inline Rotation2D slerp(Scalar t, const Rotation2D& other) const
-  { return m_angle * (1-t) + other.angle() * t; }
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<Rotation2D,Rotation2D<NewScalarType> >::type cast() const
-  { return typename internal::cast_return_type<Rotation2D,Rotation2D<NewScalarType> >::type(*this); }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit Rotation2D(const Rotation2D<OtherScalarType>& other)
-  {
-    m_angle = Scalar(other.angle());
-  }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const Rotation2D& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return ei_isApprox(m_angle,other.m_angle, prec); }
-};
-
-/** \ingroup Geometry_Module
-  * single precision 2D rotation type */
-typedef Rotation2D<float> Rotation2Df;
-/** \ingroup Geometry_Module
-  * double precision 2D rotation type */
-typedef Rotation2D<double> Rotation2Dd;
-
-/** Set \c *this from a 2x2 rotation matrix \a mat.
-  * In other words, this function extract the rotation angle
-  * from the rotation matrix.
-  */
-template<typename Scalar>
-template<typename Derived>
-Rotation2D<Scalar>& Rotation2D<Scalar>::fromRotationMatrix(const MatrixBase<Derived>& mat)
-{
-  EIGEN_STATIC_ASSERT(Derived::RowsAtCompileTime==2 && Derived::ColsAtCompileTime==2,YOU_MADE_A_PROGRAMMING_MISTAKE)
-  m_angle = ei_atan2(mat.coeff(1,0), mat.coeff(0,0));
-  return *this;
-}
-
-/** Constructs and \returns an equivalent 2x2 rotation matrix.
-  */
-template<typename Scalar>
-typename Rotation2D<Scalar>::Matrix2
-Rotation2D<Scalar>::toRotationMatrix(void) const
-{
-  Scalar sinA = ei_sin(m_angle);
-  Scalar cosA = ei_cos(m_angle);
-  return (Matrix2() << cosA, -sinA, sinA, cosA).finished();
-}
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h
@@ -1,123 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-// this file aims to contains the various representations of rotation/orientation
-// in 2D and 3D space excepted Matrix and Quaternion.
-
-/** \class RotationBase
-  *
-  * \brief Common base class for compact rotation representations
-  *
-  * \param Derived is the derived type, i.e., a rotation type
-  * \param _Dim the dimension of the space
-  */
-template<typename Derived, int _Dim>
-class RotationBase
-{
-  public:
-    enum { Dim = _Dim };
-    /** the scalar type of the coefficients */
-    typedef typename ei_traits<Derived>::Scalar Scalar;
-    
-    /** corresponding linear transformation matrix type */
-    typedef Matrix<Scalar,Dim,Dim> RotationMatrixType;
-
-    inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
-    inline Derived& derived() { return *static_cast<Derived*>(this); }
-
-    /** \returns an equivalent rotation matrix */
-    inline RotationMatrixType toRotationMatrix() const { return derived().toRotationMatrix(); }
-
-    /** \returns the inverse rotation */
-    inline Derived inverse() const { return derived().inverse(); }
-
-    /** \returns the concatenation of the rotation \c *this with a translation \a t */
-    inline Transform<Scalar,Dim> operator*(const Translation<Scalar,Dim>& t) const
-    { return toRotationMatrix() * t; }
-
-    /** \returns the concatenation of the rotation \c *this with a scaling \a s */
-    inline RotationMatrixType operator*(const Scaling<Scalar,Dim>& s) const
-    { return toRotationMatrix() * s; }
-
-    /** \returns the concatenation of the rotation \c *this with an affine transformation \a t */
-    inline Transform<Scalar,Dim> operator*(const Transform<Scalar,Dim>& t) const
-    { return toRotationMatrix() * t; }
-};
-
-/** \geometry_module
-  *
-  * Constructs a Dim x Dim rotation matrix from the rotation \a r
-  */
-template<typename _Scalar, int _Rows, int _Cols, int _Storage, int _MaxRows, int _MaxCols>
-template<typename OtherDerived>
-Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>
-::Matrix(const RotationBase<OtherDerived,ColsAtCompileTime>& r)
-{
-  EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(Matrix,int(OtherDerived::Dim),int(OtherDerived::Dim))
-  *this = r.toRotationMatrix();
-}
-
-/** \geometry_module
-  *
-  * Set a Dim x Dim rotation matrix from the rotation \a r
-  */
-template<typename _Scalar, int _Rows, int _Cols, int _Storage, int _MaxRows, int _MaxCols>
-template<typename OtherDerived>
-Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>
-::operator=(const RotationBase<OtherDerived,ColsAtCompileTime>& r)
-{
-  EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(Matrix,int(OtherDerived::Dim),int(OtherDerived::Dim))
-  return *this = r.toRotationMatrix();
-}
-
-/** \internal
-  *
-  * Helper function to return an arbitrary rotation object to a rotation matrix.
-  *
-  * \param Scalar the numeric type of the matrix coefficients
-  * \param Dim the dimension of the current space
-  *
-  * It returns a Dim x Dim fixed size matrix.
-  *
-  * Default specializations are provided for:
-  *   - any scalar type (2D),
-  *   - any matrix expression,
-  *   - any type based on RotationBase (e.g., Quaternion, AngleAxis, Rotation2D)
-  *
-  * Currently ei_toRotationMatrix is only used by Transform.
-  *
-  * \sa class Transform, class Rotation2D, class Quaternion, class AngleAxis
-  */
-template<typename Scalar, int Dim>
-static inline Matrix<Scalar,2,2> ei_toRotationMatrix(const Scalar& s)
-{
-  EIGEN_STATIC_ASSERT(Dim==2,YOU_MADE_A_PROGRAMMING_MISTAKE)
-  return Rotation2D<Scalar>(s).toRotationMatrix();
-}
-
-template<typename Scalar, int Dim, typename OtherDerived>
-static inline Matrix<Scalar,Dim,Dim> ei_toRotationMatrix(const RotationBase<OtherDerived,Dim>& r)
-{
-  return r.toRotationMatrix();
-}
-
-template<typename Scalar, int Dim, typename OtherDerived>
-static inline const MatrixBase<OtherDerived>& ei_toRotationMatrix(const MatrixBase<OtherDerived>& mat)
-{
-  EIGEN_STATIC_ASSERT(OtherDerived::RowsAtCompileTime==Dim && OtherDerived::ColsAtCompileTime==Dim,
-    YOU_MADE_A_PROGRAMMING_MISTAKE)
-  return mat;
-}
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h
@@ -1,167 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-/** \geometry_module \ingroup Geometry_Module
-  *
-  * \class Scaling
-  *
-  * \brief Represents a possibly non uniform scaling transformation
-  *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients.
-  * \param _Dim the  dimension of the space, can be a compile time value or Dynamic
-  *
-  * \note This class is not aimed to be used to store a scaling transformation,
-  * but rather to make easier the constructions and updates of Transform objects.
-  *
-  * \sa class Translation, class Transform
-  */
-template<typename _Scalar, int _Dim>
-class Scaling
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_Dim)
-  /** dimension of the space */
-  enum { Dim = _Dim };
-  /** the scalar type of the coefficients */
-  typedef _Scalar Scalar;
-  /** corresponding vector type */
-  typedef Matrix<Scalar,Dim,1> VectorType;
-  /** corresponding linear transformation matrix type */
-  typedef Matrix<Scalar,Dim,Dim> LinearMatrixType;
-  /** corresponding translation type */
-  typedef Translation<Scalar,Dim> TranslationType;
-  /** corresponding affine transformation type */
-  typedef Transform<Scalar,Dim> TransformType;
-
-protected:
-
-  VectorType m_coeffs;
-
-public:
-
-  /** Default constructor without initialization. */
-  Scaling() {}
-  /** Constructs and initialize a uniform scaling transformation */
-  explicit inline Scaling(const Scalar& s) { m_coeffs.setConstant(s); }
-  /** 2D only */
-  inline Scaling(const Scalar& sx, const Scalar& sy)
-  {
-    ei_assert(Dim==2);
-    m_coeffs.x() = sx;
-    m_coeffs.y() = sy;
-  }
-  /** 3D only */
-  inline Scaling(const Scalar& sx, const Scalar& sy, const Scalar& sz)
-  {
-    ei_assert(Dim==3);
-    m_coeffs.x() = sx;
-    m_coeffs.y() = sy;
-    m_coeffs.z() = sz;
-  }
-  /** Constructs and initialize the scaling transformation from a vector of scaling coefficients */
-  explicit inline Scaling(const VectorType& coeffs) : m_coeffs(coeffs) {}
-
-  const VectorType& coeffs() const { return m_coeffs; }
-  VectorType& coeffs() { return m_coeffs; }
-
-  /** Concatenates two scaling */
-  inline Scaling operator* (const Scaling& other) const
-  { return Scaling(coeffs().cwise() * other.coeffs()); }
-
-  /** Concatenates a scaling and a translation */
-  inline TransformType operator* (const TranslationType& t) const;
-
-  /** Concatenates a scaling and an affine transformation */
-  inline TransformType operator* (const TransformType& t) const;
-
-  /** Concatenates a scaling and a linear transformation matrix */
-  // TODO returns an expression
-  inline LinearMatrixType operator* (const LinearMatrixType& other) const
-  { return coeffs().asDiagonal() * other; }
-
-  /** Concatenates a linear transformation matrix and a scaling */
-  // TODO returns an expression
-  friend inline LinearMatrixType operator* (const LinearMatrixType& other, const Scaling& s)
-  { return other * s.coeffs().asDiagonal(); }
-
-  template<typename Derived>
-  inline LinearMatrixType operator*(const RotationBase<Derived,Dim>& r) const
-  { return *this * r.toRotationMatrix(); }
-
-  /** Applies scaling to vector */
-  inline VectorType operator* (const VectorType& other) const
-  { return coeffs().asDiagonal() * other; }
-
-  /** \returns the inverse scaling */
-  inline Scaling inverse() const
-  { return Scaling(coeffs().cwise().inverse()); }
-
-  inline Scaling& operator=(const Scaling& other)
-  {
-    m_coeffs = other.m_coeffs;
-    return *this;
-  }
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<Scaling,Scaling<NewScalarType,Dim> >::type cast() const
-  { return typename internal::cast_return_type<Scaling,Scaling<NewScalarType,Dim> >::type(*this); }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit Scaling(const Scaling<OtherScalarType,Dim>& other)
-  { m_coeffs = other.coeffs().template cast<Scalar>(); }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const Scaling& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return m_coeffs.isApprox(other.m_coeffs, prec); }
-
-};
-
-/** \addtogroup Geometry_Module */
-//@{
-typedef Scaling<float, 2> Scaling2f;
-typedef Scaling<double,2> Scaling2d;
-typedef Scaling<float, 3> Scaling3f;
-typedef Scaling<double,3> Scaling3d;
-//@}
-
-template<typename Scalar, int Dim>
-inline typename Scaling<Scalar,Dim>::TransformType
-Scaling<Scalar,Dim>::operator* (const TranslationType& t) const
-{
-  TransformType res;
-  res.matrix().setZero();
-  res.linear().diagonal() = coeffs();
-  res.translation() = m_coeffs.cwise() * t.vector();
-  res(Dim,Dim) = Scalar(1);
-  return res;
-}
-
-template<typename Scalar, int Dim>
-inline typename Scaling<Scalar,Dim>::TransformType
-Scaling<Scalar,Dim>::operator* (const TransformType& t) const
-{
-  TransformType res = t;
-  res.prescale(m_coeffs);
-  return res;
-}
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h
@@ -1,786 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-// Note that we have to pass Dim and HDim because it is not allowed to use a template
-// parameter to define a template specialization. To be more precise, in the following
-// specializations, it is not allowed to use Dim+1 instead of HDim.
-template< typename Other,
-          int Dim,
-          int HDim,
-          int OtherRows=Other::RowsAtCompileTime,
-          int OtherCols=Other::ColsAtCompileTime>
-struct ei_transform_product_impl;
-
-/** \geometry_module \ingroup Geometry_Module
-  *
-  * \class Transform
-  *
-  * \brief Represents an homogeneous transformation in a N dimensional space
-  *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
-  * \param _Dim the dimension of the space
-  *
-  * The homography is internally represented and stored as a (Dim+1)^2 matrix which
-  * is available through the matrix() method.
-  *
-  * Conversion methods from/to Qt's QMatrix and QTransform are available if the
-  * preprocessor token EIGEN_QT_SUPPORT is defined.
-  *
-  * \sa class Matrix, class Quaternion
-  */
-template<typename _Scalar, int _Dim>
-class Transform
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_Dim==Dynamic ? Dynamic : (_Dim+1)*(_Dim+1))
-  enum {
-    Dim = _Dim,     ///< space dimension in which the transformation holds
-    HDim = _Dim+1   ///< size of a respective homogeneous vector
-  };
-  /** the scalar type of the coefficients */
-  typedef _Scalar Scalar;
-  /** type of the matrix used to represent the transformation */
-  typedef Matrix<Scalar,HDim,HDim> MatrixType;
-  /** type of the matrix used to represent the linear part of the transformation */
-  typedef Matrix<Scalar,Dim,Dim> LinearMatrixType;
-  /** type of read/write reference to the linear part of the transformation */
-  typedef Block<MatrixType,Dim,Dim> LinearPart;
-  /** type of read/write reference to the linear part of the transformation */
-  typedef const Block<const MatrixType,Dim,Dim> ConstLinearPart;
-  /** type of a vector */
-  typedef Matrix<Scalar,Dim,1> VectorType;
-  /** type of a read/write reference to the translation part of the rotation */
-  typedef Block<MatrixType,Dim,1> TranslationPart;
-  /** type of a read/write reference to the translation part of the rotation */
-  typedef const Block<const MatrixType,Dim,1> ConstTranslationPart;
-  /** corresponding translation type */
-  typedef Translation<Scalar,Dim> TranslationType;
-  /** corresponding scaling transformation type */
-  typedef Scaling<Scalar,Dim> ScalingType;
-
-protected:
-
-  MatrixType m_matrix;
-
-public:
-
-  /** Default constructor without initialization of the coefficients. */
-  inline Transform() { }
-
-  inline Transform(const Transform& other)
-  {
-    m_matrix = other.m_matrix;
-  }
-
-  inline explicit Transform(const TranslationType& t) { *this = t; }
-  inline explicit Transform(const ScalingType& s) { *this = s; }
-  template<typename Derived>
-  inline explicit Transform(const RotationBase<Derived, Dim>& r) { *this = r; }
-
-  inline Transform& operator=(const Transform& other)
-  { m_matrix = other.m_matrix; return *this; }
-
-  template<typename OtherDerived, bool BigMatrix> // MSVC 2005 will commit suicide if BigMatrix has a default value
-  struct construct_from_matrix
-  {
-    static inline void run(Transform *transform, const MatrixBase<OtherDerived>& other)
-    {
-      transform->matrix() = other;
-    }
-  };
-
-  template<typename OtherDerived> struct construct_from_matrix<OtherDerived, true>
-  {
-    static inline void run(Transform *transform, const MatrixBase<OtherDerived>& other)
-    {
-      transform->linear() = other;
-      transform->translation().setZero();
-      transform->matrix()(Dim,Dim) = Scalar(1);
-      transform->matrix().template block<1,Dim>(Dim,0).setZero();
-    }
-  };
-
-  /** Constructs and initializes a transformation from a Dim^2 or a (Dim+1)^2 matrix. */
-  template<typename OtherDerived>
-  inline explicit Transform(const MatrixBase<OtherDerived>& other)
-  {
-    construct_from_matrix<OtherDerived, int(OtherDerived::RowsAtCompileTime) == Dim>::run(this, other);
-  }
-
-  /** Set \c *this from a (Dim+1)^2 matrix. */
-  template<typename OtherDerived>
-  inline Transform& operator=(const MatrixBase<OtherDerived>& other)
-  { m_matrix = other; return *this; }
-
-  #ifdef EIGEN_QT_SUPPORT
-  inline Transform(const QMatrix& other);
-  inline Transform& operator=(const QMatrix& other);
-  inline QMatrix toQMatrix(void) const;
-  inline Transform(const QTransform& other);
-  inline Transform& operator=(const QTransform& other);
-  inline QTransform toQTransform(void) const;
-  #endif
-
-  /** shortcut for m_matrix(row,col);
-    * \sa MatrixBase::operaror(int,int) const */
-  inline Scalar operator() (int row, int col) const { return m_matrix(row,col); }
-  /** shortcut for m_matrix(row,col);
-    * \sa MatrixBase::operaror(int,int) */
-  inline Scalar& operator() (int row, int col) { return m_matrix(row,col); }
-
-  /** \returns a read-only expression of the transformation matrix */
-  inline const MatrixType& matrix() const { return m_matrix; }
-  /** \returns a writable expression of the transformation matrix */
-  inline MatrixType& matrix() { return m_matrix; }
-
-  /** \returns a read-only expression of the linear (linear) part of the transformation */
-  inline ConstLinearPart linear() const { return m_matrix.template block<Dim,Dim>(0,0); }
-  /** \returns a writable expression of the linear (linear) part of the transformation */
-  inline LinearPart linear() { return m_matrix.template block<Dim,Dim>(0,0); }
-
-  /** \returns a read-only expression of the translation vector of the transformation */
-  inline ConstTranslationPart translation() const { return m_matrix.template block<Dim,1>(0,Dim); }
-  /** \returns a writable expression of the translation vector of the transformation */
-  inline TranslationPart translation() { return m_matrix.template block<Dim,1>(0,Dim); }
-
-  /** \returns an expression of the product between the transform \c *this and a matrix expression \a other
-  *
-  * The right hand side \a other might be either:
-  * \li a vector of size Dim,
-  * \li an homogeneous vector of size Dim+1,
-  * \li a transformation matrix of size Dim+1 x Dim+1.
-  */
-  // note: this function is defined here because some compilers cannot find the respective declaration
-  template<typename OtherDerived>
-  inline const typename ei_transform_product_impl<OtherDerived,_Dim,_Dim+1>::ResultType
-  operator * (const MatrixBase<OtherDerived> &other) const
-  { return ei_transform_product_impl<OtherDerived,Dim,HDim>::run(*this,other.derived()); }
-
-  /** \returns the product expression of a transformation matrix \a a times a transform \a b
-    * The transformation matrix \a a must have a Dim+1 x Dim+1 sizes. */
-  template<typename OtherDerived>
-  friend inline const typename ProductReturnType<OtherDerived,MatrixType>::Type
-  operator * (const MatrixBase<OtherDerived> &a, const Transform &b)
-  { return a.derived() * b.matrix(); }
-
-  /** Contatenates two transformations */
-  inline const Transform
-  operator * (const Transform& other) const
-  { return Transform(m_matrix * other.matrix()); }
-
-  /** \sa MatrixBase::setIdentity() */
-  void setIdentity() { m_matrix.setIdentity(); }
-  static const typename MatrixType::IdentityReturnType Identity()
-  {
-    return MatrixType::Identity();
-  }
-
-  template<typename OtherDerived>
-  inline Transform& scale(const MatrixBase<OtherDerived> &other);
-
-  template<typename OtherDerived>
-  inline Transform& prescale(const MatrixBase<OtherDerived> &other);
-
-  inline Transform& scale(Scalar s);
-  inline Transform& prescale(Scalar s);
-
-  template<typename OtherDerived>
-  inline Transform& translate(const MatrixBase<OtherDerived> &other);
-
-  template<typename OtherDerived>
-  inline Transform& pretranslate(const MatrixBase<OtherDerived> &other);
-
-  template<typename RotationType>
-  inline Transform& rotate(const RotationType& rotation);
-
-  template<typename RotationType>
-  inline Transform& prerotate(const RotationType& rotation);
-
-  Transform& shear(Scalar sx, Scalar sy);
-  Transform& preshear(Scalar sx, Scalar sy);
-
-  inline Transform& operator=(const TranslationType& t);
-  inline Transform& operator*=(const TranslationType& t) { return translate(t.vector()); }
-  inline Transform operator*(const TranslationType& t) const;
-
-  inline Transform& operator=(const ScalingType& t);
-  inline Transform& operator*=(const ScalingType& s) { return scale(s.coeffs()); }
-  inline Transform operator*(const ScalingType& s) const;
-  friend inline Transform operator*(const LinearMatrixType& mat, const Transform& t)
-  {
-    Transform res = t;
-    res.matrix().row(Dim) = t.matrix().row(Dim);
-    res.matrix().template block<Dim,HDim>(0,0) = (mat * t.matrix().template block<Dim,HDim>(0,0)).lazy();
-    return res;
-  }
-
-  template<typename Derived>
-  inline Transform& operator=(const RotationBase<Derived,Dim>& r);
-  template<typename Derived>
-  inline Transform& operator*=(const RotationBase<Derived,Dim>& r) { return rotate(r.toRotationMatrix()); }
-  template<typename Derived>
-  inline Transform operator*(const RotationBase<Derived,Dim>& r) const;
-
-  LinearMatrixType rotation() const;
-  template<typename RotationMatrixType, typename ScalingMatrixType>
-  void computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const;
-  template<typename ScalingMatrixType, typename RotationMatrixType>
-  void computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const;
-
-  template<typename PositionDerived, typename OrientationType, typename ScaleDerived>
-  Transform& fromPositionOrientationScale(const MatrixBase<PositionDerived> &position,
-    const OrientationType& orientation, const MatrixBase<ScaleDerived> &scale);
-
-  inline const MatrixType inverse(TransformTraits traits = Affine) const;
-
-  /** \returns a const pointer to the column major internal matrix */
-  const Scalar* data() const { return m_matrix.data(); }
-  /** \returns a non-const pointer to the column major internal matrix */
-  Scalar* data() { return m_matrix.data(); }
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<Transform,Transform<NewScalarType,Dim> >::type cast() const
-  { return typename internal::cast_return_type<Transform,Transform<NewScalarType,Dim> >::type(*this); }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit Transform(const Transform<OtherScalarType,Dim>& other)
-  { m_matrix = other.matrix().template cast<Scalar>(); }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const Transform& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return m_matrix.isApprox(other.m_matrix, prec); }
-
-  #ifdef EIGEN_TRANSFORM_PLUGIN
-  #include EIGEN_TRANSFORM_PLUGIN
-  #endif
-
-protected:
-
-};
-
-/** \ingroup Geometry_Module */
-typedef Transform<float,2> Transform2f;
-/** \ingroup Geometry_Module */
-typedef Transform<float,3> Transform3f;
-/** \ingroup Geometry_Module */
-typedef Transform<double,2> Transform2d;
-/** \ingroup Geometry_Module */
-typedef Transform<double,3> Transform3d;
-
-/**************************
-*** Optional QT support ***
-**************************/
-
-#ifdef EIGEN_QT_SUPPORT
-/** Initialises \c *this from a QMatrix assuming the dimension is 2.
-  *
-  * This function is available only if the token EIGEN_QT_SUPPORT is defined.
-  */
-template<typename Scalar, int Dim>
-Transform<Scalar,Dim>::Transform(const QMatrix& other)
-{
-  *this = other;
-}
-
-/** Set \c *this from a QMatrix assuming the dimension is 2.
-  *
-  * This function is available only if the token EIGEN_QT_SUPPORT is defined.
-  */
-template<typename Scalar, int Dim>
-Transform<Scalar,Dim>& Transform<Scalar,Dim>::operator=(const QMatrix& other)
-{
-  EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  m_matrix << other.m11(), other.m21(), other.dx(),
-              other.m12(), other.m22(), other.dy(),
-              0, 0, 1;
-   return *this;
-}
-
-/** \returns a QMatrix from \c *this assuming the dimension is 2.
-  *
-  * \warning this convertion might loss data if \c *this is not affine
-  *
-  * This function is available only if the token EIGEN_QT_SUPPORT is defined.
-  */
-template<typename Scalar, int Dim>
-QMatrix Transform<Scalar,Dim>::toQMatrix(void) const
-{
-  EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  return QMatrix(m_matrix.coeff(0,0), m_matrix.coeff(1,0),
-                 m_matrix.coeff(0,1), m_matrix.coeff(1,1),
-                 m_matrix.coeff(0,2), m_matrix.coeff(1,2));
-}
-
-/** Initialises \c *this from a QTransform assuming the dimension is 2.
-  *
-  * This function is available only if the token EIGEN_QT_SUPPORT is defined.
-  */
-template<typename Scalar, int Dim>
-Transform<Scalar,Dim>::Transform(const QTransform& other)
-{
-  *this = other;
-}
-
-/** Set \c *this from a QTransform assuming the dimension is 2.
-  *
-  * This function is available only if the token EIGEN_QT_SUPPORT is defined.
-  */
-template<typename Scalar, int Dim>
-Transform<Scalar,Dim>& Transform<Scalar,Dim>::operator=(const QTransform& other)
-{
-  EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  m_matrix << other.m11(), other.m21(), other.dx(),
-              other.m12(), other.m22(), other.dy(),
-              other.m13(), other.m23(), other.m33();
-   return *this;
-}
-
-/** \returns a QTransform from \c *this assuming the dimension is 2.
-  *
-  * This function is available only if the token EIGEN_QT_SUPPORT is defined.
-  */
-template<typename Scalar, int Dim>
-QTransform Transform<Scalar,Dim>::toQTransform(void) const
-{
-  EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  return QTransform(m_matrix.coeff(0,0), m_matrix.coeff(1,0), m_matrix.coeff(2,0),
-                    m_matrix.coeff(0,1), m_matrix.coeff(1,1), m_matrix.coeff(2,1),
-                    m_matrix.coeff(0,2), m_matrix.coeff(1,2), m_matrix.coeff(2,2));
-}
-#endif
-
-/*********************
-*** Procedural API ***
-*********************/
-
-/** Applies on the right the non uniform scale transformation represented
-  * by the vector \a other to \c *this and returns a reference to \c *this.
-  * \sa prescale()
-  */
-template<typename Scalar, int Dim>
-template<typename OtherDerived>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::scale(const MatrixBase<OtherDerived> &other)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
-  linear() = (linear() * other.asDiagonal()).lazy();
-  return *this;
-}
-
-/** Applies on the right a uniform scale of a factor \a c to \c *this
-  * and returns a reference to \c *this.
-  * \sa prescale(Scalar)
-  */
-template<typename Scalar, int Dim>
-inline Transform<Scalar,Dim>& Transform<Scalar,Dim>::scale(Scalar s)
-{
-  linear() *= s;
-  return *this;
-}
-
-/** Applies on the left the non uniform scale transformation represented
-  * by the vector \a other to \c *this and returns a reference to \c *this.
-  * \sa scale()
-  */
-template<typename Scalar, int Dim>
-template<typename OtherDerived>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::prescale(const MatrixBase<OtherDerived> &other)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
-  m_matrix.template block<Dim,HDim>(0,0) = (other.asDiagonal() * m_matrix.template block<Dim,HDim>(0,0)).lazy();
-  return *this;
-}
-
-/** Applies on the left a uniform scale of a factor \a c to \c *this
-  * and returns a reference to \c *this.
-  * \sa scale(Scalar)
-  */
-template<typename Scalar, int Dim>
-inline Transform<Scalar,Dim>& Transform<Scalar,Dim>::prescale(Scalar s)
-{
-  m_matrix.template corner<Dim,HDim>(TopLeft) *= s;
-  return *this;
-}
-
-/** Applies on the right the translation matrix represented by the vector \a other
-  * to \c *this and returns a reference to \c *this.
-  * \sa pretranslate()
-  */
-template<typename Scalar, int Dim>
-template<typename OtherDerived>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::translate(const MatrixBase<OtherDerived> &other)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
-  translation() += linear() * other;
-  return *this;
-}
-
-/** Applies on the left the translation matrix represented by the vector \a other
-  * to \c *this and returns a reference to \c *this.
-  * \sa translate()
-  */
-template<typename Scalar, int Dim>
-template<typename OtherDerived>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::pretranslate(const MatrixBase<OtherDerived> &other)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
-  translation() += other;
-  return *this;
-}
-
-/** Applies on the right the rotation represented by the rotation \a rotation
-  * to \c *this and returns a reference to \c *this.
-  *
-  * The template parameter \a RotationType is the type of the rotation which
-  * must be known by ei_toRotationMatrix<>.
-  *
-  * Natively supported types includes:
-  *   - any scalar (2D),
-  *   - a Dim x Dim matrix expression,
-  *   - a Quaternion (3D),
-  *   - a AngleAxis (3D)
-  *
-  * This mechanism is easily extendable to support user types such as Euler angles,
-  * or a pair of Quaternion for 4D rotations.
-  *
-  * \sa rotate(Scalar), class Quaternion, class AngleAxis, prerotate(RotationType)
-  */
-template<typename Scalar, int Dim>
-template<typename RotationType>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::rotate(const RotationType& rotation)
-{
-  linear() *= ei_toRotationMatrix<Scalar,Dim>(rotation);
-  return *this;
-}
-
-/** Applies on the left the rotation represented by the rotation \a rotation
-  * to \c *this and returns a reference to \c *this.
-  *
-  * See rotate() for further details.
-  *
-  * \sa rotate()
-  */
-template<typename Scalar, int Dim>
-template<typename RotationType>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::prerotate(const RotationType& rotation)
-{
-  m_matrix.template block<Dim,HDim>(0,0) = ei_toRotationMatrix<Scalar,Dim>(rotation)
-                                         * m_matrix.template block<Dim,HDim>(0,0);
-  return *this;
-}
-
-/** Applies on the right the shear transformation represented
-  * by the vector \a other to \c *this and returns a reference to \c *this.
-  * \warning 2D only.
-  * \sa preshear()
-  */
-template<typename Scalar, int Dim>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::shear(Scalar sx, Scalar sy)
-{
-  EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  VectorType tmp = linear().col(0)*sy + linear().col(1);
-  linear() << linear().col(0) + linear().col(1)*sx, tmp;
-  return *this;
-}
-
-/** Applies on the left the shear transformation represented
-  * by the vector \a other to \c *this and returns a reference to \c *this.
-  * \warning 2D only.
-  * \sa shear()
-  */
-template<typename Scalar, int Dim>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::preshear(Scalar sx, Scalar sy)
-{
-  EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  m_matrix.template block<Dim,HDim>(0,0) = LinearMatrixType(1, sx, sy, 1) * m_matrix.template block<Dim,HDim>(0,0);
-  return *this;
-}
-
-/******************************************************
-*** Scaling, Translation and Rotation compatibility ***
-******************************************************/
-
-template<typename Scalar, int Dim>
-inline Transform<Scalar,Dim>& Transform<Scalar,Dim>::operator=(const TranslationType& t)
-{
-  linear().setIdentity();
-  translation() = t.vector();
-  m_matrix.template block<1,Dim>(Dim,0).setZero();
-  m_matrix(Dim,Dim) = Scalar(1);
-  return *this;
-}
-
-template<typename Scalar, int Dim>
-inline Transform<Scalar,Dim> Transform<Scalar,Dim>::operator*(const TranslationType& t) const
-{
-  Transform res = *this;
-  res.translate(t.vector());
-  return res;
-}
-
-template<typename Scalar, int Dim>
-inline Transform<Scalar,Dim>& Transform<Scalar,Dim>::operator=(const ScalingType& s)
-{
-  m_matrix.setZero();
-  linear().diagonal() = s.coeffs();
-  m_matrix.coeffRef(Dim,Dim) = Scalar(1);
-  return *this;
-}
-
-template<typename Scalar, int Dim>
-inline Transform<Scalar,Dim> Transform<Scalar,Dim>::operator*(const ScalingType& s) const
-{
-  Transform res = *this;
-  res.scale(s.coeffs());
-  return res;
-}
-
-template<typename Scalar, int Dim>
-template<typename Derived>
-inline Transform<Scalar,Dim>& Transform<Scalar,Dim>::operator=(const RotationBase<Derived,Dim>& r)
-{
-  linear() = ei_toRotationMatrix<Scalar,Dim>(r);
-  translation().setZero();
-  m_matrix.template block<1,Dim>(Dim,0).setZero();
-  m_matrix.coeffRef(Dim,Dim) = Scalar(1);
-  return *this;
-}
-
-template<typename Scalar, int Dim>
-template<typename Derived>
-inline Transform<Scalar,Dim> Transform<Scalar,Dim>::operator*(const RotationBase<Derived,Dim>& r) const
-{
-  Transform res = *this;
-  res.rotate(r.derived());
-  return res;
-}
-
-/************************
-*** Special functions ***
-************************/
-
-/** \returns the rotation part of the transformation
-  * \nonstableyet
-  *
-  * \svd_module
-  *
-  * \sa computeRotationScaling(), computeScalingRotation(), class SVD
-  */
-template<typename Scalar, int Dim>
-typename Transform<Scalar,Dim>::LinearMatrixType
-Transform<Scalar,Dim>::rotation() const
-{
-  LinearMatrixType result;
-  computeRotationScaling(&result, (LinearMatrixType*)0);
-  return result;
-}
-
-
-/** decomposes the linear part of the transformation as a product rotation x scaling, the scaling being
-  * not necessarily positive.
-  *
-  * If either pointer is zero, the corresponding computation is skipped.
-  *
-  * \nonstableyet
-  *
-  * \svd_module
-  *
-  * \sa computeScalingRotation(), rotation(), class SVD
-  */
-template<typename Scalar, int Dim>
-template<typename RotationMatrixType, typename ScalingMatrixType>
-void Transform<Scalar,Dim>::computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const
-{
-  JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU|ComputeFullV);
-  Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
-  Matrix<Scalar, Dim, 1> sv(svd.singularValues());
-  sv.coeffRef(0) *= x;
-  if(scaling)
-  {
-    scaling->noalias() = svd.matrixV() * sv.asDiagonal() * svd.matrixV().adjoint();
-  }
-  if(rotation)
-  {
-    LinearMatrixType m(svd.matrixU());
-    m.col(0) /= x;
-    rotation->noalias() = m * svd.matrixV().adjoint();
-  }
-}
-
-/** decomposes the linear part of the transformation as a product rotation x scaling, the scaling being
-  * not necessarily positive.
-  *
-  * If either pointer is zero, the corresponding computation is skipped.
-  *
-  * \nonstableyet
-  *
-  * \svd_module
-  *
-  * \sa computeRotationScaling(), rotation(), class SVD
-  */
-template<typename Scalar, int Dim>
-template<typename ScalingMatrixType, typename RotationMatrixType>
-void Transform<Scalar,Dim>::computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const
-{
-  JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU|ComputeFullV);
-  Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
-  Matrix<Scalar, Dim, 1> sv(svd.singularValues());
-  sv.coeffRef(0) *= x;
-  if(scaling)
-  {
-    scaling->noalias() = svd.matrixU() * sv.asDiagonal() * svd.matrixU().adjoint();
-  }
-  if(rotation)
-  {
-    LinearMatrixType m(svd.matrixU());
-    m.col(0) /= x;
-    rotation->noalias() = m * svd.matrixV().adjoint();
-  }
-}
-
-/** Convenient method to set \c *this from a position, orientation and scale
-  * of a 3D object.
-  */
-template<typename Scalar, int Dim>
-template<typename PositionDerived, typename OrientationType, typename ScaleDerived>
-Transform<Scalar,Dim>&
-Transform<Scalar,Dim>::fromPositionOrientationScale(const MatrixBase<PositionDerived> &position,
-  const OrientationType& orientation, const MatrixBase<ScaleDerived> &scale)
-{
-  linear() = ei_toRotationMatrix<Scalar,Dim>(orientation);
-  linear() *= scale.asDiagonal();
-  translation() = position;
-  m_matrix.template block<1,Dim>(Dim,0).setZero();
-  m_matrix(Dim,Dim) = Scalar(1);
-  return *this;
-}
-
-/** \nonstableyet
-  *
-  * \returns the inverse transformation matrix according to some given knowledge
-  * on \c *this.
-  *
-  * \param traits allows to optimize the inversion process when the transformion
-  * is known to be not a general transformation. The possible values are:
-  *  - Projective if the transformation is not necessarily affine, i.e., if the
-  *    last row is not guaranteed to be [0 ... 0 1]
-  *  - Affine is the default, the last row is assumed to be [0 ... 0 1]
-  *  - Isometry if the transformation is only a concatenations of translations
-  *    and rotations.
-  *
-  * \warning unless \a traits is always set to NoShear or NoScaling, this function
-  * requires the generic inverse method of MatrixBase defined in the LU module. If
-  * you forget to include this module, then you will get hard to debug linking errors.
-  *
-  * \sa MatrixBase::inverse()
-  */
-template<typename Scalar, int Dim>
-inline const typename Transform<Scalar,Dim>::MatrixType
-Transform<Scalar,Dim>::inverse(TransformTraits traits) const
-{
-  if (traits == Projective)
-  {
-    return m_matrix.inverse();
-  }
-  else
-  {
-    MatrixType res;
-    if (traits == Affine)
-    {
-      res.template corner<Dim,Dim>(TopLeft) = linear().inverse();
-    }
-    else if (traits == Isometry)
-    {
-      res.template corner<Dim,Dim>(TopLeft) = linear().transpose();
-    }
-    else
-    {
-      ei_assert("invalid traits value in Transform::inverse()");
-    }
-    // translation and remaining parts
-    res.template corner<Dim,1>(TopRight) = - res.template corner<Dim,Dim>(TopLeft) * translation();
-    res.template corner<1,Dim>(BottomLeft).setZero();
-    res.coeffRef(Dim,Dim) = Scalar(1);
-    return res;
-  }
-}
-
-/*****************************************************
-*** Specializations of operator* with a MatrixBase ***
-*****************************************************/
-
-template<typename Other, int Dim, int HDim>
-struct ei_transform_product_impl<Other,Dim,HDim, HDim,HDim>
-{
-  typedef Transform<typename Other::Scalar,Dim> TransformType;
-  typedef typename TransformType::MatrixType MatrixType;
-  typedef typename ProductReturnType<MatrixType,Other>::Type ResultType;
-  static ResultType run(const TransformType& tr, const Other& other)
-  { return tr.matrix() * other; }
-};
-
-template<typename Other, int Dim, int HDim>
-struct ei_transform_product_impl<Other,Dim,HDim, Dim,Dim>
-{
-  typedef Transform<typename Other::Scalar,Dim> TransformType;
-  typedef typename TransformType::MatrixType MatrixType;
-  typedef TransformType ResultType;
-  static ResultType run(const TransformType& tr, const Other& other)
-  {
-    TransformType res;
-    res.translation() = tr.translation();
-    res.matrix().row(Dim) = tr.matrix().row(Dim);
-    res.linear() = (tr.linear() * other).lazy();
-    return res;
-  }
-};
-
-template<typename Other, int Dim, int HDim>
-struct ei_transform_product_impl<Other,Dim,HDim, HDim,1>
-{
-  typedef Transform<typename Other::Scalar,Dim> TransformType;
-  typedef typename TransformType::MatrixType MatrixType;
-  typedef typename ProductReturnType<MatrixType,Other>::Type ResultType;
-  static ResultType run(const TransformType& tr, const Other& other)
-  { return tr.matrix() * other; }
-};
-
-template<typename Other, int Dim, int HDim>
-struct ei_transform_product_impl<Other,Dim,HDim, Dim,1>
-{
-  typedef typename Other::Scalar Scalar;
-  typedef Transform<Scalar,Dim> TransformType;
-  typedef Matrix<Scalar,Dim,1> ResultType;
-  static ResultType run(const TransformType& tr, const Other& other)
-  { return ((tr.linear() * other) + tr.translation())
-          * (Scalar(1) / ( (tr.matrix().template block<1,Dim>(Dim,0) * other).coeff(0) + tr.matrix().coeff(Dim,Dim))); }
-};
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h
@@ -1,184 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
-
-namespace Eigen { 
-
-/** \geometry_module \ingroup Geometry_Module
-  *
-  * \class Translation
-  *
-  * \brief Represents a translation transformation
-  *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients.
-  * \param _Dim the  dimension of the space, can be a compile time value or Dynamic
-  *
-  * \note This class is not aimed to be used to store a translation transformation,
-  * but rather to make easier the constructions and updates of Transform objects.
-  *
-  * \sa class Scaling, class Transform
-  */
-template<typename _Scalar, int _Dim>
-class Translation
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_Dim)
-  /** dimension of the space */
-  enum { Dim = _Dim };
-  /** the scalar type of the coefficients */
-  typedef _Scalar Scalar;
-  /** corresponding vector type */
-  typedef Matrix<Scalar,Dim,1> VectorType;
-  /** corresponding linear transformation matrix type */
-  typedef Matrix<Scalar,Dim,Dim> LinearMatrixType;
-  /** corresponding scaling transformation type */
-  typedef Scaling<Scalar,Dim> ScalingType;
-  /** corresponding affine transformation type */
-  typedef Transform<Scalar,Dim> TransformType;
-
-protected:
-
-  VectorType m_coeffs;
-
-public:
-
-  /** Default constructor without initialization. */
-  Translation() {}
-  /**  */
-  inline Translation(const Scalar& sx, const Scalar& sy)
-  {
-    ei_assert(Dim==2);
-    m_coeffs.x() = sx;
-    m_coeffs.y() = sy;
-  }
-  /**  */
-  inline Translation(const Scalar& sx, const Scalar& sy, const Scalar& sz)
-  {
-    ei_assert(Dim==3);
-    m_coeffs.x() = sx;
-    m_coeffs.y() = sy;
-    m_coeffs.z() = sz;
-  }
-  /** Constructs and initialize the scaling transformation from a vector of scaling coefficients */
-  explicit inline Translation(const VectorType& vector) : m_coeffs(vector) {}
-
-  const VectorType& vector() const { return m_coeffs; }
-  VectorType& vector() { return m_coeffs; }
-
-  /** Concatenates two translation */
-  inline Translation operator* (const Translation& other) const
-  { return Translation(m_coeffs + other.m_coeffs); }
-
-  /** Concatenates a translation and a scaling */
-  inline TransformType operator* (const ScalingType& other) const;
-
-  /** Concatenates a translation and a linear transformation */
-  inline TransformType operator* (const LinearMatrixType& linear) const;
-
-  template<typename Derived>
-  inline TransformType operator*(const RotationBase<Derived,Dim>& r) const
-  { return *this * r.toRotationMatrix(); }
-
-  /** Concatenates a linear transformation and a translation */
-  // its a nightmare to define a templated friend function outside its declaration
-  friend inline TransformType operator* (const LinearMatrixType& linear, const Translation& t)
-  {
-    TransformType res;
-    res.matrix().setZero();
-    res.linear() = linear;
-    res.translation() = linear * t.m_coeffs;
-    res.matrix().row(Dim).setZero();
-    res(Dim,Dim) = Scalar(1);
-    return res;
-  }
-
-  /** Concatenates a translation and an affine transformation */
-  inline TransformType operator* (const TransformType& t) const;
-
-  /** Applies translation to vector */
-  inline VectorType operator* (const VectorType& other) const
-  { return m_coeffs + other; }
-
-  /** \returns the inverse translation (opposite) */
-  Translation inverse() const { return Translation(-m_coeffs); }
-
-  Translation& operator=(const Translation& other)
-  {
-    m_coeffs = other.m_coeffs;
-    return *this;
-  }
-
-  /** \returns \c *this with scalar type casted to \a NewScalarType
-    *
-    * Note that if \a NewScalarType is equal to the current scalar type of \c *this
-    * then this function smartly returns a const reference to \c *this.
-    */
-  template<typename NewScalarType>
-  inline typename internal::cast_return_type<Translation,Translation<NewScalarType,Dim> >::type cast() const
-  { return typename internal::cast_return_type<Translation,Translation<NewScalarType,Dim> >::type(*this); }
-
-  /** Copy constructor with scalar type conversion */
-  template<typename OtherScalarType>
-  inline explicit Translation(const Translation<OtherScalarType,Dim>& other)
-  { m_coeffs = other.vector().template cast<Scalar>(); }
-
-  /** \returns \c true if \c *this is approximately equal to \a other, within the precision
-    * determined by \a prec.
-    *
-    * \sa MatrixBase::isApprox() */
-  bool isApprox(const Translation& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
-  { return m_coeffs.isApprox(other.m_coeffs, prec); }
-
-};
-
-/** \addtogroup Geometry_Module */
-//@{
-typedef Translation<float, 2> Translation2f;
-typedef Translation<double,2> Translation2d;
-typedef Translation<float, 3> Translation3f;
-typedef Translation<double,3> Translation3d;
-//@}
-
-
-template<typename Scalar, int Dim>
-inline typename Translation<Scalar,Dim>::TransformType
-Translation<Scalar,Dim>::operator* (const ScalingType& other) const
-{
-  TransformType res;
-  res.matrix().setZero();
-  res.linear().diagonal() = other.coeffs();
-  res.translation() = m_coeffs;
-  res(Dim,Dim) = Scalar(1);
-  return res;
-}
-
-template<typename Scalar, int Dim>
-inline typename Translation<Scalar,Dim>::TransformType
-Translation<Scalar,Dim>::operator* (const LinearMatrixType& linear) const
-{
-  TransformType res;
-  res.matrix().setZero();
-  res.linear() = linear;
-  res.translation() = m_coeffs;
-  res.matrix().row(Dim).setZero();
-  res(Dim,Dim) = Scalar(1);
-  return res;
-}
-
-template<typename Scalar, int Dim>
-inline typename Translation<Scalar,Dim>::TransformType
-Translation<Scalar,Dim>::operator* (const TransformType& t) const
-{
-  TransformType res = t;
-  res.pretranslate(m_coeffs);
-  return res;
-}
-
-} // end namespace Eigen

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/LU.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/LU.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/LU.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/LU.h
@@ -1,120 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_LU_H
-#define EIGEN2_LU_H
-
-namespace Eigen { 
-
-template<typename MatrixType>
-class LU : public FullPivLU<MatrixType>
-{
-  public:
-
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef Matrix<int, 1, MatrixType::ColsAtCompileTime, MatrixType::Options, 1, MatrixType::MaxColsAtCompileTime> IntRowVectorType;
-    typedef Matrix<int, MatrixType::RowsAtCompileTime, 1, MatrixType::Options, MatrixType::MaxRowsAtCompileTime, 1> IntColVectorType;
-    typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime, MatrixType::Options, 1, MatrixType::MaxColsAtCompileTime> RowVectorType;
-    typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1, MatrixType::Options, MatrixType::MaxRowsAtCompileTime, 1> ColVectorType;
-
-    typedef Matrix<typename MatrixType::Scalar,
-                  MatrixType::ColsAtCompileTime, // the number of rows in the "kernel matrix" is the number of cols of the original matrix
-                                                 // so that the product "matrix * kernel = zero" makes sense
-                  Dynamic,                       // we don't know at compile-time the dimension of the kernel
-                  MatrixType::Options,
-                  MatrixType::MaxColsAtCompileTime, // see explanation for 2nd template parameter
-                  MatrixType::MaxColsAtCompileTime // the kernel is a subspace of the domain space, whose dimension is the number
-                                                   // of columns of the original matrix
-    > KernelResultType;
-
-    typedef Matrix<typename MatrixType::Scalar,
-                   MatrixType::RowsAtCompileTime, // the image is a subspace of the destination space, whose dimension is the number
-                                                  // of rows of the original matrix
-                   Dynamic,                       // we don't know at compile time the dimension of the image (the rank)
-                   MatrixType::Options,
-                   MatrixType::MaxRowsAtCompileTime, // the image matrix will consist of columns from the original matrix,
-                   MatrixType::MaxColsAtCompileTime  // so it has the same number of rows and at most as many columns.
-    > ImageResultType;
-
-    typedef FullPivLU<MatrixType> Base;
-
-    template<typename T>
-    explicit LU(const T& t) : Base(t), m_originalMatrix(t) {}
-
-    template<typename OtherDerived, typename ResultType>
-    bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
-    {
-      *result = static_cast<const Base*>(this)->solve(b);
-      return true;
-    }
-
-    template<typename ResultType>
-    inline void computeInverse(ResultType *result) const
-    {
-      solve(MatrixType::Identity(this->rows(), this->cols()), result);
-    }
-    
-    template<typename KernelMatrixType>
-    void computeKernel(KernelMatrixType *result) const
-    {
-      *result = static_cast<const Base*>(this)->kernel();
-    }
-    
-    template<typename ImageMatrixType>
-    void computeImage(ImageMatrixType *result) const
-    {
-      *result = static_cast<const Base*>(this)->image(m_originalMatrix);
-    }
-    
-    const ImageResultType image() const
-    {
-      return static_cast<const Base*>(this)->image(m_originalMatrix);
-    }
-    
-    const MatrixType& m_originalMatrix;
-};
-
-#if EIGEN2_SUPPORT_STAGE < STAGE20_RESOLVE_API_CONFLICTS
-/** \lu_module
-  *
-  * Synonym of partialPivLu().
-  *
-  * \return the partial-pivoting LU decomposition of \c *this.
-  *
-  * \sa class PartialPivLU
-  */
-template<typename Derived>
-inline const LU<typename MatrixBase<Derived>::PlainObject>
-MatrixBase<Derived>::lu() const
-{
-  return LU<PlainObject>(eval());
-}
-#endif
-
-#ifdef EIGEN2_SUPPORT
-/** \lu_module
-  *
-  * Synonym of partialPivLu().
-  *
-  * \return the partial-pivoting LU decomposition of \c *this.
-  *
-  * \sa class PartialPivLU
-  */
-template<typename Derived>
-inline const LU<typename MatrixBase<Derived>::PlainObject>
-MatrixBase<Derived>::eigen2_lu() const
-{
-  return LU<PlainObject>(eval());
-}
-#endif
-
-} // end namespace Eigen
-
-#endif // EIGEN2_LU_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Lazy.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Lazy.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Lazy.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Lazy.h
@@ -1,71 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_LAZY_H
-#define EIGEN_LAZY_H
-
-namespace Eigen { 
-
-/** \deprecated it is only used by lazy() which is deprecated
-  *
-  * \returns an expression of *this with added flags
-  *
-  * Example: \include MatrixBase_marked.cpp
-  * Output: \verbinclude MatrixBase_marked.out
-  *
-  * \sa class Flagged, extract(), part()
-  */
-template<typename Derived>
-template<unsigned int Added>
-inline const Flagged<Derived, Added, 0>
-MatrixBase<Derived>::marked() const
-{
-  return derived();
-}
-
-/** \deprecated use MatrixBase::noalias()
-  *
-  * \returns an expression of *this with the EvalBeforeAssigningBit flag removed.
-  *
-  * Example: \include MatrixBase_lazy.cpp
-  * Output: \verbinclude MatrixBase_lazy.out
-  *
-  * \sa class Flagged, marked()
-  */
-template<typename Derived>
-inline const Flagged<Derived, 0, EvalBeforeAssigningBit>
-MatrixBase<Derived>::lazy() const
-{
-  return derived();
-}
-
-
-/** \internal
-  * Overloaded to perform an efficient C += (A*B).lazy() */
-template<typename Derived>
-template<typename ProductDerived, typename Lhs, typename Rhs>
-Derived& MatrixBase<Derived>::operator+=(const Flagged<ProductBase<ProductDerived, Lhs,Rhs>, 0,
-                                                       EvalBeforeAssigningBit>& other)
-{
-  other._expression().derived().addTo(derived()); return derived();
-}
-
-/** \internal
-  * Overloaded to perform an efficient C -= (A*B).lazy() */
-template<typename Derived>
-template<typename ProductDerived, typename Lhs, typename Rhs>
-Derived& MatrixBase<Derived>::operator-=(const Flagged<ProductBase<ProductDerived, Lhs,Rhs>, 0,
-                                                       EvalBeforeAssigningBit>& other)
-{
-  other._expression().derived().subTo(derived()); return derived();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_LAZY_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/LeastSquares.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/LeastSquares.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/LeastSquares.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/LeastSquares.h
@@ -1,169 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_LEASTSQUARES_H
-#define EIGEN2_LEASTSQUARES_H
-
-namespace Eigen { 
-
-/** \ingroup LeastSquares_Module
-  *
-  * \leastsquares_module
-  *
-  * For a set of points, this function tries to express
-  * one of the coords as a linear (affine) function of the other coords.
-  *
-  * This is best explained by an example. This function works in full
-  * generality, for points in a space of arbitrary dimension, and also over
-  * the complex numbers, but for this example we will work in dimension 3
-  * over the real numbers (doubles).
-  *
-  * So let us work with the following set of 5 points given by their
-  * \f$(x,y,z)\f$ coordinates:
-  * @code
-    Vector3d points[5];
-    points[0] = Vector3d( 3.02, 6.89, -4.32 );
-    points[1] = Vector3d( 2.01, 5.39, -3.79 );
-    points[2] = Vector3d( 2.41, 6.01, -4.01 );
-    points[3] = Vector3d( 2.09, 5.55, -3.86 );
-    points[4] = Vector3d( 2.58, 6.32, -4.10 );
-  * @endcode
-  * Suppose that we want to express the second coordinate (\f$y\f$) as a linear
-  * expression in \f$x\f$ and \f$z\f$, that is,
-  * \f[ y=ax+bz+c \f]
-  * for some constants \f$a,b,c\f$. Thus, we want to find the best possible
-  * constants \f$a,b,c\f$ so that the plane of equation \f$y=ax+bz+c\f$ fits
-  * best the five above points. To do that, call this function as follows:
-  * @code
-    Vector3d coeffs; // will store the coefficients a, b, c
-    linearRegression(
-      5,
-      &points,
-      &coeffs,
-      1 // the coord to express as a function of
-        // the other ones. 0 means x, 1 means y, 2 means z.
-    );
-  * @endcode
-  * Now the vector \a coeffs is approximately
-  * \f$( 0.495 ,  -1.927 ,  -2.906 )\f$.
-  * Thus, we get \f$a=0.495, b = -1.927, c = -2.906\f$. Let us check for
-  * instance how near points[0] is from the plane of equation \f$y=ax+bz+c\f$.
-  * Looking at the coords of points[0], we see that:
-  * \f[ax+bz+c = 0.495 * 3.02 + (-1.927) * (-4.32) + (-2.906) = 6.91.\f]
-  * On the other hand, we have \f$y=6.89\f$. We see that the values
-  * \f$6.91\f$ and \f$6.89\f$
-  * are near, so points[0] is very near the plane of equation \f$y=ax+bz+c\f$.
-  *
-  * Let's now describe precisely the parameters:
-  * @param numPoints the number of points
-  * @param points the array of pointers to the points on which to perform the linear regression
-  * @param result pointer to the vector in which to store the result.
-                  This vector must be of the same type and size as the
-                  data points. The meaning of its coords is as follows.
-                  For brevity, let \f$n=Size\f$,
-                  \f$r_i=result[i]\f$,
-                  and \f$f=funcOfOthers\f$. Denote by
-                  \f$x_0,\ldots,x_{n-1}\f$
-                  the n coordinates in the n-dimensional space.
-                  Then the resulting equation is:
-                  \f[ x_f = r_0 x_0 + \cdots + r_{f-1}x_{f-1}
-                   + r_{f+1}x_{f+1} + \cdots + r_{n-1}x_{n-1} + r_n. \f]
-  * @param funcOfOthers Determines which coord to express as a function of the
-                        others. Coords are numbered starting from 0, so that a
-                        value of 0 means \f$x\f$, 1 means \f$y\f$,
-                        2 means \f$z\f$, ...
-  *
-  * \sa fitHyperplane()
-  */
-template<typename VectorType>
-void linearRegression(int numPoints,
-                      VectorType **points,
-                      VectorType *result,
-                      int funcOfOthers )
-{
-  typedef typename VectorType::Scalar Scalar;
-  typedef Hyperplane<Scalar, VectorType::SizeAtCompileTime> HyperplaneType;
-  const int size = points[0]->size();
-  result->resize(size);
-  HyperplaneType h(size);
-  fitHyperplane(numPoints, points, &h);
-  for(int i = 0; i < funcOfOthers; i++)
-    result->coeffRef(i) = - h.coeffs()[i] / h.coeffs()[funcOfOthers];
-  for(int i = funcOfOthers; i < size; i++)
-    result->coeffRef(i) = - h.coeffs()[i+1] / h.coeffs()[funcOfOthers];
-}
-
-/** \ingroup LeastSquares_Module
-  *
-  * \leastsquares_module
-  *
-  * This function is quite similar to linearRegression(), so we refer to the
-  * documentation of this function and only list here the differences.
-  *
-  * The main difference from linearRegression() is that this function doesn't
-  * take a \a funcOfOthers argument. Instead, it finds a general equation
-  * of the form
-  * \f[ r_0 x_0 + \cdots + r_{n-1}x_{n-1} + r_n = 0, \f]
-  * where \f$n=Size\f$, \f$r_i=retCoefficients[i]\f$, and we denote by
-  * \f$x_0,\ldots,x_{n-1}\f$ the n coordinates in the n-dimensional space.
-  *
-  * Thus, the vector \a retCoefficients has size \f$n+1\f$, which is another
-  * difference from linearRegression().
-  *
-  * In practice, this function performs an hyper-plane fit in a total least square sense
-  * via the following steps:
-  *  1 - center the data to the mean
-  *  2 - compute the covariance matrix
-  *  3 - pick the eigenvector corresponding to the smallest eigenvalue of the covariance matrix
-  * The ratio of the smallest eigenvalue and the second one gives us a hint about the relevance
-  * of the solution. This value is optionally returned in \a soundness.
-  *
-  * \sa linearRegression()
-  */
-template<typename VectorType, typename HyperplaneType>
-void fitHyperplane(int numPoints,
-                   VectorType **points,
-                   HyperplaneType *result,
-                   typename NumTraits<typename VectorType::Scalar>::Real* soundness = 0)
-{
-  typedef typename VectorType::Scalar Scalar;
-  typedef Matrix<Scalar,VectorType::SizeAtCompileTime,VectorType::SizeAtCompileTime> CovMatrixType;
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType)
-  ei_assert(numPoints >= 1);
-  int size = points[0]->size();
-  ei_assert(size+1 == result->coeffs().size());
-
-  // compute the mean of the data
-  VectorType mean = VectorType::Zero(size);
-  for(int i = 0; i < numPoints; ++i)
-    mean += *(points[i]);
-  mean /= numPoints;
-
-  // compute the covariance matrix
-  CovMatrixType covMat = CovMatrixType::Zero(size, size);
-  for(int i = 0; i < numPoints; ++i)
-  {
-    VectorType diff = (*(points[i]) - mean).conjugate();
-    covMat += diff * diff.adjoint();
-  }
-
-  // now we just have to pick the eigen vector with smallest eigen value
-  SelfAdjointEigenSolver<CovMatrixType> eig(covMat);
-  result->normal() = eig.eigenvectors().col(0);
-  if (soundness)
-    *soundness = eig.eigenvalues().coeff(0)/eig.eigenvalues().coeff(1);
-
-  // let's compute the constant coefficient such that the
-  // plane pass trough the mean point:
-  result->offset() = - (result->normal().cwise()* mean).sum();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN2_LEASTSQUARES_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Macros.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Macros.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Macros.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Macros.h
@@ -1,20 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_MACROS_H
-#define EIGEN2_MACROS_H
-
-#define ei_assert eigen_assert
-#define ei_internal_assert eigen_internal_assert
-
-#define EIGEN_ALIGN_128 EIGEN_ALIGN16
-
-#define EIGEN_ARCH_WANTS_ALIGNMENT EIGEN_ALIGN_STATICALLY
-
-#endif // EIGEN2_MACROS_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/MathFunctions.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/MathFunctions.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/MathFunctions.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/MathFunctions.h
@@ -1,57 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_MATH_FUNCTIONS_H
-#define EIGEN2_MATH_FUNCTIONS_H
-
-namespace Eigen { 
-
-template<typename T> inline typename NumTraits<T>::Real ei_real(const T& x) { return numext::real(x); }
-template<typename T> inline typename NumTraits<T>::Real ei_imag(const T& x) { return numext::imag(x); }
-template<typename T> inline T ei_conj(const T& x) { return numext::conj(x); }
-template<typename T> inline typename NumTraits<T>::Real ei_abs (const T& x) { using std::abs; return abs(x); }
-template<typename T> inline typename NumTraits<T>::Real ei_abs2(const T& x) { return numext::abs2(x); }
-template<typename T> inline T ei_sqrt(const T& x) { using std::sqrt; return sqrt(x); }
-template<typename T> inline T ei_exp (const T& x) { using std::exp;  return exp(x); }
-template<typename T> inline T ei_log (const T& x) { using std::log;  return log(x); }
-template<typename T> inline T ei_sin (const T& x) { using std::sin;  return sin(x); }
-template<typename T> inline T ei_cos (const T& x) { using std::cos;  return cos(x); }
-template<typename T> inline T ei_atan2(const T& x,const T& y) { using std::atan2; return atan2(x,y); }
-template<typename T> inline T ei_pow (const T& x,const T& y) { return numext::pow(x,y); }
-template<typename T> inline T ei_random () { return internal::random<T>(); }
-template<typename T> inline T ei_random (const T& x, const T& y) { return internal::random(x, y); }
-
-template<typename T> inline T precision () { return NumTraits<T>::dummy_precision(); }
-template<typename T> inline T machine_epsilon () { return NumTraits<T>::epsilon(); }
-
-
-template<typename Scalar, typename OtherScalar>
-inline bool ei_isMuchSmallerThan(const Scalar& x, const OtherScalar& y,
-                                   typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
-{
-  return internal::isMuchSmallerThan(x, y, precision);
-}
-
-template<typename Scalar>
-inline bool ei_isApprox(const Scalar& x, const Scalar& y,
-                          typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
-{
-  return internal::isApprox(x, y, precision);
-}
-
-template<typename Scalar>
-inline bool ei_isApproxOrLessThan(const Scalar& x, const Scalar& y,
-                                    typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision())
-{
-  return internal::isApproxOrLessThan(x, y, precision);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN2_MATH_FUNCTIONS_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Memory.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Memory.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Memory.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Memory.h
@@ -1,45 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_MEMORY_H
-#define EIGEN2_MEMORY_H
-
-namespace Eigen { 
-
-inline void* ei_aligned_malloc(size_t size) { return internal::aligned_malloc(size); }
-inline void  ei_aligned_free(void *ptr) { internal::aligned_free(ptr); }
-inline void* ei_aligned_realloc(void *ptr, size_t new_size, size_t old_size) { return internal::aligned_realloc(ptr, new_size, old_size); }
-inline void* ei_handmade_aligned_malloc(size_t size) { return internal::handmade_aligned_malloc(size); }
-inline void  ei_handmade_aligned_free(void *ptr) { internal::handmade_aligned_free(ptr); }
-
-template<bool Align> inline void* ei_conditional_aligned_malloc(size_t size)
-{
-  return internal::conditional_aligned_malloc<Align>(size);
-}
-template<bool Align> inline void ei_conditional_aligned_free(void *ptr)
-{
-  internal::conditional_aligned_free<Align>(ptr);
-}
-template<bool Align> inline void* ei_conditional_aligned_realloc(void* ptr, size_t new_size, size_t old_size)
-{
-  return internal::conditional_aligned_realloc<Align>(ptr, new_size, old_size);
-}
-
-template<typename T> inline T* ei_aligned_new(size_t size)
-{
-  return internal::aligned_new<T>(size);
-}
-template<typename T> inline void ei_aligned_delete(T *ptr, size_t size)
-{
-  return internal::aligned_delete(ptr, size);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN2_MACROS_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Meta.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Meta.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Meta.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Meta.h
@@ -1,75 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_META_H
-#define EIGEN2_META_H
-
-namespace Eigen { 
-
-template<typename T>
-struct ei_traits : internal::traits<T>
-{};
-
-struct ei_meta_true {  enum { ret = 1 }; };
-struct ei_meta_false { enum { ret = 0 }; };
-
-template<bool Condition, typename Then, typename Else>
-struct ei_meta_if { typedef Then ret; };
-
-template<typename Then, typename Else>
-struct ei_meta_if <false, Then, Else> { typedef Else ret; };
-
-template<typename T, typename U> struct ei_is_same_type { enum { ret = 0 }; };
-template<typename T> struct ei_is_same_type<T,T> { enum { ret = 1 }; };
-
-template<typename T> struct ei_unref { typedef T type; };
-template<typename T> struct ei_unref<T&> { typedef T type; };
-
-template<typename T> struct ei_unpointer { typedef T type; };
-template<typename T> struct ei_unpointer<T*> { typedef T type; };
-template<typename T> struct ei_unpointer<T*const> { typedef T type; };
-
-template<typename T> struct ei_unconst { typedef T type; };
-template<typename T> struct ei_unconst<const T> { typedef T type; };
-template<typename T> struct ei_unconst<T const &> { typedef T & type; };
-template<typename T> struct ei_unconst<T const *> { typedef T * type; };
-
-template<typename T> struct ei_cleantype { typedef T type; };
-template<typename T> struct ei_cleantype<const T>   { typedef typename ei_cleantype<T>::type type; };
-template<typename T> struct ei_cleantype<const T&>  { typedef typename ei_cleantype<T>::type type; };
-template<typename T> struct ei_cleantype<T&>        { typedef typename ei_cleantype<T>::type type; };
-template<typename T> struct ei_cleantype<const T*>  { typedef typename ei_cleantype<T>::type type; };
-template<typename T> struct ei_cleantype<T*>        { typedef typename ei_cleantype<T>::type type; };
-
-/** \internal In short, it computes int(sqrt(\a Y)) with \a Y an integer.
-  * Usage example: \code ei_meta_sqrt<1023>::ret \endcode
-  */
-template<int Y,
-         int InfX = 0,
-         int SupX = ((Y==1) ? 1 : Y/2),
-         bool Done = ((SupX-InfX)<=1 ? true : ((SupX*SupX <= Y) && ((SupX+1)*(SupX+1) > Y))) >
-                                // use ?: instead of || just to shut up a stupid gcc 4.3 warning
-class ei_meta_sqrt
-{
-    enum {
-      MidX = (InfX+SupX)/2,
-      TakeInf = MidX*MidX > Y ? 1 : 0,
-      NewInf = int(TakeInf) ? InfX : int(MidX),
-      NewSup = int(TakeInf) ? int(MidX) : SupX
-    };
-  public:
-    enum { ret = ei_meta_sqrt<Y,NewInf,NewSup>::ret };
-};
-
-template<int Y, int InfX, int SupX>
-class ei_meta_sqrt<Y, InfX, SupX, true> { public:  enum { ret = (SupX*SupX <= Y) ? SupX : InfX }; };
-
-} // end namespace Eigen
-
-#endif // EIGEN2_META_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/Minor.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/Minor.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/Minor.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/Minor.h
@@ -1,117 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_MINOR_H
-#define EIGEN_MINOR_H
-
-namespace Eigen { 
-
-/**
-  * \class Minor
-  *
-  * \brief Expression of a minor
-  *
-  * \param MatrixType the type of the object in which we are taking a minor
-  *
-  * This class represents an expression of a minor. It is the return
-  * type of MatrixBase::minor() and most of the time this is the only way it
-  * is used.
-  *
-  * \sa MatrixBase::minor()
-  */
-
-namespace internal {
-template<typename MatrixType>
-struct traits<Minor<MatrixType> >
- : traits<MatrixType>
-{
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
-  typedef typename MatrixType::StorageKind StorageKind;
-  enum {
-    RowsAtCompileTime = (MatrixType::RowsAtCompileTime != Dynamic) ?
-                          int(MatrixType::RowsAtCompileTime) - 1 : Dynamic,
-    ColsAtCompileTime = (MatrixType::ColsAtCompileTime != Dynamic) ?
-                          int(MatrixType::ColsAtCompileTime) - 1 : Dynamic,
-    MaxRowsAtCompileTime = (MatrixType::MaxRowsAtCompileTime != Dynamic) ?
-                             int(MatrixType::MaxRowsAtCompileTime) - 1 : Dynamic,
-    MaxColsAtCompileTime = (MatrixType::MaxColsAtCompileTime != Dynamic) ?
-                             int(MatrixType::MaxColsAtCompileTime) - 1 : Dynamic,
-    Flags = _MatrixTypeNested::Flags & (HereditaryBits | LvalueBit),
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost // minor is used typically on tiny matrices,
-      // where loops are unrolled and the 'if' evaluates at compile time
-  };
-};
-}
-
-template<typename MatrixType> class Minor
-  : public MatrixBase<Minor<MatrixType> >
-{
-  public:
-
-    typedef MatrixBase<Minor> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(Minor)
-
-    inline Minor(const MatrixType& matrix,
-                       Index row, Index col)
-      : m_matrix(matrix), m_row(row), m_col(col)
-    {
-      eigen_assert(row >= 0 && row < matrix.rows()
-          && col >= 0 && col < matrix.cols());
-    }
-
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Minor)
-
-    inline Index rows() const { return m_matrix.rows() - 1; }
-    inline Index cols() const { return m_matrix.cols() - 1; }
-
-    inline Scalar& coeffRef(Index row, Index col)
-    {
-      return m_matrix.const_cast_derived().coeffRef(row + (row >= m_row), col + (col >= m_col));
-    }
-
-    inline const Scalar coeff(Index row, Index col) const
-    {
-      return m_matrix.coeff(row + (row >= m_row), col + (col >= m_col));
-    }
-
-  protected:
-    const typename MatrixType::Nested m_matrix;
-    const Index m_row, m_col;
-};
-
-/**
-  * \return an expression of the (\a row, \a col)-minor of *this,
-  * i.e. an expression constructed from *this by removing the specified
-  * row and column.
-  *
-  * Example: \include MatrixBase_minor.cpp
-  * Output: \verbinclude MatrixBase_minor.out
-  *
-  * \sa class Minor
-  */
-template<typename Derived>
-inline Minor<Derived>
-MatrixBase<Derived>::minor(Index row, Index col)
-{
-  return Minor<Derived>(derived(), row, col);
-}
-
-/**
-  * This is the const version of minor(). */
-template<typename Derived>
-inline const Minor<Derived>
-MatrixBase<Derived>::minor(Index row, Index col) const
-{
-  return Minor<Derived>(derived(), row, col);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_MINOR_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/QR.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/QR.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/QR.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/QR.h
@@ -1,67 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_QR_H
-#define EIGEN2_QR_H
-
-namespace Eigen { 
-
-template<typename MatrixType>
-class QR : public HouseholderQR<MatrixType>
-{
-  public:
-
-    typedef HouseholderQR<MatrixType> Base;
-    typedef Block<const MatrixType, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> MatrixRBlockType;
-
-    QR() : Base() {}
-
-    template<typename T>
-    explicit QR(const T& t) : Base(t) {}
-
-    template<typename OtherDerived, typename ResultType>
-    bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
-    {
-      *result = static_cast<const Base*>(this)->solve(b);
-      return true;
-    }
-
-    MatrixType matrixQ(void) const {
-      MatrixType ret = MatrixType::Identity(this->rows(), this->cols());
-      ret = this->householderQ() * ret;
-      return ret;
-    }
-
-    bool isFullRank() const {
-      return true;
-    }
-    
-    const TriangularView<MatrixRBlockType, UpperTriangular>
-    matrixR(void) const
-    {
-      int cols = this->cols();
-      return MatrixRBlockType(this->matrixQR(), 0, 0, cols, cols).template triangularView<UpperTriangular>();
-    }
-};
-
-/** \return the QR decomposition of \c *this.
-  *
-  * \sa class QR
-  */
-template<typename Derived>
-const QR<typename MatrixBase<Derived>::PlainObject>
-MatrixBase<Derived>::qr() const
-{
-  return QR<PlainObject>(eval());
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN2_QR_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/SVD.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/SVD.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/SVD.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/SVD.h
@@ -1,637 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_SVD_H
-#define EIGEN2_SVD_H
-
-namespace Eigen {
-
-/** \ingroup SVD_Module
-  * \nonstableyet
-  *
-  * \class SVD
-  *
-  * \brief Standard SVD decomposition of a matrix and associated features
-  *
-  * \param MatrixType the type of the matrix of which we are computing the SVD decomposition
-  *
-  * This class performs a standard SVD decomposition of a real matrix A of size \c M x \c N
-  * with \c M \>= \c N.
-  *
-  *
-  * \sa MatrixBase::SVD()
-  */
-template<typename MatrixType> class SVD
-{
-  private:
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-
-    enum {
-      PacketSize = internal::packet_traits<Scalar>::size,
-      AlignmentMask = int(PacketSize)-1,
-      MinSize = EIGEN_SIZE_MIN_PREFER_DYNAMIC(MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime)
-    };
-
-    typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> ColVector;
-    typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> RowVector;
-
-    typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MinSize> MatrixUType;
-    typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> MatrixVType;
-    typedef Matrix<Scalar, MinSize, 1> SingularValuesType;
-
-  public:
-
-    SVD() {} // a user who relied on compiler-generated default compiler reported problems with MSVC in 2.0.7
-    
-    SVD(const MatrixType& matrix)
-      : m_matU(matrix.rows(), (std::min)(matrix.rows(), matrix.cols())),
-        m_matV(matrix.cols(),matrix.cols()),
-        m_sigma((std::min)(matrix.rows(),matrix.cols()))
-    {
-      compute(matrix);
-    }
-
-    template<typename OtherDerived, typename ResultType>
-    bool solve(const MatrixBase<OtherDerived> &b, ResultType* result) const;
-
-    const MatrixUType& matrixU() const { return m_matU; }
-    const SingularValuesType& singularValues() const { return m_sigma; }
-    const MatrixVType& matrixV() const { return m_matV; }
-
-    void compute(const MatrixType& matrix);
-    SVD& sort();
-
-    template<typename UnitaryType, typename PositiveType>
-    void computeUnitaryPositive(UnitaryType *unitary, PositiveType *positive) const;
-    template<typename PositiveType, typename UnitaryType>
-    void computePositiveUnitary(PositiveType *positive, UnitaryType *unitary) const;
-    template<typename RotationType, typename ScalingType>
-    void computeRotationScaling(RotationType *unitary, ScalingType *positive) const;
-    template<typename ScalingType, typename RotationType>
-    void computeScalingRotation(ScalingType *positive, RotationType *unitary) const;
-
-  protected:
-    /** \internal */
-    MatrixUType m_matU;
-    /** \internal */
-    MatrixVType m_matV;
-    /** \internal */
-    SingularValuesType m_sigma;
-};
-
-/** Computes / recomputes the SVD decomposition A = U S V^* of \a matrix
-  *
-  * \note this code has been adapted from JAMA (public domain)
-  */
-template<typename MatrixType>
-void SVD<MatrixType>::compute(const MatrixType& matrix)
-{
-  const int m = matrix.rows();
-  const int n = matrix.cols();
-  const int nu = (std::min)(m,n);
-  ei_assert(m>=n && "In Eigen 2.0, SVD only works for MxN matrices with M>=N. Sorry!");
-  ei_assert(m>1 && "In Eigen 2.0, SVD doesn't work on 1x1 matrices");
-
-  m_matU.resize(m, nu);
-  m_matU.setZero();
-  m_sigma.resize((std::min)(m,n));
-  m_matV.resize(n,n);
-
-  RowVector e(n);
-  ColVector work(m);
-  MatrixType matA(matrix);
-  const bool wantu = true;
-  const bool wantv = true;
-  int i=0, j=0, k=0;
-
-  // Reduce A to bidiagonal form, storing the diagonal elements
-  // in s and the super-diagonal elements in e.
-  int nct = (std::min)(m-1,n);
-  int nrt = (std::max)(0,(std::min)(n-2,m));
-  for (k = 0; k < (std::max)(nct,nrt); ++k)
-  {
-    if (k < nct)
-    {
-      // Compute the transformation for the k-th column and
-      // place the k-th diagonal in m_sigma[k].
-      m_sigma[k] = matA.col(k).end(m-k).norm();
-      if (m_sigma[k] != 0.0) // FIXME
-      {
-        if (matA(k,k) < 0.0)
-          m_sigma[k] = -m_sigma[k];
-        matA.col(k).end(m-k) /= m_sigma[k];
-        matA(k,k) += 1.0;
-      }
-      m_sigma[k] = -m_sigma[k];
-    }
-
-    for (j = k+1; j < n; ++j)
-    {
-      if ((k < nct) && (m_sigma[k] != 0.0))
-      {
-        // Apply the transformation.
-        Scalar t = matA.col(k).end(m-k).eigen2_dot(matA.col(j).end(m-k)); // FIXME dot product or cwise prod + .sum() ??
-        t = -t/matA(k,k);
-        matA.col(j).end(m-k) += t * matA.col(k).end(m-k);
-      }
-
-      // Place the k-th row of A into e for the
-      // subsequent calculation of the row transformation.
-      e[j] = matA(k,j);
-    }
-
-    // Place the transformation in U for subsequent back multiplication.
-    if (wantu & (k < nct))
-      m_matU.col(k).end(m-k) = matA.col(k).end(m-k);
-
-    if (k < nrt)
-    {
-      // Compute the k-th row transformation and place the
-      // k-th super-diagonal in e[k].
-      e[k] = e.end(n-k-1).norm();
-      if (e[k] != 0.0)
-      {
-          if (e[k+1] < 0.0)
-            e[k] = -e[k];
-          e.end(n-k-1) /= e[k];
-          e[k+1] += 1.0;
-      }
-      e[k] = -e[k];
-      if ((k+1 < m) & (e[k] != 0.0))
-      {
-        // Apply the transformation.
-        work.end(m-k-1) = matA.corner(BottomRight,m-k-1,n-k-1) * e.end(n-k-1);
-        for (j = k+1; j < n; ++j)
-          matA.col(j).end(m-k-1) += (-e[j]/e[k+1]) * work.end(m-k-1);
-      }
-
-      // Place the transformation in V for subsequent back multiplication.
-      if (wantv)
-        m_matV.col(k).end(n-k-1) = e.end(n-k-1);
-    }
-  }
-
-
-  // Set up the final bidiagonal matrix or order p.
-  int p = (std::min)(n,m+1);
-  if (nct < n)
-    m_sigma[nct] = matA(nct,nct);
-  if (m < p)
-    m_sigma[p-1] = 0.0;
-  if (nrt+1 < p)
-    e[nrt] = matA(nrt,p-1);
-  e[p-1] = 0.0;
-
-  // If required, generate U.
-  if (wantu)
-  {
-    for (j = nct; j < nu; ++j)
-    {
-      m_matU.col(j).setZero();
-      m_matU(j,j) = 1.0;
-    }
-    for (k = nct-1; k >= 0; k--)
-    {
-      if (m_sigma[k] != 0.0)
-      {
-        for (j = k+1; j < nu; ++j)
-        {
-          Scalar t = m_matU.col(k).end(m-k).eigen2_dot(m_matU.col(j).end(m-k)); // FIXME is it really a dot product we want ?
-          t = -t/m_matU(k,k);
-          m_matU.col(j).end(m-k) += t * m_matU.col(k).end(m-k);
-        }
-        m_matU.col(k).end(m-k) = - m_matU.col(k).end(m-k);
-        m_matU(k,k) = Scalar(1) + m_matU(k,k);
-        if (k-1>0)
-          m_matU.col(k).start(k-1).setZero();
-      }
-      else
-      {
-        m_matU.col(k).setZero();
-        m_matU(k,k) = 1.0;
-      }
-    }
-  }
-
-  // If required, generate V.
-  if (wantv)
-  {
-    for (k = n-1; k >= 0; k--)
-    {
-      if ((k < nrt) & (e[k] != 0.0))
-      {
-        for (j = k+1; j < nu; ++j)
-        {
-          Scalar t = m_matV.col(k).end(n-k-1).eigen2_dot(m_matV.col(j).end(n-k-1)); // FIXME is it really a dot product we want ?
-          t = -t/m_matV(k+1,k);
-          m_matV.col(j).end(n-k-1) += t * m_matV.col(k).end(n-k-1);
-        }
-      }
-      m_matV.col(k).setZero();
-      m_matV(k,k) = 1.0;
-    }
-  }
-
-  // Main iteration loop for the singular values.
-  int pp = p-1;
-  int iter = 0;
-  Scalar eps = ei_pow(Scalar(2),ei_is_same_type<Scalar,float>::ret ? Scalar(-23) : Scalar(-52));
-  while (p > 0)
-  {
-    int k=0;
-    int kase=0;
-
-    // Here is where a test for too many iterations would go.
-
-    // This section of the program inspects for
-    // negligible elements in the s and e arrays.  On
-    // completion the variables kase and k are set as follows.
-
-    // kase = 1     if s(p) and e[k-1] are negligible and k<p
-    // kase = 2     if s(k) is negligible and k<p
-    // kase = 3     if e[k-1] is negligible, k<p, and
-    //              s(k), ..., s(p) are not negligible (qr step).
-    // kase = 4     if e(p-1) is negligible (convergence).
-
-    for (k = p-2; k >= -1; --k)
-    {
-      if (k == -1)
-          break;
-      if (ei_abs(e[k]) <= eps*(ei_abs(m_sigma[k]) + ei_abs(m_sigma[k+1])))
-      {
-          e[k] = 0.0;
-          break;
-      }
-    }
-    if (k == p-2)
-    {
-      kase = 4;
-    }
-    else
-    {
-      int ks;
-      for (ks = p-1; ks >= k; --ks)
-      {
-        if (ks == k)
-          break;
-        Scalar t = (ks != p ? ei_abs(e[ks]) : Scalar(0)) + (ks != k+1 ? ei_abs(e[ks-1]) : Scalar(0));
-        if (ei_abs(m_sigma[ks]) <= eps*t)
-        {
-          m_sigma[ks] = 0.0;
-          break;
-        }
-      }
-      if (ks == k)
-      {
-        kase = 3;
-      }
-      else if (ks == p-1)
-      {
-        kase = 1;
-      }
-      else
-      {
-        kase = 2;
-        k = ks;
-      }
-    }
-    ++k;
-
-    // Perform the task indicated by kase.
-    switch (kase)
-    {
-
-      // Deflate negligible s(p).
-      case 1:
-      {
-        Scalar f(e[p-2]);
-        e[p-2] = 0.0;
-        for (j = p-2; j >= k; --j)
-        {
-          Scalar t(numext::hypot(m_sigma[j],f));
-          Scalar cs(m_sigma[j]/t);
-          Scalar sn(f/t);
-          m_sigma[j] = t;
-          if (j != k)
-          {
-            f = -sn*e[j-1];
-            e[j-1] = cs*e[j-1];
-          }
-          if (wantv)
-          {
-            for (i = 0; i < n; ++i)
-            {
-              t = cs*m_matV(i,j) + sn*m_matV(i,p-1);
-              m_matV(i,p-1) = -sn*m_matV(i,j) + cs*m_matV(i,p-1);
-              m_matV(i,j) = t;
-            }
-          }
-        }
-      }
-      break;
-
-      // Split at negligible s(k).
-      case 2:
-      {
-        Scalar f(e[k-1]);
-        e[k-1] = 0.0;
-        for (j = k; j < p; ++j)
-        {
-          Scalar t(numext::hypot(m_sigma[j],f));
-          Scalar cs( m_sigma[j]/t);
-          Scalar sn(f/t);
-          m_sigma[j] = t;
-          f = -sn*e[j];
-          e[j] = cs*e[j];
-          if (wantu)
-          {
-            for (i = 0; i < m; ++i)
-            {
-              t = cs*m_matU(i,j) + sn*m_matU(i,k-1);
-              m_matU(i,k-1) = -sn*m_matU(i,j) + cs*m_matU(i,k-1);
-              m_matU(i,j) = t;
-            }
-          }
-        }
-      }
-      break;
-
-      // Perform one qr step.
-      case 3:
-      {
-        // Calculate the shift.
-        Scalar scale = (std::max)((std::max)((std::max)((std::max)(
-                        ei_abs(m_sigma[p-1]),ei_abs(m_sigma[p-2])),ei_abs(e[p-2])),
-                        ei_abs(m_sigma[k])),ei_abs(e[k]));
-        Scalar sp = m_sigma[p-1]/scale;
-        Scalar spm1 = m_sigma[p-2]/scale;
-        Scalar epm1 = e[p-2]/scale;
-        Scalar sk = m_sigma[k]/scale;
-        Scalar ek = e[k]/scale;
-        Scalar b = ((spm1 + sp)*(spm1 - sp) + epm1*epm1)/Scalar(2);
-        Scalar c = (sp*epm1)*(sp*epm1);
-        Scalar shift(0);
-        if ((b != 0.0) || (c != 0.0))
-        {
-          shift = ei_sqrt(b*b + c);
-          if (b < 0.0)
-            shift = -shift;
-          shift = c/(b + shift);
-        }
-        Scalar f = (sk + sp)*(sk - sp) + shift;
-        Scalar g = sk*ek;
-
-        // Chase zeros.
-
-        for (j = k; j < p-1; ++j)
-        {
-          Scalar t = numext::hypot(f,g);
-          Scalar cs = f/t;
-          Scalar sn = g/t;
-          if (j != k)
-            e[j-1] = t;
-          f = cs*m_sigma[j] + sn*e[j];
-          e[j] = cs*e[j] - sn*m_sigma[j];
-          g = sn*m_sigma[j+1];
-          m_sigma[j+1] = cs*m_sigma[j+1];
-          if (wantv)
-          {
-            for (i = 0; i < n; ++i)
-            {
-              t = cs*m_matV(i,j) + sn*m_matV(i,j+1);
-              m_matV(i,j+1) = -sn*m_matV(i,j) + cs*m_matV(i,j+1);
-              m_matV(i,j) = t;
-            }
-          }
-          t = numext::hypot(f,g);
-          cs = f/t;
-          sn = g/t;
-          m_sigma[j] = t;
-          f = cs*e[j] + sn*m_sigma[j+1];
-          m_sigma[j+1] = -sn*e[j] + cs*m_sigma[j+1];
-          g = sn*e[j+1];
-          e[j+1] = cs*e[j+1];
-          if (wantu && (j < m-1))
-          {
-            for (i = 0; i < m; ++i)
-            {
-              t = cs*m_matU(i,j) + sn*m_matU(i,j+1);
-              m_matU(i,j+1) = -sn*m_matU(i,j) + cs*m_matU(i,j+1);
-              m_matU(i,j) = t;
-            }
-          }
-        }
-        e[p-2] = f;
-        iter = iter + 1;
-      }
-      break;
-
-      // Convergence.
-      case 4:
-      {
-        // Make the singular values positive.
-        if (m_sigma[k] <= 0.0)
-        {
-          m_sigma[k] = m_sigma[k] < Scalar(0) ? -m_sigma[k] : Scalar(0);
-          if (wantv)
-            m_matV.col(k).start(pp+1) = -m_matV.col(k).start(pp+1);
-        }
-
-        // Order the singular values.
-        while (k < pp)
-        {
-          if (m_sigma[k] >= m_sigma[k+1])
-            break;
-          Scalar t = m_sigma[k];
-          m_sigma[k] = m_sigma[k+1];
-          m_sigma[k+1] = t;
-          if (wantv && (k < n-1))
-            m_matV.col(k).swap(m_matV.col(k+1));
-          if (wantu && (k < m-1))
-            m_matU.col(k).swap(m_matU.col(k+1));
-          ++k;
-        }
-        iter = 0;
-        p--;
-      }
-      break;
-    } // end big switch
-  } // end iterations
-}
-
-template<typename MatrixType>
-SVD<MatrixType>& SVD<MatrixType>::sort()
-{
-  int mu = m_matU.rows();
-  int mv = m_matV.rows();
-  int n  = m_matU.cols();
-
-  for (int i=0; i<n; ++i)
-  {
-    int  k = i;
-    Scalar p = m_sigma.coeff(i);
-
-    for (int j=i+1; j<n; ++j)
-    {
-      if (m_sigma.coeff(j) > p)
-      {
-        k = j;
-        p = m_sigma.coeff(j);
-      }
-    }
-    if (k != i)
-    {
-      m_sigma.coeffRef(k) = m_sigma.coeff(i);  // i.e.
-      m_sigma.coeffRef(i) = p;                 // swaps the i-th and the k-th elements
-
-      int j = mu;
-      for(int s=0; j!=0; ++s, --j)
-        std::swap(m_matU.coeffRef(s,i), m_matU.coeffRef(s,k));
-
-      j = mv;
-      for (int s=0; j!=0; ++s, --j)
-        std::swap(m_matV.coeffRef(s,i), m_matV.coeffRef(s,k));
-    }
-  }
-  return *this;
-}
-
-/** \returns the solution of \f$ A x = b \f$ using the current SVD decomposition of A.
-  * The parts of the solution corresponding to zero singular values are ignored.
-  *
-  * \sa MatrixBase::svd(), LU::solve(), LLT::solve()
-  */
-template<typename MatrixType>
-template<typename OtherDerived, typename ResultType>
-bool SVD<MatrixType>::solve(const MatrixBase<OtherDerived> &b, ResultType* result) const
-{
-  ei_assert(b.rows() == m_matU.rows());
-
-  Scalar maxVal = m_sigma.cwise().abs().maxCoeff();
-  for (int j=0; j<b.cols(); ++j)
-  {
-    Matrix<Scalar,MatrixUType::RowsAtCompileTime,1> aux = m_matU.transpose() * b.col(j);
-
-    for (int i = 0; i <m_matU.cols(); ++i)
-    {
-      Scalar si = m_sigma.coeff(i);
-      if (ei_isMuchSmallerThan(ei_abs(si),maxVal))
-        aux.coeffRef(i) = 0;
-      else
-        aux.coeffRef(i) /= si;
-    }
-
-    result->col(j) = m_matV * aux;
-  }
-  return true;
-}
-
-/** Computes the polar decomposition of the matrix, as a product unitary x positive.
-  *
-  * If either pointer is zero, the corresponding computation is skipped.
-  *
-  * Only for square matrices.
-  *
-  * \sa computePositiveUnitary(), computeRotationScaling()
-  */
-template<typename MatrixType>
-template<typename UnitaryType, typename PositiveType>
-void SVD<MatrixType>::computeUnitaryPositive(UnitaryType *unitary,
-                                             PositiveType *positive) const
-{
-  ei_assert(m_matU.cols() == m_matV.cols() && "Polar decomposition is only for square matrices");
-  if(unitary) *unitary = m_matU * m_matV.adjoint();
-  if(positive) *positive = m_matV * m_sigma.asDiagonal() * m_matV.adjoint();
-}
-
-/** Computes the polar decomposition of the matrix, as a product positive x unitary.
-  *
-  * If either pointer is zero, the corresponding computation is skipped.
-  *
-  * Only for square matrices.
-  *
-  * \sa computeUnitaryPositive(), computeRotationScaling()
-  */
-template<typename MatrixType>
-template<typename UnitaryType, typename PositiveType>
-void SVD<MatrixType>::computePositiveUnitary(UnitaryType *positive,
-                                             PositiveType *unitary) const
-{
-  ei_assert(m_matU.rows() == m_matV.rows() && "Polar decomposition is only for square matrices");
-  if(unitary) *unitary = m_matU * m_matV.adjoint();
-  if(positive) *positive = m_matU * m_sigma.asDiagonal() * m_matU.adjoint();
-}
-
-/** decomposes the matrix as a product rotation x scaling, the scaling being
-  * not necessarily positive.
-  *
-  * If either pointer is zero, the corresponding computation is skipped.
-  *
-  * This method requires the Geometry module.
-  *
-  * \sa computeScalingRotation(), computeUnitaryPositive()
-  */
-template<typename MatrixType>
-template<typename RotationType, typename ScalingType>
-void SVD<MatrixType>::computeRotationScaling(RotationType *rotation, ScalingType *scaling) const
-{
-  ei_assert(m_matU.rows() == m_matV.rows() && "Polar decomposition is only for square matrices");
-  Scalar x = (m_matU * m_matV.adjoint()).determinant(); // so x has absolute value 1
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> sv(m_sigma);
-  sv.coeffRef(0) *= x;
-  if(scaling) scaling->lazyAssign(m_matV * sv.asDiagonal() * m_matV.adjoint());
-  if(rotation)
-  {
-    MatrixType m(m_matU);
-    m.col(0) /= x;
-    rotation->lazyAssign(m * m_matV.adjoint());
-  }
-}
-
-/** decomposes the matrix as a product scaling x rotation, the scaling being
-  * not necessarily positive.
-  *
-  * If either pointer is zero, the corresponding computation is skipped.
-  *
-  * This method requires the Geometry module.
-  *
-  * \sa computeRotationScaling(), computeUnitaryPositive()
-  */
-template<typename MatrixType>
-template<typename ScalingType, typename RotationType>
-void SVD<MatrixType>::computeScalingRotation(ScalingType *scaling, RotationType *rotation) const
-{
-  ei_assert(m_matU.rows() == m_matV.rows() && "Polar decomposition is only for square matrices");
-  Scalar x = (m_matU * m_matV.adjoint()).determinant(); // so x has absolute value 1
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> sv(m_sigma);
-  sv.coeffRef(0) *= x;
-  if(scaling) scaling->lazyAssign(m_matU * sv.asDiagonal() * m_matU.adjoint());
-  if(rotation)
-  {
-    MatrixType m(m_matU);
-    m.col(0) /= x;
-    rotation->lazyAssign(m * m_matV.adjoint());
-  }
-}
-
-
-/** \svd_module
-  * \returns the SVD decomposition of \c *this
-  */
-template<typename Derived>
-inline SVD<typename MatrixBase<Derived>::PlainObject>
-MatrixBase<Derived>::svd() const
-{
-  return SVD<PlainObject>(derived());
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN2_SVD_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/TriangularSolver.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/TriangularSolver.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/TriangularSolver.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/TriangularSolver.h
@@ -1,42 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_TRIANGULAR_SOLVER2_H
-#define EIGEN_TRIANGULAR_SOLVER2_H
-
-namespace Eigen { 
-
-const unsigned int UnitDiagBit = UnitDiag;
-const unsigned int SelfAdjointBit = SelfAdjoint;
-const unsigned int UpperTriangularBit = Upper;
-const unsigned int LowerTriangularBit = Lower;
-
-const unsigned int UpperTriangular = Upper;
-const unsigned int LowerTriangular = Lower;
-const unsigned int UnitUpperTriangular = UnitUpper;
-const unsigned int UnitLowerTriangular = UnitLower;
-
-template<typename ExpressionType, unsigned int Added, unsigned int Removed>
-template<typename OtherDerived>
-typename ExpressionType::PlainObject
-Flagged<ExpressionType,Added,Removed>::solveTriangular(const MatrixBase<OtherDerived>& other) const
-{
-  return m_matrix.template triangularView<Added>().solve(other.derived());
-}
-
-template<typename ExpressionType, unsigned int Added, unsigned int Removed>
-template<typename OtherDerived>
-void Flagged<ExpressionType,Added,Removed>::solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const
-{
-  m_matrix.template triangularView<Added>().solveInPlace(other.derived());
-}
-
-} // end namespace Eigen
-    
-#endif // EIGEN_TRIANGULAR_SOLVER2_H

DELETED 3rd_party/eigen/Eigen/src/Eigen2Support/VectorBlock.h
Index: 3rd_party/eigen/Eigen/src/Eigen2Support/VectorBlock.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigen2Support/VectorBlock.h
+++ 3rd_party/eigen/Eigen/src/Eigen2Support/VectorBlock.h
@@ -1,94 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN2_VECTORBLOCK_H
-#define EIGEN2_VECTORBLOCK_H
-
-namespace Eigen { 
-
-/** \deprecated use DenseMase::head(Index) */
-template<typename Derived>
-inline VectorBlock<Derived>
-MatrixBase<Derived>::start(Index size)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return VectorBlock<Derived>(derived(), 0, size);
-}
-
-/** \deprecated use DenseMase::head(Index) */
-template<typename Derived>
-inline const VectorBlock<const Derived>
-MatrixBase<Derived>::start(Index size) const
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return VectorBlock<const Derived>(derived(), 0, size);
-}
-
-/** \deprecated use DenseMase::tail(Index) */
-template<typename Derived>
-inline VectorBlock<Derived>
-MatrixBase<Derived>::end(Index size)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return VectorBlock<Derived>(derived(), this->size() - size, size);
-}
-
-/** \deprecated use DenseMase::tail(Index) */
-template<typename Derived>
-inline const VectorBlock<const Derived>
-MatrixBase<Derived>::end(Index size) const
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return VectorBlock<const Derived>(derived(), this->size() - size, size);
-}
-
-/** \deprecated use DenseMase::head() */
-template<typename Derived>
-template<int Size>
-inline VectorBlock<Derived,Size>
-MatrixBase<Derived>::start()
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return VectorBlock<Derived,Size>(derived(), 0);
-}
-
-/** \deprecated use DenseMase::head() */
-template<typename Derived>
-template<int Size>
-inline const VectorBlock<const Derived,Size>
-MatrixBase<Derived>::start() const
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return VectorBlock<const Derived,Size>(derived(), 0);
-}
-
-/** \deprecated use DenseMase::tail() */
-template<typename Derived>
-template<int Size>
-inline VectorBlock<Derived,Size>
-MatrixBase<Derived>::end()
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return VectorBlock<Derived, Size>(derived(), size() - Size);
-}
-
-/** \deprecated use DenseMase::tail() */
-template<typename Derived>
-template<int Size>
-inline const VectorBlock<const Derived,Size>
-MatrixBase<Derived>::end() const
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return VectorBlock<const Derived, Size>(derived(), size() - Size);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN2_VECTORBLOCK_H

DELETED 3rd_party/eigen/Eigen/src/Eigenvalues/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Eigenvalues/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_EIGENVALUES_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_EIGENVALUES_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Eigenvalues COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h
@@ -58,11 +58,11 @@
     };
 
     /** \brief Scalar type for matrices of type #MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     /** \brief Complex scalar type for #MatrixType.
       *
       * This is \c std::complex<Scalar> if #Scalar is real (e.g.,
       * \c float or \c double) and just \c Scalar if #Scalar is
@@ -102,11 +102,11 @@
       *
       * Like the default constructor but with preallocation of the internal data
       * according to the specified problem \a size.
       * \sa ComplexEigenSolver()
       */
-    ComplexEigenSolver(Index size)
+    explicit ComplexEigenSolver(Index size)
             : m_eivec(size, size),
               m_eivalues(size),
               m_schur(size),
               m_isInitialized(false),
               m_eigenvectorsOk(false),
@@ -120,19 +120,20 @@
       *    eigenvalues are computed; if false, only the eigenvalues are
       *    computed.
       *
       * This constructor calls compute() to compute the eigendecomposition.
       */
-      ComplexEigenSolver(const MatrixType& matrix, bool computeEigenvectors = true)
+    template<typename InputType>
+    explicit ComplexEigenSolver(const EigenBase<InputType>& matrix, bool computeEigenvectors = true)
             : m_eivec(matrix.rows(),matrix.cols()),
               m_eivalues(matrix.cols()),
               m_schur(matrix.rows()),
               m_isInitialized(false),
               m_eigenvectorsOk(false),
               m_matX(matrix.rows(),matrix.cols())
     {
-      compute(matrix, computeEigenvectors);
+      compute(matrix.derived(), computeEigenvectors);
     }
 
     /** \brief Returns the eigenvectors of given matrix.
       *
       * \returns  A const reference to the matrix whose columns are the eigenvectors.
@@ -206,11 +207,12 @@
       * is the size of the matrix.
       *
       * Example: \include ComplexEigenSolver_compute.cpp
       * Output: \verbinclude ComplexEigenSolver_compute.out
       */
-    ComplexEigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true);
+    template<typename InputType>
+    ComplexEigenSolver& compute(const EigenBase<InputType>& matrix, bool computeEigenvectors = true);
 
     /** \brief Reports whether previous computation was successful.
       *
       * \returns \c Success if computation was succesful, \c NoConvergence otherwise.
       */
@@ -232,39 +234,48 @@
     {
       return m_schur.getMaxIterations();
     }
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+    
     EigenvectorType m_eivec;
     EigenvalueType m_eivalues;
     ComplexSchur<MatrixType> m_schur;
     bool m_isInitialized;
     bool m_eigenvectorsOk;
     EigenvectorType m_matX;
 
   private:
-    void doComputeEigenvectors(const RealScalar& matrixnorm);
+    void doComputeEigenvectors(RealScalar matrixnorm);
     void sortEigenvalues(bool computeEigenvectors);
 };
 
 
 template<typename MatrixType>
+template<typename InputType>
 ComplexEigenSolver<MatrixType>& 
-ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
+ComplexEigenSolver<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeEigenvectors)
 {
+  check_template_parameters();
+  
   // this code is inspired from Jampack
   eigen_assert(matrix.cols() == matrix.rows());
 
   // Do a complex Schur decomposition, A = U T U^*
   // The eigenvalues are on the diagonal of T.
-  m_schur.compute(matrix, computeEigenvectors);
+  m_schur.compute(matrix.derived(), computeEigenvectors);
 
   if(m_schur.info() == Success)
   {
     m_eivalues = m_schur.matrixT().diagonal();
     if(computeEigenvectors)
-      doComputeEigenvectors(matrix.norm());
+      doComputeEigenvectors(m_schur.matrixT().norm());
     sortEigenvalues(computeEigenvectors);
   }
 
   m_isInitialized = true;
   m_eigenvectorsOk = computeEigenvectors;
@@ -271,13 +282,15 @@
   return *this;
 }
 
 
 template<typename MatrixType>
-void ComplexEigenSolver<MatrixType>::doComputeEigenvectors(const RealScalar& matrixnorm)
+void ComplexEigenSolver<MatrixType>::doComputeEigenvectors(RealScalar matrixnorm)
 {
   const Index n = m_eivalues.size();
+
+  matrixnorm = numext::maxi(matrixnorm,(std::numeric_limits<RealScalar>::min)());
 
   // Compute X such that T = X D X^(-1), where D is the diagonal of T.
   // The matrix X is unit triangular.
   m_matX = EigenvectorType::Zero(n, n);
   for(Index k=n-1 ; k>=0 ; k--)

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur.h
@@ -61,11 +61,11 @@
     };
 
     /** \brief Scalar type for matrices of type \p _MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     /** \brief Complex scalar type for \p _MatrixType. 
       *
       * This is \c std::complex<Scalar> if #Scalar is real (e.g.,
       * \c float or \c double) and just \c Scalar if #Scalar is
@@ -89,11 +89,11 @@
       * parameter is only used as a hint. It is not an error to give a
       * wrong \p size, but it may impair performance.
       *
       * \sa compute() for an example.
       */
-    ComplexSchur(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime)
+    explicit ComplexSchur(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime)
       : m_matT(size,size),
         m_matU(size,size),
         m_hess(size),
         m_isInitialized(false),
         m_matUisUptodate(false),
@@ -107,19 +107,20 @@
       *
       * This constructor calls compute() to compute the Schur decomposition.
       *
       * \sa matrixT() and matrixU() for examples.
       */
-    ComplexSchur(const MatrixType& matrix, bool computeU = true)
+    template<typename InputType>
+    explicit ComplexSchur(const EigenBase<InputType>& matrix, bool computeU = true)
       : m_matT(matrix.rows(),matrix.cols()),
         m_matU(matrix.rows(),matrix.cols()),
         m_hess(matrix.rows()),
         m_isInitialized(false),
         m_matUisUptodate(false),
         m_maxIters(-1)
     {
-      compute(matrix, computeU);
+      compute(matrix.derived(), computeU);
     }
 
     /** \brief Returns the unitary matrix in the Schur decomposition. 
       *
       * \returns A const reference to the matrix U.
@@ -184,11 +185,12 @@
       * Example: \include ComplexSchur_compute.cpp
       * Output: \verbinclude ComplexSchur_compute.out
       *
       * \sa compute(const MatrixType&, bool, Index)
       */
-    ComplexSchur& compute(const MatrixType& matrix, bool computeU = true);
+    template<typename InputType>
+    ComplexSchur& compute(const EigenBase<InputType>& matrix, bool computeU = true);
     
     /** \brief Compute Schur decomposition from a given Hessenberg matrix
      *  \param[in] matrixH Matrix in Hessenberg form H
      *  \param[in] matrixQ orthogonal matrix Q that transform a matrix A to H : A = Q H Q^T
      *  \param computeU Computes the matriX U of the Schur vectors
@@ -311,26 +313,27 @@
     return normt * eival2;
 }
 
 
 template<typename MatrixType>
-ComplexSchur<MatrixType>& ComplexSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU)
+template<typename InputType>
+ComplexSchur<MatrixType>& ComplexSchur<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeU)
 {
   m_matUisUptodate = false;
   eigen_assert(matrix.cols() == matrix.rows());
 
   if(matrix.cols() == 1)
   {
-    m_matT = matrix.template cast<ComplexScalar>();
+    m_matT = matrix.derived().template cast<ComplexScalar>();
     if(computeU)  m_matU = ComplexMatrixType::Identity(1,1);
     m_info = Success;
     m_isInitialized = true;
     m_matUisUptodate = computeU;
     return *this;
   }
 
-  internal::complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>::run(*this, matrix, computeU);
+  internal::complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>::run(*this, matrix.derived(), computeU);
   computeFromHessenberg(m_matT, m_matU, computeU);
   return *this;
 }
 
 template<typename MatrixType>

ADDED   3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur_LAPACKE.h
Index: 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur_LAPACKE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur_LAPACKE.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur_LAPACKE.h
@@ -0,0 +1,91 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to LAPACKe
+ *    Complex Schur needed to complex unsymmetrical eigenvalues/eigenvectors.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_COMPLEX_SCHUR_LAPACKE_H
+#define EIGEN_COMPLEX_SCHUR_LAPACKE_H
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by LAPACKe */
+
+#define EIGEN_LAPACKE_SCHUR_COMPLEX(EIGTYPE, LAPACKE_TYPE, LAPACKE_PREFIX, LAPACKE_PREFIX_U, EIGCOLROW, LAPACKE_COLROW) \
+template<> template<typename InputType> inline \
+ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
+ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const EigenBase<InputType>& matrix, bool computeU) \
+{ \
+  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> MatrixType; \
+  typedef MatrixType::RealScalar RealScalar; \
+  typedef std::complex<RealScalar> ComplexScalar; \
+\
+  eigen_assert(matrix.cols() == matrix.rows()); \
+\
+  m_matUisUptodate = false; \
+  if(matrix.cols() == 1) \
+  { \
+    m_matT = matrix.derived().template cast<ComplexScalar>(); \
+    if(computeU)  m_matU = ComplexMatrixType::Identity(1,1); \
+      m_info = Success; \
+      m_isInitialized = true; \
+      m_matUisUptodate = computeU; \
+      return *this; \
+  } \
+  lapack_int n = internal::convert_index<lapack_int>(matrix.cols()), sdim, info; \
+  lapack_int matrix_order = LAPACKE_COLROW; \
+  char jobvs, sort='N'; \
+  LAPACK_##LAPACKE_PREFIX_U##_SELECT1 select = 0; \
+  jobvs = (computeU) ? 'V' : 'N'; \
+  m_matU.resize(n, n); \
+  lapack_int ldvs  = internal::convert_index<lapack_int>(m_matU.outerStride()); \
+  m_matT = matrix; \
+  lapack_int lda = internal::convert_index<lapack_int>(m_matT.outerStride()); \
+  Matrix<EIGTYPE, Dynamic, Dynamic> w; \
+  w.resize(n, 1);\
+  info = LAPACKE_##LAPACKE_PREFIX##gees( matrix_order, jobvs, sort, select, n, (LAPACKE_TYPE*)m_matT.data(), lda, &sdim, (LAPACKE_TYPE*)w.data(), (LAPACKE_TYPE*)m_matU.data(), ldvs ); \
+  if(info == 0) \
+    m_info = Success; \
+  else \
+    m_info = NoConvergence; \
+\
+  m_isInitialized = true; \
+  m_matUisUptodate = computeU; \
+  return *this; \
+\
+}
+
+EIGEN_LAPACKE_SCHUR_COMPLEX(dcomplex, lapack_complex_double, z, Z, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_SCHUR_COMPLEX(scomplex, lapack_complex_float,  c, C, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_SCHUR_COMPLEX(dcomplex, lapack_complex_double, z, Z, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_SCHUR_COMPLEX(scomplex, lapack_complex_float,  c, C, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_COMPLEX_SCHUR_LAPACKE_H

DELETED 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
Index: 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
@@ -1,94 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *    Complex Schur needed to complex unsymmetrical eigenvalues/eigenvectors.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_COMPLEX_SCHUR_MKL_H
-#define EIGEN_COMPLEX_SCHUR_MKL_H
-
-#include "Eigen/src/Core/util/MKL_support.h"
-
-namespace Eigen { 
-
-/** \internal Specialization for the data types supported by MKL */
-
-#define EIGEN_MKL_SCHUR_COMPLEX(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \
-template<> inline \
-ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
-ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, bool computeU) \
-{ \
-  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> MatrixType; \
-  typedef MatrixType::Scalar Scalar; \
-  typedef MatrixType::RealScalar RealScalar; \
-  typedef std::complex<RealScalar> ComplexScalar; \
-\
-  eigen_assert(matrix.cols() == matrix.rows()); \
-\
-  m_matUisUptodate = false; \
-  if(matrix.cols() == 1) \
-  { \
-    m_matT = matrix.cast<ComplexScalar>(); \
-    if(computeU)  m_matU = ComplexMatrixType::Identity(1,1); \
-      m_info = Success; \
-      m_isInitialized = true; \
-      m_matUisUptodate = computeU; \
-      return *this; \
-  } \
-  lapack_int n = matrix.cols(), sdim, info; \
-  lapack_int lda = matrix.outerStride(); \
-  lapack_int matrix_order = MKLCOLROW; \
-  char jobvs, sort='N'; \
-  LAPACK_##MKLPREFIX_U##_SELECT1 select = 0; \
-  jobvs = (computeU) ? 'V' : 'N'; \
-  m_matU.resize(n, n); \
-  lapack_int ldvs  = m_matU.outerStride(); \
-  m_matT = matrix; \
-  Matrix<EIGTYPE, Dynamic, Dynamic> w; \
-  w.resize(n, 1);\
-  info = LAPACKE_##MKLPREFIX##gees( matrix_order, jobvs, sort, select, n, (MKLTYPE*)m_matT.data(), lda, &sdim, (MKLTYPE*)w.data(), (MKLTYPE*)m_matU.data(), ldvs ); \
-  if(info == 0) \
-    m_info = Success; \
-  else \
-    m_info = NoConvergence; \
-\
-  m_isInitialized = true; \
-  m_matUisUptodate = computeU; \
-  return *this; \
-\
-}
-
-EIGEN_MKL_SCHUR_COMPLEX(dcomplex, MKL_Complex16, z, Z, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_SCHUR_COMPLEX(scomplex, MKL_Complex8,  c, C, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_SCHUR_COMPLEX(dcomplex, MKL_Complex16, z, Z, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_SCHUR_COMPLEX(scomplex, MKL_Complex8,  c, C, RowMajor, LAPACK_ROW_MAJOR)
-
-} // end namespace Eigen
-
-#endif // EIGEN_COMPLEX_SCHUR_MKL_H

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/EigenSolver.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/EigenSolver.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/EigenSolver.h
@@ -77,11 +77,11 @@
     };
 
     /** \brief Scalar type for matrices of type #MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     /** \brief Complex scalar type for #MatrixType. 
       *
       * This is \c std::complex<Scalar> if #Scalar is real (e.g.,
       * \c float or \c double) and just \c Scalar if #Scalar is
@@ -108,19 +108,19 @@
       * The default constructor is useful in cases in which the user intends to
       * perform decompositions via EigenSolver::compute(const MatrixType&, bool).
       *
       * \sa compute() for an example.
       */
- EigenSolver() : m_eivec(), m_eivalues(), m_isInitialized(false), m_realSchur(), m_matT(), m_tmp() {}
+    EigenSolver() : m_eivec(), m_eivalues(), m_isInitialized(false), m_realSchur(), m_matT(), m_tmp() {}
 
     /** \brief Default constructor with memory preallocation
       *
       * Like the default constructor but with preallocation of the internal data
       * according to the specified problem \a size.
       * \sa EigenSolver()
       */
-    EigenSolver(Index size)
+    explicit EigenSolver(Index size)
       : m_eivec(size, size),
         m_eivalues(size),
         m_isInitialized(false),
         m_eigenvectorsOk(false),
         m_realSchur(size),
@@ -141,20 +141,21 @@
       * Example: \include EigenSolver_EigenSolver_MatrixType.cpp
       * Output: \verbinclude EigenSolver_EigenSolver_MatrixType.out
       *
       * \sa compute()
       */
-    EigenSolver(const MatrixType& matrix, bool computeEigenvectors = true)
+    template<typename InputType>
+    explicit EigenSolver(const EigenBase<InputType>& matrix, bool computeEigenvectors = true)
       : m_eivec(matrix.rows(), matrix.cols()),
         m_eivalues(matrix.cols()),
         m_isInitialized(false),
         m_eigenvectorsOk(false),
         m_realSchur(matrix.cols()),
         m_matT(matrix.rows(), matrix.cols()), 
         m_tmp(matrix.cols())
     {
-      compute(matrix, computeEigenvectors);
+      compute(matrix.derived(), computeEigenvectors);
     }
 
     /** \brief Returns the eigenvectors of given matrix. 
       *
       * \returns  %Matrix whose columns are the (possibly complex) eigenvectors.
@@ -271,16 +272,18 @@
       * This method reuses of the allocated data in the EigenSolver object.
       *
       * Example: \include EigenSolver_compute.cpp
       * Output: \verbinclude EigenSolver_compute.out
       */
-    EigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true);
+    template<typename InputType>
+    EigenSolver& compute(const EigenBase<InputType>& matrix, bool computeEigenvectors = true);
 
+    /** \returns NumericalIssue if the input contains INF or NaN values or overflow occured. Returns Success otherwise. */
     ComputationInfo info() const
     {
       eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
-      return m_realSchur.info();
+      return m_info;
     }
 
     /** \brief Sets the maximum number of iterations allowed. */
     EigenSolver& setMaxIterations(Index maxIters)
     {
@@ -296,14 +299,22 @@
 
   private:
     void doComputeEigenvectors();
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+      EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL);
+    }
+    
     MatrixType m_eivec;
     EigenvalueType m_eivalues;
     bool m_isInitialized;
     bool m_eigenvectorsOk;
+    ComputationInfo m_info;
     RealSchur<MatrixType> m_realSchur;
     MatrixType m_matT;
 
     typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ColumnVectorType;
     ColumnVectorType m_tmp;
@@ -311,15 +322,16 @@
 
 template<typename MatrixType>
 MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const
 {
   eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
+  const RealScalar precision = RealScalar(2)*NumTraits<RealScalar>::epsilon();
   Index n = m_eivalues.rows();
   MatrixType matD = MatrixType::Zero(n,n);
   for (Index i=0; i<n; ++i)
   {
-    if (internal::isMuchSmallerThan(numext::imag(m_eivalues.coeff(i)), numext::real(m_eivalues.coeff(i))))
+    if (internal::isMuchSmallerThan(numext::imag(m_eivalues.coeff(i)), numext::real(m_eivalues.coeff(i)), precision))
       matD.coeffRef(i,i) = numext::real(m_eivalues.coeff(i));
     else
     {
       matD.template block<2,2>(i,i) <<  numext::real(m_eivalues.coeff(i)), numext::imag(m_eivalues.coeff(i)),
                                        -numext::imag(m_eivalues.coeff(i)), numext::real(m_eivalues.coeff(i));
@@ -332,15 +344,16 @@
 template<typename MatrixType>
 typename EigenSolver<MatrixType>::EigenvectorsType EigenSolver<MatrixType>::eigenvectors() const
 {
   eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
   eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
+  const RealScalar precision = RealScalar(2)*NumTraits<RealScalar>::epsilon();
   Index n = m_eivec.cols();
   EigenvectorsType matV(n,n);
   for (Index j=0; j<n; ++j)
   {
-    if (internal::isMuchSmallerThan(numext::imag(m_eivalues.coeff(j)), numext::real(m_eivalues.coeff(j))) || j+1==n)
+    if (internal::isMuchSmallerThan(numext::imag(m_eivalues.coeff(j)), numext::real(m_eivalues.coeff(j)), precision) || j+1==n)
     {
       // we have a real eigen value
       matV.col(j) = m_eivec.col(j).template cast<ComplexScalar>();
       matV.col(j).normalize();
     }
@@ -359,21 +372,27 @@
   }
   return matV;
 }
 
 template<typename MatrixType>
+template<typename InputType>
 EigenSolver<MatrixType>& 
-EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
+EigenSolver<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeEigenvectors)
 {
+  check_template_parameters();
+  
   using std::sqrt;
   using std::abs;
+  using numext::isfinite;
   eigen_assert(matrix.cols() == matrix.rows());
 
   // Reduce to real Schur form.
-  m_realSchur.compute(matrix, computeEigenvectors);
+  m_realSchur.compute(matrix.derived(), computeEigenvectors);
+  
+  m_info = m_realSchur.info();
 
-  if (m_realSchur.info() == Success)
+  if (m_info == Success)
   {
     m_matT = m_realSchur.matrixT();
     if (computeEigenvectors)
       m_eivec = m_realSchur.matrixU();
   
@@ -383,18 +402,44 @@
     while (i < matrix.cols()) 
     {
       if (i == matrix.cols() - 1 || m_matT.coeff(i+1, i) == Scalar(0)) 
       {
         m_eivalues.coeffRef(i) = m_matT.coeff(i, i);
+        if(!(isfinite)(m_eivalues.coeffRef(i)))
+        {
+          m_isInitialized = true;
+          m_eigenvectorsOk = false;
+          m_info = NumericalIssue;
+          return *this;
+        }
         ++i;
       }
       else
       {
         Scalar p = Scalar(0.5) * (m_matT.coeff(i, i) - m_matT.coeff(i+1, i+1));
-        Scalar z = sqrt(abs(p * p + m_matT.coeff(i+1, i) * m_matT.coeff(i, i+1)));
+        Scalar z;
+        // Compute z = sqrt(abs(p * p + m_matT.coeff(i+1, i) * m_matT.coeff(i, i+1)));
+        // without overflow
+        {
+          Scalar t0 = m_matT.coeff(i+1, i);
+          Scalar t1 = m_matT.coeff(i, i+1);
+          Scalar maxval = numext::maxi<Scalar>(abs(p),numext::maxi<Scalar>(abs(t0),abs(t1)));
+          t0 /= maxval;
+          t1 /= maxval;
+          Scalar p0 = p/maxval;
+          z = maxval * sqrt(abs(p0 * p0 + t0 * t1));
+        }
+        
         m_eivalues.coeffRef(i)   = ComplexScalar(m_matT.coeff(i+1, i+1) + p, z);
         m_eivalues.coeffRef(i+1) = ComplexScalar(m_matT.coeff(i+1, i+1) + p, -z);
+        if(!((isfinite)(m_eivalues.coeffRef(i)) && (isfinite)(m_eivalues.coeffRef(i+1))))
+        {
+          m_isInitialized = true;
+          m_eigenvectorsOk = false;
+          m_info = NumericalIssue;
+          return *this;
+        }
         i += 2;
       }
     }
     
     // Compute eigenvectors.
@@ -406,30 +451,10 @@
   m_eigenvectorsOk = computeEigenvectors;
 
   return *this;
 }
 
-// Complex scalar division.
-template<typename Scalar>
-std::complex<Scalar> cdiv(const Scalar& xr, const Scalar& xi, const Scalar& yr, const Scalar& yi)
-{
-  using std::abs;
-  Scalar r,d;
-  if (abs(yr) > abs(yi))
-  {
-      r = yi/yr;
-      d = yr + r*yi;
-      return std::complex<Scalar>((xr + r*xi)/d, (xi - r*xr)/d);
-  }
-  else
-  {
-      r = yr/yi;
-      d = yi + r*yr;
-      return std::complex<Scalar>((r*xr + xi)/d, (r*xi - xr)/d);
-  }
-}
-
 
 template<typename MatrixType>
 void EigenSolver<MatrixType>::doComputeEigenvectors()
 {
   using std::abs;
@@ -442,11 +467,11 @@
   {
     norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum();
   }
   
   // Backsubstitute to find vectors of upper triangular form
-  if (norm == 0.0)
+  if (norm == Scalar(0))
   {
     return;
   }
 
   for (Index n = size-1; n >= 0; n--)
@@ -458,27 +483,27 @@
     if (q == Scalar(0))
     {
       Scalar lastr(0), lastw(0);
       Index l = n;
 
-      m_matT.coeffRef(n,n) = 1.0;
+      m_matT.coeffRef(n,n) = Scalar(1);
       for (Index i = n-1; i >= 0; i--)
       {
         Scalar w = m_matT.coeff(i,i) - p;
         Scalar r = m_matT.row(i).segment(l,n-l+1).dot(m_matT.col(n).segment(l, n-l+1));
 
-        if (m_eivalues.coeff(i).imag() < 0.0)
+        if (m_eivalues.coeff(i).imag() < Scalar(0))
         {
           lastw = w;
           lastr = r;
         }
         else
         {
           l = i;
-          if (m_eivalues.coeff(i).imag() == 0.0)
+          if (m_eivalues.coeff(i).imag() == Scalar(0))
           {
-            if (w != 0.0)
+            if (w != Scalar(0))
               m_matT.coeffRef(i,n) = -r / w;
             else
               m_matT.coeffRef(i,n) = -r / (eps * norm);
           }
           else // Solve real equations
@@ -512,23 +537,23 @@
         m_matT.coeffRef(n-1,n-1) = q / m_matT.coeff(n,n-1);
         m_matT.coeffRef(n-1,n) = -(m_matT.coeff(n,n) - p) / m_matT.coeff(n,n-1);
       }
       else
       {
-        std::complex<Scalar> cc = cdiv<Scalar>(0.0,-m_matT.coeff(n-1,n),m_matT.coeff(n-1,n-1)-p,q);
+        ComplexScalar cc = ComplexScalar(Scalar(0),-m_matT.coeff(n-1,n)) / ComplexScalar(m_matT.coeff(n-1,n-1)-p,q);
         m_matT.coeffRef(n-1,n-1) = numext::real(cc);
         m_matT.coeffRef(n-1,n) = numext::imag(cc);
       }
-      m_matT.coeffRef(n,n-1) = 0.0;
-      m_matT.coeffRef(n,n) = 1.0;
+      m_matT.coeffRef(n,n-1) = Scalar(0);
+      m_matT.coeffRef(n,n) = Scalar(1);
       for (Index i = n-2; i >= 0; i--)
       {
         Scalar ra = m_matT.row(i).segment(l, n-l+1).dot(m_matT.col(n-1).segment(l, n-l+1));
         Scalar sa = m_matT.row(i).segment(l, n-l+1).dot(m_matT.col(n).segment(l, n-l+1));
         Scalar w = m_matT.coeff(i,i) - p;
 
-        if (m_eivalues.coeff(i).imag() < 0.0)
+        if (m_eivalues.coeff(i).imag() < Scalar(0))
         {
           lastw = w;
           lastra = ra;
           lastsa = sa;
         }
@@ -535,11 +560,11 @@
         else
         {
           l = i;
           if (m_eivalues.coeff(i).imag() == RealScalar(0))
           {
-            std::complex<Scalar> cc = cdiv(-ra,-sa,w,q);
+            ComplexScalar cc = ComplexScalar(-ra,-sa) / ComplexScalar(w,q);
             m_matT.coeffRef(i,n-1) = numext::real(cc);
             m_matT.coeffRef(i,n) = numext::imag(cc);
           }
           else
           {
@@ -546,32 +571,31 @@
             // Solve complex equations
             Scalar x = m_matT.coeff(i,i+1);
             Scalar y = m_matT.coeff(i+1,i);
             Scalar vr = (m_eivalues.coeff(i).real() - p) * (m_eivalues.coeff(i).real() - p) + m_eivalues.coeff(i).imag() * m_eivalues.coeff(i).imag() - q * q;
             Scalar vi = (m_eivalues.coeff(i).real() - p) * Scalar(2) * q;
-            if ((vr == 0.0) && (vi == 0.0))
+            if ((vr == Scalar(0)) && (vi == Scalar(0)))
               vr = eps * norm * (abs(w) + abs(q) + abs(x) + abs(y) + abs(lastw));
 
-            std::complex<Scalar> cc = cdiv(x*lastra-lastw*ra+q*sa,x*lastsa-lastw*sa-q*ra,vr,vi);
+            ComplexScalar cc = ComplexScalar(x*lastra-lastw*ra+q*sa,x*lastsa-lastw*sa-q*ra) / ComplexScalar(vr,vi);
             m_matT.coeffRef(i,n-1) = numext::real(cc);
             m_matT.coeffRef(i,n) = numext::imag(cc);
             if (abs(x) > (abs(lastw) + abs(q)))
             {
               m_matT.coeffRef(i+1,n-1) = (-ra - w * m_matT.coeff(i,n-1) + q * m_matT.coeff(i,n)) / x;
               m_matT.coeffRef(i+1,n) = (-sa - w * m_matT.coeff(i,n) - q * m_matT.coeff(i,n-1)) / x;
             }
             else
             {
-              cc = cdiv(-lastra-y*m_matT.coeff(i,n-1),-lastsa-y*m_matT.coeff(i,n),lastw,q);
+              cc = ComplexScalar(-lastra-y*m_matT.coeff(i,n-1),-lastsa-y*m_matT.coeff(i,n)) / ComplexScalar(lastw,q);
               m_matT.coeffRef(i+1,n-1) = numext::real(cc);
               m_matT.coeffRef(i+1,n) = numext::imag(cc);
             }
           }
 
           // Overflow control
-          using std::max;
-          Scalar t = (max)(abs(m_matT.coeff(i,n-1)),abs(m_matT.coeff(i,n)));
+          Scalar t = numext::maxi<Scalar>(abs(m_matT.coeff(i,n-1)),abs(m_matT.coeff(i,n)));
           if ((eps * t) * t > Scalar(1))
             m_matT.block(i, n-1, size-i, 2) /= t;
 
         }
       }
@@ -579,11 +603,11 @@
       // We handled a pair of complex conjugate eigenvalues, so need to skip them both
       n--;
     }
     else
     {
-      eigen_assert(0 && "Internal bug in EigenSolver"); // this should not happen
+      eigen_assert(0 && "Internal bug in EigenSolver (INF or NaN has not been detected)"); // this should not happen
     }
   }
 
   // Back transformation to get eigenvectors of original matrix
   for (Index j = size-1; j >= 0; j--)

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h
@@ -1,10 +1,11 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2012-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2016 Tobias Wood <tobias@spinicist.org.uk>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -70,11 +71,11 @@
     };
 
     /** \brief Scalar type for matrices of type #MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     /** \brief Complex scalar type for #MatrixType. 
       *
       * This is \c std::complex<Scalar> if #Scalar is real (e.g.,
       * \c float or \c double) and just \c Scalar if #Scalar is
@@ -87,11 +88,11 @@
       * This is a column vector with entries of type #Scalar.
       * The length of the vector is the size of #MatrixType.
       */
     typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> VectorType;
 
-    /** \brief Type for vector of complex scalar values eigenvalues as returned by betas().
+    /** \brief Type for vector of complex scalar values eigenvalues as returned by alphas().
       *
       * This is a column vector with entries of type #ComplexScalar.
       * The length of the vector is the size of #MatrixType.
       */
     typedef Matrix<ComplexScalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ComplexVectorType;
@@ -112,26 +113,32 @@
       * The default constructor is useful in cases in which the user intends to
       * perform decompositions via EigenSolver::compute(const MatrixType&, bool).
       *
       * \sa compute() for an example.
       */
-    GeneralizedEigenSolver() : m_eivec(), m_alphas(), m_betas(), m_isInitialized(false), m_realQZ(), m_matS(), m_tmp() {}
+    GeneralizedEigenSolver()
+      : m_eivec(),
+        m_alphas(),
+        m_betas(),
+        m_valuesOkay(false),
+        m_vectorsOkay(false),
+        m_realQZ()
+    {}
 
     /** \brief Default constructor with memory preallocation
       *
       * Like the default constructor but with preallocation of the internal data
       * according to the specified problem \a size.
       * \sa GeneralizedEigenSolver()
       */
-    GeneralizedEigenSolver(Index size)
+    explicit GeneralizedEigenSolver(Index size)
       : m_eivec(size, size),
         m_alphas(size),
         m_betas(size),
-        m_isInitialized(false),
-        m_eigenvectorsOk(false),
+        m_valuesOkay(false),
+        m_vectorsOkay(false),
         m_realQZ(size),
-        m_matS(size, size),
         m_tmp(size)
     {}
 
     /** \brief Constructor; computes the generalized eigendecomposition of given matrix pair.
       * 
@@ -147,37 +154,34 @@
       */
     GeneralizedEigenSolver(const MatrixType& A, const MatrixType& B, bool computeEigenvectors = true)
       : m_eivec(A.rows(), A.cols()),
         m_alphas(A.cols()),
         m_betas(A.cols()),
-        m_isInitialized(false),
-        m_eigenvectorsOk(false),
+        m_valuesOkay(false),
+        m_vectorsOkay(false),
         m_realQZ(A.cols()),
-        m_matS(A.rows(), A.cols()),
         m_tmp(A.cols())
     {
       compute(A, B, computeEigenvectors);
     }
 
     /* \brief Returns the computed generalized eigenvectors.
       *
-      * \returns  %Matrix whose columns are the (possibly complex) eigenvectors.
+      * \returns  %Matrix whose columns are the (possibly complex) right eigenvectors.
+      * i.e. the eigenvectors that solve (A - l*B)x = 0. The ordering matches the eigenvalues.
       *
       * \pre Either the constructor 
       * GeneralizedEigenSolver(const MatrixType&,const MatrixType&, bool) or the member function
       * compute(const MatrixType&, const MatrixType& bool) has been called before, and
       * \p computeEigenvectors was set to true (the default).
       *
-      * Column \f$ k \f$ of the returned matrix is an eigenvector corresponding
-      * to eigenvalue number \f$ k \f$ as returned by eigenvalues().  The
-      * eigenvectors are normalized to have (Euclidean) norm equal to one. The
-      * matrix returned by this function is the matrix \f$ V \f$ in the
-      * generalized eigendecomposition \f$ A = B V D V^{-1} \f$, if it exists.
-      *
       * \sa eigenvalues()
       */
-//    EigenvectorsType eigenvectors() const;
+    EigenvectorsType eigenvectors() const {
+      eigen_assert(m_vectorsOkay && "Eigenvectors for GeneralizedEigenSolver were not calculated.");
+      return m_eivec;
+    }
 
     /** \brief Returns an expression of the computed generalized eigenvalues.
       *
       * \returns An expression of the column vector containing the eigenvalues.
       *
@@ -195,11 +199,11 @@
       *
       * \sa alphas(), betas(), eigenvectors()
       */
     EigenvalueType eigenvalues() const
     {
-      eigen_assert(m_isInitialized && "GeneralizedEigenSolver is not initialized.");
+      eigen_assert(m_valuesOkay && "GeneralizedEigenSolver is not initialized.");
       return EigenvalueType(m_alphas,m_betas);
     }
 
     /** \returns A const reference to the vectors containing the alpha values
       *
@@ -206,11 +210,11 @@
       * This vector permits to reconstruct the j-th eigenvalues as alphas(i)/betas(j).
       *
       * \sa betas(), eigenvalues() */
     ComplexVectorType alphas() const
     {
-      eigen_assert(m_isInitialized && "GeneralizedEigenSolver is not initialized.");
+      eigen_assert(m_valuesOkay && "GeneralizedEigenSolver is not initialized.");
       return m_alphas;
     }
 
     /** \returns A const reference to the vectors containing the beta values
       *
@@ -217,11 +221,11 @@
       * This vector permits to reconstruct the j-th eigenvalues as alphas(i)/betas(j).
       *
       * \sa alphas(), eigenvalues() */
     VectorType betas() const
     {
-      eigen_assert(m_isInitialized && "GeneralizedEigenSolver is not initialized.");
+      eigen_assert(m_valuesOkay && "GeneralizedEigenSolver is not initialized.");
       return m_betas;
     }
 
     /** \brief Computes generalized eigendecomposition of given matrix.
       * 
@@ -248,11 +252,11 @@
       */
     GeneralizedEigenSolver& compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors = true);
 
     ComputationInfo info() const
     {
-      eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
+      eigen_assert(m_valuesOkay && "EigenSolver is not initialized.");
       return m_realQZ.info();
     }
 
     /** Sets the maximal number of iterations allowed.
     */
@@ -261,81 +265,155 @@
       m_realQZ.setMaxIterations(maxIters);
       return *this;
     }
 
   protected:
-    MatrixType m_eivec;
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+      EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL);
+    }
+    
+    EigenvectorsType m_eivec;
     ComplexVectorType m_alphas;
     VectorType m_betas;
-    bool m_isInitialized;
-    bool m_eigenvectorsOk;
+    bool m_valuesOkay, m_vectorsOkay;
     RealQZ<MatrixType> m_realQZ;
-    MatrixType m_matS;
-
-    typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ColumnVectorType;
-    ColumnVectorType m_tmp;
+    ComplexVectorType m_tmp;
 };
 
-//template<typename MatrixType>
-//typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType GeneralizedEigenSolver<MatrixType>::eigenvectors() const
-//{
-//  eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
-//  eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
-//  Index n = m_eivec.cols();
-//  EigenvectorsType matV(n,n);
-//  // TODO
-//  return matV;
-//}
-
 template<typename MatrixType>
 GeneralizedEigenSolver<MatrixType>&
 GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors)
 {
+  check_template_parameters();
+  
   using std::sqrt;
   using std::abs;
   eigen_assert(A.cols() == A.rows() && B.cols() == A.rows() && B.cols() == B.rows());
-
+  Index size = A.cols();
+  m_valuesOkay = false;
+  m_vectorsOkay = false;
   // Reduce to generalized real Schur form:
   // A = Q S Z and B = Q T Z
   m_realQZ.compute(A, B, computeEigenvectors);
-
   if (m_realQZ.info() == Success)
   {
-    m_matS = m_realQZ.matrixS();
+    // Resize storage
+    m_alphas.resize(size);
+    m_betas.resize(size);
     if (computeEigenvectors)
-      m_eivec = m_realQZ.matrixZ().transpose();
-  
-    // Compute eigenvalues from matS
-    m_alphas.resize(A.cols());
-    m_betas.resize(A.cols());
+    {
+      m_eivec.resize(size,size);
+      m_tmp.resize(size);
+    }
+
+    // Aliases:
+    Map<VectorType> v(reinterpret_cast<Scalar*>(m_tmp.data()), size);
+    ComplexVectorType &cv = m_tmp;
+    const MatrixType &mZ = m_realQZ.matrixZ();
+    const MatrixType &mS = m_realQZ.matrixS();
+    const MatrixType &mT = m_realQZ.matrixT();
+
     Index i = 0;
-    while (i < A.cols())
+    while (i < size)
     {
-      if (i == A.cols() - 1 || m_matS.coeff(i+1, i) == Scalar(0))
+      if (i == size - 1 || mS.coeff(i+1, i) == Scalar(0))
       {
-        m_alphas.coeffRef(i) = m_matS.coeff(i, i);
-        m_betas.coeffRef(i)  = m_realQZ.matrixT().coeff(i,i);
+        // Real eigenvalue
+        m_alphas.coeffRef(i) = mS.diagonal().coeff(i);
+        m_betas.coeffRef(i)  = mT.diagonal().coeff(i);
+        if (computeEigenvectors)
+        {
+          v.setConstant(Scalar(0.0));
+          v.coeffRef(i) = Scalar(1.0);
+          // For singular eigenvalues do nothing more
+          if(abs(m_betas.coeffRef(i)) >= (std::numeric_limits<RealScalar>::min)())
+          {
+            // Non-singular eigenvalue
+            const Scalar alpha = real(m_alphas.coeffRef(i));
+            const Scalar beta = m_betas.coeffRef(i);
+            for (Index j = i-1; j >= 0; j--)
+            {
+              const Index st = j+1;
+              const Index sz = i-j;
+              if (j > 0 && mS.coeff(j, j-1) != Scalar(0))
+              {
+                // 2x2 block
+                Matrix<Scalar, 2, 1> rhs = (alpha*mT.template block<2,Dynamic>(j-1,st,2,sz) - beta*mS.template block<2,Dynamic>(j-1,st,2,sz)) .lazyProduct( v.segment(st,sz) );
+                Matrix<Scalar, 2, 2> lhs = beta * mS.template block<2,2>(j-1,j-1) - alpha * mT.template block<2,2>(j-1,j-1);
+                v.template segment<2>(j-1) = lhs.partialPivLu().solve(rhs);
+                j--;
+              }
+              else
+              {
+                v.coeffRef(j) = -v.segment(st,sz).transpose().cwiseProduct(beta*mS.block(j,st,1,sz) - alpha*mT.block(j,st,1,sz)).sum() / (beta*mS.coeffRef(j,j) - alpha*mT.coeffRef(j,j));
+              }
+            }
+          }
+          m_eivec.col(i).real().noalias() = mZ.transpose() * v;
+          m_eivec.col(i).real().normalize();
+          m_eivec.col(i).imag().setConstant(0);
+        }
         ++i;
       }
       else
       {
-        Scalar p = Scalar(0.5) * (m_matS.coeff(i, i) - m_matS.coeff(i+1, i+1));
-        Scalar z = sqrt(abs(p * p + m_matS.coeff(i+1, i) * m_matS.coeff(i, i+1)));
-        m_alphas.coeffRef(i)   = ComplexScalar(m_matS.coeff(i+1, i+1) + p, z);
-        m_alphas.coeffRef(i+1) = ComplexScalar(m_matS.coeff(i+1, i+1) + p, -z);
+        // We need to extract the generalized eigenvalues of the pair of a general 2x2 block S and a positive diagonal 2x2 block T
+        // Then taking beta=T_00*T_11, we can avoid any division, and alpha is the eigenvalues of A = (U^-1 * S * U) * diag(T_11,T_00):
+
+        // T =  [a 0]
+        //      [0 b]
+        RealScalar a = mT.diagonal().coeff(i),
+                   b = mT.diagonal().coeff(i+1);
+        const RealScalar beta = m_betas.coeffRef(i) = m_betas.coeffRef(i+1) = a*b;
+
+        // ^^ NOTE: using diagonal()(i) instead of coeff(i,i) workarounds a MSVC bug.
+        Matrix<RealScalar,2,2> S2 = mS.template block<2,2>(i,i) * Matrix<Scalar,2,1>(b,a).asDiagonal();
+
+        Scalar p = Scalar(0.5) * (S2.coeff(0,0) - S2.coeff(1,1));
+        Scalar z = sqrt(abs(p * p + S2.coeff(1,0) * S2.coeff(0,1)));
+        const ComplexScalar alpha = ComplexScalar(S2.coeff(1,1) + p, (beta > 0) ? z : -z);
+        m_alphas.coeffRef(i)   = conj(alpha);
+        m_alphas.coeffRef(i+1) = alpha;
 
-        m_betas.coeffRef(i)   = m_realQZ.matrixT().coeff(i,i);
-        m_betas.coeffRef(i+1) = m_realQZ.matrixT().coeff(i,i);
+        if (computeEigenvectors) {
+          // Compute eigenvector in position (i+1) and then position (i) is just the conjugate
+          cv.setZero();
+          cv.coeffRef(i+1) = Scalar(1.0);
+          // here, the "static_cast" workaound expression template issues.
+          cv.coeffRef(i) = -(static_cast<Scalar>(beta*mS.coeffRef(i,i+1)) - alpha*mT.coeffRef(i,i+1))
+                          / (static_cast<Scalar>(beta*mS.coeffRef(i,i))   - alpha*mT.coeffRef(i,i));
+          for (Index j = i-1; j >= 0; j--)
+          {
+            const Index st = j+1;
+            const Index sz = i+1-j;
+            if (j > 0 && mS.coeff(j, j-1) != Scalar(0))
+            {
+              // 2x2 block
+              Matrix<ComplexScalar, 2, 1> rhs = (alpha*mT.template block<2,Dynamic>(j-1,st,2,sz) - beta*mS.template block<2,Dynamic>(j-1,st,2,sz)) .lazyProduct( cv.segment(st,sz) );
+              Matrix<ComplexScalar, 2, 2> lhs = beta * mS.template block<2,2>(j-1,j-1) - alpha * mT.template block<2,2>(j-1,j-1);
+              cv.template segment<2>(j-1) = lhs.partialPivLu().solve(rhs);
+              j--;
+            } else {
+              cv.coeffRef(j) =  cv.segment(st,sz).transpose().cwiseProduct(beta*mS.block(j,st,1,sz) - alpha*mT.block(j,st,1,sz)).sum()
+                              / (alpha*mT.coeffRef(j,j) - static_cast<Scalar>(beta*mS.coeffRef(j,j)));
+            }
+          }
+          m_eivec.col(i+1).noalias() = (mZ.transpose() * cv);
+          m_eivec.col(i+1).normalize();
+          m_eivec.col(i) = m_eivec.col(i+1).conjugate();
+        }
         i += 2;
       }
     }
-  }
 
-  m_isInitialized = true;
-  m_eigenvectorsOk = false;//computeEigenvectors;
-
+    m_valuesOkay = true;
+    m_vectorsOkay = computeEigenvectors;
+  }
   return *this;
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_GENERALIZEDEIGENSOLVER_H

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h
@@ -48,11 +48,10 @@
 class GeneralizedSelfAdjointEigenSolver : public SelfAdjointEigenSolver<_MatrixType>
 {
     typedef SelfAdjointEigenSolver<_MatrixType> Base;
   public:
 
-    typedef typename Base::Index Index;
     typedef _MatrixType MatrixType;
 
     /** \brief Default constructor for fixed-size matrices.
       *
       * The default constructor is useful in cases in which the user intends to
@@ -72,11 +71,11 @@
       * parameter is only used as a hint. It is not an error to give a wrong
       * \p size, but it may impair performance.
       *
       * \sa compute() for an example
       */
-    GeneralizedSelfAdjointEigenSolver(Index size)
+    explicit GeneralizedSelfAdjointEigenSolver(Index size)
         : Base(size)
     {}
 
     /** \brief Constructor; computes generalized eigendecomposition of given matrix pencil.
       *

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/HessenbergDecomposition.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/HessenbergDecomposition.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/HessenbergDecomposition.h
@@ -69,11 +69,11 @@
       MaxSizeMinusOne = MaxSize == Dynamic ? Dynamic : MaxSize - 1
     };
 
     /** \brief Scalar type for matrices of type #MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     /** \brief Type for vector of Householder coefficients.
       *
       * This is column vector with entries of type #Scalar. The length of the
       * vector is one less than the size of #MatrixType, if it is a fixed-side
@@ -95,11 +95,11 @@
       * used as a hint. It is not an error to give a wrong \p size, but it may
       * impair performance.
       *
       * \sa compute() for an example.
       */
-    HessenbergDecomposition(Index size = Size==Dynamic ? 2 : Size)
+    explicit HessenbergDecomposition(Index size = Size==Dynamic ? 2 : Size)
       : m_matrix(size,size),
         m_temp(size),
         m_isInitialized(false)
     {
       if(size>1)
@@ -113,12 +113,13 @@
       * This constructor calls compute() to compute the Hessenberg
       * decomposition.
       *
       * \sa matrixH() for an example.
       */
-    HessenbergDecomposition(const MatrixType& matrix)
-      : m_matrix(matrix),
+    template<typename InputType>
+    explicit HessenbergDecomposition(const EigenBase<InputType>& matrix)
+      : m_matrix(matrix.derived()),
         m_temp(matrix.rows()),
         m_isInitialized(false)
     {
       if(matrix.rows()<2)
       {
@@ -145,13 +146,14 @@
       * object.
       *
       * Example: \include HessenbergDecomposition_compute.cpp
       * Output: \verbinclude HessenbergDecomposition_compute.out
       */
-    HessenbergDecomposition& compute(const MatrixType& matrix)
+    template<typename InputType>
+    HessenbergDecomposition& compute(const EigenBase<InputType>& matrix)
     {
-      m_matrix = matrix;
+      m_matrix = matrix.derived();
       if(matrix.rows()<2)
       {
         m_isInitialized = true;
         return *this;
       }
@@ -335,11 +337,10 @@
   * class.
   */
 template<typename MatrixType> struct HessenbergDecompositionMatrixHReturnType
 : public ReturnByValue<HessenbergDecompositionMatrixHReturnType<MatrixType> >
 {
-    typedef typename MatrixType::Index Index;
   public:
     /** \brief Constructor.
       *
       * \param[in] hess  Hessenberg decomposition
       */

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/RealQZ.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/RealQZ.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/RealQZ.h
@@ -65,11 +65,11 @@
         MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
         MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
       };
       typedef typename MatrixType::Scalar Scalar;
       typedef std::complex<typename NumTraits<Scalar>::Real> ComplexScalar;
-      typedef typename MatrixType::Index Index;
+      typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
       typedef Matrix<ComplexScalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> EigenvalueType;
       typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ColumnVectorType;
 
       /** \brief Default constructor.
@@ -81,11 +81,11 @@
        * used as a hint. It is not an error to give a wrong \p size, but it may
        * impair performance.
        *
        * \sa compute() for an example.
        */
-      RealQZ(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime) : 
+      explicit RealQZ(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime) :
         m_S(size, size),
         m_T(size, size),
         m_Q(size, size),
         m_Z(size, size),
         m_workspace(size*2),
@@ -238,25 +238,25 @@
           {
             G.makeGivens(m_S.coeff(i-1,j), m_S.coeff(i,j), &m_S.coeffRef(i-1, j));
             m_S.coeffRef(i,j) = Scalar(0.0);
             m_S.rightCols(dim-j-1).applyOnTheLeft(i-1,i,G.adjoint());
             m_T.rightCols(dim-i+1).applyOnTheLeft(i-1,i,G.adjoint());
+            // update Q
+            if (m_computeQZ)
+              m_Q.applyOnTheRight(i-1,i,G);
           }
-          // update Q
-          if (m_computeQZ)
-            m_Q.applyOnTheRight(i-1,i,G);
           // kill T(i,i-1)
           if(m_T.coeff(i,i-1)!=Scalar(0))
           {
             G.makeGivens(m_T.coeff(i,i), m_T.coeff(i,i-1), &m_T.coeffRef(i,i));
             m_T.coeffRef(i,i-1) = Scalar(0.0);
             m_S.applyOnTheRight(i,i-1,G);
             m_T.topRows(i).applyOnTheRight(i,i-1,G);
+            // update Z
+            if (m_computeQZ)
+              m_Z.applyOnTheLeft(i,i-1,G.adjoint());
           }
-          // update Z
-          if (m_computeQZ)
-            m_Z.applyOnTheLeft(i,i-1,G.adjoint());
         }
       }
     }
 
   /** \internal Computes vector L1 norms of S and T when in Hessenberg-Triangular form already */
@@ -274,11 +274,11 @@
     }
 
 
   /** \internal Look for single small sub-diagonal element S(res, res-1) and return res (or 0) */
   template<typename MatrixType>
-    inline typename MatrixType::Index RealQZ<MatrixType>::findSmallSubdiagEntry(Index iu)
+    inline Index RealQZ<MatrixType>::findSmallSubdiagEntry(Index iu)
     {
       using std::abs;
       Index res = iu;
       while (res > 0)
       {
@@ -292,11 +292,11 @@
       return res;
     }
 
   /** \internal Look for single small diagonal element T(res, res) for res between f and l, and return res (or f-1)  */
   template<typename MatrixType>
-    inline typename MatrixType::Index RealQZ<MatrixType>::findSmallDiagEntry(Index f, Index l)
+    inline Index RealQZ<MatrixType>::findSmallDiagEntry(Index f, Index l)
     {
       using std::abs;
       Index res = l;
       while (res >= f) {
         if (abs(m_T.coeff(res,res)) <= NumTraits<Scalar>::epsilon() * m_normOfT)
@@ -313,12 +313,12 @@
       using std::abs;
       using std::sqrt;
       const Index dim=m_S.cols();
       if (abs(m_S.coeff(i+1,i))==Scalar(0))
         return;
-      Index z = findSmallDiagEntry(i,i+1);
-      if (z==i-1)
+      Index j = findSmallDiagEntry(i,i+1);
+      if (j==i-1)
       {
         // block of (S T^{-1})
         Matrix2s STi = m_T.template block<2,2>(i,i).template triangularView<Upper>().
           template solve<OnTheRight>(m_S.template block<2,2>(i,i));
         Scalar p = Scalar(0.5)*(STi(0,0)-STi(1,1));
@@ -350,11 +350,11 @@
           m_T.coeffRef(i+1,i) = Scalar(0.0);
         }
       }
       else
       {
-        pushDownZero(z,i,i+1);
+        pushDownZero(j,i,i+1);
       }
     }
 
   /** \internal use zero in T(z,z) to zero S(l,l-1), working in block f..l */
   template<typename MatrixType>
@@ -550,11 +550,10 @@
       if (m_computeQZ)
         m_Z.applyOnTheLeft(l,l-1,G.adjoint());
       m_T.coeffRef(l,l-1) = Scalar(0.0);
     }
 
-
   template<typename MatrixType>
     RealQZ<MatrixType>& RealQZ<MatrixType>::compute(const MatrixType& A_in, const MatrixType& B_in, bool computeQZ)
     {
 
       const Index dim = A_in.cols();
@@ -614,11 +613,42 @@
           }
         }
       }
       // check if we converged before reaching iterations limit
       m_info = (local_iter<m_maxIters) ? Success : NoConvergence;
+
+      // For each non triangular 2x2 diagonal block of S,
+      //    reduce the respective 2x2 diagonal block of T to positive diagonal form using 2x2 SVD.
+      // This step is not mandatory for QZ, but it does help further extraction of eigenvalues/eigenvectors,
+      // and is in par with Lapack/Matlab QZ.
+      if(m_info==Success)
+      {
+        for(Index i=0; i<dim-1; ++i)
+        {
+          if(m_S.coeff(i+1, i) != Scalar(0))
+          {
+            JacobiRotation<Scalar> j_left, j_right;
+            internal::real_2x2_jacobi_svd(m_T, i, i+1, &j_left, &j_right);
+
+            // Apply resulting Jacobi rotations
+            m_S.applyOnTheLeft(i,i+1,j_left);
+            m_S.applyOnTheRight(i,i+1,j_right);
+            m_T.applyOnTheLeft(i,i+1,j_left);
+            m_T.applyOnTheRight(i,i+1,j_right);
+            m_T(i+1,i) = m_T(i,i+1) = Scalar(0);
+
+            if(m_computeQZ) {
+              m_Q.applyOnTheRight(i,i+1,j_left.transpose());
+              m_Z.applyOnTheLeft(i,i+1,j_right.transpose());
+            }
+
+            i++;
+          }
+        }
+      }
+
       return *this;
     } // end compute
 
 } // end namespace Eigen
 
 #endif //EIGEN_REAL_QZ

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur.h
@@ -62,11 +62,11 @@
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef std::complex<typename NumTraits<Scalar>::Real> ComplexScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     typedef Matrix<ComplexScalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> EigenvalueType;
     typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ColumnVectorType;
 
     /** \brief Default constructor.
@@ -78,11 +78,11 @@
       * used as a hint. It is not an error to give a wrong \p size, but it may
       * impair performance.
       *
       * \sa compute() for an example.
       */
-    RealSchur(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime)
+    explicit RealSchur(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime)
             : m_matT(size, size),
               m_matU(size, size),
               m_workspaceVector(size),
               m_hess(size),
               m_isInitialized(false),
@@ -98,20 +98,21 @@
       * This constructor calls compute() to compute the Schur decomposition.
       *
       * Example: \include RealSchur_RealSchur_MatrixType.cpp
       * Output: \verbinclude RealSchur_RealSchur_MatrixType.out
       */
-    RealSchur(const MatrixType& matrix, bool computeU = true)
+    template<typename InputType>
+    explicit RealSchur(const EigenBase<InputType>& matrix, bool computeU = true)
             : m_matT(matrix.rows(),matrix.cols()),
               m_matU(matrix.rows(),matrix.cols()),
               m_workspaceVector(matrix.rows()),
               m_hess(matrix.rows()),
               m_isInitialized(false),
               m_matUisUptodate(false),
               m_maxIters(-1)
     {
-      compute(matrix, computeU);
+      compute(matrix.derived(), computeU);
     }
 
     /** \brief Returns the orthogonal matrix in the Schur decomposition. 
       *
       * \returns A const reference to the matrix U.
@@ -163,11 +164,12 @@
       * Example: \include RealSchur_compute.cpp
       * Output: \verbinclude RealSchur_compute.out
       *
       * \sa compute(const MatrixType&, bool, Index)
       */
-    RealSchur& compute(const MatrixType& matrix, bool computeU = true);
+    template<typename InputType>
+    RealSchur& compute(const EigenBase<InputType>& matrix, bool computeU = true);
 
     /** \brief Computes Schur decomposition of a Hessenberg matrix H = Z T Z^T
      *  \param[in] matrixH Matrix in Hessenberg form H
      *  \param[in] matrixQ orthogonal matrix Q that transform a matrix A to H : A = Q H Q^T
      *  \param computeU Computes the matriX U of the Schur vectors
@@ -232,39 +234,58 @@
     Index m_maxIters;
 
     typedef Matrix<Scalar,3,1> Vector3s;
 
     Scalar computeNormOfT();
-    Index findSmallSubdiagEntry(Index iu, const Scalar& norm);
+    Index findSmallSubdiagEntry(Index iu);
     void splitOffTwoRows(Index iu, bool computeU, const Scalar& exshift);
     void computeShift(Index iu, Index iter, Scalar& exshift, Vector3s& shiftInfo);
     void initFrancisQRStep(Index il, Index iu, const Vector3s& shiftInfo, Index& im, Vector3s& firstHouseholderVector);
     void performFrancisQRStep(Index il, Index im, Index iu, bool computeU, const Vector3s& firstHouseholderVector, Scalar* workspace);
 };
 
 
 template<typename MatrixType>
-RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU)
+template<typename InputType>
+RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeU)
 {
+  const Scalar considerAsZero = (std::numeric_limits<Scalar>::min)();
+
   eigen_assert(matrix.cols() == matrix.rows());
   Index maxIters = m_maxIters;
   if (maxIters == -1)
     maxIters = m_maxIterationsPerRow * matrix.rows();
+
+  Scalar scale = matrix.derived().cwiseAbs().maxCoeff();
+  if(scale<considerAsZero)
+  {
+    m_matT.setZero(matrix.rows(),matrix.cols());
+    if(computeU)
+      m_matU.setIdentity(matrix.rows(),matrix.cols());
+    m_info = Success;
+    m_isInitialized = true;
+    m_matUisUptodate = computeU;
+    return *this;
+  }
 
   // Step 1. Reduce to Hessenberg form
-  m_hess.compute(matrix);
+  m_hess.compute(matrix.derived()/scale);
 
   // Step 2. Reduce to real Schur form  
   computeFromHessenberg(m_hess.matrixH(), m_hess.matrixQ(), computeU);
+
+  m_matT *= scale;
   
   return *this;
 }
 template<typename MatrixType>
 template<typename HessMatrixType, typename OrthMatrixType>
 RealSchur<MatrixType>& RealSchur<MatrixType>::computeFromHessenberg(const HessMatrixType& matrixH, const OrthMatrixType& matrixQ,  bool computeU)
-{  
-  m_matT = matrixH; 
+{
+  using std::abs;
+
+  m_matT = matrixH;
   if(computeU)
     m_matU = matrixQ;
   
   Index maxIters = m_maxIters;
   if (maxIters == -1)
@@ -284,11 +305,11 @@
 
   if(norm!=0)
   {
     while (iu >= 0)
     {
-      Index il = findSmallSubdiagEntry(iu, norm);
+      Index il = findSmallSubdiagEntry(iu);
 
       // Check for convergence
       if (il == iu) // One root found
       {
         m_matT.coeffRef(iu,iu) = m_matT.coeff(iu,iu) + exshift;
@@ -341,20 +362,18 @@
   return norm;
 }
 
 /** \internal Look for single small sub-diagonal element and returns its index */
 template<typename MatrixType>
-inline typename MatrixType::Index RealSchur<MatrixType>::findSmallSubdiagEntry(Index iu, const Scalar& norm)
+inline Index RealSchur<MatrixType>::findSmallSubdiagEntry(Index iu)
 {
   using std::abs;
   Index res = iu;
   while (res > 0)
   {
     Scalar s = abs(m_matT.coeff(res-1,res-1)) + abs(m_matT.coeff(res,res));
-    if (s == 0.0)
-      s = norm;
-    if (abs(m_matT.coeff(res,res-1)) < NumTraits<Scalar>::epsilon() * s)
+    if (abs(m_matT.coeff(res,res-1)) <= NumTraits<Scalar>::epsilon() * s)
       break;
     res--;
   }
   return res;
 }
@@ -455,13 +474,11 @@
       break;
     }
     const Scalar lhs = m_matT.coeff(im,im-1) * (abs(v.coeff(1)) + abs(v.coeff(2)));
     const Scalar rhs = v.coeff(0) * (abs(m_matT.coeff(im-1,im-1)) + abs(Tmm) + abs(m_matT.coeff(im+1,im+1)));
     if (abs(lhs) < NumTraits<Scalar>::epsilon() * rhs)
-    {
       break;
-    }
   }
 }
 
 /** \internal Perform a Francis QR step involving rows il:iu and columns im:iu. */
 template<typename MatrixType>

ADDED   3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur_LAPACKE.h
Index: 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur_LAPACKE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur_LAPACKE.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur_LAPACKE.h
@@ -0,0 +1,77 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to LAPACKe
+ *    Real Schur needed to real unsymmetrical eigenvalues/eigenvectors.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_REAL_SCHUR_LAPACKE_H
+#define EIGEN_REAL_SCHUR_LAPACKE_H
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by LAPACKe */
+
+#define EIGEN_LAPACKE_SCHUR_REAL(EIGTYPE, LAPACKE_TYPE, LAPACKE_PREFIX, LAPACKE_PREFIX_U, EIGCOLROW, LAPACKE_COLROW) \
+template<> template<typename InputType> inline \
+RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
+RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const EigenBase<InputType>& matrix, bool computeU) \
+{ \
+  eigen_assert(matrix.cols() == matrix.rows()); \
+\
+  lapack_int n = internal::convert_index<lapack_int>(matrix.cols()), sdim, info; \
+  lapack_int matrix_order = LAPACKE_COLROW; \
+  char jobvs, sort='N'; \
+  LAPACK_##LAPACKE_PREFIX_U##_SELECT2 select = 0; \
+  jobvs = (computeU) ? 'V' : 'N'; \
+  m_matU.resize(n, n); \
+  lapack_int ldvs  = internal::convert_index<lapack_int>(m_matU.outerStride()); \
+  m_matT = matrix; \
+  lapack_int lda = internal::convert_index<lapack_int>(m_matT.outerStride()); \
+  Matrix<EIGTYPE, Dynamic, Dynamic> wr, wi; \
+  wr.resize(n, 1); wi.resize(n, 1); \
+  info = LAPACKE_##LAPACKE_PREFIX##gees( matrix_order, jobvs, sort, select, n, (LAPACKE_TYPE*)m_matT.data(), lda, &sdim, (LAPACKE_TYPE*)wr.data(), (LAPACKE_TYPE*)wi.data(), (LAPACKE_TYPE*)m_matU.data(), ldvs ); \
+  if(info == 0) \
+    m_info = Success; \
+  else \
+    m_info = NoConvergence; \
+\
+  m_isInitialized = true; \
+  m_matUisUptodate = computeU; \
+  return *this; \
+\
+}
+
+EIGEN_LAPACKE_SCHUR_REAL(double,   double, d, D, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_SCHUR_REAL(float,    float,  s, S, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_SCHUR_REAL(double,   double, d, D, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_SCHUR_REAL(float,    float,  s, S, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_REAL_SCHUR_LAPACKE_H

DELETED 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur_MKL.h
Index: 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur_MKL.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/RealSchur_MKL.h
@@ -1,83 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *    Real Schur needed to real unsymmetrical eigenvalues/eigenvectors.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_REAL_SCHUR_MKL_H
-#define EIGEN_REAL_SCHUR_MKL_H
-
-#include "Eigen/src/Core/util/MKL_support.h"
-
-namespace Eigen { 
-
-/** \internal Specialization for the data types supported by MKL */
-
-#define EIGEN_MKL_SCHUR_REAL(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \
-template<> inline \
-RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
-RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, bool computeU) \
-{ \
-  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> MatrixType; \
-  typedef MatrixType::Scalar Scalar; \
-  typedef MatrixType::RealScalar RealScalar; \
-\
-  eigen_assert(matrix.cols() == matrix.rows()); \
-\
-  lapack_int n = matrix.cols(), sdim, info; \
-  lapack_int lda = matrix.outerStride(); \
-  lapack_int matrix_order = MKLCOLROW; \
-  char jobvs, sort='N'; \
-  LAPACK_##MKLPREFIX_U##_SELECT2 select = 0; \
-  jobvs = (computeU) ? 'V' : 'N'; \
-  m_matU.resize(n, n); \
-  lapack_int ldvs  = m_matU.outerStride(); \
-  m_matT = matrix; \
-  Matrix<EIGTYPE, Dynamic, Dynamic> wr, wi; \
-  wr.resize(n, 1); wi.resize(n, 1); \
-  info = LAPACKE_##MKLPREFIX##gees( matrix_order, jobvs, sort, select, n, (MKLTYPE*)m_matT.data(), lda, &sdim, (MKLTYPE*)wr.data(), (MKLTYPE*)wi.data(), (MKLTYPE*)m_matU.data(), ldvs ); \
-  if(info == 0) \
-    m_info = Success; \
-  else \
-    m_info = NoConvergence; \
-\
-  m_isInitialized = true; \
-  m_matUisUptodate = computeU; \
-  return *this; \
-\
-}
-
-EIGEN_MKL_SCHUR_REAL(double,   double, d, D, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_SCHUR_REAL(float,    float,  s, S, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_SCHUR_REAL(double,   double, d, D, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_SCHUR_REAL(float,    float,  s, S, RowMajor, LAPACK_ROW_MAJOR)
-
-} // end namespace Eigen
-
-#endif // EIGEN_REAL_SCHUR_MKL_H

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
@@ -18,10 +18,12 @@
 template<typename _MatrixType>
 class GeneralizedSelfAdjointEigenSolver;
 
 namespace internal {
 template<typename SolverType,int Size,bool IsComplex> struct direct_selfadjoint_eigenvalues;
+template<typename MatrixType, typename DiagType, typename SubDiagType>
+ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag, const Index maxIterations, bool computeEigenvectors, MatrixType& eivec);
 }
 
 /** \eigenvalues_module \ingroup Eigenvalues_Module
   *
   *
@@ -77,11 +79,13 @@
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
     
     /** \brief Scalar type for matrices of type \p _MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
+    
+    typedef Matrix<Scalar,Size,Size,ColMajor,MaxColsAtCompileTime,MaxColsAtCompileTime> EigenvectorsType;
 
     /** \brief Real scalar type for \p _MatrixType.
       *
       * This is just \c Scalar if #Scalar is real (e.g., \c float or
       * \c double), and the type of the real part of \c Scalar if #Scalar is
@@ -96,10 +100,11 @@
       * This is a column vector with entries of type #RealScalar.
       * The length of the vector is the size of \p _MatrixType.
       */
     typedef typename internal::plain_col_type<MatrixType, RealScalar>::type RealVectorType;
     typedef Tridiagonalization<MatrixType> TridiagonalizationType;
+    typedef typename TridiagonalizationType::SubDiagonalType SubDiagonalType;
 
     /** \brief Default constructor for fixed-size matrices.
       *
       * The default constructor is useful in cases in which the user intends to
       * perform decompositions via compute(). This constructor
@@ -107,10 +112,11 @@
       * SelfAdjointEigenSolver(Index) for dynamic-size matrices.
       *
       * Example: \include SelfAdjointEigenSolver_SelfAdjointEigenSolver.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_SelfAdjointEigenSolver.out
       */
+    EIGEN_DEVICE_FUNC
     SelfAdjointEigenSolver()
         : m_eivec(),
           m_eivalues(),
           m_subdiag(),
           m_isInitialized(false)
@@ -126,11 +132,12 @@
       * parameter is only used as a hint. It is not an error to give a wrong
       * \p size, but it may impair performance.
       *
       * \sa compute() for an example
       */
-    SelfAdjointEigenSolver(Index size)
+    EIGEN_DEVICE_FUNC
+    explicit SelfAdjointEigenSolver(Index size)
         : m_eivec(size, size),
           m_eivalues(size),
           m_subdiag(size > 1 ? size - 1 : 1),
           m_isInitialized(false)
     {}
@@ -148,17 +155,19 @@
       * Example: \include SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.out
       *
       * \sa compute(const MatrixType&, int)
       */
-    SelfAdjointEigenSolver(const MatrixType& matrix, int options = ComputeEigenvectors)
+    template<typename InputType>
+    EIGEN_DEVICE_FUNC
+    explicit SelfAdjointEigenSolver(const EigenBase<InputType>& matrix, int options = ComputeEigenvectors)
       : m_eivec(matrix.rows(), matrix.cols()),
         m_eivalues(matrix.cols()),
         m_subdiag(matrix.rows() > 1 ? matrix.rows() - 1 : 1),
         m_isInitialized(false)
     {
-      compute(matrix, options);
+      compute(matrix.derived(), options);
     }
 
     /** \brief Computes eigendecomposition of given matrix.
       *
       * \param[in]  matrix  Selfadjoint matrix whose eigendecomposition is to
@@ -187,28 +196,49 @@
       * Example: \include SelfAdjointEigenSolver_compute_MatrixType.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_compute_MatrixType.out
       *
       * \sa SelfAdjointEigenSolver(const MatrixType&, int)
       */
-    SelfAdjointEigenSolver& compute(const MatrixType& matrix, int options = ComputeEigenvectors);
+    template<typename InputType>
+    EIGEN_DEVICE_FUNC
+    SelfAdjointEigenSolver& compute(const EigenBase<InputType>& matrix, int options = ComputeEigenvectors);
     
-    /** \brief Computes eigendecomposition of given matrix using a direct algorithm
+    /** \brief Computes eigendecomposition of given matrix using a closed-form algorithm
       *
       * This is a variant of compute(const MatrixType&, int options) which
       * directly solves the underlying polynomial equation.
       * 
-      * Currently only 3x3 matrices for which the sizes are known at compile time are supported (e.g., Matrix3d).
+      * Currently only 2x2 and 3x3 matrices for which the sizes are known at compile time are supported (e.g., Matrix3d).
       * 
-      * This method is usually significantly faster than the QR algorithm
+      * This method is usually significantly faster than the QR iterative algorithm
       * but it might also be less accurate. It is also worth noting that
       * for 3x3 matrices it involves trigonometric operations which are
       * not necessarily available for all scalar types.
+      * 
+      * For the 3x3 case, we observed the following worst case relative error regarding the eigenvalues:
+      *   - double: 1e-8
+      *   - float:  1e-3
       *
       * \sa compute(const MatrixType&, int options)
       */
+    EIGEN_DEVICE_FUNC
     SelfAdjointEigenSolver& computeDirect(const MatrixType& matrix, int options = ComputeEigenvectors);
 
+    /**
+      *\brief Computes the eigen decomposition from a tridiagonal symmetric matrix
+      *
+      * \param[in] diag The vector containing the diagonal of the matrix.
+      * \param[in] subdiag The subdiagonal of the matrix.
+      * \param[in] options Can be #ComputeEigenvectors (default) or #EigenvaluesOnly.
+      * \returns Reference to \c *this
+      *
+      * This function assumes that the matrix has been reduced to tridiagonal form.
+      *
+      * \sa compute(const MatrixType&, int) for more information
+      */
+    SelfAdjointEigenSolver& computeFromTridiagonal(const RealVectorType& diag, const SubDiagonalType& subdiag , int options=ComputeEigenvectors);
+
     /** \brief Returns the eigenvectors of given matrix.
       *
       * \returns  A const reference to the matrix whose columns are the eigenvectors.
       *
       * \pre The eigenvectors have been computed before.
@@ -223,11 +253,12 @@
       * Example: \include SelfAdjointEigenSolver_eigenvectors.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_eigenvectors.out
       *
       * \sa eigenvalues()
       */
-    const MatrixType& eigenvectors() const
+    EIGEN_DEVICE_FUNC
+    const EigenvectorsType& eigenvectors() const
     {
       eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
       eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
       return m_eivec;
     }
@@ -245,10 +276,11 @@
       * Example: \include SelfAdjointEigenSolver_eigenvalues.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_eigenvalues.out
       *
       * \sa eigenvectors(), MatrixBase::eigenvalues()
       */
+    EIGEN_DEVICE_FUNC
     const RealVectorType& eigenvalues() const
     {
       eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
       return m_eivalues;
     }
@@ -266,13 +298,13 @@
       * square root as \f$ A^{1/2} = V D^{1/2} V^{-1} \f$.
       *
       * Example: \include SelfAdjointEigenSolver_operatorSqrt.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_operatorSqrt.out
       *
-      * \sa operatorInverseSqrt(),
-      *     \ref MatrixFunctions_Module "MatrixFunctions Module"
+      * \sa operatorInverseSqrt(), <a href="unsupported/group__MatrixFunctions__Module.html">MatrixFunctions Module</a>
       */
+    EIGEN_DEVICE_FUNC
     MatrixType operatorSqrt() const
     {
       eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
       eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
       return m_eivec * m_eivalues.cwiseSqrt().asDiagonal() * m_eivec.adjoint();
@@ -291,13 +323,13 @@
       * then its inverse with MatrixBase::inverse().
       *
       * Example: \include SelfAdjointEigenSolver_operatorInverseSqrt.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_operatorInverseSqrt.out
       *
-      * \sa operatorSqrt(), MatrixBase::inverse(),
-      *     \ref MatrixFunctions_Module "MatrixFunctions Module"
+      * \sa operatorSqrt(), MatrixBase::inverse(), <a href="unsupported/group__MatrixFunctions__Module.html">MatrixFunctions Module</a>
       */
+    EIGEN_DEVICE_FUNC
     MatrixType operatorInverseSqrt() const
     {
       eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
       eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
       return m_eivec * m_eivalues.cwiseInverse().cwiseSqrt().asDiagonal() * m_eivec.adjoint();
@@ -305,10 +337,11 @@
 
     /** \brief Reports whether previous computation was successful.
       *
       * \returns \c Success if computation was succesful, \c NoConvergence otherwise.
       */
+    EIGEN_DEVICE_FUNC
     ComputationInfo info() const
     {
       eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
       return m_info;
     }
@@ -318,74 +351,60 @@
       * The algorithm terminates if it does not converge within m_maxIterations * n iterations, where n
       * denotes the size of the matrix. This value is currently set to 30 (copied from LAPACK).
       */
     static const int m_maxIterations = 30;
 
-    #ifdef EIGEN2_SUPPORT
-    SelfAdjointEigenSolver(const MatrixType& matrix, bool computeEigenvectors)
-      : m_eivec(matrix.rows(), matrix.cols()),
-        m_eivalues(matrix.cols()),
-        m_subdiag(matrix.rows() > 1 ? matrix.rows() - 1 : 1),
-        m_isInitialized(false)
-    {
-      compute(matrix, computeEigenvectors);
-    }
-    
-    SelfAdjointEigenSolver(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors = true)
-        : m_eivec(matA.cols(), matA.cols()),
-          m_eivalues(matA.cols()),
-          m_subdiag(matA.cols() > 1 ? matA.cols() - 1 : 1),
-          m_isInitialized(false)
-    {
-      static_cast<GeneralizedSelfAdjointEigenSolver<MatrixType>*>(this)->compute(matA, matB, computeEigenvectors ? ComputeEigenvectors : EigenvaluesOnly);
-    }
-    
-    void compute(const MatrixType& matrix, bool computeEigenvectors)
-    {
-      compute(matrix, computeEigenvectors ? ComputeEigenvectors : EigenvaluesOnly);
-    }
-
-    void compute(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors = true)
-    {
-      compute(matA, matB, computeEigenvectors ? ComputeEigenvectors : EigenvaluesOnly);
-    }
-    #endif // EIGEN2_SUPPORT
-
   protected:
-    MatrixType m_eivec;
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+    
+    EigenvectorsType m_eivec;
     RealVectorType m_eivalues;
     typename TridiagonalizationType::SubDiagonalType m_subdiag;
     ComputationInfo m_info;
     bool m_isInitialized;
     bool m_eigenvectorsOk;
 };
 
+namespace internal {
 /** \internal
   *
   * \eigenvalues_module \ingroup Eigenvalues_Module
   *
   * Performs a QR step on a tridiagonal symmetric matrix represented as a
   * pair of two vectors \a diag and \a subdiag.
   *
-  * \param matA the input selfadjoint matrix
-  * \param hCoeffs returned Householder coefficients
+  * \param diag the diagonal part of the input selfadjoint tridiagonal matrix
+  * \param subdiag the sub-diagonal part of the input selfadjoint tridiagonal matrix
+  * \param start starting index of the submatrix to work on
+  * \param end last+1 index of the submatrix to work on
+  * \param matrixQ pointer to the column-major matrix holding the eigenvectors, can be 0
+  * \param n size of the input matrix
   *
   * For compilation efficiency reasons, this procedure does not use eigen expression
   * for its arguments.
   *
   * Implemented from Golub's "Matrix Computations", algorithm 8.3.2:
   * "implicit symmetric QR step with Wilkinson shift"
   */
-namespace internal {
 template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
+EIGEN_DEVICE_FUNC
 static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n);
 }
 
 template<typename MatrixType>
+template<typename InputType>
+EIGEN_DEVICE_FUNC
 SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
-::compute(const MatrixType& matrix, int options)
+::compute(const EigenBase<InputType>& a_matrix, int options)
 {
+  check_template_parameters();
+  
+  const InputType &matrix(a_matrix.derived());
+  
   using std::abs;
   eigen_assert(matrix.cols() == matrix.rows());
   eigen_assert((options&~(EigVecMask|GenEigMask))==0
           && (options&EigVecMask)!=EigVecMask
           && "invalid option parameter");
@@ -393,11 +412,12 @@
   Index n = matrix.cols();
   m_eivalues.resize(n,1);
 
   if(n==1)
   {
-    m_eivalues.coeffRef(0,0) = numext::real(matrix.coeff(0,0));
+    m_eivec = matrix;
+    m_eivalues.coeffRef(0,0) = numext::real(m_eivec.coeff(0,0));
     if(computeEigenvectors)
       m_eivec.setOnes(n,n);
     m_info = Success;
     m_isInitialized = true;
     m_eigenvectorsOk = computeEigenvectors;
@@ -404,103 +424,156 @@
     return *this;
   }
 
   // declare some aliases
   RealVectorType& diag = m_eivalues;
-  MatrixType& mat = m_eivec;
+  EigenvectorsType& mat = m_eivec;
 
   // map the matrix coefficients to [-1:1] to avoid over- and underflow.
   mat = matrix.template triangularView<Lower>();
   RealScalar scale = mat.cwiseAbs().maxCoeff();
   if(scale==RealScalar(0)) scale = RealScalar(1);
   mat.template triangularView<Lower>() /= scale;
   m_subdiag.resize(n-1);
   internal::tridiagonalization_inplace(mat, diag, m_subdiag, computeEigenvectors);
-  
-  Index end = n-1;
-  Index start = 0;
-  Index iter = 0; // total number of iterations
-
-  while (end>0)
-  {
-    for (Index i = start; i<end; ++i)
-      if (internal::isMuchSmallerThan(abs(m_subdiag[i]),(abs(diag[i])+abs(diag[i+1]))))
-        m_subdiag[i] = 0;
-
-    // find the largest unreduced block
-    while (end>0 && m_subdiag[end-1]==0)
-    {
-      end--;
-    }
-    if (end<=0)
-      break;
-
-    // if we spent too many iterations, we give up
-    iter++;
-    if(iter > m_maxIterations * n) break;
-
-    start = end - 1;
-    while (start>0 && m_subdiag[start-1]!=0)
-      start--;
-
-    internal::tridiagonal_qr_step<MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor>(diag.data(), m_subdiag.data(), start, end, computeEigenvectors ? m_eivec.data() : (Scalar*)0, n);
-  }
-
-  if (iter <= m_maxIterations * n)
-    m_info = Success;
-  else
-    m_info = NoConvergence;
-
-  // Sort eigenvalues and corresponding vectors.
-  // TODO make the sort optional ?
-  // TODO use a better sort algorithm !!
-  if (m_info == Success)
-  {
-    for (Index i = 0; i < n-1; ++i)
-    {
-      Index k;
-      m_eivalues.segment(i,n-i).minCoeff(&k);
-      if (k > 0)
-      {
-        std::swap(m_eivalues[i], m_eivalues[k+i]);
-        if(computeEigenvectors)
-          m_eivec.col(i).swap(m_eivec.col(k+i));
-      }
-    }
-  }
+
+  m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec);
   
   // scale back the eigen values
   m_eivalues *= scale;
 
   m_isInitialized = true;
   m_eigenvectorsOk = computeEigenvectors;
   return *this;
 }
 
+template<typename MatrixType>
+SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
+::computeFromTridiagonal(const RealVectorType& diag, const SubDiagonalType& subdiag , int options)
+{
+  //TODO : Add an option to scale the values beforehand
+  bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
+
+  m_eivalues = diag;
+  m_subdiag = subdiag;
+  if (computeEigenvectors)
+  {
+    m_eivec.setIdentity(diag.size(), diag.size());
+  }
+  m_info = internal::computeFromTridiagonal_impl(m_eivalues, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec);
+
+  m_isInitialized = true;
+  m_eigenvectorsOk = computeEigenvectors;
+  return *this;
+}
 
 namespace internal {
+/**
+  * \internal
+  * \brief Compute the eigendecomposition from a tridiagonal matrix
+  *
+  * \param[in,out] diag : On input, the diagonal of the matrix, on output the eigenvalues
+  * \param[in,out] subdiag : The subdiagonal part of the matrix (entries are modified during the decomposition)
+  * \param[in] maxIterations : the maximum number of iterations
+  * \param[in] computeEigenvectors : whether the eigenvectors have to be computed or not
+  * \param[out] eivec : The matrix to store the eigenvectors if computeEigenvectors==true. Must be allocated on input.
+  * \returns \c Success or \c NoConvergence
+  */
+template<typename MatrixType, typename DiagType, typename SubDiagType>
+ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag, const Index maxIterations, bool computeEigenvectors, MatrixType& eivec)
+{
+  using std::abs;
+
+  ComputationInfo info;
+  typedef typename MatrixType::Scalar Scalar;
+
+  Index n = diag.size();
+  Index end = n-1;
+  Index start = 0;
+  Index iter = 0; // total number of iterations
+  
+  typedef typename DiagType::RealScalar RealScalar;
+  const RealScalar considerAsZero = (std::numeric_limits<RealScalar>::min)();
+  const RealScalar precision = RealScalar(2)*NumTraits<RealScalar>::epsilon();
+  
+  while (end>0)
+  {
+    for (Index i = start; i<end; ++i)
+      if (internal::isMuchSmallerThan(abs(subdiag[i]),(abs(diag[i])+abs(diag[i+1])),precision) || abs(subdiag[i]) <= considerAsZero)
+        subdiag[i] = 0;
+
+    // find the largest unreduced block
+    while (end>0 && subdiag[end-1]==RealScalar(0))
+    {
+      end--;
+    }
+    if (end<=0)
+      break;
+
+    // if we spent too many iterations, we give up
+    iter++;
+    if(iter > maxIterations * n) break;
+
+    start = end - 1;
+    while (start>0 && subdiag[start-1]!=0)
+      start--;
+
+    internal::tridiagonal_qr_step<MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor>(diag.data(), subdiag.data(), start, end, computeEigenvectors ? eivec.data() : (Scalar*)0, n);
+  }
+  if (iter <= maxIterations * n)
+    info = Success;
+  else
+    info = NoConvergence;
+
+  // Sort eigenvalues and corresponding vectors.
+  // TODO make the sort optional ?
+  // TODO use a better sort algorithm !!
+  if (info == Success)
+  {
+    for (Index i = 0; i < n-1; ++i)
+    {
+      Index k;
+      diag.segment(i,n-i).minCoeff(&k);
+      if (k > 0)
+      {
+        std::swap(diag[i], diag[k+i]);
+        if(computeEigenvectors)
+          eivec.col(i).swap(eivec.col(k+i));
+      }
+    }
+  }
+  return info;
+}
   
 template<typename SolverType,int Size,bool IsComplex> struct direct_selfadjoint_eigenvalues
 {
+  EIGEN_DEVICE_FUNC
   static inline void run(SolverType& eig, const typename SolverType::MatrixType& A, int options)
   { eig.compute(A,options); }
 };
 
 template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3,false>
 {
   typedef typename SolverType::MatrixType MatrixType;
   typedef typename SolverType::RealVectorType VectorType;
   typedef typename SolverType::Scalar Scalar;
+  typedef typename SolverType::EigenvectorsType EigenvectorsType;
   
+
+  /** \internal
+   * Computes the roots of the characteristic polynomial of \a m.
+   * For numerical stability m.trace() should be near zero and to avoid over- or underflow m should be normalized.
+   */
+  EIGEN_DEVICE_FUNC
   static inline void computeRoots(const MatrixType& m, VectorType& roots)
   {
-    using std::sqrt;
-    using std::atan2;
-    using std::cos;
-    using std::sin;
-    const Scalar s_inv3 = Scalar(1.0)/Scalar(3.0);
-    const Scalar s_sqrt3 = sqrt(Scalar(3.0));
+    EIGEN_USING_STD_MATH(sqrt)
+    EIGEN_USING_STD_MATH(atan2)
+    EIGEN_USING_STD_MATH(cos)
+    EIGEN_USING_STD_MATH(sin)
+    const Scalar s_inv3 = Scalar(1)/Scalar(3);
+    const Scalar s_sqrt3 = sqrt(Scalar(3));
 
     // The characteristic equation is x^3 - c2*x^2 + c1*x - c0 = 0.  The
     // eigenvalues are the roots to this equation, all guaranteed to be
     // real-valued, because the matrix is symmetric.
     Scalar c0 = m(0,0)*m(1,1)*m(2,2) + Scalar(2)*m(1,0)*m(2,0)*m(2,1) - m(0,0)*m(2,1)*m(2,1) - m(1,1)*m(2,0)*m(2,0) - m(2,2)*m(1,0)*m(1,0);
@@ -508,247 +581,232 @@
     Scalar c2 = m(0,0) + m(1,1) + m(2,2);
 
     // Construct the parameters used in classifying the roots of the equation
     // and in solving the equation for the roots in closed form.
     Scalar c2_over_3 = c2*s_inv3;
-    Scalar a_over_3 = (c1 - c2*c2_over_3)*s_inv3;
-    if (a_over_3 > Scalar(0))
-      a_over_3 = Scalar(0);
+    Scalar a_over_3 = (c2*c2_over_3 - c1)*s_inv3;
+    a_over_3 = numext::maxi(a_over_3, Scalar(0));
 
     Scalar half_b = Scalar(0.5)*(c0 + c2_over_3*(Scalar(2)*c2_over_3*c2_over_3 - c1));
 
-    Scalar q = half_b*half_b + a_over_3*a_over_3*a_over_3;
-    if (q > Scalar(0))
-      q = Scalar(0);
+    Scalar q = a_over_3*a_over_3*a_over_3 - half_b*half_b;
+    q = numext::maxi(q, Scalar(0));
 
     // Compute the eigenvalues by solving for the roots of the polynomial.
-    Scalar rho = sqrt(-a_over_3);
-    Scalar theta = atan2(sqrt(-q),half_b)*s_inv3;
+    Scalar rho = sqrt(a_over_3);
+    Scalar theta = atan2(sqrt(q),half_b)*s_inv3;  // since sqrt(q) > 0, atan2 is in [0, pi] and theta is in [0, pi/3]
     Scalar cos_theta = cos(theta);
     Scalar sin_theta = sin(theta);
-    roots(0) = c2_over_3 + Scalar(2)*rho*cos_theta;
-    roots(1) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
-    roots(2) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
-
-    // Sort in increasing order.
-    if (roots(0) >= roots(1))
-      std::swap(roots(0),roots(1));
-    if (roots(1) >= roots(2))
-    {
-      std::swap(roots(1),roots(2));
-      if (roots(0) >= roots(1))
-        std::swap(roots(0),roots(1));
-    }
-  }
-  
+    // roots are already sorted, since cos is monotonically decreasing on [0, pi]
+    roots(0) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta); // == 2*rho*cos(theta+2pi/3)
+    roots(1) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta); // == 2*rho*cos(theta+ pi/3)
+    roots(2) = c2_over_3 + Scalar(2)*rho*cos_theta;
+  }
+
+  EIGEN_DEVICE_FUNC
+  static inline bool extract_kernel(MatrixType& mat, Ref<VectorType> res, Ref<VectorType> representative)
+  {
+    using std::abs;
+    Index i0;
+    // Find non-zero column i0 (by construction, there must exist a non zero coefficient on the diagonal):
+    mat.diagonal().cwiseAbs().maxCoeff(&i0);
+    // mat.col(i0) is a good candidate for an orthogonal vector to the current eigenvector,
+    // so let's save it:
+    representative = mat.col(i0);
+    Scalar n0, n1;
+    VectorType c0, c1;
+    n0 = (c0 = representative.cross(mat.col((i0+1)%3))).squaredNorm();
+    n1 = (c1 = representative.cross(mat.col((i0+2)%3))).squaredNorm();
+    if(n0>n1) res = c0/std::sqrt(n0);
+    else      res = c1/std::sqrt(n1);
+
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC
   static inline void run(SolverType& solver, const MatrixType& mat, int options)
   {
-    using std::sqrt;
     eigen_assert(mat.cols() == 3 && mat.cols() == mat.rows());
     eigen_assert((options&~(EigVecMask|GenEigMask))==0
             && (options&EigVecMask)!=EigVecMask
             && "invalid option parameter");
     bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
     
-    MatrixType& eivecs = solver.m_eivec;
+    EigenvectorsType& eivecs = solver.m_eivec;
     VectorType& eivals = solver.m_eivalues;
   
-    // map the matrix coefficients to [-1:1] to avoid over- and underflow.
-    Scalar scale = mat.cwiseAbs().maxCoeff();
-    MatrixType scaledMat = mat / scale;
+    // Shift the matrix to the mean eigenvalue and map the matrix coefficients to [-1:1] to avoid over- and underflow.
+    Scalar shift = mat.trace() / Scalar(3);
+    // TODO Avoid this copy. Currently it is necessary to suppress bogus values when determining maxCoeff and for computing the eigenvectors later
+    MatrixType scaledMat = mat.template selfadjointView<Lower>();
+    scaledMat.diagonal().array() -= shift;
+    Scalar scale = scaledMat.cwiseAbs().maxCoeff();
+    if(scale > 0) scaledMat /= scale;   // TODO for scale==0 we could save the remaining operations
 
     // compute the eigenvalues
     computeRoots(scaledMat,eivals);
 
-    // compute the eigen vectors
+    // compute the eigenvectors
     if(computeEigenvectors)
     {
-      Scalar safeNorm2 = Eigen::NumTraits<Scalar>::epsilon();
       if((eivals(2)-eivals(0))<=Eigen::NumTraits<Scalar>::epsilon())
       {
+        // All three eigenvalues are numerically the same
         eivecs.setIdentity();
       }
       else
       {
-        scaledMat = scaledMat.template selfadjointView<Lower>();
-        MatrixType tmp;
-        tmp = scaledMat;
-
-        Scalar d0 = eivals(2) - eivals(1);
-        Scalar d1 = eivals(1) - eivals(0);
-        int k =  d0 > d1 ? 2 : 0;
-        d0 = d0 > d1 ? d0 : d1;
-
-        tmp.diagonal().array () -= eivals(k);
-        VectorType cross;
-        Scalar n;
-        n = (cross = tmp.row(0).cross(tmp.row(1))).squaredNorm();
-
-        if(n>safeNorm2)
-        {
-          eivecs.col(k) = cross / sqrt(n);
-        }
-        else
-        {
-          n = (cross = tmp.row(0).cross(tmp.row(2))).squaredNorm();
-
-          if(n>safeNorm2)
-          {
-            eivecs.col(k) = cross / sqrt(n);
-          }
-          else
-          {
-            n = (cross = tmp.row(1).cross(tmp.row(2))).squaredNorm();
-
-            if(n>safeNorm2)
-            {
-              eivecs.col(k) = cross / sqrt(n);
-            }
-            else
-            {
-              // the input matrix and/or the eigenvaues probably contains some inf/NaN,
-              // => exit
-              // scale back to the original size.
-              eivals *= scale;
-
-              solver.m_info = NumericalIssue;
-              solver.m_isInitialized = true;
-              solver.m_eigenvectorsOk = computeEigenvectors;
-              return;
-            }
-          }
-        }
-
-        tmp = scaledMat;
-        tmp.diagonal().array() -= eivals(1);
-
-        if(d0<=Eigen::NumTraits<Scalar>::epsilon())
-        {
-          eivecs.col(1) = eivecs.col(k).unitOrthogonal();
-        }
-        else
-        {
-          n = (cross = eivecs.col(k).cross(tmp.row(0))).squaredNorm();
-          if(n>safeNorm2)
-          {
-            eivecs.col(1) = cross / sqrt(n);
-          }
-          else
-          {
-            n = (cross = eivecs.col(k).cross(tmp.row(1))).squaredNorm();
-            if(n>safeNorm2)
-              eivecs.col(1) = cross / sqrt(n);
-            else
-            {
-              n = (cross = eivecs.col(k).cross(tmp.row(2))).squaredNorm();
-              if(n>safeNorm2)
-                eivecs.col(1) = cross / sqrt(n);
-              else
-              {
-                // we should never reach this point,
-                // if so the last two eigenvalues are likely to be very close to each other
-                eivecs.col(1) = eivecs.col(k).unitOrthogonal();
-              }
-            }
-          }
-
-          // make sure that eivecs[1] is orthogonal to eivecs[2]
-          // FIXME: this step should not be needed
-          Scalar d = eivecs.col(1).dot(eivecs.col(k));
-          eivecs.col(1) = (eivecs.col(1) - d * eivecs.col(k)).normalized();
-        }
-
-        eivecs.col(k==2 ? 0 : 2) = eivecs.col(k).cross(eivecs.col(1)).normalized();
-      }
-    }
-    // Rescale back to the original size.
-    eivals *= scale;
+        MatrixType tmp;
+        tmp = scaledMat;
+
+        // Compute the eigenvector of the most distinct eigenvalue
+        Scalar d0 = eivals(2) - eivals(1);
+        Scalar d1 = eivals(1) - eivals(0);
+        Index k(0), l(2);
+        if(d0 > d1)
+        {
+          numext::swap(k,l);
+          d0 = d1;
+        }
+
+        // Compute the eigenvector of index k
+        {
+          tmp.diagonal().array () -= eivals(k);
+          // By construction, 'tmp' is of rank 2, and its kernel corresponds to the respective eigenvector.
+          extract_kernel(tmp, eivecs.col(k), eivecs.col(l));
+        }
+
+        // Compute eigenvector of index l
+        if(d0<=2*Eigen::NumTraits<Scalar>::epsilon()*d1)
+        {
+          // If d0 is too small, then the two other eigenvalues are numerically the same,
+          // and thus we only have to ortho-normalize the near orthogonal vector we saved above.
+          eivecs.col(l) -= eivecs.col(k).dot(eivecs.col(l))*eivecs.col(l);
+          eivecs.col(l).normalize();
+        }
+        else
+        {
+          tmp = scaledMat;
+          tmp.diagonal().array () -= eivals(l);
+
+          VectorType dummy;
+          extract_kernel(tmp, eivecs.col(l), dummy);
+        }
+
+        // Compute last eigenvector from the other two
+        eivecs.col(1) = eivecs.col(2).cross(eivecs.col(0)).normalized();
+      }
+    }
+
+    // Rescale back to the original size.
+    eivals *= scale;
+    eivals.array() += shift;
     
     solver.m_info = Success;
     solver.m_isInitialized = true;
     solver.m_eigenvectorsOk = computeEigenvectors;
   }
 };
 
 // 2x2 direct eigenvalues decomposition, code from Hauke Heibel
-template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2,false>
+template<typename SolverType> 
+struct direct_selfadjoint_eigenvalues<SolverType,2,false>
 {
   typedef typename SolverType::MatrixType MatrixType;
   typedef typename SolverType::RealVectorType VectorType;
   typedef typename SolverType::Scalar Scalar;
+  typedef typename SolverType::EigenvectorsType EigenvectorsType;
   
+  EIGEN_DEVICE_FUNC
   static inline void computeRoots(const MatrixType& m, VectorType& roots)
   {
     using std::sqrt;
-    const Scalar t0 = Scalar(0.5) * sqrt( numext::abs2(m(0,0)-m(1,1)) + Scalar(4)*m(1,0)*m(1,0));
+    const Scalar t0 = Scalar(0.5) * sqrt( numext::abs2(m(0,0)-m(1,1)) + Scalar(4)*numext::abs2(m(1,0)));
     const Scalar t1 = Scalar(0.5) * (m(0,0) + m(1,1));
     roots(0) = t1 - t0;
     roots(1) = t1 + t0;
   }
   
+  EIGEN_DEVICE_FUNC
   static inline void run(SolverType& solver, const MatrixType& mat, int options)
   {
-    using std::sqrt;
+    EIGEN_USING_STD_MATH(sqrt);
+    EIGEN_USING_STD_MATH(abs);
+    
     eigen_assert(mat.cols() == 2 && mat.cols() == mat.rows());
     eigen_assert((options&~(EigVecMask|GenEigMask))==0
             && (options&EigVecMask)!=EigVecMask
             && "invalid option parameter");
     bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
     
-    MatrixType& eivecs = solver.m_eivec;
+    EigenvectorsType& eivecs = solver.m_eivec;
     VectorType& eivals = solver.m_eivalues;
   
-    // map the matrix coefficients to [-1:1] to avoid over- and underflow.
-    Scalar scale = mat.cwiseAbs().maxCoeff();
-    scale = (std::max)(scale,Scalar(1));
-    MatrixType scaledMat = mat / scale;
-    
+    // Shift the matrix to the mean eigenvalue and map the matrix coefficients to [-1:1] to avoid over- and underflow.
+    Scalar shift = mat.trace() / Scalar(2);
+    MatrixType scaledMat = mat;
+    scaledMat.coeffRef(0,1) = mat.coeff(1,0);
+    scaledMat.diagonal().array() -= shift;
+    Scalar scale = scaledMat.cwiseAbs().maxCoeff();
+    if(scale > Scalar(0))
+      scaledMat /= scale;
+
     // Compute the eigenvalues
     computeRoots(scaledMat,eivals);
-    
+
     // compute the eigen vectors
     if(computeEigenvectors)
     {
-      scaledMat.diagonal().array () -= eivals(1);
-      Scalar a2 = numext::abs2(scaledMat(0,0));
-      Scalar c2 = numext::abs2(scaledMat(1,1));
-      Scalar b2 = numext::abs2(scaledMat(1,0));
-      if(a2>c2)
-      {
-        eivecs.col(1) << -scaledMat(1,0), scaledMat(0,0);
-        eivecs.col(1) /= sqrt(a2+b2);
+      if((eivals(1)-eivals(0))<=abs(eivals(1))*Eigen::NumTraits<Scalar>::epsilon())
+      {
+        eivecs.setIdentity();
       }
       else
       {
-        eivecs.col(1) << -scaledMat(1,1), scaledMat(1,0);
-        eivecs.col(1) /= sqrt(c2+b2);
-      }
+        scaledMat.diagonal().array () -= eivals(1);
+        Scalar a2 = numext::abs2(scaledMat(0,0));
+        Scalar c2 = numext::abs2(scaledMat(1,1));
+        Scalar b2 = numext::abs2(scaledMat(1,0));
+        if(a2>c2)
+        {
+          eivecs.col(1) << -scaledMat(1,0), scaledMat(0,0);
+          eivecs.col(1) /= sqrt(a2+b2);
+        }
+        else
+        {
+          eivecs.col(1) << -scaledMat(1,1), scaledMat(1,0);
+          eivecs.col(1) /= sqrt(c2+b2);
+        }
 
-      eivecs.col(0) << eivecs.col(1).unitOrthogonal();
+        eivecs.col(0) << eivecs.col(1).unitOrthogonal();
+      }
     }
-    
+
     // Rescale back to the original size.
     eivals *= scale;
-    
+    eivals.array() += shift;
+
     solver.m_info = Success;
     solver.m_isInitialized = true;
     solver.m_eigenvectorsOk = computeEigenvectors;
   }
 };
 
 }
 
 template<typename MatrixType>
+EIGEN_DEVICE_FUNC
 SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
 ::computeDirect(const MatrixType& matrix, int options)
 {
   internal::direct_selfadjoint_eigenvalues<SelfAdjointEigenSolver,Size,NumTraits<Scalar>::IsComplex>::run(*this,matrix,options);
   return *this;
 }
 
 namespace internal {
 template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
+EIGEN_DEVICE_FUNC
 static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
 {
   using std::abs;
   RealScalar td = (diag[end-1] - diag[end])*RealScalar(0.5);
   RealScalar e = subdiag[end-1];
@@ -756,18 +814,18 @@
   // underflow thus leading to inf/NaN values when using the following commented code:
 //   RealScalar e2 = numext::abs2(subdiag[end-1]);
 //   RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * sqrt(td*td + e2));
   // This explain the following, somewhat more complicated, version:
   RealScalar mu = diag[end];
-  if(td==0)
+  if(td==RealScalar(0))
     mu -= abs(e);
   else
   {
     RealScalar e2 = numext::abs2(subdiag[end-1]);
     RealScalar h = numext::hypot(td,e);
-    if(e2==0)  mu -= (e / (td + (td>0 ? 1 : -1))) * (e / h);
-    else       mu -= e2 / (td + (td>0 ? h : -h));
+    if(e2==RealScalar(0)) mu -= (e / (td + (td>RealScalar(0) ? RealScalar(1) : RealScalar(-1)))) * (e / h);
+    else                  mu -= e2 / (td + (td>RealScalar(0) ? h : -h));
   }
   
   RealScalar x = diag[start] - mu;
   RealScalar z = subdiag[start];
   for (Index k = start; k < end; ++k)

ADDED   3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h
Index: 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h
@@ -0,0 +1,90 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to LAPACKe
+ *    Self-adjoint eigenvalues/eigenvectors.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_SAEIGENSOLVER_LAPACKE_H
+#define EIGEN_SAEIGENSOLVER_LAPACKE_H
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by LAPACKe */
+
+#define EIGEN_LAPACKE_EIG_SELFADJ(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, EIGCOLROW, LAPACKE_COLROW ) \
+template<> template<typename InputType> inline \
+SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
+SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const EigenBase<InputType>& matrix, int options) \
+{ \
+  eigen_assert(matrix.cols() == matrix.rows()); \
+  eigen_assert((options&~(EigVecMask|GenEigMask))==0 \
+          && (options&EigVecMask)!=EigVecMask \
+          && "invalid option parameter"); \
+  bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; \
+  lapack_int n = internal::convert_index<lapack_int>(matrix.cols()), lda, matrix_order, info; \
+  m_eivalues.resize(n,1); \
+  m_subdiag.resize(n-1); \
+  m_eivec = matrix; \
+\
+  if(n==1) \
+  { \
+    m_eivalues.coeffRef(0,0) = numext::real(m_eivec.coeff(0,0)); \
+    if(computeEigenvectors) m_eivec.setOnes(n,n); \
+    m_info = Success; \
+    m_isInitialized = true; \
+    m_eigenvectorsOk = computeEigenvectors; \
+    return *this; \
+  } \
+\
+  lda = internal::convert_index<lapack_int>(m_eivec.outerStride()); \
+  matrix_order=LAPACKE_COLROW; \
+  char jobz, uplo='L'/*, range='A'*/; \
+  jobz = computeEigenvectors ? 'V' : 'N'; \
+\
+  info = LAPACKE_##LAPACKE_NAME( matrix_order, jobz, uplo, n, (LAPACKE_TYPE*)m_eivec.data(), lda, (LAPACKE_RTYPE*)m_eivalues.data() ); \
+  m_info = (info==0) ? Success : NoConvergence; \
+  m_isInitialized = true; \
+  m_eigenvectorsOk = computeEigenvectors; \
+  return *this; \
+}
+
+
+EIGEN_LAPACKE_EIG_SELFADJ(double,   double,                double, dsyev, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_EIG_SELFADJ(float,    float,                 float,  ssyev, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_EIG_SELFADJ(dcomplex, lapack_complex_double, double, zheev, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_EIG_SELFADJ(scomplex, lapack_complex_float,  float,  cheev, ColMajor, LAPACK_COL_MAJOR)
+
+EIGEN_LAPACKE_EIG_SELFADJ(double,   double,                double, dsyev, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_EIG_SELFADJ(float,    float,                 float,  ssyev, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_EIG_SELFADJ(dcomplex, lapack_complex_double, double, zheev, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_EIG_SELFADJ(scomplex, lapack_complex_float,  float,  cheev, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_SAEIGENSOLVER_H

DELETED 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
Index: 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
@@ -1,92 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *    Self-adjoint eigenvalues/eigenvectors.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_SAEIGENSOLVER_MKL_H
-#define EIGEN_SAEIGENSOLVER_MKL_H
-
-#include "Eigen/src/Core/util/MKL_support.h"
-
-namespace Eigen { 
-
-/** \internal Specialization for the data types supported by MKL */
-
-#define EIGEN_MKL_EIG_SELFADJ(EIGTYPE, MKLTYPE, MKLRTYPE, MKLNAME, EIGCOLROW, MKLCOLROW ) \
-template<> inline \
-SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
-SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, int options) \
-{ \
-  eigen_assert(matrix.cols() == matrix.rows()); \
-  eigen_assert((options&~(EigVecMask|GenEigMask))==0 \
-          && (options&EigVecMask)!=EigVecMask \
-          && "invalid option parameter"); \
-  bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; \
-  lapack_int n = matrix.cols(), lda, matrix_order, info; \
-  m_eivalues.resize(n,1); \
-  m_subdiag.resize(n-1); \
-  m_eivec = matrix; \
-\
-  if(n==1) \
-  { \
-    m_eivalues.coeffRef(0,0) = numext::real(matrix.coeff(0,0)); \
-    if(computeEigenvectors) m_eivec.setOnes(n,n); \
-    m_info = Success; \
-    m_isInitialized = true; \
-    m_eigenvectorsOk = computeEigenvectors; \
-    return *this; \
-  } \
-\
-  lda = matrix.outerStride(); \
-  matrix_order=MKLCOLROW; \
-  char jobz, uplo='L'/*, range='A'*/; \
-  jobz = computeEigenvectors ? 'V' : 'N'; \
-\
-  info = LAPACKE_##MKLNAME( matrix_order, jobz, uplo, n, (MKLTYPE*)m_eivec.data(), lda, (MKLRTYPE*)m_eivalues.data() ); \
-  m_info = (info==0) ? Success : NoConvergence; \
-  m_isInitialized = true; \
-  m_eigenvectorsOk = computeEigenvectors; \
-  return *this; \
-}
-
-
-EIGEN_MKL_EIG_SELFADJ(double,   double,        double, dsyev, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_EIG_SELFADJ(float,    float,         float,  ssyev, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_EIG_SELFADJ(dcomplex, MKL_Complex16, double, zheev, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_EIG_SELFADJ(scomplex, MKL_Complex8,  float,  cheev, ColMajor, LAPACK_COL_MAJOR)
-
-EIGEN_MKL_EIG_SELFADJ(double,   double,        double, dsyev, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_EIG_SELFADJ(float,    float,         float,  ssyev, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_EIG_SELFADJ(dcomplex, MKL_Complex16, double, zheev, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_EIG_SELFADJ(scomplex, MKL_Complex8,  float,  cheev, RowMajor, LAPACK_ROW_MAJOR)
-
-} // end namespace Eigen
-
-#endif // EIGEN_SAEIGENSOLVER_H

Index: 3rd_party/eigen/Eigen/src/Eigenvalues/Tridiagonalization.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Eigenvalues/Tridiagonalization.h
+++ 3rd_party/eigen/Eigen/src/Eigenvalues/Tridiagonalization.h
@@ -16,12 +16,14 @@
 namespace internal {
   
 template<typename MatrixType> struct TridiagonalizationMatrixTReturnType;
 template<typename MatrixType>
 struct traits<TridiagonalizationMatrixTReturnType<MatrixType> >
+  : public traits<typename MatrixType::PlainObject>
 {
-  typedef typename MatrixType::PlainObject ReturnType;
+  typedef typename MatrixType::PlainObject ReturnType; // FIXME shall it be a BandMatrix?
+  enum { Flags = 0 };
 };
 
 template<typename MatrixType, typename CoeffVectorType>
 void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs);
 }
@@ -65,11 +67,11 @@
     /** \brief Synonym for the template parameter \p _MatrixType. */
     typedef _MatrixType MatrixType;
 
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     enum {
       Size = MatrixType::RowsAtCompileTime,
       SizeMinusOne = Size == Dynamic ? Dynamic : (Size > 1 ? Size - 1 : 1),
       Options = MatrixType::Options,
@@ -87,14 +89,12 @@
               typename internal::add_const_on_value_type<typename Diagonal<const MatrixType>::RealReturnType>::type,
               const Diagonal<const MatrixType>
             >::type DiagonalReturnType;
 
     typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
-              typename internal::add_const_on_value_type<typename Diagonal<
-                Block<const MatrixType,SizeMinusOne,SizeMinusOne> >::RealReturnType>::type,
-              const Diagonal<
-                Block<const MatrixType,SizeMinusOne,SizeMinusOne> >
+              typename internal::add_const_on_value_type<typename Diagonal<const MatrixType, -1>::RealReturnType>::type,
+              const Diagonal<const MatrixType, -1>
             >::type SubDiagonalReturnType;
 
     /** \brief Return type of matrixQ() */
     typedef HouseholderSequence<MatrixType,typename internal::remove_all<typename CoeffVectorType::ConjugateReturnType>::type> HouseholderSequenceType;
 
@@ -108,11 +108,11 @@
       * used as a hint. It is not an error to give a wrong \p size, but it may
       * impair performance.
       *
       * \sa compute() for an example.
       */
-    Tridiagonalization(Index size = Size==Dynamic ? 2 : Size)
+    explicit Tridiagonalization(Index size = Size==Dynamic ? 2 : Size)
       : m_matrix(size,size),
         m_hCoeffs(size > 1 ? size-1 : 1),
         m_isInitialized(false)
     {}
 
@@ -124,12 +124,13 @@
       * This constructor calls compute() to compute the tridiagonal decomposition.
       *
       * Example: \include Tridiagonalization_Tridiagonalization_MatrixType.cpp
       * Output: \verbinclude Tridiagonalization_Tridiagonalization_MatrixType.out
       */
-    Tridiagonalization(const MatrixType& matrix)
-      : m_matrix(matrix),
+    template<typename InputType>
+    explicit Tridiagonalization(const EigenBase<InputType>& matrix)
+      : m_matrix(matrix.derived()),
         m_hCoeffs(matrix.cols() > 1 ? matrix.cols()-1 : 1),
         m_isInitialized(false)
     {
       internal::tridiagonalization_inplace(m_matrix, m_hCoeffs);
       m_isInitialized = true;
@@ -150,13 +151,14 @@
       * object, if the size of the matrix does not change.
       *
       * Example: \include Tridiagonalization_compute.cpp
       * Output: \verbinclude Tridiagonalization_compute.out
       */
-    Tridiagonalization& compute(const MatrixType& matrix)
+    template<typename InputType>
+    Tridiagonalization& compute(const EigenBase<InputType>& matrix)
     {
-      m_matrix = matrix;
+      m_matrix = matrix.derived();
       m_hCoeffs.resize(matrix.rows()-1, 1);
       internal::tridiagonalization_inplace(m_matrix, m_hCoeffs);
       m_isInitialized = true;
       return *this;
     }
@@ -303,20 +305,19 @@
 template<typename MatrixType>
 typename Tridiagonalization<MatrixType>::DiagonalReturnType
 Tridiagonalization<MatrixType>::diagonal() const
 {
   eigen_assert(m_isInitialized && "Tridiagonalization is not initialized.");
-  return m_matrix.diagonal();
+  return m_matrix.diagonal().real();
 }
 
 template<typename MatrixType>
 typename Tridiagonalization<MatrixType>::SubDiagonalReturnType
 Tridiagonalization<MatrixType>::subDiagonal() const
 {
   eigen_assert(m_isInitialized && "Tridiagonalization is not initialized.");
-  Index n = m_matrix.rows();
-  return Block<const MatrixType,SizeMinusOne,SizeMinusOne>(m_matrix, 1, 0, n-1,n-1).diagonal();
+  return m_matrix.template diagonal<-1>().real();
 }
 
 namespace internal {
 
 /** \internal
@@ -344,11 +345,10 @@
   */
 template<typename MatrixType, typename CoeffVectorType>
 void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs)
 {
   using numext::conj;
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
   Index n = matA.rows();
   eigen_assert(n==matA.cols());
   eigen_assert(n==hCoeffs.size()+1 || n==1);
@@ -365,14 +365,14 @@
     matA.col(i).coeffRef(i+1) = 1;
 
     hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
                                   * (conj(h) * matA.col(i).tail(remainingSize)));
 
-    hCoeffs.tail(n-i-1) += (conj(h)*Scalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1);
+    hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1);
 
     matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
-      .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), -1);
+      .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1));
 
     matA.col(i).coeffRef(i+1) = beta;
     hCoeffs.coeffRef(i) = h;
   }
 }
@@ -436,11 +436,10 @@
 template<typename MatrixType, int Size, bool IsComplex>
 struct tridiagonalization_inplace_selector
 {
   typedef typename Tridiagonalization<MatrixType>::CoeffVectorType CoeffVectorType;
   typedef typename Tridiagonalization<MatrixType>::HouseholderSequenceType HouseholderSequenceType;
-  typedef typename MatrixType::Index Index;
   template<typename DiagonalType, typename SubDiagonalType>
   static void run(MatrixType& mat, DiagonalType& diag, SubDiagonalType& subdiag, bool extractQ)
   {
     CoeffVectorType hCoeffs(mat.cols()-1);
     tridiagonalization_inplace(mat,hCoeffs);
@@ -465,13 +464,14 @@
 
   template<typename DiagonalType, typename SubDiagonalType>
   static void run(MatrixType& mat, DiagonalType& diag, SubDiagonalType& subdiag, bool extractQ)
   {
     using std::sqrt;
+    const RealScalar tol = (std::numeric_limits<RealScalar>::min)();
     diag[0] = mat(0,0);
     RealScalar v1norm2 = numext::abs2(mat(2,0));
-    if(v1norm2 == RealScalar(0))
+    if(v1norm2 <= tol)
     {
       diag[1] = mat(1,1);
       diag[2] = mat(2,2);
       subdiag[0] = mat(1,0);
       subdiag[1] = mat(2,1);
@@ -524,11 +524,10 @@
   * \tparam MatrixType type of underlying dense matrix
   */
 template<typename MatrixType> struct TridiagonalizationMatrixTReturnType
 : public ReturnByValue<TridiagonalizationMatrixTReturnType<MatrixType> >
 {
-    typedef typename MatrixType::Index Index;
   public:
     /** \brief Constructor.
       *
       * \param[in] mat The underlying dense matrix
       */

Index: 3rd_party/eigen/Eigen/src/Geometry/AlignedBox.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/AlignedBox.h
+++ 3rd_party/eigen/Eigen/src/Geometry/AlignedBox.h
@@ -17,119 +17,123 @@
   *
   * \class AlignedBox
   *
   * \brief An axis aligned box
   *
-  * \param _Scalar the type of the scalar coefficients
-  * \param _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
+  * \tparam _Scalar the type of the scalar coefficients
+  * \tparam _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
   *
   * This class represents an axis aligned box as a pair of the minimal and maximal corners.
+  * \warning The result of most methods is undefined when applied to an empty box. You can check for empty boxes using isEmpty().
+  * \sa alignedboxtypedefs
   */
 template <typename _Scalar, int _AmbientDim>
 class AlignedBox
 {
 public:
 EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
   enum { AmbientDimAtCompileTime = _AmbientDim };
   typedef _Scalar                                   Scalar;
   typedef NumTraits<Scalar>                         ScalarTraits;
-  typedef DenseIndex                                Index;
+  typedef Eigen::Index                              Index; ///< \deprecated since Eigen 3.3
   typedef typename ScalarTraits::Real               RealScalar;
-  typedef typename ScalarTraits::NonInteger      NonInteger;
+  typedef typename ScalarTraits::NonInteger         NonInteger;
   typedef Matrix<Scalar,AmbientDimAtCompileTime,1>  VectorType;
+  typedef CwiseBinaryOp<internal::scalar_sum_op<Scalar>, const VectorType, const VectorType> VectorTypeSum;
 
   /** Define constants to name the corners of a 1D, 2D or 3D axis aligned bounding box */
   enum CornerType
   {
-    /** 1D names */
+    /** 1D names @{ */
     Min=0, Max=1,
+    /** @} */
 
-    /** Added names for 2D */
+    /** Identifier for 2D corner @{ */
     BottomLeft=0, BottomRight=1,
     TopLeft=2, TopRight=3,
+    /** @} */
 
-    /** Added names for 3D */
+    /** Identifier for 3D corner  @{ */
     BottomLeftFloor=0, BottomRightFloor=1,
     TopLeftFloor=2, TopRightFloor=3,
     BottomLeftCeil=4, BottomRightCeil=5,
     TopLeftCeil=6, TopRightCeil=7
+    /** @} */
   };
 
 
   /** Default constructor initializing a null box. */
-  inline AlignedBox()
+  EIGEN_DEVICE_FUNC inline AlignedBox()
   { if (AmbientDimAtCompileTime!=Dynamic) setEmpty(); }
 
   /** Constructs a null box with \a _dim the dimension of the ambient space. */
-  inline explicit AlignedBox(Index _dim) : m_min(_dim), m_max(_dim)
+  EIGEN_DEVICE_FUNC inline explicit AlignedBox(Index _dim) : m_min(_dim), m_max(_dim)
   { setEmpty(); }
 
-  /** Constructs a box with extremities \a _min and \a _max. */
+  /** Constructs a box with extremities \a _min and \a _max.
+   * \warning If either component of \a _min is larger than the same component of \a _max, the constructed box is empty. */
   template<typename OtherVectorType1, typename OtherVectorType2>
-  inline AlignedBox(const OtherVectorType1& _min, const OtherVectorType2& _max) : m_min(_min), m_max(_max) {}
+  EIGEN_DEVICE_FUNC inline AlignedBox(const OtherVectorType1& _min, const OtherVectorType2& _max) : m_min(_min), m_max(_max) {}
 
   /** Constructs a box containing a single point \a p. */
   template<typename Derived>
-  inline explicit AlignedBox(const MatrixBase<Derived>& a_p)
-  {
-    typename internal::nested<Derived,2>::type p(a_p.derived());
-    m_min = p;
-    m_max = p;
-  }
-
-  ~AlignedBox() {}
+  EIGEN_DEVICE_FUNC inline explicit AlignedBox(const MatrixBase<Derived>& p) : m_min(p), m_max(m_min)
+  { }
+
+  EIGEN_DEVICE_FUNC ~AlignedBox() {}
 
   /** \returns the dimension in which the box holds */
-  inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size() : Index(AmbientDimAtCompileTime); }
-
-  /** \deprecated use isEmpty */
-  inline bool isNull() const { return isEmpty(); }
-
-  /** \deprecated use setEmpty */
-  inline void setNull() { setEmpty(); }
-
-  /** \returns true if the box is empty. */
-  inline bool isEmpty() const { return (m_min.array() > m_max.array()).any(); }
-
-  /** Makes \c *this an empty box. */
-  inline void setEmpty()
+  EIGEN_DEVICE_FUNC inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size() : Index(AmbientDimAtCompileTime); }
+
+  /** \deprecated use isEmpty() */
+  EIGEN_DEVICE_FUNC inline bool isNull() const { return isEmpty(); }
+
+  /** \deprecated use setEmpty() */
+  EIGEN_DEVICE_FUNC inline void setNull() { setEmpty(); }
+
+  /** \returns true if the box is empty.
+   * \sa setEmpty */
+  EIGEN_DEVICE_FUNC inline bool isEmpty() const { return (m_min.array() > m_max.array()).any(); }
+
+  /** Makes \c *this an empty box.
+   * \sa isEmpty */
+  EIGEN_DEVICE_FUNC inline void setEmpty()
   {
     m_min.setConstant( ScalarTraits::highest() );
     m_max.setConstant( ScalarTraits::lowest() );
   }
 
   /** \returns the minimal corner */
-  inline const VectorType& (min)() const { return m_min; }
+  EIGEN_DEVICE_FUNC inline const VectorType& (min)() const { return m_min; }
   /** \returns a non const reference to the minimal corner */
-  inline VectorType& (min)() { return m_min; }
+  EIGEN_DEVICE_FUNC inline VectorType& (min)() { return m_min; }
   /** \returns the maximal corner */
-  inline const VectorType& (max)() const { return m_max; }
+  EIGEN_DEVICE_FUNC inline const VectorType& (max)() const { return m_max; }
   /** \returns a non const reference to the maximal corner */
-  inline VectorType& (max)() { return m_max; }
+  EIGEN_DEVICE_FUNC inline VectorType& (max)() { return m_max; }
 
   /** \returns the center of the box */
-  inline const CwiseUnaryOp<internal::scalar_quotient1_op<Scalar>,
-                            const CwiseBinaryOp<internal::scalar_sum_op<Scalar>, const VectorType, const VectorType> >
+  EIGEN_DEVICE_FUNC inline const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(VectorTypeSum, RealScalar, quotient)
   center() const
-  { return (m_min+m_max)/2; }
+  { return (m_min+m_max)/RealScalar(2); }
 
   /** \returns the lengths of the sides of the bounding box.
     * Note that this function does not get the same
     * result for integral or floating scalar types: see
     */
-  inline const CwiseBinaryOp< internal::scalar_difference_op<Scalar>, const VectorType, const VectorType> sizes() const
+  EIGEN_DEVICE_FUNC inline const CwiseBinaryOp< internal::scalar_difference_op<Scalar,Scalar>, const VectorType, const VectorType> sizes() const
   { return m_max - m_min; }
 
   /** \returns the volume of the bounding box */
-  inline Scalar volume() const
+  EIGEN_DEVICE_FUNC inline Scalar volume() const
   { return sizes().prod(); }
 
   /** \returns an expression for the bounding box diagonal vector
     * if the length of the diagonal is needed: diagonal().norm()
     * will provide it.
     */
-  inline CwiseBinaryOp< internal::scalar_difference_op<Scalar>, const VectorType, const VectorType> diagonal() const
+  EIGEN_DEVICE_FUNC inline CwiseBinaryOp< internal::scalar_difference_op<Scalar,Scalar>, const VectorType, const VectorType> diagonal() const
   { return sizes(); }
 
   /** \returns the vertex of the bounding box at the corner defined by
     * the corner-id corner. It works only for a 1D, 2D or 3D bounding box.
     * For 1D bounding boxes corners are named by 2 enum constants:
@@ -137,11 +141,11 @@
     * For 2D bounding boxes, corners are named by 4 enum constants:
     * BottomLeft, BottomRight, TopLeft, TopRight.
     * For 3D bounding boxes, the following names are added:
     * BottomLeftCeil, BottomRightCeil, TopLeftCeil, TopRightCeil.
     */
-  inline VectorType corner(CornerType corner) const
+  EIGEN_DEVICE_FUNC inline VectorType corner(CornerType corner) const
   {
     EIGEN_STATIC_ASSERT(_AmbientDim <= 3, THIS_METHOD_IS_ONLY_FOR_VECTORS_OF_A_SPECIFIC_SIZE);
 
     VectorType res;
 
@@ -155,13 +159,13 @@
     return res;
   }
 
   /** \returns a random point inside the bounding box sampled with
    * a uniform distribution */
-  inline VectorType sample() const
+  EIGEN_DEVICE_FUNC inline VectorType sample() const
   {
-    VectorType r;
+    VectorType r(dim());
     for(Index d=0; d<dim(); ++d)
     {
       if(!ScalarTraits::IsInteger)
       {
         r[d] = m_min[d] + (m_max[d]-m_min[d])
@@ -173,118 +177,131 @@
     return r;
   }
 
   /** \returns true if the point \a p is inside the box \c *this. */
   template<typename Derived>
-  inline bool contains(const MatrixBase<Derived>& a_p) const
+  EIGEN_DEVICE_FUNC inline bool contains(const MatrixBase<Derived>& p) const
   {
-    typename internal::nested<Derived,2>::type p(a_p.derived());
-    return (m_min.array()<=p.array()).all() && (p.array()<=m_max.array()).all();
+    typename internal::nested_eval<Derived,2>::type p_n(p.derived());
+    return (m_min.array()<=p_n.array()).all() && (p_n.array()<=m_max.array()).all();
   }
 
   /** \returns true if the box \a b is entirely inside the box \c *this. */
-  inline bool contains(const AlignedBox& b) const
+  EIGEN_DEVICE_FUNC inline bool contains(const AlignedBox& b) const
   { return (m_min.array()<=(b.min)().array()).all() && ((b.max)().array()<=m_max.array()).all(); }
 
-  /** Extends \c *this such that it contains the point \a p and returns a reference to \c *this. */
+  /** \returns true if the box \a b is intersecting the box \c *this.
+   * \sa intersection, clamp */
+  EIGEN_DEVICE_FUNC inline bool intersects(const AlignedBox& b) const
+  { return (m_min.array()<=(b.max)().array()).all() && ((b.min)().array()<=m_max.array()).all(); }
+
+  /** Extends \c *this such that it contains the point \a p and returns a reference to \c *this.
+   * \sa extend(const AlignedBox&) */
   template<typename Derived>
-  inline AlignedBox& extend(const MatrixBase<Derived>& a_p)
+  EIGEN_DEVICE_FUNC inline AlignedBox& extend(const MatrixBase<Derived>& p)
   {
-    typename internal::nested<Derived,2>::type p(a_p.derived());
-    m_min = m_min.cwiseMin(p);
-    m_max = m_max.cwiseMax(p);
+    typename internal::nested_eval<Derived,2>::type p_n(p.derived());
+    m_min = m_min.cwiseMin(p_n);
+    m_max = m_max.cwiseMax(p_n);
     return *this;
   }
 
-  /** Extends \c *this such that it contains the box \a b and returns a reference to \c *this. */
-  inline AlignedBox& extend(const AlignedBox& b)
+  /** Extends \c *this such that it contains the box \a b and returns a reference to \c *this.
+   * \sa merged, extend(const MatrixBase&) */
+  EIGEN_DEVICE_FUNC inline AlignedBox& extend(const AlignedBox& b)
   {
     m_min = m_min.cwiseMin(b.m_min);
     m_max = m_max.cwiseMax(b.m_max);
     return *this;
   }
 
-  /** Clamps \c *this by the box \a b and returns a reference to \c *this. */
-  inline AlignedBox& clamp(const AlignedBox& b)
+  /** Clamps \c *this by the box \a b and returns a reference to \c *this.
+   * \note If the boxes don't intersect, the resulting box is empty.
+   * \sa intersection(), intersects() */
+  EIGEN_DEVICE_FUNC inline AlignedBox& clamp(const AlignedBox& b)
   {
     m_min = m_min.cwiseMax(b.m_min);
     m_max = m_max.cwiseMin(b.m_max);
     return *this;
   }
 
-  /** Returns an AlignedBox that is the intersection of \a b and \c *this */
-  inline AlignedBox intersection(const AlignedBox& b) const
+  /** Returns an AlignedBox that is the intersection of \a b and \c *this
+   * \note If the boxes don't intersect, the resulting box is empty.
+   * \sa intersects(), clamp, contains()  */
+  EIGEN_DEVICE_FUNC inline AlignedBox intersection(const AlignedBox& b) const
   {return AlignedBox(m_min.cwiseMax(b.m_min), m_max.cwiseMin(b.m_max)); }
 
-  /** Returns an AlignedBox that is the union of \a b and \c *this */
-  inline AlignedBox merged(const AlignedBox& b) const
+  /** Returns an AlignedBox that is the union of \a b and \c *this.
+   * \note Merging with an empty box may result in a box bigger than \c *this. 
+   * \sa extend(const AlignedBox&) */
+  EIGEN_DEVICE_FUNC inline AlignedBox merged(const AlignedBox& b) const
   { return AlignedBox(m_min.cwiseMin(b.m_min), m_max.cwiseMax(b.m_max)); }
 
   /** Translate \c *this by the vector \a t and returns a reference to \c *this. */
   template<typename Derived>
-  inline AlignedBox& translate(const MatrixBase<Derived>& a_t)
+  EIGEN_DEVICE_FUNC inline AlignedBox& translate(const MatrixBase<Derived>& a_t)
   {
-    const typename internal::nested<Derived,2>::type t(a_t.derived());
+    const typename internal::nested_eval<Derived,2>::type t(a_t.derived());
     m_min += t;
     m_max += t;
     return *this;
   }
 
   /** \returns the squared distance between the point \a p and the box \c *this,
     * and zero if \a p is inside the box.
-    * \sa exteriorDistance()
+    * \sa exteriorDistance(const MatrixBase&), squaredExteriorDistance(const AlignedBox&)
     */
   template<typename Derived>
-  inline Scalar squaredExteriorDistance(const MatrixBase<Derived>& a_p) const;
+  EIGEN_DEVICE_FUNC inline Scalar squaredExteriorDistance(const MatrixBase<Derived>& p) const;
 
   /** \returns the squared distance between the boxes \a b and \c *this,
     * and zero if the boxes intersect.
-    * \sa exteriorDistance()
+    * \sa exteriorDistance(const AlignedBox&), squaredExteriorDistance(const MatrixBase&)
     */
-  inline Scalar squaredExteriorDistance(const AlignedBox& b) const;
+  EIGEN_DEVICE_FUNC inline Scalar squaredExteriorDistance(const AlignedBox& b) const;
 
   /** \returns the distance between the point \a p and the box \c *this,
     * and zero if \a p is inside the box.
-    * \sa squaredExteriorDistance()
+    * \sa squaredExteriorDistance(const MatrixBase&), exteriorDistance(const AlignedBox&)
     */
   template<typename Derived>
-  inline NonInteger exteriorDistance(const MatrixBase<Derived>& p) const
-  { using std::sqrt; return sqrt(NonInteger(squaredExteriorDistance(p))); }
+  EIGEN_DEVICE_FUNC inline NonInteger exteriorDistance(const MatrixBase<Derived>& p) const
+  { EIGEN_USING_STD_MATH(sqrt) return sqrt(NonInteger(squaredExteriorDistance(p))); }
 
   /** \returns the distance between the boxes \a b and \c *this,
     * and zero if the boxes intersect.
-    * \sa squaredExteriorDistance()
+    * \sa squaredExteriorDistance(const AlignedBox&), exteriorDistance(const MatrixBase&)
     */
-  inline NonInteger exteriorDistance(const AlignedBox& b) const
-  { using std::sqrt; return sqrt(NonInteger(squaredExteriorDistance(b))); }
+  EIGEN_DEVICE_FUNC inline NonInteger exteriorDistance(const AlignedBox& b) const
+  { EIGEN_USING_STD_MATH(sqrt) return sqrt(NonInteger(squaredExteriorDistance(b))); }
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
     *
     * Note that if \a NewScalarType is equal to the current scalar type of \c *this
     * then this function smartly returns a const reference to \c *this.
     */
   template<typename NewScalarType>
-  inline typename internal::cast_return_type<AlignedBox,
+  EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<AlignedBox,
            AlignedBox<NewScalarType,AmbientDimAtCompileTime> >::type cast() const
   {
     return typename internal::cast_return_type<AlignedBox,
                     AlignedBox<NewScalarType,AmbientDimAtCompileTime> >::type(*this);
   }
 
   /** Copy constructor with scalar type conversion */
   template<typename OtherScalarType>
-  inline explicit AlignedBox(const AlignedBox<OtherScalarType,AmbientDimAtCompileTime>& other)
+  EIGEN_DEVICE_FUNC inline explicit AlignedBox(const AlignedBox<OtherScalarType,AmbientDimAtCompileTime>& other)
   {
     m_min = (other.min)().template cast<Scalar>();
     m_max = (other.max)().template cast<Scalar>();
   }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const AlignedBox& other, const RealScalar& prec = ScalarTraits::dummy_precision()) const
+  EIGEN_DEVICE_FUNC bool isApprox(const AlignedBox& other, const RealScalar& prec = ScalarTraits::dummy_precision()) const
   { return m_min.isApprox(other.m_min, prec) && m_max.isApprox(other.m_max, prec); }
 
 protected:
 
   VectorType m_min, m_max;
@@ -292,13 +309,13 @@
 
 
 
 template<typename Scalar,int AmbientDim>
 template<typename Derived>
-inline Scalar AlignedBox<Scalar,AmbientDim>::squaredExteriorDistance(const MatrixBase<Derived>& a_p) const
+EIGEN_DEVICE_FUNC inline Scalar AlignedBox<Scalar,AmbientDim>::squaredExteriorDistance(const MatrixBase<Derived>& a_p) const
 {
-  typename internal::nested<Derived,2*AmbientDim>::type p(a_p.derived());
+  typename internal::nested_eval<Derived,2*AmbientDim>::type p(a_p.derived());
   Scalar dist2(0);
   Scalar aux;
   for (Index k=0; k<dim(); ++k)
   {
     if( m_min[k] > p[k] )
@@ -314,11 +331,11 @@
   }
   return dist2;
 }
 
 template<typename Scalar,int AmbientDim>
-inline Scalar AlignedBox<Scalar,AmbientDim>::squaredExteriorDistance(const AlignedBox& b) const
+EIGEN_DEVICE_FUNC inline Scalar AlignedBox<Scalar,AmbientDim>::squaredExteriorDistance(const AlignedBox& b) const
 {
   Scalar dist2(0);
   Scalar aux;
   for (Index k=0; k<dim(); ++k)
   {

Index: 3rd_party/eigen/Eigen/src/Geometry/AngleAxis.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/AngleAxis.h
+++ 3rd_party/eigen/Eigen/src/Geometry/AngleAxis.h
@@ -67,79 +67,90 @@
   Scalar m_angle;
 
 public:
 
   /** Default constructor without initialization. */
-  AngleAxis() {}
+  EIGEN_DEVICE_FUNC AngleAxis() {}
   /** Constructs and initialize the angle-axis rotation from an \a angle in radian
     * and an \a axis which \b must \b be \b normalized.
     *
     * \warning If the \a axis vector is not normalized, then the angle-axis object
     *          represents an invalid rotation. */
   template<typename Derived>
+  EIGEN_DEVICE_FUNC 
   inline AngleAxis(const Scalar& angle, const MatrixBase<Derived>& axis) : m_axis(axis), m_angle(angle) {}
-  /** Constructs and initialize the angle-axis rotation from a quaternion \a q. */
-  template<typename QuatDerived> inline explicit AngleAxis(const QuaternionBase<QuatDerived>& q) { *this = q; }
+  /** Constructs and initialize the angle-axis rotation from a quaternion \a q.
+    * This function implicitly normalizes the quaternion \a q.
+    */
+  template<typename QuatDerived> 
+  EIGEN_DEVICE_FUNC inline explicit AngleAxis(const QuaternionBase<QuatDerived>& q) { *this = q; }
   /** Constructs and initialize the angle-axis rotation from a 3x3 rotation matrix. */
   template<typename Derived>
-  inline explicit AngleAxis(const MatrixBase<Derived>& m) { *this = m; }
+  EIGEN_DEVICE_FUNC inline explicit AngleAxis(const MatrixBase<Derived>& m) { *this = m; }
 
-  Scalar angle() const { return m_angle; }
-  Scalar& angle() { return m_angle; }
+  /** \returns the value of the rotation angle in radian */
+  EIGEN_DEVICE_FUNC Scalar angle() const { return m_angle; }
+  /** \returns a read-write reference to the stored angle in radian */
+  EIGEN_DEVICE_FUNC Scalar& angle() { return m_angle; }
 
-  const Vector3& axis() const { return m_axis; }
-  Vector3& axis() { return m_axis; }
+  /** \returns the rotation axis */
+  EIGEN_DEVICE_FUNC const Vector3& axis() const { return m_axis; }
+  /** \returns a read-write reference to the stored rotation axis.
+    *
+    * \warning The rotation axis must remain a \b unit vector.
+    */
+  EIGEN_DEVICE_FUNC Vector3& axis() { return m_axis; }
 
   /** Concatenates two rotations */
-  inline QuaternionType operator* (const AngleAxis& other) const
+  EIGEN_DEVICE_FUNC inline QuaternionType operator* (const AngleAxis& other) const
   { return QuaternionType(*this) * QuaternionType(other); }
 
   /** Concatenates two rotations */
-  inline QuaternionType operator* (const QuaternionType& other) const
+  EIGEN_DEVICE_FUNC inline QuaternionType operator* (const QuaternionType& other) const
   { return QuaternionType(*this) * other; }
 
   /** Concatenates two rotations */
-  friend inline QuaternionType operator* (const QuaternionType& a, const AngleAxis& b)
+  friend EIGEN_DEVICE_FUNC inline QuaternionType operator* (const QuaternionType& a, const AngleAxis& b)
   { return a * QuaternionType(b); }
 
   /** \returns the inverse rotation, i.e., an angle-axis with opposite rotation angle */
-  AngleAxis inverse() const
+  EIGEN_DEVICE_FUNC AngleAxis inverse() const
   { return AngleAxis(-m_angle, m_axis); }
 
   template<class QuatDerived>
-  AngleAxis& operator=(const QuaternionBase<QuatDerived>& q);
+  EIGEN_DEVICE_FUNC AngleAxis& operator=(const QuaternionBase<QuatDerived>& q);
   template<typename Derived>
-  AngleAxis& operator=(const MatrixBase<Derived>& m);
+  EIGEN_DEVICE_FUNC AngleAxis& operator=(const MatrixBase<Derived>& m);
 
   template<typename Derived>
-  AngleAxis& fromRotationMatrix(const MatrixBase<Derived>& m);
-  Matrix3 toRotationMatrix(void) const;
+  EIGEN_DEVICE_FUNC AngleAxis& fromRotationMatrix(const MatrixBase<Derived>& m);
+  EIGEN_DEVICE_FUNC Matrix3 toRotationMatrix(void) const;
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
     *
     * Note that if \a NewScalarType is equal to the current scalar type of \c *this
     * then this function smartly returns a const reference to \c *this.
     */
   template<typename NewScalarType>
-  inline typename internal::cast_return_type<AngleAxis,AngleAxis<NewScalarType> >::type cast() const
+  EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<AngleAxis,AngleAxis<NewScalarType> >::type cast() const
   { return typename internal::cast_return_type<AngleAxis,AngleAxis<NewScalarType> >::type(*this); }
 
   /** Copy constructor with scalar type conversion */
   template<typename OtherScalarType>
-  inline explicit AngleAxis(const AngleAxis<OtherScalarType>& other)
+  EIGEN_DEVICE_FUNC inline explicit AngleAxis(const AngleAxis<OtherScalarType>& other)
   {
     m_axis = other.axis().template cast<Scalar>();
     m_angle = Scalar(other.angle());
   }
 
-  static inline const AngleAxis Identity() { return AngleAxis(0, Vector3::UnitX()); }
+  EIGEN_DEVICE_FUNC static inline const AngleAxis Identity() { return AngleAxis(Scalar(0), Vector3::UnitX()); }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const AngleAxis& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
+  EIGEN_DEVICE_FUNC bool isApprox(const AngleAxis& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return m_axis.isApprox(other.m_axis, prec) && internal::isApprox(m_angle,other.m_angle, prec); }
 };
 
 /** \ingroup Geometry_Module
   * single precision angle-axis type */
@@ -147,42 +158,45 @@
 /** \ingroup Geometry_Module
   * double precision angle-axis type */
 typedef AngleAxis<double> AngleAxisd;
 
 /** Set \c *this from a \b unit quaternion.
-  * The axis is normalized.
+  *
+  * The resulting axis is normalized, and the computed angle is in the [0,pi] range.
   * 
-  * \warning As any other method dealing with quaternion, if the input quaternion
-  *          is not normalized then the result is undefined.
+  * This function implicitly normalizes the quaternion \a q.
   */
 template<typename Scalar>
 template<typename QuatDerived>
-AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const QuaternionBase<QuatDerived>& q)
-{
-  using std::acos;
-  using std::min;
-  using std::max;
-  using std::sqrt;
-  Scalar n2 = q.vec().squaredNorm();
-  if (n2 < NumTraits<Scalar>::dummy_precision()*NumTraits<Scalar>::dummy_precision())
-  {
-    m_angle = 0;
-    m_axis << 1, 0, 0;
+EIGEN_DEVICE_FUNC AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const QuaternionBase<QuatDerived>& q)
+{
+  EIGEN_USING_STD_MATH(atan2)
+  EIGEN_USING_STD_MATH(abs)
+  Scalar n = q.vec().norm();
+  if(n<NumTraits<Scalar>::epsilon())
+    n = q.vec().stableNorm();
+
+  if (n != Scalar(0))
+  {
+    m_angle = Scalar(2)*atan2(n, abs(q.w()));
+    if(q.w() < 0)
+      n = -n;
+    m_axis  = q.vec() / n;
   }
   else
   {
-    m_angle = Scalar(2)*acos((min)((max)(Scalar(-1),q.w()),Scalar(1)));
-    m_axis = q.vec() / sqrt(n2);
+    m_angle = Scalar(0);
+    m_axis << Scalar(1), Scalar(0), Scalar(0);
   }
   return *this;
 }
 
 /** Set \c *this from a 3x3 rotation matrix \a mat.
   */
 template<typename Scalar>
 template<typename Derived>
-AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const MatrixBase<Derived>& mat)
+EIGEN_DEVICE_FUNC AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const MatrixBase<Derived>& mat)
 {
   // Since a direct conversion would not be really faster,
   // let's use the robust Quaternion implementation:
   return *this = QuaternionType(mat);
 }
@@ -190,23 +204,23 @@
 /**
 * \brief Sets \c *this from a 3x3 rotation matrix.
 **/
 template<typename Scalar>
 template<typename Derived>
-AngleAxis<Scalar>& AngleAxis<Scalar>::fromRotationMatrix(const MatrixBase<Derived>& mat)
+EIGEN_DEVICE_FUNC AngleAxis<Scalar>& AngleAxis<Scalar>::fromRotationMatrix(const MatrixBase<Derived>& mat)
 {
   return *this = QuaternionType(mat);
 }
 
 /** Constructs and \returns an equivalent 3x3 rotation matrix.
   */
 template<typename Scalar>
 typename AngleAxis<Scalar>::Matrix3
-AngleAxis<Scalar>::toRotationMatrix(void) const
+EIGEN_DEVICE_FUNC AngleAxis<Scalar>::toRotationMatrix(void) const
 {
-  using std::sin;
-  using std::cos;
+  EIGEN_USING_STD_MATH(sin)
+  EIGEN_USING_STD_MATH(cos)
   Matrix3 res;
   Vector3 sin_axis  = sin(m_angle) * m_axis;
   Scalar c = cos(m_angle);
   Vector3 cos1_axis = (Scalar(1)-c) * m_axis;
 

DELETED 3rd_party/eigen/Eigen/src/Geometry/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Geometry/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Geometry/CMakeLists.txt
@@ -1,8 +0,0 @@
-FILE(GLOB Eigen_Geometry_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Geometry_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Geometry COMPONENT Devel
-  )
-
-ADD_SUBDIRECTORY(arch)

Index: 3rd_party/eigen/Eigen/src/Geometry/EulerAngles.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/EulerAngles.h
+++ 3rd_party/eigen/Eigen/src/Geometry/EulerAngles.h
@@ -31,16 +31,16 @@
   * The returned angles are in the ranges [0:pi]x[-pi:pi]x[-pi:pi].
   * 
   * \sa class AngleAxis
   */
 template<typename Derived>
-inline Matrix<typename MatrixBase<Derived>::Scalar,3,1>
+EIGEN_DEVICE_FUNC inline Matrix<typename MatrixBase<Derived>::Scalar,3,1>
 MatrixBase<Derived>::eulerAngles(Index a0, Index a1, Index a2) const
 {
-  using std::atan2;
-  using std::sin;
-  using std::cos;
+  EIGEN_USING_STD_MATH(atan2)
+  EIGEN_USING_STD_MATH(sin)
+  EIGEN_USING_STD_MATH(cos)
   /* Implemented from Graphics Gems IV */
   EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(Derived,3,3)
 
   Matrix<Scalar,3,1> res;
   typedef Matrix<typename Derived::Scalar,2,1> Vector2;
@@ -53,11 +53,16 @@
   if (a0==a2)
   {
     res[0] = atan2(coeff(j,i), coeff(k,i));
     if((odd && res[0]<Scalar(0)) || ((!odd) && res[0]>Scalar(0)))
     {
-      res[0] = (res[0] > Scalar(0)) ? res[0] - Scalar(M_PI) : res[0] + Scalar(M_PI);
+      if(res[0] > Scalar(0)) {
+        res[0] -= Scalar(EIGEN_PI);
+      }
+      else {
+        res[0] += Scalar(EIGEN_PI);
+      }
       Scalar s2 = Vector2(coeff(j,i), coeff(k,i)).norm();
       res[1] = -atan2(s2, coeff(i,i));
     }
     else
     {
@@ -82,11 +87,16 @@
   else
   {
     res[0] = atan2(coeff(j,k), coeff(k,k));
     Scalar c2 = Vector2(coeff(i,i), coeff(i,j)).norm();
     if((odd && res[0]<Scalar(0)) || ((!odd) && res[0]>Scalar(0))) {
-      res[0] = (res[0] > Scalar(0)) ? res[0] - Scalar(M_PI) : res[0] + Scalar(M_PI);
+      if(res[0] > Scalar(0)) {
+        res[0] -= Scalar(EIGEN_PI);
+      }
+      else {
+        res[0] += Scalar(EIGEN_PI);
+      }
       res[1] = atan2(-coeff(i,k), -c2);
     }
     else
       res[1] = atan2(-coeff(i,k), c2);
     Scalar s1 = sin(res[0]);

Index: 3rd_party/eigen/Eigen/src/Geometry/Homogeneous.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/Homogeneous.h
+++ 3rd_party/eigen/Eigen/src/Geometry/Homogeneous.h
@@ -32,11 +32,11 @@
 template<typename MatrixType,int Direction>
 struct traits<Homogeneous<MatrixType,Direction> >
  : traits<MatrixType>
 {
   typedef typename traits<MatrixType>::StorageKind StorageKind;
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
   typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
     RowsPlusOne = (MatrixType::RowsAtCompileTime != Dynamic) ?
                   int(MatrixType::RowsAtCompileTime) + 1 : Dynamic,
     ColsPlusOne = (MatrixType::ColsAtCompileTime != Dynamic) ?
@@ -46,135 +46,155 @@
     MaxRowsAtCompileTime = RowsAtCompileTime,
     MaxColsAtCompileTime = ColsAtCompileTime,
     TmpFlags = _MatrixTypeNested::Flags & HereditaryBits,
     Flags = ColsAtCompileTime==1 ? (TmpFlags & ~RowMajorBit)
           : RowsAtCompileTime==1 ? (TmpFlags | RowMajorBit)
-          : TmpFlags,
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost
+          : TmpFlags
   };
 };
 
 template<typename MatrixType,typename Lhs> struct homogeneous_left_product_impl;
 template<typename MatrixType,typename Rhs> struct homogeneous_right_product_impl;
 
 } // end namespace internal
 
 template<typename MatrixType,int _Direction> class Homogeneous
-  : internal::no_assignment_operator, public MatrixBase<Homogeneous<MatrixType,_Direction> >
+  : public MatrixBase<Homogeneous<MatrixType,_Direction> >, internal::no_assignment_operator
 {
   public:
 
+    typedef MatrixType NestedExpression;
     enum { Direction = _Direction };
 
     typedef MatrixBase<Homogeneous> Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Homogeneous)
 
-    inline Homogeneous(const MatrixType& matrix)
+    EIGEN_DEVICE_FUNC explicit inline Homogeneous(const MatrixType& matrix)
       : m_matrix(matrix)
     {}
 
-    inline Index rows() const { return m_matrix.rows() + (int(Direction)==Vertical   ? 1 : 0); }
-    inline Index cols() const { return m_matrix.cols() + (int(Direction)==Horizontal ? 1 : 0); }
-
-    inline Scalar coeff(Index row, Index col) const
-    {
-      if(  (int(Direction)==Vertical   && row==m_matrix.rows())
-        || (int(Direction)==Horizontal && col==m_matrix.cols()))
-        return 1;
-      return m_matrix.coeff(row, col);
-    }
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.rows() + (int(Direction)==Vertical   ? 1 : 0); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.cols() + (int(Direction)==Horizontal ? 1 : 0); }
+    
+    EIGEN_DEVICE_FUNC const NestedExpression& nestedExpression() const { return m_matrix; }
 
     template<typename Rhs>
-    inline const internal::homogeneous_right_product_impl<Homogeneous,Rhs>
+    EIGEN_DEVICE_FUNC inline const Product<Homogeneous,Rhs>
     operator* (const MatrixBase<Rhs>& rhs) const
     {
       eigen_assert(int(Direction)==Horizontal);
-      return internal::homogeneous_right_product_impl<Homogeneous,Rhs>(m_matrix,rhs.derived());
+      return Product<Homogeneous,Rhs>(*this,rhs.derived());
     }
 
     template<typename Lhs> friend
-    inline const internal::homogeneous_left_product_impl<Homogeneous,Lhs>
+    EIGEN_DEVICE_FUNC inline const Product<Lhs,Homogeneous>
     operator* (const MatrixBase<Lhs>& lhs, const Homogeneous& rhs)
     {
       eigen_assert(int(Direction)==Vertical);
-      return internal::homogeneous_left_product_impl<Homogeneous,Lhs>(lhs.derived(),rhs.m_matrix);
+      return Product<Lhs,Homogeneous>(lhs.derived(),rhs);
     }
 
     template<typename Scalar, int Dim, int Mode, int Options> friend
-    inline const internal::homogeneous_left_product_impl<Homogeneous,Transform<Scalar,Dim,Mode,Options> >
+    EIGEN_DEVICE_FUNC inline const Product<Transform<Scalar,Dim,Mode,Options>, Homogeneous >
     operator* (const Transform<Scalar,Dim,Mode,Options>& lhs, const Homogeneous& rhs)
     {
       eigen_assert(int(Direction)==Vertical);
-      return internal::homogeneous_left_product_impl<Homogeneous,Transform<Scalar,Dim,Mode,Options> >(lhs,rhs.m_matrix);
+      return Product<Transform<Scalar,Dim,Mode,Options>, Homogeneous>(lhs,rhs);
+    }
+
+    template<typename Func>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::result_of<Func(Scalar,Scalar)>::type
+    redux(const Func& func) const
+    {
+      return func(m_matrix.redux(func), Scalar(1));
     }
 
   protected:
     typename MatrixType::Nested m_matrix;
 };
 
-/** \geometry_module
+/** \geometry_module \ingroup Geometry_Module
+  *
+  * \returns a vector expression that is one longer than the vector argument, with the value 1 symbolically appended as the last coefficient.
   *
-  * \return an expression of the equivalent homogeneous vector
+  * This can be used to convert affine coordinates to homogeneous coordinates.
   *
   * \only_for_vectors
   *
   * Example: \include MatrixBase_homogeneous.cpp
   * Output: \verbinclude MatrixBase_homogeneous.out
   *
-  * \sa class Homogeneous
+  * \sa VectorwiseOp::homogeneous(), class Homogeneous
   */
 template<typename Derived>
-inline typename MatrixBase<Derived>::HomogeneousReturnType
+EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::HomogeneousReturnType
 MatrixBase<Derived>::homogeneous() const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
-  return derived();
+  return HomogeneousReturnType(derived());
 }
 
-/** \geometry_module
+/** \geometry_module \ingroup Geometry_Module
+  *
+  * \returns an expression where the value 1 is symbolically appended as the final coefficient to each column (or row) of the matrix.
   *
-  * \returns a matrix expression of homogeneous column (or row) vectors
+  * This can be used to convert affine coordinates to homogeneous coordinates.
   *
   * Example: \include VectorwiseOp_homogeneous.cpp
   * Output: \verbinclude VectorwiseOp_homogeneous.out
   *
-  * \sa MatrixBase::homogeneous() */
+  * \sa MatrixBase::homogeneous(), class Homogeneous */
 template<typename ExpressionType, int Direction>
-inline Homogeneous<ExpressionType,Direction>
+EIGEN_DEVICE_FUNC inline Homogeneous<ExpressionType,Direction>
 VectorwiseOp<ExpressionType,Direction>::homogeneous() const
 {
-  return _expression();
+  return HomogeneousReturnType(_expression());
 }
 
-/** \geometry_module
+/** \geometry_module \ingroup Geometry_Module
+  *
+  * \brief homogeneous normalization
+  *
+  * \returns a vector expression of the N-1 first coefficients of \c *this divided by that last coefficient.
+  *
+  * This can be used to convert homogeneous coordinates to affine coordinates.
   *
-  * \returns an expression of the homogeneous normalized vector of \c *this
+  * It is essentially a shortcut for:
+  * \code
+    this->head(this->size()-1)/this->coeff(this->size()-1);
+    \endcode
   *
   * Example: \include MatrixBase_hnormalized.cpp
   * Output: \verbinclude MatrixBase_hnormalized.out
   *
   * \sa VectorwiseOp::hnormalized() */
 template<typename Derived>
-inline const typename MatrixBase<Derived>::HNormalizedReturnType
+EIGEN_DEVICE_FUNC inline const typename MatrixBase<Derived>::HNormalizedReturnType
 MatrixBase<Derived>::hnormalized() const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
   return ConstStartMinusOne(derived(),0,0,
     ColsAtCompileTime==1?size()-1:1,
     ColsAtCompileTime==1?1:size()-1) / coeff(size()-1);
 }
 
-/** \geometry_module
+/** \geometry_module \ingroup Geometry_Module
+  *
+  * \brief column or row-wise homogeneous normalization
+  *
+  * \returns an expression of the first N-1 coefficients of each column (or row) of \c *this divided by the last coefficient of each column (or row).
+  *
+  * This can be used to convert homogeneous coordinates to affine coordinates.
   *
-  * \returns an expression of the homogeneous normalized vector of \c *this
+  * It is conceptually equivalent to calling MatrixBase::hnormalized() to each column (or row) of \c *this.
   *
   * Example: \include DirectionWise_hnormalized.cpp
   * Output: \verbinclude DirectionWise_hnormalized.out
   *
   * \sa MatrixBase::hnormalized() */
 template<typename ExpressionType, int Direction>
-inline const typename VectorwiseOp<ExpressionType,Direction>::HNormalizedReturnType
+EIGEN_DEVICE_FUNC inline const typename VectorwiseOp<ExpressionType,Direction>::HNormalizedReturnType
 VectorwiseOp<ExpressionType,Direction>::hnormalized() const
 {
   return HNormalized_Block(_expression(),0,0,
       Direction==Vertical   ? _expression().rows()-1 : _expression().rows(),
       Direction==Horizontal ? _expression().cols()-1 : _expression().cols()).cwiseQuotient(
@@ -194,27 +214,27 @@
 
 template<typename MatrixOrTransformType>
 struct take_matrix_for_product
 {
   typedef MatrixOrTransformType type;
-  static const type& run(const type &x) { return x; }
+  EIGEN_DEVICE_FUNC static const type& run(const type &x) { return x; }
 };
 
 template<typename Scalar, int Dim, int Mode,int Options>
 struct take_matrix_for_product<Transform<Scalar, Dim, Mode, Options> >
 {
   typedef Transform<Scalar, Dim, Mode, Options> TransformType;
   typedef typename internal::add_const<typename TransformType::ConstAffinePart>::type type;
-  static type run (const TransformType& x) { return x.affine(); }
+  EIGEN_DEVICE_FUNC static type run (const TransformType& x) { return x.affine(); }
 };
 
 template<typename Scalar, int Dim, int Options>
 struct take_matrix_for_product<Transform<Scalar, Dim, Projective, Options> >
 {
   typedef Transform<Scalar, Dim, Projective, Options> TransformType;
   typedef typename TransformType::MatrixType type;
-  static const type& run (const TransformType& x) { return x.matrix(); }
+  EIGEN_DEVICE_FUNC static const type& run (const TransformType& x) { return x.matrix(); }
 };
 
 template<typename MatrixType,typename Lhs>
 struct traits<homogeneous_left_product_impl<Homogeneous<MatrixType,Vertical>,Lhs> >
 {
@@ -235,20 +255,19 @@
   : public ReturnByValue<homogeneous_left_product_impl<Homogeneous<MatrixType,Vertical>,Lhs> >
 {
   typedef typename traits<homogeneous_left_product_impl>::LhsMatrixType LhsMatrixType;
   typedef typename remove_all<LhsMatrixType>::type LhsMatrixTypeCleaned;
   typedef typename remove_all<typename LhsMatrixTypeCleaned::Nested>::type LhsMatrixTypeNested;
-  typedef typename MatrixType::Index Index;
-  homogeneous_left_product_impl(const Lhs& lhs, const MatrixType& rhs)
+  EIGEN_DEVICE_FUNC homogeneous_left_product_impl(const Lhs& lhs, const MatrixType& rhs)
     : m_lhs(take_matrix_for_product<Lhs>::run(lhs)),
       m_rhs(rhs)
   {}
 
-  inline Index rows() const { return m_lhs.rows(); }
-  inline Index cols() const { return m_rhs.cols(); }
+  EIGEN_DEVICE_FUNC inline Index rows() const { return m_lhs.rows(); }
+  EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); }
 
-  template<typename Dest> void evalTo(Dest& dst) const
+  template<typename Dest> EIGEN_DEVICE_FUNC void evalTo(Dest& dst) const
   {
     // FIXME investigate how to allow lazy evaluation of this product when possible
     dst = Block<const LhsMatrixTypeNested,
               LhsMatrixTypeNested::RowsAtCompileTime,
               LhsMatrixTypeNested::ColsAtCompileTime==Dynamic?Dynamic:LhsMatrixTypeNested::ColsAtCompileTime-1>
@@ -275,19 +294,18 @@
 template<typename MatrixType,typename Rhs>
 struct homogeneous_right_product_impl<Homogeneous<MatrixType,Horizontal>,Rhs>
   : public ReturnByValue<homogeneous_right_product_impl<Homogeneous<MatrixType,Horizontal>,Rhs> >
 {
   typedef typename remove_all<typename Rhs::Nested>::type RhsNested;
-  typedef typename MatrixType::Index Index;
-  homogeneous_right_product_impl(const MatrixType& lhs, const Rhs& rhs)
+  EIGEN_DEVICE_FUNC homogeneous_right_product_impl(const MatrixType& lhs, const Rhs& rhs)
     : m_lhs(lhs), m_rhs(rhs)
   {}
 
-  inline Index rows() const { return m_lhs.rows(); }
-  inline Index cols() const { return m_rhs.cols(); }
+  EIGEN_DEVICE_FUNC inline Index rows() const { return m_lhs.rows(); }
+  EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); }
 
-  template<typename Dest> void evalTo(Dest& dst) const
+  template<typename Dest> EIGEN_DEVICE_FUNC void evalTo(Dest& dst) const
   {
     // FIXME investigate how to allow lazy evaluation of this product when possible
     dst = m_lhs * Block<const RhsNested,
                         RhsNested::RowsAtCompileTime==Dynamic?Dynamic:RhsNested::RowsAtCompileTime-1,
                         RhsNested::ColsAtCompileTime>
@@ -297,11 +315,183 @@
   }
 
   typename MatrixType::Nested m_lhs;
   typename Rhs::Nested m_rhs;
 };
+
+template<typename ArgType,int Direction>
+struct evaluator_traits<Homogeneous<ArgType,Direction> >
+{
+  typedef typename storage_kind_to_evaluator_kind<typename ArgType::StorageKind>::Kind Kind;
+  typedef HomogeneousShape Shape;  
+};
+
+template<> struct AssignmentKind<DenseShape,HomogeneousShape> { typedef Dense2Dense Kind; };
+
+
+template<typename ArgType,int Direction>
+struct unary_evaluator<Homogeneous<ArgType,Direction>, IndexBased>
+  : evaluator<typename Homogeneous<ArgType,Direction>::PlainObject >
+{
+  typedef Homogeneous<ArgType,Direction> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  typedef evaluator<PlainObject> Base;
+
+  EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& op)
+    : Base(), m_temp(op)
+  {
+    ::new (static_cast<Base*>(this)) Base(m_temp);
+  }
+
+protected:
+  PlainObject m_temp;
+};
+
+// dense = homogeneous
+template< typename DstXprType, typename ArgType, typename Scalar>
+struct Assignment<DstXprType, Homogeneous<ArgType,Vertical>, internal::assign_op<Scalar,typename ArgType::Scalar>, Dense2Dense>
+{
+  typedef Homogeneous<ArgType,Vertical> SrcXprType;
+  EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,typename ArgType::Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    dst.template topRows<ArgType::RowsAtCompileTime>(src.nestedExpression().rows()) = src.nestedExpression();
+    dst.row(dst.rows()-1).setOnes();
+  }
+};
+
+// dense = homogeneous
+template< typename DstXprType, typename ArgType, typename Scalar>
+struct Assignment<DstXprType, Homogeneous<ArgType,Horizontal>, internal::assign_op<Scalar,typename ArgType::Scalar>, Dense2Dense>
+{
+  typedef Homogeneous<ArgType,Horizontal> SrcXprType;
+  EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,typename ArgType::Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    dst.template leftCols<ArgType::ColsAtCompileTime>(src.nestedExpression().cols()) = src.nestedExpression();
+    dst.col(dst.cols()-1).setOnes();
+  }
+};
+
+template<typename LhsArg, typename Rhs, int ProductTag>
+struct generic_product_impl<Homogeneous<LhsArg,Horizontal>, Rhs, HomogeneousShape, DenseShape, ProductTag>
+{
+  template<typename Dest>
+  EIGEN_DEVICE_FUNC static void evalTo(Dest& dst, const Homogeneous<LhsArg,Horizontal>& lhs, const Rhs& rhs)
+  {
+    homogeneous_right_product_impl<Homogeneous<LhsArg,Horizontal>, Rhs>(lhs.nestedExpression(), rhs).evalTo(dst);
+  }
+};
+
+template<typename Lhs,typename Rhs>
+struct homogeneous_right_product_refactoring_helper
+{
+  enum {
+    Dim  = Lhs::ColsAtCompileTime,
+    Rows = Lhs::RowsAtCompileTime
+  };
+  typedef typename Rhs::template ConstNRowsBlockXpr<Dim>::Type          LinearBlockConst;
+  typedef typename remove_const<LinearBlockConst>::type                 LinearBlock;
+  typedef typename Rhs::ConstRowXpr                                     ConstantColumn;
+  typedef Replicate<const ConstantColumn,Rows,1>                        ConstantBlock;
+  typedef Product<Lhs,LinearBlock,LazyProduct>                          LinearProduct;
+  typedef CwiseBinaryOp<internal::scalar_sum_op<typename Lhs::Scalar,typename Rhs::Scalar>, const LinearProduct, const ConstantBlock> Xpr;
+};
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, HomogeneousShape, DenseShape>
+ : public evaluator<typename homogeneous_right_product_refactoring_helper<typename Lhs::NestedExpression,Rhs>::Xpr>
+{
+  typedef Product<Lhs, Rhs, LazyProduct> XprType;
+  typedef homogeneous_right_product_refactoring_helper<typename Lhs::NestedExpression,Rhs> helper;
+  typedef typename helper::ConstantBlock ConstantBlock;
+  typedef typename helper::Xpr RefactoredXpr;
+  typedef evaluator<RefactoredXpr> Base;
+  
+  EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
+    : Base(  xpr.lhs().nestedExpression() .lazyProduct(  xpr.rhs().template topRows<helper::Dim>(xpr.lhs().nestedExpression().cols()) )
+            + ConstantBlock(xpr.rhs().row(xpr.rhs().rows()-1),xpr.lhs().rows(), 1) )
+  {}
+};
+
+template<typename Lhs, typename RhsArg, int ProductTag>
+struct generic_product_impl<Lhs, Homogeneous<RhsArg,Vertical>, DenseShape, HomogeneousShape, ProductTag>
+{
+  template<typename Dest>
+  EIGEN_DEVICE_FUNC static void evalTo(Dest& dst, const Lhs& lhs, const Homogeneous<RhsArg,Vertical>& rhs)
+  {
+    homogeneous_left_product_impl<Homogeneous<RhsArg,Vertical>, Lhs>(lhs, rhs.nestedExpression()).evalTo(dst);
+  }
+};
+
+// TODO: the following specialization is to address a regression from 3.2 to 3.3
+// In the future, this path should be optimized.
+template<typename Lhs, typename RhsArg, int ProductTag>
+struct generic_product_impl<Lhs, Homogeneous<RhsArg,Vertical>, TriangularShape, HomogeneousShape, ProductTag>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Homogeneous<RhsArg,Vertical>& rhs)
+  {
+    dst.noalias() = lhs * rhs.eval();
+  }
+};
+
+template<typename Lhs,typename Rhs>
+struct homogeneous_left_product_refactoring_helper
+{
+  enum {
+    Dim = Rhs::RowsAtCompileTime,
+    Cols = Rhs::ColsAtCompileTime
+  };
+  typedef typename Lhs::template ConstNColsBlockXpr<Dim>::Type          LinearBlockConst;
+  typedef typename remove_const<LinearBlockConst>::type                 LinearBlock;
+  typedef typename Lhs::ConstColXpr                                     ConstantColumn;
+  typedef Replicate<const ConstantColumn,1,Cols>                        ConstantBlock;
+  typedef Product<LinearBlock,Rhs,LazyProduct>                          LinearProduct;
+  typedef CwiseBinaryOp<internal::scalar_sum_op<typename Lhs::Scalar,typename Rhs::Scalar>, const LinearProduct, const ConstantBlock> Xpr;
+};
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape, HomogeneousShape>
+ : public evaluator<typename homogeneous_left_product_refactoring_helper<Lhs,typename Rhs::NestedExpression>::Xpr>
+{
+  typedef Product<Lhs, Rhs, LazyProduct> XprType;
+  typedef homogeneous_left_product_refactoring_helper<Lhs,typename Rhs::NestedExpression> helper;
+  typedef typename helper::ConstantBlock ConstantBlock;
+  typedef typename helper::Xpr RefactoredXpr;
+  typedef evaluator<RefactoredXpr> Base;
+  
+  EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
+    : Base(   xpr.lhs().template leftCols<helper::Dim>(xpr.rhs().nestedExpression().rows()) .lazyProduct( xpr.rhs().nestedExpression() )
+            + ConstantBlock(xpr.lhs().col(xpr.lhs().cols()-1),1,xpr.rhs().cols()) )
+  {}
+};
+
+template<typename Scalar, int Dim, int Mode,int Options, typename RhsArg, int ProductTag>
+struct generic_product_impl<Transform<Scalar,Dim,Mode,Options>, Homogeneous<RhsArg,Vertical>, DenseShape, HomogeneousShape, ProductTag>
+{
+  typedef Transform<Scalar,Dim,Mode,Options> TransformType;
+  template<typename Dest>
+  EIGEN_DEVICE_FUNC static void evalTo(Dest& dst, const TransformType& lhs, const Homogeneous<RhsArg,Vertical>& rhs)
+  {
+    homogeneous_left_product_impl<Homogeneous<RhsArg,Vertical>, TransformType>(lhs, rhs.nestedExpression()).evalTo(dst);
+  }
+};
+
+template<typename ExpressionType, int Side, bool Transposed>
+struct permutation_matrix_product<ExpressionType, Side, Transposed, HomogeneousShape>
+  : public permutation_matrix_product<ExpressionType, Side, Transposed, DenseShape>
+{};
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_HOMOGENEOUS_H

Index: 3rd_party/eigen/Eigen/src/Geometry/Hyperplane.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/Hyperplane.h
+++ 3rd_party/eigen/Eigen/src/Geometry/Hyperplane.h
@@ -20,12 +20,12 @@
   * \brief A hyperplane
   *
   * A hyperplane is an affine subspace of dimension n-1 in a space of dimension n.
   * For example, a hyperplane in a plane is a line; a hyperplane in 3-space is a plane.
   *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
-  * \param _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
+  * \tparam _Scalar the scalar type, i.e., the type of the coefficients
+  * \tparam _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
   *             Notice that the dimension of the hyperplane is _AmbientDim-1.
   *
   * This class represents an hyperplane as the zero set of the implicit equation
   * \f$ n \cdot x + d = 0 \f$ where \f$ n \f$ is a unit normal vector of the plane (linear part)
   * and \f$ d \f$ is the distance (offset) to the origin.
@@ -39,34 +39,34 @@
     AmbientDimAtCompileTime = _AmbientDim,
     Options = _Options
   };
   typedef _Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef DenseIndex Index;
+  typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
   typedef Matrix<Scalar,AmbientDimAtCompileTime,1> VectorType;
   typedef Matrix<Scalar,Index(AmbientDimAtCompileTime)==Dynamic
                         ? Dynamic
                         : Index(AmbientDimAtCompileTime)+1,1,Options> Coefficients;
   typedef Block<Coefficients,AmbientDimAtCompileTime,1> NormalReturnType;
   typedef const Block<const Coefficients,AmbientDimAtCompileTime,1> ConstNormalReturnType;
 
   /** Default constructor without initialization */
-  inline Hyperplane() {}
+  EIGEN_DEVICE_FUNC inline Hyperplane() {}
   
   template<int OtherOptions>
-  Hyperplane(const Hyperplane<Scalar,AmbientDimAtCompileTime,OtherOptions>& other)
+  EIGEN_DEVICE_FUNC Hyperplane(const Hyperplane<Scalar,AmbientDimAtCompileTime,OtherOptions>& other)
    : m_coeffs(other.coeffs())
   {}
 
   /** Constructs a dynamic-size hyperplane with \a _dim the dimension
     * of the ambient space */
-  inline explicit Hyperplane(Index _dim) : m_coeffs(_dim+1) {}
+  EIGEN_DEVICE_FUNC inline explicit Hyperplane(Index _dim) : m_coeffs(_dim+1) {}
 
   /** Construct a plane from its normal \a n and a point \a e onto the plane.
     * \warning the vector normal is assumed to be normalized.
     */
-  inline Hyperplane(const VectorType& n, const VectorType& e)
+  EIGEN_DEVICE_FUNC inline Hyperplane(const VectorType& n, const VectorType& e)
     : m_coeffs(n.size()+1)
   {
     normal() = n;
     offset() = -n.dot(e);
   }
@@ -73,21 +73,21 @@
 
   /** Constructs a plane from its normal \a n and distance to the origin \a d
     * such that the algebraic equation of the plane is \f$ n \cdot x + d = 0 \f$.
     * \warning the vector normal is assumed to be normalized.
     */
-  inline Hyperplane(const VectorType& n, const Scalar& d)
+  EIGEN_DEVICE_FUNC inline Hyperplane(const VectorType& n, const Scalar& d)
     : m_coeffs(n.size()+1)
   {
     normal() = n;
     offset() = d;
   }
 
   /** Constructs a hyperplane passing through the two points. If the dimension of the ambient space
     * is greater than 2, then there isn't uniqueness, so an arbitrary choice is made.
     */
-  static inline Hyperplane Through(const VectorType& p0, const VectorType& p1)
+  EIGEN_DEVICE_FUNC static inline Hyperplane Through(const VectorType& p0, const VectorType& p1)
   {
     Hyperplane result(p0.size());
     result.normal() = (p1 - p0).unitOrthogonal();
     result.offset() = -p0.dot(result.normal());
     return result;
@@ -94,11 +94,11 @@
   }
 
   /** Constructs a hyperplane passing through the three points. The dimension of the ambient space
     * is required to be exactly 3.
     */
-  static inline Hyperplane Through(const VectorType& p0, const VectorType& p1, const VectorType& p2)
+  EIGEN_DEVICE_FUNC static inline Hyperplane Through(const VectorType& p0, const VectorType& p1, const VectorType& p2)
   {
     EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(VectorType, 3)
     Hyperplane result(p0.size());
     VectorType v0(p2 - p0), v1(p1 - p0);
     result.normal() = v0.cross(v1);
@@ -118,86 +118,85 @@
   /** Constructs a hyperplane passing through the parametrized line \a parametrized.
     * If the dimension of the ambient space is greater than 2, then there isn't uniqueness,
     * so an arbitrary choice is made.
     */
   // FIXME to be consitent with the rest this could be implemented as a static Through function ??
-  explicit Hyperplane(const ParametrizedLine<Scalar, AmbientDimAtCompileTime>& parametrized)
+  EIGEN_DEVICE_FUNC explicit Hyperplane(const ParametrizedLine<Scalar, AmbientDimAtCompileTime>& parametrized)
   {
     normal() = parametrized.direction().unitOrthogonal();
     offset() = -parametrized.origin().dot(normal());
   }
 
-  ~Hyperplane() {}
+  EIGEN_DEVICE_FUNC ~Hyperplane() {}
 
   /** \returns the dimension in which the plane holds */
-  inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_coeffs.size()-1 : Index(AmbientDimAtCompileTime); }
+  EIGEN_DEVICE_FUNC inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_coeffs.size()-1 : Index(AmbientDimAtCompileTime); }
 
   /** normalizes \c *this */
-  void normalize(void)
+  EIGEN_DEVICE_FUNC void normalize(void)
   {
     m_coeffs /= normal().norm();
   }
 
   /** \returns the signed distance between the plane \c *this and a point \a p.
     * \sa absDistance()
     */
-  inline Scalar signedDistance(const VectorType& p) const { return normal().dot(p) + offset(); }
+  EIGEN_DEVICE_FUNC inline Scalar signedDistance(const VectorType& p) const { return normal().dot(p) + offset(); }
 
   /** \returns the absolute distance between the plane \c *this and a point \a p.
     * \sa signedDistance()
     */
-  inline Scalar absDistance(const VectorType& p) const { using std::abs; return abs(signedDistance(p)); }
+  EIGEN_DEVICE_FUNC inline Scalar absDistance(const VectorType& p) const { return numext::abs(signedDistance(p)); }
 
   /** \returns the projection of a point \a p onto the plane \c *this.
     */
-  inline VectorType projection(const VectorType& p) const { return p - signedDistance(p) * normal(); }
+  EIGEN_DEVICE_FUNC inline VectorType projection(const VectorType& p) const { return p - signedDistance(p) * normal(); }
 
   /** \returns a constant reference to the unit normal vector of the plane, which corresponds
     * to the linear part of the implicit equation.
     */
-  inline ConstNormalReturnType normal() const { return ConstNormalReturnType(m_coeffs,0,0,dim(),1); }
+  EIGEN_DEVICE_FUNC inline ConstNormalReturnType normal() const { return ConstNormalReturnType(m_coeffs,0,0,dim(),1); }
 
   /** \returns a non-constant reference to the unit normal vector of the plane, which corresponds
     * to the linear part of the implicit equation.
     */
-  inline NormalReturnType normal() { return NormalReturnType(m_coeffs,0,0,dim(),1); }
+  EIGEN_DEVICE_FUNC inline NormalReturnType normal() { return NormalReturnType(m_coeffs,0,0,dim(),1); }
 
   /** \returns the distance to the origin, which is also the "constant term" of the implicit equation
     * \warning the vector normal is assumed to be normalized.
     */
-  inline const Scalar& offset() const { return m_coeffs.coeff(dim()); }
+  EIGEN_DEVICE_FUNC inline const Scalar& offset() const { return m_coeffs.coeff(dim()); }
 
   /** \returns a non-constant reference to the distance to the origin, which is also the constant part
     * of the implicit equation */
-  inline Scalar& offset() { return m_coeffs(dim()); }
+  EIGEN_DEVICE_FUNC inline Scalar& offset() { return m_coeffs(dim()); }
 
   /** \returns a constant reference to the coefficients c_i of the plane equation:
     * \f$ c_0*x_0 + ... + c_{d-1}*x_{d-1} + c_d = 0 \f$
     */
-  inline const Coefficients& coeffs() const { return m_coeffs; }
+  EIGEN_DEVICE_FUNC inline const Coefficients& coeffs() const { return m_coeffs; }
 
   /** \returns a non-constant reference to the coefficients c_i of the plane equation:
     * \f$ c_0*x_0 + ... + c_{d-1}*x_{d-1} + c_d = 0 \f$
     */
-  inline Coefficients& coeffs() { return m_coeffs; }
+  EIGEN_DEVICE_FUNC inline Coefficients& coeffs() { return m_coeffs; }
 
   /** \returns the intersection of *this with \a other.
     *
     * \warning The ambient space must be a plane, i.e. have dimension 2, so that \c *this and \a other are lines.
     *
     * \note If \a other is approximately parallel to *this, this method will return any point on *this.
     */
-  VectorType intersection(const Hyperplane& other) const
+  EIGEN_DEVICE_FUNC VectorType intersection(const Hyperplane& other) const
   {
-    using std::abs;
     EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(VectorType, 2)
     Scalar det = coeffs().coeff(0) * other.coeffs().coeff(1) - coeffs().coeff(1) * other.coeffs().coeff(0);
     // since the line equations ax+by=c are normalized with a^2+b^2=1, the following tests
     // whether the two lines are approximately parallel.
     if(internal::isMuchSmallerThan(det, Scalar(1)))
     {   // special case where the two lines are approximately parallel. Pick any point on the first line.
-        if(abs(coeffs().coeff(1))>abs(coeffs().coeff(0)))
+        if(numext::abs(coeffs().coeff(1))>numext::abs(coeffs().coeff(0)))
             return VectorType(coeffs().coeff(1), -coeffs().coeff(2)/coeffs().coeff(1)-coeffs().coeff(0));
         else
             return VectorType(-coeffs().coeff(2)/coeffs().coeff(0)-coeffs().coeff(1), coeffs().coeff(0));
     }
     else
@@ -213,14 +212,17 @@
     * \param mat the Dim x Dim transformation matrix
     * \param traits specifies whether the matrix \a mat represents an #Isometry
     *               or a more generic #Affine transformation. The default is #Affine.
     */
   template<typename XprType>
-  inline Hyperplane& transform(const MatrixBase<XprType>& mat, TransformTraits traits = Affine)
+  EIGEN_DEVICE_FUNC inline Hyperplane& transform(const MatrixBase<XprType>& mat, TransformTraits traits = Affine)
   {
     if (traits==Affine)
+    {
       normal() = mat.inverse().transpose() * normal();
+      m_coeffs /= normal().norm();
+    }
     else if (traits==Isometry)
       normal() = mat * normal();
     else
     {
       eigen_assert(0 && "invalid traits value in Hyperplane::transform()");
@@ -234,11 +236,11 @@
     * \param traits specifies whether the transformation \a t represents an #Isometry
     *               or a more generic #Affine transformation. The default is #Affine.
     *               Other kind of transformations are not supported.
     */
   template<int TrOptions>
-  inline Hyperplane& transform(const Transform<Scalar,AmbientDimAtCompileTime,Affine,TrOptions>& t,
+  EIGEN_DEVICE_FUNC inline Hyperplane& transform(const Transform<Scalar,AmbientDimAtCompileTime,Affine,TrOptions>& t,
                                 TransformTraits traits = Affine)
   {
     transform(t.linear(), traits);
     offset() -= normal().dot(t.translation());
     return *this;
@@ -248,28 +250,28 @@
     *
     * Note that if \a NewScalarType is equal to the current scalar type of \c *this
     * then this function smartly returns a const reference to \c *this.
     */
   template<typename NewScalarType>
-  inline typename internal::cast_return_type<Hyperplane,
+  EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<Hyperplane,
            Hyperplane<NewScalarType,AmbientDimAtCompileTime,Options> >::type cast() const
   {
     return typename internal::cast_return_type<Hyperplane,
                     Hyperplane<NewScalarType,AmbientDimAtCompileTime,Options> >::type(*this);
   }
 
   /** Copy constructor with scalar type conversion */
   template<typename OtherScalarType,int OtherOptions>
-  inline explicit Hyperplane(const Hyperplane<OtherScalarType,AmbientDimAtCompileTime,OtherOptions>& other)
+  EIGEN_DEVICE_FUNC inline explicit Hyperplane(const Hyperplane<OtherScalarType,AmbientDimAtCompileTime,OtherOptions>& other)
   { m_coeffs = other.coeffs().template cast<Scalar>(); }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
   template<int OtherOptions>
-  bool isApprox(const Hyperplane<Scalar,AmbientDimAtCompileTime,OtherOptions>& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
+  EIGEN_DEVICE_FUNC bool isApprox(const Hyperplane<Scalar,AmbientDimAtCompileTime,OtherOptions>& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return m_coeffs.isApprox(other.m_coeffs, prec); }
 
 protected:
 
   Coefficients m_coeffs;

Index: 3rd_party/eigen/Eigen/src/Geometry/OrthoMethods.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/OrthoMethods.h
+++ 3rd_party/eigen/Eigen/src/Geometry/OrthoMethods.h
@@ -11,29 +11,37 @@
 #ifndef EIGEN_ORTHOMETHODS_H
 #define EIGEN_ORTHOMETHODS_H
 
 namespace Eigen { 
 
-/** \geometry_module
+/** \geometry_module \ingroup Geometry_Module
   *
   * \returns the cross product of \c *this and \a other
   *
   * Here is a very good explanation of cross-product: http://xkcd.com/199/
+  * 
+  * With complex numbers, the cross product is implemented as
+  * \f$ (\mathbf{a}+i\mathbf{b}) \times (\mathbf{c}+i\mathbf{d}) = (\mathbf{a} \times \mathbf{c} - \mathbf{b} \times \mathbf{d}) - i(\mathbf{a} \times \mathbf{d} - \mathbf{b} \times \mathbf{c})\f$
+  * 
   * \sa MatrixBase::cross3()
   */
 template<typename Derived>
 template<typename OtherDerived>
-inline typename MatrixBase<Derived>::template cross_product_return_type<OtherDerived>::type
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::template cross_product_return_type<OtherDerived>::type
+#else
+inline typename MatrixBase<Derived>::PlainObject
+#endif
 MatrixBase<Derived>::cross(const MatrixBase<OtherDerived>& other) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Derived,3)
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,3)
 
   // Note that there is no need for an expression here since the compiler
   // optimize such a small temporary very well (even within a complex expression)
-  typename internal::nested<Derived,2>::type lhs(derived());
-  typename internal::nested<OtherDerived,2>::type rhs(other.derived());
+  typename internal::nested_eval<Derived,2>::type lhs(derived());
+  typename internal::nested_eval<OtherDerived,2>::type rhs(other.derived());
   return typename cross_product_return_type<OtherDerived>::type(
     numext::conj(lhs.coeff(1) * rhs.coeff(2) - lhs.coeff(2) * rhs.coeff(1)),
     numext::conj(lhs.coeff(2) * rhs.coeff(0) - lhs.coeff(0) * rhs.coeff(2)),
     numext::conj(lhs.coeff(0) * rhs.coeff(1) - lhs.coeff(1) * rhs.coeff(0))
   );
@@ -43,11 +51,11 @@
 
 template< int Arch,typename VectorLhs,typename VectorRhs,
           typename Scalar = typename VectorLhs::Scalar,
           bool Vectorizable = bool((VectorLhs::Flags&VectorRhs::Flags)&PacketAccessBit)>
 struct cross3_impl {
-  static inline typename internal::plain_matrix_type<VectorLhs>::type
+  EIGEN_DEVICE_FUNC static inline typename internal::plain_matrix_type<VectorLhs>::type
   run(const VectorLhs& lhs, const VectorRhs& rhs)
   {
     return typename internal::plain_matrix_type<VectorLhs>::type(
       numext::conj(lhs.coeff(1) * rhs.coeff(2) - lhs.coeff(2) * rhs.coeff(1)),
       numext::conj(lhs.coeff(2) * rhs.coeff(0) - lhs.coeff(0) * rhs.coeff(2)),
@@ -57,11 +65,11 @@
   }
 };
 
 }
 
-/** \geometry_module
+/** \geometry_module \ingroup Geometry_Module
   *
   * \returns the cross product of \c *this and \a other using only the x, y, and z coefficients
   *
   * The size of \c *this and \a other must be four. This function is especially useful
   * when using 4D vectors instead of 3D ones to get advantage of SSE/AltiVec vectorization.
@@ -68,58 +76,62 @@
   *
   * \sa MatrixBase::cross()
   */
 template<typename Derived>
 template<typename OtherDerived>
-inline typename MatrixBase<Derived>::PlainObject
+EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::PlainObject
 MatrixBase<Derived>::cross3(const MatrixBase<OtherDerived>& other) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Derived,4)
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,4)
 
-  typedef typename internal::nested<Derived,2>::type DerivedNested;
-  typedef typename internal::nested<OtherDerived,2>::type OtherDerivedNested;
+  typedef typename internal::nested_eval<Derived,2>::type DerivedNested;
+  typedef typename internal::nested_eval<OtherDerived,2>::type OtherDerivedNested;
   DerivedNested lhs(derived());
   OtherDerivedNested rhs(other.derived());
 
   return internal::cross3_impl<Architecture::Target,
                         typename internal::remove_all<DerivedNested>::type,
                         typename internal::remove_all<OtherDerivedNested>::type>::run(lhs,rhs);
 }
 
-/** \returns a matrix expression of the cross product of each column or row
+/** \geometry_module \ingroup Geometry_Module
+  *
+  * \returns a matrix expression of the cross product of each column or row
   * of the referenced expression with the \a other vector.
   *
   * The referenced matrix must have one dimension equal to 3.
   * The result matrix has the same dimensions than the referenced one.
   *
-  * \geometry_module
-  *
   * \sa MatrixBase::cross() */
 template<typename ExpressionType, int Direction>
 template<typename OtherDerived>
+EIGEN_DEVICE_FUNC 
 const typename VectorwiseOp<ExpressionType,Direction>::CrossReturnType
 VectorwiseOp<ExpressionType,Direction>::cross(const MatrixBase<OtherDerived>& other) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,3)
   EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
     YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+  
+  typename internal::nested_eval<ExpressionType,2>::type mat(_expression());
+  typename internal::nested_eval<OtherDerived,2>::type vec(other.derived());
 
   CrossReturnType res(_expression().rows(),_expression().cols());
   if(Direction==Vertical)
   {
     eigen_assert(CrossReturnType::RowsAtCompileTime==3 && "the matrix must have exactly 3 rows");
-    res.row(0) = (_expression().row(1) * other.coeff(2) - _expression().row(2) * other.coeff(1)).conjugate();
-    res.row(1) = (_expression().row(2) * other.coeff(0) - _expression().row(0) * other.coeff(2)).conjugate();
-    res.row(2) = (_expression().row(0) * other.coeff(1) - _expression().row(1) * other.coeff(0)).conjugate();
+    res.row(0) = (mat.row(1) * vec.coeff(2) - mat.row(2) * vec.coeff(1)).conjugate();
+    res.row(1) = (mat.row(2) * vec.coeff(0) - mat.row(0) * vec.coeff(2)).conjugate();
+    res.row(2) = (mat.row(0) * vec.coeff(1) - mat.row(1) * vec.coeff(0)).conjugate();
   }
   else
   {
     eigen_assert(CrossReturnType::ColsAtCompileTime==3 && "the matrix must have exactly 3 columns");
-    res.col(0) = (_expression().col(1) * other.coeff(2) - _expression().col(2) * other.coeff(1)).conjugate();
-    res.col(1) = (_expression().col(2) * other.coeff(0) - _expression().col(0) * other.coeff(2)).conjugate();
-    res.col(2) = (_expression().col(0) * other.coeff(1) - _expression().col(1) * other.coeff(0)).conjugate();
+    res.col(0) = (mat.col(1) * vec.coeff(2) - mat.col(2) * vec.coeff(1)).conjugate();
+    res.col(1) = (mat.col(2) * vec.coeff(0) - mat.col(0) * vec.coeff(2)).conjugate();
+    res.col(2) = (mat.col(0) * vec.coeff(1) - mat.col(1) * vec.coeff(0)).conjugate();
   }
   return res;
 }
 
 namespace internal {
@@ -128,12 +140,12 @@
 struct unitOrthogonal_selector
 {
   typedef typename plain_matrix_type<Derived>::type VectorType;
   typedef typename traits<Derived>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef typename Derived::Index Index;
   typedef Matrix<Scalar,2,1> Vector2;
+  EIGEN_DEVICE_FUNC
   static inline VectorType run(const Derived& src)
   {
     VectorType perp = VectorType::Zero(src.size());
     Index maxi = 0;
     Index sndi = 0;
@@ -152,10 +164,11 @@
 struct unitOrthogonal_selector<Derived,3>
 {
   typedef typename plain_matrix_type<Derived>::type VectorType;
   typedef typename traits<Derived>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  EIGEN_DEVICE_FUNC
   static inline VectorType run(const Derived& src)
   {
     VectorType perp;
     /* Let us compute the crossed product of *this with a vector
      * that is not too close to being colinear to *this.
@@ -190,29 +203,32 @@
 
 template<typename Derived>
 struct unitOrthogonal_selector<Derived,2>
 {
   typedef typename plain_matrix_type<Derived>::type VectorType;
+  EIGEN_DEVICE_FUNC
   static inline VectorType run(const Derived& src)
   { return VectorType(-numext::conj(src.y()), numext::conj(src.x())).normalized(); }
 };
 
 } // end namespace internal
 
-/** \returns a unit vector which is orthogonal to \c *this
+/** \geometry_module \ingroup Geometry_Module
+  *
+  * \returns a unit vector which is orthogonal to \c *this
   *
   * The size of \c *this must be at least 2. If the size is exactly 2,
   * then the returned vector is a counter clock wise rotation of \c *this, i.e., (-y,x).normalized().
   *
   * \sa cross()
   */
 template<typename Derived>
-typename MatrixBase<Derived>::PlainObject
+EIGEN_DEVICE_FUNC typename MatrixBase<Derived>::PlainObject
 MatrixBase<Derived>::unitOrthogonal() const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return internal::unitOrthogonal_selector<Derived>::run(derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_ORTHOMETHODS_H

Index: 3rd_party/eigen/Eigen/src/Geometry/ParametrizedLine.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/ParametrizedLine.h
+++ 3rd_party/eigen/Eigen/src/Geometry/ParametrizedLine.h
@@ -21,12 +21,12 @@
   *
   * A parametrized line is defined by an origin point \f$ \mathbf{o} \f$ and a unit
   * direction vector \f$ \mathbf{d} \f$ such that the line corresponds to
   * the set \f$ l(t) = \mathbf{o} + t \mathbf{d} \f$, \f$ t \in \mathbf{R} \f$.
   *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
-  * \param _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
+  * \tparam _Scalar the scalar type, i.e., the type of the coefficients
+  * \tparam _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
   */
 template <typename _Scalar, int _AmbientDim, int _Options>
 class ParametrizedLine
 {
 public:
@@ -35,103 +35,103 @@
     AmbientDimAtCompileTime = _AmbientDim,
     Options = _Options
   };
   typedef _Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef DenseIndex Index;
+  typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
   typedef Matrix<Scalar,AmbientDimAtCompileTime,1,Options> VectorType;
 
   /** Default constructor without initialization */
-  inline ParametrizedLine() {}
+  EIGEN_DEVICE_FUNC inline ParametrizedLine() {}
   
   template<int OtherOptions>
-  ParametrizedLine(const ParametrizedLine<Scalar,AmbientDimAtCompileTime,OtherOptions>& other)
+  EIGEN_DEVICE_FUNC ParametrizedLine(const ParametrizedLine<Scalar,AmbientDimAtCompileTime,OtherOptions>& other)
    : m_origin(other.origin()), m_direction(other.direction())
   {}
 
   /** Constructs a dynamic-size line with \a _dim the dimension
     * of the ambient space */
-  inline explicit ParametrizedLine(Index _dim) : m_origin(_dim), m_direction(_dim) {}
+  EIGEN_DEVICE_FUNC inline explicit ParametrizedLine(Index _dim) : m_origin(_dim), m_direction(_dim) {}
 
   /** Initializes a parametrized line of direction \a direction and origin \a origin.
     * \warning the vector direction is assumed to be normalized.
     */
-  ParametrizedLine(const VectorType& origin, const VectorType& direction)
+  EIGEN_DEVICE_FUNC ParametrizedLine(const VectorType& origin, const VectorType& direction)
     : m_origin(origin), m_direction(direction) {}
 
   template <int OtherOptions>
-  explicit ParametrizedLine(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane);
+  EIGEN_DEVICE_FUNC explicit ParametrizedLine(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane);
 
   /** Constructs a parametrized line going from \a p0 to \a p1. */
-  static inline ParametrizedLine Through(const VectorType& p0, const VectorType& p1)
+  EIGEN_DEVICE_FUNC static inline ParametrizedLine Through(const VectorType& p0, const VectorType& p1)
   { return ParametrizedLine(p0, (p1-p0).normalized()); }
 
-  ~ParametrizedLine() {}
+  EIGEN_DEVICE_FUNC ~ParametrizedLine() {}
 
   /** \returns the dimension in which the line holds */
-  inline Index dim() const { return m_direction.size(); }
+  EIGEN_DEVICE_FUNC inline Index dim() const { return m_direction.size(); }
 
-  const VectorType& origin() const { return m_origin; }
-  VectorType& origin() { return m_origin; }
+  EIGEN_DEVICE_FUNC const VectorType& origin() const { return m_origin; }
+  EIGEN_DEVICE_FUNC VectorType& origin() { return m_origin; }
 
-  const VectorType& direction() const { return m_direction; }
-  VectorType& direction() { return m_direction; }
+  EIGEN_DEVICE_FUNC const VectorType& direction() const { return m_direction; }
+  EIGEN_DEVICE_FUNC VectorType& direction() { return m_direction; }
 
   /** \returns the squared distance of a point \a p to its projection onto the line \c *this.
     * \sa distance()
     */
-  RealScalar squaredDistance(const VectorType& p) const
+  EIGEN_DEVICE_FUNC RealScalar squaredDistance(const VectorType& p) const
   {
     VectorType diff = p - origin();
     return (diff - direction().dot(diff) * direction()).squaredNorm();
   }
   /** \returns the distance of a point \a p to its projection onto the line \c *this.
     * \sa squaredDistance()
     */
-  RealScalar distance(const VectorType& p) const { using std::sqrt; return sqrt(squaredDistance(p)); }
+  EIGEN_DEVICE_FUNC RealScalar distance(const VectorType& p) const { EIGEN_USING_STD_MATH(sqrt) return sqrt(squaredDistance(p)); }
 
   /** \returns the projection of a point \a p onto the line \c *this. */
-  VectorType projection(const VectorType& p) const
+  EIGEN_DEVICE_FUNC VectorType projection(const VectorType& p) const
   { return origin() + direction().dot(p-origin()) * direction(); }
 
-  VectorType pointAt(const Scalar& t) const;
+  EIGEN_DEVICE_FUNC VectorType pointAt(const Scalar& t) const;
   
   template <int OtherOptions>
-  Scalar intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
+  EIGEN_DEVICE_FUNC Scalar intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
  
   template <int OtherOptions>
-  Scalar intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
+  EIGEN_DEVICE_FUNC Scalar intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
   
   template <int OtherOptions>
-  VectorType intersectionPoint(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
+  EIGEN_DEVICE_FUNC VectorType intersectionPoint(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
     *
     * Note that if \a NewScalarType is equal to the current scalar type of \c *this
     * then this function smartly returns a const reference to \c *this.
     */
   template<typename NewScalarType>
-  inline typename internal::cast_return_type<ParametrizedLine,
+  EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<ParametrizedLine,
            ParametrizedLine<NewScalarType,AmbientDimAtCompileTime,Options> >::type cast() const
   {
     return typename internal::cast_return_type<ParametrizedLine,
                     ParametrizedLine<NewScalarType,AmbientDimAtCompileTime,Options> >::type(*this);
   }
 
   /** Copy constructor with scalar type conversion */
   template<typename OtherScalarType,int OtherOptions>
-  inline explicit ParametrizedLine(const ParametrizedLine<OtherScalarType,AmbientDimAtCompileTime,OtherOptions>& other)
+  EIGEN_DEVICE_FUNC inline explicit ParametrizedLine(const ParametrizedLine<OtherScalarType,AmbientDimAtCompileTime,OtherOptions>& other)
   {
     m_origin = other.origin().template cast<Scalar>();
     m_direction = other.direction().template cast<Scalar>();
   }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const ParametrizedLine& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+  EIGEN_DEVICE_FUNC bool isApprox(const ParametrizedLine& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return m_origin.isApprox(other.m_origin, prec) && m_direction.isApprox(other.m_direction, prec); }
 
 protected:
 
   VectorType m_origin, m_direction;
@@ -141,31 +141,31 @@
   *
   * \warning the ambient space must have dimension 2 such that the hyperplane actually describes a line
   */
 template <typename _Scalar, int _AmbientDim, int _Options>
 template <int OtherOptions>
-inline ParametrizedLine<_Scalar, _AmbientDim,_Options>::ParametrizedLine(const Hyperplane<_Scalar, _AmbientDim,OtherOptions>& hyperplane)
+EIGEN_DEVICE_FUNC inline ParametrizedLine<_Scalar, _AmbientDim,_Options>::ParametrizedLine(const Hyperplane<_Scalar, _AmbientDim,OtherOptions>& hyperplane)
 {
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(VectorType, 2)
   direction() = hyperplane.normal().unitOrthogonal();
   origin() = -hyperplane.normal()*hyperplane.offset();
 }
 
 /** \returns the point at \a t along this line
   */
 template <typename _Scalar, int _AmbientDim, int _Options>
-inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType
+EIGEN_DEVICE_FUNC inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType
 ParametrizedLine<_Scalar, _AmbientDim,_Options>::pointAt(const _Scalar& t) const
 {
   return origin() + (direction()*t); 
 }
 
 /** \returns the parameter value of the intersection between \c *this and the given \a hyperplane
   */
 template <typename _Scalar, int _AmbientDim, int _Options>
 template <int OtherOptions>
-inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
+EIGEN_DEVICE_FUNC inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
 {
   return -(hyperplane.offset()+hyperplane.normal().dot(origin()))
           / hyperplane.normal().dot(direction());
 }
 
@@ -173,23 +173,23 @@
 /** \deprecated use intersectionParameter()
   * \returns the parameter value of the intersection between \c *this and the given \a hyperplane
   */
 template <typename _Scalar, int _AmbientDim, int _Options>
 template <int OtherOptions>
-inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
+EIGEN_DEVICE_FUNC inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
 {
   return intersectionParameter(hyperplane);
 }
 
 /** \returns the point of the intersection between \c *this and the given hyperplane
   */
 template <typename _Scalar, int _AmbientDim, int _Options>
 template <int OtherOptions>
-inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType
+EIGEN_DEVICE_FUNC inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType
 ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersectionPoint(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
 {
   return pointAt(intersectionParameter(hyperplane));
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_PARAMETRIZEDLINE_H

Index: 3rd_party/eigen/Eigen/src/Geometry/Quaternion.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/Quaternion.h
+++ 3rd_party/eigen/Eigen/src/Geometry/Quaternion.h
@@ -32,12 +32,13 @@
   * \sa class Quaternion
   */
 template<class Derived>
 class QuaternionBase : public RotationBase<Derived, 3>
 {
+ public:
   typedef RotationBase<Derived, 3> Base;
-public:
+
   using Base::operator*;
   using Base::derived;
 
   typedef typename internal::traits<Derived>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -55,123 +56,123 @@
   typedef AngleAxis<Scalar> AngleAxisType;
 
 
 
   /** \returns the \c x coefficient */
-  inline Scalar x() const { return this->derived().coeffs().coeff(0); }
+  EIGEN_DEVICE_FUNC inline Scalar x() const { return this->derived().coeffs().coeff(0); }
   /** \returns the \c y coefficient */
-  inline Scalar y() const { return this->derived().coeffs().coeff(1); }
+  EIGEN_DEVICE_FUNC inline Scalar y() const { return this->derived().coeffs().coeff(1); }
   /** \returns the \c z coefficient */
-  inline Scalar z() const { return this->derived().coeffs().coeff(2); }
+  EIGEN_DEVICE_FUNC inline Scalar z() const { return this->derived().coeffs().coeff(2); }
   /** \returns the \c w coefficient */
-  inline Scalar w() const { return this->derived().coeffs().coeff(3); }
+  EIGEN_DEVICE_FUNC inline Scalar w() const { return this->derived().coeffs().coeff(3); }
 
   /** \returns a reference to the \c x coefficient */
-  inline Scalar& x() { return this->derived().coeffs().coeffRef(0); }
+  EIGEN_DEVICE_FUNC inline Scalar& x() { return this->derived().coeffs().coeffRef(0); }
   /** \returns a reference to the \c y coefficient */
-  inline Scalar& y() { return this->derived().coeffs().coeffRef(1); }
+  EIGEN_DEVICE_FUNC inline Scalar& y() { return this->derived().coeffs().coeffRef(1); }
   /** \returns a reference to the \c z coefficient */
-  inline Scalar& z() { return this->derived().coeffs().coeffRef(2); }
+  EIGEN_DEVICE_FUNC inline Scalar& z() { return this->derived().coeffs().coeffRef(2); }
   /** \returns a reference to the \c w coefficient */
-  inline Scalar& w() { return this->derived().coeffs().coeffRef(3); }
+  EIGEN_DEVICE_FUNC inline Scalar& w() { return this->derived().coeffs().coeffRef(3); }
 
   /** \returns a read-only vector expression of the imaginary part (x,y,z) */
-  inline const VectorBlock<const Coefficients,3> vec() const { return coeffs().template head<3>(); }
+  EIGEN_DEVICE_FUNC inline const VectorBlock<const Coefficients,3> vec() const { return coeffs().template head<3>(); }
 
   /** \returns a vector expression of the imaginary part (x,y,z) */
-  inline VectorBlock<Coefficients,3> vec() { return coeffs().template head<3>(); }
+  EIGEN_DEVICE_FUNC inline VectorBlock<Coefficients,3> vec() { return coeffs().template head<3>(); }
 
   /** \returns a read-only vector expression of the coefficients (x,y,z,w) */
-  inline const typename internal::traits<Derived>::Coefficients& coeffs() const { return derived().coeffs(); }
+  EIGEN_DEVICE_FUNC inline const typename internal::traits<Derived>::Coefficients& coeffs() const { return derived().coeffs(); }
 
   /** \returns a vector expression of the coefficients (x,y,z,w) */
-  inline typename internal::traits<Derived>::Coefficients& coeffs() { return derived().coeffs(); }
+  EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Coefficients& coeffs() { return derived().coeffs(); }
 
-  EIGEN_STRONG_INLINE QuaternionBase<Derived>& operator=(const QuaternionBase<Derived>& other);
-  template<class OtherDerived> EIGEN_STRONG_INLINE Derived& operator=(const QuaternionBase<OtherDerived>& other);
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE QuaternionBase<Derived>& operator=(const QuaternionBase<Derived>& other);
+  template<class OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const QuaternionBase<OtherDerived>& other);
 
 // disabled this copy operator as it is giving very strange compilation errors when compiling
 // test_stdvector with GCC 4.4.2. This looks like a GCC bug though, so feel free to re-enable it if it's
 // useful; however notice that we already have the templated operator= above and e.g. in MatrixBase
 // we didn't have to add, in addition to templated operator=, such a non-templated copy operator.
 //  Derived& operator=(const QuaternionBase& other)
 //  { return operator=<Derived>(other); }
 
-  Derived& operator=(const AngleAxisType& aa);
-  template<class OtherDerived> Derived& operator=(const MatrixBase<OtherDerived>& m);
+  EIGEN_DEVICE_FUNC Derived& operator=(const AngleAxisType& aa);
+  template<class OtherDerived> EIGEN_DEVICE_FUNC Derived& operator=(const MatrixBase<OtherDerived>& m);
 
   /** \returns a quaternion representing an identity rotation
     * \sa MatrixBase::Identity()
     */
-  static inline Quaternion<Scalar> Identity() { return Quaternion<Scalar>(1, 0, 0, 0); }
+  EIGEN_DEVICE_FUNC static inline Quaternion<Scalar> Identity() { return Quaternion<Scalar>(Scalar(1), Scalar(0), Scalar(0), Scalar(0)); }
 
   /** \sa QuaternionBase::Identity(), MatrixBase::setIdentity()
     */
-  inline QuaternionBase& setIdentity() { coeffs() << 0, 0, 0, 1; return *this; }
+  EIGEN_DEVICE_FUNC inline QuaternionBase& setIdentity() { coeffs() << Scalar(0), Scalar(0), Scalar(0), Scalar(1); return *this; }
 
   /** \returns the squared norm of the quaternion's coefficients
     * \sa QuaternionBase::norm(), MatrixBase::squaredNorm()
     */
-  inline Scalar squaredNorm() const { return coeffs().squaredNorm(); }
+  EIGEN_DEVICE_FUNC inline Scalar squaredNorm() const { return coeffs().squaredNorm(); }
 
   /** \returns the norm of the quaternion's coefficients
     * \sa QuaternionBase::squaredNorm(), MatrixBase::norm()
     */
-  inline Scalar norm() const { return coeffs().norm(); }
+  EIGEN_DEVICE_FUNC inline Scalar norm() const { return coeffs().norm(); }
 
   /** Normalizes the quaternion \c *this
     * \sa normalized(), MatrixBase::normalize() */
-  inline void normalize() { coeffs().normalize(); }
+  EIGEN_DEVICE_FUNC inline void normalize() { coeffs().normalize(); }
   /** \returns a normalized copy of \c *this
     * \sa normalize(), MatrixBase::normalized() */
-  inline Quaternion<Scalar> normalized() const { return Quaternion<Scalar>(coeffs().normalized()); }
+  EIGEN_DEVICE_FUNC inline Quaternion<Scalar> normalized() const { return Quaternion<Scalar>(coeffs().normalized()); }
 
     /** \returns the dot product of \c *this and \a other
     * Geometrically speaking, the dot product of two unit quaternions
     * corresponds to the cosine of half the angle between the two rotations.
     * \sa angularDistance()
     */
-  template<class OtherDerived> inline Scalar dot(const QuaternionBase<OtherDerived>& other) const { return coeffs().dot(other.coeffs()); }
+  template<class OtherDerived> EIGEN_DEVICE_FUNC inline Scalar dot(const QuaternionBase<OtherDerived>& other) const { return coeffs().dot(other.coeffs()); }
 
-  template<class OtherDerived> Scalar angularDistance(const QuaternionBase<OtherDerived>& other) const;
+  template<class OtherDerived> EIGEN_DEVICE_FUNC Scalar angularDistance(const QuaternionBase<OtherDerived>& other) const;
 
   /** \returns an equivalent 3x3 rotation matrix */
-  Matrix3 toRotationMatrix() const;
+  EIGEN_DEVICE_FUNC Matrix3 toRotationMatrix() const;
 
   /** \returns the quaternion which transform \a a into \a b through a rotation */
   template<typename Derived1, typename Derived2>
-  Derived& setFromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b);
+  EIGEN_DEVICE_FUNC Derived& setFromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b);
 
-  template<class OtherDerived> EIGEN_STRONG_INLINE Quaternion<Scalar> operator* (const QuaternionBase<OtherDerived>& q) const;
-  template<class OtherDerived> EIGEN_STRONG_INLINE Derived& operator*= (const QuaternionBase<OtherDerived>& q);
+  template<class OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Quaternion<Scalar> operator* (const QuaternionBase<OtherDerived>& q) const;
+  template<class OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*= (const QuaternionBase<OtherDerived>& q);
 
   /** \returns the quaternion describing the inverse rotation */
-  Quaternion<Scalar> inverse() const;
+  EIGEN_DEVICE_FUNC Quaternion<Scalar> inverse() const;
 
   /** \returns the conjugated quaternion */
-  Quaternion<Scalar> conjugate() const;
+  EIGEN_DEVICE_FUNC Quaternion<Scalar> conjugate() const;
 
-  template<class OtherDerived> Quaternion<Scalar> slerp(const Scalar& t, const QuaternionBase<OtherDerived>& other) const;
+  template<class OtherDerived> EIGEN_DEVICE_FUNC Quaternion<Scalar> slerp(const Scalar& t, const QuaternionBase<OtherDerived>& other) const;
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
   template<class OtherDerived>
-  bool isApprox(const QuaternionBase<OtherDerived>& other, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
+  EIGEN_DEVICE_FUNC bool isApprox(const QuaternionBase<OtherDerived>& other, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
   { return coeffs().isApprox(other.coeffs(), prec); }
 
-	/** return the result vector of \a v through the rotation*/
-  EIGEN_STRONG_INLINE Vector3 _transformVector(Vector3 v) const;
+  /** return the result vector of \a v through the rotation*/
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Vector3 _transformVector(const Vector3& v) const;
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
     *
     * Note that if \a NewScalarType is equal to the current scalar type of \c *this
     * then this function smartly returns a const reference to \c *this.
     */
   template<typename NewScalarType>
-  inline typename internal::cast_return_type<Derived,Quaternion<NewScalarType> >::type cast() const
+  EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<Derived,Quaternion<NewScalarType> >::type cast() const
   {
     return typename internal::cast_return_type<Derived,Quaternion<NewScalarType> >::type(derived());
   }
 
 #ifdef EIGEN_QUATERNIONBASE_PLUGIN
@@ -214,71 +215,77 @@
 {
   typedef Quaternion<_Scalar,_Options> PlainObject;
   typedef _Scalar Scalar;
   typedef Matrix<_Scalar,4,1,_Options> Coefficients;
   enum{
-    IsAligned = internal::traits<Coefficients>::Flags & AlignedBit,
-    Flags = IsAligned ? (AlignedBit | LvalueBit) : LvalueBit
+    Alignment = internal::traits<Coefficients>::Alignment,
+    Flags = LvalueBit
   };
 };
 }
 
 template<typename _Scalar, int _Options>
 class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
 {
+public:
   typedef QuaternionBase<Quaternion<_Scalar,_Options> > Base;
-  enum { IsAligned = internal::traits<Quaternion>::IsAligned };
+  enum { NeedsAlignment = internal::traits<Quaternion>::Alignment>0 };
 
-public:
   typedef _Scalar Scalar;
 
-  EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Quaternion)
+  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Quaternion)
   using Base::operator*=;
 
   typedef typename internal::traits<Quaternion>::Coefficients Coefficients;
   typedef typename Base::AngleAxisType AngleAxisType;
 
   /** Default constructor leaving the quaternion uninitialized. */
-  inline Quaternion() {}
+  EIGEN_DEVICE_FUNC inline Quaternion() {}
 
   /** Constructs and initializes the quaternion \f$ w+xi+yj+zk \f$ from
     * its four coefficients \a w, \a x, \a y and \a z.
     *
     * \warning Note the order of the arguments: the real \a w coefficient first,
     * while internally the coefficients are stored in the following order:
     * [\c x, \c y, \c z, \c w]
     */
-  inline Quaternion(const Scalar& w, const Scalar& x, const Scalar& y, const Scalar& z) : m_coeffs(x, y, z, w){}
+  EIGEN_DEVICE_FUNC inline Quaternion(const Scalar& w, const Scalar& x, const Scalar& y, const Scalar& z) : m_coeffs(x, y, z, w){}
 
   /** Constructs and initialize a quaternion from the array data */
-  inline Quaternion(const Scalar* data) : m_coeffs(data) {}
+  EIGEN_DEVICE_FUNC explicit inline Quaternion(const Scalar* data) : m_coeffs(data) {}
 
   /** Copy constructor */
-  template<class Derived> EIGEN_STRONG_INLINE Quaternion(const QuaternionBase<Derived>& other) { this->Base::operator=(other); }
+  template<class Derived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Quaternion(const QuaternionBase<Derived>& other) { this->Base::operator=(other); }
 
   /** Constructs and initializes a quaternion from the angle-axis \a aa */
-  explicit inline Quaternion(const AngleAxisType& aa) { *this = aa; }
+  EIGEN_DEVICE_FUNC explicit inline Quaternion(const AngleAxisType& aa) { *this = aa; }
 
   /** Constructs and initializes a quaternion from either:
     *  - a rotation matrix expression,
     *  - a 4D vector expression representing quaternion coefficients.
     */
   template<typename Derived>
-  explicit inline Quaternion(const MatrixBase<Derived>& other) { *this = other; }
+  EIGEN_DEVICE_FUNC explicit inline Quaternion(const MatrixBase<Derived>& other) { *this = other; }
 
   /** Explicit copy constructor with scalar conversion */
   template<typename OtherScalar, int OtherOptions>
-  explicit inline Quaternion(const Quaternion<OtherScalar, OtherOptions>& other)
+  EIGEN_DEVICE_FUNC explicit inline Quaternion(const Quaternion<OtherScalar, OtherOptions>& other)
   { m_coeffs = other.coeffs().template cast<Scalar>(); }
 
+  EIGEN_DEVICE_FUNC static Quaternion UnitRandom();
+
   template<typename Derived1, typename Derived2>
-  static Quaternion FromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b);
+  EIGEN_DEVICE_FUNC static Quaternion FromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b);
 
-  inline Coefficients& coeffs() { return m_coeffs;}
-  inline const Coefficients& coeffs() const { return m_coeffs;}
+  EIGEN_DEVICE_FUNC inline Coefficients& coeffs() { return m_coeffs;}
+  EIGEN_DEVICE_FUNC inline const Coefficients& coeffs() const { return m_coeffs;}
 
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(IsAligned)
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(bool(NeedsAlignment))
+  
+#ifdef EIGEN_QUATERNION_PLUGIN
+# include EIGEN_QUATERNION_PLUGIN
+#endif
 
 protected:
   Coefficients m_coeffs;
   
 #ifndef EIGEN_PARSED_BY_DOXYGEN
@@ -334,27 +341,27 @@
   */
 template<typename _Scalar, int _Options>
 class Map<const Quaternion<_Scalar>, _Options >
   : public QuaternionBase<Map<const Quaternion<_Scalar>, _Options> >
 {
+  public:
     typedef QuaternionBase<Map<const Quaternion<_Scalar>, _Options> > Base;
 
-  public:
     typedef _Scalar Scalar;
     typedef typename internal::traits<Map>::Coefficients Coefficients;
-    EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Map)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
     using Base::operator*=;
 
     /** Constructs a Mapped Quaternion object from the pointer \a coeffs
       *
       * The pointer \a coeffs must reference the four coefficients of Quaternion in the following order:
       * \code *coeffs == {x, y, z, w} \endcode
       *
       * If the template parameter _Options is set to #Aligned, then the pointer coeffs must be aligned. */
-    EIGEN_STRONG_INLINE Map(const Scalar* coeffs) : m_coeffs(coeffs) {}
+    EIGEN_DEVICE_FUNC explicit EIGEN_STRONG_INLINE Map(const Scalar* coeffs) : m_coeffs(coeffs) {}
 
-    inline const Coefficients& coeffs() const { return m_coeffs;}
+    EIGEN_DEVICE_FUNC inline const Coefficients& coeffs() const { return m_coeffs;}
 
   protected:
     const Coefficients m_coeffs;
 };
 
@@ -371,28 +378,28 @@
   */
 template<typename _Scalar, int _Options>
 class Map<Quaternion<_Scalar>, _Options >
   : public QuaternionBase<Map<Quaternion<_Scalar>, _Options> >
 {
+  public:
     typedef QuaternionBase<Map<Quaternion<_Scalar>, _Options> > Base;
 
-  public:
     typedef _Scalar Scalar;
     typedef typename internal::traits<Map>::Coefficients Coefficients;
-    EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Map)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
     using Base::operator*=;
 
     /** Constructs a Mapped Quaternion object from the pointer \a coeffs
       *
       * The pointer \a coeffs must reference the four coefficients of Quaternion in the following order:
       * \code *coeffs == {x, y, z, w} \endcode
       *
       * If the template parameter _Options is set to #Aligned, then the pointer coeffs must be aligned. */
-    EIGEN_STRONG_INLINE Map(Scalar* coeffs) : m_coeffs(coeffs) {}
+    EIGEN_DEVICE_FUNC explicit EIGEN_STRONG_INLINE Map(Scalar* coeffs) : m_coeffs(coeffs) {}
 
-    inline Coefficients& coeffs() { return m_coeffs; }
-    inline const Coefficients& coeffs() const { return m_coeffs; }
+    EIGEN_DEVICE_FUNC inline Coefficients& coeffs() { return m_coeffs; }
+    EIGEN_DEVICE_FUNC inline const Coefficients& coeffs() const { return m_coeffs; }
 
   protected:
     Coefficients m_coeffs;
 };
 
@@ -414,13 +421,13 @@
 ***************************************************************************/
 
 // Generic Quaternion * Quaternion product
 // This product can be specialized for a given architecture via the Arch template argument.
 namespace internal {
-template<int Arch, class Derived1, class Derived2, typename Scalar, int _Options> struct quat_product
+template<int Arch, class Derived1, class Derived2, typename Scalar> struct quat_product
 {
-  static EIGEN_STRONG_INLINE Quaternion<Scalar> run(const QuaternionBase<Derived1>& a, const QuaternionBase<Derived2>& b){
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Quaternion<Scalar> run(const QuaternionBase<Derived1>& a, const QuaternionBase<Derived2>& b){
     return Quaternion<Scalar>
     (
       a.w() * b.w() - a.x() * b.x() - a.y() * b.y() - a.z() * b.z(),
       a.w() * b.x() + a.x() * b.w() + a.y() * b.z() - a.z() * b.y(),
       a.w() * b.y() + a.y() * b.w() + a.z() * b.x() - a.x() * b.z(),
@@ -431,24 +438,23 @@
 }
 
 /** \returns the concatenation of two rotations as a quaternion-quaternion product */
 template <class Derived>
 template <class OtherDerived>
-EIGEN_STRONG_INLINE Quaternion<typename internal::traits<Derived>::Scalar>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Quaternion<typename internal::traits<Derived>::Scalar>
 QuaternionBase<Derived>::operator* (const QuaternionBase<OtherDerived>& other) const
 {
   EIGEN_STATIC_ASSERT((internal::is_same<typename Derived::Scalar, typename OtherDerived::Scalar>::value),
    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
   return internal::quat_product<Architecture::Target, Derived, OtherDerived,
-                         typename internal::traits<Derived>::Scalar,
-                         internal::traits<Derived>::IsAligned && internal::traits<OtherDerived>::IsAligned>::run(*this, other);
+                         typename internal::traits<Derived>::Scalar>::run(*this, other);
 }
 
 /** \sa operator*(Quaternion) */
 template <class Derived>
 template <class OtherDerived>
-EIGEN_STRONG_INLINE Derived& QuaternionBase<Derived>::operator*= (const QuaternionBase<OtherDerived>& other)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& QuaternionBase<Derived>::operator*= (const QuaternionBase<OtherDerived>& other)
 {
   derived() = derived() * other.derived();
   return derived();
 }
 
@@ -458,12 +464,12 @@
   * Comparison of the operation cost for n transformations:
   *   - Quaternion2:    30n
   *   - Via a Matrix3: 24 + 15n
   */
 template <class Derived>
-EIGEN_STRONG_INLINE typename QuaternionBase<Derived>::Vector3
-QuaternionBase<Derived>::_transformVector(Vector3 v) const
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename QuaternionBase<Derived>::Vector3
+QuaternionBase<Derived>::_transformVector(const Vector3& v) const
 {
     // Note that this algorithm comes from the optimization by hand
     // of the conversion to a Matrix followed by a Matrix/Vector product.
     // It appears to be much faster than the common algorithm found
     // in the literature (30 versus 39 flops). It also requires two
@@ -472,31 +478,31 @@
     uv += uv;
     return v + this->w() * uv + this->vec().cross(uv);
 }
 
 template<class Derived>
-EIGEN_STRONG_INLINE QuaternionBase<Derived>& QuaternionBase<Derived>::operator=(const QuaternionBase<Derived>& other)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE QuaternionBase<Derived>& QuaternionBase<Derived>::operator=(const QuaternionBase<Derived>& other)
 {
   coeffs() = other.coeffs();
   return derived();
 }
 
 template<class Derived>
 template<class OtherDerived>
-EIGEN_STRONG_INLINE Derived& QuaternionBase<Derived>::operator=(const QuaternionBase<OtherDerived>& other)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& QuaternionBase<Derived>::operator=(const QuaternionBase<OtherDerived>& other)
 {
   coeffs() = other.coeffs();
   return derived();
 }
 
 /** Set \c *this from an angle-axis \a aa and returns a reference to \c *this
   */
 template<class Derived>
-EIGEN_STRONG_INLINE Derived& QuaternionBase<Derived>::operator=(const AngleAxisType& aa)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& QuaternionBase<Derived>::operator=(const AngleAxisType& aa)
 {
-  using std::cos;
-  using std::sin;
+  EIGEN_USING_STD_MATH(cos)
+  EIGEN_USING_STD_MATH(sin)
   Scalar ha = Scalar(0.5)*aa.angle(); // Scalar(0.5) to suppress precision loss warnings
   this->w() = cos(ha);
   this->vec() = sin(ha) * aa.axis();
   return derived();
 }
@@ -507,11 +513,11 @@
   *     and \a xpr is converted to a quaternion
   */
 
 template<class Derived>
 template<class MatrixDerived>
-inline Derived& QuaternionBase<Derived>::operator=(const MatrixBase<MatrixDerived>& xpr)
+EIGEN_DEVICE_FUNC inline Derived& QuaternionBase<Derived>::operator=(const MatrixBase<MatrixDerived>& xpr)
 {
   EIGEN_STATIC_ASSERT((internal::is_same<typename Derived::Scalar, typename MatrixDerived::Scalar>::value),
    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
   internal::quaternionbase_assign_impl<MatrixDerived>::run(*this, xpr.derived());
   return derived();
@@ -519,11 +525,11 @@
 
 /** Convert the quaternion to a 3x3 rotation matrix. The quaternion is required to
   * be normalized, otherwise the result is undefined.
   */
 template<class Derived>
-inline typename QuaternionBase<Derived>::Matrix3
+EIGEN_DEVICE_FUNC inline typename QuaternionBase<Derived>::Matrix3
 QuaternionBase<Derived>::toRotationMatrix(void) const
 {
   // NOTE if inlined, then gcc 4.2 and 4.4 get rid of the temporary (not gcc 4.3 !!)
   // if not inlined then the cost of the return by value is huge ~ +35%,
   // however, not inlining this function is an order of magnitude slower, so
@@ -566,14 +572,13 @@
   * Note that the two input vectors do \b not have to be normalized, and
   * do not need to have the same norm.
   */
 template<class Derived>
 template<typename Derived1, typename Derived2>
-inline Derived& QuaternionBase<Derived>::setFromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b)
+EIGEN_DEVICE_FUNC inline Derived& QuaternionBase<Derived>::setFromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b)
 {
-  using std::max;
-  using std::sqrt;
+  EIGEN_USING_STD_MATH(sqrt)
   Vector3 v0 = a.normalized();
   Vector3 v1 = b.normalized();
   Scalar c = v1.dot(v0);
 
   // if dot == -1, vectors are nearly opposites
@@ -584,11 +589,11 @@
   //    under the constraint:
   //       ||x|| = 1
   //    which yields a singular value problem
   if (c < Scalar(-1)+NumTraits<Scalar>::dummy_precision())
   {
-    c = (max)(c,Scalar(-1));
+    c = numext::maxi(c,Scalar(-1));
     Matrix<Scalar,2,3> m; m << v0.transpose(), v1.transpose();
     JacobiSVD<Matrix<Scalar,2,3> > svd(m, ComputeFullV);
     Vector3 axis = svd.matrixV().col(2);
 
     Scalar w2 = (Scalar(1)+c)*Scalar(0.5);
@@ -603,10 +608,28 @@
   this->w() = s * Scalar(0.5);
 
   return derived();
 }
 
+/** \returns a random unit quaternion following a uniform distribution law on SO(3)
+  *
+  * \note The implementation is based on http://planning.cs.uiuc.edu/node198.html
+  */
+template<typename Scalar, int Options>
+EIGEN_DEVICE_FUNC Quaternion<Scalar,Options> Quaternion<Scalar,Options>::UnitRandom()
+{
+  EIGEN_USING_STD_MATH(sqrt)
+  EIGEN_USING_STD_MATH(sin)
+  EIGEN_USING_STD_MATH(cos)
+  const Scalar u1 = internal::random<Scalar>(0, 1),
+               u2 = internal::random<Scalar>(0, 2*EIGEN_PI),
+               u3 = internal::random<Scalar>(0, 2*EIGEN_PI);
+  const Scalar a = sqrt(1 - u1),
+               b = sqrt(u1);
+  return Quaternion (a * sin(u2), a * cos(u2), b * sin(u3), b * cos(u3));
+}
+
 
 /** Returns a quaternion representing a rotation between
   * the two arbitrary vectors \a a and \a b. In other words, the built
   * rotation represent a rotation sending the line of direction \a a
   * to the line of direction \a b, both lines passing through the origin.
@@ -616,11 +639,11 @@
   * Note that the two input vectors do \b not have to be normalized, and
   * do not need to have the same norm.
   */
 template<typename Scalar, int Options>
 template<typename Derived1, typename Derived2>
-Quaternion<Scalar,Options> Quaternion<Scalar,Options>::FromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b)
+EIGEN_DEVICE_FUNC Quaternion<Scalar,Options> Quaternion<Scalar,Options>::FromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b)
 {
     Quaternion quat;
     quat.setFromTwoVectors(a, b);
     return quat;
 }
@@ -631,50 +654,59 @@
   * and/or the quaternion is normalized, then it is enough to use the conjugate.
   *
   * \sa QuaternionBase::conjugate()
   */
 template <class Derived>
-inline Quaternion<typename internal::traits<Derived>::Scalar> QuaternionBase<Derived>::inverse() const
+EIGEN_DEVICE_FUNC inline Quaternion<typename internal::traits<Derived>::Scalar> QuaternionBase<Derived>::inverse() const
 {
   // FIXME should this function be called multiplicativeInverse and conjugate() be called inverse() or opposite()  ??
   Scalar n2 = this->squaredNorm();
-  if (n2 > 0)
+  if (n2 > Scalar(0))
     return Quaternion<Scalar>(conjugate().coeffs() / n2);
   else
   {
     // return an invalid result to flag the error
     return Quaternion<Scalar>(Coefficients::Zero());
   }
 }
 
+// Generic conjugate of a Quaternion
+namespace internal {
+template<int Arch, class Derived, typename Scalar> struct quat_conj
+{
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Quaternion<Scalar> run(const QuaternionBase<Derived>& q){
+    return Quaternion<Scalar>(q.w(),-q.x(),-q.y(),-q.z());
+  }
+};
+}
+                         
 /** \returns the conjugate of the \c *this which is equal to the multiplicative inverse
   * if the quaternion is normalized.
   * The conjugate of a quaternion represents the opposite rotation.
   *
   * \sa Quaternion2::inverse()
   */
 template <class Derived>
-inline Quaternion<typename internal::traits<Derived>::Scalar>
+EIGEN_DEVICE_FUNC inline Quaternion<typename internal::traits<Derived>::Scalar>
 QuaternionBase<Derived>::conjugate() const
 {
-  return Quaternion<Scalar>(this->w(),-this->x(),-this->y(),-this->z());
+  return internal::quat_conj<Architecture::Target, Derived,
+                         typename internal::traits<Derived>::Scalar>::run(*this);
+                         
 }
 
 /** \returns the angle (in radian) between two rotations
   * \sa dot()
   */
 template <class Derived>
 template <class OtherDerived>
-inline typename internal::traits<Derived>::Scalar
+EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar
 QuaternionBase<Derived>::angularDistance(const QuaternionBase<OtherDerived>& other) const
 {
-  using std::acos;
-  using std::abs;
-  Scalar d = abs(this->dot(other));
-  if (d>=Scalar(1))
-    return Scalar(0);
-  return Scalar(2) * acos(d);
+  EIGEN_USING_STD_MATH(atan2)
+  Quaternion<Scalar> d = (*this) * other.conjugate();
+  return Scalar(2) * atan2( d.vec().norm(), numext::abs(d.w()) );
 }
 
  
     
 /** \returns the spherical linear interpolation between the two quaternions
@@ -683,19 +715,18 @@
   * This represents an interpolation for a constant motion between \c *this and \a other,
   * see also http://en.wikipedia.org/wiki/Slerp.
   */
 template <class Derived>
 template <class OtherDerived>
-Quaternion<typename internal::traits<Derived>::Scalar>
+EIGEN_DEVICE_FUNC Quaternion<typename internal::traits<Derived>::Scalar>
 QuaternionBase<Derived>::slerp(const Scalar& t, const QuaternionBase<OtherDerived>& other) const
 {
-  using std::acos;
-  using std::sin;
-  using std::abs;
-  static const Scalar one = Scalar(1) - NumTraits<Scalar>::epsilon();
+  EIGEN_USING_STD_MATH(acos)
+  EIGEN_USING_STD_MATH(sin)
+  const Scalar one = Scalar(1) - NumTraits<Scalar>::epsilon();
   Scalar d = this->dot(other);
-  Scalar absD = abs(d);
+  Scalar absD = numext::abs(d);
 
   Scalar scale0;
   Scalar scale1;
 
   if(absD>=one)
@@ -710,11 +741,11 @@
     Scalar sinTheta = sin(theta);
 
     scale0 = sin( ( Scalar(1) - t ) * theta) / sinTheta;
     scale1 = sin( ( t * theta) ) / sinTheta;
   }
-  if(d<0) scale1 = -scale1;
+  if(d<Scalar(0)) scale1 = -scale1;
 
   return Quaternion<Scalar>(scale0 * coeffs() + scale1 * other.coeffs());
 }
 
 namespace internal {
@@ -722,14 +753,14 @@
 // set from a rotation matrix
 template<typename Other>
 struct quaternionbase_assign_impl<Other,3,3>
 {
   typedef typename Other::Scalar Scalar;
-  typedef DenseIndex Index;
-  template<class Derived> static inline void run(QuaternionBase<Derived>& q, const Other& mat)
+  template<class Derived> EIGEN_DEVICE_FUNC static inline void run(QuaternionBase<Derived>& q, const Other& a_mat)
   {
-    using std::sqrt;
+    const typename internal::nested_eval<Other,2>::type mat(a_mat);
+    EIGEN_USING_STD_MATH(sqrt)
     // This algorithm comes from  "Quaternion Calculus and Fast Animation",
     // Ken Shoemake, 1987 SIGGRAPH course notes
     Scalar t = mat.trace();
     if (t > Scalar(0))
     {
@@ -740,17 +771,17 @@
       q.y() = (mat.coeff(0,2) - mat.coeff(2,0)) * t;
       q.z() = (mat.coeff(1,0) - mat.coeff(0,1)) * t;
     }
     else
     {
-      DenseIndex i = 0;
+      Index i = 0;
       if (mat.coeff(1,1) > mat.coeff(0,0))
         i = 1;
       if (mat.coeff(2,2) > mat.coeff(i,i))
         i = 2;
-      DenseIndex j = (i+1)%3;
-      DenseIndex k = (j+1)%3;
+      Index j = (i+1)%3;
+      Index k = (j+1)%3;
 
       t = sqrt(mat.coeff(i,i)-mat.coeff(j,j)-mat.coeff(k,k) + Scalar(1.0));
       q.coeffs().coeffRef(i) = Scalar(0.5) * t;
       t = Scalar(0.5)/t;
       q.w() = (mat.coeff(k,j)-mat.coeff(j,k))*t;
@@ -763,11 +794,11 @@
 // set from a vector of coefficients assumed to be a quaternion
 template<typename Other>
 struct quaternionbase_assign_impl<Other,4,1>
 {
   typedef typename Other::Scalar Scalar;
-  template<class Derived> static inline void run(QuaternionBase<Derived>& q, const Other& vec)
+  template<class Derived> EIGEN_DEVICE_FUNC static inline void run(QuaternionBase<Derived>& q, const Other& vec)
   {
     q.coeffs() = vec;
   }
 };
 

Index: 3rd_party/eigen/Eigen/src/Geometry/Rotation2D.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/Rotation2D.h
+++ 3rd_party/eigen/Eigen/src/Geometry/Rotation2D.h
@@ -16,11 +16,11 @@
   *
   * \class Rotation2D
   *
   * \brief Represents a rotation/orientation in a 2 dimensional space.
   *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
+  * \tparam _Scalar the scalar type, i.e., the type of the coefficients
   *
   * This class is equivalent to a single scalar representing a counter clock wise rotation
   * as a single angle in radian. It provides some additional features such as the automatic
   * conversion from/to a 2x2 rotation matrix. Moreover this class aims to provide a similar
   * interface to Quaternion in order to facilitate the writing of generic algorithms
@@ -57,70 +57,109 @@
   Scalar m_angle;
 
 public:
 
   /** Construct a 2D counter clock wise rotation from the angle \a a in radian. */
-  inline Rotation2D(const Scalar& a) : m_angle(a) {}
+  EIGEN_DEVICE_FUNC explicit inline Rotation2D(const Scalar& a) : m_angle(a) {}
   
   /** Default constructor wihtout initialization. The represented rotation is undefined. */
-  Rotation2D() {}
+  EIGEN_DEVICE_FUNC Rotation2D() {}
+
+  /** Construct a 2D rotation from a 2x2 rotation matrix \a mat.
+    *
+    * \sa fromRotationMatrix()
+    */
+  template<typename Derived>
+  EIGEN_DEVICE_FUNC explicit Rotation2D(const MatrixBase<Derived>& m)
+  {
+    fromRotationMatrix(m.derived());
+  }
 
   /** \returns the rotation angle */
-  inline Scalar angle() const { return m_angle; }
+  EIGEN_DEVICE_FUNC inline Scalar angle() const { return m_angle; }
 
   /** \returns a read-write reference to the rotation angle */
-  inline Scalar& angle() { return m_angle; }
+  EIGEN_DEVICE_FUNC inline Scalar& angle() { return m_angle; }
+  
+  /** \returns the rotation angle in [0,2pi] */
+  EIGEN_DEVICE_FUNC inline Scalar smallestPositiveAngle() const {
+    Scalar tmp = numext::fmod(m_angle,Scalar(2*EIGEN_PI));
+    return tmp<Scalar(0) ? tmp + Scalar(2*EIGEN_PI) : tmp;
+  }
+  
+  /** \returns the rotation angle in [-pi,pi] */
+  EIGEN_DEVICE_FUNC inline Scalar smallestAngle() const {
+    Scalar tmp = numext::fmod(m_angle,Scalar(2*EIGEN_PI));
+    if(tmp>Scalar(EIGEN_PI))       tmp -= Scalar(2*EIGEN_PI);
+    else if(tmp<-Scalar(EIGEN_PI)) tmp += Scalar(2*EIGEN_PI);
+    return tmp;
+  }
 
   /** \returns the inverse rotation */
-  inline Rotation2D inverse() const { return -m_angle; }
+  EIGEN_DEVICE_FUNC inline Rotation2D inverse() const { return Rotation2D(-m_angle); }
 
   /** Concatenates two rotations */
-  inline Rotation2D operator*(const Rotation2D& other) const
-  { return m_angle + other.m_angle; }
+  EIGEN_DEVICE_FUNC inline Rotation2D operator*(const Rotation2D& other) const
+  { return Rotation2D(m_angle + other.m_angle); }
 
   /** Concatenates two rotations */
-  inline Rotation2D& operator*=(const Rotation2D& other)
+  EIGEN_DEVICE_FUNC inline Rotation2D& operator*=(const Rotation2D& other)
   { m_angle += other.m_angle; return *this; }
 
   /** Applies the rotation to a 2D vector */
-  Vector2 operator* (const Vector2& vec) const
+  EIGEN_DEVICE_FUNC Vector2 operator* (const Vector2& vec) const
   { return toRotationMatrix() * vec; }
   
   template<typename Derived>
-  Rotation2D& fromRotationMatrix(const MatrixBase<Derived>& m);
-  Matrix2 toRotationMatrix() const;
+  EIGEN_DEVICE_FUNC Rotation2D& fromRotationMatrix(const MatrixBase<Derived>& m);
+  EIGEN_DEVICE_FUNC Matrix2 toRotationMatrix() const;
+
+  /** Set \c *this from a 2x2 rotation matrix \a mat.
+    * In other words, this function extract the rotation angle from the rotation matrix.
+    *
+    * This method is an alias for fromRotationMatrix()
+    *
+    * \sa fromRotationMatrix()
+    */
+  template<typename Derived>
+  EIGEN_DEVICE_FUNC Rotation2D& operator=(const  MatrixBase<Derived>& m)
+  { return fromRotationMatrix(m.derived()); }
 
   /** \returns the spherical interpolation between \c *this and \a other using
     * parameter \a t. It is in fact equivalent to a linear interpolation.
     */
-  inline Rotation2D slerp(const Scalar& t, const Rotation2D& other) const
-  { return m_angle * (1-t) + other.angle() * t; }
+  EIGEN_DEVICE_FUNC inline Rotation2D slerp(const Scalar& t, const Rotation2D& other) const
+  {
+    Scalar dist = Rotation2D(other.m_angle-m_angle).smallestAngle();
+    return Rotation2D(m_angle + dist*t);
+  }
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
     *
     * Note that if \a NewScalarType is equal to the current scalar type of \c *this
     * then this function smartly returns a const reference to \c *this.
     */
   template<typename NewScalarType>
-  inline typename internal::cast_return_type<Rotation2D,Rotation2D<NewScalarType> >::type cast() const
+  EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<Rotation2D,Rotation2D<NewScalarType> >::type cast() const
   { return typename internal::cast_return_type<Rotation2D,Rotation2D<NewScalarType> >::type(*this); }
 
   /** Copy constructor with scalar type conversion */
   template<typename OtherScalarType>
-  inline explicit Rotation2D(const Rotation2D<OtherScalarType>& other)
+  EIGEN_DEVICE_FUNC inline explicit Rotation2D(const Rotation2D<OtherScalarType>& other)
   {
     m_angle = Scalar(other.angle());
   }
 
-  static inline Rotation2D Identity() { return Rotation2D(0); }
+  EIGEN_DEVICE_FUNC static inline Rotation2D Identity() { return Rotation2D(0); }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const Rotation2D& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
+  EIGEN_DEVICE_FUNC bool isApprox(const Rotation2D& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return internal::isApprox(m_angle,other.m_angle, prec); }
+  
 };
 
 /** \ingroup Geometry_Module
   * single precision 2D rotation type */
 typedef Rotation2D<float> Rotation2Df;
@@ -132,29 +171,29 @@
   * In other words, this function extract the rotation angle
   * from the rotation matrix.
   */
 template<typename Scalar>
 template<typename Derived>
-Rotation2D<Scalar>& Rotation2D<Scalar>::fromRotationMatrix(const MatrixBase<Derived>& mat)
+EIGEN_DEVICE_FUNC Rotation2D<Scalar>& Rotation2D<Scalar>::fromRotationMatrix(const MatrixBase<Derived>& mat)
 {
-  using std::atan2;
+  EIGEN_USING_STD_MATH(atan2)
   EIGEN_STATIC_ASSERT(Derived::RowsAtCompileTime==2 && Derived::ColsAtCompileTime==2,YOU_MADE_A_PROGRAMMING_MISTAKE)
   m_angle = atan2(mat.coeff(1,0), mat.coeff(0,0));
   return *this;
 }
 
 /** Constructs and \returns an equivalent 2x2 rotation matrix.
   */
 template<typename Scalar>
 typename Rotation2D<Scalar>::Matrix2
-Rotation2D<Scalar>::toRotationMatrix(void) const
+EIGEN_DEVICE_FUNC Rotation2D<Scalar>::toRotationMatrix(void) const
 {
-  using std::sin;
-  using std::cos;
+  EIGEN_USING_STD_MATH(sin)
+  EIGEN_USING_STD_MATH(cos)
   Scalar sinA = sin(m_angle);
   Scalar cosA = cos(m_angle);
   return (Matrix2() << cosA, -sinA, sinA, cosA).finished();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_ROTATION2D_H

Index: 3rd_party/eigen/Eigen/src/Geometry/RotationBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/RotationBase.h
+++ 3rd_party/eigen/Eigen/src/Geometry/RotationBase.h
@@ -20,12 +20,12 @@
 
 /** \class RotationBase
   *
   * \brief Common base class for compact rotation representations
   *
-  * \param Derived is the derived type, i.e., a rotation type
-  * \param _Dim the dimension of the space
+  * \tparam Derived is the derived type, i.e., a rotation type
+  * \tparam _Dim the dimension of the space
   */
 template<typename Derived, int _Dim>
 class RotationBase
 {
   public:
@@ -36,63 +36,63 @@
     /** corresponding linear transformation matrix type */
     typedef Matrix<Scalar,Dim,Dim> RotationMatrixType;
     typedef Matrix<Scalar,Dim,1> VectorType;
 
   public:
-    inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
-    inline Derived& derived() { return *static_cast<Derived*>(this); }
+    EIGEN_DEVICE_FUNC inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    EIGEN_DEVICE_FUNC inline Derived& derived() { return *static_cast<Derived*>(this); }
 
     /** \returns an equivalent rotation matrix */
-    inline RotationMatrixType toRotationMatrix() const { return derived().toRotationMatrix(); }
+    EIGEN_DEVICE_FUNC inline RotationMatrixType toRotationMatrix() const { return derived().toRotationMatrix(); }
 
     /** \returns an equivalent rotation matrix 
       * This function is added to be conform with the Transform class' naming scheme.
       */
-    inline RotationMatrixType matrix() const { return derived().toRotationMatrix(); }
+    EIGEN_DEVICE_FUNC inline RotationMatrixType matrix() const { return derived().toRotationMatrix(); }
 
     /** \returns the inverse rotation */
-    inline Derived inverse() const { return derived().inverse(); }
+    EIGEN_DEVICE_FUNC inline Derived inverse() const { return derived().inverse(); }
 
     /** \returns the concatenation of the rotation \c *this with a translation \a t */
-    inline Transform<Scalar,Dim,Isometry> operator*(const Translation<Scalar,Dim>& t) const
+    EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Isometry> operator*(const Translation<Scalar,Dim>& t) const
     { return Transform<Scalar,Dim,Isometry>(*this) * t; }
 
     /** \returns the concatenation of the rotation \c *this with a uniform scaling \a s */
-    inline RotationMatrixType operator*(const UniformScaling<Scalar>& s) const
+    EIGEN_DEVICE_FUNC inline RotationMatrixType operator*(const UniformScaling<Scalar>& s) const
     { return toRotationMatrix() * s.factor(); }
 
     /** \returns the concatenation of the rotation \c *this with a generic expression \a e
       * \a e can be:
       *  - a DimxDim linear transformation matrix
       *  - a DimxDim diagonal matrix (axis aligned scaling)
       *  - a vector of size Dim
       */
     template<typename OtherDerived>
-    EIGEN_STRONG_INLINE typename internal::rotation_base_generic_product_selector<Derived,OtherDerived,OtherDerived::IsVectorAtCompileTime>::ReturnType
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::rotation_base_generic_product_selector<Derived,OtherDerived,OtherDerived::IsVectorAtCompileTime>::ReturnType
     operator*(const EigenBase<OtherDerived>& e) const
     { return internal::rotation_base_generic_product_selector<Derived,OtherDerived>::run(derived(), e.derived()); }
 
     /** \returns the concatenation of a linear transformation \a l with the rotation \a r */
     template<typename OtherDerived> friend
-    inline RotationMatrixType operator*(const EigenBase<OtherDerived>& l, const Derived& r)
+    EIGEN_DEVICE_FUNC inline RotationMatrixType operator*(const EigenBase<OtherDerived>& l, const Derived& r)
     { return l.derived() * r.toRotationMatrix(); }
 
     /** \returns the concatenation of a scaling \a l with the rotation \a r */
-    friend inline Transform<Scalar,Dim,Affine> operator*(const DiagonalMatrix<Scalar,Dim>& l, const Derived& r)
+    EIGEN_DEVICE_FUNC friend inline Transform<Scalar,Dim,Affine> operator*(const DiagonalMatrix<Scalar,Dim>& l, const Derived& r)
     { 
       Transform<Scalar,Dim,Affine> res(r);
       res.linear().applyOnTheLeft(l);
       return res;
     }
 
     /** \returns the concatenation of the rotation \c *this with a transformation \a t */
     template<int Mode, int Options>
-    inline Transform<Scalar,Dim,Mode> operator*(const Transform<Scalar,Dim,Mode,Options>& t) const
+    EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode> operator*(const Transform<Scalar,Dim,Mode,Options>& t) const
     { return toRotationMatrix() * t; }
 
     template<typename OtherVectorType>
-    inline VectorType _transformVector(const OtherVectorType& v) const
+    EIGEN_DEVICE_FUNC inline VectorType _transformVector(const OtherVectorType& v) const
     { return toRotationMatrix() * v; }
 };
 
 namespace internal {
 
@@ -100,19 +100,19 @@
 template<typename RotationDerived, typename MatrixType>
 struct rotation_base_generic_product_selector<RotationDerived,MatrixType,false>
 {
   enum { Dim = RotationDerived::Dim };
   typedef Matrix<typename RotationDerived::Scalar,Dim,Dim> ReturnType;
-  static inline ReturnType run(const RotationDerived& r, const MatrixType& m)
+  EIGEN_DEVICE_FUNC static inline ReturnType run(const RotationDerived& r, const MatrixType& m)
   { return r.toRotationMatrix() * m; }
 };
 
 template<typename RotationDerived, typename Scalar, int Dim, int MaxDim>
 struct rotation_base_generic_product_selector< RotationDerived, DiagonalMatrix<Scalar,Dim,MaxDim>, false >
 {
   typedef Transform<Scalar,Dim,Affine> ReturnType;
-  static inline ReturnType run(const RotationDerived& r, const DiagonalMatrix<Scalar,Dim,MaxDim>& m)
+  EIGEN_DEVICE_FUNC static inline ReturnType run(const RotationDerived& r, const DiagonalMatrix<Scalar,Dim,MaxDim>& m)
   {
     ReturnType res(r);
     res.linear() *= m;
     return res;
   }
@@ -121,11 +121,11 @@
 template<typename RotationDerived,typename OtherVectorType>
 struct rotation_base_generic_product_selector<RotationDerived,OtherVectorType,true>
 {
   enum { Dim = RotationDerived::Dim };
   typedef Matrix<typename RotationDerived::Scalar,Dim,1> ReturnType;
-  static EIGEN_STRONG_INLINE ReturnType run(const RotationDerived& r, const OtherVectorType& v)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE ReturnType run(const RotationDerived& r, const OtherVectorType& v)
   {
     return r._transformVector(v);
   }
 };
 
@@ -135,11 +135,11 @@
   *
   * \brief Constructs a Dim x Dim rotation matrix from the rotation \a r
   */
 template<typename _Scalar, int _Rows, int _Cols, int _Storage, int _MaxRows, int _MaxCols>
 template<typename OtherDerived>
-Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>
+EIGEN_DEVICE_FUNC Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>
 ::Matrix(const RotationBase<OtherDerived,ColsAtCompileTime>& r)
 {
   EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(Matrix,int(OtherDerived::Dim),int(OtherDerived::Dim))
   *this = r.toRotationMatrix();
 }
@@ -148,11 +148,11 @@
   *
   * \brief Set a Dim x Dim rotation matrix from the rotation \a r
   */
 template<typename _Scalar, int _Rows, int _Cols, int _Storage, int _MaxRows, int _MaxCols>
 template<typename OtherDerived>
-Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>&
+EIGEN_DEVICE_FUNC Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>&
 Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>
 ::operator=(const RotationBase<OtherDerived,ColsAtCompileTime>& r)
 {
   EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(Matrix,int(OtherDerived::Dim),int(OtherDerived::Dim))
   return *this = r.toRotationMatrix();
@@ -162,12 +162,12 @@
 
 /** \internal
   *
   * Helper function to return an arbitrary rotation object to a rotation matrix.
   *
-  * \param Scalar the numeric type of the matrix coefficients
-  * \param Dim the dimension of the current space
+  * \tparam Scalar the numeric type of the matrix coefficients
+  * \tparam Dim the dimension of the current space
   *
   * It returns a Dim x Dim fixed size matrix.
   *
   * Default specializations are provided for:
   *   - any scalar type (2D),
@@ -177,24 +177,24 @@
   * Currently toRotationMatrix is only used by Transform.
   *
   * \sa class Transform, class Rotation2D, class Quaternion, class AngleAxis
   */
 template<typename Scalar, int Dim>
-static inline Matrix<Scalar,2,2> toRotationMatrix(const Scalar& s)
+EIGEN_DEVICE_FUNC static inline Matrix<Scalar,2,2> toRotationMatrix(const Scalar& s)
 {
   EIGEN_STATIC_ASSERT(Dim==2,YOU_MADE_A_PROGRAMMING_MISTAKE)
   return Rotation2D<Scalar>(s).toRotationMatrix();
 }
 
 template<typename Scalar, int Dim, typename OtherDerived>
-static inline Matrix<Scalar,Dim,Dim> toRotationMatrix(const RotationBase<OtherDerived,Dim>& r)
+EIGEN_DEVICE_FUNC static inline Matrix<Scalar,Dim,Dim> toRotationMatrix(const RotationBase<OtherDerived,Dim>& r)
 {
   return r.toRotationMatrix();
 }
 
 template<typename Scalar, int Dim, typename OtherDerived>
-static inline const MatrixBase<OtherDerived>& toRotationMatrix(const MatrixBase<OtherDerived>& mat)
+EIGEN_DEVICE_FUNC static inline const MatrixBase<OtherDerived>& toRotationMatrix(const MatrixBase<OtherDerived>& mat)
 {
   EIGEN_STATIC_ASSERT(OtherDerived::RowsAtCompileTime==Dim && OtherDerived::ColsAtCompileTime==Dim,
     YOU_MADE_A_PROGRAMMING_MISTAKE)
   return mat;
 }

Index: 3rd_party/eigen/Eigen/src/Geometry/Scaling.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/Scaling.h
+++ 3rd_party/eigen/Eigen/src/Geometry/Scaling.h
@@ -16,11 +16,11 @@
   *
   * \class Scaling
   *
   * \brief Represents a generic uniform scaling transformation
   *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients.
+  * \tparam _Scalar the scalar type, i.e., the type of the coefficients.
   *
   * This class represent a uniform scaling transformation. It is the return
   * type of Scaling(Scalar), and most of the time this is the only way it
   * is used. In particular, this class is not aimed to be used to store a scaling transformation,
   * but rather to make easier the constructions and updates of Transform objects.
@@ -60,14 +60,14 @@
 
   /** Concatenates a uniform scaling and an affine transformation */
   template<int Dim, int Mode, int Options>
   inline Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Mode)> operator* (const Transform<Scalar,Dim, Mode, Options>& t) const
   {
-   Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Mode)> res = t;
-   res.prescale(factor());
-   return res;
-}
+    Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Mode)> res = t;
+    res.prescale(factor());
+    return res;
+  }
 
   /** Concatenates a uniform scaling and a linear transformation matrix */
   // TODO returns an expression
   template<typename Derived>
   inline typename internal::plain_matrix_type<Derived>::type operator* (const MatrixBase<Derived>& other) const
@@ -102,44 +102,48 @@
   bool isApprox(const UniformScaling& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return internal::isApprox(m_factor, other.factor(), prec); }
 
 };
 
-/** Concatenates a linear transformation matrix and a uniform scaling */
+/** \addtogroup Geometry_Module */
+//@{
+
+/** Concatenates a linear transformation matrix and a uniform scaling
+  * \relates UniformScaling
+  */
 // NOTE this operator is defiend in MatrixBase and not as a friend function
 // of UniformScaling to fix an internal crash of Intel's ICC
-template<typename Derived> typename MatrixBase<Derived>::ScalarMultipleReturnType
-MatrixBase<Derived>::operator*(const UniformScaling<Scalar>& s) const
-{ return derived() * s.factor(); }
-
-/** Constructs a uniform scaling from scale factor \a s */
-static inline UniformScaling<float> Scaling(float s) { return UniformScaling<float>(s); }
-/** Constructs a uniform scaling from scale factor \a s */
-static inline UniformScaling<double> Scaling(double s) { return UniformScaling<double>(s); }
+template<typename Derived,typename Scalar>
+EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,Scalar,product)
+operator*(const MatrixBase<Derived>& matrix, const UniformScaling<Scalar>& s)
+{ return matrix.derived() * s.factor(); }
+
+/** Constructs a uniform scaling from scale factor \a s */
+inline UniformScaling<float> Scaling(float s) { return UniformScaling<float>(s); }
+/** Constructs a uniform scaling from scale factor \a s */
+inline UniformScaling<double> Scaling(double s) { return UniformScaling<double>(s); }
 /** Constructs a uniform scaling from scale factor \a s */
 template<typename RealScalar>
-static inline UniformScaling<std::complex<RealScalar> > Scaling(const std::complex<RealScalar>& s)
+inline UniformScaling<std::complex<RealScalar> > Scaling(const std::complex<RealScalar>& s)
 { return UniformScaling<std::complex<RealScalar> >(s); }
 
 /** Constructs a 2D axis aligned scaling */
 template<typename Scalar>
-static inline DiagonalMatrix<Scalar,2> Scaling(const Scalar& sx, const Scalar& sy)
+inline DiagonalMatrix<Scalar,2> Scaling(const Scalar& sx, const Scalar& sy)
 { return DiagonalMatrix<Scalar,2>(sx, sy); }
 /** Constructs a 3D axis aligned scaling */
 template<typename Scalar>
-static inline DiagonalMatrix<Scalar,3> Scaling(const Scalar& sx, const Scalar& sy, const Scalar& sz)
+inline DiagonalMatrix<Scalar,3> Scaling(const Scalar& sx, const Scalar& sy, const Scalar& sz)
 { return DiagonalMatrix<Scalar,3>(sx, sy, sz); }
 
 /** Constructs an axis aligned scaling expression from vector expression \a coeffs
   * This is an alias for coeffs.asDiagonal()
   */
 template<typename Derived>
-static inline const DiagonalWrapper<const Derived> Scaling(const MatrixBase<Derived>& coeffs)
+inline const DiagonalWrapper<const Derived> Scaling(const MatrixBase<Derived>& coeffs)
 { return coeffs.asDiagonal(); }
 
-/** \addtogroup Geometry_Module */
-//@{
 /** \deprecated */
 typedef DiagonalMatrix<float, 2> AlignedScaling2f;
 /** \deprecated */
 typedef DiagonalMatrix<double,2> AlignedScaling2d;
 /** \deprecated */

Index: 3rd_party/eigen/Eigen/src/Geometry/Transform.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/Transform.h
+++ 3rd_party/eigen/Eigen/src/Geometry/Transform.h
@@ -30,11 +30,12 @@
 
 template< typename TransformType,
           typename MatrixType,
           int Case = transform_traits<TransformType>::IsProjective ? 0
                    : int(MatrixType::RowsAtCompileTime) == int(transform_traits<TransformType>::HDim) ? 1
-                   : 2>
+                   : 2,
+          int RhsCols = MatrixType::ColsAtCompileTime>
 struct transform_right_product_impl;
 
 template< typename Other,
           int Mode,
           int Options,
@@ -59,10 +60,26 @@
           int OtherRows=Other::RowsAtCompileTime,
           int OtherCols=Other::ColsAtCompileTime>
 struct transform_construct_from_matrix;
 
 template<typename TransformType> struct transform_take_affine_part;
+
+template<typename _Scalar, int _Dim, int _Mode, int _Options>
+struct traits<Transform<_Scalar,_Dim,_Mode,_Options> >
+{
+  typedef _Scalar Scalar;
+  typedef Eigen::Index StorageIndex;
+  typedef Dense StorageKind;
+  enum {
+    Dim1 = _Dim==Dynamic ? _Dim : _Dim + 1,
+    RowsAtCompileTime = _Mode==Projective ? Dim1 : _Dim,
+    ColsAtCompileTime = Dim1,
+    MaxRowsAtCompileTime = RowsAtCompileTime,
+    MaxColsAtCompileTime = ColsAtCompileTime,
+    Flags = 0
+  };
+};
 
 template<int Mode> struct transform_make_affine;
 
 } // end namespace internal
 
@@ -100,19 +117,19 @@
   * Note that for a projective transformation the last row can be anything,
   * and then the interpretation of different parts might be sightly different.
   *
   * However, unlike a plain matrix, the Transform class provides many features
   * simplifying both its assembly and usage. In particular, it can be composed
-  * with any other transformations (Transform,Translation,RotationBase,Matrix)
+  * with any other transformations (Transform,Translation,RotationBase,DiagonalMatrix)
   * and can be directly used to transform implicit homogeneous vectors. All these
   * operations are handled via the operator*. For the composition of transformations,
   * its principle consists to first convert the right/left hand sides of the product
   * to a compatible (Dim+1)^2 matrix and then perform a pure matrix product.
   * Of course, internally, operator* tries to perform the minimal number of operations
   * according to the nature of each terms. Likewise, when applying the transform
-  * to non homogeneous vectors, the latters are automatically promoted to homogeneous
-  * one before doing the matrix product. The convertions to homogeneous representations
+  * to points, the latters are automatically promoted to homogeneous vectors
+  * before doing the matrix product. The conventions to homogeneous representations
   * are performed as follow:
   *
   * \b Translation t (Dim)x(1):
   * \f$ \left( \begin{array}{cc}
   * I & t \\
@@ -122,11 +139,11 @@
   * \b Rotation R (Dim)x(Dim):
   * \f$ \left( \begin{array}{cc}
   * R & 0\\
   * 0\,...\,0 & 1
   * \end{array} \right) \f$
-  *
+  *<!--
   * \b Linear \b Matrix L (Dim)x(Dim):
   * \f$ \left( \begin{array}{cc}
   * L & 0\\
   * 0\,...\,0 & 1
   * \end{array} \right) \f$
@@ -134,18 +151,24 @@
   * \b Affine \b Matrix A (Dim)x(Dim+1):
   * \f$ \left( \begin{array}{c}
   * A\\
   * 0\,...\,0\,1
   * \end{array} \right) \f$
+  *-->
+  * \b Scaling \b DiagonalMatrix S (Dim)x(Dim):
+  * \f$ \left( \begin{array}{cc}
+  * S & 0\\
+  * 0\,...\,0 & 1
+  * \end{array} \right) \f$
   *
-  * \b Column \b vector v (Dim)x(1):
+  * \b Column \b point v (Dim)x(1):
   * \f$ \left( \begin{array}{c}
   * v\\
   * 1
   * \end{array} \right) \f$
   *
-  * \b Set \b of \b column \b vectors V1...Vn (Dim)x(n):
+  * \b Set \b of \b column \b points V1...Vn (Dim)x(n):
   * \f$ \left( \begin{array}{ccc}
   * v_1 & ... & v_n\\
   * 1 & ... & 1
   * \end{array} \right) \f$
   *
@@ -168,11 +191,11 @@
   *
   * Conversion methods from/to Qt's QMatrix and QTransform are available if the
   * preprocessor token EIGEN_QT_SUPPORT is defined.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_TRANSFORM_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_TRANSFORM_PLUGIN.
   *
   * \sa class Matrix, class Quaternion
   */
 template<typename _Scalar, int _Dim, int _Mode, int _Options>
 class Transform
@@ -186,11 +209,12 @@
     HDim = _Dim+1,  ///< size of a respective homogeneous vector
     Rows = int(Mode)==(AffineCompact) ? Dim : HDim
   };
   /** the scalar type of the coefficients */
   typedef _Scalar Scalar;
-  typedef DenseIndex Index;
+  typedef Eigen::Index StorageIndex;
+  typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
   /** type of the matrix used to represent the transformation */
   typedef typename internal::make_proper_matrix_type<Scalar,Rows,HDim,Options>::type MatrixType;
   /** constified MatrixType */
   typedef const MatrixType ConstMatrixType;
   /** type of the matrix used to represent the linear part of the transformation */
@@ -208,13 +232,13 @@
                               const MatrixType&,
                               const Block<const MatrixType,Dim,HDim> >::type ConstAffinePart;
   /** type of a vector */
   typedef Matrix<Scalar,Dim,1> VectorType;
   /** type of a read/write reference to the translation part of the rotation */
-  typedef Block<MatrixType,Dim,1,int(Mode)==(AffineCompact)> TranslationPart;
+  typedef Block<MatrixType,Dim,1,!(internal::traits<MatrixType>::Flags & RowMajorBit)> TranslationPart;
   /** type of a read reference to the translation part of the rotation */
-  typedef const Block<ConstMatrixType,Dim,1,int(Mode)==(AffineCompact)> ConstTranslationPart;
+  typedef const Block<ConstMatrixType,Dim,1,!(internal::traits<MatrixType>::Flags & RowMajorBit)> ConstTranslationPart;
   /** corresponding translation type */
   typedef Translation<Scalar,Dim> TranslationType;
   
   // this intermediate enum is needed to avoid an ICE with gcc 3.4 and 4.0
   enum { TransformTimeDiagonalMode = ((Mode==int(Isometry))?Affine:int(Mode)) };
@@ -227,47 +251,47 @@
 
 public:
 
   /** Default constructor without initialization of the meaningful coefficients.
     * If Mode==Affine, then the last row is set to [0 ... 0 1] */
-  inline Transform()
+  EIGEN_DEVICE_FUNC inline Transform()
   {
     check_template_params();
     internal::transform_make_affine<(int(Mode)==Affine) ? Affine : AffineCompact>::run(m_matrix);
   }
 
-  inline Transform(const Transform& other)
+  EIGEN_DEVICE_FUNC inline Transform(const Transform& other)
   {
     check_template_params();
     m_matrix = other.m_matrix;
   }
 
-  inline explicit Transform(const TranslationType& t)
+  EIGEN_DEVICE_FUNC inline explicit Transform(const TranslationType& t)
   {
     check_template_params();
     *this = t;
   }
-  inline explicit Transform(const UniformScaling<Scalar>& s)
+  EIGEN_DEVICE_FUNC inline explicit Transform(const UniformScaling<Scalar>& s)
   {
     check_template_params();
     *this = s;
   }
   template<typename Derived>
-  inline explicit Transform(const RotationBase<Derived, Dim>& r)
+  EIGEN_DEVICE_FUNC inline explicit Transform(const RotationBase<Derived, Dim>& r)
   {
     check_template_params();
     *this = r;
   }
 
-  inline Transform& operator=(const Transform& other)
+  EIGEN_DEVICE_FUNC inline Transform& operator=(const Transform& other)
   { m_matrix = other.m_matrix; return *this; }
 
   typedef internal::transform_take_affine_part<Transform> take_affine_part;
 
   /** Constructs and initializes a transformation from a Dim^2 or a (Dim+1)^2 matrix. */
   template<typename OtherDerived>
-  inline explicit Transform(const EigenBase<OtherDerived>& other)
+  EIGEN_DEVICE_FUNC inline explicit Transform(const EigenBase<OtherDerived>& other)
   {
     EIGEN_STATIC_ASSERT((internal::is_same<Scalar,typename OtherDerived::Scalar>::value),
       YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY);
 
     check_template_params();
@@ -274,29 +298,29 @@
     internal::transform_construct_from_matrix<OtherDerived,Mode,Options,Dim,HDim>::run(this, other.derived());
   }
 
   /** Set \c *this from a Dim^2 or (Dim+1)^2 matrix. */
   template<typename OtherDerived>
-  inline Transform& operator=(const EigenBase<OtherDerived>& other)
+  EIGEN_DEVICE_FUNC inline Transform& operator=(const EigenBase<OtherDerived>& other)
   {
     EIGEN_STATIC_ASSERT((internal::is_same<Scalar,typename OtherDerived::Scalar>::value),
       YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY);
 
     internal::transform_construct_from_matrix<OtherDerived,Mode,Options,Dim,HDim>::run(this, other.derived());
     return *this;
   }
   
   template<int OtherOptions>
-  inline Transform(const Transform<Scalar,Dim,Mode,OtherOptions>& other)
+  EIGEN_DEVICE_FUNC inline Transform(const Transform<Scalar,Dim,Mode,OtherOptions>& other)
   {
     check_template_params();
     // only the options change, we can directly copy the matrices
     m_matrix = other.matrix();
   }
 
   template<int OtherMode,int OtherOptions>
-  inline Transform(const Transform<Scalar,Dim,OtherMode,OtherOptions>& other)
+  EIGEN_DEVICE_FUNC inline Transform(const Transform<Scalar,Dim,OtherMode,OtherOptions>& other)
   {
     check_template_params();
     // prevent conversions as:
     // Affine | AffineCompact | Isometry = Projective
     EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(OtherMode==int(Projective), Mode==int(Projective)),
@@ -333,18 +357,18 @@
       translation() = other.translation();
     }
   }
 
   template<typename OtherDerived>
-  Transform(const ReturnByValue<OtherDerived>& other)
+  EIGEN_DEVICE_FUNC Transform(const ReturnByValue<OtherDerived>& other)
   {
     check_template_params();
     other.evalTo(*this);
   }
 
   template<typename OtherDerived>
-  Transform& operator=(const ReturnByValue<OtherDerived>& other)
+  EIGEN_DEVICE_FUNC Transform& operator=(const ReturnByValue<OtherDerived>& other)
   {
     other.evalTo(*this);
     return *this;
   }
 
@@ -354,64 +378,80 @@
   inline QMatrix toQMatrix(void) const;
   inline Transform(const QTransform& other);
   inline Transform& operator=(const QTransform& other);
   inline QTransform toQTransform(void) const;
   #endif
+  
+  EIGEN_DEVICE_FUNC Index rows() const { return int(Mode)==int(Projective) ? m_matrix.cols() : (m_matrix.cols()-1); }
+  EIGEN_DEVICE_FUNC Index cols() const { return m_matrix.cols(); }
 
   /** shortcut for m_matrix(row,col);
     * \sa MatrixBase::operator(Index,Index) const */
-  inline Scalar operator() (Index row, Index col) const { return m_matrix(row,col); }
+  EIGEN_DEVICE_FUNC inline Scalar operator() (Index row, Index col) const { return m_matrix(row,col); }
   /** shortcut for m_matrix(row,col);
     * \sa MatrixBase::operator(Index,Index) */
-  inline Scalar& operator() (Index row, Index col) { return m_matrix(row,col); }
+  EIGEN_DEVICE_FUNC inline Scalar& operator() (Index row, Index col) { return m_matrix(row,col); }
 
   /** \returns a read-only expression of the transformation matrix */
-  inline const MatrixType& matrix() const { return m_matrix; }
+  EIGEN_DEVICE_FUNC inline const MatrixType& matrix() const { return m_matrix; }
   /** \returns a writable expression of the transformation matrix */
-  inline MatrixType& matrix() { return m_matrix; }
+  EIGEN_DEVICE_FUNC inline MatrixType& matrix() { return m_matrix; }
 
   /** \returns a read-only expression of the linear part of the transformation */
-  inline ConstLinearPart linear() const { return ConstLinearPart(m_matrix,0,0); }
+  EIGEN_DEVICE_FUNC inline ConstLinearPart linear() const { return ConstLinearPart(m_matrix,0,0); }
   /** \returns a writable expression of the linear part of the transformation */
-  inline LinearPart linear() { return LinearPart(m_matrix,0,0); }
+  EIGEN_DEVICE_FUNC inline LinearPart linear() { return LinearPart(m_matrix,0,0); }
 
   /** \returns a read-only expression of the Dim x HDim affine part of the transformation */
-  inline ConstAffinePart affine() const { return take_affine_part::run(m_matrix); }
+  EIGEN_DEVICE_FUNC inline ConstAffinePart affine() const { return take_affine_part::run(m_matrix); }
   /** \returns a writable expression of the Dim x HDim affine part of the transformation */
-  inline AffinePart affine() { return take_affine_part::run(m_matrix); }
+  EIGEN_DEVICE_FUNC inline AffinePart affine() { return take_affine_part::run(m_matrix); }
 
   /** \returns a read-only expression of the translation vector of the transformation */
-  inline ConstTranslationPart translation() const { return ConstTranslationPart(m_matrix,0,Dim); }
+  EIGEN_DEVICE_FUNC inline ConstTranslationPart translation() const { return ConstTranslationPart(m_matrix,0,Dim); }
   /** \returns a writable expression of the translation vector of the transformation */
-  inline TranslationPart translation() { return TranslationPart(m_matrix,0,Dim); }
+  EIGEN_DEVICE_FUNC inline TranslationPart translation() { return TranslationPart(m_matrix,0,Dim); }
 
-  /** \returns an expression of the product between the transform \c *this and a matrix expression \a other
+  /** \returns an expression of the product between the transform \c *this and a matrix expression \a other.
     *
-    * The right hand side \a other might be either:
-    * \li a vector of size Dim,
+    * The right-hand-side \a other can be either:
     * \li an homogeneous vector of size Dim+1,
-    * \li a set of vectors of size Dim x Dynamic,
-    * \li a set of homogeneous vectors of size Dim+1 x Dynamic,
-    * \li a linear transformation matrix of size Dim x Dim,
-    * \li an affine transformation matrix of size Dim x Dim+1,
+    * \li a set of homogeneous vectors of size Dim+1 x N,
     * \li a transformation matrix of size Dim+1 x Dim+1.
+    *
+    * Moreover, if \c *this represents an affine transformation (i.e., Mode!=Projective), then \a other can also be:
+    * \li a point of size Dim (computes: \code this->linear() * other + this->translation()\endcode),
+    * \li a set of N points as a Dim x N matrix (computes: \code (this->linear() * other).colwise() + this->translation()\endcode),
+    *
+    * In all cases, the return type is a matrix or vector of same sizes as the right-hand-side \a other.
+    *
+    * If you want to interpret \a other as a linear or affine transformation, then first convert it to a Transform<> type,
+    * or do your own cooking.
+    *
+    * Finally, if you want to apply Affine transformations to vectors, then explicitly apply the linear part only:
+    * \code
+    * Affine3f A;
+    * Vector3f v1, v2;
+    * v2 = A.linear() * v1;
+    * \endcode
+    *
     */
   // note: this function is defined here because some compilers cannot find the respective declaration
   template<typename OtherDerived>
-  EIGEN_STRONG_INLINE const typename internal::transform_right_product_impl<Transform, OtherDerived>::ResultType
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename internal::transform_right_product_impl<Transform, OtherDerived>::ResultType
   operator * (const EigenBase<OtherDerived> &other) const
   { return internal::transform_right_product_impl<Transform, OtherDerived>::run(*this,other.derived()); }
 
   /** \returns the product expression of a transformation matrix \a a times a transform \a b
     *
-    * The left hand side \a other might be either:
+    * The left hand side \a other can be either:
     * \li a linear transformation matrix of size Dim x Dim,
     * \li an affine transformation matrix of size Dim x Dim+1,
     * \li a general transformation matrix of size Dim+1 x Dim+1.
     */
   template<typename OtherDerived> friend
-  inline const typename internal::transform_left_product_impl<OtherDerived,Mode,Options,_Dim,_Dim+1>::ResultType
+  EIGEN_DEVICE_FUNC inline const typename internal::transform_left_product_impl<OtherDerived,Mode,Options,_Dim,_Dim+1>::ResultType
     operator * (const EigenBase<OtherDerived> &a, const Transform &b)
   { return internal::transform_left_product_impl<OtherDerived,Mode,Options,Dim,HDim>::run(a.derived(),b); }
 
   /** \returns The product expression of a transform \a a times a diagonal matrix \a b
     *
@@ -418,15 +458,15 @@
     * The rhs diagonal matrix is interpreted as an affine scaling transformation. The
     * product results in a Transform of the same type (mode) as the lhs only if the lhs 
     * mode is no isometry. In that case, the returned transform is an affinity.
     */
   template<typename DiagonalDerived>
-  inline const TransformTimeDiagonalReturnType
+  EIGEN_DEVICE_FUNC inline const TransformTimeDiagonalReturnType
     operator * (const DiagonalBase<DiagonalDerived> &b) const
   {
     TransformTimeDiagonalReturnType res(*this);
-    res.linear() *= b;
+    res.linearExt() *= b;
     return res;
   }
 
   /** \returns The product expression of a diagonal matrix \a a times a transform \a b
     *
@@ -433,11 +473,11 @@
     * The lhs diagonal matrix is interpreted as an affine scaling transformation. The
     * product results in a Transform of the same type (mode) as the lhs only if the lhs 
     * mode is no isometry. In that case, the returned transform is an affinity.
     */
   template<typename DiagonalDerived>
-  friend inline TransformTimeDiagonalReturnType
+  EIGEN_DEVICE_FUNC friend inline TransformTimeDiagonalReturnType
     operator * (const DiagonalBase<DiagonalDerived> &a, const Transform &b)
   {
     TransformTimeDiagonalReturnType res;
     res.linear().noalias() = a*b.linear();
     res.translation().noalias() = a*b.translation();
@@ -445,19 +485,19 @@
       res.matrix().row(Dim) = b.matrix().row(Dim);
     return res;
   }
 
   template<typename OtherDerived>
-  inline Transform& operator*=(const EigenBase<OtherDerived>& other) { return *this = *this * other; }
+  EIGEN_DEVICE_FUNC inline Transform& operator*=(const EigenBase<OtherDerived>& other) { return *this = *this * other; }
 
   /** Concatenates two transformations */
-  inline const Transform operator * (const Transform& other) const
+  EIGEN_DEVICE_FUNC inline const Transform operator * (const Transform& other) const
   {
     return internal::transform_transform_product_impl<Transform,Transform>::run(*this,other);
   }
   
-  #ifdef __INTEL_COMPILER
+  #if EIGEN_COMP_ICC
 private:
   // this intermediate structure permits to workaround a bug in ICC 11:
   //   error: template instantiation resulted in unexpected function type of "Eigen::Transform<double, 3, 32, 0>
   //             (const Eigen::Transform<double, 3, 2, 0> &) const"
   //  (the meaning of a name may have changed since the template declaration -- the type of the template is:
@@ -480,157 +520,176 @@
     return ProductType::run(*this,other);
   }
   #else
   /** Concatenates two different transformations */
   template<int OtherMode,int OtherOptions>
-  inline typename internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> >::ResultType
+  EIGEN_DEVICE_FUNC inline typename internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> >::ResultType
     operator * (const Transform<Scalar,Dim,OtherMode,OtherOptions>& other) const
   {
     return internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> >::run(*this,other);
   }
   #endif
 
   /** \sa MatrixBase::setIdentity() */
-  void setIdentity() { m_matrix.setIdentity(); }
+  EIGEN_DEVICE_FUNC void setIdentity() { m_matrix.setIdentity(); }
 
   /**
    * \brief Returns an identity transformation.
    * \todo In the future this function should be returning a Transform expression.
    */
-  static const Transform Identity()
+  EIGEN_DEVICE_FUNC static const Transform Identity()
   {
     return Transform(MatrixType::Identity());
   }
 
   template<typename OtherDerived>
+  EIGEN_DEVICE_FUNC 
   inline Transform& scale(const MatrixBase<OtherDerived> &other);
 
   template<typename OtherDerived>
+  EIGEN_DEVICE_FUNC
   inline Transform& prescale(const MatrixBase<OtherDerived> &other);
 
-  inline Transform& scale(const Scalar& s);
-  inline Transform& prescale(const Scalar& s);
+  EIGEN_DEVICE_FUNC inline Transform& scale(const Scalar& s);
+  EIGEN_DEVICE_FUNC inline Transform& prescale(const Scalar& s);
 
   template<typename OtherDerived>
+  EIGEN_DEVICE_FUNC
   inline Transform& translate(const MatrixBase<OtherDerived> &other);
 
   template<typename OtherDerived>
+  EIGEN_DEVICE_FUNC
   inline Transform& pretranslate(const MatrixBase<OtherDerived> &other);
 
   template<typename RotationType>
+  EIGEN_DEVICE_FUNC
   inline Transform& rotate(const RotationType& rotation);
 
   template<typename RotationType>
+  EIGEN_DEVICE_FUNC
   inline Transform& prerotate(const RotationType& rotation);
 
-  Transform& shear(const Scalar& sx, const Scalar& sy);
-  Transform& preshear(const Scalar& sx, const Scalar& sy);
+  EIGEN_DEVICE_FUNC Transform& shear(const Scalar& sx, const Scalar& sy);
+  EIGEN_DEVICE_FUNC Transform& preshear(const Scalar& sx, const Scalar& sy);
 
-  inline Transform& operator=(const TranslationType& t);
+  EIGEN_DEVICE_FUNC inline Transform& operator=(const TranslationType& t);
+  
+  EIGEN_DEVICE_FUNC
   inline Transform& operator*=(const TranslationType& t) { return translate(t.vector()); }
-  inline Transform operator*(const TranslationType& t) const;
+  
+  EIGEN_DEVICE_FUNC inline Transform operator*(const TranslationType& t) const;
 
+  EIGEN_DEVICE_FUNC 
   inline Transform& operator=(const UniformScaling<Scalar>& t);
+  
+  EIGEN_DEVICE_FUNC
   inline Transform& operator*=(const UniformScaling<Scalar>& s) { return scale(s.factor()); }
-  inline Transform<Scalar,Dim,(int(Mode)==int(Isometry)?int(Affine):int(Mode))> operator*(const UniformScaling<Scalar>& s) const
+  
+  EIGEN_DEVICE_FUNC
+  inline TransformTimeDiagonalReturnType operator*(const UniformScaling<Scalar>& s) const
   {
-    Transform<Scalar,Dim,(int(Mode)==int(Isometry)?int(Affine):int(Mode)),Options> res = *this;
+    TransformTimeDiagonalReturnType res = *this;
     res.scale(s.factor());
     return res;
   }
 
-  inline Transform& operator*=(const DiagonalMatrix<Scalar,Dim>& s) { linear() *= s; return *this; }
-
-  template<typename Derived>
-  inline Transform& operator=(const RotationBase<Derived,Dim>& r);
-  template<typename Derived>
-  inline Transform& operator*=(const RotationBase<Derived,Dim>& r) { return rotate(r.toRotationMatrix()); }
-  template<typename Derived>
-  inline Transform operator*(const RotationBase<Derived,Dim>& r) const;
-
-  const LinearMatrixType rotation() const;
-  template<typename RotationMatrixType, typename ScalingMatrixType>
+  EIGEN_DEVICE_FUNC
+  inline Transform& operator*=(const DiagonalMatrix<Scalar,Dim>& s) { linearExt() *= s; return *this; }
+
+  template<typename Derived>
+  EIGEN_DEVICE_FUNC inline Transform& operator=(const RotationBase<Derived,Dim>& r);
+  template<typename Derived>
+  EIGEN_DEVICE_FUNC inline Transform& operator*=(const RotationBase<Derived,Dim>& r) { return rotate(r.toRotationMatrix()); }
+  template<typename Derived>
+  EIGEN_DEVICE_FUNC inline Transform operator*(const RotationBase<Derived,Dim>& r) const;
+
+  EIGEN_DEVICE_FUNC const LinearMatrixType rotation() const;
+  template<typename RotationMatrixType, typename ScalingMatrixType>
+  EIGEN_DEVICE_FUNC
   void computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const;
   template<typename ScalingMatrixType, typename RotationMatrixType>
+  EIGEN_DEVICE_FUNC
   void computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const;
 
   template<typename PositionDerived, typename OrientationType, typename ScaleDerived>
+  EIGEN_DEVICE_FUNC
   Transform& fromPositionOrientationScale(const MatrixBase<PositionDerived> &position,
     const OrientationType& orientation, const MatrixBase<ScaleDerived> &scale);
 
+  EIGEN_DEVICE_FUNC
   inline Transform inverse(TransformTraits traits = (TransformTraits)Mode) const;
 
   /** \returns a const pointer to the column major internal matrix */
-  const Scalar* data() const { return m_matrix.data(); }
+  EIGEN_DEVICE_FUNC const Scalar* data() const { return m_matrix.data(); }
   /** \returns a non-const pointer to the column major internal matrix */
-  Scalar* data() { return m_matrix.data(); }
+  EIGEN_DEVICE_FUNC Scalar* data() { return m_matrix.data(); }
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
     *
     * Note that if \a NewScalarType is equal to the current scalar type of \c *this
     * then this function smartly returns a const reference to \c *this.
     */
   template<typename NewScalarType>
-  inline typename internal::cast_return_type<Transform,Transform<NewScalarType,Dim,Mode,Options> >::type cast() const
+  EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<Transform,Transform<NewScalarType,Dim,Mode,Options> >::type cast() const
   { return typename internal::cast_return_type<Transform,Transform<NewScalarType,Dim,Mode,Options> >::type(*this); }
 
   /** Copy constructor with scalar type conversion */
   template<typename OtherScalarType>
-  inline explicit Transform(const Transform<OtherScalarType,Dim,Mode,Options>& other)
+  EIGEN_DEVICE_FUNC inline explicit Transform(const Transform<OtherScalarType,Dim,Mode,Options>& other)
   {
     check_template_params();
     m_matrix = other.matrix().template cast<Scalar>();
   }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const Transform& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
+  EIGEN_DEVICE_FUNC bool isApprox(const Transform& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return m_matrix.isApprox(other.m_matrix, prec); }
 
   /** Sets the last row to [0 ... 0 1]
     */
-  void makeAffine()
+  EIGEN_DEVICE_FUNC void makeAffine()
   {
     internal::transform_make_affine<int(Mode)>::run(m_matrix);
   }
 
   /** \internal
     * \returns the Dim x Dim linear part if the transformation is affine,
     *          and the HDim x Dim part for projective transformations.
     */
-  inline Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,Dim> linearExt()
+  EIGEN_DEVICE_FUNC inline Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,Dim> linearExt()
   { return m_matrix.template block<int(Mode)==int(Projective)?HDim:Dim,Dim>(0,0); }
   /** \internal
     * \returns the Dim x Dim linear part if the transformation is affine,
     *          and the HDim x Dim part for projective transformations.
     */
-  inline const Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,Dim> linearExt() const
+  EIGEN_DEVICE_FUNC inline const Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,Dim> linearExt() const
   { return m_matrix.template block<int(Mode)==int(Projective)?HDim:Dim,Dim>(0,0); }
 
   /** \internal
     * \returns the translation part if the transformation is affine,
     *          and the last column for projective transformations.
     */
-  inline Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,1> translationExt()
+  EIGEN_DEVICE_FUNC inline Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,1> translationExt()
   { return m_matrix.template block<int(Mode)==int(Projective)?HDim:Dim,1>(0,Dim); }
   /** \internal
     * \returns the translation part if the transformation is affine,
     *          and the last column for projective transformations.
     */
-  inline const Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,1> translationExt() const
+  EIGEN_DEVICE_FUNC inline const Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,1> translationExt() const
   { return m_matrix.template block<int(Mode)==int(Projective)?HDim:Dim,1>(0,Dim); }
 
 
   #ifdef EIGEN_TRANSFORM_PLUGIN
   #include EIGEN_TRANSFORM_PLUGIN
   #endif
   
 protected:
   #ifndef EIGEN_PARSED_BY_DOXYGEN
-    static EIGEN_STRONG_INLINE void check_template_params()
+    EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void check_template_params()
     {
       EIGEN_STATIC_ASSERT((Options & (DontAlign|RowMajor)) == Options, INVALID_MATRIX_TEMPLATE_PARAMETERS)
     }
   #endif
 
@@ -694,13 +753,17 @@
   */
 template<typename Scalar, int Dim, int Mode,int Options>
 Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const QMatrix& other)
 {
   EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  m_matrix << other.m11(), other.m21(), other.dx(),
-              other.m12(), other.m22(), other.dy(),
-              0, 0, 1;
+  if (Mode == int(AffineCompact))
+    m_matrix << other.m11(), other.m21(), other.dx(),
+                other.m12(), other.m22(), other.dy();
+  else
+    m_matrix << other.m11(), other.m21(), other.dx(),
+                other.m12(), other.m22(), other.dy(),
+                0, 0, 1;
   return *this;
 }
 
 /** \returns a QMatrix from \c *this assuming the dimension is 2.
   *
@@ -775,11 +838,11 @@
   * by the vector \a other to \c *this and returns a reference to \c *this.
   * \sa prescale()
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename OtherDerived>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::scale(const MatrixBase<OtherDerived> &other)
 {
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
   linearExt().noalias() = (linearExt() * other.asDiagonal());
@@ -789,11 +852,11 @@
 /** Applies on the right a uniform scale of a factor \a c to \c *this
   * and returns a reference to \c *this.
   * \sa prescale(Scalar)
   */
 template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::scale(const Scalar& s)
+EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::scale(const Scalar& s)
 {
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
   linearExt() *= s;
   return *this;
 }
@@ -802,25 +865,25 @@
   * by the vector \a other to \c *this and returns a reference to \c *this.
   * \sa scale()
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename OtherDerived>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::prescale(const MatrixBase<OtherDerived> &other)
 {
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
-  m_matrix.template block<Dim,HDim>(0,0).noalias() = (other.asDiagonal() * m_matrix.template block<Dim,HDim>(0,0));
+  affine().noalias() = (other.asDiagonal() * affine());
   return *this;
 }
 
 /** Applies on the left a uniform scale of a factor \a c to \c *this
   * and returns a reference to \c *this.
   * \sa scale(Scalar)
   */
 template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::prescale(const Scalar& s)
+EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::prescale(const Scalar& s)
 {
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
   m_matrix.template topRows<Dim>() *= s;
   return *this;
 }
@@ -829,11 +892,11 @@
   * to \c *this and returns a reference to \c *this.
   * \sa pretranslate()
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename OtherDerived>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::translate(const MatrixBase<OtherDerived> &other)
 {
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
   translationExt() += linearExt() * other;
   return *this;
@@ -843,11 +906,11 @@
   * to \c *this and returns a reference to \c *this.
   * \sa translate()
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename OtherDerived>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::pretranslate(const MatrixBase<OtherDerived> &other)
 {
   EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
   if(int(Mode)==int(Projective))
     affine() += other * m_matrix.row(Dim);
@@ -873,11 +936,11 @@
   *
   * \sa rotate(Scalar), class Quaternion, class AngleAxis, prerotate(RotationType)
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename RotationType>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::rotate(const RotationType& rotation)
 {
   linearExt() *= internal::toRotationMatrix<Scalar,Dim>(rotation);
   return *this;
 }
@@ -889,11 +952,11 @@
   *
   * \sa rotate()
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename RotationType>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::prerotate(const RotationType& rotation)
 {
   m_matrix.template block<Dim,HDim>(0,0) = internal::toRotationMatrix<Scalar,Dim>(rotation)
                                          * m_matrix.template block<Dim,HDim>(0,0);
   return *this;
@@ -903,11 +966,11 @@
   * by the vector \a other to \c *this and returns a reference to \c *this.
   * \warning 2D only.
   * \sa preshear()
   */
 template<typename Scalar, int Dim, int Mode, int Options>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::shear(const Scalar& sx, const Scalar& sy)
 {
   EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
   VectorType tmp = linear().col(0)*sy + linear().col(1);
@@ -919,11 +982,11 @@
   * by the vector \a other to \c *this and returns a reference to \c *this.
   * \warning 2D only.
   * \sa shear()
   */
 template<typename Scalar, int Dim, int Mode, int Options>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::preshear(const Scalar& sx, const Scalar& sy)
 {
   EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
   m_matrix.template block<Dim,HDim>(0,0) = LinearMatrixType(1, sx, sy, 1) * m_matrix.template block<Dim,HDim>(0,0);
@@ -933,48 +996,48 @@
 /******************************************************
 *** Scaling, Translation and Rotation compatibility ***
 ******************************************************/
 
 template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const TranslationType& t)
+EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const TranslationType& t)
 {
   linear().setIdentity();
   translation() = t.vector();
   makeAffine();
   return *this;
 }
 
 template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options> Transform<Scalar,Dim,Mode,Options>::operator*(const TranslationType& t) const
+EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options> Transform<Scalar,Dim,Mode,Options>::operator*(const TranslationType& t) const
 {
   Transform res = *this;
   res.translate(t.vector());
   return res;
 }
 
 template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const UniformScaling<Scalar>& s)
+EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const UniformScaling<Scalar>& s)
 {
   m_matrix.setZero();
   linear().diagonal().fill(s.factor());
   makeAffine();
   return *this;
 }
 
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename Derived>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const RotationBase<Derived,Dim>& r)
+EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const RotationBase<Derived,Dim>& r)
 {
   linear() = internal::toRotationMatrix<Scalar,Dim>(r);
   translation().setZero();
   makeAffine();
   return *this;
 }
 
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename Derived>
-inline Transform<Scalar,Dim,Mode,Options> Transform<Scalar,Dim,Mode,Options>::operator*(const RotationBase<Derived,Dim>& r) const
+EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options> Transform<Scalar,Dim,Mode,Options>::operator*(const RotationBase<Derived,Dim>& r) const
 {
   Transform res = *this;
   res.rotate(r.derived());
   return res;
 }
@@ -989,11 +1052,11 @@
   * \svd_module
   *
   * \sa computeRotationScaling(), computeScalingRotation(), class SVD
   */
 template<typename Scalar, int Dim, int Mode, int Options>
-const typename Transform<Scalar,Dim,Mode,Options>::LinearMatrixType
+EIGEN_DEVICE_FUNC const typename Transform<Scalar,Dim,Mode,Options>::LinearMatrixType
 Transform<Scalar,Dim,Mode,Options>::rotation() const
 {
   LinearMatrixType result;
   computeRotationScaling(&result, (LinearMatrixType*)0);
   return result;
@@ -1011,11 +1074,11 @@
   *
   * \sa computeScalingRotation(), rotation(), class SVD
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename RotationMatrixType, typename ScalingMatrixType>
-void Transform<Scalar,Dim,Mode,Options>::computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const
+EIGEN_DEVICE_FUNC void Transform<Scalar,Dim,Mode,Options>::computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const
 {
   JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU | ComputeFullV);
 
   Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
   VectorType sv(svd.singularValues());
@@ -1027,11 +1090,11 @@
     m.col(0) /= x;
     rotation->lazyAssign(m * svd.matrixV().adjoint());
   }
 }
 
-/** decomposes the linear part of the transformation as a product rotation x scaling, the scaling being
+/** decomposes the linear part of the transformation as a product scaling x rotation, the scaling being
   * not necessarily positive.
   *
   * If either pointer is zero, the corresponding computation is skipped.
   *
   *
@@ -1040,11 +1103,11 @@
   *
   * \sa computeRotationScaling(), rotation(), class SVD
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename ScalingMatrixType, typename RotationMatrixType>
-void Transform<Scalar,Dim,Mode,Options>::computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const
+EIGEN_DEVICE_FUNC void Transform<Scalar,Dim,Mode,Options>::computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const
 {
   JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU | ComputeFullV);
 
   Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
   VectorType sv(svd.singularValues());
@@ -1061,11 +1124,11 @@
 /** Convenient method to set \c *this from a position, orientation and scale
   * of a 3D object.
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 template<typename PositionDerived, typename OrientationType, typename ScaleDerived>
-Transform<Scalar,Dim,Mode,Options>&
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
 Transform<Scalar,Dim,Mode,Options>::fromPositionOrientationScale(const MatrixBase<PositionDerived> &position,
   const OrientationType& orientation, const MatrixBase<ScaleDerived> &scale)
 {
   linear() = internal::toRotationMatrix<Scalar,Dim>(orientation);
   linear() *= scale.asDiagonal();
@@ -1078,11 +1141,11 @@
 
 template<int Mode>
 struct transform_make_affine
 {
   template<typename MatrixType>
-  static void run(MatrixType &mat)
+  EIGEN_DEVICE_FUNC static void run(MatrixType &mat)
   {
     static const int Dim = MatrixType::ColsAtCompileTime-1;
     mat.template block<1,Dim>(Dim,0).setZero();
     mat.coeffRef(Dim,Dim) = typename MatrixType::Scalar(1);
   }
@@ -1089,25 +1152,25 @@
 };
 
 template<>
 struct transform_make_affine<AffineCompact>
 {
-  template<typename MatrixType> static void run(MatrixType &) { }
+  template<typename MatrixType> EIGEN_DEVICE_FUNC static void run(MatrixType &) { }
 };
     
 // selector needed to avoid taking the inverse of a 3x4 matrix
 template<typename TransformType, int Mode=TransformType::Mode>
 struct projective_transform_inverse
 {
-  static inline void run(const TransformType&, TransformType&)
+  EIGEN_DEVICE_FUNC static inline void run(const TransformType&, TransformType&)
   {}
 };
 
 template<typename TransformType>
 struct projective_transform_inverse<TransformType, Projective>
 {
-  static inline void run(const TransformType& m, TransformType& res)
+  EIGEN_DEVICE_FUNC static inline void run(const TransformType& m, TransformType& res)
   {
     res.matrix() = m.matrix().inverse();
   }
 };
 
@@ -1133,11 +1196,11 @@
   * you forget to include this module, then you will get hard to debug linking errors.
   *
   * \sa MatrixBase::inverse()
   */
 template<typename Scalar, int Dim, int Mode, int Options>
-Transform<Scalar,Dim,Mode,Options>
+EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>
 Transform<Scalar,Dim,Mode,Options>::inverse(TransformTraits hint) const
 {
   Transform res;
   if (hint == Projective)
   {
@@ -1242,23 +1305,23 @@
       (LhsMode == (int)AffineCompact || RhsMode == (int)AffineCompact ) ? AffineCompact :
       (LhsMode == (int)Isometry      || RhsMode == (int)Isometry      ) ? Isometry : Projective
   };
 };
 
-template< typename TransformType, typename MatrixType >
-struct transform_right_product_impl< TransformType, MatrixType, 0 >
+template< typename TransformType, typename MatrixType, int RhsCols>
+struct transform_right_product_impl< TransformType, MatrixType, 0, RhsCols>
 {
   typedef typename MatrixType::PlainObject ResultType;
 
   static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
   {
     return T.matrix() * other;
   }
 };
 
-template< typename TransformType, typename MatrixType >
-struct transform_right_product_impl< TransformType, MatrixType, 1 >
+template< typename TransformType, typename MatrixType, int RhsCols>
+struct transform_right_product_impl< TransformType, MatrixType, 1, RhsCols>
 {
   enum { 
     Dim = TransformType::Dim, 
     HDim = TransformType::HDim,
     OtherRows = MatrixType::RowsAtCompileTime,
@@ -1279,12 +1342,12 @@
     
     return res;
   }
 };
 
-template< typename TransformType, typename MatrixType >
-struct transform_right_product_impl< TransformType, MatrixType, 2 >
+template< typename TransformType, typename MatrixType, int RhsCols>
+struct transform_right_product_impl< TransformType, MatrixType, 2, RhsCols>
 {
   enum { 
     Dim = TransformType::Dim, 
     HDim = TransformType::HDim,
     OtherRows = MatrixType::RowsAtCompileTime,
@@ -1302,10 +1365,34 @@
     TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() += T.linear() * other;
 
     return res;
   }
 };
+
+template< typename TransformType, typename MatrixType >
+struct transform_right_product_impl< TransformType, MatrixType, 2, 1> // rhs is a vector of size Dim
+{
+  typedef typename TransformType::MatrixType TransformMatrix;
+  enum {
+    Dim = TransformType::Dim,
+    HDim = TransformType::HDim,
+    OtherRows = MatrixType::RowsAtCompileTime,
+    WorkingRows = EIGEN_PLAIN_ENUM_MIN(TransformMatrix::RowsAtCompileTime,HDim)
+  };
+
+  typedef typename MatrixType::PlainObject ResultType;
+
+  static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
+  {
+    EIGEN_STATIC_ASSERT(OtherRows==Dim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES);
+
+    Matrix<typename ResultType::Scalar, Dim+1, 1> rhs;
+    rhs.template head<Dim>() = other; rhs[Dim] = typename ResultType::Scalar(1);
+    Matrix<typename ResultType::Scalar, WorkingRows, 1> res(T.matrix() * rhs);
+    return res.template head<Dim>();
+  }
+};
 
 /**********************************************************
 ***   Specializations of operator* with lhs EigenBase   ***
 **********************************************************/
 

Index: 3rd_party/eigen/Eigen/src/Geometry/Translation.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/Translation.h
+++ 3rd_party/eigen/Eigen/src/Geometry/Translation.h
@@ -16,12 +16,12 @@
   *
   * \class Translation
   *
   * \brief Represents a translation transformation
   *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients.
-  * \param _Dim the  dimension of the space, can be a compile time value or Dynamic
+  * \tparam _Scalar the scalar type, i.e., the type of the coefficients.
+  * \tparam _Dim the  dimension of the space, can be a compile time value or Dynamic
   *
   * \note This class is not aimed to be used to store a translation transformation,
   * but rather to make easier the constructions and updates of Transform objects.
   *
   * \sa class Scaling, class Transform
@@ -49,69 +49,69 @@
   VectorType m_coeffs;
 
 public:
 
   /** Default constructor without initialization. */
-  Translation() {}
+  EIGEN_DEVICE_FUNC Translation() {}
   /**  */
-  inline Translation(const Scalar& sx, const Scalar& sy)
+  EIGEN_DEVICE_FUNC inline Translation(const Scalar& sx, const Scalar& sy)
   {
     eigen_assert(Dim==2);
     m_coeffs.x() = sx;
     m_coeffs.y() = sy;
   }
   /**  */
-  inline Translation(const Scalar& sx, const Scalar& sy, const Scalar& sz)
+  EIGEN_DEVICE_FUNC inline Translation(const Scalar& sx, const Scalar& sy, const Scalar& sz)
   {
     eigen_assert(Dim==3);
     m_coeffs.x() = sx;
     m_coeffs.y() = sy;
     m_coeffs.z() = sz;
   }
   /** Constructs and initialize the translation transformation from a vector of translation coefficients */
-  explicit inline Translation(const VectorType& vector) : m_coeffs(vector) {}
+  EIGEN_DEVICE_FUNC explicit inline Translation(const VectorType& vector) : m_coeffs(vector) {}
 
   /** \brief Retruns the x-translation by value. **/
-  inline Scalar x() const { return m_coeffs.x(); }
+  EIGEN_DEVICE_FUNC inline Scalar x() const { return m_coeffs.x(); }
   /** \brief Retruns the y-translation by value. **/
-  inline Scalar y() const { return m_coeffs.y(); }
+  EIGEN_DEVICE_FUNC inline Scalar y() const { return m_coeffs.y(); }
   /** \brief Retruns the z-translation by value. **/
-  inline Scalar z() const { return m_coeffs.z(); }
+  EIGEN_DEVICE_FUNC inline Scalar z() const { return m_coeffs.z(); }
 
   /** \brief Retruns the x-translation as a reference. **/
-  inline Scalar& x() { return m_coeffs.x(); }
+  EIGEN_DEVICE_FUNC inline Scalar& x() { return m_coeffs.x(); }
   /** \brief Retruns the y-translation as a reference. **/
-  inline Scalar& y() { return m_coeffs.y(); }
+  EIGEN_DEVICE_FUNC inline Scalar& y() { return m_coeffs.y(); }
   /** \brief Retruns the z-translation as a reference. **/
-  inline Scalar& z() { return m_coeffs.z(); }
+  EIGEN_DEVICE_FUNC inline Scalar& z() { return m_coeffs.z(); }
 
-  const VectorType& vector() const { return m_coeffs; }
-  VectorType& vector() { return m_coeffs; }
+  EIGEN_DEVICE_FUNC const VectorType& vector() const { return m_coeffs; }
+  EIGEN_DEVICE_FUNC VectorType& vector() { return m_coeffs; }
 
-  const VectorType& translation() const { return m_coeffs; }
-  VectorType& translation() { return m_coeffs; }
+  EIGEN_DEVICE_FUNC const VectorType& translation() const { return m_coeffs; }
+  EIGEN_DEVICE_FUNC VectorType& translation() { return m_coeffs; }
 
   /** Concatenates two translation */
-  inline Translation operator* (const Translation& other) const
+  EIGEN_DEVICE_FUNC inline Translation operator* (const Translation& other) const
   { return Translation(m_coeffs + other.m_coeffs); }
 
   /** Concatenates a translation and a uniform scaling */
-  inline AffineTransformType operator* (const UniformScaling<Scalar>& other) const;
+  EIGEN_DEVICE_FUNC inline AffineTransformType operator* (const UniformScaling<Scalar>& other) const;
 
   /** Concatenates a translation and a linear transformation */
   template<typename OtherDerived>
-  inline AffineTransformType operator* (const EigenBase<OtherDerived>& linear) const;
+  EIGEN_DEVICE_FUNC inline AffineTransformType operator* (const EigenBase<OtherDerived>& linear) const;
 
   /** Concatenates a translation and a rotation */
   template<typename Derived>
-  inline IsometryTransformType operator*(const RotationBase<Derived,Dim>& r) const
+  EIGEN_DEVICE_FUNC inline IsometryTransformType operator*(const RotationBase<Derived,Dim>& r) const
   { return *this * IsometryTransformType(r); }
 
   /** \returns the concatenation of a linear transformation \a l with the translation \a t */
   // its a nightmare to define a templated friend function outside its declaration
   template<typename OtherDerived> friend
-  inline AffineTransformType operator*(const EigenBase<OtherDerived>& linear, const Translation& t)
+  EIGEN_DEVICE_FUNC inline AffineTransformType operator*(const EigenBase<OtherDerived>& linear, const Translation& t)
   {
     AffineTransformType res;
     res.matrix().setZero();
     res.linear() = linear.derived();
     res.translation() = linear.derived() * t.m_coeffs;
@@ -120,20 +120,22 @@
     return res;
   }
 
   /** Concatenates a translation and a transformation */
   template<int Mode, int Options>
-  inline Transform<Scalar,Dim,Mode> operator* (const Transform<Scalar,Dim,Mode,Options>& t) const
+  EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode> operator* (const Transform<Scalar,Dim,Mode,Options>& t) const
   {
     Transform<Scalar,Dim,Mode> res = t;
     res.pretranslate(m_coeffs);
     return res;
   }
 
   /** Applies translation to vector */
-  inline VectorType operator* (const VectorType& other) const
-  { return m_coeffs + other; }
+  template<typename Derived>
+  inline typename internal::enable_if<Derived::IsVectorAtCompileTime,VectorType>::type
+  operator* (const MatrixBase<Derived>& vec) const
+  { return m_coeffs + vec.derived(); }
 
   /** \returns the inverse translation (opposite) */
   Translation inverse() const { return Translation(-m_coeffs); }
 
   Translation& operator=(const Translation& other)
@@ -148,23 +150,23 @@
     *
     * Note that if \a NewScalarType is equal to the current scalar type of \c *this
     * then this function smartly returns a const reference to \c *this.
     */
   template<typename NewScalarType>
-  inline typename internal::cast_return_type<Translation,Translation<NewScalarType,Dim> >::type cast() const
+  EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<Translation,Translation<NewScalarType,Dim> >::type cast() const
   { return typename internal::cast_return_type<Translation,Translation<NewScalarType,Dim> >::type(*this); }
 
   /** Copy constructor with scalar type conversion */
   template<typename OtherScalarType>
-  inline explicit Translation(const Translation<OtherScalarType,Dim>& other)
+  EIGEN_DEVICE_FUNC inline explicit Translation(const Translation<OtherScalarType,Dim>& other)
   { m_coeffs = other.vector().template cast<Scalar>(); }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const Translation& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+  EIGEN_DEVICE_FUNC bool isApprox(const Translation& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return m_coeffs.isApprox(other.m_coeffs, prec); }
 
 };
 
 /** \addtogroup Geometry_Module */
@@ -174,11 +176,11 @@
 typedef Translation<float, 3> Translation3f;
 typedef Translation<double,3> Translation3d;
 //@}
 
 template<typename Scalar, int Dim>
-inline typename Translation<Scalar,Dim>::AffineTransformType
+EIGEN_DEVICE_FUNC inline typename Translation<Scalar,Dim>::AffineTransformType
 Translation<Scalar,Dim>::operator* (const UniformScaling<Scalar>& other) const
 {
   AffineTransformType res;
   res.matrix().setZero();
   res.linear().diagonal().fill(other.factor());
@@ -187,11 +189,11 @@
   return res;
 }
 
 template<typename Scalar, int Dim>
 template<typename OtherDerived>
-inline typename Translation<Scalar,Dim>::AffineTransformType
+EIGEN_DEVICE_FUNC inline typename Translation<Scalar,Dim>::AffineTransformType
 Translation<Scalar,Dim>::operator* (const EigenBase<OtherDerived>& linear) const
 {
   AffineTransformType res;
   res.matrix().setZero();
   res.linear() = linear.derived();

Index: 3rd_party/eigen/Eigen/src/Geometry/Umeyama.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/Umeyama.h
+++ 3rd_party/eigen/Eigen/src/Geometry/Umeyama.h
@@ -95,11 +95,10 @@
 umeyama(const MatrixBase<Derived>& src, const MatrixBase<OtherDerived>& dst, bool with_scaling = true)
 {
   typedef typename internal::umeyama_transform_matrix_type<Derived, OtherDerived>::type TransformationMatrixType;
   typedef typename internal::traits<TransformationMatrixType>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef typename Derived::Index Index;
 
   EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL)
   EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename internal::traits<OtherDerived>::Scalar>::value),
     YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
@@ -134,26 +133,16 @@
   // Initialize the resulting transformation with an identity matrix...
   TransformationMatrixType Rt = TransformationMatrixType::Identity(m+1,m+1);
 
   // Eq. (39)
   VectorType S = VectorType::Ones(m);
-  if (sigma.determinant()<Scalar(0)) S(m-1) = Scalar(-1);
+
+  if  ( svd.matrixU().determinant() * svd.matrixV().determinant() < 0 )
+    S(m-1) = -1;
 
   // Eq. (40) and (43)
-  const VectorType& d = svd.singularValues();
-  Index rank = 0; for (Index i=0; i<m; ++i) if (!internal::isMuchSmallerThan(d.coeff(i),d.coeff(0))) ++rank;
-  if (rank == m-1) {
-    if ( svd.matrixU().determinant() * svd.matrixV().determinant() > Scalar(0) ) {
-      Rt.block(0,0,m,m).noalias() = svd.matrixU()*svd.matrixV().transpose();
-    } else {
-      const Scalar s = S(m-1); S(m-1) = Scalar(-1);
-      Rt.block(0,0,m,m).noalias() = svd.matrixU() * S.asDiagonal() * svd.matrixV().transpose();
-      S(m-1) = s;
-    }
-  } else {
-    Rt.block(0,0,m,m).noalias() = svd.matrixU() * S.asDiagonal() * svd.matrixV().transpose();
-  }
+  Rt.block(0,0,m,m).noalias() = svd.matrixU() * S.asDiagonal() * svd.matrixV().transpose();
 
   if (with_scaling)
   {
     // Eq. (42)
     const Scalar c = Scalar(1)/src_var * svd.singularValues().dot(S);

DELETED 3rd_party/eigen/Eigen/src/Geometry/arch/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Geometry/arch/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/arch/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Geometry/arch/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Geometry_arch_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Geometry_arch_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Geometry/arch COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/Geometry/arch/Geometry_SSE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Geometry/arch/Geometry_SSE.h
+++ 3rd_party/eigen/Eigen/src/Geometry/arch/Geometry_SSE.h
@@ -14,62 +14,91 @@
 namespace Eigen { 
 
 namespace internal {
 
 template<class Derived, class OtherDerived>
-struct quat_product<Architecture::SSE, Derived, OtherDerived, float, Aligned>
+struct quat_product<Architecture::SSE, Derived, OtherDerived, float>
 {
+  enum {
+    AAlignment = traits<Derived>::Alignment,
+    BAlignment = traits<OtherDerived>::Alignment,
+    ResAlignment = traits<Quaternion<float> >::Alignment
+  };
   static inline Quaternion<float> run(const QuaternionBase<Derived>& _a, const QuaternionBase<OtherDerived>& _b)
   {
-    const __m128 mask = _mm_castsi128_ps(_mm_setr_epi32(0,0,0,0x80000000));
     Quaternion<float> res;
-    __m128 a = _a.coeffs().template packet<Aligned>(0);
-    __m128 b = _b.coeffs().template packet<Aligned>(0);
-    __m128 flip1 = _mm_xor_ps(_mm_mul_ps(vec4f_swizzle1(a,1,2,0,2),
-                                         vec4f_swizzle1(b,2,0,1,2)),mask);
-    __m128 flip2 = _mm_xor_ps(_mm_mul_ps(vec4f_swizzle1(a,3,3,3,1),
-                                         vec4f_swizzle1(b,0,1,2,1)),mask);
-    pstore(&res.x(),
+    const __m128 mask = _mm_setr_ps(0.f,0.f,0.f,-0.f);
+    __m128 a = _a.coeffs().template packet<AAlignment>(0);
+    __m128 b = _b.coeffs().template packet<BAlignment>(0);
+    __m128 s1 = _mm_mul_ps(vec4f_swizzle1(a,1,2,0,2),vec4f_swizzle1(b,2,0,1,2));
+    __m128 s2 = _mm_mul_ps(vec4f_swizzle1(a,3,3,3,1),vec4f_swizzle1(b,0,1,2,1));
+    pstoret<float,Packet4f,ResAlignment>(
+              &res.x(),
               _mm_add_ps(_mm_sub_ps(_mm_mul_ps(a,vec4f_swizzle1(b,3,3,3,3)),
                                     _mm_mul_ps(vec4f_swizzle1(a,2,0,1,0),
                                                vec4f_swizzle1(b,1,2,0,0))),
-                         _mm_add_ps(flip1,flip2)));
+                         _mm_xor_ps(mask,_mm_add_ps(s1,s2))));
+    
+    return res;
+  }
+};
+
+template<class Derived>
+struct quat_conj<Architecture::SSE, Derived, float>
+{
+  enum {
+    ResAlignment = traits<Quaternion<float> >::Alignment
+  };
+  static inline Quaternion<float> run(const QuaternionBase<Derived>& q)
+  {
+    Quaternion<float> res;
+    const __m128 mask = _mm_setr_ps(-0.f,-0.f,-0.f,0.f);
+    pstoret<float,Packet4f,ResAlignment>(&res.x(), _mm_xor_ps(mask, q.coeffs().template packet<traits<Derived>::Alignment>(0)));
     return res;
   }
 };
+
 
 template<typename VectorLhs,typename VectorRhs>
 struct cross3_impl<Architecture::SSE,VectorLhs,VectorRhs,float,true>
 {
+  enum {
+    ResAlignment = traits<typename plain_matrix_type<VectorLhs>::type>::Alignment
+  };
   static inline typename plain_matrix_type<VectorLhs>::type
   run(const VectorLhs& lhs, const VectorRhs& rhs)
   {
-    __m128 a = lhs.template packet<VectorLhs::Flags&AlignedBit ? Aligned : Unaligned>(0);
-    __m128 b = rhs.template packet<VectorRhs::Flags&AlignedBit ? Aligned : Unaligned>(0);
+    __m128 a = lhs.template packet<traits<VectorLhs>::Alignment>(0);
+    __m128 b = rhs.template packet<traits<VectorRhs>::Alignment>(0);
     __m128 mul1=_mm_mul_ps(vec4f_swizzle1(a,1,2,0,3),vec4f_swizzle1(b,2,0,1,3));
     __m128 mul2=_mm_mul_ps(vec4f_swizzle1(a,2,0,1,3),vec4f_swizzle1(b,1,2,0,3));
     typename plain_matrix_type<VectorLhs>::type res;
-    pstore(&res.x(),_mm_sub_ps(mul1,mul2));
+    pstoret<float,Packet4f,ResAlignment>(&res.x(),_mm_sub_ps(mul1,mul2));
     return res;
   }
 };
 
 
 
 
 template<class Derived, class OtherDerived>
-struct quat_product<Architecture::SSE, Derived, OtherDerived, double, Aligned>
+struct quat_product<Architecture::SSE, Derived, OtherDerived, double>
 {
+  enum {
+    BAlignment = traits<OtherDerived>::Alignment,
+    ResAlignment = traits<Quaternion<double> >::Alignment
+  };
+
   static inline Quaternion<double> run(const QuaternionBase<Derived>& _a, const QuaternionBase<OtherDerived>& _b)
   {
   const Packet2d mask = _mm_castsi128_pd(_mm_set_epi32(0x0,0x0,0x80000000,0x0));
 
   Quaternion<double> res;
 
   const double* a = _a.coeffs().data();
-  Packet2d b_xy = _b.coeffs().template packet<Aligned>(0);
-  Packet2d b_zw = _b.coeffs().template packet<Aligned>(2);
+  Packet2d b_xy = _b.coeffs().template packet<BAlignment>(0);
+  Packet2d b_zw = _b.coeffs().template packet<BAlignment>(2);
   Packet2d a_xx = pset1<Packet2d>(a[0]);
   Packet2d a_yy = pset1<Packet2d>(a[1]);
   Packet2d a_zz = pset1<Packet2d>(a[2]);
   Packet2d a_ww = pset1<Packet2d>(a[3]);
 
@@ -83,13 +112,13 @@
    */
   t1 = padd(pmul(a_ww, b_xy), pmul(a_yy, b_zw));
   t2 = psub(pmul(a_zz, b_xy), pmul(a_xx, b_zw));
 #ifdef EIGEN_VECTORIZE_SSE3
   EIGEN_UNUSED_VARIABLE(mask)
-  pstore(&res.x(), _mm_addsub_pd(t1, preverse(t2)));
+  pstoret<double,Packet2d,ResAlignment>(&res.x(), _mm_addsub_pd(t1, preverse(t2)));
 #else
-  pstore(&res.x(), padd(t1, pxor(mask,preverse(t2))));
+  pstoret<double,Packet2d,ResAlignment>(&res.x(), padd(t1, pxor(mask,preverse(t2))));
 #endif
   
   /*
    * t1 = ww*zw - yy*xy
    * t2 = zz*zw + xx*xy
@@ -97,19 +126,36 @@
    */
   t1 = psub(pmul(a_ww, b_zw), pmul(a_yy, b_xy));
   t2 = padd(pmul(a_zz, b_zw), pmul(a_xx, b_xy));
 #ifdef EIGEN_VECTORIZE_SSE3
   EIGEN_UNUSED_VARIABLE(mask)
-  pstore(&res.z(), preverse(_mm_addsub_pd(preverse(t1), t2)));
+  pstoret<double,Packet2d,ResAlignment>(&res.z(), preverse(_mm_addsub_pd(preverse(t1), t2)));
 #else
-  pstore(&res.z(), psub(t1, pxor(mask,preverse(t2))));
+  pstoret<double,Packet2d,ResAlignment>(&res.z(), psub(t1, pxor(mask,preverse(t2))));
 #endif
 
   return res;
 }
 };
+
+template<class Derived>
+struct quat_conj<Architecture::SSE, Derived, double>
+{
+  enum {
+    ResAlignment = traits<Quaternion<double> >::Alignment
+  };
+  static inline Quaternion<double> run(const QuaternionBase<Derived>& q)
+  {
+    Quaternion<double> res;
+    const __m128d mask0 = _mm_setr_pd(-0.,-0.);
+    const __m128d mask2 = _mm_setr_pd(-0.,0.);
+    pstoret<double,Packet2d,ResAlignment>(&res.x(), _mm_xor_pd(mask0, q.coeffs().template packet<traits<Derived>::Alignment>(0)));
+    pstoret<double,Packet2d,ResAlignment>(&res.z(), _mm_xor_pd(mask2, q.coeffs().template packet<traits<Derived>::Alignment>(2)));
+    return res;
+  }
+};
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_GEOMETRY_SSE_H

Index: 3rd_party/eigen/Eigen/src/Householder/BlockHouseholder.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Householder/BlockHouseholder.h
+++ 3rd_party/eigen/Eigen/src/Householder/BlockHouseholder.h
@@ -14,55 +14,90 @@
 // This file contains some helper function to deal with block householder reflectors
 
 namespace Eigen { 
 
 namespace internal {
+  
+/** \internal */
+// template<typename TriangularFactorType,typename VectorsType,typename CoeffsType>
+// void make_block_householder_triangular_factor(TriangularFactorType& triFactor, const VectorsType& vectors, const CoeffsType& hCoeffs)
+// {
+//   typedef typename VectorsType::Scalar Scalar;
+//   const Index nbVecs = vectors.cols();
+//   eigen_assert(triFactor.rows() == nbVecs && triFactor.cols() == nbVecs && vectors.rows()>=nbVecs);
+// 
+//   for(Index i = 0; i < nbVecs; i++)
+//   {
+//     Index rs = vectors.rows() - i;
+//     // Warning, note that hCoeffs may alias with vectors.
+//     // It is then necessary to copy it before modifying vectors(i,i). 
+//     typename CoeffsType::Scalar h = hCoeffs(i);
+//     // This hack permits to pass trough nested Block<> and Transpose<> expressions.
+//     Scalar *Vii_ptr = const_cast<Scalar*>(vectors.data() + vectors.outerStride()*i + vectors.innerStride()*i);
+//     Scalar Vii = *Vii_ptr;
+//     *Vii_ptr = Scalar(1);
+//     triFactor.col(i).head(i).noalias() = -h * vectors.block(i, 0, rs, i).adjoint()
+//                                        * vectors.col(i).tail(rs);
+//     *Vii_ptr = Vii;
+//     // FIXME add .noalias() once the triangular product can work inplace
+//     triFactor.col(i).head(i) = triFactor.block(0,0,i,i).template triangularView<Upper>()
+//                              * triFactor.col(i).head(i);
+//     triFactor(i,i) = hCoeffs(i);
+//   }
+// }
 
 /** \internal */
+// This variant avoid modifications in vectors
 template<typename TriangularFactorType,typename VectorsType,typename CoeffsType>
 void make_block_householder_triangular_factor(TriangularFactorType& triFactor, const VectorsType& vectors, const CoeffsType& hCoeffs)
 {
-  typedef typename TriangularFactorType::Index Index;
-  typedef typename VectorsType::Scalar Scalar;
   const Index nbVecs = vectors.cols();
   eigen_assert(triFactor.rows() == nbVecs && triFactor.cols() == nbVecs && vectors.rows()>=nbVecs);
 
-  for(Index i = 0; i < nbVecs; i++)
-  {
-    Index rs = vectors.rows() - i;
-    Scalar Vii = vectors(i,i);
-    vectors.const_cast_derived().coeffRef(i,i) = Scalar(1);
-    triFactor.col(i).head(i).noalias() = -hCoeffs(i) * vectors.block(i, 0, rs, i).adjoint()
-                                       * vectors.col(i).tail(rs);
-    vectors.const_cast_derived().coeffRef(i, i) = Vii;
-    // FIXME add .noalias() once the triangular product can work inplace
-    triFactor.col(i).head(i) = triFactor.block(0,0,i,i).template triangularView<Upper>()
-                             * triFactor.col(i).head(i);
+  for(Index i = nbVecs-1; i >=0 ; --i)
+  {
+    Index rs = vectors.rows() - i - 1;
+    Index rt = nbVecs-i-1;
+
+    if(rt>0)
+    {
+      triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint()
+                                                        * vectors.bottomRightCorner(rs, rt).template triangularView<UnitLower>();
+            
+      // FIXME add .noalias() once the triangular product can work inplace
+      triFactor.row(i).tail(rt) = triFactor.row(i).tail(rt) * triFactor.bottomRightCorner(rt,rt).template triangularView<Upper>();
+      
+    }
     triFactor(i,i) = hCoeffs(i);
   }
 }
 
-/** \internal */
+/** \internal
+  * if forward then perform   mat = H0 * H1 * H2 * mat
+  * otherwise perform         mat = H2 * H1 * H0 * mat
+  */
 template<typename MatrixType,typename VectorsType,typename CoeffsType>
-void apply_block_householder_on_the_left(MatrixType& mat, const VectorsType& vectors, const CoeffsType& hCoeffs)
+void apply_block_householder_on_the_left(MatrixType& mat, const VectorsType& vectors, const CoeffsType& hCoeffs, bool forward)
 {
-  typedef typename MatrixType::Index Index;
   enum { TFactorSize = MatrixType::ColsAtCompileTime };
   Index nbVecs = vectors.cols();
-  Matrix<typename MatrixType::Scalar, TFactorSize, TFactorSize, ColMajor> T(nbVecs,nbVecs);
-  make_block_householder_triangular_factor(T, vectors, hCoeffs);
-
-  const TriangularView<const VectorsType, UnitLower>& V(vectors);
+  Matrix<typename MatrixType::Scalar, TFactorSize, TFactorSize, RowMajor> T(nbVecs,nbVecs);
+  
+  if(forward) make_block_householder_triangular_factor(T, vectors, hCoeffs);
+  else        make_block_householder_triangular_factor(T, vectors, hCoeffs.conjugate());  
+  const TriangularView<const VectorsType, UnitLower> V(vectors);
 
   // A -= V T V^* A
-  Matrix<typename MatrixType::Scalar,VectorsType::ColsAtCompileTime,MatrixType::ColsAtCompileTime,0,
+  Matrix<typename MatrixType::Scalar,VectorsType::ColsAtCompileTime,MatrixType::ColsAtCompileTime,
+         (VectorsType::MaxColsAtCompileTime==1 && MatrixType::MaxColsAtCompileTime!=1)?RowMajor:ColMajor,
          VectorsType::MaxColsAtCompileTime,MatrixType::MaxColsAtCompileTime> tmp = V.adjoint() * mat;
   // FIXME add .noalias() once the triangular product can work inplace
-  tmp = T.template triangularView<Upper>().adjoint() * tmp;
+  if(forward) tmp = T.template triangularView<Upper>()           * tmp;
+  else        tmp = T.template triangularView<Upper>().adjoint() * tmp;
   mat.noalias() -= V * tmp;
 }
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_BLOCK_HOUSEHOLDER_H

DELETED 3rd_party/eigen/Eigen/src/Householder/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Householder/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Householder/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Householder/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Householder_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Householder_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Householder COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/Householder/Householder.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Householder/Householder.h
+++ 3rd_party/eigen/Eigen/src/Householder/Householder.h
@@ -73,12 +73,13 @@
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(EssentialPart)
   VectorBlock<const Derived, EssentialPart::SizeAtCompileTime> tail(derived(), 1, size()-1);
   
   RealScalar tailSqNorm = size()==1 ? RealScalar(0) : tail.squaredNorm();
   Scalar c0 = coeff(0);
+  const RealScalar tol = (std::numeric_limits<RealScalar>::min)();
 
-  if(tailSqNorm == RealScalar(0) && numext::imag(c0)==RealScalar(0))
+  if(tailSqNorm <= tol && numext::abs2(numext::imag(c0))<=tol)
   {
     tau = RealScalar(0);
     beta = numext::real(c0);
     essential.setZero();
   }
@@ -116,11 +117,11 @@
 {
   if(rows() == 1)
   {
     *this *= Scalar(1)-tau;
   }
-  else
+  else if(tau!=Scalar(0))
   {
     Map<typename internal::plain_row_type<PlainObject>::type> tmp(workspace,cols());
     Block<Derived, EssentialPart::SizeAtCompileTime, Derived::ColsAtCompileTime> bottom(derived(), 1, 0, rows()-1, cols());
     tmp.noalias() = essential.adjoint() * bottom;
     tmp += this->row(0);
@@ -153,11 +154,11 @@
 {
   if(cols() == 1)
   {
     *this *= Scalar(1)-tau;
   }
-  else
+  else if(tau!=Scalar(0))
   {
     Map<typename internal::plain_col_type<PlainObject>::type> tmp(workspace,rows());
     Block<Derived, Derived::RowsAtCompileTime, EssentialPart::SizeAtCompileTime> right(derived(), 0, 1, rows(), cols()-1);
     tmp.noalias() = right * essential.conjugate();
     tmp += this->col(0);

Index: 3rd_party/eigen/Eigen/src/Householder/HouseholderSequence.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Householder/HouseholderSequence.h
+++ 3rd_party/eigen/Eigen/src/Householder/HouseholderSequence.h
@@ -58,11 +58,11 @@
 
 template<typename VectorsType, typename CoeffsType, int Side>
 struct traits<HouseholderSequence<VectorsType,CoeffsType,Side> >
 {
   typedef typename VectorsType::Scalar Scalar;
-  typedef typename VectorsType::Index Index;
+  typedef typename VectorsType::StorageIndex StorageIndex;
   typedef typename VectorsType::StorageKind StorageKind;
   enum {
     RowsAtCompileTime = Side==OnTheLeft ? traits<VectorsType>::RowsAtCompileTime
                                         : traits<VectorsType>::ColsAtCompileTime,
     ColsAtCompileTime = RowsAtCompileTime,
@@ -70,17 +70,25 @@
                                            : traits<VectorsType>::MaxColsAtCompileTime,
     MaxColsAtCompileTime = MaxRowsAtCompileTime,
     Flags = 0
   };
 };
+
+struct HouseholderSequenceShape {};
+
+template<typename VectorsType, typename CoeffsType, int Side>
+struct evaluator_traits<HouseholderSequence<VectorsType,CoeffsType,Side> >
+  : public evaluator_traits_base<HouseholderSequence<VectorsType,CoeffsType,Side> >
+{
+  typedef HouseholderSequenceShape Shape;
+};
 
 template<typename VectorsType, typename CoeffsType, int Side>
 struct hseq_side_dependent_impl
 {
   typedef Block<const VectorsType, Dynamic, 1> EssentialVectorType;
   typedef HouseholderSequence<VectorsType, CoeffsType, OnTheLeft> HouseholderSequenceType;
-  typedef typename VectorsType::Index Index;
   static inline const EssentialVectorType essentialVector(const HouseholderSequenceType& h, Index k)
   {
     Index start = k+1+h.m_shift;
     return Block<const VectorsType,Dynamic,1>(h.m_vectors, start, k, h.rows()-start, 1);
   }
@@ -89,21 +97,20 @@
 template<typename VectorsType, typename CoeffsType>
 struct hseq_side_dependent_impl<VectorsType, CoeffsType, OnTheRight>
 {
   typedef Transpose<Block<const VectorsType, 1, Dynamic> > EssentialVectorType;
   typedef HouseholderSequence<VectorsType, CoeffsType, OnTheRight> HouseholderSequenceType;
-  typedef typename VectorsType::Index Index;
   static inline const EssentialVectorType essentialVector(const HouseholderSequenceType& h, Index k)
   {
     Index start = k+1+h.m_shift;
     return Block<const VectorsType,1,Dynamic>(h.m_vectors, k, start, 1, h.rows()-start).transpose();
   }
 };
 
 template<typename OtherScalarType, typename MatrixType> struct matrix_type_times_scalar_type
 {
-  typedef typename scalar_product_traits<OtherScalarType, typename MatrixType::Scalar>::ReturnType
+  typedef typename ScalarBinaryOpTraits<OtherScalarType, typename MatrixType::Scalar>::ReturnType
     ResultScalar;
   typedef Matrix<ResultScalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime,
                  0, MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime> Type;
 };
 
@@ -120,11 +127,10 @@
       ColsAtCompileTime = internal::traits<HouseholderSequence>::ColsAtCompileTime,
       MaxRowsAtCompileTime = internal::traits<HouseholderSequence>::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = internal::traits<HouseholderSequence>::MaxColsAtCompileTime
     };
     typedef typename internal::traits<HouseholderSequence>::Scalar Scalar;
-    typedef typename VectorsType::Index Index;
 
     typedef HouseholderSequence<
       typename internal::conditional<NumTraits<Scalar>::IsComplex,
         typename internal::remove_all<typename VectorsType::ConjugateReturnType>::type,
         VectorsType>::type,
@@ -235,12 +241,11 @@
     template<typename Dest, typename Workspace>
     void evalTo(Dest& dst, Workspace& workspace) const
     {
       workspace.resize(rows());
       Index vecs = m_length;
-      if(    internal::is_same<typename internal::remove_all<VectorsType>::type,Dest>::value
-          && internal::extract_data(dst) == internal::extract_data(m_vectors))
+      if(internal::is_same_dense(dst,m_vectors))
       {
         // in-place
         dst.diagonal().setOnes();
         dst.template triangularView<StrictlyUpper>().setZero();
         for(Index k = vecs-1; k >= 0; --k)
@@ -297,24 +302,48 @@
     }
 
     /** \internal */
     template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
     {
-      Matrix<Scalar,1,Dest::ColsAtCompileTime,RowMajor,1,Dest::MaxColsAtCompileTime> workspace(dst.cols());
+      Matrix<Scalar,1,Dest::ColsAtCompileTime,RowMajor,1,Dest::MaxColsAtCompileTime> workspace;
       applyThisOnTheLeft(dst, workspace);
     }
 
     /** \internal */
     template<typename Dest, typename Workspace>
     inline void applyThisOnTheLeft(Dest& dst, Workspace& workspace) const
     {
-      workspace.resize(dst.cols());
-      for(Index k = 0; k < m_length; ++k)
+      const Index BlockSize = 48;
+      // if the entries are large enough, then apply the reflectors by block
+      if(m_length>=BlockSize && dst.cols()>1)
+      {
+        for(Index i = 0; i < m_length; i+=BlockSize)
+        {
+          Index end = m_trans ? (std::min)(m_length,i+BlockSize) : m_length-i;
+          Index k = m_trans ? i : (std::max)(Index(0),end-BlockSize);
+          Index bs = end-k;
+          Index start = k + m_shift;
+          
+          typedef Block<typename internal::remove_all<VectorsType>::type,Dynamic,Dynamic> SubVectorsType;
+          SubVectorsType sub_vecs1(m_vectors.const_cast_derived(), Side==OnTheRight ? k : start,
+                                                                   Side==OnTheRight ? start : k,
+                                                                   Side==OnTheRight ? bs : m_vectors.rows()-start,
+                                                                   Side==OnTheRight ? m_vectors.cols()-start : bs);
+          typename internal::conditional<Side==OnTheRight, Transpose<SubVectorsType>, SubVectorsType&>::type sub_vecs(sub_vecs1);
+          Block<Dest,Dynamic,Dynamic> sub_dst(dst,dst.rows()-rows()+m_shift+k,0, rows()-m_shift-k,dst.cols());
+          apply_block_householder_on_the_left(sub_dst, sub_vecs, m_coeffs.segment(k, bs), !m_trans);
+        }
+      }
+      else
       {
-        Index actual_k = m_trans ? k : m_length-k-1;
-        dst.bottomRows(rows()-m_shift-actual_k)
-           .applyHouseholderOnTheLeft(essentialVector(actual_k), m_coeffs.coeff(actual_k), workspace.data());
+        workspace.resize(dst.cols());
+        for(Index k = 0; k < m_length; ++k)
+        {
+          Index actual_k = m_trans ? k : m_length-k-1;
+          dst.bottomRows(rows()-m_shift-actual_k)
+            .applyHouseholderOnTheLeft(essentialVector(actual_k), m_coeffs.coeff(actual_k), workspace.data());
+        }
       }
     }
 
     /** \brief Computes the product of a Householder sequence with a matrix.
       * \param[in]  other  %Matrix being multiplied.

Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -15,37 +15,41 @@
 /** \ingroup IterativeLinearSolvers_Module
   * \brief A preconditioner based on the digonal entries
   *
   * This class allows to approximately solve for A.x = b problems assuming A is a diagonal matrix.
   * In other words, this preconditioner neglects all off diagonal entries and, in Eigen's language, solves for:
-  * \code
-  * A.diagonal().asDiagonal() . x = b
-  * \endcode
+    \code
+    A.diagonal().asDiagonal() . x = b
+    \endcode
   *
   * \tparam _Scalar the type of the scalar.
+  *
+  * \implsparsesolverconcept
   *
   * This preconditioner is suitable for both selfadjoint and general problems.
   * The diagonal entries are pre-inverted and stored into a dense vector.
   *
   * \note A variant that has yet to be implemented would attempt to preserve the norm of each column.
   *
+  * \sa class LeastSquareDiagonalPreconditioner, class ConjugateGradient
   */
 template <typename _Scalar>
 class DiagonalPreconditioner
 {
     typedef _Scalar Scalar;
     typedef Matrix<Scalar,Dynamic,1> Vector;
-    typedef typename Vector::Index Index;
-
   public:
-    // this typedef is only to export the scalar type and compile-time dimensions to solve_retval
-    typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
+    typedef typename Vector::StorageIndex StorageIndex;
+    enum {
+      ColsAtCompileTime = Dynamic,
+      MaxColsAtCompileTime = Dynamic
+    };
 
     DiagonalPreconditioner() : m_isInitialized(false) {}
 
     template<typename MatType>
-    DiagonalPreconditioner(const MatType& mat) : m_invdiag(mat.cols())
+    explicit DiagonalPreconditioner(const MatType& mat) : m_invdiag(mat.cols())
     {
       compute(mat);
     }
 
     Index rows() const { return m_invdiag.size(); }
@@ -63,14 +67,14 @@
       m_invdiag.resize(mat.cols());
       for(int j=0; j<mat.outerSize(); ++j)
       {
         typename MatType::InnerIterator it(mat,j);
         while(it && it.index()!=j) ++it;
-        if(it && it.index()==j)
+        if(it && it.index()==j && it.value()!=Scalar(0))
           m_invdiag(j) = Scalar(1)/it.value();
         else
-          m_invdiag(j) = 0;
+          m_invdiag(j) = Scalar(1);
       }
       m_isInitialized = true;
       return *this;
     }
     
@@ -78,49 +82,120 @@
     DiagonalPreconditioner& compute(const MatType& mat)
     {
       return factorize(mat);
     }
 
+    /** \internal */
     template<typename Rhs, typename Dest>
-    void _solve(const Rhs& b, Dest& x) const
+    void _solve_impl(const Rhs& b, Dest& x) const
     {
       x = m_invdiag.array() * b.array() ;
     }
 
-    template<typename Rhs> inline const internal::solve_retval<DiagonalPreconditioner, Rhs>
+    template<typename Rhs> inline const Solve<DiagonalPreconditioner, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
       eigen_assert(m_isInitialized && "DiagonalPreconditioner is not initialized.");
       eigen_assert(m_invdiag.size()==b.rows()
                 && "DiagonalPreconditioner::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<DiagonalPreconditioner, Rhs>(*this, b.derived());
+      return Solve<DiagonalPreconditioner, Rhs>(*this, b.derived());
     }
+    
+    ComputationInfo info() { return Success; }
 
   protected:
     Vector m_invdiag;
     bool m_isInitialized;
 };
 
-namespace internal {
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<DiagonalPreconditioner<_MatrixType>, Rhs>
-  : solve_retval_base<DiagonalPreconditioner<_MatrixType>, Rhs>
-{
-  typedef DiagonalPreconditioner<_MatrixType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-}
+/** \ingroup IterativeLinearSolvers_Module
+  * \brief Jacobi preconditioner for LeastSquaresConjugateGradient
+  *
+  * This class allows to approximately solve for A' A x  = A' b problems assuming A' A is a diagonal matrix.
+  * In other words, this preconditioner neglects all off diagonal entries and, in Eigen's language, solves for:
+    \code
+    (A.adjoint() * A).diagonal().asDiagonal() * x = b
+    \endcode
+  *
+  * \tparam _Scalar the type of the scalar.
+  *
+  * \implsparsesolverconcept
+  *
+  * The diagonal entries are pre-inverted and stored into a dense vector.
+  * 
+  * \sa class LeastSquaresConjugateGradient, class DiagonalPreconditioner
+  */
+template <typename _Scalar>
+class LeastSquareDiagonalPreconditioner : public DiagonalPreconditioner<_Scalar>
+{
+    typedef _Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef DiagonalPreconditioner<_Scalar> Base;
+    using Base::m_invdiag;
+  public:
+
+    LeastSquareDiagonalPreconditioner() : Base() {}
+
+    template<typename MatType>
+    explicit LeastSquareDiagonalPreconditioner(const MatType& mat) : Base()
+    {
+      compute(mat);
+    }
+
+    template<typename MatType>
+    LeastSquareDiagonalPreconditioner& analyzePattern(const MatType& )
+    {
+      return *this;
+    }
+    
+    template<typename MatType>
+    LeastSquareDiagonalPreconditioner& factorize(const MatType& mat)
+    {
+      // Compute the inverse squared-norm of each column of mat
+      m_invdiag.resize(mat.cols());
+      if(MatType::IsRowMajor)
+      {
+        m_invdiag.setZero();
+        for(Index j=0; j<mat.outerSize(); ++j)
+        {
+          for(typename MatType::InnerIterator it(mat,j); it; ++it)
+            m_invdiag(it.index()) += numext::abs2(it.value());
+        }
+        for(Index j=0; j<mat.cols(); ++j)
+          if(numext::real(m_invdiag(j))>RealScalar(0))
+            m_invdiag(j) = RealScalar(1)/numext::real(m_invdiag(j));
+      }
+      else
+      {
+        for(Index j=0; j<mat.outerSize(); ++j)
+        {
+          RealScalar sum = mat.innerVector(j).squaredNorm();
+          if(sum>RealScalar(0))
+            m_invdiag(j) = RealScalar(1)/sum;
+          else
+            m_invdiag(j) = RealScalar(1);
+        }
+      }
+      Base::m_isInitialized = true;
+      return *this;
+    }
+    
+    template<typename MatType>
+    LeastSquareDiagonalPreconditioner& compute(const MatType& mat)
+    {
+      return factorize(mat);
+    }
+    
+    ComputationInfo info() { return Success; }
+
+  protected:
+};
 
 /** \ingroup IterativeLinearSolvers_Module
   * \brief A naive preconditioner which approximates any matrix as the identity matrix
+  *
+  * \implsparsesolverconcept
   *
   * \sa class DiagonalPreconditioner
   */
 class IdentityPreconditioner
 {
@@ -127,11 +202,11 @@
   public:
 
     IdentityPreconditioner() {}
 
     template<typename MatrixType>
-    IdentityPreconditioner(const MatrixType& ) {}
+    explicit IdentityPreconditioner(const MatrixType& ) {}
     
     template<typename MatrixType>
     IdentityPreconditioner& analyzePattern(const MatrixType& ) { return *this; }
     
     template<typename MatrixType>
@@ -140,10 +215,12 @@
     template<typename MatrixType>
     IdentityPreconditioner& compute(const MatrixType& ) { return *this; }
     
     template<typename Rhs>
     inline const Rhs& solve(const Rhs& b) const { return b; }
+    
+    ComputationInfo info() { return Success; }
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_BASIC_PRECONDITIONERS_H

Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -25,22 +25,22 @@
   * \param tol_error On input the tolerance error, on output an estimation of the relative error.
   * \return false in the case of numerical issue, for example a break down of BiCGSTAB. 
   */
 template<typename MatrixType, typename Rhs, typename Dest, typename Preconditioner>
 bool bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
-              const Preconditioner& precond, int& iters,
+              const Preconditioner& precond, Index& iters,
               typename Dest::RealScalar& tol_error)
 {
   using std::sqrt;
   using std::abs;
   typedef typename Dest::RealScalar RealScalar;
   typedef typename Dest::Scalar Scalar;
   typedef Matrix<Scalar,Dynamic,1> VectorType;
   RealScalar tol = tol_error;
-  int maxIters = iters;
+  Index maxIters = iters;
 
-  int n = mat.cols();
+  Index n = mat.cols();
   VectorType r  = rhs - mat * x;
   VectorType r0 = r;
   
   RealScalar r0_sqnorm = r0.squaredNorm();
   RealScalar rhs_sqnorm = rhs.squaredNorm();
@@ -57,24 +57,25 @@
   VectorType y(n),  z(n);
   VectorType kt(n), ks(n);
 
   VectorType s(n), t(n);
 
-  RealScalar tol2 = tol*tol;
+  RealScalar tol2 = tol*tol*rhs_sqnorm;
   RealScalar eps2 = NumTraits<Scalar>::epsilon()*NumTraits<Scalar>::epsilon();
-  int i = 0;
-  int restarts = 0;
+  Index i = 0;
+  Index restarts = 0;
 
-  while ( r.squaredNorm()/rhs_sqnorm > tol2 && i<maxIters )
+  while ( r.squaredNorm() > tol2 && i<maxIters )
   {
     Scalar rho_old = rho;
 
     rho = r0.dot(r);
     if (abs(rho) < eps2*r0_sqnorm)
     {
-      // The new residual vector became too orthogonal to the arbitrarily choosen direction r0
+      // The new residual vector became too orthogonal to the arbitrarily chosen direction r0
       // Let's restart with a new r0:
+      r  = rhs - mat * x;
       r0 = r;
       rho = r0_sqnorm = r.squaredNorm();
       if(restarts++ == 0)
         i = 0;
     }
@@ -128,61 +129,45 @@
   * This class allows to solve for A.x = b sparse linear problems using a bi conjugate gradient
   * stabilized algorithm. The vectors x and b can be either dense or sparse.
   *
   * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix.
   * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
+  *
+  * \implsparsesolverconcept
   *
   * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
   * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
   * and NumTraits<Scalar>::epsilon() for the tolerance.
+  * 
+  * The tolerance corresponds to the relative residual error: |Ax-b|/|b|
+  * 
+  * \b Performance: when using sparse matrices, best performance is achied for a row-major sparse matrix format.
+  * Moreover, in this case multi-threading can be exploited if the user code is compiled with OpenMP enabled.
+  * See \ref TopicMultiThreading for details.
   * 
   * This class can be used as the direct solver classes. Here is a typical usage example:
-  * \code
-  * int n = 10000;
-  * VectorXd x(n), b(n);
-  * SparseMatrix<double> A(n,n);
-  * // fill A and b
-  * BiCGSTAB<SparseMatrix<double> > solver;
-  * solver.compute(A);
-  * x = solver.solve(b);
-  * std::cout << "#iterations:     " << solver.iterations() << std::endl;
-  * std::cout << "estimated error: " << solver.error()      << std::endl;
-  * // update b, and solve again
-  * x = solver.solve(b);
-  * \endcode
+  * \include BiCGSTAB_simple.cpp
   * 
   * By default the iterations start with x=0 as an initial guess of the solution.
-  * One can control the start using the solveWithGuess() method. Here is a step by
-  * step execution example starting with a random guess and printing the evolution
-  * of the estimated error:
-  * * \code
-  * x = VectorXd::Random(n);
-  * solver.setMaxIterations(1);
-  * int i = 0;
-  * do {
-  *   x = solver.solveWithGuess(b,x);
-  *   std::cout << i << " : " << solver.error() << std::endl;
-  *   ++i;
-  * } while (solver.info()!=Success && i<100);
-  * \endcode
-  * Note that such a step by step excution is slightly slower.
-  * 
+  * One can control the start using the solveWithGuess() method.
+  * 
+  * BiCGSTAB can also be used in a matrix-free context, see the following \link MatrixfreeSolverExample example \endlink.
+  *
   * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
   */
 template< typename _MatrixType, typename _Preconditioner>
 class BiCGSTAB : public IterativeSolverBase<BiCGSTAB<_MatrixType,_Preconditioner> >
 {
   typedef IterativeSolverBase<BiCGSTAB> Base;
-  using Base::mp_matrix;
+  using Base::matrix;
   using Base::m_error;
   using Base::m_iterations;
   using Base::m_info;
   using Base::m_isInitialized;
 public:
   typedef _MatrixType MatrixType;
   typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::RealScalar RealScalar;
   typedef _Preconditioner Preconditioner;
 
 public:
 
@@ -197,79 +182,47 @@
     * \warning this class stores a reference to the matrix A as well as some
     * precomputed values that depend on it. Therefore, if \a A is changed
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  BiCGSTAB(const MatrixType& A) : Base(A) {}
+  template<typename MatrixDerived>
+  explicit BiCGSTAB(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
 
   ~BiCGSTAB() {}
-  
-  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A
-    * \a x0 as an initial solution.
-    *
-    * \sa compute()
-    */
-  template<typename Rhs,typename Guess>
-  inline const internal::solve_retval_with_guess<BiCGSTAB, Rhs, Guess>
-  solveWithGuess(const MatrixBase<Rhs>& b, const Guess& x0) const
-  {
-    eigen_assert(m_isInitialized && "BiCGSTAB is not initialized.");
-    eigen_assert(Base::rows()==b.rows()
-              && "BiCGSTAB::solve(): invalid number of rows of the right hand side matrix b");
-    return internal::solve_retval_with_guess
-            <BiCGSTAB, Rhs, Guess>(*this, b.derived(), x0);
-  }
-  
+
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solveWithGuess(const Rhs& b, Dest& x) const
+  void _solve_with_guess_impl(const Rhs& b, Dest& x) const
   {    
     bool failed = false;
-    for(int j=0; j<b.cols(); ++j)
+    for(Index j=0; j<b.cols(); ++j)
     {
       m_iterations = Base::maxIterations();
       m_error = Base::m_tolerance;
       
       typename Dest::ColXpr xj(x,j);
-      if(!internal::bicgstab(*mp_matrix, b.col(j), xj, Base::m_preconditioner, m_iterations, m_error))
+      if(!internal::bicgstab(matrix(), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error))
         failed = true;
     }
     m_info = failed ? NumericalIssue
            : m_error <= Base::m_tolerance ? Success
            : NoConvergence;
     m_isInitialized = true;
   }
 
   /** \internal */
+  using Base::_solve_impl;
   template<typename Rhs,typename Dest>
-  void _solve(const Rhs& b, Dest& x) const
+  void _solve_impl(const MatrixBase<Rhs>& b, Dest& x) const
   {
-//     x.setZero();
-  x = b;
-    _solveWithGuess(b,x);
+    x.resize(this->rows(),b.cols());
+    x.setZero();
+    _solve_with_guess_impl(b,x);
   }
 
 protected:
 
 };
 
-
-namespace internal {
-
-  template<typename _MatrixType, typename _Preconditioner, typename Rhs>
-struct solve_retval<BiCGSTAB<_MatrixType, _Preconditioner>, Rhs>
-  : solve_retval_base<BiCGSTAB<_MatrixType, _Preconditioner>, Rhs>
-{
-  typedef BiCGSTAB<_MatrixType, _Preconditioner> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-} // end namespace internal
-
 } // end namespace Eigen
 
 #endif // EIGEN_BICGSTAB_H

DELETED 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_IterativeLinearSolvers_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_IterativeLinearSolvers_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/IterativeLinearSolvers COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -24,23 +24,23 @@
   * \param tol_error On input the tolerance error, on output an estimation of the relative error.
   */
 template<typename MatrixType, typename Rhs, typename Dest, typename Preconditioner>
 EIGEN_DONT_INLINE
 void conjugate_gradient(const MatrixType& mat, const Rhs& rhs, Dest& x,
-                        const Preconditioner& precond, int& iters,
+                        const Preconditioner& precond, Index& iters,
                         typename Dest::RealScalar& tol_error)
 {
   using std::sqrt;
   using std::abs;
   typedef typename Dest::RealScalar RealScalar;
   typedef typename Dest::Scalar Scalar;
   typedef Matrix<Scalar,Dynamic,1> VectorType;
   
   RealScalar tol = tol_error;
-  int maxIters = iters;
+  Index maxIters = iters;
   
-  int n = mat.cols();
+  Index n = mat.cols();
 
   VectorType residual = rhs - mat * x; //initial residual
 
   RealScalar rhsNorm2 = rhs.squaredNorm();
   if(rhsNorm2 == 0) 
@@ -58,33 +58,33 @@
     tol_error = sqrt(residualNorm2 / rhsNorm2);
     return;
   }
   
   VectorType p(n);
-  p = precond.solve(residual);      //initial search direction
+  p = precond.solve(residual);      // initial search direction
 
   VectorType z(n), tmp(n);
   RealScalar absNew = numext::real(residual.dot(p));  // the square of the absolute value of r scaled by invM
-  int i = 0;
+  Index i = 0;
   while(i < maxIters)
   {
-    tmp.noalias() = mat * p;              // the bottleneck of the algorithm
+    tmp.noalias() = mat * p;                    // the bottleneck of the algorithm
 
-    Scalar alpha = absNew / p.dot(tmp);   // the amount we travel on dir
-    x += alpha * p;                       // update solution
-    residual -= alpha * tmp;              // update residue
+    Scalar alpha = absNew / p.dot(tmp);         // the amount we travel on dir
+    x += alpha * p;                             // update solution
+    residual -= alpha * tmp;                    // update residual
     
     residualNorm2 = residual.squaredNorm();
     if(residualNorm2 < threshold)
       break;
     
-    z = precond.solve(residual);          // approximately solve for "A z = residual"
+    z = precond.solve(residual);                // approximately solve for "A z = residual"
 
     RealScalar absOld = absNew;
     absNew = numext::real(residual.dot(z));     // update the absolute value of r
-    RealScalar beta = absNew / absOld;            // calculate the Gram-Schmidt value used to create the new search direction
-    p = z + beta * p;                             // update search direction
+    RealScalar beta = absNew / absOld;          // calculate the Gram-Schmidt value used to create the new search direction
+    p = z + beta * p;                           // update search direction
     i++;
   }
   tol_error = sqrt(residualNorm2 / rhsNorm2);
   iters = i;
 }
@@ -105,70 +105,68 @@
 };
 
 }
 
 /** \ingroup IterativeLinearSolvers_Module
-  * \brief A conjugate gradient solver for sparse self-adjoint problems
-  *
-  * This class allows to solve for A.x = b sparse linear problems using a conjugate gradient algorithm.
-  * The sparse matrix A must be selfadjoint. The vectors x and b can be either dense or sparse.
-  *
-  * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix.
-  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
-  *               or Upper. Default is Lower.
+  * \brief A conjugate gradient solver for sparse (or dense) self-adjoint problems
+  *
+  * This class allows to solve for A.x = b linear problems using an iterative conjugate gradient algorithm.
+  * The matrix A must be selfadjoint. The matrix A and the vectors x and b can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the matrix A, can be a dense or a sparse matrix.
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower,
+  *               \c Upper, or \c Lower|Upper in which the full matrix entries will be considered.
+  *               Default is \c Lower, best performance is \c Lower|Upper.
   * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
+  *
+  * \implsparsesolverconcept
   *
   * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
   * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
   * and NumTraits<Scalar>::epsilon() for the tolerance.
+  * 
+  * The tolerance corresponds to the relative residual error: |Ax-b|/|b|
+  * 
+  * \b Performance: Even though the default value of \c _UpLo is \c Lower, significantly higher performance is
+  * achieved when using a complete matrix and \b Lower|Upper as the \a _UpLo template parameter. Moreover, in this
+  * case multi-threading can be exploited if the user code is compiled with OpenMP enabled.
+  * See \ref TopicMultiThreading for details.
   * 
   * This class can be used as the direct solver classes. Here is a typical usage example:
-  * \code
-  * int n = 10000;
-  * VectorXd x(n), b(n);
-  * SparseMatrix<double> A(n,n);
-  * // fill A and b
-  * ConjugateGradient<SparseMatrix<double> > cg;
-  * cg.compute(A);
-  * x = cg.solve(b);
-  * std::cout << "#iterations:     " << cg.iterations() << std::endl;
-  * std::cout << "estimated error: " << cg.error()      << std::endl;
-  * // update b, and solve again
-  * x = cg.solve(b);
-  * \endcode
+    \code
+    int n = 10000;
+    VectorXd x(n), b(n);
+    SparseMatrix<double> A(n,n);
+    // fill A and b
+    ConjugateGradient<SparseMatrix<double>, Lower|Upper> cg;
+    cg.compute(A);
+    x = cg.solve(b);
+    std::cout << "#iterations:     " << cg.iterations() << std::endl;
+    std::cout << "estimated error: " << cg.error()      << std::endl;
+    // update b, and solve again
+    x = cg.solve(b);
+    \endcode
   * 
   * By default the iterations start with x=0 as an initial guess of the solution.
-  * One can control the start using the solveWithGuess() method. Here is a step by
-  * step execution example starting with a random guess and printing the evolution
-  * of the estimated error:
-  * * \code
-  * x = VectorXd::Random(n);
-  * cg.setMaxIterations(1);
-  * int i = 0;
-  * do {
-  *   x = cg.solveWithGuess(b,x);
-  *   std::cout << i << " : " << cg.error() << std::endl;
-  *   ++i;
-  * } while (cg.info()!=Success && i<100);
-  * \endcode
-  * Note that such a step by step excution is slightly slower.
-  * 
-  * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
+  * One can control the start using the solveWithGuess() method.
+  * 
+  * ConjugateGradient can also be used in a matrix-free context, see the following \link MatrixfreeSolverExample example \endlink.
+  *
+  * \sa class LeastSquaresConjugateGradient, class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
   */
 template< typename _MatrixType, int _UpLo, typename _Preconditioner>
 class ConjugateGradient : public IterativeSolverBase<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
 {
   typedef IterativeSolverBase<ConjugateGradient> Base;
-  using Base::mp_matrix;
+  using Base::matrix;
   using Base::m_error;
   using Base::m_iterations;
   using Base::m_info;
   using Base::m_isInitialized;
 public:
   typedef _MatrixType MatrixType;
   typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::RealScalar RealScalar;
   typedef _Preconditioner Preconditioner;
 
   enum {
     UpLo = _UpLo
@@ -187,79 +185,61 @@
     * \warning this class stores a reference to the matrix A as well as some
     * precomputed values that depend on it. Therefore, if \a A is changed
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  ConjugateGradient(const MatrixType& A) : Base(A) {}
+  template<typename MatrixDerived>
+  explicit ConjugateGradient(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
 
   ~ConjugateGradient() {}
-  
-  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A
-    * \a x0 as an initial solution.
-    *
-    * \sa compute()
-    */
-  template<typename Rhs,typename Guess>
-  inline const internal::solve_retval_with_guess<ConjugateGradient, Rhs, Guess>
-  solveWithGuess(const MatrixBase<Rhs>& b, const Guess& x0) const
-  {
-    eigen_assert(m_isInitialized && "ConjugateGradient is not initialized.");
-    eigen_assert(Base::rows()==b.rows()
-              && "ConjugateGradient::solve(): invalid number of rows of the right hand side matrix b");
-    return internal::solve_retval_with_guess
-            <ConjugateGradient, Rhs, Guess>(*this, b.derived(), x0);
-  }
 
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solveWithGuess(const Rhs& b, Dest& x) const
+  void _solve_with_guess_impl(const Rhs& b, Dest& x) const
   {
+    typedef typename Base::MatrixWrapper MatrixWrapper;
+    typedef typename Base::ActualMatrixType ActualMatrixType;
+    enum {
+      TransposeInput  =   (!MatrixWrapper::MatrixFree)
+                      &&  (UpLo==(Lower|Upper))
+                      &&  (!MatrixType::IsRowMajor)
+                      &&  (!NumTraits<Scalar>::IsComplex)
+    };
+    typedef typename internal::conditional<TransposeInput,Transpose<const ActualMatrixType>, ActualMatrixType const&>::type RowMajorWrapper;
+    EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(MatrixWrapper::MatrixFree,UpLo==(Lower|Upper)),MATRIX_FREE_CONJUGATE_GRADIENT_IS_COMPATIBLE_WITH_UPPER_UNION_LOWER_MODE_ONLY);
+    typedef typename internal::conditional<UpLo==(Lower|Upper),
+                                           RowMajorWrapper,
+                                           typename MatrixWrapper::template ConstSelfAdjointViewReturnType<UpLo>::Type
+                                          >::type SelfAdjointWrapper;
     m_iterations = Base::maxIterations();
     m_error = Base::m_tolerance;
 
-    for(int j=0; j<b.cols(); ++j)
+    for(Index j=0; j<b.cols(); ++j)
     {
       m_iterations = Base::maxIterations();
       m_error = Base::m_tolerance;
 
       typename Dest::ColXpr xj(x,j);
-      internal::conjugate_gradient(mp_matrix->template selfadjointView<UpLo>(), b.col(j), xj,
-                                   Base::m_preconditioner, m_iterations, m_error);
+      RowMajorWrapper row_mat(matrix());
+      internal::conjugate_gradient(SelfAdjointWrapper(row_mat), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
     }
 
     m_isInitialized = true;
     m_info = m_error <= Base::m_tolerance ? Success : NoConvergence;
   }
   
   /** \internal */
+  using Base::_solve_impl;
   template<typename Rhs,typename Dest>
-  void _solve(const Rhs& b, Dest& x) const
+  void _solve_impl(const MatrixBase<Rhs>& b, Dest& x) const
   {
-    x.setOnes();
-    _solveWithGuess(b,x);
+    x.setZero();
+    _solve_with_guess_impl(b.derived(),x);
   }
 
 protected:
 
 };
 
-
-namespace internal {
-
-template<typename _MatrixType, int _UpLo, typename _Preconditioner, typename Rhs>
-struct solve_retval<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner>, Rhs>
-  : solve_retval_base<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner>, Rhs>
-{
-  typedef ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-} // end namespace internal
-
 } // end namespace Eigen
 
 #endif // EIGEN_CONJUGATE_GRADIENT_H

ADDED   3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IncompleteCholesky.h
Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IncompleteCholesky.h
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IncompleteCholesky.h
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IncompleteCholesky.h
@@ -0,0 +1,400 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_INCOMPLETE_CHOlESKY_H
+#define EIGEN_INCOMPLETE_CHOlESKY_H
+
+#include <vector>
+#include <list>
+
+namespace Eigen {  
+/** 
+  * \brief Modified Incomplete Cholesky with dual threshold
+  *
+  * References : C-J. Lin and J. J. Moré, Incomplete Cholesky Factorizations with
+  *              Limited memory, SIAM J. Sci. Comput.  21(1), pp. 24-45, 1999
+  *
+  * \tparam Scalar the scalar type of the input matrices
+  * \tparam _UpLo The triangular part that will be used for the computations. It can be Lower
+    *               or Upper. Default is Lower.
+  * \tparam _OrderingType The ordering method to use, either AMDOrdering<> or NaturalOrdering<>. Default is AMDOrdering<int>,
+  *                       unless EIGEN_MPL2_ONLY is defined, in which case the default is NaturalOrdering<int>.
+  *
+  * \implsparsesolverconcept
+  *
+  * It performs the following incomplete factorization: \f$ S P A P' S \approx L L' \f$
+  * where L is a lower triangular factor, S is a diagonal scaling matrix, and P is a
+  * fill-in reducing permutation as computed by the ordering method.
+  *
+  * \b Shifting \b strategy: Let \f$ B = S P A P' S \f$  be the scaled matrix on which the factorization is carried out,
+  * and \f$ \beta \f$ be the minimum value of the diagonal. If \f$ \beta > 0 \f$ then, the factorization is directly performed
+  * on the matrix B. Otherwise, the factorization is performed on the shifted matrix \f$ B + (\sigma+|\beta| I \f$ where
+  * \f$ \sigma \f$ is the initial shift value as returned and set by setInitialShift() method. The default value is \f$ \sigma = 10^{-3} \f$.
+  * If the factorization fails, then the shift in doubled until it succeed or a maximum of ten attempts. If it still fails, as returned by
+  * the info() method, then you can either increase the initial shift, or better use another preconditioning technique.
+  *
+  */
+template <typename Scalar, int _UpLo = Lower, typename _OrderingType =
+#ifndef EIGEN_MPL2_ONLY
+AMDOrdering<int>
+#else
+NaturalOrdering<int>
+#endif
+>
+class IncompleteCholesky : public SparseSolverBase<IncompleteCholesky<Scalar,_UpLo,_OrderingType> >
+{
+  protected:
+    typedef SparseSolverBase<IncompleteCholesky<Scalar,_UpLo,_OrderingType> > Base;
+    using Base::m_isInitialized;
+  public:
+    typedef typename NumTraits<Scalar>::Real RealScalar; 
+    typedef _OrderingType OrderingType;
+    typedef typename OrderingType::PermutationType PermutationType;
+    typedef typename PermutationType::StorageIndex StorageIndex; 
+    typedef SparseMatrix<Scalar,ColMajor,StorageIndex> FactorType;
+    typedef Matrix<Scalar,Dynamic,1> VectorSx;
+    typedef Matrix<RealScalar,Dynamic,1> VectorRx;
+    typedef Matrix<StorageIndex,Dynamic, 1> VectorIx;
+    typedef std::vector<std::list<StorageIndex> > VectorList; 
+    enum { UpLo = _UpLo };
+    enum {
+      ColsAtCompileTime = Dynamic,
+      MaxColsAtCompileTime = Dynamic
+    };
+  public:
+
+    /** Default constructor leaving the object in a partly non-initialized stage.
+      *
+      * You must call compute() or the pair analyzePattern()/factorize() to make it valid.
+      *
+      * \sa IncompleteCholesky(const MatrixType&)
+      */
+    IncompleteCholesky() : m_initialShift(1e-3),m_factorizationIsOk(false) {}
+    
+    /** Constructor computing the incomplete factorization for the given matrix \a matrix.
+      */
+    template<typename MatrixType>
+    IncompleteCholesky(const MatrixType& matrix) : m_initialShift(1e-3),m_factorizationIsOk(false)
+    {
+      compute(matrix);
+    }
+    
+    /** \returns number of rows of the factored matrix */
+    Index rows() const { return m_L.rows(); }
+    
+    /** \returns number of columns of the factored matrix */
+    Index cols() const { return m_L.cols(); }
+    
+
+    /** \brief Reports whether previous computation was successful.
+      *
+      * It triggers an assertion if \c *this has not been initialized through the respective constructor,
+      * or a call to compute() or analyzePattern().
+      *
+      * \returns \c Success if computation was successful,
+      *          \c NumericalIssue if the matrix appears to be negative.
+      */
+    ComputationInfo info() const
+    {
+      eigen_assert(m_isInitialized && "IncompleteCholesky is not initialized.");
+      return m_info;
+    }
+    
+    /** \brief Set the initial shift parameter \f$ \sigma \f$.
+      */
+    void setInitialShift(RealScalar shift) { m_initialShift = shift; }
+    
+    /** \brief Computes the fill reducing permutation vector using the sparsity pattern of \a mat
+      */
+    template<typename MatrixType>
+    void analyzePattern(const MatrixType& mat)
+    {
+      OrderingType ord; 
+      PermutationType pinv;
+      ord(mat.template selfadjointView<UpLo>(), pinv); 
+      if(pinv.size()>0) m_perm = pinv.inverse();
+      else              m_perm.resize(0);
+      m_L.resize(mat.rows(), mat.cols());
+      m_analysisIsOk = true;
+      m_isInitialized = true;
+      m_info = Success;
+    }
+    
+    /** \brief Performs the numerical factorization of the input matrix \a mat
+      *
+      * The method analyzePattern() or compute() must have been called beforehand
+      * with a matrix having the same pattern.
+      *
+      * \sa compute(), analyzePattern()
+      */
+    template<typename MatrixType>
+    void factorize(const MatrixType& mat);
+    
+    /** Computes or re-computes the incomplete Cholesky factorization of the input matrix \a mat
+      *
+      * It is a shortcut for a sequential call to the analyzePattern() and factorize() methods.
+      *
+      * \sa analyzePattern(), factorize()
+      */
+    template<typename MatrixType>
+    void compute(const MatrixType& mat)
+    {
+      analyzePattern(mat);
+      factorize(mat);
+    }
+    
+    // internal
+    template<typename Rhs, typename Dest>
+    void _solve_impl(const Rhs& b, Dest& x) const
+    {
+      eigen_assert(m_factorizationIsOk && "factorize() should be called first");
+      if (m_perm.rows() == b.rows())  x = m_perm * b;
+      else                            x = b;
+      x = m_scale.asDiagonal() * x;
+      x = m_L.template triangularView<Lower>().solve(x);
+      x = m_L.adjoint().template triangularView<Upper>().solve(x);
+      x = m_scale.asDiagonal() * x;
+      if (m_perm.rows() == b.rows())
+        x = m_perm.inverse() * x;
+    }
+
+    /** \returns the sparse lower triangular factor L */
+    const FactorType& matrixL() const { eigen_assert("m_factorizationIsOk"); return m_L; }
+
+    /** \returns a vector representing the scaling factor S */
+    const VectorRx& scalingS() const { eigen_assert("m_factorizationIsOk"); return m_scale; }
+
+    /** \returns the fill-in reducing permutation P (can be empty for a natural ordering) */
+    const PermutationType& permutationP() const { eigen_assert("m_analysisIsOk"); return m_perm; }
+
+  protected:
+    FactorType m_L;              // The lower part stored in CSC
+    VectorRx m_scale;            // The vector for scaling the matrix 
+    RealScalar m_initialShift;   // The initial shift parameter
+    bool m_analysisIsOk; 
+    bool m_factorizationIsOk; 
+    ComputationInfo m_info;
+    PermutationType m_perm; 
+
+  private:
+    inline void updateList(Ref<const VectorIx> colPtr, Ref<VectorIx> rowIdx, Ref<VectorSx> vals, const Index& col, const Index& jk, VectorIx& firstElt, VectorList& listCol); 
+}; 
+
+// Based on the following paper:
+//   C-J. Lin and J. J. Moré, Incomplete Cholesky Factorizations with
+//   Limited memory, SIAM J. Sci. Comput.  21(1), pp. 24-45, 1999
+//   http://ftp.mcs.anl.gov/pub/tech_reports/reports/P682.pdf
+template<typename Scalar, int _UpLo, typename OrderingType>
+template<typename _MatrixType>
+void IncompleteCholesky<Scalar,_UpLo, OrderingType>::factorize(const _MatrixType& mat)
+{
+  using std::sqrt;
+  eigen_assert(m_analysisIsOk && "analyzePattern() should be called first"); 
+    
+  // Dropping strategy : Keep only the p largest elements per column, where p is the number of elements in the column of the original matrix. Other strategies will be added
+  
+  // Apply the fill-reducing permutation computed in analyzePattern()
+  if (m_perm.rows() == mat.rows() ) // To detect the null permutation
+  {
+    // The temporary is needed to make sure that the diagonal entry is properly sorted
+    FactorType tmp(mat.rows(), mat.cols());
+    tmp = mat.template selfadjointView<_UpLo>().twistedBy(m_perm);
+    m_L.template selfadjointView<Lower>() = tmp.template selfadjointView<Lower>();
+  }
+  else
+  {
+    m_L.template selfadjointView<Lower>() = mat.template selfadjointView<_UpLo>();
+  }
+  
+  Index n = m_L.cols(); 
+  Index nnz = m_L.nonZeros();
+  Map<VectorSx> vals(m_L.valuePtr(), nnz);         //values
+  Map<VectorIx> rowIdx(m_L.innerIndexPtr(), nnz);  //Row indices
+  Map<VectorIx> colPtr( m_L.outerIndexPtr(), n+1); // Pointer to the beginning of each row
+  VectorIx firstElt(n-1); // for each j, points to the next entry in vals that will be used in the factorization
+  VectorList listCol(n);  // listCol(j) is a linked list of columns to update column j
+  VectorSx col_vals(n);   // Store a  nonzero values in each column
+  VectorIx col_irow(n);   // Row indices of nonzero elements in each column
+  VectorIx col_pattern(n);
+  col_pattern.fill(-1);
+  StorageIndex col_nnz;
+  
+  
+  // Computes the scaling factors 
+  m_scale.resize(n);
+  m_scale.setZero();
+  for (Index j = 0; j < n; j++)
+    for (Index k = colPtr[j]; k < colPtr[j+1]; k++)
+    {
+      m_scale(j) += numext::abs2(vals(k));
+      if(rowIdx[k]!=j)
+        m_scale(rowIdx[k]) += numext::abs2(vals(k));
+    }
+  
+  m_scale = m_scale.cwiseSqrt().cwiseSqrt();
+
+  for (Index j = 0; j < n; ++j)
+    if(m_scale(j)>(std::numeric_limits<RealScalar>::min)())
+      m_scale(j) = RealScalar(1)/m_scale(j);
+    else
+      m_scale(j) = 1;
+
+  // TODO disable scaling if not needed, i.e., if it is roughly uniform? (this will make solve() faster)
+  
+  // Scale and compute the shift for the matrix 
+  RealScalar mindiag = NumTraits<RealScalar>::highest();
+  for (Index j = 0; j < n; j++)
+  {
+    for (Index k = colPtr[j]; k < colPtr[j+1]; k++)
+      vals[k] *= (m_scale(j)*m_scale(rowIdx[k]));
+    eigen_internal_assert(rowIdx[colPtr[j]]==j && "IncompleteCholesky: only the lower triangular part must be stored");
+    mindiag = numext::mini(numext::real(vals[colPtr[j]]), mindiag);
+  }
+
+  FactorType L_save = m_L;
+  
+  RealScalar shift = 0;
+  if(mindiag <= RealScalar(0.))
+    shift = m_initialShift - mindiag;
+
+  m_info = NumericalIssue;
+
+  // Try to perform the incomplete factorization using the current shift
+  int iter = 0;
+  do
+  {
+    // Apply the shift to the diagonal elements of the matrix
+    for (Index j = 0; j < n; j++)
+      vals[colPtr[j]] += shift;
+
+    // jki version of the Cholesky factorization
+    Index j=0;
+    for (; j < n; ++j)
+    {
+      // Left-looking factorization of the j-th column
+      // First, load the j-th column into col_vals
+      Scalar diag = vals[colPtr[j]];  // It is assumed that only the lower part is stored
+      col_nnz = 0;
+      for (Index i = colPtr[j] + 1; i < colPtr[j+1]; i++)
+      {
+        StorageIndex l = rowIdx[i];
+        col_vals(col_nnz) = vals[i];
+        col_irow(col_nnz) = l;
+        col_pattern(l) = col_nnz;
+        col_nnz++;
+      }
+      {
+        typename std::list<StorageIndex>::iterator k;
+        // Browse all previous columns that will update column j
+        for(k = listCol[j].begin(); k != listCol[j].end(); k++)
+        {
+          Index jk = firstElt(*k); // First element to use in the column
+          eigen_internal_assert(rowIdx[jk]==j);
+          Scalar v_j_jk = numext::conj(vals[jk]);
+
+          jk += 1;
+          for (Index i = jk; i < colPtr[*k+1]; i++)
+          {
+            StorageIndex l = rowIdx[i];
+            if(col_pattern[l]<0)
+            {
+              col_vals(col_nnz) = vals[i] * v_j_jk;
+              col_irow[col_nnz] = l;
+              col_pattern(l) = col_nnz;
+              col_nnz++;
+            }
+            else
+              col_vals(col_pattern[l]) -= vals[i] * v_j_jk;
+          }
+          updateList(colPtr,rowIdx,vals, *k, jk, firstElt, listCol);
+        }
+      }
+
+      // Scale the current column
+      if(numext::real(diag) <= 0)
+      {
+        if(++iter>=10)
+          return;
+
+        // increase shift
+        shift = numext::maxi(m_initialShift,RealScalar(2)*shift);
+        // restore m_L, col_pattern, and listCol
+        vals = Map<const VectorSx>(L_save.valuePtr(), nnz);
+        rowIdx = Map<const VectorIx>(L_save.innerIndexPtr(), nnz);
+        colPtr = Map<const VectorIx>(L_save.outerIndexPtr(), n+1);
+        col_pattern.fill(-1);
+        for(Index i=0; i<n; ++i)
+          listCol[i].clear();
+
+        break;
+      }
+
+      RealScalar rdiag = sqrt(numext::real(diag));
+      vals[colPtr[j]] = rdiag;
+      for (Index k = 0; k<col_nnz; ++k)
+      {
+        Index i = col_irow[k];
+        //Scale
+        col_vals(k) /= rdiag;
+        //Update the remaining diagonals with col_vals
+        vals[colPtr[i]] -= numext::abs2(col_vals(k));
+      }
+      // Select the largest p elements
+      // p is the original number of elements in the column (without the diagonal)
+      Index p = colPtr[j+1] - colPtr[j] - 1 ;
+      Ref<VectorSx> cvals = col_vals.head(col_nnz);
+      Ref<VectorIx> cirow = col_irow.head(col_nnz);
+      internal::QuickSplit(cvals,cirow, p);
+      // Insert the largest p elements in the matrix
+      Index cpt = 0;
+      for (Index i = colPtr[j]+1; i < colPtr[j+1]; i++)
+      {
+        vals[i] = col_vals(cpt);
+        rowIdx[i] = col_irow(cpt);
+        // restore col_pattern:
+        col_pattern(col_irow(cpt)) = -1;
+        cpt++;
+      }
+      // Get the first smallest row index and put it after the diagonal element
+      Index jk = colPtr(j)+1;
+      updateList(colPtr,rowIdx,vals,j,jk,firstElt,listCol);
+    }
+
+    if(j==n)
+    {
+      m_factorizationIsOk = true;
+      m_info = Success;
+    }
+  } while(m_info!=Success);
+}
+
+template<typename Scalar, int _UpLo, typename OrderingType>
+inline void IncompleteCholesky<Scalar,_UpLo, OrderingType>::updateList(Ref<const VectorIx> colPtr, Ref<VectorIx> rowIdx, Ref<VectorSx> vals, const Index& col, const Index& jk, VectorIx& firstElt, VectorList& listCol)
+{
+  if (jk < colPtr(col+1) )
+  {
+    Index p = colPtr(col+1) - jk;
+    Index minpos; 
+    rowIdx.segment(jk,p).minCoeff(&minpos);
+    minpos += jk;
+    if (rowIdx(minpos) != rowIdx(jk))
+    {
+      //Swap
+      std::swap(rowIdx(jk),rowIdx(minpos));
+      std::swap(vals(jk),vals(minpos));
+    }
+    firstElt(col) = internal::convert_index<StorageIndex,Index>(jk);
+    listCol[rowIdx(jk)].push_back(internal::convert_index<StorageIndex,Index>(col));
+  }
+}
+
+} // end namespace Eigen 
+
+#endif

Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
@@ -1,9 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -22,11 +23,11 @@
   * abs(row(i)) <= abs(row(ncut)) if i>ncut 
   * \param row The vector of values
   * \param ind The array of index for the elements in @p row
   * \param ncut  The number of largest elements to keep
   **/ 
-template <typename VectorV, typename VectorI, typename Index>
+template <typename VectorV, typename VectorI>
 Index QuickSplit(VectorV &row, VectorI &ind, Index ncut)
 {
   typedef typename VectorV::RealScalar RealScalar;
   using std::swap;
   using std::abs;
@@ -63,10 +64,12 @@
 }// end namespace internal
 
 /** \ingroup IterativeLinearSolvers_Module
   * \class IncompleteLUT
   * \brief Incomplete LU factorization with dual-threshold strategy
+  *
+  * \implsparsesolverconcept
   *
   * During the numerical factorization, two dropping rules are used :
   *  1) any element whose magnitude is less than some tolerance is dropped.
   *    This tolerance is obtained by multiplying the input tolerance @p droptol 
   *    by the average magnitude of all the original elements in the current row.
@@ -90,32 +93,40 @@
   * See the Eigen mailing list archive, thread: ILUT, date: July 8, 2012:
   *   http://listengine.tuxfamily.org/lists.tuxfamily.org/eigen/2012/07/msg00064.html
   * alternatively, on GMANE:
   *   http://comments.gmane.org/gmane.comp.lib.eigen/3302
   */
-template <typename _Scalar>
-class IncompleteLUT : internal::noncopyable
+template <typename _Scalar, typename _StorageIndex = int>
+class IncompleteLUT : public SparseSolverBase<IncompleteLUT<_Scalar, _StorageIndex> >
 {
+  protected:
+    typedef SparseSolverBase<IncompleteLUT> Base;
+    using Base::m_isInitialized;
+  public:
     typedef _Scalar Scalar;
+    typedef _StorageIndex StorageIndex;
     typedef typename NumTraits<Scalar>::Real RealScalar;
     typedef Matrix<Scalar,Dynamic,1> Vector;
-    typedef SparseMatrix<Scalar,RowMajor> FactorType;
-    typedef SparseMatrix<Scalar,ColMajor> PermutType;
-    typedef typename FactorType::Index Index;
+    typedef Matrix<StorageIndex,Dynamic,1> VectorI;
+    typedef SparseMatrix<Scalar,RowMajor,StorageIndex> FactorType;
+
+    enum {
+      ColsAtCompileTime = Dynamic,
+      MaxColsAtCompileTime = Dynamic
+    };
 
   public:
-    typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
     
     IncompleteLUT()
       : m_droptol(NumTraits<Scalar>::dummy_precision()), m_fillfactor(10),
-        m_analysisIsOk(false), m_factorizationIsOk(false), m_isInitialized(false)
+        m_analysisIsOk(false), m_factorizationIsOk(false)
     {}
     
     template<typename MatrixType>
-    IncompleteLUT(const MatrixType& mat, const RealScalar& droptol=NumTraits<Scalar>::dummy_precision(), int fillfactor = 10)
+    explicit IncompleteLUT(const MatrixType& mat, const RealScalar& droptol=NumTraits<Scalar>::dummy_precision(), int fillfactor = 10)
       : m_droptol(droptol),m_fillfactor(fillfactor),
-        m_analysisIsOk(false),m_factorizationIsOk(false),m_isInitialized(false)
+        m_analysisIsOk(false),m_factorizationIsOk(false)
     {
       eigen_assert(fillfactor != 0);
       compute(mat); 
     }
     
@@ -144,39 +155,29 @@
       * Compute an incomplete LU factorization with dual threshold on the matrix mat
       * No pivoting is done in this version
       * 
       **/
     template<typename MatrixType>
-    IncompleteLUT<Scalar>& compute(const MatrixType& amat)
+    IncompleteLUT& compute(const MatrixType& amat)
     {
       analyzePattern(amat); 
       factorize(amat);
-      m_isInitialized = m_factorizationIsOk;
       return *this;
     }
 
     void setDroptol(const RealScalar& droptol); 
     void setFillfactor(int fillfactor); 
     
     template<typename Rhs, typename Dest>
-    void _solve(const Rhs& b, Dest& x) const
+    void _solve_impl(const Rhs& b, Dest& x) const
     {
-      x = m_Pinv * b;  
+      x = m_Pinv * b;
       x = m_lu.template triangularView<UnitLower>().solve(x);
       x = m_lu.template triangularView<Upper>().solve(x);
       x = m_P * x; 
     }
 
-    template<typename Rhs> inline const internal::solve_retval<IncompleteLUT, Rhs>
-     solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "IncompleteLUT is not initialized.");
-      eigen_assert(cols()==b.rows()
-                && "IncompleteLUT::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<IncompleteLUT, Rhs>(*this, b.derived());
-    }
-
 protected:
 
     /** keeps off-diagonal entries; drops diagonal entries */
     struct keep_diag {
       inline bool operator() (const Index& row, const Index& col, const Scalar&) const
@@ -190,83 +191,94 @@
     FactorType m_lu;
     RealScalar m_droptol;
     int m_fillfactor;
     bool m_analysisIsOk;
     bool m_factorizationIsOk;
-    bool m_isInitialized;
     ComputationInfo m_info;
-    PermutationMatrix<Dynamic,Dynamic,Index> m_P;     // Fill-reducing permutation
-    PermutationMatrix<Dynamic,Dynamic,Index> m_Pinv;  // Inverse permutation
+    PermutationMatrix<Dynamic,Dynamic,StorageIndex> m_P;     // Fill-reducing permutation
+    PermutationMatrix<Dynamic,Dynamic,StorageIndex> m_Pinv;  // Inverse permutation
 };
 
 /**
  * Set control parameter droptol
  *  \param droptol   Drop any element whose magnitude is less than this tolerance 
  **/ 
-template<typename Scalar>
-void IncompleteLUT<Scalar>::setDroptol(const RealScalar& droptol)
+template<typename Scalar, typename StorageIndex>
+void IncompleteLUT<Scalar,StorageIndex>::setDroptol(const RealScalar& droptol)
 {
   this->m_droptol = droptol;   
 }
 
 /**
  * Set control parameter fillfactor
  * \param fillfactor  This is used to compute the  number @p fill_in of largest elements to keep on each row. 
  **/ 
-template<typename Scalar>
-void IncompleteLUT<Scalar>::setFillfactor(int fillfactor)
+template<typename Scalar, typename StorageIndex>
+void IncompleteLUT<Scalar,StorageIndex>::setFillfactor(int fillfactor)
 {
   this->m_fillfactor = fillfactor;   
 }
 
-template <typename Scalar>
+template <typename Scalar, typename StorageIndex>
 template<typename _MatrixType>
-void IncompleteLUT<Scalar>::analyzePattern(const _MatrixType& amat)
+void IncompleteLUT<Scalar,StorageIndex>::analyzePattern(const _MatrixType& amat)
 {
   // Compute the Fill-reducing permutation
-  SparseMatrix<Scalar,ColMajor, Index> mat1 = amat;
-  SparseMatrix<Scalar,ColMajor, Index> mat2 = amat.transpose();
-  // Symmetrize the pattern
+  // Since ILUT does not perform any numerical pivoting,
+  // it is highly preferable to keep the diagonal through symmetric permutations.
+#ifndef EIGEN_MPL2_ONLY
+  // To this end, let's symmetrize the pattern and perform AMD on it.
+  SparseMatrix<Scalar,ColMajor, StorageIndex> mat1 = amat;
+  SparseMatrix<Scalar,ColMajor, StorageIndex> mat2 = amat.transpose();
   // FIXME for a matrix with nearly symmetric pattern, mat2+mat1 is the appropriate choice.
   //       on the other hand for a really non-symmetric pattern, mat2*mat1 should be prefered...
-  SparseMatrix<Scalar,ColMajor, Index> AtA = mat2 + mat1;
-  AtA.prune(keep_diag());
-  internal::minimum_degree_ordering<Scalar, Index>(AtA, m_P);  // Then compute the AMD ordering...
-
-  m_Pinv  = m_P.inverse(); // ... and the inverse permutation
+  SparseMatrix<Scalar,ColMajor, StorageIndex> AtA = mat2 + mat1;
+  AMDOrdering<StorageIndex> ordering;
+  ordering(AtA,m_P);
+  m_Pinv  = m_P.inverse(); // cache the inverse permutation
+#else
+  // If AMD is not available, (MPL2-only), then let's use the slower COLAMD routine.
+  SparseMatrix<Scalar,ColMajor, StorageIndex> mat1 = amat;
+  COLAMDOrdering<StorageIndex> ordering;
+  ordering(mat1,m_Pinv);
+  m_P = m_Pinv.inverse();
+#endif
 
   m_analysisIsOk = true;
+  m_factorizationIsOk = false;
+  m_isInitialized = true;
 }
 
-template <typename Scalar>
+template <typename Scalar, typename StorageIndex>
 template<typename _MatrixType>
-void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
+void IncompleteLUT<Scalar,StorageIndex>::factorize(const _MatrixType& amat)
 {
   using std::sqrt;
   using std::swap;
   using std::abs;
+  using internal::convert_index;
 
   eigen_assert((amat.rows() == amat.cols()) && "The factorization should be done on a square matrix");
   Index n = amat.cols();  // Size of the matrix
   m_lu.resize(n,n);
   // Declare Working vectors and variables
   Vector u(n) ;     // real values of the row -- maximum size is n --
-  VectorXi ju(n);   // column position of the values in u -- maximum size  is n
-  VectorXi jr(n);   // Indicate the position of the nonzero elements in the vector u -- A zero location is indicated by -1
+  VectorI ju(n);   // column position of the values in u -- maximum size  is n
+  VectorI jr(n);   // Indicate the position of the nonzero elements in the vector u -- A zero location is indicated by -1
 
   // Apply the fill-reducing permutation
   eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
-  SparseMatrix<Scalar,RowMajor, Index> mat;
+  SparseMatrix<Scalar,RowMajor, StorageIndex> mat;
   mat = amat.twistedBy(m_Pinv);
 
   // Initialization
   jr.fill(-1);
   ju.fill(0);
   u.fill(0);
 
   // number of largest elements to keep in each row:
-  Index fill_in =   static_cast<Index> (amat.nonZeros()*m_fillfactor)/n+1;
+  Index fill_in = (amat.nonZeros()*m_fillfactor)/n + 1;
   if (fill_in > n) fill_in = n;
 
   // number of largest nonzero elements to keep in the L and the U part of the current row:
   Index nnzL = fill_in/2;
   Index nnzU = nnzL;
@@ -277,25 +289,25 @@
   {
     // 1 - copy the lower and the upper part of the row i of mat in the working vector u
 
     Index sizeu = 1; // number of nonzero elements in the upper part of the current row
     Index sizel = 0; // number of nonzero elements in the lower part of the current row
-    ju(ii)    = ii;
+    ju(ii)    = convert_index<StorageIndex>(ii);
     u(ii)     = 0;
-    jr(ii)    = ii;
+    jr(ii)    = convert_index<StorageIndex>(ii);
     RealScalar rownorm = 0;
 
     typename FactorType::InnerIterator j_it(mat, ii); // Iterate through the current row ii
     for (; j_it; ++j_it)
     {
       Index k = j_it.index();
       if (k < ii)
       {
         // copy the lower part
-        ju(sizel) = k;
+        ju(sizel) = convert_index<StorageIndex>(k);
         u(sizel) = j_it.value();
-        jr(k) = sizel;
+        jr(k) = convert_index<StorageIndex>(sizel);
         ++sizel;
       }
       else if (k == ii)
       {
         u(ii) = j_it.value();
@@ -302,13 +314,13 @@
       }
       else
       {
         // copy the upper part
         Index jpos = ii + sizeu;
-        ju(jpos) = k;
+        ju(jpos) = convert_index<StorageIndex>(k);
         u(jpos) = j_it.value();
-        jr(k) = jpos;
+        jr(k) = convert_index<StorageIndex>(jpos);
         ++sizeu;
       }
       rownorm += numext::abs2(j_it.value());
     }
 
@@ -334,11 +346,12 @@
       if (minrow != ju(jj))
       {
         // swap the two locations
         Index j = ju(jj);
         swap(ju(jj), ju(k));
-        jr(minrow) = jj;   jr(j) = k;
+        jr(minrow) = convert_index<StorageIndex>(jj);
+        jr(j) = convert_index<StorageIndex>(k);
         swap(u(jj), u(k));
       }
       // Reset this location
       jr(minrow) = -1;
 
@@ -358,12 +371,12 @@
       // linear combination of the current row ii and the row minrow
       ++ki_it;
       for (; ki_it; ++ki_it)
       {
         Scalar prod = fact * ki_it.value();
-        Index j       = ki_it.index();
-        Index jpos    = jr(j);
+        Index j     = ki_it.index();
+        Index jpos  = jr(j);
         if (jpos == -1) // fill-in element
         {
           Index newpos;
           if (j >= ii) // dealing with the upper part
           {
@@ -375,20 +388,20 @@
           {
             newpos = sizel;
             sizel++;
             eigen_internal_assert(sizel<=ii);
           }
-          ju(newpos) = j;
+          ju(newpos) = convert_index<StorageIndex>(j);
           u(newpos) = -prod;
-          jr(j) = newpos;
+          jr(j) = convert_index<StorageIndex>(newpos);
         }
         else
           u(jpos) -= prod;
       }
       // store the pivot element
-      u(len) = fact;
-      ju(len) = minrow;
+      u(len)  = fact;
+      ju(len) = convert_index<StorageIndex>(minrow);
       ++len;
 
       jj++;
     } // end of the elimination on the row ii
 
@@ -399,11 +412,11 @@
 
     // sort the L-part of the row
     sizel = len;
     len = (std::min)(sizel, nnzL);
     typename Vector::SegmentReturnType ul(u.segment(0, sizel));
-    typename VectorXi::SegmentReturnType jul(ju.segment(0, sizel));
+    typename VectorI::SegmentReturnType jul(ju.segment(0, sizel));
     internal::QuickSplit(ul, jul, len);
 
     // store the largest m_fill elements of the L part
     m_lu.startVec(ii);
     for(Index k = 0; k < len; k++)
@@ -428,40 +441,22 @@
       }
     }
     sizeu = len + 1; // +1 to take into account the diagonal element
     len = (std::min)(sizeu, nnzU);
     typename Vector::SegmentReturnType uu(u.segment(ii+1, sizeu-1));
-    typename VectorXi::SegmentReturnType juu(ju.segment(ii+1, sizeu-1));
+    typename VectorI::SegmentReturnType juu(ju.segment(ii+1, sizeu-1));
     internal::QuickSplit(uu, juu, len);
 
     // store the largest elements of the U part
     for(Index k = ii + 1; k < ii + len; k++)
       m_lu.insertBackByOuterInnerUnordered(ii,ju(k)) = u(k);
   }
-
   m_lu.finalize();
   m_lu.makeCompressed();
 
   m_factorizationIsOk = true;
   m_info = Success;
 }
 
-namespace internal {
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<IncompleteLUT<_MatrixType>, Rhs>
-  : solve_retval_base<IncompleteLUT<_MatrixType>, Rhs>
-{
-  typedef IncompleteLUT<_MatrixType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-} // end namespace internal
-
 } // end namespace Eigen
 
 #endif // EIGEN_INCOMPLETE_LUT_H

Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
@@ -1,42 +1,171 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ITERATIVE_SOLVER_BASE_H
 #define EIGEN_ITERATIVE_SOLVER_BASE_H
 
 namespace Eigen { 
+
+namespace internal {
+
+template<typename MatrixType>
+struct is_ref_compatible_impl
+{
+private:
+  template <typename T0>
+  struct any_conversion
+  {
+    template <typename T> any_conversion(const volatile T&);
+    template <typename T> any_conversion(T&);
+  };
+  struct yes {int a[1];};
+  struct no  {int a[2];};
+
+  template<typename T>
+  static yes test(const Ref<const T>&, int);
+  template<typename T>
+  static no  test(any_conversion<T>, ...);
+
+public:
+  static MatrixType ms_from;
+  enum { value = sizeof(test<MatrixType>(ms_from, 0))==sizeof(yes) };
+};
+
+template<typename MatrixType>
+struct is_ref_compatible
+{
+  enum { value = is_ref_compatible_impl<typename remove_all<MatrixType>::type>::value };
+};
+
+template<typename MatrixType, bool MatrixFree = !internal::is_ref_compatible<MatrixType>::value>
+class generic_matrix_wrapper;
+
+// We have an explicit matrix at hand, compatible with Ref<>
+template<typename MatrixType>
+class generic_matrix_wrapper<MatrixType,false>
+{
+public:
+  typedef Ref<const MatrixType> ActualMatrixType;
+  template<int UpLo> struct ConstSelfAdjointViewReturnType {
+    typedef typename ActualMatrixType::template ConstSelfAdjointViewReturnType<UpLo>::Type Type;
+  };
+
+  enum {
+    MatrixFree = false
+  };
+
+  generic_matrix_wrapper()
+    : m_dummy(0,0), m_matrix(m_dummy)
+  {}
+
+  template<typename InputType>
+  generic_matrix_wrapper(const InputType &mat)
+    : m_matrix(mat)
+  {}
+
+  const ActualMatrixType& matrix() const
+  {
+    return m_matrix;
+  }
+
+  template<typename MatrixDerived>
+  void grab(const EigenBase<MatrixDerived> &mat)
+  {
+    m_matrix.~Ref<const MatrixType>();
+    ::new (&m_matrix) Ref<const MatrixType>(mat.derived());
+  }
+
+  void grab(const Ref<const MatrixType> &mat)
+  {
+    if(&(mat.derived()) != &m_matrix)
+    {
+      m_matrix.~Ref<const MatrixType>();
+      ::new (&m_matrix) Ref<const MatrixType>(mat);
+    }
+  }
+
+protected:
+  MatrixType m_dummy; // used to default initialize the Ref<> object
+  ActualMatrixType m_matrix;
+};
+
+// MatrixType is not compatible with Ref<> -> matrix-free wrapper
+template<typename MatrixType>
+class generic_matrix_wrapper<MatrixType,true>
+{
+public:
+  typedef MatrixType ActualMatrixType;
+  template<int UpLo> struct ConstSelfAdjointViewReturnType
+  {
+    typedef ActualMatrixType Type;
+  };
+
+  enum {
+    MatrixFree = true
+  };
+
+  generic_matrix_wrapper()
+    : mp_matrix(0)
+  {}
+
+  generic_matrix_wrapper(const MatrixType &mat)
+    : mp_matrix(&mat)
+  {}
+
+  const ActualMatrixType& matrix() const
+  {
+    return *mp_matrix;
+  }
+
+  void grab(const MatrixType &mat)
+  {
+    mp_matrix = &mat;
+  }
+
+protected:
+  const ActualMatrixType *mp_matrix;
+};
+
+}
 
 /** \ingroup IterativeLinearSolvers_Module
   * \brief Base class for linear iterative solvers
   *
   * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
   */
 template< typename Derived>
-class IterativeSolverBase : internal::noncopyable
+class IterativeSolverBase : public SparseSolverBase<Derived>
 {
+protected:
+  typedef SparseSolverBase<Derived> Base;
+  using Base::m_isInitialized;
+  
 public:
   typedef typename internal::traits<Derived>::MatrixType MatrixType;
   typedef typename internal::traits<Derived>::Preconditioner Preconditioner;
   typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::StorageIndex StorageIndex;
   typedef typename MatrixType::RealScalar RealScalar;
+
+  enum {
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+  };
 
 public:
 
-  Derived& derived() { return *static_cast<Derived*>(this); }
-  const Derived& derived() const { return *static_cast<const Derived*>(this); }
+  using Base::derived;
 
   /** Default constructor. */
   IterativeSolverBase()
-    : mp_matrix(0)
   {
     init();
   }
 
   /** Initialize the solver with matrix \a A for further \c Ax=b solving.
@@ -47,81 +176,94 @@
     * \warning this class stores a reference to the matrix A as well as some
     * precomputed values that depend on it. Therefore, if \a A is changed
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  IterativeSolverBase(const MatrixType& A)
+  template<typename MatrixDerived>
+  explicit IterativeSolverBase(const EigenBase<MatrixDerived>& A)
+    : m_matrixWrapper(A.derived())
   {
     init();
-    compute(A);
+    compute(matrix());
   }
 
   ~IterativeSolverBase() {}
   
-  /** Initializes the iterative solver for the sparcity pattern of the matrix \a A for further solving \c Ax=b problems.
+  /** Initializes the iterative solver for the sparsity pattern of the matrix \a A for further solving \c Ax=b problems.
     *
-    * Currently, this function mostly call analyzePattern on the preconditioner. In the future
-    * we might, for instance, implement column reodering for faster matrix vector products.
+    * Currently, this function mostly calls analyzePattern on the preconditioner. In the future
+    * we might, for instance, implement column reordering for faster matrix vector products.
     */
-  Derived& analyzePattern(const MatrixType& A)
+  template<typename MatrixDerived>
+  Derived& analyzePattern(const EigenBase<MatrixDerived>& A)
   {
-    m_preconditioner.analyzePattern(A);
+    grab(A.derived());
+    m_preconditioner.analyzePattern(matrix());
     m_isInitialized = true;
     m_analysisIsOk = true;
-    m_info = Success;
+    m_info = m_preconditioner.info();
     return derived();
   }
   
   /** Initializes the iterative solver with the numerical values of the matrix \a A for further solving \c Ax=b problems.
     *
-    * Currently, this function mostly call factorize on the preconditioner.
+    * Currently, this function mostly calls factorize on the preconditioner.
     *
     * \warning this class stores a reference to the matrix A as well as some
     * precomputed values that depend on it. Therefore, if \a A is changed
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  Derived& factorize(const MatrixType& A)
+  template<typename MatrixDerived>
+  Derived& factorize(const EigenBase<MatrixDerived>& A)
   {
     eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); 
-    mp_matrix = &A;
-    m_preconditioner.factorize(A);
+    grab(A.derived());
+    m_preconditioner.factorize(matrix());
     m_factorizationIsOk = true;
-    m_info = Success;
+    m_info = m_preconditioner.info();
     return derived();
   }
 
   /** Initializes the iterative solver with the matrix \a A for further solving \c Ax=b problems.
     *
-    * Currently, this function mostly initialized/compute the preconditioner. In the future
-    * we might, for instance, implement column reodering for faster matrix vector products.
+    * Currently, this function mostly initializes/computes the preconditioner. In the future
+    * we might, for instance, implement column reordering for faster matrix vector products.
     *
     * \warning this class stores a reference to the matrix A as well as some
     * precomputed values that depend on it. Therefore, if \a A is changed
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  Derived& compute(const MatrixType& A)
+  template<typename MatrixDerived>
+  Derived& compute(const EigenBase<MatrixDerived>& A)
   {
-    mp_matrix = &A;
-    m_preconditioner.compute(A);
+    grab(A.derived());
+    m_preconditioner.compute(matrix());
     m_isInitialized = true;
     m_analysisIsOk = true;
     m_factorizationIsOk = true;
-    m_info = Success;
+    m_info = m_preconditioner.info();
     return derived();
   }
 
   /** \internal */
-  Index rows() const { return mp_matrix ? mp_matrix->rows() : 0; }
+  Index rows() const { return matrix().rows(); }
+
   /** \internal */
-  Index cols() const { return mp_matrix ? mp_matrix->cols() : 0; }
+  Index cols() const { return matrix().cols(); }
 
-  /** \returns the tolerance threshold used by the stopping criteria */
+  /** \returns the tolerance threshold used by the stopping criteria.
+    * \sa setTolerance()
+    */
   RealScalar tolerance() const { return m_tolerance; }
   
-  /** Sets the tolerance threshold used by the stopping criteria */
+  /** Sets the tolerance threshold used by the stopping criteria.
+    *
+    * This value is used as an upper bound to the relative residual error: |Ax-b|/|b|.
+    * The default value is the machine precision given by NumTraits<Scalar>::epsilon()
+    */
   Derived& setTolerance(const RealScalar& tolerance)
   {
     m_tolerance = tolerance;
     return derived();
   }
@@ -130,62 +272,56 @@
   Preconditioner& preconditioner() { return m_preconditioner; }
   
   /** \returns a read-only reference to the preconditioner. */
   const Preconditioner& preconditioner() const { return m_preconditioner; }
 
-  /** \returns the max number of iterations */
-  int maxIterations() const
+  /** \returns the max number of iterations.
+    * It is either the value setted by setMaxIterations or, by default,
+    * twice the number of columns of the matrix.
+    */
+  Index maxIterations() const
   {
-    return (mp_matrix && m_maxIterations<0) ? mp_matrix->cols() : m_maxIterations;
+    return (m_maxIterations<0) ? 2*matrix().cols() : m_maxIterations;
   }
   
-  /** Sets the max number of iterations */
-  Derived& setMaxIterations(int maxIters)
+  /** Sets the max number of iterations.
+    * Default is twice the number of columns of the matrix.
+    */
+  Derived& setMaxIterations(Index maxIters)
   {
     m_maxIterations = maxIters;
     return derived();
   }
 
   /** \returns the number of iterations performed during the last solve */
-  int iterations() const
+  Index iterations() const
   {
     eigen_assert(m_isInitialized && "ConjugateGradient is not initialized.");
     return m_iterations;
   }
 
-  /** \returns the tolerance error reached during the last solve */
+  /** \returns the tolerance error reached during the last solve.
+    * It is a close approximation of the true relative residual error |Ax-b|/|b|.
+    */
   RealScalar error() const
   {
     eigen_assert(m_isInitialized && "ConjugateGradient is not initialized.");
     return m_error;
   }
 
-  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-    *
-    * \sa compute()
-    */
-  template<typename Rhs> inline const internal::solve_retval<Derived, Rhs>
-  solve(const MatrixBase<Rhs>& b) const
-  {
-    eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized.");
-    eigen_assert(rows()==b.rows()
-              && "IterativeSolverBase::solve(): invalid number of rows of the right hand side matrix b");
-    return internal::solve_retval<Derived, Rhs>(derived(), b.derived());
-  }
-  
-  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-    *
-    * \sa compute()
-    */
-  template<typename Rhs>
-  inline const internal::sparse_solve_retval<IterativeSolverBase, Rhs>
-  solve(const SparseMatrixBase<Rhs>& b) const
-  {
-    eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized.");
-    eigen_assert(rows()==b.rows()
-              && "IterativeSolverBase::solve(): invalid number of rows of the right hand side matrix b");
-    return internal::sparse_solve_retval<IterativeSolverBase, Rhs>(*this, b.derived());
+  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A
+    * and \a x0 as an initial solution.
+    *
+    * \sa solve(), compute()
+    */
+  template<typename Rhs,typename Guess>
+  inline const SolveWithGuess<Derived, Rhs, Guess>
+  solveWithGuess(const MatrixBase<Rhs>& b, const Guess& x0) const
+  {
+    eigen_assert(m_isInitialized && "Solver is not initialized.");
+    eigen_assert(derived().rows()==b.rows() && "solve(): invalid number of rows of the right hand side matrix b");
+    return SolveWithGuess<Derived, Rhs, Guess>(derived(), b.derived(), x0);
   }
 
   /** \returns Success if the iterations converged, and NoConvergence otherwise. */
   ComputationInfo info() const
   {
@@ -192,25 +328,31 @@
     eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized.");
     return m_info;
   }
   
   /** \internal */
-  template<typename Rhs, typename DestScalar, int DestOptions, typename DestIndex>
-  void _solve_sparse(const Rhs& b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
+  template<typename Rhs, typename DestDerived>
+  void _solve_impl(const Rhs& b, SparseMatrixBase<DestDerived> &aDest) const
   {
     eigen_assert(rows()==b.rows());
     
-    int rhsCols = b.cols();
-    int size = b.rows();
+    Index rhsCols = b.cols();
+    Index size = b.rows();
+    DestDerived& dest(aDest.derived());
+    typedef typename DestDerived::Scalar DestScalar;
     Eigen::Matrix<DestScalar,Dynamic,1> tb(size);
-    Eigen::Matrix<DestScalar,Dynamic,1> tx(size);
-    for(int k=0; k<rhsCols; ++k)
+    Eigen::Matrix<DestScalar,Dynamic,1> tx(cols());
+    // We do not directly fill dest because sparse expressions have to be free of aliasing issue.
+    // For non square least-square problems, b and dest might not have the same size whereas they might alias each-other.
+    typename DestDerived::PlainObject tmp(cols(),rhsCols);
+    for(Index k=0; k<rhsCols; ++k)
     {
       tb = b.col(k);
       tx = derived().solve(tb);
-      dest.col(k) = tx.sparseView(0);
+      tmp.col(k) = tx.sparseView(0);
     }
+    dest.swap(tmp);
   }
 
 protected:
   void init()
   {
@@ -218,37 +360,35 @@
     m_analysisIsOk = false;
     m_factorizationIsOk = false;
     m_maxIterations = -1;
     m_tolerance = NumTraits<Scalar>::epsilon();
   }
-  const MatrixType* mp_matrix;
+
+  typedef internal::generic_matrix_wrapper<MatrixType> MatrixWrapper;
+  typedef typename MatrixWrapper::ActualMatrixType ActualMatrixType;
+
+  const ActualMatrixType& matrix() const
+  {
+    return m_matrixWrapper.matrix();
+  }
+  
+  template<typename InputType>
+  void grab(const InputType &A)
+  {
+    m_matrixWrapper.grab(A);
+  }
+  
+  MatrixWrapper m_matrixWrapper;
   Preconditioner m_preconditioner;
 
-  int m_maxIterations;
+  Index m_maxIterations;
   RealScalar m_tolerance;
   
   mutable RealScalar m_error;
-  mutable int m_iterations;
+  mutable Index m_iterations;
   mutable ComputationInfo m_info;
-  mutable bool m_isInitialized, m_analysisIsOk, m_factorizationIsOk;
-};
-
-namespace internal {
- 
-template<typename Derived, typename Rhs>
-struct sparse_solve_retval<IterativeSolverBase<Derived>, Rhs>
-  : sparse_solve_retval_base<IterativeSolverBase<Derived>, Rhs>
-{
-  typedef IterativeSolverBase<Derived> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec().derived()._solve_sparse(rhs(),dst);
-  }
-};
-
-} // end namespace internal
+  mutable bool m_analysisIsOk, m_factorizationIsOk;
+};
 
 } // end namespace Eigen
 
 #endif // EIGEN_ITERATIVE_SOLVER_BASE_H

ADDED   3rd_party/eigen/Eigen/src/IterativeLinearSolvers/LeastSquareConjugateGradient.h
Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/LeastSquareConjugateGradient.h
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/LeastSquareConjugateGradient.h
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/LeastSquareConjugateGradient.h
@@ -0,0 +1,216 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_LEAST_SQUARE_CONJUGATE_GRADIENT_H
+#define EIGEN_LEAST_SQUARE_CONJUGATE_GRADIENT_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/** \internal Low-level conjugate gradient algorithm for least-square problems
+  * \param mat The matrix A
+  * \param rhs The right hand side vector b
+  * \param x On input and initial solution, on output the computed solution.
+  * \param precond A preconditioner being able to efficiently solve for an
+  *                approximation of A'Ax=b (regardless of b)
+  * \param iters On input the max number of iteration, on output the number of performed iterations.
+  * \param tol_error On input the tolerance error, on output an estimation of the relative error.
+  */
+template<typename MatrixType, typename Rhs, typename Dest, typename Preconditioner>
+EIGEN_DONT_INLINE
+void least_square_conjugate_gradient(const MatrixType& mat, const Rhs& rhs, Dest& x,
+                                     const Preconditioner& precond, Index& iters,
+                                     typename Dest::RealScalar& tol_error)
+{
+  using std::sqrt;
+  using std::abs;
+  typedef typename Dest::RealScalar RealScalar;
+  typedef typename Dest::Scalar Scalar;
+  typedef Matrix<Scalar,Dynamic,1> VectorType;
+  
+  RealScalar tol = tol_error;
+  Index maxIters = iters;
+  
+  Index m = mat.rows(), n = mat.cols();
+
+  VectorType residual        = rhs - mat * x;
+  VectorType normal_residual = mat.adjoint() * residual;
+
+  RealScalar rhsNorm2 = (mat.adjoint()*rhs).squaredNorm();
+  if(rhsNorm2 == 0) 
+  {
+    x.setZero();
+    iters = 0;
+    tol_error = 0;
+    return;
+  }
+  RealScalar threshold = tol*tol*rhsNorm2;
+  RealScalar residualNorm2 = normal_residual.squaredNorm();
+  if (residualNorm2 < threshold)
+  {
+    iters = 0;
+    tol_error = sqrt(residualNorm2 / rhsNorm2);
+    return;
+  }
+  
+  VectorType p(n);
+  p = precond.solve(normal_residual);                         // initial search direction
+
+  VectorType z(n), tmp(m);
+  RealScalar absNew = numext::real(normal_residual.dot(p));  // the square of the absolute value of r scaled by invM
+  Index i = 0;
+  while(i < maxIters)
+  {
+    tmp.noalias() = mat * p;
+
+    Scalar alpha = absNew / tmp.squaredNorm();      // the amount we travel on dir
+    x += alpha * p;                                 // update solution
+    residual -= alpha * tmp;                        // update residual
+    normal_residual = mat.adjoint() * residual;     // update residual of the normal equation
+    
+    residualNorm2 = normal_residual.squaredNorm();
+    if(residualNorm2 < threshold)
+      break;
+    
+    z = precond.solve(normal_residual);             // approximately solve for "A'A z = normal_residual"
+
+    RealScalar absOld = absNew;
+    absNew = numext::real(normal_residual.dot(z));  // update the absolute value of r
+    RealScalar beta = absNew / absOld;              // calculate the Gram-Schmidt value used to create the new search direction
+    p = z + beta * p;                               // update search direction
+    i++;
+  }
+  tol_error = sqrt(residualNorm2 / rhsNorm2);
+  iters = i;
+}
+
+}
+
+template< typename _MatrixType,
+          typename _Preconditioner = LeastSquareDiagonalPreconditioner<typename _MatrixType::Scalar> >
+class LeastSquaresConjugateGradient;
+
+namespace internal {
+
+template< typename _MatrixType, typename _Preconditioner>
+struct traits<LeastSquaresConjugateGradient<_MatrixType,_Preconditioner> >
+{
+  typedef _MatrixType MatrixType;
+  typedef _Preconditioner Preconditioner;
+};
+
+}
+
+/** \ingroup IterativeLinearSolvers_Module
+  * \brief A conjugate gradient solver for sparse (or dense) least-square problems
+  *
+  * This class allows to solve for A x = b linear problems using an iterative conjugate gradient algorithm.
+  * The matrix A can be non symmetric and rectangular, but the matrix A' A should be positive-definite to guaranty stability.
+  * Otherwise, the SparseLU or SparseQR classes might be preferable.
+  * The matrix A and the vectors x and b can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the matrix A, can be a dense or a sparse matrix.
+  * \tparam _Preconditioner the type of the preconditioner. Default is LeastSquareDiagonalPreconditioner
+  *
+  * \implsparsesolverconcept
+  * 
+  * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
+  * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
+  * and NumTraits<Scalar>::epsilon() for the tolerance.
+  * 
+  * This class can be used as the direct solver classes. Here is a typical usage example:
+    \code
+    int m=1000000, n = 10000;
+    VectorXd x(n), b(m);
+    SparseMatrix<double> A(m,n);
+    // fill A and b
+    LeastSquaresConjugateGradient<SparseMatrix<double> > lscg;
+    lscg.compute(A);
+    x = lscg.solve(b);
+    std::cout << "#iterations:     " << lscg.iterations() << std::endl;
+    std::cout << "estimated error: " << lscg.error()      << std::endl;
+    // update b, and solve again
+    x = lscg.solve(b);
+    \endcode
+  * 
+  * By default the iterations start with x=0 as an initial guess of the solution.
+  * One can control the start using the solveWithGuess() method.
+  * 
+  * \sa class ConjugateGradient, SparseLU, SparseQR
+  */
+template< typename _MatrixType, typename _Preconditioner>
+class LeastSquaresConjugateGradient : public IterativeSolverBase<LeastSquaresConjugateGradient<_MatrixType,_Preconditioner> >
+{
+  typedef IterativeSolverBase<LeastSquaresConjugateGradient> Base;
+  using Base::matrix;
+  using Base::m_error;
+  using Base::m_iterations;
+  using Base::m_info;
+  using Base::m_isInitialized;
+public:
+  typedef _MatrixType MatrixType;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef _Preconditioner Preconditioner;
+
+public:
+
+  /** Default constructor. */
+  LeastSquaresConjugateGradient() : Base() {}
+
+  /** Initialize the solver with matrix \a A for further \c Ax=b solving.
+    * 
+    * This constructor is a shortcut for the default constructor followed
+    * by a call to compute().
+    * 
+    * \warning this class stores a reference to the matrix A as well as some
+    * precomputed values that depend on it. Therefore, if \a A is changed
+    * this class becomes invalid. Call compute() to update it with the new
+    * matrix A, or modify a copy of A.
+    */
+  template<typename MatrixDerived>
+  explicit LeastSquaresConjugateGradient(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
+
+  ~LeastSquaresConjugateGradient() {}
+
+  /** \internal */
+  template<typename Rhs,typename Dest>
+  void _solve_with_guess_impl(const Rhs& b, Dest& x) const
+  {
+    m_iterations = Base::maxIterations();
+    m_error = Base::m_tolerance;
+
+    for(Index j=0; j<b.cols(); ++j)
+    {
+      m_iterations = Base::maxIterations();
+      m_error = Base::m_tolerance;
+
+      typename Dest::ColXpr xj(x,j);
+      internal::least_square_conjugate_gradient(matrix(), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
+    }
+
+    m_isInitialized = true;
+    m_info = m_error <= Base::m_tolerance ? Success : NoConvergence;
+  }
+  
+  /** \internal */
+  using Base::_solve_impl;
+  template<typename Rhs,typename Dest>
+  void _solve_impl(const MatrixBase<Rhs>& b, Dest& x) const
+  {
+    x.setZero();
+    _solve_with_guess_impl(b.derived(),x);
+  }
+
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_LEAST_SQUARE_CONJUGATE_GRADIENT_H

ADDED   3rd_party/eigen/Eigen/src/IterativeLinearSolvers/SolveWithGuess.h
Index: 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/SolveWithGuess.h
==================================================================
--- 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/SolveWithGuess.h
+++ 3rd_party/eigen/Eigen/src/IterativeLinearSolvers/SolveWithGuess.h
@@ -0,0 +1,115 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SOLVEWITHGUESS_H
+#define EIGEN_SOLVEWITHGUESS_H
+
+namespace Eigen {
+
+template<typename Decomposition, typename RhsType, typename GuessType> class SolveWithGuess;
+  
+/** \class SolveWithGuess
+  * \ingroup IterativeLinearSolvers_Module
+  *
+  * \brief Pseudo expression representing a solving operation
+  *
+  * \tparam Decomposition the type of the matrix or decomposion object
+  * \tparam Rhstype the type of the right-hand side
+  *
+  * This class represents an expression of A.solve(B)
+  * and most of the time this is the only way it is used.
+  *
+  */
+namespace internal {
+
+
+template<typename Decomposition, typename RhsType, typename GuessType>
+struct traits<SolveWithGuess<Decomposition, RhsType, GuessType> >
+  : traits<Solve<Decomposition,RhsType> >
+{};
+
+}
+
+
+template<typename Decomposition, typename RhsType, typename GuessType>
+class SolveWithGuess : public internal::generic_xpr_base<SolveWithGuess<Decomposition,RhsType,GuessType>, MatrixXpr, typename internal::traits<RhsType>::StorageKind>::type
+{
+public:
+  typedef typename internal::traits<SolveWithGuess>::Scalar Scalar;
+  typedef typename internal::traits<SolveWithGuess>::PlainObject PlainObject;
+  typedef typename internal::generic_xpr_base<SolveWithGuess<Decomposition,RhsType,GuessType>, MatrixXpr, typename internal::traits<RhsType>::StorageKind>::type Base;
+  typedef typename internal::ref_selector<SolveWithGuess>::type Nested;
+  
+  SolveWithGuess(const Decomposition &dec, const RhsType &rhs, const GuessType &guess)
+    : m_dec(dec), m_rhs(rhs), m_guess(guess)
+  {}
+  
+  EIGEN_DEVICE_FUNC Index rows() const { return m_dec.cols(); }
+  EIGEN_DEVICE_FUNC Index cols() const { return m_rhs.cols(); }
+
+  EIGEN_DEVICE_FUNC const Decomposition& dec()   const { return m_dec; }
+  EIGEN_DEVICE_FUNC const RhsType&       rhs()   const { return m_rhs; }
+  EIGEN_DEVICE_FUNC const GuessType&     guess() const { return m_guess; }
+
+protected:
+  const Decomposition &m_dec;
+  const RhsType       &m_rhs;
+  const GuessType     &m_guess;
+  
+private:
+  Scalar coeff(Index row, Index col) const;
+  Scalar coeff(Index i) const;
+};
+
+namespace internal {
+
+// Evaluator of SolveWithGuess -> eval into a temporary
+template<typename Decomposition, typename RhsType, typename GuessType>
+struct evaluator<SolveWithGuess<Decomposition,RhsType, GuessType> >
+  : public evaluator<typename SolveWithGuess<Decomposition,RhsType,GuessType>::PlainObject>
+{
+  typedef SolveWithGuess<Decomposition,RhsType,GuessType> SolveType;
+  typedef typename SolveType::PlainObject PlainObject;
+  typedef evaluator<PlainObject> Base;
+
+  evaluator(const SolveType& solve)
+    : m_result(solve.rows(), solve.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    m_result = solve.guess();
+    solve.dec()._solve_with_guess_impl(solve.rhs(), m_result);
+  }
+  
+protected:  
+  PlainObject m_result;
+};
+
+// Specialization for "dst = dec.solveWithGuess(rhs)"
+// NOTE we need to specialize it for Dense2Dense to avoid ambiguous specialization error and a Sparse2Sparse specialization must exist somewhere
+template<typename DstXprType, typename DecType, typename RhsType, typename GuessType, typename Scalar>
+struct Assignment<DstXprType, SolveWithGuess<DecType,RhsType,GuessType>, internal::assign_op<Scalar,Scalar>, Dense2Dense>
+{
+  typedef SolveWithGuess<DecType,RhsType,GuessType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    dst = src.guess();
+    src.dec()._solve_with_guess_impl(src.rhs(), dst/*, src.guess()*/);
+  }
+};
+
+} // end namepsace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SOLVEWITHGUESS_H

DELETED 3rd_party/eigen/Eigen/src/Jacobi/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/Jacobi/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/Jacobi/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/Jacobi/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Jacobi_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Jacobi_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Jacobi COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/Jacobi/Jacobi.h
==================================================================
--- 3rd_party/eigen/Eigen/src/Jacobi/Jacobi.h
+++ 3rd_party/eigen/Eigen/src/Jacobi/Jacobi.h
@@ -60,11 +60,11 @@
 
     /** Returns the adjoint transformation */
     JacobiRotation adjoint() const { using numext::conj; return JacobiRotation(conj(m_c), -m_s); }
 
     template<typename Derived>
-    bool makeJacobi(const MatrixBase<Derived>&, typename Derived::Index p, typename Derived::Index q);
+    bool makeJacobi(const MatrixBase<Derived>&, Index p, Index q);
     bool makeJacobi(const RealScalar& x, const Scalar& y, const RealScalar& z);
 
     void makeGivens(const Scalar& p, const Scalar& q, Scalar* z=0);
 
   protected:
@@ -83,19 +83,20 @@
 bool JacobiRotation<Scalar>::makeJacobi(const RealScalar& x, const Scalar& y, const RealScalar& z)
 {
   using std::sqrt;
   using std::abs;
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  if(y == Scalar(0))
+  RealScalar deno = RealScalar(2)*abs(y);
+  if(deno < (std::numeric_limits<RealScalar>::min)())
   {
     m_c = Scalar(1);
     m_s = Scalar(0);
     return false;
   }
   else
   {
-    RealScalar tau = (x-z)/(RealScalar(2)*abs(y));
+    RealScalar tau = (x-z)/deno;
     RealScalar w = sqrt(numext::abs2(tau) + RealScalar(1));
     RealScalar t;
     if(tau>RealScalar(0))
     {
       t = RealScalar(1) / (tau + w);
@@ -121,11 +122,11 @@
   *
   * \sa JacobiRotation::makeJacobi(RealScalar, Scalar, RealScalar), MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
   */
 template<typename Scalar>
 template<typename Derived>
-inline bool JacobiRotation<Scalar>::makeJacobi(const MatrixBase<Derived>& m, typename Derived::Index p, typename Derived::Index q)
+inline bool JacobiRotation<Scalar>::makeJacobi(const MatrixBase<Derived>& m, Index p, Index q)
 {
   return makeJacobi(numext::real(m.coeff(p,p)), m.coeff(p,q), numext::real(m.coeff(q,q)));
 }
 
 /** Makes \c *this as a Givens rotation \c G such that applying \f$ G^* \f$ to the left of the vector
@@ -253,19 +254,19 @@
 
 /****************************************************************************************
 *   Implementation of MatrixBase methods
 ****************************************************************************************/
 
+namespace internal {
 /** \jacobi_module
   * Applies the clock wise 2D rotation \a j to the set of 2D vectors of cordinates \a x and \a y:
   * \f$ \left ( \begin{array}{cc} x \\ y \end{array} \right )  =  J \left ( \begin{array}{cc} x \\ y \end{array} \right ) \f$
   *
   * \sa MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
   */
-namespace internal {
 template<typename VectorX, typename VectorY, typename OtherScalar>
-void apply_rotation_in_the_plane(VectorX& _x, VectorY& _y, const JacobiRotation<OtherScalar>& j);
+void apply_rotation_in_the_plane(DenseBase<VectorX>& xpr_x, DenseBase<VectorY>& xpr_y, const JacobiRotation<OtherScalar>& j);
 }
 
 /** \jacobi_module
   * Applies the rotation in the plane \a j to the rows \a p and \a q of \c *this, i.e., it computes B = J * B,
   * with \f$ B = \left ( \begin{array}{cc} \text{*this.row}(p) \\ \text{*this.row}(q) \end{array} \right ) \f$.
@@ -296,23 +297,26 @@
   internal::apply_rotation_in_the_plane(x, y, j.transpose());
 }
 
 namespace internal {
 template<typename VectorX, typename VectorY, typename OtherScalar>
-void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y, const JacobiRotation<OtherScalar>& j)
+void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(DenseBase<VectorX>& xpr_x, DenseBase<VectorY>& xpr_y, const JacobiRotation<OtherScalar>& j)
 {
-  typedef typename VectorX::Index Index;
   typedef typename VectorX::Scalar Scalar;
-  enum { PacketSize = packet_traits<Scalar>::size };
+  enum {
+    PacketSize = packet_traits<Scalar>::size,
+    OtherPacketSize = packet_traits<OtherScalar>::size
+  };
   typedef typename packet_traits<Scalar>::type Packet;
-  eigen_assert(_x.size() == _y.size());
-  Index size = _x.size();
-  Index incrx = _x.innerStride();
-  Index incry = _y.innerStride();
+  typedef typename packet_traits<OtherScalar>::type OtherPacket;
+  eigen_assert(xpr_x.size() == xpr_y.size());
+  Index size = xpr_x.size();
+  Index incrx = xpr_x.derived().innerStride();
+  Index incry = xpr_y.derived().innerStride();
 
-  Scalar* EIGEN_RESTRICT x = &_x.coeffRef(0);
-  Scalar* EIGEN_RESTRICT y = &_y.coeffRef(0);
+  Scalar* EIGEN_RESTRICT x = &xpr_x.derived().coeffRef(0);
+  Scalar* EIGEN_RESTRICT y = &xpr_y.derived().coeffRef(0);
   
   OtherScalar c = j.c();
   OtherScalar s = j.s();
   if (c==OtherScalar(1) && s==OtherScalar(0))
     return;
@@ -319,21 +323,23 @@
 
   /*** dynamic-size vectorized paths ***/
 
   if(VectorX::SizeAtCompileTime == Dynamic &&
     (VectorX::Flags & VectorY::Flags & PacketAccessBit) &&
+    (PacketSize == OtherPacketSize) &&
     ((incrx==1 && incry==1) || PacketSize == 1))
   {
     // both vectors are sequentially stored in memory => vectorization
     enum { Peeling = 2 };
 
-    Index alignedStart = internal::first_aligned(y, size);
+    Index alignedStart = internal::first_default_aligned(y, size);
     Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize;
 
-    const Packet pc = pset1<Packet>(c);
-    const Packet ps = pset1<Packet>(s);
-    conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex,false> pcj;
+    const OtherPacket pc = pset1<OtherPacket>(c);
+    const OtherPacket ps = pset1<OtherPacket>(s);
+    conj_helper<OtherPacket,Packet,NumTraits<OtherScalar>::IsComplex,false> pcj;
+    conj_helper<OtherPacket,Packet,false,false> pm;
 
     for(Index i=0; i<alignedStart; ++i)
     {
       Scalar xi = x[i];
       Scalar yi = y[i];
@@ -342,18 +348,18 @@
     }
 
     Scalar* EIGEN_RESTRICT px = x + alignedStart;
     Scalar* EIGEN_RESTRICT py = y + alignedStart;
 
-    if(internal::first_aligned(x, size)==alignedStart)
+    if(internal::first_default_aligned(x, size)==alignedStart)
     {
       for(Index i=alignedStart; i<alignedEnd; i+=PacketSize)
       {
         Packet xi = pload<Packet>(px);
         Packet yi = pload<Packet>(py);
-        pstore(px, padd(pmul(pc,xi),pcj.pmul(ps,yi)));
-        pstore(py, psub(pcj.pmul(pc,yi),pmul(ps,xi)));
+        pstore(px, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi)));
+        pstore(py, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi)));
         px += PacketSize;
         py += PacketSize;
       }
     }
     else
@@ -363,23 +369,23 @@
       {
         Packet xi   = ploadu<Packet>(px);
         Packet xi1  = ploadu<Packet>(px+PacketSize);
         Packet yi   = pload <Packet>(py);
         Packet yi1  = pload <Packet>(py+PacketSize);
-        pstoreu(px, padd(pmul(pc,xi),pcj.pmul(ps,yi)));
-        pstoreu(px+PacketSize, padd(pmul(pc,xi1),pcj.pmul(ps,yi1)));
-        pstore (py, psub(pcj.pmul(pc,yi),pmul(ps,xi)));
-        pstore (py+PacketSize, psub(pcj.pmul(pc,yi1),pmul(ps,xi1)));
+        pstoreu(px, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi)));
+        pstoreu(px+PacketSize, padd(pm.pmul(pc,xi1),pcj.pmul(ps,yi1)));
+        pstore (py, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi)));
+        pstore (py+PacketSize, psub(pcj.pmul(pc,yi1),pm.pmul(ps,xi1)));
         px += Peeling*PacketSize;
         py += Peeling*PacketSize;
       }
       if(alignedEnd!=peelingEnd)
       {
         Packet xi = ploadu<Packet>(x+peelingEnd);
         Packet yi = pload <Packet>(y+peelingEnd);
-        pstoreu(x+peelingEnd, padd(pmul(pc,xi),pcj.pmul(ps,yi)));
-        pstore (y+peelingEnd, psub(pcj.pmul(pc,yi),pmul(ps,xi)));
+        pstoreu(x+peelingEnd, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi)));
+        pstore (y+peelingEnd, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi)));
       }
     }
 
     for(Index i=alignedEnd; i<size; ++i)
     {
@@ -391,23 +397,25 @@
   }
 
   /*** fixed-size vectorized path ***/
   else if(VectorX::SizeAtCompileTime != Dynamic &&
           (VectorX::Flags & VectorY::Flags & PacketAccessBit) &&
-          (VectorX::Flags & VectorY::Flags & AlignedBit))
+          (PacketSize == OtherPacketSize) &&
+          (EIGEN_PLAIN_ENUM_MIN(evaluator<VectorX>::Alignment, evaluator<VectorY>::Alignment)>0)) // FIXME should be compared to the required alignment
   {
-    const Packet pc = pset1<Packet>(c);
-    const Packet ps = pset1<Packet>(s);
-    conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex,false> pcj;
+    const OtherPacket pc = pset1<OtherPacket>(c);
+    const OtherPacket ps = pset1<OtherPacket>(s);
+    conj_helper<OtherPacket,Packet,NumTraits<OtherPacket>::IsComplex,false> pcj;
+    conj_helper<OtherPacket,Packet,false,false> pm;
     Scalar* EIGEN_RESTRICT px = x;
     Scalar* EIGEN_RESTRICT py = y;
     for(Index i=0; i<size; i+=PacketSize)
     {
       Packet xi = pload<Packet>(px);
       Packet yi = pload<Packet>(py);
-      pstore(px, padd(pmul(pc,xi),pcj.pmul(ps,yi)));
-      pstore(py, psub(pcj.pmul(pc,yi),pmul(ps,xi)));
+      pstore(px, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi)));
+      pstore(py, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi)));
       px += PacketSize;
       py += PacketSize;
     }
   }
 

DELETED 3rd_party/eigen/Eigen/src/LU/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/LU/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/LU/CMakeLists.txt
@@ -1,8 +0,0 @@
-FILE(GLOB Eigen_LU_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_LU_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/LU COMPONENT Devel
-  )
-
-ADD_SUBDIRECTORY(arch)

Index: 3rd_party/eigen/Eigen/src/LU/Determinant.h
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/Determinant.h
+++ 3rd_party/eigen/Eigen/src/LU/Determinant.h
@@ -90,12 +90,12 @@
   */
 template<typename Derived>
 inline typename internal::traits<Derived>::Scalar MatrixBase<Derived>::determinant() const
 {
   eigen_assert(rows() == cols());
-  typedef typename internal::nested<Derived,Base::RowsAtCompileTime>::type Nested;
+  typedef typename internal::nested_eval<Derived,Base::RowsAtCompileTime>::type Nested;
   return internal::determinant_impl<typename internal::remove_all<Nested>::type>::run(derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_DETERMINANT_H

Index: 3rd_party/eigen/Eigen/src/LU/FullPivLU.h
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/FullPivLU.h
+++ 3rd_party/eigen/Eigen/src/LU/FullPivLU.h
@@ -8,19 +8,30 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_LU_H
 #define EIGEN_LU_H
 
-namespace Eigen { 
+namespace Eigen {
+
+namespace internal {
+template<typename _MatrixType> struct traits<FullPivLU<_MatrixType> >
+ : traits<_MatrixType>
+{
+  typedef MatrixXpr XprKind;
+  typedef SolverStorage StorageKind;
+  enum { Flags = 0 };
+};
+
+} // end namespace internal
 
 /** \ingroup LU_Module
   *
   * \class FullPivLU
   *
   * \brief LU decomposition of a matrix with complete pivoting, and related features
   *
-  * \param MatrixType the type of the matrix of which we are computing the LU decomposition
+  * \tparam _MatrixType the type of the matrix of which we are computing the LU decomposition
   *
   * This class represents a LU decomposition of any matrix, with complete pivoting: the matrix A is
   * decomposed as \f$ A = P^{-1} L U Q^{-1} \f$ where L is unit-lower-triangular, U is
   * upper-triangular, and P and Q are permutation matrices. This is a rank-revealing LU
   * decomposition. The eigenvalues (diagonal coefficients) of U are sorted in such a way that any
@@ -39,31 +50,32 @@
   *
   * As an exemple, here is how the original matrix can be retrieved:
   * \include class_FullPivLU.cpp
   * Output: \verbinclude class_FullPivLU.out
   *
+  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
+  * 
   * \sa MatrixBase::fullPivLu(), MatrixBase::determinant(), MatrixBase::inverse()
   */
 template<typename _MatrixType> class FullPivLU
+  : public SolverBase<FullPivLU<_MatrixType> >
 {
   public:
     typedef _MatrixType MatrixType;
+    typedef SolverBase<FullPivLU> Base;
+
+    EIGEN_GENERIC_PUBLIC_INTERFACE(FullPivLU)
+    // FIXME StorageIndex defined in EIGEN_GENERIC_PUBLIC_INTERFACE should be int
     enum {
-      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      Options = MatrixType::Options,
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename internal::traits<MatrixType>::StorageKind StorageKind;
-    typedef typename MatrixType::Index Index;
-    typedef typename internal::plain_row_type<MatrixType, Index>::type IntRowVectorType;
-    typedef typename internal::plain_col_type<MatrixType, Index>::type IntColVectorType;
+    typedef typename internal::plain_row_type<MatrixType, StorageIndex>::type IntRowVectorType;
+    typedef typename internal::plain_col_type<MatrixType, StorageIndex>::type IntColVectorType;
     typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime> PermutationQType;
     typedef PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> PermutationPType;
+    typedef typename MatrixType::PlainObject PlainObject;
 
     /**
       * \brief Default Constructor.
       *
       * The default constructor is useful in cases in which the user intends to
@@ -82,20 +94,35 @@
     /** Constructor.
       *
       * \param matrix the matrix of which to compute the LU decomposition.
       *               It is required to be nonzero.
       */
-    FullPivLU(const MatrixType& matrix);
+    template<typename InputType>
+    explicit FullPivLU(const EigenBase<InputType>& matrix);
+
+    /** \brief Constructs a LU factorization from a given matrix
+      *
+      * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when \c MatrixType is a Eigen::Ref.
+      *
+      * \sa FullPivLU(const EigenBase&)
+      */
+    template<typename InputType>
+    explicit FullPivLU(EigenBase<InputType>& matrix);
 
     /** Computes the LU decomposition of the given matrix.
       *
       * \param matrix the matrix of which to compute the LU decomposition.
       *               It is required to be nonzero.
       *
       * \returns a reference to *this
       */
-    FullPivLU& compute(const MatrixType& matrix);
+    template<typename InputType>
+    FullPivLU& compute(const EigenBase<InputType>& matrix) {
+      m_lu = matrix.derived();
+      computeInPlace();
+      return *this;
+    }
 
     /** \returns the LU decomposition matrix: the upper-triangular part is U, the
       * unit-lower-triangular part is L (at least for square matrices; in the non-square
       * case, special care is needed, see the documentation of class FullPivLU).
       *
@@ -127,11 +154,11 @@
 
     /** \returns the permutation matrix P
       *
       * \sa permutationQ()
       */
-    inline const PermutationPType& permutationP() const
+    EIGEN_DEVICE_FUNC inline const PermutationPType& permutationP() const
     {
       eigen_assert(m_isInitialized && "LU is not initialized.");
       return m_p;
     }
 
@@ -164,11 +191,11 @@
       eigen_assert(m_isInitialized && "LU is not initialized.");
       return internal::kernel_retval<FullPivLU>(*this);
     }
 
     /** \returns the image of the matrix, also called its column-space. The columns of the returned matrix
-      * will form a basis of the kernel.
+      * will form a basis of the image (column-space).
       *
       * \param originalMatrix the original matrix, of which *this is the LU decomposition.
       *                       The reason why it is needed to pass it here, is that this allows
       *                       a large optimization, as otherwise this method would need to reconstruct it
       *                       from the LU decomposition.
@@ -208,16 +235,26 @@
       * Example: \include FullPivLU_solve.cpp
       * Output: \verbinclude FullPivLU_solve.out
       *
       * \sa TriangularView::solve(), kernel(), inverse()
       */
+    // FIXME this is a copy-paste of the base-class member to add the isInitialized assertion.
     template<typename Rhs>
-    inline const internal::solve_retval<FullPivLU, Rhs>
+    inline const Solve<FullPivLU, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
       eigen_assert(m_isInitialized && "LU is not initialized.");
-      return internal::solve_retval<FullPivLU, Rhs>(*this, b.derived());
+      return Solve<FullPivLU, Rhs>(*this, b.derived());
+    }
+
+    /** \returns an estimate of the reciprocal condition number of the matrix of which \c *this is
+        the LU decomposition.
+      */
+    inline RealScalar rcond() const
+    {
+      eigen_assert(m_isInitialized && "PartialPivLU is not initialized.");
+      return internal::rcond_estimate_helper(m_l1_norm, *this);
     }
 
     /** \returns the determinant of the matrix of which
       * *this is the LU decomposition. It has only linear complexity
       * (that is, O(n) where n is the dimension of the square matrix)
@@ -358,31 +395,50 @@
       * \note If this matrix is not invertible, the returned matrix has undefined coefficients.
       *       Use isInvertible() to first determine whether this matrix is invertible.
       *
       * \sa MatrixBase::inverse()
       */
-    inline const internal::solve_retval<FullPivLU,typename MatrixType::IdentityReturnType> inverse() const
+    inline const Inverse<FullPivLU> inverse() const
     {
       eigen_assert(m_isInitialized && "LU is not initialized.");
       eigen_assert(m_lu.rows() == m_lu.cols() && "You can't take the inverse of a non-square matrix!");
-      return internal::solve_retval<FullPivLU,typename MatrixType::IdentityReturnType>
-               (*this, MatrixType::Identity(m_lu.rows(), m_lu.cols()));
+      return Inverse<FullPivLU>(*this);
     }
 
     MatrixType reconstructedMatrix() const;
 
-    inline Index rows() const { return m_lu.rows(); }
-    inline Index cols() const { return m_lu.cols(); }
+    EIGEN_DEVICE_FUNC inline Index rows() const { return m_lu.rows(); }
+    EIGEN_DEVICE_FUNC inline Index cols() const { return m_lu.cols(); }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl(const RhsType &rhs, DstType &dst) const;
+
+    template<bool Conjugate, typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl_transposed(const RhsType &rhs, DstType &dst) const;
+    #endif
 
   protected:
+
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+
+    void computeInPlace();
+
     MatrixType m_lu;
     PermutationPType m_p;
     PermutationQType m_q;
     IntColVectorType m_rowsTranspositions;
     IntRowVectorType m_colsTranspositions;
-    Index m_det_pq, m_nonzero_pivots;
+    Index m_nonzero_pivots;
+    RealScalar m_l1_norm;
     RealScalar m_maxpivot, m_prescribedThreshold;
+    signed char m_det_pq;
     bool m_isInitialized, m_usePrescribedThreshold;
 };
 
 template<typename MatrixType>
 FullPivLU<MatrixType>::FullPivLU()
@@ -401,39 +457,55 @@
     m_usePrescribedThreshold(false)
 {
 }
 
 template<typename MatrixType>
-FullPivLU<MatrixType>::FullPivLU(const MatrixType& matrix)
+template<typename InputType>
+FullPivLU<MatrixType>::FullPivLU(const EigenBase<InputType>& matrix)
   : m_lu(matrix.rows(), matrix.cols()),
     m_p(matrix.rows()),
     m_q(matrix.cols()),
     m_rowsTranspositions(matrix.rows()),
     m_colsTranspositions(matrix.cols()),
     m_isInitialized(false),
     m_usePrescribedThreshold(false)
 {
-  compute(matrix);
+  compute(matrix.derived());
+}
+
+template<typename MatrixType>
+template<typename InputType>
+FullPivLU<MatrixType>::FullPivLU(EigenBase<InputType>& matrix)
+  : m_lu(matrix.derived()),
+    m_p(matrix.rows()),
+    m_q(matrix.cols()),
+    m_rowsTranspositions(matrix.rows()),
+    m_colsTranspositions(matrix.cols()),
+    m_isInitialized(false),
+    m_usePrescribedThreshold(false)
+{
+  computeInPlace();
 }
 
 template<typename MatrixType>
-FullPivLU<MatrixType>& FullPivLU<MatrixType>::compute(const MatrixType& matrix)
+void FullPivLU<MatrixType>::computeInPlace()
 {
+  check_template_parameters();
+
   // the permutations are stored as int indices, so just to be sure:
-  eigen_assert(matrix.rows()<=NumTraits<int>::highest() && matrix.cols()<=NumTraits<int>::highest());
-  
-  m_isInitialized = true;
-  m_lu = matrix;
-
-  const Index size = matrix.diagonalSize();
-  const Index rows = matrix.rows();
-  const Index cols = matrix.cols();
+  eigen_assert(m_lu.rows()<=NumTraits<int>::highest() && m_lu.cols()<=NumTraits<int>::highest());
+
+  m_l1_norm = m_lu.cwiseAbs().colwise().sum().maxCoeff();
+
+  const Index size = m_lu.diagonalSize();
+  const Index rows = m_lu.rows();
+  const Index cols = m_lu.cols();
 
   // will store the transpositions, before we accumulate them at the end.
   // can't accumulate on-the-fly because that will be done in reverse order for the rows.
-  m_rowsTranspositions.resize(matrix.rows());
-  m_colsTranspositions.resize(matrix.cols());
+  m_rowsTranspositions.resize(m_lu.rows());
+  m_colsTranspositions.resize(m_lu.cols());
   Index number_of_transpositions = 0; // number of NONTRIVIAL transpositions, i.e. m_rowsTranspositions[i]!=i
 
   m_nonzero_pivots = size; // the generic case is that in which all pivots are nonzero (invertible case)
   m_maxpivot = RealScalar(0);
 
@@ -441,18 +513,20 @@
   {
     // First, we need to find the pivot.
 
     // biggest coefficient in the remaining bottom-right corner (starting at row k, col k)
     Index row_of_biggest_in_corner, col_of_biggest_in_corner;
-    RealScalar biggest_in_corner;
+    typedef internal::scalar_score_coeff_op<Scalar> Scoring;
+    typedef typename Scoring::result_type Score;
+    Score biggest_in_corner;
     biggest_in_corner = m_lu.bottomRightCorner(rows-k, cols-k)
-                        .cwiseAbs()
+                        .unaryExpr(Scoring())
                         .maxCoeff(&row_of_biggest_in_corner, &col_of_biggest_in_corner);
     row_of_biggest_in_corner += k; // correct the values! since they were computed in the corner,
     col_of_biggest_in_corner += k; // need to add k to them.
 
-    if(biggest_in_corner==RealScalar(0))
+    if(biggest_in_corner==Score(0))
     {
       // before exiting, make sure to initialize the still uninitialized transpositions
       // in a sane state without destroying what we already have.
       m_nonzero_pivots = k;
       for(Index i = k; i < size; ++i)
@@ -461,11 +535,12 @@
         m_colsTranspositions.coeffRef(i) = i;
       }
       break;
     }
 
-    if(biggest_in_corner > m_maxpivot) m_maxpivot = biggest_in_corner;
+    RealScalar abs_pivot = internal::abs_knowing_score<Scalar>()(m_lu(row_of_biggest_in_corner, col_of_biggest_in_corner), biggest_in_corner);
+    if(abs_pivot > m_maxpivot) m_maxpivot = abs_pivot;
 
     // Now that we've found the pivot, we need to apply the row/col swaps to
     // bring it to the location (k,k).
 
     m_rowsTranspositions.coeffRef(k) = row_of_biggest_in_corner;
@@ -498,11 +573,12 @@
   m_q.setIdentity(cols);
   for(Index k = 0; k < size; ++k)
     m_q.applyTranspositionOnTheRight(k, m_colsTranspositions.coeff(k));
 
   m_det_pq = (number_of_transpositions%2) ? -1 : 1;
-  return *this;
+
+  m_isInitialized = true;
 }
 
 template<typename MatrixType>
 typename internal::traits<MatrixType>::Scalar FullPivLU<MatrixType>::determinant() const
 {
@@ -661,68 +737,140 @@
   }
 };
 
 /***** Implementation of solve() *****************************************************/
 
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<FullPivLU<_MatrixType>, Rhs>
-  : solve_retval_base<FullPivLU<_MatrixType>, Rhs>
-{
-  EIGEN_MAKE_SOLVE_HELPERS(FullPivLU<_MatrixType>,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    /* The decomposition PAQ = LU can be rewritten as A = P^{-1} L U Q^{-1}.
-     * So we proceed as follows:
-     * Step 1: compute c = P * rhs.
-     * Step 2: replace c by the solution x to Lx = c. Exists because L is invertible.
-     * Step 3: replace c by the solution x to Ux = c. May or may not exist.
-     * Step 4: result = Q * c;
-     */
-
-    const Index rows = dec().rows(), cols = dec().cols(),
-              nonzero_pivots = dec().nonzeroPivots();
-    eigen_assert(rhs().rows() == rows);
-    const Index smalldim = (std::min)(rows, cols);
-
-    if(nonzero_pivots == 0)
-    {
-      dst.setZero();
-      return;
-    }
-
-    typename Rhs::PlainObject c(rhs().rows(), rhs().cols());
-
-    // Step 1
-    c = dec().permutationP() * rhs();
-
+} // end namespace internal
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename _MatrixType>
+template<typename RhsType, typename DstType>
+void FullPivLU<_MatrixType>::_solve_impl(const RhsType &rhs, DstType &dst) const
+{
+  /* The decomposition PAQ = LU can be rewritten as A = P^{-1} L U Q^{-1}.
+  * So we proceed as follows:
+  * Step 1: compute c = P * rhs.
+  * Step 2: replace c by the solution x to Lx = c. Exists because L is invertible.
+  * Step 3: replace c by the solution x to Ux = c. May or may not exist.
+  * Step 4: result = Q * c;
+  */
+
+  const Index rows = this->rows(),
+              cols = this->cols(),
+              nonzero_pivots = this->rank();
+  eigen_assert(rhs.rows() == rows);
+  const Index smalldim = (std::min)(rows, cols);
+
+  if(nonzero_pivots == 0)
+  {
+    dst.setZero();
+    return;
+  }
+
+  typename RhsType::PlainObject c(rhs.rows(), rhs.cols());
+
+  // Step 1
+  c = permutationP() * rhs;
+
+  // Step 2
+  m_lu.topLeftCorner(smalldim,smalldim)
+      .template triangularView<UnitLower>()
+      .solveInPlace(c.topRows(smalldim));
+  if(rows>cols)
+    c.bottomRows(rows-cols) -= m_lu.bottomRows(rows-cols) * c.topRows(cols);
+
+  // Step 3
+  m_lu.topLeftCorner(nonzero_pivots, nonzero_pivots)
+      .template triangularView<Upper>()
+      .solveInPlace(c.topRows(nonzero_pivots));
+
+  // Step 4
+  for(Index i = 0; i < nonzero_pivots; ++i)
+    dst.row(permutationQ().indices().coeff(i)) = c.row(i);
+  for(Index i = nonzero_pivots; i < m_lu.cols(); ++i)
+    dst.row(permutationQ().indices().coeff(i)).setZero();
+}
+
+template<typename _MatrixType>
+template<bool Conjugate, typename RhsType, typename DstType>
+void FullPivLU<_MatrixType>::_solve_impl_transposed(const RhsType &rhs, DstType &dst) const
+{
+  /* The decomposition PAQ = LU can be rewritten as A = P^{-1} L U Q^{-1},
+   * and since permutations are real and unitary, we can write this
+   * as   A^T = Q U^T L^T P,
+   * So we proceed as follows:
+   * Step 1: compute c = Q^T rhs.
+   * Step 2: replace c by the solution x to U^T x = c. May or may not exist.
+   * Step 3: replace c by the solution x to L^T x = c.
+   * Step 4: result = P^T c.
+   * If Conjugate is true, replace "^T" by "^*" above.
+   */
+
+  const Index rows = this->rows(), cols = this->cols(),
+    nonzero_pivots = this->rank();
+   eigen_assert(rhs.rows() == cols);
+  const Index smalldim = (std::min)(rows, cols);
+
+  if(nonzero_pivots == 0)
+  {
+    dst.setZero();
+    return;
+  }
+
+  typename RhsType::PlainObject c(rhs.rows(), rhs.cols());
+
+  // Step 1
+  c = permutationQ().inverse() * rhs;
+
+  if (Conjugate) {
+    // Step 2
+    m_lu.topLeftCorner(nonzero_pivots, nonzero_pivots)
+        .template triangularView<Upper>()
+        .adjoint()
+        .solveInPlace(c.topRows(nonzero_pivots));
+    // Step 3
+    m_lu.topLeftCorner(smalldim, smalldim)
+        .template triangularView<UnitLower>()
+        .adjoint()
+        .solveInPlace(c.topRows(smalldim));
+  } else {
     // Step 2
-    dec().matrixLU()
-        .topLeftCorner(smalldim,smalldim)
-        .template triangularView<UnitLower>()
-        .solveInPlace(c.topRows(smalldim));
-    if(rows>cols)
-    {
-      c.bottomRows(rows-cols)
-        -= dec().matrixLU().bottomRows(rows-cols)
-         * c.topRows(cols);
-    }
-
+    m_lu.topLeftCorner(nonzero_pivots, nonzero_pivots)
+        .template triangularView<Upper>()
+        .transpose()
+        .solveInPlace(c.topRows(nonzero_pivots));
     // Step 3
-    dec().matrixLU()
-        .topLeftCorner(nonzero_pivots, nonzero_pivots)
-        .template triangularView<Upper>()
-        .solveInPlace(c.topRows(nonzero_pivots));
-
-    // Step 4
-    for(Index i = 0; i < nonzero_pivots; ++i)
-      dst.row(dec().permutationQ().indices().coeff(i)) = c.row(i);
-    for(Index i = nonzero_pivots; i < dec().matrixLU().cols(); ++i)
-      dst.row(dec().permutationQ().indices().coeff(i)).setZero();
+    m_lu.topLeftCorner(smalldim, smalldim)
+        .template triangularView<UnitLower>()
+        .transpose()
+        .solveInPlace(c.topRows(smalldim));
+  }
+
+  // Step 4
+  PermutationPType invp = permutationP().inverse().eval();
+  for(Index i = 0; i < smalldim; ++i)
+    dst.row(invp.indices().coeff(i)) = c.row(i);
+  for(Index i = smalldim; i < rows; ++i)
+    dst.row(invp.indices().coeff(i)).setZero();
+}
+
+#endif
+
+namespace internal {
+
+
+/***** Implementation of inverse() *****************************************************/
+template<typename DstXprType, typename MatrixType>
+struct Assignment<DstXprType, Inverse<FullPivLU<MatrixType> >, internal::assign_op<typename DstXprType::Scalar,typename FullPivLU<MatrixType>::Scalar>, Dense2Dense>
+{
+  typedef FullPivLU<MatrixType> LuType;
+  typedef Inverse<LuType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename MatrixType::Scalar> &)
+  {
+    dst = src.nestedExpression().solve(MatrixType::Identity(src.rows(), src.cols()));
   }
 };
-
 } // end namespace internal
 
 /******* MatrixBase methods *****************************************************************/
 
 /** \lu_module

DELETED 3rd_party/eigen/Eigen/src/LU/Inverse.h
Index: 3rd_party/eigen/Eigen/src/LU/Inverse.h
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/Inverse.h
+++ 3rd_party/eigen/Eigen/src/LU/Inverse.h
@@ -1,400 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_INVERSE_H
-#define EIGEN_INVERSE_H
-
-namespace Eigen { 
-
-namespace internal {
-
-/**********************************
-*** General case implementation ***
-**********************************/
-
-template<typename MatrixType, typename ResultType, int Size = MatrixType::RowsAtCompileTime>
-struct compute_inverse
-{
-  static inline void run(const MatrixType& matrix, ResultType& result)
-  {
-    result = matrix.partialPivLu().inverse();
-  }
-};
-
-template<typename MatrixType, typename ResultType, int Size = MatrixType::RowsAtCompileTime>
-struct compute_inverse_and_det_with_check { /* nothing! general case not supported. */ };
-
-/****************************
-*** Size 1 implementation ***
-****************************/
-
-template<typename MatrixType, typename ResultType>
-struct compute_inverse<MatrixType, ResultType, 1>
-{
-  static inline void run(const MatrixType& matrix, ResultType& result)
-  {
-    typedef typename MatrixType::Scalar Scalar;
-    result.coeffRef(0,0) = Scalar(1) / matrix.coeff(0,0);
-  }
-};
-
-template<typename MatrixType, typename ResultType>
-struct compute_inverse_and_det_with_check<MatrixType, ResultType, 1>
-{
-  static inline void run(
-    const MatrixType& matrix,
-    const typename MatrixType::RealScalar& absDeterminantThreshold,
-    ResultType& result,
-    typename ResultType::Scalar& determinant,
-    bool& invertible
-  )
-  {
-    using std::abs;
-    determinant = matrix.coeff(0,0);
-    invertible = abs(determinant) > absDeterminantThreshold;
-    if(invertible) result.coeffRef(0,0) = typename ResultType::Scalar(1) / determinant;
-  }
-};
-
-/****************************
-*** Size 2 implementation ***
-****************************/
-
-template<typename MatrixType, typename ResultType>
-inline void compute_inverse_size2_helper(
-    const MatrixType& matrix, const typename ResultType::Scalar& invdet,
-    ResultType& result)
-{
-  result.coeffRef(0,0) = matrix.coeff(1,1) * invdet;
-  result.coeffRef(1,0) = -matrix.coeff(1,0) * invdet;
-  result.coeffRef(0,1) = -matrix.coeff(0,1) * invdet;
-  result.coeffRef(1,1) = matrix.coeff(0,0) * invdet;
-}
-
-template<typename MatrixType, typename ResultType>
-struct compute_inverse<MatrixType, ResultType, 2>
-{
-  static inline void run(const MatrixType& matrix, ResultType& result)
-  {
-    typedef typename ResultType::Scalar Scalar;
-    const Scalar invdet = typename MatrixType::Scalar(1) / matrix.determinant();
-    compute_inverse_size2_helper(matrix, invdet, result);
-  }
-};
-
-template<typename MatrixType, typename ResultType>
-struct compute_inverse_and_det_with_check<MatrixType, ResultType, 2>
-{
-  static inline void run(
-    const MatrixType& matrix,
-    const typename MatrixType::RealScalar& absDeterminantThreshold,
-    ResultType& inverse,
-    typename ResultType::Scalar& determinant,
-    bool& invertible
-  )
-  {
-    using std::abs;
-    typedef typename ResultType::Scalar Scalar;
-    determinant = matrix.determinant();
-    invertible = abs(determinant) > absDeterminantThreshold;
-    if(!invertible) return;
-    const Scalar invdet = Scalar(1) / determinant;
-    compute_inverse_size2_helper(matrix, invdet, inverse);
-  }
-};
-
-/****************************
-*** Size 3 implementation ***
-****************************/
-
-template<typename MatrixType, int i, int j>
-inline typename MatrixType::Scalar cofactor_3x3(const MatrixType& m)
-{
-  enum {
-    i1 = (i+1) % 3,
-    i2 = (i+2) % 3,
-    j1 = (j+1) % 3,
-    j2 = (j+2) % 3
-  };
-  return m.coeff(i1, j1) * m.coeff(i2, j2)
-       - m.coeff(i1, j2) * m.coeff(i2, j1);
-}
-
-template<typename MatrixType, typename ResultType>
-inline void compute_inverse_size3_helper(
-    const MatrixType& matrix,
-    const typename ResultType::Scalar& invdet,
-    const Matrix<typename ResultType::Scalar,3,1>& cofactors_col0,
-    ResultType& result)
-{
-  result.row(0) = cofactors_col0 * invdet;
-  result.coeffRef(1,0) =  cofactor_3x3<MatrixType,0,1>(matrix) * invdet;
-  result.coeffRef(1,1) =  cofactor_3x3<MatrixType,1,1>(matrix) * invdet;
-  result.coeffRef(1,2) =  cofactor_3x3<MatrixType,2,1>(matrix) * invdet;
-  result.coeffRef(2,0) =  cofactor_3x3<MatrixType,0,2>(matrix) * invdet;
-  result.coeffRef(2,1) =  cofactor_3x3<MatrixType,1,2>(matrix) * invdet;
-  result.coeffRef(2,2) =  cofactor_3x3<MatrixType,2,2>(matrix) * invdet;
-}
-
-template<typename MatrixType, typename ResultType>
-struct compute_inverse<MatrixType, ResultType, 3>
-{
-  static inline void run(const MatrixType& matrix, ResultType& result)
-  {
-    typedef typename ResultType::Scalar Scalar;
-    Matrix<typename MatrixType::Scalar,3,1> cofactors_col0;
-    cofactors_col0.coeffRef(0) =  cofactor_3x3<MatrixType,0,0>(matrix);
-    cofactors_col0.coeffRef(1) =  cofactor_3x3<MatrixType,1,0>(matrix);
-    cofactors_col0.coeffRef(2) =  cofactor_3x3<MatrixType,2,0>(matrix);
-    const Scalar det = (cofactors_col0.cwiseProduct(matrix.col(0))).sum();
-    const Scalar invdet = Scalar(1) / det;
-    compute_inverse_size3_helper(matrix, invdet, cofactors_col0, result);
-  }
-};
-
-template<typename MatrixType, typename ResultType>
-struct compute_inverse_and_det_with_check<MatrixType, ResultType, 3>
-{
-  static inline void run(
-    const MatrixType& matrix,
-    const typename MatrixType::RealScalar& absDeterminantThreshold,
-    ResultType& inverse,
-    typename ResultType::Scalar& determinant,
-    bool& invertible
-  )
-  {
-    using std::abs;
-    typedef typename ResultType::Scalar Scalar;
-    Matrix<Scalar,3,1> cofactors_col0;
-    cofactors_col0.coeffRef(0) =  cofactor_3x3<MatrixType,0,0>(matrix);
-    cofactors_col0.coeffRef(1) =  cofactor_3x3<MatrixType,1,0>(matrix);
-    cofactors_col0.coeffRef(2) =  cofactor_3x3<MatrixType,2,0>(matrix);
-    determinant = (cofactors_col0.cwiseProduct(matrix.col(0))).sum();
-    invertible = abs(determinant) > absDeterminantThreshold;
-    if(!invertible) return;
-    const Scalar invdet = Scalar(1) / determinant;
-    compute_inverse_size3_helper(matrix, invdet, cofactors_col0, inverse);
-  }
-};
-
-/****************************
-*** Size 4 implementation ***
-****************************/
-
-template<typename Derived>
-inline const typename Derived::Scalar general_det3_helper
-(const MatrixBase<Derived>& matrix, int i1, int i2, int i3, int j1, int j2, int j3)
-{
-  return matrix.coeff(i1,j1)
-         * (matrix.coeff(i2,j2) * matrix.coeff(i3,j3) - matrix.coeff(i2,j3) * matrix.coeff(i3,j2));
-}
-
-template<typename MatrixType, int i, int j>
-inline typename MatrixType::Scalar cofactor_4x4(const MatrixType& matrix)
-{
-  enum {
-    i1 = (i+1) % 4,
-    i2 = (i+2) % 4,
-    i3 = (i+3) % 4,
-    j1 = (j+1) % 4,
-    j2 = (j+2) % 4,
-    j3 = (j+3) % 4
-  };
-  return general_det3_helper(matrix, i1, i2, i3, j1, j2, j3)
-       + general_det3_helper(matrix, i2, i3, i1, j1, j2, j3)
-       + general_det3_helper(matrix, i3, i1, i2, j1, j2, j3);
-}
-
-template<int Arch, typename Scalar, typename MatrixType, typename ResultType>
-struct compute_inverse_size4
-{
-  static void run(const MatrixType& matrix, ResultType& result)
-  {
-    result.coeffRef(0,0) =  cofactor_4x4<MatrixType,0,0>(matrix);
-    result.coeffRef(1,0) = -cofactor_4x4<MatrixType,0,1>(matrix);
-    result.coeffRef(2,0) =  cofactor_4x4<MatrixType,0,2>(matrix);
-    result.coeffRef(3,0) = -cofactor_4x4<MatrixType,0,3>(matrix);
-    result.coeffRef(0,2) =  cofactor_4x4<MatrixType,2,0>(matrix);
-    result.coeffRef(1,2) = -cofactor_4x4<MatrixType,2,1>(matrix);
-    result.coeffRef(2,2) =  cofactor_4x4<MatrixType,2,2>(matrix);
-    result.coeffRef(3,2) = -cofactor_4x4<MatrixType,2,3>(matrix);
-    result.coeffRef(0,1) = -cofactor_4x4<MatrixType,1,0>(matrix);
-    result.coeffRef(1,1) =  cofactor_4x4<MatrixType,1,1>(matrix);
-    result.coeffRef(2,1) = -cofactor_4x4<MatrixType,1,2>(matrix);
-    result.coeffRef(3,1) =  cofactor_4x4<MatrixType,1,3>(matrix);
-    result.coeffRef(0,3) = -cofactor_4x4<MatrixType,3,0>(matrix);
-    result.coeffRef(1,3) =  cofactor_4x4<MatrixType,3,1>(matrix);
-    result.coeffRef(2,3) = -cofactor_4x4<MatrixType,3,2>(matrix);
-    result.coeffRef(3,3) =  cofactor_4x4<MatrixType,3,3>(matrix);
-    result /= (matrix.col(0).cwiseProduct(result.row(0).transpose())).sum();
-  }
-};
-
-template<typename MatrixType, typename ResultType>
-struct compute_inverse<MatrixType, ResultType, 4>
- : compute_inverse_size4<Architecture::Target, typename MatrixType::Scalar,
-                            MatrixType, ResultType>
-{
-};
-
-template<typename MatrixType, typename ResultType>
-struct compute_inverse_and_det_with_check<MatrixType, ResultType, 4>
-{
-  static inline void run(
-    const MatrixType& matrix,
-    const typename MatrixType::RealScalar& absDeterminantThreshold,
-    ResultType& inverse,
-    typename ResultType::Scalar& determinant,
-    bool& invertible
-  )
-  {
-    using std::abs;
-    determinant = matrix.determinant();
-    invertible = abs(determinant) > absDeterminantThreshold;
-    if(invertible) compute_inverse<MatrixType, ResultType>::run(matrix, inverse);
-  }
-};
-
-/*************************
-*** MatrixBase methods ***
-*************************/
-
-template<typename MatrixType>
-struct traits<inverse_impl<MatrixType> >
-{
-  typedef typename MatrixType::PlainObject ReturnType;
-};
-
-template<typename MatrixType>
-struct inverse_impl : public ReturnByValue<inverse_impl<MatrixType> >
-{
-  typedef typename MatrixType::Index Index;
-  typedef typename internal::eval<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
-  MatrixTypeNested m_matrix;
-
-  inverse_impl(const MatrixType& matrix)
-    : m_matrix(matrix)
-  {}
-
-  inline Index rows() const { return m_matrix.rows(); }
-  inline Index cols() const { return m_matrix.cols(); }
-
-  template<typename Dest> inline void evalTo(Dest& dst) const
-  {
-    const int Size = EIGEN_PLAIN_ENUM_MIN(MatrixType::ColsAtCompileTime,Dest::ColsAtCompileTime);
-    EIGEN_ONLY_USED_FOR_DEBUG(Size);
-    eigen_assert(( (Size<=1) || (Size>4) || (extract_data(m_matrix)!=extract_data(dst)))
-              && "Aliasing problem detected in inverse(), you need to do inverse().eval() here.");
-
-    compute_inverse<MatrixTypeNestedCleaned, Dest>::run(m_matrix, dst);
-  }
-};
-
-} // end namespace internal
-
-/** \lu_module
-  *
-  * \returns the matrix inverse of this matrix.
-  *
-  * For small fixed sizes up to 4x4, this method uses cofactors.
-  * In the general case, this method uses class PartialPivLU.
-  *
-  * \note This matrix must be invertible, otherwise the result is undefined. If you need an
-  * invertibility check, do the following:
-  * \li for fixed sizes up to 4x4, use computeInverseAndDetWithCheck().
-  * \li for the general case, use class FullPivLU.
-  *
-  * Example: \include MatrixBase_inverse.cpp
-  * Output: \verbinclude MatrixBase_inverse.out
-  *
-  * \sa computeInverseAndDetWithCheck()
-  */
-template<typename Derived>
-inline const internal::inverse_impl<Derived> MatrixBase<Derived>::inverse() const
-{
-  EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsInteger,THIS_FUNCTION_IS_NOT_FOR_INTEGER_NUMERIC_TYPES)
-  eigen_assert(rows() == cols());
-  return internal::inverse_impl<Derived>(derived());
-}
-
-/** \lu_module
-  *
-  * Computation of matrix inverse and determinant, with invertibility check.
-  *
-  * This is only for fixed-size square matrices of size up to 4x4.
-  *
-  * \param inverse Reference to the matrix in which to store the inverse.
-  * \param determinant Reference to the variable in which to store the determinant.
-  * \param invertible Reference to the bool variable in which to store whether the matrix is invertible.
-  * \param absDeterminantThreshold Optional parameter controlling the invertibility check.
-  *                                The matrix will be declared invertible if the absolute value of its
-  *                                determinant is greater than this threshold.
-  *
-  * Example: \include MatrixBase_computeInverseAndDetWithCheck.cpp
-  * Output: \verbinclude MatrixBase_computeInverseAndDetWithCheck.out
-  *
-  * \sa inverse(), computeInverseWithCheck()
-  */
-template<typename Derived>
-template<typename ResultType>
-inline void MatrixBase<Derived>::computeInverseAndDetWithCheck(
-    ResultType& inverse,
-    typename ResultType::Scalar& determinant,
-    bool& invertible,
-    const RealScalar& absDeterminantThreshold
-  ) const
-{
-  // i'd love to put some static assertions there, but SFINAE means that they have no effect...
-  eigen_assert(rows() == cols());
-  // for 2x2, it's worth giving a chance to avoid evaluating.
-  // for larger sizes, evaluating has negligible cost and limits code size.
-  typedef typename internal::conditional<
-    RowsAtCompileTime == 2,
-    typename internal::remove_all<typename internal::nested<Derived, 2>::type>::type,
-    PlainObject
-  >::type MatrixType;
-  internal::compute_inverse_and_det_with_check<MatrixType, ResultType>::run
-    (derived(), absDeterminantThreshold, inverse, determinant, invertible);
-}
-
-/** \lu_module
-  *
-  * Computation of matrix inverse, with invertibility check.
-  *
-  * This is only for fixed-size square matrices of size up to 4x4.
-  *
-  * \param inverse Reference to the matrix in which to store the inverse.
-  * \param invertible Reference to the bool variable in which to store whether the matrix is invertible.
-  * \param absDeterminantThreshold Optional parameter controlling the invertibility check.
-  *                                The matrix will be declared invertible if the absolute value of its
-  *                                determinant is greater than this threshold.
-  *
-  * Example: \include MatrixBase_computeInverseWithCheck.cpp
-  * Output: \verbinclude MatrixBase_computeInverseWithCheck.out
-  *
-  * \sa inverse(), computeInverseAndDetWithCheck()
-  */
-template<typename Derived>
-template<typename ResultType>
-inline void MatrixBase<Derived>::computeInverseWithCheck(
-    ResultType& inverse,
-    bool& invertible,
-    const RealScalar& absDeterminantThreshold
-  ) const
-{
-  RealScalar determinant;
-  // i'd love to put some static assertions there, but SFINAE means that they have no effect...
-  eigen_assert(rows() == cols());
-  computeInverseAndDetWithCheck(inverse,determinant,invertible,absDeterminantThreshold);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_INVERSE_H

ADDED   3rd_party/eigen/Eigen/src/LU/InverseImpl.h
Index: 3rd_party/eigen/Eigen/src/LU/InverseImpl.h
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/InverseImpl.h
+++ 3rd_party/eigen/Eigen/src/LU/InverseImpl.h
@@ -0,0 +1,415 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_INVERSE_IMPL_H
+#define EIGEN_INVERSE_IMPL_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************
+*** General case implementation ***
+**********************************/
+
+template<typename MatrixType, typename ResultType, int Size = MatrixType::RowsAtCompileTime>
+struct compute_inverse
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(const MatrixType& matrix, ResultType& result)
+  {
+    result = matrix.partialPivLu().inverse();
+  }
+};
+
+template<typename MatrixType, typename ResultType, int Size = MatrixType::RowsAtCompileTime>
+struct compute_inverse_and_det_with_check { /* nothing! general case not supported. */ };
+
+/****************************
+*** Size 1 implementation ***
+****************************/
+
+template<typename MatrixType, typename ResultType>
+struct compute_inverse<MatrixType, ResultType, 1>
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(const MatrixType& matrix, ResultType& result)
+  {
+    typedef typename MatrixType::Scalar Scalar;
+    internal::evaluator<MatrixType> matrixEval(matrix);
+    result.coeffRef(0,0) = Scalar(1) / matrixEval.coeff(0,0);
+  }
+};
+
+template<typename MatrixType, typename ResultType>
+struct compute_inverse_and_det_with_check<MatrixType, ResultType, 1>
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(
+    const MatrixType& matrix,
+    const typename MatrixType::RealScalar& absDeterminantThreshold,
+    ResultType& result,
+    typename ResultType::Scalar& determinant,
+    bool& invertible
+  )
+  {
+    using std::abs;
+    determinant = matrix.coeff(0,0);
+    invertible = abs(determinant) > absDeterminantThreshold;
+    if(invertible) result.coeffRef(0,0) = typename ResultType::Scalar(1) / determinant;
+  }
+};
+
+/****************************
+*** Size 2 implementation ***
+****************************/
+
+template<typename MatrixType, typename ResultType>
+EIGEN_DEVICE_FUNC 
+inline void compute_inverse_size2_helper(
+    const MatrixType& matrix, const typename ResultType::Scalar& invdet,
+    ResultType& result)
+{
+  result.coeffRef(0,0) =  matrix.coeff(1,1) * invdet;
+  result.coeffRef(1,0) = -matrix.coeff(1,0) * invdet;
+  result.coeffRef(0,1) = -matrix.coeff(0,1) * invdet;
+  result.coeffRef(1,1) =  matrix.coeff(0,0) * invdet;
+}
+
+template<typename MatrixType, typename ResultType>
+struct compute_inverse<MatrixType, ResultType, 2>
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(const MatrixType& matrix, ResultType& result)
+  {
+    typedef typename ResultType::Scalar Scalar;
+    const Scalar invdet = typename MatrixType::Scalar(1) / matrix.determinant();
+    compute_inverse_size2_helper(matrix, invdet, result);
+  }
+};
+
+template<typename MatrixType, typename ResultType>
+struct compute_inverse_and_det_with_check<MatrixType, ResultType, 2>
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(
+    const MatrixType& matrix,
+    const typename MatrixType::RealScalar& absDeterminantThreshold,
+    ResultType& inverse,
+    typename ResultType::Scalar& determinant,
+    bool& invertible
+  )
+  {
+    using std::abs;
+    typedef typename ResultType::Scalar Scalar;
+    determinant = matrix.determinant();
+    invertible = abs(determinant) > absDeterminantThreshold;
+    if(!invertible) return;
+    const Scalar invdet = Scalar(1) / determinant;
+    compute_inverse_size2_helper(matrix, invdet, inverse);
+  }
+};
+
+/****************************
+*** Size 3 implementation ***
+****************************/
+
+template<typename MatrixType, int i, int j>
+EIGEN_DEVICE_FUNC 
+inline typename MatrixType::Scalar cofactor_3x3(const MatrixType& m)
+{
+  enum {
+    i1 = (i+1) % 3,
+    i2 = (i+2) % 3,
+    j1 = (j+1) % 3,
+    j2 = (j+2) % 3
+  };
+  return m.coeff(i1, j1) * m.coeff(i2, j2)
+       - m.coeff(i1, j2) * m.coeff(i2, j1);
+}
+
+template<typename MatrixType, typename ResultType>
+EIGEN_DEVICE_FUNC
+inline void compute_inverse_size3_helper(
+    const MatrixType& matrix,
+    const typename ResultType::Scalar& invdet,
+    const Matrix<typename ResultType::Scalar,3,1>& cofactors_col0,
+    ResultType& result)
+{
+  result.row(0) = cofactors_col0 * invdet;
+  result.coeffRef(1,0) =  cofactor_3x3<MatrixType,0,1>(matrix) * invdet;
+  result.coeffRef(1,1) =  cofactor_3x3<MatrixType,1,1>(matrix) * invdet;
+  result.coeffRef(1,2) =  cofactor_3x3<MatrixType,2,1>(matrix) * invdet;
+  result.coeffRef(2,0) =  cofactor_3x3<MatrixType,0,2>(matrix) * invdet;
+  result.coeffRef(2,1) =  cofactor_3x3<MatrixType,1,2>(matrix) * invdet;
+  result.coeffRef(2,2) =  cofactor_3x3<MatrixType,2,2>(matrix) * invdet;
+}
+
+template<typename MatrixType, typename ResultType>
+struct compute_inverse<MatrixType, ResultType, 3>
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(const MatrixType& matrix, ResultType& result)
+  {
+    typedef typename ResultType::Scalar Scalar;
+    Matrix<typename MatrixType::Scalar,3,1> cofactors_col0;
+    cofactors_col0.coeffRef(0) =  cofactor_3x3<MatrixType,0,0>(matrix);
+    cofactors_col0.coeffRef(1) =  cofactor_3x3<MatrixType,1,0>(matrix);
+    cofactors_col0.coeffRef(2) =  cofactor_3x3<MatrixType,2,0>(matrix);
+    const Scalar det = (cofactors_col0.cwiseProduct(matrix.col(0))).sum();
+    const Scalar invdet = Scalar(1) / det;
+    compute_inverse_size3_helper(matrix, invdet, cofactors_col0, result);
+  }
+};
+
+template<typename MatrixType, typename ResultType>
+struct compute_inverse_and_det_with_check<MatrixType, ResultType, 3>
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(
+    const MatrixType& matrix,
+    const typename MatrixType::RealScalar& absDeterminantThreshold,
+    ResultType& inverse,
+    typename ResultType::Scalar& determinant,
+    bool& invertible
+  )
+  {
+    using std::abs;
+    typedef typename ResultType::Scalar Scalar;
+    Matrix<Scalar,3,1> cofactors_col0;
+    cofactors_col0.coeffRef(0) =  cofactor_3x3<MatrixType,0,0>(matrix);
+    cofactors_col0.coeffRef(1) =  cofactor_3x3<MatrixType,1,0>(matrix);
+    cofactors_col0.coeffRef(2) =  cofactor_3x3<MatrixType,2,0>(matrix);
+    determinant = (cofactors_col0.cwiseProduct(matrix.col(0))).sum();
+    invertible = abs(determinant) > absDeterminantThreshold;
+    if(!invertible) return;
+    const Scalar invdet = Scalar(1) / determinant;
+    compute_inverse_size3_helper(matrix, invdet, cofactors_col0, inverse);
+  }
+};
+
+/****************************
+*** Size 4 implementation ***
+****************************/
+
+template<typename Derived>
+EIGEN_DEVICE_FUNC 
+inline const typename Derived::Scalar general_det3_helper
+(const MatrixBase<Derived>& matrix, int i1, int i2, int i3, int j1, int j2, int j3)
+{
+  return matrix.coeff(i1,j1)
+         * (matrix.coeff(i2,j2) * matrix.coeff(i3,j3) - matrix.coeff(i2,j3) * matrix.coeff(i3,j2));
+}
+
+template<typename MatrixType, int i, int j>
+EIGEN_DEVICE_FUNC 
+inline typename MatrixType::Scalar cofactor_4x4(const MatrixType& matrix)
+{
+  enum {
+    i1 = (i+1) % 4,
+    i2 = (i+2) % 4,
+    i3 = (i+3) % 4,
+    j1 = (j+1) % 4,
+    j2 = (j+2) % 4,
+    j3 = (j+3) % 4
+  };
+  return general_det3_helper(matrix, i1, i2, i3, j1, j2, j3)
+       + general_det3_helper(matrix, i2, i3, i1, j1, j2, j3)
+       + general_det3_helper(matrix, i3, i1, i2, j1, j2, j3);
+}
+
+template<int Arch, typename Scalar, typename MatrixType, typename ResultType>
+struct compute_inverse_size4
+{
+  EIGEN_DEVICE_FUNC
+  static void run(const MatrixType& matrix, ResultType& result)
+  {
+    result.coeffRef(0,0) =  cofactor_4x4<MatrixType,0,0>(matrix);
+    result.coeffRef(1,0) = -cofactor_4x4<MatrixType,0,1>(matrix);
+    result.coeffRef(2,0) =  cofactor_4x4<MatrixType,0,2>(matrix);
+    result.coeffRef(3,0) = -cofactor_4x4<MatrixType,0,3>(matrix);
+    result.coeffRef(0,2) =  cofactor_4x4<MatrixType,2,0>(matrix);
+    result.coeffRef(1,2) = -cofactor_4x4<MatrixType,2,1>(matrix);
+    result.coeffRef(2,2) =  cofactor_4x4<MatrixType,2,2>(matrix);
+    result.coeffRef(3,2) = -cofactor_4x4<MatrixType,2,3>(matrix);
+    result.coeffRef(0,1) = -cofactor_4x4<MatrixType,1,0>(matrix);
+    result.coeffRef(1,1) =  cofactor_4x4<MatrixType,1,1>(matrix);
+    result.coeffRef(2,1) = -cofactor_4x4<MatrixType,1,2>(matrix);
+    result.coeffRef(3,1) =  cofactor_4x4<MatrixType,1,3>(matrix);
+    result.coeffRef(0,3) = -cofactor_4x4<MatrixType,3,0>(matrix);
+    result.coeffRef(1,3) =  cofactor_4x4<MatrixType,3,1>(matrix);
+    result.coeffRef(2,3) = -cofactor_4x4<MatrixType,3,2>(matrix);
+    result.coeffRef(3,3) =  cofactor_4x4<MatrixType,3,3>(matrix);
+    result /= (matrix.col(0).cwiseProduct(result.row(0).transpose())).sum();
+  }
+};
+
+template<typename MatrixType, typename ResultType>
+struct compute_inverse<MatrixType, ResultType, 4>
+ : compute_inverse_size4<Architecture::Target, typename MatrixType::Scalar,
+                            MatrixType, ResultType>
+{
+};
+
+template<typename MatrixType, typename ResultType>
+struct compute_inverse_and_det_with_check<MatrixType, ResultType, 4>
+{
+  EIGEN_DEVICE_FUNC
+  static inline void run(
+    const MatrixType& matrix,
+    const typename MatrixType::RealScalar& absDeterminantThreshold,
+    ResultType& inverse,
+    typename ResultType::Scalar& determinant,
+    bool& invertible
+  )
+  {
+    using std::abs;
+    determinant = matrix.determinant();
+    invertible = abs(determinant) > absDeterminantThreshold;
+    if(invertible) compute_inverse<MatrixType, ResultType>::run(matrix, inverse);
+  }
+};
+
+/*************************
+*** MatrixBase methods ***
+*************************/
+
+} // end namespace internal
+
+namespace internal {
+
+// Specialization for "dense = dense_xpr.inverse()"
+template<typename DstXprType, typename XprType>
+struct Assignment<DstXprType, Inverse<XprType>, internal::assign_op<typename DstXprType::Scalar,typename XprType::Scalar>, Dense2Dense>
+{
+  typedef Inverse<XprType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename XprType::Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+    
+    const int Size = EIGEN_PLAIN_ENUM_MIN(XprType::ColsAtCompileTime,DstXprType::ColsAtCompileTime);
+    EIGEN_ONLY_USED_FOR_DEBUG(Size);
+    eigen_assert(( (Size<=1) || (Size>4) || (extract_data(src.nestedExpression())!=extract_data(dst)))
+              && "Aliasing problem detected in inverse(), you need to do inverse().eval() here.");
+
+    typedef typename internal::nested_eval<XprType,XprType::ColsAtCompileTime>::type  ActualXprType;
+    typedef typename internal::remove_all<ActualXprType>::type                        ActualXprTypeCleanded;
+    
+    ActualXprType actual_xpr(src.nestedExpression());
+    
+    compute_inverse<ActualXprTypeCleanded, DstXprType>::run(actual_xpr, dst);
+  }
+};
+
+  
+} // end namespace internal
+
+/** \lu_module
+  *
+  * \returns the matrix inverse of this matrix.
+  *
+  * For small fixed sizes up to 4x4, this method uses cofactors.
+  * In the general case, this method uses class PartialPivLU.
+  *
+  * \note This matrix must be invertible, otherwise the result is undefined. If you need an
+  * invertibility check, do the following:
+  * \li for fixed sizes up to 4x4, use computeInverseAndDetWithCheck().
+  * \li for the general case, use class FullPivLU.
+  *
+  * Example: \include MatrixBase_inverse.cpp
+  * Output: \verbinclude MatrixBase_inverse.out
+  *
+  * \sa computeInverseAndDetWithCheck()
+  */
+template<typename Derived>
+inline const Inverse<Derived> MatrixBase<Derived>::inverse() const
+{
+  EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsInteger,THIS_FUNCTION_IS_NOT_FOR_INTEGER_NUMERIC_TYPES)
+  eigen_assert(rows() == cols());
+  return Inverse<Derived>(derived());
+}
+
+/** \lu_module
+  *
+  * Computation of matrix inverse and determinant, with invertibility check.
+  *
+  * This is only for fixed-size square matrices of size up to 4x4.
+  *
+  * \param inverse Reference to the matrix in which to store the inverse.
+  * \param determinant Reference to the variable in which to store the determinant.
+  * \param invertible Reference to the bool variable in which to store whether the matrix is invertible.
+  * \param absDeterminantThreshold Optional parameter controlling the invertibility check.
+  *                                The matrix will be declared invertible if the absolute value of its
+  *                                determinant is greater than this threshold.
+  *
+  * Example: \include MatrixBase_computeInverseAndDetWithCheck.cpp
+  * Output: \verbinclude MatrixBase_computeInverseAndDetWithCheck.out
+  *
+  * \sa inverse(), computeInverseWithCheck()
+  */
+template<typename Derived>
+template<typename ResultType>
+inline void MatrixBase<Derived>::computeInverseAndDetWithCheck(
+    ResultType& inverse,
+    typename ResultType::Scalar& determinant,
+    bool& invertible,
+    const RealScalar& absDeterminantThreshold
+  ) const
+{
+  // i'd love to put some static assertions there, but SFINAE means that they have no effect...
+  eigen_assert(rows() == cols());
+  // for 2x2, it's worth giving a chance to avoid evaluating.
+  // for larger sizes, evaluating has negligible cost and limits code size.
+  typedef typename internal::conditional<
+    RowsAtCompileTime == 2,
+    typename internal::remove_all<typename internal::nested_eval<Derived, 2>::type>::type,
+    PlainObject
+  >::type MatrixType;
+  internal::compute_inverse_and_det_with_check<MatrixType, ResultType>::run
+    (derived(), absDeterminantThreshold, inverse, determinant, invertible);
+}
+
+/** \lu_module
+  *
+  * Computation of matrix inverse, with invertibility check.
+  *
+  * This is only for fixed-size square matrices of size up to 4x4.
+  *
+  * \param inverse Reference to the matrix in which to store the inverse.
+  * \param invertible Reference to the bool variable in which to store whether the matrix is invertible.
+  * \param absDeterminantThreshold Optional parameter controlling the invertibility check.
+  *                                The matrix will be declared invertible if the absolute value of its
+  *                                determinant is greater than this threshold.
+  *
+  * Example: \include MatrixBase_computeInverseWithCheck.cpp
+  * Output: \verbinclude MatrixBase_computeInverseWithCheck.out
+  *
+  * \sa inverse(), computeInverseAndDetWithCheck()
+  */
+template<typename Derived>
+template<typename ResultType>
+inline void MatrixBase<Derived>::computeInverseWithCheck(
+    ResultType& inverse,
+    bool& invertible,
+    const RealScalar& absDeterminantThreshold
+  ) const
+{
+  RealScalar determinant;
+  // i'd love to put some static assertions there, but SFINAE means that they have no effect...
+  eigen_assert(rows() == cols());
+  computeInverseAndDetWithCheck(inverse,determinant,invertible,absDeterminantThreshold);
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_INVERSE_IMPL_H

Index: 3rd_party/eigen/Eigen/src/LU/PartialPivLU.h
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/PartialPivLU.h
+++ 3rd_party/eigen/Eigen/src/LU/PartialPivLU.h
@@ -9,19 +9,45 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PARTIALLU_H
 #define EIGEN_PARTIALLU_H
 
-namespace Eigen { 
+namespace Eigen {
+
+namespace internal {
+template<typename _MatrixType> struct traits<PartialPivLU<_MatrixType> >
+ : traits<_MatrixType>
+{
+  typedef MatrixXpr XprKind;
+  typedef SolverStorage StorageKind;
+  typedef traits<_MatrixType> BaseTraits;
+  enum {
+    Flags = BaseTraits::Flags & RowMajorBit,
+    CoeffReadCost = Dynamic
+  };
+};
+
+template<typename T,typename Derived>
+struct enable_if_ref;
+// {
+//   typedef Derived type;
+// };
+
+template<typename T,typename Derived>
+struct enable_if_ref<Ref<T>,Derived> {
+  typedef Derived type;
+};
+
+} // end namespace internal
 
 /** \ingroup LU_Module
   *
   * \class PartialPivLU
   *
   * \brief LU decomposition of a matrix with partial pivoting, and related features
   *
-  * \param MatrixType the type of the matrix of which we are computing the LU decomposition
+  * \tparam _MatrixType the type of the matrix of which we are computing the LU decomposition
   *
   * This class represents a LU decomposition of a \b square \b invertible matrix, with partial pivoting: the matrix A
   * is decomposed as A = PLU where L is unit-lower-triangular, U is upper-triangular, and P
   * is a permutation matrix.
   *
@@ -40,58 +66,73 @@
   * in the general case.
   * On the other hand, it is \b not suitable to determine whether a given matrix is invertible.
   *
   * The data of the LU decomposition can be directly accessed through the methods matrixLU(), permutationP().
   *
+  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
+  * 
   * \sa MatrixBase::partialPivLu(), MatrixBase::determinant(), MatrixBase::inverse(), MatrixBase::computeInverse(), class FullPivLU
   */
 template<typename _MatrixType> class PartialPivLU
+  : public SolverBase<PartialPivLU<_MatrixType> >
 {
   public:
 
     typedef _MatrixType MatrixType;
+    typedef SolverBase<PartialPivLU> Base;
+    EIGEN_GENERIC_PUBLIC_INTERFACE(PartialPivLU)
+    // FIXME StorageIndex defined in EIGEN_GENERIC_PUBLIC_INTERFACE should be int
     enum {
-      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      Options = MatrixType::Options,
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename internal::traits<MatrixType>::StorageKind StorageKind;
-    typedef typename MatrixType::Index Index;
     typedef PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> PermutationType;
     typedef Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> TranspositionType;
-
+    typedef typename MatrixType::PlainObject PlainObject;
 
     /**
-    * \brief Default Constructor.
-    *
-    * The default constructor is useful in cases in which the user intends to
-    * perform decompositions via PartialPivLU::compute(const MatrixType&).
-    */
+      * \brief Default Constructor.
+      *
+      * The default constructor is useful in cases in which the user intends to
+      * perform decompositions via PartialPivLU::compute(const MatrixType&).
+      */
     PartialPivLU();
 
     /** \brief Default Constructor with memory preallocation
       *
       * Like the default constructor but with preallocation of the internal data
       * according to the specified problem \a size.
       * \sa PartialPivLU()
       */
-    PartialPivLU(Index size);
+    explicit PartialPivLU(Index size);
 
     /** Constructor.
       *
       * \param matrix the matrix of which to compute the LU decomposition.
       *
       * \warning The matrix should have full rank (e.g. if it's square, it should be invertible).
       * If you need to deal with non-full rank, use class FullPivLU instead.
       */
-    PartialPivLU(const MatrixType& matrix);
+    template<typename InputType>
+    explicit PartialPivLU(const EigenBase<InputType>& matrix);
 
-    PartialPivLU& compute(const MatrixType& matrix);
+    /** Constructor for \link InplaceDecomposition inplace decomposition \endlink
+      *
+      * \param matrix the matrix of which to compute the LU decomposition.
+      *
+      * \warning The matrix should have full rank (e.g. if it's square, it should be invertible).
+      * If you need to deal with non-full rank, use class FullPivLU instead.
+      */
+    template<typename InputType>
+    explicit PartialPivLU(EigenBase<InputType>& matrix);
+
+    template<typename InputType>
+    PartialPivLU& compute(const EigenBase<InputType>& matrix) {
+      m_lu = matrix.derived();
+      compute();
+      return *this;
+    }
 
     /** \returns the LU decomposition matrix: the upper-triangular part is U, the
       * unit-lower-triangular part is L (at least for square matrices; in the non-square
       * case, special care is needed, see the documentation of class FullPivLU).
       *
@@ -126,30 +167,39 @@
       * Since this PartialPivLU class assumes anyway that the matrix A is invertible, the solution
       * theoretically exists and is unique regardless of b.
       *
       * \sa TriangularView::solve(), inverse(), computeInverse()
       */
+    // FIXME this is a copy-paste of the base-class member to add the isInitialized assertion.
     template<typename Rhs>
-    inline const internal::solve_retval<PartialPivLU, Rhs>
+    inline const Solve<PartialPivLU, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
       eigen_assert(m_isInitialized && "PartialPivLU is not initialized.");
-      return internal::solve_retval<PartialPivLU, Rhs>(*this, b.derived());
+      return Solve<PartialPivLU, Rhs>(*this, b.derived());
+    }
+
+    /** \returns an estimate of the reciprocal condition number of the matrix of which \c *this is
+        the LU decomposition.
+      */
+    inline RealScalar rcond() const
+    {
+      eigen_assert(m_isInitialized && "PartialPivLU is not initialized.");
+      return internal::rcond_estimate_helper(m_l1_norm, *this);
     }
 
     /** \returns the inverse of the matrix of which *this is the LU decomposition.
       *
       * \warning The matrix being decomposed here is assumed to be invertible. If you need to check for
       *          invertibility, use class FullPivLU instead.
       *
       * \sa MatrixBase::inverse(), LU::inverse()
       */
-    inline const internal::solve_retval<PartialPivLU,typename MatrixType::IdentityReturnType> inverse() const
+    inline const Inverse<PartialPivLU> inverse() const
     {
       eigen_assert(m_isInitialized && "PartialPivLU is not initialized.");
-      return internal::solve_retval<PartialPivLU,typename MatrixType::IdentityReturnType>
-               (*this, MatrixType::Identity(m_lu.rows(), m_lu.cols()));
+      return Inverse<PartialPivLU>(*this);
     }
 
     /** \returns the determinant of the matrix of which
       * *this is the LU decomposition. It has only linear complexity
       * (that is, O(n) where n is the dimension of the square matrix)
@@ -161,30 +211,91 @@
       * \warning a determinant can be very big or small, so for matrices
       * of large enough dimension, there is a risk of overflow/underflow.
       *
       * \sa MatrixBase::determinant()
       */
-    typename internal::traits<MatrixType>::Scalar determinant() const;
+    Scalar determinant() const;
 
     MatrixType reconstructedMatrix() const;
 
     inline Index rows() const { return m_lu.rows(); }
     inline Index cols() const { return m_lu.cols(); }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl(const RhsType &rhs, DstType &dst) const {
+     /* The decomposition PA = LU can be rewritten as A = P^{-1} L U.
+      * So we proceed as follows:
+      * Step 1: compute c = Pb.
+      * Step 2: replace c by the solution x to Lx = c.
+      * Step 3: replace c by the solution x to Ux = c.
+      */
+
+      eigen_assert(rhs.rows() == m_lu.rows());
+
+      // Step 1
+      dst = permutationP() * rhs;
+
+      // Step 2
+      m_lu.template triangularView<UnitLower>().solveInPlace(dst);
+
+      // Step 3
+      m_lu.template triangularView<Upper>().solveInPlace(dst);
+    }
+
+    template<bool Conjugate, typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl_transposed(const RhsType &rhs, DstType &dst) const {
+     /* The decomposition PA = LU can be rewritten as A = P^{-1} L U.
+      * So we proceed as follows:
+      * Step 1: compute c = Pb.
+      * Step 2: replace c by the solution x to Lx = c.
+      * Step 3: replace c by the solution x to Ux = c.
+      */
+
+      eigen_assert(rhs.rows() == m_lu.cols());
+
+      if (Conjugate) {
+        // Step 1
+        dst = m_lu.template triangularView<Upper>().adjoint().solve(rhs);
+        // Step 2
+        m_lu.template triangularView<UnitLower>().adjoint().solveInPlace(dst);
+      } else {
+        // Step 1
+        dst = m_lu.template triangularView<Upper>().transpose().solve(rhs);
+        // Step 2
+        m_lu.template triangularView<UnitLower>().transpose().solveInPlace(dst);
+      }
+      // Step 3
+      dst = permutationP().transpose() * dst;
+    }
+    #endif
 
   protected:
+
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+
+    void compute();
+
     MatrixType m_lu;
     PermutationType m_p;
     TranspositionType m_rowsTranspositions;
-    Index m_det_p;
+    RealScalar m_l1_norm;
+    signed char m_det_p;
     bool m_isInitialized;
 };
 
 template<typename MatrixType>
 PartialPivLU<MatrixType>::PartialPivLU()
   : m_lu(),
     m_p(),
     m_rowsTranspositions(),
+    m_l1_norm(0),
     m_det_p(0),
     m_isInitialized(false)
 {
 }
 
@@ -191,24 +302,40 @@
 template<typename MatrixType>
 PartialPivLU<MatrixType>::PartialPivLU(Index size)
   : m_lu(size, size),
     m_p(size),
     m_rowsTranspositions(size),
+    m_l1_norm(0),
+    m_det_p(0),
+    m_isInitialized(false)
+{
+}
+
+template<typename MatrixType>
+template<typename InputType>
+PartialPivLU<MatrixType>::PartialPivLU(const EigenBase<InputType>& matrix)
+  : m_lu(matrix.rows(),matrix.cols()),
+    m_p(matrix.rows()),
+    m_rowsTranspositions(matrix.rows()),
+    m_l1_norm(0),
     m_det_p(0),
     m_isInitialized(false)
 {
+  compute(matrix.derived());
 }
 
 template<typename MatrixType>
-PartialPivLU<MatrixType>::PartialPivLU(const MatrixType& matrix)
-  : m_lu(matrix.rows(), matrix.rows()),
+template<typename InputType>
+PartialPivLU<MatrixType>::PartialPivLU(EigenBase<InputType>& matrix)
+  : m_lu(matrix.derived()),
     m_p(matrix.rows()),
     m_rowsTranspositions(matrix.rows()),
+    m_l1_norm(0),
     m_det_p(0),
     m_isInitialized(false)
 {
-  compute(matrix);
+  compute();
 }
 
 namespace internal {
 
 /** \internal This is the blocked version of fullpivlu_unblocked() */
@@ -222,11 +349,10 @@
   // and Block.
   typedef Map<Matrix<Scalar, Dynamic, Dynamic, StorageOrder> > MapLU;
   typedef Block<MapLU, Dynamic, Dynamic> MatrixType;
   typedef Block<MatrixType,Dynamic,Dynamic> BlockType;
   typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::Index Index;
 
   /** \internal performs the LU decomposition in-place of the matrix \a lu
     * using an unblocked algorithm.
     *
     * In addition, this function returns the row transpositions in the
@@ -236,28 +362,30 @@
     *
     * \returns The index of the first pivot which is exactly zero if any, or a negative number otherwise.
     */
   static Index unblocked_lu(MatrixType& lu, PivIndex* row_transpositions, PivIndex& nb_transpositions)
   {
+    typedef scalar_score_coeff_op<Scalar> Scoring;
+    typedef typename Scoring::result_type Score;
     const Index rows = lu.rows();
     const Index cols = lu.cols();
     const Index size = (std::min)(rows,cols);
     nb_transpositions = 0;
     Index first_zero_pivot = -1;
     for(Index k = 0; k < size; ++k)
     {
       Index rrows = rows-k-1;
       Index rcols = cols-k-1;
-        
+
       Index row_of_biggest_in_col;
-      RealScalar biggest_in_corner
-        = lu.col(k).tail(rows-k).cwiseAbs().maxCoeff(&row_of_biggest_in_col);
+      Score biggest_in_corner
+        = lu.col(k).tail(rows-k).unaryExpr(Scoring()).maxCoeff(&row_of_biggest_in_col);
       row_of_biggest_in_col += k;
 
       row_transpositions[k] = PivIndex(row_of_biggest_in_col);
 
-      if(biggest_in_corner != RealScalar(0))
+      if(biggest_in_corner != Score(0))
       {
         if(k != row_of_biggest_in_col)
         {
           lu.row(k).swap(lu.row(row_of_biggest_in_col));
           ++nb_transpositions;
@@ -346,11 +474,11 @@
 
       nb_transpositions += nb_transpositions_in_panel;
       // update permutations and apply them to A_0
       for(Index i=k; i<k+bs; ++i)
       {
-        Index piv = (row_transpositions[i] += k);
+        Index piv = (row_transpositions[i] += internal::convert_index<PivIndex>(k));
         A_0.row(i).swap(A_0.row(piv));
       }
 
       if(trows)
       {
@@ -369,47 +497,48 @@
 };
 
 /** \internal performs the LU decomposition with partial pivoting in-place.
   */
 template<typename MatrixType, typename TranspositionType>
-void partial_lu_inplace(MatrixType& lu, TranspositionType& row_transpositions, typename TranspositionType::Index& nb_transpositions)
+void partial_lu_inplace(MatrixType& lu, TranspositionType& row_transpositions, typename TranspositionType::StorageIndex& nb_transpositions)
 {
   eigen_assert(lu.cols() == row_transpositions.size());
   eigen_assert((&row_transpositions.coeffRef(1)-&row_transpositions.coeffRef(0)) == 1);
 
   partial_lu_impl
-    <typename MatrixType::Scalar, MatrixType::Flags&RowMajorBit?RowMajor:ColMajor, typename TranspositionType::Index>
+    <typename MatrixType::Scalar, MatrixType::Flags&RowMajorBit?RowMajor:ColMajor, typename TranspositionType::StorageIndex>
     ::blocked_lu(lu.rows(), lu.cols(), &lu.coeffRef(0,0), lu.outerStride(), &row_transpositions.coeffRef(0), nb_transpositions);
 }
 
 } // end namespace internal
 
 template<typename MatrixType>
-PartialPivLU<MatrixType>& PartialPivLU<MatrixType>::compute(const MatrixType& matrix)
-{
-  // the row permutation is stored as int indices, so just to be sure:
-  eigen_assert(matrix.rows()<NumTraits<int>::highest());
-  
-  m_lu = matrix;
-
-  eigen_assert(matrix.rows() == matrix.cols() && "PartialPivLU is only for square (and moreover invertible) matrices");
-  const Index size = matrix.rows();
+void PartialPivLU<MatrixType>::compute()
+{
+  check_template_parameters();
+
+  // the row permutation is stored as int indices, so just to be sure:
+  eigen_assert(m_lu.rows()<NumTraits<int>::highest());
+
+  m_l1_norm = m_lu.cwiseAbs().colwise().sum().maxCoeff();
+
+  eigen_assert(m_lu.rows() == m_lu.cols() && "PartialPivLU is only for square (and moreover invertible) matrices");
+  const Index size = m_lu.rows();
 
   m_rowsTranspositions.resize(size);
 
-  typename TranspositionType::Index nb_transpositions;
+  typename TranspositionType::StorageIndex nb_transpositions;
   internal::partial_lu_inplace(m_lu, m_rowsTranspositions, nb_transpositions);
   m_det_p = (nb_transpositions%2) ? -1 : 1;
 
   m_p = m_rowsTranspositions;
 
   m_isInitialized = true;
-  return *this;
 }
 
 template<typename MatrixType>
-typename internal::traits<MatrixType>::Scalar PartialPivLU<MatrixType>::determinant() const
+typename PartialPivLU<MatrixType>::Scalar PartialPivLU<MatrixType>::determinant() const
 {
   eigen_assert(m_isInitialized && "PartialPivLU is not initialized.");
   return Scalar(m_det_p) * m_lu.diagonal().prod();
 }
 
@@ -428,42 +557,25 @@
   res = m_p.inverse() * res;
 
   return res;
 }
 
-/***** Implementation of solve() *****************************************************/
+/***** Implementation details *****************************************************/
 
 namespace internal {
 
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<PartialPivLU<_MatrixType>, Rhs>
-  : solve_retval_base<PartialPivLU<_MatrixType>, Rhs>
-{
-  EIGEN_MAKE_SOLVE_HELPERS(PartialPivLU<_MatrixType>,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    /* The decomposition PA = LU can be rewritten as A = P^{-1} L U.
-    * So we proceed as follows:
-    * Step 1: compute c = Pb.
-    * Step 2: replace c by the solution x to Lx = c.
-    * Step 3: replace c by the solution x to Ux = c.
-    */
-
-    eigen_assert(rhs().rows() == dec().matrixLU().rows());
-
-    // Step 1
-    dst = dec().permutationP() * rhs();
-
-    // Step 2
-    dec().matrixLU().template triangularView<UnitLower>().solveInPlace(dst);
-
-    // Step 3
-    dec().matrixLU().template triangularView<Upper>().solveInPlace(dst);
+/***** Implementation of inverse() *****************************************************/
+template<typename DstXprType, typename MatrixType>
+struct Assignment<DstXprType, Inverse<PartialPivLU<MatrixType> >, internal::assign_op<typename DstXprType::Scalar,typename PartialPivLU<MatrixType>::Scalar>, Dense2Dense>
+{
+  typedef PartialPivLU<MatrixType> LuType;
+  typedef Inverse<LuType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename LuType::Scalar> &)
+  {
+    dst = src.nestedExpression().solve(MatrixType::Identity(src.rows(), src.cols()));
   }
 };
-
 } // end namespace internal
 
 /******** MatrixBase methods *******/
 
 /** \lu_module
@@ -477,11 +589,10 @@
 MatrixBase<Derived>::partialPivLu() const
 {
   return PartialPivLU<PlainObject>(eval());
 }
 
-#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
 /** \lu_module
   *
   * Synonym of partialPivLu().
   *
   * \return the partial-pivoting LU decomposition of \c *this.
@@ -492,10 +603,9 @@
 inline const PartialPivLU<typename MatrixBase<Derived>::PlainObject>
 MatrixBase<Derived>::lu() const
 {
   return PartialPivLU<PlainObject>(eval());
 }
-#endif
 
 } // end namespace Eigen
 
 #endif // EIGEN_PARTIALLU_H

ADDED   3rd_party/eigen/Eigen/src/LU/PartialPivLU_LAPACKE.h
Index: 3rd_party/eigen/Eigen/src/LU/PartialPivLU_LAPACKE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/PartialPivLU_LAPACKE.h
+++ 3rd_party/eigen/Eigen/src/LU/PartialPivLU_LAPACKE.h
@@ -0,0 +1,83 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to LAPACKe
+ *     LU decomposition with partial pivoting based on LAPACKE_?getrf function.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_PARTIALLU_LAPACK_H
+#define EIGEN_PARTIALLU_LAPACK_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/** \internal Specialization for the data types supported by LAPACKe */
+
+#define EIGEN_LAPACKE_LU_PARTPIV(EIGTYPE, LAPACKE_TYPE, LAPACKE_PREFIX) \
+template<int StorageOrder> \
+struct partial_lu_impl<EIGTYPE, StorageOrder, lapack_int> \
+{ \
+  /* \internal performs the LU decomposition in-place of the matrix represented */ \
+  static lapack_int blocked_lu(Index rows, Index cols, EIGTYPE* lu_data, Index luStride, lapack_int* row_transpositions, lapack_int& nb_transpositions, lapack_int maxBlockSize=256) \
+  { \
+    EIGEN_UNUSED_VARIABLE(maxBlockSize);\
+    lapack_int matrix_order, first_zero_pivot; \
+    lapack_int m, n, lda, *ipiv, info; \
+    EIGTYPE* a; \
+/* Set up parameters for ?getrf */ \
+    matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
+    lda = convert_index<lapack_int>(luStride); \
+    a = lu_data; \
+    ipiv = row_transpositions; \
+    m = convert_index<lapack_int>(rows); \
+    n = convert_index<lapack_int>(cols); \
+    nb_transpositions = 0; \
+\
+    info = LAPACKE_##LAPACKE_PREFIX##getrf( matrix_order, m, n, (LAPACKE_TYPE*)a, lda, ipiv ); \
+\
+    for(int i=0;i<m;i++) { ipiv[i]--; if (ipiv[i]!=i) nb_transpositions++; } \
+\
+    eigen_assert(info >= 0); \
+/* something should be done with nb_transpositions */ \
+\
+    first_zero_pivot = info; \
+    return first_zero_pivot; \
+  } \
+};
+
+EIGEN_LAPACKE_LU_PARTPIV(double, double, d)
+EIGEN_LAPACKE_LU_PARTPIV(float, float, s)
+EIGEN_LAPACKE_LU_PARTPIV(dcomplex, lapack_complex_double, z)
+EIGEN_LAPACKE_LU_PARTPIV(scomplex, lapack_complex_float,  c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_PARTIALLU_LAPACK_H

DELETED 3rd_party/eigen/Eigen/src/LU/PartialPivLU_MKL.h
Index: 3rd_party/eigen/Eigen/src/LU/PartialPivLU_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/PartialPivLU_MKL.h
+++ 3rd_party/eigen/Eigen/src/LU/PartialPivLU_MKL.h
@@ -1,85 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *     LU decomposition with partial pivoting based on LAPACKE_?getrf function.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_PARTIALLU_LAPACK_H
-#define EIGEN_PARTIALLU_LAPACK_H
-
-#include "Eigen/src/Core/util/MKL_support.h"
-
-namespace Eigen { 
-
-namespace internal {
-
-/** \internal Specialization for the data types supported by MKL */
-
-#define EIGEN_MKL_LU_PARTPIV(EIGTYPE, MKLTYPE, MKLPREFIX) \
-template<int StorageOrder> \
-struct partial_lu_impl<EIGTYPE, StorageOrder, lapack_int> \
-{ \
-  /* \internal performs the LU decomposition in-place of the matrix represented */ \
-  static lapack_int blocked_lu(lapack_int rows, lapack_int cols, EIGTYPE* lu_data, lapack_int luStride, lapack_int* row_transpositions, lapack_int& nb_transpositions, lapack_int maxBlockSize=256) \
-  { \
-    EIGEN_UNUSED_VARIABLE(maxBlockSize);\
-    lapack_int matrix_order, first_zero_pivot; \
-    lapack_int m, n, lda, *ipiv, info; \
-    EIGTYPE* a; \
-/* Set up parameters for ?getrf */ \
-    matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
-    lda = luStride; \
-    a = lu_data; \
-    ipiv = row_transpositions; \
-    m = rows; \
-    n = cols; \
-    nb_transpositions = 0; \
-\
-    info = LAPACKE_##MKLPREFIX##getrf( matrix_order, m, n, (MKLTYPE*)a, lda, ipiv ); \
-\
-    for(int i=0;i<m;i++) { ipiv[i]--; if (ipiv[i]!=i) nb_transpositions++; } \
-\
-    eigen_assert(info >= 0); \
-/* something should be done with nb_transpositions */ \
-\
-    first_zero_pivot = info; \
-    return first_zero_pivot; \
-  } \
-};
-
-EIGEN_MKL_LU_PARTPIV(double, double, d)
-EIGEN_MKL_LU_PARTPIV(float, float, s)
-EIGEN_MKL_LU_PARTPIV(dcomplex, MKL_Complex16, z)
-EIGEN_MKL_LU_PARTPIV(scomplex, MKL_Complex8, c)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_PARTIALLU_LAPACK_H

DELETED 3rd_party/eigen/Eigen/src/LU/arch/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/LU/arch/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/arch/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/LU/arch/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_LU_arch_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_LU_arch_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/LU/arch COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/LU/arch/Inverse_SSE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/LU/arch/Inverse_SSE.h
+++ 3rd_party/eigen/Eigen/src/LU/arch/Inverse_SSE.h
@@ -33,17 +33,19 @@
 
 template<typename MatrixType, typename ResultType>
 struct compute_inverse_size4<Architecture::SSE, float, MatrixType, ResultType>
 {
   enum {
-    MatrixAlignment     = bool(MatrixType::Flags&AlignedBit),
-    ResultAlignment     = bool(ResultType::Flags&AlignedBit),
+    MatrixAlignment     = traits<MatrixType>::Alignment,
+    ResultAlignment     = traits<ResultType>::Alignment,
     StorageOrdersMatch  = (MatrixType::Flags&RowMajorBit) == (ResultType::Flags&RowMajorBit)
   };
+  typedef typename conditional<(MatrixType::Flags&LinearAccessBit),MatrixType const &,typename MatrixType::PlainObject>::type ActualMatrixType;
   
-  static void run(const MatrixType& matrix, ResultType& result)
+  static void run(const MatrixType& mat, ResultType& result)
   {
+    ActualMatrixType matrix(mat);
     EIGEN_ALIGN16 const unsigned int _Sign_PNNP[4] = { 0x00000000, 0x80000000, 0x80000000, 0x00000000 };
 
     // Load the full matrix into registers
     __m128 _L1 = matrix.template packet<MatrixAlignment>( 0);
     __m128 _L2 = matrix.template packet<MatrixAlignment>( 4);
@@ -149,34 +151,39 @@
     iA = _mm_mul_ps(rd,iA);
     iB = _mm_mul_ps(rd,iB);
     iC = _mm_mul_ps(rd,iC);
     iD = _mm_mul_ps(rd,iD);
 
-    result.template writePacket<ResultAlignment>( 0, _mm_shuffle_ps(iA,iB,0x77));
-    result.template writePacket<ResultAlignment>( 4, _mm_shuffle_ps(iA,iB,0x22));
-    result.template writePacket<ResultAlignment>( 8, _mm_shuffle_ps(iC,iD,0x77));
-    result.template writePacket<ResultAlignment>(12, _mm_shuffle_ps(iC,iD,0x22));
+    Index res_stride = result.outerStride();
+    float* res = result.data();
+    pstoret<float, Packet4f, ResultAlignment>(res+0,            _mm_shuffle_ps(iA,iB,0x77));
+    pstoret<float, Packet4f, ResultAlignment>(res+res_stride,   _mm_shuffle_ps(iA,iB,0x22));
+    pstoret<float, Packet4f, ResultAlignment>(res+2*res_stride, _mm_shuffle_ps(iC,iD,0x77));
+    pstoret<float, Packet4f, ResultAlignment>(res+3*res_stride, _mm_shuffle_ps(iC,iD,0x22));
   }
 
 };
 
 template<typename MatrixType, typename ResultType>
 struct compute_inverse_size4<Architecture::SSE, double, MatrixType, ResultType>
 {
   enum {
-    MatrixAlignment = bool(MatrixType::Flags&AlignedBit),
-    ResultAlignment = bool(ResultType::Flags&AlignedBit),
+    MatrixAlignment     = traits<MatrixType>::Alignment,
+    ResultAlignment     = traits<ResultType>::Alignment,
     StorageOrdersMatch  = (MatrixType::Flags&RowMajorBit) == (ResultType::Flags&RowMajorBit)
   };
-  static void run(const MatrixType& matrix, ResultType& result)
+  typedef typename conditional<(MatrixType::Flags&LinearAccessBit),MatrixType const &,typename MatrixType::PlainObject>::type ActualMatrixType;
+  
+  static void run(const MatrixType& mat, ResultType& result)
   {
+    ActualMatrixType matrix(mat);
     const __m128d _Sign_NP = _mm_castsi128_pd(_mm_set_epi32(0x0,0x0,0x80000000,0x0));
     const __m128d _Sign_PN = _mm_castsi128_pd(_mm_set_epi32(0x80000000,0x0,0x0,0x0));
 
     // The inverse is calculated using "Divide and Conquer" technique. The
     // original matrix is divide into four 2x2 sub-matrices. Since each
-    // register of the matrix holds two element, the smaller matrices are
+    // register of the matrix holds two elements, the smaller matrices are
     // consisted of two registers. Hence we get a better locality of the
     // calculations.
 
     // the four sub-matrices
     __m128d A1, A2, B1, B2, C1, C2, D1, D2;
@@ -309,21 +316,23 @@
     //  iC = B*|C| - A*C#*D;
     dC = _mm_shuffle_pd(dC,dC,0);
     iC1 = _mm_sub_pd(_mm_mul_pd(B1, dC), iC1);
     iC2 = _mm_sub_pd(_mm_mul_pd(B2, dC), iC2);
 
-    result.template writePacket<ResultAlignment>( 0, _mm_mul_pd(_mm_shuffle_pd(iA2, iA1, 3), d1));     // iA# / det
-    result.template writePacket<ResultAlignment>( 4, _mm_mul_pd(_mm_shuffle_pd(iA2, iA1, 0), d2));
-    result.template writePacket<ResultAlignment>( 2, _mm_mul_pd(_mm_shuffle_pd(iB2, iB1, 3), d1));     // iB# / det
-    result.template writePacket<ResultAlignment>( 6, _mm_mul_pd(_mm_shuffle_pd(iB2, iB1, 0), d2));
-    result.template writePacket<ResultAlignment>( 8, _mm_mul_pd(_mm_shuffle_pd(iC2, iC1, 3), d1));     // iC# / det
-    result.template writePacket<ResultAlignment>(12, _mm_mul_pd(_mm_shuffle_pd(iC2, iC1, 0), d2));
-    result.template writePacket<ResultAlignment>(10, _mm_mul_pd(_mm_shuffle_pd(iD2, iD1, 3), d1));     // iD# / det
-    result.template writePacket<ResultAlignment>(14, _mm_mul_pd(_mm_shuffle_pd(iD2, iD1, 0), d2));
+    Index res_stride = result.outerStride();
+    double* res = result.data();
+    pstoret<double, Packet2d, ResultAlignment>(res+0,             _mm_mul_pd(_mm_shuffle_pd(iA2, iA1, 3), d1));
+    pstoret<double, Packet2d, ResultAlignment>(res+res_stride,    _mm_mul_pd(_mm_shuffle_pd(iA2, iA1, 0), d2));
+    pstoret<double, Packet2d, ResultAlignment>(res+2,             _mm_mul_pd(_mm_shuffle_pd(iB2, iB1, 3), d1));
+    pstoret<double, Packet2d, ResultAlignment>(res+res_stride+2,  _mm_mul_pd(_mm_shuffle_pd(iB2, iB1, 0), d2));
+    pstoret<double, Packet2d, ResultAlignment>(res+2*res_stride,  _mm_mul_pd(_mm_shuffle_pd(iC2, iC1, 3), d1));
+    pstoret<double, Packet2d, ResultAlignment>(res+3*res_stride,  _mm_mul_pd(_mm_shuffle_pd(iC2, iC1, 0), d2));
+    pstoret<double, Packet2d, ResultAlignment>(res+2*res_stride+2,_mm_mul_pd(_mm_shuffle_pd(iD2, iD1, 3), d1));
+    pstoret<double, Packet2d, ResultAlignment>(res+3*res_stride+2,_mm_mul_pd(_mm_shuffle_pd(iD2, iD1, 0), d2));
   }
 };
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_INVERSE_SSE_H

DELETED 3rd_party/eigen/Eigen/src/MetisSupport/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/MetisSupport/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/MetisSupport/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/MetisSupport/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_MetisSupport_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_MetisSupport_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/MetisSupport COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/MetisSupport/MetisSupport.h
==================================================================
--- 3rd_party/eigen/Eigen/src/MetisSupport/MetisSupport.h
+++ 3rd_party/eigen/Eigen/src/MetisSupport/MetisSupport.h
@@ -16,16 +16,16 @@
  * If A is the original matrix and Ap is the permuted matrix, 
  * the fill-reducing permutation is defined as follows :
  * Row (column) i of A is the matperm(i) row (column) of Ap. 
  * WARNING: As computed by METIS, this corresponds to the vector iperm (instead of perm)
  */
-template <typename Index>
+template <typename StorageIndex>
 class MetisOrdering
 {
 public:
-  typedef PermutationMatrix<Dynamic,Dynamic,Index> PermutationType;
-  typedef Matrix<Index,Dynamic,1> IndexVector; 
+  typedef PermutationMatrix<Dynamic,Dynamic,StorageIndex> PermutationType;
+  typedef Matrix<StorageIndex,Dynamic,1> IndexVector; 
   
   template <typename MatrixType>
   void get_symmetrized_graph(const MatrixType& A)
   {
     Index m = A.cols(); 
@@ -34,11 +34,11 @@
     MatrixType At = A.transpose(); 
     // Get the number of nonzeros elements in each row/col of At+A
     Index TotNz = 0; 
     IndexVector visited(m); 
     visited.setConstant(-1); 
-    for (int j = 0; j < m; j++)
+    for (StorageIndex j = 0; j < m; j++)
     {
       // Compute the union structure of of A(j,:) and At(j,:)
       visited(j) = j; // Do not include the diagonal element
       // Get the nonzeros in row/column j of A
       for (typename MatrixType::InnerIterator it(A, j); it; ++it)
@@ -65,20 +65,20 @@
     m_indexPtr.resize(m+1);
     m_innerIndices.resize(TotNz); 
 
     // Now compute the real adjacency list of each column/row 
     visited.setConstant(-1); 
-    Index CurNz = 0; 
-    for (int j = 0; j < m; j++)
+    StorageIndex CurNz = 0; 
+    for (StorageIndex j = 0; j < m; j++)
     {
       m_indexPtr(j) = CurNz; 
       
       visited(j) = j; // Do not include the diagonal element
       // Add the pattern of row/column j of A to A+At
       for (typename MatrixType::InnerIterator it(A,j); it; ++it)
       {
-        Index idx = it.index(); // Get the row index (for column major) or column index (for row major)
+        StorageIndex idx = it.index(); // Get the row index (for column major) or column index (for row major)
         if (visited(idx) != j ) 
         {
           visited(idx) = j; 
           m_innerIndices(CurNz) = idx; 
           CurNz++; 
@@ -85,11 +85,11 @@
         }
       }
       //Add the pattern of row/column j of At to A+At
       for (typename MatrixType::InnerIterator it(At, j); it; ++it)
       {
-        Index idx = it.index(); 
+        StorageIndex idx = it.index(); 
         if(visited(idx) != j)
         {
           visited(idx) = j; 
           m_innerIndices(CurNz) = idx; 
           ++CurNz; 
@@ -100,11 +100,11 @@
   }
   
   template <typename MatrixType>
   void operator() (const MatrixType& A, PermutationType& matperm)
   {
-     Index m = A.cols();
+     StorageIndex m = internal::convert_index<StorageIndex>(A.cols()); // must be StorageIndex, because it is passed by address to METIS
      IndexVector perm(m),iperm(m); 
     // First, symmetrize the matrix graph. 
      get_symmetrized_graph(A); 
      int output_error;
      

Index: 3rd_party/eigen/Eigen/src/OrderingMethods/Amd.h
==================================================================
--- 3rd_party/eigen/Eigen/src/OrderingMethods/Amd.h
+++ 3rd_party/eigen/Eigen/src/OrderingMethods/Amd.h
@@ -6,11 +6,11 @@
 /*
 
 NOTE: this routine has been adapted from the CSparse library:
 
 Copyright (c) 2006, Timothy A. Davis.
-http://www.cise.ufl.edu/research/sparse/CSparse
+http://www.suitesparse.com
 
 CSparse is free software; you can redistribute it and/or
 modify it under the terms of the GNU Lesser General Public
 License as published by the Free Software Foundation; either
 version 2.1 of the License, or (at your option) any later version.
@@ -39,14 +39,14 @@
 template<typename T> inline T amd_unflip(const T& i) { return i<0 ? amd_flip(i) : i; }
 template<typename T0, typename T1> inline bool amd_marked(const T0* w, const T1& j) { return w[j]<0; }
 template<typename T0, typename T1> inline void amd_mark(const T0* w, const T1& j) { return w[j] = amd_flip(w[j]); }
 
 /* clear w */
-template<typename Index>
-static int cs_wclear (Index mark, Index lemax, Index *w, Index n)
+template<typename StorageIndex>
+static StorageIndex cs_wclear (StorageIndex mark, StorageIndex lemax, StorageIndex *w, StorageIndex n)
 {
-  Index k;
+  StorageIndex k;
   if(mark < 2 || (mark + lemax < 0))
   {
     for(k = 0; k < n; k++)
       if(w[k] != 0)
         w[k] = 1;
@@ -54,14 +54,14 @@
   }
   return (mark);     /* at this point, w[0..n-1] < mark holds */
 }
 
 /* depth-first search and postorder of a tree rooted at node j */
-template<typename Index>
-Index cs_tdfs(Index j, Index k, Index *head, const Index *next, Index *post, Index *stack)
+template<typename StorageIndex>
+StorageIndex cs_tdfs(StorageIndex j, StorageIndex k, StorageIndex *head, const StorageIndex *next, StorageIndex *post, StorageIndex *stack)
 {
-  int i, p, top = 0;
+  StorageIndex i, p, top = 0;
   if(!head || !next || !post || !stack) return (-1);    /* check inputs */
   stack[0] = j;                 /* place j on the stack */
   while (top >= 0)                /* while (stack is not empty) */
   {
     p = stack[top];           /* p = top of stack */
@@ -82,46 +82,49 @@
 
 
 /** \internal
   * \ingroup OrderingMethods_Module 
   * Approximate minimum degree ordering algorithm.
-  * \returns the permutation P reducing the fill-in of the input matrix \a C
-  * The input matrix \a C must be a selfadjoint compressed column major SparseMatrix object. Both the upper and lower parts have to be stored, but the diagonal entries are optional.
+  *
+  * \param[in] C the input selfadjoint matrix stored in compressed column major format.
+  * \param[out] perm the permutation P reducing the fill-in of the input matrix \a C
+  *
+  * Note that the input matrix \a C must be complete, that is both the upper and lower parts have to be stored, as well as the diagonal entries.
   * On exit the values of C are destroyed */
-template<typename Scalar, typename Index>
-void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,Index>& C, PermutationMatrix<Dynamic,Dynamic,Index>& perm)
+template<typename Scalar, typename StorageIndex>
+void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,StorageIndex>& C, PermutationMatrix<Dynamic,Dynamic,StorageIndex>& perm)
 {
   using std::sqrt;
   
-  int d, dk, dext, lemax = 0, e, elenk, eln, i, j, k, k1,
-      k2, k3, jlast, ln, dense, nzmax, mindeg = 0, nvi, nvj, nvk, mark, wnvi,
-      ok, nel = 0, p, p1, p2, p3, p4, pj, pk, pk1, pk2, pn, q, t;
-  unsigned int h;
-  
-  Index n = C.cols();
-  dense = std::max<Index> (16, Index(10 * sqrt(double(n))));   /* find dense threshold */
-  dense = std::min<Index> (n-2, dense);
-  
-  Index cnz = C.nonZeros();
+  StorageIndex d, dk, dext, lemax = 0, e, elenk, eln, i, j, k, k1,
+                k2, k3, jlast, ln, dense, nzmax, mindeg = 0, nvi, nvj, nvk, mark, wnvi,
+                ok, nel = 0, p, p1, p2, p3, p4, pj, pk, pk1, pk2, pn, q, t, h;
+  
+  StorageIndex n = StorageIndex(C.cols());
+  dense = std::max<StorageIndex> (16, StorageIndex(10 * sqrt(double(n))));   /* find dense threshold */
+  dense = (std::min)(n-2, dense);
+  
+  StorageIndex cnz = StorageIndex(C.nonZeros());
   perm.resize(n+1);
   t = cnz + cnz/5 + 2*n;                 /* add elbow room to C */
   C.resizeNonZeros(t);
   
-  Index* W       = new Index[8*(n+1)]; /* get workspace */
-  Index* len     = W;
-  Index* nv      = W +   (n+1);
-  Index* next    = W + 2*(n+1);
-  Index* head    = W + 3*(n+1);
-  Index* elen    = W + 4*(n+1);
-  Index* degree  = W + 5*(n+1);
-  Index* w       = W + 6*(n+1);
-  Index* hhead   = W + 7*(n+1);
-  Index* last    = perm.indices().data();                              /* use P as workspace for last */
+  // get workspace
+  ei_declare_aligned_stack_constructed_variable(StorageIndex,W,8*(n+1),0);
+  StorageIndex* len     = W;
+  StorageIndex* nv      = W +   (n+1);
+  StorageIndex* next    = W + 2*(n+1);
+  StorageIndex* head    = W + 3*(n+1);
+  StorageIndex* elen    = W + 4*(n+1);
+  StorageIndex* degree  = W + 5*(n+1);
+  StorageIndex* w       = W + 6*(n+1);
+  StorageIndex* hhead   = W + 7*(n+1);
+  StorageIndex* last    = perm.indices().data();                              /* use P as workspace for last */
   
   /* --- Initialize quotient graph ---------------------------------------- */
-  Index* Cp = C.outerIndexPtr();
-  Index* Ci = C.innerIndexPtr();
+  StorageIndex* Cp = C.outerIndexPtr();
+  StorageIndex* Ci = C.innerIndexPtr();
   for(k = 0; k < n; k++)
     len[k] = Cp[k+1] - Cp[k];
   len[n] = 0;
   nzmax = t;
   
@@ -134,27 +137,32 @@
     nv[i]     = 1;                      // node i is just one node
     w[i]      = 1;                      // node i is alive
     elen[i]   = 0;                      // Ek of node i is empty
     degree[i] = len[i];                 // degree of node i
   }
-  mark = internal::cs_wclear<Index>(0, 0, w, n);         /* clear w */
-  elen[n] = -2;                         /* n is a dead element */
-  Cp[n] = -1;                           /* n is a root of assembly tree */
-  w[n] = 0;                             /* n is a dead element */
+  mark = internal::cs_wclear<StorageIndex>(0, 0, w, n);         /* clear w */
   
   /* --- Initialize degree lists ------------------------------------------ */
   for(i = 0; i < n; i++)
   {
+    bool has_diag = false;
+    for(p = Cp[i]; p<Cp[i+1]; ++p)
+      if(Ci[p]==i)
+      {
+        has_diag = true;
+        break;
+      }
+   
     d = degree[i];
-    if(d == 0)                         /* node i is empty */
+    if(d == 1 && has_diag)           /* node i is empty */
     {
       elen[i] = -2;                 /* element i is dead */
       nel++;
       Cp[i] = -1;                   /* i is a root of assembly tree */
       w[i] = 0;
     }
-    else if(d > dense)                 /* node i is dense */
+    else if(d > dense || !has_diag)  /* node i is dense or has no structural diagonal element */
     {
       nv[i] = 0;                    /* absorb i into element n */
       elen[i] = -1;                 /* node i is dead */
       nel++;
       Cp[i] = amd_flip (n);
@@ -165,10 +173,14 @@
       if(head[d] != -1) last[head[d]] = i;
       next[i] = head[d];           /* put node i in degree list d */
       head[d] = i;
     }
   }
+  
+  elen[n] = -2;                         /* n is a dead element */
+  Cp[n] = -1;                           /* n is a root of assembly tree */
+  w[n] = 0;                             /* n is a dead element */
   
   while (nel < n)                         /* while (selecting pivots) do */
   {
     /* --- Select node of minimum approximate degree -------------------- */
     for(k = -1; mindeg < n && (k = head[mindeg]) == -1; mindeg++) {}
@@ -249,11 +261,11 @@
     Cp[k] = pk1;                      /* element k is in Ci[pk1..pk2-1] */
     len[k] = pk2 - pk1;
     elen[k] = -2;                     /* k is now an element */
     
     /* --- Find set differences ----------------------------------------- */
-    mark = internal::cs_wclear<Index>(mark, lemax, w, n);  /* clear w if necessary */
+    mark = internal::cs_wclear<StorageIndex>(mark, lemax, w, n);  /* clear w if necessary */
     for(pk = pk1; pk < pk2; pk++)    /* scan 1: find |Le\Lk| */
     {
       i = Ci[pk];
       if((eln = elen[i]) <= 0) continue;/* skip if elen[i] empty */
       nvi = -nv[i];                      /* nv[i] was negated */
@@ -319,24 +331,24 @@
         nv[i] = 0;
         elen[i] = -1;             /* node i is dead */
       }
       else
       {
-        degree[i] = std::min<Index> (degree[i], d);   /* update degree(i) */
+        degree[i] = std::min<StorageIndex> (degree[i], d);   /* update degree(i) */
         Ci[pn] = Ci[p3];         /* move first node to end */
         Ci[p3] = Ci[p1];         /* move 1st el. to end of Ei */
         Ci[p1] = k;               /* add k as 1st element in of Ei */
         len[i] = pn - p1 + 1;     /* new len of adj. list of node i */
         h %= n;                    /* finalize hash of i */
         next[i] = hhead[h];      /* place i in hash bucket */
         hhead[h] = i;
-        last[i] = h;              /* save hash of i in last[i] */
+        last[i] = h;      /* save hash of i in last[i] */
       }
     }                                   /* scan2 is done */
     degree[k] = dk;                   /* finalize |Lk| */
-    lemax = std::max<Index>(lemax, dk);
-    mark = internal::cs_wclear<Index>(mark+lemax, lemax, w, n);    /* clear w */
+    lemax = std::max<StorageIndex>(lemax, dk);
+    mark = internal::cs_wclear<StorageIndex>(mark+lemax, lemax, w, n);    /* clear w */
     
     /* --- Supernode detection ------------------------------------------ */
     for(pk = pk1; pk < pk2; pk++)
     {
       i = Ci[pk];
@@ -380,16 +392,16 @@
     {
       i = Ci[pk];
       if((nvi = -nv[i]) <= 0) continue;/* skip if i is dead */
       nv[i] = nvi;                      /* restore nv[i] */
       d = degree[i] + dk - nvi;         /* compute external degree(i) */
-      d = std::min<Index> (d, n - nel - nvi);
+      d = std::min<StorageIndex> (d, n - nel - nvi);
       if(head[d] != -1) last[head[d]] = i;
       next[i] = head[d];               /* put i back in degree list */
       last[i] = -1;
       head[d] = i;
-      mindeg = std::min<Index> (mindeg, d);       /* find new minimum degree */
+      mindeg = std::min<StorageIndex> (mindeg, d);       /* find new minimum degree */
       degree[i] = d;
       Ci[p++] = i;                      /* place i in Lk */
     }
     nv[k] = nvk;                      /* # nodes absorbed into k */
     if((len[k] = p-pk1) == 0)         /* length of adj list of element k*/
@@ -418,18 +430,16 @@
       head[Cp[e]] = e;
     }
   }
   for(k = 0, i = 0; i <= n; i++)       /* postorder the assembly tree */
   {
-    if(Cp[i] == -1) k = internal::cs_tdfs<Index>(i, k, head, next, perm.indices().data(), w);
+    if(Cp[i] == -1) k = internal::cs_tdfs<StorageIndex>(i, k, head, next, perm.indices().data(), w);
   }
   
   perm.indices().conservativeResize(n);
-
-  delete[] W;
 }
 
 } // namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSE_AMD_H

DELETED 3rd_party/eigen/Eigen/src/OrderingMethods/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/OrderingMethods/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/OrderingMethods/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/OrderingMethods/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_OrderingMethods_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_OrderingMethods_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/OrderingMethods COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/OrderingMethods/Eigen_Colamd.h
==================================================================
--- 3rd_party/eigen/Eigen/src/OrderingMethods/Eigen_Colamd.h
+++ 3rd_party/eigen/Eigen/src/OrderingMethods/Eigen_Colamd.h
@@ -39,16 +39,12 @@
 // 
 //     Availability:
 // 
 //   The colamd/symamd library is available at
 // 
-//       http://www.cise.ufl.edu/research/sparse/colamd/
+//       http://www.suitesparse.com
 
-//   This is the http://www.cise.ufl.edu/research/sparse/colamd/colamd.h
-//   file.  It is required by the colamd.c, colamdmex.c, and symamdmex.c
-//   files, and by any C code that calls the routines whose prototypes are
-//   listed below, or that uses the colamd/symamd definitions listed below.
   
 #ifndef EIGEN_COLAMD_H
 #define EIGEN_COLAMD_H
 
 namespace internal {
@@ -100,13 +96,10 @@
 
 /* ========================================================================== */
 /* === Definitions ========================================================== */
 /* ========================================================================== */
 
-#define COLAMD_MAX(a,b) (((a) > (b)) ? (a) : (b))
-#define COLAMD_MIN(a,b) (((a) < (b)) ? (a) : (b))
-
 #define ONES_COMPLEMENT(r) (-(r)-1)
 
 /* -------------------------------------------------------------------------- */
 
 #define COLAMD_EMPTY (-1)
@@ -133,58 +126,58 @@
 /* ========================================================================== */
 /* === Colamd reporting mechanism =========================================== */
 /* ========================================================================== */
 
 // == Row and Column structures ==
-template <typename Index>
+template <typename IndexType>
 struct colamd_col
 {
-  Index start ;   /* index for A of first row in this column, or DEAD */
+  IndexType start ;   /* index for A of first row in this column, or DEAD */
   /* if column is dead */
-  Index length ;  /* number of rows in this column */
+  IndexType length ;  /* number of rows in this column */
   union
   {
-    Index thickness ; /* number of original columns represented by this */
+    IndexType thickness ; /* number of original columns represented by this */
     /* col, if the column is alive */
-    Index parent ;  /* parent in parent tree super-column structure, if */
+    IndexType parent ;  /* parent in parent tree super-column structure, if */
     /* the column is dead */
   } shared1 ;
   union
   {
-    Index score ; /* the score used to maintain heap, if col is alive */
-    Index order ; /* pivot ordering of this column, if col is dead */
+    IndexType score ; /* the score used to maintain heap, if col is alive */
+    IndexType order ; /* pivot ordering of this column, if col is dead */
   } shared2 ;
   union
   {
-    Index headhash ;  /* head of a hash bucket, if col is at the head of */
+    IndexType headhash ;  /* head of a hash bucket, if col is at the head of */
     /* a degree list */
-    Index hash ;  /* hash value, if col is not in a degree list */
-    Index prev ;  /* previous column in degree list, if col is in a */
+    IndexType hash ;  /* hash value, if col is not in a degree list */
+    IndexType prev ;  /* previous column in degree list, if col is in a */
     /* degree list (but not at the head of a degree list) */
   } shared3 ;
   union
   {
-    Index degree_next ; /* next column, if col is in a degree list */
-    Index hash_next ;   /* next column, if col is in a hash list */
+    IndexType degree_next ; /* next column, if col is in a degree list */
+    IndexType hash_next ;   /* next column, if col is in a hash list */
   } shared4 ;
   
 };
  
-template <typename Index>
+template <typename IndexType>
 struct Colamd_Row
 {
-  Index start ;   /* index for A of first col in this row */
-  Index length ;  /* number of principal columns in this row */
+  IndexType start ;   /* index for A of first col in this row */
+  IndexType length ;  /* number of principal columns in this row */
   union
   {
-    Index degree ;  /* number of principal & non-principal columns in row */
-    Index p ;   /* used as a row pointer in init_rows_cols () */
+    IndexType degree ;  /* number of principal & non-principal columns in row */
+    IndexType p ;   /* used as a row pointer in init_rows_cols () */
   } shared1 ;
   union
   {
-    Index mark ;  /* for computing set differences and marking dead rows*/
-    Index first_column ;/* first column in row (used in garbage collection) */
+    IndexType mark ;  /* for computing set differences and marking dead rows*/
+    IndexType first_column ;/* first column in row (used in garbage collection) */
   } shared2 ;
   
 };
  
 /* ========================================================================== */
@@ -200,42 +193,42 @@
   colamd.  An additional n_col space is the minimal amount of "elbow room",
   and nnz/5 more space is recommended for run time efficiency.
   
   This macro is not needed when using symamd.
   
-  Explicit typecast to Index added Sept. 23, 2002, COLAMD version 2.2, to avoid
+  Explicit typecast to IndexType added Sept. 23, 2002, COLAMD version 2.2, to avoid
   gcc -pedantic warning messages.
 */
-template <typename Index>
-inline Index colamd_c(Index n_col) 
-{ return Index( ((n_col) + 1) * sizeof (colamd_col<Index>) / sizeof (Index) ) ; }
+template <typename IndexType>
+inline IndexType colamd_c(IndexType n_col) 
+{ return IndexType( ((n_col) + 1) * sizeof (colamd_col<IndexType>) / sizeof (IndexType) ) ; }
 
-template <typename Index>
-inline Index  colamd_r(Index n_row)
-{ return Index(((n_row) + 1) * sizeof (Colamd_Row<Index>) / sizeof (Index)); }
+template <typename IndexType>
+inline IndexType  colamd_r(IndexType n_row)
+{ return IndexType(((n_row) + 1) * sizeof (Colamd_Row<IndexType>) / sizeof (IndexType)); }
 
 // Prototypes of non-user callable routines
-template <typename Index>
-static Index init_rows_cols (Index n_row, Index n_col, Colamd_Row<Index> Row [], colamd_col<Index> col [], Index A [], Index p [], Index stats[COLAMD_STATS] ); 
-
-template <typename Index>
-static void init_scoring (Index n_row, Index n_col, Colamd_Row<Index> Row [], colamd_col<Index> Col [], Index A [], Index head [], double knobs[COLAMD_KNOBS], Index *p_n_row2, Index *p_n_col2, Index *p_max_deg);
-
-template <typename Index>
-static Index find_ordering (Index n_row, Index n_col, Index Alen, Colamd_Row<Index> Row [], colamd_col<Index> Col [], Index A [], Index head [], Index n_col2, Index max_deg, Index pfree);
-
-template <typename Index>
-static void order_children (Index n_col, colamd_col<Index> Col [], Index p []);
-
-template <typename Index>
-static void detect_super_cols (colamd_col<Index> Col [], Index A [], Index head [], Index row_start, Index row_length ) ;
-
-template <typename Index>
-static Index garbage_collection (Index n_row, Index n_col, Colamd_Row<Index> Row [], colamd_col<Index> Col [], Index A [], Index *pfree) ;
-
-template <typename Index>
-static inline  Index clear_mark (Index n_row, Colamd_Row<Index> Row [] ) ;
+template <typename IndexType>
+static IndexType init_rows_cols (IndexType n_row, IndexType n_col, Colamd_Row<IndexType> Row [], colamd_col<IndexType> col [], IndexType A [], IndexType p [], IndexType stats[COLAMD_STATS] ); 
+
+template <typename IndexType>
+static void init_scoring (IndexType n_row, IndexType n_col, Colamd_Row<IndexType> Row [], colamd_col<IndexType> Col [], IndexType A [], IndexType head [], double knobs[COLAMD_KNOBS], IndexType *p_n_row2, IndexType *p_n_col2, IndexType *p_max_deg);
+
+template <typename IndexType>
+static IndexType find_ordering (IndexType n_row, IndexType n_col, IndexType Alen, Colamd_Row<IndexType> Row [], colamd_col<IndexType> Col [], IndexType A [], IndexType head [], IndexType n_col2, IndexType max_deg, IndexType pfree);
+
+template <typename IndexType>
+static void order_children (IndexType n_col, colamd_col<IndexType> Col [], IndexType p []);
+
+template <typename IndexType>
+static void detect_super_cols (colamd_col<IndexType> Col [], IndexType A [], IndexType head [], IndexType row_start, IndexType row_length ) ;
+
+template <typename IndexType>
+static IndexType garbage_collection (IndexType n_row, IndexType n_col, Colamd_Row<IndexType> Row [], colamd_col<IndexType> Col [], IndexType A [], IndexType *pfree) ;
+
+template <typename IndexType>
+static inline  IndexType clear_mark (IndexType n_row, Colamd_Row<IndexType> Row [] ) ;
 
 /* === No debugging ========================================================= */
 
 #define COLAMD_DEBUG0(params) ;
 #define COLAMD_DEBUG1(params) ;
@@ -258,12 +251,12 @@
  * \param nnz nonzeros in A
  * \param n_row number of rows in A
  * \param n_col number of columns in A
  * \return recommended value of Alen for use by colamd
  */
-template <typename Index>
-inline Index colamd_recommended ( Index nnz, Index n_row, Index n_col)
+template <typename IndexType>
+inline IndexType colamd_recommended ( IndexType nnz, IndexType n_row, IndexType n_col)
 {
   if ((nnz) < 0 || (n_row) < 0 || (n_col) < 0)
     return (-1);
   else
     return (2 * (nnz) + colamd_c (n_col) + colamd_r (n_row) + (n_col) + ((nnz) / 5)); 
@@ -323,26 +316,26 @@
  * \param A row indices of the matrix, of size ALen
  * \param p column pointers of A, of size n_col+1
  * \param knobs parameter settings for colamd
  * \param stats colamd output statistics and error codes
  */
-template <typename Index>
-static bool colamd(Index n_row, Index n_col, Index Alen, Index *A, Index *p, double knobs[COLAMD_KNOBS], Index stats[COLAMD_STATS])
+template <typename IndexType>
+static bool colamd(IndexType n_row, IndexType n_col, IndexType Alen, IndexType *A, IndexType *p, double knobs[COLAMD_KNOBS], IndexType stats[COLAMD_STATS])
 {
   /* === Local variables ================================================== */
   
-  Index i ;     /* loop index */
-  Index nnz ;     /* nonzeros in A */
-  Index Row_size ;    /* size of Row [], in integers */
-  Index Col_size ;    /* size of Col [], in integers */
-  Index need ;      /* minimum required length of A */
-  Colamd_Row<Index> *Row ;   /* pointer into A of Row [0..n_row] array */
-  colamd_col<Index> *Col ;   /* pointer into A of Col [0..n_col] array */
-  Index n_col2 ;    /* number of non-dense, non-empty columns */
-  Index n_row2 ;    /* number of non-dense, non-empty rows */
-  Index ngarbage ;    /* number of garbage collections performed */
-  Index max_deg ;   /* maximum row degree */
+  IndexType i ;     /* loop index */
+  IndexType nnz ;     /* nonzeros in A */
+  IndexType Row_size ;    /* size of Row [], in integers */
+  IndexType Col_size ;    /* size of Col [], in integers */
+  IndexType need ;      /* minimum required length of A */
+  Colamd_Row<IndexType> *Row ;   /* pointer into A of Row [0..n_row] array */
+  colamd_col<IndexType> *Col ;   /* pointer into A of Col [0..n_col] array */
+  IndexType n_col2 ;    /* number of non-dense, non-empty columns */
+  IndexType n_row2 ;    /* number of non-dense, non-empty rows */
+  IndexType ngarbage ;    /* number of garbage collections performed */
+  IndexType max_deg ;   /* maximum row degree */
   double default_knobs [COLAMD_KNOBS] ; /* default knobs array */
   
   
   /* === Check the input arguments ======================================== */
   
@@ -429,12 +422,12 @@
     COLAMD_DEBUG0 (("colamd: Need Alen >= %d, given only Alen = %d\n", need,Alen));
     return (false) ;
   }
   
   Alen -= Col_size + Row_size ;
-  Col = (colamd_col<Index> *) &A [Alen] ;
-  Row = (Colamd_Row<Index> *) &A [Alen + Col_size] ;
+  Col = (colamd_col<IndexType> *) &A [Alen] ;
+  Row = (Colamd_Row<IndexType> *) &A [Alen + Col_size] ;
 
   /* === Construct the row and column data structures ===================== */
   
   if (!Eigen::internal::init_rows_cols (n_row, n_col, Row, Col, A, p, stats))
   {
@@ -483,42 +476,42 @@
   structs.  If the columns are un-sorted or contain duplicate row indices,
   this routine will also sort and remove duplicate row indices from the
   column form of the matrix.  Returns false if the matrix is invalid,
   true otherwise.  Not user-callable.
 */
-template <typename Index>
-static Index init_rows_cols  /* returns true if OK, or false otherwise */
+template <typename IndexType>
+static IndexType init_rows_cols  /* returns true if OK, or false otherwise */
   (
     /* === Parameters ======================================================= */
 
-    Index n_row,      /* number of rows of A */
-    Index n_col,      /* number of columns of A */
-    Colamd_Row<Index> Row [],    /* of size n_row+1 */
-    colamd_col<Index> Col [],    /* of size n_col+1 */
-    Index A [],     /* row indices of A, of size Alen */
-    Index p [],     /* pointers to columns in A, of size n_col+1 */
-    Index stats [COLAMD_STATS]  /* colamd statistics */ 
+    IndexType n_row,      /* number of rows of A */
+    IndexType n_col,      /* number of columns of A */
+    Colamd_Row<IndexType> Row [],    /* of size n_row+1 */
+    colamd_col<IndexType> Col [],    /* of size n_col+1 */
+    IndexType A [],     /* row indices of A, of size Alen */
+    IndexType p [],     /* pointers to columns in A, of size n_col+1 */
+    IndexType stats [COLAMD_STATS]  /* colamd statistics */ 
     )
 {
   /* === Local variables ================================================== */
 
-  Index col ;     /* a column index */
-  Index row ;     /* a row index */
-  Index *cp ;     /* a column pointer */
-  Index *cp_end ;   /* a pointer to the end of a column */
-  Index *rp ;     /* a row pointer */
-  Index *rp_end ;   /* a pointer to the end of a row */
-  Index last_row ;    /* previous row */
+  IndexType col ;     /* a column index */
+  IndexType row ;     /* a row index */
+  IndexType *cp ;     /* a column pointer */
+  IndexType *cp_end ;   /* a pointer to the end of a column */
+  IndexType *rp ;     /* a row pointer */
+  IndexType *rp_end ;   /* a pointer to the end of a row */
+  IndexType last_row ;    /* previous row */
 
   /* === Initialize columns, and check column pointers ==================== */
 
   for (col = 0 ; col < n_col ; col++)
   {
     Col [col].start = p [col] ;
     Col [col].length = p [col+1] - p [col] ;
 
-    if (Col [col].length < 0)
+    if ((Col [col].length) < 0) // extra parentheses to work-around gcc bug 10200
     {
       /* column pointers must be non-decreasing */
       stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ;
       stats [COLAMD_INFO1] = col ;
       stats [COLAMD_INFO2] = Col [col].length ;
@@ -699,50 +692,50 @@
 
 /*
   Kills dense or empty columns and rows, calculates an initial score for
   each column, and places all columns in the degree lists.  Not user-callable.
 */
-template <typename Index>
+template <typename IndexType>
 static void init_scoring
   (
     /* === Parameters ======================================================= */
 
-    Index n_row,      /* number of rows of A */
-    Index n_col,      /* number of columns of A */
-    Colamd_Row<Index> Row [],    /* of size n_row+1 */
-    colamd_col<Index> Col [],    /* of size n_col+1 */
-    Index A [],     /* column form and row form of A */
-    Index head [],    /* of size n_col+1 */
+    IndexType n_row,      /* number of rows of A */
+    IndexType n_col,      /* number of columns of A */
+    Colamd_Row<IndexType> Row [],    /* of size n_row+1 */
+    colamd_col<IndexType> Col [],    /* of size n_col+1 */
+    IndexType A [],     /* column form and row form of A */
+    IndexType head [],    /* of size n_col+1 */
     double knobs [COLAMD_KNOBS],/* parameters */
-    Index *p_n_row2,    /* number of non-dense, non-empty rows */
-    Index *p_n_col2,    /* number of non-dense, non-empty columns */
-    Index *p_max_deg    /* maximum row degree */
+    IndexType *p_n_row2,    /* number of non-dense, non-empty rows */
+    IndexType *p_n_col2,    /* number of non-dense, non-empty columns */
+    IndexType *p_max_deg    /* maximum row degree */
     )
 {
   /* === Local variables ================================================== */
 
-  Index c ;     /* a column index */
-  Index r, row ;    /* a row index */
-  Index *cp ;     /* a column pointer */
-  Index deg ;     /* degree of a row or column */
-  Index *cp_end ;   /* a pointer to the end of a column */
-  Index *new_cp ;   /* new column pointer */
-  Index col_length ;    /* length of pruned column */
-  Index score ;     /* current column score */
-  Index n_col2 ;    /* number of non-dense, non-empty columns */
-  Index n_row2 ;    /* number of non-dense, non-empty rows */
-  Index dense_row_count ; /* remove rows with more entries than this */
-  Index dense_col_count ; /* remove cols with more entries than this */
-  Index min_score ;   /* smallest column score */
-  Index max_deg ;   /* maximum row degree */
-  Index next_col ;    /* Used to add to degree list.*/
+  IndexType c ;     /* a column index */
+  IndexType r, row ;    /* a row index */
+  IndexType *cp ;     /* a column pointer */
+  IndexType deg ;     /* degree of a row or column */
+  IndexType *cp_end ;   /* a pointer to the end of a column */
+  IndexType *new_cp ;   /* new column pointer */
+  IndexType col_length ;    /* length of pruned column */
+  IndexType score ;     /* current column score */
+  IndexType n_col2 ;    /* number of non-dense, non-empty columns */
+  IndexType n_row2 ;    /* number of non-dense, non-empty rows */
+  IndexType dense_row_count ; /* remove rows with more entries than this */
+  IndexType dense_col_count ; /* remove cols with more entries than this */
+  IndexType min_score ;   /* smallest column score */
+  IndexType max_deg ;   /* maximum row degree */
+  IndexType next_col ;    /* Used to add to degree list.*/
 
 
   /* === Extract knobs ==================================================== */
 
-  dense_row_count = COLAMD_MAX (0, COLAMD_MIN (knobs [COLAMD_DENSE_ROW] * n_col, n_col)) ;
-  dense_col_count = COLAMD_MAX (0, COLAMD_MIN (knobs [COLAMD_DENSE_COL] * n_row, n_row)) ;
+  dense_row_count = numext::maxi(IndexType(0), numext::mini(IndexType(knobs [COLAMD_DENSE_ROW] * n_col), n_col)) ;
+  dense_col_count = numext::maxi(IndexType(0), numext::mini(IndexType(knobs [COLAMD_DENSE_COL] * n_row), n_row)) ;
   COLAMD_DEBUG1 (("colamd: densecount: %d %d\n", dense_row_count, dense_col_count)) ;
   max_deg = 0 ;
   n_col2 = n_col ;
   n_row2 = n_row ;
 
@@ -802,11 +795,11 @@
       --n_row2 ;
     }
     else
     {
       /* keep track of max degree of remaining rows */
-      max_deg = COLAMD_MAX (max_deg, deg) ;
+      max_deg = numext::maxi(max_deg, deg) ;
     }
   }
   COLAMD_DEBUG1 (("colamd: Dense and null rows killed: %d\n", n_row - n_row2)) ;
 
   /* === Compute initial column scores ==================================== */
@@ -840,14 +833,14 @@
       /* compact the column */
       *new_cp++ = row ;
       /* add row's external degree */
       score += Row [row].shared1.degree - 1 ;
       /* guard against integer overflow */
-      score = COLAMD_MIN (score, n_col) ;
+      score = numext::mini(score, n_col) ;
     }
     /* determine pruned column length */
-    col_length = (Index) (new_cp - &A [Col [c].start]) ;
+    col_length = (IndexType) (new_cp - &A [Col [c].start]) ;
     if (col_length == 0)
     {
       /* a newly-made null column (all rows in this col are "dense" */
       /* and have already been killed) */
       COLAMD_DEBUG2 (("Newly null killed: %d\n", c)) ;
@@ -912,11 +905,11 @@
 	Col [next_col].shared3.prev = c ;
       }
       head [score] = c ;
 
       /* see if this score is less than current min */
-      min_score = COLAMD_MIN (min_score, score) ;
+      min_score = numext::mini(min_score, score) ;
 
 
     }
   }
 
@@ -936,60 +929,60 @@
 /*
   Order the principal columns of the supercolumn form of the matrix
   (no supercolumns on input).  Uses a minimum approximate column minimum
   degree ordering method.  Not user-callable.
 */
-template <typename Index>
-static Index find_ordering /* return the number of garbage collections */
+template <typename IndexType>
+static IndexType find_ordering /* return the number of garbage collections */
   (
     /* === Parameters ======================================================= */
 
-    Index n_row,      /* number of rows of A */
-    Index n_col,      /* number of columns of A */
-    Index Alen,     /* size of A, 2*nnz + n_col or larger */
-    Colamd_Row<Index> Row [],    /* of size n_row+1 */
-    colamd_col<Index> Col [],    /* of size n_col+1 */
-    Index A [],     /* column form and row form of A */
-    Index head [],    /* of size n_col+1 */
-    Index n_col2,     /* Remaining columns to order */
-    Index max_deg,    /* Maximum row degree */
-    Index pfree     /* index of first free slot (2*nnz on entry) */
+    IndexType n_row,      /* number of rows of A */
+    IndexType n_col,      /* number of columns of A */
+    IndexType Alen,     /* size of A, 2*nnz + n_col or larger */
+    Colamd_Row<IndexType> Row [],    /* of size n_row+1 */
+    colamd_col<IndexType> Col [],    /* of size n_col+1 */
+    IndexType A [],     /* column form and row form of A */
+    IndexType head [],    /* of size n_col+1 */
+    IndexType n_col2,     /* Remaining columns to order */
+    IndexType max_deg,    /* Maximum row degree */
+    IndexType pfree     /* index of first free slot (2*nnz on entry) */
     )
 {
   /* === Local variables ================================================== */
 
-  Index k ;     /* current pivot ordering step */
-  Index pivot_col ;   /* current pivot column */
-  Index *cp ;     /* a column pointer */
-  Index *rp ;     /* a row pointer */
-  Index pivot_row ;   /* current pivot row */
-  Index *new_cp ;   /* modified column pointer */
-  Index *new_rp ;   /* modified row pointer */
-  Index pivot_row_start ; /* pointer to start of pivot row */
-  Index pivot_row_degree ;  /* number of columns in pivot row */
-  Index pivot_row_length ;  /* number of supercolumns in pivot row */
-  Index pivot_col_score ; /* score of pivot column */
-  Index needed_memory ;   /* free space needed for pivot row */
-  Index *cp_end ;   /* pointer to the end of a column */
-  Index *rp_end ;   /* pointer to the end of a row */
-  Index row ;     /* a row index */
-  Index col ;     /* a column index */
-  Index max_score ;   /* maximum possible score */
-  Index cur_score ;   /* score of current column */
+  IndexType k ;     /* current pivot ordering step */
+  IndexType pivot_col ;   /* current pivot column */
+  IndexType *cp ;     /* a column pointer */
+  IndexType *rp ;     /* a row pointer */
+  IndexType pivot_row ;   /* current pivot row */
+  IndexType *new_cp ;   /* modified column pointer */
+  IndexType *new_rp ;   /* modified row pointer */
+  IndexType pivot_row_start ; /* pointer to start of pivot row */
+  IndexType pivot_row_degree ;  /* number of columns in pivot row */
+  IndexType pivot_row_length ;  /* number of supercolumns in pivot row */
+  IndexType pivot_col_score ; /* score of pivot column */
+  IndexType needed_memory ;   /* free space needed for pivot row */
+  IndexType *cp_end ;   /* pointer to the end of a column */
+  IndexType *rp_end ;   /* pointer to the end of a row */
+  IndexType row ;     /* a row index */
+  IndexType col ;     /* a column index */
+  IndexType max_score ;   /* maximum possible score */
+  IndexType cur_score ;   /* score of current column */
   unsigned int hash ;   /* hash value for supernode detection */
-  Index head_column ;   /* head of hash bucket */
-  Index first_col ;   /* first column in hash bucket */
-  Index tag_mark ;    /* marker value for mark array */
-  Index row_mark ;    /* Row [row].shared2.mark */
-  Index set_difference ;  /* set difference size of row with pivot row */
-  Index min_score ;   /* smallest column score */
-  Index col_thickness ;   /* "thickness" (no. of columns in a supercol) */
-  Index max_mark ;    /* maximum value of tag_mark */
-  Index pivot_col_thickness ; /* number of columns represented by pivot col */
-  Index prev_col ;    /* Used by Dlist operations. */
-  Index next_col ;    /* Used by Dlist operations. */
-  Index ngarbage ;    /* number of garbage collections performed */
+  IndexType head_column ;   /* head of hash bucket */
+  IndexType first_col ;   /* first column in hash bucket */
+  IndexType tag_mark ;    /* marker value for mark array */
+  IndexType row_mark ;    /* Row [row].shared2.mark */
+  IndexType set_difference ;  /* set difference size of row with pivot row */
+  IndexType min_score ;   /* smallest column score */
+  IndexType col_thickness ;   /* "thickness" (no. of columns in a supercol) */
+  IndexType max_mark ;    /* maximum value of tag_mark */
+  IndexType pivot_col_thickness ; /* number of columns represented by pivot col */
+  IndexType prev_col ;    /* Used by Dlist operations. */
+  IndexType next_col ;    /* Used by Dlist operations. */
+  IndexType ngarbage ;    /* number of garbage collections performed */
 
 
   /* === Initialization and clear mark ==================================== */
 
   max_mark = INT_MAX - n_col ;  /* INT_MAX defined in <limits.h> */
@@ -1009,11 +1002,11 @@
     COLAMD_ASSERT (min_score >= 0) ;
     COLAMD_ASSERT (min_score <= n_col) ;
     COLAMD_ASSERT (head [min_score] >= COLAMD_EMPTY) ;
 
     /* get pivot column from head of minimum degree list */
-    while (head [min_score] == COLAMD_EMPTY && min_score < n_col)
+    while (min_score < n_col && head [min_score] == COLAMD_EMPTY)
     {
       min_score++ ;
     }
     pivot_col = head [min_score] ;
     COLAMD_ASSERT (pivot_col >= 0 && pivot_col <= n_col) ;
@@ -1038,11 +1031,11 @@
     k += pivot_col_thickness ;
     COLAMD_ASSERT (pivot_col_thickness > 0) ;
 
     /* === Garbage_collection, if necessary ============================= */
 
-    needed_memory = COLAMD_MIN (pivot_col_score, n_col - k) ;
+    needed_memory = numext::mini(pivot_col_score, n_col - k) ;
     if (pfree + needed_memory >= Alen)
     {
       pfree = Eigen::internal::garbage_collection (n_row, n_col, Row, Col, A, &A [pfree]) ;
       ngarbage++ ;
       /* after garbage collection we will have enough */
@@ -1097,11 +1090,11 @@
       }
     }
 
     /* clear tag on pivot column */
     Col [pivot_col].shared1.thickness = pivot_col_thickness ;
-    max_deg = COLAMD_MAX (max_deg, pivot_row_degree) ;
+    max_deg = numext::maxi(max_deg, pivot_row_degree) ;
 
 
     /* === Kill all rows used to construct pivot row ==================== */
 
     /* also kill pivot row, temporarily */
@@ -1271,15 +1264,15 @@
 	/* compute hash function */
 	hash += row ;
 	/* add set difference */
 	cur_score += row_mark - tag_mark ;
 	/* integer overflow... */
-	cur_score = COLAMD_MIN (cur_score, n_col) ;
+	cur_score = numext::mini(cur_score, n_col) ;
       }
 
       /* recompute the column's length */
-      Col [col].length = (Index) (new_cp - &A [Col [col].start]) ;
+      Col [col].length = (IndexType) (new_cp - &A [Col [col].start]) ;
 
       /* === Further mass elimination ================================= */
 
       if (Col [col].length == 0)
       {
@@ -1323,11 +1316,11 @@
 	  head [hash] = - (col + 2) ;
 	}
 	Col [col].shared4.hash_next = first_col ;
 
 	/* save hash function in Col [col].shared3.hash */
-	Col [col].shared3.hash = (Index) hash ;
+	Col [col].shared3.hash = (IndexType) hash ;
 	COLAMD_ASSERT (COL_IS_ALIVE (col)) ;
       }
     }
 
     /* The approximate external column degree is now computed.  */
@@ -1384,11 +1377,11 @@
 
       /* make the score the external degree of the union-of-rows */
       cur_score -= Col [col].shared1.thickness ;
 
       /* make sure score is less or equal than the max score */
-      cur_score = COLAMD_MIN (cur_score, max_score) ;
+      cur_score = numext::mini(cur_score, max_score) ;
       COLAMD_ASSERT (cur_score >= 0) ;
 
       /* store updated score */
       Col [col].shared2.score = cur_score ;
 
@@ -1407,11 +1400,11 @@
 	Col [next_col].shared3.prev = col ;
       }
       head [cur_score] = col ;
 
       /* see if this score is less than current min */
-      min_score = COLAMD_MIN (min_score, cur_score) ;
+      min_score = numext::mini(min_score, cur_score) ;
 
     }
 
     /* === Resurrect the new pivot row ================================== */
 
@@ -1418,11 +1411,11 @@
     if (pivot_row_degree > 0)
     {
       /* update pivot row length to reflect any cols that were killed */
       /* during super-col detection and mass elimination */
       Row [pivot_row].start  = pivot_row_start ;
-      Row [pivot_row].length = (Index) (new_rp - &A[pivot_row_start]) ;
+      Row [pivot_row].length = (IndexType) (new_rp - &A[pivot_row_start]) ;
       Row [pivot_row].shared1.degree = pivot_row_degree ;
       Row [pivot_row].shared2.mark = 0 ;
       /* pivot row is no longer dead */
     }
   }
@@ -1447,26 +1440,26 @@
   like it at first glance, but be assured that this routine takes time linear
   in the number of columns.  Although not immediately obvious, the time
   taken by this routine is O (n_col), that is, linear in the number of
   columns.  Not user-callable.
 */
-template <typename Index>
+template <typename IndexType>
 static inline  void order_children
 (
   /* === Parameters ======================================================= */
 
-  Index n_col,      /* number of columns of A */
-  colamd_col<Index> Col [],    /* of size n_col+1 */
-  Index p []      /* p [0 ... n_col-1] is the column permutation*/
+  IndexType n_col,      /* number of columns of A */
+  colamd_col<IndexType> Col [],    /* of size n_col+1 */
+  IndexType p []      /* p [0 ... n_col-1] is the column permutation*/
   )
 {
   /* === Local variables ================================================== */
 
-  Index i ;     /* loop counter for all columns */
-  Index c ;     /* column index */
-  Index parent ;    /* index of column's parent */
-  Index order ;     /* column's order */
+  IndexType i ;     /* loop counter for all columns */
+  IndexType c ;     /* column index */
+  IndexType parent ;    /* index of column's parent */
+  IndexType order ;     /* column's order */
 
   /* === Order each non-principal column ================================== */
 
   for (i = 0 ; i < n_col ; i++)
   {
@@ -1548,37 +1541,37 @@
   Assuming no, or "few" hash collisions, the time taken by this routine is
   linear in the sum of the sizes (lengths) of each column whose score has
   just been computed in the approximate degree computation.
   Not user-callable.
 */
-template <typename Index>
+template <typename IndexType>
 static void detect_super_cols
 (
   /* === Parameters ======================================================= */
   
-  colamd_col<Index> Col [],    /* of size n_col+1 */
-  Index A [],     /* row indices of A */
-  Index head [],    /* head of degree lists and hash buckets */
-  Index row_start,    /* pointer to set of columns to check */
-  Index row_length    /* number of columns to check */
+  colamd_col<IndexType> Col [],    /* of size n_col+1 */
+  IndexType A [],     /* row indices of A */
+  IndexType head [],    /* head of degree lists and hash buckets */
+  IndexType row_start,    /* pointer to set of columns to check */
+  IndexType row_length    /* number of columns to check */
 )
 {
   /* === Local variables ================================================== */
 
-  Index hash ;      /* hash value for a column */
-  Index *rp ;     /* pointer to a row */
-  Index c ;     /* a column index */
-  Index super_c ;   /* column index of the column to absorb into */
-  Index *cp1 ;      /* column pointer for column super_c */
-  Index *cp2 ;      /* column pointer for column c */
-  Index length ;    /* length of column super_c */
-  Index prev_c ;    /* column preceding c in hash bucket */
-  Index i ;     /* loop counter */
-  Index *rp_end ;   /* pointer to the end of the row */
-  Index col ;     /* a column index in the row to check */
-  Index head_column ;   /* first column in hash bucket or degree list */
-  Index first_col ;   /* first column in hash bucket */
+  IndexType hash ;      /* hash value for a column */
+  IndexType *rp ;     /* pointer to a row */
+  IndexType c ;     /* a column index */
+  IndexType super_c ;   /* column index of the column to absorb into */
+  IndexType *cp1 ;      /* column pointer for column super_c */
+  IndexType *cp2 ;      /* column pointer for column c */
+  IndexType length ;    /* length of column super_c */
+  IndexType prev_c ;    /* column preceding c in hash bucket */
+  IndexType i ;     /* loop counter */
+  IndexType *rp_end ;   /* pointer to the end of the row */
+  IndexType col ;     /* a column index in the row to check */
+  IndexType head_column ;   /* first column in hash bucket or degree list */
+  IndexType first_col ;   /* first column in hash bucket */
 
   /* === Consider each column in the row ================================== */
 
   rp = &A [row_start] ;
   rp_end = rp + row_length ;
@@ -1699,31 +1692,31 @@
   the index of the first free position in A, after garbage collection.  The
   time taken by this routine is linear is the size of the array A, which is
   itself linear in the number of nonzeros in the input matrix.
   Not user-callable.
 */
-template <typename Index>
-static Index garbage_collection  /* returns the new value of pfree */
+template <typename IndexType>
+static IndexType garbage_collection  /* returns the new value of pfree */
   (
     /* === Parameters ======================================================= */
     
-    Index n_row,      /* number of rows */
-    Index n_col,      /* number of columns */
-    Colamd_Row<Index> Row [],    /* row info */
-    colamd_col<Index> Col [],    /* column info */
-    Index A [],     /* A [0 ... Alen-1] holds the matrix */
-    Index *pfree      /* &A [0] ... pfree is in use */
+    IndexType n_row,      /* number of rows */
+    IndexType n_col,      /* number of columns */
+    Colamd_Row<IndexType> Row [],    /* row info */
+    colamd_col<IndexType> Col [],    /* column info */
+    IndexType A [],     /* A [0 ... Alen-1] holds the matrix */
+    IndexType *pfree      /* &A [0] ... pfree is in use */
     )
 {
   /* === Local variables ================================================== */
 
-  Index *psrc ;     /* source pointer */
-  Index *pdest ;    /* destination pointer */
-  Index j ;     /* counter */
-  Index r ;     /* a row index */
-  Index c ;     /* a column index */
-  Index length ;    /* length of a row or column */
+  IndexType *psrc ;     /* source pointer */
+  IndexType *pdest ;    /* destination pointer */
+  IndexType j ;     /* counter */
+  IndexType r ;     /* a row index */
+  IndexType c ;     /* a column index */
+  IndexType length ;    /* length of a row or column */
 
   /* === Defragment the columns =========================================== */
 
   pdest = &A[0] ;
   for (c = 0 ; c < n_col ; c++)
@@ -1732,21 +1725,21 @@
     {
       psrc = &A [Col [c].start] ;
 
       /* move and compact the column */
       COLAMD_ASSERT (pdest <= psrc) ;
-      Col [c].start = (Index) (pdest - &A [0]) ;
+      Col [c].start = (IndexType) (pdest - &A [0]) ;
       length = Col [c].length ;
       for (j = 0 ; j < length ; j++)
       {
 	r = *psrc++ ;
 	if (ROW_IS_ALIVE (r))
 	{
 	  *pdest++ = r ;
 	}
       }
-      Col [c].length = (Index) (pdest - &A [Col [c].start]) ;
+      Col [c].length = (IndexType) (pdest - &A [Col [c].start]) ;
     }
   }
 
   /* === Prepare to defragment the rows =================================== */
 
@@ -1789,30 +1782,30 @@
       *psrc = Row [r].shared2.first_column ;
       COLAMD_ASSERT (ROW_IS_ALIVE (r)) ;
 
       /* move and compact the row */
       COLAMD_ASSERT (pdest <= psrc) ;
-      Row [r].start = (Index) (pdest - &A [0]) ;
+      Row [r].start = (IndexType) (pdest - &A [0]) ;
       length = Row [r].length ;
       for (j = 0 ; j < length ; j++)
       {
 	c = *psrc++ ;
 	if (COL_IS_ALIVE (c))
 	{
 	  *pdest++ = c ;
 	}
       }
-      Row [r].length = (Index) (pdest - &A [Row [r].start]) ;
+      Row [r].length = (IndexType) (pdest - &A [Row [r].start]) ;
 
     }
   }
   /* ensure we found all the rows */
   COLAMD_ASSERT (debug_rows == 0) ;
 
   /* === Return the new value of pfree ==================================== */
 
-  return ((Index) (pdest - &A [0])) ;
+  return ((IndexType) (pdest - &A [0])) ;
 }
 
 
 /* ========================================================================== */
 /* === clear_mark =========================================================== */
@@ -1820,22 +1813,22 @@
 
 /*
   Clears the Row [].shared2.mark array, and returns the new tag_mark.
   Return value is the new tag_mark.  Not user-callable.
 */
-template <typename Index>
-static inline  Index clear_mark  /* return the new value for tag_mark */
+template <typename IndexType>
+static inline  IndexType clear_mark  /* return the new value for tag_mark */
   (
       /* === Parameters ======================================================= */
 
-    Index n_row,    /* number of rows in A */
-    Colamd_Row<Index> Row [] /* Row [0 ... n_row-1].shared2.mark is set to zero */
+    IndexType n_row,    /* number of rows in A */
+    Colamd_Row<IndexType> Row [] /* Row [0 ... n_row-1].shared2.mark is set to zero */
     )
 {
   /* === Local variables ================================================== */
 
-  Index r ;
+  IndexType r ;
 
   for (r = 0 ; r < n_row ; r++)
   {
     if (ROW_IS_ALIVE (r))
     {

Index: 3rd_party/eigen/Eigen/src/OrderingMethods/Ordering.h
==================================================================
--- 3rd_party/eigen/Eigen/src/OrderingMethods/Ordering.h
+++ 3rd_party/eigen/Eigen/src/OrderingMethods/Ordering.h
@@ -17,24 +17,25 @@
 
 namespace internal {
     
 /** \internal
   * \ingroup OrderingMethods_Module
-  * \returns the symmetric pattern A^T+A from the input matrix A. 
+  * \param[in] A the input non-symmetric matrix
+  * \param[out] symmat the symmetric pattern A^T+A from the input matrix \a A.
   * FIXME: The values should not be considered here
   */
 template<typename MatrixType> 
-void ordering_helper_at_plus_a(const MatrixType& mat, MatrixType& symmat)
+void ordering_helper_at_plus_a(const MatrixType& A, MatrixType& symmat)
 {
   MatrixType C;
-  C = mat.transpose(); // NOTE: Could be  costly
+  C = A.transpose(); // NOTE: Could be  costly
   for (int i = 0; i < C.rows(); i++) 
   {
       for (typename MatrixType::InnerIterator it(C, i); it; ++it)
         it.valueRef() = 0.0;
   }
-  symmat = C + mat; 
+  symmat = C + A;
 }
     
 }
 
 #ifndef EIGEN_MPL2_ONLY
@@ -42,27 +43,27 @@
 /** \ingroup OrderingMethods_Module
   * \class AMDOrdering
   *
   * Functor computing the \em approximate \em minimum \em degree ordering
   * If the matrix is not structurally symmetric, an ordering of A^T+A is computed
-  * \tparam  Index The type of indices of the matrix 
+  * \tparam  StorageIndex The type of indices of the matrix 
   * \sa COLAMDOrdering
   */
-template <typename Index>
+template <typename StorageIndex>
 class AMDOrdering
 {
   public:
-    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+    typedef PermutationMatrix<Dynamic, Dynamic, StorageIndex> PermutationType;
     
     /** Compute the permutation vector from a sparse matrix
      * This routine is much faster if the input matrix is column-major     
      */
     template <typename MatrixType>
     void operator()(const MatrixType& mat, PermutationType& perm)
     {
       // Compute the symmetric pattern
-      SparseMatrix<typename MatrixType::Scalar, ColMajor, Index> symm;
+      SparseMatrix<typename MatrixType::Scalar, ColMajor, StorageIndex> symm;
       internal::ordering_helper_at_plus_a(mat,symm); 
     
       // Call the AMD routine 
       //m_mat.prune(keep_diag());
       internal::minimum_degree_ordering(symm, perm);
@@ -70,11 +71,11 @@
     
     /** Compute the permutation with a selfadjoint matrix */
     template <typename SrcType, unsigned int SrcUpLo> 
     void operator()(const SparseSelfAdjointView<SrcType, SrcUpLo>& mat, PermutationType& perm)
     { 
-      SparseMatrix<typename SrcType::Scalar, ColMajor, Index> C; C = mat;
+      SparseMatrix<typename SrcType::Scalar, ColMajor, StorageIndex> C; C = mat;
       
       // Call the AMD routine 
       // m_mat.prune(keep_diag()); //Remove the diagonal elements 
       internal::minimum_degree_ordering(C, perm);
     }
@@ -86,17 +87,17 @@
   * \class NaturalOrdering
   *
   * Functor computing the natural ordering (identity)
   * 
   * \note Returns an empty permutation matrix
-  * \tparam  Index The type of indices of the matrix 
+  * \tparam  StorageIndex The type of indices of the matrix 
   */
-template <typename Index>
+template <typename StorageIndex>
 class NaturalOrdering
 {
   public:
-    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+    typedef PermutationMatrix<Dynamic, Dynamic, StorageIndex> PermutationType;
     
     /** Compute the permutation vector from a column-major sparse matrix */
     template <typename MatrixType>
     void operator()(const MatrixType& /*mat*/, PermutationType& perm)
     {
@@ -106,49 +107,51 @@
 };
 
 /** \ingroup OrderingMethods_Module
   * \class COLAMDOrdering
   *
+  * \tparam  StorageIndex The type of indices of the matrix 
+  * 
   * Functor computing the \em column \em approximate \em minimum \em degree ordering 
   * The matrix should be in column-major and \b compressed format (see SparseMatrix::makeCompressed()).
   */
-template<typename Index>
+template<typename StorageIndex>
 class COLAMDOrdering
 {
   public:
-    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType; 
-    typedef Matrix<Index, Dynamic, 1> IndexVector;
+    typedef PermutationMatrix<Dynamic, Dynamic, StorageIndex> PermutationType; 
+    typedef Matrix<StorageIndex, Dynamic, 1> IndexVector;
     
     /** Compute the permutation vector \a perm form the sparse matrix \a mat
       * \warning The input sparse matrix \a mat must be in compressed mode (see SparseMatrix::makeCompressed()).
       */
     template <typename MatrixType>
     void operator() (const MatrixType& mat, PermutationType& perm)
     {
       eigen_assert(mat.isCompressed() && "COLAMDOrdering requires a sparse matrix in compressed mode. Call .makeCompressed() before passing it to COLAMDOrdering");
       
-      Index m = mat.rows();
-      Index n = mat.cols();
-      Index nnz = mat.nonZeros();
+      StorageIndex m = StorageIndex(mat.rows());
+      StorageIndex n = StorageIndex(mat.cols());
+      StorageIndex nnz = StorageIndex(mat.nonZeros());
       // Get the recommended value of Alen to be used by colamd
-      Index Alen = internal::colamd_recommended(nnz, m, n); 
+      StorageIndex Alen = internal::colamd_recommended(nnz, m, n); 
       // Set the default parameters
       double knobs [COLAMD_KNOBS]; 
-      Index stats [COLAMD_STATS];
+      StorageIndex stats [COLAMD_STATS];
       internal::colamd_set_defaults(knobs);
       
       IndexVector p(n+1), A(Alen); 
-      for(Index i=0; i <= n; i++)   p(i) = mat.outerIndexPtr()[i];
-      for(Index i=0; i < nnz; i++)  A(i) = mat.innerIndexPtr()[i];
+      for(StorageIndex i=0; i <= n; i++)   p(i) = mat.outerIndexPtr()[i];
+      for(StorageIndex i=0; i < nnz; i++)  A(i) = mat.innerIndexPtr()[i];
       // Call Colamd routine to compute the ordering 
-      Index info = internal::colamd(m, n, Alen, A.data(), p.data(), knobs, stats); 
+      StorageIndex info = internal::colamd(m, n, Alen, A.data(), p.data(), knobs, stats); 
       EIGEN_UNUSED_VARIABLE(info);
       eigen_assert( info && "COLAMD failed " );
       
       perm.resize(n);
-      for (Index i = 0; i < n; i++) perm.indices()(p(i)) = i;
+      for (StorageIndex i = 0; i < n; i++) perm.indices()(p(i)) = i;
     }
 };
 
 } // end namespace Eigen
 
 #endif

DELETED 3rd_party/eigen/Eigen/src/PaStiXSupport/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/PaStiXSupport/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/PaStiXSupport/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/PaStiXSupport/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_PastixSupport_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_PastixSupport_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/PaStiXSupport COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h
==================================================================
--- 3rd_party/eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h
+++ 3rd_party/eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h
@@ -9,10 +9,18 @@
 
 #ifndef EIGEN_PASTIXSUPPORT_H
 #define EIGEN_PASTIXSUPPORT_H
 
 namespace Eigen { 
+
+#if defined(DCOMPLEX)
+  #define PASTIX_COMPLEX  COMPLEX
+  #define PASTIX_DCOMPLEX DCOMPLEX
+#else
+  #define PASTIX_COMPLEX  std::complex<float>
+  #define PASTIX_DCOMPLEX std::complex<double>
+#endif
 
 /** \ingroup PaStiXSupport_Module
   * \brief Interface to the PaStix solver
   * 
   * This class is used to solve the linear systems A.X = B via the PaStix library. 
@@ -33,29 +41,29 @@
   struct pastix_traits< PastixLU<_MatrixType> >
   {
     typedef _MatrixType MatrixType;
     typedef typename _MatrixType::Scalar Scalar;
     typedef typename _MatrixType::RealScalar RealScalar;
-    typedef typename _MatrixType::Index Index;
+    typedef typename _MatrixType::StorageIndex StorageIndex;
   };
 
   template<typename _MatrixType, int Options>
   struct pastix_traits< PastixLLT<_MatrixType,Options> >
   {
     typedef _MatrixType MatrixType;
     typedef typename _MatrixType::Scalar Scalar;
     typedef typename _MatrixType::RealScalar RealScalar;
-    typedef typename _MatrixType::Index Index;
+    typedef typename _MatrixType::StorageIndex StorageIndex;
   };
 
   template<typename _MatrixType, int Options>
   struct pastix_traits< PastixLDLT<_MatrixType,Options> >
   {
     typedef _MatrixType MatrixType;
     typedef typename _MatrixType::Scalar Scalar;
     typedef typename _MatrixType::RealScalar RealScalar;
-    typedef typename _MatrixType::Index Index;
+    typedef typename _MatrixType::StorageIndex StorageIndex;
   };
   
   void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, float *vals, int *perm, int * invp, float *x, int nbrhs, int *iparm, double *dparm)
   {
     if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; }
@@ -72,18 +80,18 @@
   
   void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex<float> *vals, int *perm, int * invp, std::complex<float> *x, int nbrhs, int *iparm, double *dparm)
   {
     if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; }
     if (nbrhs == 0) {x = NULL; nbrhs=1;}
-    c_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast<COMPLEX*>(vals), perm, invp, reinterpret_cast<COMPLEX*>(x), nbrhs, iparm, dparm); 
+    c_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast<PASTIX_COMPLEX*>(vals), perm, invp, reinterpret_cast<PASTIX_COMPLEX*>(x), nbrhs, iparm, dparm); 
   }
   
   void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex<double> *vals, int *perm, int * invp, std::complex<double> *x, int nbrhs, int *iparm, double *dparm)
   {
     if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; }
     if (nbrhs == 0) {x = NULL; nbrhs=1;}
-    z_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast<DCOMPLEX*>(vals), perm, invp, reinterpret_cast<DCOMPLEX*>(x), nbrhs, iparm, dparm); 
+    z_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast<PASTIX_DCOMPLEX*>(vals), perm, invp, reinterpret_cast<PASTIX_DCOMPLEX*>(x), nbrhs, iparm, dparm); 
   }
 
   // Convert the matrix  to Fortran-style Numbering
   template <typename MatrixType>
   void c_to_fortran_numbering (MatrixType& mat)
@@ -115,65 +123,52 @@
 }
 
 // This is the base class to interface with PaStiX functions. 
 // Users should not used this class directly. 
 template <class Derived>
-class PastixBase : internal::noncopyable
+class PastixBase : public SparseSolverBase<Derived>
 {
+  protected:
+    typedef SparseSolverBase<Derived> Base;
+    using Base::derived;
+    using Base::m_isInitialized;
   public:
+    using Base::_solve_impl;
+    
     typedef typename internal::pastix_traits<Derived>::MatrixType _MatrixType;
     typedef _MatrixType MatrixType;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::StorageIndex StorageIndex;
     typedef Matrix<Scalar,Dynamic,1> Vector;
     typedef SparseMatrix<Scalar, ColMajor> ColSpMatrix;
+    enum {
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
     
   public:
     
-    PastixBase() : m_initisOk(false), m_analysisIsOk(false), m_factorizationIsOk(false), m_isInitialized(false), m_pastixdata(0), m_size(0)
+    PastixBase() : m_initisOk(false), m_analysisIsOk(false), m_factorizationIsOk(false), m_pastixdata(0), m_size(0)
     {
       init();
     }
     
     ~PastixBase() 
     {
       clean();
     }
-
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<PastixBase, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "Pastix solver is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "PastixBase::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<PastixBase, Rhs>(*this, b.derived());
-    }
     
     template<typename Rhs,typename Dest>
-    bool _solve (const MatrixBase<Rhs> &b, MatrixBase<Dest> &x) const;
-    
-    Derived& derived()
-    {
-      return *static_cast<Derived*>(this);
-    }
-    const Derived& derived() const
-    {
-      return *static_cast<const Derived*>(this);
-    }
-
+    bool _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &x) const;
+    
     /** Returns a reference to the integer vector IPARM of PaStiX parameters
       * to modify the default parameters. 
       * The statistics related to the different phases of factorization and solve are saved here as well
       * \sa analyzePattern() factorize()
       */
-    Array<Index,IPARM_SIZE,1>& iparm()
+    Array<StorageIndex,IPARM_SIZE,1>& iparm()
     {
       return m_iparm; 
     }
     
     /** Return a reference to a particular index parameter of the IPARM vector 
@@ -187,11 +182,11 @@
     
      /** Returns a reference to the double vector DPARM of PaStiX parameters 
       * The statistics related to the different phases of factorization and solve are saved here as well
       * \sa analyzePattern() factorize()
       */
-    Array<RealScalar,IPARM_SIZE,1>& dparm()
+    Array<double,DPARM_SIZE,1>& dparm()
     {
       return m_dparm; 
     }
     
     
@@ -218,24 +213,10 @@
     {
       eigen_assert(m_isInitialized && "Decomposition is not initialized.");
       return m_info;
     }
     
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::sparse_solve_retval<PastixBase, Rhs>
-    solve(const SparseMatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "Pastix LU, LLT or LDLT is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "PastixBase::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::sparse_solve_retval<PastixBase, Rhs>(*this, b.derived());
-    }
-    
   protected:
 
     // Initialize the Pastix data structure, check the matrix
     void init(); 
     
@@ -258,18 +239,17 @@
     void compute(ColSpMatrix& mat);
     
     int m_initisOk; 
     int m_analysisIsOk;
     int m_factorizationIsOk;
-    bool m_isInitialized;
     mutable ComputationInfo m_info; 
     mutable pastix_data_t *m_pastixdata; // Data structure for pastix
     mutable int m_comm; // The MPI communicator identifier
-    mutable Matrix<int,IPARM_SIZE,1> m_iparm; // integer vector for the input parameters
-    mutable Matrix<double,DPARM_SIZE,1> m_dparm; // Scalar vector for the input parameters
-    mutable Matrix<Index,Dynamic,1> m_perm;  // Permutation vector
-    mutable Matrix<Index,Dynamic,1> m_invp;  // Inverse permutation vector
+    mutable Array<int,IPARM_SIZE,1> m_iparm; // integer vector for the input parameters
+    mutable Array<double,DPARM_SIZE,1> m_dparm; // Scalar vector for the input parameters
+    mutable Matrix<StorageIndex,Dynamic,1> m_perm;  // Permutation vector
+    mutable Matrix<StorageIndex,Dynamic,1> m_invp;  // Inverse permutation vector
     mutable int m_size; // Size of the matrix 
 }; 
 
  /** Initialize the PaStiX data structure. 
    *A first call to this function fills iparm and dparm with the default PaStiX parameters
@@ -286,11 +266,11 @@
   pastix(&m_pastixdata, MPI_COMM_WORLD,
          0, 0, 0, 0,
          0, 0, 0, 1, m_iparm.data(), m_dparm.data());
   
   m_iparm[IPARM_MATRIX_VERIFICATION] = API_NO;
-  m_iparm[IPARM_VERBOSE]             = 2;
+  m_iparm[IPARM_VERBOSE]             = API_VERBOSE_NOT;
   m_iparm[IPARM_ORDERING]            = API_ORDER_SCOTCH;
   m_iparm[IPARM_INCOMPLETE]          = API_NO;
   m_iparm[IPARM_OOC_LIMIT]           = 2000;
   m_iparm[IPARM_RHS_MAKING]          = API_RHS_B;
   m_iparm(IPARM_MATRIX_VERIFICATION) = API_NO;
@@ -318,11 +298,10 @@
   
   analyzePattern(mat);  
   factorize(mat);
   
   m_iparm(IPARM_MATRIX_VERIFICATION) = API_NO;
-  m_isInitialized = m_factorizationIsOk;
 }
 
 
 template <class Derived>
 void PastixBase<Derived>::analyzePattern(ColSpMatrix& mat)
@@ -331,11 +310,11 @@
   
   // clean previous calls
   if(m_size>0)
     clean();
   
-  m_size = mat.rows();
+  m_size = internal::convert_index<int>(mat.rows());
   m_perm.resize(m_size);
   m_invp.resize(m_size);
   
   m_iparm(IPARM_START_TASK) = API_TASK_ORDERING;
   m_iparm(IPARM_END_TASK) = API_TASK_ANALYSE;
@@ -360,11 +339,11 @@
 {
 //   if(&m_cpyMat != &mat) m_cpyMat = mat;
   eigen_assert(m_analysisIsOk && "The analysis phase should be called before the factorization phase");
   m_iparm(IPARM_START_TASK) = API_TASK_NUMFACT;
   m_iparm(IPARM_END_TASK) = API_TASK_NUMFACT;
-  m_size = mat.rows();
+  m_size = internal::convert_index<int>(mat.rows());
   
   internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, m_size, mat.outerIndexPtr(), mat.innerIndexPtr(),
                mat.valuePtr(), m_perm.data(), m_invp.data(), 0, 0, m_iparm.data(), m_dparm.data());
   
   // Check the returned error
@@ -383,11 +362,11 @@
 }
 
 /* Solve the system */
 template<typename Base>
 template<typename Rhs,typename Dest>
-bool PastixBase<Base>::_solve (const MatrixBase<Rhs> &b, MatrixBase<Dest> &x) const
+bool PastixBase<Base>::_solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &x) const
 {
   eigen_assert(m_isInitialized && "The matrix should be factorized first");
   EIGEN_STATIC_ASSERT((Dest::Flags&RowMajorBit)==0,
                      THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
   int rhs = 1;
@@ -396,11 +375,11 @@
   
   for (int i = 0; i < b.cols(); i++){
     m_iparm[IPARM_START_TASK]          = API_TASK_SOLVE;
     m_iparm[IPARM_END_TASK]            = API_TASK_REFINE;
   
-    internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, x.rows(), 0, 0, 0,
+    internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, internal::convert_index<int>(x.rows()), 0, 0, 0,
                            m_perm.data(), m_invp.data(), &x(0, i), rhs, m_iparm.data(), m_dparm.data());
   }
   
   // Check the returned error
   m_info = m_iparm(IPARM_ERROR_NUMBER)==0 ? Success : NumericalIssue;
@@ -421,30 +400,32 @@
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam IsStrSym Indicates if the input matrix has a symmetric pattern, default is false
   * NOTE : Note that if the analysis and factorization phase are called separately, 
   * the input matrix will be symmetrized at each call, hence it is advised to 
   * symmetrize the matrix in a end-user program and set \p IsStrSym to true
-  * 
-  * \sa \ref TutorialSparseDirectSolvers
+  *
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class SparseLU
   * 
   */
 template<typename _MatrixType, bool IsStrSym>
 class PastixLU : public PastixBase< PastixLU<_MatrixType> >
 {
   public:
     typedef _MatrixType MatrixType;
     typedef PastixBase<PastixLU<MatrixType> > Base;
     typedef typename Base::ColSpMatrix ColSpMatrix;
-    typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::StorageIndex StorageIndex;
     
   public:
     PastixLU() : Base()
     {
       init();
     }
     
-    PastixLU(const MatrixType& matrix):Base()
+    explicit PastixLU(const MatrixType& matrix):Base()
     {
       init();
       compute(matrix);
     }
     /** Compute the LU supernodal factorization of \p matrix. 
@@ -532,12 +513,14 @@
   * WARNING Selfadjoint complex matrices are not supported in the current version of PaStiX
   * The vectors or matrices X and B can be either dense or sparse
   * 
   * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam UpLo The part of the matrix to use : Lower or Upper. The default is Lower as required by PaStiX
-  * 
-  * \sa \ref TutorialSparseDirectSolvers
+  *
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class SimplicialLLT
   */
 template<typename _MatrixType, int _UpLo>
 class PastixLLT : public PastixBase< PastixLLT<_MatrixType, _UpLo> >
 {
   public:
@@ -550,11 +533,11 @@
     PastixLLT() : Base()
     {
       init();
     }
     
-    PastixLLT(const MatrixType& matrix):Base()
+    explicit PastixLLT(const MatrixType& matrix):Base()
     {
       init();
       compute(matrix);
     }
 
@@ -596,10 +579,11 @@
       m_iparm(IPARM_FACTORIZATION) = API_FACT_LLT;
     }
     
     void grabMatrix(const MatrixType& matrix, ColSpMatrix& out)
     {
+      out.resize(matrix.rows(), matrix.cols());
       // Pastix supports only lower, column-major matrices 
       out.template selfadjointView<Lower>() = matrix.template selfadjointView<UpLo>();
       internal::c_to_fortran_numbering(out);
     }
 };
@@ -613,12 +597,14 @@
   * WARNING Selfadjoint complex matrices are not supported in the current version of PaStiX
   * The vectors or matrices X and B can be either dense or sparse
   * 
   * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam UpLo The part of the matrix to use : Lower or Upper. The default is Lower as required by PaStiX
-  * 
-  * \sa \ref TutorialSparseDirectSolvers
+  *
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class SimplicialLDLT
   */
 template<typename _MatrixType, int _UpLo>
 class PastixLDLT : public PastixBase< PastixLDLT<_MatrixType, _UpLo> >
 {
   public:
@@ -631,11 +617,11 @@
     PastixLDLT():Base()
     {
       init();
     }
     
-    PastixLDLT(const MatrixType& matrix):Base()
+    explicit PastixLDLT(const MatrixType& matrix):Base()
     {
       init();
       compute(matrix);
     }
 
@@ -679,43 +665,14 @@
     }
     
     void grabMatrix(const MatrixType& matrix, ColSpMatrix& out)
     {
       // Pastix supports only lower, column-major matrices 
+      out.resize(matrix.rows(), matrix.cols());
       out.template selfadjointView<Lower>() = matrix.template selfadjointView<UpLo>();
       internal::c_to_fortran_numbering(out);
     }
 };
 
-namespace internal {
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<PastixBase<_MatrixType>, Rhs>
-  : solve_retval_base<PastixBase<_MatrixType>, Rhs>
-{
-  typedef PastixBase<_MatrixType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-template<typename _MatrixType, typename Rhs>
-struct sparse_solve_retval<PastixBase<_MatrixType>, Rhs>
-  : sparse_solve_retval_base<PastixBase<_MatrixType>, Rhs>
-{
-  typedef PastixBase<_MatrixType> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    this->defaultEvalTo(dst);
-  }
-};
-
-} // end namespace internal
-
 } // end namespace Eigen
 
 #endif

DELETED 3rd_party/eigen/Eigen/src/PardisoSupport/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/PardisoSupport/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/PardisoSupport/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/PardisoSupport/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_PardisoSupport_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_PardisoSupport_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/PardisoSupport COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/PardisoSupport/PardisoSupport.h
==================================================================
--- 3rd_party/eigen/Eigen/src/PardisoSupport/PardisoSupport.h
+++ 3rd_party/eigen/Eigen/src/PardisoSupport/PardisoSupport.h
@@ -38,29 +38,29 @@
 template<typename _MatrixType, int Options=Upper> class PardisoLLT;
 template<typename _MatrixType, int Options=Upper> class PardisoLDLT;
 
 namespace internal
 {
-  template<typename Index>
+  template<typename IndexType>
   struct pardiso_run_selector
   {
-    static Index run( _MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a,
-                      Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x)
+    static IndexType run( _MKL_DSS_HANDLE_t pt, IndexType maxfct, IndexType mnum, IndexType type, IndexType phase, IndexType n, void *a,
+                      IndexType *ia, IndexType *ja, IndexType *perm, IndexType nrhs, IndexType *iparm, IndexType msglvl, void *b, void *x)
     {
-      Index error = 0;
+      IndexType error = 0;
       ::pardiso(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error);
       return error;
     }
   };
   template<>
   struct pardiso_run_selector<long long int>
   {
-    typedef long long int Index;
-    static Index run( _MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a,
-                      Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x)
+    typedef long long int IndexType;
+    static IndexType run( _MKL_DSS_HANDLE_t pt, IndexType maxfct, IndexType mnum, IndexType type, IndexType phase, IndexType n, void *a,
+                      IndexType *ia, IndexType *ja, IndexType *perm, IndexType nrhs, IndexType *iparm, IndexType msglvl, void *b, void *x)
     {
-      Index error = 0;
+      IndexType error = 0;
       ::pardiso_64(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error);
       return error;
     }
   };
 
@@ -70,57 +70,66 @@
   struct pardiso_traits< PardisoLU<_MatrixType> >
   {
     typedef _MatrixType MatrixType;
     typedef typename _MatrixType::Scalar Scalar;
     typedef typename _MatrixType::RealScalar RealScalar;
-    typedef typename _MatrixType::Index Index;
+    typedef typename _MatrixType::StorageIndex StorageIndex;
   };
 
   template<typename _MatrixType, int Options>
   struct pardiso_traits< PardisoLLT<_MatrixType, Options> >
   {
     typedef _MatrixType MatrixType;
     typedef typename _MatrixType::Scalar Scalar;
     typedef typename _MatrixType::RealScalar RealScalar;
-    typedef typename _MatrixType::Index Index;
+    typedef typename _MatrixType::StorageIndex StorageIndex;
   };
 
   template<typename _MatrixType, int Options>
   struct pardiso_traits< PardisoLDLT<_MatrixType, Options> >
   {
     typedef _MatrixType MatrixType;
     typedef typename _MatrixType::Scalar Scalar;
     typedef typename _MatrixType::RealScalar RealScalar;
-    typedef typename _MatrixType::Index Index;    
+    typedef typename _MatrixType::StorageIndex StorageIndex;    
   };
 
-}
+} // end namespace internal
 
 template<class Derived>
-class PardisoImpl
+class PardisoImpl : public SparseSolverBase<Derived>
 {
+  protected:
+    typedef SparseSolverBase<Derived> Base;
+    using Base::derived;
+    using Base::m_isInitialized;
+    
     typedef internal::pardiso_traits<Derived> Traits;
   public:
+    using Base::_solve_impl;
+    
     typedef typename Traits::MatrixType MatrixType;
     typedef typename Traits::Scalar Scalar;
     typedef typename Traits::RealScalar RealScalar;
-    typedef typename Traits::Index Index;
-    typedef SparseMatrix<Scalar,RowMajor,Index> SparseMatrixType;
+    typedef typename Traits::StorageIndex StorageIndex;
+    typedef SparseMatrix<Scalar,RowMajor,StorageIndex> SparseMatrixType;
     typedef Matrix<Scalar,Dynamic,1> VectorType;
-    typedef Matrix<Index, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
-    typedef Matrix<Index, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
-    typedef Array<Index,64,1,DontAlign> ParameterType;
+    typedef Matrix<StorageIndex, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
+    typedef Matrix<StorageIndex, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
+    typedef Array<StorageIndex,64,1,DontAlign> ParameterType;
     enum {
-      ScalarIsComplex = NumTraits<Scalar>::IsComplex
+      ScalarIsComplex = NumTraits<Scalar>::IsComplex,
+      ColsAtCompileTime = Dynamic,
+      MaxColsAtCompileTime = Dynamic
     };
 
     PardisoImpl()
     {
-      eigen_assert((sizeof(Index) >= sizeof(_INTEGER_t) && sizeof(Index) <= 8) && "Non-supported index type");
+      eigen_assert((sizeof(StorageIndex) >= sizeof(_INTEGER_t) && sizeof(StorageIndex) <= 8) && "Non-supported index type");
       m_iparm.setZero();
       m_msglvl = 0; // No output
-      m_initialized = false;
+      m_isInitialized = false;
     }
 
     ~PardisoImpl()
     {
       pardisoRelease();
@@ -134,11 +143,11 @@
       * \returns \c Success if computation was succesful,
       *          \c NumericalIssue if the matrix appears to be negative.
       */
     ComputationInfo info() const
     {
-      eigen_assert(m_initialized && "Decomposition is not initialized.");
+      eigen_assert(m_isInitialized && "Decomposition is not initialized.");
       return m_info;
     }
 
     /** \warning for advanced usage only.
       * \returns a reference to the parameter array controlling PARDISO.
@@ -163,71 +172,35 @@
       * \sa analyzePattern()
       */
     Derived& factorize(const MatrixType& matrix);
 
     Derived& compute(const MatrixType& matrix);
-    
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<PardisoImpl, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_initialized && "Pardiso solver is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "PardisoImpl::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<PardisoImpl, Rhs>(*this, b.derived());
-    }
-
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::sparse_solve_retval<PardisoImpl, Rhs>
-    solve(const SparseMatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_initialized && "Pardiso solver is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "PardisoImpl::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::sparse_solve_retval<PardisoImpl, Rhs>(*this, b.derived());
-    }
-
-    Derived& derived()
-    {
-      return *static_cast<Derived*>(this);
-    }
-    const Derived& derived() const
-    {
-      return *static_cast<const Derived*>(this);
-    }
-
-    template<typename BDerived, typename XDerived>
-    bool _solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>& x) const;
+
+    template<typename Rhs,typename Dest>
+    void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const;
 
   protected:
     void pardisoRelease()
     {
-      if(m_initialized) // Factorization ran at least once
+      if(m_isInitialized) // Factorization ran at least once
       {
-        internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, -1, m_size, 0, 0, 0, m_perm.data(), 0,
-                                                   m_iparm.data(), m_msglvl, 0, 0);
+        internal::pardiso_run_selector<StorageIndex>::run(m_pt, 1, 1, m_type, -1, internal::convert_index<StorageIndex>(m_size),0, 0, 0, m_perm.data(), 0,
+                                                          m_iparm.data(), m_msglvl, NULL, NULL);
+        m_isInitialized = false;
       }
     }
 
     void pardisoInit(int type)
     {
       m_type = type;
       bool symmetric = std::abs(m_type) < 10;
       m_iparm[0] = 1;   // No solver default
-      m_iparm[1] = 3;   // use Metis for the ordering
-      m_iparm[2] = 1;   // Numbers of processors, value of OMP_NUM_THREADS
+      m_iparm[1] = 2;   // use Metis for the ordering
+      m_iparm[2] = 0;   // Reserved. Set to zero. (??Numbers of processors, value of OMP_NUM_THREADS??)
       m_iparm[3] = 0;   // No iterative-direct algorithm
       m_iparm[4] = 0;   // No user fill-in reducing permutation
-      m_iparm[5] = 0;   // Write solution into x
+      m_iparm[5] = 0;   // Write solution into x, b is left unchanged
       m_iparm[6] = 0;   // Not in use
       m_iparm[7] = 2;   // Max numbers of iterative refinement steps
       m_iparm[8] = 0;   // Not in use
       m_iparm[9] = 13;  // Perturb the pivot elements with 1E-13
       m_iparm[10] = symmetric ? 0 : 1; // Use nonsymmetric permutation and scaling MPS
@@ -244,17 +217,20 @@
       
       m_iparm[20] = 0;  // 1x1 pivoting
       m_iparm[26] = 0;  // No matrix checker
       m_iparm[27] = (sizeof(RealScalar) == 4) ? 1 : 0;
       m_iparm[34] = 1;  // C indexing
-      m_iparm[59] = 1;  // Automatic switch between In-Core and Out-of-Core modes
+      m_iparm[36] = 0;  // CSR
+      m_iparm[59] = 0;  // 0 - In-Core ; 1 - Automatic switch between In-Core and Out-of-Core modes ; 2 - Out-of-Core
+      
+      memset(m_pt, 0, sizeof(m_pt));
     }
 
   protected:
     // cached data to reduce reallocation, etc.
     
-    void manageErrorCode(Index error)
+    void manageErrorCode(Index error) const
     {
       switch(error)
       {
         case 0:
           m_info = Success;
@@ -267,42 +243,38 @@
           m_info = InvalidInput;
       }
     }
 
     mutable SparseMatrixType m_matrix;
-    ComputationInfo m_info;
-    bool m_initialized, m_analysisIsOk, m_factorizationIsOk;
-    Index m_type, m_msglvl;
+    mutable ComputationInfo m_info;
+    bool m_analysisIsOk, m_factorizationIsOk;
+    StorageIndex m_type, m_msglvl;
     mutable void *m_pt[64];
     mutable ParameterType m_iparm;
     mutable IntColVectorType m_perm;
     Index m_size;
     
-  private:
-    PardisoImpl(PardisoImpl &) {}
 };
 
 template<class Derived>
 Derived& PardisoImpl<Derived>::compute(const MatrixType& a)
 {
   m_size = a.rows();
   eigen_assert(a.rows() == a.cols());
 
   pardisoRelease();
-  memset(m_pt, 0, sizeof(m_pt));
   m_perm.setZero(m_size);
   derived().getMatrix(a);
   
   Index error;
-  error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 12, m_size,
-                                                     m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
-                                                     m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
-
+  error = internal::pardiso_run_selector<StorageIndex>::run(m_pt, 1, 1, m_type, 12, internal::convert_index<StorageIndex>(m_size),
+                                                            m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
+                                                            m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
   manageErrorCode(error);
   m_analysisIsOk = true;
   m_factorizationIsOk = true;
-  m_initialized = true;
+  m_isInitialized = true;
   return derived();
 }
 
 template<class Derived>
 Derived& PardisoImpl<Derived>::analyzePattern(const MatrixType& a)
@@ -309,23 +281,22 @@
 {
   m_size = a.rows();
   eigen_assert(m_size == a.cols());
 
   pardisoRelease();
-  memset(m_pt, 0, sizeof(m_pt));
   m_perm.setZero(m_size);
   derived().getMatrix(a);
   
   Index error;
-  error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 11, m_size,
-                                                     m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
-                                                     m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
+  error = internal::pardiso_run_selector<StorageIndex>::run(m_pt, 1, 1, m_type, 11, internal::convert_index<StorageIndex>(m_size),
+                                                            m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
+                                                            m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
   
   manageErrorCode(error);
   m_analysisIsOk = true;
   m_factorizationIsOk = false;
-  m_initialized = true;
+  m_isInitialized = true;
   return derived();
 }
 
 template<class Derived>
 Derived& PardisoImpl<Derived>::factorize(const MatrixType& a)
@@ -333,26 +304,29 @@
   eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
   eigen_assert(m_size == a.rows() && m_size == a.cols());
   
   derived().getMatrix(a);
 
-  Index error;  
-  error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 22, m_size,
-                                                     m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
-                                                     m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
+  Index error;
+  error = internal::pardiso_run_selector<StorageIndex>::run(m_pt, 1, 1, m_type, 22, internal::convert_index<StorageIndex>(m_size),
+                                                            m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
+                                                            m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
   
   manageErrorCode(error);
   m_factorizationIsOk = true;
   return derived();
 }
 
-template<class Base>
+template<class Derived>
 template<typename BDerived,typename XDerived>
-bool PardisoImpl<Base>::_solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>& x) const
+void PardisoImpl<Derived>::_solve_impl(const MatrixBase<BDerived> &b, MatrixBase<XDerived>& x) const
 {
   if(m_iparm[0] == 0) // Factorization was not computed
-    return false;
+  {
+    m_info = InvalidInput;
+    return;
+  }
 
   //Index n = m_matrix.rows();
   Index nrhs = Index(b.cols());
   eigen_assert(m_size==b.rows());
   eigen_assert(((MatrixBase<BDerived>::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major right hand sides are not supported");
@@ -378,16 +352,16 @@
     tmp = b;
     rhs_ptr = tmp.data();
   }
   
   Index error;
-  error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 33, m_size,
-                                                     m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
-                                                     m_perm.data(), nrhs, m_iparm.data(), m_msglvl,
-                                                     rhs_ptr, x.derived().data());
+  error = internal::pardiso_run_selector<StorageIndex>::run(m_pt, 1, 1, m_type, 33, internal::convert_index<StorageIndex>(m_size),
+                                                            m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
+                                                            m_perm.data(), internal::convert_index<StorageIndex>(nrhs), m_iparm.data(), m_msglvl,
+                                                            rhs_ptr, x.derived().data());
 
-  return error==0;
+  manageErrorCode(error);
 }
 
 
 /** \ingroup PardisoSupport_Module
   * \class PardisoLU
@@ -394,20 +368,25 @@
   * \brief A sparse direct LU factorization and solver based on the PARDISO library
   *
   * This class allows to solve for A.X = B sparse linear problems via a direct LU factorization
   * using the Intel MKL PARDISO library. The sparse matrix A must be squared and invertible.
   * The vectors or matrices X and B can be either dense or sparse.
+  *
+  * By default, it runs in in-core mode. To enable PARDISO's out-of-core feature, set:
+  * \code solver.pardisoParameterArray()[59] = 1; \endcode
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   *
-  * \sa \ref TutorialSparseDirectSolvers
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class SparseLU
   */
 template<typename MatrixType>
 class PardisoLU : public PardisoImpl< PardisoLU<MatrixType> >
 {
   protected:
-    typedef PardisoImpl< PardisoLU<MatrixType> > Base;
+    typedef PardisoImpl<PardisoLU> Base;
     typedef typename Base::Scalar Scalar;
     typedef typename Base::RealScalar RealScalar;
     using Base::pardisoInit;
     using Base::m_matrix;
     friend class PardisoImpl< PardisoLU<MatrixType> >;
@@ -421,65 +400,67 @@
       : Base()
     {
       pardisoInit(Base::ScalarIsComplex ? 13 : 11);
     }
 
-    PardisoLU(const MatrixType& matrix)
+    explicit PardisoLU(const MatrixType& matrix)
       : Base()
     {
       pardisoInit(Base::ScalarIsComplex ? 13 : 11);
       compute(matrix);
     }
   protected:
     void getMatrix(const MatrixType& matrix)
     {
       m_matrix = matrix;
+      m_matrix.makeCompressed();
     }
-    
-  private:
-    PardisoLU(PardisoLU& ) {}
 };
 
 /** \ingroup PardisoSupport_Module
   * \class PardisoLLT
   * \brief A sparse direct Cholesky (LLT) factorization and solver based on the PARDISO library
   *
   * This class allows to solve for A.X = B sparse linear problems via a LL^T Cholesky factorization
   * using the Intel MKL PARDISO library. The sparse matrix A must be selfajoint and positive definite.
   * The vectors or matrices X and B can be either dense or sparse.
+  *
+  * By default, it runs in in-core mode. To enable PARDISO's out-of-core feature, set:
+  * \code solver.pardisoParameterArray()[59] = 1; \endcode
   *
   * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam UpLo can be any bitwise combination of Upper, Lower. The default is Upper, meaning only the upper triangular part has to be used.
   *         Upper|Lower can be used to tell both triangular parts can be used as input.
   *
-  * \sa \ref TutorialSparseDirectSolvers
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class SimplicialLLT
   */
 template<typename MatrixType, int _UpLo>
 class PardisoLLT : public PardisoImpl< PardisoLLT<MatrixType,_UpLo> >
 {
   protected:
     typedef PardisoImpl< PardisoLLT<MatrixType,_UpLo> > Base;
     typedef typename Base::Scalar Scalar;
-    typedef typename Base::Index Index;
     typedef typename Base::RealScalar RealScalar;
     using Base::pardisoInit;
     using Base::m_matrix;
     friend class PardisoImpl< PardisoLLT<MatrixType,_UpLo> >;
 
   public:
 
+    typedef typename Base::StorageIndex StorageIndex;
     enum { UpLo = _UpLo };
     using Base::compute;
-    using Base::solve;
 
     PardisoLLT()
       : Base()
     {
       pardisoInit(Base::ScalarIsComplex ? 4 : 2);
     }
 
-    PardisoLLT(const MatrixType& matrix)
+    explicit PardisoLLT(const MatrixType& matrix)
       : Base()
     {
       pardisoInit(Base::ScalarIsComplex ? 4 : 2);
       compute(matrix);
     }
@@ -487,17 +468,15 @@
   protected:
     
     void getMatrix(const MatrixType& matrix)
     {
       // PARDISO supports only upper, row-major matrices
-      PermutationMatrix<Dynamic,Dynamic,Index> p_null;
+      PermutationMatrix<Dynamic,Dynamic,StorageIndex> p_null;
       m_matrix.resize(matrix.rows(), matrix.cols());
       m_matrix.template selfadjointView<Upper>() = matrix.template selfadjointView<UpLo>().twistedBy(p_null);
+      m_matrix.makeCompressed();
     }
-    
-  private:
-    PardisoLLT(PardisoLLT& ) {}
 };
 
 /** \ingroup PardisoSupport_Module
   * \class PardisoLDLT
   * \brief A sparse direct Cholesky (LDLT) factorization and solver based on the PARDISO library
@@ -504,89 +483,61 @@
   *
   * This class allows to solve for A.X = B sparse linear problems via a LDL^T Cholesky factorization
   * using the Intel MKL PARDISO library. The sparse matrix A is assumed to be selfajoint and positive definite.
   * For complex matrices, A can also be symmetric only, see the \a Options template parameter.
   * The vectors or matrices X and B can be either dense or sparse.
+  *
+  * By default, it runs in in-core mode. To enable PARDISO's out-of-core feature, set:
+  * \code solver.pardisoParameterArray()[59] = 1; \endcode
   *
   * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam Options can be any bitwise combination of Upper, Lower, and Symmetric. The default is Upper, meaning only the upper triangular part has to be used.
   *         Symmetric can be used for symmetric, non-selfadjoint complex matrices, the default being to assume a selfadjoint matrix.
   *         Upper|Lower can be used to tell both triangular parts can be used as input.
   *
-  * \sa \ref TutorialSparseDirectSolvers
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class SimplicialLDLT
   */
 template<typename MatrixType, int Options>
 class PardisoLDLT : public PardisoImpl< PardisoLDLT<MatrixType,Options> >
 {
   protected:
     typedef PardisoImpl< PardisoLDLT<MatrixType,Options> > Base;
     typedef typename Base::Scalar Scalar;
-    typedef typename Base::Index Index;
     typedef typename Base::RealScalar RealScalar;
     using Base::pardisoInit;
     using Base::m_matrix;
     friend class PardisoImpl< PardisoLDLT<MatrixType,Options> >;
 
   public:
 
+    typedef typename Base::StorageIndex StorageIndex;
     using Base::compute;
-    using Base::solve;
     enum { UpLo = Options&(Upper|Lower) };
 
     PardisoLDLT()
       : Base()
     {
       pardisoInit(Base::ScalarIsComplex ? ( bool(Options&Symmetric) ? 6 : -4 ) : -2);
     }
 
-    PardisoLDLT(const MatrixType& matrix)
+    explicit PardisoLDLT(const MatrixType& matrix)
       : Base()
     {
       pardisoInit(Base::ScalarIsComplex ? ( bool(Options&Symmetric) ? 6 : -4 ) : -2);
       compute(matrix);
     }
     
     void getMatrix(const MatrixType& matrix)
     {
       // PARDISO supports only upper, row-major matrices
-      PermutationMatrix<Dynamic,Dynamic,Index> p_null;
+      PermutationMatrix<Dynamic,Dynamic,StorageIndex> p_null;
       m_matrix.resize(matrix.rows(), matrix.cols());
       m_matrix.template selfadjointView<Upper>() = matrix.template selfadjointView<UpLo>().twistedBy(p_null);
-    }
-    
-  private:
-    PardisoLDLT(PardisoLDLT& ) {}
-};
-
-namespace internal {
-  
-template<typename _Derived, typename Rhs>
-struct solve_retval<PardisoImpl<_Derived>, Rhs>
-  : solve_retval_base<PardisoImpl<_Derived>, Rhs>
-{
-  typedef PardisoImpl<_Derived> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-template<typename Derived, typename Rhs>
-struct sparse_solve_retval<PardisoImpl<Derived>, Rhs>
-  : sparse_solve_retval_base<PardisoImpl<Derived>, Rhs>
-{
-  typedef PardisoImpl<Derived> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    this->defaultEvalTo(dst);
-  }
-};
-
-} // end namespace internal
+      m_matrix.makeCompressed();
+    }
+};
 
 } // end namespace Eigen
 
 #endif // EIGEN_PARDISOSUPPORT_H

DELETED 3rd_party/eigen/Eigen/src/QR/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/QR/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/QR/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_QR_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_QR_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/QR COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR.h
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR.h
+++ 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR.h
@@ -9,31 +9,42 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COLPIVOTINGHOUSEHOLDERQR_H
 #define EIGEN_COLPIVOTINGHOUSEHOLDERQR_H
 
-namespace Eigen { 
+namespace Eigen {
+
+namespace internal {
+template<typename _MatrixType> struct traits<ColPivHouseholderQR<_MatrixType> >
+ : traits<_MatrixType>
+{
+  enum { Flags = 0 };
+};
+
+} // end namespace internal
 
 /** \ingroup QR_Module
   *
   * \class ColPivHouseholderQR
   *
   * \brief Householder rank-revealing QR decomposition of a matrix with column-pivoting
   *
-  * \param MatrixType the type of the matrix of which we are computing the QR decomposition
+  * \tparam _MatrixType the type of the matrix of which we are computing the QR decomposition
   *
   * This class performs a rank-revealing QR decomposition of a matrix \b A into matrices \b P, \b Q and \b R
-  * such that 
+  * such that
   * \f[
   *  \mathbf{A} \, \mathbf{P} = \mathbf{Q} \, \mathbf{R}
   * \f]
-  * by using Householder transformations. Here, \b P is a permutation matrix, \b Q a unitary matrix and \b R an 
+  * by using Householder transformations. Here, \b P is a permutation matrix, \b Q a unitary matrix and \b R an
   * upper triangular matrix.
   *
   * This decomposition performs column pivoting in order to be rank-revealing and improve
   * numerical stability. It is slower than HouseholderQR, and faster than FullPivHouseholderQR.
   *
+  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
+  * 
   * \sa MatrixBase::colPivHouseholderQr()
   */
 template<typename _MatrixType> class ColPivHouseholderQR
 {
   public:
@@ -40,29 +51,29 @@
 
     typedef _MatrixType MatrixType;
     enum {
       RowsAtCompileTime = MatrixType::RowsAtCompileTime,
       ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      Options = MatrixType::Options,
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
-    typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, Options, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixQType;
+    // FIXME should be int
+    typedef typename MatrixType::StorageIndex StorageIndex;
     typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
     typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime> PermutationType;
     typedef typename internal::plain_row_type<MatrixType, Index>::type IntRowVectorType;
     typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
     typedef typename internal::plain_row_type<MatrixType, RealScalar>::type RealRowVectorType;
     typedef HouseholderSequence<MatrixType,typename internal::remove_all<typename HCoeffsType::ConjugateReturnType>::type> HouseholderSequenceType;
-    
+    typedef typename MatrixType::PlainObject PlainObject;
+
   private:
-    
-    typedef typename PermutationType::Index PermIndexType;
-    
+
+    typedef typename PermutationType::StorageIndex PermIndexType;
+
   public:
 
     /**
     * \brief Default Constructor.
     *
@@ -73,11 +84,12 @@
       : m_qr(),
         m_hCoeffs(),
         m_colsPermutation(),
         m_colsTranspositions(),
         m_temp(),
-        m_colSqNorms(),
+        m_colNormsUpdated(),
+        m_colNormsDirect(),
         m_isInitialized(false),
         m_usePrescribedThreshold(false) {}
 
     /** \brief Default Constructor with memory preallocation
       *
@@ -89,94 +101,116 @@
       : m_qr(rows, cols),
         m_hCoeffs((std::min)(rows,cols)),
         m_colsPermutation(PermIndexType(cols)),
         m_colsTranspositions(cols),
         m_temp(cols),
-        m_colSqNorms(cols),
+        m_colNormsUpdated(cols),
+        m_colNormsDirect(cols),
         m_isInitialized(false),
         m_usePrescribedThreshold(false) {}
 
     /** \brief Constructs a QR factorization from a given matrix
       *
       * This constructor computes the QR factorization of the matrix \a matrix by calling
       * the method compute(). It is a short cut for:
-      * 
+      *
       * \code
       * ColPivHouseholderQR<MatrixType> qr(matrix.rows(), matrix.cols());
       * qr.compute(matrix);
       * \endcode
-      * 
+      *
       * \sa compute()
       */
-    ColPivHouseholderQR(const MatrixType& matrix)
+    template<typename InputType>
+    explicit ColPivHouseholderQR(const EigenBase<InputType>& matrix)
       : m_qr(matrix.rows(), matrix.cols()),
         m_hCoeffs((std::min)(matrix.rows(),matrix.cols())),
         m_colsPermutation(PermIndexType(matrix.cols())),
         m_colsTranspositions(matrix.cols()),
         m_temp(matrix.cols()),
-        m_colSqNorms(matrix.cols()),
+        m_colNormsUpdated(matrix.cols()),
+        m_colNormsDirect(matrix.cols()),
+        m_isInitialized(false),
+        m_usePrescribedThreshold(false)
+    {
+      compute(matrix.derived());
+    }
+
+    /** \brief Constructs a QR factorization from a given matrix
+      *
+      * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when \c MatrixType is a Eigen::Ref.
+      *
+      * \sa ColPivHouseholderQR(const EigenBase&)
+      */
+    template<typename InputType>
+    explicit ColPivHouseholderQR(EigenBase<InputType>& matrix)
+      : m_qr(matrix.derived()),
+        m_hCoeffs((std::min)(matrix.rows(),matrix.cols())),
+        m_colsPermutation(PermIndexType(matrix.cols())),
+        m_colsTranspositions(matrix.cols()),
+        m_temp(matrix.cols()),
+        m_colNormsUpdated(matrix.cols()),
+        m_colNormsDirect(matrix.cols()),
         m_isInitialized(false),
         m_usePrescribedThreshold(false)
     {
-      compute(matrix);
+      computeInPlace();
     }
 
     /** This method finds a solution x to the equation Ax=b, where A is the matrix of which
       * *this is the QR decomposition, if any exists.
       *
       * \param b the right-hand-side of the equation to solve.
       *
       * \returns a solution.
       *
-      * \note The case where b is a matrix is not yet implemented. Also, this
-      *       code is space inefficient.
-      *
       * \note_about_checking_solutions
       *
       * \note_about_arbitrary_choice_of_solution
       *
       * Example: \include ColPivHouseholderQR_solve.cpp
       * Output: \verbinclude ColPivHouseholderQR_solve.out
       */
     template<typename Rhs>
-    inline const internal::solve_retval<ColPivHouseholderQR, Rhs>
+    inline const Solve<ColPivHouseholderQR, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
       eigen_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
-      return internal::solve_retval<ColPivHouseholderQR, Rhs>(*this, b.derived());
+      return Solve<ColPivHouseholderQR, Rhs>(*this, b.derived());
     }
 
-    HouseholderSequenceType householderQ(void) const;
-    HouseholderSequenceType matrixQ(void) const
+    HouseholderSequenceType householderQ() const;
+    HouseholderSequenceType matrixQ() const
     {
-      return householderQ(); 
+      return householderQ();
     }
 
     /** \returns a reference to the matrix where the Householder QR decomposition is stored
       */
     const MatrixType& matrixQR() const
     {
       eigen_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
       return m_qr;
     }
-    
-    /** \returns a reference to the matrix where the result Householder QR is stored 
-     * \warning The strict lower part of this matrix contains internal values. 
+
+    /** \returns a reference to the matrix where the result Householder QR is stored
+     * \warning The strict lower part of this matrix contains internal values.
      * Only the upper triangular part should be referenced. To get it, use
      * \code matrixR().template triangularView<Upper>() \endcode
-     * For rank-deficient matrices, use 
-     * \code 
-     * matrixR().topLeftCorner(rank(), rank()).template triangularView<Upper>() 
+     * For rank-deficient matrices, use
+     * \code
+     * matrixR().topLeftCorner(rank(), rank()).template triangularView<Upper>()
      * \endcode
      */
     const MatrixType& matrixR() const
     {
       eigen_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
       return m_qr;
     }
-    
-    ColPivHouseholderQR& compute(const MatrixType& matrix);
+
+    template<typename InputType>
+    ColPivHouseholderQR& compute(const EigenBase<InputType>& matrix);
 
     /** \returns a const reference to the column permutation matrix */
     const PermutationType& colsPermutation() const
     {
       eigen_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
@@ -282,24 +316,21 @@
     /** \returns the inverse of the matrix of which *this is the QR decomposition.
       *
       * \note If this matrix is not invertible, the returned matrix has undefined coefficients.
       *       Use isInvertible() to first determine whether this matrix is invertible.
       */
-    inline const
-    internal::solve_retval<ColPivHouseholderQR, typename MatrixType::IdentityReturnType>
-    inverse() const
+    inline const Inverse<ColPivHouseholderQR> inverse() const
     {
       eigen_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
-      return internal::solve_retval<ColPivHouseholderQR,typename MatrixType::IdentityReturnType>
-               (*this, MatrixType::Identity(m_qr.rows(), m_qr.cols()));
+      return Inverse<ColPivHouseholderQR>(*this);
     }
 
     inline Index rows() const { return m_qr.rows(); }
     inline Index cols() const { return m_qr.cols(); }
-    
+
     /** \returns a const reference to the vector of Householder coefficients used to represent the factor \c Q.
-      * 
+      *
       * For advanced uses only.
       */
     const HCoeffsType& hCoeffs() const { return m_hCoeffs; }
 
     /** Allows to prescribe a threshold to be used by certain methods, such as rank(),
@@ -368,30 +399,47 @@
 
     /** \returns the absolute value of the biggest pivot, i.e. the biggest
       *          diagonal coefficient of R.
       */
     RealScalar maxPivot() const { return m_maxpivot; }
-    
+
     /** \brief Reports whether the QR factorization was succesful.
       *
-      * \note This function always returns \c Success. It is provided for compatibility 
+      * \note This function always returns \c Success. It is provided for compatibility
       * with other factorization routines.
-      * \returns \c Success 
+      * \returns \c Success
       */
     ComputationInfo info() const
     {
       eigen_assert(m_isInitialized && "Decomposition is not initialized.");
       return Success;
     }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl(const RhsType &rhs, DstType &dst) const;
+    #endif
 
   protected:
+
+    friend class CompleteOrthogonalDecomposition<MatrixType>;
+
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+
+    void computeInPlace();
+
     MatrixType m_qr;
     HCoeffsType m_hCoeffs;
     PermutationType m_colsPermutation;
     IntRowVectorType m_colsTranspositions;
     RowVectorType m_temp;
-    RealRowVectorType m_colSqNorms;
+    RealRowVectorType m_colNormsUpdated;
+    RealRowVectorType m_colNormsDirect;
     bool m_isInitialized, m_usePrescribedThreshold;
     RealScalar m_prescribedThreshold, m_maxpivot;
     Index m_nonzero_pivots;
     Index m_det_pq;
 };
@@ -418,73 +466,72 @@
   * is returned.
   *
   * \sa class ColPivHouseholderQR, ColPivHouseholderQR(const MatrixType&)
   */
 template<typename MatrixType>
-ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
+template<typename InputType>
+ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const EigenBase<InputType>& matrix)
+{
+  m_qr = matrix.derived();
+  computeInPlace();
+  return *this;
+}
+
+template<typename MatrixType>
+void ColPivHouseholderQR<MatrixType>::computeInPlace()
 {
-  using std::abs;
-  Index rows = matrix.rows();
-  Index cols = matrix.cols();
-  Index size = matrix.diagonalSize();
-  
+  check_template_parameters();
+
   // the column permutation is stored as int indices, so just to be sure:
-  eigen_assert(cols<=NumTraits<int>::highest());
+  eigen_assert(m_qr.cols()<=NumTraits<int>::highest());
+
+  using std::abs;
 
-  m_qr = matrix;
+  Index rows = m_qr.rows();
+  Index cols = m_qr.cols();
+  Index size = m_qr.diagonalSize();
+
   m_hCoeffs.resize(size);
 
   m_temp.resize(cols);
 
-  m_colsTranspositions.resize(matrix.cols());
+  m_colsTranspositions.resize(m_qr.cols());
   Index number_of_transpositions = 0;
 
-  m_colSqNorms.resize(cols);
-  for(Index k = 0; k < cols; ++k)
-    m_colSqNorms.coeffRef(k) = m_qr.col(k).squaredNorm();
+  m_colNormsUpdated.resize(cols);
+  m_colNormsDirect.resize(cols);
+  for (Index k = 0; k < cols; ++k) {
+    // colNormsDirect(k) caches the most recent directly computed norm of
+    // column k.
+    m_colNormsDirect.coeffRef(k) = m_qr.col(k).norm();
+    m_colNormsUpdated.coeffRef(k) = m_colNormsDirect.coeffRef(k);
+  }
 
-  RealScalar threshold_helper = m_colSqNorms.maxCoeff() * numext::abs2(NumTraits<Scalar>::epsilon()) / RealScalar(rows);
+  RealScalar threshold_helper =  numext::abs2<RealScalar>(m_colNormsUpdated.maxCoeff() * NumTraits<RealScalar>::epsilon()) / RealScalar(rows);
+  RealScalar norm_downdate_threshold = numext::sqrt(NumTraits<RealScalar>::epsilon());
 
   m_nonzero_pivots = size; // the generic case is that in which all pivots are nonzero (invertible case)
   m_maxpivot = RealScalar(0);
 
   for(Index k = 0; k < size; ++k)
   {
-    // first, we look up in our table m_colSqNorms which column has the biggest squared norm
+    // first, we look up in our table m_colNormsUpdated which column has the biggest norm
     Index biggest_col_index;
-    RealScalar biggest_col_sq_norm = m_colSqNorms.tail(cols-k).maxCoeff(&biggest_col_index);
+    RealScalar biggest_col_sq_norm = numext::abs2(m_colNormsUpdated.tail(cols-k).maxCoeff(&biggest_col_index));
     biggest_col_index += k;
 
-    // since our table m_colSqNorms accumulates imprecision at every step, we must now recompute
-    // the actual squared norm of the selected column.
-    // Note that not doing so does result in solve() sometimes returning inf/nan values
-    // when running the unit test with 1000 repetitions.
-    biggest_col_sq_norm = m_qr.col(biggest_col_index).tail(rows-k).squaredNorm();
-
-    // we store that back into our table: it can't hurt to correct our table.
-    m_colSqNorms.coeffRef(biggest_col_index) = biggest_col_sq_norm;
-
-    // if the current biggest column is smaller than epsilon times the initial biggest column,
-    // terminate to avoid generating nan/inf values.
-    // Note that here, if we test instead for "biggest == 0", we get a failure every 1000 (or so)
-    // repetitions of the unit test, with the result of solve() filled with large values of the order
-    // of 1/(size*epsilon).
-    if(biggest_col_sq_norm < threshold_helper * RealScalar(rows-k))
-    {
+    // Track the number of meaningful pivots but do not stop the decomposition to make
+    // sure that the initial matrix is properly reproduced. See bug 941.
+    if(m_nonzero_pivots==size && biggest_col_sq_norm < threshold_helper * RealScalar(rows-k))
       m_nonzero_pivots = k;
-      m_hCoeffs.tail(size-k).setZero();
-      m_qr.bottomRightCorner(rows-k,cols-k)
-          .template triangularView<StrictlyLower>()
-          .setZero();
-      break;
-    }
 
     // apply the transposition to the columns
     m_colsTranspositions.coeffRef(k) = biggest_col_index;
     if(k != biggest_col_index) {
       m_qr.col(k).swap(m_qr.col(biggest_col_index));
-      std::swap(m_colSqNorms.coeffRef(k), m_colSqNorms.coeffRef(biggest_col_index));
+      std::swap(m_colNormsUpdated.coeffRef(k), m_colNormsUpdated.coeffRef(biggest_col_index));
+      std::swap(m_colNormsDirect.coeffRef(k), m_colNormsDirect.coeffRef(biggest_col_index));
       ++number_of_transpositions;
     }
 
     // generate the householder vector, store it below the diagonal
     RealScalar beta;
@@ -498,72 +545,98 @@
 
     // apply the householder transformation
     m_qr.bottomRightCorner(rows-k, cols-k-1)
         .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), m_hCoeffs.coeffRef(k), &m_temp.coeffRef(k+1));
 
-    // update our table of squared norms of the columns
-    m_colSqNorms.tail(cols-k-1) -= m_qr.row(k).tail(cols-k-1).cwiseAbs2();
+    // update our table of norms of the columns
+    for (Index j = k + 1; j < cols; ++j) {
+      // The following implements the stable norm downgrade step discussed in
+      // http://www.netlib.org/lapack/lawnspdf/lawn176.pdf
+      // and used in LAPACK routines xGEQPF and xGEQP3.
+      // See lines 278-297 in http://www.netlib.org/lapack/explore-html/dc/df4/sgeqpf_8f_source.html
+      if (m_colNormsUpdated.coeffRef(j) != RealScalar(0)) {
+        RealScalar temp = abs(m_qr.coeffRef(k, j)) / m_colNormsUpdated.coeffRef(j);
+        temp = (RealScalar(1) + temp) * (RealScalar(1) - temp);
+        temp = temp <  RealScalar(0) ? RealScalar(0) : temp;
+        RealScalar temp2 = temp * numext::abs2<RealScalar>(m_colNormsUpdated.coeffRef(j) /
+                                                           m_colNormsDirect.coeffRef(j));
+        if (temp2 <= norm_downdate_threshold) {
+          // The updated norm has become too inaccurate so re-compute the column
+          // norm directly.
+          m_colNormsDirect.coeffRef(j) = m_qr.col(j).tail(rows - k - 1).norm();
+          m_colNormsUpdated.coeffRef(j) = m_colNormsDirect.coeffRef(j);
+        } else {
+          m_colNormsUpdated.coeffRef(j) *= numext::sqrt(temp);
+        }
+      }
+    }
   }
 
   m_colsPermutation.setIdentity(PermIndexType(cols));
-  for(PermIndexType k = 0; k < m_nonzero_pivots; ++k)
+  for(PermIndexType k = 0; k < size/*m_nonzero_pivots*/; ++k)
     m_colsPermutation.applyTranspositionOnTheRight(k, PermIndexType(m_colsTranspositions.coeff(k)));
 
   m_det_pq = (number_of_transpositions%2) ? -1 : 1;
   m_isInitialized = true;
+}
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename _MatrixType>
+template<typename RhsType, typename DstType>
+void ColPivHouseholderQR<_MatrixType>::_solve_impl(const RhsType &rhs, DstType &dst) const
+{
+  eigen_assert(rhs.rows() == rows());
+
+  const Index nonzero_pivots = nonzeroPivots();
+
+  if(nonzero_pivots == 0)
+  {
+    dst.setZero();
+    return;
+  }
+
+  typename RhsType::PlainObject c(rhs);
+
+  // Note that the matrix Q = H_0^* H_1^*... so its inverse is Q^* = (H_0 H_1 ...)^T
+  c.applyOnTheLeft(householderSequence(m_qr, m_hCoeffs)
+                    .setLength(nonzero_pivots)
+                    .transpose()
+    );
+
+  m_qr.topLeftCorner(nonzero_pivots, nonzero_pivots)
+      .template triangularView<Upper>()
+      .solveInPlace(c.topRows(nonzero_pivots));
 
-  return *this;
+  for(Index i = 0; i < nonzero_pivots; ++i) dst.row(m_colsPermutation.indices().coeff(i)) = c.row(i);
+  for(Index i = nonzero_pivots; i < cols(); ++i) dst.row(m_colsPermutation.indices().coeff(i)).setZero();
 }
+#endif
 
 namespace internal {
 
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<ColPivHouseholderQR<_MatrixType>, Rhs>
-  : solve_retval_base<ColPivHouseholderQR<_MatrixType>, Rhs>
-{
-  EIGEN_MAKE_SOLVE_HELPERS(ColPivHouseholderQR<_MatrixType>,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    eigen_assert(rhs().rows() == dec().rows());
-
-    const Index cols = dec().cols(),
-				nonzero_pivots = dec().nonzeroPivots();
-
-    if(nonzero_pivots == 0)
-    {
-      dst.setZero();
-      return;
-    }
-
-    typename Rhs::PlainObject c(rhs());
-
-    // Note that the matrix Q = H_0^* H_1^*... so its inverse is Q^* = (H_0 H_1 ...)^T
-    c.applyOnTheLeft(householderSequence(dec().matrixQR(), dec().hCoeffs())
-                     .setLength(dec().nonzeroPivots())
-		     .transpose()
-      );
-
-    dec().matrixR()
-       .topLeftCorner(nonzero_pivots, nonzero_pivots)
-       .template triangularView<Upper>()
-       .solveInPlace(c.topRows(nonzero_pivots));
-
-    for(Index i = 0; i < nonzero_pivots; ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
-    for(Index i = nonzero_pivots; i < cols; ++i) dst.row(dec().colsPermutation().indices().coeff(i)).setZero();
+template<typename DstXprType, typename MatrixType>
+struct Assignment<DstXprType, Inverse<ColPivHouseholderQR<MatrixType> >, internal::assign_op<typename DstXprType::Scalar,typename ColPivHouseholderQR<MatrixType>::Scalar>, Dense2Dense>
+{
+  typedef ColPivHouseholderQR<MatrixType> QrType;
+  typedef Inverse<QrType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename QrType::Scalar> &)
+  {
+    dst = src.nestedExpression().solve(MatrixType::Identity(src.rows(), src.cols()));
   }
 };
 
 } // end namespace internal
 
-/** \returns the matrix Q as a sequence of householder transformations */
+/** \returns the matrix Q as a sequence of householder transformations.
+  * You can extract the meaningful part only by using:
+  * \code qr.householderQ().setLength(qr.nonzeroPivots()) \endcode*/
 template<typename MatrixType>
 typename ColPivHouseholderQR<MatrixType>::HouseholderSequenceType ColPivHouseholderQR<MatrixType>
   ::householderQ() const
 {
   eigen_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
-  return HouseholderSequenceType(m_qr, m_hCoeffs.conjugate()).setLength(m_nonzero_pivots);
+  return HouseholderSequenceType(m_qr, m_hCoeffs.conjugate());
 }
 
 /** \return the column-pivoting Householder QR decomposition of \c *this.
   *
   * \sa class ColPivHouseholderQR

ADDED   3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR_LAPACKE.h
Index: 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR_LAPACKE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR_LAPACKE.h
+++ 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR_LAPACKE.h
@@ -0,0 +1,97 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to LAPACKe
+ *    Householder QR decomposition of a matrix with column pivoting based on
+ *    LAPACKE_?geqp3 function.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_COLPIVOTINGHOUSEHOLDERQR_LAPACKE_H
+#define EIGEN_COLPIVOTINGHOUSEHOLDERQR_LAPACKE_H
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by LAPACKe */
+
+#define EIGEN_LAPACKE_QR_COLPIV(EIGTYPE, LAPACKE_TYPE, LAPACKE_PREFIX, EIGCOLROW, LAPACKE_COLROW) \
+template<> template<typename InputType> inline \
+ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >& \
+ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >::compute( \
+              const EigenBase<InputType>& matrix) \
+\
+{ \
+  using std::abs; \
+  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \
+  typedef MatrixType::RealScalar RealScalar; \
+  Index rows = matrix.rows();\
+  Index cols = matrix.cols();\
+\
+  m_qr = matrix;\
+  Index size = m_qr.diagonalSize();\
+  m_hCoeffs.resize(size);\
+\
+  m_colsTranspositions.resize(cols);\
+  /*Index number_of_transpositions = 0;*/ \
+\
+  m_nonzero_pivots = 0; \
+  m_maxpivot = RealScalar(0);\
+  m_colsPermutation.resize(cols); \
+  m_colsPermutation.indices().setZero(); \
+\
+  lapack_int lda = internal::convert_index<lapack_int,Index>(m_qr.outerStride()); \
+  lapack_int matrix_order = LAPACKE_COLROW; \
+  LAPACKE_##LAPACKE_PREFIX##geqp3( matrix_order, internal::convert_index<lapack_int,Index>(rows), internal::convert_index<lapack_int,Index>(cols), \
+                              (LAPACKE_TYPE*)m_qr.data(), lda, (lapack_int*)m_colsPermutation.indices().data(), (LAPACKE_TYPE*)m_hCoeffs.data()); \
+  m_isInitialized = true; \
+  m_maxpivot=m_qr.diagonal().cwiseAbs().maxCoeff(); \
+  m_hCoeffs.adjointInPlace(); \
+  RealScalar premultiplied_threshold = abs(m_maxpivot) * threshold(); \
+  lapack_int *perm = m_colsPermutation.indices().data(); \
+  for(Index i=0;i<size;i++) { \
+    m_nonzero_pivots += (abs(m_qr.coeff(i,i)) > premultiplied_threshold);\
+  } \
+  for(Index i=0;i<cols;i++) perm[i]--;\
+\
+  /*m_det_pq = (number_of_transpositions%2) ? -1 : 1;  // TODO: It's not needed now; fix upon availability in Eigen */ \
+\
+  return *this; \
+}
+
+EIGEN_LAPACKE_QR_COLPIV(double,   double,        d, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_QR_COLPIV(float,    float,         s, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_QR_COLPIV(dcomplex, lapack_complex_double, z, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_QR_COLPIV(scomplex, lapack_complex_float,  c, ColMajor, LAPACK_COL_MAJOR)
+
+EIGEN_LAPACKE_QR_COLPIV(double,   double,        d, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_QR_COLPIV(float,    float,         s, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_QR_COLPIV(dcomplex, lapack_complex_double, z, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_QR_COLPIV(scomplex, lapack_complex_float,  c, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_COLPIVOTINGHOUSEHOLDERQR_LAPACKE_H

DELETED 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h
Index: 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h
+++ 3rd_party/eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h
@@ -1,99 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *    Householder QR decomposition of a matrix with column pivoting based on
- *    LAPACKE_?geqp3 function.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_COLPIVOTINGHOUSEHOLDERQR_MKL_H
-#define EIGEN_COLPIVOTINGHOUSEHOLDERQR_MKL_H
-
-#include "Eigen/src/Core/util/MKL_support.h"
-
-namespace Eigen { 
-
-/** \internal Specialization for the data types supported by MKL */
-
-#define EIGEN_MKL_QR_COLPIV(EIGTYPE, MKLTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
-template<> inline \
-ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >& \
-ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >::compute( \
-              const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix) \
-\
-{ \
-  using std::abs; \
-  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \
-  typedef MatrixType::Scalar Scalar; \
-  typedef MatrixType::RealScalar RealScalar; \
-  Index rows = matrix.rows();\
-  Index cols = matrix.cols();\
-  Index size = matrix.diagonalSize();\
-\
-  m_qr = matrix;\
-  m_hCoeffs.resize(size);\
-\
-  m_colsTranspositions.resize(cols);\
-  /*Index number_of_transpositions = 0;*/ \
-\
-  m_nonzero_pivots = 0; \
-  m_maxpivot = RealScalar(0);\
-  m_colsPermutation.resize(cols); \
-  m_colsPermutation.indices().setZero(); \
-\
-  lapack_int lda = m_qr.outerStride(), i; \
-  lapack_int matrix_order = MKLCOLROW; \
-  LAPACKE_##MKLPREFIX##geqp3( matrix_order, rows, cols, (MKLTYPE*)m_qr.data(), lda, (lapack_int*)m_colsPermutation.indices().data(), (MKLTYPE*)m_hCoeffs.data()); \
-  m_isInitialized = true; \
-  m_maxpivot=m_qr.diagonal().cwiseAbs().maxCoeff(); \
-  m_hCoeffs.adjointInPlace(); \
-  RealScalar premultiplied_threshold = abs(m_maxpivot) * threshold(); \
-  lapack_int *perm = m_colsPermutation.indices().data(); \
-  for(i=0;i<size;i++) { \
-    m_nonzero_pivots += (abs(m_qr.coeff(i,i)) > premultiplied_threshold);\
-  } \
-  for(i=0;i<cols;i++) perm[i]--;\
-\
-  /*m_det_pq = (number_of_transpositions%2) ? -1 : 1;  // TODO: It's not needed now; fix upon availability in Eigen */ \
-\
-  return *this; \
-}
-
-EIGEN_MKL_QR_COLPIV(double,   double,        d, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_QR_COLPIV(float,    float,         s, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_QR_COLPIV(dcomplex, MKL_Complex16, z, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_QR_COLPIV(scomplex, MKL_Complex8,  c, ColMajor, LAPACK_COL_MAJOR)
-
-EIGEN_MKL_QR_COLPIV(double,   double,        d, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_QR_COLPIV(float,    float,         s, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_QR_COLPIV(dcomplex, MKL_Complex16, z, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_QR_COLPIV(scomplex, MKL_Complex8,  c, RowMajor, LAPACK_ROW_MAJOR)
-
-} // end namespace Eigen
-
-#endif // EIGEN_COLPIVOTINGHOUSEHOLDERQR_MKL_H

ADDED   3rd_party/eigen/Eigen/src/QR/CompleteOrthogonalDecomposition.h
Index: 3rd_party/eigen/Eigen/src/QR/CompleteOrthogonalDecomposition.h
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/CompleteOrthogonalDecomposition.h
+++ 3rd_party/eigen/Eigen/src/QR/CompleteOrthogonalDecomposition.h
@@ -0,0 +1,562 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Rasmus Munk Larsen <rmlarsen@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_COMPLETEORTHOGONALDECOMPOSITION_H
+#define EIGEN_COMPLETEORTHOGONALDECOMPOSITION_H
+
+namespace Eigen {
+
+namespace internal {
+template <typename _MatrixType>
+struct traits<CompleteOrthogonalDecomposition<_MatrixType> >
+    : traits<_MatrixType> {
+  enum { Flags = 0 };
+};
+
+}  // end namespace internal
+
+/** \ingroup QR_Module
+  *
+  * \class CompleteOrthogonalDecomposition
+  *
+  * \brief Complete orthogonal decomposition (COD) of a matrix.
+  *
+  * \param MatrixType the type of the matrix of which we are computing the COD.
+  *
+  * This class performs a rank-revealing complete orthogonal decomposition of a
+  * matrix  \b A into matrices \b P, \b Q, \b T, and \b Z such that
+  * \f[
+  *  \mathbf{A} \, \mathbf{P} = \mathbf{Q} \,
+  *                     \begin{bmatrix} \mathbf{T} &  \mathbf{0} \\
+  *                                     \mathbf{0} & \mathbf{0} \end{bmatrix} \, \mathbf{Z}
+  * \f]
+  * by using Householder transformations. Here, \b P is a permutation matrix,
+  * \b Q and \b Z are unitary matrices and \b T an upper triangular matrix of
+  * size rank-by-rank. \b A may be rank deficient.
+  *
+  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
+  * 
+  * \sa MatrixBase::completeOrthogonalDecomposition()
+  */
+template <typename _MatrixType>
+class CompleteOrthogonalDecomposition {
+ public:
+  typedef _MatrixType MatrixType;
+  enum {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+  };
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename MatrixType::StorageIndex StorageIndex;
+  typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
+  typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime>
+      PermutationType;
+  typedef typename internal::plain_row_type<MatrixType, Index>::type
+      IntRowVectorType;
+  typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
+  typedef typename internal::plain_row_type<MatrixType, RealScalar>::type
+      RealRowVectorType;
+  typedef HouseholderSequence<
+      MatrixType, typename internal::remove_all<
+                      typename HCoeffsType::ConjugateReturnType>::type>
+      HouseholderSequenceType;
+  typedef typename MatrixType::PlainObject PlainObject;
+
+ private:
+  typedef typename PermutationType::Index PermIndexType;
+
+ public:
+  /**
+   * \brief Default Constructor.
+   *
+   * The default constructor is useful in cases in which the user intends to
+   * perform decompositions via
+   * \c CompleteOrthogonalDecomposition::compute(const* MatrixType&).
+   */
+  CompleteOrthogonalDecomposition() : m_cpqr(), m_zCoeffs(), m_temp() {}
+
+  /** \brief Default Constructor with memory preallocation
+   *
+   * Like the default constructor but with preallocation of the internal data
+   * according to the specified problem \a size.
+   * \sa CompleteOrthogonalDecomposition()
+   */
+  CompleteOrthogonalDecomposition(Index rows, Index cols)
+      : m_cpqr(rows, cols), m_zCoeffs((std::min)(rows, cols)), m_temp(cols) {}
+
+  /** \brief Constructs a complete orthogonal decomposition from a given
+   * matrix.
+   *
+   * This constructor computes the complete orthogonal decomposition of the
+   * matrix \a matrix by calling the method compute(). The default
+   * threshold for rank determination will be used. It is a short cut for:
+   *
+   * \code
+   * CompleteOrthogonalDecomposition<MatrixType> cod(matrix.rows(),
+   *                                                 matrix.cols());
+   * cod.setThreshold(Default);
+   * cod.compute(matrix);
+   * \endcode
+   *
+   * \sa compute()
+   */
+  template <typename InputType>
+  explicit CompleteOrthogonalDecomposition(const EigenBase<InputType>& matrix)
+      : m_cpqr(matrix.rows(), matrix.cols()),
+        m_zCoeffs((std::min)(matrix.rows(), matrix.cols())),
+        m_temp(matrix.cols())
+  {
+    compute(matrix.derived());
+  }
+
+  /** \brief Constructs a complete orthogonal decomposition from a given matrix
+    *
+    * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when \c MatrixType is a Eigen::Ref.
+    *
+    * \sa CompleteOrthogonalDecomposition(const EigenBase&)
+    */
+  template<typename InputType>
+  explicit CompleteOrthogonalDecomposition(EigenBase<InputType>& matrix)
+    : m_cpqr(matrix.derived()),
+      m_zCoeffs((std::min)(matrix.rows(), matrix.cols())),
+      m_temp(matrix.cols())
+  {
+    computeInPlace();
+  }
+
+
+  /** This method computes the minimum-norm solution X to a least squares
+   * problem \f[\mathrm{minimize} \|A X - B\|, \f] where \b A is the matrix of
+   * which \c *this is the complete orthogonal decomposition.
+   *
+   * \param b the right-hand sides of the problem to solve.
+   *
+   * \returns a solution.
+   *
+   */
+  template <typename Rhs>
+  inline const Solve<CompleteOrthogonalDecomposition, Rhs> solve(
+      const MatrixBase<Rhs>& b) const {
+    eigen_assert(m_cpqr.m_isInitialized &&
+                 "CompleteOrthogonalDecomposition is not initialized.");
+    return Solve<CompleteOrthogonalDecomposition, Rhs>(*this, b.derived());
+  }
+
+  HouseholderSequenceType householderQ(void) const;
+  HouseholderSequenceType matrixQ(void) const { return m_cpqr.householderQ(); }
+
+  /** \returns the matrix \b Z.
+   */
+  MatrixType matrixZ() const {
+    MatrixType Z = MatrixType::Identity(m_cpqr.cols(), m_cpqr.cols());
+    applyZAdjointOnTheLeftInPlace(Z);
+    return Z.adjoint();
+  }
+
+  /** \returns a reference to the matrix where the complete orthogonal
+   * decomposition is stored
+   */
+  const MatrixType& matrixQTZ() const { return m_cpqr.matrixQR(); }
+
+  /** \returns a reference to the matrix where the complete orthogonal
+   * decomposition is stored.
+   * \warning The strict lower part and \code cols() - rank() \endcode right
+   * columns of this matrix contains internal values.
+   * Only the upper triangular part should be referenced. To get it, use
+   * \code matrixT().template triangularView<Upper>() \endcode
+   * For rank-deficient matrices, use
+   * \code
+   * matrixR().topLeftCorner(rank(), rank()).template triangularView<Upper>()
+   * \endcode
+   */
+  const MatrixType& matrixT() const { return m_cpqr.matrixQR(); }
+
+  template <typename InputType>
+  CompleteOrthogonalDecomposition& compute(const EigenBase<InputType>& matrix) {
+    // Compute the column pivoted QR factorization A P = Q R.
+    m_cpqr.compute(matrix);
+    computeInPlace();
+    return *this;
+  }
+
+  /** \returns a const reference to the column permutation matrix */
+  const PermutationType& colsPermutation() const {
+    return m_cpqr.colsPermutation();
+  }
+
+  /** \returns the absolute value of the determinant of the matrix of which
+   * *this is the complete orthogonal decomposition. It has only linear
+   * complexity (that is, O(n) where n is the dimension of the square matrix)
+   * as the complete orthogonal decomposition has already been computed.
+   *
+   * \note This is only for square matrices.
+   *
+   * \warning a determinant can be very big or small, so for matrices
+   * of large enough dimension, there is a risk of overflow/underflow.
+   * One way to work around that is to use logAbsDeterminant() instead.
+   *
+   * \sa logAbsDeterminant(), MatrixBase::determinant()
+   */
+  typename MatrixType::RealScalar absDeterminant() const;
+
+  /** \returns the natural log of the absolute value of the determinant of the
+   * matrix of which *this is the complete orthogonal decomposition. It has
+   * only linear complexity (that is, O(n) where n is the dimension of the
+   * square matrix) as the complete orthogonal decomposition has already been
+   * computed.
+   *
+   * \note This is only for square matrices.
+   *
+   * \note This method is useful to work around the risk of overflow/underflow
+   * that's inherent to determinant computation.
+   *
+   * \sa absDeterminant(), MatrixBase::determinant()
+   */
+  typename MatrixType::RealScalar logAbsDeterminant() const;
+
+  /** \returns the rank of the matrix of which *this is the complete orthogonal
+   * decomposition.
+   *
+   * \note This method has to determine which pivots should be considered
+   * nonzero. For that, it uses the threshold value that you can control by
+   * calling setThreshold(const RealScalar&).
+   */
+  inline Index rank() const { return m_cpqr.rank(); }
+
+  /** \returns the dimension of the kernel of the matrix of which *this is the
+   * complete orthogonal decomposition.
+   *
+   * \note This method has to determine which pivots should be considered
+   * nonzero. For that, it uses the threshold value that you can control by
+   * calling setThreshold(const RealScalar&).
+   */
+  inline Index dimensionOfKernel() const { return m_cpqr.dimensionOfKernel(); }
+
+  /** \returns true if the matrix of which *this is the decomposition represents
+   * an injective linear map, i.e. has trivial kernel; false otherwise.
+   *
+   * \note This method has to determine which pivots should be considered
+   * nonzero. For that, it uses the threshold value that you can control by
+   * calling setThreshold(const RealScalar&).
+   */
+  inline bool isInjective() const { return m_cpqr.isInjective(); }
+
+  /** \returns true if the matrix of which *this is the decomposition represents
+   * a surjective linear map; false otherwise.
+   *
+   * \note This method has to determine which pivots should be considered
+   * nonzero. For that, it uses the threshold value that you can control by
+   * calling setThreshold(const RealScalar&).
+   */
+  inline bool isSurjective() const { return m_cpqr.isSurjective(); }
+
+  /** \returns true if the matrix of which *this is the complete orthogonal
+   * decomposition is invertible.
+   *
+   * \note This method has to determine which pivots should be considered
+   * nonzero. For that, it uses the threshold value that you can control by
+   * calling setThreshold(const RealScalar&).
+   */
+  inline bool isInvertible() const { return m_cpqr.isInvertible(); }
+
+  /** \returns the pseudo-inverse of the matrix of which *this is the complete
+   * orthogonal decomposition.
+   * \warning: Do not compute \c this->pseudoInverse()*rhs to solve a linear systems.
+   * It is more efficient and numerically stable to call \c this->solve(rhs).
+   */
+  inline const Inverse<CompleteOrthogonalDecomposition> pseudoInverse() const
+  {
+    return Inverse<CompleteOrthogonalDecomposition>(*this);
+  }
+
+  inline Index rows() const { return m_cpqr.rows(); }
+  inline Index cols() const { return m_cpqr.cols(); }
+
+  /** \returns a const reference to the vector of Householder coefficients used
+   * to represent the factor \c Q.
+   *
+   * For advanced uses only.
+   */
+  inline const HCoeffsType& hCoeffs() const { return m_cpqr.hCoeffs(); }
+
+  /** \returns a const reference to the vector of Householder coefficients
+   * used to represent the factor \c Z.
+   *
+   * For advanced uses only.
+   */
+  const HCoeffsType& zCoeffs() const { return m_zCoeffs; }
+
+  /** Allows to prescribe a threshold to be used by certain methods, such as
+   * rank(), who need to determine when pivots are to be considered nonzero.
+   * Most be called before calling compute().
+   *
+   * When it needs to get the threshold value, Eigen calls threshold(). By
+   * default, this uses a formula to automatically determine a reasonable
+   * threshold. Once you have called the present method
+   * setThreshold(const RealScalar&), your value is used instead.
+   *
+   * \param threshold The new value to use as the threshold.
+   *
+   * A pivot will be considered nonzero if its absolute value is strictly
+   * greater than
+   *  \f$ \vert pivot \vert \leqslant threshold \times \vert maxpivot \vert \f$
+   * where maxpivot is the biggest pivot.
+   *
+   * If you want to come back to the default behavior, call
+   * setThreshold(Default_t)
+   */
+  CompleteOrthogonalDecomposition& setThreshold(const RealScalar& threshold) {
+    m_cpqr.setThreshold(threshold);
+    return *this;
+  }
+
+  /** Allows to come back to the default behavior, letting Eigen use its default
+   * formula for determining the threshold.
+   *
+   * You should pass the special object Eigen::Default as parameter here.
+   * \code qr.setThreshold(Eigen::Default); \endcode
+   *
+   * See the documentation of setThreshold(const RealScalar&).
+   */
+  CompleteOrthogonalDecomposition& setThreshold(Default_t) {
+    m_cpqr.setThreshold(Default);
+    return *this;
+  }
+
+  /** Returns the threshold that will be used by certain methods such as rank().
+   *
+   * See the documentation of setThreshold(const RealScalar&).
+   */
+  RealScalar threshold() const { return m_cpqr.threshold(); }
+
+  /** \returns the number of nonzero pivots in the complete orthogonal
+   * decomposition. Here nonzero is meant in the exact sense, not in a
+   * fuzzy sense. So that notion isn't really intrinsically interesting,
+   * but it is still useful when implementing algorithms.
+   *
+   * \sa rank()
+   */
+  inline Index nonzeroPivots() const { return m_cpqr.nonzeroPivots(); }
+
+  /** \returns the absolute value of the biggest pivot, i.e. the biggest
+   *          diagonal coefficient of R.
+   */
+  inline RealScalar maxPivot() const { return m_cpqr.maxPivot(); }
+
+  /** \brief Reports whether the complete orthogonal decomposition was
+   * succesful.
+   *
+   * \note This function always returns \c Success. It is provided for
+   * compatibility
+   * with other factorization routines.
+   * \returns \c Success
+   */
+  ComputationInfo info() const {
+    eigen_assert(m_cpqr.m_isInitialized && "Decomposition is not initialized.");
+    return Success;
+  }
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+  template <typename RhsType, typename DstType>
+  EIGEN_DEVICE_FUNC void _solve_impl(const RhsType& rhs, DstType& dst) const;
+#endif
+
+ protected:
+  static void check_template_parameters() {
+    EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+  }
+
+  void computeInPlace();
+
+  /** Overwrites \b rhs with \f$ \mathbf{Z}^* * \mathbf{rhs} \f$.
+   */
+  template <typename Rhs>
+  void applyZAdjointOnTheLeftInPlace(Rhs& rhs) const;
+
+  ColPivHouseholderQR<MatrixType> m_cpqr;
+  HCoeffsType m_zCoeffs;
+  RowVectorType m_temp;
+};
+
+template <typename MatrixType>
+typename MatrixType::RealScalar
+CompleteOrthogonalDecomposition<MatrixType>::absDeterminant() const {
+  return m_cpqr.absDeterminant();
+}
+
+template <typename MatrixType>
+typename MatrixType::RealScalar
+CompleteOrthogonalDecomposition<MatrixType>::logAbsDeterminant() const {
+  return m_cpqr.logAbsDeterminant();
+}
+
+/** Performs the complete orthogonal decomposition of the given matrix \a
+ * matrix. The result of the factorization is stored into \c *this, and a
+ * reference to \c *this is returned.
+ *
+ * \sa class CompleteOrthogonalDecomposition,
+ * CompleteOrthogonalDecomposition(const MatrixType&)
+ */
+template <typename MatrixType>
+void CompleteOrthogonalDecomposition<MatrixType>::computeInPlace()
+{
+  check_template_parameters();
+
+  // the column permutation is stored as int indices, so just to be sure:
+  eigen_assert(m_cpqr.cols() <= NumTraits<int>::highest());
+
+  const Index rank = m_cpqr.rank();
+  const Index cols = m_cpqr.cols();
+  const Index rows = m_cpqr.rows();
+  m_zCoeffs.resize((std::min)(rows, cols));
+  m_temp.resize(cols);
+
+  if (rank < cols) {
+    // We have reduced the (permuted) matrix to the form
+    //   [R11 R12]
+    //   [ 0  R22]
+    // where R11 is r-by-r (r = rank) upper triangular, R12 is
+    // r-by-(n-r), and R22 is empty or the norm of R22 is negligible.
+    // We now compute the complete orthogonal decomposition by applying
+    // Householder transformations from the right to the upper trapezoidal
+    // matrix X = [R11 R12] to zero out R12 and obtain the factorization
+    // [R11 R12] = [T11 0] * Z, where T11 is r-by-r upper triangular and
+    // Z = Z(0) * Z(1) ... Z(r-1) is an n-by-n orthogonal matrix.
+    // We store the data representing Z in R12 and m_zCoeffs.
+    for (Index k = rank - 1; k >= 0; --k) {
+      if (k != rank - 1) {
+        // Given the API for Householder reflectors, it is more convenient if
+        // we swap the leading parts of columns k and r-1 (zero-based) to form
+        // the matrix X_k = [X(0:k, k), X(0:k, r:n)]
+        m_cpqr.m_qr.col(k).head(k + 1).swap(
+            m_cpqr.m_qr.col(rank - 1).head(k + 1));
+      }
+      // Construct Householder reflector Z(k) to zero out the last row of X_k,
+      // i.e. choose Z(k) such that
+      // [X(k, k), X(k, r:n)] * Z(k) = [beta, 0, .., 0].
+      RealScalar beta;
+      m_cpqr.m_qr.row(k)
+          .tail(cols - rank + 1)
+          .makeHouseholderInPlace(m_zCoeffs(k), beta);
+      m_cpqr.m_qr(k, rank - 1) = beta;
+      if (k > 0) {
+        // Apply Z(k) to the first k rows of X_k
+        m_cpqr.m_qr.topRightCorner(k, cols - rank + 1)
+            .applyHouseholderOnTheRight(
+                m_cpqr.m_qr.row(k).tail(cols - rank).transpose(), m_zCoeffs(k),
+                &m_temp(0));
+      }
+      if (k != rank - 1) {
+        // Swap X(0:k,k) back to its proper location.
+        m_cpqr.m_qr.col(k).head(k + 1).swap(
+            m_cpqr.m_qr.col(rank - 1).head(k + 1));
+      }
+    }
+  }
+}
+
+template <typename MatrixType>
+template <typename Rhs>
+void CompleteOrthogonalDecomposition<MatrixType>::applyZAdjointOnTheLeftInPlace(
+    Rhs& rhs) const {
+  const Index cols = this->cols();
+  const Index nrhs = rhs.cols();
+  const Index rank = this->rank();
+  Matrix<typename MatrixType::Scalar, Dynamic, 1> temp((std::max)(cols, nrhs));
+  for (Index k = 0; k < rank; ++k) {
+    if (k != rank - 1) {
+      rhs.row(k).swap(rhs.row(rank - 1));
+    }
+    rhs.middleRows(rank - 1, cols - rank + 1)
+        .applyHouseholderOnTheLeft(
+            matrixQTZ().row(k).tail(cols - rank).adjoint(), zCoeffs()(k),
+            &temp(0));
+    if (k != rank - 1) {
+      rhs.row(k).swap(rhs.row(rank - 1));
+    }
+  }
+}
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template <typename _MatrixType>
+template <typename RhsType, typename DstType>
+void CompleteOrthogonalDecomposition<_MatrixType>::_solve_impl(
+    const RhsType& rhs, DstType& dst) const {
+  eigen_assert(rhs.rows() == this->rows());
+
+  const Index rank = this->rank();
+  if (rank == 0) {
+    dst.setZero();
+    return;
+  }
+
+  // Compute c = Q^* * rhs
+  // Note that the matrix Q = H_0^* H_1^*... so its inverse is
+  // Q^* = (H_0 H_1 ...)^T
+  typename RhsType::PlainObject c(rhs);
+  c.applyOnTheLeft(
+      householderSequence(matrixQTZ(), hCoeffs()).setLength(rank).transpose());
+
+  // Solve T z = c(1:rank, :)
+  dst.topRows(rank) = matrixT()
+                          .topLeftCorner(rank, rank)
+                          .template triangularView<Upper>()
+                          .solve(c.topRows(rank));
+
+  const Index cols = this->cols();
+  if (rank < cols) {
+    // Compute y = Z^* * [ z ]
+    //                   [ 0 ]
+    dst.bottomRows(cols - rank).setZero();
+    applyZAdjointOnTheLeftInPlace(dst);
+  }
+
+  // Undo permutation to get x = P^{-1} * y.
+  dst = colsPermutation() * dst;
+}
+#endif
+
+namespace internal {
+
+template<typename DstXprType, typename MatrixType>
+struct Assignment<DstXprType, Inverse<CompleteOrthogonalDecomposition<MatrixType> >, internal::assign_op<typename DstXprType::Scalar,typename CompleteOrthogonalDecomposition<MatrixType>::Scalar>, Dense2Dense>
+{
+  typedef CompleteOrthogonalDecomposition<MatrixType> CodType;
+  typedef Inverse<CodType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename CodType::Scalar> &)
+  {
+    dst = src.nestedExpression().solve(MatrixType::Identity(src.rows(), src.rows()));
+  }
+};
+
+} // end namespace internal
+
+/** \returns the matrix Q as a sequence of householder transformations */
+template <typename MatrixType>
+typename CompleteOrthogonalDecomposition<MatrixType>::HouseholderSequenceType
+CompleteOrthogonalDecomposition<MatrixType>::householderQ() const {
+  return m_cpqr.householderQ();
+}
+
+/** \return the complete orthogonal decomposition of \c *this.
+  *
+  * \sa class CompleteOrthogonalDecomposition
+  */
+template <typename Derived>
+const CompleteOrthogonalDecomposition<typename MatrixBase<Derived>::PlainObject>
+MatrixBase<Derived>::completeOrthogonalDecomposition() const {
+  return CompleteOrthogonalDecomposition<PlainObject>(eval());
+}
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_COMPLETEORTHOGONALDECOMPOSITION_H

Index: 3rd_party/eigen/Eigen/src/QR/FullPivHouseholderQR.h
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/FullPivHouseholderQR.h
+++ 3rd_party/eigen/Eigen/src/QR/FullPivHouseholderQR.h
@@ -12,40 +12,48 @@
 #define EIGEN_FULLPIVOTINGHOUSEHOLDERQR_H
 
 namespace Eigen { 
 
 namespace internal {
+
+template<typename _MatrixType> struct traits<FullPivHouseholderQR<_MatrixType> >
+ : traits<_MatrixType>
+{
+  enum { Flags = 0 };
+};
 
 template<typename MatrixType> struct FullPivHouseholderQRMatrixQReturnType;
 
 template<typename MatrixType>
 struct traits<FullPivHouseholderQRMatrixQReturnType<MatrixType> >
 {
   typedef typename MatrixType::PlainObject ReturnType;
 };
 
-}
+} // end namespace internal
 
 /** \ingroup QR_Module
   *
   * \class FullPivHouseholderQR
   *
   * \brief Householder rank-revealing QR decomposition of a matrix with full pivoting
   *
-  * \param MatrixType the type of the matrix of which we are computing the QR decomposition
+  * \tparam _MatrixType the type of the matrix of which we are computing the QR decomposition
   *
-  * This class performs a rank-revealing QR decomposition of a matrix \b A into matrices \b P, \b Q and \b R
+  * This class performs a rank-revealing QR decomposition of a matrix \b A into matrices \b P, \b P', \b Q and \b R
   * such that 
   * \f[
-  *  \mathbf{A} \, \mathbf{P} = \mathbf{Q} \, \mathbf{R}
+  *  \mathbf{P} \, \mathbf{A} \, \mathbf{P}' = \mathbf{Q} \, \mathbf{R}
   * \f]
-  * by using Householder transformations. Here, \b P is a permutation matrix, \b Q a unitary matrix and \b R an 
-  * upper triangular matrix.
+  * by using Householder transformations. Here, \b P and \b P' are permutation matrices, \b Q a unitary matrix 
+  * and \b R an upper triangular matrix.
   *
   * This decomposition performs a very prudent full pivoting in order to be rank-revealing and achieve optimal
   * numerical stability. The trade-off is that it is slower than HouseholderQR and ColPivHouseholderQR.
   *
+  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
+  * 
   * \sa MatrixBase::fullPivHouseholderQr()
   */
 template<typename _MatrixType> class FullPivHouseholderQR
 {
   public:
@@ -52,25 +60,26 @@
 
     typedef _MatrixType MatrixType;
     enum {
       RowsAtCompileTime = MatrixType::RowsAtCompileTime,
       ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      Options = MatrixType::Options,
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
+    // FIXME should be int
+    typedef typename MatrixType::StorageIndex StorageIndex;
     typedef internal::FullPivHouseholderQRMatrixQReturnType<MatrixType> MatrixQReturnType;
     typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
-    typedef Matrix<Index, 1,
+    typedef Matrix<StorageIndex, 1,
                    EIGEN_SIZE_MIN_PREFER_DYNAMIC(ColsAtCompileTime,RowsAtCompileTime), RowMajor, 1,
                    EIGEN_SIZE_MIN_PREFER_FIXED(MaxColsAtCompileTime,MaxRowsAtCompileTime)> IntDiagSizeVectorType;
     typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime> PermutationType;
     typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
     typedef typename internal::plain_col_type<MatrixType>::type ColVectorType;
+    typedef typename MatrixType::PlainObject PlainObject;
 
     /** \brief Default Constructor.
       *
       * The default constructor is useful in cases in which the user intends to
       * perform decompositions via FullPivHouseholderQR::compute(const MatrixType&).
@@ -111,21 +120,42 @@
       * qr.compute(matrix);
       * \endcode
       * 
       * \sa compute()
       */
-    FullPivHouseholderQR(const MatrixType& matrix)
+    template<typename InputType>
+    explicit FullPivHouseholderQR(const EigenBase<InputType>& matrix)
       : m_qr(matrix.rows(), matrix.cols()),
         m_hCoeffs((std::min)(matrix.rows(), matrix.cols())),
         m_rows_transpositions((std::min)(matrix.rows(), matrix.cols())),
         m_cols_transpositions((std::min)(matrix.rows(), matrix.cols())),
         m_cols_permutation(matrix.cols()),
         m_temp(matrix.cols()),
         m_isInitialized(false),
         m_usePrescribedThreshold(false)
     {
-      compute(matrix);
+      compute(matrix.derived());
+    }
+
+    /** \brief Constructs a QR factorization from a given matrix
+      *
+      * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when \c MatrixType is a Eigen::Ref.
+      *
+      * \sa FullPivHouseholderQR(const EigenBase&)
+      */
+    template<typename InputType>
+    explicit FullPivHouseholderQR(EigenBase<InputType>& matrix)
+      : m_qr(matrix.derived()),
+        m_hCoeffs((std::min)(matrix.rows(), matrix.cols())),
+        m_rows_transpositions((std::min)(matrix.rows(), matrix.cols())),
+        m_cols_transpositions((std::min)(matrix.rows(), matrix.cols())),
+        m_cols_permutation(matrix.cols()),
+        m_temp(matrix.cols()),
+        m_isInitialized(false),
+        m_usePrescribedThreshold(false)
+    {
+      computeInPlace();
     }
 
     /** This method finds a solution x to the equation Ax=b, where A is the matrix of which
       * \c *this is the QR decomposition.
       *
@@ -132,26 +162,23 @@
       * \param b the right-hand-side of the equation to solve.
       *
       * \returns the exact or least-square solution if the rank is greater or equal to the number of columns of A,
       * and an arbitrary solution otherwise.
       *
-      * \note The case where b is a matrix is not yet implemented. Also, this
-      *       code is space inefficient.
-      *
       * \note_about_checking_solutions
       *
       * \note_about_arbitrary_choice_of_solution
       *
       * Example: \include FullPivHouseholderQR_solve.cpp
       * Output: \verbinclude FullPivHouseholderQR_solve.out
       */
     template<typename Rhs>
-    inline const internal::solve_retval<FullPivHouseholderQR, Rhs>
+    inline const Solve<FullPivHouseholderQR, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
       eigen_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
-      return internal::solve_retval<FullPivHouseholderQR, Rhs>(*this, b.derived());
+      return Solve<FullPivHouseholderQR, Rhs>(*this, b.derived());
     }
 
     /** \returns Expression object representing the matrix Q
       */
     MatrixQReturnType matrixQ(void) const;
@@ -162,11 +189,12 @@
     {
       eigen_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
       return m_qr;
     }
 
-    FullPivHouseholderQR& compute(const MatrixType& matrix);
+    template<typename InputType>
+    FullPivHouseholderQR& compute(const EigenBase<InputType>& matrix);
 
     /** \returns a const reference to the column permutation matrix */
     const PermutationType& colsPermutation() const
     {
       eigen_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
@@ -278,17 +306,15 @@
 
     /** \returns the inverse of the matrix of which *this is the QR decomposition.
       *
       * \note If this matrix is not invertible, the returned matrix has undefined coefficients.
       *       Use isInvertible() to first determine whether this matrix is invertible.
-      */    inline const
-    internal::solve_retval<FullPivHouseholderQR, typename MatrixType::IdentityReturnType>
-    inverse() const
+      */
+    inline const Inverse<FullPivHouseholderQR> inverse() const
     {
       eigen_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
-      return internal::solve_retval<FullPivHouseholderQR,typename MatrixType::IdentityReturnType>
-               (*this, MatrixType::Identity(m_qr.rows(), m_qr.cols()));
+      return Inverse<FullPivHouseholderQR>(*this);
     }
 
     inline Index rows() const { return m_qr.rows(); }
     inline Index cols() const { return m_qr.cols(); }
     
@@ -364,12 +390,26 @@
 
     /** \returns the absolute value of the biggest pivot, i.e. the biggest
       *          diagonal coefficient of U.
       */
     RealScalar maxPivot() const { return m_maxpivot; }
+    
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl(const RhsType &rhs, DstType &dst) const;
+    #endif
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+    
+    void computeInPlace();
+    
     MatrixType m_qr;
     HCoeffsType m_hCoeffs;
     IntDiagSizeVectorType m_rows_transpositions;
     IntDiagSizeVectorType m_cols_transpositions;
     PermutationType m_cols_permutation;
@@ -403,18 +443,29 @@
   * is returned.
   *
   * \sa class FullPivHouseholderQR, FullPivHouseholderQR(const MatrixType&)
   */
 template<typename MatrixType>
-FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
+template<typename InputType>
+FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(const EigenBase<InputType>& matrix)
+{
+  m_qr = matrix.derived();
+  computeInPlace();
+  return *this;
+}
+
+template<typename MatrixType>
+void FullPivHouseholderQR<MatrixType>::computeInPlace()
 {
+  check_template_parameters();
+
   using std::abs;
-  Index rows = matrix.rows();
-  Index cols = matrix.cols();
+  Index rows = m_qr.rows();
+  Index cols = m_qr.cols();
   Index size = (std::min)(rows,cols);
 
-  m_qr = matrix;
+  
   m_hCoeffs.resize(size);
 
   m_temp.resize(cols);
 
   m_precision = NumTraits<Scalar>::epsilon() * RealScalar(size);
@@ -429,17 +480,19 @@
   m_maxpivot = RealScalar(0);
 
   for (Index k = 0; k < size; ++k)
   {
     Index row_of_biggest_in_corner, col_of_biggest_in_corner;
-    RealScalar biggest_in_corner;
+    typedef internal::scalar_score_coeff_op<Scalar> Scoring;
+    typedef typename Scoring::result_type Score;
 
-    biggest_in_corner = m_qr.bottomRightCorner(rows-k, cols-k)
-                            .cwiseAbs()
-                            .maxCoeff(&row_of_biggest_in_corner, &col_of_biggest_in_corner);
+    Score score = m_qr.bottomRightCorner(rows-k, cols-k)
+                      .unaryExpr(Scoring())
+                      .maxCoeff(&row_of_biggest_in_corner, &col_of_biggest_in_corner);
     row_of_biggest_in_corner += k;
     col_of_biggest_in_corner += k;
+    RealScalar biggest_in_corner = internal::abs_knowing_score<Scalar>()(m_qr(row_of_biggest_in_corner, col_of_biggest_in_corner), score);
     if(k==0) biggest = biggest_in_corner;
 
     // if the corner is negligible, then we have less than full rank, and we can finish early
     if(internal::isMuchSmallerThan(biggest_in_corner, biggest, m_precision))
     {
@@ -479,54 +532,59 @@
   for(Index k = 0; k < size; ++k)
     m_cols_permutation.applyTranspositionOnTheRight(k, m_cols_transpositions.coeff(k));
 
   m_det_pq = (number_of_transpositions%2) ? -1 : 1;
   m_isInitialized = true;
+}
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename _MatrixType>
+template<typename RhsType, typename DstType>
+void FullPivHouseholderQR<_MatrixType>::_solve_impl(const RhsType &rhs, DstType &dst) const
+{
+  eigen_assert(rhs.rows() == rows());
+  const Index l_rank = rank();
+
+  // FIXME introduce nonzeroPivots() and use it here. and more generally,
+  // make the same improvements in this dec as in FullPivLU.
+  if(l_rank==0)
+  {
+    dst.setZero();
+    return;
+  }
+
+  typename RhsType::PlainObject c(rhs);
+
+  Matrix<Scalar,1,RhsType::ColsAtCompileTime> temp(rhs.cols());
+  for (Index k = 0; k < l_rank; ++k)
+  {
+    Index remainingSize = rows()-k;
+    c.row(k).swap(c.row(m_rows_transpositions.coeff(k)));
+    c.bottomRightCorner(remainingSize, rhs.cols())
+      .applyHouseholderOnTheLeft(m_qr.col(k).tail(remainingSize-1),
+                               m_hCoeffs.coeff(k), &temp.coeffRef(0));
+  }
+
+  m_qr.topLeftCorner(l_rank, l_rank)
+      .template triangularView<Upper>()
+      .solveInPlace(c.topRows(l_rank));
 
-  return *this;
+  for(Index i = 0; i < l_rank; ++i) dst.row(m_cols_permutation.indices().coeff(i)) = c.row(i);
+  for(Index i = l_rank; i < cols(); ++i) dst.row(m_cols_permutation.indices().coeff(i)).setZero();
 }
+#endif
 
 namespace internal {
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<FullPivHouseholderQR<_MatrixType>, Rhs>
-  : solve_retval_base<FullPivHouseholderQR<_MatrixType>, Rhs>
-{
-  EIGEN_MAKE_SOLVE_HELPERS(FullPivHouseholderQR<_MatrixType>,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    const Index rows = dec().rows(), cols = dec().cols();
-    eigen_assert(rhs().rows() == rows);
-
-    // FIXME introduce nonzeroPivots() and use it here. and more generally,
-    // make the same improvements in this dec as in FullPivLU.
-    if(dec().rank()==0)
-    {
-      dst.setZero();
-      return;
-    }
-
-    typename Rhs::PlainObject c(rhs());
-
-    Matrix<Scalar,1,Rhs::ColsAtCompileTime> temp(rhs().cols());
-    for (Index k = 0; k < dec().rank(); ++k)
-    {
-      Index remainingSize = rows-k;
-      c.row(k).swap(c.row(dec().rowsTranspositions().coeff(k)));
-      c.bottomRightCorner(remainingSize, rhs().cols())
-       .applyHouseholderOnTheLeft(dec().matrixQR().col(k).tail(remainingSize-1),
-                                  dec().hCoeffs().coeff(k), &temp.coeffRef(0));
-    }
-
-    dec().matrixQR()
-       .topLeftCorner(dec().rank(), dec().rank())
-       .template triangularView<Upper>()
-       .solveInPlace(c.topRows(dec().rank()));
-
-    for(Index i = 0; i < dec().rank(); ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
-    for(Index i = dec().rank(); i < cols; ++i) dst.row(dec().colsPermutation().indices().coeff(i)).setZero();
+  
+template<typename DstXprType, typename MatrixType>
+struct Assignment<DstXprType, Inverse<FullPivHouseholderQR<MatrixType> >, internal::assign_op<typename DstXprType::Scalar,typename FullPivHouseholderQR<MatrixType>::Scalar>, Dense2Dense>
+{
+  typedef FullPivHouseholderQR<MatrixType> QrType;
+  typedef Inverse<QrType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename QrType::Scalar> &)
+  {    
+    dst = src.nestedExpression().solve(MatrixType::Identity(src.rows(), src.cols()));
   }
 };
 
 /** \ingroup QR_Module
   *
@@ -536,11 +594,10 @@
   */
 template<typename MatrixType> struct FullPivHouseholderQRMatrixQReturnType
   : public ReturnByValue<FullPivHouseholderQRMatrixQReturnType<MatrixType> >
 {
 public:
-  typedef typename MatrixType::Index Index;
   typedef typename FullPivHouseholderQR<MatrixType>::IntDiagSizeVectorType IntDiagSizeVectorType;
   typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
   typedef Matrix<typename MatrixType::Scalar, 1, MatrixType::RowsAtCompileTime, RowMajor, 1,
                  MatrixType::MaxRowsAtCompileTime> WorkVectorType;
 
@@ -548,11 +605,11 @@
                                         const HCoeffsType&      hCoeffs,
                                         const IntDiagSizeVectorType& rowsTranspositions)
     : m_qr(qr),
       m_hCoeffs(hCoeffs),
       m_rowsTranspositions(rowsTranspositions)
-      {}
+  {}
 
   template <typename ResultType>
   void evalTo(ResultType& result) const
   {
     const Index rows = m_qr.rows();
@@ -578,18 +635,23 @@
             .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), conj(m_hCoeffs.coeff(k)), &workspace.coeffRef(k));
       result.row(k).swap(result.row(m_rowsTranspositions.coeff(k)));
     }
   }
 
-    Index rows() const { return m_qr.rows(); }
-    Index cols() const { return m_qr.rows(); }
+  Index rows() const { return m_qr.rows(); }
+  Index cols() const { return m_qr.rows(); }
 
 protected:
   typename MatrixType::Nested m_qr;
   typename HCoeffsType::Nested m_hCoeffs;
   typename IntDiagSizeVectorType::Nested m_rowsTranspositions;
 };
+
+// template<typename MatrixType>
+// struct evaluator<FullPivHouseholderQRMatrixQReturnType<MatrixType> >
+//  : public evaluator<ReturnByValue<FullPivHouseholderQRMatrixQReturnType<MatrixType> > >
+// {};
 
 } // end namespace internal
 
 template<typename MatrixType>
 inline typename FullPivHouseholderQR<MatrixType>::MatrixQReturnType FullPivHouseholderQR<MatrixType>::matrixQ() const

Index: 3rd_party/eigen/Eigen/src/QR/HouseholderQR.h
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/HouseholderQR.h
+++ 3rd_party/eigen/Eigen/src/QR/HouseholderQR.h
@@ -19,11 +19,11 @@
   *
   * \class HouseholderQR
   *
   * \brief Householder QR decomposition of a matrix
   *
-  * \param MatrixType the type of the matrix of which we are computing the QR decomposition
+  * \tparam _MatrixType the type of the matrix of which we are computing the QR decomposition
   *
   * This class performs a QR decomposition of a matrix \b A into matrices \b Q and \b R
   * such that 
   * \f[
   *  \mathbf{A} = \mathbf{Q} \, \mathbf{R}
@@ -35,10 +35,12 @@
   * If you want that feature, use FullPivHouseholderQR or ColPivHouseholderQR instead.
   *
   * This Householder QR decomposition is faster, but less numerically stable and less feature-full than
   * FullPivHouseholderQR or ColPivHouseholderQR.
   *
+  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
+  *
   * \sa MatrixBase::householderQr()
   */
 template<typename _MatrixType> class HouseholderQR
 {
   public:
@@ -45,17 +47,17 @@
 
     typedef _MatrixType MatrixType;
     enum {
       RowsAtCompileTime = MatrixType::RowsAtCompileTime,
       ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      Options = MatrixType::Options,
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
+    // FIXME should be int
+    typedef typename MatrixType::StorageIndex StorageIndex;
     typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, (MatrixType::Flags&RowMajorBit) ? RowMajor : ColMajor, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixQType;
     typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
     typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
     typedef HouseholderSequence<MatrixType,typename internal::remove_all<typename HCoeffsType::ConjugateReturnType>::type> HouseholderSequenceType;
 
@@ -89,42 +91,58 @@
       * qr.compute(matrix);
       * \endcode
       * 
       * \sa compute()
       */
-    HouseholderQR(const MatrixType& matrix)
+    template<typename InputType>
+    explicit HouseholderQR(const EigenBase<InputType>& matrix)
       : m_qr(matrix.rows(), matrix.cols()),
         m_hCoeffs((std::min)(matrix.rows(),matrix.cols())),
         m_temp(matrix.cols()),
         m_isInitialized(false)
     {
-      compute(matrix);
+      compute(matrix.derived());
+    }
+
+
+    /** \brief Constructs a QR factorization from a given matrix
+      *
+      * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when
+      * \c MatrixType is a Eigen::Ref.
+      *
+      * \sa HouseholderQR(const EigenBase&)
+      */
+    template<typename InputType>
+    explicit HouseholderQR(EigenBase<InputType>& matrix)
+      : m_qr(matrix.derived()),
+        m_hCoeffs((std::min)(matrix.rows(),matrix.cols())),
+        m_temp(matrix.cols()),
+        m_isInitialized(false)
+    {
+      computeInPlace();
     }
 
     /** This method finds a solution x to the equation Ax=b, where A is the matrix of which
       * *this is the QR decomposition, if any exists.
       *
       * \param b the right-hand-side of the equation to solve.
       *
       * \returns a solution.
       *
-      * \note The case where b is a matrix is not yet implemented. Also, this
-      *       code is space inefficient.
-      *
       * \note_about_checking_solutions
       *
       * \note_about_arbitrary_choice_of_solution
       *
       * Example: \include HouseholderQR_solve.cpp
       * Output: \verbinclude HouseholderQR_solve.out
       */
     template<typename Rhs>
-    inline const internal::solve_retval<HouseholderQR, Rhs>
+    inline const Solve<HouseholderQR, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
       eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
-      return internal::solve_retval<HouseholderQR, Rhs>(*this, b.derived());
+      return Solve<HouseholderQR, Rhs>(*this, b.derived());
     }
 
     /** This method returns an expression of the unitary matrix Q as a sequence of Householder transformations.
       *
       * The returned expression can directly be used to perform matrix products. It can also be assigned to a dense Matrix object.
@@ -146,11 +164,16 @@
     {
         eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
         return m_qr;
     }
 
-    HouseholderQR& compute(const MatrixType& matrix);
+    template<typename InputType>
+    HouseholderQR& compute(const EigenBase<InputType>& matrix) {
+      m_qr = matrix.derived();
+      computeInPlace();
+      return *this;
+    }
 
     /** \returns the absolute value of the determinant of the matrix of which
       * *this is the QR decomposition. It has only linear complexity
       * (that is, O(n) where n is the dimension of the square matrix)
       * as the QR decomposition has already been computed.
@@ -185,12 +208,26 @@
     /** \returns a const reference to the vector of Householder coefficients used to represent the factor \c Q.
       * 
       * For advanced uses only.
       */
     const HCoeffsType& hCoeffs() const { return m_hCoeffs; }
+    
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    void _solve_impl(const RhsType &rhs, DstType &dst) const;
+    #endif
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+
+    void computeInPlace();
+    
     MatrixType m_qr;
     HCoeffsType m_hCoeffs;
     RowVectorType m_temp;
     bool m_isInitialized;
 };
@@ -216,11 +253,10 @@
 
 /** \internal */
 template<typename MatrixQR, typename HCoeffs>
 void householder_qr_inplace_unblocked(MatrixQR& mat, HCoeffs& hCoeffs, typename MatrixQR::Scalar* tempData = 0)
 {
-  typedef typename MatrixQR::Index Index;
   typedef typename MatrixQR::Scalar Scalar;
   typedef typename MatrixQR::RealScalar RealScalar;
   Index rows = mat.rows();
   Index cols = mat.cols();
   Index size = (std::min)(rows,cols);
@@ -249,115 +285,114 @@
         .applyHouseholderOnTheLeft(mat.col(k).tail(remainingRows-1), hCoeffs.coeffRef(k), tempData+k+1);
   }
 }
 
 /** \internal */
-template<typename MatrixQR, typename HCoeffs>
-void householder_qr_inplace_blocked(MatrixQR& mat, HCoeffs& hCoeffs,
-                                       typename MatrixQR::Index maxBlockSize=32,
-                                       typename MatrixQR::Scalar* tempData = 0)
-{
-  typedef typename MatrixQR::Index Index;
-  typedef typename MatrixQR::Scalar Scalar;
-  typedef Block<MatrixQR,Dynamic,Dynamic> BlockType;
-
-  Index rows = mat.rows();
-  Index cols = mat.cols();
-  Index size = (std::min)(rows, cols);
-
-  typedef Matrix<Scalar,Dynamic,1,ColMajor,MatrixQR::MaxColsAtCompileTime,1> TempType;
-  TempType tempVector;
-  if(tempData==0)
-  {
-    tempVector.resize(cols);
-    tempData = tempVector.data();
-  }
-
-  Index blockSize = (std::min)(maxBlockSize,size);
-
-  Index k = 0;
-  for (k = 0; k < size; k += blockSize)
-  {
-    Index bs = (std::min)(size-k,blockSize);  // actual size of the block
-    Index tcols = cols - k - bs;            // trailing columns
-    Index brows = rows-k;                   // rows of the block
-
-    // partition the matrix:
-    //        A00 | A01 | A02
-    // mat  = A10 | A11 | A12
-    //        A20 | A21 | A22
-    // and performs the qr dec of [A11^T A12^T]^T
-    // and update [A21^T A22^T]^T using level 3 operations.
-    // Finally, the algorithm continue on A22
-
-    BlockType A11_21 = mat.block(k,k,brows,bs);
-    Block<HCoeffs,Dynamic,1> hCoeffsSegment = hCoeffs.segment(k,bs);
-
-    householder_qr_inplace_unblocked(A11_21, hCoeffsSegment, tempData);
-
-    if(tcols)
-    {
-      BlockType A21_22 = mat.block(k,k+bs,brows,tcols);
-      apply_block_householder_on_the_left(A21_22,A11_21,hCoeffsSegment.adjoint());
-    }
-  }
-}
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<HouseholderQR<_MatrixType>, Rhs>
-  : solve_retval_base<HouseholderQR<_MatrixType>, Rhs>
-{
-  EIGEN_MAKE_SOLVE_HELPERS(HouseholderQR<_MatrixType>,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    const Index rows = dec().rows(), cols = dec().cols();
-    const Index rank = (std::min)(rows, cols);
-    eigen_assert(rhs().rows() == rows);
-
-    typename Rhs::PlainObject c(rhs());
-
-    // Note that the matrix Q = H_0^* H_1^*... so its inverse is Q^* = (H_0 H_1 ...)^T
-    c.applyOnTheLeft(householderSequence(
-      dec().matrixQR().leftCols(rank),
-      dec().hCoeffs().head(rank)).transpose()
-    );
-
-    dec().matrixQR()
-       .topLeftCorner(rank, rank)
-       .template triangularView<Upper>()
-       .solveInPlace(c.topRows(rank));
-
-    dst.topRows(rank) = c.topRows(rank);
-    dst.bottomRows(cols-rank).setZero();
+template<typename MatrixQR, typename HCoeffs,
+  typename MatrixQRScalar = typename MatrixQR::Scalar,
+  bool InnerStrideIsOne = (MatrixQR::InnerStrideAtCompileTime == 1 && HCoeffs::InnerStrideAtCompileTime == 1)>
+struct householder_qr_inplace_blocked
+{
+  // This is specialized for MKL-supported Scalar types in HouseholderQR_MKL.h
+  static void run(MatrixQR& mat, HCoeffs& hCoeffs, Index maxBlockSize=32,
+      typename MatrixQR::Scalar* tempData = 0)
+  {
+    typedef typename MatrixQR::Scalar Scalar;
+    typedef Block<MatrixQR,Dynamic,Dynamic> BlockType;
+
+    Index rows = mat.rows();
+    Index cols = mat.cols();
+    Index size = (std::min)(rows, cols);
+
+    typedef Matrix<Scalar,Dynamic,1,ColMajor,MatrixQR::MaxColsAtCompileTime,1> TempType;
+    TempType tempVector;
+    if(tempData==0)
+    {
+      tempVector.resize(cols);
+      tempData = tempVector.data();
+    }
+
+    Index blockSize = (std::min)(maxBlockSize,size);
+
+    Index k = 0;
+    for (k = 0; k < size; k += blockSize)
+    {
+      Index bs = (std::min)(size-k,blockSize);  // actual size of the block
+      Index tcols = cols - k - bs;              // trailing columns
+      Index brows = rows-k;                     // rows of the block
+
+      // partition the matrix:
+      //        A00 | A01 | A02
+      // mat  = A10 | A11 | A12
+      //        A20 | A21 | A22
+      // and performs the qr dec of [A11^T A12^T]^T
+      // and update [A21^T A22^T]^T using level 3 operations.
+      // Finally, the algorithm continue on A22
+
+      BlockType A11_21 = mat.block(k,k,brows,bs);
+      Block<HCoeffs,Dynamic,1> hCoeffsSegment = hCoeffs.segment(k,bs);
+
+      householder_qr_inplace_unblocked(A11_21, hCoeffsSegment, tempData);
+
+      if(tcols)
+      {
+        BlockType A21_22 = mat.block(k,k+bs,brows,tcols);
+        apply_block_householder_on_the_left(A21_22,A11_21,hCoeffsSegment, false); // false == backward
+      }
+    }
   }
 };
 
 } // end namespace internal
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename _MatrixType>
+template<typename RhsType, typename DstType>
+void HouseholderQR<_MatrixType>::_solve_impl(const RhsType &rhs, DstType &dst) const
+{
+  const Index rank = (std::min)(rows(), cols());
+  eigen_assert(rhs.rows() == rows());
+
+  typename RhsType::PlainObject c(rhs);
+
+  // Note that the matrix Q = H_0^* H_1^*... so its inverse is Q^* = (H_0 H_1 ...)^T
+  c.applyOnTheLeft(householderSequence(
+    m_qr.leftCols(rank),
+    m_hCoeffs.head(rank)).transpose()
+  );
+
+  m_qr.topLeftCorner(rank, rank)
+      .template triangularView<Upper>()
+      .solveInPlace(c.topRows(rank));
+
+  dst.topRows(rank) = c.topRows(rank);
+  dst.bottomRows(cols()-rank).setZero();
+}
+#endif
 
 /** Performs the QR factorization of the given matrix \a matrix. The result of
   * the factorization is stored into \c *this, and a reference to \c *this
   * is returned.
   *
   * \sa class HouseholderQR, HouseholderQR(const MatrixType&)
   */
 template<typename MatrixType>
-HouseholderQR<MatrixType>& HouseholderQR<MatrixType>::compute(const MatrixType& matrix)
+void HouseholderQR<MatrixType>::computeInPlace()
 {
-  Index rows = matrix.rows();
-  Index cols = matrix.cols();
+  check_template_parameters();
+  
+  Index rows = m_qr.rows();
+  Index cols = m_qr.cols();
   Index size = (std::min)(rows,cols);
 
-  m_qr = matrix;
   m_hCoeffs.resize(size);
 
   m_temp.resize(cols);
 
-  internal::householder_qr_inplace_blocked(m_qr, m_hCoeffs, 48, m_temp.data());
+  internal::householder_qr_inplace_blocked<MatrixType, HCoeffsType>::run(m_qr, m_hCoeffs, 48, m_temp.data());
 
   m_isInitialized = true;
-  return *this;
 }
 
 /** \return the Householder QR decomposition of \c *this.
   *
   * \sa class HouseholderQR

ADDED   3rd_party/eigen/Eigen/src/QR/HouseholderQR_LAPACKE.h
Index: 3rd_party/eigen/Eigen/src/QR/HouseholderQR_LAPACKE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/HouseholderQR_LAPACKE.h
+++ 3rd_party/eigen/Eigen/src/QR/HouseholderQR_LAPACKE.h
@@ -0,0 +1,68 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to LAPACKe
+ *    Householder QR decomposition of a matrix w/o pivoting based on
+ *    LAPACKE_?geqrf function.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_QR_LAPACKE_H
+#define EIGEN_QR_LAPACKE_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/** \internal Specialization for the data types supported by LAPACKe */
+
+#define EIGEN_LAPACKE_QR_NOPIV(EIGTYPE, LAPACKE_TYPE, LAPACKE_PREFIX) \
+template<typename MatrixQR, typename HCoeffs> \
+struct householder_qr_inplace_blocked<MatrixQR, HCoeffs, EIGTYPE, true> \
+{ \
+  static void run(MatrixQR& mat, HCoeffs& hCoeffs, Index = 32, \
+      typename MatrixQR::Scalar* = 0) \
+  { \
+    lapack_int m = (lapack_int) mat.rows(); \
+    lapack_int n = (lapack_int) mat.cols(); \
+    lapack_int lda = (lapack_int) mat.outerStride(); \
+    lapack_int matrix_order = (MatrixQR::IsRowMajor) ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
+    LAPACKE_##LAPACKE_PREFIX##geqrf( matrix_order, m, n, (LAPACKE_TYPE*)mat.data(), lda, (LAPACKE_TYPE*)hCoeffs.data()); \
+    hCoeffs.adjointInPlace(); \
+  } \
+};
+
+EIGEN_LAPACKE_QR_NOPIV(double, double, d)
+EIGEN_LAPACKE_QR_NOPIV(float, float, s)
+EIGEN_LAPACKE_QR_NOPIV(dcomplex, lapack_complex_double, z)
+EIGEN_LAPACKE_QR_NOPIV(scomplex, lapack_complex_float, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_QR_LAPACKE_H

DELETED 3rd_party/eigen/Eigen/src/QR/HouseholderQR_MKL.h
Index: 3rd_party/eigen/Eigen/src/QR/HouseholderQR_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/QR/HouseholderQR_MKL.h
+++ 3rd_party/eigen/Eigen/src/QR/HouseholderQR_MKL.h
@@ -1,69 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *    Householder QR decomposition of a matrix w/o pivoting based on
- *    LAPACKE_?geqrf function.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_QR_MKL_H
-#define EIGEN_QR_MKL_H
-
-#include "Eigen/src/Core/util/MKL_support.h"
-
-namespace Eigen { 
-
-namespace internal {
-
-/** \internal Specialization for the data types supported by MKL */
-
-#define EIGEN_MKL_QR_NOPIV(EIGTYPE, MKLTYPE, MKLPREFIX) \
-template<typename MatrixQR, typename HCoeffs> \
-void householder_qr_inplace_blocked(MatrixQR& mat, HCoeffs& hCoeffs, \
-                                       typename MatrixQR::Index maxBlockSize=32, \
-                                       EIGTYPE* tempData = 0) \
-{ \
-  lapack_int m = mat.rows(); \
-  lapack_int n = mat.cols(); \
-  lapack_int lda = mat.outerStride(); \
-  lapack_int matrix_order = (MatrixQR::IsRowMajor) ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
-  LAPACKE_##MKLPREFIX##geqrf( matrix_order, m, n, (MKLTYPE*)mat.data(), lda, (MKLTYPE*)hCoeffs.data()); \
-  hCoeffs.adjointInPlace(); \
-\
-}
-
-EIGEN_MKL_QR_NOPIV(double, double, d)
-EIGEN_MKL_QR_NOPIV(float, float, s)
-EIGEN_MKL_QR_NOPIV(dcomplex, MKL_Complex16, z)
-EIGEN_MKL_QR_NOPIV(scomplex, MKL_Complex8, c)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_QR_MKL_H

DELETED 3rd_party/eigen/Eigen/src/SPQRSupport/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/SPQRSupport/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/SPQRSupport/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/SPQRSupport/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SPQRSupport_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_SPQRSupport_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SPQRSupport/ COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/SPQRSupport/SuiteSparseQRSupport.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SPQRSupport/SuiteSparseQRSupport.h
+++ 3rd_party/eigen/Eigen/src/SPQRSupport/SuiteSparseQRSupport.h
@@ -1,9 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2012 Desire Nuentsa <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -30,55 +31,58 @@
       typedef typename Derived::PlainObject ReturnType;
     };
   } // End namespace internal
   
 /**
- * \ingroup SPQRSupport_Module
- * \class SPQR
- * \brief Sparse QR factorization based on SuiteSparseQR library
- * 
- * This class is used to perform a multithreaded and multifrontal rank-revealing QR decomposition 
- * of sparse matrices. The result is then used to solve linear leasts_square systems.
- * Clearly, a QR factorization is returned such that A*P = Q*R where :
- * 
- * P is the column permutation. Use colsPermutation() to get it.
- * 
- * Q is the orthogonal matrix represented as Householder reflectors. 
- * Use matrixQ() to get an expression and matrixQ().transpose() to get the transpose.
- * You can then apply it to a vector.
- * 
- * R is the sparse triangular factor. Use matrixQR() to get it as SparseMatrix.
- * NOTE : The Index type of R is always UF_long. You can get it with SPQR::Index
- * 
- * \tparam _MatrixType The type of the sparse matrix A, must be a column-major SparseMatrix<>
- * NOTE 
- * 
- */
+  * \ingroup SPQRSupport_Module
+  * \class SPQR
+  * \brief Sparse QR factorization based on SuiteSparseQR library
+  *
+  * This class is used to perform a multithreaded and multifrontal rank-revealing QR decomposition
+  * of sparse matrices. The result is then used to solve linear leasts_square systems.
+  * Clearly, a QR factorization is returned such that A*P = Q*R where :
+  *
+  * P is the column permutation. Use colsPermutation() to get it.
+  *
+  * Q is the orthogonal matrix represented as Householder reflectors.
+  * Use matrixQ() to get an expression and matrixQ().transpose() to get the transpose.
+  * You can then apply it to a vector.
+  *
+  * R is the sparse triangular factor. Use matrixQR() to get it as SparseMatrix.
+  * NOTE : The Index type of R is always SuiteSparse_long. You can get it with SPQR::Index
+  *
+  * \tparam _MatrixType The type of the sparse matrix A, must be a column-major SparseMatrix<>
+  *
+  * \implsparsesolverconcept
+  *
+  *
+  */
 template<typename _MatrixType>
-class SPQR
+class SPQR : public SparseSolverBase<SPQR<_MatrixType> >
 {
+  protected:
+    typedef SparseSolverBase<SPQR<_MatrixType> > Base;
+    using Base::m_isInitialized;
   public:
     typedef typename _MatrixType::Scalar Scalar;
     typedef typename _MatrixType::RealScalar RealScalar;
-    typedef UF_long Index ; 
-    typedef SparseMatrix<Scalar, ColMajor, Index> MatrixType;
-    typedef PermutationMatrix<Dynamic, Dynamic> PermutationType;
+    typedef SuiteSparse_long StorageIndex ;
+    typedef SparseMatrix<Scalar, ColMajor, StorageIndex> MatrixType;
+    typedef Map<PermutationMatrix<Dynamic, Dynamic, StorageIndex> > PermutationType;
+    enum {
+      ColsAtCompileTime = Dynamic,
+      MaxColsAtCompileTime = Dynamic
+    };
   public:
     SPQR() 
-      : m_isInitialized(false),
-      m_ordering(SPQR_ORDERING_DEFAULT),
-      m_allow_tol(SPQR_DEFAULT_TOL),
-      m_tolerance (NumTraits<Scalar>::epsilon())
+      : m_ordering(SPQR_ORDERING_DEFAULT), m_allow_tol(SPQR_DEFAULT_TOL), m_tolerance (NumTraits<Scalar>::epsilon()), m_useDefaultThreshold(true)
     { 
       cholmod_l_start(&m_cc);
     }
     
-    SPQR(const _MatrixType& matrix) 
-    : m_isInitialized(false),
-      m_ordering(SPQR_ORDERING_DEFAULT),
-      m_allow_tol(SPQR_DEFAULT_TOL),
-      m_tolerance (NumTraits<Scalar>::epsilon())
+    explicit SPQR(const _MatrixType& matrix)
+    : m_ordering(SPQR_ORDERING_DEFAULT), m_allow_tol(SPQR_DEFAULT_TOL), m_tolerance (NumTraits<Scalar>::epsilon()), m_useDefaultThreshold(true)
     {
       cholmod_l_start(&m_cc);
       compute(matrix);
     }
     
@@ -99,19 +103,34 @@
     void compute(const _MatrixType& matrix)
     {
       if(m_isInitialized) SPQR_free();
 
       MatrixType mat(matrix);
+      
+      /* Compute the default threshold as in MatLab, see:
+       * Tim Davis, "Algorithm 915, SuiteSparseQR: Multifrontal Multithreaded Rank-Revealing
+       * Sparse QR Factorization, ACM Trans. on Math. Soft. 38(1), 2011, Page 8:3 
+       */
+      RealScalar pivotThreshold = m_tolerance;
+      if(m_useDefaultThreshold) 
+      {
+        RealScalar max2Norm = 0.0;
+        for (int j = 0; j < mat.cols(); j++) max2Norm = numext::maxi(max2Norm, mat.col(j).norm());
+        if(max2Norm==RealScalar(0))
+          max2Norm = RealScalar(1);
+        pivotThreshold = 20 * (mat.rows() + mat.cols()) * max2Norm * NumTraits<RealScalar>::epsilon();
+      }
       cholmod_sparse A; 
       A = viewAsCholmod(mat);
+      m_rows = matrix.rows();
       Index col = matrix.cols();
-      m_rank = SuiteSparseQR<Scalar>(m_ordering, m_tolerance, col, &A, 
+      m_rank = SuiteSparseQR<Scalar>(m_ordering, pivotThreshold, col, &A, 
                              &m_cR, &m_E, &m_H, &m_HPinv, &m_HTau, &m_cc);
 
       if (!m_cR)
       {
-        m_info = NumericalIssue; 
+        m_info = NumericalIssue;
         m_isInitialized = false;
         return;
       }
       m_info = Success;
       m_isInitialized = true;
@@ -118,45 +137,41 @@
       m_isRUpToDate = false;
     }
     /** 
      * Get the number of rows of the input matrix and the Q matrix
      */
-    inline Index rows() const {return m_H->nrow; }
+    inline Index rows() const {return m_rows; }
     
     /** 
      * Get the number of columns of the input matrix. 
      */
     inline Index cols() const { return m_cR->ncol; }
-   
-      /** \returns the solution X of \f$ A X = B \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<SPQR, Rhs> solve(const MatrixBase<Rhs>& B) const 
-    {
-      eigen_assert(m_isInitialized && " The QR factorization should be computed first, call compute()");
-      eigen_assert(this->rows()==B.rows()
-                    && "SPQR::solve(): invalid number of rows of the right hand side matrix B");
-          return internal::solve_retval<SPQR, Rhs>(*this, B.derived());
-    }
     
     template<typename Rhs, typename Dest>
-    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
+    void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
     {
       eigen_assert(m_isInitialized && " The QR factorization should be computed first, call compute()");
       eigen_assert(b.cols()==1 && "This method is for vectors only");
-      
+
       //Compute Q^T * b
-      typename Dest::PlainObject y;
+      typename Dest::PlainObject y, y2;
       y = matrixQ().transpose() * b;
-        // Solves with the triangular matrix R
+      
+      // Solves with the triangular matrix R
       Index rk = this->rank();
-      y.topRows(rk) = this->matrixR().topLeftCorner(rk, rk).template triangularView<Upper>().solve(y.topRows(rk));
-      y.bottomRows(cols()-rk).setZero();
+      y2 = y;
+      y.resize((std::max)(cols(),Index(y.rows())),y.cols());
+      y.topRows(rk) = this->matrixR().topLeftCorner(rk, rk).template triangularView<Upper>().solve(y2.topRows(rk));
+
       // Apply the column permutation 
-      dest.topRows(cols()) = colsPermutation() * y.topRows(cols());
+      // colsPermutation() performs a copy of the permutation,
+      // so let's apply it manually:
+      for(Index i = 0; i < rk; ++i) dest.row(m_E[i]) = y.row(i);
+      for(Index i = rk; i < cols(); ++i) dest.row(m_E[i]).setZero();
+      
+//       y.bottomRows(y.rows()-rk).setZero();
+//       dest = colsPermutation() * y.topRows(cols());
       
       m_info = Success;
     }
     
     /** \returns the sparse triangular factor R. It is a sparse matrix
@@ -163,11 +178,11 @@
      */
     const MatrixType matrixR() const
     {
       eigen_assert(m_isInitialized && " The QR factorization should be computed first, call compute()");
       if(!m_isRUpToDate) {
-        m_R = viewAsEigen<Scalar,ColMajor, typename MatrixType::Index>(*m_cR);
+        m_R = viewAsEigen<Scalar,ColMajor, typename MatrixType::StorageIndex>(*m_cR);
         m_isRUpToDate = true;
       }
       return m_R;
     }
     /// Get an expression of the matrix Q
@@ -177,15 +192,11 @@
     }
     /// Get the permutation that was applied to columns of A
     PermutationType colsPermutation() const
     { 
       eigen_assert(m_isInitialized && "Decomposition is not initialized.");
-      Index n = m_cR->ncol;
-      PermutationType colsPerm(n);
-      for(Index j = 0; j <n; j++) colsPerm.indices()(j) = m_E[j];
-      return colsPerm; 
-      
+      return PermutationType(m_E, m_cR->ncol);
     }
     /**
      * Gets the rank of the matrix. 
      * It should be equal to matrixQR().cols if the matrix is full-rank
      */
@@ -195,11 +206,15 @@
       return m_cc.SPQR_istat[4];
     }
     /// Set the fill-reducing ordering method to be used
     void setSPQROrdering(int ord) { m_ordering = ord;}
     /// Set the tolerance tol to treat columns with 2-norm < =tol as zero
-    void setPivotThreshold(const RealScalar& tol) { m_tolerance = tol; }
+    void setPivotThreshold(const RealScalar& tol)
+    {
+      m_useDefaultThreshold = false;
+      m_tolerance = tol;
+    }
     
     /** \returns a pointer to the SPQR workspace */
     cholmod_common *cholmodCommon() const { return &m_cc; }
     
     
@@ -212,34 +227,35 @@
     {
       eigen_assert(m_isInitialized && "Decomposition is not initialized.");
       return m_info;
     }
   protected:
-    bool m_isInitialized;
     bool m_analysisIsOk;
     bool m_factorizationIsOk;
     mutable bool m_isRUpToDate;
     mutable ComputationInfo m_info;
     int m_ordering; // Ordering method to use, see SPQR's manual
     int m_allow_tol; // Allow to use some tolerance during numerical factorization.
     RealScalar m_tolerance; // treat columns with 2-norm below this tolerance as zero
     mutable cholmod_sparse *m_cR; // The sparse R factor in cholmod format
     mutable MatrixType m_R; // The sparse matrix R in Eigen format
-    mutable Index *m_E; // The permutation applied to columns
+    mutable StorageIndex *m_E; // The permutation applied to columns
     mutable cholmod_sparse *m_H;  //The householder vectors
-    mutable Index *m_HPinv; // The row permutation of H
+    mutable StorageIndex *m_HPinv; // The row permutation of H
     mutable cholmod_dense *m_HTau; // The Householder coefficients
     mutable Index m_rank; // The rank of the matrix
     mutable cholmod_common m_cc; // Workspace and parameters
+    bool m_useDefaultThreshold;     // Use default threshold
+    Index m_rows;
     template<typename ,typename > friend struct SPQR_QProduct;
 };
 
 template <typename SPQRType, typename Derived>
 struct SPQR_QProduct : ReturnByValue<SPQR_QProduct<SPQRType,Derived> >
 {
   typedef typename SPQRType::Scalar Scalar;
-  typedef typename SPQRType::Index Index;
+  typedef typename SPQRType::StorageIndex StorageIndex;
   //Define the constructor to get reference to argument types
   SPQR_QProduct(const SPQRType& spqr, const Derived& other, bool transpose) : m_spqr(spqr),m_other(other),m_transpose(transpose) {}
   
   inline Index rows() const { return m_transpose ? m_spqr.rows() : m_spqr.cols(); }
   inline Index cols() const { return m_other.cols(); }
@@ -291,24 +307,7 @@
     return SPQR_QProduct<SPQRType,Derived>(m_spqr,other.derived(), true);
   }
   const SPQRType& m_spqr;
 };
 
-namespace internal {
-  
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<SPQR<_MatrixType>, Rhs>
-  : solve_retval_base<SPQR<_MatrixType>, Rhs>
-{
-  typedef SPQR<_MatrixType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-} // end namespace internal
-
 }// End namespace Eigen
 #endif

ADDED   3rd_party/eigen/Eigen/src/SVD/BDCSVD.h
Index: 3rd_party/eigen/Eigen/src/SVD/BDCSVD.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SVD/BDCSVD.h
+++ 3rd_party/eigen/Eigen/src/SVD/BDCSVD.h
@@ -0,0 +1,1231 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+// 
+// We used the "A Divide-And-Conquer Algorithm for the Bidiagonal SVD"
+// research report written by Ming Gu and Stanley C.Eisenstat
+// The code variable names correspond to the names they used in their 
+// report
+//
+// Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com>
+// Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr>
+// Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr>
+// Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr>
+// Copyright (C) 2013 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2014-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_BDCSVD_H
+#define EIGEN_BDCSVD_H
+// #define EIGEN_BDCSVD_DEBUG_VERBOSE
+// #define EIGEN_BDCSVD_SANITY_CHECKS
+
+namespace Eigen {
+
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+IOFormat bdcsvdfmt(8, 0, ", ", "\n", "  [", "]");
+#endif
+  
+template<typename _MatrixType> class BDCSVD;
+
+namespace internal {
+
+template<typename _MatrixType> 
+struct traits<BDCSVD<_MatrixType> >
+{
+  typedef _MatrixType MatrixType;
+};  
+
+} // end namespace internal
+  
+  
+/** \ingroup SVD_Module
+ *
+ *
+ * \class BDCSVD
+ *
+ * \brief class Bidiagonal Divide and Conquer SVD
+ *
+ * \tparam _MatrixType the type of the matrix of which we are computing the SVD decomposition
+ *
+ * This class first reduces the input matrix to bi-diagonal form using class UpperBidiagonalization,
+ * and then performs a divide-and-conquer diagonalization. Small blocks are diagonalized using class JacobiSVD.
+ * You can control the switching size with the setSwitchSize() method, default is 16.
+ * For small matrice (<16), it is thus preferable to directly use JacobiSVD. For larger ones, BDCSVD is highly
+ * recommended and can several order of magnitude faster.
+ *
+ * \warning this algorithm is unlikely to provide accurate result when compiled with unsafe math optimizations.
+ * For instance, this concerns Intel's compiler (ICC), which perfroms such optimization by default unless
+ * you compile with the \c -fp-model \c precise option. Likewise, the \c -ffast-math option of GCC or clang will
+ * significantly degrade the accuracy.
+ *
+ * \sa class JacobiSVD
+ */
+template<typename _MatrixType> 
+class BDCSVD : public SVDBase<BDCSVD<_MatrixType> >
+{
+  typedef SVDBase<BDCSVD> Base;
+    
+public:
+  using Base::rows;
+  using Base::cols;
+  using Base::computeU;
+  using Base::computeV;
+  
+  typedef _MatrixType MatrixType;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+  typedef typename NumTraits<RealScalar>::Literal Literal;
+  enum {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime, 
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime, 
+    DiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime), 
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, 
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, 
+    MaxDiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(MaxRowsAtCompileTime, MaxColsAtCompileTime), 
+    MatrixOptions = MatrixType::Options
+  };
+
+  typedef typename Base::MatrixUType MatrixUType;
+  typedef typename Base::MatrixVType MatrixVType;
+  typedef typename Base::SingularValuesType SingularValuesType;
+  
+  typedef Matrix<Scalar, Dynamic, Dynamic, ColMajor> MatrixX;
+  typedef Matrix<RealScalar, Dynamic, Dynamic, ColMajor> MatrixXr;
+  typedef Matrix<RealScalar, Dynamic, 1> VectorType;
+  typedef Array<RealScalar, Dynamic, 1> ArrayXr;
+  typedef Array<Index,1,Dynamic> ArrayXi;
+  typedef Ref<ArrayXr> ArrayRef;
+  typedef Ref<ArrayXi> IndicesRef;
+
+  /** \brief Default Constructor.
+   *
+   * The default constructor is useful in cases in which the user intends to
+   * perform decompositions via BDCSVD::compute(const MatrixType&).
+   */
+  BDCSVD() : m_algoswap(16), m_numIters(0)
+  {}
+
+
+  /** \brief Default Constructor with memory preallocation
+   *
+   * Like the default constructor but with preallocation of the internal data
+   * according to the specified problem size.
+   * \sa BDCSVD()
+   */
+  BDCSVD(Index rows, Index cols, unsigned int computationOptions = 0)
+    : m_algoswap(16), m_numIters(0)
+  {
+    allocate(rows, cols, computationOptions);
+  }
+
+  /** \brief Constructor performing the decomposition of given matrix.
+   *
+   * \param matrix the matrix to decompose
+   * \param computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed.
+   *                           By default, none is computed. This is a bit - field, the possible bits are #ComputeFullU, #ComputeThinU, 
+   *                           #ComputeFullV, #ComputeThinV.
+   *
+   * Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not
+   * available with the (non - default) FullPivHouseholderQR preconditioner.
+   */
+  BDCSVD(const MatrixType& matrix, unsigned int computationOptions = 0)
+    : m_algoswap(16), m_numIters(0)
+  {
+    compute(matrix, computationOptions);
+  }
+
+  ~BDCSVD() 
+  {
+  }
+  
+  /** \brief Method performing the decomposition of given matrix using custom options.
+   *
+   * \param matrix the matrix to decompose
+   * \param computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed.
+   *                           By default, none is computed. This is a bit - field, the possible bits are #ComputeFullU, #ComputeThinU, 
+   *                           #ComputeFullV, #ComputeThinV.
+   *
+   * Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not
+   * available with the (non - default) FullPivHouseholderQR preconditioner.
+   */
+  BDCSVD& compute(const MatrixType& matrix, unsigned int computationOptions);
+
+  /** \brief Method performing the decomposition of given matrix using current options.
+   *
+   * \param matrix the matrix to decompose
+   *
+   * This method uses the current \a computationOptions, as already passed to the constructor or to compute(const MatrixType&, unsigned int).
+   */
+  BDCSVD& compute(const MatrixType& matrix)
+  {
+    return compute(matrix, this->m_computationOptions);
+  }
+
+  void setSwitchSize(int s) 
+  {
+    eigen_assert(s>3 && "BDCSVD the size of the algo switch has to be greater than 3");
+    m_algoswap = s;
+  }
+ 
+private:
+  void allocate(Index rows, Index cols, unsigned int computationOptions);
+  void divide(Index firstCol, Index lastCol, Index firstRowW, Index firstColW, Index shift);
+  void computeSVDofM(Index firstCol, Index n, MatrixXr& U, VectorType& singVals, MatrixXr& V);
+  void computeSingVals(const ArrayRef& col0, const ArrayRef& diag, const IndicesRef& perm, VectorType& singVals, ArrayRef shifts, ArrayRef mus);
+  void perturbCol0(const ArrayRef& col0, const ArrayRef& diag, const IndicesRef& perm, const VectorType& singVals, const ArrayRef& shifts, const ArrayRef& mus, ArrayRef zhat);
+  void computeSingVecs(const ArrayRef& zhat, const ArrayRef& diag, const IndicesRef& perm, const VectorType& singVals, const ArrayRef& shifts, const ArrayRef& mus, MatrixXr& U, MatrixXr& V);
+  void deflation43(Index firstCol, Index shift, Index i, Index size);
+  void deflation44(Index firstColu , Index firstColm, Index firstRowW, Index firstColW, Index i, Index j, Index size);
+  void deflation(Index firstCol, Index lastCol, Index k, Index firstRowW, Index firstColW, Index shift);
+  template<typename HouseholderU, typename HouseholderV, typename NaiveU, typename NaiveV>
+  void copyUV(const HouseholderU &householderU, const HouseholderV &householderV, const NaiveU &naiveU, const NaiveV &naivev);
+  void structured_update(Block<MatrixXr,Dynamic,Dynamic> A, const MatrixXr &B, Index n1);
+  static RealScalar secularEq(RealScalar x, const ArrayRef& col0, const ArrayRef& diag, const IndicesRef &perm, const ArrayRef& diagShifted, RealScalar shift);
+
+protected:
+  MatrixXr m_naiveU, m_naiveV;
+  MatrixXr m_computed;
+  Index m_nRec;
+  ArrayXr m_workspace;
+  ArrayXi m_workspaceI;
+  int m_algoswap;
+  bool m_isTranspose, m_compU, m_compV;
+  
+  using Base::m_singularValues;
+  using Base::m_diagSize;
+  using Base::m_computeFullU;
+  using Base::m_computeFullV;
+  using Base::m_computeThinU;
+  using Base::m_computeThinV;
+  using Base::m_matrixU;
+  using Base::m_matrixV;
+  using Base::m_isInitialized;
+  using Base::m_nonzeroSingularValues;
+
+public:  
+  int m_numIters;
+}; //end class BDCSVD
+
+
+// Method to allocate and initialize matrix and attributes
+template<typename MatrixType>
+void BDCSVD<MatrixType>::allocate(Index rows, Index cols, unsigned int computationOptions)
+{
+  m_isTranspose = (cols > rows);
+
+  if (Base::allocate(rows, cols, computationOptions))
+    return;
+  
+  m_computed = MatrixXr::Zero(m_diagSize + 1, m_diagSize );
+  m_compU = computeV();
+  m_compV = computeU();
+  if (m_isTranspose)
+    std::swap(m_compU, m_compV);
+  
+  if (m_compU) m_naiveU = MatrixXr::Zero(m_diagSize + 1, m_diagSize + 1 );
+  else         m_naiveU = MatrixXr::Zero(2, m_diagSize + 1 );
+  
+  if (m_compV) m_naiveV = MatrixXr::Zero(m_diagSize, m_diagSize);
+  
+  m_workspace.resize((m_diagSize+1)*(m_diagSize+1)*3);
+  m_workspaceI.resize(3*m_diagSize);
+}// end allocate
+
+template<typename MatrixType>
+BDCSVD<MatrixType>& BDCSVD<MatrixType>::compute(const MatrixType& matrix, unsigned int computationOptions) 
+{
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  std::cout << "\n\n\n======================================================================================================================\n\n\n";
+#endif
+  allocate(matrix.rows(), matrix.cols(), computationOptions);
+  using std::abs;
+
+  const RealScalar considerZero = (std::numeric_limits<RealScalar>::min)();
+  
+  //**** step -1 - If the problem is too small, directly falls back to JacobiSVD and return
+  if(matrix.cols() < m_algoswap)
+  {
+    // FIXME this line involves temporaries
+    JacobiSVD<MatrixType> jsvd(matrix,computationOptions);
+    if(computeU()) m_matrixU = jsvd.matrixU();
+    if(computeV()) m_matrixV = jsvd.matrixV();
+    m_singularValues = jsvd.singularValues();
+    m_nonzeroSingularValues = jsvd.nonzeroSingularValues();
+    m_isInitialized = true;
+    return *this;
+  }
+  
+  //**** step 0 - Copy the input matrix and apply scaling to reduce over/under-flows
+  RealScalar scale = matrix.cwiseAbs().maxCoeff();
+  if(scale==Literal(0)) scale = Literal(1);
+  MatrixX copy;
+  if (m_isTranspose) copy = matrix.adjoint()/scale;
+  else               copy = matrix/scale;
+  
+  //**** step 1 - Bidiagonalization
+  // FIXME this line involves temporaries
+  internal::UpperBidiagonalization<MatrixX> bid(copy);
+
+  //**** step 2 - Divide & Conquer
+  m_naiveU.setZero();
+  m_naiveV.setZero();
+  // FIXME this line involves a temporary matrix
+  m_computed.topRows(m_diagSize) = bid.bidiagonal().toDenseMatrix().transpose();
+  m_computed.template bottomRows<1>().setZero();
+  divide(0, m_diagSize - 1, 0, 0, 0);
+
+  //**** step 3 - Copy singular values and vectors
+  for (int i=0; i<m_diagSize; i++)
+  {
+    RealScalar a = abs(m_computed.coeff(i, i));
+    m_singularValues.coeffRef(i) = a * scale;
+    if (a<considerZero)
+    {
+      m_nonzeroSingularValues = i;
+      m_singularValues.tail(m_diagSize - i - 1).setZero();
+      break;
+    }
+    else if (i == m_diagSize - 1)
+    {
+      m_nonzeroSingularValues = i + 1;
+      break;
+    }
+  }
+
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+//   std::cout << "m_naiveU\n" << m_naiveU << "\n\n";
+//   std::cout << "m_naiveV\n" << m_naiveV << "\n\n";
+#endif
+  if(m_isTranspose) copyUV(bid.householderV(), bid.householderU(), m_naiveV, m_naiveU);
+  else              copyUV(bid.householderU(), bid.householderV(), m_naiveU, m_naiveV);
+
+  m_isInitialized = true;
+  return *this;
+}// end compute
+
+
+template<typename MatrixType>
+template<typename HouseholderU, typename HouseholderV, typename NaiveU, typename NaiveV>
+void BDCSVD<MatrixType>::copyUV(const HouseholderU &householderU, const HouseholderV &householderV, const NaiveU &naiveU, const NaiveV &naiveV)
+{
+  // Note exchange of U and V: m_matrixU is set from m_naiveV and vice versa
+  if (computeU())
+  {
+    Index Ucols = m_computeThinU ? m_diagSize : householderU.cols();
+    m_matrixU = MatrixX::Identity(householderU.cols(), Ucols);
+    m_matrixU.topLeftCorner(m_diagSize, m_diagSize) = naiveV.template cast<Scalar>().topLeftCorner(m_diagSize, m_diagSize);
+    householderU.applyThisOnTheLeft(m_matrixU); // FIXME this line involves a temporary buffer
+  }
+  if (computeV())
+  {
+    Index Vcols = m_computeThinV ? m_diagSize : householderV.cols();
+    m_matrixV = MatrixX::Identity(householderV.cols(), Vcols);
+    m_matrixV.topLeftCorner(m_diagSize, m_diagSize) = naiveU.template cast<Scalar>().topLeftCorner(m_diagSize, m_diagSize);
+    householderV.applyThisOnTheLeft(m_matrixV); // FIXME this line involves a temporary buffer
+  }
+}
+
+/** \internal
+  * Performs A = A * B exploiting the special structure of the matrix A. Splitting A as:
+  *  A = [A1]
+  *      [A2]
+  * such that A1.rows()==n1, then we assume that at least half of the columns of A1 and A2 are zeros.
+  * We can thus pack them prior to the the matrix product. However, this is only worth the effort if the matrix is large
+  * enough.
+  */
+template<typename MatrixType>
+void BDCSVD<MatrixType>::structured_update(Block<MatrixXr,Dynamic,Dynamic> A, const MatrixXr &B, Index n1)
+{
+  Index n = A.rows();
+  if(n>100)
+  {
+    // If the matrices are large enough, let's exploit the sparse structure of A by
+    // splitting it in half (wrt n1), and packing the non-zero columns.
+    Index n2 = n - n1;
+    Map<MatrixXr> A1(m_workspace.data()      , n1, n);
+    Map<MatrixXr> A2(m_workspace.data()+ n1*n, n2, n);
+    Map<MatrixXr> B1(m_workspace.data()+  n*n, n,  n);
+    Map<MatrixXr> B2(m_workspace.data()+2*n*n, n,  n);
+    Index k1=0, k2=0;
+    for(Index j=0; j<n; ++j)
+    {
+      if( (A.col(j).head(n1).array()!=Literal(0)).any() )
+      {
+        A1.col(k1) = A.col(j).head(n1);
+        B1.row(k1) = B.row(j);
+        ++k1;
+      }
+      if( (A.col(j).tail(n2).array()!=Literal(0)).any() )
+      {
+        A2.col(k2) = A.col(j).tail(n2);
+        B2.row(k2) = B.row(j);
+        ++k2;
+      }
+    }
+  
+    A.topRows(n1).noalias()    = A1.leftCols(k1) * B1.topRows(k1);
+    A.bottomRows(n2).noalias() = A2.leftCols(k2) * B2.topRows(k2);
+  }
+  else
+  {
+    Map<MatrixXr,Aligned> tmp(m_workspace.data(),n,n);
+    tmp.noalias() = A*B;
+    A = tmp;
+  }
+}
+
+// The divide algorithm is done "in place", we are always working on subsets of the same matrix. The divide methods takes as argument the 
+// place of the submatrix we are currently working on.
+
+//@param firstCol : The Index of the first column of the submatrix of m_computed and for m_naiveU;
+//@param lastCol : The Index of the last column of the submatrix of m_computed and for m_naiveU; 
+// lastCol + 1 - firstCol is the size of the submatrix.
+//@param firstRowW : The Index of the first row of the matrix W that we are to change. (see the reference paper section 1 for more information on W)
+//@param firstRowW : Same as firstRowW with the column.
+//@param shift : Each time one takes the left submatrix, one must add 1 to the shift. Why? Because! We actually want the last column of the U submatrix 
+// to become the first column (*coeff) and to shift all the other columns to the right. There are more details on the reference paper.
+template<typename MatrixType>
+void BDCSVD<MatrixType>::divide (Index firstCol, Index lastCol, Index firstRowW, Index firstColW, Index shift)
+{
+  // requires rows = cols + 1;
+  using std::pow;
+  using std::sqrt;
+  using std::abs;
+  const Index n = lastCol - firstCol + 1;
+  const Index k = n/2;
+  const RealScalar considerZero = (std::numeric_limits<RealScalar>::min)();
+  RealScalar alphaK;
+  RealScalar betaK; 
+  RealScalar r0; 
+  RealScalar lambda, phi, c0, s0;
+  VectorType l, f;
+  // We use the other algorithm which is more efficient for small 
+  // matrices.
+  if (n < m_algoswap)
+  {
+    // FIXME this line involves temporaries
+    JacobiSVD<MatrixXr> b(m_computed.block(firstCol, firstCol, n + 1, n), ComputeFullU | (m_compV ? ComputeFullV : 0));
+    if (m_compU)
+      m_naiveU.block(firstCol, firstCol, n + 1, n + 1).real() = b.matrixU();
+    else 
+    {
+      m_naiveU.row(0).segment(firstCol, n + 1).real() = b.matrixU().row(0);
+      m_naiveU.row(1).segment(firstCol, n + 1).real() = b.matrixU().row(n);
+    }
+    if (m_compV) m_naiveV.block(firstRowW, firstColW, n, n).real() = b.matrixV();
+    m_computed.block(firstCol + shift, firstCol + shift, n + 1, n).setZero();
+    m_computed.diagonal().segment(firstCol + shift, n) = b.singularValues().head(n);
+    return;
+  }
+  // We use the divide and conquer algorithm
+  alphaK =  m_computed(firstCol + k, firstCol + k);
+  betaK = m_computed(firstCol + k + 1, firstCol + k);
+  // The divide must be done in that order in order to have good results. Divide change the data inside the submatrices
+  // and the divide of the right submatrice reads one column of the left submatrice. That's why we need to treat the 
+  // right submatrix before the left one. 
+  divide(k + 1 + firstCol, lastCol, k + 1 + firstRowW, k + 1 + firstColW, shift);
+  divide(firstCol, k - 1 + firstCol, firstRowW, firstColW + 1, shift + 1);
+
+  if (m_compU)
+  {
+    lambda = m_naiveU(firstCol + k, firstCol + k);
+    phi = m_naiveU(firstCol + k + 1, lastCol + 1);
+  } 
+  else 
+  {
+    lambda = m_naiveU(1, firstCol + k);
+    phi = m_naiveU(0, lastCol + 1);
+  }
+  r0 = sqrt((abs(alphaK * lambda) * abs(alphaK * lambda)) + abs(betaK * phi) * abs(betaK * phi));
+  if (m_compU)
+  {
+    l = m_naiveU.row(firstCol + k).segment(firstCol, k);
+    f = m_naiveU.row(firstCol + k + 1).segment(firstCol + k + 1, n - k - 1);
+  } 
+  else 
+  {
+    l = m_naiveU.row(1).segment(firstCol, k);
+    f = m_naiveU.row(0).segment(firstCol + k + 1, n - k - 1);
+  }
+  if (m_compV) m_naiveV(firstRowW+k, firstColW) = Literal(1);
+  if (r0<considerZero)
+  {
+    c0 = Literal(1);
+    s0 = Literal(0);
+  }
+  else
+  {
+    c0 = alphaK * lambda / r0;
+    s0 = betaK * phi / r0;
+  }
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(m_naiveU.allFinite());
+  assert(m_naiveV.allFinite());
+  assert(m_computed.allFinite());
+#endif
+  
+  if (m_compU)
+  {
+    MatrixXr q1 (m_naiveU.col(firstCol + k).segment(firstCol, k + 1));     
+    // we shiftW Q1 to the right
+    for (Index i = firstCol + k - 1; i >= firstCol; i--) 
+      m_naiveU.col(i + 1).segment(firstCol, k + 1) = m_naiveU.col(i).segment(firstCol, k + 1);
+    // we shift q1 at the left with a factor c0
+    m_naiveU.col(firstCol).segment( firstCol, k + 1) = (q1 * c0);
+    // last column = q1 * - s0
+    m_naiveU.col(lastCol + 1).segment(firstCol, k + 1) = (q1 * ( - s0));
+    // first column = q2 * s0
+    m_naiveU.col(firstCol).segment(firstCol + k + 1, n - k) = m_naiveU.col(lastCol + 1).segment(firstCol + k + 1, n - k) * s0; 
+    // q2 *= c0
+    m_naiveU.col(lastCol + 1).segment(firstCol + k + 1, n - k) *= c0;
+  } 
+  else 
+  {
+    RealScalar q1 = m_naiveU(0, firstCol + k);
+    // we shift Q1 to the right
+    for (Index i = firstCol + k - 1; i >= firstCol; i--) 
+      m_naiveU(0, i + 1) = m_naiveU(0, i);
+    // we shift q1 at the left with a factor c0
+    m_naiveU(0, firstCol) = (q1 * c0);
+    // last column = q1 * - s0
+    m_naiveU(0, lastCol + 1) = (q1 * ( - s0));
+    // first column = q2 * s0
+    m_naiveU(1, firstCol) = m_naiveU(1, lastCol + 1) *s0; 
+    // q2 *= c0
+    m_naiveU(1, lastCol + 1) *= c0;
+    m_naiveU.row(1).segment(firstCol + 1, k).setZero();
+    m_naiveU.row(0).segment(firstCol + k + 1, n - k - 1).setZero();
+  }
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(m_naiveU.allFinite());
+  assert(m_naiveV.allFinite());
+  assert(m_computed.allFinite());
+#endif
+  
+  m_computed(firstCol + shift, firstCol + shift) = r0;
+  m_computed.col(firstCol + shift).segment(firstCol + shift + 1, k) = alphaK * l.transpose().real();
+  m_computed.col(firstCol + shift).segment(firstCol + shift + k + 1, n - k - 1) = betaK * f.transpose().real();
+
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  ArrayXr tmp1 = (m_computed.block(firstCol+shift, firstCol+shift, n, n)).jacobiSvd().singularValues();
+#endif
+  // Second part: try to deflate singular values in combined matrix
+  deflation(firstCol, lastCol, k, firstRowW, firstColW, shift);
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  ArrayXr tmp2 = (m_computed.block(firstCol+shift, firstCol+shift, n, n)).jacobiSvd().singularValues();
+  std::cout << "\n\nj1 = " << tmp1.transpose().format(bdcsvdfmt) << "\n";
+  std::cout << "j2 = " << tmp2.transpose().format(bdcsvdfmt) << "\n\n";
+  std::cout << "err:      " << ((tmp1-tmp2).abs()>1e-12*tmp2.abs()).transpose() << "\n";
+  static int count = 0;
+  std::cout << "# " << ++count << "\n\n";
+  assert((tmp1-tmp2).matrix().norm() < 1e-14*tmp2.matrix().norm());
+//   assert(count<681);
+//   assert(((tmp1-tmp2).abs()<1e-13*tmp2.abs()).all());
+#endif
+  
+  // Third part: compute SVD of combined matrix
+  MatrixXr UofSVD, VofSVD;
+  VectorType singVals;
+  computeSVDofM(firstCol + shift, n, UofSVD, singVals, VofSVD);
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(UofSVD.allFinite());
+  assert(VofSVD.allFinite());
+#endif
+  
+  if (m_compU)
+    structured_update(m_naiveU.block(firstCol, firstCol, n + 1, n + 1), UofSVD, (n+2)/2);
+  else
+  {
+    Map<Matrix<RealScalar,2,Dynamic>,Aligned> tmp(m_workspace.data(),2,n+1);
+    tmp.noalias() = m_naiveU.middleCols(firstCol, n+1) * UofSVD;
+    m_naiveU.middleCols(firstCol, n + 1) = tmp;
+  }
+  
+  if (m_compV)  structured_update(m_naiveV.block(firstRowW, firstColW, n, n), VofSVD, (n+1)/2);
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(m_naiveU.allFinite());
+  assert(m_naiveV.allFinite());
+  assert(m_computed.allFinite());
+#endif
+  
+  m_computed.block(firstCol + shift, firstCol + shift, n, n).setZero();
+  m_computed.block(firstCol + shift, firstCol + shift, n, n).diagonal() = singVals;
+}// end divide
+
+// Compute SVD of m_computed.block(firstCol, firstCol, n + 1, n); this block only has non-zeros in
+// the first column and on the diagonal and has undergone deflation, so diagonal is in increasing
+// order except for possibly the (0,0) entry. The computed SVD is stored U, singVals and V, except
+// that if m_compV is false, then V is not computed. Singular values are sorted in decreasing order.
+//
+// TODO Opportunities for optimization: better root finding algo, better stopping criterion, better
+// handling of round-off errors, be consistent in ordering
+// For instance, to solve the secular equation using FMM, see http://www.stat.uchicago.edu/~lekheng/courses/302/classics/greengard-rokhlin.pdf
+template <typename MatrixType>
+void BDCSVD<MatrixType>::computeSVDofM(Index firstCol, Index n, MatrixXr& U, VectorType& singVals, MatrixXr& V)
+{
+  const RealScalar considerZero = (std::numeric_limits<RealScalar>::min)();
+  using std::abs;
+  ArrayRef col0 = m_computed.col(firstCol).segment(firstCol, n);
+  m_workspace.head(n) =  m_computed.block(firstCol, firstCol, n, n).diagonal();
+  ArrayRef diag = m_workspace.head(n);
+  diag(0) = Literal(0);
+
+  // Allocate space for singular values and vectors
+  singVals.resize(n);
+  U.resize(n+1, n+1);
+  if (m_compV) V.resize(n, n);
+
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  if (col0.hasNaN() || diag.hasNaN())
+    std::cout << "\n\nHAS NAN\n\n";
+#endif
+  
+  // Many singular values might have been deflated, the zero ones have been moved to the end,
+  // but others are interleaved and we must ignore them at this stage.
+  // To this end, let's compute a permutation skipping them:
+  Index actual_n = n;
+  while(actual_n>1 && diag(actual_n-1)==Literal(0)) --actual_n;
+  Index m = 0; // size of the deflated problem
+  for(Index k=0;k<actual_n;++k)
+    if(abs(col0(k))>considerZero)
+      m_workspaceI(m++) = k;
+  Map<ArrayXi> perm(m_workspaceI.data(),m);
+  
+  Map<ArrayXr> shifts(m_workspace.data()+1*n, n);
+  Map<ArrayXr> mus(m_workspace.data()+2*n, n);
+  Map<ArrayXr> zhat(m_workspace.data()+3*n, n);
+
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  std::cout << "computeSVDofM using:\n";
+  std::cout << "  z: " << col0.transpose() << "\n";
+  std::cout << "  d: " << diag.transpose() << "\n";
+#endif
+  
+  // Compute singVals, shifts, and mus
+  computeSingVals(col0, diag, perm, singVals, shifts, mus);
+  
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  std::cout << "  j:        " << (m_computed.block(firstCol, firstCol, n, n)).jacobiSvd().singularValues().transpose().reverse() << "\n\n";
+  std::cout << "  sing-val: " << singVals.transpose() << "\n";
+  std::cout << "  mu:       " << mus.transpose() << "\n";
+  std::cout << "  shift:    " << shifts.transpose() << "\n";
+  
+  {
+    Index actual_n = n;
+    while(actual_n>1 && abs(col0(actual_n-1))<considerZero) --actual_n;
+    std::cout << "\n\n    mus:    " << mus.head(actual_n).transpose() << "\n\n";
+    std::cout << "    check1 (expect0) : " << ((singVals.array()-(shifts+mus)) / singVals.array()).head(actual_n).transpose() << "\n\n";
+    std::cout << "    check2 (>0)      : " << ((singVals.array()-diag) / singVals.array()).head(actual_n).transpose() << "\n\n";
+    std::cout << "    check3 (>0)      : " << ((diag.segment(1,actual_n-1)-singVals.head(actual_n-1).array()) / singVals.head(actual_n-1).array()).transpose() << "\n\n\n";
+    std::cout << "    check4 (>0)      : " << ((singVals.segment(1,actual_n-1)-singVals.head(actual_n-1))).transpose() << "\n\n\n";
+  }
+#endif
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(singVals.allFinite());
+  assert(mus.allFinite());
+  assert(shifts.allFinite());
+#endif
+  
+  // Compute zhat
+  perturbCol0(col0, diag, perm, singVals, shifts, mus, zhat);
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE
+  std::cout << "  zhat: " << zhat.transpose() << "\n";
+#endif
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(zhat.allFinite());
+#endif
+  
+  computeSingVecs(zhat, diag, perm, singVals, shifts, mus, U, V);
+  
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE
+  std::cout << "U^T U: " << (U.transpose() * U - MatrixXr(MatrixXr::Identity(U.cols(),U.cols()))).norm() << "\n";
+  std::cout << "V^T V: " << (V.transpose() * V - MatrixXr(MatrixXr::Identity(V.cols(),V.cols()))).norm() << "\n";
+#endif
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(U.allFinite());
+  assert(V.allFinite());
+  assert((U.transpose() * U - MatrixXr(MatrixXr::Identity(U.cols(),U.cols()))).norm() < 1e-14 * n);
+  assert((V.transpose() * V - MatrixXr(MatrixXr::Identity(V.cols(),V.cols()))).norm() < 1e-14 * n);
+  assert(m_naiveU.allFinite());
+  assert(m_naiveV.allFinite());
+  assert(m_computed.allFinite());
+#endif
+  
+  // Because of deflation, the singular values might not be completely sorted.
+  // Fortunately, reordering them is a O(n) problem
+  for(Index i=0; i<actual_n-1; ++i)
+  {
+    if(singVals(i)>singVals(i+1))
+    {
+      using std::swap;
+      swap(singVals(i),singVals(i+1));
+      U.col(i).swap(U.col(i+1));
+      if(m_compV) V.col(i).swap(V.col(i+1));
+    }
+  }
+  
+  // Reverse order so that singular values in increased order
+  // Because of deflation, the zeros singular-values are already at the end
+  singVals.head(actual_n).reverseInPlace();
+  U.leftCols(actual_n).rowwise().reverseInPlace();
+  if (m_compV) V.leftCols(actual_n).rowwise().reverseInPlace();
+  
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  JacobiSVD<MatrixXr> jsvd(m_computed.block(firstCol, firstCol, n, n) );
+  std::cout << "  * j:        " << jsvd.singularValues().transpose() << "\n\n";
+  std::cout << "  * sing-val: " << singVals.transpose() << "\n";
+//   std::cout << "  * err:      " << ((jsvd.singularValues()-singVals)>1e-13*singVals.norm()).transpose() << "\n";
+#endif
+}
+
+template <typename MatrixType>
+typename BDCSVD<MatrixType>::RealScalar BDCSVD<MatrixType>::secularEq(RealScalar mu, const ArrayRef& col0, const ArrayRef& diag, const IndicesRef &perm, const ArrayRef& diagShifted, RealScalar shift)
+{
+  Index m = perm.size();
+  RealScalar res = Literal(1);
+  for(Index i=0; i<m; ++i)
+  {
+    Index j = perm(i);
+    res += numext::abs2(col0(j)) / ((diagShifted(j) - mu) * (diag(j) + shift + mu));
+  }
+  return res;
+
+}
+
+template <typename MatrixType>
+void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& diag, const IndicesRef &perm,
+                                         VectorType& singVals, ArrayRef shifts, ArrayRef mus)
+{
+  using std::abs;
+  using std::swap;
+
+  Index n = col0.size();
+  Index actual_n = n;
+  while(actual_n>1 && col0(actual_n-1)==Literal(0)) --actual_n;
+
+  for (Index k = 0; k < n; ++k)
+  {
+    if (col0(k) == Literal(0) || actual_n==1)
+    {
+      // if col0(k) == 0, then entry is deflated, so singular value is on diagonal
+      // if actual_n==1, then the deflated problem is already diagonalized
+      singVals(k) = k==0 ? col0(0) : diag(k);
+      mus(k) = Literal(0);
+      shifts(k) = k==0 ? col0(0) : diag(k);
+      continue;
+    } 
+
+    // otherwise, use secular equation to find singular value
+    RealScalar left = diag(k);
+    RealScalar right; // was: = (k != actual_n-1) ? diag(k+1) : (diag(actual_n-1) + col0.matrix().norm());
+    if(k==actual_n-1)
+      right = (diag(actual_n-1) + col0.matrix().norm());
+    else
+    {
+      // Skip deflated singular values
+      Index l = k+1;
+      while(col0(l)==Literal(0)) { ++l; eigen_internal_assert(l<actual_n); }
+      right = diag(l);
+    }
+
+    // first decide whether it's closer to the left end or the right end
+    RealScalar mid = left + (right-left) / Literal(2);
+    RealScalar fMid = secularEq(mid, col0, diag, perm, diag, Literal(0));
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+    std::cout << right-left << "\n";
+    std::cout << "fMid = " << fMid << " " << secularEq(mid-left, col0, diag, perm, diag-left, left) << " " << secularEq(mid-right, col0, diag, perm, diag-right, right)   << "\n";
+    std::cout << "     = " << secularEq(0.1*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.2*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.3*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.4*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.49*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.5*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.51*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.6*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.7*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.8*(left+right), col0, diag, perm, diag, 0)
+              << " "       << secularEq(0.9*(left+right), col0, diag, perm, diag, 0) << "\n";
+#endif
+    RealScalar shift = (k == actual_n-1 || fMid > Literal(0)) ? left : right;
+    
+    // measure everything relative to shift
+    Map<ArrayXr> diagShifted(m_workspace.data()+4*n, n);
+    diagShifted = diag - shift;
+    
+    // initial guess
+    RealScalar muPrev, muCur;
+    if (shift == left)
+    {
+      muPrev = (right - left) * RealScalar(0.1);
+      if (k == actual_n-1) muCur = right - left;
+      else                 muCur = (right - left) * RealScalar(0.5);
+    }
+    else
+    {
+      muPrev = -(right - left) * RealScalar(0.1);
+      muCur = -(right - left) * RealScalar(0.5);
+    }
+
+    RealScalar fPrev = secularEq(muPrev, col0, diag, perm, diagShifted, shift);
+    RealScalar fCur = secularEq(muCur, col0, diag, perm, diagShifted, shift);
+    if (abs(fPrev) < abs(fCur))
+    {
+      swap(fPrev, fCur);
+      swap(muPrev, muCur);
+    }
+
+    // rational interpolation: fit a function of the form a / mu + b through the two previous
+    // iterates and use its zero to compute the next iterate
+    bool useBisection = fPrev*fCur>Literal(0);
+    while (fCur!=Literal(0) && abs(muCur - muPrev) > Literal(8) * NumTraits<RealScalar>::epsilon() * numext::maxi<RealScalar>(abs(muCur), abs(muPrev)) && abs(fCur - fPrev)>NumTraits<RealScalar>::epsilon() && !useBisection)
+    {
+      ++m_numIters;
+
+      // Find a and b such that the function f(mu) = a / mu + b matches the current and previous samples.
+      RealScalar a = (fCur - fPrev) / (Literal(1)/muCur - Literal(1)/muPrev);
+      RealScalar b = fCur - a / muCur;
+      // And find mu such that f(mu)==0:
+      RealScalar muZero = -a/b;
+      RealScalar fZero = secularEq(muZero, col0, diag, perm, diagShifted, shift);
+      
+      muPrev = muCur;
+      fPrev = fCur;
+      muCur = muZero;
+      fCur = fZero;
+      
+      
+      if (shift == left  && (muCur < Literal(0) || muCur > right - left)) useBisection = true;
+      if (shift == right && (muCur < -(right - left) || muCur > Literal(0))) useBisection = true;
+      if (abs(fCur)>abs(fPrev)) useBisection = true;
+    }
+
+    // fall back on bisection method if rational interpolation did not work
+    if (useBisection)
+    {
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE
+      std::cout << "useBisection for k = " << k << ", actual_n = " << actual_n << "\n";
+#endif
+      RealScalar leftShifted, rightShifted;
+      if (shift == left)
+      {
+        leftShifted = (std::numeric_limits<RealScalar>::min)();
+        // I don't understand why the case k==0 would be special there:
+        // if (k == 0) rightShifted = right - left; else 
+        rightShifted = (k==actual_n-1) ? right : ((right - left) * RealScalar(0.6)); // theoretically we can take 0.5, but let's be safe
+      }
+      else
+      {
+        leftShifted = -(right - left) * RealScalar(0.6);
+        rightShifted = -(std::numeric_limits<RealScalar>::min)();
+      }
+      
+      RealScalar fLeft = secularEq(leftShifted, col0, diag, perm, diagShifted, shift);
+
+#if defined EIGEN_INTERNAL_DEBUGGING || defined EIGEN_BDCSVD_DEBUG_VERBOSE
+      RealScalar fRight = secularEq(rightShifted, col0, diag, perm, diagShifted, shift);
+#endif
+
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE
+      if(!(fLeft * fRight<0))
+      {
+        std::cout << "fLeft: " << leftShifted << " - " << diagShifted.head(10).transpose()  << "\n ; " << bool(left==shift) << " " << (left-shift) << "\n";
+        std::cout << k << " : " <<  fLeft << " * " << fRight << " == " << fLeft * fRight << "  ;  " << left << " - " << right << " -> " <<  leftShifted << " " << rightShifted << "   shift=" << shift << "\n";
+      }
+#endif
+      eigen_internal_assert(fLeft * fRight < Literal(0));
+      
+      while (rightShifted - leftShifted > Literal(2) * NumTraits<RealScalar>::epsilon() * numext::maxi<RealScalar>(abs(leftShifted), abs(rightShifted)))
+      {
+        RealScalar midShifted = (leftShifted + rightShifted) / Literal(2);
+        fMid = secularEq(midShifted, col0, diag, perm, diagShifted, shift);
+        if (fLeft * fMid < Literal(0))
+        {
+          rightShifted = midShifted;
+        }
+        else
+        {
+          leftShifted = midShifted;
+          fLeft = fMid;
+        }
+      }
+
+      muCur = (leftShifted + rightShifted) / Literal(2);
+    }
+      
+    singVals[k] = shift + muCur;
+    shifts[k] = shift;
+    mus[k] = muCur;
+
+    // perturb singular value slightly if it equals diagonal entry to avoid division by zero later
+    // (deflation is supposed to avoid this from happening)
+    // - this does no seem to be necessary anymore -
+//     if (singVals[k] == left) singVals[k] *= 1 + NumTraits<RealScalar>::epsilon();
+//     if (singVals[k] == right) singVals[k] *= 1 - NumTraits<RealScalar>::epsilon();
+  }
+}
+
+
+// zhat is perturbation of col0 for which singular vectors can be computed stably (see Section 3.1)
+template <typename MatrixType>
+void BDCSVD<MatrixType>::perturbCol0
+   (const ArrayRef& col0, const ArrayRef& diag, const IndicesRef &perm, const VectorType& singVals,
+    const ArrayRef& shifts, const ArrayRef& mus, ArrayRef zhat)
+{
+  using std::sqrt;
+  Index n = col0.size();
+  Index m = perm.size();
+  if(m==0)
+  {
+    zhat.setZero();
+    return;
+  }
+  Index last = perm(m-1);
+  // The offset permits to skip deflated entries while computing zhat
+  for (Index k = 0; k < n; ++k)
+  {
+    if (col0(k) == Literal(0)) // deflated
+      zhat(k) = Literal(0);
+    else
+    {
+      // see equation (3.6)
+      RealScalar dk = diag(k);
+      RealScalar prod = (singVals(last) + dk) * (mus(last) + (shifts(last) - dk));
+
+      for(Index l = 0; l<m; ++l)
+      {
+        Index i = perm(l);
+        if(i!=k)
+        {
+          Index j = i<k ? i : perm(l-1);
+          prod *= ((singVals(j)+dk) / ((diag(i)+dk))) * ((mus(j)+(shifts(j)-dk)) / ((diag(i)-dk)));
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+          if(i!=k && std::abs(((singVals(j)+dk)*(mus(j)+(shifts(j)-dk)))/((diag(i)+dk)*(diag(i)-dk)) - 1) > 0.9 )
+            std::cout << "     " << ((singVals(j)+dk)*(mus(j)+(shifts(j)-dk)))/((diag(i)+dk)*(diag(i)-dk)) << " == (" << (singVals(j)+dk) << " * " << (mus(j)+(shifts(j)-dk))
+                       << ") / (" << (diag(i)+dk) << " * " << (diag(i)-dk) << ")\n";
+#endif
+        }
+      }
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+      std::cout << "zhat(" << k << ") =  sqrt( " << prod << ")  ;  " << (singVals(last) + dk) << " * " << mus(last) + shifts(last) << " - " << dk << "\n";
+#endif
+      RealScalar tmp = sqrt(prod);
+      zhat(k) = col0(k) > Literal(0) ? tmp : -tmp;
+    }
+  }
+}
+
+// compute singular vectors
+template <typename MatrixType>
+void BDCSVD<MatrixType>::computeSingVecs
+   (const ArrayRef& zhat, const ArrayRef& diag, const IndicesRef &perm, const VectorType& singVals,
+    const ArrayRef& shifts, const ArrayRef& mus, MatrixXr& U, MatrixXr& V)
+{
+  Index n = zhat.size();
+  Index m = perm.size();
+  
+  for (Index k = 0; k < n; ++k)
+  {
+    if (zhat(k) == Literal(0))
+    {
+      U.col(k) = VectorType::Unit(n+1, k);
+      if (m_compV) V.col(k) = VectorType::Unit(n, k);
+    }
+    else
+    {
+      U.col(k).setZero();
+      for(Index l=0;l<m;++l)
+      {
+        Index i = perm(l);
+        U(i,k) = zhat(i)/(((diag(i) - shifts(k)) - mus(k)) )/( (diag(i) + singVals[k]));
+      }
+      U(n,k) = Literal(0);
+      U.col(k).normalize();
+    
+      if (m_compV)
+      {
+        V.col(k).setZero();
+        for(Index l=1;l<m;++l)
+        {
+          Index i = perm(l);
+          V(i,k) = diag(i) * zhat(i) / (((diag(i) - shifts(k)) - mus(k)) )/( (diag(i) + singVals[k]));
+        }
+        V(0,k) = Literal(-1);
+        V.col(k).normalize();
+      }
+    }
+  }
+  U.col(n) = VectorType::Unit(n+1, n);
+}
+
+
+// page 12_13
+// i >= 1, di almost null and zi non null.
+// We use a rotation to zero out zi applied to the left of M
+template <typename MatrixType>
+void BDCSVD<MatrixType>::deflation43(Index firstCol, Index shift, Index i, Index size)
+{
+  using std::abs;
+  using std::sqrt;
+  using std::pow;
+  Index start = firstCol + shift;
+  RealScalar c = m_computed(start, start);
+  RealScalar s = m_computed(start+i, start);
+  RealScalar r = sqrt(numext::abs2(c) + numext::abs2(s));
+  if (r == Literal(0))
+  {
+    m_computed(start+i, start+i) = Literal(0);
+    return;
+  }
+  m_computed(start,start) = r;  
+  m_computed(start+i, start) = Literal(0);
+  m_computed(start+i, start+i) = Literal(0);
+  
+  JacobiRotation<RealScalar> J(c/r,-s/r);
+  if (m_compU)  m_naiveU.middleRows(firstCol, size+1).applyOnTheRight(firstCol, firstCol+i, J);
+  else          m_naiveU.applyOnTheRight(firstCol, firstCol+i, J);
+}// end deflation 43
+
+
+// page 13
+// i,j >= 1, i!=j and |di - dj| < epsilon * norm2(M)
+// We apply two rotations to have zj = 0;
+// TODO deflation44 is still broken and not properly tested
+template <typename MatrixType>
+void BDCSVD<MatrixType>::deflation44(Index firstColu , Index firstColm, Index firstRowW, Index firstColW, Index i, Index j, Index size)
+{
+  using std::abs;
+  using std::sqrt;
+  using std::conj;
+  using std::pow;
+  RealScalar c = m_computed(firstColm+i, firstColm);
+  RealScalar s = m_computed(firstColm+j, firstColm);
+  RealScalar r = sqrt(numext::abs2(c) + numext::abs2(s));
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE
+  std::cout << "deflation 4.4: " << i << "," << j << " -> " << c << " " << s << " " << r << " ; "
+    << m_computed(firstColm + i-1, firstColm)  << " "
+    << m_computed(firstColm + i, firstColm)  << " "
+    << m_computed(firstColm + i+1, firstColm) << " "
+    << m_computed(firstColm + i+2, firstColm) << "\n";
+  std::cout << m_computed(firstColm + i-1, firstColm + i-1)  << " "
+    << m_computed(firstColm + i, firstColm+i)  << " "
+    << m_computed(firstColm + i+1, firstColm+i+1) << " "
+    << m_computed(firstColm + i+2, firstColm+i+2) << "\n";
+#endif
+  if (r==Literal(0))
+  {
+    m_computed(firstColm + i, firstColm + i) = m_computed(firstColm + j, firstColm + j);
+    return;
+  }
+  c/=r;
+  s/=r;
+  m_computed(firstColm + i, firstColm) = r;  
+  m_computed(firstColm + j, firstColm + j) = m_computed(firstColm + i, firstColm + i);
+  m_computed(firstColm + j, firstColm) = Literal(0);
+
+  JacobiRotation<RealScalar> J(c,-s);
+  if (m_compU)  m_naiveU.middleRows(firstColu, size+1).applyOnTheRight(firstColu + i, firstColu + j, J);
+  else          m_naiveU.applyOnTheRight(firstColu+i, firstColu+j, J);
+  if (m_compV)  m_naiveV.middleRows(firstRowW, size).applyOnTheRight(firstColW + i, firstColW + j, J);
+}// end deflation 44
+
+
+// acts on block from (firstCol+shift, firstCol+shift) to (lastCol+shift, lastCol+shift) [inclusive]
+template <typename MatrixType>
+void BDCSVD<MatrixType>::deflation(Index firstCol, Index lastCol, Index k, Index firstRowW, Index firstColW, Index shift)
+{
+  using std::sqrt;
+  using std::abs;
+  const Index length = lastCol + 1 - firstCol;
+  
+  Block<MatrixXr,Dynamic,1> col0(m_computed, firstCol+shift, firstCol+shift, length, 1);
+  Diagonal<MatrixXr> fulldiag(m_computed);
+  VectorBlock<Diagonal<MatrixXr>,Dynamic> diag(fulldiag, firstCol+shift, length);
+  
+  const RealScalar considerZero = (std::numeric_limits<RealScalar>::min)();
+  RealScalar maxDiag = diag.tail((std::max)(Index(1),length-1)).cwiseAbs().maxCoeff();
+  RealScalar epsilon_strict = numext::maxi<RealScalar>(considerZero,NumTraits<RealScalar>::epsilon() * maxDiag);
+  RealScalar epsilon_coarse = Literal(8) * NumTraits<RealScalar>::epsilon() * numext::maxi<RealScalar>(col0.cwiseAbs().maxCoeff(), maxDiag);
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(m_naiveU.allFinite());
+  assert(m_naiveV.allFinite());
+  assert(m_computed.allFinite());
+#endif
+
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE  
+  std::cout << "\ndeflate:" << diag.head(k+1).transpose() << "  |  " << diag.segment(k+1,length-k-1).transpose() << "\n";
+#endif
+  
+  //condition 4.1
+  if (diag(0) < epsilon_coarse)
+  { 
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE
+    std::cout << "deflation 4.1, because " << diag(0) << " < " << epsilon_coarse << "\n";
+#endif
+    diag(0) = epsilon_coarse;
+  }
+
+  //condition 4.2
+  for (Index i=1;i<length;++i)
+    if (abs(col0(i)) < epsilon_strict)
+    {
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE
+      std::cout << "deflation 4.2, set z(" << i << ") to zero because " << abs(col0(i)) << " < " << epsilon_strict << "  (diag(" << i << ")=" << diag(i) << ")\n";
+#endif
+      col0(i) = Literal(0);
+    }
+
+  //condition 4.3
+  for (Index i=1;i<length; i++)
+    if (diag(i) < epsilon_coarse)
+    {
+#ifdef  EIGEN_BDCSVD_DEBUG_VERBOSE
+      std::cout << "deflation 4.3, cancel z(" << i << ")=" << col0(i) << " because diag(" << i << ")=" << diag(i) << " < " << epsilon_coarse << "\n";
+#endif
+      deflation43(firstCol, shift, i, length);
+    }
+
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(m_naiveU.allFinite());
+  assert(m_naiveV.allFinite());
+  assert(m_computed.allFinite());
+#endif
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  std::cout << "to be sorted: " << diag.transpose() << "\n\n";
+#endif
+  {
+    // Check for total deflation
+    // If we have a total deflation, then we have to consider col0(0)==diag(0) as a singular value during sorting
+    bool total_deflation = (col0.tail(length-1).array()<considerZero).all();
+    
+    // Sort the diagonal entries, since diag(1:k-1) and diag(k:length) are already sorted, let's do a sorted merge.
+    // First, compute the respective permutation.
+    Index *permutation = m_workspaceI.data();
+    {
+      permutation[0] = 0;
+      Index p = 1;
+      
+      // Move deflated diagonal entries at the end.
+      for(Index i=1; i<length; ++i)
+        if(abs(diag(i))<considerZero)
+          permutation[p++] = i;
+        
+      Index i=1, j=k+1;
+      for( ; p < length; ++p)
+      {
+             if (i > k)             permutation[p] = j++;
+        else if (j >= length)       permutation[p] = i++;
+        else if (diag(i) < diag(j)) permutation[p] = j++;
+        else                        permutation[p] = i++;
+      }
+    }
+    
+    // If we have a total deflation, then we have to insert diag(0) at the right place
+    if(total_deflation)
+    {
+      for(Index i=1; i<length; ++i)
+      {
+        Index pi = permutation[i];
+        if(abs(diag(pi))<considerZero || diag(0)<diag(pi))
+          permutation[i-1] = permutation[i];
+        else
+        {
+          permutation[i-1] = 0;
+          break;
+        }
+      }
+    }
+    
+    // Current index of each col, and current column of each index
+    Index *realInd = m_workspaceI.data()+length;
+    Index *realCol = m_workspaceI.data()+2*length;
+    
+    for(int pos = 0; pos< length; pos++)
+    {
+      realCol[pos] = pos;
+      realInd[pos] = pos;
+    }
+    
+    for(Index i = total_deflation?0:1; i < length; i++)
+    {
+      const Index pi = permutation[length - (total_deflation ? i+1 : i)];
+      const Index J = realCol[pi];
+      
+      using std::swap;
+      // swap diagonal and first column entries:
+      swap(diag(i), diag(J));
+      if(i!=0 && J!=0) swap(col0(i), col0(J));
+
+      // change columns
+      if (m_compU) m_naiveU.col(firstCol+i).segment(firstCol, length + 1).swap(m_naiveU.col(firstCol+J).segment(firstCol, length + 1));
+      else         m_naiveU.col(firstCol+i).segment(0, 2)                .swap(m_naiveU.col(firstCol+J).segment(0, 2));
+      if (m_compV) m_naiveV.col(firstColW + i).segment(firstRowW, length).swap(m_naiveV.col(firstColW + J).segment(firstRowW, length));
+
+      //update real pos
+      const Index realI = realInd[i];
+      realCol[realI] = J;
+      realCol[pi] = i;
+      realInd[J] = realI;
+      realInd[i] = pi;
+    }
+  }
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+  std::cout << "sorted: " << diag.transpose().format(bdcsvdfmt) << "\n";
+  std::cout << "      : " << col0.transpose() << "\n\n";
+#endif
+    
+  //condition 4.4
+  {
+    Index i = length-1;
+    while(i>0 && (abs(diag(i))<considerZero || abs(col0(i))<considerZero)) --i;
+    for(; i>1;--i)
+       if( (diag(i) - diag(i-1)) < NumTraits<RealScalar>::epsilon()*maxDiag )
+      {
+#ifdef EIGEN_BDCSVD_DEBUG_VERBOSE
+        std::cout << "deflation 4.4 with i = " << i << " because " << (diag(i) - diag(i-1)) << " < " << NumTraits<RealScalar>::epsilon()*diag(i) << "\n";
+#endif
+        eigen_internal_assert(abs(diag(i) - diag(i-1))<epsilon_coarse && " diagonal entries are not properly sorted");
+        deflation44(firstCol, firstCol + shift, firstRowW, firstColW, i-1, i, length);
+      }
+  }
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  for(Index j=2;j<length;++j)
+    assert(diag(j-1)<=diag(j) || abs(diag(j))<considerZero);
+#endif
+  
+#ifdef EIGEN_BDCSVD_SANITY_CHECKS
+  assert(m_naiveU.allFinite());
+  assert(m_naiveV.allFinite());
+  assert(m_computed.allFinite());
+#endif
+}//end deflation
+
+#ifndef __CUDACC__
+/** \svd_module
+  *
+  * \return the singular value decomposition of \c *this computed by Divide & Conquer algorithm
+  *
+  * \sa class BDCSVD
+  */
+template<typename Derived>
+BDCSVD<typename MatrixBase<Derived>::PlainObject>
+MatrixBase<Derived>::bdcSvd(unsigned int computationOptions) const
+{
+  return BDCSVD<PlainObject>(*this, computationOptions);
+}
+#endif
+
+} // end namespace Eigen
+
+#endif

DELETED 3rd_party/eigen/Eigen/src/SVD/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/SVD/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/SVD/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/SVD/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SVD_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_SVD_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SVD COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/SVD/JacobiSVD.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SVD/JacobiSVD.h
+++ 3rd_party/eigen/Eigen/src/SVD/JacobiSVD.h
@@ -1,9 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2013-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -49,11 +50,10 @@
 
 template<typename MatrixType, int QRPreconditioner, int Case>
 class qr_preconditioner_impl<MatrixType, QRPreconditioner, Case, false>
 {
 public:
-  typedef typename MatrixType::Index Index;
   void allocate(const JacobiSVD<MatrixType, QRPreconditioner>&) {}
   bool run(JacobiSVD<MatrixType, QRPreconditioner>&, const MatrixType&)
   {
     return false;
   }
@@ -63,11 +63,10 @@
 
 template<typename MatrixType>
 class qr_preconditioner_impl<MatrixType, FullPivHouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
 {
 public:
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   enum
   {
     RowsAtCompileTime = MatrixType::RowsAtCompileTime,
     MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime
@@ -104,21 +103,22 @@
 
 template<typename MatrixType>
 class qr_preconditioner_impl<MatrixType, FullPivHouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
 {
 public:
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   enum
   {
     RowsAtCompileTime = MatrixType::RowsAtCompileTime,
     ColsAtCompileTime = MatrixType::ColsAtCompileTime,
     MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    Options = MatrixType::Options
+    TrOptions = RowsAtCompileTime==1 ? (MatrixType::Options & ~(RowMajor))
+              : ColsAtCompileTime==1 ? (MatrixType::Options |   RowMajor)
+              : MatrixType::Options
   };
-  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, Options, MaxColsAtCompileTime, MaxRowsAtCompileTime>
+  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, TrOptions, MaxColsAtCompileTime, MaxRowsAtCompileTime>
           TransposeTypeWithSameStorageOrder;
 
   void allocate(const JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd)
   {
     if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
@@ -154,12 +154,10 @@
 
 template<typename MatrixType>
 class qr_preconditioner_impl<MatrixType, ColPivHouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
 {
 public:
-  typedef typename MatrixType::Index Index;
-
   void allocate(const JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd)
   {
     if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
     {
       m_qr.~QRType();
@@ -195,22 +193,23 @@
 
 template<typename MatrixType>
 class qr_preconditioner_impl<MatrixType, ColPivHouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
 {
 public:
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   enum
   {
     RowsAtCompileTime = MatrixType::RowsAtCompileTime,
     ColsAtCompileTime = MatrixType::ColsAtCompileTime,
     MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    Options = MatrixType::Options
+    TrOptions = RowsAtCompileTime==1 ? (MatrixType::Options & ~(RowMajor))
+              : ColsAtCompileTime==1 ? (MatrixType::Options |   RowMajor)
+              : MatrixType::Options
   };
 
-  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, Options, MaxColsAtCompileTime, MaxRowsAtCompileTime>
+  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, TrOptions, MaxColsAtCompileTime, MaxRowsAtCompileTime>
           TransposeTypeWithSameStorageOrder;
 
   void allocate(const JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd)
   {
     if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
@@ -254,12 +253,10 @@
 
 template<typename MatrixType>
 class qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
 {
 public:
-  typedef typename MatrixType::Index Index;
-
   void allocate(const JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd)
   {
     if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
     {
       m_qr.~QRType();
@@ -294,11 +291,10 @@
 
 template<typename MatrixType>
 class qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
 {
 public:
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   enum
   {
     RowsAtCompileTime = MatrixType::RowsAtCompileTime,
     ColsAtCompileTime = MatrixType::ColsAtCompileTime,
@@ -356,34 +352,44 @@
 
 template<typename MatrixType, int QRPreconditioner>
 struct svd_precondition_2x2_block_to_be_real<MatrixType, QRPreconditioner, false>
 {
   typedef JacobiSVD<MatrixType, QRPreconditioner> SVD;
-  typedef typename SVD::Index Index;
-  static void run(typename SVD::WorkMatrixType&, SVD&, Index, Index) {}
+  typedef typename MatrixType::RealScalar RealScalar;
+  static bool run(typename SVD::WorkMatrixType&, SVD&, Index, Index, RealScalar&) { return true; }
 };
 
 template<typename MatrixType, int QRPreconditioner>
 struct svd_precondition_2x2_block_to_be_real<MatrixType, QRPreconditioner, true>
 {
   typedef JacobiSVD<MatrixType, QRPreconditioner> SVD;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename SVD::Index Index;
-  static void run(typename SVD::WorkMatrixType& work_matrix, SVD& svd, Index p, Index q)
+  static bool run(typename SVD::WorkMatrixType& work_matrix, SVD& svd, Index p, Index q, RealScalar& maxDiagEntry)
   {
     using std::sqrt;
+    using std::abs;
     Scalar z;
     JacobiRotation<Scalar> rot;
     RealScalar n = sqrt(numext::abs2(work_matrix.coeff(p,p)) + numext::abs2(work_matrix.coeff(q,p)));
-    
+
+    const RealScalar considerAsZero = (std::numeric_limits<RealScalar>::min)();
+    const RealScalar precision = NumTraits<Scalar>::epsilon();
+
     if(n==0)
     {
-      z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q);
-      work_matrix.row(p) *= z;
-      if(svd.computeU()) svd.m_matrixU.col(p) *= conj(z);
-      if(work_matrix.coeff(q,q)!=Scalar(0))
+      // make sure first column is zero
+      work_matrix.coeffRef(p,p) = work_matrix.coeffRef(q,p) = Scalar(0);
+
+      if(abs(numext::imag(work_matrix.coeff(p,q)))>considerAsZero)
+      {
+        // work_matrix.coeff(p,q) can be zero if work_matrix.coeff(q,p) is not zero but small enough to underflow when computing n
+        z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q);
+        work_matrix.row(p) *= z;
+        if(svd.computeU()) svd.m_matrixU.col(p) *= conj(z);
+      }
+      if(abs(numext::imag(work_matrix.coeff(q,q)))>considerAsZero)
       {
         z = abs(work_matrix.coeff(q,q)) / work_matrix.coeff(q,q);
         work_matrix.row(q) *= z;
         if(svd.computeU()) svd.m_matrixU.col(q) *= conj(z);
       }
@@ -393,56 +399,37 @@
     {
       rot.c() = conj(work_matrix.coeff(p,p)) / n;
       rot.s() = work_matrix.coeff(q,p) / n;
       work_matrix.applyOnTheLeft(p,q,rot);
       if(svd.computeU()) svd.m_matrixU.applyOnTheRight(p,q,rot.adjoint());
-      if(work_matrix.coeff(p,q) != Scalar(0))
+      if(abs(numext::imag(work_matrix.coeff(p,q)))>considerAsZero)
       {
-        Scalar z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q);
+        z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q);
         work_matrix.col(q) *= z;
         if(svd.computeV()) svd.m_matrixV.col(q) *= z;
       }
-      if(work_matrix.coeff(q,q) != Scalar(0))
+      if(abs(numext::imag(work_matrix.coeff(q,q)))>considerAsZero)
       {
         z = abs(work_matrix.coeff(q,q)) / work_matrix.coeff(q,q);
         work_matrix.row(q) *= z;
         if(svd.computeU()) svd.m_matrixU.col(q) *= conj(z);
       }
     }
+
+    // update largest diagonal entry
+    maxDiagEntry = numext::maxi<RealScalar>(maxDiagEntry,numext::maxi<RealScalar>(abs(work_matrix.coeff(p,p)), abs(work_matrix.coeff(q,q))));
+    // and check whether the 2x2 block is already diagonal
+    RealScalar threshold = numext::maxi<RealScalar>(considerAsZero, precision * maxDiagEntry);
+    return abs(work_matrix.coeff(p,q))>threshold || abs(work_matrix.coeff(q,p)) > threshold;
   }
 };
 
-template<typename MatrixType, typename RealScalar, typename Index>
-void real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q,
-                            JacobiRotation<RealScalar> *j_left,
-                            JacobiRotation<RealScalar> *j_right)
-{
-  using std::sqrt;
-  using std::abs;
-  Matrix<RealScalar,2,2> m;
-  m << numext::real(matrix.coeff(p,p)), numext::real(matrix.coeff(p,q)),
-       numext::real(matrix.coeff(q,p)), numext::real(matrix.coeff(q,q));
-  JacobiRotation<RealScalar> rot1;
-  RealScalar t = m.coeff(0,0) + m.coeff(1,1);
-  RealScalar d = m.coeff(1,0) - m.coeff(0,1);
-  if(t == RealScalar(0))
-  {
-    rot1.c() = RealScalar(0);
-    rot1.s() = d > RealScalar(0) ? RealScalar(1) : RealScalar(-1);
-  }
-  else
-  {
-    RealScalar t2d2 = numext::hypot(t,d);
-    rot1.c() = abs(t)/t2d2;
-    rot1.s() = d/t2d2;
-    if(t<RealScalar(0))
-      rot1.s() = -rot1.s();
-  }
-  m.applyOnTheLeft(0,1,rot1);
-  j_right->makeJacobi(m,0,1);
-  *j_left  = rot1 * j_right->transpose();
-}
+template<typename _MatrixType, int QRPreconditioner> 
+struct traits<JacobiSVD<_MatrixType,QRPreconditioner> >
+{
+  typedef _MatrixType MatrixType;
+};
 
 } // end namespace internal
 
 /** \ingroup SVD_Module
   *
@@ -449,12 +436,12 @@
   *
   * \class JacobiSVD
   *
   * \brief Two-sided Jacobi SVD decomposition of a rectangular matrix
   *
-  * \param MatrixType the type of the matrix of which we are computing the SVD decomposition
-  * \param QRPreconditioner this optional parameter allows to specify the type of QR decomposition that will be used internally
+  * \tparam _MatrixType the type of the matrix of which we are computing the SVD decomposition
+  * \tparam QRPreconditioner this optional parameter allows to specify the type of QR decomposition that will be used internally
   *                        for the R-SVD step for non-square matrices. See discussion of possible values below.
   *
   * SVD decomposition consists in decomposing any n-by-p matrix \a A as a product
   *   \f[ A = U S V^* \f]
   * where \a U is a n-by-n unitary, \a V is a p-by-p unitary, and \a S is a n-by-p real positive matrix which is zero outside of its main diagonal;
@@ -496,17 +483,18 @@
   *     if QR preconditioning is needed before applying it anyway.
   *
   * \sa MatrixBase::jacobiSvd()
   */
 template<typename _MatrixType, int QRPreconditioner> class JacobiSVD
+ : public SVDBase<JacobiSVD<_MatrixType,QRPreconditioner> >
 {
+    typedef SVDBase<JacobiSVD> Base;
   public:
 
     typedef _MatrixType MatrixType;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
     enum {
       RowsAtCompileTime = MatrixType::RowsAtCompileTime,
       ColsAtCompileTime = MatrixType::ColsAtCompileTime,
       DiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime),
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
@@ -513,17 +501,14 @@
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
       MaxDiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(MaxRowsAtCompileTime,MaxColsAtCompileTime),
       MatrixOptions = MatrixType::Options
     };
 
-    typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime,
-                   MatrixOptions, MaxRowsAtCompileTime, MaxRowsAtCompileTime>
-            MatrixUType;
-    typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime,
-                   MatrixOptions, MaxColsAtCompileTime, MaxColsAtCompileTime>
-            MatrixVType;
-    typedef typename internal::plain_diag_type<MatrixType, RealScalar>::type SingularValuesType;
+    typedef typename Base::MatrixUType MatrixUType;
+    typedef typename Base::MatrixVType MatrixVType;
+    typedef typename Base::SingularValuesType SingularValuesType;
+    
     typedef typename internal::plain_row_type<MatrixType>::type RowType;
     typedef typename internal::plain_col_type<MatrixType>::type ColType;
     typedef Matrix<Scalar, DiagSizeAtCompileTime, DiagSizeAtCompileTime,
                    MatrixOptions, MaxDiagSizeAtCompileTime, MaxDiagSizeAtCompileTime>
             WorkMatrixType;
@@ -532,15 +517,10 @@
       *
       * The default constructor is useful in cases in which the user intends to
       * perform decompositions via JacobiSVD::compute(const MatrixType&).
       */
     JacobiSVD()
-      : m_isInitialized(false),
-        m_isAllocated(false),
-        m_usePrescribedThreshold(false),
-        m_computationOptions(0),
-        m_rows(-1), m_cols(-1), m_diagSize(0)
     {}
 
 
     /** \brief Default Constructor with memory preallocation
       *
@@ -547,15 +527,10 @@
       * Like the default constructor but with preallocation of the internal data
       * according to the specified problem size.
       * \sa JacobiSVD()
       */
     JacobiSVD(Index rows, Index cols, unsigned int computationOptions = 0)
-      : m_isInitialized(false),
-        m_isAllocated(false),
-        m_usePrescribedThreshold(false),
-        m_computationOptions(0),
-        m_rows(-1), m_cols(-1)
     {
       allocate(rows, cols, computationOptions);
     }
 
     /** \brief Constructor performing the decomposition of given matrix.
@@ -566,16 +541,11 @@
      *                           #ComputeFullV, #ComputeThinV.
      *
      * Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not
      * available with the (non-default) FullPivHouseholderQR preconditioner.
      */
-    JacobiSVD(const MatrixType& matrix, unsigned int computationOptions = 0)
-      : m_isInitialized(false),
-        m_isAllocated(false),
-        m_usePrescribedThreshold(false),
-        m_computationOptions(0),
-        m_rows(-1), m_cols(-1)
+    explicit JacobiSVD(const MatrixType& matrix, unsigned int computationOptions = 0)
     {
       compute(matrix, computationOptions);
     }
 
     /** \brief Method performing the decomposition of given matrix using custom options.
@@ -599,163 +569,37 @@
     JacobiSVD& compute(const MatrixType& matrix)
     {
       return compute(matrix, m_computationOptions);
     }
 
-    /** \returns the \a U matrix.
-     *
-     * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p,
-     * the U matrix is n-by-n if you asked for #ComputeFullU, and is n-by-m if you asked for #ComputeThinU.
-     *
-     * The \a m first columns of \a U are the left singular vectors of the matrix being decomposed.
-     *
-     * This method asserts that you asked for \a U to be computed.
-     */
-    const MatrixUType& matrixU() const
-    {
-      eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
-      eigen_assert(computeU() && "This JacobiSVD decomposition didn't compute U. Did you ask for it?");
-      return m_matrixU;
-    }
-
-    /** \returns the \a V matrix.
-     *
-     * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p,
-     * the V matrix is p-by-p if you asked for #ComputeFullV, and is p-by-m if you asked for ComputeThinV.
-     *
-     * The \a m first columns of \a V are the right singular vectors of the matrix being decomposed.
-     *
-     * This method asserts that you asked for \a V to be computed.
-     */
-    const MatrixVType& matrixV() const
-    {
-      eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
-      eigen_assert(computeV() && "This JacobiSVD decomposition didn't compute V. Did you ask for it?");
-      return m_matrixV;
-    }
-
-    /** \returns the vector of singular values.
-     *
-     * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p, the
-     * returned vector has size \a m.  Singular values are always sorted in decreasing order.
-     */
-    const SingularValuesType& singularValues() const
-    {
-      eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
-      return m_singularValues;
-    }
-
-    /** \returns true if \a U (full or thin) is asked for in this SVD decomposition */
-    inline bool computeU() const { return m_computeFullU || m_computeThinU; }
-    /** \returns true if \a V (full or thin) is asked for in this SVD decomposition */
-    inline bool computeV() const { return m_computeFullV || m_computeThinV; }
-
-    /** \returns a (least squares) solution of \f$ A x = b \f$ using the current SVD decomposition of A.
-      *
-      * \param b the right-hand-side of the equation to solve.
-      *
-      * \note Solving requires both U and V to be computed. Thin U and V are enough, there is no need for full U or V.
-      *
-      * \note SVD solving is implicitly least-squares. Thus, this method serves both purposes of exact solving and least-squares solving.
-      * In other words, the returned solution is guaranteed to minimize the Euclidean norm \f$ \Vert A x - b \Vert \f$.
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<JacobiSVD, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
-      eigen_assert(computeU() && computeV() && "JacobiSVD::solve() requires both unitaries U and V to be computed (thin unitaries suffice).");
-      return internal::solve_retval<JacobiSVD, Rhs>(*this, b.derived());
-    }
-
-    /** \returns the number of singular values that are not exactly 0 */
-    Index nonzeroSingularValues() const
-    {
-      eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
-      return m_nonzeroSingularValues;
-    }
-    
-    /** \returns the rank of the matrix of which \c *this is the SVD.
-      *
-      * \note This method has to determine which singular values should be considered nonzero.
-      *       For that, it uses the threshold value that you can control by calling
-      *       setThreshold(const RealScalar&).
-      */
-    inline Index rank() const
-    {
-      using std::abs;
-      eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
-      if(m_singularValues.size()==0) return 0;
-      RealScalar premultiplied_threshold = m_singularValues.coeff(0) * threshold();
-      Index i = m_nonzeroSingularValues-1;
-      while(i>=0 && m_singularValues.coeff(i) < premultiplied_threshold) --i;
-      return i+1;
-    }
-    
-    /** Allows to prescribe a threshold to be used by certain methods, such as rank() and solve(),
-      * which need to determine when singular values are to be considered nonzero.
-      * This is not used for the SVD decomposition itself.
-      *
-      * When it needs to get the threshold value, Eigen calls threshold().
-      * The default is \c NumTraits<Scalar>::epsilon()
-      *
-      * \param threshold The new value to use as the threshold.
-      *
-      * A singular value will be considered nonzero if its value is strictly greater than
-      *  \f$ \vert singular value \vert \leqslant threshold \times \vert max singular value \vert \f$.
-      *
-      * If you want to come back to the default behavior, call setThreshold(Default_t)
-      */
-    JacobiSVD& setThreshold(const RealScalar& threshold)
-    {
-      m_usePrescribedThreshold = true;
-      m_prescribedThreshold = threshold;
-      return *this;
-    }
-
-    /** Allows to come back to the default behavior, letting Eigen use its default formula for
-      * determining the threshold.
-      *
-      * You should pass the special object Eigen::Default as parameter here.
-      * \code svd.setThreshold(Eigen::Default); \endcode
-      *
-      * See the documentation of setThreshold(const RealScalar&).
-      */
-    JacobiSVD& setThreshold(Default_t)
-    {
-      m_usePrescribedThreshold = false;
-      return *this;
-    }
-
-    /** Returns the threshold that will be used by certain methods such as rank().
-      *
-      * See the documentation of setThreshold(const RealScalar&).
-      */
-    RealScalar threshold() const
-    {
-      eigen_assert(m_isInitialized || m_usePrescribedThreshold);
-      return m_usePrescribedThreshold ? m_prescribedThreshold
-                                      : (std::max<Index>)(1,m_diagSize)*NumTraits<Scalar>::epsilon();
-    }
-
-    inline Index rows() const { return m_rows; }
-    inline Index cols() const { return m_cols; }
+    using Base::computeU;
+    using Base::computeV;
+    using Base::rows;
+    using Base::cols;
+    using Base::rank;
 
   private:
     void allocate(Index rows, Index cols, unsigned int computationOptions);
 
   protected:
-    MatrixUType m_matrixU;
-    MatrixVType m_matrixV;
-    SingularValuesType m_singularValues;
+    using Base::m_matrixU;
+    using Base::m_matrixV;
+    using Base::m_singularValues;
+    using Base::m_isInitialized;
+    using Base::m_isAllocated;
+    using Base::m_usePrescribedThreshold;
+    using Base::m_computeFullU;
+    using Base::m_computeThinU;
+    using Base::m_computeFullV;
+    using Base::m_computeThinV;
+    using Base::m_computationOptions;
+    using Base::m_nonzeroSingularValues;
+    using Base::m_rows;
+    using Base::m_cols;
+    using Base::m_diagSize;
+    using Base::m_prescribedThreshold;
     WorkMatrixType m_workMatrix;
-    bool m_isInitialized, m_isAllocated, m_usePrescribedThreshold;
-    bool m_computeFullU, m_computeThinU;
-    bool m_computeFullV, m_computeThinV;
-    unsigned int m_computationOptions;
-    Index m_nonzeroSingularValues, m_rows, m_cols, m_diagSize;
-    RealScalar m_prescribedThreshold;
 
     template<typename __MatrixType, int _QRPreconditioner, bool _IsComplex>
     friend struct internal::svd_precondition_2x2_block_to_be_real;
     template<typename __MatrixType, int _QRPreconditioner, int _Case, bool _DoAnything>
     friend struct internal::qr_preconditioner_impl;
@@ -809,11 +653,11 @@
                             : 0);
   m_workMatrix.resize(m_diagSize, m_diagSize);
   
   if(m_cols>m_rows)   m_qr_precond_morecols.allocate(*this);
   if(m_rows>m_cols)   m_qr_precond_morerows.allocate(*this);
-  if(m_cols!=m_cols)  m_scaledMatrix.resize(rows,cols);
+  if(m_rows!=m_cols)  m_scaledMatrix.resize(rows,cols);
 }
 
 template<typename MatrixType, int QRPreconditioner>
 JacobiSVD<MatrixType, QRPreconditioner>&
 JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsigned int computationOptions)
@@ -823,12 +667,12 @@
 
   // currently we stop when we reach precision 2*epsilon as the last bit of precision can require an unreasonable number of iterations,
   // only worsening the precision of U and V as we accumulate more rotations
   const RealScalar precision = RealScalar(2) * NumTraits<Scalar>::epsilon();
 
-  // limit for very small denormal numbers to be considered zero in order to avoid infinite loops (see bug 286)
-  const RealScalar considerAsZero = RealScalar(2) * std::numeric_limits<RealScalar>::denorm_min();
+  // limit for denormal numbers to be considered zero in order to avoid infinite loops (see bug 286)
+  const RealScalar considerAsZero = (std::numeric_limits<RealScalar>::min)();
 
   // Scaling factor to reduce over/under-flows
   RealScalar scale = matrix.cwiseAbs().maxCoeff();
   if(scale==RealScalar(0)) scale = RealScalar(1);
   
@@ -848,10 +692,11 @@
     if(m_computeFullV) m_matrixV.setIdentity(m_cols,m_cols);
     if(m_computeThinV) m_matrixV.setIdentity(m_cols, m_diagSize);
   }
 
   /*** step 2. The main Jacobi SVD iteration. ***/
+  RealScalar maxDiagEntry = m_workMatrix.cwiseAbs().diagonal().maxCoeff();
 
   bool finished = false;
   while(!finished)
   {
     finished = true;
@@ -863,42 +708,59 @@
       for(Index q = 0; q < p; ++q)
       {
         // if this 2x2 sub-matrix is not diagonal already...
         // notice that this comparison will evaluate to false if any NaN is involved, ensuring that NaN's don't
         // keep us iterating forever. Similarly, small denormal numbers are considered zero.
-        using std::max;
-        RealScalar threshold = (max)(considerAsZero, precision * (max)(abs(m_workMatrix.coeff(p,p)),
-                                                                       abs(m_workMatrix.coeff(q,q))));
-        // We compare both values to threshold instead of calling max to be robust to NaN (See bug 791)
+        RealScalar threshold = numext::maxi<RealScalar>(considerAsZero, precision * maxDiagEntry);
         if(abs(m_workMatrix.coeff(p,q))>threshold || abs(m_workMatrix.coeff(q,p)) > threshold)
         {
           finished = false;
-
           // perform SVD decomposition of 2x2 sub-matrix corresponding to indices p,q to make it diagonal
-          internal::svd_precondition_2x2_block_to_be_real<MatrixType, QRPreconditioner>::run(m_workMatrix, *this, p, q);
-          JacobiRotation<RealScalar> j_left, j_right;
-          internal::real_2x2_jacobi_svd(m_workMatrix, p, q, &j_left, &j_right);
-
-          // accumulate resulting Jacobi rotations
-          m_workMatrix.applyOnTheLeft(p,q,j_left);
-          if(computeU()) m_matrixU.applyOnTheRight(p,q,j_left.transpose());
-
-          m_workMatrix.applyOnTheRight(p,q,j_right);
-          if(computeV()) m_matrixV.applyOnTheRight(p,q,j_right);
+          // the complex to real operation returns true if the updated 2x2 block is not already diagonal
+          if(internal::svd_precondition_2x2_block_to_be_real<MatrixType, QRPreconditioner>::run(m_workMatrix, *this, p, q, maxDiagEntry))
+          {
+            JacobiRotation<RealScalar> j_left, j_right;
+            internal::real_2x2_jacobi_svd(m_workMatrix, p, q, &j_left, &j_right);
+
+            // accumulate resulting Jacobi rotations
+            m_workMatrix.applyOnTheLeft(p,q,j_left);
+            if(computeU()) m_matrixU.applyOnTheRight(p,q,j_left.transpose());
+
+            m_workMatrix.applyOnTheRight(p,q,j_right);
+            if(computeV()) m_matrixV.applyOnTheRight(p,q,j_right);
+
+            // keep track of the largest diagonal coefficient
+            maxDiagEntry = numext::maxi<RealScalar>(maxDiagEntry,numext::maxi<RealScalar>(abs(m_workMatrix.coeff(p,p)), abs(m_workMatrix.coeff(q,q))));
+          }
         }
       }
     }
   }
 
   /*** step 3. The work matrix is now diagonal, so ensure it's positive so its diagonal entries are the singular values ***/
 
   for(Index i = 0; i < m_diagSize; ++i)
   {
-    RealScalar a = abs(m_workMatrix.coeff(i,i));
-    m_singularValues.coeffRef(i) = a;
-    if(computeU() && (a!=RealScalar(0))) m_matrixU.col(i) *= m_workMatrix.coeff(i,i)/a;
+    // For a complex matrix, some diagonal coefficients might note have been
+    // treated by svd_precondition_2x2_block_to_be_real, and the imaginary part
+    // of some diagonal entry might not be null.
+    if(NumTraits<Scalar>::IsComplex && abs(numext::imag(m_workMatrix.coeff(i,i)))>considerAsZero)
+    {
+      RealScalar a = abs(m_workMatrix.coeff(i,i));
+      m_singularValues.coeffRef(i) = abs(a);
+      if(computeU()) m_matrixU.col(i) *= m_workMatrix.coeff(i,i)/a;
+    }
+    else
+    {
+      // m_workMatrix.coeff(i,i) is already real, no difficulty:
+      RealScalar a = numext::real(m_workMatrix.coeff(i,i));
+      m_singularValues.coeffRef(i) = abs(a);
+      if(computeU() && (a<RealScalar(0))) m_matrixU.col(i) = -m_matrixU.col(i);
+    }
   }
+  
+  m_singularValues *= scale;
 
   /*** step 4. Sort singular values in descending order and compute the number of nonzero singular values ***/
 
   m_nonzeroSingularValues = m_diagSize;
   for(Index i = 0; i < m_diagSize; i++)
@@ -916,42 +778,15 @@
       std::swap(m_singularValues.coeffRef(i), m_singularValues.coeffRef(pos));
       if(computeU()) m_matrixU.col(pos).swap(m_matrixU.col(i));
       if(computeV()) m_matrixV.col(pos).swap(m_matrixV.col(i));
     }
   }
-  
-  m_singularValues *= scale;
 
   m_isInitialized = true;
   return *this;
 }
 
-namespace internal {
-template<typename _MatrixType, int QRPreconditioner, typename Rhs>
-struct solve_retval<JacobiSVD<_MatrixType, QRPreconditioner>, Rhs>
-  : solve_retval_base<JacobiSVD<_MatrixType, QRPreconditioner>, Rhs>
-{
-  typedef JacobiSVD<_MatrixType, QRPreconditioner> JacobiSVDType;
-  EIGEN_MAKE_SOLVE_HELPERS(JacobiSVDType,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    eigen_assert(rhs().rows() == dec().rows());
-
-    // A = U S V^*
-    // So A^{-1} = V S^{-1} U^*
-
-    Matrix<Scalar, Dynamic, Rhs::ColsAtCompileTime, 0, _MatrixType::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime> tmp;
-    Index rank = dec().rank();
-    
-    tmp.noalias() = dec().matrixU().leftCols(rank).adjoint() * rhs();
-    tmp = dec().singularValues().head(rank).asDiagonal().inverse() * tmp;
-    dst = dec().matrixV().leftCols(rank) * tmp;
-  }
-};
-} // end namespace internal
-
 /** \svd_module
   *
   * \return the singular value decomposition of \c *this computed by two-sided
   * Jacobi transformations.
   *

ADDED   3rd_party/eigen/Eigen/src/SVD/JacobiSVD_LAPACKE.h
Index: 3rd_party/eigen/Eigen/src/SVD/JacobiSVD_LAPACKE.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SVD/JacobiSVD_LAPACKE.h
+++ 3rd_party/eigen/Eigen/src/SVD/JacobiSVD_LAPACKE.h
@@ -0,0 +1,90 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to LAPACKe
+ *    Singular Value Decomposition - SVD.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_JACOBISVD_LAPACKE_H
+#define EIGEN_JACOBISVD_LAPACKE_H
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by LAPACKe */
+
+#define EIGEN_LAPACKE_SVD(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_PREFIX, EIGCOLROW, LAPACKE_COLROW) \
+template<> inline \
+JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>& \
+JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) \
+{ \
+  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \
+  /*typedef MatrixType::Scalar Scalar;*/ \
+  /*typedef MatrixType::RealScalar RealScalar;*/ \
+  allocate(matrix.rows(), matrix.cols(), computationOptions); \
+\
+  /*const RealScalar precision = RealScalar(2) * NumTraits<Scalar>::epsilon();*/ \
+  m_nonzeroSingularValues = m_diagSize; \
+\
+  lapack_int lda = internal::convert_index<lapack_int>(matrix.outerStride()), ldu, ldvt; \
+  lapack_int matrix_order = LAPACKE_COLROW; \
+  char jobu, jobvt; \
+  LAPACKE_TYPE *u, *vt, dummy; \
+  jobu  = (m_computeFullU) ? 'A' : (m_computeThinU) ? 'S' : 'N'; \
+  jobvt = (m_computeFullV) ? 'A' : (m_computeThinV) ? 'S' : 'N'; \
+  if (computeU()) { \
+    ldu  = internal::convert_index<lapack_int>(m_matrixU.outerStride()); \
+    u    = (LAPACKE_TYPE*)m_matrixU.data(); \
+  } else { ldu=1; u=&dummy; }\
+  MatrixType localV; \
+  ldvt = (m_computeFullV) ? internal::convert_index<lapack_int>(m_cols) : (m_computeThinV) ? internal::convert_index<lapack_int>(m_diagSize) : 1; \
+  if (computeV()) { \
+    localV.resize(ldvt, m_cols); \
+    vt   = (LAPACKE_TYPE*)localV.data(); \
+  } else { ldvt=1; vt=&dummy; }\
+  Matrix<LAPACKE_RTYPE, Dynamic, Dynamic> superb; superb.resize(m_diagSize, 1); \
+  MatrixType m_temp; m_temp = matrix; \
+  LAPACKE_##LAPACKE_PREFIX##gesvd( matrix_order, jobu, jobvt, internal::convert_index<lapack_int>(m_rows), internal::convert_index<lapack_int>(m_cols), (LAPACKE_TYPE*)m_temp.data(), lda, (LAPACKE_RTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \
+  if (computeV()) m_matrixV = localV.adjoint(); \
+ /* for(int i=0;i<m_diagSize;i++) if (m_singularValues.coeffRef(i) < precision) { m_nonzeroSingularValues--; m_singularValues.coeffRef(i)=RealScalar(0);}*/ \
+  m_isInitialized = true; \
+  return *this; \
+}
+
+EIGEN_LAPACKE_SVD(double,   double,                double, d, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_SVD(float,    float,                 float , s, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_SVD(dcomplex, lapack_complex_double, double, z, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_LAPACKE_SVD(scomplex, lapack_complex_float,  float , c, ColMajor, LAPACK_COL_MAJOR)
+
+EIGEN_LAPACKE_SVD(double,   double,                double, d, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_SVD(float,    float,                 float , s, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_SVD(dcomplex, lapack_complex_double, double, z, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_LAPACKE_SVD(scomplex, lapack_complex_float,  float , c, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_JACOBISVD_LAPACKE_H

DELETED 3rd_party/eigen/Eigen/src/SVD/JacobiSVD_MKL.h
Index: 3rd_party/eigen/Eigen/src/SVD/JacobiSVD_MKL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SVD/JacobiSVD_MKL.h
+++ 3rd_party/eigen/Eigen/src/SVD/JacobiSVD_MKL.h
@@ -1,92 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *    Singular Value Decomposition - SVD.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_JACOBISVD_MKL_H
-#define EIGEN_JACOBISVD_MKL_H
-
-#include "Eigen/src/Core/util/MKL_support.h"
-
-namespace Eigen { 
-
-/** \internal Specialization for the data types supported by MKL */
-
-#define EIGEN_MKL_SVD(EIGTYPE, MKLTYPE, MKLRTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
-template<> inline \
-JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>& \
-JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) \
-{ \
-  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \
-  typedef MatrixType::Scalar Scalar; \
-  typedef MatrixType::RealScalar RealScalar; \
-  allocate(matrix.rows(), matrix.cols(), computationOptions); \
-\
-  /*const RealScalar precision = RealScalar(2) * NumTraits<Scalar>::epsilon();*/ \
-  m_nonzeroSingularValues = m_diagSize; \
-\
-  lapack_int lda = matrix.outerStride(), ldu, ldvt; \
-  lapack_int matrix_order = MKLCOLROW; \
-  char jobu, jobvt; \
-  MKLTYPE *u, *vt, dummy; \
-  jobu  = (m_computeFullU) ? 'A' : (m_computeThinU) ? 'S' : 'N'; \
-  jobvt = (m_computeFullV) ? 'A' : (m_computeThinV) ? 'S' : 'N'; \
-  if (computeU()) { \
-    ldu  = m_matrixU.outerStride(); \
-    u    = (MKLTYPE*)m_matrixU.data(); \
-  } else { ldu=1; u=&dummy; }\
-  MatrixType localV; \
-  ldvt = (m_computeFullV) ? m_cols : (m_computeThinV) ? m_diagSize : 1; \
-  if (computeV()) { \
-    localV.resize(ldvt, m_cols); \
-    vt   = (MKLTYPE*)localV.data(); \
-  } else { ldvt=1; vt=&dummy; }\
-  Matrix<MKLRTYPE, Dynamic, Dynamic> superb; superb.resize(m_diagSize, 1); \
-  MatrixType m_temp; m_temp = matrix; \
-  LAPACKE_##MKLPREFIX##gesvd( matrix_order, jobu, jobvt, m_rows, m_cols, (MKLTYPE*)m_temp.data(), lda, (MKLRTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \
-  if (computeV()) m_matrixV = localV.adjoint(); \
- /* for(int i=0;i<m_diagSize;i++) if (m_singularValues.coeffRef(i) < precision) { m_nonzeroSingularValues--; m_singularValues.coeffRef(i)=RealScalar(0);}*/ \
-  m_isInitialized = true; \
-  return *this; \
-}
-
-EIGEN_MKL_SVD(double,   double,        double, d, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_SVD(float,    float,         float , s, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_SVD(dcomplex, MKL_Complex16, double, z, ColMajor, LAPACK_COL_MAJOR)
-EIGEN_MKL_SVD(scomplex, MKL_Complex8,  float , c, ColMajor, LAPACK_COL_MAJOR)
-
-EIGEN_MKL_SVD(double,   double,        double, d, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_SVD(float,    float,         float , s, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_SVD(dcomplex, MKL_Complex16, double, z, RowMajor, LAPACK_ROW_MAJOR)
-EIGEN_MKL_SVD(scomplex, MKL_Complex8,  float , c, RowMajor, LAPACK_ROW_MAJOR)
-
-} // end namespace Eigen
-
-#endif // EIGEN_JACOBISVD_MKL_H

ADDED   3rd_party/eigen/Eigen/src/SVD/SVDBase.h
Index: 3rd_party/eigen/Eigen/src/SVD/SVDBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SVD/SVDBase.h
+++ 3rd_party/eigen/Eigen/src/SVD/SVDBase.h
@@ -0,0 +1,313 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com>
+// Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr>
+// Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr>
+// Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SVDBASE_H
+#define EIGEN_SVDBASE_H
+
+namespace Eigen {
+/** \ingroup SVD_Module
+ *
+ *
+ * \class SVDBase
+ *
+ * \brief Base class of SVD algorithms
+ *
+ * \tparam Derived the type of the actual SVD decomposition
+ *
+ * SVD decomposition consists in decomposing any n-by-p matrix \a A as a product
+ *   \f[ A = U S V^* \f]
+ * where \a U is a n-by-n unitary, \a V is a p-by-p unitary, and \a S is a n-by-p real positive matrix which is zero outside of its main diagonal;
+ * the diagonal entries of S are known as the \em singular \em values of \a A and the columns of \a U and \a V are known as the left
+ * and right \em singular \em vectors of \a A respectively.
+ *
+ * Singular values are always sorted in decreasing order.
+ *
+ * 
+ * You can ask for only \em thin \a U or \a V to be computed, meaning the following. In case of a rectangular n-by-p matrix, letting \a m be the
+ * smaller value among \a n and \a p, there are only \a m singular vectors; the remaining columns of \a U and \a V do not correspond to actual
+ * singular vectors. Asking for \em thin \a U or \a V means asking for only their \a m first columns to be formed. So \a U is then a n-by-m matrix,
+ * and \a V is then a p-by-m matrix. Notice that thin \a U and \a V are all you need for (least squares) solving.
+ *  
+ * If the input matrix has inf or nan coefficients, the result of the computation is undefined, but the computation is guaranteed to
+ * terminate in finite (and reasonable) time.
+ * \sa class BDCSVD, class JacobiSVD
+ */
+template<typename Derived>
+class SVDBase
+{
+
+public:
+  typedef typename internal::traits<Derived>::MatrixType MatrixType;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+  typedef typename MatrixType::StorageIndex StorageIndex;
+  typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
+  enum {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+    DiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime),
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
+    MaxDiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(MaxRowsAtCompileTime,MaxColsAtCompileTime),
+    MatrixOptions = MatrixType::Options
+  };
+
+  typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, MatrixOptions, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixUType;
+  typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime, MatrixOptions, MaxColsAtCompileTime, MaxColsAtCompileTime> MatrixVType;
+  typedef typename internal::plain_diag_type<MatrixType, RealScalar>::type SingularValuesType;
+  
+  Derived& derived() { return *static_cast<Derived*>(this); }
+  const Derived& derived() const { return *static_cast<const Derived*>(this); }
+
+  /** \returns the \a U matrix.
+   *
+   * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p,
+   * the U matrix is n-by-n if you asked for \link Eigen::ComputeFullU ComputeFullU \endlink, and is n-by-m if you asked for \link Eigen::ComputeThinU ComputeThinU \endlink.
+   *
+   * The \a m first columns of \a U are the left singular vectors of the matrix being decomposed.
+   *
+   * This method asserts that you asked for \a U to be computed.
+   */
+  const MatrixUType& matrixU() const
+  {
+    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    eigen_assert(computeU() && "This SVD decomposition didn't compute U. Did you ask for it?");
+    return m_matrixU;
+  }
+
+  /** \returns the \a V matrix.
+   *
+   * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p,
+   * the V matrix is p-by-p if you asked for \link Eigen::ComputeFullV ComputeFullV \endlink, and is p-by-m if you asked for \link Eigen::ComputeThinV ComputeThinV \endlink.
+   *
+   * The \a m first columns of \a V are the right singular vectors of the matrix being decomposed.
+   *
+   * This method asserts that you asked for \a V to be computed.
+   */
+  const MatrixVType& matrixV() const
+  {
+    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    eigen_assert(computeV() && "This SVD decomposition didn't compute V. Did you ask for it?");
+    return m_matrixV;
+  }
+
+  /** \returns the vector of singular values.
+   *
+   * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p, the
+   * returned vector has size \a m.  Singular values are always sorted in decreasing order.
+   */
+  const SingularValuesType& singularValues() const
+  {
+    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    return m_singularValues;
+  }
+
+  /** \returns the number of singular values that are not exactly 0 */
+  Index nonzeroSingularValues() const
+  {
+    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    return m_nonzeroSingularValues;
+  }
+  
+  /** \returns the rank of the matrix of which \c *this is the SVD.
+    *
+    * \note This method has to determine which singular values should be considered nonzero.
+    *       For that, it uses the threshold value that you can control by calling
+    *       setThreshold(const RealScalar&).
+    */
+  inline Index rank() const
+  {
+    using std::abs;
+    eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
+    if(m_singularValues.size()==0) return 0;
+    RealScalar premultiplied_threshold = numext::maxi<RealScalar>(m_singularValues.coeff(0) * threshold(), (std::numeric_limits<RealScalar>::min)());
+    Index i = m_nonzeroSingularValues-1;
+    while(i>=0 && m_singularValues.coeff(i) < premultiplied_threshold) --i;
+    return i+1;
+  }
+  
+  /** Allows to prescribe a threshold to be used by certain methods, such as rank() and solve(),
+    * which need to determine when singular values are to be considered nonzero.
+    * This is not used for the SVD decomposition itself.
+    *
+    * When it needs to get the threshold value, Eigen calls threshold().
+    * The default is \c NumTraits<Scalar>::epsilon()
+    *
+    * \param threshold The new value to use as the threshold.
+    *
+    * A singular value will be considered nonzero if its value is strictly greater than
+    *  \f$ \vert singular value \vert \leqslant threshold \times \vert max singular value \vert \f$.
+    *
+    * If you want to come back to the default behavior, call setThreshold(Default_t)
+    */
+  Derived& setThreshold(const RealScalar& threshold)
+  {
+    m_usePrescribedThreshold = true;
+    m_prescribedThreshold = threshold;
+    return derived();
+  }
+
+  /** Allows to come back to the default behavior, letting Eigen use its default formula for
+    * determining the threshold.
+    *
+    * You should pass the special object Eigen::Default as parameter here.
+    * \code svd.setThreshold(Eigen::Default); \endcode
+    *
+    * See the documentation of setThreshold(const RealScalar&).
+    */
+  Derived& setThreshold(Default_t)
+  {
+    m_usePrescribedThreshold = false;
+    return derived();
+  }
+
+  /** Returns the threshold that will be used by certain methods such as rank().
+    *
+    * See the documentation of setThreshold(const RealScalar&).
+    */
+  RealScalar threshold() const
+  {
+    eigen_assert(m_isInitialized || m_usePrescribedThreshold);
+    return m_usePrescribedThreshold ? m_prescribedThreshold
+                                    : (std::max<Index>)(1,m_diagSize)*NumTraits<Scalar>::epsilon();
+  }
+
+  /** \returns true if \a U (full or thin) is asked for in this SVD decomposition */
+  inline bool computeU() const { return m_computeFullU || m_computeThinU; }
+  /** \returns true if \a V (full or thin) is asked for in this SVD decomposition */
+  inline bool computeV() const { return m_computeFullV || m_computeThinV; }
+
+  inline Index rows() const { return m_rows; }
+  inline Index cols() const { return m_cols; }
+  
+  /** \returns a (least squares) solution of \f$ A x = b \f$ using the current SVD decomposition of A.
+    *
+    * \param b the right-hand-side of the equation to solve.
+    *
+    * \note Solving requires both U and V to be computed. Thin U and V are enough, there is no need for full U or V.
+    *
+    * \note SVD solving is implicitly least-squares. Thus, this method serves both purposes of exact solving and least-squares solving.
+    * In other words, the returned solution is guaranteed to minimize the Euclidean norm \f$ \Vert A x - b \Vert \f$.
+    */
+  template<typename Rhs>
+  inline const Solve<Derived, Rhs>
+  solve(const MatrixBase<Rhs>& b) const
+  {
+    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    eigen_assert(computeU() && computeV() && "SVD::solve() requires both unitaries U and V to be computed (thin unitaries suffice).");
+    return Solve<Derived, Rhs>(derived(), b.derived());
+  }
+  
+  #ifndef EIGEN_PARSED_BY_DOXYGEN
+  template<typename RhsType, typename DstType>
+  EIGEN_DEVICE_FUNC
+  void _solve_impl(const RhsType &rhs, DstType &dst) const;
+  #endif
+
+protected:
+  
+  static void check_template_parameters()
+  {
+    EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+  }
+  
+  // return true if already allocated
+  bool allocate(Index rows, Index cols, unsigned int computationOptions) ;
+
+  MatrixUType m_matrixU;
+  MatrixVType m_matrixV;
+  SingularValuesType m_singularValues;
+  bool m_isInitialized, m_isAllocated, m_usePrescribedThreshold;
+  bool m_computeFullU, m_computeThinU;
+  bool m_computeFullV, m_computeThinV;
+  unsigned int m_computationOptions;
+  Index m_nonzeroSingularValues, m_rows, m_cols, m_diagSize;
+  RealScalar m_prescribedThreshold;
+
+  /** \brief Default Constructor.
+   *
+   * Default constructor of SVDBase
+   */
+  SVDBase()
+    : m_isInitialized(false),
+      m_isAllocated(false),
+      m_usePrescribedThreshold(false),
+      m_computationOptions(0),
+      m_rows(-1), m_cols(-1), m_diagSize(0)
+  {
+    check_template_parameters();
+  }
+
+
+};
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename Derived>
+template<typename RhsType, typename DstType>
+void SVDBase<Derived>::_solve_impl(const RhsType &rhs, DstType &dst) const
+{
+  eigen_assert(rhs.rows() == rows());
+
+  // A = U S V^*
+  // So A^{-1} = V S^{-1} U^*
+
+  Matrix<Scalar, Dynamic, RhsType::ColsAtCompileTime, 0, MatrixType::MaxRowsAtCompileTime, RhsType::MaxColsAtCompileTime> tmp;
+  Index l_rank = rank();
+  tmp.noalias() =  m_matrixU.leftCols(l_rank).adjoint() * rhs;
+  tmp = m_singularValues.head(l_rank).asDiagonal().inverse() * tmp;
+  dst = m_matrixV.leftCols(l_rank) * tmp;
+}
+#endif
+
+template<typename MatrixType>
+bool SVDBase<MatrixType>::allocate(Index rows, Index cols, unsigned int computationOptions)
+{
+  eigen_assert(rows >= 0 && cols >= 0);
+
+  if (m_isAllocated &&
+      rows == m_rows &&
+      cols == m_cols &&
+      computationOptions == m_computationOptions)
+  {
+    return true;
+  }
+
+  m_rows = rows;
+  m_cols = cols;
+  m_isInitialized = false;
+  m_isAllocated = true;
+  m_computationOptions = computationOptions;
+  m_computeFullU = (computationOptions & ComputeFullU) != 0;
+  m_computeThinU = (computationOptions & ComputeThinU) != 0;
+  m_computeFullV = (computationOptions & ComputeFullV) != 0;
+  m_computeThinV = (computationOptions & ComputeThinV) != 0;
+  eigen_assert(!(m_computeFullU && m_computeThinU) && "SVDBase: you can't ask for both full and thin U");
+  eigen_assert(!(m_computeFullV && m_computeThinV) && "SVDBase: you can't ask for both full and thin V");
+  eigen_assert(EIGEN_IMPLIES(m_computeThinU || m_computeThinV, MatrixType::ColsAtCompileTime==Dynamic) &&
+	       "SVDBase: thin U and V are only available when your matrix has a dynamic number of columns.");
+
+  m_diagSize = (std::min)(m_rows, m_cols);
+  m_singularValues.resize(m_diagSize);
+  if(RowsAtCompileTime==Dynamic)
+    m_matrixU.resize(m_rows, m_computeFullU ? m_rows : m_computeThinU ? m_diagSize : 0);
+  if(ColsAtCompileTime==Dynamic)
+    m_matrixV.resize(m_cols, m_computeFullV ? m_cols : m_computeThinV ? m_diagSize : 0);
+
+  return false;
+}
+
+}// end namespace
+
+#endif // EIGEN_SVDBASE_H

Index: 3rd_party/eigen/Eigen/src/SVD/UpperBidiagonalization.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SVD/UpperBidiagonalization.h
+++ 3rd_party/eigen/Eigen/src/SVD/UpperBidiagonalization.h
@@ -1,9 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2013-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -26,19 +27,19 @@
       ColsAtCompileTime = MatrixType::ColsAtCompileTime,
       ColsAtCompileTimeMinusOne = internal::decrement_size<ColsAtCompileTime>::ret
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
     typedef Matrix<Scalar, 1, ColsAtCompileTime> RowVectorType;
     typedef Matrix<Scalar, RowsAtCompileTime, 1> ColVectorType;
-    typedef BandMatrix<RealScalar, ColsAtCompileTime, ColsAtCompileTime, 1, 0> BidiagonalType;
+    typedef BandMatrix<RealScalar, ColsAtCompileTime, ColsAtCompileTime, 1, 0, RowMajor> BidiagonalType;
     typedef Matrix<Scalar, ColsAtCompileTime, 1> DiagVectorType;
     typedef Matrix<Scalar, ColsAtCompileTimeMinusOne, 1> SuperDiagVectorType;
     typedef HouseholderSequence<
               const MatrixType,
-              CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, const Diagonal<const MatrixType,0> >
+              const typename internal::remove_all<typename Diagonal<const MatrixType,0>::ConjugateReturnType>::type
             > HouseholderUSequenceType;
     typedef HouseholderSequence<
               const typename internal::remove_all<typename MatrixType::ConjugateReturnType>::type,
               Diagonal<const MatrixType,1>,
               OnTheRight
@@ -50,19 +51,20 @@
     * The default constructor is useful in cases in which the user intends to
     * perform decompositions via Bidiagonalization::compute(const MatrixType&).
     */
     UpperBidiagonalization() : m_householder(), m_bidiagonal(), m_isInitialized(false) {}
 
-    UpperBidiagonalization(const MatrixType& matrix)
+    explicit UpperBidiagonalization(const MatrixType& matrix)
       : m_householder(matrix.rows(), matrix.cols()),
         m_bidiagonal(matrix.cols(), matrix.cols()),
         m_isInitialized(false)
     {
       compute(matrix);
     }
     
     UpperBidiagonalization& compute(const MatrixType& matrix);
+    UpperBidiagonalization& computeUnblocked(const MatrixType& matrix);
     
     const MatrixType& householder() const { return m_householder; }
     const BidiagonalType& bidiagonal() const { return m_bidiagonal; }
     
     const HouseholderUSequenceType householderU() const
@@ -83,49 +85,313 @@
     MatrixType m_householder;
     BidiagonalType m_bidiagonal;
     bool m_isInitialized;
 };
 
-template<typename _MatrixType>
-UpperBidiagonalization<_MatrixType>& UpperBidiagonalization<_MatrixType>::compute(const _MatrixType& matrix)
-{
-  Index rows = matrix.rows();
-  Index cols = matrix.cols();
-  
-  eigen_assert(rows >= cols && "UpperBidiagonalization is only for matrices satisfying rows>=cols.");
-  
-  m_householder = matrix;
-
-  ColVectorType temp(rows);
+// Standard upper bidiagonalization without fancy optimizations
+// This version should be faster for small matrix size
+template<typename MatrixType>
+void upperbidiagonalization_inplace_unblocked(MatrixType& mat,
+                                              typename MatrixType::RealScalar *diagonal,
+                                              typename MatrixType::RealScalar *upper_diagonal,
+                                              typename MatrixType::Scalar* tempData = 0)
+{
+  typedef typename MatrixType::Scalar Scalar;
+
+  Index rows = mat.rows();
+  Index cols = mat.cols();
+
+  typedef Matrix<Scalar,Dynamic,1,ColMajor,MatrixType::MaxRowsAtCompileTime,1> TempType;
+  TempType tempVector;
+  if(tempData==0)
+  {
+    tempVector.resize(rows);
+    tempData = tempVector.data();
+  }
 
   for (Index k = 0; /* breaks at k==cols-1 below */ ; ++k)
   {
     Index remainingRows = rows - k;
     Index remainingCols = cols - k - 1;
 
-    // construct left householder transform in-place in m_householder
-    m_householder.col(k).tail(remainingRows)
-                 .makeHouseholderInPlace(m_householder.coeffRef(k,k),
-                                         m_bidiagonal.template diagonal<0>().coeffRef(k));
-    // apply householder transform to remaining part of m_householder on the left
-    m_householder.bottomRightCorner(remainingRows, remainingCols)
-                 .applyHouseholderOnTheLeft(m_householder.col(k).tail(remainingRows-1),
-                                            m_householder.coeff(k,k),
-                                            temp.data());
+    // construct left householder transform in-place in A
+    mat.col(k).tail(remainingRows)
+       .makeHouseholderInPlace(mat.coeffRef(k,k), diagonal[k]);
+    // apply householder transform to remaining part of A on the left
+    mat.bottomRightCorner(remainingRows, remainingCols)
+       .applyHouseholderOnTheLeft(mat.col(k).tail(remainingRows-1), mat.coeff(k,k), tempData);
 
     if(k == cols-1) break;
-    
-    // construct right householder transform in-place in m_householder
-    m_householder.row(k).tail(remainingCols)
-                 .makeHouseholderInPlace(m_householder.coeffRef(k,k+1),
-                                         m_bidiagonal.template diagonal<1>().coeffRef(k));
-    // apply householder transform to remaining part of m_householder on the left
-    m_householder.bottomRightCorner(remainingRows-1, remainingCols)
-                 .applyHouseholderOnTheRight(m_householder.row(k).tail(remainingCols-1).transpose(),
-                                             m_householder.coeff(k,k+1),
-                                             temp.data());
-  }
+
+    // construct right householder transform in-place in mat
+    mat.row(k).tail(remainingCols)
+       .makeHouseholderInPlace(mat.coeffRef(k,k+1), upper_diagonal[k]);
+    // apply householder transform to remaining part of mat on the left
+    mat.bottomRightCorner(remainingRows-1, remainingCols)
+       .applyHouseholderOnTheRight(mat.row(k).tail(remainingCols-1).transpose(), mat.coeff(k,k+1), tempData);
+  }
+}
+
+/** \internal
+  * Helper routine for the block reduction to upper bidiagonal form.
+  *
+  * Let's partition the matrix A:
+  * 
+  *      | A00 A01 |
+  *  A = |         |
+  *      | A10 A11 |
+  *
+  * This function reduces to bidiagonal form the left \c rows x \a blockSize vertical panel [A00/A10]
+  * and the \a blockSize x \c cols horizontal panel [A00 A01] of the matrix \a A. The bottom-right block A11
+  * is updated using matrix-matrix products:
+  *   A22 -= V * Y^T - X * U^T
+  * where V and U contains the left and right Householder vectors. U and V are stored in A10, and A01
+  * respectively, and the update matrices X and Y are computed during the reduction.
+  * 
+  */
+template<typename MatrixType>
+void upperbidiagonalization_blocked_helper(MatrixType& A,
+                                           typename MatrixType::RealScalar *diagonal,
+                                           typename MatrixType::RealScalar *upper_diagonal,
+                                           Index bs,
+                                           Ref<Matrix<typename MatrixType::Scalar, Dynamic, Dynamic,
+                                                      traits<MatrixType>::Flags & RowMajorBit> > X,
+                                           Ref<Matrix<typename MatrixType::Scalar, Dynamic, Dynamic,
+                                                      traits<MatrixType>::Flags & RowMajorBit> > Y)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename NumTraits<RealScalar>::Literal Literal;
+  enum { StorageOrder = traits<MatrixType>::Flags & RowMajorBit };
+  typedef InnerStride<int(StorageOrder) == int(ColMajor) ? 1 : Dynamic> ColInnerStride;
+  typedef InnerStride<int(StorageOrder) == int(ColMajor) ? Dynamic : 1> RowInnerStride;
+  typedef Ref<Matrix<Scalar, Dynamic, 1>, 0, ColInnerStride>    SubColumnType;
+  typedef Ref<Matrix<Scalar, 1, Dynamic>, 0, RowInnerStride>    SubRowType;
+  typedef Ref<Matrix<Scalar, Dynamic, Dynamic, StorageOrder > > SubMatType;
+  
+  Index brows = A.rows();
+  Index bcols = A.cols();
+
+  Scalar tau_u, tau_u_prev(0), tau_v;
+
+  for(Index k = 0; k < bs; ++k)
+  {
+    Index remainingRows = brows - k;
+    Index remainingCols = bcols - k - 1;
+
+    SubMatType X_k1( X.block(k,0, remainingRows,k) );
+    SubMatType V_k1( A.block(k,0, remainingRows,k) );
+
+    // 1 - update the k-th column of A
+    SubColumnType v_k = A.col(k).tail(remainingRows);
+          v_k -= V_k1 * Y.row(k).head(k).adjoint();
+    if(k) v_k -= X_k1 * A.col(k).head(k);
+    
+    // 2 - construct left Householder transform in-place
+    v_k.makeHouseholderInPlace(tau_v, diagonal[k]);
+       
+    if(k+1<bcols)
+    {
+      SubMatType Y_k  ( Y.block(k+1,0, remainingCols, k+1) );
+      SubMatType U_k1 ( A.block(0,k+1, k,remainingCols) );
+      
+      // this eases the application of Householder transforAions
+      // A(k,k) will store tau_v later
+      A(k,k) = Scalar(1);
+
+      // 3 - Compute y_k^T = tau_v * ( A^T*v_k - Y_k-1*V_k-1^T*v_k - U_k-1*X_k-1^T*v_k )
+      {
+        SubColumnType y_k( Y.col(k).tail(remainingCols) );
+        
+        // let's use the begining of column k of Y as a temporary vector
+        SubColumnType tmp( Y.col(k).head(k) );
+        y_k.noalias()  = A.block(k,k+1, remainingRows,remainingCols).adjoint() * v_k; // bottleneck
+        tmp.noalias()  = V_k1.adjoint()  * v_k;
+        y_k.noalias() -= Y_k.leftCols(k) * tmp;
+        tmp.noalias()  = X_k1.adjoint()  * v_k;
+        y_k.noalias() -= U_k1.adjoint()  * tmp;
+        y_k *= numext::conj(tau_v);
+      }
+
+      // 4 - update k-th row of A (it will become u_k)
+      SubRowType u_k( A.row(k).tail(remainingCols) );
+      u_k = u_k.conjugate();
+      {
+        u_k -= Y_k * A.row(k).head(k+1).adjoint();
+        if(k) u_k -= U_k1.adjoint() * X.row(k).head(k).adjoint();
+      }
+
+      // 5 - construct right Householder transform in-place
+      u_k.makeHouseholderInPlace(tau_u, upper_diagonal[k]);
+
+      // this eases the application of Householder transformations
+      // A(k,k+1) will store tau_u later
+      A(k,k+1) = Scalar(1);
+
+      // 6 - Compute x_k = tau_u * ( A*u_k - X_k-1*U_k-1^T*u_k - V_k*Y_k^T*u_k )
+      {
+        SubColumnType x_k ( X.col(k).tail(remainingRows-1) );
+        
+        // let's use the begining of column k of X as a temporary vectors
+        // note that tmp0 and tmp1 overlaps
+        SubColumnType tmp0 ( X.col(k).head(k) ),
+                      tmp1 ( X.col(k).head(k+1) );
+                    
+        x_k.noalias()   = A.block(k+1,k+1, remainingRows-1,remainingCols) * u_k.transpose(); // bottleneck
+        tmp0.noalias()  = U_k1 * u_k.transpose();
+        x_k.noalias()  -= X_k1.bottomRows(remainingRows-1) * tmp0;
+        tmp1.noalias()  = Y_k.adjoint() * u_k.transpose();
+        x_k.noalias()  -= A.block(k+1,0, remainingRows-1,k+1) * tmp1;
+        x_k *= numext::conj(tau_u);
+        tau_u = numext::conj(tau_u);
+        u_k = u_k.conjugate();
+      }
+
+      if(k>0) A.coeffRef(k-1,k) = tau_u_prev;
+      tau_u_prev = tau_u;
+    }
+    else
+      A.coeffRef(k-1,k) = tau_u_prev;
+
+    A.coeffRef(k,k) = tau_v;
+  }
+  
+  if(bs<bcols)
+    A.coeffRef(bs-1,bs) = tau_u_prev;
+
+  // update A22
+  if(bcols>bs && brows>bs)
+  {
+    SubMatType A11( A.bottomRightCorner(brows-bs,bcols-bs) );
+    SubMatType A10( A.block(bs,0, brows-bs,bs) );
+    SubMatType A01( A.block(0,bs, bs,bcols-bs) );
+    Scalar tmp = A01(bs-1,0);
+    A01(bs-1,0) = Literal(1);
+    A11.noalias() -= A10 * Y.topLeftCorner(bcols,bs).bottomRows(bcols-bs).adjoint();
+    A11.noalias() -= X.topLeftCorner(brows,bs).bottomRows(brows-bs) * A01;
+    A01(bs-1,0) = tmp;
+  }
+}
+
+/** \internal
+  *
+  * Implementation of a block-bidiagonal reduction.
+  * It is based on the following paper:
+  *   The Design of a Parallel Dense Linear Algebra Software Library: Reduction to Hessenberg, Tridiagonal, and Bidiagonal Form.
+  *   by Jaeyoung Choi, Jack J. Dongarra, David W. Walker. (1995)
+  *   section 3.3
+  */
+template<typename MatrixType, typename BidiagType>
+void upperbidiagonalization_inplace_blocked(MatrixType& A, BidiagType& bidiagonal,
+                                            Index maxBlockSize=32,
+                                            typename MatrixType::Scalar* /*tempData*/ = 0)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef Block<MatrixType,Dynamic,Dynamic> BlockType;
+
+  Index rows = A.rows();
+  Index cols = A.cols();
+  Index size = (std::min)(rows, cols);
+
+  // X and Y are work space
+  enum { StorageOrder = traits<MatrixType>::Flags & RowMajorBit };
+  Matrix<Scalar,
+         MatrixType::RowsAtCompileTime,
+         Dynamic,
+         StorageOrder,
+         MatrixType::MaxRowsAtCompileTime> X(rows,maxBlockSize);
+  Matrix<Scalar,
+         MatrixType::ColsAtCompileTime,
+         Dynamic,
+         StorageOrder,
+         MatrixType::MaxColsAtCompileTime> Y(cols,maxBlockSize);
+  Index blockSize = (std::min)(maxBlockSize,size);
+
+  Index k = 0;
+  for(k = 0; k < size; k += blockSize)
+  {
+    Index bs = (std::min)(size-k,blockSize);  // actual size of the block
+    Index brows = rows - k;                   // rows of the block
+    Index bcols = cols - k;                   // columns of the block
+
+    // partition the matrix A:
+    // 
+    //      | A00 A01 A02 |
+    //      |             |
+    // A  = | A10 A11 A12 |
+    //      |             |
+    //      | A20 A21 A22 |
+    //
+    // where A11 is a bs x bs diagonal block,
+    // and let:
+    //      | A11 A12 |
+    //  B = |         |
+    //      | A21 A22 |
+
+    BlockType B = A.block(k,k,brows,bcols);
+    
+    // This stage performs the bidiagonalization of A11, A21, A12, and updating of A22.
+    // Finally, the algorithm continue on the updated A22.
+    //
+    // However, if B is too small, or A22 empty, then let's use an unblocked strategy
+    if(k+bs==cols || bcols<48) // somewhat arbitrary threshold
+    {
+      upperbidiagonalization_inplace_unblocked(B,
+                                               &(bidiagonal.template diagonal<0>().coeffRef(k)),
+                                               &(bidiagonal.template diagonal<1>().coeffRef(k)),
+                                               X.data()
+                                              );
+      break; // We're done
+    }
+    else
+    {
+      upperbidiagonalization_blocked_helper<BlockType>( B,
+                                                        &(bidiagonal.template diagonal<0>().coeffRef(k)),
+                                                        &(bidiagonal.template diagonal<1>().coeffRef(k)),
+                                                        bs,
+                                                        X.topLeftCorner(brows,bs),
+                                                        Y.topLeftCorner(bcols,bs)
+                                                      );
+    }
+  }
+}
+
+template<typename _MatrixType>
+UpperBidiagonalization<_MatrixType>& UpperBidiagonalization<_MatrixType>::computeUnblocked(const _MatrixType& matrix)
+{
+  Index rows = matrix.rows();
+  Index cols = matrix.cols();
+  EIGEN_ONLY_USED_FOR_DEBUG(cols);
+
+  eigen_assert(rows >= cols && "UpperBidiagonalization is only for Arices satisfying rows>=cols.");
+
+  m_householder = matrix;
+
+  ColVectorType temp(rows);
+
+  upperbidiagonalization_inplace_unblocked(m_householder,
+                                           &(m_bidiagonal.template diagonal<0>().coeffRef(0)),
+                                           &(m_bidiagonal.template diagonal<1>().coeffRef(0)),
+                                           temp.data());
+
+  m_isInitialized = true;
+  return *this;
+}
+
+template<typename _MatrixType>
+UpperBidiagonalization<_MatrixType>& UpperBidiagonalization<_MatrixType>::compute(const _MatrixType& matrix)
+{
+  Index rows = matrix.rows();
+  Index cols = matrix.cols();
+  EIGEN_ONLY_USED_FOR_DEBUG(rows);
+  EIGEN_ONLY_USED_FOR_DEBUG(cols);
+
+  eigen_assert(rows >= cols && "UpperBidiagonalization is only for Arices satisfying rows>=cols.");
+
+  m_householder = matrix;
+  upperbidiagonalization_inplace_blocked(m_householder, m_bidiagonal);
+            
   m_isInitialized = true;
   return *this;
 }
 
 #if 0

DELETED 3rd_party/eigen/Eigen/src/SparseCholesky/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/SparseCholesky/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCholesky/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/SparseCholesky/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SparseCholesky_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_SparseCholesky_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SparseCholesky COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/SparseCholesky/SimplicialCholesky.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCholesky/SimplicialCholesky.h
+++ 3rd_party/eigen/Eigen/src/SparseCholesky/SimplicialCholesky.h
@@ -15,47 +15,78 @@
 enum SimplicialCholeskyMode {
   SimplicialCholeskyLLT,
   SimplicialCholeskyLDLT
 };
 
+namespace internal {
+  template<typename CholMatrixType, typename InputMatrixType>
+  struct simplicial_cholesky_grab_input {
+    typedef CholMatrixType const * ConstCholMatrixPtr;
+    static void run(const InputMatrixType& input, ConstCholMatrixPtr &pmat, CholMatrixType &tmp)
+    {
+      tmp = input;
+      pmat = &tmp;
+    }
+  };
+  
+  template<typename MatrixType>
+  struct simplicial_cholesky_grab_input<MatrixType,MatrixType> {
+    typedef MatrixType const * ConstMatrixPtr;
+    static void run(const MatrixType& input, ConstMatrixPtr &pmat, MatrixType &/*tmp*/)
+    {
+      pmat = &input;
+    }
+  };
+} // end namespace internal
+
 /** \ingroup SparseCholesky_Module
-  * \brief A direct sparse Cholesky factorizations
+  * \brief A base class for direct sparse Cholesky factorizations
   *
-  * These classes provide LL^T and LDL^T Cholesky factorizations of sparse matrices that are
-  * selfadjoint and positive definite. The factorization allows for solving A.X = B where
+  * This is a base class for LL^T and LDL^T Cholesky factorizations of sparse matrices that are
+  * selfadjoint and positive definite. These factorizations allow for solving A.X = B where
   * X and B can be either dense or sparse.
   * 
   * In order to reduce the fill-in, a symmetric permutation P is applied prior to the factorization
   * such that the factorized matrix is P A P^-1.
   *
-  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
-  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
-  *               or Upper. Default is Lower.
+  * \tparam Derived the type of the derived class, that is the actual factorization type.
   *
   */
 template<typename Derived>
-class SimplicialCholeskyBase : internal::noncopyable
+class SimplicialCholeskyBase : public SparseSolverBase<Derived>
 {
+    typedef SparseSolverBase<Derived> Base;
+    using Base::m_isInitialized;
+    
   public:
     typedef typename internal::traits<Derived>::MatrixType MatrixType;
     typedef typename internal::traits<Derived>::OrderingType OrderingType;
     enum { UpLo = internal::traits<Derived>::UpLo };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
-    typedef SparseMatrix<Scalar,ColMajor,Index> CholMatrixType;
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    typedef SparseMatrix<Scalar,ColMajor,StorageIndex> CholMatrixType;
+    typedef CholMatrixType const * ConstCholMatrixPtr;
     typedef Matrix<Scalar,Dynamic,1> VectorType;
+    typedef Matrix<StorageIndex,Dynamic,1> VectorI;
+
+    enum {
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
 
   public:
+    
+    using Base::derived;
 
     /** Default constructor */
     SimplicialCholeskyBase()
-      : m_info(Success), m_isInitialized(false), m_shiftOffset(0), m_shiftScale(1)
+      : m_info(Success), m_shiftOffset(0), m_shiftScale(1)
     {}
 
-    SimplicialCholeskyBase(const MatrixType& matrix)
-      : m_info(Success), m_isInitialized(false), m_shiftOffset(0), m_shiftScale(1)
+    explicit SimplicialCholeskyBase(const MatrixType& matrix)
+      : m_info(Success), m_shiftOffset(0), m_shiftScale(1)
     {
       derived().compute(matrix);
     }
 
     ~SimplicialCholeskyBase()
@@ -77,46 +108,18 @@
     {
       eigen_assert(m_isInitialized && "Decomposition is not initialized.");
       return m_info;
     }
     
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<SimplicialCholeskyBase, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "Simplicial LLT or LDLT is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "SimplicialCholeskyBase::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<SimplicialCholeskyBase, Rhs>(*this, b.derived());
-    }
-    
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::sparse_solve_retval<SimplicialCholeskyBase, Rhs>
-    solve(const SparseMatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "Simplicial LLT or LDLT is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "SimplicialCholesky::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::sparse_solve_retval<SimplicialCholeskyBase, Rhs>(*this, b.derived());
-    }
-    
     /** \returns the permutation P
       * \sa permutationPinv() */
-    const PermutationMatrix<Dynamic,Dynamic,Index>& permutationP() const
+    const PermutationMatrix<Dynamic,Dynamic,StorageIndex>& permutationP() const
     { return m_P; }
     
     /** \returns the inverse P^-1 of the permutation P
       * \sa permutationP() */
-    const PermutationMatrix<Dynamic,Dynamic,Index>& permutationPinv() const
+    const PermutationMatrix<Dynamic,Dynamic,StorageIndex>& permutationPinv() const
     { return m_Pinv; }
 
     /** Sets the shift parameters that will be used to adjust the diagonal coefficients during the numerical factorization.
       *
       * During the numerical factorization, the diagonal coefficients are transformed by the following linear model:\n
@@ -148,11 +151,11 @@
       s << "  TOTAL:    " << (total>> 20) << "Mb" << "\n";
     }
 
     /** \internal */
     template<typename Rhs,typename Dest>
-    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
+    void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
     {
       eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
       eigen_assert(m_matrix.rows()==b.rows());
 
       if(m_info!=Success)
@@ -173,10 +176,16 @@
         derived().matrixU().solveInPlace(dest);
 
       if(m_P.size()>0)
         dest = m_Pinv * dest;
     }
+    
+    template<typename Rhs,typename Dest>
+    void _solve_impl(const SparseMatrixBase<Rhs> &b, SparseMatrixBase<Dest> &dest) const
+    {
+      internal::solve_sparse_through_dense_panels(derived(), b, dest);
+    }
 
 #endif // EIGEN_PARSED_BY_DOXYGEN
 
   protected:
     
@@ -184,40 +193,54 @@
     template<bool DoLDLT>
     void compute(const MatrixType& matrix)
     {
       eigen_assert(matrix.rows()==matrix.cols());
       Index size = matrix.cols();
-      CholMatrixType ap(size,size);
-      ordering(matrix, ap);
-      analyzePattern_preordered(ap, DoLDLT);
-      factorize_preordered<DoLDLT>(ap);
+      CholMatrixType tmp(size,size);
+      ConstCholMatrixPtr pmat;
+      ordering(matrix, pmat, tmp);
+      analyzePattern_preordered(*pmat, DoLDLT);
+      factorize_preordered<DoLDLT>(*pmat);
     }
     
     template<bool DoLDLT>
     void factorize(const MatrixType& a)
     {
       eigen_assert(a.rows()==a.cols());
-      int size = a.cols();
-      CholMatrixType ap(size,size);
-      ap.template selfadjointView<Upper>() = a.template selfadjointView<UpLo>().twistedBy(m_P);
-      factorize_preordered<DoLDLT>(ap);
+      Index size = a.cols();
+      CholMatrixType tmp(size,size);
+      ConstCholMatrixPtr pmat;
+      
+      if(m_P.size()==0 && (UpLo&Upper)==Upper)
+      {
+        // If there is no ordering, try to directly use the input matrix without any copy
+        internal::simplicial_cholesky_grab_input<CholMatrixType,MatrixType>::run(a, pmat, tmp);
+      }
+      else
+      {
+        tmp.template selfadjointView<Upper>() = a.template selfadjointView<UpLo>().twistedBy(m_P);
+        pmat = &tmp;
+      }
+      
+      factorize_preordered<DoLDLT>(*pmat);
     }
 
     template<bool DoLDLT>
     void factorize_preordered(const CholMatrixType& a);
 
     void analyzePattern(const MatrixType& a, bool doLDLT)
     {
       eigen_assert(a.rows()==a.cols());
-      int size = a.cols();
-      CholMatrixType ap(size,size);
-      ordering(a, ap);
-      analyzePattern_preordered(ap,doLDLT);
+      Index size = a.cols();
+      CholMatrixType tmp(size,size);
+      ConstCholMatrixPtr pmat;
+      ordering(a, pmat, tmp);
+      analyzePattern_preordered(*pmat,doLDLT);
     }
     void analyzePattern_preordered(const CholMatrixType& a, bool doLDLT);
     
-    void ordering(const MatrixType& a, CholMatrixType& ap);
+    void ordering(const MatrixType& a, ConstCholMatrixPtr &pmat, CholMatrixType& ap);
 
     /** keeps off-diagonal entries; drops diagonal entries */
     struct keep_diag {
       inline bool operator() (const Index& row, const Index& col, const Scalar&) const
       {
@@ -224,57 +247,56 @@
         return row!=col;
       }
     };
 
     mutable ComputationInfo m_info;
-    bool m_isInitialized;
     bool m_factorizationIsOk;
     bool m_analysisIsOk;
     
     CholMatrixType m_matrix;
     VectorType m_diag;                                // the diagonal coefficients (LDLT mode)
-    VectorXi m_parent;                                // elimination tree
-    VectorXi m_nonZerosPerCol;
-    PermutationMatrix<Dynamic,Dynamic,Index> m_P;     // the permutation
-    PermutationMatrix<Dynamic,Dynamic,Index> m_Pinv;  // the inverse permutation
+    VectorI m_parent;                                 // elimination tree
+    VectorI m_nonZerosPerCol;
+    PermutationMatrix<Dynamic,Dynamic,StorageIndex> m_P;     // the permutation
+    PermutationMatrix<Dynamic,Dynamic,StorageIndex> m_Pinv;  // the inverse permutation
 
     RealScalar m_shiftOffset;
     RealScalar m_shiftScale;
 };
 
-template<typename _MatrixType, int _UpLo = Lower, typename _Ordering = AMDOrdering<typename _MatrixType::Index> > class SimplicialLLT;
-template<typename _MatrixType, int _UpLo = Lower, typename _Ordering = AMDOrdering<typename _MatrixType::Index> > class SimplicialLDLT;
-template<typename _MatrixType, int _UpLo = Lower, typename _Ordering = AMDOrdering<typename _MatrixType::Index> > class SimplicialCholesky;
+template<typename _MatrixType, int _UpLo = Lower, typename _Ordering = AMDOrdering<typename _MatrixType::StorageIndex> > class SimplicialLLT;
+template<typename _MatrixType, int _UpLo = Lower, typename _Ordering = AMDOrdering<typename _MatrixType::StorageIndex> > class SimplicialLDLT;
+template<typename _MatrixType, int _UpLo = Lower, typename _Ordering = AMDOrdering<typename _MatrixType::StorageIndex> > class SimplicialCholesky;
 
 namespace internal {
 
 template<typename _MatrixType, int _UpLo, typename _Ordering> struct traits<SimplicialLLT<_MatrixType,_UpLo,_Ordering> >
 {
   typedef _MatrixType MatrixType;
   typedef _Ordering OrderingType;
   enum { UpLo = _UpLo };
   typedef typename MatrixType::Scalar                         Scalar;
-  typedef typename MatrixType::Index                          Index;
-  typedef SparseMatrix<Scalar, ColMajor, Index>               CholMatrixType;
-  typedef SparseTriangularView<CholMatrixType, Eigen::Lower>  MatrixL;
-  typedef SparseTriangularView<typename CholMatrixType::AdjointReturnType, Eigen::Upper>   MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m; }
-  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  typedef typename MatrixType::StorageIndex                   StorageIndex;
+  typedef SparseMatrix<Scalar, ColMajor, StorageIndex>        CholMatrixType;
+  typedef TriangularView<const CholMatrixType, Eigen::Lower>  MatrixL;
+  typedef TriangularView<const typename CholMatrixType::AdjointReturnType, Eigen::Upper>   MatrixU;
+  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
+  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
 };
 
 template<typename _MatrixType,int _UpLo, typename _Ordering> struct traits<SimplicialLDLT<_MatrixType,_UpLo,_Ordering> >
 {
   typedef _MatrixType MatrixType;
   typedef _Ordering OrderingType;
   enum { UpLo = _UpLo };
   typedef typename MatrixType::Scalar                             Scalar;
-  typedef typename MatrixType::Index                              Index;
-  typedef SparseMatrix<Scalar, ColMajor, Index>                   CholMatrixType;
-  typedef SparseTriangularView<CholMatrixType, Eigen::UnitLower>  MatrixL;
-  typedef SparseTriangularView<typename CholMatrixType::AdjointReturnType, Eigen::UnitUpper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m; }
-  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  typedef typename MatrixType::StorageIndex                       StorageIndex;
+  typedef SparseMatrix<Scalar, ColMajor, StorageIndex>            CholMatrixType;
+  typedef TriangularView<const CholMatrixType, Eigen::UnitLower>  MatrixL;
+  typedef TriangularView<const typename CholMatrixType::AdjointReturnType, Eigen::UnitUpper> MatrixU;
+  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
+  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
 };
 
 template<typename _MatrixType, int _UpLo, typename _Ordering> struct traits<SimplicialCholesky<_MatrixType,_UpLo,_Ordering> >
 {
   typedef _MatrixType MatrixType;
@@ -297,10 +319,12 @@
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
   * \tparam _Ordering The ordering method to use, either AMDOrdering<> or NaturalOrdering<>. Default is AMDOrdering<>
+  *
+  * \implsparsesolverconcept
   *
   * \sa class SimplicialLDLT, class AMDOrdering, class NaturalOrdering
   */
 template<typename _MatrixType, int _UpLo, typename _Ordering>
     class SimplicialLLT : public SimplicialCholeskyBase<SimplicialLLT<_MatrixType,_UpLo,_Ordering> >
@@ -309,21 +333,21 @@
     typedef _MatrixType MatrixType;
     enum { UpLo = _UpLo };
     typedef SimplicialCholeskyBase<SimplicialLLT> Base;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::StorageIndex StorageIndex;
     typedef SparseMatrix<Scalar,ColMajor,Index> CholMatrixType;
     typedef Matrix<Scalar,Dynamic,1> VectorType;
     typedef internal::traits<SimplicialLLT> Traits;
     typedef typename Traits::MatrixL  MatrixL;
     typedef typename Traits::MatrixU  MatrixU;
 public:
     /** Default constructor */
     SimplicialLLT() : Base() {}
     /** Constructs and performs the LLT factorization of \a matrix */
-    SimplicialLLT(const MatrixType& matrix)
+    explicit SimplicialLLT(const MatrixType& matrix)
         : Base(matrix) {}
 
     /** \returns an expression of the factor L */
     inline const MatrixL matrixL() const {
         eigen_assert(Base::m_factorizationIsOk && "Simplicial LLT not factorized");
@@ -386,10 +410,12 @@
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
   * \tparam _Ordering The ordering method to use, either AMDOrdering<> or NaturalOrdering<>. Default is AMDOrdering<>
+  *
+  * \implsparsesolverconcept
   *
   * \sa class SimplicialLLT, class AMDOrdering, class NaturalOrdering
   */
 template<typename _MatrixType, int _UpLo, typename _Ordering>
     class SimplicialLDLT : public SimplicialCholeskyBase<SimplicialLDLT<_MatrixType,_UpLo,_Ordering> >
@@ -398,22 +424,22 @@
     typedef _MatrixType MatrixType;
     enum { UpLo = _UpLo };
     typedef SimplicialCholeskyBase<SimplicialLDLT> Base;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
-    typedef SparseMatrix<Scalar,ColMajor,Index> CholMatrixType;
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    typedef SparseMatrix<Scalar,ColMajor,StorageIndex> CholMatrixType;
     typedef Matrix<Scalar,Dynamic,1> VectorType;
     typedef internal::traits<SimplicialLDLT> Traits;
     typedef typename Traits::MatrixL  MatrixL;
     typedef typename Traits::MatrixU  MatrixU;
 public:
     /** Default constructor */
     SimplicialLDLT() : Base() {}
 
     /** Constructs and performs the LLT factorization of \a matrix */
-    SimplicialLDLT(const MatrixType& matrix)
+    explicit SimplicialLDLT(const MatrixType& matrix)
         : Base(matrix) {}
 
     /** \returns a vector expression of the diagonal D */
     inline const VectorType vectorD() const {
         eigen_assert(Base::m_factorizationIsOk && "Simplicial LDLT not factorized");
@@ -480,20 +506,20 @@
     typedef _MatrixType MatrixType;
     enum { UpLo = _UpLo };
     typedef SimplicialCholeskyBase<SimplicialCholesky> Base;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
-    typedef SparseMatrix<Scalar,ColMajor,Index> CholMatrixType;
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    typedef SparseMatrix<Scalar,ColMajor,StorageIndex> CholMatrixType;
     typedef Matrix<Scalar,Dynamic,1> VectorType;
     typedef internal::traits<SimplicialCholesky> Traits;
     typedef internal::traits<SimplicialLDLT<MatrixType,UpLo> > LDLTTraits;
     typedef internal::traits<SimplicialLLT<MatrixType,UpLo>  > LLTTraits;
   public:
     SimplicialCholesky() : Base(), m_LDLT(true) {}
 
-    SimplicialCholesky(const MatrixType& matrix)
+    explicit SimplicialCholesky(const MatrixType& matrix)
       : Base(), m_LDLT(true)
     {
       compute(matrix);
     }
 
@@ -558,11 +584,11 @@
         Base::template factorize<false>(a);
     }
 
     /** \internal */
     template<typename Rhs,typename Dest>
-    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
+    void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
     {
       eigen_assert(Base::m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
       eigen_assert(Base::m_matrix.rows()==b.rows());
 
       if(Base::m_info!=Success)
@@ -593,10 +619,17 @@
       }
 
       if(Base::m_P.size()>0)
         dest = Base::m_Pinv * dest;
     }
+    
+    /** \internal */
+    template<typename Rhs,typename Dest>
+    void _solve_impl(const SparseMatrixBase<Rhs> &b, SparseMatrixBase<Dest> &dest) const
+    {
+      internal::solve_sparse_through_dense_panels(*this, b, dest);
+    }
     
     Scalar determinant() const
     {
       if(m_LDLT)
       {
@@ -612,60 +645,45 @@
   protected:
     bool m_LDLT;
 };
 
 template<typename Derived>
-void SimplicialCholeskyBase<Derived>::ordering(const MatrixType& a, CholMatrixType& ap)
+void SimplicialCholeskyBase<Derived>::ordering(const MatrixType& a, ConstCholMatrixPtr &pmat, CholMatrixType& ap)
 {
   eigen_assert(a.rows()==a.cols());
   const Index size = a.rows();
-  // Note that amd compute the inverse permutation
-  {
-    CholMatrixType C;
-    C = a.template selfadjointView<UpLo>();
-    
-    OrderingType ordering;
-    ordering(C,m_Pinv);
-  }
-
-  if(m_Pinv.size()>0)
-    m_P = m_Pinv.inverse();
-  else
-    m_P.resize(0);
-
-  ap.resize(size,size);
-  ap.template selfadjointView<Upper>() = a.template selfadjointView<UpLo>().twistedBy(m_P);
-}
-
-namespace internal {
-  
-template<typename Derived, typename Rhs>
-struct solve_retval<SimplicialCholeskyBase<Derived>, Rhs>
-  : solve_retval_base<SimplicialCholeskyBase<Derived>, Rhs>
-{
-  typedef SimplicialCholeskyBase<Derived> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec().derived()._solve(rhs(),dst);
-  }
-};
-
-template<typename Derived, typename Rhs>
-struct sparse_solve_retval<SimplicialCholeskyBase<Derived>, Rhs>
-  : sparse_solve_retval_base<SimplicialCholeskyBase<Derived>, Rhs>
-{
-  typedef SimplicialCholeskyBase<Derived> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    this->defaultEvalTo(dst);
-  }
-};
-
-} // end namespace internal
+  pmat = &ap;
+  // Note that ordering methods compute the inverse permutation
+  if(!internal::is_same<OrderingType,NaturalOrdering<Index> >::value)
+  {
+    {
+      CholMatrixType C;
+      C = a.template selfadjointView<UpLo>();
+      
+      OrderingType ordering;
+      ordering(C,m_Pinv);
+    }
+
+    if(m_Pinv.size()>0) m_P = m_Pinv.inverse();
+    else                m_P.resize(0);
+    
+    ap.resize(size,size);
+    ap.template selfadjointView<Upper>() = a.template selfadjointView<UpLo>().twistedBy(m_P);
+  }
+  else
+  {
+    m_Pinv.resize(0);
+    m_P.resize(0);
+    if(int(UpLo)==int(Lower) || MatrixType::IsRowMajor)
+    {
+      // we have to transpose the lower part to to the upper one
+      ap.resize(size,size);
+      ap.template selfadjointView<Upper>() = a.template selfadjointView<UpLo>();
+    }
+    else
+      internal::simplicial_cholesky_grab_input<CholMatrixType,MatrixType>::run(a, pmat, ap);
+  }  
+}
 
 } // end namespace Eigen
 
 #endif // EIGEN_SIMPLICIAL_CHOLESKY_H

Index: 3rd_party/eigen/Eigen/src/SparseCholesky/SimplicialCholesky_impl.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCholesky/SimplicialCholesky_impl.h
+++ 3rd_party/eigen/Eigen/src/SparseCholesky/SimplicialCholesky_impl.h
@@ -48,26 +48,26 @@
 namespace Eigen {
 
 template<typename Derived>
 void SimplicialCholeskyBase<Derived>::analyzePattern_preordered(const CholMatrixType& ap, bool doLDLT)
 {
-  const Index size = ap.rows();
+  const StorageIndex size = StorageIndex(ap.rows());
   m_matrix.resize(size, size);
   m_parent.resize(size);
   m_nonZerosPerCol.resize(size);
 
-  ei_declare_aligned_stack_constructed_variable(Index, tags, size, 0);
+  ei_declare_aligned_stack_constructed_variable(StorageIndex, tags, size, 0);
 
-  for(Index k = 0; k < size; ++k)
+  for(StorageIndex k = 0; k < size; ++k)
   {
     /* L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) */
     m_parent[k] = -1;             /* parent of k is not yet known */
     tags[k] = k;                  /* mark node k as visited */
     m_nonZerosPerCol[k] = 0;      /* count of nonzeros in column k of L */
     for(typename CholMatrixType::InnerIterator it(ap,k); it; ++it)
     {
-      Index i = it.index();
+      StorageIndex i = it.index();
       if(i < k)
       {
         /* follow path from i to root of etree, stop at flagged node */
         for(; tags[i] != k; i = m_parent[i])
         {
@@ -80,13 +80,13 @@
       }
     }
   }
 
   /* construct Lp index array from m_nonZerosPerCol column counts */
-  Index* Lp = m_matrix.outerIndexPtr();
+  StorageIndex* Lp = m_matrix.outerIndexPtr();
   Lp[0] = 0;
-  for(Index k = 0; k < size; ++k)
+  for(StorageIndex k = 0; k < size; ++k)
     Lp[k+1] = Lp[k] + m_nonZerosPerCol[k] + (doLDLT ? 0 : 1);
 
   m_matrix.resizeNonZeros(Lp[size]);
 
   m_isInitialized     = true;
@@ -102,35 +102,35 @@
 {
   using std::sqrt;
 
   eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
   eigen_assert(ap.rows()==ap.cols());
-  const Index size = ap.rows();
-  eigen_assert(m_parent.size()==size);
-  eigen_assert(m_nonZerosPerCol.size()==size);
+  eigen_assert(m_parent.size()==ap.rows());
+  eigen_assert(m_nonZerosPerCol.size()==ap.rows());
 
-  const Index* Lp = m_matrix.outerIndexPtr();
-  Index* Li = m_matrix.innerIndexPtr();
+  const StorageIndex size = StorageIndex(ap.rows());
+  const StorageIndex* Lp = m_matrix.outerIndexPtr();
+  StorageIndex* Li = m_matrix.innerIndexPtr();
   Scalar* Lx = m_matrix.valuePtr();
 
   ei_declare_aligned_stack_constructed_variable(Scalar, y, size, 0);
-  ei_declare_aligned_stack_constructed_variable(Index,  pattern, size, 0);
-  ei_declare_aligned_stack_constructed_variable(Index,  tags, size, 0);
+  ei_declare_aligned_stack_constructed_variable(StorageIndex,  pattern, size, 0);
+  ei_declare_aligned_stack_constructed_variable(StorageIndex,  tags, size, 0);
 
   bool ok = true;
   m_diag.resize(DoLDLT ? size : 0);
 
-  for(Index k = 0; k < size; ++k)
+  for(StorageIndex k = 0; k < size; ++k)
   {
     // compute nonzero pattern of kth row of L, in topological order
     y[k] = 0.0;                     // Y(0:k) is now all zero
-    Index top = size;               // stack for pattern is empty
+    StorageIndex top = size;               // stack for pattern is empty
     tags[k] = k;                    // mark node k as visited
     m_nonZerosPerCol[k] = 0;        // count of nonzeros in column k of L
-    for(typename MatrixType::InnerIterator it(ap,k); it; ++it)
+    for(typename CholMatrixType::InnerIterator it(ap,k); it; ++it)
     {
-      Index i = it.index();
+      StorageIndex i = it.index();
       if(i <= k)
       {
         y[i] += numext::conj(it.value());            /* scatter A(i,k) into Y (sum duplicates) */
         Index len;
         for(len = 0; tags[i] != k; i = m_parent[i])

Index: 3rd_party/eigen/Eigen/src/SparseCore/AmbiVector.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/AmbiVector.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/AmbiVector.h
@@ -17,19 +17,19 @@
 /** \internal
   * Hybrid sparse/dense vector class designed for intensive read-write operations.
   *
   * See BasicSparseLLT and SparseProduct for usage examples.
   */
-template<typename _Scalar, typename _Index>
+template<typename _Scalar, typename _StorageIndex>
 class AmbiVector
 {
   public:
     typedef _Scalar Scalar;
-    typedef _Index Index;
+    typedef _StorageIndex StorageIndex;
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
-    AmbiVector(Index size)
+    explicit AmbiVector(Index size)
       : m_buffer(0), m_zero(0), m_size(0), m_allocatedSize(0), m_allocatedElements(0), m_mode(-1)
     {
       resize(size);
     }
 
@@ -37,11 +37,11 @@
     void init(int mode);
 
     Index nonZeros() const;
 
     /** Specifies a sub-vector to work on */
-    void setBounds(Index start, Index end) { m_start = start; m_end = end; }
+    void setBounds(Index start, Index end) { m_start = convert_index(start); m_end = convert_index(end); }
 
     void setZero();
 
     void restart();
     Scalar& coeffRef(Index i);
@@ -53,42 +53,46 @@
 
     void resize(Index size)
     {
       if (m_allocatedSize < size)
         reallocate(size);
-      m_size = size;
+      m_size = convert_index(size);
     }
 
-    Index size() const { return m_size; }
+    StorageIndex size() const { return m_size; }
 
   protected:
+    StorageIndex convert_index(Index idx)
+    {
+      return internal::convert_index<StorageIndex>(idx);
+    }
 
     void reallocate(Index size)
     {
       // if the size of the matrix is not too large, let's allocate a bit more than needed such
       // that we can handle dense vector even in sparse mode.
       delete[] m_buffer;
       if (size<1000)
       {
         Index allocSize = (size * sizeof(ListEl) + sizeof(Scalar) - 1)/sizeof(Scalar);
-        m_allocatedElements = (allocSize*sizeof(Scalar))/sizeof(ListEl);
+        m_allocatedElements = convert_index((allocSize*sizeof(Scalar))/sizeof(ListEl));
         m_buffer = new Scalar[allocSize];
       }
       else
       {
-        m_allocatedElements = (size*sizeof(Scalar))/sizeof(ListEl);
+        m_allocatedElements = convert_index((size*sizeof(Scalar))/sizeof(ListEl));
         m_buffer = new Scalar[size];
       }
-      m_size = size;
+      m_size = convert_index(size);
       m_start = 0;
       m_end = m_size;
     }
 
     void reallocateSparse()
     {
       Index copyElements = m_allocatedElements;
-      m_allocatedElements = (std::min)(Index(m_allocatedElements*1.5),m_size);
+      m_allocatedElements = (std::min)(StorageIndex(m_allocatedElements*1.5),m_size);
       Index allocSize = m_allocatedElements * sizeof(ListEl);
       allocSize = (allocSize + sizeof(Scalar) - 1)/sizeof(Scalar);
       Scalar* newBuffer = new Scalar[allocSize];
       memcpy(newBuffer,  m_buffer,  copyElements * sizeof(ListEl));
       delete[] m_buffer;
@@ -97,52 +101,52 @@
 
   protected:
     // element type of the linked list
     struct ListEl
     {
-      Index next;
-      Index index;
+      StorageIndex next;
+      StorageIndex index;
       Scalar value;
     };
 
     // used to store data in both mode
     Scalar* m_buffer;
     Scalar m_zero;
-    Index m_size;
-    Index m_start;
-    Index m_end;
-    Index m_allocatedSize;
-    Index m_allocatedElements;
-    Index m_mode;
+    StorageIndex m_size;
+    StorageIndex m_start;
+    StorageIndex m_end;
+    StorageIndex m_allocatedSize;
+    StorageIndex m_allocatedElements;
+    StorageIndex m_mode;
 
     // linked list mode
-    Index m_llStart;
-    Index m_llCurrent;
-    Index m_llSize;
+    StorageIndex m_llStart;
+    StorageIndex m_llCurrent;
+    StorageIndex m_llSize;
 };
 
 /** \returns the number of non zeros in the current sub vector */
-template<typename _Scalar,typename _Index>
-_Index AmbiVector<_Scalar,_Index>::nonZeros() const
+template<typename _Scalar,typename _StorageIndex>
+Index AmbiVector<_Scalar,_StorageIndex>::nonZeros() const
 {
   if (m_mode==IsSparse)
     return m_llSize;
   else
     return m_end - m_start;
 }
 
-template<typename _Scalar,typename _Index>
-void AmbiVector<_Scalar,_Index>::init(double estimatedDensity)
+template<typename _Scalar,typename _StorageIndex>
+void AmbiVector<_Scalar,_StorageIndex>::init(double estimatedDensity)
 {
   if (estimatedDensity>0.1)
     init(IsDense);
   else
     init(IsSparse);
 }
 
-template<typename _Scalar,typename _Index>
-void AmbiVector<_Scalar,_Index>::init(int mode)
+template<typename _Scalar,typename _StorageIndex>
+void AmbiVector<_Scalar,_StorageIndex>::init(int mode)
 {
   m_mode = mode;
   if (m_mode==IsSparse)
   {
     m_llSize = 0;
@@ -153,19 +157,19 @@
 /** Must be called whenever we might perform a write access
   * with an index smaller than the previous one.
   *
   * Don't worry, this function is extremely cheap.
   */
-template<typename _Scalar,typename _Index>
-void AmbiVector<_Scalar,_Index>::restart()
+template<typename _Scalar,typename _StorageIndex>
+void AmbiVector<_Scalar,_StorageIndex>::restart()
 {
   m_llCurrent = m_llStart;
 }
 
 /** Set all coefficients of current subvector to zero */
-template<typename _Scalar,typename _Index>
-void AmbiVector<_Scalar,_Index>::setZero()
+template<typename _Scalar,typename _StorageIndex>
+void AmbiVector<_Scalar,_StorageIndex>::setZero()
 {
   if (m_mode==IsDense)
   {
     for (Index i=m_start; i<m_end; ++i)
       m_buffer[i] = Scalar(0);
@@ -176,12 +180,12 @@
     m_llSize = 0;
     m_llStart = -1;
   }
 }
 
-template<typename _Scalar,typename _Index>
-_Scalar& AmbiVector<_Scalar,_Index>::coeffRef(_Index i)
+template<typename _Scalar,typename _StorageIndex>
+_Scalar& AmbiVector<_Scalar,_StorageIndex>::coeffRef(Index i)
 {
   if (m_mode==IsDense)
     return m_buffer[i];
   else
   {
@@ -193,29 +197,29 @@
       // this is the first element
       m_llStart = 0;
       m_llCurrent = 0;
       ++m_llSize;
       llElements[0].value = Scalar(0);
-      llElements[0].index = i;
+      llElements[0].index = convert_index(i);
       llElements[0].next = -1;
       return llElements[0].value;
     }
     else if (i<llElements[m_llStart].index)
     {
       // this is going to be the new first element of the list
       ListEl& el = llElements[m_llSize];
       el.value = Scalar(0);
-      el.index = i;
+      el.index = convert_index(i);
       el.next = m_llStart;
       m_llStart = m_llSize;
       ++m_llSize;
       m_llCurrent = m_llStart;
       return el.value;
     }
     else
     {
-      Index nextel = llElements[m_llCurrent].next;
+      StorageIndex nextel = llElements[m_llCurrent].next;
       eigen_assert(i>=llElements[m_llCurrent].index && "you must call restart() before inserting an element with lower or equal index");
       while (nextel >= 0 && llElements[nextel].index<=i)
       {
         m_llCurrent = nextel;
         nextel = llElements[nextel].next;
@@ -235,22 +239,22 @@
         }
         eigen_internal_assert(m_llSize<m_allocatedElements && "internal error: overflow in sparse mode");
         // let's insert a new coefficient
         ListEl& el = llElements[m_llSize];
         el.value = Scalar(0);
-        el.index = i;
+        el.index = convert_index(i);
         el.next = llElements[m_llCurrent].next;
         llElements[m_llCurrent].next = m_llSize;
         ++m_llSize;
         return el.value;
       }
     }
   }
 }
 
-template<typename _Scalar,typename _Index>
-_Scalar& AmbiVector<_Scalar,_Index>::coeff(_Index i)
+template<typename _Scalar,typename _StorageIndex>
+_Scalar& AmbiVector<_Scalar,_StorageIndex>::coeff(Index i)
 {
   if (m_mode==IsDense)
     return m_buffer[i];
   else
   {
@@ -273,12 +277,12 @@
     }
   }
 }
 
 /** Iterator over the nonzero coefficients */
-template<typename _Scalar,typename _Index>
-class AmbiVector<_Scalar,_Index>::Iterator
+template<typename _Scalar,typename _StorageIndex>
+class AmbiVector<_Scalar,_StorageIndex>::Iterator
 {
   public:
     typedef _Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
@@ -286,11 +290,11 @@
       * \param vec the vector on which we iterate
       * \param epsilon the minimal value used to prune zero coefficients.
       * In practice, all coefficients having a magnitude smaller than \a epsilon
       * are skipped.
       */
-    Iterator(const AmbiVector& vec, const RealScalar& epsilon = 0)
+    explicit Iterator(const AmbiVector& vec, const RealScalar& epsilon = 0)
       : m_vector(vec)
     {
       using std::abs;
       m_epsilon = epsilon;
       m_isDense = m_vector.m_mode==IsDense;
@@ -318,11 +322,11 @@
           m_cachedValue = llElements[m_currentEl].value;
         }
       }
     }
 
-    Index index() const { return m_cachedIndex; }
+    StorageIndex index() const { return m_cachedIndex; }
     Scalar value() const { return m_cachedValue; }
 
     operator bool() const { return m_cachedIndex>=0; }
 
     Iterator& operator++()
@@ -330,11 +334,11 @@
       using std::abs;
       if (m_isDense)
       {
         do {
           ++m_cachedIndex;
-        } while (m_cachedIndex<m_vector.m_end && abs(m_vector.m_buffer[m_cachedIndex])<m_epsilon);
+        } while (m_cachedIndex<m_vector.m_end && abs(m_vector.m_buffer[m_cachedIndex])<=m_epsilon);
         if (m_cachedIndex<m_vector.m_end)
           m_cachedValue = m_vector.m_buffer[m_cachedIndex];
         else
           m_cachedIndex=-1;
       }
@@ -341,11 +345,11 @@
       else
       {
         ListEl* EIGEN_RESTRICT llElements = reinterpret_cast<ListEl*>(m_vector.m_buffer);
         do {
           m_currentEl = llElements[m_currentEl].next;
-        } while (m_currentEl>=0 && abs(llElements[m_currentEl].value)<m_epsilon);
+        } while (m_currentEl>=0 && abs(llElements[m_currentEl].value)<=m_epsilon);
         if (m_currentEl<0)
         {
           m_cachedIndex = -1;
         }
         else
@@ -357,17 +361,17 @@
       return *this;
     }
 
   protected:
     const AmbiVector& m_vector; // the target vector
-    Index m_currentEl;            // the current element in sparse/linked-list mode
+    StorageIndex m_currentEl;   // the current element in sparse/linked-list mode
     RealScalar m_epsilon;       // epsilon used to prune zero coefficients
-    Index m_cachedIndex;          // current coordinate
+    StorageIndex m_cachedIndex; // current coordinate
     Scalar m_cachedValue;       // current value
     bool m_isDense;             // mode of the vector
 };
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_AMBIVECTOR_H

DELETED 3rd_party/eigen/Eigen/src/SparseCore/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/SparseCore/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/SparseCore/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SparseCore_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_SparseCore_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SparseCore COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/SparseCore/CompressedStorage.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/CompressedStorage.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/CompressedStorage.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -16,17 +16,17 @@
 
 /** \internal
   * Stores a sparse set of values as a list of values and a list of indices.
   *
   */
-template<typename _Scalar,typename _Index>
+template<typename _Scalar,typename _StorageIndex>
 class CompressedStorage
 {
   public:
 
     typedef _Scalar Scalar;
-    typedef _Index Index;
+    typedef _StorageIndex StorageIndex;
 
   protected:
 
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
@@ -34,11 +34,11 @@
 
     CompressedStorage()
       : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
     {}
 
-    CompressedStorage(size_t size)
+    explicit CompressedStorage(Index size)
       : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
     {
       resize(size);
     }
 
@@ -49,12 +49,15 @@
     }
 
     CompressedStorage& operator=(const CompressedStorage& other)
     {
       resize(other.size());
-      internal::smart_copy(other.m_values,  other.m_values  + m_size, m_values);
-      internal::smart_copy(other.m_indices, other.m_indices + m_size, m_indices);
+      if(other.size()>0)
+      {
+        internal::smart_copy(other.m_values,  other.m_values  + m_size, m_values);
+        internal::smart_copy(other.m_indices, other.m_indices + m_size, m_indices);
+      }
       return *this;
     }
 
     void swap(CompressedStorage& other)
     {
@@ -68,13 +71,13 @@
     {
       delete[] m_values;
       delete[] m_indices;
     }
 
-    void reserve(size_t size)
+    void reserve(Index size)
     {
-      size_t newAllocatedSize = m_size + size;
+      Index newAllocatedSize = m_size + size;
       if (newAllocatedSize > m_allocatedSize)
         reallocate(newAllocatedSize);
     }
 
     void squeeze()
@@ -81,62 +84,63 @@
     {
       if (m_allocatedSize>m_size)
         reallocate(m_size);
     }
 
-    void resize(size_t size, double reserveSizeFactor = 0)
+    void resize(Index size, double reserveSizeFactor = 0)
     {
       if (m_allocatedSize<size)
-        reallocate(size + size_t(reserveSizeFactor*double(size)));
+      {
+        Index realloc_size = (std::min<Index>)(NumTraits<StorageIndex>::highest(),  size + Index(reserveSizeFactor*double(size)));
+        if(realloc_size<size)
+          internal::throw_std_bad_alloc();
+        reallocate(realloc_size);
+      }
       m_size = size;
     }
 
     void append(const Scalar& v, Index i)
     {
-      Index id = static_cast<Index>(m_size);
+      Index id = m_size;
       resize(m_size+1, 1);
       m_values[id] = v;
-      m_indices[id] = i;
+      m_indices[id] = internal::convert_index<StorageIndex>(i);
     }
 
-    inline size_t size() const { return m_size; }
-    inline size_t allocatedSize() const { return m_allocatedSize; }
+    inline Index size() const { return m_size; }
+    inline Index allocatedSize() const { return m_allocatedSize; }
     inline void clear() { m_size = 0; }
 
-    inline Scalar& value(size_t i) { return m_values[i]; }
-    inline const Scalar& value(size_t i) const { return m_values[i]; }
-
-    inline Index& index(size_t i) { return m_indices[i]; }
-    inline const Index& index(size_t i) const { return m_indices[i]; }
-
-    static CompressedStorage Map(Index* indices, Scalar* values, size_t size)
-    {
-      CompressedStorage res;
-      res.m_indices = indices;
-      res.m_values = values;
-      res.m_allocatedSize = res.m_size = size;
-      return res;
-    }
+    const Scalar* valuePtr() const { return m_values; }
+    Scalar* valuePtr() { return m_values; }
+    const StorageIndex* indexPtr() const { return m_indices; }
+    StorageIndex* indexPtr() { return m_indices; }
+
+    inline Scalar& value(Index i) { eigen_internal_assert(m_values!=0); return m_values[i]; }
+    inline const Scalar& value(Index i) const { eigen_internal_assert(m_values!=0); return m_values[i]; }
+
+    inline StorageIndex& index(Index i) { eigen_internal_assert(m_indices!=0); return m_indices[i]; }
+    inline const StorageIndex& index(Index i) const { eigen_internal_assert(m_indices!=0); return m_indices[i]; }
 
     /** \returns the largest \c k such that for all \c j in [0,k) index[\c j]\<\a key */
     inline Index searchLowerIndex(Index key) const
     {
       return searchLowerIndex(0, m_size, key);
     }
 
     /** \returns the largest \c k in [start,end) such that for all \c j in [start,k) index[\c j]\<\a key */
-    inline Index searchLowerIndex(size_t start, size_t end, Index key) const
+    inline Index searchLowerIndex(Index start, Index end, Index key) const
     {
       while(end>start)
       {
-        size_t mid = (end+start)>>1;
+        Index mid = (end+start)>>1;
         if (m_indices[mid]<key)
           start = mid+1;
         else
           end = mid;
       }
-      return static_cast<Index>(start);
+      return start;
     }
 
     /** \returns the stored value at index \a key
       * If the value does not exist, then the value \a defaultValue is returned without any insertion. */
     inline Scalar at(Index key, const Scalar& defaultValue = Scalar(0)) const
@@ -145,52 +149,71 @@
         return defaultValue;
       else if (key==m_indices[m_size-1])
         return m_values[m_size-1];
       // ^^  optimization: let's first check if it is the last coefficient
       // (very common in high level algorithms)
-      const size_t id = searchLowerIndex(0,m_size-1,key);
+      const Index id = searchLowerIndex(0,m_size-1,key);
       return ((id<m_size) && (m_indices[id]==key)) ? m_values[id] : defaultValue;
     }
 
     /** Like at(), but the search is performed in the range [start,end) */
-    inline Scalar atInRange(size_t start, size_t end, Index key, const Scalar& defaultValue = Scalar(0)) const
+    inline Scalar atInRange(Index start, Index end, Index key, const Scalar &defaultValue = Scalar(0)) const
     {
       if (start>=end)
-        return Scalar(0);
+        return defaultValue;
       else if (end>start && key==m_indices[end-1])
         return m_values[end-1];
       // ^^  optimization: let's first check if it is the last coefficient
       // (very common in high level algorithms)
-      const size_t id = searchLowerIndex(start,end-1,key);
+      const Index id = searchLowerIndex(start,end-1,key);
       return ((id<end) && (m_indices[id]==key)) ? m_values[id] : defaultValue;
     }
 
     /** \returns a reference to the value at index \a key
       * If the value does not exist, then the value \a defaultValue is inserted
       * such that the keys are sorted. */
     inline Scalar& atWithInsertion(Index key, const Scalar& defaultValue = Scalar(0))
     {
-      size_t id = searchLowerIndex(0,m_size,key);
+      Index id = searchLowerIndex(0,m_size,key);
       if (id>=m_size || m_indices[id]!=key)
       {
-        resize(m_size+1,1);
-        for (size_t j=m_size-1; j>id; --j)
+        if (m_allocatedSize<m_size+1)
+        {
+          m_allocatedSize = 2*(m_size+1);
+          internal::scoped_array<Scalar> newValues(m_allocatedSize);
+          internal::scoped_array<StorageIndex> newIndices(m_allocatedSize);
+
+          // copy first chunk
+          internal::smart_copy(m_values,  m_values +id, newValues.ptr());
+          internal::smart_copy(m_indices, m_indices+id, newIndices.ptr());
+
+          // copy the rest
+          if(m_size>id)
+          {
+            internal::smart_copy(m_values +id,  m_values +m_size, newValues.ptr() +id+1);
+            internal::smart_copy(m_indices+id,  m_indices+m_size, newIndices.ptr()+id+1);
+          }
+          std::swap(m_values,newValues.ptr());
+          std::swap(m_indices,newIndices.ptr());
+        }
+        else if(m_size>id)
         {
-          m_indices[j] = m_indices[j-1];
-          m_values[j] = m_values[j-1];
+          internal::smart_memmove(m_values +id, m_values +m_size, m_values +id+1);
+          internal::smart_memmove(m_indices+id, m_indices+m_size, m_indices+id+1);
         }
-        m_indices[id] = key;
+        m_size++;
+        m_indices[id] = internal::convert_index<StorageIndex>(key);
         m_values[id] = defaultValue;
       }
       return m_values[id];
     }
 
     void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
     {
-      size_t k = 0;
-      size_t n = size();
-      for (size_t i=0; i<n; ++i)
+      Index k = 0;
+      Index n = size();
+      for (Index i=0; i<n; ++i)
       {
         if (!internal::isMuchSmallerThan(value(i), reference, epsilon))
         {
           value(k) = value(i);
           index(k) = index(i);
@@ -200,34 +223,36 @@
       resize(k,0);
     }
 
   protected:
 
-    inline void reallocate(size_t size)
-    {
-      Scalar* newValues  = new Scalar[size];
-      Index* newIndices = new Index[size];
-      size_t copySize = (std::min)(size, m_size);
-      // copy
-      internal::smart_copy(m_values, m_values+copySize, newValues);
-      internal::smart_copy(m_indices, m_indices+copySize, newIndices);
-      // delete old stuff
-      delete[] m_values;
-      delete[] m_indices;
-      m_values = newValues;
-      m_indices = newIndices;
+    inline void reallocate(Index size)
+    {
+      #ifdef EIGEN_SPARSE_COMPRESSED_STORAGE_REALLOCATE_PLUGIN
+        EIGEN_SPARSE_COMPRESSED_STORAGE_REALLOCATE_PLUGIN
+      #endif
+      eigen_internal_assert(size!=m_allocatedSize);
+      internal::scoped_array<Scalar> newValues(size);
+      internal::scoped_array<StorageIndex> newIndices(size);
+      Index copySize = (std::min)(size, m_size);
+      if (copySize>0) {
+        internal::smart_copy(m_values, m_values+copySize, newValues.ptr());
+        internal::smart_copy(m_indices, m_indices+copySize, newIndices.ptr());
+      }
+      std::swap(m_values,newValues.ptr());
+      std::swap(m_indices,newIndices.ptr());
       m_allocatedSize = size;
     }
 
   protected:
     Scalar* m_values;
-    Index* m_indices;
-    size_t m_size;
-    size_t m_allocatedSize;
+    StorageIndex* m_indices;
+    Index m_size;
+    Index m_allocatedSize;
 
 };
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_COMPRESSED_STORAGE_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -13,45 +13,49 @@
 namespace Eigen { 
 
 namespace internal {
 
 template<typename Lhs, typename Rhs, typename ResultType>
-static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, bool sortedInsertion = false)
 {
   typedef typename remove_all<Lhs>::type::Scalar Scalar;
-  typedef typename remove_all<Lhs>::type::Index Index;
 
   // make sure to call innerSize/outerSize since we fake the storage order.
   Index rows = lhs.innerSize();
   Index cols = rhs.outerSize();
   eigen_assert(lhs.outerSize() == rhs.innerSize());
-
-  std::vector<bool> mask(rows,false);
-  Matrix<Scalar,Dynamic,1> values(rows);
-  Matrix<Index,Dynamic,1>  indices(rows);
+  
+  ei_declare_aligned_stack_constructed_variable(bool,   mask,     rows, 0);
+  ei_declare_aligned_stack_constructed_variable(Scalar, values,   rows, 0);
+  ei_declare_aligned_stack_constructed_variable(Index,  indices,  rows, 0);
+  
+  std::memset(mask,0,sizeof(bool)*rows);
 
+  evaluator<Lhs> lhsEval(lhs);
+  evaluator<Rhs> rhsEval(rhs);
+  
   // estimate the number of non zero entries
   // given a rhs column containing Y non zeros, we assume that the respective Y columns
   // of the lhs differs in average of one non zeros, thus the number of non zeros for
   // the product of a rhs column with the lhs is X+Y where X is the average number of non zero
   // per column of the lhs.
   // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs)
-  Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros();
+  Index estimated_nnz_prod = lhsEval.nonZerosEstimate() + rhsEval.nonZerosEstimate();
 
   res.setZero();
   res.reserve(Index(estimated_nnz_prod));
   // we compute each column of the result, one after the other
   for (Index j=0; j<cols; ++j)
   {
 
     res.startVec(j);
     Index nnz = 0;
-    for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
+    for (typename evaluator<Rhs>::InnerIterator rhsIt(rhsEval, j); rhsIt; ++rhsIt)
     {
       Scalar y = rhsIt.value();
       Index k = rhsIt.index();
-      for (typename Lhs::InnerIterator lhsIt(lhs, k); lhsIt; ++lhsIt)
+      for (typename evaluator<Lhs>::InnerIterator lhsIt(lhsEval, k); lhsIt; ++lhsIt)
       {
         Index i = lhsIt.index();
         Scalar x = lhsIt.value();
         if(!mask[i])
         {
@@ -62,57 +66,55 @@
         }
         else
           values[i] += x * y;
       }
     }
-
-    // unordered insertion
-    for(Index k=0; k<nnz; ++k)
-    {
-      Index i = indices[k];
-      res.insertBackByOuterInnerUnordered(j,i) = values[i];
-      mask[i] = false;
-    }
-
-#if 0
-    // alternative ordered insertion code:
-
-    Index t200 = rows/(log2(200)*1.39);
-    Index t = (rows*100)/139;
-
-    // FIXME reserve nnz non zeros
-    // FIXME implement fast sort algorithms for very small nnz
-    // if the result is sparse enough => use a quick sort
-    // otherwise => loop through the entire vector
-    // In order to avoid to perform an expensive log2 when the
-    // result is clearly very sparse we use a linear bound up to 200.
-    //if((nnz<200 && nnz<t200) || nnz * log2(nnz) < t)
-    //res.startVec(j);
-    if(true)
-    {
-      if(nnz>1) std::sort(indices.data(),indices.data()+nnz);
-      for(Index k=0; k<nnz; ++k)
-      {
-        Index i = indices[k];
-        res.insertBackByOuterInner(j,i) = values[i];
+    if(!sortedInsertion)
+    {
+      // unordered insertion
+      for(Index k=0; k<nnz; ++k)
+      {
+        Index i = indices[k];
+        res.insertBackByOuterInnerUnordered(j,i) = values[i];
         mask[i] = false;
       }
     }
     else
     {
-      // dense path
-      for(Index i=0; i<rows; ++i)
+      // alternative ordered insertion code:
+      const Index t200 = rows/11; // 11 == (log2(200)*1.39)
+      const Index t = (rows*100)/139;
+
+      // FIXME reserve nnz non zeros
+      // FIXME implement faster sorting algorithms for very small nnz
+      // if the result is sparse enough => use a quick sort
+      // otherwise => loop through the entire vector
+      // In order to avoid to perform an expensive log2 when the
+      // result is clearly very sparse we use a linear bound up to 200.
+      if((nnz<200 && nnz<t200) || nnz * numext::log2(int(nnz)) < t)
       {
-        if(mask[i])
+        if(nnz>1) std::sort(indices,indices+nnz);
+        for(Index k=0; k<nnz; ++k)
         {
-          mask[i] = false;
+          Index i = indices[k];
           res.insertBackByOuterInner(j,i) = values[i];
+          mask[i] = false;
+        }
+      }
+      else
+      {
+        // dense path
+        for(Index i=0; i<rows; ++i)
+        {
+          if(mask[i])
+          {
+            mask[i] = false;
+            res.insertBackByOuterInner(j,i) = values[i];
+          }
         }
       }
     }
-#endif
-
   }
   res.finalize();
 }
 
 
@@ -132,26 +134,41 @@
   typedef typename remove_all<Lhs>::type LhsCleaned;
   typedef typename LhsCleaned::Scalar Scalar;
 
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
   {
-    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
-    ColMajorMatrix resCol(lhs.rows(),rhs.cols());
-    internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol);
-    // sort the non zeros:
-    RowMajorMatrix resRow(resCol);
-    res = resRow;
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrixAux;
+    typedef typename sparse_eval<ColMajorMatrixAux,ResultType::RowsAtCompileTime,ResultType::ColsAtCompileTime,ColMajorMatrixAux::Flags>::type ColMajorMatrix;
+    
+    // If the result is tall and thin (in the extreme case a column vector)
+    // then it is faster to sort the coefficients inplace instead of transposing twice.
+    // FIXME, the following heuristic is probably not very good.
+    if(lhs.rows()>rhs.cols())
+    {
+      ColMajorMatrix resCol(lhs.rows(),rhs.cols());
+      // perform sorted insertion
+      internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol, true);
+      res = resCol.markAsRValue();
+    }
+    else
+    {
+      ColMajorMatrixAux resCol(lhs.rows(),rhs.cols());
+      // ressort to transpose to sort the entries
+      internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrixAux>(lhs, rhs, resCol, false);
+      RowMajorMatrix resRow(resCol);
+      res = resRow.markAsRValue();
+    }
   }
 };
 
 template<typename Lhs, typename Rhs, typename ResultType>
 struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor,ColMajor>
 {
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
   {
-     typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
+     typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorMatrix;
      RowMajorMatrix rhsRow = rhs;
      RowMajorMatrix resRow(lhs.rows(), rhs.cols());
      internal::conservative_sparse_sparse_product_impl<RowMajorMatrix,Lhs,RowMajorMatrix>(rhsRow, lhs, resRow);
      res = resRow;
   }
@@ -160,11 +177,11 @@
 template<typename Lhs, typename Rhs, typename ResultType>
 struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor,ColMajor>
 {
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
   {
-    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorMatrix;
     RowMajorMatrix lhsRow = lhs;
     RowMajorMatrix resRow(lhs.rows(), rhs.cols());
     internal::conservative_sparse_sparse_product_impl<Rhs,RowMajorMatrix,RowMajorMatrix>(rhs, lhsRow, resRow);
     res = resRow;
   }
@@ -173,11 +190,11 @@
 template<typename Lhs, typename Rhs, typename ResultType>
 struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor>
 {
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
   {
-    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorMatrix;
     RowMajorMatrix resRow(lhs.rows(), rhs.cols());
     internal::conservative_sparse_sparse_product_impl<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow);
     res = resRow;
   }
 };
@@ -188,11 +205,11 @@
 {
   typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
 
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
   {
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix;
     ColMajorMatrix resCol(lhs.rows(), rhs.cols());
     internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol);
     res = resCol;
   }
 };
@@ -200,11 +217,11 @@
 template<typename Lhs, typename Rhs, typename ResultType>
 struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor,RowMajor>
 {
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
   {
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix;
     ColMajorMatrix lhsCol = lhs;
     ColMajorMatrix resCol(lhs.rows(), rhs.cols());
     internal::conservative_sparse_sparse_product_impl<ColMajorMatrix,Rhs,ColMajorMatrix>(lhsCol, rhs, resCol);
     res = resCol;
   }
@@ -213,11 +230,11 @@
 template<typename Lhs, typename Rhs, typename ResultType>
 struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor,RowMajor>
 {
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
   {
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix;
     ColMajorMatrix rhsCol = rhs;
     ColMajorMatrix resCol(lhs.rows(), rhs.cols());
     internal::conservative_sparse_sparse_product_impl<Lhs,ColMajorMatrix,ColMajorMatrix>(lhs, rhsCol, resCol);
     res = resCol;
   }
@@ -226,20 +243,103 @@
 template<typename Lhs, typename Rhs, typename ResultType>
 struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,RowMajor>
 {
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
   {
-    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix;
     RowMajorMatrix resRow(lhs.rows(),rhs.cols());
     internal::conservative_sparse_sparse_product_impl<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow);
     // sort the non zeros:
     ColMajorMatrix resCol(resRow);
     res = resCol;
   }
 };
+
+} // end namespace internal
+
+
+namespace internal {
+
+template<typename Lhs, typename Rhs, typename ResultType>
+static void sparse_sparse_to_dense_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+{
+  typedef typename remove_all<Lhs>::type::Scalar Scalar;
+  Index cols = rhs.outerSize();
+  eigen_assert(lhs.outerSize() == rhs.innerSize());
+
+  evaluator<Lhs> lhsEval(lhs);
+  evaluator<Rhs> rhsEval(rhs);
+
+  for (Index j=0; j<cols; ++j)
+  {
+    for (typename evaluator<Rhs>::InnerIterator rhsIt(rhsEval, j); rhsIt; ++rhsIt)
+    {
+      Scalar y = rhsIt.value();
+      Index k = rhsIt.index();
+      for (typename evaluator<Lhs>::InnerIterator lhsIt(lhsEval, k); lhsIt; ++lhsIt)
+      {
+        Index i = lhsIt.index();
+        Scalar x = lhsIt.value();
+        res.coeffRef(i,j) += x * y;
+      }
+    }
+  }
+}
+
+
+} // end namespace internal
+
+namespace internal {
+
+template<typename Lhs, typename Rhs, typename ResultType,
+  int LhsStorageOrder = (traits<Lhs>::Flags&RowMajorBit) ? RowMajor : ColMajor,
+  int RhsStorageOrder = (traits<Rhs>::Flags&RowMajorBit) ? RowMajor : ColMajor>
+struct sparse_sparse_to_dense_product_selector;
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_to_dense_product_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    internal::sparse_sparse_to_dense_product_impl<Lhs,Rhs,ResultType>(lhs, rhs, res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_to_dense_product_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix;
+    ColMajorMatrix lhsCol(lhs);
+    internal::sparse_sparse_to_dense_product_impl<ColMajorMatrix,Rhs,ResultType>(lhsCol, rhs, res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_to_dense_product_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix;
+    ColMajorMatrix rhsCol(rhs);
+    internal::sparse_sparse_to_dense_product_impl<Lhs,ColMajorMatrix,ResultType>(lhs, rhsCol, res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_to_dense_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    Transpose<ResultType> trRes(res);
+    internal::sparse_sparse_to_dense_product_impl<Rhs,Lhs,Transpose<ResultType> >(rhs, lhs, trRes);
+  }
+};
+
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/MappedSparseMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/MappedSparseMatrix.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/MappedSparseMatrix.h
@@ -1,181 +1,67 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MAPPED_SPARSEMATRIX_H
 #define EIGEN_MAPPED_SPARSEMATRIX_H
 
-namespace Eigen { 
+namespace Eigen {
 
-/** \class MappedSparseMatrix
+/** \deprecated Use Map<SparseMatrix<> >
+  * \class MappedSparseMatrix
   *
   * \brief Sparse matrix
   *
   * \param _Scalar the scalar type, i.e. the type of the coefficients
   *
   * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
   *
   */
 namespace internal {
-template<typename _Scalar, int _Flags, typename _Index>
-struct traits<MappedSparseMatrix<_Scalar, _Flags, _Index> > : traits<SparseMatrix<_Scalar, _Flags, _Index> >
-{};
-}
-
-template<typename _Scalar, int _Flags, typename _Index>
-class MappedSparseMatrix
-  : public SparseMatrixBase<MappedSparseMatrix<_Scalar, _Flags, _Index> >
-{
-  public:
-    EIGEN_SPARSE_PUBLIC_INTERFACE(MappedSparseMatrix)
-    enum { IsRowMajor = Base::IsRowMajor };
-
-  protected:
-
-    Index   m_outerSize;
-    Index   m_innerSize;
-    Index   m_nnz;
-    Index*  m_outerIndex;
-    Index*  m_innerIndices;
-    Scalar* m_values;
-
-  public:
-
-    inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
-    inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
-    inline Index innerSize() const { return m_innerSize; }
-    inline Index outerSize() const { return m_outerSize; }
-    
-    bool isCompressed() const { return true; }
-
-    //----------------------------------------
-    // direct access interface
-    inline const Scalar* valuePtr() const { return m_values; }
-    inline Scalar* valuePtr() { return m_values; }
-
-    inline const Index* innerIndexPtr() const { return m_innerIndices; }
-    inline Index* innerIndexPtr() { return m_innerIndices; }
-
-    inline const Index* outerIndexPtr() const { return m_outerIndex; }
-    inline Index* outerIndexPtr() { return m_outerIndex; }
-    //----------------------------------------
-
-    inline Scalar coeff(Index row, Index col) const
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-
-      Index start = m_outerIndex[outer];
-      Index end = m_outerIndex[outer+1];
-      if (start==end)
-        return Scalar(0);
-      else if (end>0 && inner==m_innerIndices[end-1])
-        return m_values[end-1];
-      // ^^  optimization: let's first check if it is the last coefficient
-      // (very common in high level algorithms)
-
-      const Index* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end-1],inner);
-      const Index id = r-&m_innerIndices[0];
-      return ((*r==inner) && (id<end)) ? m_values[id] : Scalar(0);
-    }
-
-    inline Scalar& coeffRef(Index row, Index col)
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-
-      Index start = m_outerIndex[outer];
-      Index end = m_outerIndex[outer+1];
-      eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
-      eigen_assert(end>start && "coeffRef cannot be called on a zero coefficient");
-      Index* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end],inner);
-      const Index id = r-&m_innerIndices[0];
-      eigen_assert((*r==inner) && (id<end) && "coeffRef cannot be called on a zero coefficient");
-      return m_values[id];
-    }
-
-    class InnerIterator;
-    class ReverseInnerIterator;
-
-    /** \returns the number of non zero coefficients */
-    inline Index nonZeros() const  { return m_nnz; }
-
-    inline MappedSparseMatrix(Index rows, Index cols, Index nnz, Index* outerIndexPtr, Index* innerIndexPtr, Scalar* valuePtr)
-      : m_outerSize(IsRowMajor?rows:cols), m_innerSize(IsRowMajor?cols:rows), m_nnz(nnz), m_outerIndex(outerIndexPtr),
-        m_innerIndices(innerIndexPtr), m_values(valuePtr)
+template<typename _Scalar, int _Flags, typename _StorageIndex>
+struct traits<MappedSparseMatrix<_Scalar, _Flags, _StorageIndex> > : traits<SparseMatrix<_Scalar, _Flags, _StorageIndex> >
+{};
+} // end namespace internal
+
+template<typename _Scalar, int _Flags, typename _StorageIndex>
+class MappedSparseMatrix
+  : public Map<SparseMatrix<_Scalar, _Flags, _StorageIndex> >
+{
+    typedef Map<SparseMatrix<_Scalar, _Flags, _StorageIndex> > Base;
+
+  public:
+    
+    typedef typename Base::StorageIndex StorageIndex;
+    typedef typename Base::Scalar Scalar;
+
+    inline MappedSparseMatrix(Index rows, Index cols, Index nnz, StorageIndex* outerIndexPtr, StorageIndex* innerIndexPtr, Scalar* valuePtr, StorageIndex* innerNonZeroPtr = 0)
+      : Base(rows, cols, nnz, outerIndexPtr, innerIndexPtr, valuePtr, innerNonZeroPtr)
     {}
 
     /** Empty destructor */
     inline ~MappedSparseMatrix() {}
 };
 
-template<typename Scalar, int _Flags, typename _Index>
-class MappedSparseMatrix<Scalar,_Flags,_Index>::InnerIterator
-{
-  public:
-    InnerIterator(const MappedSparseMatrix& mat, Index outer)
-      : m_matrix(mat),
-        m_outer(outer),
-        m_id(mat.outerIndexPtr()[outer]),
-        m_start(m_id),
-        m_end(mat.outerIndexPtr()[outer+1])
-    {}
-
-    inline InnerIterator& operator++() { m_id++; return *this; }
-
-    inline Scalar value() const { return m_matrix.valuePtr()[m_id]; }
-    inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.valuePtr()[m_id]); }
-
-    inline Index index() const { return m_matrix.innerIndexPtr()[m_id]; }
-    inline Index row() const { return IsRowMajor ? m_outer : index(); }
-    inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-    inline operator bool() const { return (m_id < m_end) && (m_id>=m_start); }
-
-  protected:
-    const MappedSparseMatrix& m_matrix;
-    const Index m_outer;
-    Index m_id;
-    const Index m_start;
-    const Index m_end;
-};
-
-template<typename Scalar, int _Flags, typename _Index>
-class MappedSparseMatrix<Scalar,_Flags,_Index>::ReverseInnerIterator
-{
-  public:
-    ReverseInnerIterator(const MappedSparseMatrix& mat, Index outer)
-      : m_matrix(mat),
-        m_outer(outer),
-        m_id(mat.outerIndexPtr()[outer+1]),
-        m_start(mat.outerIndexPtr()[outer]),
-        m_end(m_id)
-    {}
-
-    inline ReverseInnerIterator& operator--() { m_id--; return *this; }
-
-    inline Scalar value() const { return m_matrix.valuePtr()[m_id-1]; }
-    inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.valuePtr()[m_id-1]); }
-
-    inline Index index() const { return m_matrix.innerIndexPtr()[m_id-1]; }
-    inline Index row() const { return IsRowMajor ? m_outer : index(); }
-    inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-    inline operator bool() const { return (m_id <= m_end) && (m_id>m_start); }
-
-  protected:
-    const MappedSparseMatrix& m_matrix;
-    const Index m_outer;
-    Index m_id;
-    const Index m_start;
-    const Index m_end;
-};
+namespace internal {
+
+template<typename _Scalar, int _Options, typename _StorageIndex>
+struct evaluator<MappedSparseMatrix<_Scalar,_Options,_StorageIndex> >
+  : evaluator<SparseCompressedBase<MappedSparseMatrix<_Scalar,_Options,_StorageIndex> > >
+{
+  typedef MappedSparseMatrix<_Scalar,_Options,_StorageIndex> XprType;
+  typedef evaluator<SparseCompressedBase<XprType> > Base;
+  
+  evaluator() : Base() {}
+  explicit evaluator(const XprType &mat) : Base(mat) {}
+};
+
+}
 
 } // end namespace Eigen
 
 #endif // EIGEN_MAPPED_SPARSEMATRIX_H

ADDED   3rd_party/eigen/Eigen/src/SparseCore/SparseAssign.h
Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseAssign.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseAssign.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseAssign.h
@@ -0,0 +1,216 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSEASSIGN_H
+#define EIGEN_SPARSEASSIGN_H
+
+namespace Eigen { 
+
+template<typename Derived>    
+template<typename OtherDerived>
+Derived& SparseMatrixBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
+{
+  internal::call_assignment_no_alias(derived(), other.derived());
+  return derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+Derived& SparseMatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
+{
+  // TODO use the evaluator mechanism
+  other.evalTo(derived());
+  return derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+inline Derived& SparseMatrixBase<Derived>::operator=(const SparseMatrixBase<OtherDerived>& other)
+{
+  // by default sparse evaluation do not alias, so we can safely bypass the generic call_assignment routine
+  internal::Assignment<Derived,OtherDerived,internal::assign_op<Scalar,typename OtherDerived::Scalar> >
+          ::run(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
+  return derived();
+}
+
+template<typename Derived>
+inline Derived& SparseMatrixBase<Derived>::operator=(const Derived& other)
+{
+  internal::call_assignment_no_alias(derived(), other.derived());
+  return derived();
+}
+
+namespace internal {
+
+template<>
+struct storage_kind_to_evaluator_kind<Sparse> {
+  typedef IteratorBased Kind;
+};
+
+template<>
+struct storage_kind_to_shape<Sparse> {
+  typedef SparseShape Shape;
+};
+
+struct Sparse2Sparse {};
+struct Sparse2Dense  {};
+
+template<> struct AssignmentKind<SparseShape, SparseShape>           { typedef Sparse2Sparse Kind; };
+template<> struct AssignmentKind<SparseShape, SparseTriangularShape> { typedef Sparse2Sparse Kind; };
+template<> struct AssignmentKind<DenseShape,  SparseShape>           { typedef Sparse2Dense  Kind; };
+template<> struct AssignmentKind<DenseShape,  SparseTriangularShape> { typedef Sparse2Dense  Kind; };
+
+
+template<typename DstXprType, typename SrcXprType>
+void assign_sparse_to_sparse(DstXprType &dst, const SrcXprType &src)
+{
+  typedef typename DstXprType::Scalar Scalar;
+  typedef internal::evaluator<DstXprType> DstEvaluatorType;
+  typedef internal::evaluator<SrcXprType> SrcEvaluatorType;
+
+  SrcEvaluatorType srcEvaluator(src);
+
+  const bool transpose = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit);
+  const Index outerEvaluationSize = (SrcEvaluatorType::Flags&RowMajorBit) ? src.rows() : src.cols();
+  if ((!transpose) && src.isRValue())
+  {
+    // eval without temporary
+    dst.resize(src.rows(), src.cols());
+    dst.setZero();
+    dst.reserve((std::max)(src.rows(),src.cols())*2);
+    for (Index j=0; j<outerEvaluationSize; ++j)
+    {
+      dst.startVec(j);
+      for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
+      {
+        Scalar v = it.value();
+        dst.insertBackByOuterInner(j,it.index()) = v;
+      }
+    }
+    dst.finalize();
+  }
+  else
+  {
+    // eval through a temporary
+    eigen_assert(( ((internal::traits<DstXprType>::SupportedAccessPatterns & OuterRandomAccessPattern)==OuterRandomAccessPattern) ||
+              (!((DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit)))) &&
+              "the transpose operation is supposed to be handled in SparseMatrix::operator=");
+
+    enum { Flip = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit) };
+
+    
+    DstXprType temp(src.rows(), src.cols());
+
+    temp.reserve((std::max)(src.rows(),src.cols())*2);
+    for (Index j=0; j<outerEvaluationSize; ++j)
+    {
+      temp.startVec(j);
+      for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
+      {
+        Scalar v = it.value();
+        temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
+      }
+    }
+    temp.finalize();
+
+    dst = temp.markAsRValue();
+  }
+}
+
+// Generic Sparse to Sparse assignment
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Sparse>
+{
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  {
+    assign_sparse_to_sparse(dst.derived(), src.derived());
+  }
+};
+
+// Generic Sparse to Dense assignment
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Dense>
+{
+  static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
+  {
+    if(internal::is_same<Functor,internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> >::value)
+      dst.setZero();
+    
+    internal::evaluator<SrcXprType> srcEval(src);
+    resize_if_allowed(dst, src, func);
+    internal::evaluator<DstXprType> dstEval(dst);
+    
+    const Index outerEvaluationSize = (internal::evaluator<SrcXprType>::Flags&RowMajorBit) ? src.rows() : src.cols();
+    for (Index j=0; j<outerEvaluationSize; ++j)
+      for (typename internal::evaluator<SrcXprType>::InnerIterator i(srcEval,j); i; ++i)
+        func.assignCoeff(dstEval.coeffRef(i.row(),i.col()), i.value());
+  }
+};
+
+// Specialization for "dst = dec.solve(rhs)"
+// NOTE we need to specialize it for Sparse2Sparse to avoid ambiguous specialization error
+template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
+struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar,Scalar>, Sparse2Sparse>
+{
+  typedef Solve<DecType,RhsType> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    src.dec()._solve_impl(src.rhs(), dst);
+  }
+};
+
+struct Diagonal2Sparse {};
+
+template<> struct AssignmentKind<SparseShape,DiagonalShape> { typedef Diagonal2Sparse Kind; };
+
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Sparse>
+{
+  typedef typename DstXprType::StorageIndex StorageIndex;
+  typedef typename DstXprType::Scalar Scalar;
+  typedef Array<StorageIndex,Dynamic,1> ArrayXI;
+  typedef Array<Scalar,Dynamic,1> ArrayXS;
+  template<int Options>
+  static void run(SparseMatrix<Scalar,Options,StorageIndex> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+
+    Index size = src.diagonal().size();
+    dst.makeCompressed();
+    dst.resizeNonZeros(size);
+    Map<ArrayXI>(dst.innerIndexPtr(), size).setLinSpaced(0,StorageIndex(size)-1);
+    Map<ArrayXI>(dst.outerIndexPtr(), size+1).setLinSpaced(0,StorageIndex(size));
+    Map<ArrayXS>(dst.valuePtr(), size) = src.diagonal();
+  }
+  
+  template<typename DstDerived>
+  static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  {
+    dst.diagonal() = src.diagonal();
+  }
+  
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  { dst.diagonal() += src.diagonal(); }
+  
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  { dst.diagonal() -= src.diagonal(); }
+};
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSEASSIGN_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseBlock.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseBlock.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseBlock.h
@@ -1,19 +1,20 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_BLOCK_H
 #define EIGEN_SPARSE_BLOCK_H
 
-namespace Eigen { 
+namespace Eigen {
 
+// Subset of columns or rows
 template<typename XprType, int BlockRows, int BlockCols>
 class BlockImpl<XprType,BlockRows,BlockCols,true,Sparse>
   : public SparseMatrixBase<Block<XprType,BlockRows,BlockCols,true> >
 {
     typedef typename internal::remove_all<typename XprType::Nested>::type _MatrixTypeNested;
@@ -20,179 +21,193 @@
     typedef Block<XprType, BlockRows, BlockCols, true> BlockType;
 public:
     enum { IsRowMajor = internal::traits<BlockType>::IsRowMajor };
 protected:
     enum { OuterSize = IsRowMajor ? BlockRows : BlockCols };
+    typedef SparseMatrixBase<BlockType> Base;
+    using Base::convert_index;
 public:
     EIGEN_SPARSE_PUBLIC_INTERFACE(BlockType)
-    
-    class InnerIterator: public XprType::InnerIterator
-    {
-        typedef typename BlockImpl::Index Index;
-      public:
-        inline InnerIterator(const BlockType& xpr, Index outer)
-          : XprType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
-        {}
-        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
-      protected:
-        Index m_outer;
-    };
-    class ReverseInnerIterator: public XprType::ReverseInnerIterator
-    {
-        typedef typename BlockImpl::Index Index;
-      public:
-        inline ReverseInnerIterator(const BlockType& xpr, Index outer)
-          : XprType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
-        {}
-        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
-      protected:
-        Index m_outer;
-    };
-
-    inline BlockImpl(const XprType& xpr, int i)
-      : m_matrix(xpr), m_outerStart(i), m_outerSize(OuterSize)
-    {}
-
-    inline BlockImpl(const XprType& xpr, int startRow, int startCol, int blockRows, int blockCols)
-      : m_matrix(xpr), m_outerStart(IsRowMajor ? startRow : startCol), m_outerSize(IsRowMajor ? blockRows : blockCols)
+
+    inline BlockImpl(XprType& xpr, Index i)
+      : m_matrix(xpr), m_outerStart(convert_index(i)), m_outerSize(OuterSize)
+    {}
+
+    inline BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
+      : m_matrix(xpr), m_outerStart(convert_index(IsRowMajor ? startRow : startCol)), m_outerSize(convert_index(IsRowMajor ? blockRows : blockCols))
     {}
 
     EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
     EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
 
+    Index nonZeros() const
+    {
+      typedef internal::evaluator<XprType> EvaluatorType;
+      EvaluatorType matEval(m_matrix);
+      Index nnz = 0;
+      Index end = m_outerStart + m_outerSize.value();
+      for(Index j=m_outerStart; j<end; ++j)
+        for(typename EvaluatorType::InnerIterator it(matEval, j); it; ++it)
+          ++nnz;
+      return nnz;
+    }
+
+    inline const Scalar coeff(Index row, Index col) const
+    {
+      return m_matrix.coeff(row + (IsRowMajor ? m_outerStart : 0), col + (IsRowMajor ? 0 :  m_outerStart));
+    }
+
+    inline const Scalar coeff(Index index) const
+    {
+      return m_matrix.coeff(IsRowMajor ? m_outerStart : index, IsRowMajor ? index :  m_outerStart);
+    }
+
+    inline const XprType& nestedExpression() const { return m_matrix; }
+    inline XprType& nestedExpression() { return m_matrix; }
+    Index startRow() const { return IsRowMajor ? m_outerStart : 0; }
+    Index startCol() const { return IsRowMajor ? 0 : m_outerStart; }
+    Index blockRows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+    Index blockCols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+
   protected:
 
-    typename XprType::Nested m_matrix;
+    typename internal::ref_selector<XprType>::non_const_type m_matrix;
     Index m_outerStart;
     const internal::variable_if_dynamic<Index, OuterSize> m_outerSize;
 
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
-  private:
-    Index nonZeros() const;
+  protected:
+    // Disable assignment with clear error message.
+    // Note that simply removing operator= yields compilation errors with ICC+MSVC
+    template<typename T>
+    BlockImpl& operator=(const T&)
+    {
+      EIGEN_STATIC_ASSERT(sizeof(T)==0, THIS_SPARSE_BLOCK_SUBEXPRESSION_IS_READ_ONLY);
+      return *this;
+    }
 };
 
 
 /***************************************************************************
-* specialisation for SparseMatrix
+* specialization for SparseMatrix
 ***************************************************************************/
 
-template<typename _Scalar, int _Options, typename _Index, int BlockRows, int BlockCols>
-class BlockImpl<SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols,true,Sparse>
-  : public SparseMatrixBase<Block<SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols,true> >
+namespace internal {
+
+template<typename SparseMatrixType, int BlockRows, int BlockCols>
+class sparse_matrix_block_impl
+  : public SparseCompressedBase<Block<SparseMatrixType,BlockRows,BlockCols,true> >
 {
-    typedef SparseMatrix<_Scalar, _Options, _Index> SparseMatrixType;
     typedef typename internal::remove_all<typename SparseMatrixType::Nested>::type _MatrixTypeNested;
     typedef Block<SparseMatrixType, BlockRows, BlockCols, true> BlockType;
-    typedef Block<const SparseMatrixType, BlockRows, BlockCols, true> ConstBlockType;
+    typedef SparseCompressedBase<Block<SparseMatrixType,BlockRows,BlockCols,true> > Base;
+    using Base::convert_index;
 public:
     enum { IsRowMajor = internal::traits<BlockType>::IsRowMajor };
     EIGEN_SPARSE_PUBLIC_INTERFACE(BlockType)
 protected:
+    typedef typename Base::IndexVector IndexVector;
     enum { OuterSize = IsRowMajor ? BlockRows : BlockCols };
 public:
-    
-    class InnerIterator: public SparseMatrixType::InnerIterator
-    {
-      public:
-        inline InnerIterator(const BlockType& xpr, Index outer)
-          : SparseMatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
-        {}
-        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
-      protected:
-        Index m_outer;
-    };
-    class ReverseInnerIterator: public SparseMatrixType::ReverseInnerIterator
-    {
-      public:
-        inline ReverseInnerIterator(const BlockType& xpr, Index outer)
-          : SparseMatrixType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
-        {}
-        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
-      protected:
-        Index m_outer;
-    };
-
-    inline BlockImpl(const SparseMatrixType& xpr, int i)
-      : m_matrix(xpr), m_outerStart(i), m_outerSize(OuterSize)
-    {}
-
-    inline BlockImpl(const SparseMatrixType& xpr, int startRow, int startCol, int blockRows, int blockCols)
-      : m_matrix(xpr), m_outerStart(IsRowMajor ? startRow : startCol), m_outerSize(IsRowMajor ? blockRows : blockCols)
+
+    inline sparse_matrix_block_impl(SparseMatrixType& xpr, Index i)
+      : m_matrix(xpr), m_outerStart(convert_index(i)), m_outerSize(OuterSize)
+    {}
+
+    inline sparse_matrix_block_impl(SparseMatrixType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
+      : m_matrix(xpr), m_outerStart(convert_index(IsRowMajor ? startRow : startCol)), m_outerSize(convert_index(IsRowMajor ? blockRows : blockCols))
     {}
 
     template<typename OtherDerived>
     inline BlockType& operator=(const SparseMatrixBase<OtherDerived>& other)
     {
       typedef typename internal::remove_all<typename SparseMatrixType::Nested>::type _NestedMatrixType;
-      _NestedMatrixType& matrix = const_cast<_NestedMatrixType&>(m_matrix);;
-      // This assignement is slow if this vector set is not empty
+      _NestedMatrixType& matrix = m_matrix;
+      // This assignment is slow if this vector set is not empty
       // and/or it is not at the end of the nonzeros of the underlying matrix.
 
       // 1 - eval to a temporary to avoid transposition and/or aliasing issues
-      SparseMatrix<Scalar, IsRowMajor ? RowMajor : ColMajor, Index> tmp(other);
+      Ref<const SparseMatrix<Scalar, IsRowMajor ? RowMajor : ColMajor, StorageIndex> > tmp(other.derived());
+      eigen_internal_assert(tmp.outerSize()==m_outerSize.value());
 
       // 2 - let's check whether there is enough allocated memory
       Index nnz           = tmp.nonZeros();
-      Index start         = m_outerStart==0 ? 0 : matrix.outerIndexPtr()[m_outerStart]; // starting position of the current block
-      Index end           = m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()]; // ending posiiton of the current block
+      Index start         = m_outerStart==0 ? 0 : m_matrix.outerIndexPtr()[m_outerStart]; // starting position of the current block
+      Index end           = m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()]; // ending position of the current block
       Index block_size    = end - start;                                                // available room in the current block
       Index tail_size     = m_matrix.outerIndexPtr()[m_matrix.outerSize()] - end;
-      
+
       Index free_size     = m_matrix.isCompressed()
                           ? Index(matrix.data().allocatedSize()) + block_size
                           : block_size;
 
-      if(nnz>free_size) 
+      Index tmp_start = tmp.outerIndexPtr()[0];
+
+      bool update_trailing_pointers = false;
+      if(nnz>free_size)
       {
         // realloc manually to reduce copies
         typename SparseMatrixType::Storage newdata(m_matrix.data().allocatedSize() - block_size + nnz);
 
-        std::memcpy(&newdata.value(0), &m_matrix.data().value(0), start*sizeof(Scalar));
-        std::memcpy(&newdata.index(0), &m_matrix.data().index(0), start*sizeof(Index));
-
-        std::memcpy(&newdata.value(start), &tmp.data().value(0), nnz*sizeof(Scalar));
-        std::memcpy(&newdata.index(start), &tmp.data().index(0), nnz*sizeof(Index));
-
-        std::memcpy(&newdata.value(start+nnz), &matrix.data().value(end), tail_size*sizeof(Scalar));
-        std::memcpy(&newdata.index(start+nnz), &matrix.data().index(end), tail_size*sizeof(Index));
-        
+        internal::smart_copy(m_matrix.valuePtr(),       m_matrix.valuePtr() + start,      newdata.valuePtr());
+        internal::smart_copy(m_matrix.innerIndexPtr(),  m_matrix.innerIndexPtr() + start, newdata.indexPtr());
+
+        internal::smart_copy(tmp.valuePtr() + tmp_start,      tmp.valuePtr() + tmp_start + nnz,       newdata.valuePtr() + start);
+        internal::smart_copy(tmp.innerIndexPtr() + tmp_start, tmp.innerIndexPtr() + tmp_start + nnz,  newdata.indexPtr() + start);
+
+        internal::smart_copy(matrix.valuePtr()+end,       matrix.valuePtr()+end + tail_size,      newdata.valuePtr()+start+nnz);
+        internal::smart_copy(matrix.innerIndexPtr()+end,  matrix.innerIndexPtr()+end + tail_size, newdata.indexPtr()+start+nnz);
+
         newdata.resize(m_matrix.outerIndexPtr()[m_matrix.outerSize()] - block_size + nnz);
 
         matrix.data().swap(newdata);
+
+        update_trailing_pointers = true;
+      }
+      else
+      {
+        if(m_matrix.isCompressed())
+        {
+          // no need to realloc, simply copy the tail at its respective position and insert tmp
+          matrix.data().resize(start + nnz + tail_size);
+
+          internal::smart_memmove(matrix.valuePtr()+end,      matrix.valuePtr() + end+tail_size,      matrix.valuePtr() + start+nnz);
+          internal::smart_memmove(matrix.innerIndexPtr()+end, matrix.innerIndexPtr() + end+tail_size, matrix.innerIndexPtr() + start+nnz);
+
+          update_trailing_pointers = true;
+        }
+
+        internal::smart_copy(tmp.valuePtr() + tmp_start,      tmp.valuePtr() + tmp_start + nnz,       matrix.valuePtr() + start);
+        internal::smart_copy(tmp.innerIndexPtr() + tmp_start, tmp.innerIndexPtr() + tmp_start + nnz,  matrix.innerIndexPtr() + start);
+      }
+
+      // update outer index pointers and innerNonZeros
+      if(IsVectorAtCompileTime)
+      {
+        if(!m_matrix.isCompressed())
+          matrix.innerNonZeroPtr()[m_outerStart] = StorageIndex(nnz);
+        matrix.outerIndexPtr()[m_outerStart] = StorageIndex(start);
       }
       else
       {
-        // no need to realloc, simply copy the tail at its respective position and insert tmp
-        matrix.data().resize(start + nnz + tail_size);
-
-        std::memmove(&matrix.data().value(start+nnz), &matrix.data().value(end), tail_size*sizeof(Scalar));
-        std::memmove(&matrix.data().index(start+nnz), &matrix.data().index(end), tail_size*sizeof(Index));
-
-        std::memcpy(&matrix.data().value(start), &tmp.data().value(0), nnz*sizeof(Scalar));
-        std::memcpy(&matrix.data().index(start), &tmp.data().index(0), nnz*sizeof(Index));
-      }
-      
-      // update innerNonZeros
-      if(!m_matrix.isCompressed())
-        for(Index j=0; j<m_outerSize.value(); ++j)
-          matrix.innerNonZeroPtr()[m_outerStart+j] = tmp.innerVector(j).nonZeros();
-
-      // update outer index pointers
-      Index p = start;
-      for(Index k=0; k<m_outerSize.value(); ++k)
-      {
-        matrix.outerIndexPtr()[m_outerStart+k] = p;
-        p += tmp.innerVector(k).nonZeros();
-      }
-      std::ptrdiff_t offset = nnz - block_size;
-      for(Index k = m_outerStart + m_outerSize.value(); k<=matrix.outerSize(); ++k)
-      {
-        matrix.outerIndexPtr()[k] += offset;
+        StorageIndex p = StorageIndex(start);
+        for(Index k=0; k<m_outerSize.value(); ++k)
+        {
+          StorageIndex nnz_k = internal::convert_index<StorageIndex>(tmp.innerVector(k).nonZeros());
+          if(!m_matrix.isCompressed())
+            matrix.innerNonZeroPtr()[m_outerStart+k] = nnz_k;
+          matrix.outerIndexPtr()[m_outerStart+k] = p;
+          p += nnz_k;
+        }
+      }
+
+      if(update_trailing_pointers)
+      {
+        StorageIndex offset = internal::convert_index<StorageIndex>(nnz - block_size);
+        for(Index k = m_outerStart + m_outerSize.value(); k<=matrix.outerSize(); ++k)
+        {
+          matrix.outerIndexPtr()[k] += offset;
+        }
       }
 
       return derived();
     }
 
@@ -200,141 +215,115 @@
     {
       return operator=<BlockType>(other);
     }
 
     inline const Scalar* valuePtr() const
-    { return m_matrix.valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
+    { return m_matrix.valuePtr(); }
     inline Scalar* valuePtr()
-    { return m_matrix.const_cast_derived().valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
-
-    inline const Index* innerIndexPtr() const
-    { return m_matrix.innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
-    inline Index* innerIndexPtr()
-    { return m_matrix.const_cast_derived().innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
-
-    inline const Index* outerIndexPtr() const
+    { return m_matrix.valuePtr(); }
+
+    inline const StorageIndex* innerIndexPtr() const
+    { return m_matrix.innerIndexPtr(); }
+    inline StorageIndex* innerIndexPtr()
+    { return m_matrix.innerIndexPtr(); }
+
+    inline const StorageIndex* outerIndexPtr() const
+    { return m_matrix.outerIndexPtr() + m_outerStart; }
+    inline StorageIndex* outerIndexPtr()
     { return m_matrix.outerIndexPtr() + m_outerStart; }
-    inline Index* outerIndexPtr()
-    { return m_matrix.const_cast_derived().outerIndexPtr() + m_outerStart; }
-
-    Index nonZeros() const
-    {
-      if(m_matrix.isCompressed())
-        return  std::size_t(m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()])
-              - std::size_t(m_matrix.outerIndexPtr()[m_outerStart]);
-      else if(m_outerSize.value()==0)
-        return 0;
-      else
-        return Map<const Matrix<Index,OuterSize,1> >(m_matrix.innerNonZeroPtr()+m_outerStart, m_outerSize.value()).sum();
+
+    inline const StorageIndex* innerNonZeroPtr() const
+    { return isCompressed() ? 0 : (m_matrix.innerNonZeroPtr()+m_outerStart); }
+    inline StorageIndex* innerNonZeroPtr()
+    { return isCompressed() ? 0 : (m_matrix.innerNonZeroPtr()+m_outerStart); }
+
+    bool isCompressed() const { return m_matrix.innerNonZeroPtr()==0; }
+
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      return m_matrix.coeffRef(row + (IsRowMajor ? m_outerStart : 0), col + (IsRowMajor ? 0 :  m_outerStart));
+    }
+
+    inline const Scalar coeff(Index row, Index col) const
+    {
+      return m_matrix.coeff(row + (IsRowMajor ? m_outerStart : 0), col + (IsRowMajor ? 0 :  m_outerStart));
+    }
+
+    inline const Scalar coeff(Index index) const
+    {
+      return m_matrix.coeff(IsRowMajor ? m_outerStart : index, IsRowMajor ? index :  m_outerStart);
     }
 
     const Scalar& lastCoeff() const
     {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(BlockImpl);
-      eigen_assert(nonZeros()>0);
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(sparse_matrix_block_impl);
+      eigen_assert(Base::nonZeros()>0);
       if(m_matrix.isCompressed())
         return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart+1]-1];
       else
         return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart]+m_matrix.innerNonZeroPtr()[m_outerStart]-1];
     }
 
     EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
     EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
 
-  protected:
-
-    typename SparseMatrixType::Nested m_matrix;
-    Index m_outerStart;
-    const internal::variable_if_dynamic<Index, OuterSize> m_outerSize;
-
-};
-
-
-template<typename _Scalar, int _Options, typename _Index, int BlockRows, int BlockCols>
-class BlockImpl<const SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols,true,Sparse>
-  : public SparseMatrixBase<Block<const SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols,true> >
-{
-    typedef SparseMatrix<_Scalar, _Options, _Index> SparseMatrixType;
-    typedef typename internal::remove_all<typename SparseMatrixType::Nested>::type _MatrixTypeNested;
-    typedef Block<const SparseMatrixType, BlockRows, BlockCols, true> BlockType;
-public:
-    enum { IsRowMajor = internal::traits<BlockType>::IsRowMajor };
-    EIGEN_SPARSE_PUBLIC_INTERFACE(BlockType)
-protected:
-    enum { OuterSize = IsRowMajor ? BlockRows : BlockCols };
-public:
-    
-    class InnerIterator: public SparseMatrixType::InnerIterator
-    {
-      public:
-        inline InnerIterator(const BlockType& xpr, Index outer)
-          : SparseMatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
-        {}
-        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
-      protected:
-        Index m_outer;
-    };
-    class ReverseInnerIterator: public SparseMatrixType::ReverseInnerIterator
-    {
-      public:
-        inline ReverseInnerIterator(const BlockType& xpr, Index outer)
-          : SparseMatrixType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
-        {}
-        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
-      protected:
-        Index m_outer;
-    };
-
-    inline BlockImpl(const SparseMatrixType& xpr, int i)
-      : m_matrix(xpr), m_outerStart(i), m_outerSize(OuterSize)
-    {}
-
-    inline BlockImpl(const SparseMatrixType& xpr, int startRow, int startCol, int blockRows, int blockCols)
-      : m_matrix(xpr), m_outerStart(IsRowMajor ? startRow : startCol), m_outerSize(IsRowMajor ? blockRows : blockCols)
-    {}
-
-    inline const Scalar* valuePtr() const
-    { return m_matrix.valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
-
-    inline const Index* innerIndexPtr() const
-    { return m_matrix.innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
-
-    inline const Index* outerIndexPtr() const
-    { return m_matrix.outerIndexPtr() + m_outerStart; }
-
-    Index nonZeros() const
-    {
-      if(m_matrix.isCompressed())
-        return  std::size_t(m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()])
-              - std::size_t(m_matrix.outerIndexPtr()[m_outerStart]);
-      else if(m_outerSize.value()==0)
-        return 0;
-      else
-        return Map<const Matrix<Index,OuterSize,1> >(m_matrix.innerNonZeroPtr()+m_outerStart, m_outerSize.value()).sum();
-    }
-
-    const Scalar& lastCoeff() const
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(BlockImpl);
-      eigen_assert(nonZeros()>0);
-      if(m_matrix.isCompressed())
-        return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart+1]-1];
-      else
-        return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart]+m_matrix.innerNonZeroPtr()[m_outerStart]-1];
-    }
-
-    EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
-
-  protected:
-
-    typename SparseMatrixType::Nested m_matrix;
-    Index m_outerStart;
-    const internal::variable_if_dynamic<Index, OuterSize> m_outerSize;
-
+    inline const SparseMatrixType& nestedExpression() const { return m_matrix; }
+    inline SparseMatrixType& nestedExpression() { return m_matrix; }
+    Index startRow() const { return IsRowMajor ? m_outerStart : 0; }
+    Index startCol() const { return IsRowMajor ? 0 : m_outerStart; }
+    Index blockRows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+    Index blockCols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+
+  protected:
+
+    typename internal::ref_selector<SparseMatrixType>::non_const_type m_matrix;
+    Index m_outerStart;
+    const internal::variable_if_dynamic<Index, OuterSize> m_outerSize;
+
+};
+
+} // namespace internal
+
+template<typename _Scalar, int _Options, typename _StorageIndex, int BlockRows, int BlockCols>
+class BlockImpl<SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols,true,Sparse>
+  : public internal::sparse_matrix_block_impl<SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols>
+{
+public:
+  typedef _StorageIndex StorageIndex;
+  typedef SparseMatrix<_Scalar, _Options, _StorageIndex> SparseMatrixType;
+  typedef internal::sparse_matrix_block_impl<SparseMatrixType,BlockRows,BlockCols> Base;
+  inline BlockImpl(SparseMatrixType& xpr, Index i)
+    : Base(xpr, i)
+  {}
+
+  inline BlockImpl(SparseMatrixType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
+    : Base(xpr, startRow, startCol, blockRows, blockCols)
+  {}
+
+  using Base::operator=;
+};
+
+template<typename _Scalar, int _Options, typename _StorageIndex, int BlockRows, int BlockCols>
+class BlockImpl<const SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols,true,Sparse>
+  : public internal::sparse_matrix_block_impl<const SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols>
+{
+public:
+  typedef _StorageIndex StorageIndex;
+  typedef const SparseMatrix<_Scalar, _Options, _StorageIndex> SparseMatrixType;
+  typedef internal::sparse_matrix_block_impl<SparseMatrixType,BlockRows,BlockCols> Base;
+  inline BlockImpl(SparseMatrixType& xpr, Index i)
+    : Base(xpr, i)
+  {}
+
+  inline BlockImpl(SparseMatrixType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
+    : Base(xpr, startRow, startCol, blockRows, blockCols)
+  {}
+
+  using Base::operator=;
+private:
+  template<typename Derived> BlockImpl(const SparseMatrixBase<Derived>& xpr, Index i);
+  template<typename Derived> BlockImpl(const SparseMatrixBase<Derived>& xpr);
 };
 
 //----------
 
 /** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
@@ -353,147 +342,262 @@
 
 /** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
   * is col-major (resp. row-major).
   */
 template<typename Derived>
-Block<Derived,Dynamic,Dynamic,true> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize)
+typename SparseMatrixBase<Derived>::InnerVectorsReturnType
+SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize)
 {
   return Block<Derived,Dynamic,Dynamic,true>(derived(),
                                              IsRowMajor ? outerStart : 0, IsRowMajor ? 0 : outerStart,
                                              IsRowMajor ? outerSize : rows(), IsRowMajor ? cols() : outerSize);
-  
+
 }
 
 /** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
   * is col-major (resp. row-major). Read-only.
   */
 template<typename Derived>
-const Block<const Derived,Dynamic,Dynamic,true> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize) const
+const typename SparseMatrixBase<Derived>::ConstInnerVectorsReturnType
+SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize) const
 {
   return Block<const Derived,Dynamic,Dynamic,true>(derived(),
                                                   IsRowMajor ? outerStart : 0, IsRowMajor ? 0 : outerStart,
                                                   IsRowMajor ? outerSize : rows(), IsRowMajor ? cols() : outerSize);
-  
+
 }
 
 /** Generic implementation of sparse Block expression.
-  * Real-only. 
+  * Real-only.
   */
 template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
 class BlockImpl<XprType,BlockRows,BlockCols,InnerPanel,Sparse>
   : public SparseMatrixBase<Block<XprType,BlockRows,BlockCols,InnerPanel> >, internal::no_assignment_operator
 {
-  typedef typename internal::remove_all<typename XprType::Nested>::type _MatrixTypeNested;
-  typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
+    typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
+    typedef SparseMatrixBase<BlockType> Base;
+    using Base::convert_index;
 public:
     enum { IsRowMajor = internal::traits<BlockType>::IsRowMajor };
     EIGEN_SPARSE_PUBLIC_INTERFACE(BlockType)
 
+    typedef typename internal::remove_all<typename XprType::Nested>::type _MatrixTypeNested;
+
     /** Column or Row constructor
       */
-    inline BlockImpl(const XprType& xpr, int i)
+    inline BlockImpl(XprType& xpr, Index i)
       : m_matrix(xpr),
-        m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0),
-        m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0),
-        m_blockRows(xpr.rows()),
-        m_blockCols(xpr.cols())
+        m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? convert_index(i) : 0),
+        m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? convert_index(i) : 0),
+        m_blockRows(BlockRows==1 ? 1 : xpr.rows()),
+        m_blockCols(BlockCols==1 ? 1 : xpr.cols())
     {}
 
     /** Dynamic-size constructor
       */
-    inline BlockImpl(const XprType& xpr, int startRow, int startCol, int blockRows, int blockCols)
-      : m_matrix(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(blockRows), m_blockCols(blockCols)
+    inline BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
+      : m_matrix(xpr), m_startRow(convert_index(startRow)), m_startCol(convert_index(startCol)), m_blockRows(convert_index(blockRows)), m_blockCols(convert_index(blockCols))
     {}
 
-    inline int rows() const { return m_blockRows.value(); }
-    inline int cols() const { return m_blockCols.value(); }
+    inline Index rows() const { return m_blockRows.value(); }
+    inline Index cols() const { return m_blockCols.value(); }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
-      return m_matrix.const_cast_derived()
-               .coeffRef(row + m_startRow.value(), col + m_startCol.value());
+      return m_matrix.coeffRef(row + m_startRow.value(), col + m_startCol.value());
     }
 
-    inline const Scalar coeff(int row, int col) const
+    inline const Scalar coeff(Index row, Index col) const
     {
       return m_matrix.coeff(row + m_startRow.value(), col + m_startCol.value());
     }
 
-    inline Scalar& coeffRef(int index)
-    {
-      return m_matrix.const_cast_derived()
-             .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                       m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-    }
-
-    inline const Scalar coeff(int index) const
-    {
-      return m_matrix
-             .coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                    m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-    }
-    
-    inline const _MatrixTypeNested& nestedExpression() const { return m_matrix; }
-    
-    class InnerIterator : public _MatrixTypeNested::InnerIterator
-    {
-      typedef typename _MatrixTypeNested::InnerIterator Base;
-      const BlockType& m_block;
-      Index m_end;
-    public:
-
-      EIGEN_STRONG_INLINE InnerIterator(const BlockType& block, Index outer)
-        : Base(block.derived().nestedExpression(), outer + (IsRowMajor ? block.m_startRow.value() : block.m_startCol.value())),
-          m_block(block),
-          m_end(IsRowMajor ? block.m_startCol.value()+block.m_blockCols.value() : block.m_startRow.value()+block.m_blockRows.value())
-      {
-        while( (Base::operator bool()) && (Base::index() < (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value())) )
-          Base::operator++();
-      }
-
-      inline Index index()  const { return Base::index() - (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value()); }
-      inline Index outer()  const { return Base::outer() - (IsRowMajor ? m_block.m_startRow.value() : m_block.m_startCol.value()); }
-      inline Index row()    const { return Base::row()   - m_block.m_startRow.value(); }
-      inline Index col()    const { return Base::col()   - m_block.m_startCol.value(); }
-      
-      inline operator bool() const { return Base::operator bool() && Base::index() < m_end; }
-    };
-    class ReverseInnerIterator : public _MatrixTypeNested::ReverseInnerIterator
-    {
-      typedef typename _MatrixTypeNested::ReverseInnerIterator Base;
-      const BlockType& m_block;
-      Index m_begin;
-    public:
-
-      EIGEN_STRONG_INLINE ReverseInnerIterator(const BlockType& block, Index outer)
-        : Base(block.derived().nestedExpression(), outer + (IsRowMajor ? block.m_startRow.value() : block.m_startCol.value())),
-          m_block(block),
-          m_begin(IsRowMajor ? block.m_startCol.value() : block.m_startRow.value())
-      {
-        while( (Base::operator bool()) && (Base::index() >= (IsRowMajor ? m_block.m_startCol.value()+block.m_blockCols.value() : m_block.m_startRow.value()+block.m_blockRows.value())) )
-          Base::operator--();
-      }
-
-      inline Index index()  const { return Base::index() - (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value()); }
-      inline Index outer()  const { return Base::outer() - (IsRowMajor ? m_block.m_startRow.value() : m_block.m_startCol.value()); }
-      inline Index row()    const { return Base::row()   - m_block.m_startRow.value(); }
-      inline Index col()    const { return Base::col()   - m_block.m_startCol.value(); }
-      
-      inline operator bool() const { return Base::operator bool() && Base::index() >= m_begin; }
-    };
-  protected:
-    friend class InnerIterator;
-    friend class ReverseInnerIterator;
-    
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
-
-    typename XprType::Nested m_matrix;
+    inline Scalar& coeffRef(Index index)
+    {
+      return m_matrix.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+                               m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
+    }
+
+    inline const Scalar coeff(Index index) const
+    {
+      return m_matrix.coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+                            m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
+    }
+
+    inline const XprType& nestedExpression() const { return m_matrix; }
+    inline XprType& nestedExpression() { return m_matrix; }
+    Index startRow() const { return m_startRow.value(); }
+    Index startCol() const { return m_startCol.value(); }
+    Index blockRows() const { return m_blockRows.value(); }
+    Index blockCols() const { return m_blockCols.value(); }
+
+  protected:
+//     friend class internal::GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel>;
+    friend struct internal::unary_evaluator<Block<XprType,BlockRows,BlockCols,InnerPanel>, internal::IteratorBased, Scalar >;
+
+    Index nonZeros() const { return Dynamic; }
+
+    typename internal::ref_selector<XprType>::non_const_type m_matrix;
     const internal::variable_if_dynamic<Index, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
     const internal::variable_if_dynamic<Index, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
     const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_blockRows;
     const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_blockCols;
 
+  protected:
+    // Disable assignment with clear error message.
+    // Note that simply removing operator= yields compilation errors with ICC+MSVC
+    template<typename T>
+    BlockImpl& operator=(const T&)
+    {
+      EIGEN_STATIC_ASSERT(sizeof(T)==0, THIS_SPARSE_BLOCK_SUBEXPRESSION_IS_READ_ONLY);
+      return *this;
+    }
+
+};
+
+namespace internal {
+
+template<typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
+struct unary_evaluator<Block<ArgType,BlockRows,BlockCols,InnerPanel>, IteratorBased >
+ : public evaluator_base<Block<ArgType,BlockRows,BlockCols,InnerPanel> >
+{
+    class InnerVectorInnerIterator;
+    class OuterVectorInnerIterator;
+  public:
+    typedef Block<ArgType,BlockRows,BlockCols,InnerPanel> XprType;
+    typedef typename XprType::StorageIndex StorageIndex;
+    typedef typename XprType::Scalar Scalar;
+
+    enum {
+      IsRowMajor = XprType::IsRowMajor,
+
+      OuterVector =  (BlockCols==1 && ArgType::IsRowMajor)
+                    | // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
+                      // revert to || as soon as not needed anymore.
+                     (BlockRows==1 && !ArgType::IsRowMajor),
+
+      CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+      Flags = XprType::Flags
+    };
+
+    typedef typename internal::conditional<OuterVector,OuterVectorInnerIterator,InnerVectorInnerIterator>::type InnerIterator;
+
+    explicit unary_evaluator(const XprType& op)
+      : m_argImpl(op.nestedExpression()), m_block(op)
+    {}
+
+    inline Index nonZerosEstimate() const {
+      Index nnz = m_block.nonZeros();
+      if(nnz<0)
+        return m_argImpl.nonZerosEstimate() * m_block.size() / m_block.nestedExpression().size();
+      return nnz;
+    }
+
+  protected:
+    typedef typename evaluator<ArgType>::InnerIterator EvalIterator;
+
+    evaluator<ArgType> m_argImpl;
+    const XprType &m_block;
+};
+
+template<typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
+class unary_evaluator<Block<ArgType,BlockRows,BlockCols,InnerPanel>, IteratorBased>::InnerVectorInnerIterator
+ : public EvalIterator
+{
+  enum { IsRowMajor = unary_evaluator::IsRowMajor };
+  const XprType& m_block;
+  Index m_end;
+public:
+
+  EIGEN_STRONG_INLINE InnerVectorInnerIterator(const unary_evaluator& aEval, Index outer)
+    : EvalIterator(aEval.m_argImpl, outer + (IsRowMajor ? aEval.m_block.startRow() : aEval.m_block.startCol())),
+      m_block(aEval.m_block),
+      m_end(IsRowMajor ? aEval.m_block.startCol()+aEval.m_block.blockCols() : aEval.m_block.startRow()+aEval.m_block.blockRows())
+  {
+    while( (EvalIterator::operator bool()) && (EvalIterator::index() < (IsRowMajor ? m_block.startCol() : m_block.startRow())) )
+      EvalIterator::operator++();
+  }
+
+  inline StorageIndex index() const { return EvalIterator::index() - convert_index<StorageIndex>(IsRowMajor ? m_block.startCol() : m_block.startRow()); }
+  inline Index outer()  const { return EvalIterator::outer() - (IsRowMajor ? m_block.startRow() : m_block.startCol()); }
+  inline Index row()    const { return EvalIterator::row()   - m_block.startRow(); }
+  inline Index col()    const { return EvalIterator::col()   - m_block.startCol(); }
+
+  inline operator bool() const { return EvalIterator::operator bool() && EvalIterator::index() < m_end; }
+};
+
+template<typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
+class unary_evaluator<Block<ArgType,BlockRows,BlockCols,InnerPanel>, IteratorBased>::OuterVectorInnerIterator
+{
+  enum { IsRowMajor = unary_evaluator::IsRowMajor };
+  const unary_evaluator& m_eval;
+  Index m_outerPos;
+  const Index m_innerIndex;
+  Index m_end;
+  EvalIterator m_it;
+public:
+
+  EIGEN_STRONG_INLINE OuterVectorInnerIterator(const unary_evaluator& aEval, Index outer)
+    : m_eval(aEval),
+      m_outerPos( (IsRowMajor ? aEval.m_block.startCol() : aEval.m_block.startRow()) ),
+      m_innerIndex(IsRowMajor ? aEval.m_block.startRow() : aEval.m_block.startCol()),
+      m_end(IsRowMajor ? aEval.m_block.startCol()+aEval.m_block.blockCols() : aEval.m_block.startRow()+aEval.m_block.blockRows()),
+      m_it(m_eval.m_argImpl, m_outerPos)
+  {
+    EIGEN_UNUSED_VARIABLE(outer);
+    eigen_assert(outer==0);
+
+    while(m_it && m_it.index() < m_innerIndex) ++m_it;
+    if((!m_it) || (m_it.index()!=m_innerIndex))
+      ++(*this);
+  }
+
+  inline StorageIndex index() const { return convert_index<StorageIndex>(m_outerPos - (IsRowMajor ? m_eval.m_block.startCol() : m_eval.m_block.startRow())); }
+  inline Index outer()  const { return 0; }
+  inline Index row()    const { return IsRowMajor ? 0 : index(); }
+  inline Index col()    const { return IsRowMajor ? index() : 0; }
+
+  inline Scalar value() const { return m_it.value(); }
+  inline Scalar& valueRef() { return m_it.valueRef(); }
+
+  inline OuterVectorInnerIterator& operator++()
+  {
+    // search next non-zero entry
+    while(++m_outerPos<m_end)
+    {
+      // Restart iterator at the next inner-vector:
+      m_it.~EvalIterator();
+      ::new (&m_it) EvalIterator(m_eval.m_argImpl, m_outerPos);
+      // search for the key m_innerIndex in the current outer-vector
+      while(m_it && m_it.index() < m_innerIndex) ++m_it;
+      if(m_it && m_it.index()==m_innerIndex) break;
+    }
+    return *this;
+  }
+
+  inline operator bool() const { return m_outerPos < m_end; }
+};
+
+template<typename _Scalar, int _Options, typename _StorageIndex, int BlockRows, int BlockCols>
+struct unary_evaluator<Block<SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols,true>, IteratorBased>
+  : evaluator<SparseCompressedBase<Block<SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols,true> > >
+{
+  typedef Block<SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols,true> XprType;
+  typedef evaluator<SparseCompressedBase<XprType> > Base;
+  explicit unary_evaluator(const XprType &xpr) : Base(xpr) {}
+};
+
+template<typename _Scalar, int _Options, typename _StorageIndex, int BlockRows, int BlockCols>
+struct unary_evaluator<Block<const SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols,true>, IteratorBased>
+  : evaluator<SparseCompressedBase<Block<const SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols,true> > >
+{
+  typedef Block<const SparseMatrix<_Scalar, _Options, _StorageIndex>,BlockRows,BlockCols,true> XprType;
+  typedef evaluator<SparseCompressedBase<XprType> > Base;
+  explicit unary_evaluator(const XprType &xpr) : Base(xpr) {}
 };
+
+} // end namespace internal
+
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSE_BLOCK_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseColEtree.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseColEtree.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseColEtree.h
@@ -56,60 +56,59 @@
   * \param parent The elimination tree
   * \param firstRowElt The column index of the first element in each row
   * \param perm The permutation to apply to the column of \b mat
   */
 template <typename MatrixType, typename IndexVector>
-int coletree(const MatrixType& mat, IndexVector& parent, IndexVector& firstRowElt, typename MatrixType::Index *perm=0)
+int coletree(const MatrixType& mat, IndexVector& parent, IndexVector& firstRowElt, typename MatrixType::StorageIndex *perm=0)
 {
-  typedef typename MatrixType::Index Index;
-  Index nc = mat.cols(); // Number of columns 
-  Index m = mat.rows();
-  Index diagSize = (std::min)(nc,m);
+  typedef typename MatrixType::StorageIndex StorageIndex;
+  StorageIndex nc = convert_index<StorageIndex>(mat.cols()); // Number of columns
+  StorageIndex m = convert_index<StorageIndex>(mat.rows());
+  StorageIndex diagSize = (std::min)(nc,m);
   IndexVector root(nc); // root of subtree of etree 
   root.setZero();
   IndexVector pp(nc); // disjoint sets 
   pp.setZero(); // Initialize disjoint sets 
   parent.resize(mat.cols());
   //Compute first nonzero column in each row 
-  Index row,col; 
   firstRowElt.resize(m);
   firstRowElt.setConstant(nc);
   firstRowElt.segment(0, diagSize).setLinSpaced(diagSize, 0, diagSize-1);
   bool found_diag;
-  for (col = 0; col < nc; col++)
+  for (StorageIndex col = 0; col < nc; col++)
   {
-    Index pcol = col;
+    StorageIndex pcol = col;
     if(perm) pcol  = perm[col];
     for (typename MatrixType::InnerIterator it(mat, pcol); it; ++it)
     { 
-      row = it.row();
+      Index row = it.row();
       firstRowElt(row) = (std::min)(firstRowElt(row), col);
     }
   }
   /* Compute etree by Liu's algorithm for symmetric matrices,
           except use (firstRowElt[r],c) in place of an edge (r,c) of A.
     Thus each row clique in A'*A is replaced by a star
     centered at its first vertex, which has the same fill. */
-  Index rset, cset, rroot; 
-  for (col = 0; col < nc; col++) 
+  StorageIndex rset, cset, rroot;
+  for (StorageIndex col = 0; col < nc; col++) 
   {
     found_diag = col>=m;
     pp(col) = col; 
     cset = col; 
     root(cset) = col; 
     parent(col) = nc; 
     /* The diagonal element is treated here even if it does not exist in the matrix
      * hence the loop is executed once more */ 
-    Index pcol = col;
+    StorageIndex pcol = col;
     if(perm) pcol  = perm[col];
     for (typename MatrixType::InnerIterator it(mat, pcol); it||!found_diag; ++it)
     { //  A sequence of interleaved find and union is performed 
       Index i = col;
       if(it) i = it.index();
       if (i == col) found_diag = true;
       
-      row = firstRowElt(i);
+      StorageIndex row = firstRowElt(i);
       if (row >= col) continue; 
       rset = internal::etree_find(row, pp); // Find the name of the set containing row
       rroot = root(rset);
       if (rroot != col) 
       {
@@ -125,14 +124,15 @@
 
 /** 
   * Depth-first search from vertex n.  No recursion.
   * This routine was contributed by Cédric Doucet, CEDRAT Group, Meylan, France.
 */
-template <typename Index, typename IndexVector>
-void nr_etdfs (Index n, IndexVector& parent, IndexVector& first_kid, IndexVector& next_kid, IndexVector& post, Index postnum)
+template <typename IndexVector>
+void nr_etdfs (typename IndexVector::Scalar n, IndexVector& parent, IndexVector& first_kid, IndexVector& next_kid, IndexVector& post, typename IndexVector::Scalar postnum)
 {
-  Index current = n, first, next;
+  typedef typename IndexVector::Scalar StorageIndex;
+  StorageIndex current = n, first, next;
   while (postnum != n) 
   {
     // No kid for the current node
     first = first_kid(current);
     
@@ -172,26 +172,26 @@
   * \brief Post order a tree 
   * \param n the number of nodes
   * \param parent Input tree
   * \param post postordered tree
   */
-template <typename Index, typename IndexVector>
-void treePostorder(Index n, IndexVector& parent, IndexVector& post)
+template <typename IndexVector>
+void treePostorder(typename IndexVector::Scalar n, IndexVector& parent, IndexVector& post)
 {
+  typedef typename IndexVector::Scalar StorageIndex;
   IndexVector first_kid, next_kid; // Linked list of children 
-  Index postnum; 
+  StorageIndex postnum; 
   // Allocate storage for working arrays and results 
   first_kid.resize(n+1); 
   next_kid.setZero(n+1);
   post.setZero(n+1);
   
   // Set up structure describing children
-  Index v, dad; 
   first_kid.setConstant(-1); 
-  for (v = n-1; v >= 0; v--) 
+  for (StorageIndex v = n-1; v >= 0; v--) 
   {
-    dad = parent(v);
+    StorageIndex dad = parent(v);
     next_kid(v) = first_kid(dad); 
     first_kid(dad) = v; 
   }
   
   // Depth-first search from dummy root vertex #n

ADDED   3rd_party/eigen/Eigen/src/SparseCore/SparseCompressedBase.h
Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseCompressedBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseCompressedBase.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseCompressedBase.h
@@ -0,0 +1,341 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_COMPRESSED_BASE_H
+#define EIGEN_SPARSE_COMPRESSED_BASE_H
+
+namespace Eigen { 
+
+template<typename Derived> class SparseCompressedBase;
+  
+namespace internal {
+
+template<typename Derived>
+struct traits<SparseCompressedBase<Derived> > : traits<Derived>
+{};
+
+} // end namespace internal
+
+/** \ingroup SparseCore_Module
+  * \class SparseCompressedBase
+  * \brief Common base class for sparse [compressed]-{row|column}-storage format.
+  *
+  * This class defines the common interface for all derived classes implementing the compressed sparse storage format, such as:
+  *  - SparseMatrix
+  *  - Ref<SparseMatrixType,Options>
+  *  - Map<SparseMatrixType>
+  *
+  */
+template<typename Derived>
+class SparseCompressedBase
+  : public SparseMatrixBase<Derived>
+{
+  public:
+    typedef SparseMatrixBase<Derived> Base;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseCompressedBase)
+    using Base::operator=;
+    using Base::IsRowMajor;
+    
+    class InnerIterator;
+    class ReverseInnerIterator;
+    
+  protected:
+    typedef typename Base::IndexVector IndexVector;
+    Eigen::Map<IndexVector> innerNonZeros() { return Eigen::Map<IndexVector>(innerNonZeroPtr(), isCompressed()?0:derived().outerSize()); }
+    const  Eigen::Map<const IndexVector> innerNonZeros() const { return Eigen::Map<const IndexVector>(innerNonZeroPtr(), isCompressed()?0:derived().outerSize()); }
+        
+  public:
+    
+    /** \returns the number of non zero coefficients */
+    inline Index nonZeros() const
+    {
+      if(Derived::IsVectorAtCompileTime && outerIndexPtr()==0)
+        return derived().nonZeros();
+      else if(isCompressed())
+        return outerIndexPtr()[derived().outerSize()]-outerIndexPtr()[0];
+      else if(derived().outerSize()==0)
+        return 0;
+      else
+        return innerNonZeros().sum();
+    }
+    
+    /** \returns a const pointer to the array of values.
+      * This function is aimed at interoperability with other libraries.
+      * \sa innerIndexPtr(), outerIndexPtr() */
+    inline const Scalar* valuePtr() const { return derived().valuePtr(); }
+    /** \returns a non-const pointer to the array of values.
+      * This function is aimed at interoperability with other libraries.
+      * \sa innerIndexPtr(), outerIndexPtr() */
+    inline Scalar* valuePtr() { return derived().valuePtr(); }
+
+    /** \returns a const pointer to the array of inner indices.
+      * This function is aimed at interoperability with other libraries.
+      * \sa valuePtr(), outerIndexPtr() */
+    inline const StorageIndex* innerIndexPtr() const { return derived().innerIndexPtr(); }
+    /** \returns a non-const pointer to the array of inner indices.
+      * This function is aimed at interoperability with other libraries.
+      * \sa valuePtr(), outerIndexPtr() */
+    inline StorageIndex* innerIndexPtr() { return derived().innerIndexPtr(); }
+
+    /** \returns a const pointer to the array of the starting positions of the inner vectors.
+      * This function is aimed at interoperability with other libraries.
+      * \warning it returns the null pointer 0 for SparseVector
+      * \sa valuePtr(), innerIndexPtr() */
+    inline const StorageIndex* outerIndexPtr() const { return derived().outerIndexPtr(); }
+    /** \returns a non-const pointer to the array of the starting positions of the inner vectors.
+      * This function is aimed at interoperability with other libraries.
+      * \warning it returns the null pointer 0 for SparseVector
+      * \sa valuePtr(), innerIndexPtr() */
+    inline StorageIndex* outerIndexPtr() { return derived().outerIndexPtr(); }
+
+    /** \returns a const pointer to the array of the number of non zeros of the inner vectors.
+      * This function is aimed at interoperability with other libraries.
+      * \warning it returns the null pointer 0 in compressed mode */
+    inline const StorageIndex* innerNonZeroPtr() const { return derived().innerNonZeroPtr(); }
+    /** \returns a non-const pointer to the array of the number of non zeros of the inner vectors.
+      * This function is aimed at interoperability with other libraries.
+      * \warning it returns the null pointer 0 in compressed mode */
+    inline StorageIndex* innerNonZeroPtr() { return derived().innerNonZeroPtr(); }
+    
+    /** \returns whether \c *this is in compressed form. */
+    inline bool isCompressed() const { return innerNonZeroPtr()==0; }
+
+    /** \returns a read-only view of the stored coefficients as a 1D array expression.
+      *
+      * \warning this method is for \b compressed \b storage \b only, and it will trigger an assertion otherwise.
+      *
+      * \sa valuePtr(), isCompressed() */
+    const Map<const Array<Scalar,Dynamic,1> > coeffs() const { eigen_assert(isCompressed()); return Array<Scalar,Dynamic,1>::Map(valuePtr(),nonZeros()); }
+
+    /** \returns a read-write view of the stored coefficients as a 1D array expression
+      *
+      * \warning this method is for \b compressed \b storage \b only, and it will trigger an assertion otherwise.
+      *
+      * Here is an example:
+      * \include SparseMatrix_coeffs.cpp
+      * and the output is:
+      * \include SparseMatrix_coeffs.out
+      *
+      * \sa valuePtr(), isCompressed() */
+    Map<Array<Scalar,Dynamic,1> > coeffs() { eigen_assert(isCompressed()); return Array<Scalar,Dynamic,1>::Map(valuePtr(),nonZeros()); }
+
+  protected:
+    /** Default constructor. Do nothing. */
+    SparseCompressedBase() {}
+  private:
+    template<typename OtherDerived> explicit SparseCompressedBase(const SparseCompressedBase<OtherDerived>&);
+};
+
+template<typename Derived>
+class SparseCompressedBase<Derived>::InnerIterator
+{
+  public:
+    InnerIterator()
+      : m_values(0), m_indices(0), m_outer(0), m_id(0), m_end(0)
+    {}
+
+    InnerIterator(const InnerIterator& other)
+      : m_values(other.m_values), m_indices(other.m_indices), m_outer(other.m_outer), m_id(other.m_id), m_end(other.m_end)
+    {}
+
+    InnerIterator& operator=(const InnerIterator& other)
+    {
+      m_values = other.m_values;
+      m_indices = other.m_indices;
+      const_cast<OuterType&>(m_outer).setValue(other.m_outer.value());
+      m_id = other.m_id;
+      m_end = other.m_end;
+      return *this;
+    }
+
+    InnerIterator(const SparseCompressedBase& mat, Index outer)
+      : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer)
+    {
+      if(Derived::IsVectorAtCompileTime && mat.outerIndexPtr()==0)
+      {
+        m_id = 0;
+        m_end = mat.nonZeros();
+      }
+      else
+      {
+        m_id = mat.outerIndexPtr()[outer];
+        if(mat.isCompressed())
+          m_end = mat.outerIndexPtr()[outer+1];
+        else
+          m_end = m_id + mat.innerNonZeroPtr()[outer];
+      }
+    }
+
+    explicit InnerIterator(const SparseCompressedBase& mat)
+      : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(0), m_id(0), m_end(mat.nonZeros())
+    {
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
+    }
+
+    explicit InnerIterator(const internal::CompressedStorage<Scalar,StorageIndex>& data)
+      : m_values(data.valuePtr()), m_indices(data.indexPtr()), m_outer(0), m_id(0), m_end(data.size())
+    {
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
+    }
+
+    inline InnerIterator& operator++() { m_id++; return *this; }
+
+    inline const Scalar& value() const { return m_values[m_id]; }
+    inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id]); }
+
+    inline StorageIndex index() const { return m_indices[m_id]; }
+    inline Index outer() const { return m_outer.value(); }
+    inline Index row() const { return IsRowMajor ? m_outer.value() : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer.value(); }
+
+    inline operator bool() const { return (m_id < m_end); }
+
+  protected:
+    const Scalar* m_values;
+    const StorageIndex* m_indices;
+    typedef internal::variable_if_dynamic<Index,Derived::IsVectorAtCompileTime?0:Dynamic> OuterType;
+    const OuterType m_outer;
+    Index m_id;
+    Index m_end;
+  private:
+    // If you get here, then you're not using the right InnerIterator type, e.g.:
+    //   SparseMatrix<double,RowMajor> A;
+    //   SparseMatrix<double>::InnerIterator it(A,0);
+    template<typename T> InnerIterator(const SparseMatrixBase<T>&, Index outer);
+};
+
+template<typename Derived>
+class SparseCompressedBase<Derived>::ReverseInnerIterator
+{
+  public:
+    ReverseInnerIterator(const SparseCompressedBase& mat, Index outer)
+      : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer)
+    {
+      if(Derived::IsVectorAtCompileTime && mat.outerIndexPtr()==0)
+      {
+        m_start = 0;
+        m_id = mat.nonZeros();
+      }
+      else
+      {
+        m_start = mat.outerIndexPtr()[outer];
+        if(mat.isCompressed())
+          m_id = mat.outerIndexPtr()[outer+1];
+        else
+          m_id = m_start + mat.innerNonZeroPtr()[outer];
+      }
+    }
+
+    explicit ReverseInnerIterator(const SparseCompressedBase& mat)
+      : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(0), m_start(0), m_id(mat.nonZeros())
+    {
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
+    }
+
+    explicit ReverseInnerIterator(const internal::CompressedStorage<Scalar,StorageIndex>& data)
+      : m_values(data.valuePtr()), m_indices(data.indexPtr()), m_outer(0), m_start(0), m_id(data.size())
+    {
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
+    }
+
+    inline ReverseInnerIterator& operator--() { --m_id; return *this; }
+
+    inline const Scalar& value() const { return m_values[m_id-1]; }
+    inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id-1]); }
+
+    inline StorageIndex index() const { return m_indices[m_id-1]; }
+    inline Index outer() const { return m_outer.value(); }
+    inline Index row() const { return IsRowMajor ? m_outer.value() : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer.value(); }
+
+    inline operator bool() const { return (m_id > m_start); }
+
+  protected:
+    const Scalar* m_values;
+    const StorageIndex* m_indices;
+    typedef internal::variable_if_dynamic<Index,Derived::IsVectorAtCompileTime?0:Dynamic> OuterType;
+    const OuterType m_outer;
+    Index m_start;
+    Index m_id;
+};
+
+namespace internal {
+
+template<typename Derived>
+struct evaluator<SparseCompressedBase<Derived> >
+  : evaluator_base<Derived>
+{
+  typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::InnerIterator InnerIterator;
+  
+  enum {
+    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    Flags = Derived::Flags
+  };
+  
+  evaluator() : m_matrix(0), m_zero(0)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  explicit evaluator(const Derived &mat) : m_matrix(&mat), m_zero(0)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  inline Index nonZerosEstimate() const {
+    return m_matrix->nonZeros();
+  }
+  
+  operator Derived&() { return m_matrix->const_cast_derived(); }
+  operator const Derived&() const { return *m_matrix; }
+  
+  typedef typename DenseCoeffsBase<Derived,ReadOnlyAccessors>::CoeffReturnType CoeffReturnType;
+  const Scalar& coeff(Index row, Index col) const
+  {
+    Index p = find(row,col);
+
+    if(p==Dynamic)
+      return m_zero;
+    else
+      return m_matrix->const_cast_derived().valuePtr()[p];
+  }
+
+  Scalar& coeffRef(Index row, Index col)
+  {
+    Index p = find(row,col);
+    eigen_assert(p!=Dynamic && "written coefficient does not exist");
+    return m_matrix->const_cast_derived().valuePtr()[p];
+  }
+
+protected:
+
+  Index find(Index row, Index col) const
+  {
+    eigen_internal_assert(row>=0 && row<m_matrix->rows() && col>=0 && col<m_matrix->cols());
+
+    const Index outer = Derived::IsRowMajor ? row : col;
+    const Index inner = Derived::IsRowMajor ? col : row;
+
+    Index start = m_matrix->outerIndexPtr()[outer];
+    Index end = m_matrix->isCompressed() ? m_matrix->outerIndexPtr()[outer+1] : m_matrix->outerIndexPtr()[outer] + m_matrix->innerNonZeroPtr()[outer];
+    eigen_assert(end>=start && "you are using a non finalized sparse matrix or written coefficient does not exist");
+    const Index p = std::lower_bound(m_matrix->innerIndexPtr()+start, m_matrix->innerIndexPtr()+end,inner) - m_matrix->innerIndexPtr();
+
+    return ((p<end) && (m_matrix->innerIndexPtr()[p]==inner)) ? p : Dynamic;
+  }
+
+  const Derived *m_matrix;
+  const Scalar m_zero;
+};
+
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_COMPRESSED_BASE_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseCwiseBinaryOp.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseCwiseBinaryOp.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseCwiseBinaryOp.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -26,93 +26,61 @@
 //                         generic      dense
 //  3 - sparse op sparse   product      sparse
 //                         generic      sparse
 //  4 - dense op dense     product      dense
 //                         generic      dense
-
-namespace internal {
-
-template<> struct promote_storage_type<Dense,Sparse>
-{ typedef Sparse ret; };
-
-template<> struct promote_storage_type<Sparse,Dense>
-{ typedef Sparse ret; };
-
-template<typename BinaryOp, typename Lhs, typename Rhs, typename Derived,
-  typename _LhsStorageMode = typename traits<Lhs>::StorageKind,
-  typename _RhsStorageMode = typename traits<Rhs>::StorageKind>
-class sparse_cwise_binary_op_inner_iterator_selector;
-
-} // end namespace internal
+//
+// TODO to ease compiler job, we could specialize product/quotient with a scalar
+//      and fallback to cwise-unary evaluator using bind1st_op and bind2nd_op.
 
 template<typename BinaryOp, typename Lhs, typename Rhs>
 class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Sparse>
   : public SparseMatrixBase<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
 {
   public:
-    class InnerIterator;
-    class ReverseInnerIterator;
     typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived;
+    typedef SparseMatrixBase<Derived> Base;
     EIGEN_SPARSE_PUBLIC_INTERFACE(Derived)
     CwiseBinaryOpImpl()
     {
-      typedef typename internal::traits<Lhs>::StorageKind LhsStorageKind;
-      typedef typename internal::traits<Rhs>::StorageKind RhsStorageKind;
       EIGEN_STATIC_ASSERT((
-                (!internal::is_same<LhsStorageKind,RhsStorageKind>::value)
-            ||  ((Lhs::Flags&RowMajorBit) == (Rhs::Flags&RowMajorBit))),
+                (!internal::is_same<typename internal::traits<Lhs>::StorageKind,
+                                    typename internal::traits<Rhs>::StorageKind>::value)
+            ||  ((internal::evaluator<Lhs>::Flags&RowMajorBit) == (internal::evaluator<Rhs>::Flags&RowMajorBit))),
             THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH);
     }
 };
 
-template<typename BinaryOp, typename Lhs, typename Rhs>
-class CwiseBinaryOpImpl<BinaryOp,Lhs,Rhs,Sparse>::InnerIterator
-  : public internal::sparse_cwise_binary_op_inner_iterator_selector<BinaryOp,Lhs,Rhs,typename CwiseBinaryOpImpl<BinaryOp,Lhs,Rhs,Sparse>::InnerIterator>
-{
-  public:
-    typedef typename Lhs::Index Index;
-    typedef internal::sparse_cwise_binary_op_inner_iterator_selector<
-      BinaryOp,Lhs,Rhs, InnerIterator> Base;
-
-    // NOTE: we have to prefix Index by "typename Lhs::" to avoid an ICE with VC11
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOpImpl& binOp, typename Lhs::Index outer)
-      : Base(binOp.derived(),outer)
-    {}
-};
-
-/***************************************************************************
-* Implementation of inner-iterators
-***************************************************************************/
-
-// template<typename T> struct internal::func_is_conjunction { enum { ret = false }; };
-// template<typename T> struct internal::func_is_conjunction<internal::scalar_product_op<T> > { enum { ret = true }; };
-
-// TODO generalize the internal::scalar_product_op specialization to all conjunctions if any !
-
 namespace internal {
 
-// sparse - sparse  (generic)
-template<typename BinaryOp, typename Lhs, typename Rhs, typename Derived>
-class sparse_cwise_binary_op_inner_iterator_selector<BinaryOp, Lhs, Rhs, Derived, Sparse, Sparse>
-{
-    typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> CwiseBinaryXpr;
-    typedef typename traits<CwiseBinaryXpr>::Scalar Scalar;
-    typedef typename traits<CwiseBinaryXpr>::_LhsNested _LhsNested;
-    typedef typename traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
-    typedef typename _LhsNested::InnerIterator LhsIterator;
-    typedef typename _RhsNested::InnerIterator RhsIterator;
-    typedef typename Lhs::Index Index;
-
+  
+// Generic "sparse OP sparse"
+template<typename XprType> struct binary_sparse_evaluator;
+
+template<typename BinaryOp, typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>, IteratorBased, IteratorBased>
+  : evaluator_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
+protected:
+  typedef typename evaluator<Lhs>::InnerIterator  LhsIterator;
+  typedef typename evaluator<Rhs>::InnerIterator  RhsIterator;
+  typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> XprType;
+  typedef typename traits<XprType>::Scalar Scalar;
+  typedef typename XprType::StorageIndex StorageIndex;
+public:
+
+  class InnerIterator
+  {
   public:
-
-    EIGEN_STRONG_INLINE sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer)
-      : m_lhsIter(xpr.lhs(),outer), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor())
+    
+    EIGEN_STRONG_INLINE InnerIterator(const binary_evaluator& aEval, Index outer)
+      : m_lhsIter(aEval.m_lhsImpl,outer), m_rhsIter(aEval.m_rhsImpl,outer), m_functor(aEval.m_functor)
     {
       this->operator++();
     }
 
-    EIGEN_STRONG_INLINE Derived& operator++()
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
     {
       if (m_lhsIter && m_rhsIter && (m_lhsIter.index() == m_rhsIter.index()))
       {
         m_id = m_lhsIter.index();
         m_value = m_functor(m_lhsIter.value(), m_rhsIter.value());
@@ -134,16 +102,17 @@
       else
       {
         m_value = 0; // this is to avoid a compilation warning
         m_id = -1;
       }
-      return *static_cast<Derived*>(this);
+      return *this;
     }
 
     EIGEN_STRONG_INLINE Scalar value() const { return m_value; }
 
-    EIGEN_STRONG_INLINE Index index() const { return m_id; }
+    EIGEN_STRONG_INLINE StorageIndex index() const { return m_id; }
+    EIGEN_STRONG_INLINE Index outer() const { return m_lhsIter.outer(); }
     EIGEN_STRONG_INLINE Index row() const { return Lhs::IsRowMajor ? m_lhsIter.row() : index(); }
     EIGEN_STRONG_INLINE Index col() const { return Lhs::IsRowMajor ? index() : m_lhsIter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_id>=0; }
 
@@ -150,29 +119,307 @@
   protected:
     LhsIterator m_lhsIter;
     RhsIterator m_rhsIter;
     const BinaryOp& m_functor;
     Scalar m_value;
-    Index m_id;
+    StorageIndex m_id;
+  };
+  
+  
+  enum {
+    CoeffReadCost = evaluator<Lhs>::CoeffReadCost + evaluator<Rhs>::CoeffReadCost + functor_traits<BinaryOp>::Cost,
+    Flags = XprType::Flags
+  };
+  
+  explicit binary_evaluator(const XprType& xpr)
+    : m_functor(xpr.functor()),
+      m_lhsImpl(xpr.lhs()), 
+      m_rhsImpl(xpr.rhs())  
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<BinaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  inline Index nonZerosEstimate() const {
+    return m_lhsImpl.nonZerosEstimate() + m_rhsImpl.nonZerosEstimate();
+  }
+
+protected:
+  const BinaryOp m_functor;
+  evaluator<Lhs> m_lhsImpl;
+  evaluator<Rhs> m_rhsImpl;
+};
+
+// dense op sparse
+template<typename BinaryOp, typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>, IndexBased, IteratorBased>
+  : evaluator_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
+protected:
+  typedef typename evaluator<Rhs>::InnerIterator  RhsIterator;
+  typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> XprType;
+  typedef typename traits<XprType>::Scalar Scalar;
+  typedef typename XprType::StorageIndex StorageIndex;
+public:
+
+  class InnerIterator
+  {
+    enum { IsRowMajor = (int(Rhs::Flags)&RowMajorBit)==RowMajorBit };
+  public:
+
+    EIGEN_STRONG_INLINE InnerIterator(const binary_evaluator& aEval, Index outer)
+      : m_lhsEval(aEval.m_lhsImpl), m_rhsIter(aEval.m_rhsImpl,outer), m_functor(aEval.m_functor), m_value(0), m_id(-1), m_innerSize(aEval.m_expr.rhs().innerSize())
+    {
+      this->operator++();
+    }
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    {
+      ++m_id;
+      if(m_id<m_innerSize)
+      {
+        Scalar lhsVal = m_lhsEval.coeff(IsRowMajor?m_rhsIter.outer():m_id,
+                                        IsRowMajor?m_id:m_rhsIter.outer());
+        if(m_rhsIter && m_rhsIter.index()==m_id)
+        {
+          m_value = m_functor(lhsVal, m_rhsIter.value());
+          ++m_rhsIter;
+        }
+        else
+          m_value = m_functor(lhsVal, Scalar(0));
+      }
+
+      return *this;
+    }
+
+    EIGEN_STRONG_INLINE Scalar value() const { eigen_internal_assert(m_id<m_innerSize); return m_value; }
+
+    EIGEN_STRONG_INLINE StorageIndex index() const { return m_id; }
+    EIGEN_STRONG_INLINE Index outer() const { return m_rhsIter.outer(); }
+    EIGEN_STRONG_INLINE Index row() const { return IsRowMajor ? m_rhsIter.outer() : m_id; }
+    EIGEN_STRONG_INLINE Index col() const { return IsRowMajor ? m_id : m_rhsIter.outer(); }
+
+    EIGEN_STRONG_INLINE operator bool() const { return m_id<m_innerSize; }
+
+  protected:
+    const evaluator<Lhs> &m_lhsEval;
+    RhsIterator m_rhsIter;
+    const BinaryOp& m_functor;
+    Scalar m_value;
+    StorageIndex m_id;
+    StorageIndex m_innerSize;
+  };
+
+
+  enum {
+    CoeffReadCost = evaluator<Lhs>::CoeffReadCost + evaluator<Rhs>::CoeffReadCost + functor_traits<BinaryOp>::Cost,
+    // Expose storage order of the sparse expression
+    Flags = (XprType::Flags & ~RowMajorBit) | (int(Rhs::Flags)&RowMajorBit)
+  };
+
+  explicit binary_evaluator(const XprType& xpr)
+    : m_functor(xpr.functor()),
+      m_lhsImpl(xpr.lhs()),
+      m_rhsImpl(xpr.rhs()),
+      m_expr(xpr)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<BinaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  inline Index nonZerosEstimate() const {
+    return m_expr.size();
+  }
+
+protected:
+  const BinaryOp m_functor;
+  evaluator<Lhs> m_lhsImpl;
+  evaluator<Rhs> m_rhsImpl;
+  const XprType &m_expr;
+};
+
+// sparse op dense
+template<typename BinaryOp, typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>, IteratorBased, IndexBased>
+  : evaluator_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
+protected:
+  typedef typename evaluator<Lhs>::InnerIterator  LhsIterator;
+  typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> XprType;
+  typedef typename traits<XprType>::Scalar Scalar;
+  typedef typename XprType::StorageIndex StorageIndex;
+public:
+
+  class InnerIterator
+  {
+    enum { IsRowMajor = (int(Lhs::Flags)&RowMajorBit)==RowMajorBit };
+  public:
+
+    EIGEN_STRONG_INLINE InnerIterator(const binary_evaluator& aEval, Index outer)
+      : m_lhsIter(aEval.m_lhsImpl,outer), m_rhsEval(aEval.m_rhsImpl), m_functor(aEval.m_functor), m_value(0), m_id(-1), m_innerSize(aEval.m_expr.lhs().innerSize())
+    {
+      this->operator++();
+    }
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    {
+      ++m_id;
+      if(m_id<m_innerSize)
+      {
+        Scalar rhsVal = m_rhsEval.coeff(IsRowMajor?m_lhsIter.outer():m_id,
+                                        IsRowMajor?m_id:m_lhsIter.outer());
+        if(m_lhsIter && m_lhsIter.index()==m_id)
+        {
+          m_value = m_functor(m_lhsIter.value(), rhsVal);
+          ++m_lhsIter;
+        }
+        else
+          m_value = m_functor(Scalar(0),rhsVal);
+      }
+
+      return *this;
+    }
+
+    EIGEN_STRONG_INLINE Scalar value() const { eigen_internal_assert(m_id<m_innerSize); return m_value; }
+
+    EIGEN_STRONG_INLINE StorageIndex index() const { return m_id; }
+    EIGEN_STRONG_INLINE Index outer() const { return m_lhsIter.outer(); }
+    EIGEN_STRONG_INLINE Index row() const { return IsRowMajor ? m_lhsIter.outer() : m_id; }
+    EIGEN_STRONG_INLINE Index col() const { return IsRowMajor ? m_id : m_lhsIter.outer(); }
+
+    EIGEN_STRONG_INLINE operator bool() const { return m_id<m_innerSize; }
+
+  protected:
+    LhsIterator m_lhsIter;
+    const evaluator<Rhs> &m_rhsEval;
+    const BinaryOp& m_functor;
+    Scalar m_value;
+    StorageIndex m_id;
+    StorageIndex m_innerSize;
+  };
+
+
+  enum {
+    CoeffReadCost = evaluator<Lhs>::CoeffReadCost + evaluator<Rhs>::CoeffReadCost + functor_traits<BinaryOp>::Cost,
+    // Expose storage order of the sparse expression
+    Flags = (XprType::Flags & ~RowMajorBit) | (int(Lhs::Flags)&RowMajorBit)
+  };
+
+  explicit binary_evaluator(const XprType& xpr)
+    : m_functor(xpr.functor()),
+      m_lhsImpl(xpr.lhs()),
+      m_rhsImpl(xpr.rhs()),
+      m_expr(xpr)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<BinaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+
+  inline Index nonZerosEstimate() const {
+    return m_expr.size();
+  }
+
+protected:
+  const BinaryOp m_functor;
+  evaluator<Lhs> m_lhsImpl;
+  evaluator<Rhs> m_rhsImpl;
+  const XprType &m_expr;
+};
+
+template<typename T,
+         typename LhsKind   = typename evaluator_traits<typename T::Lhs>::Kind,
+         typename RhsKind   = typename evaluator_traits<typename T::Rhs>::Kind,
+         typename LhsScalar = typename traits<typename T::Lhs>::Scalar,
+         typename RhsScalar = typename traits<typename T::Rhs>::Scalar> struct sparse_conjunction_evaluator;
+
+// "sparse .* sparse"
+template<typename T1, typename T2, typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs>, IteratorBased, IteratorBased>
+  : sparse_conjunction_evaluator<CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs> XprType;
+  typedef sparse_conjunction_evaluator<XprType> Base;
+  explicit binary_evaluator(const XprType& xpr) : Base(xpr) {}
+};
+// "dense .* sparse"
+template<typename T1, typename T2, typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs>, IndexBased, IteratorBased>
+  : sparse_conjunction_evaluator<CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs> XprType;
+  typedef sparse_conjunction_evaluator<XprType> Base;
+  explicit binary_evaluator(const XprType& xpr) : Base(xpr) {}
+};
+// "sparse .* dense"
+template<typename T1, typename T2, typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs>, IteratorBased, IndexBased>
+  : sparse_conjunction_evaluator<CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<scalar_product_op<T1,T2>, Lhs, Rhs> XprType;
+  typedef sparse_conjunction_evaluator<XprType> Base;
+  explicit binary_evaluator(const XprType& xpr) : Base(xpr) {}
+};
+
+// "sparse ./ dense"
+template<typename T1, typename T2, typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<scalar_quotient_op<T1,T2>, Lhs, Rhs>, IteratorBased, IndexBased>
+  : sparse_conjunction_evaluator<CwiseBinaryOp<scalar_quotient_op<T1,T2>, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<scalar_quotient_op<T1,T2>, Lhs, Rhs> XprType;
+  typedef sparse_conjunction_evaluator<XprType> Base;
+  explicit binary_evaluator(const XprType& xpr) : Base(xpr) {}
+};
+
+// "sparse && sparse"
+template<typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs>, IteratorBased, IteratorBased>
+  : sparse_conjunction_evaluator<CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs> XprType;
+  typedef sparse_conjunction_evaluator<XprType> Base;
+  explicit binary_evaluator(const XprType& xpr) : Base(xpr) {}
+};
+// "dense && sparse"
+template<typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs>, IndexBased, IteratorBased>
+  : sparse_conjunction_evaluator<CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs> XprType;
+  typedef sparse_conjunction_evaluator<XprType> Base;
+  explicit binary_evaluator(const XprType& xpr) : Base(xpr) {}
+};
+// "sparse && dense"
+template<typename Lhs, typename Rhs>
+struct binary_evaluator<CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs>, IteratorBased, IndexBased>
+  : sparse_conjunction_evaluator<CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs> >
+{
+  typedef CwiseBinaryOp<scalar_boolean_and_op, Lhs, Rhs> XprType;
+  typedef sparse_conjunction_evaluator<XprType> Base;
+  explicit binary_evaluator(const XprType& xpr) : Base(xpr) {}
 };
 
-// sparse - sparse  (product)
-template<typename T, typename Lhs, typename Rhs, typename Derived>
-class sparse_cwise_binary_op_inner_iterator_selector<scalar_product_op<T>, Lhs, Rhs, Derived, Sparse, Sparse>
-{
-    typedef scalar_product_op<T> BinaryFunc;
-    typedef CwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr;
-    typedef typename CwiseBinaryXpr::Scalar Scalar;
-    typedef typename traits<CwiseBinaryXpr>::_LhsNested _LhsNested;
-    typedef typename _LhsNested::InnerIterator LhsIterator;
-    typedef typename traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
-    typedef typename _RhsNested::InnerIterator RhsIterator;
-    typedef typename Lhs::Index Index;
+// "sparse ^ sparse"
+template<typename XprType>
+struct sparse_conjunction_evaluator<XprType, IteratorBased, IteratorBased>
+  : evaluator_base<XprType>
+{
+protected:
+  typedef typename XprType::Functor BinaryOp;
+  typedef typename XprType::Lhs LhsArg;
+  typedef typename XprType::Rhs RhsArg;
+  typedef typename evaluator<LhsArg>::InnerIterator  LhsIterator;
+  typedef typename evaluator<RhsArg>::InnerIterator  RhsIterator;
+  typedef typename XprType::StorageIndex StorageIndex;
+  typedef typename traits<XprType>::Scalar Scalar;
+public:
+
+  class InnerIterator
+  {
   public:
-
-    EIGEN_STRONG_INLINE sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer)
-      : m_lhsIter(xpr.lhs(),outer), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor())
+    
+    EIGEN_STRONG_INLINE InnerIterator(const sparse_conjunction_evaluator& aEval, Index outer)
+      : m_lhsIter(aEval.m_lhsImpl,outer), m_rhsIter(aEval.m_rhsImpl,outer), m_functor(aEval.m_functor)
     {
       while (m_lhsIter && m_rhsIter && (m_lhsIter.index() != m_rhsIter.index()))
       {
         if (m_lhsIter.index() < m_rhsIter.index())
           ++m_lhsIter;
@@ -179,11 +426,11 @@
         else
           ++m_rhsIter;
       }
     }
 
-    EIGEN_STRONG_INLINE Derived& operator++()
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
     {
       ++m_lhsIter;
       ++m_rhsIter;
       while (m_lhsIter && m_rhsIter && (m_lhsIter.index() != m_rhsIter.index()))
       {
@@ -190,113 +437,223 @@
         if (m_lhsIter.index() < m_rhsIter.index())
           ++m_lhsIter;
         else
           ++m_rhsIter;
       }
-      return *static_cast<Derived*>(this);
+      return *this;
     }
-
+    
     EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_lhsIter.value(), m_rhsIter.value()); }
 
-    EIGEN_STRONG_INLINE Index index() const { return m_lhsIter.index(); }
+    EIGEN_STRONG_INLINE StorageIndex index() const { return m_lhsIter.index(); }
+    EIGEN_STRONG_INLINE Index outer() const { return m_lhsIter.outer(); }
     EIGEN_STRONG_INLINE Index row() const { return m_lhsIter.row(); }
     EIGEN_STRONG_INLINE Index col() const { return m_lhsIter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return (m_lhsIter && m_rhsIter); }
 
   protected:
     LhsIterator m_lhsIter;
     RhsIterator m_rhsIter;
-    const BinaryFunc& m_functor;
-};
-
-// sparse - dense  (product)
-template<typename T, typename Lhs, typename Rhs, typename Derived>
-class sparse_cwise_binary_op_inner_iterator_selector<scalar_product_op<T>, Lhs, Rhs, Derived, Sparse, Dense>
-{
-    typedef scalar_product_op<T> BinaryFunc;
-    typedef CwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr;
-    typedef typename CwiseBinaryXpr::Scalar Scalar;
-    typedef typename traits<CwiseBinaryXpr>::_LhsNested _LhsNested;
-    typedef typename traits<CwiseBinaryXpr>::RhsNested RhsNested;
-    typedef typename _LhsNested::InnerIterator LhsIterator;
-    typedef typename Lhs::Index Index;
-    enum { IsRowMajor = (int(Lhs::Flags)&RowMajorBit)==RowMajorBit };
-  public:
-
-    EIGEN_STRONG_INLINE sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer)
-      : m_rhs(xpr.rhs()), m_lhsIter(xpr.lhs(),outer), m_functor(xpr.functor()), m_outer(outer)
-    {}
-
-    EIGEN_STRONG_INLINE Derived& operator++()
-    {
-      ++m_lhsIter;
-      return *static_cast<Derived*>(this);
-    }
-
-    EIGEN_STRONG_INLINE Scalar value() const
-    { return m_functor(m_lhsIter.value(),
-                       m_rhs.coeff(IsRowMajor?m_outer:m_lhsIter.index(),IsRowMajor?m_lhsIter.index():m_outer)); }
-
-    EIGEN_STRONG_INLINE Index index() const { return m_lhsIter.index(); }
-    EIGEN_STRONG_INLINE Index row() const { return m_lhsIter.row(); }
-    EIGEN_STRONG_INLINE Index col() const { return m_lhsIter.col(); }
-
-    EIGEN_STRONG_INLINE operator bool() const { return m_lhsIter; }
-
-  protected:
-    RhsNested m_rhs;
-    LhsIterator m_lhsIter;
-    const BinaryFunc m_functor;
-    const Index m_outer;
-};
-
-// sparse - dense  (product)
-template<typename T, typename Lhs, typename Rhs, typename Derived>
-class sparse_cwise_binary_op_inner_iterator_selector<scalar_product_op<T>, Lhs, Rhs, Derived, Dense, Sparse>
-{
-    typedef scalar_product_op<T> BinaryFunc;
-    typedef CwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr;
-    typedef typename CwiseBinaryXpr::Scalar Scalar;
-    typedef typename traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
-    typedef typename _RhsNested::InnerIterator RhsIterator;
-    typedef typename Lhs::Index Index;
-
-    enum { IsRowMajor = (int(Rhs::Flags)&RowMajorBit)==RowMajorBit };
-  public:
-
-    EIGEN_STRONG_INLINE sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer)
-      : m_xpr(xpr), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor()), m_outer(outer)
-    {}
-
-    EIGEN_STRONG_INLINE Derived& operator++()
-    {
-      ++m_rhsIter;
-      return *static_cast<Derived*>(this);
-    }
-
-    EIGEN_STRONG_INLINE Scalar value() const
-    { return m_functor(m_xpr.lhs().coeff(IsRowMajor?m_outer:m_rhsIter.index(),IsRowMajor?m_rhsIter.index():m_outer), m_rhsIter.value()); }
-
-    EIGEN_STRONG_INLINE Index index() const { return m_rhsIter.index(); }
+    const BinaryOp& m_functor;
+  };
+  
+  
+  enum {
+    CoeffReadCost = evaluator<LhsArg>::CoeffReadCost + evaluator<RhsArg>::CoeffReadCost + functor_traits<BinaryOp>::Cost,
+    Flags = XprType::Flags
+  };
+  
+  explicit sparse_conjunction_evaluator(const XprType& xpr)
+    : m_functor(xpr.functor()),
+      m_lhsImpl(xpr.lhs()), 
+      m_rhsImpl(xpr.rhs())  
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<BinaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  inline Index nonZerosEstimate() const {
+    return (std::min)(m_lhsImpl.nonZerosEstimate(), m_rhsImpl.nonZerosEstimate());
+  }
+
+protected:
+  const BinaryOp m_functor;
+  evaluator<LhsArg> m_lhsImpl;
+  evaluator<RhsArg> m_rhsImpl;
+};
+
+// "dense ^ sparse"
+template<typename XprType>
+struct sparse_conjunction_evaluator<XprType, IndexBased, IteratorBased>
+  : evaluator_base<XprType>
+{
+protected:
+  typedef typename XprType::Functor BinaryOp;
+  typedef typename XprType::Lhs LhsArg;
+  typedef typename XprType::Rhs RhsArg;
+  typedef evaluator<LhsArg> LhsEvaluator;
+  typedef typename evaluator<RhsArg>::InnerIterator  RhsIterator;
+  typedef typename XprType::StorageIndex StorageIndex;
+  typedef typename traits<XprType>::Scalar Scalar;
+public:
+
+  class InnerIterator
+  {
+    enum { IsRowMajor = (int(RhsArg::Flags)&RowMajorBit)==RowMajorBit };
+
+  public:
+    
+    EIGEN_STRONG_INLINE InnerIterator(const sparse_conjunction_evaluator& aEval, Index outer)
+      : m_lhsEval(aEval.m_lhsImpl), m_rhsIter(aEval.m_rhsImpl,outer), m_functor(aEval.m_functor), m_outer(outer)
+    {}
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    {
+      ++m_rhsIter;
+      return *this;
+    }
+
+    EIGEN_STRONG_INLINE Scalar value() const
+    { return m_functor(m_lhsEval.coeff(IsRowMajor?m_outer:m_rhsIter.index(),IsRowMajor?m_rhsIter.index():m_outer), m_rhsIter.value()); }
+
+    EIGEN_STRONG_INLINE StorageIndex index() const { return m_rhsIter.index(); }
+    EIGEN_STRONG_INLINE Index outer() const { return m_rhsIter.outer(); }
     EIGEN_STRONG_INLINE Index row() const { return m_rhsIter.row(); }
     EIGEN_STRONG_INLINE Index col() const { return m_rhsIter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_rhsIter; }
-
+    
   protected:
-    const CwiseBinaryXpr& m_xpr;
+    const LhsEvaluator &m_lhsEval;
     RhsIterator m_rhsIter;
-    const BinaryFunc& m_functor;
+    const BinaryOp& m_functor;
+    const Index m_outer;
+  };
+  
+  
+  enum {
+    CoeffReadCost = evaluator<LhsArg>::CoeffReadCost + evaluator<RhsArg>::CoeffReadCost + functor_traits<BinaryOp>::Cost,
+    // Expose storage order of the sparse expression
+    Flags = (XprType::Flags & ~RowMajorBit) | (int(RhsArg::Flags)&RowMajorBit)
+  };
+  
+  explicit sparse_conjunction_evaluator(const XprType& xpr)
+    : m_functor(xpr.functor()),
+      m_lhsImpl(xpr.lhs()), 
+      m_rhsImpl(xpr.rhs())  
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<BinaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  inline Index nonZerosEstimate() const {
+    return m_rhsImpl.nonZerosEstimate();
+  }
+
+protected:
+  const BinaryOp m_functor;
+  evaluator<LhsArg> m_lhsImpl;
+  evaluator<RhsArg> m_rhsImpl;
+};
+
+// "sparse ^ dense"
+template<typename XprType>
+struct sparse_conjunction_evaluator<XprType, IteratorBased, IndexBased>
+  : evaluator_base<XprType>
+{
+protected:
+  typedef typename XprType::Functor BinaryOp;
+  typedef typename XprType::Lhs LhsArg;
+  typedef typename XprType::Rhs RhsArg;
+  typedef typename evaluator<LhsArg>::InnerIterator LhsIterator;
+  typedef evaluator<RhsArg> RhsEvaluator;
+  typedef typename XprType::StorageIndex StorageIndex;
+  typedef typename traits<XprType>::Scalar Scalar;
+public:
+
+  class InnerIterator
+  {
+    enum { IsRowMajor = (int(LhsArg::Flags)&RowMajorBit)==RowMajorBit };
+
+  public:
+    
+    EIGEN_STRONG_INLINE InnerIterator(const sparse_conjunction_evaluator& aEval, Index outer)
+      : m_lhsIter(aEval.m_lhsImpl,outer), m_rhsEval(aEval.m_rhsImpl), m_functor(aEval.m_functor), m_outer(outer)
+    {}
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    {
+      ++m_lhsIter;
+      return *this;
+    }
+
+    EIGEN_STRONG_INLINE Scalar value() const
+    { return m_functor(m_lhsIter.value(),
+                       m_rhsEval.coeff(IsRowMajor?m_outer:m_lhsIter.index(),IsRowMajor?m_lhsIter.index():m_outer)); }
+
+    EIGEN_STRONG_INLINE StorageIndex index() const { return m_lhsIter.index(); }
+    EIGEN_STRONG_INLINE Index outer() const { return m_lhsIter.outer(); }
+    EIGEN_STRONG_INLINE Index row() const { return m_lhsIter.row(); }
+    EIGEN_STRONG_INLINE Index col() const { return m_lhsIter.col(); }
+
+    EIGEN_STRONG_INLINE operator bool() const { return m_lhsIter; }
+    
+  protected:
+    LhsIterator m_lhsIter;
+    const evaluator<RhsArg> &m_rhsEval;
+    const BinaryOp& m_functor;
     const Index m_outer;
+  };
+  
+  
+  enum {
+    CoeffReadCost = evaluator<LhsArg>::CoeffReadCost + evaluator<RhsArg>::CoeffReadCost + functor_traits<BinaryOp>::Cost,
+    // Expose storage order of the sparse expression
+    Flags = (XprType::Flags & ~RowMajorBit) | (int(LhsArg::Flags)&RowMajorBit)
+  };
+  
+  explicit sparse_conjunction_evaluator(const XprType& xpr)
+    : m_functor(xpr.functor()),
+      m_lhsImpl(xpr.lhs()), 
+      m_rhsImpl(xpr.rhs())  
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<BinaryOp>::Cost);
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  inline Index nonZerosEstimate() const {
+    return m_lhsImpl.nonZerosEstimate();
+  }
+
+protected:
+  const BinaryOp m_functor;
+  evaluator<LhsArg> m_lhsImpl;
+  evaluator<RhsArg> m_rhsImpl;
 };
 
-} // end namespace internal
+}
 
 /***************************************************************************
 * Implementation of SparseMatrixBase and SparseCwise functions/operators
 ***************************************************************************/
+
+template<typename Derived>
+template<typename OtherDerived>
+Derived& SparseMatrixBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
+{
+  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
+  return derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+Derived& SparseMatrixBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
+{
+  call_assignment(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
+  return derived();
+}
 
 template<typename Derived>
 template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived &
 SparseMatrixBase<Derived>::operator-=(const SparseMatrixBase<OtherDerived> &other)
@@ -312,14 +669,58 @@
   return derived() = derived() + other.derived();
 }
 
 template<typename Derived>
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
+Derived& SparseMatrixBase<Derived>::operator+=(const DiagonalBase<OtherDerived>& other)
+{
+  call_assignment_no_alias(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
+  return derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+Derived& SparseMatrixBase<Derived>::operator-=(const DiagonalBase<OtherDerived>& other)
+{
+  call_assignment_no_alias(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
+  return derived();
+}
+    
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE const typename SparseMatrixBase<Derived>::template CwiseProductDenseReturnType<OtherDerived>::Type
 SparseMatrixBase<Derived>::cwiseProduct(const MatrixBase<OtherDerived> &other) const
 {
-  return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(derived(), other.derived());
+  return typename CwiseProductDenseReturnType<OtherDerived>::Type(derived(), other.derived());
+}
+
+template<typename DenseDerived, typename SparseDerived>
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_sum_op<typename DenseDerived::Scalar,typename SparseDerived::Scalar>, const DenseDerived, const SparseDerived>
+operator+(const MatrixBase<DenseDerived> &a, const SparseMatrixBase<SparseDerived> &b)
+{
+  return CwiseBinaryOp<internal::scalar_sum_op<typename DenseDerived::Scalar,typename SparseDerived::Scalar>, const DenseDerived, const SparseDerived>(a.derived(), b.derived());
+}
+
+template<typename SparseDerived, typename DenseDerived>
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_sum_op<typename SparseDerived::Scalar,typename DenseDerived::Scalar>, const SparseDerived, const DenseDerived>
+operator+(const SparseMatrixBase<SparseDerived> &a, const MatrixBase<DenseDerived> &b)
+{
+  return CwiseBinaryOp<internal::scalar_sum_op<typename SparseDerived::Scalar,typename DenseDerived::Scalar>, const SparseDerived, const DenseDerived>(a.derived(), b.derived());
+}
+
+template<typename DenseDerived, typename SparseDerived>
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_difference_op<typename DenseDerived::Scalar,typename SparseDerived::Scalar>, const DenseDerived, const SparseDerived>
+operator-(const MatrixBase<DenseDerived> &a, const SparseMatrixBase<SparseDerived> &b)
+{
+  return CwiseBinaryOp<internal::scalar_difference_op<typename DenseDerived::Scalar,typename SparseDerived::Scalar>, const DenseDerived, const SparseDerived>(a.derived(), b.derived());
+}
+
+template<typename SparseDerived, typename DenseDerived>
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_difference_op<typename SparseDerived::Scalar,typename DenseDerived::Scalar>, const SparseDerived, const DenseDerived>
+operator-(const SparseMatrixBase<SparseDerived> &a, const MatrixBase<DenseDerived> &b)
+{
+  return CwiseBinaryOp<internal::scalar_difference_op<typename SparseDerived::Scalar,typename DenseDerived::Scalar>, const SparseDerived, const DenseDerived>(a.derived(), b.derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSE_CWISE_BINARY_OP_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseCwiseUnaryOp.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseCwiseUnaryOp.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseCwiseUnaryOp.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -10,154 +10,139 @@
 #ifndef EIGEN_SPARSE_CWISE_UNARY_OP_H
 #define EIGEN_SPARSE_CWISE_UNARY_OP_H
 
 namespace Eigen { 
 
-template<typename UnaryOp, typename MatrixType>
-class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>
-  : public SparseMatrixBase<CwiseUnaryOp<UnaryOp, MatrixType> >
-{
-  public:
-
-    class InnerIterator;
-    class ReverseInnerIterator;
-
-    typedef CwiseUnaryOp<UnaryOp, MatrixType> Derived;
-    EIGEN_SPARSE_PUBLIC_INTERFACE(Derived)
-
-  protected:
-    typedef typename internal::traits<Derived>::_XprTypeNested _MatrixTypeNested;
-    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
-    typedef typename _MatrixTypeNested::ReverseInnerIterator MatrixTypeReverseIterator;
-};
-
-template<typename UnaryOp, typename MatrixType>
-class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::InnerIterator
-    : public CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeIterator
-{
-    typedef typename CwiseUnaryOpImpl::Scalar Scalar;
-    typedef typename CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeIterator Base;
-  public:
-
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOpImpl& unaryOp, typename CwiseUnaryOpImpl::Index outer)
-      : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
-    {}
-
-    EIGEN_STRONG_INLINE InnerIterator& operator++()
-    { Base::operator++(); return *this; }
-
-    EIGEN_STRONG_INLINE typename CwiseUnaryOpImpl::Scalar value() const { return m_functor(Base::value()); }
-
-  protected:
-    const UnaryOp m_functor;
-  private:
-    typename CwiseUnaryOpImpl::Scalar& valueRef();
-};
-
-template<typename UnaryOp, typename MatrixType>
-class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::ReverseInnerIterator
-    : public CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeReverseIterator
-{
-    typedef typename CwiseUnaryOpImpl::Scalar Scalar;
-    typedef typename CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeReverseIterator Base;
-  public:
-
-    EIGEN_STRONG_INLINE ReverseInnerIterator(const CwiseUnaryOpImpl& unaryOp, typename CwiseUnaryOpImpl::Index outer)
-      : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
-    {}
-
-    EIGEN_STRONG_INLINE ReverseInnerIterator& operator--()
-    { Base::operator--(); return *this; }
-
-    EIGEN_STRONG_INLINE typename CwiseUnaryOpImpl::Scalar value() const { return m_functor(Base::value()); }
-
-  protected:
-    const UnaryOp m_functor;
-  private:
-    typename CwiseUnaryOpImpl::Scalar& valueRef();
-};
-
-template<typename ViewOp, typename MatrixType>
-class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>
-  : public SparseMatrixBase<CwiseUnaryView<ViewOp, MatrixType> >
-{
-  public:
-
-    class InnerIterator;
-    class ReverseInnerIterator;
-
-    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
-    EIGEN_SPARSE_PUBLIC_INTERFACE(Derived)
-
-  protected:
-    typedef typename internal::traits<Derived>::_MatrixTypeNested _MatrixTypeNested;
-    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
-    typedef typename _MatrixTypeNested::ReverseInnerIterator MatrixTypeReverseIterator;
-};
-
-template<typename ViewOp, typename MatrixType>
-class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::InnerIterator
-    : public CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeIterator
-{
-    typedef typename CwiseUnaryViewImpl::Scalar Scalar;
-    typedef typename CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeIterator Base;
-  public:
-
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryViewImpl& unaryOp, typename CwiseUnaryViewImpl::Index outer)
-      : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
-    {}
-
-    EIGEN_STRONG_INLINE InnerIterator& operator++()
-    { Base::operator++(); return *this; }
-
-    EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar value() const { return m_functor(Base::value()); }
-    EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar& valueRef() { return m_functor(Base::valueRef()); }
-
-  protected:
-    const ViewOp m_functor;
-};
-
-template<typename ViewOp, typename MatrixType>
-class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::ReverseInnerIterator
-    : public CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeReverseIterator
-{
-    typedef typename CwiseUnaryViewImpl::Scalar Scalar;
-    typedef typename CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeReverseIterator Base;
-  public:
-
-    EIGEN_STRONG_INLINE ReverseInnerIterator(const CwiseUnaryViewImpl& unaryOp, typename CwiseUnaryViewImpl::Index outer)
-      : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
-    {}
-
-    EIGEN_STRONG_INLINE ReverseInnerIterator& operator--()
-    { Base::operator--(); return *this; }
-
-    EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar value() const { return m_functor(Base::value()); }
-    EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar& valueRef() { return m_functor(Base::valueRef()); }
-
-  protected:
-    const ViewOp m_functor;
-};
-
-template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
-SparseMatrixBase<Derived>::operator*=(const Scalar& other)
-{
-  for (Index j=0; j<outerSize(); ++j)
-    for (typename Derived::InnerIterator i(derived(),j); i; ++i)
+namespace internal {
+  
+template<typename UnaryOp, typename ArgType>
+struct unary_evaluator<CwiseUnaryOp<UnaryOp,ArgType>, IteratorBased>
+  : public evaluator_base<CwiseUnaryOp<UnaryOp,ArgType> >
+{
+  public:
+    typedef CwiseUnaryOp<UnaryOp, ArgType> XprType;
+
+    class InnerIterator;
+    
+    enum {
+      CoeffReadCost = evaluator<ArgType>::CoeffReadCost + functor_traits<UnaryOp>::Cost,
+      Flags = XprType::Flags
+    };
+    
+    explicit unary_evaluator(const XprType& op) : m_functor(op.functor()), m_argImpl(op.nestedExpression())
+    {
+      EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<UnaryOp>::Cost);
+      EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+    }
+    
+    inline Index nonZerosEstimate() const {
+      return m_argImpl.nonZerosEstimate();
+    }
+
+  protected:
+    typedef typename evaluator<ArgType>::InnerIterator        EvalIterator;
+    
+    const UnaryOp m_functor;
+    evaluator<ArgType> m_argImpl;
+};
+
+template<typename UnaryOp, typename ArgType>
+class unary_evaluator<CwiseUnaryOp<UnaryOp,ArgType>, IteratorBased>::InnerIterator
+    : public unary_evaluator<CwiseUnaryOp<UnaryOp,ArgType>, IteratorBased>::EvalIterator
+{
+    typedef typename XprType::Scalar Scalar;
+    typedef typename unary_evaluator<CwiseUnaryOp<UnaryOp,ArgType>, IteratorBased>::EvalIterator Base;
+  public:
+
+    EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& unaryOp, Index outer)
+      : Base(unaryOp.m_argImpl,outer), m_functor(unaryOp.m_functor)
+    {}
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    { Base::operator++(); return *this; }
+
+    EIGEN_STRONG_INLINE Scalar value() const { return m_functor(Base::value()); }
+
+  protected:
+    const UnaryOp m_functor;
+  private:
+    Scalar& valueRef();
+};
+
+template<typename ViewOp, typename ArgType>
+struct unary_evaluator<CwiseUnaryView<ViewOp,ArgType>, IteratorBased>
+  : public evaluator_base<CwiseUnaryView<ViewOp,ArgType> >
+{
+  public:
+    typedef CwiseUnaryView<ViewOp, ArgType> XprType;
+
+    class InnerIterator;
+    
+    enum {
+      CoeffReadCost = evaluator<ArgType>::CoeffReadCost + functor_traits<ViewOp>::Cost,
+      Flags = XprType::Flags
+    };
+    
+    explicit unary_evaluator(const XprType& op) : m_functor(op.functor()), m_argImpl(op.nestedExpression())
+    {
+      EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<ViewOp>::Cost);
+      EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+    }
+
+  protected:
+    typedef typename evaluator<ArgType>::InnerIterator        EvalIterator;
+    
+    const ViewOp m_functor;
+    evaluator<ArgType> m_argImpl;
+};
+
+template<typename ViewOp, typename ArgType>
+class unary_evaluator<CwiseUnaryView<ViewOp,ArgType>, IteratorBased>::InnerIterator
+    : public unary_evaluator<CwiseUnaryView<ViewOp,ArgType>, IteratorBased>::EvalIterator
+{
+    typedef typename XprType::Scalar Scalar;
+    typedef typename unary_evaluator<CwiseUnaryView<ViewOp,ArgType>, IteratorBased>::EvalIterator Base;
+  public:
+
+    EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& unaryOp, Index outer)
+      : Base(unaryOp.m_argImpl,outer), m_functor(unaryOp.m_functor)
+    {}
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    { Base::operator++(); return *this; }
+
+    EIGEN_STRONG_INLINE Scalar value() const { return m_functor(Base::value()); }
+    EIGEN_STRONG_INLINE Scalar& valueRef() { return m_functor(Base::valueRef()); }
+
+  protected:
+    const ViewOp m_functor;
+};
+
+} // end namespace internal
+
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+SparseMatrixBase<Derived>::operator*=(const Scalar& other)
+{
+  typedef typename internal::evaluator<Derived>::InnerIterator EvalIterator;
+  internal::evaluator<Derived> thisEval(derived());
+  for (Index j=0; j<outerSize(); ++j)
+    for (EvalIterator i(thisEval,j); i; ++i)
       i.valueRef() *= other;
   return derived();
 }
 
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
 SparseMatrixBase<Derived>::operator/=(const Scalar& other)
 {
+  typedef typename internal::evaluator<Derived>::InnerIterator EvalIterator;
+  internal::evaluator<Derived> thisEval(derived());
   for (Index j=0; j<outerSize(); ++j)
-    for (typename Derived::InnerIterator i(derived(),j); i; ++i)
+    for (EvalIterator i(thisEval,j); i; ++i)
       i.valueRef() /= other;
   return derived();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSE_CWISE_UNARY_OP_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseDenseProduct.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseDenseProduct.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseDenseProduct.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -10,302 +10,311 @@
 #ifndef EIGEN_SPARSEDENSEPRODUCT_H
 #define EIGEN_SPARSEDENSEPRODUCT_H
 
 namespace Eigen { 
 
-template<typename Lhs, typename Rhs, int InnerSize> struct SparseDenseProductReturnType
-{
-  typedef SparseTimeDenseProduct<Lhs,Rhs> Type;
-};
-
-template<typename Lhs, typename Rhs> struct SparseDenseProductReturnType<Lhs,Rhs,1>
-{
-  typedef typename internal::conditional<
-    Lhs::IsRowMajor,
-    SparseDenseOuterProduct<Rhs,Lhs,true>,
-    SparseDenseOuterProduct<Lhs,Rhs,false> >::type Type;
-};
-
-template<typename Lhs, typename Rhs, int InnerSize> struct DenseSparseProductReturnType
-{
-  typedef DenseTimeSparseProduct<Lhs,Rhs> Type;
-};
-
-template<typename Lhs, typename Rhs> struct DenseSparseProductReturnType<Lhs,Rhs,1>
-{
-  typedef typename internal::conditional<
-    Rhs::IsRowMajor,
-    SparseDenseOuterProduct<Rhs,Lhs,true>,
-    SparseDenseOuterProduct<Lhs,Rhs,false> >::type Type;
-};
-
-namespace internal {
-
-template<typename Lhs, typename Rhs, bool Tr>
-struct traits<SparseDenseOuterProduct<Lhs,Rhs,Tr> >
-{
-  typedef Sparse StorageKind;
-  typedef typename scalar_product_traits<typename traits<Lhs>::Scalar,
-                                         typename traits<Rhs>::Scalar>::ReturnType Scalar;
-  typedef typename Lhs::Index Index;
-  typedef typename Lhs::Nested LhsNested;
-  typedef typename Rhs::Nested RhsNested;
-  typedef typename remove_all<LhsNested>::type _LhsNested;
-  typedef typename remove_all<RhsNested>::type _RhsNested;
-
-  enum {
-    LhsCoeffReadCost = traits<_LhsNested>::CoeffReadCost,
-    RhsCoeffReadCost = traits<_RhsNested>::CoeffReadCost,
-
-    RowsAtCompileTime    = Tr ? int(traits<Rhs>::RowsAtCompileTime)     : int(traits<Lhs>::RowsAtCompileTime),
-    ColsAtCompileTime    = Tr ? int(traits<Lhs>::ColsAtCompileTime)     : int(traits<Rhs>::ColsAtCompileTime),
-    MaxRowsAtCompileTime = Tr ? int(traits<Rhs>::MaxRowsAtCompileTime)  : int(traits<Lhs>::MaxRowsAtCompileTime),
-    MaxColsAtCompileTime = Tr ? int(traits<Lhs>::MaxColsAtCompileTime)  : int(traits<Rhs>::MaxColsAtCompileTime),
-
-    Flags = Tr ? RowMajorBit : 0,
-
-    CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + NumTraits<Scalar>::MulCost
-  };
-};
-
-} // end namespace internal
-
-template<typename Lhs, typename Rhs, bool Tr>
-class SparseDenseOuterProduct
- : public SparseMatrixBase<SparseDenseOuterProduct<Lhs,Rhs,Tr> >
-{
-  public:
-
-    typedef SparseMatrixBase<SparseDenseOuterProduct> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(SparseDenseOuterProduct)
-    typedef internal::traits<SparseDenseOuterProduct> Traits;
-
-  private:
-
-    typedef typename Traits::LhsNested LhsNested;
-    typedef typename Traits::RhsNested RhsNested;
-    typedef typename Traits::_LhsNested _LhsNested;
-    typedef typename Traits::_RhsNested _RhsNested;
-
-  public:
-
-    class InnerIterator;
-
-    EIGEN_STRONG_INLINE SparseDenseOuterProduct(const Lhs& lhs, const Rhs& rhs)
-      : m_lhs(lhs), m_rhs(rhs)
-    {
-      EIGEN_STATIC_ASSERT(!Tr,YOU_MADE_A_PROGRAMMING_MISTAKE);
-    }
-
-    EIGEN_STRONG_INLINE SparseDenseOuterProduct(const Rhs& rhs, const Lhs& lhs)
-      : m_lhs(lhs), m_rhs(rhs)
-    {
-      EIGEN_STATIC_ASSERT(Tr,YOU_MADE_A_PROGRAMMING_MISTAKE);
-    }
-
-    EIGEN_STRONG_INLINE Index rows() const { return Tr ? m_rhs.rows() : m_lhs.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return Tr ? m_lhs.cols() : m_rhs.cols(); }
-
-    EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
-    EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
-
-  protected:
-    LhsNested m_lhs;
-    RhsNested m_rhs;
-};
-
-template<typename Lhs, typename Rhs, bool Transpose>
-class SparseDenseOuterProduct<Lhs,Rhs,Transpose>::InnerIterator : public _LhsNested::InnerIterator
-{
-    typedef typename _LhsNested::InnerIterator Base;
-    typedef typename SparseDenseOuterProduct::Index Index;
-  public:
-    EIGEN_STRONG_INLINE InnerIterator(const SparseDenseOuterProduct& prod, Index outer)
-      : Base(prod.lhs(), 0), m_outer(outer), m_factor(get(prod.rhs(), outer, typename internal::traits<Rhs>::StorageKind() ))
-    { }
-
-    inline Index outer() const { return m_outer; }
-    inline Index row() const { return Transpose ? m_outer : Base::index(); }
-    inline Index col() const { return Transpose ? Base::index() : m_outer; }
-
-    inline Scalar value() const { return Base::value() * m_factor; }
-
-  protected:
-    static Scalar get(const _RhsNested &rhs, Index outer, Dense = Dense())
-    {
-      return rhs.coeff(outer);
-    }
-    
-    static Scalar get(const _RhsNested &rhs, Index outer, Sparse = Sparse())
-    {
-      typename Traits::_RhsNested::InnerIterator it(rhs, outer);
-      if (it && it.index()==0)
-        return it.value();
-      
-      return Scalar(0);
-    }
-    
-    Index m_outer;
-    Scalar m_factor;
-};
-
-namespace internal {
-template<typename Lhs, typename Rhs>
-struct traits<SparseTimeDenseProduct<Lhs,Rhs> >
- : traits<ProductBase<SparseTimeDenseProduct<Lhs,Rhs>, Lhs, Rhs> >
-{
-  typedef Dense StorageKind;
-  typedef MatrixXpr XprKind;
-};
-
-template<typename SparseLhsType, typename DenseRhsType, typename DenseResType,
+namespace internal {
+
+template <> struct product_promote_storage_type<Sparse,Dense, OuterProduct> { typedef Sparse ret; };
+template <> struct product_promote_storage_type<Dense,Sparse, OuterProduct> { typedef Sparse ret; };
+
+template<typename SparseLhsType, typename DenseRhsType, typename DenseResType,
+         typename AlphaType,
          int LhsStorageOrder = ((SparseLhsType::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor,
          bool ColPerCol = ((DenseRhsType::Flags&RowMajorBit)==0) || DenseRhsType::ColsAtCompileTime==1>
 struct sparse_time_dense_product_impl;
 
 template<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
-struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, RowMajor, true>
-{
-  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
-  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
-  typedef typename internal::remove_all<DenseResType>::type Res;
-  typedef typename Lhs::Index Index;
-  typedef typename Lhs::InnerIterator LhsInnerIterator;
-  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
-  {
-    for(Index c=0; c<rhs.cols(); ++c)
-    {
-      Index n = lhs.outerSize();
-      for(Index j=0; j<n; ++j)
-      {
-        typename Res::Scalar tmp(0);
-        for(LhsInnerIterator it(lhs,j); it ;++it)
-          tmp += it.value() * rhs.coeff(it.index(),c);
-        res.coeffRef(j,c) = alpha * tmp;
-      }
-    }
-  }
-};
-
-template<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
-struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, ColMajor, true>
-{
-  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
-  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
-  typedef typename internal::remove_all<DenseResType>::type Res;
-  typedef typename Lhs::InnerIterator LhsInnerIterator;
-  typedef typename Lhs::Index Index;
-  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
-  {
-    for(Index c=0; c<rhs.cols(); ++c)
-    {
-      for(Index j=0; j<lhs.outerSize(); ++j)
-      {
-        typename Res::Scalar rhs_j = alpha * rhs.coeff(j,c);
-        for(LhsInnerIterator it(lhs,j); it ;++it)
+struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, typename DenseResType::Scalar, RowMajor, true>
+{
+  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
+  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
+  typedef typename internal::remove_all<DenseResType>::type Res;
+  typedef typename evaluator<Lhs>::InnerIterator LhsInnerIterator;
+  typedef evaluator<Lhs> LhsEval;
+  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
+  {
+    LhsEval lhsEval(lhs);
+    
+    Index n = lhs.outerSize();
+#ifdef EIGEN_HAS_OPENMP
+    Eigen::initParallel();
+    Index threads = Eigen::nbThreads();
+#endif
+    
+    for(Index c=0; c<rhs.cols(); ++c)
+    {
+#ifdef EIGEN_HAS_OPENMP
+      // This 20000 threshold has been found experimentally on 2D and 3D Poisson problems.
+      // It basically represents the minimal amount of work to be done to be worth it.
+      if(threads>1 && lhsEval.nonZerosEstimate() > 20000)
+      {
+        #pragma omp parallel for schedule(dynamic,(n+threads*4-1)/(threads*4)) num_threads(threads)
+        for(Index i=0; i<n; ++i)
+          processRow(lhsEval,rhs,res,alpha,i,c);
+      }
+      else
+#endif
+      {
+        for(Index i=0; i<n; ++i)
+          processRow(lhsEval,rhs,res,alpha,i,c);
+      }
+    }
+  }
+  
+  static void processRow(const LhsEval& lhsEval, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha, Index i, Index col)
+  {
+    typename Res::Scalar tmp(0);
+    for(LhsInnerIterator it(lhsEval,i); it ;++it)
+      tmp += it.value() * rhs.coeff(it.index(),col);
+    res.coeffRef(i,col) += alpha * tmp;
+  }
+  
+};
+
+// FIXME: what is the purpose of the following specialization? Is it for the BlockedSparse format?
+// -> let's disable it for now as it is conflicting with generic scalar*matrix and matrix*scalar operators
+// template<typename T1, typename T2/*, int _Options, typename _StrideType*/>
+// struct ScalarBinaryOpTraits<T1, Ref<T2/*, _Options, _StrideType*/> >
+// {
+//   enum {
+//     Defined = 1
+//   };
+//   typedef typename CwiseUnaryOp<scalar_multiple2_op<T1, typename T2::Scalar>, T2>::PlainObject ReturnType;
+// };
+
+template<typename SparseLhsType, typename DenseRhsType, typename DenseResType, typename AlphaType>
+struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, AlphaType, ColMajor, true>
+{
+  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
+  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
+  typedef typename internal::remove_all<DenseResType>::type Res;
+  typedef typename evaluator<Lhs>::InnerIterator LhsInnerIterator;
+  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha)
+  {
+    evaluator<Lhs> lhsEval(lhs);
+    for(Index c=0; c<rhs.cols(); ++c)
+    {
+      for(Index j=0; j<lhs.outerSize(); ++j)
+      {
+//        typename Res::Scalar rhs_j = alpha * rhs.coeff(j,c);
+        typename ScalarBinaryOpTraits<AlphaType, typename Rhs::Scalar>::ReturnType rhs_j(alpha * rhs.coeff(j,c));
+        for(LhsInnerIterator it(lhsEval,j); it ;++it)
           res.coeffRef(it.index(),c) += it.value() * rhs_j;
       }
     }
   }
 };
 
 template<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
-struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, RowMajor, false>
+struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, typename DenseResType::Scalar, RowMajor, false>
 {
   typedef typename internal::remove_all<SparseLhsType>::type Lhs;
   typedef typename internal::remove_all<DenseRhsType>::type Rhs;
   typedef typename internal::remove_all<DenseResType>::type Res;
-  typedef typename Lhs::InnerIterator LhsInnerIterator;
-  typedef typename Lhs::Index Index;
+  typedef typename evaluator<Lhs>::InnerIterator LhsInnerIterator;
   static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
   {
+    evaluator<Lhs> lhsEval(lhs);
     for(Index j=0; j<lhs.outerSize(); ++j)
     {
       typename Res::RowXpr res_j(res.row(j));
-      for(LhsInnerIterator it(lhs,j); it ;++it)
+      for(LhsInnerIterator it(lhsEval,j); it ;++it)
         res_j += (alpha*it.value()) * rhs.row(it.index());
     }
   }
 };
 
 template<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
-struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, ColMajor, false>
+struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, typename DenseResType::Scalar, ColMajor, false>
 {
   typedef typename internal::remove_all<SparseLhsType>::type Lhs;
   typedef typename internal::remove_all<DenseRhsType>::type Rhs;
   typedef typename internal::remove_all<DenseResType>::type Res;
-  typedef typename Lhs::InnerIterator LhsInnerIterator;
-  typedef typename Lhs::Index Index;
+  typedef typename evaluator<Lhs>::InnerIterator LhsInnerIterator;
   static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
   {
+    evaluator<Lhs> lhsEval(lhs);
     for(Index j=0; j<lhs.outerSize(); ++j)
     {
       typename Rhs::ConstRowXpr rhs_j(rhs.row(j));
-      for(LhsInnerIterator it(lhs,j); it ;++it)
+      for(LhsInnerIterator it(lhsEval,j); it ;++it)
         res.row(it.index()) += (alpha*it.value()) * rhs_j;
     }
   }
 };
 
 template<typename SparseLhsType, typename DenseRhsType, typename DenseResType,typename AlphaType>
 inline void sparse_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha)
 {
-  sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType>::run(lhs, rhs, res, alpha);
-}
-
-} // end namespace internal
-
-template<typename Lhs, typename Rhs>
-class SparseTimeDenseProduct
-  : public ProductBase<SparseTimeDenseProduct<Lhs,Rhs>, Lhs, Rhs>
-{
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseTimeDenseProduct)
-
-    SparseTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
-    {}
-
-    template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
-    {
-      internal::sparse_time_dense_product(m_lhs, m_rhs, dest, alpha);
-    }
-
-  private:
-    SparseTimeDenseProduct& operator=(const SparseTimeDenseProduct&);
-};
-
-
-// dense = dense * sparse
-namespace internal {
-template<typename Lhs, typename Rhs>
-struct traits<DenseTimeSparseProduct<Lhs,Rhs> >
- : traits<ProductBase<DenseTimeSparseProduct<Lhs,Rhs>, Lhs, Rhs> >
-{
-  typedef Dense StorageKind;
-};
-} // end namespace internal
-
-template<typename Lhs, typename Rhs>
-class DenseTimeSparseProduct
-  : public ProductBase<DenseTimeSparseProduct<Lhs,Rhs>, Lhs, Rhs>
-{
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseProduct)
-
-    DenseTimeSparseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
-    {}
-
-    template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
-    {
-      Transpose<const _LhsNested> lhs_t(m_lhs);
-      Transpose<const _RhsNested> rhs_t(m_rhs);
-      Transpose<Dest> dest_t(dest);
-      internal::sparse_time_dense_product(rhs_t, lhs_t, dest_t, alpha);
-    }
-
-  private:
-    DenseTimeSparseProduct& operator=(const DenseTimeSparseProduct&);
-};
+  sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, AlphaType>::run(lhs, rhs, res, alpha);
+}
+
+} // end namespace internal
+
+namespace internal {
+
+template<typename Lhs, typename Rhs, int ProductType>
+struct generic_product_impl<Lhs, Rhs, SparseShape, DenseShape, ProductType>
+ : generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,SparseShape,DenseShape,ProductType> >
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  template<typename Dest>
+  static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  {
+    typedef typename nested_eval<Lhs,((Rhs::Flags&RowMajorBit)==0) ? 1 : Rhs::ColsAtCompileTime>::type LhsNested;
+    typedef typename nested_eval<Rhs,((Lhs::Flags&RowMajorBit)==0) ? 1 : Dynamic>::type RhsNested;
+    LhsNested lhsNested(lhs);
+    RhsNested rhsNested(rhs);
+    internal::sparse_time_dense_product(lhsNested, rhsNested, dst, alpha);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductType>
+struct generic_product_impl<Lhs, Rhs, SparseTriangularShape, DenseShape, ProductType>
+  : generic_product_impl<Lhs, Rhs, SparseShape, DenseShape, ProductType>
+{};
+
+template<typename Lhs, typename Rhs, int ProductType>
+struct generic_product_impl<Lhs, Rhs, DenseShape, SparseShape, ProductType>
+  : generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,SparseShape,ProductType> >
+{
+  typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+  
+  template<typename Dst>
+  static void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
+  {
+    typedef typename nested_eval<Lhs,((Rhs::Flags&RowMajorBit)==0) ? Dynamic : 1>::type LhsNested;
+    typedef typename nested_eval<Rhs,((Lhs::Flags&RowMajorBit)==RowMajorBit) ? 1 : Lhs::RowsAtCompileTime>::type RhsNested;
+    LhsNested lhsNested(lhs);
+    RhsNested rhsNested(rhs);
+    
+    // transpose everything
+    Transpose<Dst> dstT(dst);
+    internal::sparse_time_dense_product(rhsNested.transpose(), lhsNested.transpose(), dstT, alpha);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductType>
+struct generic_product_impl<Lhs, Rhs, DenseShape, SparseTriangularShape, ProductType>
+  : generic_product_impl<Lhs, Rhs, DenseShape, SparseShape, ProductType>
+{};
+
+template<typename LhsT, typename RhsT, bool NeedToTranspose>
+struct sparse_dense_outer_product_evaluator
+{
+protected:
+  typedef typename conditional<NeedToTranspose,RhsT,LhsT>::type Lhs1;
+  typedef typename conditional<NeedToTranspose,LhsT,RhsT>::type ActualRhs;
+  typedef Product<LhsT,RhsT,DefaultProduct> ProdXprType;
+  
+  // if the actual left-hand side is a dense vector,
+  // then build a sparse-view so that we can seamlessly iterate over it.
+  typedef typename conditional<is_same<typename internal::traits<Lhs1>::StorageKind,Sparse>::value,
+            Lhs1, SparseView<Lhs1> >::type ActualLhs;
+  typedef typename conditional<is_same<typename internal::traits<Lhs1>::StorageKind,Sparse>::value,
+            Lhs1 const&, SparseView<Lhs1> >::type LhsArg;
+            
+  typedef evaluator<ActualLhs> LhsEval;
+  typedef evaluator<ActualRhs> RhsEval;
+  typedef typename evaluator<ActualLhs>::InnerIterator LhsIterator;
+  typedef typename ProdXprType::Scalar Scalar;
+  
+public:
+  enum {
+    Flags = NeedToTranspose ? RowMajorBit : 0,
+    CoeffReadCost = HugeCost
+  };
+  
+  class InnerIterator : public LhsIterator
+  {
+  public:
+    InnerIterator(const sparse_dense_outer_product_evaluator &xprEval, Index outer)
+      : LhsIterator(xprEval.m_lhsXprImpl, 0),
+        m_outer(outer),
+        m_empty(false),
+        m_factor(get(xprEval.m_rhsXprImpl, outer, typename internal::traits<ActualRhs>::StorageKind() ))
+    {}
+    
+    EIGEN_STRONG_INLINE Index outer() const { return m_outer; }
+    EIGEN_STRONG_INLINE Index row()   const { return NeedToTranspose ? m_outer : LhsIterator::index(); }
+    EIGEN_STRONG_INLINE Index col()   const { return NeedToTranspose ? LhsIterator::index() : m_outer; }
+
+    EIGEN_STRONG_INLINE Scalar value() const { return LhsIterator::value() * m_factor; }
+    EIGEN_STRONG_INLINE operator bool() const { return LhsIterator::operator bool() && (!m_empty); }
+    
+  protected:
+    Scalar get(const RhsEval &rhs, Index outer, Dense = Dense()) const
+    {
+      return rhs.coeff(outer);
+    }
+    
+    Scalar get(const RhsEval &rhs, Index outer, Sparse = Sparse())
+    {
+      typename RhsEval::InnerIterator it(rhs, outer);
+      if (it && it.index()==0 && it.value()!=Scalar(0))
+        return it.value();
+      m_empty = true;
+      return Scalar(0);
+    }
+    
+    Index m_outer;
+    bool m_empty;
+    Scalar m_factor;
+  };
+  
+  sparse_dense_outer_product_evaluator(const Lhs1 &lhs, const ActualRhs &rhs)
+     : m_lhs(lhs), m_lhsXprImpl(m_lhs), m_rhsXprImpl(rhs)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  // transpose case
+  sparse_dense_outer_product_evaluator(const ActualRhs &rhs, const Lhs1 &lhs)
+     : m_lhs(lhs), m_lhsXprImpl(m_lhs), m_rhsXprImpl(rhs)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+    
+protected:
+  const LhsArg m_lhs;
+  evaluator<ActualLhs> m_lhsXprImpl;
+  evaluator<ActualRhs> m_rhsXprImpl;
+};
+
+// sparse * dense outer product
+template<typename Lhs, typename Rhs>
+struct product_evaluator<Product<Lhs, Rhs, DefaultProduct>, OuterProduct, SparseShape, DenseShape>
+  : sparse_dense_outer_product_evaluator<Lhs,Rhs, Lhs::IsRowMajor>
+{
+  typedef sparse_dense_outer_product_evaluator<Lhs,Rhs, Lhs::IsRowMajor> Base;
+  
+  typedef Product<Lhs, Rhs> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+
+  explicit product_evaluator(const XprType& xpr)
+    : Base(xpr.lhs(), xpr.rhs())
+  {}
+  
+};
+
+template<typename Lhs, typename Rhs>
+struct product_evaluator<Product<Lhs, Rhs, DefaultProduct>, OuterProduct, DenseShape, SparseShape>
+  : sparse_dense_outer_product_evaluator<Lhs,Rhs, Rhs::IsRowMajor>
+{
+  typedef sparse_dense_outer_product_evaluator<Lhs,Rhs, Rhs::IsRowMajor> Base;
+  
+  typedef Product<Lhs, Rhs> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+
+  explicit product_evaluator(const XprType& xpr)
+    : Base(xpr.lhs(), xpr.rhs())
+  {}
+  
+};
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSEDENSEPRODUCT_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseDiagonalProduct.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseDiagonalProduct.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseDiagonalProduct.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -24,173 +24,115 @@
 //        for that particular case
 // The two other cases are symmetric.
 
 namespace internal {
 
-template<typename Lhs, typename Rhs>
-struct traits<SparseDiagonalProduct<Lhs, Rhs> >
-{
-  typedef typename remove_all<Lhs>::type _Lhs;
-  typedef typename remove_all<Rhs>::type _Rhs;
-  typedef typename _Lhs::Scalar Scalar;
-  typedef typename promote_index_type<typename traits<Lhs>::Index,
-                                         typename traits<Rhs>::Index>::type Index;
-  typedef Sparse StorageKind;
-  typedef MatrixXpr XprKind;
-  enum {
-    RowsAtCompileTime = _Lhs::RowsAtCompileTime,
-    ColsAtCompileTime = _Rhs::ColsAtCompileTime,
-
-    MaxRowsAtCompileTime = _Lhs::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = _Rhs::MaxColsAtCompileTime,
-
-    SparseFlags = is_diagonal<_Lhs>::ret ? int(_Rhs::Flags) : int(_Lhs::Flags),
-    Flags = (SparseFlags&RowMajorBit),
-    CoeffReadCost = Dynamic
-  };
-};
-
-enum {SDP_IsDiagonal, SDP_IsSparseRowMajor, SDP_IsSparseColMajor};
-template<typename Lhs, typename Rhs, typename SparseDiagonalProductType, int RhsMode, int LhsMode>
-class sparse_diagonal_product_inner_iterator_selector;
-
-} // end namespace internal
-
-template<typename Lhs, typename Rhs>
-class SparseDiagonalProduct
-  : public SparseMatrixBase<SparseDiagonalProduct<Lhs,Rhs> >,
-    internal::no_assignment_operator
-{
-    typedef typename Lhs::Nested LhsNested;
-    typedef typename Rhs::Nested RhsNested;
-
-    typedef typename internal::remove_all<LhsNested>::type _LhsNested;
-    typedef typename internal::remove_all<RhsNested>::type _RhsNested;
-
-    enum {
-      LhsMode = internal::is_diagonal<_LhsNested>::ret ? internal::SDP_IsDiagonal
-              : (_LhsNested::Flags&RowMajorBit) ? internal::SDP_IsSparseRowMajor : internal::SDP_IsSparseColMajor,
-      RhsMode = internal::is_diagonal<_RhsNested>::ret ? internal::SDP_IsDiagonal
-              : (_RhsNested::Flags&RowMajorBit) ? internal::SDP_IsSparseRowMajor : internal::SDP_IsSparseColMajor
-    };
-
-  public:
-
-    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseDiagonalProduct)
-
-    typedef internal::sparse_diagonal_product_inner_iterator_selector
-                      <_LhsNested,_RhsNested,SparseDiagonalProduct,LhsMode,RhsMode> InnerIterator;
-    
-    // We do not want ReverseInnerIterator for diagonal-sparse products,
-    // but this dummy declaration is needed to make diag * sparse * diag compile.
-    class ReverseInnerIterator;
-
-    EIGEN_STRONG_INLINE SparseDiagonalProduct(const Lhs& lhs, const Rhs& rhs)
-      : m_lhs(lhs), m_rhs(rhs)
-    {
-      eigen_assert(lhs.cols() == rhs.rows() && "invalid sparse matrix * diagonal matrix product");
-    }
-
-    EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
-
-    EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
-    EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
-
-  protected:
-    LhsNested m_lhs;
-    RhsNested m_rhs;
-};
-
-namespace internal {
-
-template<typename Lhs, typename Rhs, typename SparseDiagonalProductType>
-class sparse_diagonal_product_inner_iterator_selector
-<Lhs,Rhs,SparseDiagonalProductType,SDP_IsDiagonal,SDP_IsSparseRowMajor>
-  : public CwiseUnaryOp<scalar_multiple_op<typename Lhs::Scalar>,const Rhs>::InnerIterator
-{
-    typedef typename CwiseUnaryOp<scalar_multiple_op<typename Lhs::Scalar>,const Rhs>::InnerIterator Base;
-    typedef typename Lhs::Index Index;
-  public:
-    inline sparse_diagonal_product_inner_iterator_selector(
-              const SparseDiagonalProductType& expr, Index outer)
-      : Base(expr.rhs()*(expr.lhs().diagonal().coeff(outer)), outer)
-    {}
-};
-
-template<typename Lhs, typename Rhs, typename SparseDiagonalProductType>
-class sparse_diagonal_product_inner_iterator_selector
-<Lhs,Rhs,SparseDiagonalProductType,SDP_IsDiagonal,SDP_IsSparseColMajor>
-  : public CwiseBinaryOp<
-      scalar_product_op<typename Lhs::Scalar>,
-      const typename Rhs::ConstInnerVectorReturnType,
-      const typename Lhs::DiagonalVectorType>::InnerIterator
-{
-    typedef typename CwiseBinaryOp<
-      scalar_product_op<typename Lhs::Scalar>,
-      const typename Rhs::ConstInnerVectorReturnType,
-      const typename Lhs::DiagonalVectorType>::InnerIterator Base;
-    typedef typename Lhs::Index Index;
-    Index m_outer;
-  public:
-    inline sparse_diagonal_product_inner_iterator_selector(
-              const SparseDiagonalProductType& expr, Index outer)
-      : Base(expr.rhs().innerVector(outer) .cwiseProduct(expr.lhs().diagonal()), 0), m_outer(outer)
-    {}
-    
-    inline Index outer() const { return m_outer; }
-    inline Index col() const { return m_outer; }
-};
-
-template<typename Lhs, typename Rhs, typename SparseDiagonalProductType>
-class sparse_diagonal_product_inner_iterator_selector
-<Lhs,Rhs,SparseDiagonalProductType,SDP_IsSparseColMajor,SDP_IsDiagonal>
-  : public CwiseUnaryOp<scalar_multiple_op<typename Rhs::Scalar>,const Lhs>::InnerIterator
-{
-    typedef typename CwiseUnaryOp<scalar_multiple_op<typename Rhs::Scalar>,const Lhs>::InnerIterator Base;
-    typedef typename Lhs::Index Index;
-  public:
-    inline sparse_diagonal_product_inner_iterator_selector(
-              const SparseDiagonalProductType& expr, Index outer)
-      : Base(expr.lhs()*expr.rhs().diagonal().coeff(outer), outer)
-    {}
-};
-
-template<typename Lhs, typename Rhs, typename SparseDiagonalProductType>
-class sparse_diagonal_product_inner_iterator_selector
-<Lhs,Rhs,SparseDiagonalProductType,SDP_IsSparseRowMajor,SDP_IsDiagonal>
-  : public CwiseBinaryOp<
-      scalar_product_op<typename Rhs::Scalar>,
-      const typename Lhs::ConstInnerVectorReturnType,
-      const Transpose<const typename Rhs::DiagonalVectorType> >::InnerIterator
-{
-    typedef typename CwiseBinaryOp<
-      scalar_product_op<typename Rhs::Scalar>,
-      const typename Lhs::ConstInnerVectorReturnType,
-      const Transpose<const typename Rhs::DiagonalVectorType> >::InnerIterator Base;
-    typedef typename Lhs::Index Index;
-    Index m_outer;
-  public:
-    inline sparse_diagonal_product_inner_iterator_selector(
-              const SparseDiagonalProductType& expr, Index outer)
-      : Base(expr.lhs().innerVector(outer) .cwiseProduct(expr.rhs().diagonal().transpose()), 0), m_outer(outer)
-    {}
-    
-    inline Index outer() const { return m_outer; }
-    inline Index row() const { return m_outer; }
-};
-
-} // end namespace internal
-
-// SparseMatrixBase functions
-
-template<typename Derived>
-template<typename OtherDerived>
-const SparseDiagonalProduct<Derived,OtherDerived>
-SparseMatrixBase<Derived>::operator*(const DiagonalBase<OtherDerived> &other) const
-{
-  return SparseDiagonalProduct<Derived,OtherDerived>(this->derived(), other.derived());
-}
+enum {
+  SDP_AsScalarProduct,
+  SDP_AsCwiseProduct
+};
+  
+template<typename SparseXprType, typename DiagonalCoeffType, int SDP_Tag>
+struct sparse_diagonal_product_evaluator;
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, DefaultProduct>, ProductTag, DiagonalShape, SparseShape>
+  : public sparse_diagonal_product_evaluator<Rhs, typename Lhs::DiagonalVectorType, Rhs::Flags&RowMajorBit?SDP_AsScalarProduct:SDP_AsCwiseProduct>
+{
+  typedef Product<Lhs, Rhs, DefaultProduct> XprType;
+  enum { CoeffReadCost = HugeCost, Flags = Rhs::Flags&RowMajorBit, Alignment = 0 }; // FIXME CoeffReadCost & Flags
+  
+  typedef sparse_diagonal_product_evaluator<Rhs, typename Lhs::DiagonalVectorType, Rhs::Flags&RowMajorBit?SDP_AsScalarProduct:SDP_AsCwiseProduct> Base;
+  explicit product_evaluator(const XprType& xpr) : Base(xpr.rhs(), xpr.lhs().diagonal()) {}
+};
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, DefaultProduct>, ProductTag, SparseShape, DiagonalShape>
+  : public sparse_diagonal_product_evaluator<Lhs, Transpose<const typename Rhs::DiagonalVectorType>, Lhs::Flags&RowMajorBit?SDP_AsCwiseProduct:SDP_AsScalarProduct>
+{
+  typedef Product<Lhs, Rhs, DefaultProduct> XprType;
+  enum { CoeffReadCost = HugeCost, Flags = Lhs::Flags&RowMajorBit, Alignment = 0 }; // FIXME CoeffReadCost & Flags
+  
+  typedef sparse_diagonal_product_evaluator<Lhs, Transpose<const typename Rhs::DiagonalVectorType>, Lhs::Flags&RowMajorBit?SDP_AsCwiseProduct:SDP_AsScalarProduct> Base;
+  explicit product_evaluator(const XprType& xpr) : Base(xpr.lhs(), xpr.rhs().diagonal().transpose()) {}
+};
+
+template<typename SparseXprType, typename DiagonalCoeffType>
+struct sparse_diagonal_product_evaluator<SparseXprType, DiagonalCoeffType, SDP_AsScalarProduct>
+{
+protected:
+  typedef typename evaluator<SparseXprType>::InnerIterator SparseXprInnerIterator;
+  typedef typename SparseXprType::Scalar Scalar;
+  
+public:
+  class InnerIterator : public SparseXprInnerIterator
+  {
+  public:
+    InnerIterator(const sparse_diagonal_product_evaluator &xprEval, Index outer)
+      : SparseXprInnerIterator(xprEval.m_sparseXprImpl, outer),
+        m_coeff(xprEval.m_diagCoeffImpl.coeff(outer))
+    {}
+    
+    EIGEN_STRONG_INLINE Scalar value() const { return m_coeff * SparseXprInnerIterator::value(); }
+  protected:
+    typename DiagonalCoeffType::Scalar m_coeff;
+  };
+  
+  sparse_diagonal_product_evaluator(const SparseXprType &sparseXpr, const DiagonalCoeffType &diagCoeff)
+    : m_sparseXprImpl(sparseXpr), m_diagCoeffImpl(diagCoeff)
+  {}
+
+  Index nonZerosEstimate() const { return m_sparseXprImpl.nonZerosEstimate(); }
+    
+protected:
+  evaluator<SparseXprType> m_sparseXprImpl;
+  evaluator<DiagonalCoeffType> m_diagCoeffImpl;
+};
+
+
+template<typename SparseXprType, typename DiagCoeffType>
+struct sparse_diagonal_product_evaluator<SparseXprType, DiagCoeffType, SDP_AsCwiseProduct>
+{
+  typedef typename SparseXprType::Scalar Scalar;
+  typedef typename SparseXprType::StorageIndex StorageIndex;
+  
+  typedef typename nested_eval<DiagCoeffType,SparseXprType::IsRowMajor ? SparseXprType::RowsAtCompileTime
+                                                                       : SparseXprType::ColsAtCompileTime>::type DiagCoeffNested;
+  
+  class InnerIterator
+  {
+    typedef typename evaluator<SparseXprType>::InnerIterator SparseXprIter;
+  public:
+    InnerIterator(const sparse_diagonal_product_evaluator &xprEval, Index outer)
+      : m_sparseIter(xprEval.m_sparseXprEval, outer), m_diagCoeffNested(xprEval.m_diagCoeffNested)
+    {}
+    
+    inline Scalar value() const { return m_sparseIter.value() * m_diagCoeffNested.coeff(index()); }
+    inline StorageIndex index() const  { return m_sparseIter.index(); }
+    inline Index outer() const  { return m_sparseIter.outer(); }
+    inline Index col() const    { return SparseXprType::IsRowMajor ? m_sparseIter.index() : m_sparseIter.outer(); }
+    inline Index row() const    { return SparseXprType::IsRowMajor ? m_sparseIter.outer() : m_sparseIter.index(); }
+    
+    EIGEN_STRONG_INLINE InnerIterator& operator++() { ++m_sparseIter; return *this; }
+    inline operator bool() const  { return m_sparseIter; }
+    
+  protected:
+    SparseXprIter m_sparseIter;
+    DiagCoeffNested m_diagCoeffNested;
+  };
+  
+  sparse_diagonal_product_evaluator(const SparseXprType &sparseXpr, const DiagCoeffType &diagCoeff)
+    : m_sparseXprEval(sparseXpr), m_diagCoeffNested(diagCoeff)
+  {}
+
+  Index nonZerosEstimate() const { return m_sparseXprEval.nonZerosEstimate(); }
+    
+protected:
+  evaluator<SparseXprType> m_sparseXprEval;
+  DiagCoeffNested m_diagCoeffNested;
+};
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSE_DIAGONAL_PRODUCT_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseDot.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseDot.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseDot.h
@@ -24,11 +24,12 @@
     YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
   eigen_assert(size() == other.size());
   eigen_assert(other.size()>0 && "you are using a non initialized vector");
 
-  typename Derived::InnerIterator i(derived(),0);
+  internal::evaluator<Derived> thisEval(derived());
+  typename internal::evaluator<Derived>::InnerIterator i(thisEval, 0);
   Scalar res(0);
   while (i)
   {
     res += numext::conj(i.value()) * other.coeff(i.index());
     ++i;
@@ -47,20 +48,16 @@
   EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
     YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
   eigen_assert(size() == other.size());
 
-  typedef typename Derived::Nested  Nested;
-  typedef typename OtherDerived::Nested  OtherNested;
-  typedef typename internal::remove_all<Nested>::type  NestedCleaned;
-  typedef typename internal::remove_all<OtherNested>::type  OtherNestedCleaned;
-
-  Nested nthis(derived());
-  OtherNested nother(other.derived());
-
-  typename NestedCleaned::InnerIterator i(nthis,0);
-  typename OtherNestedCleaned::InnerIterator j(nother,0);
+  internal::evaluator<Derived> thisEval(derived());
+  typename internal::evaluator<Derived>::InnerIterator i(thisEval, 0);
+  
+  internal::evaluator<OtherDerived>  otherEval(other.derived());
+  typename internal::evaluator<OtherDerived>::InnerIterator j(otherEval, 0);
+
   Scalar res(0);
   while (i && j)
   {
     if (i.index()==j.index())
     {

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseFuzzy.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseFuzzy.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseFuzzy.h
@@ -1,26 +1,29 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_FUZZY_H
 #define EIGEN_SPARSE_FUZZY_H
 
-// template<typename Derived>
-// template<typename OtherDerived>
-// bool SparseMatrixBase<Derived>::isApprox(
-//   const OtherDerived& other,
-//   typename NumTraits<Scalar>::Real prec
-// ) const
-// {
-//   const typename internal::nested<Derived,2>::type nested(derived());
-//   const typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
-//   return    (nested - otherNested).cwise().abs2().sum()
-//          <= prec * prec * (std::min)(nested.cwise().abs2().sum(), otherNested.cwise().abs2().sum());
-// }
+namespace Eigen {
+  
+template<typename Derived>
+template<typename OtherDerived>
+bool SparseMatrixBase<Derived>::isApprox(const SparseMatrixBase<OtherDerived>& other, const RealScalar &prec) const
+{
+  const typename internal::nested_eval<Derived,2,PlainObject>::type actualA(derived());
+  typename internal::conditional<bool(IsRowMajor)==bool(OtherDerived::IsRowMajor),
+    const typename internal::nested_eval<OtherDerived,2,PlainObject>::type,
+    const PlainObject>::type actualB(other.derived());
+
+  return (actualA - actualB).squaredNorm() <= prec * prec * numext::mini(actualA.squaredNorm(), actualB.squaredNorm());
+}
+
+} // end namespace Eigen
 
 #endif // EIGEN_SPARSE_FUZZY_H

ADDED   3rd_party/eigen/Eigen/src/SparseCore/SparseMap.h
Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseMap.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseMap.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseMap.h
@@ -0,0 +1,305 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_MAP_H
+#define EIGEN_SPARSE_MAP_H
+
+namespace Eigen {
+
+namespace internal {
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+struct traits<Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+  : public traits<SparseMatrix<MatScalar,MatOptions,MatIndex> >
+{
+  typedef SparseMatrix<MatScalar,MatOptions,MatIndex> PlainObjectType;
+  typedef traits<PlainObjectType> TraitsBase;
+  enum {
+    Flags = TraitsBase::Flags & (~NestByRefBit)
+  };
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+struct traits<Map<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+  : public traits<SparseMatrix<MatScalar,MatOptions,MatIndex> >
+{
+  typedef SparseMatrix<MatScalar,MatOptions,MatIndex> PlainObjectType;
+  typedef traits<PlainObjectType> TraitsBase;
+  enum {
+    Flags = TraitsBase::Flags & (~ (NestByRefBit | LvalueBit))
+  };
+};
+
+} // end namespace internal
+
+template<typename Derived,
+         int Level = internal::accessors_level<Derived>::has_write_access ? WriteAccessors : ReadOnlyAccessors
+> class SparseMapBase;
+
+/** \ingroup SparseCore_Module
+  * class SparseMapBase
+  * \brief Common base class for Map and Ref instance of sparse matrix and vector.
+  */
+template<typename Derived>
+class SparseMapBase<Derived,ReadOnlyAccessors>
+  : public SparseCompressedBase<Derived>
+{
+  public:
+    typedef SparseCompressedBase<Derived> Base;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::StorageIndex StorageIndex;
+    enum { IsRowMajor = Base::IsRowMajor };
+    using Base::operator=;
+  protected:
+    
+    typedef typename internal::conditional<
+                         bool(internal::is_lvalue<Derived>::value),
+                         Scalar *, const Scalar *>::type ScalarPointer;
+    typedef typename internal::conditional<
+                         bool(internal::is_lvalue<Derived>::value),
+                         StorageIndex *, const StorageIndex *>::type IndexPointer;
+
+    Index   m_outerSize;
+    Index   m_innerSize;
+    Array<StorageIndex,2,1>  m_zero_nnz;
+    IndexPointer  m_outerIndex;
+    IndexPointer  m_innerIndices;
+    ScalarPointer m_values;
+    IndexPointer  m_innerNonZeros;
+
+  public:
+
+    /** \copydoc SparseMatrixBase::rows() */
+    inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
+    /** \copydoc SparseMatrixBase::cols() */
+    inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
+    /** \copydoc SparseMatrixBase::innerSize() */
+    inline Index innerSize() const { return m_innerSize; }
+    /** \copydoc SparseMatrixBase::outerSize() */
+    inline Index outerSize() const { return m_outerSize; }
+    /** \copydoc SparseCompressedBase::nonZeros */
+    inline Index nonZeros() const { return m_zero_nnz[1]; }
+    
+    /** \copydoc SparseCompressedBase::isCompressed */
+    bool isCompressed() const { return m_innerNonZeros==0; }
+
+    //----------------------------------------
+    // direct access interface
+    /** \copydoc SparseMatrix::valuePtr */
+    inline const Scalar* valuePtr() const { return m_values; }
+    /** \copydoc SparseMatrix::innerIndexPtr */
+    inline const StorageIndex* innerIndexPtr() const { return m_innerIndices; }
+    /** \copydoc SparseMatrix::outerIndexPtr */
+    inline const StorageIndex* outerIndexPtr() const { return m_outerIndex; }
+    /** \copydoc SparseMatrix::innerNonZeroPtr */
+    inline const StorageIndex* innerNonZeroPtr() const { return m_innerNonZeros; }
+    //----------------------------------------
+
+    /** \copydoc SparseMatrix::coeff */
+    inline Scalar coeff(Index row, Index col) const
+    {
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
+
+      Index start = m_outerIndex[outer];
+      Index end = isCompressed() ? m_outerIndex[outer+1] : start + m_innerNonZeros[outer];
+      if (start==end)
+        return Scalar(0);
+      else if (end>0 && inner==m_innerIndices[end-1])
+        return m_values[end-1];
+      // ^^  optimization: let's first check if it is the last coefficient
+      // (very common in high level algorithms)
+
+      const StorageIndex* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end-1],inner);
+      const Index id = r-&m_innerIndices[0];
+      return ((*r==inner) && (id<end)) ? m_values[id] : Scalar(0);
+    }
+
+    inline SparseMapBase(Index rows, Index cols, Index nnz, IndexPointer outerIndexPtr, IndexPointer innerIndexPtr,
+                              ScalarPointer valuePtr, IndexPointer innerNonZerosPtr = 0)
+      : m_outerSize(IsRowMajor?rows:cols), m_innerSize(IsRowMajor?cols:rows), m_zero_nnz(0,internal::convert_index<StorageIndex>(nnz)), m_outerIndex(outerIndexPtr),
+        m_innerIndices(innerIndexPtr), m_values(valuePtr), m_innerNonZeros(innerNonZerosPtr)
+    {}
+
+    // for vectors
+    inline SparseMapBase(Index size, Index nnz, IndexPointer innerIndexPtr, ScalarPointer valuePtr)
+      : m_outerSize(1), m_innerSize(size), m_zero_nnz(0,internal::convert_index<StorageIndex>(nnz)), m_outerIndex(m_zero_nnz.data()),
+        m_innerIndices(innerIndexPtr), m_values(valuePtr), m_innerNonZeros(0)
+    {}
+
+    /** Empty destructor */
+    inline ~SparseMapBase() {}
+
+  protected:
+    inline SparseMapBase() {}
+};
+
+/** \ingroup SparseCore_Module
+  * class SparseMapBase
+  * \brief Common base class for writable Map and Ref instance of sparse matrix and vector.
+  */
+template<typename Derived>
+class SparseMapBase<Derived,WriteAccessors>
+  : public SparseMapBase<Derived,ReadOnlyAccessors>
+{
+    typedef MapBase<Derived, ReadOnlyAccessors> ReadOnlyMapBase;
+    
+  public:
+    typedef SparseMapBase<Derived, ReadOnlyAccessors> Base;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::StorageIndex StorageIndex;
+    enum { IsRowMajor = Base::IsRowMajor };
+    
+    using Base::operator=;
+
+  public:
+    
+    //----------------------------------------
+    // direct access interface
+    using Base::valuePtr;
+    using Base::innerIndexPtr;
+    using Base::outerIndexPtr;
+    using Base::innerNonZeroPtr;
+    /** \copydoc SparseMatrix::valuePtr */
+    inline Scalar* valuePtr()              { return Base::m_values; }
+    /** \copydoc SparseMatrix::innerIndexPtr */
+    inline StorageIndex* innerIndexPtr()   { return Base::m_innerIndices; }
+    /** \copydoc SparseMatrix::outerIndexPtr */
+    inline StorageIndex* outerIndexPtr()   { return Base::m_outerIndex; }
+    /** \copydoc SparseMatrix::innerNonZeroPtr */
+    inline StorageIndex* innerNonZeroPtr() { return Base::m_innerNonZeros; }
+    //----------------------------------------
+
+    /** \copydoc SparseMatrix::coeffRef */
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
+
+      Index start = Base::m_outerIndex[outer];
+      Index end = Base::isCompressed() ? Base::m_outerIndex[outer+1] : start + Base::m_innerNonZeros[outer];
+      eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
+      eigen_assert(end>start && "coeffRef cannot be called on a zero coefficient");
+      StorageIndex* r = std::lower_bound(&Base::m_innerIndices[start],&Base::m_innerIndices[end],inner);
+      const Index id = r - &Base::m_innerIndices[0];
+      eigen_assert((*r==inner) && (id<end) && "coeffRef cannot be called on a zero coefficient");
+      return const_cast<Scalar*>(Base::m_values)[id];
+    }
+    
+    inline SparseMapBase(Index rows, Index cols, Index nnz, StorageIndex* outerIndexPtr, StorageIndex* innerIndexPtr,
+                         Scalar* valuePtr, StorageIndex* innerNonZerosPtr = 0)
+      : Base(rows, cols, nnz, outerIndexPtr, innerIndexPtr, valuePtr, innerNonZerosPtr)
+    {}
+
+    // for vectors
+    inline SparseMapBase(Index size, Index nnz, StorageIndex* innerIndexPtr, Scalar* valuePtr)
+      : Base(size, nnz, innerIndexPtr, valuePtr)
+    {}
+
+    /** Empty destructor */
+    inline ~SparseMapBase() {}
+
+  protected:
+    inline SparseMapBase() {}
+};
+
+/** \ingroup SparseCore_Module
+  *
+  * \brief Specialization of class Map for SparseMatrix-like storage.
+  *
+  * \tparam SparseMatrixType the equivalent sparse matrix type of the referenced data, it must be a template instance of class SparseMatrix.
+  *
+  * \sa class Map, class SparseMatrix, class Ref<SparseMatrixType,Options>
+  */
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+class Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType>
+  : public SparseMapBase<Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+#else
+template<typename SparseMatrixType>
+class Map<SparseMatrixType>
+  : public SparseMapBase<Derived,WriteAccessors>
+#endif
+{
+  public:
+    typedef SparseMapBase<Map> Base;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(Map)
+    enum { IsRowMajor = Base::IsRowMajor };
+
+  public:
+
+    /** Constructs a read-write Map to a sparse matrix of size \a rows x \a cols, containing \a nnz non-zero coefficients,
+      * stored as a sparse format as defined by the pointers \a outerIndexPtr, \a innerIndexPtr, and \a valuePtr.
+      * If the optional parameter \a innerNonZerosPtr is the null pointer, then a standard compressed format is assumed.
+      *
+      * This constructor is available only if \c SparseMatrixType is non-const.
+      *
+      * More details on the expected storage schemes are given in the \ref TutorialSparse "manual pages".
+      */
+    inline Map(Index rows, Index cols, Index nnz, StorageIndex* outerIndexPtr,
+               StorageIndex* innerIndexPtr, Scalar* valuePtr, StorageIndex* innerNonZerosPtr = 0)
+      : Base(rows, cols, nnz, outerIndexPtr, innerIndexPtr, valuePtr, innerNonZerosPtr)
+    {}
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** Empty destructor */
+    inline ~Map() {}
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+class Map<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType>
+  : public SparseMapBase<Map<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+{
+  public:
+    typedef SparseMapBase<Map> Base;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(Map)
+    enum { IsRowMajor = Base::IsRowMajor };
+
+  public:
+#endif
+    /** This is the const version of the above constructor.
+      *
+      * This constructor is available only if \c SparseMatrixType is const, e.g.:
+      * \code Map<const SparseMatrix<double> >  \endcode
+      */
+    inline Map(Index rows, Index cols, Index nnz, const StorageIndex* outerIndexPtr,
+               const StorageIndex* innerIndexPtr, const Scalar* valuePtr, const StorageIndex* innerNonZerosPtr = 0)
+      : Base(rows, cols, nnz, outerIndexPtr, innerIndexPtr, valuePtr, innerNonZerosPtr)
+    {}
+
+    /** Empty destructor */
+    inline ~Map() {}
+};
+
+namespace internal {
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+struct evaluator<Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+  : evaluator<SparseCompressedBase<Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> > >
+{
+  typedef evaluator<SparseCompressedBase<Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> > > Base;
+  typedef Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> XprType;  
+  evaluator() : Base() {}
+  explicit evaluator(const XprType &mat) : Base(mat) {}
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+struct evaluator<Map<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+  : evaluator<SparseCompressedBase<Map<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> > >
+{
+  typedef evaluator<SparseCompressedBase<Map<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> > > Base;
+  typedef Map<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> XprType;  
+  evaluator() : Base() {}
+  explicit evaluator(const XprType &mat) : Base(mat) {}
+};
+
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_MAP_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseMatrix.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseMatrix.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -30,93 +30,110 @@
   * More details on this storage sceheme are given in the \ref TutorialSparse "manual pages".
   *
   * \tparam _Scalar the scalar type, i.e. the type of the coefficients
   * \tparam _Options Union of bit flags controlling the storage scheme. Currently the only possibility
   *                 is ColMajor or RowMajor. The default is 0 which means column-major.
-  * \tparam _Index the type of the indices. It has to be a \b signed type (e.g., short, int, std::ptrdiff_t). Default is \c int.
+  * \tparam _StorageIndex the type of the indices. It has to be a \b signed type (e.g., short, int, std::ptrdiff_t). Default is \c int.
+  *
+  * \warning In %Eigen 3.2, the undocumented type \c SparseMatrix::Index was improperly defined as the storage index type (e.g., int),
+  *          whereas it is now (starting from %Eigen 3.3) deprecated and always defined as Eigen::Index.
+  *          Codes making use of \c SparseMatrix::Index, might thus likely have to be changed to use \c SparseMatrix::StorageIndex instead.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIX_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEMATRIX_PLUGIN.
   */
 
 namespace internal {
-template<typename _Scalar, int _Options, typename _Index>
-struct traits<SparseMatrix<_Scalar, _Options, _Index> >
+template<typename _Scalar, int _Options, typename _StorageIndex>
+struct traits<SparseMatrix<_Scalar, _Options, _StorageIndex> >
 {
   typedef _Scalar Scalar;
-  typedef _Index Index;
+  typedef _StorageIndex StorageIndex;
   typedef Sparse StorageKind;
   typedef MatrixXpr XprKind;
   enum {
     RowsAtCompileTime = Dynamic,
     ColsAtCompileTime = Dynamic,
     MaxRowsAtCompileTime = Dynamic,
     MaxColsAtCompileTime = Dynamic,
-    Flags = _Options | NestByRefBit | LvalueBit,
-    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    Flags = _Options | NestByRefBit | LvalueBit | CompressedAccessBit,
     SupportedAccessPatterns = InnerRandomAccessPattern
   };
 };
 
-template<typename _Scalar, int _Options, typename _Index, int DiagIndex>
-struct traits<Diagonal<const SparseMatrix<_Scalar, _Options, _Index>, DiagIndex> >
+template<typename _Scalar, int _Options, typename _StorageIndex, int DiagIndex>
+struct traits<Diagonal<SparseMatrix<_Scalar, _Options, _StorageIndex>, DiagIndex> >
 {
-  typedef SparseMatrix<_Scalar, _Options, _Index> MatrixType;
-  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef SparseMatrix<_Scalar, _Options, _StorageIndex> MatrixType;
+  typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
   typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
 
   typedef _Scalar Scalar;
   typedef Dense StorageKind;
-  typedef _Index Index;
+  typedef _StorageIndex StorageIndex;
   typedef MatrixXpr XprKind;
 
   enum {
     RowsAtCompileTime = Dynamic,
     ColsAtCompileTime = 1,
     MaxRowsAtCompileTime = Dynamic,
     MaxColsAtCompileTime = 1,
-    Flags = 0,
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost*10
+    Flags = LvalueBit
+  };
+};
+
+template<typename _Scalar, int _Options, typename _StorageIndex, int DiagIndex>
+struct traits<Diagonal<const SparseMatrix<_Scalar, _Options, _StorageIndex>, DiagIndex> >
+ : public traits<Diagonal<SparseMatrix<_Scalar, _Options, _StorageIndex>, DiagIndex> >
+{
+  enum {
+    Flags = 0
   };
 };
 
 } // end namespace internal
 
-template<typename _Scalar, int _Options, typename _Index>
+template<typename _Scalar, int _Options, typename _StorageIndex>
 class SparseMatrix
-  : public SparseMatrixBase<SparseMatrix<_Scalar, _Options, _Index> >
+  : public SparseCompressedBase<SparseMatrix<_Scalar, _Options, _StorageIndex> >
 {
+    typedef SparseCompressedBase<SparseMatrix> Base;
+    using Base::convert_index;
+    friend class SparseVector<_Scalar,0,_StorageIndex>;
   public:
+    using Base::isCompressed;
+    using Base::nonZeros;
     EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix)
-    EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=)
-    EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=)
+    using Base::operator+=;
+    using Base::operator-=;
 
     typedef MappedSparseMatrix<Scalar,Flags> Map;
+    typedef Diagonal<SparseMatrix> DiagonalReturnType;
+    typedef Diagonal<const SparseMatrix> ConstDiagonalReturnType;
+    typedef typename Base::InnerIterator InnerIterator;
+    typedef typename Base::ReverseInnerIterator ReverseInnerIterator;
+    
+
     using Base::IsRowMajor;
-    typedef internal::CompressedStorage<Scalar,Index> Storage;
+    typedef internal::CompressedStorage<Scalar,StorageIndex> Storage;
     enum {
       Options = _Options
     };
 
+    typedef typename Base::IndexVector IndexVector;
+    typedef typename Base::ScalarVector ScalarVector;
   protected:
-
     typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
 
     Index m_outerSize;
     Index m_innerSize;
-    Index* m_outerIndex;
-    Index* m_innerNonZeros;     // optional, if null then the data is compressed
+    StorageIndex* m_outerIndex;
+    StorageIndex* m_innerNonZeros;     // optional, if null then the data is compressed
     Storage m_data;
-    
-    Eigen::Map<Matrix<Index,Dynamic,1> > innerNonZeros() { return Eigen::Map<Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); }
-    const  Eigen::Map<const Matrix<Index,Dynamic,1> > innerNonZeros() const { return Eigen::Map<const Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); }
 
   public:
     
-    /** \returns whether \c *this is in compressed form. */
-    inline bool isCompressed() const { return m_innerNonZeros==0; }
-
     /** \returns the number of rows of the matrix */
     inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
     /** \returns the number of columns of the matrix */
     inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
 
@@ -126,42 +143,42 @@
     inline Index outerSize() const { return m_outerSize; }
     
     /** \returns a const pointer to the array of values.
       * This function is aimed at interoperability with other libraries.
       * \sa innerIndexPtr(), outerIndexPtr() */
-    inline const Scalar* valuePtr() const { return &m_data.value(0); }
+    inline const Scalar* valuePtr() const { return m_data.valuePtr(); }
     /** \returns a non-const pointer to the array of values.
       * This function is aimed at interoperability with other libraries.
       * \sa innerIndexPtr(), outerIndexPtr() */
-    inline Scalar* valuePtr() { return &m_data.value(0); }
+    inline Scalar* valuePtr() { return m_data.valuePtr(); }
 
     /** \returns a const pointer to the array of inner indices.
       * This function is aimed at interoperability with other libraries.
       * \sa valuePtr(), outerIndexPtr() */
-    inline const Index* innerIndexPtr() const { return &m_data.index(0); }
+    inline const StorageIndex* innerIndexPtr() const { return m_data.indexPtr(); }
     /** \returns a non-const pointer to the array of inner indices.
       * This function is aimed at interoperability with other libraries.
       * \sa valuePtr(), outerIndexPtr() */
-    inline Index* innerIndexPtr() { return &m_data.index(0); }
+    inline StorageIndex* innerIndexPtr() { return m_data.indexPtr(); }
 
     /** \returns a const pointer to the array of the starting positions of the inner vectors.
       * This function is aimed at interoperability with other libraries.
       * \sa valuePtr(), innerIndexPtr() */
-    inline const Index* outerIndexPtr() const { return m_outerIndex; }
+    inline const StorageIndex* outerIndexPtr() const { return m_outerIndex; }
     /** \returns a non-const pointer to the array of the starting positions of the inner vectors.
       * This function is aimed at interoperability with other libraries.
       * \sa valuePtr(), innerIndexPtr() */
-    inline Index* outerIndexPtr() { return m_outerIndex; }
+    inline StorageIndex* outerIndexPtr() { return m_outerIndex; }
 
     /** \returns a const pointer to the array of the number of non zeros of the inner vectors.
       * This function is aimed at interoperability with other libraries.
       * \warning it returns the null pointer 0 in compressed mode */
-    inline const Index* innerNonZeroPtr() const { return m_innerNonZeros; }
+    inline const StorageIndex* innerNonZeroPtr() const { return m_innerNonZeros; }
     /** \returns a non-const pointer to the array of the number of non zeros of the inner vectors.
       * This function is aimed at interoperability with other libraries.
       * \warning it returns the null pointer 0 in compressed mode */
-    inline Index* innerNonZeroPtr() { return m_innerNonZeros; }
+    inline StorageIndex* innerNonZeroPtr() { return m_innerNonZeros; }
 
     /** \internal */
     inline Storage& data() { return m_data; }
     /** \internal */
     inline const Storage& data() const { return m_data; }
@@ -173,11 +190,11 @@
       eigen_assert(row>=0 && row<rows() && col>=0 && col<cols());
       
       const Index outer = IsRowMajor ? row : col;
       const Index inner = IsRowMajor ? col : row;
       Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1];
-      return m_data.atInRange(m_outerIndex[outer], end, inner);
+      return m_data.atInRange(m_outerIndex[outer], end, StorageIndex(inner));
     }
 
     /** \returns a non-const reference to the value of the matrix at position \a i, \a j
       *
       * If the element does not exist then it is inserted via the insert(Index,Index) function
@@ -196,11 +213,11 @@
       Index start = m_outerIndex[outer];
       Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1];
       eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
       if(end<=start)
         return insert(row,col);
-      const Index p = m_data.searchLowerIndex(start,end-1,inner);
+      const Index p = m_data.searchLowerIndex(start,end-1,StorageIndex(inner));
       if((p<end) && (m_data.index(p)==inner))
         return m_data.value(p);
       else
         return insert(row,col);
     }
@@ -207,49 +224,38 @@
 
     /** \returns a reference to a novel non zero coefficient with coordinates \a row x \a col.
       * The non zero coefficient must \b not already exist.
       *
       * If the matrix \c *this is in compressed mode, then \c *this is turned into uncompressed
-      * mode while reserving room for 2 non zeros per inner vector. It is strongly recommended to first
-      * call reserve(const SizesType &) to reserve a more appropriate number of elements per
-      * inner vector that better match your scenario.
+      * mode while reserving room for 2 x this->innerSize() non zeros if reserve(Index) has not been called earlier.
+      * In this case, the insertion procedure is optimized for a \e sequential insertion mode where elements are assumed to be
+      * inserted by increasing outer-indices.
+      * 
+      * If that's not the case, then it is strongly recommended to either use a triplet-list to assemble the matrix, or to first
+      * call reserve(const SizesType &) to reserve the appropriate number of non-zero elements per inner vector.
       *
-      * This function performs a sorted insertion in O(1) if the elements of each inner vector are
-      * inserted in increasing inner index order, and in O(nnz_j) for a random insertion.
+      * Assuming memory has been appropriately reserved, this function performs a sorted insertion in O(1)
+      * if the elements of each inner vector are inserted in increasing inner index order, and in O(nnz_j) for a random insertion.
       *
       */
-    Scalar& insert(Index row, Index col)
-    {
-      eigen_assert(row>=0 && row<rows() && col>=0 && col<cols());
-      
-      if(isCompressed())
-      {
-        reserve(Matrix<Index,Dynamic,1>::Constant(outerSize(), 2));
-      }
-      return insertUncompressed(row,col);
-    }
+    Scalar& insert(Index row, Index col);
 
   public:
 
-    class InnerIterator;
-    class ReverseInnerIterator;
-
-    /** Removes all non zeros but keep allocated memory */
+    /** Removes all non zeros but keep allocated memory
+      *
+      * This function does not free the currently allocated memory. To release as much as memory as possible,
+      * call \code mat.data().squeeze(); \endcode after resizing it.
+      * 
+      * \sa resize(Index,Index), data()
+      */
     inline void setZero()
     {
       m_data.clear();
-      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
-      if(m_innerNonZeros)
-        memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(Index));
-    }
-
-    /** \returns the number of non zero coefficients */
-    inline Index nonZeros() const
-    {
-      if(m_innerNonZeros)
-        return innerNonZeros().sum();
-      return static_cast<Index>(m_data.size());
+      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(StorageIndex));
+      if(m_innerNonZeros)
+        memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(StorageIndex));
     }
 
     /** Preallocates \a reserveSize non zeros.
       *
       * Precondition: the matrix must be in compressed mode. */
@@ -260,26 +266,29 @@
     }
     
     #ifdef EIGEN_PARSED_BY_DOXYGEN
     /** Preallocates \a reserveSize[\c j] non zeros for each column (resp. row) \c j.
       *
-      * This function turns the matrix in non-compressed mode */
+      * This function turns the matrix in non-compressed mode.
+      * 
+      * The type \c SizesType must expose the following interface:
+        \code
+        typedef value_type;
+        const value_type& operator[](i) const;
+        \endcode
+      * for \c i in the [0,this->outerSize()[ range.
+      * Typical choices include std::vector<int>, Eigen::VectorXi, Eigen::VectorXi::Constant, etc.
+      */
     template<class SizesType>
     inline void reserve(const SizesType& reserveSizes);
     #else
     template<class SizesType>
-    inline void reserve(const SizesType& reserveSizes, const typename SizesType::value_type& enableif = typename SizesType::value_type())
-    {
-      EIGEN_UNUSED_VARIABLE(enableif);
-      reserveInnerVectors(reserveSizes);
-    }
-    template<class SizesType>
-    inline void reserve(const SizesType& reserveSizes, const typename SizesType::Scalar& enableif =
-    #if (!defined(_MSC_VER)) || (_MSC_VER>=1500) // MSVC 2005 fails to compile with this typename
+    inline void reserve(const SizesType& reserveSizes, const typename SizesType::value_type& enableif =
+    #if (!EIGEN_COMP_MSVC) || (EIGEN_COMP_MSVC>=1500) // MSVC 2005 fails to compile with this typename
         typename
     #endif
-        SizesType::Scalar())
+        SizesType::value_type())
     {
       EIGEN_UNUSED_VARIABLE(enableif);
       reserveInnerVectors(reserveSizes);
     }
     #endif // EIGEN_PARSED_BY_DOXYGEN
@@ -287,30 +296,30 @@
     template<class SizesType>
     inline void reserveInnerVectors(const SizesType& reserveSizes)
     {
       if(isCompressed())
       {
-        std::size_t totalReserveSize = 0;
+        Index totalReserveSize = 0;
         // turn the matrix into non-compressed mode
-        m_innerNonZeros = static_cast<Index*>(std::malloc(m_outerSize * sizeof(Index)));
+        m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex)));
         if (!m_innerNonZeros) internal::throw_std_bad_alloc();
         
         // temporarily use m_innerSizes to hold the new starting points.
-        Index* newOuterIndex = m_innerNonZeros;
+        StorageIndex* newOuterIndex = m_innerNonZeros;
         
-        Index count = 0;
+        StorageIndex count = 0;
         for(Index j=0; j<m_outerSize; ++j)
         {
           newOuterIndex[j] = count;
           count += reserveSizes[j] + (m_outerIndex[j+1]-m_outerIndex[j]);
           totalReserveSize += reserveSizes[j];
         }
         m_data.reserve(totalReserveSize);
-        Index previousOuterIndex = m_outerIndex[m_outerSize];
+        StorageIndex previousOuterIndex = m_outerIndex[m_outerSize];
         for(Index j=m_outerSize-1; j>=0; --j)
         {
-          Index innerNNZ = previousOuterIndex - m_outerIndex[j];
+          StorageIndex innerNNZ = previousOuterIndex - m_outerIndex[j];
           for(Index i=innerNNZ-1; i>=0; --i)
           {
             m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i);
             m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i);
           }
@@ -322,19 +331,19 @@
         
         m_data.resize(m_outerIndex[m_outerSize]);
       }
       else
       {
-        Index* newOuterIndex = static_cast<Index*>(std::malloc((m_outerSize+1)*sizeof(Index)));
+        StorageIndex* newOuterIndex = static_cast<StorageIndex*>(std::malloc((m_outerSize+1)*sizeof(StorageIndex)));
         if (!newOuterIndex) internal::throw_std_bad_alloc();
         
-        Index count = 0;
+        StorageIndex count = 0;
         for(Index j=0; j<m_outerSize; ++j)
         {
           newOuterIndex[j] = count;
-          Index alreadyReserved = (m_outerIndex[j+1]-m_outerIndex[j]) - m_innerNonZeros[j];
-          Index toReserve = std::max<Index>(reserveSizes[j], alreadyReserved);
+          StorageIndex alreadyReserved = (m_outerIndex[j+1]-m_outerIndex[j]) - m_innerNonZeros[j];
+          StorageIndex toReserve = std::max<StorageIndex>(reserveSizes[j], alreadyReserved);
           count += toReserve + m_innerNonZeros[j];
         }
         newOuterIndex[m_outerSize] = count;
         
         m_data.resize(count);
@@ -341,11 +350,11 @@
         for(Index j=m_outerSize-1; j>=0; --j)
         {
           Index offset = newOuterIndex[j] - m_outerIndex[j];
           if(offset>0)
           {
-            Index innerNNZ = m_innerNonZeros[j];
+            StorageIndex innerNNZ = m_innerNonZeros[j];
             for(Index i=innerNNZ-1; i>=0; --i)
             {
               m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i);
               m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i);
             }
@@ -378,25 +387,25 @@
 
     /** \internal
       * \sa insertBack, startVec */
     inline Scalar& insertBackByOuterInner(Index outer, Index inner)
     {
-      eigen_assert(size_t(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)");
+      eigen_assert(Index(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)");
       eigen_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)<inner) && "Invalid ordered insertion (invalid inner index)");
       Index p = m_outerIndex[outer+1];
       ++m_outerIndex[outer+1];
-      m_data.append(0, inner);
+      m_data.append(Scalar(0), inner);
       return m_data.value(p);
     }
 
     /** \internal
       * \warning use it only if you know what you are doing */
     inline Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner)
     {
       Index p = m_outerIndex[outer+1];
       ++m_outerIndex[outer+1];
-      m_data.append(0, inner);
+      m_data.append(Scalar(0), inner);
       return m_data.value(p);
     }
 
     /** \internal
       * \sa insertBack, insertBackByOuterInner */
@@ -412,11 +421,11 @@
       */
     inline void finalize()
     {
       if(isCompressed())
       {
-        Index size = static_cast<Index>(m_data.size());
+        StorageIndex size = internal::convert_index<StorageIndex>(m_data.size());
         Index i = m_outerSize;
         // find the last filled column
         while (i>=0 && m_outerIndex[i]==0)
           --i;
         ++i;
@@ -431,11 +440,17 @@
     //---
 
     template<typename InputIterators>
     void setFromTriplets(const InputIterators& begin, const InputIterators& end);
 
-    void sumupDuplicates();
+    template<typename InputIterators,typename DupFunctor>
+    void setFromTriplets(const InputIterators& begin, const InputIterators& end, DupFunctor dup_func);
+
+    void sumupDuplicates() { collapseDuplicates(internal::scalar_sum_op<Scalar,Scalar>()); }
+
+    template<typename DupFunctor>
+    void collapseDuplicates(DupFunctor dup_func = DupFunctor());
 
     //---
     
     /** \internal
       * same as insert(Index,Index) except that the indices are given relative to the storage order */
@@ -448,10 +463,12 @@
       */
     void makeCompressed()
     {
       if(isCompressed())
         return;
+      
+      eigen_internal_assert(m_outerIndex!=0 && m_outerSize>0);
       
       Index oldStart = m_outerIndex[1];
       m_outerIndex[1] = m_innerNonZeros[0];
       for(Index j=1; j<m_outerSize; ++j)
       {
@@ -477,11 +494,11 @@
     /** Turns the matrix into the uncompressed mode */
     void uncompress()
     {
       if(m_innerNonZeros != 0)
         return; 
-      m_innerNonZeros = static_cast<Index*>(std::malloc(m_outerSize * sizeof(Index)));
+      m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex)));
       for (Index i = 0; i < m_outerSize; i++)
       {
         m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i]; 
       }
     }
@@ -501,14 +518,13 @@
       */
     template<typename KeepFunc>
     void prune(const KeepFunc& keep = KeepFunc())
     {
       // TODO optimize the uncompressed mode to avoid moving and allocating the data twice
-      // TODO also implement a unit test
       makeCompressed();
 
-      Index k = 0;
+      StorageIndex k = 0;
       for(Index j=0; j<m_outerSize; ++j)
       {
         Index previousStart = m_outerIndex[j];
         m_outerIndex[j] = k;
         Index end = m_outerIndex[j+1];
@@ -525,11 +541,16 @@
       m_outerIndex[m_outerSize] = k;
       m_data.resize(k,0);
     }
 
     /** Resizes the matrix to a \a rows x \a cols matrix leaving old values untouched.
-      * \sa resizeNonZeros(Index), reserve(), setZero()
+      *
+      * If the sizes of the matrix are decreased, then the matrix is turned to \b uncompressed-mode
+      * and the storage of the out of bounds coefficients is kept and reserved.
+      * Call makeCompressed() to pack the entries and squeeze extra memory.
+      *
+      * \sa reserve(), setZero(), makeCompressed()
       */
     void conservativeResize(Index rows, Index cols) 
     {
       // No change
       if (this->rows() == rows && this->cols() == cols) return;
@@ -537,27 +558,27 @@
       // If one dimension is null, then there is nothing to be preserved
       if(rows==0 || cols==0) return resize(rows,cols);
 
       Index innerChange = IsRowMajor ? cols - this->cols() : rows - this->rows();
       Index outerChange = IsRowMajor ? rows - this->rows() : cols - this->cols();
-      Index newInnerSize = IsRowMajor ? cols : rows;
+      StorageIndex newInnerSize = convert_index(IsRowMajor ? cols : rows);
 
       // Deals with inner non zeros
       if (m_innerNonZeros)
       {
         // Resize m_innerNonZeros
-        Index *newInnerNonZeros = static_cast<Index*>(std::realloc(m_innerNonZeros, (m_outerSize + outerChange) * sizeof(Index)));
+        StorageIndex *newInnerNonZeros = static_cast<StorageIndex*>(std::realloc(m_innerNonZeros, (m_outerSize + outerChange) * sizeof(StorageIndex)));
         if (!newInnerNonZeros) internal::throw_std_bad_alloc();
         m_innerNonZeros = newInnerNonZeros;
         
         for(Index i=m_outerSize; i<m_outerSize+outerChange; i++)          
           m_innerNonZeros[i] = 0;
       } 
       else if (innerChange < 0) 
       {
         // Inner size decreased: allocate a new m_innerNonZeros
-        m_innerNonZeros = static_cast<Index*>(std::malloc((m_outerSize+outerChange+1) * sizeof(Index)));
+        m_innerNonZeros = static_cast<StorageIndex*>(std::malloc((m_outerSize+outerChange+1) * sizeof(StorageIndex)));
         if (!m_innerNonZeros) internal::throw_std_bad_alloc();
         for(Index i = 0; i < m_outerSize; i++)
           m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i];
       }
       
@@ -564,12 +585,12 @@
       // Change the m_innerNonZeros in case of a decrease of inner size
       if (m_innerNonZeros && innerChange < 0)
       {
         for(Index i = 0; i < m_outerSize + (std::min)(outerChange, Index(0)); i++)
         {
-          Index &n = m_innerNonZeros[i];
-          Index start = m_outerIndex[i];
+          StorageIndex &n = m_innerNonZeros[i];
+          StorageIndex start = m_outerIndex[i];
           while (n > 0 && m_data.index(start+n-1) >= newInnerSize) --n; 
         }
       }
       
       m_innerSize = newInnerSize;
@@ -576,56 +597,65 @@
 
       // Re-allocate outer index structure if necessary
       if (outerChange == 0)
         return;
           
-      Index *newOuterIndex = static_cast<Index*>(std::realloc(m_outerIndex, (m_outerSize + outerChange + 1) * sizeof(Index)));
+      StorageIndex *newOuterIndex = static_cast<StorageIndex*>(std::realloc(m_outerIndex, (m_outerSize + outerChange + 1) * sizeof(StorageIndex)));
       if (!newOuterIndex) internal::throw_std_bad_alloc();
       m_outerIndex = newOuterIndex;
       if (outerChange > 0)
       {
-        Index last = m_outerSize == 0 ? 0 : m_outerIndex[m_outerSize];
+        StorageIndex last = m_outerSize == 0 ? 0 : m_outerIndex[m_outerSize];
         for(Index i=m_outerSize; i<m_outerSize+outerChange+1; i++)          
           m_outerIndex[i] = last; 
       }
       m_outerSize += outerChange;
     }
     
     /** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero.
-      * \sa resizeNonZeros(Index), reserve(), setZero()
+      * 
+      * This function does not free the currently allocated memory. To release as much as memory as possible,
+      * call \code mat.data().squeeze(); \endcode after resizing it.
+      * 
+      * \sa reserve(), setZero()
       */
     void resize(Index rows, Index cols)
     {
       const Index outerSize = IsRowMajor ? rows : cols;
       m_innerSize = IsRowMajor ? cols : rows;
       m_data.clear();
       if (m_outerSize != outerSize || m_outerSize==0)
       {
         std::free(m_outerIndex);
-        m_outerIndex = static_cast<Index*>(std::malloc((outerSize + 1) * sizeof(Index)));
+        m_outerIndex = static_cast<StorageIndex*>(std::malloc((outerSize + 1) * sizeof(StorageIndex)));
         if (!m_outerIndex) internal::throw_std_bad_alloc();
         
         m_outerSize = outerSize;
       }
       if(m_innerNonZeros)
       {
         std::free(m_innerNonZeros);
         m_innerNonZeros = 0;
       }
-      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
+      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(StorageIndex));
     }
 
     /** \internal
       * Resize the nonzero vector to \a size */
     void resizeNonZeros(Index size)
     {
-      // TODO remove this function
       m_data.resize(size);
     }
 
-    /** \returns a const expression of the diagonal coefficients */
-    const Diagonal<const SparseMatrix> diagonal() const { return *this; }
+    /** \returns a const expression of the diagonal coefficients. */
+    const ConstDiagonalReturnType diagonal() const { return ConstDiagonalReturnType(*this); }
+    
+    /** \returns a read-write expression of the diagonal coefficients.
+      * \warning If the diagonal entries are written, then all diagonal
+      * entries \b must already exist, otherwise an assertion will be raised.
+      */
+    DiagonalReturnType diagonal() { return DiagonalReturnType(*this); }
 
     /** Default constructor yielding an empty \c 0 \c x \c 0 matrix */
     inline SparseMatrix()
       : m_outerSize(-1), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
     {
@@ -647,20 +677,29 @@
       : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
     {
       EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
       check_template_parameters();
-      *this = other.derived();
+      const bool needToTranspose = (Flags & RowMajorBit) != (internal::evaluator<OtherDerived>::Flags & RowMajorBit);
+      if (needToTranspose)
+        *this = other.derived();
+      else
+      {
+        #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
+          EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
+        #endif
+        internal::call_assignment_no_alias(*this, other.derived());
+      }
     }
     
     /** Constructs a sparse matrix from the sparse selfadjoint view \a other */
     template<typename OtherDerived, unsigned int UpLo>
     inline SparseMatrix(const SparseSelfAdjointView<OtherDerived, UpLo>& other)
       : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
     {
       check_template_parameters();
-      *this = other;
+      Base::operator=(other);
     }
 
     /** Copy constructor (it performs a deep copy) */
     inline SparseMatrix(const SparseMatrix& other)
       : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
@@ -676,10 +715,19 @@
     {
       check_template_parameters();
       initAssignment(other);
       other.evalTo(*this);
     }
+    
+    /** \brief Copy constructor with in-place evaluation */
+    template<typename OtherDerived>
+    explicit SparseMatrix(const DiagonalBase<OtherDerived>& other)
+      : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
+    {
+      check_template_parameters();
+      *this = other.derived();
+    }
 
     /** Swaps the content of two sparse matrices of the same type.
       * This is a fast operation that simply swaps the underlying pointers and parameters. */
     inline void swap(SparseMatrix& other)
     {
@@ -689,31 +737,37 @@
       std::swap(m_outerSize, other.m_outerSize);
       std::swap(m_innerNonZeros, other.m_innerNonZeros);
       m_data.swap(other.m_data);
     }
 
-    /** Sets *this to the identity matrix */
+    /** Sets *this to the identity matrix.
+      * This function also turns the matrix into compressed mode, and drop any reserved memory. */
     inline void setIdentity()
     {
       eigen_assert(rows() == cols() && "ONLY FOR SQUARED MATRICES");
       this->m_data.resize(rows());
-      Eigen::Map<Matrix<Index, Dynamic, 1> >(&this->m_data.index(0), rows()).setLinSpaced(0, rows()-1);
-      Eigen::Map<Matrix<Scalar, Dynamic, 1> >(&this->m_data.value(0), rows()).setOnes();
-      Eigen::Map<Matrix<Index, Dynamic, 1> >(this->m_outerIndex, rows()+1).setLinSpaced(0, rows());
+      Eigen::Map<IndexVector>(this->m_data.indexPtr(), rows()).setLinSpaced(0, StorageIndex(rows()-1));
+      Eigen::Map<ScalarVector>(this->m_data.valuePtr(), rows()).setOnes();
+      Eigen::Map<IndexVector>(this->m_outerIndex, rows()+1).setLinSpaced(0, StorageIndex(rows()));
+      std::free(m_innerNonZeros);
+      m_innerNonZeros = 0;
     }
     inline SparseMatrix& operator=(const SparseMatrix& other)
     {
       if (other.isRValue())
       {
         swap(other.const_cast_derived());
       }
       else if(this!=&other)
       {
+        #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
+          EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
+        #endif
         initAssignment(other);
         if(other.isCompressed())
         {
-          memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(Index));
+          internal::smart_copy(other.m_outerIndex, other.m_outerIndex + m_outerSize + 1, m_outerIndex);
           m_data = other.m_data;
         }
         else
         {
           Base::operator=(other);
@@ -720,59 +774,56 @@
         }
       }
       return *this;
     }
 
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    template<typename Lhs, typename Rhs>
-    inline SparseMatrix& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
-    { return Base::operator=(product); }
-    
-    template<typename OtherDerived>
-    inline SparseMatrix& operator=(const ReturnByValue<OtherDerived>& other)
-    {
-      initAssignment(other);
-      return Base::operator=(other.derived());
-    }
-    
+#ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename OtherDerived>
     inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other)
     { return Base::operator=(other.derived()); }
-    #endif
+#endif // EIGEN_PARSED_BY_DOXYGEN
 
     template<typename OtherDerived>
     EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other);
 
     friend std::ostream & operator << (std::ostream & s, const SparseMatrix& m)
     {
       EIGEN_DBG_SPARSE(
         s << "Nonzero entries:\n";
         if(m.isCompressed())
+        {
           for (Index i=0; i<m.nonZeros(); ++i)
             s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
+        }
         else
+        {
           for (Index i=0; i<m.outerSize(); ++i)
           {
             Index p = m.m_outerIndex[i];
             Index pe = m.m_outerIndex[i]+m.m_innerNonZeros[i];
             Index k=p;
-            for (; k<pe; ++k)
+            for (; k<pe; ++k) {
               s << "(" << m.m_data.value(k) << "," << m.m_data.index(k) << ") ";
-            for (; k<m.m_outerIndex[i+1]; ++k)
+            }
+            for (; k<m.m_outerIndex[i+1]; ++k) {
               s << "(_,_) ";
+            }
           }
+        }
         s << std::endl;
         s << std::endl;
         s << "Outer pointers:\n";
-        for (Index i=0; i<m.outerSize(); ++i)
+        for (Index i=0; i<m.outerSize(); ++i) {
           s << m.m_outerIndex[i] << " ";
+        }
         s << " $" << std::endl;
         if(!m.isCompressed())
         {
           s << "Inner non zeros:\n";
-          for (Index i=0; i<m.outerSize(); ++i)
+          for (Index i=0; i<m.outerSize(); ++i) {
             s << m.m_innerNonZeros[i] << " ";
+          }
           s << " $" << std::endl;
         }
         s << std::endl;
       );
       s << static_cast<const SparseMatrixBase<SparseMatrix>&>(m);
@@ -784,14 +835,12 @@
     {
       std::free(m_outerIndex);
       std::free(m_innerNonZeros);
     }
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
     /** Overloaded for performance */
     Scalar sum() const;
-#endif
     
 #   ifdef EIGEN_SPARSEMATRIX_PLUGIN
 #     include EIGEN_SPARSEMATRIX_PLUGIN
 #   endif
 
@@ -814,19 +863,19 @@
 
     /** \internal
       * A vector object that is equal to 0 everywhere but v at the position i */
     class SingletonVector
     {
-        Index m_index;
-        Index m_value;
+        StorageIndex m_index;
+        StorageIndex m_value;
       public:
-        typedef Index value_type;
+        typedef StorageIndex value_type;
         SingletonVector(Index i, Index v)
-          : m_index(i), m_value(v)
+          : m_index(convert_index(i)), m_value(convert_index(v))
         {}
 
-        Index operator[](Index i) const { return i==m_index ? m_value : 0; }
+        StorageIndex operator[](Index i) const { return i==m_index ? m_value : 0; }
     };
 
     /** \internal
       * \sa insert(Index,Index) */
     EIGEN_DONT_INLINE Scalar& insertUncompressed(Index row, Index col);
@@ -841,18 +890,18 @@
 
       eigen_assert(!isCompressed());
       eigen_assert(m_innerNonZeros[outer]<=(m_outerIndex[outer+1] - m_outerIndex[outer]));
 
       Index p = m_outerIndex[outer] + m_innerNonZeros[outer]++;
-      m_data.index(p) = inner;
+      m_data.index(p) = convert_index(inner);
       return (m_data.value(p) = 0);
     }
 
 private:
   static void check_template_parameters()
   {
-    EIGEN_STATIC_ASSERT(NumTraits<Index>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
+    EIGEN_STATIC_ASSERT(NumTraits<StorageIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
     EIGEN_STATIC_ASSERT((Options&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS);
   }
 
   struct default_prunning_func {
     default_prunning_func(const Scalar& ref, const RealScalar& eps) : reference(ref), epsilon(eps) {}
@@ -863,91 +912,24 @@
     Scalar reference;
     RealScalar epsilon;
   };
 };
 
-template<typename Scalar, int _Options, typename _Index>
-class SparseMatrix<Scalar,_Options,_Index>::InnerIterator
-{
-  public:
-    InnerIterator(const SparseMatrix& mat, Index outer)
-      : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_id(mat.m_outerIndex[outer])
-    {
-      if(mat.isCompressed())
-        m_end = mat.m_outerIndex[outer+1];
-      else
-        m_end = m_id + mat.m_innerNonZeros[outer];
-    }
-
-    inline InnerIterator& operator++() { m_id++; return *this; }
-
-    inline const Scalar& value() const { return m_values[m_id]; }
-    inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id]); }
-
-    inline Index index() const { return m_indices[m_id]; }
-    inline Index outer() const { return m_outer; }
-    inline Index row() const { return IsRowMajor ? m_outer : index(); }
-    inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-    inline operator bool() const { return (m_id < m_end); }
-
-  protected:
-    const Scalar* m_values;
-    const Index* m_indices;
-    const Index m_outer;
-    Index m_id;
-    Index m_end;
-};
-
-template<typename Scalar, int _Options, typename _Index>
-class SparseMatrix<Scalar,_Options,_Index>::ReverseInnerIterator
-{
-  public:
-    ReverseInnerIterator(const SparseMatrix& mat, Index outer)
-      : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_start(mat.m_outerIndex[outer])
-    {
-      if(mat.isCompressed())
-        m_id = mat.m_outerIndex[outer+1];
-      else
-        m_id = m_start + mat.m_innerNonZeros[outer];
-    }
-
-    inline ReverseInnerIterator& operator--() { --m_id; return *this; }
-
-    inline const Scalar& value() const { return m_values[m_id-1]; }
-    inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id-1]); }
-
-    inline Index index() const { return m_indices[m_id-1]; }
-    inline Index outer() const { return m_outer; }
-    inline Index row() const { return IsRowMajor ? m_outer : index(); }
-    inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-    inline operator bool() const { return (m_id > m_start); }
-
-  protected:
-    const Scalar* m_values;
-    const Index* m_indices;
-    const Index m_outer;
-    Index m_id;
-    const Index m_start;
-};
-
 namespace internal {
 
-template<typename InputIterator, typename SparseMatrixType>
-void set_from_triplets(const InputIterator& begin, const InputIterator& end, SparseMatrixType& mat, int Options = 0)
+template<typename InputIterator, typename SparseMatrixType, typename DupFunctor>
+void set_from_triplets(const InputIterator& begin, const InputIterator& end, SparseMatrixType& mat, DupFunctor dup_func)
 {
-  EIGEN_UNUSED_VARIABLE(Options);
   enum { IsRowMajor = SparseMatrixType::IsRowMajor };
   typedef typename SparseMatrixType::Scalar Scalar;
-  typedef typename SparseMatrixType::Index Index;
-  SparseMatrix<Scalar,IsRowMajor?ColMajor:RowMajor,Index> trMat(mat.rows(),mat.cols());
+  typedef typename SparseMatrixType::StorageIndex StorageIndex;
+  SparseMatrix<Scalar,IsRowMajor?ColMajor:RowMajor,StorageIndex> trMat(mat.rows(),mat.cols());
 
   if(begin!=end)
   {
     // pass 1: count the nnz per inner-vector
-    Matrix<Index,Dynamic,1> wi(trMat.outerSize());
+    typename SparseMatrixType::IndexVector wi(trMat.outerSize());
     wi.setZero();
     for(InputIterator it(begin); it!=end; ++it)
     {
       eigen_assert(it->row()>=0 && it->row()<mat.rows() && it->col()>=0 && it->col()<mat.cols());
       wi(IsRowMajor ? it->col() : it->row())++;
@@ -957,11 +939,11 @@
     trMat.reserve(wi);
     for(InputIterator it(begin); it!=end; ++it)
       trMat.insertBackUncompressed(it->row(),it->col()) = it->value();
 
     // pass 3:
-    trMat.sumupDuplicates();
+    trMat.collapseDuplicates(dup_func);
   }
 
   // pass 4: transposed copy -> implicit sorting
   mat = trMat;
 }
@@ -1004,38 +986,55 @@
   *
   * \warning The list of triplets is read multiple times (at least twice). Therefore, it is not recommended to define
   * an abstract iterator over a complex data-structure that would be expensive to evaluate. The triplets should rather
   * be explicitely stored into a std::vector for instance.
   */
-template<typename Scalar, int _Options, typename _Index>
+template<typename Scalar, int _Options, typename _StorageIndex>
 template<typename InputIterators>
-void SparseMatrix<Scalar,_Options,_Index>::setFromTriplets(const InputIterators& begin, const InputIterators& end)
+void SparseMatrix<Scalar,_Options,_StorageIndex>::setFromTriplets(const InputIterators& begin, const InputIterators& end)
+{
+  internal::set_from_triplets<InputIterators, SparseMatrix<Scalar,_Options,_StorageIndex> >(begin, end, *this, internal::scalar_sum_op<Scalar,Scalar>());
+}
+
+/** The same as setFromTriplets but when duplicates are met the functor \a dup_func is applied:
+  * \code
+  * value = dup_func(OldValue, NewValue)
+  * \endcode 
+  * Here is a C++11 example keeping the latest entry only:
+  * \code
+  * mat.setFromTriplets(triplets.begin(), triplets.end(), [] (const Scalar&,const Scalar &b) { return b; });
+  * \endcode
+  */
+template<typename Scalar, int _Options, typename _StorageIndex>
+template<typename InputIterators,typename DupFunctor>
+void SparseMatrix<Scalar,_Options,_StorageIndex>::setFromTriplets(const InputIterators& begin, const InputIterators& end, DupFunctor dup_func)
 {
-  internal::set_from_triplets(begin, end, *this);
+  internal::set_from_triplets<InputIterators, SparseMatrix<Scalar,_Options,_StorageIndex>, DupFunctor>(begin, end, *this, dup_func);
 }
 
 /** \internal */
-template<typename Scalar, int _Options, typename _Index>
-void SparseMatrix<Scalar,_Options,_Index>::sumupDuplicates()
+template<typename Scalar, int _Options, typename _StorageIndex>
+template<typename DupFunctor>
+void SparseMatrix<Scalar,_Options,_StorageIndex>::collapseDuplicates(DupFunctor dup_func)
 {
   eigen_assert(!isCompressed());
   // TODO, in practice we should be able to use m_innerNonZeros for that task
-  Matrix<Index,Dynamic,1> wi(innerSize());
+  IndexVector wi(innerSize());
   wi.fill(-1);
-  Index count = 0;
+  StorageIndex count = 0;
   // for each inner-vector, wi[inner_index] will hold the position of first element into the index/value buffers
   for(Index j=0; j<outerSize(); ++j)
   {
-    Index start   = count;
+    StorageIndex start   = count;
     Index oldEnd  = m_outerIndex[j]+m_innerNonZeros[j];
     for(Index k=m_outerIndex[j]; k<oldEnd; ++k)
     {
       Index i = m_data.index(k);
       if(wi(i)>=start)
       {
         // we already meet this entry => accumulate it
-        m_data.value(wi(i)) += m_data.value(k);
+        m_data.value(wi(i)) = dup_func(m_data.value(wi(i)), m_data.value(k));
       }
       else
       {
         m_data.value(count) = m_data.value(k);
         m_data.index(count) = m_data.index(k);
@@ -1051,54 +1050,63 @@
   std::free(m_innerNonZeros);
   m_innerNonZeros = 0;
   m_data.resize(m_outerIndex[m_outerSize]);
 }
 
-template<typename Scalar, int _Options, typename _Index>
+template<typename Scalar, int _Options, typename _StorageIndex>
 template<typename OtherDerived>
-EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_Index>& SparseMatrix<Scalar,_Options,_Index>::operator=(const SparseMatrixBase<OtherDerived>& other)
+EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_StorageIndex>& SparseMatrix<Scalar,_Options,_StorageIndex>::operator=(const SparseMatrixBase<OtherDerived>& other)
 {
   EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-  
-  const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
+
+  #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
+    EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
+  #endif
+      
+  const bool needToTranspose = (Flags & RowMajorBit) != (internal::evaluator<OtherDerived>::Flags & RowMajorBit);
   if (needToTranspose)
   {
+    #ifdef EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN
+      EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN
+    #endif
     // two passes algorithm:
     //  1 - compute the number of coeffs per dest inner vector
     //  2 - do the actual copy/eval
     // Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed
-    typedef typename internal::nested<OtherDerived,2>::type OtherCopy;
+    typedef typename internal::nested_eval<OtherDerived,2,typename internal::plain_matrix_type<OtherDerived>::type >::type OtherCopy;
     typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
+    typedef internal::evaluator<_OtherCopy> OtherCopyEval;
     OtherCopy otherCopy(other.derived());
+    OtherCopyEval otherCopyEval(otherCopy);
 
     SparseMatrix dest(other.rows(),other.cols());
-    Eigen::Map<Matrix<Index, Dynamic, 1> > (dest.m_outerIndex,dest.outerSize()).setZero();
+    Eigen::Map<IndexVector> (dest.m_outerIndex,dest.outerSize()).setZero();
 
     // pass 1
     // FIXME the above copy could be merged with that pass
     for (Index j=0; j<otherCopy.outerSize(); ++j)
-      for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
+      for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it)
         ++dest.m_outerIndex[it.index()];
 
     // prefix sum
-    Index count = 0;
-    Matrix<Index,Dynamic,1> positions(dest.outerSize());
+    StorageIndex count = 0;
+    IndexVector positions(dest.outerSize());
     for (Index j=0; j<dest.outerSize(); ++j)
     {
-      Index tmp = dest.m_outerIndex[j];
+      StorageIndex tmp = dest.m_outerIndex[j];
       dest.m_outerIndex[j] = count;
       positions[j] = count;
       count += tmp;
     }
     dest.m_outerIndex[dest.outerSize()] = count;
     // alloc
     dest.m_data.resize(count);
     // pass 2
-    for (Index j=0; j<otherCopy.outerSize(); ++j)
+    for (StorageIndex j=0; j<otherCopy.outerSize(); ++j)
     {
-      for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
+      for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it)
       {
         Index pos = positions[it.index()]++;
         dest.m_data.index(pos) = j;
         dest.m_data.value(pos) = it.value();
       }
@@ -1107,30 +1115,152 @@
     return *this;
   }
   else
   {
     if(other.isRValue())
+    {
       initAssignment(other.derived());
+    }
     // there is no special optimization
     return Base::operator=(other.derived());
   }
 }
 
-template<typename _Scalar, int _Options, typename _Index>
-EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& SparseMatrix<_Scalar,_Options,_Index>::insertUncompressed(Index row, Index col)
+template<typename _Scalar, int _Options, typename _StorageIndex>
+typename SparseMatrix<_Scalar,_Options,_StorageIndex>::Scalar& SparseMatrix<_Scalar,_Options,_StorageIndex>::insert(Index row, Index col)
+{
+  eigen_assert(row>=0 && row<rows() && col>=0 && col<cols());
+  
+  const Index outer = IsRowMajor ? row : col;
+  const Index inner = IsRowMajor ? col : row;
+  
+  if(isCompressed())
+  {
+    if(nonZeros()==0)
+    {
+      // reserve space if not already done
+      if(m_data.allocatedSize()==0)
+        m_data.reserve(2*m_innerSize);
+      
+      // turn the matrix into non-compressed mode
+      m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex)));
+      if(!m_innerNonZeros) internal::throw_std_bad_alloc();
+      
+      memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(StorageIndex));
+      
+      // pack all inner-vectors to the end of the pre-allocated space
+      // and allocate the entire free-space to the first inner-vector
+      StorageIndex end = convert_index(m_data.allocatedSize());
+      for(Index j=1; j<=m_outerSize; ++j)
+        m_outerIndex[j] = end;
+    }
+    else
+    {
+      // turn the matrix into non-compressed mode
+      m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex)));
+      if(!m_innerNonZeros) internal::throw_std_bad_alloc();
+      for(Index j=0; j<m_outerSize; ++j)
+        m_innerNonZeros[j] = m_outerIndex[j+1]-m_outerIndex[j];
+    }
+  }
+  
+  // check whether we can do a fast "push back" insertion
+  Index data_end = m_data.allocatedSize();
+  
+  // First case: we are filling a new inner vector which is packed at the end.
+  // We assume that all remaining inner-vectors are also empty and packed to the end.
+  if(m_outerIndex[outer]==data_end)
+  {
+    eigen_internal_assert(m_innerNonZeros[outer]==0);
+    
+    // pack previous empty inner-vectors to end of the used-space
+    // and allocate the entire free-space to the current inner-vector.
+    StorageIndex p = convert_index(m_data.size());
+    Index j = outer;
+    while(j>=0 && m_innerNonZeros[j]==0)
+      m_outerIndex[j--] = p;
+    
+    // push back the new element
+    ++m_innerNonZeros[outer];
+    m_data.append(Scalar(0), inner);
+    
+    // check for reallocation
+    if(data_end != m_data.allocatedSize())
+    {
+      // m_data has been reallocated
+      //  -> move remaining inner-vectors back to the end of the free-space
+      //     so that the entire free-space is allocated to the current inner-vector.
+      eigen_internal_assert(data_end < m_data.allocatedSize());
+      StorageIndex new_end = convert_index(m_data.allocatedSize());
+      for(Index k=outer+1; k<=m_outerSize; ++k)
+        if(m_outerIndex[k]==data_end)
+          m_outerIndex[k] = new_end;
+    }
+    return m_data.value(p);
+  }
+  
+  // Second case: the next inner-vector is packed to the end
+  // and the current inner-vector end match the used-space.
+  if(m_outerIndex[outer+1]==data_end && m_outerIndex[outer]+m_innerNonZeros[outer]==m_data.size())
+  {
+    eigen_internal_assert(outer+1==m_outerSize || m_innerNonZeros[outer+1]==0);
+    
+    // add space for the new element
+    ++m_innerNonZeros[outer];
+    m_data.resize(m_data.size()+1);
+    
+    // check for reallocation
+    if(data_end != m_data.allocatedSize())
+    {
+      // m_data has been reallocated
+      //  -> move remaining inner-vectors back to the end of the free-space
+      //     so that the entire free-space is allocated to the current inner-vector.
+      eigen_internal_assert(data_end < m_data.allocatedSize());
+      StorageIndex new_end = convert_index(m_data.allocatedSize());
+      for(Index k=outer+1; k<=m_outerSize; ++k)
+        if(m_outerIndex[k]==data_end)
+          m_outerIndex[k] = new_end;
+    }
+    
+    // and insert it at the right position (sorted insertion)
+    Index startId = m_outerIndex[outer];
+    Index p = m_outerIndex[outer]+m_innerNonZeros[outer]-1;
+    while ( (p > startId) && (m_data.index(p-1) > inner) )
+    {
+      m_data.index(p) = m_data.index(p-1);
+      m_data.value(p) = m_data.value(p-1);
+      --p;
+    }
+    
+    m_data.index(p) = convert_index(inner);
+    return (m_data.value(p) = 0);
+  }
+  
+  if(m_data.size() != m_data.allocatedSize())
+  {
+    // make sure the matrix is compatible to random un-compressed insertion:
+    m_data.resize(m_data.allocatedSize());
+    this->reserveInnerVectors(Array<StorageIndex,Dynamic,1>::Constant(m_outerSize, 2));
+  }
+  
+  return insertUncompressed(row,col);
+}
+    
+template<typename _Scalar, int _Options, typename _StorageIndex>
+EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_StorageIndex>::Scalar& SparseMatrix<_Scalar,_Options,_StorageIndex>::insertUncompressed(Index row, Index col)
 {
   eigen_assert(!isCompressed());
 
   const Index outer = IsRowMajor ? row : col;
-  const Index inner = IsRowMajor ? col : row;
+  const StorageIndex inner = convert_index(IsRowMajor ? col : row);
 
   Index room = m_outerIndex[outer+1] - m_outerIndex[outer];
-  Index innerNNZ = m_innerNonZeros[outer];
+  StorageIndex innerNNZ = m_innerNonZeros[outer];
   if(innerNNZ>=room)
   {
     // this inner vector is full, we need to reallocate the whole buffer :(
-    reserve(SingletonVector(outer,std::max<Index>(2,innerNNZ)));
+    reserve(SingletonVector(outer,std::max<StorageIndex>(2,innerNNZ)));
   }
 
   Index startId = m_outerIndex[outer];
   Index p = startId + m_innerNonZeros[outer];
   while ( (p > startId) && (m_data.index(p-1) > inner) )
@@ -1137,20 +1267,20 @@
   {
     m_data.index(p) = m_data.index(p-1);
     m_data.value(p) = m_data.value(p-1);
     --p;
   }
-  eigen_assert((p<=startId || m_data.index(p-1)!=inner) && "you cannot insert an element that already exist, you must call coeffRef to this end");
+  eigen_assert((p<=startId || m_data.index(p-1)!=inner) && "you cannot insert an element that already exists, you must call coeffRef to this end");
 
   m_innerNonZeros[outer]++;
 
   m_data.index(p) = inner;
   return (m_data.value(p) = 0);
 }
 
-template<typename _Scalar, int _Options, typename _Index>
-EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& SparseMatrix<_Scalar,_Options,_Index>::insertCompressed(Index row, Index col)
+template<typename _Scalar, int _Options, typename _StorageIndex>
+EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_StorageIndex>::Scalar& SparseMatrix<_Scalar,_Options,_StorageIndex>::insertCompressed(Index row, Index col)
 {
   eigen_assert(isCompressed());
 
   const Index outer = IsRowMajor ? row : col;
   const Index inner = IsRowMajor ? col : row;
@@ -1159,25 +1289,25 @@
   if (m_outerIndex[outer+1]==0)
   {
     // we start a new inner vector
     while (previousOuter>=0 && m_outerIndex[previousOuter]==0)
     {
-      m_outerIndex[previousOuter] = static_cast<Index>(m_data.size());
+      m_outerIndex[previousOuter] = convert_index(m_data.size());
       --previousOuter;
     }
     m_outerIndex[outer+1] = m_outerIndex[outer];
   }
 
   // here we have to handle the tricky case where the outerIndex array
   // starts with: [ 0 0 0 0 0 1 ...] and we are inserted in, e.g.,
   // the 2nd inner vector...
   bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0))
-                && (size_t(m_outerIndex[outer+1]) == m_data.size());
+                && (std::size_t(m_outerIndex[outer+1]) == m_data.size());
 
-  size_t startId = m_outerIndex[outer];
-  // FIXME let's make sure sizeof(long int) == sizeof(size_t)
-  size_t p = m_outerIndex[outer+1];
+  std::size_t startId = m_outerIndex[outer];
+  // FIXME let's make sure sizeof(long int) == sizeof(std::size_t)
+  std::size_t p = m_outerIndex[outer+1];
   ++m_outerIndex[outer+1];
 
   double reallocRatio = 1;
   if (m_data.allocatedSize()<=m_data.size())
   {
@@ -1250,10 +1380,24 @@
     --p;
   }
 
   m_data.index(p) = inner;
   return (m_data.value(p) = 0);
+}
+
+namespace internal {
+
+template<typename _Scalar, int _Options, typename _StorageIndex>
+struct evaluator<SparseMatrix<_Scalar,_Options,_StorageIndex> >
+  : evaluator<SparseCompressedBase<SparseMatrix<_Scalar,_Options,_StorageIndex> > >
+{
+  typedef evaluator<SparseCompressedBase<SparseMatrix<_Scalar,_Options,_StorageIndex> > > Base;
+  typedef SparseMatrix<_Scalar,_Options,_StorageIndex> SparseMatrixType;
+  evaluator() : Base() {}
+  explicit evaluator(const SparseMatrixType &mat) : Base(mat) {}
+};
+
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSEMATRIX_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseMatrixBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseMatrixBase.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseMatrixBase.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -16,36 +16,45 @@
   *
   * \class SparseMatrixBase
   *
   * \brief Base class of any sparse matrices or sparse expressions
   *
-  * \tparam Derived
+  * \tparam Derived is the derived type, e.g. a sparse matrix type, or an expression, etc.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIXBASE_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEMATRIXBASE_PLUGIN.
   */
-template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
+template<typename Derived> class SparseMatrixBase
+  : public EigenBase<Derived>
 {
   public:
 
     typedef typename internal::traits<Derived>::Scalar Scalar;
+    
+    /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
+      *
+      * It is an alias for the Scalar type */
+    typedef Scalar value_type;
+    
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Index Index;
+
+    /** The integer type used to \b store indices within a SparseMatrix.
+      * For a \c SparseMatrix<Scalar,Options,IndexType> it an alias of the third template parameter \c IndexType. */
+    typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
+
     typedef typename internal::add_const_on_value_type_if_arithmetic<
                          typename internal::packet_traits<Scalar>::type
                      >::type PacketReturnType;
 
     typedef SparseMatrixBase StorageBaseType;
-    typedef EigenBase<Derived> Base;
+
+    typedef Matrix<StorageIndex,Dynamic,1> IndexVector;
+    typedef Matrix<Scalar,Dynamic,1> ScalarVector;
     
     template<typename OtherDerived>
-    Derived& operator=(const EigenBase<OtherDerived> &other)
-    {
-      other.derived().evalTo(derived());
-      return derived();
-    }
+    Derived& operator=(const EigenBase<OtherDerived> &other);
 
     enum {
 
       RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
         /**< The number of rows at compile-time. This is just a copy of the value provided
@@ -81,15 +90,10 @@
       Flags = internal::traits<Derived>::Flags,
         /**< This stores expression \ref flags flags which may or may not be inherited by new expressions
           * constructed from this one. See the \ref flags "list of flags".
           */
 
-      CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
-        /**< This is a rough measure of how expensive it is to read one coefficient from
-          * this expression.
-          */
-
       IsRowMajor = Flags&RowMajorBit ? 1 : 0,
       
       InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
                              : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
 
@@ -101,14 +105,15 @@
     /** \internal the return type of MatrixBase::adjoint() */
     typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
                         CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, Eigen::Transpose<const Derived> >,
                         Transpose<const Derived>
                      >::type AdjointReturnType;
-
+    typedef Transpose<Derived> TransposeReturnType;
+    typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
 
-    typedef SparseMatrix<Scalar, Flags&RowMajorBit ? RowMajor : ColMajor, Index> PlainObject;
-
+    // FIXME storage order do not match evaluator storage order
+    typedef SparseMatrix<Scalar, Flags&RowMajorBit ? RowMajor : ColMajor, StorageIndex> PlainObject;
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** This is the "real scalar" type; if the \a Scalar type is already real numbers
       * (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If
       * \a Scalar is \a std::complex<T> then RealScalar is \a T.
@@ -122,42 +127,55 @@
     typedef typename internal::conditional<_HasDirectAccess, const Scalar&, Scalar>::type CoeffReturnType;
 
     /** \internal Represents a matrix with all coefficients equal to one another*/
     typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Matrix<Scalar,Dynamic,Dynamic> > ConstantReturnType;
 
+    /** type of the equivalent dense matrix */
+    typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
     /** type of the equivalent square matrix */
     typedef Matrix<Scalar,EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime),
                           EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime)> SquareMatrixType;
 
     inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
     inline Derived& derived() { return *static_cast<Derived*>(this); }
     inline Derived& const_cast_derived() const
     { return *static_cast<Derived*>(const_cast<SparseMatrixBase*>(this)); }
+
+    typedef EigenBase<Derived> Base;
+
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
 #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase
+#ifdef EIGEN_PARSED_BY_DOXYGEN
+#define EIGEN_DOC_UNARY_ADDONS(METHOD,OP)           /** <p>This method does not change the sparsity of \c *this: the OP is applied to explicitly stored coefficients only. \sa SparseCompressedBase::coeffs() </p> */
+#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL      /** <p> \warning This method returns a read-only expression for any sparse matrices. \sa \ref TutorialSparse_SubMatrices "Sparse block operations" </p> */
+#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND) /** <p> \warning This method returns a read-write expression for COND sparse matrices only. Otherwise, the returned expression is read-only. \sa \ref TutorialSparse_SubMatrices "Sparse block operations" </p> */
+#else
+#define EIGEN_DOC_UNARY_ADDONS(X,Y)
+#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND)
+#endif
 #   include "../plugins/CommonCwiseUnaryOps.h"
 #   include "../plugins/CommonCwiseBinaryOps.h"
 #   include "../plugins/MatrixCwiseUnaryOps.h"
 #   include "../plugins/MatrixCwiseBinaryOps.h"
 #   include "../plugins/BlockMethods.h"
 #   ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN
 #     include EIGEN_SPARSEMATRIXBASE_PLUGIN
 #   endif
-#   undef EIGEN_CURRENT_STORAGE_BASE_CLASS
 #undef EIGEN_CURRENT_STORAGE_BASE_CLASS
+#undef EIGEN_DOC_UNARY_ADDONS
+#undef EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+#undef EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF
 
     /** \returns the number of rows. \sa cols() */
     inline Index rows() const { return derived().rows(); }
     /** \returns the number of columns. \sa rows() */
     inline Index cols() const { return derived().cols(); }
     /** \returns the number of coefficients, which is \a rows()*cols().
       * \sa rows(), cols(). */
     inline Index size() const { return rows() * cols(); }
-    /** \returns the number of nonzero coefficients which is in practice the number
-      * of stored coefficients. */
-    inline Index nonZeros() const { return derived().nonZeros(); }
     /** \returns true if either the number of rows or the number of columns is equal to 1.
       * In other words, this function returns
       * \code rows()==1 || cols()==1 \endcode
       * \sa rows(), cols(), IsVectorAtCompileTime. */
     inline bool isVector() const { return rows()==1 || cols()==1; }
@@ -173,109 +191,40 @@
 
     SparseMatrixBase() : m_isRValue(false) { /* TODO check flags */ }
 
     
     template<typename OtherDerived>
-    Derived& operator=(const ReturnByValue<OtherDerived>& other)
-    {
-      other.evalTo(derived());
-      return derived();
-    }
-
+    Derived& operator=(const ReturnByValue<OtherDerived>& other);
 
     template<typename OtherDerived>
-    inline Derived& operator=(const SparseMatrixBase<OtherDerived>& other)
-    {
-      return assign(other.derived());
-    }
-
-    inline Derived& operator=(const Derived& other)
-    {
-//       if (other.isRValue())
-//         derived().swap(other.const_cast_derived());
-//       else
-      return assign(other.derived());
-    }
+    inline Derived& operator=(const SparseMatrixBase<OtherDerived>& other);
+
+    inline Derived& operator=(const Derived& other);
 
   protected:
 
     template<typename OtherDerived>
-    inline Derived& assign(const OtherDerived& other)
-    {
-      const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
-      const Index outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols();
-      if ((!transpose) && other.isRValue())
-      {
-        // eval without temporary
-        derived().resize(other.rows(), other.cols());
-        derived().setZero();
-        derived().reserve((std::max)(this->rows(),this->cols())*2);
-        for (Index j=0; j<outerSize; ++j)
-        {
-          derived().startVec(j);
-          for (typename OtherDerived::InnerIterator it(other, j); it; ++it)
-          {
-            Scalar v = it.value();
-            derived().insertBackByOuterInner(j,it.index()) = v;
-          }
-        }
-        derived().finalize();
-      }
-      else
-      {
-        assignGeneric(other);
-      }
-      return derived();
-    }
+    inline Derived& assign(const OtherDerived& other);
 
     template<typename OtherDerived>
-    inline void assignGeneric(const OtherDerived& other)
-    {
-      //const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
-      eigen_assert(( ((internal::traits<Derived>::SupportedAccessPatterns&OuterRandomAccessPattern)==OuterRandomAccessPattern) ||
-                  (!((Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit)))) &&
-                  "the transpose operation is supposed to be handled in SparseMatrix::operator=");
-
-      enum { Flip = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit) };
-
-      const Index outerSize = other.outerSize();
-      //typedef typename internal::conditional<transpose, LinkedVectorMatrix<Scalar,Flags&RowMajorBit>, Derived>::type TempType;
-      // thanks to shallow copies, we always eval to a tempary
-      Derived temp(other.rows(), other.cols());
-
-      temp.reserve((std::max)(this->rows(),this->cols())*2);
-      for (Index j=0; j<outerSize; ++j)
-      {
-        temp.startVec(j);
-        for (typename OtherDerived::InnerIterator it(other.derived(), j); it; ++it)
-        {
-          Scalar v = it.value();
-          temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
-        }
-      }
-      temp.finalize();
-
-      derived() = temp.markAsRValue();
-    }
+    inline void assignGeneric(const OtherDerived& other);
 
   public:
 
-    template<typename Lhs, typename Rhs>
-    inline Derived& operator=(const SparseSparseProduct<Lhs,Rhs>& product);
-
     friend std::ostream & operator << (std::ostream & s, const SparseMatrixBase& m)
     {
       typedef typename Derived::Nested Nested;
       typedef typename internal::remove_all<Nested>::type NestedCleaned;
 
       if (Flags&RowMajorBit)
       {
-        const Nested nm(m.derived());
+        Nested nm(m.derived());
+        internal::evaluator<NestedCleaned> thisEval(nm);
         for (Index row=0; row<nm.outerSize(); ++row)
         {
           Index col = 0;
-          for (typename NestedCleaned::InnerIterator it(nm.derived(), row); it; ++it)
+          for (typename internal::evaluator<NestedCleaned>::InnerIterator it(thisEval, row); it; ++it)
           {
             for ( ; col<it.index(); ++col)
               s << "0 ";
             s << it.value() << " ";
             ++col;
@@ -285,14 +234,15 @@
           s << std::endl;
         }
       }
       else
       {
-        const Nested nm(m.derived());
+        Nested nm(m.derived());
+        internal::evaluator<NestedCleaned> thisEval(nm);
         if (m.cols() == 1) {
           Index row = 0;
-          for (typename NestedCleaned::InnerIterator it(nm.derived(), 0); it; ++it)
+          for (typename internal::evaluator<NestedCleaned>::InnerIterator it(thisEval, 0); it; ++it)
           {
             for ( ; row<it.index(); ++row)
               s << "0" << std::endl;
             s << it.value() << std::endl;
             ++row;
@@ -300,134 +250,128 @@
           for ( ; row<m.rows(); ++row)
             s << "0" << std::endl;
         }
         else
         {
-          SparseMatrix<Scalar, RowMajorBit, Index> trans = m;
-          s << static_cast<const SparseMatrixBase<SparseMatrix<Scalar, RowMajorBit, Index> >&>(trans);
+          SparseMatrix<Scalar, RowMajorBit, StorageIndex> trans = m;
+          s << static_cast<const SparseMatrixBase<SparseMatrix<Scalar, RowMajorBit, StorageIndex> >&>(trans);
         }
       }
       return s;
     }
 
     template<typename OtherDerived>
     Derived& operator+=(const SparseMatrixBase<OtherDerived>& other);
     template<typename OtherDerived>
     Derived& operator-=(const SparseMatrixBase<OtherDerived>& other);
+    
+    template<typename OtherDerived>
+    Derived& operator+=(const DiagonalBase<OtherDerived>& other);
+    template<typename OtherDerived>
+    Derived& operator-=(const DiagonalBase<OtherDerived>& other);
+
+    template<typename OtherDerived>
+    Derived& operator+=(const EigenBase<OtherDerived> &other);
+    template<typename OtherDerived>
+    Derived& operator-=(const EigenBase<OtherDerived> &other);
 
     Derived& operator*=(const Scalar& other);
     Derived& operator/=(const Scalar& other);
 
-    #define EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE \
-      CwiseBinaryOp< \
-        internal::scalar_product_op< \
-          typename internal::scalar_product_traits< \
-            typename internal::traits<Derived>::Scalar, \
-            typename internal::traits<OtherDerived>::Scalar \
-          >::ReturnType \
-        >, \
-        const Derived, \
-        const OtherDerived \
-      >
-
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
-    cwiseProduct(const MatrixBase<OtherDerived> &other) const;
-
-    // sparse * sparse
-    template<typename OtherDerived>
-    const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type
-    operator*(const SparseMatrixBase<OtherDerived> &other) const;
+    template<typename OtherDerived> struct CwiseProductDenseReturnType {
+      typedef CwiseBinaryOp<internal::scalar_product_op<typename ScalarBinaryOpTraits<
+                                                          typename internal::traits<Derived>::Scalar,
+                                                          typename internal::traits<OtherDerived>::Scalar
+                                                        >::ReturnType>,
+                            const Derived,
+                            const OtherDerived
+                          > Type;
+    };
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE const typename CwiseProductDenseReturnType<OtherDerived>::Type
+    cwiseProduct(const MatrixBase<OtherDerived> &other) const;
 
     // sparse * diagonal
     template<typename OtherDerived>
-    const SparseDiagonalProduct<Derived,OtherDerived>
-    operator*(const DiagonalBase<OtherDerived> &other) const;
+    const Product<Derived,OtherDerived>
+    operator*(const DiagonalBase<OtherDerived> &other) const
+    { return Product<Derived,OtherDerived>(derived(), other.derived()); }
 
     // diagonal * sparse
     template<typename OtherDerived> friend
-    const SparseDiagonalProduct<OtherDerived,Derived>
+    const Product<OtherDerived,Derived>
     operator*(const DiagonalBase<OtherDerived> &lhs, const SparseMatrixBase& rhs)
-    { return SparseDiagonalProduct<OtherDerived,Derived>(lhs.derived(), rhs.derived()); }
-
-    /** dense * sparse (return a dense object unless it is an outer product) */
-    template<typename OtherDerived> friend
-    const typename DenseSparseProductReturnType<OtherDerived,Derived>::Type
-    operator*(const MatrixBase<OtherDerived>& lhs, const Derived& rhs)
-    { return typename DenseSparseProductReturnType<OtherDerived,Derived>::Type(lhs.derived(),rhs); }
-
-    /** sparse * dense (returns a dense object unless it is an outer product) */
+    { return Product<OtherDerived,Derived>(lhs.derived(), rhs.derived()); }
+    
+    // sparse * sparse
+    template<typename OtherDerived>
+    const Product<Derived,OtherDerived,AliasFreeProduct>
+    operator*(const SparseMatrixBase<OtherDerived> &other) const;
+    
+    // sparse * dense
     template<typename OtherDerived>
-    const typename SparseDenseProductReturnType<Derived,OtherDerived>::Type
+    const Product<Derived,OtherDerived>
     operator*(const MatrixBase<OtherDerived> &other) const
-    { return typename SparseDenseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived()); }
+    { return Product<Derived,OtherDerived>(derived(), other.derived()); }
+    
+    // dense * sparse
+    template<typename OtherDerived> friend
+    const Product<OtherDerived,Derived>
+    operator*(const MatrixBase<OtherDerived> &lhs, const SparseMatrixBase& rhs)
+    { return Product<OtherDerived,Derived>(lhs.derived(), rhs.derived()); }
     
      /** \returns an expression of P H P^-1 where H is the matrix represented by \c *this */
-    SparseSymmetricPermutationProduct<Derived,Upper|Lower> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& perm) const
+    SparseSymmetricPermutationProduct<Derived,Upper|Lower> twistedBy(const PermutationMatrix<Dynamic,Dynamic,StorageIndex>& perm) const
     {
       return SparseSymmetricPermutationProduct<Derived,Upper|Lower>(derived(), perm);
     }
 
     template<typename OtherDerived>
     Derived& operator*=(const SparseMatrixBase<OtherDerived>& other);
 
-    #ifdef EIGEN2_SUPPORT
-    // deprecated
-    template<typename OtherDerived>
-    typename internal::plain_matrix_type_column_major<OtherDerived>::type
-    solveTriangular(const MatrixBase<OtherDerived>& other) const;
-
-    // deprecated
-    template<typename OtherDerived>
-    void solveTriangularInPlace(MatrixBase<OtherDerived>& other) const;
-    #endif // EIGEN2_SUPPORT
-
     template<int Mode>
-    inline const SparseTriangularView<Derived, Mode> triangularView() const;
+    inline const TriangularView<const Derived, Mode> triangularView() const;
+    
+    template<unsigned int UpLo> struct SelfAdjointViewReturnType { typedef SparseSelfAdjointView<Derived, UpLo> Type; };
+    template<unsigned int UpLo> struct ConstSelfAdjointViewReturnType { typedef const SparseSelfAdjointView<const Derived, UpLo> Type; };
 
-    template<unsigned int UpLo> inline const SparseSelfAdjointView<Derived, UpLo> selfadjointView() const;
-    template<unsigned int UpLo> inline SparseSelfAdjointView<Derived, UpLo> selfadjointView();
+    template<unsigned int UpLo> inline 
+    typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
+    template<unsigned int UpLo> inline
+    typename SelfAdjointViewReturnType<UpLo>::Type selfadjointView();
 
     template<typename OtherDerived> Scalar dot(const MatrixBase<OtherDerived>& other) const;
     template<typename OtherDerived> Scalar dot(const SparseMatrixBase<OtherDerived>& other) const;
     RealScalar squaredNorm() const;
     RealScalar norm()  const;
     RealScalar blueNorm() const;
 
-    Transpose<Derived> transpose() { return derived(); }
-    const Transpose<const Derived> transpose() const { return derived(); }
-    const AdjointReturnType adjoint() const { return transpose(); }
+    TransposeReturnType transpose() { return TransposeReturnType(derived()); }
+    const ConstTransposeReturnType transpose() const { return ConstTransposeReturnType(derived()); }
+    const AdjointReturnType adjoint() const { return AdjointReturnType(transpose()); }
 
     // inner-vector
     typedef Block<Derived,IsRowMajor?1:Dynamic,IsRowMajor?Dynamic:1,true>       InnerVectorReturnType;
     typedef Block<const Derived,IsRowMajor?1:Dynamic,IsRowMajor?Dynamic:1,true> ConstInnerVectorReturnType;
     InnerVectorReturnType innerVector(Index outer);
     const ConstInnerVectorReturnType innerVector(Index outer) const;
 
     // set of inner-vectors
-    Block<Derived,Dynamic,Dynamic,true> innerVectors(Index outerStart, Index outerSize);
-    const Block<const Derived,Dynamic,Dynamic,true> innerVectors(Index outerStart, Index outerSize) const;
-
-    /** \internal use operator= */
-    template<typename DenseDerived>
-    void evalTo(MatrixBase<DenseDerived>& dst) const
-    {
-      dst.setZero();
-      for (Index j=0; j<outerSize(); ++j)
-        for (typename Derived::InnerIterator i(derived(),j); i; ++i)
-          dst.coeffRef(i.row(),i.col()) = i.value();
-    }
-
-    Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> toDense() const
-    {
-      return derived();
+    typedef Block<Derived,Dynamic,Dynamic,true> InnerVectorsReturnType;
+    typedef Block<const Derived,Dynamic,Dynamic,true> ConstInnerVectorsReturnType;
+    InnerVectorsReturnType innerVectors(Index outerStart, Index outerSize);
+    const ConstInnerVectorsReturnType innerVectors(Index outerStart, Index outerSize) const;
+
+    DenseMatrixType toDense() const
+    {
+      return DenseMatrixType(derived());
     }
 
     template<typename OtherDerived>
     bool isApprox(const SparseMatrixBase<OtherDerived>& other,
-                  const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
-    { return toDense().isApprox(other.toDense(),prec); }
+                  const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
     template<typename OtherDerived>
     bool isApprox(const MatrixBase<OtherDerived>& other,
                   const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
     { return toDense().isApprox(other,prec); }
@@ -439,14 +383,23 @@
       */
     inline const typename internal::eval<Derived>::type eval() const
     { return typename internal::eval<Derived>::type(derived()); }
 
     Scalar sum() const;
+    
+    inline const SparseView<Derived>
+    pruned(const Scalar& reference = Scalar(0), const RealScalar& epsilon = NumTraits<Scalar>::dummy_precision()) const;
 
   protected:
 
     bool m_isRValue;
+
+    static inline StorageIndex convert_index(const Index idx) {
+      return internal::convert_index<StorageIndex>(idx);
+    }
+  private:
+    template<typename Dest> void evalTo(Dest &) const;
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSEMATRIXBASE_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparsePermutation.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparsePermutation.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparsePermutation.h
@@ -14,135 +14,165 @@
 
 namespace Eigen { 
 
 namespace internal {
 
-template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
-struct traits<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
-{
-  typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
-  typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
-  typedef typename MatrixTypeNestedCleaned::Index Index;
-  enum {
-    SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
-    MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
-  };
-
-  typedef typename internal::conditional<MoveOuter,
-        SparseMatrix<Scalar,SrcStorageOrder,Index>,
-        SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> >::type ReturnType;
-};
-
-template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
-struct permut_sparsematrix_product_retval
- : public ReturnByValue<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
-{
-    typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
-    typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
-    typedef typename MatrixTypeNestedCleaned::Index Index;
-
-    enum {
-      SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
-      MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
-    };
-
-    permut_sparsematrix_product_retval(const PermutationType& perm, const MatrixType& matrix)
-      : m_permutation(perm), m_matrix(matrix)
-    {}
-
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
-
-    template<typename Dest> inline void evalTo(Dest& dst) const
-    {
-      if(MoveOuter)
-      {
-        SparseMatrix<Scalar,SrcStorageOrder,Index> tmp(m_matrix.rows(), m_matrix.cols());
-        Matrix<Index,Dynamic,1> sizes(m_matrix.outerSize());
-        for(Index j=0; j<m_matrix.outerSize(); ++j)
-        {
-          Index jp = m_permutation.indices().coeff(j);
-          sizes[((Side==OnTheLeft) ^ Transposed) ? jp : j] = m_matrix.innerVector(((Side==OnTheRight) ^ Transposed) ? jp : j).nonZeros();
-        }
-        tmp.reserve(sizes);
-        for(Index j=0; j<m_matrix.outerSize(); ++j)
-        {
-          Index jp = m_permutation.indices().coeff(j);
-          Index jsrc = ((Side==OnTheRight) ^ Transposed) ? jp : j;
-          Index jdst = ((Side==OnTheLeft) ^ Transposed) ? jp : j;
-          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,jsrc); it; ++it)
+template<typename ExpressionType, int Side, bool Transposed>
+struct permutation_matrix_product<ExpressionType, Side, Transposed, SparseShape>
+{
+    typedef typename nested_eval<ExpressionType, 1>::type MatrixType;
+    typedef typename remove_all<MatrixType>::type MatrixTypeCleaned;
+
+    typedef typename MatrixTypeCleaned::Scalar Scalar;
+    typedef typename MatrixTypeCleaned::StorageIndex StorageIndex;
+
+    enum {
+      SrcStorageOrder = MatrixTypeCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
+      MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
+    };
+    
+    typedef typename internal::conditional<MoveOuter,
+        SparseMatrix<Scalar,SrcStorageOrder,StorageIndex>,
+        SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,StorageIndex> >::type ReturnType;
+
+    template<typename Dest,typename PermutationType>
+    static inline void run(Dest& dst, const PermutationType& perm, const ExpressionType& xpr)
+    {
+      MatrixType mat(xpr);
+      if(MoveOuter)
+      {
+        SparseMatrix<Scalar,SrcStorageOrder,StorageIndex> tmp(mat.rows(), mat.cols());
+        Matrix<StorageIndex,Dynamic,1> sizes(mat.outerSize());
+        for(Index j=0; j<mat.outerSize(); ++j)
+        {
+          Index jp = perm.indices().coeff(j);
+          sizes[((Side==OnTheLeft) ^ Transposed) ? jp : j] = StorageIndex(mat.innerVector(((Side==OnTheRight) ^ Transposed) ? jp : j).nonZeros());
+        }
+        tmp.reserve(sizes);
+        for(Index j=0; j<mat.outerSize(); ++j)
+        {
+          Index jp = perm.indices().coeff(j);
+          Index jsrc = ((Side==OnTheRight) ^ Transposed) ? jp : j;
+          Index jdst = ((Side==OnTheLeft) ^ Transposed) ? jp : j;
+          for(typename MatrixTypeCleaned::InnerIterator it(mat,jsrc); it; ++it)
             tmp.insertByOuterInner(jdst,it.index()) = it.value();
         }
         dst = tmp;
       }
       else
       {
-        SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> tmp(m_matrix.rows(), m_matrix.cols());
-        Matrix<Index,Dynamic,1> sizes(tmp.outerSize());
+        SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,StorageIndex> tmp(mat.rows(), mat.cols());
+        Matrix<StorageIndex,Dynamic,1> sizes(tmp.outerSize());
         sizes.setZero();
-        PermutationMatrix<Dynamic,Dynamic,Index> perm;
+        PermutationMatrix<Dynamic,Dynamic,StorageIndex> perm_cpy;
         if((Side==OnTheLeft) ^ Transposed)
-          perm = m_permutation;
+          perm_cpy = perm;
         else
-          perm = m_permutation.transpose();
+          perm_cpy = perm.transpose();
 
-        for(Index j=0; j<m_matrix.outerSize(); ++j)
-          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it)
-            sizes[perm.indices().coeff(it.index())]++;
+        for(Index j=0; j<mat.outerSize(); ++j)
+          for(typename MatrixTypeCleaned::InnerIterator it(mat,j); it; ++it)
+            sizes[perm_cpy.indices().coeff(it.index())]++;
         tmp.reserve(sizes);
-        for(Index j=0; j<m_matrix.outerSize(); ++j)
-          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it)
-            tmp.insertByOuterInner(perm.indices().coeff(it.index()),j) = it.value();
+        for(Index j=0; j<mat.outerSize(); ++j)
+          for(typename MatrixTypeCleaned::InnerIterator it(mat,j); it; ++it)
+            tmp.insertByOuterInner(perm_cpy.indices().coeff(it.index()),j) = it.value();
         dst = tmp;
       }
     }
-
-  protected:
-    const PermutationType& m_permutation;
-    typename MatrixType::Nested m_matrix;
 };
 
 }
 
+namespace internal {
+
+template <int ProductTag> struct product_promote_storage_type<Sparse,             PermutationStorage, ProductTag> { typedef Sparse ret; };
+template <int ProductTag> struct product_promote_storage_type<PermutationStorage, Sparse,             ProductTag> { typedef Sparse ret; };
+
+// TODO, the following two overloads are only needed to define the right temporary type through 
+// typename traits<permutation_sparse_matrix_product<Rhs,Lhs,OnTheRight,false> >::ReturnType
+// whereas it should be correctly handled by traits<Product<> >::PlainObject
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, AliasFreeProduct>, ProductTag, PermutationShape, SparseShape>
+  : public evaluator<typename permutation_matrix_product<Rhs,OnTheLeft,false,SparseShape>::ReturnType>
+{
+  typedef Product<Lhs, Rhs, AliasFreeProduct> XprType;
+  typedef typename permutation_matrix_product<Rhs,OnTheLeft,false,SparseShape>::ReturnType PlainObject;
+  typedef evaluator<PlainObject> Base;
+
+  enum {
+    Flags = Base::Flags | EvalBeforeNestingBit
+  };
+
+  explicit product_evaluator(const XprType& xpr)
+    : m_result(xpr.rows(), xpr.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    generic_product_impl<Lhs, Rhs, PermutationShape, SparseShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
+  }
+
+protected:
+  PlainObject m_result;
+};
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct product_evaluator<Product<Lhs, Rhs, AliasFreeProduct>, ProductTag, SparseShape, PermutationShape >
+  : public evaluator<typename permutation_matrix_product<Lhs,OnTheRight,false,SparseShape>::ReturnType>
+{
+  typedef Product<Lhs, Rhs, AliasFreeProduct> XprType;
+  typedef typename permutation_matrix_product<Lhs,OnTheRight,false,SparseShape>::ReturnType PlainObject;
+  typedef evaluator<PlainObject> Base;
+
+  enum {
+    Flags = Base::Flags | EvalBeforeNestingBit
+  };
+
+  explicit product_evaluator(const XprType& xpr)
+    : m_result(xpr.rows(), xpr.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    generic_product_impl<Lhs, Rhs, SparseShape, PermutationShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
+  }
+
+protected:
+  PlainObject m_result;
+};
 
+} // end namespace internal
 
 /** \returns the matrix with the permutation applied to the columns
   */
 template<typename SparseDerived, typename PermDerived>
-inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>
+inline const Product<SparseDerived, PermDerived, AliasFreeProduct>
 operator*(const SparseMatrixBase<SparseDerived>& matrix, const PermutationBase<PermDerived>& perm)
-{
-  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>(perm, matrix.derived());
-}
+{ return Product<SparseDerived, PermDerived, AliasFreeProduct>(matrix.derived(), perm.derived()); }
 
 /** \returns the matrix with the permutation applied to the rows
   */
 template<typename SparseDerived, typename PermDerived>
-inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>
+inline const Product<PermDerived, SparseDerived, AliasFreeProduct>
 operator*( const PermutationBase<PermDerived>& perm, const SparseMatrixBase<SparseDerived>& matrix)
-{
-  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>(perm, matrix.derived());
-}
-
+{ return  Product<PermDerived, SparseDerived, AliasFreeProduct>(perm.derived(), matrix.derived()); }
 
 
 /** \returns the matrix with the inverse permutation applied to the columns.
   */
-template<typename SparseDerived, typename PermDerived>
-inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>
-operator*(const SparseMatrixBase<SparseDerived>& matrix, const Transpose<PermutationBase<PermDerived> >& tperm)
+template<typename SparseDerived, typename PermutationType>
+inline const Product<SparseDerived, Inverse<PermutationType>, AliasFreeProduct>
+operator*(const SparseMatrixBase<SparseDerived>& matrix, const InverseImpl<PermutationType, PermutationStorage>& tperm)
 {
-  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>(tperm.nestedPermutation(), matrix.derived());
+  return Product<SparseDerived, Inverse<PermutationType>, AliasFreeProduct>(matrix.derived(), tperm.derived());
 }
 
 /** \returns the matrix with the inverse permutation applied to the rows.
   */
-template<typename SparseDerived, typename PermDerived>
-inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>
-operator*(const Transpose<PermutationBase<PermDerived> >& tperm, const SparseMatrixBase<SparseDerived>& matrix)
+template<typename SparseDerived, typename PermutationType>
+inline const Product<Inverse<PermutationType>, SparseDerived, AliasFreeProduct>
+operator*(const InverseImpl<PermutationType,PermutationStorage>& tperm, const SparseMatrixBase<SparseDerived>& matrix)
 {
-  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>(tperm.nestedPermutation(), matrix.derived());
+  return Product<Inverse<PermutationType>, SparseDerived, AliasFreeProduct>(tperm.derived(), matrix.derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSE_SELFADJOINTVIEW_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseProduct.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseProduct.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseProduct.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -10,162 +10,10 @@
 #ifndef EIGEN_SPARSEPRODUCT_H
 #define EIGEN_SPARSEPRODUCT_H
 
 namespace Eigen { 
 
-template<typename Lhs, typename Rhs>
-struct SparseSparseProductReturnType
-{
-  typedef typename internal::traits<Lhs>::Scalar Scalar;
-  typedef typename internal::traits<Lhs>::Index Index;
-  enum {
-    LhsRowMajor = internal::traits<Lhs>::Flags & RowMajorBit,
-    RhsRowMajor = internal::traits<Rhs>::Flags & RowMajorBit,
-    TransposeRhs = (!LhsRowMajor) && RhsRowMajor,
-    TransposeLhs = LhsRowMajor && (!RhsRowMajor)
-  };
-
-  typedef typename internal::conditional<TransposeLhs,
-    SparseMatrix<Scalar,0,Index>,
-    typename internal::nested<Lhs,Rhs::RowsAtCompileTime>::type>::type LhsNested;
-
-  typedef typename internal::conditional<TransposeRhs,
-    SparseMatrix<Scalar,0,Index>,
-    typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type>::type RhsNested;
-
-  typedef SparseSparseProduct<LhsNested, RhsNested> Type;
-};
-
-namespace internal {
-template<typename LhsNested, typename RhsNested>
-struct traits<SparseSparseProduct<LhsNested, RhsNested> >
-{
-  typedef MatrixXpr XprKind;
-  // clean the nested types:
-  typedef typename remove_all<LhsNested>::type _LhsNested;
-  typedef typename remove_all<RhsNested>::type _RhsNested;
-  typedef typename _LhsNested::Scalar Scalar;
-  typedef typename promote_index_type<typename traits<_LhsNested>::Index,
-                                         typename traits<_RhsNested>::Index>::type Index;
-
-  enum {
-    LhsCoeffReadCost = _LhsNested::CoeffReadCost,
-    RhsCoeffReadCost = _RhsNested::CoeffReadCost,
-    LhsFlags = _LhsNested::Flags,
-    RhsFlags = _RhsNested::Flags,
-
-    RowsAtCompileTime    = _LhsNested::RowsAtCompileTime,
-    ColsAtCompileTime    = _RhsNested::ColsAtCompileTime,
-    MaxRowsAtCompileTime = _LhsNested::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = _RhsNested::MaxColsAtCompileTime,
-
-    InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(_LhsNested::ColsAtCompileTime, _RhsNested::RowsAtCompileTime),
-
-    EvalToRowMajor = (RhsFlags & LhsFlags & RowMajorBit),
-
-    RemovedBits = ~(EvalToRowMajor ? 0 : RowMajorBit),
-
-    Flags = (int(LhsFlags | RhsFlags) & HereditaryBits & RemovedBits)
-          | EvalBeforeAssigningBit
-          | EvalBeforeNestingBit,
-
-    CoeffReadCost = Dynamic
-  };
-
-  typedef Sparse StorageKind;
-};
-
-} // end namespace internal
-
-template<typename LhsNested, typename RhsNested>
-class SparseSparseProduct : internal::no_assignment_operator,
-  public SparseMatrixBase<SparseSparseProduct<LhsNested, RhsNested> >
-{
-  public:
-
-    typedef SparseMatrixBase<SparseSparseProduct> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(SparseSparseProduct)
-
-  private:
-
-    typedef typename internal::traits<SparseSparseProduct>::_LhsNested _LhsNested;
-    typedef typename internal::traits<SparseSparseProduct>::_RhsNested _RhsNested;
-
-  public:
-
-    template<typename Lhs, typename Rhs>
-    EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs)
-      : m_lhs(lhs), m_rhs(rhs), m_tolerance(0), m_conservative(true)
-    {
-      init();
-    }
-
-    template<typename Lhs, typename Rhs>
-    EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs, const RealScalar& tolerance)
-      : m_lhs(lhs), m_rhs(rhs), m_tolerance(tolerance), m_conservative(false)
-    {
-      init();
-    }
-
-    SparseSparseProduct pruned(const Scalar& reference = 0, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) const
-    {
-      using std::abs;
-      return SparseSparseProduct(m_lhs,m_rhs,abs(reference)*epsilon);
-    }
-
-    template<typename Dest>
-    void evalTo(Dest& result) const
-    {
-      if(m_conservative)
-        internal::conservative_sparse_sparse_product_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result);
-      else
-        internal::sparse_sparse_product_with_pruning_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result,m_tolerance);
-    }
-
-    EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
-
-    EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
-    EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
-
-  protected:
-    void init()
-    {
-      eigen_assert(m_lhs.cols() == m_rhs.rows());
-
-      enum {
-        ProductIsValid = _LhsNested::ColsAtCompileTime==Dynamic
-                      || _RhsNested::RowsAtCompileTime==Dynamic
-                      || int(_LhsNested::ColsAtCompileTime)==int(_RhsNested::RowsAtCompileTime),
-        AreVectors = _LhsNested::IsVectorAtCompileTime && _RhsNested::IsVectorAtCompileTime,
-        SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(_LhsNested,_RhsNested)
-      };
-      // note to the lost user:
-      //    * for a dot product use: v1.dot(v2)
-      //    * for a coeff-wise product use: v1.cwise()*v2
-      EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
-        INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
-      EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
-        INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
-      EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
-    }
-
-    LhsNested m_lhs;
-    RhsNested m_rhs;
-    RealScalar m_tolerance;
-    bool m_conservative;
-};
-
-// sparse = sparse * sparse
-template<typename Derived>
-template<typename Lhs, typename Rhs>
-inline Derived& SparseMatrixBase<Derived>::operator=(const SparseSparseProduct<Lhs,Rhs>& product)
-{
-  product.evalTo(derived());
-  return derived();
-}
-
 /** \returns an expression of the product of two sparse matrices.
   * By default a conservative product preserving the symbolic non zeros is performed.
   * The automatic pruning of the small values can be achieved by calling the pruned() function
   * in which case a totally different product algorithm is employed:
   * \code
@@ -175,14 +23,147 @@
   * \endcode
   * where \c ref is a meaningful non zero reference value.
   * */
 template<typename Derived>
 template<typename OtherDerived>
-inline const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type
+inline const Product<Derived,OtherDerived,AliasFreeProduct>
 SparseMatrixBase<Derived>::operator*(const SparseMatrixBase<OtherDerived> &other) const
 {
-  return typename SparseSparseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
+  return Product<Derived,OtherDerived,AliasFreeProduct>(derived(), other.derived());
 }
 
+namespace internal {
+
+// sparse * sparse
+template<typename Lhs, typename Rhs, int ProductType>
+struct generic_product_impl<Lhs, Rhs, SparseShape, SparseShape, ProductType>
+{
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    evalTo(dst, lhs, rhs, typename evaluator_traits<Dest>::Shape());
+  }
+
+  // dense += sparse * sparse
+  template<typename Dest,typename ActualLhs>
+  static void addTo(Dest& dst, const ActualLhs& lhs, const Rhs& rhs, typename enable_if<is_same<typename evaluator_traits<Dest>::Shape,DenseShape>::value,int*>::type* = 0)
+  {
+    typedef typename nested_eval<ActualLhs,Dynamic>::type LhsNested;
+    typedef typename nested_eval<Rhs,Dynamic>::type RhsNested;
+    LhsNested lhsNested(lhs);
+    RhsNested rhsNested(rhs);
+    internal::sparse_sparse_to_dense_product_selector<typename remove_all<LhsNested>::type,
+                                                      typename remove_all<RhsNested>::type, Dest>::run(lhsNested,rhsNested,dst);
+  }
+
+  // dense -= sparse * sparse
+  template<typename Dest>
+  static void subTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, typename enable_if<is_same<typename evaluator_traits<Dest>::Shape,DenseShape>::value,int*>::type* = 0)
+  {
+    addTo(dst, -lhs, rhs);
+  }
+
+protected:
+
+  // sparse = sparse * sparse
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, SparseShape)
+  {
+    typedef typename nested_eval<Lhs,Dynamic>::type LhsNested;
+    typedef typename nested_eval<Rhs,Dynamic>::type RhsNested;
+    LhsNested lhsNested(lhs);
+    RhsNested rhsNested(rhs);
+    internal::conservative_sparse_sparse_product_selector<typename remove_all<LhsNested>::type,
+                                                          typename remove_all<RhsNested>::type, Dest>::run(lhsNested,rhsNested,dst);
+  }
+
+  // dense = sparse * sparse
+  template<typename Dest>
+  static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, DenseShape)
+  {
+    dst.setZero();
+    addTo(dst, lhs, rhs);
+  }
+};
+
+// sparse * sparse-triangular
+template<typename Lhs, typename Rhs, int ProductType>
+struct generic_product_impl<Lhs, Rhs, SparseShape, SparseTriangularShape, ProductType>
+ : public generic_product_impl<Lhs, Rhs, SparseShape, SparseShape, ProductType>
+{};
+
+// sparse-triangular * sparse
+template<typename Lhs, typename Rhs, int ProductType>
+struct generic_product_impl<Lhs, Rhs, SparseTriangularShape, SparseShape, ProductType>
+ : public generic_product_impl<Lhs, Rhs, SparseShape, SparseShape, ProductType>
+{};
+
+// dense = sparse-product (can be sparse*sparse, sparse*perm, etc.)
+template< typename DstXprType, typename Lhs, typename Rhs>
+struct Assignment<DstXprType, Product<Lhs,Rhs,AliasFreeProduct>, internal::assign_op<typename DstXprType::Scalar,typename Product<Lhs,Rhs,AliasFreeProduct>::Scalar>, Sparse2Dense>
+{
+  typedef Product<Lhs,Rhs,AliasFreeProduct> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &)
+  {
+    Index dstRows = src.rows();
+    Index dstCols = src.cols();
+    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
+      dst.resize(dstRows, dstCols);
+    
+    generic_product_impl<Lhs, Rhs>::evalTo(dst,src.lhs(),src.rhs());
+  }
+};
+
+// dense += sparse-product (can be sparse*sparse, sparse*perm, etc.)
+template< typename DstXprType, typename Lhs, typename Rhs>
+struct Assignment<DstXprType, Product<Lhs,Rhs,AliasFreeProduct>, internal::add_assign_op<typename DstXprType::Scalar,typename Product<Lhs,Rhs,AliasFreeProduct>::Scalar>, Sparse2Dense>
+{
+  typedef Product<Lhs,Rhs,AliasFreeProduct> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &)
+  {
+    generic_product_impl<Lhs, Rhs>::addTo(dst,src.lhs(),src.rhs());
+  }
+};
+
+// dense -= sparse-product (can be sparse*sparse, sparse*perm, etc.)
+template< typename DstXprType, typename Lhs, typename Rhs>
+struct Assignment<DstXprType, Product<Lhs,Rhs,AliasFreeProduct>, internal::sub_assign_op<typename DstXprType::Scalar,typename Product<Lhs,Rhs,AliasFreeProduct>::Scalar>, Sparse2Dense>
+{
+  typedef Product<Lhs,Rhs,AliasFreeProduct> SrcXprType;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &)
+  {
+    generic_product_impl<Lhs, Rhs>::subTo(dst,src.lhs(),src.rhs());
+  }
+};
+
+template<typename Lhs, typename Rhs, int Options>
+struct unary_evaluator<SparseView<Product<Lhs, Rhs, Options> >, IteratorBased>
+ : public evaluator<typename Product<Lhs, Rhs, DefaultProduct>::PlainObject>
+{
+  typedef SparseView<Product<Lhs, Rhs, Options> > XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  typedef evaluator<PlainObject> Base;
+
+  explicit unary_evaluator(const XprType& xpr)
+    : m_result(xpr.rows(), xpr.cols())
+  {
+    using std::abs;
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    typedef typename nested_eval<Lhs,Dynamic>::type LhsNested;
+    typedef typename nested_eval<Rhs,Dynamic>::type RhsNested;
+    LhsNested lhsNested(xpr.nestedExpression().lhs());
+    RhsNested rhsNested(xpr.nestedExpression().rhs());
+
+    internal::sparse_sparse_product_with_pruning_selector<typename remove_all<LhsNested>::type,
+                                                          typename remove_all<RhsNested>::type, PlainObject>::run(lhsNested,rhsNested,m_result,
+                                                                                                                  abs(xpr.reference())*xpr.epsilon());
+  }
+
+protected:
+  PlainObject m_result;
+};
+
+} // end namespace internal
+
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSEPRODUCT_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseRedux.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseRedux.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseRedux.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -16,30 +16,34 @@
 typename internal::traits<Derived>::Scalar
 SparseMatrixBase<Derived>::sum() const
 {
   eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix");
   Scalar res(0);
+  internal::evaluator<Derived> thisEval(derived());
   for (Index j=0; j<outerSize(); ++j)
-    for (typename Derived::InnerIterator iter(derived(),j); iter; ++iter)
+    for (typename internal::evaluator<Derived>::InnerIterator iter(thisEval,j); iter; ++iter)
       res += iter.value();
   return res;
 }
 
 template<typename _Scalar, int _Options, typename _Index>
 typename internal::traits<SparseMatrix<_Scalar,_Options,_Index> >::Scalar
 SparseMatrix<_Scalar,_Options,_Index>::sum() const
 {
   eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix");
-  return Matrix<Scalar,1,Dynamic>::Map(&m_data.value(0), m_data.size()).sum();
+  if(this->isCompressed())
+    return Matrix<Scalar,1,Dynamic>::Map(m_data.valuePtr(), m_data.size()).sum();
+  else
+    return Base::sum();
 }
 
 template<typename _Scalar, int _Options, typename _Index>
 typename internal::traits<SparseVector<_Scalar,_Options, _Index> >::Scalar
 SparseVector<_Scalar,_Options,_Index>::sum() const
 {
   eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix");
-  return Matrix<Scalar,1,Dynamic>::Map(&m_data.value(0), m_data.size()).sum();
+  return Matrix<Scalar,1,Dynamic>::Map(m_data.valuePtr(), m_data.size()).sum();
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSEREDUX_H

ADDED   3rd_party/eigen/Eigen/src/SparseCore/SparseRef.h
Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseRef.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseRef.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseRef.h
@@ -0,0 +1,397 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_REF_H
+#define EIGEN_SPARSE_REF_H
+
+namespace Eigen {
+
+enum {
+  StandardCompressedFormat = 2 /**< used by Ref<SparseMatrix> to specify whether the input storage must be in standard compressed form */
+};
+  
+namespace internal {
+
+template<typename Derived> class SparseRefBase;
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int _Options, typename _StrideType>
+struct traits<Ref<SparseMatrix<MatScalar,MatOptions,MatIndex>, _Options, _StrideType> >
+  : public traits<SparseMatrix<MatScalar,MatOptions,MatIndex> >
+{
+  typedef SparseMatrix<MatScalar,MatOptions,MatIndex> PlainObjectType;
+  enum {
+    Options = _Options,
+    Flags = traits<PlainObjectType>::Flags | CompressedAccessBit | NestByRefBit
+  };
+
+  template<typename Derived> struct match {
+    enum {
+      StorageOrderMatch = PlainObjectType::IsVectorAtCompileTime || Derived::IsVectorAtCompileTime || ((PlainObjectType::Flags&RowMajorBit)==(Derived::Flags&RowMajorBit)),
+      MatchAtCompileTime = (Derived::Flags&CompressedAccessBit) && StorageOrderMatch
+    };
+    typedef typename internal::conditional<MatchAtCompileTime,internal::true_type,internal::false_type>::type type;
+  };
+  
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int _Options, typename _StrideType>
+struct traits<Ref<const SparseMatrix<MatScalar,MatOptions,MatIndex>, _Options, _StrideType> >
+  : public traits<Ref<SparseMatrix<MatScalar,MatOptions,MatIndex>, _Options, _StrideType> >
+{
+  enum {
+    Flags = (traits<SparseMatrix<MatScalar,MatOptions,MatIndex> >::Flags | CompressedAccessBit | NestByRefBit) & ~LvalueBit
+  };
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int _Options, typename _StrideType>
+struct traits<Ref<SparseVector<MatScalar,MatOptions,MatIndex>, _Options, _StrideType> >
+  : public traits<SparseVector<MatScalar,MatOptions,MatIndex> >
+{
+  typedef SparseVector<MatScalar,MatOptions,MatIndex> PlainObjectType;
+  enum {
+    Options = _Options,
+    Flags = traits<PlainObjectType>::Flags | CompressedAccessBit | NestByRefBit
+  };
+
+  template<typename Derived> struct match {
+    enum {
+      MatchAtCompileTime = (Derived::Flags&CompressedAccessBit) && Derived::IsVectorAtCompileTime
+    };
+    typedef typename internal::conditional<MatchAtCompileTime,internal::true_type,internal::false_type>::type type;
+  };
+
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int _Options, typename _StrideType>
+struct traits<Ref<const SparseVector<MatScalar,MatOptions,MatIndex>, _Options, _StrideType> >
+  : public traits<Ref<SparseVector<MatScalar,MatOptions,MatIndex>, _Options, _StrideType> >
+{
+  enum {
+    Flags = (traits<SparseVector<MatScalar,MatOptions,MatIndex> >::Flags | CompressedAccessBit | NestByRefBit) & ~LvalueBit
+  };
+};
+
+template<typename Derived>
+struct traits<SparseRefBase<Derived> > : public traits<Derived> {};
+
+template<typename Derived> class SparseRefBase
+  : public SparseMapBase<Derived>
+{
+public:
+
+  typedef SparseMapBase<Derived> Base;
+  EIGEN_SPARSE_PUBLIC_INTERFACE(SparseRefBase)
+
+  SparseRefBase()
+    : Base(RowsAtCompileTime==Dynamic?0:RowsAtCompileTime,ColsAtCompileTime==Dynamic?0:ColsAtCompileTime, 0, 0, 0, 0, 0)
+  {}
+  
+protected:
+
+  template<typename Expression>
+  void construct(Expression& expr)
+  {
+    if(expr.outerIndexPtr()==0)
+      ::new (static_cast<Base*>(this)) Base(expr.size(), expr.nonZeros(), expr.innerIndexPtr(), expr.valuePtr());
+    else
+      ::new (static_cast<Base*>(this)) Base(expr.rows(), expr.cols(), expr.nonZeros(), expr.outerIndexPtr(), expr.innerIndexPtr(), expr.valuePtr(), expr.innerNonZeroPtr());
+  }
+};
+
+} // namespace internal
+
+
+/** 
+  * \ingroup SparseCore_Module
+  *
+  * \brief A sparse matrix expression referencing an existing sparse expression
+  *
+  * \tparam SparseMatrixType the equivalent sparse matrix type of the referenced data, it must be a template instance of class SparseMatrix.
+  * \tparam Options specifies whether the a standard compressed format is required \c Options is  \c #StandardCompressedFormat, or \c 0.
+  *                The default is \c 0.
+  *
+  * \sa class Ref
+  */
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+class Ref<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType >
+  : public internal::SparseRefBase<Ref<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType > >
+#else
+template<typename SparseMatrixType, int Options>
+class Ref<SparseMatrixType, Options>
+  : public SparseMapBase<Derived,WriteAccessors> // yes, that's weird to use Derived here, but that works!
+#endif
+{
+    typedef SparseMatrix<MatScalar,MatOptions,MatIndex> PlainObjectType;
+    typedef internal::traits<Ref> Traits;
+    template<int OtherOptions>
+    inline Ref(const SparseMatrix<MatScalar,OtherOptions,MatIndex>& expr);
+    template<int OtherOptions>
+    inline Ref(const MappedSparseMatrix<MatScalar,OtherOptions,MatIndex>& expr);
+  public:
+
+    typedef internal::SparseRefBase<Ref> Base;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(Ref)
+
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<int OtherOptions>
+    inline Ref(SparseMatrix<MatScalar,OtherOptions,MatIndex>& expr)
+    {
+      EIGEN_STATIC_ASSERT(bool(Traits::template match<SparseMatrix<MatScalar,OtherOptions,MatIndex> >::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
+      eigen_assert( ((Options & int(StandardCompressedFormat))==0) || (expr.isCompressed()) );
+      Base::construct(expr.derived());
+    }
+    
+    template<int OtherOptions>
+    inline Ref(MappedSparseMatrix<MatScalar,OtherOptions,MatIndex>& expr)
+    {
+      EIGEN_STATIC_ASSERT(bool(Traits::template match<SparseMatrix<MatScalar,OtherOptions,MatIndex> >::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
+      eigen_assert( ((Options & int(StandardCompressedFormat))==0) || (expr.isCompressed()) );
+      Base::construct(expr.derived());
+    }
+    
+    template<typename Derived>
+    inline Ref(const SparseCompressedBase<Derived>& expr)
+    #else
+    /** Implicit constructor from any sparse expression (2D matrix or 1D vector) */
+    template<typename Derived>
+    inline Ref(SparseCompressedBase<Derived>& expr)
+    #endif
+    {
+      EIGEN_STATIC_ASSERT(bool(internal::is_lvalue<Derived>::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
+      EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
+      eigen_assert( ((Options & int(StandardCompressedFormat))==0) || (expr.isCompressed()) );
+      Base::construct(expr.const_cast_derived());
+    }
+};
+
+// this is the const ref version
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+class Ref<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType>
+  : public internal::SparseRefBase<Ref<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+{
+    typedef SparseMatrix<MatScalar,MatOptions,MatIndex> TPlainObjectType;
+    typedef internal::traits<Ref> Traits;
+  public:
+
+    typedef internal::SparseRefBase<Ref> Base;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(Ref)
+
+    template<typename Derived>
+    inline Ref(const SparseMatrixBase<Derived>& expr) : m_hasCopy(false)
+    {
+      construct(expr.derived(), typename Traits::template match<Derived>::type());
+    }
+
+    inline Ref(const Ref& other) : Base(other), m_hasCopy(false) {
+      // copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy
+    }
+
+    template<typename OtherRef>
+    inline Ref(const RefBase<OtherRef>& other) : m_hasCopy(false) {
+      construct(other.derived(), typename Traits::template match<OtherRef>::type());
+    }
+
+    ~Ref() {
+      if(m_hasCopy) {
+        TPlainObjectType* obj = reinterpret_cast<TPlainObjectType*>(m_object_bytes);
+        obj->~TPlainObjectType();
+      }
+    }
+
+  protected:
+
+    template<typename Expression>
+    void construct(const Expression& expr,internal::true_type)
+    {
+      if((Options & int(StandardCompressedFormat)) && (!expr.isCompressed()))
+      {
+        TPlainObjectType* obj = reinterpret_cast<TPlainObjectType*>(m_object_bytes);
+        ::new (obj) TPlainObjectType(expr);
+        m_hasCopy = true;
+        Base::construct(*obj);
+      }
+      else
+      {
+        Base::construct(expr);
+      }
+    }
+
+    template<typename Expression>
+    void construct(const Expression& expr, internal::false_type)
+    {
+      TPlainObjectType* obj = reinterpret_cast<TPlainObjectType*>(m_object_bytes);
+      ::new (obj) TPlainObjectType(expr);
+      m_hasCopy = true;
+      Base::construct(*obj);
+    }
+
+  protected:
+    char m_object_bytes[sizeof(TPlainObjectType)];
+    bool m_hasCopy;
+};
+
+
+
+/**
+  * \ingroup SparseCore_Module
+  *
+  * \brief A sparse vector expression referencing an existing sparse vector expression
+  *
+  * \tparam SparseVectorType the equivalent sparse vector type of the referenced data, it must be a template instance of class SparseVector.
+  *
+  * \sa class Ref
+  */
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+class Ref<SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType >
+  : public internal::SparseRefBase<Ref<SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType > >
+#else
+template<typename SparseVectorType>
+class Ref<SparseVectorType>
+  : public SparseMapBase<Derived,WriteAccessors>
+#endif
+{
+    typedef SparseVector<MatScalar,MatOptions,MatIndex> PlainObjectType;
+    typedef internal::traits<Ref> Traits;
+    template<int OtherOptions>
+    inline Ref(const SparseVector<MatScalar,OtherOptions,MatIndex>& expr);
+  public:
+
+    typedef internal::SparseRefBase<Ref> Base;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(Ref)
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<int OtherOptions>
+    inline Ref(SparseVector<MatScalar,OtherOptions,MatIndex>& expr)
+    {
+      EIGEN_STATIC_ASSERT(bool(Traits::template match<SparseVector<MatScalar,OtherOptions,MatIndex> >::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
+      Base::construct(expr.derived());
+    }
+
+    template<typename Derived>
+    inline Ref(const SparseCompressedBase<Derived>& expr)
+    #else
+    /** Implicit constructor from any 1D sparse vector expression */
+    template<typename Derived>
+    inline Ref(SparseCompressedBase<Derived>& expr)
+    #endif
+    {
+      EIGEN_STATIC_ASSERT(bool(internal::is_lvalue<Derived>::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
+      EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
+      Base::construct(expr.const_cast_derived());
+    }
+};
+
+// this is the const ref version
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+class Ref<const SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType>
+  : public internal::SparseRefBase<Ref<const SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+{
+    typedef SparseVector<MatScalar,MatOptions,MatIndex> TPlainObjectType;
+    typedef internal::traits<Ref> Traits;
+  public:
+
+    typedef internal::SparseRefBase<Ref> Base;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(Ref)
+
+    template<typename Derived>
+    inline Ref(const SparseMatrixBase<Derived>& expr) : m_hasCopy(false)
+    {
+      construct(expr.derived(), typename Traits::template match<Derived>::type());
+    }
+
+    inline Ref(const Ref& other) : Base(other), m_hasCopy(false) {
+      // copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy
+    }
+
+    template<typename OtherRef>
+    inline Ref(const RefBase<OtherRef>& other) : m_hasCopy(false) {
+      construct(other.derived(), typename Traits::template match<OtherRef>::type());
+    }
+
+    ~Ref() {
+      if(m_hasCopy) {
+        TPlainObjectType* obj = reinterpret_cast<TPlainObjectType*>(m_object_bytes);
+        obj->~TPlainObjectType();
+      }
+    }
+
+  protected:
+
+    template<typename Expression>
+    void construct(const Expression& expr,internal::true_type)
+    {
+      Base::construct(expr);
+    }
+
+    template<typename Expression>
+    void construct(const Expression& expr, internal::false_type)
+    {
+      TPlainObjectType* obj = reinterpret_cast<TPlainObjectType*>(m_object_bytes);
+      ::new (obj) TPlainObjectType(expr);
+      m_hasCopy = true;
+      Base::construct(*obj);
+    }
+
+  protected:
+    char m_object_bytes[sizeof(TPlainObjectType)];
+    bool m_hasCopy;
+};
+
+namespace internal {
+
+// FIXME shall we introduce a general evaluatior_ref that we can specialize for any sparse object once, and thus remove this copy-pasta thing...
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+struct evaluator<Ref<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+  : evaluator<SparseCompressedBase<Ref<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> > >
+{
+  typedef evaluator<SparseCompressedBase<Ref<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> > > Base;
+  typedef Ref<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> XprType;  
+  evaluator() : Base() {}
+  explicit evaluator(const XprType &mat) : Base(mat) {}
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+struct evaluator<Ref<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+  : evaluator<SparseCompressedBase<Ref<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> > >
+{
+  typedef evaluator<SparseCompressedBase<Ref<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> > > Base;
+  typedef Ref<const SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType> XprType;  
+  evaluator() : Base() {}
+  explicit evaluator(const XprType &mat) : Base(mat) {}
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+struct evaluator<Ref<SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+  : evaluator<SparseCompressedBase<Ref<SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> > >
+{
+  typedef evaluator<SparseCompressedBase<Ref<SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> > > Base;
+  typedef Ref<SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> XprType;
+  evaluator() : Base() {}
+  explicit evaluator(const XprType &mat) : Base(mat) {}
+};
+
+template<typename MatScalar, int MatOptions, typename MatIndex, int Options, typename StrideType>
+struct evaluator<Ref<const SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> >
+  : evaluator<SparseCompressedBase<Ref<const SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> > >
+{
+  typedef evaluator<SparseCompressedBase<Ref<const SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> > > Base;
+  typedef Ref<const SparseVector<MatScalar,MatOptions,MatIndex>, Options, StrideType> XprType;
+  evaluator() : Base() {}
+  explicit evaluator(const XprType &mat) : Base(mat) {}
+};
+
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_REF_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h
@@ -1,114 +1,116 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_SELFADJOINTVIEW_H
 #define EIGEN_SPARSE_SELFADJOINTVIEW_H
 
 namespace Eigen { 
-
+  
 /** \ingroup SparseCore_Module
   * \class SparseSelfAdjointView
   *
   * \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix.
   *
   * \param MatrixType the type of the dense matrix storing the coefficients
-  * \param UpLo can be either \c #Lower or \c #Upper
+  * \param Mode can be either \c #Lower or \c #Upper
   *
   * This class is an expression of a sefladjoint matrix from a triangular part of a matrix
   * with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView()
   * and most of the time this is the only way that it is used.
   *
   * \sa SparseMatrixBase::selfadjointView()
   */
-template<typename Lhs, typename Rhs, int UpLo>
-class SparseSelfAdjointTimeDenseProduct;
-
-template<typename Lhs, typename Rhs, int UpLo>
-class DenseTimeSparseSelfAdjointProduct;
-
 namespace internal {
   
-template<typename MatrixType, unsigned int UpLo>
-struct traits<SparseSelfAdjointView<MatrixType,UpLo> > : traits<MatrixType> {
+template<typename MatrixType, unsigned int Mode>
+struct traits<SparseSelfAdjointView<MatrixType,Mode> > : traits<MatrixType> {
 };
 
-template<int SrcUpLo,int DstUpLo,typename MatrixType,int DestOrder>
-void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0);
+template<int SrcMode,int DstMode,typename MatrixType,int DestOrder>
+void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm = 0);
 
-template<int UpLo,typename MatrixType,int DestOrder>
-void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0);
+template<int Mode,typename MatrixType,int DestOrder>
+void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm = 0);
 
 }
 
-template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
-  : public EigenBase<SparseSelfAdjointView<MatrixType,UpLo> >
+template<typename MatrixType, unsigned int _Mode> class SparseSelfAdjointView
+  : public EigenBase<SparseSelfAdjointView<MatrixType,_Mode> >
 {
   public:
+    
+    enum {
+      Mode = _Mode,
+      TransposeMode = ((Mode & Upper) ? Lower : 0) | ((Mode & Lower) ? Upper : 0),
+      RowsAtCompileTime = internal::traits<SparseSelfAdjointView>::RowsAtCompileTime,
+      ColsAtCompileTime = internal::traits<SparseSelfAdjointView>::ColsAtCompileTime
+    };
 
+    typedef EigenBase<SparseSelfAdjointView> Base;
     typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
-    typedef Matrix<Index,Dynamic,1> VectorI;
-    typedef typename MatrixType::Nested MatrixTypeNested;
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    typedef Matrix<StorageIndex,Dynamic,1> VectorI;
+    typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;
     typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
-
-    inline SparseSelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
+    
+    explicit inline SparseSelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
     {
       eigen_assert(rows()==cols() && "SelfAdjointView is only for squared matrices");
     }
 
     inline Index rows() const { return m_matrix.rows(); }
     inline Index cols() const { return m_matrix.cols(); }
 
     /** \internal \returns a reference to the nested matrix */
     const _MatrixTypeNested& matrix() const { return m_matrix; }
-    _MatrixTypeNested& matrix() { return m_matrix.const_cast_derived(); }
+    typename internal::remove_reference<MatrixTypeNested>::type& matrix() { return m_matrix; }
 
     /** \returns an expression of the matrix product between a sparse self-adjoint matrix \c *this and a sparse matrix \a rhs.
       *
       * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product.
       * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product.
       */
     template<typename OtherDerived>
-    SparseSparseProduct<typename OtherDerived::PlainObject, OtherDerived>
+    Product<SparseSelfAdjointView, OtherDerived>
     operator*(const SparseMatrixBase<OtherDerived>& rhs) const
     {
-      return SparseSparseProduct<typename OtherDerived::PlainObject, OtherDerived>(*this, rhs.derived());
+      return Product<SparseSelfAdjointView, OtherDerived>(*this, rhs.derived());
     }
 
     /** \returns an expression of the matrix product between a sparse matrix \a lhs and a sparse self-adjoint matrix \a rhs.
       *
       * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product.
       * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product.
       */
     template<typename OtherDerived> friend
-    SparseSparseProduct<OtherDerived, typename OtherDerived::PlainObject >
+    Product<OtherDerived, SparseSelfAdjointView>
     operator*(const SparseMatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs)
     {
-      return SparseSparseProduct<OtherDerived, typename OtherDerived::PlainObject>(lhs.derived(), rhs);
+      return Product<OtherDerived, SparseSelfAdjointView>(lhs.derived(), rhs);
     }
     
     /** Efficient sparse self-adjoint matrix times dense vector/matrix product */
     template<typename OtherDerived>
-    SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>
+    Product<SparseSelfAdjointView,OtherDerived>
     operator*(const MatrixBase<OtherDerived>& rhs) const
     {
-      return SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>(m_matrix, rhs.derived());
+      return Product<SparseSelfAdjointView,OtherDerived>(*this, rhs.derived());
     }
 
     /** Efficient dense vector/matrix times sparse self-adjoint matrix product */
     template<typename OtherDerived> friend
-    DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>
+    Product<OtherDerived,SparseSelfAdjointView>
     operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs)
     {
-      return DenseTimeSparseSelfAdjointProduct<OtherDerived,_MatrixTypeNested,UpLo>(lhs.derived(), rhs.m_matrix);
+      return Product<OtherDerived,SparseSelfAdjointView>(lhs.derived(), rhs);
     }
 
     /** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
       * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix.
       *
@@ -118,208 +120,322 @@
       * call this function with u.adjoint().
       */
     template<typename DerivedU>
     SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha = Scalar(1));
     
-    /** \internal triggered by sparse_matrix = SparseSelfadjointView; */
-    template<typename DestScalar,int StorageOrder> void evalTo(SparseMatrix<DestScalar,StorageOrder,Index>& _dest) const
-    {
-      internal::permute_symm_to_fullsymm<UpLo>(m_matrix, _dest);
-    }
-    
-    template<typename DestScalar> void evalTo(DynamicSparseMatrix<DestScalar,ColMajor,Index>& _dest) const
-    {
-      // TODO directly evaluate into _dest;
-      SparseMatrix<DestScalar,ColMajor,Index> tmp(_dest.rows(),_dest.cols());
-      internal::permute_symm_to_fullsymm<UpLo>(m_matrix, tmp);
-      _dest = tmp;
-    }
-    
     /** \returns an expression of P H P^-1 */
-    SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& perm) const
-    {
-      return SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo>(m_matrix, perm);
-    }
-    
-    template<typename SrcMatrixType,int SrcUpLo>
-    SparseSelfAdjointView& operator=(const SparseSymmetricPermutationProduct<SrcMatrixType,SrcUpLo>& permutedMatrix)
-    {
-      permutedMatrix.evalTo(*this);
+    // TODO implement twists in a more evaluator friendly fashion
+    SparseSymmetricPermutationProduct<_MatrixTypeNested,Mode> twistedBy(const PermutationMatrix<Dynamic,Dynamic,StorageIndex>& perm) const
+    {
+      return SparseSymmetricPermutationProduct<_MatrixTypeNested,Mode>(m_matrix, perm);
+    }
+
+    template<typename SrcMatrixType,int SrcMode>
+    SparseSelfAdjointView& operator=(const SparseSymmetricPermutationProduct<SrcMatrixType,SrcMode>& permutedMatrix)
+    {
+      internal::call_assignment_no_alias_no_transpose(*this, permutedMatrix);
       return *this;
     }
 
-
-    SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src)
-    {
-      PermutationMatrix<Dynamic> pnull;
-      return *this = src.twistedBy(pnull);
-    }
-
-    template<typename SrcMatrixType,unsigned int SrcUpLo>
-    SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcUpLo>& src)
-    {
-      PermutationMatrix<Dynamic> pnull;
-      return *this = src.twistedBy(pnull);
-    }
-    
-
-    // const SparseLLT<PlainObject, UpLo> llt() const;
-    // const SparseLDLT<PlainObject, UpLo> ldlt() const;
-
-  protected:
-
-    typename MatrixType::Nested m_matrix;
-    mutable VectorI m_countPerRow;
-    mutable VectorI m_countPerCol;
+    SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src)
+    {
+      PermutationMatrix<Dynamic,Dynamic,StorageIndex> pnull;
+      return *this = src.twistedBy(pnull);
+    }
+
+    template<typename SrcMatrixType,unsigned int SrcMode>
+    SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcMode>& src)
+    {
+      PermutationMatrix<Dynamic,Dynamic,StorageIndex> pnull;
+      return *this = src.twistedBy(pnull);
+    }
+    
+    void resize(Index rows, Index cols)
+    {
+      EIGEN_ONLY_USED_FOR_DEBUG(rows);
+      EIGEN_ONLY_USED_FOR_DEBUG(cols);
+      eigen_assert(rows == this->rows() && cols == this->cols()
+                && "SparseSelfadjointView::resize() does not actually allow to resize.");
+    }
+    
+  protected:
+
+    MatrixTypeNested m_matrix;
+    //mutable VectorI m_countPerRow;
+    //mutable VectorI m_countPerCol;
+  private:
+    template<typename Dest> void evalTo(Dest &) const;
 };
 
 /***************************************************************************
 * Implementation of SparseMatrixBase methods
 ***************************************************************************/
 
 template<typename Derived>
 template<unsigned int UpLo>
-const SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() const
+typename SparseMatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type SparseMatrixBase<Derived>::selfadjointView() const
 {
-  return derived();
+  return SparseSelfAdjointView<const Derived, UpLo>(derived());
 }
 
 template<typename Derived>
 template<unsigned int UpLo>
-SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView()
+typename SparseMatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type SparseMatrixBase<Derived>::selfadjointView()
 {
-  return derived();
+  return SparseSelfAdjointView<Derived, UpLo>(derived());
 }
 
 /***************************************************************************
 * Implementation of SparseSelfAdjointView methods
 ***************************************************************************/
 
-template<typename MatrixType, unsigned int UpLo>
+template<typename MatrixType, unsigned int Mode>
 template<typename DerivedU>
-SparseSelfAdjointView<MatrixType,UpLo>&
-SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha)
+SparseSelfAdjointView<MatrixType,Mode>&
+SparseSelfAdjointView<MatrixType,Mode>::rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha)
 {
-  SparseMatrix<Scalar,MatrixType::Flags&RowMajorBit?RowMajor:ColMajor> tmp = u * u.adjoint();
+  SparseMatrix<Scalar,(MatrixType::Flags&RowMajorBit)?RowMajor:ColMajor> tmp = u * u.adjoint();
   if(alpha==Scalar(0))
-    m_matrix.const_cast_derived() = tmp.template triangularView<UpLo>();
+    m_matrix = tmp.template triangularView<Mode>();
   else
-    m_matrix.const_cast_derived() += alpha * tmp.template triangularView<UpLo>();
+    m_matrix += alpha * tmp.template triangularView<Mode>();
 
   return *this;
 }
 
+namespace internal {
+  
+// TODO currently a selfadjoint expression has the form SelfAdjointView<.,.>
+//      in the future selfadjoint-ness should be defined by the expression traits
+//      such that Transpose<SelfAdjointView<.,.> > is valid. (currently TriangularBase::transpose() is overloaded to make it work)
+template<typename MatrixType, unsigned int Mode>
+struct evaluator_traits<SparseSelfAdjointView<MatrixType,Mode> >
+{
+  typedef typename storage_kind_to_evaluator_kind<typename MatrixType::StorageKind>::Kind Kind;
+  typedef SparseSelfAdjointShape Shape;
+};
+
+struct SparseSelfAdjoint2Sparse {};
+
+template<> struct AssignmentKind<SparseShape,SparseSelfAdjointShape> { typedef SparseSelfAdjoint2Sparse Kind; };
+template<> struct AssignmentKind<SparseSelfAdjointShape,SparseShape> { typedef Sparse2Sparse Kind; };
+
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, SparseSelfAdjoint2Sparse>
+{
+  typedef typename DstXprType::StorageIndex StorageIndex;
+  typedef internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> AssignOpType;
+
+  template<typename DestScalar,int StorageOrder>
+  static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, const AssignOpType&/*func*/)
+  {
+    internal::permute_symm_to_fullsymm<SrcXprType::Mode>(src.matrix(), dst);
+  }
+
+  // FIXME: the handling of += and -= in sparse matrices should be cleanup so that next two overloads could be reduced to:
+  template<typename DestScalar,int StorageOrder,typename AssignFunc>
+  static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src, const AssignFunc& func)
+  {
+    SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols());
+    run(tmp, src, AssignOpType());
+    call_assignment_no_alias_no_transpose(dst, tmp, func);
+  }
+
+  template<typename DestScalar,int StorageOrder>
+  static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src,
+                  const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>& /* func */)
+  {
+    SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols());
+    run(tmp, src, AssignOpType());
+    dst += tmp;
+  }
+
+  template<typename DestScalar,int StorageOrder>
+  static void run(SparseMatrix<DestScalar,StorageOrder,StorageIndex> &dst, const SrcXprType &src,
+                  const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>& /* func */)
+  {
+    SparseMatrix<DestScalar,StorageOrder,StorageIndex> tmp(src.rows(),src.cols());
+    run(tmp, src, AssignOpType());
+    dst -= tmp;
+  }
+  
+  template<typename DestScalar>
+  static void run(DynamicSparseMatrix<DestScalar,ColMajor,StorageIndex>& dst, const SrcXprType &src, const AssignOpType&/*func*/)
+  {
+    // TODO directly evaluate into dst;
+    SparseMatrix<DestScalar,ColMajor,StorageIndex> tmp(dst.rows(),dst.cols());
+    internal::permute_symm_to_fullsymm<SrcXprType::Mode>(src.matrix(), tmp);
+    dst = tmp;
+  }
+};
+
+} // end namespace internal
+
 /***************************************************************************
 * Implementation of sparse self-adjoint time dense matrix
 ***************************************************************************/
 
 namespace internal {
-template<typename Lhs, typename Rhs, int UpLo>
-struct traits<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo> >
- : traits<ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
-{
-  typedef Dense StorageKind;
-};
-}
-
-template<typename Lhs, typename Rhs, int UpLo>
-class SparseSelfAdjointTimeDenseProduct
-  : public ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
-{
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseSelfAdjointTimeDenseProduct)
-
-    SparseSelfAdjointTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
-    {}
-
-    template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
-    {
-      EIGEN_ONLY_USED_FOR_DEBUG(alpha);
-      // TODO use alpha
-      eigen_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry");
-      typedef typename internal::remove_all<Lhs>::type _Lhs;
-      typedef typename _Lhs::InnerIterator LhsInnerIterator;
-      enum {
-        LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit,
-        ProcessFirstHalf =
-                 ((UpLo&(Upper|Lower))==(Upper|Lower))
-              || ( (UpLo&Upper) && !LhsIsRowMajor)
-              || ( (UpLo&Lower) && LhsIsRowMajor),
-        ProcessSecondHalf = !ProcessFirstHalf
-      };
-      for (Index j=0; j<m_lhs.outerSize(); ++j)
-      {
-        LhsInnerIterator i(m_lhs,j);
-        if (ProcessSecondHalf)
-        {
-          while (i && i.index()<j) ++i;
-          if(i && i.index()==j)
-          {
-            dest.row(j) += i.value() * m_rhs.row(j);
-            ++i;
-          }
-        }
-        for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i)
-        {
-          Index a = LhsIsRowMajor ? j : i.index();
-          Index b = LhsIsRowMajor ? i.index() : j;
-          typename Lhs::Scalar v = i.value();
-          dest.row(a) += (v) * m_rhs.row(b);
-          dest.row(b) += numext::conj(v) * m_rhs.row(a);
-        }
-        if (ProcessFirstHalf && i && (i.index()==j))
-          dest.row(j) += i.value() * m_rhs.row(j);
-      }
-    }
-
-  private:
-    SparseSelfAdjointTimeDenseProduct& operator=(const SparseSelfAdjointTimeDenseProduct&);
-};
-
-namespace internal {
-template<typename Lhs, typename Rhs, int UpLo>
-struct traits<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo> >
- : traits<ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
-{};
-}
-
-template<typename Lhs, typename Rhs, int UpLo>
-class DenseTimeSparseSelfAdjointProduct
-  : public ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
-{
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseSelfAdjointProduct)
-
-    DenseTimeSparseSelfAdjointProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
-    {}
-
-    template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, const Scalar& /*alpha*/) const
-    {
-      // TODO
-    }
-
-  private:
-    DenseTimeSparseSelfAdjointProduct& operator=(const DenseTimeSparseSelfAdjointProduct&);
-};
+
+template<int Mode, typename SparseLhsType, typename DenseRhsType, typename DenseResType, typename AlphaType>
+inline void sparse_selfadjoint_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha)
+{
+  EIGEN_ONLY_USED_FOR_DEBUG(alpha);
+  
+  typedef typename internal::nested_eval<SparseLhsType,DenseRhsType::MaxColsAtCompileTime>::type SparseLhsTypeNested;
+  typedef typename internal::remove_all<SparseLhsTypeNested>::type SparseLhsTypeNestedCleaned;
+  typedef evaluator<SparseLhsTypeNestedCleaned> LhsEval;
+  typedef typename LhsEval::InnerIterator LhsIterator;
+  typedef typename SparseLhsType::Scalar LhsScalar;
+  
+  enum {
+    LhsIsRowMajor = (LhsEval::Flags&RowMajorBit)==RowMajorBit,
+    ProcessFirstHalf =
+              ((Mode&(Upper|Lower))==(Upper|Lower))
+          || ( (Mode&Upper) && !LhsIsRowMajor)
+          || ( (Mode&Lower) && LhsIsRowMajor),
+    ProcessSecondHalf = !ProcessFirstHalf
+  };
+  
+  SparseLhsTypeNested lhs_nested(lhs);
+  LhsEval lhsEval(lhs_nested);
+
+  // work on one column at once
+  for (Index k=0; k<rhs.cols(); ++k)
+  {
+    for (Index j=0; j<lhs.outerSize(); ++j)
+    {
+      LhsIterator i(lhsEval,j);
+      // handle diagonal coeff
+      if (ProcessSecondHalf)
+      {
+        while (i && i.index()<j) ++i;
+        if(i && i.index()==j)
+        {
+          res(j,k) += alpha * i.value() * rhs(j,k);
+          ++i;
+        }
+      }
+
+      // premultiplied rhs for scatters
+      typename ScalarBinaryOpTraits<AlphaType, typename DenseRhsType::Scalar>::ReturnType rhs_j(alpha*rhs(j,k));
+      // accumulator for partial scalar product
+      typename DenseResType::Scalar res_j(0);
+      for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i)
+      {
+        LhsScalar lhs_ij = i.value();
+        if(!LhsIsRowMajor) lhs_ij = numext::conj(lhs_ij);
+        res_j += lhs_ij * rhs(i.index(),k);
+        res(i.index(),k) += numext::conj(lhs_ij) * rhs_j;
+      }
+      res(j,k) += alpha * res_j;
+
+      // handle diagonal coeff
+      if (ProcessFirstHalf && i && (i.index()==j))
+        res(j,k) += alpha * i.value() * rhs(j,k);
+    }
+  }
+}
+
+
+template<typename LhsView, typename Rhs, int ProductType>
+struct generic_product_impl<LhsView, Rhs, SparseSelfAdjointShape, DenseShape, ProductType>
+: generic_product_impl_base<LhsView, Rhs, generic_product_impl<LhsView, Rhs, SparseSelfAdjointShape, DenseShape, ProductType> >
+{
+  template<typename Dest>
+  static void scaleAndAddTo(Dest& dst, const LhsView& lhsView, const Rhs& rhs, const typename Dest::Scalar& alpha)
+  {
+    typedef typename LhsView::_MatrixTypeNested Lhs;
+    typedef typename nested_eval<Lhs,Dynamic>::type LhsNested;
+    typedef typename nested_eval<Rhs,Dynamic>::type RhsNested;
+    LhsNested lhsNested(lhsView.matrix());
+    RhsNested rhsNested(rhs);
+    
+    internal::sparse_selfadjoint_time_dense_product<LhsView::Mode>(lhsNested, rhsNested, dst, alpha);
+  }
+};
+
+template<typename Lhs, typename RhsView, int ProductType>
+struct generic_product_impl<Lhs, RhsView, DenseShape, SparseSelfAdjointShape, ProductType>
+: generic_product_impl_base<Lhs, RhsView, generic_product_impl<Lhs, RhsView, DenseShape, SparseSelfAdjointShape, ProductType> >
+{
+  template<typename Dest>
+  static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const RhsView& rhsView, const typename Dest::Scalar& alpha)
+  {
+    typedef typename RhsView::_MatrixTypeNested Rhs;
+    typedef typename nested_eval<Lhs,Dynamic>::type LhsNested;
+    typedef typename nested_eval<Rhs,Dynamic>::type RhsNested;
+    LhsNested lhsNested(lhs);
+    RhsNested rhsNested(rhsView.matrix());
+    
+    // transpose everything
+    Transpose<Dest> dstT(dst);
+    internal::sparse_selfadjoint_time_dense_product<RhsView::TransposeMode>(rhsNested.transpose(), lhsNested.transpose(), dstT, alpha);
+  }
+};
+
+// NOTE: these two overloads are needed to evaluate the sparse selfadjoint view into a full sparse matrix
+// TODO: maybe the copy could be handled by generic_product_impl so that these overloads would not be needed anymore
+
+template<typename LhsView, typename Rhs, int ProductTag>
+struct product_evaluator<Product<LhsView, Rhs, DefaultProduct>, ProductTag, SparseSelfAdjointShape, SparseShape>
+  : public evaluator<typename Product<typename Rhs::PlainObject, Rhs, DefaultProduct>::PlainObject>
+{
+  typedef Product<LhsView, Rhs, DefaultProduct> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  typedef evaluator<PlainObject> Base;
+
+  product_evaluator(const XprType& xpr)
+    : m_lhs(xpr.lhs()), m_result(xpr.rows(), xpr.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    generic_product_impl<typename Rhs::PlainObject, Rhs, SparseShape, SparseShape, ProductTag>::evalTo(m_result, m_lhs, xpr.rhs());
+  }
+  
+protected:
+  typename Rhs::PlainObject m_lhs;
+  PlainObject m_result;
+};
+
+template<typename Lhs, typename RhsView, int ProductTag>
+struct product_evaluator<Product<Lhs, RhsView, DefaultProduct>, ProductTag, SparseShape, SparseSelfAdjointShape>
+  : public evaluator<typename Product<Lhs, typename Lhs::PlainObject, DefaultProduct>::PlainObject>
+{
+  typedef Product<Lhs, RhsView, DefaultProduct> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  typedef evaluator<PlainObject> Base;
+
+  product_evaluator(const XprType& xpr)
+    : m_rhs(xpr.rhs()), m_result(xpr.rows(), xpr.cols())
+  {
+    ::new (static_cast<Base*>(this)) Base(m_result);
+    generic_product_impl<Lhs, typename Lhs::PlainObject, SparseShape, SparseShape, ProductTag>::evalTo(m_result, xpr.lhs(), m_rhs);
+  }
+  
+protected:
+  typename Lhs::PlainObject m_rhs;
+  PlainObject m_result;
+};
+
+} // namespace internal
 
 /***************************************************************************
 * Implementation of symmetric copies and permutations
 ***************************************************************************/
 namespace internal {
-  
-template<typename MatrixType, int UpLo>
-struct traits<SparseSymmetricPermutationProduct<MatrixType,UpLo> > : traits<MatrixType> {
-};
-
-template<int UpLo,typename MatrixType,int DestOrder>
-void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
-{
-  typedef typename MatrixType::Index Index;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef SparseMatrix<Scalar,DestOrder,Index> Dest;
-  typedef Matrix<Index,Dynamic,1> VectorI;
-  
+
+template<int Mode,typename MatrixType,int DestOrder>
+void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm)
+{
+  typedef typename MatrixType::StorageIndex StorageIndex;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef SparseMatrix<Scalar,DestOrder,StorageIndex> Dest;
+  typedef Matrix<StorageIndex,Dynamic,1> VectorI;
+  typedef evaluator<MatrixType> MatEval;
+  typedef typename evaluator<MatrixType>::InnerIterator MatIterator;
+  
+  MatEval matEval(mat);
   Dest& dest(_dest.derived());
   enum {
     StorageOrderMatch = int(Dest::IsRowMajor) == int(MatrixType::IsRowMajor)
   };
   
@@ -329,21 +445,21 @@
   count.setZero();
   dest.resize(size,size);
   for(Index j = 0; j<size; ++j)
   {
     Index jp = perm ? perm[j] : j;
-    for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
+    for(MatIterator it(matEval,j); it; ++it)
     {
       Index i = it.index();
       Index r = it.row();
       Index c = it.col();
       Index ip = perm ? perm[i] : i;
-      if(UpLo==(Upper|Lower))
+      if(Mode==(Upper|Lower))
         count[StorageOrderMatch ? jp : ip]++;
       else if(r==c)
         count[ip]++;
-      else if(( UpLo==Lower && r>c) || ( UpLo==Upper && r<c))
+      else if(( Mode==Lower && r>c) || ( Mode==Upper && r<c))
       {
         count[ip]++;
         count[jp]++;
       }
     }
@@ -357,22 +473,22 @@
     dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j];
   for(Index j=0; j<size; ++j)
     count[j] = dest.outerIndexPtr()[j];
   
   // copy data
-  for(Index j = 0; j<size; ++j)
+  for(StorageIndex j = 0; j<size; ++j)
   {
-    for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
+    for(MatIterator it(matEval,j); it; ++it)
     {
-      Index i = it.index();
+      StorageIndex i = internal::convert_index<StorageIndex>(it.index());
       Index r = it.row();
       Index c = it.col();
       
-      Index jp = perm ? perm[j] : j;
-      Index ip = perm ? perm[i] : i;
+      StorageIndex jp = perm ? perm[j] : j;
+      StorageIndex ip = perm ? perm[i] : i;
       
-      if(UpLo==(Upper|Lower))
+      if(Mode==(Upper|Lower))
       {
         Index k = count[StorageOrderMatch ? jp : ip]++;
         dest.innerIndexPtr()[k] = StorageOrderMatch ? ip : jp;
         dest.valuePtr()[k] = it.value();
       }
@@ -380,11 +496,11 @@
       {
         Index k = count[ip]++;
         dest.innerIndexPtr()[k] = ip;
         dest.valuePtr()[k] = it.value();
       }
-      else if(( (UpLo&Lower)==Lower && r>c) || ( (UpLo&Upper)==Upper && r<c))
+      else if(( (Mode&Lower)==Lower && r>c) || ( (Mode&Upper)==Upper && r<c))
       {
         if(!StorageOrderMatch)
           std::swap(ip,jp);
         Index k = count[jp]++;
         dest.innerIndexPtr()[k] = ip;
@@ -395,113 +511,146 @@
       }
     }
   }
 }
 
-template<int _SrcUpLo,int _DstUpLo,typename MatrixType,int DstOrder>
-void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
+template<int _SrcMode,int _DstMode,typename MatrixType,int DstOrder>
+void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::StorageIndex>& _dest, const typename MatrixType::StorageIndex* perm)
 {
-  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::StorageIndex StorageIndex;
   typedef typename MatrixType::Scalar Scalar;
-  SparseMatrix<Scalar,DstOrder,Index>& dest(_dest.derived());
-  typedef Matrix<Index,Dynamic,1> VectorI;
+  SparseMatrix<Scalar,DstOrder,StorageIndex>& dest(_dest.derived());
+  typedef Matrix<StorageIndex,Dynamic,1> VectorI;
+  typedef evaluator<MatrixType> MatEval;
+  typedef typename evaluator<MatrixType>::InnerIterator MatIterator;
+
   enum {
     SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor,
     StorageOrderMatch = int(SrcOrder) == int(DstOrder),
-    DstUpLo = DstOrder==RowMajor ? (_DstUpLo==Upper ? Lower : Upper) : _DstUpLo,
-    SrcUpLo = SrcOrder==RowMajor ? (_SrcUpLo==Upper ? Lower : Upper) : _SrcUpLo
+    DstMode = DstOrder==RowMajor ? (_DstMode==Upper ? Lower : Upper) : _DstMode,
+    SrcMode = SrcOrder==RowMajor ? (_SrcMode==Upper ? Lower : Upper) : _SrcMode
   };
+
+  MatEval matEval(mat);
   
   Index size = mat.rows();
   VectorI count(size);
   count.setZero();
   dest.resize(size,size);
-  for(Index j = 0; j<size; ++j)
+  for(StorageIndex j = 0; j<size; ++j)
   {
-    Index jp = perm ? perm[j] : j;
-    for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
+    StorageIndex jp = perm ? perm[j] : j;
+    for(MatIterator it(matEval,j); it; ++it)
     {
-      Index i = it.index();
-      if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
+      StorageIndex i = it.index();
+      if((int(SrcMode)==int(Lower) && i<j) || (int(SrcMode)==int(Upper) && i>j))
         continue;
                   
-      Index ip = perm ? perm[i] : i;
-      count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
+      StorageIndex ip = perm ? perm[i] : i;
+      count[int(DstMode)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
     }
   }
   dest.outerIndexPtr()[0] = 0;
   for(Index j=0; j<size; ++j)
     dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j];
   dest.resizeNonZeros(dest.outerIndexPtr()[size]);
   for(Index j=0; j<size; ++j)
     count[j] = dest.outerIndexPtr()[j];
   
-  for(Index j = 0; j<size; ++j)
+  for(StorageIndex j = 0; j<size; ++j)
   {
     
-    for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
+    for(MatIterator it(matEval,j); it; ++it)
     {
-      Index i = it.index();
-      if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
+      StorageIndex i = it.index();
+      if((int(SrcMode)==int(Lower) && i<j) || (int(SrcMode)==int(Upper) && i>j))
         continue;
                   
-      Index jp = perm ? perm[j] : j;
-      Index ip = perm? perm[i] : i;
+      StorageIndex jp = perm ? perm[j] : j;
+      StorageIndex ip = perm? perm[i] : i;
       
-      Index k = count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
-      dest.innerIndexPtr()[k] = int(DstUpLo)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp);
+      Index k = count[int(DstMode)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
+      dest.innerIndexPtr()[k] = int(DstMode)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp);
       
       if(!StorageOrderMatch) std::swap(ip,jp);
-      if( ((int(DstUpLo)==int(Lower) && ip<jp) || (int(DstUpLo)==int(Upper) && ip>jp)))
+      if( ((int(DstMode)==int(Lower) && ip<jp) || (int(DstMode)==int(Upper) && ip>jp)))
         dest.valuePtr()[k] = numext::conj(it.value());
       else
         dest.valuePtr()[k] = it.value();
     }
   }
 }
 
 }
 
-template<typename MatrixType,int UpLo>
+// TODO implement twists in a more evaluator friendly fashion
+
+namespace internal {
+
+template<typename MatrixType, int Mode>
+struct traits<SparseSymmetricPermutationProduct<MatrixType,Mode> > : traits<MatrixType> {
+};
+
+}
+
+template<typename MatrixType,int Mode>
 class SparseSymmetricPermutationProduct
-  : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,UpLo> >
+  : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,Mode> >
 {
   public:
     typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    enum {
+      RowsAtCompileTime = internal::traits<SparseSymmetricPermutationProduct>::RowsAtCompileTime,
+      ColsAtCompileTime = internal::traits<SparseSymmetricPermutationProduct>::ColsAtCompileTime
+    };
   protected:
-    typedef PermutationMatrix<Dynamic,Dynamic,Index> Perm;
+    typedef PermutationMatrix<Dynamic,Dynamic,StorageIndex> Perm;
   public:
-    typedef Matrix<Index,Dynamic,1> VectorI;
+    typedef Matrix<StorageIndex,Dynamic,1> VectorI;
     typedef typename MatrixType::Nested MatrixTypeNested;
-    typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
+    typedef typename internal::remove_all<MatrixTypeNested>::type NestedExpression;
     
     SparseSymmetricPermutationProduct(const MatrixType& mat, const Perm& perm)
       : m_matrix(mat), m_perm(perm)
     {}
     
     inline Index rows() const { return m_matrix.rows(); }
     inline Index cols() const { return m_matrix.cols(); }
-    
-    template<typename DestScalar, int Options, typename DstIndex>
-    void evalTo(SparseMatrix<DestScalar,Options,DstIndex>& _dest) const
-    {
-//       internal::permute_symm_to_fullsymm<UpLo>(m_matrix,_dest,m_perm.indices().data());
-      SparseMatrix<DestScalar,(Options&RowMajor)==RowMajor ? ColMajor : RowMajor, DstIndex> tmp;
-      internal::permute_symm_to_fullsymm<UpLo>(m_matrix,tmp,m_perm.indices().data());
-      _dest = tmp;
-    }
-    
-    template<typename DestType,unsigned int DestUpLo> void evalTo(SparseSelfAdjointView<DestType,DestUpLo>& dest) const
-    {
-      internal::permute_symm_to_symm<UpLo,DestUpLo>(m_matrix,dest.matrix(),m_perm.indices().data());
-    }
+        
+    const NestedExpression& matrix() const { return m_matrix; }
+    const Perm& perm() const { return m_perm; }
     
   protected:
     MatrixTypeNested m_matrix;
     const Perm& m_perm;
 
 };
 
+namespace internal {
+  
+template<typename DstXprType, typename MatrixType, int Mode, typename Scalar>
+struct Assignment<DstXprType, SparseSymmetricPermutationProduct<MatrixType,Mode>, internal::assign_op<Scalar,typename MatrixType::Scalar>, Sparse2Sparse>
+{
+  typedef SparseSymmetricPermutationProduct<MatrixType,Mode> SrcXprType;
+  typedef typename DstXprType::StorageIndex DstIndex;
+  template<int Options>
+  static void run(SparseMatrix<Scalar,Options,DstIndex> &dst, const SrcXprType &src, const internal::assign_op<Scalar,typename MatrixType::Scalar> &)
+  {
+    // internal::permute_symm_to_fullsymm<Mode>(m_matrix,_dest,m_perm.indices().data());
+    SparseMatrix<Scalar,(Options&RowMajor)==RowMajor ? ColMajor : RowMajor, DstIndex> tmp;
+    internal::permute_symm_to_fullsymm<Mode>(src.matrix(),tmp,src.perm().indices().data());
+    dst = tmp;
+  }
+  
+  template<typename DestType,unsigned int DestMode>
+  static void run(SparseSelfAdjointView<DestType,DestMode>& dst, const SrcXprType &src, const internal::assign_op<Scalar,typename MatrixType::Scalar> &)
+  {
+    internal::permute_symm_to_symm<Mode,DestMode>(src.matrix(),dst.matrix(),src.perm().indices().data());
+  }
+};
+
+} // end namespace internal
+
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSE_SELFADJOINTVIEW_H

ADDED   3rd_party/eigen/Eigen/src/SparseCore/SparseSolverBase.h
Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseSolverBase.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseSolverBase.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseSolverBase.h
@@ -0,0 +1,124 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSESOLVERBASE_H
+#define EIGEN_SPARSESOLVERBASE_H
+
+namespace Eigen { 
+
+namespace internal {
+
+  /** \internal
+  * Helper functions to solve with a sparse right-hand-side and result.
+  * The rhs is decomposed into small vertical panels which are solved through dense temporaries.
+  */
+template<typename Decomposition, typename Rhs, typename Dest>
+typename enable_if<Rhs::ColsAtCompileTime!=1 && Dest::ColsAtCompileTime!=1>::type
+solve_sparse_through_dense_panels(const Decomposition &dec, const Rhs& rhs, Dest &dest)
+{
+  EIGEN_STATIC_ASSERT((Dest::Flags&RowMajorBit)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+  typedef typename Dest::Scalar DestScalar;
+  // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix.
+  static const Index NbColsAtOnce = 4;
+  Index rhsCols = rhs.cols();
+  Index size = rhs.rows();
+  // the temporary matrices do not need more columns than NbColsAtOnce:
+  Index tmpCols = (std::min)(rhsCols, NbColsAtOnce); 
+  Eigen::Matrix<DestScalar,Dynamic,Dynamic> tmp(size,tmpCols);
+  Eigen::Matrix<DestScalar,Dynamic,Dynamic> tmpX(size,tmpCols);
+  for(Index k=0; k<rhsCols; k+=NbColsAtOnce)
+  {
+    Index actualCols = std::min<Index>(rhsCols-k, NbColsAtOnce);
+    tmp.leftCols(actualCols) = rhs.middleCols(k,actualCols);
+    tmpX.leftCols(actualCols) = dec.solve(tmp.leftCols(actualCols));
+    dest.middleCols(k,actualCols) = tmpX.leftCols(actualCols).sparseView();
+  }
+}
+
+// Overload for vector as rhs
+template<typename Decomposition, typename Rhs, typename Dest>
+typename enable_if<Rhs::ColsAtCompileTime==1 || Dest::ColsAtCompileTime==1>::type
+solve_sparse_through_dense_panels(const Decomposition &dec, const Rhs& rhs, Dest &dest)
+{
+  typedef typename Dest::Scalar DestScalar;
+  Index size = rhs.rows();
+  Eigen::Matrix<DestScalar,Dynamic,1> rhs_dense(rhs);
+  Eigen::Matrix<DestScalar,Dynamic,1> dest_dense(size);
+  dest_dense = dec.solve(rhs_dense);
+  dest = dest_dense.sparseView();
+}
+
+} // end namespace internal
+
+/** \class SparseSolverBase
+  * \ingroup SparseCore_Module
+  * \brief A base class for sparse solvers
+  *
+  * \tparam Derived the actual type of the solver.
+  *
+  */
+template<typename Derived>
+class SparseSolverBase : internal::noncopyable
+{
+  public:
+
+    /** Default constructor */
+    SparseSolverBase()
+      : m_isInitialized(false)
+    {}
+
+    ~SparseSolverBase()
+    {}
+
+    Derived& derived() { return *static_cast<Derived*>(this); }
+    const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    
+    /** \returns an expression of the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const Solve<Derived, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "Solver is not initialized.");
+      eigen_assert(derived().rows()==b.rows() && "solve(): invalid number of rows of the right hand side matrix b");
+      return Solve<Derived, Rhs>(derived(), b.derived());
+    }
+    
+    /** \returns an expression of the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const Solve<Derived, Rhs>
+    solve(const SparseMatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "Solver is not initialized.");
+      eigen_assert(derived().rows()==b.rows() && "solve(): invalid number of rows of the right hand side matrix b");
+      return Solve<Derived, Rhs>(derived(), b.derived());
+    }
+    
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal default implementation of solving with a sparse rhs */
+    template<typename Rhs,typename Dest>
+    void _solve_impl(const SparseMatrixBase<Rhs> &b, SparseMatrixBase<Dest> &dest) const
+    {
+      internal::solve_sparse_through_dense_panels(derived(), b.derived(), dest.derived());
+    }
+    #endif // EIGEN_PARSED_BY_DOXYGEN
+
+  protected:
+    
+    mutable bool m_isInitialized;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSESOLVERBASE_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -20,56 +20,59 @@
 static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, const typename ResultType::RealScalar& tolerance)
 {
   // return sparse_sparse_product_with_pruning_impl2(lhs,rhs,res);
 
   typedef typename remove_all<Lhs>::type::Scalar Scalar;
-  typedef typename remove_all<Lhs>::type::Index Index;
+  typedef typename remove_all<Lhs>::type::StorageIndex StorageIndex;
 
   // make sure to call innerSize/outerSize since we fake the storage order.
   Index rows = lhs.innerSize();
   Index cols = rhs.outerSize();
   //Index size = lhs.outerSize();
   eigen_assert(lhs.outerSize() == rhs.innerSize());
 
   // allocate a temporary buffer
-  AmbiVector<Scalar,Index> tempVector(rows);
-
-  // estimate the number of non zero entries
-  // given a rhs column containing Y non zeros, we assume that the respective Y columns
-  // of the lhs differs in average of one non zeros, thus the number of non zeros for
-  // the product of a rhs column with the lhs is X+Y where X is the average number of non zero
-  // per column of the lhs.
-  // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs)
-  Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros();
+  AmbiVector<Scalar,StorageIndex> tempVector(rows);
 
   // mimics a resizeByInnerOuter:
   if(ResultType::IsRowMajor)
     res.resize(cols, rows);
   else
     res.resize(rows, cols);
+  
+  evaluator<Lhs> lhsEval(lhs);
+  evaluator<Rhs> rhsEval(rhs);
+  
+  // estimate the number of non zero entries
+  // given a rhs column containing Y non zeros, we assume that the respective Y columns
+  // of the lhs differs in average of one non zeros, thus the number of non zeros for
+  // the product of a rhs column with the lhs is X+Y where X is the average number of non zero
+  // per column of the lhs.
+  // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs)
+  Index estimated_nnz_prod = lhsEval.nonZerosEstimate() + rhsEval.nonZerosEstimate();
 
   res.reserve(estimated_nnz_prod);
-  double ratioColRes = double(estimated_nnz_prod)/double(lhs.rows()*rhs.cols());
+  double ratioColRes = double(estimated_nnz_prod)/(double(lhs.rows())*double(rhs.cols()));
   for (Index j=0; j<cols; ++j)
   {
     // FIXME:
     //double ratioColRes = (double(rhs.innerVector(j).nonZeros()) + double(lhs.nonZeros())/double(lhs.cols()))/double(lhs.rows());
     // let's do a more accurate determination of the nnz ratio for the current column j of res
     tempVector.init(ratioColRes);
     tempVector.setZero();
-    for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
+    for (typename evaluator<Rhs>::InnerIterator rhsIt(rhsEval, j); rhsIt; ++rhsIt)
     {
       // FIXME should be written like this: tmp += rhsIt.value() * lhs.col(rhsIt.index())
       tempVector.restart();
       Scalar x = rhsIt.value();
-      for (typename Lhs::InnerIterator lhsIt(lhs, rhsIt.index()); lhsIt; ++lhsIt)
+      for (typename evaluator<Lhs>::InnerIterator lhsIt(lhsEval, rhsIt.index()); lhsIt; ++lhsIt)
       {
         tempVector.coeffRef(lhsIt.index()) += lhsIt.value() * x;
       }
     }
     res.startVec(j);
-    for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector,tolerance); it; ++it)
+    for (typename AmbiVector<Scalar,StorageIndex>::Iterator it(tempVector,tolerance); it; ++it)
       res.insertBackByOuterInner(j,it.index()) = it.value();
   }
   res.finalize();
 }
 
@@ -98,11 +101,11 @@
 {
   typedef typename ResultType::RealScalar RealScalar;
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
   {
     // we need a col-major matrix to hold the result
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> SparseTemporaryType;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> SparseTemporaryType;
     SparseTemporaryType _res(res.rows(), res.cols());
     internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,SparseTemporaryType>(lhs, rhs, _res, tolerance);
     res = _res;
   }
 };
@@ -124,12 +127,12 @@
 struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor>
 {
   typedef typename ResultType::RealScalar RealScalar;
   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
   {
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::Index> ColMajorMatrixLhs;
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::Index> ColMajorMatrixRhs;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixLhs;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixRhs;
     ColMajorMatrixLhs colLhs(lhs);
     ColMajorMatrixRhs colRhs(rhs);
     internal::sparse_sparse_product_with_pruning_impl<ColMajorMatrixLhs,ColMajorMatrixRhs,ResultType>(colLhs, colRhs, res, tolerance);
 
     // let's transpose the product to get a column x column product
@@ -138,13 +141,58 @@
 //     sparse_sparse_product_with_pruning_impl<Rhs,Lhs,SparseTemporaryType>(rhs, lhs, _res);
 //     res = _res.transpose();
   }
 };
 
-// NOTE the 2 others cases (col row *) must never occur since they are caught
-// by ProductReturnType which transforms it to (col col *) by evaluating rhs.
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor,RowMajor>
+{
+  typedef typename ResultType::RealScalar RealScalar;
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename Lhs::StorageIndex> RowMajorMatrixLhs;
+    RowMajorMatrixLhs rowLhs(lhs);
+    sparse_sparse_product_with_pruning_selector<RowMajorMatrixLhs,Rhs,ResultType,RowMajor,RowMajor>(rowLhs,rhs,res,tolerance);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor,RowMajor>
+{
+  typedef typename ResultType::RealScalar RealScalar;
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename Lhs::StorageIndex> RowMajorMatrixRhs;
+    RowMajorMatrixRhs rowRhs(rhs);
+    sparse_sparse_product_with_pruning_selector<Lhs,RowMajorMatrixRhs,ResultType,RowMajor,RowMajor,RowMajor>(lhs,rowRhs,res,tolerance);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor,ColMajor>
+{
+  typedef typename ResultType::RealScalar RealScalar;
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixRhs;
+    ColMajorMatrixRhs colRhs(rhs);
+    internal::sparse_sparse_product_with_pruning_impl<Lhs,ColMajorMatrixRhs,ResultType>(lhs, colRhs, res, tolerance);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor,ColMajor>
+{
+  typedef typename ResultType::RealScalar RealScalar;
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixLhs;
+    ColMajorMatrixLhs colLhs(lhs);
+    internal::sparse_sparse_product_with_pruning_impl<ColMajorMatrixLhs,Rhs,ResultType>(colLhs, rhs, res, tolerance);
+  }
+};
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseTranspose.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseTranspose.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseTranspose.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -10,54 +10,83 @@
 #ifndef EIGEN_SPARSETRANSPOSE_H
 #define EIGEN_SPARSETRANSPOSE_H
 
 namespace Eigen { 
 
-template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>
-  : public SparseMatrixBase<Transpose<MatrixType> >
-{
-    typedef typename internal::remove_all<typename MatrixType::Nested>::type _MatrixTypeNested;
+namespace internal {
+  template<typename MatrixType,int CompressedAccess=int(MatrixType::Flags&CompressedAccessBit)>
+  class SparseTransposeImpl
+    : public SparseMatrixBase<Transpose<MatrixType> >
+  {};
+  
+  template<typename MatrixType>
+  class SparseTransposeImpl<MatrixType,CompressedAccessBit>
+    : public SparseCompressedBase<Transpose<MatrixType> >
+  {
+    typedef SparseCompressedBase<Transpose<MatrixType> > Base;
   public:
-
-    EIGEN_SPARSE_PUBLIC_INTERFACE(Transpose<MatrixType> )
-
-    class InnerIterator;
-    class ReverseInnerIterator;
+    using Base::derived;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::StorageIndex StorageIndex;
 
     inline Index nonZeros() const { return derived().nestedExpression().nonZeros(); }
-};
-
-// NOTE: VC10 and VC11 trigger an ICE if don't put typename TransposeImpl<MatrixType,Sparse>:: in front of Index,
-// a typedef typename TransposeImpl<MatrixType,Sparse>::Index Index;
-// does not fix the issue.
-// An alternative is to define the nested class in the parent class itself.
-template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>::InnerIterator
-  : public _MatrixTypeNested::InnerIterator
-{
-    typedef typename _MatrixTypeNested::InnerIterator Base;
-    typedef typename TransposeImpl::Index Index;
-  public:
-
-    EIGEN_STRONG_INLINE InnerIterator(const TransposeImpl& trans, typename TransposeImpl<MatrixType,Sparse>::Index outer)
-      : Base(trans.derived().nestedExpression(), outer)
-    {}
-    typename TransposeImpl<MatrixType,Sparse>::Index row() const { return Base::col(); }
-    typename TransposeImpl<MatrixType,Sparse>::Index col() const { return Base::row(); }
-};
-
-template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>::ReverseInnerIterator
-  : public _MatrixTypeNested::ReverseInnerIterator
-{
-    typedef typename _MatrixTypeNested::ReverseInnerIterator Base;
-    typedef typename TransposeImpl::Index Index;
-  public:
-
-    EIGEN_STRONG_INLINE ReverseInnerIterator(const TransposeImpl& xpr, typename TransposeImpl<MatrixType,Sparse>::Index outer)
-      : Base(xpr.derived().nestedExpression(), outer)
-    {}
-    typename TransposeImpl<MatrixType,Sparse>::Index row() const { return Base::col(); }
-    typename TransposeImpl<MatrixType,Sparse>::Index col() const { return Base::row(); }
-};
+    
+    inline const Scalar* valuePtr() const { return derived().nestedExpression().valuePtr(); }
+    inline const StorageIndex* innerIndexPtr() const { return derived().nestedExpression().innerIndexPtr(); }
+    inline const StorageIndex* outerIndexPtr() const { return derived().nestedExpression().outerIndexPtr(); }
+    inline const StorageIndex* innerNonZeroPtr() const { return derived().nestedExpression().innerNonZeroPtr(); }
+
+    inline Scalar* valuePtr() { return derived().nestedExpression().valuePtr(); }
+    inline StorageIndex* innerIndexPtr() { return derived().nestedExpression().innerIndexPtr(); }
+    inline StorageIndex* outerIndexPtr() { return derived().nestedExpression().outerIndexPtr(); }
+    inline StorageIndex* innerNonZeroPtr() { return derived().nestedExpression().innerNonZeroPtr(); }
+  };
+}
+  
+template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>
+  : public internal::SparseTransposeImpl<MatrixType>
+{
+  protected:
+    typedef internal::SparseTransposeImpl<MatrixType> Base;
+};
+
+namespace internal {
+  
+template<typename ArgType>
+struct unary_evaluator<Transpose<ArgType>, IteratorBased>
+  : public evaluator_base<Transpose<ArgType> >
+{
+    typedef typename evaluator<ArgType>::InnerIterator        EvalIterator;
+  public:
+    typedef Transpose<ArgType> XprType;
+    
+    inline Index nonZerosEstimate() const {
+      return m_argImpl.nonZerosEstimate();
+    }
+
+    class InnerIterator : public EvalIterator
+    {
+    public:
+      EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& unaryOp, Index outer)
+        : EvalIterator(unaryOp.m_argImpl,outer)
+      {}
+      
+      Index row() const { return EvalIterator::col(); }
+      Index col() const { return EvalIterator::row(); }
+    };
+    
+    enum {
+      CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+      Flags = XprType::Flags
+    };
+    
+    explicit unary_evaluator(const XprType& op) :m_argImpl(op.nestedExpression()) {}
+
+  protected:
+    evaluator<ArgType> m_argImpl;
+};
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSETRANSPOSE_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseTriangularView.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseTriangularView.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseTriangularView.h
@@ -1,179 +1,189 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_TRIANGULARVIEW_H
 #define EIGEN_SPARSE_TRIANGULARVIEW_H
 
-namespace Eigen { 
-
-namespace internal {
-  
-template<typename MatrixType, int Mode>
-struct traits<SparseTriangularView<MatrixType,Mode> >
-: public traits<MatrixType>
-{};
-
-} // namespace internal
-
-template<typename MatrixType, int Mode> class SparseTriangularView
-  : public SparseMatrixBase<SparseTriangularView<MatrixType,Mode> >
+namespace Eigen {
+
+/** \ingroup SparseCore_Module
+  *
+  * \brief Base class for a triangular part in a \b sparse matrix
+  *
+  * This class is an abstract base class of class TriangularView, and objects of type TriangularViewImpl cannot be instantiated.
+  * It extends class TriangularView with additional methods which are available for sparse expressions only.
+  *
+  * \sa class TriangularView, SparseMatrixBase::triangularView()
+  */
+template<typename MatrixType, unsigned int Mode> class TriangularViewImpl<MatrixType,Mode,Sparse>
+  : public SparseMatrixBase<TriangularView<MatrixType,Mode> >
 {
     enum { SkipFirst = ((Mode&Lower) && !(MatrixType::Flags&RowMajorBit))
                     || ((Mode&Upper) &&  (MatrixType::Flags&RowMajorBit)),
            SkipLast = !SkipFirst,
            SkipDiag = (Mode&ZeroDiag) ? 1 : 0,
            HasUnitDiag = (Mode&UnitDiag) ? 1 : 0
     };
+    
+    typedef TriangularView<MatrixType,Mode> TriangularViewType;
+    
+  protected:
+    // dummy solve function to make TriangularView happy.
+    void solve() const;
 
+    typedef SparseMatrixBase<TriangularViewType> Base;
   public:
     
-    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseTriangularView)
-
-    class InnerIterator;
-    class ReverseInnerIterator;
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-
+    EIGEN_SPARSE_PUBLIC_INTERFACE(TriangularViewType)
+    
     typedef typename MatrixType::Nested MatrixTypeNested;
     typedef typename internal::remove_reference<MatrixTypeNested>::type MatrixTypeNestedNonRef;
     typedef typename internal::remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
 
-    inline SparseTriangularView(const MatrixType& matrix) : m_matrix(matrix) {}
-
-    /** \internal */
-    inline const MatrixTypeNestedCleaned& nestedExpression() const { return m_matrix; }
-
-    template<typename OtherDerived>
-    typename internal::plain_matrix_type_column_major<OtherDerived>::type
-    solve(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename OtherDerived> void solveInPlace(MatrixBase<OtherDerived>& other) const;
-    template<typename OtherDerived> void solveInPlace(SparseMatrixBase<OtherDerived>& other) const;
-
-  protected:
-    MatrixTypeNested m_matrix;
-};
-
-template<typename MatrixType, int Mode>
-class SparseTriangularView<MatrixType,Mode>::InnerIterator : public MatrixTypeNestedCleaned::InnerIterator
-{
-    typedef typename MatrixTypeNestedCleaned::InnerIterator Base;
-    typedef typename SparseTriangularView::Index Index;
-  public:
-
-    EIGEN_STRONG_INLINE InnerIterator(const SparseTriangularView& view, Index outer)
-      : Base(view.nestedExpression(), outer), m_returnOne(false)
-    {
-      if(SkipFirst)
-      {
-        while((*this) && ((HasUnitDiag||SkipDiag)  ? this->index()<=outer : this->index()<outer))
-          Base::operator++();
-        if(HasUnitDiag)
-          m_returnOne = true;
-      }
-      else if(HasUnitDiag && ((!Base::operator bool()) || Base::index()>=Base::outer()))
-      {
-        if((!SkipFirst) && Base::operator bool())
-          Base::operator++();
-        m_returnOne = true;
-      }
-    }
-
-    EIGEN_STRONG_INLINE InnerIterator& operator++()
-    {
-      if(HasUnitDiag && m_returnOne)
-        m_returnOne = false;
-      else
-      {
-        Base::operator++();
-        if(HasUnitDiag && (!SkipFirst) && ((!Base::operator bool()) || Base::index()>=Base::outer()))
-        {
-          if((!SkipFirst) && Base::operator bool())
-            Base::operator++();
-          m_returnOne = true;
-        }
-      }
-      return *this;
-    }
-
-    inline Index row() const { return (MatrixType::Flags&RowMajorBit ? Base::outer() : this->index()); }
-    inline Index col() const { return (MatrixType::Flags&RowMajorBit ? this->index() : Base::outer()); }
-    inline Index index() const
-    {
-      if(HasUnitDiag && m_returnOne)  return Base::outer();
-      else                            return Base::index();
-    }
-    inline Scalar value() const
-    {
-      if(HasUnitDiag && m_returnOne)  return Scalar(1);
-      else                            return Base::value();
-    }
-
-    EIGEN_STRONG_INLINE operator bool() const
-    {
-      if(HasUnitDiag && m_returnOne)
-        return true;
-      if(SkipFirst) return  Base::operator bool();
-      else
-      {
-        if (SkipDiag) return (Base::operator bool() && this->index() < this->outer());
-        else return (Base::operator bool() && this->index() <= this->outer());
-      }
-    }
-  protected:
-    bool m_returnOne;
-};
-
-template<typename MatrixType, int Mode>
-class SparseTriangularView<MatrixType,Mode>::ReverseInnerIterator : public MatrixTypeNestedCleaned::ReverseInnerIterator
-{
-    typedef typename MatrixTypeNestedCleaned::ReverseInnerIterator Base;
-    typedef typename SparseTriangularView::Index Index;
-  public:
-
-    EIGEN_STRONG_INLINE ReverseInnerIterator(const SparseTriangularView& view, Index outer)
-      : Base(view.nestedExpression(), outer)
-    {
-      eigen_assert((!HasUnitDiag) && "ReverseInnerIterator does not support yet triangular views with a unit diagonal");
-      if(SkipLast) {
-        while((*this) && (SkipDiag ? this->index()>=outer : this->index()>outer))
-          --(*this);
-      }
-    }
-
-    EIGEN_STRONG_INLINE ReverseInnerIterator& operator--()
-    { Base::operator--(); return *this; }
-
-    inline Index row() const { return Base::row(); }
-    inline Index col() const { return Base::col(); }
-
-    EIGEN_STRONG_INLINE operator bool() const
-    {
-      if (SkipLast) return Base::operator bool() ;
-      else
-      {
-        if(SkipDiag) return (Base::operator bool() && this->index() > this->outer());
-        else return (Base::operator bool() && this->index() >= this->outer());
-      }
-    }
-};
-
-template<typename Derived>
-template<int Mode>
-inline const SparseTriangularView<Derived, Mode>
-SparseMatrixBase<Derived>::triangularView() const
-{
-  return derived();
+    template<typename RhsType, typename DstType>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE void _solve_impl(const RhsType &rhs, DstType &dst) const {
+      if(!(internal::is_same<RhsType,DstType>::value && internal::extract_data(dst) == internal::extract_data(rhs)))
+        dst = rhs;
+      this->solveInPlace(dst);
+    }
+
+    /** Applies the inverse of \c *this to the dense vector or matrix \a other, "in-place" */
+    template<typename OtherDerived> void solveInPlace(MatrixBase<OtherDerived>& other) const;
+
+    /** Applies the inverse of \c *this to the sparse vector or matrix \a other, "in-place" */
+    template<typename OtherDerived> void solveInPlace(SparseMatrixBase<OtherDerived>& other) const;
+  
+};
+
+namespace internal {
+
+template<typename ArgType, unsigned int Mode>
+struct unary_evaluator<TriangularView<ArgType,Mode>, IteratorBased>
+ : evaluator_base<TriangularView<ArgType,Mode> >
+{
+  typedef TriangularView<ArgType,Mode> XprType;
+  
+protected:
+  
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::StorageIndex StorageIndex;
+  typedef typename evaluator<ArgType>::InnerIterator EvalIterator;
+  
+  enum { SkipFirst = ((Mode&Lower) && !(ArgType::Flags&RowMajorBit))
+                    || ((Mode&Upper) &&  (ArgType::Flags&RowMajorBit)),
+         SkipLast = !SkipFirst,
+         SkipDiag = (Mode&ZeroDiag) ? 1 : 0,
+         HasUnitDiag = (Mode&UnitDiag) ? 1 : 0
+  };
+  
+public:
+  
+  enum {
+    CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+    Flags = XprType::Flags
+  };
+    
+  explicit unary_evaluator(const XprType &xpr) : m_argImpl(xpr.nestedExpression()), m_arg(xpr.nestedExpression()) {}
+  
+  inline Index nonZerosEstimate() const {
+    return m_argImpl.nonZerosEstimate();
+  }
+  
+  class InnerIterator : public EvalIterator
+  {
+      typedef EvalIterator Base;
+    public:
+
+      EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& xprEval, Index outer)
+        : Base(xprEval.m_argImpl,outer), m_returnOne(false), m_containsDiag(Base::outer()<xprEval.m_arg.innerSize())
+      {
+        if(SkipFirst)
+        {
+          while((*this) && ((HasUnitDiag||SkipDiag)  ? this->index()<=outer : this->index()<outer))
+            Base::operator++();
+          if(HasUnitDiag)
+            m_returnOne = m_containsDiag;
+        }
+        else if(HasUnitDiag && ((!Base::operator bool()) || Base::index()>=Base::outer()))
+        {
+          if((!SkipFirst) && Base::operator bool())
+            Base::operator++();
+          m_returnOne = m_containsDiag;
+        }
+      }
+
+      EIGEN_STRONG_INLINE InnerIterator& operator++()
+      {
+        if(HasUnitDiag && m_returnOne)
+          m_returnOne = false;
+        else
+        {
+          Base::operator++();
+          if(HasUnitDiag && (!SkipFirst) && ((!Base::operator bool()) || Base::index()>=Base::outer()))
+          {
+            if((!SkipFirst) && Base::operator bool())
+              Base::operator++();
+            m_returnOne = m_containsDiag;
+          }
+        }
+        return *this;
+      }
+      
+      EIGEN_STRONG_INLINE operator bool() const
+      {
+        if(HasUnitDiag && m_returnOne)
+          return true;
+        if(SkipFirst) return  Base::operator bool();
+        else
+        {
+          if (SkipDiag) return (Base::operator bool() && this->index() < this->outer());
+          else return (Base::operator bool() && this->index() <= this->outer());
+        }
+      }
+
+//       inline Index row() const { return (ArgType::Flags&RowMajorBit ? Base::outer() : this->index()); }
+//       inline Index col() const { return (ArgType::Flags&RowMajorBit ? this->index() : Base::outer()); }
+      inline StorageIndex index() const
+      {
+        if(HasUnitDiag && m_returnOne)  return internal::convert_index<StorageIndex>(Base::outer());
+        else                            return Base::index();
+      }
+      inline Scalar value() const
+      {
+        if(HasUnitDiag && m_returnOne)  return Scalar(1);
+        else                            return Base::value();
+      }
+
+    protected:
+      bool m_returnOne;
+      bool m_containsDiag;
+    private:
+      Scalar& valueRef();
+  };
+  
+protected:
+  evaluator<ArgType> m_argImpl;
+  const ArgType& m_arg;
+};
+
+} // end namespace internal
+
+template<typename Derived>
+template<int Mode>
+inline const TriangularView<const Derived, Mode>
+SparseMatrixBase<Derived>::triangularView() const
+{
+  return TriangularView<const Derived, Mode>(derived());
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSE_TRIANGULARVIEW_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseUtil.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseUtil.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseUtil.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -35,47 +35,27 @@
 { \
   return Base::operator Op(scalar); \
 }
 
 #define EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATORS(Derived) \
-EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, =) \
-EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, +=) \
-EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, -=) \
-EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, *=) \
-EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, /=)
-
-#define _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, BaseClass) \
-  typedef BaseClass Base; \
-  typedef typename Eigen::internal::traits<Derived >::Scalar Scalar; \
-  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; \
-  typedef typename Eigen::internal::nested<Derived >::type Nested; \
-  typedef typename Eigen::internal::traits<Derived >::StorageKind StorageKind; \
-  typedef typename Eigen::internal::traits<Derived >::Index Index; \
-  enum { RowsAtCompileTime = Eigen::internal::traits<Derived >::RowsAtCompileTime, \
-        ColsAtCompileTime = Eigen::internal::traits<Derived >::ColsAtCompileTime, \
-        Flags = Eigen::internal::traits<Derived >::Flags, \
-        CoeffReadCost = Eigen::internal::traits<Derived >::CoeffReadCost, \
-        SizeAtCompileTime = Base::SizeAtCompileTime, \
-        IsVectorAtCompileTime = Base::IsVectorAtCompileTime }; \
-  using Base::derived; \
-  using Base::const_cast_derived;
+EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, =)
+
 
 #define EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) \
-  _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, Eigen::SparseMatrixBase<Derived >)
+  EIGEN_GENERIC_PUBLIC_INTERFACE(Derived)
 
+  
 const int CoherentAccessPattern     = 0x1;
 const int InnerRandomAccessPattern  = 0x2 | CoherentAccessPattern;
 const int OuterRandomAccessPattern  = 0x4 | CoherentAccessPattern;
 const int RandomAccessPattern       = 0x8 | OuterRandomAccessPattern | InnerRandomAccessPattern;
 
-template<typename Derived> class SparseMatrixBase;
-template<typename _Scalar, int _Flags = 0, typename _Index = int>  class SparseMatrix;
-template<typename _Scalar, int _Flags = 0, typename _Index = int>  class DynamicSparseMatrix;
-template<typename _Scalar, int _Flags = 0, typename _Index = int>  class SparseVector;
-template<typename _Scalar, int _Flags = 0, typename _Index = int>  class MappedSparseMatrix;
+template<typename _Scalar, int _Flags = 0, typename _StorageIndex = int>  class SparseMatrix;
+template<typename _Scalar, int _Flags = 0, typename _StorageIndex = int>  class DynamicSparseMatrix;
+template<typename _Scalar, int _Flags = 0, typename _StorageIndex = int>  class SparseVector;
+template<typename _Scalar, int _Flags = 0, typename _StorageIndex = int>  class MappedSparseMatrix;
 
-template<typename MatrixType, int Mode>           class SparseTriangularView;
 template<typename MatrixType, unsigned int UpLo>  class SparseSelfAdjointView;
 template<typename Lhs, typename Rhs>              class SparseDiagonalProduct;
 template<typename MatrixType> class SparseView;
 
 template<typename Lhs, typename Rhs>        class SparseSparseProduct;
@@ -83,60 +63,85 @@
 template<typename Lhs, typename Rhs>        class DenseTimeSparseProduct;
 template<typename Lhs, typename Rhs, bool Transpose> class SparseDenseOuterProduct;
 
 template<typename Lhs, typename Rhs> struct SparseSparseProductReturnType;
 template<typename Lhs, typename Rhs,
-         int InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(internal::traits<Lhs>::ColsAtCompileTime,internal::traits<Rhs>::RowsAtCompileTime)> struct DenseSparseProductReturnType;         
+         int InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(internal::traits<Lhs>::ColsAtCompileTime,internal::traits<Rhs>::RowsAtCompileTime)> struct DenseSparseProductReturnType;
+         
 template<typename Lhs, typename Rhs,
          int InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(internal::traits<Lhs>::ColsAtCompileTime,internal::traits<Rhs>::RowsAtCompileTime)> struct SparseDenseProductReturnType;
 template<typename MatrixType,int UpLo> class SparseSymmetricPermutationProduct;
 
 namespace internal {
 
-template<typename T,int Rows,int Cols> struct sparse_eval;
+template<typename T,int Rows,int Cols,int Flags> struct sparse_eval;
 
 template<typename T> struct eval<T,Sparse>
-  : public sparse_eval<T, traits<T>::RowsAtCompileTime,traits<T>::ColsAtCompileTime>
+  : sparse_eval<T, traits<T>::RowsAtCompileTime,traits<T>::ColsAtCompileTime,traits<T>::Flags>
 {};
 
-template<typename T,int Cols> struct sparse_eval<T,1,Cols> {
-    typedef typename traits<T>::Scalar _Scalar;
-    typedef typename traits<T>::Index _Index;
-  public:
-    typedef SparseVector<_Scalar, RowMajor, _Index> type;
-};
-
-template<typename T,int Rows> struct sparse_eval<T,Rows,1> {
-    typedef typename traits<T>::Scalar _Scalar;
-    typedef typename traits<T>::Index _Index;
-  public:
-    typedef SparseVector<_Scalar, ColMajor, _Index> type;
-};
-
-template<typename T,int Rows,int Cols> struct sparse_eval {
-    typedef typename traits<T>::Scalar _Scalar;
-    typedef typename traits<T>::Index _Index;
-    enum { _Options = ((traits<T>::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor };
-  public:
-    typedef SparseMatrix<_Scalar, _Options, _Index> type;
-};
-
-template<typename T> struct sparse_eval<T,1,1> {
+template<typename T,int Cols,int Flags> struct sparse_eval<T,1,Cols,Flags> {
+    typedef typename traits<T>::Scalar _Scalar;
+    typedef typename traits<T>::StorageIndex _StorageIndex;
+  public:
+    typedef SparseVector<_Scalar, RowMajor, _StorageIndex> type;
+};
+
+template<typename T,int Rows,int Flags> struct sparse_eval<T,Rows,1,Flags> {
+    typedef typename traits<T>::Scalar _Scalar;
+    typedef typename traits<T>::StorageIndex _StorageIndex;
+  public:
+    typedef SparseVector<_Scalar, ColMajor, _StorageIndex> type;
+};
+
+// TODO this seems almost identical to plain_matrix_type<T, Sparse>
+template<typename T,int Rows,int Cols,int Flags> struct sparse_eval {
+    typedef typename traits<T>::Scalar _Scalar;
+    typedef typename traits<T>::StorageIndex _StorageIndex;
+    enum { _Options = ((Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor };
+  public:
+    typedef SparseMatrix<_Scalar, _Options, _StorageIndex> type;
+};
+
+template<typename T,int Flags> struct sparse_eval<T,1,1,Flags> {
     typedef typename traits<T>::Scalar _Scalar;
   public:
     typedef Matrix<_Scalar, 1, 1> type;
 };
 
 template<typename T> struct plain_matrix_type<T,Sparse>
 {
   typedef typename traits<T>::Scalar _Scalar;
-  typedef typename traits<T>::Index _Index;
-  enum { _Options = ((traits<T>::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor };
+  typedef typename traits<T>::StorageIndex _StorageIndex;
+  enum { _Options = ((evaluator<T>::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor };
   public:
-    typedef SparseMatrix<_Scalar, _Options, _Index> type;
+    typedef SparseMatrix<_Scalar, _Options, _StorageIndex> type;
+};
+
+template<typename T>
+struct plain_object_eval<T,Sparse>
+  : sparse_eval<T, traits<T>::RowsAtCompileTime,traits<T>::ColsAtCompileTime, evaluator<T>::Flags>
+{};
+
+template<typename Decomposition, typename RhsType>
+struct solve_traits<Decomposition,RhsType,Sparse>
+{
+  typedef typename sparse_eval<RhsType, RhsType::RowsAtCompileTime, RhsType::ColsAtCompileTime,traits<RhsType>::Flags>::type PlainObject;
+};
+
+template<typename Derived>
+struct generic_xpr_base<Derived, MatrixXpr, Sparse>
+{
+  typedef SparseMatrixBase<Derived> type;
 };
 
+struct SparseTriangularShape  { static std::string debugName() { return "SparseTriangularShape"; } };
+struct SparseSelfAdjointShape { static std::string debugName() { return "SparseSelfAdjointShape"; } };
+
+template<> struct glue_shapes<SparseShape,SelfAdjointShape> { typedef SparseSelfAdjointShape type;  };
+template<> struct glue_shapes<SparseShape,TriangularShape > { typedef SparseTriangularShape  type;  };
+
 } // end namespace internal
 
 /** \ingroup SparseCore_Module
   *
   * \class Triplet
@@ -143,31 +148,31 @@
   *
   * \brief A small structure to hold a non zero as a triplet (i,j,value).
   *
   * \sa SparseMatrix::setFromTriplets()
   */
-template<typename Scalar, typename Index=typename SparseMatrix<Scalar>::Index >
+template<typename Scalar, typename StorageIndex=typename SparseMatrix<Scalar>::StorageIndex >
 class Triplet
 {
 public:
   Triplet() : m_row(0), m_col(0), m_value(0) {}
 
-  Triplet(const Index& i, const Index& j, const Scalar& v = Scalar(0))
+  Triplet(const StorageIndex& i, const StorageIndex& j, const Scalar& v = Scalar(0))
     : m_row(i), m_col(j), m_value(v)
   {}
 
   /** \returns the row index of the element */
-  const Index& row() const { return m_row; }
+  const StorageIndex& row() const { return m_row; }
 
   /** \returns the column index of the element */
-  const Index& col() const { return m_col; }
+  const StorageIndex& col() const { return m_col; }
 
   /** \returns the value of the element */
   const Scalar& value() const { return m_value; }
 protected:
-  Index m_row, m_col;
+  StorageIndex m_row, m_col;
   Scalar m_value;
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSEUTIL_H

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseVector.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseVector.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseVector.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -20,30 +20,29 @@
   * \tparam _Scalar the scalar type, i.e. the type of the coefficients
   *
   * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
+  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
   */
 
 namespace internal {
-template<typename _Scalar, int _Options, typename _Index>
-struct traits<SparseVector<_Scalar, _Options, _Index> >
+template<typename _Scalar, int _Options, typename _StorageIndex>
+struct traits<SparseVector<_Scalar, _Options, _StorageIndex> >
 {
   typedef _Scalar Scalar;
-  typedef _Index Index;
+  typedef _StorageIndex StorageIndex;
   typedef Sparse StorageKind;
   typedef MatrixXpr XprKind;
   enum {
     IsColVector = (_Options & RowMajorBit) ? 0 : 1,
 
     RowsAtCompileTime = IsColVector ? Dynamic : 1,
     ColsAtCompileTime = IsColVector ? 1 : Dynamic,
     MaxRowsAtCompileTime = RowsAtCompileTime,
     MaxColsAtCompileTime = ColsAtCompileTime,
-    Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit),
-    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit) | CompressedAccessBit,
     SupportedAccessPatterns = InnerRandomAccessPattern
   };
 };
 
 // Sparse-Vector-Assignment kinds:
@@ -59,22 +58,22 @@
                              : SVA_Inner>
 struct sparse_vector_assign_selector;
 
 }
 
-template<typename _Scalar, int _Options, typename _Index>
+template<typename _Scalar, int _Options, typename _StorageIndex>
 class SparseVector
-  : public SparseMatrixBase<SparseVector<_Scalar, _Options, _Index> >
+  : public SparseCompressedBase<SparseVector<_Scalar, _Options, _StorageIndex> >
 {
-    typedef SparseMatrixBase<SparseVector> SparseBase;
-    
+    typedef SparseCompressedBase<SparseVector> Base;
+    using Base::convert_index;
   public:
     EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
     EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
     EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)
     
-    typedef internal::CompressedStorage<Scalar,Index> Storage;
+    typedef internal::CompressedStorage<Scalar,StorageIndex> Storage;
     enum { IsColVector = internal::traits<SparseVector>::IsColVector };
     
     enum {
       Options = _Options
     };
@@ -82,15 +81,20 @@
     EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; }
     EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; }
     EIGEN_STRONG_INLINE Index innerSize() const { return m_size; }
     EIGEN_STRONG_INLINE Index outerSize() const { return 1; }
 
-    EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return &m_data.value(0); }
-    EIGEN_STRONG_INLINE Scalar* valuePtr() { return &m_data.value(0); }
+    EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return m_data.valuePtr(); }
+    EIGEN_STRONG_INLINE Scalar* valuePtr() { return m_data.valuePtr(); }
+
+    EIGEN_STRONG_INLINE const StorageIndex* innerIndexPtr() const { return m_data.indexPtr(); }
+    EIGEN_STRONG_INLINE StorageIndex* innerIndexPtr() { return m_data.indexPtr(); }
 
-    EIGEN_STRONG_INLINE const Index* innerIndexPtr() const { return &m_data.index(0); }
-    EIGEN_STRONG_INLINE Index* innerIndexPtr() { return &m_data.index(0); }
+    inline const StorageIndex* outerIndexPtr() const { return 0; }
+    inline StorageIndex* outerIndexPtr() { return 0; }
+    inline const StorageIndex* innerNonZeroPtr() const { return 0; }
+    inline StorageIndex* innerNonZeroPtr() { return 0; }
     
     /** \internal */
     inline Storage& data() { return m_data; }
     /** \internal */
     inline const Storage& data() const { return m_data; }
@@ -101,17 +105,17 @@
       return coeff(IsColVector ? row : col);
     }
     inline Scalar coeff(Index i) const
     {
       eigen_assert(i>=0 && i<m_size);
-      return m_data.at(i);
+      return m_data.at(StorageIndex(i));
     }
 
     inline Scalar& coeffRef(Index row, Index col)
     {
       eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
-      return coeff(IsColVector ? row : col);
+      return coeffRef(IsColVector ? row : col);
     }
 
     /** \returns a reference to the coefficient value at given index \a i
       * This operation involes a log(rho*size) binary search. If the coefficient does not
       * exist yet, then a sorted insertion into a sequential buffer is performed.
@@ -119,22 +123,23 @@
       * This insertion might be very costly if the number of nonzeros above \a i is large.
       */
     inline Scalar& coeffRef(Index i)
     {
       eigen_assert(i>=0 && i<m_size);
-      return m_data.atWithInsertion(i);
+
+      return m_data.atWithInsertion(StorageIndex(i));
     }
 
   public:
 
-    class InnerIterator;
-    class ReverseInnerIterator;
+    typedef typename Base::InnerIterator InnerIterator;
+    typedef typename Base::ReverseInnerIterator ReverseInnerIterator;
 
     inline void setZero() { m_data.clear(); }
 
     /** \returns the number of non zero coefficients */
-    inline Index nonZeros() const  { return static_cast<Index>(m_data.size()); }
+    inline Index nonZeros() const  { return m_data.size(); }
 
     inline void startVec(Index outer)
     {
       EIGEN_UNUSED_VARIABLE(outer);
       eigen_assert(outer==0);
@@ -149,17 +154,30 @@
     inline Scalar& insertBack(Index i)
     {
       m_data.append(0, i);
       return m_data.value(m_data.size()-1);
     }
+    
+    Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner)
+    {
+      EIGEN_UNUSED_VARIABLE(outer);
+      eigen_assert(outer==0);
+      return insertBackUnordered(inner);
+    }
+    inline Scalar& insertBackUnordered(Index i)
+    {
+      m_data.append(0, i);
+      return m_data.value(m_data.size()-1);
+    }
 
     inline Scalar& insert(Index row, Index col)
     {
       eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size));
       
       Index inner = IsColVector ? row : col;
       Index outer = IsColVector ? col : row;
+      EIGEN_ONLY_USED_FOR_DEBUG(outer);
       eigen_assert(outer==0);
       return insert(inner);
     }
     Scalar& insert(Index i)
     {
@@ -174,11 +192,11 @@
       {
         m_data.index(p+1) = m_data.index(p);
         m_data.value(p+1) = m_data.value(p);
         --p;
       }
-      m_data.index(p+1) = i;
+      m_data.index(p+1) = convert_index(i);
       m_data.value(p+1) = 0;
       return m_data.value(p+1);
     }
 
     /**
@@ -186,45 +204,79 @@
     inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }
 
 
     inline void finalize() {}
 
+    /** \copydoc SparseMatrix::prune(const Scalar&,const RealScalar&) */
     void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
     {
       m_data.prune(reference,epsilon);
     }
 
+    /** Resizes the sparse vector to \a rows x \a cols
+      *
+      * This method is provided for compatibility with matrices.
+      * For a column vector, \a cols must be equal to 1.
+      * For a row vector, \a rows must be equal to 1.
+      *
+      * \sa resize(Index)
+      */
     void resize(Index rows, Index cols)
     {
-      eigen_assert(rows==1 || cols==1);
+      eigen_assert((IsColVector ? cols : rows)==1 && "Outer dimension must equal 1");
       resize(IsColVector ? rows : cols);
     }
 
+    /** Resizes the sparse vector to \a newSize
+      * This method deletes all entries, thus leaving an empty sparse vector
+      *
+      * \sa  conservativeResize(), setZero() */
     void resize(Index newSize)
     {
       m_size = newSize;
       m_data.clear();
     }
+
+    /** Resizes the sparse vector to \a newSize, while leaving old values untouched.
+      *
+      * If the size of the vector is decreased, then the storage of the out-of bounds coefficients is kept and reserved.
+      * Call .data().squeeze() to free extra memory.
+      *
+      * \sa reserve(), setZero()
+      */
+    void conservativeResize(Index newSize)
+    {
+      if (newSize < m_size)
+      {
+        Index i = 0;
+        while (i<m_data.size() && m_data.index(i)<newSize) ++i;
+        m_data.resize(i);
+      }
+      m_size = newSize;
+    }
 
     void resizeNonZeros(Index size) { m_data.resize(size); }
 
     inline SparseVector() : m_size(0) { check_template_parameters(); resize(0); }
 
-    inline SparseVector(Index size) : m_size(0) { check_template_parameters(); resize(size); }
+    explicit inline SparseVector(Index size) : m_size(0) { check_template_parameters(); resize(size); }
 
     inline SparseVector(Index rows, Index cols) : m_size(0) { check_template_parameters(); resize(rows,cols); }
 
     template<typename OtherDerived>
     inline SparseVector(const SparseMatrixBase<OtherDerived>& other)
       : m_size(0)
     {
+      #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
+        EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
+      #endif
       check_template_parameters();
       *this = other.derived();
     }
 
     inline SparseVector(const SparseVector& other)
-      : SparseBase(other), m_size(0)
+      : Base(other), m_size(0)
     {
       check_template_parameters();
       *this = other.derived();
     }
 
@@ -235,10 +287,18 @@
     inline void swap(SparseVector& other)
     {
       std::swap(m_size, other.m_size);
       m_data.swap(other.m_data);
     }
+
+    template<int OtherOptions>
+    inline void swap(SparseMatrix<Scalar,OtherOptions,StorageIndex>& other)
+    {
+      eigen_assert(other.outerSize()==1);
+      std::swap(m_size, other.m_innerSize);
+      m_data.swap(other.m_data);
+    }
 
     inline SparseVector& operator=(const SparseVector& other)
     {
       if (other.isRValue())
       {
@@ -334,100 +394,71 @@
 
 protected:
   
     static void check_template_parameters()
     {
-      EIGEN_STATIC_ASSERT(NumTraits<Index>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
+      EIGEN_STATIC_ASSERT(NumTraits<StorageIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
       EIGEN_STATIC_ASSERT((_Options&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS);
     }
     
     Storage m_data;
     Index m_size;
 };
 
-template<typename Scalar, int _Options, typename _Index>
-class SparseVector<Scalar,_Options,_Index>::InnerIterator
-{
-  public:
-    InnerIterator(const SparseVector& vec, Index outer=0)
-      : m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size()))
-    {
-      EIGEN_UNUSED_VARIABLE(outer);
-      eigen_assert(outer==0);
-    }
-
-    InnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
-      : m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size()))
-    {}
-
-    inline InnerIterator& operator++() { m_id++; return *this; }
-
-    inline Scalar value() const { return m_data.value(m_id); }
-    inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id)); }
-
-    inline Index index() const { return m_data.index(m_id); }
-    inline Index row() const { return IsColVector ? index() : 0; }
-    inline Index col() const { return IsColVector ? 0 : index(); }
-
-    inline operator bool() const { return (m_id < m_end); }
-
-  protected:
-    const internal::CompressedStorage<Scalar,Index>& m_data;
-    Index m_id;
-    const Index m_end;
-};
-
-template<typename Scalar, int _Options, typename _Index>
-class SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator
-{
-  public:
-    ReverseInnerIterator(const SparseVector& vec, Index outer=0)
-      : m_data(vec.m_data), m_id(static_cast<Index>(m_data.size())), m_start(0)
-    {
-      EIGEN_UNUSED_VARIABLE(outer);
-      eigen_assert(outer==0);
-    }
-
-    ReverseInnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
-      : m_data(data), m_id(static_cast<Index>(m_data.size())), m_start(0)
-    {}
-
-    inline ReverseInnerIterator& operator--() { m_id--; return *this; }
-
-    inline Scalar value() const { return m_data.value(m_id-1); }
-    inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id-1)); }
-
-    inline Index index() const { return m_data.index(m_id-1); }
-    inline Index row() const { return IsColVector ? index() : 0; }
-    inline Index col() const { return IsColVector ? 0 : index(); }
-
-    inline operator bool() const { return (m_id > m_start); }
-
-  protected:
-    const internal::CompressedStorage<Scalar,Index>& m_data;
-    Index m_id;
-    const Index m_start;
-};
-
-namespace internal {
+namespace internal {
+
+template<typename _Scalar, int _Options, typename _Index>
+struct evaluator<SparseVector<_Scalar,_Options,_Index> >
+  : evaluator_base<SparseVector<_Scalar,_Options,_Index> >
+{
+  typedef SparseVector<_Scalar,_Options,_Index> SparseVectorType;
+  typedef evaluator_base<SparseVectorType> Base;
+  typedef typename SparseVectorType::InnerIterator InnerIterator;
+  typedef typename SparseVectorType::ReverseInnerIterator ReverseInnerIterator;
+  
+  enum {
+    CoeffReadCost = NumTraits<_Scalar>::ReadCost,
+    Flags = SparseVectorType::Flags
+  };
+
+  evaluator() : Base() {}
+  
+  explicit evaluator(const SparseVectorType &mat) : m_matrix(&mat)
+  {
+    EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
+  }
+  
+  inline Index nonZerosEstimate() const {
+    return m_matrix->nonZeros();
+  }
+  
+  operator SparseVectorType&() { return m_matrix->const_cast_derived(); }
+  operator const SparseVectorType&() const { return *m_matrix; }
+  
+  const SparseVectorType *m_matrix;
+};
 
 template< typename Dest, typename Src>
 struct sparse_vector_assign_selector<Dest,Src,SVA_Inner> {
   static void run(Dest& dst, const Src& src) {
     eigen_internal_assert(src.innerSize()==src.size());
-    for(typename Src::InnerIterator it(src, 0); it; ++it)
+    typedef internal::evaluator<Src> SrcEvaluatorType;
+    SrcEvaluatorType srcEval(src);
+    for(typename SrcEvaluatorType::InnerIterator it(srcEval, 0); it; ++it)
       dst.insert(it.index()) = it.value();
   }
 };
 
 template< typename Dest, typename Src>
 struct sparse_vector_assign_selector<Dest,Src,SVA_Outer> {
   static void run(Dest& dst, const Src& src) {
     eigen_internal_assert(src.outerSize()==src.size());
-    for(typename Dest::Index i=0; i<src.size(); ++i)
+    typedef internal::evaluator<Src> SrcEvaluatorType;
+    SrcEvaluatorType srcEval(src);
+    for(Index i=0; i<src.size(); ++i)
     {
-      typename Src::InnerIterator it(src, i);
+      typename SrcEvaluatorType::InnerIterator it(srcEval, i);
       if(it)
         dst.insert(i) = it.value();
     }
   }
 };

Index: 3rd_party/eigen/Eigen/src/SparseCore/SparseView.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/SparseView.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/SparseView.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Daniel Lowengrub <lowdanie@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -16,84 +16,238 @@
 namespace internal {
 
 template<typename MatrixType>
 struct traits<SparseView<MatrixType> > : traits<MatrixType>
 {
-  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::StorageIndex StorageIndex;
   typedef Sparse StorageKind;
   enum {
     Flags = int(traits<MatrixType>::Flags) & (RowMajorBit)
   };
 };
 
 } // end namespace internal
 
+/** \ingroup SparseCore_Module
+  * \class SparseView
+  *
+  * \brief Expression of a dense or sparse matrix with zero or too small values removed
+  *
+  * \tparam MatrixType the type of the object of which we are removing the small entries
+  *
+  * This class represents an expression of a given dense or sparse matrix with
+  * entries smaller than \c reference * \c epsilon are removed.
+  * It is the return type of MatrixBase::sparseView() and SparseMatrixBase::pruned()
+  * and most of the time this is the only way it is used.
+  *
+  * \sa MatrixBase::sparseView(), SparseMatrixBase::pruned()
+  */
 template<typename MatrixType>
 class SparseView : public SparseMatrixBase<SparseView<MatrixType> >
 {
   typedef typename MatrixType::Nested MatrixTypeNested;
   typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
+  typedef SparseMatrixBase<SparseView > Base;
 public:
   EIGEN_SPARSE_PUBLIC_INTERFACE(SparseView)
+  typedef typename internal::remove_all<MatrixType>::type NestedExpression;
 
-  SparseView(const MatrixType& mat, const Scalar& m_reference = Scalar(0),
-             typename NumTraits<Scalar>::Real m_epsilon = NumTraits<Scalar>::dummy_precision()) : 
-    m_matrix(mat), m_reference(m_reference), m_epsilon(m_epsilon) {}
-
-  class InnerIterator;
+  explicit SparseView(const MatrixType& mat, const Scalar& reference = Scalar(0),
+                      const RealScalar &epsilon = NumTraits<Scalar>::dummy_precision())
+    : m_matrix(mat), m_reference(reference), m_epsilon(epsilon) {}
 
   inline Index rows() const { return m_matrix.rows(); }
   inline Index cols() const { return m_matrix.cols(); }
 
   inline Index innerSize() const { return m_matrix.innerSize(); }
   inline Index outerSize() const { return m_matrix.outerSize(); }
-
+  
+  /** \returns the nested expression */
+  const typename internal::remove_all<MatrixTypeNested>::type&
+  nestedExpression() const { return m_matrix; }
+  
+  Scalar reference() const { return m_reference; }
+  RealScalar epsilon() const { return m_epsilon; }
+  
 protected:
   MatrixTypeNested m_matrix;
   Scalar m_reference;
-  typename NumTraits<Scalar>::Real m_epsilon;
-};
-
-template<typename MatrixType>
-class SparseView<MatrixType>::InnerIterator : public _MatrixTypeNested::InnerIterator
-{
-  typedef typename SparseView::Index Index;
-public:
-  typedef typename _MatrixTypeNested::InnerIterator IterBase;
-  InnerIterator(const SparseView& view, Index outer) :
-  IterBase(view.m_matrix, outer), m_view(view)
-  {
-    incrementToNonZero();
-  }
-
-  EIGEN_STRONG_INLINE InnerIterator& operator++()
-  {
-    IterBase::operator++();
-    incrementToNonZero();
-    return *this;
-  }
-
-  using IterBase::value;
-
-protected:
-  const SparseView& m_view;
-
-private:
-  void incrementToNonZero()
-  {
-    while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.m_reference, m_view.m_epsilon))
-    {
-      IterBase::operator++();
-    }
-  }
-};
-
-template<typename Derived>
-const SparseView<Derived> MatrixBase<Derived>::sparseView(const Scalar& m_reference,
-                                                          const typename NumTraits<Scalar>::Real& m_epsilon) const
-{
-  return SparseView<Derived>(derived(), m_reference, m_epsilon);
+  RealScalar m_epsilon;
+};
+
+namespace internal {
+
+// TODO find a way to unify the two following variants
+// This is tricky because implementing an inner iterator on top of an IndexBased evaluator is
+// not easy because the evaluators do not expose the sizes of the underlying expression.
+  
+template<typename ArgType>
+struct unary_evaluator<SparseView<ArgType>, IteratorBased>
+  : public evaluator_base<SparseView<ArgType> >
+{
+    typedef typename evaluator<ArgType>::InnerIterator EvalIterator;
+  public:
+    typedef SparseView<ArgType> XprType;
+    
+    class InnerIterator : public EvalIterator
+    {
+        typedef typename XprType::Scalar Scalar;
+      public:
+
+        EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer)
+          : EvalIterator(sve.m_argImpl,outer), m_view(sve.m_view)
+        {
+          incrementToNonZero();
+        }
+
+        EIGEN_STRONG_INLINE InnerIterator& operator++()
+        {
+          EvalIterator::operator++();
+          incrementToNonZero();
+          return *this;
+        }
+
+        using EvalIterator::value;
+
+      protected:
+        const XprType &m_view;
+
+      private:
+        void incrementToNonZero()
+        {
+          while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.reference(), m_view.epsilon()))
+          {
+            EvalIterator::operator++();
+          }
+        }
+    };
+    
+    enum {
+      CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+      Flags = XprType::Flags
+    };
+    
+    explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {}
+
+  protected:
+    evaluator<ArgType> m_argImpl;
+    const XprType &m_view;
+};
+
+template<typename ArgType>
+struct unary_evaluator<SparseView<ArgType>, IndexBased>
+  : public evaluator_base<SparseView<ArgType> >
+{
+  public:
+    typedef SparseView<ArgType> XprType;
+  protected:
+    enum { IsRowMajor = (XprType::Flags&RowMajorBit)==RowMajorBit };
+    typedef typename XprType::Scalar Scalar;
+    typedef typename XprType::StorageIndex StorageIndex;
+  public:
+    
+    class InnerIterator
+    {
+      public:
+
+        EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer)
+          : m_sve(sve), m_inner(0), m_outer(outer), m_end(sve.m_view.innerSize())
+        {
+          incrementToNonZero();
+        }
+
+        EIGEN_STRONG_INLINE InnerIterator& operator++()
+        {
+          m_inner++;
+          incrementToNonZero();
+          return *this;
+        }
+
+        EIGEN_STRONG_INLINE Scalar value() const
+        {
+          return (IsRowMajor) ? m_sve.m_argImpl.coeff(m_outer, m_inner)
+                              : m_sve.m_argImpl.coeff(m_inner, m_outer);
+        }
+
+        EIGEN_STRONG_INLINE StorageIndex index() const { return m_inner; }
+        inline Index row() const { return IsRowMajor ? m_outer : index(); }
+        inline Index col() const { return IsRowMajor ? index() : m_outer; }
+
+        EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
+
+      protected:
+        const unary_evaluator &m_sve;
+        Index m_inner;
+        const Index m_outer;
+        const Index m_end;
+
+      private:
+        void incrementToNonZero()
+        {
+          while((bool(*this)) && internal::isMuchSmallerThan(value(), m_sve.m_view.reference(), m_sve.m_view.epsilon()))
+          {
+            m_inner++;
+          }
+        }
+    };
+    
+    enum {
+      CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
+      Flags = XprType::Flags
+    };
+    
+    explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {}
+
+  protected:
+    evaluator<ArgType> m_argImpl;
+    const XprType &m_view;
+};
+
+} // end namespace internal
+
+/** \ingroup SparseCore_Module
+  *
+  * \returns a sparse expression of the dense expression \c *this with values smaller than
+  * \a reference * \a epsilon removed.
+  *
+  * This method is typically used when prototyping to convert a quickly assembled dense Matrix \c D to a SparseMatrix \c S:
+  * \code
+  * MatrixXd D(n,m);
+  * SparseMatrix<double> S;
+  * S = D.sparseView();             // suppress numerical zeros (exact)
+  * S = D.sparseView(reference);
+  * S = D.sparseView(reference,epsilon);
+  * \endcode
+  * where \a reference is a meaningful non zero reference value,
+  * and \a epsilon is a tolerance factor defaulting to NumTraits<Scalar>::dummy_precision().
+  *
+  * \sa SparseMatrixBase::pruned(), class SparseView */
+template<typename Derived>
+const SparseView<Derived> MatrixBase<Derived>::sparseView(const Scalar& reference,
+                                                          const typename NumTraits<Scalar>::Real& epsilon) const
+{
+  return SparseView<Derived>(derived(), reference, epsilon);
+}
+
+/** \returns an expression of \c *this with values smaller than
+  * \a reference * \a epsilon removed.
+  *
+  * This method is typically used in conjunction with the product of two sparse matrices
+  * to automatically prune the smallest values as follows:
+  * \code
+  * C = (A*B).pruned();             // suppress numerical zeros (exact)
+  * C = (A*B).pruned(ref);
+  * C = (A*B).pruned(ref,epsilon);
+  * \endcode
+  * where \c ref is a meaningful non zero reference value.
+  * */
+template<typename Derived>
+const SparseView<Derived>
+SparseMatrixBase<Derived>::pruned(const Scalar& reference,
+                                  const RealScalar& epsilon) const
+{
+  return SparseView<Derived>(derived(), reference, epsilon);
 }
 
 } // end namespace Eigen
 
 #endif

Index: 3rd_party/eigen/Eigen/src/SparseCore/TriangularSolver.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseCore/TriangularSolver.h
+++ 3rd_party/eigen/Eigen/src/SparseCore/TriangularSolver.h
@@ -26,20 +26,23 @@
 // forward substitution, row-major
 template<typename Lhs, typename Rhs, int Mode>
 struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,RowMajor>
 {
   typedef typename Rhs::Scalar Scalar;
+  typedef evaluator<Lhs> LhsEval;
+  typedef typename evaluator<Lhs>::InnerIterator LhsIterator;
   static void run(const Lhs& lhs, Rhs& other)
   {
-    for(int col=0 ; col<other.cols() ; ++col)
+    LhsEval lhsEval(lhs);
+    for(Index col=0 ; col<other.cols() ; ++col)
     {
-      for(int i=0; i<lhs.rows(); ++i)
+      for(Index i=0; i<lhs.rows(); ++i)
       {
         Scalar tmp = other.coeff(i,col);
         Scalar lastVal(0);
-        int lastIndex = 0;
-        for(typename Lhs::InnerIterator it(lhs, i); it; ++it)
+        Index lastIndex = 0;
+        for(LhsIterator it(lhsEval, i); it; ++it)
         {
           lastVal = it.value();
           lastIndex = it.index();
           if(lastIndex==i)
             break;
@@ -60,19 +63,22 @@
 // backward substitution, row-major
 template<typename Lhs, typename Rhs, int Mode>
 struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,RowMajor>
 {
   typedef typename Rhs::Scalar Scalar;
+  typedef evaluator<Lhs> LhsEval;
+  typedef typename evaluator<Lhs>::InnerIterator LhsIterator;
   static void run(const Lhs& lhs, Rhs& other)
   {
-    for(int col=0 ; col<other.cols() ; ++col)
+    LhsEval lhsEval(lhs);
+    for(Index col=0 ; col<other.cols() ; ++col)
     {
-      for(int i=lhs.rows()-1 ; i>=0 ; --i)
+      for(Index i=lhs.rows()-1 ; i>=0 ; --i)
       {
         Scalar tmp = other.coeff(i,col);
-        Scalar l_ii = 0;
-        typename Lhs::InnerIterator it(lhs, i);
+        Scalar l_ii(0);
+        LhsIterator it(lhsEval, i);
         while(it && it.index()<i)
           ++it;
         if(!(Mode & UnitDiag))
         {
           eigen_assert(it && it.index()==i);
@@ -84,14 +90,12 @@
         for(; it; ++it)
         {
           tmp -= it.value() * other.coeff(it.index(),col);
         }
 
-        if (Mode & UnitDiag)
-          other.coeffRef(i,col) = tmp;
-        else
-          other.coeffRef(i,col) = tmp/l_ii;
+        if (Mode & UnitDiag)  other.coeffRef(i,col) = tmp;
+        else                  other.coeffRef(i,col) = tmp/l_ii;
       }
     }
   }
 };
 
@@ -98,20 +102,23 @@
 // forward substitution, col-major
 template<typename Lhs, typename Rhs, int Mode>
 struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,ColMajor>
 {
   typedef typename Rhs::Scalar Scalar;
+  typedef evaluator<Lhs> LhsEval;
+  typedef typename evaluator<Lhs>::InnerIterator LhsIterator;
   static void run(const Lhs& lhs, Rhs& other)
   {
-    for(int col=0 ; col<other.cols() ; ++col)
+    LhsEval lhsEval(lhs);
+    for(Index col=0 ; col<other.cols() ; ++col)
     {
-      for(int i=0; i<lhs.cols(); ++i)
+      for(Index i=0; i<lhs.cols(); ++i)
       {
         Scalar& tmp = other.coeffRef(i,col);
         if (tmp!=Scalar(0)) // optimization when other is actually sparse
         {
-          typename Lhs::InnerIterator it(lhs, i);
+          LhsIterator it(lhsEval, i);
           while(it && it.index()<i)
             ++it;
           if(!(Mode & UnitDiag))
           {
             eigen_assert(it && it.index()==i);
@@ -130,29 +137,32 @@
 // backward substitution, col-major
 template<typename Lhs, typename Rhs, int Mode>
 struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,ColMajor>
 {
   typedef typename Rhs::Scalar Scalar;
+  typedef evaluator<Lhs> LhsEval;
+  typedef typename evaluator<Lhs>::InnerIterator LhsIterator;
   static void run(const Lhs& lhs, Rhs& other)
   {
-    for(int col=0 ; col<other.cols() ; ++col)
+    LhsEval lhsEval(lhs);
+    for(Index col=0 ; col<other.cols() ; ++col)
     {
-      for(int i=lhs.cols()-1; i>=0; --i)
+      for(Index i=lhs.cols()-1; i>=0; --i)
       {
         Scalar& tmp = other.coeffRef(i,col);
         if (tmp!=Scalar(0)) // optimization when other is actually sparse
         {
           if(!(Mode & UnitDiag))
           {
             // TODO replace this by a binary search. make sure the binary search is safe for partially sorted elements
-            typename Lhs::ReverseInnerIterator it(lhs, i);
+            LhsIterator it(lhsEval, i);
             while(it && it.index()!=i)
-              --it;
+              ++it;
             eigen_assert(it && it.index()==i);
             other.coeffRef(i,col) /= it.value();
           }
-          typename Lhs::InnerIterator it(lhs, i);
+          LhsIterator it(lhsEval, i);
           for(; it && it.index()<i; ++it)
             other.coeffRef(it.index(), col) -= tmp * it.value();
         }
       }
     }
@@ -159,38 +169,31 @@
   }
 };
 
 } // end namespace internal
 
-template<typename ExpressionType,int Mode>
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+
+template<typename ExpressionType,unsigned int Mode>
 template<typename OtherDerived>
-void SparseTriangularView<ExpressionType,Mode>::solveInPlace(MatrixBase<OtherDerived>& other) const
+void TriangularViewImpl<ExpressionType,Mode,Sparse>::solveInPlace(MatrixBase<OtherDerived>& other) const
 {
-  eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows());
+  eigen_assert(derived().cols() == derived().rows() && derived().cols() == other.rows());
   eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
 
   enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit };
 
   typedef typename internal::conditional<copy,
     typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::type OtherCopy;
   OtherCopy otherCopy(other.derived());
 
-  internal::sparse_solve_triangular_selector<ExpressionType, typename internal::remove_reference<OtherCopy>::type, Mode>::run(m_matrix, otherCopy);
+  internal::sparse_solve_triangular_selector<ExpressionType, typename internal::remove_reference<OtherCopy>::type, Mode>::run(derived().nestedExpression(), otherCopy);
 
   if (copy)
     other = otherCopy;
 }
-
-template<typename ExpressionType,int Mode>
-template<typename OtherDerived>
-typename internal::plain_matrix_type_column_major<OtherDerived>::type
-SparseTriangularView<ExpressionType,Mode>::solve(const MatrixBase<OtherDerived>& other) const
-{
-  typename internal::plain_matrix_type_column_major<OtherDerived>::type res(other);
-  solveInPlace(res);
-  return res;
-}
+#endif
 
 // pure sparse path
 
 namespace internal {
 
@@ -206,22 +209,22 @@
 // forward substitution, col-major
 template<typename Lhs, typename Rhs, int Mode, int UpLo>
 struct sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor>
 {
   typedef typename Rhs::Scalar Scalar;
-  typedef typename promote_index_type<typename traits<Lhs>::Index,
-                                         typename traits<Rhs>::Index>::type Index;
+  typedef typename promote_index_type<typename traits<Lhs>::StorageIndex,
+                                      typename traits<Rhs>::StorageIndex>::type StorageIndex;
   static void run(const Lhs& lhs, Rhs& other)
   {
     const bool IsLower = (UpLo==Lower);
-    AmbiVector<Scalar,Index> tempVector(other.rows()*2);
+    AmbiVector<Scalar,StorageIndex> tempVector(other.rows()*2);
     tempVector.setBounds(0,other.rows());
 
     Rhs res(other.rows(), other.cols());
     res.reserve(other.nonZeros());
 
-    for(int col=0 ; col<other.cols() ; ++col)
+    for(Index col=0 ; col<other.cols() ; ++col)
     {
       // FIXME estimate number of non zeros
       tempVector.init(.99/*float(other.col(col).nonZeros())/float(other.rows())*/);
       tempVector.setZero();
       tempVector.restart();
@@ -228,11 +231,11 @@
       for (typename Rhs::InnerIterator rhsIt(other, col); rhsIt; ++rhsIt)
       {
         tempVector.coeffRef(rhsIt.index()) = rhsIt.value();
       }
 
-      for(int i=IsLower?0:lhs.cols()-1;
+      for(Index i=IsLower?0:lhs.cols()-1;
           IsLower?i<lhs.cols():i>=0;
           i+=IsLower?1:-1)
       {
         tempVector.restart();
         Scalar& ci = tempVector.coeffRef(i);
@@ -265,13 +268,13 @@
           }
         }
       }
 
 
-      int count = 0;
+      Index count = 0;
       // FIXME compute a reference value to filter zeros
-      for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector/*,1e-12*/); it; ++it)
+      for (typename AmbiVector<Scalar,StorageIndex>::Iterator it(tempVector/*,1e-12*/); it; ++it)
       {
         ++ count;
 //         std::cerr << "fill " << it.index() << ", " << col << "\n";
 //         std::cout << it.value() << "  ";
         // FIXME use insertBack
@@ -284,51 +287,29 @@
   }
 };
 
 } // end namespace internal
 
-template<typename ExpressionType,int Mode>
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename ExpressionType,unsigned int Mode>
 template<typename OtherDerived>
-void SparseTriangularView<ExpressionType,Mode>::solveInPlace(SparseMatrixBase<OtherDerived>& other) const
+void TriangularViewImpl<ExpressionType,Mode,Sparse>::solveInPlace(SparseMatrixBase<OtherDerived>& other) const
 {
-  eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows());
+  eigen_assert(derived().cols() == derived().rows() && derived().cols() == other.rows());
   eigen_assert( (!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
 
 //   enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit };
 
 //   typedef typename internal::conditional<copy,
 //     typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::type OtherCopy;
 //   OtherCopy otherCopy(other.derived());
 
-  internal::sparse_solve_triangular_sparse_selector<ExpressionType, OtherDerived, Mode>::run(m_matrix, other.derived());
+  internal::sparse_solve_triangular_sparse_selector<ExpressionType, OtherDerived, Mode>::run(derived().nestedExpression(), other.derived());
 
 //   if (copy)
 //     other = otherCopy;
 }
-
-#ifdef EIGEN2_SUPPORT
-
-// deprecated stuff:
-
-/** \deprecated */
-template<typename Derived>
-template<typename OtherDerived>
-void SparseMatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other) const
-{
-  this->template triangular<Flags&(Upper|Lower)>().solveInPlace(other);
-}
-
-/** \deprecated */
-template<typename Derived>
-template<typename OtherDerived>
-typename internal::plain_matrix_type_column_major<OtherDerived>::type
-SparseMatrixBase<Derived>::solveTriangular(const MatrixBase<OtherDerived>& other) const
-{
-  typename internal::plain_matrix_type_column_major<OtherDerived>::type res(other);
-  derived().solveTriangularInPlace(res);
-  return res;
-}
-#endif // EIGEN2_SUPPORT
+#endif
 
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSETRIANGULARSOLVER_H

DELETED 3rd_party/eigen/Eigen/src/SparseLU/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/SparseLU/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/SparseLU/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SparseLU_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_SparseLU_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SparseLU COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU.h
@@ -1,10 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
-// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2012-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -12,11 +12,11 @@
 #ifndef EIGEN_SPARSE_LU_H
 #define EIGEN_SPARSE_LU_H
 
 namespace Eigen {
 
-template <typename _MatrixType, typename _OrderingType = COLAMDOrdering<typename _MatrixType::Index> > class SparseLU;
+template <typename _MatrixType, typename _OrderingType = COLAMDOrdering<typename _MatrixType::StorageIndex> > class SparseLU;
 template <typename MappedSparseMatrixType> struct SparseLUMatrixLReturnType;
 template <typename MatrixLType, typename MatrixUType> struct SparseLUMatrixUReturnType;
 
 /** \ingroup SparseLU_Module
   * \class SparseLU
@@ -62,37 +62,49 @@
   * If this is the case for your matrices, you can try the basic scaling method at
   *  "unsupported/Eigen/src/IterativeSolvers/Scaling.h"
   * 
   * \tparam _MatrixType The type of the sparse matrix. It must be a column-major SparseMatrix<>
   * \tparam _OrderingType The ordering method to use, either AMD, COLAMD or METIS. Default is COLMAD
-  * 
+  *
+  * \implsparsesolverconcept
   * 
-  * \sa \ref TutorialSparseDirectSolvers
+  * \sa \ref TutorialSparseSolverConcept
   * \sa \ref OrderingMethods_Module
   */
 template <typename _MatrixType, typename _OrderingType>
-class SparseLU : public internal::SparseLUImpl<typename _MatrixType::Scalar, typename _MatrixType::Index>
+class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >, public internal::SparseLUImpl<typename _MatrixType::Scalar, typename _MatrixType::StorageIndex>
 {
+  protected:
+    typedef SparseSolverBase<SparseLU<_MatrixType,_OrderingType> > APIBase;
+    using APIBase::m_isInitialized;
   public:
+    using APIBase::_solve_impl;
+    
     typedef _MatrixType MatrixType; 
     typedef _OrderingType OrderingType;
     typedef typename MatrixType::Scalar Scalar; 
     typedef typename MatrixType::RealScalar RealScalar; 
-    typedef typename MatrixType::Index Index; 
-    typedef SparseMatrix<Scalar,ColMajor,Index> NCMatrix;
-    typedef internal::MappedSuperNodalMatrix<Scalar, Index> SCMatrix; 
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    typedef SparseMatrix<Scalar,ColMajor,StorageIndex> NCMatrix;
+    typedef internal::MappedSuperNodalMatrix<Scalar, StorageIndex> SCMatrix;
     typedef Matrix<Scalar,Dynamic,1> ScalarVector;
-    typedef Matrix<Index,Dynamic,1> IndexVector;
-    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
-    typedef internal::SparseLUImpl<Scalar, Index> Base;
+    typedef Matrix<StorageIndex,Dynamic,1> IndexVector;
+    typedef PermutationMatrix<Dynamic, Dynamic, StorageIndex> PermutationType;
+    typedef internal::SparseLUImpl<Scalar, StorageIndex> Base;
+
+    enum {
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
     
   public:
-    SparseLU():m_isInitialized(true),m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0),m_detPermR(1)
+    SparseLU():m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0),m_detPermR(1)
     {
       initperfvalues(); 
     }
-    SparseLU(const MatrixType& matrix):m_isInitialized(true),m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0),m_detPermR(1)
+    explicit SparseLU(const MatrixType& matrix)
+      : m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0),m_detPermR(1)
     {
       initperfvalues(); 
       compute(matrix);
     }
     
@@ -139,13 +151,13 @@
       * The only operation available with this expression is the triangular solve
       * \code
       * y = b; matrixU().solveInPlace(y);
       * \endcode
       */
-    SparseLUMatrixUReturnType<SCMatrix,MappedSparseMatrix<Scalar,ColMajor,Index> > matrixU() const
+    SparseLUMatrixUReturnType<SCMatrix,MappedSparseMatrix<Scalar,ColMajor,StorageIndex> > matrixU() const
     {
-      return SparseLUMatrixUReturnType<SCMatrix, MappedSparseMatrix<Scalar,ColMajor,Index> >(m_Lstore, m_Ustore);
+      return SparseLUMatrixUReturnType<SCMatrix, MappedSparseMatrix<Scalar,ColMajor,StorageIndex> >(m_Lstore, m_Ustore);
     }
 
     /**
       * \returns a reference to the row matrix permutation \f$ P_r \f$ such that \f$P_r A P_c^T = L U\f$
       * \sa colsPermutation()
@@ -166,37 +178,20 @@
     void setPivotThreshold(const RealScalar& thresh)
     {
       m_diagpivotthresh = thresh; 
     }
 
+#ifdef EIGEN_PARSED_BY_DOXYGEN
     /** \returns the solution X of \f$ A X = B \f$ using the current decomposition of A.
       *
       * \warning the destination matrix X in X = this->solve(B) must be colmun-major.
       *
       * \sa compute()
       */
     template<typename Rhs>
-    inline const internal::solve_retval<SparseLU, Rhs> solve(const MatrixBase<Rhs>& B) const 
-    {
-      eigen_assert(m_factorizationIsOk && "SparseLU is not initialized."); 
-      eigen_assert(rows()==B.rows()
-                    && "SparseLU::solve(): invalid number of rows of the right hand side matrix B");
-          return internal::solve_retval<SparseLU, Rhs>(*this, B.derived());
-    }
-
-    /** \returns the solution X of \f$ A X = B \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::sparse_solve_retval<SparseLU, Rhs> solve(const SparseMatrixBase<Rhs>& B) const 
-    {
-      eigen_assert(m_factorizationIsOk && "SparseLU is not initialized."); 
-      eigen_assert(rows()==B.rows()
-                    && "SparseLU::solve(): invalid number of rows of the right hand side matrix B");
-          return internal::sparse_solve_retval<SparseLU, Rhs>(*this, B.derived());
-    }
+    inline const Solve<SparseLU, Rhs> solve(const MatrixBase<Rhs>& B) const;
+#endif // EIGEN_PARSED_BY_DOXYGEN
     
     /** \brief Reports whether previous computation was successful.
       *
       * \returns \c Success if computation was succesful,
       *          \c NumericalIssue if the LU factorization reports a problem, zero diagonal for instance
@@ -217,11 +212,11 @@
     {
       return m_lastError; 
     }
 
     template<typename Rhs, typename Dest>
-    bool _solve(const MatrixBase<Rhs> &B, MatrixBase<Dest> &X_base) const
+    bool _solve_impl(const MatrixBase<Rhs> &B, MatrixBase<Dest> &X_base) const
     {
       Dest& X(X_base.derived());
       eigen_assert(m_factorizationIsOk && "The matrix should be factorized first");
       EIGEN_STATIC_ASSERT((Dest::Flags&RowMajorBit)==0,
                         THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
@@ -253,11 +248,95 @@
       * of large enough dimension, there is a risk of overflow/underflow.
       * One way to work around that is to use logAbsDeterminant() instead.
       *
       * \sa logAbsDeterminant(), signDeterminant()
       */
-     Scalar absDeterminant()
+    Scalar absDeterminant()
+    {
+      using std::abs;
+      eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
+      // Initialize with the determinant of the row matrix
+      Scalar det = Scalar(1.);
+      // Note that the diagonal blocks of U are stored in supernodes,
+      // which are available in the  L part :)
+      for (Index j = 0; j < this->cols(); ++j)
+      {
+        for (typename SCMatrix::InnerIterator it(m_Lstore, j); it; ++it)
+        {
+          if(it.index() == j)
+          {
+            det *= abs(it.value());
+            break;
+          }
+        }
+      }
+      return det;
+    }
+
+    /** \returns the natural log of the absolute value of the determinant of the matrix
+      * of which **this is the QR decomposition
+      *
+      * \note This method is useful to work around the risk of overflow/underflow that's
+      * inherent to the determinant computation.
+      *
+      * \sa absDeterminant(), signDeterminant()
+      */
+    Scalar logAbsDeterminant() const
+    {
+      using std::log;
+      using std::abs;
+
+      eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
+      Scalar det = Scalar(0.);
+      for (Index j = 0; j < this->cols(); ++j)
+      {
+        for (typename SCMatrix::InnerIterator it(m_Lstore, j); it; ++it)
+        {
+          if(it.row() < j) continue;
+          if(it.row() == j)
+          {
+            det += log(abs(it.value()));
+            break;
+          }
+        }
+      }
+      return det;
+    }
+
+    /** \returns A number representing the sign of the determinant
+      *
+      * \sa absDeterminant(), logAbsDeterminant()
+      */
+    Scalar signDeterminant()
+    {
+      eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
+      // Initialize with the determinant of the row matrix
+      Index det = 1;
+      // Note that the diagonal blocks of U are stored in supernodes,
+      // which are available in the  L part :)
+      for (Index j = 0; j < this->cols(); ++j)
+      {
+        for (typename SCMatrix::InnerIterator it(m_Lstore, j); it; ++it)
+        {
+          if(it.index() == j)
+          {
+            if(it.value()<0)
+              det = -det;
+            else if(it.value()==0)
+              return 0;
+            break;
+          }
+        }
+      }
+      return det * m_detPermR * m_detPermC;
+    }
+    
+    /** \returns The determinant of the matrix.
+      *
+      * \sa absDeterminant(), logAbsDeterminant()
+      */
+    Scalar determinant()
     {
       eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
       // Initialize with the determinant of the row matrix
       Scalar det = Scalar(1.);
       // Note that the diagonal blocks of U are stored in supernodes,
@@ -266,89 +345,51 @@
       {
         for (typename SCMatrix::InnerIterator it(m_Lstore, j); it; ++it)
         {
           if(it.index() == j)
           {
-            det *= (std::abs)(it.value());
-            break;
-          }
-        }
-       }
-       return det;
-     }
-
-     /** \returns the natural log of the absolute value of the determinant of the matrix
-       * of which **this is the QR decomposition
-       *
-       * \note This method is useful to work around the risk of overflow/underflow that's
-       * inherent to the determinant computation.
-       *
-       * \sa absDeterminant(), signDeterminant()
-       */
-     Scalar logAbsDeterminant() const
-     {
-       eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
-       Scalar det = Scalar(0.);
-       for (Index j = 0; j < this->cols(); ++j)
-       {
-         for (typename SCMatrix::InnerIterator it(m_Lstore, j); it; ++it)
-         {
-           if(it.row() < j) continue;
-           if(it.row() == j)
-           {
-             det += (std::log)((std::abs)(it.value()));
-             break;
-           }
-         }
-       }
-       return det;
-     }
-
-     /** \returns A number representing the sign of the determinant
-       *
-       * \sa absDeterminant(), logAbsDeterminant()
-       */
-     Scalar signDeterminant()
-     {
-       eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
-       return Scalar(m_detPermR);
-     }
+            det *= it.value();
+            break;
+          }
+        }
+      }
+      return (m_detPermR * m_detPermC) > 0 ? det : -det;
+    }
 
   protected:
     // Functions 
     void initperfvalues()
     {
-      m_perfv.panel_size = 1;
+      m_perfv.panel_size = 16;
       m_perfv.relax = 1; 
       m_perfv.maxsuper = 128; 
       m_perfv.rowblk = 16; 
       m_perfv.colblk = 8; 
       m_perfv.fillfactor = 20;  
     }
       
     // Variables 
     mutable ComputationInfo m_info;
-    bool m_isInitialized;
     bool m_factorizationIsOk;
     bool m_analysisIsOk;
     std::string m_lastError;
     NCMatrix m_mat; // The input (permuted ) matrix 
     SCMatrix m_Lstore; // The lower triangular matrix (supernodal)
-    MappedSparseMatrix<Scalar,ColMajor,Index> m_Ustore; // The upper triangular matrix
+    MappedSparseMatrix<Scalar,ColMajor,StorageIndex> m_Ustore; // The upper triangular matrix
     PermutationType m_perm_c; // Column permutation 
     PermutationType m_perm_r ; // Row permutation
     IndexVector m_etree; // Column elimination tree 
     
     typename Base::GlobalLU_t m_glu; 
                                
     // SparseLU options 
     bool m_symmetricmode;
     // values for performance 
-    internal::perfvalues<Index> m_perfv; 
+    internal::perfvalues m_perfv;
     RealScalar m_diagpivotthresh; // Specifies the threshold used for a diagonal entry to be an acceptable pivot
-    Index m_nnzL, m_nnzU; // Nonzeros in L and U factors 
-    Index m_detPermR; // Determinant of the coefficient matrix
+    Index m_nnzL, m_nnzU; // Nonzeros in L and U factors
+    Index m_detPermR, m_detPermC; // Determinants of the permutation matrices
   private:
     // Disable copy constructor 
     SparseLU (const SparseLU& );
   
 }; // End class SparseLU
@@ -370,43 +411,45 @@
 void SparseLU<MatrixType, OrderingType>::analyzePattern(const MatrixType& mat)
 {
   
   //TODO  It is possible as in SuperLU to compute row and columns scaling vectors to equilibrate the matrix mat.
   
+  // Firstly, copy the whole input matrix. 
+  m_mat = mat;
+  
+  // Compute fill-in ordering
   OrderingType ord; 
-  ord(mat,m_perm_c);
+  ord(m_mat,m_perm_c);
   
   // Apply the permutation to the column of the input  matrix
-  //First copy the whole input matrix. 
-  m_mat = mat;
-  if (m_perm_c.size()) {
+  if (m_perm_c.size())
+  {
     m_mat.uncompress(); //NOTE: The effect of this command is only to create the InnerNonzeros pointers. FIXME : This vector is filled but not subsequently used.  
-    //Then, permute only the column pointers
-    const Index * outerIndexPtr;
-    if (mat.isCompressed()) outerIndexPtr = mat.outerIndexPtr();
-    else
-    {
-      Index *outerIndexPtr_t = new Index[mat.cols()+1];
-      for(Index i = 0; i <= mat.cols(); i++) outerIndexPtr_t[i] = m_mat.outerIndexPtr()[i];
-      outerIndexPtr = outerIndexPtr_t;
-    }
+    // Then, permute only the column pointers
+    ei_declare_aligned_stack_constructed_variable(StorageIndex,outerIndexPtr,mat.cols()+1,mat.isCompressed()?const_cast<StorageIndex*>(mat.outerIndexPtr()):0);
+    
+    // If the input matrix 'mat' is uncompressed, then the outer-indices do not match the ones of m_mat, and a copy is thus needed.
+    if(!mat.isCompressed()) 
+      IndexVector::Map(outerIndexPtr, mat.cols()+1) = IndexVector::Map(m_mat.outerIndexPtr(),mat.cols()+1);
+    
+    // Apply the permutation and compute the nnz per column.
     for (Index i = 0; i < mat.cols(); i++)
     {
       m_mat.outerIndexPtr()[m_perm_c.indices()(i)] = outerIndexPtr[i];
       m_mat.innerNonZeroPtr()[m_perm_c.indices()(i)] = outerIndexPtr[i+1] - outerIndexPtr[i];
     }
-    if(!mat.isCompressed()) delete[] outerIndexPtr;
   }
+  
   // Compute the column elimination tree of the permuted matrix 
   IndexVector firstRowElt;
   internal::coletree(m_mat, m_etree,firstRowElt); 
      
   // In symmetric mode, do not do postorder here
   if (!m_symmetricmode) {
     IndexVector post, iwork; 
     // Post order etree
-    internal::treePostorder(m_mat.cols(), m_etree, post); 
+    internal::treePostorder(StorageIndex(m_mat.cols()), m_etree, post); 
       
    
     // Renumber etree in postorder 
     Index m = m_mat.cols(); 
     iwork.resize(m+1);
@@ -454,25 +497,27 @@
 {
   using internal::emptyIdxLU;
   eigen_assert(m_analysisIsOk && "analyzePattern() should be called first"); 
   eigen_assert((matrix.rows() == matrix.cols()) && "Only for squared matrices");
   
-  typedef typename IndexVector::Scalar Index; 
+  typedef typename IndexVector::Scalar StorageIndex; 
+  
+  m_isInitialized = true;
   
   
   // Apply the column permutation computed in analyzepattern()
   //   m_mat = matrix * m_perm_c.inverse(); 
   m_mat = matrix;
   if (m_perm_c.size()) 
   {
     m_mat.uncompress(); //NOTE: The effect of this command is only to create the InnerNonzeros pointers.
     //Then, permute only the column pointers
-    const Index * outerIndexPtr;
+    const StorageIndex * outerIndexPtr;
     if (matrix.isCompressed()) outerIndexPtr = matrix.outerIndexPtr();
     else
     {
-      Index* outerIndexPtr_t = new Index[matrix.cols()+1];
+      StorageIndex* outerIndexPtr_t = new StorageIndex[matrix.cols()+1];
       for(Index i = 0; i <= matrix.cols(); i++) outerIndexPtr_t[i] = m_mat.outerIndexPtr()[i];
       outerIndexPtr = outerIndexPtr_t;
     }
     for (Index i = 0; i < matrix.cols(); i++)
     {
@@ -482,11 +527,11 @@
     if(!matrix.isCompressed()) delete[] outerIndexPtr;
   } 
   else 
   { //FIXME This should not be needed if the empty permutation is handled transparently
     m_perm_c.resize(matrix.cols());
-    for(Index i = 0; i < matrix.cols(); ++i) m_perm_c.indices()(i) = i;
+    for(StorageIndex i = 0; i < matrix.cols(); ++i) m_perm_c.indices()(i) = i;
   }
   
   Index m = m_mat.rows();
   Index n = m_mat.cols();
   Index nnz = m_mat.nonZeros();
@@ -620,11 +665,12 @@
         m_factorizationIsOk = false; 
         return; 
       }
       
       // Update the determinant of the row permutation matrix
-      if (pivrow != jj) m_detPermR *= -1;
+      // FIXME: the following test is not correct, we should probably take iperm_c into account and pivrow is not directly the row pivot.
+      if (pivrow != jj) m_detPermR = -m_detPermR;
 
       // Prune columns (0:jj-1) using column jj
       Base::pruneL(jj, m_perm_r.indices(), pivrow, nseg, segrep, repfnz_k, xprune, m_glu); 
       
       // Reset repfnz for this column 
@@ -634,31 +680,33 @@
         repfnz_k(irep) = emptyIdxLU; 
       }
     } // end SparseLU within the panel  
     jcol += panel_size;  // Move to the next panel
   } // end for -- end elimination 
+  
+  m_detPermR = m_perm_r.determinant();
+  m_detPermC = m_perm_c.determinant();
   
   // Count the number of nonzeros in factors 
   Base::countnz(n, m_nnzL, m_nnzU, m_glu); 
   // Apply permutation  to the L subscripts 
-  Base::fixupL(n, m_perm_r.indices(), m_glu); 
+  Base::fixupL(n, m_perm_r.indices(), m_glu);
   
   // Create supernode matrix L 
   m_Lstore.setInfos(m, n, m_glu.lusup, m_glu.xlusup, m_glu.lsub, m_glu.xlsub, m_glu.supno, m_glu.xsup); 
   // Create the column major upper sparse matrix  U; 
-  new (&m_Ustore) MappedSparseMatrix<Scalar, ColMajor, Index> ( m, n, m_nnzU, m_glu.xusub.data(), m_glu.usub.data(), m_glu.ucol.data() ); 
+  new (&m_Ustore) MappedSparseMatrix<Scalar, ColMajor, StorageIndex> ( m, n, m_nnzU, m_glu.xusub.data(), m_glu.usub.data(), m_glu.ucol.data() );
   
   m_info = Success;
   m_factorizationIsOk = true;
 }
 
 template<typename MappedSupernodalType>
 struct SparseLUMatrixLReturnType : internal::no_assignment_operator
 {
-  typedef typename MappedSupernodalType::Index Index;
   typedef typename MappedSupernodalType::Scalar Scalar;
-  SparseLUMatrixLReturnType(const MappedSupernodalType& mapL) : m_mapL(mapL)
+  explicit SparseLUMatrixLReturnType(const MappedSupernodalType& mapL) : m_mapL(mapL)
   { }
   Index rows() { return m_mapL.rows(); }
   Index cols() { return m_mapL.cols(); }
   template<typename Dest>
   void solveInPlace( MatrixBase<Dest> &X) const
@@ -669,11 +717,10 @@
 };
 
 template<typename MatrixLType, typename MatrixUType>
 struct SparseLUMatrixUReturnType : internal::no_assignment_operator
 {
-  typedef typename MatrixLType::Index Index;
   typedef typename MatrixLType::Scalar Scalar;
   SparseLUMatrixUReturnType(const MatrixLType& mapL, const MatrixUType& mapU)
   : m_mapL(mapL),m_mapU(mapU)
   { }
   Index rows() { return m_mapL.rows(); }
@@ -680,11 +727,11 @@
   Index cols() { return m_mapL.cols(); }
 
   template<typename Dest>   void solveInPlace(MatrixBase<Dest> &X) const
   {
     Index nrhs = X.cols();
-    Index n = X.rows();
+    Index n    = X.rows();
     // Backward solve with U
     for (Index k = m_mapL.nsuper(); k >= 0; k--)
     {
       Index fsupc = m_mapL.supToCol()[k];
       Index lda = m_mapL.colIndexPtr()[fsupc+1] - m_mapL.colIndexPtr()[fsupc]; // leading dimension
@@ -698,12 +745,12 @@
           X(fsupc, j) /= m_mapL.valuePtr()[luptr];
         }
       }
       else
       {
-        Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(m_mapL.valuePtr()[luptr]), nsupc, nsupc, OuterStride<>(lda) );
-        Map< Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
+        Map<const Matrix<Scalar,Dynamic,Dynamic, ColMajor>, 0, OuterStride<> > A( &(m_mapL.valuePtr()[luptr]), nsupc, nsupc, OuterStride<>(lda) );
+        Map< Matrix<Scalar,Dynamic,Dest::ColsAtCompileTime, ColMajor>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
         U = A.template triangularView<Upper>().solve(U);
       }
 
       for (Index j = 0; j < nrhs; ++j)
       {
@@ -721,37 +768,8 @@
   }
   const MatrixLType& m_mapL;
   const MatrixUType& m_mapU;
 };
 
-namespace internal {
-  
-template<typename _MatrixType, typename Derived, typename Rhs>
-struct solve_retval<SparseLU<_MatrixType,Derived>, Rhs>
-  : solve_retval_base<SparseLU<_MatrixType,Derived>, Rhs>
-{
-  typedef SparseLU<_MatrixType,Derived> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-template<typename _MatrixType, typename Derived, typename Rhs>
-struct sparse_solve_retval<SparseLU<_MatrixType,Derived>, Rhs>
-  : sparse_solve_retval_base<SparseLU<_MatrixType,Derived>, Rhs>
-{
-  typedef SparseLU<_MatrixType,Derived> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    this->defaultEvalTo(dst);
-  }
-};
-} // end namespace internal
-
 } // End namespace Eigen 
 
 #endif

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLUImpl.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLUImpl.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLUImpl.h
@@ -14,21 +14,23 @@
   
 /** \ingroup SparseLU_Module
   * \class SparseLUImpl
   * Base class for sparseLU
   */
-template <typename Scalar, typename Index>
+template <typename Scalar, typename StorageIndex>
 class SparseLUImpl
 {
   public:
     typedef Matrix<Scalar,Dynamic,1> ScalarVector;
-    typedef Matrix<Index,Dynamic,1> IndexVector; 
+    typedef Matrix<StorageIndex,Dynamic,1> IndexVector; 
+    typedef Matrix<Scalar,Dynamic,Dynamic,ColMajor> ScalarMatrix;
+    typedef Map<ScalarMatrix, 0,  OuterStride<> > MappedMatrixBlock;
     typedef typename ScalarVector::RealScalar RealScalar; 
     typedef Ref<Matrix<Scalar,Dynamic,1> > BlockScalarVector;
-    typedef Ref<Matrix<Index,Dynamic,1> > BlockIndexVector;
+    typedef Ref<Matrix<StorageIndex,Dynamic,1> > BlockIndexVector;
     typedef LU_GlobalLU_t<IndexVector, ScalarVector> GlobalLU_t; 
-    typedef SparseMatrix<Scalar,ColMajor,Index> MatrixType; 
+    typedef SparseMatrix<Scalar,ColMajor,StorageIndex> MatrixType; 
     
   protected:
      template <typename VectorType>
      Index expand(VectorType& vec, Index& length, Index nbElts, Index keep_prev, Index& num_expansions);
      Index memInit(Index m, Index n, Index annz, Index lwork, Index fillratio, Index panel_size,  GlobalLU_t& glu); 
@@ -38,11 +40,11 @@
      void relax_snode (const Index n, IndexVector& et, const Index relax_columns, IndexVector& descendants, IndexVector& relax_end); 
      Index snode_dfs(const Index jcol, const Index kcol,const MatrixType& mat,  IndexVector& xprune, IndexVector& marker, GlobalLU_t& glu); 
      Index snode_bmod (const Index jcol, const Index fsupc, ScalarVector& dense, GlobalLU_t& glu);
      Index pivotL(const Index jcol, const RealScalar& diagpivotthresh, IndexVector& perm_r, IndexVector& iperm_c, Index& pivrow, GlobalLU_t& glu);
      template <typename Traits>
-     void dfs_kernel(const Index jj, IndexVector& perm_r,
+     void dfs_kernel(const StorageIndex jj, IndexVector& perm_r,
                     Index& nseg, IndexVector& panel_lsub, IndexVector& segrep,
                     Ref<IndexVector> repfnz_col, IndexVector& xprune, Ref<IndexVector> marker, IndexVector& parent,
                     IndexVector& xplore, GlobalLU_t& glu, Index& nextl_col, Index krow, Traits& traits);
      void panel_dfs(const Index m, const Index w, const Index jcol, MatrixType& A, IndexVector& perm_r, Index& nseg, ScalarVector& dense, IndexVector& panel_lsub, IndexVector& segrep, IndexVector& repfnz, IndexVector& xprune, IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu);
     

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Memory.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Memory.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Memory.h
@@ -34,17 +34,16 @@
 namespace Eigen {
 namespace internal {
   
 enum { LUNoMarker = 3 };
 enum {emptyIdxLU = -1};
-template<typename Index>
 inline Index LUnumTempV(Index& m, Index& w, Index& t, Index& b)
 {
   return (std::max)(m, (t+b)*w);
 }
 
-template< typename Scalar, typename Index>
+template< typename Scalar>
 inline Index LUTempSpace(Index&m, Index& w)
 {
   return (2*w + 4 + LUNoMarker) * m * sizeof(Index) + (w + 1) * m * sizeof(Scalar);
 }
 
@@ -57,13 +56,13 @@
   * \param[in,out] length  At input, contain the current length of the vector that is to be increased. At output, length of the newly allocated vector
   * \param[in] nbElts Current number of elements in the factors
   * \param keep_prev  1: use length  and do not expand the vector; 0: compute new_len and expand
   * \param[in,out] num_expansions Number of times the memory has been expanded
   */
-template <typename Scalar, typename Index>
+template <typename Scalar, typename StorageIndex>
 template <typename VectorType>
-Index  SparseLUImpl<Scalar,Index>::expand(VectorType& vec, Index& length, Index nbElts, Index keep_prev, Index& num_expansions) 
+Index  SparseLUImpl<Scalar,StorageIndex>::expand(VectorType& vec, Index& length, Index nbElts, Index keep_prev, Index& num_expansions) 
 {
   
   float alpha = 1.5; // Ratio of the memory increase 
   Index new_len; // New size of the allocated memory
   
@@ -146,17 +145,17 @@
  * \param fillratio estimated ratio of fill in the factors
  * \param panel_size Size of a panel
  * \return an estimated size of the required memory if lwork = -1; otherwise, return the size of actually allocated memory when allocation failed, and 0 on success
  * \note Unlike SuperLU, this routine does not support successive factorization with the same pattern and the same row permutation
  */
-template <typename Scalar, typename Index>
-Index SparseLUImpl<Scalar,Index>::memInit(Index m, Index n, Index annz, Index lwork, Index fillratio, Index panel_size,  GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+Index SparseLUImpl<Scalar,StorageIndex>::memInit(Index m, Index n, Index annz, Index lwork, Index fillratio, Index panel_size,  GlobalLU_t& glu)
 {
   Index& num_expansions = glu.num_expansions; //No memory expansions so far
   num_expansions = 0;
-  glu.nzumax = glu.nzlumax = (std::min)(fillratio * annz / n, m) * n; // estimated number of nonzeros in U 
-  glu.nzlmax = (std::max)(Index(4), fillratio) * annz / 4; // estimated  nnz in L factor
+  glu.nzumax = glu.nzlumax = (std::min)(fillratio * (annz+1) / n, m) * n; // estimated number of nonzeros in U 
+  glu.nzlmax = (std::max)(Index(4), fillratio) * (annz+1) / 4; // estimated  nnz in L factor
   // Return the estimated size to the user if necessary
   Index tempSpace;
   tempSpace = (2*panel_size + 4 + LUNoMarker) * m * sizeof(Index) + (panel_size + 1) * m * sizeof(Scalar);
   if (lwork == emptyIdxLU) 
   {
@@ -203,13 +202,13 @@
  * \param nbElts current number of elements in the vector.
  * \param memtype Type of the element to expand
  * \param num_expansions Number of expansions 
  * \return 0 on success, > 0 size of the memory allocated so far
  */
-template <typename Scalar, typename Index>
+template <typename Scalar, typename StorageIndex>
 template <typename VectorType>
-Index SparseLUImpl<Scalar,Index>::memXpand(VectorType& vec, Index& maxlen, Index nbElts, MemType memtype, Index& num_expansions)
+Index SparseLUImpl<Scalar,StorageIndex>::memXpand(VectorType& vec, Index& maxlen, Index nbElts, MemType memtype, Index& num_expansions)
 {
   Index failed_size; 
   if (memtype == USUB)
      failed_size = this->expand<VectorType>(vec, maxlen, nbElts, 1, num_expansions);
   else

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Structs.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Structs.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Structs.h
@@ -73,11 +73,11 @@
   
 typedef enum {LUSUP, UCOL, LSUB, USUB, LLVL, ULVL} MemType; 
 
 template <typename IndexVector, typename ScalarVector>
 struct LU_GlobalLU_t {
-  typedef typename IndexVector::Scalar Index; 
+  typedef typename IndexVector::Scalar StorageIndex; 
   IndexVector xsup; //First supernode column ... xsup(s) points to the beginning of the s-th supernode
   IndexVector supno; // Supernode number corresponding to this column (column to supernode mapping)
   ScalarVector  lusup; // nonzero values of L ordered by columns 
   IndexVector lsub; // Compressed row indices of L rectangular supernodes. 
   IndexVector xlusup; // pointers to the beginning of each column in lusup
@@ -91,11 +91,10 @@
   Index   n; // Number of columns in the matrix  
   Index   num_expansions; 
 };
 
 // Values to set for performance
-template <typename Index>
 struct perfvalues {
   Index panel_size; // a panel consists of at most <panel_size> consecutive columns
   Index relax; // To control degree of relaxing supernodes. If the number of nodes (columns) 
                 // in a subtree of the elimination tree is less than relax, this subtree is considered 
                 // as one supernode regardless of the row structures of those columns

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_SupernodalMatrix.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_SupernodalMatrix.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_SupernodalMatrix.h
@@ -27,24 +27,24 @@
 /* TODO
  * InnerIterator as for sparsematrix 
  * SuperInnerIterator to iterate through all supernodes 
  * Function for triangular solve
  */
-template <typename _Scalar, typename _Index>
+template <typename _Scalar, typename _StorageIndex>
 class MappedSuperNodalMatrix
 {
   public:
     typedef _Scalar Scalar; 
-    typedef _Index Index;
-    typedef Matrix<Index,Dynamic,1> IndexVector; 
+    typedef _StorageIndex StorageIndex;
+    typedef Matrix<StorageIndex,Dynamic,1> IndexVector;
     typedef Matrix<Scalar,Dynamic,1> ScalarVector;
   public:
     MappedSuperNodalMatrix()
     {
       
     }
-    MappedSuperNodalMatrix(Index m, Index n,  ScalarVector& nzval, IndexVector& nzval_colptr, IndexVector& rowind, 
+    MappedSuperNodalMatrix(Index m, Index n,  ScalarVector& nzval, IndexVector& nzval_colptr, IndexVector& rowind,
              IndexVector& rowind_colptr, IndexVector& col_to_sup, IndexVector& sup_to_col )
     {
       setInfos(m, n, nzval, nzval_colptr, rowind, rowind_colptr, col_to_sup, sup_to_col);
     }
     
@@ -56,11 +56,11 @@
      * Set appropriate pointers for the lower triangular supernodal matrix
      * These infos are available at the end of the numerical factorization
      * FIXME This class will be modified such that it can be use in the course 
      * of the factorization.
      */
-    void setInfos(Index m, Index n, ScalarVector& nzval, IndexVector& nzval_colptr, IndexVector& rowind, 
+    void setInfos(Index m, Index n, ScalarVector& nzval, IndexVector& nzval_colptr, IndexVector& rowind,
              IndexVector& rowind_colptr, IndexVector& col_to_sup, IndexVector& sup_to_col )
     {
       m_row = m;
       m_col = n; 
       m_nzval = nzval.data(); 
@@ -94,63 +94,63 @@
       return m_nzval; 
     }
     /**
      * Return the pointers to the beginning of each column in \ref valuePtr()
      */
-    Index* colIndexPtr()
+    StorageIndex* colIndexPtr()
     {
       return m_nzval_colptr; 
     }
     
-    const Index* colIndexPtr() const
+    const StorageIndex* colIndexPtr() const
     {
       return m_nzval_colptr; 
     }
     
     /**
      * Return the array of compressed row indices of all supernodes
      */
-    Index* rowIndex()  { return m_rowind; }
+    StorageIndex* rowIndex()  { return m_rowind; }
     
-    const Index* rowIndex() const
+    const StorageIndex* rowIndex() const
     {
       return m_rowind; 
     }
     
     /**
      * Return the location in \em rowvaluePtr() which starts each column
      */
-    Index* rowIndexPtr() { return m_rowind_colptr; }
+    StorageIndex* rowIndexPtr() { return m_rowind_colptr; }
     
-    const Index* rowIndexPtr() const 
+    const StorageIndex* rowIndexPtr() const
     {
       return m_rowind_colptr; 
     }
     
     /** 
      * Return the array of column-to-supernode mapping 
      */
-    Index* colToSup()  { return m_col_to_sup; }
+    StorageIndex* colToSup()  { return m_col_to_sup; }
     
-    const Index* colToSup() const
+    const StorageIndex* colToSup() const
     {
       return m_col_to_sup;       
     }
     /**
      * Return the array of supernode-to-column mapping
      */
-    Index* supToCol() { return m_sup_to_col; }
+    StorageIndex* supToCol() { return m_sup_to_col; }
     
-    const Index* supToCol() const 
+    const StorageIndex* supToCol() const
     {
       return m_sup_to_col;
     }
     
     /**
      * Return the number of supernodes
      */
-    Index nsuper() const 
+    Index nsuper() const
     {
       return m_nsuper; 
     }
     
     class InnerIterator; 
@@ -160,33 +160,33 @@
       
       
     
   protected:
     Index m_row; // Number of rows
-    Index m_col; // Number of columns 
-    Index m_nsuper; // Number of supernodes 
+    Index m_col; // Number of columns
+    Index m_nsuper; // Number of supernodes
     Scalar* m_nzval; //array of nonzero values packed by column
-    Index* m_nzval_colptr; //nzval_colptr[j] Stores the location in nzval[] which starts column j 
-    Index* m_rowind; // Array of compressed row indices of rectangular supernodes
-    Index* m_rowind_colptr; //rowind_colptr[j] stores the location in rowind[] which starts column j
-    Index* m_col_to_sup; // col_to_sup[j] is the supernode number to which column j belongs
-    Index* m_sup_to_col; //sup_to_col[s] points to the starting column of the s-th supernode
+    StorageIndex* m_nzval_colptr; //nzval_colptr[j] Stores the location in nzval[] which starts column j
+    StorageIndex* m_rowind; // Array of compressed row indices of rectangular supernodes
+    StorageIndex* m_rowind_colptr; //rowind_colptr[j] stores the location in rowind[] which starts column j
+    StorageIndex* m_col_to_sup; // col_to_sup[j] is the supernode number to which column j belongs
+    StorageIndex* m_sup_to_col; //sup_to_col[s] points to the starting column of the s-th supernode
     
   private :
 };
 
 /**
   * \brief InnerIterator class to iterate over nonzero values of the current column in the supernodal matrix L
   * 
   */
-template<typename Scalar, typename Index>
-class MappedSuperNodalMatrix<Scalar,Index>::InnerIterator
+template<typename Scalar, typename StorageIndex>
+class MappedSuperNodalMatrix<Scalar,StorageIndex>::InnerIterator
 {
   public:
      InnerIterator(const MappedSuperNodalMatrix& mat, Index outer)
       : m_matrix(mat),
-        m_outer(outer), 
+        m_outer(outer),
         m_supno(mat.colToSup()[outer]),
         m_idval(mat.colIndexPtr()[outer]),
         m_startidval(m_idval),
         m_endidval(mat.colIndexPtr()[outer+1]),
         m_idrow(mat.rowIndexPtr()[mat.supToCol()[mat.colToSup()[outer]]]),
@@ -227,18 +227,21 @@
 
 /**
  * \brief Solve with the supernode triangular matrix
  * 
  */
-template<typename Scalar, typename Index>
-template<typename Dest>
-void MappedSuperNodalMatrix<Scalar,Index>::solveInPlace( MatrixBase<Dest>&X) const
-{
-    Index n = X.rows(); 
-    Index nrhs = X.cols(); 
-    const Scalar * Lval = valuePtr();                 // Nonzero values 
-    Matrix<Scalar,Dynamic,Dynamic> work(n, nrhs);     // working vector
+template<typename Scalar, typename Index_>
+template<typename Dest>
+void MappedSuperNodalMatrix<Scalar,Index_>::solveInPlace( MatrixBase<Dest>&X) const
+{
+    /* Explicit type conversion as the Index type of MatrixBase<Dest> may be wider than Index */
+//    eigen_assert(X.rows() <= NumTraits<Index>::highest());
+//    eigen_assert(X.cols() <= NumTraits<Index>::highest());
+    Index n    = int(X.rows());
+    Index nrhs = Index(X.cols());
+    const Scalar * Lval = valuePtr();                 // Nonzero values 
+    Matrix<Scalar,Dynamic,Dest::ColsAtCompileTime, ColMajor> work(n, nrhs);     // working vector
     work.setZero();
     for (Index k = 0; k <= nsuper(); k ++)
     {
       Index fsupc = supToCol()[k];                    // First column of the current supernode 
       Index istart = rowIndexPtr()[fsupc];            // Pointer index to the subscript of the current column
@@ -265,17 +268,17 @@
         // The supernode has more than one column 
         Index luptr = colIndexPtr()[fsupc]; 
         Index lda = colIndexPtr()[fsupc+1] - luptr;
         
         // Triangular solve 
-        Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(Lval[luptr]), nsupc, nsupc, OuterStride<>(lda) ); 
-        Map< Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) ); 
+        Map<const Matrix<Scalar,Dynamic,Dynamic, ColMajor>, 0, OuterStride<> > A( &(Lval[luptr]), nsupc, nsupc, OuterStride<>(lda) );
+        Map< Matrix<Scalar,Dynamic,Dest::ColsAtCompileTime, ColMajor>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
         U = A.template triangularView<UnitLower>().solve(U); 
         
         // Matrix-vector product 
-        new (&A) Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > ( &(Lval[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) ); 
-        work.block(0, 0, nrow, nrhs) = A * U; 
+        new (&A) Map<const Matrix<Scalar,Dynamic,Dynamic, ColMajor>, 0, OuterStride<> > ( &(Lval[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) );
+        work.topRows(nrow).noalias() = A * U;
         
         //Begin Scatter 
         for (Index j = 0; j < nrhs; j++)
         {
           Index iptr = istart + nsupc; 

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Utils.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Utils.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_Utils.h
@@ -15,12 +15,12 @@
 namespace internal {
 
 /**
  * \brief Count Nonzero elements in the factors
  */
-template <typename Scalar, typename Index>
-void SparseLUImpl<Scalar,Index>::countnz(const Index n, Index& nnzL, Index& nnzU, GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+void SparseLUImpl<Scalar,StorageIndex>::countnz(const Index n, Index& nnzL, Index& nnzU, GlobalLU_t& glu)
 {
  nnzL = 0; 
  nnzU = (glu.xusub)(n); 
  Index nsuper = (glu.supno)(n); 
  Index jlen; 
@@ -46,16 +46,16 @@
  * 
  * It removes the subscripts sets for structural pruning, 
  * and applies permutation to the remaining subscripts
  * 
  */
-template <typename Scalar, typename Index>
-void SparseLUImpl<Scalar,Index>::fixupL(const Index n, const IndexVector& perm_r, GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+void SparseLUImpl<Scalar,StorageIndex>::fixupL(const Index n, const IndexVector& perm_r, GlobalLU_t& glu)
 {
   Index fsupc, i, j, k, jstart; 
   
-  Index nextl = 0; 
+  StorageIndex nextl = 0; 
   Index nsuper = (glu.supno)(n); 
   
   // For each supernode 
   for (i = 0; i <= nsuper; i++)
   {

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_column_bmod.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_column_bmod.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_column_bmod.h
@@ -47,12 +47,13 @@
  * \param glu Global LU data. 
  * \return 0 - successful return 
  *         > 0 - number of bytes allocated when run out of space
  * 
  */
-template <typename Scalar, typename Index>
-Index SparseLUImpl<Scalar,Index>::column_bmod(const Index jcol, const Index nseg, BlockScalarVector dense, ScalarVector& tempv, BlockIndexVector segrep, BlockIndexVector repfnz, Index fpanelc, GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+Index SparseLUImpl<Scalar,StorageIndex>::column_bmod(const Index jcol, const Index nseg, BlockScalarVector dense, ScalarVector& tempv,
+                                                     BlockIndexVector segrep, BlockIndexVector repfnz, Index fpanelc, GlobalLU_t& glu)
 {
   Index  jsupno, k, ksub, krep, ksupno; 
   Index lptr, nrow, isub, irow, nextlu, new_next, ufirst; 
   Index fsupc, nsupc, nsupr, luptr, kfnz, no_zeros; 
   /* krep = representative of current k-th supernode
@@ -135,11 +136,11 @@
   if(offset)
   {
     glu.lusup.segment(nextlu,offset).setZero();
     nextlu += offset;
   }
-  glu.xlusup(jcol + 1) = nextlu;  // close L\U(*,jcol); 
+  glu.xlusup(jcol + 1) = StorageIndex(nextlu);  // close L\U(*,jcol); 
   
   /* For more updates within the panel (also within the current supernode),
    * should start from the first column of the panel, or the first column
    * of the supernode, whichever is bigger. There are two cases:
    *  1) fsupc < fpanelc, then fst_col <-- fpanelc
@@ -160,15 +161,15 @@
     nrow = nsupr - d_fsupc - nsupc; 
     
     // points to the beginning of jcol in snode L\U(jsupno) 
     ufirst = glu.xlusup(jcol) + d_fsupc; 
     Index lda = glu.xlusup(jcol+1) - glu.xlusup(jcol);
-    Map<Matrix<Scalar,Dynamic,Dynamic>, 0,  OuterStride<> > A( &(glu.lusup.data()[luptr]), nsupc, nsupc, OuterStride<>(lda) ); 
+    MappedMatrixBlock A( &(glu.lusup.data()[luptr]), nsupc, nsupc, OuterStride<>(lda) );
     VectorBlock<ScalarVector> u(glu.lusup, ufirst, nsupc); 
     u = A.template triangularView<UnitLower>().solve(u); 
     
-    new (&A) Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > ( &(glu.lusup.data()[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) ); 
+    new (&A) MappedMatrixBlock ( &(glu.lusup.data()[luptr+nsupc]), nrow, nsupc, OuterStride<>(lda) );
     VectorBlock<ScalarVector> l(glu.lusup, ufirst+nsupc, nrow); 
     l.noalias() -= A * u;
     
   } // End if fst_col
   return 0; 

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_column_dfs.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_column_dfs.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_column_dfs.h
@@ -28,21 +28,21 @@
  * the code was modified is included with the above copyright notice.
  */
 #ifndef SPARSELU_COLUMN_DFS_H
 #define SPARSELU_COLUMN_DFS_H
 
-template <typename Scalar, typename Index> class SparseLUImpl;
+template <typename Scalar, typename StorageIndex> class SparseLUImpl;
 namespace Eigen {
 
 namespace internal {
 
 template<typename IndexVector, typename ScalarVector>
 struct column_dfs_traits : no_assignment_operator
 {
   typedef typename ScalarVector::Scalar Scalar;
-  typedef typename IndexVector::Scalar Index;
-  column_dfs_traits(Index jcol, Index& jsuper, typename SparseLUImpl<Scalar, Index>::GlobalLU_t& glu, SparseLUImpl<Scalar, Index>& luImpl)
+  typedef typename IndexVector::Scalar StorageIndex;
+  column_dfs_traits(Index jcol, Index& jsuper, typename SparseLUImpl<Scalar, StorageIndex>::GlobalLU_t& glu, SparseLUImpl<Scalar, StorageIndex>& luImpl)
    : m_jcol(jcol), m_jsuper_ref(jsuper), m_glu(glu), m_luImpl(luImpl)
  {}
   bool update_segrep(Index /*krep*/, Index /*jj*/)
   {
     return true;
@@ -55,12 +55,12 @@
   }
   enum { ExpandMem = true };
   
   Index m_jcol;
   Index& m_jsuper_ref;
-  typename SparseLUImpl<Scalar, Index>::GlobalLU_t& m_glu;
-  SparseLUImpl<Scalar, Index>& m_luImpl;
+  typename SparseLUImpl<Scalar, StorageIndex>::GlobalLU_t& m_glu;
+  SparseLUImpl<Scalar, StorageIndex>& m_luImpl;
 };
 
 
 /**
  * \brief Performs a symbolic factorization on column jcol and decide the supernode boundary
@@ -87,12 +87,14 @@
  * \param glu global LU data 
  * \return 0 success
  *         > 0 number of bytes allocated when run out of space
  * 
  */
-template <typename Scalar, typename Index>
-Index SparseLUImpl<Scalar,Index>::column_dfs(const Index m, const Index jcol, IndexVector& perm_r, Index maxsuper, Index& nseg,  BlockIndexVector lsub_col, IndexVector& segrep, BlockIndexVector repfnz, IndexVector& xprune, IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+Index SparseLUImpl<Scalar,StorageIndex>::column_dfs(const Index m, const Index jcol, IndexVector& perm_r, Index maxsuper, Index& nseg,
+                                                    BlockIndexVector lsub_col, IndexVector& segrep, BlockIndexVector repfnz, IndexVector& xprune,
+                                                    IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu)
 {
   
   Index jsuper = glu.supno(jcol); 
   Index nextl = glu.xlsub(jcol); 
   VectorBlock<IndexVector> marker2(marker, 2*m, m); 
@@ -108,17 +110,17 @@
     Index kmark = marker2(krow); 
     
     // krow was visited before, go to the next nonz; 
     if (kmark == jcol) continue;
     
-    dfs_kernel(jcol, perm_r, nseg, glu.lsub, segrep, repfnz, xprune, marker2, parent,
+    dfs_kernel(StorageIndex(jcol), perm_r, nseg, glu.lsub, segrep, repfnz, xprune, marker2, parent,
                    xplore, glu, nextl, krow, traits);
   } // for each nonzero ... 
   
-  Index fsupc, jptr, jm1ptr, ito, ifrom, istop;
-  Index nsuper = glu.supno(jcol);
-  Index jcolp1 = jcol + 1;
+  Index fsupc;
+  StorageIndex nsuper = glu.supno(jcol);
+  StorageIndex jcolp1 = StorageIndex(jcol) + 1;
   Index jcolm1 = jcol - 1;
   
   // check to see if j belongs in the same supernode as j-1
   if ( jcol == 0 )
   { // Do nothing for column 0 
@@ -125,12 +127,12 @@
     nsuper = glu.supno(0) = 0 ;
   }
   else 
   {
     fsupc = glu.xsup(nsuper); 
-    jptr = glu.xlsub(jcol); // Not yet compressed
-    jm1ptr = glu.xlsub(jcolm1); 
+    StorageIndex jptr = glu.xlsub(jcol); // Not yet compressed
+    StorageIndex jm1ptr = glu.xlsub(jcolm1); 
     
     // Use supernodes of type T2 : see SuperLU paper
     if ( (nextl-jptr != jptr-jm1ptr-1) ) jsuper = emptyIdxLU;
     
     // Make sure the number of columns in a supernode doesn't
@@ -144,17 +146,17 @@
      */
     if (jsuper == emptyIdxLU)
     { // starts a new supernode 
       if ( (fsupc < jcolm1-1) ) 
       { // >= 3 columns in nsuper
-        ito = glu.xlsub(fsupc+1);
+        StorageIndex ito = glu.xlsub(fsupc+1);
         glu.xlsub(jcolm1) = ito; 
-        istop = ito + jptr - jm1ptr; 
+        StorageIndex istop = ito + jptr - jm1ptr; 
         xprune(jcolm1) = istop; // intialize xprune(jcol-1)
         glu.xlsub(jcol) = istop; 
         
-        for (ifrom = jm1ptr; ifrom < nextl; ++ifrom, ++ito)
+        for (StorageIndex ifrom = jm1ptr; ifrom < nextl; ++ifrom, ++ito)
           glu.lsub(ito) = glu.lsub(ifrom); 
         nextl = ito;  // = istop + length(jcol)
       }
       nsuper++; 
       glu.supno(jcol) = nsuper; 
@@ -162,16 +164,16 @@
   } // end else:  jcol > 0
   
   // Tidy up the pointers before exit
   glu.xsup(nsuper+1) = jcolp1; 
   glu.supno(jcolp1) = nsuper; 
-  xprune(jcol) = nextl;  // Intialize upper bound for pruning
-  glu.xlsub(jcolp1) = nextl; 
+  xprune(jcol) = StorageIndex(nextl);  // Intialize upper bound for pruning
+  glu.xlsub(jcolp1) = StorageIndex(nextl); 
   
   return 0; 
 }
 
 } // end namespace internal
 
 } // end namespace Eigen
 
 #endif

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h
@@ -44,20 +44,21 @@
  * \param glu Global LU data. 
  * \return 0 - successful return 
  *         > 0 - number of bytes allocated when run out of space
  * 
  */
-template <typename Scalar, typename Index>
-Index SparseLUImpl<Scalar,Index>::copy_to_ucol(const Index jcol, const Index nseg, IndexVector& segrep, BlockIndexVector repfnz ,IndexVector& perm_r, BlockScalarVector dense, GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+Index SparseLUImpl<Scalar,StorageIndex>::copy_to_ucol(const Index jcol, const Index nseg, IndexVector& segrep,
+                                                      BlockIndexVector repfnz ,IndexVector& perm_r, BlockScalarVector dense, GlobalLU_t& glu)
 {  
   Index ksub, krep, ksupno; 
     
   Index jsupno = glu.supno(jcol);
   
   // For each nonzero supernode segment of U[*,j] in topological order 
   Index k = nseg - 1, i; 
-  Index nextu = glu.xusub(jcol); 
+  StorageIndex nextu = glu.xusub(jcol); 
   Index kfnz, isub, segsize; 
   Index new_next,irow; 
   Index fsupc, mem; 
   for (ksub = 0; ksub < nseg; ksub++)
   {

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_gemm_kernel.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_gemm_kernel.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_gemm_kernel.h
@@ -19,11 +19,11 @@
   * A general matrix-matrix product kernel optimized for the SparseLU factorization.
   *  - A, B, and C must be column major
   *  - lda and ldc must be multiples of the respective packet size
   *  - C must have the same alignment as A
   */
-template<typename Scalar,typename Index>
+template<typename Scalar>
 EIGEN_DONT_INLINE
 void sparselu_gemm(Index m, Index n, Index d, const Scalar* A, Index lda, const Scalar* B, Index ldb, Scalar* C, Index ldc)
 {
   using namespace Eigen::internal;
   
@@ -37,13 +37,13 @@
     BM = 4096/sizeof(Scalar),           // number of rows of A-C per chunk
     SM = PM*PacketSize                  // step along M
   };
   Index d_end = (d/RK)*RK;    // number of columns of A (rows of B) suitable for full register blocking
   Index n_end = (n/RN)*RN;    // number of columns of B-C suitable for processing RN columns at once
-  Index i0 = internal::first_aligned(A,m);
+  Index i0 = internal::first_default_aligned(A,m);
   
-  eigen_internal_assert(((lda%PacketSize)==0) && ((ldc%PacketSize)==0) && (i0==internal::first_aligned(C,m)));
+  eigen_internal_assert(((lda%PacketSize)==0) && ((ldc%PacketSize)==0) && (i0==internal::first_default_aligned(C,m)));
   
   // handle the non aligned rows of A and C without any optimization:
   for(Index i=0; i<i0; ++i)
   {
     for(Index j=0; j<n; ++j)
@@ -70,18 +70,18 @@
       for(Index k=0; k<d_end; k+=RK)
       {
         
         // load and expand a RN x RK block of B
         Packet b00, b10, b20, b30, b01, b11, b21, b31;
-                  b00 = pset1<Packet>(Bc0[0]);
-                  b10 = pset1<Packet>(Bc0[1]);
-        if(RK==4) b20 = pset1<Packet>(Bc0[2]);
-        if(RK==4) b30 = pset1<Packet>(Bc0[3]);
-                  b01 = pset1<Packet>(Bc1[0]);
-                  b11 = pset1<Packet>(Bc1[1]);
-        if(RK==4) b21 = pset1<Packet>(Bc1[2]);
-        if(RK==4) b31 = pset1<Packet>(Bc1[3]);
+                  { b00 = pset1<Packet>(Bc0[0]); }
+                  { b10 = pset1<Packet>(Bc0[1]); }
+        if(RK==4) { b20 = pset1<Packet>(Bc0[2]); }
+        if(RK==4) { b30 = pset1<Packet>(Bc0[3]); }
+                  { b01 = pset1<Packet>(Bc1[0]); }
+                  { b11 = pset1<Packet>(Bc1[1]); }
+        if(RK==4) { b21 = pset1<Packet>(Bc1[2]); }
+        if(RK==4) { b31 = pset1<Packet>(Bc1[3]); }
         
         Packet a0, a1, a2, a3, c0, c1, t0, t1;
         
         const Scalar* A0 = A+ib+(k+0)*lda;
         const Scalar* A1 = A+ib+(k+1)*lda;
@@ -104,43 +104,44 @@
           a2 = a3 = a0;
         }
         
 #define KMADD(c, a, b, tmp) {tmp = b; tmp = pmul(a,tmp); c = padd(c,tmp);}
 #define WORK(I)  \
-                    c0 = pload<Packet>(C0+i+(I)*PacketSize);   \
-                    c1 = pload<Packet>(C1+i+(I)*PacketSize);   \
-                    KMADD(c0, a0, b00, t0)      \
-                    KMADD(c1, a0, b01, t1)      \
-                    a0 = pload<Packet>(A0+i+(I+1)*PacketSize); \
-                    KMADD(c0, a1, b10, t0)      \
-                    KMADD(c1, a1, b11, t1)       \
-                    a1 = pload<Packet>(A1+i+(I+1)*PacketSize); \
-          if(RK==4) KMADD(c0, a2, b20, t0)       \
-          if(RK==4) KMADD(c1, a2, b21, t1)       \
-          if(RK==4) a2 = pload<Packet>(A2+i+(I+1)*PacketSize); \
-          if(RK==4) KMADD(c0, a3, b30, t0)       \
-          if(RK==4) KMADD(c1, a3, b31, t1)       \
-          if(RK==4) a3 = pload<Packet>(A3+i+(I+1)*PacketSize); \
-                    pstore(C0+i+(I)*PacketSize, c0);           \
-                    pstore(C1+i+(I)*PacketSize, c1)
+                     c0 = pload<Packet>(C0+i+(I)*PacketSize);    \
+                     c1 = pload<Packet>(C1+i+(I)*PacketSize);    \
+                     KMADD(c0, a0, b00, t0)                      \
+                     KMADD(c1, a0, b01, t1)                      \
+                     a0 = pload<Packet>(A0+i+(I+1)*PacketSize);  \
+                     KMADD(c0, a1, b10, t0)                      \
+                     KMADD(c1, a1, b11, t1)                      \
+                     a1 = pload<Packet>(A1+i+(I+1)*PacketSize);  \
+          if(RK==4){ KMADD(c0, a2, b20, t0)                     }\
+          if(RK==4){ KMADD(c1, a2, b21, t1)                     }\
+          if(RK==4){ a2 = pload<Packet>(A2+i+(I+1)*PacketSize); }\
+          if(RK==4){ KMADD(c0, a3, b30, t0)                     }\
+          if(RK==4){ KMADD(c1, a3, b31, t1)                     }\
+          if(RK==4){ a3 = pload<Packet>(A3+i+(I+1)*PacketSize); }\
+                     pstore(C0+i+(I)*PacketSize, c0);            \
+                     pstore(C1+i+(I)*PacketSize, c1)
         
         // process rows of A' - C' with aggressive vectorization and peeling 
         for(Index i=0; i<actual_b_end1; i+=PacketSize*8)
         {
           EIGEN_ASM_COMMENT("SPARSELU_GEMML_KERNEL1");
                     prefetch((A0+i+(5)*PacketSize));
                     prefetch((A1+i+(5)*PacketSize));
           if(RK==4) prefetch((A2+i+(5)*PacketSize));
           if(RK==4) prefetch((A3+i+(5)*PacketSize));
-                    WORK(0);
-                    WORK(1);
-                    WORK(2);
-                    WORK(3);
-                    WORK(4);
-                    WORK(5);
-                    WORK(6);
-                    WORK(7);
+
+          WORK(0);
+          WORK(1);
+          WORK(2);
+          WORK(3);
+          WORK(4);
+          WORK(5);
+          WORK(6);
+          WORK(7);
         }
         // process the remaining rows with vectorization only
         for(Index i=actual_b_end1; i<actual_b_end2; i+=PacketSize)
         {
           WORK(0);
@@ -163,11 +164,11 @@
         
         Bc0 += RK;
         Bc1 += RK;
       } // peeled loop on k
     } // peeled loop on the columns j
-    // process the last column (we now perform a matrux-vector product)
+    // process the last column (we now perform a matrix-vector product)
     if((n-n_end)>0)
     {
       const Scalar* Bc0 = B+(n-1)*ldb;
       
       for(Index k=0; k<d_end; k+=RK)
@@ -201,20 +202,20 @@
           // workaround "may be used uninitialized in this function" warning
           a2 = a3 = a0;
         }
         
 #define WORK(I) \
-                  c0 = pload<Packet>(C0+i+(I)*PacketSize);   \
-                  KMADD(c0, a0, b00, t0)       \
-                  a0 = pload<Packet>(A0+i+(I+1)*PacketSize); \
-                  KMADD(c0, a1, b10, t0)       \
-                  a1 = pload<Packet>(A1+i+(I+1)*PacketSize); \
-        if(RK==4) KMADD(c0, a2, b20, t0)       \
-        if(RK==4) a2 = pload<Packet>(A2+i+(I+1)*PacketSize); \
-        if(RK==4) KMADD(c0, a3, b30, t0)       \
-        if(RK==4) a3 = pload<Packet>(A3+i+(I+1)*PacketSize); \
-                  pstore(C0+i+(I)*PacketSize, c0);
+                   c0 = pload<Packet>(C0+i+(I)*PacketSize);     \
+                   KMADD(c0, a0, b00, t0)                       \
+                   a0 = pload<Packet>(A0+i+(I+1)*PacketSize);   \
+                   KMADD(c0, a1, b10, t0)                       \
+                   a1 = pload<Packet>(A1+i+(I+1)*PacketSize);   \
+        if(RK==4){ KMADD(c0, a2, b20, t0)                      }\
+        if(RK==4){ a2 = pload<Packet>(A2+i+(I+1)*PacketSize);  }\
+        if(RK==4){ KMADD(c0, a3, b30, t0)                      }\
+        if(RK==4){ a3 = pload<Packet>(A3+i+(I+1)*PacketSize);  }\
+                   pstore(C0+i+(I)*PacketSize, c0);
         
         // agressive vectorization and peeling
         for(Index i=0; i<actual_b_end1; i+=PacketSize*8)
         {
           EIGEN_ASM_COMMENT("SPARSELU_GEMML_KERNEL2");

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h
@@ -40,25 +40,24 @@
  * \param et elimination tree 
  * \param relax_columns Maximum number of columns allowed in a relaxed snode 
  * \param descendants Number of descendants of each node in the etree
  * \param relax_end last column in a supernode
  */
-template <typename Scalar, typename Index>
-void SparseLUImpl<Scalar,Index>::heap_relax_snode (const Index n, IndexVector& et, const Index relax_columns, IndexVector& descendants, IndexVector& relax_end)
+template <typename Scalar, typename StorageIndex>
+void SparseLUImpl<Scalar,StorageIndex>::heap_relax_snode (const Index n, IndexVector& et, const Index relax_columns, IndexVector& descendants, IndexVector& relax_end)
 {
   
   // The etree may not be postordered, but its heap ordered  
   IndexVector post;
-  internal::treePostorder(n, et, post); // Post order etree
+  internal::treePostorder(StorageIndex(n), et, post); // Post order etree
   IndexVector inv_post(n+1); 
-  Index i;
-  for (i = 0; i < n+1; ++i) inv_post(post(i)) = i; // inv_post = post.inverse()???
+  for (StorageIndex i = 0; i < n+1; ++i) inv_post(post(i)) = i; // inv_post = post.inverse()???
   
   // Renumber etree in postorder 
   IndexVector iwork(n);
   IndexVector et_save(n+1);
-  for (i = 0; i < n; ++i)
+  for (Index i = 0; i < n; ++i)
   {
     iwork(post(i)) = post(et(i));
   }
   et_save = et; // Save the original etree
   et = iwork; 
@@ -73,14 +72,14 @@
     if (parent != n) // not the dummy root
       descendants(parent) += descendants(j) + 1;
   }
   // Identify the relaxed supernodes by postorder traversal of the etree
   Index snode_start; // beginning of a snode 
-  Index k;
+  StorageIndex k;
   Index nsuper_et_post = 0; // Number of relaxed snodes in postordered etree 
   Index nsuper_et = 0; // Number of relaxed snodes in the original etree 
-  Index l; 
+  StorageIndex l; 
   for (j = 0; j < n; )
   {
     parent = et(j);
     snode_start = j; 
     while ( parent != n && descendants(parent) < relax_columns ) 
@@ -88,12 +87,12 @@
       j = parent; 
       parent = et(j);
     }
     // Found a supernode in postordered etree, j is the last column 
     ++nsuper_et_post;
-    k = n;
-    for (i = snode_start; i <= j; ++i)
+    k = StorageIndex(n);
+    for (Index i = snode_start; i <= j; ++i)
       k = (std::min)(k, inv_post(i));
     l = inv_post(j);
     if ( (l - k) == (j - snode_start) )  // Same number of columns in the snode
     {
       // This is also a supernode in the original etree
@@ -100,11 +99,11 @@
       relax_end(k) = l; // Record last column 
       ++nsuper_et; 
     }
     else 
     {
-      for (i = snode_start; i <= j; ++i) 
+      for (Index i = snode_start; i <= j; ++i) 
       {
         l = inv_post(i);
         if (descendants(i) == 0) 
         {
           relax_end(l) = l;

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_kernel_bmod.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_kernel_bmod.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_kernel_bmod.h
@@ -12,42 +12,41 @@
 #define SPARSELU_KERNEL_BMOD_H
 
 namespace Eigen {
 namespace internal {
   
-/**
- * \brief Performs numeric block updates from a given supernode to a single column
- * 
- * \param segsize Size of the segment (and blocks ) to use for updates
- * \param[in,out] dense Packed values of the original matrix
- * \param tempv temporary vector to use for updates
- * \param lusup array containing the supernodes
- * \param lda Leading dimension in the supernode
- * \param nrow Number of rows in the rectangular part of the supernode
- * \param lsub compressed row subscripts of supernodes
- * \param lptr pointer to the first column of the current supernode in lsub
- * \param no_zeros Number of nonzeros elements before the diagonal part of the supernode
- * \return 0 on success
- */
 template <int SegSizeAtCompileTime> struct LU_kernel_bmod
 {
-  template <typename BlockScalarVector, typename ScalarVector, typename IndexVector, typename Index>
-  static EIGEN_DONT_INLINE void run(const int segsize, BlockScalarVector& dense, ScalarVector& tempv, ScalarVector& lusup, Index& luptr, const Index lda,
+  /** \internal
+    * \brief Performs numeric block updates from a given supernode to a single column
+    *
+    * \param segsize Size of the segment (and blocks ) to use for updates
+    * \param[in,out] dense Packed values of the original matrix
+    * \param tempv temporary vector to use for updates
+    * \param lusup array containing the supernodes
+    * \param lda Leading dimension in the supernode
+    * \param nrow Number of rows in the rectangular part of the supernode
+    * \param lsub compressed row subscripts of supernodes
+    * \param lptr pointer to the first column of the current supernode in lsub
+    * \param no_zeros Number of nonzeros elements before the diagonal part of the supernode
+    */
+  template <typename BlockScalarVector, typename ScalarVector, typename IndexVector>
+  static EIGEN_DONT_INLINE void run(const Index segsize, BlockScalarVector& dense, ScalarVector& tempv, ScalarVector& lusup, Index& luptr, const Index lda,
                                     const Index nrow, IndexVector& lsub, const Index lptr, const Index no_zeros);
 };
 
 template <int SegSizeAtCompileTime>
-template <typename BlockScalarVector, typename ScalarVector, typename IndexVector, typename Index>
-EIGEN_DONT_INLINE void LU_kernel_bmod<SegSizeAtCompileTime>::run(const int segsize, BlockScalarVector& dense, ScalarVector& tempv, ScalarVector& lusup, Index& luptr, const Index lda,
+template <typename BlockScalarVector, typename ScalarVector, typename IndexVector>
+EIGEN_DONT_INLINE void LU_kernel_bmod<SegSizeAtCompileTime>::run(const Index segsize, BlockScalarVector& dense, ScalarVector& tempv, ScalarVector& lusup, Index& luptr, const Index lda,
                                                                   const Index nrow, IndexVector& lsub, const Index lptr, const Index no_zeros)
 {
   typedef typename ScalarVector::Scalar Scalar;
   // First, copy U[*,j] segment from dense(*) to tempv(*)
   // The result of triangular solve is in tempv[*]; 
     // The result of matric-vector update is in dense[*]
   Index isub = lptr + no_zeros; 
-  int i;
+  Index i;
   Index irow;
   for (i = 0; i < ((SegSizeAtCompileTime==Dynamic)?segsize:SegSizeAtCompileTime); i++)
   {
     irow = lsub(isub); 
     tempv(i) = dense(irow); 
@@ -54,22 +53,22 @@
     ++isub; 
   }
   // Dense triangular solve -- start effective triangle
   luptr += lda * no_zeros + no_zeros; 
   // Form Eigen matrix and vector 
-  Map<Matrix<Scalar,SegSizeAtCompileTime,SegSizeAtCompileTime>, 0, OuterStride<> > A( &(lusup.data()[luptr]), segsize, segsize, OuterStride<>(lda) );
+  Map<Matrix<Scalar,SegSizeAtCompileTime,SegSizeAtCompileTime, ColMajor>, 0, OuterStride<> > A( &(lusup.data()[luptr]), segsize, segsize, OuterStride<>(lda) );
   Map<Matrix<Scalar,SegSizeAtCompileTime,1> > u(tempv.data(), segsize);
   
   u = A.template triangularView<UnitLower>().solve(u); 
   
   // Dense matrix-vector product y <-- B*x 
   luptr += segsize;
   const Index PacketSize = internal::packet_traits<Scalar>::size;
   Index ldl = internal::first_multiple(nrow, PacketSize);
-  Map<Matrix<Scalar,Dynamic,SegSizeAtCompileTime>, 0, OuterStride<> > B( &(lusup.data()[luptr]), nrow, segsize, OuterStride<>(lda) );
-  Index aligned_offset = internal::first_aligned(tempv.data()+segsize, PacketSize);
-  Index aligned_with_B_offset = (PacketSize-internal::first_aligned(B.data(), PacketSize))%PacketSize;
+  Map<Matrix<Scalar,Dynamic,SegSizeAtCompileTime, ColMajor>, 0, OuterStride<> > B( &(lusup.data()[luptr]), nrow, segsize, OuterStride<>(lda) );
+  Index aligned_offset = internal::first_default_aligned(tempv.data()+segsize, PacketSize);
+  Index aligned_with_B_offset = (PacketSize-internal::first_default_aligned(B.data(), PacketSize))%PacketSize;
   Map<Matrix<Scalar,Dynamic,1>, 0, OuterStride<> > l(tempv.data()+segsize+aligned_offset+aligned_with_B_offset, nrow, OuterStride<>(ldl) );
   
   l.setZero();
   internal::sparselu_gemm<Scalar>(l.rows(), l.cols(), B.cols(), B.data(), B.outerStride(), u.data(), u.outerStride(), l.data(), l.outerStride());
   
@@ -89,25 +88,26 @@
   } 
 }
 
 template <> struct LU_kernel_bmod<1>
 {
-  template <typename BlockScalarVector, typename ScalarVector, typename IndexVector, typename Index>
-  static EIGEN_DONT_INLINE void run(const int /*segsize*/, BlockScalarVector& dense, ScalarVector& /*tempv*/, ScalarVector& lusup, Index& luptr,
+  template <typename BlockScalarVector, typename ScalarVector, typename IndexVector>
+  static EIGEN_DONT_INLINE void run(const Index /*segsize*/, BlockScalarVector& dense, ScalarVector& /*tempv*/, ScalarVector& lusup, Index& luptr,
                                     const Index lda, const Index nrow, IndexVector& lsub, const Index lptr, const Index no_zeros);
 };
 
 
-template <typename BlockScalarVector, typename ScalarVector, typename IndexVector, typename Index>
-EIGEN_DONT_INLINE void LU_kernel_bmod<1>::run(const int /*segsize*/, BlockScalarVector& dense, ScalarVector& /*tempv*/, ScalarVector& lusup, Index& luptr,
+template <typename BlockScalarVector, typename ScalarVector, typename IndexVector>
+EIGEN_DONT_INLINE void LU_kernel_bmod<1>::run(const Index /*segsize*/, BlockScalarVector& dense, ScalarVector& /*tempv*/, ScalarVector& lusup, Index& luptr,
                                               const Index lda, const Index nrow, IndexVector& lsub, const Index lptr, const Index no_zeros)
 {
   typedef typename ScalarVector::Scalar Scalar;
+  typedef typename IndexVector::Scalar StorageIndex;
   Scalar f = dense(lsub(lptr + no_zeros));
   luptr += lda * no_zeros + no_zeros + 1;
   const Scalar* a(lusup.data() + luptr);
-  const /*typename IndexVector::Scalar*/Index*  irow(lsub.data()+lptr + no_zeros + 1);
+  const StorageIndex*  irow(lsub.data()+lptr + no_zeros + 1);
   Index i = 0;
   for (; i+1 < nrow; i+=2)
   {
     Index i0 = *(irow++);
     Index i1 = *(irow++);

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_panel_bmod.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_panel_bmod.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_panel_bmod.h
@@ -50,12 +50,12 @@
  * \param repfnz First nonzero rows
  * \param glu Global LU data. 
  * 
  * 
  */
-template <typename Scalar, typename Index>
-void SparseLUImpl<Scalar,Index>::panel_bmod(const Index m, const Index w, const Index jcol, 
+template <typename Scalar, typename StorageIndex>
+void SparseLUImpl<Scalar,StorageIndex>::panel_bmod(const Index m, const Index w, const Index jcol, 
                                             const Index nseg, ScalarVector& dense, ScalarVector& tempv,
                                             IndexVector& segrep, IndexVector& repfnz, GlobalLU_t& glu)
 {
   
   Index ksub,jj,nextl_col; 
@@ -100,11 +100,11 @@
     }
     
     if(nsupc >= 2)
     { 
       Index ldu = internal::first_multiple<Index>(u_rows, PacketSize);
-      Map<Matrix<Scalar,Dynamic,Dynamic>, Aligned,  OuterStride<> > U(tempv.data(), u_rows, u_cols, OuterStride<>(ldu));
+      Map<ScalarMatrix, Aligned,  OuterStride<> > U(tempv.data(), u_rows, u_cols, OuterStride<>(ldu));
       
       // gather U
       Index u_col = 0;
       for (jj = jcol; jj < jcol + w; jj++)
       {
@@ -134,21 +134,21 @@
       // solve U = A^-1 U
       luptr = glu.xlusup(fsupc);
       Index lda = glu.xlusup(fsupc+1) - glu.xlusup(fsupc);
       no_zeros = (krep - u_rows + 1) - fsupc;
       luptr += lda * no_zeros + no_zeros;
-      Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A(glu.lusup.data()+luptr, u_rows, u_rows, OuterStride<>(lda) );
+      MappedMatrixBlock A(glu.lusup.data()+luptr, u_rows, u_rows, OuterStride<>(lda) );
       U = A.template triangularView<UnitLower>().solve(U);
       
       // update
       luptr += u_rows;
-      Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > B(glu.lusup.data()+luptr, nrow, u_rows, OuterStride<>(lda) );
+      MappedMatrixBlock B(glu.lusup.data()+luptr, nrow, u_rows, OuterStride<>(lda) );
       eigen_assert(tempv.size()>w*ldu + nrow*w + 1);
       
       Index ldl = internal::first_multiple<Index>(nrow, PacketSize);
-      Index offset = (PacketSize-internal::first_aligned(B.data(), PacketSize)) % PacketSize;
-      Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > L(tempv.data()+w*ldu+offset, nrow, u_cols, OuterStride<>(ldl));
+      Index offset = (PacketSize-internal::first_default_aligned(B.data(), PacketSize)) % PacketSize;
+      MappedMatrixBlock L(tempv.data()+w*ldu+offset, nrow, u_cols, OuterStride<>(ldl));
       
       L.setZero();
       internal::sparselu_gemm<Scalar>(L.rows(), L.cols(), B.cols(), B.data(), B.outerStride(), U.data(), U.outerStride(), L.data(), L.outerStride());
       
       // scatter U and L

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_panel_dfs.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_panel_dfs.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_panel_dfs.h
@@ -35,15 +35,15 @@
 namespace internal {
   
 template<typename IndexVector>
 struct panel_dfs_traits
 {
-  typedef typename IndexVector::Scalar Index;
-  panel_dfs_traits(Index jcol, Index* marker)
+  typedef typename IndexVector::Scalar StorageIndex;
+  panel_dfs_traits(Index jcol, StorageIndex* marker)
     : m_jcol(jcol), m_marker(marker)
   {}
-  bool update_segrep(Index krep, Index jj)
+  bool update_segrep(Index krep, StorageIndex jj)
   {
     if(m_marker[krep]<m_jcol)
     {
       m_marker[krep] = jj; 
       return true;
@@ -51,43 +51,43 @@
     return false;
   }
   void mem_expand(IndexVector& /*glu.lsub*/, Index /*nextl*/, Index /*chmark*/) {}
   enum { ExpandMem = false };
   Index m_jcol;
-  Index* m_marker;
+  StorageIndex* m_marker;
 };
 
 
-template <typename Scalar, typename Index>
+template <typename Scalar, typename StorageIndex>
 template <typename Traits>
-void SparseLUImpl<Scalar,Index>::dfs_kernel(const Index jj, IndexVector& perm_r,
+void SparseLUImpl<Scalar,StorageIndex>::dfs_kernel(const StorageIndex jj, IndexVector& perm_r,
                    Index& nseg, IndexVector& panel_lsub, IndexVector& segrep,
                    Ref<IndexVector> repfnz_col, IndexVector& xprune, Ref<IndexVector> marker, IndexVector& parent,
                    IndexVector& xplore, GlobalLU_t& glu,
                    Index& nextl_col, Index krow, Traits& traits
                   )
 {
   
-  Index kmark = marker(krow);
+  StorageIndex kmark = marker(krow);
       
   // For each unmarked krow of jj
   marker(krow) = jj; 
-  Index kperm = perm_r(krow); 
+  StorageIndex kperm = perm_r(krow); 
   if (kperm == emptyIdxLU ) {
     // krow is in L : place it in structure of L(*, jj)
-    panel_lsub(nextl_col++) = krow;  // krow is indexed into A
+    panel_lsub(nextl_col++) = StorageIndex(krow);  // krow is indexed into A
     
     traits.mem_expand(panel_lsub, nextl_col, kmark);
   }
   else 
   {
     // krow is in U : if its supernode-representative krep
     // has been explored, update repfnz(*)
     // krep = supernode representative of the current row
-    Index krep = glu.xsup(glu.supno(kperm)+1) - 1; 
+    StorageIndex krep = glu.xsup(glu.supno(kperm)+1) - 1; 
     // First nonzero element in the current column:
-    Index myfnz = repfnz_col(krep); 
+    StorageIndex myfnz = repfnz_col(krep); 
     
     if (myfnz != emptyIdxLU )
     {
       // Representative visited before
       if (myfnz > kperm ) repfnz_col(krep) = kperm; 
@@ -94,30 +94,30 @@
       
     }
     else 
     {
       // Otherwise, perform dfs starting at krep
-      Index oldrep = emptyIdxLU; 
+      StorageIndex oldrep = emptyIdxLU; 
       parent(krep) = oldrep; 
       repfnz_col(krep) = kperm; 
-      Index xdfs =  glu.xlsub(krep); 
+      StorageIndex xdfs =  glu.xlsub(krep); 
       Index maxdfs = xprune(krep); 
       
-      Index kpar;
+      StorageIndex kpar;
       do 
       {
         // For each unmarked kchild of krep
         while (xdfs < maxdfs) 
         {
-          Index kchild = glu.lsub(xdfs); 
+          StorageIndex kchild = glu.lsub(xdfs); 
           xdfs++; 
-          Index chmark = marker(kchild); 
+          StorageIndex chmark = marker(kchild); 
           
           if (chmark != jj ) 
           {
             marker(kchild) = jj; 
-            Index chperm = perm_r(kchild); 
+            StorageIndex chperm = perm_r(kchild); 
             
             if (chperm == emptyIdxLU) 
             {
               // case kchild is in L: place it in L(*, j)
               panel_lsub(nextl_col++) = kchild;
@@ -126,11 +126,11 @@
             else
             {
               // case kchild is in U :
               // chrep = its supernode-rep. If its rep has been explored, 
               // update its repfnz(*)
-              Index chrep = glu.xsup(glu.supno(chperm)+1) - 1; 
+              StorageIndex chrep = glu.xsup(glu.supno(chperm)+1) - 1; 
               myfnz = repfnz_col(chrep); 
               
               if (myfnz != emptyIdxLU) 
               { // Visited before 
                 if (myfnz > chperm) 
@@ -213,12 +213,12 @@
  * \param xplore work vector
  * \param glu The global data structure
  * 
  */
 
-template <typename Scalar, typename Index>
-void SparseLUImpl<Scalar,Index>::panel_dfs(const Index m, const Index w, const Index jcol, MatrixType& A, IndexVector& perm_r, Index& nseg, ScalarVector& dense, IndexVector& panel_lsub, IndexVector& segrep, IndexVector& repfnz, IndexVector& xprune, IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+void SparseLUImpl<Scalar,StorageIndex>::panel_dfs(const Index m, const Index w, const Index jcol, MatrixType& A, IndexVector& perm_r, Index& nseg, ScalarVector& dense, IndexVector& panel_lsub, IndexVector& segrep, IndexVector& repfnz, IndexVector& xprune, IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu)
 {
   Index nextl_col; // Next available position in panel_lsub[*,jj] 
   
   // Initialize pointers 
   VectorBlock<IndexVector> marker1(marker, m, m); 
@@ -225,11 +225,11 @@
   nseg = 0; 
   
   panel_dfs_traits<IndexVector> traits(jcol, marker1.data());
   
   // For each column in the panel 
-  for (Index jj = jcol; jj < jcol + w; jj++) 
+  for (StorageIndex jj = StorageIndex(jcol); jj < jcol + w; jj++) 
   {
     nextl_col = (jj - jcol) * m; 
     
     VectorBlock<IndexVector> repfnz_col(repfnz, nextl_col, m); // First nonzero location in each row
     VectorBlock<ScalarVector> dense_col(dense,nextl_col, m); // Accumulate a column vector here
@@ -239,11 +239,11 @@
     for (typename MatrixType::InnerIterator it(A, jj); it; ++it)
     {
       Index krow = it.row(); 
       dense_col(krow) = it.value();
       
-      Index kmark = marker(krow); 
+      StorageIndex kmark = marker(krow); 
       if (kmark == jj) 
         continue; // krow visited before, go to the next nonzero
       
       dfs_kernel(jj, perm_r, nseg, panel_lsub, segrep, repfnz_col, xprune, marker, parent,
                    xplore, glu, nextl_col, krow, traits);

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_pivotL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_pivotL.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_pivotL.h
@@ -54,43 +54,45 @@
  * \param[out] pivrow  The pivot row
  * \param glu Global LU data
  * \return 0 if success, i > 0 if U(i,i) is exactly zero 
  * 
  */
-template <typename Scalar, typename Index>
-Index SparseLUImpl<Scalar,Index>::pivotL(const Index jcol, const RealScalar& diagpivotthresh, IndexVector& perm_r, IndexVector& iperm_c, Index& pivrow, GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+Index SparseLUImpl<Scalar,StorageIndex>::pivotL(const Index jcol, const RealScalar& diagpivotthresh, IndexVector& perm_r, IndexVector& iperm_c, Index& pivrow, GlobalLU_t& glu)
 {
   
   Index fsupc = (glu.xsup)((glu.supno)(jcol)); // First column in the supernode containing the column jcol
   Index nsupc = jcol - fsupc; // Number of columns in the supernode portion, excluding jcol; nsupc >=0
   Index lptr = glu.xlsub(fsupc); // pointer to the starting location of the row subscripts for this supernode portion
   Index nsupr = glu.xlsub(fsupc+1) - lptr; // Number of rows in the supernode
   Index lda = glu.xlusup(fsupc+1) - glu.xlusup(fsupc); // leading dimension
   Scalar* lu_sup_ptr = &(glu.lusup.data()[glu.xlusup(fsupc)]); // Start of the current supernode
   Scalar* lu_col_ptr = &(glu.lusup.data()[glu.xlusup(jcol)]); // Start of jcol in the supernode
-  Index* lsub_ptr = &(glu.lsub.data()[lptr]); // Start of row indices of the supernode
+  StorageIndex* lsub_ptr = &(glu.lsub.data()[lptr]); // Start of row indices of the supernode
   
   // Determine the largest abs numerical value for partial pivoting 
   Index diagind = iperm_c(jcol); // diagonal index 
-  RealScalar pivmax = 0.0; 
+  RealScalar pivmax(-1.0);
   Index pivptr = nsupc; 
   Index diag = emptyIdxLU; 
   RealScalar rtemp;
   Index isub, icol, itemp, k; 
   for (isub = nsupc; isub < nsupr; ++isub) {
-    rtemp = std::abs(lu_col_ptr[isub]);
+    using std::abs;
+    rtemp = abs(lu_col_ptr[isub]);
     if (rtemp > pivmax) {
       pivmax = rtemp; 
       pivptr = isub;
     } 
     if (lsub_ptr[isub] == diagind) diag = isub;
   }
   
   // Test for singularity
-  if ( pivmax == 0.0 ) {
-    pivrow = lsub_ptr[pivptr];
-    perm_r(pivrow) = jcol;
+  if ( pivmax <= RealScalar(0.0) ) {
+    // if pivmax == -1, the column is structurally empty, otherwise it is only numerically zero
+    pivrow = pivmax < RealScalar(0.0) ? diagind : lsub_ptr[pivptr];
+    perm_r(pivrow) = StorageIndex(jcol);
     return (jcol+1);
   }
   
   RealScalar thresh = diagpivotthresh * pivmax; 
   
@@ -99,18 +101,19 @@
   {
     // Test if the diagonal element can be used as a pivot (given the threshold value)
     if (diag >= 0 ) 
     {
       // Diagonal element exists
-      rtemp = std::abs(lu_col_ptr[diag]);
-      if (rtemp != 0.0 && rtemp >= thresh) pivptr = diag;
+      using std::abs;
+      rtemp = abs(lu_col_ptr[diag]);
+      if (rtemp != RealScalar(0.0) && rtemp >= thresh) pivptr = diag;
     }
     pivrow = lsub_ptr[pivptr];
   }
   
   // Record pivot row
-  perm_r(pivrow) = jcol; 
+  perm_r(pivrow) = StorageIndex(jcol);
   // Interchange row subscripts
   if (pivptr != nsupc )
   {
     std::swap( lsub_ptr[pivptr], lsub_ptr[nsupc] );
     // Interchange numerical values as well, for the two rows in the whole snode

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_pruneL.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_pruneL.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_pruneL.h
@@ -47,12 +47,13 @@
  * \param repfnz
  * \param[out] xprune 
  * \param glu Global LU data
  * 
  */
-template <typename Scalar, typename Index>
-void SparseLUImpl<Scalar,Index>::pruneL(const Index jcol, const IndexVector& perm_r, const Index pivrow, const Index nseg, const IndexVector& segrep, BlockIndexVector repfnz, IndexVector& xprune, GlobalLU_t& glu)
+template <typename Scalar, typename StorageIndex>
+void SparseLUImpl<Scalar,StorageIndex>::pruneL(const Index jcol, const IndexVector& perm_r, const Index pivrow, const Index nseg,
+                                               const IndexVector& segrep, BlockIndexVector repfnz, IndexVector& xprune, GlobalLU_t& glu)
 {
   // For each supernode-rep irep in U(*,j]
   Index jsupno = glu.supno(jcol); 
   Index i,irep,irep1; 
   bool movnum, do_prune = false; 
@@ -121,15 +122,15 @@
             kmin++;
             kmax--;
           }
         } // end while 
         
-        xprune(irep) = kmin;  //Pruning 
+        xprune(irep) = StorageIndex(kmin);  //Pruning 
       } // end if do_prune 
     } // end pruning 
   } // End for each U-segment
 }
 
 } // end namespace internal
 } // end namespace Eigen
 
 #endif // SPARSELU_PRUNEL_H

Index: 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_relax_snode.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_relax_snode.h
+++ 3rd_party/eigen/Eigen/src/SparseLU/SparseLU_relax_snode.h
@@ -41,37 +41,37 @@
  * \param et elimination tree 
  * \param relax_columns Maximum number of columns allowed in a relaxed snode 
  * \param descendants Number of descendants of each node in the etree
  * \param relax_end last column in a supernode
  */
-template <typename Scalar, typename Index>
-void SparseLUImpl<Scalar,Index>::relax_snode (const Index n, IndexVector& et, const Index relax_columns, IndexVector& descendants, IndexVector& relax_end)
+template <typename Scalar, typename StorageIndex>
+void SparseLUImpl<Scalar,StorageIndex>::relax_snode (const Index n, IndexVector& et, const Index relax_columns, IndexVector& descendants, IndexVector& relax_end)
 {
   
   // compute the number of descendants of each node in the etree
-  Index j, parent; 
+  Index parent; 
   relax_end.setConstant(emptyIdxLU);
   descendants.setZero();
-  for (j = 0; j < n; j++) 
+  for (Index j = 0; j < n; j++) 
   {
     parent = et(j);
     if (parent != n) // not the dummy root
       descendants(parent) += descendants(j) + 1;
   }
   // Identify the relaxed supernodes by postorder traversal of the etree
   Index snode_start; // beginning of a snode 
-  for (j = 0; j < n; )
+  for (Index j = 0; j < n; )
   {
     parent = et(j);
     snode_start = j; 
     while ( parent != n && descendants(parent) < relax_columns ) 
     {
       j = parent; 
       parent = et(j);
     }
     // Found a supernode in postordered etree, j is the last column 
-    relax_end(snode_start) = j; // Record last column
+    relax_end(snode_start) = StorageIndex(j); // Record last column
     j++;
     // Search for a new leaf
     while (descendants(j) != 0 && j < n) j++;
   } // End postorder traversal of the etree
   

DELETED 3rd_party/eigen/Eigen/src/SparseQR/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/SparseQR/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseQR/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/SparseQR/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SparseQR_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_SparseQR_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SparseQR/ COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/SparseQR/SparseQR.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SparseQR/SparseQR.h
+++ 3rd_party/eigen/Eigen/src/SparseQR/SparseQR.h
@@ -19,12 +19,16 @@
 template<typename SparseQRType, typename Derived> struct SparseQR_QProduct;
 namespace internal {
   template <typename SparseQRType> struct traits<SparseQRMatrixQReturnType<SparseQRType> >
   {
     typedef typename SparseQRType::MatrixType ReturnType;
-    typedef typename ReturnType::Index Index;
+    typedef typename ReturnType::StorageIndex StorageIndex;
     typedef typename ReturnType::StorageKind StorageKind;
+    enum {
+      RowsAtCompileTime = Dynamic,
+      ColsAtCompileTime = Dynamic
+    };
   };
   template <typename SparseQRType> struct traits<SparseQRMatrixQTransposeReturnType<SparseQRType> >
   {
     typedef typename SparseQRType::MatrixType ReturnType;
   };
@@ -56,37 +60,49 @@
   * 
   * \tparam _MatrixType The type of the sparse matrix A, must be a column-major SparseMatrix<>
   * \tparam _OrderingType The fill-reducing ordering method. See the \link OrderingMethods_Module 
   *  OrderingMethods \endlink module for the list of built-in and external ordering methods.
   * 
+  * \implsparsesolverconcept
+  *
   * \warning The input sparse matrix A must be in compressed mode (see SparseMatrix::makeCompressed()).
   * 
   */
 template<typename _MatrixType, typename _OrderingType>
-class SparseQR
+class SparseQR : public SparseSolverBase<SparseQR<_MatrixType,_OrderingType> >
 {
+  protected:
+    typedef SparseSolverBase<SparseQR<_MatrixType,_OrderingType> > Base;
+    using Base::m_isInitialized;
   public:
+    using Base::_solve_impl;
     typedef _MatrixType MatrixType;
     typedef _OrderingType OrderingType;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
-    typedef SparseMatrix<Scalar,ColMajor,Index> QRMatrixType;
-    typedef Matrix<Index, Dynamic, 1> IndexVector;
+    typedef typename MatrixType::StorageIndex StorageIndex;
+    typedef SparseMatrix<Scalar,ColMajor,StorageIndex> QRMatrixType;
+    typedef Matrix<StorageIndex, Dynamic, 1> IndexVector;
     typedef Matrix<Scalar, Dynamic, 1> ScalarVector;
-    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+    typedef PermutationMatrix<Dynamic, Dynamic, StorageIndex> PermutationType;
+
+    enum {
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
+    
   public:
-    SparseQR () : m_isInitialized(false), m_analysisIsok(false), m_lastError(""), m_useDefaultThreshold(true),m_isQSorted(false),m_isEtreeOk(false)
+    SparseQR () :  m_analysisIsok(false), m_lastError(""), m_useDefaultThreshold(true),m_isQSorted(false),m_isEtreeOk(false)
     { }
     
     /** Construct a QR factorization of the matrix \a mat.
       * 
       * \warning The matrix \a mat must be in compressed mode (see SparseMatrix::makeCompressed()).
       * 
       * \sa compute()
       */
-    SparseQR(const MatrixType& mat) : m_isInitialized(false), m_analysisIsok(false), m_lastError(""), m_useDefaultThreshold(true),m_isQSorted(false),m_isEtreeOk(false)
+    explicit SparseQR(const MatrixType& mat) : m_analysisIsok(false), m_lastError(""), m_useDefaultThreshold(true),m_isQSorted(false),m_isEtreeOk(false)
     {
       compute(mat);
     }
     
     /** Computes the QR factorization of the sparse matrix \a mat.
@@ -110,18 +126,29 @@
     /** \returns the number of columns of the represented matrix. 
       */
     inline Index cols() const { return m_pmat.cols();}
     
     /** \returns a const reference to the \b sparse upper triangular matrix R of the QR factorization.
+      * \warning The entries of the returned matrix are not sorted. This means that using it in algorithms
+      *          expecting sorted entries will fail. This include random coefficient accesses (SpaseMatrix::coeff()),
+      *          and coefficient-wise operations. Matrix products and triangular solves are fine though.
+      *
+      * To sort the entries, you can assign it to a row-major matrix, and if a column-major matrix
+      * is required, you can copy it again:
+      * \code
+      * SparseMatrix<double>          R  = qr.matrixR();  // column-major, not sorted!
+      * SparseMatrix<double,RowMajor> Rr = qr.matrixR();  // row-major, sorted
+      * SparseMatrix<double>          Rc = Rr;            // column-major, sorted
+      * \endcode
       */
     const QRMatrixType& matrixR() const { return m_R; }
     
     /** \returns the number of non linearly dependent columns as determined by the pivoting threshold.
       *
       * \sa setPivotThreshold()
       */
-    Index rank() const 
+    Index rank() const
     {
       eigen_assert(m_isInitialized && "The factorization should be called first, use compute()");
       return m_nonzeropivots; 
     }
     
@@ -160,11 +187,11 @@
       */
     std::string lastErrorMessage() const { return m_lastError; }
     
     /** \internal */
     template<typename Rhs, typename Dest>
-    bool _solve(const MatrixBase<Rhs> &B, MatrixBase<Dest> &dest) const
+    bool _solve_impl(const MatrixBase<Rhs> &B, MatrixBase<Dest> &dest) const
     {
       eigen_assert(m_isInitialized && "The factorization should be called first, use compute()");
       eigen_assert(this->rows() == B.rows() && "SparseQR::solve() : invalid number of rows in the right hand side matrix");
 
       Index rank = this->rank();
@@ -173,22 +200,21 @@
       typename Dest::PlainObject y, b;
       y = this->matrixQ().transpose() * B; 
       b = y;
       
       // Solve with the triangular matrix R
-      y.resize((std::max)(cols(),Index(y.rows())),y.cols());
+      y.resize((std::max<Index>)(cols(),y.rows()),y.cols());
       y.topRows(rank) = this->matrixR().topLeftCorner(rank, rank).template triangularView<Upper>().solve(b.topRows(rank));
       y.bottomRows(y.rows()-rank).setZero();
-
+      
       // Apply the column permutation
       if (m_perm_c.size())  dest = colsPermutation() * y.topRows(cols());
       else                  dest = y.topRows(cols());
       
       m_info = Success;
       return true;
     }
-    
 
     /** Sets the threshold that is used to determine linearly dependent columns during the factorization.
       *
       * In practice, if during the factorization the norm of the column that has to be eliminated is below
       * this threshold, then the entire column is treated as zero, and it is moved at the end.
@@ -202,22 +228,22 @@
     /** \returns the solution X of \f$ A X = B \f$ using the current decomposition of A.
       *
       * \sa compute()
       */
     template<typename Rhs>
-    inline const internal::solve_retval<SparseQR, Rhs> solve(const MatrixBase<Rhs>& B) const 
+    inline const Solve<SparseQR, Rhs> solve(const MatrixBase<Rhs>& B) const 
     {
       eigen_assert(m_isInitialized && "The factorization should be called first, use compute()");
       eigen_assert(this->rows() == B.rows() && "SparseQR::solve() : invalid number of rows in the right hand side matrix");
-      return internal::solve_retval<SparseQR, Rhs>(*this, B.derived());
+      return Solve<SparseQR, Rhs>(*this, B.derived());
     }
     template<typename Rhs>
-    inline const internal::sparse_solve_retval<SparseQR, Rhs> solve(const SparseMatrixBase<Rhs>& B) const
+    inline const Solve<SparseQR, Rhs> solve(const SparseMatrixBase<Rhs>& B) const
     {
           eigen_assert(m_isInitialized && "The factorization should be called first, use compute()");
           eigen_assert(this->rows() == B.rows() && "SparseQR::solve() : invalid number of rows in the right hand side matrix");
-          return internal::sparse_solve_retval<SparseQR, Rhs>(*this, B.derived());
+          return Solve<SparseQR, Rhs>(*this, B.derived());
     }
     
     /** \brief Reports whether previous computation was successful.
       *
       * \returns \c Success if computation was successful,
@@ -230,12 +256,13 @@
     {
       eigen_assert(m_isInitialized && "Decomposition is not initialized.");
       return m_info;
     }
 
-  protected:
-    inline void sort_matrix_Q()
+
+    /** \internal */
+    inline void _sort_matrix_Q()
     {
       if(this->m_isQSorted) return;
       // The matrix Q is sorted during the transposition
       SparseMatrix<Scalar, RowMajor, Index> mQrm(this->m_Q);
       this->m_Q = mQrm;
@@ -242,11 +269,10 @@
       this->m_isQSorted = true;
     }
 
     
   protected:
-    bool m_isInitialized;
     bool m_analysisIsok;
     bool m_factorizationIsok;
     mutable ComputationInfo m_info;
     std::string m_lastError;
     QRMatrixType m_pmat;            // Temporary matrix
@@ -256,18 +282,17 @@
     PermutationType m_perm_c;       // Fill-reducing  Column  permutation
     PermutationType m_pivotperm;    // The permutation for rank revealing
     PermutationType m_outputPerm_c; // The final column permutation
     RealScalar m_threshold;         // Threshold to determine null Householder reflections
     bool m_useDefaultThreshold;     // Use default threshold
-    Index m_nonzeropivots;          // Number of non zero pivots found 
+    Index m_nonzeropivots;          // Number of non zero pivots found
     IndexVector m_etree;            // Column elimination tree
     IndexVector m_firstRowElt;      // First element in each row
     bool m_isQSorted;               // whether Q is sorted or not
     bool m_isEtreeOk;               // whether the elimination tree match the initial input matrix
     
     template <typename, typename > friend struct SparseQR_QProduct;
-    template <typename > friend struct SparseQRMatrixQReturnType;
     
 };
 
 /** \brief Preprocessing step of a QR factorization 
   * 
@@ -292,11 +317,11 @@
   Index diagSize = (std::min)(m,n);
   
   if (!m_perm_c.size())
   {
     m_perm_c.resize(n);
-    m_perm_c.indices().setLinSpaced(n, 0,n-1);
+    m_perm_c.indices().setLinSpaced(n, 0,StorageIndex(n-1));
   }
   
   // Compute the column elimination tree of the permuted matrix
   m_outputPerm_c = m_perm_c.inverse();
   internal::coletree(matCpy, m_etree, m_firstRowElt, m_outputPerm_c.indices().data());
@@ -321,16 +346,15 @@
   */
 template <typename MatrixType, typename OrderingType>
 void SparseQR<MatrixType,OrderingType>::factorize(const MatrixType& mat)
 {
   using std::abs;
-  using std::max;
   
   eigen_assert(m_analysisIsok && "analyzePattern() should be called before this step");
-  Index m = mat.rows();
-  Index n = mat.cols();
-  Index diagSize = (std::min)(m,n);
+  StorageIndex m = StorageIndex(mat.rows());
+  StorageIndex n = StorageIndex(mat.cols());
+  StorageIndex diagSize = (std::min)(m,n);
   IndexVector mark((std::max)(m,n)); mark.setConstant(-1);  // Record the visited nodes
   IndexVector Ridx(n), Qidx(m);                             // Store temporarily the row indexes for the current column of R and Q
   Index nzcolR, nzcolQ;                                     // Number of nonzero for the current column of R and Q
   ScalarVector tval(m);                                     // The dense vector used to compute the current column
   RealScalar pivotThreshold = m_threshold;
@@ -351,11 +375,11 @@
   {
     // If the input is row major, copy the original column indices,
     // otherwise directly use the input matrix
     // 
     IndexVector originalOuterIndicesCpy;
-    const Index *originalOuterIndices = mat.outerIndexPtr();
+    const StorageIndex *originalOuterIndices = mat.outerIndexPtr();
     if(MatrixType::IsRowMajor)
     {
       originalOuterIndicesCpy = IndexVector::Map(m_pmat.outerIndexPtr(),n+1);
       originalOuterIndices = originalOuterIndicesCpy.data();
     }
@@ -373,24 +397,24 @@
    * Sparse QR Factorization, ACM Trans. on Math. Soft. 38(1), 2011, Page 8:3 
    */
   if(m_useDefaultThreshold) 
   {
     RealScalar max2Norm = 0.0;
-    for (int j = 0; j < n; j++) max2Norm = (max)(max2Norm, m_pmat.col(j).norm());
+    for (int j = 0; j < n; j++) max2Norm = numext::maxi(max2Norm, m_pmat.col(j).norm());
     if(max2Norm==RealScalar(0))
       max2Norm = RealScalar(1);
     pivotThreshold = 20 * (m + n) * max2Norm * NumTraits<RealScalar>::epsilon();
   }
   
   // Initialize the numerical permutation
   m_pivotperm.setIdentity(n);
   
-  Index nonzeroCol = 0; // Record the number of valid pivots
+  StorageIndex nonzeroCol = 0; // Record the number of valid pivots
   m_Q.startVec(0);
 
   // Left looking rank-revealing QR factorization: compute a column of R and Q at a time
-  for (Index col = 0; col < n; ++col)
+  for (StorageIndex col = 0; col < n; ++col)
   {
     mark.setConstant(-1);
     m_R.startVec(col);
     mark(nonzeroCol) = col;
     Qidx(0) = nonzeroCol;
@@ -402,16 +426,16 @@
     // all the nodes (with indexes lower than rank) reachable through the column elimination tree (etree) rooted at node k.
     // Note: if the diagonal entry does not exist, then its contribution must be explicitly added,
     // thus the trick with found_diag that permits to do one more iteration on the diagonal element if this one has not been found.
     for (typename QRMatrixType::InnerIterator itp(m_pmat, col); itp || !found_diag; ++itp)
     {
-      Index curIdx = nonzeroCol;
-      if(itp) curIdx = itp.row();
+      StorageIndex curIdx = nonzeroCol;
+      if(itp) curIdx = StorageIndex(itp.row());
       if(curIdx == nonzeroCol) found_diag = true;
       
       // Get the nonzeros indexes of the current column of R
-      Index st = m_firstRowElt(curIdx); // The traversal of the etree starts here 
+      StorageIndex st = m_firstRowElt(curIdx); // The traversal of the etree starts here
       if (st < 0 )
       {
         m_lastError = "Empty row found during numerical factorization";
         m_info = InvalidInput;
         return;
@@ -464,21 +488,21 @@
       // Detect fill-in for the current column of Q
       if(m_etree(Ridx(i)) == nonzeroCol)
       {
         for (typename QRMatrixType::InnerIterator itq(m_Q, curIdx); itq; ++itq)
         {
-          Index iQ = itq.row();
+          StorageIndex iQ = StorageIndex(itq.row());
           if (mark(iQ) != col)
           {
             Qidx(nzcolQ++) = iQ;  // Add this row to the pattern of Q,
             mark(iQ) = col;       // and mark it as visited
           }
         }
       }
     } // End update current column
     
-    Scalar tau = 0;
+    Scalar tau = RealScalar(0);
     RealScalar beta = 0;
     
     if(nonzeroCol < diagSize)
     {
       // Compute the Householder reflection that eliminate the current column
@@ -570,44 +594,15 @@
   m_isInitialized = true; 
   m_factorizationIsok = true;
   m_info = Success;
 }
 
-namespace internal {
-  
-template<typename _MatrixType, typename OrderingType, typename Rhs>
-struct solve_retval<SparseQR<_MatrixType,OrderingType>, Rhs>
-  : solve_retval_base<SparseQR<_MatrixType,OrderingType>, Rhs>
-{
-  typedef SparseQR<_MatrixType,OrderingType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-template<typename _MatrixType, typename OrderingType, typename Rhs>
-struct sparse_solve_retval<SparseQR<_MatrixType, OrderingType>, Rhs>
- : sparse_solve_retval_base<SparseQR<_MatrixType, OrderingType>, Rhs>
-{
-  typedef SparseQR<_MatrixType, OrderingType> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec, Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    this->defaultEvalTo(dst);
-  }
-};
-} // end namespace internal
-
 template <typename SparseQRType, typename Derived>
 struct SparseQR_QProduct : ReturnByValue<SparseQR_QProduct<SparseQRType, Derived> >
 {
   typedef typename SparseQRType::QRMatrixType MatrixType;
   typedef typename SparseQRType::Scalar Scalar;
-  typedef typename SparseQRType::Index Index;
   // Get the references 
   SparseQR_QProduct(const SparseQRType& qr, const Derived& other, bool transpose) : 
   m_qr(qr),m_other(other),m_transpose(transpose) {}
   inline Index rows() const { return m_transpose ? m_qr.rows() : m_qr.cols(); }
   inline Index cols() const { return m_other.cols(); }
@@ -659,14 +654,17 @@
 };
 
 template<typename SparseQRType>
 struct SparseQRMatrixQReturnType : public EigenBase<SparseQRMatrixQReturnType<SparseQRType> >
 {  
-  typedef typename SparseQRType::Index Index;
   typedef typename SparseQRType::Scalar Scalar;
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  SparseQRMatrixQReturnType(const SparseQRType& qr) : m_qr(qr) {}
+  enum {
+    RowsAtCompileTime = Dynamic,
+    ColsAtCompileTime = Dynamic
+  };
+  explicit SparseQRMatrixQReturnType(const SparseQRType& qr) : m_qr(qr) {}
   template<typename Derived>
   SparseQR_QProduct<SparseQRType, Derived> operator*(const MatrixBase<Derived>& other)
   {
     return SparseQR_QProduct<SparseQRType,Derived>(m_qr,other.derived(),false);
   }
@@ -679,36 +677,63 @@
   // To use for operations with the transpose of Q
   SparseQRMatrixQTransposeReturnType<SparseQRType> transpose() const
   {
     return SparseQRMatrixQTransposeReturnType<SparseQRType>(m_qr);
   }
-  template<typename Dest> void evalTo(MatrixBase<Dest>& dest) const
-  {
-    dest.derived() = m_qr.matrixQ() * Dest::Identity(m_qr.rows(), m_qr.rows());
-  }
-  template<typename Dest> void evalTo(SparseMatrixBase<Dest>& dest) const
-  {
-    Dest idMat(m_qr.rows(), m_qr.rows());
-    idMat.setIdentity();
-    // Sort the sparse householder reflectors if needed
-    const_cast<SparseQRType *>(&m_qr)->sort_matrix_Q();
-    dest.derived() = SparseQR_QProduct<SparseQRType, Dest>(m_qr, idMat, false);
-  }
-
   const SparseQRType& m_qr;
 };
 
 template<typename SparseQRType>
 struct SparseQRMatrixQTransposeReturnType
 {
-  SparseQRMatrixQTransposeReturnType(const SparseQRType& qr) : m_qr(qr) {}
+  explicit SparseQRMatrixQTransposeReturnType(const SparseQRType& qr) : m_qr(qr) {}
   template<typename Derived>
   SparseQR_QProduct<SparseQRType,Derived> operator*(const MatrixBase<Derived>& other)
   {
     return SparseQR_QProduct<SparseQRType,Derived>(m_qr,other.derived(), true);
   }
   const SparseQRType& m_qr;
 };
 
+namespace internal {
+  
+template<typename SparseQRType>
+struct evaluator_traits<SparseQRMatrixQReturnType<SparseQRType> >
+{
+  typedef typename SparseQRType::MatrixType MatrixType;
+  typedef typename storage_kind_to_evaluator_kind<typename MatrixType::StorageKind>::Kind Kind;
+  typedef SparseShape Shape;
+};
+
+template< typename DstXprType, typename SparseQRType>
+struct Assignment<DstXprType, SparseQRMatrixQReturnType<SparseQRType>, internal::assign_op<typename DstXprType::Scalar,typename DstXprType::Scalar>, Sparse2Sparse>
+{
+  typedef SparseQRMatrixQReturnType<SparseQRType> SrcXprType;
+  typedef typename DstXprType::Scalar Scalar;
+  typedef typename DstXprType::StorageIndex StorageIndex;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &/*func*/)
+  {
+    typename DstXprType::PlainObject idMat(src.m_qr.rows(), src.m_qr.rows());
+    idMat.setIdentity();
+    // Sort the sparse householder reflectors if needed
+    const_cast<SparseQRType *>(&src.m_qr)->_sort_matrix_Q();
+    dst = SparseQR_QProduct<SparseQRType, DstXprType>(src.m_qr, idMat, false);
+  }
+};
+
+template< typename DstXprType, typename SparseQRType>
+struct Assignment<DstXprType, SparseQRMatrixQReturnType<SparseQRType>, internal::assign_op<typename DstXprType::Scalar,typename DstXprType::Scalar>, Sparse2Dense>
+{
+  typedef SparseQRMatrixQReturnType<SparseQRType> SrcXprType;
+  typedef typename DstXprType::Scalar Scalar;
+  typedef typename DstXprType::StorageIndex StorageIndex;
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &/*func*/)
+  {
+    dst = src.m_qr.matrixQ() * DstXprType::Identity(src.m_qr.rows(), src.m_qr.rows());
+  }
+};
+
+} // end namespace internal
+
 } // end namespace Eigen
 
 #endif

DELETED 3rd_party/eigen/Eigen/src/StlSupport/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/StlSupport/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/StlSupport/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/StlSupport/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_StlSupport_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_StlSupport_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/StlSupport COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/StlSupport/StdDeque.h
==================================================================
--- 3rd_party/eigen/Eigen/src/StlSupport/StdDeque.h
+++ 3rd_party/eigen/Eigen/src/StlSupport/StdDeque.h
@@ -11,36 +11,28 @@
 #ifndef EIGEN_STDDEQUE_H
 #define EIGEN_STDDEQUE_H
 
 #include "details.h"
 
-// Define the explicit instantiation (e.g. necessary for the Intel compiler)
-#if defined(__INTEL_COMPILER) || defined(__GNUC__)
-  #define EIGEN_EXPLICIT_STL_DEQUE_INSTANTIATION(...) template class std::deque<__VA_ARGS__, EIGEN_ALIGNED_ALLOCATOR<__VA_ARGS__> >;
-#else
-  #define EIGEN_EXPLICIT_STL_DEQUE_INSTANTIATION(...)
-#endif
-
 /**
  * This section contains a convenience MACRO which allows an easy specialization of
  * std::deque such that for data types with alignment issues the correct allocator
  * is used automatically.
  */
 #define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...) \
-EIGEN_EXPLICIT_STL_DEQUE_INSTANTIATION(__VA_ARGS__) \
 namespace std \
 { \
-  template<typename _Ay> \
-  class deque<__VA_ARGS__, _Ay>  \
+  template<> \
+  class deque<__VA_ARGS__, std::allocator<__VA_ARGS__> >           \
     : public deque<__VA_ARGS__, EIGEN_ALIGNED_ALLOCATOR<__VA_ARGS__> > \
   { \
     typedef deque<__VA_ARGS__, EIGEN_ALIGNED_ALLOCATOR<__VA_ARGS__> > deque_base; \
   public: \
     typedef __VA_ARGS__ value_type; \
-    typedef typename deque_base::allocator_type allocator_type; \
-    typedef typename deque_base::size_type size_type;  \
-    typedef typename deque_base::iterator iterator;  \
+    typedef deque_base::allocator_type allocator_type; \
+    typedef deque_base::size_type size_type;  \
+    typedef deque_base::iterator iterator;  \
     explicit deque(const allocator_type& a = allocator_type()) : deque_base(a) {}  \
     template<typename InputIterator> \
     deque(InputIterator first, InputIterator last, const allocator_type& a = allocator_type()) : deque_base(first, last, a) {} \
     deque(const deque& c) : deque_base(c) {}  \
     explicit deque(size_type num, const value_type& val = value_type()) : deque_base(num, val) {} \
@@ -51,11 +43,11 @@
     } \
   }; \
 }
 
 // check whether we really need the std::deque specialization
-#if !(defined(_GLIBCXX_DEQUE) && (!EIGEN_GNUC_AT_LEAST(4,1))) /* Note that before gcc-4.1 we already have: std::deque::resize(size_type,const T&). */
+#if !EIGEN_HAS_CXX11_CONTAINERS && !(defined(_GLIBCXX_DEQUE) && (!EIGEN_GNUC_AT_LEAST(4,1))) /* Note that before gcc-4.1 we already have: std::deque::resize(size_type,const T&). */
 
 namespace std {
 
 #define EIGEN_STD_DEQUE_SPECIALIZATION_BODY \
   public:  \

Index: 3rd_party/eigen/Eigen/src/StlSupport/StdList.h
==================================================================
--- 3rd_party/eigen/Eigen/src/StlSupport/StdList.h
+++ 3rd_party/eigen/Eigen/src/StlSupport/StdList.h
@@ -10,36 +10,28 @@
 #ifndef EIGEN_STDLIST_H
 #define EIGEN_STDLIST_H
 
 #include "details.h"
 
-// Define the explicit instantiation (e.g. necessary for the Intel compiler)
-#if defined(__INTEL_COMPILER) || defined(__GNUC__)
-  #define EIGEN_EXPLICIT_STL_LIST_INSTANTIATION(...) template class std::list<__VA_ARGS__, EIGEN_ALIGNED_ALLOCATOR<__VA_ARGS__> >;
-#else
-  #define EIGEN_EXPLICIT_STL_LIST_INSTANTIATION(...)
-#endif
-
 /**
  * This section contains a convenience MACRO which allows an easy specialization of
  * std::list such that for data types with alignment issues the correct allocator
  * is used automatically.
  */
 #define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...) \
-EIGEN_EXPLICIT_STL_LIST_INSTANTIATION(__VA_ARGS__) \
 namespace std \
 { \
-  template<typename _Ay> \
-  class list<__VA_ARGS__, _Ay>  \
+  template<> \
+  class list<__VA_ARGS__, std::allocator<__VA_ARGS__> >           \
     : public list<__VA_ARGS__, EIGEN_ALIGNED_ALLOCATOR<__VA_ARGS__> > \
   { \
     typedef list<__VA_ARGS__, EIGEN_ALIGNED_ALLOCATOR<__VA_ARGS__> > list_base; \
   public: \
     typedef __VA_ARGS__ value_type; \
-    typedef typename list_base::allocator_type allocator_type; \
-    typedef typename list_base::size_type size_type;  \
-    typedef typename list_base::iterator iterator;  \
+    typedef list_base::allocator_type allocator_type; \
+    typedef list_base::size_type size_type;  \
+    typedef list_base::iterator iterator;  \
     explicit list(const allocator_type& a = allocator_type()) : list_base(a) {}  \
     template<typename InputIterator> \
     list(InputIterator first, InputIterator last, const allocator_type& a = allocator_type()) : list_base(first, last, a) {} \
     list(const list& c) : list_base(c) {}  \
     explicit list(size_type num, const value_type& val = value_type()) : list_base(num, val) {} \
@@ -49,12 +41,12 @@
       return *this;  \
     } \
   }; \
 }
 
-// check whether we really need the std::vector specialization
-#if !(defined(_GLIBCXX_VECTOR) && (!EIGEN_GNUC_AT_LEAST(4,1))) /* Note that before gcc-4.1 we already have: std::list::resize(size_type,const T&). */
+// check whether we really need the std::list specialization
+#if !EIGEN_HAS_CXX11_CONTAINERS && !(defined(_GLIBCXX_LIST) && (!EIGEN_GNUC_AT_LEAST(4,1))) /* Note that before gcc-4.1 we already have: std::list::resize(size_type,const T&). */
 
 namespace std
 {
 
 #define EIGEN_STD_LIST_SPECIALIZATION_BODY \

Index: 3rd_party/eigen/Eigen/src/StlSupport/StdVector.h
==================================================================
--- 3rd_party/eigen/Eigen/src/StlSupport/StdVector.h
+++ 3rd_party/eigen/Eigen/src/StlSupport/StdVector.h
@@ -42,10 +42,13 @@
       return *this;  \
     } \
   }; \
 }
 
+// Don't specialize if containers are implemented according to C++11
+#if !EIGEN_HAS_CXX11_CONTAINERS
+
 namespace std {
 
 #define EIGEN_STD_VECTOR_SPECIALIZATION_BODY \
   public:  \
     typedef T value_type; \
@@ -120,7 +123,9 @@
       vector_base::insert(vector_base::end(), new_size - vector_base::size(), x);
   }
 #endif
   };
 }
+#endif // !EIGEN_HAS_CXX11_CONTAINERS
+
 
 #endif // EIGEN_STDVECTOR_H

Index: 3rd_party/eigen/Eigen/src/StlSupport/details.h
==================================================================
--- 3rd_party/eigen/Eigen/src/StlSupport/details.h
+++ 3rd_party/eigen/Eigen/src/StlSupport/details.h
@@ -20,17 +20,17 @@
   // This one is needed to prevent reimplementing the whole std::vector.
   template <class T>
   class aligned_allocator_indirection : public EIGEN_ALIGNED_ALLOCATOR<T>
   {
   public:
-    typedef size_t    size_type;
-    typedef ptrdiff_t difference_type;
-    typedef T*        pointer;
-    typedef const T*  const_pointer;
-    typedef T&        reference;
-    typedef const T&  const_reference;
-    typedef T         value_type;
+    typedef std::size_t     size_type;
+    typedef std::ptrdiff_t  difference_type;
+    typedef T*              pointer;
+    typedef const T*        const_pointer;
+    typedef T&              reference;
+    typedef const T&        const_reference;
+    typedef T               value_type;
 
     template<class U>
     struct rebind
     {
       typedef aligned_allocator_indirection<U> other;
@@ -44,11 +44,11 @@
     template<class U>
     aligned_allocator_indirection(const EIGEN_ALIGNED_ALLOCATOR<U>& ) {}
     ~aligned_allocator_indirection() {}
   };
 
-#ifdef _MSC_VER
+#if EIGEN_COMP_MSVC
 
   // sometimes, MSVC detects, at compile time, that the argument x
   // in std::vector::resize(size_t s,T x) won't be aligned and generate an error
   // even if this function is never called. Whence this little wrapper.
 #define EIGEN_WORKAROUND_MSVC_STL_SUPPORT(T) \

DELETED 3rd_party/eigen/Eigen/src/SuperLUSupport/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/SuperLUSupport/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/SuperLUSupport/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/SuperLUSupport/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SuperLUSupport_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_SuperLUSupport_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SuperLUSupport COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h
==================================================================
--- 3rd_party/eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h
+++ 3rd_party/eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h
@@ -1,42 +1,67 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SUPERLUSUPPORT_H
 #define EIGEN_SUPERLUSUPPORT_H
 
-namespace Eigen { 
+namespace Eigen {
 
+#if defined(SUPERLU_MAJOR_VERSION) && (SUPERLU_MAJOR_VERSION >= 5)
 #define DECL_GSSVX(PREFIX,FLOATTYPE,KEYTYPE)		\
     extern "C" {                                                                                          \
-      typedef struct { FLOATTYPE for_lu; FLOATTYPE total_needed; int expansions; } PREFIX##mem_usage_t;   \
+      extern void PREFIX##gssvx(superlu_options_t *, SuperMatrix *, int *, int *, int *,                  \
+                                char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *,           \
+                                void *, int, SuperMatrix *, SuperMatrix *,                                \
+                                FLOATTYPE *, FLOATTYPE *, FLOATTYPE *, FLOATTYPE *,                       \
+                                GlobalLU_t *, mem_usage_t *, SuperLUStat_t *, int *);                     \
+    }                                                                                                     \
+    inline float SuperLU_gssvx(superlu_options_t *options, SuperMatrix *A,                                \
+         int *perm_c, int *perm_r, int *etree, char *equed,                                               \
+         FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L,                                                      \
+         SuperMatrix *U, void *work, int lwork,                                                           \
+         SuperMatrix *B, SuperMatrix *X,                                                                  \
+         FLOATTYPE *recip_pivot_growth,                                                                   \
+         FLOATTYPE *rcond, FLOATTYPE *ferr, FLOATTYPE *berr,                                              \
+         SuperLUStat_t *stats, int *info, KEYTYPE) {                                                      \
+    mem_usage_t mem_usage;                                                                                \
+    GlobalLU_t gLU;                                                                                       \
+    PREFIX##gssvx(options, A, perm_c, perm_r, etree, equed, R, C, L,                                      \
+         U, work, lwork, B, X, recip_pivot_growth, rcond,                                                 \
+         ferr, berr, &gLU, &mem_usage, stats, info);                                                      \
+    return mem_usage.for_lu; /* bytes used by the factor storage */                                       \
+  }
+#else // version < 5.0
+#define DECL_GSSVX(PREFIX,FLOATTYPE,KEYTYPE)		\
+    extern "C" {                                                                                          \
       extern void PREFIX##gssvx(superlu_options_t *, SuperMatrix *, int *, int *, int *,                  \
                                 char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *,           \
                                 void *, int, SuperMatrix *, SuperMatrix *,                                \
                                 FLOATTYPE *, FLOATTYPE *, FLOATTYPE *, FLOATTYPE *,                       \
-                                PREFIX##mem_usage_t *, SuperLUStat_t *, int *);                           \
+                                mem_usage_t *, SuperLUStat_t *, int *);                                   \
     }                                                                                                     \
     inline float SuperLU_gssvx(superlu_options_t *options, SuperMatrix *A,                                \
          int *perm_c, int *perm_r, int *etree, char *equed,                                               \
          FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L,                                                      \
          SuperMatrix *U, void *work, int lwork,                                                           \
          SuperMatrix *B, SuperMatrix *X,                                                                  \
          FLOATTYPE *recip_pivot_growth,                                                                   \
          FLOATTYPE *rcond, FLOATTYPE *ferr, FLOATTYPE *berr,                                              \
          SuperLUStat_t *stats, int *info, KEYTYPE) {                                                      \
-    PREFIX##mem_usage_t mem_usage;                                                                        \
+    mem_usage_t mem_usage;                                                                                \
     PREFIX##gssvx(options, A, perm_c, perm_r, etree, equed, R, C, L,                                      \
          U, work, lwork, B, X, recip_pivot_growth, rcond,                                                 \
          ferr, berr, &mem_usage, stats, info);                                                            \
     return mem_usage.for_lu; /* bytes used by the factor storage */                                       \
   }
+#endif
 
 DECL_GSSVX(s,float,float)
 DECL_GSSVX(c,float,std::complex<float>)
 DECL_GSSVX(d,double,double)
 DECL_GSSVX(z,double,std::complex<double>)
@@ -51,21 +76,21 @@
 #define DECL_GSISX(PREFIX,FLOATTYPE,KEYTYPE)                                                    \
     extern "C" {                                                                                \
       extern void PREFIX##gsisx(superlu_options_t *, SuperMatrix *, int *, int *, int *,        \
                          char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *,        \
                          void *, int, SuperMatrix *, SuperMatrix *, FLOATTYPE *, FLOATTYPE *,   \
-                         PREFIX##mem_usage_t *, SuperLUStat_t *, int *);                        \
+                         mem_usage_t *, SuperLUStat_t *, int *);                        \
     }                                                                                           \
     inline float SuperLU_gsisx(superlu_options_t *options, SuperMatrix *A,                      \
          int *perm_c, int *perm_r, int *etree, char *equed,                                     \
          FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L,                                            \
          SuperMatrix *U, void *work, int lwork,                                                 \
          SuperMatrix *B, SuperMatrix *X,                                                        \
          FLOATTYPE *recip_pivot_growth,                                                         \
          FLOATTYPE *rcond,                                                                      \
          SuperLUStat_t *stats, int *info, KEYTYPE) {                                            \
-    PREFIX##mem_usage_t mem_usage;                                                              \
+    mem_usage_t mem_usage;                                                              \
     PREFIX##gsisx(options, A, perm_c, perm_r, etree, equed, R, C, L,                            \
          U, work, lwork, B, X, recip_pivot_growth, rcond,                                       \
          &mem_usage, stats, info);                                                              \
     return mem_usage.for_lu; /* bytes used by the factor storage */                             \
   }
@@ -154,41 +179,42 @@
     SluMatrix res;
     res.setStorageType(SLU_DN);
     res.setScalarType<typename MatrixType::Scalar>();
     res.Mtype     = SLU_GE;
 
-    res.nrow      = mat.rows();
-    res.ncol      = mat.cols();
+    res.nrow      = internal::convert_index<int>(mat.rows());
+    res.ncol      = internal::convert_index<int>(mat.cols());
 
-    res.storage.lda       = MatrixType::IsVectorAtCompileTime ? mat.size() : mat.outerStride();
+    res.storage.lda       = internal::convert_index<int>(MatrixType::IsVectorAtCompileTime ? mat.size() : mat.outerStride());
     res.storage.values    = (void*)(mat.data());
     return res;
   }
 
   template<typename MatrixType>
-  static SluMatrix Map(SparseMatrixBase<MatrixType>& mat)
+  static SluMatrix Map(SparseMatrixBase<MatrixType>& a_mat)
   {
+    MatrixType &mat(a_mat.derived());
     SluMatrix res;
     if ((MatrixType::Flags&RowMajorBit)==RowMajorBit)
     {
       res.setStorageType(SLU_NR);
-      res.nrow      = mat.cols();
-      res.ncol      = mat.rows();
+      res.nrow      = internal::convert_index<int>(mat.cols());
+      res.ncol      = internal::convert_index<int>(mat.rows());
     }
     else
     {
       res.setStorageType(SLU_NC);
-      res.nrow      = mat.rows();
-      res.ncol      = mat.cols();
+      res.nrow      = internal::convert_index<int>(mat.rows());
+      res.ncol      = internal::convert_index<int>(mat.cols());
     }
 
     res.Mtype       = SLU_GE;
 
-    res.storage.nnz       = mat.nonZeros();
-    res.storage.values    = mat.derived().valuePtr();
-    res.storage.innerInd  = mat.derived().innerIndexPtr();
-    res.storage.outerInd  = mat.derived().outerIndexPtr();
+    res.storage.nnz       = internal::convert_index<int>(mat.nonZeros());
+    res.storage.values    = mat.valuePtr();
+    res.storage.innerInd  = mat.innerIndexPtr();
+    res.storage.outerInd  = mat.outerIndexPtr();
 
     res.setScalarType<typename MatrixType::Scalar>();
 
     // FIXME the following is not very accurate
     if (MatrixType::Flags & Upper)
@@ -286,21 +312,30 @@
 /** \ingroup SuperLUSupport_Module
   * \class SuperLUBase
   * \brief The base class for the direct and incomplete LU factorization of SuperLU
   */
 template<typename _MatrixType, typename Derived>
-class SuperLUBase : internal::noncopyable
+class SuperLUBase : public SparseSolverBase<Derived>
 {
+  protected:
+    typedef SparseSolverBase<Derived> Base;
+    using Base::derived;
+    using Base::m_isInitialized;
   public:
     typedef _MatrixType MatrixType;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::StorageIndex StorageIndex;
     typedef Matrix<Scalar,Dynamic,1> Vector;
     typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
     typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;    
+    typedef Map<PermutationMatrix<Dynamic,Dynamic,int> > PermutationMap;
     typedef SparseMatrix<Scalar> LUMatrixType;
+    enum {
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
 
   public:
 
     SuperLUBase() {}
 
@@ -307,13 +342,10 @@
     ~SuperLUBase()
     {
       clearFactors();
     }
     
-    Derived& derived() { return *static_cast<Derived*>(this); }
-    const Derived& derived() const { return *static_cast<const Derived*>(this); }
-    
     inline Index rows() const { return m_matrix.rows(); }
     inline Index cols() const { return m_matrix.cols(); }
     
     /** \returns a reference to the Super LU option object to configure the  Super LU algorithms. */
     inline superlu_options_t& options() { return m_sluOptions; }
@@ -333,37 +365,11 @@
     void compute(const MatrixType& matrix)
     {
       derived().analyzePattern(matrix);
       derived().factorize(matrix);
     }
-    
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<SuperLUBase, Rhs> solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "SuperLU is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "SuperLU::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<SuperLUBase, Rhs>(*this, b.derived());
-    }
-    
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::sparse_solve_retval<SuperLUBase, Rhs> solve(const SparseMatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "SuperLU is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "SuperLU::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::sparse_solve_retval<SuperLUBase, Rhs>(*this, b.derived());
-    }
-    
+
     /** Performs a symbolic decomposition on the sparcity of \a matrix.
       *
       * This function is particularly useful when solving for several problems having the same structure.
       * 
       * \sa factorize()
@@ -384,11 +390,11 @@
     
     void initFactorization(const MatrixType& a)
     {
       set_default_options(&this->m_sluOptions);
       
-      const int size = a.rows();
+      const Index size = a.rows();
       m_matrix = a;
 
       m_sluA = internal::asSluMatrix(m_matrix);
       clearFactors();
 
@@ -403,11 +409,11 @@
       m_sluB.setScalarType<Scalar>();
       m_sluB.Mtype          = SLU_GE;
       m_sluB.storage.values = 0;
       m_sluB.nrow           = 0;
       m_sluB.ncol           = 0;
-      m_sluB.storage.lda    = size;
+      m_sluB.storage.lda    = internal::convert_index<int>(size);
       m_sluX                = m_sluB;
       
       m_extractedDataAreDirty = true;
     }
     
@@ -451,11 +457,10 @@
     mutable Matrix<RealScalar,Dynamic,1> m_sluRscale, m_sluCscale;
     mutable Matrix<RealScalar,Dynamic,1> m_sluFerr, m_sluBerr;
     mutable char m_sluEqued;
 
     mutable ComputationInfo m_info;
-    bool m_isInitialized;
     int m_factorizationIsOk;
     int m_analysisIsOk;
     mutable bool m_extractedDataAreDirty;
     
   private:
@@ -471,32 +476,38 @@
   * using the SuperLU library. The sparse matrix A must be squared and invertible. The vectors or matrices
   * X and B can be either dense or sparse.
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   *
-  * \sa \ref TutorialSparseDirectSolvers
+  * \warning This class is only for the 4.x versions of SuperLU. The 3.x and 5.x versions are not supported.
+  *
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class SparseLU
   */
 template<typename _MatrixType>
 class SuperLU : public SuperLUBase<_MatrixType,SuperLU<_MatrixType> >
 {
   public:
     typedef SuperLUBase<_MatrixType,SuperLU> Base;
     typedef _MatrixType MatrixType;
     typedef typename Base::Scalar Scalar;
     typedef typename Base::RealScalar RealScalar;
-    typedef typename Base::Index Index;
+    typedef typename Base::StorageIndex StorageIndex;
     typedef typename Base::IntRowVectorType IntRowVectorType;
-    typedef typename Base::IntColVectorType IntColVectorType;    
+    typedef typename Base::IntColVectorType IntColVectorType;   
+    typedef typename Base::PermutationMap PermutationMap;
     typedef typename Base::LUMatrixType LUMatrixType;
     typedef TriangularView<LUMatrixType, Lower|UnitDiag>  LMatrixType;
-    typedef TriangularView<LUMatrixType,  Upper>           UMatrixType;
+    typedef TriangularView<LUMatrixType,  Upper>          UMatrixType;
 
   public:
+    using Base::_solve_impl;
 
     SuperLU() : Base() { init(); }
 
-    SuperLU(const MatrixType& matrix) : Base()
+    explicit SuperLU(const MatrixType& matrix) : Base()
     {
       init();
       Base::compute(matrix);
     }
 
@@ -523,15 +534,13 @@
       *
       * \sa analyzePattern()
       */
     void factorize(const MatrixType& matrix);
     
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** \internal */
     template<typename Rhs,typename Dest>
-    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const;
-    #endif // EIGEN_PARSED_BY_DOXYGEN
+    void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const;
     
     inline const LMatrixType& matrixL() const
     {
       if (m_extractedDataAreDirty) this->extractData();
       return m_l;
@@ -635,27 +644,31 @@
   m_factorizationIsOk = true;
 }
 
 template<typename MatrixType>
 template<typename Rhs,typename Dest>
-void SuperLU<MatrixType>::_solve(const MatrixBase<Rhs> &b, MatrixBase<Dest>& x) const
+void SuperLU<MatrixType>::_solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest>& x) const
 {
   eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or analyzePattern()/factorize()");
 
-  const int size = m_matrix.rows();
-  const int rhsCols = b.cols();
+  const Index size = m_matrix.rows();
+  const Index rhsCols = b.cols();
   eigen_assert(size==b.rows());
 
   m_sluOptions.Trans = NOTRANS;
   m_sluOptions.Fact = FACTORED;
   m_sluOptions.IterRefine = NOREFINE;
   
 
   m_sluFerr.resize(rhsCols);
   m_sluBerr.resize(rhsCols);
-  m_sluB = SluMatrix::Map(b.const_cast_derived());
-  m_sluX = SluMatrix::Map(x.derived());
+  
+  Ref<const Matrix<typename Rhs::Scalar,Dynamic,Dynamic,ColMajor> > b_ref(b);
+  Ref<const Matrix<typename Dest::Scalar,Dynamic,Dynamic,ColMajor> > x_ref(x);
+  
+  m_sluB = SluMatrix::Map(b_ref.const_cast_derived());
+  m_sluX = SluMatrix::Map(x_ref.const_cast_derived());
   
   typename Rhs::PlainObject b_cpy;
   if(m_sluEqued!='N')
   {
     b_cpy = b;
@@ -674,10 +687,14 @@
                 &m_sluB, &m_sluX,
                 &recip_pivot_growth, &rcond,
                 &m_sluFerr[0], &m_sluBerr[0],
                 &m_sluStat, &info, Scalar());
   StatFree(&m_sluStat);
+  
+  if(x.derived().data() != x_ref.data())
+    x = x_ref;
+  
   m_info = info==0 ? Success : NumericalIssue;
 }
 
 // the code of this extractData() function has been adapted from the SuperLU's Matlab support code,
 //
@@ -697,11 +714,11 @@
     int         lastl = 0, lastu = 0;
     SCformat    *Lstore = static_cast<SCformat*>(m_sluL.Store);
     NCformat    *Ustore = static_cast<NCformat*>(m_sluU.Store);
     Scalar      *SNptr;
 
-    const int size = m_matrix.rows();
+    const Index size = m_matrix.rows();
     m_l.resize(size,size);
     m_l.resizeNonZeros(Lstore->nnz);
     m_u.resize(size,size);
     m_u.resizeNonZeros(Ustore->nnz);
 
@@ -789,10 +806,12 @@
       eigen_assert(m_u.innerIndexPtr()[lastId]<=j);
       if (m_u.innerIndexPtr()[lastId]==j)
         det *= m_u.valuePtr()[lastId];
     }
   }
+  if(PermutationMap(m_p.data(),m_p.size()).determinant()*PermutationMap(m_q.data(),m_q.size()).determinant()<0)
+    det = -det;
   if(m_sluEqued!='N')
     return det/m_sluRscale.prod()/m_sluCscale.prod();
   else
     return det;
 }
@@ -808,15 +827,17 @@
   * \brief A sparse direct \b incomplete LU factorization and solver based on the SuperLU library
   *
   * This class allows to solve for an approximate solution of A.X = B sparse linear problems via an incomplete LU factorization
   * using the SuperLU library. This class is aimed to be used as a preconditioner of the iterative linear solvers.
   *
-  * \warning This class requires SuperLU 4 or later.
+  * \warning This class is only for the 4.x versions of SuperLU. The 3.x and 5.x versions are not supported.
   *
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   *
-  * \sa \ref TutorialSparseDirectSolvers, class ConjugateGradient, class BiCGSTAB
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class IncompleteLUT, class ConjugateGradient, class BiCGSTAB
   */
 
 template<typename _MatrixType>
 class SuperILU : public SuperLUBase<_MatrixType,SuperILU<_MatrixType> >
 {
@@ -823,13 +844,13 @@
   public:
     typedef SuperLUBase<_MatrixType,SuperILU> Base;
     typedef _MatrixType MatrixType;
     typedef typename Base::Scalar Scalar;
     typedef typename Base::RealScalar RealScalar;
-    typedef typename Base::Index Index;
 
   public:
+    using Base::_solve_impl;
 
     SuperILU() : Base() { init(); }
 
     SuperILU(const MatrixType& matrix) : Base()
     {
@@ -861,11 +882,11 @@
     void factorize(const MatrixType& matrix);
     
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** \internal */
     template<typename Rhs,typename Dest>
-    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const;
+    void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const;
     #endif // EIGEN_PARSED_BY_DOXYGEN
     
   protected:
     
     using Base::m_matrix;
@@ -944,13 +965,14 @@
   // FIXME how to better check for errors ???
   m_info = info == 0 ? Success : NumericalIssue;
   m_factorizationIsOk = true;
 }
 
+#ifndef EIGEN_PARSED_BY_DOXYGEN
 template<typename MatrixType>
 template<typename Rhs,typename Dest>
-void SuperILU<MatrixType>::_solve(const MatrixBase<Rhs> &b, MatrixBase<Dest>& x) const
+void SuperILU<MatrixType>::_solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest>& x) const
 {
   eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or analyzePattern()/factorize()");
 
   const int size = m_matrix.rows();
   const int rhsCols = b.cols();
@@ -960,12 +982,16 @@
   m_sluOptions.Fact = FACTORED;
   m_sluOptions.IterRefine = NOREFINE;
 
   m_sluFerr.resize(rhsCols);
   m_sluBerr.resize(rhsCols);
-  m_sluB = SluMatrix::Map(b.const_cast_derived());
-  m_sluX = SluMatrix::Map(x.derived());
+  
+  Ref<const Matrix<typename Rhs::Scalar,Dynamic,Dynamic,ColMajor> > b_ref(b);
+  Ref<const Matrix<typename Dest::Scalar,Dynamic,Dynamic,ColMajor> > x_ref(x);
+  
+  m_sluB = SluMatrix::Map(b_ref.const_cast_derived());
+  m_sluX = SluMatrix::Map(x_ref.const_cast_derived());
 
   typename Rhs::PlainObject b_cpy;
   if(m_sluEqued!='N')
   {
     b_cpy = b;
@@ -984,43 +1010,18 @@
                 NULL, 0,
                 &m_sluB, &m_sluX,
                 &recip_pivot_growth, &rcond,
                 &m_sluStat, &info, Scalar());
   StatFree(&m_sluStat);
+  
+  if(x.derived().data() != x_ref.data())
+    x = x_ref;
 
   m_info = info==0 ? Success : NumericalIssue;
 }
 #endif
 
-namespace internal {
-  
-template<typename _MatrixType, typename Derived, typename Rhs>
-struct solve_retval<SuperLUBase<_MatrixType,Derived>, Rhs>
-  : solve_retval_base<SuperLUBase<_MatrixType,Derived>, Rhs>
-{
-  typedef SuperLUBase<_MatrixType,Derived> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec().derived()._solve(rhs(),dst);
-  }
-};
-
-template<typename _MatrixType, typename Derived, typename Rhs>
-struct sparse_solve_retval<SuperLUBase<_MatrixType,Derived>, Rhs>
-  : sparse_solve_retval_base<SuperLUBase<_MatrixType,Derived>, Rhs>
-{
-  typedef SuperLUBase<_MatrixType,Derived> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    this->defaultEvalTo(dst);
-  }
-};
-
-} // end namespace internal
+#endif
 
 } // end namespace Eigen
 
 #endif // EIGEN_SUPERLUSUPPORT_H

DELETED 3rd_party/eigen/Eigen/src/UmfPackSupport/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/UmfPackSupport/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/UmfPackSupport/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/UmfPackSupport/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_UmfPackSupport_SRCS "*.h")
-
-INSTALL(FILES 
-  ${Eigen_UmfPackSupport_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/UmfPackSupport COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/UmfPackSupport/UmfPackSupport.h
==================================================================
--- 3rd_party/eigen/Eigen/src/UmfPackSupport/UmfPackSupport.h
+++ 3rd_party/eigen/Eigen/src/UmfPackSupport/UmfPackSupport.h
@@ -8,16 +8,41 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_UMFPACKSUPPORT_H
 #define EIGEN_UMFPACKSUPPORT_H
 
-namespace Eigen { 
+namespace Eigen {
 
 /* TODO extract L, extract U, compute det, etc... */
 
 // generic double/complex<double> wrapper functions:
 
+
+inline void umfpack_defaults(double control[UMFPACK_CONTROL], double)
+{ umfpack_di_defaults(control); }
+
+inline void umfpack_defaults(double control[UMFPACK_CONTROL], std::complex<double>)
+{ umfpack_zi_defaults(control); }
+
+inline void umfpack_report_info(double control[UMFPACK_CONTROL], double info[UMFPACK_INFO], double)
+{ umfpack_di_report_info(control, info);}
+
+inline void umfpack_report_info(double control[UMFPACK_CONTROL], double info[UMFPACK_INFO], std::complex<double>)
+{ umfpack_zi_report_info(control, info);}
+
+inline void umfpack_report_status(double control[UMFPACK_CONTROL], int status, double)
+{ umfpack_di_report_status(control, status);}
+
+inline void umfpack_report_status(double control[UMFPACK_CONTROL], int status, std::complex<double>)
+{ umfpack_zi_report_status(control, status);}
+
+inline void umfpack_report_control(double control[UMFPACK_CONTROL], double)
+{ umfpack_di_report_control(control);}
+
+inline void umfpack_report_control(double control[UMFPACK_CONTROL], std::complex<double>)
+{ umfpack_zi_report_control(control);}
+
 inline void umfpack_free_numeric(void **Numeric, double)
 { umfpack_di_free_numeric(Numeric); *Numeric = 0; }
 
 inline void umfpack_free_numeric(void **Numeric, std::complex<double>)
 { umfpack_zi_free_numeric(Numeric); *Numeric = 0; }
@@ -105,19 +130,10 @@
 {
   double& mx_real = numext::real_ref(*Mx);
   return umfpack_zi_get_determinant(&mx_real,0,Ex,NumericHandle,User_Info);
 }
 
-namespace internal {
-  template<typename T> struct umfpack_helper_is_sparse_plain : false_type {};
-  template<typename Scalar, int Options, typename StorageIndex>
-  struct umfpack_helper_is_sparse_plain<SparseMatrix<Scalar,Options,StorageIndex> >
-    : true_type {};
-  template<typename Scalar, int Options, typename StorageIndex>
-  struct umfpack_helper_is_sparse_plain<MappedSparseMatrix<Scalar,Options,StorageIndex> >
-    : true_type {};
-}
 
 /** \ingroup UmfPackSupport_Module
   * \brief A sparse LU factorization and solver based on UmfPack
   *
   * This class allows to solve for A.X = B sparse linear problems via a LU factorization
@@ -126,31 +142,51 @@
   *
   * \warning The input matrix A should be in a \b compressed and \b column-major form.
   * Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix.
   * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
   *
-  * \sa \ref TutorialSparseDirectSolvers
+  * \implsparsesolverconcept
+  *
+  * \sa \ref TutorialSparseSolverConcept, class SparseLU
   */
 template<typename _MatrixType>
-class UmfPackLU : internal::noncopyable
+class UmfPackLU : public SparseSolverBase<UmfPackLU<_MatrixType> >
 {
+  protected:
+    typedef SparseSolverBase<UmfPackLU<_MatrixType> > Base;
+    using Base::m_isInitialized;
   public:
+    using Base::_solve_impl;
     typedef _MatrixType MatrixType;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::StorageIndex StorageIndex;
     typedef Matrix<Scalar,Dynamic,1> Vector;
     typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
     typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
     typedef SparseMatrix<Scalar> LUMatrixType;
     typedef SparseMatrix<Scalar,ColMajor,int> UmfpackMatrixType;
+    typedef Ref<const UmfpackMatrixType, StandardCompressedFormat> UmfpackMatrixRef;
+    enum {
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
 
   public:
 
-    UmfPackLU() { init(); }
+    typedef Array<double, UMFPACK_CONTROL, 1> UmfpackControl;
+    typedef Array<double, UMFPACK_INFO, 1> UmfpackInfo;
+
+    UmfPackLU()
+      : m_dummy(0,0), mp_matrix(m_dummy)
+    {
+      init();
+    }
 
-    UmfPackLU(const MatrixType& matrix)
+    template<typename InputMatrixType>
+    explicit UmfPackLU(const InputMatrixType& matrix)
+      : mp_matrix(matrix)
     {
       init();
       compute(matrix);
     }
 
@@ -158,12 +194,12 @@
     {
       if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar());
       if(m_numeric)  umfpack_free_numeric(&m_numeric,Scalar());
     }
 
-    inline Index rows() const { return m_copyMatrix.rows(); }
-    inline Index cols() const { return m_copyMatrix.cols(); }
+    inline Index rows() const { return mp_matrix.rows(); }
+    inline Index cols() const { return mp_matrix.cols(); }
 
     /** \brief Reports whether previous computation was successful.
       *
       * \returns \c Success if computation was succesful,
       *          \c NumericalIssue if the matrix.appears to be negative.
@@ -196,50 +232,24 @@
     {
       if (m_extractedDataAreDirty) extractData();
       return m_q;
     }
 
-    /** Computes the sparse Cholesky decomposition of \a matrix 
+    /** Computes the sparse Cholesky decomposition of \a matrix
      *  Note that the matrix should be column-major, and in compressed format for best performance.
      *  \sa SparseMatrix::makeCompressed().
      */
     template<typename InputMatrixType>
     void compute(const InputMatrixType& matrix)
     {
       if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar());
       if(m_numeric)  umfpack_free_numeric(&m_numeric,Scalar());
-      grapInput(matrix.derived());
+      grab(matrix.derived());
       analyzePattern_impl();
       factorize_impl();
     }
 
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<UmfPackLU, Rhs> solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "UmfPackLU is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<UmfPackLU, Rhs>(*this, b.derived());
-    }
-
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::sparse_solve_retval<UmfPackLU, Rhs> solve(const SparseMatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "UmfPackLU is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::sparse_solve_retval<UmfPackLU, Rhs>(*this, b.derived());
-    }
-
     /** Performs a symbolic decomposition on the sparcity of \a matrix.
       *
       * This function is particularly useful when solving for several problems having the same structure.
       *
       * \sa factorize(), compute()
@@ -247,15 +257,48 @@
     template<typename InputMatrixType>
     void analyzePattern(const InputMatrixType& matrix)
     {
       if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar());
       if(m_numeric)  umfpack_free_numeric(&m_numeric,Scalar());
-      
-      grapInput(matrix.derived());
+
+      grab(matrix.derived());
 
       analyzePattern_impl();
     }
+
+    /** Provides the return status code returned by UmfPack during the numeric
+      * factorization.
+      *
+      * \sa factorize(), compute()
+      */
+    inline int umfpackFactorizeReturncode() const
+    {
+      eigen_assert(m_numeric && "UmfPackLU: you must first call factorize()");
+      return m_fact_errorCode;
+    }
+
+    /** Provides access to the control settings array used by UmfPack.
+      *
+      * If this array contains NaN's, the default values are used.
+      *
+      * See UMFPACK documentation for details.
+      */
+    inline const UmfpackControl& umfpackControl() const
+    {
+      return m_control;
+    }
+
+    /** Provides access to the control settings array used by UmfPack.
+      *
+      * If this array contains NaN's, the default values are used.
+      *
+      * See UMFPACK documentation for details.
+      */
+    inline UmfpackControl& umfpackControl()
+    {
+      return m_control;
+    }
 
     /** Performs a numeric decomposition of \a matrix
       *
       * The given matrix must has the same sparcity than the matrix on which the pattern anylysis has been performed.
       *
@@ -266,20 +309,46 @@
     {
       eigen_assert(m_analysisIsOk && "UmfPackLU: you must first call analyzePattern()");
       if(m_numeric)
         umfpack_free_numeric(&m_numeric,Scalar());
 
-      grapInput(matrix.derived());
-      
+      grab(matrix.derived());
+
       factorize_impl();
     }
 
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** Prints the current UmfPack control settings.
+      *
+      * \sa umfpackControl()
+      */
+    void umfpackReportControl()
+    {
+      umfpack_report_control(m_control.data(), Scalar());
+    }
+
+    /** Prints statistics collected by UmfPack.
+      *
+      * \sa analyzePattern(), compute()
+      */
+    void umfpackReportInfo()
+    {
+      eigen_assert(m_analysisIsOk && "UmfPackLU: you must first call analyzePattern()");
+      umfpack_report_info(m_control.data(), m_umfpackInfo.data(), Scalar());
+    }
+
+    /** Prints the status of the previous factorization operation performed by UmfPack (symbolic or numerical factorization).
+      *
+      * \sa analyzePattern(), compute()
+      */
+    void umfpackReportStatus() {
+      eigen_assert(m_analysisIsOk && "UmfPackLU: you must first call analyzePattern()");
+      umfpack_report_status(m_control.data(), m_fact_errorCode, Scalar());
+    }
+
     /** \internal */
     template<typename BDerived,typename XDerived>
-    bool _solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const;
-    #endif
+    bool _solve_impl(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const;
 
     Scalar determinant() const;
 
     void extractData() const;
 
@@ -289,96 +358,79 @@
     {
       m_info                  = InvalidInput;
       m_isInitialized         = false;
       m_numeric               = 0;
       m_symbolic              = 0;
-      m_outerIndexPtr         = 0;
-      m_innerIndexPtr         = 0;
-      m_valuePtr              = 0;
-      m_extractedDataAreDirty = true;
-    }
-    
-    template<typename InputMatrixType>
-    void grapInput_impl(const InputMatrixType& mat, internal::true_type)
-    {
-      m_copyMatrix.resize(mat.rows(), mat.cols());
-      if( ((MatrixType::Flags&RowMajorBit)==RowMajorBit) || sizeof(typename MatrixType::Index)!=sizeof(int) || !mat.isCompressed() )
-      {
-        // non supported input -> copy
-        m_copyMatrix = mat;
-        m_outerIndexPtr = m_copyMatrix.outerIndexPtr();
-        m_innerIndexPtr = m_copyMatrix.innerIndexPtr();
-        m_valuePtr      = m_copyMatrix.valuePtr();
-      }
-      else
-      {
-        m_outerIndexPtr = mat.outerIndexPtr();
-        m_innerIndexPtr = mat.innerIndexPtr();
-        m_valuePtr      = mat.valuePtr();
-      }
-    }
-    
-    template<typename InputMatrixType>
-    void grapInput_impl(const InputMatrixType& mat, internal::false_type)
-    {
-      m_copyMatrix = mat;
-      m_outerIndexPtr = m_copyMatrix.outerIndexPtr();
-      m_innerIndexPtr = m_copyMatrix.innerIndexPtr();
-      m_valuePtr      = m_copyMatrix.valuePtr();
-    }
-    
-    template<typename InputMatrixType>
-    void grapInput(const InputMatrixType& mat)
-    {
-      grapInput_impl(mat, internal::umfpack_helper_is_sparse_plain<InputMatrixType>());
-    }
-    
+      m_extractedDataAreDirty = true;
+
+      umfpack_defaults(m_control.data(), Scalar());
+    }
+
     void analyzePattern_impl()
     {
-      int errorCode = 0;
-      errorCode = umfpack_symbolic(m_copyMatrix.rows(), m_copyMatrix.cols(), m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
-                                   &m_symbolic, 0, 0);
+      m_fact_errorCode = umfpack_symbolic(internal::convert_index<int>(mp_matrix.rows()),
+                                          internal::convert_index<int>(mp_matrix.cols()),
+                                          mp_matrix.outerIndexPtr(), mp_matrix.innerIndexPtr(), mp_matrix.valuePtr(),
+                                          &m_symbolic, m_control.data(), m_umfpackInfo.data());
 
       m_isInitialized = true;
-      m_info = errorCode ? InvalidInput : Success;
+      m_info = m_fact_errorCode ? InvalidInput : Success;
       m_analysisIsOk = true;
       m_factorizationIsOk = false;
       m_extractedDataAreDirty = true;
     }
-    
+
     void factorize_impl()
     {
-      int errorCode;
-      errorCode = umfpack_numeric(m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
-                                  m_symbolic, &m_numeric, 0, 0);
+
+      m_fact_errorCode = umfpack_numeric(mp_matrix.outerIndexPtr(), mp_matrix.innerIndexPtr(), mp_matrix.valuePtr(),
+                                         m_symbolic, &m_numeric, m_control.data(), m_umfpackInfo.data());
 
-      m_info = errorCode ? NumericalIssue : Success;
+      m_info = m_fact_errorCode == UMFPACK_OK ? Success : NumericalIssue;
       m_factorizationIsOk = true;
       m_extractedDataAreDirty = true;
     }
+
+    template<typename MatrixDerived>
+    void grab(const EigenBase<MatrixDerived> &A)
+    {
+      mp_matrix.~UmfpackMatrixRef();
+      ::new (&mp_matrix) UmfpackMatrixRef(A.derived());
+    }
+
+    void grab(const UmfpackMatrixRef &A)
+    {
+      if(&(A.derived()) != &mp_matrix)
+      {
+        mp_matrix.~UmfpackMatrixRef();
+        ::new (&mp_matrix) UmfpackMatrixRef(A);
+      }
+    }
 
     // cached data to reduce reallocation, etc.
     mutable LUMatrixType m_l;
+    int m_fact_errorCode;
+    UmfpackControl m_control;
+    mutable UmfpackInfo m_umfpackInfo;
+
     mutable LUMatrixType m_u;
     mutable IntColVectorType m_p;
     mutable IntRowVectorType m_q;
 
-    UmfpackMatrixType m_copyMatrix;
-    const Scalar* m_valuePtr;
-    const int* m_outerIndexPtr;
-    const int* m_innerIndexPtr;
+    UmfpackMatrixType m_dummy;
+    UmfpackMatrixRef mp_matrix;
+
     void* m_numeric;
     void* m_symbolic;
 
     mutable ComputationInfo m_info;
-    bool m_isInitialized;
     int m_factorizationIsOk;
     int m_analysisIsOk;
     mutable bool m_extractedDataAreDirty;
-    
+
   private:
-    UmfPackLU(UmfPackLU& ) { }
+    UmfPackLU(const UmfPackLU& ) { }
 };
 
 
 template<typename MatrixType>
 void UmfPackLU<MatrixType>::extractData() const
@@ -416,59 +468,39 @@
   return det;
 }
 
 template<typename MatrixType>
 template<typename BDerived,typename XDerived>
-bool UmfPackLU<MatrixType>::_solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const
+bool UmfPackLU<MatrixType>::_solve_impl(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const
 {
-  const int rhsCols = b.cols();
+  Index rhsCols = b.cols();
   eigen_assert((BDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major rhs yet");
   eigen_assert((XDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major result yet");
   eigen_assert(b.derived().data() != x.derived().data() && " Umfpack does not support inplace solve");
-  
+
   int errorCode;
+  Scalar* x_ptr = 0;
+  Matrix<Scalar,Dynamic,1> x_tmp;
+  if(x.innerStride()!=1)
+  {
+    x_tmp.resize(x.rows());
+    x_ptr = x_tmp.data();
+  }
   for (int j=0; j<rhsCols; ++j)
   {
+    if(x.innerStride()==1)
+      x_ptr = &x.col(j).coeffRef(0);
     errorCode = umfpack_solve(UMFPACK_A,
-        m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
-        &x.col(j).coeffRef(0), &b.const_cast_derived().col(j).coeffRef(0), m_numeric, 0, 0);
+        mp_matrix.outerIndexPtr(), mp_matrix.innerIndexPtr(), mp_matrix.valuePtr(),
+        x_ptr, &b.const_cast_derived().col(j).coeffRef(0), m_numeric, m_control.data(), m_umfpackInfo.data());
+    if(x.innerStride()!=1)
+      x.col(j) = x_tmp;
     if (errorCode!=0)
       return false;
   }
 
   return true;
 }
 
-
-namespace internal {
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<UmfPackLU<_MatrixType>, Rhs>
-  : solve_retval_base<UmfPackLU<_MatrixType>, Rhs>
-{
-  typedef UmfPackLU<_MatrixType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-template<typename _MatrixType, typename Rhs>
-struct sparse_solve_retval<UmfPackLU<_MatrixType>, Rhs>
-  : sparse_solve_retval_base<UmfPackLU<_MatrixType>, Rhs>
-{
-  typedef UmfPackLU<_MatrixType> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    this->defaultEvalTo(dst);
-  }
-};
-
-} // end namespace internal
-
 } // end namespace Eigen
 
 #endif // EIGEN_UMFPACKSUPPORT_H

DELETED 3rd_party/eigen/Eigen/src/misc/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/misc/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/misc/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_misc_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_misc_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/misc COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/misc/Image.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/Image.h
+++ 3rd_party/eigen/Eigen/src/misc/Image.h
@@ -36,11 +36,10 @@
  : public ReturnByValue<image_retval_base<_DecompositionType> >
 {
   typedef _DecompositionType DecompositionType;
   typedef typename DecompositionType::MatrixType MatrixType;
   typedef ReturnByValue<image_retval_base> Base;
-  typedef typename Base::Index Index;
 
   image_retval_base(const DecompositionType& dec, const MatrixType& originalMatrix)
     : m_dec(dec), m_rank(dec.rank()),
       m_cols(m_rank == 0 ? 1 : m_rank),
       m_originalMatrix(originalMatrix)
@@ -67,11 +66,10 @@
 
 #define EIGEN_MAKE_IMAGE_HELPERS(DecompositionType) \
   typedef typename DecompositionType::MatrixType MatrixType; \
   typedef typename MatrixType::Scalar Scalar; \
   typedef typename MatrixType::RealScalar RealScalar; \
-  typedef typename MatrixType::Index Index; \
   typedef Eigen::internal::image_retval_base<DecompositionType> Base; \
   using Base::dec; \
   using Base::originalMatrix; \
   using Base::rank; \
   using Base::rows; \

Index: 3rd_party/eigen/Eigen/src/misc/Kernel.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/Kernel.h
+++ 3rd_party/eigen/Eigen/src/misc/Kernel.h
@@ -37,13 +37,12 @@
 template<typename _DecompositionType> struct kernel_retval_base
  : public ReturnByValue<kernel_retval_base<_DecompositionType> >
 {
   typedef _DecompositionType DecompositionType;
   typedef ReturnByValue<kernel_retval_base> Base;
-  typedef typename Base::Index Index;
 
-  kernel_retval_base(const DecompositionType& dec)
+  explicit kernel_retval_base(const DecompositionType& dec)
     : m_dec(dec),
       m_rank(dec.rank()),
       m_cols(m_rank==dec.cols() ? 1 : dec.cols() - m_rank)
   {}
 
@@ -66,11 +65,10 @@
 
 #define EIGEN_MAKE_KERNEL_HELPERS(DecompositionType) \
   typedef typename DecompositionType::MatrixType MatrixType; \
   typedef typename MatrixType::Scalar Scalar; \
   typedef typename MatrixType::RealScalar RealScalar; \
-  typedef typename MatrixType::Index Index; \
   typedef Eigen::internal::kernel_retval_base<DecompositionType> Base; \
   using Base::dec; \
   using Base::rank; \
   using Base::rows; \
   using Base::cols; \

ADDED   3rd_party/eigen/Eigen/src/misc/RealSvd2x2.h
Index: 3rd_party/eigen/Eigen/src/misc/RealSvd2x2.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/RealSvd2x2.h
+++ 3rd_party/eigen/Eigen/src/misc/RealSvd2x2.h
@@ -0,0 +1,55 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2013-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_REALSVD2X2_H
+#define EIGEN_REALSVD2X2_H
+
+namespace Eigen {
+
+namespace internal {
+
+template<typename MatrixType, typename RealScalar, typename Index>
+void real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q,
+                         JacobiRotation<RealScalar> *j_left,
+                         JacobiRotation<RealScalar> *j_right)
+{
+  using std::sqrt;
+  using std::abs;
+  Matrix<RealScalar,2,2> m;
+  m << numext::real(matrix.coeff(p,p)), numext::real(matrix.coeff(p,q)),
+       numext::real(matrix.coeff(q,p)), numext::real(matrix.coeff(q,q));
+  JacobiRotation<RealScalar> rot1;
+  RealScalar t = m.coeff(0,0) + m.coeff(1,1);
+  RealScalar d = m.coeff(1,0) - m.coeff(0,1);
+
+  if(abs(d) < (std::numeric_limits<RealScalar>::min)())
+  {
+    rot1.s() = RealScalar(0);
+    rot1.c() = RealScalar(1);
+  }
+  else
+  {
+    // If d!=0, then t/d cannot overflow because the magnitude of the
+    // entries forming d are not too small compared to the ones forming t.
+    RealScalar u = t / d;
+    RealScalar tmp = sqrt(RealScalar(1) + numext::abs2(u));
+    rot1.s() = RealScalar(1) / tmp;
+    rot1.c() = u / tmp;
+  }
+  m.applyOnTheLeft(0,1,rot1);
+  j_right->makeJacobi(m,0,1);
+  *j_left = rot1 * j_right->transpose();
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_REALSVD2X2_H

DELETED 3rd_party/eigen/Eigen/src/misc/Solve.h
Index: 3rd_party/eigen/Eigen/src/misc/Solve.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/Solve.h
+++ 3rd_party/eigen/Eigen/src/misc/Solve.h
@@ -1,76 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_MISC_SOLVE_H
-#define EIGEN_MISC_SOLVE_H
-
-namespace Eigen { 
-
-namespace internal {
-
-/** \class solve_retval_base
-  *
-  */
-template<typename DecompositionType, typename Rhs>
-struct traits<solve_retval_base<DecompositionType, Rhs> >
-{
-  typedef typename DecompositionType::MatrixType MatrixType;
-  typedef Matrix<typename Rhs::Scalar,
-                 MatrixType::ColsAtCompileTime,
-                 Rhs::ColsAtCompileTime,
-                 Rhs::PlainObject::Options,
-                 MatrixType::MaxColsAtCompileTime,
-                 Rhs::MaxColsAtCompileTime> ReturnType;
-};
-
-template<typename _DecompositionType, typename Rhs> struct solve_retval_base
- : public ReturnByValue<solve_retval_base<_DecompositionType, Rhs> >
-{
-  typedef typename remove_all<typename Rhs::Nested>::type RhsNestedCleaned;
-  typedef _DecompositionType DecompositionType;
-  typedef ReturnByValue<solve_retval_base> Base;
-  typedef typename Base::Index Index;
-
-  solve_retval_base(const DecompositionType& dec, const Rhs& rhs)
-    : m_dec(dec), m_rhs(rhs)
-  {}
-
-  inline Index rows() const { return m_dec.cols(); }
-  inline Index cols() const { return m_rhs.cols(); }
-  inline const DecompositionType& dec() const { return m_dec; }
-  inline const RhsNestedCleaned& rhs() const { return m_rhs; }
-
-  template<typename Dest> inline void evalTo(Dest& dst) const
-  {
-    static_cast<const solve_retval<DecompositionType,Rhs>*>(this)->evalTo(dst);
-  }
-
-  protected:
-    const DecompositionType& m_dec;
-    typename Rhs::Nested m_rhs;
-};
-
-} // end namespace internal
-
-#define EIGEN_MAKE_SOLVE_HELPERS(DecompositionType,Rhs) \
-  typedef typename DecompositionType::MatrixType MatrixType; \
-  typedef typename MatrixType::Scalar Scalar; \
-  typedef typename MatrixType::RealScalar RealScalar; \
-  typedef typename MatrixType::Index Index; \
-  typedef Eigen::internal::solve_retval_base<DecompositionType,Rhs> Base; \
-  using Base::dec; \
-  using Base::rhs; \
-  using Base::rows; \
-  using Base::cols; \
-  solve_retval(const DecompositionType& dec, const Rhs& rhs) \
-    : Base(dec, rhs) {}
-
-} // end namespace Eigen
-
-#endif // EIGEN_MISC_SOLVE_H

DELETED 3rd_party/eigen/Eigen/src/misc/SparseSolve.h
Index: 3rd_party/eigen/Eigen/src/misc/SparseSolve.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/SparseSolve.h
+++ 3rd_party/eigen/Eigen/src/misc/SparseSolve.h
@@ -1,128 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPARSE_SOLVE_H
-#define EIGEN_SPARSE_SOLVE_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename _DecompositionType, typename Rhs> struct sparse_solve_retval_base;
-template<typename _DecompositionType, typename Rhs> struct sparse_solve_retval;
-  
-template<typename DecompositionType, typename Rhs>
-struct traits<sparse_solve_retval_base<DecompositionType, Rhs> >
-{
-  typedef typename DecompositionType::MatrixType MatrixType;
-  typedef SparseMatrix<typename Rhs::Scalar, Rhs::Options, typename Rhs::Index> ReturnType;
-};
-
-template<typename _DecompositionType, typename Rhs> struct sparse_solve_retval_base
- : public ReturnByValue<sparse_solve_retval_base<_DecompositionType, Rhs> >
-{
-  typedef typename remove_all<typename Rhs::Nested>::type RhsNestedCleaned;
-  typedef _DecompositionType DecompositionType;
-  typedef ReturnByValue<sparse_solve_retval_base> Base;
-  typedef typename Base::Index Index;
-
-  sparse_solve_retval_base(const DecompositionType& dec, const Rhs& rhs)
-    : m_dec(dec), m_rhs(rhs)
-  {}
-
-  inline Index rows() const { return m_dec.cols(); }
-  inline Index cols() const { return m_rhs.cols(); }
-  inline const DecompositionType& dec() const { return m_dec; }
-  inline const RhsNestedCleaned& rhs() const { return m_rhs; }
-
-  template<typename Dest> inline void evalTo(Dest& dst) const
-  {
-    static_cast<const sparse_solve_retval<DecompositionType,Rhs>*>(this)->evalTo(dst);
-  }
-
-  protected:
-    template<typename DestScalar, int DestOptions, typename DestIndex>
-    inline void defaultEvalTo(SparseMatrix<DestScalar,DestOptions,DestIndex>& dst) const
-    {
-      // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix.
-      static const int NbColsAtOnce = 4;
-      int rhsCols = m_rhs.cols();
-      int size = m_rhs.rows();
-      Eigen::Matrix<DestScalar,Dynamic,Dynamic> tmp(size,rhsCols);
-      Eigen::Matrix<DestScalar,Dynamic,Dynamic> tmpX(size,rhsCols);
-      for(int k=0; k<rhsCols; k+=NbColsAtOnce)
-      {
-        int actualCols = std::min<int>(rhsCols-k, NbColsAtOnce);
-        tmp.leftCols(actualCols) = m_rhs.middleCols(k,actualCols);
-        tmpX.leftCols(actualCols) = m_dec.solve(tmp.leftCols(actualCols));
-        dst.middleCols(k,actualCols) = tmpX.leftCols(actualCols).sparseView();
-      }
-    }
-    const DecompositionType& m_dec;
-    typename Rhs::Nested m_rhs;
-};
-
-#define EIGEN_MAKE_SPARSE_SOLVE_HELPERS(DecompositionType,Rhs) \
-  typedef typename DecompositionType::MatrixType MatrixType; \
-  typedef typename MatrixType::Scalar Scalar; \
-  typedef typename MatrixType::RealScalar RealScalar; \
-  typedef typename MatrixType::Index Index; \
-  typedef Eigen::internal::sparse_solve_retval_base<DecompositionType,Rhs> Base; \
-  using Base::dec; \
-  using Base::rhs; \
-  using Base::rows; \
-  using Base::cols; \
-  sparse_solve_retval(const DecompositionType& dec, const Rhs& rhs) \
-    : Base(dec, rhs) {}
-
-
-
-template<typename DecompositionType, typename Rhs, typename Guess> struct solve_retval_with_guess;
-
-template<typename DecompositionType, typename Rhs, typename Guess>
-struct traits<solve_retval_with_guess<DecompositionType, Rhs, Guess> >
-{
-  typedef typename DecompositionType::MatrixType MatrixType;
-  typedef Matrix<typename Rhs::Scalar,
-                 MatrixType::ColsAtCompileTime,
-                 Rhs::ColsAtCompileTime,
-                 Rhs::PlainObject::Options,
-                 MatrixType::MaxColsAtCompileTime,
-                 Rhs::MaxColsAtCompileTime> ReturnType;
-};
-
-template<typename DecompositionType, typename Rhs, typename Guess> struct solve_retval_with_guess
- : public ReturnByValue<solve_retval_with_guess<DecompositionType, Rhs, Guess> >
-{
-  typedef typename DecompositionType::Index Index;
-
-  solve_retval_with_guess(const DecompositionType& dec, const Rhs& rhs, const Guess& guess)
-    : m_dec(dec), m_rhs(rhs), m_guess(guess)
-  {}
-
-  inline Index rows() const { return m_dec.cols(); }
-  inline Index cols() const { return m_rhs.cols(); }
-
-  template<typename Dest> inline void evalTo(Dest& dst) const
-  {
-    dst = m_guess;
-    m_dec._solveWithGuess(m_rhs,dst);
-  }
-
-  protected:
-    const DecompositionType& m_dec;
-    const typename Rhs::Nested m_rhs;
-    const typename Guess::Nested m_guess;
-};
-
-} // namepsace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_SPARSE_SOLVE_H

Index: 3rd_party/eigen/Eigen/src/misc/blas.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/blas.h
+++ 3rd_party/eigen/Eigen/src/misc/blas.h
@@ -28,19 +28,19 @@
 int  BLASFUNC(cdotuw)  (int *, float  *, int *, float  *, int *, float*);
 int  BLASFUNC(cdotcw)  (int *, float  *, int *, float  *, int *, float*);
 int  BLASFUNC(zdotuw)  (int *, double  *, int *, double  *, int *, double*);
 int  BLASFUNC(zdotcw)  (int *, double  *, int *, double  *, int *, double*);
 
-int    BLASFUNC(saxpy) (int *, float  *, float  *, int *, float  *, int *);
-int    BLASFUNC(daxpy) (int *, double *, double *, int *, double *, int *);
-int    BLASFUNC(qaxpy) (int *, double *, double *, int *, double *, int *);
-int    BLASFUNC(caxpy) (int *, float  *, float  *, int *, float  *, int *);
-int    BLASFUNC(zaxpy) (int *, double *, double *, int *, double *, int *);
-int    BLASFUNC(xaxpy) (int *, double *, double *, int *, double *, int *);
-int    BLASFUNC(caxpyc)(int *, float  *, float  *, int *, float  *, int *);
-int    BLASFUNC(zaxpyc)(int *, double *, double *, int *, double *, int *);
-int    BLASFUNC(xaxpyc)(int *, double *, double *, int *, double *, int *);
+int    BLASFUNC(saxpy) (const int *, const float  *, const float  *, const int *, float  *, const int *);
+int    BLASFUNC(daxpy) (const int *, const double *, const double *, const int *, double *, const int *);
+int    BLASFUNC(qaxpy) (const int *, const double *, const double *, const int *, double *, const int *);
+int    BLASFUNC(caxpy) (const int *, const float  *, const float  *, const int *, float  *, const int *);
+int    BLASFUNC(zaxpy) (const int *, const double *, const double *, const int *, double *, const int *);
+int    BLASFUNC(xaxpy) (const int *, const double *, const double *, const int *, double *, const int *);
+int    BLASFUNC(caxpyc)(const int *, const float  *, const float  *, const int *, float  *, const int *);
+int    BLASFUNC(zaxpyc)(const int *, const double *, const double *, const int *, double *, const int *);
+int    BLASFUNC(xaxpyc)(const int *, const double *, const double *, const int *, double *, const int *);
 
 int    BLASFUNC(scopy) (int *, float  *, int *, float  *, int *);
 int    BLASFUNC(dcopy) (int *, double *, int *, double *, int *);
 int    BLASFUNC(qcopy) (int *, double *, int *, double *, int *);
 int    BLASFUNC(ccopy) (int *, float  *, int *, float  *, int *);
@@ -175,55 +175,37 @@
 int BLASFUNC(xgeru)(int *,    int *, double *, double *, int *,
 		    double *, int *, double *, int *);
 int BLASFUNC(xgerc)(int *,    int *, double *, double *, int *,
 		    double *, int *, double *, int *);
 
-int BLASFUNC(sgemv)(char *, int *, int *, float  *, float  *, int *,
-		    float  *, int *, float  *, float  *, int *);
-int BLASFUNC(dgemv)(char *, int *, int *, double *, double *, int *,
-		    double *, int *, double *, double *, int *);
-int BLASFUNC(qgemv)(char *, int *, int *, double *, double *, int *,
-		    double *, int *, double *, double *, int *);
-int BLASFUNC(cgemv)(char *, int *, int *, float  *, float  *, int *,
-		    float  *, int *, float  *, float  *, int *);
-int BLASFUNC(zgemv)(char *, int *, int *, double *, double *, int *,
-		    double *, int *, double *, double *, int *);
-int BLASFUNC(xgemv)(char *, int *, int *, double *, double *, int *,
-		    double *, int *, double *, double *, int *);
-
-int BLASFUNC(strsv) (char *, char *, char *, int *, float  *, int *,
-		     float  *, int *);
-int BLASFUNC(dtrsv) (char *, char *, char *, int *, double *, int *,
-		     double *, int *);
-int BLASFUNC(qtrsv) (char *, char *, char *, int *, double *, int *,
-		     double *, int *);
-int BLASFUNC(ctrsv) (char *, char *, char *, int *, float  *, int *,
-		     float  *, int *);
-int BLASFUNC(ztrsv) (char *, char *, char *, int *, double *, int *,
-		     double *, int *);
-int BLASFUNC(xtrsv) (char *, char *, char *, int *, double *, int *,
-		     double *, int *);
+int BLASFUNC(sgemv)(const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(dgemv)(const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(qgemv)(const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(cgemv)(const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zgemv)(const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xgemv)(const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+
+int BLASFUNC(strsv) (const char *, const char *, const char *, const int *, const float  *, const int *, float  *, const int *);
+int BLASFUNC(dtrsv) (const char *, const char *, const char *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(qtrsv) (const char *, const char *, const char *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(ctrsv) (const char *, const char *, const char *, const int *, const float  *, const int *, float  *, const int *);
+int BLASFUNC(ztrsv) (const char *, const char *, const char *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(xtrsv) (const char *, const char *, const char *, const int *, const double *, const int *, double *, const int *);
 
 int BLASFUNC(stpsv) (char *, char *, char *, int *, float  *, float  *, int *);
 int BLASFUNC(dtpsv) (char *, char *, char *, int *, double *, double *, int *);
 int BLASFUNC(qtpsv) (char *, char *, char *, int *, double *, double *, int *);
 int BLASFUNC(ctpsv) (char *, char *, char *, int *, float  *, float  *, int *);
 int BLASFUNC(ztpsv) (char *, char *, char *, int *, double *, double *, int *);
 int BLASFUNC(xtpsv) (char *, char *, char *, int *, double *, double *, int *);
 
-int BLASFUNC(strmv) (char *, char *, char *, int *, float  *, int *,
-		     float  *, int *);
-int BLASFUNC(dtrmv) (char *, char *, char *, int *, double *, int *,
-		     double *, int *);
-int BLASFUNC(qtrmv) (char *, char *, char *, int *, double *, int *,
-		     double *, int *);
-int BLASFUNC(ctrmv) (char *, char *, char *, int *, float  *, int *,
-		     float  *, int *);
-int BLASFUNC(ztrmv) (char *, char *, char *, int *, double *, int *,
-		     double *, int *);
-int BLASFUNC(xtrmv) (char *, char *, char *, int *, double *, int *,
-		     double *, int *);
+int BLASFUNC(strmv) (const char *, const char *, const char *, const int *, const float  *, const int *, float  *, const int *);
+int BLASFUNC(dtrmv) (const char *, const char *, const char *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(qtrmv) (const char *, const char *, const char *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(ctrmv) (const char *, const char *, const char *, const int *, const float  *, const int *, float  *, const int *);
+int BLASFUNC(ztrmv) (const char *, const char *, const char *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(xtrmv) (const char *, const char *, const char *, const int *, const double *, const int *, double *, const int *);
 
 int BLASFUNC(stpmv) (char *, char *, char *, int *, float  *, float  *, int *);
 int BLASFUNC(dtpmv) (char *, char *, char *, int *, double *, double *, int *);
 int BLASFUNC(qtpmv) (char *, char *, char *, int *, double *, double *, int *);
 int BLASFUNC(ctpmv) (char *, char *, char *, int *, float  *, float  *, int *);
@@ -242,74 +224,38 @@
 int BLASFUNC(qtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
 int BLASFUNC(ctbsv) (char *, char *, char *, int *, int *, float  *, int *, float  *, int *);
 int BLASFUNC(ztbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
 int BLASFUNC(xtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
 
-int BLASFUNC(ssymv) (char *, int *, float  *, float *, int *,
-		     float  *, int *, float *, float *, int *);
-int BLASFUNC(dsymv) (char *, int *, double  *, double *, int *,
-		     double  *, int *, double *, double *, int *);
-int BLASFUNC(qsymv) (char *, int *, double  *, double *, int *,
-		     double  *, int *, double *, double *, int *);
-int BLASFUNC(csymv) (char *, int *, float  *, float *, int *,
-		     float  *, int *, float *, float *, int *);
-int BLASFUNC(zsymv) (char *, int *, double  *, double *, int *,
-		     double  *, int *, double *, double *, int *);
-int BLASFUNC(xsymv) (char *, int *, double  *, double *, int *,
-		     double  *, int *, double *, double *, int *);
+int BLASFUNC(ssymv) (const char *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(dsymv) (const char *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(qsymv) (const char *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
 
 int BLASFUNC(sspmv) (char *, int *, float  *, float *,
 		     float  *, int *, float *, float *, int *);
 int BLASFUNC(dspmv) (char *, int *, double  *, double *,
 		     double  *, int *, double *, double *, int *);
 int BLASFUNC(qspmv) (char *, int *, double  *, double *,
 		     double  *, int *, double *, double *, int *);
-int BLASFUNC(cspmv) (char *, int *, float  *, float *,
-		     float  *, int *, float *, float *, int *);
-int BLASFUNC(zspmv) (char *, int *, double  *, double *,
-		     double  *, int *, double *, double *, int *);
-int BLASFUNC(xspmv) (char *, int *, double  *, double *,
-		     double  *, int *, double *, double *, int *);
-
-int BLASFUNC(ssyr) (char *, int *, float   *, float  *, int *,
-		    float  *, int *);
-int BLASFUNC(dsyr) (char *, int *, double  *, double *, int *,
-		    double *, int *);
-int BLASFUNC(qsyr) (char *, int *, double  *, double *, int *,
-		    double *, int *);
-int BLASFUNC(csyr) (char *, int *, float   *, float  *, int *,
-		    float  *, int *);
-int BLASFUNC(zsyr) (char *, int *, double  *, double *, int *,
-		    double *, int *);
-int BLASFUNC(xsyr) (char *, int *, double  *, double *, int *,
-		    double *, int *);
-
-int BLASFUNC(ssyr2) (char *, int *, float   *,
-		     float  *, int *, float  *, int *, float  *, int *);
-int BLASFUNC(dsyr2) (char *, int *, double  *,
-		     double *, int *, double *, int *, double *, int *);
-int BLASFUNC(qsyr2) (char *, int *, double  *,
-		     double *, int *, double *, int *, double *, int *);
-int BLASFUNC(csyr2) (char *, int *, float   *,
-		     float  *, int *, float  *, int *, float  *, int *);
-int BLASFUNC(zsyr2) (char *, int *, double  *,
-		     double *, int *, double *, int *, double *, int *);
-int BLASFUNC(xsyr2) (char *, int *, double  *,
-		     double *, int *, double *, int *, double *, int *);
+
+int BLASFUNC(ssyr) (const char *, const int *, const float   *, const float  *, const int *, float  *, const int *);
+int BLASFUNC(dsyr) (const char *, const int *, const double  *, const double *, const int *, double *, const int *);
+int BLASFUNC(qsyr) (const char *, const int *, const double  *, const double *, const int *, double *, const int *);
+
+int BLASFUNC(ssyr2) (const char *, const int *, const float   *, const float  *, const int *, const float  *, const int *, float  *, const int *);
+int BLASFUNC(dsyr2) (const char *, const int *, const double  *, const double *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(qsyr2) (const char *, const int *, const double  *, const double *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(csyr2) (const char *, const int *, const float   *, const float  *, const int *, const float  *, const int *, float  *, const int *);
+int BLASFUNC(zsyr2) (const char *, const int *, const double  *, const double *, const int *, const double *, const int *, double *, const int *);
+int BLASFUNC(xsyr2) (const char *, const int *, const double  *, const double *, const int *, const double *, const int *, double *, const int *);
 
 int BLASFUNC(sspr) (char *, int *, float   *, float  *, int *,
 		    float  *);
 int BLASFUNC(dspr) (char *, int *, double  *, double *, int *,
 		    double *);
 int BLASFUNC(qspr) (char *, int *, double  *, double *, int *,
 		    double *);
-int BLASFUNC(cspr) (char *, int *, float   *, float  *, int *,
-		    float  *);
-int BLASFUNC(zspr) (char *, int *, double  *, double *, int *,
-		    double *);
-int BLASFUNC(xspr) (char *, int *, double  *, double *, int *,
-		    double *);
 
 int BLASFUNC(sspr2) (char *, int *, float   *,
 		     float  *, int *, float  *, int *, float  *);
 int BLASFUNC(dspr2) (char *, int *, double  *,
 		     double *, int *, double *, int *, double *);
@@ -345,16 +291,13 @@
 int BLASFUNC(zhpr2) (char *, int *, double  *,
 		     double *, int *, double *, int *, double *);
 int BLASFUNC(xhpr2) (char *, int *, double  *,
 		     double *, int *, double *, int *, double *);
 
-int BLASFUNC(chemv) (char *, int *, float  *, float *, int *,
-		     float  *, int *, float *, float *, int *);
-int BLASFUNC(zhemv) (char *, int *, double  *, double *, int *,
-		     double  *, int *, double *, double *, int *);
-int BLASFUNC(xhemv) (char *, int *, double  *, double *, int *,
-		     double  *, int *, double *, double *, int *);
+int BLASFUNC(chemv) (const char *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zhemv) (const char *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xhemv) (const char *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
 
 int BLASFUNC(chpmv) (char *, int *, float  *, float *,
 		     float  *, int *, float *, float *, int *);
 int BLASFUNC(zhpmv) (char *, int *, double  *, double *,
 		     double  *, int *, double *, double *, int *);
@@ -399,22 +342,16 @@
 int BLASFUNC(xhbmv)(char *, int *, int *, double *, double *, int *,
 		    double *, int *, double *, double *, int *);
 
 /* Level 3 routines */
 
-int BLASFUNC(sgemm)(char *, char *, int *, int *, int *, float *,
-	   float  *, int *, float  *, int *, float  *, float  *, int *);
-int BLASFUNC(dgemm)(char *, char *, int *, int *, int *, double *,
-	   double *, int *, double *, int *, double *, double *, int *);
-int BLASFUNC(qgemm)(char *, char *, int *, int *, int *, double *,
-	   double *, int *, double *, int *, double *, double *, int *);
-int BLASFUNC(cgemm)(char *, char *, int *, int *, int *, float *,
-	   float  *, int *, float  *, int *, float  *, float  *, int *);
-int BLASFUNC(zgemm)(char *, char *, int *, int *, int *, double *,
-	   double *, int *, double *, int *, double *, double *, int *);
-int BLASFUNC(xgemm)(char *, char *, int *, int *, int *, double *,
-	   double *, int *, double *, int *, double *, double *, int *);
+int BLASFUNC(sgemm)(const char *, const char *, const int *, const int *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(dgemm)(const char *, const char *, const int *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(qgemm)(const char *, const char *, const int *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(cgemm)(const char *, const char *, const int *, const int *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zgemm)(const char *, const char *, const int *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xgemm)(const char *, const char *, const int *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
 
 int BLASFUNC(cgemm3m)(char *, char *, int *, int *, int *, float *,
 	   float  *, int *, float  *, int *, float  *, float  *, int *);
 int BLASFUNC(zgemm3m)(char *, char *, int *, int *, int *, double *,
 	   double *, int *, double *, int *, double *, double *, int *);
@@ -432,227 +369,72 @@
 		     float *, float  *, int *);
 int BLASFUNC(zge2mm)(char *, char *, char *, int *, int *,
 		     double *, double  *, int *, double  *, int *,
 		     double *, double  *, int *);
 
-int BLASFUNC(strsm)(char *, char *, char *, char *, int *, int *,
-	   float *,  float *, int *, float *, int *);
-int BLASFUNC(dtrsm)(char *, char *, char *, char *, int *, int *,
-	   double *,  double *, int *, double *, int *);
-int BLASFUNC(qtrsm)(char *, char *, char *, char *, int *, int *,
-	   double *,  double *, int *, double *, int *);
-int BLASFUNC(ctrsm)(char *, char *, char *, char *, int *, int *,
-	   float *,  float *, int *, float *, int *);
-int BLASFUNC(ztrsm)(char *, char *, char *, char *, int *, int *,
-	   double *,  double *, int *, double *, int *);
-int BLASFUNC(xtrsm)(char *, char *, char *, char *, int *, int *,
-	   double *,  double *, int *, double *, int *);
-
-int BLASFUNC(strmm)(char *, char *, char *, char *, int *, int *,
-	   float *,  float *, int *, float *, int *);
-int BLASFUNC(dtrmm)(char *, char *, char *, char *, int *, int *,
-	   double *,  double *, int *, double *, int *);
-int BLASFUNC(qtrmm)(char *, char *, char *, char *, int *, int *,
-	   double *,  double *, int *, double *, int *);
-int BLASFUNC(ctrmm)(char *, char *, char *, char *, int *, int *,
-	   float *,  float *, int *, float *, int *);
-int BLASFUNC(ztrmm)(char *, char *, char *, char *, int *, int *,
-	   double *,  double *, int *, double *, int *);
-int BLASFUNC(xtrmm)(char *, char *, char *, char *, int *, int *,
-	   double *,  double *, int *, double *, int *);
-
-int BLASFUNC(ssymm)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float  *, int *, float  *, float  *, int *);
-int BLASFUNC(dsymm)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, int *, double *, double *, int *);
-int BLASFUNC(qsymm)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, int *, double *, double *, int *);
-int BLASFUNC(csymm)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float  *, int *, float  *, float  *, int *);
-int BLASFUNC(zsymm)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, int *, double *, double *, int *);
-int BLASFUNC(xsymm)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, int *, double *, double *, int *);
-
-int BLASFUNC(csymm3m)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float  *, int *, float  *, float  *, int *);
-int BLASFUNC(zsymm3m)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, int *, double *, double *, int *);
-int BLASFUNC(xsymm3m)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, int *, double *, double *, int *);
-
-int BLASFUNC(ssyrk)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float  *, float  *, int *);
-int BLASFUNC(dsyrk)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, double *, int *);
-int BLASFUNC(qsyrk)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, double *, int *);
-int BLASFUNC(csyrk)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float  *, float  *, int *);
-int BLASFUNC(zsyrk)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, double *, int *);
-int BLASFUNC(xsyrk)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, double *, int *);
-
-int BLASFUNC(ssyr2k)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float *, int *, float  *, float  *, int *);
-int BLASFUNC(dsyr2k)(char *, char *, int *, int *, double *, double *, int *,
-	   double*, int *, double *, double *, int *);
-int BLASFUNC(qsyr2k)(char *, char *, int *, int *, double *, double *, int *,
-	   double*, int *, double *, double *, int *);
-int BLASFUNC(csyr2k)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float *, int *, float  *, float  *, int *);
-int BLASFUNC(zsyr2k)(char *, char *, int *, int *, double *, double *, int *,
-	   double*, int *, double *, double *, int *);
-int BLASFUNC(xsyr2k)(char *, char *, int *, int *, double *, double *, int *,
-	   double*, int *, double *, double *, int *);
-
-int BLASFUNC(chemm)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float  *, int *, float  *, float  *, int *);
-int BLASFUNC(zhemm)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, int *, double *, double *, int *);
-int BLASFUNC(xhemm)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, int *, double *, double *, int *);
+int BLASFUNC(strsm)(const char *, const char *, const char *, const char *, const int *, const int *, const float *,  const float *,  const int *, float *,  const int *);
+int BLASFUNC(dtrsm)(const char *, const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, double *, const int *);
+int BLASFUNC(qtrsm)(const char *, const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, double *, const int *);
+int BLASFUNC(ctrsm)(const char *, const char *, const char *, const char *, const int *, const int *, const float *,  const float *,  const int *, float *,  const int *);
+int BLASFUNC(ztrsm)(const char *, const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, double *, const int *);
+int BLASFUNC(xtrsm)(const char *, const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, double *, const int *);
+
+int BLASFUNC(strmm)(const char *, const char *, const char *, const char *, const int *, const int *, const float *,  const float *,  const int *, float *,  const int *);
+int BLASFUNC(dtrmm)(const char *, const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, double *, const int *);
+int BLASFUNC(qtrmm)(const char *, const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, double *, const int *);
+int BLASFUNC(ctrmm)(const char *, const char *, const char *, const char *, const int *, const int *, const float *,  const float *,  const int *, float *,  const int *);
+int BLASFUNC(ztrmm)(const char *, const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, double *, const int *);
+int BLASFUNC(xtrmm)(const char *, const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, double *, const int *);
+
+int BLASFUNC(ssymm)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(dsymm)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(qsymm)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(csymm)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zsymm)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xsymm)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+
+int BLASFUNC(csymm3m)(char *, char *, int *, int *, float  *, float  *, int *, float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zsymm3m)(char *, char *, int *, int *, double *, double *, int *, double *, int *, double *, double *, int *);
+int BLASFUNC(xsymm3m)(char *, char *, int *, int *, double *, double *, int *, double *, int *, double *, double *, int *);
+
+int BLASFUNC(ssyrk)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(dsyrk)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(qsyrk)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(csyrk)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zsyrk)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xsyrk)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, double *, const int *);
+
+int BLASFUNC(ssyr2k)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(dsyr2k)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double*, const int *, const double *, double *, const int *);
+int BLASFUNC(qsyr2k)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double*, const int *, const double *, double *, const int *);
+int BLASFUNC(csyr2k)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zsyr2k)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double*, const int *, const double *, double *, const int *);
+int BLASFUNC(xsyr2k)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double*, const int *, const double *, double *, const int *);
+
+int BLASFUNC(chemm)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zhemm)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xhemm)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
 
 int BLASFUNC(chemm3m)(char *, char *, int *, int *, float  *, float  *, int *,
 	   float  *, int *, float  *, float  *, int *);
 int BLASFUNC(zhemm3m)(char *, char *, int *, int *, double *, double *, int *,
 	   double *, int *, double *, double *, int *);
 int BLASFUNC(xhemm3m)(char *, char *, int *, int *, double *, double *, int *,
 	   double *, int *, double *, double *, int *);
 
-int BLASFUNC(cherk)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float  *, float  *, int *);
-int BLASFUNC(zherk)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, double *, int *);
-int BLASFUNC(xherk)(char *, char *, int *, int *, double *, double *, int *,
-	   double *, double *, int *);
-
-int BLASFUNC(cher2k)(char *, char *, int *, int *, float  *, float  *, int *,
-	   float *, int *, float  *, float  *, int *);
-int BLASFUNC(zher2k)(char *, char *, int *, int *, double *, double *, int *,
-	   double*, int *, double *, double *, int *);
-int BLASFUNC(xher2k)(char *, char *, int *, int *, double *, double *, int *,
-	   double*, int *, double *, double *, int *);
-int BLASFUNC(cher2m)(char *, char *, char *, int *, int *, float  *, float  *, int *,
-	   float *, int *, float  *, float  *, int *);
-int BLASFUNC(zher2m)(char *, char *, char *, int *, int *, double *, double *, int *,
-	   double*, int *, double *, double *, int *);
-int BLASFUNC(xher2m)(char *, char *, char *, int *, int *, double *, double *, int *,
-	   double*, int *, double *, double *, int *);
-
-int BLASFUNC(sgemt)(char *, int *, int *, float  *, float  *, int *,
-		    float  *, int *);
-int BLASFUNC(dgemt)(char *, int *, int *, double *, double *, int *,
-		    double *, int *);
-int BLASFUNC(cgemt)(char *, int *, int *, float  *, float  *, int *,
-		    float  *, int *);
-int BLASFUNC(zgemt)(char *, int *, int *, double *, double *, int *,
-		    double *, int *);
-
-int BLASFUNC(sgema)(char *, char *, int *, int *, float  *,
-		    float  *, int *, float *, float  *, int *, float *, int *);
-int BLASFUNC(dgema)(char *, char *, int *, int *, double *,
-		    double *, int *, double*, double *, int *, double*, int *);
-int BLASFUNC(cgema)(char *, char *, int *, int *, float  *,
-		    float  *, int *, float *, float  *, int *, float *, int *);
-int BLASFUNC(zgema)(char *, char *, int *, int *, double *,
-		    double *, int *, double*, double *, int *, double*, int *);
-
-int BLASFUNC(sgems)(char *, char *, int *, int *, float  *,
-		    float  *, int *, float *, float  *, int *, float *, int *);
-int BLASFUNC(dgems)(char *, char *, int *, int *, double *,
-		    double *, int *, double*, double *, int *, double*, int *);
-int BLASFUNC(cgems)(char *, char *, int *, int *, float  *,
-		    float  *, int *, float *, float  *, int *, float *, int *);
-int BLASFUNC(zgems)(char *, char *, int *, int *, double *,
-		    double *, int *, double*, double *, int *, double*, int *);
-
-int BLASFUNC(sgetf2)(int *, int *, float  *, int *, int *, int *);
-int BLASFUNC(dgetf2)(int *, int *, double *, int *, int *, int *);
-int BLASFUNC(qgetf2)(int *, int *, double *, int *, int *, int *);
-int BLASFUNC(cgetf2)(int *, int *, float  *, int *, int *, int *);
-int BLASFUNC(zgetf2)(int *, int *, double *, int *, int *, int *);
-int BLASFUNC(xgetf2)(int *, int *, double *, int *, int *, int *);
-
-int BLASFUNC(sgetrf)(int *, int *, float  *, int *, int *, int *);
-int BLASFUNC(dgetrf)(int *, int *, double *, int *, int *, int *);
-int BLASFUNC(qgetrf)(int *, int *, double *, int *, int *, int *);
-int BLASFUNC(cgetrf)(int *, int *, float  *, int *, int *, int *);
-int BLASFUNC(zgetrf)(int *, int *, double *, int *, int *, int *);
-int BLASFUNC(xgetrf)(int *, int *, double *, int *, int *, int *);
-
-int BLASFUNC(slaswp)(int *, float  *, int *, int *, int *, int *, int *);
-int BLASFUNC(dlaswp)(int *, double *, int *, int *, int *, int *, int *);
-int BLASFUNC(qlaswp)(int *, double *, int *, int *, int *, int *, int *);
-int BLASFUNC(claswp)(int *, float  *, int *, int *, int *, int *, int *);
-int BLASFUNC(zlaswp)(int *, double *, int *, int *, int *, int *, int *);
-int BLASFUNC(xlaswp)(int *, double *, int *, int *, int *, int *, int *);
-
-int BLASFUNC(sgetrs)(char *, int *, int *, float  *, int *, int *, float  *, int *, int *);
-int BLASFUNC(dgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
-int BLASFUNC(qgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
-int BLASFUNC(cgetrs)(char *, int *, int *, float  *, int *, int *, float  *, int *, int *);
-int BLASFUNC(zgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
-int BLASFUNC(xgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
-
-int BLASFUNC(sgesv)(int *, int *, float  *, int *, int *, float *, int *, int *);
-int BLASFUNC(dgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
-int BLASFUNC(qgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
-int BLASFUNC(cgesv)(int *, int *, float  *, int *, int *, float *, int *, int *);
-int BLASFUNC(zgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
-int BLASFUNC(xgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
-
-int BLASFUNC(spotf2)(char *, int *, float  *, int *, int *);
-int BLASFUNC(dpotf2)(char *, int *, double *, int *, int *);
-int BLASFUNC(qpotf2)(char *, int *, double *, int *, int *);
-int BLASFUNC(cpotf2)(char *, int *, float  *, int *, int *);
-int BLASFUNC(zpotf2)(char *, int *, double *, int *, int *);
-int BLASFUNC(xpotf2)(char *, int *, double *, int *, int *);
-
-int BLASFUNC(spotrf)(char *, int *, float  *, int *, int *);
-int BLASFUNC(dpotrf)(char *, int *, double *, int *, int *);
-int BLASFUNC(qpotrf)(char *, int *, double *, int *, int *);
-int BLASFUNC(cpotrf)(char *, int *, float  *, int *, int *);
-int BLASFUNC(zpotrf)(char *, int *, double *, int *, int *);
-int BLASFUNC(xpotrf)(char *, int *, double *, int *, int *);
-
-int BLASFUNC(slauu2)(char *, int *, float  *, int *, int *);
-int BLASFUNC(dlauu2)(char *, int *, double *, int *, int *);
-int BLASFUNC(qlauu2)(char *, int *, double *, int *, int *);
-int BLASFUNC(clauu2)(char *, int *, float  *, int *, int *);
-int BLASFUNC(zlauu2)(char *, int *, double *, int *, int *);
-int BLASFUNC(xlauu2)(char *, int *, double *, int *, int *);
-
-int BLASFUNC(slauum)(char *, int *, float  *, int *, int *);
-int BLASFUNC(dlauum)(char *, int *, double *, int *, int *);
-int BLASFUNC(qlauum)(char *, int *, double *, int *, int *);
-int BLASFUNC(clauum)(char *, int *, float  *, int *, int *);
-int BLASFUNC(zlauum)(char *, int *, double *, int *, int *);
-int BLASFUNC(xlauum)(char *, int *, double *, int *, int *);
-
-int BLASFUNC(strti2)(char *, char *, int *, float  *, int *, int *);
-int BLASFUNC(dtrti2)(char *, char *, int *, double *, int *, int *);
-int BLASFUNC(qtrti2)(char *, char *, int *, double *, int *, int *);
-int BLASFUNC(ctrti2)(char *, char *, int *, float  *, int *, int *);
-int BLASFUNC(ztrti2)(char *, char *, int *, double *, int *, int *);
-int BLASFUNC(xtrti2)(char *, char *, int *, double *, int *, int *);
-
-int BLASFUNC(strtri)(char *, char *, int *, float  *, int *, int *);
-int BLASFUNC(dtrtri)(char *, char *, int *, double *, int *, int *);
-int BLASFUNC(qtrtri)(char *, char *, int *, double *, int *, int *);
-int BLASFUNC(ctrtri)(char *, char *, int *, float  *, int *, int *);
-int BLASFUNC(ztrtri)(char *, char *, int *, double *, int *, int *);
-int BLASFUNC(xtrtri)(char *, char *, int *, double *, int *, int *);
-
-int BLASFUNC(spotri)(char *, int *, float  *, int *, int *);
-int BLASFUNC(dpotri)(char *, int *, double *, int *, int *);
-int BLASFUNC(qpotri)(char *, int *, double *, int *, int *);
-int BLASFUNC(cpotri)(char *, int *, float  *, int *, int *);
-int BLASFUNC(zpotri)(char *, int *, double *, int *, int *);
-int BLASFUNC(xpotri)(char *, int *, double *, int *, int *);
+int BLASFUNC(cherk)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zherk)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xherk)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, double *, const int *);
+
+int BLASFUNC(cher2k)(const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zher2k)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xher2k)(const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(cher2m)(const char *, const char *, const char *, const int *, const int *, const float  *, const float  *, const int *, const float *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zher2m)(const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double*, const int *, const double *, double *, const int *);
+int BLASFUNC(xher2m)(const char *, const char *, const char *, const int *, const int *, const double *, const double *, const int *, const double*, const int *, const double *, double *, const int *);
+
 
 #ifdef __cplusplus
 }
 #endif
 
 #endif

ADDED   3rd_party/eigen/Eigen/src/misc/lapack.h
Index: 3rd_party/eigen/Eigen/src/misc/lapack.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/lapack.h
+++ 3rd_party/eigen/Eigen/src/misc/lapack.h
@@ -0,0 +1,152 @@
+#ifndef LAPACK_H
+#define LAPACK_H
+
+#include "blas.h"
+
+#ifdef __cplusplus
+extern "C"
+{
+#endif
+
+int BLASFUNC(csymv) (const char *, const int *, const float  *, const float  *, const int *, const float  *, const int *, const float  *, float  *, const int *);
+int BLASFUNC(zsymv) (const char *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+int BLASFUNC(xsymv) (const char *, const int *, const double *, const double *, const int *, const double *, const int *, const double *, double *, const int *);
+
+
+int BLASFUNC(cspmv) (char *, int *, float  *, float *,
+         float  *, int *, float *, float *, int *);
+int BLASFUNC(zspmv) (char *, int *, double  *, double *,
+         double  *, int *, double *, double *, int *);
+int BLASFUNC(xspmv) (char *, int *, double  *, double *,
+         double  *, int *, double *, double *, int *);
+
+int BLASFUNC(csyr) (char *, int *, float   *, float  *, int *,
+        float  *, int *);
+int BLASFUNC(zsyr) (char *, int *, double  *, double *, int *,
+        double *, int *);
+int BLASFUNC(xsyr) (char *, int *, double  *, double *, int *,
+        double *, int *);
+
+int BLASFUNC(cspr) (char *, int *, float   *, float  *, int *,
+        float  *);
+int BLASFUNC(zspr) (char *, int *, double  *, double *, int *,
+        double *);
+int BLASFUNC(xspr) (char *, int *, double  *, double *, int *,
+        double *);
+
+int BLASFUNC(sgemt)(char *, int *, int *, float  *, float  *, int *,
+        float  *, int *);
+int BLASFUNC(dgemt)(char *, int *, int *, double *, double *, int *,
+        double *, int *);
+int BLASFUNC(cgemt)(char *, int *, int *, float  *, float  *, int *,
+        float  *, int *);
+int BLASFUNC(zgemt)(char *, int *, int *, double *, double *, int *,
+        double *, int *);
+
+int BLASFUNC(sgema)(char *, char *, int *, int *, float  *,
+        float  *, int *, float *, float  *, int *, float *, int *);
+int BLASFUNC(dgema)(char *, char *, int *, int *, double *,
+        double *, int *, double*, double *, int *, double*, int *);
+int BLASFUNC(cgema)(char *, char *, int *, int *, float  *,
+        float  *, int *, float *, float  *, int *, float *, int *);
+int BLASFUNC(zgema)(char *, char *, int *, int *, double *,
+        double *, int *, double*, double *, int *, double*, int *);
+
+int BLASFUNC(sgems)(char *, char *, int *, int *, float  *,
+        float  *, int *, float *, float  *, int *, float *, int *);
+int BLASFUNC(dgems)(char *, char *, int *, int *, double *,
+        double *, int *, double*, double *, int *, double*, int *);
+int BLASFUNC(cgems)(char *, char *, int *, int *, float  *,
+        float  *, int *, float *, float  *, int *, float *, int *);
+int BLASFUNC(zgems)(char *, char *, int *, int *, double *,
+        double *, int *, double*, double *, int *, double*, int *);
+
+int BLASFUNC(sgetf2)(int *, int *, float  *, int *, int *, int *);
+int BLASFUNC(dgetf2)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(qgetf2)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(cgetf2)(int *, int *, float  *, int *, int *, int *);
+int BLASFUNC(zgetf2)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(xgetf2)(int *, int *, double *, int *, int *, int *);
+
+int BLASFUNC(sgetrf)(int *, int *, float  *, int *, int *, int *);
+int BLASFUNC(dgetrf)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(qgetrf)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(cgetrf)(int *, int *, float  *, int *, int *, int *);
+int BLASFUNC(zgetrf)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(xgetrf)(int *, int *, double *, int *, int *, int *);
+
+int BLASFUNC(slaswp)(int *, float  *, int *, int *, int *, int *, int *);
+int BLASFUNC(dlaswp)(int *, double *, int *, int *, int *, int *, int *);
+int BLASFUNC(qlaswp)(int *, double *, int *, int *, int *, int *, int *);
+int BLASFUNC(claswp)(int *, float  *, int *, int *, int *, int *, int *);
+int BLASFUNC(zlaswp)(int *, double *, int *, int *, int *, int *, int *);
+int BLASFUNC(xlaswp)(int *, double *, int *, int *, int *, int *, int *);
+
+int BLASFUNC(sgetrs)(char *, int *, int *, float  *, int *, int *, float  *, int *, int *);
+int BLASFUNC(dgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
+int BLASFUNC(qgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
+int BLASFUNC(cgetrs)(char *, int *, int *, float  *, int *, int *, float  *, int *, int *);
+int BLASFUNC(zgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
+int BLASFUNC(xgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
+
+int BLASFUNC(sgesv)(int *, int *, float  *, int *, int *, float *, int *, int *);
+int BLASFUNC(dgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
+int BLASFUNC(qgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
+int BLASFUNC(cgesv)(int *, int *, float  *, int *, int *, float *, int *, int *);
+int BLASFUNC(zgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
+int BLASFUNC(xgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
+
+int BLASFUNC(spotf2)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dpotf2)(char *, int *, double *, int *, int *);
+int BLASFUNC(qpotf2)(char *, int *, double *, int *, int *);
+int BLASFUNC(cpotf2)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zpotf2)(char *, int *, double *, int *, int *);
+int BLASFUNC(xpotf2)(char *, int *, double *, int *, int *);
+
+int BLASFUNC(spotrf)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dpotrf)(char *, int *, double *, int *, int *);
+int BLASFUNC(qpotrf)(char *, int *, double *, int *, int *);
+int BLASFUNC(cpotrf)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zpotrf)(char *, int *, double *, int *, int *);
+int BLASFUNC(xpotrf)(char *, int *, double *, int *, int *);
+
+int BLASFUNC(slauu2)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dlauu2)(char *, int *, double *, int *, int *);
+int BLASFUNC(qlauu2)(char *, int *, double *, int *, int *);
+int BLASFUNC(clauu2)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zlauu2)(char *, int *, double *, int *, int *);
+int BLASFUNC(xlauu2)(char *, int *, double *, int *, int *);
+
+int BLASFUNC(slauum)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dlauum)(char *, int *, double *, int *, int *);
+int BLASFUNC(qlauum)(char *, int *, double *, int *, int *);
+int BLASFUNC(clauum)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zlauum)(char *, int *, double *, int *, int *);
+int BLASFUNC(xlauum)(char *, int *, double *, int *, int *);
+
+int BLASFUNC(strti2)(char *, char *, int *, float  *, int *, int *);
+int BLASFUNC(dtrti2)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(qtrti2)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(ctrti2)(char *, char *, int *, float  *, int *, int *);
+int BLASFUNC(ztrti2)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(xtrti2)(char *, char *, int *, double *, int *, int *);
+
+int BLASFUNC(strtri)(char *, char *, int *, float  *, int *, int *);
+int BLASFUNC(dtrtri)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(qtrtri)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(ctrtri)(char *, char *, int *, float  *, int *, int *);
+int BLASFUNC(ztrtri)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(xtrtri)(char *, char *, int *, double *, int *, int *);
+
+int BLASFUNC(spotri)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dpotri)(char *, int *, double *, int *, int *);
+int BLASFUNC(qpotri)(char *, int *, double *, int *, int *);
+int BLASFUNC(cpotri)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zpotri)(char *, int *, double *, int *, int *);
+int BLASFUNC(xpotri)(char *, int *, double *, int *, int *);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif

ADDED   3rd_party/eigen/Eigen/src/misc/lapacke.h
Index: 3rd_party/eigen/Eigen/src/misc/lapacke.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/lapacke.h
+++ 3rd_party/eigen/Eigen/src/misc/lapacke.h
@@ -0,0 +1,16291 @@
+/*****************************************************************************
+  Copyright (c) 2010, Intel Corp.
+  All rights reserved.
+
+  Redistribution and use in source and binary forms, with or without
+  modification, are permitted provided that the following conditions are met:
+
+    * Redistributions of source code must retain the above copyright notice,
+      this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in the
+      documentation and/or other materials provided with the distribution.
+    * Neither the name of Intel Corporation nor the names of its contributors
+      may be used to endorse or promote products derived from this software
+      without specific prior written permission.
+
+  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+  AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+  IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+  ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+  LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+  CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+  SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+  INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+  CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+  ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+  THE POSSIBILITY OF SUCH DAMAGE.
+******************************************************************************
+* Contents: Native C interface to LAPACK
+* Author: Intel Corporation
+* Generated November, 2011
+*****************************************************************************/
+
+#ifndef _MKL_LAPACKE_H_
+
+#ifndef _LAPACKE_H_
+#define _LAPACKE_H_
+
+/*
+*  Turn on HAVE_LAPACK_CONFIG_H to redefine C-LAPACK datatypes
+*/
+#ifdef HAVE_LAPACK_CONFIG_H
+#include "lapacke_config.h"
+#endif
+
+#ifdef __cplusplus
+extern "C" {
+#endif /* __cplusplus */
+
+#include <stdlib.h>
+
+#ifndef lapack_int
+#define lapack_int     int
+#endif
+
+#ifndef lapack_logical
+#define lapack_logical lapack_int
+#endif
+
+/* Complex types are structures equivalent to the
+* Fortran complex types COMPLEX(4) and COMPLEX(8).
+*
+* One can also redefine the types with his own types
+* for example by including in the code definitions like
+*
+* #define lapack_complex_float std::complex<float>
+* #define lapack_complex_double std::complex<double>
+*
+* or define these types in the command line:
+*
+* -Dlapack_complex_float="std::complex<float>"
+* -Dlapack_complex_double="std::complex<double>"
+*/
+
+#ifndef LAPACK_COMPLEX_CUSTOM
+
+/* Complex type (single precision) */
+#ifndef lapack_complex_float
+#include <complex.h>
+#define lapack_complex_float    float _Complex
+#endif
+
+#ifndef lapack_complex_float_real
+#define lapack_complex_float_real(z)       (creal(z))
+#endif
+
+#ifndef lapack_complex_float_imag
+#define lapack_complex_float_imag(z)       (cimag(z))
+#endif
+
+lapack_complex_float lapack_make_complex_float( float re, float im );
+
+/* Complex type (double precision) */
+#ifndef lapack_complex_double
+#include <complex.h>
+#define lapack_complex_double   double _Complex
+#endif
+
+#ifndef lapack_complex_double_real
+#define lapack_complex_double_real(z)      (creal(z))
+#endif
+
+#ifndef lapack_complex_double_imag
+#define lapack_complex_double_imag(z)       (cimag(z))
+#endif
+
+lapack_complex_double lapack_make_complex_double( double re, double im );
+
+#endif
+
+#ifndef LAPACKE_malloc
+#define LAPACKE_malloc( size ) malloc( size )
+#endif
+#ifndef LAPACKE_free
+#define LAPACKE_free( p )      free( p )
+#endif
+
+#define LAPACK_C2INT( x ) (lapack_int)(*((float*)&x ))
+#define LAPACK_Z2INT( x ) (lapack_int)(*((double*)&x ))
+
+#define LAPACK_ROW_MAJOR               101
+#define LAPACK_COL_MAJOR               102
+
+#define LAPACK_WORK_MEMORY_ERROR       -1010
+#define LAPACK_TRANSPOSE_MEMORY_ERROR  -1011
+
+/* Callback logical functions of one, two, or three arguments are used
+*  to select eigenvalues to sort to the top left of the Schur form.
+*  The value is selected if function returns TRUE (non-zero). */
+
+typedef lapack_logical (*LAPACK_S_SELECT2) ( const float*, const float* );
+typedef lapack_logical (*LAPACK_S_SELECT3)
+    ( const float*, const float*, const float* );
+typedef lapack_logical (*LAPACK_D_SELECT2) ( const double*, const double* );
+typedef lapack_logical (*LAPACK_D_SELECT3)
+    ( const double*, const double*, const double* );
+
+typedef lapack_logical (*LAPACK_C_SELECT1) ( const lapack_complex_float* );
+typedef lapack_logical (*LAPACK_C_SELECT2)
+    ( const lapack_complex_float*, const lapack_complex_float* );
+typedef lapack_logical (*LAPACK_Z_SELECT1) ( const lapack_complex_double* );
+typedef lapack_logical (*LAPACK_Z_SELECT2)
+    ( const lapack_complex_double*, const lapack_complex_double* );
+
+#include "lapacke_mangling.h"
+
+#define LAPACK_lsame LAPACK_GLOBAL(lsame,LSAME)
+lapack_logical LAPACK_lsame( char* ca,  char* cb,
+                              lapack_int lca, lapack_int lcb );
+
+/* C-LAPACK function prototypes */
+
+lapack_int LAPACKE_sbdsdc( int matrix_order, char uplo, char compq,
+                           lapack_int n, float* d, float* e, float* u,
+                           lapack_int ldu, float* vt, lapack_int ldvt, float* q,
+                           lapack_int* iq );
+lapack_int LAPACKE_dbdsdc( int matrix_order, char uplo, char compq,
+                           lapack_int n, double* d, double* e, double* u,
+                           lapack_int ldu, double* vt, lapack_int ldvt,
+                           double* q, lapack_int* iq );
+
+lapack_int LAPACKE_sbdsqr( int matrix_order, char uplo, lapack_int n,
+                           lapack_int ncvt, lapack_int nru, lapack_int ncc,
+                           float* d, float* e, float* vt, lapack_int ldvt,
+                           float* u, lapack_int ldu, float* c, lapack_int ldc );
+lapack_int LAPACKE_dbdsqr( int matrix_order, char uplo, lapack_int n,
+                           lapack_int ncvt, lapack_int nru, lapack_int ncc,
+                           double* d, double* e, double* vt, lapack_int ldvt,
+                           double* u, lapack_int ldu, double* c,
+                           lapack_int ldc );
+lapack_int LAPACKE_cbdsqr( int matrix_order, char uplo, lapack_int n,
+                           lapack_int ncvt, lapack_int nru, lapack_int ncc,
+                           float* d, float* e, lapack_complex_float* vt,
+                           lapack_int ldvt, lapack_complex_float* u,
+                           lapack_int ldu, lapack_complex_float* c,
+                           lapack_int ldc );
+lapack_int LAPACKE_zbdsqr( int matrix_order, char uplo, lapack_int n,
+                           lapack_int ncvt, lapack_int nru, lapack_int ncc,
+                           double* d, double* e, lapack_complex_double* vt,
+                           lapack_int ldvt, lapack_complex_double* u,
+                           lapack_int ldu, lapack_complex_double* c,
+                           lapack_int ldc );
+
+lapack_int LAPACKE_sdisna( char job, lapack_int m, lapack_int n, const float* d,
+                           float* sep );
+lapack_int LAPACKE_ddisna( char job, lapack_int m, lapack_int n,
+                           const double* d, double* sep );
+
+lapack_int LAPACKE_sgbbrd( int matrix_order, char vect, lapack_int m,
+                           lapack_int n, lapack_int ncc, lapack_int kl,
+                           lapack_int ku, float* ab, lapack_int ldab, float* d,
+                           float* e, float* q, lapack_int ldq, float* pt,
+                           lapack_int ldpt, float* c, lapack_int ldc );
+lapack_int LAPACKE_dgbbrd( int matrix_order, char vect, lapack_int m,
+                           lapack_int n, lapack_int ncc, lapack_int kl,
+                           lapack_int ku, double* ab, lapack_int ldab,
+                           double* d, double* e, double* q, lapack_int ldq,
+                           double* pt, lapack_int ldpt, double* c,
+                           lapack_int ldc );
+lapack_int LAPACKE_cgbbrd( int matrix_order, char vect, lapack_int m,
+                           lapack_int n, lapack_int ncc, lapack_int kl,
+                           lapack_int ku, lapack_complex_float* ab,
+                           lapack_int ldab, float* d, float* e,
+                           lapack_complex_float* q, lapack_int ldq,
+                           lapack_complex_float* pt, lapack_int ldpt,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zgbbrd( int matrix_order, char vect, lapack_int m,
+                           lapack_int n, lapack_int ncc, lapack_int kl,
+                           lapack_int ku, lapack_complex_double* ab,
+                           lapack_int ldab, double* d, double* e,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_complex_double* pt, lapack_int ldpt,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sgbcon( int matrix_order, char norm, lapack_int n,
+                           lapack_int kl, lapack_int ku, const float* ab,
+                           lapack_int ldab, const lapack_int* ipiv, float anorm,
+                           float* rcond );
+lapack_int LAPACKE_dgbcon( int matrix_order, char norm, lapack_int n,
+                           lapack_int kl, lapack_int ku, const double* ab,
+                           lapack_int ldab, const lapack_int* ipiv,
+                           double anorm, double* rcond );
+lapack_int LAPACKE_cgbcon( int matrix_order, char norm, lapack_int n,
+                           lapack_int kl, lapack_int ku,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           const lapack_int* ipiv, float anorm, float* rcond );
+lapack_int LAPACKE_zgbcon( int matrix_order, char norm, lapack_int n,
+                           lapack_int kl, lapack_int ku,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           const lapack_int* ipiv, double anorm,
+                           double* rcond );
+
+lapack_int LAPACKE_sgbequ( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku, const float* ab,
+                           lapack_int ldab, float* r, float* c, float* rowcnd,
+                           float* colcnd, float* amax );
+lapack_int LAPACKE_dgbequ( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku, const double* ab,
+                           lapack_int ldab, double* r, double* c,
+                           double* rowcnd, double* colcnd, double* amax );
+lapack_int LAPACKE_cgbequ( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           float* r, float* c, float* rowcnd, float* colcnd,
+                           float* amax );
+lapack_int LAPACKE_zgbequ( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           double* r, double* c, double* rowcnd, double* colcnd,
+                           double* amax );
+
+lapack_int LAPACKE_sgbequb( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_int kl, lapack_int ku, const float* ab,
+                            lapack_int ldab, float* r, float* c, float* rowcnd,
+                            float* colcnd, float* amax );
+lapack_int LAPACKE_dgbequb( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_int kl, lapack_int ku, const double* ab,
+                            lapack_int ldab, double* r, double* c,
+                            double* rowcnd, double* colcnd, double* amax );
+lapack_int LAPACKE_cgbequb( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_int kl, lapack_int ku,
+                            const lapack_complex_float* ab, lapack_int ldab,
+                            float* r, float* c, float* rowcnd, float* colcnd,
+                            float* amax );
+lapack_int LAPACKE_zgbequb( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_int kl, lapack_int ku,
+                            const lapack_complex_double* ab, lapack_int ldab,
+                            double* r, double* c, double* rowcnd,
+                            double* colcnd, double* amax );
+
+lapack_int LAPACKE_sgbrfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int kl, lapack_int ku, lapack_int nrhs,
+                           const float* ab, lapack_int ldab, const float* afb,
+                           lapack_int ldafb, const lapack_int* ipiv,
+                           const float* b, lapack_int ldb, float* x,
+                           lapack_int ldx, float* ferr, float* berr );
+lapack_int LAPACKE_dgbrfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int kl, lapack_int ku, lapack_int nrhs,
+                           const double* ab, lapack_int ldab, const double* afb,
+                           lapack_int ldafb, const lapack_int* ipiv,
+                           const double* b, lapack_int ldb, double* x,
+                           lapack_int ldx, double* ferr, double* berr );
+lapack_int LAPACKE_cgbrfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int kl, lapack_int ku, lapack_int nrhs,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           const lapack_complex_float* afb, lapack_int ldafb,
+                           const lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zgbrfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int kl, lapack_int ku, lapack_int nrhs,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           const lapack_complex_double* afb, lapack_int ldafb,
+                           const lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_sgbrfsx( int matrix_order, char trans, char equed,
+                            lapack_int n, lapack_int kl, lapack_int ku,
+                            lapack_int nrhs, const float* ab, lapack_int ldab,
+                            const float* afb, lapack_int ldafb,
+                            const lapack_int* ipiv, const float* r,
+                            const float* c, const float* b, lapack_int ldb,
+                            float* x, lapack_int ldx, float* rcond, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_dgbrfsx( int matrix_order, char trans, char equed,
+                            lapack_int n, lapack_int kl, lapack_int ku,
+                            lapack_int nrhs, const double* ab, lapack_int ldab,
+                            const double* afb, lapack_int ldafb,
+                            const lapack_int* ipiv, const double* r,
+                            const double* c, const double* b, lapack_int ldb,
+                            double* x, lapack_int ldx, double* rcond,
+                            double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+lapack_int LAPACKE_cgbrfsx( int matrix_order, char trans, char equed,
+                            lapack_int n, lapack_int kl, lapack_int ku,
+                            lapack_int nrhs, const lapack_complex_float* ab,
+                            lapack_int ldab, const lapack_complex_float* afb,
+                            lapack_int ldafb, const lapack_int* ipiv,
+                            const float* r, const float* c,
+                            const lapack_complex_float* b, lapack_int ldb,
+                            lapack_complex_float* x, lapack_int ldx,
+                            float* rcond, float* berr, lapack_int n_err_bnds,
+                            float* err_bnds_norm, float* err_bnds_comp,
+                            lapack_int nparams, float* params );
+lapack_int LAPACKE_zgbrfsx( int matrix_order, char trans, char equed,
+                            lapack_int n, lapack_int kl, lapack_int ku,
+                            lapack_int nrhs, const lapack_complex_double* ab,
+                            lapack_int ldab, const lapack_complex_double* afb,
+                            lapack_int ldafb, const lapack_int* ipiv,
+                            const double* r, const double* c,
+                            const lapack_complex_double* b, lapack_int ldb,
+                            lapack_complex_double* x, lapack_int ldx,
+                            double* rcond, double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+
+lapack_int LAPACKE_sgbsv( int matrix_order, lapack_int n, lapack_int kl,
+                          lapack_int ku, lapack_int nrhs, float* ab,
+                          lapack_int ldab, lapack_int* ipiv, float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_dgbsv( int matrix_order, lapack_int n, lapack_int kl,
+                          lapack_int ku, lapack_int nrhs, double* ab,
+                          lapack_int ldab, lapack_int* ipiv, double* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_cgbsv( int matrix_order, lapack_int n, lapack_int kl,
+                          lapack_int ku, lapack_int nrhs,
+                          lapack_complex_float* ab, lapack_int ldab,
+                          lapack_int* ipiv, lapack_complex_float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_zgbsv( int matrix_order, lapack_int n, lapack_int kl,
+                          lapack_int ku, lapack_int nrhs,
+                          lapack_complex_double* ab, lapack_int ldab,
+                          lapack_int* ipiv, lapack_complex_double* b,
+                          lapack_int ldb );
+
+lapack_int LAPACKE_sgbsvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int kl, lapack_int ku,
+                           lapack_int nrhs, float* ab, lapack_int ldab,
+                           float* afb, lapack_int ldafb, lapack_int* ipiv,
+                           char* equed, float* r, float* c, float* b,
+                           lapack_int ldb, float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr,
+                           float* rpivot );
+lapack_int LAPACKE_dgbsvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int kl, lapack_int ku,
+                           lapack_int nrhs, double* ab, lapack_int ldab,
+                           double* afb, lapack_int ldafb, lapack_int* ipiv,
+                           char* equed, double* r, double* c, double* b,
+                           lapack_int ldb, double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr,
+                           double* rpivot );
+lapack_int LAPACKE_cgbsvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int kl, lapack_int ku,
+                           lapack_int nrhs, lapack_complex_float* ab,
+                           lapack_int ldab, lapack_complex_float* afb,
+                           lapack_int ldafb, lapack_int* ipiv, char* equed,
+                           float* r, float* c, lapack_complex_float* b,
+                           lapack_int ldb, lapack_complex_float* x,
+                           lapack_int ldx, float* rcond, float* ferr,
+                           float* berr, float* rpivot );
+lapack_int LAPACKE_zgbsvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int kl, lapack_int ku,
+                           lapack_int nrhs, lapack_complex_double* ab,
+                           lapack_int ldab, lapack_complex_double* afb,
+                           lapack_int ldafb, lapack_int* ipiv, char* equed,
+                           double* r, double* c, lapack_complex_double* b,
+                           lapack_int ldb, lapack_complex_double* x,
+                           lapack_int ldx, double* rcond, double* ferr,
+                           double* berr, double* rpivot );
+
+lapack_int LAPACKE_sgbsvxx( int matrix_order, char fact, char trans,
+                            lapack_int n, lapack_int kl, lapack_int ku,
+                            lapack_int nrhs, float* ab, lapack_int ldab,
+                            float* afb, lapack_int ldafb, lapack_int* ipiv,
+                            char* equed, float* r, float* c, float* b,
+                            lapack_int ldb, float* x, lapack_int ldx,
+                            float* rcond, float* rpvgrw, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_dgbsvxx( int matrix_order, char fact, char trans,
+                            lapack_int n, lapack_int kl, lapack_int ku,
+                            lapack_int nrhs, double* ab, lapack_int ldab,
+                            double* afb, lapack_int ldafb, lapack_int* ipiv,
+                            char* equed, double* r, double* c, double* b,
+                            lapack_int ldb, double* x, lapack_int ldx,
+                            double* rcond, double* rpvgrw, double* berr,
+                            lapack_int n_err_bnds, double* err_bnds_norm,
+                            double* err_bnds_comp, lapack_int nparams,
+                            double* params );
+lapack_int LAPACKE_cgbsvxx( int matrix_order, char fact, char trans,
+                            lapack_int n, lapack_int kl, lapack_int ku,
+                            lapack_int nrhs, lapack_complex_float* ab,
+                            lapack_int ldab, lapack_complex_float* afb,
+                            lapack_int ldafb, lapack_int* ipiv, char* equed,
+                            float* r, float* c, lapack_complex_float* b,
+                            lapack_int ldb, lapack_complex_float* x,
+                            lapack_int ldx, float* rcond, float* rpvgrw,
+                            float* berr, lapack_int n_err_bnds,
+                            float* err_bnds_norm, float* err_bnds_comp,
+                            lapack_int nparams, float* params );
+lapack_int LAPACKE_zgbsvxx( int matrix_order, char fact, char trans,
+                            lapack_int n, lapack_int kl, lapack_int ku,
+                            lapack_int nrhs, lapack_complex_double* ab,
+                            lapack_int ldab, lapack_complex_double* afb,
+                            lapack_int ldafb, lapack_int* ipiv, char* equed,
+                            double* r, double* c, lapack_complex_double* b,
+                            lapack_int ldb, lapack_complex_double* x,
+                            lapack_int ldx, double* rcond, double* rpvgrw,
+                            double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+
+lapack_int LAPACKE_sgbtrf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku, float* ab,
+                           lapack_int ldab, lapack_int* ipiv );
+lapack_int LAPACKE_dgbtrf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku, double* ab,
+                           lapack_int ldab, lapack_int* ipiv );
+lapack_int LAPACKE_cgbtrf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku,
+                           lapack_complex_float* ab, lapack_int ldab,
+                           lapack_int* ipiv );
+lapack_int LAPACKE_zgbtrf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku,
+                           lapack_complex_double* ab, lapack_int ldab,
+                           lapack_int* ipiv );
+
+lapack_int LAPACKE_sgbtrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int kl, lapack_int ku, lapack_int nrhs,
+                           const float* ab, lapack_int ldab,
+                           const lapack_int* ipiv, float* b, lapack_int ldb );
+lapack_int LAPACKE_dgbtrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int kl, lapack_int ku, lapack_int nrhs,
+                           const double* ab, lapack_int ldab,
+                           const lapack_int* ipiv, double* b, lapack_int ldb );
+lapack_int LAPACKE_cgbtrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int kl, lapack_int ku, lapack_int nrhs,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           const lapack_int* ipiv, lapack_complex_float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_zgbtrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int kl, lapack_int ku, lapack_int nrhs,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           const lapack_int* ipiv, lapack_complex_double* b,
+                           lapack_int ldb );
+
+lapack_int LAPACKE_sgebak( int matrix_order, char job, char side, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, const float* scale,
+                           lapack_int m, float* v, lapack_int ldv );
+lapack_int LAPACKE_dgebak( int matrix_order, char job, char side, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, const double* scale,
+                           lapack_int m, double* v, lapack_int ldv );
+lapack_int LAPACKE_cgebak( int matrix_order, char job, char side, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, const float* scale,
+                           lapack_int m, lapack_complex_float* v,
+                           lapack_int ldv );
+lapack_int LAPACKE_zgebak( int matrix_order, char job, char side, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, const double* scale,
+                           lapack_int m, lapack_complex_double* v,
+                           lapack_int ldv );
+
+lapack_int LAPACKE_sgebal( int matrix_order, char job, lapack_int n, float* a,
+                           lapack_int lda, lapack_int* ilo, lapack_int* ihi,
+                           float* scale );
+lapack_int LAPACKE_dgebal( int matrix_order, char job, lapack_int n, double* a,
+                           lapack_int lda, lapack_int* ilo, lapack_int* ihi,
+                           double* scale );
+lapack_int LAPACKE_cgebal( int matrix_order, char job, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* ilo, lapack_int* ihi, float* scale );
+lapack_int LAPACKE_zgebal( int matrix_order, char job, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* ilo, lapack_int* ihi, double* scale );
+
+lapack_int LAPACKE_sgebrd( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, float* d, float* e,
+                           float* tauq, float* taup );
+lapack_int LAPACKE_dgebrd( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, double* d, double* e,
+                           double* tauq, double* taup );
+lapack_int LAPACKE_cgebrd( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda, float* d,
+                           float* e, lapack_complex_float* tauq,
+                           lapack_complex_float* taup );
+lapack_int LAPACKE_zgebrd( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda, double* d,
+                           double* e, lapack_complex_double* tauq,
+                           lapack_complex_double* taup );
+
+lapack_int LAPACKE_sgecon( int matrix_order, char norm, lapack_int n,
+                           const float* a, lapack_int lda, float anorm,
+                           float* rcond );
+lapack_int LAPACKE_dgecon( int matrix_order, char norm, lapack_int n,
+                           const double* a, lapack_int lda, double anorm,
+                           double* rcond );
+lapack_int LAPACKE_cgecon( int matrix_order, char norm, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           float anorm, float* rcond );
+lapack_int LAPACKE_zgecon( int matrix_order, char norm, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           double anorm, double* rcond );
+
+lapack_int LAPACKE_sgeequ( int matrix_order, lapack_int m, lapack_int n,
+                           const float* a, lapack_int lda, float* r, float* c,
+                           float* rowcnd, float* colcnd, float* amax );
+lapack_int LAPACKE_dgeequ( int matrix_order, lapack_int m, lapack_int n,
+                           const double* a, lapack_int lda, double* r,
+                           double* c, double* rowcnd, double* colcnd,
+                           double* amax );
+lapack_int LAPACKE_cgeequ( int matrix_order, lapack_int m, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           float* r, float* c, float* rowcnd, float* colcnd,
+                           float* amax );
+lapack_int LAPACKE_zgeequ( int matrix_order, lapack_int m, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           double* r, double* c, double* rowcnd, double* colcnd,
+                           double* amax );
+
+lapack_int LAPACKE_sgeequb( int matrix_order, lapack_int m, lapack_int n,
+                            const float* a, lapack_int lda, float* r, float* c,
+                            float* rowcnd, float* colcnd, float* amax );
+lapack_int LAPACKE_dgeequb( int matrix_order, lapack_int m, lapack_int n,
+                            const double* a, lapack_int lda, double* r,
+                            double* c, double* rowcnd, double* colcnd,
+                            double* amax );
+lapack_int LAPACKE_cgeequb( int matrix_order, lapack_int m, lapack_int n,
+                            const lapack_complex_float* a, lapack_int lda,
+                            float* r, float* c, float* rowcnd, float* colcnd,
+                            float* amax );
+lapack_int LAPACKE_zgeequb( int matrix_order, lapack_int m, lapack_int n,
+                            const lapack_complex_double* a, lapack_int lda,
+                            double* r, double* c, double* rowcnd,
+                            double* colcnd, double* amax );
+
+lapack_int LAPACKE_sgees( int matrix_order, char jobvs, char sort,
+                          LAPACK_S_SELECT2 select, lapack_int n, float* a,
+                          lapack_int lda, lapack_int* sdim, float* wr,
+                          float* wi, float* vs, lapack_int ldvs );
+lapack_int LAPACKE_dgees( int matrix_order, char jobvs, char sort,
+                          LAPACK_D_SELECT2 select, lapack_int n, double* a,
+                          lapack_int lda, lapack_int* sdim, double* wr,
+                          double* wi, double* vs, lapack_int ldvs );
+lapack_int LAPACKE_cgees( int matrix_order, char jobvs, char sort,
+                          LAPACK_C_SELECT1 select, lapack_int n,
+                          lapack_complex_float* a, lapack_int lda,
+                          lapack_int* sdim, lapack_complex_float* w,
+                          lapack_complex_float* vs, lapack_int ldvs );
+lapack_int LAPACKE_zgees( int matrix_order, char jobvs, char sort,
+                          LAPACK_Z_SELECT1 select, lapack_int n,
+                          lapack_complex_double* a, lapack_int lda,
+                          lapack_int* sdim, lapack_complex_double* w,
+                          lapack_complex_double* vs, lapack_int ldvs );
+
+lapack_int LAPACKE_sgeesx( int matrix_order, char jobvs, char sort,
+                           LAPACK_S_SELECT2 select, char sense, lapack_int n,
+                           float* a, lapack_int lda, lapack_int* sdim,
+                           float* wr, float* wi, float* vs, lapack_int ldvs,
+                           float* rconde, float* rcondv );
+lapack_int LAPACKE_dgeesx( int matrix_order, char jobvs, char sort,
+                           LAPACK_D_SELECT2 select, char sense, lapack_int n,
+                           double* a, lapack_int lda, lapack_int* sdim,
+                           double* wr, double* wi, double* vs, lapack_int ldvs,
+                           double* rconde, double* rcondv );
+lapack_int LAPACKE_cgeesx( int matrix_order, char jobvs, char sort,
+                           LAPACK_C_SELECT1 select, char sense, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* sdim, lapack_complex_float* w,
+                           lapack_complex_float* vs, lapack_int ldvs,
+                           float* rconde, float* rcondv );
+lapack_int LAPACKE_zgeesx( int matrix_order, char jobvs, char sort,
+                           LAPACK_Z_SELECT1 select, char sense, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* sdim, lapack_complex_double* w,
+                           lapack_complex_double* vs, lapack_int ldvs,
+                           double* rconde, double* rcondv );
+
+lapack_int LAPACKE_sgeev( int matrix_order, char jobvl, char jobvr,
+                          lapack_int n, float* a, lapack_int lda, float* wr,
+                          float* wi, float* vl, lapack_int ldvl, float* vr,
+                          lapack_int ldvr );
+lapack_int LAPACKE_dgeev( int matrix_order, char jobvl, char jobvr,
+                          lapack_int n, double* a, lapack_int lda, double* wr,
+                          double* wi, double* vl, lapack_int ldvl, double* vr,
+                          lapack_int ldvr );
+lapack_int LAPACKE_cgeev( int matrix_order, char jobvl, char jobvr,
+                          lapack_int n, lapack_complex_float* a, lapack_int lda,
+                          lapack_complex_float* w, lapack_complex_float* vl,
+                          lapack_int ldvl, lapack_complex_float* vr,
+                          lapack_int ldvr );
+lapack_int LAPACKE_zgeev( int matrix_order, char jobvl, char jobvr,
+                          lapack_int n, lapack_complex_double* a,
+                          lapack_int lda, lapack_complex_double* w,
+                          lapack_complex_double* vl, lapack_int ldvl,
+                          lapack_complex_double* vr, lapack_int ldvr );
+
+lapack_int LAPACKE_sgeevx( int matrix_order, char balanc, char jobvl,
+                           char jobvr, char sense, lapack_int n, float* a,
+                           lapack_int lda, float* wr, float* wi, float* vl,
+                           lapack_int ldvl, float* vr, lapack_int ldvr,
+                           lapack_int* ilo, lapack_int* ihi, float* scale,
+                           float* abnrm, float* rconde, float* rcondv );
+lapack_int LAPACKE_dgeevx( int matrix_order, char balanc, char jobvl,
+                           char jobvr, char sense, lapack_int n, double* a,
+                           lapack_int lda, double* wr, double* wi, double* vl,
+                           lapack_int ldvl, double* vr, lapack_int ldvr,
+                           lapack_int* ilo, lapack_int* ihi, double* scale,
+                           double* abnrm, double* rconde, double* rcondv );
+lapack_int LAPACKE_cgeevx( int matrix_order, char balanc, char jobvl,
+                           char jobvr, char sense, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* w, lapack_complex_float* vl,
+                           lapack_int ldvl, lapack_complex_float* vr,
+                           lapack_int ldvr, lapack_int* ilo, lapack_int* ihi,
+                           float* scale, float* abnrm, float* rconde,
+                           float* rcondv );
+lapack_int LAPACKE_zgeevx( int matrix_order, char balanc, char jobvl,
+                           char jobvr, char sense, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* w, lapack_complex_double* vl,
+                           lapack_int ldvl, lapack_complex_double* vr,
+                           lapack_int ldvr, lapack_int* ilo, lapack_int* ihi,
+                           double* scale, double* abnrm, double* rconde,
+                           double* rcondv );
+
+lapack_int LAPACKE_sgehrd( int matrix_order, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, float* a, lapack_int lda,
+                           float* tau );
+lapack_int LAPACKE_dgehrd( int matrix_order, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, double* a, lapack_int lda,
+                           double* tau );
+lapack_int LAPACKE_cgehrd( int matrix_order, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* tau );
+lapack_int LAPACKE_zgehrd( int matrix_order, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgejsv( int matrix_order, char joba, char jobu, char jobv,
+                           char jobr, char jobt, char jobp, lapack_int m,
+                           lapack_int n, float* a, lapack_int lda, float* sva,
+                           float* u, lapack_int ldu, float* v, lapack_int ldv,
+                           float* stat, lapack_int* istat );
+lapack_int LAPACKE_dgejsv( int matrix_order, char joba, char jobu, char jobv,
+                           char jobr, char jobt, char jobp, lapack_int m,
+                           lapack_int n, double* a, lapack_int lda, double* sva,
+                           double* u, lapack_int ldu, double* v, lapack_int ldv,
+                           double* stat, lapack_int* istat );
+
+lapack_int LAPACKE_sgelq2( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, float* tau );
+lapack_int LAPACKE_dgelq2( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, double* tau );
+lapack_int LAPACKE_cgelq2( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_zgelq2( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgelqf( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, float* tau );
+lapack_int LAPACKE_dgelqf( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, double* tau );
+lapack_int LAPACKE_cgelqf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_zgelqf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgels( int matrix_order, char trans, lapack_int m,
+                          lapack_int n, lapack_int nrhs, float* a,
+                          lapack_int lda, float* b, lapack_int ldb );
+lapack_int LAPACKE_dgels( int matrix_order, char trans, lapack_int m,
+                          lapack_int n, lapack_int nrhs, double* a,
+                          lapack_int lda, double* b, lapack_int ldb );
+lapack_int LAPACKE_cgels( int matrix_order, char trans, lapack_int m,
+                          lapack_int n, lapack_int nrhs,
+                          lapack_complex_float* a, lapack_int lda,
+                          lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zgels( int matrix_order, char trans, lapack_int m,
+                          lapack_int n, lapack_int nrhs,
+                          lapack_complex_double* a, lapack_int lda,
+                          lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sgelsd( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, float* a, lapack_int lda, float* b,
+                           lapack_int ldb, float* s, float rcond,
+                           lapack_int* rank );
+lapack_int LAPACKE_dgelsd( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, double* a, lapack_int lda,
+                           double* b, lapack_int ldb, double* s, double rcond,
+                           lapack_int* rank );
+lapack_int LAPACKE_cgelsd( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb, float* s, float rcond,
+                           lapack_int* rank );
+lapack_int LAPACKE_zgelsd( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, double* s, double rcond,
+                           lapack_int* rank );
+
+lapack_int LAPACKE_sgelss( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, float* a, lapack_int lda, float* b,
+                           lapack_int ldb, float* s, float rcond,
+                           lapack_int* rank );
+lapack_int LAPACKE_dgelss( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, double* a, lapack_int lda,
+                           double* b, lapack_int ldb, double* s, double rcond,
+                           lapack_int* rank );
+lapack_int LAPACKE_cgelss( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb, float* s, float rcond,
+                           lapack_int* rank );
+lapack_int LAPACKE_zgelss( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, double* s, double rcond,
+                           lapack_int* rank );
+
+lapack_int LAPACKE_sgelsy( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, float* a, lapack_int lda, float* b,
+                           lapack_int ldb, lapack_int* jpvt, float rcond,
+                           lapack_int* rank );
+lapack_int LAPACKE_dgelsy( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, double* a, lapack_int lda,
+                           double* b, lapack_int ldb, lapack_int* jpvt,
+                           double rcond, lapack_int* rank );
+lapack_int LAPACKE_cgelsy( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb, lapack_int* jpvt, float rcond,
+                           lapack_int* rank );
+lapack_int LAPACKE_zgelsy( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nrhs, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, lapack_int* jpvt, double rcond,
+                           lapack_int* rank );
+
+lapack_int LAPACKE_sgeqlf( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, float* tau );
+lapack_int LAPACKE_dgeqlf( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, double* tau );
+lapack_int LAPACKE_cgeqlf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_zgeqlf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgeqp3( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, lapack_int* jpvt,
+                           float* tau );
+lapack_int LAPACKE_dgeqp3( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, lapack_int* jpvt,
+                           double* tau );
+lapack_int LAPACKE_cgeqp3( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* jpvt, lapack_complex_float* tau );
+lapack_int LAPACKE_zgeqp3( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* jpvt, lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgeqpf( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, lapack_int* jpvt,
+                           float* tau );
+lapack_int LAPACKE_dgeqpf( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, lapack_int* jpvt,
+                           double* tau );
+lapack_int LAPACKE_cgeqpf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* jpvt, lapack_complex_float* tau );
+lapack_int LAPACKE_zgeqpf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* jpvt, lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgeqr2( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, float* tau );
+lapack_int LAPACKE_dgeqr2( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, double* tau );
+lapack_int LAPACKE_cgeqr2( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_zgeqr2( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgeqrf( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, float* tau );
+lapack_int LAPACKE_dgeqrf( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, double* tau );
+lapack_int LAPACKE_cgeqrf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_zgeqrf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgeqrfp( int matrix_order, lapack_int m, lapack_int n,
+                            float* a, lapack_int lda, float* tau );
+lapack_int LAPACKE_dgeqrfp( int matrix_order, lapack_int m, lapack_int n,
+                            double* a, lapack_int lda, double* tau );
+lapack_int LAPACKE_cgeqrfp( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* tau );
+lapack_int LAPACKE_zgeqrfp( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgerfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const float* a, lapack_int lda,
+                           const float* af, lapack_int ldaf,
+                           const lapack_int* ipiv, const float* b,
+                           lapack_int ldb, float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_dgerfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const double* a, lapack_int lda,
+                           const double* af, lapack_int ldaf,
+                           const lapack_int* ipiv, const double* b,
+                           lapack_int ldb, double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_cgerfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* af,
+                           lapack_int ldaf, const lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zgerfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* af,
+                           lapack_int ldaf, const lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_sgerfsx( int matrix_order, char trans, char equed,
+                            lapack_int n, lapack_int nrhs, const float* a,
+                            lapack_int lda, const float* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const float* r,
+                            const float* c, const float* b, lapack_int ldb,
+                            float* x, lapack_int ldx, float* rcond, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_dgerfsx( int matrix_order, char trans, char equed,
+                            lapack_int n, lapack_int nrhs, const double* a,
+                            lapack_int lda, const double* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const double* r,
+                            const double* c, const double* b, lapack_int ldb,
+                            double* x, lapack_int ldx, double* rcond,
+                            double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+lapack_int LAPACKE_cgerfsx( int matrix_order, char trans, char equed,
+                            lapack_int n, lapack_int nrhs,
+                            const lapack_complex_float* a, lapack_int lda,
+                            const lapack_complex_float* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const float* r,
+                            const float* c, const lapack_complex_float* b,
+                            lapack_int ldb, lapack_complex_float* x,
+                            lapack_int ldx, float* rcond, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_zgerfsx( int matrix_order, char trans, char equed,
+                            lapack_int n, lapack_int nrhs,
+                            const lapack_complex_double* a, lapack_int lda,
+                            const lapack_complex_double* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const double* r,
+                            const double* c, const lapack_complex_double* b,
+                            lapack_int ldb, lapack_complex_double* x,
+                            lapack_int ldx, double* rcond, double* berr,
+                            lapack_int n_err_bnds, double* err_bnds_norm,
+                            double* err_bnds_comp, lapack_int nparams,
+                            double* params );
+
+lapack_int LAPACKE_sgerqf( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, float* tau );
+lapack_int LAPACKE_dgerqf( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, double* tau );
+lapack_int LAPACKE_cgerqf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_zgerqf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_sgesdd( int matrix_order, char jobz, lapack_int m,
+                           lapack_int n, float* a, lapack_int lda, float* s,
+                           float* u, lapack_int ldu, float* vt,
+                           lapack_int ldvt );
+lapack_int LAPACKE_dgesdd( int matrix_order, char jobz, lapack_int m,
+                           lapack_int n, double* a, lapack_int lda, double* s,
+                           double* u, lapack_int ldu, double* vt,
+                           lapack_int ldvt );
+lapack_int LAPACKE_cgesdd( int matrix_order, char jobz, lapack_int m,
+                           lapack_int n, lapack_complex_float* a,
+                           lapack_int lda, float* s, lapack_complex_float* u,
+                           lapack_int ldu, lapack_complex_float* vt,
+                           lapack_int ldvt );
+lapack_int LAPACKE_zgesdd( int matrix_order, char jobz, lapack_int m,
+                           lapack_int n, lapack_complex_double* a,
+                           lapack_int lda, double* s, lapack_complex_double* u,
+                           lapack_int ldu, lapack_complex_double* vt,
+                           lapack_int ldvt );
+
+lapack_int LAPACKE_sgesv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          float* a, lapack_int lda, lapack_int* ipiv, float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_dgesv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          double* a, lapack_int lda, lapack_int* ipiv,
+                          double* b, lapack_int ldb );
+lapack_int LAPACKE_cgesv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          lapack_complex_float* a, lapack_int lda,
+                          lapack_int* ipiv, lapack_complex_float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_zgesv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          lapack_complex_double* a, lapack_int lda,
+                          lapack_int* ipiv, lapack_complex_double* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_dsgesv( int matrix_order, lapack_int n, lapack_int nrhs,
+                           double* a, lapack_int lda, lapack_int* ipiv,
+                           double* b, lapack_int ldb, double* x, lapack_int ldx,
+                           lapack_int* iter );
+lapack_int LAPACKE_zcgesv( int matrix_order, lapack_int n, lapack_int nrhs,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* ipiv, lapack_complex_double* b,
+                           lapack_int ldb, lapack_complex_double* x,
+                           lapack_int ldx, lapack_int* iter );
+
+lapack_int LAPACKE_sgesvd( int matrix_order, char jobu, char jobvt,
+                           lapack_int m, lapack_int n, float* a, lapack_int lda,
+                           float* s, float* u, lapack_int ldu, float* vt,
+                           lapack_int ldvt, float* superb );
+lapack_int LAPACKE_dgesvd( int matrix_order, char jobu, char jobvt,
+                           lapack_int m, lapack_int n, double* a,
+                           lapack_int lda, double* s, double* u, lapack_int ldu,
+                           double* vt, lapack_int ldvt, double* superb );
+lapack_int LAPACKE_cgesvd( int matrix_order, char jobu, char jobvt,
+                           lapack_int m, lapack_int n, lapack_complex_float* a,
+                           lapack_int lda, float* s, lapack_complex_float* u,
+                           lapack_int ldu, lapack_complex_float* vt,
+                           lapack_int ldvt, float* superb );
+lapack_int LAPACKE_zgesvd( int matrix_order, char jobu, char jobvt,
+                           lapack_int m, lapack_int n, lapack_complex_double* a,
+                           lapack_int lda, double* s, lapack_complex_double* u,
+                           lapack_int ldu, lapack_complex_double* vt,
+                           lapack_int ldvt, double* superb );
+
+lapack_int LAPACKE_sgesvj( int matrix_order, char joba, char jobu, char jobv,
+                           lapack_int m, lapack_int n, float* a, lapack_int lda,
+                           float* sva, lapack_int mv, float* v, lapack_int ldv,
+                           float* stat );
+lapack_int LAPACKE_dgesvj( int matrix_order, char joba, char jobu, char jobv,
+                           lapack_int m, lapack_int n, double* a,
+                           lapack_int lda, double* sva, lapack_int mv,
+                           double* v, lapack_int ldv, double* stat );
+
+lapack_int LAPACKE_sgesvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int nrhs, float* a,
+                           lapack_int lda, float* af, lapack_int ldaf,
+                           lapack_int* ipiv, char* equed, float* r, float* c,
+                           float* b, lapack_int ldb, float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr,
+                           float* rpivot );
+lapack_int LAPACKE_dgesvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int nrhs, double* a,
+                           lapack_int lda, double* af, lapack_int ldaf,
+                           lapack_int* ipiv, char* equed, double* r, double* c,
+                           double* b, lapack_int ldb, double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr,
+                           double* rpivot );
+lapack_int LAPACKE_cgesvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int nrhs,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* af, lapack_int ldaf,
+                           lapack_int* ipiv, char* equed, float* r, float* c,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr,
+                           float* rpivot );
+lapack_int LAPACKE_zgesvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int nrhs,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* af, lapack_int ldaf,
+                           lapack_int* ipiv, char* equed, double* r, double* c,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr,
+                           double* rpivot );
+
+lapack_int LAPACKE_sgesvxx( int matrix_order, char fact, char trans,
+                            lapack_int n, lapack_int nrhs, float* a,
+                            lapack_int lda, float* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, float* r, float* c,
+                            float* b, lapack_int ldb, float* x, lapack_int ldx,
+                            float* rcond, float* rpvgrw, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_dgesvxx( int matrix_order, char fact, char trans,
+                            lapack_int n, lapack_int nrhs, double* a,
+                            lapack_int lda, double* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, double* r, double* c,
+                            double* b, lapack_int ldb, double* x,
+                            lapack_int ldx, double* rcond, double* rpvgrw,
+                            double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+lapack_int LAPACKE_cgesvxx( int matrix_order, char fact, char trans,
+                            lapack_int n, lapack_int nrhs,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, float* r, float* c,
+                            lapack_complex_float* b, lapack_int ldb,
+                            lapack_complex_float* x, lapack_int ldx,
+                            float* rcond, float* rpvgrw, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_zgesvxx( int matrix_order, char fact, char trans,
+                            lapack_int n, lapack_int nrhs,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, double* r, double* c,
+                            lapack_complex_double* b, lapack_int ldb,
+                            lapack_complex_double* x, lapack_int ldx,
+                            double* rcond, double* rpvgrw, double* berr,
+                            lapack_int n_err_bnds, double* err_bnds_norm,
+                            double* err_bnds_comp, lapack_int nparams,
+                            double* params );
+
+lapack_int LAPACKE_sgetf2( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_dgetf2( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_cgetf2( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* ipiv );
+lapack_int LAPACKE_zgetf2( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* ipiv );
+
+lapack_int LAPACKE_sgetrf( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_dgetrf( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_cgetrf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* ipiv );
+lapack_int LAPACKE_zgetrf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* ipiv );
+
+lapack_int LAPACKE_sgetri( int matrix_order, lapack_int n, float* a,
+                           lapack_int lda, const lapack_int* ipiv );
+lapack_int LAPACKE_dgetri( int matrix_order, lapack_int n, double* a,
+                           lapack_int lda, const lapack_int* ipiv );
+lapack_int LAPACKE_cgetri( int matrix_order, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           const lapack_int* ipiv );
+lapack_int LAPACKE_zgetri( int matrix_order, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           const lapack_int* ipiv );
+
+lapack_int LAPACKE_sgetrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const float* a, lapack_int lda,
+                           const lapack_int* ipiv, float* b, lapack_int ldb );
+lapack_int LAPACKE_dgetrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const double* a, lapack_int lda,
+                           const lapack_int* ipiv, double* b, lapack_int ldb );
+lapack_int LAPACKE_cgetrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_int* ipiv,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zgetrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_int* ipiv,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sggbak( int matrix_order, char job, char side, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, const float* lscale,
+                           const float* rscale, lapack_int m, float* v,
+                           lapack_int ldv );
+lapack_int LAPACKE_dggbak( int matrix_order, char job, char side, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, const double* lscale,
+                           const double* rscale, lapack_int m, double* v,
+                           lapack_int ldv );
+lapack_int LAPACKE_cggbak( int matrix_order, char job, char side, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, const float* lscale,
+                           const float* rscale, lapack_int m,
+                           lapack_complex_float* v, lapack_int ldv );
+lapack_int LAPACKE_zggbak( int matrix_order, char job, char side, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, const double* lscale,
+                           const double* rscale, lapack_int m,
+                           lapack_complex_double* v, lapack_int ldv );
+
+lapack_int LAPACKE_sggbal( int matrix_order, char job, lapack_int n, float* a,
+                           lapack_int lda, float* b, lapack_int ldb,
+                           lapack_int* ilo, lapack_int* ihi, float* lscale,
+                           float* rscale );
+lapack_int LAPACKE_dggbal( int matrix_order, char job, lapack_int n, double* a,
+                           lapack_int lda, double* b, lapack_int ldb,
+                           lapack_int* ilo, lapack_int* ihi, double* lscale,
+                           double* rscale );
+lapack_int LAPACKE_cggbal( int matrix_order, char job, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_int* ilo, lapack_int* ihi, float* lscale,
+                           float* rscale );
+lapack_int LAPACKE_zggbal( int matrix_order, char job, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_int* ilo, lapack_int* ihi, double* lscale,
+                           double* rscale );
+
+lapack_int LAPACKE_sgges( int matrix_order, char jobvsl, char jobvsr, char sort,
+                          LAPACK_S_SELECT3 selctg, lapack_int n, float* a,
+                          lapack_int lda, float* b, lapack_int ldb,
+                          lapack_int* sdim, float* alphar, float* alphai,
+                          float* beta, float* vsl, lapack_int ldvsl, float* vsr,
+                          lapack_int ldvsr );
+lapack_int LAPACKE_dgges( int matrix_order, char jobvsl, char jobvsr, char sort,
+                          LAPACK_D_SELECT3 selctg, lapack_int n, double* a,
+                          lapack_int lda, double* b, lapack_int ldb,
+                          lapack_int* sdim, double* alphar, double* alphai,
+                          double* beta, double* vsl, lapack_int ldvsl,
+                          double* vsr, lapack_int ldvsr );
+lapack_int LAPACKE_cgges( int matrix_order, char jobvsl, char jobvsr, char sort,
+                          LAPACK_C_SELECT2 selctg, lapack_int n,
+                          lapack_complex_float* a, lapack_int lda,
+                          lapack_complex_float* b, lapack_int ldb,
+                          lapack_int* sdim, lapack_complex_float* alpha,
+                          lapack_complex_float* beta, lapack_complex_float* vsl,
+                          lapack_int ldvsl, lapack_complex_float* vsr,
+                          lapack_int ldvsr );
+lapack_int LAPACKE_zgges( int matrix_order, char jobvsl, char jobvsr, char sort,
+                          LAPACK_Z_SELECT2 selctg, lapack_int n,
+                          lapack_complex_double* a, lapack_int lda,
+                          lapack_complex_double* b, lapack_int ldb,
+                          lapack_int* sdim, lapack_complex_double* alpha,
+                          lapack_complex_double* beta,
+                          lapack_complex_double* vsl, lapack_int ldvsl,
+                          lapack_complex_double* vsr, lapack_int ldvsr );
+
+lapack_int LAPACKE_sggesx( int matrix_order, char jobvsl, char jobvsr,
+                           char sort, LAPACK_S_SELECT3 selctg, char sense,
+                           lapack_int n, float* a, lapack_int lda, float* b,
+                           lapack_int ldb, lapack_int* sdim, float* alphar,
+                           float* alphai, float* beta, float* vsl,
+                           lapack_int ldvsl, float* vsr, lapack_int ldvsr,
+                           float* rconde, float* rcondv );
+lapack_int LAPACKE_dggesx( int matrix_order, char jobvsl, char jobvsr,
+                           char sort, LAPACK_D_SELECT3 selctg, char sense,
+                           lapack_int n, double* a, lapack_int lda, double* b,
+                           lapack_int ldb, lapack_int* sdim, double* alphar,
+                           double* alphai, double* beta, double* vsl,
+                           lapack_int ldvsl, double* vsr, lapack_int ldvsr,
+                           double* rconde, double* rcondv );
+lapack_int LAPACKE_cggesx( int matrix_order, char jobvsl, char jobvsr,
+                           char sort, LAPACK_C_SELECT2 selctg, char sense,
+                           lapack_int n, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb, lapack_int* sdim,
+                           lapack_complex_float* alpha,
+                           lapack_complex_float* beta,
+                           lapack_complex_float* vsl, lapack_int ldvsl,
+                           lapack_complex_float* vsr, lapack_int ldvsr,
+                           float* rconde, float* rcondv );
+lapack_int LAPACKE_zggesx( int matrix_order, char jobvsl, char jobvsr,
+                           char sort, LAPACK_Z_SELECT2 selctg, char sense,
+                           lapack_int n, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, lapack_int* sdim,
+                           lapack_complex_double* alpha,
+                           lapack_complex_double* beta,
+                           lapack_complex_double* vsl, lapack_int ldvsl,
+                           lapack_complex_double* vsr, lapack_int ldvsr,
+                           double* rconde, double* rcondv );
+
+lapack_int LAPACKE_sggev( int matrix_order, char jobvl, char jobvr,
+                          lapack_int n, float* a, lapack_int lda, float* b,
+                          lapack_int ldb, float* alphar, float* alphai,
+                          float* beta, float* vl, lapack_int ldvl, float* vr,
+                          lapack_int ldvr );
+lapack_int LAPACKE_dggev( int matrix_order, char jobvl, char jobvr,
+                          lapack_int n, double* a, lapack_int lda, double* b,
+                          lapack_int ldb, double* alphar, double* alphai,
+                          double* beta, double* vl, lapack_int ldvl, double* vr,
+                          lapack_int ldvr );
+lapack_int LAPACKE_cggev( int matrix_order, char jobvl, char jobvr,
+                          lapack_int n, lapack_complex_float* a, lapack_int lda,
+                          lapack_complex_float* b, lapack_int ldb,
+                          lapack_complex_float* alpha,
+                          lapack_complex_float* beta, lapack_complex_float* vl,
+                          lapack_int ldvl, lapack_complex_float* vr,
+                          lapack_int ldvr );
+lapack_int LAPACKE_zggev( int matrix_order, char jobvl, char jobvr,
+                          lapack_int n, lapack_complex_double* a,
+                          lapack_int lda, lapack_complex_double* b,
+                          lapack_int ldb, lapack_complex_double* alpha,
+                          lapack_complex_double* beta,
+                          lapack_complex_double* vl, lapack_int ldvl,
+                          lapack_complex_double* vr, lapack_int ldvr );
+
+lapack_int LAPACKE_sggevx( int matrix_order, char balanc, char jobvl,
+                           char jobvr, char sense, lapack_int n, float* a,
+                           lapack_int lda, float* b, lapack_int ldb,
+                           float* alphar, float* alphai, float* beta, float* vl,
+                           lapack_int ldvl, float* vr, lapack_int ldvr,
+                           lapack_int* ilo, lapack_int* ihi, float* lscale,
+                           float* rscale, float* abnrm, float* bbnrm,
+                           float* rconde, float* rcondv );
+lapack_int LAPACKE_dggevx( int matrix_order, char balanc, char jobvl,
+                           char jobvr, char sense, lapack_int n, double* a,
+                           lapack_int lda, double* b, lapack_int ldb,
+                           double* alphar, double* alphai, double* beta,
+                           double* vl, lapack_int ldvl, double* vr,
+                           lapack_int ldvr, lapack_int* ilo, lapack_int* ihi,
+                           double* lscale, double* rscale, double* abnrm,
+                           double* bbnrm, double* rconde, double* rcondv );
+lapack_int LAPACKE_cggevx( int matrix_order, char balanc, char jobvl,
+                           char jobvr, char sense, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* alpha,
+                           lapack_complex_float* beta, lapack_complex_float* vl,
+                           lapack_int ldvl, lapack_complex_float* vr,
+                           lapack_int ldvr, lapack_int* ilo, lapack_int* ihi,
+                           float* lscale, float* rscale, float* abnrm,
+                           float* bbnrm, float* rconde, float* rcondv );
+lapack_int LAPACKE_zggevx( int matrix_order, char balanc, char jobvl,
+                           char jobvr, char sense, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* alpha,
+                           lapack_complex_double* beta,
+                           lapack_complex_double* vl, lapack_int ldvl,
+                           lapack_complex_double* vr, lapack_int ldvr,
+                           lapack_int* ilo, lapack_int* ihi, double* lscale,
+                           double* rscale, double* abnrm, double* bbnrm,
+                           double* rconde, double* rcondv );
+
+lapack_int LAPACKE_sggglm( int matrix_order, lapack_int n, lapack_int m,
+                           lapack_int p, float* a, lapack_int lda, float* b,
+                           lapack_int ldb, float* d, float* x, float* y );
+lapack_int LAPACKE_dggglm( int matrix_order, lapack_int n, lapack_int m,
+                           lapack_int p, double* a, lapack_int lda, double* b,
+                           lapack_int ldb, double* d, double* x, double* y );
+lapack_int LAPACKE_cggglm( int matrix_order, lapack_int n, lapack_int m,
+                           lapack_int p, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb, lapack_complex_float* d,
+                           lapack_complex_float* x, lapack_complex_float* y );
+lapack_int LAPACKE_zggglm( int matrix_order, lapack_int n, lapack_int m,
+                           lapack_int p, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, lapack_complex_double* d,
+                           lapack_complex_double* x, lapack_complex_double* y );
+
+lapack_int LAPACKE_sgghrd( int matrix_order, char compq, char compz,
+                           lapack_int n, lapack_int ilo, lapack_int ihi,
+                           float* a, lapack_int lda, float* b, lapack_int ldb,
+                           float* q, lapack_int ldq, float* z, lapack_int ldz );
+lapack_int LAPACKE_dgghrd( int matrix_order, char compq, char compz,
+                           lapack_int n, lapack_int ilo, lapack_int ihi,
+                           double* a, lapack_int lda, double* b, lapack_int ldb,
+                           double* q, lapack_int ldq, double* z,
+                           lapack_int ldz );
+lapack_int LAPACKE_cgghrd( int matrix_order, char compq, char compz,
+                           lapack_int n, lapack_int ilo, lapack_int ihi,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* q, lapack_int ldq,
+                           lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zgghrd( int matrix_order, char compq, char compz,
+                           lapack_int n, lapack_int ilo, lapack_int ihi,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_complex_double* z, lapack_int ldz );
+
+lapack_int LAPACKE_sgglse( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int p, float* a, lapack_int lda, float* b,
+                           lapack_int ldb, float* c, float* d, float* x );
+lapack_int LAPACKE_dgglse( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int p, double* a, lapack_int lda, double* b,
+                           lapack_int ldb, double* c, double* d, double* x );
+lapack_int LAPACKE_cgglse( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int p, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb, lapack_complex_float* c,
+                           lapack_complex_float* d, lapack_complex_float* x );
+lapack_int LAPACKE_zgglse( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int p, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, lapack_complex_double* c,
+                           lapack_complex_double* d, lapack_complex_double* x );
+
+lapack_int LAPACKE_sggqrf( int matrix_order, lapack_int n, lapack_int m,
+                           lapack_int p, float* a, lapack_int lda, float* taua,
+                           float* b, lapack_int ldb, float* taub );
+lapack_int LAPACKE_dggqrf( int matrix_order, lapack_int n, lapack_int m,
+                           lapack_int p, double* a, lapack_int lda,
+                           double* taua, double* b, lapack_int ldb,
+                           double* taub );
+lapack_int LAPACKE_cggqrf( int matrix_order, lapack_int n, lapack_int m,
+                           lapack_int p, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* taua,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* taub );
+lapack_int LAPACKE_zggqrf( int matrix_order, lapack_int n, lapack_int m,
+                           lapack_int p, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* taua,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* taub );
+
+lapack_int LAPACKE_sggrqf( int matrix_order, lapack_int m, lapack_int p,
+                           lapack_int n, float* a, lapack_int lda, float* taua,
+                           float* b, lapack_int ldb, float* taub );
+lapack_int LAPACKE_dggrqf( int matrix_order, lapack_int m, lapack_int p,
+                           lapack_int n, double* a, lapack_int lda,
+                           double* taua, double* b, lapack_int ldb,
+                           double* taub );
+lapack_int LAPACKE_cggrqf( int matrix_order, lapack_int m, lapack_int p,
+                           lapack_int n, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* taua,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* taub );
+lapack_int LAPACKE_zggrqf( int matrix_order, lapack_int m, lapack_int p,
+                           lapack_int n, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* taua,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* taub );
+
+lapack_int LAPACKE_sggsvd( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int n, lapack_int p,
+                           lapack_int* k, lapack_int* l, float* a,
+                           lapack_int lda, float* b, lapack_int ldb,
+                           float* alpha, float* beta, float* u, lapack_int ldu,
+                           float* v, lapack_int ldv, float* q, lapack_int ldq,
+                           lapack_int* iwork );
+lapack_int LAPACKE_dggsvd( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int n, lapack_int p,
+                           lapack_int* k, lapack_int* l, double* a,
+                           lapack_int lda, double* b, lapack_int ldb,
+                           double* alpha, double* beta, double* u,
+                           lapack_int ldu, double* v, lapack_int ldv, double* q,
+                           lapack_int ldq, lapack_int* iwork );
+lapack_int LAPACKE_cggsvd( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int n, lapack_int p,
+                           lapack_int* k, lapack_int* l,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb,
+                           float* alpha, float* beta, lapack_complex_float* u,
+                           lapack_int ldu, lapack_complex_float* v,
+                           lapack_int ldv, lapack_complex_float* q,
+                           lapack_int ldq, lapack_int* iwork );
+lapack_int LAPACKE_zggsvd( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int n, lapack_int p,
+                           lapack_int* k, lapack_int* l,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           double* alpha, double* beta,
+                           lapack_complex_double* u, lapack_int ldu,
+                           lapack_complex_double* v, lapack_int ldv,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_int* iwork );
+
+lapack_int LAPACKE_sggsvp( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int p, lapack_int n, float* a,
+                           lapack_int lda, float* b, lapack_int ldb, float tola,
+                           float tolb, lapack_int* k, lapack_int* l, float* u,
+                           lapack_int ldu, float* v, lapack_int ldv, float* q,
+                           lapack_int ldq );
+lapack_int LAPACKE_dggsvp( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int p, lapack_int n, double* a,
+                           lapack_int lda, double* b, lapack_int ldb,
+                           double tola, double tolb, lapack_int* k,
+                           lapack_int* l, double* u, lapack_int ldu, double* v,
+                           lapack_int ldv, double* q, lapack_int ldq );
+lapack_int LAPACKE_cggsvp( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int p, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb, float tola,
+                           float tolb, lapack_int* k, lapack_int* l,
+                           lapack_complex_float* u, lapack_int ldu,
+                           lapack_complex_float* v, lapack_int ldv,
+                           lapack_complex_float* q, lapack_int ldq );
+lapack_int LAPACKE_zggsvp( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int p, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           double tola, double tolb, lapack_int* k,
+                           lapack_int* l, lapack_complex_double* u,
+                           lapack_int ldu, lapack_complex_double* v,
+                           lapack_int ldv, lapack_complex_double* q,
+                           lapack_int ldq );
+
+lapack_int LAPACKE_sgtcon( char norm, lapack_int n, const float* dl,
+                           const float* d, const float* du, const float* du2,
+                           const lapack_int* ipiv, float anorm, float* rcond );
+lapack_int LAPACKE_dgtcon( char norm, lapack_int n, const double* dl,
+                           const double* d, const double* du, const double* du2,
+                           const lapack_int* ipiv, double anorm,
+                           double* rcond );
+lapack_int LAPACKE_cgtcon( char norm, lapack_int n,
+                           const lapack_complex_float* dl,
+                           const lapack_complex_float* d,
+                           const lapack_complex_float* du,
+                           const lapack_complex_float* du2,
+                           const lapack_int* ipiv, float anorm, float* rcond );
+lapack_int LAPACKE_zgtcon( char norm, lapack_int n,
+                           const lapack_complex_double* dl,
+                           const lapack_complex_double* d,
+                           const lapack_complex_double* du,
+                           const lapack_complex_double* du2,
+                           const lapack_int* ipiv, double anorm,
+                           double* rcond );
+
+lapack_int LAPACKE_sgtrfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const float* dl, const float* d,
+                           const float* du, const float* dlf, const float* df,
+                           const float* duf, const float* du2,
+                           const lapack_int* ipiv, const float* b,
+                           lapack_int ldb, float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_dgtrfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const double* dl, const double* d,
+                           const double* du, const double* dlf,
+                           const double* df, const double* duf,
+                           const double* du2, const lapack_int* ipiv,
+                           const double* b, lapack_int ldb, double* x,
+                           lapack_int ldx, double* ferr, double* berr );
+lapack_int LAPACKE_cgtrfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* dl,
+                           const lapack_complex_float* d,
+                           const lapack_complex_float* du,
+                           const lapack_complex_float* dlf,
+                           const lapack_complex_float* df,
+                           const lapack_complex_float* duf,
+                           const lapack_complex_float* du2,
+                           const lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zgtrfs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* dl,
+                           const lapack_complex_double* d,
+                           const lapack_complex_double* du,
+                           const lapack_complex_double* dlf,
+                           const lapack_complex_double* df,
+                           const lapack_complex_double* duf,
+                           const lapack_complex_double* du2,
+                           const lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_sgtsv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          float* dl, float* d, float* du, float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_dgtsv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          double* dl, double* d, double* du, double* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_cgtsv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          lapack_complex_float* dl, lapack_complex_float* d,
+                          lapack_complex_float* du, lapack_complex_float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_zgtsv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          lapack_complex_double* dl, lapack_complex_double* d,
+                          lapack_complex_double* du, lapack_complex_double* b,
+                          lapack_int ldb );
+
+lapack_int LAPACKE_sgtsvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int nrhs, const float* dl,
+                           const float* d, const float* du, float* dlf,
+                           float* df, float* duf, float* du2, lapack_int* ipiv,
+                           const float* b, lapack_int ldb, float* x,
+                           lapack_int ldx, float* rcond, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_dgtsvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int nrhs, const double* dl,
+                           const double* d, const double* du, double* dlf,
+                           double* df, double* duf, double* du2,
+                           lapack_int* ipiv, const double* b, lapack_int ldb,
+                           double* x, lapack_int ldx, double* rcond,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_cgtsvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_float* dl,
+                           const lapack_complex_float* d,
+                           const lapack_complex_float* du,
+                           lapack_complex_float* dlf, lapack_complex_float* df,
+                           lapack_complex_float* duf, lapack_complex_float* du2,
+                           lapack_int* ipiv, const lapack_complex_float* b,
+                           lapack_int ldb, lapack_complex_float* x,
+                           lapack_int ldx, float* rcond, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zgtsvx( int matrix_order, char fact, char trans,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_double* dl,
+                           const lapack_complex_double* d,
+                           const lapack_complex_double* du,
+                           lapack_complex_double* dlf,
+                           lapack_complex_double* df,
+                           lapack_complex_double* duf,
+                           lapack_complex_double* du2, lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+
+lapack_int LAPACKE_sgttrf( lapack_int n, float* dl, float* d, float* du,
+                           float* du2, lapack_int* ipiv );
+lapack_int LAPACKE_dgttrf( lapack_int n, double* dl, double* d, double* du,
+                           double* du2, lapack_int* ipiv );
+lapack_int LAPACKE_cgttrf( lapack_int n, lapack_complex_float* dl,
+                           lapack_complex_float* d, lapack_complex_float* du,
+                           lapack_complex_float* du2, lapack_int* ipiv );
+lapack_int LAPACKE_zgttrf( lapack_int n, lapack_complex_double* dl,
+                           lapack_complex_double* d, lapack_complex_double* du,
+                           lapack_complex_double* du2, lapack_int* ipiv );
+
+lapack_int LAPACKE_sgttrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const float* dl, const float* d,
+                           const float* du, const float* du2,
+                           const lapack_int* ipiv, float* b, lapack_int ldb );
+lapack_int LAPACKE_dgttrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const double* dl, const double* d,
+                           const double* du, const double* du2,
+                           const lapack_int* ipiv, double* b, lapack_int ldb );
+lapack_int LAPACKE_cgttrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* dl,
+                           const lapack_complex_float* d,
+                           const lapack_complex_float* du,
+                           const lapack_complex_float* du2,
+                           const lapack_int* ipiv, lapack_complex_float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_zgttrs( int matrix_order, char trans, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* dl,
+                           const lapack_complex_double* d,
+                           const lapack_complex_double* du,
+                           const lapack_complex_double* du2,
+                           const lapack_int* ipiv, lapack_complex_double* b,
+                           lapack_int ldb );
+
+lapack_int LAPACKE_chbev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_int kd, lapack_complex_float* ab,
+                          lapack_int ldab, float* w, lapack_complex_float* z,
+                          lapack_int ldz );
+lapack_int LAPACKE_zhbev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_int kd, lapack_complex_double* ab,
+                          lapack_int ldab, double* w, lapack_complex_double* z,
+                          lapack_int ldz );
+
+lapack_int LAPACKE_chbevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_int kd, lapack_complex_float* ab,
+                           lapack_int ldab, float* w, lapack_complex_float* z,
+                           lapack_int ldz );
+lapack_int LAPACKE_zhbevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_int kd, lapack_complex_double* ab,
+                           lapack_int ldab, double* w, lapack_complex_double* z,
+                           lapack_int ldz );
+
+lapack_int LAPACKE_chbevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_int kd,
+                           lapack_complex_float* ab, lapack_int ldab,
+                           lapack_complex_float* q, lapack_int ldq, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, lapack_complex_float* z,
+                           lapack_int ldz, lapack_int* ifail );
+lapack_int LAPACKE_zhbevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_int kd,
+                           lapack_complex_double* ab, lapack_int ldab,
+                           lapack_complex_double* q, lapack_int ldq, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* ifail );
+
+lapack_int LAPACKE_chbgst( int matrix_order, char vect, char uplo, lapack_int n,
+                           lapack_int ka, lapack_int kb,
+                           lapack_complex_float* ab, lapack_int ldab,
+                           const lapack_complex_float* bb, lapack_int ldbb,
+                           lapack_complex_float* x, lapack_int ldx );
+lapack_int LAPACKE_zhbgst( int matrix_order, char vect, char uplo, lapack_int n,
+                           lapack_int ka, lapack_int kb,
+                           lapack_complex_double* ab, lapack_int ldab,
+                           const lapack_complex_double* bb, lapack_int ldbb,
+                           lapack_complex_double* x, lapack_int ldx );
+
+lapack_int LAPACKE_chbgv( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_int ka, lapack_int kb,
+                          lapack_complex_float* ab, lapack_int ldab,
+                          lapack_complex_float* bb, lapack_int ldbb, float* w,
+                          lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zhbgv( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_int ka, lapack_int kb,
+                          lapack_complex_double* ab, lapack_int ldab,
+                          lapack_complex_double* bb, lapack_int ldbb, double* w,
+                          lapack_complex_double* z, lapack_int ldz );
+
+lapack_int LAPACKE_chbgvd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_int ka, lapack_int kb,
+                           lapack_complex_float* ab, lapack_int ldab,
+                           lapack_complex_float* bb, lapack_int ldbb, float* w,
+                           lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zhbgvd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_int ka, lapack_int kb,
+                           lapack_complex_double* ab, lapack_int ldab,
+                           lapack_complex_double* bb, lapack_int ldbb,
+                           double* w, lapack_complex_double* z,
+                           lapack_int ldz );
+
+lapack_int LAPACKE_chbgvx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_int ka, lapack_int kb,
+                           lapack_complex_float* ab, lapack_int ldab,
+                           lapack_complex_float* bb, lapack_int ldbb,
+                           lapack_complex_float* q, lapack_int ldq, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, lapack_complex_float* z,
+                           lapack_int ldz, lapack_int* ifail );
+lapack_int LAPACKE_zhbgvx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_int ka, lapack_int kb,
+                           lapack_complex_double* ab, lapack_int ldab,
+                           lapack_complex_double* bb, lapack_int ldbb,
+                           lapack_complex_double* q, lapack_int ldq, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* ifail );
+
+lapack_int LAPACKE_chbtrd( int matrix_order, char vect, char uplo, lapack_int n,
+                           lapack_int kd, lapack_complex_float* ab,
+                           lapack_int ldab, float* d, float* e,
+                           lapack_complex_float* q, lapack_int ldq );
+lapack_int LAPACKE_zhbtrd( int matrix_order, char vect, char uplo, lapack_int n,
+                           lapack_int kd, lapack_complex_double* ab,
+                           lapack_int ldab, double* d, double* e,
+                           lapack_complex_double* q, lapack_int ldq );
+
+lapack_int LAPACKE_checon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_int* ipiv, float anorm, float* rcond );
+lapack_int LAPACKE_zhecon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_int* ipiv, double anorm,
+                           double* rcond );
+
+lapack_int LAPACKE_cheequb( int matrix_order, char uplo, lapack_int n,
+                            const lapack_complex_float* a, lapack_int lda,
+                            float* s, float* scond, float* amax );
+lapack_int LAPACKE_zheequb( int matrix_order, char uplo, lapack_int n,
+                            const lapack_complex_double* a, lapack_int lda,
+                            double* s, double* scond, double* amax );
+
+lapack_int LAPACKE_cheev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_complex_float* a, lapack_int lda, float* w );
+lapack_int LAPACKE_zheev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_complex_double* a, lapack_int lda, double* w );
+
+lapack_int LAPACKE_cheevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda, float* w );
+lapack_int LAPACKE_zheevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           double* w );
+
+lapack_int LAPACKE_cheevr( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_complex_float* a,
+                           lapack_int lda, float vl, float vu, lapack_int il,
+                           lapack_int iu, float abstol, lapack_int* m, float* w,
+                           lapack_complex_float* z, lapack_int ldz,
+                           lapack_int* isuppz );
+lapack_int LAPACKE_zheevr( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_complex_double* a,
+                           lapack_int lda, double vl, double vu, lapack_int il,
+                           lapack_int iu, double abstol, lapack_int* m,
+                           double* w, lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* isuppz );
+
+lapack_int LAPACKE_cheevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_complex_float* a,
+                           lapack_int lda, float vl, float vu, lapack_int il,
+                           lapack_int iu, float abstol, lapack_int* m, float* w,
+                           lapack_complex_float* z, lapack_int ldz,
+                           lapack_int* ifail );
+lapack_int LAPACKE_zheevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_complex_double* a,
+                           lapack_int lda, double vl, double vu, lapack_int il,
+                           lapack_int iu, double abstol, lapack_int* m,
+                           double* w, lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* ifail );
+
+lapack_int LAPACKE_chegst( int matrix_order, lapack_int itype, char uplo,
+                           lapack_int n, lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_zhegst( int matrix_order, lapack_int itype, char uplo,
+                           lapack_int n, lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* b,
+                           lapack_int ldb );
+
+lapack_int LAPACKE_chegv( int matrix_order, lapack_int itype, char jobz,
+                          char uplo, lapack_int n, lapack_complex_float* a,
+                          lapack_int lda, lapack_complex_float* b,
+                          lapack_int ldb, float* w );
+lapack_int LAPACKE_zhegv( int matrix_order, lapack_int itype, char jobz,
+                          char uplo, lapack_int n, lapack_complex_double* a,
+                          lapack_int lda, lapack_complex_double* b,
+                          lapack_int ldb, double* w );
+
+lapack_int LAPACKE_chegvd( int matrix_order, lapack_int itype, char jobz,
+                           char uplo, lapack_int n, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb, float* w );
+lapack_int LAPACKE_zhegvd( int matrix_order, lapack_int itype, char jobz,
+                           char uplo, lapack_int n, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, double* w );
+
+lapack_int LAPACKE_chegvx( int matrix_order, lapack_int itype, char jobz,
+                           char range, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, lapack_complex_float* z,
+                           lapack_int ldz, lapack_int* ifail );
+lapack_int LAPACKE_zhegvx( int matrix_order, lapack_int itype, char jobz,
+                           char range, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* ifail );
+
+lapack_int LAPACKE_cherfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* af,
+                           lapack_int ldaf, const lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zherfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* af,
+                           lapack_int ldaf, const lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_cherfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs,
+                            const lapack_complex_float* a, lapack_int lda,
+                            const lapack_complex_float* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const float* s,
+                            const lapack_complex_float* b, lapack_int ldb,
+                            lapack_complex_float* x, lapack_int ldx,
+                            float* rcond, float* berr, lapack_int n_err_bnds,
+                            float* err_bnds_norm, float* err_bnds_comp,
+                            lapack_int nparams, float* params );
+lapack_int LAPACKE_zherfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs,
+                            const lapack_complex_double* a, lapack_int lda,
+                            const lapack_complex_double* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const double* s,
+                            const lapack_complex_double* b, lapack_int ldb,
+                            lapack_complex_double* x, lapack_int ldx,
+                            double* rcond, double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+
+lapack_int LAPACKE_chesv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_float* a,
+                          lapack_int lda, lapack_int* ipiv,
+                          lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zhesv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_double* a,
+                          lapack_int lda, lapack_int* ipiv,
+                          lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_chesvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* af,
+                           lapack_int ldaf, lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr );
+lapack_int LAPACKE_zhesvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* af,
+                           lapack_int ldaf, lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+
+lapack_int LAPACKE_chesvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, float* s,
+                            lapack_complex_float* b, lapack_int ldb,
+                            lapack_complex_float* x, lapack_int ldx,
+                            float* rcond, float* rpvgrw, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_zhesvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, double* s,
+                            lapack_complex_double* b, lapack_int ldb,
+                            lapack_complex_double* x, lapack_int ldx,
+                            double* rcond, double* rpvgrw, double* berr,
+                            lapack_int n_err_bnds, double* err_bnds_norm,
+                            double* err_bnds_comp, lapack_int nparams,
+                            double* params );
+
+lapack_int LAPACKE_chetrd( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda, float* d,
+                           float* e, lapack_complex_float* tau );
+lapack_int LAPACKE_zhetrd( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda, double* d,
+                           double* e, lapack_complex_double* tau );
+
+lapack_int LAPACKE_chetrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* ipiv );
+lapack_int LAPACKE_zhetrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* ipiv );
+
+lapack_int LAPACKE_chetri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           const lapack_int* ipiv );
+lapack_int LAPACKE_zhetri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           const lapack_int* ipiv );
+
+lapack_int LAPACKE_chetrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_int* ipiv,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zhetrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_int* ipiv,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_chfrk( int matrix_order, char transr, char uplo, char trans,
+                          lapack_int n, lapack_int k, float alpha,
+                          const lapack_complex_float* a, lapack_int lda,
+                          float beta, lapack_complex_float* c );
+lapack_int LAPACKE_zhfrk( int matrix_order, char transr, char uplo, char trans,
+                          lapack_int n, lapack_int k, double alpha,
+                          const lapack_complex_double* a, lapack_int lda,
+                          double beta, lapack_complex_double* c );
+
+lapack_int LAPACKE_shgeqz( int matrix_order, char job, char compq, char compz,
+                           lapack_int n, lapack_int ilo, lapack_int ihi,
+                           float* h, lapack_int ldh, float* t, lapack_int ldt,
+                           float* alphar, float* alphai, float* beta, float* q,
+                           lapack_int ldq, float* z, lapack_int ldz );
+lapack_int LAPACKE_dhgeqz( int matrix_order, char job, char compq, char compz,
+                           lapack_int n, lapack_int ilo, lapack_int ihi,
+                           double* h, lapack_int ldh, double* t, lapack_int ldt,
+                           double* alphar, double* alphai, double* beta,
+                           double* q, lapack_int ldq, double* z,
+                           lapack_int ldz );
+lapack_int LAPACKE_chgeqz( int matrix_order, char job, char compq, char compz,
+                           lapack_int n, lapack_int ilo, lapack_int ihi,
+                           lapack_complex_float* h, lapack_int ldh,
+                           lapack_complex_float* t, lapack_int ldt,
+                           lapack_complex_float* alpha,
+                           lapack_complex_float* beta, lapack_complex_float* q,
+                           lapack_int ldq, lapack_complex_float* z,
+                           lapack_int ldz );
+lapack_int LAPACKE_zhgeqz( int matrix_order, char job, char compq, char compz,
+                           lapack_int n, lapack_int ilo, lapack_int ihi,
+                           lapack_complex_double* h, lapack_int ldh,
+                           lapack_complex_double* t, lapack_int ldt,
+                           lapack_complex_double* alpha,
+                           lapack_complex_double* beta,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_complex_double* z, lapack_int ldz );
+
+lapack_int LAPACKE_chpcon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* ap,
+                           const lapack_int* ipiv, float anorm, float* rcond );
+lapack_int LAPACKE_zhpcon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* ap,
+                           const lapack_int* ipiv, double anorm,
+                           double* rcond );
+
+lapack_int LAPACKE_chpev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_complex_float* ap, float* w,
+                          lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zhpev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_complex_double* ap, double* w,
+                          lapack_complex_double* z, lapack_int ldz );
+
+lapack_int LAPACKE_chpevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_complex_float* ap, float* w,
+                           lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zhpevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_complex_double* ap, double* w,
+                           lapack_complex_double* z, lapack_int ldz );
+
+lapack_int LAPACKE_chpevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_complex_float* ap, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, lapack_complex_float* z,
+                           lapack_int ldz, lapack_int* ifail );
+lapack_int LAPACKE_zhpevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_complex_double* ap, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* ifail );
+
+lapack_int LAPACKE_chpgst( int matrix_order, lapack_int itype, char uplo,
+                           lapack_int n, lapack_complex_float* ap,
+                           const lapack_complex_float* bp );
+lapack_int LAPACKE_zhpgst( int matrix_order, lapack_int itype, char uplo,
+                           lapack_int n, lapack_complex_double* ap,
+                           const lapack_complex_double* bp );
+
+lapack_int LAPACKE_chpgv( int matrix_order, lapack_int itype, char jobz,
+                          char uplo, lapack_int n, lapack_complex_float* ap,
+                          lapack_complex_float* bp, float* w,
+                          lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zhpgv( int matrix_order, lapack_int itype, char jobz,
+                          char uplo, lapack_int n, lapack_complex_double* ap,
+                          lapack_complex_double* bp, double* w,
+                          lapack_complex_double* z, lapack_int ldz );
+
+lapack_int LAPACKE_chpgvd( int matrix_order, lapack_int itype, char jobz,
+                           char uplo, lapack_int n, lapack_complex_float* ap,
+                           lapack_complex_float* bp, float* w,
+                           lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zhpgvd( int matrix_order, lapack_int itype, char jobz,
+                           char uplo, lapack_int n, lapack_complex_double* ap,
+                           lapack_complex_double* bp, double* w,
+                           lapack_complex_double* z, lapack_int ldz );
+
+lapack_int LAPACKE_chpgvx( int matrix_order, lapack_int itype, char jobz,
+                           char range, char uplo, lapack_int n,
+                           lapack_complex_float* ap, lapack_complex_float* bp,
+                           float vl, float vu, lapack_int il, lapack_int iu,
+                           float abstol, lapack_int* m, float* w,
+                           lapack_complex_float* z, lapack_int ldz,
+                           lapack_int* ifail );
+lapack_int LAPACKE_zhpgvx( int matrix_order, lapack_int itype, char jobz,
+                           char range, char uplo, lapack_int n,
+                           lapack_complex_double* ap, lapack_complex_double* bp,
+                           double vl, double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* ifail );
+
+lapack_int LAPACKE_chprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* ap,
+                           const lapack_complex_float* afp,
+                           const lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zhprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* ap,
+                           const lapack_complex_double* afp,
+                           const lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_chpsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_float* ap,
+                          lapack_int* ipiv, lapack_complex_float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_zhpsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_double* ap,
+                          lapack_int* ipiv, lapack_complex_double* b,
+                          lapack_int ldb );
+
+lapack_int LAPACKE_chpsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* ap,
+                           lapack_complex_float* afp, lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr );
+lapack_int LAPACKE_zhpsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* ap,
+                           lapack_complex_double* afp, lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+
+lapack_int LAPACKE_chptrd( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* ap, float* d, float* e,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_zhptrd( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* ap, double* d, double* e,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_chptrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* ap, lapack_int* ipiv );
+lapack_int LAPACKE_zhptrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* ap, lapack_int* ipiv );
+
+lapack_int LAPACKE_chptri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* ap, const lapack_int* ipiv );
+lapack_int LAPACKE_zhptri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* ap, const lapack_int* ipiv );
+
+lapack_int LAPACKE_chptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* ap,
+                           const lapack_int* ipiv, lapack_complex_float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_zhptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* ap,
+                           const lapack_int* ipiv, lapack_complex_double* b,
+                           lapack_int ldb );
+
+lapack_int LAPACKE_shsein( int matrix_order, char job, char eigsrc, char initv,
+                           lapack_logical* select, lapack_int n, const float* h,
+                           lapack_int ldh, float* wr, const float* wi,
+                           float* vl, lapack_int ldvl, float* vr,
+                           lapack_int ldvr, lapack_int mm, lapack_int* m,
+                           lapack_int* ifaill, lapack_int* ifailr );
+lapack_int LAPACKE_dhsein( int matrix_order, char job, char eigsrc, char initv,
+                           lapack_logical* select, lapack_int n,
+                           const double* h, lapack_int ldh, double* wr,
+                           const double* wi, double* vl, lapack_int ldvl,
+                           double* vr, lapack_int ldvr, lapack_int mm,
+                           lapack_int* m, lapack_int* ifaill,
+                           lapack_int* ifailr );
+lapack_int LAPACKE_chsein( int matrix_order, char job, char eigsrc, char initv,
+                           const lapack_logical* select, lapack_int n,
+                           const lapack_complex_float* h, lapack_int ldh,
+                           lapack_complex_float* w, lapack_complex_float* vl,
+                           lapack_int ldvl, lapack_complex_float* vr,
+                           lapack_int ldvr, lapack_int mm, lapack_int* m,
+                           lapack_int* ifaill, lapack_int* ifailr );
+lapack_int LAPACKE_zhsein( int matrix_order, char job, char eigsrc, char initv,
+                           const lapack_logical* select, lapack_int n,
+                           const lapack_complex_double* h, lapack_int ldh,
+                           lapack_complex_double* w, lapack_complex_double* vl,
+                           lapack_int ldvl, lapack_complex_double* vr,
+                           lapack_int ldvr, lapack_int mm, lapack_int* m,
+                           lapack_int* ifaill, lapack_int* ifailr );
+
+lapack_int LAPACKE_shseqr( int matrix_order, char job, char compz, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, float* h,
+                           lapack_int ldh, float* wr, float* wi, float* z,
+                           lapack_int ldz );
+lapack_int LAPACKE_dhseqr( int matrix_order, char job, char compz, lapack_int n,
+                           lapack_int ilo, lapack_int ihi, double* h,
+                           lapack_int ldh, double* wr, double* wi, double* z,
+                           lapack_int ldz );
+lapack_int LAPACKE_chseqr( int matrix_order, char job, char compz, lapack_int n,
+                           lapack_int ilo, lapack_int ihi,
+                           lapack_complex_float* h, lapack_int ldh,
+                           lapack_complex_float* w, lapack_complex_float* z,
+                           lapack_int ldz );
+lapack_int LAPACKE_zhseqr( int matrix_order, char job, char compz, lapack_int n,
+                           lapack_int ilo, lapack_int ihi,
+                           lapack_complex_double* h, lapack_int ldh,
+                           lapack_complex_double* w, lapack_complex_double* z,
+                           lapack_int ldz );
+
+lapack_int LAPACKE_clacgv( lapack_int n, lapack_complex_float* x,
+                           lapack_int incx );
+lapack_int LAPACKE_zlacgv( lapack_int n, lapack_complex_double* x,
+                           lapack_int incx );
+
+lapack_int LAPACKE_slacpy( int matrix_order, char uplo, lapack_int m,
+                           lapack_int n, const float* a, lapack_int lda, float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_dlacpy( int matrix_order, char uplo, lapack_int m,
+                           lapack_int n, const double* a, lapack_int lda, double* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_clacpy( int matrix_order, char uplo, lapack_int m,
+                           lapack_int n, const lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_zlacpy( int matrix_order, char uplo, lapack_int m,
+                           lapack_int n, const lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb );
+
+lapack_int LAPACKE_zlag2c( int matrix_order, lapack_int m, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_float* sa, lapack_int ldsa );
+
+lapack_int LAPACKE_slag2d( int matrix_order, lapack_int m, lapack_int n,
+                           const float* sa, lapack_int ldsa, double* a,
+                           lapack_int lda );
+
+lapack_int LAPACKE_dlag2s( int matrix_order, lapack_int m, lapack_int n,
+                           const double* a, lapack_int lda, float* sa,
+                           lapack_int ldsa );
+
+lapack_int LAPACKE_clag2z( int matrix_order, lapack_int m, lapack_int n,
+                           const lapack_complex_float* sa, lapack_int ldsa,
+                           lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_slagge( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku, const float* d,
+                           float* a, lapack_int lda, lapack_int* iseed );
+lapack_int LAPACKE_dlagge( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku, const double* d,
+                           double* a, lapack_int lda, lapack_int* iseed );
+lapack_int LAPACKE_clagge( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku, const float* d,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* iseed );
+lapack_int LAPACKE_zlagge( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int kl, lapack_int ku, const double* d,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* iseed );
+
+float LAPACKE_slamch( char cmach );
+double LAPACKE_dlamch( char cmach );
+
+float LAPACKE_slange( int matrix_order, char norm, lapack_int m,
+                           lapack_int n, const float* a, lapack_int lda );
+double LAPACKE_dlange( int matrix_order, char norm, lapack_int m,
+                           lapack_int n, const double* a, lapack_int lda );
+float LAPACKE_clange( int matrix_order, char norm, lapack_int m,
+                           lapack_int n, const lapack_complex_float* a,
+                           lapack_int lda );
+double LAPACKE_zlange( int matrix_order, char norm, lapack_int m,
+                           lapack_int n, const lapack_complex_double* a,
+                           lapack_int lda );
+
+float LAPACKE_clanhe( int matrix_order, char norm, char uplo, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda );
+double LAPACKE_zlanhe( int matrix_order, char norm, char uplo, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda );
+
+float LAPACKE_slansy( int matrix_order, char norm, char uplo, lapack_int n,
+                           const float* a, lapack_int lda );
+double LAPACKE_dlansy( int matrix_order, char norm, char uplo, lapack_int n,
+                           const double* a, lapack_int lda );
+float LAPACKE_clansy( int matrix_order, char norm, char uplo, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda );
+double LAPACKE_zlansy( int matrix_order, char norm, char uplo, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda );
+
+float LAPACKE_slantr( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int m, lapack_int n, const float* a,
+                           lapack_int lda );
+double LAPACKE_dlantr( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int m, lapack_int n, const double* a,
+                           lapack_int lda );
+float LAPACKE_clantr( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int m, lapack_int n, const lapack_complex_float* a,
+                           lapack_int lda );
+double LAPACKE_zlantr( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int m, lapack_int n, const lapack_complex_double* a,
+                           lapack_int lda );
+
+
+lapack_int LAPACKE_slarfb( int matrix_order, char side, char trans, char direct,
+                           char storev, lapack_int m, lapack_int n,
+                           lapack_int k, const float* v, lapack_int ldv,
+                           const float* t, lapack_int ldt, float* c,
+                           lapack_int ldc );
+lapack_int LAPACKE_dlarfb( int matrix_order, char side, char trans, char direct,
+                           char storev, lapack_int m, lapack_int n,
+                           lapack_int k, const double* v, lapack_int ldv,
+                           const double* t, lapack_int ldt, double* c,
+                           lapack_int ldc );
+lapack_int LAPACKE_clarfb( int matrix_order, char side, char trans, char direct,
+                           char storev, lapack_int m, lapack_int n,
+                           lapack_int k, const lapack_complex_float* v,
+                           lapack_int ldv, const lapack_complex_float* t,
+                           lapack_int ldt, lapack_complex_float* c,
+                           lapack_int ldc );
+lapack_int LAPACKE_zlarfb( int matrix_order, char side, char trans, char direct,
+                           char storev, lapack_int m, lapack_int n,
+                           lapack_int k, const lapack_complex_double* v,
+                           lapack_int ldv, const lapack_complex_double* t,
+                           lapack_int ldt, lapack_complex_double* c,
+                           lapack_int ldc );
+
+lapack_int LAPACKE_slarfg( lapack_int n, float* alpha, float* x,
+                           lapack_int incx, float* tau );
+lapack_int LAPACKE_dlarfg( lapack_int n, double* alpha, double* x,
+                           lapack_int incx, double* tau );
+lapack_int LAPACKE_clarfg( lapack_int n, lapack_complex_float* alpha,
+                           lapack_complex_float* x, lapack_int incx,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_zlarfg( lapack_int n, lapack_complex_double* alpha,
+                           lapack_complex_double* x, lapack_int incx,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_slarft( int matrix_order, char direct, char storev,
+                           lapack_int n, lapack_int k, const float* v,
+                           lapack_int ldv, const float* tau, float* t,
+                           lapack_int ldt );
+lapack_int LAPACKE_dlarft( int matrix_order, char direct, char storev,
+                           lapack_int n, lapack_int k, const double* v,
+                           lapack_int ldv, const double* tau, double* t,
+                           lapack_int ldt );
+lapack_int LAPACKE_clarft( int matrix_order, char direct, char storev,
+                           lapack_int n, lapack_int k,
+                           const lapack_complex_float* v, lapack_int ldv,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* t, lapack_int ldt );
+lapack_int LAPACKE_zlarft( int matrix_order, char direct, char storev,
+                           lapack_int n, lapack_int k,
+                           const lapack_complex_double* v, lapack_int ldv,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_slarfx( int matrix_order, char side, lapack_int m,
+                           lapack_int n, const float* v, float tau, float* c,
+                           lapack_int ldc, float* work );
+lapack_int LAPACKE_dlarfx( int matrix_order, char side, lapack_int m,
+                           lapack_int n, const double* v, double tau, double* c,
+                           lapack_int ldc, double* work );
+lapack_int LAPACKE_clarfx( int matrix_order, char side, lapack_int m,
+                           lapack_int n, const lapack_complex_float* v,
+                           lapack_complex_float tau, lapack_complex_float* c,
+                           lapack_int ldc, lapack_complex_float* work );
+lapack_int LAPACKE_zlarfx( int matrix_order, char side, lapack_int m,
+                           lapack_int n, const lapack_complex_double* v,
+                           lapack_complex_double tau, lapack_complex_double* c,
+                           lapack_int ldc, lapack_complex_double* work );
+
+lapack_int LAPACKE_slarnv( lapack_int idist, lapack_int* iseed, lapack_int n,
+                           float* x );
+lapack_int LAPACKE_dlarnv( lapack_int idist, lapack_int* iseed, lapack_int n,
+                           double* x );
+lapack_int LAPACKE_clarnv( lapack_int idist, lapack_int* iseed, lapack_int n,
+                           lapack_complex_float* x );
+lapack_int LAPACKE_zlarnv( lapack_int idist, lapack_int* iseed, lapack_int n,
+                           lapack_complex_double* x );
+
+lapack_int LAPACKE_slaset( int matrix_order, char uplo, lapack_int m,
+                           lapack_int n, float alpha, float beta, float* a,
+                           lapack_int lda );
+lapack_int LAPACKE_dlaset( int matrix_order, char uplo, lapack_int m,
+                           lapack_int n, double alpha, double beta, double* a,
+                           lapack_int lda );
+lapack_int LAPACKE_claset( int matrix_order, char uplo, lapack_int m,
+                           lapack_int n, lapack_complex_float alpha,
+                           lapack_complex_float beta, lapack_complex_float* a,
+                           lapack_int lda );
+lapack_int LAPACKE_zlaset( int matrix_order, char uplo, lapack_int m,
+                           lapack_int n, lapack_complex_double alpha,
+                           lapack_complex_double beta, lapack_complex_double* a,
+                           lapack_int lda );
+
+lapack_int LAPACKE_slasrt( char id, lapack_int n, float* d );
+lapack_int LAPACKE_dlasrt( char id, lapack_int n, double* d );
+
+lapack_int LAPACKE_slaswp( int matrix_order, lapack_int n, float* a,
+                           lapack_int lda, lapack_int k1, lapack_int k2,
+                           const lapack_int* ipiv, lapack_int incx );
+lapack_int LAPACKE_dlaswp( int matrix_order, lapack_int n, double* a,
+                           lapack_int lda, lapack_int k1, lapack_int k2,
+                           const lapack_int* ipiv, lapack_int incx );
+lapack_int LAPACKE_claswp( int matrix_order, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int k1, lapack_int k2, const lapack_int* ipiv,
+                           lapack_int incx );
+lapack_int LAPACKE_zlaswp( int matrix_order, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int k1, lapack_int k2, const lapack_int* ipiv,
+                           lapack_int incx );
+
+lapack_int LAPACKE_slatms( int matrix_order, lapack_int m, lapack_int n,
+                           char dist, lapack_int* iseed, char sym, float* d,
+                           lapack_int mode, float cond, float dmax,
+                           lapack_int kl, lapack_int ku, char pack, float* a,
+                           lapack_int lda );
+lapack_int LAPACKE_dlatms( int matrix_order, lapack_int m, lapack_int n,
+                           char dist, lapack_int* iseed, char sym, double* d,
+                           lapack_int mode, double cond, double dmax,
+                           lapack_int kl, lapack_int ku, char pack, double* a,
+                           lapack_int lda );
+lapack_int LAPACKE_clatms( int matrix_order, lapack_int m, lapack_int n,
+                           char dist, lapack_int* iseed, char sym, float* d,
+                           lapack_int mode, float cond, float dmax,
+                           lapack_int kl, lapack_int ku, char pack,
+                           lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zlatms( int matrix_order, lapack_int m, lapack_int n,
+                           char dist, lapack_int* iseed, char sym, double* d,
+                           lapack_int mode, double cond, double dmax,
+                           lapack_int kl, lapack_int ku, char pack,
+                           lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_slauum( int matrix_order, char uplo, lapack_int n, float* a,
+                           lapack_int lda );
+lapack_int LAPACKE_dlauum( int matrix_order, char uplo, lapack_int n, double* a,
+                           lapack_int lda );
+lapack_int LAPACKE_clauum( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zlauum( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_sopgtr( int matrix_order, char uplo, lapack_int n,
+                           const float* ap, const float* tau, float* q,
+                           lapack_int ldq );
+lapack_int LAPACKE_dopgtr( int matrix_order, char uplo, lapack_int n,
+                           const double* ap, const double* tau, double* q,
+                           lapack_int ldq );
+
+lapack_int LAPACKE_sopmtr( int matrix_order, char side, char uplo, char trans,
+                           lapack_int m, lapack_int n, const float* ap,
+                           const float* tau, float* c, lapack_int ldc );
+lapack_int LAPACKE_dopmtr( int matrix_order, char side, char uplo, char trans,
+                           lapack_int m, lapack_int n, const double* ap,
+                           const double* tau, double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sorgbr( int matrix_order, char vect, lapack_int m,
+                           lapack_int n, lapack_int k, float* a, lapack_int lda,
+                           const float* tau );
+lapack_int LAPACKE_dorgbr( int matrix_order, char vect, lapack_int m,
+                           lapack_int n, lapack_int k, double* a,
+                           lapack_int lda, const double* tau );
+
+lapack_int LAPACKE_sorghr( int matrix_order, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, float* a, lapack_int lda,
+                           const float* tau );
+lapack_int LAPACKE_dorghr( int matrix_order, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, double* a, lapack_int lda,
+                           const double* tau );
+
+lapack_int LAPACKE_sorglq( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, float* a, lapack_int lda,
+                           const float* tau );
+lapack_int LAPACKE_dorglq( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, double* a, lapack_int lda,
+                           const double* tau );
+
+lapack_int LAPACKE_sorgql( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, float* a, lapack_int lda,
+                           const float* tau );
+lapack_int LAPACKE_dorgql( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, double* a, lapack_int lda,
+                           const double* tau );
+
+lapack_int LAPACKE_sorgqr( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, float* a, lapack_int lda,
+                           const float* tau );
+lapack_int LAPACKE_dorgqr( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, double* a, lapack_int lda,
+                           const double* tau );
+
+lapack_int LAPACKE_sorgrq( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, float* a, lapack_int lda,
+                           const float* tau );
+lapack_int LAPACKE_dorgrq( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, double* a, lapack_int lda,
+                           const double* tau );
+
+lapack_int LAPACKE_sorgtr( int matrix_order, char uplo, lapack_int n, float* a,
+                           lapack_int lda, const float* tau );
+lapack_int LAPACKE_dorgtr( int matrix_order, char uplo, lapack_int n, double* a,
+                           lapack_int lda, const double* tau );
+
+lapack_int LAPACKE_sormbr( int matrix_order, char vect, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const float* a, lapack_int lda, const float* tau,
+                           float* c, lapack_int ldc );
+lapack_int LAPACKE_dormbr( int matrix_order, char vect, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const double* a, lapack_int lda, const double* tau,
+                           double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sormhr( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, const float* a, lapack_int lda,
+                           const float* tau, float* c, lapack_int ldc );
+lapack_int LAPACKE_dormhr( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, const double* a, lapack_int lda,
+                           const double* tau, double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sormlq( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const float* a, lapack_int lda, const float* tau,
+                           float* c, lapack_int ldc );
+lapack_int LAPACKE_dormlq( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const double* a, lapack_int lda, const double* tau,
+                           double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sormql( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const float* a, lapack_int lda, const float* tau,
+                           float* c, lapack_int ldc );
+lapack_int LAPACKE_dormql( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const double* a, lapack_int lda, const double* tau,
+                           double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sormqr( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const float* a, lapack_int lda, const float* tau,
+                           float* c, lapack_int ldc );
+lapack_int LAPACKE_dormqr( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const double* a, lapack_int lda, const double* tau,
+                           double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sormrq( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const float* a, lapack_int lda, const float* tau,
+                           float* c, lapack_int ldc );
+lapack_int LAPACKE_dormrq( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const double* a, lapack_int lda, const double* tau,
+                           double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sormrz( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           lapack_int l, const float* a, lapack_int lda,
+                           const float* tau, float* c, lapack_int ldc );
+lapack_int LAPACKE_dormrz( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           lapack_int l, const double* a, lapack_int lda,
+                           const double* tau, double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sormtr( int matrix_order, char side, char uplo, char trans,
+                           lapack_int m, lapack_int n, const float* a,
+                           lapack_int lda, const float* tau, float* c,
+                           lapack_int ldc );
+lapack_int LAPACKE_dormtr( int matrix_order, char side, char uplo, char trans,
+                           lapack_int m, lapack_int n, const double* a,
+                           lapack_int lda, const double* tau, double* c,
+                           lapack_int ldc );
+
+lapack_int LAPACKE_spbcon( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, const float* ab, lapack_int ldab,
+                           float anorm, float* rcond );
+lapack_int LAPACKE_dpbcon( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, const double* ab, lapack_int ldab,
+                           double anorm, double* rcond );
+lapack_int LAPACKE_cpbcon( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, const lapack_complex_float* ab,
+                           lapack_int ldab, float anorm, float* rcond );
+lapack_int LAPACKE_zpbcon( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, const lapack_complex_double* ab,
+                           lapack_int ldab, double anorm, double* rcond );
+
+lapack_int LAPACKE_spbequ( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, const float* ab, lapack_int ldab,
+                           float* s, float* scond, float* amax );
+lapack_int LAPACKE_dpbequ( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, const double* ab, lapack_int ldab,
+                           double* s, double* scond, double* amax );
+lapack_int LAPACKE_cpbequ( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, const lapack_complex_float* ab,
+                           lapack_int ldab, float* s, float* scond,
+                           float* amax );
+lapack_int LAPACKE_zpbequ( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, const lapack_complex_double* ab,
+                           lapack_int ldab, double* s, double* scond,
+                           double* amax );
+
+lapack_int LAPACKE_spbrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs, const float* ab,
+                           lapack_int ldab, const float* afb, lapack_int ldafb,
+                           const float* b, lapack_int ldb, float* x,
+                           lapack_int ldx, float* ferr, float* berr );
+lapack_int LAPACKE_dpbrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs, const double* ab,
+                           lapack_int ldab, const double* afb, lapack_int ldafb,
+                           const double* b, lapack_int ldb, double* x,
+                           lapack_int ldx, double* ferr, double* berr );
+lapack_int LAPACKE_cpbrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           const lapack_complex_float* afb, lapack_int ldafb,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zpbrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           const lapack_complex_double* afb, lapack_int ldafb,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_spbstf( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kb, float* bb, lapack_int ldbb );
+lapack_int LAPACKE_dpbstf( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kb, double* bb, lapack_int ldbb );
+lapack_int LAPACKE_cpbstf( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kb, lapack_complex_float* bb,
+                           lapack_int ldbb );
+lapack_int LAPACKE_zpbstf( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kb, lapack_complex_double* bb,
+                           lapack_int ldbb );
+
+lapack_int LAPACKE_spbsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int kd, lapack_int nrhs, float* ab,
+                          lapack_int ldab, float* b, lapack_int ldb );
+lapack_int LAPACKE_dpbsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int kd, lapack_int nrhs, double* ab,
+                          lapack_int ldab, double* b, lapack_int ldb );
+lapack_int LAPACKE_cpbsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int kd, lapack_int nrhs,
+                          lapack_complex_float* ab, lapack_int ldab,
+                          lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpbsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int kd, lapack_int nrhs,
+                          lapack_complex_double* ab, lapack_int ldab,
+                          lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_spbsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs, float* ab,
+                           lapack_int ldab, float* afb, lapack_int ldafb,
+                           char* equed, float* s, float* b, lapack_int ldb,
+                           float* x, lapack_int ldx, float* rcond, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_dpbsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs, double* ab,
+                           lapack_int ldab, double* afb, lapack_int ldafb,
+                           char* equed, double* s, double* b, lapack_int ldb,
+                           double* x, lapack_int ldx, double* rcond,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_cpbsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs,
+                           lapack_complex_float* ab, lapack_int ldab,
+                           lapack_complex_float* afb, lapack_int ldafb,
+                           char* equed, float* s, lapack_complex_float* b,
+                           lapack_int ldb, lapack_complex_float* x,
+                           lapack_int ldx, float* rcond, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zpbsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs,
+                           lapack_complex_double* ab, lapack_int ldab,
+                           lapack_complex_double* afb, lapack_int ldafb,
+                           char* equed, double* s, lapack_complex_double* b,
+                           lapack_int ldb, lapack_complex_double* x,
+                           lapack_int ldx, double* rcond, double* ferr,
+                           double* berr );
+
+lapack_int LAPACKE_spbtrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, float* ab, lapack_int ldab );
+lapack_int LAPACKE_dpbtrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, double* ab, lapack_int ldab );
+lapack_int LAPACKE_cpbtrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_complex_float* ab,
+                           lapack_int ldab );
+lapack_int LAPACKE_zpbtrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_complex_double* ab,
+                           lapack_int ldab );
+
+lapack_int LAPACKE_spbtrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs, const float* ab,
+                           lapack_int ldab, float* b, lapack_int ldb );
+lapack_int LAPACKE_dpbtrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs, const double* ab,
+                           lapack_int ldab, double* b, lapack_int ldb );
+lapack_int LAPACKE_cpbtrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpbtrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int kd, lapack_int nrhs,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_spftrf( int matrix_order, char transr, char uplo,
+                           lapack_int n, float* a );
+lapack_int LAPACKE_dpftrf( int matrix_order, char transr, char uplo,
+                           lapack_int n, double* a );
+lapack_int LAPACKE_cpftrf( int matrix_order, char transr, char uplo,
+                           lapack_int n, lapack_complex_float* a );
+lapack_int LAPACKE_zpftrf( int matrix_order, char transr, char uplo,
+                           lapack_int n, lapack_complex_double* a );
+
+lapack_int LAPACKE_spftri( int matrix_order, char transr, char uplo,
+                           lapack_int n, float* a );
+lapack_int LAPACKE_dpftri( int matrix_order, char transr, char uplo,
+                           lapack_int n, double* a );
+lapack_int LAPACKE_cpftri( int matrix_order, char transr, char uplo,
+                           lapack_int n, lapack_complex_float* a );
+lapack_int LAPACKE_zpftri( int matrix_order, char transr, char uplo,
+                           lapack_int n, lapack_complex_double* a );
+
+lapack_int LAPACKE_spftrs( int matrix_order, char transr, char uplo,
+                           lapack_int n, lapack_int nrhs, const float* a,
+                           float* b, lapack_int ldb );
+lapack_int LAPACKE_dpftrs( int matrix_order, char transr, char uplo,
+                           lapack_int n, lapack_int nrhs, const double* a,
+                           double* b, lapack_int ldb );
+lapack_int LAPACKE_cpftrs( int matrix_order, char transr, char uplo,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_float* a,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpftrs( int matrix_order, char transr, char uplo,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_double* a,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_spocon( int matrix_order, char uplo, lapack_int n,
+                           const float* a, lapack_int lda, float anorm,
+                           float* rcond );
+lapack_int LAPACKE_dpocon( int matrix_order, char uplo, lapack_int n,
+                           const double* a, lapack_int lda, double anorm,
+                           double* rcond );
+lapack_int LAPACKE_cpocon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           float anorm, float* rcond );
+lapack_int LAPACKE_zpocon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           double anorm, double* rcond );
+
+lapack_int LAPACKE_spoequ( int matrix_order, lapack_int n, const float* a,
+                           lapack_int lda, float* s, float* scond,
+                           float* amax );
+lapack_int LAPACKE_dpoequ( int matrix_order, lapack_int n, const double* a,
+                           lapack_int lda, double* s, double* scond,
+                           double* amax );
+lapack_int LAPACKE_cpoequ( int matrix_order, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           float* s, float* scond, float* amax );
+lapack_int LAPACKE_zpoequ( int matrix_order, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           double* s, double* scond, double* amax );
+
+lapack_int LAPACKE_spoequb( int matrix_order, lapack_int n, const float* a,
+                            lapack_int lda, float* s, float* scond,
+                            float* amax );
+lapack_int LAPACKE_dpoequb( int matrix_order, lapack_int n, const double* a,
+                            lapack_int lda, double* s, double* scond,
+                            double* amax );
+lapack_int LAPACKE_cpoequb( int matrix_order, lapack_int n,
+                            const lapack_complex_float* a, lapack_int lda,
+                            float* s, float* scond, float* amax );
+lapack_int LAPACKE_zpoequb( int matrix_order, lapack_int n,
+                            const lapack_complex_double* a, lapack_int lda,
+                            double* s, double* scond, double* amax );
+
+lapack_int LAPACKE_sporfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* a, lapack_int lda,
+                           const float* af, lapack_int ldaf, const float* b,
+                           lapack_int ldb, float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_dporfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* a, lapack_int lda,
+                           const double* af, lapack_int ldaf, const double* b,
+                           lapack_int ldb, double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_cporfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* af,
+                           lapack_int ldaf, const lapack_complex_float* b,
+                           lapack_int ldb, lapack_complex_float* x,
+                           lapack_int ldx, float* ferr, float* berr );
+lapack_int LAPACKE_zporfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* af,
+                           lapack_int ldaf, const lapack_complex_double* b,
+                           lapack_int ldb, lapack_complex_double* x,
+                           lapack_int ldx, double* ferr, double* berr );
+
+lapack_int LAPACKE_sporfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs, const float* a,
+                            lapack_int lda, const float* af, lapack_int ldaf,
+                            const float* s, const float* b, lapack_int ldb,
+                            float* x, lapack_int ldx, float* rcond, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_dporfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs, const double* a,
+                            lapack_int lda, const double* af, lapack_int ldaf,
+                            const double* s, const double* b, lapack_int ldb,
+                            double* x, lapack_int ldx, double* rcond,
+                            double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+lapack_int LAPACKE_cporfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs,
+                            const lapack_complex_float* a, lapack_int lda,
+                            const lapack_complex_float* af, lapack_int ldaf,
+                            const float* s, const lapack_complex_float* b,
+                            lapack_int ldb, lapack_complex_float* x,
+                            lapack_int ldx, float* rcond, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_zporfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs,
+                            const lapack_complex_double* a, lapack_int lda,
+                            const lapack_complex_double* af, lapack_int ldaf,
+                            const double* s, const lapack_complex_double* b,
+                            lapack_int ldb, lapack_complex_double* x,
+                            lapack_int ldx, double* rcond, double* berr,
+                            lapack_int n_err_bnds, double* err_bnds_norm,
+                            double* err_bnds_comp, lapack_int nparams,
+                            double* params );
+
+lapack_int LAPACKE_sposv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, float* a, lapack_int lda, float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_dposv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, double* a, lapack_int lda, double* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_cposv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_float* a,
+                          lapack_int lda, lapack_complex_float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_zposv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_double* a,
+                          lapack_int lda, lapack_complex_double* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_dsposv( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, double* a, lapack_int lda,
+                           double* b, lapack_int ldb, double* x, lapack_int ldx,
+                           lapack_int* iter );
+lapack_int LAPACKE_zcposv( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, lapack_complex_double* x,
+                           lapack_int ldx, lapack_int* iter );
+
+lapack_int LAPACKE_sposvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, float* a, lapack_int lda, float* af,
+                           lapack_int ldaf, char* equed, float* s, float* b,
+                           lapack_int ldb, float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr );
+lapack_int LAPACKE_dposvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, double* a, lapack_int lda,
+                           double* af, lapack_int ldaf, char* equed, double* s,
+                           double* b, lapack_int ldb, double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+lapack_int LAPACKE_cposvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* af,
+                           lapack_int ldaf, char* equed, float* s,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr );
+lapack_int LAPACKE_zposvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* af,
+                           lapack_int ldaf, char* equed, double* s,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+
+lapack_int LAPACKE_sposvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs, float* a,
+                            lapack_int lda, float* af, lapack_int ldaf,
+                            char* equed, float* s, float* b, lapack_int ldb,
+                            float* x, lapack_int ldx, float* rcond,
+                            float* rpvgrw, float* berr, lapack_int n_err_bnds,
+                            float* err_bnds_norm, float* err_bnds_comp,
+                            lapack_int nparams, float* params );
+lapack_int LAPACKE_dposvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs, double* a,
+                            lapack_int lda, double* af, lapack_int ldaf,
+                            char* equed, double* s, double* b, lapack_int ldb,
+                            double* x, lapack_int ldx, double* rcond,
+                            double* rpvgrw, double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+lapack_int LAPACKE_cposvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* af, lapack_int ldaf,
+                            char* equed, float* s, lapack_complex_float* b,
+                            lapack_int ldb, lapack_complex_float* x,
+                            lapack_int ldx, float* rcond, float* rpvgrw,
+                            float* berr, lapack_int n_err_bnds,
+                            float* err_bnds_norm, float* err_bnds_comp,
+                            lapack_int nparams, float* params );
+lapack_int LAPACKE_zposvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* af, lapack_int ldaf,
+                            char* equed, double* s, lapack_complex_double* b,
+                            lapack_int ldb, lapack_complex_double* x,
+                            lapack_int ldx, double* rcond, double* rpvgrw,
+                            double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+
+lapack_int LAPACKE_spotrf( int matrix_order, char uplo, lapack_int n, float* a,
+                           lapack_int lda );
+lapack_int LAPACKE_dpotrf( int matrix_order, char uplo, lapack_int n, double* a,
+                           lapack_int lda );
+lapack_int LAPACKE_cpotrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zpotrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_spotri( int matrix_order, char uplo, lapack_int n, float* a,
+                           lapack_int lda );
+lapack_int LAPACKE_dpotri( int matrix_order, char uplo, lapack_int n, double* a,
+                           lapack_int lda );
+lapack_int LAPACKE_cpotri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zpotri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_spotrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* a, lapack_int lda,
+                           float* b, lapack_int ldb );
+lapack_int LAPACKE_dpotrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* a, lapack_int lda,
+                           double* b, lapack_int ldb );
+lapack_int LAPACKE_cpotrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_zpotrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb );
+
+lapack_int LAPACKE_sppcon( int matrix_order, char uplo, lapack_int n,
+                           const float* ap, float anorm, float* rcond );
+lapack_int LAPACKE_dppcon( int matrix_order, char uplo, lapack_int n,
+                           const double* ap, double anorm, double* rcond );
+lapack_int LAPACKE_cppcon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* ap, float anorm,
+                           float* rcond );
+lapack_int LAPACKE_zppcon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* ap, double anorm,
+                           double* rcond );
+
+lapack_int LAPACKE_sppequ( int matrix_order, char uplo, lapack_int n,
+                           const float* ap, float* s, float* scond,
+                           float* amax );
+lapack_int LAPACKE_dppequ( int matrix_order, char uplo, lapack_int n,
+                           const double* ap, double* s, double* scond,
+                           double* amax );
+lapack_int LAPACKE_cppequ( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* ap, float* s,
+                           float* scond, float* amax );
+lapack_int LAPACKE_zppequ( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* ap, double* s,
+                           double* scond, double* amax );
+
+lapack_int LAPACKE_spprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* ap, const float* afp,
+                           const float* b, lapack_int ldb, float* x,
+                           lapack_int ldx, float* ferr, float* berr );
+lapack_int LAPACKE_dpprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* ap, const double* afp,
+                           const double* b, lapack_int ldb, double* x,
+                           lapack_int ldx, double* ferr, double* berr );
+lapack_int LAPACKE_cpprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* ap,
+                           const lapack_complex_float* afp,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zpprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* ap,
+                           const lapack_complex_double* afp,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_sppsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, float* ap, float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_dppsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, double* ap, double* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_cppsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_float* ap,
+                          lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zppsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_double* ap,
+                          lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sppsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, float* ap, float* afp, char* equed,
+                           float* s, float* b, lapack_int ldb, float* x,
+                           lapack_int ldx, float* rcond, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_dppsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, double* ap, double* afp,
+                           char* equed, double* s, double* b, lapack_int ldb,
+                           double* x, lapack_int ldx, double* rcond,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_cppsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, lapack_complex_float* ap,
+                           lapack_complex_float* afp, char* equed, float* s,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr );
+lapack_int LAPACKE_zppsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, lapack_complex_double* ap,
+                           lapack_complex_double* afp, char* equed, double* s,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+
+lapack_int LAPACKE_spptrf( int matrix_order, char uplo, lapack_int n,
+                           float* ap );
+lapack_int LAPACKE_dpptrf( int matrix_order, char uplo, lapack_int n,
+                           double* ap );
+lapack_int LAPACKE_cpptrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* ap );
+lapack_int LAPACKE_zpptrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* ap );
+
+lapack_int LAPACKE_spptri( int matrix_order, char uplo, lapack_int n,
+                           float* ap );
+lapack_int LAPACKE_dpptri( int matrix_order, char uplo, lapack_int n,
+                           double* ap );
+lapack_int LAPACKE_cpptri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* ap );
+lapack_int LAPACKE_zpptri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* ap );
+
+lapack_int LAPACKE_spptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* ap, float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_dpptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* ap, double* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_cpptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* ap,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* ap,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_spstrf( int matrix_order, char uplo, lapack_int n, float* a,
+                           lapack_int lda, lapack_int* piv, lapack_int* rank,
+                           float tol );
+lapack_int LAPACKE_dpstrf( int matrix_order, char uplo, lapack_int n, double* a,
+                           lapack_int lda, lapack_int* piv, lapack_int* rank,
+                           double tol );
+lapack_int LAPACKE_cpstrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* piv, lapack_int* rank, float tol );
+lapack_int LAPACKE_zpstrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* piv, lapack_int* rank, double tol );
+
+lapack_int LAPACKE_sptcon( lapack_int n, const float* d, const float* e,
+                           float anorm, float* rcond );
+lapack_int LAPACKE_dptcon( lapack_int n, const double* d, const double* e,
+                           double anorm, double* rcond );
+lapack_int LAPACKE_cptcon( lapack_int n, const float* d,
+                           const lapack_complex_float* e, float anorm,
+                           float* rcond );
+lapack_int LAPACKE_zptcon( lapack_int n, const double* d,
+                           const lapack_complex_double* e, double anorm,
+                           double* rcond );
+
+lapack_int LAPACKE_spteqr( int matrix_order, char compz, lapack_int n, float* d,
+                           float* e, float* z, lapack_int ldz );
+lapack_int LAPACKE_dpteqr( int matrix_order, char compz, lapack_int n,
+                           double* d, double* e, double* z, lapack_int ldz );
+lapack_int LAPACKE_cpteqr( int matrix_order, char compz, lapack_int n, float* d,
+                           float* e, lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zpteqr( int matrix_order, char compz, lapack_int n,
+                           double* d, double* e, lapack_complex_double* z,
+                           lapack_int ldz );
+
+lapack_int LAPACKE_sptrfs( int matrix_order, lapack_int n, lapack_int nrhs,
+                           const float* d, const float* e, const float* df,
+                           const float* ef, const float* b, lapack_int ldb,
+                           float* x, lapack_int ldx, float* ferr, float* berr );
+lapack_int LAPACKE_dptrfs( int matrix_order, lapack_int n, lapack_int nrhs,
+                           const double* d, const double* e, const double* df,
+                           const double* ef, const double* b, lapack_int ldb,
+                           double* x, lapack_int ldx, double* ferr,
+                           double* berr );
+lapack_int LAPACKE_cptrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* d,
+                           const lapack_complex_float* e, const float* df,
+                           const lapack_complex_float* ef,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zptrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* d,
+                           const lapack_complex_double* e, const double* df,
+                           const lapack_complex_double* ef,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_sptsv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          float* d, float* e, float* b, lapack_int ldb );
+lapack_int LAPACKE_dptsv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          double* d, double* e, double* b, lapack_int ldb );
+lapack_int LAPACKE_cptsv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          float* d, lapack_complex_float* e,
+                          lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zptsv( int matrix_order, lapack_int n, lapack_int nrhs,
+                          double* d, lapack_complex_double* e,
+                          lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sptsvx( int matrix_order, char fact, lapack_int n,
+                           lapack_int nrhs, const float* d, const float* e,
+                           float* df, float* ef, const float* b, lapack_int ldb,
+                           float* x, lapack_int ldx, float* rcond, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_dptsvx( int matrix_order, char fact, lapack_int n,
+                           lapack_int nrhs, const double* d, const double* e,
+                           double* df, double* ef, const double* b,
+                           lapack_int ldb, double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+lapack_int LAPACKE_cptsvx( int matrix_order, char fact, lapack_int n,
+                           lapack_int nrhs, const float* d,
+                           const lapack_complex_float* e, float* df,
+                           lapack_complex_float* ef,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr );
+lapack_int LAPACKE_zptsvx( int matrix_order, char fact, lapack_int n,
+                           lapack_int nrhs, const double* d,
+                           const lapack_complex_double* e, double* df,
+                           lapack_complex_double* ef,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+
+lapack_int LAPACKE_spttrf( lapack_int n, float* d, float* e );
+lapack_int LAPACKE_dpttrf( lapack_int n, double* d, double* e );
+lapack_int LAPACKE_cpttrf( lapack_int n, float* d, lapack_complex_float* e );
+lapack_int LAPACKE_zpttrf( lapack_int n, double* d, lapack_complex_double* e );
+
+lapack_int LAPACKE_spttrs( int matrix_order, lapack_int n, lapack_int nrhs,
+                           const float* d, const float* e, float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_dpttrs( int matrix_order, lapack_int n, lapack_int nrhs,
+                           const double* d, const double* e, double* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_cpttrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* d,
+                           const lapack_complex_float* e,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpttrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* d,
+                           const lapack_complex_double* e,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_ssbev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_int kd, float* ab, lapack_int ldab, float* w,
+                          float* z, lapack_int ldz );
+lapack_int LAPACKE_dsbev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_int kd, double* ab, lapack_int ldab, double* w,
+                          double* z, lapack_int ldz );
+
+lapack_int LAPACKE_ssbevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_int kd, float* ab, lapack_int ldab, float* w,
+                           float* z, lapack_int ldz );
+lapack_int LAPACKE_dsbevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_int kd, double* ab, lapack_int ldab,
+                           double* w, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_ssbevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_int kd, float* ab,
+                           lapack_int ldab, float* q, lapack_int ldq, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* ifail );
+lapack_int LAPACKE_dsbevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_int kd, double* ab,
+                           lapack_int ldab, double* q, lapack_int ldq,
+                           double vl, double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w, double* z,
+                           lapack_int ldz, lapack_int* ifail );
+
+lapack_int LAPACKE_ssbgst( int matrix_order, char vect, char uplo, lapack_int n,
+                           lapack_int ka, lapack_int kb, float* ab,
+                           lapack_int ldab, const float* bb, lapack_int ldbb,
+                           float* x, lapack_int ldx );
+lapack_int LAPACKE_dsbgst( int matrix_order, char vect, char uplo, lapack_int n,
+                           lapack_int ka, lapack_int kb, double* ab,
+                           lapack_int ldab, const double* bb, lapack_int ldbb,
+                           double* x, lapack_int ldx );
+
+lapack_int LAPACKE_ssbgv( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_int ka, lapack_int kb, float* ab,
+                          lapack_int ldab, float* bb, lapack_int ldbb, float* w,
+                          float* z, lapack_int ldz );
+lapack_int LAPACKE_dsbgv( int matrix_order, char jobz, char uplo, lapack_int n,
+                          lapack_int ka, lapack_int kb, double* ab,
+                          lapack_int ldab, double* bb, lapack_int ldbb,
+                          double* w, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_ssbgvd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_int ka, lapack_int kb, float* ab,
+                           lapack_int ldab, float* bb, lapack_int ldbb,
+                           float* w, float* z, lapack_int ldz );
+lapack_int LAPACKE_dsbgvd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           lapack_int ka, lapack_int kb, double* ab,
+                           lapack_int ldab, double* bb, lapack_int ldbb,
+                           double* w, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_ssbgvx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_int ka, lapack_int kb,
+                           float* ab, lapack_int ldab, float* bb,
+                           lapack_int ldbb, float* q, lapack_int ldq, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* ifail );
+lapack_int LAPACKE_dsbgvx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, lapack_int ka, lapack_int kb,
+                           double* ab, lapack_int ldab, double* bb,
+                           lapack_int ldbb, double* q, lapack_int ldq,
+                           double vl, double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w, double* z,
+                           lapack_int ldz, lapack_int* ifail );
+
+lapack_int LAPACKE_ssbtrd( int matrix_order, char vect, char uplo, lapack_int n,
+                           lapack_int kd, float* ab, lapack_int ldab, float* d,
+                           float* e, float* q, lapack_int ldq );
+lapack_int LAPACKE_dsbtrd( int matrix_order, char vect, char uplo, lapack_int n,
+                           lapack_int kd, double* ab, lapack_int ldab,
+                           double* d, double* e, double* q, lapack_int ldq );
+
+lapack_int LAPACKE_ssfrk( int matrix_order, char transr, char uplo, char trans,
+                          lapack_int n, lapack_int k, float alpha,
+                          const float* a, lapack_int lda, float beta,
+                          float* c );
+lapack_int LAPACKE_dsfrk( int matrix_order, char transr, char uplo, char trans,
+                          lapack_int n, lapack_int k, double alpha,
+                          const double* a, lapack_int lda, double beta,
+                          double* c );
+
+lapack_int LAPACKE_sspcon( int matrix_order, char uplo, lapack_int n,
+                           const float* ap, const lapack_int* ipiv, float anorm,
+                           float* rcond );
+lapack_int LAPACKE_dspcon( int matrix_order, char uplo, lapack_int n,
+                           const double* ap, const lapack_int* ipiv,
+                           double anorm, double* rcond );
+lapack_int LAPACKE_cspcon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* ap,
+                           const lapack_int* ipiv, float anorm, float* rcond );
+lapack_int LAPACKE_zspcon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* ap,
+                           const lapack_int* ipiv, double anorm,
+                           double* rcond );
+
+lapack_int LAPACKE_sspev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          float* ap, float* w, float* z, lapack_int ldz );
+lapack_int LAPACKE_dspev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          double* ap, double* w, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_sspevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           float* ap, float* w, float* z, lapack_int ldz );
+lapack_int LAPACKE_dspevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           double* ap, double* w, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_sspevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, float* ap, float vl, float vu,
+                           lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* ifail );
+lapack_int LAPACKE_dspevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, double* ap, double vl, double vu,
+                           lapack_int il, lapack_int iu, double abstol,
+                           lapack_int* m, double* w, double* z, lapack_int ldz,
+                           lapack_int* ifail );
+
+lapack_int LAPACKE_sspgst( int matrix_order, lapack_int itype, char uplo,
+                           lapack_int n, float* ap, const float* bp );
+lapack_int LAPACKE_dspgst( int matrix_order, lapack_int itype, char uplo,
+                           lapack_int n, double* ap, const double* bp );
+
+lapack_int LAPACKE_sspgv( int matrix_order, lapack_int itype, char jobz,
+                          char uplo, lapack_int n, float* ap, float* bp,
+                          float* w, float* z, lapack_int ldz );
+lapack_int LAPACKE_dspgv( int matrix_order, lapack_int itype, char jobz,
+                          char uplo, lapack_int n, double* ap, double* bp,
+                          double* w, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_sspgvd( int matrix_order, lapack_int itype, char jobz,
+                           char uplo, lapack_int n, float* ap, float* bp,
+                           float* w, float* z, lapack_int ldz );
+lapack_int LAPACKE_dspgvd( int matrix_order, lapack_int itype, char jobz,
+                           char uplo, lapack_int n, double* ap, double* bp,
+                           double* w, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_sspgvx( int matrix_order, lapack_int itype, char jobz,
+                           char range, char uplo, lapack_int n, float* ap,
+                           float* bp, float vl, float vu, lapack_int il,
+                           lapack_int iu, float abstol, lapack_int* m, float* w,
+                           float* z, lapack_int ldz, lapack_int* ifail );
+lapack_int LAPACKE_dspgvx( int matrix_order, lapack_int itype, char jobz,
+                           char range, char uplo, lapack_int n, double* ap,
+                           double* bp, double vl, double vu, lapack_int il,
+                           lapack_int iu, double abstol, lapack_int* m,
+                           double* w, double* z, lapack_int ldz,
+                           lapack_int* ifail );
+
+lapack_int LAPACKE_ssprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* ap, const float* afp,
+                           const lapack_int* ipiv, const float* b,
+                           lapack_int ldb, float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_dsprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* ap, const double* afp,
+                           const lapack_int* ipiv, const double* b,
+                           lapack_int ldb, double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_csprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* ap,
+                           const lapack_complex_float* afp,
+                           const lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zsprfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* ap,
+                           const lapack_complex_double* afp,
+                           const lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_sspsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, float* ap, lapack_int* ipiv,
+                          float* b, lapack_int ldb );
+lapack_int LAPACKE_dspsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, double* ap, lapack_int* ipiv,
+                          double* b, lapack_int ldb );
+lapack_int LAPACKE_cspsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_float* ap,
+                          lapack_int* ipiv, lapack_complex_float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_zspsv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_double* ap,
+                          lapack_int* ipiv, lapack_complex_double* b,
+                          lapack_int ldb );
+
+lapack_int LAPACKE_sspsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* ap, float* afp,
+                           lapack_int* ipiv, const float* b, lapack_int ldb,
+                           float* x, lapack_int ldx, float* rcond, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_dspsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* ap, double* afp,
+                           lapack_int* ipiv, const double* b, lapack_int ldb,
+                           double* x, lapack_int ldx, double* rcond,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_cspsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* ap,
+                           lapack_complex_float* afp, lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr );
+lapack_int LAPACKE_zspsvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* ap,
+                           lapack_complex_double* afp, lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+
+lapack_int LAPACKE_ssptrd( int matrix_order, char uplo, lapack_int n, float* ap,
+                           float* d, float* e, float* tau );
+lapack_int LAPACKE_dsptrd( int matrix_order, char uplo, lapack_int n,
+                           double* ap, double* d, double* e, double* tau );
+
+lapack_int LAPACKE_ssptrf( int matrix_order, char uplo, lapack_int n, float* ap,
+                           lapack_int* ipiv );
+lapack_int LAPACKE_dsptrf( int matrix_order, char uplo, lapack_int n,
+                           double* ap, lapack_int* ipiv );
+lapack_int LAPACKE_csptrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* ap, lapack_int* ipiv );
+lapack_int LAPACKE_zsptrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* ap, lapack_int* ipiv );
+
+lapack_int LAPACKE_ssptri( int matrix_order, char uplo, lapack_int n, float* ap,
+                           const lapack_int* ipiv );
+lapack_int LAPACKE_dsptri( int matrix_order, char uplo, lapack_int n,
+                           double* ap, const lapack_int* ipiv );
+lapack_int LAPACKE_csptri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* ap, const lapack_int* ipiv );
+lapack_int LAPACKE_zsptri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* ap, const lapack_int* ipiv );
+
+lapack_int LAPACKE_ssptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* ap,
+                           const lapack_int* ipiv, float* b, lapack_int ldb );
+lapack_int LAPACKE_dsptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* ap,
+                           const lapack_int* ipiv, double* b, lapack_int ldb );
+lapack_int LAPACKE_csptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* ap,
+                           const lapack_int* ipiv, lapack_complex_float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_zsptrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* ap,
+                           const lapack_int* ipiv, lapack_complex_double* b,
+                           lapack_int ldb );
+
+lapack_int LAPACKE_sstebz( char range, char order, lapack_int n, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           const float* d, const float* e, lapack_int* m,
+                           lapack_int* nsplit, float* w, lapack_int* iblock,
+                           lapack_int* isplit );
+lapack_int LAPACKE_dstebz( char range, char order, lapack_int n, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, const double* d, const double* e,
+                           lapack_int* m, lapack_int* nsplit, double* w,
+                           lapack_int* iblock, lapack_int* isplit );
+
+lapack_int LAPACKE_sstedc( int matrix_order, char compz, lapack_int n, float* d,
+                           float* e, float* z, lapack_int ldz );
+lapack_int LAPACKE_dstedc( int matrix_order, char compz, lapack_int n,
+                           double* d, double* e, double* z, lapack_int ldz );
+lapack_int LAPACKE_cstedc( int matrix_order, char compz, lapack_int n, float* d,
+                           float* e, lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zstedc( int matrix_order, char compz, lapack_int n,
+                           double* d, double* e, lapack_complex_double* z,
+                           lapack_int ldz );
+
+lapack_int LAPACKE_sstegr( int matrix_order, char jobz, char range,
+                           lapack_int n, float* d, float* e, float vl, float vu,
+                           lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* isuppz );
+lapack_int LAPACKE_dstegr( int matrix_order, char jobz, char range,
+                           lapack_int n, double* d, double* e, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w, double* z,
+                           lapack_int ldz, lapack_int* isuppz );
+lapack_int LAPACKE_cstegr( int matrix_order, char jobz, char range,
+                           lapack_int n, float* d, float* e, float vl, float vu,
+                           lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, lapack_complex_float* z,
+                           lapack_int ldz, lapack_int* isuppz );
+lapack_int LAPACKE_zstegr( int matrix_order, char jobz, char range,
+                           lapack_int n, double* d, double* e, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* isuppz );
+
+lapack_int LAPACKE_sstein( int matrix_order, lapack_int n, const float* d,
+                           const float* e, lapack_int m, const float* w,
+                           const lapack_int* iblock, const lapack_int* isplit,
+                           float* z, lapack_int ldz, lapack_int* ifailv );
+lapack_int LAPACKE_dstein( int matrix_order, lapack_int n, const double* d,
+                           const double* e, lapack_int m, const double* w,
+                           const lapack_int* iblock, const lapack_int* isplit,
+                           double* z, lapack_int ldz, lapack_int* ifailv );
+lapack_int LAPACKE_cstein( int matrix_order, lapack_int n, const float* d,
+                           const float* e, lapack_int m, const float* w,
+                           const lapack_int* iblock, const lapack_int* isplit,
+                           lapack_complex_float* z, lapack_int ldz,
+                           lapack_int* ifailv );
+lapack_int LAPACKE_zstein( int matrix_order, lapack_int n, const double* d,
+                           const double* e, lapack_int m, const double* w,
+                           const lapack_int* iblock, const lapack_int* isplit,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* ifailv );
+
+lapack_int LAPACKE_sstemr( int matrix_order, char jobz, char range,
+                           lapack_int n, float* d, float* e, float vl, float vu,
+                           lapack_int il, lapack_int iu, lapack_int* m,
+                           float* w, float* z, lapack_int ldz, lapack_int nzc,
+                           lapack_int* isuppz, lapack_logical* tryrac );
+lapack_int LAPACKE_dstemr( int matrix_order, char jobz, char range,
+                           lapack_int n, double* d, double* e, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           lapack_int* m, double* w, double* z, lapack_int ldz,
+                           lapack_int nzc, lapack_int* isuppz,
+                           lapack_logical* tryrac );
+lapack_int LAPACKE_cstemr( int matrix_order, char jobz, char range,
+                           lapack_int n, float* d, float* e, float vl, float vu,
+                           lapack_int il, lapack_int iu, lapack_int* m,
+                           float* w, lapack_complex_float* z, lapack_int ldz,
+                           lapack_int nzc, lapack_int* isuppz,
+                           lapack_logical* tryrac );
+lapack_int LAPACKE_zstemr( int matrix_order, char jobz, char range,
+                           lapack_int n, double* d, double* e, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           lapack_int* m, double* w, lapack_complex_double* z,
+                           lapack_int ldz, lapack_int nzc, lapack_int* isuppz,
+                           lapack_logical* tryrac );
+
+lapack_int LAPACKE_ssteqr( int matrix_order, char compz, lapack_int n, float* d,
+                           float* e, float* z, lapack_int ldz );
+lapack_int LAPACKE_dsteqr( int matrix_order, char compz, lapack_int n,
+                           double* d, double* e, double* z, lapack_int ldz );
+lapack_int LAPACKE_csteqr( int matrix_order, char compz, lapack_int n, float* d,
+                           float* e, lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zsteqr( int matrix_order, char compz, lapack_int n,
+                           double* d, double* e, lapack_complex_double* z,
+                           lapack_int ldz );
+
+lapack_int LAPACKE_ssterf( lapack_int n, float* d, float* e );
+lapack_int LAPACKE_dsterf( lapack_int n, double* d, double* e );
+
+lapack_int LAPACKE_sstev( int matrix_order, char jobz, lapack_int n, float* d,
+                          float* e, float* z, lapack_int ldz );
+lapack_int LAPACKE_dstev( int matrix_order, char jobz, lapack_int n, double* d,
+                          double* e, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_sstevd( int matrix_order, char jobz, lapack_int n, float* d,
+                           float* e, float* z, lapack_int ldz );
+lapack_int LAPACKE_dstevd( int matrix_order, char jobz, lapack_int n, double* d,
+                           double* e, double* z, lapack_int ldz );
+
+lapack_int LAPACKE_sstevr( int matrix_order, char jobz, char range,
+                           lapack_int n, float* d, float* e, float vl, float vu,
+                           lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* isuppz );
+lapack_int LAPACKE_dstevr( int matrix_order, char jobz, char range,
+                           lapack_int n, double* d, double* e, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w, double* z,
+                           lapack_int ldz, lapack_int* isuppz );
+
+lapack_int LAPACKE_sstevx( int matrix_order, char jobz, char range,
+                           lapack_int n, float* d, float* e, float vl, float vu,
+                           lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* ifail );
+lapack_int LAPACKE_dstevx( int matrix_order, char jobz, char range,
+                           lapack_int n, double* d, double* e, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w, double* z,
+                           lapack_int ldz, lapack_int* ifail );
+
+lapack_int LAPACKE_ssycon( int matrix_order, char uplo, lapack_int n,
+                           const float* a, lapack_int lda,
+                           const lapack_int* ipiv, float anorm, float* rcond );
+lapack_int LAPACKE_dsycon( int matrix_order, char uplo, lapack_int n,
+                           const double* a, lapack_int lda,
+                           const lapack_int* ipiv, double anorm,
+                           double* rcond );
+lapack_int LAPACKE_csycon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_int* ipiv, float anorm, float* rcond );
+lapack_int LAPACKE_zsycon( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_int* ipiv, double anorm,
+                           double* rcond );
+
+lapack_int LAPACKE_ssyequb( int matrix_order, char uplo, lapack_int n,
+                            const float* a, lapack_int lda, float* s,
+                            float* scond, float* amax );
+lapack_int LAPACKE_dsyequb( int matrix_order, char uplo, lapack_int n,
+                            const double* a, lapack_int lda, double* s,
+                            double* scond, double* amax );
+lapack_int LAPACKE_csyequb( int matrix_order, char uplo, lapack_int n,
+                            const lapack_complex_float* a, lapack_int lda,
+                            float* s, float* scond, float* amax );
+lapack_int LAPACKE_zsyequb( int matrix_order, char uplo, lapack_int n,
+                            const lapack_complex_double* a, lapack_int lda,
+                            double* s, double* scond, double* amax );
+
+lapack_int LAPACKE_ssyev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          float* a, lapack_int lda, float* w );
+lapack_int LAPACKE_dsyev( int matrix_order, char jobz, char uplo, lapack_int n,
+                          double* a, lapack_int lda, double* w );
+
+lapack_int LAPACKE_ssyevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           float* a, lapack_int lda, float* w );
+lapack_int LAPACKE_dsyevd( int matrix_order, char jobz, char uplo, lapack_int n,
+                           double* a, lapack_int lda, double* w );
+
+lapack_int LAPACKE_ssyevr( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, float* a, lapack_int lda, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* isuppz );
+lapack_int LAPACKE_dsyevr( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, double* a, lapack_int lda, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w, double* z,
+                           lapack_int ldz, lapack_int* isuppz );
+
+lapack_int LAPACKE_ssyevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, float* a, lapack_int lda, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* ifail );
+lapack_int LAPACKE_dsyevx( int matrix_order, char jobz, char range, char uplo,
+                           lapack_int n, double* a, lapack_int lda, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w, double* z,
+                           lapack_int ldz, lapack_int* ifail );
+
+lapack_int LAPACKE_ssygst( int matrix_order, lapack_int itype, char uplo,
+                           lapack_int n, float* a, lapack_int lda,
+                           const float* b, lapack_int ldb );
+lapack_int LAPACKE_dsygst( int matrix_order, lapack_int itype, char uplo,
+                           lapack_int n, double* a, lapack_int lda,
+                           const double* b, lapack_int ldb );
+
+lapack_int LAPACKE_ssygv( int matrix_order, lapack_int itype, char jobz,
+                          char uplo, lapack_int n, float* a, lapack_int lda,
+                          float* b, lapack_int ldb, float* w );
+lapack_int LAPACKE_dsygv( int matrix_order, lapack_int itype, char jobz,
+                          char uplo, lapack_int n, double* a, lapack_int lda,
+                          double* b, lapack_int ldb, double* w );
+
+lapack_int LAPACKE_ssygvd( int matrix_order, lapack_int itype, char jobz,
+                           char uplo, lapack_int n, float* a, lapack_int lda,
+                           float* b, lapack_int ldb, float* w );
+lapack_int LAPACKE_dsygvd( int matrix_order, lapack_int itype, char jobz,
+                           char uplo, lapack_int n, double* a, lapack_int lda,
+                           double* b, lapack_int ldb, double* w );
+
+lapack_int LAPACKE_ssygvx( int matrix_order, lapack_int itype, char jobz,
+                           char range, char uplo, lapack_int n, float* a,
+                           lapack_int lda, float* b, lapack_int ldb, float vl,
+                           float vu, lapack_int il, lapack_int iu, float abstol,
+                           lapack_int* m, float* w, float* z, lapack_int ldz,
+                           lapack_int* ifail );
+lapack_int LAPACKE_dsygvx( int matrix_order, lapack_int itype, char jobz,
+                           char range, char uplo, lapack_int n, double* a,
+                           lapack_int lda, double* b, lapack_int ldb, double vl,
+                           double vu, lapack_int il, lapack_int iu,
+                           double abstol, lapack_int* m, double* w, double* z,
+                           lapack_int ldz, lapack_int* ifail );
+
+lapack_int LAPACKE_ssyrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* a, lapack_int lda,
+                           const float* af, lapack_int ldaf,
+                           const lapack_int* ipiv, const float* b,
+                           lapack_int ldb, float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_dsyrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* a, lapack_int lda,
+                           const double* af, lapack_int ldaf,
+                           const lapack_int* ipiv, const double* b,
+                           lapack_int ldb, double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_csyrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* af,
+                           lapack_int ldaf, const lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_zsyrfs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* af,
+                           lapack_int ldaf, const lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_ssyrfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs, const float* a,
+                            lapack_int lda, const float* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const float* s,
+                            const float* b, lapack_int ldb, float* x,
+                            lapack_int ldx, float* rcond, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_dsyrfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs, const double* a,
+                            lapack_int lda, const double* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const double* s,
+                            const double* b, lapack_int ldb, double* x,
+                            lapack_int ldx, double* rcond, double* berr,
+                            lapack_int n_err_bnds, double* err_bnds_norm,
+                            double* err_bnds_comp, lapack_int nparams,
+                            double* params );
+lapack_int LAPACKE_csyrfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs,
+                            const lapack_complex_float* a, lapack_int lda,
+                            const lapack_complex_float* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const float* s,
+                            const lapack_complex_float* b, lapack_int ldb,
+                            lapack_complex_float* x, lapack_int ldx,
+                            float* rcond, float* berr, lapack_int n_err_bnds,
+                            float* err_bnds_norm, float* err_bnds_comp,
+                            lapack_int nparams, float* params );
+lapack_int LAPACKE_zsyrfsx( int matrix_order, char uplo, char equed,
+                            lapack_int n, lapack_int nrhs,
+                            const lapack_complex_double* a, lapack_int lda,
+                            const lapack_complex_double* af, lapack_int ldaf,
+                            const lapack_int* ipiv, const double* s,
+                            const lapack_complex_double* b, lapack_int ldb,
+                            lapack_complex_double* x, lapack_int ldx,
+                            double* rcond, double* berr, lapack_int n_err_bnds,
+                            double* err_bnds_norm, double* err_bnds_comp,
+                            lapack_int nparams, double* params );
+
+lapack_int LAPACKE_ssysv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, float* a, lapack_int lda,
+                          lapack_int* ipiv, float* b, lapack_int ldb );
+lapack_int LAPACKE_dsysv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, double* a, lapack_int lda,
+                          lapack_int* ipiv, double* b, lapack_int ldb );
+lapack_int LAPACKE_csysv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_float* a,
+                          lapack_int lda, lapack_int* ipiv,
+                          lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zsysv( int matrix_order, char uplo, lapack_int n,
+                          lapack_int nrhs, lapack_complex_double* a,
+                          lapack_int lda, lapack_int* ipiv,
+                          lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_ssysvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* a, lapack_int lda,
+                           float* af, lapack_int ldaf, lapack_int* ipiv,
+                           const float* b, lapack_int ldb, float* x,
+                           lapack_int ldx, float* rcond, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_dsysvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* a, lapack_int lda,
+                           double* af, lapack_int ldaf, lapack_int* ipiv,
+                           const double* b, lapack_int ldb, double* x,
+                           lapack_int ldx, double* rcond, double* ferr,
+                           double* berr );
+lapack_int LAPACKE_csysvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* af,
+                           lapack_int ldaf, lapack_int* ipiv,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* x, lapack_int ldx,
+                           float* rcond, float* ferr, float* berr );
+lapack_int LAPACKE_zsysvx( int matrix_order, char fact, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* af,
+                           lapack_int ldaf, lapack_int* ipiv,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* x, lapack_int ldx,
+                           double* rcond, double* ferr, double* berr );
+
+lapack_int LAPACKE_ssysvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs, float* a,
+                            lapack_int lda, float* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, float* s, float* b,
+                            lapack_int ldb, float* x, lapack_int ldx,
+                            float* rcond, float* rpvgrw, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_dsysvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs, double* a,
+                            lapack_int lda, double* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, double* s, double* b,
+                            lapack_int ldb, double* x, lapack_int ldx,
+                            double* rcond, double* rpvgrw, double* berr,
+                            lapack_int n_err_bnds, double* err_bnds_norm,
+                            double* err_bnds_comp, lapack_int nparams,
+                            double* params );
+lapack_int LAPACKE_csysvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, float* s,
+                            lapack_complex_float* b, lapack_int ldb,
+                            lapack_complex_float* x, lapack_int ldx,
+                            float* rcond, float* rpvgrw, float* berr,
+                            lapack_int n_err_bnds, float* err_bnds_norm,
+                            float* err_bnds_comp, lapack_int nparams,
+                            float* params );
+lapack_int LAPACKE_zsysvxx( int matrix_order, char fact, char uplo,
+                            lapack_int n, lapack_int nrhs,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* af, lapack_int ldaf,
+                            lapack_int* ipiv, char* equed, double* s,
+                            lapack_complex_double* b, lapack_int ldb,
+                            lapack_complex_double* x, lapack_int ldx,
+                            double* rcond, double* rpvgrw, double* berr,
+                            lapack_int n_err_bnds, double* err_bnds_norm,
+                            double* err_bnds_comp, lapack_int nparams,
+                            double* params );
+
+lapack_int LAPACKE_ssytrd( int matrix_order, char uplo, lapack_int n, float* a,
+                           lapack_int lda, float* d, float* e, float* tau );
+lapack_int LAPACKE_dsytrd( int matrix_order, char uplo, lapack_int n, double* a,
+                           lapack_int lda, double* d, double* e, double* tau );
+
+lapack_int LAPACKE_ssytrf( int matrix_order, char uplo, lapack_int n, float* a,
+                           lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_dsytrf( int matrix_order, char uplo, lapack_int n, double* a,
+                           lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_csytrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_int* ipiv );
+lapack_int LAPACKE_zsytrf( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_int* ipiv );
+
+lapack_int LAPACKE_ssytri( int matrix_order, char uplo, lapack_int n, float* a,
+                           lapack_int lda, const lapack_int* ipiv );
+lapack_int LAPACKE_dsytri( int matrix_order, char uplo, lapack_int n, double* a,
+                           lapack_int lda, const lapack_int* ipiv );
+lapack_int LAPACKE_csytri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           const lapack_int* ipiv );
+lapack_int LAPACKE_zsytri( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           const lapack_int* ipiv );
+
+lapack_int LAPACKE_ssytrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const float* a, lapack_int lda,
+                           const lapack_int* ipiv, float* b, lapack_int ldb );
+lapack_int LAPACKE_dsytrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const double* a, lapack_int lda,
+                           const lapack_int* ipiv, double* b, lapack_int ldb );
+lapack_int LAPACKE_csytrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_int* ipiv,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zsytrs( int matrix_order, char uplo, lapack_int n,
+                           lapack_int nrhs, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_int* ipiv,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_stbcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, lapack_int kd, const float* ab,
+                           lapack_int ldab, float* rcond );
+lapack_int LAPACKE_dtbcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, lapack_int kd, const double* ab,
+                           lapack_int ldab, double* rcond );
+lapack_int LAPACKE_ctbcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, lapack_int kd,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           float* rcond );
+lapack_int LAPACKE_ztbcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, lapack_int kd,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           double* rcond );
+
+lapack_int LAPACKE_stbrfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int kd, lapack_int nrhs,
+                           const float* ab, lapack_int ldab, const float* b,
+                           lapack_int ldb, const float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_dtbrfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int kd, lapack_int nrhs,
+                           const double* ab, lapack_int ldab, const double* b,
+                           lapack_int ldb, const double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+lapack_int LAPACKE_ctbrfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int kd, lapack_int nrhs,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           const lapack_complex_float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_ztbrfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int kd, lapack_int nrhs,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           const lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_stbtrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int kd, lapack_int nrhs,
+                           const float* ab, lapack_int ldab, float* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_dtbtrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int kd, lapack_int nrhs,
+                           const double* ab, lapack_int ldab, double* b,
+                           lapack_int ldb );
+lapack_int LAPACKE_ctbtrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int kd, lapack_int nrhs,
+                           const lapack_complex_float* ab, lapack_int ldab,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_ztbtrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int kd, lapack_int nrhs,
+                           const lapack_complex_double* ab, lapack_int ldab,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_stfsm( int matrix_order, char transr, char side, char uplo,
+                          char trans, char diag, lapack_int m, lapack_int n,
+                          float alpha, const float* a, float* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_dtfsm( int matrix_order, char transr, char side, char uplo,
+                          char trans, char diag, lapack_int m, lapack_int n,
+                          double alpha, const double* a, double* b,
+                          lapack_int ldb );
+lapack_int LAPACKE_ctfsm( int matrix_order, char transr, char side, char uplo,
+                          char trans, char diag, lapack_int m, lapack_int n,
+                          lapack_complex_float alpha,
+                          const lapack_complex_float* a,
+                          lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_ztfsm( int matrix_order, char transr, char side, char uplo,
+                          char trans, char diag, lapack_int m, lapack_int n,
+                          lapack_complex_double alpha,
+                          const lapack_complex_double* a,
+                          lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_stftri( int matrix_order, char transr, char uplo, char diag,
+                           lapack_int n, float* a );
+lapack_int LAPACKE_dtftri( int matrix_order, char transr, char uplo, char diag,
+                           lapack_int n, double* a );
+lapack_int LAPACKE_ctftri( int matrix_order, char transr, char uplo, char diag,
+                           lapack_int n, lapack_complex_float* a );
+lapack_int LAPACKE_ztftri( int matrix_order, char transr, char uplo, char diag,
+                           lapack_int n, lapack_complex_double* a );
+
+lapack_int LAPACKE_stfttp( int matrix_order, char transr, char uplo,
+                           lapack_int n, const float* arf, float* ap );
+lapack_int LAPACKE_dtfttp( int matrix_order, char transr, char uplo,
+                           lapack_int n, const double* arf, double* ap );
+lapack_int LAPACKE_ctfttp( int matrix_order, char transr, char uplo,
+                           lapack_int n, const lapack_complex_float* arf,
+                           lapack_complex_float* ap );
+lapack_int LAPACKE_ztfttp( int matrix_order, char transr, char uplo,
+                           lapack_int n, const lapack_complex_double* arf,
+                           lapack_complex_double* ap );
+
+lapack_int LAPACKE_stfttr( int matrix_order, char transr, char uplo,
+                           lapack_int n, const float* arf, float* a,
+                           lapack_int lda );
+lapack_int LAPACKE_dtfttr( int matrix_order, char transr, char uplo,
+                           lapack_int n, const double* arf, double* a,
+                           lapack_int lda );
+lapack_int LAPACKE_ctfttr( int matrix_order, char transr, char uplo,
+                           lapack_int n, const lapack_complex_float* arf,
+                           lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_ztfttr( int matrix_order, char transr, char uplo,
+                           lapack_int n, const lapack_complex_double* arf,
+                           lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_stgevc( int matrix_order, char side, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const float* s, lapack_int lds, const float* p,
+                           lapack_int ldp, float* vl, lapack_int ldvl,
+                           float* vr, lapack_int ldvr, lapack_int mm,
+                           lapack_int* m );
+lapack_int LAPACKE_dtgevc( int matrix_order, char side, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const double* s, lapack_int lds, const double* p,
+                           lapack_int ldp, double* vl, lapack_int ldvl,
+                           double* vr, lapack_int ldvr, lapack_int mm,
+                           lapack_int* m );
+lapack_int LAPACKE_ctgevc( int matrix_order, char side, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const lapack_complex_float* s, lapack_int lds,
+                           const lapack_complex_float* p, lapack_int ldp,
+                           lapack_complex_float* vl, lapack_int ldvl,
+                           lapack_complex_float* vr, lapack_int ldvr,
+                           lapack_int mm, lapack_int* m );
+lapack_int LAPACKE_ztgevc( int matrix_order, char side, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const lapack_complex_double* s, lapack_int lds,
+                           const lapack_complex_double* p, lapack_int ldp,
+                           lapack_complex_double* vl, lapack_int ldvl,
+                           lapack_complex_double* vr, lapack_int ldvr,
+                           lapack_int mm, lapack_int* m );
+
+lapack_int LAPACKE_stgexc( int matrix_order, lapack_logical wantq,
+                           lapack_logical wantz, lapack_int n, float* a,
+                           lapack_int lda, float* b, lapack_int ldb, float* q,
+                           lapack_int ldq, float* z, lapack_int ldz,
+                           lapack_int* ifst, lapack_int* ilst );
+lapack_int LAPACKE_dtgexc( int matrix_order, lapack_logical wantq,
+                           lapack_logical wantz, lapack_int n, double* a,
+                           lapack_int lda, double* b, lapack_int ldb, double* q,
+                           lapack_int ldq, double* z, lapack_int ldz,
+                           lapack_int* ifst, lapack_int* ilst );
+lapack_int LAPACKE_ctgexc( int matrix_order, lapack_logical wantq,
+                           lapack_logical wantz, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* q, lapack_int ldq,
+                           lapack_complex_float* z, lapack_int ldz,
+                           lapack_int ifst, lapack_int ilst );
+lapack_int LAPACKE_ztgexc( int matrix_order, lapack_logical wantq,
+                           lapack_logical wantz, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int ifst, lapack_int ilst );
+
+lapack_int LAPACKE_stgsen( int matrix_order, lapack_int ijob,
+                           lapack_logical wantq, lapack_logical wantz,
+                           const lapack_logical* select, lapack_int n, float* a,
+                           lapack_int lda, float* b, lapack_int ldb,
+                           float* alphar, float* alphai, float* beta, float* q,
+                           lapack_int ldq, float* z, lapack_int ldz,
+                           lapack_int* m, float* pl, float* pr, float* dif );
+lapack_int LAPACKE_dtgsen( int matrix_order, lapack_int ijob,
+                           lapack_logical wantq, lapack_logical wantz,
+                           const lapack_logical* select, lapack_int n,
+                           double* a, lapack_int lda, double* b, lapack_int ldb,
+                           double* alphar, double* alphai, double* beta,
+                           double* q, lapack_int ldq, double* z, lapack_int ldz,
+                           lapack_int* m, double* pl, double* pr, double* dif );
+lapack_int LAPACKE_ctgsen( int matrix_order, lapack_int ijob,
+                           lapack_logical wantq, lapack_logical wantz,
+                           const lapack_logical* select, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* alpha,
+                           lapack_complex_float* beta, lapack_complex_float* q,
+                           lapack_int ldq, lapack_complex_float* z,
+                           lapack_int ldz, lapack_int* m, float* pl, float* pr,
+                           float* dif );
+lapack_int LAPACKE_ztgsen( int matrix_order, lapack_int ijob,
+                           lapack_logical wantq, lapack_logical wantz,
+                           const lapack_logical* select, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* alpha,
+                           lapack_complex_double* beta,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_complex_double* z, lapack_int ldz,
+                           lapack_int* m, double* pl, double* pr, double* dif );
+
+lapack_int LAPACKE_stgsja( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int p, lapack_int n,
+                           lapack_int k, lapack_int l, float* a, lapack_int lda,
+                           float* b, lapack_int ldb, float tola, float tolb,
+                           float* alpha, float* beta, float* u, lapack_int ldu,
+                           float* v, lapack_int ldv, float* q, lapack_int ldq,
+                           lapack_int* ncycle );
+lapack_int LAPACKE_dtgsja( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int p, lapack_int n,
+                           lapack_int k, lapack_int l, double* a,
+                           lapack_int lda, double* b, lapack_int ldb,
+                           double tola, double tolb, double* alpha,
+                           double* beta, double* u, lapack_int ldu, double* v,
+                           lapack_int ldv, double* q, lapack_int ldq,
+                           lapack_int* ncycle );
+lapack_int LAPACKE_ctgsja( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int p, lapack_int n,
+                           lapack_int k, lapack_int l, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* b,
+                           lapack_int ldb, float tola, float tolb, float* alpha,
+                           float* beta, lapack_complex_float* u, lapack_int ldu,
+                           lapack_complex_float* v, lapack_int ldv,
+                           lapack_complex_float* q, lapack_int ldq,
+                           lapack_int* ncycle );
+lapack_int LAPACKE_ztgsja( int matrix_order, char jobu, char jobv, char jobq,
+                           lapack_int m, lapack_int p, lapack_int n,
+                           lapack_int k, lapack_int l, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* b,
+                           lapack_int ldb, double tola, double tolb,
+                           double* alpha, double* beta,
+                           lapack_complex_double* u, lapack_int ldu,
+                           lapack_complex_double* v, lapack_int ldv,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_int* ncycle );
+
+lapack_int LAPACKE_stgsna( int matrix_order, char job, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const float* a, lapack_int lda, const float* b,
+                           lapack_int ldb, const float* vl, lapack_int ldvl,
+                           const float* vr, lapack_int ldvr, float* s,
+                           float* dif, lapack_int mm, lapack_int* m );
+lapack_int LAPACKE_dtgsna( int matrix_order, char job, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const double* a, lapack_int lda, const double* b,
+                           lapack_int ldb, const double* vl, lapack_int ldvl,
+                           const double* vr, lapack_int ldvr, double* s,
+                           double* dif, lapack_int mm, lapack_int* m );
+lapack_int LAPACKE_ctgsna( int matrix_order, char job, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           const lapack_complex_float* vl, lapack_int ldvl,
+                           const lapack_complex_float* vr, lapack_int ldvr,
+                           float* s, float* dif, lapack_int mm, lapack_int* m );
+lapack_int LAPACKE_ztgsna( int matrix_order, char job, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           const lapack_complex_double* vl, lapack_int ldvl,
+                           const lapack_complex_double* vr, lapack_int ldvr,
+                           double* s, double* dif, lapack_int mm,
+                           lapack_int* m );
+
+lapack_int LAPACKE_stgsyl( int matrix_order, char trans, lapack_int ijob,
+                           lapack_int m, lapack_int n, const float* a,
+                           lapack_int lda, const float* b, lapack_int ldb,
+                           float* c, lapack_int ldc, const float* d,
+                           lapack_int ldd, const float* e, lapack_int lde,
+                           float* f, lapack_int ldf, float* scale, float* dif );
+lapack_int LAPACKE_dtgsyl( int matrix_order, char trans, lapack_int ijob,
+                           lapack_int m, lapack_int n, const double* a,
+                           lapack_int lda, const double* b, lapack_int ldb,
+                           double* c, lapack_int ldc, const double* d,
+                           lapack_int ldd, const double* e, lapack_int lde,
+                           double* f, lapack_int ldf, double* scale,
+                           double* dif );
+lapack_int LAPACKE_ctgsyl( int matrix_order, char trans, lapack_int ijob,
+                           lapack_int m, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* c, lapack_int ldc,
+                           const lapack_complex_float* d, lapack_int ldd,
+                           const lapack_complex_float* e, lapack_int lde,
+                           lapack_complex_float* f, lapack_int ldf,
+                           float* scale, float* dif );
+lapack_int LAPACKE_ztgsyl( int matrix_order, char trans, lapack_int ijob,
+                           lapack_int m, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* c, lapack_int ldc,
+                           const lapack_complex_double* d, lapack_int ldd,
+                           const lapack_complex_double* e, lapack_int lde,
+                           lapack_complex_double* f, lapack_int ldf,
+                           double* scale, double* dif );
+
+lapack_int LAPACKE_stpcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, const float* ap, float* rcond );
+lapack_int LAPACKE_dtpcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, const double* ap, double* rcond );
+lapack_int LAPACKE_ctpcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, const lapack_complex_float* ap,
+                           float* rcond );
+lapack_int LAPACKE_ztpcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, const lapack_complex_double* ap,
+                           double* rcond );
+
+lapack_int LAPACKE_stprfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs, const float* ap,
+                           const float* b, lapack_int ldb, const float* x,
+                           lapack_int ldx, float* ferr, float* berr );
+lapack_int LAPACKE_dtprfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs, const double* ap,
+                           const double* b, lapack_int ldb, const double* x,
+                           lapack_int ldx, double* ferr, double* berr );
+lapack_int LAPACKE_ctprfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_float* ap,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           const lapack_complex_float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_ztprfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_double* ap,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           const lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_stptri( int matrix_order, char uplo, char diag, lapack_int n,
+                           float* ap );
+lapack_int LAPACKE_dtptri( int matrix_order, char uplo, char diag, lapack_int n,
+                           double* ap );
+lapack_int LAPACKE_ctptri( int matrix_order, char uplo, char diag, lapack_int n,
+                           lapack_complex_float* ap );
+lapack_int LAPACKE_ztptri( int matrix_order, char uplo, char diag, lapack_int n,
+                           lapack_complex_double* ap );
+
+lapack_int LAPACKE_stptrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs, const float* ap,
+                           float* b, lapack_int ldb );
+lapack_int LAPACKE_dtptrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs, const double* ap,
+                           double* b, lapack_int ldb );
+lapack_int LAPACKE_ctptrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_float* ap,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_ztptrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_double* ap,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_stpttf( int matrix_order, char transr, char uplo,
+                           lapack_int n, const float* ap, float* arf );
+lapack_int LAPACKE_dtpttf( int matrix_order, char transr, char uplo,
+                           lapack_int n, const double* ap, double* arf );
+lapack_int LAPACKE_ctpttf( int matrix_order, char transr, char uplo,
+                           lapack_int n, const lapack_complex_float* ap,
+                           lapack_complex_float* arf );
+lapack_int LAPACKE_ztpttf( int matrix_order, char transr, char uplo,
+                           lapack_int n, const lapack_complex_double* ap,
+                           lapack_complex_double* arf );
+
+lapack_int LAPACKE_stpttr( int matrix_order, char uplo, lapack_int n,
+                           const float* ap, float* a, lapack_int lda );
+lapack_int LAPACKE_dtpttr( int matrix_order, char uplo, lapack_int n,
+                           const double* ap, double* a, lapack_int lda );
+lapack_int LAPACKE_ctpttr( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* ap,
+                           lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_ztpttr( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* ap,
+                           lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_strcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, const float* a, lapack_int lda,
+                           float* rcond );
+lapack_int LAPACKE_dtrcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, const double* a, lapack_int lda,
+                           double* rcond );
+lapack_int LAPACKE_ctrcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, const lapack_complex_float* a,
+                           lapack_int lda, float* rcond );
+lapack_int LAPACKE_ztrcon( int matrix_order, char norm, char uplo, char diag,
+                           lapack_int n, const lapack_complex_double* a,
+                           lapack_int lda, double* rcond );
+
+lapack_int LAPACKE_strevc( int matrix_order, char side, char howmny,
+                           lapack_logical* select, lapack_int n, const float* t,
+                           lapack_int ldt, float* vl, lapack_int ldvl,
+                           float* vr, lapack_int ldvr, lapack_int mm,
+                           lapack_int* m );
+lapack_int LAPACKE_dtrevc( int matrix_order, char side, char howmny,
+                           lapack_logical* select, lapack_int n,
+                           const double* t, lapack_int ldt, double* vl,
+                           lapack_int ldvl, double* vr, lapack_int ldvr,
+                           lapack_int mm, lapack_int* m );
+lapack_int LAPACKE_ctrevc( int matrix_order, char side, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           lapack_complex_float* t, lapack_int ldt,
+                           lapack_complex_float* vl, lapack_int ldvl,
+                           lapack_complex_float* vr, lapack_int ldvr,
+                           lapack_int mm, lapack_int* m );
+lapack_int LAPACKE_ztrevc( int matrix_order, char side, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           lapack_complex_double* t, lapack_int ldt,
+                           lapack_complex_double* vl, lapack_int ldvl,
+                           lapack_complex_double* vr, lapack_int ldvr,
+                           lapack_int mm, lapack_int* m );
+
+lapack_int LAPACKE_strexc( int matrix_order, char compq, lapack_int n, float* t,
+                           lapack_int ldt, float* q, lapack_int ldq,
+                           lapack_int* ifst, lapack_int* ilst );
+lapack_int LAPACKE_dtrexc( int matrix_order, char compq, lapack_int n,
+                           double* t, lapack_int ldt, double* q, lapack_int ldq,
+                           lapack_int* ifst, lapack_int* ilst );
+lapack_int LAPACKE_ctrexc( int matrix_order, char compq, lapack_int n,
+                           lapack_complex_float* t, lapack_int ldt,
+                           lapack_complex_float* q, lapack_int ldq,
+                           lapack_int ifst, lapack_int ilst );
+lapack_int LAPACKE_ztrexc( int matrix_order, char compq, lapack_int n,
+                           lapack_complex_double* t, lapack_int ldt,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_int ifst, lapack_int ilst );
+
+lapack_int LAPACKE_strrfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs, const float* a,
+                           lapack_int lda, const float* b, lapack_int ldb,
+                           const float* x, lapack_int ldx, float* ferr,
+                           float* berr );
+lapack_int LAPACKE_dtrrfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs, const double* a,
+                           lapack_int lda, const double* b, lapack_int ldb,
+                           const double* x, lapack_int ldx, double* ferr,
+                           double* berr );
+lapack_int LAPACKE_ctrrfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           const lapack_complex_float* x, lapack_int ldx,
+                           float* ferr, float* berr );
+lapack_int LAPACKE_ztrrfs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           const lapack_complex_double* x, lapack_int ldx,
+                           double* ferr, double* berr );
+
+lapack_int LAPACKE_strsen( int matrix_order, char job, char compq,
+                           const lapack_logical* select, lapack_int n, float* t,
+                           lapack_int ldt, float* q, lapack_int ldq, float* wr,
+                           float* wi, lapack_int* m, float* s, float* sep );
+lapack_int LAPACKE_dtrsen( int matrix_order, char job, char compq,
+                           const lapack_logical* select, lapack_int n,
+                           double* t, lapack_int ldt, double* q, lapack_int ldq,
+                           double* wr, double* wi, lapack_int* m, double* s,
+                           double* sep );
+lapack_int LAPACKE_ctrsen( int matrix_order, char job, char compq,
+                           const lapack_logical* select, lapack_int n,
+                           lapack_complex_float* t, lapack_int ldt,
+                           lapack_complex_float* q, lapack_int ldq,
+                           lapack_complex_float* w, lapack_int* m, float* s,
+                           float* sep );
+lapack_int LAPACKE_ztrsen( int matrix_order, char job, char compq,
+                           const lapack_logical* select, lapack_int n,
+                           lapack_complex_double* t, lapack_int ldt,
+                           lapack_complex_double* q, lapack_int ldq,
+                           lapack_complex_double* w, lapack_int* m, double* s,
+                           double* sep );
+
+lapack_int LAPACKE_strsna( int matrix_order, char job, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const float* t, lapack_int ldt, const float* vl,
+                           lapack_int ldvl, const float* vr, lapack_int ldvr,
+                           float* s, float* sep, lapack_int mm, lapack_int* m );
+lapack_int LAPACKE_dtrsna( int matrix_order, char job, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const double* t, lapack_int ldt, const double* vl,
+                           lapack_int ldvl, const double* vr, lapack_int ldvr,
+                           double* s, double* sep, lapack_int mm,
+                           lapack_int* m );
+lapack_int LAPACKE_ctrsna( int matrix_order, char job, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const lapack_complex_float* t, lapack_int ldt,
+                           const lapack_complex_float* vl, lapack_int ldvl,
+                           const lapack_complex_float* vr, lapack_int ldvr,
+                           float* s, float* sep, lapack_int mm, lapack_int* m );
+lapack_int LAPACKE_ztrsna( int matrix_order, char job, char howmny,
+                           const lapack_logical* select, lapack_int n,
+                           const lapack_complex_double* t, lapack_int ldt,
+                           const lapack_complex_double* vl, lapack_int ldvl,
+                           const lapack_complex_double* vr, lapack_int ldvr,
+                           double* s, double* sep, lapack_int mm,
+                           lapack_int* m );
+
+lapack_int LAPACKE_strsyl( int matrix_order, char trana, char tranb,
+                           lapack_int isgn, lapack_int m, lapack_int n,
+                           const float* a, lapack_int lda, const float* b,
+                           lapack_int ldb, float* c, lapack_int ldc,
+                           float* scale );
+lapack_int LAPACKE_dtrsyl( int matrix_order, char trana, char tranb,
+                           lapack_int isgn, lapack_int m, lapack_int n,
+                           const double* a, lapack_int lda, const double* b,
+                           lapack_int ldb, double* c, lapack_int ldc,
+                           double* scale );
+lapack_int LAPACKE_ctrsyl( int matrix_order, char trana, char tranb,
+                           lapack_int isgn, lapack_int m, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* b, lapack_int ldb,
+                           lapack_complex_float* c, lapack_int ldc,
+                           float* scale );
+lapack_int LAPACKE_ztrsyl( int matrix_order, char trana, char tranb,
+                           lapack_int isgn, lapack_int m, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* c, lapack_int ldc,
+                           double* scale );
+
+lapack_int LAPACKE_strtri( int matrix_order, char uplo, char diag, lapack_int n,
+                           float* a, lapack_int lda );
+lapack_int LAPACKE_dtrtri( int matrix_order, char uplo, char diag, lapack_int n,
+                           double* a, lapack_int lda );
+lapack_int LAPACKE_ctrtri( int matrix_order, char uplo, char diag, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_ztrtri( int matrix_order, char uplo, char diag, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_strtrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs, const float* a,
+                           lapack_int lda, float* b, lapack_int ldb );
+lapack_int LAPACKE_dtrtrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs, const double* a,
+                           lapack_int lda, double* b, lapack_int ldb );
+lapack_int LAPACKE_ctrtrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_ztrtrs( int matrix_order, char uplo, char trans, char diag,
+                           lapack_int n, lapack_int nrhs,
+                           const lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_strttf( int matrix_order, char transr, char uplo,
+                           lapack_int n, const float* a, lapack_int lda,
+                           float* arf );
+lapack_int LAPACKE_dtrttf( int matrix_order, char transr, char uplo,
+                           lapack_int n, const double* a, lapack_int lda,
+                           double* arf );
+lapack_int LAPACKE_ctrttf( int matrix_order, char transr, char uplo,
+                           lapack_int n, const lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* arf );
+lapack_int LAPACKE_ztrttf( int matrix_order, char transr, char uplo,
+                           lapack_int n, const lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* arf );
+
+lapack_int LAPACKE_strttp( int matrix_order, char uplo, lapack_int n,
+                           const float* a, lapack_int lda, float* ap );
+lapack_int LAPACKE_dtrttp( int matrix_order, char uplo, lapack_int n,
+                           const double* a, lapack_int lda, double* ap );
+lapack_int LAPACKE_ctrttp( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* ap );
+lapack_int LAPACKE_ztrttp( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* ap );
+
+lapack_int LAPACKE_stzrzf( int matrix_order, lapack_int m, lapack_int n,
+                           float* a, lapack_int lda, float* tau );
+lapack_int LAPACKE_dtzrzf( int matrix_order, lapack_int m, lapack_int n,
+                           double* a, lapack_int lda, double* tau );
+lapack_int LAPACKE_ctzrzf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* tau );
+lapack_int LAPACKE_ztzrzf( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* tau );
+
+lapack_int LAPACKE_cungbr( int matrix_order, char vect, lapack_int m,
+                           lapack_int n, lapack_int k, lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* tau );
+lapack_int LAPACKE_zungbr( int matrix_order, char vect, lapack_int m,
+                           lapack_int n, lapack_int k, lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* tau );
+
+lapack_int LAPACKE_cunghr( int matrix_order, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* tau );
+lapack_int LAPACKE_zunghr( int matrix_order, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* tau );
+
+lapack_int LAPACKE_cunglq( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* tau );
+lapack_int LAPACKE_zunglq( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* tau );
+
+lapack_int LAPACKE_cungql( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* tau );
+lapack_int LAPACKE_zungql( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* tau );
+
+lapack_int LAPACKE_cungqr( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* tau );
+lapack_int LAPACKE_zungqr( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* tau );
+
+lapack_int LAPACKE_cungrq( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* tau );
+lapack_int LAPACKE_zungrq( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* tau );
+
+lapack_int LAPACKE_cungtr( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* tau );
+lapack_int LAPACKE_zungtr( int matrix_order, char uplo, lapack_int n,
+                           lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* tau );
+
+lapack_int LAPACKE_cunmbr( int matrix_order, char vect, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zunmbr( int matrix_order, char vect, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_cunmhr( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zunmhr( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int ilo,
+                           lapack_int ihi, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_cunmlq( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zunmlq( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_cunmql( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zunmql( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_cunmqr( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zunmqr( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_cunmrq( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zunmrq( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_cunmrz( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           lapack_int l, const lapack_complex_float* a,
+                           lapack_int lda, const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zunmrz( int matrix_order, char side, char trans,
+                           lapack_int m, lapack_int n, lapack_int k,
+                           lapack_int l, const lapack_complex_double* a,
+                           lapack_int lda, const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_cunmtr( int matrix_order, char side, char uplo, char trans,
+                           lapack_int m, lapack_int n,
+                           const lapack_complex_float* a, lapack_int lda,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zunmtr( int matrix_order, char side, char uplo, char trans,
+                           lapack_int m, lapack_int n,
+                           const lapack_complex_double* a, lapack_int lda,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_cupgtr( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_float* ap,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* q, lapack_int ldq );
+lapack_int LAPACKE_zupgtr( int matrix_order, char uplo, lapack_int n,
+                           const lapack_complex_double* ap,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* q, lapack_int ldq );
+
+lapack_int LAPACKE_cupmtr( int matrix_order, char side, char uplo, char trans,
+                           lapack_int m, lapack_int n,
+                           const lapack_complex_float* ap,
+                           const lapack_complex_float* tau,
+                           lapack_complex_float* c, lapack_int ldc );
+lapack_int LAPACKE_zupmtr( int matrix_order, char side, char uplo, char trans,
+                           lapack_int m, lapack_int n,
+                           const lapack_complex_double* ap,
+                           const lapack_complex_double* tau,
+                           lapack_complex_double* c, lapack_int ldc );
+
+lapack_int LAPACKE_sbdsdc_work( int matrix_order, char uplo, char compq,
+                                lapack_int n, float* d, float* e, float* u,
+                                lapack_int ldu, float* vt, lapack_int ldvt,
+                                float* q, lapack_int* iq, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dbdsdc_work( int matrix_order, char uplo, char compq,
+                                lapack_int n, double* d, double* e, double* u,
+                                lapack_int ldu, double* vt, lapack_int ldvt,
+                                double* q, lapack_int* iq, double* work,
+                                lapack_int* iwork );
+
+lapack_int LAPACKE_sbdsqr_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int ncvt, lapack_int nru, lapack_int ncc,
+                                float* d, float* e, float* vt, lapack_int ldvt,
+                                float* u, lapack_int ldu, float* c,
+                                lapack_int ldc, float* work );
+lapack_int LAPACKE_dbdsqr_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int ncvt, lapack_int nru, lapack_int ncc,
+                                double* d, double* e, double* vt,
+                                lapack_int ldvt, double* u, lapack_int ldu,
+                                double* c, lapack_int ldc, double* work );
+lapack_int LAPACKE_cbdsqr_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int ncvt, lapack_int nru, lapack_int ncc,
+                                float* d, float* e, lapack_complex_float* vt,
+                                lapack_int ldvt, lapack_complex_float* u,
+                                lapack_int ldu, lapack_complex_float* c,
+                                lapack_int ldc, float* work );
+lapack_int LAPACKE_zbdsqr_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int ncvt, lapack_int nru, lapack_int ncc,
+                                double* d, double* e, lapack_complex_double* vt,
+                                lapack_int ldvt, lapack_complex_double* u,
+                                lapack_int ldu, lapack_complex_double* c,
+                                lapack_int ldc, double* work );
+
+lapack_int LAPACKE_sdisna_work( char job, lapack_int m, lapack_int n,
+                                const float* d, float* sep );
+lapack_int LAPACKE_ddisna_work( char job, lapack_int m, lapack_int n,
+                                const double* d, double* sep );
+
+lapack_int LAPACKE_sgbbrd_work( int matrix_order, char vect, lapack_int m,
+                                lapack_int n, lapack_int ncc, lapack_int kl,
+                                lapack_int ku, float* ab, lapack_int ldab,
+                                float* d, float* e, float* q, lapack_int ldq,
+                                float* pt, lapack_int ldpt, float* c,
+                                lapack_int ldc, float* work );
+lapack_int LAPACKE_dgbbrd_work( int matrix_order, char vect, lapack_int m,
+                                lapack_int n, lapack_int ncc, lapack_int kl,
+                                lapack_int ku, double* ab, lapack_int ldab,
+                                double* d, double* e, double* q, lapack_int ldq,
+                                double* pt, lapack_int ldpt, double* c,
+                                lapack_int ldc, double* work );
+lapack_int LAPACKE_cgbbrd_work( int matrix_order, char vect, lapack_int m,
+                                lapack_int n, lapack_int ncc, lapack_int kl,
+                                lapack_int ku, lapack_complex_float* ab,
+                                lapack_int ldab, float* d, float* e,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_complex_float* pt, lapack_int ldpt,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zgbbrd_work( int matrix_order, char vect, lapack_int m,
+                                lapack_int n, lapack_int ncc, lapack_int kl,
+                                lapack_int ku, lapack_complex_double* ab,
+                                lapack_int ldab, double* d, double* e,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_complex_double* pt, lapack_int ldpt,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgbcon_work( int matrix_order, char norm, lapack_int n,
+                                lapack_int kl, lapack_int ku, const float* ab,
+                                lapack_int ldab, const lapack_int* ipiv,
+                                float anorm, float* rcond, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgbcon_work( int matrix_order, char norm, lapack_int n,
+                                lapack_int kl, lapack_int ku, const double* ab,
+                                lapack_int ldab, const lapack_int* ipiv,
+                                double anorm, double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cgbcon_work( int matrix_order, char norm, lapack_int n,
+                                lapack_int kl, lapack_int ku,
+                                const lapack_complex_float* ab, lapack_int ldab,
+                                const lapack_int* ipiv, float anorm,
+                                float* rcond, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_zgbcon_work( int matrix_order, char norm, lapack_int n,
+                                lapack_int kl, lapack_int ku,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab, const lapack_int* ipiv,
+                                double anorm, double* rcond,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgbequ_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku, const float* ab,
+                                lapack_int ldab, float* r, float* c,
+                                float* rowcnd, float* colcnd, float* amax );
+lapack_int LAPACKE_dgbequ_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku, const double* ab,
+                                lapack_int ldab, double* r, double* c,
+                                double* rowcnd, double* colcnd, double* amax );
+lapack_int LAPACKE_cgbequ_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku,
+                                const lapack_complex_float* ab, lapack_int ldab,
+                                float* r, float* c, float* rowcnd,
+                                float* colcnd, float* amax );
+lapack_int LAPACKE_zgbequ_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab, double* r, double* c,
+                                double* rowcnd, double* colcnd, double* amax );
+
+lapack_int LAPACKE_sgbequb_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_int kl, lapack_int ku, const float* ab,
+                                 lapack_int ldab, float* r, float* c,
+                                 float* rowcnd, float* colcnd, float* amax );
+lapack_int LAPACKE_dgbequb_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_int kl, lapack_int ku, const double* ab,
+                                 lapack_int ldab, double* r, double* c,
+                                 double* rowcnd, double* colcnd, double* amax );
+lapack_int LAPACKE_cgbequb_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_int kl, lapack_int ku,
+                                 const lapack_complex_float* ab,
+                                 lapack_int ldab, float* r, float* c,
+                                 float* rowcnd, float* colcnd, float* amax );
+lapack_int LAPACKE_zgbequb_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_int kl, lapack_int ku,
+                                 const lapack_complex_double* ab,
+                                 lapack_int ldab, double* r, double* c,
+                                 double* rowcnd, double* colcnd, double* amax );
+
+lapack_int LAPACKE_sgbrfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int kl, lapack_int ku, lapack_int nrhs,
+                                const float* ab, lapack_int ldab,
+                                const float* afb, lapack_int ldafb,
+                                const lapack_int* ipiv, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* ferr, float* berr, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgbrfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int kl, lapack_int ku, lapack_int nrhs,
+                                const double* ab, lapack_int ldab,
+                                const double* afb, lapack_int ldafb,
+                                const lapack_int* ipiv, const double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* ferr, double* berr, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cgbrfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int kl, lapack_int ku, lapack_int nrhs,
+                                const lapack_complex_float* ab, lapack_int ldab,
+                                const lapack_complex_float* afb,
+                                lapack_int ldafb, const lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zgbrfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int kl, lapack_int ku, lapack_int nrhs,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab,
+                                const lapack_complex_double* afb,
+                                lapack_int ldafb, const lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgbrfsx_work( int matrix_order, char trans, char equed,
+                                 lapack_int n, lapack_int kl, lapack_int ku,
+                                 lapack_int nrhs, const float* ab,
+                                 lapack_int ldab, const float* afb,
+                                 lapack_int ldafb, const lapack_int* ipiv,
+                                 const float* r, const float* c, const float* b,
+                                 lapack_int ldb, float* x, lapack_int ldx,
+                                 float* rcond, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, float* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_dgbrfsx_work( int matrix_order, char trans, char equed,
+                                 lapack_int n, lapack_int kl, lapack_int ku,
+                                 lapack_int nrhs, const double* ab,
+                                 lapack_int ldab, const double* afb,
+                                 lapack_int ldafb, const lapack_int* ipiv,
+                                 const double* r, const double* c,
+                                 const double* b, lapack_int ldb, double* x,
+                                 lapack_int ldx, double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, double* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_cgbrfsx_work( int matrix_order, char trans, char equed,
+                                 lapack_int n, lapack_int kl, lapack_int ku,
+                                 lapack_int nrhs,
+                                 const lapack_complex_float* ab,
+                                 lapack_int ldab,
+                                 const lapack_complex_float* afb,
+                                 lapack_int ldafb, const lapack_int* ipiv,
+                                 const float* r, const float* c,
+                                 const lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* x, lapack_int ldx,
+                                 float* rcond, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, lapack_complex_float* work,
+                                 float* rwork );
+lapack_int LAPACKE_zgbrfsx_work( int matrix_order, char trans, char equed,
+                                 lapack_int n, lapack_int kl, lapack_int ku,
+                                 lapack_int nrhs,
+                                 const lapack_complex_double* ab,
+                                 lapack_int ldab,
+                                 const lapack_complex_double* afb,
+                                 lapack_int ldafb, const lapack_int* ipiv,
+                                 const double* r, const double* c,
+                                 const lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_sgbsv_work( int matrix_order, lapack_int n, lapack_int kl,
+                               lapack_int ku, lapack_int nrhs, float* ab,
+                               lapack_int ldab, lapack_int* ipiv, float* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_dgbsv_work( int matrix_order, lapack_int n, lapack_int kl,
+                               lapack_int ku, lapack_int nrhs, double* ab,
+                               lapack_int ldab, lapack_int* ipiv, double* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_cgbsv_work( int matrix_order, lapack_int n, lapack_int kl,
+                               lapack_int ku, lapack_int nrhs,
+                               lapack_complex_float* ab, lapack_int ldab,
+                               lapack_int* ipiv, lapack_complex_float* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_zgbsv_work( int matrix_order, lapack_int n, lapack_int kl,
+                               lapack_int ku, lapack_int nrhs,
+                               lapack_complex_double* ab, lapack_int ldab,
+                               lapack_int* ipiv, lapack_complex_double* b,
+                               lapack_int ldb );
+
+lapack_int LAPACKE_sgbsvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int kl, lapack_int ku,
+                                lapack_int nrhs, float* ab, lapack_int ldab,
+                                float* afb, lapack_int ldafb, lapack_int* ipiv,
+                                char* equed, float* r, float* c, float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dgbsvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int kl, lapack_int ku,
+                                lapack_int nrhs, double* ab, lapack_int ldab,
+                                double* afb, lapack_int ldafb, lapack_int* ipiv,
+                                char* equed, double* r, double* c, double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cgbsvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int kl, lapack_int ku,
+                                lapack_int nrhs, lapack_complex_float* ab,
+                                lapack_int ldab, lapack_complex_float* afb,
+                                lapack_int ldafb, lapack_int* ipiv, char* equed,
+                                float* r, float* c, lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_zgbsvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int kl, lapack_int ku,
+                                lapack_int nrhs, lapack_complex_double* ab,
+                                lapack_int ldab, lapack_complex_double* afb,
+                                lapack_int ldafb, lapack_int* ipiv, char* equed,
+                                double* r, double* c, lapack_complex_double* b,
+                                lapack_int ldb, lapack_complex_double* x,
+                                lapack_int ldx, double* rcond, double* ferr,
+                                double* berr, lapack_complex_double* work,
+                                double* rwork );
+
+lapack_int LAPACKE_sgbsvxx_work( int matrix_order, char fact, char trans,
+                                 lapack_int n, lapack_int kl, lapack_int ku,
+                                 lapack_int nrhs, float* ab, lapack_int ldab,
+                                 float* afb, lapack_int ldafb, lapack_int* ipiv,
+                                 char* equed, float* r, float* c, float* b,
+                                 lapack_int ldb, float* x, lapack_int ldx,
+                                 float* rcond, float* rpvgrw, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, float* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_dgbsvxx_work( int matrix_order, char fact, char trans,
+                                 lapack_int n, lapack_int kl, lapack_int ku,
+                                 lapack_int nrhs, double* ab, lapack_int ldab,
+                                 double* afb, lapack_int ldafb,
+                                 lapack_int* ipiv, char* equed, double* r,
+                                 double* c, double* b, lapack_int ldb,
+                                 double* x, lapack_int ldx, double* rcond,
+                                 double* rpvgrw, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, double* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_cgbsvxx_work( int matrix_order, char fact, char trans,
+                                 lapack_int n, lapack_int kl, lapack_int ku,
+                                 lapack_int nrhs, lapack_complex_float* ab,
+                                 lapack_int ldab, lapack_complex_float* afb,
+                                 lapack_int ldafb, lapack_int* ipiv,
+                                 char* equed, float* r, float* c,
+                                 lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* x, lapack_int ldx,
+                                 float* rcond, float* rpvgrw, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, lapack_complex_float* work,
+                                 float* rwork );
+lapack_int LAPACKE_zgbsvxx_work( int matrix_order, char fact, char trans,
+                                 lapack_int n, lapack_int kl, lapack_int ku,
+                                 lapack_int nrhs, lapack_complex_double* ab,
+                                 lapack_int ldab, lapack_complex_double* afb,
+                                 lapack_int ldafb, lapack_int* ipiv,
+                                 char* equed, double* r, double* c,
+                                 lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* rpvgrw, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_sgbtrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku, float* ab,
+                                lapack_int ldab, lapack_int* ipiv );
+lapack_int LAPACKE_dgbtrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku, double* ab,
+                                lapack_int ldab, lapack_int* ipiv );
+lapack_int LAPACKE_cgbtrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku,
+                                lapack_complex_float* ab, lapack_int ldab,
+                                lapack_int* ipiv );
+lapack_int LAPACKE_zgbtrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku,
+                                lapack_complex_double* ab, lapack_int ldab,
+                                lapack_int* ipiv );
+
+lapack_int LAPACKE_sgbtrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int kl, lapack_int ku, lapack_int nrhs,
+                                const float* ab, lapack_int ldab,
+                                const lapack_int* ipiv, float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_dgbtrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int kl, lapack_int ku, lapack_int nrhs,
+                                const double* ab, lapack_int ldab,
+                                const lapack_int* ipiv, double* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_cgbtrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int kl, lapack_int ku, lapack_int nrhs,
+                                const lapack_complex_float* ab, lapack_int ldab,
+                                const lapack_int* ipiv, lapack_complex_float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_zgbtrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int kl, lapack_int ku, lapack_int nrhs,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab, const lapack_int* ipiv,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sgebak_work( int matrix_order, char job, char side,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                const float* scale, lapack_int m, float* v,
+                                lapack_int ldv );
+lapack_int LAPACKE_dgebak_work( int matrix_order, char job, char side,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                const double* scale, lapack_int m, double* v,
+                                lapack_int ldv );
+lapack_int LAPACKE_cgebak_work( int matrix_order, char job, char side,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                const float* scale, lapack_int m,
+                                lapack_complex_float* v, lapack_int ldv );
+lapack_int LAPACKE_zgebak_work( int matrix_order, char job, char side,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                const double* scale, lapack_int m,
+                                lapack_complex_double* v, lapack_int ldv );
+
+lapack_int LAPACKE_sgebal_work( int matrix_order, char job, lapack_int n,
+                                float* a, lapack_int lda, lapack_int* ilo,
+                                lapack_int* ihi, float* scale );
+lapack_int LAPACKE_dgebal_work( int matrix_order, char job, lapack_int n,
+                                double* a, lapack_int lda, lapack_int* ilo,
+                                lapack_int* ihi, double* scale );
+lapack_int LAPACKE_cgebal_work( int matrix_order, char job, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* ilo, lapack_int* ihi,
+                                float* scale );
+lapack_int LAPACKE_zgebal_work( int matrix_order, char job, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* ilo, lapack_int* ihi,
+                                double* scale );
+
+lapack_int LAPACKE_sgebrd_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, float* d, float* e,
+                                float* tauq, float* taup, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dgebrd_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* d, double* e,
+                                double* tauq, double* taup, double* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_cgebrd_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                float* d, float* e, lapack_complex_float* tauq,
+                                lapack_complex_float* taup,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgebrd_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                double* d, double* e,
+                                lapack_complex_double* tauq,
+                                lapack_complex_double* taup,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgecon_work( int matrix_order, char norm, lapack_int n,
+                                const float* a, lapack_int lda, float anorm,
+                                float* rcond, float* work, lapack_int* iwork );
+lapack_int LAPACKE_dgecon_work( int matrix_order, char norm, lapack_int n,
+                                const double* a, lapack_int lda, double anorm,
+                                double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cgecon_work( int matrix_order, char norm, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                float anorm, float* rcond,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zgecon_work( int matrix_order, char norm, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                double anorm, double* rcond,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgeequ_work( int matrix_order, lapack_int m, lapack_int n,
+                                const float* a, lapack_int lda, float* r,
+                                float* c, float* rowcnd, float* colcnd,
+                                float* amax );
+lapack_int LAPACKE_dgeequ_work( int matrix_order, lapack_int m, lapack_int n,
+                                const double* a, lapack_int lda, double* r,
+                                double* c, double* rowcnd, double* colcnd,
+                                double* amax );
+lapack_int LAPACKE_cgeequ_work( int matrix_order, lapack_int m, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                float* r, float* c, float* rowcnd,
+                                float* colcnd, float* amax );
+lapack_int LAPACKE_zgeequ_work( int matrix_order, lapack_int m, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                double* r, double* c, double* rowcnd,
+                                double* colcnd, double* amax );
+
+lapack_int LAPACKE_sgeequb_work( int matrix_order, lapack_int m, lapack_int n,
+                                 const float* a, lapack_int lda, float* r,
+                                 float* c, float* rowcnd, float* colcnd,
+                                 float* amax );
+lapack_int LAPACKE_dgeequb_work( int matrix_order, lapack_int m, lapack_int n,
+                                 const double* a, lapack_int lda, double* r,
+                                 double* c, double* rowcnd, double* colcnd,
+                                 double* amax );
+lapack_int LAPACKE_cgeequb_work( int matrix_order, lapack_int m, lapack_int n,
+                                 const lapack_complex_float* a, lapack_int lda,
+                                 float* r, float* c, float* rowcnd,
+                                 float* colcnd, float* amax );
+lapack_int LAPACKE_zgeequb_work( int matrix_order, lapack_int m, lapack_int n,
+                                 const lapack_complex_double* a, lapack_int lda,
+                                 double* r, double* c, double* rowcnd,
+                                 double* colcnd, double* amax );
+
+lapack_int LAPACKE_sgees_work( int matrix_order, char jobvs, char sort,
+                               LAPACK_S_SELECT2 select, lapack_int n, float* a,
+                               lapack_int lda, lapack_int* sdim, float* wr,
+                               float* wi, float* vs, lapack_int ldvs,
+                               float* work, lapack_int lwork,
+                               lapack_logical* bwork );
+lapack_int LAPACKE_dgees_work( int matrix_order, char jobvs, char sort,
+                               LAPACK_D_SELECT2 select, lapack_int n, double* a,
+                               lapack_int lda, lapack_int* sdim, double* wr,
+                               double* wi, double* vs, lapack_int ldvs,
+                               double* work, lapack_int lwork,
+                               lapack_logical* bwork );
+lapack_int LAPACKE_cgees_work( int matrix_order, char jobvs, char sort,
+                               LAPACK_C_SELECT1 select, lapack_int n,
+                               lapack_complex_float* a, lapack_int lda,
+                               lapack_int* sdim, lapack_complex_float* w,
+                               lapack_complex_float* vs, lapack_int ldvs,
+                               lapack_complex_float* work, lapack_int lwork,
+                               float* rwork, lapack_logical* bwork );
+lapack_int LAPACKE_zgees_work( int matrix_order, char jobvs, char sort,
+                               LAPACK_Z_SELECT1 select, lapack_int n,
+                               lapack_complex_double* a, lapack_int lda,
+                               lapack_int* sdim, lapack_complex_double* w,
+                               lapack_complex_double* vs, lapack_int ldvs,
+                               lapack_complex_double* work, lapack_int lwork,
+                               double* rwork, lapack_logical* bwork );
+
+lapack_int LAPACKE_sgeesx_work( int matrix_order, char jobvs, char sort,
+                                LAPACK_S_SELECT2 select, char sense,
+                                lapack_int n, float* a, lapack_int lda,
+                                lapack_int* sdim, float* wr, float* wi,
+                                float* vs, lapack_int ldvs, float* rconde,
+                                float* rcondv, float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork,
+                                lapack_logical* bwork );
+lapack_int LAPACKE_dgeesx_work( int matrix_order, char jobvs, char sort,
+                                LAPACK_D_SELECT2 select, char sense,
+                                lapack_int n, double* a, lapack_int lda,
+                                lapack_int* sdim, double* wr, double* wi,
+                                double* vs, lapack_int ldvs, double* rconde,
+                                double* rcondv, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork,
+                                lapack_logical* bwork );
+lapack_int LAPACKE_cgeesx_work( int matrix_order, char jobvs, char sort,
+                                LAPACK_C_SELECT1 select, char sense,
+                                lapack_int n, lapack_complex_float* a,
+                                lapack_int lda, lapack_int* sdim,
+                                lapack_complex_float* w,
+                                lapack_complex_float* vs, lapack_int ldvs,
+                                float* rconde, float* rcondv,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork, lapack_logical* bwork );
+lapack_int LAPACKE_zgeesx_work( int matrix_order, char jobvs, char sort,
+                                LAPACK_Z_SELECT1 select, char sense,
+                                lapack_int n, lapack_complex_double* a,
+                                lapack_int lda, lapack_int* sdim,
+                                lapack_complex_double* w,
+                                lapack_complex_double* vs, lapack_int ldvs,
+                                double* rconde, double* rcondv,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork, lapack_logical* bwork );
+
+lapack_int LAPACKE_sgeev_work( int matrix_order, char jobvl, char jobvr,
+                               lapack_int n, float* a, lapack_int lda,
+                               float* wr, float* wi, float* vl, lapack_int ldvl,
+                               float* vr, lapack_int ldvr, float* work,
+                               lapack_int lwork );
+lapack_int LAPACKE_dgeev_work( int matrix_order, char jobvl, char jobvr,
+                               lapack_int n, double* a, lapack_int lda,
+                               double* wr, double* wi, double* vl,
+                               lapack_int ldvl, double* vr, lapack_int ldvr,
+                               double* work, lapack_int lwork );
+lapack_int LAPACKE_cgeev_work( int matrix_order, char jobvl, char jobvr,
+                               lapack_int n, lapack_complex_float* a,
+                               lapack_int lda, lapack_complex_float* w,
+                               lapack_complex_float* vl, lapack_int ldvl,
+                               lapack_complex_float* vr, lapack_int ldvr,
+                               lapack_complex_float* work, lapack_int lwork,
+                               float* rwork );
+lapack_int LAPACKE_zgeev_work( int matrix_order, char jobvl, char jobvr,
+                               lapack_int n, lapack_complex_double* a,
+                               lapack_int lda, lapack_complex_double* w,
+                               lapack_complex_double* vl, lapack_int ldvl,
+                               lapack_complex_double* vr, lapack_int ldvr,
+                               lapack_complex_double* work, lapack_int lwork,
+                               double* rwork );
+
+lapack_int LAPACKE_sgeevx_work( int matrix_order, char balanc, char jobvl,
+                                char jobvr, char sense, lapack_int n, float* a,
+                                lapack_int lda, float* wr, float* wi, float* vl,
+                                lapack_int ldvl, float* vr, lapack_int ldvr,
+                                lapack_int* ilo, lapack_int* ihi, float* scale,
+                                float* abnrm, float* rconde, float* rcondv,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgeevx_work( int matrix_order, char balanc, char jobvl,
+                                char jobvr, char sense, lapack_int n, double* a,
+                                lapack_int lda, double* wr, double* wi,
+                                double* vl, lapack_int ldvl, double* vr,
+                                lapack_int ldvr, lapack_int* ilo,
+                                lapack_int* ihi, double* scale, double* abnrm,
+                                double* rconde, double* rcondv, double* work,
+                                lapack_int lwork, lapack_int* iwork );
+lapack_int LAPACKE_cgeevx_work( int matrix_order, char balanc, char jobvl,
+                                char jobvr, char sense, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* w,
+                                lapack_complex_float* vl, lapack_int ldvl,
+                                lapack_complex_float* vr, lapack_int ldvr,
+                                lapack_int* ilo, lapack_int* ihi, float* scale,
+                                float* abnrm, float* rconde, float* rcondv,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork );
+lapack_int LAPACKE_zgeevx_work( int matrix_order, char balanc, char jobvl,
+                                char jobvr, char sense, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* w,
+                                lapack_complex_double* vl, lapack_int ldvl,
+                                lapack_complex_double* vr, lapack_int ldvr,
+                                lapack_int* ilo, lapack_int* ihi, double* scale,
+                                double* abnrm, double* rconde, double* rcondv,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork );
+
+lapack_int LAPACKE_sgehrd_work( int matrix_order, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, float* a, lapack_int lda,
+                                float* tau, float* work, lapack_int lwork );
+lapack_int LAPACKE_dgehrd_work( int matrix_order, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, double* a, lapack_int lda,
+                                double* tau, double* work, lapack_int lwork );
+lapack_int LAPACKE_cgehrd_work( int matrix_order, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgehrd_work( int matrix_order, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgejsv_work( int matrix_order, char joba, char jobu,
+                                char jobv, char jobr, char jobt, char jobp,
+                                lapack_int m, lapack_int n, float* a,
+                                lapack_int lda, float* sva, float* u,
+                                lapack_int ldu, float* v, lapack_int ldv,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgejsv_work( int matrix_order, char joba, char jobu,
+                                char jobv, char jobr, char jobt, char jobp,
+                                lapack_int m, lapack_int n, double* a,
+                                lapack_int lda, double* sva, double* u,
+                                lapack_int ldu, double* v, lapack_int ldv,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork );
+
+lapack_int LAPACKE_sgelq2_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, float* tau,
+                                float* work );
+lapack_int LAPACKE_dgelq2_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* tau,
+                                double* work );
+lapack_int LAPACKE_cgelq2_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* tau,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zgelq2_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_sgelqf_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, float* tau,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dgelqf_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* tau,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_cgelqf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgelqf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgels_work( int matrix_order, char trans, lapack_int m,
+                               lapack_int n, lapack_int nrhs, float* a,
+                               lapack_int lda, float* b, lapack_int ldb,
+                               float* work, lapack_int lwork );
+lapack_int LAPACKE_dgels_work( int matrix_order, char trans, lapack_int m,
+                               lapack_int n, lapack_int nrhs, double* a,
+                               lapack_int lda, double* b, lapack_int ldb,
+                               double* work, lapack_int lwork );
+lapack_int LAPACKE_cgels_work( int matrix_order, char trans, lapack_int m,
+                               lapack_int n, lapack_int nrhs,
+                               lapack_complex_float* a, lapack_int lda,
+                               lapack_complex_float* b, lapack_int ldb,
+                               lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgels_work( int matrix_order, char trans, lapack_int m,
+                               lapack_int n, lapack_int nrhs,
+                               lapack_complex_double* a, lapack_int lda,
+                               lapack_complex_double* b, lapack_int ldb,
+                               lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgelsd_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, float* a, lapack_int lda,
+                                float* b, lapack_int ldb, float* s, float rcond,
+                                lapack_int* rank, float* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgelsd_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, double* a, lapack_int lda,
+                                double* b, lapack_int ldb, double* s,
+                                double rcond, lapack_int* rank, double* work,
+                                lapack_int lwork, lapack_int* iwork );
+lapack_int LAPACKE_cgelsd_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb, float* s, float rcond,
+                                lapack_int* rank, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_zgelsd_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb, double* s, double rcond,
+                                lapack_int* rank, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork,
+                                lapack_int* iwork );
+
+lapack_int LAPACKE_sgelss_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, float* a, lapack_int lda,
+                                float* b, lapack_int ldb, float* s, float rcond,
+                                lapack_int* rank, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dgelss_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, double* a, lapack_int lda,
+                                double* b, lapack_int ldb, double* s,
+                                double rcond, lapack_int* rank, double* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_cgelss_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb, float* s, float rcond,
+                                lapack_int* rank, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork );
+lapack_int LAPACKE_zgelss_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb, double* s, double rcond,
+                                lapack_int* rank, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork );
+
+lapack_int LAPACKE_sgelsy_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, float* a, lapack_int lda,
+                                float* b, lapack_int ldb, lapack_int* jpvt,
+                                float rcond, lapack_int* rank, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dgelsy_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, double* a, lapack_int lda,
+                                double* b, lapack_int ldb, lapack_int* jpvt,
+                                double rcond, lapack_int* rank, double* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_cgelsy_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb, lapack_int* jpvt, float rcond,
+                                lapack_int* rank, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork );
+lapack_int LAPACKE_zgelsy_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nrhs, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb, lapack_int* jpvt, double rcond,
+                                lapack_int* rank, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork );
+
+lapack_int LAPACKE_sgeqlf_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, float* tau,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dgeqlf_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* tau,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_cgeqlf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgeqlf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgeqp3_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, lapack_int* jpvt,
+                                float* tau, float* work, lapack_int lwork );
+lapack_int LAPACKE_dgeqp3_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, lapack_int* jpvt,
+                                double* tau, double* work, lapack_int lwork );
+lapack_int LAPACKE_cgeqp3_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* jpvt, lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork );
+lapack_int LAPACKE_zgeqp3_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* jpvt, lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork );
+
+lapack_int LAPACKE_sgeqpf_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, lapack_int* jpvt,
+                                float* tau, float* work );
+lapack_int LAPACKE_dgeqpf_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, lapack_int* jpvt,
+                                double* tau, double* work );
+lapack_int LAPACKE_cgeqpf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* jpvt, lapack_complex_float* tau,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zgeqpf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* jpvt, lapack_complex_double* tau,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgeqr2_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, float* tau,
+                                float* work );
+lapack_int LAPACKE_dgeqr2_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* tau,
+                                double* work );
+lapack_int LAPACKE_cgeqr2_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* tau,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zgeqr2_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_sgeqrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, float* tau,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dgeqrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* tau,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_cgeqrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgeqrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgeqrfp_work( int matrix_order, lapack_int m, lapack_int n,
+                                 float* a, lapack_int lda, float* tau,
+                                 float* work, lapack_int lwork );
+lapack_int LAPACKE_dgeqrfp_work( int matrix_order, lapack_int m, lapack_int n,
+                                 double* a, lapack_int lda, double* tau,
+                                 double* work, lapack_int lwork );
+lapack_int LAPACKE_cgeqrfp_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* tau,
+                                 lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgeqrfp_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* tau,
+                                 lapack_complex_double* work,
+                                 lapack_int lwork );
+
+lapack_int LAPACKE_sgerfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const float* a, lapack_int lda,
+                                const float* af, lapack_int ldaf,
+                                const lapack_int* ipiv, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* ferr, float* berr, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgerfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const double* a,
+                                lapack_int lda, const double* af,
+                                lapack_int ldaf, const lapack_int* ipiv,
+                                const double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cgerfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* af,
+                                lapack_int ldaf, const lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zgerfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_double* a,
+                                lapack_int lda, const lapack_complex_double* af,
+                                lapack_int ldaf, const lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgerfsx_work( int matrix_order, char trans, char equed,
+                                 lapack_int n, lapack_int nrhs, const float* a,
+                                 lapack_int lda, const float* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const float* r, const float* c, const float* b,
+                                 lapack_int ldb, float* x, lapack_int ldx,
+                                 float* rcond, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, float* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_dgerfsx_work( int matrix_order, char trans, char equed,
+                                 lapack_int n, lapack_int nrhs, const double* a,
+                                 lapack_int lda, const double* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const double* r, const double* c,
+                                 const double* b, lapack_int ldb, double* x,
+                                 lapack_int ldx, double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, double* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_cgerfsx_work( int matrix_order, char trans, char equed,
+                                 lapack_int n, lapack_int nrhs,
+                                 const lapack_complex_float* a, lapack_int lda,
+                                 const lapack_complex_float* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const float* r, const float* c,
+                                 const lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* x, lapack_int ldx,
+                                 float* rcond, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, lapack_complex_float* work,
+                                 float* rwork );
+lapack_int LAPACKE_zgerfsx_work( int matrix_order, char trans, char equed,
+                                 lapack_int n, lapack_int nrhs,
+                                 const lapack_complex_double* a, lapack_int lda,
+                                 const lapack_complex_double* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const double* r, const double* c,
+                                 const lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_sgerqf_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, float* tau,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dgerqf_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* tau,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_cgerqf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgerqf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgesdd_work( int matrix_order, char jobz, lapack_int m,
+                                lapack_int n, float* a, lapack_int lda,
+                                float* s, float* u, lapack_int ldu, float* vt,
+                                lapack_int ldvt, float* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgesdd_work( int matrix_order, char jobz, lapack_int m,
+                                lapack_int n, double* a, lapack_int lda,
+                                double* s, double* u, lapack_int ldu,
+                                double* vt, lapack_int ldvt, double* work,
+                                lapack_int lwork, lapack_int* iwork );
+lapack_int LAPACKE_cgesdd_work( int matrix_order, char jobz, lapack_int m,
+                                lapack_int n, lapack_complex_float* a,
+                                lapack_int lda, float* s,
+                                lapack_complex_float* u, lapack_int ldu,
+                                lapack_complex_float* vt, lapack_int ldvt,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork, lapack_int* iwork );
+lapack_int LAPACKE_zgesdd_work( int matrix_order, char jobz, lapack_int m,
+                                lapack_int n, lapack_complex_double* a,
+                                lapack_int lda, double* s,
+                                lapack_complex_double* u, lapack_int ldu,
+                                lapack_complex_double* vt, lapack_int ldvt,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork, lapack_int* iwork );
+
+lapack_int LAPACKE_sgesv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               float* a, lapack_int lda, lapack_int* ipiv,
+                               float* b, lapack_int ldb );
+lapack_int LAPACKE_dgesv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               double* a, lapack_int lda, lapack_int* ipiv,
+                               double* b, lapack_int ldb );
+lapack_int LAPACKE_cgesv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               lapack_complex_float* a, lapack_int lda,
+                               lapack_int* ipiv, lapack_complex_float* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_zgesv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               lapack_complex_double* a, lapack_int lda,
+                               lapack_int* ipiv, lapack_complex_double* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_dsgesv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                                double* a, lapack_int lda, lapack_int* ipiv,
+                                double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* work, float* swork,
+                                lapack_int* iter );
+lapack_int LAPACKE_zcgesv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* ipiv, lapack_complex_double* b,
+                                lapack_int ldb, lapack_complex_double* x,
+                                lapack_int ldx, lapack_complex_double* work,
+                                lapack_complex_float* swork, double* rwork,
+                                lapack_int* iter );
+
+lapack_int LAPACKE_sgesvd_work( int matrix_order, char jobu, char jobvt,
+                                lapack_int m, lapack_int n, float* a,
+                                lapack_int lda, float* s, float* u,
+                                lapack_int ldu, float* vt, lapack_int ldvt,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dgesvd_work( int matrix_order, char jobu, char jobvt,
+                                lapack_int m, lapack_int n, double* a,
+                                lapack_int lda, double* s, double* u,
+                                lapack_int ldu, double* vt, lapack_int ldvt,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_cgesvd_work( int matrix_order, char jobu, char jobvt,
+                                lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                float* s, lapack_complex_float* u,
+                                lapack_int ldu, lapack_complex_float* vt,
+                                lapack_int ldvt, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork );
+lapack_int LAPACKE_zgesvd_work( int matrix_order, char jobu, char jobvt,
+                                lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                double* s, lapack_complex_double* u,
+                                lapack_int ldu, lapack_complex_double* vt,
+                                lapack_int ldvt, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork );
+
+lapack_int LAPACKE_sgesvj_work( int matrix_order, char joba, char jobu,
+                                char jobv, lapack_int m, lapack_int n, float* a,
+                                lapack_int lda, float* sva, lapack_int mv,
+                                float* v, lapack_int ldv, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dgesvj_work( int matrix_order, char joba, char jobu,
+                                char jobv, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* sva,
+                                lapack_int mv, double* v, lapack_int ldv,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgesvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int nrhs, float* a,
+                                lapack_int lda, float* af, lapack_int ldaf,
+                                lapack_int* ipiv, char* equed, float* r,
+                                float* c, float* b, lapack_int ldb, float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, float* work, lapack_int* iwork );
+lapack_int LAPACKE_dgesvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int nrhs, double* a,
+                                lapack_int lda, double* af, lapack_int ldaf,
+                                lapack_int* ipiv, char* equed, double* r,
+                                double* c, double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* rcond, double* ferr,
+                                double* berr, double* work, lapack_int* iwork );
+lapack_int LAPACKE_cgesvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int nrhs,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* af, lapack_int ldaf,
+                                lapack_int* ipiv, char* equed, float* r,
+                                float* c, lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_zgesvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int nrhs,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* af, lapack_int ldaf,
+                                lapack_int* ipiv, char* equed, double* r,
+                                double* c, lapack_complex_double* b,
+                                lapack_int ldb, lapack_complex_double* x,
+                                lapack_int ldx, double* rcond, double* ferr,
+                                double* berr, lapack_complex_double* work,
+                                double* rwork );
+
+lapack_int LAPACKE_sgesvxx_work( int matrix_order, char fact, char trans,
+                                 lapack_int n, lapack_int nrhs, float* a,
+                                 lapack_int lda, float* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, float* r,
+                                 float* c, float* b, lapack_int ldb, float* x,
+                                 lapack_int ldx, float* rcond, float* rpvgrw,
+                                 float* berr, lapack_int n_err_bnds,
+                                 float* err_bnds_norm, float* err_bnds_comp,
+                                 lapack_int nparams, float* params, float* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_dgesvxx_work( int matrix_order, char fact, char trans,
+                                 lapack_int n, lapack_int nrhs, double* a,
+                                 lapack_int lda, double* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, double* r,
+                                 double* c, double* b, lapack_int ldb,
+                                 double* x, lapack_int ldx, double* rcond,
+                                 double* rpvgrw, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, double* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_cgesvxx_work( int matrix_order, char fact, char trans,
+                                 lapack_int n, lapack_int nrhs,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, float* r,
+                                 float* c, lapack_complex_float* b,
+                                 lapack_int ldb, lapack_complex_float* x,
+                                 lapack_int ldx, float* rcond, float* rpvgrw,
+                                 float* berr, lapack_int n_err_bnds,
+                                 float* err_bnds_norm, float* err_bnds_comp,
+                                 lapack_int nparams, float* params,
+                                 lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zgesvxx_work( int matrix_order, char fact, char trans,
+                                 lapack_int n, lapack_int nrhs,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, double* r,
+                                 double* c, lapack_complex_double* b,
+                                 lapack_int ldb, lapack_complex_double* x,
+                                 lapack_int ldx, double* rcond, double* rpvgrw,
+                                 double* berr, lapack_int n_err_bnds,
+                                 double* err_bnds_norm, double* err_bnds_comp,
+                                 lapack_int nparams, double* params,
+                                 lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgetf2_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_dgetf2_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_cgetf2_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* ipiv );
+lapack_int LAPACKE_zgetf2_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* ipiv );
+
+lapack_int LAPACKE_sgetrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_dgetrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, lapack_int* ipiv );
+lapack_int LAPACKE_cgetrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* ipiv );
+lapack_int LAPACKE_zgetrf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* ipiv );
+
+lapack_int LAPACKE_sgetri_work( int matrix_order, lapack_int n, float* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dgetri_work( int matrix_order, lapack_int n, double* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_cgetri_work( int matrix_order, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                const lapack_int* ipiv,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgetri_work( int matrix_order, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                const lapack_int* ipiv,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgetrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const float* a, lapack_int lda,
+                                const lapack_int* ipiv, float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_dgetrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const double* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                double* b, lapack_int ldb );
+lapack_int LAPACKE_cgetrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zgetrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_double* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sggbak_work( int matrix_order, char job, char side,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                const float* lscale, const float* rscale,
+                                lapack_int m, float* v, lapack_int ldv );
+lapack_int LAPACKE_dggbak_work( int matrix_order, char job, char side,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                const double* lscale, const double* rscale,
+                                lapack_int m, double* v, lapack_int ldv );
+lapack_int LAPACKE_cggbak_work( int matrix_order, char job, char side,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                const float* lscale, const float* rscale,
+                                lapack_int m, lapack_complex_float* v,
+                                lapack_int ldv );
+lapack_int LAPACKE_zggbak_work( int matrix_order, char job, char side,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                const double* lscale, const double* rscale,
+                                lapack_int m, lapack_complex_double* v,
+                                lapack_int ldv );
+
+lapack_int LAPACKE_sggbal_work( int matrix_order, char job, lapack_int n,
+                                float* a, lapack_int lda, float* b,
+                                lapack_int ldb, lapack_int* ilo,
+                                lapack_int* ihi, float* lscale, float* rscale,
+                                float* work );
+lapack_int LAPACKE_dggbal_work( int matrix_order, char job, lapack_int n,
+                                double* a, lapack_int lda, double* b,
+                                lapack_int ldb, lapack_int* ilo,
+                                lapack_int* ihi, double* lscale, double* rscale,
+                                double* work );
+lapack_int LAPACKE_cggbal_work( int matrix_order, char job, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                lapack_int* ilo, lapack_int* ihi, float* lscale,
+                                float* rscale, float* work );
+lapack_int LAPACKE_zggbal_work( int matrix_order, char job, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_int* ilo, lapack_int* ihi,
+                                double* lscale, double* rscale, double* work );
+
+lapack_int LAPACKE_sgges_work( int matrix_order, char jobvsl, char jobvsr,
+                               char sort, LAPACK_S_SELECT3 selctg, lapack_int n,
+                               float* a, lapack_int lda, float* b,
+                               lapack_int ldb, lapack_int* sdim, float* alphar,
+                               float* alphai, float* beta, float* vsl,
+                               lapack_int ldvsl, float* vsr, lapack_int ldvsr,
+                               float* work, lapack_int lwork,
+                               lapack_logical* bwork );
+lapack_int LAPACKE_dgges_work( int matrix_order, char jobvsl, char jobvsr,
+                               char sort, LAPACK_D_SELECT3 selctg, lapack_int n,
+                               double* a, lapack_int lda, double* b,
+                               lapack_int ldb, lapack_int* sdim, double* alphar,
+                               double* alphai, double* beta, double* vsl,
+                               lapack_int ldvsl, double* vsr, lapack_int ldvsr,
+                               double* work, lapack_int lwork,
+                               lapack_logical* bwork );
+lapack_int LAPACKE_cgges_work( int matrix_order, char jobvsl, char jobvsr,
+                               char sort, LAPACK_C_SELECT2 selctg, lapack_int n,
+                               lapack_complex_float* a, lapack_int lda,
+                               lapack_complex_float* b, lapack_int ldb,
+                               lapack_int* sdim, lapack_complex_float* alpha,
+                               lapack_complex_float* beta,
+                               lapack_complex_float* vsl, lapack_int ldvsl,
+                               lapack_complex_float* vsr, lapack_int ldvsr,
+                               lapack_complex_float* work, lapack_int lwork,
+                               float* rwork, lapack_logical* bwork );
+lapack_int LAPACKE_zgges_work( int matrix_order, char jobvsl, char jobvsr,
+                               char sort, LAPACK_Z_SELECT2 selctg, lapack_int n,
+                               lapack_complex_double* a, lapack_int lda,
+                               lapack_complex_double* b, lapack_int ldb,
+                               lapack_int* sdim, lapack_complex_double* alpha,
+                               lapack_complex_double* beta,
+                               lapack_complex_double* vsl, lapack_int ldvsl,
+                               lapack_complex_double* vsr, lapack_int ldvsr,
+                               lapack_complex_double* work, lapack_int lwork,
+                               double* rwork, lapack_logical* bwork );
+
+lapack_int LAPACKE_sggesx_work( int matrix_order, char jobvsl, char jobvsr,
+                                char sort, LAPACK_S_SELECT3 selctg, char sense,
+                                lapack_int n, float* a, lapack_int lda,
+                                float* b, lapack_int ldb, lapack_int* sdim,
+                                float* alphar, float* alphai, float* beta,
+                                float* vsl, lapack_int ldvsl, float* vsr,
+                                lapack_int ldvsr, float* rconde, float* rcondv,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork,
+                                lapack_logical* bwork );
+lapack_int LAPACKE_dggesx_work( int matrix_order, char jobvsl, char jobvsr,
+                                char sort, LAPACK_D_SELECT3 selctg, char sense,
+                                lapack_int n, double* a, lapack_int lda,
+                                double* b, lapack_int ldb, lapack_int* sdim,
+                                double* alphar, double* alphai, double* beta,
+                                double* vsl, lapack_int ldvsl, double* vsr,
+                                lapack_int ldvsr, double* rconde,
+                                double* rcondv, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork,
+                                lapack_logical* bwork );
+lapack_int LAPACKE_cggesx_work( int matrix_order, char jobvsl, char jobvsr,
+                                char sort, LAPACK_C_SELECT2 selctg, char sense,
+                                lapack_int n, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb, lapack_int* sdim,
+                                lapack_complex_float* alpha,
+                                lapack_complex_float* beta,
+                                lapack_complex_float* vsl, lapack_int ldvsl,
+                                lapack_complex_float* vsr, lapack_int ldvsr,
+                                float* rconde, float* rcondv,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork, lapack_int* iwork,
+                                lapack_int liwork, lapack_logical* bwork );
+lapack_int LAPACKE_zggesx_work( int matrix_order, char jobvsl, char jobvsr,
+                                char sort, LAPACK_Z_SELECT2 selctg, char sense,
+                                lapack_int n, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb, lapack_int* sdim,
+                                lapack_complex_double* alpha,
+                                lapack_complex_double* beta,
+                                lapack_complex_double* vsl, lapack_int ldvsl,
+                                lapack_complex_double* vsr, lapack_int ldvsr,
+                                double* rconde, double* rcondv,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork, lapack_int* iwork,
+                                lapack_int liwork, lapack_logical* bwork );
+
+lapack_int LAPACKE_sggev_work( int matrix_order, char jobvl, char jobvr,
+                               lapack_int n, float* a, lapack_int lda, float* b,
+                               lapack_int ldb, float* alphar, float* alphai,
+                               float* beta, float* vl, lapack_int ldvl,
+                               float* vr, lapack_int ldvr, float* work,
+                               lapack_int lwork );
+lapack_int LAPACKE_dggev_work( int matrix_order, char jobvl, char jobvr,
+                               lapack_int n, double* a, lapack_int lda,
+                               double* b, lapack_int ldb, double* alphar,
+                               double* alphai, double* beta, double* vl,
+                               lapack_int ldvl, double* vr, lapack_int ldvr,
+                               double* work, lapack_int lwork );
+lapack_int LAPACKE_cggev_work( int matrix_order, char jobvl, char jobvr,
+                               lapack_int n, lapack_complex_float* a,
+                               lapack_int lda, lapack_complex_float* b,
+                               lapack_int ldb, lapack_complex_float* alpha,
+                               lapack_complex_float* beta,
+                               lapack_complex_float* vl, lapack_int ldvl,
+                               lapack_complex_float* vr, lapack_int ldvr,
+                               lapack_complex_float* work, lapack_int lwork,
+                               float* rwork );
+lapack_int LAPACKE_zggev_work( int matrix_order, char jobvl, char jobvr,
+                               lapack_int n, lapack_complex_double* a,
+                               lapack_int lda, lapack_complex_double* b,
+                               lapack_int ldb, lapack_complex_double* alpha,
+                               lapack_complex_double* beta,
+                               lapack_complex_double* vl, lapack_int ldvl,
+                               lapack_complex_double* vr, lapack_int ldvr,
+                               lapack_complex_double* work, lapack_int lwork,
+                               double* rwork );
+
+lapack_int LAPACKE_sggevx_work( int matrix_order, char balanc, char jobvl,
+                                char jobvr, char sense, lapack_int n, float* a,
+                                lapack_int lda, float* b, lapack_int ldb,
+                                float* alphar, float* alphai, float* beta,
+                                float* vl, lapack_int ldvl, float* vr,
+                                lapack_int ldvr, lapack_int* ilo,
+                                lapack_int* ihi, float* lscale, float* rscale,
+                                float* abnrm, float* bbnrm, float* rconde,
+                                float* rcondv, float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_logical* bwork );
+lapack_int LAPACKE_dggevx_work( int matrix_order, char balanc, char jobvl,
+                                char jobvr, char sense, lapack_int n, double* a,
+                                lapack_int lda, double* b, lapack_int ldb,
+                                double* alphar, double* alphai, double* beta,
+                                double* vl, lapack_int ldvl, double* vr,
+                                lapack_int ldvr, lapack_int* ilo,
+                                lapack_int* ihi, double* lscale, double* rscale,
+                                double* abnrm, double* bbnrm, double* rconde,
+                                double* rcondv, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_logical* bwork );
+lapack_int LAPACKE_cggevx_work( int matrix_order, char balanc, char jobvl,
+                                char jobvr, char sense, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* alpha,
+                                lapack_complex_float* beta,
+                                lapack_complex_float* vl, lapack_int ldvl,
+                                lapack_complex_float* vr, lapack_int ldvr,
+                                lapack_int* ilo, lapack_int* ihi, float* lscale,
+                                float* rscale, float* abnrm, float* bbnrm,
+                                float* rconde, float* rcondv,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork, lapack_int* iwork,
+                                lapack_logical* bwork );
+lapack_int LAPACKE_zggevx_work( int matrix_order, char balanc, char jobvl,
+                                char jobvr, char sense, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* alpha,
+                                lapack_complex_double* beta,
+                                lapack_complex_double* vl, lapack_int ldvl,
+                                lapack_complex_double* vr, lapack_int ldvr,
+                                lapack_int* ilo, lapack_int* ihi,
+                                double* lscale, double* rscale, double* abnrm,
+                                double* bbnrm, double* rconde, double* rcondv,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork, lapack_int* iwork,
+                                lapack_logical* bwork );
+
+lapack_int LAPACKE_sggglm_work( int matrix_order, lapack_int n, lapack_int m,
+                                lapack_int p, float* a, lapack_int lda,
+                                float* b, lapack_int ldb, float* d, float* x,
+                                float* y, float* work, lapack_int lwork );
+lapack_int LAPACKE_dggglm_work( int matrix_order, lapack_int n, lapack_int m,
+                                lapack_int p, double* a, lapack_int lda,
+                                double* b, lapack_int ldb, double* d, double* x,
+                                double* y, double* work, lapack_int lwork );
+lapack_int LAPACKE_cggglm_work( int matrix_order, lapack_int n, lapack_int m,
+                                lapack_int p, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* d,
+                                lapack_complex_float* x,
+                                lapack_complex_float* y,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zggglm_work( int matrix_order, lapack_int n, lapack_int m,
+                                lapack_int p, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb, lapack_complex_double* d,
+                                lapack_complex_double* x,
+                                lapack_complex_double* y,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sgghrd_work( int matrix_order, char compq, char compz,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                float* a, lapack_int lda, float* b,
+                                lapack_int ldb, float* q, lapack_int ldq,
+                                float* z, lapack_int ldz );
+lapack_int LAPACKE_dgghrd_work( int matrix_order, char compq, char compz,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                double* a, lapack_int lda, double* b,
+                                lapack_int ldb, double* q, lapack_int ldq,
+                                double* z, lapack_int ldz );
+lapack_int LAPACKE_cgghrd_work( int matrix_order, char compq, char compz,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_complex_float* z, lapack_int ldz );
+lapack_int LAPACKE_zgghrd_work( int matrix_order, char compq, char compz,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_complex_double* z, lapack_int ldz );
+
+lapack_int LAPACKE_sgglse_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int p, float* a, lapack_int lda,
+                                float* b, lapack_int ldb, float* c, float* d,
+                                float* x, float* work, lapack_int lwork );
+lapack_int LAPACKE_dgglse_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int p, double* a, lapack_int lda,
+                                double* b, lapack_int ldb, double* c, double* d,
+                                double* x, double* work, lapack_int lwork );
+lapack_int LAPACKE_cgglse_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int p, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* c,
+                                lapack_complex_float* d,
+                                lapack_complex_float* x,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zgglse_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int p, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb, lapack_complex_double* c,
+                                lapack_complex_double* d,
+                                lapack_complex_double* x,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sggqrf_work( int matrix_order, lapack_int n, lapack_int m,
+                                lapack_int p, float* a, lapack_int lda,
+                                float* taua, float* b, lapack_int ldb,
+                                float* taub, float* work, lapack_int lwork );
+lapack_int LAPACKE_dggqrf_work( int matrix_order, lapack_int n, lapack_int m,
+                                lapack_int p, double* a, lapack_int lda,
+                                double* taua, double* b, lapack_int ldb,
+                                double* taub, double* work, lapack_int lwork );
+lapack_int LAPACKE_cggqrf_work( int matrix_order, lapack_int n, lapack_int m,
+                                lapack_int p, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* taua,
+                                lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* taub,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zggqrf_work( int matrix_order, lapack_int n, lapack_int m,
+                                lapack_int p, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* taua,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* taub,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sggrqf_work( int matrix_order, lapack_int m, lapack_int p,
+                                lapack_int n, float* a, lapack_int lda,
+                                float* taua, float* b, lapack_int ldb,
+                                float* taub, float* work, lapack_int lwork );
+lapack_int LAPACKE_dggrqf_work( int matrix_order, lapack_int m, lapack_int p,
+                                lapack_int n, double* a, lapack_int lda,
+                                double* taua, double* b, lapack_int ldb,
+                                double* taub, double* work, lapack_int lwork );
+lapack_int LAPACKE_cggrqf_work( int matrix_order, lapack_int m, lapack_int p,
+                                lapack_int n, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* taua,
+                                lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* taub,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zggrqf_work( int matrix_order, lapack_int m, lapack_int p,
+                                lapack_int n, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* taua,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* taub,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sggsvd_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int n,
+                                lapack_int p, lapack_int* k, lapack_int* l,
+                                float* a, lapack_int lda, float* b,
+                                lapack_int ldb, float* alpha, float* beta,
+                                float* u, lapack_int ldu, float* v,
+                                lapack_int ldv, float* q, lapack_int ldq,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dggsvd_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int n,
+                                lapack_int p, lapack_int* k, lapack_int* l,
+                                double* a, lapack_int lda, double* b,
+                                lapack_int ldb, double* alpha, double* beta,
+                                double* u, lapack_int ldu, double* v,
+                                lapack_int ldv, double* q, lapack_int ldq,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cggsvd_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int n,
+                                lapack_int p, lapack_int* k, lapack_int* l,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                float* alpha, float* beta,
+                                lapack_complex_float* u, lapack_int ldu,
+                                lapack_complex_float* v, lapack_int ldv,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_complex_float* work, float* rwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_zggsvd_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int n,
+                                lapack_int p, lapack_int* k, lapack_int* l,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                double* alpha, double* beta,
+                                lapack_complex_double* u, lapack_int ldu,
+                                lapack_complex_double* v, lapack_int ldv,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_complex_double* work, double* rwork,
+                                lapack_int* iwork );
+
+lapack_int LAPACKE_sggsvp_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int p,
+                                lapack_int n, float* a, lapack_int lda,
+                                float* b, lapack_int ldb, float tola,
+                                float tolb, lapack_int* k, lapack_int* l,
+                                float* u, lapack_int ldu, float* v,
+                                lapack_int ldv, float* q, lapack_int ldq,
+                                lapack_int* iwork, float* tau, float* work );
+lapack_int LAPACKE_dggsvp_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int p,
+                                lapack_int n, double* a, lapack_int lda,
+                                double* b, lapack_int ldb, double tola,
+                                double tolb, lapack_int* k, lapack_int* l,
+                                double* u, lapack_int ldu, double* v,
+                                lapack_int ldv, double* q, lapack_int ldq,
+                                lapack_int* iwork, double* tau, double* work );
+lapack_int LAPACKE_cggsvp_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int p,
+                                lapack_int n, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb, float tola, float tolb,
+                                lapack_int* k, lapack_int* l,
+                                lapack_complex_float* u, lapack_int ldu,
+                                lapack_complex_float* v, lapack_int ldv,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_int* iwork, float* rwork,
+                                lapack_complex_float* tau,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zggsvp_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int p,
+                                lapack_int n, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb, double tola, double tolb,
+                                lapack_int* k, lapack_int* l,
+                                lapack_complex_double* u, lapack_int ldu,
+                                lapack_complex_double* v, lapack_int ldv,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_int* iwork, double* rwork,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_sgtcon_work( char norm, lapack_int n, const float* dl,
+                                const float* d, const float* du,
+                                const float* du2, const lapack_int* ipiv,
+                                float anorm, float* rcond, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgtcon_work( char norm, lapack_int n, const double* dl,
+                                const double* d, const double* du,
+                                const double* du2, const lapack_int* ipiv,
+                                double anorm, double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cgtcon_work( char norm, lapack_int n,
+                                const lapack_complex_float* dl,
+                                const lapack_complex_float* d,
+                                const lapack_complex_float* du,
+                                const lapack_complex_float* du2,
+                                const lapack_int* ipiv, float anorm,
+                                float* rcond, lapack_complex_float* work );
+lapack_int LAPACKE_zgtcon_work( char norm, lapack_int n,
+                                const lapack_complex_double* dl,
+                                const lapack_complex_double* d,
+                                const lapack_complex_double* du,
+                                const lapack_complex_double* du2,
+                                const lapack_int* ipiv, double anorm,
+                                double* rcond, lapack_complex_double* work );
+
+lapack_int LAPACKE_sgtrfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const float* dl,
+                                const float* d, const float* du,
+                                const float* dlf, const float* df,
+                                const float* duf, const float* du2,
+                                const lapack_int* ipiv, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* ferr, float* berr, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dgtrfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const double* dl,
+                                const double* d, const double* du,
+                                const double* dlf, const double* df,
+                                const double* duf, const double* du2,
+                                const lapack_int* ipiv, const double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* ferr, double* berr, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cgtrfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* dl,
+                                const lapack_complex_float* d,
+                                const lapack_complex_float* du,
+                                const lapack_complex_float* dlf,
+                                const lapack_complex_float* df,
+                                const lapack_complex_float* duf,
+                                const lapack_complex_float* du2,
+                                const lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zgtrfs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs,
+                                const lapack_complex_double* dl,
+                                const lapack_complex_double* d,
+                                const lapack_complex_double* du,
+                                const lapack_complex_double* dlf,
+                                const lapack_complex_double* df,
+                                const lapack_complex_double* duf,
+                                const lapack_complex_double* du2,
+                                const lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgtsv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               float* dl, float* d, float* du, float* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_dgtsv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               double* dl, double* d, double* du, double* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_cgtsv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               lapack_complex_float* dl,
+                               lapack_complex_float* d,
+                               lapack_complex_float* du,
+                               lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zgtsv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               lapack_complex_double* dl,
+                               lapack_complex_double* d,
+                               lapack_complex_double* du,
+                               lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sgtsvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int nrhs, const float* dl,
+                                const float* d, const float* du, float* dlf,
+                                float* df, float* duf, float* du2,
+                                lapack_int* ipiv, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dgtsvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int nrhs, const double* dl,
+                                const double* d, const double* du, double* dlf,
+                                double* df, double* duf, double* du2,
+                                lapack_int* ipiv, const double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cgtsvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* dl,
+                                const lapack_complex_float* d,
+                                const lapack_complex_float* du,
+                                lapack_complex_float* dlf,
+                                lapack_complex_float* df,
+                                lapack_complex_float* duf,
+                                lapack_complex_float* du2, lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zgtsvx_work( int matrix_order, char fact, char trans,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* dl,
+                                const lapack_complex_double* d,
+                                const lapack_complex_double* du,
+                                lapack_complex_double* dlf,
+                                lapack_complex_double* df,
+                                lapack_complex_double* duf,
+                                lapack_complex_double* du2, lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sgttrf_work( lapack_int n, float* dl, float* d, float* du,
+                                float* du2, lapack_int* ipiv );
+lapack_int LAPACKE_dgttrf_work( lapack_int n, double* dl, double* d, double* du,
+                                double* du2, lapack_int* ipiv );
+lapack_int LAPACKE_cgttrf_work( lapack_int n, lapack_complex_float* dl,
+                                lapack_complex_float* d,
+                                lapack_complex_float* du,
+                                lapack_complex_float* du2, lapack_int* ipiv );
+lapack_int LAPACKE_zgttrf_work( lapack_int n, lapack_complex_double* dl,
+                                lapack_complex_double* d,
+                                lapack_complex_double* du,
+                                lapack_complex_double* du2, lapack_int* ipiv );
+
+lapack_int LAPACKE_sgttrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const float* dl,
+                                const float* d, const float* du,
+                                const float* du2, const lapack_int* ipiv,
+                                float* b, lapack_int ldb );
+lapack_int LAPACKE_dgttrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const double* dl,
+                                const double* d, const double* du,
+                                const double* du2, const lapack_int* ipiv,
+                                double* b, lapack_int ldb );
+lapack_int LAPACKE_cgttrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* dl,
+                                const lapack_complex_float* d,
+                                const lapack_complex_float* du,
+                                const lapack_complex_float* du2,
+                                const lapack_int* ipiv, lapack_complex_float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_zgttrs_work( int matrix_order, char trans, lapack_int n,
+                                lapack_int nrhs,
+                                const lapack_complex_double* dl,
+                                const lapack_complex_double* d,
+                                const lapack_complex_double* du,
+                                const lapack_complex_double* du2,
+                                const lapack_int* ipiv,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_chbev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_int kd,
+                               lapack_complex_float* ab, lapack_int ldab,
+                               float* w, lapack_complex_float* z,
+                               lapack_int ldz, lapack_complex_float* work,
+                               float* rwork );
+lapack_int LAPACKE_zhbev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_int kd,
+                               lapack_complex_double* ab, lapack_int ldab,
+                               double* w, lapack_complex_double* z,
+                               lapack_int ldz, lapack_complex_double* work,
+                               double* rwork );
+
+lapack_int LAPACKE_chbevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_int kd,
+                                lapack_complex_float* ab, lapack_int ldab,
+                                float* w, lapack_complex_float* z,
+                                lapack_int ldz, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_zhbevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_int kd,
+                                lapack_complex_double* ab, lapack_int ldab,
+                                double* w, lapack_complex_double* z,
+                                lapack_int ldz, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+
+lapack_int LAPACKE_chbevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, lapack_int kd,
+                                lapack_complex_float* ab, lapack_int ldab,
+                                lapack_complex_float* q, lapack_int ldq,
+                                float vl, float vu, lapack_int il,
+                                lapack_int iu, float abstol, lapack_int* m,
+                                float* w, lapack_complex_float* z,
+                                lapack_int ldz, lapack_complex_float* work,
+                                float* rwork, lapack_int* iwork,
+                                lapack_int* ifail );
+lapack_int LAPACKE_zhbevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, lapack_int kd,
+                                lapack_complex_double* ab, lapack_int ldab,
+                                lapack_complex_double* q, lapack_int ldq,
+                                double vl, double vu, lapack_int il,
+                                lapack_int iu, double abstol, lapack_int* m,
+                                double* w, lapack_complex_double* z,
+                                lapack_int ldz, lapack_complex_double* work,
+                                double* rwork, lapack_int* iwork,
+                                lapack_int* ifail );
+
+lapack_int LAPACKE_chbgst_work( int matrix_order, char vect, char uplo,
+                                lapack_int n, lapack_int ka, lapack_int kb,
+                                lapack_complex_float* ab, lapack_int ldab,
+                                const lapack_complex_float* bb, lapack_int ldbb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zhbgst_work( int matrix_order, char vect, char uplo,
+                                lapack_int n, lapack_int ka, lapack_int kb,
+                                lapack_complex_double* ab, lapack_int ldab,
+                                const lapack_complex_double* bb,
+                                lapack_int ldbb, lapack_complex_double* x,
+                                lapack_int ldx, lapack_complex_double* work,
+                                double* rwork );
+
+lapack_int LAPACKE_chbgv_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_int ka, lapack_int kb,
+                               lapack_complex_float* ab, lapack_int ldab,
+                               lapack_complex_float* bb, lapack_int ldbb,
+                               float* w, lapack_complex_float* z,
+                               lapack_int ldz, lapack_complex_float* work,
+                               float* rwork );
+lapack_int LAPACKE_zhbgv_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_int ka, lapack_int kb,
+                               lapack_complex_double* ab, lapack_int ldab,
+                               lapack_complex_double* bb, lapack_int ldbb,
+                               double* w, lapack_complex_double* z,
+                               lapack_int ldz, lapack_complex_double* work,
+                               double* rwork );
+
+lapack_int LAPACKE_chbgvd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_int ka, lapack_int kb,
+                                lapack_complex_float* ab, lapack_int ldab,
+                                lapack_complex_float* bb, lapack_int ldbb,
+                                float* w, lapack_complex_float* z,
+                                lapack_int ldz, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_zhbgvd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_int ka, lapack_int kb,
+                                lapack_complex_double* ab, lapack_int ldab,
+                                lapack_complex_double* bb, lapack_int ldbb,
+                                double* w, lapack_complex_double* z,
+                                lapack_int ldz, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+
+lapack_int LAPACKE_chbgvx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, lapack_int ka,
+                                lapack_int kb, lapack_complex_float* ab,
+                                lapack_int ldab, lapack_complex_float* bb,
+                                lapack_int ldbb, lapack_complex_float* q,
+                                lapack_int ldq, float vl, float vu,
+                                lapack_int il, lapack_int iu, float abstol,
+                                lapack_int* m, float* w,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_complex_float* work, float* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+lapack_int LAPACKE_zhbgvx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, lapack_int ka,
+                                lapack_int kb, lapack_complex_double* ab,
+                                lapack_int ldab, lapack_complex_double* bb,
+                                lapack_int ldbb, lapack_complex_double* q,
+                                lapack_int ldq, double vl, double vu,
+                                lapack_int il, lapack_int iu, double abstol,
+                                lapack_int* m, double* w,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_complex_double* work, double* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_chbtrd_work( int matrix_order, char vect, char uplo,
+                                lapack_int n, lapack_int kd,
+                                lapack_complex_float* ab, lapack_int ldab,
+                                float* d, float* e, lapack_complex_float* q,
+                                lapack_int ldq, lapack_complex_float* work );
+lapack_int LAPACKE_zhbtrd_work( int matrix_order, char vect, char uplo,
+                                lapack_int n, lapack_int kd,
+                                lapack_complex_double* ab, lapack_int ldab,
+                                double* d, double* e, lapack_complex_double* q,
+                                lapack_int ldq, lapack_complex_double* work );
+
+lapack_int LAPACKE_checon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_int* ipiv, float anorm,
+                                float* rcond, lapack_complex_float* work );
+lapack_int LAPACKE_zhecon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_int* ipiv, double anorm,
+                                double* rcond, lapack_complex_double* work );
+
+lapack_int LAPACKE_cheequb_work( int matrix_order, char uplo, lapack_int n,
+                                 const lapack_complex_float* a, lapack_int lda,
+                                 float* s, float* scond, float* amax,
+                                 lapack_complex_float* work );
+lapack_int LAPACKE_zheequb_work( int matrix_order, char uplo, lapack_int n,
+                                 const lapack_complex_double* a, lapack_int lda,
+                                 double* s, double* scond, double* amax,
+                                 lapack_complex_double* work );
+
+lapack_int LAPACKE_cheev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_complex_float* a,
+                               lapack_int lda, float* w,
+                               lapack_complex_float* work, lapack_int lwork,
+                               float* rwork );
+lapack_int LAPACKE_zheev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_complex_double* a,
+                               lapack_int lda, double* w,
+                               lapack_complex_double* work, lapack_int lwork,
+                               double* rwork );
+
+lapack_int LAPACKE_cheevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_complex_float* a,
+                                lapack_int lda, float* w,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork, lapack_int lrwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_zheevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_complex_double* a,
+                                lapack_int lda, double* w,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork, lapack_int lrwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_cheevr_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                float vl, float vu, lapack_int il,
+                                lapack_int iu, float abstol, lapack_int* m,
+                                float* w, lapack_complex_float* z,
+                                lapack_int ldz, lapack_int* isuppz,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork, lapack_int lrwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_zheevr_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                double vl, double vu, lapack_int il,
+                                lapack_int iu, double abstol, lapack_int* m,
+                                double* w, lapack_complex_double* z,
+                                lapack_int ldz, lapack_int* isuppz,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork, lapack_int lrwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_cheevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                float vl, float vu, lapack_int il,
+                                lapack_int iu, float abstol, lapack_int* m,
+                                float* w, lapack_complex_float* z,
+                                lapack_int ldz, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+lapack_int LAPACKE_zheevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                double vl, double vu, lapack_int il,
+                                lapack_int iu, double abstol, lapack_int* m,
+                                double* w, lapack_complex_double* z,
+                                lapack_int ldz, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_chegst_work( int matrix_order, lapack_int itype, char uplo,
+                                lapack_int n, lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_zhegst_work( int matrix_order, lapack_int itype, char uplo,
+                                lapack_int n, lapack_complex_double* a,
+                                lapack_int lda, const lapack_complex_double* b,
+                                lapack_int ldb );
+
+lapack_int LAPACKE_chegv_work( int matrix_order, lapack_int itype, char jobz,
+                               char uplo, lapack_int n, lapack_complex_float* a,
+                               lapack_int lda, lapack_complex_float* b,
+                               lapack_int ldb, float* w,
+                               lapack_complex_float* work, lapack_int lwork,
+                               float* rwork );
+lapack_int LAPACKE_zhegv_work( int matrix_order, lapack_int itype, char jobz,
+                               char uplo, lapack_int n,
+                               lapack_complex_double* a, lapack_int lda,
+                               lapack_complex_double* b, lapack_int ldb,
+                               double* w, lapack_complex_double* work,
+                               lapack_int lwork, double* rwork );
+
+lapack_int LAPACKE_chegvd_work( int matrix_order, lapack_int itype, char jobz,
+                                char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                float* w, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_zhegvd_work( int matrix_order, lapack_int itype, char jobz,
+                                char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                double* w, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+
+lapack_int LAPACKE_chegvx_work( int matrix_order, lapack_int itype, char jobz,
+                                char range, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                float vl, float vu, lapack_int il,
+                                lapack_int iu, float abstol, lapack_int* m,
+                                float* w, lapack_complex_float* z,
+                                lapack_int ldz, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+lapack_int LAPACKE_zhegvx_work( int matrix_order, lapack_int itype, char jobz,
+                                char range, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                double vl, double vu, lapack_int il,
+                                lapack_int iu, double abstol, lapack_int* m,
+                                double* w, lapack_complex_double* z,
+                                lapack_int ldz, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_cherfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* af,
+                                lapack_int ldaf, const lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zherfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_double* a,
+                                lapack_int lda, const lapack_complex_double* af,
+                                lapack_int ldaf, const lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_cherfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs,
+                                 const lapack_complex_float* a, lapack_int lda,
+                                 const lapack_complex_float* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const float* s, const lapack_complex_float* b,
+                                 lapack_int ldb, lapack_complex_float* x,
+                                 lapack_int ldx, float* rcond, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, lapack_complex_float* work,
+                                 float* rwork );
+lapack_int LAPACKE_zherfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs,
+                                 const lapack_complex_double* a, lapack_int lda,
+                                 const lapack_complex_double* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const double* s,
+                                 const lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_chesv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_float* a,
+                               lapack_int lda, lapack_int* ipiv,
+                               lapack_complex_float* b, lapack_int ldb,
+                               lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zhesv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_double* a,
+                               lapack_int lda, lapack_int* ipiv,
+                               lapack_complex_double* b, lapack_int ldb,
+                               lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_chesvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* af, lapack_int ldaf,
+                                lapack_int* ipiv, const lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork );
+lapack_int LAPACKE_zhesvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* af, lapack_int ldaf,
+                                lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork );
+
+lapack_int LAPACKE_chesvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, float* s,
+                                 lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* x, lapack_int ldx,
+                                 float* rcond, float* rpvgrw, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, lapack_complex_float* work,
+                                 float* rwork );
+lapack_int LAPACKE_zhesvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, double* s,
+                                 lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* rpvgrw, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_chetrd_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                float* d, float* e, lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zhetrd_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                double* d, double* e,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_chetrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* ipiv, lapack_complex_float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_zhetrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* ipiv, lapack_complex_double* work,
+                                lapack_int lwork );
+
+lapack_int LAPACKE_chetri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                const lapack_int* ipiv,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zhetri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                const lapack_int* ipiv,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_chetrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zhetrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_double* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_chfrk_work( int matrix_order, char transr, char uplo,
+                               char trans, lapack_int n, lapack_int k,
+                               float alpha, const lapack_complex_float* a,
+                               lapack_int lda, float beta,
+                               lapack_complex_float* c );
+lapack_int LAPACKE_zhfrk_work( int matrix_order, char transr, char uplo,
+                               char trans, lapack_int n, lapack_int k,
+                               double alpha, const lapack_complex_double* a,
+                               lapack_int lda, double beta,
+                               lapack_complex_double* c );
+
+lapack_int LAPACKE_shgeqz_work( int matrix_order, char job, char compq,
+                                char compz, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, float* h, lapack_int ldh,
+                                float* t, lapack_int ldt, float* alphar,
+                                float* alphai, float* beta, float* q,
+                                lapack_int ldq, float* z, lapack_int ldz,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dhgeqz_work( int matrix_order, char job, char compq,
+                                char compz, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, double* h, lapack_int ldh,
+                                double* t, lapack_int ldt, double* alphar,
+                                double* alphai, double* beta, double* q,
+                                lapack_int ldq, double* z, lapack_int ldz,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_chgeqz_work( int matrix_order, char job, char compq,
+                                char compz, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, lapack_complex_float* h,
+                                lapack_int ldh, lapack_complex_float* t,
+                                lapack_int ldt, lapack_complex_float* alpha,
+                                lapack_complex_float* beta,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork );
+lapack_int LAPACKE_zhgeqz_work( int matrix_order, char job, char compq,
+                                char compz, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, lapack_complex_double* h,
+                                lapack_int ldh, lapack_complex_double* t,
+                                lapack_int ldt, lapack_complex_double* alpha,
+                                lapack_complex_double* beta,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork );
+
+lapack_int LAPACKE_chpcon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* ap,
+                                const lapack_int* ipiv, float anorm,
+                                float* rcond, lapack_complex_float* work );
+lapack_int LAPACKE_zhpcon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* ap,
+                                const lapack_int* ipiv, double anorm,
+                                double* rcond, lapack_complex_double* work );
+
+lapack_int LAPACKE_chpev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_complex_float* ap, float* w,
+                               lapack_complex_float* z, lapack_int ldz,
+                               lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zhpev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_complex_double* ap,
+                               double* w, lapack_complex_double* z,
+                               lapack_int ldz, lapack_complex_double* work,
+                               double* rwork );
+
+lapack_int LAPACKE_chpevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_complex_float* ap,
+                                float* w, lapack_complex_float* z,
+                                lapack_int ldz, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_zhpevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_complex_double* ap,
+                                double* w, lapack_complex_double* z,
+                                lapack_int ldz, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+
+lapack_int LAPACKE_chpevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n,
+                                lapack_complex_float* ap, float vl, float vu,
+                                lapack_int il, lapack_int iu, float abstol,
+                                lapack_int* m, float* w,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_complex_float* work, float* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+lapack_int LAPACKE_zhpevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n,
+                                lapack_complex_double* ap, double vl, double vu,
+                                lapack_int il, lapack_int iu, double abstol,
+                                lapack_int* m, double* w,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_complex_double* work, double* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_chpgst_work( int matrix_order, lapack_int itype, char uplo,
+                                lapack_int n, lapack_complex_float* ap,
+                                const lapack_complex_float* bp );
+lapack_int LAPACKE_zhpgst_work( int matrix_order, lapack_int itype, char uplo,
+                                lapack_int n, lapack_complex_double* ap,
+                                const lapack_complex_double* bp );
+
+lapack_int LAPACKE_chpgv_work( int matrix_order, lapack_int itype, char jobz,
+                               char uplo, lapack_int n,
+                               lapack_complex_float* ap,
+                               lapack_complex_float* bp, float* w,
+                               lapack_complex_float* z, lapack_int ldz,
+                               lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zhpgv_work( int matrix_order, lapack_int itype, char jobz,
+                               char uplo, lapack_int n,
+                               lapack_complex_double* ap,
+                               lapack_complex_double* bp, double* w,
+                               lapack_complex_double* z, lapack_int ldz,
+                               lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_chpgvd_work( int matrix_order, lapack_int itype, char jobz,
+                                char uplo, lapack_int n,
+                                lapack_complex_float* ap,
+                                lapack_complex_float* bp, float* w,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork, lapack_int lrwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_zhpgvd_work( int matrix_order, lapack_int itype, char jobz,
+                                char uplo, lapack_int n,
+                                lapack_complex_double* ap,
+                                lapack_complex_double* bp, double* w,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork, lapack_int lrwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_chpgvx_work( int matrix_order, lapack_int itype, char jobz,
+                                char range, char uplo, lapack_int n,
+                                lapack_complex_float* ap,
+                                lapack_complex_float* bp, float vl, float vu,
+                                lapack_int il, lapack_int iu, float abstol,
+                                lapack_int* m, float* w,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_complex_float* work, float* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+lapack_int LAPACKE_zhpgvx_work( int matrix_order, lapack_int itype, char jobz,
+                                char range, char uplo, lapack_int n,
+                                lapack_complex_double* ap,
+                                lapack_complex_double* bp, double vl, double vu,
+                                lapack_int il, lapack_int iu, double abstol,
+                                lapack_int* m, double* w,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_complex_double* work, double* rwork,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_chprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* ap,
+                                const lapack_complex_float* afp,
+                                const lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zhprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                const lapack_complex_double* afp,
+                                const lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_chpsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_float* ap,
+                               lapack_int* ipiv, lapack_complex_float* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_zhpsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_double* ap,
+                               lapack_int* ipiv, lapack_complex_double* b,
+                               lapack_int ldb );
+
+lapack_int LAPACKE_chpsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* ap,
+                                lapack_complex_float* afp, lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zhpsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                lapack_complex_double* afp, lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_chptrd_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* ap, float* d, float* e,
+                                lapack_complex_float* tau );
+lapack_int LAPACKE_zhptrd_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* ap, double* d, double* e,
+                                lapack_complex_double* tau );
+
+lapack_int LAPACKE_chptrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* ap, lapack_int* ipiv );
+lapack_int LAPACKE_zhptrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* ap, lapack_int* ipiv );
+
+lapack_int LAPACKE_chptri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* ap,
+                                const lapack_int* ipiv,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zhptri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* ap,
+                                const lapack_int* ipiv,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_chptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* ap,
+                                const lapack_int* ipiv, lapack_complex_float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_zhptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                const lapack_int* ipiv,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_shsein_work( int matrix_order, char job, char eigsrc,
+                                char initv, lapack_logical* select,
+                                lapack_int n, const float* h, lapack_int ldh,
+                                float* wr, const float* wi, float* vl,
+                                lapack_int ldvl, float* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m, float* work,
+                                lapack_int* ifaill, lapack_int* ifailr );
+lapack_int LAPACKE_dhsein_work( int matrix_order, char job, char eigsrc,
+                                char initv, lapack_logical* select,
+                                lapack_int n, const double* h, lapack_int ldh,
+                                double* wr, const double* wi, double* vl,
+                                lapack_int ldvl, double* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m, double* work,
+                                lapack_int* ifaill, lapack_int* ifailr );
+lapack_int LAPACKE_chsein_work( int matrix_order, char job, char eigsrc,
+                                char initv, const lapack_logical* select,
+                                lapack_int n, const lapack_complex_float* h,
+                                lapack_int ldh, lapack_complex_float* w,
+                                lapack_complex_float* vl, lapack_int ldvl,
+                                lapack_complex_float* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m,
+                                lapack_complex_float* work, float* rwork,
+                                lapack_int* ifaill, lapack_int* ifailr );
+lapack_int LAPACKE_zhsein_work( int matrix_order, char job, char eigsrc,
+                                char initv, const lapack_logical* select,
+                                lapack_int n, const lapack_complex_double* h,
+                                lapack_int ldh, lapack_complex_double* w,
+                                lapack_complex_double* vl, lapack_int ldvl,
+                                lapack_complex_double* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m,
+                                lapack_complex_double* work, double* rwork,
+                                lapack_int* ifaill, lapack_int* ifailr );
+
+lapack_int LAPACKE_shseqr_work( int matrix_order, char job, char compz,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                float* h, lapack_int ldh, float* wr, float* wi,
+                                float* z, lapack_int ldz, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dhseqr_work( int matrix_order, char job, char compz,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                double* h, lapack_int ldh, double* wr,
+                                double* wi, double* z, lapack_int ldz,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_chseqr_work( int matrix_order, char job, char compz,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                lapack_complex_float* h, lapack_int ldh,
+                                lapack_complex_float* w,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zhseqr_work( int matrix_order, char job, char compz,
+                                lapack_int n, lapack_int ilo, lapack_int ihi,
+                                lapack_complex_double* h, lapack_int ldh,
+                                lapack_complex_double* w,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_clacgv_work( lapack_int n, lapack_complex_float* x,
+                                lapack_int incx );
+lapack_int LAPACKE_zlacgv_work( lapack_int n, lapack_complex_double* x,
+                                lapack_int incx );
+
+lapack_int LAPACKE_slacpy_work( int matrix_order, char uplo, lapack_int m,
+                                lapack_int n, const float* a, lapack_int lda,
+                                float* b, lapack_int ldb );
+lapack_int LAPACKE_dlacpy_work( int matrix_order, char uplo, lapack_int m,
+                                lapack_int n, const double* a, lapack_int lda,
+                                double* b, lapack_int ldb );
+lapack_int LAPACKE_clacpy_work( int matrix_order, char uplo, lapack_int m,
+                                lapack_int n, const lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_zlacpy_work( int matrix_order, char uplo, lapack_int m,
+                                lapack_int n, const lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb );
+
+lapack_int LAPACKE_zlag2c_work( int matrix_order, lapack_int m, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_float* sa, lapack_int ldsa );
+
+lapack_int LAPACKE_slag2d_work( int matrix_order, lapack_int m, lapack_int n,
+                                const float* sa, lapack_int ldsa, double* a,
+                                lapack_int lda );
+
+lapack_int LAPACKE_dlag2s_work( int matrix_order, lapack_int m, lapack_int n,
+                                const double* a, lapack_int lda, float* sa,
+                                lapack_int ldsa );
+
+lapack_int LAPACKE_clag2z_work( int matrix_order, lapack_int m, lapack_int n,
+                                const lapack_complex_float* sa, lapack_int ldsa,
+                                lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_slagge_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku, const float* d,
+                                float* a, lapack_int lda, lapack_int* iseed,
+                                float* work );
+lapack_int LAPACKE_dlagge_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku, const double* d,
+                                double* a, lapack_int lda, lapack_int* iseed,
+                                double* work );
+lapack_int LAPACKE_clagge_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku, const float* d,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* iseed, lapack_complex_float* work );
+lapack_int LAPACKE_zlagge_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int kl, lapack_int ku, const double* d,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* iseed,
+                                lapack_complex_double* work );
+                                
+lapack_int LAPACKE_claghe_work( int matrix_order, lapack_int n, lapack_int k,
+                                const float* d, lapack_complex_float* a,
+                                lapack_int lda, lapack_int* iseed,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zlaghe_work( int matrix_order, lapack_int n, lapack_int k,
+                                const double* d, lapack_complex_double* a,
+                                lapack_int lda, lapack_int* iseed,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_slagsy_work( int matrix_order, lapack_int n, lapack_int k,
+                                const float* d, float* a, lapack_int lda,
+                                lapack_int* iseed, float* work );
+lapack_int LAPACKE_dlagsy_work( int matrix_order, lapack_int n, lapack_int k,
+                                const double* d, double* a, lapack_int lda,
+                                lapack_int* iseed, double* work );
+lapack_int LAPACKE_clagsy_work( int matrix_order, lapack_int n, lapack_int k,
+                                const float* d, lapack_complex_float* a,
+                                lapack_int lda, lapack_int* iseed,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zlagsy_work( int matrix_order, lapack_int n, lapack_int k,
+                                const double* d, lapack_complex_double* a,
+                                lapack_int lda, lapack_int* iseed,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_slapmr_work( int matrix_order, lapack_logical forwrd,
+                                lapack_int m, lapack_int n, float* x,
+                                lapack_int ldx, lapack_int* k );
+lapack_int LAPACKE_dlapmr_work( int matrix_order, lapack_logical forwrd,
+                                lapack_int m, lapack_int n, double* x,
+                                lapack_int ldx, lapack_int* k );
+lapack_int LAPACKE_clapmr_work( int matrix_order, lapack_logical forwrd,
+                                lapack_int m, lapack_int n,
+                                lapack_complex_float* x, lapack_int ldx,
+                                lapack_int* k );
+lapack_int LAPACKE_zlapmr_work( int matrix_order, lapack_logical forwrd,
+                                lapack_int m, lapack_int n,
+                                lapack_complex_double* x, lapack_int ldx,
+                                lapack_int* k );
+
+lapack_int LAPACKE_slartgp_work( float f, float g, float* cs, float* sn,
+                                 float* r );
+lapack_int LAPACKE_dlartgp_work( double f, double g, double* cs, double* sn,
+                                 double* r );
+
+lapack_int LAPACKE_slartgs_work( float x, float y, float sigma, float* cs,
+                                 float* sn );
+lapack_int LAPACKE_dlartgs_work( double x, double y, double sigma, double* cs,
+                                 double* sn );
+                                
+float LAPACKE_slapy2_work( float x, float y );
+double LAPACKE_dlapy2_work( double x, double y );
+
+float LAPACKE_slapy3_work( float x, float y, float z );
+double LAPACKE_dlapy3_work( double x, double y, double z );
+
+float LAPACKE_slamch_work( char cmach );
+double LAPACKE_dlamch_work( char cmach );
+
+float LAPACKE_slange_work( int matrix_order, char norm, lapack_int m,
+                                lapack_int n, const float* a, lapack_int lda,
+                                float* work );
+double LAPACKE_dlange_work( int matrix_order, char norm, lapack_int m,
+                                lapack_int n, const double* a, lapack_int lda,
+                                double* work );
+float LAPACKE_clange_work( int matrix_order, char norm, lapack_int m,
+                                lapack_int n, const lapack_complex_float* a,
+                                lapack_int lda, float* work );
+double LAPACKE_zlange_work( int matrix_order, char norm, lapack_int m,
+                                lapack_int n, const lapack_complex_double* a,
+                                lapack_int lda, double* work );
+
+float LAPACKE_clanhe_work( int matrix_order, char norm, char uplo,
+                                lapack_int n, const lapack_complex_float* a,
+                                lapack_int lda, float* work );
+double LAPACKE_zlanhe_work( int matrix_order, char norm, char uplo,
+                                lapack_int n, const lapack_complex_double* a,
+                                lapack_int lda, double* work );
+
+float LAPACKE_slansy_work( int matrix_order, char norm, char uplo,
+                                lapack_int n, const float* a, lapack_int lda,
+                                float* work );
+double LAPACKE_dlansy_work( int matrix_order, char norm, char uplo,
+                                lapack_int n, const double* a, lapack_int lda,
+                                double* work );
+float LAPACKE_clansy_work( int matrix_order, char norm, char uplo,
+                                lapack_int n, const lapack_complex_float* a,
+                                lapack_int lda, float* work );
+double LAPACKE_zlansy_work( int matrix_order, char norm, char uplo,
+                                lapack_int n, const lapack_complex_double* a,
+                                lapack_int lda, double* work );
+
+float LAPACKE_slantr_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int m, lapack_int n, const float* a,
+                                lapack_int lda, float* work );
+double LAPACKE_dlantr_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int m, lapack_int n,
+                                const double* a, lapack_int lda, double* work );
+float LAPACKE_clantr_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int m, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                float* work );
+double LAPACKE_zlantr_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int m, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                double* work );
+
+lapack_int LAPACKE_slarfb_work( int matrix_order, char side, char trans,
+                                char direct, char storev, lapack_int m,
+                                lapack_int n, lapack_int k, const float* v,
+                                lapack_int ldv, const float* t, lapack_int ldt,
+                                float* c, lapack_int ldc, float* work,
+                                lapack_int ldwork );
+lapack_int LAPACKE_dlarfb_work( int matrix_order, char side, char trans,
+                                char direct, char storev, lapack_int m,
+                                lapack_int n, lapack_int k, const double* v,
+                                lapack_int ldv, const double* t, lapack_int ldt,
+                                double* c, lapack_int ldc, double* work,
+                                lapack_int ldwork );
+lapack_int LAPACKE_clarfb_work( int matrix_order, char side, char trans,
+                                char direct, char storev, lapack_int m,
+                                lapack_int n, lapack_int k,
+                                const lapack_complex_float* v, lapack_int ldv,
+                                const lapack_complex_float* t, lapack_int ldt,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int ldwork );
+lapack_int LAPACKE_zlarfb_work( int matrix_order, char side, char trans,
+                                char direct, char storev, lapack_int m,
+                                lapack_int n, lapack_int k,
+                                const lapack_complex_double* v, lapack_int ldv,
+                                const lapack_complex_double* t, lapack_int ldt,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work,
+                                lapack_int ldwork );
+
+lapack_int LAPACKE_slarfg_work( lapack_int n, float* alpha, float* x,
+                                lapack_int incx, float* tau );
+lapack_int LAPACKE_dlarfg_work( lapack_int n, double* alpha, double* x,
+                                lapack_int incx, double* tau );
+lapack_int LAPACKE_clarfg_work( lapack_int n, lapack_complex_float* alpha,
+                                lapack_complex_float* x, lapack_int incx,
+                                lapack_complex_float* tau );
+lapack_int LAPACKE_zlarfg_work( lapack_int n, lapack_complex_double* alpha,
+                                lapack_complex_double* x, lapack_int incx,
+                                lapack_complex_double* tau );
+
+lapack_int LAPACKE_slarft_work( int matrix_order, char direct, char storev,
+                                lapack_int n, lapack_int k, const float* v,
+                                lapack_int ldv, const float* tau, float* t,
+                                lapack_int ldt );
+lapack_int LAPACKE_dlarft_work( int matrix_order, char direct, char storev,
+                                lapack_int n, lapack_int k, const double* v,
+                                lapack_int ldv, const double* tau, double* t,
+                                lapack_int ldt );
+lapack_int LAPACKE_clarft_work( int matrix_order, char direct, char storev,
+                                lapack_int n, lapack_int k,
+                                const lapack_complex_float* v, lapack_int ldv,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* t, lapack_int ldt );
+lapack_int LAPACKE_zlarft_work( int matrix_order, char direct, char storev,
+                                lapack_int n, lapack_int k,
+                                const lapack_complex_double* v, lapack_int ldv,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_slarfx_work( int matrix_order, char side, lapack_int m,
+                                lapack_int n, const float* v, float tau,
+                                float* c, lapack_int ldc, float* work );
+lapack_int LAPACKE_dlarfx_work( int matrix_order, char side, lapack_int m,
+                                lapack_int n, const double* v, double tau,
+                                double* c, lapack_int ldc, double* work );
+lapack_int LAPACKE_clarfx_work( int matrix_order, char side, lapack_int m,
+                                lapack_int n, const lapack_complex_float* v,
+                                lapack_complex_float tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zlarfx_work( int matrix_order, char side, lapack_int m,
+                                lapack_int n, const lapack_complex_double* v,
+                                lapack_complex_double tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_slarnv_work( lapack_int idist, lapack_int* iseed,
+                                lapack_int n, float* x );
+lapack_int LAPACKE_dlarnv_work( lapack_int idist, lapack_int* iseed,
+                                lapack_int n, double* x );
+lapack_int LAPACKE_clarnv_work( lapack_int idist, lapack_int* iseed,
+                                lapack_int n, lapack_complex_float* x );
+lapack_int LAPACKE_zlarnv_work( lapack_int idist, lapack_int* iseed,
+                                lapack_int n, lapack_complex_double* x );
+
+lapack_int LAPACKE_slaset_work( int matrix_order, char uplo, lapack_int m,
+                                lapack_int n, float alpha, float beta, float* a,
+                                lapack_int lda );
+lapack_int LAPACKE_dlaset_work( int matrix_order, char uplo, lapack_int m,
+                                lapack_int n, double alpha, double beta,
+                                double* a, lapack_int lda );
+lapack_int LAPACKE_claset_work( int matrix_order, char uplo, lapack_int m,
+                                lapack_int n, lapack_complex_float alpha,
+                                lapack_complex_float beta,
+                                lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zlaset_work( int matrix_order, char uplo, lapack_int m,
+                                lapack_int n, lapack_complex_double alpha,
+                                lapack_complex_double beta,
+                                lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_slasrt_work( char id, lapack_int n, float* d );
+lapack_int LAPACKE_dlasrt_work( char id, lapack_int n, double* d );
+
+lapack_int LAPACKE_slaswp_work( int matrix_order, lapack_int n, float* a,
+                                lapack_int lda, lapack_int k1, lapack_int k2,
+                                const lapack_int* ipiv, lapack_int incx );
+lapack_int LAPACKE_dlaswp_work( int matrix_order, lapack_int n, double* a,
+                                lapack_int lda, lapack_int k1, lapack_int k2,
+                                const lapack_int* ipiv, lapack_int incx );
+lapack_int LAPACKE_claswp_work( int matrix_order, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int k1, lapack_int k2,
+                                const lapack_int* ipiv, lapack_int incx );
+lapack_int LAPACKE_zlaswp_work( int matrix_order, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int k1, lapack_int k2,
+                                const lapack_int* ipiv, lapack_int incx );
+
+lapack_int LAPACKE_slatms_work( int matrix_order, lapack_int m, lapack_int n,
+                                char dist, lapack_int* iseed, char sym,
+                                float* d, lapack_int mode, float cond,
+                                float dmax, lapack_int kl, lapack_int ku,
+                                char pack, float* a, lapack_int lda,
+                                float* work );
+lapack_int LAPACKE_dlatms_work( int matrix_order, lapack_int m, lapack_int n,
+                                char dist, lapack_int* iseed, char sym,
+                                double* d, lapack_int mode, double cond,
+                                double dmax, lapack_int kl, lapack_int ku,
+                                char pack, double* a, lapack_int lda,
+                                double* work );
+lapack_int LAPACKE_clatms_work( int matrix_order, lapack_int m, lapack_int n,
+                                char dist, lapack_int* iseed, char sym,
+                                float* d, lapack_int mode, float cond,
+                                float dmax, lapack_int kl, lapack_int ku,
+                                char pack, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* work );
+lapack_int LAPACKE_zlatms_work( int matrix_order, lapack_int m, lapack_int n,
+                                char dist, lapack_int* iseed, char sym,
+                                double* d, lapack_int mode, double cond,
+                                double dmax, lapack_int kl, lapack_int ku,
+                                char pack, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* work );
+
+lapack_int LAPACKE_slauum_work( int matrix_order, char uplo, lapack_int n,
+                                float* a, lapack_int lda );
+lapack_int LAPACKE_dlauum_work( int matrix_order, char uplo, lapack_int n,
+                                double* a, lapack_int lda );
+lapack_int LAPACKE_clauum_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zlauum_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_sopgtr_work( int matrix_order, char uplo, lapack_int n,
+                                const float* ap, const float* tau, float* q,
+                                lapack_int ldq, float* work );
+lapack_int LAPACKE_dopgtr_work( int matrix_order, char uplo, lapack_int n,
+                                const double* ap, const double* tau, double* q,
+                                lapack_int ldq, double* work );
+
+lapack_int LAPACKE_sopmtr_work( int matrix_order, char side, char uplo,
+                                char trans, lapack_int m, lapack_int n,
+                                const float* ap, const float* tau, float* c,
+                                lapack_int ldc, float* work );
+lapack_int LAPACKE_dopmtr_work( int matrix_order, char side, char uplo,
+                                char trans, lapack_int m, lapack_int n,
+                                const double* ap, const double* tau, double* c,
+                                lapack_int ldc, double* work );
+
+lapack_int LAPACKE_sorgbr_work( int matrix_order, char vect, lapack_int m,
+                                lapack_int n, lapack_int k, float* a,
+                                lapack_int lda, const float* tau, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dorgbr_work( int matrix_order, char vect, lapack_int m,
+                                lapack_int n, lapack_int k, double* a,
+                                lapack_int lda, const double* tau, double* work,
+                                lapack_int lwork );
+
+lapack_int LAPACKE_sorghr_work( int matrix_order, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, float* a, lapack_int lda,
+                                const float* tau, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dorghr_work( int matrix_order, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, double* a, lapack_int lda,
+                                const double* tau, double* work,
+                                lapack_int lwork );
+
+lapack_int LAPACKE_sorglq_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, float* a, lapack_int lda,
+                                const float* tau, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dorglq_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, double* a, lapack_int lda,
+                                const double* tau, double* work,
+                                lapack_int lwork );
+
+lapack_int LAPACKE_sorgql_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, float* a, lapack_int lda,
+                                const float* tau, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dorgql_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, double* a, lapack_int lda,
+                                const double* tau, double* work,
+                                lapack_int lwork );
+
+lapack_int LAPACKE_sorgqr_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, float* a, lapack_int lda,
+                                const float* tau, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dorgqr_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, double* a, lapack_int lda,
+                                const double* tau, double* work,
+                                lapack_int lwork );
+
+lapack_int LAPACKE_sorgrq_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, float* a, lapack_int lda,
+                                const float* tau, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dorgrq_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, double* a, lapack_int lda,
+                                const double* tau, double* work,
+                                lapack_int lwork );
+
+lapack_int LAPACKE_sorgtr_work( int matrix_order, char uplo, lapack_int n,
+                                float* a, lapack_int lda, const float* tau,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dorgtr_work( int matrix_order, char uplo, lapack_int n,
+                                double* a, lapack_int lda, const double* tau,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sormbr_work( int matrix_order, char vect, char side,
+                                char trans, lapack_int m, lapack_int n,
+                                lapack_int k, const float* a, lapack_int lda,
+                                const float* tau, float* c, lapack_int ldc,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dormbr_work( int matrix_order, char vect, char side,
+                                char trans, lapack_int m, lapack_int n,
+                                lapack_int k, const double* a, lapack_int lda,
+                                const double* tau, double* c, lapack_int ldc,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sormhr_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, const float* a, lapack_int lda,
+                                const float* tau, float* c, lapack_int ldc,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dormhr_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, const double* a, lapack_int lda,
+                                const double* tau, double* c, lapack_int ldc,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sormlq_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const float* a, lapack_int lda,
+                                const float* tau, float* c, lapack_int ldc,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dormlq_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const double* a, lapack_int lda,
+                                const double* tau, double* c, lapack_int ldc,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sormql_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const float* a, lapack_int lda,
+                                const float* tau, float* c, lapack_int ldc,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dormql_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const double* a, lapack_int lda,
+                                const double* tau, double* c, lapack_int ldc,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sormqr_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const float* a, lapack_int lda,
+                                const float* tau, float* c, lapack_int ldc,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dormqr_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const double* a, lapack_int lda,
+                                const double* tau, double* c, lapack_int ldc,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sormrq_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const float* a, lapack_int lda,
+                                const float* tau, float* c, lapack_int ldc,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dormrq_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const double* a, lapack_int lda,
+                                const double* tau, double* c, lapack_int ldc,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sormrz_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                lapack_int l, const float* a, lapack_int lda,
+                                const float* tau, float* c, lapack_int ldc,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dormrz_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                lapack_int l, const double* a, lapack_int lda,
+                                const double* tau, double* c, lapack_int ldc,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_sormtr_work( int matrix_order, char side, char uplo,
+                                char trans, lapack_int m, lapack_int n,
+                                const float* a, lapack_int lda,
+                                const float* tau, float* c, lapack_int ldc,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dormtr_work( int matrix_order, char side, char uplo,
+                                char trans, lapack_int m, lapack_int n,
+                                const double* a, lapack_int lda,
+                                const double* tau, double* c, lapack_int ldc,
+                                double* work, lapack_int lwork );
+
+lapack_int LAPACKE_spbcon_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, const float* ab, lapack_int ldab,
+                                float anorm, float* rcond, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dpbcon_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, const double* ab,
+                                lapack_int ldab, double anorm, double* rcond,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cpbcon_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, const lapack_complex_float* ab,
+                                lapack_int ldab, float anorm, float* rcond,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zpbcon_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, const lapack_complex_double* ab,
+                                lapack_int ldab, double anorm, double* rcond,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_spbequ_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, const float* ab, lapack_int ldab,
+                                float* s, float* scond, float* amax );
+lapack_int LAPACKE_dpbequ_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, const double* ab,
+                                lapack_int ldab, double* s, double* scond,
+                                double* amax );
+lapack_int LAPACKE_cpbequ_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, const lapack_complex_float* ab,
+                                lapack_int ldab, float* s, float* scond,
+                                float* amax );
+lapack_int LAPACKE_zpbequ_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, const lapack_complex_double* ab,
+                                lapack_int ldab, double* s, double* scond,
+                                double* amax );
+
+lapack_int LAPACKE_spbrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_int nrhs, const float* ab,
+                                lapack_int ldab, const float* afb,
+                                lapack_int ldafb, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* ferr, float* berr, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dpbrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_int nrhs,
+                                const double* ab, lapack_int ldab,
+                                const double* afb, lapack_int ldafb,
+                                const double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cpbrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_int nrhs,
+                                const lapack_complex_float* ab, lapack_int ldab,
+                                const lapack_complex_float* afb,
+                                lapack_int ldafb, const lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zpbrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_int nrhs,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab,
+                                const lapack_complex_double* afb,
+                                lapack_int ldafb,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_spbstf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kb, float* bb, lapack_int ldbb );
+lapack_int LAPACKE_dpbstf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kb, double* bb, lapack_int ldbb );
+lapack_int LAPACKE_cpbstf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kb, lapack_complex_float* bb,
+                                lapack_int ldbb );
+lapack_int LAPACKE_zpbstf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kb, lapack_complex_double* bb,
+                                lapack_int ldbb );
+
+lapack_int LAPACKE_spbsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int kd, lapack_int nrhs, float* ab,
+                               lapack_int ldab, float* b, lapack_int ldb );
+lapack_int LAPACKE_dpbsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int kd, lapack_int nrhs, double* ab,
+                               lapack_int ldab, double* b, lapack_int ldb );
+lapack_int LAPACKE_cpbsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int kd, lapack_int nrhs,
+                               lapack_complex_float* ab, lapack_int ldab,
+                               lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpbsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int kd, lapack_int nrhs,
+                               lapack_complex_double* ab, lapack_int ldab,
+                               lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_spbsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int kd, lapack_int nrhs,
+                                float* ab, lapack_int ldab, float* afb,
+                                lapack_int ldafb, char* equed, float* s,
+                                float* b, lapack_int ldb, float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, float* work, lapack_int* iwork );
+lapack_int LAPACKE_dpbsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int kd, lapack_int nrhs,
+                                double* ab, lapack_int ldab, double* afb,
+                                lapack_int ldafb, char* equed, double* s,
+                                double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* rcond, double* ferr,
+                                double* berr, double* work, lapack_int* iwork );
+lapack_int LAPACKE_cpbsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int kd, lapack_int nrhs,
+                                lapack_complex_float* ab, lapack_int ldab,
+                                lapack_complex_float* afb, lapack_int ldafb,
+                                char* equed, float* s, lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_zpbsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int kd, lapack_int nrhs,
+                                lapack_complex_double* ab, lapack_int ldab,
+                                lapack_complex_double* afb, lapack_int ldafb,
+                                char* equed, double* s,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_spbtrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, float* ab, lapack_int ldab );
+lapack_int LAPACKE_dpbtrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, double* ab, lapack_int ldab );
+lapack_int LAPACKE_cpbtrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_complex_float* ab,
+                                lapack_int ldab );
+lapack_int LAPACKE_zpbtrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_complex_double* ab,
+                                lapack_int ldab );
+
+lapack_int LAPACKE_spbtrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_int nrhs, const float* ab,
+                                lapack_int ldab, float* b, lapack_int ldb );
+lapack_int LAPACKE_dpbtrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_int nrhs,
+                                const double* ab, lapack_int ldab, double* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_cpbtrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_int nrhs,
+                                const lapack_complex_float* ab, lapack_int ldab,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpbtrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int kd, lapack_int nrhs,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab, lapack_complex_double* b,
+                                lapack_int ldb );
+
+lapack_int LAPACKE_spftrf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, float* a );
+lapack_int LAPACKE_dpftrf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, double* a );
+lapack_int LAPACKE_cpftrf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, lapack_complex_float* a );
+lapack_int LAPACKE_zpftrf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, lapack_complex_double* a );
+
+lapack_int LAPACKE_spftri_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, float* a );
+lapack_int LAPACKE_dpftri_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, double* a );
+lapack_int LAPACKE_cpftri_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, lapack_complex_float* a );
+lapack_int LAPACKE_zpftri_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, lapack_complex_double* a );
+
+lapack_int LAPACKE_spftrs_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, lapack_int nrhs, const float* a,
+                                float* b, lapack_int ldb );
+lapack_int LAPACKE_dpftrs_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, lapack_int nrhs, const double* a,
+                                double* b, lapack_int ldb );
+lapack_int LAPACKE_cpftrs_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* a,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpftrs_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* a,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_spocon_work( int matrix_order, char uplo, lapack_int n,
+                                const float* a, lapack_int lda, float anorm,
+                                float* rcond, float* work, lapack_int* iwork );
+lapack_int LAPACKE_dpocon_work( int matrix_order, char uplo, lapack_int n,
+                                const double* a, lapack_int lda, double anorm,
+                                double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cpocon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                float anorm, float* rcond,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zpocon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                double anorm, double* rcond,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_spoequ_work( int matrix_order, lapack_int n, const float* a,
+                                lapack_int lda, float* s, float* scond,
+                                float* amax );
+lapack_int LAPACKE_dpoequ_work( int matrix_order, lapack_int n, const double* a,
+                                lapack_int lda, double* s, double* scond,
+                                double* amax );
+lapack_int LAPACKE_cpoequ_work( int matrix_order, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                float* s, float* scond, float* amax );
+lapack_int LAPACKE_zpoequ_work( int matrix_order, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                double* s, double* scond, double* amax );
+
+lapack_int LAPACKE_spoequb_work( int matrix_order, lapack_int n, const float* a,
+                                 lapack_int lda, float* s, float* scond,
+                                 float* amax );
+lapack_int LAPACKE_dpoequb_work( int matrix_order, lapack_int n,
+                                 const double* a, lapack_int lda, double* s,
+                                 double* scond, double* amax );
+lapack_int LAPACKE_cpoequb_work( int matrix_order, lapack_int n,
+                                 const lapack_complex_float* a, lapack_int lda,
+                                 float* s, float* scond, float* amax );
+lapack_int LAPACKE_zpoequb_work( int matrix_order, lapack_int n,
+                                 const lapack_complex_double* a, lapack_int lda,
+                                 double* s, double* scond, double* amax );
+
+lapack_int LAPACKE_sporfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* a, lapack_int lda,
+                                const float* af, lapack_int ldaf,
+                                const float* b, lapack_int ldb, float* x,
+                                lapack_int ldx, float* ferr, float* berr,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dporfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* a,
+                                lapack_int lda, const double* af,
+                                lapack_int ldaf, const double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* ferr, double* berr, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cporfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* af,
+                                lapack_int ldaf, const lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zporfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_double* a,
+                                lapack_int lda, const lapack_complex_double* af,
+                                lapack_int ldaf, const lapack_complex_double* b,
+                                lapack_int ldb, lapack_complex_double* x,
+                                lapack_int ldx, double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sporfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs, const float* a,
+                                 lapack_int lda, const float* af,
+                                 lapack_int ldaf, const float* s,
+                                 const float* b, lapack_int ldb, float* x,
+                                 lapack_int ldx, float* rcond, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, float* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_dporfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs, const double* a,
+                                 lapack_int lda, const double* af,
+                                 lapack_int ldaf, const double* s,
+                                 const double* b, lapack_int ldb, double* x,
+                                 lapack_int ldx, double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, double* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_cporfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs,
+                                 const lapack_complex_float* a, lapack_int lda,
+                                 const lapack_complex_float* af,
+                                 lapack_int ldaf, const float* s,
+                                 const lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* x, lapack_int ldx,
+                                 float* rcond, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, lapack_complex_float* work,
+                                 float* rwork );
+lapack_int LAPACKE_zporfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs,
+                                 const lapack_complex_double* a, lapack_int lda,
+                                 const lapack_complex_double* af,
+                                 lapack_int ldaf, const double* s,
+                                 const lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_sposv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, float* a, lapack_int lda,
+                               float* b, lapack_int ldb );
+lapack_int LAPACKE_dposv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, double* a, lapack_int lda,
+                               double* b, lapack_int ldb );
+lapack_int LAPACKE_cposv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_float* a,
+                               lapack_int lda, lapack_complex_float* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_zposv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_double* a,
+                               lapack_int lda, lapack_complex_double* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_dsposv_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, double* a, lapack_int lda,
+                                double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* work, float* swork,
+                                lapack_int* iter );
+lapack_int LAPACKE_zcposv_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb, lapack_complex_double* x,
+                                lapack_int ldx, lapack_complex_double* work,
+                                lapack_complex_float* swork, double* rwork,
+                                lapack_int* iter );
+
+lapack_int LAPACKE_sposvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs, float* a,
+                                lapack_int lda, float* af, lapack_int ldaf,
+                                char* equed, float* s, float* b, lapack_int ldb,
+                                float* x, lapack_int ldx, float* rcond,
+                                float* ferr, float* berr, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dposvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs, double* a,
+                                lapack_int lda, double* af, lapack_int ldaf,
+                                char* equed, double* s, double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cposvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* af, lapack_int ldaf,
+                                char* equed, float* s, lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_zposvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* af, lapack_int ldaf,
+                                char* equed, double* s,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sposvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs, float* a,
+                                 lapack_int lda, float* af, lapack_int ldaf,
+                                 char* equed, float* s, float* b,
+                                 lapack_int ldb, float* x, lapack_int ldx,
+                                 float* rcond, float* rpvgrw, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, float* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_dposvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs, double* a,
+                                 lapack_int lda, double* af, lapack_int ldaf,
+                                 char* equed, double* s, double* b,
+                                 lapack_int ldb, double* x, lapack_int ldx,
+                                 double* rcond, double* rpvgrw, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, double* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_cposvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* af, lapack_int ldaf,
+                                 char* equed, float* s, lapack_complex_float* b,
+                                 lapack_int ldb, lapack_complex_float* x,
+                                 lapack_int ldx, float* rcond, float* rpvgrw,
+                                 float* berr, lapack_int n_err_bnds,
+                                 float* err_bnds_norm, float* err_bnds_comp,
+                                 lapack_int nparams, float* params,
+                                 lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zposvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* af, lapack_int ldaf,
+                                 char* equed, double* s,
+                                 lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* rpvgrw, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_spotrf_work( int matrix_order, char uplo, lapack_int n,
+                                float* a, lapack_int lda );
+lapack_int LAPACKE_dpotrf_work( int matrix_order, char uplo, lapack_int n,
+                                double* a, lapack_int lda );
+lapack_int LAPACKE_cpotrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zpotrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_spotri_work( int matrix_order, char uplo, lapack_int n,
+                                float* a, lapack_int lda );
+lapack_int LAPACKE_dpotri_work( int matrix_order, char uplo, lapack_int n,
+                                double* a, lapack_int lda );
+lapack_int LAPACKE_cpotri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zpotri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_spotrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* a, lapack_int lda,
+                                float* b, lapack_int ldb );
+lapack_int LAPACKE_dpotrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* a,
+                                lapack_int lda, double* b, lapack_int ldb );
+lapack_int LAPACKE_cpotrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_zpotrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* b,
+                                lapack_int ldb );
+
+lapack_int LAPACKE_sppcon_work( int matrix_order, char uplo, lapack_int n,
+                                const float* ap, float anorm, float* rcond,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dppcon_work( int matrix_order, char uplo, lapack_int n,
+                                const double* ap, double anorm, double* rcond,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cppcon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* ap, float anorm,
+                                float* rcond, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_zppcon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* ap, double anorm,
+                                double* rcond, lapack_complex_double* work,
+                                double* rwork );
+
+lapack_int LAPACKE_sppequ_work( int matrix_order, char uplo, lapack_int n,
+                                const float* ap, float* s, float* scond,
+                                float* amax );
+lapack_int LAPACKE_dppequ_work( int matrix_order, char uplo, lapack_int n,
+                                const double* ap, double* s, double* scond,
+                                double* amax );
+lapack_int LAPACKE_cppequ_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* ap, float* s,
+                                float* scond, float* amax );
+lapack_int LAPACKE_zppequ_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* ap, double* s,
+                                double* scond, double* amax );
+
+lapack_int LAPACKE_spprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* ap,
+                                const float* afp, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* ferr, float* berr, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dpprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* ap,
+                                const double* afp, const double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* ferr, double* berr, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cpprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* ap,
+                                const lapack_complex_float* afp,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zpprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                const lapack_complex_double* afp,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sppsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, float* ap, float* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_dppsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, double* ap, double* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_cppsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_float* ap,
+                               lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zppsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_double* ap,
+                               lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sppsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs, float* ap,
+                                float* afp, char* equed, float* s, float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dppsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs, double* ap,
+                                double* afp, char* equed, double* s, double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cppsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                lapack_complex_float* ap,
+                                lapack_complex_float* afp, char* equed,
+                                float* s, lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_zppsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                lapack_complex_double* ap,
+                                lapack_complex_double* afp, char* equed,
+                                double* s, lapack_complex_double* b,
+                                lapack_int ldb, lapack_complex_double* x,
+                                lapack_int ldx, double* rcond, double* ferr,
+                                double* berr, lapack_complex_double* work,
+                                double* rwork );
+
+lapack_int LAPACKE_spptrf_work( int matrix_order, char uplo, lapack_int n,
+                                float* ap );
+lapack_int LAPACKE_dpptrf_work( int matrix_order, char uplo, lapack_int n,
+                                double* ap );
+lapack_int LAPACKE_cpptrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* ap );
+lapack_int LAPACKE_zpptrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* ap );
+
+lapack_int LAPACKE_spptri_work( int matrix_order, char uplo, lapack_int n,
+                                float* ap );
+lapack_int LAPACKE_dpptri_work( int matrix_order, char uplo, lapack_int n,
+                                double* ap );
+lapack_int LAPACKE_cpptri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* ap );
+lapack_int LAPACKE_zpptri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* ap );
+
+lapack_int LAPACKE_spptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* ap, float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_dpptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* ap, double* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_cpptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* ap,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_spstrf_work( int matrix_order, char uplo, lapack_int n,
+                                float* a, lapack_int lda, lapack_int* piv,
+                                lapack_int* rank, float tol, float* work );
+lapack_int LAPACKE_dpstrf_work( int matrix_order, char uplo, lapack_int n,
+                                double* a, lapack_int lda, lapack_int* piv,
+                                lapack_int* rank, double tol, double* work );
+lapack_int LAPACKE_cpstrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* piv, lapack_int* rank, float tol,
+                                float* work );
+lapack_int LAPACKE_zpstrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* piv, lapack_int* rank, double tol,
+                                double* work );
+
+lapack_int LAPACKE_sptcon_work( lapack_int n, const float* d, const float* e,
+                                float anorm, float* rcond, float* work );
+lapack_int LAPACKE_dptcon_work( lapack_int n, const double* d, const double* e,
+                                double anorm, double* rcond, double* work );
+lapack_int LAPACKE_cptcon_work( lapack_int n, const float* d,
+                                const lapack_complex_float* e, float anorm,
+                                float* rcond, float* work );
+lapack_int LAPACKE_zptcon_work( lapack_int n, const double* d,
+                                const lapack_complex_double* e, double anorm,
+                                double* rcond, double* work );
+
+lapack_int LAPACKE_spteqr_work( int matrix_order, char compz, lapack_int n,
+                                float* d, float* e, float* z, lapack_int ldz,
+                                float* work );
+lapack_int LAPACKE_dpteqr_work( int matrix_order, char compz, lapack_int n,
+                                double* d, double* e, double* z, lapack_int ldz,
+                                double* work );
+lapack_int LAPACKE_cpteqr_work( int matrix_order, char compz, lapack_int n,
+                                float* d, float* e, lapack_complex_float* z,
+                                lapack_int ldz, float* work );
+lapack_int LAPACKE_zpteqr_work( int matrix_order, char compz, lapack_int n,
+                                double* d, double* e, lapack_complex_double* z,
+                                lapack_int ldz, double* work );
+
+lapack_int LAPACKE_sptrfs_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                                const float* d, const float* e, const float* df,
+                                const float* ef, const float* b, lapack_int ldb,
+                                float* x, lapack_int ldx, float* ferr,
+                                float* berr, float* work );
+lapack_int LAPACKE_dptrfs_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                                const double* d, const double* e,
+                                const double* df, const double* ef,
+                                const double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* ferr, double* berr,
+                                double* work );
+lapack_int LAPACKE_cptrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* d,
+                                const lapack_complex_float* e, const float* df,
+                                const lapack_complex_float* ef,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zptrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* d,
+                                const lapack_complex_double* e,
+                                const double* df,
+                                const lapack_complex_double* ef,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sptsv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               float* d, float* e, float* b, lapack_int ldb );
+lapack_int LAPACKE_dptsv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               double* d, double* e, double* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_cptsv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               float* d, lapack_complex_float* e,
+                               lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zptsv_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                               double* d, lapack_complex_double* e,
+                               lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sptsvx_work( int matrix_order, char fact, lapack_int n,
+                                lapack_int nrhs, const float* d, const float* e,
+                                float* df, float* ef, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                float* work );
+lapack_int LAPACKE_dptsvx_work( int matrix_order, char fact, lapack_int n,
+                                lapack_int nrhs, const double* d,
+                                const double* e, double* df, double* ef,
+                                const double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* rcond, double* ferr,
+                                double* berr, double* work );
+lapack_int LAPACKE_cptsvx_work( int matrix_order, char fact, lapack_int n,
+                                lapack_int nrhs, const float* d,
+                                const lapack_complex_float* e, float* df,
+                                lapack_complex_float* ef,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zptsvx_work( int matrix_order, char fact, lapack_int n,
+                                lapack_int nrhs, const double* d,
+                                const lapack_complex_double* e, double* df,
+                                lapack_complex_double* ef,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_spttrf_work( lapack_int n, float* d, float* e );
+lapack_int LAPACKE_dpttrf_work( lapack_int n, double* d, double* e );
+lapack_int LAPACKE_cpttrf_work( lapack_int n, float* d,
+                                lapack_complex_float* e );
+lapack_int LAPACKE_zpttrf_work( lapack_int n, double* d,
+                                lapack_complex_double* e );
+
+lapack_int LAPACKE_spttrs_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                                const float* d, const float* e, float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_dpttrs_work( int matrix_order, lapack_int n, lapack_int nrhs,
+                                const double* d, const double* e, double* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_cpttrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* d,
+                                const lapack_complex_float* e,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zpttrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* d,
+                                const lapack_complex_double* e,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_ssbev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_int kd, float* ab,
+                               lapack_int ldab, float* w, float* z,
+                               lapack_int ldz, float* work );
+lapack_int LAPACKE_dsbev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_int kd, double* ab,
+                               lapack_int ldab, double* w, double* z,
+                               lapack_int ldz, double* work );
+
+lapack_int LAPACKE_ssbevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_int kd, float* ab,
+                                lapack_int ldab, float* w, float* z,
+                                lapack_int ldz, float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dsbevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_int kd, double* ab,
+                                lapack_int ldab, double* w, double* z,
+                                lapack_int ldz, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_ssbevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, lapack_int kd,
+                                float* ab, lapack_int ldab, float* q,
+                                lapack_int ldq, float vl, float vu,
+                                lapack_int il, lapack_int iu, float abstol,
+                                lapack_int* m, float* w, float* z,
+                                lapack_int ldz, float* work, lapack_int* iwork,
+                                lapack_int* ifail );
+lapack_int LAPACKE_dsbevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, lapack_int kd,
+                                double* ab, lapack_int ldab, double* q,
+                                lapack_int ldq, double vl, double vu,
+                                lapack_int il, lapack_int iu, double abstol,
+                                lapack_int* m, double* w, double* z,
+                                lapack_int ldz, double* work, lapack_int* iwork,
+                                lapack_int* ifail );
+
+lapack_int LAPACKE_ssbgst_work( int matrix_order, char vect, char uplo,
+                                lapack_int n, lapack_int ka, lapack_int kb,
+                                float* ab, lapack_int ldab, const float* bb,
+                                lapack_int ldbb, float* x, lapack_int ldx,
+                                float* work );
+lapack_int LAPACKE_dsbgst_work( int matrix_order, char vect, char uplo,
+                                lapack_int n, lapack_int ka, lapack_int kb,
+                                double* ab, lapack_int ldab, const double* bb,
+                                lapack_int ldbb, double* x, lapack_int ldx,
+                                double* work );
+
+lapack_int LAPACKE_ssbgv_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_int ka, lapack_int kb,
+                               float* ab, lapack_int ldab, float* bb,
+                               lapack_int ldbb, float* w, float* z,
+                               lapack_int ldz, float* work );
+lapack_int LAPACKE_dsbgv_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, lapack_int ka, lapack_int kb,
+                               double* ab, lapack_int ldab, double* bb,
+                               lapack_int ldbb, double* w, double* z,
+                               lapack_int ldz, double* work );
+
+lapack_int LAPACKE_ssbgvd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_int ka, lapack_int kb,
+                                float* ab, lapack_int ldab, float* bb,
+                                lapack_int ldbb, float* w, float* z,
+                                lapack_int ldz, float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dsbgvd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, lapack_int ka, lapack_int kb,
+                                double* ab, lapack_int ldab, double* bb,
+                                lapack_int ldbb, double* w, double* z,
+                                lapack_int ldz, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_ssbgvx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, lapack_int ka,
+                                lapack_int kb, float* ab, lapack_int ldab,
+                                float* bb, lapack_int ldbb, float* q,
+                                lapack_int ldq, float vl, float vu,
+                                lapack_int il, lapack_int iu, float abstol,
+                                lapack_int* m, float* w, float* z,
+                                lapack_int ldz, float* work, lapack_int* iwork,
+                                lapack_int* ifail );
+lapack_int LAPACKE_dsbgvx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, lapack_int ka,
+                                lapack_int kb, double* ab, lapack_int ldab,
+                                double* bb, lapack_int ldbb, double* q,
+                                lapack_int ldq, double vl, double vu,
+                                lapack_int il, lapack_int iu, double abstol,
+                                lapack_int* m, double* w, double* z,
+                                lapack_int ldz, double* work, lapack_int* iwork,
+                                lapack_int* ifail );
+
+lapack_int LAPACKE_ssbtrd_work( int matrix_order, char vect, char uplo,
+                                lapack_int n, lapack_int kd, float* ab,
+                                lapack_int ldab, float* d, float* e, float* q,
+                                lapack_int ldq, float* work );
+lapack_int LAPACKE_dsbtrd_work( int matrix_order, char vect, char uplo,
+                                lapack_int n, lapack_int kd, double* ab,
+                                lapack_int ldab, double* d, double* e,
+                                double* q, lapack_int ldq, double* work );
+
+lapack_int LAPACKE_ssfrk_work( int matrix_order, char transr, char uplo,
+                               char trans, lapack_int n, lapack_int k,
+                               float alpha, const float* a, lapack_int lda,
+                               float beta, float* c );
+lapack_int LAPACKE_dsfrk_work( int matrix_order, char transr, char uplo,
+                               char trans, lapack_int n, lapack_int k,
+                               double alpha, const double* a, lapack_int lda,
+                               double beta, double* c );
+
+lapack_int LAPACKE_sspcon_work( int matrix_order, char uplo, lapack_int n,
+                                const float* ap, const lapack_int* ipiv,
+                                float anorm, float* rcond, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dspcon_work( int matrix_order, char uplo, lapack_int n,
+                                const double* ap, const lapack_int* ipiv,
+                                double anorm, double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_cspcon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* ap,
+                                const lapack_int* ipiv, float anorm,
+                                float* rcond, lapack_complex_float* work );
+lapack_int LAPACKE_zspcon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* ap,
+                                const lapack_int* ipiv, double anorm,
+                                double* rcond, lapack_complex_double* work );
+
+lapack_int LAPACKE_sspev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, float* ap, float* w, float* z,
+                               lapack_int ldz, float* work );
+lapack_int LAPACKE_dspev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, double* ap, double* w, double* z,
+                               lapack_int ldz, double* work );
+
+lapack_int LAPACKE_sspevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, float* ap, float* w, float* z,
+                                lapack_int ldz, float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dspevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, double* ap, double* w, double* z,
+                                lapack_int ldz, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_sspevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, float* ap, float vl,
+                                float vu, lapack_int il, lapack_int iu,
+                                float abstol, lapack_int* m, float* w, float* z,
+                                lapack_int ldz, float* work, lapack_int* iwork,
+                                lapack_int* ifail );
+lapack_int LAPACKE_dspevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, double* ap, double vl,
+                                double vu, lapack_int il, lapack_int iu,
+                                double abstol, lapack_int* m, double* w,
+                                double* z, lapack_int ldz, double* work,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_sspgst_work( int matrix_order, lapack_int itype, char uplo,
+                                lapack_int n, float* ap, const float* bp );
+lapack_int LAPACKE_dspgst_work( int matrix_order, lapack_int itype, char uplo,
+                                lapack_int n, double* ap, const double* bp );
+
+lapack_int LAPACKE_sspgv_work( int matrix_order, lapack_int itype, char jobz,
+                               char uplo, lapack_int n, float* ap, float* bp,
+                               float* w, float* z, lapack_int ldz,
+                               float* work );
+lapack_int LAPACKE_dspgv_work( int matrix_order, lapack_int itype, char jobz,
+                               char uplo, lapack_int n, double* ap, double* bp,
+                               double* w, double* z, lapack_int ldz,
+                               double* work );
+
+lapack_int LAPACKE_sspgvd_work( int matrix_order, lapack_int itype, char jobz,
+                                char uplo, lapack_int n, float* ap, float* bp,
+                                float* w, float* z, lapack_int ldz, float* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_dspgvd_work( int matrix_order, lapack_int itype, char jobz,
+                                char uplo, lapack_int n, double* ap, double* bp,
+                                double* w, double* z, lapack_int ldz,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_sspgvx_work( int matrix_order, lapack_int itype, char jobz,
+                                char range, char uplo, lapack_int n, float* ap,
+                                float* bp, float vl, float vu, lapack_int il,
+                                lapack_int iu, float abstol, lapack_int* m,
+                                float* w, float* z, lapack_int ldz, float* work,
+                                lapack_int* iwork, lapack_int* ifail );
+lapack_int LAPACKE_dspgvx_work( int matrix_order, lapack_int itype, char jobz,
+                                char range, char uplo, lapack_int n, double* ap,
+                                double* bp, double vl, double vu, lapack_int il,
+                                lapack_int iu, double abstol, lapack_int* m,
+                                double* w, double* z, lapack_int ldz,
+                                double* work, lapack_int* iwork,
+                                lapack_int* ifail );
+
+lapack_int LAPACKE_ssprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* ap,
+                                const float* afp, const lapack_int* ipiv,
+                                const float* b, lapack_int ldb, float* x,
+                                lapack_int ldx, float* ferr, float* berr,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dsprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* ap,
+                                const double* afp, const lapack_int* ipiv,
+                                const double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_csprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* ap,
+                                const lapack_complex_float* afp,
+                                const lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zsprfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                const lapack_complex_double* afp,
+                                const lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_sspsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, float* ap, lapack_int* ipiv,
+                               float* b, lapack_int ldb );
+lapack_int LAPACKE_dspsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, double* ap, lapack_int* ipiv,
+                               double* b, lapack_int ldb );
+lapack_int LAPACKE_cspsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_float* ap,
+                               lapack_int* ipiv, lapack_complex_float* b,
+                               lapack_int ldb );
+lapack_int LAPACKE_zspsv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_double* ap,
+                               lapack_int* ipiv, lapack_complex_double* b,
+                               lapack_int ldb );
+
+lapack_int LAPACKE_sspsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs, const float* ap,
+                                float* afp, lapack_int* ipiv, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dspsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs, const double* ap,
+                                double* afp, lapack_int* ipiv, const double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_cspsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* ap,
+                                lapack_complex_float* afp, lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zspsvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                lapack_complex_double* afp, lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_ssptrd_work( int matrix_order, char uplo, lapack_int n,
+                                float* ap, float* d, float* e, float* tau );
+lapack_int LAPACKE_dsptrd_work( int matrix_order, char uplo, lapack_int n,
+                                double* ap, double* d, double* e, double* tau );
+
+lapack_int LAPACKE_ssptrf_work( int matrix_order, char uplo, lapack_int n,
+                                float* ap, lapack_int* ipiv );
+lapack_int LAPACKE_dsptrf_work( int matrix_order, char uplo, lapack_int n,
+                                double* ap, lapack_int* ipiv );
+lapack_int LAPACKE_csptrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* ap, lapack_int* ipiv );
+lapack_int LAPACKE_zsptrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* ap, lapack_int* ipiv );
+
+lapack_int LAPACKE_ssptri_work( int matrix_order, char uplo, lapack_int n,
+                                float* ap, const lapack_int* ipiv,
+                                float* work );
+lapack_int LAPACKE_dsptri_work( int matrix_order, char uplo, lapack_int n,
+                                double* ap, const lapack_int* ipiv,
+                                double* work );
+lapack_int LAPACKE_csptri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* ap,
+                                const lapack_int* ipiv,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zsptri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* ap,
+                                const lapack_int* ipiv,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_ssptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* ap,
+                                const lapack_int* ipiv, float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_dsptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* ap,
+                                const lapack_int* ipiv, double* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_csptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* ap,
+                                const lapack_int* ipiv, lapack_complex_float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_zsptrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                const lapack_int* ipiv,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_sstebz_work( char range, char order, lapack_int n, float vl,
+                                float vu, lapack_int il, lapack_int iu,
+                                float abstol, const float* d, const float* e,
+                                lapack_int* m, lapack_int* nsplit, float* w,
+                                lapack_int* iblock, lapack_int* isplit,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dstebz_work( char range, char order, lapack_int n, double vl,
+                                double vu, lapack_int il, lapack_int iu,
+                                double abstol, const double* d, const double* e,
+                                lapack_int* m, lapack_int* nsplit, double* w,
+                                lapack_int* iblock, lapack_int* isplit,
+                                double* work, lapack_int* iwork );
+
+lapack_int LAPACKE_sstedc_work( int matrix_order, char compz, lapack_int n,
+                                float* d, float* e, float* z, lapack_int ldz,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dstedc_work( int matrix_order, char compz, lapack_int n,
+                                double* d, double* e, double* z, lapack_int ldz,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_cstedc_work( int matrix_order, char compz, lapack_int n,
+                                float* d, float* e, lapack_complex_float* z,
+                                lapack_int ldz, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_zstedc_work( int matrix_order, char compz, lapack_int n,
+                                double* d, double* e, lapack_complex_double* z,
+                                lapack_int ldz, lapack_complex_double* work,
+                                lapack_int lwork, double* rwork,
+                                lapack_int lrwork, lapack_int* iwork,
+                                lapack_int liwork );
+
+lapack_int LAPACKE_sstegr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, float* d, float* e, float vl,
+                                float vu, lapack_int il, lapack_int iu,
+                                float abstol, lapack_int* m, float* w, float* z,
+                                lapack_int ldz, lapack_int* isuppz, float* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_dstegr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, double* d, double* e, double vl,
+                                double vu, lapack_int il, lapack_int iu,
+                                double abstol, lapack_int* m, double* w,
+                                double* z, lapack_int ldz, lapack_int* isuppz,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_cstegr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, float* d, float* e, float vl,
+                                float vu, lapack_int il, lapack_int iu,
+                                float abstol, lapack_int* m, float* w,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_int* isuppz, float* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_zstegr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, double* d, double* e, double vl,
+                                double vu, lapack_int il, lapack_int iu,
+                                double abstol, lapack_int* m, double* w,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_int* isuppz, double* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+
+lapack_int LAPACKE_sstein_work( int matrix_order, lapack_int n, const float* d,
+                                const float* e, lapack_int m, const float* w,
+                                const lapack_int* iblock,
+                                const lapack_int* isplit, float* z,
+                                lapack_int ldz, float* work, lapack_int* iwork,
+                                lapack_int* ifailv );
+lapack_int LAPACKE_dstein_work( int matrix_order, lapack_int n, const double* d,
+                                const double* e, lapack_int m, const double* w,
+                                const lapack_int* iblock,
+                                const lapack_int* isplit, double* z,
+                                lapack_int ldz, double* work, lapack_int* iwork,
+                                lapack_int* ifailv );
+lapack_int LAPACKE_cstein_work( int matrix_order, lapack_int n, const float* d,
+                                const float* e, lapack_int m, const float* w,
+                                const lapack_int* iblock,
+                                const lapack_int* isplit,
+                                lapack_complex_float* z, lapack_int ldz,
+                                float* work, lapack_int* iwork,
+                                lapack_int* ifailv );
+lapack_int LAPACKE_zstein_work( int matrix_order, lapack_int n, const double* d,
+                                const double* e, lapack_int m, const double* w,
+                                const lapack_int* iblock,
+                                const lapack_int* isplit,
+                                lapack_complex_double* z, lapack_int ldz,
+                                double* work, lapack_int* iwork,
+                                lapack_int* ifailv );
+
+lapack_int LAPACKE_sstemr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, float* d, float* e, float vl,
+                                float vu, lapack_int il, lapack_int iu,
+                                lapack_int* m, float* w, float* z,
+                                lapack_int ldz, lapack_int nzc,
+                                lapack_int* isuppz, lapack_logical* tryrac,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dstemr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, double* d, double* e, double vl,
+                                double vu, lapack_int il, lapack_int iu,
+                                lapack_int* m, double* w, double* z,
+                                lapack_int ldz, lapack_int nzc,
+                                lapack_int* isuppz, lapack_logical* tryrac,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_cstemr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, float* d, float* e, float vl,
+                                float vu, lapack_int il, lapack_int iu,
+                                lapack_int* m, float* w,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_int nzc, lapack_int* isuppz,
+                                lapack_logical* tryrac, float* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_zstemr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, double* d, double* e, double vl,
+                                double vu, lapack_int il, lapack_int iu,
+                                lapack_int* m, double* w,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_int nzc, lapack_int* isuppz,
+                                lapack_logical* tryrac, double* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+
+lapack_int LAPACKE_ssteqr_work( int matrix_order, char compz, lapack_int n,
+                                float* d, float* e, float* z, lapack_int ldz,
+                                float* work );
+lapack_int LAPACKE_dsteqr_work( int matrix_order, char compz, lapack_int n,
+                                double* d, double* e, double* z, lapack_int ldz,
+                                double* work );
+lapack_int LAPACKE_csteqr_work( int matrix_order, char compz, lapack_int n,
+                                float* d, float* e, lapack_complex_float* z,
+                                lapack_int ldz, float* work );
+lapack_int LAPACKE_zsteqr_work( int matrix_order, char compz, lapack_int n,
+                                double* d, double* e, lapack_complex_double* z,
+                                lapack_int ldz, double* work );
+
+lapack_int LAPACKE_ssterf_work( lapack_int n, float* d, float* e );
+lapack_int LAPACKE_dsterf_work( lapack_int n, double* d, double* e );
+
+lapack_int LAPACKE_sstev_work( int matrix_order, char jobz, lapack_int n,
+                               float* d, float* e, float* z, lapack_int ldz,
+                               float* work );
+lapack_int LAPACKE_dstev_work( int matrix_order, char jobz, lapack_int n,
+                               double* d, double* e, double* z, lapack_int ldz,
+                               double* work );
+
+lapack_int LAPACKE_sstevd_work( int matrix_order, char jobz, lapack_int n,
+                                float* d, float* e, float* z, lapack_int ldz,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dstevd_work( int matrix_order, char jobz, lapack_int n,
+                                double* d, double* e, double* z, lapack_int ldz,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_sstevr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, float* d, float* e, float vl,
+                                float vu, lapack_int il, lapack_int iu,
+                                float abstol, lapack_int* m, float* w, float* z,
+                                lapack_int ldz, lapack_int* isuppz, float* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_dstevr_work( int matrix_order, char jobz, char range,
+                                lapack_int n, double* d, double* e, double vl,
+                                double vu, lapack_int il, lapack_int iu,
+                                double abstol, lapack_int* m, double* w,
+                                double* z, lapack_int ldz, lapack_int* isuppz,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_sstevx_work( int matrix_order, char jobz, char range,
+                                lapack_int n, float* d, float* e, float vl,
+                                float vu, lapack_int il, lapack_int iu,
+                                float abstol, lapack_int* m, float* w, float* z,
+                                lapack_int ldz, float* work, lapack_int* iwork,
+                                lapack_int* ifail );
+lapack_int LAPACKE_dstevx_work( int matrix_order, char jobz, char range,
+                                lapack_int n, double* d, double* e, double vl,
+                                double vu, lapack_int il, lapack_int iu,
+                                double abstol, lapack_int* m, double* w,
+                                double* z, lapack_int ldz, double* work,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_ssycon_work( int matrix_order, char uplo, lapack_int n,
+                                const float* a, lapack_int lda,
+                                const lapack_int* ipiv, float anorm,
+                                float* rcond, float* work, lapack_int* iwork );
+lapack_int LAPACKE_dsycon_work( int matrix_order, char uplo, lapack_int n,
+                                const double* a, lapack_int lda,
+                                const lapack_int* ipiv, double anorm,
+                                double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_csycon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_int* ipiv, float anorm,
+                                float* rcond, lapack_complex_float* work );
+lapack_int LAPACKE_zsycon_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_int* ipiv, double anorm,
+                                double* rcond, lapack_complex_double* work );
+
+lapack_int LAPACKE_ssyequb_work( int matrix_order, char uplo, lapack_int n,
+                                 const float* a, lapack_int lda, float* s,
+                                 float* scond, float* amax, float* work );
+lapack_int LAPACKE_dsyequb_work( int matrix_order, char uplo, lapack_int n,
+                                 const double* a, lapack_int lda, double* s,
+                                 double* scond, double* amax, double* work );
+lapack_int LAPACKE_csyequb_work( int matrix_order, char uplo, lapack_int n,
+                                 const lapack_complex_float* a, lapack_int lda,
+                                 float* s, float* scond, float* amax,
+                                 lapack_complex_float* work );
+lapack_int LAPACKE_zsyequb_work( int matrix_order, char uplo, lapack_int n,
+                                 const lapack_complex_double* a, lapack_int lda,
+                                 double* s, double* scond, double* amax,
+                                 lapack_complex_double* work );
+
+lapack_int LAPACKE_ssyev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, float* a, lapack_int lda, float* w,
+                               float* work, lapack_int lwork );
+lapack_int LAPACKE_dsyev_work( int matrix_order, char jobz, char uplo,
+                               lapack_int n, double* a, lapack_int lda,
+                               double* w, double* work, lapack_int lwork );
+
+lapack_int LAPACKE_ssyevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, float* a, lapack_int lda,
+                                float* w, float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dsyevd_work( int matrix_order, char jobz, char uplo,
+                                lapack_int n, double* a, lapack_int lda,
+                                double* w, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_ssyevr_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, float* a,
+                                lapack_int lda, float vl, float vu,
+                                lapack_int il, lapack_int iu, float abstol,
+                                lapack_int* m, float* w, float* z,
+                                lapack_int ldz, lapack_int* isuppz, float* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_dsyevr_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, double* a,
+                                lapack_int lda, double vl, double vu,
+                                lapack_int il, lapack_int iu, double abstol,
+                                lapack_int* m, double* w, double* z,
+                                lapack_int ldz, lapack_int* isuppz,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_ssyevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, float* a,
+                                lapack_int lda, float vl, float vu,
+                                lapack_int il, lapack_int iu, float abstol,
+                                lapack_int* m, float* w, float* z,
+                                lapack_int ldz, float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int* ifail );
+lapack_int LAPACKE_dsyevx_work( int matrix_order, char jobz, char range,
+                                char uplo, lapack_int n, double* a,
+                                lapack_int lda, double vl, double vu,
+                                lapack_int il, lapack_int iu, double abstol,
+                                lapack_int* m, double* w, double* z,
+                                lapack_int ldz, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_ssygst_work( int matrix_order, lapack_int itype, char uplo,
+                                lapack_int n, float* a, lapack_int lda,
+                                const float* b, lapack_int ldb );
+lapack_int LAPACKE_dsygst_work( int matrix_order, lapack_int itype, char uplo,
+                                lapack_int n, double* a, lapack_int lda,
+                                const double* b, lapack_int ldb );
+
+lapack_int LAPACKE_ssygv_work( int matrix_order, lapack_int itype, char jobz,
+                               char uplo, lapack_int n, float* a,
+                               lapack_int lda, float* b, lapack_int ldb,
+                               float* w, float* work, lapack_int lwork );
+lapack_int LAPACKE_dsygv_work( int matrix_order, lapack_int itype, char jobz,
+                               char uplo, lapack_int n, double* a,
+                               lapack_int lda, double* b, lapack_int ldb,
+                               double* w, double* work, lapack_int lwork );
+
+lapack_int LAPACKE_ssygvd_work( int matrix_order, lapack_int itype, char jobz,
+                                char uplo, lapack_int n, float* a,
+                                lapack_int lda, float* b, lapack_int ldb,
+                                float* w, float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dsygvd_work( int matrix_order, lapack_int itype, char jobz,
+                                char uplo, lapack_int n, double* a,
+                                lapack_int lda, double* b, lapack_int ldb,
+                                double* w, double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+
+lapack_int LAPACKE_ssygvx_work( int matrix_order, lapack_int itype, char jobz,
+                                char range, char uplo, lapack_int n, float* a,
+                                lapack_int lda, float* b, lapack_int ldb,
+                                float vl, float vu, lapack_int il,
+                                lapack_int iu, float abstol, lapack_int* m,
+                                float* w, float* z, lapack_int ldz, float* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int* ifail );
+lapack_int LAPACKE_dsygvx_work( int matrix_order, lapack_int itype, char jobz,
+                                char range, char uplo, lapack_int n, double* a,
+                                lapack_int lda, double* b, lapack_int ldb,
+                                double vl, double vu, lapack_int il,
+                                lapack_int iu, double abstol, lapack_int* m,
+                                double* w, double* z, lapack_int ldz,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int* ifail );
+
+lapack_int LAPACKE_ssyrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* a, lapack_int lda,
+                                const float* af, lapack_int ldaf,
+                                const lapack_int* ipiv, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* ferr, float* berr, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dsyrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* a,
+                                lapack_int lda, const double* af,
+                                lapack_int ldaf, const lapack_int* ipiv,
+                                const double* b, lapack_int ldb, double* x,
+                                lapack_int ldx, double* ferr, double* berr,
+                                double* work, lapack_int* iwork );
+lapack_int LAPACKE_csyrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* af,
+                                lapack_int ldaf, const lapack_int* ipiv,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_zsyrfs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_double* a,
+                                lapack_int lda, const lapack_complex_double* af,
+                                lapack_int ldaf, const lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_ssyrfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs, const float* a,
+                                 lapack_int lda, const float* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const float* s, const float* b, lapack_int ldb,
+                                 float* x, lapack_int ldx, float* rcond,
+                                 float* berr, lapack_int n_err_bnds,
+                                 float* err_bnds_norm, float* err_bnds_comp,
+                                 lapack_int nparams, float* params, float* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_dsyrfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs, const double* a,
+                                 lapack_int lda, const double* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const double* s, const double* b,
+                                 lapack_int ldb, double* x, lapack_int ldx,
+                                 double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, double* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_csyrfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs,
+                                 const lapack_complex_float* a, lapack_int lda,
+                                 const lapack_complex_float* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const float* s, const lapack_complex_float* b,
+                                 lapack_int ldb, lapack_complex_float* x,
+                                 lapack_int ldx, float* rcond, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, lapack_complex_float* work,
+                                 float* rwork );
+lapack_int LAPACKE_zsyrfsx_work( int matrix_order, char uplo, char equed,
+                                 lapack_int n, lapack_int nrhs,
+                                 const lapack_complex_double* a, lapack_int lda,
+                                 const lapack_complex_double* af,
+                                 lapack_int ldaf, const lapack_int* ipiv,
+                                 const double* s,
+                                 const lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_ssysv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, float* a, lapack_int lda,
+                               lapack_int* ipiv, float* b, lapack_int ldb,
+                               float* work, lapack_int lwork );
+lapack_int LAPACKE_dsysv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, double* a, lapack_int lda,
+                               lapack_int* ipiv, double* b, lapack_int ldb,
+                               double* work, lapack_int lwork );
+lapack_int LAPACKE_csysv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_float* a,
+                               lapack_int lda, lapack_int* ipiv,
+                               lapack_complex_float* b, lapack_int ldb,
+                               lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zsysv_work( int matrix_order, char uplo, lapack_int n,
+                               lapack_int nrhs, lapack_complex_double* a,
+                               lapack_int lda, lapack_int* ipiv,
+                               lapack_complex_double* b, lapack_int ldb,
+                               lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_ssysvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs, const float* a,
+                                lapack_int lda, float* af, lapack_int ldaf,
+                                lapack_int* ipiv, const float* b,
+                                lapack_int ldb, float* x, lapack_int ldx,
+                                float* rcond, float* ferr, float* berr,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dsysvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs, const double* a,
+                                lapack_int lda, double* af, lapack_int ldaf,
+                                lapack_int* ipiv, const double* b,
+                                lapack_int ldb, double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_csysvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* af, lapack_int ldaf,
+                                lapack_int* ipiv, const lapack_complex_float* b,
+                                lapack_int ldb, lapack_complex_float* x,
+                                lapack_int ldx, float* rcond, float* ferr,
+                                float* berr, lapack_complex_float* work,
+                                lapack_int lwork, float* rwork );
+lapack_int LAPACKE_zsysvx_work( int matrix_order, char fact, char uplo,
+                                lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* af, lapack_int ldaf,
+                                lapack_int* ipiv,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* x, lapack_int ldx,
+                                double* rcond, double* ferr, double* berr,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork );
+
+lapack_int LAPACKE_ssysvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs, float* a,
+                                 lapack_int lda, float* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, float* s,
+                                 float* b, lapack_int ldb, float* x,
+                                 lapack_int ldx, float* rcond, float* rpvgrw,
+                                 float* berr, lapack_int n_err_bnds,
+                                 float* err_bnds_norm, float* err_bnds_comp,
+                                 lapack_int nparams, float* params, float* work,
+                                 lapack_int* iwork );
+lapack_int LAPACKE_dsysvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs, double* a,
+                                 lapack_int lda, double* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, double* s,
+                                 double* b, lapack_int ldb, double* x,
+                                 lapack_int ldx, double* rcond, double* rpvgrw,
+                                 double* berr, lapack_int n_err_bnds,
+                                 double* err_bnds_norm, double* err_bnds_comp,
+                                 lapack_int nparams, double* params,
+                                 double* work, lapack_int* iwork );
+lapack_int LAPACKE_csysvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, float* s,
+                                 lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* x, lapack_int ldx,
+                                 float* rcond, float* rpvgrw, float* berr,
+                                 lapack_int n_err_bnds, float* err_bnds_norm,
+                                 float* err_bnds_comp, lapack_int nparams,
+                                 float* params, lapack_complex_float* work,
+                                 float* rwork );
+lapack_int LAPACKE_zsysvxx_work( int matrix_order, char fact, char uplo,
+                                 lapack_int n, lapack_int nrhs,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* af, lapack_int ldaf,
+                                 lapack_int* ipiv, char* equed, double* s,
+                                 lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* x, lapack_int ldx,
+                                 double* rcond, double* rpvgrw, double* berr,
+                                 lapack_int n_err_bnds, double* err_bnds_norm,
+                                 double* err_bnds_comp, lapack_int nparams,
+                                 double* params, lapack_complex_double* work,
+                                 double* rwork );
+
+lapack_int LAPACKE_ssytrd_work( int matrix_order, char uplo, lapack_int n,
+                                float* a, lapack_int lda, float* d, float* e,
+                                float* tau, float* work, lapack_int lwork );
+lapack_int LAPACKE_dsytrd_work( int matrix_order, char uplo, lapack_int n,
+                                double* a, lapack_int lda, double* d, double* e,
+                                double* tau, double* work, lapack_int lwork );
+
+lapack_int LAPACKE_ssytrf_work( int matrix_order, char uplo, lapack_int n,
+                                float* a, lapack_int lda, lapack_int* ipiv,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dsytrf_work( int matrix_order, char uplo, lapack_int n,
+                                double* a, lapack_int lda, lapack_int* ipiv,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_csytrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_int* ipiv, lapack_complex_float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_zsytrf_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_int* ipiv, lapack_complex_double* work,
+                                lapack_int lwork );
+
+lapack_int LAPACKE_ssytri_work( int matrix_order, char uplo, lapack_int n,
+                                float* a, lapack_int lda,
+                                const lapack_int* ipiv, float* work );
+lapack_int LAPACKE_dsytri_work( int matrix_order, char uplo, lapack_int n,
+                                double* a, lapack_int lda,
+                                const lapack_int* ipiv, double* work );
+lapack_int LAPACKE_csytri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                const lapack_int* ipiv,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zsytri_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                const lapack_int* ipiv,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_ssytrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const float* a, lapack_int lda,
+                                const lapack_int* ipiv, float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_dsytrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const double* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                double* b, lapack_int ldb );
+lapack_int LAPACKE_csytrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_zsytrs_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_int nrhs, const lapack_complex_double* a,
+                                lapack_int lda, const lapack_int* ipiv,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_stbcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n, lapack_int kd,
+                                const float* ab, lapack_int ldab, float* rcond,
+                                float* work, lapack_int* iwork );
+lapack_int LAPACKE_dtbcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n, lapack_int kd,
+                                const double* ab, lapack_int ldab,
+                                double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ctbcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n, lapack_int kd,
+                                const lapack_complex_float* ab, lapack_int ldab,
+                                float* rcond, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_ztbcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n, lapack_int kd,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab, double* rcond,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_stbrfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int kd,
+                                lapack_int nrhs, const float* ab,
+                                lapack_int ldab, const float* b, lapack_int ldb,
+                                const float* x, lapack_int ldx, float* ferr,
+                                float* berr, float* work, lapack_int* iwork );
+lapack_int LAPACKE_dtbrfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int kd,
+                                lapack_int nrhs, const double* ab,
+                                lapack_int ldab, const double* b,
+                                lapack_int ldb, const double* x, lapack_int ldx,
+                                double* ferr, double* berr, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ctbrfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int kd,
+                                lapack_int nrhs, const lapack_complex_float* ab,
+                                lapack_int ldab, const lapack_complex_float* b,
+                                lapack_int ldb, const lapack_complex_float* x,
+                                lapack_int ldx, float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_ztbrfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int kd,
+                                lapack_int nrhs,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab, const lapack_complex_double* b,
+                                lapack_int ldb, const lapack_complex_double* x,
+                                lapack_int ldx, double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_stbtrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int kd,
+                                lapack_int nrhs, const float* ab,
+                                lapack_int ldab, float* b, lapack_int ldb );
+lapack_int LAPACKE_dtbtrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int kd,
+                                lapack_int nrhs, const double* ab,
+                                lapack_int ldab, double* b, lapack_int ldb );
+lapack_int LAPACKE_ctbtrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int kd,
+                                lapack_int nrhs, const lapack_complex_float* ab,
+                                lapack_int ldab, lapack_complex_float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_ztbtrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int kd,
+                                lapack_int nrhs,
+                                const lapack_complex_double* ab,
+                                lapack_int ldab, lapack_complex_double* b,
+                                lapack_int ldb );
+
+lapack_int LAPACKE_stfsm_work( int matrix_order, char transr, char side,
+                               char uplo, char trans, char diag, lapack_int m,
+                               lapack_int n, float alpha, const float* a,
+                               float* b, lapack_int ldb );
+lapack_int LAPACKE_dtfsm_work( int matrix_order, char transr, char side,
+                               char uplo, char trans, char diag, lapack_int m,
+                               lapack_int n, double alpha, const double* a,
+                               double* b, lapack_int ldb );
+lapack_int LAPACKE_ctfsm_work( int matrix_order, char transr, char side,
+                               char uplo, char trans, char diag, lapack_int m,
+                               lapack_int n, lapack_complex_float alpha,
+                               const lapack_complex_float* a,
+                               lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_ztfsm_work( int matrix_order, char transr, char side,
+                               char uplo, char trans, char diag, lapack_int m,
+                               lapack_int n, lapack_complex_double alpha,
+                               const lapack_complex_double* a,
+                               lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_stftri_work( int matrix_order, char transr, char uplo,
+                                char diag, lapack_int n, float* a );
+lapack_int LAPACKE_dtftri_work( int matrix_order, char transr, char uplo,
+                                char diag, lapack_int n, double* a );
+lapack_int LAPACKE_ctftri_work( int matrix_order, char transr, char uplo,
+                                char diag, lapack_int n,
+                                lapack_complex_float* a );
+lapack_int LAPACKE_ztftri_work( int matrix_order, char transr, char uplo,
+                                char diag, lapack_int n,
+                                lapack_complex_double* a );
+
+lapack_int LAPACKE_stfttp_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const float* arf, float* ap );
+lapack_int LAPACKE_dtfttp_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const double* arf, double* ap );
+lapack_int LAPACKE_ctfttp_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const lapack_complex_float* arf,
+                                lapack_complex_float* ap );
+lapack_int LAPACKE_ztfttp_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const lapack_complex_double* arf,
+                                lapack_complex_double* ap );
+
+lapack_int LAPACKE_stfttr_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const float* arf, float* a,
+                                lapack_int lda );
+lapack_int LAPACKE_dtfttr_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const double* arf, double* a,
+                                lapack_int lda );
+lapack_int LAPACKE_ctfttr_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const lapack_complex_float* arf,
+                                lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_ztfttr_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const lapack_complex_double* arf,
+                                lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_stgevc_work( int matrix_order, char side, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const float* s, lapack_int lds, const float* p,
+                                lapack_int ldp, float* vl, lapack_int ldvl,
+                                float* vr, lapack_int ldvr, lapack_int mm,
+                                lapack_int* m, float* work );
+lapack_int LAPACKE_dtgevc_work( int matrix_order, char side, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const double* s, lapack_int lds,
+                                const double* p, lapack_int ldp, double* vl,
+                                lapack_int ldvl, double* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m, double* work );
+lapack_int LAPACKE_ctgevc_work( int matrix_order, char side, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const lapack_complex_float* s, lapack_int lds,
+                                const lapack_complex_float* p, lapack_int ldp,
+                                lapack_complex_float* vl, lapack_int ldvl,
+                                lapack_complex_float* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_ztgevc_work( int matrix_order, char side, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const lapack_complex_double* s, lapack_int lds,
+                                const lapack_complex_double* p, lapack_int ldp,
+                                lapack_complex_double* vl, lapack_int ldvl,
+                                lapack_complex_double* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_stgexc_work( int matrix_order, lapack_logical wantq,
+                                lapack_logical wantz, lapack_int n, float* a,
+                                lapack_int lda, float* b, lapack_int ldb,
+                                float* q, lapack_int ldq, float* z,
+                                lapack_int ldz, lapack_int* ifst,
+                                lapack_int* ilst, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dtgexc_work( int matrix_order, lapack_logical wantq,
+                                lapack_logical wantz, lapack_int n, double* a,
+                                lapack_int lda, double* b, lapack_int ldb,
+                                double* q, lapack_int ldq, double* z,
+                                lapack_int ldz, lapack_int* ifst,
+                                lapack_int* ilst, double* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_ctgexc_work( int matrix_order, lapack_logical wantq,
+                                lapack_logical wantz, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_int ifst, lapack_int ilst );
+lapack_int LAPACKE_ztgexc_work( int matrix_order, lapack_logical wantq,
+                                lapack_logical wantz, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_int ifst, lapack_int ilst );
+
+lapack_int LAPACKE_stgsen_work( int matrix_order, lapack_int ijob,
+                                lapack_logical wantq, lapack_logical wantz,
+                                const lapack_logical* select, lapack_int n,
+                                float* a, lapack_int lda, float* b,
+                                lapack_int ldb, float* alphar, float* alphai,
+                                float* beta, float* q, lapack_int ldq, float* z,
+                                lapack_int ldz, lapack_int* m, float* pl,
+                                float* pr, float* dif, float* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+lapack_int LAPACKE_dtgsen_work( int matrix_order, lapack_int ijob,
+                                lapack_logical wantq, lapack_logical wantz,
+                                const lapack_logical* select, lapack_int n,
+                                double* a, lapack_int lda, double* b,
+                                lapack_int ldb, double* alphar, double* alphai,
+                                double* beta, double* q, lapack_int ldq,
+                                double* z, lapack_int ldz, lapack_int* m,
+                                double* pl, double* pr, double* dif,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_ctgsen_work( int matrix_order, lapack_int ijob,
+                                lapack_logical wantq, lapack_logical wantz,
+                                const lapack_logical* select, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* alpha,
+                                lapack_complex_float* beta,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_complex_float* z, lapack_int ldz,
+                                lapack_int* m, float* pl, float* pr, float* dif,
+                                lapack_complex_float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_ztgsen_work( int matrix_order, lapack_int ijob,
+                                lapack_logical wantq, lapack_logical wantz,
+                                const lapack_logical* select, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* alpha,
+                                lapack_complex_double* beta,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_complex_double* z, lapack_int ldz,
+                                lapack_int* m, double* pl, double* pr,
+                                double* dif, lapack_complex_double* work,
+                                lapack_int lwork, lapack_int* iwork,
+                                lapack_int liwork );
+
+lapack_int LAPACKE_stgsja_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int p,
+                                lapack_int n, lapack_int k, lapack_int l,
+                                float* a, lapack_int lda, float* b,
+                                lapack_int ldb, float tola, float tolb,
+                                float* alpha, float* beta, float* u,
+                                lapack_int ldu, float* v, lapack_int ldv,
+                                float* q, lapack_int ldq, float* work,
+                                lapack_int* ncycle );
+lapack_int LAPACKE_dtgsja_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int p,
+                                lapack_int n, lapack_int k, lapack_int l,
+                                double* a, lapack_int lda, double* b,
+                                lapack_int ldb, double tola, double tolb,
+                                double* alpha, double* beta, double* u,
+                                lapack_int ldu, double* v, lapack_int ldv,
+                                double* q, lapack_int ldq, double* work,
+                                lapack_int* ncycle );
+lapack_int LAPACKE_ctgsja_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int p,
+                                lapack_int n, lapack_int k, lapack_int l,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                float tola, float tolb, float* alpha,
+                                float* beta, lapack_complex_float* u,
+                                lapack_int ldu, lapack_complex_float* v,
+                                lapack_int ldv, lapack_complex_float* q,
+                                lapack_int ldq, lapack_complex_float* work,
+                                lapack_int* ncycle );
+lapack_int LAPACKE_ztgsja_work( int matrix_order, char jobu, char jobv,
+                                char jobq, lapack_int m, lapack_int p,
+                                lapack_int n, lapack_int k, lapack_int l,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                double tola, double tolb, double* alpha,
+                                double* beta, lapack_complex_double* u,
+                                lapack_int ldu, lapack_complex_double* v,
+                                lapack_int ldv, lapack_complex_double* q,
+                                lapack_int ldq, lapack_complex_double* work,
+                                lapack_int* ncycle );
+
+lapack_int LAPACKE_stgsna_work( int matrix_order, char job, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const float* a, lapack_int lda, const float* b,
+                                lapack_int ldb, const float* vl,
+                                lapack_int ldvl, const float* vr,
+                                lapack_int ldvr, float* s, float* dif,
+                                lapack_int mm, lapack_int* m, float* work,
+                                lapack_int lwork, lapack_int* iwork );
+lapack_int LAPACKE_dtgsna_work( int matrix_order, char job, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const double* a, lapack_int lda,
+                                const double* b, lapack_int ldb,
+                                const double* vl, lapack_int ldvl,
+                                const double* vr, lapack_int ldvr, double* s,
+                                double* dif, lapack_int mm, lapack_int* m,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ctgsna_work( int matrix_order, char job, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                const lapack_complex_float* vl, lapack_int ldvl,
+                                const lapack_complex_float* vr, lapack_int ldvr,
+                                float* s, float* dif, lapack_int mm,
+                                lapack_int* m, lapack_complex_float* work,
+                                lapack_int lwork, lapack_int* iwork );
+lapack_int LAPACKE_ztgsna_work( int matrix_order, char job, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                const lapack_complex_double* vl,
+                                lapack_int ldvl,
+                                const lapack_complex_double* vr,
+                                lapack_int ldvr, double* s, double* dif,
+                                lapack_int mm, lapack_int* m,
+                                lapack_complex_double* work, lapack_int lwork,
+                                lapack_int* iwork );
+
+lapack_int LAPACKE_stgsyl_work( int matrix_order, char trans, lapack_int ijob,
+                                lapack_int m, lapack_int n, const float* a,
+                                lapack_int lda, const float* b, lapack_int ldb,
+                                float* c, lapack_int ldc, const float* d,
+                                lapack_int ldd, const float* e, lapack_int lde,
+                                float* f, lapack_int ldf, float* scale,
+                                float* dif, float* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dtgsyl_work( int matrix_order, char trans, lapack_int ijob,
+                                lapack_int m, lapack_int n, const double* a,
+                                lapack_int lda, const double* b, lapack_int ldb,
+                                double* c, lapack_int ldc, const double* d,
+                                lapack_int ldd, const double* e, lapack_int lde,
+                                double* f, lapack_int ldf, double* scale,
+                                double* dif, double* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ctgsyl_work( int matrix_order, char trans, lapack_int ijob,
+                                lapack_int m, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* c, lapack_int ldc,
+                                const lapack_complex_float* d, lapack_int ldd,
+                                const lapack_complex_float* e, lapack_int lde,
+                                lapack_complex_float* f, lapack_int ldf,
+                                float* scale, float* dif,
+                                lapack_complex_float* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ztgsyl_work( int matrix_order, char trans, lapack_int ijob,
+                                lapack_int m, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* c, lapack_int ldc,
+                                const lapack_complex_double* d, lapack_int ldd,
+                                const lapack_complex_double* e, lapack_int lde,
+                                lapack_complex_double* f, lapack_int ldf,
+                                double* scale, double* dif,
+                                lapack_complex_double* work, lapack_int lwork,
+                                lapack_int* iwork );
+
+lapack_int LAPACKE_stpcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n, const float* ap,
+                                float* rcond, float* work, lapack_int* iwork );
+lapack_int LAPACKE_dtpcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n, const double* ap,
+                                double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ctpcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n,
+                                const lapack_complex_float* ap, float* rcond,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_ztpcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n,
+                                const lapack_complex_double* ap, double* rcond,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_stprfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const float* ap, const float* b, lapack_int ldb,
+                                const float* x, lapack_int ldx, float* ferr,
+                                float* berr, float* work, lapack_int* iwork );
+lapack_int LAPACKE_dtprfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const double* ap, const double* b,
+                                lapack_int ldb, const double* x, lapack_int ldx,
+                                double* ferr, double* berr, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ctprfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* ap,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                const lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_ztprfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                const lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_stptri_work( int matrix_order, char uplo, char diag,
+                                lapack_int n, float* ap );
+lapack_int LAPACKE_dtptri_work( int matrix_order, char uplo, char diag,
+                                lapack_int n, double* ap );
+lapack_int LAPACKE_ctptri_work( int matrix_order, char uplo, char diag,
+                                lapack_int n, lapack_complex_float* ap );
+lapack_int LAPACKE_ztptri_work( int matrix_order, char uplo, char diag,
+                                lapack_int n, lapack_complex_double* ap );
+
+lapack_int LAPACKE_stptrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const float* ap, float* b, lapack_int ldb );
+lapack_int LAPACKE_dtptrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const double* ap, double* b, lapack_int ldb );
+lapack_int LAPACKE_ctptrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* ap,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_ztptrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* ap,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_stpttf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const float* ap, float* arf );
+lapack_int LAPACKE_dtpttf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const double* ap, double* arf );
+lapack_int LAPACKE_ctpttf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const lapack_complex_float* ap,
+                                lapack_complex_float* arf );
+lapack_int LAPACKE_ztpttf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const lapack_complex_double* ap,
+                                lapack_complex_double* arf );
+
+lapack_int LAPACKE_stpttr_work( int matrix_order, char uplo, lapack_int n,
+                                const float* ap, float* a, lapack_int lda );
+lapack_int LAPACKE_dtpttr_work( int matrix_order, char uplo, lapack_int n,
+                                const double* ap, double* a, lapack_int lda );
+lapack_int LAPACKE_ctpttr_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* ap,
+                                lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_ztpttr_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* ap,
+                                lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_strcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n, const float* a,
+                                lapack_int lda, float* rcond, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dtrcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n, const double* a,
+                                lapack_int lda, double* rcond, double* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ctrcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                float* rcond, lapack_complex_float* work,
+                                float* rwork );
+lapack_int LAPACKE_ztrcon_work( int matrix_order, char norm, char uplo,
+                                char diag, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                double* rcond, lapack_complex_double* work,
+                                double* rwork );
+
+lapack_int LAPACKE_strevc_work( int matrix_order, char side, char howmny,
+                                lapack_logical* select, lapack_int n,
+                                const float* t, lapack_int ldt, float* vl,
+                                lapack_int ldvl, float* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m, float* work );
+lapack_int LAPACKE_dtrevc_work( int matrix_order, char side, char howmny,
+                                lapack_logical* select, lapack_int n,
+                                const double* t, lapack_int ldt, double* vl,
+                                lapack_int ldvl, double* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m, double* work );
+lapack_int LAPACKE_ctrevc_work( int matrix_order, char side, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                lapack_complex_float* t, lapack_int ldt,
+                                lapack_complex_float* vl, lapack_int ldvl,
+                                lapack_complex_float* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_ztrevc_work( int matrix_order, char side, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                lapack_complex_double* t, lapack_int ldt,
+                                lapack_complex_double* vl, lapack_int ldvl,
+                                lapack_complex_double* vr, lapack_int ldvr,
+                                lapack_int mm, lapack_int* m,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_strexc_work( int matrix_order, char compq, lapack_int n,
+                                float* t, lapack_int ldt, float* q,
+                                lapack_int ldq, lapack_int* ifst,
+                                lapack_int* ilst, float* work );
+lapack_int LAPACKE_dtrexc_work( int matrix_order, char compq, lapack_int n,
+                                double* t, lapack_int ldt, double* q,
+                                lapack_int ldq, lapack_int* ifst,
+                                lapack_int* ilst, double* work );
+lapack_int LAPACKE_ctrexc_work( int matrix_order, char compq, lapack_int n,
+                                lapack_complex_float* t, lapack_int ldt,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_int ifst, lapack_int ilst );
+lapack_int LAPACKE_ztrexc_work( int matrix_order, char compq, lapack_int n,
+                                lapack_complex_double* t, lapack_int ldt,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_int ifst, lapack_int ilst );
+
+lapack_int LAPACKE_strrfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const float* a, lapack_int lda, const float* b,
+                                lapack_int ldb, const float* x, lapack_int ldx,
+                                float* ferr, float* berr, float* work,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dtrrfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const double* a, lapack_int lda,
+                                const double* b, lapack_int ldb,
+                                const double* x, lapack_int ldx, double* ferr,
+                                double* berr, double* work, lapack_int* iwork );
+lapack_int LAPACKE_ctrrfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                const lapack_complex_float* x, lapack_int ldx,
+                                float* ferr, float* berr,
+                                lapack_complex_float* work, float* rwork );
+lapack_int LAPACKE_ztrrfs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                const lapack_complex_double* x, lapack_int ldx,
+                                double* ferr, double* berr,
+                                lapack_complex_double* work, double* rwork );
+
+lapack_int LAPACKE_strsen_work( int matrix_order, char job, char compq,
+                                const lapack_logical* select, lapack_int n,
+                                float* t, lapack_int ldt, float* q,
+                                lapack_int ldq, float* wr, float* wi,
+                                lapack_int* m, float* s, float* sep,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_dtrsen_work( int matrix_order, char job, char compq,
+                                const lapack_logical* select, lapack_int n,
+                                double* t, lapack_int ldt, double* q,
+                                lapack_int ldq, double* wr, double* wi,
+                                lapack_int* m, double* s, double* sep,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork, lapack_int liwork );
+lapack_int LAPACKE_ctrsen_work( int matrix_order, char job, char compq,
+                                const lapack_logical* select, lapack_int n,
+                                lapack_complex_float* t, lapack_int ldt,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_complex_float* w, lapack_int* m,
+                                float* s, float* sep,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_ztrsen_work( int matrix_order, char job, char compq,
+                                const lapack_logical* select, lapack_int n,
+                                lapack_complex_double* t, lapack_int ldt,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_complex_double* w, lapack_int* m,
+                                double* s, double* sep,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_strsna_work( int matrix_order, char job, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const float* t, lapack_int ldt, const float* vl,
+                                lapack_int ldvl, const float* vr,
+                                lapack_int ldvr, float* s, float* sep,
+                                lapack_int mm, lapack_int* m, float* work,
+                                lapack_int ldwork, lapack_int* iwork );
+lapack_int LAPACKE_dtrsna_work( int matrix_order, char job, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const double* t, lapack_int ldt,
+                                const double* vl, lapack_int ldvl,
+                                const double* vr, lapack_int ldvr, double* s,
+                                double* sep, lapack_int mm, lapack_int* m,
+                                double* work, lapack_int ldwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ctrsna_work( int matrix_order, char job, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const lapack_complex_float* t, lapack_int ldt,
+                                const lapack_complex_float* vl, lapack_int ldvl,
+                                const lapack_complex_float* vr, lapack_int ldvr,
+                                float* s, float* sep, lapack_int mm,
+                                lapack_int* m, lapack_complex_float* work,
+                                lapack_int ldwork, float* rwork );
+lapack_int LAPACKE_ztrsna_work( int matrix_order, char job, char howmny,
+                                const lapack_logical* select, lapack_int n,
+                                const lapack_complex_double* t, lapack_int ldt,
+                                const lapack_complex_double* vl,
+                                lapack_int ldvl,
+                                const lapack_complex_double* vr,
+                                lapack_int ldvr, double* s, double* sep,
+                                lapack_int mm, lapack_int* m,
+                                lapack_complex_double* work, lapack_int ldwork,
+                                double* rwork );
+
+lapack_int LAPACKE_strsyl_work( int matrix_order, char trana, char tranb,
+                                lapack_int isgn, lapack_int m, lapack_int n,
+                                const float* a, lapack_int lda, const float* b,
+                                lapack_int ldb, float* c, lapack_int ldc,
+                                float* scale );
+lapack_int LAPACKE_dtrsyl_work( int matrix_order, char trana, char tranb,
+                                lapack_int isgn, lapack_int m, lapack_int n,
+                                const double* a, lapack_int lda,
+                                const double* b, lapack_int ldb, double* c,
+                                lapack_int ldc, double* scale );
+lapack_int LAPACKE_ctrsyl_work( int matrix_order, char trana, char tranb,
+                                lapack_int isgn, lapack_int m, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* b, lapack_int ldb,
+                                lapack_complex_float* c, lapack_int ldc,
+                                float* scale );
+lapack_int LAPACKE_ztrsyl_work( int matrix_order, char trana, char tranb,
+                                lapack_int isgn, lapack_int m, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* c, lapack_int ldc,
+                                double* scale );
+
+lapack_int LAPACKE_strtri_work( int matrix_order, char uplo, char diag,
+                                lapack_int n, float* a, lapack_int lda );
+lapack_int LAPACKE_dtrtri_work( int matrix_order, char uplo, char diag,
+                                lapack_int n, double* a, lapack_int lda );
+lapack_int LAPACKE_ctrtri_work( int matrix_order, char uplo, char diag,
+                                lapack_int n, lapack_complex_float* a,
+                                lapack_int lda );
+lapack_int LAPACKE_ztrtri_work( int matrix_order, char uplo, char diag,
+                                lapack_int n, lapack_complex_double* a,
+                                lapack_int lda );
+
+lapack_int LAPACKE_strtrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const float* a, lapack_int lda, float* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_dtrtrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const double* a, lapack_int lda, double* b,
+                                lapack_int ldb );
+lapack_int LAPACKE_ctrtrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_ztrtrs_work( int matrix_order, char uplo, char trans,
+                                char diag, lapack_int n, lapack_int nrhs,
+                                const lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_strttf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const float* a, lapack_int lda,
+                                float* arf );
+lapack_int LAPACKE_dtrttf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const double* a, lapack_int lda,
+                                double* arf );
+lapack_int LAPACKE_ctrttf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* arf );
+lapack_int LAPACKE_ztrttf_work( int matrix_order, char transr, char uplo,
+                                lapack_int n, const lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* arf );
+
+lapack_int LAPACKE_strttp_work( int matrix_order, char uplo, lapack_int n,
+                                const float* a, lapack_int lda, float* ap );
+lapack_int LAPACKE_dtrttp_work( int matrix_order, char uplo, lapack_int n,
+                                const double* a, lapack_int lda, double* ap );
+lapack_int LAPACKE_ctrttp_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* ap );
+lapack_int LAPACKE_ztrttp_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* ap );
+
+lapack_int LAPACKE_stzrzf_work( int matrix_order, lapack_int m, lapack_int n,
+                                float* a, lapack_int lda, float* tau,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_dtzrzf_work( int matrix_order, lapack_int m, lapack_int n,
+                                double* a, lapack_int lda, double* tau,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_ctzrzf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_ztzrzf_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cungbr_work( int matrix_order, char vect, lapack_int m,
+                                lapack_int n, lapack_int k,
+                                lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zungbr_work( int matrix_order, char vect, lapack_int m,
+                                lapack_int n, lapack_int k,
+                                lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunghr_work( int matrix_order, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunghr_work( int matrix_order, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, lapack_complex_double* a,
+                                lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunglq_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunglq_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, lapack_complex_double* a,
+                                lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cungql_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zungql_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, lapack_complex_double* a,
+                                lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cungqr_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zungqr_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, lapack_complex_double* a,
+                                lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cungrq_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zungrq_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int k, lapack_complex_double* a,
+                                lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cungtr_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zungtr_work( int matrix_order, char uplo, lapack_int n,
+                                lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunmbr_work( int matrix_order, char vect, char side,
+                                char trans, lapack_int m, lapack_int n,
+                                lapack_int k, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunmbr_work( int matrix_order, char vect, char side,
+                                char trans, lapack_int m, lapack_int n,
+                                lapack_int k, const lapack_complex_double* a,
+                                lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunmhr_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunmhr_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int ilo,
+                                lapack_int ihi, const lapack_complex_double* a,
+                                lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunmlq_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunmlq_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunmql_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunmql_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunmqr_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunmqr_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunmrq_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunmrq_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunmrz_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                lapack_int l, const lapack_complex_float* a,
+                                lapack_int lda, const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunmrz_work( int matrix_order, char side, char trans,
+                                lapack_int m, lapack_int n, lapack_int k,
+                                lapack_int l, const lapack_complex_double* a,
+                                lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cunmtr_work( int matrix_order, char side, char uplo,
+                                char trans, lapack_int m, lapack_int n,
+                                const lapack_complex_float* a, lapack_int lda,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_zunmtr_work( int matrix_order, char side, char uplo,
+                                char trans, lapack_int m, lapack_int n,
+                                const lapack_complex_double* a, lapack_int lda,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work, lapack_int lwork );
+
+lapack_int LAPACKE_cupgtr_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_float* ap,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* q, lapack_int ldq,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zupgtr_work( int matrix_order, char uplo, lapack_int n,
+                                const lapack_complex_double* ap,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* q, lapack_int ldq,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_cupmtr_work( int matrix_order, char side, char uplo,
+                                char trans, lapack_int m, lapack_int n,
+                                const lapack_complex_float* ap,
+                                const lapack_complex_float* tau,
+                                lapack_complex_float* c, lapack_int ldc,
+                                lapack_complex_float* work );
+lapack_int LAPACKE_zupmtr_work( int matrix_order, char side, char uplo,
+                                char trans, lapack_int m, lapack_int n,
+                                const lapack_complex_double* ap,
+                                const lapack_complex_double* tau,
+                                lapack_complex_double* c, lapack_int ldc,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_claghe( int matrix_order, lapack_int n, lapack_int k,
+                           const float* d, lapack_complex_float* a,
+                           lapack_int lda, lapack_int* iseed );
+lapack_int LAPACKE_zlaghe( int matrix_order, lapack_int n, lapack_int k,
+                           const double* d, lapack_complex_double* a,
+                           lapack_int lda, lapack_int* iseed );
+
+lapack_int LAPACKE_slagsy( int matrix_order, lapack_int n, lapack_int k,
+                           const float* d, float* a, lapack_int lda,
+                           lapack_int* iseed );
+lapack_int LAPACKE_dlagsy( int matrix_order, lapack_int n, lapack_int k,
+                           const double* d, double* a, lapack_int lda,
+                           lapack_int* iseed );
+lapack_int LAPACKE_clagsy( int matrix_order, lapack_int n, lapack_int k,
+                           const float* d, lapack_complex_float* a,
+                           lapack_int lda, lapack_int* iseed );
+lapack_int LAPACKE_zlagsy( int matrix_order, lapack_int n, lapack_int k,
+                           const double* d, lapack_complex_double* a,
+                           lapack_int lda, lapack_int* iseed );
+
+lapack_int LAPACKE_slapmr( int matrix_order, lapack_logical forwrd,
+                           lapack_int m, lapack_int n, float* x, lapack_int ldx,
+                           lapack_int* k );
+lapack_int LAPACKE_dlapmr( int matrix_order, lapack_logical forwrd,
+                           lapack_int m, lapack_int n, double* x,
+                           lapack_int ldx, lapack_int* k );
+lapack_int LAPACKE_clapmr( int matrix_order, lapack_logical forwrd,
+                           lapack_int m, lapack_int n, lapack_complex_float* x,
+                           lapack_int ldx, lapack_int* k );
+lapack_int LAPACKE_zlapmr( int matrix_order, lapack_logical forwrd,
+                           lapack_int m, lapack_int n, lapack_complex_double* x,
+                           lapack_int ldx, lapack_int* k );
+
+
+float LAPACKE_slapy2( float x, float y );
+double LAPACKE_dlapy2( double x, double y );
+
+float LAPACKE_slapy3( float x, float y, float z );
+double LAPACKE_dlapy3( double x, double y, double z );
+
+lapack_int LAPACKE_slartgp( float f, float g, float* cs, float* sn, float* r );
+lapack_int LAPACKE_dlartgp( double f, double g, double* cs, double* sn,
+                            double* r );
+
+lapack_int LAPACKE_slartgs( float x, float y, float sigma, float* cs,
+                            float* sn );
+lapack_int LAPACKE_dlartgs( double x, double y, double sigma, double* cs,
+                            double* sn );
+
+
+//LAPACK 3.3.0
+lapack_int LAPACKE_cbbcsd( int matrix_order, char jobu1, char jobu2,
+                           char jobv1t, char jobv2t, char trans, lapack_int m,
+                           lapack_int p, lapack_int q, float* theta, float* phi,
+                           lapack_complex_float* u1, lapack_int ldu1,
+                           lapack_complex_float* u2, lapack_int ldu2,
+                           lapack_complex_float* v1t, lapack_int ldv1t,
+                           lapack_complex_float* v2t, lapack_int ldv2t,
+                           float* b11d, float* b11e, float* b12d, float* b12e,
+                           float* b21d, float* b21e, float* b22d, float* b22e );
+lapack_int LAPACKE_cbbcsd_work( int matrix_order, char jobu1, char jobu2,
+                                char jobv1t, char jobv2t, char trans,
+                                lapack_int m, lapack_int p, lapack_int q,
+                                float* theta, float* phi,
+                                lapack_complex_float* u1, lapack_int ldu1,
+                                lapack_complex_float* u2, lapack_int ldu2,
+                                lapack_complex_float* v1t, lapack_int ldv1t,
+                                lapack_complex_float* v2t, lapack_int ldv2t,
+                                float* b11d, float* b11e, float* b12d,
+                                float* b12e, float* b21d, float* b21e,
+                                float* b22d, float* b22e, float* rwork,
+                                lapack_int lrwork );
+lapack_int LAPACKE_cheswapr( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_float* a, lapack_int i1,
+                             lapack_int i2 );
+lapack_int LAPACKE_cheswapr_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_float* a, lapack_int i1,
+                                  lapack_int i2 );
+lapack_int LAPACKE_chetri2( int matrix_order, char uplo, lapack_int n,
+                            lapack_complex_float* a, lapack_int lda,
+                            const lapack_int* ipiv );
+lapack_int LAPACKE_chetri2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 const lapack_int* ipiv,
+                                 lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_chetri2x( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_float* a, lapack_int lda,
+                             const lapack_int* ipiv, lapack_int nb );
+lapack_int LAPACKE_chetri2x_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_float* a, lapack_int lda,
+                                  const lapack_int* ipiv,
+                                  lapack_complex_float* work, lapack_int nb );
+lapack_int LAPACKE_chetrs2( int matrix_order, char uplo, lapack_int n,
+                            lapack_int nrhs, const lapack_complex_float* a,
+                            lapack_int lda, const lapack_int* ipiv,
+                            lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_chetrs2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_int nrhs, const lapack_complex_float* a,
+                                 lapack_int lda, const lapack_int* ipiv,
+                                 lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* work );
+lapack_int LAPACKE_csyconv( int matrix_order, char uplo, char way, lapack_int n,
+                            lapack_complex_float* a, lapack_int lda,
+                            const lapack_int* ipiv );
+lapack_int LAPACKE_csyconv_work( int matrix_order, char uplo, char way,
+                                 lapack_int n, lapack_complex_float* a,
+                                 lapack_int lda, const lapack_int* ipiv,
+                                 lapack_complex_float* work );
+lapack_int LAPACKE_csyswapr( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_float* a, lapack_int i1,
+                             lapack_int i2 );
+lapack_int LAPACKE_csyswapr_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_float* a, lapack_int i1,
+                                  lapack_int i2 );
+lapack_int LAPACKE_csytri2( int matrix_order, char uplo, lapack_int n,
+                            lapack_complex_float* a, lapack_int lda,
+                            const lapack_int* ipiv );
+lapack_int LAPACKE_csytri2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 const lapack_int* ipiv,
+                                 lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_csytri2x( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_float* a, lapack_int lda,
+                             const lapack_int* ipiv, lapack_int nb );
+lapack_int LAPACKE_csytri2x_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_float* a, lapack_int lda,
+                                  const lapack_int* ipiv,
+                                  lapack_complex_float* work, lapack_int nb );
+lapack_int LAPACKE_csytrs2( int matrix_order, char uplo, lapack_int n,
+                            lapack_int nrhs, const lapack_complex_float* a,
+                            lapack_int lda, const lapack_int* ipiv,
+                            lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_csytrs2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_int nrhs, const lapack_complex_float* a,
+                                 lapack_int lda, const lapack_int* ipiv,
+                                 lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* work );
+lapack_int LAPACKE_cunbdb( int matrix_order, char trans, char signs,
+                           lapack_int m, lapack_int p, lapack_int q,
+                           lapack_complex_float* x11, lapack_int ldx11,
+                           lapack_complex_float* x12, lapack_int ldx12,
+                           lapack_complex_float* x21, lapack_int ldx21,
+                           lapack_complex_float* x22, lapack_int ldx22,
+                           float* theta, float* phi,
+                           lapack_complex_float* taup1,
+                           lapack_complex_float* taup2,
+                           lapack_complex_float* tauq1,
+                           lapack_complex_float* tauq2 );
+lapack_int LAPACKE_cunbdb_work( int matrix_order, char trans, char signs,
+                                lapack_int m, lapack_int p, lapack_int q,
+                                lapack_complex_float* x11, lapack_int ldx11,
+                                lapack_complex_float* x12, lapack_int ldx12,
+                                lapack_complex_float* x21, lapack_int ldx21,
+                                lapack_complex_float* x22, lapack_int ldx22,
+                                float* theta, float* phi,
+                                lapack_complex_float* taup1,
+                                lapack_complex_float* taup2,
+                                lapack_complex_float* tauq1,
+                                lapack_complex_float* tauq2,
+                                lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_cuncsd( int matrix_order, char jobu1, char jobu2,
+                           char jobv1t, char jobv2t, char trans, char signs,
+                           lapack_int m, lapack_int p, lapack_int q,
+                           lapack_complex_float* x11, lapack_int ldx11,
+                           lapack_complex_float* x12, lapack_int ldx12,
+                           lapack_complex_float* x21, lapack_int ldx21,
+                           lapack_complex_float* x22, lapack_int ldx22,
+                           float* theta, lapack_complex_float* u1,
+                           lapack_int ldu1, lapack_complex_float* u2,
+                           lapack_int ldu2, lapack_complex_float* v1t,
+                           lapack_int ldv1t, lapack_complex_float* v2t,
+                           lapack_int ldv2t );
+lapack_int LAPACKE_cuncsd_work( int matrix_order, char jobu1, char jobu2,
+                                char jobv1t, char jobv2t, char trans,
+                                char signs, lapack_int m, lapack_int p,
+                                lapack_int q, lapack_complex_float* x11,
+                                lapack_int ldx11, lapack_complex_float* x12,
+                                lapack_int ldx12, lapack_complex_float* x21,
+                                lapack_int ldx21, lapack_complex_float* x22,
+                                lapack_int ldx22, float* theta,
+                                lapack_complex_float* u1, lapack_int ldu1,
+                                lapack_complex_float* u2, lapack_int ldu2,
+                                lapack_complex_float* v1t, lapack_int ldv1t,
+                                lapack_complex_float* v2t, lapack_int ldv2t,
+                                lapack_complex_float* work, lapack_int lwork,
+                                float* rwork, lapack_int lrwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dbbcsd( int matrix_order, char jobu1, char jobu2,
+                           char jobv1t, char jobv2t, char trans, lapack_int m,
+                           lapack_int p, lapack_int q, double* theta,
+                           double* phi, double* u1, lapack_int ldu1, double* u2,
+                           lapack_int ldu2, double* v1t, lapack_int ldv1t,
+                           double* v2t, lapack_int ldv2t, double* b11d,
+                           double* b11e, double* b12d, double* b12e,
+                           double* b21d, double* b21e, double* b22d,
+                           double* b22e );
+lapack_int LAPACKE_dbbcsd_work( int matrix_order, char jobu1, char jobu2,
+                                char jobv1t, char jobv2t, char trans,
+                                lapack_int m, lapack_int p, lapack_int q,
+                                double* theta, double* phi, double* u1,
+                                lapack_int ldu1, double* u2, lapack_int ldu2,
+                                double* v1t, lapack_int ldv1t, double* v2t,
+                                lapack_int ldv2t, double* b11d, double* b11e,
+                                double* b12d, double* b12e, double* b21d,
+                                double* b21e, double* b22d, double* b22e,
+                                double* work, lapack_int lwork );
+lapack_int LAPACKE_dorbdb( int matrix_order, char trans, char signs,
+                           lapack_int m, lapack_int p, lapack_int q,
+                           double* x11, lapack_int ldx11, double* x12,
+                           lapack_int ldx12, double* x21, lapack_int ldx21,
+                           double* x22, lapack_int ldx22, double* theta,
+                           double* phi, double* taup1, double* taup2,
+                           double* tauq1, double* tauq2 );
+lapack_int LAPACKE_dorbdb_work( int matrix_order, char trans, char signs,
+                                lapack_int m, lapack_int p, lapack_int q,
+                                double* x11, lapack_int ldx11, double* x12,
+                                lapack_int ldx12, double* x21, lapack_int ldx21,
+                                double* x22, lapack_int ldx22, double* theta,
+                                double* phi, double* taup1, double* taup2,
+                                double* tauq1, double* tauq2, double* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_dorcsd( int matrix_order, char jobu1, char jobu2,
+                           char jobv1t, char jobv2t, char trans, char signs,
+                           lapack_int m, lapack_int p, lapack_int q,
+                           double* x11, lapack_int ldx11, double* x12,
+                           lapack_int ldx12, double* x21, lapack_int ldx21,
+                           double* x22, lapack_int ldx22, double* theta,
+                           double* u1, lapack_int ldu1, double* u2,
+                           lapack_int ldu2, double* v1t, lapack_int ldv1t,
+                           double* v2t, lapack_int ldv2t );
+lapack_int LAPACKE_dorcsd_work( int matrix_order, char jobu1, char jobu2,
+                                char jobv1t, char jobv2t, char trans,
+                                char signs, lapack_int m, lapack_int p,
+                                lapack_int q, double* x11, lapack_int ldx11,
+                                double* x12, lapack_int ldx12, double* x21,
+                                lapack_int ldx21, double* x22, lapack_int ldx22,
+                                double* theta, double* u1, lapack_int ldu1,
+                                double* u2, lapack_int ldu2, double* v1t,
+                                lapack_int ldv1t, double* v2t, lapack_int ldv2t,
+                                double* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_dsyconv( int matrix_order, char uplo, char way, lapack_int n,
+                            double* a, lapack_int lda, const lapack_int* ipiv );
+lapack_int LAPACKE_dsyconv_work( int matrix_order, char uplo, char way,
+                                 lapack_int n, double* a, lapack_int lda,
+                                 const lapack_int* ipiv, double* work );
+lapack_int LAPACKE_dsyswapr( int matrix_order, char uplo, lapack_int n,
+                             double* a, lapack_int i1, lapack_int i2 );
+lapack_int LAPACKE_dsyswapr_work( int matrix_order, char uplo, lapack_int n,
+                                  double* a, lapack_int i1, lapack_int i2 );
+lapack_int LAPACKE_dsytri2( int matrix_order, char uplo, lapack_int n,
+                            double* a, lapack_int lda, const lapack_int* ipiv );
+lapack_int LAPACKE_dsytri2_work( int matrix_order, char uplo, lapack_int n,
+                                 double* a, lapack_int lda,
+                                 const lapack_int* ipiv,
+                                 lapack_complex_double* work, lapack_int lwork );
+lapack_int LAPACKE_dsytri2x( int matrix_order, char uplo, lapack_int n,
+                             double* a, lapack_int lda, const lapack_int* ipiv,
+                             lapack_int nb );
+lapack_int LAPACKE_dsytri2x_work( int matrix_order, char uplo, lapack_int n,
+                                  double* a, lapack_int lda,
+                                  const lapack_int* ipiv, double* work,
+                                  lapack_int nb );
+lapack_int LAPACKE_dsytrs2( int matrix_order, char uplo, lapack_int n,
+                            lapack_int nrhs, const double* a, lapack_int lda,
+                            const lapack_int* ipiv, double* b, lapack_int ldb );
+lapack_int LAPACKE_dsytrs2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_int nrhs, const double* a,
+                                 lapack_int lda, const lapack_int* ipiv,
+                                 double* b, lapack_int ldb, double* work );
+lapack_int LAPACKE_sbbcsd( int matrix_order, char jobu1, char jobu2,
+                           char jobv1t, char jobv2t, char trans, lapack_int m,
+                           lapack_int p, lapack_int q, float* theta, float* phi,
+                           float* u1, lapack_int ldu1, float* u2,
+                           lapack_int ldu2, float* v1t, lapack_int ldv1t,
+                           float* v2t, lapack_int ldv2t, float* b11d,
+                           float* b11e, float* b12d, float* b12e, float* b21d,
+                           float* b21e, float* b22d, float* b22e );
+lapack_int LAPACKE_sbbcsd_work( int matrix_order, char jobu1, char jobu2,
+                                char jobv1t, char jobv2t, char trans,
+                                lapack_int m, lapack_int p, lapack_int q,
+                                float* theta, float* phi, float* u1,
+                                lapack_int ldu1, float* u2, lapack_int ldu2,
+                                float* v1t, lapack_int ldv1t, float* v2t,
+                                lapack_int ldv2t, float* b11d, float* b11e,
+                                float* b12d, float* b12e, float* b21d,
+                                float* b21e, float* b22d, float* b22e,
+                                float* work, lapack_int lwork );
+lapack_int LAPACKE_sorbdb( int matrix_order, char trans, char signs,
+                           lapack_int m, lapack_int p, lapack_int q, float* x11,
+                           lapack_int ldx11, float* x12, lapack_int ldx12,
+                           float* x21, lapack_int ldx21, float* x22,
+                           lapack_int ldx22, float* theta, float* phi,
+                           float* taup1, float* taup2, float* tauq1,
+                           float* tauq2 );
+lapack_int LAPACKE_sorbdb_work( int matrix_order, char trans, char signs,
+                                lapack_int m, lapack_int p, lapack_int q,
+                                float* x11, lapack_int ldx11, float* x12,
+                                lapack_int ldx12, float* x21, lapack_int ldx21,
+                                float* x22, lapack_int ldx22, float* theta,
+                                float* phi, float* taup1, float* taup2,
+                                float* tauq1, float* tauq2, float* work,
+                                lapack_int lwork );
+lapack_int LAPACKE_sorcsd( int matrix_order, char jobu1, char jobu2,
+                           char jobv1t, char jobv2t, char trans, char signs,
+                           lapack_int m, lapack_int p, lapack_int q, float* x11,
+                           lapack_int ldx11, float* x12, lapack_int ldx12,
+                           float* x21, lapack_int ldx21, float* x22,
+                           lapack_int ldx22, float* theta, float* u1,
+                           lapack_int ldu1, float* u2, lapack_int ldu2,
+                           float* v1t, lapack_int ldv1t, float* v2t,
+                           lapack_int ldv2t );
+lapack_int LAPACKE_sorcsd_work( int matrix_order, char jobu1, char jobu2,
+                                char jobv1t, char jobv2t, char trans,
+                                char signs, lapack_int m, lapack_int p,
+                                lapack_int q, float* x11, lapack_int ldx11,
+                                float* x12, lapack_int ldx12, float* x21,
+                                lapack_int ldx21, float* x22, lapack_int ldx22,
+                                float* theta, float* u1, lapack_int ldu1,
+                                float* u2, lapack_int ldu2, float* v1t,
+                                lapack_int ldv1t, float* v2t, lapack_int ldv2t,
+                                float* work, lapack_int lwork,
+                                lapack_int* iwork );
+lapack_int LAPACKE_ssyconv( int matrix_order, char uplo, char way, lapack_int n,
+                            float* a, lapack_int lda, const lapack_int* ipiv );
+lapack_int LAPACKE_ssyconv_work( int matrix_order, char uplo, char way,
+                                 lapack_int n, float* a, lapack_int lda,
+                                 const lapack_int* ipiv, float* work );
+lapack_int LAPACKE_ssyswapr( int matrix_order, char uplo, lapack_int n,
+                             float* a, lapack_int i1, lapack_int i2 );
+lapack_int LAPACKE_ssyswapr_work( int matrix_order, char uplo, lapack_int n,
+                                  float* a, lapack_int i1, lapack_int i2 );
+lapack_int LAPACKE_ssytri2( int matrix_order, char uplo, lapack_int n, float* a,
+                            lapack_int lda, const lapack_int* ipiv );
+lapack_int LAPACKE_ssytri2_work( int matrix_order, char uplo, lapack_int n,
+                                 float* a, lapack_int lda,
+                                 const lapack_int* ipiv,
+                                 lapack_complex_float* work, lapack_int lwork );
+lapack_int LAPACKE_ssytri2x( int matrix_order, char uplo, lapack_int n,
+                             float* a, lapack_int lda, const lapack_int* ipiv,
+                             lapack_int nb );
+lapack_int LAPACKE_ssytri2x_work( int matrix_order, char uplo, lapack_int n,
+                                  float* a, lapack_int lda,
+                                  const lapack_int* ipiv, float* work,
+                                  lapack_int nb );
+lapack_int LAPACKE_ssytrs2( int matrix_order, char uplo, lapack_int n,
+                            lapack_int nrhs, const float* a, lapack_int lda,
+                            const lapack_int* ipiv, float* b, lapack_int ldb );
+lapack_int LAPACKE_ssytrs2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_int nrhs, const float* a,
+                                 lapack_int lda, const lapack_int* ipiv,
+                                 float* b, lapack_int ldb, float* work );
+lapack_int LAPACKE_zbbcsd( int matrix_order, char jobu1, char jobu2,
+                           char jobv1t, char jobv2t, char trans, lapack_int m,
+                           lapack_int p, lapack_int q, double* theta,
+                           double* phi, lapack_complex_double* u1,
+                           lapack_int ldu1, lapack_complex_double* u2,
+                           lapack_int ldu2, lapack_complex_double* v1t,
+                           lapack_int ldv1t, lapack_complex_double* v2t,
+                           lapack_int ldv2t, double* b11d, double* b11e,
+                           double* b12d, double* b12e, double* b21d,
+                           double* b21e, double* b22d, double* b22e );
+lapack_int LAPACKE_zbbcsd_work( int matrix_order, char jobu1, char jobu2,
+                                char jobv1t, char jobv2t, char trans,
+                                lapack_int m, lapack_int p, lapack_int q,
+                                double* theta, double* phi,
+                                lapack_complex_double* u1, lapack_int ldu1,
+                                lapack_complex_double* u2, lapack_int ldu2,
+                                lapack_complex_double* v1t, lapack_int ldv1t,
+                                lapack_complex_double* v2t, lapack_int ldv2t,
+                                double* b11d, double* b11e, double* b12d,
+                                double* b12e, double* b21d, double* b21e,
+                                double* b22d, double* b22e, double* rwork,
+                                lapack_int lrwork );
+lapack_int LAPACKE_zheswapr( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_double* a, lapack_int i1,
+                             lapack_int i2 );
+lapack_int LAPACKE_zheswapr_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_double* a, lapack_int i1,
+                                  lapack_int i2 );
+lapack_int LAPACKE_zhetri2( int matrix_order, char uplo, lapack_int n,
+                            lapack_complex_double* a, lapack_int lda,
+                            const lapack_int* ipiv );
+lapack_int LAPACKE_zhetri2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 const lapack_int* ipiv,
+                                 lapack_complex_double* work, lapack_int lwork );
+lapack_int LAPACKE_zhetri2x( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_double* a, lapack_int lda,
+                             const lapack_int* ipiv, lapack_int nb );
+lapack_int LAPACKE_zhetri2x_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_double* a, lapack_int lda,
+                                  const lapack_int* ipiv,
+                                  lapack_complex_double* work, lapack_int nb );
+lapack_int LAPACKE_zhetrs2( int matrix_order, char uplo, lapack_int n,
+                            lapack_int nrhs, const lapack_complex_double* a,
+                            lapack_int lda, const lapack_int* ipiv,
+                            lapack_complex_double* b, lapack_int ldb );
+lapack_int LAPACKE_zhetrs2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_int nrhs, const lapack_complex_double* a,
+                                 lapack_int lda, const lapack_int* ipiv,
+                                 lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* work );
+lapack_int LAPACKE_zsyconv( int matrix_order, char uplo, char way, lapack_int n,
+                            lapack_complex_double* a, lapack_int lda,
+                            const lapack_int* ipiv );
+lapack_int LAPACKE_zsyconv_work( int matrix_order, char uplo, char way,
+                                 lapack_int n, lapack_complex_double* a,
+                                 lapack_int lda, const lapack_int* ipiv,
+                                 lapack_complex_double* work );
+lapack_int LAPACKE_zsyswapr( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_double* a, lapack_int i1,
+                             lapack_int i2 );
+lapack_int LAPACKE_zsyswapr_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_double* a, lapack_int i1,
+                                  lapack_int i2 );
+lapack_int LAPACKE_zsytri2( int matrix_order, char uplo, lapack_int n,
+                            lapack_complex_double* a, lapack_int lda,
+                            const lapack_int* ipiv );
+lapack_int LAPACKE_zsytri2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 const lapack_int* ipiv,
+                                 lapack_complex_double* work, lapack_int lwork );
+lapack_int LAPACKE_zsytri2x( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_double* a, lapack_int lda,
+                             const lapack_int* ipiv, lapack_int nb );
+lapack_int LAPACKE_zsytri2x_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_double* a, lapack_int lda,
+                                  const lapack_int* ipiv,
+                                  lapack_complex_double* work, lapack_int nb );
+lapack_int LAPACKE_zsytrs2( int matrix_order, char uplo, lapack_int n,
+                            lapack_int nrhs, const lapack_complex_double* a,
+                            lapack_int lda, const lapack_int* ipiv,
+                            lapack_complex_double* b, lapack_int ldb );
+lapack_int LAPACKE_zsytrs2_work( int matrix_order, char uplo, lapack_int n,
+                                 lapack_int nrhs, const lapack_complex_double* a,
+                                 lapack_int lda, const lapack_int* ipiv,
+                                 lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* work );
+lapack_int LAPACKE_zunbdb( int matrix_order, char trans, char signs,
+                           lapack_int m, lapack_int p, lapack_int q,
+                           lapack_complex_double* x11, lapack_int ldx11,
+                           lapack_complex_double* x12, lapack_int ldx12,
+                           lapack_complex_double* x21, lapack_int ldx21,
+                           lapack_complex_double* x22, lapack_int ldx22,
+                           double* theta, double* phi,
+                           lapack_complex_double* taup1,
+                           lapack_complex_double* taup2,
+                           lapack_complex_double* tauq1,
+                           lapack_complex_double* tauq2 );
+lapack_int LAPACKE_zunbdb_work( int matrix_order, char trans, char signs,
+                                lapack_int m, lapack_int p, lapack_int q,
+                                lapack_complex_double* x11, lapack_int ldx11,
+                                lapack_complex_double* x12, lapack_int ldx12,
+                                lapack_complex_double* x21, lapack_int ldx21,
+                                lapack_complex_double* x22, lapack_int ldx22,
+                                double* theta, double* phi,
+                                lapack_complex_double* taup1,
+                                lapack_complex_double* taup2,
+                                lapack_complex_double* tauq1,
+                                lapack_complex_double* tauq2,
+                                lapack_complex_double* work, lapack_int lwork );
+lapack_int LAPACKE_zuncsd( int matrix_order, char jobu1, char jobu2,
+                           char jobv1t, char jobv2t, char trans, char signs,
+                           lapack_int m, lapack_int p, lapack_int q,
+                           lapack_complex_double* x11, lapack_int ldx11,
+                           lapack_complex_double* x12, lapack_int ldx12,
+                           lapack_complex_double* x21, lapack_int ldx21,
+                           lapack_complex_double* x22, lapack_int ldx22,
+                           double* theta, lapack_complex_double* u1,
+                           lapack_int ldu1, lapack_complex_double* u2,
+                           lapack_int ldu2, lapack_complex_double* v1t,
+                           lapack_int ldv1t, lapack_complex_double* v2t,
+                           lapack_int ldv2t );
+lapack_int LAPACKE_zuncsd_work( int matrix_order, char jobu1, char jobu2,
+                                char jobv1t, char jobv2t, char trans,
+                                char signs, lapack_int m, lapack_int p,
+                                lapack_int q, lapack_complex_double* x11,
+                                lapack_int ldx11, lapack_complex_double* x12,
+                                lapack_int ldx12, lapack_complex_double* x21,
+                                lapack_int ldx21, lapack_complex_double* x22,
+                                lapack_int ldx22, double* theta,
+                                lapack_complex_double* u1, lapack_int ldu1,
+                                lapack_complex_double* u2, lapack_int ldu2,
+                                lapack_complex_double* v1t, lapack_int ldv1t,
+                                lapack_complex_double* v2t, lapack_int ldv2t,
+                                lapack_complex_double* work, lapack_int lwork,
+                                double* rwork, lapack_int lrwork,
+                                lapack_int* iwork );
+//LAPACK 3.4.0
+lapack_int LAPACKE_sgemqrt( int matrix_order, char side, char trans,
+                            lapack_int m, lapack_int n, lapack_int k,
+                            lapack_int nb, const float* v, lapack_int ldv,
+                            const float* t, lapack_int ldt, float* c,
+                            lapack_int ldc );
+lapack_int LAPACKE_dgemqrt( int matrix_order, char side, char trans,
+                            lapack_int m, lapack_int n, lapack_int k,
+                            lapack_int nb, const double* v, lapack_int ldv,
+                            const double* t, lapack_int ldt, double* c,
+                            lapack_int ldc );
+lapack_int LAPACKE_cgemqrt( int matrix_order, char side, char trans,
+                            lapack_int m, lapack_int n, lapack_int k,
+                            lapack_int nb, const lapack_complex_float* v,
+                            lapack_int ldv, const lapack_complex_float* t,
+                            lapack_int ldt, lapack_complex_float* c,
+                            lapack_int ldc );
+lapack_int LAPACKE_zgemqrt( int matrix_order, char side, char trans,
+                            lapack_int m, lapack_int n, lapack_int k,
+                            lapack_int nb, const lapack_complex_double* v,
+                            lapack_int ldv, const lapack_complex_double* t,
+                            lapack_int ldt, lapack_complex_double* c,
+                            lapack_int ldc );
+
+lapack_int LAPACKE_sgeqrt( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nb, float* a, lapack_int lda, float* t,
+                           lapack_int ldt );
+lapack_int LAPACKE_dgeqrt( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nb, double* a, lapack_int lda, double* t,
+                           lapack_int ldt );
+lapack_int LAPACKE_cgeqrt( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nb, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* t,
+                           lapack_int ldt );
+lapack_int LAPACKE_zgeqrt( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int nb, lapack_complex_double* a,
+                           lapack_int lda, lapack_complex_double* t,
+                           lapack_int ldt );
+
+lapack_int LAPACKE_sgeqrt2( int matrix_order, lapack_int m, lapack_int n,
+                            float* a, lapack_int lda, float* t,
+                            lapack_int ldt );
+lapack_int LAPACKE_dgeqrt2( int matrix_order, lapack_int m, lapack_int n,
+                            double* a, lapack_int lda, double* t,
+                            lapack_int ldt );
+lapack_int LAPACKE_cgeqrt2( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* t, lapack_int ldt );
+lapack_int LAPACKE_zgeqrt2( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_sgeqrt3( int matrix_order, lapack_int m, lapack_int n,
+                            float* a, lapack_int lda, float* t,
+                            lapack_int ldt );
+lapack_int LAPACKE_dgeqrt3( int matrix_order, lapack_int m, lapack_int n,
+                            double* a, lapack_int lda, double* t,
+                            lapack_int ldt );
+lapack_int LAPACKE_cgeqrt3( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* t, lapack_int ldt );
+lapack_int LAPACKE_zgeqrt3( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_stpmqrt( int matrix_order, char side, char trans,
+                            lapack_int m, lapack_int n, lapack_int k,
+                            lapack_int l, lapack_int nb, const float* v,
+                            lapack_int ldv, const float* t, lapack_int ldt,
+                            float* a, lapack_int lda, float* b,
+                            lapack_int ldb );
+lapack_int LAPACKE_dtpmqrt( int matrix_order, char side, char trans,
+                            lapack_int m, lapack_int n, lapack_int k,
+                            lapack_int l, lapack_int nb, const double* v,
+                            lapack_int ldv, const double* t, lapack_int ldt,
+                            double* a, lapack_int lda, double* b,
+                            lapack_int ldb );
+lapack_int LAPACKE_ctpmqrt( int matrix_order, char side, char trans,
+                            lapack_int m, lapack_int n, lapack_int k,
+                            lapack_int l, lapack_int nb,
+                            const lapack_complex_float* v, lapack_int ldv,
+                            const lapack_complex_float* t, lapack_int ldt,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* b, lapack_int ldb );
+lapack_int LAPACKE_ztpmqrt( int matrix_order, char side, char trans,
+                            lapack_int m, lapack_int n, lapack_int k,
+                            lapack_int l, lapack_int nb,
+                            const lapack_complex_double* v, lapack_int ldv,
+                            const lapack_complex_double* t, lapack_int ldt,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* b, lapack_int ldb );
+
+lapack_int LAPACKE_dtpqrt( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int l, lapack_int nb, double* a,
+                           lapack_int lda, double* b, lapack_int ldb, double* t,
+                           lapack_int ldt );
+lapack_int LAPACKE_ctpqrt( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int l, lapack_int nb, lapack_complex_float* a,
+                           lapack_int lda, lapack_complex_float* t,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_int ldt );
+lapack_int LAPACKE_ztpqrt( int matrix_order, lapack_int m, lapack_int n,
+                           lapack_int l, lapack_int nb,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_stpqrt2( int matrix_order, lapack_int m, lapack_int n,
+                            float* a, lapack_int lda, float* b, lapack_int ldb,
+                            float* t, lapack_int ldt );
+lapack_int LAPACKE_dtpqrt2( int matrix_order, lapack_int m, lapack_int n,
+                            double* a, lapack_int lda, double* b,
+                            lapack_int ldb, double* t, lapack_int ldt );
+lapack_int LAPACKE_ctpqrt2( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_complex_float* a, lapack_int lda,
+                            lapack_complex_float* b, lapack_int ldb,
+                            lapack_complex_float* t, lapack_int ldt );
+lapack_int LAPACKE_ztpqrt2( int matrix_order, lapack_int m, lapack_int n,
+                            lapack_complex_double* a, lapack_int lda,
+                            lapack_complex_double* b, lapack_int ldb,
+                            lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_stprfb( int matrix_order, char side, char trans, char direct,
+                           char storev, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_int l, const float* v,
+                           lapack_int ldv, const float* t, lapack_int ldt,
+                           float* a, lapack_int lda, float* b, lapack_int ldb,
+                           lapack_int myldwork );
+lapack_int LAPACKE_dtprfb( int matrix_order, char side, char trans, char direct,
+                           char storev, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_int l, const double* v,
+                           lapack_int ldv, const double* t, lapack_int ldt,
+                           double* a, lapack_int lda, double* b, lapack_int ldb,
+                           lapack_int myldwork );
+lapack_int LAPACKE_ctprfb( int matrix_order, char side, char trans, char direct,
+                           char storev, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_int l,
+                           const lapack_complex_float* v, lapack_int ldv,
+                           const lapack_complex_float* t, lapack_int ldt,
+                           lapack_complex_float* a, lapack_int lda,
+                           lapack_complex_float* b, lapack_int ldb,
+                           lapack_int myldwork );
+lapack_int LAPACKE_ztprfb( int matrix_order, char side, char trans, char direct,
+                           char storev, lapack_int m, lapack_int n,
+                           lapack_int k, lapack_int l,
+                           const lapack_complex_double* v, lapack_int ldv,
+                           const lapack_complex_double* t, lapack_int ldt,
+                           lapack_complex_double* a, lapack_int lda,
+                           lapack_complex_double* b, lapack_int ldb,
+                           lapack_int myldwork );
+
+lapack_int LAPACKE_sgemqrt_work( int matrix_order, char side, char trans,
+                                 lapack_int m, lapack_int n, lapack_int k,
+                                 lapack_int nb, const float* v, lapack_int ldv,
+                                 const float* t, lapack_int ldt, float* c,
+                                 lapack_int ldc, float* work );
+lapack_int LAPACKE_dgemqrt_work( int matrix_order, char side, char trans,
+                                 lapack_int m, lapack_int n, lapack_int k,
+                                 lapack_int nb, const double* v, lapack_int ldv,
+                                 const double* t, lapack_int ldt, double* c,
+                                 lapack_int ldc, double* work );
+lapack_int LAPACKE_cgemqrt_work( int matrix_order, char side, char trans,
+                                 lapack_int m, lapack_int n, lapack_int k,
+                                 lapack_int nb, const lapack_complex_float* v,
+                                 lapack_int ldv, const lapack_complex_float* t,
+                                 lapack_int ldt, lapack_complex_float* c,
+                                 lapack_int ldc, lapack_complex_float* work );
+lapack_int LAPACKE_zgemqrt_work( int matrix_order, char side, char trans,
+                                 lapack_int m, lapack_int n, lapack_int k,
+                                 lapack_int nb, const lapack_complex_double* v,
+                                 lapack_int ldv, const lapack_complex_double* t,
+                                 lapack_int ldt, lapack_complex_double* c,
+                                 lapack_int ldc, lapack_complex_double* work );
+
+lapack_int LAPACKE_sgeqrt_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nb, float* a, lapack_int lda,
+                                float* t, lapack_int ldt, float* work );
+lapack_int LAPACKE_dgeqrt_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nb, double* a, lapack_int lda,
+                                double* t, lapack_int ldt, double* work );
+lapack_int LAPACKE_cgeqrt_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nb, lapack_complex_float* a,
+                                lapack_int lda, lapack_complex_float* t,
+                                lapack_int ldt, lapack_complex_float* work );
+lapack_int LAPACKE_zgeqrt_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int nb, lapack_complex_double* a,
+                                lapack_int lda, lapack_complex_double* t,
+                                lapack_int ldt, lapack_complex_double* work );
+
+lapack_int LAPACKE_sgeqrt2_work( int matrix_order, lapack_int m, lapack_int n,
+                                 float* a, lapack_int lda, float* t,
+                                 lapack_int ldt );
+lapack_int LAPACKE_dgeqrt2_work( int matrix_order, lapack_int m, lapack_int n,
+                                 double* a, lapack_int lda, double* t,
+                                 lapack_int ldt );
+lapack_int LAPACKE_cgeqrt2_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* t, lapack_int ldt );
+lapack_int LAPACKE_zgeqrt2_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_sgeqrt3_work( int matrix_order, lapack_int m, lapack_int n,
+                                 float* a, lapack_int lda, float* t,
+                                 lapack_int ldt );
+lapack_int LAPACKE_dgeqrt3_work( int matrix_order, lapack_int m, lapack_int n,
+                                 double* a, lapack_int lda, double* t,
+                                 lapack_int ldt );
+lapack_int LAPACKE_cgeqrt3_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* t, lapack_int ldt );
+lapack_int LAPACKE_zgeqrt3_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_stpmqrt_work( int matrix_order, char side, char trans,
+                                 lapack_int m, lapack_int n, lapack_int k,
+                                 lapack_int l, lapack_int nb, const float* v,
+                                 lapack_int ldv, const float* t, lapack_int ldt,
+                                 float* a, lapack_int lda, float* b,
+                                 lapack_int ldb, float* work );
+lapack_int LAPACKE_dtpmqrt_work( int matrix_order, char side, char trans,
+                                 lapack_int m, lapack_int n, lapack_int k,
+                                 lapack_int l, lapack_int nb, const double* v,
+                                 lapack_int ldv, const double* t,
+                                 lapack_int ldt, double* a, lapack_int lda,
+                                 double* b, lapack_int ldb, double* work );
+lapack_int LAPACKE_ctpmqrt_work( int matrix_order, char side, char trans,
+                                 lapack_int m, lapack_int n, lapack_int k,
+                                 lapack_int l, lapack_int nb,
+                                 const lapack_complex_float* v, lapack_int ldv,
+                                 const lapack_complex_float* t, lapack_int ldt,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* work );
+lapack_int LAPACKE_ztpmqrt_work( int matrix_order, char side, char trans,
+                                 lapack_int m, lapack_int n, lapack_int k,
+                                 lapack_int l, lapack_int nb,
+                                 const lapack_complex_double* v, lapack_int ldv,
+                                 const lapack_complex_double* t, lapack_int ldt,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* work );
+
+lapack_int LAPACKE_dtpqrt_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int l, lapack_int nb, double* a,
+                                lapack_int lda, double* b, lapack_int ldb,
+                                double* t, lapack_int ldt, double* work );
+lapack_int LAPACKE_ctpqrt_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int l, lapack_int nb,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* t,
+                                lapack_complex_float* b, lapack_int ldb,
+                                lapack_int ldt, lapack_complex_float* work );
+lapack_int LAPACKE_ztpqrt_work( int matrix_order, lapack_int m, lapack_int n,
+                                lapack_int l, lapack_int nb,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                lapack_complex_double* t, lapack_int ldt,
+                                lapack_complex_double* work );
+
+lapack_int LAPACKE_stpqrt2_work( int matrix_order, lapack_int m, lapack_int n,
+                                 float* a, lapack_int lda, float* b,
+                                 lapack_int ldb, float* t, lapack_int ldt );
+lapack_int LAPACKE_dtpqrt2_work( int matrix_order, lapack_int m, lapack_int n,
+                                 double* a, lapack_int lda, double* b,
+                                 lapack_int ldb, double* t, lapack_int ldt );
+lapack_int LAPACKE_ctpqrt2_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_complex_float* a, lapack_int lda,
+                                 lapack_complex_float* b, lapack_int ldb,
+                                 lapack_complex_float* t, lapack_int ldt );
+lapack_int LAPACKE_ztpqrt2_work( int matrix_order, lapack_int m, lapack_int n,
+                                 lapack_complex_double* a, lapack_int lda,
+                                 lapack_complex_double* b, lapack_int ldb,
+                                 lapack_complex_double* t, lapack_int ldt );
+
+lapack_int LAPACKE_stprfb_work( int matrix_order, char side, char trans,
+                                char direct, char storev, lapack_int m,
+                                lapack_int n, lapack_int k, lapack_int l,
+                                const float* v, lapack_int ldv, const float* t,
+                                lapack_int ldt, float* a, lapack_int lda,
+                                float* b, lapack_int ldb, const float* mywork,
+                                lapack_int myldwork );
+lapack_int LAPACKE_dtprfb_work( int matrix_order, char side, char trans,
+                                char direct, char storev, lapack_int m,
+                                lapack_int n, lapack_int k, lapack_int l,
+                                const double* v, lapack_int ldv,
+                                const double* t, lapack_int ldt, double* a,
+                                lapack_int lda, double* b, lapack_int ldb,
+                                const double* mywork, lapack_int myldwork );
+lapack_int LAPACKE_ctprfb_work( int matrix_order, char side, char trans,
+                                char direct, char storev, lapack_int m,
+                                lapack_int n, lapack_int k, lapack_int l,
+                                const lapack_complex_float* v, lapack_int ldv,
+                                const lapack_complex_float* t, lapack_int ldt,
+                                lapack_complex_float* a, lapack_int lda,
+                                lapack_complex_float* b, lapack_int ldb,
+                                const float* mywork, lapack_int myldwork );
+lapack_int LAPACKE_ztprfb_work( int matrix_order, char side, char trans,
+                                char direct, char storev, lapack_int m,
+                                lapack_int n, lapack_int k, lapack_int l,
+                                const lapack_complex_double* v, lapack_int ldv,
+                                const lapack_complex_double* t, lapack_int ldt,
+                                lapack_complex_double* a, lapack_int lda,
+                                lapack_complex_double* b, lapack_int ldb,
+                                const double* mywork, lapack_int myldwork );
+//LAPACK 3.X.X
+lapack_int LAPACKE_csyr( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_float alpha,
+                             const lapack_complex_float* x, lapack_int incx,
+                             lapack_complex_float* a, lapack_int lda );
+lapack_int LAPACKE_zsyr( int matrix_order, char uplo, lapack_int n,
+                             lapack_complex_double alpha,
+                             const lapack_complex_double* x, lapack_int incx,
+                             lapack_complex_double* a, lapack_int lda );
+
+lapack_int LAPACKE_csyr_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_float alpha,
+                                  const lapack_complex_float* x,
+                                  lapack_int incx, lapack_complex_float* a,
+                                  lapack_int lda );
+lapack_int LAPACKE_zsyr_work( int matrix_order, char uplo, lapack_int n,
+                                  lapack_complex_double alpha,
+                                  const lapack_complex_double* x,
+                                  lapack_int incx, lapack_complex_double* a,
+                                  lapack_int lda );
+
+
+
+#define LAPACK_sgetrf LAPACK_GLOBAL(sgetrf,SGETRF)
+#define LAPACK_dgetrf LAPACK_GLOBAL(dgetrf,DGETRF)
+#define LAPACK_cgetrf LAPACK_GLOBAL(cgetrf,CGETRF)
+#define LAPACK_zgetrf LAPACK_GLOBAL(zgetrf,ZGETRF)
+#define LAPACK_sgbtrf LAPACK_GLOBAL(sgbtrf,SGBTRF)
+#define LAPACK_dgbtrf LAPACK_GLOBAL(dgbtrf,DGBTRF)
+#define LAPACK_cgbtrf LAPACK_GLOBAL(cgbtrf,CGBTRF)
+#define LAPACK_zgbtrf LAPACK_GLOBAL(zgbtrf,ZGBTRF)
+#define LAPACK_sgttrf LAPACK_GLOBAL(sgttrf,SGTTRF)
+#define LAPACK_dgttrf LAPACK_GLOBAL(dgttrf,DGTTRF)
+#define LAPACK_cgttrf LAPACK_GLOBAL(cgttrf,CGTTRF)
+#define LAPACK_zgttrf LAPACK_GLOBAL(zgttrf,ZGTTRF)
+#define LAPACK_spotrf LAPACK_GLOBAL(spotrf,SPOTRF)
+#define LAPACK_dpotrf LAPACK_GLOBAL(dpotrf,DPOTRF)
+#define LAPACK_cpotrf LAPACK_GLOBAL(cpotrf,CPOTRF)
+#define LAPACK_zpotrf LAPACK_GLOBAL(zpotrf,ZPOTRF)
+#define LAPACK_dpstrf LAPACK_GLOBAL(dpstrf,DPSTRF)
+#define LAPACK_spstrf LAPACK_GLOBAL(spstrf,SPSTRF)
+#define LAPACK_zpstrf LAPACK_GLOBAL(zpstrf,ZPSTRF)
+#define LAPACK_cpstrf LAPACK_GLOBAL(cpstrf,CPSTRF)
+#define LAPACK_dpftrf LAPACK_GLOBAL(dpftrf,DPFTRF)
+#define LAPACK_spftrf LAPACK_GLOBAL(spftrf,SPFTRF)
+#define LAPACK_zpftrf LAPACK_GLOBAL(zpftrf,ZPFTRF)
+#define LAPACK_cpftrf LAPACK_GLOBAL(cpftrf,CPFTRF)
+#define LAPACK_spptrf LAPACK_GLOBAL(spptrf,SPPTRF)
+#define LAPACK_dpptrf LAPACK_GLOBAL(dpptrf,DPPTRF)
+#define LAPACK_cpptrf LAPACK_GLOBAL(cpptrf,CPPTRF)
+#define LAPACK_zpptrf LAPACK_GLOBAL(zpptrf,ZPPTRF)
+#define LAPACK_spbtrf LAPACK_GLOBAL(spbtrf,SPBTRF)
+#define LAPACK_dpbtrf LAPACK_GLOBAL(dpbtrf,DPBTRF)
+#define LAPACK_cpbtrf LAPACK_GLOBAL(cpbtrf,CPBTRF)
+#define LAPACK_zpbtrf LAPACK_GLOBAL(zpbtrf,ZPBTRF)
+#define LAPACK_spttrf LAPACK_GLOBAL(spttrf,SPTTRF)
+#define LAPACK_dpttrf LAPACK_GLOBAL(dpttrf,DPTTRF)
+#define LAPACK_cpttrf LAPACK_GLOBAL(cpttrf,CPTTRF)
+#define LAPACK_zpttrf LAPACK_GLOBAL(zpttrf,ZPTTRF)
+#define LAPACK_ssytrf LAPACK_GLOBAL(ssytrf,SSYTRF)
+#define LAPACK_dsytrf LAPACK_GLOBAL(dsytrf,DSYTRF)
+#define LAPACK_csytrf LAPACK_GLOBAL(csytrf,CSYTRF)
+#define LAPACK_zsytrf LAPACK_GLOBAL(zsytrf,ZSYTRF)
+#define LAPACK_chetrf LAPACK_GLOBAL(chetrf,CHETRF)
+#define LAPACK_zhetrf LAPACK_GLOBAL(zhetrf,ZHETRF)
+#define LAPACK_ssptrf LAPACK_GLOBAL(ssptrf,SSPTRF)
+#define LAPACK_dsptrf LAPACK_GLOBAL(dsptrf,DSPTRF)
+#define LAPACK_csptrf LAPACK_GLOBAL(csptrf,CSPTRF)
+#define LAPACK_zsptrf LAPACK_GLOBAL(zsptrf,ZSPTRF)
+#define LAPACK_chptrf LAPACK_GLOBAL(chptrf,CHPTRF)
+#define LAPACK_zhptrf LAPACK_GLOBAL(zhptrf,ZHPTRF)
+#define LAPACK_sgetrs LAPACK_GLOBAL(sgetrs,SGETRS)
+#define LAPACK_dgetrs LAPACK_GLOBAL(dgetrs,DGETRS)
+#define LAPACK_cgetrs LAPACK_GLOBAL(cgetrs,CGETRS)
+#define LAPACK_zgetrs LAPACK_GLOBAL(zgetrs,ZGETRS)
+#define LAPACK_sgbtrs LAPACK_GLOBAL(sgbtrs,SGBTRS)
+#define LAPACK_dgbtrs LAPACK_GLOBAL(dgbtrs,DGBTRS)
+#define LAPACK_cgbtrs LAPACK_GLOBAL(cgbtrs,CGBTRS)
+#define LAPACK_zgbtrs LAPACK_GLOBAL(zgbtrs,ZGBTRS)
+#define LAPACK_sgttrs LAPACK_GLOBAL(sgttrs,SGTTRS)
+#define LAPACK_dgttrs LAPACK_GLOBAL(dgttrs,DGTTRS)
+#define LAPACK_cgttrs LAPACK_GLOBAL(cgttrs,CGTTRS)
+#define LAPACK_zgttrs LAPACK_GLOBAL(zgttrs,ZGTTRS)
+#define LAPACK_spotrs LAPACK_GLOBAL(spotrs,SPOTRS)
+#define LAPACK_dpotrs LAPACK_GLOBAL(dpotrs,DPOTRS)
+#define LAPACK_cpotrs LAPACK_GLOBAL(cpotrs,CPOTRS)
+#define LAPACK_zpotrs LAPACK_GLOBAL(zpotrs,ZPOTRS)
+#define LAPACK_dpftrs LAPACK_GLOBAL(dpftrs,DPFTRS)
+#define LAPACK_spftrs LAPACK_GLOBAL(spftrs,SPFTRS)
+#define LAPACK_zpftrs LAPACK_GLOBAL(zpftrs,ZPFTRS)
+#define LAPACK_cpftrs LAPACK_GLOBAL(cpftrs,CPFTRS)
+#define LAPACK_spptrs LAPACK_GLOBAL(spptrs,SPPTRS)
+#define LAPACK_dpptrs LAPACK_GLOBAL(dpptrs,DPPTRS)
+#define LAPACK_cpptrs LAPACK_GLOBAL(cpptrs,CPPTRS)
+#define LAPACK_zpptrs LAPACK_GLOBAL(zpptrs,ZPPTRS)
+#define LAPACK_spbtrs LAPACK_GLOBAL(spbtrs,SPBTRS)
+#define LAPACK_dpbtrs LAPACK_GLOBAL(dpbtrs,DPBTRS)
+#define LAPACK_cpbtrs LAPACK_GLOBAL(cpbtrs,CPBTRS)
+#define LAPACK_zpbtrs LAPACK_GLOBAL(zpbtrs,ZPBTRS)
+#define LAPACK_spttrs LAPACK_GLOBAL(spttrs,SPTTRS)
+#define LAPACK_dpttrs LAPACK_GLOBAL(dpttrs,DPTTRS)
+#define LAPACK_cpttrs LAPACK_GLOBAL(cpttrs,CPTTRS)
+#define LAPACK_zpttrs LAPACK_GLOBAL(zpttrs,ZPTTRS)
+#define LAPACK_ssytrs LAPACK_GLOBAL(ssytrs,SSYTRS)
+#define LAPACK_dsytrs LAPACK_GLOBAL(dsytrs,DSYTRS)
+#define LAPACK_csytrs LAPACK_GLOBAL(csytrs,CSYTRS)
+#define LAPACK_zsytrs LAPACK_GLOBAL(zsytrs,ZSYTRS)
+#define LAPACK_chetrs LAPACK_GLOBAL(chetrs,CHETRS)
+#define LAPACK_zhetrs LAPACK_GLOBAL(zhetrs,ZHETRS)
+#define LAPACK_ssptrs LAPACK_GLOBAL(ssptrs,SSPTRS)
+#define LAPACK_dsptrs LAPACK_GLOBAL(dsptrs,DSPTRS)
+#define LAPACK_csptrs LAPACK_GLOBAL(csptrs,CSPTRS)
+#define LAPACK_zsptrs LAPACK_GLOBAL(zsptrs,ZSPTRS)
+#define LAPACK_chptrs LAPACK_GLOBAL(chptrs,CHPTRS)
+#define LAPACK_zhptrs LAPACK_GLOBAL(zhptrs,ZHPTRS)
+#define LAPACK_strtrs LAPACK_GLOBAL(strtrs,STRTRS)
+#define LAPACK_dtrtrs LAPACK_GLOBAL(dtrtrs,DTRTRS)
+#define LAPACK_ctrtrs LAPACK_GLOBAL(ctrtrs,CTRTRS)
+#define LAPACK_ztrtrs LAPACK_GLOBAL(ztrtrs,ZTRTRS)
+#define LAPACK_stptrs LAPACK_GLOBAL(stptrs,STPTRS)
+#define LAPACK_dtptrs LAPACK_GLOBAL(dtptrs,DTPTRS)
+#define LAPACK_ctptrs LAPACK_GLOBAL(ctptrs,CTPTRS)
+#define LAPACK_ztptrs LAPACK_GLOBAL(ztptrs,ZTPTRS)
+#define LAPACK_stbtrs LAPACK_GLOBAL(stbtrs,STBTRS)
+#define LAPACK_dtbtrs LAPACK_GLOBAL(dtbtrs,DTBTRS)
+#define LAPACK_ctbtrs LAPACK_GLOBAL(ctbtrs,CTBTRS)
+#define LAPACK_ztbtrs LAPACK_GLOBAL(ztbtrs,ZTBTRS)
+#define LAPACK_sgecon LAPACK_GLOBAL(sgecon,SGECON)
+#define LAPACK_dgecon LAPACK_GLOBAL(dgecon,DGECON)
+#define LAPACK_cgecon LAPACK_GLOBAL(cgecon,CGECON)
+#define LAPACK_zgecon LAPACK_GLOBAL(zgecon,ZGECON)
+#define LAPACK_sgbcon LAPACK_GLOBAL(sgbcon,SGBCON)
+#define LAPACK_dgbcon LAPACK_GLOBAL(dgbcon,DGBCON)
+#define LAPACK_cgbcon LAPACK_GLOBAL(cgbcon,CGBCON)
+#define LAPACK_zgbcon LAPACK_GLOBAL(zgbcon,ZGBCON)
+#define LAPACK_sgtcon LAPACK_GLOBAL(sgtcon,SGTCON)
+#define LAPACK_dgtcon LAPACK_GLOBAL(dgtcon,DGTCON)
+#define LAPACK_cgtcon LAPACK_GLOBAL(cgtcon,CGTCON)
+#define LAPACK_zgtcon LAPACK_GLOBAL(zgtcon,ZGTCON)
+#define LAPACK_spocon LAPACK_GLOBAL(spocon,SPOCON)
+#define LAPACK_dpocon LAPACK_GLOBAL(dpocon,DPOCON)
+#define LAPACK_cpocon LAPACK_GLOBAL(cpocon,CPOCON)
+#define LAPACK_zpocon LAPACK_GLOBAL(zpocon,ZPOCON)
+#define LAPACK_sppcon LAPACK_GLOBAL(sppcon,SPPCON)
+#define LAPACK_dppcon LAPACK_GLOBAL(dppcon,DPPCON)
+#define LAPACK_cppcon LAPACK_GLOBAL(cppcon,CPPCON)
+#define LAPACK_zppcon LAPACK_GLOBAL(zppcon,ZPPCON)
+#define LAPACK_spbcon LAPACK_GLOBAL(spbcon,SPBCON)
+#define LAPACK_dpbcon LAPACK_GLOBAL(dpbcon,DPBCON)
+#define LAPACK_cpbcon LAPACK_GLOBAL(cpbcon,CPBCON)
+#define LAPACK_zpbcon LAPACK_GLOBAL(zpbcon,ZPBCON)
+#define LAPACK_sptcon LAPACK_GLOBAL(sptcon,SPTCON)
+#define LAPACK_dptcon LAPACK_GLOBAL(dptcon,DPTCON)
+#define LAPACK_cptcon LAPACK_GLOBAL(cptcon,CPTCON)
+#define LAPACK_zptcon LAPACK_GLOBAL(zptcon,ZPTCON)
+#define LAPACK_ssycon LAPACK_GLOBAL(ssycon,SSYCON)
+#define LAPACK_dsycon LAPACK_GLOBAL(dsycon,DSYCON)
+#define LAPACK_csycon LAPACK_GLOBAL(csycon,CSYCON)
+#define LAPACK_zsycon LAPACK_GLOBAL(zsycon,ZSYCON)
+#define LAPACK_checon LAPACK_GLOBAL(checon,CHECON)
+#define LAPACK_zhecon LAPACK_GLOBAL(zhecon,ZHECON)
+#define LAPACK_sspcon LAPACK_GLOBAL(sspcon,SSPCON)
+#define LAPACK_dspcon LAPACK_GLOBAL(dspcon,DSPCON)
+#define LAPACK_cspcon LAPACK_GLOBAL(cspcon,CSPCON)
+#define LAPACK_zspcon LAPACK_GLOBAL(zspcon,ZSPCON)
+#define LAPACK_chpcon LAPACK_GLOBAL(chpcon,CHPCON)
+#define LAPACK_zhpcon LAPACK_GLOBAL(zhpcon,ZHPCON)
+#define LAPACK_strcon LAPACK_GLOBAL(strcon,STRCON)
+#define LAPACK_dtrcon LAPACK_GLOBAL(dtrcon,DTRCON)
+#define LAPACK_ctrcon LAPACK_GLOBAL(ctrcon,CTRCON)
+#define LAPACK_ztrcon LAPACK_GLOBAL(ztrcon,ZTRCON)
+#define LAPACK_stpcon LAPACK_GLOBAL(stpcon,STPCON)
+#define LAPACK_dtpcon LAPACK_GLOBAL(dtpcon,DTPCON)
+#define LAPACK_ctpcon LAPACK_GLOBAL(ctpcon,CTPCON)
+#define LAPACK_ztpcon LAPACK_GLOBAL(ztpcon,ZTPCON)
+#define LAPACK_stbcon LAPACK_GLOBAL(stbcon,STBCON)
+#define LAPACK_dtbcon LAPACK_GLOBAL(dtbcon,DTBCON)
+#define LAPACK_ctbcon LAPACK_GLOBAL(ctbcon,CTBCON)
+#define LAPACK_ztbcon LAPACK_GLOBAL(ztbcon,ZTBCON)
+#define LAPACK_sgerfs LAPACK_GLOBAL(sgerfs,SGERFS)
+#define LAPACK_dgerfs LAPACK_GLOBAL(dgerfs,DGERFS)
+#define LAPACK_cgerfs LAPACK_GLOBAL(cgerfs,CGERFS)
+#define LAPACK_zgerfs LAPACK_GLOBAL(zgerfs,ZGERFS)
+#define LAPACK_dgerfsx LAPACK_GLOBAL(dgerfsx,DGERFSX)
+#define LAPACK_sgerfsx LAPACK_GLOBAL(sgerfsx,SGERFSX)
+#define LAPACK_zgerfsx LAPACK_GLOBAL(zgerfsx,ZGERFSX)
+#define LAPACK_cgerfsx LAPACK_GLOBAL(cgerfsx,CGERFSX)
+#define LAPACK_sgbrfs LAPACK_GLOBAL(sgbrfs,SGBRFS)
+#define LAPACK_dgbrfs LAPACK_GLOBAL(dgbrfs,DGBRFS)
+#define LAPACK_cgbrfs LAPACK_GLOBAL(cgbrfs,CGBRFS)
+#define LAPACK_zgbrfs LAPACK_GLOBAL(zgbrfs,ZGBRFS)
+#define LAPACK_dgbrfsx LAPACK_GLOBAL(dgbrfsx,DGBRFSX)
+#define LAPACK_sgbrfsx LAPACK_GLOBAL(sgbrfsx,SGBRFSX)
+#define LAPACK_zgbrfsx LAPACK_GLOBAL(zgbrfsx,ZGBRFSX)
+#define LAPACK_cgbrfsx LAPACK_GLOBAL(cgbrfsx,CGBRFSX)
+#define LAPACK_sgtrfs LAPACK_GLOBAL(sgtrfs,SGTRFS)
+#define LAPACK_dgtrfs LAPACK_GLOBAL(dgtrfs,DGTRFS)
+#define LAPACK_cgtrfs LAPACK_GLOBAL(cgtrfs,CGTRFS)
+#define LAPACK_zgtrfs LAPACK_GLOBAL(zgtrfs,ZGTRFS)
+#define LAPACK_sporfs LAPACK_GLOBAL(sporfs,SPORFS)
+#define LAPACK_dporfs LAPACK_GLOBAL(dporfs,DPORFS)
+#define LAPACK_cporfs LAPACK_GLOBAL(cporfs,CPORFS)
+#define LAPACK_zporfs LAPACK_GLOBAL(zporfs,ZPORFS)
+#define LAPACK_dporfsx LAPACK_GLOBAL(dporfsx,DPORFSX)
+#define LAPACK_sporfsx LAPACK_GLOBAL(sporfsx,SPORFSX)
+#define LAPACK_zporfsx LAPACK_GLOBAL(zporfsx,ZPORFSX)
+#define LAPACK_cporfsx LAPACK_GLOBAL(cporfsx,CPORFSX)
+#define LAPACK_spprfs LAPACK_GLOBAL(spprfs,SPPRFS)
+#define LAPACK_dpprfs LAPACK_GLOBAL(dpprfs,DPPRFS)
+#define LAPACK_cpprfs LAPACK_GLOBAL(cpprfs,CPPRFS)
+#define LAPACK_zpprfs LAPACK_GLOBAL(zpprfs,ZPPRFS)
+#define LAPACK_spbrfs LAPACK_GLOBAL(spbrfs,SPBRFS)
+#define LAPACK_dpbrfs LAPACK_GLOBAL(dpbrfs,DPBRFS)
+#define LAPACK_cpbrfs LAPACK_GLOBAL(cpbrfs,CPBRFS)
+#define LAPACK_zpbrfs LAPACK_GLOBAL(zpbrfs,ZPBRFS)
+#define LAPACK_sptrfs LAPACK_GLOBAL(sptrfs,SPTRFS)
+#define LAPACK_dptrfs LAPACK_GLOBAL(dptrfs,DPTRFS)
+#define LAPACK_cptrfs LAPACK_GLOBAL(cptrfs,CPTRFS)
+#define LAPACK_zptrfs LAPACK_GLOBAL(zptrfs,ZPTRFS)
+#define LAPACK_ssyrfs LAPACK_GLOBAL(ssyrfs,SSYRFS)
+#define LAPACK_dsyrfs LAPACK_GLOBAL(dsyrfs,DSYRFS)
+#define LAPACK_csyrfs LAPACK_GLOBAL(csyrfs,CSYRFS)
+#define LAPACK_zsyrfs LAPACK_GLOBAL(zsyrfs,ZSYRFS)
+#define LAPACK_dsyrfsx LAPACK_GLOBAL(dsyrfsx,DSYRFSX)
+#define LAPACK_ssyrfsx LAPACK_GLOBAL(ssyrfsx,SSYRFSX)
+#define LAPACK_zsyrfsx LAPACK_GLOBAL(zsyrfsx,ZSYRFSX)
+#define LAPACK_csyrfsx LAPACK_GLOBAL(csyrfsx,CSYRFSX)
+#define LAPACK_cherfs LAPACK_GLOBAL(cherfs,CHERFS)
+#define LAPACK_zherfs LAPACK_GLOBAL(zherfs,ZHERFS)
+#define LAPACK_zherfsx LAPACK_GLOBAL(zherfsx,ZHERFSX)
+#define LAPACK_cherfsx LAPACK_GLOBAL(cherfsx,CHERFSX)
+#define LAPACK_ssprfs LAPACK_GLOBAL(ssprfs,SSPRFS)
+#define LAPACK_dsprfs LAPACK_GLOBAL(dsprfs,DSPRFS)
+#define LAPACK_csprfs LAPACK_GLOBAL(csprfs,CSPRFS)
+#define LAPACK_zsprfs LAPACK_GLOBAL(zsprfs,ZSPRFS)
+#define LAPACK_chprfs LAPACK_GLOBAL(chprfs,CHPRFS)
+#define LAPACK_zhprfs LAPACK_GLOBAL(zhprfs,ZHPRFS)
+#define LAPACK_strrfs LAPACK_GLOBAL(strrfs,STRRFS)
+#define LAPACK_dtrrfs LAPACK_GLOBAL(dtrrfs,DTRRFS)
+#define LAPACK_ctrrfs LAPACK_GLOBAL(ctrrfs,CTRRFS)
+#define LAPACK_ztrrfs LAPACK_GLOBAL(ztrrfs,ZTRRFS)
+#define LAPACK_stprfs LAPACK_GLOBAL(stprfs,STPRFS)
+#define LAPACK_dtprfs LAPACK_GLOBAL(dtprfs,DTPRFS)
+#define LAPACK_ctprfs LAPACK_GLOBAL(ctprfs,CTPRFS)
+#define LAPACK_ztprfs LAPACK_GLOBAL(ztprfs,ZTPRFS)
+#define LAPACK_stbrfs LAPACK_GLOBAL(stbrfs,STBRFS)
+#define LAPACK_dtbrfs LAPACK_GLOBAL(dtbrfs,DTBRFS)
+#define LAPACK_ctbrfs LAPACK_GLOBAL(ctbrfs,CTBRFS)
+#define LAPACK_ztbrfs LAPACK_GLOBAL(ztbrfs,ZTBRFS)
+#define LAPACK_sgetri LAPACK_GLOBAL(sgetri,SGETRI)
+#define LAPACK_dgetri LAPACK_GLOBAL(dgetri,DGETRI)
+#define LAPACK_cgetri LAPACK_GLOBAL(cgetri,CGETRI)
+#define LAPACK_zgetri LAPACK_GLOBAL(zgetri,ZGETRI)
+#define LAPACK_spotri LAPACK_GLOBAL(spotri,SPOTRI)
+#define LAPACK_dpotri LAPACK_GLOBAL(dpotri,DPOTRI)
+#define LAPACK_cpotri LAPACK_GLOBAL(cpotri,CPOTRI)
+#define LAPACK_zpotri LAPACK_GLOBAL(zpotri,ZPOTRI)
+#define LAPACK_dpftri LAPACK_GLOBAL(dpftri,DPFTRI)
+#define LAPACK_spftri LAPACK_GLOBAL(spftri,SPFTRI)
+#define LAPACK_zpftri LAPACK_GLOBAL(zpftri,ZPFTRI)
+#define LAPACK_cpftri LAPACK_GLOBAL(cpftri,CPFTRI)
+#define LAPACK_spptri LAPACK_GLOBAL(spptri,SPPTRI)
+#define LAPACK_dpptri LAPACK_GLOBAL(dpptri,DPPTRI)
+#define LAPACK_cpptri LAPACK_GLOBAL(cpptri,CPPTRI)
+#define LAPACK_zpptri LAPACK_GLOBAL(zpptri,ZPPTRI)
+#define LAPACK_ssytri LAPACK_GLOBAL(ssytri,SSYTRI)
+#define LAPACK_dsytri LAPACK_GLOBAL(dsytri,DSYTRI)
+#define LAPACK_csytri LAPACK_GLOBAL(csytri,CSYTRI)
+#define LAPACK_zsytri LAPACK_GLOBAL(zsytri,ZSYTRI)
+#define LAPACK_chetri LAPACK_GLOBAL(chetri,CHETRI)
+#define LAPACK_zhetri LAPACK_GLOBAL(zhetri,ZHETRI)
+#define LAPACK_ssptri LAPACK_GLOBAL(ssptri,SSPTRI)
+#define LAPACK_dsptri LAPACK_GLOBAL(dsptri,DSPTRI)
+#define LAPACK_csptri LAPACK_GLOBAL(csptri,CSPTRI)
+#define LAPACK_zsptri LAPACK_GLOBAL(zsptri,ZSPTRI)
+#define LAPACK_chptri LAPACK_GLOBAL(chptri,CHPTRI)
+#define LAPACK_zhptri LAPACK_GLOBAL(zhptri,ZHPTRI)
+#define LAPACK_strtri LAPACK_GLOBAL(strtri,STRTRI)
+#define LAPACK_dtrtri LAPACK_GLOBAL(dtrtri,DTRTRI)
+#define LAPACK_ctrtri LAPACK_GLOBAL(ctrtri,CTRTRI)
+#define LAPACK_ztrtri LAPACK_GLOBAL(ztrtri,ZTRTRI)
+#define LAPACK_dtftri LAPACK_GLOBAL(dtftri,DTFTRI)
+#define LAPACK_stftri LAPACK_GLOBAL(stftri,STFTRI)
+#define LAPACK_ztftri LAPACK_GLOBAL(ztftri,ZTFTRI)
+#define LAPACK_ctftri LAPACK_GLOBAL(ctftri,CTFTRI)
+#define LAPACK_stptri LAPACK_GLOBAL(stptri,STPTRI)
+#define LAPACK_dtptri LAPACK_GLOBAL(dtptri,DTPTRI)
+#define LAPACK_ctptri LAPACK_GLOBAL(ctptri,CTPTRI)
+#define LAPACK_ztptri LAPACK_GLOBAL(ztptri,ZTPTRI)
+#define LAPACK_sgeequ LAPACK_GLOBAL(sgeequ,SGEEQU)
+#define LAPACK_dgeequ LAPACK_GLOBAL(dgeequ,DGEEQU)
+#define LAPACK_cgeequ LAPACK_GLOBAL(cgeequ,CGEEQU)
+#define LAPACK_zgeequ LAPACK_GLOBAL(zgeequ,ZGEEQU)
+#define LAPACK_dgeequb LAPACK_GLOBAL(dgeequb,DGEEQUB)
+#define LAPACK_sgeequb LAPACK_GLOBAL(sgeequb,SGEEQUB)
+#define LAPACK_zgeequb LAPACK_GLOBAL(zgeequb,ZGEEQUB)
+#define LAPACK_cgeequb LAPACK_GLOBAL(cgeequb,CGEEQUB)
+#define LAPACK_sgbequ LAPACK_GLOBAL(sgbequ,SGBEQU)
+#define LAPACK_dgbequ LAPACK_GLOBAL(dgbequ,DGBEQU)
+#define LAPACK_cgbequ LAPACK_GLOBAL(cgbequ,CGBEQU)
+#define LAPACK_zgbequ LAPACK_GLOBAL(zgbequ,ZGBEQU)
+#define LAPACK_dgbequb LAPACK_GLOBAL(dgbequb,DGBEQUB)
+#define LAPACK_sgbequb LAPACK_GLOBAL(sgbequb,SGBEQUB)
+#define LAPACK_zgbequb LAPACK_GLOBAL(zgbequb,ZGBEQUB)
+#define LAPACK_cgbequb LAPACK_GLOBAL(cgbequb,CGBEQUB)
+#define LAPACK_spoequ LAPACK_GLOBAL(spoequ,SPOEQU)
+#define LAPACK_dpoequ LAPACK_GLOBAL(dpoequ,DPOEQU)
+#define LAPACK_cpoequ LAPACK_GLOBAL(cpoequ,CPOEQU)
+#define LAPACK_zpoequ LAPACK_GLOBAL(zpoequ,ZPOEQU)
+#define LAPACK_dpoequb LAPACK_GLOBAL(dpoequb,DPOEQUB)
+#define LAPACK_spoequb LAPACK_GLOBAL(spoequb,SPOEQUB)
+#define LAPACK_zpoequb LAPACK_GLOBAL(zpoequb,ZPOEQUB)
+#define LAPACK_cpoequb LAPACK_GLOBAL(cpoequb,CPOEQUB)
+#define LAPACK_sppequ LAPACK_GLOBAL(sppequ,SPPEQU)
+#define LAPACK_dppequ LAPACK_GLOBAL(dppequ,DPPEQU)
+#define LAPACK_cppequ LAPACK_GLOBAL(cppequ,CPPEQU)
+#define LAPACK_zppequ LAPACK_GLOBAL(zppequ,ZPPEQU)
+#define LAPACK_spbequ LAPACK_GLOBAL(spbequ,SPBEQU)
+#define LAPACK_dpbequ LAPACK_GLOBAL(dpbequ,DPBEQU)
+#define LAPACK_cpbequ LAPACK_GLOBAL(cpbequ,CPBEQU)
+#define LAPACK_zpbequ LAPACK_GLOBAL(zpbequ,ZPBEQU)
+#define LAPACK_dsyequb LAPACK_GLOBAL(dsyequb,DSYEQUB)
+#define LAPACK_ssyequb LAPACK_GLOBAL(ssyequb,SSYEQUB)
+#define LAPACK_zsyequb LAPACK_GLOBAL(zsyequb,ZSYEQUB)
+#define LAPACK_csyequb LAPACK_GLOBAL(csyequb,CSYEQUB)
+#define LAPACK_zheequb LAPACK_GLOBAL(zheequb,ZHEEQUB)
+#define LAPACK_cheequb LAPACK_GLOBAL(cheequb,CHEEQUB)
+#define LAPACK_sgesv LAPACK_GLOBAL(sgesv,SGESV)
+#define LAPACK_dgesv LAPACK_GLOBAL(dgesv,DGESV)
+#define LAPACK_cgesv LAPACK_GLOBAL(cgesv,CGESV)
+#define LAPACK_zgesv LAPACK_GLOBAL(zgesv,ZGESV)
+#define LAPACK_dsgesv LAPACK_GLOBAL(dsgesv,DSGESV)
+#define LAPACK_zcgesv LAPACK_GLOBAL(zcgesv,ZCGESV)
+#define LAPACK_sgesvx LAPACK_GLOBAL(sgesvx,SGESVX)
+#define LAPACK_dgesvx LAPACK_GLOBAL(dgesvx,DGESVX)
+#define LAPACK_cgesvx LAPACK_GLOBAL(cgesvx,CGESVX)
+#define LAPACK_zgesvx LAPACK_GLOBAL(zgesvx,ZGESVX)
+#define LAPACK_dgesvxx LAPACK_GLOBAL(dgesvxx,DGESVXX)
+#define LAPACK_sgesvxx LAPACK_GLOBAL(sgesvxx,SGESVXX)
+#define LAPACK_zgesvxx LAPACK_GLOBAL(zgesvxx,ZGESVXX)
+#define LAPACK_cgesvxx LAPACK_GLOBAL(cgesvxx,CGESVXX)
+#define LAPACK_sgbsv LAPACK_GLOBAL(sgbsv,SGBSV)
+#define LAPACK_dgbsv LAPACK_GLOBAL(dgbsv,DGBSV)
+#define LAPACK_cgbsv LAPACK_GLOBAL(cgbsv,CGBSV)
+#define LAPACK_zgbsv LAPACK_GLOBAL(zgbsv,ZGBSV)
+#define LAPACK_sgbsvx LAPACK_GLOBAL(sgbsvx,SGBSVX)
+#define LAPACK_dgbsvx LAPACK_GLOBAL(dgbsvx,DGBSVX)
+#define LAPACK_cgbsvx LAPACK_GLOBAL(cgbsvx,CGBSVX)
+#define LAPACK_zgbsvx LAPACK_GLOBAL(zgbsvx,ZGBSVX)
+#define LAPACK_dgbsvxx LAPACK_GLOBAL(dgbsvxx,DGBSVXX)
+#define LAPACK_sgbsvxx LAPACK_GLOBAL(sgbsvxx,SGBSVXX)
+#define LAPACK_zgbsvxx LAPACK_GLOBAL(zgbsvxx,ZGBSVXX)
+#define LAPACK_cgbsvxx LAPACK_GLOBAL(cgbsvxx,CGBSVXX)
+#define LAPACK_sgtsv LAPACK_GLOBAL(sgtsv,SGTSV)
+#define LAPACK_dgtsv LAPACK_GLOBAL(dgtsv,DGTSV)
+#define LAPACK_cgtsv LAPACK_GLOBAL(cgtsv,CGTSV)
+#define LAPACK_zgtsv LAPACK_GLOBAL(zgtsv,ZGTSV)
+#define LAPACK_sgtsvx LAPACK_GLOBAL(sgtsvx,SGTSVX)
+#define LAPACK_dgtsvx LAPACK_GLOBAL(dgtsvx,DGTSVX)
+#define LAPACK_cgtsvx LAPACK_GLOBAL(cgtsvx,CGTSVX)
+#define LAPACK_zgtsvx LAPACK_GLOBAL(zgtsvx,ZGTSVX)
+#define LAPACK_sposv LAPACK_GLOBAL(sposv,SPOSV)
+#define LAPACK_dposv LAPACK_GLOBAL(dposv,DPOSV)
+#define LAPACK_cposv LAPACK_GLOBAL(cposv,CPOSV)
+#define LAPACK_zposv LAPACK_GLOBAL(zposv,ZPOSV)
+#define LAPACK_dsposv LAPACK_GLOBAL(dsposv,DSPOSV)
+#define LAPACK_zcposv LAPACK_GLOBAL(zcposv,ZCPOSV)
+#define LAPACK_sposvx LAPACK_GLOBAL(sposvx,SPOSVX)
+#define LAPACK_dposvx LAPACK_GLOBAL(dposvx,DPOSVX)
+#define LAPACK_cposvx LAPACK_GLOBAL(cposvx,CPOSVX)
+#define LAPACK_zposvx LAPACK_GLOBAL(zposvx,ZPOSVX)
+#define LAPACK_dposvxx LAPACK_GLOBAL(dposvxx,DPOSVXX)
+#define LAPACK_sposvxx LAPACK_GLOBAL(sposvxx,SPOSVXX)
+#define LAPACK_zposvxx LAPACK_GLOBAL(zposvxx,ZPOSVXX)
+#define LAPACK_cposvxx LAPACK_GLOBAL(cposvxx,CPOSVXX)
+#define LAPACK_sppsv LAPACK_GLOBAL(sppsv,SPPSV)
+#define LAPACK_dppsv LAPACK_GLOBAL(dppsv,DPPSV)
+#define LAPACK_cppsv LAPACK_GLOBAL(cppsv,CPPSV)
+#define LAPACK_zppsv LAPACK_GLOBAL(zppsv,ZPPSV)
+#define LAPACK_sppsvx LAPACK_GLOBAL(sppsvx,SPPSVX)
+#define LAPACK_dppsvx LAPACK_GLOBAL(dppsvx,DPPSVX)
+#define LAPACK_cppsvx LAPACK_GLOBAL(cppsvx,CPPSVX)
+#define LAPACK_zppsvx LAPACK_GLOBAL(zppsvx,ZPPSVX)
+#define LAPACK_spbsv LAPACK_GLOBAL(spbsv,SPBSV)
+#define LAPACK_dpbsv LAPACK_GLOBAL(dpbsv,DPBSV)
+#define LAPACK_cpbsv LAPACK_GLOBAL(cpbsv,CPBSV)
+#define LAPACK_zpbsv LAPACK_GLOBAL(zpbsv,ZPBSV)
+#define LAPACK_spbsvx LAPACK_GLOBAL(spbsvx,SPBSVX)
+#define LAPACK_dpbsvx LAPACK_GLOBAL(dpbsvx,DPBSVX)
+#define LAPACK_cpbsvx LAPACK_GLOBAL(cpbsvx,CPBSVX)
+#define LAPACK_zpbsvx LAPACK_GLOBAL(zpbsvx,ZPBSVX)
+#define LAPACK_sptsv LAPACK_GLOBAL(sptsv,SPTSV)
+#define LAPACK_dptsv LAPACK_GLOBAL(dptsv,DPTSV)
+#define LAPACK_cptsv LAPACK_GLOBAL(cptsv,CPTSV)
+#define LAPACK_zptsv LAPACK_GLOBAL(zptsv,ZPTSV)
+#define LAPACK_sptsvx LAPACK_GLOBAL(sptsvx,SPTSVX)
+#define LAPACK_dptsvx LAPACK_GLOBAL(dptsvx,DPTSVX)
+#define LAPACK_cptsvx LAPACK_GLOBAL(cptsvx,CPTSVX)
+#define LAPACK_zptsvx LAPACK_GLOBAL(zptsvx,ZPTSVX)
+#define LAPACK_ssysv LAPACK_GLOBAL(ssysv,SSYSV)
+#define LAPACK_dsysv LAPACK_GLOBAL(dsysv,DSYSV)
+#define LAPACK_csysv LAPACK_GLOBAL(csysv,CSYSV)
+#define LAPACK_zsysv LAPACK_GLOBAL(zsysv,ZSYSV)
+#define LAPACK_ssysvx LAPACK_GLOBAL(ssysvx,SSYSVX)
+#define LAPACK_dsysvx LAPACK_GLOBAL(dsysvx,DSYSVX)
+#define LAPACK_csysvx LAPACK_GLOBAL(csysvx,CSYSVX)
+#define LAPACK_zsysvx LAPACK_GLOBAL(zsysvx,ZSYSVX)
+#define LAPACK_dsysvxx LAPACK_GLOBAL(dsysvxx,DSYSVXX)
+#define LAPACK_ssysvxx LAPACK_GLOBAL(ssysvxx,SSYSVXX)
+#define LAPACK_zsysvxx LAPACK_GLOBAL(zsysvxx,ZSYSVXX)
+#define LAPACK_csysvxx LAPACK_GLOBAL(csysvxx,CSYSVXX)
+#define LAPACK_chesv LAPACK_GLOBAL(chesv,CHESV)
+#define LAPACK_zhesv LAPACK_GLOBAL(zhesv,ZHESV)
+#define LAPACK_chesvx LAPACK_GLOBAL(chesvx,CHESVX)
+#define LAPACK_zhesvx LAPACK_GLOBAL(zhesvx,ZHESVX)
+#define LAPACK_zhesvxx LAPACK_GLOBAL(zhesvxx,ZHESVXX)
+#define LAPACK_chesvxx LAPACK_GLOBAL(chesvxx,CHESVXX)
+#define LAPACK_sspsv LAPACK_GLOBAL(sspsv,SSPSV)
+#define LAPACK_dspsv LAPACK_GLOBAL(dspsv,DSPSV)
+#define LAPACK_cspsv LAPACK_GLOBAL(cspsv,CSPSV)
+#define LAPACK_zspsv LAPACK_GLOBAL(zspsv,ZSPSV)
+#define LAPACK_sspsvx LAPACK_GLOBAL(sspsvx,SSPSVX)
+#define LAPACK_dspsvx LAPACK_GLOBAL(dspsvx,DSPSVX)
+#define LAPACK_cspsvx LAPACK_GLOBAL(cspsvx,CSPSVX)
+#define LAPACK_zspsvx LAPACK_GLOBAL(zspsvx,ZSPSVX)
+#define LAPACK_chpsv LAPACK_GLOBAL(chpsv,CHPSV)
+#define LAPACK_zhpsv LAPACK_GLOBAL(zhpsv,ZHPSV)
+#define LAPACK_chpsvx LAPACK_GLOBAL(chpsvx,CHPSVX)
+#define LAPACK_zhpsvx LAPACK_GLOBAL(zhpsvx,ZHPSVX)
+#define LAPACK_sgeqrf LAPACK_GLOBAL(sgeqrf,SGEQRF)
+#define LAPACK_dgeqrf LAPACK_GLOBAL(dgeqrf,DGEQRF)
+#define LAPACK_cgeqrf LAPACK_GLOBAL(cgeqrf,CGEQRF)
+#define LAPACK_zgeqrf LAPACK_GLOBAL(zgeqrf,ZGEQRF)
+#define LAPACK_sgeqpf LAPACK_GLOBAL(sgeqpf,SGEQPF)
+#define LAPACK_dgeqpf LAPACK_GLOBAL(dgeqpf,DGEQPF)
+#define LAPACK_cgeqpf LAPACK_GLOBAL(cgeqpf,CGEQPF)
+#define LAPACK_zgeqpf LAPACK_GLOBAL(zgeqpf,ZGEQPF)
+#define LAPACK_sgeqp3 LAPACK_GLOBAL(sgeqp3,SGEQP3)
+#define LAPACK_dgeqp3 LAPACK_GLOBAL(dgeqp3,DGEQP3)
+#define LAPACK_cgeqp3 LAPACK_GLOBAL(cgeqp3,CGEQP3)
+#define LAPACK_zgeqp3 LAPACK_GLOBAL(zgeqp3,ZGEQP3)
+#define LAPACK_sorgqr LAPACK_GLOBAL(sorgqr,SORGQR)
+#define LAPACK_dorgqr LAPACK_GLOBAL(dorgqr,DORGQR)
+#define LAPACK_sormqr LAPACK_GLOBAL(sormqr,SORMQR)
+#define LAPACK_dormqr LAPACK_GLOBAL(dormqr,DORMQR)
+#define LAPACK_cungqr LAPACK_GLOBAL(cungqr,CUNGQR)
+#define LAPACK_zungqr LAPACK_GLOBAL(zungqr,ZUNGQR)
+#define LAPACK_cunmqr LAPACK_GLOBAL(cunmqr,CUNMQR)
+#define LAPACK_zunmqr LAPACK_GLOBAL(zunmqr,ZUNMQR)
+#define LAPACK_sgelqf LAPACK_GLOBAL(sgelqf,SGELQF)
+#define LAPACK_dgelqf LAPACK_GLOBAL(dgelqf,DGELQF)
+#define LAPACK_cgelqf LAPACK_GLOBAL(cgelqf,CGELQF)
+#define LAPACK_zgelqf LAPACK_GLOBAL(zgelqf,ZGELQF)
+#define LAPACK_sorglq LAPACK_GLOBAL(sorglq,SORGLQ)
+#define LAPACK_dorglq LAPACK_GLOBAL(dorglq,DORGLQ)
+#define LAPACK_sormlq LAPACK_GLOBAL(sormlq,SORMLQ)
+#define LAPACK_dormlq LAPACK_GLOBAL(dormlq,DORMLQ)
+#define LAPACK_cunglq LAPACK_GLOBAL(cunglq,CUNGLQ)
+#define LAPACK_zunglq LAPACK_GLOBAL(zunglq,ZUNGLQ)
+#define LAPACK_cunmlq LAPACK_GLOBAL(cunmlq,CUNMLQ)
+#define LAPACK_zunmlq LAPACK_GLOBAL(zunmlq,ZUNMLQ)
+#define LAPACK_sgeqlf LAPACK_GLOBAL(sgeqlf,SGEQLF)
+#define LAPACK_dgeqlf LAPACK_GLOBAL(dgeqlf,DGEQLF)
+#define LAPACK_cgeqlf LAPACK_GLOBAL(cgeqlf,CGEQLF)
+#define LAPACK_zgeqlf LAPACK_GLOBAL(zgeqlf,ZGEQLF)
+#define LAPACK_sorgql LAPACK_GLOBAL(sorgql,SORGQL)
+#define LAPACK_dorgql LAPACK_GLOBAL(dorgql,DORGQL)
+#define LAPACK_cungql LAPACK_GLOBAL(cungql,CUNGQL)
+#define LAPACK_zungql LAPACK_GLOBAL(zungql,ZUNGQL)
+#define LAPACK_sormql LAPACK_GLOBAL(sormql,SORMQL)
+#define LAPACK_dormql LAPACK_GLOBAL(dormql,DORMQL)
+#define LAPACK_cunmql LAPACK_GLOBAL(cunmql,CUNMQL)
+#define LAPACK_zunmql LAPACK_GLOBAL(zunmql,ZUNMQL)
+#define LAPACK_sgerqf LAPACK_GLOBAL(sgerqf,SGERQF)
+#define LAPACK_dgerqf LAPACK_GLOBAL(dgerqf,DGERQF)
+#define LAPACK_cgerqf LAPACK_GLOBAL(cgerqf,CGERQF)
+#define LAPACK_zgerqf LAPACK_GLOBAL(zgerqf,ZGERQF)
+#define LAPACK_sorgrq LAPACK_GLOBAL(sorgrq,SORGRQ)
+#define LAPACK_dorgrq LAPACK_GLOBAL(dorgrq,DORGRQ)
+#define LAPACK_cungrq LAPACK_GLOBAL(cungrq,CUNGRQ)
+#define LAPACK_zungrq LAPACK_GLOBAL(zungrq,ZUNGRQ)
+#define LAPACK_sormrq LAPACK_GLOBAL(sormrq,SORMRQ)
+#define LAPACK_dormrq LAPACK_GLOBAL(dormrq,DORMRQ)
+#define LAPACK_cunmrq LAPACK_GLOBAL(cunmrq,CUNMRQ)
+#define LAPACK_zunmrq LAPACK_GLOBAL(zunmrq,ZUNMRQ)
+#define LAPACK_stzrzf LAPACK_GLOBAL(stzrzf,STZRZF)
+#define LAPACK_dtzrzf LAPACK_GLOBAL(dtzrzf,DTZRZF)
+#define LAPACK_ctzrzf LAPACK_GLOBAL(ctzrzf,CTZRZF)
+#define LAPACK_ztzrzf LAPACK_GLOBAL(ztzrzf,ZTZRZF)
+#define LAPACK_sormrz LAPACK_GLOBAL(sormrz,SORMRZ)
+#define LAPACK_dormrz LAPACK_GLOBAL(dormrz,DORMRZ)
+#define LAPACK_cunmrz LAPACK_GLOBAL(cunmrz,CUNMRZ)
+#define LAPACK_zunmrz LAPACK_GLOBAL(zunmrz,ZUNMRZ)
+#define LAPACK_sggqrf LAPACK_GLOBAL(sggqrf,SGGQRF)
+#define LAPACK_dggqrf LAPACK_GLOBAL(dggqrf,DGGQRF)
+#define LAPACK_cggqrf LAPACK_GLOBAL(cggqrf,CGGQRF)
+#define LAPACK_zggqrf LAPACK_GLOBAL(zggqrf,ZGGQRF)
+#define LAPACK_sggrqf LAPACK_GLOBAL(sggrqf,SGGRQF)
+#define LAPACK_dggrqf LAPACK_GLOBAL(dggrqf,DGGRQF)
+#define LAPACK_cggrqf LAPACK_GLOBAL(cggrqf,CGGRQF)
+#define LAPACK_zggrqf LAPACK_GLOBAL(zggrqf,ZGGRQF)
+#define LAPACK_sgebrd LAPACK_GLOBAL(sgebrd,SGEBRD)
+#define LAPACK_dgebrd LAPACK_GLOBAL(dgebrd,DGEBRD)
+#define LAPACK_cgebrd LAPACK_GLOBAL(cgebrd,CGEBRD)
+#define LAPACK_zgebrd LAPACK_GLOBAL(zgebrd,ZGEBRD)
+#define LAPACK_sgbbrd LAPACK_GLOBAL(sgbbrd,SGBBRD)
+#define LAPACK_dgbbrd LAPACK_GLOBAL(dgbbrd,DGBBRD)
+#define LAPACK_cgbbrd LAPACK_GLOBAL(cgbbrd,CGBBRD)
+#define LAPACK_zgbbrd LAPACK_GLOBAL(zgbbrd,ZGBBRD)
+#define LAPACK_sorgbr LAPACK_GLOBAL(sorgbr,SORGBR)
+#define LAPACK_dorgbr LAPACK_GLOBAL(dorgbr,DORGBR)
+#define LAPACK_sormbr LAPACK_GLOBAL(sormbr,SORMBR)
+#define LAPACK_dormbr LAPACK_GLOBAL(dormbr,DORMBR)
+#define LAPACK_cungbr LAPACK_GLOBAL(cungbr,CUNGBR)
+#define LAPACK_zungbr LAPACK_GLOBAL(zungbr,ZUNGBR)
+#define LAPACK_cunmbr LAPACK_GLOBAL(cunmbr,CUNMBR)
+#define LAPACK_zunmbr LAPACK_GLOBAL(zunmbr,ZUNMBR)
+#define LAPACK_sbdsqr LAPACK_GLOBAL(sbdsqr,SBDSQR)
+#define LAPACK_dbdsqr LAPACK_GLOBAL(dbdsqr,DBDSQR)
+#define LAPACK_cbdsqr LAPACK_GLOBAL(cbdsqr,CBDSQR)
+#define LAPACK_zbdsqr LAPACK_GLOBAL(zbdsqr,ZBDSQR)
+#define LAPACK_sbdsdc LAPACK_GLOBAL(sbdsdc,SBDSDC)
+#define LAPACK_dbdsdc LAPACK_GLOBAL(dbdsdc,DBDSDC)
+#define LAPACK_ssytrd LAPACK_GLOBAL(ssytrd,SSYTRD)
+#define LAPACK_dsytrd LAPACK_GLOBAL(dsytrd,DSYTRD)
+#define LAPACK_sorgtr LAPACK_GLOBAL(sorgtr,SORGTR)
+#define LAPACK_dorgtr LAPACK_GLOBAL(dorgtr,DORGTR)
+#define LAPACK_sormtr LAPACK_GLOBAL(sormtr,SORMTR)
+#define LAPACK_dormtr LAPACK_GLOBAL(dormtr,DORMTR)
+#define LAPACK_chetrd LAPACK_GLOBAL(chetrd,CHETRD)
+#define LAPACK_zhetrd LAPACK_GLOBAL(zhetrd,ZHETRD)
+#define LAPACK_cungtr LAPACK_GLOBAL(cungtr,CUNGTR)
+#define LAPACK_zungtr LAPACK_GLOBAL(zungtr,ZUNGTR)
+#define LAPACK_cunmtr LAPACK_GLOBAL(cunmtr,CUNMTR)
+#define LAPACK_zunmtr LAPACK_GLOBAL(zunmtr,ZUNMTR)
+#define LAPACK_ssptrd LAPACK_GLOBAL(ssptrd,SSPTRD)
+#define LAPACK_dsptrd LAPACK_GLOBAL(dsptrd,DSPTRD)
+#define LAPACK_sopgtr LAPACK_GLOBAL(sopgtr,SOPGTR)
+#define LAPACK_dopgtr LAPACK_GLOBAL(dopgtr,DOPGTR)
+#define LAPACK_sopmtr LAPACK_GLOBAL(sopmtr,SOPMTR)
+#define LAPACK_dopmtr LAPACK_GLOBAL(dopmtr,DOPMTR)
+#define LAPACK_chptrd LAPACK_GLOBAL(chptrd,CHPTRD)
+#define LAPACK_zhptrd LAPACK_GLOBAL(zhptrd,ZHPTRD)
+#define LAPACK_cupgtr LAPACK_GLOBAL(cupgtr,CUPGTR)
+#define LAPACK_zupgtr LAPACK_GLOBAL(zupgtr,ZUPGTR)
+#define LAPACK_cupmtr LAPACK_GLOBAL(cupmtr,CUPMTR)
+#define LAPACK_zupmtr LAPACK_GLOBAL(zupmtr,ZUPMTR)
+#define LAPACK_ssbtrd LAPACK_GLOBAL(ssbtrd,SSBTRD)
+#define LAPACK_dsbtrd LAPACK_GLOBAL(dsbtrd,DSBTRD)
+#define LAPACK_chbtrd LAPACK_GLOBAL(chbtrd,CHBTRD)
+#define LAPACK_zhbtrd LAPACK_GLOBAL(zhbtrd,ZHBTRD)
+#define LAPACK_ssterf LAPACK_GLOBAL(ssterf,SSTERF)
+#define LAPACK_dsterf LAPACK_GLOBAL(dsterf,DSTERF)
+#define LAPACK_ssteqr LAPACK_GLOBAL(ssteqr,SSTEQR)
+#define LAPACK_dsteqr LAPACK_GLOBAL(dsteqr,DSTEQR)
+#define LAPACK_csteqr LAPACK_GLOBAL(csteqr,CSTEQR)
+#define LAPACK_zsteqr LAPACK_GLOBAL(zsteqr,ZSTEQR)
+#define LAPACK_sstemr LAPACK_GLOBAL(sstemr,SSTEMR)
+#define LAPACK_dstemr LAPACK_GLOBAL(dstemr,DSTEMR)
+#define LAPACK_cstemr LAPACK_GLOBAL(cstemr,CSTEMR)
+#define LAPACK_zstemr LAPACK_GLOBAL(zstemr,ZSTEMR)
+#define LAPACK_sstedc LAPACK_GLOBAL(sstedc,SSTEDC)
+#define LAPACK_dstedc LAPACK_GLOBAL(dstedc,DSTEDC)
+#define LAPACK_cstedc LAPACK_GLOBAL(cstedc,CSTEDC)
+#define LAPACK_zstedc LAPACK_GLOBAL(zstedc,ZSTEDC)
+#define LAPACK_sstegr LAPACK_GLOBAL(sstegr,SSTEGR)
+#define LAPACK_dstegr LAPACK_GLOBAL(dstegr,DSTEGR)
+#define LAPACK_cstegr LAPACK_GLOBAL(cstegr,CSTEGR)
+#define LAPACK_zstegr LAPACK_GLOBAL(zstegr,ZSTEGR)
+#define LAPACK_spteqr LAPACK_GLOBAL(spteqr,SPTEQR)
+#define LAPACK_dpteqr LAPACK_GLOBAL(dpteqr,DPTEQR)
+#define LAPACK_cpteqr LAPACK_GLOBAL(cpteqr,CPTEQR)
+#define LAPACK_zpteqr LAPACK_GLOBAL(zpteqr,ZPTEQR)
+#define LAPACK_sstebz LAPACK_GLOBAL(sstebz,SSTEBZ)
+#define LAPACK_dstebz LAPACK_GLOBAL(dstebz,DSTEBZ)
+#define LAPACK_sstein LAPACK_GLOBAL(sstein,SSTEIN)
+#define LAPACK_dstein LAPACK_GLOBAL(dstein,DSTEIN)
+#define LAPACK_cstein LAPACK_GLOBAL(cstein,CSTEIN)
+#define LAPACK_zstein LAPACK_GLOBAL(zstein,ZSTEIN)
+#define LAPACK_sdisna LAPACK_GLOBAL(sdisna,SDISNA)
+#define LAPACK_ddisna LAPACK_GLOBAL(ddisna,DDISNA)
+#define LAPACK_ssygst LAPACK_GLOBAL(ssygst,SSYGST)
+#define LAPACK_dsygst LAPACK_GLOBAL(dsygst,DSYGST)
+#define LAPACK_chegst LAPACK_GLOBAL(chegst,CHEGST)
+#define LAPACK_zhegst LAPACK_GLOBAL(zhegst,ZHEGST)
+#define LAPACK_sspgst LAPACK_GLOBAL(sspgst,SSPGST)
+#define LAPACK_dspgst LAPACK_GLOBAL(dspgst,DSPGST)
+#define LAPACK_chpgst LAPACK_GLOBAL(chpgst,CHPGST)
+#define LAPACK_zhpgst LAPACK_GLOBAL(zhpgst,ZHPGST)
+#define LAPACK_ssbgst LAPACK_GLOBAL(ssbgst,SSBGST)
+#define LAPACK_dsbgst LAPACK_GLOBAL(dsbgst,DSBGST)
+#define LAPACK_chbgst LAPACK_GLOBAL(chbgst,CHBGST)
+#define LAPACK_zhbgst LAPACK_GLOBAL(zhbgst,ZHBGST)
+#define LAPACK_spbstf LAPACK_GLOBAL(spbstf,SPBSTF)
+#define LAPACK_dpbstf LAPACK_GLOBAL(dpbstf,DPBSTF)
+#define LAPACK_cpbstf LAPACK_GLOBAL(cpbstf,CPBSTF)
+#define LAPACK_zpbstf LAPACK_GLOBAL(zpbstf,ZPBSTF)
+#define LAPACK_sgehrd LAPACK_GLOBAL(sgehrd,SGEHRD)
+#define LAPACK_dgehrd LAPACK_GLOBAL(dgehrd,DGEHRD)
+#define LAPACK_cgehrd LAPACK_GLOBAL(cgehrd,CGEHRD)
+#define LAPACK_zgehrd LAPACK_GLOBAL(zgehrd,ZGEHRD)
+#define LAPACK_sorghr LAPACK_GLOBAL(sorghr,SORGHR)
+#define LAPACK_dorghr LAPACK_GLOBAL(dorghr,DORGHR)
+#define LAPACK_sormhr LAPACK_GLOBAL(sormhr,SORMHR)
+#define LAPACK_dormhr LAPACK_GLOBAL(dormhr,DORMHR)
+#define LAPACK_cunghr LAPACK_GLOBAL(cunghr,CUNGHR)
+#define LAPACK_zunghr LAPACK_GLOBAL(zunghr,ZUNGHR)
+#define LAPACK_cunmhr LAPACK_GLOBAL(cunmhr,CUNMHR)
+#define LAPACK_zunmhr LAPACK_GLOBAL(zunmhr,ZUNMHR)
+#define LAPACK_sgebal LAPACK_GLOBAL(sgebal,SGEBAL)
+#define LAPACK_dgebal LAPACK_GLOBAL(dgebal,DGEBAL)
+#define LAPACK_cgebal LAPACK_GLOBAL(cgebal,CGEBAL)
+#define LAPACK_zgebal LAPACK_GLOBAL(zgebal,ZGEBAL)
+#define LAPACK_sgebak LAPACK_GLOBAL(sgebak,SGEBAK)
+#define LAPACK_dgebak LAPACK_GLOBAL(dgebak,DGEBAK)
+#define LAPACK_cgebak LAPACK_GLOBAL(cgebak,CGEBAK)
+#define LAPACK_zgebak LAPACK_GLOBAL(zgebak,ZGEBAK)
+#define LAPACK_shseqr LAPACK_GLOBAL(shseqr,SHSEQR)
+#define LAPACK_dhseqr LAPACK_GLOBAL(dhseqr,DHSEQR)
+#define LAPACK_chseqr LAPACK_GLOBAL(chseqr,CHSEQR)
+#define LAPACK_zhseqr LAPACK_GLOBAL(zhseqr,ZHSEQR)
+#define LAPACK_shsein LAPACK_GLOBAL(shsein,SHSEIN)
+#define LAPACK_dhsein LAPACK_GLOBAL(dhsein,DHSEIN)
+#define LAPACK_chsein LAPACK_GLOBAL(chsein,CHSEIN)
+#define LAPACK_zhsein LAPACK_GLOBAL(zhsein,ZHSEIN)
+#define LAPACK_strevc LAPACK_GLOBAL(strevc,STREVC)
+#define LAPACK_dtrevc LAPACK_GLOBAL(dtrevc,DTREVC)
+#define LAPACK_ctrevc LAPACK_GLOBAL(ctrevc,CTREVC)
+#define LAPACK_ztrevc LAPACK_GLOBAL(ztrevc,ZTREVC)
+#define LAPACK_strsna LAPACK_GLOBAL(strsna,STRSNA)
+#define LAPACK_dtrsna LAPACK_GLOBAL(dtrsna,DTRSNA)
+#define LAPACK_ctrsna LAPACK_GLOBAL(ctrsna,CTRSNA)
+#define LAPACK_ztrsna LAPACK_GLOBAL(ztrsna,ZTRSNA)
+#define LAPACK_strexc LAPACK_GLOBAL(strexc,STREXC)
+#define LAPACK_dtrexc LAPACK_GLOBAL(dtrexc,DTREXC)
+#define LAPACK_ctrexc LAPACK_GLOBAL(ctrexc,CTREXC)
+#define LAPACK_ztrexc LAPACK_GLOBAL(ztrexc,ZTREXC)
+#define LAPACK_strsen LAPACK_GLOBAL(strsen,STRSEN)
+#define LAPACK_dtrsen LAPACK_GLOBAL(dtrsen,DTRSEN)
+#define LAPACK_ctrsen LAPACK_GLOBAL(ctrsen,CTRSEN)
+#define LAPACK_ztrsen LAPACK_GLOBAL(ztrsen,ZTRSEN)
+#define LAPACK_strsyl LAPACK_GLOBAL(strsyl,STRSYL)
+#define LAPACK_dtrsyl LAPACK_GLOBAL(dtrsyl,DTRSYL)
+#define LAPACK_ctrsyl LAPACK_GLOBAL(ctrsyl,CTRSYL)
+#define LAPACK_ztrsyl LAPACK_GLOBAL(ztrsyl,ZTRSYL)
+#define LAPACK_sgghrd LAPACK_GLOBAL(sgghrd,SGGHRD)
+#define LAPACK_dgghrd LAPACK_GLOBAL(dgghrd,DGGHRD)
+#define LAPACK_cgghrd LAPACK_GLOBAL(cgghrd,CGGHRD)
+#define LAPACK_zgghrd LAPACK_GLOBAL(zgghrd,ZGGHRD)
+#define LAPACK_sggbal LAPACK_GLOBAL(sggbal,SGGBAL)
+#define LAPACK_dggbal LAPACK_GLOBAL(dggbal,DGGBAL)
+#define LAPACK_cggbal LAPACK_GLOBAL(cggbal,CGGBAL)
+#define LAPACK_zggbal LAPACK_GLOBAL(zggbal,ZGGBAL)
+#define LAPACK_sggbak LAPACK_GLOBAL(sggbak,SGGBAK)
+#define LAPACK_dggbak LAPACK_GLOBAL(dggbak,DGGBAK)
+#define LAPACK_cggbak LAPACK_GLOBAL(cggbak,CGGBAK)
+#define LAPACK_zggbak LAPACK_GLOBAL(zggbak,ZGGBAK)
+#define LAPACK_shgeqz LAPACK_GLOBAL(shgeqz,SHGEQZ)
+#define LAPACK_dhgeqz LAPACK_GLOBAL(dhgeqz,DHGEQZ)
+#define LAPACK_chgeqz LAPACK_GLOBAL(chgeqz,CHGEQZ)
+#define LAPACK_zhgeqz LAPACK_GLOBAL(zhgeqz,ZHGEQZ)
+#define LAPACK_stgevc LAPACK_GLOBAL(stgevc,STGEVC)
+#define LAPACK_dtgevc LAPACK_GLOBAL(dtgevc,DTGEVC)
+#define LAPACK_ctgevc LAPACK_GLOBAL(ctgevc,CTGEVC)
+#define LAPACK_ztgevc LAPACK_GLOBAL(ztgevc,ZTGEVC)
+#define LAPACK_stgexc LAPACK_GLOBAL(stgexc,STGEXC)
+#define LAPACK_dtgexc LAPACK_GLOBAL(dtgexc,DTGEXC)
+#define LAPACK_ctgexc LAPACK_GLOBAL(ctgexc,CTGEXC)
+#define LAPACK_ztgexc LAPACK_GLOBAL(ztgexc,ZTGEXC)
+#define LAPACK_stgsen LAPACK_GLOBAL(stgsen,STGSEN)
+#define LAPACK_dtgsen LAPACK_GLOBAL(dtgsen,DTGSEN)
+#define LAPACK_ctgsen LAPACK_GLOBAL(ctgsen,CTGSEN)
+#define LAPACK_ztgsen LAPACK_GLOBAL(ztgsen,ZTGSEN)
+#define LAPACK_stgsyl LAPACK_GLOBAL(stgsyl,STGSYL)
+#define LAPACK_dtgsyl LAPACK_GLOBAL(dtgsyl,DTGSYL)
+#define LAPACK_ctgsyl LAPACK_GLOBAL(ctgsyl,CTGSYL)
+#define LAPACK_ztgsyl LAPACK_GLOBAL(ztgsyl,ZTGSYL)
+#define LAPACK_stgsna LAPACK_GLOBAL(stgsna,STGSNA)
+#define LAPACK_dtgsna LAPACK_GLOBAL(dtgsna,DTGSNA)
+#define LAPACK_ctgsna LAPACK_GLOBAL(ctgsna,CTGSNA)
+#define LAPACK_ztgsna LAPACK_GLOBAL(ztgsna,ZTGSNA)
+#define LAPACK_sggsvp LAPACK_GLOBAL(sggsvp,SGGSVP)
+#define LAPACK_dggsvp LAPACK_GLOBAL(dggsvp,DGGSVP)
+#define LAPACK_cggsvp LAPACK_GLOBAL(cggsvp,CGGSVP)
+#define LAPACK_zggsvp LAPACK_GLOBAL(zggsvp,ZGGSVP)
+#define LAPACK_stgsja LAPACK_GLOBAL(stgsja,STGSJA)
+#define LAPACK_dtgsja LAPACK_GLOBAL(dtgsja,DTGSJA)
+#define LAPACK_ctgsja LAPACK_GLOBAL(ctgsja,CTGSJA)
+#define LAPACK_ztgsja LAPACK_GLOBAL(ztgsja,ZTGSJA)
+#define LAPACK_sgels LAPACK_GLOBAL(sgels,SGELS)
+#define LAPACK_dgels LAPACK_GLOBAL(dgels,DGELS)
+#define LAPACK_cgels LAPACK_GLOBAL(cgels,CGELS)
+#define LAPACK_zgels LAPACK_GLOBAL(zgels,ZGELS)
+#define LAPACK_sgelsy LAPACK_GLOBAL(sgelsy,SGELSY)
+#define LAPACK_dgelsy LAPACK_GLOBAL(dgelsy,DGELSY)
+#define LAPACK_cgelsy LAPACK_GLOBAL(cgelsy,CGELSY)
+#define LAPACK_zgelsy LAPACK_GLOBAL(zgelsy,ZGELSY)
+#define LAPACK_sgelss LAPACK_GLOBAL(sgelss,SGELSS)
+#define LAPACK_dgelss LAPACK_GLOBAL(dgelss,DGELSS)
+#define LAPACK_cgelss LAPACK_GLOBAL(cgelss,CGELSS)
+#define LAPACK_zgelss LAPACK_GLOBAL(zgelss,ZGELSS)
+#define LAPACK_sgelsd LAPACK_GLOBAL(sgelsd,SGELSD)
+#define LAPACK_dgelsd LAPACK_GLOBAL(dgelsd,DGELSD)
+#define LAPACK_cgelsd LAPACK_GLOBAL(cgelsd,CGELSD)
+#define LAPACK_zgelsd LAPACK_GLOBAL(zgelsd,ZGELSD)
+#define LAPACK_sgglse LAPACK_GLOBAL(sgglse,SGGLSE)
+#define LAPACK_dgglse LAPACK_GLOBAL(dgglse,DGGLSE)
+#define LAPACK_cgglse LAPACK_GLOBAL(cgglse,CGGLSE)
+#define LAPACK_zgglse LAPACK_GLOBAL(zgglse,ZGGLSE)
+#define LAPACK_sggglm LAPACK_GLOBAL(sggglm,SGGGLM)
+#define LAPACK_dggglm LAPACK_GLOBAL(dggglm,DGGGLM)
+#define LAPACK_cggglm LAPACK_GLOBAL(cggglm,CGGGLM)
+#define LAPACK_zggglm LAPACK_GLOBAL(zggglm,ZGGGLM)
+#define LAPACK_ssyev LAPACK_GLOBAL(ssyev,SSYEV)
+#define LAPACK_dsyev LAPACK_GLOBAL(dsyev,DSYEV)
+#define LAPACK_cheev LAPACK_GLOBAL(cheev,CHEEV)
+#define LAPACK_zheev LAPACK_GLOBAL(zheev,ZHEEV)
+#define LAPACK_ssyevd LAPACK_GLOBAL(ssyevd,SSYEVD)
+#define LAPACK_dsyevd LAPACK_GLOBAL(dsyevd,DSYEVD)
+#define LAPACK_cheevd LAPACK_GLOBAL(cheevd,CHEEVD)
+#define LAPACK_zheevd LAPACK_GLOBAL(zheevd,ZHEEVD)
+#define LAPACK_ssyevx LAPACK_GLOBAL(ssyevx,SSYEVX)
+#define LAPACK_dsyevx LAPACK_GLOBAL(dsyevx,DSYEVX)
+#define LAPACK_cheevx LAPACK_GLOBAL(cheevx,CHEEVX)
+#define LAPACK_zheevx LAPACK_GLOBAL(zheevx,ZHEEVX)
+#define LAPACK_ssyevr LAPACK_GLOBAL(ssyevr,SSYEVR)
+#define LAPACK_dsyevr LAPACK_GLOBAL(dsyevr,DSYEVR)
+#define LAPACK_cheevr LAPACK_GLOBAL(cheevr,CHEEVR)
+#define LAPACK_zheevr LAPACK_GLOBAL(zheevr,ZHEEVR)
+#define LAPACK_sspev LAPACK_GLOBAL(sspev,SSPEV)
+#define LAPACK_dspev LAPACK_GLOBAL(dspev,DSPEV)
+#define LAPACK_chpev LAPACK_GLOBAL(chpev,CHPEV)
+#define LAPACK_zhpev LAPACK_GLOBAL(zhpev,ZHPEV)
+#define LAPACK_sspevd LAPACK_GLOBAL(sspevd,SSPEVD)
+#define LAPACK_dspevd LAPACK_GLOBAL(dspevd,DSPEVD)
+#define LAPACK_chpevd LAPACK_GLOBAL(chpevd,CHPEVD)
+#define LAPACK_zhpevd LAPACK_GLOBAL(zhpevd,ZHPEVD)
+#define LAPACK_sspevx LAPACK_GLOBAL(sspevx,SSPEVX)
+#define LAPACK_dspevx LAPACK_GLOBAL(dspevx,DSPEVX)
+#define LAPACK_chpevx LAPACK_GLOBAL(chpevx,CHPEVX)
+#define LAPACK_zhpevx LAPACK_GLOBAL(zhpevx,ZHPEVX)
+#define LAPACK_ssbev LAPACK_GLOBAL(ssbev,SSBEV)
+#define LAPACK_dsbev LAPACK_GLOBAL(dsbev,DSBEV)
+#define LAPACK_chbev LAPACK_GLOBAL(chbev,CHBEV)
+#define LAPACK_zhbev LAPACK_GLOBAL(zhbev,ZHBEV)
+#define LAPACK_ssbevd LAPACK_GLOBAL(ssbevd,SSBEVD)
+#define LAPACK_dsbevd LAPACK_GLOBAL(dsbevd,DSBEVD)
+#define LAPACK_chbevd LAPACK_GLOBAL(chbevd,CHBEVD)
+#define LAPACK_zhbevd LAPACK_GLOBAL(zhbevd,ZHBEVD)
+#define LAPACK_ssbevx LAPACK_GLOBAL(ssbevx,SSBEVX)
+#define LAPACK_dsbevx LAPACK_GLOBAL(dsbevx,DSBEVX)
+#define LAPACK_chbevx LAPACK_GLOBAL(chbevx,CHBEVX)
+#define LAPACK_zhbevx LAPACK_GLOBAL(zhbevx,ZHBEVX)
+#define LAPACK_sstev LAPACK_GLOBAL(sstev,SSTEV)
+#define LAPACK_dstev LAPACK_GLOBAL(dstev,DSTEV)
+#define LAPACK_sstevd LAPACK_GLOBAL(sstevd,SSTEVD)
+#define LAPACK_dstevd LAPACK_GLOBAL(dstevd,DSTEVD)
+#define LAPACK_sstevx LAPACK_GLOBAL(sstevx,SSTEVX)
+#define LAPACK_dstevx LAPACK_GLOBAL(dstevx,DSTEVX)
+#define LAPACK_sstevr LAPACK_GLOBAL(sstevr,SSTEVR)
+#define LAPACK_dstevr LAPACK_GLOBAL(dstevr,DSTEVR)
+#define LAPACK_sgees LAPACK_GLOBAL(sgees,SGEES)
+#define LAPACK_dgees LAPACK_GLOBAL(dgees,DGEES)
+#define LAPACK_cgees LAPACK_GLOBAL(cgees,CGEES)
+#define LAPACK_zgees LAPACK_GLOBAL(zgees,ZGEES)
+#define LAPACK_sgeesx LAPACK_GLOBAL(sgeesx,SGEESX)
+#define LAPACK_dgeesx LAPACK_GLOBAL(dgeesx,DGEESX)
+#define LAPACK_cgeesx LAPACK_GLOBAL(cgeesx,CGEESX)
+#define LAPACK_zgeesx LAPACK_GLOBAL(zgeesx,ZGEESX)
+#define LAPACK_sgeev LAPACK_GLOBAL(sgeev,SGEEV)
+#define LAPACK_dgeev LAPACK_GLOBAL(dgeev,DGEEV)
+#define LAPACK_cgeev LAPACK_GLOBAL(cgeev,CGEEV)
+#define LAPACK_zgeev LAPACK_GLOBAL(zgeev,ZGEEV)
+#define LAPACK_sgeevx LAPACK_GLOBAL(sgeevx,SGEEVX)
+#define LAPACK_dgeevx LAPACK_GLOBAL(dgeevx,DGEEVX)
+#define LAPACK_cgeevx LAPACK_GLOBAL(cgeevx,CGEEVX)
+#define LAPACK_zgeevx LAPACK_GLOBAL(zgeevx,ZGEEVX)
+#define LAPACK_sgesvd LAPACK_GLOBAL(sgesvd,SGESVD)
+#define LAPACK_dgesvd LAPACK_GLOBAL(dgesvd,DGESVD)
+#define LAPACK_cgesvd LAPACK_GLOBAL(cgesvd,CGESVD)
+#define LAPACK_zgesvd LAPACK_GLOBAL(zgesvd,ZGESVD)
+#define LAPACK_sgesdd LAPACK_GLOBAL(sgesdd,SGESDD)
+#define LAPACK_dgesdd LAPACK_GLOBAL(dgesdd,DGESDD)
+#define LAPACK_cgesdd LAPACK_GLOBAL(cgesdd,CGESDD)
+#define LAPACK_zgesdd LAPACK_GLOBAL(zgesdd,ZGESDD)
+#define LAPACK_dgejsv LAPACK_GLOBAL(dgejsv,DGEJSV)
+#define LAPACK_sgejsv LAPACK_GLOBAL(sgejsv,SGEJSV)
+#define LAPACK_dgesvj LAPACK_GLOBAL(dgesvj,DGESVJ)
+#define LAPACK_sgesvj LAPACK_GLOBAL(sgesvj,SGESVJ)
+#define LAPACK_sggsvd LAPACK_GLOBAL(sggsvd,SGGSVD)
+#define LAPACK_dggsvd LAPACK_GLOBAL(dggsvd,DGGSVD)
+#define LAPACK_cggsvd LAPACK_GLOBAL(cggsvd,CGGSVD)
+#define LAPACK_zggsvd LAPACK_GLOBAL(zggsvd,ZGGSVD)
+#define LAPACK_ssygv LAPACK_GLOBAL(ssygv,SSYGV)
+#define LAPACK_dsygv LAPACK_GLOBAL(dsygv,DSYGV)
+#define LAPACK_chegv LAPACK_GLOBAL(chegv,CHEGV)
+#define LAPACK_zhegv LAPACK_GLOBAL(zhegv,ZHEGV)
+#define LAPACK_ssygvd LAPACK_GLOBAL(ssygvd,SSYGVD)
+#define LAPACK_dsygvd LAPACK_GLOBAL(dsygvd,DSYGVD)
+#define LAPACK_chegvd LAPACK_GLOBAL(chegvd,CHEGVD)
+#define LAPACK_zhegvd LAPACK_GLOBAL(zhegvd,ZHEGVD)
+#define LAPACK_ssygvx LAPACK_GLOBAL(ssygvx,SSYGVX)
+#define LAPACK_dsygvx LAPACK_GLOBAL(dsygvx,DSYGVX)
+#define LAPACK_chegvx LAPACK_GLOBAL(chegvx,CHEGVX)
+#define LAPACK_zhegvx LAPACK_GLOBAL(zhegvx,ZHEGVX)
+#define LAPACK_sspgv LAPACK_GLOBAL(sspgv,SSPGV)
+#define LAPACK_dspgv LAPACK_GLOBAL(dspgv,DSPGV)
+#define LAPACK_chpgv LAPACK_GLOBAL(chpgv,CHPGV)
+#define LAPACK_zhpgv LAPACK_GLOBAL(zhpgv,ZHPGV)
+#define LAPACK_sspgvd LAPACK_GLOBAL(sspgvd,SSPGVD)
+#define LAPACK_dspgvd LAPACK_GLOBAL(dspgvd,DSPGVD)
+#define LAPACK_chpgvd LAPACK_GLOBAL(chpgvd,CHPGVD)
+#define LAPACK_zhpgvd LAPACK_GLOBAL(zhpgvd,ZHPGVD)
+#define LAPACK_sspgvx LAPACK_GLOBAL(sspgvx,SSPGVX)
+#define LAPACK_dspgvx LAPACK_GLOBAL(dspgvx,DSPGVX)
+#define LAPACK_chpgvx LAPACK_GLOBAL(chpgvx,CHPGVX)
+#define LAPACK_zhpgvx LAPACK_GLOBAL(zhpgvx,ZHPGVX)
+#define LAPACK_ssbgv LAPACK_GLOBAL(ssbgv,SSBGV)
+#define LAPACK_dsbgv LAPACK_GLOBAL(dsbgv,DSBGV)
+#define LAPACK_chbgv LAPACK_GLOBAL(chbgv,CHBGV)
+#define LAPACK_zhbgv LAPACK_GLOBAL(zhbgv,ZHBGV)
+#define LAPACK_ssbgvd LAPACK_GLOBAL(ssbgvd,SSBGVD)
+#define LAPACK_dsbgvd LAPACK_GLOBAL(dsbgvd,DSBGVD)
+#define LAPACK_chbgvd LAPACK_GLOBAL(chbgvd,CHBGVD)
+#define LAPACK_zhbgvd LAPACK_GLOBAL(zhbgvd,ZHBGVD)
+#define LAPACK_ssbgvx LAPACK_GLOBAL(ssbgvx,SSBGVX)
+#define LAPACK_dsbgvx LAPACK_GLOBAL(dsbgvx,DSBGVX)
+#define LAPACK_chbgvx LAPACK_GLOBAL(chbgvx,CHBGVX)
+#define LAPACK_zhbgvx LAPACK_GLOBAL(zhbgvx,ZHBGVX)
+#define LAPACK_sgges LAPACK_GLOBAL(sgges,SGGES)
+#define LAPACK_dgges LAPACK_GLOBAL(dgges,DGGES)
+#define LAPACK_cgges LAPACK_GLOBAL(cgges,CGGES)
+#define LAPACK_zgges LAPACK_GLOBAL(zgges,ZGGES)
+#define LAPACK_sggesx LAPACK_GLOBAL(sggesx,SGGESX)
+#define LAPACK_dggesx LAPACK_GLOBAL(dggesx,DGGESX)
+#define LAPACK_cggesx LAPACK_GLOBAL(cggesx,CGGESX)
+#define LAPACK_zggesx LAPACK_GLOBAL(zggesx,ZGGESX)
+#define LAPACK_sggev LAPACK_GLOBAL(sggev,SGGEV)
+#define LAPACK_dggev LAPACK_GLOBAL(dggev,DGGEV)
+#define LAPACK_cggev LAPACK_GLOBAL(cggev,CGGEV)
+#define LAPACK_zggev LAPACK_GLOBAL(zggev,ZGGEV)
+#define LAPACK_sggevx LAPACK_GLOBAL(sggevx,SGGEVX)
+#define LAPACK_dggevx LAPACK_GLOBAL(dggevx,DGGEVX)
+#define LAPACK_cggevx LAPACK_GLOBAL(cggevx,CGGEVX)
+#define LAPACK_zggevx LAPACK_GLOBAL(zggevx,ZGGEVX)
+#define LAPACK_dsfrk LAPACK_GLOBAL(dsfrk,DSFRK)
+#define LAPACK_ssfrk LAPACK_GLOBAL(ssfrk,SSFRK)
+#define LAPACK_zhfrk LAPACK_GLOBAL(zhfrk,ZHFRK)
+#define LAPACK_chfrk LAPACK_GLOBAL(chfrk,CHFRK)
+#define LAPACK_dtfsm LAPACK_GLOBAL(dtfsm,DTFSM)
+#define LAPACK_stfsm LAPACK_GLOBAL(stfsm,STFSM)
+#define LAPACK_ztfsm LAPACK_GLOBAL(ztfsm,ZTFSM)
+#define LAPACK_ctfsm LAPACK_GLOBAL(ctfsm,CTFSM)
+#define LAPACK_dtfttp LAPACK_GLOBAL(dtfttp,DTFTTP)
+#define LAPACK_stfttp LAPACK_GLOBAL(stfttp,STFTTP)
+#define LAPACK_ztfttp LAPACK_GLOBAL(ztfttp,ZTFTTP)
+#define LAPACK_ctfttp LAPACK_GLOBAL(ctfttp,CTFTTP)
+#define LAPACK_dtfttr LAPACK_GLOBAL(dtfttr,DTFTTR)
+#define LAPACK_stfttr LAPACK_GLOBAL(stfttr,STFTTR)
+#define LAPACK_ztfttr LAPACK_GLOBAL(ztfttr,ZTFTTR)
+#define LAPACK_ctfttr LAPACK_GLOBAL(ctfttr,CTFTTR)
+#define LAPACK_dtpttf LAPACK_GLOBAL(dtpttf,DTPTTF)
+#define LAPACK_stpttf LAPACK_GLOBAL(stpttf,STPTTF)
+#define LAPACK_ztpttf LAPACK_GLOBAL(ztpttf,ZTPTTF)
+#define LAPACK_ctpttf LAPACK_GLOBAL(ctpttf,CTPTTF)
+#define LAPACK_dtpttr LAPACK_GLOBAL(dtpttr,DTPTTR)
+#define LAPACK_stpttr LAPACK_GLOBAL(stpttr,STPTTR)
+#define LAPACK_ztpttr LAPACK_GLOBAL(ztpttr,ZTPTTR)
+#define LAPACK_ctpttr LAPACK_GLOBAL(ctpttr,CTPTTR)
+#define LAPACK_dtrttf LAPACK_GLOBAL(dtrttf,DTRTTF)
+#define LAPACK_strttf LAPACK_GLOBAL(strttf,STRTTF)
+#define LAPACK_ztrttf LAPACK_GLOBAL(ztrttf,ZTRTTF)
+#define LAPACK_ctrttf LAPACK_GLOBAL(ctrttf,CTRTTF)
+#define LAPACK_dtrttp LAPACK_GLOBAL(dtrttp,DTRTTP)
+#define LAPACK_strttp LAPACK_GLOBAL(strttp,STRTTP)
+#define LAPACK_ztrttp LAPACK_GLOBAL(ztrttp,ZTRTTP)
+#define LAPACK_ctrttp LAPACK_GLOBAL(ctrttp,CTRTTP)
+#define LAPACK_sgeqrfp LAPACK_GLOBAL(sgeqrfp,SGEQRFP)
+#define LAPACK_dgeqrfp LAPACK_GLOBAL(dgeqrfp,DGEQRFP)
+#define LAPACK_cgeqrfp LAPACK_GLOBAL(cgeqrfp,CGEQRFP)
+#define LAPACK_zgeqrfp LAPACK_GLOBAL(zgeqrfp,ZGEQRFP)
+#define LAPACK_clacgv LAPACK_GLOBAL(clacgv,CLACGV)
+#define LAPACK_zlacgv LAPACK_GLOBAL(zlacgv,ZLACGV)
+#define LAPACK_slarnv LAPACK_GLOBAL(slarnv,SLARNV)
+#define LAPACK_dlarnv LAPACK_GLOBAL(dlarnv,DLARNV)
+#define LAPACK_clarnv LAPACK_GLOBAL(clarnv,CLARNV)
+#define LAPACK_zlarnv LAPACK_GLOBAL(zlarnv,ZLARNV)
+#define LAPACK_sgeqr2 LAPACK_GLOBAL(sgeqr2,SGEQR2)
+#define LAPACK_dgeqr2 LAPACK_GLOBAL(dgeqr2,DGEQR2)
+#define LAPACK_cgeqr2 LAPACK_GLOBAL(cgeqr2,CGEQR2)
+#define LAPACK_zgeqr2 LAPACK_GLOBAL(zgeqr2,ZGEQR2)
+#define LAPACK_slacpy LAPACK_GLOBAL(slacpy,SLACPY)
+#define LAPACK_dlacpy LAPACK_GLOBAL(dlacpy,DLACPY)
+#define LAPACK_clacpy LAPACK_GLOBAL(clacpy,CLACPY)
+#define LAPACK_zlacpy LAPACK_GLOBAL(zlacpy,ZLACPY)
+#define LAPACK_sgetf2 LAPACK_GLOBAL(sgetf2,SGETF2)
+#define LAPACK_dgetf2 LAPACK_GLOBAL(dgetf2,DGETF2)
+#define LAPACK_cgetf2 LAPACK_GLOBAL(cgetf2,CGETF2)
+#define LAPACK_zgetf2 LAPACK_GLOBAL(zgetf2,ZGETF2)
+#define LAPACK_slaswp LAPACK_GLOBAL(slaswp,SLASWP)
+#define LAPACK_dlaswp LAPACK_GLOBAL(dlaswp,DLASWP)
+#define LAPACK_claswp LAPACK_GLOBAL(claswp,CLASWP)
+#define LAPACK_zlaswp LAPACK_GLOBAL(zlaswp,ZLASWP)
+#define LAPACK_slange LAPACK_GLOBAL(slange,SLANGE)
+#define LAPACK_dlange LAPACK_GLOBAL(dlange,DLANGE)
+#define LAPACK_clange LAPACK_GLOBAL(clange,CLANGE)
+#define LAPACK_zlange LAPACK_GLOBAL(zlange,ZLANGE)
+#define LAPACK_clanhe LAPACK_GLOBAL(clanhe,CLANHE)
+#define LAPACK_zlanhe LAPACK_GLOBAL(zlanhe,ZLANHE)
+#define LAPACK_slansy LAPACK_GLOBAL(slansy,SLANSY)
+#define LAPACK_dlansy LAPACK_GLOBAL(dlansy,DLANSY)
+#define LAPACK_clansy LAPACK_GLOBAL(clansy,CLANSY)
+#define LAPACK_zlansy LAPACK_GLOBAL(zlansy,ZLANSY)
+#define LAPACK_slantr LAPACK_GLOBAL(slantr,SLANTR)
+#define LAPACK_dlantr LAPACK_GLOBAL(dlantr,DLANTR)
+#define LAPACK_clantr LAPACK_GLOBAL(clantr,CLANTR)
+#define LAPACK_zlantr LAPACK_GLOBAL(zlantr,ZLANTR)
+#define LAPACK_slamch LAPACK_GLOBAL(slamch,SLAMCH)
+#define LAPACK_dlamch LAPACK_GLOBAL(dlamch,DLAMCH)
+#define LAPACK_sgelq2 LAPACK_GLOBAL(sgelq2,SGELQ2)
+#define LAPACK_dgelq2 LAPACK_GLOBAL(dgelq2,DGELQ2)
+#define LAPACK_cgelq2 LAPACK_GLOBAL(cgelq2,CGELQ2)
+#define LAPACK_zgelq2 LAPACK_GLOBAL(zgelq2,ZGELQ2)
+#define LAPACK_slarfb LAPACK_GLOBAL(slarfb,SLARFB)
+#define LAPACK_dlarfb LAPACK_GLOBAL(dlarfb,DLARFB)
+#define LAPACK_clarfb LAPACK_GLOBAL(clarfb,CLARFB)
+#define LAPACK_zlarfb LAPACK_GLOBAL(zlarfb,ZLARFB)
+#define LAPACK_slarfg LAPACK_GLOBAL(slarfg,SLARFG)
+#define LAPACK_dlarfg LAPACK_GLOBAL(dlarfg,DLARFG)
+#define LAPACK_clarfg LAPACK_GLOBAL(clarfg,CLARFG)
+#define LAPACK_zlarfg LAPACK_GLOBAL(zlarfg,ZLARFG)
+#define LAPACK_slarft LAPACK_GLOBAL(slarft,SLARFT)
+#define LAPACK_dlarft LAPACK_GLOBAL(dlarft,DLARFT)
+#define LAPACK_clarft LAPACK_GLOBAL(clarft,CLARFT)
+#define LAPACK_zlarft LAPACK_GLOBAL(zlarft,ZLARFT)
+#define LAPACK_slarfx LAPACK_GLOBAL(slarfx,SLARFX)
+#define LAPACK_dlarfx LAPACK_GLOBAL(dlarfx,DLARFX)
+#define LAPACK_clarfx LAPACK_GLOBAL(clarfx,CLARFX)
+#define LAPACK_zlarfx LAPACK_GLOBAL(zlarfx,ZLARFX)
+#define LAPACK_slatms LAPACK_GLOBAL(slatms,SLATMS)
+#define LAPACK_dlatms LAPACK_GLOBAL(dlatms,DLATMS)
+#define LAPACK_clatms LAPACK_GLOBAL(clatms,CLATMS)
+#define LAPACK_zlatms LAPACK_GLOBAL(zlatms,ZLATMS)
+#define LAPACK_slag2d LAPACK_GLOBAL(slag2d,SLAG2D)
+#define LAPACK_dlag2s LAPACK_GLOBAL(dlag2s,DLAG2S)
+#define LAPACK_clag2z LAPACK_GLOBAL(clag2z,CLAG2Z)
+#define LAPACK_zlag2c LAPACK_GLOBAL(zlag2c,ZLAG2C)
+#define LAPACK_slauum LAPACK_GLOBAL(slauum,SLAUUM)
+#define LAPACK_dlauum LAPACK_GLOBAL(dlauum,DLAUUM)
+#define LAPACK_clauum LAPACK_GLOBAL(clauum,CLAUUM)
+#define LAPACK_zlauum LAPACK_GLOBAL(zlauum,ZLAUUM)
+#define LAPACK_slagge LAPACK_GLOBAL(slagge,SLAGGE)
+#define LAPACK_dlagge LAPACK_GLOBAL(dlagge,DLAGGE)
+#define LAPACK_clagge LAPACK_GLOBAL(clagge,CLAGGE)
+#define LAPACK_zlagge LAPACK_GLOBAL(zlagge,ZLAGGE)
+#define LAPACK_slaset LAPACK_GLOBAL(slaset,SLASET)
+#define LAPACK_dlaset LAPACK_GLOBAL(dlaset,DLASET)
+#define LAPACK_claset LAPACK_GLOBAL(claset,CLASET)
+#define LAPACK_zlaset LAPACK_GLOBAL(zlaset,ZLASET)
+#define LAPACK_slasrt LAPACK_GLOBAL(slasrt,SLASRT)
+#define LAPACK_dlasrt LAPACK_GLOBAL(dlasrt,DLASRT)
+#define LAPACK_slagsy LAPACK_GLOBAL(slagsy,SLAGSY)
+#define LAPACK_dlagsy LAPACK_GLOBAL(dlagsy,DLAGSY)
+#define LAPACK_clagsy LAPACK_GLOBAL(clagsy,CLAGSY)
+#define LAPACK_zlagsy LAPACK_GLOBAL(zlagsy,ZLAGSY)
+#define LAPACK_claghe LAPACK_GLOBAL(claghe,CLAGHE)
+#define LAPACK_zlaghe LAPACK_GLOBAL(zlaghe,ZLAGHE)
+#define LAPACK_slapmr LAPACK_GLOBAL(slapmr,SLAPMR)
+#define LAPACK_dlapmr LAPACK_GLOBAL(dlapmr,DLAPMR)
+#define LAPACK_clapmr LAPACK_GLOBAL(clapmr,CLAPMR)
+#define LAPACK_zlapmr LAPACK_GLOBAL(zlapmr,ZLAPMR)
+#define LAPACK_slapy2 LAPACK_GLOBAL(slapy2,SLAPY2)
+#define LAPACK_dlapy2 LAPACK_GLOBAL(dlapy2,DLAPY2)
+#define LAPACK_slapy3 LAPACK_GLOBAL(slapy3,SLAPY3)
+#define LAPACK_dlapy3 LAPACK_GLOBAL(dlapy3,DLAPY3)
+#define LAPACK_slartgp LAPACK_GLOBAL(slartgp,SLARTGP)
+#define LAPACK_dlartgp LAPACK_GLOBAL(dlartgp,DLARTGP)
+#define LAPACK_slartgs LAPACK_GLOBAL(slartgs,SLARTGS)
+#define LAPACK_dlartgs LAPACK_GLOBAL(dlartgs,DLARTGS)
+// LAPACK 3.3.0
+#define LAPACK_cbbcsd LAPACK_GLOBAL(cbbcsd,CBBCSD)
+#define LAPACK_cheswapr LAPACK_GLOBAL(cheswapr,CHESWAPR)
+#define LAPACK_chetri2 LAPACK_GLOBAL(chetri2,CHETRI2)
+#define LAPACK_chetri2x LAPACK_GLOBAL(chetri2x,CHETRI2X)
+#define LAPACK_chetrs2 LAPACK_GLOBAL(chetrs2,CHETRS2)
+#define LAPACK_csyconv LAPACK_GLOBAL(csyconv,CSYCONV)
+#define LAPACK_csyswapr LAPACK_GLOBAL(csyswapr,CSYSWAPR)
+#define LAPACK_csytri2 LAPACK_GLOBAL(csytri2,CSYTRI2)
+#define LAPACK_csytri2x LAPACK_GLOBAL(csytri2x,CSYTRI2X)
+#define LAPACK_csytrs2 LAPACK_GLOBAL(csytrs2,CSYTRS2)
+#define LAPACK_cunbdb LAPACK_GLOBAL(cunbdb,CUNBDB)
+#define LAPACK_cuncsd LAPACK_GLOBAL(cuncsd,CUNCSD)
+#define LAPACK_dbbcsd LAPACK_GLOBAL(dbbcsd,DBBCSD)
+#define LAPACK_dorbdb LAPACK_GLOBAL(dorbdb,DORBDB)
+#define LAPACK_dorcsd LAPACK_GLOBAL(dorcsd,DORCSD)
+#define LAPACK_dsyconv LAPACK_GLOBAL(dsyconv,DSYCONV)
+#define LAPACK_dsyswapr LAPACK_GLOBAL(dsyswapr,DSYSWAPR)
+#define LAPACK_dsytri2 LAPACK_GLOBAL(dsytri2,DSYTRI2)
+#define LAPACK_dsytri2x LAPACK_GLOBAL(dsytri2x,DSYTRI2X)
+#define LAPACK_dsytrs2 LAPACK_GLOBAL(dsytrs2,DSYTRS2)
+#define LAPACK_sbbcsd LAPACK_GLOBAL(sbbcsd,SBBCSD)
+#define LAPACK_sorbdb LAPACK_GLOBAL(sorbdb,SORBDB)
+#define LAPACK_sorcsd LAPACK_GLOBAL(sorcsd,SORCSD)
+#define LAPACK_ssyconv LAPACK_GLOBAL(ssyconv,SSYCONV)
+#define LAPACK_ssyswapr LAPACK_GLOBAL(ssyswapr,SSYSWAPR)
+#define LAPACK_ssytri2 LAPACK_GLOBAL(ssytri2,SSYTRI2)
+#define LAPACK_ssytri2x LAPACK_GLOBAL(ssytri2x,SSYTRI2X)
+#define LAPACK_ssytrs2 LAPACK_GLOBAL(ssytrs2,SSYTRS2)
+#define LAPACK_zbbcsd LAPACK_GLOBAL(zbbcsd,ZBBCSD)
+#define LAPACK_zheswapr LAPACK_GLOBAL(zheswapr,ZHESWAPR)
+#define LAPACK_zhetri2 LAPACK_GLOBAL(zhetri2,ZHETRI2)
+#define LAPACK_zhetri2x LAPACK_GLOBAL(zhetri2x,ZHETRI2X)
+#define LAPACK_zhetrs2 LAPACK_GLOBAL(zhetrs2,ZHETRS2)
+#define LAPACK_zsyconv LAPACK_GLOBAL(zsyconv,ZSYCONV)
+#define LAPACK_zsyswapr LAPACK_GLOBAL(zsyswapr,ZSYSWAPR)
+#define LAPACK_zsytri2 LAPACK_GLOBAL(zsytri2,ZSYTRI2)
+#define LAPACK_zsytri2x LAPACK_GLOBAL(zsytri2x,ZSYTRI2X)
+#define LAPACK_zsytrs2 LAPACK_GLOBAL(zsytrs2,ZSYTRS2)
+#define LAPACK_zunbdb LAPACK_GLOBAL(zunbdb,ZUNBDB)
+#define LAPACK_zuncsd LAPACK_GLOBAL(zuncsd,ZUNCSD)
+// LAPACK 3.4.0
+#define LAPACK_sgemqrt LAPACK_GLOBAL(sgemqrt,SGEMQRT)
+#define LAPACK_dgemqrt LAPACK_GLOBAL(dgemqrt,DGEMQRT)
+#define LAPACK_cgemqrt LAPACK_GLOBAL(cgemqrt,CGEMQRT)
+#define LAPACK_zgemqrt LAPACK_GLOBAL(zgemqrt,ZGEMQRT)
+#define LAPACK_sgeqrt LAPACK_GLOBAL(sgeqrt,SGEQRT)
+#define LAPACK_dgeqrt LAPACK_GLOBAL(dgeqrt,DGEQRT)
+#define LAPACK_cgeqrt LAPACK_GLOBAL(cgeqrt,CGEQRT)
+#define LAPACK_zgeqrt LAPACK_GLOBAL(zgeqrt,ZGEQRT)
+#define LAPACK_sgeqrt2 LAPACK_GLOBAL(sgeqrt2,SGEQRT2)
+#define LAPACK_dgeqrt2 LAPACK_GLOBAL(dgeqrt2,DGEQRT2)
+#define LAPACK_cgeqrt2 LAPACK_GLOBAL(cgeqrt2,CGEQRT2)
+#define LAPACK_zgeqrt2 LAPACK_GLOBAL(zgeqrt2,ZGEQRT2)
+#define LAPACK_sgeqrt3 LAPACK_GLOBAL(sgeqrt3,SGEQRT3)
+#define LAPACK_dgeqrt3 LAPACK_GLOBAL(dgeqrt3,DGEQRT3)
+#define LAPACK_cgeqrt3 LAPACK_GLOBAL(cgeqrt3,CGEQRT3)
+#define LAPACK_zgeqrt3 LAPACK_GLOBAL(zgeqrt3,ZGEQRT3)
+#define LAPACK_stpmqrt LAPACK_GLOBAL(stpmqrt,STPMQRT)
+#define LAPACK_dtpmqrt LAPACK_GLOBAL(dtpmqrt,DTPMQRT)
+#define LAPACK_ctpmqrt LAPACK_GLOBAL(ctpmqrt,CTPMQRT)
+#define LAPACK_ztpmqrt LAPACK_GLOBAL(ztpmqrt,ZTPMQRT)
+#define LAPACK_dtpqrt LAPACK_GLOBAL(dtpqrt,DTPQRT)
+#define LAPACK_ctpqrt LAPACK_GLOBAL(ctpqrt,CTPQRT)
+#define LAPACK_ztpqrt LAPACK_GLOBAL(ztpqrt,ZTPQRT)
+#define LAPACK_stpqrt2 LAPACK_GLOBAL(stpqrt2,STPQRT2)
+#define LAPACK_dtpqrt2 LAPACK_GLOBAL(dtpqrt2,DTPQRT2)
+#define LAPACK_ctpqrt2 LAPACK_GLOBAL(ctpqrt2,CTPQRT2)
+#define LAPACK_ztpqrt2 LAPACK_GLOBAL(ztpqrt2,ZTPQRT2)
+#define LAPACK_stprfb LAPACK_GLOBAL(stprfb,STPRFB)
+#define LAPACK_dtprfb LAPACK_GLOBAL(dtprfb,DTPRFB)
+#define LAPACK_ctprfb LAPACK_GLOBAL(ctprfb,CTPRFB)
+#define LAPACK_ztprfb LAPACK_GLOBAL(ztprfb,ZTPRFB)
+// LAPACK 3.X.X
+#define LAPACK_csyr LAPACK_GLOBAL(csyr,CSYR)
+#define LAPACK_zsyr LAPACK_GLOBAL(zsyr,ZSYR)
+
+
+void LAPACK_sgetrf( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_dgetrf( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_cgetrf( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* ipiv, lapack_int *info );
+void LAPACK_zgetrf( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* ipiv, lapack_int *info );
+void LAPACK_sgbtrf( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, float* ab, lapack_int* ldab,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_dgbtrf( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, double* ab, lapack_int* ldab,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_cgbtrf( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, lapack_complex_float* ab, lapack_int* ldab,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_zgbtrf( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, lapack_complex_double* ab, lapack_int* ldab,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_sgttrf( lapack_int* n, float* dl, float* d, float* du, float* du2,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_dgttrf( lapack_int* n, double* dl, double* d, double* du,
+                    double* du2, lapack_int* ipiv, lapack_int *info );
+void LAPACK_cgttrf( lapack_int* n, lapack_complex_float* dl,
+                    lapack_complex_float* d, lapack_complex_float* du,
+                    lapack_complex_float* du2, lapack_int* ipiv,
+                    lapack_int *info );
+void LAPACK_zgttrf( lapack_int* n, lapack_complex_double* dl,
+                    lapack_complex_double* d, lapack_complex_double* du,
+                    lapack_complex_double* du2, lapack_int* ipiv,
+                    lapack_int *info );
+void LAPACK_spotrf( char* uplo, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_dpotrf( char* uplo, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_cpotrf( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_zpotrf( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_dpstrf( char* uplo, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int* piv, lapack_int* rank, double* tol,
+                    double* work, lapack_int *info );
+void LAPACK_spstrf( char* uplo, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int* piv, lapack_int* rank, float* tol, float* work,
+                    lapack_int *info );
+void LAPACK_zpstrf( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* piv, lapack_int* rank,
+                    double* tol, double* work, lapack_int *info );
+void LAPACK_cpstrf( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* piv, lapack_int* rank,
+                    float* tol, float* work, lapack_int *info );
+void LAPACK_dpftrf( char* transr, char* uplo, lapack_int* n, double* a,
+                    lapack_int *info );
+void LAPACK_spftrf( char* transr, char* uplo, lapack_int* n, float* a,
+                    lapack_int *info );
+void LAPACK_zpftrf( char* transr, char* uplo, lapack_int* n,
+                    lapack_complex_double* a, lapack_int *info );
+void LAPACK_cpftrf( char* transr, char* uplo, lapack_int* n,
+                    lapack_complex_float* a, lapack_int *info );
+void LAPACK_spptrf( char* uplo, lapack_int* n, float* ap, lapack_int *info );
+void LAPACK_dpptrf( char* uplo, lapack_int* n, double* ap, lapack_int *info );
+void LAPACK_cpptrf( char* uplo, lapack_int* n, lapack_complex_float* ap,
+                    lapack_int *info );
+void LAPACK_zpptrf( char* uplo, lapack_int* n, lapack_complex_double* ap,
+                    lapack_int *info );
+void LAPACK_spbtrf( char* uplo, lapack_int* n, lapack_int* kd, float* ab,
+                    lapack_int* ldab, lapack_int *info );
+void LAPACK_dpbtrf( char* uplo, lapack_int* n, lapack_int* kd, double* ab,
+                    lapack_int* ldab, lapack_int *info );
+void LAPACK_cpbtrf( char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_complex_float* ab, lapack_int* ldab,
+                    lapack_int *info );
+void LAPACK_zpbtrf( char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_complex_double* ab, lapack_int* ldab,
+                    lapack_int *info );
+void LAPACK_spttrf( lapack_int* n, float* d, float* e, lapack_int *info );
+void LAPACK_dpttrf( lapack_int* n, double* d, double* e, lapack_int *info );
+void LAPACK_cpttrf( lapack_int* n, float* d, lapack_complex_float* e,
+                    lapack_int *info );
+void LAPACK_zpttrf( lapack_int* n, double* d, lapack_complex_double* e,
+                    lapack_int *info );
+void LAPACK_ssytrf( char* uplo, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int* ipiv, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dsytrf( char* uplo, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int* ipiv, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_csytrf( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* ipiv,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zsytrf( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* ipiv,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_chetrf( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* ipiv,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zhetrf( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* ipiv,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_ssptrf( char* uplo, lapack_int* n, float* ap, lapack_int* ipiv,
+                    lapack_int *info );
+void LAPACK_dsptrf( char* uplo, lapack_int* n, double* ap, lapack_int* ipiv,
+                    lapack_int *info );
+void LAPACK_csptrf( char* uplo, lapack_int* n, lapack_complex_float* ap,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_zsptrf( char* uplo, lapack_int* n, lapack_complex_double* ap,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_chptrf( char* uplo, lapack_int* n, lapack_complex_float* ap,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_zhptrf( char* uplo, lapack_int* n, lapack_complex_double* ap,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_sgetrs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const float* a, lapack_int* lda, const lapack_int* ipiv,
+                    float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_dgetrs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const double* a, lapack_int* lda, const lapack_int* ipiv,
+                    double* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_cgetrs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_int* ipiv, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_zgetrs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_int* ipiv, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_sgbtrs( char* trans, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    lapack_int* nrhs, const float* ab, lapack_int* ldab,
+                    const lapack_int* ipiv, float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_dgbtrs( char* trans, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    lapack_int* nrhs, const double* ab, lapack_int* ldab,
+                    const lapack_int* ipiv, double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_cgbtrs( char* trans, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    lapack_int* nrhs, const lapack_complex_float* ab,
+                    lapack_int* ldab, const lapack_int* ipiv,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_zgbtrs( char* trans, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    lapack_int* nrhs, const lapack_complex_double* ab,
+                    lapack_int* ldab, const lapack_int* ipiv,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_sgttrs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const float* dl, const float* d, const float* du,
+                    const float* du2, const lapack_int* ipiv, float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_dgttrs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const double* dl, const double* d, const double* du,
+                    const double* du2, const lapack_int* ipiv, double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_cgttrs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* dl,
+                    const lapack_complex_float* d,
+                    const lapack_complex_float* du,
+                    const lapack_complex_float* du2, const lapack_int* ipiv,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_zgttrs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* dl,
+                    const lapack_complex_double* d,
+                    const lapack_complex_double* du,
+                    const lapack_complex_double* du2, const lapack_int* ipiv,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_spotrs( char* uplo, lapack_int* n, lapack_int* nrhs, const float* a,
+                    lapack_int* lda, float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_dpotrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* a, lapack_int* lda, double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_cpotrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_zpotrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_dpftrs( char* transr, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* a, double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_spftrs( char* transr, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const float* a, float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_zpftrs( char* transr, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_cpftrs( char* transr, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_spptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const float* ap, float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_dpptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* ap, double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_cpptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* ap, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_zpptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* ap, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_spbtrs( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                    const float* ab, lapack_int* ldab, float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_dpbtrs( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                    const double* ab, lapack_int* ldab, double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_cpbtrs( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                    const lapack_complex_float* ab, lapack_int* ldab,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_zpbtrs( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                    const lapack_complex_double* ab, lapack_int* ldab,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_spttrs( lapack_int* n, lapack_int* nrhs, const float* d,
+                    const float* e, float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_dpttrs( lapack_int* n, lapack_int* nrhs, const double* d,
+                    const double* e, double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_cpttrs( char* uplo, lapack_int* n, lapack_int* nrhs, const float* d,
+                    const lapack_complex_float* e, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_zpttrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* d, const lapack_complex_double* e,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_ssytrs( char* uplo, lapack_int* n, lapack_int* nrhs, const float* a,
+                    lapack_int* lda, const lapack_int* ipiv, float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_dsytrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* a, lapack_int* lda, const lapack_int* ipiv,
+                    double* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_csytrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_int* ipiv, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_zsytrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_int* ipiv, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_chetrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_int* ipiv, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_zhetrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_int* ipiv, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_ssptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const float* ap, const lapack_int* ipiv, float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_dsptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* ap, const lapack_int* ipiv, double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_csptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* ap, const lapack_int* ipiv,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_zsptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* ap, const lapack_int* ipiv,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_chptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* ap, const lapack_int* ipiv,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_zhptrs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* ap, const lapack_int* ipiv,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_strtrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const float* a, lapack_int* lda, float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_dtrtrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const double* a, lapack_int* lda,
+                    double* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_ctrtrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_ztrtrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_stptrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const float* ap, float* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_dtptrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const double* ap, double* b,
+                    lapack_int* ldb, lapack_int *info );
+void LAPACK_ctptrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const lapack_complex_float* ap,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_ztptrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const lapack_complex_double* ap,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_stbtrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* kd, lapack_int* nrhs, const float* ab,
+                    lapack_int* ldab, float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_dtbtrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* kd, lapack_int* nrhs, const double* ab,
+                    lapack_int* ldab, double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_ctbtrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* kd, lapack_int* nrhs,
+                    const lapack_complex_float* ab, lapack_int* ldab,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_ztbtrs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* kd, lapack_int* nrhs,
+                    const lapack_complex_double* ab, lapack_int* ldab,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_sgecon( char* norm, lapack_int* n, const float* a, lapack_int* lda,
+                    float* anorm, float* rcond, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgecon( char* norm, lapack_int* n, const double* a, lapack_int* lda,
+                    double* anorm, double* rcond, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_cgecon( char* norm, lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, float* anorm, float* rcond,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zgecon( char* norm, lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, double* anorm, double* rcond,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_sgbcon( char* norm, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    const float* ab, lapack_int* ldab, const lapack_int* ipiv,
+                    float* anorm, float* rcond, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgbcon( char* norm, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    const double* ab, lapack_int* ldab, const lapack_int* ipiv,
+                    double* anorm, double* rcond, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_cgbcon( char* norm, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    const lapack_complex_float* ab, lapack_int* ldab,
+                    const lapack_int* ipiv, float* anorm, float* rcond,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zgbcon( char* norm, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    const lapack_complex_double* ab, lapack_int* ldab,
+                    const lapack_int* ipiv, double* anorm, double* rcond,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_sgtcon( char* norm, lapack_int* n, const float* dl, const float* d,
+                    const float* du, const float* du2, const lapack_int* ipiv,
+                    float* anorm, float* rcond, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgtcon( char* norm, lapack_int* n, const double* dl,
+                    const double* d, const double* du, const double* du2,
+                    const lapack_int* ipiv, double* anorm, double* rcond,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_cgtcon( char* norm, lapack_int* n, const lapack_complex_float* dl,
+                    const lapack_complex_float* d,
+                    const lapack_complex_float* du,
+                    const lapack_complex_float* du2, const lapack_int* ipiv,
+                    float* anorm, float* rcond, lapack_complex_float* work,
+                    lapack_int *info );
+void LAPACK_zgtcon( char* norm, lapack_int* n, const lapack_complex_double* dl,
+                    const lapack_complex_double* d,
+                    const lapack_complex_double* du,
+                    const lapack_complex_double* du2, const lapack_int* ipiv,
+                    double* anorm, double* rcond, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_spocon( char* uplo, lapack_int* n, const float* a, lapack_int* lda,
+                    float* anorm, float* rcond, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dpocon( char* uplo, lapack_int* n, const double* a, lapack_int* lda,
+                    double* anorm, double* rcond, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_cpocon( char* uplo, lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, float* anorm, float* rcond,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zpocon( char* uplo, lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, double* anorm, double* rcond,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_sppcon( char* uplo, lapack_int* n, const float* ap, float* anorm,
+                    float* rcond, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dppcon( char* uplo, lapack_int* n, const double* ap, double* anorm,
+                    double* rcond, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_cppcon( char* uplo, lapack_int* n, const lapack_complex_float* ap,
+                    float* anorm, float* rcond, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zppcon( char* uplo, lapack_int* n, const lapack_complex_double* ap,
+                    double* anorm, double* rcond, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_spbcon( char* uplo, lapack_int* n, lapack_int* kd, const float* ab,
+                    lapack_int* ldab, float* anorm, float* rcond, float* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dpbcon( char* uplo, lapack_int* n, lapack_int* kd, const double* ab,
+                    lapack_int* ldab, double* anorm, double* rcond,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_cpbcon( char* uplo, lapack_int* n, lapack_int* kd,
+                    const lapack_complex_float* ab, lapack_int* ldab,
+                    float* anorm, float* rcond, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zpbcon( char* uplo, lapack_int* n, lapack_int* kd,
+                    const lapack_complex_double* ab, lapack_int* ldab,
+                    double* anorm, double* rcond, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_sptcon( lapack_int* n, const float* d, const float* e, float* anorm,
+                    float* rcond, float* work, lapack_int *info );
+void LAPACK_dptcon( lapack_int* n, const double* d, const double* e,
+                    double* anorm, double* rcond, double* work,
+                    lapack_int *info );
+void LAPACK_cptcon( lapack_int* n, const float* d,
+                    const lapack_complex_float* e, float* anorm, float* rcond,
+                    float* work, lapack_int *info );
+void LAPACK_zptcon( lapack_int* n, const double* d,
+                    const lapack_complex_double* e, double* anorm,
+                    double* rcond, double* work, lapack_int *info );
+void LAPACK_ssycon( char* uplo, lapack_int* n, const float* a, lapack_int* lda,
+                    const lapack_int* ipiv, float* anorm, float* rcond,
+                    float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_dsycon( char* uplo, lapack_int* n, const double* a, lapack_int* lda,
+                    const lapack_int* ipiv, double* anorm, double* rcond,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_csycon( char* uplo, lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_int* ipiv, float* anorm,
+                    float* rcond, lapack_complex_float* work,
+                    lapack_int *info );
+void LAPACK_zsycon( char* uplo, lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_int* ipiv, double* anorm,
+                    double* rcond, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_checon( char* uplo, lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_int* ipiv, float* anorm,
+                    float* rcond, lapack_complex_float* work,
+                    lapack_int *info );
+void LAPACK_zhecon( char* uplo, lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_int* ipiv, double* anorm,
+                    double* rcond, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_sspcon( char* uplo, lapack_int* n, const float* ap,
+                    const lapack_int* ipiv, float* anorm, float* rcond,
+                    float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_dspcon( char* uplo, lapack_int* n, const double* ap,
+                    const lapack_int* ipiv, double* anorm, double* rcond,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_cspcon( char* uplo, lapack_int* n, const lapack_complex_float* ap,
+                    const lapack_int* ipiv, float* anorm, float* rcond,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zspcon( char* uplo, lapack_int* n, const lapack_complex_double* ap,
+                    const lapack_int* ipiv, double* anorm, double* rcond,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_chpcon( char* uplo, lapack_int* n, const lapack_complex_float* ap,
+                    const lapack_int* ipiv, float* anorm, float* rcond,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zhpcon( char* uplo, lapack_int* n, const lapack_complex_double* ap,
+                    const lapack_int* ipiv, double* anorm, double* rcond,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_strcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    const float* a, lapack_int* lda, float* rcond, float* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dtrcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    const double* a, lapack_int* lda, double* rcond,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_ctrcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    float* rcond, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_ztrcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    double* rcond, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_stpcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    const float* ap, float* rcond, float* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dtpcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    const double* ap, double* rcond, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_ctpcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    const lapack_complex_float* ap, float* rcond,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_ztpcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    const lapack_complex_double* ap, double* rcond,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_stbcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    lapack_int* kd, const float* ab, lapack_int* ldab,
+                    float* rcond, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dtbcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    lapack_int* kd, const double* ab, lapack_int* ldab,
+                    double* rcond, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_ctbcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    lapack_int* kd, const lapack_complex_float* ab,
+                    lapack_int* ldab, float* rcond, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_ztbcon( char* norm, char* uplo, char* diag, lapack_int* n,
+                    lapack_int* kd, const lapack_complex_double* ab,
+                    lapack_int* ldab, double* rcond,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_sgerfs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const float* a, lapack_int* lda, const float* af,
+                    lapack_int* ldaf, const lapack_int* ipiv, const float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* ferr,
+                    float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgerfs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const double* a, lapack_int* lda, const double* af,
+                    lapack_int* ldaf, const lapack_int* ipiv, const double* b,
+                    lapack_int* ldb, double* x, lapack_int* ldx, double* ferr,
+                    double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_cgerfs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* af, lapack_int* ldaf,
+                    const lapack_int* ipiv, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* ferr, float* berr, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zgerfs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* af, lapack_int* ldaf,
+                    const lapack_int* ipiv, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_dgerfsx( char* trans, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const double* a, lapack_int* lda, const double* af,
+                     lapack_int* ldaf, const lapack_int* ipiv, const double* r,
+                     const double* c, const double* b, lapack_int* ldb,
+                     double* x, lapack_int* ldx, double* rcond, double* berr,
+                     lapack_int* n_err_bnds, double* err_bnds_norm,
+                     double* err_bnds_comp, lapack_int* nparams, double* params,
+                     double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_sgerfsx( char* trans, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const float* a, lapack_int* lda, const float* af,
+                     lapack_int* ldaf, const lapack_int* ipiv, const float* r,
+                     const float* c, const float* b, lapack_int* ldb, float* x,
+                     lapack_int* ldx, float* rcond, float* berr,
+                     lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_zgerfsx( char* trans, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const lapack_complex_double* a, lapack_int* lda,
+                     const lapack_complex_double* af, lapack_int* ldaf,
+                     const lapack_int* ipiv, const double* r, const double* c,
+                     const lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_cgerfsx( char* trans, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const lapack_complex_float* a, lapack_int* lda,
+                     const lapack_complex_float* af, lapack_int* ldaf,
+                     const lapack_int* ipiv, const float* r, const float* c,
+                     const lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* berr, lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_sgbrfs( char* trans, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    lapack_int* nrhs, const float* ab, lapack_int* ldab,
+                    const float* afb, lapack_int* ldafb, const lapack_int* ipiv,
+                    const float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                    float* ferr, float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgbrfs( char* trans, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    lapack_int* nrhs, const double* ab, lapack_int* ldab,
+                    const double* afb, lapack_int* ldafb,
+                    const lapack_int* ipiv, const double* b, lapack_int* ldb,
+                    double* x, lapack_int* ldx, double* ferr, double* berr,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_cgbrfs( char* trans, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    lapack_int* nrhs, const lapack_complex_float* ab,
+                    lapack_int* ldab, const lapack_complex_float* afb,
+                    lapack_int* ldafb, const lapack_int* ipiv,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zgbrfs( char* trans, lapack_int* n, lapack_int* kl, lapack_int* ku,
+                    lapack_int* nrhs, const lapack_complex_double* ab,
+                    lapack_int* ldab, const lapack_complex_double* afb,
+                    lapack_int* ldafb, const lapack_int* ipiv,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* ferr,
+                    double* berr, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_dgbrfsx( char* trans, char* equed, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, lapack_int* nrhs, const double* ab,
+                     lapack_int* ldab, const double* afb, lapack_int* ldafb,
+                     const lapack_int* ipiv, const double* r, const double* c,
+                     const double* b, lapack_int* ldb, double* x,
+                     lapack_int* ldx, double* rcond, double* berr,
+                     lapack_int* n_err_bnds, double* err_bnds_norm,
+                     double* err_bnds_comp, lapack_int* nparams, double* params,
+                     double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_sgbrfsx( char* trans, char* equed, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, lapack_int* nrhs, const float* ab,
+                     lapack_int* ldab, const float* afb, lapack_int* ldafb,
+                     const lapack_int* ipiv, const float* r, const float* c,
+                     const float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                     float* rcond, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params, float* work,
+                     lapack_int* iwork, lapack_int *info );
+void LAPACK_zgbrfsx( char* trans, char* equed, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, lapack_int* nrhs,
+                     const lapack_complex_double* ab, lapack_int* ldab,
+                     const lapack_complex_double* afb, lapack_int* ldafb,
+                     const lapack_int* ipiv, const double* r, const double* c,
+                     const lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_cgbrfsx( char* trans, char* equed, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, lapack_int* nrhs,
+                     const lapack_complex_float* ab, lapack_int* ldab,
+                     const lapack_complex_float* afb, lapack_int* ldafb,
+                     const lapack_int* ipiv, const float* r, const float* c,
+                     const lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* berr, lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_sgtrfs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const float* dl, const float* d, const float* du,
+                    const float* dlf, const float* df, const float* duf,
+                    const float* du2, const lapack_int* ipiv, const float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* ferr,
+                    float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgtrfs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const double* dl, const double* d, const double* du,
+                    const double* dlf, const double* df, const double* duf,
+                    const double* du2, const lapack_int* ipiv, const double* b,
+                    lapack_int* ldb, double* x, lapack_int* ldx, double* ferr,
+                    double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_cgtrfs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* dl,
+                    const lapack_complex_float* d,
+                    const lapack_complex_float* du,
+                    const lapack_complex_float* dlf,
+                    const lapack_complex_float* df,
+                    const lapack_complex_float* duf,
+                    const lapack_complex_float* du2, const lapack_int* ipiv,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zgtrfs( char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* dl,
+                    const lapack_complex_double* d,
+                    const lapack_complex_double* du,
+                    const lapack_complex_double* dlf,
+                    const lapack_complex_double* df,
+                    const lapack_complex_double* duf,
+                    const lapack_complex_double* du2, const lapack_int* ipiv,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* ferr,
+                    double* berr, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_sporfs( char* uplo, lapack_int* n, lapack_int* nrhs, const float* a,
+                    lapack_int* lda, const float* af, lapack_int* ldaf,
+                    const float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                    float* ferr, float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dporfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* a, lapack_int* lda, const double* af,
+                    lapack_int* ldaf, const double* b, lapack_int* ldb,
+                    double* x, lapack_int* ldx, double* ferr, double* berr,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_cporfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* af, lapack_int* ldaf,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zporfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* af, lapack_int* ldaf,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* ferr,
+                    double* berr, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_dporfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const double* a, lapack_int* lda, const double* af,
+                     lapack_int* ldaf, const double* s, const double* b,
+                     lapack_int* ldb, double* x, lapack_int* ldx, double* rcond,
+                     double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params, double* work,
+                     lapack_int* iwork, lapack_int *info );
+void LAPACK_sporfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const float* a, lapack_int* lda, const float* af,
+                     lapack_int* ldaf, const float* s, const float* b,
+                     lapack_int* ldb, float* x, lapack_int* ldx, float* rcond,
+                     float* berr, lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_zporfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const lapack_complex_double* a, lapack_int* lda,
+                     const lapack_complex_double* af, lapack_int* ldaf,
+                     const double* s, const lapack_complex_double* b,
+                     lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                     double* rcond, double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_cporfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const lapack_complex_float* a, lapack_int* lda,
+                     const lapack_complex_float* af, lapack_int* ldaf,
+                     const float* s, const lapack_complex_float* b,
+                     lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                     float* rcond, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_spprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const float* ap, const float* afp, const float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* ferr,
+                    float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dpprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* ap, const double* afp, const double* b,
+                    lapack_int* ldb, double* x, lapack_int* ldx, double* ferr,
+                    double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_cpprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* ap,
+                    const lapack_complex_float* afp,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zpprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* ap,
+                    const lapack_complex_double* afp,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* ferr,
+                    double* berr, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_spbrfs( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                    const float* ab, lapack_int* ldab, const float* afb,
+                    lapack_int* ldafb, const float* b, lapack_int* ldb,
+                    float* x, lapack_int* ldx, float* ferr, float* berr,
+                    float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_dpbrfs( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                    const double* ab, lapack_int* ldab, const double* afb,
+                    lapack_int* ldafb, const double* b, lapack_int* ldb,
+                    double* x, lapack_int* ldx, double* ferr, double* berr,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_cpbrfs( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                    const lapack_complex_float* ab, lapack_int* ldab,
+                    const lapack_complex_float* afb, lapack_int* ldafb,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zpbrfs( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                    const lapack_complex_double* ab, lapack_int* ldab,
+                    const lapack_complex_double* afb, lapack_int* ldafb,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* ferr,
+                    double* berr, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_sptrfs( lapack_int* n, lapack_int* nrhs, const float* d,
+                    const float* e, const float* df, const float* ef,
+                    const float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                    float* ferr, float* berr, float* work, lapack_int *info );
+void LAPACK_dptrfs( lapack_int* n, lapack_int* nrhs, const double* d,
+                    const double* e, const double* df, const double* ef,
+                    const double* b, lapack_int* ldb, double* x,
+                    lapack_int* ldx, double* ferr, double* berr, double* work,
+                    lapack_int *info );
+void LAPACK_cptrfs( char* uplo, lapack_int* n, lapack_int* nrhs, const float* d,
+                    const lapack_complex_float* e, const float* df,
+                    const lapack_complex_float* ef,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zptrfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* d, const lapack_complex_double* e,
+                    const double* df, const lapack_complex_double* ef,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* ferr,
+                    double* berr, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_ssyrfs( char* uplo, lapack_int* n, lapack_int* nrhs, const float* a,
+                    lapack_int* lda, const float* af, lapack_int* ldaf,
+                    const lapack_int* ipiv, const float* b, lapack_int* ldb,
+                    float* x, lapack_int* ldx, float* ferr, float* berr,
+                    float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_dsyrfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* a, lapack_int* lda, const double* af,
+                    lapack_int* ldaf, const lapack_int* ipiv, const double* b,
+                    lapack_int* ldb, double* x, lapack_int* ldx, double* ferr,
+                    double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_csyrfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* af, lapack_int* ldaf,
+                    const lapack_int* ipiv, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* ferr, float* berr, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zsyrfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* af, lapack_int* ldaf,
+                    const lapack_int* ipiv, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_dsyrfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const double* a, lapack_int* lda, const double* af,
+                     lapack_int* ldaf, const lapack_int* ipiv, const double* s,
+                     const double* b, lapack_int* ldb, double* x,
+                     lapack_int* ldx, double* rcond, double* berr,
+                     lapack_int* n_err_bnds, double* err_bnds_norm,
+                     double* err_bnds_comp, lapack_int* nparams, double* params,
+                     double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_ssyrfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const float* a, lapack_int* lda, const float* af,
+                     lapack_int* ldaf, const lapack_int* ipiv, const float* s,
+                     const float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                     float* rcond, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params, float* work,
+                     lapack_int* iwork, lapack_int *info );
+void LAPACK_zsyrfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const lapack_complex_double* a, lapack_int* lda,
+                     const lapack_complex_double* af, lapack_int* ldaf,
+                     const lapack_int* ipiv, const double* s,
+                     const lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_csyrfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const lapack_complex_float* a, lapack_int* lda,
+                     const lapack_complex_float* af, lapack_int* ldaf,
+                     const lapack_int* ipiv, const float* s,
+                     const lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* berr, lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_cherfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* af, lapack_int* ldaf,
+                    const lapack_int* ipiv, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* ferr, float* berr, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zherfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* af, lapack_int* ldaf,
+                    const lapack_int* ipiv, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_zherfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const lapack_complex_double* a, lapack_int* lda,
+                     const lapack_complex_double* af, lapack_int* ldaf,
+                     const lapack_int* ipiv, const double* s,
+                     const lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_cherfsx( char* uplo, char* equed, lapack_int* n, lapack_int* nrhs,
+                     const lapack_complex_float* a, lapack_int* lda,
+                     const lapack_complex_float* af, lapack_int* ldaf,
+                     const lapack_int* ipiv, const float* s,
+                     const lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* berr, lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_ssprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const float* ap, const float* afp, const lapack_int* ipiv,
+                    const float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                    float* ferr, float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dsprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* ap, const double* afp, const lapack_int* ipiv,
+                    const double* b, lapack_int* ldb, double* x,
+                    lapack_int* ldx, double* ferr, double* berr, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_csprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* ap,
+                    const lapack_complex_float* afp, const lapack_int* ipiv,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zsprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* ap,
+                    const lapack_complex_double* afp, const lapack_int* ipiv,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* ferr,
+                    double* berr, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_chprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* ap,
+                    const lapack_complex_float* afp, const lapack_int* ipiv,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zhprfs( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* ap,
+                    const lapack_complex_double* afp, const lapack_int* ipiv,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* ferr,
+                    double* berr, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_strrfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const float* a, lapack_int* lda,
+                    const float* b, lapack_int* ldb, const float* x,
+                    lapack_int* ldx, float* ferr, float* berr, float* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dtrrfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const double* a, lapack_int* lda,
+                    const double* b, lapack_int* ldb, const double* x,
+                    lapack_int* ldx, double* ferr, double* berr, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_ctrrfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* b,
+                    lapack_int* ldb, const lapack_complex_float* x,
+                    lapack_int* ldx, float* ferr, float* berr,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_ztrrfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* b,
+                    lapack_int* ldb, const lapack_complex_double* x,
+                    lapack_int* ldx, double* ferr, double* berr,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_stprfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const float* ap, const float* b,
+                    lapack_int* ldb, const float* x, lapack_int* ldx,
+                    float* ferr, float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dtprfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const double* ap, const double* b,
+                    lapack_int* ldb, const double* x, lapack_int* ldx,
+                    double* ferr, double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_ctprfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const lapack_complex_float* ap,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    const lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_ztprfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* nrhs, const lapack_complex_double* ap,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    const lapack_complex_double* x, lapack_int* ldx,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_stbrfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* kd, lapack_int* nrhs, const float* ab,
+                    lapack_int* ldab, const float* b, lapack_int* ldb,
+                    const float* x, lapack_int* ldx, float* ferr, float* berr,
+                    float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_dtbrfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* kd, lapack_int* nrhs, const double* ab,
+                    lapack_int* ldab, const double* b, lapack_int* ldb,
+                    const double* x, lapack_int* ldx, double* ferr,
+                    double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_ctbrfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* kd, lapack_int* nrhs,
+                    const lapack_complex_float* ab, lapack_int* ldab,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    const lapack_complex_float* x, lapack_int* ldx, float* ferr,
+                    float* berr, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_ztbrfs( char* uplo, char* trans, char* diag, lapack_int* n,
+                    lapack_int* kd, lapack_int* nrhs,
+                    const lapack_complex_double* ab, lapack_int* ldab,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    const lapack_complex_double* x, lapack_int* ldx,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_sgetri( lapack_int* n, float* a, lapack_int* lda,
+                    const lapack_int* ipiv, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dgetri( lapack_int* n, double* a, lapack_int* lda,
+                    const lapack_int* ipiv, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cgetri( lapack_int* n, lapack_complex_float* a, lapack_int* lda,
+                    const lapack_int* ipiv, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zgetri( lapack_int* n, lapack_complex_double* a, lapack_int* lda,
+                    const lapack_int* ipiv, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_spotri( char* uplo, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_dpotri( char* uplo, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_cpotri( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_zpotri( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_dpftri( char* transr, char* uplo, lapack_int* n, double* a,
+                    lapack_int *info );
+void LAPACK_spftri( char* transr, char* uplo, lapack_int* n, float* a,
+                    lapack_int *info );
+void LAPACK_zpftri( char* transr, char* uplo, lapack_int* n,
+                    lapack_complex_double* a, lapack_int *info );
+void LAPACK_cpftri( char* transr, char* uplo, lapack_int* n,
+                    lapack_complex_float* a, lapack_int *info );
+void LAPACK_spptri( char* uplo, lapack_int* n, float* ap, lapack_int *info );
+void LAPACK_dpptri( char* uplo, lapack_int* n, double* ap, lapack_int *info );
+void LAPACK_cpptri( char* uplo, lapack_int* n, lapack_complex_float* ap,
+                    lapack_int *info );
+void LAPACK_zpptri( char* uplo, lapack_int* n, lapack_complex_double* ap,
+                    lapack_int *info );
+void LAPACK_ssytri( char* uplo, lapack_int* n, float* a, lapack_int* lda,
+                    const lapack_int* ipiv, float* work, lapack_int *info );
+void LAPACK_dsytri( char* uplo, lapack_int* n, double* a, lapack_int* lda,
+                    const lapack_int* ipiv, double* work, lapack_int *info );
+void LAPACK_csytri( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, const lapack_int* ipiv,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zsytri( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, const lapack_int* ipiv,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_chetri( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, const lapack_int* ipiv,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zhetri( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, const lapack_int* ipiv,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_ssptri( char* uplo, lapack_int* n, float* ap,
+                    const lapack_int* ipiv, float* work, lapack_int *info );
+void LAPACK_dsptri( char* uplo, lapack_int* n, double* ap,
+                    const lapack_int* ipiv, double* work, lapack_int *info );
+void LAPACK_csptri( char* uplo, lapack_int* n, lapack_complex_float* ap,
+                    const lapack_int* ipiv, lapack_complex_float* work,
+                    lapack_int *info );
+void LAPACK_zsptri( char* uplo, lapack_int* n, lapack_complex_double* ap,
+                    const lapack_int* ipiv, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_chptri( char* uplo, lapack_int* n, lapack_complex_float* ap,
+                    const lapack_int* ipiv, lapack_complex_float* work,
+                    lapack_int *info );
+void LAPACK_zhptri( char* uplo, lapack_int* n, lapack_complex_double* ap,
+                    const lapack_int* ipiv, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_strtri( char* uplo, char* diag, lapack_int* n, float* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_dtrtri( char* uplo, char* diag, lapack_int* n, double* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_ctrtri( char* uplo, char* diag, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_ztrtri( char* uplo, char* diag, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_dtftri( char* transr, char* uplo, char* diag, lapack_int* n,
+                    double* a, lapack_int *info );
+void LAPACK_stftri( char* transr, char* uplo, char* diag, lapack_int* n,
+                    float* a, lapack_int *info );
+void LAPACK_ztftri( char* transr, char* uplo, char* diag, lapack_int* n,
+                    lapack_complex_double* a, lapack_int *info );
+void LAPACK_ctftri( char* transr, char* uplo, char* diag, lapack_int* n,
+                    lapack_complex_float* a, lapack_int *info );
+void LAPACK_stptri( char* uplo, char* diag, lapack_int* n, float* ap,
+                    lapack_int *info );
+void LAPACK_dtptri( char* uplo, char* diag, lapack_int* n, double* ap,
+                    lapack_int *info );
+void LAPACK_ctptri( char* uplo, char* diag, lapack_int* n,
+                    lapack_complex_float* ap, lapack_int *info );
+void LAPACK_ztptri( char* uplo, char* diag, lapack_int* n,
+                    lapack_complex_double* ap, lapack_int *info );
+void LAPACK_sgeequ( lapack_int* m, lapack_int* n, const float* a,
+                    lapack_int* lda, float* r, float* c, float* rowcnd,
+                    float* colcnd, float* amax, lapack_int *info );
+void LAPACK_dgeequ( lapack_int* m, lapack_int* n, const double* a,
+                    lapack_int* lda, double* r, double* c, double* rowcnd,
+                    double* colcnd, double* amax, lapack_int *info );
+void LAPACK_cgeequ( lapack_int* m, lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, float* r, float* c, float* rowcnd,
+                    float* colcnd, float* amax, lapack_int *info );
+void LAPACK_zgeequ( lapack_int* m, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda, double* r,
+                    double* c, double* rowcnd, double* colcnd, double* amax,
+                    lapack_int *info );
+void LAPACK_dgeequb( lapack_int* m, lapack_int* n, const double* a,
+                     lapack_int* lda, double* r, double* c, double* rowcnd,
+                     double* colcnd, double* amax, lapack_int *info );
+void LAPACK_sgeequb( lapack_int* m, lapack_int* n, const float* a,
+                     lapack_int* lda, float* r, float* c, float* rowcnd,
+                     float* colcnd, float* amax, lapack_int *info );
+void LAPACK_zgeequb( lapack_int* m, lapack_int* n,
+                     const lapack_complex_double* a, lapack_int* lda, double* r,
+                     double* c, double* rowcnd, double* colcnd, double* amax,
+                     lapack_int *info );
+void LAPACK_cgeequb( lapack_int* m, lapack_int* n,
+                     const lapack_complex_float* a, lapack_int* lda, float* r,
+                     float* c, float* rowcnd, float* colcnd, float* amax,
+                     lapack_int *info );
+void LAPACK_sgbequ( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, const float* ab, lapack_int* ldab, float* r,
+                    float* c, float* rowcnd, float* colcnd, float* amax,
+                    lapack_int *info );
+void LAPACK_dgbequ( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, const double* ab, lapack_int* ldab,
+                    double* r, double* c, double* rowcnd, double* colcnd,
+                    double* amax, lapack_int *info );
+void LAPACK_cgbequ( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, const lapack_complex_float* ab,
+                    lapack_int* ldab, float* r, float* c, float* rowcnd,
+                    float* colcnd, float* amax, lapack_int *info );
+void LAPACK_zgbequ( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, const lapack_complex_double* ab,
+                    lapack_int* ldab, double* r, double* c, double* rowcnd,
+                    double* colcnd, double* amax, lapack_int *info );
+void LAPACK_dgbequb( lapack_int* m, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, const double* ab, lapack_int* ldab,
+                     double* r, double* c, double* rowcnd, double* colcnd,
+                     double* amax, lapack_int *info );
+void LAPACK_sgbequb( lapack_int* m, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, const float* ab, lapack_int* ldab,
+                     float* r, float* c, float* rowcnd, float* colcnd,
+                     float* amax, lapack_int *info );
+void LAPACK_zgbequb( lapack_int* m, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, const lapack_complex_double* ab,
+                     lapack_int* ldab, double* r, double* c, double* rowcnd,
+                     double* colcnd, double* amax, lapack_int *info );
+void LAPACK_cgbequb( lapack_int* m, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, const lapack_complex_float* ab,
+                     lapack_int* ldab, float* r, float* c, float* rowcnd,
+                     float* colcnd, float* amax, lapack_int *info );
+void LAPACK_spoequ( lapack_int* n, const float* a, lapack_int* lda, float* s,
+                    float* scond, float* amax, lapack_int *info );
+void LAPACK_dpoequ( lapack_int* n, const double* a, lapack_int* lda, double* s,
+                    double* scond, double* amax, lapack_int *info );
+void LAPACK_cpoequ( lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, float* s, float* scond, float* amax,
+                    lapack_int *info );
+void LAPACK_zpoequ( lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, double* s, double* scond, double* amax,
+                    lapack_int *info );
+void LAPACK_dpoequb( lapack_int* n, const double* a, lapack_int* lda, double* s,
+                     double* scond, double* amax, lapack_int *info );
+void LAPACK_spoequb( lapack_int* n, const float* a, lapack_int* lda, float* s,
+                     float* scond, float* amax, lapack_int *info );
+void LAPACK_zpoequb( lapack_int* n, const lapack_complex_double* a,
+                     lapack_int* lda, double* s, double* scond, double* amax,
+                     lapack_int *info );
+void LAPACK_cpoequb( lapack_int* n, const lapack_complex_float* a,
+                     lapack_int* lda, float* s, float* scond, float* amax,
+                     lapack_int *info );
+void LAPACK_sppequ( char* uplo, lapack_int* n, const float* ap, float* s,
+                    float* scond, float* amax, lapack_int *info );
+void LAPACK_dppequ( char* uplo, lapack_int* n, const double* ap, double* s,
+                    double* scond, double* amax, lapack_int *info );
+void LAPACK_cppequ( char* uplo, lapack_int* n, const lapack_complex_float* ap,
+                    float* s, float* scond, float* amax, lapack_int *info );
+void LAPACK_zppequ( char* uplo, lapack_int* n, const lapack_complex_double* ap,
+                    double* s, double* scond, double* amax, lapack_int *info );
+void LAPACK_spbequ( char* uplo, lapack_int* n, lapack_int* kd, const float* ab,
+                    lapack_int* ldab, float* s, float* scond, float* amax,
+                    lapack_int *info );
+void LAPACK_dpbequ( char* uplo, lapack_int* n, lapack_int* kd, const double* ab,
+                    lapack_int* ldab, double* s, double* scond, double* amax,
+                    lapack_int *info );
+void LAPACK_cpbequ( char* uplo, lapack_int* n, lapack_int* kd,
+                    const lapack_complex_float* ab, lapack_int* ldab, float* s,
+                    float* scond, float* amax, lapack_int *info );
+void LAPACK_zpbequ( char* uplo, lapack_int* n, lapack_int* kd,
+                    const lapack_complex_double* ab, lapack_int* ldab,
+                    double* s, double* scond, double* amax, lapack_int *info );
+void LAPACK_dsyequb( char* uplo, lapack_int* n, const double* a,
+                     lapack_int* lda, double* s, double* scond, double* amax,
+                     double* work, lapack_int *info );
+void LAPACK_ssyequb( char* uplo, lapack_int* n, const float* a, lapack_int* lda,
+                     float* s, float* scond, float* amax, float* work,
+                     lapack_int *info );
+void LAPACK_zsyequb( char* uplo, lapack_int* n, const lapack_complex_double* a,
+                     lapack_int* lda, double* s, double* scond, double* amax,
+                     lapack_complex_double* work, lapack_int *info );
+void LAPACK_csyequb( char* uplo, lapack_int* n, const lapack_complex_float* a,
+                     lapack_int* lda, float* s, float* scond, float* amax,
+                     lapack_complex_float* work, lapack_int *info );
+void LAPACK_zheequb( char* uplo, lapack_int* n, const lapack_complex_double* a,
+                     lapack_int* lda, double* s, double* scond, double* amax,
+                     lapack_complex_double* work, lapack_int *info );
+void LAPACK_cheequb( char* uplo, lapack_int* n, const lapack_complex_float* a,
+                     lapack_int* lda, float* s, float* scond, float* amax,
+                     lapack_complex_float* work, lapack_int *info );
+void LAPACK_sgesv( lapack_int* n, lapack_int* nrhs, float* a, lapack_int* lda,
+                   lapack_int* ipiv, float* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_dgesv( lapack_int* n, lapack_int* nrhs, double* a, lapack_int* lda,
+                   lapack_int* ipiv, double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_cgesv( lapack_int* n, lapack_int* nrhs, lapack_complex_float* a,
+                   lapack_int* lda, lapack_int* ipiv, lapack_complex_float* b,
+                   lapack_int* ldb, lapack_int *info );
+void LAPACK_zgesv( lapack_int* n, lapack_int* nrhs, lapack_complex_double* a,
+                   lapack_int* lda, lapack_int* ipiv, lapack_complex_double* b,
+                   lapack_int* ldb, lapack_int *info );
+void LAPACK_dsgesv( lapack_int* n, lapack_int* nrhs, double* a, lapack_int* lda,
+                    lapack_int* ipiv, double* b, lapack_int* ldb, double* x,
+                    lapack_int* ldx, double* work, float* swork,
+                    lapack_int* iter, lapack_int *info );
+void LAPACK_zcgesv( lapack_int* n, lapack_int* nrhs, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* ipiv, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    lapack_complex_double* work, lapack_complex_float* swork,
+                    double* rwork, lapack_int* iter, lapack_int *info );
+void LAPACK_sgesvx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                    float* a, lapack_int* lda, float* af, lapack_int* ldaf,
+                    lapack_int* ipiv, char* equed, float* r, float* c, float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgesvx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                    double* a, lapack_int* lda, double* af, lapack_int* ldaf,
+                    lapack_int* ipiv, char* equed, double* r, double* c,
+                    double* b, lapack_int* ldb, double* x, lapack_int* ldx,
+                    double* rcond, double* ferr, double* berr, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_cgesvx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* af, lapack_int* ldaf,
+                    lapack_int* ipiv, char* equed, float* r, float* c,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zgesvx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* af, lapack_int* ldaf,
+                    lapack_int* ipiv, char* equed, double* r, double* c,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_dgesvxx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                     double* a, lapack_int* lda, double* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, double* r, double* c,
+                     double* b, lapack_int* ldb, double* x, lapack_int* ldx,
+                     double* rcond, double* rpvgrw, double* berr,
+                     lapack_int* n_err_bnds, double* err_bnds_norm,
+                     double* err_bnds_comp, lapack_int* nparams, double* params,
+                     double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_sgesvxx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                     float* a, lapack_int* lda, float* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, float* r, float* c,
+                     float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                     float* rcond, float* rpvgrw, float* berr,
+                     lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_zgesvxx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                     lapack_complex_double* a, lapack_int* lda,
+                     lapack_complex_double* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, double* r, double* c,
+                     lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* rpvgrw, double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_cgesvxx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                     lapack_complex_float* a, lapack_int* lda,
+                     lapack_complex_float* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, float* r, float* c,
+                     lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* rpvgrw, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_sgbsv( lapack_int* n, lapack_int* kl, lapack_int* ku,
+                   lapack_int* nrhs, float* ab, lapack_int* ldab,
+                   lapack_int* ipiv, float* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_dgbsv( lapack_int* n, lapack_int* kl, lapack_int* ku,
+                   lapack_int* nrhs, double* ab, lapack_int* ldab,
+                   lapack_int* ipiv, double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_cgbsv( lapack_int* n, lapack_int* kl, lapack_int* ku,
+                   lapack_int* nrhs, lapack_complex_float* ab, lapack_int* ldab,
+                   lapack_int* ipiv, lapack_complex_float* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_zgbsv( lapack_int* n, lapack_int* kl, lapack_int* ku,
+                   lapack_int* nrhs, lapack_complex_double* ab,
+                   lapack_int* ldab, lapack_int* ipiv, lapack_complex_double* b,
+                   lapack_int* ldb, lapack_int *info );
+void LAPACK_sgbsvx( char* fact, char* trans, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, lapack_int* nrhs, float* ab,
+                    lapack_int* ldab, float* afb, lapack_int* ldafb,
+                    lapack_int* ipiv, char* equed, float* r, float* c, float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgbsvx( char* fact, char* trans, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, lapack_int* nrhs, double* ab,
+                    lapack_int* ldab, double* afb, lapack_int* ldafb,
+                    lapack_int* ipiv, char* equed, double* r, double* c,
+                    double* b, lapack_int* ldb, double* x, lapack_int* ldx,
+                    double* rcond, double* ferr, double* berr, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_cgbsvx( char* fact, char* trans, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, lapack_int* nrhs, lapack_complex_float* ab,
+                    lapack_int* ldab, lapack_complex_float* afb,
+                    lapack_int* ldafb, lapack_int* ipiv, char* equed, float* r,
+                    float* c, lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zgbsvx( char* fact, char* trans, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, lapack_int* nrhs, lapack_complex_double* ab,
+                    lapack_int* ldab, lapack_complex_double* afb,
+                    lapack_int* ldafb, lapack_int* ipiv, char* equed, double* r,
+                    double* c, lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_dgbsvxx( char* fact, char* trans, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, lapack_int* nrhs, double* ab,
+                     lapack_int* ldab, double* afb, lapack_int* ldafb,
+                     lapack_int* ipiv, char* equed, double* r, double* c,
+                     double* b, lapack_int* ldb, double* x, lapack_int* ldx,
+                     double* rcond, double* rpvgrw, double* berr,
+                     lapack_int* n_err_bnds, double* err_bnds_norm,
+                     double* err_bnds_comp, lapack_int* nparams, double* params,
+                     double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_sgbsvxx( char* fact, char* trans, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, lapack_int* nrhs, float* ab,
+                     lapack_int* ldab, float* afb, lapack_int* ldafb,
+                     lapack_int* ipiv, char* equed, float* r, float* c,
+                     float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                     float* rcond, float* rpvgrw, float* berr,
+                     lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_zgbsvxx( char* fact, char* trans, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, lapack_int* nrhs,
+                     lapack_complex_double* ab, lapack_int* ldab,
+                     lapack_complex_double* afb, lapack_int* ldafb,
+                     lapack_int* ipiv, char* equed, double* r, double* c,
+                     lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* rpvgrw, double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_cgbsvxx( char* fact, char* trans, lapack_int* n, lapack_int* kl,
+                     lapack_int* ku, lapack_int* nrhs, lapack_complex_float* ab,
+                     lapack_int* ldab, lapack_complex_float* afb,
+                     lapack_int* ldafb, lapack_int* ipiv, char* equed, float* r,
+                     float* c, lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* rpvgrw, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_sgtsv( lapack_int* n, lapack_int* nrhs, float* dl, float* d,
+                   float* du, float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_dgtsv( lapack_int* n, lapack_int* nrhs, double* dl, double* d,
+                   double* du, double* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_cgtsv( lapack_int* n, lapack_int* nrhs, lapack_complex_float* dl,
+                   lapack_complex_float* d, lapack_complex_float* du,
+                   lapack_complex_float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_zgtsv( lapack_int* n, lapack_int* nrhs, lapack_complex_double* dl,
+                   lapack_complex_double* d, lapack_complex_double* du,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_sgtsvx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                    const float* dl, const float* d, const float* du,
+                    float* dlf, float* df, float* duf, float* du2,
+                    lapack_int* ipiv, const float* b, lapack_int* ldb, float* x,
+                    lapack_int* ldx, float* rcond, float* ferr, float* berr,
+                    float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_dgtsvx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                    const double* dl, const double* d, const double* du,
+                    double* dlf, double* df, double* duf, double* du2,
+                    lapack_int* ipiv, const double* b, lapack_int* ldb,
+                    double* x, lapack_int* ldx, double* rcond, double* ferr,
+                    double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_cgtsvx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* dl,
+                    const lapack_complex_float* d,
+                    const lapack_complex_float* du, lapack_complex_float* dlf,
+                    lapack_complex_float* df, lapack_complex_float* duf,
+                    lapack_complex_float* du2, lapack_int* ipiv,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zgtsvx( char* fact, char* trans, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* dl,
+                    const lapack_complex_double* d,
+                    const lapack_complex_double* du, lapack_complex_double* dlf,
+                    lapack_complex_double* df, lapack_complex_double* duf,
+                    lapack_complex_double* du2, lapack_int* ipiv,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_sposv( char* uplo, lapack_int* n, lapack_int* nrhs, float* a,
+                   lapack_int* lda, float* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_dposv( char* uplo, lapack_int* n, lapack_int* nrhs, double* a,
+                   lapack_int* lda, double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_cposv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_float* a, lapack_int* lda,
+                   lapack_complex_float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_zposv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_double* a, lapack_int* lda,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_dsposv( char* uplo, lapack_int* n, lapack_int* nrhs, double* a,
+                    lapack_int* lda, double* b, lapack_int* ldb, double* x,
+                    lapack_int* ldx, double* work, float* swork,
+                    lapack_int* iter, lapack_int *info );
+void LAPACK_zcposv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx,
+                    lapack_complex_double* work, lapack_complex_float* swork,
+                    double* rwork, lapack_int* iter, lapack_int *info );
+void LAPACK_sposvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    float* a, lapack_int* lda, float* af, lapack_int* ldaf,
+                    char* equed, float* s, float* b, lapack_int* ldb, float* x,
+                    lapack_int* ldx, float* rcond, float* ferr, float* berr,
+                    float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_dposvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    double* a, lapack_int* lda, double* af, lapack_int* ldaf,
+                    char* equed, double* s, double* b, lapack_int* ldb,
+                    double* x, lapack_int* ldx, double* rcond, double* ferr,
+                    double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_cposvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* af, lapack_int* ldaf, char* equed,
+                    float* s, lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zposvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* af, lapack_int* ldaf, char* equed,
+                    double* s, lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_dposvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     double* a, lapack_int* lda, double* af, lapack_int* ldaf,
+                     char* equed, double* s, double* b, lapack_int* ldb,
+                     double* x, lapack_int* ldx, double* rcond, double* rpvgrw,
+                     double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params, double* work,
+                     lapack_int* iwork, lapack_int *info );
+void LAPACK_sposvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     float* a, lapack_int* lda, float* af, lapack_int* ldaf,
+                     char* equed, float* s, float* b, lapack_int* ldb, float* x,
+                     lapack_int* ldx, float* rcond, float* rpvgrw, float* berr,
+                     lapack_int* n_err_bnds, float* err_bnds_norm,
+                     float* err_bnds_comp, lapack_int* nparams, float* params,
+                     float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_zposvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     lapack_complex_double* a, lapack_int* lda,
+                     lapack_complex_double* af, lapack_int* ldaf, char* equed,
+                     double* s, lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* rpvgrw, double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_cposvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     lapack_complex_float* a, lapack_int* lda,
+                     lapack_complex_float* af, lapack_int* ldaf, char* equed,
+                     float* s, lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* rpvgrw, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_sppsv( char* uplo, lapack_int* n, lapack_int* nrhs, float* ap,
+                   float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_dppsv( char* uplo, lapack_int* n, lapack_int* nrhs, double* ap,
+                   double* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_cppsv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_float* ap, lapack_complex_float* b,
+                   lapack_int* ldb, lapack_int *info );
+void LAPACK_zppsv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_double* ap, lapack_complex_double* b,
+                   lapack_int* ldb, lapack_int *info );
+void LAPACK_sppsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    float* ap, float* afp, char* equed, float* s, float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dppsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    double* ap, double* afp, char* equed, double* s, double* b,
+                    lapack_int* ldb, double* x, lapack_int* ldx, double* rcond,
+                    double* ferr, double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_cppsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_float* ap, lapack_complex_float* afp,
+                    char* equed, float* s, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* rcond, float* ferr, float* berr,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zppsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_double* ap, lapack_complex_double* afp,
+                    char* equed, double* s, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* rcond, double* ferr, double* berr,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_spbsv( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                   float* ab, lapack_int* ldab, float* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_dpbsv( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                   double* ab, lapack_int* ldab, double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_cpbsv( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                   lapack_complex_float* ab, lapack_int* ldab,
+                   lapack_complex_float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_zpbsv( char* uplo, lapack_int* n, lapack_int* kd, lapack_int* nrhs,
+                   lapack_complex_double* ab, lapack_int* ldab,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_spbsvx( char* fact, char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_int* nrhs, float* ab, lapack_int* ldab, float* afb,
+                    lapack_int* ldafb, char* equed, float* s, float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dpbsvx( char* fact, char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_int* nrhs, double* ab, lapack_int* ldab, double* afb,
+                    lapack_int* ldafb, char* equed, double* s, double* b,
+                    lapack_int* ldb, double* x, lapack_int* ldx, double* rcond,
+                    double* ferr, double* berr, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_cpbsvx( char* fact, char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_int* nrhs, lapack_complex_float* ab,
+                    lapack_int* ldab, lapack_complex_float* afb,
+                    lapack_int* ldafb, char* equed, float* s,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zpbsvx( char* fact, char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_int* nrhs, lapack_complex_double* ab,
+                    lapack_int* ldab, lapack_complex_double* afb,
+                    lapack_int* ldafb, char* equed, double* s,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                    double* ferr, double* berr, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_sptsv( lapack_int* n, lapack_int* nrhs, float* d, float* e,
+                   float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_dptsv( lapack_int* n, lapack_int* nrhs, double* d, double* e,
+                   double* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_cptsv( lapack_int* n, lapack_int* nrhs, float* d,
+                   lapack_complex_float* e, lapack_complex_float* b,
+                   lapack_int* ldb, lapack_int *info );
+void LAPACK_zptsv( lapack_int* n, lapack_int* nrhs, double* d,
+                   lapack_complex_double* e, lapack_complex_double* b,
+                   lapack_int* ldb, lapack_int *info );
+void LAPACK_sptsvx( char* fact, lapack_int* n, lapack_int* nrhs, const float* d,
+                    const float* e, float* df, float* ef, const float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, float* work, lapack_int *info );
+void LAPACK_dptsvx( char* fact, lapack_int* n, lapack_int* nrhs,
+                    const double* d, const double* e, double* df, double* ef,
+                    const double* b, lapack_int* ldb, double* x,
+                    lapack_int* ldx, double* rcond, double* ferr, double* berr,
+                    double* work, lapack_int *info );
+void LAPACK_cptsvx( char* fact, lapack_int* n, lapack_int* nrhs, const float* d,
+                    const lapack_complex_float* e, float* df,
+                    lapack_complex_float* ef, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* rcond, float* ferr, float* berr,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zptsvx( char* fact, lapack_int* n, lapack_int* nrhs,
+                    const double* d, const lapack_complex_double* e, double* df,
+                    lapack_complex_double* ef, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* rcond, double* ferr, double* berr,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_ssysv( char* uplo, lapack_int* n, lapack_int* nrhs, float* a,
+                   lapack_int* lda, lapack_int* ipiv, float* b, lapack_int* ldb,
+                   float* work, lapack_int* lwork, lapack_int *info );
+void LAPACK_dsysv( char* uplo, lapack_int* n, lapack_int* nrhs, double* a,
+                   lapack_int* lda, lapack_int* ipiv, double* b,
+                   lapack_int* ldb, double* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_csysv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_float* a, lapack_int* lda, lapack_int* ipiv,
+                   lapack_complex_float* b, lapack_int* ldb,
+                   lapack_complex_float* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_zsysv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_double* a, lapack_int* lda, lapack_int* ipiv,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_complex_double* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_ssysvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const float* a, lapack_int* lda, float* af,
+                    lapack_int* ldaf, lapack_int* ipiv, const float* b,
+                    lapack_int* ldb, float* x, lapack_int* ldx, float* rcond,
+                    float* ferr, float* berr, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dsysvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* a, lapack_int* lda, double* af,
+                    lapack_int* ldaf, lapack_int* ipiv, const double* b,
+                    lapack_int* ldb, double* x, lapack_int* ldx, double* rcond,
+                    double* ferr, double* berr, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_csysvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* af, lapack_int* ldaf,
+                    lapack_int* ipiv, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* rcond, float* ferr, float* berr,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int *info );
+void LAPACK_zsysvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* af, lapack_int* ldaf,
+                    lapack_int* ipiv, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* rcond, double* ferr, double* berr,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int *info );
+void LAPACK_dsysvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     double* a, lapack_int* lda, double* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, double* s, double* b,
+                     lapack_int* ldb, double* x, lapack_int* ldx, double* rcond,
+                     double* rpvgrw, double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params, double* work,
+                     lapack_int* iwork, lapack_int *info );
+void LAPACK_ssysvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     float* a, lapack_int* lda, float* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, float* s, float* b,
+                     lapack_int* ldb, float* x, lapack_int* ldx, float* rcond,
+                     float* rpvgrw, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params, float* work,
+                     lapack_int* iwork, lapack_int *info );
+void LAPACK_zsysvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     lapack_complex_double* a, lapack_int* lda,
+                     lapack_complex_double* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, double* s,
+                     lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* rpvgrw, double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_csysvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     lapack_complex_float* a, lapack_int* lda,
+                     lapack_complex_float* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, float* s,
+                     lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* rpvgrw, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_chesv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_float* a, lapack_int* lda, lapack_int* ipiv,
+                   lapack_complex_float* b, lapack_int* ldb,
+                   lapack_complex_float* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_zhesv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_double* a, lapack_int* lda, lapack_int* ipiv,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_complex_double* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_chesvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* af, lapack_int* ldaf,
+                    lapack_int* ipiv, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* rcond, float* ferr, float* berr,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int *info );
+void LAPACK_zhesvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* af, lapack_int* ldaf,
+                    lapack_int* ipiv, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* rcond, double* ferr, double* berr,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int *info );
+void LAPACK_zhesvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     lapack_complex_double* a, lapack_int* lda,
+                     lapack_complex_double* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, double* s,
+                     lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* x, lapack_int* ldx, double* rcond,
+                     double* rpvgrw, double* berr, lapack_int* n_err_bnds,
+                     double* err_bnds_norm, double* err_bnds_comp,
+                     lapack_int* nparams, double* params,
+                     lapack_complex_double* work, double* rwork,
+                     lapack_int *info );
+void LAPACK_chesvxx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                     lapack_complex_float* a, lapack_int* lda,
+                     lapack_complex_float* af, lapack_int* ldaf,
+                     lapack_int* ipiv, char* equed, float* s,
+                     lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* x, lapack_int* ldx, float* rcond,
+                     float* rpvgrw, float* berr, lapack_int* n_err_bnds,
+                     float* err_bnds_norm, float* err_bnds_comp,
+                     lapack_int* nparams, float* params,
+                     lapack_complex_float* work, float* rwork,
+                     lapack_int *info );
+void LAPACK_sspsv( char* uplo, lapack_int* n, lapack_int* nrhs, float* ap,
+                   lapack_int* ipiv, float* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_dspsv( char* uplo, lapack_int* n, lapack_int* nrhs, double* ap,
+                   lapack_int* ipiv, double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_cspsv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_float* ap, lapack_int* ipiv,
+                   lapack_complex_float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_zspsv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_double* ap, lapack_int* ipiv,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_sspsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const float* ap, float* afp, lapack_int* ipiv,
+                    const float* b, lapack_int* ldb, float* x, lapack_int* ldx,
+                    float* rcond, float* ferr, float* berr, float* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dspsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const double* ap, double* afp, lapack_int* ipiv,
+                    const double* b, lapack_int* ldb, double* x,
+                    lapack_int* ldx, double* rcond, double* ferr, double* berr,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_cspsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* ap, lapack_complex_float* afp,
+                    lapack_int* ipiv, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* rcond, float* ferr, float* berr,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zspsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* ap, lapack_complex_double* afp,
+                    lapack_int* ipiv, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* rcond, double* ferr, double* berr,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_chpsv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_float* ap, lapack_int* ipiv,
+                   lapack_complex_float* b, lapack_int* ldb, lapack_int *info );
+void LAPACK_zhpsv( char* uplo, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_double* ap, lapack_int* ipiv,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_int *info );
+void LAPACK_chpsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_float* ap, lapack_complex_float* afp,
+                    lapack_int* ipiv, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* x, lapack_int* ldx,
+                    float* rcond, float* ferr, float* berr,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zhpsvx( char* fact, char* uplo, lapack_int* n, lapack_int* nrhs,
+                    const lapack_complex_double* ap, lapack_complex_double* afp,
+                    lapack_int* ipiv, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* x, lapack_int* ldx,
+                    double* rcond, double* ferr, double* berr,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_sgeqrf( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    float* tau, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dgeqrf( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    double* tau, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cgeqrf( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zgeqrf( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sgeqpf( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int* jpvt, float* tau, float* work,
+                    lapack_int *info );
+void LAPACK_dgeqpf( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int* jpvt, double* tau, double* work,
+                    lapack_int *info );
+void LAPACK_cgeqpf( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* jpvt,
+                    lapack_complex_float* tau, lapack_complex_float* work,
+                    float* rwork, lapack_int *info );
+void LAPACK_zgeqpf( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* jpvt,
+                    lapack_complex_double* tau, lapack_complex_double* work,
+                    double* rwork, lapack_int *info );
+void LAPACK_sgeqp3( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int* jpvt, float* tau, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dgeqp3( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int* jpvt, double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cgeqp3( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* jpvt,
+                    lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_int *info );
+void LAPACK_zgeqp3( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* jpvt,
+                    lapack_complex_double* tau, lapack_complex_double* work,
+                    lapack_int* lwork, double* rwork, lapack_int *info );
+void LAPACK_sorgqr( lapack_int* m, lapack_int* n, lapack_int* k, float* a,
+                    lapack_int* lda, const float* tau, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dorgqr( lapack_int* m, lapack_int* n, lapack_int* k, double* a,
+                    lapack_int* lda, const double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sormqr( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const float* a, lapack_int* lda,
+                    const float* tau, float* c, lapack_int* ldc, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dormqr( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const double* a, lapack_int* lda,
+                    const double* tau, double* c, lapack_int* ldc, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cungqr( lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zungqr( lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cunmqr( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* tau,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zunmqr( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* tau,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sgelqf( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    float* tau, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dgelqf( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    double* tau, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cgelqf( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zgelqf( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sorglq( lapack_int* m, lapack_int* n, lapack_int* k, float* a,
+                    lapack_int* lda, const float* tau, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dorglq( lapack_int* m, lapack_int* n, lapack_int* k, double* a,
+                    lapack_int* lda, const double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sormlq( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const float* a, lapack_int* lda,
+                    const float* tau, float* c, lapack_int* ldc, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dormlq( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const double* a, lapack_int* lda,
+                    const double* tau, double* c, lapack_int* ldc, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cunglq( lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zunglq( lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cunmlq( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* tau,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zunmlq( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* tau,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sgeqlf( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    float* tau, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dgeqlf( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    double* tau, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cgeqlf( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zgeqlf( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sorgql( lapack_int* m, lapack_int* n, lapack_int* k, float* a,
+                    lapack_int* lda, const float* tau, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dorgql( lapack_int* m, lapack_int* n, lapack_int* k, double* a,
+                    lapack_int* lda, const double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cungql( lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zungql( lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sormql( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const float* a, lapack_int* lda,
+                    const float* tau, float* c, lapack_int* ldc, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dormql( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const double* a, lapack_int* lda,
+                    const double* tau, double* c, lapack_int* ldc, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cunmql( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* tau,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zunmql( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* tau,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sgerqf( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    float* tau, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dgerqf( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    double* tau, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cgerqf( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zgerqf( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sorgrq( lapack_int* m, lapack_int* n, lapack_int* k, float* a,
+                    lapack_int* lda, const float* tau, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dorgrq( lapack_int* m, lapack_int* n, lapack_int* k, double* a,
+                    lapack_int* lda, const double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cungrq( lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zungrq( lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sormrq( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const float* a, lapack_int* lda,
+                    const float* tau, float* c, lapack_int* ldc, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dormrq( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const double* a, lapack_int* lda,
+                    const double* tau, double* c, lapack_int* ldc, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cunmrq( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* tau,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zunmrq( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* tau,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_stzrzf( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    float* tau, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dtzrzf( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    double* tau, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_ctzrzf( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_ztzrzf( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sormrz( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, lapack_int* l, const float* a,
+                    lapack_int* lda, const float* tau, float* c,
+                    lapack_int* ldc, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dormrz( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, lapack_int* l, const double* a,
+                    lapack_int* lda, const double* tau, double* c,
+                    lapack_int* ldc, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cunmrz( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, lapack_int* l, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* tau,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zunmrz( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* k, lapack_int* l,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau, lapack_complex_double* c,
+                    lapack_int* ldc, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sggqrf( lapack_int* n, lapack_int* m, lapack_int* p, float* a,
+                    lapack_int* lda, float* taua, float* b, lapack_int* ldb,
+                    float* taub, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dggqrf( lapack_int* n, lapack_int* m, lapack_int* p, double* a,
+                    lapack_int* lda, double* taua, double* b, lapack_int* ldb,
+                    double* taub, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cggqrf( lapack_int* n, lapack_int* m, lapack_int* p,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* taua, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* taub,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zggqrf( lapack_int* n, lapack_int* m, lapack_int* p,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* taua, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* taub,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sggrqf( lapack_int* m, lapack_int* p, lapack_int* n, float* a,
+                    lapack_int* lda, float* taua, float* b, lapack_int* ldb,
+                    float* taub, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dggrqf( lapack_int* m, lapack_int* p, lapack_int* n, double* a,
+                    lapack_int* lda, double* taua, double* b, lapack_int* ldb,
+                    double* taub, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cggrqf( lapack_int* m, lapack_int* p, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* taua, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* taub,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zggrqf( lapack_int* m, lapack_int* p, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* taua, lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* taub,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sgebrd( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    float* d, float* e, float* tauq, float* taup, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dgebrd( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    double* d, double* e, double* tauq, double* taup,
+                    double* work, lapack_int* lwork, lapack_int *info );
+void LAPACK_cgebrd( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, float* d, float* e,
+                    lapack_complex_float* tauq, lapack_complex_float* taup,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zgebrd( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, double* d, double* e,
+                    lapack_complex_double* tauq, lapack_complex_double* taup,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sgbbrd( char* vect, lapack_int* m, lapack_int* n, lapack_int* ncc,
+                    lapack_int* kl, lapack_int* ku, float* ab, lapack_int* ldab,
+                    float* d, float* e, float* q, lapack_int* ldq, float* pt,
+                    lapack_int* ldpt, float* c, lapack_int* ldc, float* work,
+                    lapack_int *info );
+void LAPACK_dgbbrd( char* vect, lapack_int* m, lapack_int* n, lapack_int* ncc,
+                    lapack_int* kl, lapack_int* ku, double* ab,
+                    lapack_int* ldab, double* d, double* e, double* q,
+                    lapack_int* ldq, double* pt, lapack_int* ldpt, double* c,
+                    lapack_int* ldc, double* work, lapack_int *info );
+void LAPACK_cgbbrd( char* vect, lapack_int* m, lapack_int* n, lapack_int* ncc,
+                    lapack_int* kl, lapack_int* ku, lapack_complex_float* ab,
+                    lapack_int* ldab, float* d, float* e,
+                    lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* pt, lapack_int* ldpt,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zgbbrd( char* vect, lapack_int* m, lapack_int* n, lapack_int* ncc,
+                    lapack_int* kl, lapack_int* ku, lapack_complex_double* ab,
+                    lapack_int* ldab, double* d, double* e,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* pt, lapack_int* ldpt,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_sorgbr( char* vect, lapack_int* m, lapack_int* n, lapack_int* k,
+                    float* a, lapack_int* lda, const float* tau, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dorgbr( char* vect, lapack_int* m, lapack_int* n, lapack_int* k,
+                    double* a, lapack_int* lda, const double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sormbr( char* vect, char* side, char* trans, lapack_int* m,
+                    lapack_int* n, lapack_int* k, const float* a,
+                    lapack_int* lda, const float* tau, float* c,
+                    lapack_int* ldc, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dormbr( char* vect, char* side, char* trans, lapack_int* m,
+                    lapack_int* n, lapack_int* k, const double* a,
+                    lapack_int* lda, const double* tau, double* c,
+                    lapack_int* ldc, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cungbr( char* vect, lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zungbr( char* vect, lapack_int* m, lapack_int* n, lapack_int* k,
+                    lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cunmbr( char* vect, char* side, char* trans, lapack_int* m,
+                    lapack_int* n, lapack_int* k, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* tau,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zunmbr( char* vect, char* side, char* trans, lapack_int* m,
+                    lapack_int* n, lapack_int* k,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau, lapack_complex_double* c,
+                    lapack_int* ldc, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sbdsqr( char* uplo, lapack_int* n, lapack_int* ncvt,
+                    lapack_int* nru, lapack_int* ncc, float* d, float* e,
+                    float* vt, lapack_int* ldvt, float* u, lapack_int* ldu,
+                    float* c, lapack_int* ldc, float* work, lapack_int *info );
+void LAPACK_dbdsqr( char* uplo, lapack_int* n, lapack_int* ncvt,
+                    lapack_int* nru, lapack_int* ncc, double* d, double* e,
+                    double* vt, lapack_int* ldvt, double* u, lapack_int* ldu,
+                    double* c, lapack_int* ldc, double* work,
+                    lapack_int *info );
+void LAPACK_cbdsqr( char* uplo, lapack_int* n, lapack_int* ncvt,
+                    lapack_int* nru, lapack_int* ncc, float* d, float* e,
+                    lapack_complex_float* vt, lapack_int* ldvt,
+                    lapack_complex_float* u, lapack_int* ldu,
+                    lapack_complex_float* c, lapack_int* ldc, float* work,
+                    lapack_int *info );
+void LAPACK_zbdsqr( char* uplo, lapack_int* n, lapack_int* ncvt,
+                    lapack_int* nru, lapack_int* ncc, double* d, double* e,
+                    lapack_complex_double* vt, lapack_int* ldvt,
+                    lapack_complex_double* u, lapack_int* ldu,
+                    lapack_complex_double* c, lapack_int* ldc, double* work,
+                    lapack_int *info );
+void LAPACK_sbdsdc( char* uplo, char* compq, lapack_int* n, float* d, float* e,
+                    float* u, lapack_int* ldu, float* vt, lapack_int* ldvt,
+                    float* q, lapack_int* iq, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dbdsdc( char* uplo, char* compq, lapack_int* n, double* d,
+                    double* e, double* u, lapack_int* ldu, double* vt,
+                    lapack_int* ldvt, double* q, lapack_int* iq, double* work,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_ssytrd( char* uplo, lapack_int* n, float* a, lapack_int* lda,
+                    float* d, float* e, float* tau, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dsytrd( char* uplo, lapack_int* n, double* a, lapack_int* lda,
+                    double* d, double* e, double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sorgtr( char* uplo, lapack_int* n, float* a, lapack_int* lda,
+                    const float* tau, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dorgtr( char* uplo, lapack_int* n, double* a, lapack_int* lda,
+                    const double* tau, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_sormtr( char* side, char* uplo, char* trans, lapack_int* m,
+                    lapack_int* n, const float* a, lapack_int* lda,
+                    const float* tau, float* c, lapack_int* ldc, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dormtr( char* side, char* uplo, char* trans, lapack_int* m,
+                    lapack_int* n, const double* a, lapack_int* lda,
+                    const double* tau, double* c, lapack_int* ldc, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_chetrd( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, float* d, float* e,
+                    lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zhetrd( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, double* d, double* e,
+                    lapack_complex_double* tau, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cungtr( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zungtr( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cunmtr( char* side, char* uplo, char* trans, lapack_int* m,
+                    lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* tau,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_zunmtr( char* side, char* uplo, char* trans, lapack_int* m,
+                    lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* tau,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_ssptrd( char* uplo, lapack_int* n, float* ap, float* d, float* e,
+                    float* tau, lapack_int *info );
+void LAPACK_dsptrd( char* uplo, lapack_int* n, double* ap, double* d, double* e,
+                    double* tau, lapack_int *info );
+void LAPACK_sopgtr( char* uplo, lapack_int* n, const float* ap,
+                    const float* tau, float* q, lapack_int* ldq, float* work,
+                    lapack_int *info );
+void LAPACK_dopgtr( char* uplo, lapack_int* n, const double* ap,
+                    const double* tau, double* q, lapack_int* ldq, double* work,
+                    lapack_int *info );
+void LAPACK_sopmtr( char* side, char* uplo, char* trans, lapack_int* m,
+                    lapack_int* n, const float* ap, const float* tau, float* c,
+                    lapack_int* ldc, float* work, lapack_int *info );
+void LAPACK_dopmtr( char* side, char* uplo, char* trans, lapack_int* m,
+                    lapack_int* n, const double* ap, const double* tau,
+                    double* c, lapack_int* ldc, double* work,
+                    lapack_int *info );
+void LAPACK_chptrd( char* uplo, lapack_int* n, lapack_complex_float* ap,
+                    float* d, float* e, lapack_complex_float* tau,
+                    lapack_int *info );
+void LAPACK_zhptrd( char* uplo, lapack_int* n, lapack_complex_double* ap,
+                    double* d, double* e, lapack_complex_double* tau,
+                    lapack_int *info );
+void LAPACK_cupgtr( char* uplo, lapack_int* n, const lapack_complex_float* ap,
+                    const lapack_complex_float* tau, lapack_complex_float* q,
+                    lapack_int* ldq, lapack_complex_float* work,
+                    lapack_int *info );
+void LAPACK_zupgtr( char* uplo, lapack_int* n, const lapack_complex_double* ap,
+                    const lapack_complex_double* tau, lapack_complex_double* q,
+                    lapack_int* ldq, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_cupmtr( char* side, char* uplo, char* trans, lapack_int* m,
+                    lapack_int* n, const lapack_complex_float* ap,
+                    const lapack_complex_float* tau, lapack_complex_float* c,
+                    lapack_int* ldc, lapack_complex_float* work,
+                    lapack_int *info );
+void LAPACK_zupmtr( char* side, char* uplo, char* trans, lapack_int* m,
+                    lapack_int* n, const lapack_complex_double* ap,
+                    const lapack_complex_double* tau, lapack_complex_double* c,
+                    lapack_int* ldc, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_ssbtrd( char* vect, char* uplo, lapack_int* n, lapack_int* kd,
+                    float* ab, lapack_int* ldab, float* d, float* e, float* q,
+                    lapack_int* ldq, float* work, lapack_int *info );
+void LAPACK_dsbtrd( char* vect, char* uplo, lapack_int* n, lapack_int* kd,
+                    double* ab, lapack_int* ldab, double* d, double* e,
+                    double* q, lapack_int* ldq, double* work,
+                    lapack_int *info );
+void LAPACK_chbtrd( char* vect, char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_complex_float* ab, lapack_int* ldab, float* d,
+                    float* e, lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zhbtrd( char* vect, char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_complex_double* ab, lapack_int* ldab, double* d,
+                    double* e, lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_ssterf( lapack_int* n, float* d, float* e, lapack_int *info );
+void LAPACK_dsterf( lapack_int* n, double* d, double* e, lapack_int *info );
+void LAPACK_ssteqr( char* compz, lapack_int* n, float* d, float* e, float* z,
+                    lapack_int* ldz, float* work, lapack_int *info );
+void LAPACK_dsteqr( char* compz, lapack_int* n, double* d, double* e, double* z,
+                    lapack_int* ldz, double* work, lapack_int *info );
+void LAPACK_csteqr( char* compz, lapack_int* n, float* d, float* e,
+                    lapack_complex_float* z, lapack_int* ldz, float* work,
+                    lapack_int *info );
+void LAPACK_zsteqr( char* compz, lapack_int* n, double* d, double* e,
+                    lapack_complex_double* z, lapack_int* ldz, double* work,
+                    lapack_int *info );
+void LAPACK_sstemr( char* jobz, char* range, lapack_int* n, float* d, float* e,
+                    float* vl, float* vu, lapack_int* il, lapack_int* iu,
+                    lapack_int* m, float* w, float* z, lapack_int* ldz,
+                    lapack_int* nzc, lapack_int* isuppz, lapack_logical* tryrac,
+                    float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_dstemr( char* jobz, char* range, lapack_int* n, double* d,
+                    double* e, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, lapack_int* m, double* w, double* z,
+                    lapack_int* ldz, lapack_int* nzc, lapack_int* isuppz,
+                    lapack_logical* tryrac, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_cstemr( char* jobz, char* range, lapack_int* n, float* d, float* e,
+                    float* vl, float* vu, lapack_int* il, lapack_int* iu,
+                    lapack_int* m, float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_int* nzc, lapack_int* isuppz,
+                    lapack_logical* tryrac, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_zstemr( char* jobz, char* range, lapack_int* n, double* d,
+                    double* e, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, lapack_int* m, double* w,
+                    lapack_complex_double* z, lapack_int* ldz, lapack_int* nzc,
+                    lapack_int* isuppz, lapack_logical* tryrac, double* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_sstedc( char* compz, lapack_int* n, float* d, float* e, float* z,
+                    lapack_int* ldz, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_dstedc( char* compz, lapack_int* n, double* d, double* e, double* z,
+                    lapack_int* ldz, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_cstedc( char* compz, lapack_int* n, float* d, float* e,
+                    lapack_complex_float* z, lapack_int* ldz,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* lrwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_zstedc( char* compz, lapack_int* n, double* d, double* e,
+                    lapack_complex_double* z, lapack_int* ldz,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_sstegr( char* jobz, char* range, lapack_int* n, float* d, float* e,
+                    float* vl, float* vu, lapack_int* il, lapack_int* iu,
+                    float* abstol, lapack_int* m, float* w, float* z,
+                    lapack_int* ldz, lapack_int* isuppz, float* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_dstegr( char* jobz, char* range, lapack_int* n, double* d,
+                    double* e, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, double* abstol, lapack_int* m, double* w,
+                    double* z, lapack_int* ldz, lapack_int* isuppz,
+                    double* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_cstegr( char* jobz, char* range, lapack_int* n, float* d, float* e,
+                    float* vl, float* vu, lapack_int* il, lapack_int* iu,
+                    float* abstol, lapack_int* m, float* w,
+                    lapack_complex_float* z, lapack_int* ldz,
+                    lapack_int* isuppz, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_zstegr( char* jobz, char* range, lapack_int* n, double* d,
+                    double* e, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, double* abstol, lapack_int* m, double* w,
+                    lapack_complex_double* z, lapack_int* ldz,
+                    lapack_int* isuppz, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_spteqr( char* compz, lapack_int* n, float* d, float* e, float* z,
+                    lapack_int* ldz, float* work, lapack_int *info );
+void LAPACK_dpteqr( char* compz, lapack_int* n, double* d, double* e, double* z,
+                    lapack_int* ldz, double* work, lapack_int *info );
+void LAPACK_cpteqr( char* compz, lapack_int* n, float* d, float* e,
+                    lapack_complex_float* z, lapack_int* ldz, float* work,
+                    lapack_int *info );
+void LAPACK_zpteqr( char* compz, lapack_int* n, double* d, double* e,
+                    lapack_complex_double* z, lapack_int* ldz, double* work,
+                    lapack_int *info );
+void LAPACK_sstebz( char* range, char* order, lapack_int* n, float* vl,
+                    float* vu, lapack_int* il, lapack_int* iu, float* abstol,
+                    const float* d, const float* e, lapack_int* m,
+                    lapack_int* nsplit, float* w, lapack_int* iblock,
+                    lapack_int* isplit, float* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dstebz( char* range, char* order, lapack_int* n, double* vl,
+                    double* vu, lapack_int* il, lapack_int* iu, double* abstol,
+                    const double* d, const double* e, lapack_int* m,
+                    lapack_int* nsplit, double* w, lapack_int* iblock,
+                    lapack_int* isplit, double* work, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_sstein( lapack_int* n, const float* d, const float* e,
+                    lapack_int* m, const float* w, const lapack_int* iblock,
+                    const lapack_int* isplit, float* z, lapack_int* ldz,
+                    float* work, lapack_int* iwork, lapack_int* ifailv,
+                    lapack_int *info );
+void LAPACK_dstein( lapack_int* n, const double* d, const double* e,
+                    lapack_int* m, const double* w, const lapack_int* iblock,
+                    const lapack_int* isplit, double* z, lapack_int* ldz,
+                    double* work, lapack_int* iwork, lapack_int* ifailv,
+                    lapack_int *info );
+void LAPACK_cstein( lapack_int* n, const float* d, const float* e,
+                    lapack_int* m, const float* w, const lapack_int* iblock,
+                    const lapack_int* isplit, lapack_complex_float* z,
+                    lapack_int* ldz, float* work, lapack_int* iwork,
+                    lapack_int* ifailv, lapack_int *info );
+void LAPACK_zstein( lapack_int* n, const double* d, const double* e,
+                    lapack_int* m, const double* w, const lapack_int* iblock,
+                    const lapack_int* isplit, lapack_complex_double* z,
+                    lapack_int* ldz, double* work, lapack_int* iwork,
+                    lapack_int* ifailv, lapack_int *info );
+void LAPACK_sdisna( char* job, lapack_int* m, lapack_int* n, const float* d,
+                    float* sep, lapack_int *info );
+void LAPACK_ddisna( char* job, lapack_int* m, lapack_int* n, const double* d,
+                    double* sep, lapack_int *info );
+void LAPACK_ssygst( lapack_int* itype, char* uplo, lapack_int* n, float* a,
+                    lapack_int* lda, const float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_dsygst( lapack_int* itype, char* uplo, lapack_int* n, double* a,
+                    lapack_int* lda, const double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_chegst( lapack_int* itype, char* uplo, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_zhegst( lapack_int* itype, char* uplo, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int *info );
+void LAPACK_sspgst( lapack_int* itype, char* uplo, lapack_int* n, float* ap,
+                    const float* bp, lapack_int *info );
+void LAPACK_dspgst( lapack_int* itype, char* uplo, lapack_int* n, double* ap,
+                    const double* bp, lapack_int *info );
+void LAPACK_chpgst( lapack_int* itype, char* uplo, lapack_int* n,
+                    lapack_complex_float* ap, const lapack_complex_float* bp,
+                    lapack_int *info );
+void LAPACK_zhpgst( lapack_int* itype, char* uplo, lapack_int* n,
+                    lapack_complex_double* ap, const lapack_complex_double* bp,
+                    lapack_int *info );
+void LAPACK_ssbgst( char* vect, char* uplo, lapack_int* n, lapack_int* ka,
+                    lapack_int* kb, float* ab, lapack_int* ldab,
+                    const float* bb, lapack_int* ldbb, float* x,
+                    lapack_int* ldx, float* work, lapack_int *info );
+void LAPACK_dsbgst( char* vect, char* uplo, lapack_int* n, lapack_int* ka,
+                    lapack_int* kb, double* ab, lapack_int* ldab,
+                    const double* bb, lapack_int* ldbb, double* x,
+                    lapack_int* ldx, double* work, lapack_int *info );
+void LAPACK_chbgst( char* vect, char* uplo, lapack_int* n, lapack_int* ka,
+                    lapack_int* kb, lapack_complex_float* ab, lapack_int* ldab,
+                    const lapack_complex_float* bb, lapack_int* ldbb,
+                    lapack_complex_float* x, lapack_int* ldx,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_zhbgst( char* vect, char* uplo, lapack_int* n, lapack_int* ka,
+                    lapack_int* kb, lapack_complex_double* ab, lapack_int* ldab,
+                    const lapack_complex_double* bb, lapack_int* ldbb,
+                    lapack_complex_double* x, lapack_int* ldx,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_spbstf( char* uplo, lapack_int* n, lapack_int* kb, float* bb,
+                    lapack_int* ldbb, lapack_int *info );
+void LAPACK_dpbstf( char* uplo, lapack_int* n, lapack_int* kb, double* bb,
+                    lapack_int* ldbb, lapack_int *info );
+void LAPACK_cpbstf( char* uplo, lapack_int* n, lapack_int* kb,
+                    lapack_complex_float* bb, lapack_int* ldbb,
+                    lapack_int *info );
+void LAPACK_zpbstf( char* uplo, lapack_int* n, lapack_int* kb,
+                    lapack_complex_double* bb, lapack_int* ldbb,
+                    lapack_int *info );
+void LAPACK_sgehrd( lapack_int* n, lapack_int* ilo, lapack_int* ihi, float* a,
+                    lapack_int* lda, float* tau, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dgehrd( lapack_int* n, lapack_int* ilo, lapack_int* ihi, double* a,
+                    lapack_int* lda, double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cgehrd( lapack_int* n, lapack_int* ilo, lapack_int* ihi,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zgehrd( lapack_int* n, lapack_int* ilo, lapack_int* ihi,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* tau, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sorghr( lapack_int* n, lapack_int* ilo, lapack_int* ihi, float* a,
+                    lapack_int* lda, const float* tau, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dorghr( lapack_int* n, lapack_int* ilo, lapack_int* ihi, double* a,
+                    lapack_int* lda, const double* tau, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sormhr( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* ilo, lapack_int* ihi, const float* a,
+                    lapack_int* lda, const float* tau, float* c,
+                    lapack_int* ldc, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dormhr( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* ilo, lapack_int* ihi, const double* a,
+                    lapack_int* lda, const double* tau, double* c,
+                    lapack_int* ldc, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cunghr( lapack_int* n, lapack_int* ilo, lapack_int* ihi,
+                    lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* tau, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zunghr( lapack_int* n, lapack_int* ilo, lapack_int* ihi,
+                    lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cunmhr( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* ilo, lapack_int* ihi,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* tau, lapack_complex_float* c,
+                    lapack_int* ldc, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zunmhr( char* side, char* trans, lapack_int* m, lapack_int* n,
+                    lapack_int* ilo, lapack_int* ihi,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* tau, lapack_complex_double* c,
+                    lapack_int* ldc, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sgebal( char* job, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int* ilo, lapack_int* ihi, float* scale,
+                    lapack_int *info );
+void LAPACK_dgebal( char* job, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int* ilo, lapack_int* ihi, double* scale,
+                    lapack_int *info );
+void LAPACK_cgebal( char* job, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* ilo, lapack_int* ihi,
+                    float* scale, lapack_int *info );
+void LAPACK_zgebal( char* job, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* ilo, lapack_int* ihi,
+                    double* scale, lapack_int *info );
+void LAPACK_sgebak( char* job, char* side, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, const float* scale, lapack_int* m,
+                    float* v, lapack_int* ldv, lapack_int *info );
+void LAPACK_dgebak( char* job, char* side, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, const double* scale, lapack_int* m,
+                    double* v, lapack_int* ldv, lapack_int *info );
+void LAPACK_cgebak( char* job, char* side, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, const float* scale, lapack_int* m,
+                    lapack_complex_float* v, lapack_int* ldv,
+                    lapack_int *info );
+void LAPACK_zgebak( char* job, char* side, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, const double* scale, lapack_int* m,
+                    lapack_complex_double* v, lapack_int* ldv,
+                    lapack_int *info );
+void LAPACK_shseqr( char* job, char* compz, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, float* h, lapack_int* ldh, float* wr,
+                    float* wi, float* z, lapack_int* ldz, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dhseqr( char* job, char* compz, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, double* h, lapack_int* ldh, double* wr,
+                    double* wi, double* z, lapack_int* ldz, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_chseqr( char* job, char* compz, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, lapack_complex_float* h, lapack_int* ldh,
+                    lapack_complex_float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zhseqr( char* job, char* compz, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, lapack_complex_double* h, lapack_int* ldh,
+                    lapack_complex_double* w, lapack_complex_double* z,
+                    lapack_int* ldz, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_shsein( char* job, char* eigsrc, char* initv,
+                    lapack_logical* select, lapack_int* n, const float* h,
+                    lapack_int* ldh, float* wr, const float* wi, float* vl,
+                    lapack_int* ldvl, float* vr, lapack_int* ldvr,
+                    lapack_int* mm, lapack_int* m, float* work,
+                    lapack_int* ifaill, lapack_int* ifailr, lapack_int *info );
+void LAPACK_dhsein( char* job, char* eigsrc, char* initv,
+                    lapack_logical* select, lapack_int* n, const double* h,
+                    lapack_int* ldh, double* wr, const double* wi, double* vl,
+                    lapack_int* ldvl, double* vr, lapack_int* ldvr,
+                    lapack_int* mm, lapack_int* m, double* work,
+                    lapack_int* ifaill, lapack_int* ifailr, lapack_int *info );
+void LAPACK_chsein( char* job, char* eigsrc, char* initv,
+                    const lapack_logical* select, lapack_int* n,
+                    const lapack_complex_float* h, lapack_int* ldh,
+                    lapack_complex_float* w, lapack_complex_float* vl,
+                    lapack_int* ldvl, lapack_complex_float* vr,
+                    lapack_int* ldvr, lapack_int* mm, lapack_int* m,
+                    lapack_complex_float* work, float* rwork,
+                    lapack_int* ifaill, lapack_int* ifailr, lapack_int *info );
+void LAPACK_zhsein( char* job, char* eigsrc, char* initv,
+                    const lapack_logical* select, lapack_int* n,
+                    const lapack_complex_double* h, lapack_int* ldh,
+                    lapack_complex_double* w, lapack_complex_double* vl,
+                    lapack_int* ldvl, lapack_complex_double* vr,
+                    lapack_int* ldvr, lapack_int* mm, lapack_int* m,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int* ifaill, lapack_int* ifailr, lapack_int *info );
+void LAPACK_strevc( char* side, char* howmny, lapack_logical* select,
+                    lapack_int* n, const float* t, lapack_int* ldt, float* vl,
+                    lapack_int* ldvl, float* vr, lapack_int* ldvr,
+                    lapack_int* mm, lapack_int* m, float* work,
+                    lapack_int *info );
+void LAPACK_dtrevc( char* side, char* howmny, lapack_logical* select,
+                    lapack_int* n, const double* t, lapack_int* ldt, double* vl,
+                    lapack_int* ldvl, double* vr, lapack_int* ldvr,
+                    lapack_int* mm, lapack_int* m, double* work,
+                    lapack_int *info );
+void LAPACK_ctrevc( char* side, char* howmny, const lapack_logical* select,
+                    lapack_int* n, lapack_complex_float* t, lapack_int* ldt,
+                    lapack_complex_float* vl, lapack_int* ldvl,
+                    lapack_complex_float* vr, lapack_int* ldvr, lapack_int* mm,
+                    lapack_int* m, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_ztrevc( char* side, char* howmny, const lapack_logical* select,
+                    lapack_int* n, lapack_complex_double* t, lapack_int* ldt,
+                    lapack_complex_double* vl, lapack_int* ldvl,
+                    lapack_complex_double* vr, lapack_int* ldvr, lapack_int* mm,
+                    lapack_int* m, lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_strsna( char* job, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const float* t, lapack_int* ldt,
+                    const float* vl, lapack_int* ldvl, const float* vr,
+                    lapack_int* ldvr, float* s, float* sep, lapack_int* mm,
+                    lapack_int* m, float* work, lapack_int* ldwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dtrsna( char* job, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const double* t, lapack_int* ldt,
+                    const double* vl, lapack_int* ldvl, const double* vr,
+                    lapack_int* ldvr, double* s, double* sep, lapack_int* mm,
+                    lapack_int* m, double* work, lapack_int* ldwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_ctrsna( char* job, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const lapack_complex_float* t,
+                    lapack_int* ldt, const lapack_complex_float* vl,
+                    lapack_int* ldvl, const lapack_complex_float* vr,
+                    lapack_int* ldvr, float* s, float* sep, lapack_int* mm,
+                    lapack_int* m, lapack_complex_float* work,
+                    lapack_int* ldwork, float* rwork, lapack_int *info );
+void LAPACK_ztrsna( char* job, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const lapack_complex_double* t,
+                    lapack_int* ldt, const lapack_complex_double* vl,
+                    lapack_int* ldvl, const lapack_complex_double* vr,
+                    lapack_int* ldvr, double* s, double* sep, lapack_int* mm,
+                    lapack_int* m, lapack_complex_double* work,
+                    lapack_int* ldwork, double* rwork, lapack_int *info );
+void LAPACK_strexc( char* compq, lapack_int* n, float* t, lapack_int* ldt,
+                    float* q, lapack_int* ldq, lapack_int* ifst,
+                    lapack_int* ilst, float* work, lapack_int *info );
+void LAPACK_dtrexc( char* compq, lapack_int* n, double* t, lapack_int* ldt,
+                    double* q, lapack_int* ldq, lapack_int* ifst,
+                    lapack_int* ilst, double* work, lapack_int *info );
+void LAPACK_ctrexc( char* compq, lapack_int* n, lapack_complex_float* t,
+                    lapack_int* ldt, lapack_complex_float* q, lapack_int* ldq,
+                    lapack_int* ifst, lapack_int* ilst, lapack_int *info );
+void LAPACK_ztrexc( char* compq, lapack_int* n, lapack_complex_double* t,
+                    lapack_int* ldt, lapack_complex_double* q, lapack_int* ldq,
+                    lapack_int* ifst, lapack_int* ilst, lapack_int *info );
+void LAPACK_strsen( char* job, char* compq, const lapack_logical* select,
+                    lapack_int* n, float* t, lapack_int* ldt, float* q,
+                    lapack_int* ldq, float* wr, float* wi, lapack_int* m,
+                    float* s, float* sep, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_dtrsen( char* job, char* compq, const lapack_logical* select,
+                    lapack_int* n, double* t, lapack_int* ldt, double* q,
+                    lapack_int* ldq, double* wr, double* wi, lapack_int* m,
+                    double* s, double* sep, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_ctrsen( char* job, char* compq, const lapack_logical* select,
+                    lapack_int* n, lapack_complex_float* t, lapack_int* ldt,
+                    lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* w, lapack_int* m, float* s,
+                    float* sep, lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_ztrsen( char* job, char* compq, const lapack_logical* select,
+                    lapack_int* n, lapack_complex_double* t, lapack_int* ldt,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* w, lapack_int* m, double* s,
+                    double* sep, lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_strsyl( char* trana, char* tranb, lapack_int* isgn, lapack_int* m,
+                    lapack_int* n, const float* a, lapack_int* lda,
+                    const float* b, lapack_int* ldb, float* c, lapack_int* ldc,
+                    float* scale, lapack_int *info );
+void LAPACK_dtrsyl( char* trana, char* tranb, lapack_int* isgn, lapack_int* m,
+                    lapack_int* n, const double* a, lapack_int* lda,
+                    const double* b, lapack_int* ldb, double* c,
+                    lapack_int* ldc, double* scale, lapack_int *info );
+void LAPACK_ctrsyl( char* trana, char* tranb, lapack_int* isgn, lapack_int* m,
+                    lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* b,
+                    lapack_int* ldb, lapack_complex_float* c, lapack_int* ldc,
+                    float* scale, lapack_int *info );
+void LAPACK_ztrsyl( char* trana, char* tranb, lapack_int* isgn, lapack_int* m,
+                    lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* b,
+                    lapack_int* ldb, lapack_complex_double* c, lapack_int* ldc,
+                    double* scale, lapack_int *info );
+void LAPACK_sgghrd( char* compq, char* compz, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, float* a, lapack_int* lda, float* b,
+                    lapack_int* ldb, float* q, lapack_int* ldq, float* z,
+                    lapack_int* ldz, lapack_int *info );
+void LAPACK_dgghrd( char* compq, char* compz, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, double* a, lapack_int* lda, double* b,
+                    lapack_int* ldb, double* q, lapack_int* ldq, double* z,
+                    lapack_int* ldz, lapack_int *info );
+void LAPACK_cgghrd( char* compq, char* compz, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* z, lapack_int* ldz,
+                    lapack_int *info );
+void LAPACK_zgghrd( char* compq, char* compz, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* z, lapack_int* ldz,
+                    lapack_int *info );
+void LAPACK_sggbal( char* job, lapack_int* n, float* a, lapack_int* lda,
+                    float* b, lapack_int* ldb, lapack_int* ilo, lapack_int* ihi,
+                    float* lscale, float* rscale, float* work,
+                    lapack_int *info );
+void LAPACK_dggbal( char* job, lapack_int* n, double* a, lapack_int* lda,
+                    double* b, lapack_int* ldb, lapack_int* ilo,
+                    lapack_int* ihi, double* lscale, double* rscale,
+                    double* work, lapack_int *info );
+void LAPACK_cggbal( char* job, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* b, lapack_int* ldb,
+                    lapack_int* ilo, lapack_int* ihi, float* lscale,
+                    float* rscale, float* work, lapack_int *info );
+void LAPACK_zggbal( char* job, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* b, lapack_int* ldb,
+                    lapack_int* ilo, lapack_int* ihi, double* lscale,
+                    double* rscale, double* work, lapack_int *info );
+void LAPACK_sggbak( char* job, char* side, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, const float* lscale, const float* rscale,
+                    lapack_int* m, float* v, lapack_int* ldv,
+                    lapack_int *info );
+void LAPACK_dggbak( char* job, char* side, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, const double* lscale, const double* rscale,
+                    lapack_int* m, double* v, lapack_int* ldv,
+                    lapack_int *info );
+void LAPACK_cggbak( char* job, char* side, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, const float* lscale, const float* rscale,
+                    lapack_int* m, lapack_complex_float* v, lapack_int* ldv,
+                    lapack_int *info );
+void LAPACK_zggbak( char* job, char* side, lapack_int* n, lapack_int* ilo,
+                    lapack_int* ihi, const double* lscale, const double* rscale,
+                    lapack_int* m, lapack_complex_double* v, lapack_int* ldv,
+                    lapack_int *info );
+void LAPACK_shgeqz( char* job, char* compq, char* compz, lapack_int* n,
+                    lapack_int* ilo, lapack_int* ihi, float* h, lapack_int* ldh,
+                    float* t, lapack_int* ldt, float* alphar, float* alphai,
+                    float* beta, float* q, lapack_int* ldq, float* z,
+                    lapack_int* ldz, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dhgeqz( char* job, char* compq, char* compz, lapack_int* n,
+                    lapack_int* ilo, lapack_int* ihi, double* h,
+                    lapack_int* ldh, double* t, lapack_int* ldt, double* alphar,
+                    double* alphai, double* beta, double* q, lapack_int* ldq,
+                    double* z, lapack_int* ldz, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_chgeqz( char* job, char* compq, char* compz, lapack_int* n,
+                    lapack_int* ilo, lapack_int* ihi, lapack_complex_float* h,
+                    lapack_int* ldh, lapack_complex_float* t, lapack_int* ldt,
+                    lapack_complex_float* alpha, lapack_complex_float* beta,
+                    lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* z, lapack_int* ldz,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int *info );
+void LAPACK_zhgeqz( char* job, char* compq, char* compz, lapack_int* n,
+                    lapack_int* ilo, lapack_int* ihi, lapack_complex_double* h,
+                    lapack_int* ldh, lapack_complex_double* t, lapack_int* ldt,
+                    lapack_complex_double* alpha, lapack_complex_double* beta,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* z, lapack_int* ldz,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int *info );
+void LAPACK_stgevc( char* side, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const float* s, lapack_int* lds,
+                    const float* p, lapack_int* ldp, float* vl,
+                    lapack_int* ldvl, float* vr, lapack_int* ldvr,
+                    lapack_int* mm, lapack_int* m, float* work,
+                    lapack_int *info );
+void LAPACK_dtgevc( char* side, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const double* s, lapack_int* lds,
+                    const double* p, lapack_int* ldp, double* vl,
+                    lapack_int* ldvl, double* vr, lapack_int* ldvr,
+                    lapack_int* mm, lapack_int* m, double* work,
+                    lapack_int *info );
+void LAPACK_ctgevc( char* side, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const lapack_complex_float* s,
+                    lapack_int* lds, const lapack_complex_float* p,
+                    lapack_int* ldp, lapack_complex_float* vl, lapack_int* ldvl,
+                    lapack_complex_float* vr, lapack_int* ldvr, lapack_int* mm,
+                    lapack_int* m, lapack_complex_float* work, float* rwork,
+                    lapack_int *info );
+void LAPACK_ztgevc( char* side, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const lapack_complex_double* s,
+                    lapack_int* lds, const lapack_complex_double* p,
+                    lapack_int* ldp, lapack_complex_double* vl,
+                    lapack_int* ldvl, lapack_complex_double* vr,
+                    lapack_int* ldvr, lapack_int* mm, lapack_int* m,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int *info );
+void LAPACK_stgexc( lapack_logical* wantq, lapack_logical* wantz, lapack_int* n,
+                    float* a, lapack_int* lda, float* b, lapack_int* ldb,
+                    float* q, lapack_int* ldq, float* z, lapack_int* ldz,
+                    lapack_int* ifst, lapack_int* ilst, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dtgexc( lapack_logical* wantq, lapack_logical* wantz, lapack_int* n,
+                    double* a, lapack_int* lda, double* b, lapack_int* ldb,
+                    double* q, lapack_int* ldq, double* z, lapack_int* ldz,
+                    lapack_int* ifst, lapack_int* ilst, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_ctgexc( lapack_logical* wantq, lapack_logical* wantz, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* z, lapack_int* ldz, lapack_int* ifst,
+                    lapack_int* ilst, lapack_int *info );
+void LAPACK_ztgexc( lapack_logical* wantq, lapack_logical* wantz, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* z, lapack_int* ldz, lapack_int* ifst,
+                    lapack_int* ilst, lapack_int *info );
+void LAPACK_stgsen( lapack_int* ijob, lapack_logical* wantq,
+                    lapack_logical* wantz, const lapack_logical* select,
+                    lapack_int* n, float* a, lapack_int* lda, float* b,
+                    lapack_int* ldb, float* alphar, float* alphai, float* beta,
+                    float* q, lapack_int* ldq, float* z, lapack_int* ldz,
+                    lapack_int* m, float* pl, float* pr, float* dif,
+                    float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_dtgsen( lapack_int* ijob, lapack_logical* wantq,
+                    lapack_logical* wantz, const lapack_logical* select,
+                    lapack_int* n, double* a, lapack_int* lda, double* b,
+                    lapack_int* ldb, double* alphar, double* alphai,
+                    double* beta, double* q, lapack_int* ldq, double* z,
+                    lapack_int* ldz, lapack_int* m, double* pl, double* pr,
+                    double* dif, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_ctgsen( lapack_int* ijob, lapack_logical* wantq,
+                    lapack_logical* wantz, const lapack_logical* select,
+                    lapack_int* n, lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* alpha, lapack_complex_float* beta,
+                    lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* z, lapack_int* ldz, lapack_int* m,
+                    float* pl, float* pr, float* dif,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_ztgsen( lapack_int* ijob, lapack_logical* wantq,
+                    lapack_logical* wantz, const lapack_logical* select,
+                    lapack_int* n, lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* alpha, lapack_complex_double* beta,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* z, lapack_int* ldz, lapack_int* m,
+                    double* pl, double* pr, double* dif,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_stgsyl( char* trans, lapack_int* ijob, lapack_int* m, lapack_int* n,
+                    const float* a, lapack_int* lda, const float* b,
+                    lapack_int* ldb, float* c, lapack_int* ldc, const float* d,
+                    lapack_int* ldd, const float* e, lapack_int* lde, float* f,
+                    lapack_int* ldf, float* scale, float* dif, float* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int *info );
+void LAPACK_dtgsyl( char* trans, lapack_int* ijob, lapack_int* m, lapack_int* n,
+                    const double* a, lapack_int* lda, const double* b,
+                    lapack_int* ldb, double* c, lapack_int* ldc,
+                    const double* d, lapack_int* ldd, const double* e,
+                    lapack_int* lde, double* f, lapack_int* ldf, double* scale,
+                    double* dif, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_ctgsyl( char* trans, lapack_int* ijob, lapack_int* m, lapack_int* n,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    const lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    const lapack_complex_float* d, lapack_int* ldd,
+                    const lapack_complex_float* e, lapack_int* lde,
+                    lapack_complex_float* f, lapack_int* ldf, float* scale,
+                    float* dif, lapack_complex_float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_ztgsyl( char* trans, lapack_int* ijob, lapack_int* m, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    const lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    const lapack_complex_double* d, lapack_int* ldd,
+                    const lapack_complex_double* e, lapack_int* lde,
+                    lapack_complex_double* f, lapack_int* ldf, double* scale,
+                    double* dif, lapack_complex_double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_stgsna( char* job, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const float* a, lapack_int* lda,
+                    const float* b, lapack_int* ldb, const float* vl,
+                    lapack_int* ldvl, const float* vr, lapack_int* ldvr,
+                    float* s, float* dif, lapack_int* mm, lapack_int* m,
+                    float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dtgsna( char* job, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const double* a, lapack_int* lda,
+                    const double* b, lapack_int* ldb, const double* vl,
+                    lapack_int* ldvl, const double* vr, lapack_int* ldvr,
+                    double* s, double* dif, lapack_int* mm, lapack_int* m,
+                    double* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_ctgsna( char* job, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, const lapack_complex_float* b,
+                    lapack_int* ldb, const lapack_complex_float* vl,
+                    lapack_int* ldvl, const lapack_complex_float* vr,
+                    lapack_int* ldvr, float* s, float* dif, lapack_int* mm,
+                    lapack_int* m, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int *info );
+void LAPACK_ztgsna( char* job, char* howmny, const lapack_logical* select,
+                    lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, const lapack_complex_double* b,
+                    lapack_int* ldb, const lapack_complex_double* vl,
+                    lapack_int* ldvl, const lapack_complex_double* vr,
+                    lapack_int* ldvr, double* s, double* dif, lapack_int* mm,
+                    lapack_int* m, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int *info );
+void LAPACK_sggsvp( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* p, lapack_int* n, float* a, lapack_int* lda,
+                    float* b, lapack_int* ldb, float* tola, float* tolb,
+                    lapack_int* k, lapack_int* l, float* u, lapack_int* ldu,
+                    float* v, lapack_int* ldv, float* q, lapack_int* ldq,
+                    lapack_int* iwork, float* tau, float* work,
+                    lapack_int *info );
+void LAPACK_dggsvp( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* p, lapack_int* n, double* a, lapack_int* lda,
+                    double* b, lapack_int* ldb, double* tola, double* tolb,
+                    lapack_int* k, lapack_int* l, double* u, lapack_int* ldu,
+                    double* v, lapack_int* ldv, double* q, lapack_int* ldq,
+                    lapack_int* iwork, double* tau, double* work,
+                    lapack_int *info );
+void LAPACK_cggsvp( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* p, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* b, lapack_int* ldb,
+                    float* tola, float* tolb, lapack_int* k, lapack_int* l,
+                    lapack_complex_float* u, lapack_int* ldu,
+                    lapack_complex_float* v, lapack_int* ldv,
+                    lapack_complex_float* q, lapack_int* ldq, lapack_int* iwork,
+                    float* rwork, lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zggsvp( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* p, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* b, lapack_int* ldb,
+                    double* tola, double* tolb, lapack_int* k, lapack_int* l,
+                    lapack_complex_double* u, lapack_int* ldu,
+                    lapack_complex_double* v, lapack_int* ldv,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_int* iwork, double* rwork,
+                    lapack_complex_double* tau, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_stgsja( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* p, lapack_int* n, lapack_int* k, lapack_int* l,
+                    float* a, lapack_int* lda, float* b, lapack_int* ldb,
+                    float* tola, float* tolb, float* alpha, float* beta,
+                    float* u, lapack_int* ldu, float* v, lapack_int* ldv,
+                    float* q, lapack_int* ldq, float* work, lapack_int* ncycle,
+                    lapack_int *info );
+void LAPACK_dtgsja( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* p, lapack_int* n, lapack_int* k, lapack_int* l,
+                    double* a, lapack_int* lda, double* b, lapack_int* ldb,
+                    double* tola, double* tolb, double* alpha, double* beta,
+                    double* u, lapack_int* ldu, double* v, lapack_int* ldv,
+                    double* q, lapack_int* ldq, double* work,
+                    lapack_int* ncycle, lapack_int *info );
+void LAPACK_ctgsja( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* p, lapack_int* n, lapack_int* k, lapack_int* l,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb, float* tola,
+                    float* tolb, float* alpha, float* beta,
+                    lapack_complex_float* u, lapack_int* ldu,
+                    lapack_complex_float* v, lapack_int* ldv,
+                    lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* work, lapack_int* ncycle,
+                    lapack_int *info );
+void LAPACK_ztgsja( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* p, lapack_int* n, lapack_int* k, lapack_int* l,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb, double* tola,
+                    double* tolb, double* alpha, double* beta,
+                    lapack_complex_double* u, lapack_int* ldu,
+                    lapack_complex_double* v, lapack_int* ldv,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* work, lapack_int* ncycle,
+                    lapack_int *info );
+void LAPACK_sgels( char* trans, lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                   float* a, lapack_int* lda, float* b, lapack_int* ldb,
+                   float* work, lapack_int* lwork, lapack_int *info );
+void LAPACK_dgels( char* trans, lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                   double* a, lapack_int* lda, double* b, lapack_int* ldb,
+                   double* work, lapack_int* lwork, lapack_int *info );
+void LAPACK_cgels( char* trans, lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_float* a, lapack_int* lda,
+                   lapack_complex_float* b, lapack_int* ldb,
+                   lapack_complex_float* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_zgels( char* trans, lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                   lapack_complex_double* a, lapack_int* lda,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_complex_double* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_sgelsy( lapack_int* m, lapack_int* n, lapack_int* nrhs, float* a,
+                    lapack_int* lda, float* b, lapack_int* ldb,
+                    lapack_int* jpvt, float* rcond, lapack_int* rank,
+                    float* work, lapack_int* lwork, lapack_int *info );
+void LAPACK_dgelsy( lapack_int* m, lapack_int* n, lapack_int* nrhs, double* a,
+                    lapack_int* lda, double* b, lapack_int* ldb,
+                    lapack_int* jpvt, double* rcond, lapack_int* rank,
+                    double* work, lapack_int* lwork, lapack_int *info );
+void LAPACK_cgelsy( lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb, lapack_int* jpvt,
+                    float* rcond, lapack_int* rank, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_int *info );
+void LAPACK_zgelsy( lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb, lapack_int* jpvt,
+                    double* rcond, lapack_int* rank,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int *info );
+void LAPACK_sgelss( lapack_int* m, lapack_int* n, lapack_int* nrhs, float* a,
+                    lapack_int* lda, float* b, lapack_int* ldb, float* s,
+                    float* rcond, lapack_int* rank, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dgelss( lapack_int* m, lapack_int* n, lapack_int* nrhs, double* a,
+                    lapack_int* lda, double* b, lapack_int* ldb, double* s,
+                    double* rcond, lapack_int* rank, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cgelss( lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb, float* s,
+                    float* rcond, lapack_int* rank, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_int *info );
+void LAPACK_zgelss( lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb, double* s,
+                    double* rcond, lapack_int* rank,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int *info );
+void LAPACK_sgelsd( lapack_int* m, lapack_int* n, lapack_int* nrhs, float* a,
+                    lapack_int* lda, float* b, lapack_int* ldb, float* s,
+                    float* rcond, lapack_int* rank, float* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int *info );
+void LAPACK_dgelsd( lapack_int* m, lapack_int* n, lapack_int* nrhs, double* a,
+                    lapack_int* lda, double* b, lapack_int* ldb, double* s,
+                    double* rcond, lapack_int* rank, double* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int *info );
+void LAPACK_cgelsd( lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb, float* s,
+                    float* rcond, lapack_int* rank, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_zgelsd( lapack_int* m, lapack_int* n, lapack_int* nrhs,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb, double* s,
+                    double* rcond, lapack_int* rank,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* iwork, lapack_int *info );
+void LAPACK_sgglse( lapack_int* m, lapack_int* n, lapack_int* p, float* a,
+                    lapack_int* lda, float* b, lapack_int* ldb, float* c,
+                    float* d, float* x, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dgglse( lapack_int* m, lapack_int* n, lapack_int* p, double* a,
+                    lapack_int* lda, double* b, lapack_int* ldb, double* c,
+                    double* d, double* x, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cgglse( lapack_int* m, lapack_int* n, lapack_int* p,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* c, lapack_complex_float* d,
+                    lapack_complex_float* x, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zgglse( lapack_int* m, lapack_int* n, lapack_int* p,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* c, lapack_complex_double* d,
+                    lapack_complex_double* x, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sggglm( lapack_int* n, lapack_int* m, lapack_int* p, float* a,
+                    lapack_int* lda, float* b, lapack_int* ldb, float* d,
+                    float* x, float* y, float* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_dggglm( lapack_int* n, lapack_int* m, lapack_int* p, double* a,
+                    lapack_int* lda, double* b, lapack_int* ldb, double* d,
+                    double* x, double* y, double* work, lapack_int* lwork,
+                    lapack_int *info );
+void LAPACK_cggglm( lapack_int* n, lapack_int* m, lapack_int* p,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* d, lapack_complex_float* x,
+                    lapack_complex_float* y, lapack_complex_float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_zggglm( lapack_int* n, lapack_int* m, lapack_int* p,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* d, lapack_complex_double* x,
+                    lapack_complex_double* y, lapack_complex_double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_ssyev( char* jobz, char* uplo, lapack_int* n, float* a,
+                   lapack_int* lda, float* w, float* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_dsyev( char* jobz, char* uplo, lapack_int* n, double* a,
+                   lapack_int* lda, double* w, double* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_cheev( char* jobz, char* uplo, lapack_int* n,
+                   lapack_complex_float* a, lapack_int* lda, float* w,
+                   lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                   lapack_int *info );
+void LAPACK_zheev( char* jobz, char* uplo, lapack_int* n,
+                   lapack_complex_double* a, lapack_int* lda, double* w,
+                   lapack_complex_double* work, lapack_int* lwork,
+                   double* rwork, lapack_int *info );
+void LAPACK_ssyevd( char* jobz, char* uplo, lapack_int* n, float* a,
+                    lapack_int* lda, float* w, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_dsyevd( char* jobz, char* uplo, lapack_int* n, double* a,
+                    lapack_int* lda, double* w, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_cheevd( char* jobz, char* uplo, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda, float* w,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* lrwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_zheevd( char* jobz, char* uplo, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda, double* w,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_ssyevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    float* a, lapack_int* lda, float* vl, float* vu,
+                    lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, float* z, lapack_int* ldz,
+                    float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_dsyevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    double* a, lapack_int* lda, double* vl, double* vu,
+                    lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, double* z, lapack_int* ldz,
+                    double* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_cheevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda, float* vl,
+                    float* vu, lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_zheevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda, double* vl,
+                    double* vu, lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, lapack_complex_double* z,
+                    lapack_int* ldz, lapack_complex_double* work,
+                    lapack_int* lwork, double* rwork, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_ssyevr( char* jobz, char* range, char* uplo, lapack_int* n,
+                    float* a, lapack_int* lda, float* vl, float* vu,
+                    lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, float* z, lapack_int* ldz,
+                    lapack_int* isuppz, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_dsyevr( char* jobz, char* range, char* uplo, lapack_int* n,
+                    double* a, lapack_int* lda, double* vl, double* vu,
+                    lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, double* z, lapack_int* ldz,
+                    lapack_int* isuppz, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_cheevr( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda, float* vl,
+                    float* vu, lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_int* isuppz,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* lrwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_zheevr( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda, double* vl,
+                    double* vu, lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, lapack_complex_double* z,
+                    lapack_int* ldz, lapack_int* isuppz,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_sspev( char* jobz, char* uplo, lapack_int* n, float* ap, float* w,
+                   float* z, lapack_int* ldz, float* work, lapack_int *info );
+void LAPACK_dspev( char* jobz, char* uplo, lapack_int* n, double* ap, double* w,
+                   double* z, lapack_int* ldz, double* work, lapack_int *info );
+void LAPACK_chpev( char* jobz, char* uplo, lapack_int* n,
+                   lapack_complex_float* ap, float* w, lapack_complex_float* z,
+                   lapack_int* ldz, lapack_complex_float* work, float* rwork,
+                   lapack_int *info );
+void LAPACK_zhpev( char* jobz, char* uplo, lapack_int* n,
+                   lapack_complex_double* ap, double* w,
+                   lapack_complex_double* z, lapack_int* ldz,
+                   lapack_complex_double* work, double* rwork,
+                   lapack_int *info );
+void LAPACK_sspevd( char* jobz, char* uplo, lapack_int* n, float* ap, float* w,
+                    float* z, lapack_int* ldz, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_dspevd( char* jobz, char* uplo, lapack_int* n, double* ap,
+                    double* w, double* z, lapack_int* ldz, double* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_chpevd( char* jobz, char* uplo, lapack_int* n,
+                    lapack_complex_float* ap, float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_int* lrwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_zhpevd( char* jobz, char* uplo, lapack_int* n,
+                    lapack_complex_double* ap, double* w,
+                    lapack_complex_double* z, lapack_int* ldz,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_sspevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    float* ap, float* vl, float* vu, lapack_int* il,
+                    lapack_int* iu, float* abstol, lapack_int* m, float* w,
+                    float* z, lapack_int* ldz, float* work, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_dspevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    double* ap, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, double* abstol, lapack_int* m, double* w,
+                    double* z, lapack_int* ldz, double* work, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_chpevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_complex_float* ap, float* vl, float* vu,
+                    lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_complex_float* work, float* rwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_zhpevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_complex_double* ap, double* vl, double* vu,
+                    lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, lapack_complex_double* z,
+                    lapack_int* ldz, lapack_complex_double* work, double* rwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_ssbev( char* jobz, char* uplo, lapack_int* n, lapack_int* kd,
+                   float* ab, lapack_int* ldab, float* w, float* z,
+                   lapack_int* ldz, float* work, lapack_int *info );
+void LAPACK_dsbev( char* jobz, char* uplo, lapack_int* n, lapack_int* kd,
+                   double* ab, lapack_int* ldab, double* w, double* z,
+                   lapack_int* ldz, double* work, lapack_int *info );
+void LAPACK_chbev( char* jobz, char* uplo, lapack_int* n, lapack_int* kd,
+                   lapack_complex_float* ab, lapack_int* ldab, float* w,
+                   lapack_complex_float* z, lapack_int* ldz,
+                   lapack_complex_float* work, float* rwork, lapack_int *info );
+void LAPACK_zhbev( char* jobz, char* uplo, lapack_int* n, lapack_int* kd,
+                   lapack_complex_double* ab, lapack_int* ldab, double* w,
+                   lapack_complex_double* z, lapack_int* ldz,
+                   lapack_complex_double* work, double* rwork,
+                   lapack_int *info );
+void LAPACK_ssbevd( char* jobz, char* uplo, lapack_int* n, lapack_int* kd,
+                    float* ab, lapack_int* ldab, float* w, float* z,
+                    lapack_int* ldz, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_dsbevd( char* jobz, char* uplo, lapack_int* n, lapack_int* kd,
+                    double* ab, lapack_int* ldab, double* w, double* z,
+                    lapack_int* ldz, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_chbevd( char* jobz, char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_complex_float* ab, lapack_int* ldab, float* w,
+                    lapack_complex_float* z, lapack_int* ldz,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* lrwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_zhbevd( char* jobz, char* uplo, lapack_int* n, lapack_int* kd,
+                    lapack_complex_double* ab, lapack_int* ldab, double* w,
+                    lapack_complex_double* z, lapack_int* ldz,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_ssbevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_int* kd, float* ab, lapack_int* ldab, float* q,
+                    lapack_int* ldq, float* vl, float* vu, lapack_int* il,
+                    lapack_int* iu, float* abstol, lapack_int* m, float* w,
+                    float* z, lapack_int* ldz, float* work, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_dsbevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_int* kd, double* ab, lapack_int* ldab, double* q,
+                    lapack_int* ldq, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, double* abstol, lapack_int* m, double* w,
+                    double* z, lapack_int* ldz, double* work, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_chbevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_int* kd, lapack_complex_float* ab, lapack_int* ldab,
+                    lapack_complex_float* q, lapack_int* ldq, float* vl,
+                    float* vu, lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_complex_float* work, float* rwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_zhbevx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_int* kd, lapack_complex_double* ab, lapack_int* ldab,
+                    lapack_complex_double* q, lapack_int* ldq, double* vl,
+                    double* vu, lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, lapack_complex_double* z,
+                    lapack_int* ldz, lapack_complex_double* work, double* rwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_sstev( char* jobz, lapack_int* n, float* d, float* e, float* z,
+                   lapack_int* ldz, float* work, lapack_int *info );
+void LAPACK_dstev( char* jobz, lapack_int* n, double* d, double* e, double* z,
+                   lapack_int* ldz, double* work, lapack_int *info );
+void LAPACK_sstevd( char* jobz, lapack_int* n, float* d, float* e, float* z,
+                    lapack_int* ldz, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_dstevd( char* jobz, lapack_int* n, double* d, double* e, double* z,
+                    lapack_int* ldz, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_sstevx( char* jobz, char* range, lapack_int* n, float* d, float* e,
+                    float* vl, float* vu, lapack_int* il, lapack_int* iu,
+                    float* abstol, lapack_int* m, float* w, float* z,
+                    lapack_int* ldz, float* work, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_dstevx( char* jobz, char* range, lapack_int* n, double* d,
+                    double* e, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, double* abstol, lapack_int* m, double* w,
+                    double* z, lapack_int* ldz, double* work, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_sstevr( char* jobz, char* range, lapack_int* n, float* d, float* e,
+                    float* vl, float* vu, lapack_int* il, lapack_int* iu,
+                    float* abstol, lapack_int* m, float* w, float* z,
+                    lapack_int* ldz, lapack_int* isuppz, float* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_dstevr( char* jobz, char* range, lapack_int* n, double* d,
+                    double* e, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, double* abstol, lapack_int* m, double* w,
+                    double* z, lapack_int* ldz, lapack_int* isuppz,
+                    double* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_sgees( char* jobvs, char* sort, LAPACK_S_SELECT2 select,
+                   lapack_int* n, float* a, lapack_int* lda, lapack_int* sdim,
+                   float* wr, float* wi, float* vs, lapack_int* ldvs,
+                   float* work, lapack_int* lwork, lapack_logical* bwork,
+                   lapack_int *info );
+void LAPACK_dgees( char* jobvs, char* sort, LAPACK_D_SELECT2 select,
+                   lapack_int* n, double* a, lapack_int* lda, lapack_int* sdim,
+                   double* wr, double* wi, double* vs, lapack_int* ldvs,
+                   double* work, lapack_int* lwork, lapack_logical* bwork,
+                   lapack_int *info );
+void LAPACK_cgees( char* jobvs, char* sort, LAPACK_C_SELECT1 select,
+                   lapack_int* n, lapack_complex_float* a, lapack_int* lda,
+                   lapack_int* sdim, lapack_complex_float* w,
+                   lapack_complex_float* vs, lapack_int* ldvs,
+                   lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                   lapack_logical* bwork, lapack_int *info );
+void LAPACK_zgees( char* jobvs, char* sort, LAPACK_Z_SELECT1 select,
+                   lapack_int* n, lapack_complex_double* a, lapack_int* lda,
+                   lapack_int* sdim, lapack_complex_double* w,
+                   lapack_complex_double* vs, lapack_int* ldvs,
+                   lapack_complex_double* work, lapack_int* lwork,
+                   double* rwork, lapack_logical* bwork, lapack_int *info );
+void LAPACK_sgeesx( char* jobvs, char* sort, LAPACK_S_SELECT2 select,
+                    char* sense, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int* sdim, float* wr, float* wi, float* vs,
+                    lapack_int* ldvs, float* rconde, float* rcondv, float* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_logical* bwork, lapack_int *info );
+void LAPACK_dgeesx( char* jobvs, char* sort, LAPACK_D_SELECT2 select,
+                    char* sense, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int* sdim, double* wr, double* wi, double* vs,
+                    lapack_int* ldvs, double* rconde, double* rcondv,
+                    double* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_cgeesx( char* jobvs, char* sort, LAPACK_C_SELECT1 select,
+                    char* sense, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* sdim, lapack_complex_float* w,
+                    lapack_complex_float* vs, lapack_int* ldvs, float* rconde,
+                    float* rcondv, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_zgeesx( char* jobvs, char* sort, LAPACK_Z_SELECT1 select,
+                    char* sense, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* sdim, lapack_complex_double* w,
+                    lapack_complex_double* vs, lapack_int* ldvs, double* rconde,
+                    double* rcondv, lapack_complex_double* work,
+                    lapack_int* lwork, double* rwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_sgeev( char* jobvl, char* jobvr, lapack_int* n, float* a,
+                   lapack_int* lda, float* wr, float* wi, float* vl,
+                   lapack_int* ldvl, float* vr, lapack_int* ldvr, float* work,
+                   lapack_int* lwork, lapack_int *info );
+void LAPACK_dgeev( char* jobvl, char* jobvr, lapack_int* n, double* a,
+                   lapack_int* lda, double* wr, double* wi, double* vl,
+                   lapack_int* ldvl, double* vr, lapack_int* ldvr, double* work,
+                   lapack_int* lwork, lapack_int *info );
+void LAPACK_cgeev( char* jobvl, char* jobvr, lapack_int* n,
+                   lapack_complex_float* a, lapack_int* lda,
+                   lapack_complex_float* w, lapack_complex_float* vl,
+                   lapack_int* ldvl, lapack_complex_float* vr, lapack_int* ldvr,
+                   lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                   lapack_int *info );
+void LAPACK_zgeev( char* jobvl, char* jobvr, lapack_int* n,
+                   lapack_complex_double* a, lapack_int* lda,
+                   lapack_complex_double* w, lapack_complex_double* vl,
+                   lapack_int* ldvl, lapack_complex_double* vr,
+                   lapack_int* ldvr, lapack_complex_double* work,
+                   lapack_int* lwork, double* rwork, lapack_int *info );
+void LAPACK_sgeevx( char* balanc, char* jobvl, char* jobvr, char* sense,
+                    lapack_int* n, float* a, lapack_int* lda, float* wr,
+                    float* wi, float* vl, lapack_int* ldvl, float* vr,
+                    lapack_int* ldvr, lapack_int* ilo, lapack_int* ihi,
+                    float* scale, float* abnrm, float* rconde, float* rcondv,
+                    float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_dgeevx( char* balanc, char* jobvl, char* jobvr, char* sense,
+                    lapack_int* n, double* a, lapack_int* lda, double* wr,
+                    double* wi, double* vl, lapack_int* ldvl, double* vr,
+                    lapack_int* ldvr, lapack_int* ilo, lapack_int* ihi,
+                    double* scale, double* abnrm, double* rconde,
+                    double* rcondv, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_cgeevx( char* balanc, char* jobvl, char* jobvr, char* sense,
+                    lapack_int* n, lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* w, lapack_complex_float* vl,
+                    lapack_int* ldvl, lapack_complex_float* vr,
+                    lapack_int* ldvr, lapack_int* ilo, lapack_int* ihi,
+                    float* scale, float* abnrm, float* rconde, float* rcondv,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int *info );
+void LAPACK_zgeevx( char* balanc, char* jobvl, char* jobvr, char* sense,
+                    lapack_int* n, lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* w, lapack_complex_double* vl,
+                    lapack_int* ldvl, lapack_complex_double* vr,
+                    lapack_int* ldvr, lapack_int* ilo, lapack_int* ihi,
+                    double* scale, double* abnrm, double* rconde,
+                    double* rcondv, lapack_complex_double* work,
+                    lapack_int* lwork, double* rwork, lapack_int *info );
+void LAPACK_sgesvd( char* jobu, char* jobvt, lapack_int* m, lapack_int* n,
+                    float* a, lapack_int* lda, float* s, float* u,
+                    lapack_int* ldu, float* vt, lapack_int* ldvt, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_dgesvd( char* jobu, char* jobvt, lapack_int* m, lapack_int* n,
+                    double* a, lapack_int* lda, double* s, double* u,
+                    lapack_int* ldu, double* vt, lapack_int* ldvt, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_cgesvd( char* jobu, char* jobvt, lapack_int* m, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda, float* s,
+                    lapack_complex_float* u, lapack_int* ldu,
+                    lapack_complex_float* vt, lapack_int* ldvt,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int *info );
+void LAPACK_zgesvd( char* jobu, char* jobvt, lapack_int* m, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda, double* s,
+                    lapack_complex_double* u, lapack_int* ldu,
+                    lapack_complex_double* vt, lapack_int* ldvt,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int *info );
+void LAPACK_sgesdd( char* jobz, lapack_int* m, lapack_int* n, float* a,
+                    lapack_int* lda, float* s, float* u, lapack_int* ldu,
+                    float* vt, lapack_int* ldvt, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dgesdd( char* jobz, lapack_int* m, lapack_int* n, double* a,
+                    lapack_int* lda, double* s, double* u, lapack_int* ldu,
+                    double* vt, lapack_int* ldvt, double* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_int *info );
+void LAPACK_cgesdd( char* jobz, lapack_int* m, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda, float* s,
+                    lapack_complex_float* u, lapack_int* ldu,
+                    lapack_complex_float* vt, lapack_int* ldvt,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_zgesdd( char* jobz, lapack_int* m, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda, double* s,
+                    lapack_complex_double* u, lapack_int* ldu,
+                    lapack_complex_double* vt, lapack_int* ldvt,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* iwork, lapack_int *info );
+void LAPACK_dgejsv( char* joba, char* jobu, char* jobv, char* jobr, char* jobt,
+                    char* jobp, lapack_int* m, lapack_int* n, double* a,
+                    lapack_int* lda, double* sva, double* u, lapack_int* ldu,
+                    double* v, lapack_int* ldv, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_sgejsv( char* joba, char* jobu, char* jobv, char* jobr, char* jobt,
+                    char* jobp, lapack_int* m, lapack_int* n, float* a,
+                    lapack_int* lda, float* sva, float* u, lapack_int* ldu,
+                    float* v, lapack_int* ldv, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_dgesvj( char* joba, char* jobu, char* jobv, lapack_int* m,
+                    lapack_int* n, double* a, lapack_int* lda, double* sva,
+                    lapack_int* mv, double* v, lapack_int* ldv, double* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sgesvj( char* joba, char* jobu, char* jobv, lapack_int* m,
+                    lapack_int* n, float* a, lapack_int* lda, float* sva,
+                    lapack_int* mv, float* v, lapack_int* ldv, float* work,
+                    lapack_int* lwork, lapack_int *info );
+void LAPACK_sggsvd( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* n, lapack_int* p, lapack_int* k, lapack_int* l,
+                    float* a, lapack_int* lda, float* b, lapack_int* ldb,
+                    float* alpha, float* beta, float* u, lapack_int* ldu,
+                    float* v, lapack_int* ldv, float* q, lapack_int* ldq,
+                    float* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_dggsvd( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* n, lapack_int* p, lapack_int* k, lapack_int* l,
+                    double* a, lapack_int* lda, double* b, lapack_int* ldb,
+                    double* alpha, double* beta, double* u, lapack_int* ldu,
+                    double* v, lapack_int* ldv, double* q, lapack_int* ldq,
+                    double* work, lapack_int* iwork, lapack_int *info );
+void LAPACK_cggsvd( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* n, lapack_int* p, lapack_int* k, lapack_int* l,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb, float* alpha,
+                    float* beta, lapack_complex_float* u, lapack_int* ldu,
+                    lapack_complex_float* v, lapack_int* ldv,
+                    lapack_complex_float* q, lapack_int* ldq,
+                    lapack_complex_float* work, float* rwork, lapack_int* iwork,
+                    lapack_int *info );
+void LAPACK_zggsvd( char* jobu, char* jobv, char* jobq, lapack_int* m,
+                    lapack_int* n, lapack_int* p, lapack_int* k, lapack_int* l,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb, double* alpha,
+                    double* beta, lapack_complex_double* u, lapack_int* ldu,
+                    lapack_complex_double* v, lapack_int* ldv,
+                    lapack_complex_double* q, lapack_int* ldq,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int* iwork, lapack_int *info );
+void LAPACK_ssygv( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                   float* a, lapack_int* lda, float* b, lapack_int* ldb,
+                   float* w, float* work, lapack_int* lwork, lapack_int *info );
+void LAPACK_dsygv( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                   double* a, lapack_int* lda, double* b, lapack_int* ldb,
+                   double* w, double* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_chegv( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                   lapack_complex_float* a, lapack_int* lda,
+                   lapack_complex_float* b, lapack_int* ldb, float* w,
+                   lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                   lapack_int *info );
+void LAPACK_zhegv( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                   lapack_complex_double* a, lapack_int* lda,
+                   lapack_complex_double* b, lapack_int* ldb, double* w,
+                   lapack_complex_double* work, lapack_int* lwork,
+                   double* rwork, lapack_int *info );
+void LAPACK_ssygvd( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                    float* a, lapack_int* lda, float* b, lapack_int* ldb,
+                    float* w, float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_dsygvd( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                    double* a, lapack_int* lda, double* b, lapack_int* ldb,
+                    double* w, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_chegvd( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb, float* w,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* lrwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_zhegvd( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb, double* w,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_ssygvx( lapack_int* itype, char* jobz, char* range, char* uplo,
+                    lapack_int* n, float* a, lapack_int* lda, float* b,
+                    lapack_int* ldb, float* vl, float* vu, lapack_int* il,
+                    lapack_int* iu, float* abstol, lapack_int* m, float* w,
+                    float* z, lapack_int* ldz, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_dsygvx( lapack_int* itype, char* jobz, char* range, char* uplo,
+                    lapack_int* n, double* a, lapack_int* lda, double* b,
+                    lapack_int* ldb, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, double* abstol, lapack_int* m, double* w,
+                    double* z, lapack_int* ldz, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_chegvx( lapack_int* itype, char* jobz, char* range, char* uplo,
+                    lapack_int* n, lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb, float* vl,
+                    float* vu, lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_zhegvx( lapack_int* itype, char* jobz, char* range, char* uplo,
+                    lapack_int* n, lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb, double* vl,
+                    double* vu, lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, lapack_complex_double* z,
+                    lapack_int* ldz, lapack_complex_double* work,
+                    lapack_int* lwork, double* rwork, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_sspgv( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                   float* ap, float* bp, float* w, float* z, lapack_int* ldz,
+                   float* work, lapack_int *info );
+void LAPACK_dspgv( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                   double* ap, double* bp, double* w, double* z,
+                   lapack_int* ldz, double* work, lapack_int *info );
+void LAPACK_chpgv( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                   lapack_complex_float* ap, lapack_complex_float* bp, float* w,
+                   lapack_complex_float* z, lapack_int* ldz,
+                   lapack_complex_float* work, float* rwork, lapack_int *info );
+void LAPACK_zhpgv( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                   lapack_complex_double* ap, lapack_complex_double* bp,
+                   double* w, lapack_complex_double* z, lapack_int* ldz,
+                   lapack_complex_double* work, double* rwork,
+                   lapack_int *info );
+void LAPACK_sspgvd( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                    float* ap, float* bp, float* w, float* z, lapack_int* ldz,
+                    float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_dspgvd( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                    double* ap, double* bp, double* w, double* z,
+                    lapack_int* ldz, double* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_int* liwork, lapack_int *info );
+void LAPACK_chpgvd( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                    lapack_complex_float* ap, lapack_complex_float* bp,
+                    float* w, lapack_complex_float* z, lapack_int* ldz,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* lrwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_zhpgvd( lapack_int* itype, char* jobz, char* uplo, lapack_int* n,
+                    lapack_complex_double* ap, lapack_complex_double* bp,
+                    double* w, lapack_complex_double* z, lapack_int* ldz,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_sspgvx( lapack_int* itype, char* jobz, char* range, char* uplo,
+                    lapack_int* n, float* ap, float* bp, float* vl, float* vu,
+                    lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, float* z, lapack_int* ldz,
+                    float* work, lapack_int* iwork, lapack_int* ifail,
+                    lapack_int *info );
+void LAPACK_dspgvx( lapack_int* itype, char* jobz, char* range, char* uplo,
+                    lapack_int* n, double* ap, double* bp, double* vl,
+                    double* vu, lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, double* z, lapack_int* ldz,
+                    double* work, lapack_int* iwork, lapack_int* ifail,
+                    lapack_int *info );
+void LAPACK_chpgvx( lapack_int* itype, char* jobz, char* range, char* uplo,
+                    lapack_int* n, lapack_complex_float* ap,
+                    lapack_complex_float* bp, float* vl, float* vu,
+                    lapack_int* il, lapack_int* iu, float* abstol,
+                    lapack_int* m, float* w, lapack_complex_float* z,
+                    lapack_int* ldz, lapack_complex_float* work, float* rwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_zhpgvx( lapack_int* itype, char* jobz, char* range, char* uplo,
+                    lapack_int* n, lapack_complex_double* ap,
+                    lapack_complex_double* bp, double* vl, double* vu,
+                    lapack_int* il, lapack_int* iu, double* abstol,
+                    lapack_int* m, double* w, lapack_complex_double* z,
+                    lapack_int* ldz, lapack_complex_double* work, double* rwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_ssbgv( char* jobz, char* uplo, lapack_int* n, lapack_int* ka,
+                   lapack_int* kb, float* ab, lapack_int* ldab, float* bb,
+                   lapack_int* ldbb, float* w, float* z, lapack_int* ldz,
+                   float* work, lapack_int *info );
+void LAPACK_dsbgv( char* jobz, char* uplo, lapack_int* n, lapack_int* ka,
+                   lapack_int* kb, double* ab, lapack_int* ldab, double* bb,
+                   lapack_int* ldbb, double* w, double* z, lapack_int* ldz,
+                   double* work, lapack_int *info );
+void LAPACK_chbgv( char* jobz, char* uplo, lapack_int* n, lapack_int* ka,
+                   lapack_int* kb, lapack_complex_float* ab, lapack_int* ldab,
+                   lapack_complex_float* bb, lapack_int* ldbb, float* w,
+                   lapack_complex_float* z, lapack_int* ldz,
+                   lapack_complex_float* work, float* rwork, lapack_int *info );
+void LAPACK_zhbgv( char* jobz, char* uplo, lapack_int* n, lapack_int* ka,
+                   lapack_int* kb, lapack_complex_double* ab, lapack_int* ldab,
+                   lapack_complex_double* bb, lapack_int* ldbb, double* w,
+                   lapack_complex_double* z, lapack_int* ldz,
+                   lapack_complex_double* work, double* rwork,
+                   lapack_int *info );
+void LAPACK_ssbgvd( char* jobz, char* uplo, lapack_int* n, lapack_int* ka,
+                    lapack_int* kb, float* ab, lapack_int* ldab, float* bb,
+                    lapack_int* ldbb, float* w, float* z, lapack_int* ldz,
+                    float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_dsbgvd( char* jobz, char* uplo, lapack_int* n, lapack_int* ka,
+                    lapack_int* kb, double* ab, lapack_int* ldab, double* bb,
+                    lapack_int* ldbb, double* w, double* z, lapack_int* ldz,
+                    double* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_chbgvd( char* jobz, char* uplo, lapack_int* n, lapack_int* ka,
+                    lapack_int* kb, lapack_complex_float* ab, lapack_int* ldab,
+                    lapack_complex_float* bb, lapack_int* ldbb, float* w,
+                    lapack_complex_float* z, lapack_int* ldz,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* lrwork, lapack_int* iwork, lapack_int* liwork,
+                    lapack_int *info );
+void LAPACK_zhbgvd( char* jobz, char* uplo, lapack_int* n, lapack_int* ka,
+                    lapack_int* kb, lapack_complex_double* ab, lapack_int* ldab,
+                    lapack_complex_double* bb, lapack_int* ldbb, double* w,
+                    lapack_complex_double* z, lapack_int* ldz,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_int *info );
+void LAPACK_ssbgvx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_int* ka, lapack_int* kb, float* ab, lapack_int* ldab,
+                    float* bb, lapack_int* ldbb, float* q, lapack_int* ldq,
+                    float* vl, float* vu, lapack_int* il, lapack_int* iu,
+                    float* abstol, lapack_int* m, float* w, float* z,
+                    lapack_int* ldz, float* work, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_dsbgvx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_int* ka, lapack_int* kb, double* ab,
+                    lapack_int* ldab, double* bb, lapack_int* ldbb, double* q,
+                    lapack_int* ldq, double* vl, double* vu, lapack_int* il,
+                    lapack_int* iu, double* abstol, lapack_int* m, double* w,
+                    double* z, lapack_int* ldz, double* work, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_chbgvx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_int* ka, lapack_int* kb, lapack_complex_float* ab,
+                    lapack_int* ldab, lapack_complex_float* bb,
+                    lapack_int* ldbb, lapack_complex_float* q, lapack_int* ldq,
+                    float* vl, float* vu, lapack_int* il, lapack_int* iu,
+                    float* abstol, lapack_int* m, float* w,
+                    lapack_complex_float* z, lapack_int* ldz,
+                    lapack_complex_float* work, float* rwork, lapack_int* iwork,
+                    lapack_int* ifail, lapack_int *info );
+void LAPACK_zhbgvx( char* jobz, char* range, char* uplo, lapack_int* n,
+                    lapack_int* ka, lapack_int* kb, lapack_complex_double* ab,
+                    lapack_int* ldab, lapack_complex_double* bb,
+                    lapack_int* ldbb, lapack_complex_double* q, lapack_int* ldq,
+                    double* vl, double* vu, lapack_int* il, lapack_int* iu,
+                    double* abstol, lapack_int* m, double* w,
+                    lapack_complex_double* z, lapack_int* ldz,
+                    lapack_complex_double* work, double* rwork,
+                    lapack_int* iwork, lapack_int* ifail, lapack_int *info );
+void LAPACK_sgges( char* jobvsl, char* jobvsr, char* sort,
+                   LAPACK_S_SELECT3 selctg, lapack_int* n, float* a,
+                   lapack_int* lda, float* b, lapack_int* ldb, lapack_int* sdim,
+                   float* alphar, float* alphai, float* beta, float* vsl,
+                   lapack_int* ldvsl, float* vsr, lapack_int* ldvsr,
+                   float* work, lapack_int* lwork, lapack_logical* bwork,
+                   lapack_int *info );
+void LAPACK_dgges( char* jobvsl, char* jobvsr, char* sort,
+                   LAPACK_D_SELECT3 selctg, lapack_int* n, double* a,
+                   lapack_int* lda, double* b, lapack_int* ldb,
+                   lapack_int* sdim, double* alphar, double* alphai,
+                   double* beta, double* vsl, lapack_int* ldvsl, double* vsr,
+                   lapack_int* ldvsr, double* work, lapack_int* lwork,
+                   lapack_logical* bwork, lapack_int *info );
+void LAPACK_cgges( char* jobvsl, char* jobvsr, char* sort,
+                   LAPACK_C_SELECT2 selctg, lapack_int* n,
+                   lapack_complex_float* a, lapack_int* lda,
+                   lapack_complex_float* b, lapack_int* ldb, lapack_int* sdim,
+                   lapack_complex_float* alpha, lapack_complex_float* beta,
+                   lapack_complex_float* vsl, lapack_int* ldvsl,
+                   lapack_complex_float* vsr, lapack_int* ldvsr,
+                   lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                   lapack_logical* bwork, lapack_int *info );
+void LAPACK_zgges( char* jobvsl, char* jobvsr, char* sort,
+                   LAPACK_Z_SELECT2 selctg, lapack_int* n,
+                   lapack_complex_double* a, lapack_int* lda,
+                   lapack_complex_double* b, lapack_int* ldb, lapack_int* sdim,
+                   lapack_complex_double* alpha, lapack_complex_double* beta,
+                   lapack_complex_double* vsl, lapack_int* ldvsl,
+                   lapack_complex_double* vsr, lapack_int* ldvsr,
+                   lapack_complex_double* work, lapack_int* lwork,
+                   double* rwork, lapack_logical* bwork, lapack_int *info );
+void LAPACK_sggesx( char* jobvsl, char* jobvsr, char* sort,
+                    LAPACK_S_SELECT3 selctg, char* sense, lapack_int* n,
+                    float* a, lapack_int* lda, float* b, lapack_int* ldb,
+                    lapack_int* sdim, float* alphar, float* alphai, float* beta,
+                    float* vsl, lapack_int* ldvsl, float* vsr,
+                    lapack_int* ldvsr, float* rconde, float* rcondv,
+                    float* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_dggesx( char* jobvsl, char* jobvsr, char* sort,
+                    LAPACK_D_SELECT3 selctg, char* sense, lapack_int* n,
+                    double* a, lapack_int* lda, double* b, lapack_int* ldb,
+                    lapack_int* sdim, double* alphar, double* alphai,
+                    double* beta, double* vsl, lapack_int* ldvsl, double* vsr,
+                    lapack_int* ldvsr, double* rconde, double* rcondv,
+                    double* work, lapack_int* lwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_cggesx( char* jobvsl, char* jobvsr, char* sort,
+                    LAPACK_C_SELECT2 selctg, char* sense, lapack_int* n,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb, lapack_int* sdim,
+                    lapack_complex_float* alpha, lapack_complex_float* beta,
+                    lapack_complex_float* vsl, lapack_int* ldvsl,
+                    lapack_complex_float* vsr, lapack_int* ldvsr, float* rconde,
+                    float* rcondv, lapack_complex_float* work,
+                    lapack_int* lwork, float* rwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_zggesx( char* jobvsl, char* jobvsr, char* sort,
+                    LAPACK_Z_SELECT2 selctg, char* sense, lapack_int* n,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb, lapack_int* sdim,
+                    lapack_complex_double* alpha, lapack_complex_double* beta,
+                    lapack_complex_double* vsl, lapack_int* ldvsl,
+                    lapack_complex_double* vsr, lapack_int* ldvsr,
+                    double* rconde, double* rcondv, lapack_complex_double* work,
+                    lapack_int* lwork, double* rwork, lapack_int* iwork,
+                    lapack_int* liwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_sggev( char* jobvl, char* jobvr, lapack_int* n, float* a,
+                   lapack_int* lda, float* b, lapack_int* ldb, float* alphar,
+                   float* alphai, float* beta, float* vl, lapack_int* ldvl,
+                   float* vr, lapack_int* ldvr, float* work, lapack_int* lwork,
+                   lapack_int *info );
+void LAPACK_dggev( char* jobvl, char* jobvr, lapack_int* n, double* a,
+                   lapack_int* lda, double* b, lapack_int* ldb, double* alphar,
+                   double* alphai, double* beta, double* vl, lapack_int* ldvl,
+                   double* vr, lapack_int* ldvr, double* work,
+                   lapack_int* lwork, lapack_int *info );
+void LAPACK_cggev( char* jobvl, char* jobvr, lapack_int* n,
+                   lapack_complex_float* a, lapack_int* lda,
+                   lapack_complex_float* b, lapack_int* ldb,
+                   lapack_complex_float* alpha, lapack_complex_float* beta,
+                   lapack_complex_float* vl, lapack_int* ldvl,
+                   lapack_complex_float* vr, lapack_int* ldvr,
+                   lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                   lapack_int *info );
+void LAPACK_zggev( char* jobvl, char* jobvr, lapack_int* n,
+                   lapack_complex_double* a, lapack_int* lda,
+                   lapack_complex_double* b, lapack_int* ldb,
+                   lapack_complex_double* alpha, lapack_complex_double* beta,
+                   lapack_complex_double* vl, lapack_int* ldvl,
+                   lapack_complex_double* vr, lapack_int* ldvr,
+                   lapack_complex_double* work, lapack_int* lwork,
+                   double* rwork, lapack_int *info );
+void LAPACK_sggevx( char* balanc, char* jobvl, char* jobvr, char* sense,
+                    lapack_int* n, float* a, lapack_int* lda, float* b,
+                    lapack_int* ldb, float* alphar, float* alphai, float* beta,
+                    float* vl, lapack_int* ldvl, float* vr, lapack_int* ldvr,
+                    lapack_int* ilo, lapack_int* ihi, float* lscale,
+                    float* rscale, float* abnrm, float* bbnrm, float* rconde,
+                    float* rcondv, float* work, lapack_int* lwork,
+                    lapack_int* iwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_dggevx( char* balanc, char* jobvl, char* jobvr, char* sense,
+                    lapack_int* n, double* a, lapack_int* lda, double* b,
+                    lapack_int* ldb, double* alphar, double* alphai,
+                    double* beta, double* vl, lapack_int* ldvl, double* vr,
+                    lapack_int* ldvr, lapack_int* ilo, lapack_int* ihi,
+                    double* lscale, double* rscale, double* abnrm,
+                    double* bbnrm, double* rconde, double* rcondv, double* work,
+                    lapack_int* lwork, lapack_int* iwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_cggevx( char* balanc, char* jobvl, char* jobvr, char* sense,
+                    lapack_int* n, lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    lapack_complex_float* alpha, lapack_complex_float* beta,
+                    lapack_complex_float* vl, lapack_int* ldvl,
+                    lapack_complex_float* vr, lapack_int* ldvr, lapack_int* ilo,
+                    lapack_int* ihi, float* lscale, float* rscale, float* abnrm,
+                    float* bbnrm, float* rconde, float* rcondv,
+                    lapack_complex_float* work, lapack_int* lwork, float* rwork,
+                    lapack_int* iwork, lapack_logical* bwork,
+                    lapack_int *info );
+void LAPACK_zggevx( char* balanc, char* jobvl, char* jobvr, char* sense,
+                    lapack_int* n, lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* alpha, lapack_complex_double* beta,
+                    lapack_complex_double* vl, lapack_int* ldvl,
+                    lapack_complex_double* vr, lapack_int* ldvr,
+                    lapack_int* ilo, lapack_int* ihi, double* lscale,
+                    double* rscale, double* abnrm, double* bbnrm,
+                    double* rconde, double* rcondv, lapack_complex_double* work,
+                    lapack_int* lwork, double* rwork, lapack_int* iwork,
+                    lapack_logical* bwork, lapack_int *info );
+void LAPACK_dsfrk( char* transr, char* uplo, char* trans, lapack_int* n,
+                   lapack_int* k, double* alpha, const double* a,
+                   lapack_int* lda, double* beta, double* c );
+void LAPACK_ssfrk( char* transr, char* uplo, char* trans, lapack_int* n,
+                   lapack_int* k, float* alpha, const float* a, lapack_int* lda,
+                   float* beta, float* c );
+void LAPACK_zhfrk( char* transr, char* uplo, char* trans, lapack_int* n,
+                   lapack_int* k, double* alpha, const lapack_complex_double* a,
+                   lapack_int* lda, double* beta, lapack_complex_double* c );
+void LAPACK_chfrk( char* transr, char* uplo, char* trans, lapack_int* n,
+                   lapack_int* k, float* alpha, const lapack_complex_float* a,
+                   lapack_int* lda, float* beta, lapack_complex_float* c );
+void LAPACK_dtfsm( char* transr, char* side, char* uplo, char* trans,
+                   char* diag, lapack_int* m, lapack_int* n, double* alpha,
+                   const double* a, double* b, lapack_int* ldb );
+void LAPACK_stfsm( char* transr, char* side, char* uplo, char* trans,
+                   char* diag, lapack_int* m, lapack_int* n, float* alpha,
+                   const float* a, float* b, lapack_int* ldb );
+void LAPACK_ztfsm( char* transr, char* side, char* uplo, char* trans,
+                   char* diag, lapack_int* m, lapack_int* n,
+                   lapack_complex_double* alpha, const lapack_complex_double* a,
+                   lapack_complex_double* b, lapack_int* ldb );
+void LAPACK_ctfsm( char* transr, char* side, char* uplo, char* trans,
+                   char* diag, lapack_int* m, lapack_int* n,
+                   lapack_complex_float* alpha, const lapack_complex_float* a,
+                   lapack_complex_float* b, lapack_int* ldb );
+void LAPACK_dtfttp( char* transr, char* uplo, lapack_int* n, const double* arf,
+                    double* ap, lapack_int *info );
+void LAPACK_stfttp( char* transr, char* uplo, lapack_int* n, const float* arf,
+                    float* ap, lapack_int *info );
+void LAPACK_ztfttp( char* transr, char* uplo, lapack_int* n,
+                    const lapack_complex_double* arf, lapack_complex_double* ap,
+                    lapack_int *info );
+void LAPACK_ctfttp( char* transr, char* uplo, lapack_int* n,
+                    const lapack_complex_float* arf, lapack_complex_float* ap,
+                    lapack_int *info );
+void LAPACK_dtfttr( char* transr, char* uplo, lapack_int* n, const double* arf,
+                    double* a, lapack_int* lda, lapack_int *info );
+void LAPACK_stfttr( char* transr, char* uplo, lapack_int* n, const float* arf,
+                    float* a, lapack_int* lda, lapack_int *info );
+void LAPACK_ztfttr( char* transr, char* uplo, lapack_int* n,
+                    const lapack_complex_double* arf, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_ctfttr( char* transr, char* uplo, lapack_int* n,
+                    const lapack_complex_float* arf, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_dtpttf( char* transr, char* uplo, lapack_int* n, const double* ap,
+                    double* arf, lapack_int *info );
+void LAPACK_stpttf( char* transr, char* uplo, lapack_int* n, const float* ap,
+                    float* arf, lapack_int *info );
+void LAPACK_ztpttf( char* transr, char* uplo, lapack_int* n,
+                    const lapack_complex_double* ap, lapack_complex_double* arf,
+                    lapack_int *info );
+void LAPACK_ctpttf( char* transr, char* uplo, lapack_int* n,
+                    const lapack_complex_float* ap, lapack_complex_float* arf,
+                    lapack_int *info );
+void LAPACK_dtpttr( char* uplo, lapack_int* n, const double* ap, double* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_stpttr( char* uplo, lapack_int* n, const float* ap, float* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_ztpttr( char* uplo, lapack_int* n, const lapack_complex_double* ap,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_ctpttr( char* uplo, lapack_int* n, const lapack_complex_float* ap,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_dtrttf( char* transr, char* uplo, lapack_int* n, const double* a,
+                    lapack_int* lda, double* arf, lapack_int *info );
+void LAPACK_strttf( char* transr, char* uplo, lapack_int* n, const float* a,
+                    lapack_int* lda, float* arf, lapack_int *info );
+void LAPACK_ztrttf( char* transr, char* uplo, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* arf, lapack_int *info );
+void LAPACK_ctrttf( char* transr, char* uplo, lapack_int* n,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* arf, lapack_int *info );
+void LAPACK_dtrttp( char* uplo, lapack_int* n, const double* a, lapack_int* lda,
+                    double* ap, lapack_int *info );
+void LAPACK_strttp( char* uplo, lapack_int* n, const float* a, lapack_int* lda,
+                    float* ap, lapack_int *info );
+void LAPACK_ztrttp( char* uplo, lapack_int* n, const lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* ap,
+                    lapack_int *info );
+void LAPACK_ctrttp( char* uplo, lapack_int* n, const lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* ap,
+                    lapack_int *info );
+void LAPACK_sgeqrfp( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                     float* tau, float* work, lapack_int* lwork,
+                     lapack_int *info );
+void LAPACK_dgeqrfp( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                     double* tau, double* work, lapack_int* lwork,
+                     lapack_int *info );
+void LAPACK_cgeqrfp( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                     lapack_int* lda, lapack_complex_float* tau,
+                     lapack_complex_float* work, lapack_int* lwork,
+                     lapack_int *info );
+void LAPACK_zgeqrfp( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                     lapack_int* lda, lapack_complex_double* tau,
+                     lapack_complex_double* work, lapack_int* lwork,
+                     lapack_int *info );
+void LAPACK_clacgv( lapack_int* n, lapack_complex_float* x, lapack_int* incx );
+void LAPACK_zlacgv( lapack_int* n, lapack_complex_double* x, lapack_int* incx );
+void LAPACK_slarnv( lapack_int* idist, lapack_int* iseed, lapack_int* n,
+                    float* x );
+void LAPACK_dlarnv( lapack_int* idist, lapack_int* iseed, lapack_int* n,
+                    double* x );
+void LAPACK_clarnv( lapack_int* idist, lapack_int* iseed, lapack_int* n,
+                    lapack_complex_float* x );
+void LAPACK_zlarnv( lapack_int* idist, lapack_int* iseed, lapack_int* n,
+                    lapack_complex_double* x );
+void LAPACK_sgeqr2( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    float* tau, float* work, lapack_int *info );
+void LAPACK_dgeqr2( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    double* tau, double* work, lapack_int *info );
+void LAPACK_cgeqr2( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zgeqr2( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_slacpy( char* uplo, lapack_int* m, lapack_int* n, const float* a,
+                    lapack_int* lda, float* b, lapack_int* ldb );
+void LAPACK_dlacpy( char* uplo, lapack_int* m, lapack_int* n, const double* a,
+                    lapack_int* lda, double* b, lapack_int* ldb );
+void LAPACK_clacpy( char* uplo, lapack_int* m, lapack_int* n,
+                    const lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb );
+void LAPACK_zlacpy( char* uplo, lapack_int* m, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb );
+void LAPACK_sgetf2( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_dgetf2( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int* ipiv, lapack_int *info );
+void LAPACK_cgetf2( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* ipiv, lapack_int *info );
+void LAPACK_zgetf2( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* ipiv, lapack_int *info );
+void LAPACK_slaswp( lapack_int* n, float* a, lapack_int* lda, lapack_int* k1,
+                    lapack_int* k2, const lapack_int* ipiv, lapack_int* incx );
+void LAPACK_dlaswp( lapack_int* n, double* a, lapack_int* lda, lapack_int* k1,
+                    lapack_int* k2, const lapack_int* ipiv, lapack_int* incx );
+void LAPACK_claswp( lapack_int* n, lapack_complex_float* a, lapack_int* lda,
+                    lapack_int* k1, lapack_int* k2, const lapack_int* ipiv,
+                    lapack_int* incx );
+void LAPACK_zlaswp( lapack_int* n, lapack_complex_double* a, lapack_int* lda,
+                    lapack_int* k1, lapack_int* k2, const lapack_int* ipiv,
+                    lapack_int* incx );
+float LAPACK_slange( char* norm, lapack_int* m, lapack_int* n, const float* a,
+                    lapack_int* lda, float* work );
+double LAPACK_dlange( char* norm, lapack_int* m, lapack_int* n, const double* a,
+                    lapack_int* lda, double* work );
+float LAPACK_clange( char* norm, lapack_int* m, lapack_int* n,
+                    const lapack_complex_float* a, lapack_int* lda, float* work );
+double LAPACK_zlange( char* norm, lapack_int* m, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda, double* work );
+float LAPACK_clanhe( char* norm, char* uplo, lapack_int* n,
+                    const lapack_complex_float* a, lapack_int* lda, float* work );
+double LAPACK_zlanhe( char* norm, char* uplo, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda, double* work );
+float LAPACK_slansy( char* norm, char* uplo, lapack_int* n, const float* a,
+                    lapack_int* lda, float* work );
+double LAPACK_dlansy( char* norm, char* uplo, lapack_int* n, const double* a,
+                    lapack_int* lda, double* work );
+float LAPACK_clansy( char* norm, char* uplo, lapack_int* n,
+                    const lapack_complex_float* a, lapack_int* lda, float* work );
+double LAPACK_zlansy( char* norm, char* uplo, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda, double* work );
+float LAPACK_slantr( char* norm, char* uplo, char* diag, lapack_int* m,
+                    lapack_int* n, const float* a, lapack_int* lda, float* work );
+double LAPACK_dlantr( char* norm, char* uplo, char* diag, lapack_int* m,
+                    lapack_int* n, const double* a, lapack_int* lda, double* work );
+float LAPACK_clantr( char* norm, char* uplo, char* diag, lapack_int* m,
+                    lapack_int* n, const lapack_complex_float* a, lapack_int* lda,
+                    float* work );
+double LAPACK_zlantr( char* norm, char* uplo, char* diag, lapack_int* m,
+                    lapack_int* n, const lapack_complex_double* a, lapack_int* lda,
+                    double* work );
+float LAPACK_slamch( char* cmach );
+double LAPACK_dlamch( char* cmach );
+void LAPACK_sgelq2( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                    float* tau, float* work, lapack_int *info );
+void LAPACK_dgelq2( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                    double* tau, double* work, lapack_int *info );
+void LAPACK_cgelq2( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_complex_float* tau,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zgelq2( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_complex_double* tau,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_slarfb( char* side, char* trans, char* direct, char* storev,
+                    lapack_int* m, lapack_int* n, lapack_int* k, const float* v,
+                    lapack_int* ldv, const float* t, lapack_int* ldt, float* c,
+                    lapack_int* ldc, float* work, lapack_int* ldwork );
+void LAPACK_dlarfb( char* side, char* trans, char* direct, char* storev,
+                    lapack_int* m, lapack_int* n, lapack_int* k,
+                    const double* v, lapack_int* ldv, const double* t,
+                    lapack_int* ldt, double* c, lapack_int* ldc, double* work,
+                    lapack_int* ldwork );
+void LAPACK_clarfb( char* side, char* trans, char* direct, char* storev,
+                    lapack_int* m, lapack_int* n, lapack_int* k,
+                    const lapack_complex_float* v, lapack_int* ldv,
+                    const lapack_complex_float* t, lapack_int* ldt,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work, lapack_int* ldwork );
+void LAPACK_zlarfb( char* side, char* trans, char* direct, char* storev,
+                    lapack_int* m, lapack_int* n, lapack_int* k,
+                    const lapack_complex_double* v, lapack_int* ldv,
+                    const lapack_complex_double* t, lapack_int* ldt,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    lapack_complex_double* work, lapack_int* ldwork );
+void LAPACK_slarfg( lapack_int* n, float* alpha, float* x, lapack_int* incx,
+                    float* tau );
+void LAPACK_dlarfg( lapack_int* n, double* alpha, double* x, lapack_int* incx,
+                    double* tau );
+void LAPACK_clarfg( lapack_int* n, lapack_complex_float* alpha,
+                    lapack_complex_float* x, lapack_int* incx,
+                    lapack_complex_float* tau );
+void LAPACK_zlarfg( lapack_int* n, lapack_complex_double* alpha,
+                    lapack_complex_double* x, lapack_int* incx,
+                    lapack_complex_double* tau );
+void LAPACK_slarft( char* direct, char* storev, lapack_int* n, lapack_int* k,
+                    const float* v, lapack_int* ldv, const float* tau, float* t,
+                    lapack_int* ldt );
+void LAPACK_dlarft( char* direct, char* storev, lapack_int* n, lapack_int* k,
+                    const double* v, lapack_int* ldv, const double* tau,
+                    double* t, lapack_int* ldt );
+void LAPACK_clarft( char* direct, char* storev, lapack_int* n, lapack_int* k,
+                    const lapack_complex_float* v, lapack_int* ldv,
+                    const lapack_complex_float* tau, lapack_complex_float* t,
+                    lapack_int* ldt );
+void LAPACK_zlarft( char* direct, char* storev, lapack_int* n, lapack_int* k,
+                    const lapack_complex_double* v, lapack_int* ldv,
+                    const lapack_complex_double* tau, lapack_complex_double* t,
+                    lapack_int* ldt );
+void LAPACK_slarfx( char* side, lapack_int* m, lapack_int* n, const float* v,
+                    float* tau, float* c, lapack_int* ldc, float* work );
+void LAPACK_dlarfx( char* side, lapack_int* m, lapack_int* n, const double* v,
+                    double* tau, double* c, lapack_int* ldc, double* work );
+void LAPACK_clarfx( char* side, lapack_int* m, lapack_int* n,
+                    const lapack_complex_float* v, lapack_complex_float* tau,
+                    lapack_complex_float* c, lapack_int* ldc,
+                    lapack_complex_float* work );
+void LAPACK_zlarfx( char* side, lapack_int* m, lapack_int* n,
+                    const lapack_complex_double* v, lapack_complex_double* tau,
+                    lapack_complex_double* c, lapack_int* ldc,
+                    lapack_complex_double* work );
+void LAPACK_slatms( lapack_int* m, lapack_int* n, char* dist, lapack_int* iseed,
+                    char* sym, float* d, lapack_int* mode, float* cond,
+                    float* dmax, lapack_int* kl, lapack_int* ku, char* pack,
+                    float* a, lapack_int* lda, float* work, lapack_int *info );
+void LAPACK_dlatms( lapack_int* m, lapack_int* n, char* dist, lapack_int* iseed,
+                    char* sym, double* d, lapack_int* mode, double* cond,
+                    double* dmax, lapack_int* kl, lapack_int* ku, char* pack,
+                    double* a, lapack_int* lda, double* work,
+                    lapack_int *info );
+void LAPACK_clatms( lapack_int* m, lapack_int* n, char* dist, lapack_int* iseed,
+                    char* sym, float* d, lapack_int* mode, float* cond,
+                    float* dmax, lapack_int* kl, lapack_int* ku, char* pack,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zlatms( lapack_int* m, lapack_int* n, char* dist, lapack_int* iseed,
+                    char* sym, double* d, lapack_int* mode, double* cond,
+                    double* dmax, lapack_int* kl, lapack_int* ku, char* pack,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_slag2d( lapack_int* m, lapack_int* n, const float* sa,
+                    lapack_int* ldsa, double* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_dlag2s( lapack_int* m, lapack_int* n, const double* a,
+                    lapack_int* lda, float* sa, lapack_int* ldsa,
+                    lapack_int *info );
+void LAPACK_clag2z( lapack_int* m, lapack_int* n,
+                    const lapack_complex_float* sa, lapack_int* ldsa,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_zlag2c( lapack_int* m, lapack_int* n,
+                    const lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_float* sa, lapack_int* ldsa,
+                    lapack_int *info );
+void LAPACK_slauum( char* uplo, lapack_int* n, float* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_dlauum( char* uplo, lapack_int* n, double* a, lapack_int* lda,
+                    lapack_int *info );
+void LAPACK_clauum( char* uplo, lapack_int* n, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_zlauum( char* uplo, lapack_int* n, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int *info );
+void LAPACK_slagge( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, const float* d, float* a, lapack_int* lda,
+                    lapack_int* iseed, float* work, lapack_int *info );
+void LAPACK_dlagge( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, const double* d, double* a, lapack_int* lda,
+                    lapack_int* iseed, double* work, lapack_int *info );
+void LAPACK_clagge( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, const float* d, lapack_complex_float* a,
+                    lapack_int* lda, lapack_int* iseed,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zlagge( lapack_int* m, lapack_int* n, lapack_int* kl,
+                    lapack_int* ku, const double* d, lapack_complex_double* a,
+                    lapack_int* lda, lapack_int* iseed,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_slaset( char* uplo, lapack_int* m, lapack_int* n, float* alpha,
+                    float* beta, float* a, lapack_int* lda );
+void LAPACK_dlaset( char* uplo, lapack_int* m, lapack_int* n, double* alpha,
+                    double* beta, double* a, lapack_int* lda );
+void LAPACK_claset( char* uplo, lapack_int* m, lapack_int* n,
+                    lapack_complex_float* alpha, lapack_complex_float* beta,
+                    lapack_complex_float* a, lapack_int* lda );
+void LAPACK_zlaset( char* uplo, lapack_int* m, lapack_int* n,
+                    lapack_complex_double* alpha, lapack_complex_double* beta,
+                    lapack_complex_double* a, lapack_int* lda );
+void LAPACK_slasrt( char* id, lapack_int* n, float* d, lapack_int *info );
+void LAPACK_dlasrt( char* id, lapack_int* n, double* d, lapack_int *info );
+void LAPACK_claghe( lapack_int* n, lapack_int* k, const float* d,
+                    lapack_complex_float* a, lapack_int* lda, lapack_int* iseed,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zlaghe( lapack_int* n, lapack_int* k, const double* d,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_int* iseed, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_slagsy( lapack_int* n, lapack_int* k, const float* d, float* a,
+                    lapack_int* lda, lapack_int* iseed, float* work,
+                    lapack_int *info );
+void LAPACK_dlagsy( lapack_int* n, lapack_int* k, const double* d, double* a,
+                    lapack_int* lda, lapack_int* iseed, double* work,
+                    lapack_int *info );
+void LAPACK_clagsy( lapack_int* n, lapack_int* k, const float* d,
+                    lapack_complex_float* a, lapack_int* lda, lapack_int* iseed,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zlagsy( lapack_int* n, lapack_int* k, const double* d,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_int* iseed, lapack_complex_double* work,
+                    lapack_int *info );
+void LAPACK_slapmr( lapack_logical* forwrd, lapack_int* m, lapack_int* n,
+                    float* x, lapack_int* ldx, lapack_int* k );
+void LAPACK_dlapmr( lapack_logical* forwrd, lapack_int* m, lapack_int* n,
+                    double* x, lapack_int* ldx, lapack_int* k );
+void LAPACK_clapmr( lapack_logical* forwrd, lapack_int* m, lapack_int* n,
+                    lapack_complex_float* x, lapack_int* ldx, lapack_int* k );
+void LAPACK_zlapmr( lapack_logical* forwrd, lapack_int* m, lapack_int* n,
+                    lapack_complex_double* x, lapack_int* ldx, lapack_int* k );
+float LAPACK_slapy2( float* x, float* y );
+double LAPACK_dlapy2( double* x, double* y );
+float LAPACK_slapy3( float* x, float* y, float* z );
+double LAPACK_dlapy3( double* x, double* y, double* z );
+void LAPACK_slartgp( float* f, float* g, float* cs, float* sn, float* r );
+void LAPACK_dlartgp( double* f, double* g, double* cs, double* sn, double* r );
+void LAPACK_slartgs( float* x, float* y, float* sigma, float* cs, float* sn );
+void LAPACK_dlartgs( double* x, double* y, double* sigma, double* cs,
+                     double* sn );
+// LAPACK 3.3.0
+void LAPACK_cbbcsd( char* jobu1, char* jobu2,
+                    char* jobv1t, char* jobv2t, char* trans,
+                    lapack_int* m, lapack_int* p, lapack_int* q,
+                    float* theta, float* phi,
+                    lapack_complex_float* u1, lapack_int* ldu1,
+                    lapack_complex_float* u2, lapack_int* ldu2,
+                    lapack_complex_float* v1t, lapack_int* ldv1t,
+                    lapack_complex_float* v2t, lapack_int* ldv2t,
+                    float* b11d, float* b11e, float* b12d,
+                    float* b12e, float* b21d, float* b21e,
+                    float* b22d, float* b22e, float* rwork,
+                    lapack_int* lrwork , lapack_int *info );
+void LAPACK_cheswapr( char* uplo, lapack_int* n,
+                      lapack_complex_float* a, lapack_int* i1,
+                      lapack_int* i2 );
+void LAPACK_chetri2( char* uplo, lapack_int* n,
+                     lapack_complex_float* a, lapack_int* lda,
+                     const lapack_int* ipiv,
+                     lapack_complex_float* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_chetri2x( char* uplo, lapack_int* n,
+                      lapack_complex_float* a, lapack_int* lda,
+                      const lapack_int* ipiv,
+                      lapack_complex_float* work, lapack_int* nb , lapack_int *info );
+void LAPACK_chetrs2( char* uplo, lapack_int* n,
+                     lapack_int* nrhs, const lapack_complex_float* a,
+                     lapack_int* lda, const lapack_int* ipiv,
+                     lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* work , lapack_int *info );
+void LAPACK_csyconv( char* uplo, char* way,
+                     lapack_int* n, lapack_complex_float* a,
+                     lapack_int* lda, const lapack_int* ipiv,
+                     lapack_complex_float* work , lapack_int *info );
+void LAPACK_csyswapr( char* uplo, lapack_int* n,
+                      lapack_complex_float* a, lapack_int* i1,
+                      lapack_int* i2 );
+void LAPACK_csytri2( char* uplo, lapack_int* n,
+                     lapack_complex_float* a, lapack_int* lda,
+                     const lapack_int* ipiv,
+                     lapack_complex_float* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_csytri2x( char* uplo, lapack_int* n,
+                      lapack_complex_float* a, lapack_int* lda,
+                      const lapack_int* ipiv,
+                      lapack_complex_float* work, lapack_int* nb , lapack_int *info );
+void LAPACK_csytrs2( char* uplo, lapack_int* n,
+                     lapack_int* nrhs, const lapack_complex_float* a,
+                     lapack_int* lda, const lapack_int* ipiv,
+                     lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* work , lapack_int *info );
+void LAPACK_cunbdb( char* trans, char* signs,
+                    lapack_int* m, lapack_int* p, lapack_int* q,
+                    lapack_complex_float* x11, lapack_int* ldx11,
+                    lapack_complex_float* x12, lapack_int* ldx12,
+                    lapack_complex_float* x21, lapack_int* ldx21,
+                    lapack_complex_float* x22, lapack_int* ldx22,
+                    float* theta, float* phi,
+                    lapack_complex_float* taup1,
+                    lapack_complex_float* taup2,
+                    lapack_complex_float* tauq1,
+                    lapack_complex_float* tauq2,
+                    lapack_complex_float* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_cuncsd( char* jobu1, char* jobu2,
+                    char* jobv1t, char* jobv2t, char* trans,
+                    char* signs, lapack_int* m, lapack_int* p,
+                    lapack_int* q, lapack_complex_float* x11,
+                    lapack_int* ldx11, lapack_complex_float* x12,
+                    lapack_int* ldx12, lapack_complex_float* x21,
+                    lapack_int* ldx21, lapack_complex_float* x22,
+                    lapack_int* ldx22, float* theta,
+                    lapack_complex_float* u1, lapack_int* ldu1,
+                    lapack_complex_float* u2, lapack_int* ldu2,
+                    lapack_complex_float* v1t, lapack_int* ldv1t,
+                    lapack_complex_float* v2t, lapack_int* ldv2t,
+                    lapack_complex_float* work, lapack_int* lwork,
+                    float* rwork, lapack_int* lrwork,
+                    lapack_int* iwork , lapack_int *info );
+void LAPACK_dbbcsd( char* jobu1, char* jobu2,
+                    char* jobv1t, char* jobv2t, char* trans,
+                    lapack_int* m, lapack_int* p, lapack_int* q,
+                    double* theta, double* phi, double* u1,
+                    lapack_int* ldu1, double* u2, lapack_int* ldu2,
+                    double* v1t, lapack_int* ldv1t, double* v2t,
+                    lapack_int* ldv2t, double* b11d, double* b11e,
+                    double* b12d, double* b12e, double* b21d,
+                    double* b21e, double* b22d, double* b22e,
+                    double* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_dorbdb( char* trans, char* signs,
+                    lapack_int* m, lapack_int* p, lapack_int* q,
+                    double* x11, lapack_int* ldx11, double* x12,
+                    lapack_int* ldx12, double* x21, lapack_int* ldx21,
+                    double* x22, lapack_int* ldx22, double* theta,
+                    double* phi, double* taup1, double* taup2,
+                    double* tauq1, double* tauq2, double* work,
+                    lapack_int* lwork , lapack_int *info );
+void LAPACK_dorcsd( char* jobu1, char* jobu2,
+                    char* jobv1t, char* jobv2t, char* trans,
+                    char* signs, lapack_int* m, lapack_int* p,
+                    lapack_int* q, double* x11, lapack_int* ldx11,
+                    double* x12, lapack_int* ldx12, double* x21,
+                    lapack_int* ldx21, double* x22, lapack_int* ldx22,
+                    double* theta, double* u1, lapack_int* ldu1,
+                    double* u2, lapack_int* ldu2, double* v1t,
+                    lapack_int* ldv1t, double* v2t, lapack_int* ldv2t,
+                    double* work, lapack_int* lwork,
+                    lapack_int* iwork , lapack_int *info );
+void LAPACK_dsyconv( char* uplo, char* way,
+                     lapack_int* n, double* a, lapack_int* lda,
+                     const lapack_int* ipiv, double* work , lapack_int *info );
+void LAPACK_dsyswapr( char* uplo, lapack_int* n,
+                      double* a, lapack_int* i1, lapack_int* i2 );
+void LAPACK_dsytri2( char* uplo, lapack_int* n,
+                     double* a, lapack_int* lda,
+                     const lapack_int* ipiv,
+                     lapack_complex_double* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_dsytri2x( char* uplo, lapack_int* n,
+                      double* a, lapack_int* lda,
+                      const lapack_int* ipiv, double* work,
+                      lapack_int* nb , lapack_int *info );
+void LAPACK_dsytrs2( char* uplo, lapack_int* n,
+                     lapack_int* nrhs, const double* a,
+                     lapack_int* lda, const lapack_int* ipiv,
+                     double* b, lapack_int* ldb, double* work , lapack_int *info );
+void LAPACK_sbbcsd( char* jobu1, char* jobu2,
+                    char* jobv1t, char* jobv2t, char* trans,
+                    lapack_int* m, lapack_int* p, lapack_int* q,
+                    float* theta, float* phi, float* u1,
+                    lapack_int* ldu1, float* u2, lapack_int* ldu2,
+                    float* v1t, lapack_int* ldv1t, float* v2t,
+                    lapack_int* ldv2t, float* b11d, float* b11e,
+                    float* b12d, float* b12e, float* b21d,
+                    float* b21e, float* b22d, float* b22e,
+                    float* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_sorbdb( char* trans, char* signs,
+                    lapack_int* m, lapack_int* p, lapack_int* q,
+                    float* x11, lapack_int* ldx11, float* x12,
+                    lapack_int* ldx12, float* x21, lapack_int* ldx21,
+                    float* x22, lapack_int* ldx22, float* theta,
+                    float* phi, float* taup1, float* taup2,
+                    float* tauq1, float* tauq2, float* work,
+                    lapack_int* lwork , lapack_int *info );
+void LAPACK_sorcsd( char* jobu1, char* jobu2,
+                    char* jobv1t, char* jobv2t, char* trans,
+                    char* signs, lapack_int* m, lapack_int* p,
+                    lapack_int* q, float* x11, lapack_int* ldx11,
+                    float* x12, lapack_int* ldx12, float* x21,
+                    lapack_int* ldx21, float* x22, lapack_int* ldx22,
+                    float* theta, float* u1, lapack_int* ldu1,
+                    float* u2, lapack_int* ldu2, float* v1t,
+                    lapack_int* ldv1t, float* v2t, lapack_int* ldv2t,
+                    float* work, lapack_int* lwork,
+                    lapack_int* iwork , lapack_int *info );
+void LAPACK_ssyconv( char* uplo, char* way,
+                     lapack_int* n, float* a, lapack_int* lda,
+                     const lapack_int* ipiv, float* work , lapack_int *info );
+void LAPACK_ssyswapr( char* uplo, lapack_int* n,
+                      float* a, lapack_int* i1, lapack_int* i2 );
+void LAPACK_ssytri2( char* uplo, lapack_int* n,
+                     float* a, lapack_int* lda,
+                     const lapack_int* ipiv,
+                     lapack_complex_float* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_ssytri2x( char* uplo, lapack_int* n,
+                      float* a, lapack_int* lda,
+                      const lapack_int* ipiv, float* work,
+                      lapack_int* nb , lapack_int *info );
+void LAPACK_ssytrs2( char* uplo, lapack_int* n,
+                     lapack_int* nrhs, const float* a,
+                     lapack_int* lda, const lapack_int* ipiv,
+                     float* b, lapack_int* ldb, float* work , lapack_int *info );
+void LAPACK_zbbcsd( char* jobu1, char* jobu2,
+                    char* jobv1t, char* jobv2t, char* trans,
+                    lapack_int* m, lapack_int* p, lapack_int* q,
+                    double* theta, double* phi,
+                    lapack_complex_double* u1, lapack_int* ldu1,
+                    lapack_complex_double* u2, lapack_int* ldu2,
+                    lapack_complex_double* v1t, lapack_int* ldv1t,
+                    lapack_complex_double* v2t, lapack_int* ldv2t,
+                    double* b11d, double* b11e, double* b12d,
+                    double* b12e, double* b21d, double* b21e,
+                    double* b22d, double* b22e, double* rwork,
+                    lapack_int* lrwork , lapack_int *info );
+void LAPACK_zheswapr( char* uplo, lapack_int* n,
+                      lapack_complex_double* a, lapack_int* i1,
+                      lapack_int* i2 );
+void LAPACK_zhetri2( char* uplo, lapack_int* n,
+                     lapack_complex_double* a, lapack_int* lda,
+                     const lapack_int* ipiv,
+                     lapack_complex_double* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_zhetri2x( char* uplo, lapack_int* n,
+                      lapack_complex_double* a, lapack_int* lda,
+                      const lapack_int* ipiv,
+                      lapack_complex_double* work, lapack_int* nb , lapack_int *info );
+void LAPACK_zhetrs2( char* uplo, lapack_int* n,
+                     lapack_int* nrhs,
+                     const lapack_complex_double* a, lapack_int* lda,
+                     const lapack_int* ipiv,
+                     lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* work , lapack_int *info );
+void LAPACK_zsyconv( char* uplo, char* way,
+                     lapack_int* n, lapack_complex_double* a,
+                     lapack_int* lda, const lapack_int* ipiv,
+                     lapack_complex_double* work , lapack_int *info );
+void LAPACK_zsyswapr( char* uplo, lapack_int* n,
+                      lapack_complex_double* a, lapack_int* i1,
+                      lapack_int* i2 );
+void LAPACK_zsytri2( char* uplo, lapack_int* n,
+                     lapack_complex_double* a, lapack_int* lda,
+                     const lapack_int* ipiv,
+                     lapack_complex_double* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_zsytri2x( char* uplo, lapack_int* n,
+                      lapack_complex_double* a, lapack_int* lda,
+                      const lapack_int* ipiv,
+                      lapack_complex_double* work, lapack_int* nb , lapack_int *info );
+void LAPACK_zsytrs2( char* uplo, lapack_int* n,
+                     lapack_int* nrhs,
+                     const lapack_complex_double* a, lapack_int* lda,
+                     const lapack_int* ipiv,
+                     lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* work , lapack_int *info );
+void LAPACK_zunbdb( char* trans, char* signs,
+                    lapack_int* m, lapack_int* p, lapack_int* q,
+                    lapack_complex_double* x11, lapack_int* ldx11,
+                    lapack_complex_double* x12, lapack_int* ldx12,
+                    lapack_complex_double* x21, lapack_int* ldx21,
+                    lapack_complex_double* x22, lapack_int* ldx22,
+                    double* theta, double* phi,
+                    lapack_complex_double* taup1,
+                    lapack_complex_double* taup2,
+                    lapack_complex_double* tauq1,
+                    lapack_complex_double* tauq2,
+                    lapack_complex_double* work, lapack_int* lwork , lapack_int *info );
+void LAPACK_zuncsd( char* jobu1, char* jobu2,
+                    char* jobv1t, char* jobv2t, char* trans,
+                    char* signs, lapack_int* m, lapack_int* p,
+                    lapack_int* q, lapack_complex_double* x11,
+                    lapack_int* ldx11, lapack_complex_double* x12,
+                    lapack_int* ldx12, lapack_complex_double* x21,
+                    lapack_int* ldx21, lapack_complex_double* x22,
+                    lapack_int* ldx22, double* theta,
+                    lapack_complex_double* u1, lapack_int* ldu1,
+                    lapack_complex_double* u2, lapack_int* ldu2,
+                    lapack_complex_double* v1t, lapack_int* ldv1t,
+                    lapack_complex_double* v2t, lapack_int* ldv2t,
+                    lapack_complex_double* work, lapack_int* lwork,
+                    double* rwork, lapack_int* lrwork,
+                    lapack_int* iwork , lapack_int *info );
+// LAPACK 3.4.0
+void LAPACK_sgemqrt( char* side, char* trans, lapack_int* m, lapack_int* n,
+                     lapack_int* k, lapack_int* nb, const float* v,
+                     lapack_int* ldv, const float* t, lapack_int* ldt, float* c,
+                     lapack_int* ldc, float* work, lapack_int *info );
+void LAPACK_dgemqrt( char* side, char* trans, lapack_int* m, lapack_int* n,
+                     lapack_int* k, lapack_int* nb, const double* v,
+                     lapack_int* ldv, const double* t, lapack_int* ldt,
+                     double* c, lapack_int* ldc, double* work,
+                     lapack_int *info );
+void LAPACK_cgemqrt( char* side, char* trans, lapack_int* m, lapack_int* n,
+                     lapack_int* k, lapack_int* nb,
+                     const lapack_complex_float* v, lapack_int* ldv,
+                     const lapack_complex_float* t, lapack_int* ldt,
+                     lapack_complex_float* c, lapack_int* ldc,
+                     lapack_complex_float* work, lapack_int *info );
+void LAPACK_zgemqrt( char* side, char* trans, lapack_int* m, lapack_int* n,
+                     lapack_int* k, lapack_int* nb,
+                     const lapack_complex_double* v, lapack_int* ldv,
+                     const lapack_complex_double* t, lapack_int* ldt,
+                     lapack_complex_double* c, lapack_int* ldc,
+                     lapack_complex_double* work, lapack_int *info );
+void LAPACK_sgeqrt( lapack_int* m, lapack_int* n, lapack_int* nb, float* a,
+                    lapack_int* lda, float* t, lapack_int* ldt, float* work,
+                    lapack_int *info );
+void LAPACK_dgeqrt( lapack_int* m, lapack_int* n, lapack_int* nb, double* a,
+                    lapack_int* lda, double* t, lapack_int* ldt, double* work,
+                    lapack_int *info );
+void LAPACK_cgeqrt( lapack_int* m, lapack_int* n, lapack_int* nb,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* t, lapack_int* ldt,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_zgeqrt( lapack_int* m, lapack_int* n, lapack_int* nb,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* t, lapack_int* ldt,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_sgeqrt2( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                     float* t, lapack_int* ldt, lapack_int *info );
+void LAPACK_dgeqrt2( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                     double* t, lapack_int* ldt, lapack_int *info );
+void LAPACK_cgeqrt2( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                     lapack_int* lda, lapack_complex_float* t, lapack_int* ldt,
+                     lapack_int *info );
+void LAPACK_zgeqrt2( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                     lapack_int* lda, lapack_complex_double* t, lapack_int* ldt,
+                     lapack_int *info );
+void LAPACK_sgeqrt3( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                     float* t, lapack_int* ldt, lapack_int *info );
+void LAPACK_dgeqrt3( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                     double* t, lapack_int* ldt, lapack_int *info );
+void LAPACK_cgeqrt3( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                     lapack_int* lda, lapack_complex_float* t, lapack_int* ldt,
+                     lapack_int *info );
+void LAPACK_zgeqrt3( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                     lapack_int* lda, lapack_complex_double* t, lapack_int* ldt,
+                     lapack_int *info );
+void LAPACK_stpmqrt( char* side, char* trans, lapack_int* m, lapack_int* n,
+                     lapack_int* k, lapack_int* l, lapack_int* nb,
+                     const float* v, lapack_int* ldv, const float* t,
+                     lapack_int* ldt, float* a, lapack_int* lda, float* b,
+                     lapack_int* ldb, float* work, lapack_int *info );
+void LAPACK_dtpmqrt( char* side, char* trans, lapack_int* m, lapack_int* n,
+                     lapack_int* k, lapack_int* l, lapack_int* nb,
+                     const double* v, lapack_int* ldv, const double* t,
+                     lapack_int* ldt, double* a, lapack_int* lda, double* b,
+                     lapack_int* ldb, double* work, lapack_int *info );
+void LAPACK_ctpmqrt( char* side, char* trans, lapack_int* m, lapack_int* n,
+                     lapack_int* k, lapack_int* l, lapack_int* nb,
+                     const lapack_complex_float* v, lapack_int* ldv,
+                     const lapack_complex_float* t, lapack_int* ldt,
+                     lapack_complex_float* a, lapack_int* lda,
+                     lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* work, lapack_int *info );
+void LAPACK_ztpmqrt( char* side, char* trans, lapack_int* m, lapack_int* n,
+                     lapack_int* k, lapack_int* l, lapack_int* nb,
+                     const lapack_complex_double* v, lapack_int* ldv,
+                     const lapack_complex_double* t, lapack_int* ldt,
+                     lapack_complex_double* a, lapack_int* lda,
+                     lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* work, lapack_int *info );
+void LAPACK_dtpqrt( lapack_int* m, lapack_int* n, lapack_int* l, lapack_int* nb,
+                    double* a, lapack_int* lda, double* b, lapack_int* ldb,
+                    double* t, lapack_int* ldt, double* work,
+                    lapack_int *info );
+void LAPACK_ctpqrt( lapack_int* m, lapack_int* n, lapack_int* l, lapack_int* nb,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* t, lapack_complex_float* b,
+                    lapack_int* ldb, lapack_int* ldt,
+                    lapack_complex_float* work, lapack_int *info );
+void LAPACK_ztpqrt( lapack_int* m, lapack_int* n, lapack_int* l, lapack_int* nb,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    lapack_complex_double* t, lapack_int* ldt,
+                    lapack_complex_double* work, lapack_int *info );
+void LAPACK_stpqrt2( lapack_int* m, lapack_int* n, float* a, lapack_int* lda,
+                     float* b, lapack_int* ldb, float* t, lapack_int* ldt,
+                     lapack_int *info );
+void LAPACK_dtpqrt2( lapack_int* m, lapack_int* n, double* a, lapack_int* lda,
+                     double* b, lapack_int* ldb, double* t, lapack_int* ldt,
+                     lapack_int *info );
+void LAPACK_ctpqrt2( lapack_int* m, lapack_int* n, lapack_complex_float* a,
+                     lapack_int* lda, lapack_complex_float* b, lapack_int* ldb,
+                     lapack_complex_float* t, lapack_int* ldt,
+                     lapack_int *info );
+void LAPACK_ztpqrt2( lapack_int* m, lapack_int* n, lapack_complex_double* a,
+                     lapack_int* lda, lapack_complex_double* b, lapack_int* ldb,
+                     lapack_complex_double* t, lapack_int* ldt,
+                     lapack_int *info );
+void LAPACK_stprfb( char* side, char* trans, char* direct, char* storev,
+                    lapack_int* m, lapack_int* n, lapack_int* k, lapack_int* l,
+                    const float* v, lapack_int* ldv, const float* t,
+                    lapack_int* ldt, float* a, lapack_int* lda, float* b,
+                    lapack_int* ldb, const float* mywork,
+                    lapack_int* myldwork );
+void LAPACK_dtprfb( char* side, char* trans, char* direct, char* storev,
+                    lapack_int* m, lapack_int* n, lapack_int* k, lapack_int* l,
+                    const double* v, lapack_int* ldv, const double* t,
+                    lapack_int* ldt, double* a, lapack_int* lda, double* b,
+                    lapack_int* ldb, const double* mywork,
+                    lapack_int* myldwork );
+void LAPACK_ctprfb( char* side, char* trans, char* direct, char* storev,
+                    lapack_int* m, lapack_int* n, lapack_int* k, lapack_int* l,
+                    const lapack_complex_float* v, lapack_int* ldv,
+                    const lapack_complex_float* t, lapack_int* ldt,
+                    lapack_complex_float* a, lapack_int* lda,
+                    lapack_complex_float* b, lapack_int* ldb,
+                    const float* mywork, lapack_int* myldwork );
+void LAPACK_ztprfb( char* side, char* trans, char* direct, char* storev,
+                    lapack_int* m, lapack_int* n, lapack_int* k, lapack_int* l,
+                    const lapack_complex_double* v, lapack_int* ldv,
+                    const lapack_complex_double* t, lapack_int* ldt,
+                    lapack_complex_double* a, lapack_int* lda,
+                    lapack_complex_double* b, lapack_int* ldb,
+                    const double* mywork, lapack_int* myldwork );
+// LAPACK 3.X.X
+void LAPACK_csyr( char* uplo, lapack_int* n, lapack_complex_float* alpha,
+                      const lapack_complex_float* x, lapack_int* incx,
+                      lapack_complex_float* a, lapack_int* lda );
+void LAPACK_zsyr( char* uplo, lapack_int* n, lapack_complex_double* alpha,
+                      const lapack_complex_double* x, lapack_int* incx,
+                      lapack_complex_double* a, lapack_int* lda );
+
+#ifdef __cplusplus
+}
+#endif /* __cplusplus */
+
+#endif /* _LAPACKE_H_ */
+
+#endif /* _MKL_LAPACKE_H_ */

ADDED   3rd_party/eigen/Eigen/src/misc/lapacke_mangling.h
Index: 3rd_party/eigen/Eigen/src/misc/lapacke_mangling.h
==================================================================
--- 3rd_party/eigen/Eigen/src/misc/lapacke_mangling.h
+++ 3rd_party/eigen/Eigen/src/misc/lapacke_mangling.h
@@ -0,0 +1,17 @@
+#ifndef LAPACK_HEADER_INCLUDED
+#define LAPACK_HEADER_INCLUDED
+
+#ifndef LAPACK_GLOBAL
+#if defined(LAPACK_GLOBAL_PATTERN_LC) || defined(ADD_)
+#define LAPACK_GLOBAL(lcname,UCNAME)  lcname##_
+#elif defined(LAPACK_GLOBAL_PATTERN_UC) || defined(UPPER)
+#define LAPACK_GLOBAL(lcname,UCNAME)  UCNAME
+#elif defined(LAPACK_GLOBAL_PATTERN_MC) || defined(NOCHANGE)
+#define LAPACK_GLOBAL(lcname,UCNAME)  lcname
+#else
+#define LAPACK_GLOBAL(lcname,UCNAME)  lcname##_
+#endif
+#endif
+
+#endif
+

Index: 3rd_party/eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h
==================================================================
--- 3rd_party/eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h
+++ 3rd_party/eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h
@@ -1,41 +1,45 @@
+
 /** \returns an expression of the coefficient wise product of \c *this and \a other
   *
   * \sa MatrixBase::cwiseProduct
   */
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_PRODUCT_RETURN_TYPE(Derived,OtherDerived)
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const EIGEN_CWISE_BINARY_RETURN_TYPE(Derived,OtherDerived,product)
 operator*(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
 {
-  return EIGEN_CWISE_PRODUCT_RETURN_TYPE(Derived,OtherDerived)(derived(), other.derived());
+  return EIGEN_CWISE_BINARY_RETURN_TYPE(Derived,OtherDerived,product)(derived(), other.derived());
 }
 
 /** \returns an expression of the coefficient wise quotient of \c *this and \a other
   *
   * \sa MatrixBase::cwiseQuotient
   */
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_quotient_op<Scalar,typename OtherDerived::Scalar>, const Derived, const OtherDerived>
 operator/(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
 {
-  return CwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
+  return CwiseBinaryOp<internal::scalar_quotient_op<Scalar,typename OtherDerived::Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
 }
 
 /** \returns an expression of the coefficient-wise min of \c *this and \a other
   *
   * Example: \include Cwise_min.cpp
   * Output: \verbinclude Cwise_min.out
   *
   * \sa max()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(min,internal::scalar_min_op)
+EIGEN_MAKE_CWISE_BINARY_OP(min,min)
 
 /** \returns an expression of the coefficient-wise min of \c *this and scalar \a other
   *
   * \sa max()
   */
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived,
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar,Scalar>, const Derived,
                                         const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> >
 #ifdef EIGEN_PARSED_BY_DOXYGEN
 min
 #else
 (min)
@@ -50,17 +54,18 @@
   * Example: \include Cwise_max.cpp
   * Output: \verbinclude Cwise_max.out
   *
   * \sa min()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(max,internal::scalar_max_op)
+EIGEN_MAKE_CWISE_BINARY_OP(max,max)
 
 /** \returns an expression of the coefficient-wise max of \c *this and scalar \a other
   *
   * \sa min()
   */
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived,
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar,Scalar>, const Derived,
                                         const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> >
 #ifdef EIGEN_PARSED_BY_DOXYGEN
 max
 #else
 (max)
@@ -67,46 +72,113 @@
 #endif
 (const Scalar &other) const
 {
   return (max)(Derived::PlainObject::Constant(rows(), cols(), other));
 }
+
+/** \returns an expression of the coefficient-wise power of \c *this to the given array of \a exponents.
+  *
+  * This function computes the coefficient-wise power.
+  *
+  * Example: \include Cwise_array_power_array.cpp
+  * Output: \verbinclude Cwise_array_power_array.out
+  */
+EIGEN_MAKE_CWISE_BINARY_OP(pow,pow)
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+EIGEN_MAKE_SCALAR_BINARY_OP_ONTHERIGHT(pow,pow)
+#else
+/** \returns an expression of the coefficients of \c *this rasied to the constant power \a exponent
+  *
+  * \tparam T is the scalar type of \a exponent. It must be compatible with the scalar type of the given expression.
+  *
+  * This function computes the coefficient-wise power. The function MatrixBase::pow() in the
+  * unsupported module MatrixFunctions computes the matrix power.
+  *
+  * Example: \include Cwise_pow.cpp
+  * Output: \verbinclude Cwise_pow.out
+  *
+  * \sa ArrayBase::pow(ArrayBase), square(), cube(), exp(), log()
+  */
+template<typename T>
+const CwiseBinaryOp<internal::scalar_pow_op<Scalar,T>,Derived,Constant<T> > pow(const T& exponent) const;
+#endif
+
+
+// TODO code generating macros could be moved to Macros.h and could include generation of documentation
+#define EIGEN_MAKE_CWISE_COMP_OP(OP, COMPARATOR) \
+template<typename OtherDerived> \
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_cmp_op<Scalar, typename OtherDerived::Scalar, internal::cmp_ ## COMPARATOR>, const Derived, const OtherDerived> \
+OP(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const \
+{ \
+  return CwiseBinaryOp<internal::scalar_cmp_op<Scalar, typename OtherDerived::Scalar, internal::cmp_ ## COMPARATOR>, const Derived, const OtherDerived>(derived(), other.derived()); \
+}\
+typedef CwiseBinaryOp<internal::scalar_cmp_op<Scalar,Scalar, internal::cmp_ ## COMPARATOR>, const Derived, const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> > Cmp ## COMPARATOR ## ReturnType; \
+typedef CwiseBinaryOp<internal::scalar_cmp_op<Scalar,Scalar, internal::cmp_ ## COMPARATOR>, const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject>, const Derived > RCmp ## COMPARATOR ## ReturnType; \
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Cmp ## COMPARATOR ## ReturnType \
+OP(const Scalar& s) const { \
+  return this->OP(Derived::PlainObject::Constant(rows(), cols(), s)); \
+} \
+EIGEN_DEVICE_FUNC friend EIGEN_STRONG_INLINE const RCmp ## COMPARATOR ## ReturnType \
+OP(const Scalar& s, const Derived& d) { \
+  return Derived::PlainObject::Constant(d.rows(), d.cols(), s).OP(d); \
+}
+
+#define EIGEN_MAKE_CWISE_COMP_R_OP(OP, R_OP, RCOMPARATOR) \
+template<typename OtherDerived> \
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_cmp_op<typename OtherDerived::Scalar, Scalar, internal::cmp_##RCOMPARATOR>, const OtherDerived, const Derived> \
+OP(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const \
+{ \
+  return CwiseBinaryOp<internal::scalar_cmp_op<typename OtherDerived::Scalar, Scalar, internal::cmp_##RCOMPARATOR>, const OtherDerived, const Derived>(other.derived(), derived()); \
+} \
+EIGEN_DEVICE_FUNC \
+inline const RCmp ## RCOMPARATOR ## ReturnType \
+OP(const Scalar& s) const { \
+  return Derived::PlainObject::Constant(rows(), cols(), s).R_OP(*this); \
+} \
+friend inline const Cmp ## RCOMPARATOR ## ReturnType \
+OP(const Scalar& s, const Derived& d) { \
+  return d.R_OP(Derived::PlainObject::Constant(d.rows(), d.cols(), s)); \
+}
+
+
 
 /** \returns an expression of the coefficient-wise \< operator of *this and \a other
   *
   * Example: \include Cwise_less.cpp
   * Output: \verbinclude Cwise_less.out
   *
   * \sa all(), any(), operator>(), operator<=()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(operator<,std::less)
+EIGEN_MAKE_CWISE_COMP_OP(operator<, LT)
 
 /** \returns an expression of the coefficient-wise \<= operator of *this and \a other
   *
   * Example: \include Cwise_less_equal.cpp
   * Output: \verbinclude Cwise_less_equal.out
   *
   * \sa all(), any(), operator>=(), operator<()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(operator<=,std::less_equal)
+EIGEN_MAKE_CWISE_COMP_OP(operator<=, LE)
 
 /** \returns an expression of the coefficient-wise \> operator of *this and \a other
   *
   * Example: \include Cwise_greater.cpp
   * Output: \verbinclude Cwise_greater.out
   *
   * \sa all(), any(), operator>=(), operator<()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(operator>,std::greater)
+EIGEN_MAKE_CWISE_COMP_R_OP(operator>, operator<, LT)
 
 /** \returns an expression of the coefficient-wise \>= operator of *this and \a other
   *
   * Example: \include Cwise_greater_equal.cpp
   * Output: \verbinclude Cwise_greater_equal.out
   *
   * \sa all(), any(), operator>(), operator<=()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(operator>=,std::greater_equal)
+EIGEN_MAKE_CWISE_COMP_R_OP(operator>=, operator<=, LE)
 
 /** \returns an expression of the coefficient-wise == operator of *this and \a other
   *
   * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
   * In order to check for equality between two vectors or matrices with floating-point coefficients, it is
@@ -116,11 +188,11 @@
   * Example: \include Cwise_equal_equal.cpp
   * Output: \verbinclude Cwise_equal_equal.out
   *
   * \sa all(), any(), isApprox(), isMuchSmallerThan()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(operator==,std::equal_to)
+EIGEN_MAKE_CWISE_COMP_OP(operator==, EQ)
 
 /** \returns an expression of the coefficient-wise != operator of *this and \a other
   *
   * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
   * In order to check for equality between two vectors or matrices with floating-point coefficients, it is
@@ -130,82 +202,131 @@
   * Example: \include Cwise_not_equal.cpp
   * Output: \verbinclude Cwise_not_equal.out
   *
   * \sa all(), any(), isApprox(), isMuchSmallerThan()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(operator!=,std::not_equal_to)
+EIGEN_MAKE_CWISE_COMP_OP(operator!=, NEQ)
+
+
+#undef EIGEN_MAKE_CWISE_COMP_OP
+#undef EIGEN_MAKE_CWISE_COMP_R_OP
 
 // scalar addition
-
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+EIGEN_MAKE_SCALAR_BINARY_OP(operator+,sum)
+#else
 /** \returns an expression of \c *this with each coeff incremented by the constant \a scalar
+  *
+  * \tparam T is the scalar type of \a scalar. It must be compatible with the scalar type of the given expression.
   *
   * Example: \include Cwise_plus.cpp
   * Output: \verbinclude Cwise_plus.out
   *
   * \sa operator+=(), operator-()
   */
-inline const CwiseUnaryOp<internal::scalar_add_op<Scalar>, const Derived>
-operator+(const Scalar& scalar) const
-{
-  return CwiseUnaryOp<internal::scalar_add_op<Scalar>, const Derived>(derived(), internal::scalar_add_op<Scalar>(scalar));
-}
-
-friend inline const CwiseUnaryOp<internal::scalar_add_op<Scalar>, const Derived>
-operator+(const Scalar& scalar,const EIGEN_CURRENT_STORAGE_BASE_CLASS<Derived>& other)
-{
-  return other + scalar;
-}
-
+template<typename T>
+const CwiseBinaryOp<internal::scalar_sum_op<Scalar,T>,Derived,Constant<T> > operator+(const T& scalar) const;
+/** \returns an expression of \a expr with each coeff incremented by the constant \a scalar
+  *
+  * \tparam T is the scalar type of \a scalar. It must be compatible with the scalar type of the given expression.
+  */
+template<typename T> friend
+const CwiseBinaryOp<internal::scalar_sum_op<T,Scalar>,Constant<T>,Derived> operator+(const T& scalar, const StorageBaseType& expr);
+#endif
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+EIGEN_MAKE_SCALAR_BINARY_OP(operator-,difference)
+#else
 /** \returns an expression of \c *this with each coeff decremented by the constant \a scalar
+  *
+  * \tparam T is the scalar type of \a scalar. It must be compatible with the scalar type of the given expression.
   *
   * Example: \include Cwise_minus.cpp
   * Output: \verbinclude Cwise_minus.out
   *
-  * \sa operator+(), operator-=()
-  */
-inline const CwiseUnaryOp<internal::scalar_add_op<Scalar>, const Derived>
-operator-(const Scalar& scalar) const
-{
-  return *this + (-scalar);
-}
-
-friend inline const CwiseUnaryOp<internal::scalar_add_op<Scalar>, const CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const Derived> >
-operator-(const Scalar& scalar,const EIGEN_CURRENT_STORAGE_BASE_CLASS<Derived>& other)
-{
-  return (-other) + scalar;
-}
-
-/** \returns an expression of the coefficient-wise && operator of *this and \a other
-  *
-  * \warning this operator is for expression of bool only.
-  *
-  * Example: \include Cwise_boolean_and.cpp
-  * Output: \verbinclude Cwise_boolean_and.out
-  *
-  * \sa operator||(), select()
-  */
-template<typename OtherDerived>
-inline const CwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived>
-operator&&(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
-{
-  EIGEN_STATIC_ASSERT((internal::is_same<bool,Scalar>::value && internal::is_same<bool,typename OtherDerived::Scalar>::value),
-                      THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
-  return CwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived>(derived(),other.derived());
-}
-
-/** \returns an expression of the coefficient-wise || operator of *this and \a other
-  *
-  * \warning this operator is for expression of bool only.
-  *
-  * Example: \include Cwise_boolean_or.cpp
-  * Output: \verbinclude Cwise_boolean_or.out
-  *
-  * \sa operator&&(), select()
-  */
-template<typename OtherDerived>
-inline const CwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>
-operator||(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
-{
-  EIGEN_STATIC_ASSERT((internal::is_same<bool,Scalar>::value && internal::is_same<bool,typename OtherDerived::Scalar>::value),
-                      THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
-  return CwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>(derived(),other.derived());
+  * \sa operator+=(), operator-()
+  */
+template<typename T>
+const CwiseBinaryOp<internal::scalar_difference_op<Scalar,T>,Derived,Constant<T> > operator-(const T& scalar) const;
+/** \returns an expression of the constant matrix of value \a scalar decremented by the coefficients of \a expr
+  *
+  * \tparam T is the scalar type of \a scalar. It must be compatible with the scalar type of the given expression.
+  */
+template<typename T> friend
+const CwiseBinaryOp<internal::scalar_difference_op<T,Scalar>,Constant<T>,Derived> operator-(const T& scalar, const StorageBaseType& expr);
+#endif
+
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+  EIGEN_MAKE_SCALAR_BINARY_OP_ONTHELEFT(operator/,quotient)
+#else
+  /**
+    * \brief Component-wise division of the scalar \a s by array elements of \a a.
+    *
+    * \tparam Scalar is the scalar type of \a x. It must be compatible with the scalar type of the given array expression (\c Derived::Scalar).
+    */
+  template<typename T> friend
+  inline const CwiseBinaryOp<internal::scalar_quotient_op<T,Scalar>,Constant<T>,Derived>
+  operator/(const T& s,const StorageBaseType& a);
+#endif
+
+/** \returns an expression of the coefficient-wise ^ operator of *this and \a other
+ *
+ * \warning this operator is for expression of bool only.
+ *
+ * Example: \include Cwise_boolean_xor.cpp
+ * Output: \verbinclude Cwise_boolean_xor.out
+ *
+ * \sa operator&&(), select()
+ */
+template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
+inline const CwiseBinaryOp<internal::scalar_boolean_xor_op, const Derived, const OtherDerived>
+operator^(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
+{
+  EIGEN_STATIC_ASSERT((internal::is_same<bool,Scalar>::value && internal::is_same<bool,typename OtherDerived::Scalar>::value),
+                      THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
+  return CwiseBinaryOp<internal::scalar_boolean_xor_op, const Derived, const OtherDerived>(derived(),other.derived());
+}
+
+// NOTE disabled until we agree on argument order
+#if 0
+/** \cpp11 \returns an expression of the coefficient-wise polygamma function.
+  *
+  * \specialfunctions_module
+  *
+  * It returns the \a n -th derivative of the digamma(psi) evaluated at \c *this.
+  *
+  * \warning Be careful with the order of the parameters: x.polygamma(n) is equivalent to polygamma(n,x)
+  *
+  * \sa Eigen::polygamma()
+  */
+template<typename DerivedN>
+inline const CwiseBinaryOp<internal::scalar_polygamma_op<Scalar>, const DerivedN, const Derived>
+polygamma(const EIGEN_CURRENT_STORAGE_BASE_CLASS<DerivedN> &n) const
+{
+  return CwiseBinaryOp<internal::scalar_polygamma_op<Scalar>, const DerivedN, const Derived>(n.derived(), this->derived());
+}
+#endif
+
+/** \returns an expression of the coefficient-wise zeta function.
+  *
+  * \specialfunctions_module
+  *
+  * It returns the Riemann zeta function of two arguments \c *this and \a q:
+  *
+  * \param *this is the exposent, it must be > 1
+  * \param q is the shift, it must be > 0
+  *
+  * \note This function supports only float and double scalar types. To support other scalar types, the user has
+  * to provide implementations of zeta(T,T) for any scalar type T to be supported.
+  *
+  * This method is an alias for zeta(*this,q);
+  *
+  * \sa Eigen::zeta()
+  */
+template<typename DerivedQ>
+inline const CwiseBinaryOp<internal::scalar_zeta_op<Scalar>, const Derived, const DerivedQ>
+zeta(const EIGEN_CURRENT_STORAGE_BASE_CLASS<DerivedQ> &q) const
+{
+  return CwiseBinaryOp<internal::scalar_zeta_op<Scalar>, const Derived, const DerivedQ>(this->derived(), q.derived());
 }

Index: 3rd_party/eigen/Eigen/src/plugins/ArrayCwiseUnaryOps.h
==================================================================
--- 3rd_party/eigen/Eigen/src/plugins/ArrayCwiseUnaryOps.h
+++ 3rd_party/eigen/Eigen/src/plugins/ArrayCwiseUnaryOps.h
@@ -1,203 +1,552 @@
 
 
+typedef CwiseUnaryOp<internal::scalar_abs_op<Scalar>, const Derived> AbsReturnType;
+typedef CwiseUnaryOp<internal::scalar_arg_op<Scalar>, const Derived> ArgReturnType;
+typedef CwiseUnaryOp<internal::scalar_abs2_op<Scalar>, const Derived> Abs2ReturnType;
+typedef CwiseUnaryOp<internal::scalar_sqrt_op<Scalar>, const Derived> SqrtReturnType;
+typedef CwiseUnaryOp<internal::scalar_rsqrt_op<Scalar>, const Derived> RsqrtReturnType;
+typedef CwiseUnaryOp<internal::scalar_sign_op<Scalar>, const Derived> SignReturnType;
+typedef CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived> InverseReturnType;
+typedef CwiseUnaryOp<internal::scalar_boolean_not_op<Scalar>, const Derived> BooleanNotReturnType;
+
+typedef CwiseUnaryOp<internal::scalar_exp_op<Scalar>, const Derived> ExpReturnType;
+typedef CwiseUnaryOp<internal::scalar_log_op<Scalar>, const Derived> LogReturnType;
+typedef CwiseUnaryOp<internal::scalar_log1p_op<Scalar>, const Derived> Log1pReturnType;
+typedef CwiseUnaryOp<internal::scalar_log10_op<Scalar>, const Derived> Log10ReturnType;
+typedef CwiseUnaryOp<internal::scalar_cos_op<Scalar>, const Derived> CosReturnType;
+typedef CwiseUnaryOp<internal::scalar_sin_op<Scalar>, const Derived> SinReturnType;
+typedef CwiseUnaryOp<internal::scalar_tan_op<Scalar>, const Derived> TanReturnType;
+typedef CwiseUnaryOp<internal::scalar_acos_op<Scalar>, const Derived> AcosReturnType;
+typedef CwiseUnaryOp<internal::scalar_asin_op<Scalar>, const Derived> AsinReturnType;
+typedef CwiseUnaryOp<internal::scalar_atan_op<Scalar>, const Derived> AtanReturnType;
+typedef CwiseUnaryOp<internal::scalar_tanh_op<Scalar>, const Derived> TanhReturnType;
+typedef CwiseUnaryOp<internal::scalar_sinh_op<Scalar>, const Derived> SinhReturnType;
+typedef CwiseUnaryOp<internal::scalar_cosh_op<Scalar>, const Derived> CoshReturnType;
+typedef CwiseUnaryOp<internal::scalar_square_op<Scalar>, const Derived> SquareReturnType;
+typedef CwiseUnaryOp<internal::scalar_cube_op<Scalar>, const Derived> CubeReturnType;
+typedef CwiseUnaryOp<internal::scalar_round_op<Scalar>, const Derived> RoundReturnType;
+typedef CwiseUnaryOp<internal::scalar_floor_op<Scalar>, const Derived> FloorReturnType;
+typedef CwiseUnaryOp<internal::scalar_ceil_op<Scalar>, const Derived> CeilReturnType;
+typedef CwiseUnaryOp<internal::scalar_isnan_op<Scalar>, const Derived> IsNaNReturnType;
+typedef CwiseUnaryOp<internal::scalar_isinf_op<Scalar>, const Derived> IsInfReturnType;
+typedef CwiseUnaryOp<internal::scalar_isfinite_op<Scalar>, const Derived> IsFiniteReturnType;
+
 /** \returns an expression of the coefficient-wise absolute value of \c *this
   *
   * Example: \include Cwise_abs.cpp
   * Output: \verbinclude Cwise_abs.out
   *
-  * \sa abs2()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_abs">Math functions</a>, abs2()
   */
-EIGEN_STRONG_INLINE const CwiseUnaryOp<internal::scalar_abs_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const AbsReturnType
 abs() const
 {
-  return derived();
+  return AbsReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise phase angle of \c *this
+  *
+  * Example: \include Cwise_arg.cpp
+  * Output: \verbinclude Cwise_arg.out
+  *
+  * \sa abs()
+  */
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const ArgReturnType
+arg() const
+{
+  return ArgReturnType(derived());
 }
 
 /** \returns an expression of the coefficient-wise squared absolute value of \c *this
   *
   * Example: \include Cwise_abs2.cpp
   * Output: \verbinclude Cwise_abs2.out
   *
-  * \sa abs(), square()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_abs2">Math functions</a>, abs(), square()
   */
-EIGEN_STRONG_INLINE const CwiseUnaryOp<internal::scalar_abs2_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const Abs2ReturnType
 abs2() const
 {
-  return derived();
+  return Abs2ReturnType(derived());
 }
 
 /** \returns an expression of the coefficient-wise exponential of *this.
   *
+  * This function computes the coefficient-wise exponential. The function MatrixBase::exp() in the
+  * unsupported module MatrixFunctions computes the matrix exponential.
+  *
   * Example: \include Cwise_exp.cpp
   * Output: \verbinclude Cwise_exp.out
   *
-  * \sa pow(), log(), sin(), cos()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_exp">Math functions</a>, pow(), log(), sin(), cos()
   */
-inline const CwiseUnaryOp<internal::scalar_exp_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+inline const ExpReturnType
 exp() const
 {
-  return derived();
+  return ExpReturnType(derived());
 }
 
 /** \returns an expression of the coefficient-wise logarithm of *this.
   *
+  * This function computes the coefficient-wise logarithm. The function MatrixBase::log() in the
+  * unsupported module MatrixFunctions computes the matrix logarithm.
+  *
   * Example: \include Cwise_log.cpp
   * Output: \verbinclude Cwise_log.out
   *
-  * \sa exp()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_log">Math functions</a>, exp()
   */
-inline const CwiseUnaryOp<internal::scalar_log_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+inline const LogReturnType
 log() const
 {
-  return derived();
+  return LogReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise logarithm of 1 plus \c *this.
+  *
+  * In exact arithmetic, \c x.log() is equivalent to \c (x+1).log(),
+  * however, with finite precision, this function is much more accurate when \c x is close to zero.
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_log1p">Math functions</a>, log()
+  */
+EIGEN_DEVICE_FUNC
+inline const Log1pReturnType
+log1p() const
+{
+  return Log1pReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise base-10 logarithm of *this.
+  *
+  * This function computes the coefficient-wise base-10 logarithm.
+  *
+  * Example: \include Cwise_log10.cpp
+  * Output: \verbinclude Cwise_log10.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_log10">Math functions</a>, log()
+  */
+EIGEN_DEVICE_FUNC
+inline const Log10ReturnType
+log10() const
+{
+  return Log10ReturnType(derived());
 }
 
 /** \returns an expression of the coefficient-wise square root of *this.
+  *
+  * This function computes the coefficient-wise square root. The function MatrixBase::sqrt() in the
+  * unsupported module MatrixFunctions computes the matrix square root.
+  *
+  * Example: \include Cwise_sqrt.cpp
+  * Output: \verbinclude Cwise_sqrt.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_sqrt">Math functions</a>, pow(), square()
+  */
+EIGEN_DEVICE_FUNC
+inline const SqrtReturnType
+sqrt() const
+{
+  return SqrtReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise inverse square root of *this.
+  *
+  * This function computes the coefficient-wise inverse square root.
   *
   * Example: \include Cwise_sqrt.cpp
   * Output: \verbinclude Cwise_sqrt.out
   *
   * \sa pow(), square()
   */
-inline const CwiseUnaryOp<internal::scalar_sqrt_op<Scalar>, const Derived>
-sqrt() const
+EIGEN_DEVICE_FUNC
+inline const RsqrtReturnType
+rsqrt() const
+{
+  return RsqrtReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise signum of *this.
+  *
+  * This function computes the coefficient-wise signum.
+  *
+  * Example: \include Cwise_sign.cpp
+  * Output: \verbinclude Cwise_sign.out
+  *
+  * \sa pow(), square()
+  */
+EIGEN_DEVICE_FUNC
+inline const SignReturnType
+sign() const
 {
-  return derived();
+  return SignReturnType(derived());
 }
+
 
 /** \returns an expression of the coefficient-wise cosine of *this.
+  *
+  * This function computes the coefficient-wise cosine. The function MatrixBase::cos() in the
+  * unsupported module MatrixFunctions computes the matrix cosine.
   *
   * Example: \include Cwise_cos.cpp
   * Output: \verbinclude Cwise_cos.out
   *
-  * \sa sin(), acos()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_cos">Math functions</a>, sin(), acos()
   */
-inline const CwiseUnaryOp<internal::scalar_cos_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+inline const CosReturnType
 cos() const
 {
-  return derived();
+  return CosReturnType(derived());
 }
 
 
 /** \returns an expression of the coefficient-wise sine of *this.
   *
+  * This function computes the coefficient-wise sine. The function MatrixBase::sin() in the
+  * unsupported module MatrixFunctions computes the matrix sine.
+  *
   * Example: \include Cwise_sin.cpp
   * Output: \verbinclude Cwise_sin.out
   *
-  * \sa cos(), asin()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_sin">Math functions</a>, cos(), asin()
   */
-inline const CwiseUnaryOp<internal::scalar_sin_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+inline const SinReturnType
 sin() const
 {
-  return derived();
-}
-
-/** \returns an expression of the coefficient-wise arc cosine of *this.
-  *
-  * Example: \include Cwise_acos.cpp
-  * Output: \verbinclude Cwise_acos.out
-  *
-  * \sa cos(), asin()
-  */
-inline const CwiseUnaryOp<internal::scalar_acos_op<Scalar>, const Derived>
-acos() const
-{
-  return derived();
-}
-
-/** \returns an expression of the coefficient-wise arc sine of *this.
-  *
-  * Example: \include Cwise_asin.cpp
-  * Output: \verbinclude Cwise_asin.out
-  *
-  * \sa sin(), acos()
-  */
-inline const CwiseUnaryOp<internal::scalar_asin_op<Scalar>, const Derived>
-asin() const
-{
-  return derived();
+  return SinReturnType(derived());
 }
 
 /** \returns an expression of the coefficient-wise tan of *this.
   *
   * Example: \include Cwise_tan.cpp
   * Output: \verbinclude Cwise_tan.out
   *
-  * \sa cos(), sin()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_tan">Math functions</a>, cos(), sin()
   */
-inline const CwiseUnaryOp<internal::scalar_tan_op<Scalar>, Derived>
+EIGEN_DEVICE_FUNC
+inline const TanReturnType
 tan() const
 {
-  return derived();
-}
-
-
-/** \returns an expression of the coefficient-wise power of *this to the given exponent.
-  *
-  * Example: \include Cwise_pow.cpp
-  * Output: \verbinclude Cwise_pow.out
-  *
-  * \sa exp(), log()
-  */
-inline const CwiseUnaryOp<internal::scalar_pow_op<Scalar>, const Derived>
-pow(const Scalar& exponent) const
-{
-  return CwiseUnaryOp<internal::scalar_pow_op<Scalar>, const Derived>
-          (derived(), internal::scalar_pow_op<Scalar>(exponent));
-}
-
+  return TanReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise arc tan of *this.
+  *
+  * Example: \include Cwise_atan.cpp
+  * Output: \verbinclude Cwise_atan.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_atan">Math functions</a>, tan(), asin(), acos()
+  */
+EIGEN_DEVICE_FUNC
+inline const AtanReturnType
+atan() const
+{
+  return AtanReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise arc cosine of *this.
+  *
+  * Example: \include Cwise_acos.cpp
+  * Output: \verbinclude Cwise_acos.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_acos">Math functions</a>, cos(), asin()
+  */
+EIGEN_DEVICE_FUNC
+inline const AcosReturnType
+acos() const
+{
+  return AcosReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise arc sine of *this.
+  *
+  * Example: \include Cwise_asin.cpp
+  * Output: \verbinclude Cwise_asin.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_asin">Math functions</a>, sin(), acos()
+  */
+EIGEN_DEVICE_FUNC
+inline const AsinReturnType
+asin() const
+{
+  return AsinReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise hyperbolic tan of *this.
+  *
+  * Example: \include Cwise_tanh.cpp
+  * Output: \verbinclude Cwise_tanh.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_tanh">Math functions</a>, tan(), sinh(), cosh()
+  */
+EIGEN_DEVICE_FUNC
+inline const TanhReturnType
+tanh() const
+{
+  return TanhReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise hyperbolic sin of *this.
+  *
+  * Example: \include Cwise_sinh.cpp
+  * Output: \verbinclude Cwise_sinh.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_sinh">Math functions</a>, sin(), tanh(), cosh()
+  */
+EIGEN_DEVICE_FUNC
+inline const SinhReturnType
+sinh() const
+{
+  return SinhReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise hyperbolic cos of *this.
+  *
+  * Example: \include Cwise_cosh.cpp
+  * Output: \verbinclude Cwise_cosh.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_cosh">Math functions</a>, tan(), sinh(), cosh()
+  */
+EIGEN_DEVICE_FUNC
+inline const CoshReturnType
+cosh() const
+{
+  return CoshReturnType(derived());
+}
 
 /** \returns an expression of the coefficient-wise inverse of *this.
   *
   * Example: \include Cwise_inverse.cpp
   * Output: \verbinclude Cwise_inverse.out
   *
   * \sa operator/(), operator*()
   */
-inline const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+inline const InverseReturnType
 inverse() const
 {
-  return derived();
+  return InverseReturnType(derived());
 }
 
 /** \returns an expression of the coefficient-wise square of *this.
   *
   * Example: \include Cwise_square.cpp
   * Output: \verbinclude Cwise_square.out
   *
-  * \sa operator/(), operator*(), abs2()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_squareE">Math functions</a>, abs2(), cube(), pow()
   */
-inline const CwiseUnaryOp<internal::scalar_square_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+inline const SquareReturnType
 square() const
 {
-  return derived();
+  return SquareReturnType(derived());
 }
 
 /** \returns an expression of the coefficient-wise cube of *this.
   *
   * Example: \include Cwise_cube.cpp
   * Output: \verbinclude Cwise_cube.out
   *
-  * \sa square(), pow()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_cube">Math functions</a>, square(), pow()
   */
-inline const CwiseUnaryOp<internal::scalar_cube_op<Scalar>, const Derived>
+EIGEN_DEVICE_FUNC
+inline const CubeReturnType
 cube() const
 {
-  return derived();
-}
-
-#define EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(METHOD_NAME,FUNCTOR) \
-  inline const CwiseUnaryOp<std::binder2nd<FUNCTOR<Scalar> >, const Derived> \
-  METHOD_NAME(const Scalar& s) const { \
-    return CwiseUnaryOp<std::binder2nd<FUNCTOR<Scalar> >, const Derived> \
-            (derived(), std::bind2nd(FUNCTOR<Scalar>(), s)); \
-  }
-
-EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator==,  std::equal_to)
-EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator!=,  std::not_equal_to)
-EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator<,   std::less)
-EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator<=,  std::less_equal)
-EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator>,   std::greater)
-EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator>=,  std::greater_equal)
-
-
+  return CubeReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise round of *this.
+  *
+  * Example: \include Cwise_round.cpp
+  * Output: \verbinclude Cwise_round.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_round">Math functions</a>, ceil(), floor()
+  */
+EIGEN_DEVICE_FUNC
+inline const RoundReturnType
+round() const
+{
+  return RoundReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise floor of *this.
+  *
+  * Example: \include Cwise_floor.cpp
+  * Output: \verbinclude Cwise_floor.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_floor">Math functions</a>, ceil(), round()
+  */
+EIGEN_DEVICE_FUNC
+inline const FloorReturnType
+floor() const
+{
+  return FloorReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise ceil of *this.
+  *
+  * Example: \include Cwise_ceil.cpp
+  * Output: \verbinclude Cwise_ceil.out
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_ceil">Math functions</a>, floor(), round()
+  */
+EIGEN_DEVICE_FUNC
+inline const CeilReturnType
+ceil() const
+{
+  return CeilReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise isnan of *this.
+  *
+  * Example: \include Cwise_isNaN.cpp
+  * Output: \verbinclude Cwise_isNaN.out
+  *
+  * \sa isfinite(), isinf()
+  */
+EIGEN_DEVICE_FUNC
+inline const IsNaNReturnType
+isNaN() const
+{
+  return IsNaNReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise isinf of *this.
+  *
+  * Example: \include Cwise_isInf.cpp
+  * Output: \verbinclude Cwise_isInf.out
+  *
+  * \sa isnan(), isfinite()
+  */
+EIGEN_DEVICE_FUNC
+inline const IsInfReturnType
+isInf() const
+{
+  return IsInfReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise isfinite of *this.
+  *
+  * Example: \include Cwise_isFinite.cpp
+  * Output: \verbinclude Cwise_isFinite.out
+  *
+  * \sa isnan(), isinf()
+  */
+EIGEN_DEVICE_FUNC
+inline const IsFiniteReturnType
+isFinite() const
+{
+  return IsFiniteReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise ! operator of *this
+  *
+  * \warning this operator is for expression of bool only.
+  *
+  * Example: \include Cwise_boolean_not.cpp
+  * Output: \verbinclude Cwise_boolean_not.out
+  *
+  * \sa operator!=()
+  */
+EIGEN_DEVICE_FUNC
+inline const BooleanNotReturnType
+operator!() const
+{
+  EIGEN_STATIC_ASSERT((internal::is_same<bool,Scalar>::value),
+                      THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
+  return BooleanNotReturnType(derived());
+}
+
+
+// --- SpecialFunctions module ---
+
+typedef CwiseUnaryOp<internal::scalar_lgamma_op<Scalar>, const Derived> LgammaReturnType;
+typedef CwiseUnaryOp<internal::scalar_digamma_op<Scalar>, const Derived> DigammaReturnType;
+typedef CwiseUnaryOp<internal::scalar_erf_op<Scalar>, const Derived> ErfReturnType;
+typedef CwiseUnaryOp<internal::scalar_erfc_op<Scalar>, const Derived> ErfcReturnType;
+
+/** \cpp11 \returns an expression of the coefficient-wise ln(|gamma(*this)|).
+  *
+  * \specialfunctions_module
+  *
+  * Example: \include Cwise_lgamma.cpp
+  * Output: \verbinclude Cwise_lgamma.out
+  *
+  * \note This function supports only float and double scalar types in c++11 mode. To support other scalar types,
+  * or float/double in non c++11 mode, the user has to provide implementations of lgamma(T) for any scalar
+  * type T to be supported.
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_lgamma">Math functions</a>, digamma()
+  */
+EIGEN_DEVICE_FUNC
+inline const LgammaReturnType
+lgamma() const
+{
+  return LgammaReturnType(derived());
+}
+
+/** \returns an expression of the coefficient-wise digamma (psi, derivative of lgamma).
+  *
+  * \specialfunctions_module
+  *
+  * \note This function supports only float and double scalar types. To support other scalar types,
+  * the user has to provide implementations of digamma(T) for any scalar
+  * type T to be supported.
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_digamma">Math functions</a>, Eigen::digamma(), Eigen::polygamma(), lgamma()
+  */
+EIGEN_DEVICE_FUNC
+inline const DigammaReturnType
+digamma() const
+{
+  return DigammaReturnType(derived());
+}
+
+/** \cpp11 \returns an expression of the coefficient-wise Gauss error
+  * function of *this.
+  *
+  * \specialfunctions_module
+  *
+  * Example: \include Cwise_erf.cpp
+  * Output: \verbinclude Cwise_erf.out
+  *
+  * \note This function supports only float and double scalar types in c++11 mode. To support other scalar types,
+  * or float/double in non c++11 mode, the user has to provide implementations of erf(T) for any scalar
+  * type T to be supported.
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_erf">Math functions</a>, erfc()
+  */
+EIGEN_DEVICE_FUNC
+inline const ErfReturnType
+erf() const
+{
+  return ErfReturnType(derived());
+}
+
+/** \cpp11 \returns an expression of the coefficient-wise Complementary error
+  * function of *this.
+  *
+  * \specialfunctions_module
+  *
+  * Example: \include Cwise_erfc.cpp
+  * Output: \verbinclude Cwise_erfc.out
+  *
+  * \note This function supports only float and double scalar types in c++11 mode. To support other scalar types,
+  * or float/double in non c++11 mode, the user has to provide implementations of erfc(T) for any scalar
+  * type T to be supported.
+  *
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_erfc">Math functions</a>, erf()
+  */
+EIGEN_DEVICE_FUNC
+inline const ErfcReturnType
+erfc() const
+{
+  return ErfcReturnType(derived());
+}

Index: 3rd_party/eigen/Eigen/src/plugins/BlockMethods.h
==================================================================
--- 3rd_party/eigen/Eigen/src/plugins/BlockMethods.h
+++ 3rd_party/eigen/Eigen/src/plugins/BlockMethods.h
@@ -6,930 +6,1053 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
-
 #ifndef EIGEN_PARSED_BY_DOXYGEN
 
-/** \internal expression type of a column */
+/// \internal expression type of a column */
 typedef Block<Derived, internal::traits<Derived>::RowsAtCompileTime, 1, !IsRowMajor> ColXpr;
 typedef const Block<const Derived, internal::traits<Derived>::RowsAtCompileTime, 1, !IsRowMajor> ConstColXpr;
-/** \internal expression type of a row */
+/// \internal expression type of a row */
 typedef Block<Derived, 1, internal::traits<Derived>::ColsAtCompileTime, IsRowMajor> RowXpr;
 typedef const Block<const Derived, 1, internal::traits<Derived>::ColsAtCompileTime, IsRowMajor> ConstRowXpr;
-/** \internal expression type of a block of whole columns */
+/// \internal expression type of a block of whole columns */
 typedef Block<Derived, internal::traits<Derived>::RowsAtCompileTime, Dynamic, !IsRowMajor> ColsBlockXpr;
 typedef const Block<const Derived, internal::traits<Derived>::RowsAtCompileTime, Dynamic, !IsRowMajor> ConstColsBlockXpr;
-/** \internal expression type of a block of whole rows */
+/// \internal expression type of a block of whole rows */
 typedef Block<Derived, Dynamic, internal::traits<Derived>::ColsAtCompileTime, IsRowMajor> RowsBlockXpr;
 typedef const Block<const Derived, Dynamic, internal::traits<Derived>::ColsAtCompileTime, IsRowMajor> ConstRowsBlockXpr;
-/** \internal expression type of a block of whole columns */
+/// \internal expression type of a block of whole columns */
 template<int N> struct NColsBlockXpr { typedef Block<Derived, internal::traits<Derived>::RowsAtCompileTime, N, !IsRowMajor> Type; };
 template<int N> struct ConstNColsBlockXpr { typedef const Block<const Derived, internal::traits<Derived>::RowsAtCompileTime, N, !IsRowMajor> Type; };
-/** \internal expression type of a block of whole rows */
+/// \internal expression type of a block of whole rows */
 template<int N> struct NRowsBlockXpr { typedef Block<Derived, N, internal::traits<Derived>::ColsAtCompileTime, IsRowMajor> Type; };
 template<int N> struct ConstNRowsBlockXpr { typedef const Block<const Derived, N, internal::traits<Derived>::ColsAtCompileTime, IsRowMajor> Type; };
+/// \internal expression of a block */
+typedef Block<Derived> BlockXpr;
+typedef const Block<const Derived> ConstBlockXpr;
+/// \internal expression of a block of fixed sizes */
+template<int Rows, int Cols> struct FixedBlockXpr { typedef Block<Derived,Rows,Cols> Type; };
+template<int Rows, int Cols> struct ConstFixedBlockXpr { typedef Block<const Derived,Rows,Cols> Type; };
 
 typedef VectorBlock<Derived> SegmentReturnType;
 typedef const VectorBlock<const Derived> ConstSegmentReturnType;
 template<int Size> struct FixedSegmentReturnType { typedef VectorBlock<Derived, Size> Type; };
 template<int Size> struct ConstFixedSegmentReturnType { typedef const VectorBlock<const Derived, Size> Type; };
 
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
-/** \returns a dynamic-size expression of a block in *this.
-  *
-  * \param startRow the first row in the block
-  * \param startCol the first column in the block
-  * \param blockRows the number of rows in the block
-  * \param blockCols the number of columns in the block
-  *
-  * Example: \include MatrixBase_block_int_int_int_int.cpp
-  * Output: \verbinclude MatrixBase_block_int_int_int_int.out
-  *
-  * \note Even though the returned expression has dynamic size, in the case
-  * when it is applied to a fixed-size matrix, it inherits a fixed maximal size,
-  * which means that evaluating it does not cause a dynamic memory allocation.
-  *
-  * \sa class Block, block(Index,Index)
-  */
-inline Block<Derived> block(Index startRow, Index startCol, Index blockRows, Index blockCols)
-{
-  return Block<Derived>(derived(), startRow, startCol, blockRows, blockCols);
-}
-
-/** This is the const version of block(Index,Index,Index,Index). */
-inline const Block<const Derived> block(Index startRow, Index startCol, Index blockRows, Index blockCols) const
-{
-  return Block<const Derived>(derived(), startRow, startCol, blockRows, blockCols);
-}
-
-
-
-
-/** \returns a dynamic-size expression of a top-right corner of *this.
-  *
-  * \param cRows the number of rows in the corner
-  * \param cCols the number of columns in the corner
-  *
-  * Example: \include MatrixBase_topRightCorner_int_int.cpp
-  * Output: \verbinclude MatrixBase_topRightCorner_int_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-inline Block<Derived> topRightCorner(Index cRows, Index cCols)
-{
-  return Block<Derived>(derived(), 0, cols() - cCols, cRows, cCols);
-}
-
-/** This is the const version of topRightCorner(Index, Index).*/
-inline const Block<const Derived> topRightCorner(Index cRows, Index cCols) const
-{
-  return Block<const Derived>(derived(), 0, cols() - cCols, cRows, cCols);
-}
-
-/** \returns an expression of a fixed-size top-right corner of *this.
-  *
-  * \tparam CRows the number of rows in the corner
-  * \tparam CCols the number of columns in the corner
-  *
-  * Example: \include MatrixBase_template_int_int_topRightCorner.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_topRightCorner.out
-  *
-  * \sa class Block, block<int,int>(Index,Index)
-  */
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols> topRightCorner()
-{
-  return Block<Derived, CRows, CCols>(derived(), 0, cols() - CCols);
-}
-
-/** This is the const version of topRightCorner<int, int>().*/
-template<int CRows, int CCols>
-inline const Block<const Derived, CRows, CCols> topRightCorner() const
-{
-  return Block<const Derived, CRows, CCols>(derived(), 0, cols() - CCols);
-}
-
-/** \returns an expression of a top-right corner of *this.
-  *
-  * \tparam CRows number of rows in corner as specified at compile-time
-  * \tparam CCols number of columns in corner as specified at compile-time
-  * \param  cRows number of rows in corner as specified at run-time
-  * \param  cCols number of columns in corner as specified at run-time
-  *
-  * This function is mainly useful for corners where the number of rows is specified at compile-time
-  * and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
-  * information should not contradict. In other words, \a cRows should equal \a CRows unless
-  * \a CRows is \a Dynamic, and the same for the number of columns.
-  *
-  * Example: \include MatrixBase_template_int_int_topRightCorner_int_int.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_topRightCorner_int_int.out
-  *
-  * \sa class Block
-  */
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols> topRightCorner(Index cRows, Index cCols)
-{
-  return Block<Derived, CRows, CCols>(derived(), 0, cols() - cCols, cRows, cCols);
-}
-
-/** This is the const version of topRightCorner<int, int>(Index, Index).*/
-template<int CRows, int CCols>
-inline const Block<const Derived, CRows, CCols> topRightCorner(Index cRows, Index cCols) const
-{
-  return Block<const Derived, CRows, CCols>(derived(), 0, cols() - cCols, cRows, cCols);
-}
-
-
-
-/** \returns a dynamic-size expression of a top-left corner of *this.
-  *
-  * \param cRows the number of rows in the corner
-  * \param cCols the number of columns in the corner
-  *
-  * Example: \include MatrixBase_topLeftCorner_int_int.cpp
-  * Output: \verbinclude MatrixBase_topLeftCorner_int_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-inline Block<Derived> topLeftCorner(Index cRows, Index cCols)
-{
-  return Block<Derived>(derived(), 0, 0, cRows, cCols);
-}
-
-/** This is the const version of topLeftCorner(Index, Index).*/
-inline const Block<const Derived> topLeftCorner(Index cRows, Index cCols) const
-{
-  return Block<const Derived>(derived(), 0, 0, cRows, cCols);
-}
-
-/** \returns an expression of a fixed-size top-left corner of *this.
-  *
-  * The template parameters CRows and CCols are the number of rows and columns in the corner.
-  *
-  * Example: \include MatrixBase_template_int_int_topLeftCorner.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_topLeftCorner.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols> topLeftCorner()
-{
-  return Block<Derived, CRows, CCols>(derived(), 0, 0);
-}
-
-/** This is the const version of topLeftCorner<int, int>().*/
-template<int CRows, int CCols>
-inline const Block<const Derived, CRows, CCols> topLeftCorner() const
-{
-  return Block<const Derived, CRows, CCols>(derived(), 0, 0);
-}
-
-/** \returns an expression of a top-left corner of *this.
-  *
-  * \tparam CRows number of rows in corner as specified at compile-time
-  * \tparam CCols number of columns in corner as specified at compile-time
-  * \param  cRows number of rows in corner as specified at run-time
-  * \param  cCols number of columns in corner as specified at run-time
-  *
-  * This function is mainly useful for corners where the number of rows is specified at compile-time
-  * and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
-  * information should not contradict. In other words, \a cRows should equal \a CRows unless
-  * \a CRows is \a Dynamic, and the same for the number of columns.
-  *
-  * Example: \include MatrixBase_template_int_int_topLeftCorner_int_int.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_topLeftCorner_int_int.out
-  *
-  * \sa class Block
-  */
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols> topLeftCorner(Index cRows, Index cCols)
-{
-  return Block<Derived, CRows, CCols>(derived(), 0, 0, cRows, cCols);
-}
-
-/** This is the const version of topLeftCorner<int, int>(Index, Index).*/
-template<int CRows, int CCols>
-inline const Block<const Derived, CRows, CCols> topLeftCorner(Index cRows, Index cCols) const
-{
-  return Block<const Derived, CRows, CCols>(derived(), 0, 0, cRows, cCols);
-}
-
-
-
-/** \returns a dynamic-size expression of a bottom-right corner of *this.
-  *
-  * \param cRows the number of rows in the corner
-  * \param cCols the number of columns in the corner
-  *
-  * Example: \include MatrixBase_bottomRightCorner_int_int.cpp
-  * Output: \verbinclude MatrixBase_bottomRightCorner_int_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-inline Block<Derived> bottomRightCorner(Index cRows, Index cCols)
-{
-  return Block<Derived>(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
-}
-
-/** This is the const version of bottomRightCorner(Index, Index).*/
-inline const Block<const Derived> bottomRightCorner(Index cRows, Index cCols) const
-{
-  return Block<const Derived>(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
-}
-
-/** \returns an expression of a fixed-size bottom-right corner of *this.
-  *
-  * The template parameters CRows and CCols are the number of rows and columns in the corner.
-  *
-  * Example: \include MatrixBase_template_int_int_bottomRightCorner.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_bottomRightCorner.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols> bottomRightCorner()
-{
-  return Block<Derived, CRows, CCols>(derived(), rows() - CRows, cols() - CCols);
-}
-
-/** This is the const version of bottomRightCorner<int, int>().*/
-template<int CRows, int CCols>
-inline const Block<const Derived, CRows, CCols> bottomRightCorner() const
-{
-  return Block<const Derived, CRows, CCols>(derived(), rows() - CRows, cols() - CCols);
-}
-
-/** \returns an expression of a bottom-right corner of *this.
-  *
-  * \tparam CRows number of rows in corner as specified at compile-time
-  * \tparam CCols number of columns in corner as specified at compile-time
-  * \param  cRows number of rows in corner as specified at run-time
-  * \param  cCols number of columns in corner as specified at run-time
-  *
-  * This function is mainly useful for corners where the number of rows is specified at compile-time
-  * and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
-  * information should not contradict. In other words, \a cRows should equal \a CRows unless
-  * \a CRows is \a Dynamic, and the same for the number of columns.
-  *
-  * Example: \include MatrixBase_template_int_int_bottomRightCorner_int_int.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_bottomRightCorner_int_int.out
-  *
-  * \sa class Block
-  */
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols> bottomRightCorner(Index cRows, Index cCols)
-{
-  return Block<Derived, CRows, CCols>(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
-}
-
-/** This is the const version of bottomRightCorner<int, int>(Index, Index).*/
-template<int CRows, int CCols>
-inline const Block<const Derived, CRows, CCols> bottomRightCorner(Index cRows, Index cCols) const
-{
-  return Block<const Derived, CRows, CCols>(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
-}
-
-
-
-/** \returns a dynamic-size expression of a bottom-left corner of *this.
-  *
-  * \param cRows the number of rows in the corner
-  * \param cCols the number of columns in the corner
-  *
-  * Example: \include MatrixBase_bottomLeftCorner_int_int.cpp
-  * Output: \verbinclude MatrixBase_bottomLeftCorner_int_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-inline Block<Derived> bottomLeftCorner(Index cRows, Index cCols)
-{
-  return Block<Derived>(derived(), rows() - cRows, 0, cRows, cCols);
-}
-
-/** This is the const version of bottomLeftCorner(Index, Index).*/
-inline const Block<const Derived> bottomLeftCorner(Index cRows, Index cCols) const
-{
-  return Block<const Derived>(derived(), rows() - cRows, 0, cRows, cCols);
-}
-
-/** \returns an expression of a fixed-size bottom-left corner of *this.
-  *
-  * The template parameters CRows and CCols are the number of rows and columns in the corner.
-  *
-  * Example: \include MatrixBase_template_int_int_bottomLeftCorner.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_bottomLeftCorner.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols> bottomLeftCorner()
-{
-  return Block<Derived, CRows, CCols>(derived(), rows() - CRows, 0);
-}
-
-/** This is the const version of bottomLeftCorner<int, int>().*/
-template<int CRows, int CCols>
-inline const Block<const Derived, CRows, CCols> bottomLeftCorner() const
-{
-  return Block<const Derived, CRows, CCols>(derived(), rows() - CRows, 0);
-}
-
-/** \returns an expression of a bottom-left corner of *this.
-  *
-  * \tparam CRows number of rows in corner as specified at compile-time
-  * \tparam CCols number of columns in corner as specified at compile-time
-  * \param  cRows number of rows in corner as specified at run-time
-  * \param  cCols number of columns in corner as specified at run-time
-  *
-  * This function is mainly useful for corners where the number of rows is specified at compile-time
-  * and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
-  * information should not contradict. In other words, \a cRows should equal \a CRows unless
-  * \a CRows is \a Dynamic, and the same for the number of columns.
-  *
-  * Example: \include MatrixBase_template_int_int_bottomLeftCorner_int_int.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_bottomLeftCorner_int_int.out
-  *
-  * \sa class Block
-  */
-template<int CRows, int CCols>
-inline Block<Derived, CRows, CCols> bottomLeftCorner(Index cRows, Index cCols)
-{
-  return Block<Derived, CRows, CCols>(derived(), rows() - cRows, 0, cRows, cCols);
-}
-
-/** This is the const version of bottomLeftCorner<int, int>(Index, Index).*/
-template<int CRows, int CCols>
-inline const Block<const Derived, CRows, CCols> bottomLeftCorner(Index cRows, Index cCols) const
-{
-  return Block<const Derived, CRows, CCols>(derived(), rows() - cRows, 0, cRows, cCols);
-}
-
-
-
-/** \returns a block consisting of the top rows of *this.
-  *
-  * \param n the number of rows in the block
-  *
-  * Example: \include MatrixBase_topRows_int.cpp
-  * Output: \verbinclude MatrixBase_topRows_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a dynamic-size expression of a block in *this.
+///
+/// \param startRow the first row in the block
+/// \param startCol the first column in the block
+/// \param blockRows the number of rows in the block
+/// \param blockCols the number of columns in the block
+///
+/// Example: \include MatrixBase_block_int_int_int_int.cpp
+/// Output: \verbinclude MatrixBase_block_int_int_int_int.out
+///
+/// \note Even though the returned expression has dynamic size, in the case
+/// when it is applied to a fixed-size matrix, it inherits a fixed maximal size,
+/// which means that evaluating it does not cause a dynamic memory allocation.
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index)
+///
+EIGEN_DEVICE_FUNC
+inline BlockXpr block(Index startRow, Index startCol, Index blockRows, Index blockCols)
+{
+  return BlockXpr(derived(), startRow, startCol, blockRows, blockCols);
+}
+
+/// This is the const version of block(Index,Index,Index,Index). */
+EIGEN_DEVICE_FUNC
+inline const ConstBlockXpr block(Index startRow, Index startCol, Index blockRows, Index blockCols) const
+{
+  return ConstBlockXpr(derived(), startRow, startCol, blockRows, blockCols);
+}
+
+
+
+
+/// \returns a dynamic-size expression of a top-right corner of *this.
+///
+/// \param cRows the number of rows in the corner
+/// \param cCols the number of columns in the corner
+///
+/// Example: \include MatrixBase_topRightCorner_int_int.cpp
+/// Output: \verbinclude MatrixBase_topRightCorner_int_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
+inline BlockXpr topRightCorner(Index cRows, Index cCols)
+{
+  return BlockXpr(derived(), 0, cols() - cCols, cRows, cCols);
+}
+
+/// This is the const version of topRightCorner(Index, Index).
+EIGEN_DEVICE_FUNC
+inline const ConstBlockXpr topRightCorner(Index cRows, Index cCols) const
+{
+  return ConstBlockXpr(derived(), 0, cols() - cCols, cRows, cCols);
+}
+
+/// \returns an expression of a fixed-size top-right corner of *this.
+///
+/// \tparam CRows the number of rows in the corner
+/// \tparam CCols the number of columns in the corner
+///
+/// Example: \include MatrixBase_template_int_int_topRightCorner.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_topRightCorner.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block<int,int>(Index,Index)
+///
+template<int CRows, int CCols>
+EIGEN_DEVICE_FUNC
+inline typename FixedBlockXpr<CRows,CCols>::Type topRightCorner()
+{
+  return typename FixedBlockXpr<CRows,CCols>::Type(derived(), 0, cols() - CCols);
+}
+
+/// This is the const version of topRightCorner<int, int>().
+template<int CRows, int CCols>
+EIGEN_DEVICE_FUNC
+inline const typename ConstFixedBlockXpr<CRows,CCols>::Type topRightCorner() const
+{
+  return typename ConstFixedBlockXpr<CRows,CCols>::Type(derived(), 0, cols() - CCols);
+}
+
+/// \returns an expression of a top-right corner of *this.
+///
+/// \tparam CRows number of rows in corner as specified at compile-time
+/// \tparam CCols number of columns in corner as specified at compile-time
+/// \param  cRows number of rows in corner as specified at run-time
+/// \param  cCols number of columns in corner as specified at run-time
+///
+/// This function is mainly useful for corners where the number of rows is specified at compile-time
+/// and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
+/// information should not contradict. In other words, \a cRows should equal \a CRows unless
+/// \a CRows is \a Dynamic, and the same for the number of columns.
+///
+/// Example: \include MatrixBase_template_int_int_topRightCorner_int_int.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_topRightCorner_int_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block
+///
+template<int CRows, int CCols>
+inline typename FixedBlockXpr<CRows,CCols>::Type topRightCorner(Index cRows, Index cCols)
+{
+  return typename FixedBlockXpr<CRows,CCols>::Type(derived(), 0, cols() - cCols, cRows, cCols);
+}
+
+/// This is the const version of topRightCorner<int, int>(Index, Index).
+template<int CRows, int CCols>
+inline const typename ConstFixedBlockXpr<CRows,CCols>::Type topRightCorner(Index cRows, Index cCols) const
+{
+  return typename ConstFixedBlockXpr<CRows,CCols>::Type(derived(), 0, cols() - cCols, cRows, cCols);
+}
+
+
+
+/// \returns a dynamic-size expression of a top-left corner of *this.
+///
+/// \param cRows the number of rows in the corner
+/// \param cCols the number of columns in the corner
+///
+/// Example: \include MatrixBase_topLeftCorner_int_int.cpp
+/// Output: \verbinclude MatrixBase_topLeftCorner_int_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
+inline BlockXpr topLeftCorner(Index cRows, Index cCols)
+{
+  return BlockXpr(derived(), 0, 0, cRows, cCols);
+}
+
+/// This is the const version of topLeftCorner(Index, Index).
+EIGEN_DEVICE_FUNC
+inline const ConstBlockXpr topLeftCorner(Index cRows, Index cCols) const
+{
+  return ConstBlockXpr(derived(), 0, 0, cRows, cCols);
+}
+
+/// \returns an expression of a fixed-size top-left corner of *this.
+///
+/// The template parameters CRows and CCols are the number of rows and columns in the corner.
+///
+/// Example: \include MatrixBase_template_int_int_topLeftCorner.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_topLeftCorner.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+template<int CRows, int CCols>
+EIGEN_DEVICE_FUNC
+inline typename FixedBlockXpr<CRows,CCols>::Type topLeftCorner()
+{
+  return typename FixedBlockXpr<CRows,CCols>::Type(derived(), 0, 0);
+}
+
+/// This is the const version of topLeftCorner<int, int>().
+template<int CRows, int CCols>
+EIGEN_DEVICE_FUNC
+inline const typename ConstFixedBlockXpr<CRows,CCols>::Type topLeftCorner() const
+{
+  return typename ConstFixedBlockXpr<CRows,CCols>::Type(derived(), 0, 0);
+}
+
+/// \returns an expression of a top-left corner of *this.
+///
+/// \tparam CRows number of rows in corner as specified at compile-time
+/// \tparam CCols number of columns in corner as specified at compile-time
+/// \param  cRows number of rows in corner as specified at run-time
+/// \param  cCols number of columns in corner as specified at run-time
+///
+/// This function is mainly useful for corners where the number of rows is specified at compile-time
+/// and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
+/// information should not contradict. In other words, \a cRows should equal \a CRows unless
+/// \a CRows is \a Dynamic, and the same for the number of columns.
+///
+/// Example: \include MatrixBase_template_int_int_topLeftCorner_int_int.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_topLeftCorner_int_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block
+///
+template<int CRows, int CCols>
+inline typename FixedBlockXpr<CRows,CCols>::Type topLeftCorner(Index cRows, Index cCols)
+{
+  return typename FixedBlockXpr<CRows,CCols>::Type(derived(), 0, 0, cRows, cCols);
+}
+
+/// This is the const version of topLeftCorner<int, int>(Index, Index).
+template<int CRows, int CCols>
+inline const typename ConstFixedBlockXpr<CRows,CCols>::Type topLeftCorner(Index cRows, Index cCols) const
+{
+  return typename ConstFixedBlockXpr<CRows,CCols>::Type(derived(), 0, 0, cRows, cCols);
+}
+
+
+
+/// \returns a dynamic-size expression of a bottom-right corner of *this.
+///
+/// \param cRows the number of rows in the corner
+/// \param cCols the number of columns in the corner
+///
+/// Example: \include MatrixBase_bottomRightCorner_int_int.cpp
+/// Output: \verbinclude MatrixBase_bottomRightCorner_int_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
+inline BlockXpr bottomRightCorner(Index cRows, Index cCols)
+{
+  return BlockXpr(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
+}
+
+/// This is the const version of bottomRightCorner(Index, Index).
+EIGEN_DEVICE_FUNC
+inline const ConstBlockXpr bottomRightCorner(Index cRows, Index cCols) const
+{
+  return ConstBlockXpr(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
+}
+
+/// \returns an expression of a fixed-size bottom-right corner of *this.
+///
+/// The template parameters CRows and CCols are the number of rows and columns in the corner.
+///
+/// Example: \include MatrixBase_template_int_int_bottomRightCorner.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_bottomRightCorner.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+template<int CRows, int CCols>
+EIGEN_DEVICE_FUNC
+inline typename FixedBlockXpr<CRows,CCols>::Type bottomRightCorner()
+{
+  return typename FixedBlockXpr<CRows,CCols>::Type(derived(), rows() - CRows, cols() - CCols);
+}
+
+/// This is the const version of bottomRightCorner<int, int>().
+template<int CRows, int CCols>
+EIGEN_DEVICE_FUNC
+inline const typename ConstFixedBlockXpr<CRows,CCols>::Type bottomRightCorner() const
+{
+  return typename ConstFixedBlockXpr<CRows,CCols>::Type(derived(), rows() - CRows, cols() - CCols);
+}
+
+/// \returns an expression of a bottom-right corner of *this.
+///
+/// \tparam CRows number of rows in corner as specified at compile-time
+/// \tparam CCols number of columns in corner as specified at compile-time
+/// \param  cRows number of rows in corner as specified at run-time
+/// \param  cCols number of columns in corner as specified at run-time
+///
+/// This function is mainly useful for corners where the number of rows is specified at compile-time
+/// and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
+/// information should not contradict. In other words, \a cRows should equal \a CRows unless
+/// \a CRows is \a Dynamic, and the same for the number of columns.
+///
+/// Example: \include MatrixBase_template_int_int_bottomRightCorner_int_int.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_bottomRightCorner_int_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block
+///
+template<int CRows, int CCols>
+inline typename FixedBlockXpr<CRows,CCols>::Type bottomRightCorner(Index cRows, Index cCols)
+{
+  return typename FixedBlockXpr<CRows,CCols>::Type(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
+}
+
+/// This is the const version of bottomRightCorner<int, int>(Index, Index).
+template<int CRows, int CCols>
+inline const typename ConstFixedBlockXpr<CRows,CCols>::Type bottomRightCorner(Index cRows, Index cCols) const
+{
+  return typename ConstFixedBlockXpr<CRows,CCols>::Type(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
+}
+
+
+
+/// \returns a dynamic-size expression of a bottom-left corner of *this.
+///
+/// \param cRows the number of rows in the corner
+/// \param cCols the number of columns in the corner
+///
+/// Example: \include MatrixBase_bottomLeftCorner_int_int.cpp
+/// Output: \verbinclude MatrixBase_bottomLeftCorner_int_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
+inline BlockXpr bottomLeftCorner(Index cRows, Index cCols)
+{
+  return BlockXpr(derived(), rows() - cRows, 0, cRows, cCols);
+}
+
+/// This is the const version of bottomLeftCorner(Index, Index).
+EIGEN_DEVICE_FUNC
+inline const ConstBlockXpr bottomLeftCorner(Index cRows, Index cCols) const
+{
+  return ConstBlockXpr(derived(), rows() - cRows, 0, cRows, cCols);
+}
+
+/// \returns an expression of a fixed-size bottom-left corner of *this.
+///
+/// The template parameters CRows and CCols are the number of rows and columns in the corner.
+///
+/// Example: \include MatrixBase_template_int_int_bottomLeftCorner.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_bottomLeftCorner.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+template<int CRows, int CCols>
+EIGEN_DEVICE_FUNC
+inline typename FixedBlockXpr<CRows,CCols>::Type bottomLeftCorner()
+{
+  return typename FixedBlockXpr<CRows,CCols>::Type(derived(), rows() - CRows, 0);
+}
+
+/// This is the const version of bottomLeftCorner<int, int>().
+template<int CRows, int CCols>
+EIGEN_DEVICE_FUNC
+inline const typename ConstFixedBlockXpr<CRows,CCols>::Type bottomLeftCorner() const
+{
+  return typename ConstFixedBlockXpr<CRows,CCols>::Type(derived(), rows() - CRows, 0);
+}
+
+/// \returns an expression of a bottom-left corner of *this.
+///
+/// \tparam CRows number of rows in corner as specified at compile-time
+/// \tparam CCols number of columns in corner as specified at compile-time
+/// \param  cRows number of rows in corner as specified at run-time
+/// \param  cCols number of columns in corner as specified at run-time
+///
+/// This function is mainly useful for corners where the number of rows is specified at compile-time
+/// and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
+/// information should not contradict. In other words, \a cRows should equal \a CRows unless
+/// \a CRows is \a Dynamic, and the same for the number of columns.
+///
+/// Example: \include MatrixBase_template_int_int_bottomLeftCorner_int_int.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_bottomLeftCorner_int_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block
+///
+template<int CRows, int CCols>
+inline typename FixedBlockXpr<CRows,CCols>::Type bottomLeftCorner(Index cRows, Index cCols)
+{
+  return typename FixedBlockXpr<CRows,CCols>::Type(derived(), rows() - cRows, 0, cRows, cCols);
+}
+
+/// This is the const version of bottomLeftCorner<int, int>(Index, Index).
+template<int CRows, int CCols>
+inline const typename ConstFixedBlockXpr<CRows,CCols>::Type bottomLeftCorner(Index cRows, Index cCols) const
+{
+  return typename ConstFixedBlockXpr<CRows,CCols>::Type(derived(), rows() - cRows, 0, cRows, cCols);
+}
+
+
+
+/// \returns a block consisting of the top rows of *this.
+///
+/// \param n the number of rows in the block
+///
+/// Example: \include MatrixBase_topRows_int.cpp
+/// Output: \verbinclude MatrixBase_topRows_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(row-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
 inline RowsBlockXpr topRows(Index n)
 {
   return RowsBlockXpr(derived(), 0, 0, n, cols());
 }
 
-/** This is the const version of topRows(Index).*/
+/// This is the const version of topRows(Index).
+EIGEN_DEVICE_FUNC
 inline ConstRowsBlockXpr topRows(Index n) const
 {
   return ConstRowsBlockXpr(derived(), 0, 0, n, cols());
 }
 
-/** \returns a block consisting of the top rows of *this.
-  *
-  * \tparam N the number of rows in the block as specified at compile-time
-  * \param n the number of rows in the block as specified at run-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include MatrixBase_template_int_topRows.cpp
-  * Output: \verbinclude MatrixBase_template_int_topRows.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of the top rows of *this.
+///
+/// \tparam N the number of rows in the block as specified at compile-time
+/// \param n the number of rows in the block as specified at run-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include MatrixBase_template_int_topRows.cpp
+/// Output: \verbinclude MatrixBase_template_int_topRows.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(row-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename NRowsBlockXpr<N>::Type topRows(Index n = N)
 {
   return typename NRowsBlockXpr<N>::Type(derived(), 0, 0, n, cols());
 }
 
-/** This is the const version of topRows<int>().*/
+/// This is the const version of topRows<int>().
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstNRowsBlockXpr<N>::Type topRows(Index n = N) const
 {
   return typename ConstNRowsBlockXpr<N>::Type(derived(), 0, 0, n, cols());
 }
 
 
 
-/** \returns a block consisting of the bottom rows of *this.
-  *
-  * \param n the number of rows in the block
-  *
-  * Example: \include MatrixBase_bottomRows_int.cpp
-  * Output: \verbinclude MatrixBase_bottomRows_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of the bottom rows of *this.
+///
+/// \param n the number of rows in the block
+///
+/// Example: \include MatrixBase_bottomRows_int.cpp
+/// Output: \verbinclude MatrixBase_bottomRows_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(row-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
 inline RowsBlockXpr bottomRows(Index n)
 {
   return RowsBlockXpr(derived(), rows() - n, 0, n, cols());
 }
 
-/** This is the const version of bottomRows(Index).*/
+/// This is the const version of bottomRows(Index).
+EIGEN_DEVICE_FUNC
 inline ConstRowsBlockXpr bottomRows(Index n) const
 {
   return ConstRowsBlockXpr(derived(), rows() - n, 0, n, cols());
 }
 
-/** \returns a block consisting of the bottom rows of *this.
-  *
-  * \tparam N the number of rows in the block as specified at compile-time
-  * \param n the number of rows in the block as specified at run-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include MatrixBase_template_int_bottomRows.cpp
-  * Output: \verbinclude MatrixBase_template_int_bottomRows.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of the bottom rows of *this.
+///
+/// \tparam N the number of rows in the block as specified at compile-time
+/// \param n the number of rows in the block as specified at run-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include MatrixBase_template_int_bottomRows.cpp
+/// Output: \verbinclude MatrixBase_template_int_bottomRows.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(row-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename NRowsBlockXpr<N>::Type bottomRows(Index n = N)
 {
   return typename NRowsBlockXpr<N>::Type(derived(), rows() - n, 0, n, cols());
 }
 
-/** This is the const version of bottomRows<int>().*/
+/// This is the const version of bottomRows<int>().
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstNRowsBlockXpr<N>::Type bottomRows(Index n = N) const
 {
   return typename ConstNRowsBlockXpr<N>::Type(derived(), rows() - n, 0, n, cols());
 }
 
 
 
-/** \returns a block consisting of a range of rows of *this.
-  *
-  * \param startRow the index of the first row in the block
-  * \param n the number of rows in the block
-  *
-  * Example: \include DenseBase_middleRows_int.cpp
-  * Output: \verbinclude DenseBase_middleRows_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of a range of rows of *this.
+///
+/// \param startRow the index of the first row in the block
+/// \param n the number of rows in the block
+///
+/// Example: \include DenseBase_middleRows_int.cpp
+/// Output: \verbinclude DenseBase_middleRows_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(row-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
 inline RowsBlockXpr middleRows(Index startRow, Index n)
 {
   return RowsBlockXpr(derived(), startRow, 0, n, cols());
 }
 
-/** This is the const version of middleRows(Index,Index).*/
+/// This is the const version of middleRows(Index,Index).
+EIGEN_DEVICE_FUNC
 inline ConstRowsBlockXpr middleRows(Index startRow, Index n) const
 {
   return ConstRowsBlockXpr(derived(), startRow, 0, n, cols());
 }
 
-/** \returns a block consisting of a range of rows of *this.
-  *
-  * \tparam N the number of rows in the block as specified at compile-time
-  * \param startRow the index of the first row in the block
-  * \param n the number of rows in the block as specified at run-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include DenseBase_template_int_middleRows.cpp
-  * Output: \verbinclude DenseBase_template_int_middleRows.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of a range of rows of *this.
+///
+/// \tparam N the number of rows in the block as specified at compile-time
+/// \param startRow the index of the first row in the block
+/// \param n the number of rows in the block as specified at run-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include DenseBase_template_int_middleRows.cpp
+/// Output: \verbinclude DenseBase_template_int_middleRows.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(row-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename NRowsBlockXpr<N>::Type middleRows(Index startRow, Index n = N)
 {
   return typename NRowsBlockXpr<N>::Type(derived(), startRow, 0, n, cols());
 }
 
-/** This is the const version of middleRows<int>().*/
+/// This is the const version of middleRows<int>().
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstNRowsBlockXpr<N>::Type middleRows(Index startRow, Index n = N) const
 {
   return typename ConstNRowsBlockXpr<N>::Type(derived(), startRow, 0, n, cols());
 }
 
 
 
-/** \returns a block consisting of the left columns of *this.
-  *
-  * \param n the number of columns in the block
-  *
-  * Example: \include MatrixBase_leftCols_int.cpp
-  * Output: \verbinclude MatrixBase_leftCols_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of the left columns of *this.
+///
+/// \param n the number of columns in the block
+///
+/// Example: \include MatrixBase_leftCols_int.cpp
+/// Output: \verbinclude MatrixBase_leftCols_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(column-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
 inline ColsBlockXpr leftCols(Index n)
 {
   return ColsBlockXpr(derived(), 0, 0, rows(), n);
 }
 
-/** This is the const version of leftCols(Index).*/
+/// This is the const version of leftCols(Index).
+EIGEN_DEVICE_FUNC
 inline ConstColsBlockXpr leftCols(Index n) const
 {
   return ConstColsBlockXpr(derived(), 0, 0, rows(), n);
 }
 
-/** \returns a block consisting of the left columns of *this.
-  *
-  * \tparam N the number of columns in the block as specified at compile-time
-  * \param n the number of columns in the block as specified at run-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include MatrixBase_template_int_leftCols.cpp
-  * Output: \verbinclude MatrixBase_template_int_leftCols.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of the left columns of *this.
+///
+/// \tparam N the number of columns in the block as specified at compile-time
+/// \param n the number of columns in the block as specified at run-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include MatrixBase_template_int_leftCols.cpp
+/// Output: \verbinclude MatrixBase_template_int_leftCols.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(column-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename NColsBlockXpr<N>::Type leftCols(Index n = N)
 {
   return typename NColsBlockXpr<N>::Type(derived(), 0, 0, rows(), n);
 }
 
-/** This is the const version of leftCols<int>().*/
+/// This is the const version of leftCols<int>().
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstNColsBlockXpr<N>::Type leftCols(Index n = N) const
 {
   return typename ConstNColsBlockXpr<N>::Type(derived(), 0, 0, rows(), n);
 }
 
 
 
-/** \returns a block consisting of the right columns of *this.
-  *
-  * \param n the number of columns in the block
-  *
-  * Example: \include MatrixBase_rightCols_int.cpp
-  * Output: \verbinclude MatrixBase_rightCols_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of the right columns of *this.
+///
+/// \param n the number of columns in the block
+///
+/// Example: \include MatrixBase_rightCols_int.cpp
+/// Output: \verbinclude MatrixBase_rightCols_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(column-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
 inline ColsBlockXpr rightCols(Index n)
 {
   return ColsBlockXpr(derived(), 0, cols() - n, rows(), n);
 }
 
-/** This is the const version of rightCols(Index).*/
+/// This is the const version of rightCols(Index).
+EIGEN_DEVICE_FUNC
 inline ConstColsBlockXpr rightCols(Index n) const
 {
   return ConstColsBlockXpr(derived(), 0, cols() - n, rows(), n);
 }
 
-/** \returns a block consisting of the right columns of *this.
-  *
-  * \tparam N the number of columns in the block as specified at compile-time
-  * \param n the number of columns in the block as specified at run-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include MatrixBase_template_int_rightCols.cpp
-  * Output: \verbinclude MatrixBase_template_int_rightCols.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of the right columns of *this.
+///
+/// \tparam N the number of columns in the block as specified at compile-time
+/// \param n the number of columns in the block as specified at run-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include MatrixBase_template_int_rightCols.cpp
+/// Output: \verbinclude MatrixBase_template_int_rightCols.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(column-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename NColsBlockXpr<N>::Type rightCols(Index n = N)
 {
   return typename NColsBlockXpr<N>::Type(derived(), 0, cols() - n, rows(), n);
 }
 
-/** This is the const version of rightCols<int>().*/
+/// This is the const version of rightCols<int>().
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstNColsBlockXpr<N>::Type rightCols(Index n = N) const
 {
   return typename ConstNColsBlockXpr<N>::Type(derived(), 0, cols() - n, rows(), n);
 }
 
 
 
-/** \returns a block consisting of a range of columns of *this.
-  *
-  * \param startCol the index of the first column in the block
-  * \param numCols the number of columns in the block
-  *
-  * Example: \include DenseBase_middleCols_int.cpp
-  * Output: \verbinclude DenseBase_middleCols_int.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of a range of columns of *this.
+///
+/// \param startCol the index of the first column in the block
+/// \param numCols the number of columns in the block
+///
+/// Example: \include DenseBase_middleCols_int.cpp
+/// Output: \verbinclude DenseBase_middleCols_int.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(column-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+EIGEN_DEVICE_FUNC
 inline ColsBlockXpr middleCols(Index startCol, Index numCols)
 {
   return ColsBlockXpr(derived(), 0, startCol, rows(), numCols);
 }
 
-/** This is the const version of middleCols(Index,Index).*/
+/// This is the const version of middleCols(Index,Index).
+EIGEN_DEVICE_FUNC
 inline ConstColsBlockXpr middleCols(Index startCol, Index numCols) const
 {
   return ConstColsBlockXpr(derived(), 0, startCol, rows(), numCols);
 }
 
-/** \returns a block consisting of a range of columns of *this.
-  *
-  * \tparam N the number of columns in the block as specified at compile-time
-  * \param startCol the index of the first column in the block
-  * \param n the number of columns in the block as specified at run-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include DenseBase_template_int_middleCols.cpp
-  * Output: \verbinclude DenseBase_template_int_middleCols.out
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
+/// \returns a block consisting of a range of columns of *this.
+///
+/// \tparam N the number of columns in the block as specified at compile-time
+/// \param startCol the index of the first column in the block
+/// \param n the number of columns in the block as specified at run-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include DenseBase_template_int_middleCols.cpp
+/// Output: \verbinclude DenseBase_template_int_middleCols.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(column-major)
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename NColsBlockXpr<N>::Type middleCols(Index startCol, Index n = N)
 {
   return typename NColsBlockXpr<N>::Type(derived(), 0, startCol, rows(), n);
 }
 
-/** This is the const version of middleCols<int>().*/
+/// This is the const version of middleCols<int>().
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstNColsBlockXpr<N>::Type middleCols(Index startCol, Index n = N) const
 {
   return typename ConstNColsBlockXpr<N>::Type(derived(), 0, startCol, rows(), n);
 }
 
 
 
-/** \returns a fixed-size expression of a block in *this.
-  *
-  * The template parameters \a BlockRows and \a BlockCols are the number of
-  * rows and columns in the block.
-  *
-  * \param startRow the first row in the block
-  * \param startCol the first column in the block
-  *
-  * Example: \include MatrixBase_block_int_int.cpp
-  * Output: \verbinclude MatrixBase_block_int_int.out
-  *
-  * \note since block is a templated member, the keyword template has to be used
-  * if the matrix type is also a template parameter: \code m.template block<3,3>(1,1); \endcode
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-template<int BlockRows, int BlockCols>
-inline Block<Derived, BlockRows, BlockCols> block(Index startRow, Index startCol)
-{
-  return Block<Derived, BlockRows, BlockCols>(derived(), startRow, startCol);
-}
-
-/** This is the const version of block<>(Index, Index). */
-template<int BlockRows, int BlockCols>
-inline const Block<const Derived, BlockRows, BlockCols> block(Index startRow, Index startCol) const
-{
-  return Block<const Derived, BlockRows, BlockCols>(derived(), startRow, startCol);
-}
-
-/** \returns an expression of a block in *this.
-  *
-  * \tparam BlockRows number of rows in block as specified at compile-time
-  * \tparam BlockCols number of columns in block as specified at compile-time
-  * \param  startRow  the first row in the block
-  * \param  startCol  the first column in the block
-  * \param  blockRows number of rows in block as specified at run-time
-  * \param  blockCols number of columns in block as specified at run-time
-  *
-  * This function is mainly useful for blocks where the number of rows is specified at compile-time
-  * and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
-  * information should not contradict. In other words, \a blockRows should equal \a BlockRows unless
-  * \a BlockRows is \a Dynamic, and the same for the number of columns.
-  *
-  * Example: \include MatrixBase_template_int_int_block_int_int_int_int.cpp
-  * Output: \verbinclude MatrixBase_template_int_int_block_int_int_int_int.cpp
-  *
-  * \sa class Block, block(Index,Index,Index,Index)
-  */
-template<int BlockRows, int BlockCols>
-inline Block<Derived, BlockRows, BlockCols> block(Index startRow, Index startCol, 
+/// \returns a fixed-size expression of a block in *this.
+///
+/// The template parameters \a NRows and \a NCols are the number of
+/// rows and columns in the block.
+///
+/// \param startRow the first row in the block
+/// \param startCol the first column in the block
+///
+/// Example: \include MatrixBase_block_int_int.cpp
+/// Output: \verbinclude MatrixBase_block_int_int.out
+///
+/// \note since block is a templated member, the keyword template has to be used
+/// if the matrix type is also a template parameter: \code m.template block<3,3>(1,1); \endcode
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+template<int NRows, int NCols>
+EIGEN_DEVICE_FUNC
+inline typename FixedBlockXpr<NRows,NCols>::Type block(Index startRow, Index startCol)
+{
+  return typename FixedBlockXpr<NRows,NCols>::Type(derived(), startRow, startCol);
+}
+
+/// This is the const version of block<>(Index, Index). */
+template<int NRows, int NCols>
+EIGEN_DEVICE_FUNC
+inline const typename ConstFixedBlockXpr<NRows,NCols>::Type block(Index startRow, Index startCol) const
+{
+  return typename ConstFixedBlockXpr<NRows,NCols>::Type(derived(), startRow, startCol);
+}
+
+/// \returns an expression of a block in *this.
+///
+/// \tparam NRows number of rows in block as specified at compile-time
+/// \tparam NCols number of columns in block as specified at compile-time
+/// \param  startRow  the first row in the block
+/// \param  startCol  the first column in the block
+/// \param  blockRows number of rows in block as specified at run-time
+/// \param  blockCols number of columns in block as specified at run-time
+///
+/// This function is mainly useful for blocks where the number of rows is specified at compile-time
+/// and the number of columns is specified at run-time, or vice versa. The compile-time and run-time
+/// information should not contradict. In other words, \a blockRows should equal \a NRows unless
+/// \a NRows is \a Dynamic, and the same for the number of columns.
+///
+/// Example: \include MatrixBase_template_int_int_block_int_int_int_int.cpp
+/// Output: \verbinclude MatrixBase_template_int_int_block_int_int_int_int.cpp
+///
+EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
+///
+/// \sa class Block, block(Index,Index,Index,Index)
+///
+template<int NRows, int NCols>
+inline typename FixedBlockXpr<NRows,NCols>::Type block(Index startRow, Index startCol,
                                                   Index blockRows, Index blockCols)
 {
-  return Block<Derived, BlockRows, BlockCols>(derived(), startRow, startCol, blockRows, blockCols);
+  return typename FixedBlockXpr<NRows,NCols>::Type(derived(), startRow, startCol, blockRows, blockCols);
 }
 
-/** This is the const version of block<>(Index, Index, Index, Index). */
-template<int BlockRows, int BlockCols>
-inline const Block<const Derived, BlockRows, BlockCols> block(Index startRow, Index startCol,
+/// This is the const version of block<>(Index, Index, Index, Index).
+template<int NRows, int NCols>
+inline const typename ConstFixedBlockXpr<NRows,NCols>::Type block(Index startRow, Index startCol,
                                                               Index blockRows, Index blockCols) const
 {
-  return Block<const Derived, BlockRows, BlockCols>(derived(), startRow, startCol, blockRows, blockCols);
+  return typename ConstFixedBlockXpr<NRows,NCols>::Type(derived(), startRow, startCol, blockRows, blockCols);
 }
 
-/** \returns an expression of the \a i-th column of *this. Note that the numbering starts at 0.
-  *
-  * Example: \include MatrixBase_col.cpp
-  * Output: \verbinclude MatrixBase_col.out
-  *
+/// \returns an expression of the \a i-th column of *this. Note that the numbering starts at 0.
+///
+/// Example: \include MatrixBase_col.cpp
+/// Output: \verbinclude MatrixBase_col.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(column-major)
+/**
   * \sa row(), class Block */
+EIGEN_DEVICE_FUNC
 inline ColXpr col(Index i)
 {
   return ColXpr(derived(), i);
 }
 
-/** This is the const version of col(). */
+/// This is the const version of col().
+EIGEN_DEVICE_FUNC
 inline ConstColXpr col(Index i) const
 {
   return ConstColXpr(derived(), i);
 }
 
-/** \returns an expression of the \a i-th row of *this. Note that the numbering starts at 0.
-  *
-  * Example: \include MatrixBase_row.cpp
-  * Output: \verbinclude MatrixBase_row.out
-  *
+/// \returns an expression of the \a i-th row of *this. Note that the numbering starts at 0.
+///
+/// Example: \include MatrixBase_row.cpp
+/// Output: \verbinclude MatrixBase_row.out
+///
+EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(row-major)
+/**
   * \sa col(), class Block */
+EIGEN_DEVICE_FUNC
 inline RowXpr row(Index i)
 {
   return RowXpr(derived(), i);
 }
 
-/** This is the const version of row(). */
+/// This is the const version of row(). */
+EIGEN_DEVICE_FUNC
 inline ConstRowXpr row(Index i) const
 {
   return ConstRowXpr(derived(), i);
 }
 
-/** \returns a dynamic-size expression of a segment (i.e. a vector block) in *this.
-  *
-  * \only_for_vectors
-  *
-  * \param start the first coefficient in the segment
-  * \param n the number of coefficients in the segment
-  *
-  * Example: \include MatrixBase_segment_int_int.cpp
-  * Output: \verbinclude MatrixBase_segment_int_int.out
-  *
-  * \note Even though the returned expression has dynamic size, in the case
-  * when it is applied to a fixed-size vector, it inherits a fixed maximal size,
-  * which means that evaluating it does not cause a dynamic memory allocation.
-  *
-  * \sa class Block, segment(Index)
-  */
+/// \returns a dynamic-size expression of a segment (i.e. a vector block) in *this.
+///
+/// \only_for_vectors
+///
+/// \param start the first coefficient in the segment
+/// \param n the number of coefficients in the segment
+///
+/// Example: \include MatrixBase_segment_int_int.cpp
+/// Output: \verbinclude MatrixBase_segment_int_int.out
+///
+/// \note Even though the returned expression has dynamic size, in the case
+/// when it is applied to a fixed-size vector, it inherits a fixed maximal size,
+/// which means that evaluating it does not cause a dynamic memory allocation.
+///
+/// \sa class Block, segment(Index)
+///
+EIGEN_DEVICE_FUNC
 inline SegmentReturnType segment(Index start, Index n)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return SegmentReturnType(derived(), start, n);
 }
 
 
-/** This is the const version of segment(Index,Index).*/
+/// This is the const version of segment(Index,Index).
+EIGEN_DEVICE_FUNC
 inline ConstSegmentReturnType segment(Index start, Index n) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return ConstSegmentReturnType(derived(), start, n);
 }
 
-/** \returns a dynamic-size expression of the first coefficients of *this.
-  *
-  * \only_for_vectors
-  *
-  * \param n the number of coefficients in the segment
-  *
-  * Example: \include MatrixBase_start_int.cpp
-  * Output: \verbinclude MatrixBase_start_int.out
-  *
-  * \note Even though the returned expression has dynamic size, in the case
-  * when it is applied to a fixed-size vector, it inherits a fixed maximal size,
-  * which means that evaluating it does not cause a dynamic memory allocation.
-  *
-  * \sa class Block, block(Index,Index)
-  */
+/// \returns a dynamic-size expression of the first coefficients of *this.
+///
+/// \only_for_vectors
+///
+/// \param n the number of coefficients in the segment
+///
+/// Example: \include MatrixBase_start_int.cpp
+/// Output: \verbinclude MatrixBase_start_int.out
+///
+/// \note Even though the returned expression has dynamic size, in the case
+/// when it is applied to a fixed-size vector, it inherits a fixed maximal size,
+/// which means that evaluating it does not cause a dynamic memory allocation.
+///
+/// \sa class Block, block(Index,Index)
+///
+EIGEN_DEVICE_FUNC
 inline SegmentReturnType head(Index n)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return SegmentReturnType(derived(), 0, n);
 }
 
-/** This is the const version of head(Index).*/
+/// This is the const version of head(Index).
+EIGEN_DEVICE_FUNC
 inline ConstSegmentReturnType head(Index n) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return ConstSegmentReturnType(derived(), 0, n);
 }
 
-/** \returns a dynamic-size expression of the last coefficients of *this.
-  *
-  * \only_for_vectors
-  *
-  * \param n the number of coefficients in the segment
-  *
-  * Example: \include MatrixBase_end_int.cpp
-  * Output: \verbinclude MatrixBase_end_int.out
-  *
-  * \note Even though the returned expression has dynamic size, in the case
-  * when it is applied to a fixed-size vector, it inherits a fixed maximal size,
-  * which means that evaluating it does not cause a dynamic memory allocation.
-  *
-  * \sa class Block, block(Index,Index)
-  */
+/// \returns a dynamic-size expression of the last coefficients of *this.
+///
+/// \only_for_vectors
+///
+/// \param n the number of coefficients in the segment
+///
+/// Example: \include MatrixBase_end_int.cpp
+/// Output: \verbinclude MatrixBase_end_int.out
+///
+/// \note Even though the returned expression has dynamic size, in the case
+/// when it is applied to a fixed-size vector, it inherits a fixed maximal size,
+/// which means that evaluating it does not cause a dynamic memory allocation.
+///
+/// \sa class Block, block(Index,Index)
+///
+EIGEN_DEVICE_FUNC
 inline SegmentReturnType tail(Index n)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return SegmentReturnType(derived(), this->size() - n, n);
 }
 
-/** This is the const version of tail(Index).*/
+/// This is the const version of tail(Index).
+EIGEN_DEVICE_FUNC
 inline ConstSegmentReturnType tail(Index n) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return ConstSegmentReturnType(derived(), this->size() - n, n);
 }
 
-/** \returns a fixed-size expression of a segment (i.e. a vector block) in \c *this
-  *
-  * \only_for_vectors
-  *
-  * \tparam N the number of coefficients in the segment as specified at compile-time
-  * \param start the index of the first element in the segment
-  * \param n the number of coefficients in the segment as specified at compile-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include MatrixBase_template_int_segment.cpp
-  * Output: \verbinclude MatrixBase_template_int_segment.out
-  *
-  * \sa class Block
-  */
+/// \returns a fixed-size expression of a segment (i.e. a vector block) in \c *this
+///
+/// \only_for_vectors
+///
+/// \tparam N the number of coefficients in the segment as specified at compile-time
+/// \param start the index of the first element in the segment
+/// \param n the number of coefficients in the segment as specified at compile-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include MatrixBase_template_int_segment.cpp
+/// Output: \verbinclude MatrixBase_template_int_segment.out
+///
+/// \sa class Block
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename FixedSegmentReturnType<N>::Type segment(Index start, Index n = N)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return typename FixedSegmentReturnType<N>::Type(derived(), start, n);
 }
 
-/** This is the const version of segment<int>(Index).*/
+/// This is the const version of segment<int>(Index).
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstFixedSegmentReturnType<N>::Type segment(Index start, Index n = N) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return typename ConstFixedSegmentReturnType<N>::Type(derived(), start, n);
 }
 
-/** \returns a fixed-size expression of the first coefficients of *this.
-  *
-  * \only_for_vectors
-  *
-  * \tparam N the number of coefficients in the segment as specified at compile-time
-  * \param  n the number of coefficients in the segment as specified at run-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include MatrixBase_template_int_start.cpp
-  * Output: \verbinclude MatrixBase_template_int_start.out
-  *
-  * \sa class Block
-  */
+/// \returns a fixed-size expression of the first coefficients of *this.
+///
+/// \only_for_vectors
+///
+/// \tparam N the number of coefficients in the segment as specified at compile-time
+/// \param  n the number of coefficients in the segment as specified at run-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include MatrixBase_template_int_start.cpp
+/// Output: \verbinclude MatrixBase_template_int_start.out
+///
+/// \sa class Block
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename FixedSegmentReturnType<N>::Type head(Index n = N)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return typename FixedSegmentReturnType<N>::Type(derived(), 0, n);
 }
 
-/** This is the const version of head<int>().*/
+/// This is the const version of head<int>().
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstFixedSegmentReturnType<N>::Type head(Index n = N) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return typename ConstFixedSegmentReturnType<N>::Type(derived(), 0, n);
 }
 
-/** \returns a fixed-size expression of the last coefficients of *this.
-  *
-  * \only_for_vectors
-  *
-  * \tparam N the number of coefficients in the segment as specified at compile-time
-  * \param  n the number of coefficients in the segment as specified at run-time
-  *
-  * The compile-time and run-time information should not contradict. In other words,
-  * \a n should equal \a N unless \a N is \a Dynamic.
-  *
-  * Example: \include MatrixBase_template_int_end.cpp
-  * Output: \verbinclude MatrixBase_template_int_end.out
-  *
-  * \sa class Block
-  */
+/// \returns a fixed-size expression of the last coefficients of *this.
+///
+/// \only_for_vectors
+///
+/// \tparam N the number of coefficients in the segment as specified at compile-time
+/// \param  n the number of coefficients in the segment as specified at run-time
+///
+/// The compile-time and run-time information should not contradict. In other words,
+/// \a n should equal \a N unless \a N is \a Dynamic.
+///
+/// Example: \include MatrixBase_template_int_end.cpp
+/// Output: \verbinclude MatrixBase_template_int_end.out
+///
+/// \sa class Block
+///
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename FixedSegmentReturnType<N>::Type tail(Index n = N)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return typename FixedSegmentReturnType<N>::Type(derived(), size() - n);
 }
 
-/** This is the const version of tail<int>.*/
+/// This is the const version of tail<int>.
 template<int N>
+EIGEN_DEVICE_FUNC
 inline typename ConstFixedSegmentReturnType<N>::Type tail(Index n = N) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return typename ConstFixedSegmentReturnType<N>::Type(derived(), size() - n);
 }

DELETED 3rd_party/eigen/Eigen/src/plugins/CMakeLists.txt
Index: 3rd_party/eigen/Eigen/src/plugins/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/Eigen/src/plugins/CMakeLists.txt
+++ 3rd_party/eigen/Eigen/src/plugins/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_plugins_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_plugins_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/plugins COMPONENT Devel
-  )

Index: 3rd_party/eigen/Eigen/src/plugins/CommonCwiseBinaryOps.h
==================================================================
--- 3rd_party/eigen/Eigen/src/plugins/CommonCwiseBinaryOps.h
+++ 3rd_party/eigen/Eigen/src/plugins/CommonCwiseBinaryOps.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -14,19 +14,19 @@
   *
   * \note If you want to substract a given scalar from all coefficients, see Cwise::operator-().
   *
   * \sa class CwiseBinaryOp, operator-=()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(operator-,internal::scalar_difference_op)
+EIGEN_MAKE_CWISE_BINARY_OP(operator-,difference)
 
 /** \returns an expression of the sum of \c *this and \a other
   *
   * \note If you want to add a given scalar to all coefficients, see Cwise::operator+().
   *
   * \sa class CwiseBinaryOp, operator+=()
   */
-EIGEN_MAKE_CWISE_BINARY_OP(operator+,internal::scalar_sum_op)
+EIGEN_MAKE_CWISE_BINARY_OP(operator+,sum)
 
 /** \returns an expression of a custom coefficient-wise operator \a func of *this and \a other
   *
   * The template parameter \a CustomBinaryOp is the type of the functor
   * of the custom operator (see class CwiseBinaryOp for an example)
@@ -36,11 +36,80 @@
   * Output: \verbinclude class_CwiseBinaryOp.out
   *
   * \sa class CwiseBinaryOp, operator+(), operator-(), cwiseProduct()
   */
 template<typename CustomBinaryOp, typename OtherDerived>
+EIGEN_DEVICE_FUNC
 EIGEN_STRONG_INLINE const CwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived>
 binaryExpr(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other, const CustomBinaryOp& func = CustomBinaryOp()) const
 {
   return CwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived>(derived(), other.derived(), func);
 }
 
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+EIGEN_MAKE_SCALAR_BINARY_OP(operator*,product)
+#else
+/** \returns an expression of \c *this scaled by the scalar factor \a scalar
+  *
+  * \tparam T is the scalar type of \a scalar. It must be compatible with the scalar type of the given expression.
+  */
+template<typename T>
+const CwiseBinaryOp<internal::scalar_product_op<Scalar,T>,Derived,Constant<T> > operator*(const T& scalar) const;
+/** \returns an expression of \a expr scaled by the scalar factor \a scalar
+  *
+  * \tparam T is the scalar type of \a scalar. It must be compatible with the scalar type of the given expression.
+  */
+template<typename T> friend
+const CwiseBinaryOp<internal::scalar_product_op<T,Scalar>,Constant<T>,Derived> operator*(const T& scalar, const StorageBaseType& expr);
+#endif
+
+
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+EIGEN_MAKE_SCALAR_BINARY_OP_ONTHERIGHT(operator/,quotient)
+#else
+/** \returns an expression of \c *this divided by the scalar value \a scalar
+  *
+  * \tparam T is the scalar type of \a scalar. It must be compatible with the scalar type of the given expression.
+  */
+template<typename T>
+const CwiseBinaryOp<internal::scalar_quotient_op<Scalar,T>,Derived,Constant<T> > operator/(const T& scalar) const;
+#endif
+
+/** \returns an expression of the coefficient-wise boolean \b and operator of \c *this and \a other
+  *
+  * \warning this operator is for expression of bool only.
+  *
+  * Example: \include Cwise_boolean_and.cpp
+  * Output: \verbinclude Cwise_boolean_and.out
+  *
+  * \sa operator||(), select()
+  */
+template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
+inline const CwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived>
+operator&&(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
+{
+  EIGEN_STATIC_ASSERT((internal::is_same<bool,Scalar>::value && internal::is_same<bool,typename OtherDerived::Scalar>::value),
+                      THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
+  return CwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived>(derived(),other.derived());
+}
+
+/** \returns an expression of the coefficient-wise boolean \b or operator of \c *this and \a other
+  *
+  * \warning this operator is for expression of bool only.
+  *
+  * Example: \include Cwise_boolean_or.cpp
+  * Output: \verbinclude Cwise_boolean_or.out
+  *
+  * \sa operator&&(), select()
+  */
+template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
+inline const CwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>
+operator||(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
+{
+  EIGEN_STATIC_ASSERT((internal::is_same<bool,Scalar>::value && internal::is_same<bool,typename OtherDerived::Scalar>::value),
+                      THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
+  return CwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>(derived(),other.derived());
+}

Index: 3rd_party/eigen/Eigen/src/plugins/CommonCwiseUnaryOps.h
==================================================================
--- 3rd_party/eigen/Eigen/src/plugins/CommonCwiseUnaryOps.h
+++ 3rd_party/eigen/Eigen/src/plugins/CommonCwiseUnaryOps.h
@@ -10,14 +10,10 @@
 
 // This file is a base class plugin containing common coefficient wise functions.
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
 
-/** \internal Represents a scalar multiple of an expression */
-typedef CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Derived> ScalarMultipleReturnType;
-/** \internal Represents a quotient of an expression by a scalar*/
-typedef CwiseUnaryOp<internal::scalar_quotient1_op<Scalar>, const Derived> ScalarQuotient1ReturnType;
 /** \internal the return type of conjugate() */
 typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
                     const CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, const Derived>,
                     const Derived&
                   >::type ConjugateReturnType;
@@ -34,139 +30,134 @@
 /** \internal the return type of imag() const */
 typedef CwiseUnaryOp<internal::scalar_imag_op<Scalar>, const Derived> ImagReturnType;
 /** \internal the return type of imag() */
 typedef CwiseUnaryView<internal::scalar_imag_ref_op<Scalar>, Derived> NonConstImagReturnType;
 
-#endif // not EIGEN_PARSED_BY_DOXYGEN
-
-/** \returns an expression of the opposite of \c *this
-  */
-inline const CwiseUnaryOp<internal::scalar_opposite_op<typename internal::traits<Derived>::Scalar>, const Derived>
-operator-() const { return derived(); }
-
-
-/** \returns an expression of \c *this scaled by the scalar factor \a scalar */
-inline const ScalarMultipleReturnType
-operator*(const Scalar& scalar) const
-{
-  return CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Derived>
-    (derived(), internal::scalar_multiple_op<Scalar>(scalar));
-}
-
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-const ScalarMultipleReturnType operator*(const RealScalar& scalar) const;
-#endif
-
-/** \returns an expression of \c *this divided by the scalar value \a scalar */
-inline const CwiseUnaryOp<internal::scalar_quotient1_op<typename internal::traits<Derived>::Scalar>, const Derived>
-operator/(const Scalar& scalar) const
-{
-  return CwiseUnaryOp<internal::scalar_quotient1_op<Scalar>, const Derived>
-    (derived(), internal::scalar_quotient1_op<Scalar>(scalar));
-}
-
-/** Overloaded for efficient real matrix times complex scalar value */
-inline const CwiseUnaryOp<internal::scalar_multiple2_op<Scalar,std::complex<Scalar> >, const Derived>
-operator*(const std::complex<Scalar>& scalar) const
-{
-  return CwiseUnaryOp<internal::scalar_multiple2_op<Scalar,std::complex<Scalar> >, const Derived>
-    (*static_cast<const Derived*>(this), internal::scalar_multiple2_op<Scalar,std::complex<Scalar> >(scalar));
-}
-
-inline friend const ScalarMultipleReturnType
-operator*(const Scalar& scalar, const StorageBaseType& matrix)
-{ return matrix*scalar; }
-
-inline friend const CwiseUnaryOp<internal::scalar_multiple2_op<Scalar,std::complex<Scalar> >, const Derived>
-operator*(const std::complex<Scalar>& scalar, const StorageBaseType& matrix)
-{ return matrix*scalar; }
-
-/** \returns an expression of *this with the \a Scalar type casted to
-  * \a NewScalar.
-  *
-  * The template parameter \a NewScalar is the type we are casting the scalars to.
-  *
-  * \sa class CwiseUnaryOp
-  */
-template<typename NewType>
-typename internal::cast_return_type<Derived,const CwiseUnaryOp<internal::scalar_cast_op<typename internal::traits<Derived>::Scalar, NewType>, const Derived> >::type
-cast() const
-{
-  return derived();
-}
-
-/** \returns an expression of the complex conjugate of \c *this.
-  *
-  * \sa adjoint() */
+typedef CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const Derived> NegativeReturnType;
+
+#endif // not EIGEN_PARSED_BY_DOXYGEN
+
+/// \returns an expression of the opposite of \c *this
+///
+EIGEN_DOC_UNARY_ADDONS(operator-,opposite)
+///
+EIGEN_DEVICE_FUNC
+inline const NegativeReturnType
+operator-() const { return NegativeReturnType(derived()); }
+
+
+template<class NewType> struct CastXpr { typedef typename internal::cast_return_type<Derived,const CwiseUnaryOp<internal::scalar_cast_op<Scalar, NewType>, const Derived> >::type Type; };
+
+/// \returns an expression of \c *this with the \a Scalar type casted to
+/// \a NewScalar.
+///
+/// The template parameter \a NewScalar is the type we are casting the scalars to.
+///
+EIGEN_DOC_UNARY_ADDONS(cast,conversion function)
+///
+/// \sa class CwiseUnaryOp
+///
+template<typename NewType>
+EIGEN_DEVICE_FUNC
+typename CastXpr<NewType>::Type
+cast() const
+{
+  return typename CastXpr<NewType>::Type(derived());
+}
+
+/// \returns an expression of the complex conjugate of \c *this.
+///
+EIGEN_DOC_UNARY_ADDONS(conjugate,complex conjugate)
+///
+/// \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_conj">Math functions</a>, MatrixBase::adjoint()
+EIGEN_DEVICE_FUNC
 inline ConjugateReturnType
 conjugate() const
 {
   return ConjugateReturnType(derived());
 }
 
-/** \returns a read-only expression of the real part of \c *this.
-  *
-  * \sa imag() */
-inline RealReturnType
-real() const { return derived(); }
-
-/** \returns an read-only expression of the imaginary part of \c *this.
-  *
-  * \sa real() */
-inline const ImagReturnType
-imag() const { return derived(); }
-
-/** \brief Apply a unary operator coefficient-wise
-  * \param[in]  func  Functor implementing the unary operator
-  * \tparam  CustomUnaryOp Type of \a func  
-  * \returns An expression of a custom coefficient-wise unary operator \a func of *this
-  *
-  * The function \c ptr_fun() from the C++ standard library can be used to make functors out of normal functions.
-  *
-  * Example:
-  * \include class_CwiseUnaryOp_ptrfun.cpp
-  * Output: \verbinclude class_CwiseUnaryOp_ptrfun.out
-  *
-  * Genuine functors allow for more possibilities, for instance it may contain a state.
-  *
-  * Example:
-  * \include class_CwiseUnaryOp.cpp
-  * Output: \verbinclude class_CwiseUnaryOp.out
-  *
-  * \sa class CwiseUnaryOp, class CwiseBinaryOp
-  */
-template<typename CustomUnaryOp>
+/// \returns a read-only expression of the real part of \c *this.
+///
+EIGEN_DOC_UNARY_ADDONS(real,real part function)
+///
+/// \sa imag()
+EIGEN_DEVICE_FUNC
+inline RealReturnType
+real() const { return RealReturnType(derived()); }
+
+/// \returns an read-only expression of the imaginary part of \c *this.
+///
+EIGEN_DOC_UNARY_ADDONS(imag,imaginary part function)
+///
+/// \sa real()
+EIGEN_DEVICE_FUNC
+inline const ImagReturnType
+imag() const { return ImagReturnType(derived()); }
+
+/// \brief Apply a unary operator coefficient-wise
+/// \param[in]  func  Functor implementing the unary operator
+/// \tparam  CustomUnaryOp Type of \a func
+/// \returns An expression of a custom coefficient-wise unary operator \a func of *this
+///
+/// The function \c ptr_fun() from the C++ standard library can be used to make functors out of normal functions.
+///
+/// Example:
+/// \include class_CwiseUnaryOp_ptrfun.cpp
+/// Output: \verbinclude class_CwiseUnaryOp_ptrfun.out
+///
+/// Genuine functors allow for more possibilities, for instance it may contain a state.
+///
+/// Example:
+/// \include class_CwiseUnaryOp.cpp
+/// Output: \verbinclude class_CwiseUnaryOp.out
+///
+EIGEN_DOC_UNARY_ADDONS(unaryExpr,unary function)
+///
+/// \sa unaryViewExpr, binaryExpr, class CwiseUnaryOp
+///
+template<typename CustomUnaryOp>
+EIGEN_DEVICE_FUNC
 inline const CwiseUnaryOp<CustomUnaryOp, const Derived>
 unaryExpr(const CustomUnaryOp& func = CustomUnaryOp()) const
 {
   return CwiseUnaryOp<CustomUnaryOp, const Derived>(derived(), func);
 }
 
-/** \returns an expression of a custom coefficient-wise unary operator \a func of *this
-  *
-  * The template parameter \a CustomUnaryOp is the type of the functor
-  * of the custom unary operator.
-  *
-  * Example:
-  * \include class_CwiseUnaryOp.cpp
-  * Output: \verbinclude class_CwiseUnaryOp.out
-  *
-  * \sa class CwiseUnaryOp, class CwiseBinaryOp
-  */
+/// \returns an expression of a custom coefficient-wise unary operator \a func of *this
+///
+/// The template parameter \a CustomUnaryOp is the type of the functor
+/// of the custom unary operator.
+///
+/// Example:
+/// \include class_CwiseUnaryOp.cpp
+/// Output: \verbinclude class_CwiseUnaryOp.out
+///
+EIGEN_DOC_UNARY_ADDONS(unaryViewExpr,unary function)
+///
+/// \sa unaryExpr, binaryExpr class CwiseUnaryOp
+///
 template<typename CustomViewOp>
+EIGEN_DEVICE_FUNC
 inline const CwiseUnaryView<CustomViewOp, const Derived>
 unaryViewExpr(const CustomViewOp& func = CustomViewOp()) const
 {
   return CwiseUnaryView<CustomViewOp, const Derived>(derived(), func);
 }
 
-/** \returns a non const expression of the real part of \c *this.
-  *
-  * \sa imag() */
-inline NonConstRealReturnType
-real() { return derived(); }
-
-/** \returns a non const expression of the imaginary part of \c *this.
-  *
-  * \sa real() */
-inline NonConstImagReturnType
-imag() { return derived(); }
+/// \returns a non const expression of the real part of \c *this.
+///
+EIGEN_DOC_UNARY_ADDONS(real,real part function)
+///
+/// \sa imag()
+EIGEN_DEVICE_FUNC
+inline NonConstRealReturnType
+real() { return NonConstRealReturnType(derived()); }
+
+/// \returns a non const expression of the imaginary part of \c *this.
+///
+EIGEN_DOC_UNARY_ADDONS(imag,imaginary part function)
+///
+/// \sa real()
+EIGEN_DEVICE_FUNC
+inline NonConstImagReturnType
+imag() { return NonConstImagReturnType(derived()); }

Index: 3rd_party/eigen/Eigen/src/plugins/MatrixCwiseBinaryOps.h
==================================================================
--- 3rd_party/eigen/Eigen/src/plugins/MatrixCwiseBinaryOps.h
+++ 3rd_party/eigen/Eigen/src/plugins/MatrixCwiseBinaryOps.h
@@ -16,14 +16,15 @@
   * Output: \verbinclude MatrixBase_cwiseProduct.out
   *
   * \sa class CwiseBinaryOp, cwiseAbs2
   */
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_PRODUCT_RETURN_TYPE(Derived,OtherDerived)
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const EIGEN_CWISE_BINARY_RETURN_TYPE(Derived,OtherDerived,product)
 cwiseProduct(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
 {
-  return EIGEN_CWISE_PRODUCT_RETURN_TYPE(Derived,OtherDerived)(derived(), other.derived());
+  return EIGEN_CWISE_BINARY_RETURN_TYPE(Derived,OtherDerived,product)(derived(), other.derived());
 }
 
 /** \returns an expression of the coefficient-wise == operator of *this and \a other
   *
   * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
@@ -35,10 +36,11 @@
   * Output: \verbinclude MatrixBase_cwiseEqual.out
   *
   * \sa cwiseNotEqual(), isApprox(), isMuchSmallerThan()
   */
 template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
 inline const CwiseBinaryOp<std::equal_to<Scalar>, const Derived, const OtherDerived>
 cwiseEqual(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
 {
   return CwiseBinaryOp<std::equal_to<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
 }
@@ -54,10 +56,11 @@
   * Output: \verbinclude MatrixBase_cwiseNotEqual.out
   *
   * \sa cwiseEqual(), isApprox(), isMuchSmallerThan()
   */
 template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
 inline const CwiseBinaryOp<std::not_equal_to<Scalar>, const Derived, const OtherDerived>
 cwiseNotEqual(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
 {
   return CwiseBinaryOp<std::not_equal_to<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
 }
@@ -68,21 +71,23 @@
   * Output: \verbinclude MatrixBase_cwiseMin.out
   *
   * \sa class CwiseBinaryOp, max()
   */
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const OtherDerived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar,Scalar>, const Derived, const OtherDerived>
 cwiseMin(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
 {
-  return CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
+  return CwiseBinaryOp<internal::scalar_min_op<Scalar,Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
 }
 
 /** \returns an expression of the coefficient-wise min of *this and scalar \a other
   *
   * \sa class CwiseBinaryOp, min()
   */
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const ConstantReturnType>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar,Scalar>, const Derived, const ConstantReturnType>
 cwiseMin(const Scalar &other) const
 {
   return cwiseMin(Derived::Constant(rows(), cols(), other));
 }
 
@@ -92,21 +97,23 @@
   * Output: \verbinclude MatrixBase_cwiseMax.out
   *
   * \sa class CwiseBinaryOp, min()
   */
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const OtherDerived>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar,Scalar>, const Derived, const OtherDerived>
 cwiseMax(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
 {
-  return CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
+  return CwiseBinaryOp<internal::scalar_max_op<Scalar,Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
 }
 
 /** \returns an expression of the coefficient-wise max of *this and scalar \a other
   *
   * \sa class CwiseBinaryOp, min()
   */
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const ConstantReturnType>
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar,Scalar>, const Derived, const ConstantReturnType>
 cwiseMax(const Scalar &other) const
 {
   return cwiseMax(Derived::Constant(rows(), cols(), other));
 }
 
@@ -117,10 +124,29 @@
   * Output: \verbinclude MatrixBase_cwiseQuotient.out
   *
   * \sa class CwiseBinaryOp, cwiseProduct(), cwiseInverse()
   */
 template<typename OtherDerived>
+EIGEN_DEVICE_FUNC
 EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>
 cwiseQuotient(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
 {
   return CwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
 }
+
+typedef CwiseBinaryOp<internal::scalar_cmp_op<Scalar,Scalar,internal::cmp_EQ>, const Derived, const ConstantReturnType> CwiseScalarEqualReturnType;
+
+/** \returns an expression of the coefficient-wise == operator of \c *this and a scalar \a s
+  *
+  * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
+  * In order to check for equality between two vectors or matrices with floating-point coefficients, it is
+  * generally a far better idea to use a fuzzy comparison as provided by isApprox() and
+  * isMuchSmallerThan().
+  *
+  * \sa cwiseEqual(const MatrixBase<OtherDerived> &) const
+  */
+EIGEN_DEVICE_FUNC
+inline const CwiseScalarEqualReturnType
+cwiseEqual(const Scalar& s) const
+{
+  return CwiseScalarEqualReturnType(derived(), Derived::Constant(rows(), cols(), s), internal::scalar_cmp_op<Scalar,Scalar,internal::cmp_EQ>());
+}

Index: 3rd_party/eigen/Eigen/src/plugins/MatrixCwiseUnaryOps.h
==================================================================
--- 3rd_party/eigen/Eigen/src/plugins/MatrixCwiseUnaryOps.h
+++ 3rd_party/eigen/Eigen/src/plugins/MatrixCwiseUnaryOps.h
@@ -6,62 +6,80 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
-// This file is a base class plugin containing matrix specifics coefficient wise functions.
-
-/** \returns an expression of the coefficient-wise absolute value of \c *this
-  *
-  * Example: \include MatrixBase_cwiseAbs.cpp
-  * Output: \verbinclude MatrixBase_cwiseAbs.out
-  *
-  * \sa cwiseAbs2()
-  */
-EIGEN_STRONG_INLINE const CwiseUnaryOp<internal::scalar_abs_op<Scalar>, const Derived>
-cwiseAbs() const { return derived(); }
-
-/** \returns an expression of the coefficient-wise squared absolute value of \c *this
-  *
-  * Example: \include MatrixBase_cwiseAbs2.cpp
-  * Output: \verbinclude MatrixBase_cwiseAbs2.out
-  *
-  * \sa cwiseAbs()
-  */
-EIGEN_STRONG_INLINE const CwiseUnaryOp<internal::scalar_abs2_op<Scalar>, const Derived>
-cwiseAbs2() const { return derived(); }
-
-/** \returns an expression of the coefficient-wise square root of *this.
-  *
-  * Example: \include MatrixBase_cwiseSqrt.cpp
-  * Output: \verbinclude MatrixBase_cwiseSqrt.out
-  *
-  * \sa cwisePow(), cwiseSquare()
-  */
-inline const CwiseUnaryOp<internal::scalar_sqrt_op<Scalar>, const Derived>
-cwiseSqrt() const { return derived(); }
-
-/** \returns an expression of the coefficient-wise inverse of *this.
-  *
-  * Example: \include MatrixBase_cwiseInverse.cpp
-  * Output: \verbinclude MatrixBase_cwiseInverse.out
-  *
-  * \sa cwiseProduct()
-  */
-inline const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived>
-cwiseInverse() const { return derived(); }
-
-/** \returns an expression of the coefficient-wise == operator of \c *this and a scalar \a s
-  *
-  * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
-  * In order to check for equality between two vectors or matrices with floating-point coefficients, it is
-  * generally a far better idea to use a fuzzy comparison as provided by isApprox() and
-  * isMuchSmallerThan().
-  *
-  * \sa cwiseEqual(const MatrixBase<OtherDerived> &) const
-  */
-inline const CwiseUnaryOp<std::binder1st<std::equal_to<Scalar> >, const Derived>
-cwiseEqual(const Scalar& s) const
-{
-  return CwiseUnaryOp<std::binder1st<std::equal_to<Scalar> >,const Derived>
-          (derived(), std::bind1st(std::equal_to<Scalar>(), s));
-}
+// This file is included into the body of the base classes supporting matrix specific coefficient-wise functions.
+// This include MatrixBase and SparseMatrixBase.
+
+
+typedef CwiseUnaryOp<internal::scalar_abs_op<Scalar>, const Derived> CwiseAbsReturnType;
+typedef CwiseUnaryOp<internal::scalar_abs2_op<Scalar>, const Derived> CwiseAbs2ReturnType;
+typedef CwiseUnaryOp<internal::scalar_sqrt_op<Scalar>, const Derived> CwiseSqrtReturnType;
+typedef CwiseUnaryOp<internal::scalar_sign_op<Scalar>, const Derived> CwiseSignReturnType;
+typedef CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived> CwiseInverseReturnType;
+
+/// \returns an expression of the coefficient-wise absolute value of \c *this
+///
+/// Example: \include MatrixBase_cwiseAbs.cpp
+/// Output: \verbinclude MatrixBase_cwiseAbs.out
+///
+EIGEN_DOC_UNARY_ADDONS(cwiseAbs,absolute value)
+///
+/// \sa cwiseAbs2()
+///
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseAbsReturnType
+cwiseAbs() const { return CwiseAbsReturnType(derived()); }
+
+/// \returns an expression of the coefficient-wise squared absolute value of \c *this
+///
+/// Example: \include MatrixBase_cwiseAbs2.cpp
+/// Output: \verbinclude MatrixBase_cwiseAbs2.out
+///
+EIGEN_DOC_UNARY_ADDONS(cwiseAbs2,squared absolute value)
+///
+/// \sa cwiseAbs()
+///
+EIGEN_DEVICE_FUNC
+EIGEN_STRONG_INLINE const CwiseAbs2ReturnType
+cwiseAbs2() const { return CwiseAbs2ReturnType(derived()); }
+
+/// \returns an expression of the coefficient-wise square root of *this.
+///
+/// Example: \include MatrixBase_cwiseSqrt.cpp
+/// Output: \verbinclude MatrixBase_cwiseSqrt.out
+///
+EIGEN_DOC_UNARY_ADDONS(cwiseSqrt,square-root)
+///
+/// \sa cwisePow(), cwiseSquare()
+///
+EIGEN_DEVICE_FUNC
+inline const CwiseSqrtReturnType
+cwiseSqrt() const { return CwiseSqrtReturnType(derived()); }
+
+/// \returns an expression of the coefficient-wise signum of *this.
+///
+/// Example: \include MatrixBase_cwiseSign.cpp
+/// Output: \verbinclude MatrixBase_cwiseSign.out
+///
+EIGEN_DOC_UNARY_ADDONS(cwiseSign,sign function)
+///
+EIGEN_DEVICE_FUNC
+inline const CwiseSignReturnType
+cwiseSign() const { return CwiseSignReturnType(derived()); }
+
+
+/// \returns an expression of the coefficient-wise inverse of *this.
+///
+/// Example: \include MatrixBase_cwiseInverse.cpp
+/// Output: \verbinclude MatrixBase_cwiseInverse.out
+///
+EIGEN_DOC_UNARY_ADDONS(cwiseInverse,inverse)
+///
+/// \sa cwiseProduct()
+///
+EIGEN_DEVICE_FUNC
+inline const CwiseInverseReturnType
+cwiseInverse() const { return CwiseInverseReturnType(derived()); }
+
+

ADDED   3rd_party/eigen/README.md
Index: 3rd_party/eigen/README.md
==================================================================
--- 3rd_party/eigen/README.md
+++ 3rd_party/eigen/README.md
@@ -0,0 +1,3 @@
+**Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.**
+
+For more information go to http://eigen.tuxfamily.org/.

Index: 3rd_party/eigen/bench/BenchTimer.h
==================================================================
--- 3rd_party/eigen/bench/BenchTimer.h
+++ 3rd_party/eigen/bench/BenchTimer.h
@@ -20,15 +20,22 @@
 #   define WIN32_LEAN_AND_MEAN
 #   define EIGEN_BT_UNDEF_WIN32_LEAN_AND_MEAN
 # endif
 # include <windows.h>
 #elif defined(__APPLE__)
-#include <CoreServices/CoreServices.h>
 #include <mach/mach_time.h>
 #else
 # include <unistd.h>
 #endif
+
+static void escape(void *p) {
+  asm volatile("" : : "g"(p) : "memory");
+}
+
+static void clobber() {
+  asm volatile("" : : : "memory");
+}
 
 #include <Eigen/Core>
 
 namespace Eigen
 {
@@ -166,10 +173,11 @@
       TIMER.start(); \
       for(int uglyvarname2=0; uglyvarname2<REP; ++uglyvarname2){ \
         CODE; \
       } \
       TIMER.stop(); \
+      clobber(); \
     } \
   }
 
 }
 

ADDED   3rd_party/eigen/bench/analyze-blocking-sizes.cpp
Index: 3rd_party/eigen/bench/analyze-blocking-sizes.cpp
==================================================================
--- 3rd_party/eigen/bench/analyze-blocking-sizes.cpp
+++ 3rd_party/eigen/bench/analyze-blocking-sizes.cpp
@@ -0,0 +1,876 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Jacob <benoitjacob@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include <iostream>
+#include <cstdint>
+#include <cstdlib>
+#include <vector>
+#include <algorithm>
+#include <fstream>
+#include <string>
+#include <cmath>
+#include <cassert>
+#include <cstring>
+#include <memory>
+
+#include <Eigen/Core>
+
+using namespace std;
+
+const int default_precision = 4;
+
+// see --only-cubic-sizes
+bool only_cubic_sizes = false;
+
+// see --dump-tables
+bool dump_tables = false;
+
+uint8_t log2_pot(size_t x) {
+  size_t l = 0;
+  while (x >>= 1) l++;
+  return l;
+}
+
+uint16_t compact_size_triple(size_t k, size_t m, size_t n)
+{
+  return (log2_pot(k) << 8) | (log2_pot(m) << 4) | log2_pot(n);
+}
+
+// just a helper to store a triple of K,M,N sizes for matrix product
+struct size_triple_t
+{
+  uint16_t k, m, n;
+  size_triple_t() : k(0), m(0), n(0) {}
+  size_triple_t(size_t _k, size_t _m, size_t _n) : k(_k), m(_m), n(_n) {}
+  size_triple_t(const size_triple_t& o) : k(o.k), m(o.m), n(o.n) {}
+  size_triple_t(uint16_t compact)
+  {
+    k = 1 << ((compact & 0xf00) >> 8);
+    m = 1 << ((compact & 0x0f0) >> 4);
+    n = 1 << ((compact & 0x00f) >> 0);
+  }
+  bool is_cubic() const { return k == m && m == n; }
+};
+
+ostream& operator<<(ostream& s, const size_triple_t& t)
+{
+  return s << "(" << t.k << ", " << t.m << ", " << t.n << ")";
+}
+
+struct inputfile_entry_t
+{
+  uint16_t product_size;
+  uint16_t pot_block_size;
+  size_triple_t nonpot_block_size;
+  float gflops;
+};
+
+struct inputfile_t
+{
+  enum class type_t {
+    unknown,
+    all_pot_sizes,
+    default_sizes
+  };
+
+  string filename;
+  vector<inputfile_entry_t> entries;
+  type_t type;
+
+  inputfile_t(const string& fname)
+    : filename(fname)
+    , type(type_t::unknown)
+  {
+    ifstream stream(filename);
+    if (!stream.is_open()) {
+      cerr << "couldn't open input file: " << filename << endl;
+      exit(1);
+    }
+    string line;
+    while (getline(stream, line)) {
+      if (line.empty()) continue;
+      if (line.find("BEGIN MEASUREMENTS ALL POT SIZES") == 0) {
+        if (type != type_t::unknown) {
+          cerr << "Input file " << filename << " contains redundant BEGIN MEASUREMENTS lines";
+          exit(1);
+        }
+        type = type_t::all_pot_sizes;
+        continue;
+      }
+      if (line.find("BEGIN MEASUREMENTS DEFAULT SIZES") == 0) {
+        if (type != type_t::unknown) {
+          cerr << "Input file " << filename << " contains redundant BEGIN MEASUREMENTS lines";
+          exit(1);
+        }
+        type = type_t::default_sizes;
+        continue;
+      }
+      
+
+      if (type == type_t::unknown) {
+        continue;
+      }
+      switch(type) {
+        case type_t::all_pot_sizes: {
+          unsigned int product_size, block_size;
+          float gflops;
+          int sscanf_result =
+            sscanf(line.c_str(), "%x %x %f",
+                   &product_size,
+                   &block_size,
+                   &gflops);
+          if (3 != sscanf_result ||
+              !product_size ||
+              product_size > 0xfff ||
+              !block_size ||
+              block_size > 0xfff ||
+              !isfinite(gflops))
+          {
+            cerr << "ill-formed input file: " << filename << endl;
+            cerr << "offending line:" << endl << line << endl;
+            exit(1);
+          }
+          if (only_cubic_sizes && !size_triple_t(product_size).is_cubic()) {
+            continue;
+          }
+          inputfile_entry_t entry;
+          entry.product_size = uint16_t(product_size);
+          entry.pot_block_size = uint16_t(block_size);
+          entry.gflops = gflops;
+          entries.push_back(entry);
+          break;
+        }
+        case type_t::default_sizes: {
+          unsigned int product_size;
+          float gflops;
+          int bk, bm, bn;
+          int sscanf_result =
+            sscanf(line.c_str(), "%x default(%d, %d, %d) %f",
+                   &product_size,
+                   &bk, &bm, &bn,
+                   &gflops);
+          if (5 != sscanf_result ||
+              !product_size ||
+              product_size > 0xfff ||
+              !isfinite(gflops))
+          {
+            cerr << "ill-formed input file: " << filename << endl;
+            cerr << "offending line:" << endl << line << endl;
+            exit(1);
+          }
+          if (only_cubic_sizes && !size_triple_t(product_size).is_cubic()) {
+            continue;
+          }
+          inputfile_entry_t entry;
+          entry.product_size = uint16_t(product_size);
+          entry.pot_block_size = 0;
+          entry.nonpot_block_size = size_triple_t(bk, bm, bn);
+          entry.gflops = gflops;
+          entries.push_back(entry);
+          break;
+        }
+        
+        default:
+          break;
+      }
+    }
+    stream.close();
+    if (type == type_t::unknown) {
+      cerr << "Unrecognized input file " << filename << endl;
+      exit(1);
+    }
+    if (entries.empty()) {
+      cerr << "didn't find any measurements in input file: " << filename << endl;
+      exit(1);
+    }
+  }
+};
+
+struct preprocessed_inputfile_entry_t
+{
+  uint16_t product_size;
+  uint16_t block_size;
+
+  float efficiency;
+};
+
+bool lower_efficiency(const preprocessed_inputfile_entry_t& e1, const preprocessed_inputfile_entry_t& e2)
+{
+  return e1.efficiency < e2.efficiency;
+}
+
+struct preprocessed_inputfile_t
+{
+  string filename;
+  vector<preprocessed_inputfile_entry_t> entries;
+
+  preprocessed_inputfile_t(const inputfile_t& inputfile)
+    : filename(inputfile.filename)
+  {
+    if (inputfile.type != inputfile_t::type_t::all_pot_sizes) {
+      abort();
+    }
+    auto it = inputfile.entries.begin();
+    auto it_first_with_given_product_size = it;
+    while (it != inputfile.entries.end()) {
+      ++it;
+      if (it == inputfile.entries.end() ||
+        it->product_size != it_first_with_given_product_size->product_size)
+      {
+        import_input_file_range_one_product_size(it_first_with_given_product_size, it);
+        it_first_with_given_product_size = it;
+      }
+    }
+  }
+
+private:
+  void import_input_file_range_one_product_size(
+    const vector<inputfile_entry_t>::const_iterator& begin,
+    const vector<inputfile_entry_t>::const_iterator& end)
+  {
+    uint16_t product_size = begin->product_size;
+    float max_gflops = 0.0f;
+    for (auto it = begin; it != end; ++it) {
+      if (it->product_size != product_size) {
+        cerr << "Unexpected ordering of entries in " << filename << endl;
+        cerr << "(Expected all entries for product size " << hex << product_size << dec << " to be grouped)" << endl;
+        exit(1);
+      }
+      max_gflops = max(max_gflops, it->gflops);
+    }
+    for (auto it = begin; it != end; ++it) {
+      preprocessed_inputfile_entry_t entry;
+      entry.product_size = it->product_size;
+      entry.block_size = it->pot_block_size;
+      entry.efficiency = it->gflops / max_gflops;
+      entries.push_back(entry);
+    }
+  }
+};
+
+void check_all_files_in_same_exact_order(
+       const vector<preprocessed_inputfile_t>& preprocessed_inputfiles)
+{
+  if (preprocessed_inputfiles.empty()) {
+    return;
+  }
+
+  const preprocessed_inputfile_t& first_file = preprocessed_inputfiles[0];
+  const size_t num_entries = first_file.entries.size();
+
+  for (size_t i = 0; i < preprocessed_inputfiles.size(); i++) {
+    if (preprocessed_inputfiles[i].entries.size() != num_entries) {
+      cerr << "these files have different number of entries: "
+           << preprocessed_inputfiles[i].filename
+           << " and "
+           << first_file.filename
+           << endl;
+      exit(1);
+    }
+  }
+
+  for (size_t entry_index = 0; entry_index < num_entries; entry_index++) {
+    const uint16_t entry_product_size = first_file.entries[entry_index].product_size;
+    const uint16_t entry_block_size = first_file.entries[entry_index].block_size;
+    for (size_t file_index = 0; file_index < preprocessed_inputfiles.size(); file_index++) {
+      const preprocessed_inputfile_t& cur_file = preprocessed_inputfiles[file_index];
+      if (cur_file.entries[entry_index].product_size != entry_product_size ||
+          cur_file.entries[entry_index].block_size != entry_block_size)
+      {
+        cerr << "entries not in same order between these files: "
+             << first_file.filename
+             << " and "
+             << cur_file.filename
+             << endl;
+        exit(1);
+      }
+    }
+  }
+}
+
+float efficiency_of_subset(
+        const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
+        const vector<size_t>& subset)
+{
+  if (subset.size() <= 1) {
+    return 1.0f;
+  }
+  const preprocessed_inputfile_t& first_file = preprocessed_inputfiles[subset[0]];
+  const size_t num_entries = first_file.entries.size();
+  float efficiency = 1.0f;
+  size_t entry_index = 0;
+  size_t first_entry_index_with_this_product_size = 0;
+  uint16_t product_size = first_file.entries[0].product_size;
+  while (entry_index < num_entries) {
+    ++entry_index;
+    if (entry_index == num_entries ||
+        first_file.entries[entry_index].product_size != product_size)
+    {
+      float efficiency_this_product_size = 0.0f;
+      for (size_t e = first_entry_index_with_this_product_size; e < entry_index; e++) {
+        float efficiency_this_entry = 1.0f;
+        for (auto i = subset.begin(); i != subset.end(); ++i) {
+          efficiency_this_entry = min(efficiency_this_entry, preprocessed_inputfiles[*i].entries[e].efficiency);
+        }
+        efficiency_this_product_size = max(efficiency_this_product_size, efficiency_this_entry);
+      }
+      efficiency = min(efficiency, efficiency_this_product_size);
+      if (entry_index < num_entries) {
+        first_entry_index_with_this_product_size = entry_index;
+        product_size = first_file.entries[entry_index].product_size;
+      }
+    }
+  }
+
+  return efficiency;
+}
+
+void dump_table_for_subset(
+        const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
+        const vector<size_t>& subset)
+{
+  const preprocessed_inputfile_t& first_file = preprocessed_inputfiles[subset[0]];
+  const size_t num_entries = first_file.entries.size();
+  size_t entry_index = 0;
+  size_t first_entry_index_with_this_product_size = 0;
+  uint16_t product_size = first_file.entries[0].product_size;
+  size_t i = 0;
+  size_triple_t min_product_size(first_file.entries.front().product_size);
+  size_triple_t max_product_size(first_file.entries.back().product_size);
+  if (!min_product_size.is_cubic() || !max_product_size.is_cubic()) {
+    abort();
+  }
+  if (only_cubic_sizes) {
+    cerr << "Can't generate tables with --only-cubic-sizes." << endl;
+    abort();
+  }
+  cout << "struct LookupTable {" << endl;
+  cout << "  static const size_t BaseSize = " << min_product_size.k << ";" << endl;
+  const size_t NumSizes = log2_pot(max_product_size.k / min_product_size.k) + 1;
+  const size_t TableSize = NumSizes * NumSizes * NumSizes;
+  cout << "  static const size_t NumSizes = " << NumSizes << ";" << endl;
+  cout << "  static const unsigned short* Data() {" << endl;
+  cout << "    static const unsigned short data[" << TableSize << "] = {";
+  while (entry_index < num_entries) {
+    ++entry_index;
+    if (entry_index == num_entries ||
+        first_file.entries[entry_index].product_size != product_size)
+    {
+      float best_efficiency_this_product_size = 0.0f;
+      uint16_t best_block_size_this_product_size = 0;
+      for (size_t e = first_entry_index_with_this_product_size; e < entry_index; e++) {
+        float efficiency_this_entry = 1.0f;
+        for (auto i = subset.begin(); i != subset.end(); ++i) {
+          efficiency_this_entry = min(efficiency_this_entry, preprocessed_inputfiles[*i].entries[e].efficiency);
+        }
+        if (efficiency_this_entry > best_efficiency_this_product_size) {
+          best_efficiency_this_product_size = efficiency_this_entry;
+          best_block_size_this_product_size = first_file.entries[e].block_size;
+        }
+      }
+      if ((i++) % NumSizes) {
+        cout << " ";
+      } else {
+        cout << endl << "      ";
+      }
+      cout << "0x" << hex << best_block_size_this_product_size << dec;
+      if (entry_index < num_entries) {
+        cout << ",";
+        first_entry_index_with_this_product_size = entry_index;
+        product_size = first_file.entries[entry_index].product_size;
+      }
+    }
+  }
+  if (i != TableSize) {
+    cerr << endl << "Wrote " << i << " table entries, expected " << TableSize << endl;
+    abort();
+  }
+  cout << endl << "    };" << endl;
+  cout << "    return data;" << endl;
+  cout << "  }" << endl;
+  cout << "};" << endl;
+}
+
+float efficiency_of_partition(
+        const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
+        const vector<vector<size_t>>& partition)
+{
+  float efficiency = 1.0f;
+  for (auto s = partition.begin(); s != partition.end(); ++s) {
+    efficiency = min(efficiency, efficiency_of_subset(preprocessed_inputfiles, *s));
+  }
+  return efficiency;
+}
+
+void make_first_subset(size_t subset_size, vector<size_t>& out_subset, size_t set_size)
+{
+  assert(subset_size >= 1 && subset_size <= set_size);
+  out_subset.resize(subset_size);
+  for (size_t i = 0; i < subset_size; i++) {
+    out_subset[i] = i;
+  }
+}
+
+bool is_last_subset(const vector<size_t>& subset, size_t set_size)
+{
+  return subset[0] == set_size - subset.size();
+}
+
+void next_subset(vector<size_t>& inout_subset, size_t set_size)
+{
+  if (is_last_subset(inout_subset, set_size)) {
+    cerr << "iterating past the last subset" << endl;
+    abort();
+  }
+  size_t i = 1;
+  while (inout_subset[inout_subset.size() - i] == set_size - i) {
+    i++;
+    assert(i <= inout_subset.size());
+  }
+  size_t first_index_to_change = inout_subset.size() - i;
+  inout_subset[first_index_to_change]++;
+  size_t p = inout_subset[first_index_to_change];
+  for (size_t j = first_index_to_change + 1; j < inout_subset.size(); j++) {
+    inout_subset[j] = ++p;
+  }
+}
+
+const size_t number_of_subsets_limit = 100;
+const size_t always_search_subsets_of_size_at_least = 2;
+
+bool is_number_of_subsets_feasible(size_t n, size_t p)
+{ 
+  assert(n>0 && p>0 && p<=n);
+  uint64_t numerator = 1, denominator = 1;
+  for (size_t i = 0; i < p; i++) {
+    numerator *= n - i;
+    denominator *= i + 1;
+    if (numerator > denominator * number_of_subsets_limit) {
+      return false;
+    }
+  }
+  return true;
+}
+
+size_t max_feasible_subset_size(size_t n)
+{
+  assert(n > 0);
+  const size_t minresult = min<size_t>(n-1, always_search_subsets_of_size_at_least);
+  for (size_t p = 1; p <= n - 1; p++) {
+    if (!is_number_of_subsets_feasible(n, p+1)) {
+      return max(p, minresult);
+    }
+  }
+  return n - 1;
+}
+
+void find_subset_with_efficiency_higher_than(
+       const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
+       float required_efficiency_to_beat,
+       vector<size_t>& inout_remainder,
+       vector<size_t>& out_subset)
+{
+  out_subset.resize(0);
+
+  if (required_efficiency_to_beat >= 1.0f) {
+    cerr << "can't beat efficiency 1." << endl;
+    abort();
+  }
+
+  while (!inout_remainder.empty()) {
+
+    vector<size_t> candidate_indices(inout_remainder.size());
+    for (size_t i = 0; i < candidate_indices.size(); i++) {
+      candidate_indices[i] = i;
+    }
+
+    size_t candidate_indices_subset_size = max_feasible_subset_size(candidate_indices.size());
+    while (candidate_indices_subset_size >= 1) {
+      vector<size_t> candidate_indices_subset;
+      make_first_subset(candidate_indices_subset_size,
+                        candidate_indices_subset,
+                        candidate_indices.size());
+
+      vector<size_t> best_candidate_indices_subset;
+      float best_efficiency = 0.0f;
+      vector<size_t> trial_subset = out_subset;
+      trial_subset.resize(out_subset.size() + candidate_indices_subset_size);
+      while (true)
+      {
+        for (size_t i = 0; i < candidate_indices_subset_size; i++) {
+          trial_subset[out_subset.size() + i] = inout_remainder[candidate_indices_subset[i]];
+        }
+        
+        float trial_efficiency = efficiency_of_subset(preprocessed_inputfiles, trial_subset);
+        if (trial_efficiency > best_efficiency) {
+          best_efficiency = trial_efficiency;
+          best_candidate_indices_subset = candidate_indices_subset;
+        }
+        if (is_last_subset(candidate_indices_subset, candidate_indices.size())) {
+          break;
+        }
+        next_subset(candidate_indices_subset, candidate_indices.size());
+      }
+       
+      if (best_efficiency > required_efficiency_to_beat) {
+        for (size_t i = 0; i < best_candidate_indices_subset.size(); i++) {
+          candidate_indices[i] = candidate_indices[best_candidate_indices_subset[i]];
+        }
+        candidate_indices.resize(best_candidate_indices_subset.size());
+      }
+      candidate_indices_subset_size--;
+    }
+      
+    size_t candidate_index = candidate_indices[0];
+    auto candidate_iterator = inout_remainder.begin() + candidate_index;
+    vector<size_t> trial_subset = out_subset;
+
+    trial_subset.push_back(*candidate_iterator);
+    float trial_efficiency = efficiency_of_subset(preprocessed_inputfiles, trial_subset);
+    if (trial_efficiency > required_efficiency_to_beat) {
+      out_subset.push_back(*candidate_iterator);
+      inout_remainder.erase(candidate_iterator);
+    } else {
+      break;
+    }
+  }
+}
+
+void find_partition_with_efficiency_higher_than(
+       const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
+       float required_efficiency_to_beat,
+       vector<vector<size_t>>& out_partition)
+{
+  out_partition.resize(0);
+
+  vector<size_t> remainder;
+  for (size_t i = 0; i < preprocessed_inputfiles.size(); i++) {
+    remainder.push_back(i);
+  }
+
+  while (!remainder.empty()) {
+    vector<size_t> new_subset;
+    find_subset_with_efficiency_higher_than(
+      preprocessed_inputfiles,
+      required_efficiency_to_beat,
+      remainder,
+      new_subset);
+    out_partition.push_back(new_subset);
+  }
+}
+
+void print_partition(
+       const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
+       const vector<vector<size_t>>& partition)
+{
+  float efficiency = efficiency_of_partition(preprocessed_inputfiles, partition);
+  cout << "Partition into " << partition.size() << " subsets for " << efficiency * 100.0f << "% efficiency"  << endl;
+  for (auto subset = partition.begin(); subset != partition.end(); ++subset) {
+    cout << "  Subset " << (subset - partition.begin())
+         << ", efficiency " << efficiency_of_subset(preprocessed_inputfiles, *subset) * 100.0f << "%:"
+         << endl;
+    for (auto file = subset->begin(); file != subset->end(); ++file) {
+      cout << "    " << preprocessed_inputfiles[*file].filename << endl;
+    }
+    if (dump_tables) {
+      cout << "  Table:" << endl;
+      dump_table_for_subset(preprocessed_inputfiles, *subset);
+    }
+  }
+  cout << endl;
+}
+
+struct action_t
+{
+  virtual const char* invokation_name() const { abort(); return nullptr; }
+  virtual void run(const vector<string>&) const { abort(); }
+  virtual ~action_t() {}
+};
+
+struct partition_action_t : action_t
+{
+  virtual const char* invokation_name() const override { return "partition"; }
+  virtual void run(const vector<string>& input_filenames) const override
+  {
+    vector<preprocessed_inputfile_t> preprocessed_inputfiles;
+
+    if (input_filenames.empty()) {
+      cerr << "The " << invokation_name() << " action needs a list of input files." << endl;
+      exit(1);
+    }
+
+    for (auto it = input_filenames.begin(); it != input_filenames.end(); ++it) {
+      inputfile_t inputfile(*it);
+      switch (inputfile.type) {
+        case inputfile_t::type_t::all_pot_sizes:
+          preprocessed_inputfiles.emplace_back(inputfile);
+          break;
+        case inputfile_t::type_t::default_sizes:
+          cerr << "The " << invokation_name() << " action only uses measurements for all pot sizes, and "
+               << "has no use for " << *it << " which contains measurements for default sizes." << endl;
+          exit(1);
+          break;
+        default:
+          cerr << "Unrecognized input file: " << *it << endl;
+          exit(1);
+      }
+    }
+
+    check_all_files_in_same_exact_order(preprocessed_inputfiles);
+
+    float required_efficiency_to_beat = 0.0f;
+    vector<vector<vector<size_t>>> partitions;
+    cerr << "searching for partitions...\r" << flush;
+    while (true)
+    {
+      vector<vector<size_t>> partition;
+      find_partition_with_efficiency_higher_than(
+        preprocessed_inputfiles,
+        required_efficiency_to_beat,
+        partition);
+      float actual_efficiency = efficiency_of_partition(preprocessed_inputfiles, partition);
+      cerr << "partition " << preprocessed_inputfiles.size() << " files into " << partition.size()
+           << " subsets for " << 100.0f * actual_efficiency
+           << " % efficiency"
+           << "                  \r" << flush;
+      partitions.push_back(partition);
+      if (partition.size() == preprocessed_inputfiles.size() || actual_efficiency == 1.0f) {
+        break;
+      }
+      required_efficiency_to_beat = actual_efficiency;
+    }
+    cerr << "                                                                  " << endl;
+    while (true) {
+      bool repeat = false;
+      for (size_t i = 0; i < partitions.size() - 1; i++) {
+        if (partitions[i].size() >= partitions[i+1].size()) {
+          partitions.erase(partitions.begin() + i);
+          repeat = true;
+          break;
+        }
+      }
+      if (!repeat) {
+        break;
+      }
+    }
+    for (auto it = partitions.begin(); it != partitions.end(); ++it) {
+      print_partition(preprocessed_inputfiles, *it);
+    }
+  }
+};
+
+struct evaluate_defaults_action_t : action_t
+{
+  struct results_entry_t {
+    uint16_t product_size;
+    size_triple_t default_block_size;
+    uint16_t best_pot_block_size;
+    float default_gflops;
+    float best_pot_gflops;
+    float default_efficiency;
+  };
+  friend ostream& operator<<(ostream& s, const results_entry_t& entry)
+  {
+    return s
+      << "Product size " << size_triple_t(entry.product_size)
+      << ": default block size " << entry.default_block_size
+      << " -> " << entry.default_gflops
+      << " GFlop/s = " << entry.default_efficiency * 100.0f << " %"
+      << " of best POT block size " << size_triple_t(entry.best_pot_block_size)
+      << " -> " << entry.best_pot_gflops
+      << " GFlop/s" << dec;
+  }
+  static bool lower_efficiency(const results_entry_t& e1, const results_entry_t& e2) {
+    return e1.default_efficiency < e2.default_efficiency;
+  }
+  virtual const char* invokation_name() const override { return "evaluate-defaults"; }
+  void show_usage_and_exit() const
+  {
+    cerr << "usage: " << invokation_name() << " default-sizes-data all-pot-sizes-data" << endl;
+    cerr << "checks how well the performance with default sizes compares to the best "
+         << "performance measured over all POT sizes." << endl;
+    exit(1);
+  }
+  virtual void run(const vector<string>& input_filenames) const override
+  {
+    if (input_filenames.size() != 2) {
+      show_usage_and_exit();
+    }
+    inputfile_t inputfile_default_sizes(input_filenames[0]);
+    inputfile_t inputfile_all_pot_sizes(input_filenames[1]);
+    if (inputfile_default_sizes.type != inputfile_t::type_t::default_sizes) {
+      cerr << inputfile_default_sizes.filename << " is not an input file with default sizes." << endl;
+      show_usage_and_exit();
+    }
+    if (inputfile_all_pot_sizes.type != inputfile_t::type_t::all_pot_sizes) {
+      cerr << inputfile_all_pot_sizes.filename << " is not an input file with all POT sizes." << endl;
+      show_usage_and_exit();
+    }
+    vector<results_entry_t> results;
+    vector<results_entry_t> cubic_results;
+    
+    uint16_t product_size = 0;
+    auto it_all_pot_sizes = inputfile_all_pot_sizes.entries.begin();
+    for (auto it_default_sizes = inputfile_default_sizes.entries.begin();
+         it_default_sizes != inputfile_default_sizes.entries.end();
+         ++it_default_sizes)
+    {
+      if (it_default_sizes->product_size == product_size) {
+        continue;
+      }
+      product_size = it_default_sizes->product_size;
+      while (it_all_pot_sizes != inputfile_all_pot_sizes.entries.end() &&
+             it_all_pot_sizes->product_size != product_size)
+      {
+        ++it_all_pot_sizes;
+      }
+      if (it_all_pot_sizes == inputfile_all_pot_sizes.entries.end()) {
+        break;
+      }
+      uint16_t best_pot_block_size = 0;
+      float best_pot_gflops = 0;
+      for (auto it = it_all_pot_sizes;
+           it != inputfile_all_pot_sizes.entries.end() && it->product_size == product_size;
+           ++it)
+      {
+        if (it->gflops > best_pot_gflops) {
+          best_pot_gflops = it->gflops;
+          best_pot_block_size = it->pot_block_size;
+        }
+      }
+      results_entry_t entry;
+      entry.product_size = product_size;
+      entry.default_block_size = it_default_sizes->nonpot_block_size;
+      entry.best_pot_block_size = best_pot_block_size;
+      entry.default_gflops = it_default_sizes->gflops;
+      entry.best_pot_gflops = best_pot_gflops;
+      entry.default_efficiency = entry.default_gflops / entry.best_pot_gflops;
+      results.push_back(entry);
+
+      size_triple_t t(product_size);
+      if (t.k == t.m && t.m == t.n) {
+        cubic_results.push_back(entry);
+      }
+    }
+
+    cout << "All results:" << endl;
+    for (auto it = results.begin(); it != results.end(); ++it) {
+      cout << *it << endl;
+    }
+    cout << endl;
+
+    sort(results.begin(), results.end(), lower_efficiency);
+    
+    const size_t n = min<size_t>(20, results.size());
+    cout << n << " worst results:" << endl;
+    for (size_t i = 0; i < n; i++) {
+      cout << results[i] << endl;
+    }
+    cout << endl;
+
+    cout << "cubic results:" << endl;
+    for (auto it = cubic_results.begin(); it != cubic_results.end(); ++it) {
+      cout << *it << endl;
+    }
+    cout << endl;
+
+    sort(cubic_results.begin(), cubic_results.end(), lower_efficiency);
+    
+    cout.precision(2);
+    vector<float> a = {0.5f, 0.20f, 0.10f, 0.05f, 0.02f, 0.01f};
+    for (auto it = a.begin(); it != a.end(); ++it) {
+      size_t n = min(results.size() - 1, size_t(*it * results.size()));
+      cout << (100.0f * n / (results.size() - 1))
+           << " % of product sizes have default efficiency <= "
+           << 100.0f * results[n].default_efficiency << " %" << endl;
+    }
+    cout.precision(default_precision);
+  }
+};
+
+
+void show_usage_and_exit(int argc, char* argv[],
+                         const vector<unique_ptr<action_t>>& available_actions)
+{
+  cerr << "usage: " << argv[0] << " <action> [options...] <input files...>" << endl;
+  cerr << "available actions:" << endl;
+  for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
+    cerr << "  " << (*it)->invokation_name() << endl;
+  } 
+  cerr << "the input files should each contain an output of benchmark-blocking-sizes" << endl;
+  exit(1);
+}
+
+int main(int argc, char* argv[])
+{
+  cout.precision(default_precision);
+  cerr.precision(default_precision);
+
+  vector<unique_ptr<action_t>> available_actions;
+  available_actions.emplace_back(new partition_action_t);
+  available_actions.emplace_back(new evaluate_defaults_action_t);
+
+  vector<string> input_filenames;
+
+  action_t* action = nullptr;
+
+  if (argc < 2) {
+    show_usage_and_exit(argc, argv, available_actions);
+  }
+  for (int i = 1; i < argc; i++) {
+    bool arg_handled = false;
+    // Step 1. Try to match action invokation names.
+    for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
+      if (!strcmp(argv[i], (*it)->invokation_name())) {
+        if (!action) {
+          action = it->get();
+          arg_handled = true;
+          break;
+        } else {
+          cerr << "can't specify more than one action!" << endl;
+          show_usage_and_exit(argc, argv, available_actions);
+        }
+      }
+    }
+    if (arg_handled) {
+      continue;
+    }
+    // Step 2. Try to match option names.
+    if (argv[i][0] == '-') {
+      if (!strcmp(argv[i], "--only-cubic-sizes")) {
+        only_cubic_sizes = true;
+        arg_handled = true;
+      }
+      if (!strcmp(argv[i], "--dump-tables")) {
+        dump_tables = true;
+        arg_handled = true;
+      }
+      if (!arg_handled) {
+        cerr << "Unrecognized option: " << argv[i] << endl;
+        show_usage_and_exit(argc, argv, available_actions);
+      }
+    }
+    if (arg_handled) {
+      continue;
+    }
+    // Step 3. Default to interpreting args as input filenames.
+    input_filenames.emplace_back(argv[i]);
+  }
+
+  if (dump_tables && only_cubic_sizes) {
+    cerr << "Incompatible options: --only-cubic-sizes and --dump-tables." << endl;
+    show_usage_and_exit(argc, argv, available_actions);
+  }
+
+  if (!action) {
+    show_usage_and_exit(argc, argv, available_actions);
+  }
+
+  action->run(input_filenames);
+}

Index: 3rd_party/eigen/bench/benchCholesky.cpp
==================================================================
--- 3rd_party/eigen/bench/benchCholesky.cpp
+++ 3rd_party/eigen/bench/benchCholesky.cpp
@@ -29,11 +29,11 @@
 __attribute__ ((noinline)) void benchLLT(const MatrixType& m)
 {
   int rows = m.rows();
   int cols = m.cols();
 
-  int cost = 0;
+  double cost = 0;
   for (int j=0; j<rows; ++j)
   {
     int r = std::max(rows - j -1,0);
     cost += 2*(r*j+r+j);
   }
@@ -76,14 +76,14 @@
   if (MatrixType::RowsAtCompileTime==Dynamic)
     std::cout << "dyn   ";
   else
     std::cout << "fixed ";
   std::cout << covMat.rows() << " \t"
-            << (timerNoSqrt.value() * REPEAT) / repeats << "s "
-            << "(" << 1e-6 * cost*repeats/timerNoSqrt.value() << " MFLOPS)\t"
-            << (timerSqrt.value() * REPEAT) / repeats << "s "
-            << "(" << 1e-6 * cost*repeats/timerSqrt.value() << " MFLOPS)\n";
+            << (timerNoSqrt.best()) / repeats << "s "
+            << "(" << 1e-9 * cost*repeats/timerNoSqrt.best() << " GFLOPS)\t"
+            << (timerSqrt.best()) / repeats << "s "
+            << "(" << 1e-9 * cost*repeats/timerSqrt.best() << " GFLOPS)\n";
 
 
   #ifdef BENCH_GSL
   if (MatrixType::RowsAtCompileTime==Dynamic)
   {
@@ -117,17 +117,17 @@
     std::cout << acc;
 }
 
 int main(int argc, char* argv[])
 {
-  const int dynsizes[] = {4,6,8,16,24,32,49,64,128,256,512,900,0};
-  std::cout << "size            no sqrt                           standard";
+  const int dynsizes[] = {4,6,8,16,24,32,49,64,128,256,512,900,1500,0};
+  std::cout << "size            LDLT                            LLT";
 //   #ifdef BENCH_GSL
 //   std::cout << "       GSL (standard + double + ATLAS)  ";
 //   #endif
   std::cout << "\n";
-  for (uint i=0; dynsizes[i]>0; ++i)
+  for (int i=0; dynsizes[i]>0; ++i)
     benchLLT(Matrix<Scalar,Dynamic,Dynamic>(dynsizes[i],dynsizes[i]));
 
   benchLLT(Matrix<Scalar,2,2>());
   benchLLT(Matrix<Scalar,3,3>());
   benchLLT(Matrix<Scalar,4,4>());

Index: 3rd_party/eigen/bench/bench_gemm.cpp
==================================================================
--- 3rd_party/eigen/bench/bench_gemm.cpp
+++ 3rd_party/eigen/bench/bench_gemm.cpp
@@ -1,8 +1,16 @@
 
 // g++-4.4 bench_gemm.cpp -I .. -O2 -DNDEBUG -lrt -fopenmp && OMP_NUM_THREADS=2  ./a.out
 // icpc bench_gemm.cpp -I .. -O3 -DNDEBUG -lrt -openmp  && OMP_NUM_THREADS=2  ./a.out
+
+// Compilation options:
+// 
+// -DSCALAR=std::complex<double>
+// -DSCALARA=double or -DSCALARB=double
+// -DHAVE_BLAS
+// -DDECOUPLED
+//
 
 #include <iostream>
 #include <Eigen/Core>
 #include <bench/BenchTimer.h>
 
@@ -11,15 +19,23 @@
 
 #ifndef SCALAR
 // #define SCALAR std::complex<float>
 #define SCALAR float
 #endif
+
+#ifndef SCALARA
+#define SCALARA SCALAR
+#endif
+
+#ifndef SCALARB
+#define SCALARB SCALAR
+#endif
 
 typedef SCALAR Scalar;
 typedef NumTraits<Scalar>::Real RealScalar;
-typedef Matrix<RealScalar,Dynamic,Dynamic> A;
-typedef Matrix</*Real*/Scalar,Dynamic,Dynamic> B;
+typedef Matrix<SCALARA,Dynamic,Dynamic> A;
+typedef Matrix<SCALARB,Dynamic,Dynamic> B;
 typedef Matrix<Scalar,Dynamic,Dynamic> C;
 typedef Matrix<RealScalar,Dynamic,Dynamic> M;
 
 #ifdef HAVE_BLAS
 
@@ -127,39 +143,73 @@
 
   int rep = 1;    // number of repetitions per try
   int tries = 2;  // number of tries, we keep the best
 
   int s = 2048;
-  int cache_size = -1;
+  int m = s;
+  int n = s;
+  int p = s;
+  int cache_size1=-1, cache_size2=l2, cache_size3 = 0;
 
   bool need_help = false;
-  for (int i=1; i<argc; ++i)
-  {
-    if(argv[i][0]=='s')
-      s = atoi(argv[i]+1);
-    else if(argv[i][0]=='c')
-      cache_size = atoi(argv[i]+1);
-    else if(argv[i][0]=='t')
-      tries = atoi(argv[i]+1);
-    else if(argv[i][0]=='p')
-      rep = atoi(argv[i]+1);
+  for (int i=1; i<argc;)
+  {
+    if(argv[i][0]=='-')
+    {
+      if(argv[i][1]=='s')
+      {
+        ++i;
+        s = atoi(argv[i++]);
+        m = n = p = s;
+        if(argv[i][0]!='-')
+        {
+          n = atoi(argv[i++]);
+          p = atoi(argv[i++]);
+        }
+      }
+      else if(argv[i][1]=='c')
+      {
+        ++i;
+        cache_size1 = atoi(argv[i++]);
+        if(argv[i][0]!='-')
+        {
+          cache_size2 = atoi(argv[i++]);
+          if(argv[i][0]!='-')
+            cache_size3 = atoi(argv[i++]);
+        }
+      }
+      else if(argv[i][1]=='t')
+      {
+        ++i;
+        tries = atoi(argv[i++]);
+      }
+      else if(argv[i][1]=='p')
+      {
+        ++i;
+        rep = atoi(argv[i++]);
+      }
+    }
     else
+    {
       need_help = true;
+      break;
+    }
   }
 
   if(need_help)
   {
-    std::cout << argv[0] << " s<matrix size> c<cache size> t<nb tries> p<nb repeats>\n";
+    std::cout << argv[0] << " -s <matrix sizes> -c <cache sizes> -t <nb tries> -p <nb repeats>\n";
+    std::cout << "   <matrix sizes> : size\n";
+    std::cout << "   <matrix sizes> : rows columns depth\n";
     return 1;
   }
 
-  if(cache_size>0)
-    setCpuCacheSizes(cache_size,96*cache_size);
-
-  int m = s;
-  int n = s;
-  int p = s;
+#if EIGEN_VERSION_AT_LEAST(3,2,90)
+  if(cache_size1>0)
+    setCpuCacheSizes(cache_size1,cache_size2,cache_size3);
+#endif
+  
   A a(m,p); a.setRandom();
   B b(p,n); b.setRandom();
   C c(m,n); c.setOnes();
   C rc = c;
 
@@ -170,10 +220,11 @@
 
   C r = c;
 
   // check the parallel product is correct
   #if defined EIGEN_HAS_OPENMP
+  Eigen::initParallel();
   int procs = omp_get_max_threads();
   if(procs>1)
   {
     #ifdef HAVE_BLAS
     blas_gemm(a,b,r);
@@ -186,15 +237,24 @@
     if(!r.isApprox(c)) std::cerr << "Warning, your parallel product is crap!\n\n";
   }
   #elif defined HAVE_BLAS
     blas_gemm(a,b,r);
     c.noalias() += a * b;
-    if(!r.isApprox(c)) std::cerr << "Warning, your product is crap!\n\n";
+    if(!r.isApprox(c)) {
+      std::cout << r  - c << "\n";
+      std::cerr << "Warning, your product is crap!\n\n";
+    }
   #else
-    gemm(a,b,c);
-    r.noalias() += a.cast<Scalar>() * b.cast<Scalar>();
-    if(!r.isApprox(c)) std::cerr << "Warning, your product is crap!\n\n";
+    if(1.*m*n*p<2000.*2000*2000)
+    {
+      gemm(a,b,c);
+      r.noalias() += a.cast<Scalar>() .lazyProduct( b.cast<Scalar>() );
+      if(!r.isApprox(c)) {
+        std::cout << r - c << "\n";
+        std::cerr << "Warning, your product is crap!\n\n";
+      }
+    }
   #endif
 
   #ifdef HAVE_BLAS
   BenchTimer tblas;
   c = rc;
@@ -212,18 +272,27 @@
   #ifdef EIGEN_HAS_OPENMP
   if(procs>1)
   {
     BenchTimer tmono;
     omp_set_num_threads(1);
-    Eigen::internal::setNbThreads(1);
+    Eigen::setNbThreads(1);
     c = rc;
     BENCH(tmono, tries, rep, gemm(a,b,c));
     std::cout << "eigen mono cpu    " << tmono.best(CPU_TIMER)/rep  << "s  \t" << (double(m)*n*p*rep*2/tmono.best(CPU_TIMER))*1e-9  <<  " GFLOPS \t(" << tmono.total(CPU_TIMER)  << "s)\n";
     std::cout << "eigen mono real   " << tmono.best(REAL_TIMER)/rep << "s  \t" << (double(m)*n*p*rep*2/tmono.best(REAL_TIMER))*1e-9 <<  " GFLOPS \t(" << tmono.total(REAL_TIMER) << "s)\n";
     std::cout << "mt speed up x" << tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER)  << " => " << (100.0*tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER))/procs << "%\n";
   }
   #endif
+  
+  if(1.*m*n*p<30*30*30)
+  {
+      BenchTimer tmt;
+      c = rc;
+      BENCH(tmt, tries, rep, c.noalias()+=a.lazyProduct(b));
+      std::cout << "lazy cpu         " << tmt.best(CPU_TIMER)/rep  << "s  \t" << (double(m)*n*p*rep*2/tmt.best(CPU_TIMER))*1e-9  <<  " GFLOPS \t(" << tmt.total(CPU_TIMER)  << "s)\n";
+      std::cout << "lazy real        " << tmt.best(REAL_TIMER)/rep << "s  \t" << (double(m)*n*p*rep*2/tmt.best(REAL_TIMER))*1e-9 <<  " GFLOPS \t(" << tmt.total(REAL_TIMER) << "s)\n";
+  }
   
   #ifdef DECOUPLED
   if((NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
   {
     M ar(m,p); ar.setRandom();

Index: 3rd_party/eigen/bench/bench_norm.cpp
==================================================================
--- 3rd_party/eigen/bench/bench_norm.cpp
+++ 3rd_party/eigen/bench/bench_norm.cpp
@@ -4,23 +4,29 @@
 #include "BenchTimer.h"
 using namespace Eigen;
 using namespace std;
 
 template<typename T>
-EIGEN_DONT_INLINE typename T::Scalar sqsumNorm(const T& v)
+EIGEN_DONT_INLINE typename T::Scalar sqsumNorm(T& v)
 {
   return v.norm();
 }
 
 template<typename T>
-EIGEN_DONT_INLINE typename T::Scalar hypotNorm(const T& v)
+EIGEN_DONT_INLINE typename T::Scalar stableNorm(T& v)
+{
+  return v.stableNorm();
+}
+
+template<typename T>
+EIGEN_DONT_INLINE typename T::Scalar hypotNorm(T& v)
 {
   return v.hypotNorm();
 }
 
 template<typename T>
-EIGEN_DONT_INLINE typename T::Scalar blueNorm(const T& v)
+EIGEN_DONT_INLINE typename T::Scalar blueNorm(T& v)
 {
   return v.blueNorm();
 }
 
 template<typename T>
@@ -30,29 +36,29 @@
   int n = v.size();
   Scalar scale = 0;
   Scalar ssq = 1;
   for (int i=0;i<n;++i)
   {
-    Scalar ax = internal::abs(v.coeff(i));
+    Scalar ax = std::abs(v.coeff(i));
     if (scale >= ax)
     {
-      ssq += internal::abs2(ax/scale);
+      ssq += numext::abs2(ax/scale);
     }
     else
     {
-      ssq = Scalar(1) + ssq * internal::abs2(scale/ax);
+      ssq = Scalar(1) + ssq * numext::abs2(scale/ax);
       scale = ax;
     }
   }
-  return scale * internal::sqrt(ssq);
+  return scale * std::sqrt(ssq);
 }
 
 template<typename T>
 EIGEN_DONT_INLINE typename T::Scalar twopassNorm(T& v)
 {
   typedef typename T::Scalar Scalar;
-  Scalar s = v.cwise().abs().maxCoeff();
+  Scalar s = v.array().abs().maxCoeff();
   return s*(v/s).norm();
 }
 
 template<typename T>
 EIGEN_DONT_INLINE typename T::Scalar bl2passNorm(T& v)
@@ -71,20 +77,24 @@
   {
     for (int i=0;i<n;++i)
       v(i) = v(2*i) + v(2*i+1);
     n = n/2;
   }
-  return internal::sqrt(v(0));
+  return std::sqrt(v(0));
 }
 
+namespace Eigen {
+namespace internal {
 #ifdef EIGEN_VECTORIZE
-Packet4f internal::plt(const Packet4f& a, Packet4f& b) { return _mm_cmplt_ps(a,b); }
-Packet2d internal::plt(const Packet2d& a, Packet2d& b) { return _mm_cmplt_pd(a,b); }
+Packet4f plt(const Packet4f& a, Packet4f& b) { return _mm_cmplt_ps(a,b); }
+Packet2d plt(const Packet2d& a, Packet2d& b) { return _mm_cmplt_pd(a,b); }
 
-Packet4f internal::pandnot(const Packet4f& a, Packet4f& b) { return _mm_andnot_ps(a,b); }
-Packet2d internal::pandnot(const Packet2d& a, Packet2d& b) { return _mm_andnot_pd(a,b); }
+Packet4f pandnot(const Packet4f& a, Packet4f& b) { return _mm_andnot_ps(a,b); }
+Packet2d pandnot(const Packet2d& a, Packet2d& b) { return _mm_andnot_pd(a,b); }
 #endif
+}
+}
 
 template<typename T>
 EIGEN_DONT_INLINE typename T::Scalar pblueNorm(const T& v)
 {
   #ifndef EIGEN_VECTORIZE
@@ -124,25 +134,25 @@
     iexp  = - ((iemax+it)/2);
     s2m   = std::pow(ibeta,iexp);   // scaling factor for upper range
 
     overfl  = rbig*s2m;          // overfow boundary for abig
     eps     = std::pow(ibeta, 1-it);
-    relerr  = internal::sqrt(eps);      // tolerance for neglecting asml
+    relerr  = std::sqrt(eps);      // tolerance for neglecting asml
     abig    = 1.0/eps - 1.0;
     if (Scalar(nbig)>abig)  nmax = abig;  // largest safe n
     else                    nmax = nbig;
   }
 
   typedef typename internal::packet_traits<Scalar>::type Packet;
   const int ps = internal::packet_traits<Scalar>::size;
-  Packet pasml = internal::pset1(Scalar(0));
-  Packet pamed = internal::pset1(Scalar(0));
-  Packet pabig = internal::pset1(Scalar(0));
-  Packet ps2m = internal::pset1(s2m);
-  Packet ps1m = internal::pset1(s1m);
-  Packet pb2  = internal::pset1(b2);
-  Packet pb1  = internal::pset1(b1);
+  Packet pasml = internal::pset1<Packet>(Scalar(0));
+  Packet pamed = internal::pset1<Packet>(Scalar(0));
+  Packet pabig = internal::pset1<Packet>(Scalar(0));
+  Packet ps2m = internal::pset1<Packet>(s2m);
+  Packet ps1m = internal::pset1<Packet>(s1m);
+  Packet pb2  = internal::pset1<Packet>(b2);
+  Packet pb1  = internal::pset1<Packet>(b1);
   for(int j=0; j<v.size(); j+=ps)
   {
     Packet ax = internal::pabs(v.template packet<Aligned>(j));
     Packet ax_s2m = internal::pmul(ax,ps2m);
     Packet ax_s1m = internal::pmul(ax,ps1m);
@@ -168,20 +178,20 @@
   Scalar abig = internal::predux(pabig);
   Scalar asml = internal::predux(pasml);
   Scalar amed = internal::predux(pamed);
   if(abig > Scalar(0))
   {
-    abig = internal::sqrt(abig);
+    abig = std::sqrt(abig);
     if(abig > overfl)
     {
       eigen_assert(false && "overflow");
       return rbig;
     }
     if(amed > Scalar(0))
     {
       abig = abig/s2m;
-      amed = internal::sqrt(amed);
+      amed = std::sqrt(amed);
     }
     else
     {
       return abig/s2m;
     }
@@ -189,59 +199,60 @@
   }
   else if(asml > Scalar(0))
   {
     if (amed > Scalar(0))
     {
-      abig = internal::sqrt(amed);
-      amed = internal::sqrt(asml) / s1m;
+      abig = std::sqrt(amed);
+      amed = std::sqrt(asml) / s1m;
     }
     else
     {
-      return internal::sqrt(asml)/s1m;
+      return std::sqrt(asml)/s1m;
     }
   }
   else
   {
-    return internal::sqrt(amed);
+    return std::sqrt(amed);
   }
   asml = std::min(abig, amed);
   abig = std::max(abig, amed);
   if(asml <= abig*relerr)
     return abig;
   else
-    return abig * internal::sqrt(Scalar(1) + internal::abs2(asml/abig));
+    return abig * std::sqrt(Scalar(1) + numext::abs2(asml/abig));
   #endif
 }
 
 #define BENCH_PERF(NRM) { \
+  float af = 0; double ad = 0; std::complex<float> ac = 0; \
   Eigen::BenchTimer tf, td, tcf; tf.reset(); td.reset(); tcf.reset();\
   for (int k=0; k<tries; ++k) { \
     tf.start(); \
-    for (int i=0; i<iters; ++i) NRM(vf); \
+    for (int i=0; i<iters; ++i) { af += NRM(vf); } \
     tf.stop(); \
   } \
   for (int k=0; k<tries; ++k) { \
     td.start(); \
-    for (int i=0; i<iters; ++i) NRM(vd); \
+    for (int i=0; i<iters; ++i) { ad += NRM(vd); } \
     td.stop(); \
   } \
-  for (int k=0; k<std::max(1,tries/3); ++k) { \
+  /*for (int k=0; k<std::max(1,tries/3); ++k) { \
     tcf.start(); \
-    for (int i=0; i<iters; ++i) NRM(vcf); \
+    for (int i=0; i<iters; ++i) { ac += NRM(vcf); } \
     tcf.stop(); \
-  } \
+  } */\
   std::cout << #NRM << "\t" << tf.value() << "   " << td.value() <<  "    " << tcf.value() << "\n"; \
 }
 
 void check_accuracy(double basef, double based, int s)
 {
-  double yf = basef * internal::abs(internal::random<double>());
-  double yd = based * internal::abs(internal::random<double>());
+  double yf = basef * std::abs(internal::random<double>());
+  double yd = based * std::abs(internal::random<double>());
   VectorXf vf = VectorXf::Ones(s) * yf;
   VectorXd vd = VectorXd::Ones(s) * yd;
 
-  std::cout << "reference\t" << internal::sqrt(double(s))*yf << "\t" << internal::sqrt(double(s))*yd << "\n";
+  std::cout << "reference\t" << std::sqrt(double(s))*yf << "\t" << std::sqrt(double(s))*yd << "\n";
   std::cout << "sqsumNorm\t" << sqsumNorm(vf) << "\t" << sqsumNorm(vd) << "\n";
   std::cout << "hypotNorm\t" << hypotNorm(vf) << "\t" << hypotNorm(vd) << "\n";
   std::cout << "blueNorm\t" << blueNorm(vf) << "\t" << blueNorm(vd) << "\n";
   std::cout << "pblueNorm\t" << pblueNorm(vf) << "\t" << pblueNorm(vd) << "\n";
   std::cout << "lapackNorm\t" << lapackNorm(vf) << "\t" << lapackNorm(vd) << "\n";
@@ -253,12 +264,12 @@
 {
   VectorXf vf(s);
   VectorXd vd(s);
   for (int i=0; i<s; ++i)
   {
-    vf[i] = internal::abs(internal::random<double>()) * std::pow(double(10), internal::random<int>(ef0,ef1));
-    vd[i] = internal::abs(internal::random<double>()) * std::pow(double(10), internal::random<int>(ed0,ed1));
+    vf[i] = std::abs(internal::random<double>()) * std::pow(double(10), internal::random<int>(ef0,ef1));
+    vd[i] = std::abs(internal::random<double>()) * std::pow(double(10), internal::random<int>(ed0,ed1));
   }
 
   //std::cout << "reference\t" << internal::sqrt(double(s))*yf << "\t" << internal::sqrt(double(s))*yd << "\n";
   std::cout << "sqsumNorm\t"  << sqsumNorm(vf)  << "\t" << sqsumNorm(vd)  << "\t" << sqsumNorm(vf.cast<long double>()) << "\t" << sqsumNorm(vd.cast<long double>()) << "\n";
   std::cout << "hypotNorm\t"  << hypotNorm(vf)  << "\t" << hypotNorm(vd)  << "\t" << hypotNorm(vf.cast<long double>()) << "\t" << hypotNorm(vd.cast<long double>()) << "\n";
@@ -310,36 +321,40 @@
   {
     check_accuracy_var(-27,20,-302,-190,s);
     std::cout << "\n";
   }
 
+  y = 1;
   std::cout.precision(4);
-  std::cerr << "Performance (out of cache):\n";
+  int s1 = 1024*1024*32;
+  std::cerr << "Performance (out of cache, " << s1 << "):\n";
   {
     int iters = 1;
-    VectorXf vf = VectorXf::Random(1024*1024*32) * y;
-    VectorXd vd = VectorXd::Random(1024*1024*32) * y;
-    VectorXcf vcf = VectorXcf::Random(1024*1024*32) * y;
+    VectorXf vf = VectorXf::Random(s1) * y;
+    VectorXd vd = VectorXd::Random(s1) * y;
+    VectorXcf vcf = VectorXcf::Random(s1) * y;
     BENCH_PERF(sqsumNorm);
+    BENCH_PERF(stableNorm);
     BENCH_PERF(blueNorm);
-//     BENCH_PERF(pblueNorm);
-//     BENCH_PERF(lapackNorm);
-//     BENCH_PERF(hypotNorm);
-//     BENCH_PERF(twopassNorm);
+    BENCH_PERF(pblueNorm);
+    BENCH_PERF(lapackNorm);
+    BENCH_PERF(hypotNorm);
+    BENCH_PERF(twopassNorm);
     BENCH_PERF(bl2passNorm);
   }
 
-  std::cerr << "\nPerformance (in cache):\n";
+  std::cerr << "\nPerformance (in cache, " << 512 << "):\n";
   {
     int iters = 100000;
     VectorXf vf = VectorXf::Random(512) * y;
     VectorXd vd = VectorXd::Random(512) * y;
     VectorXcf vcf = VectorXcf::Random(512) * y;
     BENCH_PERF(sqsumNorm);
+    BENCH_PERF(stableNorm);
     BENCH_PERF(blueNorm);
-//     BENCH_PERF(pblueNorm);
-//     BENCH_PERF(lapackNorm);
-//     BENCH_PERF(hypotNorm);
-//     BENCH_PERF(twopassNorm);
+    BENCH_PERF(pblueNorm);
+    BENCH_PERF(lapackNorm);
+    BENCH_PERF(hypotNorm);
+    BENCH_PERF(twopassNorm);
     BENCH_PERF(bl2passNorm);
   }
 }

ADDED   3rd_party/eigen/bench/benchmark-blocking-sizes.cpp
Index: 3rd_party/eigen/bench/benchmark-blocking-sizes.cpp
==================================================================
--- 3rd_party/eigen/bench/benchmark-blocking-sizes.cpp
+++ 3rd_party/eigen/bench/benchmark-blocking-sizes.cpp
@@ -0,0 +1,677 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Jacob <benoitjacob@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include <iostream>
+#include <cstdint>
+#include <cstdlib>
+#include <vector>
+#include <fstream>
+#include <memory>
+#include <cstdio>
+
+bool eigen_use_specific_block_size;
+int eigen_block_size_k, eigen_block_size_m, eigen_block_size_n;
+#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZES eigen_use_specific_block_size
+#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_K eigen_block_size_k
+#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_M eigen_block_size_m
+#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_N eigen_block_size_n
+#include <Eigen/Core>
+
+#include <bench/BenchTimer.h>
+
+using namespace Eigen;
+using namespace std;
+
+static BenchTimer timer;
+
+// how many times we repeat each measurement.
+// measurements are randomly shuffled - we're not doing
+// all N identical measurements in a row.
+const int measurement_repetitions = 3;
+
+// Timings below this value are too short to be accurate,
+// we'll repeat measurements with more iterations until
+// we get a timing above that threshold.
+const float min_accurate_time = 1e-2f;
+
+// See --min-working-set-size command line parameter.
+size_t min_working_set_size = 0;
+
+float max_clock_speed = 0.0f;
+
+// range of sizes that we will benchmark (in all 3 K,M,N dimensions)
+const size_t maxsize = 2048;
+const size_t minsize = 16;
+
+typedef MatrixXf MatrixType;
+typedef MatrixType::Scalar Scalar;
+typedef internal::packet_traits<Scalar>::type Packet;
+
+static_assert((maxsize & (maxsize - 1)) == 0, "maxsize must be a power of two");
+static_assert((minsize & (minsize - 1)) == 0, "minsize must be a power of two");
+static_assert(maxsize > minsize, "maxsize must be larger than minsize");
+static_assert(maxsize < (minsize << 16), "maxsize must be less than (minsize<<16)");
+
+// just a helper to store a triple of K,M,N sizes for matrix product
+struct size_triple_t
+{
+  size_t k, m, n;
+  size_triple_t() : k(0), m(0), n(0) {}
+  size_triple_t(size_t _k, size_t _m, size_t _n) : k(_k), m(_m), n(_n) {}
+  size_triple_t(const size_triple_t& o) : k(o.k), m(o.m), n(o.n) {}
+  size_triple_t(uint16_t compact)
+  {
+    k = 1 << ((compact & 0xf00) >> 8);
+    m = 1 << ((compact & 0x0f0) >> 4);
+    n = 1 << ((compact & 0x00f) >> 0);
+  }
+};
+
+uint8_t log2_pot(size_t x) {
+  size_t l = 0;
+  while (x >>= 1) l++;
+  return l;
+}
+
+// Convert between size tripes and a compact form fitting in 12 bits
+// where each size, which must be a POT, is encoded as its log2, on 4 bits
+// so the largest representable size is 2^15 == 32k  ... big enough.
+uint16_t compact_size_triple(size_t k, size_t m, size_t n)
+{
+  return (log2_pot(k) << 8) | (log2_pot(m) << 4) | log2_pot(n);
+}
+
+uint16_t compact_size_triple(const size_triple_t& t)
+{
+  return compact_size_triple(t.k, t.m, t.n);
+}
+
+// A single benchmark. Initially only contains benchmark params.
+// Then call run(), which stores the result in the gflops field.
+struct benchmark_t
+{
+  uint16_t compact_product_size;
+  uint16_t compact_block_size;
+  bool use_default_block_size;
+  float gflops;
+  benchmark_t()
+    : compact_product_size(0)
+    , compact_block_size(0)
+    , use_default_block_size(false)
+    , gflops(0)
+  {
+  }
+  benchmark_t(size_t pk, size_t pm, size_t pn,
+              size_t bk, size_t bm, size_t bn)
+    : compact_product_size(compact_size_triple(pk, pm, pn))
+    , compact_block_size(compact_size_triple(bk, bm, bn))
+    , use_default_block_size(false)
+    , gflops(0)
+  {}
+  benchmark_t(size_t pk, size_t pm, size_t pn)
+    : compact_product_size(compact_size_triple(pk, pm, pn))
+    , compact_block_size(0)
+    , use_default_block_size(true)
+    , gflops(0)
+  {}
+
+  void run();
+};
+
+ostream& operator<<(ostream& s, const benchmark_t& b)
+{
+  s << hex << b.compact_product_size << dec;
+  if (b.use_default_block_size) {
+    size_triple_t t(b.compact_product_size);
+    Index k = t.k, m = t.m, n = t.n;
+    internal::computeProductBlockingSizes<Scalar, Scalar>(k, m, n);
+    s << " default(" << k << ", " << m << ", " << n << ")";
+  } else {
+    s << " " << hex << b.compact_block_size << dec;
+  }
+  s << " " << b.gflops;
+  return s;
+}
+
+// We sort first by increasing benchmark parameters,
+// then by decreasing performance.
+bool operator<(const benchmark_t& b1, const benchmark_t& b2)
+{ 
+  return b1.compact_product_size < b2.compact_product_size ||
+           (b1.compact_product_size == b2.compact_product_size && (
+             (b1.compact_block_size < b2.compact_block_size || (
+               b1.compact_block_size == b2.compact_block_size &&
+                 b1.gflops > b2.gflops))));
+}
+
+void benchmark_t::run()
+{
+  size_triple_t productsizes(compact_product_size);
+
+  if (use_default_block_size) {
+    eigen_use_specific_block_size = false;
+  } else {
+    // feed eigen with our custom blocking params
+    eigen_use_specific_block_size = true;
+    size_triple_t blocksizes(compact_block_size);
+    eigen_block_size_k = blocksizes.k;
+    eigen_block_size_m = blocksizes.m;
+    eigen_block_size_n = blocksizes.n;
+  }
+
+  // set up the matrix pool
+
+  const size_t combined_three_matrices_sizes =
+    sizeof(Scalar) *
+      (productsizes.k * productsizes.m +
+       productsizes.k * productsizes.n +
+       productsizes.m * productsizes.n);
+
+  // 64 M is large enough that nobody has a cache bigger than that,
+  // while still being small enough that everybody has this much RAM,
+  // so conveniently we don't need to special-case platforms here.
+  const size_t unlikely_large_cache_size = 64 << 20;
+
+  const size_t working_set_size =
+    min_working_set_size ? min_working_set_size : unlikely_large_cache_size;
+
+  const size_t matrix_pool_size =
+    1 + working_set_size / combined_three_matrices_sizes;
+
+  MatrixType *lhs = new MatrixType[matrix_pool_size];
+  MatrixType *rhs = new MatrixType[matrix_pool_size];
+  MatrixType *dst = new MatrixType[matrix_pool_size];
+  
+  for (size_t i = 0; i < matrix_pool_size; i++) {
+    lhs[i] = MatrixType::Zero(productsizes.m, productsizes.k);
+    rhs[i] = MatrixType::Zero(productsizes.k, productsizes.n);
+    dst[i] = MatrixType::Zero(productsizes.m, productsizes.n);
+  }
+
+  // main benchmark loop
+
+  int iters_at_a_time = 1;
+  float time_per_iter = 0.0f;
+  size_t matrix_index = 0;
+  while (true) {
+
+    double starttime = timer.getCpuTime();
+    for (int i = 0; i < iters_at_a_time; i++) {
+      dst[matrix_index].noalias() = lhs[matrix_index] * rhs[matrix_index];
+      matrix_index++;
+      if (matrix_index == matrix_pool_size) {
+        matrix_index = 0;
+      }
+    }
+    double endtime = timer.getCpuTime();
+
+    const float timing = float(endtime - starttime);
+
+    if (timing >= min_accurate_time) {
+      time_per_iter = timing / iters_at_a_time;
+      break;
+    }
+
+    iters_at_a_time *= 2;
+  }
+
+  delete[] lhs;
+  delete[] rhs;
+  delete[] dst;
+
+  gflops = 2e-9 * productsizes.k * productsizes.m * productsizes.n / time_per_iter;
+}
+
+void print_cpuinfo()
+{
+#ifdef __linux__
+  cout << "contents of /proc/cpuinfo:" << endl;
+  string line;
+  ifstream cpuinfo("/proc/cpuinfo");
+  if (cpuinfo.is_open()) {
+    while (getline(cpuinfo, line)) {
+      cout << line << endl;
+    }
+    cpuinfo.close();
+  }
+  cout << endl;
+#elif defined __APPLE__
+  cout << "output of sysctl hw:" << endl;
+  system("sysctl hw");
+  cout << endl;
+#endif
+}
+
+template <typename T>
+string type_name()
+{
+  return "unknown";
+}
+
+template<>
+string type_name<float>()
+{
+  return "float";
+}
+
+template<>
+string type_name<double>()
+{
+  return "double";
+}
+
+struct action_t
+{
+  virtual const char* invokation_name() const { abort(); return nullptr; }
+  virtual void run() const { abort(); }
+  virtual ~action_t() {}
+};
+
+void show_usage_and_exit(int /*argc*/, char* argv[],
+                         const vector<unique_ptr<action_t>>& available_actions)
+{
+  cerr << "usage: " << argv[0] << " <action> [options...]" << endl << endl;
+  cerr << "available actions:" << endl << endl;
+  for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
+    cerr << "  " << (*it)->invokation_name() << endl;
+  }
+  cerr << endl;
+  cerr << "options:" << endl << endl;
+  cerr << "  --min-working-set-size=N:" << endl;
+  cerr << "       Set the minimum working set size to N bytes." << endl;
+  cerr << "       This is rounded up as needed to a multiple of matrix size." << endl;
+  cerr << "       A larger working set lowers the chance of a warm cache." << endl;
+  cerr << "       The default value 0 means use a large enough working" << endl;
+  cerr << "       set to likely outsize caches." << endl;
+  cerr << "       A value of 1 (that is, 1 byte) would mean don't do anything to" << endl;
+  cerr << "       avoid warm caches." << endl;
+  exit(1);
+}
+     
+float measure_clock_speed()
+{
+  cerr << "Measuring clock speed...                              \r" << flush;
+          
+  vector<float> all_gflops;
+  for (int i = 0; i < 8; i++) {
+    benchmark_t b(1024, 1024, 1024);
+    b.run();
+    all_gflops.push_back(b.gflops);
+  }
+
+  sort(all_gflops.begin(), all_gflops.end());
+  float stable_estimate = all_gflops[2] + all_gflops[3] + all_gflops[4] + all_gflops[5];
+
+  // multiply by an arbitrary constant to discourage trying doing anything with the
+  // returned values besides just comparing them with each other.
+  float result = stable_estimate * 123.456f;
+
+  return result;
+}
+
+struct human_duration_t
+{
+  int seconds;
+  human_duration_t(int s) : seconds(s) {}
+};
+
+ostream& operator<<(ostream& s, const human_duration_t& d)
+{
+  int remainder = d.seconds;
+  if (remainder > 3600) {
+    int hours = remainder / 3600;
+    s << hours << " h ";
+    remainder -= hours * 3600;
+  }
+  if (remainder > 60) {
+    int minutes = remainder / 60;
+    s << minutes << " min ";
+    remainder -= minutes * 60;
+  }
+  if (d.seconds < 600) {
+    s << remainder << " s";
+  }
+  return s;
+}
+
+const char session_filename[] = "/data/local/tmp/benchmark-blocking-sizes-session.data";
+
+void serialize_benchmarks(const char* filename, const vector<benchmark_t>& benchmarks, size_t first_benchmark_to_run)
+{
+  FILE* file = fopen(filename, "w");
+  if (!file) {
+    cerr << "Could not open file " << filename << " for writing." << endl;
+    cerr << "Do you have write permissions on the current working directory?" << endl;
+    exit(1);
+  }
+  size_t benchmarks_vector_size = benchmarks.size();
+  fwrite(&max_clock_speed, sizeof(max_clock_speed), 1, file);
+  fwrite(&benchmarks_vector_size, sizeof(benchmarks_vector_size), 1, file);
+  fwrite(&first_benchmark_to_run, sizeof(first_benchmark_to_run), 1, file);
+  fwrite(benchmarks.data(), sizeof(benchmark_t), benchmarks.size(), file);
+  fclose(file);
+}
+
+bool deserialize_benchmarks(const char* filename, vector<benchmark_t>& benchmarks, size_t& first_benchmark_to_run)
+{
+  FILE* file = fopen(filename, "r");
+  if (!file) {
+    return false;
+  }
+  if (1 != fread(&max_clock_speed, sizeof(max_clock_speed), 1, file)) {
+    return false;
+  }
+  size_t benchmarks_vector_size = 0;
+  if (1 != fread(&benchmarks_vector_size, sizeof(benchmarks_vector_size), 1, file)) {
+    return false;
+  }
+  if (1 != fread(&first_benchmark_to_run, sizeof(first_benchmark_to_run), 1, file)) {
+    return false;
+  }
+  benchmarks.resize(benchmarks_vector_size);
+  if (benchmarks.size() != fread(benchmarks.data(), sizeof(benchmark_t), benchmarks.size(), file)) {
+    return false;
+  }
+  unlink(filename);
+  return true;
+}
+
+void try_run_some_benchmarks(
+  vector<benchmark_t>& benchmarks,
+  double time_start,
+  size_t& first_benchmark_to_run)
+{
+  if (first_benchmark_to_run == benchmarks.size()) {
+    return;
+  }
+
+  double time_last_progress_update = 0;
+  double time_last_clock_speed_measurement = 0;
+  double time_now = 0;
+
+  size_t benchmark_index = first_benchmark_to_run;
+
+  while (true) {
+    float ratio_done = float(benchmark_index) / benchmarks.size();
+    time_now = timer.getRealTime();
+
+    // We check clock speed every minute and at the end.
+    if (benchmark_index == benchmarks.size() ||
+        time_now > time_last_clock_speed_measurement + 60.0f)
+    {
+      time_last_clock_speed_measurement = time_now;
+
+      // Ensure that clock speed is as expected
+      float current_clock_speed = measure_clock_speed();
+
+      // The tolerance needs to be smaller than the relative difference between
+      // clock speeds that a device could operate under.
+      // It seems unlikely that a device would be throttling clock speeds by
+      // amounts smaller than 2%.
+      // With a value of 1%, I was getting within noise on a Sandy Bridge.
+      const float clock_speed_tolerance = 0.02f;
+
+      if (current_clock_speed > (1 + clock_speed_tolerance) * max_clock_speed) {
+        // Clock speed is now higher than we previously measured.
+        // Either our initial measurement was inaccurate, which won't happen
+        // too many times as we are keeping the best clock speed value and
+        // and allowing some tolerance; or something really weird happened,
+        // which invalidates all benchmark results collected so far.
+        // Either way, we better restart all over again now.
+        if (benchmark_index) {
+          cerr << "Restarting at " << 100.0f * ratio_done
+               << " % because clock speed increased.          " << endl;
+        }
+        max_clock_speed = current_clock_speed;
+        first_benchmark_to_run = 0;
+        return;
+      }
+
+      bool rerun_last_tests = false;
+
+      if (current_clock_speed < (1 - clock_speed_tolerance) * max_clock_speed) {
+        cerr << "Measurements completed so far: "
+             << 100.0f * ratio_done
+             << " %                             " << endl;
+        cerr << "Clock speed seems to be only "
+             << current_clock_speed/max_clock_speed
+             << " times what it used to be." << endl;
+
+        unsigned int seconds_to_sleep_if_lower_clock_speed = 1;
+
+        while (current_clock_speed < (1 - clock_speed_tolerance) * max_clock_speed) {
+          if (seconds_to_sleep_if_lower_clock_speed > 32) {
+            cerr << "Sleeping longer probably won't make a difference." << endl;
+            cerr << "Serializing benchmarks to " << session_filename << endl;
+            serialize_benchmarks(session_filename, benchmarks, first_benchmark_to_run);
+            cerr << "Now restart this benchmark, and it should pick up where we left." << endl;
+            exit(2);
+          }
+          rerun_last_tests = true;
+          cerr << "Sleeping "
+               << seconds_to_sleep_if_lower_clock_speed
+               << " s...                                   \r" << endl;
+          sleep(seconds_to_sleep_if_lower_clock_speed);
+          current_clock_speed = measure_clock_speed();
+          seconds_to_sleep_if_lower_clock_speed *= 2;
+        }
+      }
+
+      if (rerun_last_tests) {
+        cerr << "Redoing the last "
+             << 100.0f * float(benchmark_index - first_benchmark_to_run) / benchmarks.size()
+             << " % because clock speed had been low.   " << endl;
+        return;
+      }
+
+      // nothing wrong with the clock speed so far, so there won't be a need to rerun
+      // benchmarks run so far in case we later encounter a lower clock speed.
+      first_benchmark_to_run = benchmark_index;
+    }
+
+    if (benchmark_index == benchmarks.size()) {
+      // We're done!
+      first_benchmark_to_run = benchmarks.size();
+      // Erase progress info
+      cerr << "                                                            " << endl;
+      return;
+    }
+
+    // Display progress info on stderr
+    if (time_now > time_last_progress_update + 1.0f) {
+      time_last_progress_update = time_now;
+      cerr << "Measurements... " << 100.0f * ratio_done
+           << " %, ETA "
+           << human_duration_t(float(time_now - time_start) * (1.0f - ratio_done) / ratio_done)
+           << "                          \r" << flush;
+    }
+
+    // This is where we actually run a benchmark!
+    benchmarks[benchmark_index].run();
+    benchmark_index++;
+  }
+}
+
+void run_benchmarks(vector<benchmark_t>& benchmarks)
+{
+  size_t first_benchmark_to_run;
+  vector<benchmark_t> deserialized_benchmarks;
+  bool use_deserialized_benchmarks = false;
+  if (deserialize_benchmarks(session_filename, deserialized_benchmarks, first_benchmark_to_run)) {
+    cerr << "Found serialized session with "
+         << 100.0f * first_benchmark_to_run / deserialized_benchmarks.size()
+         << " % already done" << endl;
+    if (deserialized_benchmarks.size() == benchmarks.size() &&
+        first_benchmark_to_run > 0 &&
+        first_benchmark_to_run < benchmarks.size())
+    {
+      use_deserialized_benchmarks = true;
+    }
+  }
+
+  if (use_deserialized_benchmarks) {
+    benchmarks = deserialized_benchmarks;
+  } else {
+    // not using deserialized benchmarks, starting from scratch
+    first_benchmark_to_run = 0;
+
+    // Randomly shuffling benchmarks allows us to get accurate enough progress info,
+    // as now the cheap/expensive benchmarks are randomly mixed so they average out.
+    // It also means that if data is corrupted for some time span, the odds are that
+    // not all repetitions of a given benchmark will be corrupted.
+    random_shuffle(benchmarks.begin(), benchmarks.end());
+  }
+
+  for (int i = 0; i < 4; i++) {
+    max_clock_speed = max(max_clock_speed, measure_clock_speed());
+  }
+  
+  double time_start = 0.0;
+  while (first_benchmark_to_run < benchmarks.size()) {
+    if (first_benchmark_to_run == 0) {
+      time_start = timer.getRealTime();
+    }
+    try_run_some_benchmarks(benchmarks,
+                            time_start,
+                            first_benchmark_to_run);
+  }
+
+  // Sort timings by increasing benchmark parameters, and decreasing gflops.
+  // The latter is very important. It means that we can ignore all but the first
+  // benchmark with given parameters.
+  sort(benchmarks.begin(), benchmarks.end());
+
+  // Collect best (i.e. now first) results for each parameter values.
+  vector<benchmark_t> best_benchmarks;
+  for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
+    if (best_benchmarks.empty() ||
+        best_benchmarks.back().compact_product_size != it->compact_product_size ||
+        best_benchmarks.back().compact_block_size != it->compact_block_size)
+    {
+      best_benchmarks.push_back(*it);
+    }
+  }
+
+  // keep and return only the best benchmarks
+  benchmarks = best_benchmarks;
+}
+
+struct measure_all_pot_sizes_action_t : action_t
+{
+  virtual const char* invokation_name() const { return "all-pot-sizes"; }
+  virtual void run() const
+  {
+    vector<benchmark_t> benchmarks;
+    for (int repetition = 0; repetition < measurement_repetitions; repetition++) {
+      for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) {
+        for (size_t msize = minsize; msize <= maxsize; msize *= 2) {
+          for (size_t nsize = minsize; nsize <= maxsize; nsize *= 2) {
+            for (size_t kblock = minsize; kblock <= ksize; kblock *= 2) {
+              for (size_t mblock = minsize; mblock <= msize; mblock *= 2) {
+                for (size_t nblock = minsize; nblock <= nsize; nblock *= 2) {
+                  benchmarks.emplace_back(ksize, msize, nsize, kblock, mblock, nblock);
+                }
+              }
+            }
+          }
+        }
+      }
+    }
+
+    run_benchmarks(benchmarks);
+
+    cout << "BEGIN MEASUREMENTS ALL POT SIZES" << endl;
+    for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
+      cout << *it << endl;
+    }
+  }
+};
+
+struct measure_default_sizes_action_t : action_t
+{
+  virtual const char* invokation_name() const { return "default-sizes"; }
+  virtual void run() const
+  {
+    vector<benchmark_t> benchmarks;
+    for (int repetition = 0; repetition < measurement_repetitions; repetition++) {
+      for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) {
+        for (size_t msize = minsize; msize <= maxsize; msize *= 2) {
+          for (size_t nsize = minsize; nsize <= maxsize; nsize *= 2) {
+            benchmarks.emplace_back(ksize, msize, nsize);
+          }
+        }
+      }
+    }
+
+    run_benchmarks(benchmarks);
+
+    cout << "BEGIN MEASUREMENTS DEFAULT SIZES" << endl;
+    for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
+      cout << *it << endl;
+    }
+  }
+};
+
+int main(int argc, char* argv[])
+{
+  double time_start = timer.getRealTime();
+  cout.precision(4);
+  cerr.precision(4);
+
+  vector<unique_ptr<action_t>> available_actions;
+  available_actions.emplace_back(new measure_all_pot_sizes_action_t);
+  available_actions.emplace_back(new measure_default_sizes_action_t);
+
+  auto action = available_actions.end();
+
+  if (argc <= 1) {
+    show_usage_and_exit(argc, argv, available_actions);
+  }
+  for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
+    if (!strcmp(argv[1], (*it)->invokation_name())) {
+      action = it;
+      break;
+    }
+  }
+
+  if (action == available_actions.end()) {
+    show_usage_and_exit(argc, argv, available_actions);
+  }
+
+  for (int i = 2; i < argc; i++) {
+    if (argv[i] == strstr(argv[i], "--min-working-set-size=")) {
+      const char* equals_sign = strchr(argv[i], '=');
+      min_working_set_size = strtoul(equals_sign+1, nullptr, 10);
+    } else {
+      cerr << "unrecognized option: " << argv[i] << endl << endl;
+      show_usage_and_exit(argc, argv, available_actions);
+    }
+  }
+
+  print_cpuinfo();
+
+  cout << "benchmark parameters:" << endl;
+  cout << "pointer size: " << 8*sizeof(void*) << " bits" << endl;
+  cout << "scalar type: " << type_name<Scalar>() << endl;
+  cout << "packet size: " << internal::packet_traits<MatrixType::Scalar>::size << endl;
+  cout << "minsize = " << minsize << endl;
+  cout << "maxsize = " << maxsize << endl;
+  cout << "measurement_repetitions = " << measurement_repetitions << endl;
+  cout << "min_accurate_time = " << min_accurate_time << endl;
+  cout << "min_working_set_size = " << min_working_set_size;
+  if (min_working_set_size == 0) {
+    cout << " (try to outsize caches)";
+  }
+  cout << endl << endl;
+
+  (*action)->run();
+
+  double time_end = timer.getRealTime();
+  cerr << "Finished in " << human_duration_t(time_end - time_start) << endl;
+}

Index: 3rd_party/eigen/bench/btl/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/bench/btl/CMakeLists.txt
+++ 3rd_party/eigen/bench/btl/CMakeLists.txt
@@ -9,33 +9,28 @@
 
 SET(CMAKE_INCLUDE_CURRENT_DIR ON)
 
 string(REGEX MATCH icpc IS_ICPC ${CMAKE_CXX_COMPILER})
 IF(CMAKE_COMPILER_IS_GNUCXX OR IS_ICPC)
-  SET(CMAKE_CXX_FLAGS "-g0 -O3 -DNDEBUG")
-  SET(CMAKE_Fortran_FLAGS "-g0 -O3 -DNDEBUG")
-  IF(NOT BTL_NOVEC)
-    SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse2")
-    SET(CMAKE_Fortran_FLAGS "${CMAKE_Fortran_FLAGS} -msse2")
-  ELSE(NOT BTL_NOVEC)
+  SET(CMAKE_CXX_FLAGS "-g0 -O3 -DNDEBUG ${CMAKE_CXX_FLAGS}")
+  SET(CMAKE_Fortran_FLAGS "-g0 -O3 -DNDEBUG ${CMAKE_Fortran_FLAGS}")
+  IF(BTL_NOVEC)
     SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DEIGEN_DONT_VECTORIZE")
-  ENDIF(NOT BTL_NOVEC)
+  ENDIF(BTL_NOVEC)
 ENDIF(CMAKE_COMPILER_IS_GNUCXX OR IS_ICPC)
 
 IF(MSVC)
   SET(CMAKE_CXX_FLAGS " /O2 /Ot /GL /fp:fast -DNDEBUG")
 #   SET(CMAKE_Fortran_FLAGS "-g0 -O3 -DNDEBUG")
-  IF(NOT BTL_NOVEC)
-    SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:SSE2")
-  ELSE(NOT BTL_NOVEC)
+  IF(BTL_NOVEC)
     SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DEIGEN_DONT_VECTORIZE")
-  ENDIF(NOT BTL_NOVEC)
+  ENDIF(BTL_NOVEC)
 ENDIF(MSVC)
 
 if(IS_ICPC)
-  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fast")
-  set(CMAKE_Fortran_FLAGS "${CMAKE_Fortran_FLAGS} -fast")
+  set(CMAKE_CXX_FLAGS "-fast ${CMAKE_CXX_FLAGS}")
+  set(CMAKE_Fortran_FLAGS "-fast ${CMAKE_Fortran_FLAGS}")
 endif(IS_ICPC)
 
 include_directories(
   ${PROJECT_SOURCE_DIR}/actions
   ${PROJECT_SOURCE_DIR}/generic_bench
@@ -45,10 +40,16 @@
 # find_package(MKL)
 # if (MKL_FOUND)
 #   add_definitions(-DHAVE_MKL)
 #   set(DEFAULT_LIBRARIES ${MKL_LIBRARIES})
 # endif (MKL_FOUND)
+
+find_library(EIGEN_BTL_RT_LIBRARY rt)
+# if we cannot find it easily, then we don't need it!
+if(NOT EIGEN_BTL_RT_LIBRARY)
+  set(EIGEN_BTL_RT_LIBRARY "")
+endif()
 
 MACRO(BTL_ADD_BENCH targetname)
 
   foreach(_current_var ${ARGN})
     set(_last_var ${_current_var})
@@ -68,11 +69,11 @@
   OPTION(BUILD_${targetname} "Build benchmark ${targetname}" ${_last_var})
 
   IF(BUILD_${targetname})
     ADD_EXECUTABLE(${targetname} ${_sources})
     ADD_TEST(${targetname} "${targetname}")
-    target_link_libraries(${targetname} ${DEFAULT_LIBRARIES} rt)
+    target_link_libraries(${targetname} ${DEFAULT_LIBRARIES} ${EIGEN_BTL_RT_LIBRARY})
   ENDIF(BUILD_${targetname})
 
 ENDMACRO(BTL_ADD_BENCH)
 
 macro(btl_add_target_property target prop value)
@@ -89,16 +90,18 @@
 
 ENABLE_TESTING()
 
 add_subdirectory(libs/eigen3)
 add_subdirectory(libs/eigen2)
+add_subdirectory(libs/tensors)
 add_subdirectory(libs/BLAS)
 add_subdirectory(libs/ublas)
 add_subdirectory(libs/gmm)
 add_subdirectory(libs/mtl4)
 add_subdirectory(libs/blitz)
 add_subdirectory(libs/tvmet)
 add_subdirectory(libs/STL)
+add_subdirectory(libs/blaze)
 
 add_subdirectory(data)
 
 

Index: 3rd_party/eigen/bench/btl/actions/action_axpby.hh
==================================================================
--- 3rd_party/eigen/bench/btl/actions/action_axpby.hh
+++ 3rd_party/eigen/bench/btl/actions/action_axpby.hh
@@ -31,11 +31,11 @@
 class Action_axpby {
 
 public :
 
   // Ctor
-  Action_axpby( int size ):_size(size),_alpha(0.5),_beta(0.95)
+  Action_axpby( int size ):_alpha(0.5),_beta(0.95),_size(size)
   {
     MESSAGE("Action_axpby Ctor");
 
     // STL vector initialization
     init_vector<pseudo_random>(X_stl,_size);

Index: 3rd_party/eigen/bench/btl/actions/action_axpy.hh
==================================================================
--- 3rd_party/eigen/bench/btl/actions/action_axpy.hh
+++ 3rd_party/eigen/bench/btl/actions/action_axpy.hh
@@ -33,11 +33,11 @@
 
 public :
 
   // Ctor
 
-  Action_axpy( int size ):_size(size),_coef(1.0)
+  Action_axpy( int size ):_coef(1.0),_size(size)
   {
     MESSAGE("Action_axpy Ctor");
 
     // STL vector initialization
 

Index: 3rd_party/eigen/bench/btl/cmake/FindACML.cmake
==================================================================
--- 3rd_party/eigen/bench/btl/cmake/FindACML.cmake
+++ 3rd_party/eigen/bench/btl/cmake/FindACML.cmake
@@ -15,10 +15,11 @@
 find_file(ACML_LIBRARIES
   NAMES
   libacml_mp.so
   PATHS
   /usr/lib
+  /usr/lib64
   $ENV{ACMLDIR}/lib
   ${LIB_INSTALL_DIR}
 )
 
 if(NOT ACML_LIBRARIES)
@@ -33,10 +34,11 @@
         )
     find_file(ACML_LIBRARIES
         libacml.so libacml_mv.so
         PATHS
         /usr/lib
+        /usr/lib64
         $ENV{ACMLDIR}/lib
         ${LIB_INSTALL_DIR}
         )
 endif()
 

Index: 3rd_party/eigen/bench/btl/cmake/FindATLAS.cmake
==================================================================
--- 3rd_party/eigen/bench/btl/cmake/FindATLAS.cmake
+++ 3rd_party/eigen/bench/btl/cmake/FindATLAS.cmake
@@ -1,39 +1,31 @@
 
 if (ATLAS_LIBRARIES)
   set(ATLAS_FIND_QUIETLY TRUE)
 endif (ATLAS_LIBRARIES)
 
-find_file(ATLAS_LIB libatlas.so.3 PATHS /usr/lib $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
-find_library(ATLAS_LIB atlas PATHS $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
-
-find_file(ATLAS_CBLAS libcblas.so.3 PATHS /usr/lib $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
-find_library(ATLAS_CBLAS cblas PATHS $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
-
-find_file(ATLAS_LAPACK liblapack_atlas.so.3 PATHS /usr/lib $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
-find_library(ATLAS_LAPACK lapack_atlas PATHS $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
-
-if(NOT ATLAS_LAPACK)
-  find_file(ATLAS_LAPACK liblapack.so.3 PATHS /usr/lib/atlas $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
-  find_library(ATLAS_LAPACK lapack PATHS $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
-endif(NOT ATLAS_LAPACK)
-
-find_file(ATLAS_F77BLAS libf77blas.so.3 PATHS /usr/lib $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
+find_file(ATLAS_LIB libatlas.so.3 PATHS /usr/lib /usr/lib/atlas /usr/lib64 /usr/lib64/atlas $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
+find_library(ATLAS_LIB satlas PATHS $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
+
+find_file(ATLAS_LAPACK NAMES liblapack_atlas.so.3 liblapack.so.3 PATHS /usr/lib /usr/lib/atlas /usr/lib64 /usr/lib64/atlas $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
+find_library(ATLAS_LAPACK NAMES lapack_atlas lapack PATHS $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
+
+find_file(ATLAS_F77BLAS libf77blas.so.3 PATHS /usr/lib /usr/lib/atlas /usr/lib64 /usr/lib64/atlas $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
 find_library(ATLAS_F77BLAS f77blas PATHS $ENV{ATLASDIR} ${LIB_INSTALL_DIR})
 
 if(ATLAS_LIB AND ATLAS_CBLAS AND ATLAS_LAPACK AND ATLAS_F77BLAS)
 
-  set(ATLAS_LIBRARIES ${ATLAS_LAPACK} ${ATLAS_CBLAS}  ${ATLAS_F77BLAS} ${ATLAS_LIB})
+  set(ATLAS_LIBRARIES ${ATLAS_LAPACK}  ${ATLAS_LIB})
   
   # search the default lapack lib link to it
   find_file(ATLAS_REFERENCE_LAPACK liblapack.so.3 PATHS /usr/lib /usr/lib64)
   find_library(ATLAS_REFERENCE_LAPACK NAMES lapack)
-  if(ATLAS_REFERENCE_LAPACK)
-    set(ATLAS_LIBRARIES ${ATLAS_LIBRARIES} ${ATLAS_REFERENCE_LAPACK})
-  endif()
+#   if(ATLAS_REFERENCE_LAPACK)
+#     set(ATLAS_LIBRARIES ${ATLAS_LIBRARIES} ${ATLAS_REFERENCE_LAPACK})
+#   endif()
   
 endif(ATLAS_LIB AND ATLAS_CBLAS AND ATLAS_LAPACK AND ATLAS_F77BLAS)
 
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(ATLAS DEFAULT_MSG ATLAS_LIBRARIES)
 
 mark_as_advanced(ATLAS_LIBRARIES)

ADDED   3rd_party/eigen/bench/btl/cmake/FindBLAZE.cmake
Index: 3rd_party/eigen/bench/btl/cmake/FindBLAZE.cmake
==================================================================
--- 3rd_party/eigen/bench/btl/cmake/FindBLAZE.cmake
+++ 3rd_party/eigen/bench/btl/cmake/FindBLAZE.cmake
@@ -0,0 +1,31 @@
+# - Try to find eigen2 headers
+# Once done this will define
+#
+#  BLAZE_FOUND - system has blaze lib
+#  BLAZE_INCLUDE_DIR - the blaze include directory
+#
+# Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+# Adapted from FindEigen.cmake:
+# Copyright (c) 2006, 2007 Montel Laurent, <montel@kde.org>
+# Redistribution and use is allowed according to the terms of the BSD license.
+# For details see the accompanying COPYING-CMAKE-SCRIPTS file.
+
+if (BLAZE_INCLUDE_DIR)
+
+  # in cache already
+  set(BLAZE_FOUND TRUE)
+
+else (BLAZE_INCLUDE_DIR)
+
+find_path(BLAZE_INCLUDE_DIR NAMES blaze/Blaze.h
+     PATHS
+     ${INCLUDE_INSTALL_DIR}
+   )
+
+include(FindPackageHandleStandardArgs)
+find_package_handle_standard_args(BLAZE DEFAULT_MSG BLAZE_INCLUDE_DIR)
+
+mark_as_advanced(BLAZE_INCLUDE_DIR)
+
+endif(BLAZE_INCLUDE_DIR)
+

Index: 3rd_party/eigen/bench/btl/cmake/FindCBLAS.cmake
==================================================================
--- 3rd_party/eigen/bench/btl/cmake/FindCBLAS.cmake
+++ 3rd_party/eigen/bench/btl/cmake/FindCBLAS.cmake
@@ -21,14 +21,15 @@
 
 find_file(CBLAS_LIBRARIES
   libcblas.so.3
   PATHS
   /usr/lib
+  /usr/lib64
   $ENV{CBLASDIR}/lib
   ${LIB_INSTALL_DIR}
 )
 
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(CBLAS DEFAULT_MSG
                                   CBLAS_INCLUDES CBLAS_LIBRARIES)
 
 mark_as_advanced(CBLAS_INCLUDES CBLAS_LIBRARIES)

DELETED 3rd_party/eigen/bench/btl/cmake/FindGOTO.cmake
Index: 3rd_party/eigen/bench/btl/cmake/FindGOTO.cmake
==================================================================
--- 3rd_party/eigen/bench/btl/cmake/FindGOTO.cmake
+++ 3rd_party/eigen/bench/btl/cmake/FindGOTO.cmake
@@ -1,15 +0,0 @@
-
-if (GOTO_LIBRARIES)
-  set(GOTO_FIND_QUIETLY TRUE)
-endif (GOTO_LIBRARIES)
-
-find_library(GOTO_LIBRARIES goto PATHS $ENV{GOTODIR} ${LIB_INSTALL_DIR})
-
-if(GOTO_LIBRARIES AND CMAKE_COMPILER_IS_GNUCXX)
-  set(GOTO_LIBRARIES ${GOTO_LIBRARIES} "-lpthread -lgfortran")
-endif()
-
-include(FindPackageHandleStandardArgs)
-find_package_handle_standard_args(GOTO DEFAULT_MSG GOTO_LIBRARIES)
-
-mark_as_advanced(GOTO_LIBRARIES)

DELETED 3rd_party/eigen/bench/btl/cmake/FindGOTO2.cmake
Index: 3rd_party/eigen/bench/btl/cmake/FindGOTO2.cmake
==================================================================
--- 3rd_party/eigen/bench/btl/cmake/FindGOTO2.cmake
+++ 3rd_party/eigen/bench/btl/cmake/FindGOTO2.cmake
@@ -1,25 +0,0 @@
-
-if (GOTO2_LIBRARIES)
-  set(GOTO2_FIND_QUIETLY TRUE)
-endif (GOTO2_LIBRARIES)
-# 
-# find_path(GOTO_INCLUDES
-#   NAMES
-#   cblas.h
-#   PATHS
-#   $ENV{GOTODIR}/include
-#   ${INCLUDE_INSTALL_DIR}
-# )
-
-find_file(GOTO2_LIBRARIES libgoto2.so PATHS /usr/lib $ENV{GOTO2DIR} ${LIB_INSTALL_DIR})
-find_library(GOTO2_LIBRARIES goto2 PATHS $ENV{GOTO2DIR} ${LIB_INSTALL_DIR})
-
-if(GOTO2_LIBRARIES AND CMAKE_COMPILER_IS_GNUCXX)
-  set(GOTO2_LIBRARIES ${GOTO2_LIBRARIES} "-lpthread -lgfortran")
-endif()
-
-include(FindPackageHandleStandardArgs)
-find_package_handle_standard_args(GOTO2 DEFAULT_MSG
-                                  GOTO2_LIBRARIES)
-
-mark_as_advanced(GOTO2_LIBRARIES)

ADDED   3rd_party/eigen/bench/btl/cmake/FindOPENBLAS.cmake
Index: 3rd_party/eigen/bench/btl/cmake/FindOPENBLAS.cmake
==================================================================
--- 3rd_party/eigen/bench/btl/cmake/FindOPENBLAS.cmake
+++ 3rd_party/eigen/bench/btl/cmake/FindOPENBLAS.cmake
@@ -0,0 +1,17 @@
+
+if (OPENBLAS_LIBRARIES)
+  set(OPENBLAS_FIND_QUIETLY TRUE)
+endif (OPENBLAS_LIBRARIES)
+
+find_file(OPENBLAS_LIBRARIES NAMES libopenblas.so libopenblas.so.0 PATHS /usr/lib /usr/lib64 $ENV{OPENBLASDIR} ${LIB_INSTALL_DIR})
+find_library(OPENBLAS_LIBRARIES openblas PATHS $ENV{OPENBLASDIR} ${LIB_INSTALL_DIR})
+
+if(OPENBLAS_LIBRARIES AND CMAKE_COMPILER_IS_GNUCXX)
+  set(OPENBLAS_LIBRARIES ${OPENBLAS_LIBRARIES} "-lpthread -lgfortran")
+endif()
+
+include(FindPackageHandleStandardArgs)
+find_package_handle_standard_args(OPENBLAS DEFAULT_MSG
+                                  OPENBLAS_LIBRARIES)
+
+mark_as_advanced(OPENBLAS_LIBRARIES)

Index: 3rd_party/eigen/bench/btl/data/action_settings.txt
==================================================================
--- 3rd_party/eigen/bench/btl/data/action_settings.txt
+++ 3rd_party/eigen/bench/btl/data/action_settings.txt
@@ -1,19 +1,19 @@
-aat ; "{/*1.5 A x A^T}" ; "matrix size" ; 4:3000
-ata ; "{/*1.5 A^T x A}" ; "matrix size" ; 4:3000
-atv ; "{/*1.5 matrix^T x vector}" ; "matrix size" ; 4:3000
+aat ; "{/*1.5 A x A^T}" ; "matrix size" ; 4:5000
+ata ; "{/*1.5 A^T x A}" ; "matrix size" ; 4:5000
+atv ; "{/*1.5 matrix^T x vector}" ; "matrix size" ; 4:5000
 axpby ; "{/*1.5 Y = alpha X + beta Y}" ; "vector size" ; 5:1000000
 axpy ; "{/*1.5 Y += alpha X}" ; "vector size" ; 5:1000000
-matrix_matrix ; "{/*1.5 matrix matrix product}" ; "matrix size" ; 4:3000
-matrix_vector ; "{/*1.5 matrix vector product}" ; "matrix size" ; 4:3000
-trmm ; "{/*1.5 triangular matrix matrix product}" ; "matrix size" ; 4:3000
-trisolve_vector ; "{/*1.5 triangular solver - vector (X = inv(L) X)}" ; "size" ; 4:3000
-trisolve_matrix ; "{/*1.5 triangular solver - matrix (M = inv(L) M)}" ; "size" ; 4:3000
-cholesky ; "{/*1.5 Cholesky decomposition}" ; "matrix size" ; 4:3000
-complete_lu_decomp ; "{/*1.5 Complete LU decomposition}" ; "matrix size" ; 4:3000
-partial_lu_decomp ; "{/*1.5 Partial LU decomposition}" ; "matrix size" ; 4:3000
-tridiagonalization ; "{/*1.5 Tridiagonalization}" ; "matrix size" ; 4:3000
-hessenberg ; "{/*1.5 Hessenberg decomposition}" ; "matrix size" ; 4:3000
-symv ; "{/*1.5 symmetric matrix vector product}" ; "matrix size" ; 4:3000
-syr2 ; "{/*1.5 symmretric rank-2 update (A += u^T v + u v^T)}" ; "matrix size" ; 4:3000
-ger ; "{/*1.5 general rank-1 update (A += u v^T)}" ; "matrix size" ; 4:3000
+matrix_matrix ; "{/*1.5 matrix matrix product}" ; "matrix size" ; 4:5000
+matrix_vector ; "{/*1.5 matrix vector product}" ; "matrix size" ; 4:5000
+trmm ; "{/*1.5 triangular matrix matrix product}" ; "matrix size" ; 4:5000
+trisolve_vector ; "{/*1.5 triangular solver - vector (X = inv(L) X)}" ; "size" ; 4:5000
+trisolve_matrix ; "{/*1.5 triangular solver - matrix (M = inv(L) M)}" ; "size" ; 4:5000
+cholesky ; "{/*1.5 Cholesky decomposition}" ; "matrix size" ; 4:5000
+complete_lu_decomp ; "{/*1.5 Complete LU decomposition}" ; "matrix size" ; 4:5000
+partial_lu_decomp ; "{/*1.5 Partial LU decomposition}" ; "matrix size" ; 4:5000
+tridiagonalization ; "{/*1.5 Tridiagonalization}" ; "matrix size" ; 4:5000
+hessenberg ; "{/*1.5 Hessenberg decomposition}" ; "matrix size" ; 4:5000
+symv ; "{/*1.5 symmetric matrix vector product}" ; "matrix size" ; 4:5000
+syr2 ; "{/*1.5 symmretric rank-2 update (A += u^T v + u v^T)}" ; "matrix size" ; 4:5000
+ger ; "{/*1.5 general rank-1 update (A += u v^T)}" ; "matrix size" ; 4:5000
 rot ; "{/*1.5 apply rotation in the plane}" ; "vector size" ; 4:1000000

Index: 3rd_party/eigen/bench/btl/data/perlib_plot_settings.txt
==================================================================
--- 3rd_party/eigen/bench/btl/data/perlib_plot_settings.txt
+++ 3rd_party/eigen/bench/btl/data/perlib_plot_settings.txt
@@ -8,9 +8,9 @@
 gmm ;             with lines lw 3 lt 1 lc rgbcolor "#0000ff"
 ublas ;           with lines lw 3 lt 1 lc rgbcolor "#00b7ff"
 mtl4 ;            with lines lw 3 lt 1 lc rgbcolor "#d18847"
 blitz ;           with lines lw 3 lt 1 lc rgbcolor "#ff00ff"
 F77 ;             with lines lw 3 lt 3 lc rgbcolor "#e6e64c"
-GOTO ;            with lines lw 3 lt 3 lc rgbcolor "#C05600"
-GOTO2 ;           with lines lw 3 lt 1 lc rgbcolor "#C05600"
+OPENBLAS ;        with lines lw 3 lt 1 lc rgbcolor "#C05600"
 C ;               with lines lw 3 lt 3 lc rgbcolor "#e6bd96"
 ACML ;            with lines lw 2 lt 3 lc rgbcolor "#e6e64c"
+blaze ;           with lines lw 3 lt 1 lc rgbcolor "#ff00ff"

Index: 3rd_party/eigen/bench/btl/generic_bench/bench.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/bench.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/bench.hh
@@ -100,12 +100,12 @@
     if (hasOldResults)
     {
       // merge the two data
       std::vector<int> newSizes;
       std::vector<double> newFlops;
-      int i=0;
-      int j=0;
+      unsigned int i=0;
+      unsigned int j=0;
       while (i<tab_sizes.size() && j<oldSizes.size())
       {
         if (tab_sizes[i] == oldSizes[j])
         {
           newSizes.push_back(tab_sizes[i]);

Index: 3rd_party/eigen/bench/btl/generic_bench/bench_parameter.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/bench_parameter.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/bench_parameter.hh
@@ -27,15 +27,15 @@
 // nb of point on bench curves
 #define NB_POINT 100
 // min vector size for axpy bench
 #define MIN_AXPY 5
 // max vector size for axpy bench
-#define MAX_AXPY 1000000
+#define MAX_AXPY 3000000
 // min matrix size for matrix vector product bench
 #define MIN_MV 5
 // max matrix size for matrix vector product bench
-#define MAX_MV 3000
+#define MAX_MV 5000
 // min matrix size for matrix matrix product bench
 #define MIN_MM 5
 // max matrix size for matrix matrix product bench
 #define MAX_MM MAX_MV
 // min matrix size for LU bench

Index: 3rd_party/eigen/bench/btl/generic_bench/btl.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/btl.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/btl.hh
@@ -42,19 +42,14 @@
 #define BTL_ASM_COMMENT(X)  asm("#" X)
 #else
 #define BTL_ASM_COMMENT(X)
 #endif
 
-#if (defined __GNUC__) && (!defined __INTEL_COMPILER) && !defined(__arm__) && !defined(__powerpc__)
-#define BTL_DISABLE_SSE_EXCEPTIONS()  { \
-  int aux; \
-  asm( \
-  "stmxcsr   %[aux]           \n\t" \
-  "orl       $32832, %[aux]   \n\t" \
-  "ldmxcsr   %[aux]           \n\t" \
-  : : [aux] "m" (aux)); \
-}
+#ifdef __SSE__
+#include "xmmintrin.h"
+// This enables flush to zero (FTZ) and denormals are zero (DAZ) modes:
+#define BTL_DISABLE_SSE_EXCEPTIONS()  { _mm_setcsr(_mm_getcsr() | 0x8040); }
 #else
 #define BTL_DISABLE_SSE_EXCEPTIONS()
 #endif
 
 /** Enhanced std::string
@@ -174,11 +169,11 @@
     char * _config;
     _config = getenv ("BTL_CONFIG");
     if (_config!=NULL)
     {
       std::vector<BtlString> config = BtlString(_config).split(" \t\n");
-      for (int i = 0; i<config.size(); i++)
+      for (unsigned int i = 0; i<config.size(); i++)
       {
         if (config[i].beginsWith("-a"))
         {
           if (i+1==config.size())
           {
@@ -222,11 +217,11 @@
   {
     if (Instance.m_selectedActionNames.empty())
       return false;
 
     BtlString name(_name);
-    for (int i=0; i<Instance.m_selectedActionNames.size(); ++i)
+    for (unsigned int i=0; i<Instance.m_selectedActionNames.size(); ++i)
       if (name.contains(Instance.m_selectedActionNames[i]))
         return false;
 
     return true;
   }

Index: 3rd_party/eigen/bench/btl/generic_bench/init/init_function.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/init/init_function.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/init/init_function.hh
@@ -28,27 +28,27 @@
 double simple_function(int index_i, int index_j)
 {
   return index_i+index_j;
 }
 
-double pseudo_random(int index)
+double pseudo_random(int /*index*/)
 {
   return std::rand()/double(RAND_MAX);
 }
 
-double pseudo_random(int index_i, int index_j)
+double pseudo_random(int /*index_i*/, int /*index_j*/)
 {
   return std::rand()/double(RAND_MAX);
 }
 
 
-double null_function(int index)
+double null_function(int /*index*/)
 {
   return 0.0;
 }
 
-double null_function(int index_i, int index_j)
+double null_function(int /*index_i*/, int /*index_j*/)
 {
   return 0.0;
 }
 
 #endif

Index: 3rd_party/eigen/bench/btl/generic_bench/init/init_matrix.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/init/init_matrix.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/init/init_matrix.hh
@@ -27,11 +27,11 @@
 template<double init_function(int,int), class Vector>
 BTL_DONT_INLINE void init_row(Vector & X, int size, int row){
 
   X.resize(size);
 
-  for (int j=0;j<X.size();j++){
+  for (unsigned int j=0;j<X.size();j++){
     X[j]=typename Vector::value_type(init_function(row,j));
   }
 }
 
 
@@ -40,25 +40,25 @@
 //            resize() method
 //            [] operator for setting rows
 template<double init_function(int,int),class Vector>
 BTL_DONT_INLINE void init_matrix(Vector &  A, int size){
   A.resize(size);
-  for (int row=0; row<A.size() ; row++){
+  for (unsigned int row=0; row<A.size() ; row++){
     init_row<init_function>(A[row],size,row);
   }
 }
 
 template<double init_function(int,int),class Matrix>
 BTL_DONT_INLINE void init_matrix_symm(Matrix&  A, int size){
   A.resize(size);
-  for (int row=0; row<A.size() ; row++)
+  for (unsigned int row=0; row<A.size() ; row++)
     A[row].resize(size);
-  for (int row=0; row<A.size() ; row++){
+  for (unsigned int row=0; row<A.size() ; row++){
     A[row][row] = init_function(row,row);
-    for (int col=0; col<row ; col++){
+    for (unsigned int col=0; col<row ; col++){
       double x = init_function(row,col);
       A[row][col] = A[col][row] = x;
     }
   }
 }
 
 #endif

Index: 3rd_party/eigen/bench/btl/generic_bench/init/init_vector.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/init/init_vector.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/init/init_vector.hh
@@ -27,11 +27,11 @@
 template<double init_function(int), class Vector>
 void init_vector(Vector & X, int size){
 
   X.resize(size);
 
-  for (int i=0;i<X.size();i++){
+  for (unsigned int i=0;i<X.size();i++){
     X[i]=typename Vector::value_type(init_function(i));
   }
 }
 
 #endif

Index: 3rd_party/eigen/bench/btl/generic_bench/timers/portable_perf_analyzer.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/timers/portable_perf_analyzer.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/timers/portable_perf_analyzer.hh
@@ -76,11 +76,11 @@
   BTL_DONT_INLINE double time_calculate(Action & action)
   {
     // time measurement
     action.calculate();
     _chronos.start();
-    for (int ii=0;ii<_nb_calc;ii++)
+    for (unsigned int ii=0;ii<_nb_calc;ii++)
     {
       action.calculate();
     }
     _chronos.stop();
     return _chronos.user_time();

Index: 3rd_party/eigen/bench/btl/generic_bench/timers/portable_timer.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/timers/portable_timer.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/timers/portable_timer.hh
@@ -32,11 +32,11 @@
 
 
 //  timer  -------------------------------------------------------------------//
 
 //  A timer object measures CPU time.
-#ifdef _MSC_VER
+#if defined(_MSC_VER)
 
 #define NOMINMAX
 #include <windows.h>
 
 /*#ifndef hr_timer
@@ -85,10 +85,52 @@
    LARGE_INTEGER frequency;
 
 
  }; // Portable_Timer
 
+#elif defined(__APPLE__)
+#include <CoreServices/CoreServices.h>
+#include <mach/mach_time.h>
+
+
+class Portable_Timer
+{
+ public:
+
+  Portable_Timer()
+  {
+  }
+
+  void start()
+  {
+    m_start_time = double(mach_absolute_time())*1e-9;;
+
+  }
+
+  void stop()
+  {
+    m_stop_time = double(mach_absolute_time())*1e-9;;
+
+  }
+
+  double elapsed()
+  {
+    return  user_time();
+  }
+
+  double user_time()
+  {
+    return m_stop_time - m_start_time;
+  }
+
+
+private:
+
+  double m_stop_time, m_start_time;
+
+}; // Portable_Timer (Apple)
+
 #else
 
 #include <sys/time.h>
 #include <sys/resource.h>
 #include <unistd.h>
@@ -136,10 +178,10 @@
 private:
 
   int m_clkid;
   double m_stop_time, m_start_time;
 
-}; // Portable_Timer
+}; // Portable_Timer (Linux)
 
 #endif
 
 #endif  // PORTABLE_TIMER_HPP

Index: 3rd_party/eigen/bench/btl/generic_bench/utils/size_lin_log.hh
==================================================================
--- 3rd_party/eigen/bench/btl/generic_bench/utils/size_lin_log.hh
+++ 3rd_party/eigen/bench/btl/generic_bench/utils/size_lin_log.hh
@@ -21,11 +21,11 @@
 #define SIZE_LIN_LOG
 
 #include "size_log.hh"
 
 template<class Vector>
-void size_lin_log(const int nb_point, const int size_min, const int size_max, Vector & X)
+void size_lin_log(const int nb_point, const int /*size_min*/, const int size_max, Vector & X)
 {
   int ten=10;
   int nine=9;
 
   X.resize(nb_point);

Index: 3rd_party/eigen/bench/btl/libs/BLAS/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/bench/btl/libs/BLAS/CMakeLists.txt
+++ 3rd_party/eigen/bench/btl/libs/BLAS/CMakeLists.txt
@@ -16,31 +16,18 @@
     set_target_properties(btl_mkl PROPERTIES COMPILE_FLAGS "-DCBLASNAME=INTEL_MKL -DHAS_LAPACK=1")
   endif(BUILD_btl_mkl)
 endif (MKL_FOUND)
 
 
-find_package(GOTO2)
-if (GOTO2_FOUND)
-  btl_add_bench(btl_goto2 main.cpp)
-  if(BUILD_btl_goto2)
-    target_link_libraries(btl_goto2 ${GOTO_LIBRARIES} )
-    set_target_properties(btl_goto2 PROPERTIES COMPILE_FLAGS "-DCBLASNAME=GOTO2")
-  endif(BUILD_btl_goto2)
-endif (GOTO2_FOUND)
-
-find_package(GOTO)
-if (GOTO_FOUND)
-  if(GOTO2_FOUND)
-    btl_add_bench(btl_goto main.cpp OFF)
-  else()
-    btl_add_bench(btl_goto main.cpp)
-  endif()
-  if(BUILD_btl_goto)
-    target_link_libraries(btl_goto ${GOTO_LIBRARIES} )
-    set_target_properties(btl_goto PROPERTIES COMPILE_FLAGS "-DCBLASNAME=GOTO")
-  endif(BUILD_btl_goto)
-endif (GOTO_FOUND)
+find_package(OPENBLAS)
+if (OPENBLAS_FOUND)
+  btl_add_bench(btl_openblas main.cpp)
+  if(BUILD_btl_openblas)
+    target_link_libraries(btl_openblas ${OPENBLAS_LIBRARIES} )
+    set_target_properties(btl_openblas PROPERTIES COMPILE_FLAGS "-DCBLASNAME=OPENBLAS")
+  endif(BUILD_btl_openblas)
+endif (OPENBLAS_FOUND)
 
 find_package(ACML)
 if (ACML_FOUND)
   btl_add_bench(btl_acml main.cpp)
   if(BUILD_btl_acml)

Index: 3rd_party/eigen/bench/btl/libs/BLAS/blas_interface_impl.hh
==================================================================
--- 3rd_party/eigen/bench/btl/libs/BLAS/blas_interface_impl.hh
+++ 3rd_party/eigen/bench/btl/libs/BLAS/blas_interface_impl.hh
@@ -73,11 +73,10 @@
   }
 
   static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
     int N2 = N*N;
     BLAS_FUNC(copy)(&N2, X, &intone, C, &intone);
-    char uplo = 'L';
     int info = 0;
     int * ipiv = (int*)alloca(sizeof(int)*N);
     BLAS_FUNC(getrf)(&N, &N, C, &N, ipiv, &info);
     if(info!=0) std::cerr << "getrf_ error " << info << "\n";
   }
@@ -90,20 +89,19 @@
   static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix & X, int N){
     BLAS_FUNC(copy)(&N, B, &intone, X, &intone);
     BLAS_FUNC(trsm)(&right, &lower, &notrans, &nonunit, &N, &N, &fone, L, &N, X, &N);
   }
 
-  static inline void trmm(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){
+  static inline void trmm(gene_matrix & A, gene_matrix & B, gene_matrix & /*X*/, int N){
     BLAS_FUNC(trmm)(&left, &lower, &notrans,&nonunit, &N,&N,&fone,A,&N,B,&N);
   }
 
   #ifdef HAS_LAPACK
 
   static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
     int N2 = N*N;
     BLAS_FUNC(copy)(&N2, X, &intone, C, &intone);
-    char uplo = 'L';
     int info = 0;
     int * ipiv = (int*)alloca(sizeof(int)*N);
     int * jpiv = (int*)alloca(sizeof(int)*N);
     BLAS_FUNC(getc2)(&N, C, &N, ipiv, jpiv, &info);
   }
@@ -132,12 +130,10 @@
       int inc = 1;
       BLAS_FUNC(copy)(&N2, X, &inc, C, &inc);
     }
     char uplo = 'U';
     int info = 0;
-    int ilo = 1;
-    int ihi = N;
     int bsize = 64;
     int worksize = N*bsize;
     SCALAR* d = new SCALAR[3*N+worksize];
     BLAS_FUNC(sytrd)(&uplo, &N, C, &N, d, d+N, d+2*N, d+3*N, &worksize, &info);
     delete[] d;

Index: 3rd_party/eigen/bench/btl/libs/BLAS/c_interface_base.h
==================================================================
--- 3rd_party/eigen/bench/btl/libs/BLAS/c_interface_base.h
+++ 3rd_party/eigen/bench/btl/libs/BLAS/c_interface_base.h
@@ -15,16 +15,16 @@
   typedef std::vector<stl_vector >  stl_matrix;
 
   typedef real* gene_matrix;
   typedef real* gene_vector;
 
-  static void free_matrix(gene_matrix & A, int N){
-    delete A;
+  static void free_matrix(gene_matrix & A, int /*N*/){
+    delete[] A;
   }
 
   static void free_vector(gene_vector & B){
-    delete B;
+    delete[] B;
   }
 
   static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
     int N = A_stl.size();
     A = new real[N*N];

Index: 3rd_party/eigen/bench/btl/libs/BLAS/main.cpp
==================================================================
--- 3rd_party/eigen/bench/btl/libs/BLAS/main.cpp
+++ 3rd_party/eigen/bench/btl/libs/BLAS/main.cpp
@@ -54,20 +54,20 @@
   bench<Action_trisolve<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
   bench<Action_trisolve_matrix<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
 
   bench<Action_trmm<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
 
-  bench<Action_cholesky<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-  bench<Action_partial_lu<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
+  bench<Action_cholesky<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+  bench<Action_partial_lu<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
 
   #ifdef HAS_LAPACK
-  bench<Action_lu_decomp<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-  bench<Action_hessenberg<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-  bench<Action_tridiagonalization<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
+//   bench<Action_lu_decomp<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+  bench<Action_hessenberg<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+  bench<Action_tridiagonalization<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
   #endif
 
   //bench<Action_lu_solve<blas_LU_solve_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
 
   return 0;
 }
 
 

Index: 3rd_party/eigen/bench/btl/libs/STL/STL_interface.hh
==================================================================
--- 3rd_party/eigen/bench/btl/libs/STL/STL_interface.hh
+++ 3rd_party/eigen/bench/btl/libs/STL/STL_interface.hh
@@ -42,13 +42,13 @@
   static inline std::string name( void )
   {
     return "STL";
   }
 
-  static void free_matrix(gene_matrix & A, int N){}
+  static void free_matrix(gene_matrix & /*A*/, int /*N*/){}
 
-  static void free_vector(gene_vector & B){}
+  static void free_vector(gene_vector & /*B*/){}
 
   static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
     A = A_stl;
   }
 

ADDED   3rd_party/eigen/bench/btl/libs/blaze/CMakeLists.txt
Index: 3rd_party/eigen/bench/btl/libs/blaze/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/bench/btl/libs/blaze/CMakeLists.txt
+++ 3rd_party/eigen/bench/btl/libs/blaze/CMakeLists.txt
@@ -0,0 +1,13 @@
+
+find_package(BLAZE)
+find_package(Boost COMPONENTS system)
+if (BLAZE_FOUND AND Boost_FOUND)
+  include_directories(${BLAZE_INCLUDE_DIR} ${Boost_INCLUDE_DIRS})
+  btl_add_bench(btl_blaze main.cpp)
+  # Note: The newest blaze version requires C++14.
+  # Ideally, we should set this depending on the version of Blaze we found
+  set_property(TARGET btl_blaze PROPERTY CXX_STANDARD 14)
+  if(BUILD_btl_blaze)
+    target_link_libraries(btl_blaze ${Boost_LIBRARIES})
+  endif()
+endif ()

ADDED   3rd_party/eigen/bench/btl/libs/blaze/blaze_interface.hh
Index: 3rd_party/eigen/bench/btl/libs/blaze/blaze_interface.hh
==================================================================
--- 3rd_party/eigen/bench/btl/libs/blaze/blaze_interface.hh
+++ 3rd_party/eigen/bench/btl/libs/blaze/blaze_interface.hh
@@ -0,0 +1,140 @@
+//=====================================================
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+//=====================================================
+//
+// This program is free software; you can redistribute it and/or
+// modify it under the terms of the GNU General Public License
+// as published by the Free Software Foundation; either version 2
+// of the License, or (at your option) any later version.
+//
+// This program is distributed in the hope that it will be useful,
+// but WITHOUT ANY WARRANTY; without even the implied warranty of
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+// GNU General Public License for more details.
+// You should have received a copy of the GNU General Public License
+// along with this program; if not, write to the Free Software
+// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
+//
+#ifndef BLAZE_INTERFACE_HH
+#define BLAZE_INTERFACE_HH
+
+#include <blaze/Math.h>
+#include <blaze/Blaze.h>
+// using namespace blaze;
+
+#include <vector>
+
+template<class real>
+class blaze_interface {
+
+public :
+
+  typedef real real_type ;
+
+  typedef std::vector<real>        stl_vector;
+  typedef std::vector<stl_vector > stl_matrix;
+
+  typedef blaze::DynamicMatrix<real,blaze::columnMajor>  gene_matrix;
+  typedef blaze::DynamicVector<real>  gene_vector;
+
+  static inline std::string name() { return "blaze"; }
+
+  static void free_matrix(gene_matrix & A, int N){
+    return ;
+  }
+
+  static void free_vector(gene_vector & B){
+    return ;
+  }
+
+  static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
+    A.resize(A_stl[0].size(), A_stl.size());
+
+    for (int j=0; j<A_stl.size() ; j++){
+      for (int i=0; i<A_stl[j].size() ; i++){
+        A(i,j) = A_stl[j][i];
+      }
+    }
+  }
+
+  static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
+    B.resize(B_stl.size());
+    for (int i=0; i<B_stl.size() ; i++){
+      B[i] = B_stl[i];
+    }
+  }
+
+  static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
+    for (int i=0; i<B_stl.size() ; i++){
+      B_stl[i] = B[i];
+    }
+  }
+
+  static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
+    int N=A_stl.size();
+    for (int j=0;j<N;j++){
+      A_stl[j].resize(N);
+      for (int i=0;i<N;i++){
+        A_stl[j][i] = A(i,j);
+      }
+    }
+  }
+
+  static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
+    X = (A*B);
+  }
+
+  static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
+    X = (trans(A)*trans(B));
+  }
+
+  static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
+    X = (trans(A)*A);
+  }
+
+  static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
+    X = (A*trans(A));
+  }
+
+  static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
+    X = (A*B);
+  }
+
+  static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
+    X = (trans(A)*B);
+  }
+
+  static inline void axpy(const real coef, const gene_vector & X, gene_vector & Y, int N){
+    Y += coef * X;
+  }
+
+  static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
+    Y = a*X + b*Y;
+  }
+
+//   static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
+//     C = X;
+//     recursive_cholesky(C);
+//   }
+
+//   static inline void lu_decomp(const gene_matrix & X, gene_matrix & R, int N){
+//     R = X;
+//     std::vector<int> ipvt(N);
+//     lu_factor(R, ipvt);
+//   }
+
+//   static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector & X, int N){
+//     X = lower_trisolve(L, B);
+//   }
+
+  static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
+    cible = source;
+  }
+
+  static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
+    cible = source;
+  }
+
+};
+
+#endif

ADDED   3rd_party/eigen/bench/btl/libs/blaze/main.cpp
Index: 3rd_party/eigen/bench/btl/libs/blaze/main.cpp
==================================================================
--- 3rd_party/eigen/bench/btl/libs/blaze/main.cpp
+++ 3rd_party/eigen/bench/btl/libs/blaze/main.cpp
@@ -0,0 +1,40 @@
+//=====================================================
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+//=====================================================
+//
+// This program is free software; you can redistribute it and/or
+// modify it under the terms of the GNU General Public License
+// as published by the Free Software Foundation; either version 2
+// of the License, or (at your option) any later version.
+//
+// This program is distributed in the hope that it will be useful,
+// but WITHOUT ANY WARRANTY; without even the implied warranty of
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+// GNU General Public License for more details.
+// You should have received a copy of the GNU General Public License
+// along with this program; if not, write to the Free Software
+// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
+//
+#include "utilities.h"
+#include "blaze_interface.hh"
+#include "bench.hh"
+#include "basic_actions.hh"
+
+BTL_MAIN;
+
+int main()
+{
+
+  bench<Action_axpy<blaze_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
+  bench<Action_axpby<blaze_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
+
+  bench<Action_matrix_vector_product<blaze_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
+  bench<Action_atv_product<blaze_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
+//   bench<Action_matrix_matrix_product<blaze_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
+//   bench<Action_ata_product<blaze_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
+//   bench<Action_aat_product<blaze_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
+
+  return 0;
+}
+
+

Index: 3rd_party/eigen/bench/btl/libs/eigen2/eigen2_interface.hh
==================================================================
--- 3rd_party/eigen/bench/btl/libs/eigen2/eigen2_interface.hh
+++ 3rd_party/eigen/bench/btl/libs/eigen2/eigen2_interface.hh
@@ -45,11 +45,11 @@
 
   static inline std::string name( void )
   {
     #if defined(EIGEN_VECTORIZE_SSE)
     if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2";
-    #elif defined(EIGEN_VECTORIZE_ALTIVEC)
+    #elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
     if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2";
     #else
     if (SIZE==Dynamic) return "eigen2_novec"; else return "tiny_eigen2_novec";
     #endif
   }

Index: 3rd_party/eigen/bench/btl/libs/eigen3/eigen3_interface.hh
==================================================================
--- 3rd_party/eigen/bench/btl/libs/eigen3/eigen3_interface.hh
+++ 3rd_party/eigen/bench/btl/libs/eigen3/eigen3_interface.hh
@@ -43,71 +43,71 @@
   static inline std::string name( void )
   {
     return EIGEN_MAKESTRING(BTL_PREFIX);
   }
 
-  static void free_matrix(gene_matrix & A, int N) {}
+  static void free_matrix(gene_matrix & /*A*/, int /*N*/) {}
 
-  static void free_vector(gene_vector & B) {}
+  static void free_vector(gene_vector & /*B*/) {}
 
   static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
     A.resize(A_stl[0].size(), A_stl.size());
 
-    for (int j=0; j<A_stl.size() ; j++){
-      for (int i=0; i<A_stl[j].size() ; i++){
+    for (unsigned int j=0; j<A_stl.size() ; j++){
+      for (unsigned int i=0; i<A_stl[j].size() ; i++){
         A.coeffRef(i,j) = A_stl[j][i];
       }
     }
   }
 
   static BTL_DONT_INLINE  void vector_from_stl(gene_vector & B, stl_vector & B_stl){
     B.resize(B_stl.size(),1);
 
-    for (int i=0; i<B_stl.size() ; i++){
+    for (unsigned int i=0; i<B_stl.size() ; i++){
       B.coeffRef(i) = B_stl[i];
     }
   }
 
   static BTL_DONT_INLINE  void vector_to_stl(gene_vector & B, stl_vector & B_stl){
-    for (int i=0; i<B_stl.size() ; i++){
+    for (unsigned int i=0; i<B_stl.size() ; i++){
       B_stl[i] = B.coeff(i);
     }
   }
 
   static BTL_DONT_INLINE  void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
-    int N=A_stl.size();
+    int  N=A_stl.size();
 
     for (int j=0;j<N;j++){
       A_stl[j].resize(N);
       for (int i=0;i<N;i++){
         A_stl[j][i] = A.coeff(i,j);
       }
     }
   }
 
-  static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
+  static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int  /*N*/){
     X.noalias() = A*B;
   }
 
-  static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
+  static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int  /*N*/){
     X.noalias() = A.transpose()*B.transpose();
   }
 
-//   static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
+//   static inline void ata_product(const gene_matrix & A, gene_matrix & X, int  /*N*/){
 //     X.noalias() = A.transpose()*A;
 //   }
 
-  static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
+  static inline void aat_product(const gene_matrix & A, gene_matrix & X, int  /*N*/){
     X.template triangularView<Lower>().setZero();
     X.template selfadjointView<Lower>().rankUpdate(A);
   }
 
-  static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
+  static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int  /*N*/){
     X.noalias() = A*B;
   }
 
-  static inline void symv(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
+  static inline void symv(const gene_matrix & A, const gene_vector & B, gene_vector & X, int  /*N*/){
     X.noalias() = (A.template selfadjointView<Lower>() * B);
 //     internal::product_selfadjoint_vector<real,0,LowerTriangularBit,false,false>(N,A.data(),N, B.data(), 1, X.data(), 1);
   }
 
   template<typename Dest, typename Src> static void triassign(Dest& dst, const Src& src)
@@ -153,88 +153,88 @@
       }
       //dst.col(j).tail(N-j) = src.col(j).tail(N-j);
     }
   }
 
-  static EIGEN_DONT_INLINE void syr2(gene_matrix & A,  gene_vector & X, gene_vector & Y, int N){
+  static EIGEN_DONT_INLINE void syr2(gene_matrix & A,  gene_vector & X, gene_vector & Y, int  N){
     // internal::product_selfadjoint_rank2_update<real,0,LowerTriangularBit>(N,A.data(),N, X.data(), 1, Y.data(), 1, -1);
     for(int j=0; j<N; ++j)
       A.col(j).tail(N-j) += X[j] * Y.tail(N-j) + Y[j] * X.tail(N-j);
   }
 
-  static EIGEN_DONT_INLINE void ger(gene_matrix & A,  gene_vector & X, gene_vector & Y, int N){
+  static EIGEN_DONT_INLINE void ger(gene_matrix & A,  gene_vector & X, gene_vector & Y, int  N){
     for(int j=0; j<N; ++j)
       A.col(j) += X * Y[j];
   }
 
-  static EIGEN_DONT_INLINE void rot(gene_vector & A,  gene_vector & B, real c, real s, int N){
+  static EIGEN_DONT_INLINE void rot(gene_vector & A,  gene_vector & B, real c, real s, int  /*N*/){
     internal::apply_rotation_in_the_plane(A, B, JacobiRotation<real>(c,s));
   }
 
-  static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
+  static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int  /*N*/){
     X.noalias() = (A.transpose()*B);
   }
 
-  static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){
+  static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int  /*N*/){
     Y += coef * X;
   }
 
-  static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
+  static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int  /*N*/){
     Y = a*X + b*Y;
   }
 
-  static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
+  static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int  /*N*/){
     cible = source;
   }
 
-  static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int N){
+  static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int  /*N*/){
     cible = source;
   }
 
-  static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int N){
+  static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int  /*N*/){
     X = L.template triangularView<Lower>().solve(B);
   }
 
-  static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
+  static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int  /*N*/){
     X = L.template triangularView<Upper>().solve(B);
   }
 
-  static inline void trmm(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
+  static inline void trmm(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int  /*N*/){
     X.noalias() = L.template triangularView<Lower>() * B;
   }
 
-  static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
+  static inline void cholesky(const gene_matrix & X, gene_matrix & C, int  /*N*/){
     C = X;
     internal::llt_inplace<real,Lower>::blocked(C);
     //C = X.llt().matrixL();
 //     C = X;
 //     Cholesky<gene_matrix>::computeInPlace(C);
 //     Cholesky<gene_matrix>::computeInPlaceBlock(C);
   }
 
-  static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
+  static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int  /*N*/){
     C = X.fullPivLu().matrixLU();
   }
 
-  static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
+  static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int  N){
     Matrix<DenseIndex,1,Dynamic> piv(N);
     DenseIndex nb;
     C = X;
     internal::partial_lu_inplace(C,piv,nb);
 //     C = X.partialPivLu().matrixLU();
   }
 
-  static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){
+  static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int  N){
     typename Tridiagonalization<gene_matrix>::CoeffVectorType aux(N-1);
     C = X;
     internal::tridiagonalization_inplace(C, aux);
   }
 
-  static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){
+  static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int  /*N*/){
     C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
   }
 
 
 
 };
 
 #endif

Index: 3rd_party/eigen/bench/btl/libs/eigen3/main_adv.cpp
==================================================================
--- 3rd_party/eigen/bench/btl/libs/eigen3/main_adv.cpp
+++ 3rd_party/eigen/bench/btl/libs/eigen3/main_adv.cpp
@@ -27,18 +27,18 @@
 
 BTL_MAIN;
 
 int main()
 {
-  bench<Action_trisolve<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-  bench<Action_trisolve_matrix<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-  bench<Action_cholesky<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-  bench<Action_lu_decomp<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-  bench<Action_partial_lu<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-
-  bench<Action_hessenberg<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
-  bench<Action_tridiagonalization<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
+  bench<Action_trisolve<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+  bench<Action_trisolve_matrix<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+  bench<Action_cholesky<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+//   bench<Action_lu_decomp<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+  bench<Action_partial_lu<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+
+//   bench<Action_hessenberg<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
+  bench<Action_tridiagonalization<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
 
   return 0;
 }
 
 

ADDED   3rd_party/eigen/bench/btl/libs/tensors/CMakeLists.txt
Index: 3rd_party/eigen/bench/btl/libs/tensors/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/bench/btl/libs/tensors/CMakeLists.txt
+++ 3rd_party/eigen/bench/btl/libs/tensors/CMakeLists.txt
@@ -0,0 +1,44 @@
+
+
+if((NOT TENSOR_INCLUDE_DIR) AND Eigen_SOURCE_DIR)
+  # unless TENSOR_INCLUDE_DIR is defined, let's use current Eigen version
+  set(TENSOR_INCLUDE_DIR ${Eigen_SOURCE_DIR})
+  set(TENSOR_FOUND TRUE)
+else()
+  find_package(Tensor)
+endif()
+
+if (TENSOR_FOUND)
+
+  include_directories(${TENSOR_INCLUDE_DIR})
+  btl_add_bench(btl_tensor_linear main_linear.cpp)
+  btl_add_bench(btl_tensor_vecmat main_vecmat.cpp)
+  btl_add_bench(btl_tensor_matmat main_matmat.cpp)
+
+  btl_add_target_property(btl_tensor_linear COMPILE_FLAGS "-fno-exceptions -DBTL_PREFIX=tensor")
+  btl_add_target_property(btl_tensor_vecmat COMPILE_FLAGS "-fno-exceptions -DBTL_PREFIX=tensor")
+  btl_add_target_property(btl_tensor_matmat COMPILE_FLAGS "-fno-exceptions -DBTL_PREFIX=tensor")
+
+  option(BTL_BENCH_NOGCCVEC "also bench Eigen explicit vec without GCC's auto vec" OFF)
+  if(CMAKE_COMPILER_IS_GNUCXX AND BTL_BENCH_NOGCCVEC)
+    btl_add_bench(btl_tensor_nogccvec_linear main_linear.cpp)
+    btl_add_bench(btl_tensor_nogccvec_vecmat main_vecmat.cpp)
+    btl_add_bench(btl_tensor_nogccvec_matmat main_matmat.cpp)
+
+    btl_add_target_property(btl_tensor_nogccvec_linear COMPILE_FLAGS "-fno-exceptions -fno-tree-vectorize -DBTL_PREFIX=tensor_nogccvec")
+    btl_add_target_property(btl_tensor_nogccvec_vecmat COMPILE_FLAGS "-fno-exceptions -fno-tree-vectorize -DBTL_PREFIX=tensor_nogccvec")
+    btl_add_target_property(btl_tensor_nogccvec_matmat COMPILE_FLAGS "-fno-exceptions -fno-tree-vectorize -DBTL_PREFIX=tensor_nogccvec")
+  endif()
+
+
+  if(NOT BTL_NOVEC)
+    btl_add_bench(btl_tensor_novec_linear main_linear.cpp OFF)
+    btl_add_bench(btl_tensor_novec_vecmat main_vecmat.cpp OFF)
+    btl_add_bench(btl_tensor_novec_matmat main_matmat.cpp OFF)
+    btl_add_target_property(btl_tensor_novec_linear COMPILE_FLAGS "-fno-exceptions -DEIGEN_DONT_VECTORIZE -DBTL_PREFIX=tensor_novec")
+    btl_add_target_property(btl_tensor_novec_vecmat COMPILE_FLAGS "-fno-exceptions -DEIGEN_DONT_VECTORIZE -DBTL_PREFIX=tensor_novec")
+    btl_add_target_property(btl_tensor_novec_matmat COMPILE_FLAGS "-fno-exceptions -DEIGEN_DONT_VECTORIZE -DBTL_PREFIX=tensor_novec")
+
+  endif(NOT BTL_NOVEC)
+
+endif (TENSOR_FOUND)

ADDED   3rd_party/eigen/bench/btl/libs/tensors/main_linear.cpp
Index: 3rd_party/eigen/bench/btl/libs/tensors/main_linear.cpp
==================================================================
--- 3rd_party/eigen/bench/btl/libs/tensors/main_linear.cpp
+++ 3rd_party/eigen/bench/btl/libs/tensors/main_linear.cpp
@@ -0,0 +1,23 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "utilities.h"
+#include "tensor_interface.hh"
+#include "bench.hh"
+#include "basic_actions.hh"
+
+BTL_MAIN;
+
+int main()
+{
+  bench<Action_axpy<tensor_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
+  bench<Action_axpby<tensor_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
+
+  return 0;
+}

ADDED   3rd_party/eigen/bench/btl/libs/tensors/main_matmat.cpp
Index: 3rd_party/eigen/bench/btl/libs/tensors/main_matmat.cpp
==================================================================
--- 3rd_party/eigen/bench/btl/libs/tensors/main_matmat.cpp
+++ 3rd_party/eigen/bench/btl/libs/tensors/main_matmat.cpp
@@ -0,0 +1,21 @@
+//=====================================================
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//=====================================================
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+//
+#include "utilities.h"
+#include "tensor_interface.hh"
+#include "bench.hh"
+#include "basic_actions.hh"
+
+BTL_MAIN;
+
+int main()
+{
+  bench<Action_matrix_matrix_product<tensor_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
+
+  return 0;
+}

ADDED   3rd_party/eigen/bench/btl/libs/tensors/main_vecmat.cpp
Index: 3rd_party/eigen/bench/btl/libs/tensors/main_vecmat.cpp
==================================================================
--- 3rd_party/eigen/bench/btl/libs/tensors/main_vecmat.cpp
+++ 3rd_party/eigen/bench/btl/libs/tensors/main_vecmat.cpp
@@ -0,0 +1,21 @@
+//=====================================================
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//=====================================================
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+//
+#include "utilities.h"
+#include "tensor_interface.hh"
+#include "bench.hh"
+#include "basic_actions.hh"
+
+BTL_MAIN;
+
+int main()
+{
+  bench<Action_matrix_vector_product<tensor_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
+
+  return 0;
+}

ADDED   3rd_party/eigen/bench/btl/libs/tensors/tensor_interface.hh
Index: 3rd_party/eigen/bench/btl/libs/tensors/tensor_interface.hh
==================================================================
--- 3rd_party/eigen/bench/btl/libs/tensors/tensor_interface.hh
+++ 3rd_party/eigen/bench/btl/libs/tensors/tensor_interface.hh
@@ -0,0 +1,105 @@
+//=====================================================
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//=====================================================
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+//
+#ifndef TENSOR_INTERFACE_HH
+#define TENSOR_INTERFACE_HH
+
+#include <unsupported/Eigen/CXX11/Tensor>
+#include <vector>
+#include "btl.hh"
+
+using namespace Eigen;
+
+template<class real>
+class tensor_interface
+{
+public :
+  typedef real real_type;
+  typedef typename Eigen::Tensor<real,2>::Index Index;
+
+  typedef std::vector<real> stl_vector;
+  typedef std::vector<stl_vector> stl_matrix;
+
+  typedef Eigen::Tensor<real,2> gene_matrix;
+  typedef Eigen::Tensor<real,1> gene_vector;
+
+
+  static inline std::string name( void )
+  {
+    return EIGEN_MAKESTRING(BTL_PREFIX);
+  }
+
+  static void free_matrix(gene_matrix & /*A*/, int /*N*/) {}
+
+  static void free_vector(gene_vector & /*B*/) {}
+
+  static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
+    A.resize(Eigen::array<Index,2>(A_stl[0].size(), A_stl.size()));
+
+    for (unsigned int j=0; j<A_stl.size() ; j++){
+      for (unsigned int i=0; i<A_stl[j].size() ; i++){
+        A.coeffRef(Eigen::array<Index,2>(i,j)) = A_stl[j][i];
+      }
+    }
+  }
+
+  static BTL_DONT_INLINE  void vector_from_stl(gene_vector & B, stl_vector & B_stl){
+    B.resize(B_stl.size());
+
+    for (unsigned int i=0; i<B_stl.size() ; i++){
+      B.coeffRef(i) = B_stl[i];
+    }
+  }
+
+  static BTL_DONT_INLINE  void vector_to_stl(gene_vector & B, stl_vector & B_stl){
+    for (unsigned int i=0; i<B_stl.size() ; i++){
+      B_stl[i] = B.coeff(i);
+    }
+  }
+
+  static BTL_DONT_INLINE  void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
+    int  N=A_stl.size();
+
+    for (int j=0;j<N;j++){
+      A_stl[j].resize(N);
+      for (int i=0;i<N;i++){
+        A_stl[j][i] = A.coeff(Eigen::array<Index,2>(i,j));
+      }
+    }
+  }
+
+  static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int  /*N*/){
+    typedef typename Eigen::Tensor<real_type, 1>::DimensionPair DimPair;
+    const Eigen::array<DimPair, 1> dims(DimPair(1, 0));
+    X/*.noalias()*/ = A.contract(B, dims);
+  }
+
+  static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int  /*N*/){
+    typedef typename Eigen::Tensor<real_type, 1>::DimensionPair DimPair;
+    const Eigen::array<DimPair, 1> dims(DimPair(1, 0));
+    X/*.noalias()*/ = A.contract(B, dims);
+  }
+
+  static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int  /*N*/){
+    Y += X.constant(coef) * X;
+  }
+
+  static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int  /*N*/){
+    Y = X.constant(a)*X + Y.constant(b)*Y;
+  }
+
+  static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int  /*N*/){
+    cible = source;
+  }
+
+  static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int  /*N*/){
+    cible = source;
+  }
+};
+
+#endif

ADDED   3rd_party/eigen/bench/dense_solvers.cpp
Index: 3rd_party/eigen/bench/dense_solvers.cpp
==================================================================
--- 3rd_party/eigen/bench/dense_solvers.cpp
+++ 3rd_party/eigen/bench/dense_solvers.cpp
@@ -0,0 +1,186 @@
+#include <iostream>
+#include "BenchTimer.h"
+#include <Eigen/Dense>
+#include <map>
+#include <vector>
+#include <string>
+#include <sstream>
+using namespace Eigen;
+
+std::map<std::string,Array<float,1,8,DontAlign|RowMajor> > results;
+std::vector<std::string> labels;
+std::vector<Array2i> sizes;
+
+template<typename Solver,typename MatrixType>
+EIGEN_DONT_INLINE
+void compute_norm_equation(Solver &solver, const MatrixType &A) {
+  if(A.rows()!=A.cols())
+    solver.compute(A.transpose()*A);
+  else
+    solver.compute(A);
+}
+
+template<typename Solver,typename MatrixType>
+EIGEN_DONT_INLINE
+void compute(Solver &solver, const MatrixType &A) {
+  solver.compute(A);
+}
+
+template<typename Scalar,int Size>
+void bench(int id, int rows, int size = Size)
+{
+  typedef Matrix<Scalar,Dynamic,Size> Mat;
+  typedef Matrix<Scalar,Dynamic,Dynamic> MatDyn;
+  typedef Matrix<Scalar,Size,Size> MatSquare;
+  Mat A(rows,size);
+  A.setRandom();
+  if(rows==size)
+    A = A*A.adjoint();
+  BenchTimer t_llt, t_ldlt, t_lu, t_fplu, t_qr, t_cpqr, t_cod, t_fpqr, t_jsvd, t_bdcsvd;
+
+  int svd_opt = ComputeThinU|ComputeThinV;
+  
+  int tries = 5;
+  int rep = 1000/size;
+  if(rep==0) rep = 1;
+//   rep = rep*rep;
+  
+  LLT<MatSquare> llt(size);
+  LDLT<MatSquare> ldlt(size);
+  PartialPivLU<MatSquare> lu(size);
+  FullPivLU<MatSquare> fplu(size,size);
+  HouseholderQR<Mat> qr(A.rows(),A.cols());
+  ColPivHouseholderQR<Mat> cpqr(A.rows(),A.cols());
+  CompleteOrthogonalDecomposition<Mat> cod(A.rows(),A.cols());
+  FullPivHouseholderQR<Mat> fpqr(A.rows(),A.cols());
+  JacobiSVD<MatDyn> jsvd(A.rows(),A.cols());
+  BDCSVD<MatDyn> bdcsvd(A.rows(),A.cols());
+  
+  BENCH(t_llt, tries, rep, compute_norm_equation(llt,A));
+  BENCH(t_ldlt, tries, rep, compute_norm_equation(ldlt,A));
+  BENCH(t_lu, tries, rep, compute_norm_equation(lu,A));
+  if(size<=1000)
+    BENCH(t_fplu, tries, rep, compute_norm_equation(fplu,A));
+  BENCH(t_qr, tries, rep, compute(qr,A));
+  BENCH(t_cpqr, tries, rep, compute(cpqr,A));
+  BENCH(t_cod, tries, rep, compute(cod,A));
+  if(size*rows<=10000000)
+    BENCH(t_fpqr, tries, rep, compute(fpqr,A));
+  if(size<500) // JacobiSVD is really too slow for too large matrices
+    BENCH(t_jsvd, tries, rep, jsvd.compute(A,svd_opt));
+//   if(size*rows<=20000000)
+    BENCH(t_bdcsvd, tries, rep, bdcsvd.compute(A,svd_opt));
+  
+  results["LLT"][id] = t_llt.best();
+  results["LDLT"][id] = t_ldlt.best();
+  results["PartialPivLU"][id] = t_lu.best();
+  results["FullPivLU"][id] = t_fplu.best();
+  results["HouseholderQR"][id] = t_qr.best();
+  results["ColPivHouseholderQR"][id] = t_cpqr.best();
+  results["CompleteOrthogonalDecomposition"][id] = t_cod.best();
+  results["FullPivHouseholderQR"][id] = t_fpqr.best();
+  results["JacobiSVD"][id] = t_jsvd.best();
+  results["BDCSVD"][id] = t_bdcsvd.best();
+}
+
+
+int main()
+{
+  labels.push_back("LLT");
+  labels.push_back("LDLT");
+  labels.push_back("PartialPivLU");
+  labels.push_back("FullPivLU");
+  labels.push_back("HouseholderQR");
+  labels.push_back("ColPivHouseholderQR");
+  labels.push_back("CompleteOrthogonalDecomposition");
+  labels.push_back("FullPivHouseholderQR");
+  labels.push_back("JacobiSVD");
+  labels.push_back("BDCSVD");
+
+  for(int i=0; i<labels.size(); ++i)
+    results[labels[i]].fill(-1);
+
+  const int small = 8;
+  sizes.push_back(Array2i(small,small));
+  sizes.push_back(Array2i(100,100));
+  sizes.push_back(Array2i(1000,1000));
+  sizes.push_back(Array2i(4000,4000));
+  sizes.push_back(Array2i(10000,small));
+  sizes.push_back(Array2i(10000,100));
+  sizes.push_back(Array2i(10000,1000));
+  sizes.push_back(Array2i(10000,4000));
+
+  using namespace std;
+
+  for(int k=0; k<sizes.size(); ++k)
+  {
+    cout << sizes[k](0) << "x" << sizes[k](1) << "...\n";
+    bench<float,Dynamic>(k,sizes[k](0),sizes[k](1));
+  }
+
+  cout.width(32);
+  cout << "solver/size";
+  cout << "  ";
+  for(int k=0; k<sizes.size(); ++k)
+  {
+    std::stringstream ss;
+    ss << sizes[k](0) << "x" << sizes[k](1);
+    cout.width(10); cout << ss.str(); cout << " ";
+  }
+  cout << endl;
+
+
+  for(int i=0; i<labels.size(); ++i)
+  {
+    cout.width(32); cout << labels[i]; cout << "  ";
+    ArrayXf r = (results[labels[i]]*100000.f).floor()/100.f;
+    for(int k=0; k<sizes.size(); ++k)
+    {
+      cout.width(10);
+      if(r(k)>=1e6)  cout << "-";
+      else           cout << r(k);
+      cout << " ";
+    }
+    cout << endl;
+  }
+
+  // HTML output
+  cout << "<table class=\"manual\">" << endl;
+  cout << "<tr><th>solver/size</th>" << endl;
+  for(int k=0; k<sizes.size(); ++k)
+    cout << "  <th>" << sizes[k](0) << "x" << sizes[k](1) << "</th>";
+  cout << "</tr>" << endl;
+  for(int i=0; i<labels.size(); ++i)
+  {
+    cout << "<tr";
+    if(i%2==1) cout << " class=\"alt\"";
+    cout << "><td>" << labels[i] << "</td>";
+    ArrayXf r = (results[labels[i]]*100000.f).floor()/100.f;
+    for(int k=0; k<sizes.size(); ++k)
+    {
+      if(r(k)>=1e6) cout << "<td>-</td>";
+      else
+      {
+        cout << "<td>" << r(k);
+        if(i>0)
+          cout << " (x" << numext::round(10.f*results[labels[i]](k)/results["LLT"](k))/10.f << ")";
+        if(i<4 && sizes[k](0)!=sizes[k](1))
+          cout << " <sup><a href=\"#note_ls\">*</a></sup>";
+        cout << "</td>";
+      }
+    }
+    cout << "</tr>" << endl;
+  }
+  cout << "</table>" << endl;
+
+//   cout << "LLT                             (ms)  " << (results["LLT"]*1000.).format(fmt) << "\n";
+//   cout << "LDLT                             (%)  " << (results["LDLT"]/results["LLT"]).format(fmt) << "\n";
+//   cout << "PartialPivLU                     (%)  " << (results["PartialPivLU"]/results["LLT"]).format(fmt) << "\n";
+//   cout << "FullPivLU                        (%)  " << (results["FullPivLU"]/results["LLT"]).format(fmt) << "\n";
+//   cout << "HouseholderQR                    (%)  " << (results["HouseholderQR"]/results["LLT"]).format(fmt) << "\n";
+//   cout << "ColPivHouseholderQR              (%)  " << (results["ColPivHouseholderQR"]/results["LLT"]).format(fmt) << "\n";
+//   cout << "CompleteOrthogonalDecomposition  (%)  " << (results["CompleteOrthogonalDecomposition"]/results["LLT"]).format(fmt) << "\n";
+//   cout << "FullPivHouseholderQR             (%)  " << (results["FullPivHouseholderQR"]/results["LLT"]).format(fmt) << "\n";
+//   cout << "JacobiSVD                        (%)  " << (results["JacobiSVD"]/results["LLT"]).format(fmt) << "\n";
+//   cout << "BDCSVD                           (%)  " << (results["BDCSVD"]/results["LLT"]).format(fmt) << "\n";
+}

Index: 3rd_party/eigen/bench/eig33.cpp
==================================================================
--- 3rd_party/eigen/bench/eig33.cpp
+++ 3rd_party/eigen/bench/eig33.cpp
@@ -48,11 +48,11 @@
 template<typename Matrix, typename Roots>
 inline void computeRoots(const Matrix& m, Roots& roots)
 {
   typedef typename Matrix::Scalar Scalar;
   const Scalar s_inv3 = 1.0/3.0;
-  const Scalar s_sqrt3 = internal::sqrt(Scalar(3.0));
+  const Scalar s_sqrt3 = std::sqrt(Scalar(3.0));
 
   // The characteristic equation is x^3 - c2*x^2 + c1*x - c0 = 0.  The
   // eigenvalues are the roots to this equation, all guaranteed to be
   // real-valued, because the matrix is symmetric.
   Scalar c0 = m(0,0)*m(1,1)*m(2,2) + Scalar(2)*m(0,1)*m(0,2)*m(1,2) - m(0,0)*m(1,2)*m(1,2) - m(1,1)*m(0,2)*m(0,2) - m(2,2)*m(0,1)*m(0,1);
@@ -71,39 +71,32 @@
   Scalar q = half_b*half_b + a_over_3*a_over_3*a_over_3;
   if (q > Scalar(0))
     q = Scalar(0);
 
   // Compute the eigenvalues by solving for the roots of the polynomial.
-  Scalar rho = internal::sqrt(-a_over_3);
-  Scalar theta = std::atan2(internal::sqrt(-q),half_b)*s_inv3;
-  Scalar cos_theta = internal::cos(theta);
-  Scalar sin_theta = internal::sin(theta);
-  roots(0) = c2_over_3 + Scalar(2)*rho*cos_theta;
-  roots(1) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
-  roots(2) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
-
-  // Sort in increasing order.
-  if (roots(0) >= roots(1))
-    std::swap(roots(0),roots(1));
-  if (roots(1) >= roots(2))
-  {
-    std::swap(roots(1),roots(2));
-    if (roots(0) >= roots(1))
-      std::swap(roots(0),roots(1));
-  }
+  Scalar rho = std::sqrt(-a_over_3);
+  Scalar theta = std::atan2(std::sqrt(-q),half_b)*s_inv3;
+  Scalar cos_theta = std::cos(theta);
+  Scalar sin_theta = std::sin(theta);
+  roots(2) = c2_over_3 + Scalar(2)*rho*cos_theta;
+  roots(0) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
+  roots(1) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
 }
 
 template<typename Matrix, typename Vector>
 void eigen33(const Matrix& mat, Matrix& evecs, Vector& evals)
 {
   typedef typename Matrix::Scalar Scalar;
   // Scale the matrix so its entries are in [-1,1].  The scaling is applied
   // only when at least one matrix entry has magnitude larger than 1.
 
-  Scalar scale = mat.cwiseAbs()/*.template triangularView<Lower>()*/.maxCoeff();
+  Scalar shift = mat.trace()/3;
+  Matrix scaledMat = mat;
+  scaledMat.diagonal().array() -= shift;
+  Scalar scale = scaledMat.cwiseAbs()/*.template triangularView<Lower>()*/.maxCoeff();
   scale = std::max(scale,Scalar(1));
-  Matrix scaledMat = mat / scale;
+  scaledMat/=scale;
 
   // Compute the eigenvalues
 //   scaledMat.setZero();
   computeRoots(scaledMat,evals);
 
@@ -164,33 +157,39 @@
     evecs.col(0) = evecs.col(2).cross(evecs.col(1));
   }
   
   // Rescale back to the original size.
   evals *= scale;
+  evals.array()+=shift;
 }
 
 int main()
 {
   BenchTimer t;
   int tries = 10;
   int rep = 400000;
-  typedef Matrix3f Mat;
-  typedef Vector3f Vec;
+  typedef Matrix3d Mat;
+  typedef Vector3d Vec;
   Mat A = Mat::Random(3,3);
   A = A.adjoint() * A;
+//   Mat Q = A.householderQr().householderQ();
+//   A = Q * Vec(2.2424567,2.2424566,7.454353).asDiagonal() * Q.transpose();
 
   SelfAdjointEigenSolver<Mat> eig(A);
   BENCH(t, tries, rep, eig.compute(A));
-  std::cout << "Eigen:  " << t.best() << "s\n";
+  std::cout << "Eigen iterative:  " << t.best() << "s\n";
+  
+  BENCH(t, tries, rep, eig.computeDirect(A));
+  std::cout << "Eigen direct   :  " << t.best() << "s\n";
 
   Mat evecs;
   Vec evals;
   BENCH(t, tries, rep, eigen33(A,evecs,evals));
   std::cout << "Direct: " << t.best() << "s\n\n";
 
-  std::cerr << "Eigenvalue/eigenvector diffs:\n";
-  std::cerr << (evals - eig.eigenvalues()).transpose() << "\n";
-  for(int k=0;k<3;++k)
-    if(evecs.col(k).dot(eig.eigenvectors().col(k))<0)
-      evecs.col(k) = -evecs.col(k);
-  std::cerr << evecs - eig.eigenvectors() << "\n\n";
+//   std::cerr << "Eigenvalue/eigenvector diffs:\n";
+//   std::cerr << (evals - eig.eigenvalues()).transpose() << "\n";
+//   for(int k=0;k<3;++k)
+//     if(evecs.col(k).dot(eig.eigenvectors().col(k))<0)
+//       evecs.col(k) = -evecs.col(k);
+//   std::cerr << evecs - eig.eigenvectors() << "\n\n";
 }

ADDED   3rd_party/eigen/bench/perf_monitoring/gemm/changesets.txt
Index: 3rd_party/eigen/bench/perf_monitoring/gemm/changesets.txt
==================================================================
--- 3rd_party/eigen/bench/perf_monitoring/gemm/changesets.txt
+++ 3rd_party/eigen/bench/perf_monitoring/gemm/changesets.txt
@@ -0,0 +1,61 @@
+#3.0.1
+#3.1.1
+#3.2.0
+3.2.4
+#5745:37f59e65eb6c
+5891:d8652709345d  # introduce AVX
+#5893:24b4dc92c6d3  # merge
+5895:997c2ef9fc8b  # introduce FMA
+#5904:e1eafd14eaa1  # complex and AVX
+5908:f8ee3c721251  # improve packing with ptranspose
+#5921:ca808bb456b0  # merge
+#5927:8b1001f9e3ac
+5937:5a4ca1ad8c53  # New gebp kernel handling up to 3 packets x 4 register-level blocks
+#5949:f3488f4e45b2  # merge
+#5969:e09031dccfd9  # Disable 3pX4 kernel on Altivec
+#5992:4a429f5e0483  # merge
+before-evaluators
+#6334:f6a45e5b8b7c  # Implement evaluator for sparse outer products
+#6639:c9121c60b5c7
+#6655:06f163b5221f  # Properly detect FMA support on ARM
+#6677:700e023044e7   # FMA has been wrongly disabled
+#6681:11d31dafb0e3
+#6699:5e6e8e10aad1   # merge default to tensors
+#6726:ff2d2388e7b9   # merge default to tensors
+#6742:0cbd6195e829   # merge default to tensors
+#6747:853d2bafeb8f   # Generalized the gebp apis
+6765:71584fd55762   # Made the blocking computation aware of the l3 cache; Also optimized the blocking parameters to take into account the number of threads used for a computation
+#6781:9cc5a931b2c6   # generalized gemv
+#6792:f6e1daab600a   # ensured that contractions that can be reduced to a matrix vector product
+#6844:039efd86b75c   # merge tensor
+6845:7333ed40c6ef   # change prefetching in gebp
+#6856:b5be5e10eb7f   # merge index conversion
+#6893:c3a64aba7c70   # clean blocking size computation
+#6898:6fb31ebe6492   # rotating kernel for ARM
+6899:877facace746   # rotating kernel for ARM only
+#6904:c250623ae9fa   # result_of
+6921:915f1b1fc158   # fix prefetching change for ARM
+6923:9ff25f6dacc6   # prefetching
+6933:52572e60b5d3   # blocking size strategy
+6937:c8c042f286b2   # avoid redundant pack_rhs
+6981:7e5d6f78da59   # dynamic loop swapping
+6984:45f26866c091   # rm dynamic loop swapping, adjust lhs's micro panel height to fully exploit L1 cache
+6986:a675d05b6f8f   # blocking heuristic: block on the rhs in L1 if the lhs fit in L1.
+7013:f875e75f07e5   # organize a little our default cache sizes, and use a saner default L1 outside of x86 (10% faster on Nexus 5)
+7015:8aad8f35c955   # Refactor computeProductBlockingSizes to make room for the possibility of using lookup tables
+7016:a58d253e8c91   # Polish lookup tables generation
+7018:9b27294a8186   # actual_panel_rows computation should always be resilient to parameters not consistent with the known L1 cache size, see comment
+7019:c758b1e2c073   # Provide a empirical lookup table for blocking sizes measured on a Nexus 5. Only for float, only for Android on ARM 32bit for now.
+7085:627e039fba68   # Bug 986: add support for coefficient-based product with 0 depth.
+7098:b6f1db9cf9ec   # Bug 992: don't select a 3p GEMM path with non-vectorizable scalar types, this hits unsupported paths in symm/triangular products code
+7591:09a8e2186610   # 3.3-alpha1
+7650:b0f3c8f43025   # help clang inlining
+#8744:74b789ada92a   # Improved the matrix multiplication blocking in the case where mr is not a power of 2 (e.g on Haswell CPUs)
+8789:efcb912e4356   # Made the index type a template parameter to evaluateProductBlockingSizes. Use numext::mini and numext::maxi instead of std::min/std::max to compute blocking sizes
+8972:81d53c711775   # Don't optimize the processing of the last rows of a matrix matrix product in cases that violate the assumptions made by the optimized code path
+8985:d935df21a082   # Remove the rotating kernel.
+8988:6c2dc56e73b3   # Bug 256: enable vectorization with unaligned loads/stores.
+9148:b8b8c421e36c   # Relax mixing-type constraints for binary coefficient-wise operators
+9174:d228bc282ac9   # merge
+9212:c90098affa7b   # Fix performance regression introduced in changeset 8aad8f35c955
+9213:9f1c14e4694b   # Fix performance regression in dgemm introduced by changeset 81d53c711775

ADDED   3rd_party/eigen/bench/perf_monitoring/gemm/gemm.cpp
Index: 3rd_party/eigen/bench/perf_monitoring/gemm/gemm.cpp
==================================================================
--- 3rd_party/eigen/bench/perf_monitoring/gemm/gemm.cpp
+++ 3rd_party/eigen/bench/perf_monitoring/gemm/gemm.cpp
@@ -0,0 +1,67 @@
+#include <iostream>
+#include <fstream>
+#include <vector>
+#include <Eigen/Core>
+#include "../../BenchTimer.h"
+using namespace Eigen;
+
+#ifndef SCALAR
+#error SCALAR must be defined
+#endif
+
+typedef SCALAR Scalar;
+
+typedef Matrix<Scalar,Dynamic,Dynamic> Mat;
+
+EIGEN_DONT_INLINE
+void gemm(const Mat &A, const Mat &B, Mat &C)
+{
+  C.noalias() += A * B;
+}
+
+EIGEN_DONT_INLINE
+double bench(long m, long n, long k)
+{
+  Mat A(m,k);
+  Mat B(k,n);
+  Mat C(m,n);
+  A.setRandom();
+  B.setRandom();
+  C.setZero();
+  
+  BenchTimer t;
+  
+  double up = 1e8*4/sizeof(Scalar);
+  double tm0 = 4, tm1 = 10;
+  if(NumTraits<Scalar>::IsComplex)
+  {
+    up /= 4;
+    tm0 = 2;
+    tm1 = 4;
+  }
+  
+  double flops = 2. * m * n * k;
+  long rep = std::max(1., std::min(100., up/flops) );
+  long tries = std::max(tm0, std::min(tm1, up/flops) );
+  
+  BENCH(t, tries, rep, gemm(A,B,C));
+  
+  return 1e-9 * rep * flops / t.best();
+}
+
+int main(int argc, char **argv)
+{
+  std::vector<double> results;
+  
+  std::ifstream settings("gemm_settings.txt");
+  long m, n, k;
+  while(settings >> m >> n >> k)
+  {
+    //std::cerr << "  Testing " << m << " " << n << " " << k << std::endl;
+    results.push_back( bench(m, n, k) );
+  }
+  
+  std::cout << RowVectorXd::Map(results.data(), results.size());
+  
+  return 0;
+}

ADDED   3rd_party/eigen/bench/perf_monitoring/gemm/gemm_settings.txt
Index: 3rd_party/eigen/bench/perf_monitoring/gemm/gemm_settings.txt
==================================================================
--- 3rd_party/eigen/bench/perf_monitoring/gemm/gemm_settings.txt
+++ 3rd_party/eigen/bench/perf_monitoring/gemm/gemm_settings.txt
@@ -0,0 +1,15 @@
+8 8 8
+9 9 9
+24 24 24
+239 239 239
+240 240 240
+2400 24 24
+24 2400 24
+24 24 2400
+24 2400 2400
+2400 24 2400
+2400 2400 24
+2400 2400 64
+4800 23 160
+23 4800 160
+2400 2400 2400

ADDED   3rd_party/eigen/bench/perf_monitoring/gemm/lazy_gemm.cpp
Index: 3rd_party/eigen/bench/perf_monitoring/gemm/lazy_gemm.cpp
==================================================================
--- 3rd_party/eigen/bench/perf_monitoring/gemm/lazy_gemm.cpp
+++ 3rd_party/eigen/bench/perf_monitoring/gemm/lazy_gemm.cpp
@@ -0,0 +1,98 @@
+#include <iostream>
+#include <fstream>
+#include <vector>
+#include <Eigen/Core>
+#include "../../BenchTimer.h"
+using namespace Eigen;
+
+#ifndef SCALAR
+#error SCALAR must be defined
+#endif
+
+typedef SCALAR Scalar;
+
+template<typename MatA, typename MatB, typename MatC>
+EIGEN_DONT_INLINE
+void lazy_gemm(const MatA &A, const MatB &B, MatC &C)
+{
+//   escape((void*)A.data());
+//   escape((void*)B.data());
+  C.noalias() += A.lazyProduct(B);
+//   escape((void*)C.data());
+}
+
+template<int m, int n, int k, int TA>
+EIGEN_DONT_INLINE
+double bench()
+{
+  typedef Matrix<Scalar,m,k,TA> MatA;
+  typedef Matrix<Scalar,k,n> MatB;
+  typedef Matrix<Scalar,m,n> MatC;
+
+  MatA A(m,k);
+  MatB B(k,n);
+  MatC C(m,n);
+  A.setRandom();
+  B.setRandom();
+  C.setZero();
+
+  BenchTimer t;
+
+  double up = 1e7*4/sizeof(Scalar);
+  double tm0 = 10, tm1 = 20;
+
+  double flops = 2. * m * n * k;
+  long rep = std::max(10., std::min(10000., up/flops) );
+  long tries = std::max(tm0, std::min(tm1, up/flops) );
+
+  BENCH(t, tries, rep, lazy_gemm(A,B,C));
+
+  return 1e-9 * rep * flops / t.best();
+}
+
+template<int m, int n, int k>
+double bench_t(int t)
+{
+  if(t)
+    return bench<m,n,k,RowMajor>();
+  else
+    return bench<m,n,k,0>();
+}
+
+EIGEN_DONT_INLINE
+double bench_mnk(int m, int n, int k, int t)
+{
+  int id = m*10000 + n*100 + k;
+  switch(id) {
+    case  10101 : return bench_t< 1, 1, 1>(t); break;
+    case  20202 : return bench_t< 2, 2, 2>(t); break;
+    case  30303 : return bench_t< 3, 3, 3>(t); break;
+    case  40404 : return bench_t< 4, 4, 4>(t); break;
+    case  50505 : return bench_t< 5, 5, 5>(t); break;
+    case  60606 : return bench_t< 6, 6, 6>(t); break;
+    case  70707 : return bench_t< 7, 7, 7>(t); break;
+    case  80808 : return bench_t< 8, 8, 8>(t); break;
+    case  90909 : return bench_t< 9, 9, 9>(t); break;
+    case 101010 : return bench_t<10,10,10>(t); break;
+    case 111111 : return bench_t<11,11,11>(t); break;
+    case 121212 : return bench_t<12,12,12>(t); break;
+  }
+  return 0;
+}
+
+int main(int argc, char **argv)
+{
+  std::vector<double> results;
+  
+  std::ifstream settings("lazy_gemm_settings.txt");
+  long m, n, k, t;
+  while(settings >> m >> n >> k >> t)
+  {
+    //std::cerr << "  Testing " << m << " " << n << " " << k << std::endl;
+    results.push_back( bench_mnk(m, n, k, t) );
+  }
+  
+  std::cout << RowVectorXd::Map(results.data(), results.size());
+  
+  return 0;
+}

ADDED   3rd_party/eigen/bench/perf_monitoring/gemm/lazy_gemm_settings.txt
Index: 3rd_party/eigen/bench/perf_monitoring/gemm/lazy_gemm_settings.txt
==================================================================
--- 3rd_party/eigen/bench/perf_monitoring/gemm/lazy_gemm_settings.txt
+++ 3rd_party/eigen/bench/perf_monitoring/gemm/lazy_gemm_settings.txt
@@ -0,0 +1,15 @@
+1 1 1 0
+2 2 2 0
+3 3 3 0
+4 4 4 0
+4 4 4 1
+5 5 5 0
+6 6 6 0
+7 7 7 0
+7 7 7 1
+8 8 8 0
+9 9 9 0
+10 10 10 0
+11 11 11 0
+12 12 12 0
+12 12 12 1

ADDED   3rd_party/eigen/bench/perf_monitoring/gemm/make_plot.sh
Index: 3rd_party/eigen/bench/perf_monitoring/gemm/make_plot.sh
==================================================================
--- 3rd_party/eigen/bench/perf_monitoring/gemm/make_plot.sh
+++ 3rd_party/eigen/bench/perf_monitoring/gemm/make_plot.sh
@@ -0,0 +1,38 @@
+#!/bin/bash
+
+# base name of the bench
+# it reads $1.out
+# and generates $1.pdf
+WHAT=$1
+bench=$2
+
+header="rev "
+while read line
+do
+  if [ ! -z '$line' ]; then
+    header="$header  \"$line\""
+  fi
+done < $bench"_settings.txt"
+
+echo $header > $WHAT.out.header
+cat $WHAT.out >> $WHAT.out.header
+
+
+echo "set title '$WHAT'" > $WHAT.gnuplot
+echo "set key autotitle columnhead outside " >> $WHAT.gnuplot
+echo "set xtics rotate 1" >> $WHAT.gnuplot
+
+echo "set term pdf color rounded enhanced fontscale 0.35 size 7in,5in" >> $WHAT.gnuplot
+echo set output "'"$WHAT.pdf"'" >> $WHAT.gnuplot
+
+col=`cat $bench"_settings.txt" | wc -l`
+echo "plot for [col=2:$col+1] '$WHAT.out.header' using 0:col:xticlabels(1) with lines" >> $WHAT.gnuplot
+echo " " >>  $WHAT.gnuplot
+
+gnuplot -persist < $WHAT.gnuplot
+
+# generate a png file
+# convert -background white -density 120 -rotate 90 -resize 800 +dither -colors 256 -quality 0 $WHAT.ps -background white -flatten  .$WHAT.png
+
+# clean
+rm $WHAT.out.header $WHAT.gnuplot

ADDED   3rd_party/eigen/bench/perf_monitoring/gemm/run.sh
Index: 3rd_party/eigen/bench/perf_monitoring/gemm/run.sh
==================================================================
--- 3rd_party/eigen/bench/perf_monitoring/gemm/run.sh
+++ 3rd_party/eigen/bench/perf_monitoring/gemm/run.sh
@@ -0,0 +1,156 @@
+#!/bin/bash
+
+# ./run.sh gemm
+# ./run.sh lazy_gemm
+
+# Examples of environment variables to be set:
+#   PREFIX="haswell-fma-"
+#   CXX_FLAGS="-mfma"
+
+# Options:
+#   -up : enforce the recomputation of existing data, and keep best results as a merging strategy
+#   -s  : recompute selected changesets only and keep bests
+
+bench=$1
+
+if echo "$*" | grep '\-up' > /dev/null; then
+  update=true
+else
+  update=false
+fi
+
+if echo "$*" | grep '\-s' > /dev/null; then
+  selected=true
+else
+  selected=false
+fi
+
+global_args="$*"
+
+if [ $selected == true ]; then
+ echo "Recompute selected changesets only and keep bests"
+elif [ $update == true ]; then
+ echo "(Re-)Compute all changesets and keep bests"
+else
+ echo "Skip previously computed changesets"
+fi
+
+
+
+if [ ! -d "eigen_src" ]; then
+  hg clone https://bitbucket.org/eigen/eigen eigen_src
+else
+  cd eigen_src
+  hg pull -u
+  cd ..
+fi
+
+if [ ! -z '$CXX' ]; then
+  CXX=g++
+fi
+
+function make_backup
+{
+  if [ -f "$1.out" ]; then
+    mv "$1.out" "$1.backup"
+  fi
+}
+
+function merge
+{
+  count1=`echo $1 |  wc -w`
+  count2=`echo $2 |  wc -w`
+  
+  if [ $count1 == $count2 ]; then
+    a=( $1 ); b=( $2 )
+    res=""
+    for (( i=0 ; i<$count1 ; i++ )); do
+      ai=${a[$i]}; bi=${b[$i]}
+      tmp=`echo "if ($ai > $bi) $ai else $bi " | bc -l`
+      res="$res $tmp"
+    done
+    echo $res
+
+  else
+    echo $1
+  fi
+}
+
+function test_current 
+{
+  rev=$1
+  scalar=$2
+  name=$3
+  
+  prev=""
+  if [ -e "$name.backup" ]; then
+    prev=`grep $rev "$name.backup" | cut -c 14-`
+  fi
+  res=$prev
+  count_rev=`echo $prev |  wc -w`
+  count_ref=`cat $bench"_settings.txt" |  wc -l`
+  if echo "$global_args" | grep "$rev" > /dev/null; then
+    rev_found=true
+  else
+    rev_found=false
+  fi
+#  echo $update et $selected et $rev_found because $rev et "$global_args"
+#  echo $count_rev et $count_ref
+  if [ $update == true ] || [ $count_rev != $count_ref ] || ([ $selected == true ] &&  [ $rev_found == true ]); then
+    if $CXX -O2 -DNDEBUG -march=native $CXX_FLAGS -I eigen_src $bench.cpp -DSCALAR=$scalar -o $name; then
+      curr=`./$name`
+      if [ $count_rev == $count_ref ]; then
+        echo "merge previous $prev"
+        echo "with new       $curr"
+      else
+        echo "got            $curr"
+      fi
+      res=`merge "$curr" "$prev"`
+#       echo $res
+      echo "$rev $res" >> $name.out
+    else
+      echo "Compilation failed, skip rev $rev"
+    fi
+  else
+    echo "Skip existing results for $rev / $name"
+    echo "$rev $res" >> $name.out
+  fi
+}
+
+make_backup $PREFIX"s"$bench
+make_backup $PREFIX"d"$bench
+make_backup $PREFIX"c"$bench
+
+cut -f1 -d"#" < changesets.txt | grep -E '[[:alnum:]]' | while read rev
+do
+  if [ ! -z '$rev' ]; then
+    echo "Testing rev $rev"
+    cd eigen_src
+    hg up -C $rev > /dev/null
+    actual_rev=`hg identify | cut -f1 -d' '`
+    cd ..
+    
+    test_current $actual_rev float                  $PREFIX"s"$bench
+    test_current $actual_rev double                 $PREFIX"d"$bench
+    test_current $actual_rev "std::complex<double>" $PREFIX"c"$bench
+  fi
+  
+done
+
+echo "Float:"
+cat $PREFIX"s""$bench.out"
+echo " "
+
+echo "Double:"
+cat $PREFIX"d""$bench.out"
+echo ""
+
+echo "Complex:"
+cat $PREFIX"c""$bench.out"
+echo ""
+
+./make_plot.sh $PREFIX"s"$bench $bench
+./make_plot.sh $PREFIX"d"$bench $bench
+./make_plot.sh $PREFIX"c"$bench $bench
+
+

Index: 3rd_party/eigen/bench/spbench/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/bench/spbench/CMakeLists.txt
+++ 3rd_party/eigen/bench/spbench/CMakeLists.txt
@@ -27,38 +27,45 @@
   include_directories(${UMFPACK_INCLUDES})
   set(SPARSE_LIBS ${SPARSE_LIBS} ${UMFPACK_LIBRARIES} ${BLAS_LIBRARIES})
   set(UMFPACK_ALL_LIBS ${UMFPACK_LIBRARIES} ${BLAS_LIBRARIES})
 endif()
 
-find_package(SuperLU)
+find_package(SuperLU 4.0)
 if(SUPERLU_FOUND AND BLAS_FOUND)
   add_definitions("-DEIGEN_SUPERLU_SUPPORT")
   include_directories(${SUPERLU_INCLUDES})
   set(SPARSE_LIBS ${SPARSE_LIBS} ${SUPERLU_LIBRARIES} ${BLAS_LIBRARIES})
   set(SUPERLU_ALL_LIBS ${SUPERLU_LIBRARIES} ${BLAS_LIBRARIES})
 endif()
 
 
-find_package(Pastix)
-find_package(Scotch)
-find_package(Metis)
-if(PASTIX_FOUND AND BLAS_FOUND)
+find_package(PASTIX QUIET COMPONENTS METIS SCOTCH)
+# check that the PASTIX found is a version without MPI
+find_path(PASTIX_pastix_nompi.h_INCLUDE_DIRS
+  NAMES pastix_nompi.h
+  HINTS ${PASTIX_INCLUDE_DIRS}
+)
+if (NOT PASTIX_pastix_nompi.h_INCLUDE_DIRS)
+  message(STATUS "A version of Pastix has been found but pastix_nompi.h does not exist in the include directory."
+                 " Because Eigen tests require a version without MPI, we disable the Pastix backend.")
+endif()
+if(PASTIX_FOUND AND PASTIX_pastix_nompi.h_INCLUDE_DIRS AND BLAS_FOUND)
   add_definitions("-DEIGEN_PASTIX_SUPPORT")
-  include_directories(${PASTIX_INCLUDES})
+  include_directories(${PASTIX_INCLUDE_DIRS_DEP})
   if(SCOTCH_FOUND)
-    include_directories(${SCOTCH_INCLUDES})
+    include_directories(${SCOTCH_INCLUDE_DIRS})
     set(PASTIX_LIBRARIES ${PASTIX_LIBRARIES} ${SCOTCH_LIBRARIES})
   elseif(METIS_FOUND)
-    include_directories(${METIS_INCLUDES})
+    include_directories(${METIS_INCLUDE_DIRS})
     set(PASTIX_LIBRARIES ${PASTIX_LIBRARIES} ${METIS_LIBRARIES})  
   endif(SCOTCH_FOUND)
-  set(SPARSE_LIBS ${SPARSE_LIBS} ${PASTIX_LIBRARIES} ${ORDERING_LIBRARIES} ${BLAS_LIBRARIES})
-  set(PASTIX_ALL_LIBS ${PASTIX_LIBRARIES} ${BLAS_LIBRARIES})
+  set(SPARSE_LIBS ${SPARSE_LIBS} ${PASTIX_LIBRARIES_DEP} ${ORDERING_LIBRARIES})
+  set(PASTIX_ALL_LIBS ${PASTIX_LIBRARIES_DEP})
 endif(PASTIX_FOUND AND BLAS_FOUND)
 
 if(METIS_FOUND)
-  include_directories(${METIS_INCLUDES})
+  include_directories(${METIS_INCLUDE_DIRS})
   set (SPARSE_LIBS ${SPARSE_LIBS} ${METIS_LIBRARIES})
   add_definitions("-DEIGEN_METIS_SUPPORT")
 endif(METIS_FOUND)
 
 find_library(RT_LIBRARY rt)

Index: 3rd_party/eigen/bench/spbench/spbenchstyle.h
==================================================================
--- 3rd_party/eigen/bench/spbench/spbenchstyle.h
+++ 3rd_party/eigen/bench/spbench/spbenchstyle.h
@@ -89,6 +89,7 @@
     </html>\n \
   </xsl:template>\n \
   </xsl:stylesheet>\n\n";
   
 }
+
 #endif

ADDED   3rd_party/eigen/bench/tensors/README
Index: 3rd_party/eigen/bench/tensors/README
==================================================================
--- 3rd_party/eigen/bench/tensors/README
+++ 3rd_party/eigen/bench/tensors/README
@@ -0,0 +1,21 @@
+The tensor benchmark suite is made of several parts.
+
+The first part is a generic suite, in which each benchmark comes in 2 flavors: one that runs on CPU, and one that runs on GPU.
+
+To compile the floating point CPU benchmarks, simply call:
+g++ tensor_benchmarks_cpu.cc benchmark_main.cc -I ../../ -std=c++11 -O3 -DNDEBUG -pthread -mavx -o benchmarks_cpu
+
+To compile the floating point GPU benchmarks, simply call:
+nvcc tensor_benchmarks_gpu.cu benchmark_main.cc -I ../../ -std=c++11 -O2 -DNDEBUG -use_fast_math -ftz=true -arch compute_35 -o benchmarks_gpu
+
+We also provide a version of the generic GPU tensor benchmarks that uses half floats (aka fp16) instead of regular floats. To compile these benchmarks, simply call the command line below. You'll need a recent GPU that supports compute capability 5.3 or higher to run them and nvcc 7.5 or higher to compile the code.
+nvcc tensor_benchmarks_fp16_gpu.cu benchmark_main.cc -I ../../ -std=c++11 -O2 -DNDEBUG -use_fast_math -ftz=true -arch compute_53 -o benchmarks_fp16_gpu
+
+last but not least, we also provide a suite of benchmarks to measure the scalability of the contraction code on CPU. To compile these benchmarks, call
+g++ contraction_benchmarks_cpu.cc benchmark_main.cc -I ../../ -std=c++11 -O3 -DNDEBUG -pthread -mavx -o benchmarks_cpu
+
+To compile the benchmark for SYCL, using ComputeCpp you currently need 2 passes (only for translation units containing device code):
+1. The device compilation pass that generates the device code (SYCL kernels and referenced device functions) and glue code needed by the host compiler to reference the device code from host code.
+{ComputeCpp_ROOT}/bin/compute++ -I ../../ -I {ComputeCpp_ROOT}/include/ -std=c++11 -mllvm -inline-threshold=1000 -Wno-ignored-attributes -sycl -intelspirmetadata -emit-llvm -no-serial-memop -sycl-compress-name -DBUILD_PLATFORM_SPIR -DNDBUG -O3 -c tensor_benchmarks_sycl.cc
+2. The host compilation pass that generates the final host binary.
+clang++-3.7 -include tensor_benchmarks_sycl.sycl benchmark_main.cc tensor_benchmarks_sycl.cc -pthread -I ../../ -I {ComputeCpp_ROOT}/include/ -L {ComputeCpp_ROOT}/lib/ -lComputeCpp -lOpenCL -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11 -o tensor_benchmark_sycl

ADDED   3rd_party/eigen/bench/tensors/benchmark.h
Index: 3rd_party/eigen/bench/tensors/benchmark.h
==================================================================
--- 3rd_party/eigen/bench/tensors/benchmark.h
+++ 3rd_party/eigen/bench/tensors/benchmark.h
@@ -0,0 +1,49 @@
+/*
+ * Copyright (C) 2012 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <stddef.h>
+#include <stdint.h>
+#include <vector>
+
+namespace testing {
+class Benchmark {
+ public:
+  Benchmark(const char* name, void (*fn)(int)) {
+    Register(name, fn, NULL);
+  }
+  Benchmark(const char* name, void (*fn_range)(int, int)) {
+    Register(name, NULL, fn_range);
+  }
+  Benchmark* Arg(int x);
+  Benchmark* Range(int lo, int hi);
+  const char* Name();
+  bool ShouldRun(int argc, char* argv[]);
+  void Run();
+ private:
+  const char* name_;
+  void (*fn_)(int);
+  void (*fn_range_)(int, int);
+  std::vector<int> args_;
+  void Register(const char* name, void (*fn)(int), void (*fn_range)(int, int));
+  void RunRepeatedlyWithArg(int iterations, int arg);
+  void RunWithArg(int arg);
+};
+}  // namespace testing
+void SetBenchmarkFlopsProcessed(int64_t);
+void StopBenchmarkTiming();
+void StartBenchmarkTiming();
+#define BENCHMARK(f) \
+    static ::testing::Benchmark* _benchmark_##f __attribute__((unused)) = \
+        (new ::testing::Benchmark(#f, f))

ADDED   3rd_party/eigen/bench/tensors/benchmark_main.cc
Index: 3rd_party/eigen/bench/tensors/benchmark_main.cc
==================================================================
--- 3rd_party/eigen/bench/tensors/benchmark_main.cc
+++ 3rd_party/eigen/bench/tensors/benchmark_main.cc
@@ -0,0 +1,237 @@
+/*
+ * Copyright (C) 2012 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "benchmark.h"
+#include <regex.h>
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <string>
+#include <inttypes.h>
+#include <time.h>
+#include <map>
+
+static int64_t g_flops_processed;
+static int64_t g_benchmark_total_time_ns;
+static int64_t g_benchmark_start_time_ns;
+typedef std::map<std::string, ::testing::Benchmark*> BenchmarkMap;
+typedef BenchmarkMap::iterator BenchmarkMapIt;
+
+BenchmarkMap& gBenchmarks() {
+  static BenchmarkMap g_benchmarks;
+  return g_benchmarks;
+}
+
+static int g_name_column_width = 20;
+
+static int Round(int n) {
+  int base = 1;
+  while (base*10 < n) {
+    base *= 10;
+  }
+  if (n < 2*base) {
+    return 2*base;
+  }
+  if (n < 5*base) {
+    return 5*base;
+  }
+  return 10*base;
+}
+
+#ifdef __APPLE__
+  #include <mach/mach_time.h>
+  static mach_timebase_info_data_t g_time_info;
+  static void __attribute__((constructor)) init_info() {
+    mach_timebase_info(&g_time_info);
+  }
+#endif
+
+static int64_t NanoTime() {
+#if defined(__APPLE__)
+  uint64_t t = mach_absolute_time();
+  return t * g_time_info.numer / g_time_info.denom;
+#else
+  struct timespec t;
+  t.tv_sec = t.tv_nsec = 0;
+  clock_gettime(CLOCK_MONOTONIC, &t);
+  return static_cast<int64_t>(t.tv_sec) * 1000000000LL + t.tv_nsec;
+#endif
+}
+
+namespace testing {
+Benchmark* Benchmark::Arg(int arg) {
+  args_.push_back(arg);
+  return this;
+}
+
+Benchmark* Benchmark::Range(int lo, int hi) {
+  const int kRangeMultiplier = 8;
+  if (hi < lo) {
+    int temp = hi;
+    hi = lo;
+    lo = temp;
+  }
+  while (lo < hi) {
+    args_.push_back(lo);
+    lo *= kRangeMultiplier;
+  }
+  // We always run the hi number.
+  args_.push_back(hi);
+  return this;
+}
+
+const char* Benchmark::Name() {
+  return name_;
+}
+bool Benchmark::ShouldRun(int argc, char* argv[]) {
+  if (argc == 1) {
+    return true;  // With no arguments, we run all benchmarks.
+  }
+  // Otherwise, we interpret each argument as a regular expression and
+  // see if any of our benchmarks match.
+  for (int i = 1; i < argc; i++) {
+    regex_t re;
+    if (regcomp(&re, argv[i], 0) != 0) {
+      fprintf(stderr, "couldn't compile \"%s\" as a regular expression!\n", argv[i]);
+      exit(EXIT_FAILURE);
+    }
+    int match = regexec(&re, name_, 0, NULL, 0);
+    regfree(&re);
+    if (match != REG_NOMATCH) {
+      return true;
+    }
+  }
+  return false;
+}
+void Benchmark::Register(const char* name, void (*fn)(int), void (*fn_range)(int, int)) {
+  name_ = name;
+  fn_ = fn;
+  fn_range_ = fn_range;
+  if (fn_ == NULL && fn_range_ == NULL) {
+    fprintf(stderr, "%s: missing function\n", name_);
+    exit(EXIT_FAILURE);
+  }
+  gBenchmarks().insert(std::make_pair(name, this));
+}
+void Benchmark::Run() {
+  if (fn_ != NULL) {
+    RunWithArg(0);
+  } else {
+    if (args_.empty()) {
+      fprintf(stderr, "%s: no args!\n", name_);
+      exit(EXIT_FAILURE);
+    }
+    for (size_t i = 0; i < args_.size(); ++i) {
+      RunWithArg(args_[i]);
+    }
+  }
+}
+void Benchmark::RunRepeatedlyWithArg(int iterations, int arg) {
+  g_flops_processed = 0;
+  g_benchmark_total_time_ns = 0;
+  g_benchmark_start_time_ns = NanoTime();
+  if (fn_ != NULL) {
+    fn_(iterations);
+  } else {
+    fn_range_(iterations, arg);
+  }
+  if (g_benchmark_start_time_ns != 0) {
+    g_benchmark_total_time_ns += NanoTime() - g_benchmark_start_time_ns;
+  }
+}
+void Benchmark::RunWithArg(int arg) {
+  // run once in case it's expensive
+  int iterations = 1;
+  RunRepeatedlyWithArg(iterations, arg);
+  while (g_benchmark_total_time_ns < 1e9 && iterations < 1e9) {
+    int last = iterations;
+    if (g_benchmark_total_time_ns/iterations == 0) {
+      iterations = 1e9;
+    } else {
+      iterations = 1e9 / (g_benchmark_total_time_ns/iterations);
+    }
+    iterations = std::max(last + 1, std::min(iterations + iterations/2, 100*last));
+    iterations = Round(iterations);
+    RunRepeatedlyWithArg(iterations, arg);
+  }
+  char throughput[100];
+  throughput[0] = '\0';
+  if (g_benchmark_total_time_ns > 0 && g_flops_processed > 0) {
+    double mflops_processed = static_cast<double>(g_flops_processed)/1e6;
+    double seconds = static_cast<double>(g_benchmark_total_time_ns)/1e9;
+    snprintf(throughput, sizeof(throughput), " %8.2f MFlops/s", mflops_processed/seconds);
+  }
+  char full_name[100];
+  if (fn_range_ != NULL) {
+    if (arg >= (1<<20)) {
+      snprintf(full_name, sizeof(full_name), "%s/%dM", name_, arg/(1<<20));
+    } else if (arg >= (1<<10)) {
+      snprintf(full_name, sizeof(full_name), "%s/%dK", name_, arg/(1<<10));
+    } else {
+      snprintf(full_name, sizeof(full_name), "%s/%d", name_, arg);
+    }
+  } else {
+    snprintf(full_name, sizeof(full_name), "%s", name_);
+  }
+  printf("%-*s %10d %10" PRId64 "%s\n", g_name_column_width, full_name,
+         iterations, g_benchmark_total_time_ns/iterations, throughput);
+  fflush(stdout);
+}
+}  // namespace testing
+void SetBenchmarkFlopsProcessed(int64_t x) {
+  g_flops_processed = x;
+}
+void StopBenchmarkTiming() {
+  if (g_benchmark_start_time_ns != 0) {
+    g_benchmark_total_time_ns += NanoTime() - g_benchmark_start_time_ns;
+  }
+  g_benchmark_start_time_ns = 0;
+}
+void StartBenchmarkTiming() {
+  if (g_benchmark_start_time_ns == 0) {
+    g_benchmark_start_time_ns = NanoTime();
+  }
+}
+int main(int argc, char* argv[]) {
+  if (gBenchmarks().empty()) {
+    fprintf(stderr, "No benchmarks registered!\n");
+    exit(EXIT_FAILURE);
+  }
+  for (BenchmarkMapIt it = gBenchmarks().begin(); it != gBenchmarks().end(); ++it) {
+    int name_width = static_cast<int>(strlen(it->second->Name()));
+    g_name_column_width = std::max(g_name_column_width, name_width);
+  }
+  bool need_header = true;
+  for (BenchmarkMapIt it = gBenchmarks().begin(); it != gBenchmarks().end(); ++it) {
+    ::testing::Benchmark* b = it->second;
+    if (b->ShouldRun(argc, argv)) {
+      if (need_header) {
+        printf("%-*s %10s %10s\n", g_name_column_width, "", "iterations", "ns/op");
+        fflush(stdout);
+        need_header = false;
+      }
+      b->Run();
+    }
+  }
+  if (need_header) {
+    fprintf(stderr, "No matching benchmarks!\n");
+    fprintf(stderr, "Available benchmarks:\n");
+    for (BenchmarkMapIt it = gBenchmarks().begin(); it != gBenchmarks().end(); ++it) {
+      fprintf(stderr, "  %s\n", it->second->Name());
+    }
+    exit(EXIT_FAILURE);
+  }
+  return 0;
+}

ADDED   3rd_party/eigen/bench/tensors/contraction_benchmarks_cpu.cc
Index: 3rd_party/eigen/bench/tensors/contraction_benchmarks_cpu.cc
==================================================================
--- 3rd_party/eigen/bench/tensors/contraction_benchmarks_cpu.cc
+++ 3rd_party/eigen/bench/tensors/contraction_benchmarks_cpu.cc
@@ -0,0 +1,39 @@
+#define EIGEN_USE_THREADS
+
+#include <string>
+
+#include "tensor_benchmarks.h"
+
+#define CREATE_THREAD_POOL(threads)             \
+Eigen::ThreadPool pool(threads);                \
+Eigen::ThreadPoolDevice device(&pool, threads);
+
+
+// Contractions for number of threads ranging from 1 to 32
+// Dimensions are Rows, Cols, Depth
+#define BM_ContractionCPU(D1, D2, D3)                                         \
+  static void BM_##Contraction##_##D1##x##D2##x##D3(int iters, int Threads) { \
+    StopBenchmarkTiming();                                                    \
+    CREATE_THREAD_POOL(Threads);                                              \
+    BenchmarkSuite<Eigen::ThreadPoolDevice, float> suite(device, D1, D2, D3); \
+    suite.contraction(iters);                                                 \
+  }                                                                           \
+  BENCHMARK_RANGE(BM_##Contraction##_##D1##x##D2##x##D3, 1, 32);
+
+
+// Vector Matrix and Matrix Vector products
+BM_ContractionCPU(1, 2000, 500);
+BM_ContractionCPU(2000, 1, 500);
+
+// Various skinny matrices
+BM_ContractionCPU(250, 3, 512);
+BM_ContractionCPU(1500, 3, 512);
+
+BM_ContractionCPU(512, 800, 4);
+BM_ContractionCPU(512, 80, 800);
+BM_ContractionCPU(512, 80, 13522);
+BM_ContractionCPU(1, 80, 13522);
+
+BM_ContractionCPU(3200, 512, 4);
+BM_ContractionCPU(3200, 512, 80);
+BM_ContractionCPU(3200, 80, 512);

ADDED   3rd_party/eigen/bench/tensors/tensor_benchmarks.h
Index: 3rd_party/eigen/bench/tensors/tensor_benchmarks.h
==================================================================
--- 3rd_party/eigen/bench/tensors/tensor_benchmarks.h
+++ 3rd_party/eigen/bench/tensors/tensor_benchmarks.h
@@ -0,0 +1,478 @@
+#ifndef THIRD_PARTY_EIGEN3_TENSOR_BENCHMARKS_H_
+#define THIRD_PARTY_EIGEN3_TENSOR_BENCHMARKS_H_
+
+typedef int TensorIndex;
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+
+#include "unsupported/Eigen/CXX11/Tensor"
+#include "benchmark.h"
+
+#define BENCHMARK_RANGE(bench, lo, hi) \
+  BENCHMARK(bench)->Range(lo, hi)
+
+using Eigen::Tensor;
+using Eigen::TensorMap;
+
+// TODO(bsteiner): also templatize on the input type since we have users
+// for int8 as well as floats.
+template <typename Device, typename T> class BenchmarkSuite {
+ public:
+  BenchmarkSuite(const Device& device, size_t m, size_t k, size_t n)
+      : m_(m), k_(k), n_(n), device_(device) {
+    initialize();
+  }
+
+  BenchmarkSuite(const Device& device, size_t m)
+      : m_(m), k_(m), n_(m), device_(device) {
+    initialize();
+  }
+
+  ~BenchmarkSuite() {
+    device_.deallocate(a_);
+    device_.deallocate(b_);
+    device_.deallocate(c_);
+  }
+
+  void memcpy(int num_iters) {
+    eigen_assert(m_ == k_ && k_ == n_);
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
+    }
+    // Record the number of values copied per second
+    finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+  }
+
+  void typeCasting(int num_iters) {
+    eigen_assert(m_ == n_);
+    Eigen::array<TensorIndex, 2> sizes;
+    if (sizeof(T) >= sizeof(int)) {
+      sizes[0] = m_;
+      sizes[1] = k_;
+    } else {
+      sizes[0] = m_ * sizeof(T) / sizeof(int);
+      sizes[1] = k_ * sizeof(T) / sizeof(int);
+    }
+    const TensorMap<Tensor<int, 2, 0, TensorIndex>, Eigen::Aligned> A((int*)a_, sizes);
+    TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, sizes);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      B.device(device_) = A.template cast<T>();
+    }
+    // Record the number of values copied per second
+    finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+  }
+
+  void random(int num_iters) {
+    eigen_assert(m_ == k_ && k_ == n_);
+    Eigen::array<TensorIndex, 2> sizes;
+    sizes[0] = m_;
+    sizes[1] = m_;
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = C.random();
+    }
+    // Record the number of random numbers generated per second
+    finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+  }
+
+  void slicing(int num_iters) {
+    eigen_assert(m_ == k_ && k_ == n_);
+    Eigen::array<TensorIndex, 2> sizes;
+    sizes[0] = m_;
+    sizes[1] = m_;
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, sizes);
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
+
+    const Eigen::DSizes<TensorIndex, 2> quarter_sizes(m_/2, m_/2);
+    const Eigen::DSizes<TensorIndex, 2> first_quadrant(0, 0);
+    const Eigen::DSizes<TensorIndex, 2> second_quadrant(0, m_/2);
+    const Eigen::DSizes<TensorIndex, 2> third_quadrant(m_/2, 0);
+    const Eigen::DSizes<TensorIndex, 2> fourth_quadrant(m_/2, m_/2);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.slice(first_quadrant, quarter_sizes).device(device_) =
+          A.slice(first_quadrant, quarter_sizes);
+      C.slice(second_quadrant, quarter_sizes).device(device_) =
+          B.slice(second_quadrant, quarter_sizes);
+      C.slice(third_quadrant, quarter_sizes).device(device_) =
+          A.slice(third_quadrant, quarter_sizes);
+      C.slice(fourth_quadrant, quarter_sizes).device(device_) =
+          B.slice(fourth_quadrant, quarter_sizes);
+    }
+    // Record the number of values copied from the rhs slice to the lhs slice
+    // each second
+    finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+  }
+
+  void rowChip(int num_iters) {
+    Eigen::array<TensorIndex, 2> input_size;
+    input_size[0] = k_;
+    input_size[1] = n_;
+    const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
+    Eigen::array<TensorIndex, 1> output_size;
+    output_size[0] = n_;
+    TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = B.chip(iter % k_, 0);
+    }
+    // Record the number of values copied from the rhs chip to the lhs.
+    finalizeBenchmark(static_cast<int64_t>(n_) * num_iters);
+  }
+
+  void colChip(int num_iters) {
+    Eigen::array<TensorIndex, 2> input_size;
+    input_size[0] = k_;
+    input_size[1] = n_;
+    const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
+    Eigen::array<TensorIndex, 1> output_size;
+    output_size[0] = n_;
+    TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = B.chip(iter % n_, 1);
+    }
+    // Record the number of values copied from the rhs chip to the lhs.
+    finalizeBenchmark(static_cast<int64_t>(n_) * num_iters);
+  }
+
+  void shuffling(int num_iters) {
+    eigen_assert(m_ == n_);
+    Eigen::array<TensorIndex, 2> size_a;
+    size_a[0] = m_;
+    size_a[1] = k_;
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, size_a);
+    Eigen::array<TensorIndex, 2> size_b;
+    size_b[0] = k_;
+    size_b[1] = m_;
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, size_b);
+
+    Eigen::array<int, 2> shuffle;
+    shuffle[0] = 1;
+    shuffle[1] = 0;
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      B.device(device_) = A.shuffle(shuffle);
+    }
+    // Record the number of values shuffled from A and copied to B each second
+    finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+  }
+
+ void padding(int num_iters) {
+    eigen_assert(m_ == k_);
+    Eigen::array<TensorIndex, 2> size_a;
+    size_a[0] = m_;
+    size_a[1] = k_-3;
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, size_a);
+    Eigen::array<TensorIndex, 2> size_b;
+    size_b[0] = k_;
+    size_b[1] = m_;
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, size_b);
+
+#if defined(EIGEN_HAS_INDEX_LIST)
+    Eigen::IndexPairList<Eigen::type2indexpair<0, 0>,
+                         Eigen::type2indexpair<2, 1> > paddings;
+#else
+    Eigen::array<Eigen::IndexPair<TensorIndex>, 2> paddings;
+    paddings[0] = Eigen::IndexPair<TensorIndex>(0, 0);
+    paddings[1] = Eigen::IndexPair<TensorIndex>(2, 1);
+#endif
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      B.device(device_) = A.pad(paddings);
+    }
+    // Record the number of values copied from the padded tensor A each second
+    finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+  }
+
+ void striding(int num_iters) {
+    eigen_assert(m_ == k_);
+    Eigen::array<TensorIndex, 2> size_a;
+    size_a[0] = m_;
+    size_a[1] = k_;
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, size_a);
+    Eigen::array<TensorIndex, 2> size_b;
+    size_b[0] = m_;
+    size_b[1] = k_/2;
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, size_b);
+
+#ifndef EIGEN_HAS_INDEX_LIST
+    Eigen::array<TensorIndex, 2> strides;
+    strides[0] = 1;
+    strides[1] = 2;
+#else
+    // Take advantage of cxx11 to give the compiler information it can use to
+    // optimize the code.
+    Eigen::IndexList<Eigen::type2index<1>, Eigen::type2index<2> > strides;
+#endif
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      B.device(device_) = A.stride(strides);
+    }
+    // Record the number of values copied from the padded tensor A each second
+    finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+  }
+
+  void broadcasting(int num_iters) {
+    Eigen::array<TensorIndex, 2> size_a;
+    size_a[0] = m_;
+    size_a[1] = 1;
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, size_a);
+    Eigen::array<TensorIndex, 2> size_c;
+    size_c[0] = m_;
+    size_c[1] = n_;
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, size_c);
+
+#ifndef EIGEN_HAS_INDEX_LIST
+    Eigen::array<int, 2> broadcast;
+    broadcast[0] = 1;
+    broadcast[1] = n_;
+#else
+    // Take advantage of cxx11 to give the compiler information it can use to
+    // optimize the code.
+    Eigen::IndexList<Eigen::type2index<1>, int> broadcast;
+    broadcast.set(1, n_);
+#endif
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = A.broadcast(broadcast);
+    }
+    // Record the number of values broadcasted from A and copied to C each second
+    finalizeBenchmark(static_cast<int64_t>(m_) * n_ * num_iters);
+  }
+
+  void coeffWiseOp(int num_iters) {
+    eigen_assert(m_ == k_ && k_ == n_);
+    Eigen::array<TensorIndex, 2> sizes;
+    sizes[0] = m_;
+    sizes[1] = m_;
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, sizes);
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = A * A.constant(static_cast<T>(3.14)) + B * B.constant(static_cast<T>(2.7));
+    }
+    // Record the number of FLOP executed per second (2 multiplications and
+    // 1 addition per value)
+    finalizeBenchmark(static_cast<int64_t>(3) * m_ * m_ * num_iters);
+  }
+
+  void algebraicFunc(int num_iters) {
+    eigen_assert(m_ == k_ && k_ == n_);
+    Eigen::array<TensorIndex, 2> sizes;
+    sizes[0] = m_;
+    sizes[1] = m_;
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, sizes);
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
+    }
+    // Record the number of FLOP executed per second (assuming one operation
+    // per value)
+    finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+  }
+
+  void transcendentalFunc(int num_iters) {
+    eigen_assert(m_ == k_ && k_ == n_);
+    Eigen::array<TensorIndex, 2> sizes;
+    sizes[0] = m_;
+    sizes[1] = m_;
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, sizes);
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = A.exp() + B.log();
+    }
+    // Record the number of FLOP executed per second (assuming one operation
+    // per value)
+    finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+  }
+
+ // Row reduction
+  void rowReduction(int num_iters) {
+    Eigen::array<TensorIndex, 2> input_size;
+    input_size[0] = k_;
+    input_size[1] = n_;
+    const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
+    Eigen::array<TensorIndex, 1> output_size;
+    output_size[0] = n_;
+    TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
+
+#ifndef EIGEN_HAS_INDEX_LIST
+    Eigen::array<TensorIndex, 1> sum_along_dim;
+    sum_along_dim[0] = 0;
+#else
+    // Take advantage of cxx11 to give the compiler information it can use to
+    // optimize the code.
+    Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
+#endif
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = B.sum(sum_along_dim);
+    }
+    // Record the number of FLOP executed per second (assuming one operation
+    // per value)
+    finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+  }
+
+  // Column reduction
+  void colReduction(int num_iters) {
+    Eigen::array<TensorIndex, 2> input_size;
+    input_size[0] = k_;
+    input_size[1] = n_;
+    const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(
+        b_, input_size);
+    Eigen::array<TensorIndex, 1> output_size;
+    output_size[0] = k_;
+    TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(
+        c_, output_size);
+
+#ifndef EIGEN_HAS_INDEX_LIST
+    Eigen::array<TensorIndex, 1> sum_along_dim;
+    sum_along_dim[0] = 1;
+#else
+    // Take advantage of cxx11 to give the compiler information it can use to
+    // optimize the code.
+    Eigen::IndexList<Eigen::type2index<1>> sum_along_dim;
+#endif
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = B.sum(sum_along_dim);
+    }
+    // Record the number of FLOP executed per second (assuming one operation
+    // per value)
+    finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+  }
+
+  // Full reduction
+  void fullReduction(int num_iters) {
+    Eigen::array<TensorIndex, 2> input_size;
+    input_size[0] = k_;
+    input_size[1] = n_;
+    const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(
+        b_, input_size);
+    Eigen::array<TensorIndex, 0> output_size;
+    TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(
+        c_, output_size);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = B.sum();
+    }
+    // Record the number of FLOP executed per second (assuming one operation
+    // per value)
+    finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+  }
+
+  // do a contraction which is equivalent to a matrix multiplication
+  void contraction(int num_iters) {
+    Eigen::array<TensorIndex, 2> sizeA;
+    sizeA[0] = m_;
+    sizeA[1] = k_;
+    Eigen::array<TensorIndex, 2> sizeB;
+    sizeB[0] = k_;
+    sizeB[1] = n_;
+    Eigen::array<TensorIndex, 2> sizeC;
+    sizeC[0] = m_;
+    sizeC[1] = n_;
+
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, sizeA);
+    const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizeB);
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizeC);
+
+    typedef typename Tensor<T, 2>::DimensionPair DimPair;
+    Eigen::array<DimPair, 1> dims;
+    dims[0] = DimPair(1, 0);
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = A.contract(B, dims);
+    }
+    // Record the number of FLOP executed per second (size_ multiplications and
+    // additions for each value in the resulting tensor)
+    finalizeBenchmark(static_cast<int64_t>(2) * m_ * n_ * k_ * num_iters);
+  }
+
+  void convolution(int num_iters, int kernel_x, int kernel_y) {
+    Eigen::array<TensorIndex, 2> input_sizes;
+    input_sizes[0] = m_;
+    input_sizes[1] = n_;
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, input_sizes);
+    Eigen::array<TensorIndex, 2> kernel_sizes;
+    kernel_sizes[0] = kernel_x;
+    kernel_sizes[1] = kernel_y;
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, kernel_sizes);
+    Eigen::array<TensorIndex, 2> result_sizes;
+    result_sizes[0] = m_ - kernel_x + 1;
+    result_sizes[1] = n_ - kernel_y + 1;
+    TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, result_sizes);
+    Eigen::array<TensorIndex, 2> dims;
+    dims[0] = 0;
+    dims[1] = 1;
+
+    StartBenchmarkTiming();
+    for (int iter = 0; iter < num_iters; ++iter) {
+      C.device(device_) = A.convolve(B, dims);
+    }
+    // Record the number of FLOP executed per second (kernel_size
+    // multiplications and additions for each value in the resulting tensor)
+    finalizeBenchmark(static_cast<int64_t>(2) *
+        (m_ - kernel_x + 1) * (n_ - kernel_y + 1) * kernel_x * kernel_y * num_iters);
+  }
+
+ private:
+  void initialize() {
+    a_ = (T *) device_.allocate(m_ * k_ * sizeof(T));
+    b_ = (T *) device_.allocate(k_ * n_ * sizeof(T));
+    c_ = (T *) device_.allocate(m_ * n_ * sizeof(T));
+
+    // Initialize the content of the memory pools to prevent asan from
+    // complaining.
+    device_.memset(a_, 12, m_ * k_ * sizeof(T));
+    device_.memset(b_, 23, k_ * n_ * sizeof(T));
+    device_.memset(c_, 31, m_ * n_ * sizeof(T));
+
+    //BenchmarkUseRealTime();
+  }
+
+  inline void finalizeBenchmark(int64_t num_items) {
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+    if (Eigen::internal::is_same<Device, Eigen::GpuDevice>::value) {
+      device_.synchronize();
+    }
+#endif
+    StopBenchmarkTiming();
+    SetBenchmarkFlopsProcessed(num_items);
+  }
+
+
+  TensorIndex m_;
+  TensorIndex k_;
+  TensorIndex n_;
+  T* a_;
+  T* b_;
+  T* c_;
+  Device device_;
+};
+#endif  // THIRD_PARTY_EIGEN3_TENSOR_BENCHMARKS_H_

ADDED   3rd_party/eigen/bench/tensors/tensor_benchmarks_cpu.cc
Index: 3rd_party/eigen/bench/tensors/tensor_benchmarks_cpu.cc
==================================================================
--- 3rd_party/eigen/bench/tensors/tensor_benchmarks_cpu.cc
+++ 3rd_party/eigen/bench/tensors/tensor_benchmarks_cpu.cc
@@ -0,0 +1,168 @@
+#define EIGEN_USE_THREADS
+
+#include <string>
+
+#include "tensor_benchmarks.h"
+
+#define CREATE_THREAD_POOL(threads)             \
+Eigen::ThreadPool pool(threads);                \
+Eigen::ThreadPoolDevice device(&pool, threads);
+
+// Simple functions
+#define BM_FuncCPU(FUNC, THREADS)                                    \
+  static void BM_##FUNC##_##THREADS##T(int iters, int N) {           \
+    StopBenchmarkTiming();                                           \
+    CREATE_THREAD_POOL(THREADS);                                     \
+    BenchmarkSuite<Eigen::ThreadPoolDevice, float> suite(device, N); \
+    suite.FUNC(iters);                                               \
+  }                                                                  \
+  BENCHMARK_RANGE(BM_##FUNC##_##THREADS##T, 10, 5000);
+
+BM_FuncCPU(memcpy, 4);
+BM_FuncCPU(memcpy, 8);
+BM_FuncCPU(memcpy, 12);
+
+BM_FuncCPU(typeCasting, 4);
+BM_FuncCPU(typeCasting, 8);
+BM_FuncCPU(typeCasting, 12);
+
+BM_FuncCPU(random, 4);
+BM_FuncCPU(random, 8);
+BM_FuncCPU(random, 12);
+
+BM_FuncCPU(slicing, 4);
+BM_FuncCPU(slicing, 8);
+BM_FuncCPU(slicing, 12);
+
+BM_FuncCPU(rowChip, 4);
+BM_FuncCPU(rowChip, 8);
+BM_FuncCPU(rowChip, 12);
+
+BM_FuncCPU(colChip, 4);
+BM_FuncCPU(colChip, 8);
+BM_FuncCPU(colChip, 12);
+
+BM_FuncCPU(shuffling, 4);
+BM_FuncCPU(shuffling, 8);
+BM_FuncCPU(shuffling, 12);
+
+BM_FuncCPU(padding, 4);
+BM_FuncCPU(padding, 8);
+BM_FuncCPU(padding, 12);
+
+BM_FuncCPU(striding, 4);
+BM_FuncCPU(striding, 8);
+BM_FuncCPU(striding, 12);
+
+BM_FuncCPU(broadcasting, 4);
+BM_FuncCPU(broadcasting, 8);
+BM_FuncCPU(broadcasting, 12);
+
+BM_FuncCPU(coeffWiseOp, 4);
+BM_FuncCPU(coeffWiseOp, 8);
+BM_FuncCPU(coeffWiseOp, 12);
+
+BM_FuncCPU(algebraicFunc, 4);
+BM_FuncCPU(algebraicFunc, 8);
+BM_FuncCPU(algebraicFunc, 12);
+
+BM_FuncCPU(transcendentalFunc, 4);
+BM_FuncCPU(transcendentalFunc, 8);
+BM_FuncCPU(transcendentalFunc, 12);
+
+BM_FuncCPU(rowReduction, 4);
+BM_FuncCPU(rowReduction, 8);
+BM_FuncCPU(rowReduction, 12);
+
+BM_FuncCPU(colReduction, 4);
+BM_FuncCPU(colReduction, 8);
+BM_FuncCPU(colReduction, 12);
+
+
+// Contractions
+#define BM_FuncWithInputDimsCPU(FUNC, D1, D2, D3, THREADS)                      \
+  static void BM_##FUNC##_##D1##x##D2##x##D3##_##THREADS##T(int iters, int N) { \
+    StopBenchmarkTiming();                                                      \
+    if (THREADS == 1) {                                                         \
+      Eigen::DefaultDevice device;                                              \
+      BenchmarkSuite<Eigen::DefaultDevice, float> suite(device, D1, D2, D3);    \
+      suite.FUNC(iters);                                                        \
+    } else {                                                                    \
+      CREATE_THREAD_POOL(THREADS);                                              \
+      BenchmarkSuite<Eigen::ThreadPoolDevice, float> suite(device, D1, D2, D3); \
+      suite.FUNC(iters);                                                        \
+    }                                                                           \
+  }                                                                             \
+  BENCHMARK_RANGE(BM_##FUNC##_##D1##x##D2##x##D3##_##THREADS##T, 10, 5000);
+
+
+BM_FuncWithInputDimsCPU(contraction, N, N, N, 1);
+BM_FuncWithInputDimsCPU(contraction, N, N, N, 4);
+BM_FuncWithInputDimsCPU(contraction, N, N, N, 8);
+BM_FuncWithInputDimsCPU(contraction, N, N, N, 12);
+BM_FuncWithInputDimsCPU(contraction, N, N, N, 16);
+
+BM_FuncWithInputDimsCPU(contraction, 64, N, N, 1);
+BM_FuncWithInputDimsCPU(contraction, 64, N, N, 4);
+BM_FuncWithInputDimsCPU(contraction, 64, N, N, 8);
+BM_FuncWithInputDimsCPU(contraction, 64, N, N, 12);
+BM_FuncWithInputDimsCPU(contraction, 64, N, N, 16);
+
+BM_FuncWithInputDimsCPU(contraction, N, 64, N, 1);
+BM_FuncWithInputDimsCPU(contraction, N, 64, N, 4);
+BM_FuncWithInputDimsCPU(contraction, N, 64, N, 8);
+BM_FuncWithInputDimsCPU(contraction, N, 64, N, 12);
+BM_FuncWithInputDimsCPU(contraction, N, 64, N, 16);
+
+BM_FuncWithInputDimsCPU(contraction, N, N, 64, 1);
+BM_FuncWithInputDimsCPU(contraction, N, N, 64, 4);
+BM_FuncWithInputDimsCPU(contraction, N, N, 64, 8);
+BM_FuncWithInputDimsCPU(contraction, N, N, 64, 12);
+BM_FuncWithInputDimsCPU(contraction, N, N, 64, 16);
+
+BM_FuncWithInputDimsCPU(contraction, 1, N, N, 1);
+BM_FuncWithInputDimsCPU(contraction, 1, N, N, 4);
+BM_FuncWithInputDimsCPU(contraction, 1, N, N, 8);
+BM_FuncWithInputDimsCPU(contraction, 1, N, N, 12);
+BM_FuncWithInputDimsCPU(contraction, 1, N, N, 16);
+
+BM_FuncWithInputDimsCPU(contraction, N, N, 1, 1);
+BM_FuncWithInputDimsCPU(contraction, N, N, 1, 4);
+BM_FuncWithInputDimsCPU(contraction, N, N, 1, 8);
+BM_FuncWithInputDimsCPU(contraction, N, N, 1, 12);
+BM_FuncWithInputDimsCPU(contraction, N, N, 1, 16);
+
+
+// Convolutions
+#define BM_FuncWithKernelDimsCPU(FUNC, DIM1, DIM2, THREADS)                    \
+  static void BM_##FUNC##_##DIM1##x##DIM2##_##THREADS##T(int iters, int N) {   \
+    StopBenchmarkTiming();                                                     \
+    CREATE_THREAD_POOL(THREADS);                                               \
+    BenchmarkSuite<Eigen::ThreadPoolDevice, float> suite(device, N);	       \
+    suite.FUNC(iters, DIM1, DIM2);                                             \
+  }                                                                            \
+  BENCHMARK_RANGE(BM_##FUNC##_##DIM1##x##DIM2##_##THREADS##T, 128, 5000);
+
+BM_FuncWithKernelDimsCPU(convolution, 7, 1, 4);
+BM_FuncWithKernelDimsCPU(convolution, 7, 1, 8);
+BM_FuncWithKernelDimsCPU(convolution, 7, 1, 12);
+
+BM_FuncWithKernelDimsCPU(convolution, 1, 7, 4);
+BM_FuncWithKernelDimsCPU(convolution, 1, 7, 8);
+BM_FuncWithKernelDimsCPU(convolution, 1, 7, 12);
+
+BM_FuncWithKernelDimsCPU(convolution, 7, 4, 4);
+BM_FuncWithKernelDimsCPU(convolution, 7, 4, 8);
+BM_FuncWithKernelDimsCPU(convolution, 7, 4, 12);
+
+BM_FuncWithKernelDimsCPU(convolution, 4, 7, 4);
+BM_FuncWithKernelDimsCPU(convolution, 4, 7, 8);
+BM_FuncWithKernelDimsCPU(convolution, 4, 7, 12);
+
+BM_FuncWithKernelDimsCPU(convolution, 7, 64, 4);
+BM_FuncWithKernelDimsCPU(convolution, 7, 64, 8);
+BM_FuncWithKernelDimsCPU(convolution, 7, 64, 12);
+
+BM_FuncWithKernelDimsCPU(convolution, 64, 7, 4);
+BM_FuncWithKernelDimsCPU(convolution, 64, 7, 8);
+BM_FuncWithKernelDimsCPU(convolution, 64, 7, 12);

ADDED   3rd_party/eigen/bench/tensors/tensor_benchmarks_fp16_gpu.cu
Index: 3rd_party/eigen/bench/tensors/tensor_benchmarks_fp16_gpu.cu
==================================================================
--- 3rd_party/eigen/bench/tensors/tensor_benchmarks_fp16_gpu.cu
+++ 3rd_party/eigen/bench/tensors/tensor_benchmarks_fp16_gpu.cu
@@ -0,0 +1,77 @@
+#define EIGEN_USE_GPU
+
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <iostream>
+
+#include "tensor_benchmarks.h"
+
+// Simple functions
+#define BM_FuncGPU(FUNC)                                                       \
+  static void BM_##FUNC(int iters, int N) {                                    \
+    StopBenchmarkTiming();                                                     \
+    Eigen::CudaStreamDevice stream;                                            \
+    Eigen::GpuDevice device(&stream);                                          \
+    BenchmarkSuite<Eigen::GpuDevice, Eigen::half> suite(device, N);            \
+    cudaDeviceSynchronize();                                                   \
+    suite.FUNC(iters);                                                         \
+  }                                                                            \
+  BENCHMARK_RANGE(BM_##FUNC, 10, 5000);
+
+BM_FuncGPU(memcpy);
+BM_FuncGPU(typeCasting);
+//BM_FuncGPU(random);
+BM_FuncGPU(slicing);
+BM_FuncGPU(rowChip);
+BM_FuncGPU(colChip);
+BM_FuncGPU(shuffling);
+BM_FuncGPU(padding);
+BM_FuncGPU(striding);
+BM_FuncGPU(broadcasting);
+BM_FuncGPU(coeffWiseOp);
+BM_FuncGPU(algebraicFunc);
+BM_FuncGPU(transcendentalFunc);
+BM_FuncGPU(rowReduction);
+BM_FuncGPU(colReduction);
+BM_FuncGPU(fullReduction);
+
+
+// Contractions
+#define BM_FuncWithInputDimsGPU(FUNC, D1, D2, D3)                              \
+  static void BM_##FUNC##_##D1##x##D2##x##D3(int iters, int N) {               \
+    StopBenchmarkTiming();                                                     \
+    Eigen::CudaStreamDevice stream;                                            \
+    Eigen::GpuDevice device(&stream);                                          \
+    BenchmarkSuite<Eigen::GpuDevice, Eigen::half> suite(device, D1, D2, D3);   \
+    cudaDeviceSynchronize();                                                   \
+    suite.FUNC(iters);                                                         \
+  }                                                                            \
+  BENCHMARK_RANGE(BM_##FUNC##_##D1##x##D2##x##D3, 10, 5000);
+
+
+BM_FuncWithInputDimsGPU(contraction, N, N, N);
+BM_FuncWithInputDimsGPU(contraction, 64, N, N);
+BM_FuncWithInputDimsGPU(contraction, N, 64, N);
+BM_FuncWithInputDimsGPU(contraction, N, N, 64);
+
+
+// Convolutions
+#define BM_FuncWithKernelDimsGPU(FUNC, DIM1, DIM2)                             \
+  static void BM_##FUNC##_##DIM1##x##DIM2(int iters, int N) {                  \
+    StopBenchmarkTiming();                                                     \
+    Eigen::CudaStreamDevice stream;                                            \
+    Eigen::GpuDevice device(&stream);                                          \
+    BenchmarkSuite<Eigen::GpuDevice, Eigen::half> suite(device, N);            \
+    cudaDeviceSynchronize();                                                   \
+    suite.FUNC(iters, DIM1, DIM2);                                             \
+  }                                                                            \
+  BENCHMARK_RANGE(BM_##FUNC##_##DIM1##x##DIM2, 128, 5000);
+
+/*
+BM_FuncWithKernelDimsGPU(convolution, 7, 1);
+BM_FuncWithKernelDimsGPU(convolution, 1, 7);
+BM_FuncWithKernelDimsGPU(convolution, 7, 4);
+BM_FuncWithKernelDimsGPU(convolution, 4, 7);
+BM_FuncWithKernelDimsGPU(convolution, 7, 64);
+BM_FuncWithKernelDimsGPU(convolution, 64, 7);
+*/

ADDED   3rd_party/eigen/bench/tensors/tensor_benchmarks_gpu.cu
Index: 3rd_party/eigen/bench/tensors/tensor_benchmarks_gpu.cu
==================================================================
--- 3rd_party/eigen/bench/tensors/tensor_benchmarks_gpu.cu
+++ 3rd_party/eigen/bench/tensors/tensor_benchmarks_gpu.cu
@@ -0,0 +1,75 @@
+#define EIGEN_USE_GPU
+
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <iostream>
+
+#include "tensor_benchmarks.h"
+
+// Simple functions
+#define BM_FuncGPU(FUNC)                                                       \
+  static void BM_##FUNC(int iters, int N) {                                    \
+    StopBenchmarkTiming();                                                     \
+    Eigen::CudaStreamDevice stream;                                            \
+    Eigen::GpuDevice device(&stream);                                          \
+    BenchmarkSuite<Eigen::GpuDevice, float> suite(device, N);                  \
+    cudaDeviceSynchronize();                                                   \
+    suite.FUNC(iters);                                                         \
+  }                                                                            \
+  BENCHMARK_RANGE(BM_##FUNC, 10, 5000);
+
+BM_FuncGPU(memcpy);
+BM_FuncGPU(typeCasting);
+BM_FuncGPU(random);
+BM_FuncGPU(slicing);
+BM_FuncGPU(rowChip);
+BM_FuncGPU(colChip);
+BM_FuncGPU(shuffling);
+BM_FuncGPU(padding);
+BM_FuncGPU(striding);
+BM_FuncGPU(broadcasting);
+BM_FuncGPU(coeffWiseOp);
+BM_FuncGPU(algebraicFunc);
+BM_FuncGPU(transcendentalFunc);
+BM_FuncGPU(rowReduction);
+BM_FuncGPU(colReduction);
+BM_FuncGPU(fullReduction);
+
+
+// Contractions
+#define BM_FuncWithInputDimsGPU(FUNC, D1, D2, D3)                              \
+  static void BM_##FUNC##_##D1##x##D2##x##D3(int iters, int N) {               \
+    StopBenchmarkTiming();                                                     \
+    Eigen::CudaStreamDevice stream;                                            \
+    Eigen::GpuDevice device(&stream);                                          \
+    BenchmarkSuite<Eigen::GpuDevice, float> suite(device, D1, D2, D3);         \
+    cudaDeviceSynchronize();                                                   \
+    suite.FUNC(iters);                                                         \
+  }                                                                            \
+  BENCHMARK_RANGE(BM_##FUNC##_##D1##x##D2##x##D3, 10, 5000);
+
+
+BM_FuncWithInputDimsGPU(contraction, N, N, N);
+BM_FuncWithInputDimsGPU(contraction, 64, N, N);
+BM_FuncWithInputDimsGPU(contraction, N, 64, N);
+BM_FuncWithInputDimsGPU(contraction, N, N, 64);
+
+
+// Convolutions
+#define BM_FuncWithKernelDimsGPU(FUNC, DIM1, DIM2)                             \
+  static void BM_##FUNC##_##DIM1##x##DIM2(int iters, int N) {                  \
+    StopBenchmarkTiming();                                                     \
+    Eigen::CudaStreamDevice stream;                                            \
+    Eigen::GpuDevice device(&stream);                                          \
+    BenchmarkSuite<Eigen::GpuDevice, float> suite(device, N);                  \
+    cudaDeviceSynchronize();                                                   \
+    suite.FUNC(iters, DIM1, DIM2);                                             \
+  }                                                                            \
+  BENCHMARK_RANGE(BM_##FUNC##_##DIM1##x##DIM2, 128, 5000);
+
+BM_FuncWithKernelDimsGPU(convolution, 7, 1);
+BM_FuncWithKernelDimsGPU(convolution, 1, 7);
+BM_FuncWithKernelDimsGPU(convolution, 7, 4);
+BM_FuncWithKernelDimsGPU(convolution, 4, 7);
+BM_FuncWithKernelDimsGPU(convolution, 7, 64);
+BM_FuncWithKernelDimsGPU(convolution, 64, 7);

ADDED   3rd_party/eigen/bench/tensors/tensor_benchmarks_sycl.cc
Index: 3rd_party/eigen/bench/tensors/tensor_benchmarks_sycl.cc
==================================================================
--- 3rd_party/eigen/bench/tensors/tensor_benchmarks_sycl.cc
+++ 3rd_party/eigen/bench/tensors/tensor_benchmarks_sycl.cc
@@ -0,0 +1,37 @@
+#define EIGEN_USE_SYCL
+
+#include <SYCL/sycl.hpp>
+#include <iostream>
+
+#include "tensor_benchmarks.h"
+
+using Eigen::array;
+using Eigen::SyclDevice;
+using Eigen::Tensor;
+using Eigen::TensorMap;
+// Simple functions
+template <typename device_selector>
+cl::sycl::queue sycl_queue() {
+  return cl::sycl::queue(device_selector(), [=](cl::sycl::exception_list l) {
+    for (const auto& e : l) {
+      try {
+        std::rethrow_exception(e);
+      } catch (cl::sycl::exception e) {
+        std::cout << e.what() << std::endl;
+      }
+    }
+  });
+}
+
+#define BM_FuncGPU(FUNC)                                       \
+  static void BM_##FUNC(int iters, int N) {                    \
+    StopBenchmarkTiming();                                     \
+    cl::sycl::queue q = sycl_queue<cl::sycl::gpu_selector>();  \
+    Eigen::SyclDevice device(q);                               \
+    BenchmarkSuite<Eigen::SyclDevice, float> suite(device, N); \
+    suite.FUNC(iters);                                         \
+  }                                                            \
+  BENCHMARK_RANGE(BM_##FUNC, 10, 5000);
+
+BM_FuncGPU(broadcasting);
+BM_FuncGPU(coeffWiseOp);

Index: 3rd_party/eigen/blas/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/blas/CMakeLists.txt
+++ 3rd_party/eigen/blas/CMakeLists.txt
@@ -12,27 +12,22 @@
   endif()
 endif()
 
 add_custom_target(blas)
 
-set(EigenBlas_SRCS single.cpp double.cpp complex_single.cpp complex_double.cpp xerbla.cpp)
-
-if(EIGEN_Fortran_COMPILER_WORKS)
-
-set(EigenBlas_SRCS ${EigenBlas_SRCS}
-    complexdots.f
-    srotm.f srotmg.f drotm.f drotmg.f
-    lsame.f  dspmv.f ssbmv.f
-    chbmv.f  sspmv.f
-    zhbmv.f  chpmv.f dsbmv.f
-    zhpmv.f
-    dtbmv.f stbmv.f ctbmv.f ztbmv.f
-)
+set(EigenBlas_SRCS  single.cpp double.cpp complex_single.cpp complex_double.cpp xerbla.cpp
+                    f2c/srotm.c   f2c/srotmg.c  f2c/drotm.c f2c/drotmg.c
+                    f2c/lsame.c   f2c/dspmv.c   f2c/ssbmv.c f2c/chbmv.c
+                    f2c/sspmv.c   f2c/zhbmv.c   f2c/chpmv.c f2c/dsbmv.c
+                    f2c/zhpmv.c   f2c/dtbmv.c   f2c/stbmv.c f2c/ctbmv.c
+                    f2c/ztbmv.c   f2c/d_cnjg.c  f2c/r_cnjg.c
+   )
+
+if (EIGEN_Fortran_COMPILER_WORKS)
+  set(EigenBlas_SRCS ${EigenBlas_SRCS} fortran/complexdots.f)
 else()
-
-message(WARNING " No fortran compiler has been detected, the blas build will be incomplete.")
-
+  set(EigenBlas_SRCS ${EigenBlas_SRCS} f2c/complexdots.c)
 endif()
 
 add_library(eigen_blas_static ${EigenBlas_SRCS})
 add_library(eigen_blas SHARED ${EigenBlas_SRCS})
 

Index: 3rd_party/eigen/blas/PackedTriangularMatrixVector.h
==================================================================
--- 3rd_party/eigen/blas/PackedTriangularMatrixVector.h
+++ 3rd_party/eigen/blas/PackedTriangularMatrixVector.h
@@ -16,11 +16,11 @@
 struct packed_triangular_matrix_vector_product;
 
 template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
 struct packed_triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor>
 {
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   enum {
     IsLower     = (Mode & Lower)   ==Lower,
     HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
     HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
   };
@@ -45,11 +45,11 @@
 };
 
 template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
 struct packed_triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor>
 {
-  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   enum {
     IsLower     = (Mode & Lower)   ==Lower,
     HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
     HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
   };

DELETED 3rd_party/eigen/blas/chbmv.f
Index: 3rd_party/eigen/blas/chbmv.f
==================================================================
--- 3rd_party/eigen/blas/chbmv.f
+++ 3rd_party/eigen/blas/chbmv.f
@@ -1,310 +0,0 @@
-      SUBROUTINE CHBMV(UPLO,N,K,ALPHA,A,LDA,X,INCX,BETA,Y,INCY)
-*     .. Scalar Arguments ..
-      COMPLEX ALPHA,BETA
-      INTEGER INCX,INCY,K,LDA,N
-      CHARACTER UPLO
-*     ..
-*     .. Array Arguments ..
-      COMPLEX A(LDA,*),X(*),Y(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  CHBMV  performs the matrix-vector  operation
-*
-*     y := alpha*A*x + beta*y,
-*
-*  where alpha and beta are scalars, x and y are n element vectors and
-*  A is an n by n hermitian band matrix, with k super-diagonals.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the upper or lower
-*           triangular part of the band matrix A is being supplied as
-*           follows:
-*
-*              UPLO = 'U' or 'u'   The upper triangular part of A is
-*                                  being supplied.
-*
-*              UPLO = 'L' or 'l'   The lower triangular part of A is
-*                                  being supplied.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  K      - INTEGER.
-*           On entry, K specifies the number of super-diagonals of the
-*           matrix A. K must satisfy  0 .le. K.
-*           Unchanged on exit.
-*
-*  ALPHA  - COMPLEX         .
-*           On entry, ALPHA specifies the scalar alpha.
-*           Unchanged on exit.
-*
-*  A      - COMPLEX          array of DIMENSION ( LDA, n ).
-*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 )
-*           by n part of the array A must contain the upper triangular
-*           band part of the hermitian matrix, supplied column by
-*           column, with the leading diagonal of the matrix in row
-*           ( k + 1 ) of the array, the first super-diagonal starting at
-*           position 2 in row k, and so on. The top left k by k triangle
-*           of the array A is not referenced.
-*           The following program segment will transfer the upper
-*           triangular part of a hermitian band matrix from conventional
-*           full matrix storage to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = K + 1 - J
-*                    DO 10, I = MAX( 1, J - K ), J
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 )
-*           by n part of the array A must contain the lower triangular
-*           band part of the hermitian matrix, supplied column by
-*           column, with the leading diagonal of the matrix in row 1 of
-*           the array, the first sub-diagonal starting at position 1 in
-*           row 2, and so on. The bottom right k by k triangle of the
-*           array A is not referenced.
-*           The following program segment will transfer the lower
-*           triangular part of a hermitian band matrix from conventional
-*           full matrix storage to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = 1 - J
-*                    DO 10, I = J, MIN( N, J + K )
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Note that the imaginary parts of the diagonal elements need
-*           not be set and are assumed to be zero.
-*           Unchanged on exit.
-*
-*  LDA    - INTEGER.
-*           On entry, LDA specifies the first dimension of A as declared
-*           in the calling (sub) program. LDA must be at least
-*           ( k + 1 ).
-*           Unchanged on exit.
-*
-*  X      - COMPLEX          array of DIMENSION at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the
-*           vector x.
-*           Unchanged on exit.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  BETA   - COMPLEX         .
-*           On entry, BETA specifies the scalar beta.
-*           Unchanged on exit.
-*
-*  Y      - COMPLEX          array of DIMENSION at least
-*           ( 1 + ( n - 1 )*abs( INCY ) ).
-*           Before entry, the incremented array Y must contain the
-*           vector y. On exit, Y is overwritten by the updated vector y.
-*
-*  INCY   - INTEGER.
-*           On entry, INCY specifies the increment for the elements of
-*           Y. INCY must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      COMPLEX ONE
-      PARAMETER (ONE= (1.0E+0,0.0E+0))
-      COMPLEX ZERO
-      PARAMETER (ZERO= (0.0E+0,0.0E+0))
-*     ..
-*     .. Local Scalars ..
-      COMPLEX TEMP1,TEMP2
-      INTEGER I,INFO,IX,IY,J,JX,JY,KPLUS1,KX,KY,L
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC CONJG,MAX,MIN,REAL
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (N.LT.0) THEN
-          INFO = 2
-      ELSE IF (K.LT.0) THEN
-          INFO = 3
-      ELSE IF (LDA.LT. (K+1)) THEN
-          INFO = 6
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 8
-      ELSE IF (INCY.EQ.0) THEN
-          INFO = 11
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('CHBMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF ((N.EQ.0) .OR. ((ALPHA.EQ.ZERO).AND. (BETA.EQ.ONE))) RETURN
-*
-*     Set up the start points in  X  and  Y.
-*
-      IF (INCX.GT.0) THEN
-          KX = 1
-      ELSE
-          KX = 1 - (N-1)*INCX
-      END IF
-      IF (INCY.GT.0) THEN
-          KY = 1
-      ELSE
-          KY = 1 - (N-1)*INCY
-      END IF
-*
-*     Start the operations. In this version the elements of the array A
-*     are accessed sequentially with one pass through A.
-*
-*     First form  y := beta*y.
-*
-      IF (BETA.NE.ONE) THEN
-          IF (INCY.EQ.1) THEN
-              IF (BETA.EQ.ZERO) THEN
-                  DO 10 I = 1,N
-                      Y(I) = ZERO
-   10             CONTINUE
-              ELSE
-                  DO 20 I = 1,N
-                      Y(I) = BETA*Y(I)
-   20             CONTINUE
-              END IF
-          ELSE
-              IY = KY
-              IF (BETA.EQ.ZERO) THEN
-                  DO 30 I = 1,N
-                      Y(IY) = ZERO
-                      IY = IY + INCY
-   30             CONTINUE
-              ELSE
-                  DO 40 I = 1,N
-                      Y(IY) = BETA*Y(IY)
-                      IY = IY + INCY
-   40             CONTINUE
-              END IF
-          END IF
-      END IF
-      IF (ALPHA.EQ.ZERO) RETURN
-      IF (LSAME(UPLO,'U')) THEN
-*
-*        Form  y  when upper triangle of A is stored.
-*
-          KPLUS1 = K + 1
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 60 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  L = KPLUS1 - J
-                  DO 50 I = MAX(1,J-K),J - 1
-                      Y(I) = Y(I) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + CONJG(A(L+I,J))*X(I)
-   50             CONTINUE
-                  Y(J) = Y(J) + TEMP1*REAL(A(KPLUS1,J)) + ALPHA*TEMP2
-   60         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 80 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  IX = KX
-                  IY = KY
-                  L = KPLUS1 - J
-                  DO 70 I = MAX(1,J-K),J - 1
-                      Y(IY) = Y(IY) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + CONJG(A(L+I,J))*X(IX)
-                      IX = IX + INCX
-                      IY = IY + INCY
-   70             CONTINUE
-                  Y(JY) = Y(JY) + TEMP1*REAL(A(KPLUS1,J)) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  IF (J.GT.K) THEN
-                      KX = KX + INCX
-                      KY = KY + INCY
-                  END IF
-   80         CONTINUE
-          END IF
-      ELSE
-*
-*        Form  y  when lower triangle of A is stored.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 100 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  Y(J) = Y(J) + TEMP1*REAL(A(1,J))
-                  L = 1 - J
-                  DO 90 I = J + 1,MIN(N,J+K)
-                      Y(I) = Y(I) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + CONJG(A(L+I,J))*X(I)
-   90             CONTINUE
-                  Y(J) = Y(J) + ALPHA*TEMP2
-  100         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 120 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  Y(JY) = Y(JY) + TEMP1*REAL(A(1,J))
-                  L = 1 - J
-                  IX = JX
-                  IY = JY
-                  DO 110 I = J + 1,MIN(N,J+K)
-                      IX = IX + INCX
-                      IY = IY + INCY
-                      Y(IY) = Y(IY) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + CONJG(A(L+I,J))*X(IX)
-  110             CONTINUE
-                  Y(JY) = Y(JY) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-  120         CONTINUE
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of CHBMV .
-*
-      END

DELETED 3rd_party/eigen/blas/chpmv.f
Index: 3rd_party/eigen/blas/chpmv.f
==================================================================
--- 3rd_party/eigen/blas/chpmv.f
+++ 3rd_party/eigen/blas/chpmv.f
@@ -1,272 +0,0 @@
-      SUBROUTINE CHPMV(UPLO,N,ALPHA,AP,X,INCX,BETA,Y,INCY)
-*     .. Scalar Arguments ..
-      COMPLEX ALPHA,BETA
-      INTEGER INCX,INCY,N
-      CHARACTER UPLO
-*     ..
-*     .. Array Arguments ..
-      COMPLEX AP(*),X(*),Y(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  CHPMV  performs the matrix-vector operation
-*
-*     y := alpha*A*x + beta*y,
-*
-*  where alpha and beta are scalars, x and y are n element vectors and
-*  A is an n by n hermitian matrix, supplied in packed form.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the upper or lower
-*           triangular part of the matrix A is supplied in the packed
-*           array AP as follows:
-*
-*              UPLO = 'U' or 'u'   The upper triangular part of A is
-*                                  supplied in AP.
-*
-*              UPLO = 'L' or 'l'   The lower triangular part of A is
-*                                  supplied in AP.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  ALPHA  - COMPLEX         .
-*           On entry, ALPHA specifies the scalar alpha.
-*           Unchanged on exit.
-*
-*  AP     - COMPLEX          array of DIMENSION at least
-*           ( ( n*( n + 1 ) )/2 ).
-*           Before entry with UPLO = 'U' or 'u', the array AP must
-*           contain the upper triangular part of the hermitian matrix
-*           packed sequentially, column by column, so that AP( 1 )
-*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-*           and a( 2, 2 ) respectively, and so on.
-*           Before entry with UPLO = 'L' or 'l', the array AP must
-*           contain the lower triangular part of the hermitian matrix
-*           packed sequentially, column by column, so that AP( 1 )
-*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-*           and a( 3, 1 ) respectively, and so on.
-*           Note that the imaginary parts of the diagonal elements need
-*           not be set and are assumed to be zero.
-*           Unchanged on exit.
-*
-*  X      - COMPLEX          array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the n
-*           element vector x.
-*           Unchanged on exit.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  BETA   - COMPLEX         .
-*           On entry, BETA specifies the scalar beta. When BETA is
-*           supplied as zero then Y need not be set on input.
-*           Unchanged on exit.
-*
-*  Y      - COMPLEX          array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCY ) ).
-*           Before entry, the incremented array Y must contain the n
-*           element vector y. On exit, Y is overwritten by the updated
-*           vector y.
-*
-*  INCY   - INTEGER.
-*           On entry, INCY specifies the increment for the elements of
-*           Y. INCY must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      COMPLEX ONE
-      PARAMETER (ONE= (1.0E+0,0.0E+0))
-      COMPLEX ZERO
-      PARAMETER (ZERO= (0.0E+0,0.0E+0))
-*     ..
-*     .. Local Scalars ..
-      COMPLEX TEMP1,TEMP2
-      INTEGER I,INFO,IX,IY,J,JX,JY,K,KK,KX,KY
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC CONJG,REAL
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (N.LT.0) THEN
-          INFO = 2
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 6
-      ELSE IF (INCY.EQ.0) THEN
-          INFO = 9
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('CHPMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF ((N.EQ.0) .OR. ((ALPHA.EQ.ZERO).AND. (BETA.EQ.ONE))) RETURN
-*
-*     Set up the start points in  X  and  Y.
-*
-      IF (INCX.GT.0) THEN
-          KX = 1
-      ELSE
-          KX = 1 - (N-1)*INCX
-      END IF
-      IF (INCY.GT.0) THEN
-          KY = 1
-      ELSE
-          KY = 1 - (N-1)*INCY
-      END IF
-*
-*     Start the operations. In this version the elements of the array AP
-*     are accessed sequentially with one pass through AP.
-*
-*     First form  y := beta*y.
-*
-      IF (BETA.NE.ONE) THEN
-          IF (INCY.EQ.1) THEN
-              IF (BETA.EQ.ZERO) THEN
-                  DO 10 I = 1,N
-                      Y(I) = ZERO
-   10             CONTINUE
-              ELSE
-                  DO 20 I = 1,N
-                      Y(I) = BETA*Y(I)
-   20             CONTINUE
-              END IF
-          ELSE
-              IY = KY
-              IF (BETA.EQ.ZERO) THEN
-                  DO 30 I = 1,N
-                      Y(IY) = ZERO
-                      IY = IY + INCY
-   30             CONTINUE
-              ELSE
-                  DO 40 I = 1,N
-                      Y(IY) = BETA*Y(IY)
-                      IY = IY + INCY
-   40             CONTINUE
-              END IF
-          END IF
-      END IF
-      IF (ALPHA.EQ.ZERO) RETURN
-      KK = 1
-      IF (LSAME(UPLO,'U')) THEN
-*
-*        Form  y  when AP contains the upper triangle.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 60 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  K = KK
-                  DO 50 I = 1,J - 1
-                      Y(I) = Y(I) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + CONJG(AP(K))*X(I)
-                      K = K + 1
-   50             CONTINUE
-                  Y(J) = Y(J) + TEMP1*REAL(AP(KK+J-1)) + ALPHA*TEMP2
-                  KK = KK + J
-   60         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 80 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  IX = KX
-                  IY = KY
-                  DO 70 K = KK,KK + J - 2
-                      Y(IY) = Y(IY) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + CONJG(AP(K))*X(IX)
-                      IX = IX + INCX
-                      IY = IY + INCY
-   70             CONTINUE
-                  Y(JY) = Y(JY) + TEMP1*REAL(AP(KK+J-1)) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  KK = KK + J
-   80         CONTINUE
-          END IF
-      ELSE
-*
-*        Form  y  when AP contains the lower triangle.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 100 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  Y(J) = Y(J) + TEMP1*REAL(AP(KK))
-                  K = KK + 1
-                  DO 90 I = J + 1,N
-                      Y(I) = Y(I) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + CONJG(AP(K))*X(I)
-                      K = K + 1
-   90             CONTINUE
-                  Y(J) = Y(J) + ALPHA*TEMP2
-                  KK = KK + (N-J+1)
-  100         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 120 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  Y(JY) = Y(JY) + TEMP1*REAL(AP(KK))
-                  IX = JX
-                  IY = JY
-                  DO 110 K = KK + 1,KK + N - J
-                      IX = IX + INCX
-                      IY = IY + INCY
-                      Y(IY) = Y(IY) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + CONJG(AP(K))*X(IX)
-  110             CONTINUE
-                  Y(JY) = Y(JY) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  KK = KK + (N-J+1)
-  120         CONTINUE
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of CHPMV .
-*
-      END

Index: 3rd_party/eigen/blas/common.h
==================================================================
--- 3rd_party/eigen/blas/common.h
+++ 3rd_party/eigen/blas/common.h
@@ -1,29 +1,27 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_BLAS_COMMON_H
 #define EIGEN_BLAS_COMMON_H
 
-#include <Eigen/Core>
-#include <Eigen/Jacobi>
+#include "../Eigen/Core"
+#include "../Eigen/Jacobi"
 
-#include <iostream>
 #include <complex>
 
 #ifndef SCALAR
 #error the token SCALAR must be defined to compile this file
 #endif
 
-#include <Eigen/src/misc/blas.h>
-
+#include "../Eigen/src/misc/blas.h"
 
 #define NOTR    0
 #define TR      1
 #define ADJ     2
 
@@ -93,10 +91,11 @@
   Conj = IsComplex
 };
 
 typedef Matrix<Scalar,Dynamic,Dynamic,ColMajor> PlainMatrixType;
 typedef Map<Matrix<Scalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > MatrixType;
+typedef Map<const Matrix<Scalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > ConstMatrixType;
 typedef Map<Matrix<Scalar,Dynamic,1>, 0, InnerStride<Dynamic> > StridedVectorType;
 typedef Map<Matrix<Scalar,Dynamic,1> > CompactVectorType;
 
 template<typename T>
 Map<Matrix<T,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> >
@@ -104,42 +103,61 @@
 {
   return Map<Matrix<T,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> >(data, rows, cols, OuterStride<>(stride));
 }
 
 template<typename T>
-Map<Matrix<T,Dynamic,1>, 0, InnerStride<Dynamic> > vector(T* data, int size, int incr)
+Map<const Matrix<T,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> >
+matrix(const T* data, int rows, int cols, int stride)
+{
+  return Map<const Matrix<T,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> >(data, rows, cols, OuterStride<>(stride));
+}
+
+template<typename T>
+Map<Matrix<T,Dynamic,1>, 0, InnerStride<Dynamic> > make_vector(T* data, int size, int incr)
 {
   return Map<Matrix<T,Dynamic,1>, 0, InnerStride<Dynamic> >(data, size, InnerStride<Dynamic>(incr));
 }
 
 template<typename T>
-Map<Matrix<T,Dynamic,1> > vector(T* data, int size)
+Map<const Matrix<T,Dynamic,1>, 0, InnerStride<Dynamic> > make_vector(const T* data, int size, int incr)
+{
+  return Map<const Matrix<T,Dynamic,1>, 0, InnerStride<Dynamic> >(data, size, InnerStride<Dynamic>(incr));
+}
+
+template<typename T>
+Map<Matrix<T,Dynamic,1> > make_vector(T* data, int size)
 {
   return Map<Matrix<T,Dynamic,1> >(data, size);
 }
+
+template<typename T>
+Map<const Matrix<T,Dynamic,1> > make_vector(const T* data, int size)
+{
+  return Map<const Matrix<T,Dynamic,1> >(data, size);
+}
 
 template<typename T>
 T* get_compact_vector(T* x, int n, int incx)
 {
   if(incx==1)
     return x;
 
-  T* ret = new Scalar[n];
-  if(incx<0) vector(ret,n) = vector(x,n,-incx).reverse();
-  else       vector(ret,n) = vector(x,n, incx);
+  typename Eigen::internal::remove_const<T>::type* ret = new Scalar[n];
+  if(incx<0) make_vector(ret,n) = make_vector(x,n,-incx).reverse();
+  else       make_vector(ret,n) = make_vector(x,n, incx);
   return ret;
 }
 
 template<typename T>
 T* copy_back(T* x_cpy, T* x, int n, int incx)
 {
   if(x_cpy==x)
     return 0;
 
-  if(incx<0) vector(x,n,-incx).reverse() = vector(x_cpy,n);
-  else       vector(x,n, incx)           = vector(x_cpy,n);
+  if(incx<0) make_vector(x,n,-incx).reverse() = make_vector(x_cpy,n);
+  else       make_vector(x,n, incx)           = make_vector(x_cpy,n);
   return x_cpy;
 }
 
 #define EIGEN_BLAS_FUNC(X) EIGEN_CAT(SCALAR_SUFFIX,X##_)
 
 #endif // EIGEN_BLAS_COMMON_H

DELETED 3rd_party/eigen/blas/complexdots.f
Index: 3rd_party/eigen/blas/complexdots.f
==================================================================
--- 3rd_party/eigen/blas/complexdots.f
+++ 3rd_party/eigen/blas/complexdots.f
@@ -1,43 +0,0 @@
-      COMPLEX FUNCTION CDOTC(N,CX,INCX,CY,INCY)
-      INTEGER INCX,INCY,N
-      COMPLEX CX(*),CY(*)
-      COMPLEX RES
-      EXTERNAL CDOTCW
-      
-      CALL CDOTCW(N,CX,INCX,CY,INCY,RES)
-      CDOTC = RES
-      RETURN
-      END
-      
-      COMPLEX FUNCTION CDOTU(N,CX,INCX,CY,INCY)
-      INTEGER INCX,INCY,N
-      COMPLEX CX(*),CY(*)
-      COMPLEX RES
-      EXTERNAL CDOTUW
-      
-      CALL CDOTUW(N,CX,INCX,CY,INCY,RES)
-      CDOTU = RES
-      RETURN
-      END
-      
-      DOUBLE COMPLEX FUNCTION ZDOTC(N,CX,INCX,CY,INCY)
-      INTEGER INCX,INCY,N
-      DOUBLE COMPLEX CX(*),CY(*)
-      DOUBLE COMPLEX RES
-      EXTERNAL ZDOTCW
-      
-      CALL ZDOTCW(N,CX,INCX,CY,INCY,RES)
-      ZDOTC = RES
-      RETURN
-      END
-      
-      DOUBLE COMPLEX FUNCTION ZDOTU(N,CX,INCX,CY,INCY)
-      INTEGER INCX,INCY,N
-      DOUBLE COMPLEX CX(*),CY(*)
-      DOUBLE COMPLEX RES
-      EXTERNAL ZDOTUW
-      
-      CALL ZDOTUW(N,CX,INCX,CY,INCY,RES)
-      ZDOTU = RES
-      RETURN
-      END

DELETED 3rd_party/eigen/blas/ctbmv.f
Index: 3rd_party/eigen/blas/ctbmv.f
==================================================================
--- 3rd_party/eigen/blas/ctbmv.f
+++ 3rd_party/eigen/blas/ctbmv.f
@@ -1,366 +0,0 @@
-      SUBROUTINE CTBMV(UPLO,TRANS,DIAG,N,K,A,LDA,X,INCX)
-*     .. Scalar Arguments ..
-      INTEGER INCX,K,LDA,N
-      CHARACTER DIAG,TRANS,UPLO
-*     ..
-*     .. Array Arguments ..
-      COMPLEX A(LDA,*),X(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  CTBMV  performs one of the matrix-vector operations
-*
-*     x := A*x,   or   x := A'*x,   or   x := conjg( A' )*x,
-*
-*  where x is an n element vector and  A is an n by n unit, or non-unit,
-*  upper or lower triangular band matrix, with ( k + 1 ) diagonals.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the matrix is an upper or
-*           lower triangular matrix as follows:
-*
-*              UPLO = 'U' or 'u'   A is an upper triangular matrix.
-*
-*              UPLO = 'L' or 'l'   A is a lower triangular matrix.
-*
-*           Unchanged on exit.
-*
-*  TRANS  - CHARACTER*1.
-*           On entry, TRANS specifies the operation to be performed as
-*           follows:
-*
-*              TRANS = 'N' or 'n'   x := A*x.
-*
-*              TRANS = 'T' or 't'   x := A'*x.
-*
-*              TRANS = 'C' or 'c'   x := conjg( A' )*x.
-*
-*           Unchanged on exit.
-*
-*  DIAG   - CHARACTER*1.
-*           On entry, DIAG specifies whether or not A is unit
-*           triangular as follows:
-*
-*              DIAG = 'U' or 'u'   A is assumed to be unit triangular.
-*
-*              DIAG = 'N' or 'n'   A is not assumed to be unit
-*                                  triangular.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  K      - INTEGER.
-*           On entry with UPLO = 'U' or 'u', K specifies the number of
-*           super-diagonals of the matrix A.
-*           On entry with UPLO = 'L' or 'l', K specifies the number of
-*           sub-diagonals of the matrix A.
-*           K must satisfy  0 .le. K.
-*           Unchanged on exit.
-*
-*  A      - COMPLEX          array of DIMENSION ( LDA, n ).
-*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 )
-*           by n part of the array A must contain the upper triangular
-*           band part of the matrix of coefficients, supplied column by
-*           column, with the leading diagonal of the matrix in row
-*           ( k + 1 ) of the array, the first super-diagonal starting at
-*           position 2 in row k, and so on. The top left k by k triangle
-*           of the array A is not referenced.
-*           The following program segment will transfer an upper
-*           triangular band matrix from conventional full matrix storage
-*           to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = K + 1 - J
-*                    DO 10, I = MAX( 1, J - K ), J
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 )
-*           by n part of the array A must contain the lower triangular
-*           band part of the matrix of coefficients, supplied column by
-*           column, with the leading diagonal of the matrix in row 1 of
-*           the array, the first sub-diagonal starting at position 1 in
-*           row 2, and so on. The bottom right k by k triangle of the
-*           array A is not referenced.
-*           The following program segment will transfer a lower
-*           triangular band matrix from conventional full matrix storage
-*           to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = 1 - J
-*                    DO 10, I = J, MIN( N, J + K )
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Note that when DIAG = 'U' or 'u' the elements of the array A
-*           corresponding to the diagonal elements of the matrix are not
-*           referenced, but are assumed to be unity.
-*           Unchanged on exit.
-*
-*  LDA    - INTEGER.
-*           On entry, LDA specifies the first dimension of A as declared
-*           in the calling (sub) program. LDA must be at least
-*           ( k + 1 ).
-*           Unchanged on exit.
-*
-*  X      - COMPLEX          array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the n
-*           element vector x. On exit, X is overwritten with the
-*           tranformed vector x.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      COMPLEX ZERO
-      PARAMETER (ZERO= (0.0E+0,0.0E+0))
-*     ..
-*     .. Local Scalars ..
-      COMPLEX TEMP
-      INTEGER I,INFO,IX,J,JX,KPLUS1,KX,L
-      LOGICAL NOCONJ,NOUNIT
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC CONJG,MAX,MIN
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
-     +         .NOT.LSAME(TRANS,'C')) THEN
-          INFO = 2
-      ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
-          INFO = 3
-      ELSE IF (N.LT.0) THEN
-          INFO = 4
-      ELSE IF (K.LT.0) THEN
-          INFO = 5
-      ELSE IF (LDA.LT. (K+1)) THEN
-          INFO = 7
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 9
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('CTBMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF (N.EQ.0) RETURN
-*
-      NOCONJ = LSAME(TRANS,'T')
-      NOUNIT = LSAME(DIAG,'N')
-*
-*     Set up the start point in X if the increment is not unity. This
-*     will be  ( N - 1 )*INCX   too small for descending loops.
-*
-      IF (INCX.LE.0) THEN
-          KX = 1 - (N-1)*INCX
-      ELSE IF (INCX.NE.1) THEN
-          KX = 1
-      END IF
-*
-*     Start the operations. In this version the elements of A are
-*     accessed sequentially with one pass through A.
-*
-      IF (LSAME(TRANS,'N')) THEN
-*
-*         Form  x := A*x.
-*
-          IF (LSAME(UPLO,'U')) THEN
-              KPLUS1 = K + 1
-              IF (INCX.EQ.1) THEN
-                  DO 20 J = 1,N
-                      IF (X(J).NE.ZERO) THEN
-                          TEMP = X(J)
-                          L = KPLUS1 - J
-                          DO 10 I = MAX(1,J-K),J - 1
-                              X(I) = X(I) + TEMP*A(L+I,J)
-   10                     CONTINUE
-                          IF (NOUNIT) X(J) = X(J)*A(KPLUS1,J)
-                      END IF
-   20             CONTINUE
-              ELSE
-                  JX = KX
-                  DO 40 J = 1,N
-                      IF (X(JX).NE.ZERO) THEN
-                          TEMP = X(JX)
-                          IX = KX
-                          L = KPLUS1 - J
-                          DO 30 I = MAX(1,J-K),J - 1
-                              X(IX) = X(IX) + TEMP*A(L+I,J)
-                              IX = IX + INCX
-   30                     CONTINUE
-                          IF (NOUNIT) X(JX) = X(JX)*A(KPLUS1,J)
-                      END IF
-                      JX = JX + INCX
-                      IF (J.GT.K) KX = KX + INCX
-   40             CONTINUE
-              END IF
-          ELSE
-              IF (INCX.EQ.1) THEN
-                  DO 60 J = N,1,-1
-                      IF (X(J).NE.ZERO) THEN
-                          TEMP = X(J)
-                          L = 1 - J
-                          DO 50 I = MIN(N,J+K),J + 1,-1
-                              X(I) = X(I) + TEMP*A(L+I,J)
-   50                     CONTINUE
-                          IF (NOUNIT) X(J) = X(J)*A(1,J)
-                      END IF
-   60             CONTINUE
-              ELSE
-                  KX = KX + (N-1)*INCX
-                  JX = KX
-                  DO 80 J = N,1,-1
-                      IF (X(JX).NE.ZERO) THEN
-                          TEMP = X(JX)
-                          IX = KX
-                          L = 1 - J
-                          DO 70 I = MIN(N,J+K),J + 1,-1
-                              X(IX) = X(IX) + TEMP*A(L+I,J)
-                              IX = IX - INCX
-   70                     CONTINUE
-                          IF (NOUNIT) X(JX) = X(JX)*A(1,J)
-                      END IF
-                      JX = JX - INCX
-                      IF ((N-J).GE.K) KX = KX - INCX
-   80             CONTINUE
-              END IF
-          END IF
-      ELSE
-*
-*        Form  x := A'*x  or  x := conjg( A' )*x.
-*
-          IF (LSAME(UPLO,'U')) THEN
-              KPLUS1 = K + 1
-              IF (INCX.EQ.1) THEN
-                  DO 110 J = N,1,-1
-                      TEMP = X(J)
-                      L = KPLUS1 - J
-                      IF (NOCONJ) THEN
-                          IF (NOUNIT) TEMP = TEMP*A(KPLUS1,J)
-                          DO 90 I = J - 1,MAX(1,J-K),-1
-                              TEMP = TEMP + A(L+I,J)*X(I)
-   90                     CONTINUE
-                      ELSE
-                          IF (NOUNIT) TEMP = TEMP*CONJG(A(KPLUS1,J))
-                          DO 100 I = J - 1,MAX(1,J-K),-1
-                              TEMP = TEMP + CONJG(A(L+I,J))*X(I)
-  100                     CONTINUE
-                      END IF
-                      X(J) = TEMP
-  110             CONTINUE
-              ELSE
-                  KX = KX + (N-1)*INCX
-                  JX = KX
-                  DO 140 J = N,1,-1
-                      TEMP = X(JX)
-                      KX = KX - INCX
-                      IX = KX
-                      L = KPLUS1 - J
-                      IF (NOCONJ) THEN
-                          IF (NOUNIT) TEMP = TEMP*A(KPLUS1,J)
-                          DO 120 I = J - 1,MAX(1,J-K),-1
-                              TEMP = TEMP + A(L+I,J)*X(IX)
-                              IX = IX - INCX
-  120                     CONTINUE
-                      ELSE
-                          IF (NOUNIT) TEMP = TEMP*CONJG(A(KPLUS1,J))
-                          DO 130 I = J - 1,MAX(1,J-K),-1
-                              TEMP = TEMP + CONJG(A(L+I,J))*X(IX)
-                              IX = IX - INCX
-  130                     CONTINUE
-                      END IF
-                      X(JX) = TEMP
-                      JX = JX - INCX
-  140             CONTINUE
-              END IF
-          ELSE
-              IF (INCX.EQ.1) THEN
-                  DO 170 J = 1,N
-                      TEMP = X(J)
-                      L = 1 - J
-                      IF (NOCONJ) THEN
-                          IF (NOUNIT) TEMP = TEMP*A(1,J)
-                          DO 150 I = J + 1,MIN(N,J+K)
-                              TEMP = TEMP + A(L+I,J)*X(I)
-  150                     CONTINUE
-                      ELSE
-                          IF (NOUNIT) TEMP = TEMP*CONJG(A(1,J))
-                          DO 160 I = J + 1,MIN(N,J+K)
-                              TEMP = TEMP + CONJG(A(L+I,J))*X(I)
-  160                     CONTINUE
-                      END IF
-                      X(J) = TEMP
-  170             CONTINUE
-              ELSE
-                  JX = KX
-                  DO 200 J = 1,N
-                      TEMP = X(JX)
-                      KX = KX + INCX
-                      IX = KX
-                      L = 1 - J
-                      IF (NOCONJ) THEN
-                          IF (NOUNIT) TEMP = TEMP*A(1,J)
-                          DO 180 I = J + 1,MIN(N,J+K)
-                              TEMP = TEMP + A(L+I,J)*X(IX)
-                              IX = IX + INCX
-  180                     CONTINUE
-                      ELSE
-                          IF (NOUNIT) TEMP = TEMP*CONJG(A(1,J))
-                          DO 190 I = J + 1,MIN(N,J+K)
-                              TEMP = TEMP + CONJG(A(L+I,J))*X(IX)
-                              IX = IX + INCX
-  190                     CONTINUE
-                      END IF
-                      X(JX) = TEMP
-                      JX = JX + INCX
-  200             CONTINUE
-              END IF
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of CTBMV .
-*
-      END

Index: 3rd_party/eigen/blas/double.cpp
==================================================================
--- 3rd_party/eigen/blas/double.cpp
+++ 3rd_party/eigen/blas/double.cpp
@@ -21,13 +21,12 @@
 
 double BLASFUNC(dsdot)(int* n, float* x, int* incx, float* y, int* incy)
 {
   if(*n<=0) return 0;
 
-  if(*incx==1 && *incy==1)    return (vector(x,*n).cast<double>().cwiseProduct(vector(y,*n).cast<double>())).sum();
-  else if(*incx>0 && *incy>0) return (vector(x,*n,*incx).cast<double>().cwiseProduct(vector(y,*n,*incy).cast<double>())).sum();
-  else if(*incx<0 && *incy>0) return (vector(x,*n,-*incx).reverse().cast<double>().cwiseProduct(vector(y,*n,*incy).cast<double>())).sum();
-  else if(*incx>0 && *incy<0) return (vector(x,*n,*incx).cast<double>().cwiseProduct(vector(y,*n,-*incy).reverse().cast<double>())).sum();
-  else if(*incx<0 && *incy<0) return (vector(x,*n,-*incx).reverse().cast<double>().cwiseProduct(vector(y,*n,-*incy).reverse().cast<double>())).sum();
+  if(*incx==1 && *incy==1)    return (make_vector(x,*n).cast<double>().cwiseProduct(make_vector(y,*n).cast<double>())).sum();
+  else if(*incx>0 && *incy>0) return (make_vector(x,*n,*incx).cast<double>().cwiseProduct(make_vector(y,*n,*incy).cast<double>())).sum();
+  else if(*incx<0 && *incy>0) return (make_vector(x,*n,-*incx).reverse().cast<double>().cwiseProduct(make_vector(y,*n,*incy).cast<double>())).sum();
+  else if(*incx>0 && *incy<0) return (make_vector(x,*n,*incx).cast<double>().cwiseProduct(make_vector(y,*n,-*incy).reverse().cast<double>())).sum();
+  else if(*incx<0 && *incy<0) return (make_vector(x,*n,-*incx).reverse().cast<double>().cwiseProduct(make_vector(y,*n,-*incy).reverse().cast<double>())).sum();
   else return 0;
 }
-

DELETED 3rd_party/eigen/blas/drotm.f
Index: 3rd_party/eigen/blas/drotm.f
==================================================================
--- 3rd_party/eigen/blas/drotm.f
+++ 3rd_party/eigen/blas/drotm.f
@@ -1,147 +0,0 @@
-      SUBROUTINE DROTM(N,DX,INCX,DY,INCY,DPARAM)
-*     .. Scalar Arguments ..
-      INTEGER INCX,INCY,N
-*     ..
-*     .. Array Arguments ..
-      DOUBLE PRECISION DPARAM(5),DX(*),DY(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*     APPLY THE MODIFIED GIVENS TRANSFORMATION, H, TO THE 2 BY N MATRIX
-*
-*     (DX**T) , WHERE **T INDICATES TRANSPOSE. THE ELEMENTS OF DX ARE IN
-*     (DY**T)
-*
-*     DX(LX+I*INCX), I = 0 TO N-1, WHERE LX = 1 IF INCX .GE. 0, ELSE
-*     LX = (-INCX)*N, AND SIMILARLY FOR SY USING LY AND INCY.
-*     WITH DPARAM(1)=DFLAG, H HAS ONE OF THE FOLLOWING FORMS..
-*
-*     DFLAG=-1.D0     DFLAG=0.D0        DFLAG=1.D0     DFLAG=-2.D0
-*
-*       (DH11  DH12)    (1.D0  DH12)    (DH11  1.D0)    (1.D0  0.D0)
-*     H=(          )    (          )    (          )    (          )
-*       (DH21  DH22),   (DH21  1.D0),   (-1.D0 DH22),   (0.D0  1.D0).
-*     SEE DROTMG FOR A DESCRIPTION OF DATA STORAGE IN DPARAM.
-*
-*  Arguments
-*  =========
-*
-*  N      (input) INTEGER
-*         number of elements in input vector(s)
-*
-*  DX     (input/output) DOUBLE PRECISION array, dimension N
-*         double precision vector with N elements
-*
-*  INCX   (input) INTEGER
-*         storage spacing between elements of DX
-*
-*  DY     (input/output) DOUBLE PRECISION array, dimension N
-*         double precision vector with N elements
-*
-*  INCY   (input) INTEGER
-*         storage spacing between elements of DY
-*
-*  DPARAM (input/output)  DOUBLE PRECISION array, dimension 5 
-*     DPARAM(1)=DFLAG
-*     DPARAM(2)=DH11
-*     DPARAM(3)=DH21
-*     DPARAM(4)=DH12
-*     DPARAM(5)=DH22
-*
-*  =====================================================================
-*
-*     .. Local Scalars ..
-      DOUBLE PRECISION DFLAG,DH11,DH12,DH21,DH22,TWO,W,Z,ZERO
-      INTEGER I,KX,KY,NSTEPS
-*     ..
-*     .. Data statements ..
-      DATA ZERO,TWO/0.D0,2.D0/
-*     ..
-*
-      DFLAG = DPARAM(1)
-      IF (N.LE.0 .OR. (DFLAG+TWO.EQ.ZERO)) GO TO 140
-      IF (.NOT. (INCX.EQ.INCY.AND.INCX.GT.0)) GO TO 70
-*
-      NSTEPS = N*INCX
-      IF (DFLAG) 50,10,30
-   10 CONTINUE
-      DH12 = DPARAM(4)
-      DH21 = DPARAM(3)
-      DO 20 I = 1,NSTEPS,INCX
-          W = DX(I)
-          Z = DY(I)
-          DX(I) = W + Z*DH12
-          DY(I) = W*DH21 + Z
-   20 CONTINUE
-      GO TO 140
-   30 CONTINUE
-      DH11 = DPARAM(2)
-      DH22 = DPARAM(5)
-      DO 40 I = 1,NSTEPS,INCX
-          W = DX(I)
-          Z = DY(I)
-          DX(I) = W*DH11 + Z
-          DY(I) = -W + DH22*Z
-   40 CONTINUE
-      GO TO 140
-   50 CONTINUE
-      DH11 = DPARAM(2)
-      DH12 = DPARAM(4)
-      DH21 = DPARAM(3)
-      DH22 = DPARAM(5)
-      DO 60 I = 1,NSTEPS,INCX
-          W = DX(I)
-          Z = DY(I)
-          DX(I) = W*DH11 + Z*DH12
-          DY(I) = W*DH21 + Z*DH22
-   60 CONTINUE
-      GO TO 140
-   70 CONTINUE
-      KX = 1
-      KY = 1
-      IF (INCX.LT.0) KX = 1 + (1-N)*INCX
-      IF (INCY.LT.0) KY = 1 + (1-N)*INCY
-*
-      IF (DFLAG) 120,80,100
-   80 CONTINUE
-      DH12 = DPARAM(4)
-      DH21 = DPARAM(3)
-      DO 90 I = 1,N
-          W = DX(KX)
-          Z = DY(KY)
-          DX(KX) = W + Z*DH12
-          DY(KY) = W*DH21 + Z
-          KX = KX + INCX
-          KY = KY + INCY
-   90 CONTINUE
-      GO TO 140
-  100 CONTINUE
-      DH11 = DPARAM(2)
-      DH22 = DPARAM(5)
-      DO 110 I = 1,N
-          W = DX(KX)
-          Z = DY(KY)
-          DX(KX) = W*DH11 + Z
-          DY(KY) = -W + DH22*Z
-          KX = KX + INCX
-          KY = KY + INCY
-  110 CONTINUE
-      GO TO 140
-  120 CONTINUE
-      DH11 = DPARAM(2)
-      DH12 = DPARAM(4)
-      DH21 = DPARAM(3)
-      DH22 = DPARAM(5)
-      DO 130 I = 1,N
-          W = DX(KX)
-          Z = DY(KY)
-          DX(KX) = W*DH11 + Z*DH12
-          DY(KY) = W*DH21 + Z*DH22
-          KX = KX + INCX
-          KY = KY + INCY
-  130 CONTINUE
-  140 CONTINUE
-      RETURN
-      END

DELETED 3rd_party/eigen/blas/drotmg.f
Index: 3rd_party/eigen/blas/drotmg.f
==================================================================
--- 3rd_party/eigen/blas/drotmg.f
+++ 3rd_party/eigen/blas/drotmg.f
@@ -1,206 +0,0 @@
-      SUBROUTINE DROTMG(DD1,DD2,DX1,DY1,DPARAM)
-*     .. Scalar Arguments ..
-      DOUBLE PRECISION DD1,DD2,DX1,DY1
-*     ..
-*     .. Array Arguments ..
-      DOUBLE PRECISION DPARAM(5)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*     CONSTRUCT THE MODIFIED GIVENS TRANSFORMATION MATRIX H WHICH ZEROS
-*     THE SECOND COMPONENT OF THE 2-VECTOR  (DSQRT(DD1)*DX1,DSQRT(DD2)*
-*     DY2)**T.
-*     WITH DPARAM(1)=DFLAG, H HAS ONE OF THE FOLLOWING FORMS..
-*
-*     DFLAG=-1.D0     DFLAG=0.D0        DFLAG=1.D0     DFLAG=-2.D0
-*
-*       (DH11  DH12)    (1.D0  DH12)    (DH11  1.D0)    (1.D0  0.D0)
-*     H=(          )    (          )    (          )    (          )
-*       (DH21  DH22),   (DH21  1.D0),   (-1.D0 DH22),   (0.D0  1.D0).
-*     LOCATIONS 2-4 OF DPARAM CONTAIN DH11, DH21, DH12, AND DH22
-*     RESPECTIVELY. (VALUES OF 1.D0, -1.D0, OR 0.D0 IMPLIED BY THE
-*     VALUE OF DPARAM(1) ARE NOT STORED IN DPARAM.)
-*
-*     THE VALUES OF GAMSQ AND RGAMSQ SET IN THE DATA STATEMENT MAY BE
-*     INEXACT.  THIS IS OK AS THEY ARE ONLY USED FOR TESTING THE SIZE
-*     OF DD1 AND DD2.  ALL ACTUAL SCALING OF DATA IS DONE USING GAM.
-*
-*
-*  Arguments
-*  =========
-*
-*  DD1    (input/output) DOUBLE PRECISION
-*
-*  DD2    (input/output) DOUBLE PRECISION 
-*
-*  DX1    (input/output) DOUBLE PRECISION 
-*
-*  DY1    (input) DOUBLE PRECISION
-*
-*  DPARAM (input/output)  DOUBLE PRECISION array, dimension 5
-*     DPARAM(1)=DFLAG
-*     DPARAM(2)=DH11
-*     DPARAM(3)=DH21
-*     DPARAM(4)=DH12
-*     DPARAM(5)=DH22
-*
-*  =====================================================================
-*
-*     .. Local Scalars ..
-      DOUBLE PRECISION DFLAG,DH11,DH12,DH21,DH22,DP1,DP2,DQ1,DQ2,DTEMP,
-     +                 DU,GAM,GAMSQ,ONE,RGAMSQ,TWO,ZERO
-      INTEGER IGO
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC DABS
-*     ..
-*     .. Data statements ..
-*
-      DATA ZERO,ONE,TWO/0.D0,1.D0,2.D0/
-      DATA GAM,GAMSQ,RGAMSQ/4096.D0,16777216.D0,5.9604645D-8/
-*     ..
-
-      IF (.NOT.DD1.LT.ZERO) GO TO 10
-*       GO ZERO-H-D-AND-DX1..
-      GO TO 60
-   10 CONTINUE
-*     CASE-DD1-NONNEGATIVE
-      DP2 = DD2*DY1
-      IF (.NOT.DP2.EQ.ZERO) GO TO 20
-      DFLAG = -TWO
-      GO TO 260
-*     REGULAR-CASE..
-   20 CONTINUE
-      DP1 = DD1*DX1
-      DQ2 = DP2*DY1
-      DQ1 = DP1*DX1
-*
-      IF (.NOT.DABS(DQ1).GT.DABS(DQ2)) GO TO 40
-      DH21 = -DY1/DX1
-      DH12 = DP2/DP1
-*
-      DU = ONE - DH12*DH21
-*
-      IF (.NOT.DU.LE.ZERO) GO TO 30
-*         GO ZERO-H-D-AND-DX1..
-      GO TO 60
-   30 CONTINUE
-      DFLAG = ZERO
-      DD1 = DD1/DU
-      DD2 = DD2/DU
-      DX1 = DX1*DU
-*         GO SCALE-CHECK..
-      GO TO 100
-   40 CONTINUE
-      IF (.NOT.DQ2.LT.ZERO) GO TO 50
-*         GO ZERO-H-D-AND-DX1..
-      GO TO 60
-   50 CONTINUE
-      DFLAG = ONE
-      DH11 = DP1/DP2
-      DH22 = DX1/DY1
-      DU = ONE + DH11*DH22
-      DTEMP = DD2/DU
-      DD2 = DD1/DU
-      DD1 = DTEMP
-      DX1 = DY1*DU
-*         GO SCALE-CHECK
-      GO TO 100
-*     PROCEDURE..ZERO-H-D-AND-DX1..
-   60 CONTINUE
-      DFLAG = -ONE
-      DH11 = ZERO
-      DH12 = ZERO
-      DH21 = ZERO
-      DH22 = ZERO
-*
-      DD1 = ZERO
-      DD2 = ZERO
-      DX1 = ZERO
-*         RETURN..
-      GO TO 220
-*     PROCEDURE..FIX-H..
-   70 CONTINUE
-      IF (.NOT.DFLAG.GE.ZERO) GO TO 90
-*
-      IF (.NOT.DFLAG.EQ.ZERO) GO TO 80
-      DH11 = ONE
-      DH22 = ONE
-      DFLAG = -ONE
-      GO TO 90
-   80 CONTINUE
-      DH21 = -ONE
-      DH12 = ONE
-      DFLAG = -ONE
-   90 CONTINUE
-      GO TO IGO(120,150,180,210)
-*     PROCEDURE..SCALE-CHECK
-  100 CONTINUE
-  110 CONTINUE
-      IF (.NOT.DD1.LE.RGAMSQ) GO TO 130
-      IF (DD1.EQ.ZERO) GO TO 160
-      ASSIGN 120 TO IGO
-*              FIX-H..
-      GO TO 70
-  120 CONTINUE
-      DD1 = DD1*GAM**2
-      DX1 = DX1/GAM
-      DH11 = DH11/GAM
-      DH12 = DH12/GAM
-      GO TO 110
-  130 CONTINUE
-  140 CONTINUE
-      IF (.NOT.DD1.GE.GAMSQ) GO TO 160
-      ASSIGN 150 TO IGO
-*              FIX-H..
-      GO TO 70
-  150 CONTINUE
-      DD1 = DD1/GAM**2
-      DX1 = DX1*GAM
-      DH11 = DH11*GAM
-      DH12 = DH12*GAM
-      GO TO 140
-  160 CONTINUE
-  170 CONTINUE
-      IF (.NOT.DABS(DD2).LE.RGAMSQ) GO TO 190
-      IF (DD2.EQ.ZERO) GO TO 220
-      ASSIGN 180 TO IGO
-*              FIX-H..
-      GO TO 70
-  180 CONTINUE
-      DD2 = DD2*GAM**2
-      DH21 = DH21/GAM
-      DH22 = DH22/GAM
-      GO TO 170
-  190 CONTINUE
-  200 CONTINUE
-      IF (.NOT.DABS(DD2).GE.GAMSQ) GO TO 220
-      ASSIGN 210 TO IGO
-*              FIX-H..
-      GO TO 70
-  210 CONTINUE
-      DD2 = DD2/GAM**2
-      DH21 = DH21*GAM
-      DH22 = DH22*GAM
-      GO TO 200
-  220 CONTINUE
-      IF (DFLAG) 250,230,240
-  230 CONTINUE
-      DPARAM(3) = DH21
-      DPARAM(4) = DH12
-      GO TO 260
-  240 CONTINUE
-      DPARAM(2) = DH11
-      DPARAM(5) = DH22
-      GO TO 260
-  250 CONTINUE
-      DPARAM(2) = DH11
-      DPARAM(3) = DH21
-      DPARAM(4) = DH12
-      DPARAM(5) = DH22
-  260 CONTINUE
-      DPARAM(1) = DFLAG
-      RETURN
-      END

DELETED 3rd_party/eigen/blas/dsbmv.f
Index: 3rd_party/eigen/blas/dsbmv.f
==================================================================
--- 3rd_party/eigen/blas/dsbmv.f
+++ 3rd_party/eigen/blas/dsbmv.f
@@ -1,304 +0,0 @@
-      SUBROUTINE DSBMV(UPLO,N,K,ALPHA,A,LDA,X,INCX,BETA,Y,INCY)
-*     .. Scalar Arguments ..
-      DOUBLE PRECISION ALPHA,BETA
-      INTEGER INCX,INCY,K,LDA,N
-      CHARACTER UPLO
-*     ..
-*     .. Array Arguments ..
-      DOUBLE PRECISION A(LDA,*),X(*),Y(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  DSBMV  performs the matrix-vector  operation
-*
-*     y := alpha*A*x + beta*y,
-*
-*  where alpha and beta are scalars, x and y are n element vectors and
-*  A is an n by n symmetric band matrix, with k super-diagonals.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the upper or lower
-*           triangular part of the band matrix A is being supplied as
-*           follows:
-*
-*              UPLO = 'U' or 'u'   The upper triangular part of A is
-*                                  being supplied.
-*
-*              UPLO = 'L' or 'l'   The lower triangular part of A is
-*                                  being supplied.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  K      - INTEGER.
-*           On entry, K specifies the number of super-diagonals of the
-*           matrix A. K must satisfy  0 .le. K.
-*           Unchanged on exit.
-*
-*  ALPHA  - DOUBLE PRECISION.
-*           On entry, ALPHA specifies the scalar alpha.
-*           Unchanged on exit.
-*
-*  A      - DOUBLE PRECISION array of DIMENSION ( LDA, n ).
-*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 )
-*           by n part of the array A must contain the upper triangular
-*           band part of the symmetric matrix, supplied column by
-*           column, with the leading diagonal of the matrix in row
-*           ( k + 1 ) of the array, the first super-diagonal starting at
-*           position 2 in row k, and so on. The top left k by k triangle
-*           of the array A is not referenced.
-*           The following program segment will transfer the upper
-*           triangular part of a symmetric band matrix from conventional
-*           full matrix storage to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = K + 1 - J
-*                    DO 10, I = MAX( 1, J - K ), J
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 )
-*           by n part of the array A must contain the lower triangular
-*           band part of the symmetric matrix, supplied column by
-*           column, with the leading diagonal of the matrix in row 1 of
-*           the array, the first sub-diagonal starting at position 1 in
-*           row 2, and so on. The bottom right k by k triangle of the
-*           array A is not referenced.
-*           The following program segment will transfer the lower
-*           triangular part of a symmetric band matrix from conventional
-*           full matrix storage to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = 1 - J
-*                    DO 10, I = J, MIN( N, J + K )
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Unchanged on exit.
-*
-*  LDA    - INTEGER.
-*           On entry, LDA specifies the first dimension of A as declared
-*           in the calling (sub) program. LDA must be at least
-*           ( k + 1 ).
-*           Unchanged on exit.
-*
-*  X      - DOUBLE PRECISION array of DIMENSION at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the
-*           vector x.
-*           Unchanged on exit.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  BETA   - DOUBLE PRECISION.
-*           On entry, BETA specifies the scalar beta.
-*           Unchanged on exit.
-*
-*  Y      - DOUBLE PRECISION array of DIMENSION at least
-*           ( 1 + ( n - 1 )*abs( INCY ) ).
-*           Before entry, the incremented array Y must contain the
-*           vector y. On exit, Y is overwritten by the updated vector y.
-*
-*  INCY   - INTEGER.
-*           On entry, INCY specifies the increment for the elements of
-*           Y. INCY must not be zero.
-*           Unchanged on exit.
-*
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      DOUBLE PRECISION ONE,ZERO
-      PARAMETER (ONE=1.0D+0,ZERO=0.0D+0)
-*     ..
-*     .. Local Scalars ..
-      DOUBLE PRECISION TEMP1,TEMP2
-      INTEGER I,INFO,IX,IY,J,JX,JY,KPLUS1,KX,KY,L
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC MAX,MIN
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (N.LT.0) THEN
-          INFO = 2
-      ELSE IF (K.LT.0) THEN
-          INFO = 3
-      ELSE IF (LDA.LT. (K+1)) THEN
-          INFO = 6
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 8
-      ELSE IF (INCY.EQ.0) THEN
-          INFO = 11
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('DSBMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF ((N.EQ.0) .OR. ((ALPHA.EQ.ZERO).AND. (BETA.EQ.ONE))) RETURN
-*
-*     Set up the start points in  X  and  Y.
-*
-      IF (INCX.GT.0) THEN
-          KX = 1
-      ELSE
-          KX = 1 - (N-1)*INCX
-      END IF
-      IF (INCY.GT.0) THEN
-          KY = 1
-      ELSE
-          KY = 1 - (N-1)*INCY
-      END IF
-*
-*     Start the operations. In this version the elements of the array A
-*     are accessed sequentially with one pass through A.
-*
-*     First form  y := beta*y.
-*
-      IF (BETA.NE.ONE) THEN
-          IF (INCY.EQ.1) THEN
-              IF (BETA.EQ.ZERO) THEN
-                  DO 10 I = 1,N
-                      Y(I) = ZERO
-   10             CONTINUE
-              ELSE
-                  DO 20 I = 1,N
-                      Y(I) = BETA*Y(I)
-   20             CONTINUE
-              END IF
-          ELSE
-              IY = KY
-              IF (BETA.EQ.ZERO) THEN
-                  DO 30 I = 1,N
-                      Y(IY) = ZERO
-                      IY = IY + INCY
-   30             CONTINUE
-              ELSE
-                  DO 40 I = 1,N
-                      Y(IY) = BETA*Y(IY)
-                      IY = IY + INCY
-   40             CONTINUE
-              END IF
-          END IF
-      END IF
-      IF (ALPHA.EQ.ZERO) RETURN
-      IF (LSAME(UPLO,'U')) THEN
-*
-*        Form  y  when upper triangle of A is stored.
-*
-          KPLUS1 = K + 1
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 60 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  L = KPLUS1 - J
-                  DO 50 I = MAX(1,J-K),J - 1
-                      Y(I) = Y(I) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + A(L+I,J)*X(I)
-   50             CONTINUE
-                  Y(J) = Y(J) + TEMP1*A(KPLUS1,J) + ALPHA*TEMP2
-   60         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 80 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  IX = KX
-                  IY = KY
-                  L = KPLUS1 - J
-                  DO 70 I = MAX(1,J-K),J - 1
-                      Y(IY) = Y(IY) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + A(L+I,J)*X(IX)
-                      IX = IX + INCX
-                      IY = IY + INCY
-   70             CONTINUE
-                  Y(JY) = Y(JY) + TEMP1*A(KPLUS1,J) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  IF (J.GT.K) THEN
-                      KX = KX + INCX
-                      KY = KY + INCY
-                  END IF
-   80         CONTINUE
-          END IF
-      ELSE
-*
-*        Form  y  when lower triangle of A is stored.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 100 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  Y(J) = Y(J) + TEMP1*A(1,J)
-                  L = 1 - J
-                  DO 90 I = J + 1,MIN(N,J+K)
-                      Y(I) = Y(I) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + A(L+I,J)*X(I)
-   90             CONTINUE
-                  Y(J) = Y(J) + ALPHA*TEMP2
-  100         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 120 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  Y(JY) = Y(JY) + TEMP1*A(1,J)
-                  L = 1 - J
-                  IX = JX
-                  IY = JY
-                  DO 110 I = J + 1,MIN(N,J+K)
-                      IX = IX + INCX
-                      IY = IY + INCY
-                      Y(IY) = Y(IY) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + A(L+I,J)*X(IX)
-  110             CONTINUE
-                  Y(JY) = Y(JY) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-  120         CONTINUE
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of DSBMV .
-*
-      END

DELETED 3rd_party/eigen/blas/dspmv.f
Index: 3rd_party/eigen/blas/dspmv.f
==================================================================
--- 3rd_party/eigen/blas/dspmv.f
+++ 3rd_party/eigen/blas/dspmv.f
@@ -1,265 +0,0 @@
-      SUBROUTINE DSPMV(UPLO,N,ALPHA,AP,X,INCX,BETA,Y,INCY)
-*     .. Scalar Arguments ..
-      DOUBLE PRECISION ALPHA,BETA
-      INTEGER INCX,INCY,N
-      CHARACTER UPLO
-*     ..
-*     .. Array Arguments ..
-      DOUBLE PRECISION AP(*),X(*),Y(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  DSPMV  performs the matrix-vector operation
-*
-*     y := alpha*A*x + beta*y,
-*
-*  where alpha and beta are scalars, x and y are n element vectors and
-*  A is an n by n symmetric matrix, supplied in packed form.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the upper or lower
-*           triangular part of the matrix A is supplied in the packed
-*           array AP as follows:
-*
-*              UPLO = 'U' or 'u'   The upper triangular part of A is
-*                                  supplied in AP.
-*
-*              UPLO = 'L' or 'l'   The lower triangular part of A is
-*                                  supplied in AP.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  ALPHA  - DOUBLE PRECISION.
-*           On entry, ALPHA specifies the scalar alpha.
-*           Unchanged on exit.
-*
-*  AP     - DOUBLE PRECISION array of DIMENSION at least
-*           ( ( n*( n + 1 ) )/2 ).
-*           Before entry with UPLO = 'U' or 'u', the array AP must
-*           contain the upper triangular part of the symmetric matrix
-*           packed sequentially, column by column, so that AP( 1 )
-*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-*           and a( 2, 2 ) respectively, and so on.
-*           Before entry with UPLO = 'L' or 'l', the array AP must
-*           contain the lower triangular part of the symmetric matrix
-*           packed sequentially, column by column, so that AP( 1 )
-*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-*           and a( 3, 1 ) respectively, and so on.
-*           Unchanged on exit.
-*
-*  X      - DOUBLE PRECISION array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the n
-*           element vector x.
-*           Unchanged on exit.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  BETA   - DOUBLE PRECISION.
-*           On entry, BETA specifies the scalar beta. When BETA is
-*           supplied as zero then Y need not be set on input.
-*           Unchanged on exit.
-*
-*  Y      - DOUBLE PRECISION array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCY ) ).
-*           Before entry, the incremented array Y must contain the n
-*           element vector y. On exit, Y is overwritten by the updated
-*           vector y.
-*
-*  INCY   - INTEGER.
-*           On entry, INCY specifies the increment for the elements of
-*           Y. INCY must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      DOUBLE PRECISION ONE,ZERO
-      PARAMETER (ONE=1.0D+0,ZERO=0.0D+0)
-*     ..
-*     .. Local Scalars ..
-      DOUBLE PRECISION TEMP1,TEMP2
-      INTEGER I,INFO,IX,IY,J,JX,JY,K,KK,KX,KY
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (N.LT.0) THEN
-          INFO = 2
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 6
-      ELSE IF (INCY.EQ.0) THEN
-          INFO = 9
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('DSPMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF ((N.EQ.0) .OR. ((ALPHA.EQ.ZERO).AND. (BETA.EQ.ONE))) RETURN
-*
-*     Set up the start points in  X  and  Y.
-*
-      IF (INCX.GT.0) THEN
-          KX = 1
-      ELSE
-          KX = 1 - (N-1)*INCX
-      END IF
-      IF (INCY.GT.0) THEN
-          KY = 1
-      ELSE
-          KY = 1 - (N-1)*INCY
-      END IF
-*
-*     Start the operations. In this version the elements of the array AP
-*     are accessed sequentially with one pass through AP.
-*
-*     First form  y := beta*y.
-*
-      IF (BETA.NE.ONE) THEN
-          IF (INCY.EQ.1) THEN
-              IF (BETA.EQ.ZERO) THEN
-                  DO 10 I = 1,N
-                      Y(I) = ZERO
-   10             CONTINUE
-              ELSE
-                  DO 20 I = 1,N
-                      Y(I) = BETA*Y(I)
-   20             CONTINUE
-              END IF
-          ELSE
-              IY = KY
-              IF (BETA.EQ.ZERO) THEN
-                  DO 30 I = 1,N
-                      Y(IY) = ZERO
-                      IY = IY + INCY
-   30             CONTINUE
-              ELSE
-                  DO 40 I = 1,N
-                      Y(IY) = BETA*Y(IY)
-                      IY = IY + INCY
-   40             CONTINUE
-              END IF
-          END IF
-      END IF
-      IF (ALPHA.EQ.ZERO) RETURN
-      KK = 1
-      IF (LSAME(UPLO,'U')) THEN
-*
-*        Form  y  when AP contains the upper triangle.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 60 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  K = KK
-                  DO 50 I = 1,J - 1
-                      Y(I) = Y(I) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + AP(K)*X(I)
-                      K = K + 1
-   50             CONTINUE
-                  Y(J) = Y(J) + TEMP1*AP(KK+J-1) + ALPHA*TEMP2
-                  KK = KK + J
-   60         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 80 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  IX = KX
-                  IY = KY
-                  DO 70 K = KK,KK + J - 2
-                      Y(IY) = Y(IY) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + AP(K)*X(IX)
-                      IX = IX + INCX
-                      IY = IY + INCY
-   70             CONTINUE
-                  Y(JY) = Y(JY) + TEMP1*AP(KK+J-1) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  KK = KK + J
-   80         CONTINUE
-          END IF
-      ELSE
-*
-*        Form  y  when AP contains the lower triangle.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 100 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  Y(J) = Y(J) + TEMP1*AP(KK)
-                  K = KK + 1
-                  DO 90 I = J + 1,N
-                      Y(I) = Y(I) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + AP(K)*X(I)
-                      K = K + 1
-   90             CONTINUE
-                  Y(J) = Y(J) + ALPHA*TEMP2
-                  KK = KK + (N-J+1)
-  100         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 120 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  Y(JY) = Y(JY) + TEMP1*AP(KK)
-                  IX = JX
-                  IY = JY
-                  DO 110 K = KK + 1,KK + N - J
-                      IX = IX + INCX
-                      IY = IY + INCY
-                      Y(IY) = Y(IY) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + AP(K)*X(IX)
-  110             CONTINUE
-                  Y(JY) = Y(JY) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  KK = KK + (N-J+1)
-  120         CONTINUE
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of DSPMV .
-*
-      END

DELETED 3rd_party/eigen/blas/dtbmv.f
Index: 3rd_party/eigen/blas/dtbmv.f
==================================================================
--- 3rd_party/eigen/blas/dtbmv.f
+++ 3rd_party/eigen/blas/dtbmv.f
@@ -1,335 +0,0 @@
-      SUBROUTINE DTBMV(UPLO,TRANS,DIAG,N,K,A,LDA,X,INCX)
-*     .. Scalar Arguments ..
-      INTEGER INCX,K,LDA,N
-      CHARACTER DIAG,TRANS,UPLO
-*     ..
-*     .. Array Arguments ..
-      DOUBLE PRECISION A(LDA,*),X(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  DTBMV  performs one of the matrix-vector operations
-*
-*     x := A*x,   or   x := A'*x,
-*
-*  where x is an n element vector and  A is an n by n unit, or non-unit,
-*  upper or lower triangular band matrix, with ( k + 1 ) diagonals.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the matrix is an upper or
-*           lower triangular matrix as follows:
-*
-*              UPLO = 'U' or 'u'   A is an upper triangular matrix.
-*
-*              UPLO = 'L' or 'l'   A is a lower triangular matrix.
-*
-*           Unchanged on exit.
-*
-*  TRANS  - CHARACTER*1.
-*           On entry, TRANS specifies the operation to be performed as
-*           follows:
-*
-*              TRANS = 'N' or 'n'   x := A*x.
-*
-*              TRANS = 'T' or 't'   x := A'*x.
-*
-*              TRANS = 'C' or 'c'   x := A'*x.
-*
-*           Unchanged on exit.
-*
-*  DIAG   - CHARACTER*1.
-*           On entry, DIAG specifies whether or not A is unit
-*           triangular as follows:
-*
-*              DIAG = 'U' or 'u'   A is assumed to be unit triangular.
-*
-*              DIAG = 'N' or 'n'   A is not assumed to be unit
-*                                  triangular.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  K      - INTEGER.
-*           On entry with UPLO = 'U' or 'u', K specifies the number of
-*           super-diagonals of the matrix A.
-*           On entry with UPLO = 'L' or 'l', K specifies the number of
-*           sub-diagonals of the matrix A.
-*           K must satisfy  0 .le. K.
-*           Unchanged on exit.
-*
-*  A      - DOUBLE PRECISION array of DIMENSION ( LDA, n ).
-*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 )
-*           by n part of the array A must contain the upper triangular
-*           band part of the matrix of coefficients, supplied column by
-*           column, with the leading diagonal of the matrix in row
-*           ( k + 1 ) of the array, the first super-diagonal starting at
-*           position 2 in row k, and so on. The top left k by k triangle
-*           of the array A is not referenced.
-*           The following program segment will transfer an upper
-*           triangular band matrix from conventional full matrix storage
-*           to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = K + 1 - J
-*                    DO 10, I = MAX( 1, J - K ), J
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 )
-*           by n part of the array A must contain the lower triangular
-*           band part of the matrix of coefficients, supplied column by
-*           column, with the leading diagonal of the matrix in row 1 of
-*           the array, the first sub-diagonal starting at position 1 in
-*           row 2, and so on. The bottom right k by k triangle of the
-*           array A is not referenced.
-*           The following program segment will transfer a lower
-*           triangular band matrix from conventional full matrix storage
-*           to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = 1 - J
-*                    DO 10, I = J, MIN( N, J + K )
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Note that when DIAG = 'U' or 'u' the elements of the array A
-*           corresponding to the diagonal elements of the matrix are not
-*           referenced, but are assumed to be unity.
-*           Unchanged on exit.
-*
-*  LDA    - INTEGER.
-*           On entry, LDA specifies the first dimension of A as declared
-*           in the calling (sub) program. LDA must be at least
-*           ( k + 1 ).
-*           Unchanged on exit.
-*
-*  X      - DOUBLE PRECISION array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the n
-*           element vector x. On exit, X is overwritten with the
-*           tranformed vector x.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      DOUBLE PRECISION ZERO
-      PARAMETER (ZERO=0.0D+0)
-*     ..
-*     .. Local Scalars ..
-      DOUBLE PRECISION TEMP
-      INTEGER I,INFO,IX,J,JX,KPLUS1,KX,L
-      LOGICAL NOUNIT
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC MAX,MIN
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
-     +         .NOT.LSAME(TRANS,'C')) THEN
-          INFO = 2
-      ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
-          INFO = 3
-      ELSE IF (N.LT.0) THEN
-          INFO = 4
-      ELSE IF (K.LT.0) THEN
-          INFO = 5
-      ELSE IF (LDA.LT. (K+1)) THEN
-          INFO = 7
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 9
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('DTBMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF (N.EQ.0) RETURN
-*
-      NOUNIT = LSAME(DIAG,'N')
-*
-*     Set up the start point in X if the increment is not unity. This
-*     will be  ( N - 1 )*INCX   too small for descending loops.
-*
-      IF (INCX.LE.0) THEN
-          KX = 1 - (N-1)*INCX
-      ELSE IF (INCX.NE.1) THEN
-          KX = 1
-      END IF
-*
-*     Start the operations. In this version the elements of A are
-*     accessed sequentially with one pass through A.
-*
-      IF (LSAME(TRANS,'N')) THEN
-*
-*         Form  x := A*x.
-*
-          IF (LSAME(UPLO,'U')) THEN
-              KPLUS1 = K + 1
-              IF (INCX.EQ.1) THEN
-                  DO 20 J = 1,N
-                      IF (X(J).NE.ZERO) THEN
-                          TEMP = X(J)
-                          L = KPLUS1 - J
-                          DO 10 I = MAX(1,J-K),J - 1
-                              X(I) = X(I) + TEMP*A(L+I,J)
-   10                     CONTINUE
-                          IF (NOUNIT) X(J) = X(J)*A(KPLUS1,J)
-                      END IF
-   20             CONTINUE
-              ELSE
-                  JX = KX
-                  DO 40 J = 1,N
-                      IF (X(JX).NE.ZERO) THEN
-                          TEMP = X(JX)
-                          IX = KX
-                          L = KPLUS1 - J
-                          DO 30 I = MAX(1,J-K),J - 1
-                              X(IX) = X(IX) + TEMP*A(L+I,J)
-                              IX = IX + INCX
-   30                     CONTINUE
-                          IF (NOUNIT) X(JX) = X(JX)*A(KPLUS1,J)
-                      END IF
-                      JX = JX + INCX
-                      IF (J.GT.K) KX = KX + INCX
-   40             CONTINUE
-              END IF
-          ELSE
-              IF (INCX.EQ.1) THEN
-                  DO 60 J = N,1,-1
-                      IF (X(J).NE.ZERO) THEN
-                          TEMP = X(J)
-                          L = 1 - J
-                          DO 50 I = MIN(N,J+K),J + 1,-1
-                              X(I) = X(I) + TEMP*A(L+I,J)
-   50                     CONTINUE
-                          IF (NOUNIT) X(J) = X(J)*A(1,J)
-                      END IF
-   60             CONTINUE
-              ELSE
-                  KX = KX + (N-1)*INCX
-                  JX = KX
-                  DO 80 J = N,1,-1
-                      IF (X(JX).NE.ZERO) THEN
-                          TEMP = X(JX)
-                          IX = KX
-                          L = 1 - J
-                          DO 70 I = MIN(N,J+K),J + 1,-1
-                              X(IX) = X(IX) + TEMP*A(L+I,J)
-                              IX = IX - INCX
-   70                     CONTINUE
-                          IF (NOUNIT) X(JX) = X(JX)*A(1,J)
-                      END IF
-                      JX = JX - INCX
-                      IF ((N-J).GE.K) KX = KX - INCX
-   80             CONTINUE
-              END IF
-          END IF
-      ELSE
-*
-*        Form  x := A'*x.
-*
-          IF (LSAME(UPLO,'U')) THEN
-              KPLUS1 = K + 1
-              IF (INCX.EQ.1) THEN
-                  DO 100 J = N,1,-1
-                      TEMP = X(J)
-                      L = KPLUS1 - J
-                      IF (NOUNIT) TEMP = TEMP*A(KPLUS1,J)
-                      DO 90 I = J - 1,MAX(1,J-K),-1
-                          TEMP = TEMP + A(L+I,J)*X(I)
-   90                 CONTINUE
-                      X(J) = TEMP
-  100             CONTINUE
-              ELSE
-                  KX = KX + (N-1)*INCX
-                  JX = KX
-                  DO 120 J = N,1,-1
-                      TEMP = X(JX)
-                      KX = KX - INCX
-                      IX = KX
-                      L = KPLUS1 - J
-                      IF (NOUNIT) TEMP = TEMP*A(KPLUS1,J)
-                      DO 110 I = J - 1,MAX(1,J-K),-1
-                          TEMP = TEMP + A(L+I,J)*X(IX)
-                          IX = IX - INCX
-  110                 CONTINUE
-                      X(JX) = TEMP
-                      JX = JX - INCX
-  120             CONTINUE
-              END IF
-          ELSE
-              IF (INCX.EQ.1) THEN
-                  DO 140 J = 1,N
-                      TEMP = X(J)
-                      L = 1 - J
-                      IF (NOUNIT) TEMP = TEMP*A(1,J)
-                      DO 130 I = J + 1,MIN(N,J+K)
-                          TEMP = TEMP + A(L+I,J)*X(I)
-  130                 CONTINUE
-                      X(J) = TEMP
-  140             CONTINUE
-              ELSE
-                  JX = KX
-                  DO 160 J = 1,N
-                      TEMP = X(JX)
-                      KX = KX + INCX
-                      IX = KX
-                      L = 1 - J
-                      IF (NOUNIT) TEMP = TEMP*A(1,J)
-                      DO 150 I = J + 1,MIN(N,J+K)
-                          TEMP = TEMP + A(L+I,J)*X(IX)
-                          IX = IX + INCX
-  150                 CONTINUE
-                      X(JX) = TEMP
-                      JX = JX + INCX
-  160             CONTINUE
-              END IF
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of DTBMV .
-*
-      END

ADDED   3rd_party/eigen/blas/f2c/chbmv.c
Index: 3rd_party/eigen/blas/f2c/chbmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/chbmv.c
+++ 3rd_party/eigen/blas/f2c/chbmv.c
@@ -0,0 +1,487 @@
+/* chbmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int chbmv_(char *uplo, integer *n, integer *k, complex *
+	alpha, complex *a, integer *lda, complex *x, integer *incx, complex *
+	beta, complex *y, integer *incy, ftnlen uplo_len)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5;
+    real r__1;
+    complex q__1, q__2, q__3, q__4;
+
+    /* Builtin functions */
+    void r_cnjg(complex *, complex *);
+
+    /* Local variables */
+    integer i__, j, l, ix, iy, jx, jy, kx, ky, info;
+    complex temp1, temp2;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    integer kplus1;
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  CHBMV  performs the matrix-vector  operation */
+
+/*     y := alpha*A*x + beta*y, */
+
+/*  where alpha and beta are scalars, x and y are n element vectors and */
+/*  A is an n by n hermitian band matrix, with k super-diagonals. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the upper or lower */
+/*           triangular part of the band matrix A is being supplied as */
+/*           follows: */
+
+/*              UPLO = 'U' or 'u'   The upper triangular part of A is */
+/*                                  being supplied. */
+
+/*              UPLO = 'L' or 'l'   The lower triangular part of A is */
+/*                                  being supplied. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  K      - INTEGER. */
+/*           On entry, K specifies the number of super-diagonals of the */
+/*           matrix A. K must satisfy  0 .le. K. */
+/*           Unchanged on exit. */
+
+/*  ALPHA  - COMPLEX         . */
+/*           On entry, ALPHA specifies the scalar alpha. */
+/*           Unchanged on exit. */
+
+/*  A      - COMPLEX          array of DIMENSION ( LDA, n ). */
+/*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the upper triangular */
+/*           band part of the hermitian matrix, supplied column by */
+/*           column, with the leading diagonal of the matrix in row */
+/*           ( k + 1 ) of the array, the first super-diagonal starting at */
+/*           position 2 in row k, and so on. The top left k by k triangle */
+/*           of the array A is not referenced. */
+/*           The following program segment will transfer the upper */
+/*           triangular part of a hermitian band matrix from conventional */
+/*           full matrix storage to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = K + 1 - J */
+/*                    DO 10, I = MAX( 1, J - K ), J */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the lower triangular */
+/*           band part of the hermitian matrix, supplied column by */
+/*           column, with the leading diagonal of the matrix in row 1 of */
+/*           the array, the first sub-diagonal starting at position 1 in */
+/*           row 2, and so on. The bottom right k by k triangle of the */
+/*           array A is not referenced. */
+/*           The following program segment will transfer the lower */
+/*           triangular part of a hermitian band matrix from conventional */
+/*           full matrix storage to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = 1 - J */
+/*                    DO 10, I = J, MIN( N, J + K ) */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Note that the imaginary parts of the diagonal elements need */
+/*           not be set and are assumed to be zero. */
+/*           Unchanged on exit. */
+
+/*  LDA    - INTEGER. */
+/*           On entry, LDA specifies the first dimension of A as declared */
+/*           in the calling (sub) program. LDA must be at least */
+/*           ( k + 1 ). */
+/*           Unchanged on exit. */
+
+/*  X      - COMPLEX          array of DIMENSION at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the */
+/*           vector x. */
+/*           Unchanged on exit. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  BETA   - COMPLEX         . */
+/*           On entry, BETA specifies the scalar beta. */
+/*           Unchanged on exit. */
+
+/*  Y      - COMPLEX          array of DIMENSION at least */
+/*           ( 1 + ( n - 1 )*abs( INCY ) ). */
+/*           Before entry, the incremented array Y must contain the */
+/*           vector y. On exit, Y is overwritten by the updated vector y. */
+
+/*  INCY   - INTEGER. */
+/*           On entry, INCY specifies the increment for the elements of */
+/*           Y. INCY must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    --x;
+    --y;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (*n < 0) {
+	info = 2;
+    } else if (*k < 0) {
+	info = 3;
+    } else if (*lda < *k + 1) {
+	info = 6;
+    } else if (*incx == 0) {
+	info = 8;
+    } else if (*incy == 0) {
+	info = 11;
+    }
+    if (info != 0) {
+	xerbla_("CHBMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0 || (alpha->r == 0.f && alpha->i == 0.f && (beta->r == 1.f && 
+                                                           beta->i == 0.f))) {
+	return 0;
+    }
+
+/*     Set up the start points in  X  and  Y. */
+
+    if (*incx > 0) {
+	kx = 1;
+    } else {
+	kx = 1 - (*n - 1) * *incx;
+    }
+    if (*incy > 0) {
+	ky = 1;
+    } else {
+	ky = 1 - (*n - 1) * *incy;
+    }
+
+/*     Start the operations. In this version the elements of the array A */
+/*     are accessed sequentially with one pass through A. */
+
+/*     First form  y := beta*y. */
+
+    if (beta->r != 1.f || beta->i != 0.f) {
+	if (*incy == 1) {
+	    if (beta->r == 0.f && beta->i == 0.f) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = i__;
+		    y[i__2].r = 0.f, y[i__2].i = 0.f;
+/* L10: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = i__;
+		    i__3 = i__;
+		    q__1.r = beta->r * y[i__3].r - beta->i * y[i__3].i, 
+			    q__1.i = beta->r * y[i__3].i + beta->i * y[i__3]
+			    .r;
+		    y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+/* L20: */
+		}
+	    }
+	} else {
+	    iy = ky;
+	    if (beta->r == 0.f && beta->i == 0.f) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = iy;
+		    y[i__2].r = 0.f, y[i__2].i = 0.f;
+		    iy += *incy;
+/* L30: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = iy;
+		    i__3 = iy;
+		    q__1.r = beta->r * y[i__3].r - beta->i * y[i__3].i, 
+			    q__1.i = beta->r * y[i__3].i + beta->i * y[i__3]
+			    .r;
+		    y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		    iy += *incy;
+/* L40: */
+		}
+	    }
+	}
+    }
+    if (alpha->r == 0.f && alpha->i == 0.f) {
+	return 0;
+    }
+    if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+
+/*        Form  y  when upper triangle of A is stored. */
+
+	kplus1 = *k + 1;
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = j;
+		q__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, q__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = q__1.r, temp1.i = q__1.i;
+		temp2.r = 0.f, temp2.i = 0.f;
+		l = kplus1 - j;
+/* Computing MAX */
+		i__2 = 1, i__3 = j - *k;
+		i__4 = j - 1;
+		for (i__ = max(i__2,i__3); i__ <= i__4; ++i__) {
+		    i__2 = i__;
+		    i__3 = i__;
+		    i__5 = l + i__ + j * a_dim1;
+		    q__2.r = temp1.r * a[i__5].r - temp1.i * a[i__5].i, 
+			    q__2.i = temp1.r * a[i__5].i + temp1.i * a[i__5]
+			    .r;
+		    q__1.r = y[i__3].r + q__2.r, q__1.i = y[i__3].i + q__2.i;
+		    y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		    r_cnjg(&q__3, &a[l + i__ + j * a_dim1]);
+		    i__2 = i__;
+		    q__2.r = q__3.r * x[i__2].r - q__3.i * x[i__2].i, q__2.i =
+			     q__3.r * x[i__2].i + q__3.i * x[i__2].r;
+		    q__1.r = temp2.r + q__2.r, q__1.i = temp2.i + q__2.i;
+		    temp2.r = q__1.r, temp2.i = q__1.i;
+/* L50: */
+		}
+		i__4 = j;
+		i__2 = j;
+		i__3 = kplus1 + j * a_dim1;
+		r__1 = a[i__3].r;
+		q__3.r = r__1 * temp1.r, q__3.i = r__1 * temp1.i;
+		q__2.r = y[i__2].r + q__3.r, q__2.i = y[i__2].i + q__3.i;
+		q__4.r = alpha->r * temp2.r - alpha->i * temp2.i, q__4.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		q__1.r = q__2.r + q__4.r, q__1.i = q__2.i + q__4.i;
+		y[i__4].r = q__1.r, y[i__4].i = q__1.i;
+/* L60: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__4 = jx;
+		q__1.r = alpha->r * x[i__4].r - alpha->i * x[i__4].i, q__1.i =
+			 alpha->r * x[i__4].i + alpha->i * x[i__4].r;
+		temp1.r = q__1.r, temp1.i = q__1.i;
+		temp2.r = 0.f, temp2.i = 0.f;
+		ix = kx;
+		iy = ky;
+		l = kplus1 - j;
+/* Computing MAX */
+		i__4 = 1, i__2 = j - *k;
+		i__3 = j - 1;
+		for (i__ = max(i__4,i__2); i__ <= i__3; ++i__) {
+		    i__4 = iy;
+		    i__2 = iy;
+		    i__5 = l + i__ + j * a_dim1;
+		    q__2.r = temp1.r * a[i__5].r - temp1.i * a[i__5].i, 
+			    q__2.i = temp1.r * a[i__5].i + temp1.i * a[i__5]
+			    .r;
+		    q__1.r = y[i__2].r + q__2.r, q__1.i = y[i__2].i + q__2.i;
+		    y[i__4].r = q__1.r, y[i__4].i = q__1.i;
+		    r_cnjg(&q__3, &a[l + i__ + j * a_dim1]);
+		    i__4 = ix;
+		    q__2.r = q__3.r * x[i__4].r - q__3.i * x[i__4].i, q__2.i =
+			     q__3.r * x[i__4].i + q__3.i * x[i__4].r;
+		    q__1.r = temp2.r + q__2.r, q__1.i = temp2.i + q__2.i;
+		    temp2.r = q__1.r, temp2.i = q__1.i;
+		    ix += *incx;
+		    iy += *incy;
+/* L70: */
+		}
+		i__3 = jy;
+		i__4 = jy;
+		i__2 = kplus1 + j * a_dim1;
+		r__1 = a[i__2].r;
+		q__3.r = r__1 * temp1.r, q__3.i = r__1 * temp1.i;
+		q__2.r = y[i__4].r + q__3.r, q__2.i = y[i__4].i + q__3.i;
+		q__4.r = alpha->r * temp2.r - alpha->i * temp2.i, q__4.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		q__1.r = q__2.r + q__4.r, q__1.i = q__2.i + q__4.i;
+		y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+		jx += *incx;
+		jy += *incy;
+		if (j > *k) {
+		    kx += *incx;
+		    ky += *incy;
+		}
+/* L80: */
+	    }
+	}
+    } else {
+
+/*        Form  y  when lower triangle of A is stored. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__3 = j;
+		q__1.r = alpha->r * x[i__3].r - alpha->i * x[i__3].i, q__1.i =
+			 alpha->r * x[i__3].i + alpha->i * x[i__3].r;
+		temp1.r = q__1.r, temp1.i = q__1.i;
+		temp2.r = 0.f, temp2.i = 0.f;
+		i__3 = j;
+		i__4 = j;
+		i__2 = j * a_dim1 + 1;
+		r__1 = a[i__2].r;
+		q__2.r = r__1 * temp1.r, q__2.i = r__1 * temp1.i;
+		q__1.r = y[i__4].r + q__2.r, q__1.i = y[i__4].i + q__2.i;
+		y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+		l = 1 - j;
+/* Computing MIN */
+		i__4 = *n, i__2 = j + *k;
+		i__3 = min(i__4,i__2);
+		for (i__ = j + 1; i__ <= i__3; ++i__) {
+		    i__4 = i__;
+		    i__2 = i__;
+		    i__5 = l + i__ + j * a_dim1;
+		    q__2.r = temp1.r * a[i__5].r - temp1.i * a[i__5].i, 
+			    q__2.i = temp1.r * a[i__5].i + temp1.i * a[i__5]
+			    .r;
+		    q__1.r = y[i__2].r + q__2.r, q__1.i = y[i__2].i + q__2.i;
+		    y[i__4].r = q__1.r, y[i__4].i = q__1.i;
+		    r_cnjg(&q__3, &a[l + i__ + j * a_dim1]);
+		    i__4 = i__;
+		    q__2.r = q__3.r * x[i__4].r - q__3.i * x[i__4].i, q__2.i =
+			     q__3.r * x[i__4].i + q__3.i * x[i__4].r;
+		    q__1.r = temp2.r + q__2.r, q__1.i = temp2.i + q__2.i;
+		    temp2.r = q__1.r, temp2.i = q__1.i;
+/* L90: */
+		}
+		i__3 = j;
+		i__4 = j;
+		q__2.r = alpha->r * temp2.r - alpha->i * temp2.i, q__2.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		q__1.r = y[i__4].r + q__2.r, q__1.i = y[i__4].i + q__2.i;
+		y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+/* L100: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__3 = jx;
+		q__1.r = alpha->r * x[i__3].r - alpha->i * x[i__3].i, q__1.i =
+			 alpha->r * x[i__3].i + alpha->i * x[i__3].r;
+		temp1.r = q__1.r, temp1.i = q__1.i;
+		temp2.r = 0.f, temp2.i = 0.f;
+		i__3 = jy;
+		i__4 = jy;
+		i__2 = j * a_dim1 + 1;
+		r__1 = a[i__2].r;
+		q__2.r = r__1 * temp1.r, q__2.i = r__1 * temp1.i;
+		q__1.r = y[i__4].r + q__2.r, q__1.i = y[i__4].i + q__2.i;
+		y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+		l = 1 - j;
+		ix = jx;
+		iy = jy;
+/* Computing MIN */
+		i__4 = *n, i__2 = j + *k;
+		i__3 = min(i__4,i__2);
+		for (i__ = j + 1; i__ <= i__3; ++i__) {
+		    ix += *incx;
+		    iy += *incy;
+		    i__4 = iy;
+		    i__2 = iy;
+		    i__5 = l + i__ + j * a_dim1;
+		    q__2.r = temp1.r * a[i__5].r - temp1.i * a[i__5].i, 
+			    q__2.i = temp1.r * a[i__5].i + temp1.i * a[i__5]
+			    .r;
+		    q__1.r = y[i__2].r + q__2.r, q__1.i = y[i__2].i + q__2.i;
+		    y[i__4].r = q__1.r, y[i__4].i = q__1.i;
+		    r_cnjg(&q__3, &a[l + i__ + j * a_dim1]);
+		    i__4 = ix;
+		    q__2.r = q__3.r * x[i__4].r - q__3.i * x[i__4].i, q__2.i =
+			     q__3.r * x[i__4].i + q__3.i * x[i__4].r;
+		    q__1.r = temp2.r + q__2.r, q__1.i = temp2.i + q__2.i;
+		    temp2.r = q__1.r, temp2.i = q__1.i;
+/* L110: */
+		}
+		i__3 = jy;
+		i__4 = jy;
+		q__2.r = alpha->r * temp2.r - alpha->i * temp2.i, q__2.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		q__1.r = y[i__4].r + q__2.r, q__1.i = y[i__4].i + q__2.i;
+		y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+		jx += *incx;
+		jy += *incy;
+/* L120: */
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of CHBMV . */
+
+} /* chbmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/chpmv.c
Index: 3rd_party/eigen/blas/f2c/chpmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/chpmv.c
+++ 3rd_party/eigen/blas/f2c/chpmv.c
@@ -0,0 +1,438 @@
+/* chpmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int chpmv_(char *uplo, integer *n, complex *alpha, complex *
+	ap, complex *x, integer *incx, complex *beta, complex *y, integer *
+	incy, ftnlen uplo_len)
+{
+    /* System generated locals */
+    integer i__1, i__2, i__3, i__4, i__5;
+    real r__1;
+    complex q__1, q__2, q__3, q__4;
+
+    /* Builtin functions */
+    void r_cnjg(complex *, complex *);
+
+    /* Local variables */
+    integer i__, j, k, kk, ix, iy, jx, jy, kx, ky, info;
+    complex temp1, temp2;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  CHPMV  performs the matrix-vector operation */
+
+/*     y := alpha*A*x + beta*y, */
+
+/*  where alpha and beta are scalars, x and y are n element vectors and */
+/*  A is an n by n hermitian matrix, supplied in packed form. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the upper or lower */
+/*           triangular part of the matrix A is supplied in the packed */
+/*           array AP as follows: */
+
+/*              UPLO = 'U' or 'u'   The upper triangular part of A is */
+/*                                  supplied in AP. */
+
+/*              UPLO = 'L' or 'l'   The lower triangular part of A is */
+/*                                  supplied in AP. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  ALPHA  - COMPLEX         . */
+/*           On entry, ALPHA specifies the scalar alpha. */
+/*           Unchanged on exit. */
+
+/*  AP     - COMPLEX          array of DIMENSION at least */
+/*           ( ( n*( n + 1 ) )/2 ). */
+/*           Before entry with UPLO = 'U' or 'u', the array AP must */
+/*           contain the upper triangular part of the hermitian matrix */
+/*           packed sequentially, column by column, so that AP( 1 ) */
+/*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 ) */
+/*           and a( 2, 2 ) respectively, and so on. */
+/*           Before entry with UPLO = 'L' or 'l', the array AP must */
+/*           contain the lower triangular part of the hermitian matrix */
+/*           packed sequentially, column by column, so that AP( 1 ) */
+/*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 ) */
+/*           and a( 3, 1 ) respectively, and so on. */
+/*           Note that the imaginary parts of the diagonal elements need */
+/*           not be set and are assumed to be zero. */
+/*           Unchanged on exit. */
+
+/*  X      - COMPLEX          array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the n */
+/*           element vector x. */
+/*           Unchanged on exit. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  BETA   - COMPLEX         . */
+/*           On entry, BETA specifies the scalar beta. When BETA is */
+/*           supplied as zero then Y need not be set on input. */
+/*           Unchanged on exit. */
+
+/*  Y      - COMPLEX          array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCY ) ). */
+/*           Before entry, the incremented array Y must contain the n */
+/*           element vector y. On exit, Y is overwritten by the updated */
+/*           vector y. */
+
+/*  INCY   - INTEGER. */
+/*           On entry, INCY specifies the increment for the elements of */
+/*           Y. INCY must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    --y;
+    --x;
+    --ap;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (*n < 0) {
+	info = 2;
+    } else if (*incx == 0) {
+	info = 6;
+    } else if (*incy == 0) {
+	info = 9;
+    }
+    if (info != 0) {
+	xerbla_("CHPMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0 || (alpha->r == 0.f && alpha->i == 0.f && (beta->r == 1.f && 
+                                                           beta->i == 0.f))) {
+	return 0;
+    }
+
+/*     Set up the start points in  X  and  Y. */
+
+    if (*incx > 0) {
+	kx = 1;
+    } else {
+	kx = 1 - (*n - 1) * *incx;
+    }
+    if (*incy > 0) {
+	ky = 1;
+    } else {
+	ky = 1 - (*n - 1) * *incy;
+    }
+
+/*     Start the operations. In this version the elements of the array AP */
+/*     are accessed sequentially with one pass through AP. */
+
+/*     First form  y := beta*y. */
+
+    if (beta->r != 1.f || beta->i != 0.f) {
+	if (*incy == 1) {
+	    if (beta->r == 0.f && beta->i == 0.f) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = i__;
+		    y[i__2].r = 0.f, y[i__2].i = 0.f;
+/* L10: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = i__;
+		    i__3 = i__;
+		    q__1.r = beta->r * y[i__3].r - beta->i * y[i__3].i, 
+			    q__1.i = beta->r * y[i__3].i + beta->i * y[i__3]
+			    .r;
+		    y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+/* L20: */
+		}
+	    }
+	} else {
+	    iy = ky;
+	    if (beta->r == 0.f && beta->i == 0.f) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = iy;
+		    y[i__2].r = 0.f, y[i__2].i = 0.f;
+		    iy += *incy;
+/* L30: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = iy;
+		    i__3 = iy;
+		    q__1.r = beta->r * y[i__3].r - beta->i * y[i__3].i, 
+			    q__1.i = beta->r * y[i__3].i + beta->i * y[i__3]
+			    .r;
+		    y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		    iy += *incy;
+/* L40: */
+		}
+	    }
+	}
+    }
+    if (alpha->r == 0.f && alpha->i == 0.f) {
+	return 0;
+    }
+    kk = 1;
+    if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+
+/*        Form  y  when AP contains the upper triangle. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = j;
+		q__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, q__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = q__1.r, temp1.i = q__1.i;
+		temp2.r = 0.f, temp2.i = 0.f;
+		k = kk;
+		i__2 = j - 1;
+		for (i__ = 1; i__ <= i__2; ++i__) {
+		    i__3 = i__;
+		    i__4 = i__;
+		    i__5 = k;
+		    q__2.r = temp1.r * ap[i__5].r - temp1.i * ap[i__5].i, 
+			    q__2.i = temp1.r * ap[i__5].i + temp1.i * ap[i__5]
+			    .r;
+		    q__1.r = y[i__4].r + q__2.r, q__1.i = y[i__4].i + q__2.i;
+		    y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+		    r_cnjg(&q__3, &ap[k]);
+		    i__3 = i__;
+		    q__2.r = q__3.r * x[i__3].r - q__3.i * x[i__3].i, q__2.i =
+			     q__3.r * x[i__3].i + q__3.i * x[i__3].r;
+		    q__1.r = temp2.r + q__2.r, q__1.i = temp2.i + q__2.i;
+		    temp2.r = q__1.r, temp2.i = q__1.i;
+		    ++k;
+/* L50: */
+		}
+		i__2 = j;
+		i__3 = j;
+		i__4 = kk + j - 1;
+		r__1 = ap[i__4].r;
+		q__3.r = r__1 * temp1.r, q__3.i = r__1 * temp1.i;
+		q__2.r = y[i__3].r + q__3.r, q__2.i = y[i__3].i + q__3.i;
+		q__4.r = alpha->r * temp2.r - alpha->i * temp2.i, q__4.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		q__1.r = q__2.r + q__4.r, q__1.i = q__2.i + q__4.i;
+		y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		kk += j;
+/* L60: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = jx;
+		q__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, q__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = q__1.r, temp1.i = q__1.i;
+		temp2.r = 0.f, temp2.i = 0.f;
+		ix = kx;
+		iy = ky;
+		i__2 = kk + j - 2;
+		for (k = kk; k <= i__2; ++k) {
+		    i__3 = iy;
+		    i__4 = iy;
+		    i__5 = k;
+		    q__2.r = temp1.r * ap[i__5].r - temp1.i * ap[i__5].i, 
+			    q__2.i = temp1.r * ap[i__5].i + temp1.i * ap[i__5]
+			    .r;
+		    q__1.r = y[i__4].r + q__2.r, q__1.i = y[i__4].i + q__2.i;
+		    y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+		    r_cnjg(&q__3, &ap[k]);
+		    i__3 = ix;
+		    q__2.r = q__3.r * x[i__3].r - q__3.i * x[i__3].i, q__2.i =
+			     q__3.r * x[i__3].i + q__3.i * x[i__3].r;
+		    q__1.r = temp2.r + q__2.r, q__1.i = temp2.i + q__2.i;
+		    temp2.r = q__1.r, temp2.i = q__1.i;
+		    ix += *incx;
+		    iy += *incy;
+/* L70: */
+		}
+		i__2 = jy;
+		i__3 = jy;
+		i__4 = kk + j - 1;
+		r__1 = ap[i__4].r;
+		q__3.r = r__1 * temp1.r, q__3.i = r__1 * temp1.i;
+		q__2.r = y[i__3].r + q__3.r, q__2.i = y[i__3].i + q__3.i;
+		q__4.r = alpha->r * temp2.r - alpha->i * temp2.i, q__4.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		q__1.r = q__2.r + q__4.r, q__1.i = q__2.i + q__4.i;
+		y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		jx += *incx;
+		jy += *incy;
+		kk += j;
+/* L80: */
+	    }
+	}
+    } else {
+
+/*        Form  y  when AP contains the lower triangle. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = j;
+		q__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, q__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = q__1.r, temp1.i = q__1.i;
+		temp2.r = 0.f, temp2.i = 0.f;
+		i__2 = j;
+		i__3 = j;
+		i__4 = kk;
+		r__1 = ap[i__4].r;
+		q__2.r = r__1 * temp1.r, q__2.i = r__1 * temp1.i;
+		q__1.r = y[i__3].r + q__2.r, q__1.i = y[i__3].i + q__2.i;
+		y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		k = kk + 1;
+		i__2 = *n;
+		for (i__ = j + 1; i__ <= i__2; ++i__) {
+		    i__3 = i__;
+		    i__4 = i__;
+		    i__5 = k;
+		    q__2.r = temp1.r * ap[i__5].r - temp1.i * ap[i__5].i, 
+			    q__2.i = temp1.r * ap[i__5].i + temp1.i * ap[i__5]
+			    .r;
+		    q__1.r = y[i__4].r + q__2.r, q__1.i = y[i__4].i + q__2.i;
+		    y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+		    r_cnjg(&q__3, &ap[k]);
+		    i__3 = i__;
+		    q__2.r = q__3.r * x[i__3].r - q__3.i * x[i__3].i, q__2.i =
+			     q__3.r * x[i__3].i + q__3.i * x[i__3].r;
+		    q__1.r = temp2.r + q__2.r, q__1.i = temp2.i + q__2.i;
+		    temp2.r = q__1.r, temp2.i = q__1.i;
+		    ++k;
+/* L90: */
+		}
+		i__2 = j;
+		i__3 = j;
+		q__2.r = alpha->r * temp2.r - alpha->i * temp2.i, q__2.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		q__1.r = y[i__3].r + q__2.r, q__1.i = y[i__3].i + q__2.i;
+		y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		kk += *n - j + 1;
+/* L100: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = jx;
+		q__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, q__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = q__1.r, temp1.i = q__1.i;
+		temp2.r = 0.f, temp2.i = 0.f;
+		i__2 = jy;
+		i__3 = jy;
+		i__4 = kk;
+		r__1 = ap[i__4].r;
+		q__2.r = r__1 * temp1.r, q__2.i = r__1 * temp1.i;
+		q__1.r = y[i__3].r + q__2.r, q__1.i = y[i__3].i + q__2.i;
+		y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		ix = jx;
+		iy = jy;
+		i__2 = kk + *n - j;
+		for (k = kk + 1; k <= i__2; ++k) {
+		    ix += *incx;
+		    iy += *incy;
+		    i__3 = iy;
+		    i__4 = iy;
+		    i__5 = k;
+		    q__2.r = temp1.r * ap[i__5].r - temp1.i * ap[i__5].i, 
+			    q__2.i = temp1.r * ap[i__5].i + temp1.i * ap[i__5]
+			    .r;
+		    q__1.r = y[i__4].r + q__2.r, q__1.i = y[i__4].i + q__2.i;
+		    y[i__3].r = q__1.r, y[i__3].i = q__1.i;
+		    r_cnjg(&q__3, &ap[k]);
+		    i__3 = ix;
+		    q__2.r = q__3.r * x[i__3].r - q__3.i * x[i__3].i, q__2.i =
+			     q__3.r * x[i__3].i + q__3.i * x[i__3].r;
+		    q__1.r = temp2.r + q__2.r, q__1.i = temp2.i + q__2.i;
+		    temp2.r = q__1.r, temp2.i = q__1.i;
+/* L110: */
+		}
+		i__2 = jy;
+		i__3 = jy;
+		q__2.r = alpha->r * temp2.r - alpha->i * temp2.i, q__2.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		q__1.r = y[i__3].r + q__2.r, q__1.i = y[i__3].i + q__2.i;
+		y[i__2].r = q__1.r, y[i__2].i = q__1.i;
+		jx += *incx;
+		jy += *incy;
+		kk += *n - j + 1;
+/* L120: */
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of CHPMV . */
+
+} /* chpmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/complexdots.c
Index: 3rd_party/eigen/blas/f2c/complexdots.c
==================================================================
--- 3rd_party/eigen/blas/f2c/complexdots.c
+++ 3rd_party/eigen/blas/f2c/complexdots.c
@@ -0,0 +1,84 @@
+/* This file has been modified to use the standard gfortran calling
+   convention, rather than the f2c calling convention.
+
+   It does not require -ff2c when compiled with gfortran.
+*/
+
+/* complexdots.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+complex cdotc_(integer *n, complex *cx, integer 
+	*incx, complex *cy, integer *incy)
+{
+    complex res;
+    extern /* Subroutine */ int cdotcw_(integer *, complex *, integer *, 
+	    complex *, integer *, complex *);
+
+    /* Parameter adjustments */
+    --cy;
+    --cx;
+
+    /* Function Body */
+    cdotcw_(n, &cx[1], incx, &cy[1], incy, &res);
+    return res;
+} /* cdotc_ */
+
+complex cdotu_(integer *n, complex *cx, integer 
+	*incx, complex *cy, integer *incy)
+{
+    complex res;
+    extern /* Subroutine */ int cdotuw_(integer *, complex *, integer *, 
+	    complex *, integer *, complex *);
+
+    /* Parameter adjustments */
+    --cy;
+    --cx;
+
+    /* Function Body */
+    cdotuw_(n, &cx[1], incx, &cy[1], incy, &res);
+    return res;
+} /* cdotu_ */
+
+doublecomplex zdotc_(integer *n, doublecomplex *cx, integer *incx, 
+                     doublecomplex *cy, integer *incy)
+{
+    doublecomplex res;
+    extern /* Subroutine */ int zdotcw_(integer *, doublecomplex *, integer *,
+	     doublecomplex *, integer *, doublecomplex *);
+
+    /* Parameter adjustments */
+    --cy;
+    --cx;
+
+    /* Function Body */
+    zdotcw_(n, &cx[1], incx, &cy[1], incy, &res);
+    return res;
+} /* zdotc_ */
+
+doublecomplex zdotu_(integer *n, doublecomplex *cx, integer *incx, 
+                     doublecomplex *cy, integer *incy)
+{
+    doublecomplex res;
+    extern /* Subroutine */ int zdotuw_(integer *, doublecomplex *, integer *,
+	     doublecomplex *, integer *, doublecomplex *);
+
+    /* Parameter adjustments */
+    --cy;
+    --cx;
+
+    /* Function Body */
+    zdotuw_(n, &cx[1], incx, &cy[1], incy, &res);
+    return res;
+} /* zdotu_ */
+

ADDED   3rd_party/eigen/blas/f2c/ctbmv.c
Index: 3rd_party/eigen/blas/f2c/ctbmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/ctbmv.c
+++ 3rd_party/eigen/blas/f2c/ctbmv.c
@@ -0,0 +1,647 @@
+/* ctbmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int ctbmv_(char *uplo, char *trans, char *diag, integer *n, 
+	integer *k, complex *a, integer *lda, complex *x, integer *incx, 
+	ftnlen uplo_len, ftnlen trans_len, ftnlen diag_len)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5;
+    complex q__1, q__2, q__3;
+
+    /* Builtin functions */
+    void r_cnjg(complex *, complex *);
+
+    /* Local variables */
+    integer i__, j, l, ix, jx, kx, info;
+    complex temp;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    integer kplus1;
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+    logical noconj, nounit;
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  CTBMV  performs one of the matrix-vector operations */
+
+/*     x := A*x,   or   x := A'*x,   or   x := conjg( A' )*x, */
+
+/*  where x is an n element vector and  A is an n by n unit, or non-unit, */
+/*  upper or lower triangular band matrix, with ( k + 1 ) diagonals. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the matrix is an upper or */
+/*           lower triangular matrix as follows: */
+
+/*              UPLO = 'U' or 'u'   A is an upper triangular matrix. */
+
+/*              UPLO = 'L' or 'l'   A is a lower triangular matrix. */
+
+/*           Unchanged on exit. */
+
+/*  TRANS  - CHARACTER*1. */
+/*           On entry, TRANS specifies the operation to be performed as */
+/*           follows: */
+
+/*              TRANS = 'N' or 'n'   x := A*x. */
+
+/*              TRANS = 'T' or 't'   x := A'*x. */
+
+/*              TRANS = 'C' or 'c'   x := conjg( A' )*x. */
+
+/*           Unchanged on exit. */
+
+/*  DIAG   - CHARACTER*1. */
+/*           On entry, DIAG specifies whether or not A is unit */
+/*           triangular as follows: */
+
+/*              DIAG = 'U' or 'u'   A is assumed to be unit triangular. */
+
+/*              DIAG = 'N' or 'n'   A is not assumed to be unit */
+/*                                  triangular. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  K      - INTEGER. */
+/*           On entry with UPLO = 'U' or 'u', K specifies the number of */
+/*           super-diagonals of the matrix A. */
+/*           On entry with UPLO = 'L' or 'l', K specifies the number of */
+/*           sub-diagonals of the matrix A. */
+/*           K must satisfy  0 .le. K. */
+/*           Unchanged on exit. */
+
+/*  A      - COMPLEX          array of DIMENSION ( LDA, n ). */
+/*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the upper triangular */
+/*           band part of the matrix of coefficients, supplied column by */
+/*           column, with the leading diagonal of the matrix in row */
+/*           ( k + 1 ) of the array, the first super-diagonal starting at */
+/*           position 2 in row k, and so on. The top left k by k triangle */
+/*           of the array A is not referenced. */
+/*           The following program segment will transfer an upper */
+/*           triangular band matrix from conventional full matrix storage */
+/*           to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = K + 1 - J */
+/*                    DO 10, I = MAX( 1, J - K ), J */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the lower triangular */
+/*           band part of the matrix of coefficients, supplied column by */
+/*           column, with the leading diagonal of the matrix in row 1 of */
+/*           the array, the first sub-diagonal starting at position 1 in */
+/*           row 2, and so on. The bottom right k by k triangle of the */
+/*           array A is not referenced. */
+/*           The following program segment will transfer a lower */
+/*           triangular band matrix from conventional full matrix storage */
+/*           to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = 1 - J */
+/*                    DO 10, I = J, MIN( N, J + K ) */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Note that when DIAG = 'U' or 'u' the elements of the array A */
+/*           corresponding to the diagonal elements of the matrix are not */
+/*           referenced, but are assumed to be unity. */
+/*           Unchanged on exit. */
+
+/*  LDA    - INTEGER. */
+/*           On entry, LDA specifies the first dimension of A as declared */
+/*           in the calling (sub) program. LDA must be at least */
+/*           ( k + 1 ). */
+/*           Unchanged on exit. */
+
+/*  X      - COMPLEX          array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the n */
+/*           element vector x. On exit, X is overwritten with the */
+/*           tranformed vector x. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    --x;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (! lsame_(trans, "N", (ftnlen)1, (ftnlen)1) && ! lsame_(trans, 
+	    "T", (ftnlen)1, (ftnlen)1) && ! lsame_(trans, "C", (ftnlen)1, (
+	    ftnlen)1)) {
+	info = 2;
+    } else if (! lsame_(diag, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(diag, 
+	    "N", (ftnlen)1, (ftnlen)1)) {
+	info = 3;
+    } else if (*n < 0) {
+	info = 4;
+    } else if (*k < 0) {
+	info = 5;
+    } else if (*lda < *k + 1) {
+	info = 7;
+    } else if (*incx == 0) {
+	info = 9;
+    }
+    if (info != 0) {
+	xerbla_("CTBMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0) {
+	return 0;
+    }
+
+    noconj = lsame_(trans, "T", (ftnlen)1, (ftnlen)1);
+    nounit = lsame_(diag, "N", (ftnlen)1, (ftnlen)1);
+
+/*     Set up the start point in X if the increment is not unity. This */
+/*     will be  ( N - 1 )*INCX   too small for descending loops. */
+
+    if (*incx <= 0) {
+	kx = 1 - (*n - 1) * *incx;
+    } else if (*incx != 1) {
+	kx = 1;
+    }
+
+/*     Start the operations. In this version the elements of A are */
+/*     accessed sequentially with one pass through A. */
+
+    if (lsame_(trans, "N", (ftnlen)1, (ftnlen)1)) {
+
+/*         Form  x := A*x. */
+
+	if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+	    kplus1 = *k + 1;
+	    if (*incx == 1) {
+		i__1 = *n;
+		for (j = 1; j <= i__1; ++j) {
+		    i__2 = j;
+		    if (x[i__2].r != 0.f || x[i__2].i != 0.f) {
+			i__2 = j;
+			temp.r = x[i__2].r, temp.i = x[i__2].i;
+			l = kplus1 - j;
+/* Computing MAX */
+			i__2 = 1, i__3 = j - *k;
+			i__4 = j - 1;
+			for (i__ = max(i__2,i__3); i__ <= i__4; ++i__) {
+			    i__2 = i__;
+			    i__3 = i__;
+			    i__5 = l + i__ + j * a_dim1;
+			    q__2.r = temp.r * a[i__5].r - temp.i * a[i__5].i, 
+				    q__2.i = temp.r * a[i__5].i + temp.i * a[
+				    i__5].r;
+			    q__1.r = x[i__3].r + q__2.r, q__1.i = x[i__3].i + 
+				    q__2.i;
+			    x[i__2].r = q__1.r, x[i__2].i = q__1.i;
+/* L10: */
+			}
+			if (nounit) {
+			    i__4 = j;
+			    i__2 = j;
+			    i__3 = kplus1 + j * a_dim1;
+			    q__1.r = x[i__2].r * a[i__3].r - x[i__2].i * a[
+				    i__3].i, q__1.i = x[i__2].r * a[i__3].i + 
+				    x[i__2].i * a[i__3].r;
+			    x[i__4].r = q__1.r, x[i__4].i = q__1.i;
+			}
+		    }
+/* L20: */
+		}
+	    } else {
+		jx = kx;
+		i__1 = *n;
+		for (j = 1; j <= i__1; ++j) {
+		    i__4 = jx;
+		    if (x[i__4].r != 0.f || x[i__4].i != 0.f) {
+			i__4 = jx;
+			temp.r = x[i__4].r, temp.i = x[i__4].i;
+			ix = kx;
+			l = kplus1 - j;
+/* Computing MAX */
+			i__4 = 1, i__2 = j - *k;
+			i__3 = j - 1;
+			for (i__ = max(i__4,i__2); i__ <= i__3; ++i__) {
+			    i__4 = ix;
+			    i__2 = ix;
+			    i__5 = l + i__ + j * a_dim1;
+			    q__2.r = temp.r * a[i__5].r - temp.i * a[i__5].i, 
+				    q__2.i = temp.r * a[i__5].i + temp.i * a[
+				    i__5].r;
+			    q__1.r = x[i__2].r + q__2.r, q__1.i = x[i__2].i + 
+				    q__2.i;
+			    x[i__4].r = q__1.r, x[i__4].i = q__1.i;
+			    ix += *incx;
+/* L30: */
+			}
+			if (nounit) {
+			    i__3 = jx;
+			    i__4 = jx;
+			    i__2 = kplus1 + j * a_dim1;
+			    q__1.r = x[i__4].r * a[i__2].r - x[i__4].i * a[
+				    i__2].i, q__1.i = x[i__4].r * a[i__2].i + 
+				    x[i__4].i * a[i__2].r;
+			    x[i__3].r = q__1.r, x[i__3].i = q__1.i;
+			}
+		    }
+		    jx += *incx;
+		    if (j > *k) {
+			kx += *incx;
+		    }
+/* L40: */
+		}
+	    }
+	} else {
+	    if (*incx == 1) {
+		for (j = *n; j >= 1; --j) {
+		    i__1 = j;
+		    if (x[i__1].r != 0.f || x[i__1].i != 0.f) {
+			i__1 = j;
+			temp.r = x[i__1].r, temp.i = x[i__1].i;
+			l = 1 - j;
+/* Computing MIN */
+			i__1 = *n, i__3 = j + *k;
+			i__4 = j + 1;
+			for (i__ = min(i__1,i__3); i__ >= i__4; --i__) {
+			    i__1 = i__;
+			    i__3 = i__;
+			    i__2 = l + i__ + j * a_dim1;
+			    q__2.r = temp.r * a[i__2].r - temp.i * a[i__2].i, 
+				    q__2.i = temp.r * a[i__2].i + temp.i * a[
+				    i__2].r;
+			    q__1.r = x[i__3].r + q__2.r, q__1.i = x[i__3].i + 
+				    q__2.i;
+			    x[i__1].r = q__1.r, x[i__1].i = q__1.i;
+/* L50: */
+			}
+			if (nounit) {
+			    i__4 = j;
+			    i__1 = j;
+			    i__3 = j * a_dim1 + 1;
+			    q__1.r = x[i__1].r * a[i__3].r - x[i__1].i * a[
+				    i__3].i, q__1.i = x[i__1].r * a[i__3].i + 
+				    x[i__1].i * a[i__3].r;
+			    x[i__4].r = q__1.r, x[i__4].i = q__1.i;
+			}
+		    }
+/* L60: */
+		}
+	    } else {
+		kx += (*n - 1) * *incx;
+		jx = kx;
+		for (j = *n; j >= 1; --j) {
+		    i__4 = jx;
+		    if (x[i__4].r != 0.f || x[i__4].i != 0.f) {
+			i__4 = jx;
+			temp.r = x[i__4].r, temp.i = x[i__4].i;
+			ix = kx;
+			l = 1 - j;
+/* Computing MIN */
+			i__4 = *n, i__1 = j + *k;
+			i__3 = j + 1;
+			for (i__ = min(i__4,i__1); i__ >= i__3; --i__) {
+			    i__4 = ix;
+			    i__1 = ix;
+			    i__2 = l + i__ + j * a_dim1;
+			    q__2.r = temp.r * a[i__2].r - temp.i * a[i__2].i, 
+				    q__2.i = temp.r * a[i__2].i + temp.i * a[
+				    i__2].r;
+			    q__1.r = x[i__1].r + q__2.r, q__1.i = x[i__1].i + 
+				    q__2.i;
+			    x[i__4].r = q__1.r, x[i__4].i = q__1.i;
+			    ix -= *incx;
+/* L70: */
+			}
+			if (nounit) {
+			    i__3 = jx;
+			    i__4 = jx;
+			    i__1 = j * a_dim1 + 1;
+			    q__1.r = x[i__4].r * a[i__1].r - x[i__4].i * a[
+				    i__1].i, q__1.i = x[i__4].r * a[i__1].i + 
+				    x[i__4].i * a[i__1].r;
+			    x[i__3].r = q__1.r, x[i__3].i = q__1.i;
+			}
+		    }
+		    jx -= *incx;
+		    if (*n - j >= *k) {
+			kx -= *incx;
+		    }
+/* L80: */
+		}
+	    }
+	}
+    } else {
+
+/*        Form  x := A'*x  or  x := conjg( A' )*x. */
+
+	if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+	    kplus1 = *k + 1;
+	    if (*incx == 1) {
+		for (j = *n; j >= 1; --j) {
+		    i__3 = j;
+		    temp.r = x[i__3].r, temp.i = x[i__3].i;
+		    l = kplus1 - j;
+		    if (noconj) {
+			if (nounit) {
+			    i__3 = kplus1 + j * a_dim1;
+			    q__1.r = temp.r * a[i__3].r - temp.i * a[i__3].i, 
+				    q__1.i = temp.r * a[i__3].i + temp.i * a[
+				    i__3].r;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			}
+/* Computing MAX */
+			i__4 = 1, i__1 = j - *k;
+			i__3 = max(i__4,i__1);
+			for (i__ = j - 1; i__ >= i__3; --i__) {
+			    i__4 = l + i__ + j * a_dim1;
+			    i__1 = i__;
+			    q__2.r = a[i__4].r * x[i__1].r - a[i__4].i * x[
+				    i__1].i, q__2.i = a[i__4].r * x[i__1].i + 
+				    a[i__4].i * x[i__1].r;
+			    q__1.r = temp.r + q__2.r, q__1.i = temp.i + 
+				    q__2.i;
+			    temp.r = q__1.r, temp.i = q__1.i;
+/* L90: */
+			}
+		    } else {
+			if (nounit) {
+			    r_cnjg(&q__2, &a[kplus1 + j * a_dim1]);
+			    q__1.r = temp.r * q__2.r - temp.i * q__2.i, 
+				    q__1.i = temp.r * q__2.i + temp.i * 
+				    q__2.r;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			}
+/* Computing MAX */
+			i__4 = 1, i__1 = j - *k;
+			i__3 = max(i__4,i__1);
+			for (i__ = j - 1; i__ >= i__3; --i__) {
+			    r_cnjg(&q__3, &a[l + i__ + j * a_dim1]);
+			    i__4 = i__;
+			    q__2.r = q__3.r * x[i__4].r - q__3.i * x[i__4].i, 
+				    q__2.i = q__3.r * x[i__4].i + q__3.i * x[
+				    i__4].r;
+			    q__1.r = temp.r + q__2.r, q__1.i = temp.i + 
+				    q__2.i;
+			    temp.r = q__1.r, temp.i = q__1.i;
+/* L100: */
+			}
+		    }
+		    i__3 = j;
+		    x[i__3].r = temp.r, x[i__3].i = temp.i;
+/* L110: */
+		}
+	    } else {
+		kx += (*n - 1) * *incx;
+		jx = kx;
+		for (j = *n; j >= 1; --j) {
+		    i__3 = jx;
+		    temp.r = x[i__3].r, temp.i = x[i__3].i;
+		    kx -= *incx;
+		    ix = kx;
+		    l = kplus1 - j;
+		    if (noconj) {
+			if (nounit) {
+			    i__3 = kplus1 + j * a_dim1;
+			    q__1.r = temp.r * a[i__3].r - temp.i * a[i__3].i, 
+				    q__1.i = temp.r * a[i__3].i + temp.i * a[
+				    i__3].r;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			}
+/* Computing MAX */
+			i__4 = 1, i__1 = j - *k;
+			i__3 = max(i__4,i__1);
+			for (i__ = j - 1; i__ >= i__3; --i__) {
+			    i__4 = l + i__ + j * a_dim1;
+			    i__1 = ix;
+			    q__2.r = a[i__4].r * x[i__1].r - a[i__4].i * x[
+				    i__1].i, q__2.i = a[i__4].r * x[i__1].i + 
+				    a[i__4].i * x[i__1].r;
+			    q__1.r = temp.r + q__2.r, q__1.i = temp.i + 
+				    q__2.i;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			    ix -= *incx;
+/* L120: */
+			}
+		    } else {
+			if (nounit) {
+			    r_cnjg(&q__2, &a[kplus1 + j * a_dim1]);
+			    q__1.r = temp.r * q__2.r - temp.i * q__2.i, 
+				    q__1.i = temp.r * q__2.i + temp.i * 
+				    q__2.r;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			}
+/* Computing MAX */
+			i__4 = 1, i__1 = j - *k;
+			i__3 = max(i__4,i__1);
+			for (i__ = j - 1; i__ >= i__3; --i__) {
+			    r_cnjg(&q__3, &a[l + i__ + j * a_dim1]);
+			    i__4 = ix;
+			    q__2.r = q__3.r * x[i__4].r - q__3.i * x[i__4].i, 
+				    q__2.i = q__3.r * x[i__4].i + q__3.i * x[
+				    i__4].r;
+			    q__1.r = temp.r + q__2.r, q__1.i = temp.i + 
+				    q__2.i;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			    ix -= *incx;
+/* L130: */
+			}
+		    }
+		    i__3 = jx;
+		    x[i__3].r = temp.r, x[i__3].i = temp.i;
+		    jx -= *incx;
+/* L140: */
+		}
+	    }
+	} else {
+	    if (*incx == 1) {
+		i__3 = *n;
+		for (j = 1; j <= i__3; ++j) {
+		    i__4 = j;
+		    temp.r = x[i__4].r, temp.i = x[i__4].i;
+		    l = 1 - j;
+		    if (noconj) {
+			if (nounit) {
+			    i__4 = j * a_dim1 + 1;
+			    q__1.r = temp.r * a[i__4].r - temp.i * a[i__4].i, 
+				    q__1.i = temp.r * a[i__4].i + temp.i * a[
+				    i__4].r;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			}
+/* Computing MIN */
+			i__1 = *n, i__2 = j + *k;
+			i__4 = min(i__1,i__2);
+			for (i__ = j + 1; i__ <= i__4; ++i__) {
+			    i__1 = l + i__ + j * a_dim1;
+			    i__2 = i__;
+			    q__2.r = a[i__1].r * x[i__2].r - a[i__1].i * x[
+				    i__2].i, q__2.i = a[i__1].r * x[i__2].i + 
+				    a[i__1].i * x[i__2].r;
+			    q__1.r = temp.r + q__2.r, q__1.i = temp.i + 
+				    q__2.i;
+			    temp.r = q__1.r, temp.i = q__1.i;
+/* L150: */
+			}
+		    } else {
+			if (nounit) {
+			    r_cnjg(&q__2, &a[j * a_dim1 + 1]);
+			    q__1.r = temp.r * q__2.r - temp.i * q__2.i, 
+				    q__1.i = temp.r * q__2.i + temp.i * 
+				    q__2.r;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			}
+/* Computing MIN */
+			i__1 = *n, i__2 = j + *k;
+			i__4 = min(i__1,i__2);
+			for (i__ = j + 1; i__ <= i__4; ++i__) {
+			    r_cnjg(&q__3, &a[l + i__ + j * a_dim1]);
+			    i__1 = i__;
+			    q__2.r = q__3.r * x[i__1].r - q__3.i * x[i__1].i, 
+				    q__2.i = q__3.r * x[i__1].i + q__3.i * x[
+				    i__1].r;
+			    q__1.r = temp.r + q__2.r, q__1.i = temp.i + 
+				    q__2.i;
+			    temp.r = q__1.r, temp.i = q__1.i;
+/* L160: */
+			}
+		    }
+		    i__4 = j;
+		    x[i__4].r = temp.r, x[i__4].i = temp.i;
+/* L170: */
+		}
+	    } else {
+		jx = kx;
+		i__3 = *n;
+		for (j = 1; j <= i__3; ++j) {
+		    i__4 = jx;
+		    temp.r = x[i__4].r, temp.i = x[i__4].i;
+		    kx += *incx;
+		    ix = kx;
+		    l = 1 - j;
+		    if (noconj) {
+			if (nounit) {
+			    i__4 = j * a_dim1 + 1;
+			    q__1.r = temp.r * a[i__4].r - temp.i * a[i__4].i, 
+				    q__1.i = temp.r * a[i__4].i + temp.i * a[
+				    i__4].r;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			}
+/* Computing MIN */
+			i__1 = *n, i__2 = j + *k;
+			i__4 = min(i__1,i__2);
+			for (i__ = j + 1; i__ <= i__4; ++i__) {
+			    i__1 = l + i__ + j * a_dim1;
+			    i__2 = ix;
+			    q__2.r = a[i__1].r * x[i__2].r - a[i__1].i * x[
+				    i__2].i, q__2.i = a[i__1].r * x[i__2].i + 
+				    a[i__1].i * x[i__2].r;
+			    q__1.r = temp.r + q__2.r, q__1.i = temp.i + 
+				    q__2.i;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			    ix += *incx;
+/* L180: */
+			}
+		    } else {
+			if (nounit) {
+			    r_cnjg(&q__2, &a[j * a_dim1 + 1]);
+			    q__1.r = temp.r * q__2.r - temp.i * q__2.i, 
+				    q__1.i = temp.r * q__2.i + temp.i * 
+				    q__2.r;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			}
+/* Computing MIN */
+			i__1 = *n, i__2 = j + *k;
+			i__4 = min(i__1,i__2);
+			for (i__ = j + 1; i__ <= i__4; ++i__) {
+			    r_cnjg(&q__3, &a[l + i__ + j * a_dim1]);
+			    i__1 = ix;
+			    q__2.r = q__3.r * x[i__1].r - q__3.i * x[i__1].i, 
+				    q__2.i = q__3.r * x[i__1].i + q__3.i * x[
+				    i__1].r;
+			    q__1.r = temp.r + q__2.r, q__1.i = temp.i + 
+				    q__2.i;
+			    temp.r = q__1.r, temp.i = q__1.i;
+			    ix += *incx;
+/* L190: */
+			}
+		    }
+		    i__4 = jx;
+		    x[i__4].r = temp.r, x[i__4].i = temp.i;
+		    jx += *incx;
+/* L200: */
+		}
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of CTBMV . */
+
+} /* ctbmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/d_cnjg.c
Index: 3rd_party/eigen/blas/f2c/d_cnjg.c
==================================================================
--- 3rd_party/eigen/blas/f2c/d_cnjg.c
+++ 3rd_party/eigen/blas/f2c/d_cnjg.c
@@ -0,0 +1,6 @@
+#include "datatypes.h"    
+
+void d_cnjg(doublecomplex *r, doublecomplex *z) {
+    r->r = z->r;
+    r->i = -(z->i);
+}

ADDED   3rd_party/eigen/blas/f2c/datatypes.h
Index: 3rd_party/eigen/blas/f2c/datatypes.h
==================================================================
--- 3rd_party/eigen/blas/f2c/datatypes.h
+++ 3rd_party/eigen/blas/f2c/datatypes.h
@@ -0,0 +1,24 @@
+/* This contains a limited subset of the typedefs exposed by f2c
+   for use by the Eigen BLAS C-only implementation.
+*/
+
+#ifndef __EIGEN_DATATYPES_H__
+#define __EIGEN_DATATYPES_H__
+
+typedef int integer;
+typedef unsigned int uinteger;
+typedef float real;
+typedef double doublereal;
+typedef struct { real r, i; } complex;
+typedef struct { doublereal r, i; } doublecomplex;
+typedef int ftnlen;
+typedef int logical;
+
+#define abs(x) ((x) >= 0 ? (x) : -(x))
+#define dabs(x) (doublereal)abs(x)
+#define min(a,b) ((a) <= (b) ? (a) : (b))
+#define max(a,b) ((a) >= (b) ? (a) : (b))
+#define dmin(a,b) (doublereal)min(a,b)
+#define dmax(a,b) (doublereal)max(a,b)
+
+#endif

ADDED   3rd_party/eigen/blas/f2c/drotm.c
Index: 3rd_party/eigen/blas/f2c/drotm.c
==================================================================
--- 3rd_party/eigen/blas/f2c/drotm.c
+++ 3rd_party/eigen/blas/f2c/drotm.c
@@ -0,0 +1,215 @@
+/* drotm.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int drotm_(integer *n, doublereal *dx, integer *incx, 
+	doublereal *dy, integer *incy, doublereal *dparam)
+{
+    /* Initialized data */
+
+    static doublereal zero = 0.;
+    static doublereal two = 2.;
+
+    /* System generated locals */
+    integer i__1, i__2;
+
+    /* Local variables */
+    integer i__;
+    doublereal w, z__;
+    integer kx, ky;
+    doublereal dh11, dh12, dh21, dh22, dflag;
+    integer nsteps;
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*     APPLY THE MODIFIED GIVENS TRANSFORMATION, H, TO THE 2 BY N MATRIX */
+
+/*     (DX**T) , WHERE **T INDICATES TRANSPOSE. THE ELEMENTS OF DX ARE IN */
+/*     (DY**T) */
+
+/*     DX(LX+I*INCX), I = 0 TO N-1, WHERE LX = 1 IF INCX .GE. 0, ELSE */
+/*     LX = (-INCX)*N, AND SIMILARLY FOR SY USING LY AND INCY. */
+/*     WITH DPARAM(1)=DFLAG, H HAS ONE OF THE FOLLOWING FORMS.. */
+
+/*     DFLAG=-1.D0     DFLAG=0.D0        DFLAG=1.D0     DFLAG=-2.D0 */
+
+/*       (DH11  DH12)    (1.D0  DH12)    (DH11  1.D0)    (1.D0  0.D0) */
+/*     H=(          )    (          )    (          )    (          ) */
+/*       (DH21  DH22),   (DH21  1.D0),   (-1.D0 DH22),   (0.D0  1.D0). */
+/*     SEE DROTMG FOR A DESCRIPTION OF DATA STORAGE IN DPARAM. */
+
+/*  Arguments */
+/*  ========= */
+
+/*  N      (input) INTEGER */
+/*         number of elements in input vector(s) */
+
+/*  DX     (input/output) DOUBLE PRECISION array, dimension N */
+/*         double precision vector with N elements */
+
+/*  INCX   (input) INTEGER */
+/*         storage spacing between elements of DX */
+
+/*  DY     (input/output) DOUBLE PRECISION array, dimension N */
+/*         double precision vector with N elements */
+
+/*  INCY   (input) INTEGER */
+/*         storage spacing between elements of DY */
+
+/*  DPARAM (input/output)  DOUBLE PRECISION array, dimension 5 */
+/*     DPARAM(1)=DFLAG */
+/*     DPARAM(2)=DH11 */
+/*     DPARAM(3)=DH21 */
+/*     DPARAM(4)=DH12 */
+/*     DPARAM(5)=DH22 */
+
+/*  ===================================================================== */
+
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. Data statements .. */
+    /* Parameter adjustments */
+    --dparam;
+    --dy;
+    --dx;
+
+    /* Function Body */
+/*     .. */
+
+    dflag = dparam[1];
+    if (*n <= 0 || dflag + two == zero) {
+	goto L140;
+    }
+    if (! (*incx == *incy && *incx > 0)) {
+	goto L70;
+    }
+
+    nsteps = *n * *incx;
+    if (dflag < 0.) {
+	goto L50;
+    } else if (dflag == 0) {
+	goto L10;
+    } else {
+	goto L30;
+    }
+L10:
+    dh12 = dparam[4];
+    dh21 = dparam[3];
+    i__1 = nsteps;
+    i__2 = *incx;
+    for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
+	w = dx[i__];
+	z__ = dy[i__];
+	dx[i__] = w + z__ * dh12;
+	dy[i__] = w * dh21 + z__;
+/* L20: */
+    }
+    goto L140;
+L30:
+    dh11 = dparam[2];
+    dh22 = dparam[5];
+    i__2 = nsteps;
+    i__1 = *incx;
+    for (i__ = 1; i__1 < 0 ? i__ >= i__2 : i__ <= i__2; i__ += i__1) {
+	w = dx[i__];
+	z__ = dy[i__];
+	dx[i__] = w * dh11 + z__;
+	dy[i__] = -w + dh22 * z__;
+/* L40: */
+    }
+    goto L140;
+L50:
+    dh11 = dparam[2];
+    dh12 = dparam[4];
+    dh21 = dparam[3];
+    dh22 = dparam[5];
+    i__1 = nsteps;
+    i__2 = *incx;
+    for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
+	w = dx[i__];
+	z__ = dy[i__];
+	dx[i__] = w * dh11 + z__ * dh12;
+	dy[i__] = w * dh21 + z__ * dh22;
+/* L60: */
+    }
+    goto L140;
+L70:
+    kx = 1;
+    ky = 1;
+    if (*incx < 0) {
+	kx = (1 - *n) * *incx + 1;
+    }
+    if (*incy < 0) {
+	ky = (1 - *n) * *incy + 1;
+    }
+
+    if (dflag < 0.) {
+	goto L120;
+    } else if (dflag == 0) {
+	goto L80;
+    } else {
+	goto L100;
+    }
+L80:
+    dh12 = dparam[4];
+    dh21 = dparam[3];
+    i__2 = *n;
+    for (i__ = 1; i__ <= i__2; ++i__) {
+	w = dx[kx];
+	z__ = dy[ky];
+	dx[kx] = w + z__ * dh12;
+	dy[ky] = w * dh21 + z__;
+	kx += *incx;
+	ky += *incy;
+/* L90: */
+    }
+    goto L140;
+L100:
+    dh11 = dparam[2];
+    dh22 = dparam[5];
+    i__2 = *n;
+    for (i__ = 1; i__ <= i__2; ++i__) {
+	w = dx[kx];
+	z__ = dy[ky];
+	dx[kx] = w * dh11 + z__;
+	dy[ky] = -w + dh22 * z__;
+	kx += *incx;
+	ky += *incy;
+/* L110: */
+    }
+    goto L140;
+L120:
+    dh11 = dparam[2];
+    dh12 = dparam[4];
+    dh21 = dparam[3];
+    dh22 = dparam[5];
+    i__2 = *n;
+    for (i__ = 1; i__ <= i__2; ++i__) {
+	w = dx[kx];
+	z__ = dy[ky];
+	dx[kx] = w * dh11 + z__ * dh12;
+	dy[ky] = w * dh21 + z__ * dh22;
+	kx += *incx;
+	ky += *incy;
+/* L130: */
+    }
+L140:
+    return 0;
+} /* drotm_ */
+

ADDED   3rd_party/eigen/blas/f2c/drotmg.c
Index: 3rd_party/eigen/blas/f2c/drotmg.c
==================================================================
--- 3rd_party/eigen/blas/f2c/drotmg.c
+++ 3rd_party/eigen/blas/f2c/drotmg.c
@@ -0,0 +1,293 @@
+/* drotmg.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int drotmg_(doublereal *dd1, doublereal *dd2, doublereal *
+	dx1, doublereal *dy1, doublereal *dparam)
+{
+    /* Initialized data */
+
+    static doublereal zero = 0.;
+    static doublereal one = 1.;
+    static doublereal two = 2.;
+    static doublereal gam = 4096.;
+    static doublereal gamsq = 16777216.;
+    static doublereal rgamsq = 5.9604645e-8;
+
+    /* Format strings */
+    static char fmt_120[] = "";
+    static char fmt_150[] = "";
+    static char fmt_180[] = "";
+    static char fmt_210[] = "";
+
+    /* System generated locals */
+    doublereal d__1;
+
+    /* Local variables */
+    doublereal du, dp1, dp2, dq1, dq2, dh11, dh12, dh21, dh22;
+    integer igo;
+    doublereal dflag, dtemp;
+
+    /* Assigned format variables */
+    static char *igo_fmt;
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*     CONSTRUCT THE MODIFIED GIVENS TRANSFORMATION MATRIX H WHICH ZEROS */
+/*     THE SECOND COMPONENT OF THE 2-VECTOR  (DSQRT(DD1)*DX1,DSQRT(DD2)* */
+/*     DY2)**T. */
+/*     WITH DPARAM(1)=DFLAG, H HAS ONE OF THE FOLLOWING FORMS.. */
+
+/*     DFLAG=-1.D0     DFLAG=0.D0        DFLAG=1.D0     DFLAG=-2.D0 */
+
+/*       (DH11  DH12)    (1.D0  DH12)    (DH11  1.D0)    (1.D0  0.D0) */
+/*     H=(          )    (          )    (          )    (          ) */
+/*       (DH21  DH22),   (DH21  1.D0),   (-1.D0 DH22),   (0.D0  1.D0). */
+/*     LOCATIONS 2-4 OF DPARAM CONTAIN DH11, DH21, DH12, AND DH22 */
+/*     RESPECTIVELY. (VALUES OF 1.D0, -1.D0, OR 0.D0 IMPLIED BY THE */
+/*     VALUE OF DPARAM(1) ARE NOT STORED IN DPARAM.) */
+
+/*     THE VALUES OF GAMSQ AND RGAMSQ SET IN THE DATA STATEMENT MAY BE */
+/*     INEXACT.  THIS IS OK AS THEY ARE ONLY USED FOR TESTING THE SIZE */
+/*     OF DD1 AND DD2.  ALL ACTUAL SCALING OF DATA IS DONE USING GAM. */
+
+
+/*  Arguments */
+/*  ========= */
+
+/*  DD1    (input/output) DOUBLE PRECISION */
+
+/*  DD2    (input/output) DOUBLE PRECISION */
+
+/*  DX1    (input/output) DOUBLE PRECISION */
+
+/*  DY1    (input) DOUBLE PRECISION */
+
+/*  DPARAM (input/output)  DOUBLE PRECISION array, dimension 5 */
+/*     DPARAM(1)=DFLAG */
+/*     DPARAM(2)=DH11 */
+/*     DPARAM(3)=DH21 */
+/*     DPARAM(4)=DH12 */
+/*     DPARAM(5)=DH22 */
+
+/*  ===================================================================== */
+
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+/*     .. Data statements .. */
+
+    /* Parameter adjustments */
+    --dparam;
+
+    /* Function Body */
+/*     .. */
+    if (! (*dd1 < zero)) {
+	goto L10;
+    }
+/*       GO ZERO-H-D-AND-DX1.. */
+    goto L60;
+L10:
+/*     CASE-DD1-NONNEGATIVE */
+    dp2 = *dd2 * *dy1;
+    if (! (dp2 == zero)) {
+	goto L20;
+    }
+    dflag = -two;
+    goto L260;
+/*     REGULAR-CASE.. */
+L20:
+    dp1 = *dd1 * *dx1;
+    dq2 = dp2 * *dy1;
+    dq1 = dp1 * *dx1;
+
+    if (! (abs(dq1) > abs(dq2))) {
+	goto L40;
+    }
+    dh21 = -(*dy1) / *dx1;
+    dh12 = dp2 / dp1;
+
+    du = one - dh12 * dh21;
+
+    if (! (du <= zero)) {
+	goto L30;
+    }
+/*         GO ZERO-H-D-AND-DX1.. */
+    goto L60;
+L30:
+    dflag = zero;
+    *dd1 /= du;
+    *dd2 /= du;
+    *dx1 *= du;
+/*         GO SCALE-CHECK.. */
+    goto L100;
+L40:
+    if (! (dq2 < zero)) {
+	goto L50;
+    }
+/*         GO ZERO-H-D-AND-DX1.. */
+    goto L60;
+L50:
+    dflag = one;
+    dh11 = dp1 / dp2;
+    dh22 = *dx1 / *dy1;
+    du = one + dh11 * dh22;
+    dtemp = *dd2 / du;
+    *dd2 = *dd1 / du;
+    *dd1 = dtemp;
+    *dx1 = *dy1 * du;
+/*         GO SCALE-CHECK */
+    goto L100;
+/*     PROCEDURE..ZERO-H-D-AND-DX1.. */
+L60:
+    dflag = -one;
+    dh11 = zero;
+    dh12 = zero;
+    dh21 = zero;
+    dh22 = zero;
+
+    *dd1 = zero;
+    *dd2 = zero;
+    *dx1 = zero;
+/*         RETURN.. */
+    goto L220;
+/*     PROCEDURE..FIX-H.. */
+L70:
+    if (! (dflag >= zero)) {
+	goto L90;
+    }
+
+    if (! (dflag == zero)) {
+	goto L80;
+    }
+    dh11 = one;
+    dh22 = one;
+    dflag = -one;
+    goto L90;
+L80:
+    dh21 = -one;
+    dh12 = one;
+    dflag = -one;
+L90:
+    switch (igo) {
+	case 0: goto L120;
+	case 1: goto L150;
+	case 2: goto L180;
+	case 3: goto L210;
+    }
+/*     PROCEDURE..SCALE-CHECK */
+L100:
+L110:
+    if (! (*dd1 <= rgamsq)) {
+	goto L130;
+    }
+    if (*dd1 == zero) {
+	goto L160;
+    }
+    igo = 0;
+    igo_fmt = fmt_120;
+/*              FIX-H.. */
+    goto L70;
+L120:
+/* Computing 2nd power */
+    d__1 = gam;
+    *dd1 *= d__1 * d__1;
+    *dx1 /= gam;
+    dh11 /= gam;
+    dh12 /= gam;
+    goto L110;
+L130:
+L140:
+    if (! (*dd1 >= gamsq)) {
+	goto L160;
+    }
+    igo = 1;
+    igo_fmt = fmt_150;
+/*              FIX-H.. */
+    goto L70;
+L150:
+/* Computing 2nd power */
+    d__1 = gam;
+    *dd1 /= d__1 * d__1;
+    *dx1 *= gam;
+    dh11 *= gam;
+    dh12 *= gam;
+    goto L140;
+L160:
+L170:
+    if (! (abs(*dd2) <= rgamsq)) {
+	goto L190;
+    }
+    if (*dd2 == zero) {
+	goto L220;
+    }
+    igo = 2;
+    igo_fmt = fmt_180;
+/*              FIX-H.. */
+    goto L70;
+L180:
+/* Computing 2nd power */
+    d__1 = gam;
+    *dd2 *= d__1 * d__1;
+    dh21 /= gam;
+    dh22 /= gam;
+    goto L170;
+L190:
+L200:
+    if (! (abs(*dd2) >= gamsq)) {
+	goto L220;
+    }
+    igo = 3;
+    igo_fmt = fmt_210;
+/*              FIX-H.. */
+    goto L70;
+L210:
+/* Computing 2nd power */
+    d__1 = gam;
+    *dd2 /= d__1 * d__1;
+    dh21 *= gam;
+    dh22 *= gam;
+    goto L200;
+L220:
+    if (dflag < 0.) {
+	goto L250;
+    } else if (dflag == 0) {
+	goto L230;
+    } else {
+	goto L240;
+    }
+L230:
+    dparam[3] = dh21;
+    dparam[4] = dh12;
+    goto L260;
+L240:
+    dparam[2] = dh11;
+    dparam[5] = dh22;
+    goto L260;
+L250:
+    dparam[2] = dh11;
+    dparam[3] = dh21;
+    dparam[4] = dh12;
+    dparam[5] = dh22;
+L260:
+    dparam[1] = dflag;
+    return 0;
+} /* drotmg_ */
+

ADDED   3rd_party/eigen/blas/f2c/dsbmv.c
Index: 3rd_party/eigen/blas/f2c/dsbmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/dsbmv.c
+++ 3rd_party/eigen/blas/f2c/dsbmv.c
@@ -0,0 +1,366 @@
+/* dsbmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int dsbmv_(char *uplo, integer *n, integer *k, doublereal *
+	alpha, doublereal *a, integer *lda, doublereal *x, integer *incx, 
+	doublereal *beta, doublereal *y, integer *incy, ftnlen uplo_len)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
+
+    /* Local variables */
+    integer i__, j, l, ix, iy, jx, jy, kx, ky, info;
+    doublereal temp1, temp2;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    integer kplus1;
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  DSBMV  performs the matrix-vector  operation */
+
+/*     y := alpha*A*x + beta*y, */
+
+/*  where alpha and beta are scalars, x and y are n element vectors and */
+/*  A is an n by n symmetric band matrix, with k super-diagonals. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the upper or lower */
+/*           triangular part of the band matrix A is being supplied as */
+/*           follows: */
+
+/*              UPLO = 'U' or 'u'   The upper triangular part of A is */
+/*                                  being supplied. */
+
+/*              UPLO = 'L' or 'l'   The lower triangular part of A is */
+/*                                  being supplied. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  K      - INTEGER. */
+/*           On entry, K specifies the number of super-diagonals of the */
+/*           matrix A. K must satisfy  0 .le. K. */
+/*           Unchanged on exit. */
+
+/*  ALPHA  - DOUBLE PRECISION. */
+/*           On entry, ALPHA specifies the scalar alpha. */
+/*           Unchanged on exit. */
+
+/*  A      - DOUBLE PRECISION array of DIMENSION ( LDA, n ). */
+/*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the upper triangular */
+/*           band part of the symmetric matrix, supplied column by */
+/*           column, with the leading diagonal of the matrix in row */
+/*           ( k + 1 ) of the array, the first super-diagonal starting at */
+/*           position 2 in row k, and so on. The top left k by k triangle */
+/*           of the array A is not referenced. */
+/*           The following program segment will transfer the upper */
+/*           triangular part of a symmetric band matrix from conventional */
+/*           full matrix storage to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = K + 1 - J */
+/*                    DO 10, I = MAX( 1, J - K ), J */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the lower triangular */
+/*           band part of the symmetric matrix, supplied column by */
+/*           column, with the leading diagonal of the matrix in row 1 of */
+/*           the array, the first sub-diagonal starting at position 1 in */
+/*           row 2, and so on. The bottom right k by k triangle of the */
+/*           array A is not referenced. */
+/*           The following program segment will transfer the lower */
+/*           triangular part of a symmetric band matrix from conventional */
+/*           full matrix storage to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = 1 - J */
+/*                    DO 10, I = J, MIN( N, J + K ) */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Unchanged on exit. */
+
+/*  LDA    - INTEGER. */
+/*           On entry, LDA specifies the first dimension of A as declared */
+/*           in the calling (sub) program. LDA must be at least */
+/*           ( k + 1 ). */
+/*           Unchanged on exit. */
+
+/*  X      - DOUBLE PRECISION array of DIMENSION at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the */
+/*           vector x. */
+/*           Unchanged on exit. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  BETA   - DOUBLE PRECISION. */
+/*           On entry, BETA specifies the scalar beta. */
+/*           Unchanged on exit. */
+
+/*  Y      - DOUBLE PRECISION array of DIMENSION at least */
+/*           ( 1 + ( n - 1 )*abs( INCY ) ). */
+/*           Before entry, the incremented array Y must contain the */
+/*           vector y. On exit, Y is overwritten by the updated vector y. */
+
+/*  INCY   - INTEGER. */
+/*           On entry, INCY specifies the increment for the elements of */
+/*           Y. INCY must not be zero. */
+/*           Unchanged on exit. */
+
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    --x;
+    --y;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (*n < 0) {
+	info = 2;
+    } else if (*k < 0) {
+	info = 3;
+    } else if (*lda < *k + 1) {
+	info = 6;
+    } else if (*incx == 0) {
+	info = 8;
+    } else if (*incy == 0) {
+	info = 11;
+    }
+    if (info != 0) {
+	xerbla_("DSBMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0 || (*alpha == 0. && *beta == 1.)) {
+	return 0;
+    }
+
+/*     Set up the start points in  X  and  Y. */
+
+    if (*incx > 0) {
+	kx = 1;
+    } else {
+	kx = 1 - (*n - 1) * *incx;
+    }
+    if (*incy > 0) {
+	ky = 1;
+    } else {
+	ky = 1 - (*n - 1) * *incy;
+    }
+
+/*     Start the operations. In this version the elements of the array A */
+/*     are accessed sequentially with one pass through A. */
+
+/*     First form  y := beta*y. */
+
+    if (*beta != 1.) {
+	if (*incy == 1) {
+	    if (*beta == 0.) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[i__] = 0.;
+/* L10: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[i__] = *beta * y[i__];
+/* L20: */
+		}
+	    }
+	} else {
+	    iy = ky;
+	    if (*beta == 0.) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[iy] = 0.;
+		    iy += *incy;
+/* L30: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[iy] = *beta * y[iy];
+		    iy += *incy;
+/* L40: */
+		}
+	    }
+	}
+    }
+    if (*alpha == 0.) {
+	return 0;
+    }
+    if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+
+/*        Form  y  when upper triangle of A is stored. */
+
+	kplus1 = *k + 1;
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[j];
+		temp2 = 0.;
+		l = kplus1 - j;
+/* Computing MAX */
+		i__2 = 1, i__3 = j - *k;
+		i__4 = j - 1;
+		for (i__ = max(i__2,i__3); i__ <= i__4; ++i__) {
+		    y[i__] += temp1 * a[l + i__ + j * a_dim1];
+		    temp2 += a[l + i__ + j * a_dim1] * x[i__];
+/* L50: */
+		}
+		y[j] = y[j] + temp1 * a[kplus1 + j * a_dim1] + *alpha * temp2;
+/* L60: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[jx];
+		temp2 = 0.;
+		ix = kx;
+		iy = ky;
+		l = kplus1 - j;
+/* Computing MAX */
+		i__4 = 1, i__2 = j - *k;
+		i__3 = j - 1;
+		for (i__ = max(i__4,i__2); i__ <= i__3; ++i__) {
+		    y[iy] += temp1 * a[l + i__ + j * a_dim1];
+		    temp2 += a[l + i__ + j * a_dim1] * x[ix];
+		    ix += *incx;
+		    iy += *incy;
+/* L70: */
+		}
+		y[jy] = y[jy] + temp1 * a[kplus1 + j * a_dim1] + *alpha * 
+			temp2;
+		jx += *incx;
+		jy += *incy;
+		if (j > *k) {
+		    kx += *incx;
+		    ky += *incy;
+		}
+/* L80: */
+	    }
+	}
+    } else {
+
+/*        Form  y  when lower triangle of A is stored. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[j];
+		temp2 = 0.;
+		y[j] += temp1 * a[j * a_dim1 + 1];
+		l = 1 - j;
+/* Computing MIN */
+		i__4 = *n, i__2 = j + *k;
+		i__3 = min(i__4,i__2);
+		for (i__ = j + 1; i__ <= i__3; ++i__) {
+		    y[i__] += temp1 * a[l + i__ + j * a_dim1];
+		    temp2 += a[l + i__ + j * a_dim1] * x[i__];
+/* L90: */
+		}
+		y[j] += *alpha * temp2;
+/* L100: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[jx];
+		temp2 = 0.;
+		y[jy] += temp1 * a[j * a_dim1 + 1];
+		l = 1 - j;
+		ix = jx;
+		iy = jy;
+/* Computing MIN */
+		i__4 = *n, i__2 = j + *k;
+		i__3 = min(i__4,i__2);
+		for (i__ = j + 1; i__ <= i__3; ++i__) {
+		    ix += *incx;
+		    iy += *incy;
+		    y[iy] += temp1 * a[l + i__ + j * a_dim1];
+		    temp2 += a[l + i__ + j * a_dim1] * x[ix];
+/* L110: */
+		}
+		y[jy] += *alpha * temp2;
+		jx += *incx;
+		jy += *incy;
+/* L120: */
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of DSBMV . */
+
+} /* dsbmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/dspmv.c
Index: 3rd_party/eigen/blas/f2c/dspmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/dspmv.c
+++ 3rd_party/eigen/blas/f2c/dspmv.c
@@ -0,0 +1,316 @@
+/* dspmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int dspmv_(char *uplo, integer *n, doublereal *alpha, 
+	doublereal *ap, doublereal *x, integer *incx, doublereal *beta, 
+	doublereal *y, integer *incy, ftnlen uplo_len)
+{
+    /* System generated locals */
+    integer i__1, i__2;
+
+    /* Local variables */
+    integer i__, j, k, kk, ix, iy, jx, jy, kx, ky, info;
+    doublereal temp1, temp2;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  DSPMV  performs the matrix-vector operation */
+
+/*     y := alpha*A*x + beta*y, */
+
+/*  where alpha and beta are scalars, x and y are n element vectors and */
+/*  A is an n by n symmetric matrix, supplied in packed form. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the upper or lower */
+/*           triangular part of the matrix A is supplied in the packed */
+/*           array AP as follows: */
+
+/*              UPLO = 'U' or 'u'   The upper triangular part of A is */
+/*                                  supplied in AP. */
+
+/*              UPLO = 'L' or 'l'   The lower triangular part of A is */
+/*                                  supplied in AP. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  ALPHA  - DOUBLE PRECISION. */
+/*           On entry, ALPHA specifies the scalar alpha. */
+/*           Unchanged on exit. */
+
+/*  AP     - DOUBLE PRECISION array of DIMENSION at least */
+/*           ( ( n*( n + 1 ) )/2 ). */
+/*           Before entry with UPLO = 'U' or 'u', the array AP must */
+/*           contain the upper triangular part of the symmetric matrix */
+/*           packed sequentially, column by column, so that AP( 1 ) */
+/*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 ) */
+/*           and a( 2, 2 ) respectively, and so on. */
+/*           Before entry with UPLO = 'L' or 'l', the array AP must */
+/*           contain the lower triangular part of the symmetric matrix */
+/*           packed sequentially, column by column, so that AP( 1 ) */
+/*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 ) */
+/*           and a( 3, 1 ) respectively, and so on. */
+/*           Unchanged on exit. */
+
+/*  X      - DOUBLE PRECISION array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the n */
+/*           element vector x. */
+/*           Unchanged on exit. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  BETA   - DOUBLE PRECISION. */
+/*           On entry, BETA specifies the scalar beta. When BETA is */
+/*           supplied as zero then Y need not be set on input. */
+/*           Unchanged on exit. */
+
+/*  Y      - DOUBLE PRECISION array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCY ) ). */
+/*           Before entry, the incremented array Y must contain the n */
+/*           element vector y. On exit, Y is overwritten by the updated */
+/*           vector y. */
+
+/*  INCY   - INTEGER. */
+/*           On entry, INCY specifies the increment for the elements of */
+/*           Y. INCY must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    --y;
+    --x;
+    --ap;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (*n < 0) {
+	info = 2;
+    } else if (*incx == 0) {
+	info = 6;
+    } else if (*incy == 0) {
+	info = 9;
+    }
+    if (info != 0) {
+	xerbla_("DSPMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0 || (*alpha == 0. && *beta == 1.)) {
+	return 0;
+    }
+
+/*     Set up the start points in  X  and  Y. */
+
+    if (*incx > 0) {
+	kx = 1;
+    } else {
+	kx = 1 - (*n - 1) * *incx;
+    }
+    if (*incy > 0) {
+	ky = 1;
+    } else {
+	ky = 1 - (*n - 1) * *incy;
+    }
+
+/*     Start the operations. In this version the elements of the array AP */
+/*     are accessed sequentially with one pass through AP. */
+
+/*     First form  y := beta*y. */
+
+    if (*beta != 1.) {
+	if (*incy == 1) {
+	    if (*beta == 0.) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[i__] = 0.;
+/* L10: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[i__] = *beta * y[i__];
+/* L20: */
+		}
+	    }
+	} else {
+	    iy = ky;
+	    if (*beta == 0.) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[iy] = 0.;
+		    iy += *incy;
+/* L30: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[iy] = *beta * y[iy];
+		    iy += *incy;
+/* L40: */
+		}
+	    }
+	}
+    }
+    if (*alpha == 0.) {
+	return 0;
+    }
+    kk = 1;
+    if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+
+/*        Form  y  when AP contains the upper triangle. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[j];
+		temp2 = 0.;
+		k = kk;
+		i__2 = j - 1;
+		for (i__ = 1; i__ <= i__2; ++i__) {
+		    y[i__] += temp1 * ap[k];
+		    temp2 += ap[k] * x[i__];
+		    ++k;
+/* L50: */
+		}
+		y[j] = y[j] + temp1 * ap[kk + j - 1] + *alpha * temp2;
+		kk += j;
+/* L60: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[jx];
+		temp2 = 0.;
+		ix = kx;
+		iy = ky;
+		i__2 = kk + j - 2;
+		for (k = kk; k <= i__2; ++k) {
+		    y[iy] += temp1 * ap[k];
+		    temp2 += ap[k] * x[ix];
+		    ix += *incx;
+		    iy += *incy;
+/* L70: */
+		}
+		y[jy] = y[jy] + temp1 * ap[kk + j - 1] + *alpha * temp2;
+		jx += *incx;
+		jy += *incy;
+		kk += j;
+/* L80: */
+	    }
+	}
+    } else {
+
+/*        Form  y  when AP contains the lower triangle. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[j];
+		temp2 = 0.;
+		y[j] += temp1 * ap[kk];
+		k = kk + 1;
+		i__2 = *n;
+		for (i__ = j + 1; i__ <= i__2; ++i__) {
+		    y[i__] += temp1 * ap[k];
+		    temp2 += ap[k] * x[i__];
+		    ++k;
+/* L90: */
+		}
+		y[j] += *alpha * temp2;
+		kk += *n - j + 1;
+/* L100: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[jx];
+		temp2 = 0.;
+		y[jy] += temp1 * ap[kk];
+		ix = jx;
+		iy = jy;
+		i__2 = kk + *n - j;
+		for (k = kk + 1; k <= i__2; ++k) {
+		    ix += *incx;
+		    iy += *incy;
+		    y[iy] += temp1 * ap[k];
+		    temp2 += ap[k] * x[ix];
+/* L110: */
+		}
+		y[jy] += *alpha * temp2;
+		jx += *incx;
+		jy += *incy;
+		kk += *n - j + 1;
+/* L120: */
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of DSPMV . */
+
+} /* dspmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/dtbmv.c
Index: 3rd_party/eigen/blas/f2c/dtbmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/dtbmv.c
+++ 3rd_party/eigen/blas/f2c/dtbmv.c
@@ -0,0 +1,428 @@
+/* dtbmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int dtbmv_(char *uplo, char *trans, char *diag, integer *n, 
+	integer *k, doublereal *a, integer *lda, doublereal *x, integer *incx,
+	 ftnlen uplo_len, ftnlen trans_len, ftnlen diag_len)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
+
+    /* Local variables */
+    integer i__, j, l, ix, jx, kx, info;
+    doublereal temp;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    integer kplus1;
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+    logical nounit;
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  DTBMV  performs one of the matrix-vector operations */
+
+/*     x := A*x,   or   x := A'*x, */
+
+/*  where x is an n element vector and  A is an n by n unit, or non-unit, */
+/*  upper or lower triangular band matrix, with ( k + 1 ) diagonals. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the matrix is an upper or */
+/*           lower triangular matrix as follows: */
+
+/*              UPLO = 'U' or 'u'   A is an upper triangular matrix. */
+
+/*              UPLO = 'L' or 'l'   A is a lower triangular matrix. */
+
+/*           Unchanged on exit. */
+
+/*  TRANS  - CHARACTER*1. */
+/*           On entry, TRANS specifies the operation to be performed as */
+/*           follows: */
+
+/*              TRANS = 'N' or 'n'   x := A*x. */
+
+/*              TRANS = 'T' or 't'   x := A'*x. */
+
+/*              TRANS = 'C' or 'c'   x := A'*x. */
+
+/*           Unchanged on exit. */
+
+/*  DIAG   - CHARACTER*1. */
+/*           On entry, DIAG specifies whether or not A is unit */
+/*           triangular as follows: */
+
+/*              DIAG = 'U' or 'u'   A is assumed to be unit triangular. */
+
+/*              DIAG = 'N' or 'n'   A is not assumed to be unit */
+/*                                  triangular. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  K      - INTEGER. */
+/*           On entry with UPLO = 'U' or 'u', K specifies the number of */
+/*           super-diagonals of the matrix A. */
+/*           On entry with UPLO = 'L' or 'l', K specifies the number of */
+/*           sub-diagonals of the matrix A. */
+/*           K must satisfy  0 .le. K. */
+/*           Unchanged on exit. */
+
+/*  A      - DOUBLE PRECISION array of DIMENSION ( LDA, n ). */
+/*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the upper triangular */
+/*           band part of the matrix of coefficients, supplied column by */
+/*           column, with the leading diagonal of the matrix in row */
+/*           ( k + 1 ) of the array, the first super-diagonal starting at */
+/*           position 2 in row k, and so on. The top left k by k triangle */
+/*           of the array A is not referenced. */
+/*           The following program segment will transfer an upper */
+/*           triangular band matrix from conventional full matrix storage */
+/*           to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = K + 1 - J */
+/*                    DO 10, I = MAX( 1, J - K ), J */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the lower triangular */
+/*           band part of the matrix of coefficients, supplied column by */
+/*           column, with the leading diagonal of the matrix in row 1 of */
+/*           the array, the first sub-diagonal starting at position 1 in */
+/*           row 2, and so on. The bottom right k by k triangle of the */
+/*           array A is not referenced. */
+/*           The following program segment will transfer a lower */
+/*           triangular band matrix from conventional full matrix storage */
+/*           to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = 1 - J */
+/*                    DO 10, I = J, MIN( N, J + K ) */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Note that when DIAG = 'U' or 'u' the elements of the array A */
+/*           corresponding to the diagonal elements of the matrix are not */
+/*           referenced, but are assumed to be unity. */
+/*           Unchanged on exit. */
+
+/*  LDA    - INTEGER. */
+/*           On entry, LDA specifies the first dimension of A as declared */
+/*           in the calling (sub) program. LDA must be at least */
+/*           ( k + 1 ). */
+/*           Unchanged on exit. */
+
+/*  X      - DOUBLE PRECISION array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the n */
+/*           element vector x. On exit, X is overwritten with the */
+/*           tranformed vector x. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    --x;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (! lsame_(trans, "N", (ftnlen)1, (ftnlen)1) && ! lsame_(trans, 
+	    "T", (ftnlen)1, (ftnlen)1) && ! lsame_(trans, "C", (ftnlen)1, (
+	    ftnlen)1)) {
+	info = 2;
+    } else if (! lsame_(diag, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(diag, 
+	    "N", (ftnlen)1, (ftnlen)1)) {
+	info = 3;
+    } else if (*n < 0) {
+	info = 4;
+    } else if (*k < 0) {
+	info = 5;
+    } else if (*lda < *k + 1) {
+	info = 7;
+    } else if (*incx == 0) {
+	info = 9;
+    }
+    if (info != 0) {
+	xerbla_("DTBMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0) {
+	return 0;
+    }
+
+    nounit = lsame_(diag, "N", (ftnlen)1, (ftnlen)1);
+
+/*     Set up the start point in X if the increment is not unity. This */
+/*     will be  ( N - 1 )*INCX   too small for descending loops. */
+
+    if (*incx <= 0) {
+	kx = 1 - (*n - 1) * *incx;
+    } else if (*incx != 1) {
+	kx = 1;
+    }
+
+/*     Start the operations. In this version the elements of A are */
+/*     accessed sequentially with one pass through A. */
+
+    if (lsame_(trans, "N", (ftnlen)1, (ftnlen)1)) {
+
+/*         Form  x := A*x. */
+
+	if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+	    kplus1 = *k + 1;
+	    if (*incx == 1) {
+		i__1 = *n;
+		for (j = 1; j <= i__1; ++j) {
+		    if (x[j] != 0.) {
+			temp = x[j];
+			l = kplus1 - j;
+/* Computing MAX */
+			i__2 = 1, i__3 = j - *k;
+			i__4 = j - 1;
+			for (i__ = max(i__2,i__3); i__ <= i__4; ++i__) {
+			    x[i__] += temp * a[l + i__ + j * a_dim1];
+/* L10: */
+			}
+			if (nounit) {
+			    x[j] *= a[kplus1 + j * a_dim1];
+			}
+		    }
+/* L20: */
+		}
+	    } else {
+		jx = kx;
+		i__1 = *n;
+		for (j = 1; j <= i__1; ++j) {
+		    if (x[jx] != 0.) {
+			temp = x[jx];
+			ix = kx;
+			l = kplus1 - j;
+/* Computing MAX */
+			i__4 = 1, i__2 = j - *k;
+			i__3 = j - 1;
+			for (i__ = max(i__4,i__2); i__ <= i__3; ++i__) {
+			    x[ix] += temp * a[l + i__ + j * a_dim1];
+			    ix += *incx;
+/* L30: */
+			}
+			if (nounit) {
+			    x[jx] *= a[kplus1 + j * a_dim1];
+			}
+		    }
+		    jx += *incx;
+		    if (j > *k) {
+			kx += *incx;
+		    }
+/* L40: */
+		}
+	    }
+	} else {
+	    if (*incx == 1) {
+		for (j = *n; j >= 1; --j) {
+		    if (x[j] != 0.) {
+			temp = x[j];
+			l = 1 - j;
+/* Computing MIN */
+			i__1 = *n, i__3 = j + *k;
+			i__4 = j + 1;
+			for (i__ = min(i__1,i__3); i__ >= i__4; --i__) {
+			    x[i__] += temp * a[l + i__ + j * a_dim1];
+/* L50: */
+			}
+			if (nounit) {
+			    x[j] *= a[j * a_dim1 + 1];
+			}
+		    }
+/* L60: */
+		}
+	    } else {
+		kx += (*n - 1) * *incx;
+		jx = kx;
+		for (j = *n; j >= 1; --j) {
+		    if (x[jx] != 0.) {
+			temp = x[jx];
+			ix = kx;
+			l = 1 - j;
+/* Computing MIN */
+			i__4 = *n, i__1 = j + *k;
+			i__3 = j + 1;
+			for (i__ = min(i__4,i__1); i__ >= i__3; --i__) {
+			    x[ix] += temp * a[l + i__ + j * a_dim1];
+			    ix -= *incx;
+/* L70: */
+			}
+			if (nounit) {
+			    x[jx] *= a[j * a_dim1 + 1];
+			}
+		    }
+		    jx -= *incx;
+		    if (*n - j >= *k) {
+			kx -= *incx;
+		    }
+/* L80: */
+		}
+	    }
+	}
+    } else {
+
+/*        Form  x := A'*x. */
+
+	if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+	    kplus1 = *k + 1;
+	    if (*incx == 1) {
+		for (j = *n; j >= 1; --j) {
+		    temp = x[j];
+		    l = kplus1 - j;
+		    if (nounit) {
+			temp *= a[kplus1 + j * a_dim1];
+		    }
+/* Computing MAX */
+		    i__4 = 1, i__1 = j - *k;
+		    i__3 = max(i__4,i__1);
+		    for (i__ = j - 1; i__ >= i__3; --i__) {
+			temp += a[l + i__ + j * a_dim1] * x[i__];
+/* L90: */
+		    }
+		    x[j] = temp;
+/* L100: */
+		}
+	    } else {
+		kx += (*n - 1) * *incx;
+		jx = kx;
+		for (j = *n; j >= 1; --j) {
+		    temp = x[jx];
+		    kx -= *incx;
+		    ix = kx;
+		    l = kplus1 - j;
+		    if (nounit) {
+			temp *= a[kplus1 + j * a_dim1];
+		    }
+/* Computing MAX */
+		    i__4 = 1, i__1 = j - *k;
+		    i__3 = max(i__4,i__1);
+		    for (i__ = j - 1; i__ >= i__3; --i__) {
+			temp += a[l + i__ + j * a_dim1] * x[ix];
+			ix -= *incx;
+/* L110: */
+		    }
+		    x[jx] = temp;
+		    jx -= *incx;
+/* L120: */
+		}
+	    }
+	} else {
+	    if (*incx == 1) {
+		i__3 = *n;
+		for (j = 1; j <= i__3; ++j) {
+		    temp = x[j];
+		    l = 1 - j;
+		    if (nounit) {
+			temp *= a[j * a_dim1 + 1];
+		    }
+/* Computing MIN */
+		    i__1 = *n, i__2 = j + *k;
+		    i__4 = min(i__1,i__2);
+		    for (i__ = j + 1; i__ <= i__4; ++i__) {
+			temp += a[l + i__ + j * a_dim1] * x[i__];
+/* L130: */
+		    }
+		    x[j] = temp;
+/* L140: */
+		}
+	    } else {
+		jx = kx;
+		i__3 = *n;
+		for (j = 1; j <= i__3; ++j) {
+		    temp = x[jx];
+		    kx += *incx;
+		    ix = kx;
+		    l = 1 - j;
+		    if (nounit) {
+			temp *= a[j * a_dim1 + 1];
+		    }
+/* Computing MIN */
+		    i__1 = *n, i__2 = j + *k;
+		    i__4 = min(i__1,i__2);
+		    for (i__ = j + 1; i__ <= i__4; ++i__) {
+			temp += a[l + i__ + j * a_dim1] * x[ix];
+			ix += *incx;
+/* L150: */
+		    }
+		    x[jx] = temp;
+		    jx += *incx;
+/* L160: */
+		}
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of DTBMV . */
+
+} /* dtbmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/lsame.c
Index: 3rd_party/eigen/blas/f2c/lsame.c
==================================================================
--- 3rd_party/eigen/blas/f2c/lsame.c
+++ 3rd_party/eigen/blas/f2c/lsame.c
@@ -0,0 +1,117 @@
+/* lsame.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+logical lsame_(char *ca, char *cb, ftnlen ca_len, ftnlen cb_len)
+{
+    /* System generated locals */
+    logical ret_val;
+
+    /* Local variables */
+    integer inta, intb, zcode;
+
+
+/*  -- LAPACK auxiliary routine (version 3.1) -- */
+/*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
+/*     November 2006 */
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  LSAME returns .TRUE. if CA is the same letter as CB regardless of */
+/*  case. */
+
+/*  Arguments */
+/*  ========= */
+
+/*  CA      (input) CHARACTER*1 */
+
+/*  CB      (input) CHARACTER*1 */
+/*          CA and CB specify the single characters to be compared. */
+
+/* ===================================================================== */
+
+/*     .. Intrinsic Functions .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+
+/*     Test if the characters are equal */
+
+    ret_val = *(unsigned char *)ca == *(unsigned char *)cb;
+    if (ret_val) {
+	return ret_val;
+    }
+
+/*     Now test for equivalence if both characters are alphabetic. */
+
+    zcode = 'Z';
+
+/*     Use 'Z' rather than 'A' so that ASCII can be detected on Prime */
+/*     machines, on which ICHAR returns a value with bit 8 set. */
+/*     ICHAR('A') on Prime machines returns 193 which is the same as */
+/*     ICHAR('A') on an EBCDIC machine. */
+
+    inta = *(unsigned char *)ca;
+    intb = *(unsigned char *)cb;
+
+    if (zcode == 90 || zcode == 122) {
+
+/*        ASCII is assumed - ZCODE is the ASCII code of either lower or */
+/*        upper case 'Z'. */
+
+	if (inta >= 97 && inta <= 122) {
+	    inta += -32;
+	}
+	if (intb >= 97 && intb <= 122) {
+	    intb += -32;
+	}
+
+    } else if (zcode == 233 || zcode == 169) {
+
+/*        EBCDIC is assumed - ZCODE is the EBCDIC code of either lower or */
+/*        upper case 'Z'. */
+
+	if ((inta >= 129 && inta <= 137) || (inta >= 145 && inta <= 153) || 
+            (inta >= 162 && inta <= 169)) {
+	    inta += 64;
+	}
+	if ((intb >= 129 && intb <= 137) || (intb >= 145 && intb <= 153) || 
+            (intb >= 162 && intb <= 169)) {
+	    intb += 64;
+	}
+
+    } else if (zcode == 218 || zcode == 250) {
+
+/*        ASCII is assumed, on Prime machines - ZCODE is the ASCII code */
+/*        plus 128 of either lower or upper case 'Z'. */
+
+	if (inta >= 225 && inta <= 250) {
+	    inta += -32;
+	}
+	if (intb >= 225 && intb <= 250) {
+	    intb += -32;
+	}
+    }
+    ret_val = inta == intb;
+
+/*     RETURN */
+
+/*     End of LSAME */
+
+    return ret_val;
+} /* lsame_ */
+

ADDED   3rd_party/eigen/blas/f2c/r_cnjg.c
Index: 3rd_party/eigen/blas/f2c/r_cnjg.c
==================================================================
--- 3rd_party/eigen/blas/f2c/r_cnjg.c
+++ 3rd_party/eigen/blas/f2c/r_cnjg.c
@@ -0,0 +1,6 @@
+#include "datatypes.h"    
+
+void r_cnjg(complex *r, complex *z) {
+    r->r = z->r;
+    r->i = -(z->i);
+}

ADDED   3rd_party/eigen/blas/f2c/srotm.c
Index: 3rd_party/eigen/blas/f2c/srotm.c
==================================================================
--- 3rd_party/eigen/blas/f2c/srotm.c
+++ 3rd_party/eigen/blas/f2c/srotm.c
@@ -0,0 +1,216 @@
+/* srotm.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int srotm_(integer *n, real *sx, integer *incx, real *sy, 
+	integer *incy, real *sparam)
+{
+    /* Initialized data */
+
+    static real zero = 0.f;
+    static real two = 2.f;
+
+    /* System generated locals */
+    integer i__1, i__2;
+
+    /* Local variables */
+    integer i__;
+    real w, z__;
+    integer kx, ky;
+    real sh11, sh12, sh21, sh22, sflag;
+    integer nsteps;
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*     APPLY THE MODIFIED GIVENS TRANSFORMATION, H, TO THE 2 BY N MATRIX */
+
+/*     (SX**T) , WHERE **T INDICATES TRANSPOSE. THE ELEMENTS OF SX ARE IN */
+/*     (DX**T) */
+
+/*     SX(LX+I*INCX), I = 0 TO N-1, WHERE LX = 1 IF INCX .GE. 0, ELSE */
+/*     LX = (-INCX)*N, AND SIMILARLY FOR SY USING USING LY AND INCY. */
+/*     WITH SPARAM(1)=SFLAG, H HAS ONE OF THE FOLLOWING FORMS.. */
+
+/*     SFLAG=-1.E0     SFLAG=0.E0        SFLAG=1.E0     SFLAG=-2.E0 */
+
+/*       (SH11  SH12)    (1.E0  SH12)    (SH11  1.E0)    (1.E0  0.E0) */
+/*     H=(          )    (          )    (          )    (          ) */
+/*       (SH21  SH22),   (SH21  1.E0),   (-1.E0 SH22),   (0.E0  1.E0). */
+/*     SEE  SROTMG FOR A DESCRIPTION OF DATA STORAGE IN SPARAM. */
+
+
+/*  Arguments */
+/*  ========= */
+
+/*  N      (input) INTEGER */
+/*         number of elements in input vector(s) */
+
+/*  SX     (input/output) REAL array, dimension N */
+/*         double precision vector with N elements */
+
+/*  INCX   (input) INTEGER */
+/*         storage spacing between elements of SX */
+
+/*  SY     (input/output) REAL array, dimension N */
+/*         double precision vector with N elements */
+
+/*  INCY   (input) INTEGER */
+/*         storage spacing between elements of SY */
+
+/*  SPARAM (input/output)  REAL array, dimension 5 */
+/*     SPARAM(1)=SFLAG */
+/*     SPARAM(2)=SH11 */
+/*     SPARAM(3)=SH21 */
+/*     SPARAM(4)=SH12 */
+/*     SPARAM(5)=SH22 */
+
+/*  ===================================================================== */
+
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. Data statements .. */
+    /* Parameter adjustments */
+    --sparam;
+    --sy;
+    --sx;
+
+    /* Function Body */
+/*     .. */
+
+    sflag = sparam[1];
+    if (*n <= 0 || sflag + two == zero) {
+	goto L140;
+    }
+    if (! (*incx == *incy && *incx > 0)) {
+	goto L70;
+    }
+
+    nsteps = *n * *incx;
+    if (sflag < 0.f) {
+	goto L50;
+    } else if (sflag == 0) {
+	goto L10;
+    } else {
+	goto L30;
+    }
+L10:
+    sh12 = sparam[4];
+    sh21 = sparam[3];
+    i__1 = nsteps;
+    i__2 = *incx;
+    for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
+	w = sx[i__];
+	z__ = sy[i__];
+	sx[i__] = w + z__ * sh12;
+	sy[i__] = w * sh21 + z__;
+/* L20: */
+    }
+    goto L140;
+L30:
+    sh11 = sparam[2];
+    sh22 = sparam[5];
+    i__2 = nsteps;
+    i__1 = *incx;
+    for (i__ = 1; i__1 < 0 ? i__ >= i__2 : i__ <= i__2; i__ += i__1) {
+	w = sx[i__];
+	z__ = sy[i__];
+	sx[i__] = w * sh11 + z__;
+	sy[i__] = -w + sh22 * z__;
+/* L40: */
+    }
+    goto L140;
+L50:
+    sh11 = sparam[2];
+    sh12 = sparam[4];
+    sh21 = sparam[3];
+    sh22 = sparam[5];
+    i__1 = nsteps;
+    i__2 = *incx;
+    for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
+	w = sx[i__];
+	z__ = sy[i__];
+	sx[i__] = w * sh11 + z__ * sh12;
+	sy[i__] = w * sh21 + z__ * sh22;
+/* L60: */
+    }
+    goto L140;
+L70:
+    kx = 1;
+    ky = 1;
+    if (*incx < 0) {
+	kx = (1 - *n) * *incx + 1;
+    }
+    if (*incy < 0) {
+	ky = (1 - *n) * *incy + 1;
+    }
+
+    if (sflag < 0.f) {
+	goto L120;
+    } else if (sflag == 0) {
+	goto L80;
+    } else {
+	goto L100;
+    }
+L80:
+    sh12 = sparam[4];
+    sh21 = sparam[3];
+    i__2 = *n;
+    for (i__ = 1; i__ <= i__2; ++i__) {
+	w = sx[kx];
+	z__ = sy[ky];
+	sx[kx] = w + z__ * sh12;
+	sy[ky] = w * sh21 + z__;
+	kx += *incx;
+	ky += *incy;
+/* L90: */
+    }
+    goto L140;
+L100:
+    sh11 = sparam[2];
+    sh22 = sparam[5];
+    i__2 = *n;
+    for (i__ = 1; i__ <= i__2; ++i__) {
+	w = sx[kx];
+	z__ = sy[ky];
+	sx[kx] = w * sh11 + z__;
+	sy[ky] = -w + sh22 * z__;
+	kx += *incx;
+	ky += *incy;
+/* L110: */
+    }
+    goto L140;
+L120:
+    sh11 = sparam[2];
+    sh12 = sparam[4];
+    sh21 = sparam[3];
+    sh22 = sparam[5];
+    i__2 = *n;
+    for (i__ = 1; i__ <= i__2; ++i__) {
+	w = sx[kx];
+	z__ = sy[ky];
+	sx[kx] = w * sh11 + z__ * sh12;
+	sy[ky] = w * sh21 + z__ * sh22;
+	kx += *incx;
+	ky += *incy;
+/* L130: */
+    }
+L140:
+    return 0;
+} /* srotm_ */
+

ADDED   3rd_party/eigen/blas/f2c/srotmg.c
Index: 3rd_party/eigen/blas/f2c/srotmg.c
==================================================================
--- 3rd_party/eigen/blas/f2c/srotmg.c
+++ 3rd_party/eigen/blas/f2c/srotmg.c
@@ -0,0 +1,295 @@
+/* srotmg.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int srotmg_(real *sd1, real *sd2, real *sx1, real *sy1, real 
+	*sparam)
+{
+    /* Initialized data */
+
+    static real zero = 0.f;
+    static real one = 1.f;
+    static real two = 2.f;
+    static real gam = 4096.f;
+    static real gamsq = 16777200.f;
+    static real rgamsq = 5.96046e-8f;
+
+    /* Format strings */
+    static char fmt_120[] = "";
+    static char fmt_150[] = "";
+    static char fmt_180[] = "";
+    static char fmt_210[] = "";
+
+    /* System generated locals */
+    real r__1;
+
+    /* Local variables */
+    real su, sp1, sp2, sq1, sq2, sh11, sh12, sh21, sh22;
+    integer igo;
+    real sflag, stemp;
+
+    /* Assigned format variables */
+    static char *igo_fmt;
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*     CONSTRUCT THE MODIFIED GIVENS TRANSFORMATION MATRIX H WHICH ZEROS */
+/*     THE SECOND COMPONENT OF THE 2-VECTOR  (SQRT(SD1)*SX1,SQRT(SD2)* */
+/*     SY2)**T. */
+/*     WITH SPARAM(1)=SFLAG, H HAS ONE OF THE FOLLOWING FORMS.. */
+
+/*     SFLAG=-1.E0     SFLAG=0.E0        SFLAG=1.E0     SFLAG=-2.E0 */
+
+/*       (SH11  SH12)    (1.E0  SH12)    (SH11  1.E0)    (1.E0  0.E0) */
+/*     H=(          )    (          )    (          )    (          ) */
+/*       (SH21  SH22),   (SH21  1.E0),   (-1.E0 SH22),   (0.E0  1.E0). */
+/*     LOCATIONS 2-4 OF SPARAM CONTAIN SH11,SH21,SH12, AND SH22 */
+/*     RESPECTIVELY. (VALUES OF 1.E0, -1.E0, OR 0.E0 IMPLIED BY THE */
+/*     VALUE OF SPARAM(1) ARE NOT STORED IN SPARAM.) */
+
+/*     THE VALUES OF GAMSQ AND RGAMSQ SET IN THE DATA STATEMENT MAY BE */
+/*     INEXACT.  THIS IS OK AS THEY ARE ONLY USED FOR TESTING THE SIZE */
+/*     OF SD1 AND SD2.  ALL ACTUAL SCALING OF DATA IS DONE USING GAM. */
+
+
+/*  Arguments */
+/*  ========= */
+
+
+/*  SD1    (input/output) REAL */
+
+/*  SD2    (input/output) REAL */
+
+/*  SX1    (input/output) REAL */
+
+/*  SY1    (input) REAL */
+
+
+/*  SPARAM (input/output)  REAL array, dimension 5 */
+/*     SPARAM(1)=SFLAG */
+/*     SPARAM(2)=SH11 */
+/*     SPARAM(3)=SH21 */
+/*     SPARAM(4)=SH12 */
+/*     SPARAM(5)=SH22 */
+
+/*  ===================================================================== */
+
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+/*     .. Data statements .. */
+
+    /* Parameter adjustments */
+    --sparam;
+
+    /* Function Body */
+/*     .. */
+    if (! (*sd1 < zero)) {
+	goto L10;
+    }
+/*       GO ZERO-H-D-AND-SX1.. */
+    goto L60;
+L10:
+/*     CASE-SD1-NONNEGATIVE */
+    sp2 = *sd2 * *sy1;
+    if (! (sp2 == zero)) {
+	goto L20;
+    }
+    sflag = -two;
+    goto L260;
+/*     REGULAR-CASE.. */
+L20:
+    sp1 = *sd1 * *sx1;
+    sq2 = sp2 * *sy1;
+    sq1 = sp1 * *sx1;
+
+    if (! (dabs(sq1) > dabs(sq2))) {
+	goto L40;
+    }
+    sh21 = -(*sy1) / *sx1;
+    sh12 = sp2 / sp1;
+
+    su = one - sh12 * sh21;
+
+    if (! (su <= zero)) {
+	goto L30;
+    }
+/*         GO ZERO-H-D-AND-SX1.. */
+    goto L60;
+L30:
+    sflag = zero;
+    *sd1 /= su;
+    *sd2 /= su;
+    *sx1 *= su;
+/*         GO SCALE-CHECK.. */
+    goto L100;
+L40:
+    if (! (sq2 < zero)) {
+	goto L50;
+    }
+/*         GO ZERO-H-D-AND-SX1.. */
+    goto L60;
+L50:
+    sflag = one;
+    sh11 = sp1 / sp2;
+    sh22 = *sx1 / *sy1;
+    su = one + sh11 * sh22;
+    stemp = *sd2 / su;
+    *sd2 = *sd1 / su;
+    *sd1 = stemp;
+    *sx1 = *sy1 * su;
+/*         GO SCALE-CHECK */
+    goto L100;
+/*     PROCEDURE..ZERO-H-D-AND-SX1.. */
+L60:
+    sflag = -one;
+    sh11 = zero;
+    sh12 = zero;
+    sh21 = zero;
+    sh22 = zero;
+
+    *sd1 = zero;
+    *sd2 = zero;
+    *sx1 = zero;
+/*         RETURN.. */
+    goto L220;
+/*     PROCEDURE..FIX-H.. */
+L70:
+    if (! (sflag >= zero)) {
+	goto L90;
+    }
+
+    if (! (sflag == zero)) {
+	goto L80;
+    }
+    sh11 = one;
+    sh22 = one;
+    sflag = -one;
+    goto L90;
+L80:
+    sh21 = -one;
+    sh12 = one;
+    sflag = -one;
+L90:
+    switch (igo) {
+	case 0: goto L120;
+	case 1: goto L150;
+	case 2: goto L180;
+	case 3: goto L210;
+    }
+/*     PROCEDURE..SCALE-CHECK */
+L100:
+L110:
+    if (! (*sd1 <= rgamsq)) {
+	goto L130;
+    }
+    if (*sd1 == zero) {
+	goto L160;
+    }
+    igo = 0;
+    igo_fmt = fmt_120;
+/*              FIX-H.. */
+    goto L70;
+L120:
+/* Computing 2nd power */
+    r__1 = gam;
+    *sd1 *= r__1 * r__1;
+    *sx1 /= gam;
+    sh11 /= gam;
+    sh12 /= gam;
+    goto L110;
+L130:
+L140:
+    if (! (*sd1 >= gamsq)) {
+	goto L160;
+    }
+    igo = 1;
+    igo_fmt = fmt_150;
+/*              FIX-H.. */
+    goto L70;
+L150:
+/* Computing 2nd power */
+    r__1 = gam;
+    *sd1 /= r__1 * r__1;
+    *sx1 *= gam;
+    sh11 *= gam;
+    sh12 *= gam;
+    goto L140;
+L160:
+L170:
+    if (! (dabs(*sd2) <= rgamsq)) {
+	goto L190;
+    }
+    if (*sd2 == zero) {
+	goto L220;
+    }
+    igo = 2;
+    igo_fmt = fmt_180;
+/*              FIX-H.. */
+    goto L70;
+L180:
+/* Computing 2nd power */
+    r__1 = gam;
+    *sd2 *= r__1 * r__1;
+    sh21 /= gam;
+    sh22 /= gam;
+    goto L170;
+L190:
+L200:
+    if (! (dabs(*sd2) >= gamsq)) {
+	goto L220;
+    }
+    igo = 3;
+    igo_fmt = fmt_210;
+/*              FIX-H.. */
+    goto L70;
+L210:
+/* Computing 2nd power */
+    r__1 = gam;
+    *sd2 /= r__1 * r__1;
+    sh21 *= gam;
+    sh22 *= gam;
+    goto L200;
+L220:
+    if (sflag < 0.f) {
+	goto L250;
+    } else if (sflag == 0) {
+	goto L230;
+    } else {
+	goto L240;
+    }
+L230:
+    sparam[3] = sh21;
+    sparam[4] = sh12;
+    goto L260;
+L240:
+    sparam[2] = sh11;
+    sparam[5] = sh22;
+    goto L260;
+L250:
+    sparam[2] = sh11;
+    sparam[3] = sh21;
+    sparam[4] = sh12;
+    sparam[5] = sh22;
+L260:
+    sparam[1] = sflag;
+    return 0;
+} /* srotmg_ */
+

ADDED   3rd_party/eigen/blas/f2c/ssbmv.c
Index: 3rd_party/eigen/blas/f2c/ssbmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/ssbmv.c
+++ 3rd_party/eigen/blas/f2c/ssbmv.c
@@ -0,0 +1,368 @@
+/* ssbmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int ssbmv_(char *uplo, integer *n, integer *k, real *alpha, 
+	real *a, integer *lda, real *x, integer *incx, real *beta, real *y, 
+	integer *incy, ftnlen uplo_len)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
+
+    /* Local variables */
+    integer i__, j, l, ix, iy, jx, jy, kx, ky, info;
+    real temp1, temp2;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    integer kplus1;
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  SSBMV  performs the matrix-vector  operation */
+
+/*     y := alpha*A*x + beta*y, */
+
+/*  where alpha and beta are scalars, x and y are n element vectors and */
+/*  A is an n by n symmetric band matrix, with k super-diagonals. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the upper or lower */
+/*           triangular part of the band matrix A is being supplied as */
+/*           follows: */
+
+/*              UPLO = 'U' or 'u'   The upper triangular part of A is */
+/*                                  being supplied. */
+
+/*              UPLO = 'L' or 'l'   The lower triangular part of A is */
+/*                                  being supplied. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  K      - INTEGER. */
+/*           On entry, K specifies the number of super-diagonals of the */
+/*           matrix A. K must satisfy  0 .le. K. */
+/*           Unchanged on exit. */
+
+/*  ALPHA  - REAL            . */
+/*           On entry, ALPHA specifies the scalar alpha. */
+/*           Unchanged on exit. */
+
+/*  A      - REAL             array of DIMENSION ( LDA, n ). */
+/*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the upper triangular */
+/*           band part of the symmetric matrix, supplied column by */
+/*           column, with the leading diagonal of the matrix in row */
+/*           ( k + 1 ) of the array, the first super-diagonal starting at */
+/*           position 2 in row k, and so on. The top left k by k triangle */
+/*           of the array A is not referenced. */
+/*           The following program segment will transfer the upper */
+/*           triangular part of a symmetric band matrix from conventional */
+/*           full matrix storage to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = K + 1 - J */
+/*                    DO 10, I = MAX( 1, J - K ), J */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the lower triangular */
+/*           band part of the symmetric matrix, supplied column by */
+/*           column, with the leading diagonal of the matrix in row 1 of */
+/*           the array, the first sub-diagonal starting at position 1 in */
+/*           row 2, and so on. The bottom right k by k triangle of the */
+/*           array A is not referenced. */
+/*           The following program segment will transfer the lower */
+/*           triangular part of a symmetric band matrix from conventional */
+/*           full matrix storage to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = 1 - J */
+/*                    DO 10, I = J, MIN( N, J + K ) */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Unchanged on exit. */
+
+/*  LDA    - INTEGER. */
+/*           On entry, LDA specifies the first dimension of A as declared */
+/*           in the calling (sub) program. LDA must be at least */
+/*           ( k + 1 ). */
+/*           Unchanged on exit. */
+
+/*  X      - REAL             array of DIMENSION at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the */
+/*           vector x. */
+/*           Unchanged on exit. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  BETA   - REAL            . */
+/*           On entry, BETA specifies the scalar beta. */
+/*           Unchanged on exit. */
+
+/*  Y      - REAL             array of DIMENSION at least */
+/*           ( 1 + ( n - 1 )*abs( INCY ) ). */
+/*           Before entry, the incremented array Y must contain the */
+/*           vector y. On exit, Y is overwritten by the updated vector y. */
+
+/*  INCY   - INTEGER. */
+/*           On entry, INCY specifies the increment for the elements of */
+/*           Y. INCY must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    --x;
+    --y;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (*n < 0) {
+	info = 2;
+    } else if (*k < 0) {
+	info = 3;
+    } else if (*lda < *k + 1) {
+	info = 6;
+    } else if (*incx == 0) {
+	info = 8;
+    } else if (*incy == 0) {
+	info = 11;
+    }
+    if (info != 0) {
+	xerbla_("SSBMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0 || (*alpha == 0.f && *beta == 1.f)) {
+	return 0;
+    }
+
+/*     Set up the start points in  X  and  Y. */
+
+    if (*incx > 0) {
+	kx = 1;
+    } else {
+	kx = 1 - (*n - 1) * *incx;
+    }
+    if (*incy > 0) {
+	ky = 1;
+    } else {
+	ky = 1 - (*n - 1) * *incy;
+    }
+
+/*     Start the operations. In this version the elements of the array A */
+/*     are accessed sequentially with one pass through A. */
+
+/*     First form  y := beta*y. */
+
+    if (*beta != 1.f) {
+	if (*incy == 1) {
+	    if (*beta == 0.f) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[i__] = 0.f;
+/* L10: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[i__] = *beta * y[i__];
+/* L20: */
+		}
+	    }
+	} else {
+	    iy = ky;
+	    if (*beta == 0.f) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[iy] = 0.f;
+		    iy += *incy;
+/* L30: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[iy] = *beta * y[iy];
+		    iy += *incy;
+/* L40: */
+		}
+	    }
+	}
+    }
+    if (*alpha == 0.f) {
+	return 0;
+    }
+    if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+
+/*        Form  y  when upper triangle of A is stored. */
+
+	kplus1 = *k + 1;
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[j];
+		temp2 = 0.f;
+		l = kplus1 - j;
+/* Computing MAX */
+		i__2 = 1, i__3 = j - *k;
+		i__4 = j - 1;
+		for (i__ = max(i__2,i__3); i__ <= i__4; ++i__) {
+		    y[i__] += temp1 * a[l + i__ + j * a_dim1];
+		    temp2 += a[l + i__ + j * a_dim1] * x[i__];
+/* L50: */
+		}
+		y[j] = y[j] + temp1 * a[kplus1 + j * a_dim1] + *alpha * temp2;
+/* L60: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[jx];
+		temp2 = 0.f;
+		ix = kx;
+		iy = ky;
+		l = kplus1 - j;
+/* Computing MAX */
+		i__4 = 1, i__2 = j - *k;
+		i__3 = j - 1;
+		for (i__ = max(i__4,i__2); i__ <= i__3; ++i__) {
+		    y[iy] += temp1 * a[l + i__ + j * a_dim1];
+		    temp2 += a[l + i__ + j * a_dim1] * x[ix];
+		    ix += *incx;
+		    iy += *incy;
+/* L70: */
+		}
+		y[jy] = y[jy] + temp1 * a[kplus1 + j * a_dim1] + *alpha * 
+			temp2;
+		jx += *incx;
+		jy += *incy;
+		if (j > *k) {
+		    kx += *incx;
+		    ky += *incy;
+		}
+/* L80: */
+	    }
+	}
+    } else {
+
+/*        Form  y  when lower triangle of A is stored. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[j];
+		temp2 = 0.f;
+		y[j] += temp1 * a[j * a_dim1 + 1];
+		l = 1 - j;
+/* Computing MIN */
+		i__4 = *n, i__2 = j + *k;
+		i__3 = min(i__4,i__2);
+		for (i__ = j + 1; i__ <= i__3; ++i__) {
+		    y[i__] += temp1 * a[l + i__ + j * a_dim1];
+		    temp2 += a[l + i__ + j * a_dim1] * x[i__];
+/* L90: */
+		}
+		y[j] += *alpha * temp2;
+/* L100: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[jx];
+		temp2 = 0.f;
+		y[jy] += temp1 * a[j * a_dim1 + 1];
+		l = 1 - j;
+		ix = jx;
+		iy = jy;
+/* Computing MIN */
+		i__4 = *n, i__2 = j + *k;
+		i__3 = min(i__4,i__2);
+		for (i__ = j + 1; i__ <= i__3; ++i__) {
+		    ix += *incx;
+		    iy += *incy;
+		    y[iy] += temp1 * a[l + i__ + j * a_dim1];
+		    temp2 += a[l + i__ + j * a_dim1] * x[ix];
+/* L110: */
+		}
+		y[jy] += *alpha * temp2;
+		jx += *incx;
+		jy += *incy;
+/* L120: */
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of SSBMV . */
+
+} /* ssbmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/sspmv.c
Index: 3rd_party/eigen/blas/f2c/sspmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/sspmv.c
+++ 3rd_party/eigen/blas/f2c/sspmv.c
@@ -0,0 +1,316 @@
+/* sspmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int sspmv_(char *uplo, integer *n, real *alpha, real *ap, 
+	real *x, integer *incx, real *beta, real *y, integer *incy, ftnlen 
+	uplo_len)
+{
+    /* System generated locals */
+    integer i__1, i__2;
+
+    /* Local variables */
+    integer i__, j, k, kk, ix, iy, jx, jy, kx, ky, info;
+    real temp1, temp2;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  SSPMV  performs the matrix-vector operation */
+
+/*     y := alpha*A*x + beta*y, */
+
+/*  where alpha and beta are scalars, x and y are n element vectors and */
+/*  A is an n by n symmetric matrix, supplied in packed form. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the upper or lower */
+/*           triangular part of the matrix A is supplied in the packed */
+/*           array AP as follows: */
+
+/*              UPLO = 'U' or 'u'   The upper triangular part of A is */
+/*                                  supplied in AP. */
+
+/*              UPLO = 'L' or 'l'   The lower triangular part of A is */
+/*                                  supplied in AP. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  ALPHA  - REAL            . */
+/*           On entry, ALPHA specifies the scalar alpha. */
+/*           Unchanged on exit. */
+
+/*  AP     - REAL             array of DIMENSION at least */
+/*           ( ( n*( n + 1 ) )/2 ). */
+/*           Before entry with UPLO = 'U' or 'u', the array AP must */
+/*           contain the upper triangular part of the symmetric matrix */
+/*           packed sequentially, column by column, so that AP( 1 ) */
+/*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 ) */
+/*           and a( 2, 2 ) respectively, and so on. */
+/*           Before entry with UPLO = 'L' or 'l', the array AP must */
+/*           contain the lower triangular part of the symmetric matrix */
+/*           packed sequentially, column by column, so that AP( 1 ) */
+/*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 ) */
+/*           and a( 3, 1 ) respectively, and so on. */
+/*           Unchanged on exit. */
+
+/*  X      - REAL             array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the n */
+/*           element vector x. */
+/*           Unchanged on exit. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  BETA   - REAL            . */
+/*           On entry, BETA specifies the scalar beta. When BETA is */
+/*           supplied as zero then Y need not be set on input. */
+/*           Unchanged on exit. */
+
+/*  Y      - REAL             array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCY ) ). */
+/*           Before entry, the incremented array Y must contain the n */
+/*           element vector y. On exit, Y is overwritten by the updated */
+/*           vector y. */
+
+/*  INCY   - INTEGER. */
+/*           On entry, INCY specifies the increment for the elements of */
+/*           Y. INCY must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    --y;
+    --x;
+    --ap;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (*n < 0) {
+	info = 2;
+    } else if (*incx == 0) {
+	info = 6;
+    } else if (*incy == 0) {
+	info = 9;
+    }
+    if (info != 0) {
+	xerbla_("SSPMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0 || (*alpha == 0.f && *beta == 1.f)) {
+	return 0;
+    }
+
+/*     Set up the start points in  X  and  Y. */
+
+    if (*incx > 0) {
+	kx = 1;
+    } else {
+	kx = 1 - (*n - 1) * *incx;
+    }
+    if (*incy > 0) {
+	ky = 1;
+    } else {
+	ky = 1 - (*n - 1) * *incy;
+    }
+
+/*     Start the operations. In this version the elements of the array AP */
+/*     are accessed sequentially with one pass through AP. */
+
+/*     First form  y := beta*y. */
+
+    if (*beta != 1.f) {
+	if (*incy == 1) {
+	    if (*beta == 0.f) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[i__] = 0.f;
+/* L10: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[i__] = *beta * y[i__];
+/* L20: */
+		}
+	    }
+	} else {
+	    iy = ky;
+	    if (*beta == 0.f) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[iy] = 0.f;
+		    iy += *incy;
+/* L30: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    y[iy] = *beta * y[iy];
+		    iy += *incy;
+/* L40: */
+		}
+	    }
+	}
+    }
+    if (*alpha == 0.f) {
+	return 0;
+    }
+    kk = 1;
+    if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+
+/*        Form  y  when AP contains the upper triangle. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[j];
+		temp2 = 0.f;
+		k = kk;
+		i__2 = j - 1;
+		for (i__ = 1; i__ <= i__2; ++i__) {
+		    y[i__] += temp1 * ap[k];
+		    temp2 += ap[k] * x[i__];
+		    ++k;
+/* L50: */
+		}
+		y[j] = y[j] + temp1 * ap[kk + j - 1] + *alpha * temp2;
+		kk += j;
+/* L60: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[jx];
+		temp2 = 0.f;
+		ix = kx;
+		iy = ky;
+		i__2 = kk + j - 2;
+		for (k = kk; k <= i__2; ++k) {
+		    y[iy] += temp1 * ap[k];
+		    temp2 += ap[k] * x[ix];
+		    ix += *incx;
+		    iy += *incy;
+/* L70: */
+		}
+		y[jy] = y[jy] + temp1 * ap[kk + j - 1] + *alpha * temp2;
+		jx += *incx;
+		jy += *incy;
+		kk += j;
+/* L80: */
+	    }
+	}
+    } else {
+
+/*        Form  y  when AP contains the lower triangle. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[j];
+		temp2 = 0.f;
+		y[j] += temp1 * ap[kk];
+		k = kk + 1;
+		i__2 = *n;
+		for (i__ = j + 1; i__ <= i__2; ++i__) {
+		    y[i__] += temp1 * ap[k];
+		    temp2 += ap[k] * x[i__];
+		    ++k;
+/* L90: */
+		}
+		y[j] += *alpha * temp2;
+		kk += *n - j + 1;
+/* L100: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		temp1 = *alpha * x[jx];
+		temp2 = 0.f;
+		y[jy] += temp1 * ap[kk];
+		ix = jx;
+		iy = jy;
+		i__2 = kk + *n - j;
+		for (k = kk + 1; k <= i__2; ++k) {
+		    ix += *incx;
+		    iy += *incy;
+		    y[iy] += temp1 * ap[k];
+		    temp2 += ap[k] * x[ix];
+/* L110: */
+		}
+		y[jy] += *alpha * temp2;
+		jx += *incx;
+		jy += *incy;
+		kk += *n - j + 1;
+/* L120: */
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of SSPMV . */
+
+} /* sspmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/stbmv.c
Index: 3rd_party/eigen/blas/f2c/stbmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/stbmv.c
+++ 3rd_party/eigen/blas/f2c/stbmv.c
@@ -0,0 +1,428 @@
+/* stbmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int stbmv_(char *uplo, char *trans, char *diag, integer *n, 
+	integer *k, real *a, integer *lda, real *x, integer *incx, ftnlen 
+	uplo_len, ftnlen trans_len, ftnlen diag_len)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
+
+    /* Local variables */
+    integer i__, j, l, ix, jx, kx, info;
+    real temp;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    integer kplus1;
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+    logical nounit;
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  STBMV  performs one of the matrix-vector operations */
+
+/*     x := A*x,   or   x := A'*x, */
+
+/*  where x is an n element vector and  A is an n by n unit, or non-unit, */
+/*  upper or lower triangular band matrix, with ( k + 1 ) diagonals. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the matrix is an upper or */
+/*           lower triangular matrix as follows: */
+
+/*              UPLO = 'U' or 'u'   A is an upper triangular matrix. */
+
+/*              UPLO = 'L' or 'l'   A is a lower triangular matrix. */
+
+/*           Unchanged on exit. */
+
+/*  TRANS  - CHARACTER*1. */
+/*           On entry, TRANS specifies the operation to be performed as */
+/*           follows: */
+
+/*              TRANS = 'N' or 'n'   x := A*x. */
+
+/*              TRANS = 'T' or 't'   x := A'*x. */
+
+/*              TRANS = 'C' or 'c'   x := A'*x. */
+
+/*           Unchanged on exit. */
+
+/*  DIAG   - CHARACTER*1. */
+/*           On entry, DIAG specifies whether or not A is unit */
+/*           triangular as follows: */
+
+/*              DIAG = 'U' or 'u'   A is assumed to be unit triangular. */
+
+/*              DIAG = 'N' or 'n'   A is not assumed to be unit */
+/*                                  triangular. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  K      - INTEGER. */
+/*           On entry with UPLO = 'U' or 'u', K specifies the number of */
+/*           super-diagonals of the matrix A. */
+/*           On entry with UPLO = 'L' or 'l', K specifies the number of */
+/*           sub-diagonals of the matrix A. */
+/*           K must satisfy  0 .le. K. */
+/*           Unchanged on exit. */
+
+/*  A      - REAL             array of DIMENSION ( LDA, n ). */
+/*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the upper triangular */
+/*           band part of the matrix of coefficients, supplied column by */
+/*           column, with the leading diagonal of the matrix in row */
+/*           ( k + 1 ) of the array, the first super-diagonal starting at */
+/*           position 2 in row k, and so on. The top left k by k triangle */
+/*           of the array A is not referenced. */
+/*           The following program segment will transfer an upper */
+/*           triangular band matrix from conventional full matrix storage */
+/*           to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = K + 1 - J */
+/*                    DO 10, I = MAX( 1, J - K ), J */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the lower triangular */
+/*           band part of the matrix of coefficients, supplied column by */
+/*           column, with the leading diagonal of the matrix in row 1 of */
+/*           the array, the first sub-diagonal starting at position 1 in */
+/*           row 2, and so on. The bottom right k by k triangle of the */
+/*           array A is not referenced. */
+/*           The following program segment will transfer a lower */
+/*           triangular band matrix from conventional full matrix storage */
+/*           to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = 1 - J */
+/*                    DO 10, I = J, MIN( N, J + K ) */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Note that when DIAG = 'U' or 'u' the elements of the array A */
+/*           corresponding to the diagonal elements of the matrix are not */
+/*           referenced, but are assumed to be unity. */
+/*           Unchanged on exit. */
+
+/*  LDA    - INTEGER. */
+/*           On entry, LDA specifies the first dimension of A as declared */
+/*           in the calling (sub) program. LDA must be at least */
+/*           ( k + 1 ). */
+/*           Unchanged on exit. */
+
+/*  X      - REAL             array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the n */
+/*           element vector x. On exit, X is overwritten with the */
+/*           tranformed vector x. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    --x;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (! lsame_(trans, "N", (ftnlen)1, (ftnlen)1) && ! lsame_(trans, 
+	    "T", (ftnlen)1, (ftnlen)1) && ! lsame_(trans, "C", (ftnlen)1, (
+	    ftnlen)1)) {
+	info = 2;
+    } else if (! lsame_(diag, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(diag, 
+	    "N", (ftnlen)1, (ftnlen)1)) {
+	info = 3;
+    } else if (*n < 0) {
+	info = 4;
+    } else if (*k < 0) {
+	info = 5;
+    } else if (*lda < *k + 1) {
+	info = 7;
+    } else if (*incx == 0) {
+	info = 9;
+    }
+    if (info != 0) {
+	xerbla_("STBMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0) {
+	return 0;
+    }
+
+    nounit = lsame_(diag, "N", (ftnlen)1, (ftnlen)1);
+
+/*     Set up the start point in X if the increment is not unity. This */
+/*     will be  ( N - 1 )*INCX   too small for descending loops. */
+
+    if (*incx <= 0) {
+	kx = 1 - (*n - 1) * *incx;
+    } else if (*incx != 1) {
+	kx = 1;
+    }
+
+/*     Start the operations. In this version the elements of A are */
+/*     accessed sequentially with one pass through A. */
+
+    if (lsame_(trans, "N", (ftnlen)1, (ftnlen)1)) {
+
+/*         Form  x := A*x. */
+
+	if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+	    kplus1 = *k + 1;
+	    if (*incx == 1) {
+		i__1 = *n;
+		for (j = 1; j <= i__1; ++j) {
+		    if (x[j] != 0.f) {
+			temp = x[j];
+			l = kplus1 - j;
+/* Computing MAX */
+			i__2 = 1, i__3 = j - *k;
+			i__4 = j - 1;
+			for (i__ = max(i__2,i__3); i__ <= i__4; ++i__) {
+			    x[i__] += temp * a[l + i__ + j * a_dim1];
+/* L10: */
+			}
+			if (nounit) {
+			    x[j] *= a[kplus1 + j * a_dim1];
+			}
+		    }
+/* L20: */
+		}
+	    } else {
+		jx = kx;
+		i__1 = *n;
+		for (j = 1; j <= i__1; ++j) {
+		    if (x[jx] != 0.f) {
+			temp = x[jx];
+			ix = kx;
+			l = kplus1 - j;
+/* Computing MAX */
+			i__4 = 1, i__2 = j - *k;
+			i__3 = j - 1;
+			for (i__ = max(i__4,i__2); i__ <= i__3; ++i__) {
+			    x[ix] += temp * a[l + i__ + j * a_dim1];
+			    ix += *incx;
+/* L30: */
+			}
+			if (nounit) {
+			    x[jx] *= a[kplus1 + j * a_dim1];
+			}
+		    }
+		    jx += *incx;
+		    if (j > *k) {
+			kx += *incx;
+		    }
+/* L40: */
+		}
+	    }
+	} else {
+	    if (*incx == 1) {
+		for (j = *n; j >= 1; --j) {
+		    if (x[j] != 0.f) {
+			temp = x[j];
+			l = 1 - j;
+/* Computing MIN */
+			i__1 = *n, i__3 = j + *k;
+			i__4 = j + 1;
+			for (i__ = min(i__1,i__3); i__ >= i__4; --i__) {
+			    x[i__] += temp * a[l + i__ + j * a_dim1];
+/* L50: */
+			}
+			if (nounit) {
+			    x[j] *= a[j * a_dim1 + 1];
+			}
+		    }
+/* L60: */
+		}
+	    } else {
+		kx += (*n - 1) * *incx;
+		jx = kx;
+		for (j = *n; j >= 1; --j) {
+		    if (x[jx] != 0.f) {
+			temp = x[jx];
+			ix = kx;
+			l = 1 - j;
+/* Computing MIN */
+			i__4 = *n, i__1 = j + *k;
+			i__3 = j + 1;
+			for (i__ = min(i__4,i__1); i__ >= i__3; --i__) {
+			    x[ix] += temp * a[l + i__ + j * a_dim1];
+			    ix -= *incx;
+/* L70: */
+			}
+			if (nounit) {
+			    x[jx] *= a[j * a_dim1 + 1];
+			}
+		    }
+		    jx -= *incx;
+		    if (*n - j >= *k) {
+			kx -= *incx;
+		    }
+/* L80: */
+		}
+	    }
+	}
+    } else {
+
+/*        Form  x := A'*x. */
+
+	if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+	    kplus1 = *k + 1;
+	    if (*incx == 1) {
+		for (j = *n; j >= 1; --j) {
+		    temp = x[j];
+		    l = kplus1 - j;
+		    if (nounit) {
+			temp *= a[kplus1 + j * a_dim1];
+		    }
+/* Computing MAX */
+		    i__4 = 1, i__1 = j - *k;
+		    i__3 = max(i__4,i__1);
+		    for (i__ = j - 1; i__ >= i__3; --i__) {
+			temp += a[l + i__ + j * a_dim1] * x[i__];
+/* L90: */
+		    }
+		    x[j] = temp;
+/* L100: */
+		}
+	    } else {
+		kx += (*n - 1) * *incx;
+		jx = kx;
+		for (j = *n; j >= 1; --j) {
+		    temp = x[jx];
+		    kx -= *incx;
+		    ix = kx;
+		    l = kplus1 - j;
+		    if (nounit) {
+			temp *= a[kplus1 + j * a_dim1];
+		    }
+/* Computing MAX */
+		    i__4 = 1, i__1 = j - *k;
+		    i__3 = max(i__4,i__1);
+		    for (i__ = j - 1; i__ >= i__3; --i__) {
+			temp += a[l + i__ + j * a_dim1] * x[ix];
+			ix -= *incx;
+/* L110: */
+		    }
+		    x[jx] = temp;
+		    jx -= *incx;
+/* L120: */
+		}
+	    }
+	} else {
+	    if (*incx == 1) {
+		i__3 = *n;
+		for (j = 1; j <= i__3; ++j) {
+		    temp = x[j];
+		    l = 1 - j;
+		    if (nounit) {
+			temp *= a[j * a_dim1 + 1];
+		    }
+/* Computing MIN */
+		    i__1 = *n, i__2 = j + *k;
+		    i__4 = min(i__1,i__2);
+		    for (i__ = j + 1; i__ <= i__4; ++i__) {
+			temp += a[l + i__ + j * a_dim1] * x[i__];
+/* L130: */
+		    }
+		    x[j] = temp;
+/* L140: */
+		}
+	    } else {
+		jx = kx;
+		i__3 = *n;
+		for (j = 1; j <= i__3; ++j) {
+		    temp = x[jx];
+		    kx += *incx;
+		    ix = kx;
+		    l = 1 - j;
+		    if (nounit) {
+			temp *= a[j * a_dim1 + 1];
+		    }
+/* Computing MIN */
+		    i__1 = *n, i__2 = j + *k;
+		    i__4 = min(i__1,i__2);
+		    for (i__ = j + 1; i__ <= i__4; ++i__) {
+			temp += a[l + i__ + j * a_dim1] * x[ix];
+			ix += *incx;
+/* L150: */
+		    }
+		    x[jx] = temp;
+		    jx += *incx;
+/* L160: */
+		}
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of STBMV . */
+
+} /* stbmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/zhbmv.c
Index: 3rd_party/eigen/blas/f2c/zhbmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/zhbmv.c
+++ 3rd_party/eigen/blas/f2c/zhbmv.c
@@ -0,0 +1,488 @@
+/* zhbmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int zhbmv_(char *uplo, integer *n, integer *k, doublecomplex 
+	*alpha, doublecomplex *a, integer *lda, doublecomplex *x, integer *
+	incx, doublecomplex *beta, doublecomplex *y, integer *incy, ftnlen 
+	uplo_len)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5;
+    doublereal d__1;
+    doublecomplex z__1, z__2, z__3, z__4;
+
+    /* Builtin functions */
+    void d_cnjg(doublecomplex *, doublecomplex *);
+
+    /* Local variables */
+    integer i__, j, l, ix, iy, jx, jy, kx, ky, info;
+    doublecomplex temp1, temp2;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    integer kplus1;
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  ZHBMV  performs the matrix-vector  operation */
+
+/*     y := alpha*A*x + beta*y, */
+
+/*  where alpha and beta are scalars, x and y are n element vectors and */
+/*  A is an n by n hermitian band matrix, with k super-diagonals. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the upper or lower */
+/*           triangular part of the band matrix A is being supplied as */
+/*           follows: */
+
+/*              UPLO = 'U' or 'u'   The upper triangular part of A is */
+/*                                  being supplied. */
+
+/*              UPLO = 'L' or 'l'   The lower triangular part of A is */
+/*                                  being supplied. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  K      - INTEGER. */
+/*           On entry, K specifies the number of super-diagonals of the */
+/*           matrix A. K must satisfy  0 .le. K. */
+/*           Unchanged on exit. */
+
+/*  ALPHA  - COMPLEX*16      . */
+/*           On entry, ALPHA specifies the scalar alpha. */
+/*           Unchanged on exit. */
+
+/*  A      - COMPLEX*16       array of DIMENSION ( LDA, n ). */
+/*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the upper triangular */
+/*           band part of the hermitian matrix, supplied column by */
+/*           column, with the leading diagonal of the matrix in row */
+/*           ( k + 1 ) of the array, the first super-diagonal starting at */
+/*           position 2 in row k, and so on. The top left k by k triangle */
+/*           of the array A is not referenced. */
+/*           The following program segment will transfer the upper */
+/*           triangular part of a hermitian band matrix from conventional */
+/*           full matrix storage to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = K + 1 - J */
+/*                    DO 10, I = MAX( 1, J - K ), J */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the lower triangular */
+/*           band part of the hermitian matrix, supplied column by */
+/*           column, with the leading diagonal of the matrix in row 1 of */
+/*           the array, the first sub-diagonal starting at position 1 in */
+/*           row 2, and so on. The bottom right k by k triangle of the */
+/*           array A is not referenced. */
+/*           The following program segment will transfer the lower */
+/*           triangular part of a hermitian band matrix from conventional */
+/*           full matrix storage to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = 1 - J */
+/*                    DO 10, I = J, MIN( N, J + K ) */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Note that the imaginary parts of the diagonal elements need */
+/*           not be set and are assumed to be zero. */
+/*           Unchanged on exit. */
+
+/*  LDA    - INTEGER. */
+/*           On entry, LDA specifies the first dimension of A as declared */
+/*           in the calling (sub) program. LDA must be at least */
+/*           ( k + 1 ). */
+/*           Unchanged on exit. */
+
+/*  X      - COMPLEX*16       array of DIMENSION at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the */
+/*           vector x. */
+/*           Unchanged on exit. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  BETA   - COMPLEX*16      . */
+/*           On entry, BETA specifies the scalar beta. */
+/*           Unchanged on exit. */
+
+/*  Y      - COMPLEX*16       array of DIMENSION at least */
+/*           ( 1 + ( n - 1 )*abs( INCY ) ). */
+/*           Before entry, the incremented array Y must contain the */
+/*           vector y. On exit, Y is overwritten by the updated vector y. */
+
+/*  INCY   - INTEGER. */
+/*           On entry, INCY specifies the increment for the elements of */
+/*           Y. INCY must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    --x;
+    --y;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (*n < 0) {
+	info = 2;
+    } else if (*k < 0) {
+	info = 3;
+    } else if (*lda < *k + 1) {
+	info = 6;
+    } else if (*incx == 0) {
+	info = 8;
+    } else if (*incy == 0) {
+	info = 11;
+    }
+    if (info != 0) {
+	xerbla_("ZHBMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0 || (alpha->r == 0. && alpha->i == 0. && (beta->r == 1. && 
+                                                         beta->i == 0.))) {
+	return 0;
+    }
+
+/*     Set up the start points in  X  and  Y. */
+
+    if (*incx > 0) {
+	kx = 1;
+    } else {
+	kx = 1 - (*n - 1) * *incx;
+    }
+    if (*incy > 0) {
+	ky = 1;
+    } else {
+	ky = 1 - (*n - 1) * *incy;
+    }
+
+/*     Start the operations. In this version the elements of the array A */
+/*     are accessed sequentially with one pass through A. */
+
+/*     First form  y := beta*y. */
+
+    if (beta->r != 1. || beta->i != 0.) {
+	if (*incy == 1) {
+	    if (beta->r == 0. && beta->i == 0.) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = i__;
+		    y[i__2].r = 0., y[i__2].i = 0.;
+/* L10: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = i__;
+		    i__3 = i__;
+		    z__1.r = beta->r * y[i__3].r - beta->i * y[i__3].i, 
+			    z__1.i = beta->r * y[i__3].i + beta->i * y[i__3]
+			    .r;
+		    y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+/* L20: */
+		}
+	    }
+	} else {
+	    iy = ky;
+	    if (beta->r == 0. && beta->i == 0.) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = iy;
+		    y[i__2].r = 0., y[i__2].i = 0.;
+		    iy += *incy;
+/* L30: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = iy;
+		    i__3 = iy;
+		    z__1.r = beta->r * y[i__3].r - beta->i * y[i__3].i, 
+			    z__1.i = beta->r * y[i__3].i + beta->i * y[i__3]
+			    .r;
+		    y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		    iy += *incy;
+/* L40: */
+		}
+	    }
+	}
+    }
+    if (alpha->r == 0. && alpha->i == 0.) {
+	return 0;
+    }
+    if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+
+/*        Form  y  when upper triangle of A is stored. */
+
+	kplus1 = *k + 1;
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = j;
+		z__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, z__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = z__1.r, temp1.i = z__1.i;
+		temp2.r = 0., temp2.i = 0.;
+		l = kplus1 - j;
+/* Computing MAX */
+		i__2 = 1, i__3 = j - *k;
+		i__4 = j - 1;
+		for (i__ = max(i__2,i__3); i__ <= i__4; ++i__) {
+		    i__2 = i__;
+		    i__3 = i__;
+		    i__5 = l + i__ + j * a_dim1;
+		    z__2.r = temp1.r * a[i__5].r - temp1.i * a[i__5].i, 
+			    z__2.i = temp1.r * a[i__5].i + temp1.i * a[i__5]
+			    .r;
+		    z__1.r = y[i__3].r + z__2.r, z__1.i = y[i__3].i + z__2.i;
+		    y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		    d_cnjg(&z__3, &a[l + i__ + j * a_dim1]);
+		    i__2 = i__;
+		    z__2.r = z__3.r * x[i__2].r - z__3.i * x[i__2].i, z__2.i =
+			     z__3.r * x[i__2].i + z__3.i * x[i__2].r;
+		    z__1.r = temp2.r + z__2.r, z__1.i = temp2.i + z__2.i;
+		    temp2.r = z__1.r, temp2.i = z__1.i;
+/* L50: */
+		}
+		i__4 = j;
+		i__2 = j;
+		i__3 = kplus1 + j * a_dim1;
+		d__1 = a[i__3].r;
+		z__3.r = d__1 * temp1.r, z__3.i = d__1 * temp1.i;
+		z__2.r = y[i__2].r + z__3.r, z__2.i = y[i__2].i + z__3.i;
+		z__4.r = alpha->r * temp2.r - alpha->i * temp2.i, z__4.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		z__1.r = z__2.r + z__4.r, z__1.i = z__2.i + z__4.i;
+		y[i__4].r = z__1.r, y[i__4].i = z__1.i;
+/* L60: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__4 = jx;
+		z__1.r = alpha->r * x[i__4].r - alpha->i * x[i__4].i, z__1.i =
+			 alpha->r * x[i__4].i + alpha->i * x[i__4].r;
+		temp1.r = z__1.r, temp1.i = z__1.i;
+		temp2.r = 0., temp2.i = 0.;
+		ix = kx;
+		iy = ky;
+		l = kplus1 - j;
+/* Computing MAX */
+		i__4 = 1, i__2 = j - *k;
+		i__3 = j - 1;
+		for (i__ = max(i__4,i__2); i__ <= i__3; ++i__) {
+		    i__4 = iy;
+		    i__2 = iy;
+		    i__5 = l + i__ + j * a_dim1;
+		    z__2.r = temp1.r * a[i__5].r - temp1.i * a[i__5].i, 
+			    z__2.i = temp1.r * a[i__5].i + temp1.i * a[i__5]
+			    .r;
+		    z__1.r = y[i__2].r + z__2.r, z__1.i = y[i__2].i + z__2.i;
+		    y[i__4].r = z__1.r, y[i__4].i = z__1.i;
+		    d_cnjg(&z__3, &a[l + i__ + j * a_dim1]);
+		    i__4 = ix;
+		    z__2.r = z__3.r * x[i__4].r - z__3.i * x[i__4].i, z__2.i =
+			     z__3.r * x[i__4].i + z__3.i * x[i__4].r;
+		    z__1.r = temp2.r + z__2.r, z__1.i = temp2.i + z__2.i;
+		    temp2.r = z__1.r, temp2.i = z__1.i;
+		    ix += *incx;
+		    iy += *incy;
+/* L70: */
+		}
+		i__3 = jy;
+		i__4 = jy;
+		i__2 = kplus1 + j * a_dim1;
+		d__1 = a[i__2].r;
+		z__3.r = d__1 * temp1.r, z__3.i = d__1 * temp1.i;
+		z__2.r = y[i__4].r + z__3.r, z__2.i = y[i__4].i + z__3.i;
+		z__4.r = alpha->r * temp2.r - alpha->i * temp2.i, z__4.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		z__1.r = z__2.r + z__4.r, z__1.i = z__2.i + z__4.i;
+		y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+		jx += *incx;
+		jy += *incy;
+		if (j > *k) {
+		    kx += *incx;
+		    ky += *incy;
+		}
+/* L80: */
+	    }
+	}
+    } else {
+
+/*        Form  y  when lower triangle of A is stored. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__3 = j;
+		z__1.r = alpha->r * x[i__3].r - alpha->i * x[i__3].i, z__1.i =
+			 alpha->r * x[i__3].i + alpha->i * x[i__3].r;
+		temp1.r = z__1.r, temp1.i = z__1.i;
+		temp2.r = 0., temp2.i = 0.;
+		i__3 = j;
+		i__4 = j;
+		i__2 = j * a_dim1 + 1;
+		d__1 = a[i__2].r;
+		z__2.r = d__1 * temp1.r, z__2.i = d__1 * temp1.i;
+		z__1.r = y[i__4].r + z__2.r, z__1.i = y[i__4].i + z__2.i;
+		y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+		l = 1 - j;
+/* Computing MIN */
+		i__4 = *n, i__2 = j + *k;
+		i__3 = min(i__4,i__2);
+		for (i__ = j + 1; i__ <= i__3; ++i__) {
+		    i__4 = i__;
+		    i__2 = i__;
+		    i__5 = l + i__ + j * a_dim1;
+		    z__2.r = temp1.r * a[i__5].r - temp1.i * a[i__5].i, 
+			    z__2.i = temp1.r * a[i__5].i + temp1.i * a[i__5]
+			    .r;
+		    z__1.r = y[i__2].r + z__2.r, z__1.i = y[i__2].i + z__2.i;
+		    y[i__4].r = z__1.r, y[i__4].i = z__1.i;
+		    d_cnjg(&z__3, &a[l + i__ + j * a_dim1]);
+		    i__4 = i__;
+		    z__2.r = z__3.r * x[i__4].r - z__3.i * x[i__4].i, z__2.i =
+			     z__3.r * x[i__4].i + z__3.i * x[i__4].r;
+		    z__1.r = temp2.r + z__2.r, z__1.i = temp2.i + z__2.i;
+		    temp2.r = z__1.r, temp2.i = z__1.i;
+/* L90: */
+		}
+		i__3 = j;
+		i__4 = j;
+		z__2.r = alpha->r * temp2.r - alpha->i * temp2.i, z__2.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		z__1.r = y[i__4].r + z__2.r, z__1.i = y[i__4].i + z__2.i;
+		y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+/* L100: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__3 = jx;
+		z__1.r = alpha->r * x[i__3].r - alpha->i * x[i__3].i, z__1.i =
+			 alpha->r * x[i__3].i + alpha->i * x[i__3].r;
+		temp1.r = z__1.r, temp1.i = z__1.i;
+		temp2.r = 0., temp2.i = 0.;
+		i__3 = jy;
+		i__4 = jy;
+		i__2 = j * a_dim1 + 1;
+		d__1 = a[i__2].r;
+		z__2.r = d__1 * temp1.r, z__2.i = d__1 * temp1.i;
+		z__1.r = y[i__4].r + z__2.r, z__1.i = y[i__4].i + z__2.i;
+		y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+		l = 1 - j;
+		ix = jx;
+		iy = jy;
+/* Computing MIN */
+		i__4 = *n, i__2 = j + *k;
+		i__3 = min(i__4,i__2);
+		for (i__ = j + 1; i__ <= i__3; ++i__) {
+		    ix += *incx;
+		    iy += *incy;
+		    i__4 = iy;
+		    i__2 = iy;
+		    i__5 = l + i__ + j * a_dim1;
+		    z__2.r = temp1.r * a[i__5].r - temp1.i * a[i__5].i, 
+			    z__2.i = temp1.r * a[i__5].i + temp1.i * a[i__5]
+			    .r;
+		    z__1.r = y[i__2].r + z__2.r, z__1.i = y[i__2].i + z__2.i;
+		    y[i__4].r = z__1.r, y[i__4].i = z__1.i;
+		    d_cnjg(&z__3, &a[l + i__ + j * a_dim1]);
+		    i__4 = ix;
+		    z__2.r = z__3.r * x[i__4].r - z__3.i * x[i__4].i, z__2.i =
+			     z__3.r * x[i__4].i + z__3.i * x[i__4].r;
+		    z__1.r = temp2.r + z__2.r, z__1.i = temp2.i + z__2.i;
+		    temp2.r = z__1.r, temp2.i = z__1.i;
+/* L110: */
+		}
+		i__3 = jy;
+		i__4 = jy;
+		z__2.r = alpha->r * temp2.r - alpha->i * temp2.i, z__2.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		z__1.r = y[i__4].r + z__2.r, z__1.i = y[i__4].i + z__2.i;
+		y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+		jx += *incx;
+		jy += *incy;
+/* L120: */
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of ZHBMV . */
+
+} /* zhbmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/zhpmv.c
Index: 3rd_party/eigen/blas/f2c/zhpmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/zhpmv.c
+++ 3rd_party/eigen/blas/f2c/zhpmv.c
@@ -0,0 +1,438 @@
+/* zhpmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int zhpmv_(char *uplo, integer *n, doublecomplex *alpha, 
+	doublecomplex *ap, doublecomplex *x, integer *incx, doublecomplex *
+	beta, doublecomplex *y, integer *incy, ftnlen uplo_len)
+{
+    /* System generated locals */
+    integer i__1, i__2, i__3, i__4, i__5;
+    doublereal d__1;
+    doublecomplex z__1, z__2, z__3, z__4;
+
+    /* Builtin functions */
+    void d_cnjg(doublecomplex *, doublecomplex *);
+
+    /* Local variables */
+    integer i__, j, k, kk, ix, iy, jx, jy, kx, ky, info;
+    doublecomplex temp1, temp2;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  ZHPMV  performs the matrix-vector operation */
+
+/*     y := alpha*A*x + beta*y, */
+
+/*  where alpha and beta are scalars, x and y are n element vectors and */
+/*  A is an n by n hermitian matrix, supplied in packed form. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the upper or lower */
+/*           triangular part of the matrix A is supplied in the packed */
+/*           array AP as follows: */
+
+/*              UPLO = 'U' or 'u'   The upper triangular part of A is */
+/*                                  supplied in AP. */
+
+/*              UPLO = 'L' or 'l'   The lower triangular part of A is */
+/*                                  supplied in AP. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  ALPHA  - COMPLEX*16      . */
+/*           On entry, ALPHA specifies the scalar alpha. */
+/*           Unchanged on exit. */
+
+/*  AP     - COMPLEX*16       array of DIMENSION at least */
+/*           ( ( n*( n + 1 ) )/2 ). */
+/*           Before entry with UPLO = 'U' or 'u', the array AP must */
+/*           contain the upper triangular part of the hermitian matrix */
+/*           packed sequentially, column by column, so that AP( 1 ) */
+/*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 ) */
+/*           and a( 2, 2 ) respectively, and so on. */
+/*           Before entry with UPLO = 'L' or 'l', the array AP must */
+/*           contain the lower triangular part of the hermitian matrix */
+/*           packed sequentially, column by column, so that AP( 1 ) */
+/*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 ) */
+/*           and a( 3, 1 ) respectively, and so on. */
+/*           Note that the imaginary parts of the diagonal elements need */
+/*           not be set and are assumed to be zero. */
+/*           Unchanged on exit. */
+
+/*  X      - COMPLEX*16       array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the n */
+/*           element vector x. */
+/*           Unchanged on exit. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  BETA   - COMPLEX*16      . */
+/*           On entry, BETA specifies the scalar beta. When BETA is */
+/*           supplied as zero then Y need not be set on input. */
+/*           Unchanged on exit. */
+
+/*  Y      - COMPLEX*16       array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCY ) ). */
+/*           Before entry, the incremented array Y must contain the n */
+/*           element vector y. On exit, Y is overwritten by the updated */
+/*           vector y. */
+
+/*  INCY   - INTEGER. */
+/*           On entry, INCY specifies the increment for the elements of */
+/*           Y. INCY must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    --y;
+    --x;
+    --ap;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (*n < 0) {
+	info = 2;
+    } else if (*incx == 0) {
+	info = 6;
+    } else if (*incy == 0) {
+	info = 9;
+    }
+    if (info != 0) {
+	xerbla_("ZHPMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0 || (alpha->r == 0. && alpha->i == 0. && (beta->r == 1. && 
+                                                         beta->i == 0.))) {
+	return 0;
+    }
+
+/*     Set up the start points in  X  and  Y. */
+
+    if (*incx > 0) {
+	kx = 1;
+    } else {
+	kx = 1 - (*n - 1) * *incx;
+    }
+    if (*incy > 0) {
+	ky = 1;
+    } else {
+	ky = 1 - (*n - 1) * *incy;
+    }
+
+/*     Start the operations. In this version the elements of the array AP */
+/*     are accessed sequentially with one pass through AP. */
+
+/*     First form  y := beta*y. */
+
+    if (beta->r != 1. || beta->i != 0.) {
+	if (*incy == 1) {
+	    if (beta->r == 0. && beta->i == 0.) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = i__;
+		    y[i__2].r = 0., y[i__2].i = 0.;
+/* L10: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = i__;
+		    i__3 = i__;
+		    z__1.r = beta->r * y[i__3].r - beta->i * y[i__3].i, 
+			    z__1.i = beta->r * y[i__3].i + beta->i * y[i__3]
+			    .r;
+		    y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+/* L20: */
+		}
+	    }
+	} else {
+	    iy = ky;
+	    if (beta->r == 0. && beta->i == 0.) {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = iy;
+		    y[i__2].r = 0., y[i__2].i = 0.;
+		    iy += *incy;
+/* L30: */
+		}
+	    } else {
+		i__1 = *n;
+		for (i__ = 1; i__ <= i__1; ++i__) {
+		    i__2 = iy;
+		    i__3 = iy;
+		    z__1.r = beta->r * y[i__3].r - beta->i * y[i__3].i, 
+			    z__1.i = beta->r * y[i__3].i + beta->i * y[i__3]
+			    .r;
+		    y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		    iy += *incy;
+/* L40: */
+		}
+	    }
+	}
+    }
+    if (alpha->r == 0. && alpha->i == 0.) {
+	return 0;
+    }
+    kk = 1;
+    if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+
+/*        Form  y  when AP contains the upper triangle. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = j;
+		z__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, z__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = z__1.r, temp1.i = z__1.i;
+		temp2.r = 0., temp2.i = 0.;
+		k = kk;
+		i__2 = j - 1;
+		for (i__ = 1; i__ <= i__2; ++i__) {
+		    i__3 = i__;
+		    i__4 = i__;
+		    i__5 = k;
+		    z__2.r = temp1.r * ap[i__5].r - temp1.i * ap[i__5].i, 
+			    z__2.i = temp1.r * ap[i__5].i + temp1.i * ap[i__5]
+			    .r;
+		    z__1.r = y[i__4].r + z__2.r, z__1.i = y[i__4].i + z__2.i;
+		    y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+		    d_cnjg(&z__3, &ap[k]);
+		    i__3 = i__;
+		    z__2.r = z__3.r * x[i__3].r - z__3.i * x[i__3].i, z__2.i =
+			     z__3.r * x[i__3].i + z__3.i * x[i__3].r;
+		    z__1.r = temp2.r + z__2.r, z__1.i = temp2.i + z__2.i;
+		    temp2.r = z__1.r, temp2.i = z__1.i;
+		    ++k;
+/* L50: */
+		}
+		i__2 = j;
+		i__3 = j;
+		i__4 = kk + j - 1;
+		d__1 = ap[i__4].r;
+		z__3.r = d__1 * temp1.r, z__3.i = d__1 * temp1.i;
+		z__2.r = y[i__3].r + z__3.r, z__2.i = y[i__3].i + z__3.i;
+		z__4.r = alpha->r * temp2.r - alpha->i * temp2.i, z__4.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		z__1.r = z__2.r + z__4.r, z__1.i = z__2.i + z__4.i;
+		y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		kk += j;
+/* L60: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = jx;
+		z__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, z__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = z__1.r, temp1.i = z__1.i;
+		temp2.r = 0., temp2.i = 0.;
+		ix = kx;
+		iy = ky;
+		i__2 = kk + j - 2;
+		for (k = kk; k <= i__2; ++k) {
+		    i__3 = iy;
+		    i__4 = iy;
+		    i__5 = k;
+		    z__2.r = temp1.r * ap[i__5].r - temp1.i * ap[i__5].i, 
+			    z__2.i = temp1.r * ap[i__5].i + temp1.i * ap[i__5]
+			    .r;
+		    z__1.r = y[i__4].r + z__2.r, z__1.i = y[i__4].i + z__2.i;
+		    y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+		    d_cnjg(&z__3, &ap[k]);
+		    i__3 = ix;
+		    z__2.r = z__3.r * x[i__3].r - z__3.i * x[i__3].i, z__2.i =
+			     z__3.r * x[i__3].i + z__3.i * x[i__3].r;
+		    z__1.r = temp2.r + z__2.r, z__1.i = temp2.i + z__2.i;
+		    temp2.r = z__1.r, temp2.i = z__1.i;
+		    ix += *incx;
+		    iy += *incy;
+/* L70: */
+		}
+		i__2 = jy;
+		i__3 = jy;
+		i__4 = kk + j - 1;
+		d__1 = ap[i__4].r;
+		z__3.r = d__1 * temp1.r, z__3.i = d__1 * temp1.i;
+		z__2.r = y[i__3].r + z__3.r, z__2.i = y[i__3].i + z__3.i;
+		z__4.r = alpha->r * temp2.r - alpha->i * temp2.i, z__4.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		z__1.r = z__2.r + z__4.r, z__1.i = z__2.i + z__4.i;
+		y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		jx += *incx;
+		jy += *incy;
+		kk += j;
+/* L80: */
+	    }
+	}
+    } else {
+
+/*        Form  y  when AP contains the lower triangle. */
+
+	if (*incx == 1 && *incy == 1) {
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = j;
+		z__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, z__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = z__1.r, temp1.i = z__1.i;
+		temp2.r = 0., temp2.i = 0.;
+		i__2 = j;
+		i__3 = j;
+		i__4 = kk;
+		d__1 = ap[i__4].r;
+		z__2.r = d__1 * temp1.r, z__2.i = d__1 * temp1.i;
+		z__1.r = y[i__3].r + z__2.r, z__1.i = y[i__3].i + z__2.i;
+		y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		k = kk + 1;
+		i__2 = *n;
+		for (i__ = j + 1; i__ <= i__2; ++i__) {
+		    i__3 = i__;
+		    i__4 = i__;
+		    i__5 = k;
+		    z__2.r = temp1.r * ap[i__5].r - temp1.i * ap[i__5].i, 
+			    z__2.i = temp1.r * ap[i__5].i + temp1.i * ap[i__5]
+			    .r;
+		    z__1.r = y[i__4].r + z__2.r, z__1.i = y[i__4].i + z__2.i;
+		    y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+		    d_cnjg(&z__3, &ap[k]);
+		    i__3 = i__;
+		    z__2.r = z__3.r * x[i__3].r - z__3.i * x[i__3].i, z__2.i =
+			     z__3.r * x[i__3].i + z__3.i * x[i__3].r;
+		    z__1.r = temp2.r + z__2.r, z__1.i = temp2.i + z__2.i;
+		    temp2.r = z__1.r, temp2.i = z__1.i;
+		    ++k;
+/* L90: */
+		}
+		i__2 = j;
+		i__3 = j;
+		z__2.r = alpha->r * temp2.r - alpha->i * temp2.i, z__2.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		z__1.r = y[i__3].r + z__2.r, z__1.i = y[i__3].i + z__2.i;
+		y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		kk += *n - j + 1;
+/* L100: */
+	    }
+	} else {
+	    jx = kx;
+	    jy = ky;
+	    i__1 = *n;
+	    for (j = 1; j <= i__1; ++j) {
+		i__2 = jx;
+		z__1.r = alpha->r * x[i__2].r - alpha->i * x[i__2].i, z__1.i =
+			 alpha->r * x[i__2].i + alpha->i * x[i__2].r;
+		temp1.r = z__1.r, temp1.i = z__1.i;
+		temp2.r = 0., temp2.i = 0.;
+		i__2 = jy;
+		i__3 = jy;
+		i__4 = kk;
+		d__1 = ap[i__4].r;
+		z__2.r = d__1 * temp1.r, z__2.i = d__1 * temp1.i;
+		z__1.r = y[i__3].r + z__2.r, z__1.i = y[i__3].i + z__2.i;
+		y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		ix = jx;
+		iy = jy;
+		i__2 = kk + *n - j;
+		for (k = kk + 1; k <= i__2; ++k) {
+		    ix += *incx;
+		    iy += *incy;
+		    i__3 = iy;
+		    i__4 = iy;
+		    i__5 = k;
+		    z__2.r = temp1.r * ap[i__5].r - temp1.i * ap[i__5].i, 
+			    z__2.i = temp1.r * ap[i__5].i + temp1.i * ap[i__5]
+			    .r;
+		    z__1.r = y[i__4].r + z__2.r, z__1.i = y[i__4].i + z__2.i;
+		    y[i__3].r = z__1.r, y[i__3].i = z__1.i;
+		    d_cnjg(&z__3, &ap[k]);
+		    i__3 = ix;
+		    z__2.r = z__3.r * x[i__3].r - z__3.i * x[i__3].i, z__2.i =
+			     z__3.r * x[i__3].i + z__3.i * x[i__3].r;
+		    z__1.r = temp2.r + z__2.r, z__1.i = temp2.i + z__2.i;
+		    temp2.r = z__1.r, temp2.i = z__1.i;
+/* L110: */
+		}
+		i__2 = jy;
+		i__3 = jy;
+		z__2.r = alpha->r * temp2.r - alpha->i * temp2.i, z__2.i = 
+			alpha->r * temp2.i + alpha->i * temp2.r;
+		z__1.r = y[i__3].r + z__2.r, z__1.i = y[i__3].i + z__2.i;
+		y[i__2].r = z__1.r, y[i__2].i = z__1.i;
+		jx += *incx;
+		jy += *incy;
+		kk += *n - j + 1;
+/* L120: */
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of ZHPMV . */
+
+} /* zhpmv_ */
+

ADDED   3rd_party/eigen/blas/f2c/ztbmv.c
Index: 3rd_party/eigen/blas/f2c/ztbmv.c
==================================================================
--- 3rd_party/eigen/blas/f2c/ztbmv.c
+++ 3rd_party/eigen/blas/f2c/ztbmv.c
@@ -0,0 +1,647 @@
+/* ztbmv.f -- translated by f2c (version 20100827).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "datatypes.h"
+
+/* Subroutine */ int ztbmv_(char *uplo, char *trans, char *diag, integer *n, 
+	integer *k, doublecomplex *a, integer *lda, doublecomplex *x, integer 
+	*incx, ftnlen uplo_len, ftnlen trans_len, ftnlen diag_len)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5;
+    doublecomplex z__1, z__2, z__3;
+
+    /* Builtin functions */
+    void d_cnjg(doublecomplex *, doublecomplex *);
+
+    /* Local variables */
+    integer i__, j, l, ix, jx, kx, info;
+    doublecomplex temp;
+    extern logical lsame_(char *, char *, ftnlen, ftnlen);
+    integer kplus1;
+    extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
+    logical noconj, nounit;
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  ZTBMV  performs one of the matrix-vector operations */
+
+/*     x := A*x,   or   x := A'*x,   or   x := conjg( A' )*x, */
+
+/*  where x is an n element vector and  A is an n by n unit, or non-unit, */
+/*  upper or lower triangular band matrix, with ( k + 1 ) diagonals. */
+
+/*  Arguments */
+/*  ========== */
+
+/*  UPLO   - CHARACTER*1. */
+/*           On entry, UPLO specifies whether the matrix is an upper or */
+/*           lower triangular matrix as follows: */
+
+/*              UPLO = 'U' or 'u'   A is an upper triangular matrix. */
+
+/*              UPLO = 'L' or 'l'   A is a lower triangular matrix. */
+
+/*           Unchanged on exit. */
+
+/*  TRANS  - CHARACTER*1. */
+/*           On entry, TRANS specifies the operation to be performed as */
+/*           follows: */
+
+/*              TRANS = 'N' or 'n'   x := A*x. */
+
+/*              TRANS = 'T' or 't'   x := A'*x. */
+
+/*              TRANS = 'C' or 'c'   x := conjg( A' )*x. */
+
+/*           Unchanged on exit. */
+
+/*  DIAG   - CHARACTER*1. */
+/*           On entry, DIAG specifies whether or not A is unit */
+/*           triangular as follows: */
+
+/*              DIAG = 'U' or 'u'   A is assumed to be unit triangular. */
+
+/*              DIAG = 'N' or 'n'   A is not assumed to be unit */
+/*                                  triangular. */
+
+/*           Unchanged on exit. */
+
+/*  N      - INTEGER. */
+/*           On entry, N specifies the order of the matrix A. */
+/*           N must be at least zero. */
+/*           Unchanged on exit. */
+
+/*  K      - INTEGER. */
+/*           On entry with UPLO = 'U' or 'u', K specifies the number of */
+/*           super-diagonals of the matrix A. */
+/*           On entry with UPLO = 'L' or 'l', K specifies the number of */
+/*           sub-diagonals of the matrix A. */
+/*           K must satisfy  0 .le. K. */
+/*           Unchanged on exit. */
+
+/*  A      - COMPLEX*16       array of DIMENSION ( LDA, n ). */
+/*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the upper triangular */
+/*           band part of the matrix of coefficients, supplied column by */
+/*           column, with the leading diagonal of the matrix in row */
+/*           ( k + 1 ) of the array, the first super-diagonal starting at */
+/*           position 2 in row k, and so on. The top left k by k triangle */
+/*           of the array A is not referenced. */
+/*           The following program segment will transfer an upper */
+/*           triangular band matrix from conventional full matrix storage */
+/*           to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = K + 1 - J */
+/*                    DO 10, I = MAX( 1, J - K ), J */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) */
+/*           by n part of the array A must contain the lower triangular */
+/*           band part of the matrix of coefficients, supplied column by */
+/*           column, with the leading diagonal of the matrix in row 1 of */
+/*           the array, the first sub-diagonal starting at position 1 in */
+/*           row 2, and so on. The bottom right k by k triangle of the */
+/*           array A is not referenced. */
+/*           The following program segment will transfer a lower */
+/*           triangular band matrix from conventional full matrix storage */
+/*           to band storage: */
+
+/*                 DO 20, J = 1, N */
+/*                    M = 1 - J */
+/*                    DO 10, I = J, MIN( N, J + K ) */
+/*                       A( M + I, J ) = matrix( I, J ) */
+/*              10    CONTINUE */
+/*              20 CONTINUE */
+
+/*           Note that when DIAG = 'U' or 'u' the elements of the array A */
+/*           corresponding to the diagonal elements of the matrix are not */
+/*           referenced, but are assumed to be unity. */
+/*           Unchanged on exit. */
+
+/*  LDA    - INTEGER. */
+/*           On entry, LDA specifies the first dimension of A as declared */
+/*           in the calling (sub) program. LDA must be at least */
+/*           ( k + 1 ). */
+/*           Unchanged on exit. */
+
+/*  X      - COMPLEX*16       array of dimension at least */
+/*           ( 1 + ( n - 1 )*abs( INCX ) ). */
+/*           Before entry, the incremented array X must contain the n */
+/*           element vector x. On exit, X is overwritten with the */
+/*           tranformed vector x. */
+
+/*  INCX   - INTEGER. */
+/*           On entry, INCX specifies the increment for the elements of */
+/*           X. INCX must not be zero. */
+/*           Unchanged on exit. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  Level 2 Blas routine. */
+
+/*  -- Written on 22-October-1986. */
+/*     Jack Dongarra, Argonne National Lab. */
+/*     Jeremy Du Croz, Nag Central Office. */
+/*     Sven Hammarling, Nag Central Office. */
+/*     Richard Hanson, Sandia National Labs. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    --x;
+
+    /* Function Body */
+    info = 0;
+    if (! lsame_(uplo, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(uplo, "L", (
+	    ftnlen)1, (ftnlen)1)) {
+	info = 1;
+    } else if (! lsame_(trans, "N", (ftnlen)1, (ftnlen)1) && ! lsame_(trans, 
+	    "T", (ftnlen)1, (ftnlen)1) && ! lsame_(trans, "C", (ftnlen)1, (
+	    ftnlen)1)) {
+	info = 2;
+    } else if (! lsame_(diag, "U", (ftnlen)1, (ftnlen)1) && ! lsame_(diag, 
+	    "N", (ftnlen)1, (ftnlen)1)) {
+	info = 3;
+    } else if (*n < 0) {
+	info = 4;
+    } else if (*k < 0) {
+	info = 5;
+    } else if (*lda < *k + 1) {
+	info = 7;
+    } else if (*incx == 0) {
+	info = 9;
+    }
+    if (info != 0) {
+	xerbla_("ZTBMV ", &info, (ftnlen)6);
+	return 0;
+    }
+
+/*     Quick return if possible. */
+
+    if (*n == 0) {
+	return 0;
+    }
+
+    noconj = lsame_(trans, "T", (ftnlen)1, (ftnlen)1);
+    nounit = lsame_(diag, "N", (ftnlen)1, (ftnlen)1);
+
+/*     Set up the start point in X if the increment is not unity. This */
+/*     will be  ( N - 1 )*INCX   too small for descending loops. */
+
+    if (*incx <= 0) {
+	kx = 1 - (*n - 1) * *incx;
+    } else if (*incx != 1) {
+	kx = 1;
+    }
+
+/*     Start the operations. In this version the elements of A are */
+/*     accessed sequentially with one pass through A. */
+
+    if (lsame_(trans, "N", (ftnlen)1, (ftnlen)1)) {
+
+/*         Form  x := A*x. */
+
+	if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+	    kplus1 = *k + 1;
+	    if (*incx == 1) {
+		i__1 = *n;
+		for (j = 1; j <= i__1; ++j) {
+		    i__2 = j;
+		    if (x[i__2].r != 0. || x[i__2].i != 0.) {
+			i__2 = j;
+			temp.r = x[i__2].r, temp.i = x[i__2].i;
+			l = kplus1 - j;
+/* Computing MAX */
+			i__2 = 1, i__3 = j - *k;
+			i__4 = j - 1;
+			for (i__ = max(i__2,i__3); i__ <= i__4; ++i__) {
+			    i__2 = i__;
+			    i__3 = i__;
+			    i__5 = l + i__ + j * a_dim1;
+			    z__2.r = temp.r * a[i__5].r - temp.i * a[i__5].i, 
+				    z__2.i = temp.r * a[i__5].i + temp.i * a[
+				    i__5].r;
+			    z__1.r = x[i__3].r + z__2.r, z__1.i = x[i__3].i + 
+				    z__2.i;
+			    x[i__2].r = z__1.r, x[i__2].i = z__1.i;
+/* L10: */
+			}
+			if (nounit) {
+			    i__4 = j;
+			    i__2 = j;
+			    i__3 = kplus1 + j * a_dim1;
+			    z__1.r = x[i__2].r * a[i__3].r - x[i__2].i * a[
+				    i__3].i, z__1.i = x[i__2].r * a[i__3].i + 
+				    x[i__2].i * a[i__3].r;
+			    x[i__4].r = z__1.r, x[i__4].i = z__1.i;
+			}
+		    }
+/* L20: */
+		}
+	    } else {
+		jx = kx;
+		i__1 = *n;
+		for (j = 1; j <= i__1; ++j) {
+		    i__4 = jx;
+		    if (x[i__4].r != 0. || x[i__4].i != 0.) {
+			i__4 = jx;
+			temp.r = x[i__4].r, temp.i = x[i__4].i;
+			ix = kx;
+			l = kplus1 - j;
+/* Computing MAX */
+			i__4 = 1, i__2 = j - *k;
+			i__3 = j - 1;
+			for (i__ = max(i__4,i__2); i__ <= i__3; ++i__) {
+			    i__4 = ix;
+			    i__2 = ix;
+			    i__5 = l + i__ + j * a_dim1;
+			    z__2.r = temp.r * a[i__5].r - temp.i * a[i__5].i, 
+				    z__2.i = temp.r * a[i__5].i + temp.i * a[
+				    i__5].r;
+			    z__1.r = x[i__2].r + z__2.r, z__1.i = x[i__2].i + 
+				    z__2.i;
+			    x[i__4].r = z__1.r, x[i__4].i = z__1.i;
+			    ix += *incx;
+/* L30: */
+			}
+			if (nounit) {
+			    i__3 = jx;
+			    i__4 = jx;
+			    i__2 = kplus1 + j * a_dim1;
+			    z__1.r = x[i__4].r * a[i__2].r - x[i__4].i * a[
+				    i__2].i, z__1.i = x[i__4].r * a[i__2].i + 
+				    x[i__4].i * a[i__2].r;
+			    x[i__3].r = z__1.r, x[i__3].i = z__1.i;
+			}
+		    }
+		    jx += *incx;
+		    if (j > *k) {
+			kx += *incx;
+		    }
+/* L40: */
+		}
+	    }
+	} else {
+	    if (*incx == 1) {
+		for (j = *n; j >= 1; --j) {
+		    i__1 = j;
+		    if (x[i__1].r != 0. || x[i__1].i != 0.) {
+			i__1 = j;
+			temp.r = x[i__1].r, temp.i = x[i__1].i;
+			l = 1 - j;
+/* Computing MIN */
+			i__1 = *n, i__3 = j + *k;
+			i__4 = j + 1;
+			for (i__ = min(i__1,i__3); i__ >= i__4; --i__) {
+			    i__1 = i__;
+			    i__3 = i__;
+			    i__2 = l + i__ + j * a_dim1;
+			    z__2.r = temp.r * a[i__2].r - temp.i * a[i__2].i, 
+				    z__2.i = temp.r * a[i__2].i + temp.i * a[
+				    i__2].r;
+			    z__1.r = x[i__3].r + z__2.r, z__1.i = x[i__3].i + 
+				    z__2.i;
+			    x[i__1].r = z__1.r, x[i__1].i = z__1.i;
+/* L50: */
+			}
+			if (nounit) {
+			    i__4 = j;
+			    i__1 = j;
+			    i__3 = j * a_dim1 + 1;
+			    z__1.r = x[i__1].r * a[i__3].r - x[i__1].i * a[
+				    i__3].i, z__1.i = x[i__1].r * a[i__3].i + 
+				    x[i__1].i * a[i__3].r;
+			    x[i__4].r = z__1.r, x[i__4].i = z__1.i;
+			}
+		    }
+/* L60: */
+		}
+	    } else {
+		kx += (*n - 1) * *incx;
+		jx = kx;
+		for (j = *n; j >= 1; --j) {
+		    i__4 = jx;
+		    if (x[i__4].r != 0. || x[i__4].i != 0.) {
+			i__4 = jx;
+			temp.r = x[i__4].r, temp.i = x[i__4].i;
+			ix = kx;
+			l = 1 - j;
+/* Computing MIN */
+			i__4 = *n, i__1 = j + *k;
+			i__3 = j + 1;
+			for (i__ = min(i__4,i__1); i__ >= i__3; --i__) {
+			    i__4 = ix;
+			    i__1 = ix;
+			    i__2 = l + i__ + j * a_dim1;
+			    z__2.r = temp.r * a[i__2].r - temp.i * a[i__2].i, 
+				    z__2.i = temp.r * a[i__2].i + temp.i * a[
+				    i__2].r;
+			    z__1.r = x[i__1].r + z__2.r, z__1.i = x[i__1].i + 
+				    z__2.i;
+			    x[i__4].r = z__1.r, x[i__4].i = z__1.i;
+			    ix -= *incx;
+/* L70: */
+			}
+			if (nounit) {
+			    i__3 = jx;
+			    i__4 = jx;
+			    i__1 = j * a_dim1 + 1;
+			    z__1.r = x[i__4].r * a[i__1].r - x[i__4].i * a[
+				    i__1].i, z__1.i = x[i__4].r * a[i__1].i + 
+				    x[i__4].i * a[i__1].r;
+			    x[i__3].r = z__1.r, x[i__3].i = z__1.i;
+			}
+		    }
+		    jx -= *incx;
+		    if (*n - j >= *k) {
+			kx -= *incx;
+		    }
+/* L80: */
+		}
+	    }
+	}
+    } else {
+
+/*        Form  x := A'*x  or  x := conjg( A' )*x. */
+
+	if (lsame_(uplo, "U", (ftnlen)1, (ftnlen)1)) {
+	    kplus1 = *k + 1;
+	    if (*incx == 1) {
+		for (j = *n; j >= 1; --j) {
+		    i__3 = j;
+		    temp.r = x[i__3].r, temp.i = x[i__3].i;
+		    l = kplus1 - j;
+		    if (noconj) {
+			if (nounit) {
+			    i__3 = kplus1 + j * a_dim1;
+			    z__1.r = temp.r * a[i__3].r - temp.i * a[i__3].i, 
+				    z__1.i = temp.r * a[i__3].i + temp.i * a[
+				    i__3].r;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			}
+/* Computing MAX */
+			i__4 = 1, i__1 = j - *k;
+			i__3 = max(i__4,i__1);
+			for (i__ = j - 1; i__ >= i__3; --i__) {
+			    i__4 = l + i__ + j * a_dim1;
+			    i__1 = i__;
+			    z__2.r = a[i__4].r * x[i__1].r - a[i__4].i * x[
+				    i__1].i, z__2.i = a[i__4].r * x[i__1].i + 
+				    a[i__4].i * x[i__1].r;
+			    z__1.r = temp.r + z__2.r, z__1.i = temp.i + 
+				    z__2.i;
+			    temp.r = z__1.r, temp.i = z__1.i;
+/* L90: */
+			}
+		    } else {
+			if (nounit) {
+			    d_cnjg(&z__2, &a[kplus1 + j * a_dim1]);
+			    z__1.r = temp.r * z__2.r - temp.i * z__2.i, 
+				    z__1.i = temp.r * z__2.i + temp.i * 
+				    z__2.r;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			}
+/* Computing MAX */
+			i__4 = 1, i__1 = j - *k;
+			i__3 = max(i__4,i__1);
+			for (i__ = j - 1; i__ >= i__3; --i__) {
+			    d_cnjg(&z__3, &a[l + i__ + j * a_dim1]);
+			    i__4 = i__;
+			    z__2.r = z__3.r * x[i__4].r - z__3.i * x[i__4].i, 
+				    z__2.i = z__3.r * x[i__4].i + z__3.i * x[
+				    i__4].r;
+			    z__1.r = temp.r + z__2.r, z__1.i = temp.i + 
+				    z__2.i;
+			    temp.r = z__1.r, temp.i = z__1.i;
+/* L100: */
+			}
+		    }
+		    i__3 = j;
+		    x[i__3].r = temp.r, x[i__3].i = temp.i;
+/* L110: */
+		}
+	    } else {
+		kx += (*n - 1) * *incx;
+		jx = kx;
+		for (j = *n; j >= 1; --j) {
+		    i__3 = jx;
+		    temp.r = x[i__3].r, temp.i = x[i__3].i;
+		    kx -= *incx;
+		    ix = kx;
+		    l = kplus1 - j;
+		    if (noconj) {
+			if (nounit) {
+			    i__3 = kplus1 + j * a_dim1;
+			    z__1.r = temp.r * a[i__3].r - temp.i * a[i__3].i, 
+				    z__1.i = temp.r * a[i__3].i + temp.i * a[
+				    i__3].r;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			}
+/* Computing MAX */
+			i__4 = 1, i__1 = j - *k;
+			i__3 = max(i__4,i__1);
+			for (i__ = j - 1; i__ >= i__3; --i__) {
+			    i__4 = l + i__ + j * a_dim1;
+			    i__1 = ix;
+			    z__2.r = a[i__4].r * x[i__1].r - a[i__4].i * x[
+				    i__1].i, z__2.i = a[i__4].r * x[i__1].i + 
+				    a[i__4].i * x[i__1].r;
+			    z__1.r = temp.r + z__2.r, z__1.i = temp.i + 
+				    z__2.i;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			    ix -= *incx;
+/* L120: */
+			}
+		    } else {
+			if (nounit) {
+			    d_cnjg(&z__2, &a[kplus1 + j * a_dim1]);
+			    z__1.r = temp.r * z__2.r - temp.i * z__2.i, 
+				    z__1.i = temp.r * z__2.i + temp.i * 
+				    z__2.r;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			}
+/* Computing MAX */
+			i__4 = 1, i__1 = j - *k;
+			i__3 = max(i__4,i__1);
+			for (i__ = j - 1; i__ >= i__3; --i__) {
+			    d_cnjg(&z__3, &a[l + i__ + j * a_dim1]);
+			    i__4 = ix;
+			    z__2.r = z__3.r * x[i__4].r - z__3.i * x[i__4].i, 
+				    z__2.i = z__3.r * x[i__4].i + z__3.i * x[
+				    i__4].r;
+			    z__1.r = temp.r + z__2.r, z__1.i = temp.i + 
+				    z__2.i;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			    ix -= *incx;
+/* L130: */
+			}
+		    }
+		    i__3 = jx;
+		    x[i__3].r = temp.r, x[i__3].i = temp.i;
+		    jx -= *incx;
+/* L140: */
+		}
+	    }
+	} else {
+	    if (*incx == 1) {
+		i__3 = *n;
+		for (j = 1; j <= i__3; ++j) {
+		    i__4 = j;
+		    temp.r = x[i__4].r, temp.i = x[i__4].i;
+		    l = 1 - j;
+		    if (noconj) {
+			if (nounit) {
+			    i__4 = j * a_dim1 + 1;
+			    z__1.r = temp.r * a[i__4].r - temp.i * a[i__4].i, 
+				    z__1.i = temp.r * a[i__4].i + temp.i * a[
+				    i__4].r;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			}
+/* Computing MIN */
+			i__1 = *n, i__2 = j + *k;
+			i__4 = min(i__1,i__2);
+			for (i__ = j + 1; i__ <= i__4; ++i__) {
+			    i__1 = l + i__ + j * a_dim1;
+			    i__2 = i__;
+			    z__2.r = a[i__1].r * x[i__2].r - a[i__1].i * x[
+				    i__2].i, z__2.i = a[i__1].r * x[i__2].i + 
+				    a[i__1].i * x[i__2].r;
+			    z__1.r = temp.r + z__2.r, z__1.i = temp.i + 
+				    z__2.i;
+			    temp.r = z__1.r, temp.i = z__1.i;
+/* L150: */
+			}
+		    } else {
+			if (nounit) {
+			    d_cnjg(&z__2, &a[j * a_dim1 + 1]);
+			    z__1.r = temp.r * z__2.r - temp.i * z__2.i, 
+				    z__1.i = temp.r * z__2.i + temp.i * 
+				    z__2.r;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			}
+/* Computing MIN */
+			i__1 = *n, i__2 = j + *k;
+			i__4 = min(i__1,i__2);
+			for (i__ = j + 1; i__ <= i__4; ++i__) {
+			    d_cnjg(&z__3, &a[l + i__ + j * a_dim1]);
+			    i__1 = i__;
+			    z__2.r = z__3.r * x[i__1].r - z__3.i * x[i__1].i, 
+				    z__2.i = z__3.r * x[i__1].i + z__3.i * x[
+				    i__1].r;
+			    z__1.r = temp.r + z__2.r, z__1.i = temp.i + 
+				    z__2.i;
+			    temp.r = z__1.r, temp.i = z__1.i;
+/* L160: */
+			}
+		    }
+		    i__4 = j;
+		    x[i__4].r = temp.r, x[i__4].i = temp.i;
+/* L170: */
+		}
+	    } else {
+		jx = kx;
+		i__3 = *n;
+		for (j = 1; j <= i__3; ++j) {
+		    i__4 = jx;
+		    temp.r = x[i__4].r, temp.i = x[i__4].i;
+		    kx += *incx;
+		    ix = kx;
+		    l = 1 - j;
+		    if (noconj) {
+			if (nounit) {
+			    i__4 = j * a_dim1 + 1;
+			    z__1.r = temp.r * a[i__4].r - temp.i * a[i__4].i, 
+				    z__1.i = temp.r * a[i__4].i + temp.i * a[
+				    i__4].r;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			}
+/* Computing MIN */
+			i__1 = *n, i__2 = j + *k;
+			i__4 = min(i__1,i__2);
+			for (i__ = j + 1; i__ <= i__4; ++i__) {
+			    i__1 = l + i__ + j * a_dim1;
+			    i__2 = ix;
+			    z__2.r = a[i__1].r * x[i__2].r - a[i__1].i * x[
+				    i__2].i, z__2.i = a[i__1].r * x[i__2].i + 
+				    a[i__1].i * x[i__2].r;
+			    z__1.r = temp.r + z__2.r, z__1.i = temp.i + 
+				    z__2.i;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			    ix += *incx;
+/* L180: */
+			}
+		    } else {
+			if (nounit) {
+			    d_cnjg(&z__2, &a[j * a_dim1 + 1]);
+			    z__1.r = temp.r * z__2.r - temp.i * z__2.i, 
+				    z__1.i = temp.r * z__2.i + temp.i * 
+				    z__2.r;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			}
+/* Computing MIN */
+			i__1 = *n, i__2 = j + *k;
+			i__4 = min(i__1,i__2);
+			for (i__ = j + 1; i__ <= i__4; ++i__) {
+			    d_cnjg(&z__3, &a[l + i__ + j * a_dim1]);
+			    i__1 = ix;
+			    z__2.r = z__3.r * x[i__1].r - z__3.i * x[i__1].i, 
+				    z__2.i = z__3.r * x[i__1].i + z__3.i * x[
+				    i__1].r;
+			    z__1.r = temp.r + z__2.r, z__1.i = temp.i + 
+				    z__2.i;
+			    temp.r = z__1.r, temp.i = z__1.i;
+			    ix += *incx;
+/* L190: */
+			}
+		    }
+		    i__4 = jx;
+		    x[i__4].r = temp.r, x[i__4].i = temp.i;
+		    jx += *incx;
+/* L200: */
+		}
+	    }
+	}
+    }
+
+    return 0;
+
+/*     End of ZTBMV . */
+
+} /* ztbmv_ */
+

ADDED   3rd_party/eigen/blas/fortran/complexdots.f
Index: 3rd_party/eigen/blas/fortran/complexdots.f
==================================================================
--- 3rd_party/eigen/blas/fortran/complexdots.f
+++ 3rd_party/eigen/blas/fortran/complexdots.f
@@ -0,0 +1,43 @@
+      COMPLEX FUNCTION CDOTC(N,CX,INCX,CY,INCY)
+      INTEGER INCX,INCY,N
+      COMPLEX CX(*),CY(*)
+      COMPLEX RES
+      EXTERNAL CDOTCW
+      
+      CALL CDOTCW(N,CX,INCX,CY,INCY,RES)
+      CDOTC = RES
+      RETURN
+      END
+      
+      COMPLEX FUNCTION CDOTU(N,CX,INCX,CY,INCY)
+      INTEGER INCX,INCY,N
+      COMPLEX CX(*),CY(*)
+      COMPLEX RES
+      EXTERNAL CDOTUW
+      
+      CALL CDOTUW(N,CX,INCX,CY,INCY,RES)
+      CDOTU = RES
+      RETURN
+      END
+      
+      DOUBLE COMPLEX FUNCTION ZDOTC(N,CX,INCX,CY,INCY)
+      INTEGER INCX,INCY,N
+      DOUBLE COMPLEX CX(*),CY(*)
+      DOUBLE COMPLEX RES
+      EXTERNAL ZDOTCW
+      
+      CALL ZDOTCW(N,CX,INCX,CY,INCY,RES)
+      ZDOTC = RES
+      RETURN
+      END
+      
+      DOUBLE COMPLEX FUNCTION ZDOTU(N,CX,INCX,CY,INCY)
+      INTEGER INCX,INCY,N
+      DOUBLE COMPLEX CX(*),CY(*)
+      DOUBLE COMPLEX RES
+      EXTERNAL ZDOTUW
+      
+      CALL ZDOTUW(N,CX,INCX,CY,INCY,RES)
+      ZDOTU = RES
+      RETURN
+      END

Index: 3rd_party/eigen/blas/level1_cplx_impl.h
==================================================================
--- 3rd_party/eigen/blas/level1_cplx_impl.h
+++ 3rd_party/eigen/blas/level1_cplx_impl.h
@@ -30,49 +30,56 @@
 //   std::cerr << "__asum " << *n << " " << *incx << "\n";
   Complex* x = reinterpret_cast<Complex*>(px);
 
   if(*n<=0) return 0;
 
-  if(*incx==1)  return vector(x,*n).unaryExpr<scalar_norm1_op>().sum();
-  else          return vector(x,*n,std::abs(*incx)).unaryExpr<scalar_norm1_op>().sum();
+  if(*incx==1)  return make_vector(x,*n).unaryExpr<scalar_norm1_op>().sum();
+  else          return make_vector(x,*n,std::abs(*incx)).unaryExpr<scalar_norm1_op>().sum();
 }
 
 // computes a dot product of a conjugated vector with another vector.
 int EIGEN_BLAS_FUNC(dotcw)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar* pres)
 {
 //   std::cerr << "_dotc " << *n << " " << *incx << " " << *incy << "\n";
+  Scalar* res = reinterpret_cast<Scalar*>(pres);
 
-  if(*n<=0) return 0;
+  if(*n<=0)
+  {
+    *res = Scalar(0);
+    return 0;
+  }
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
-  Scalar* res = reinterpret_cast<Scalar*>(pres);
 
-  if(*incx==1 && *incy==1)    *res = (vector(x,*n).dot(vector(y,*n)));
-  else if(*incx>0 && *incy>0) *res = (vector(x,*n,*incx).dot(vector(y,*n,*incy)));
-  else if(*incx<0 && *incy>0) *res = (vector(x,*n,-*incx).reverse().dot(vector(y,*n,*incy)));
-  else if(*incx>0 && *incy<0) *res = (vector(x,*n,*incx).dot(vector(y,*n,-*incy).reverse()));
-  else if(*incx<0 && *incy<0) *res = (vector(x,*n,-*incx).reverse().dot(vector(y,*n,-*incy).reverse()));
+  if(*incx==1 && *incy==1)    *res = (make_vector(x,*n).dot(make_vector(y,*n)));
+  else if(*incx>0 && *incy>0) *res = (make_vector(x,*n,*incx).dot(make_vector(y,*n,*incy)));
+  else if(*incx<0 && *incy>0) *res = (make_vector(x,*n,-*incx).reverse().dot(make_vector(y,*n,*incy)));
+  else if(*incx>0 && *incy<0) *res = (make_vector(x,*n,*incx).dot(make_vector(y,*n,-*incy).reverse()));
+  else if(*incx<0 && *incy<0) *res = (make_vector(x,*n,-*incx).reverse().dot(make_vector(y,*n,-*incy).reverse()));
   return 0;
 }
 
 // computes a vector-vector dot product without complex conjugation.
 int EIGEN_BLAS_FUNC(dotuw)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar* pres)
 {
-//   std::cerr << "_dotu " << *n << " " << *incx << " " << *incy << "\n";
+  Scalar* res = reinterpret_cast<Scalar*>(pres);
 
-  if(*n<=0) return 0;
+  if(*n<=0)
+  {
+    *res = Scalar(0);
+    return 0;
+  }
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
-  Scalar* res = reinterpret_cast<Scalar*>(pres);
 
-  if(*incx==1 && *incy==1)    *res = (vector(x,*n).cwiseProduct(vector(y,*n))).sum();
-  else if(*incx>0 && *incy>0) *res = (vector(x,*n,*incx).cwiseProduct(vector(y,*n,*incy))).sum();
-  else if(*incx<0 && *incy>0) *res = (vector(x,*n,-*incx).reverse().cwiseProduct(vector(y,*n,*incy))).sum();
-  else if(*incx>0 && *incy<0) *res = (vector(x,*n,*incx).cwiseProduct(vector(y,*n,-*incy).reverse())).sum();
-  else if(*incx<0 && *incy<0) *res = (vector(x,*n,-*incx).reverse().cwiseProduct(vector(y,*n,-*incy).reverse())).sum();
+  if(*incx==1 && *incy==1)    *res = (make_vector(x,*n).cwiseProduct(make_vector(y,*n))).sum();
+  else if(*incx>0 && *incy>0) *res = (make_vector(x,*n,*incx).cwiseProduct(make_vector(y,*n,*incy))).sum();
+  else if(*incx<0 && *incy>0) *res = (make_vector(x,*n,-*incx).reverse().cwiseProduct(make_vector(y,*n,*incy))).sum();
+  else if(*incx>0 && *incy<0) *res = (make_vector(x,*n,*incx).cwiseProduct(make_vector(y,*n,-*incy).reverse())).sum();
+  else if(*incx<0 && *incy<0) *res = (make_vector(x,*n,-*incx).reverse().cwiseProduct(make_vector(y,*n,-*incy).reverse())).sum();
   return 0;
 }
 
 RealScalar EIGEN_CAT(EIGEN_CAT(REAL_SCALAR_SUFFIX,SCALAR_SUFFIX),nrm2_)(int *n, RealScalar *px, int *incx)
 {
@@ -80,13 +87,13 @@
   if(*n<=0) return 0;
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
 
   if(*incx==1)
-    return vector(x,*n).stableNorm();
+    return make_vector(x,*n).stableNorm();
 
-  return vector(x,*n,*incx).stableNorm();
+  return make_vector(x,*n,*incx).stableNorm();
 }
 
 int EIGEN_CAT(EIGEN_CAT(SCALAR_SUFFIX,REAL_SCALAR_SUFFIX),rot_)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pc, RealScalar *ps)
 {
   if(*n<=0) return 0;
@@ -94,12 +101,12 @@
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
   RealScalar c = *pc;
   RealScalar s = *ps;
 
-  StridedVectorType vx(vector(x,*n,std::abs(*incx)));
-  StridedVectorType vy(vector(y,*n,std::abs(*incy)));
+  StridedVectorType vx(make_vector(x,*n,std::abs(*incx)));
+  StridedVectorType vy(make_vector(y,*n,std::abs(*incy)));
 
   Reverse<StridedVectorType> rvx(vx);
   Reverse<StridedVectorType> rvy(vy);
 
   // TODO implement mixed real-scalar rotations
@@ -117,11 +124,10 @@
   Scalar* x = reinterpret_cast<Scalar*>(px);
   RealScalar alpha = *palpha;
 
 //   std::cerr << "__scal " << *n << " " << alpha << " " << *incx << "\n";
 
-  if(*incx==1)  vector(x,*n) *= alpha;
-  else          vector(x,*n,std::abs(*incx)) *= alpha;
+  if(*incx==1)  make_vector(x,*n) *= alpha;
+  else          make_vector(x,*n,std::abs(*incx)) *= alpha;
 
   return 0;
 }
-

Index: 3rd_party/eigen/blas/level1_impl.h
==================================================================
--- 3rd_party/eigen/blas/level1_impl.h
+++ 3rd_party/eigen/blas/level1_impl.h
@@ -7,23 +7,23 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "common.h"
 
-int EIGEN_BLAS_FUNC(axpy)(int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *py, int *incy)
+int EIGEN_BLAS_FUNC(axpy)(const int *n, const RealScalar *palpha, const RealScalar *px, const int *incx, RealScalar *py, const int *incy)
 {
-  Scalar* x = reinterpret_cast<Scalar*>(px);
+  const Scalar* x = reinterpret_cast<const Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
-  Scalar alpha  = *reinterpret_cast<Scalar*>(palpha);
+  Scalar alpha  = *reinterpret_cast<const Scalar*>(palpha);
 
   if(*n<=0) return 0;
 
-  if(*incx==1 && *incy==1)    vector(y,*n) += alpha * vector(x,*n);
-  else if(*incx>0 && *incy>0) vector(y,*n,*incy) += alpha * vector(x,*n,*incx);
-  else if(*incx>0 && *incy<0) vector(y,*n,-*incy).reverse() += alpha * vector(x,*n,*incx);
-  else if(*incx<0 && *incy>0) vector(y,*n,*incy) += alpha * vector(x,*n,-*incx).reverse();
-  else if(*incx<0 && *incy<0) vector(y,*n,-*incy).reverse() += alpha * vector(x,*n,-*incx).reverse();
+  if(*incx==1 && *incy==1)    make_vector(y,*n) += alpha * make_vector(x,*n);
+  else if(*incx>0 && *incy>0) make_vector(y,*n,*incy) += alpha * make_vector(x,*n,*incx);
+  else if(*incx>0 && *incy<0) make_vector(y,*n,-*incy).reverse() += alpha * make_vector(x,*n,*incx);
+  else if(*incx<0 && *incy>0) make_vector(y,*n,*incy) += alpha * make_vector(x,*n,-*incx).reverse();
+  else if(*incx<0 && *incy<0) make_vector(y,*n,-*incy).reverse() += alpha * make_vector(x,*n,-*incx).reverse();
 
   return 0;
 }
 
 int EIGEN_BLAS_FUNC(copy)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy)
@@ -33,11 +33,11 @@
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
 
   // be carefull, *incx==0 is allowed !!
   if(*incx==1 && *incy==1)
-    vector(y,*n) = vector(x,*n);
+    make_vector(y,*n) = make_vector(x,*n);
   else
   {
     if(*incx<0) x = x - (*n-1)*(*incx);
     if(*incy<0) y = y - (*n-1)*(*incy);
     for(int i=0;i<*n;++i)
@@ -55,31 +55,31 @@
 {
   if(*n<=0) return 0;
   Scalar* x = reinterpret_cast<Scalar*>(px);
 
   DenseIndex ret;
-  if(*incx==1)  vector(x,*n).cwiseAbs().maxCoeff(&ret);
-  else          vector(x,*n,std::abs(*incx)).cwiseAbs().maxCoeff(&ret);
-  return ret+1;
+  if(*incx==1)  make_vector(x,*n).cwiseAbs().maxCoeff(&ret);
+  else          make_vector(x,*n,std::abs(*incx)).cwiseAbs().maxCoeff(&ret);
+  return int(ret)+1;
 }
 
 int EIGEN_CAT(EIGEN_CAT(i,SCALAR_SUFFIX),amin_)(int *n, RealScalar *px, int *incx)
 {
   if(*n<=0) return 0;
   Scalar* x = reinterpret_cast<Scalar*>(px);
-  
+
   DenseIndex ret;
-  if(*incx==1)  vector(x,*n).cwiseAbs().minCoeff(&ret);
-  else          vector(x,*n,std::abs(*incx)).cwiseAbs().minCoeff(&ret);
-  return ret+1;
+  if(*incx==1)  make_vector(x,*n).cwiseAbs().minCoeff(&ret);
+  else          make_vector(x,*n,std::abs(*incx)).cwiseAbs().minCoeff(&ret);
+  return int(ret)+1;
 }
 
 int EIGEN_BLAS_FUNC(rotg)(RealScalar *pa, RealScalar *pb, RealScalar *pc, RealScalar *ps)
 {
   using std::sqrt;
   using std::abs;
-  
+
   Scalar& a = *reinterpret_cast<Scalar*>(pa);
   Scalar& b = *reinterpret_cast<Scalar*>(pb);
   RealScalar* c = pc;
   Scalar* s = reinterpret_cast<Scalar*>(ps);
 
@@ -141,12 +141,12 @@
   if(*n<=0) return 0;
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
 
-  if(*incx==1)  vector(x,*n) *= alpha;
-  else          vector(x,*n,std::abs(*incx)) *= alpha;
+  if(*incx==1)  make_vector(x,*n) *= alpha;
+  else          make_vector(x,*n,std::abs(*incx)) *= alpha;
 
   return 0;
 }
 
 int EIGEN_BLAS_FUNC(swap)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy)
@@ -154,14 +154,13 @@
   if(*n<=0) return 0;
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
 
-  if(*incx==1 && *incy==1)    vector(y,*n).swap(vector(x,*n));
-  else if(*incx>0 && *incy>0) vector(y,*n,*incy).swap(vector(x,*n,*incx));
-  else if(*incx>0 && *incy<0) vector(y,*n,-*incy).reverse().swap(vector(x,*n,*incx));
-  else if(*incx<0 && *incy>0) vector(y,*n,*incy).swap(vector(x,*n,-*incx).reverse());
-  else if(*incx<0 && *incy<0) vector(y,*n,-*incy).reverse().swap(vector(x,*n,-*incx).reverse());
+  if(*incx==1 && *incy==1)    make_vector(y,*n).swap(make_vector(x,*n));
+  else if(*incx>0 && *incy>0) make_vector(y,*n,*incy).swap(make_vector(x,*n,*incx));
+  else if(*incx>0 && *incy<0) make_vector(y,*n,-*incy).reverse().swap(make_vector(x,*n,*incx));
+  else if(*incx<0 && *incy>0) make_vector(y,*n,*incy).swap(make_vector(x,*n,-*incx).reverse());
+  else if(*incx<0 && *incy<0) make_vector(y,*n,-*incy).reverse().swap(make_vector(x,*n,-*incx).reverse());
 
   return 1;
 }
-

Index: 3rd_party/eigen/blas/level1_real_impl.h
==================================================================
--- 3rd_party/eigen/blas/level1_real_impl.h
+++ 3rd_party/eigen/blas/level1_real_impl.h
@@ -17,12 +17,12 @@
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
 
   if(*n<=0) return 0;
 
-  if(*incx==1)  return vector(x,*n).cwiseAbs().sum();
-  else          return vector(x,*n,std::abs(*incx)).cwiseAbs().sum();
+  if(*incx==1)  return make_vector(x,*n).cwiseAbs().sum();
+  else          return make_vector(x,*n,std::abs(*incx)).cwiseAbs().sum();
 }
 
 // computes a vector-vector dot product.
 Scalar EIGEN_BLAS_FUNC(dot)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy)
 {
@@ -31,15 +31,15 @@
   if(*n<=0) return 0;
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
 
-  if(*incx==1 && *incy==1)    return (vector(x,*n).cwiseProduct(vector(y,*n))).sum();
-  else if(*incx>0 && *incy>0) return (vector(x,*n,*incx).cwiseProduct(vector(y,*n,*incy))).sum();
-  else if(*incx<0 && *incy>0) return (vector(x,*n,-*incx).reverse().cwiseProduct(vector(y,*n,*incy))).sum();
-  else if(*incx>0 && *incy<0) return (vector(x,*n,*incx).cwiseProduct(vector(y,*n,-*incy).reverse())).sum();
-  else if(*incx<0 && *incy<0) return (vector(x,*n,-*incx).reverse().cwiseProduct(vector(y,*n,-*incy).reverse())).sum();
+  if(*incx==1 && *incy==1)    return (make_vector(x,*n).cwiseProduct(make_vector(y,*n))).sum();
+  else if(*incx>0 && *incy>0) return (make_vector(x,*n,*incx).cwiseProduct(make_vector(y,*n,*incy))).sum();
+  else if(*incx<0 && *incy>0) return (make_vector(x,*n,-*incx).reverse().cwiseProduct(make_vector(y,*n,*incy))).sum();
+  else if(*incx>0 && *incy<0) return (make_vector(x,*n,*incx).cwiseProduct(make_vector(y,*n,-*incy).reverse())).sum();
+  else if(*incx<0 && *incy<0) return (make_vector(x,*n,-*incx).reverse().cwiseProduct(make_vector(y,*n,-*incy).reverse())).sum();
   else return 0;
 }
 
 // computes the Euclidean norm of a vector.
 // FIXME
@@ -48,12 +48,12 @@
 //   std::cerr << "_nrm2 " << *n << " " << *incx << "\n";
   if(*n<=0) return 0;
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
 
-  if(*incx==1)  return vector(x,*n).stableNorm();
-  else          return vector(x,*n,std::abs(*incx)).stableNorm();
+  if(*incx==1)  return make_vector(x,*n).stableNorm();
+  else          return make_vector(x,*n,std::abs(*incx)).stableNorm();
 }
 
 int EIGEN_BLAS_FUNC(rot)(int *n, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pc, RealScalar *ps)
 {
 //   std::cerr << "_rot " << *n << " " << *incx << " " << *incy << "\n";
@@ -62,12 +62,12 @@
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
   Scalar c = *reinterpret_cast<Scalar*>(pc);
   Scalar s = *reinterpret_cast<Scalar*>(ps);
 
-  StridedVectorType vx(vector(x,*n,std::abs(*incx)));
-  StridedVectorType vy(vector(y,*n,std::abs(*incy)));
+  StridedVectorType vx(make_vector(x,*n,std::abs(*incx)));
+  StridedVectorType vy(make_vector(y,*n,std::abs(*incy)));
 
   Reverse<StridedVectorType> rvx(vx);
   Reverse<StridedVectorType> rvy(vy);
 
        if(*incx<0 && *incy>0) internal::apply_rotation_in_the_plane(rvx, vy, JacobiRotation<Scalar>(c,s));

Index: 3rd_party/eigen/blas/level2_cplx_impl.h
==================================================================
--- 3rd_party/eigen/blas/level2_cplx_impl.h
+++ 3rd_party/eigen/blas/level2_cplx_impl.h
@@ -14,32 +14,26 @@
   *     y := alpha*A*x + beta*y,
   *
   *  where alpha and beta are scalars, x and y are n element vectors and
   *  A is an n by n hermitian matrix.
   */
-int EIGEN_BLAS_FUNC(hemv)(char *uplo, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *px, int *incx, RealScalar *pbeta, RealScalar *py, int *incy)
-{
-  typedef void (*functype)(int, const Scalar*, int, const Scalar*, int, Scalar*, Scalar);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Upper,false,false>::run);
-    func[LO] = (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Lower,false,false>::run);
-
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* x = reinterpret_cast<Scalar*>(px);
+int EIGEN_BLAS_FUNC(hemv)(const char *uplo, const int *n, const RealScalar *palpha, const RealScalar *pa, const int *lda,
+                          const RealScalar *px, const int *incx, const RealScalar *pbeta, RealScalar *py, const int *incy)
+{
+  typedef void (*functype)(int, const Scalar*, int, const Scalar*, Scalar*, Scalar);
+  static const functype func[2] = {
+    // array index: UP
+    (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Upper,false,false>::run),
+    // array index: LO
+    (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Lower,false,false>::run),
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* x = reinterpret_cast<const Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
-  Scalar alpha  = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta   = *reinterpret_cast<Scalar*>(pbeta);
+  Scalar alpha  = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta   = *reinterpret_cast<const Scalar*>(pbeta);
 
   // check arguments
   int info = 0;
   if(UPLO(*uplo)==INVALID)        info = 1;
   else if(*n<0)                   info = 2;
@@ -50,26 +44,26 @@
     return xerbla_(SCALAR_SUFFIX_UP"HEMV ",&info,6);
 
   if(*n==0)
     return 1;
 
-  Scalar* actual_x = get_compact_vector(x,*n,*incx);
+  const Scalar* actual_x = get_compact_vector(x,*n,*incx);
   Scalar* actual_y = get_compact_vector(y,*n,*incy);
 
   if(beta!=Scalar(1))
   {
-    if(beta==Scalar(0)) vector(actual_y, *n).setZero();
-    else                vector(actual_y, *n) *= beta;
+    if(beta==Scalar(0)) make_vector(actual_y, *n).setZero();
+    else                make_vector(actual_y, *n) *= beta;
   }
 
   if(alpha!=Scalar(0))
   {
     int code = UPLO(*uplo);
     if(code>=2 || func[code]==0)
       return 0;
 
-    func[code](*n, a, *lda, actual_x, 1, actual_y, alpha);
+    func[code](*n, a, *lda, actual_x, actual_y, alpha);
   }
 
   if(actual_x!=x) delete[] actual_x;
   if(actual_y!=y) delete[] copy_back(actual_y,y,*n,*incy);
 
@@ -109,23 +103,16 @@
   *  n by n hermitian matrix, supplied in packed form.
   */
 int EIGEN_BLAS_FUNC(hpr)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *pap)
 {
   typedef void (*functype)(int, Scalar*, const Scalar*, RealScalar);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run);
-    func[LO] = (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run);
-
-    init = true;
-  }
+  static const functype func[2] = {
+    // array index: UP
+    (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run),
+    // array index: LO
+    (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run),
+  };
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* ap = reinterpret_cast<Scalar*>(pap);
   RealScalar alpha = *palpha;
 
@@ -160,23 +147,16 @@
   *  n by n hermitian matrix, supplied in packed form.
   */
 int EIGEN_BLAS_FUNC(hpr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pap)
 {
   typedef void (*functype)(int, Scalar*, const Scalar*, const Scalar*, Scalar);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (internal::packed_rank2_update_selector<Scalar,int,Upper>::run);
-    func[LO] = (internal::packed_rank2_update_selector<Scalar,int,Lower>::run);
-
-    init = true;
-  }
+  static const functype func[2] = {
+    // array index: UP
+    (internal::packed_rank2_update_selector<Scalar,int,Upper>::run),
+    // array index: LO
+    (internal::packed_rank2_update_selector<Scalar,int,Lower>::run),
+  };
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
   Scalar* ap = reinterpret_cast<Scalar*>(pap);
   Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
@@ -215,23 +195,16 @@
   *  n by n hermitian matrix.
   */
 int EIGEN_BLAS_FUNC(her)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *pa, int *lda)
 {
   typedef void (*functype)(int, Scalar*, int, const Scalar*, const Scalar*, const Scalar&);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (selfadjoint_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run);
-    func[LO] = (selfadjoint_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run);
-
-    init = true;
-  }
+  static const functype func[2] = {
+    // array index: UP
+    (selfadjoint_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run),
+    // array index: LO
+    (selfadjoint_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run),
+  };
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* a = reinterpret_cast<Scalar*>(pa);
   RealScalar alpha = *reinterpret_cast<RealScalar*>(palpha);
 
@@ -269,23 +242,16 @@
   *  by n hermitian matrix.
   */
 int EIGEN_BLAS_FUNC(her2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pa, int *lda)
 {
   typedef void (*functype)(int, Scalar*, int, const Scalar*, const Scalar*, Scalar);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (internal::rank2_update_selector<Scalar,int,Upper>::run);
-    func[LO] = (internal::rank2_update_selector<Scalar,int,Lower>::run);
-
-    init = true;
-  }
+  static const functype func[2] = {
+    // array index: UP
+    (internal::rank2_update_selector<Scalar,int,Upper>::run),
+    // array index: LO
+    (internal::rank2_update_selector<Scalar,int,Lower>::run),
+  };
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
   Scalar* a = reinterpret_cast<Scalar*>(pa);
   Scalar alpha = *reinterpret_cast<Scalar*>(palpha);

Index: 3rd_party/eigen/blas/level2_impl.h
==================================================================
--- 3rd_party/eigen/blas/level2_impl.h
+++ 3rd_party/eigen/blas/level2_impl.h
@@ -7,33 +7,43 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "common.h"
 
-int EIGEN_BLAS_FUNC(gemv)(char *opa, int *m, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *incb, RealScalar *pbeta, RealScalar *pc, int *incc)
+template<typename Index, typename Scalar, int StorageOrder, bool ConjugateLhs, bool ConjugateRhs>
+struct general_matrix_vector_product_wrapper
+{
+  static void run(Index rows, Index cols,const Scalar *lhs, Index lhsStride, const Scalar *rhs, Index rhsIncr, Scalar* res, Index resIncr, Scalar alpha)
+  {
+    typedef internal::const_blas_data_mapper<Scalar,Index,StorageOrder> LhsMapper;
+    typedef internal::const_blas_data_mapper<Scalar,Index,RowMajor> RhsMapper;
+    
+    internal::general_matrix_vector_product
+        <Index,Scalar,LhsMapper,StorageOrder,ConjugateLhs,Scalar,RhsMapper,ConjugateRhs>::run(
+        rows, cols, LhsMapper(lhs, lhsStride), RhsMapper(rhs, rhsIncr), res, resIncr, alpha);
+  }
+};
+
+int EIGEN_BLAS_FUNC(gemv)(const char *opa, const int *m, const int *n, const RealScalar *palpha,
+                          const RealScalar *pa, const int *lda, const RealScalar *pb, const int *incb, const RealScalar *pbeta, RealScalar *pc, const int *incc)
 {
   typedef void (*functype)(int, int, const Scalar *, int, const Scalar *, int , Scalar *, int, Scalar);
-  static functype func[4];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<4; ++k)
-      func[k] = 0;
-
-    func[NOTR] = (internal::general_matrix_vector_product<int,Scalar,ColMajor,false,Scalar,false>::run);
-    func[TR  ] = (internal::general_matrix_vector_product<int,Scalar,RowMajor,false,Scalar,false>::run);
-    func[ADJ ] = (internal::general_matrix_vector_product<int,Scalar,RowMajor,Conj, Scalar,false>::run);
-
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* b = reinterpret_cast<Scalar*>(pb);
+  static const functype func[4] = {
+    // array index: NOTR
+    (general_matrix_vector_product_wrapper<int,Scalar,ColMajor,false,false>::run),
+    // array index: TR  
+    (general_matrix_vector_product_wrapper<int,Scalar,RowMajor,false,false>::run),
+    // array index: ADJ 
+    (general_matrix_vector_product_wrapper<int,Scalar,RowMajor,Conj ,false>::run),
+    0
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* b = reinterpret_cast<const Scalar*>(pb);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha  = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta   = *reinterpret_cast<Scalar*>(pbeta);
+  Scalar alpha  = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta   = *reinterpret_cast<const Scalar*>(pbeta);
 
   // check arguments
   int info = 0;
   if(OP(*opa)==INVALID)           info = 1;
   else if(*m<0)                   info = 2;
@@ -51,17 +61,17 @@
   int actual_n = *n;
   int code = OP(*opa);
   if(code!=NOTR)
     std::swap(actual_m,actual_n);
 
-  Scalar* actual_b = get_compact_vector(b,actual_n,*incb);
+  const Scalar* actual_b = get_compact_vector(b,actual_n,*incb);
   Scalar* actual_c = get_compact_vector(c,actual_m,*incc);
 
   if(beta!=Scalar(1))
   {
-    if(beta==Scalar(0)) vector(actual_c, actual_m).setZero();
-    else                vector(actual_c, actual_m) *= beta;
+    if(beta==Scalar(0)) make_vector(actual_c, actual_m).setZero();
+    else                make_vector(actual_c, actual_m) *= beta;
   }
 
   if(code>=4 || func[code]==0)
     return 0;
 
@@ -71,41 +81,45 @@
   if(actual_c!=c) delete[] copy_back(actual_c,c,actual_m,*incc);
 
   return 1;
 }
 
-int EIGEN_BLAS_FUNC(trsv)(char *uplo, char *opa, char *diag, int *n, RealScalar *pa, int *lda, RealScalar *pb, int *incb)
+int EIGEN_BLAS_FUNC(trsv)(const char *uplo, const char *opa, const char *diag, const int *n, const RealScalar *pa, const int *lda, RealScalar *pb, const int *incb)
 {
   typedef void (*functype)(int, const Scalar *, int, Scalar *);
-  static functype func[16];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<16; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (UP << 2) | (NUNIT << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       false,ColMajor>::run);
-    func[TR    | (UP << 2) | (NUNIT << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       false,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (NUNIT << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       Conj, RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (NUNIT << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       false,ColMajor>::run);
-    func[TR    | (LO << 2) | (NUNIT << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       false,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (NUNIT << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       Conj, RowMajor>::run);
-
-    func[NOTR  | (UP << 2) | (UNIT  << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,ColMajor>::run);
-    func[TR    | (UP << 2) | (UNIT  << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (UNIT  << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,Conj, RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (UNIT  << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,ColMajor>::run);
-    func[TR    | (LO << 2) | (UNIT  << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (UNIT  << 3)] = (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,Conj, RowMajor>::run);
-
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
+  static const functype func[16] = {
+    // array index: NOTR  | (UP << 2) | (NUNIT << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       false,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (NUNIT << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       false,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (NUNIT << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       Conj, RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (NUNIT << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       false,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (NUNIT << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       false,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (NUNIT << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       Conj, RowMajor>::run),
+    0,
+    // array index: NOTR  | (UP << 2) | (UNIT  << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (UNIT  << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (UNIT  << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,Conj, RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (UNIT  << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (UNIT  << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (UNIT  << 3)
+    (internal::triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,Conj, RowMajor>::run),
+    0
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
   Scalar* b = reinterpret_cast<Scalar*>(pb);
 
   int info = 0;
   if(UPLO(*uplo)==INVALID)                                            info = 1;
   else if(OP(*opa)==INVALID)                                          info = 2;
@@ -126,41 +140,45 @@
   return 0;
 }
 
 
 
-int EIGEN_BLAS_FUNC(trmv)(char *uplo, char *opa, char *diag, int *n, RealScalar *pa, int *lda, RealScalar *pb, int *incb)
+int EIGEN_BLAS_FUNC(trmv)(const char *uplo, const char *opa, const char *diag, const int *n, const RealScalar *pa, const int *lda, RealScalar *pb, const int *incb)
 {
   typedef void (*functype)(int, int, const Scalar *, int, const Scalar *, int, Scalar *, int, const Scalar&);
-  static functype func[16];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<16; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (UP << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product<int,Upper|0,       Scalar,false,Scalar,false,ColMajor>::run);
-    func[TR    | (UP << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product<int,Lower|0,       Scalar,false,Scalar,false,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product<int,Lower|0,       Scalar,Conj, Scalar,false,RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product<int,Lower|0,       Scalar,false,Scalar,false,ColMajor>::run);
-    func[TR    | (LO << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product<int,Upper|0,       Scalar,false,Scalar,false,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product<int,Upper|0,       Scalar,Conj, Scalar,false,RowMajor>::run);
-
-    func[NOTR  | (UP << 2) | (UNIT  << 3)] = (internal::triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run);
-    func[TR    | (UP << 2) | (UNIT  << 3)] = (internal::triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (UNIT  << 3)] = (internal::triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (UNIT  << 3)] = (internal::triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run);
-    func[TR    | (LO << 2) | (UNIT  << 3)] = (internal::triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (UNIT  << 3)] = (internal::triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run);
-
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
+  static const functype func[16] = {
+    // array index: NOTR  | (UP << 2) | (NUNIT << 3)
+    (internal::triangular_matrix_vector_product<int,Upper|0,       Scalar,false,Scalar,false,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (NUNIT << 3)
+    (internal::triangular_matrix_vector_product<int,Lower|0,       Scalar,false,Scalar,false,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (NUNIT << 3)
+    (internal::triangular_matrix_vector_product<int,Lower|0,       Scalar,Conj, Scalar,false,RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (NUNIT << 3)
+    (internal::triangular_matrix_vector_product<int,Lower|0,       Scalar,false,Scalar,false,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (NUNIT << 3)
+    (internal::triangular_matrix_vector_product<int,Upper|0,       Scalar,false,Scalar,false,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (NUNIT << 3)
+    (internal::triangular_matrix_vector_product<int,Upper|0,       Scalar,Conj, Scalar,false,RowMajor>::run),
+    0,
+    // array index: NOTR  | (UP << 2) | (UNIT  << 3)
+    (internal::triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (UNIT  << 3)
+    (internal::triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (UNIT  << 3)
+    (internal::triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (UNIT  << 3)
+    (internal::triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (UNIT  << 3)
+    (internal::triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (UNIT  << 3)
+    (internal::triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run),
+    0
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
   Scalar* b = reinterpret_cast<Scalar*>(pb);
 
   int info = 0;
   if(UPLO(*uplo)==INVALID)                                            info = 1;
   else if(OP(*opa)==INVALID)                                          info = 2;
@@ -198,17 +216,17 @@
   *  m by n band matrix, with kl sub-diagonals and ku super-diagonals.
   */
 int EIGEN_BLAS_FUNC(gbmv)(char *trans, int *m, int *n, int *kl, int *ku, RealScalar *palpha, RealScalar *pa, int *lda,
                           RealScalar *px, int *incx, RealScalar *pbeta, RealScalar *py, int *incy)
 {
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* x = reinterpret_cast<Scalar*>(px);
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* x = reinterpret_cast<const Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
-  Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta = *reinterpret_cast<Scalar*>(pbeta);
+  Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta = *reinterpret_cast<const Scalar*>(pbeta);
   int coeff_rows = *kl+*ku+1;
-  
+
   int info = 0;
        if(OP(*trans)==INVALID)                                        info = 1;
   else if(*m<0)                                                       info = 2;
   else if(*n<0)                                                       info = 3;
   else if(*kl<0)                                                      info = 4;
@@ -216,48 +234,48 @@
   else if(*lda<coeff_rows)                                            info = 8;
   else if(*incx==0)                                                   info = 10;
   else if(*incy==0)                                                   info = 13;
   if(info)
     return xerbla_(SCALAR_SUFFIX_UP"GBMV ",&info,6);
-  
+
   if(*m==0 || *n==0 || (alpha==Scalar(0) && beta==Scalar(1)))
     return 0;
-  
+
   int actual_m = *m;
   int actual_n = *n;
   if(OP(*trans)!=NOTR)
     std::swap(actual_m,actual_n);
-  
-  Scalar* actual_x = get_compact_vector(x,actual_n,*incx);
+
+  const Scalar* actual_x = get_compact_vector(x,actual_n,*incx);
   Scalar* actual_y = get_compact_vector(y,actual_m,*incy);
-  
+
   if(beta!=Scalar(1))
   {
-    if(beta==Scalar(0)) vector(actual_y, actual_m).setZero();
-    else                vector(actual_y, actual_m) *= beta;
+    if(beta==Scalar(0)) make_vector(actual_y, actual_m).setZero();
+    else                make_vector(actual_y, actual_m) *= beta;
   }
-  
-  MatrixType mat_coeffs(a,coeff_rows,*n,*lda);
-  
+
+  ConstMatrixType mat_coeffs(a,coeff_rows,*n,*lda);
+
   int nb = std::min(*n,(*m)+(*ku));
   for(int j=0; j<nb; ++j)
   {
     int start = std::max(0,j - *ku);
     int end = std::min((*m)-1,j + *kl);
     int len = end - start + 1;
     int offset = (*ku) - j + start;
     if(OP(*trans)==NOTR)
-      vector(actual_y+start,len) += (alpha*actual_x[j]) * mat_coeffs.col(j).segment(offset,len);
+      make_vector(actual_y+start,len) += (alpha*actual_x[j]) * mat_coeffs.col(j).segment(offset,len);
     else if(OP(*trans)==TR)
-      actual_y[j] += alpha * ( mat_coeffs.col(j).segment(offset,len).transpose() * vector(actual_x+start,len) ).value();
+      actual_y[j] += alpha * ( mat_coeffs.col(j).segment(offset,len).transpose() * make_vector(actual_x+start,len) ).value();
     else
-      actual_y[j] += alpha * ( mat_coeffs.col(j).segment(offset,len).adjoint()   * vector(actual_x+start,len) ).value();
-  }    
-  
+      actual_y[j] += alpha * ( mat_coeffs.col(j).segment(offset,len).adjoint()   * make_vector(actual_x+start,len) ).value();
+  }
+
   if(actual_x!=x) delete[] actual_x;
   if(actual_y!=y) delete[] copy_back(actual_y,y,actual_m,*incy);
-  
+
   return 0;
 }
 
 #if 0
 /**  TBMV  performs one of the matrix-vector operations
@@ -270,11 +288,11 @@
 int EIGEN_BLAS_FUNC(tbmv)(char *uplo, char *opa, char *diag, int *n, int *k, RealScalar *pa, int *lda, RealScalar *px, int *incx)
 {
   Scalar* a = reinterpret_cast<Scalar*>(pa);
   Scalar* x = reinterpret_cast<Scalar*>(px);
   int coeff_rows = *k + 1;
-  
+
   int info = 0;
        if(UPLO(*uplo)==INVALID)                                       info = 1;
   else if(OP(*opa)==INVALID)                                          info = 2;
   else if(DIAG(*diag)==INVALID)                                       info = 3;
   else if(*n<0)                                                       info = 4;
@@ -281,41 +299,41 @@
   else if(*k<0)                                                       info = 5;
   else if(*lda<coeff_rows)                                            info = 7;
   else if(*incx==0)                                                   info = 9;
   if(info)
     return xerbla_(SCALAR_SUFFIX_UP"TBMV ",&info,6);
-  
+
   if(*n==0)
     return 0;
-  
+
   int actual_n = *n;
-  
+
   Scalar* actual_x = get_compact_vector(x,actual_n,*incx);
-  
+
   MatrixType mat_coeffs(a,coeff_rows,*n,*lda);
-  
+
   int ku = UPLO(*uplo)==UPPER ? *k : 0;
   int kl = UPLO(*uplo)==LOWER ? *k : 0;
-  
+
   for(int j=0; j<*n; ++j)
   {
     int start = std::max(0,j - ku);
     int end = std::min((*m)-1,j + kl);
     int len = end - start + 1;
     int offset = (ku) - j + start;
-    
+
     if(OP(*trans)==NOTR)
-      vector(actual_y+start,len) += (alpha*actual_x[j]) * mat_coeffs.col(j).segment(offset,len);
+      make_vector(actual_y+start,len) += (alpha*actual_x[j]) * mat_coeffs.col(j).segment(offset,len);
     else if(OP(*trans)==TR)
-      actual_y[j] += alpha * ( mat_coeffs.col(j).segment(offset,len).transpose() * vector(actual_x+start,len) ).value();
+      actual_y[j] += alpha * ( mat_coeffs.col(j).segment(offset,len).transpose() * make_vector(actual_x+start,len) ).value();
     else
-      actual_y[j] += alpha * ( mat_coeffs.col(j).segment(offset,len).adjoint()   * vector(actual_x+start,len) ).value();
-  }    
-  
+      actual_y[j] += alpha * ( mat_coeffs.col(j).segment(offset,len).adjoint()   * make_vector(actual_x+start,len) ).value();
+  }
+
   if(actual_x!=x) delete[] actual_x;
   if(actual_y!=y) delete[] copy_back(actual_y,y,actual_m,*incy);
-  
+
   return 0;
 }
 #endif
 
 /**  DTBSV  solves one of the systems of equations
@@ -330,41 +348,45 @@
   *  routine. Such tests must be performed before calling this routine.
   */
 int EIGEN_BLAS_FUNC(tbsv)(char *uplo, char *op, char *diag, int *n, int *k, RealScalar *pa, int *lda, RealScalar *px, int *incx)
 {
   typedef void (*functype)(int, int, const Scalar *, int, Scalar *);
-  static functype func[16];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<16; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (UP << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector<int,Upper|0,       Scalar,false,Scalar,ColMajor>::run);
-    func[TR    | (UP << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector<int,Lower|0,       Scalar,false,Scalar,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector<int,Lower|0,       Scalar,Conj, Scalar,RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector<int,Lower|0,       Scalar,false,Scalar,ColMajor>::run);
-    func[TR    | (LO << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector<int,Upper|0,       Scalar,false,Scalar,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector<int,Upper|0,       Scalar,Conj, Scalar,RowMajor>::run);
-
-    func[NOTR  | (UP << 2) | (UNIT  << 3)] = (internal::band_solve_triangular_selector<int,Upper|UnitDiag,Scalar,false,Scalar,ColMajor>::run);
-    func[TR    | (UP << 2) | (UNIT  << 3)] = (internal::band_solve_triangular_selector<int,Lower|UnitDiag,Scalar,false,Scalar,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (UNIT  << 3)] = (internal::band_solve_triangular_selector<int,Lower|UnitDiag,Scalar,Conj, Scalar,RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (UNIT  << 3)] = (internal::band_solve_triangular_selector<int,Lower|UnitDiag,Scalar,false,Scalar,ColMajor>::run);
-    func[TR    | (LO << 2) | (UNIT  << 3)] = (internal::band_solve_triangular_selector<int,Upper|UnitDiag,Scalar,false,Scalar,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (UNIT  << 3)] = (internal::band_solve_triangular_selector<int,Upper|UnitDiag,Scalar,Conj, Scalar,RowMajor>::run);
-
-    init = true;
-  }
+  static const functype func[16] = {
+    // array index: NOTR  | (UP << 2) | (NUNIT << 3)
+    (internal::band_solve_triangular_selector<int,Upper|0,       Scalar,false,Scalar,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (NUNIT << 3)
+    (internal::band_solve_triangular_selector<int,Lower|0,       Scalar,false,Scalar,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (NUNIT << 3)
+    (internal::band_solve_triangular_selector<int,Lower|0,       Scalar,Conj, Scalar,RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (NUNIT << 3)
+    (internal::band_solve_triangular_selector<int,Lower|0,       Scalar,false,Scalar,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (NUNIT << 3)
+    (internal::band_solve_triangular_selector<int,Upper|0,       Scalar,false,Scalar,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (NUNIT << 3)
+    (internal::band_solve_triangular_selector<int,Upper|0,       Scalar,Conj, Scalar,RowMajor>::run),
+    0,
+    // array index: NOTR  | (UP << 2) | (UNIT  << 3)
+    (internal::band_solve_triangular_selector<int,Upper|UnitDiag,Scalar,false,Scalar,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (UNIT  << 3)
+    (internal::band_solve_triangular_selector<int,Lower|UnitDiag,Scalar,false,Scalar,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (UNIT  << 3)
+    (internal::band_solve_triangular_selector<int,Lower|UnitDiag,Scalar,Conj, Scalar,RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (UNIT  << 3)
+    (internal::band_solve_triangular_selector<int,Lower|UnitDiag,Scalar,false,Scalar,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (UNIT  << 3)
+    (internal::band_solve_triangular_selector<int,Upper|UnitDiag,Scalar,false,Scalar,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (UNIT  << 3)
+    (internal::band_solve_triangular_selector<int,Upper|UnitDiag,Scalar,Conj, Scalar,RowMajor>::run),
+    0,
+  };
 
   Scalar* a = reinterpret_cast<Scalar*>(pa);
   Scalar* x = reinterpret_cast<Scalar*>(px);
   int coeff_rows = *k+1;
-  
+
   int info = 0;
        if(UPLO(*uplo)==INVALID)                                       info = 1;
   else if(OP(*op)==INVALID)                                           info = 2;
   else if(DIAG(*diag)==INVALID)                                       info = 3;
   else if(*n<0)                                                       info = 4;
@@ -371,26 +393,26 @@
   else if(*k<0)                                                       info = 5;
   else if(*lda<coeff_rows)                                            info = 7;
   else if(*incx==0)                                                   info = 9;
   if(info)
     return xerbla_(SCALAR_SUFFIX_UP"TBSV ",&info,6);
-  
+
   if(*n==0 || (*k==0 && DIAG(*diag)==UNIT))
     return 0;
-  
+
   int actual_n = *n;
- 
+
   Scalar* actual_x = get_compact_vector(x,actual_n,*incx);
-  
+
   int code = OP(*op) | (UPLO(*uplo) << 2) | (DIAG(*diag) << 3);
   if(code>=16 || func[code]==0)
     return 0;
 
   func[code](*n, *k, a, *lda, actual_x);
-  
+
   if(actual_x!=x) delete[] copy_back(actual_x,x,actual_n,*incx);
-  
+
   return 0;
 }
 
 /**  DTPMV  performs one of the matrix-vector operations
   *
@@ -400,36 +422,40 @@
   *  upper or lower triangular matrix, supplied in packed form.
   */
 int EIGEN_BLAS_FUNC(tpmv)(char *uplo, char *opa, char *diag, int *n, RealScalar *pap, RealScalar *px, int *incx)
 {
   typedef void (*functype)(int, const Scalar*, const Scalar*, Scalar*, Scalar);
-  static functype func[16];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<16; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|0,       Scalar,false,Scalar,false,ColMajor>::run);
-    func[TR    | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|0,       Scalar,false,Scalar,false,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|0,       Scalar,Conj, Scalar,false,RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|0,       Scalar,false,Scalar,false,ColMajor>::run);
-    func[TR    | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|0,       Scalar,false,Scalar,false,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|0,       Scalar,Conj, Scalar,false,RowMajor>::run);
-
-    func[NOTR  | (UP << 2) | (UNIT  << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run);
-    func[TR    | (UP << 2) | (UNIT  << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (UNIT  << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (UNIT  << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run);
-    func[TR    | (LO << 2) | (UNIT  << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (UNIT  << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run);
-
-    init = true;
-  }
+  static const functype func[16] = {
+    // array index: NOTR  | (UP << 2) | (NUNIT << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Upper|0,       Scalar,false,Scalar,false,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (NUNIT << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Lower|0,       Scalar,false,Scalar,false,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (NUNIT << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Lower|0,       Scalar,Conj, Scalar,false,RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (NUNIT << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Lower|0,       Scalar,false,Scalar,false,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (NUNIT << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Upper|0,       Scalar,false,Scalar,false,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (NUNIT << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Upper|0,       Scalar,Conj, Scalar,false,RowMajor>::run),
+    0,
+    // array index: NOTR  | (UP << 2) | (UNIT  << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (UNIT  << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (UNIT  << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (UNIT  << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (UNIT  << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (UNIT  << 3)
+    (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run),
+    0
+  };
 
   Scalar* ap = reinterpret_cast<Scalar*>(pap);
   Scalar* x = reinterpret_cast<Scalar*>(px);
 
   int info = 0;
@@ -471,36 +497,40 @@
   *  routine. Such tests must be performed before calling this routine.
   */
 int EIGEN_BLAS_FUNC(tpsv)(char *uplo, char *opa, char *diag, int *n, RealScalar *pap, RealScalar *px, int *incx)
 {
   typedef void (*functype)(int, const Scalar*, Scalar*);
-  static functype func[16];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<16; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       false,ColMajor>::run);
-    func[TR    | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       false,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       Conj, RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       false,ColMajor>::run);
-    func[TR    | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       false,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       Conj, RowMajor>::run);
-
-    func[NOTR  | (UP << 2) | (UNIT  << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,ColMajor>::run);
-    func[TR    | (UP << 2) | (UNIT  << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,RowMajor>::run);
-    func[ADJ   | (UP << 2) | (UNIT  << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,Conj, RowMajor>::run);
-
-    func[NOTR  | (LO << 2) | (UNIT  << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,ColMajor>::run);
-    func[TR    | (LO << 2) | (UNIT  << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,RowMajor>::run);
-    func[ADJ   | (LO << 2) | (UNIT  << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,Conj, RowMajor>::run);
-
-    init = true;
-  }
+  static const functype func[16] = {
+    // array index: NOTR  | (UP << 2) | (NUNIT << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       false,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (NUNIT << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       false,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (NUNIT << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       Conj, RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (NUNIT << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0,       false,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (NUNIT << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       false,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (NUNIT << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0,       Conj, RowMajor>::run),
+    0,
+    // array index: NOTR  | (UP << 2) | (UNIT  << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,ColMajor>::run),
+    // array index: TR    | (UP << 2) | (UNIT  << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,RowMajor>::run),
+    // array index: ADJ   | (UP << 2) | (UNIT  << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,Conj, RowMajor>::run),
+    0,
+    // array index: NOTR  | (LO << 2) | (UNIT  << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,ColMajor>::run),
+    // array index: TR    | (LO << 2) | (UNIT  << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,RowMajor>::run),
+    // array index: ADJ   | (LO << 2) | (UNIT  << 3)
+    (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,Conj, RowMajor>::run),
+    0
+  };
 
   Scalar* ap = reinterpret_cast<Scalar*>(pap);
   Scalar* x = reinterpret_cast<Scalar*>(px);
 
   int info = 0;
@@ -519,6 +549,5 @@
 
   if(actual_x!=x) delete[] copy_back(actual_x,x,*n,*incx);
 
   return 1;
 }
-

Index: 3rd_party/eigen/blas/level2_real_impl.h
==================================================================
--- 3rd_party/eigen/blas/level2_real_impl.h
+++ 3rd_party/eigen/blas/level2_real_impl.h
@@ -8,32 +8,26 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "common.h"
 
 // y = alpha*A*x + beta*y
-int EIGEN_BLAS_FUNC(symv) (char *uplo, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *px, int *incx, RealScalar *pbeta, RealScalar *py, int *incy)
-{
-  typedef void (*functype)(int, const Scalar*, int, const Scalar*, int, Scalar*, Scalar);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Upper,false,false>::run);
-    func[LO] = (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Lower,false,false>::run);
-
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* x = reinterpret_cast<Scalar*>(px);
-  Scalar* y = reinterpret_cast<Scalar*>(py);
-  Scalar alpha  = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta   = *reinterpret_cast<Scalar*>(pbeta);
+int EIGEN_BLAS_FUNC(symv) (const char *uplo, const int *n, const RealScalar *palpha, const RealScalar *pa, const int *lda,
+                           const RealScalar *px, const int *incx, const RealScalar *pbeta, RealScalar *py, const int *incy)
+{
+  typedef void (*functype)(int, const Scalar*, int, const Scalar*, Scalar*, Scalar);
+  static const functype func[2] = {
+    // array index: UP
+    (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Upper,false,false>::run),
+    // array index: LO
+    (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Lower,false,false>::run),
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* x = reinterpret_cast<const Scalar*>(px);
+  Scalar* y = reinterpret_cast<Scalar*>(py);
+  Scalar alpha  = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta   = *reinterpret_cast<const Scalar*>(pbeta);
 
   // check arguments
   int info = 0;
   if(UPLO(*uplo)==INVALID)        info = 1;
   else if(*n<0)                   info = 2;
@@ -44,67 +38,46 @@
     return xerbla_(SCALAR_SUFFIX_UP"SYMV ",&info,6);
 
   if(*n==0)
     return 0;
 
-  Scalar* actual_x = get_compact_vector(x,*n,*incx);
+  const Scalar* actual_x = get_compact_vector(x,*n,*incx);
   Scalar* actual_y = get_compact_vector(y,*n,*incy);
 
   if(beta!=Scalar(1))
   {
-    if(beta==Scalar(0)) vector(actual_y, *n).setZero();
-    else                vector(actual_y, *n) *= beta;
+    if(beta==Scalar(0)) make_vector(actual_y, *n).setZero();
+    else                make_vector(actual_y, *n) *= beta;
   }
 
   int code = UPLO(*uplo);
   if(code>=2 || func[code]==0)
     return 0;
 
-  func[code](*n, a, *lda, actual_x, 1, actual_y, alpha);
+  func[code](*n, a, *lda, actual_x, actual_y, alpha);
 
   if(actual_x!=x) delete[] actual_x;
   if(actual_y!=y) delete[] copy_back(actual_y,y,*n,*incy);
 
   return 1;
 }
 
 // C := alpha*x*x' + C
-int EIGEN_BLAS_FUNC(syr)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *pc, int *ldc)
-{
-
-//   typedef void (*functype)(int, const Scalar *, int, Scalar *, int, Scalar);
-//   static functype func[2];
-
-//   static bool init = false;
-//   if(!init)
-//   {
-//     for(int k=0; k<2; ++k)
-//       func[k] = 0;
-//
-//     func[UP] = (internal::selfadjoint_product<Scalar,ColMajor,ColMajor,false,UpperTriangular>::run);
-//     func[LO] = (internal::selfadjoint_product<Scalar,ColMajor,ColMajor,false,LowerTriangular>::run);
-
-//     init = true;
-//   }
-  typedef void (*functype)(int, Scalar*, int, const Scalar*, const Scalar*, const Scalar&);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (selfadjoint_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run);
-    func[LO] = (selfadjoint_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run);
-
-    init = true;
-  }
-
-  Scalar* x = reinterpret_cast<Scalar*>(px);
-  Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
+int EIGEN_BLAS_FUNC(syr)(const char *uplo, const int *n, const RealScalar *palpha, const RealScalar *px, const int *incx, RealScalar *pc, const int *ldc)
+{
+
+  typedef void (*functype)(int, Scalar*, int, const Scalar*, const Scalar*, const Scalar&);
+  static const functype func[2] = {
+    // array index: UP
+    (selfadjoint_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run),
+    // array index: LO
+    (selfadjoint_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run),
+  };
+
+  const Scalar* x = reinterpret_cast<const Scalar*>(px);
+  Scalar* c = reinterpret_cast<Scalar*>(pc);
+  Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
 
   int info = 0;
   if(UPLO(*uplo)==INVALID)                                            info = 1;
   else if(*n<0)                                                       info = 2;
   else if(*incx==0)                                                   info = 5;
@@ -113,11 +86,11 @@
     return xerbla_(SCALAR_SUFFIX_UP"SYR  ",&info,6);
 
   if(*n==0 || alpha==Scalar(0)) return 1;
 
   // if the increment is not 1, let's copy it to a temporary vector to enable vectorization
-  Scalar* x_cpy = get_compact_vector(x,*n,*incx);
+  const Scalar* x_cpy = get_compact_vector(x,*n,*incx);
 
   int code = UPLO(*uplo);
   if(code>=2 || func[code]==0)
     return 0;
 
@@ -127,45 +100,24 @@
 
   return 1;
 }
 
 // C := alpha*x*y' + alpha*y*x' + C
-int EIGEN_BLAS_FUNC(syr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pc, int *ldc)
-{
-//   typedef void (*functype)(int, const Scalar *, int, const Scalar *, int, Scalar *, int, Scalar);
-//   static functype func[2];
-//
-//   static bool init = false;
-//   if(!init)
-//   {
-//     for(int k=0; k<2; ++k)
-//       func[k] = 0;
-//
-//     func[UP] = (internal::selfadjoint_product<Scalar,ColMajor,ColMajor,false,UpperTriangular>::run);
-//     func[LO] = (internal::selfadjoint_product<Scalar,ColMajor,ColMajor,false,LowerTriangular>::run);
-//
-//     init = true;
-//   }
+int EIGEN_BLAS_FUNC(syr2)(const char *uplo, const int *n, const RealScalar *palpha, const RealScalar *px, const int *incx, const RealScalar *py, const int *incy, RealScalar *pc, const int *ldc)
+{
   typedef void (*functype)(int, Scalar*, int, const Scalar*, const Scalar*, Scalar);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (internal::rank2_update_selector<Scalar,int,Upper>::run);
-    func[LO] = (internal::rank2_update_selector<Scalar,int,Lower>::run);
-
-    init = true;
-  }
-
-  Scalar* x = reinterpret_cast<Scalar*>(px);
-  Scalar* y = reinterpret_cast<Scalar*>(py);
+  static const functype func[2] = {
+    // array index: UP
+    (internal::rank2_update_selector<Scalar,int,Upper>::run),
+    // array index: LO
+    (internal::rank2_update_selector<Scalar,int,Lower>::run),
+  };
+
+  const Scalar* x = reinterpret_cast<const Scalar*>(px);
+  const Scalar* y = reinterpret_cast<const Scalar*>(py);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
+  Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
 
   int info = 0;
   if(UPLO(*uplo)==INVALID)                                            info = 1;
   else if(*n<0)                                                       info = 2;
   else if(*incx==0)                                                   info = 5;
@@ -175,13 +127,13 @@
     return xerbla_(SCALAR_SUFFIX_UP"SYR2 ",&info,6);
 
   if(alpha==Scalar(0))
     return 1;
 
-  Scalar* x_cpy = get_compact_vector(x,*n,*incx);
-  Scalar* y_cpy = get_compact_vector(y,*n,*incy);
-  
+  const Scalar* x_cpy = get_compact_vector(x,*n,*incx);
+  const Scalar* y_cpy = get_compact_vector(y,*n,*incy);
+
   int code = UPLO(*uplo);
   if(code>=2 || func[code]==0)
     return 0;
 
   func[code](*n, c, *ldc, x_cpy, y_cpy, alpha);
@@ -232,23 +184,16 @@
   *  n by n symmetric matrix, supplied in packed form.
   */
 int EIGEN_BLAS_FUNC(spr)(char *uplo, int *n, Scalar *palpha, Scalar *px, int *incx, Scalar *pap)
 {
   typedef void (*functype)(int, Scalar*, const Scalar*, Scalar);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Upper,false,false>::run);
-    func[LO] = (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Lower,false,false>::run);
-
-    init = true;
-  }
+  static const functype func[2] = {
+    // array index: UP
+    (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Upper,false,false>::run),
+    // array index: LO
+    (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Lower,false,false>::run),
+  };
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* ap = reinterpret_cast<Scalar*>(pap);
   Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
 
@@ -283,23 +228,16 @@
   *  n by n symmetric matrix, supplied in packed form.
   */
 int EIGEN_BLAS_FUNC(spr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pap)
 {
   typedef void (*functype)(int, Scalar*, const Scalar*, const Scalar*, Scalar);
-  static functype func[2];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<2; ++k)
-      func[k] = 0;
-
-    func[UP] = (internal::packed_rank2_update_selector<Scalar,int,Upper>::run);
-    func[LO] = (internal::packed_rank2_update_selector<Scalar,int,Lower>::run);
-
-    init = true;
-  }
+  static const functype func[2] = {
+    // array index: UP
+    (internal::packed_rank2_update_selector<Scalar,int,Upper>::run),
+    // array index: LO
+    (internal::packed_rank2_update_selector<Scalar,int,Lower>::run),
+  };
 
   Scalar* x = reinterpret_cast<Scalar*>(px);
   Scalar* y = reinterpret_cast<Scalar*>(py);
   Scalar* ap = reinterpret_cast<Scalar*>(pap);
   Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
@@ -364,7 +302,5 @@
   if(x_cpy!=x)  delete[] x_cpy;
   if(y_cpy!=y)  delete[] y_cpy;
 
   return 1;
 }
-
-

Index: 3rd_party/eigen/blas/level3_impl.h
==================================================================
--- 3rd_party/eigen/blas/level3_impl.h
+++ 3rd_party/eigen/blas/level3_impl.h
@@ -4,41 +4,47 @@
 // Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
+#include <iostream>
 #include "common.h"
 
-int EIGEN_BLAS_FUNC(gemm)(char *opa, char *opb, int *m, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
+int EIGEN_BLAS_FUNC(gemm)(const char *opa, const char *opb, const int *m, const int *n, const int *k, const RealScalar *palpha,
+                          const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
 {
 //   std::cerr << "in gemm " << *opa << " " << *opb << " " << *m << " " << *n << " " << *k << " " << *lda << " " << *ldb << " " << *ldc << " " << *palpha << " " << *pbeta << "\n";
   typedef void (*functype)(DenseIndex, DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, Scalar, internal::level3_blocking<Scalar,Scalar>&, Eigen::internal::GemmParallelInfo<DenseIndex>*);
-  static functype func[12];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<12; ++k)
-      func[k] = 0;
-    func[NOTR  | (NOTR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,ColMajor,false,ColMajor>::run);
-    func[TR    | (NOTR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,false,ColMajor>::run);
-    func[ADJ   | (NOTR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor>::run);
-    func[NOTR  | (TR   << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,false,ColMajor>::run);
-    func[TR    | (TR   << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,RowMajor,false,ColMajor>::run);
-    func[ADJ   | (TR   << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,RowMajor,false,ColMajor>::run);
-    func[NOTR  | (ADJ  << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor>::run);
-    func[TR    | (ADJ  << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,RowMajor,Conj, ColMajor>::run);
-    func[ADJ   | (ADJ  << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,RowMajor,Conj, ColMajor>::run);
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* b = reinterpret_cast<Scalar*>(pb);
+  static const functype func[12] = {
+    // array index: NOTR  | (NOTR << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (NOTR << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,false,ColMajor>::run),
+    // array index: ADJ   | (NOTR << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor>::run),
+    0,
+    // array index: NOTR  | (TR   << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,false,ColMajor>::run),
+    // array index: TR    | (TR   << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,RowMajor,false,ColMajor>::run),
+    // array index: ADJ   | (TR   << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,RowMajor,false,ColMajor>::run),
+    0,
+    // array index: NOTR  | (ADJ  << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor>::run),
+    // array index: TR    | (ADJ  << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,RowMajor,Conj, ColMajor>::run),
+    // array index: ADJ   | (ADJ  << 2)
+    (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,RowMajor,Conj, ColMajor>::run),
+    0
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* b = reinterpret_cast<const Scalar*>(pb);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha  = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta   = *reinterpret_cast<Scalar*>(pbeta);
+  Scalar alpha  = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta   = *reinterpret_cast<const Scalar*>(pbeta);
 
   int info = 0;
   if(OP(*opa)==INVALID)                                               info = 1;
   else if(OP(*opb)==INVALID)                                          info = 2;
   else if(*m<0)                                                       info = 3;
@@ -47,75 +53,97 @@
   else if(*lda<std::max(1,(OP(*opa)==NOTR)?*m:*k))                    info = 8;
   else if(*ldb<std::max(1,(OP(*opb)==NOTR)?*k:*n))                    info = 10;
   else if(*ldc<std::max(1,*m))                                        info = 13;
   if(info)
     return xerbla_(SCALAR_SUFFIX_UP"GEMM ",&info,6);
+
+  if (*m == 0 || *n == 0)
+    return 0;
 
   if(beta!=Scalar(1))
   {
     if(beta==Scalar(0)) matrix(c, *m, *n, *ldc).setZero();
     else                matrix(c, *m, *n, *ldc) *= beta;
   }
 
-  internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*m,*n,*k);
+  if(*k == 0)
+    return 0;
+
+  internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*m,*n,*k,1,true);
 
   int code = OP(*opa) | (OP(*opb) << 2);
   func[code](*m, *n, *k, a, *lda, b, *ldb, c, *ldc, alpha, blocking, 0);
   return 0;
 }
 
-int EIGEN_BLAS_FUNC(trsm)(char *side, char *uplo, char *opa, char *diag, int *m, int *n, RealScalar *palpha,  RealScalar *pa, int *lda, RealScalar *pb, int *ldb)
+int EIGEN_BLAS_FUNC(trsm)(const char *side, const char *uplo, const char *opa, const char *diag, const int *m, const int *n,
+                          const RealScalar *palpha,  const RealScalar *pa, const int *lda, RealScalar *pb, const int *ldb)
 {
 //   std::cerr << "in trsm " << *side << " " << *uplo << " " << *opa << " " << *diag << " " << *m << "," << *n << " " << *palpha << " " << *lda << " " << *ldb<< "\n";
   typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, internal::level3_blocking<Scalar,Scalar>&);
-  static functype func[32];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<32; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0,          false,ColMajor,ColMajor>::run);
-    func[TR    | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0,          false,RowMajor,ColMajor>::run);
-    func[ADJ   | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0,          Conj, RowMajor,ColMajor>::run);
-
-    func[NOTR  | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0,          false,ColMajor,ColMajor>::run);
-    func[TR    | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0,          false,RowMajor,ColMajor>::run);
-    func[ADJ   | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0,          Conj, RowMajor,ColMajor>::run);
-
-    func[NOTR  | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0,          false,ColMajor,ColMajor>::run);
-    func[TR    | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0,          false,RowMajor,ColMajor>::run);
-    func[ADJ   | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0,          Conj, RowMajor,ColMajor>::run);
-
-    func[NOTR  | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0,          false,ColMajor,ColMajor>::run);
-    func[TR    | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0,          false,RowMajor,ColMajor>::run);
-    func[ADJ   | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0,          Conj, RowMajor,ColMajor>::run);
-
-
-    func[NOTR  | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,false,ColMajor,ColMajor>::run);
-    func[TR    | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,false,RowMajor,ColMajor>::run);
-    func[ADJ   | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,Conj, RowMajor,ColMajor>::run);
-
-    func[NOTR  | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,false,ColMajor,ColMajor>::run);
-    func[TR    | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,false,RowMajor,ColMajor>::run);
-    func[ADJ   | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,Conj, RowMajor,ColMajor>::run);
-
-    func[NOTR  | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,false,ColMajor,ColMajor>::run);
-    func[TR    | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,false,RowMajor,ColMajor>::run);
-    func[ADJ   | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,Conj, RowMajor,ColMajor>::run);
-
-    func[NOTR  | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,false,ColMajor,ColMajor>::run);
-    func[TR    | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,false,RowMajor,ColMajor>::run);
-    func[ADJ   | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,Conj, RowMajor,ColMajor>::run);
-
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
+  static const functype func[32] = {
+    // array index: NOTR  | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0,          false,ColMajor,ColMajor>::run),
+    // array index: TR    | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0,          false,RowMajor,ColMajor>::run),
+    // array index: ADJ   | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0,          Conj, RowMajor,ColMajor>::run),\
+    0,
+    // array index: NOTR  | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0,          false,ColMajor,ColMajor>::run),
+    // array index: TR    | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0,          false,RowMajor,ColMajor>::run),
+    // array index: ADJ   | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0,          Conj, RowMajor,ColMajor>::run),
+    0,
+    // array index: NOTR  | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0,          false,ColMajor,ColMajor>::run),
+    // array index: TR    | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0,          false,RowMajor,ColMajor>::run),
+    // array index: ADJ   | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0,          Conj, RowMajor,ColMajor>::run),
+    0,
+    // array index: NOTR  | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0,          false,ColMajor,ColMajor>::run),
+    // array index: TR    | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0,          false,RowMajor,ColMajor>::run),
+    // array index: ADJ   | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0,          Conj, RowMajor,ColMajor>::run),
+    0,
+    // array index: NOTR  | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,false,ColMajor,ColMajor>::run),
+    // array index: TR    | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,false,RowMajor,ColMajor>::run),
+    // array index: ADJ   | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,Conj, RowMajor,ColMajor>::run),
+    0,
+    // array index: NOTR  | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,false,ColMajor,ColMajor>::run),
+    // array index: TR    | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,false,RowMajor,ColMajor>::run),
+    // array index: ADJ   | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,Conj, RowMajor,ColMajor>::run),
+    0,
+    // array index: NOTR  | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,false,ColMajor,ColMajor>::run),
+    // array index: TR    | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,false,RowMajor,ColMajor>::run),
+    // array index: ADJ   | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,Conj, RowMajor,ColMajor>::run),
+    0,
+    // array index: NOTR  | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,false,ColMajor,ColMajor>::run),
+    // array index: TR    | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,false,RowMajor,ColMajor>::run),
+    // array index: ADJ   | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,Conj, RowMajor,ColMajor>::run),
+    0
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
   Scalar* b = reinterpret_cast<Scalar*>(pb);
-  Scalar  alpha = *reinterpret_cast<Scalar*>(palpha);
+  Scalar  alpha = *reinterpret_cast<const Scalar*>(palpha);
 
   int info = 0;
   if(SIDE(*side)==INVALID)                                            info = 1;
   else if(UPLO(*uplo)==INVALID)                                       info = 2;
   else if(OP(*opa)==INVALID)                                          info = 3;
@@ -124,21 +152,24 @@
   else if(*n<0)                                                       info = 6;
   else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n))                 info = 9;
   else if(*ldb<std::max(1,*m))                                        info = 11;
   if(info)
     return xerbla_(SCALAR_SUFFIX_UP"TRSM ",&info,6);
+
+  if(*m==0 || *n==0)
+    return 0;
 
   int code = OP(*opa) | (SIDE(*side) << 2) | (UPLO(*uplo) << 3) | (DIAG(*diag) << 4);
-  
+
   if(SIDE(*side)==LEFT)
   {
-    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*m);
+    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*m,1,false);
     func[code](*m, *n, a, *lda, b, *ldb, blocking);
   }
   else
   {
-    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*n);
+    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*n,1,false);
     func[code](*n, *m, a, *lda, b, *ldb, blocking);
   }
 
   if(alpha!=Scalar(1))
     matrix(b,*m,*n,*ldb) *= alpha;
@@ -147,59 +178,77 @@
 }
 
 
 // b = alpha*op(a)*b  for side = 'L'or'l'
 // b = alpha*b*op(a)  for side = 'R'or'r'
-int EIGEN_BLAS_FUNC(trmm)(char *side, char *uplo, char *opa, char *diag, int *m, int *n, RealScalar *palpha,  RealScalar *pa, int *lda, RealScalar *pb, int *ldb)
+int EIGEN_BLAS_FUNC(trmm)(const char *side, const char *uplo, const char *opa, const char *diag, const int *m, const int *n,
+                          const RealScalar *palpha, const RealScalar *pa, const int *lda, RealScalar *pb, const int *ldb)
 {
 //   std::cerr << "in trmm " << *side << " " << *uplo << " " << *opa << " " << *diag << " " << *m << " " << *n << " " << *lda << " " << *ldb << " " << *palpha << "\n";
   typedef void (*functype)(DenseIndex, DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&, internal::level3_blocking<Scalar,Scalar>&);
-  static functype func[32];
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<32; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          true, ColMajor,false,ColMajor,false,ColMajor>::run);
-    func[TR    | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          true, RowMajor,false,ColMajor,false,ColMajor>::run);
-    func[ADJ   | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          true, RowMajor,Conj, ColMajor,false,ColMajor>::run);
-
-    func[NOTR  | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          false,ColMajor,false,ColMajor,false,ColMajor>::run);
-    func[TR    | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          false,ColMajor,false,RowMajor,false,ColMajor>::run);
-    func[ADJ   | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          false,ColMajor,false,RowMajor,Conj, ColMajor>::run);
-
-    func[NOTR  | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          true, ColMajor,false,ColMajor,false,ColMajor>::run);
-    func[TR    | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          true, RowMajor,false,ColMajor,false,ColMajor>::run);
-    func[ADJ   | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          true, RowMajor,Conj, ColMajor,false,ColMajor>::run);
-
-    func[NOTR  | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          false,ColMajor,false,ColMajor,false,ColMajor>::run);
-    func[TR    | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          false,ColMajor,false,RowMajor,false,ColMajor>::run);
-    func[ADJ   | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          false,ColMajor,false,RowMajor,Conj, ColMajor>::run);
-
-    func[NOTR  | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, ColMajor,false,ColMajor,false,ColMajor>::run);
-    func[TR    | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, RowMajor,false,ColMajor,false,ColMajor>::run);
-    func[ADJ   | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, RowMajor,Conj, ColMajor,false,ColMajor>::run);
-
-    func[NOTR  | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,ColMajor,false,ColMajor>::run);
-    func[TR    | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,RowMajor,false,ColMajor>::run);
-    func[ADJ   | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,RowMajor,Conj, ColMajor>::run);
-
-    func[NOTR  | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, ColMajor,false,ColMajor,false,ColMajor>::run);
-    func[TR    | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, RowMajor,false,ColMajor,false,ColMajor>::run);
-    func[ADJ   | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, RowMajor,Conj, ColMajor,false,ColMajor>::run);
-
-    func[NOTR  | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,ColMajor,false,ColMajor>::run);
-    func[TR    | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,RowMajor,false,ColMajor>::run);
-    func[ADJ   | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,RowMajor,Conj, ColMajor>::run);
-
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
+  static const functype func[32] = {
+    // array index: NOTR  | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          true, ColMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          true, RowMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: ADJ   | (LEFT  << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          true, RowMajor,Conj, ColMajor,false,ColMajor>::run),
+    0,
+    // array index: NOTR  | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          false,ColMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          false,ColMajor,false,RowMajor,false,ColMajor>::run),
+    // array index: ADJ   | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          false,ColMajor,false,RowMajor,Conj, ColMajor>::run),
+    0,
+    // array index: NOTR  | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          true, ColMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          true, RowMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: ADJ   | (LEFT  << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          true, RowMajor,Conj, ColMajor,false,ColMajor>::run),
+    0,
+    // array index: NOTR  | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0,          false,ColMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          false,ColMajor,false,RowMajor,false,ColMajor>::run),
+    // array index: ADJ   | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0,          false,ColMajor,false,RowMajor,Conj, ColMajor>::run),
+    0,
+    // array index: NOTR  | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, ColMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, RowMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: ADJ   | (LEFT  << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, RowMajor,Conj, ColMajor,false,ColMajor>::run),
+    0,
+    // array index: NOTR  | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,RowMajor,false,ColMajor>::run),
+    // array index: ADJ   | (RIGHT << 2) | (UP << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,RowMajor,Conj, ColMajor>::run),
+    0,
+    // array index: NOTR  | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, ColMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, RowMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: ADJ   | (LEFT  << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, RowMajor,Conj, ColMajor,false,ColMajor>::run),
+    0,
+    // array index: NOTR  | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,ColMajor,false,ColMajor>::run),
+    // array index: TR    | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,RowMajor,false,ColMajor>::run),
+    // array index: ADJ   | (RIGHT << 2) | (LO << 3) | (UNIT  << 4)
+    (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,RowMajor,Conj, ColMajor>::run),
+    0
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
   Scalar* b = reinterpret_cast<Scalar*>(pb);
-  Scalar  alpha = *reinterpret_cast<Scalar*>(palpha);
+  Scalar  alpha = *reinterpret_cast<const Scalar*>(palpha);
 
   int info = 0;
   if(SIDE(*side)==INVALID)                                            info = 1;
   else if(UPLO(*uplo)==INVALID)                                       info = 2;
   else if(OP(*opa)==INVALID)                                          info = 3;
@@ -220,31 +269,32 @@
   Matrix<Scalar,Dynamic,Dynamic,ColMajor> tmp = matrix(b,*m,*n,*ldb);
   matrix(b,*m,*n,*ldb).setZero();
 
   if(SIDE(*side)==LEFT)
   {
-    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*m);
+    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*m,1,false);
     func[code](*m, *n, *m, a, *lda, tmp.data(), tmp.outerStride(), b, *ldb, alpha, blocking);
   }
   else
   {
-    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*n);
+    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*n,1,false);
     func[code](*m, *n, *n, tmp.data(), tmp.outerStride(), a, *lda, b, *ldb, alpha, blocking);
   }
   return 1;
 }
 
 // c = alpha*a*b + beta*c  for side = 'L'or'l'
 // c = alpha*b*a + beta*c  for side = 'R'or'r
-int EIGEN_BLAS_FUNC(symm)(char *side, char *uplo, int *m, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
+int EIGEN_BLAS_FUNC(symm)(const char *side, const char *uplo, const int *m, const int *n, const RealScalar *palpha,
+                          const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
 {
 //   std::cerr << "in symm " << *side << " " << *uplo << " " << *m << "x" << *n << " lda:" << *lda << " ldb:" << *ldb << " ldc:" << *ldc << " alpha:" << *palpha << " beta:" << *pbeta << "\n";
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* b = reinterpret_cast<Scalar*>(pb);
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* b = reinterpret_cast<const Scalar*>(pb);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta  = *reinterpret_cast<Scalar*>(pbeta);
+  Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta  = *reinterpret_cast<const Scalar*>(pbeta);
 
   int info = 0;
   if(SIDE(*side)==INVALID)                                            info = 1;
   else if(UPLO(*uplo)==INVALID)                                       info = 2;
   else if(*m<0)                                                       info = 3;
@@ -264,13 +314,13 @@
   if(*m==0 || *n==0)
   {
     return 1;
   }
 
+  int size = (SIDE(*side)==LEFT) ? (*m) : (*n);
   #if ISCOMPLEX
   // FIXME add support for symmetric complex matrix
-  int size = (SIDE(*side)==LEFT) ? (*m) : (*n);
   Matrix<Scalar,Dynamic,Dynamic,ColMajor> matA(size,size);
   if(UPLO(*uplo)==UP)
   {
     matA.triangularView<Upper>() = matrix(a,size,size,*lda);
     matA.triangularView<Lower>() = matrix(a,size,size,*lda).transpose();
@@ -283,17 +333,19 @@
   if(SIDE(*side)==LEFT)
     matrix(c, *m, *n, *ldc) += alpha * matA * matrix(b, *m, *n, *ldb);
   else if(SIDE(*side)==RIGHT)
     matrix(c, *m, *n, *ldc) += alpha * matrix(b, *m, *n, *ldb) * matA;
   #else
+  internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*m,*n,size,1,false);
+
   if(SIDE(*side)==LEFT)
-    if(UPLO(*uplo)==UP)       internal::product_selfadjoint_matrix<Scalar, DenseIndex, RowMajor,true,false, ColMajor,false,false, ColMajor>::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha);
-    else if(UPLO(*uplo)==LO)  internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,true,false, ColMajor,false,false, ColMajor>::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha);
+    if(UPLO(*uplo)==UP)       internal::product_selfadjoint_matrix<Scalar, DenseIndex, RowMajor,true,false, ColMajor,false,false, ColMajor>::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha, blocking);
+    else if(UPLO(*uplo)==LO)  internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,true,false, ColMajor,false,false, ColMajor>::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha, blocking);
     else                      return 0;
   else if(SIDE(*side)==RIGHT)
-    if(UPLO(*uplo)==UP)       internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,false,false, RowMajor,true,false, ColMajor>::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha);
-    else if(UPLO(*uplo)==LO)  internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,false,false, ColMajor,true,false, ColMajor>::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha);
+    if(UPLO(*uplo)==UP)       internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,false,false, RowMajor,true,false, ColMajor>::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha, blocking);
+    else if(UPLO(*uplo)==LO)  internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,false,false, ColMajor,true,false, ColMajor>::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha, blocking);
     else                      return 0;
   else
     return 0;
   #endif
 
@@ -300,43 +352,42 @@
   return 0;
 }
 
 // c = alpha*a*a' + beta*c  for op = 'N'or'n'
 // c = alpha*a'*a + beta*c  for op = 'T'or't','C'or'c'
-int EIGEN_BLAS_FUNC(syrk)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pbeta, RealScalar *pc, int *ldc)
+int EIGEN_BLAS_FUNC(syrk)(const char *uplo, const char *op, const int *n, const int *k,
+                          const RealScalar *palpha, const RealScalar *pa, const int *lda, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
 {
 //   std::cerr << "in syrk " << *uplo << " " << *op << " " << *n << " " << *k << " " << *palpha << " " << *lda << " " << *pbeta << " " << *ldc << "\n";
   #if !ISCOMPLEX
-  typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&);
-  static functype func[8];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<8; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,ColMajor,Conj, Upper>::run);
-    func[TR    | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,ColMajor,Conj, Upper>::run);
-    func[ADJ   | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,ColMajor,false,Upper>::run);
-
-    func[NOTR  | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,ColMajor,Conj, Lower>::run);
-    func[TR    | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,ColMajor,Conj, Lower>::run);
-    func[ADJ   | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,ColMajor,false,Lower>::run);
-
-    init = true;
-  }
+  typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&, internal::level3_blocking<Scalar,Scalar>&);
+  static const functype func[8] = {
+    // array index: NOTR  | (UP << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,ColMajor,Conj, Upper>::run),
+    // array index: TR    | (UP << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,ColMajor,Conj, Upper>::run),
+    // array index: ADJ   | (UP << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,ColMajor,false,Upper>::run),
+    0,
+    // array index: NOTR  | (LO << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,ColMajor,Conj, Lower>::run),
+    // array index: TR    | (LO << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,ColMajor,Conj, Lower>::run),
+    // array index: ADJ   | (LO << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,ColMajor,false,Lower>::run),
+    0
+  };
   #endif
 
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta  = *reinterpret_cast<Scalar*>(pbeta);
+  Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta  = *reinterpret_cast<const Scalar*>(pbeta);
 
   int info = 0;
   if(UPLO(*uplo)==INVALID)                                            info = 1;
-  else if(OP(*op)==INVALID)                                           info = 2;
+  else if(OP(*op)==INVALID || (ISCOMPLEX && OP(*op)==ADJ) )           info = 2;
   else if(*n<0)                                                       info = 3;
   else if(*k<0)                                                       info = 4;
   else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k))                     info = 7;
   else if(*ldc<std::max(1,*n))                                        info = 10;
   if(info)
@@ -349,10 +400,13 @@
       else                matrix(c, *n, *n, *ldc).triangularView<Upper>() *= beta;
     else
       if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
       else                matrix(c, *n, *n, *ldc).triangularView<Lower>() *= beta;
   }
+
+  if(*n==0 || *k==0)
+    return 0;
 
   #if ISCOMPLEX
   // FIXME add support for symmetric complex matrix
   if(UPLO(*uplo)==UP)
   {
@@ -367,30 +421,35 @@
       matrix(c, *n, *n, *ldc).triangularView<Lower>() += alpha * matrix(a,*n,*k,*lda) * matrix(a,*n,*k,*lda).transpose();
     else
       matrix(c, *n, *n, *ldc).triangularView<Lower>() += alpha * matrix(a,*k,*n,*lda).transpose() * matrix(a,*k,*n,*lda);
   }
   #else
+  internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*n,*n,*k,1,false);
+
   int code = OP(*op) | (UPLO(*uplo) << 2);
-  func[code](*n, *k, a, *lda, a, *lda, c, *ldc, alpha);
+  func[code](*n, *k, a, *lda, a, *lda, c, *ldc, alpha, blocking);
   #endif
 
   return 0;
 }
 
 // c = alpha*a*b' + alpha*b*a' + beta*c  for op = 'N'or'n'
 // c = alpha*a'*b + alpha*b'*a + beta*c  for op = 'T'or't'
-int EIGEN_BLAS_FUNC(syr2k)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
+int EIGEN_BLAS_FUNC(syr2k)(const char *uplo, const char *op, const int *n, const int *k, const RealScalar *palpha,
+                           const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
 {
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* b = reinterpret_cast<Scalar*>(pb);
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* b = reinterpret_cast<const Scalar*>(pb);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta  = *reinterpret_cast<Scalar*>(pbeta);
+  Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta  = *reinterpret_cast<const Scalar*>(pbeta);
+
+//   std::cerr << "in syr2k " << *uplo << " " << *op << " " << *n << " " << *k << " " << alpha << " " << *lda << " " << *ldb << " " << beta << " " << *ldc << "\n";
 
   int info = 0;
   if(UPLO(*uplo)==INVALID)                                            info = 1;
-  else if(OP(*op)==INVALID)                                           info = 2;
+  else if(OP(*op)==INVALID || (ISCOMPLEX && OP(*op)==ADJ) )           info = 2;
   else if(*n<0)                                                       info = 3;
   else if(*k<0)                                                       info = 4;
   else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k))                     info = 7;
   else if(*ldb<std::max(1,(OP(*op)==NOTR)?*n:*k))                     info = 9;
   else if(*ldc<std::max(1,*n))                                        info = 12;
@@ -441,17 +500,18 @@
 
 #if ISCOMPLEX
 
 // c = alpha*a*b + beta*c  for side = 'L'or'l'
 // c = alpha*b*a + beta*c  for side = 'R'or'r
-int EIGEN_BLAS_FUNC(hemm)(char *side, char *uplo, int *m, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
+int EIGEN_BLAS_FUNC(hemm)(const char *side, const char *uplo, const int *m, const int *n, const RealScalar *palpha,
+                          const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
 {
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* b = reinterpret_cast<Scalar*>(pb);
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* b = reinterpret_cast<const Scalar*>(pb);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
-  Scalar beta  = *reinterpret_cast<Scalar*>(pbeta);
+  Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
+  Scalar beta  = *reinterpret_cast<const Scalar*>(pbeta);
 
 //   std::cerr << "in hemm " << *side << " " << *uplo << " " << *m << " " << *n << " " << alpha << " " << *lda << " " << beta << " " << *ldc << "\n";
 
   int info = 0;
   if(SIDE(*side)==INVALID)                                            info = 1;
@@ -470,24 +530,27 @@
   if(*m==0 || *n==0)
   {
     return 1;
   }
 
+  int size = (SIDE(*side)==LEFT) ? (*m) : (*n);
+  internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*m,*n,size,1,false);
+
   if(SIDE(*side)==LEFT)
   {
     if(UPLO(*uplo)==UP)       internal::product_selfadjoint_matrix<Scalar,DenseIndex,RowMajor,true,Conj,  ColMajor,false,false, ColMajor>
-                                ::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha);
+                                ::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha, blocking);
     else if(UPLO(*uplo)==LO)  internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,true,false, ColMajor,false,false, ColMajor>
-                                ::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha);
+                                ::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha, blocking);
     else                      return 0;
   }
   else if(SIDE(*side)==RIGHT)
   {
     if(UPLO(*uplo)==UP)       matrix(c,*m,*n,*ldc) += alpha * matrix(b,*m,*n,*ldb) * matrix(a,*n,*n,*lda).selfadjointView<Upper>();/*internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,false,false, RowMajor,true,Conj,  ColMajor>
-                                ::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha);*/
+                                ::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha, blocking);*/
     else if(UPLO(*uplo)==LO)  internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,false,false, ColMajor,true,false, ColMajor>
-                                ::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha);
+                                ::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha, blocking);
     else                      return 0;
   }
   else
   {
     return 0;
@@ -496,31 +559,32 @@
   return 0;
 }
 
 // c = alpha*a*conj(a') + beta*c  for op = 'N'or'n'
 // c = alpha*conj(a')*a + beta*c  for op  = 'C'or'c'
-int EIGEN_BLAS_FUNC(herk)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pbeta, RealScalar *pc, int *ldc)
-{
-  typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&);
-  static functype func[8];
-
-  static bool init = false;
-  if(!init)
-  {
-    for(int k=0; k<8; ++k)
-      func[k] = 0;
-
-    func[NOTR  | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor,Upper>::run);
-    func[ADJ   | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor,Upper>::run);
-
-    func[NOTR  | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor,Lower>::run);
-    func[ADJ   | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor,Lower>::run);
-
-    init = true;
-  }
-
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
+int EIGEN_BLAS_FUNC(herk)(const char *uplo, const char *op, const int *n, const int *k,
+                          const RealScalar *palpha, const RealScalar *pa, const int *lda, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
+{
+//   std::cerr << "in herk " << *uplo << " " << *op << " " << *n << " " << *k << " " << *palpha << " " << *lda << " " << *pbeta << " " << *ldc << "\n";
+
+  typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&, internal::level3_blocking<Scalar,Scalar>&);
+  static const functype func[8] = {
+    // array index: NOTR  | (UP << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor,Upper>::run),
+    0,
+    // array index: ADJ   | (UP << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor,Upper>::run),
+    0,
+    // array index: NOTR  | (LO << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor,Lower>::run),
+    0,
+    // array index: ADJ   | (LO << 2)
+    (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor,Lower>::run),
+    0
+  };
+
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
   RealScalar alpha = *palpha;
   RealScalar beta  = *pbeta;
 
 //   std::cerr << "in herk " << *uplo << " " << *op << " " << *n << " " << *k << " " << alpha << " " << *lda << " " << beta << " " << *ldc << "\n";
@@ -543,43 +607,47 @@
       if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
       else                matrix(c, *n, *n, *ldc).triangularView<StrictlyUpper>() *= beta;
     else
       if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
       else                matrix(c, *n, *n, *ldc).triangularView<StrictlyLower>() *= beta;
-  
+
     if(beta!=Scalar(0))
     {
       matrix(c, *n, *n, *ldc).diagonal().real() *= beta;
       matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
     }
   }
 
   if(*k>0 && alpha!=RealScalar(0))
   {
-    func[code](*n, *k, a, *lda, a, *lda, c, *ldc, alpha);
+    internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*n,*n,*k,1,false);
+    func[code](*n, *k, a, *lda, a, *lda, c, *ldc, alpha, blocking);
     matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
   }
   return 0;
 }
 
 // c = alpha*a*conj(b') + conj(alpha)*b*conj(a') + beta*c,  for op = 'N'or'n'
 // c = alpha*conj(a')*b + conj(alpha)*conj(b')*a + beta*c,  for op = 'C'or'c'
-int EIGEN_BLAS_FUNC(her2k)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
+int EIGEN_BLAS_FUNC(her2k)(const char *uplo, const char *op, const int *n, const int *k,
+                           const RealScalar *palpha, const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
 {
-  Scalar* a = reinterpret_cast<Scalar*>(pa);
-  Scalar* b = reinterpret_cast<Scalar*>(pb);
+  const Scalar* a = reinterpret_cast<const Scalar*>(pa);
+  const Scalar* b = reinterpret_cast<const Scalar*>(pb);
   Scalar* c = reinterpret_cast<Scalar*>(pc);
-  Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
+  Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
   RealScalar beta  = *pbeta;
+
+//   std::cerr << "in her2k " << *uplo << " " << *op << " " << *n << " " << *k << " " << alpha << " " << *lda << " " << *ldb << " " << beta << " " << *ldc << "\n";
 
   int info = 0;
   if(UPLO(*uplo)==INVALID)                                            info = 1;
   else if((OP(*op)==INVALID) || (OP(*op)==TR))                        info = 2;
   else if(*n<0)                                                       info = 3;
   else if(*k<0)                                                       info = 4;
   else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k))                     info = 7;
-  else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k))                     info = 9;
+  else if(*ldb<std::max(1,(OP(*op)==NOTR)?*n:*k))                     info = 9;
   else if(*ldc<std::max(1,*n))                                        info = 12;
   if(info)
     return xerbla_(SCALAR_SUFFIX_UP"HER2K",&info,6);
 
   if(beta!=RealScalar(1))

DELETED 3rd_party/eigen/blas/lsame.f
Index: 3rd_party/eigen/blas/lsame.f
==================================================================
--- 3rd_party/eigen/blas/lsame.f
+++ 3rd_party/eigen/blas/lsame.f
@@ -1,85 +0,0 @@
-      LOGICAL FUNCTION LSAME(CA,CB)
-*
-*  -- LAPACK auxiliary routine (version 3.1) --
-*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
-*     November 2006
-*
-*     .. Scalar Arguments ..
-      CHARACTER CA,CB
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  LSAME returns .TRUE. if CA is the same letter as CB regardless of
-*  case.
-*
-*  Arguments
-*  =========
-*
-*  CA      (input) CHARACTER*1
-*
-*  CB      (input) CHARACTER*1
-*          CA and CB specify the single characters to be compared.
-*
-* =====================================================================
-*
-*     .. Intrinsic Functions ..
-      INTRINSIC ICHAR
-*     ..
-*     .. Local Scalars ..
-      INTEGER INTA,INTB,ZCODE
-*     ..
-*
-*     Test if the characters are equal
-*
-      LSAME = CA .EQ. CB
-      IF (LSAME) RETURN
-*
-*     Now test for equivalence if both characters are alphabetic.
-*
-      ZCODE = ICHAR('Z')
-*
-*     Use 'Z' rather than 'A' so that ASCII can be detected on Prime
-*     machines, on which ICHAR returns a value with bit 8 set.
-*     ICHAR('A') on Prime machines returns 193 which is the same as
-*     ICHAR('A') on an EBCDIC machine.
-*
-      INTA = ICHAR(CA)
-      INTB = ICHAR(CB)
-*
-      IF (ZCODE.EQ.90 .OR. ZCODE.EQ.122) THEN
-*
-*        ASCII is assumed - ZCODE is the ASCII code of either lower or
-*        upper case 'Z'.
-*
-          IF (INTA.GE.97 .AND. INTA.LE.122) INTA = INTA - 32
-          IF (INTB.GE.97 .AND. INTB.LE.122) INTB = INTB - 32
-*
-      ELSE IF (ZCODE.EQ.233 .OR. ZCODE.EQ.169) THEN
-*
-*        EBCDIC is assumed - ZCODE is the EBCDIC code of either lower or
-*        upper case 'Z'.
-*
-          IF (INTA.GE.129 .AND. INTA.LE.137 .OR.
-     +        INTA.GE.145 .AND. INTA.LE.153 .OR.
-     +        INTA.GE.162 .AND. INTA.LE.169) INTA = INTA + 64
-          IF (INTB.GE.129 .AND. INTB.LE.137 .OR.
-     +        INTB.GE.145 .AND. INTB.LE.153 .OR.
-     +        INTB.GE.162 .AND. INTB.LE.169) INTB = INTB + 64
-*
-      ELSE IF (ZCODE.EQ.218 .OR. ZCODE.EQ.250) THEN
-*
-*        ASCII is assumed, on Prime machines - ZCODE is the ASCII code
-*        plus 128 of either lower or upper case 'Z'.
-*
-          IF (INTA.GE.225 .AND. INTA.LE.250) INTA = INTA - 32
-          IF (INTB.GE.225 .AND. INTB.LE.250) INTB = INTB - 32
-      END IF
-      LSAME = INTA .EQ. INTB
-*
-*     RETURN
-*
-*     End of LSAME
-*
-      END

Index: 3rd_party/eigen/blas/single.cpp
==================================================================
--- 3rd_party/eigen/blas/single.cpp
+++ 3rd_party/eigen/blas/single.cpp
@@ -17,6 +17,6 @@
 #include "level2_impl.h"
 #include "level2_real_impl.h"
 #include "level3_impl.h"
 
 float BLASFUNC(sdsdot)(int* n, float* alpha, float* x, int* incx, float* y, int* incy)
-{ return *alpha + BLASFUNC(dsdot)(n, x, incx, y, incy); }
+{ return double(*alpha) + BLASFUNC(dsdot)(n, x, incx, y, incy); }

DELETED 3rd_party/eigen/blas/srotm.f
Index: 3rd_party/eigen/blas/srotm.f
==================================================================
--- 3rd_party/eigen/blas/srotm.f
+++ 3rd_party/eigen/blas/srotm.f
@@ -1,148 +0,0 @@
-      SUBROUTINE SROTM(N,SX,INCX,SY,INCY,SPARAM)
-*     .. Scalar Arguments ..
-      INTEGER INCX,INCY,N
-*     ..
-*     .. Array Arguments ..
-      REAL SPARAM(5),SX(*),SY(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*     APPLY THE MODIFIED GIVENS TRANSFORMATION, H, TO THE 2 BY N MATRIX
-*
-*     (SX**T) , WHERE **T INDICATES TRANSPOSE. THE ELEMENTS OF SX ARE IN
-*     (DX**T)
-*
-*     SX(LX+I*INCX), I = 0 TO N-1, WHERE LX = 1 IF INCX .GE. 0, ELSE
-*     LX = (-INCX)*N, AND SIMILARLY FOR SY USING USING LY AND INCY.
-*     WITH SPARAM(1)=SFLAG, H HAS ONE OF THE FOLLOWING FORMS..
-*
-*     SFLAG=-1.E0     SFLAG=0.E0        SFLAG=1.E0     SFLAG=-2.E0
-*
-*       (SH11  SH12)    (1.E0  SH12)    (SH11  1.E0)    (1.E0  0.E0)
-*     H=(          )    (          )    (          )    (          )
-*       (SH21  SH22),   (SH21  1.E0),   (-1.E0 SH22),   (0.E0  1.E0).
-*     SEE  SROTMG FOR A DESCRIPTION OF DATA STORAGE IN SPARAM.
-*
-*
-*  Arguments
-*  =========
-*
-*  N      (input) INTEGER
-*         number of elements in input vector(s)
-*
-*  SX     (input/output) REAL array, dimension N
-*         double precision vector with N elements
-*
-*  INCX   (input) INTEGER
-*         storage spacing between elements of SX
-*
-*  SY     (input/output) REAL array, dimension N
-*         double precision vector with N elements
-*
-*  INCY   (input) INTEGER
-*         storage spacing between elements of SY
-*
-*  SPARAM (input/output)  REAL array, dimension 5
-*     SPARAM(1)=SFLAG
-*     SPARAM(2)=SH11
-*     SPARAM(3)=SH21
-*     SPARAM(4)=SH12
-*     SPARAM(5)=SH22
-*
-*  =====================================================================
-*
-*     .. Local Scalars ..
-      REAL SFLAG,SH11,SH12,SH21,SH22,TWO,W,Z,ZERO
-      INTEGER I,KX,KY,NSTEPS
-*     ..
-*     .. Data statements ..
-      DATA ZERO,TWO/0.E0,2.E0/
-*     ..
-*
-      SFLAG = SPARAM(1)
-      IF (N.LE.0 .OR. (SFLAG+TWO.EQ.ZERO)) GO TO 140
-      IF (.NOT. (INCX.EQ.INCY.AND.INCX.GT.0)) GO TO 70
-*
-      NSTEPS = N*INCX
-      IF (SFLAG) 50,10,30
-   10 CONTINUE
-      SH12 = SPARAM(4)
-      SH21 = SPARAM(3)
-      DO 20 I = 1,NSTEPS,INCX
-          W = SX(I)
-          Z = SY(I)
-          SX(I) = W + Z*SH12
-          SY(I) = W*SH21 + Z
-   20 CONTINUE
-      GO TO 140
-   30 CONTINUE
-      SH11 = SPARAM(2)
-      SH22 = SPARAM(5)
-      DO 40 I = 1,NSTEPS,INCX
-          W = SX(I)
-          Z = SY(I)
-          SX(I) = W*SH11 + Z
-          SY(I) = -W + SH22*Z
-   40 CONTINUE
-      GO TO 140
-   50 CONTINUE
-      SH11 = SPARAM(2)
-      SH12 = SPARAM(4)
-      SH21 = SPARAM(3)
-      SH22 = SPARAM(5)
-      DO 60 I = 1,NSTEPS,INCX
-          W = SX(I)
-          Z = SY(I)
-          SX(I) = W*SH11 + Z*SH12
-          SY(I) = W*SH21 + Z*SH22
-   60 CONTINUE
-      GO TO 140
-   70 CONTINUE
-      KX = 1
-      KY = 1
-      IF (INCX.LT.0) KX = 1 + (1-N)*INCX
-      IF (INCY.LT.0) KY = 1 + (1-N)*INCY
-*
-      IF (SFLAG) 120,80,100
-   80 CONTINUE
-      SH12 = SPARAM(4)
-      SH21 = SPARAM(3)
-      DO 90 I = 1,N
-          W = SX(KX)
-          Z = SY(KY)
-          SX(KX) = W + Z*SH12
-          SY(KY) = W*SH21 + Z
-          KX = KX + INCX
-          KY = KY + INCY
-   90 CONTINUE
-      GO TO 140
-  100 CONTINUE
-      SH11 = SPARAM(2)
-      SH22 = SPARAM(5)
-      DO 110 I = 1,N
-          W = SX(KX)
-          Z = SY(KY)
-          SX(KX) = W*SH11 + Z
-          SY(KY) = -W + SH22*Z
-          KX = KX + INCX
-          KY = KY + INCY
-  110 CONTINUE
-      GO TO 140
-  120 CONTINUE
-      SH11 = SPARAM(2)
-      SH12 = SPARAM(4)
-      SH21 = SPARAM(3)
-      SH22 = SPARAM(5)
-      DO 130 I = 1,N
-          W = SX(KX)
-          Z = SY(KY)
-          SX(KX) = W*SH11 + Z*SH12
-          SY(KY) = W*SH21 + Z*SH22
-          KX = KX + INCX
-          KY = KY + INCY
-  130 CONTINUE
-  140 CONTINUE
-      RETURN
-      END

DELETED 3rd_party/eigen/blas/srotmg.f
Index: 3rd_party/eigen/blas/srotmg.f
==================================================================
--- 3rd_party/eigen/blas/srotmg.f
+++ 3rd_party/eigen/blas/srotmg.f
@@ -1,208 +0,0 @@
-      SUBROUTINE SROTMG(SD1,SD2,SX1,SY1,SPARAM)
-*     .. Scalar Arguments ..
-      REAL SD1,SD2,SX1,SY1
-*     ..
-*     .. Array Arguments ..
-      REAL SPARAM(5)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*     CONSTRUCT THE MODIFIED GIVENS TRANSFORMATION MATRIX H WHICH ZEROS
-*     THE SECOND COMPONENT OF THE 2-VECTOR  (SQRT(SD1)*SX1,SQRT(SD2)*
-*     SY2)**T.
-*     WITH SPARAM(1)=SFLAG, H HAS ONE OF THE FOLLOWING FORMS..
-*
-*     SFLAG=-1.E0     SFLAG=0.E0        SFLAG=1.E0     SFLAG=-2.E0
-*
-*       (SH11  SH12)    (1.E0  SH12)    (SH11  1.E0)    (1.E0  0.E0)
-*     H=(          )    (          )    (          )    (          )
-*       (SH21  SH22),   (SH21  1.E0),   (-1.E0 SH22),   (0.E0  1.E0).
-*     LOCATIONS 2-4 OF SPARAM CONTAIN SH11,SH21,SH12, AND SH22
-*     RESPECTIVELY. (VALUES OF 1.E0, -1.E0, OR 0.E0 IMPLIED BY THE
-*     VALUE OF SPARAM(1) ARE NOT STORED IN SPARAM.)
-*
-*     THE VALUES OF GAMSQ AND RGAMSQ SET IN THE DATA STATEMENT MAY BE
-*     INEXACT.  THIS IS OK AS THEY ARE ONLY USED FOR TESTING THE SIZE
-*     OF SD1 AND SD2.  ALL ACTUAL SCALING OF DATA IS DONE USING GAM.
-*
-*
-*  Arguments
-*  =========
-*
-*
-*  SD1    (input/output) REAL
-*
-*  SD2    (input/output) REAL
-*
-*  SX1    (input/output) REAL
-*
-*  SY1    (input) REAL
-*
-*
-*  SPARAM (input/output)  REAL array, dimension 5
-*     SPARAM(1)=SFLAG
-*     SPARAM(2)=SH11
-*     SPARAM(3)=SH21
-*     SPARAM(4)=SH12
-*     SPARAM(5)=SH22
-*
-*  =====================================================================
-*
-*     .. Local Scalars ..
-      REAL GAM,GAMSQ,ONE,RGAMSQ,SFLAG,SH11,SH12,SH21,SH22,SP1,SP2,SQ1,
-     +     SQ2,STEMP,SU,TWO,ZERO
-      INTEGER IGO
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC ABS
-*     ..
-*     .. Data statements ..
-*
-      DATA ZERO,ONE,TWO/0.E0,1.E0,2.E0/
-      DATA GAM,GAMSQ,RGAMSQ/4096.E0,1.67772E7,5.96046E-8/
-*     ..
-
-      IF (.NOT.SD1.LT.ZERO) GO TO 10
-*       GO ZERO-H-D-AND-SX1..
-      GO TO 60
-   10 CONTINUE
-*     CASE-SD1-NONNEGATIVE
-      SP2 = SD2*SY1
-      IF (.NOT.SP2.EQ.ZERO) GO TO 20
-      SFLAG = -TWO
-      GO TO 260
-*     REGULAR-CASE..
-   20 CONTINUE
-      SP1 = SD1*SX1
-      SQ2 = SP2*SY1
-      SQ1 = SP1*SX1
-*
-      IF (.NOT.ABS(SQ1).GT.ABS(SQ2)) GO TO 40
-      SH21 = -SY1/SX1
-      SH12 = SP2/SP1
-*
-      SU = ONE - SH12*SH21
-*
-      IF (.NOT.SU.LE.ZERO) GO TO 30
-*         GO ZERO-H-D-AND-SX1..
-      GO TO 60
-   30 CONTINUE
-      SFLAG = ZERO
-      SD1 = SD1/SU
-      SD2 = SD2/SU
-      SX1 = SX1*SU
-*         GO SCALE-CHECK..
-      GO TO 100
-   40 CONTINUE
-      IF (.NOT.SQ2.LT.ZERO) GO TO 50
-*         GO ZERO-H-D-AND-SX1..
-      GO TO 60
-   50 CONTINUE
-      SFLAG = ONE
-      SH11 = SP1/SP2
-      SH22 = SX1/SY1
-      SU = ONE + SH11*SH22
-      STEMP = SD2/SU
-      SD2 = SD1/SU
-      SD1 = STEMP
-      SX1 = SY1*SU
-*         GO SCALE-CHECK
-      GO TO 100
-*     PROCEDURE..ZERO-H-D-AND-SX1..
-   60 CONTINUE
-      SFLAG = -ONE
-      SH11 = ZERO
-      SH12 = ZERO
-      SH21 = ZERO
-      SH22 = ZERO
-*
-      SD1 = ZERO
-      SD2 = ZERO
-      SX1 = ZERO
-*         RETURN..
-      GO TO 220
-*     PROCEDURE..FIX-H..
-   70 CONTINUE
-      IF (.NOT.SFLAG.GE.ZERO) GO TO 90
-*
-      IF (.NOT.SFLAG.EQ.ZERO) GO TO 80
-      SH11 = ONE
-      SH22 = ONE
-      SFLAG = -ONE
-      GO TO 90
-   80 CONTINUE
-      SH21 = -ONE
-      SH12 = ONE
-      SFLAG = -ONE
-   90 CONTINUE
-      GO TO IGO(120,150,180,210)
-*     PROCEDURE..SCALE-CHECK
-  100 CONTINUE
-  110 CONTINUE
-      IF (.NOT.SD1.LE.RGAMSQ) GO TO 130
-      IF (SD1.EQ.ZERO) GO TO 160
-      ASSIGN 120 TO IGO
-*              FIX-H..
-      GO TO 70
-  120 CONTINUE
-      SD1 = SD1*GAM**2
-      SX1 = SX1/GAM
-      SH11 = SH11/GAM
-      SH12 = SH12/GAM
-      GO TO 110
-  130 CONTINUE
-  140 CONTINUE
-      IF (.NOT.SD1.GE.GAMSQ) GO TO 160
-      ASSIGN 150 TO IGO
-*              FIX-H..
-      GO TO 70
-  150 CONTINUE
-      SD1 = SD1/GAM**2
-      SX1 = SX1*GAM
-      SH11 = SH11*GAM
-      SH12 = SH12*GAM
-      GO TO 140
-  160 CONTINUE
-  170 CONTINUE
-      IF (.NOT.ABS(SD2).LE.RGAMSQ) GO TO 190
-      IF (SD2.EQ.ZERO) GO TO 220
-      ASSIGN 180 TO IGO
-*              FIX-H..
-      GO TO 70
-  180 CONTINUE
-      SD2 = SD2*GAM**2
-      SH21 = SH21/GAM
-      SH22 = SH22/GAM
-      GO TO 170
-  190 CONTINUE
-  200 CONTINUE
-      IF (.NOT.ABS(SD2).GE.GAMSQ) GO TO 220
-      ASSIGN 210 TO IGO
-*              FIX-H..
-      GO TO 70
-  210 CONTINUE
-      SD2 = SD2/GAM**2
-      SH21 = SH21*GAM
-      SH22 = SH22*GAM
-      GO TO 200
-  220 CONTINUE
-      IF (SFLAG) 250,230,240
-  230 CONTINUE
-      SPARAM(3) = SH21
-      SPARAM(4) = SH12
-      GO TO 260
-  240 CONTINUE
-      SPARAM(2) = SH11
-      SPARAM(5) = SH22
-      GO TO 260
-  250 CONTINUE
-      SPARAM(2) = SH11
-      SPARAM(3) = SH21
-      SPARAM(4) = SH12
-      SPARAM(5) = SH22
-  260 CONTINUE
-      SPARAM(1) = SFLAG
-      RETURN
-      END

DELETED 3rd_party/eigen/blas/ssbmv.f
Index: 3rd_party/eigen/blas/ssbmv.f
==================================================================
--- 3rd_party/eigen/blas/ssbmv.f
+++ 3rd_party/eigen/blas/ssbmv.f
@@ -1,306 +0,0 @@
-      SUBROUTINE SSBMV(UPLO,N,K,ALPHA,A,LDA,X,INCX,BETA,Y,INCY)
-*     .. Scalar Arguments ..
-      REAL ALPHA,BETA
-      INTEGER INCX,INCY,K,LDA,N
-      CHARACTER UPLO
-*     ..
-*     .. Array Arguments ..
-      REAL A(LDA,*),X(*),Y(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  SSBMV  performs the matrix-vector  operation
-*
-*     y := alpha*A*x + beta*y,
-*
-*  where alpha and beta are scalars, x and y are n element vectors and
-*  A is an n by n symmetric band matrix, with k super-diagonals.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the upper or lower
-*           triangular part of the band matrix A is being supplied as
-*           follows:
-*
-*              UPLO = 'U' or 'u'   The upper triangular part of A is
-*                                  being supplied.
-*
-*              UPLO = 'L' or 'l'   The lower triangular part of A is
-*                                  being supplied.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  K      - INTEGER.
-*           On entry, K specifies the number of super-diagonals of the
-*           matrix A. K must satisfy  0 .le. K.
-*           Unchanged on exit.
-*
-*  ALPHA  - REAL            .
-*           On entry, ALPHA specifies the scalar alpha.
-*           Unchanged on exit.
-*
-*  A      - REAL             array of DIMENSION ( LDA, n ).
-*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 )
-*           by n part of the array A must contain the upper triangular
-*           band part of the symmetric matrix, supplied column by
-*           column, with the leading diagonal of the matrix in row
-*           ( k + 1 ) of the array, the first super-diagonal starting at
-*           position 2 in row k, and so on. The top left k by k triangle
-*           of the array A is not referenced.
-*           The following program segment will transfer the upper
-*           triangular part of a symmetric band matrix from conventional
-*           full matrix storage to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = K + 1 - J
-*                    DO 10, I = MAX( 1, J - K ), J
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 )
-*           by n part of the array A must contain the lower triangular
-*           band part of the symmetric matrix, supplied column by
-*           column, with the leading diagonal of the matrix in row 1 of
-*           the array, the first sub-diagonal starting at position 1 in
-*           row 2, and so on. The bottom right k by k triangle of the
-*           array A is not referenced.
-*           The following program segment will transfer the lower
-*           triangular part of a symmetric band matrix from conventional
-*           full matrix storage to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = 1 - J
-*                    DO 10, I = J, MIN( N, J + K )
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Unchanged on exit.
-*
-*  LDA    - INTEGER.
-*           On entry, LDA specifies the first dimension of A as declared
-*           in the calling (sub) program. LDA must be at least
-*           ( k + 1 ).
-*           Unchanged on exit.
-*
-*  X      - REAL             array of DIMENSION at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the
-*           vector x.
-*           Unchanged on exit.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  BETA   - REAL            .
-*           On entry, BETA specifies the scalar beta.
-*           Unchanged on exit.
-*
-*  Y      - REAL             array of DIMENSION at least
-*           ( 1 + ( n - 1 )*abs( INCY ) ).
-*           Before entry, the incremented array Y must contain the
-*           vector y. On exit, Y is overwritten by the updated vector y.
-*
-*  INCY   - INTEGER.
-*           On entry, INCY specifies the increment for the elements of
-*           Y. INCY must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      REAL ONE,ZERO
-      PARAMETER (ONE=1.0E+0,ZERO=0.0E+0)
-*     ..
-*     .. Local Scalars ..
-      REAL TEMP1,TEMP2
-      INTEGER I,INFO,IX,IY,J,JX,JY,KPLUS1,KX,KY,L
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC MAX,MIN
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (N.LT.0) THEN
-          INFO = 2
-      ELSE IF (K.LT.0) THEN
-          INFO = 3
-      ELSE IF (LDA.LT. (K+1)) THEN
-          INFO = 6
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 8
-      ELSE IF (INCY.EQ.0) THEN
-          INFO = 11
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('SSBMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF ((N.EQ.0) .OR. ((ALPHA.EQ.ZERO).AND. (BETA.EQ.ONE))) RETURN
-*
-*     Set up the start points in  X  and  Y.
-*
-      IF (INCX.GT.0) THEN
-          KX = 1
-      ELSE
-          KX = 1 - (N-1)*INCX
-      END IF
-      IF (INCY.GT.0) THEN
-          KY = 1
-      ELSE
-          KY = 1 - (N-1)*INCY
-      END IF
-*
-*     Start the operations. In this version the elements of the array A
-*     are accessed sequentially with one pass through A.
-*
-*     First form  y := beta*y.
-*
-      IF (BETA.NE.ONE) THEN
-          IF (INCY.EQ.1) THEN
-              IF (BETA.EQ.ZERO) THEN
-                  DO 10 I = 1,N
-                      Y(I) = ZERO
-   10             CONTINUE
-              ELSE
-                  DO 20 I = 1,N
-                      Y(I) = BETA*Y(I)
-   20             CONTINUE
-              END IF
-          ELSE
-              IY = KY
-              IF (BETA.EQ.ZERO) THEN
-                  DO 30 I = 1,N
-                      Y(IY) = ZERO
-                      IY = IY + INCY
-   30             CONTINUE
-              ELSE
-                  DO 40 I = 1,N
-                      Y(IY) = BETA*Y(IY)
-                      IY = IY + INCY
-   40             CONTINUE
-              END IF
-          END IF
-      END IF
-      IF (ALPHA.EQ.ZERO) RETURN
-      IF (LSAME(UPLO,'U')) THEN
-*
-*        Form  y  when upper triangle of A is stored.
-*
-          KPLUS1 = K + 1
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 60 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  L = KPLUS1 - J
-                  DO 50 I = MAX(1,J-K),J - 1
-                      Y(I) = Y(I) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + A(L+I,J)*X(I)
-   50             CONTINUE
-                  Y(J) = Y(J) + TEMP1*A(KPLUS1,J) + ALPHA*TEMP2
-   60         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 80 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  IX = KX
-                  IY = KY
-                  L = KPLUS1 - J
-                  DO 70 I = MAX(1,J-K),J - 1
-                      Y(IY) = Y(IY) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + A(L+I,J)*X(IX)
-                      IX = IX + INCX
-                      IY = IY + INCY
-   70             CONTINUE
-                  Y(JY) = Y(JY) + TEMP1*A(KPLUS1,J) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  IF (J.GT.K) THEN
-                      KX = KX + INCX
-                      KY = KY + INCY
-                  END IF
-   80         CONTINUE
-          END IF
-      ELSE
-*
-*        Form  y  when lower triangle of A is stored.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 100 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  Y(J) = Y(J) + TEMP1*A(1,J)
-                  L = 1 - J
-                  DO 90 I = J + 1,MIN(N,J+K)
-                      Y(I) = Y(I) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + A(L+I,J)*X(I)
-   90             CONTINUE
-                  Y(J) = Y(J) + ALPHA*TEMP2
-  100         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 120 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  Y(JY) = Y(JY) + TEMP1*A(1,J)
-                  L = 1 - J
-                  IX = JX
-                  IY = JY
-                  DO 110 I = J + 1,MIN(N,J+K)
-                      IX = IX + INCX
-                      IY = IY + INCY
-                      Y(IY) = Y(IY) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + A(L+I,J)*X(IX)
-  110             CONTINUE
-                  Y(JY) = Y(JY) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-  120         CONTINUE
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of SSBMV .
-*
-      END

DELETED 3rd_party/eigen/blas/sspmv.f
Index: 3rd_party/eigen/blas/sspmv.f
==================================================================
--- 3rd_party/eigen/blas/sspmv.f
+++ 3rd_party/eigen/blas/sspmv.f
@@ -1,265 +0,0 @@
-      SUBROUTINE SSPMV(UPLO,N,ALPHA,AP,X,INCX,BETA,Y,INCY)
-*     .. Scalar Arguments ..
-      REAL ALPHA,BETA
-      INTEGER INCX,INCY,N
-      CHARACTER UPLO
-*     ..
-*     .. Array Arguments ..
-      REAL AP(*),X(*),Y(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  SSPMV  performs the matrix-vector operation
-*
-*     y := alpha*A*x + beta*y,
-*
-*  where alpha and beta are scalars, x and y are n element vectors and
-*  A is an n by n symmetric matrix, supplied in packed form.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the upper or lower
-*           triangular part of the matrix A is supplied in the packed
-*           array AP as follows:
-*
-*              UPLO = 'U' or 'u'   The upper triangular part of A is
-*                                  supplied in AP.
-*
-*              UPLO = 'L' or 'l'   The lower triangular part of A is
-*                                  supplied in AP.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  ALPHA  - REAL            .
-*           On entry, ALPHA specifies the scalar alpha.
-*           Unchanged on exit.
-*
-*  AP     - REAL             array of DIMENSION at least
-*           ( ( n*( n + 1 ) )/2 ).
-*           Before entry with UPLO = 'U' or 'u', the array AP must
-*           contain the upper triangular part of the symmetric matrix
-*           packed sequentially, column by column, so that AP( 1 )
-*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-*           and a( 2, 2 ) respectively, and so on.
-*           Before entry with UPLO = 'L' or 'l', the array AP must
-*           contain the lower triangular part of the symmetric matrix
-*           packed sequentially, column by column, so that AP( 1 )
-*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-*           and a( 3, 1 ) respectively, and so on.
-*           Unchanged on exit.
-*
-*  X      - REAL             array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the n
-*           element vector x.
-*           Unchanged on exit.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  BETA   - REAL            .
-*           On entry, BETA specifies the scalar beta. When BETA is
-*           supplied as zero then Y need not be set on input.
-*           Unchanged on exit.
-*
-*  Y      - REAL             array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCY ) ).
-*           Before entry, the incremented array Y must contain the n
-*           element vector y. On exit, Y is overwritten by the updated
-*           vector y.
-*
-*  INCY   - INTEGER.
-*           On entry, INCY specifies the increment for the elements of
-*           Y. INCY must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      REAL ONE,ZERO
-      PARAMETER (ONE=1.0E+0,ZERO=0.0E+0)
-*     ..
-*     .. Local Scalars ..
-      REAL TEMP1,TEMP2
-      INTEGER I,INFO,IX,IY,J,JX,JY,K,KK,KX,KY
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (N.LT.0) THEN
-          INFO = 2
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 6
-      ELSE IF (INCY.EQ.0) THEN
-          INFO = 9
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('SSPMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF ((N.EQ.0) .OR. ((ALPHA.EQ.ZERO).AND. (BETA.EQ.ONE))) RETURN
-*
-*     Set up the start points in  X  and  Y.
-*
-      IF (INCX.GT.0) THEN
-          KX = 1
-      ELSE
-          KX = 1 - (N-1)*INCX
-      END IF
-      IF (INCY.GT.0) THEN
-          KY = 1
-      ELSE
-          KY = 1 - (N-1)*INCY
-      END IF
-*
-*     Start the operations. In this version the elements of the array AP
-*     are accessed sequentially with one pass through AP.
-*
-*     First form  y := beta*y.
-*
-      IF (BETA.NE.ONE) THEN
-          IF (INCY.EQ.1) THEN
-              IF (BETA.EQ.ZERO) THEN
-                  DO 10 I = 1,N
-                      Y(I) = ZERO
-   10             CONTINUE
-              ELSE
-                  DO 20 I = 1,N
-                      Y(I) = BETA*Y(I)
-   20             CONTINUE
-              END IF
-          ELSE
-              IY = KY
-              IF (BETA.EQ.ZERO) THEN
-                  DO 30 I = 1,N
-                      Y(IY) = ZERO
-                      IY = IY + INCY
-   30             CONTINUE
-              ELSE
-                  DO 40 I = 1,N
-                      Y(IY) = BETA*Y(IY)
-                      IY = IY + INCY
-   40             CONTINUE
-              END IF
-          END IF
-      END IF
-      IF (ALPHA.EQ.ZERO) RETURN
-      KK = 1
-      IF (LSAME(UPLO,'U')) THEN
-*
-*        Form  y  when AP contains the upper triangle.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 60 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  K = KK
-                  DO 50 I = 1,J - 1
-                      Y(I) = Y(I) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + AP(K)*X(I)
-                      K = K + 1
-   50             CONTINUE
-                  Y(J) = Y(J) + TEMP1*AP(KK+J-1) + ALPHA*TEMP2
-                  KK = KK + J
-   60         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 80 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  IX = KX
-                  IY = KY
-                  DO 70 K = KK,KK + J - 2
-                      Y(IY) = Y(IY) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + AP(K)*X(IX)
-                      IX = IX + INCX
-                      IY = IY + INCY
-   70             CONTINUE
-                  Y(JY) = Y(JY) + TEMP1*AP(KK+J-1) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  KK = KK + J
-   80         CONTINUE
-          END IF
-      ELSE
-*
-*        Form  y  when AP contains the lower triangle.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 100 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  Y(J) = Y(J) + TEMP1*AP(KK)
-                  K = KK + 1
-                  DO 90 I = J + 1,N
-                      Y(I) = Y(I) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + AP(K)*X(I)
-                      K = K + 1
-   90             CONTINUE
-                  Y(J) = Y(J) + ALPHA*TEMP2
-                  KK = KK + (N-J+1)
-  100         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 120 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  Y(JY) = Y(JY) + TEMP1*AP(KK)
-                  IX = JX
-                  IY = JY
-                  DO 110 K = KK + 1,KK + N - J
-                      IX = IX + INCX
-                      IY = IY + INCY
-                      Y(IY) = Y(IY) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + AP(K)*X(IX)
-  110             CONTINUE
-                  Y(JY) = Y(JY) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  KK = KK + (N-J+1)
-  120         CONTINUE
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of SSPMV .
-*
-      END

DELETED 3rd_party/eigen/blas/stbmv.f
Index: 3rd_party/eigen/blas/stbmv.f
==================================================================
--- 3rd_party/eigen/blas/stbmv.f
+++ 3rd_party/eigen/blas/stbmv.f
@@ -1,335 +0,0 @@
-      SUBROUTINE STBMV(UPLO,TRANS,DIAG,N,K,A,LDA,X,INCX)
-*     .. Scalar Arguments ..
-      INTEGER INCX,K,LDA,N
-      CHARACTER DIAG,TRANS,UPLO
-*     ..
-*     .. Array Arguments ..
-      REAL A(LDA,*),X(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  STBMV  performs one of the matrix-vector operations
-*
-*     x := A*x,   or   x := A'*x,
-*
-*  where x is an n element vector and  A is an n by n unit, or non-unit,
-*  upper or lower triangular band matrix, with ( k + 1 ) diagonals.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the matrix is an upper or
-*           lower triangular matrix as follows:
-*
-*              UPLO = 'U' or 'u'   A is an upper triangular matrix.
-*
-*              UPLO = 'L' or 'l'   A is a lower triangular matrix.
-*
-*           Unchanged on exit.
-*
-*  TRANS  - CHARACTER*1.
-*           On entry, TRANS specifies the operation to be performed as
-*           follows:
-*
-*              TRANS = 'N' or 'n'   x := A*x.
-*
-*              TRANS = 'T' or 't'   x := A'*x.
-*
-*              TRANS = 'C' or 'c'   x := A'*x.
-*
-*           Unchanged on exit.
-*
-*  DIAG   - CHARACTER*1.
-*           On entry, DIAG specifies whether or not A is unit
-*           triangular as follows:
-*
-*              DIAG = 'U' or 'u'   A is assumed to be unit triangular.
-*
-*              DIAG = 'N' or 'n'   A is not assumed to be unit
-*                                  triangular.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  K      - INTEGER.
-*           On entry with UPLO = 'U' or 'u', K specifies the number of
-*           super-diagonals of the matrix A.
-*           On entry with UPLO = 'L' or 'l', K specifies the number of
-*           sub-diagonals of the matrix A.
-*           K must satisfy  0 .le. K.
-*           Unchanged on exit.
-*
-*  A      - REAL             array of DIMENSION ( LDA, n ).
-*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 )
-*           by n part of the array A must contain the upper triangular
-*           band part of the matrix of coefficients, supplied column by
-*           column, with the leading diagonal of the matrix in row
-*           ( k + 1 ) of the array, the first super-diagonal starting at
-*           position 2 in row k, and so on. The top left k by k triangle
-*           of the array A is not referenced.
-*           The following program segment will transfer an upper
-*           triangular band matrix from conventional full matrix storage
-*           to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = K + 1 - J
-*                    DO 10, I = MAX( 1, J - K ), J
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 )
-*           by n part of the array A must contain the lower triangular
-*           band part of the matrix of coefficients, supplied column by
-*           column, with the leading diagonal of the matrix in row 1 of
-*           the array, the first sub-diagonal starting at position 1 in
-*           row 2, and so on. The bottom right k by k triangle of the
-*           array A is not referenced.
-*           The following program segment will transfer a lower
-*           triangular band matrix from conventional full matrix storage
-*           to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = 1 - J
-*                    DO 10, I = J, MIN( N, J + K )
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Note that when DIAG = 'U' or 'u' the elements of the array A
-*           corresponding to the diagonal elements of the matrix are not
-*           referenced, but are assumed to be unity.
-*           Unchanged on exit.
-*
-*  LDA    - INTEGER.
-*           On entry, LDA specifies the first dimension of A as declared
-*           in the calling (sub) program. LDA must be at least
-*           ( k + 1 ).
-*           Unchanged on exit.
-*
-*  X      - REAL             array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the n
-*           element vector x. On exit, X is overwritten with the
-*           tranformed vector x.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      REAL ZERO
-      PARAMETER (ZERO=0.0E+0)
-*     ..
-*     .. Local Scalars ..
-      REAL TEMP
-      INTEGER I,INFO,IX,J,JX,KPLUS1,KX,L
-      LOGICAL NOUNIT
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC MAX,MIN
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
-     +         .NOT.LSAME(TRANS,'C')) THEN
-          INFO = 2
-      ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
-          INFO = 3
-      ELSE IF (N.LT.0) THEN
-          INFO = 4
-      ELSE IF (K.LT.0) THEN
-          INFO = 5
-      ELSE IF (LDA.LT. (K+1)) THEN
-          INFO = 7
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 9
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('STBMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF (N.EQ.0) RETURN
-*
-      NOUNIT = LSAME(DIAG,'N')
-*
-*     Set up the start point in X if the increment is not unity. This
-*     will be  ( N - 1 )*INCX   too small for descending loops.
-*
-      IF (INCX.LE.0) THEN
-          KX = 1 - (N-1)*INCX
-      ELSE IF (INCX.NE.1) THEN
-          KX = 1
-      END IF
-*
-*     Start the operations. In this version the elements of A are
-*     accessed sequentially with one pass through A.
-*
-      IF (LSAME(TRANS,'N')) THEN
-*
-*         Form  x := A*x.
-*
-          IF (LSAME(UPLO,'U')) THEN
-              KPLUS1 = K + 1
-              IF (INCX.EQ.1) THEN
-                  DO 20 J = 1,N
-                      IF (X(J).NE.ZERO) THEN
-                          TEMP = X(J)
-                          L = KPLUS1 - J
-                          DO 10 I = MAX(1,J-K),J - 1
-                              X(I) = X(I) + TEMP*A(L+I,J)
-   10                     CONTINUE
-                          IF (NOUNIT) X(J) = X(J)*A(KPLUS1,J)
-                      END IF
-   20             CONTINUE
-              ELSE
-                  JX = KX
-                  DO 40 J = 1,N
-                      IF (X(JX).NE.ZERO) THEN
-                          TEMP = X(JX)
-                          IX = KX
-                          L = KPLUS1 - J
-                          DO 30 I = MAX(1,J-K),J - 1
-                              X(IX) = X(IX) + TEMP*A(L+I,J)
-                              IX = IX + INCX
-   30                     CONTINUE
-                          IF (NOUNIT) X(JX) = X(JX)*A(KPLUS1,J)
-                      END IF
-                      JX = JX + INCX
-                      IF (J.GT.K) KX = KX + INCX
-   40             CONTINUE
-              END IF
-          ELSE
-              IF (INCX.EQ.1) THEN
-                  DO 60 J = N,1,-1
-                      IF (X(J).NE.ZERO) THEN
-                          TEMP = X(J)
-                          L = 1 - J
-                          DO 50 I = MIN(N,J+K),J + 1,-1
-                              X(I) = X(I) + TEMP*A(L+I,J)
-   50                     CONTINUE
-                          IF (NOUNIT) X(J) = X(J)*A(1,J)
-                      END IF
-   60             CONTINUE
-              ELSE
-                  KX = KX + (N-1)*INCX
-                  JX = KX
-                  DO 80 J = N,1,-1
-                      IF (X(JX).NE.ZERO) THEN
-                          TEMP = X(JX)
-                          IX = KX
-                          L = 1 - J
-                          DO 70 I = MIN(N,J+K),J + 1,-1
-                              X(IX) = X(IX) + TEMP*A(L+I,J)
-                              IX = IX - INCX
-   70                     CONTINUE
-                          IF (NOUNIT) X(JX) = X(JX)*A(1,J)
-                      END IF
-                      JX = JX - INCX
-                      IF ((N-J).GE.K) KX = KX - INCX
-   80             CONTINUE
-              END IF
-          END IF
-      ELSE
-*
-*        Form  x := A'*x.
-*
-          IF (LSAME(UPLO,'U')) THEN
-              KPLUS1 = K + 1
-              IF (INCX.EQ.1) THEN
-                  DO 100 J = N,1,-1
-                      TEMP = X(J)
-                      L = KPLUS1 - J
-                      IF (NOUNIT) TEMP = TEMP*A(KPLUS1,J)
-                      DO 90 I = J - 1,MAX(1,J-K),-1
-                          TEMP = TEMP + A(L+I,J)*X(I)
-   90                 CONTINUE
-                      X(J) = TEMP
-  100             CONTINUE
-              ELSE
-                  KX = KX + (N-1)*INCX
-                  JX = KX
-                  DO 120 J = N,1,-1
-                      TEMP = X(JX)
-                      KX = KX - INCX
-                      IX = KX
-                      L = KPLUS1 - J
-                      IF (NOUNIT) TEMP = TEMP*A(KPLUS1,J)
-                      DO 110 I = J - 1,MAX(1,J-K),-1
-                          TEMP = TEMP + A(L+I,J)*X(IX)
-                          IX = IX - INCX
-  110                 CONTINUE
-                      X(JX) = TEMP
-                      JX = JX - INCX
-  120             CONTINUE
-              END IF
-          ELSE
-              IF (INCX.EQ.1) THEN
-                  DO 140 J = 1,N
-                      TEMP = X(J)
-                      L = 1 - J
-                      IF (NOUNIT) TEMP = TEMP*A(1,J)
-                      DO 130 I = J + 1,MIN(N,J+K)
-                          TEMP = TEMP + A(L+I,J)*X(I)
-  130                 CONTINUE
-                      X(J) = TEMP
-  140             CONTINUE
-              ELSE
-                  JX = KX
-                  DO 160 J = 1,N
-                      TEMP = X(JX)
-                      KX = KX + INCX
-                      IX = KX
-                      L = 1 - J
-                      IF (NOUNIT) TEMP = TEMP*A(1,J)
-                      DO 150 I = J + 1,MIN(N,J+K)
-                          TEMP = TEMP + A(L+I,J)*X(IX)
-                          IX = IX + INCX
-  150                 CONTINUE
-                      X(JX) = TEMP
-                      JX = JX + INCX
-  160             CONTINUE
-              END IF
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of STBMV .
-*
-      END

Index: 3rd_party/eigen/blas/testing/cblat1.f
==================================================================
--- 3rd_party/eigen/blas/testing/cblat1.f
+++ 3rd_party/eigen/blas/testing/cblat1.f
@@ -1,9 +1,51 @@
+*> \brief \b CBLAT1
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM CBLAT1
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*>    Test program for the COMPLEX Level 1 BLAS.
+*>    Based upon the original BLAS test routine together with:
+*>
+*>    F06GAF Example Program Text
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup complex_blas_testing
+*
+*  =====================================================================
       PROGRAM CBLAT1
-*     Test program for the COMPLEX    Level 1 BLAS.
-*     Based upon the original BLAS test routine together with:
-*     F06GAF Example Program Text
+*
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
+*
 *     .. Parameters ..
       INTEGER          NOUT
       PARAMETER        (NOUT=6)
 *     .. Scalars in Common ..
       INTEGER          ICASE, INCX, INCY, MODE, N
@@ -112,12 +154,12 @@
      +                  (0.1E0,-0.3E0), (0.5E0,-0.1E0), (5.0E0,6.0E0),
      +                  (5.0E0,6.0E0), (5.0E0,6.0E0), (5.0E0,6.0E0),
      +                  (5.0E0,6.0E0), (5.0E0,6.0E0), (0.1E0,0.1E0),
      +                  (-0.6E0,0.1E0), (0.1E0,-0.3E0), (7.0E0,8.0E0),
      +                  (7.0E0,8.0E0), (7.0E0,8.0E0), (7.0E0,8.0E0),
-     +                  (7.0E0,8.0E0), (0.3E0,0.1E0), (0.1E0,0.4E0),
-     +                  (0.4E0,0.1E0), (0.1E0,0.2E0), (2.0E0,3.0E0),
+     +                  (7.0E0,8.0E0), (0.3E0,0.1E0), (0.5E0,0.0E0),
+     +                  (0.0E0,0.5E0), (0.0E0,0.2E0), (2.0E0,3.0E0),
      +                  (2.0E0,3.0E0), (2.0E0,3.0E0), (2.0E0,3.0E0)/
       DATA              ((CV(I,J,2),I=1,8),J=1,5)/(0.1E0,0.1E0),
      +                  (4.0E0,5.0E0), (4.0E0,5.0E0), (4.0E0,5.0E0),
      +                  (4.0E0,5.0E0), (4.0E0,5.0E0), (4.0E0,5.0E0),
      +                  (4.0E0,5.0E0), (0.3E0,-0.4E0), (6.0E0,7.0E0),
@@ -127,14 +169,14 @@
      +                  (2.0E0,5.0E0), (2.0E0,5.0E0), (2.0E0,5.0E0),
      +                  (2.0E0,5.0E0), (2.0E0,5.0E0), (0.1E0,0.1E0),
      +                  (3.0E0,6.0E0), (-0.6E0,0.1E0), (4.0E0,7.0E0),
      +                  (0.1E0,-0.3E0), (7.0E0,2.0E0), (7.0E0,2.0E0),
      +                  (7.0E0,2.0E0), (0.3E0,0.1E0), (5.0E0,8.0E0),
-     +                  (0.1E0,0.4E0), (6.0E0,9.0E0), (0.4E0,0.1E0),
-     +                  (8.0E0,3.0E0), (0.1E0,0.2E0), (9.0E0,4.0E0)/
-      DATA              STRUE2/0.0E0, 0.5E0, 0.6E0, 0.7E0, 0.7E0/
-      DATA              STRUE4/0.0E0, 0.7E0, 1.0E0, 1.3E0, 1.7E0/
+     +                  (0.5E0,0.0E0), (6.0E0,9.0E0), (0.0E0,0.5E0),
+     +                  (8.0E0,3.0E0), (0.0E0,0.2E0), (9.0E0,4.0E0)/
+      DATA              STRUE2/0.0E0, 0.5E0, 0.6E0, 0.7E0, 0.8E0/
+      DATA              STRUE4/0.0E0, 0.7E0, 1.0E0, 1.3E0, 1.6E0/
       DATA              ((CTRUE5(I,J,1),I=1,8),J=1,5)/(0.1E0,0.1E0),
      +                  (1.0E0,2.0E0), (1.0E0,2.0E0), (1.0E0,2.0E0),
      +                  (1.0E0,2.0E0), (1.0E0,2.0E0), (1.0E0,2.0E0),
      +                  (1.0E0,2.0E0), (-0.16E0,-0.37E0), (3.0E0,4.0E0),
      +                  (3.0E0,4.0E0), (3.0E0,4.0E0), (3.0E0,4.0E0),
@@ -143,12 +185,12 @@
      +                  (5.0E0,6.0E0), (5.0E0,6.0E0), (5.0E0,6.0E0),
      +                  (5.0E0,6.0E0), (5.0E0,6.0E0), (5.0E0,6.0E0),
      +                  (0.11E0,-0.03E0), (-0.17E0,0.46E0),
      +                  (-0.17E0,-0.19E0), (7.0E0,8.0E0), (7.0E0,8.0E0),
      +                  (7.0E0,8.0E0), (7.0E0,8.0E0), (7.0E0,8.0E0),
-     +                  (0.19E0,-0.17E0), (0.32E0,0.09E0),
-     +                  (0.23E0,-0.24E0), (0.18E0,0.01E0),
+     +                  (0.19E0,-0.17E0), (0.20E0,-0.35E0),
+     +                  (0.35E0,0.20E0), (0.14E0,0.08E0),
      +                  (2.0E0,3.0E0), (2.0E0,3.0E0), (2.0E0,3.0E0),
      +                  (2.0E0,3.0E0)/
       DATA              ((CTRUE5(I,J,2),I=1,8),J=1,5)/(0.1E0,0.1E0),
      +                  (4.0E0,5.0E0), (4.0E0,5.0E0), (4.0E0,5.0E0),
      +                  (4.0E0,5.0E0), (4.0E0,5.0E0), (4.0E0,5.0E0),
@@ -160,13 +202,13 @@
      +                  (2.0E0,5.0E0), (2.0E0,5.0E0), (2.0E0,5.0E0),
      +                  (0.11E0,-0.03E0), (3.0E0,6.0E0),
      +                  (-0.17E0,0.46E0), (4.0E0,7.0E0),
      +                  (-0.17E0,-0.19E0), (7.0E0,2.0E0), (7.0E0,2.0E0),
      +                  (7.0E0,2.0E0), (0.19E0,-0.17E0), (5.0E0,8.0E0),
-     +                  (0.32E0,0.09E0), (6.0E0,9.0E0),
-     +                  (0.23E0,-0.24E0), (8.0E0,3.0E0),
-     +                  (0.18E0,0.01E0), (9.0E0,4.0E0)/
+     +                  (0.20E0,-0.35E0), (6.0E0,9.0E0),
+     +                  (0.35E0,0.20E0), (8.0E0,3.0E0),
+     +                  (0.14E0,0.08E0), (9.0E0,4.0E0)/
       DATA              ((CTRUE6(I,J,1),I=1,8),J=1,5)/(0.1E0,0.1E0),
      +                  (1.0E0,2.0E0), (1.0E0,2.0E0), (1.0E0,2.0E0),
      +                  (1.0E0,2.0E0), (1.0E0,2.0E0), (1.0E0,2.0E0),
      +                  (1.0E0,2.0E0), (0.09E0,-0.12E0), (3.0E0,4.0E0),
      +                  (3.0E0,4.0E0), (3.0E0,4.0E0), (3.0E0,4.0E0),
@@ -175,12 +217,12 @@
      +                  (5.0E0,6.0E0), (5.0E0,6.0E0), (5.0E0,6.0E0),
      +                  (5.0E0,6.0E0), (5.0E0,6.0E0), (5.0E0,6.0E0),
      +                  (0.03E0,0.03E0), (-0.18E0,0.03E0),
      +                  (0.03E0,-0.09E0), (7.0E0,8.0E0), (7.0E0,8.0E0),
      +                  (7.0E0,8.0E0), (7.0E0,8.0E0), (7.0E0,8.0E0),
-     +                  (0.09E0,0.03E0), (0.03E0,0.12E0),
-     +                  (0.12E0,0.03E0), (0.03E0,0.06E0), (2.0E0,3.0E0),
+     +                  (0.09E0,0.03E0), (0.15E0,0.00E0),
+     +                  (0.00E0,0.15E0), (0.00E0,0.06E0), (2.0E0,3.0E0),
      +                  (2.0E0,3.0E0), (2.0E0,3.0E0), (2.0E0,3.0E0)/
       DATA              ((CTRUE6(I,J,2),I=1,8),J=1,5)/(0.1E0,0.1E0),
      +                  (4.0E0,5.0E0), (4.0E0,5.0E0), (4.0E0,5.0E0),
      +                  (4.0E0,5.0E0), (4.0E0,5.0E0), (4.0E0,5.0E0),
      +                  (4.0E0,5.0E0), (0.09E0,-0.12E0), (6.0E0,7.0E0),
@@ -191,12 +233,12 @@
      +                  (2.0E0,5.0E0), (2.0E0,5.0E0), (2.0E0,5.0E0),
      +                  (0.03E0,0.03E0), (3.0E0,6.0E0),
      +                  (-0.18E0,0.03E0), (4.0E0,7.0E0),
      +                  (0.03E0,-0.09E0), (7.0E0,2.0E0), (7.0E0,2.0E0),
      +                  (7.0E0,2.0E0), (0.09E0,0.03E0), (5.0E0,8.0E0),
-     +                  (0.03E0,0.12E0), (6.0E0,9.0E0), (0.12E0,0.03E0),
-     +                  (8.0E0,3.0E0), (0.03E0,0.06E0), (9.0E0,4.0E0)/
+     +                  (0.15E0,0.00E0), (6.0E0,9.0E0), (0.00E0,0.15E0),
+     +                  (8.0E0,3.0E0), (0.00E0,0.06E0), (9.0E0,4.0E0)/
       DATA              ITRUE3/0, 1, 2, 2, 2/
 *     .. Executable Statements ..
       DO 60 INCX = 1, 2
          DO 40 NP1 = 1, 5
             N = NP1 - 1
@@ -527,11 +569,12 @@
 *
 *     C. L. LAWSON, JPL, 1974 DEC 10
 *
 *     .. Parameters ..
       INTEGER          NOUT
-      PARAMETER        (NOUT=6)
+      REAL             ZERO
+      PARAMETER        (NOUT=6, ZERO=0.0E0)
 *     .. Scalar Arguments ..
       REAL             SFAC
       INTEGER          LEN
 *     .. Array Arguments ..
       REAL             SCOMP(LEN), SSIZE(LEN), STRUE(LEN)
@@ -550,11 +593,11 @@
       COMMON           /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
 *     .. Executable Statements ..
 *
       DO 40 I = 1, LEN
          SD = SCOMP(I) - STRUE(I)
-         IF (SDIFF(ABS(SSIZE(I))+ABS(SFAC*SD),ABS(SSIZE(I))).EQ.0.0E0)
+         IF (ABS(SFAC*SD) .LE. ABS(SSIZE(I))*EPSILON(ZERO))
      +       GO TO 40
 *
 *                             HERE    SCOMP(I) IS NOT CLOSE TO STRUE(I).
 *
          IF ( .NOT. PASS) GO TO 20

Index: 3rd_party/eigen/blas/testing/cblat2.f
==================================================================
--- 3rd_party/eigen/blas/testing/cblat2.f
+++ 3rd_party/eigen/blas/testing/cblat2.f
@@ -1,80 +1,126 @@
+*> \brief \b CBLAT2
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM CBLAT2
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*> Test program for the COMPLEX          Level 2 Blas.
+*>
+*> The program must be driven by a short data file. The first 18 records
+*> of the file are read using list-directed input, the last 17 records
+*> are read using the format ( A6, L2 ). An annotated example of a data
+*> file can be obtained by deleting the first 3 characters from the
+*> following 35 lines:
+*> 'cblat2.out'      NAME OF SUMMARY OUTPUT FILE
+*> 6                 UNIT NUMBER OF SUMMARY FILE
+*> 'CBLA2T.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
+*> -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
+*> F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
+*> F        LOGICAL FLAG, T TO STOP ON FAILURES.
+*> T        LOGICAL FLAG, T TO TEST ERROR EXITS.
+*> 16.0     THRESHOLD VALUE OF TEST RATIO
+*> 6                 NUMBER OF VALUES OF N
+*> 0 1 2 3 5 9       VALUES OF N
+*> 4                 NUMBER OF VALUES OF K
+*> 0 1 2 4           VALUES OF K
+*> 4                 NUMBER OF VALUES OF INCX AND INCY
+*> 1 2 -1 -2         VALUES OF INCX AND INCY
+*> 3                 NUMBER OF VALUES OF ALPHA
+*> (0.0,0.0) (1.0,0.0) (0.7,-0.9)       VALUES OF ALPHA
+*> 3                 NUMBER OF VALUES OF BETA
+*> (0.0,0.0) (1.0,0.0) (1.3,-1.1)       VALUES OF BETA
+*> CGEMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CGBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHEMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHPMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CTRMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CTBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CTPMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CTRSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CTBSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CTPSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CGERC  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CGERU  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHER   T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHPR   T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHER2  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHPR2  T PUT F FOR NO TEST. SAME COLUMNS.
+*>
+*> Further Details
+*> ===============
+*>
+*>    See:
+*>
+*>       Dongarra J. J., Du Croz J. J., Hammarling S.  and Hanson R. J..
+*>       An  extended  set of Fortran  Basic Linear Algebra Subprograms.
+*>
+*>       Technical  Memoranda  Nos. 41 (revision 3) and 81,  Mathematics
+*>       and  Computer Science  Division,  Argonne  National Laboratory,
+*>       9700 South Cass Avenue, Argonne, Illinois 60439, US.
+*>
+*>       Or
+*>
+*>       NAG  Technical Reports TR3/87 and TR4/87,  Numerical Algorithms
+*>       Group  Ltd.,  NAG  Central  Office,  256  Banbury  Road, Oxford
+*>       OX2 7DE, UK,  and  Numerical Algorithms Group Inc.,  1101  31st
+*>       Street,  Suite 100,  Downers Grove,  Illinois 60515-1263,  USA.
+*>
+*>
+*> -- Written on 10-August-1987.
+*>    Richard Hanson, Sandia National Labs.
+*>    Jeremy Du Croz, NAG Central Office.
+*>
+*>    10-9-00:  Change STATUS='NEW' to 'UNKNOWN' so that the testers
+*>              can be run multiple times without deleting generated
+*>              output files (susan)
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup complex_blas_testing
+*
+*  =====================================================================
       PROGRAM CBLAT2
 *
-*  Test program for the COMPLEX          Level 2 Blas.
-*
-*  The program must be driven by a short data file. The first 18 records
-*  of the file are read using list-directed input, the last 17 records
-*  are read using the format ( A6, L2 ). An annotated example of a data
-*  file can be obtained by deleting the first 3 characters from the
-*  following 35 lines:
-*  'CBLAT2.SUMM'     NAME OF SUMMARY OUTPUT FILE
-*  6                 UNIT NUMBER OF SUMMARY FILE
-*  'CBLA2T.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
-*  -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
-*  F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
-*  F        LOGICAL FLAG, T TO STOP ON FAILURES.
-*  T        LOGICAL FLAG, T TO TEST ERROR EXITS.
-*  16.0     THRESHOLD VALUE OF TEST RATIO
-*  6                 NUMBER OF VALUES OF N
-*  0 1 2 3 5 9       VALUES OF N
-*  4                 NUMBER OF VALUES OF K
-*  0 1 2 4           VALUES OF K
-*  4                 NUMBER OF VALUES OF INCX AND INCY
-*  1 2 -1 -2         VALUES OF INCX AND INCY
-*  3                 NUMBER OF VALUES OF ALPHA
-*  (0.0,0.0) (1.0,0.0) (0.7,-0.9)       VALUES OF ALPHA
-*  3                 NUMBER OF VALUES OF BETA
-*  (0.0,0.0) (1.0,0.0) (1.3,-1.1)       VALUES OF BETA
-*  CGEMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CGBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHEMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHPMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CTRMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CTBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CTPMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CTRSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CTBSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CTPSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CGERC  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CGERU  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHER   T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHPR   T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHER2  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHPR2  T PUT F FOR NO TEST. SAME COLUMNS.
-*
-*     See:
-*
-*        Dongarra J. J., Du Croz J. J., Hammarling S.  and Hanson R. J..
-*        An  extended  set of Fortran  Basic Linear Algebra Subprograms.
-*
-*        Technical  Memoranda  Nos. 41 (revision 3) and 81,  Mathematics
-*        and  Computer Science  Division,  Argonne  National Laboratory,
-*        9700 South Cass Avenue, Argonne, Illinois 60439, US.
-*
-*        Or
-*
-*        NAG  Technical Reports TR3/87 and TR4/87,  Numerical Algorithms
-*        Group  Ltd.,  NAG  Central  Office,  256  Banbury  Road, Oxford
-*        OX2 7DE, UK,  and  Numerical Algorithms Group Inc.,  1101  31st
-*        Street,  Suite 100,  Downers Grove,  Illinois 60515-1263,  USA.
-*
-*
-*  -- Written on 10-August-1987.
-*     Richard Hanson, Sandia National Labs.
-*     Jeremy Du Croz, NAG Central Office.
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
 *
 *     .. Parameters ..
       INTEGER            NIN
       PARAMETER          ( NIN = 5 )
       INTEGER            NSUBS
       PARAMETER          ( NSUBS = 17 )
       COMPLEX            ZERO, ONE
       PARAMETER          ( ZERO = ( 0.0, 0.0 ), ONE = ( 1.0, 0.0 ) )
-      REAL               RZERO, RHALF, RONE
-      PARAMETER          ( RZERO = 0.0, RHALF = 0.5, RONE = 1.0 )
+      REAL               RZERO
+      PARAMETER          ( RZERO = 0.0 )
       INTEGER            NMAX, INCMAX
       PARAMETER          ( NMAX = 65, INCMAX = 2 )
       INTEGER            NINMAX, NIDMAX, NKBMAX, NALMAX, NBEMAX
       PARAMETER          ( NINMAX = 7, NIDMAX = 9, NKBMAX = 7,
      $                   NALMAX = 7, NBEMAX = 7 )
@@ -124,20 +170,20 @@
 *
 *     Read name and unit number for summary output file and open file.
 *
       READ( NIN, FMT = * )SUMMRY
       READ( NIN, FMT = * )NOUT
-      OPEN( NOUT, FILE = SUMMRY, STATUS = 'NEW' )
+      OPEN( NOUT, FILE = SUMMRY, STATUS = 'UNKNOWN' )
       NOUTC = NOUT
 *
 *     Read name and unit number for snapshot output file and open file.
 *
       READ( NIN, FMT = * )SNAPS
       READ( NIN, FMT = * )NTRA
       TRACE = NTRA.GE.0
       IF( TRACE )THEN
-         OPEN( NTRA, FILE = SNAPS, STATUS = 'NEW' )
+         OPEN( NTRA, FILE = SNAPS, STATUS = 'UNKNOWN' )
       END IF
 *     Read the flag that directs rewinding of the snapshot file.
       READ( NIN, FMT = * )REWI
       REWI = REWI.AND.TRACE
 *     Read the flag that directs stopping on any failure.
@@ -238,18 +284,11 @@
    80 CONTINUE
       CLOSE ( NIN )
 *
 *     Compute EPS (the machine precision).
 *
-      EPS = RONE
-   90 CONTINUE
-      IF( SDIFF( RONE + EPS, RONE ).EQ.RZERO )
-     $   GO TO 100
-      EPS = RHALF*EPS
-      GO TO 90
-  100 CONTINUE
-      EPS = EPS + EPS
+      EPS = EPSILON(RZERO)
       WRITE( NOUT, FMT = 9998 )EPS
 *
 *     Check the reliability of CMVCH using exact data.
 *
       N = MIN( 32, NMAX )
@@ -3077,11 +3116,10 @@
      $            GO TO 70
    40       CONTINUE
    50    CONTINUE
       END IF
 *
-   60 CONTINUE
       LCERES = .TRUE.
       GO TO 80
    70 CONTINUE
       LCERES = .FALSE.
    80 RETURN

Index: 3rd_party/eigen/blas/testing/cblat3.f
==================================================================
--- 3rd_party/eigen/blas/testing/cblat3.f
+++ 3rd_party/eigen/blas/testing/cblat3.f
@@ -1,62 +1,108 @@
+*> \brief \b CBLAT3
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM CBLAT3
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*> Test program for the COMPLEX          Level 3 Blas.
+*>
+*> The program must be driven by a short data file. The first 14 records
+*> of the file are read using list-directed input, the last 9 records
+*> are read using the format ( A6, L2 ). An annotated example of a data
+*> file can be obtained by deleting the first 3 characters from the
+*> following 23 lines:
+*> 'cblat3.out'      NAME OF SUMMARY OUTPUT FILE
+*> 6                 UNIT NUMBER OF SUMMARY FILE
+*> 'CBLAT3.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
+*> -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
+*> F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
+*> F        LOGICAL FLAG, T TO STOP ON FAILURES.
+*> T        LOGICAL FLAG, T TO TEST ERROR EXITS.
+*> 16.0     THRESHOLD VALUE OF TEST RATIO
+*> 6                 NUMBER OF VALUES OF N
+*> 0 1 2 3 5 9       VALUES OF N
+*> 3                 NUMBER OF VALUES OF ALPHA
+*> (0.0,0.0) (1.0,0.0) (0.7,-0.9)       VALUES OF ALPHA
+*> 3                 NUMBER OF VALUES OF BETA
+*> (0.0,0.0) (1.0,0.0) (1.3,-1.1)       VALUES OF BETA
+*> CGEMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHEMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CSYMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CTRMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CTRSM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHERK  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CSYRK  T PUT F FOR NO TEST. SAME COLUMNS.
+*> CHER2K T PUT F FOR NO TEST. SAME COLUMNS.
+*> CSYR2K T PUT F FOR NO TEST. SAME COLUMNS.
+*>
+*> Further Details
+*> ===============
+*>
+*> See:
+*>
+*>    Dongarra J. J., Du Croz J. J., Duff I. S. and Hammarling S.
+*>    A Set of Level 3 Basic Linear Algebra Subprograms.
+*>
+*>    Technical Memorandum No.88 (Revision 1), Mathematics and
+*>    Computer Science Division, Argonne National Laboratory, 9700
+*>    South Cass Avenue, Argonne, Illinois 60439, US.
+*>
+*> -- Written on 8-February-1989.
+*>    Jack Dongarra, Argonne National Laboratory.
+*>    Iain Duff, AERE Harwell.
+*>    Jeremy Du Croz, Numerical Algorithms Group Ltd.
+*>    Sven Hammarling, Numerical Algorithms Group Ltd.
+*>
+*>    10-9-00:  Change STATUS='NEW' to 'UNKNOWN' so that the testers
+*>              can be run multiple times without deleting generated
+*>              output files (susan)
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup complex_blas_testing
+*
+*  =====================================================================
       PROGRAM CBLAT3
 *
-*  Test program for the COMPLEX          Level 3 Blas.
-*
-*  The program must be driven by a short data file. The first 14 records
-*  of the file are read using list-directed input, the last 9 records
-*  are read using the format ( A6, L2 ). An annotated example of a data
-*  file can be obtained by deleting the first 3 characters from the
-*  following 23 lines:
-*  'CBLAT3.SUMM'     NAME OF SUMMARY OUTPUT FILE
-*  6                 UNIT NUMBER OF SUMMARY FILE
-*  'CBLAT3.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
-*  -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
-*  F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
-*  F        LOGICAL FLAG, T TO STOP ON FAILURES.
-*  T        LOGICAL FLAG, T TO TEST ERROR EXITS.
-*  16.0     THRESHOLD VALUE OF TEST RATIO
-*  6                 NUMBER OF VALUES OF N
-*  0 1 2 3 5 9       VALUES OF N
-*  3                 NUMBER OF VALUES OF ALPHA
-*  (0.0,0.0) (1.0,0.0) (0.7,-0.9)       VALUES OF ALPHA
-*  3                 NUMBER OF VALUES OF BETA
-*  (0.0,0.0) (1.0,0.0) (1.3,-1.1)       VALUES OF BETA
-*  CGEMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHEMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CSYMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CTRMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CTRSM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHERK  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CSYRK  T PUT F FOR NO TEST. SAME COLUMNS.
-*  CHER2K T PUT F FOR NO TEST. SAME COLUMNS.
-*  CSYR2K T PUT F FOR NO TEST. SAME COLUMNS.
-*
-*  See:
-*
-*     Dongarra J. J., Du Croz J. J., Duff I. S. and Hammarling S.
-*     A Set of Level 3 Basic Linear Algebra Subprograms.
-*
-*     Technical Memorandum No.88 (Revision 1), Mathematics and
-*     Computer Science Division, Argonne National Laboratory, 9700
-*     South Cass Avenue, Argonne, Illinois 60439, US.
-*
-*  -- Written on 8-February-1989.
-*     Jack Dongarra, Argonne National Laboratory.
-*     Iain Duff, AERE Harwell.
-*     Jeremy Du Croz, Numerical Algorithms Group Ltd.
-*     Sven Hammarling, Numerical Algorithms Group Ltd.
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
 *
 *     .. Parameters ..
       INTEGER            NIN
       PARAMETER          ( NIN = 5 )
       INTEGER            NSUBS
       PARAMETER          ( NSUBS = 9 )
       COMPLEX            ZERO, ONE
       PARAMETER          ( ZERO = ( 0.0, 0.0 ), ONE = ( 1.0, 0.0 ) )
-      REAL               RZERO, RHALF, RONE
-      PARAMETER          ( RZERO = 0.0, RHALF = 0.5, RONE = 1.0 )
+      REAL               RZERO
+      PARAMETER          ( RZERO = 0.0 )
       INTEGER            NMAX
       PARAMETER          ( NMAX = 65 )
       INTEGER            NIDMAX, NALMAX, NBEMAX
       PARAMETER          ( NIDMAX = 9, NALMAX = 7, NBEMAX = 7 )
 *     .. Local Scalars ..
@@ -101,20 +147,20 @@
 *
 *     Read name and unit number for summary output file and open file.
 *
       READ( NIN, FMT = * )SUMMRY
       READ( NIN, FMT = * )NOUT
-      OPEN( NOUT, FILE = SUMMRY, STATUS = 'NEW' )
+      OPEN( NOUT, FILE = SUMMRY )
       NOUTC = NOUT
 *
 *     Read name and unit number for snapshot output file and open file.
 *
       READ( NIN, FMT = * )SNAPS
       READ( NIN, FMT = * )NTRA
       TRACE = NTRA.GE.0
       IF( TRACE )THEN
-         OPEN( NTRA, FILE = SNAPS, STATUS = 'NEW' )
+         OPEN( NTRA, FILE = SNAPS )
       END IF
 *     Read the flag that directs rewinding of the snapshot file.
       READ( NIN, FMT = * )REWI
       REWI = REWI.AND.TRACE
 *     Read the flag that directs stopping on any failure.
@@ -187,18 +233,11 @@
    60 CONTINUE
       CLOSE ( NIN )
 *
 *     Compute EPS (the machine precision).
 *
-      EPS = RONE
-   70 CONTINUE
-      IF( SDIFF( RONE + EPS, RONE ).EQ.RZERO )
-     $   GO TO 80
-      EPS = RHALF*EPS
-      GO TO 70
-   80 CONTINUE
-      EPS = EPS + EPS
+      EPS = EPSILON(RZERO)
       WRITE( NOUT, FMT = 9998 )EPS
 *
 *     Check the reliability of CMMCH using exact data.
 *
       N = MIN( 32, NMAX )
@@ -1944,26 +1983,33 @@
       END
       SUBROUTINE CCHKE( ISNUM, SRNAMT, NOUT )
 *
 *  Tests the error exits from the Level 3 Blas.
 *  Requires a special version of the error-handling routine XERBLA.
-*  ALPHA, RALPHA, BETA, RBETA, A, B and C should not need to be defined.
+*  A, B and C should not need to be defined.
 *
 *  Auxiliary routine for test program for Level 3 Blas.
 *
 *  -- Written on 8-February-1989.
 *     Jack Dongarra, Argonne National Laboratory.
 *     Iain Duff, AERE Harwell.
 *     Jeremy Du Croz, Numerical Algorithms Group Ltd.
 *     Sven Hammarling, Numerical Algorithms Group Ltd.
+*
+*  3-19-92:  Initialize ALPHA, BETA, RALPHA, and RBETA  (eca)
+*  3-19-92:  Fix argument 12 in calls to CSYMM and CHEMM
+*            with INFOT = 9  (eca)
 *
 *     .. Scalar Arguments ..
       INTEGER            ISNUM, NOUT
       CHARACTER*6        SRNAMT
 *     .. Scalars in Common ..
       INTEGER            INFOT, NOUTC
       LOGICAL            LERR, OK
+*     .. Parameters ..
+      REAL               ONE, TWO
+      PARAMETER          ( ONE = 1.0E0, TWO = 2.0E0 )
 *     .. Local Scalars ..
       COMPLEX            ALPHA, BETA
       REAL               RALPHA, RBETA
 *     .. Local Arrays ..
       COMPLEX            A( 2, 1 ), B( 2, 1 ), C( 2, 1 )
@@ -1977,10 +2023,18 @@
 *     if anything is wrong.
       OK = .TRUE.
 *     LERR is set to .TRUE. by the special version of XERBLA each time
 *     it is called, and is then tested and re-set by CHKXER.
       LERR = .FALSE.
+*
+*     Initialize ALPHA, BETA, RALPHA, and RBETA.
+*
+      ALPHA = CMPLX( ONE, -ONE )
+      BETA = CMPLX( TWO, -TWO )
+      RALPHA = ONE
+      RBETA = TWO
+*
       GO TO ( 10, 20, 30, 40, 50, 60, 70, 80,
      $        90 )ISNUM
    10 INFOT = 1
       CALL CGEMM( '/', 'N', 0, 0, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
@@ -2203,20 +2257,20 @@
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 7
       CALL CHEMM( 'R', 'L', 0, 2, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL CHEMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
+      CALL CHEMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
+      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
+      INFOT = 9
+      CALL CHEMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL CHEMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL CHEMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL CHEMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
-      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
-      INFOT = 9
-      CALL CHEMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL CHEMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
       CALL CHEMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 2, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
@@ -2270,20 +2324,20 @@
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 7
       CALL CSYMM( 'R', 'L', 0, 2, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL CSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
+      CALL CSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
+      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
+      INFOT = 9
+      CALL CSYMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL CSYMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL CSYMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL CSYMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
-      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
-      INFOT = 9
-      CALL CSYMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL CSYMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
       CALL CSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 2, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
@@ -3266,11 +3320,10 @@
      $            GO TO 70
    40       CONTINUE
    50    CONTINUE
       END IF
 *
-   60 CONTINUE
       LCERES = .TRUE.
       GO TO 80
    70 CONTINUE
       LCERES = .FALSE.
    80 RETURN

Index: 3rd_party/eigen/blas/testing/dblat2.f
==================================================================
--- 3rd_party/eigen/blas/testing/dblat2.f
+++ 3rd_party/eigen/blas/testing/dblat2.f
@@ -1,77 +1,123 @@
+*> \brief \b DBLAT2
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM DBLAT2
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*> Test program for the DOUBLE PRECISION Level 2 Blas.
+*>
+*> The program must be driven by a short data file. The first 18 records
+*> of the file are read using list-directed input, the last 16 records
+*> are read using the format ( A6, L2 ). An annotated example of a data
+*> file can be obtained by deleting the first 3 characters from the
+*> following 34 lines:
+*> 'dblat2.out'      NAME OF SUMMARY OUTPUT FILE
+*> 6                 UNIT NUMBER OF SUMMARY FILE
+*> 'DBLAT2.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
+*> -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
+*> F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
+*> F        LOGICAL FLAG, T TO STOP ON FAILURES.
+*> T        LOGICAL FLAG, T TO TEST ERROR EXITS.
+*> 16.0     THRESHOLD VALUE OF TEST RATIO
+*> 6                 NUMBER OF VALUES OF N
+*> 0 1 2 3 5 9       VALUES OF N
+*> 4                 NUMBER OF VALUES OF K
+*> 0 1 2 4           VALUES OF K
+*> 4                 NUMBER OF VALUES OF INCX AND INCY
+*> 1 2 -1 -2         VALUES OF INCX AND INCY
+*> 3                 NUMBER OF VALUES OF ALPHA
+*> 0.0 1.0 0.7       VALUES OF ALPHA
+*> 3                 NUMBER OF VALUES OF BETA
+*> 0.0 1.0 0.9       VALUES OF BETAC
+*> DGEMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DGBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSYMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSPMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DTRMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DTBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DTPMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DTRSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DTBSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DTPSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DGER   T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSYR   T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSPR   T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSYR2  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSPR2  T PUT F FOR NO TEST. SAME COLUMNS.
+*>
+*> Further Details
+*> ===============
+*>
+*>    See:
+*>
+*>       Dongarra J. J., Du Croz J. J., Hammarling S.  and Hanson R. J..
+*>       An  extended  set of Fortran  Basic Linear Algebra Subprograms.
+*>
+*>       Technical  Memoranda  Nos. 41 (revision 3) and 81,  Mathematics
+*>       and  Computer Science  Division,  Argonne  National Laboratory,
+*>       9700 South Cass Avenue, Argonne, Illinois 60439, US.
+*>
+*>       Or
+*>
+*>       NAG  Technical Reports TR3/87 and TR4/87,  Numerical Algorithms
+*>       Group  Ltd.,  NAG  Central  Office,  256  Banbury  Road, Oxford
+*>       OX2 7DE, UK,  and  Numerical Algorithms Group Inc.,  1101  31st
+*>       Street,  Suite 100,  Downers Grove,  Illinois 60515-1263,  USA.
+*>
+*>
+*> -- Written on 10-August-1987.
+*>    Richard Hanson, Sandia National Labs.
+*>    Jeremy Du Croz, NAG Central Office.
+*>
+*>    10-9-00:  Change STATUS='NEW' to 'UNKNOWN' so that the testers
+*>              can be run multiple times without deleting generated
+*>              output files (susan)
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup double_blas_testing
+*
+*  =====================================================================
       PROGRAM DBLAT2
 *
-*  Test program for the DOUBLE PRECISION Level 2 Blas.
-*
-*  The program must be driven by a short data file. The first 18 records
-*  of the file are read using list-directed input, the last 16 records
-*  are read using the format ( A6, L2 ). An annotated example of a data
-*  file can be obtained by deleting the first 3 characters from the
-*  following 34 lines:
-*  'DBLAT2.SUMM'     NAME OF SUMMARY OUTPUT FILE
-*  6                 UNIT NUMBER OF SUMMARY FILE
-*  'DBLAT2.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
-*  -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
-*  F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
-*  F        LOGICAL FLAG, T TO STOP ON FAILURES.
-*  T        LOGICAL FLAG, T TO TEST ERROR EXITS.
-*  16.0     THRESHOLD VALUE OF TEST RATIO
-*  6                 NUMBER OF VALUES OF N
-*  0 1 2 3 5 9       VALUES OF N
-*  4                 NUMBER OF VALUES OF K
-*  0 1 2 4           VALUES OF K
-*  4                 NUMBER OF VALUES OF INCX AND INCY
-*  1 2 -1 -2         VALUES OF INCX AND INCY
-*  3                 NUMBER OF VALUES OF ALPHA
-*  0.0 1.0 0.7       VALUES OF ALPHA
-*  3                 NUMBER OF VALUES OF BETA
-*  0.0 1.0 0.9       VALUES OF BETA
-*  DGEMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DGBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSYMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSPMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DTRMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DTBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DTPMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DTRSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DTBSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DTPSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DGER   T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSYR   T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSPR   T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSYR2  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSPR2  T PUT F FOR NO TEST. SAME COLUMNS.
-*
-*     See:
-*
-*        Dongarra J. J., Du Croz J. J., Hammarling S.  and Hanson R. J..
-*        An  extended  set of Fortran  Basic Linear Algebra Subprograms.
-*
-*        Technical  Memoranda  Nos. 41 (revision 3) and 81,  Mathematics
-*        and  Computer Science  Division,  Argonne  National Laboratory,
-*        9700 South Cass Avenue, Argonne, Illinois 60439, US.
-*
-*        Or
-*
-*        NAG  Technical Reports TR3/87 and TR4/87,  Numerical Algorithms
-*        Group  Ltd.,  NAG  Central  Office,  256  Banbury  Road, Oxford
-*        OX2 7DE, UK,  and  Numerical Algorithms Group Inc.,  1101  31st
-*        Street,  Suite 100,  Downers Grove,  Illinois 60515-1263,  USA.
-*
-*
-*  -- Written on 10-August-1987.
-*     Richard Hanson, Sandia National Labs.
-*     Jeremy Du Croz, NAG Central Office.
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
 *
 *     .. Parameters ..
       INTEGER            NIN
       PARAMETER          ( NIN = 5 )
       INTEGER            NSUBS
       PARAMETER          ( NSUBS = 16 )
-      DOUBLE PRECISION   ZERO, HALF, ONE
-      PARAMETER          ( ZERO = 0.0D0, HALF = 0.5D0, ONE = 1.0D0 )
+      DOUBLE PRECISION   ZERO, ONE
+      PARAMETER          ( ZERO = 0.0D0, ONE = 1.0D0 )
       INTEGER            NMAX, INCMAX
       PARAMETER          ( NMAX = 65, INCMAX = 2 )
       INTEGER            NINMAX, NIDMAX, NKBMAX, NALMAX, NBEMAX
       PARAMETER          ( NINMAX = 7, NIDMAX = 9, NKBMAX = 7,
      $                   NALMAX = 7, NBEMAX = 7 )
@@ -119,20 +165,20 @@
 *
 *     Read name and unit number for summary output file and open file.
 *
       READ( NIN, FMT = * )SUMMRY
       READ( NIN, FMT = * )NOUT
-      OPEN( NOUT, FILE = SUMMRY, STATUS = 'NEW' )
+      OPEN( NOUT, FILE = SUMMRY, STATUS = 'UNKNOWN' )
       NOUTC = NOUT
 *
 *     Read name and unit number for snapshot output file and open file.
 *
       READ( NIN, FMT = * )SNAPS
       READ( NIN, FMT = * )NTRA
       TRACE = NTRA.GE.0
       IF( TRACE )THEN
-         OPEN( NTRA, FILE = SNAPS, STATUS = 'NEW' )
+         OPEN( NTRA, FILE = SNAPS, STATUS = 'UNKNOWN' )
       END IF
 *     Read the flag that directs rewinding of the snapshot file.
       READ( NIN, FMT = * )REWI
       REWI = REWI.AND.TRACE
 *     Read the flag that directs stopping on any failure.
@@ -233,18 +279,11 @@
    80 CONTINUE
       CLOSE ( NIN )
 *
 *     Compute EPS (the machine precision).
 *
-      EPS = ONE
-   90 CONTINUE
-      IF( DDIFF( ONE + EPS, ONE ).EQ.ZERO )
-     $   GO TO 100
-      EPS = HALF*EPS
-      GO TO 90
-  100 CONTINUE
-      EPS = EPS + EPS
+      EPS = EPSILON(ZERO)
       WRITE( NOUT, FMT = 9998 )EPS
 *
 *     Check the reliability of DMVCH using exact data.
 *
       N = MIN( 32, NMAX )
@@ -2980,11 +3019,10 @@
      $            GO TO 70
    40       CONTINUE
    50    CONTINUE
       END IF
 *
-   60 CONTINUE
       LDERES = .TRUE.
       GO TO 80
    70 CONTINUE
       LDERES = .FALSE.
    80 RETURN

Index: 3rd_party/eigen/blas/testing/dblat3.f
==================================================================
--- 3rd_party/eigen/blas/testing/dblat3.f
+++ 3rd_party/eigen/blas/testing/dblat3.f
@@ -1,57 +1,103 @@
+*> \brief \b DBLAT3
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM DBLAT3
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*> Test program for the DOUBLE PRECISION Level 3 Blas.
+*>
+*> The program must be driven by a short data file. The first 14 records
+*> of the file are read using list-directed input, the last 6 records
+*> are read using the format ( A6, L2 ). An annotated example of a data
+*> file can be obtained by deleting the first 3 characters from the
+*> following 20 lines:
+*> 'dblat3.out'      NAME OF SUMMARY OUTPUT FILE
+*> 6                 UNIT NUMBER OF SUMMARY FILE
+*> 'DBLAT3.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
+*> -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
+*> F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
+*> F        LOGICAL FLAG, T TO STOP ON FAILURES.
+*> T        LOGICAL FLAG, T TO TEST ERROR EXITS.
+*> 16.0     THRESHOLD VALUE OF TEST RATIO
+*> 6                 NUMBER OF VALUES OF N
+*> 0 1 2 3 5 9       VALUES OF N
+*> 3                 NUMBER OF VALUES OF ALPHA
+*> 0.0 1.0 0.7       VALUES OF ALPHA
+*> 3                 NUMBER OF VALUES OF BETA
+*> 0.0 1.0 1.3       VALUES OF BETA
+*> DGEMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSYMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DTRMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DTRSM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSYRK  T PUT F FOR NO TEST. SAME COLUMNS.
+*> DSYR2K T PUT F FOR NO TEST. SAME COLUMNS.
+*>
+*> Further Details
+*> ===============
+*>
+*> See:
+*>
+*>    Dongarra J. J., Du Croz J. J., Duff I. S. and Hammarling S.
+*>    A Set of Level 3 Basic Linear Algebra Subprograms.
+*>
+*>    Technical Memorandum No.88 (Revision 1), Mathematics and
+*>    Computer Science Division, Argonne National Laboratory, 9700
+*>    South Cass Avenue, Argonne, Illinois 60439, US.
+*>
+*> -- Written on 8-February-1989.
+*>    Jack Dongarra, Argonne National Laboratory.
+*>    Iain Duff, AERE Harwell.
+*>    Jeremy Du Croz, Numerical Algorithms Group Ltd.
+*>    Sven Hammarling, Numerical Algorithms Group Ltd.
+*>
+*>    10-9-00:  Change STATUS='NEW' to 'UNKNOWN' so that the testers
+*>              can be run multiple times without deleting generated
+*>              output files (susan)
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup double_blas_testing
+*
+*  =====================================================================
       PROGRAM DBLAT3
 *
-*  Test program for the DOUBLE PRECISION Level 3 Blas.
-*
-*  The program must be driven by a short data file. The first 14 records
-*  of the file are read using list-directed input, the last 6 records
-*  are read using the format ( A6, L2 ). An annotated example of a data
-*  file can be obtained by deleting the first 3 characters from the
-*  following 20 lines:
-*  'DBLAT3.SUMM'     NAME OF SUMMARY OUTPUT FILE
-*  6                 UNIT NUMBER OF SUMMARY FILE
-*  'DBLAT3.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
-*  -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
-*  F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
-*  F        LOGICAL FLAG, T TO STOP ON FAILURES.
-*  T        LOGICAL FLAG, T TO TEST ERROR EXITS.
-*  16.0     THRESHOLD VALUE OF TEST RATIO
-*  6                 NUMBER OF VALUES OF N
-*  0 1 2 3 5 9       VALUES OF N
-*  3                 NUMBER OF VALUES OF ALPHA
-*  0.0 1.0 0.7       VALUES OF ALPHA
-*  3                 NUMBER OF VALUES OF BETA
-*  0.0 1.0 1.3       VALUES OF BETA
-*  DGEMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSYMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DTRMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DTRSM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSYRK  T PUT F FOR NO TEST. SAME COLUMNS.
-*  DSYR2K T PUT F FOR NO TEST. SAME COLUMNS.
-*
-*  See:
-*
-*     Dongarra J. J., Du Croz J. J., Duff I. S. and Hammarling S.
-*     A Set of Level 3 Basic Linear Algebra Subprograms.
-*
-*     Technical Memorandum No.88 (Revision 1), Mathematics and
-*     Computer Science Division, Argonne National Laboratory, 9700
-*     South Cass Avenue, Argonne, Illinois 60439, US.
-*
-*  -- Written on 8-February-1989.
-*     Jack Dongarra, Argonne National Laboratory.
-*     Iain Duff, AERE Harwell.
-*     Jeremy Du Croz, Numerical Algorithms Group Ltd.
-*     Sven Hammarling, Numerical Algorithms Group Ltd.
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
 *
 *     .. Parameters ..
       INTEGER            NIN
       PARAMETER          ( NIN = 5 )
       INTEGER            NSUBS
       PARAMETER          ( NSUBS = 6 )
-      DOUBLE PRECISION   ZERO, HALF, ONE
-      PARAMETER          ( ZERO = 0.0D0, HALF = 0.5D0, ONE = 1.0D0 )
+      DOUBLE PRECISION   ZERO, ONE
+      PARAMETER          ( ZERO = 0.0D0, ONE = 1.0D0 )
       INTEGER            NMAX
       PARAMETER          ( NMAX = 65 )
       INTEGER            NIDMAX, NALMAX, NBEMAX
       PARAMETER          ( NIDMAX = 9, NALMAX = 7, NBEMAX = 7 )
 *     .. Local Scalars ..
@@ -94,20 +140,20 @@
 *
 *     Read name and unit number for summary output file and open file.
 *
       READ( NIN, FMT = * )SUMMRY
       READ( NIN, FMT = * )NOUT
-      OPEN( NOUT, FILE = SUMMRY, STATUS = 'NEW' )
+      OPEN( NOUT, FILE = SUMMRY, STATUS = 'UNKNOWN' )
       NOUTC = NOUT
 *
 *     Read name and unit number for snapshot output file and open file.
 *
       READ( NIN, FMT = * )SNAPS
       READ( NIN, FMT = * )NTRA
       TRACE = NTRA.GE.0
       IF( TRACE )THEN
-         OPEN( NTRA, FILE = SNAPS, STATUS = 'NEW' )
+         OPEN( NTRA, FILE = SNAPS, STATUS = 'UNKNOWN' )
       END IF
 *     Read the flag that directs rewinding of the snapshot file.
       READ( NIN, FMT = * )REWI
       REWI = REWI.AND.TRACE
 *     Read the flag that directs stopping on any failure.
@@ -180,18 +226,11 @@
    60 CONTINUE
       CLOSE ( NIN )
 *
 *     Compute EPS (the machine precision).
 *
-      EPS = ONE
-   70 CONTINUE
-      IF( DDIFF( ONE + EPS, ONE ).EQ.ZERO )
-     $   GO TO 80
-      EPS = HALF*EPS
-      GO TO 70
-   80 CONTINUE
-      EPS = EPS + EPS
+      EPS = EPSILON(ZERO)
       WRITE( NOUT, FMT = 9998 )EPS
 *
 *     Check the reliability of DMMCH using exact data.
 *
       N = MIN( 32, NMAX )
@@ -1800,26 +1839,32 @@
       END
       SUBROUTINE DCHKE( ISNUM, SRNAMT, NOUT )
 *
 *  Tests the error exits from the Level 3 Blas.
 *  Requires a special version of the error-handling routine XERBLA.
-*  ALPHA, BETA, A, B and C should not need to be defined.
+*  A, B and C should not need to be defined.
 *
 *  Auxiliary routine for test program for Level 3 Blas.
 *
 *  -- Written on 8-February-1989.
 *     Jack Dongarra, Argonne National Laboratory.
 *     Iain Duff, AERE Harwell.
 *     Jeremy Du Croz, Numerical Algorithms Group Ltd.
 *     Sven Hammarling, Numerical Algorithms Group Ltd.
 *
+*  3-19-92:  Initialize ALPHA and BETA  (eca)
+*  3-19-92:  Fix argument 12 in calls to SSYMM with INFOT = 9  (eca)
+*
 *     .. Scalar Arguments ..
       INTEGER            ISNUM, NOUT
       CHARACTER*6        SRNAMT
 *     .. Scalars in Common ..
       INTEGER            INFOT, NOUTC
       LOGICAL            LERR, OK
+*     .. Parameters ..
+      DOUBLE PRECISION   ONE, TWO
+      PARAMETER          ( ONE = 1.0D0, TWO = 2.0D0 )
 *     .. Local Scalars ..
       DOUBLE PRECISION   ALPHA, BETA
 *     .. Local Arrays ..
       DOUBLE PRECISION   A( 2, 1 ), B( 2, 1 ), C( 2, 1 )
 *     .. External Subroutines ..
@@ -1832,10 +1877,16 @@
 *     if anything is wrong.
       OK = .TRUE.
 *     LERR is set to .TRUE. by the special version of XERBLA each time
 *     it is called, and is then tested and re-set by CHKXER.
       LERR = .FALSE.
+*
+*     Initialize ALPHA and BETA.
+*
+      ALPHA = ONE
+      BETA = TWO
+*
       GO TO ( 10, 20, 30, 40, 50, 60 )ISNUM
    10 INFOT = 1
       CALL DGEMM( '/', 'N', 0, 0, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 1
@@ -1961,20 +2012,20 @@
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 7
       CALL DSYMM( 'R', 'L', 0, 2, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL DSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
+      CALL DSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
+      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
+      INFOT = 9
+      CALL DSYMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL DSYMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL DSYMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL DSYMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
-      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
-      INFOT = 9
-      CALL DSYMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL DSYMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
       CALL DSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 2, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
@@ -2658,11 +2709,10 @@
      $            GO TO 70
    40       CONTINUE
    50    CONTINUE
       END IF
 *
-   60 CONTINUE
       LDERES = .TRUE.
       GO TO 80
    70 CONTINUE
       LDERES = .FALSE.
    80 RETURN

Index: 3rd_party/eigen/blas/testing/sblat2.f
==================================================================
--- 3rd_party/eigen/blas/testing/sblat2.f
+++ 3rd_party/eigen/blas/testing/sblat2.f
@@ -1,77 +1,123 @@
+*> \brief \b SBLAT2
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM SBLAT2
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*> Test program for the REAL Level 2 Blas.
+*>
+*> The program must be driven by a short data file. The first 18 records
+*> of the file are read using list-directed input, the last 16 records
+*> are read using the format ( A6, L2 ). An annotated example of a data
+*> file can be obtained by deleting the first 3 characters from the
+*> following 34 lines:
+*> 'sblat2.out'      NAME OF SUMMARY OUTPUT FILE
+*> 6                 UNIT NUMBER OF SUMMARY FILE
+*> 'SBLAT2.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
+*> -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
+*> F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
+*> F        LOGICAL FLAG, T TO STOP ON FAILURES.
+*> T        LOGICAL FLAG, T TO TEST ERROR EXITS.
+*> 16.0     THRESHOLD VALUE OF TEST RATIO
+*> 6                 NUMBER OF VALUES OF N
+*> 0 1 2 3 5 9       VALUES OF N
+*> 4                 NUMBER OF VALUES OF K
+*> 0 1 2 4           VALUES OF K
+*> 4                 NUMBER OF VALUES OF INCX AND INCY
+*> 1 2 -1 -2         VALUES OF INCX AND INCY
+*> 3                 NUMBER OF VALUES OF ALPHA
+*> 0.0 1.0 0.7       VALUES OF ALPHA
+*> 3                 NUMBER OF VALUES OF BETA
+*> 0.0 1.0 0.9       VALUES OF BETA
+*> SGEMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SGBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSYMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSPMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> STRMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> STBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> STPMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> STRSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> STBSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> STPSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SGER   T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSYR   T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSPR   T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSYR2  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSPR2  T PUT F FOR NO TEST. SAME COLUMNS.
+*>
+*> Further Details
+*> ===============
+*>
+*>    See:
+*>
+*>       Dongarra J. J., Du Croz J. J., Hammarling S.  and Hanson R. J..
+*>       An  extended  set of Fortran  Basic Linear Algebra Subprograms.
+*>
+*>       Technical  Memoranda  Nos. 41 (revision 3) and 81,  Mathematics
+*>       and  Computer Science  Division,  Argonne  National Laboratory,
+*>       9700 South Cass Avenue, Argonne, Illinois 60439, US.
+*>
+*>       Or
+*>
+*>       NAG  Technical Reports TR3/87 and TR4/87,  Numerical Algorithms
+*>       Group  Ltd.,  NAG  Central  Office,  256  Banbury  Road, Oxford
+*>       OX2 7DE, UK,  and  Numerical Algorithms Group Inc.,  1101  31st
+*>       Street,  Suite 100,  Downers Grove,  Illinois 60515-1263,  USA.
+*>
+*>
+*> -- Written on 10-August-1987.
+*>    Richard Hanson, Sandia National Labs.
+*>    Jeremy Du Croz, NAG Central Office.
+*>
+*>    10-9-00:  Change STATUS='NEW' to 'UNKNOWN' so that the testers
+*>              can be run multiple times without deleting generated
+*>              output files (susan)
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup single_blas_testing
+*
+*  =====================================================================
       PROGRAM SBLAT2
 *
-*  Test program for the REAL             Level 2 Blas.
-*
-*  The program must be driven by a short data file. The first 18 records
-*  of the file are read using list-directed input, the last 16 records
-*  are read using the format ( A6, L2 ). An annotated example of a data
-*  file can be obtained by deleting the first 3 characters from the
-*  following 34 lines:
-*  'SBLAT2.SUMM'     NAME OF SUMMARY OUTPUT FILE
-*  6                 UNIT NUMBER OF SUMMARY FILE
-*  'SBLAT2.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
-*  -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
-*  F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
-*  F        LOGICAL FLAG, T TO STOP ON FAILURES.
-*  T        LOGICAL FLAG, T TO TEST ERROR EXITS.
-*  16.0     THRESHOLD VALUE OF TEST RATIO
-*  6                 NUMBER OF VALUES OF N
-*  0 1 2 3 5 9       VALUES OF N
-*  4                 NUMBER OF VALUES OF K
-*  0 1 2 4           VALUES OF K
-*  4                 NUMBER OF VALUES OF INCX AND INCY
-*  1 2 -1 -2         VALUES OF INCX AND INCY
-*  3                 NUMBER OF VALUES OF ALPHA
-*  0.0 1.0 0.7       VALUES OF ALPHA
-*  3                 NUMBER OF VALUES OF BETA
-*  0.0 1.0 0.9       VALUES OF BETA
-*  SGEMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SGBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSYMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSPMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  STRMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  STBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  STPMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  STRSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  STBSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  STPSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SGER   T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSYR   T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSPR   T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSYR2  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSPR2  T PUT F FOR NO TEST. SAME COLUMNS.
-*
-*     See:
-*
-*        Dongarra J. J., Du Croz J. J., Hammarling S.  and Hanson R. J..
-*        An  extended  set of Fortran  Basic Linear Algebra Subprograms.
-*
-*        Technical  Memoranda  Nos. 41 (revision 3) and 81,  Mathematics
-*        and  Computer Science  Division,  Argonne  National Laboratory,
-*        9700 South Cass Avenue, Argonne, Illinois 60439, US.
-*
-*        Or
-*
-*        NAG  Technical Reports TR3/87 and TR4/87,  Numerical Algorithms
-*        Group  Ltd.,  NAG  Central  Office,  256  Banbury  Road, Oxford
-*        OX2 7DE, UK,  and  Numerical Algorithms Group Inc.,  1101  31st
-*        Street,  Suite 100,  Downers Grove,  Illinois 60515-1263,  USA.
-*
-*
-*  -- Written on 10-August-1987.
-*     Richard Hanson, Sandia National Labs.
-*     Jeremy Du Croz, NAG Central Office.
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
 *
 *     .. Parameters ..
       INTEGER            NIN
       PARAMETER          ( NIN = 5 )
       INTEGER            NSUBS
       PARAMETER          ( NSUBS = 16 )
-      REAL               ZERO, HALF, ONE
-      PARAMETER          ( ZERO = 0.0, HALF = 0.5, ONE = 1.0 )
+      REAL               ZERO, ONE
+      PARAMETER          ( ZERO = 0.0, ONE = 1.0 )
       INTEGER            NMAX, INCMAX
       PARAMETER          ( NMAX = 65, INCMAX = 2 )
       INTEGER            NINMAX, NIDMAX, NKBMAX, NALMAX, NBEMAX
       PARAMETER          ( NINMAX = 7, NIDMAX = 9, NKBMAX = 7,
      $                   NALMAX = 7, NBEMAX = 7 )
@@ -119,20 +165,20 @@
 *
 *     Read name and unit number for summary output file and open file.
 *
       READ( NIN, FMT = * )SUMMRY
       READ( NIN, FMT = * )NOUT
-      OPEN( NOUT, FILE = SUMMRY, STATUS = 'NEW' )
+      OPEN( NOUT, FILE = SUMMRY, STATUS = 'UNKNOWN' )
       NOUTC = NOUT
 *
 *     Read name and unit number for snapshot output file and open file.
 *
       READ( NIN, FMT = * )SNAPS
       READ( NIN, FMT = * )NTRA
       TRACE = NTRA.GE.0
       IF( TRACE )THEN
-         OPEN( NTRA, FILE = SNAPS, STATUS = 'NEW' )
+         OPEN( NTRA, FILE = SNAPS, STATUS = 'UNKNOWN' )
       END IF
 *     Read the flag that directs rewinding of the snapshot file.
       READ( NIN, FMT = * )REWI
       REWI = REWI.AND.TRACE
 *     Read the flag that directs stopping on any failure.
@@ -233,18 +279,11 @@
    80 CONTINUE
       CLOSE ( NIN )
 *
 *     Compute EPS (the machine precision).
 *
-      EPS = ONE
-   90 CONTINUE
-      IF( SDIFF( ONE + EPS, ONE ).EQ.ZERO )
-     $   GO TO 100
-      EPS = HALF*EPS
-      GO TO 90
-  100 CONTINUE
-      EPS = EPS + EPS
+      EPS = EPSILON(ZERO)
       WRITE( NOUT, FMT = 9998 )EPS
 *
 *     Check the reliability of SMVCH using exact data.
 *
       N = MIN( 32, NMAX )
@@ -2980,11 +3019,10 @@
      $            GO TO 70
    40       CONTINUE
    50    CONTINUE
       END IF
 *
-   60 CONTINUE
       LSERES = .TRUE.
       GO TO 80
    70 CONTINUE
       LSERES = .FALSE.
    80 RETURN

Index: 3rd_party/eigen/blas/testing/sblat3.f
==================================================================
--- 3rd_party/eigen/blas/testing/sblat3.f
+++ 3rd_party/eigen/blas/testing/sblat3.f
@@ -1,57 +1,103 @@
+*> \brief \b SBLAT3
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM SBLAT3
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*> Test program for the REAL             Level 3 Blas.
+*>
+*> The program must be driven by a short data file. The first 14 records
+*> of the file are read using list-directed input, the last 6 records
+*> are read using the format ( A6, L2 ). An annotated example of a data
+*> file can be obtained by deleting the first 3 characters from the
+*> following 20 lines:
+*> 'sblat3.out'      NAME OF SUMMARY OUTPUT FILE
+*> 6                 UNIT NUMBER OF SUMMARY FILE
+*> 'SBLAT3.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
+*> -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
+*> F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
+*> F        LOGICAL FLAG, T TO STOP ON FAILURES.
+*> T        LOGICAL FLAG, T TO TEST ERROR EXITS.
+*> 16.0     THRESHOLD VALUE OF TEST RATIO
+*> 6                 NUMBER OF VALUES OF N
+*> 0 1 2 3 5 9       VALUES OF N
+*> 3                 NUMBER OF VALUES OF ALPHA
+*> 0.0 1.0 0.7       VALUES OF ALPHA
+*> 3                 NUMBER OF VALUES OF BETA
+*> 0.0 1.0 1.3       VALUES OF BETA
+*> SGEMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSYMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> STRMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> STRSM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSYRK  T PUT F FOR NO TEST. SAME COLUMNS.
+*> SSYR2K T PUT F FOR NO TEST. SAME COLUMNS.
+*>
+*> Further Details
+*> ===============
+*>
+*> See:
+*>
+*>    Dongarra J. J., Du Croz J. J., Duff I. S. and Hammarling S.
+*>    A Set of Level 3 Basic Linear Algebra Subprograms.
+*>
+*>    Technical Memorandum No.88 (Revision 1), Mathematics and
+*>    Computer Science Division, Argonne National Laboratory, 9700
+*>    South Cass Avenue, Argonne, Illinois 60439, US.
+*>
+*> -- Written on 8-February-1989.
+*>    Jack Dongarra, Argonne National Laboratory.
+*>    Iain Duff, AERE Harwell.
+*>    Jeremy Du Croz, Numerical Algorithms Group Ltd.
+*>    Sven Hammarling, Numerical Algorithms Group Ltd.
+*>
+*>    10-9-00:  Change STATUS='NEW' to 'UNKNOWN' so that the testers
+*>              can be run multiple times without deleting generated
+*>              output files (susan)
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup single_blas_testing
+*
+*  =====================================================================
       PROGRAM SBLAT3
 *
-*  Test program for the REAL             Level 3 Blas.
-*
-*  The program must be driven by a short data file. The first 14 records
-*  of the file are read using list-directed input, the last 6 records
-*  are read using the format ( A6, L2 ). An annotated example of a data
-*  file can be obtained by deleting the first 3 characters from the
-*  following 20 lines:
-*  'SBLAT3.SUMM'     NAME OF SUMMARY OUTPUT FILE
-*  6                 UNIT NUMBER OF SUMMARY FILE
-*  'SBLAT3.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
-*  -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
-*  F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
-*  F        LOGICAL FLAG, T TO STOP ON FAILURES.
-*  T        LOGICAL FLAG, T TO TEST ERROR EXITS.
-*  16.0     THRESHOLD VALUE OF TEST RATIO
-*  6                 NUMBER OF VALUES OF N
-*  0 1 2 3 5 9       VALUES OF N
-*  3                 NUMBER OF VALUES OF ALPHA
-*  0.0 1.0 0.7       VALUES OF ALPHA
-*  3                 NUMBER OF VALUES OF BETA
-*  0.0 1.0 1.3       VALUES OF BETA
-*  SGEMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSYMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  STRMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  STRSM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSYRK  T PUT F FOR NO TEST. SAME COLUMNS.
-*  SSYR2K T PUT F FOR NO TEST. SAME COLUMNS.
-*
-*  See:
-*
-*     Dongarra J. J., Du Croz J. J., Duff I. S. and Hammarling S.
-*     A Set of Level 3 Basic Linear Algebra Subprograms.
-*
-*     Technical Memorandum No.88 (Revision 1), Mathematics and
-*     Computer Science Division, Argonne National Laboratory, 9700
-*     South Cass Avenue, Argonne, Illinois 60439, US.
-*
-*  -- Written on 8-February-1989.
-*     Jack Dongarra, Argonne National Laboratory.
-*     Iain Duff, AERE Harwell.
-*     Jeremy Du Croz, Numerical Algorithms Group Ltd.
-*     Sven Hammarling, Numerical Algorithms Group Ltd.
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
 *
 *     .. Parameters ..
       INTEGER            NIN
       PARAMETER          ( NIN = 5 )
       INTEGER            NSUBS
       PARAMETER          ( NSUBS = 6 )
-      REAL               ZERO, HALF, ONE
-      PARAMETER          ( ZERO = 0.0, HALF = 0.5, ONE = 1.0 )
+      REAL               ZERO, ONE
+      PARAMETER          ( ZERO = 0.0, ONE = 1.0 )
       INTEGER            NMAX
       PARAMETER          ( NMAX = 65 )
       INTEGER            NIDMAX, NALMAX, NBEMAX
       PARAMETER          ( NIDMAX = 9, NALMAX = 7, NBEMAX = 7 )
 *     .. Local Scalars ..
@@ -94,20 +140,20 @@
 *
 *     Read name and unit number for summary output file and open file.
 *
       READ( NIN, FMT = * )SUMMRY
       READ( NIN, FMT = * )NOUT
-      OPEN( NOUT, FILE = SUMMRY, STATUS = 'NEW' )
+      OPEN( NOUT, FILE = SUMMRY )
       NOUTC = NOUT
 *
 *     Read name and unit number for snapshot output file and open file.
 *
       READ( NIN, FMT = * )SNAPS
       READ( NIN, FMT = * )NTRA
       TRACE = NTRA.GE.0
       IF( TRACE )THEN
-         OPEN( NTRA, FILE = SNAPS, STATUS = 'NEW' )
+         OPEN( NTRA, FILE = SNAPS )
       END IF
 *     Read the flag that directs rewinding of the snapshot file.
       READ( NIN, FMT = * )REWI
       REWI = REWI.AND.TRACE
 *     Read the flag that directs stopping on any failure.
@@ -180,18 +226,11 @@
    60 CONTINUE
       CLOSE ( NIN )
 *
 *     Compute EPS (the machine precision).
 *
-      EPS = ONE
-   70 CONTINUE
-      IF( SDIFF( ONE + EPS, ONE ).EQ.ZERO )
-     $   GO TO 80
-      EPS = HALF*EPS
-      GO TO 70
-   80 CONTINUE
-      EPS = EPS + EPS
+      EPS = EPSILON(ZERO)
       WRITE( NOUT, FMT = 9998 )EPS
 *
 *     Check the reliability of SMMCH using exact data.
 *
       N = MIN( 32, NMAX )
@@ -1800,26 +1839,32 @@
       END
       SUBROUTINE SCHKE( ISNUM, SRNAMT, NOUT )
 *
 *  Tests the error exits from the Level 3 Blas.
 *  Requires a special version of the error-handling routine XERBLA.
-*  ALPHA, BETA, A, B and C should not need to be defined.
+*  A, B and C should not need to be defined.
 *
 *  Auxiliary routine for test program for Level 3 Blas.
 *
 *  -- Written on 8-February-1989.
 *     Jack Dongarra, Argonne National Laboratory.
 *     Iain Duff, AERE Harwell.
 *     Jeremy Du Croz, Numerical Algorithms Group Ltd.
 *     Sven Hammarling, Numerical Algorithms Group Ltd.
 *
+*  3-19-92:  Initialize ALPHA and BETA  (eca)
+*  3-19-92:  Fix argument 12 in calls to SSYMM with INFOT = 9  (eca)
+*
 *     .. Scalar Arguments ..
       INTEGER            ISNUM, NOUT
       CHARACTER*6        SRNAMT
 *     .. Scalars in Common ..
       INTEGER            INFOT, NOUTC
       LOGICAL            LERR, OK
+*     .. Parameters ..
+      REAL               ONE, TWO
+      PARAMETER          ( ONE = 1.0E0, TWO = 2.0E0 )
 *     .. Local Scalars ..
       REAL               ALPHA, BETA
 *     .. Local Arrays ..
       REAL               A( 2, 1 ), B( 2, 1 ), C( 2, 1 )
 *     .. External Subroutines ..
@@ -1832,10 +1877,16 @@
 *     if anything is wrong.
       OK = .TRUE.
 *     LERR is set to .TRUE. by the special version of XERBLA each time
 *     it is called, and is then tested and re-set by CHKXER.
       LERR = .FALSE.
+*
+*     Initialize ALPHA and BETA.
+*
+      ALPHA = ONE
+      BETA = TWO
+*
       GO TO ( 10, 20, 30, 40, 50, 60 )ISNUM
    10 INFOT = 1
       CALL SGEMM( '/', 'N', 0, 0, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 1
@@ -1961,20 +2012,20 @@
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 7
       CALL SSYMM( 'R', 'L', 0, 2, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL SSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
+      CALL SSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
+      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
+      INFOT = 9
+      CALL SSYMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL SSYMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL SSYMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL SSYMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
-      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
-      INFOT = 9
-      CALL SSYMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL SSYMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
       CALL SSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 2, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
@@ -2658,11 +2709,10 @@
      $            GO TO 70
    40       CONTINUE
    50    CONTINUE
       END IF
 *
-   60 CONTINUE
       LSERES = .TRUE.
       GO TO 80
    70 CONTINUE
       LSERES = .FALSE.
    80 RETURN

Index: 3rd_party/eigen/blas/testing/zblat1.f
==================================================================
--- 3rd_party/eigen/blas/testing/zblat1.f
+++ 3rd_party/eigen/blas/testing/zblat1.f
@@ -1,9 +1,51 @@
+*> \brief \b ZBLAT1
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM ZBLAT1
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*>    Test program for the COMPLEX*16 Level 1 BLAS.
+*>
+*>    Based upon the original BLAS test routine together with:
+*>    F06GAF Example Program Text
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup complex16_blas_testing
+*
+*  =====================================================================
       PROGRAM ZBLAT1
-*     Test program for the COMPLEX*16 Level 1 BLAS.
-*     Based upon the original BLAS test routine together with:
-*     F06GAF Example Program Text
+*
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
+*
 *     .. Parameters ..
       INTEGER          NOUT
       PARAMETER        (NOUT=6)
 *     .. Scalars in Common ..
       INTEGER          ICASE, INCX, INCY, MODE, N
@@ -112,12 +154,12 @@
      +                  (0.1D0,-0.3D0), (0.5D0,-0.1D0), (5.0D0,6.0D0),
      +                  (5.0D0,6.0D0), (5.0D0,6.0D0), (5.0D0,6.0D0),
      +                  (5.0D0,6.0D0), (5.0D0,6.0D0), (0.1D0,0.1D0),
      +                  (-0.6D0,0.1D0), (0.1D0,-0.3D0), (7.0D0,8.0D0),
      +                  (7.0D0,8.0D0), (7.0D0,8.0D0), (7.0D0,8.0D0),
-     +                  (7.0D0,8.0D0), (0.3D0,0.1D0), (0.1D0,0.4D0),
-     +                  (0.4D0,0.1D0), (0.1D0,0.2D0), (2.0D0,3.0D0),
+     +                  (7.0D0,8.0D0), (0.3D0,0.1D0), (0.5D0,0.0D0),
+     +                  (0.0D0,0.5D0), (0.0D0,0.2D0), (2.0D0,3.0D0),
      +                  (2.0D0,3.0D0), (2.0D0,3.0D0), (2.0D0,3.0D0)/
       DATA              ((CV(I,J,2),I=1,8),J=1,5)/(0.1D0,0.1D0),
      +                  (4.0D0,5.0D0), (4.0D0,5.0D0), (4.0D0,5.0D0),
      +                  (4.0D0,5.0D0), (4.0D0,5.0D0), (4.0D0,5.0D0),
      +                  (4.0D0,5.0D0), (0.3D0,-0.4D0), (6.0D0,7.0D0),
@@ -127,14 +169,14 @@
      +                  (2.0D0,5.0D0), (2.0D0,5.0D0), (2.0D0,5.0D0),
      +                  (2.0D0,5.0D0), (2.0D0,5.0D0), (0.1D0,0.1D0),
      +                  (3.0D0,6.0D0), (-0.6D0,0.1D0), (4.0D0,7.0D0),
      +                  (0.1D0,-0.3D0), (7.0D0,2.0D0), (7.0D0,2.0D0),
      +                  (7.0D0,2.0D0), (0.3D0,0.1D0), (5.0D0,8.0D0),
-     +                  (0.1D0,0.4D0), (6.0D0,9.0D0), (0.4D0,0.1D0),
-     +                  (8.0D0,3.0D0), (0.1D0,0.2D0), (9.0D0,4.0D0)/
-      DATA              STRUE2/0.0D0, 0.5D0, 0.6D0, 0.7D0, 0.7D0/
-      DATA              STRUE4/0.0D0, 0.7D0, 1.0D0, 1.3D0, 1.7D0/
+     +                  (0.5D0,0.0D0), (6.0D0,9.0D0), (0.0D0,0.5D0),
+     +                  (8.0D0,3.0D0), (0.0D0,0.2D0), (9.0D0,4.0D0)/
+      DATA              STRUE2/0.0D0, 0.5D0, 0.6D0, 0.7D0, 0.8D0/
+      DATA              STRUE4/0.0D0, 0.7D0, 1.0D0, 1.3D0, 1.6D0/
       DATA              ((CTRUE5(I,J,1),I=1,8),J=1,5)/(0.1D0,0.1D0),
      +                  (1.0D0,2.0D0), (1.0D0,2.0D0), (1.0D0,2.0D0),
      +                  (1.0D0,2.0D0), (1.0D0,2.0D0), (1.0D0,2.0D0),
      +                  (1.0D0,2.0D0), (-0.16D0,-0.37D0), (3.0D0,4.0D0),
      +                  (3.0D0,4.0D0), (3.0D0,4.0D0), (3.0D0,4.0D0),
@@ -143,12 +185,12 @@
      +                  (5.0D0,6.0D0), (5.0D0,6.0D0), (5.0D0,6.0D0),
      +                  (5.0D0,6.0D0), (5.0D0,6.0D0), (5.0D0,6.0D0),
      +                  (0.11D0,-0.03D0), (-0.17D0,0.46D0),
      +                  (-0.17D0,-0.19D0), (7.0D0,8.0D0), (7.0D0,8.0D0),
      +                  (7.0D0,8.0D0), (7.0D0,8.0D0), (7.0D0,8.0D0),
-     +                  (0.19D0,-0.17D0), (0.32D0,0.09D0),
-     +                  (0.23D0,-0.24D0), (0.18D0,0.01D0),
+     +                  (0.19D0,-0.17D0), (0.20D0,-0.35D0),
+     +                  (0.35D0,0.20D0), (0.14D0,0.08D0),
      +                  (2.0D0,3.0D0), (2.0D0,3.0D0), (2.0D0,3.0D0),
      +                  (2.0D0,3.0D0)/
       DATA              ((CTRUE5(I,J,2),I=1,8),J=1,5)/(0.1D0,0.1D0),
      +                  (4.0D0,5.0D0), (4.0D0,5.0D0), (4.0D0,5.0D0),
      +                  (4.0D0,5.0D0), (4.0D0,5.0D0), (4.0D0,5.0D0),
@@ -160,13 +202,13 @@
      +                  (2.0D0,5.0D0), (2.0D0,5.0D0), (2.0D0,5.0D0),
      +                  (0.11D0,-0.03D0), (3.0D0,6.0D0),
      +                  (-0.17D0,0.46D0), (4.0D0,7.0D0),
      +                  (-0.17D0,-0.19D0), (7.0D0,2.0D0), (7.0D0,2.0D0),
      +                  (7.0D0,2.0D0), (0.19D0,-0.17D0), (5.0D0,8.0D0),
-     +                  (0.32D0,0.09D0), (6.0D0,9.0D0),
-     +                  (0.23D0,-0.24D0), (8.0D0,3.0D0),
-     +                  (0.18D0,0.01D0), (9.0D0,4.0D0)/
+     +                  (0.20D0,-0.35D0), (6.0D0,9.0D0),
+     +                  (0.35D0,0.20D0), (8.0D0,3.0D0),
+     +                  (0.14D0,0.08D0), (9.0D0,4.0D0)/
       DATA              ((CTRUE6(I,J,1),I=1,8),J=1,5)/(0.1D0,0.1D0),
      +                  (1.0D0,2.0D0), (1.0D0,2.0D0), (1.0D0,2.0D0),
      +                  (1.0D0,2.0D0), (1.0D0,2.0D0), (1.0D0,2.0D0),
      +                  (1.0D0,2.0D0), (0.09D0,-0.12D0), (3.0D0,4.0D0),
      +                  (3.0D0,4.0D0), (3.0D0,4.0D0), (3.0D0,4.0D0),
@@ -175,12 +217,12 @@
      +                  (5.0D0,6.0D0), (5.0D0,6.0D0), (5.0D0,6.0D0),
      +                  (5.0D0,6.0D0), (5.0D0,6.0D0), (5.0D0,6.0D0),
      +                  (0.03D0,0.03D0), (-0.18D0,0.03D0),
      +                  (0.03D0,-0.09D0), (7.0D0,8.0D0), (7.0D0,8.0D0),
      +                  (7.0D0,8.0D0), (7.0D0,8.0D0), (7.0D0,8.0D0),
-     +                  (0.09D0,0.03D0), (0.03D0,0.12D0),
-     +                  (0.12D0,0.03D0), (0.03D0,0.06D0), (2.0D0,3.0D0),
+     +                  (0.09D0,0.03D0), (0.15D0,0.00D0),
+     +                  (0.00D0,0.15D0), (0.00D0,0.06D0), (2.0D0,3.0D0),
      +                  (2.0D0,3.0D0), (2.0D0,3.0D0), (2.0D0,3.0D0)/
       DATA              ((CTRUE6(I,J,2),I=1,8),J=1,5)/(0.1D0,0.1D0),
      +                  (4.0D0,5.0D0), (4.0D0,5.0D0), (4.0D0,5.0D0),
      +                  (4.0D0,5.0D0), (4.0D0,5.0D0), (4.0D0,5.0D0),
      +                  (4.0D0,5.0D0), (0.09D0,-0.12D0), (6.0D0,7.0D0),
@@ -191,12 +233,12 @@
      +                  (2.0D0,5.0D0), (2.0D0,5.0D0), (2.0D0,5.0D0),
      +                  (0.03D0,0.03D0), (3.0D0,6.0D0),
      +                  (-0.18D0,0.03D0), (4.0D0,7.0D0),
      +                  (0.03D0,-0.09D0), (7.0D0,2.0D0), (7.0D0,2.0D0),
      +                  (7.0D0,2.0D0), (0.09D0,0.03D0), (5.0D0,8.0D0),
-     +                  (0.03D0,0.12D0), (6.0D0,9.0D0), (0.12D0,0.03D0),
-     +                  (8.0D0,3.0D0), (0.03D0,0.06D0), (9.0D0,4.0D0)/
+     +                  (0.15D0,0.00D0), (6.0D0,9.0D0), (0.00D0,0.15D0),
+     +                  (8.0D0,3.0D0), (0.00D0,0.06D0), (9.0D0,4.0D0)/
       DATA              ITRUE3/0, 1, 2, 2, 2/
 *     .. Executable Statements ..
       DO 60 INCX = 1, 2
          DO 40 NP1 = 1, 5
             N = NP1 - 1
@@ -527,11 +569,12 @@
 *
 *     C. L. LAWSON, JPL, 1974 DEC 10
 *
 *     .. Parameters ..
       INTEGER          NOUT
-      PARAMETER        (NOUT=6)
+      DOUBLE PRECISION ZERO
+      PARAMETER        (NOUT=6, ZERO=0.0D0)
 *     .. Scalar Arguments ..
       DOUBLE PRECISION SFAC
       INTEGER          LEN
 *     .. Array Arguments ..
       DOUBLE PRECISION SCOMP(LEN), SSIZE(LEN), STRUE(LEN)
@@ -550,11 +593,11 @@
       COMMON           /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
 *     .. Executable Statements ..
 *
       DO 40 I = 1, LEN
          SD = SCOMP(I) - STRUE(I)
-         IF (SDIFF(ABS(SSIZE(I))+ABS(SFAC*SD),ABS(SSIZE(I))).EQ.0.0D0)
+         IF (ABS(SFAC*SD) .LE. ABS(SSIZE(I))*EPSILON(ZERO))
      +       GO TO 40
 *
 *                             HERE    SCOMP(I) IS NOT CLOSE TO STRUE(I).
 *
          IF ( .NOT. PASS) GO TO 20

Index: 3rd_party/eigen/blas/testing/zblat2.f
==================================================================
--- 3rd_party/eigen/blas/testing/zblat2.f
+++ 3rd_party/eigen/blas/testing/zblat2.f
@@ -1,81 +1,127 @@
+*> \brief \b ZBLAT2
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM ZBLAT2
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*> Test program for the COMPLEX*16       Level 2 Blas.
+*>
+*> The program must be driven by a short data file. The first 18 records
+*> of the file are read using list-directed input, the last 17 records
+*> are read using the format ( A6, L2 ). An annotated example of a data
+*> file can be obtained by deleting the first 3 characters from the
+*> following 35 lines:
+*> 'zblat2.out'      NAME OF SUMMARY OUTPUT FILE
+*> 6                 UNIT NUMBER OF SUMMARY FILE
+*> 'CBLA2T.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
+*> -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
+*> F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
+*> F        LOGICAL FLAG, T TO STOP ON FAILURES.
+*> T        LOGICAL FLAG, T TO TEST ERROR EXITS.
+*> 16.0     THRESHOLD VALUE OF TEST RATIO
+*> 6                 NUMBER OF VALUES OF N
+*> 0 1 2 3 5 9       VALUES OF N
+*> 4                 NUMBER OF VALUES OF K
+*> 0 1 2 4           VALUES OF K
+*> 4                 NUMBER OF VALUES OF INCX AND INCY
+*> 1 2 -1 -2         VALUES OF INCX AND INCY
+*> 3                 NUMBER OF VALUES OF ALPHA
+*> (0.0,0.0) (1.0,0.0) (0.7,-0.9)       VALUES OF ALPHA
+*> 3                 NUMBER OF VALUES OF BETA
+*> (0.0,0.0) (1.0,0.0) (1.3,-1.1)       VALUES OF BETA
+*> ZGEMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZGBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHEMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHPMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZTRMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZTBMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZTPMV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZTRSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZTBSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZTPSV  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZGERC  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZGERU  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHER   T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHPR   T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHER2  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHPR2  T PUT F FOR NO TEST. SAME COLUMNS.
+*>
+*> Further Details
+*> ===============
+*>
+*>    See:
+*>
+*>       Dongarra J. J., Du Croz J. J., Hammarling S.  and Hanson R. J..
+*>       An  extended  set of Fortran  Basic Linear Algebra Subprograms.
+*>
+*>       Technical  Memoranda  Nos. 41 (revision 3) and 81,  Mathematics
+*>       and  Computer Science  Division,  Argonne  National Laboratory,
+*>       9700 South Cass Avenue, Argonne, Illinois 60439, US.
+*>
+*>       Or
+*>
+*>       NAG  Technical Reports TR3/87 and TR4/87,  Numerical Algorithms
+*>       Group  Ltd.,  NAG  Central  Office,  256  Banbury  Road, Oxford
+*>       OX2 7DE, UK,  and  Numerical Algorithms Group Inc.,  1101  31st
+*>       Street,  Suite 100,  Downers Grove,  Illinois 60515-1263,  USA.
+*>
+*>
+*> -- Written on 10-August-1987.
+*>    Richard Hanson, Sandia National Labs.
+*>    Jeremy Du Croz, NAG Central Office.
+*>
+*>    10-9-00:  Change STATUS='NEW' to 'UNKNOWN' so that the testers
+*>              can be run multiple times without deleting generated
+*>              output files (susan)
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup complex16_blas_testing
+*
+*  =====================================================================
       PROGRAM ZBLAT2
 *
-*  Test program for the COMPLEX*16       Level 2 Blas.
-*
-*  The program must be driven by a short data file. The first 18 records
-*  of the file are read using list-directed input, the last 17 records
-*  are read using the format ( A6, L2 ). An annotated example of a data
-*  file can be obtained by deleting the first 3 characters from the
-*  following 35 lines:
-*  'ZBLAT2.SUMM'     NAME OF SUMMARY OUTPUT FILE
-*  6                 UNIT NUMBER OF SUMMARY FILE
-*  'CBLA2T.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
-*  -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
-*  F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
-*  F        LOGICAL FLAG, T TO STOP ON FAILURES.
-*  T        LOGICAL FLAG, T TO TEST ERROR EXITS.
-*  16.0     THRESHOLD VALUE OF TEST RATIO
-*  6                 NUMBER OF VALUES OF N
-*  0 1 2 3 5 9       VALUES OF N
-*  4                 NUMBER OF VALUES OF K
-*  0 1 2 4           VALUES OF K
-*  4                 NUMBER OF VALUES OF INCX AND INCY
-*  1 2 -1 -2         VALUES OF INCX AND INCY
-*  3                 NUMBER OF VALUES OF ALPHA
-*  (0.0,0.0) (1.0,0.0) (0.7,-0.9)       VALUES OF ALPHA
-*  3                 NUMBER OF VALUES OF BETA
-*  (0.0,0.0) (1.0,0.0) (1.3,-1.1)       VALUES OF BETA
-*  ZGEMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZGBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHEMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHPMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZTRMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZTBMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZTPMV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZTRSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZTBSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZTPSV  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZGERC  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZGERU  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHER   T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHPR   T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHER2  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHPR2  T PUT F FOR NO TEST. SAME COLUMNS.
-*
-*     See:
-*
-*        Dongarra J. J., Du Croz J. J., Hammarling S.  and Hanson R. J..
-*        An  extended  set of Fortran  Basic Linear Algebra Subprograms.
-*
-*        Technical  Memoranda  Nos. 41 (revision 3) and 81,  Mathematics
-*        and  Computer Science  Division,  Argonne  National Laboratory,
-*        9700 South Cass Avenue, Argonne, Illinois 60439, US.
-*
-*        Or
-*
-*        NAG  Technical Reports TR3/87 and TR4/87,  Numerical Algorithms
-*        Group  Ltd.,  NAG  Central  Office,  256  Banbury  Road, Oxford
-*        OX2 7DE, UK,  and  Numerical Algorithms Group Inc.,  1101  31st
-*        Street,  Suite 100,  Downers Grove,  Illinois 60515-1263,  USA.
-*
-*
-*  -- Written on 10-August-1987.
-*     Richard Hanson, Sandia National Labs.
-*     Jeremy Du Croz, NAG Central Office.
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
 *
 *     .. Parameters ..
       INTEGER            NIN
       PARAMETER          ( NIN = 5 )
       INTEGER            NSUBS
       PARAMETER          ( NSUBS = 17 )
       COMPLEX*16         ZERO, ONE
       PARAMETER          ( ZERO = ( 0.0D0, 0.0D0 ),
      $                   ONE = ( 1.0D0, 0.0D0 ) )
-      DOUBLE PRECISION   RZERO, RHALF, RONE
-      PARAMETER          ( RZERO = 0.0D0, RHALF = 0.5D0, RONE = 1.0D0 )
+      DOUBLE PRECISION   RZERO
+      PARAMETER          ( RZERO = 0.0D0 )
       INTEGER            NMAX, INCMAX
       PARAMETER          ( NMAX = 65, INCMAX = 2 )
       INTEGER            NINMAX, NIDMAX, NKBMAX, NALMAX, NBEMAX
       PARAMETER          ( NINMAX = 7, NIDMAX = 9, NKBMAX = 7,
      $                   NALMAX = 7, NBEMAX = 7 )
@@ -125,20 +171,20 @@
 *
 *     Read name and unit number for summary output file and open file.
 *
       READ( NIN, FMT = * )SUMMRY
       READ( NIN, FMT = * )NOUT
-      OPEN( NOUT, FILE = SUMMRY, STATUS = 'NEW' )
+      OPEN( NOUT, FILE = SUMMRY, STATUS = 'UNKNOWN' )
       NOUTC = NOUT
 *
 *     Read name and unit number for snapshot output file and open file.
 *
       READ( NIN, FMT = * )SNAPS
       READ( NIN, FMT = * )NTRA
       TRACE = NTRA.GE.0
       IF( TRACE )THEN
-         OPEN( NTRA, FILE = SNAPS, STATUS = 'NEW' )
+         OPEN( NTRA, FILE = SNAPS, STATUS = 'UNKNOWN' )
       END IF
 *     Read the flag that directs rewinding of the snapshot file.
       READ( NIN, FMT = * )REWI
       REWI = REWI.AND.TRACE
 *     Read the flag that directs stopping on any failure.
@@ -239,18 +285,11 @@
    80 CONTINUE
       CLOSE ( NIN )
 *
 *     Compute EPS (the machine precision).
 *
-      EPS = RONE
-   90 CONTINUE
-      IF( DDIFF( RONE + EPS, RONE ).EQ.RZERO )
-     $   GO TO 100
-      EPS = RHALF*EPS
-      GO TO 90
-  100 CONTINUE
-      EPS = EPS + EPS
+      EPS = EPSILON(RZERO)
       WRITE( NOUT, FMT = 9998 )EPS
 *
 *     Check the reliability of ZMVCH using exact data.
 *
       N = MIN( 32, NMAX )
@@ -3085,11 +3124,10 @@
      $            GO TO 70
    40       CONTINUE
    50    CONTINUE
       END IF
 *
-   60 CONTINUE
       LZERES = .TRUE.
       GO TO 80
    70 CONTINUE
       LZERES = .FALSE.
    80 RETURN

Index: 3rd_party/eigen/blas/testing/zblat3.f
==================================================================
--- 3rd_party/eigen/blas/testing/zblat3.f
+++ 3rd_party/eigen/blas/testing/zblat3.f
@@ -1,63 +1,110 @@
+*> \brief \b ZBLAT3
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition:
+*  ===========
+*
+*       PROGRAM ZBLAT3
+* 
+*
+*> \par Purpose:
+*  =============
+*>
+*> \verbatim
+*>
+*> Test program for the COMPLEX*16       Level 3 Blas.
+*>
+*> The program must be driven by a short data file. The first 14 records
+*> of the file are read using list-directed input, the last 9 records
+*> are read using the format ( A6, L2 ). An annotated example of a data
+*> file can be obtained by deleting the first 3 characters from the
+*> following 23 lines:
+*> 'zblat3.out'      NAME OF SUMMARY OUTPUT FILE
+*> 6                 UNIT NUMBER OF SUMMARY FILE
+*> 'ZBLAT3.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
+*> -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
+*> F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
+*> F        LOGICAL FLAG, T TO STOP ON FAILURES.
+*> T        LOGICAL FLAG, T TO TEST ERROR EXITS.
+*> 16.0     THRESHOLD VALUE OF TEST RATIO
+*> 6                 NUMBER OF VALUES OF N
+*> 0 1 2 3 5 9       VALUES OF N
+*> 3                 NUMBER OF VALUES OF ALPHA
+*> (0.0,0.0) (1.0,0.0) (0.7,-0.9)       VALUES OF ALPHA
+*> 3                 NUMBER OF VALUES OF BETA
+*> (0.0,0.0) (1.0,0.0) (1.3,-1.1)       VALUES OF BETA
+*> ZGEMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHEMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZSYMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZTRMM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZTRSM  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHERK  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZSYRK  T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZHER2K T PUT F FOR NO TEST. SAME COLUMNS.
+*> ZSYR2K T PUT F FOR NO TEST. SAME COLUMNS.
+*>
+*> 
+*> Further Details
+*> ===============
+*>
+*> See:
+*>
+*>    Dongarra J. J., Du Croz J. J., Duff I. S. and Hammarling S.
+*>    A Set of Level 3 Basic Linear Algebra Subprograms.
+*>
+*>    Technical Memorandum No.88 (Revision 1), Mathematics and
+*>    Computer Science Division, Argonne National Laboratory, 9700
+*>    South Cass Avenue, Argonne, Illinois 60439, US.
+*>
+*> -- Written on 8-February-1989.
+*>    Jack Dongarra, Argonne National Laboratory.
+*>    Iain Duff, AERE Harwell.
+*>    Jeremy Du Croz, Numerical Algorithms Group Ltd.
+*>    Sven Hammarling, Numerical Algorithms Group Ltd.
+*>
+*>    10-9-00:  Change STATUS='NEW' to 'UNKNOWN' so that the testers
+*>              can be run multiple times without deleting generated
+*>              output files (susan)
+*> \endverbatim
+*
+*  Authors:
+*  ========
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date April 2012
+*
+*> \ingroup complex16_blas_testing
+*
+*  =====================================================================
       PROGRAM ZBLAT3
 *
-*  Test program for the COMPLEX*16       Level 3 Blas.
-*
-*  The program must be driven by a short data file. The first 14 records
-*  of the file are read using list-directed input, the last 9 records
-*  are read using the format ( A6, L2 ). An annotated example of a data
-*  file can be obtained by deleting the first 3 characters from the
-*  following 23 lines:
-*  'ZBLAT3.SUMM'     NAME OF SUMMARY OUTPUT FILE
-*  6                 UNIT NUMBER OF SUMMARY FILE
-*  'ZBLAT3.SNAP'     NAME OF SNAPSHOT OUTPUT FILE
-*  -1                UNIT NUMBER OF SNAPSHOT FILE (NOT USED IF .LT. 0)
-*  F        LOGICAL FLAG, T TO REWIND SNAPSHOT FILE AFTER EACH RECORD.
-*  F        LOGICAL FLAG, T TO STOP ON FAILURES.
-*  T        LOGICAL FLAG, T TO TEST ERROR EXITS.
-*  16.0     THRESHOLD VALUE OF TEST RATIO
-*  6                 NUMBER OF VALUES OF N
-*  0 1 2 3 5 9       VALUES OF N
-*  3                 NUMBER OF VALUES OF ALPHA
-*  (0.0,0.0) (1.0,0.0) (0.7,-0.9)       VALUES OF ALPHA
-*  3                 NUMBER OF VALUES OF BETA
-*  (0.0,0.0) (1.0,0.0) (1.3,-1.1)       VALUES OF BETA
-*  ZGEMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHEMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZSYMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZTRMM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZTRSM  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHERK  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZSYRK  T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZHER2K T PUT F FOR NO TEST. SAME COLUMNS.
-*  ZSYR2K T PUT F FOR NO TEST. SAME COLUMNS.
-*
-*  See:
-*
-*     Dongarra J. J., Du Croz J. J., Duff I. S. and Hammarling S.
-*     A Set of Level 3 Basic Linear Algebra Subprograms.
-*
-*     Technical Memorandum No.88 (Revision 1), Mathematics and
-*     Computer Science Division, Argonne National Laboratory, 9700
-*     South Cass Avenue, Argonne, Illinois 60439, US.
-*
-*  -- Written on 8-February-1989.
-*     Jack Dongarra, Argonne National Laboratory.
-*     Iain Duff, AERE Harwell.
-*     Jeremy Du Croz, Numerical Algorithms Group Ltd.
-*     Sven Hammarling, Numerical Algorithms Group Ltd.
+*  -- Reference BLAS test routine (version 3.4.1) --
+*  -- Reference BLAS is a software package provided by Univ. of Tennessee,    --
+*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+*     April 2012
+*
+*  =====================================================================
 *
 *     .. Parameters ..
       INTEGER            NIN
       PARAMETER          ( NIN = 5 )
       INTEGER            NSUBS
       PARAMETER          ( NSUBS = 9 )
       COMPLEX*16         ZERO, ONE
       PARAMETER          ( ZERO = ( 0.0D0, 0.0D0 ),
      $                   ONE = ( 1.0D0, 0.0D0 ) )
-      DOUBLE PRECISION   RZERO, RHALF, RONE
-      PARAMETER          ( RZERO = 0.0D0, RHALF = 0.5D0, RONE = 1.0D0 )
+      DOUBLE PRECISION   RZERO
+      PARAMETER          ( RZERO = 0.0D0 )
       INTEGER            NMAX
       PARAMETER          ( NMAX = 65 )
       INTEGER            NIDMAX, NALMAX, NBEMAX
       PARAMETER          ( NIDMAX = 9, NALMAX = 7, NBEMAX = 7 )
 *     .. Local Scalars ..
@@ -102,20 +149,20 @@
 *
 *     Read name and unit number for summary output file and open file.
 *
       READ( NIN, FMT = * )SUMMRY
       READ( NIN, FMT = * )NOUT
-      OPEN( NOUT, FILE = SUMMRY, STATUS = 'NEW' )
+      OPEN( NOUT, FILE = SUMMRY, STATUS = 'UNKNOWN' )
       NOUTC = NOUT
 *
 *     Read name and unit number for snapshot output file and open file.
 *
       READ( NIN, FMT = * )SNAPS
       READ( NIN, FMT = * )NTRA
       TRACE = NTRA.GE.0
       IF( TRACE )THEN
-         OPEN( NTRA, FILE = SNAPS, STATUS = 'NEW' )
+         OPEN( NTRA, FILE = SNAPS, STATUS = 'UNKNOWN' )
       END IF
 *     Read the flag that directs rewinding of the snapshot file.
       READ( NIN, FMT = * )REWI
       REWI = REWI.AND.TRACE
 *     Read the flag that directs stopping on any failure.
@@ -188,18 +235,11 @@
    60 CONTINUE
       CLOSE ( NIN )
 *
 *     Compute EPS (the machine precision).
 *
-      EPS = RONE
-   70 CONTINUE
-      IF( DDIFF( RONE + EPS, RONE ).EQ.RZERO )
-     $   GO TO 80
-      EPS = RHALF*EPS
-      GO TO 70
-   80 CONTINUE
-      EPS = EPS + EPS
+      EPS = EPSILON(RZERO)
       WRITE( NOUT, FMT = 9998 )EPS
 *
 *     Check the reliability of ZMMCH using exact data.
 *
       N = MIN( 32, NMAX )
@@ -1947,43 +1987,61 @@
       END
       SUBROUTINE ZCHKE( ISNUM, SRNAMT, NOUT )
 *
 *  Tests the error exits from the Level 3 Blas.
 *  Requires a special version of the error-handling routine XERBLA.
-*  ALPHA, RALPHA, BETA, RBETA, A, B and C should not need to be defined.
+*  A, B and C should not need to be defined.
 *
 *  Auxiliary routine for test program for Level 3 Blas.
 *
 *  -- Written on 8-February-1989.
 *     Jack Dongarra, Argonne National Laboratory.
 *     Iain Duff, AERE Harwell.
 *     Jeremy Du Croz, Numerical Algorithms Group Ltd.
 *     Sven Hammarling, Numerical Algorithms Group Ltd.
+*
+*  3-19-92:  Initialize ALPHA, BETA, RALPHA, and RBETA  (eca)
+*  3-19-92:  Fix argument 12 in calls to ZSYMM and ZHEMM
+*            with INFOT = 9  (eca)
+*  10-9-00:  Declared INTRINSIC DCMPLX (susan)
 *
 *     .. Scalar Arguments ..
       INTEGER            ISNUM, NOUT
       CHARACTER*6        SRNAMT
 *     .. Scalars in Common ..
       INTEGER            INFOT, NOUTC
       LOGICAL            LERR, OK
+*     .. Parameters ..
+      REAL               ONE, TWO
+      PARAMETER          ( ONE = 1.0D0, TWO = 2.0D0 )
 *     .. Local Scalars ..
       COMPLEX*16         ALPHA, BETA
       DOUBLE PRECISION   RALPHA, RBETA
 *     .. Local Arrays ..
       COMPLEX*16         A( 2, 1 ), B( 2, 1 ), C( 2, 1 )
 *     .. External Subroutines ..
       EXTERNAL           ZGEMM, ZHEMM, ZHER2K, ZHERK, CHKXER, ZSYMM,
      $                   ZSYR2K, ZSYRK, ZTRMM, ZTRSM
+*     .. Intrinsic Functions ..
+      INTRINSIC          DCMPLX
 *     .. Common blocks ..
       COMMON             /INFOC/INFOT, NOUTC, OK, LERR
 *     .. Executable Statements ..
 *     OK is set to .FALSE. by the special version of XERBLA or by CHKXER
 *     if anything is wrong.
       OK = .TRUE.
 *     LERR is set to .TRUE. by the special version of XERBLA each time
 *     it is called, and is then tested and re-set by CHKXER.
       LERR = .FALSE.
+*
+*     Initialize ALPHA, BETA, RALPHA, and RBETA.
+*
+      ALPHA = DCMPLX( ONE, -ONE )
+      BETA = DCMPLX( TWO, -TWO )
+      RALPHA = ONE
+      RBETA = TWO
+*
       GO TO ( 10, 20, 30, 40, 50, 60, 70, 80,
      $        90 )ISNUM
    10 INFOT = 1
       CALL ZGEMM( '/', 'N', 0, 0, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
@@ -2206,20 +2264,20 @@
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 7
       CALL ZHEMM( 'R', 'L', 0, 2, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL ZHEMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
+      CALL ZHEMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
+      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
+      INFOT = 9
+      CALL ZHEMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL ZHEMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL ZHEMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL ZHEMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
-      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
-      INFOT = 9
-      CALL ZHEMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL ZHEMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
       CALL ZHEMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 2, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
@@ -2273,20 +2331,20 @@
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 7
       CALL ZSYMM( 'R', 'L', 0, 2, ALPHA, A, 1, B, 1, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL ZSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
+      CALL ZSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
+      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
+      INFOT = 9
+      CALL ZSYMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL ZSYMM( 'R', 'U', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL ZSYMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 9
-      CALL ZSYMM( 'L', 'L', 2, 0, ALPHA, A, 2, B, 1, BETA, C, 1 )
-      CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
-      INFOT = 9
-      CALL ZSYMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 1 )
+      CALL ZSYMM( 'R', 'L', 2, 0, ALPHA, A, 1, B, 1, BETA, C, 2 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
       CALL ZSYMM( 'L', 'U', 2, 0, ALPHA, A, 2, B, 2, BETA, C, 1 )
       CALL CHKXER( SRNAMT, INFOT, NOUT, LERR, OK )
       INFOT = 12
@@ -3272,11 +3330,10 @@
      $            GO TO 70
    40       CONTINUE
    50    CONTINUE
       END IF
 *
-   60 CONTINUE
       LZERES = .TRUE.
       GO TO 80
    70 CONTINUE
       LZERES = .FALSE.
    80 RETURN

Index: 3rd_party/eigen/blas/xerbla.cpp
==================================================================
--- 3rd_party/eigen/blas/xerbla.cpp
+++ 3rd_party/eigen/blas/xerbla.cpp
@@ -1,9 +1,9 @@
 
-#include <iostream>
+#include <stdio.h>
 
-#if (defined __GNUC__)
+#if (defined __GNUC__) && (!defined __MINGW32__) && (!defined __CYGWIN__)
 #define EIGEN_WEAK_LINKING __attribute__ ((weak))
 #else
 #define EIGEN_WEAK_LINKING
 #endif
 
@@ -12,12 +12,12 @@
 {
 #endif
 
 EIGEN_WEAK_LINKING int xerbla_(const char * msg, int *info, int)
 {
-  std::cerr << "Eigen BLAS ERROR #" << *info << ": " << msg << "\n";
+  printf("Eigen BLAS ERROR #%i: %s\n", *info, msg );
   return 0;
 }
 
 #ifdef __cplusplus
 }
 #endif

DELETED 3rd_party/eigen/blas/zhbmv.f
Index: 3rd_party/eigen/blas/zhbmv.f
==================================================================
--- 3rd_party/eigen/blas/zhbmv.f
+++ 3rd_party/eigen/blas/zhbmv.f
@@ -1,310 +0,0 @@
-      SUBROUTINE ZHBMV(UPLO,N,K,ALPHA,A,LDA,X,INCX,BETA,Y,INCY)
-*     .. Scalar Arguments ..
-      DOUBLE COMPLEX ALPHA,BETA
-      INTEGER INCX,INCY,K,LDA,N
-      CHARACTER UPLO
-*     ..
-*     .. Array Arguments ..
-      DOUBLE COMPLEX A(LDA,*),X(*),Y(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  ZHBMV  performs the matrix-vector  operation
-*
-*     y := alpha*A*x + beta*y,
-*
-*  where alpha and beta are scalars, x and y are n element vectors and
-*  A is an n by n hermitian band matrix, with k super-diagonals.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the upper or lower
-*           triangular part of the band matrix A is being supplied as
-*           follows:
-*
-*              UPLO = 'U' or 'u'   The upper triangular part of A is
-*                                  being supplied.
-*
-*              UPLO = 'L' or 'l'   The lower triangular part of A is
-*                                  being supplied.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  K      - INTEGER.
-*           On entry, K specifies the number of super-diagonals of the
-*           matrix A. K must satisfy  0 .le. K.
-*           Unchanged on exit.
-*
-*  ALPHA  - COMPLEX*16      .
-*           On entry, ALPHA specifies the scalar alpha.
-*           Unchanged on exit.
-*
-*  A      - COMPLEX*16       array of DIMENSION ( LDA, n ).
-*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 )
-*           by n part of the array A must contain the upper triangular
-*           band part of the hermitian matrix, supplied column by
-*           column, with the leading diagonal of the matrix in row
-*           ( k + 1 ) of the array, the first super-diagonal starting at
-*           position 2 in row k, and so on. The top left k by k triangle
-*           of the array A is not referenced.
-*           The following program segment will transfer the upper
-*           triangular part of a hermitian band matrix from conventional
-*           full matrix storage to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = K + 1 - J
-*                    DO 10, I = MAX( 1, J - K ), J
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 )
-*           by n part of the array A must contain the lower triangular
-*           band part of the hermitian matrix, supplied column by
-*           column, with the leading diagonal of the matrix in row 1 of
-*           the array, the first sub-diagonal starting at position 1 in
-*           row 2, and so on. The bottom right k by k triangle of the
-*           array A is not referenced.
-*           The following program segment will transfer the lower
-*           triangular part of a hermitian band matrix from conventional
-*           full matrix storage to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = 1 - J
-*                    DO 10, I = J, MIN( N, J + K )
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Note that the imaginary parts of the diagonal elements need
-*           not be set and are assumed to be zero.
-*           Unchanged on exit.
-*
-*  LDA    - INTEGER.
-*           On entry, LDA specifies the first dimension of A as declared
-*           in the calling (sub) program. LDA must be at least
-*           ( k + 1 ).
-*           Unchanged on exit.
-*
-*  X      - COMPLEX*16       array of DIMENSION at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the
-*           vector x.
-*           Unchanged on exit.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  BETA   - COMPLEX*16      .
-*           On entry, BETA specifies the scalar beta.
-*           Unchanged on exit.
-*
-*  Y      - COMPLEX*16       array of DIMENSION at least
-*           ( 1 + ( n - 1 )*abs( INCY ) ).
-*           Before entry, the incremented array Y must contain the
-*           vector y. On exit, Y is overwritten by the updated vector y.
-*
-*  INCY   - INTEGER.
-*           On entry, INCY specifies the increment for the elements of
-*           Y. INCY must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      DOUBLE COMPLEX ONE
-      PARAMETER (ONE= (1.0D+0,0.0D+0))
-      DOUBLE COMPLEX ZERO
-      PARAMETER (ZERO= (0.0D+0,0.0D+0))
-*     ..
-*     .. Local Scalars ..
-      DOUBLE COMPLEX TEMP1,TEMP2
-      INTEGER I,INFO,IX,IY,J,JX,JY,KPLUS1,KX,KY,L
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC DBLE,DCONJG,MAX,MIN
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (N.LT.0) THEN
-          INFO = 2
-      ELSE IF (K.LT.0) THEN
-          INFO = 3
-      ELSE IF (LDA.LT. (K+1)) THEN
-          INFO = 6
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 8
-      ELSE IF (INCY.EQ.0) THEN
-          INFO = 11
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('ZHBMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF ((N.EQ.0) .OR. ((ALPHA.EQ.ZERO).AND. (BETA.EQ.ONE))) RETURN
-*
-*     Set up the start points in  X  and  Y.
-*
-      IF (INCX.GT.0) THEN
-          KX = 1
-      ELSE
-          KX = 1 - (N-1)*INCX
-      END IF
-      IF (INCY.GT.0) THEN
-          KY = 1
-      ELSE
-          KY = 1 - (N-1)*INCY
-      END IF
-*
-*     Start the operations. In this version the elements of the array A
-*     are accessed sequentially with one pass through A.
-*
-*     First form  y := beta*y.
-*
-      IF (BETA.NE.ONE) THEN
-          IF (INCY.EQ.1) THEN
-              IF (BETA.EQ.ZERO) THEN
-                  DO 10 I = 1,N
-                      Y(I) = ZERO
-   10             CONTINUE
-              ELSE
-                  DO 20 I = 1,N
-                      Y(I) = BETA*Y(I)
-   20             CONTINUE
-              END IF
-          ELSE
-              IY = KY
-              IF (BETA.EQ.ZERO) THEN
-                  DO 30 I = 1,N
-                      Y(IY) = ZERO
-                      IY = IY + INCY
-   30             CONTINUE
-              ELSE
-                  DO 40 I = 1,N
-                      Y(IY) = BETA*Y(IY)
-                      IY = IY + INCY
-   40             CONTINUE
-              END IF
-          END IF
-      END IF
-      IF (ALPHA.EQ.ZERO) RETURN
-      IF (LSAME(UPLO,'U')) THEN
-*
-*        Form  y  when upper triangle of A is stored.
-*
-          KPLUS1 = K + 1
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 60 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  L = KPLUS1 - J
-                  DO 50 I = MAX(1,J-K),J - 1
-                      Y(I) = Y(I) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + DCONJG(A(L+I,J))*X(I)
-   50             CONTINUE
-                  Y(J) = Y(J) + TEMP1*DBLE(A(KPLUS1,J)) + ALPHA*TEMP2
-   60         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 80 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  IX = KX
-                  IY = KY
-                  L = KPLUS1 - J
-                  DO 70 I = MAX(1,J-K),J - 1
-                      Y(IY) = Y(IY) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + DCONJG(A(L+I,J))*X(IX)
-                      IX = IX + INCX
-                      IY = IY + INCY
-   70             CONTINUE
-                  Y(JY) = Y(JY) + TEMP1*DBLE(A(KPLUS1,J)) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  IF (J.GT.K) THEN
-                      KX = KX + INCX
-                      KY = KY + INCY
-                  END IF
-   80         CONTINUE
-          END IF
-      ELSE
-*
-*        Form  y  when lower triangle of A is stored.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 100 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  Y(J) = Y(J) + TEMP1*DBLE(A(1,J))
-                  L = 1 - J
-                  DO 90 I = J + 1,MIN(N,J+K)
-                      Y(I) = Y(I) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + DCONJG(A(L+I,J))*X(I)
-   90             CONTINUE
-                  Y(J) = Y(J) + ALPHA*TEMP2
-  100         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 120 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  Y(JY) = Y(JY) + TEMP1*DBLE(A(1,J))
-                  L = 1 - J
-                  IX = JX
-                  IY = JY
-                  DO 110 I = J + 1,MIN(N,J+K)
-                      IX = IX + INCX
-                      IY = IY + INCY
-                      Y(IY) = Y(IY) + TEMP1*A(L+I,J)
-                      TEMP2 = TEMP2 + DCONJG(A(L+I,J))*X(IX)
-  110             CONTINUE
-                  Y(JY) = Y(JY) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-  120         CONTINUE
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of ZHBMV .
-*
-      END

DELETED 3rd_party/eigen/blas/zhpmv.f
Index: 3rd_party/eigen/blas/zhpmv.f
==================================================================
--- 3rd_party/eigen/blas/zhpmv.f
+++ 3rd_party/eigen/blas/zhpmv.f
@@ -1,272 +0,0 @@
-      SUBROUTINE ZHPMV(UPLO,N,ALPHA,AP,X,INCX,BETA,Y,INCY)
-*     .. Scalar Arguments ..
-      DOUBLE COMPLEX ALPHA,BETA
-      INTEGER INCX,INCY,N
-      CHARACTER UPLO
-*     ..
-*     .. Array Arguments ..
-      DOUBLE COMPLEX AP(*),X(*),Y(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  ZHPMV  performs the matrix-vector operation
-*
-*     y := alpha*A*x + beta*y,
-*
-*  where alpha and beta are scalars, x and y are n element vectors and
-*  A is an n by n hermitian matrix, supplied in packed form.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the upper or lower
-*           triangular part of the matrix A is supplied in the packed
-*           array AP as follows:
-*
-*              UPLO = 'U' or 'u'   The upper triangular part of A is
-*                                  supplied in AP.
-*
-*              UPLO = 'L' or 'l'   The lower triangular part of A is
-*                                  supplied in AP.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  ALPHA  - COMPLEX*16      .
-*           On entry, ALPHA specifies the scalar alpha.
-*           Unchanged on exit.
-*
-*  AP     - COMPLEX*16       array of DIMENSION at least
-*           ( ( n*( n + 1 ) )/2 ).
-*           Before entry with UPLO = 'U' or 'u', the array AP must
-*           contain the upper triangular part of the hermitian matrix
-*           packed sequentially, column by column, so that AP( 1 )
-*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-*           and a( 2, 2 ) respectively, and so on.
-*           Before entry with UPLO = 'L' or 'l', the array AP must
-*           contain the lower triangular part of the hermitian matrix
-*           packed sequentially, column by column, so that AP( 1 )
-*           contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-*           and a( 3, 1 ) respectively, and so on.
-*           Note that the imaginary parts of the diagonal elements need
-*           not be set and are assumed to be zero.
-*           Unchanged on exit.
-*
-*  X      - COMPLEX*16       array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the n
-*           element vector x.
-*           Unchanged on exit.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  BETA   - COMPLEX*16      .
-*           On entry, BETA specifies the scalar beta. When BETA is
-*           supplied as zero then Y need not be set on input.
-*           Unchanged on exit.
-*
-*  Y      - COMPLEX*16       array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCY ) ).
-*           Before entry, the incremented array Y must contain the n
-*           element vector y. On exit, Y is overwritten by the updated
-*           vector y.
-*
-*  INCY   - INTEGER.
-*           On entry, INCY specifies the increment for the elements of
-*           Y. INCY must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      DOUBLE COMPLEX ONE
-      PARAMETER (ONE= (1.0D+0,0.0D+0))
-      DOUBLE COMPLEX ZERO
-      PARAMETER (ZERO= (0.0D+0,0.0D+0))
-*     ..
-*     .. Local Scalars ..
-      DOUBLE COMPLEX TEMP1,TEMP2
-      INTEGER I,INFO,IX,IY,J,JX,JY,K,KK,KX,KY
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC DBLE,DCONJG
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (N.LT.0) THEN
-          INFO = 2
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 6
-      ELSE IF (INCY.EQ.0) THEN
-          INFO = 9
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('ZHPMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF ((N.EQ.0) .OR. ((ALPHA.EQ.ZERO).AND. (BETA.EQ.ONE))) RETURN
-*
-*     Set up the start points in  X  and  Y.
-*
-      IF (INCX.GT.0) THEN
-          KX = 1
-      ELSE
-          KX = 1 - (N-1)*INCX
-      END IF
-      IF (INCY.GT.0) THEN
-          KY = 1
-      ELSE
-          KY = 1 - (N-1)*INCY
-      END IF
-*
-*     Start the operations. In this version the elements of the array AP
-*     are accessed sequentially with one pass through AP.
-*
-*     First form  y := beta*y.
-*
-      IF (BETA.NE.ONE) THEN
-          IF (INCY.EQ.1) THEN
-              IF (BETA.EQ.ZERO) THEN
-                  DO 10 I = 1,N
-                      Y(I) = ZERO
-   10             CONTINUE
-              ELSE
-                  DO 20 I = 1,N
-                      Y(I) = BETA*Y(I)
-   20             CONTINUE
-              END IF
-          ELSE
-              IY = KY
-              IF (BETA.EQ.ZERO) THEN
-                  DO 30 I = 1,N
-                      Y(IY) = ZERO
-                      IY = IY + INCY
-   30             CONTINUE
-              ELSE
-                  DO 40 I = 1,N
-                      Y(IY) = BETA*Y(IY)
-                      IY = IY + INCY
-   40             CONTINUE
-              END IF
-          END IF
-      END IF
-      IF (ALPHA.EQ.ZERO) RETURN
-      KK = 1
-      IF (LSAME(UPLO,'U')) THEN
-*
-*        Form  y  when AP contains the upper triangle.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 60 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  K = KK
-                  DO 50 I = 1,J - 1
-                      Y(I) = Y(I) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + DCONJG(AP(K))*X(I)
-                      K = K + 1
-   50             CONTINUE
-                  Y(J) = Y(J) + TEMP1*DBLE(AP(KK+J-1)) + ALPHA*TEMP2
-                  KK = KK + J
-   60         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 80 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  IX = KX
-                  IY = KY
-                  DO 70 K = KK,KK + J - 2
-                      Y(IY) = Y(IY) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + DCONJG(AP(K))*X(IX)
-                      IX = IX + INCX
-                      IY = IY + INCY
-   70             CONTINUE
-                  Y(JY) = Y(JY) + TEMP1*DBLE(AP(KK+J-1)) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  KK = KK + J
-   80         CONTINUE
-          END IF
-      ELSE
-*
-*        Form  y  when AP contains the lower triangle.
-*
-          IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
-              DO 100 J = 1,N
-                  TEMP1 = ALPHA*X(J)
-                  TEMP2 = ZERO
-                  Y(J) = Y(J) + TEMP1*DBLE(AP(KK))
-                  K = KK + 1
-                  DO 90 I = J + 1,N
-                      Y(I) = Y(I) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + DCONJG(AP(K))*X(I)
-                      K = K + 1
-   90             CONTINUE
-                  Y(J) = Y(J) + ALPHA*TEMP2
-                  KK = KK + (N-J+1)
-  100         CONTINUE
-          ELSE
-              JX = KX
-              JY = KY
-              DO 120 J = 1,N
-                  TEMP1 = ALPHA*X(JX)
-                  TEMP2 = ZERO
-                  Y(JY) = Y(JY) + TEMP1*DBLE(AP(KK))
-                  IX = JX
-                  IY = JY
-                  DO 110 K = KK + 1,KK + N - J
-                      IX = IX + INCX
-                      IY = IY + INCY
-                      Y(IY) = Y(IY) + TEMP1*AP(K)
-                      TEMP2 = TEMP2 + DCONJG(AP(K))*X(IX)
-  110             CONTINUE
-                  Y(JY) = Y(JY) + ALPHA*TEMP2
-                  JX = JX + INCX
-                  JY = JY + INCY
-                  KK = KK + (N-J+1)
-  120         CONTINUE
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of ZHPMV .
-*
-      END

DELETED 3rd_party/eigen/blas/ztbmv.f
Index: 3rd_party/eigen/blas/ztbmv.f
==================================================================
--- 3rd_party/eigen/blas/ztbmv.f
+++ 3rd_party/eigen/blas/ztbmv.f
@@ -1,366 +0,0 @@
-      SUBROUTINE ZTBMV(UPLO,TRANS,DIAG,N,K,A,LDA,X,INCX)
-*     .. Scalar Arguments ..
-      INTEGER INCX,K,LDA,N
-      CHARACTER DIAG,TRANS,UPLO
-*     ..
-*     .. Array Arguments ..
-      DOUBLE COMPLEX A(LDA,*),X(*)
-*     ..
-*
-*  Purpose
-*  =======
-*
-*  ZTBMV  performs one of the matrix-vector operations
-*
-*     x := A*x,   or   x := A'*x,   or   x := conjg( A' )*x,
-*
-*  where x is an n element vector and  A is an n by n unit, or non-unit,
-*  upper or lower triangular band matrix, with ( k + 1 ) diagonals.
-*
-*  Arguments
-*  ==========
-*
-*  UPLO   - CHARACTER*1.
-*           On entry, UPLO specifies whether the matrix is an upper or
-*           lower triangular matrix as follows:
-*
-*              UPLO = 'U' or 'u'   A is an upper triangular matrix.
-*
-*              UPLO = 'L' or 'l'   A is a lower triangular matrix.
-*
-*           Unchanged on exit.
-*
-*  TRANS  - CHARACTER*1.
-*           On entry, TRANS specifies the operation to be performed as
-*           follows:
-*
-*              TRANS = 'N' or 'n'   x := A*x.
-*
-*              TRANS = 'T' or 't'   x := A'*x.
-*
-*              TRANS = 'C' or 'c'   x := conjg( A' )*x.
-*
-*           Unchanged on exit.
-*
-*  DIAG   - CHARACTER*1.
-*           On entry, DIAG specifies whether or not A is unit
-*           triangular as follows:
-*
-*              DIAG = 'U' or 'u'   A is assumed to be unit triangular.
-*
-*              DIAG = 'N' or 'n'   A is not assumed to be unit
-*                                  triangular.
-*
-*           Unchanged on exit.
-*
-*  N      - INTEGER.
-*           On entry, N specifies the order of the matrix A.
-*           N must be at least zero.
-*           Unchanged on exit.
-*
-*  K      - INTEGER.
-*           On entry with UPLO = 'U' or 'u', K specifies the number of
-*           super-diagonals of the matrix A.
-*           On entry with UPLO = 'L' or 'l', K specifies the number of
-*           sub-diagonals of the matrix A.
-*           K must satisfy  0 .le. K.
-*           Unchanged on exit.
-*
-*  A      - COMPLEX*16       array of DIMENSION ( LDA, n ).
-*           Before entry with UPLO = 'U' or 'u', the leading ( k + 1 )
-*           by n part of the array A must contain the upper triangular
-*           band part of the matrix of coefficients, supplied column by
-*           column, with the leading diagonal of the matrix in row
-*           ( k + 1 ) of the array, the first super-diagonal starting at
-*           position 2 in row k, and so on. The top left k by k triangle
-*           of the array A is not referenced.
-*           The following program segment will transfer an upper
-*           triangular band matrix from conventional full matrix storage
-*           to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = K + 1 - J
-*                    DO 10, I = MAX( 1, J - K ), J
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Before entry with UPLO = 'L' or 'l', the leading ( k + 1 )
-*           by n part of the array A must contain the lower triangular
-*           band part of the matrix of coefficients, supplied column by
-*           column, with the leading diagonal of the matrix in row 1 of
-*           the array, the first sub-diagonal starting at position 1 in
-*           row 2, and so on. The bottom right k by k triangle of the
-*           array A is not referenced.
-*           The following program segment will transfer a lower
-*           triangular band matrix from conventional full matrix storage
-*           to band storage:
-*
-*                 DO 20, J = 1, N
-*                    M = 1 - J
-*                    DO 10, I = J, MIN( N, J + K )
-*                       A( M + I, J ) = matrix( I, J )
-*              10    CONTINUE
-*              20 CONTINUE
-*
-*           Note that when DIAG = 'U' or 'u' the elements of the array A
-*           corresponding to the diagonal elements of the matrix are not
-*           referenced, but are assumed to be unity.
-*           Unchanged on exit.
-*
-*  LDA    - INTEGER.
-*           On entry, LDA specifies the first dimension of A as declared
-*           in the calling (sub) program. LDA must be at least
-*           ( k + 1 ).
-*           Unchanged on exit.
-*
-*  X      - COMPLEX*16       array of dimension at least
-*           ( 1 + ( n - 1 )*abs( INCX ) ).
-*           Before entry, the incremented array X must contain the n
-*           element vector x. On exit, X is overwritten with the
-*           tranformed vector x.
-*
-*  INCX   - INTEGER.
-*           On entry, INCX specifies the increment for the elements of
-*           X. INCX must not be zero.
-*           Unchanged on exit.
-*
-*  Further Details
-*  ===============
-*
-*  Level 2 Blas routine.
-*
-*  -- Written on 22-October-1986.
-*     Jack Dongarra, Argonne National Lab.
-*     Jeremy Du Croz, Nag Central Office.
-*     Sven Hammarling, Nag Central Office.
-*     Richard Hanson, Sandia National Labs.
-*
-*  =====================================================================
-*
-*     .. Parameters ..
-      DOUBLE COMPLEX ZERO
-      PARAMETER (ZERO= (0.0D+0,0.0D+0))
-*     ..
-*     .. Local Scalars ..
-      DOUBLE COMPLEX TEMP
-      INTEGER I,INFO,IX,J,JX,KPLUS1,KX,L
-      LOGICAL NOCONJ,NOUNIT
-*     ..
-*     .. External Functions ..
-      LOGICAL LSAME
-      EXTERNAL LSAME
-*     ..
-*     .. External Subroutines ..
-      EXTERNAL XERBLA
-*     ..
-*     .. Intrinsic Functions ..
-      INTRINSIC DCONJG,MAX,MIN
-*     ..
-*
-*     Test the input parameters.
-*
-      INFO = 0
-      IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
-          INFO = 1
-      ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
-     +         .NOT.LSAME(TRANS,'C')) THEN
-          INFO = 2
-      ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
-          INFO = 3
-      ELSE IF (N.LT.0) THEN
-          INFO = 4
-      ELSE IF (K.LT.0) THEN
-          INFO = 5
-      ELSE IF (LDA.LT. (K+1)) THEN
-          INFO = 7
-      ELSE IF (INCX.EQ.0) THEN
-          INFO = 9
-      END IF
-      IF (INFO.NE.0) THEN
-          CALL XERBLA('ZTBMV ',INFO)
-          RETURN
-      END IF
-*
-*     Quick return if possible.
-*
-      IF (N.EQ.0) RETURN
-*
-      NOCONJ = LSAME(TRANS,'T')
-      NOUNIT = LSAME(DIAG,'N')
-*
-*     Set up the start point in X if the increment is not unity. This
-*     will be  ( N - 1 )*INCX   too small for descending loops.
-*
-      IF (INCX.LE.0) THEN
-          KX = 1 - (N-1)*INCX
-      ELSE IF (INCX.NE.1) THEN
-          KX = 1
-      END IF
-*
-*     Start the operations. In this version the elements of A are
-*     accessed sequentially with one pass through A.
-*
-      IF (LSAME(TRANS,'N')) THEN
-*
-*         Form  x := A*x.
-*
-          IF (LSAME(UPLO,'U')) THEN
-              KPLUS1 = K + 1
-              IF (INCX.EQ.1) THEN
-                  DO 20 J = 1,N
-                      IF (X(J).NE.ZERO) THEN
-                          TEMP = X(J)
-                          L = KPLUS1 - J
-                          DO 10 I = MAX(1,J-K),J - 1
-                              X(I) = X(I) + TEMP*A(L+I,J)
-   10                     CONTINUE
-                          IF (NOUNIT) X(J) = X(J)*A(KPLUS1,J)
-                      END IF
-   20             CONTINUE
-              ELSE
-                  JX = KX
-                  DO 40 J = 1,N
-                      IF (X(JX).NE.ZERO) THEN
-                          TEMP = X(JX)
-                          IX = KX
-                          L = KPLUS1 - J
-                          DO 30 I = MAX(1,J-K),J - 1
-                              X(IX) = X(IX) + TEMP*A(L+I,J)
-                              IX = IX + INCX
-   30                     CONTINUE
-                          IF (NOUNIT) X(JX) = X(JX)*A(KPLUS1,J)
-                      END IF
-                      JX = JX + INCX
-                      IF (J.GT.K) KX = KX + INCX
-   40             CONTINUE
-              END IF
-          ELSE
-              IF (INCX.EQ.1) THEN
-                  DO 60 J = N,1,-1
-                      IF (X(J).NE.ZERO) THEN
-                          TEMP = X(J)
-                          L = 1 - J
-                          DO 50 I = MIN(N,J+K),J + 1,-1
-                              X(I) = X(I) + TEMP*A(L+I,J)
-   50                     CONTINUE
-                          IF (NOUNIT) X(J) = X(J)*A(1,J)
-                      END IF
-   60             CONTINUE
-              ELSE
-                  KX = KX + (N-1)*INCX
-                  JX = KX
-                  DO 80 J = N,1,-1
-                      IF (X(JX).NE.ZERO) THEN
-                          TEMP = X(JX)
-                          IX = KX
-                          L = 1 - J
-                          DO 70 I = MIN(N,J+K),J + 1,-1
-                              X(IX) = X(IX) + TEMP*A(L+I,J)
-                              IX = IX - INCX
-   70                     CONTINUE
-                          IF (NOUNIT) X(JX) = X(JX)*A(1,J)
-                      END IF
-                      JX = JX - INCX
-                      IF ((N-J).GE.K) KX = KX - INCX
-   80             CONTINUE
-              END IF
-          END IF
-      ELSE
-*
-*        Form  x := A'*x  or  x := conjg( A' )*x.
-*
-          IF (LSAME(UPLO,'U')) THEN
-              KPLUS1 = K + 1
-              IF (INCX.EQ.1) THEN
-                  DO 110 J = N,1,-1
-                      TEMP = X(J)
-                      L = KPLUS1 - J
-                      IF (NOCONJ) THEN
-                          IF (NOUNIT) TEMP = TEMP*A(KPLUS1,J)
-                          DO 90 I = J - 1,MAX(1,J-K),-1
-                              TEMP = TEMP + A(L+I,J)*X(I)
-   90                     CONTINUE
-                      ELSE
-                          IF (NOUNIT) TEMP = TEMP*DCONJG(A(KPLUS1,J))
-                          DO 100 I = J - 1,MAX(1,J-K),-1
-                              TEMP = TEMP + DCONJG(A(L+I,J))*X(I)
-  100                     CONTINUE
-                      END IF
-                      X(J) = TEMP
-  110             CONTINUE
-              ELSE
-                  KX = KX + (N-1)*INCX
-                  JX = KX
-                  DO 140 J = N,1,-1
-                      TEMP = X(JX)
-                      KX = KX - INCX
-                      IX = KX
-                      L = KPLUS1 - J
-                      IF (NOCONJ) THEN
-                          IF (NOUNIT) TEMP = TEMP*A(KPLUS1,J)
-                          DO 120 I = J - 1,MAX(1,J-K),-1
-                              TEMP = TEMP + A(L+I,J)*X(IX)
-                              IX = IX - INCX
-  120                     CONTINUE
-                      ELSE
-                          IF (NOUNIT) TEMP = TEMP*DCONJG(A(KPLUS1,J))
-                          DO 130 I = J - 1,MAX(1,J-K),-1
-                              TEMP = TEMP + DCONJG(A(L+I,J))*X(IX)
-                              IX = IX - INCX
-  130                     CONTINUE
-                      END IF
-                      X(JX) = TEMP
-                      JX = JX - INCX
-  140             CONTINUE
-              END IF
-          ELSE
-              IF (INCX.EQ.1) THEN
-                  DO 170 J = 1,N
-                      TEMP = X(J)
-                      L = 1 - J
-                      IF (NOCONJ) THEN
-                          IF (NOUNIT) TEMP = TEMP*A(1,J)
-                          DO 150 I = J + 1,MIN(N,J+K)
-                              TEMP = TEMP + A(L+I,J)*X(I)
-  150                     CONTINUE
-                      ELSE
-                          IF (NOUNIT) TEMP = TEMP*DCONJG(A(1,J))
-                          DO 160 I = J + 1,MIN(N,J+K)
-                              TEMP = TEMP + DCONJG(A(L+I,J))*X(I)
-  160                     CONTINUE
-                      END IF
-                      X(J) = TEMP
-  170             CONTINUE
-              ELSE
-                  JX = KX
-                  DO 200 J = 1,N
-                      TEMP = X(JX)
-                      KX = KX + INCX
-                      IX = KX
-                      L = 1 - J
-                      IF (NOCONJ) THEN
-                          IF (NOUNIT) TEMP = TEMP*A(1,J)
-                          DO 180 I = J + 1,MIN(N,J+K)
-                              TEMP = TEMP + A(L+I,J)*X(IX)
-                              IX = IX + INCX
-  180                     CONTINUE
-                      ELSE
-                          IF (NOUNIT) TEMP = TEMP*DCONJG(A(1,J))
-                          DO 190 I = J + 1,MIN(N,J+K)
-                              TEMP = TEMP + DCONJG(A(L+I,J))*X(IX)
-                              IX = IX + INCX
-  190                     CONTINUE
-                      END IF
-                      X(JX) = TEMP
-                      JX = JX + INCX
-  200             CONTINUE
-              END IF
-          END IF
-      END IF
-*
-      RETURN
-*
-*     End of ZTBMV .
-*
-      END

ADDED   3rd_party/eigen/cmake/Eigen3Config.cmake.in
Index: 3rd_party/eigen/cmake/Eigen3Config.cmake.in
==================================================================
--- 3rd_party/eigen/cmake/Eigen3Config.cmake.in
+++ 3rd_party/eigen/cmake/Eigen3Config.cmake.in
@@ -0,0 +1,21 @@
+# This file exports the Eigen3::Eigen CMake target which should be passed to the
+# target_link_libraries command.
+
+@PACKAGE_INIT@
+
+include ("${CMAKE_CURRENT_LIST_DIR}/Eigen3Targets.cmake")
+
+# Legacy variables, do *not* use. May be removed in the future.
+
+set (EIGEN3_FOUND 1)
+set (EIGEN3_USE_FILE    "${CMAKE_CURRENT_LIST_DIR}/UseEigen3.cmake")
+
+set (EIGEN3_DEFINITIONS  "@EIGEN_DEFINITIONS@")
+set (EIGEN3_INCLUDE_DIR  "@PACKAGE_EIGEN_INCLUDE_DIR@")
+set (EIGEN3_INCLUDE_DIRS "@PACKAGE_EIGEN_INCLUDE_DIR@")
+set (EIGEN3_ROOT_DIR     "@PACKAGE_EIGEN_ROOT_DIR@")
+
+set (EIGEN3_VERSION_STRING "@EIGEN_VERSION_STRING@")
+set (EIGEN3_VERSION_MAJOR  "@EIGEN_VERSION_MAJOR@")
+set (EIGEN3_VERSION_MINOR  "@EIGEN_VERSION_MINOR@")
+set (EIGEN3_VERSION_PATCH  "@EIGEN_VERSION_PATCH@")

ADDED   3rd_party/eigen/cmake/Eigen3ConfigLegacy.cmake.in
Index: 3rd_party/eigen/cmake/Eigen3ConfigLegacy.cmake.in
==================================================================
--- 3rd_party/eigen/cmake/Eigen3ConfigLegacy.cmake.in
+++ 3rd_party/eigen/cmake/Eigen3ConfigLegacy.cmake.in
@@ -0,0 +1,30 @@
+#                                               -*- cmake -*-
+#
+#  Eigen3Config.cmake(.in)
+
+# Use the following variables to compile and link against Eigen:
+#  EIGEN3_FOUND              - True if Eigen was found on your system
+#  EIGEN3_USE_FILE           - The file making Eigen usable
+#  EIGEN3_DEFINITIONS        - Definitions needed to build with Eigen
+#  EIGEN3_INCLUDE_DIR        - Directory where signature_of_eigen3_matrix_library can be found
+#  EIGEN3_INCLUDE_DIRS       - List of directories of Eigen and it's dependencies
+#  EIGEN3_ROOT_DIR           - The base directory of Eigen
+#  EIGEN3_VERSION_STRING     - A human-readable string containing the version
+#  EIGEN3_VERSION_MAJOR      - The major version of Eigen
+#  EIGEN3_VERSION_MINOR      - The minor version of Eigen
+#  EIGEN3_VERSION_PATCH      - The patch version of Eigen
+
+@PACKAGE_INIT@
+
+set ( EIGEN3_FOUND 1 )
+set ( EIGEN3_USE_FILE     "${CMAKE_CURRENT_LIST_DIR}/UseEigen3.cmake" )
+
+set ( EIGEN3_DEFINITIONS  "@EIGEN_DEFINITIONS@" )
+set ( EIGEN3_INCLUDE_DIR  "@PACKAGE_EIGEN_INCLUDE_DIR@" )
+set ( EIGEN3_INCLUDE_DIRS "@PACKAGE_EIGEN_INCLUDE_DIR@" )
+set ( EIGEN3_ROOT_DIR     "@PACKAGE_EIGEN_ROOT_DIR@" )
+
+set ( EIGEN3_VERSION_STRING "@EIGEN_VERSION_STRING@" )
+set ( EIGEN3_VERSION_MAJOR  "@EIGEN_VERSION_MAJOR@" )
+set ( EIGEN3_VERSION_MINOR  "@EIGEN_VERSION_MINOR@" )
+set ( EIGEN3_VERSION_PATCH  "@EIGEN_VERSION_PATCH@" )

Index: 3rd_party/eigen/cmake/EigenConfigureTesting.cmake
==================================================================
--- 3rd_party/eigen/cmake/EigenConfigureTesting.cmake
+++ 3rd_party/eigen/cmake/EigenConfigureTesting.cmake
@@ -12,45 +12,27 @@
 add_dependencies(check buildtests)
 
 # check whether /bin/bash exists
 find_file(EIGEN_BIN_BASH_EXISTS "/bin/bash" PATHS "/" NO_DEFAULT_PATH)
 
-# CMake/Ctest does not allow us to change the build command,
-# so we have to workaround by directly editing the generated DartConfiguration.tcl file
-# save CMAKE_MAKE_PROGRAM
-set(CMAKE_MAKE_PROGRAM_SAVE ${CMAKE_MAKE_PROGRAM})
-# and set a fake one
-set(CMAKE_MAKE_PROGRAM "@EIGEN_MAKECOMMAND_PLACEHOLDER@")
-
 # This call activates testing and generates the DartConfiguration.tcl
 include(CTest)
 
-set(EIGEN_TEST_BUILD_FLAGS " " CACHE STRING "Options passed to the build command of unit tests")
-
-# overwrite default DartConfiguration.tcl
-# The worarounds are different for each version of the MSVC IDE
-if(MSVC_IDE)
-  if(CMAKE_MAKE_PROGRAM_SAVE MATCHES "devenv") # devenv
-    set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} Eigen.sln /build \"Release\" /project buildtests ${EIGEN_TEST_BUILD_FLAGS} \n# ")    
-  else() # msbuild
-    set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests.vcxproj /p:Configuration=\${CTEST_CONFIGURATION_TYPE}  ${EIGEN_TEST_BUILD_FLAGS}\n# ")
-  endif()
-else()
-  # for make and nmake
-  set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests ${EIGEN_TEST_BUILD_FLAGS}")
-endif()
-
-# copy ctest properties, which currently
-# o raise the warning levels
-configure_file(${CMAKE_CURRENT_BINARY_DIR}/DartConfiguration.tcl ${CMAKE_BINARY_DIR}/DartConfiguration.tcl)
-
-# restore default CMAKE_MAKE_PROGRAM
-set(CMAKE_MAKE_PROGRAM ${CMAKE_MAKE_PROGRAM_SAVE})
-# un-set temporary variables so that it is like they never existed. 
-# CMake 2.6.3 introduces the more logical unset() syntax for this.
-set(CMAKE_MAKE_PROGRAM_SAVE) 
-set(EIGEN_MAKECOMMAND_PLACEHOLDER)
+set(EIGEN_TEST_BUILD_FLAGS "" CACHE STRING "Options passed to the build command of unit tests")
+
+# Overwrite default DartConfiguration.tcl such that ctest can build our unit tests.
+# Recall that our unit tests are not in the "all" target, so we have to explicitely ask ctest to build our custom 'buildtests' target.
+# At this stage, we can also add custom flags to the build tool through the user defined EIGEN_TEST_BUILD_FLAGS variable.
+file(READ  "${CMAKE_CURRENT_BINARY_DIR}/DartConfiguration.tcl" EIGEN_DART_CONFIG_FILE)
+# try to grab the default flags
+string(REGEX MATCH "MakeCommand:.*-- (.*)\nDefaultCTestConfigurationType" EIGEN_DUMMY ${EIGEN_DART_CONFIG_FILE})
+if(NOT CMAKE_MATCH_1)
+string(REGEX MATCH "MakeCommand:.*[^c]make (.*)\nDefaultCTestConfigurationType" EIGEN_DUMMY ${EIGEN_DART_CONFIG_FILE})
+endif()
+string(REGEX REPLACE "MakeCommand:.*DefaultCTestConfigurationType" "MakeCommand: ${CMAKE_COMMAND} --build . --target buildtests --config \"\${CTEST_CONFIGURATION_TYPE}\" -- ${CMAKE_MATCH_1} ${EIGEN_TEST_BUILD_FLAGS}\nDefaultCTestConfigurationType"
+       EIGEN_DART_CONFIG_FILE2 ${EIGEN_DART_CONFIG_FILE})
+file(WRITE "${CMAKE_CURRENT_BINARY_DIR}/DartConfiguration.tcl" ${EIGEN_DART_CONFIG_FILE2})
 
 configure_file(${CMAKE_CURRENT_SOURCE_DIR}/CTestCustom.cmake.in ${CMAKE_BINARY_DIR}/CTestCustom.cmake)
 
 # some documentation of this function would be nice
 ei_init_testing()
@@ -62,20 +44,18 @@
 if(CMAKE_COMPILER_IS_GNUCXX)
   option(EIGEN_COVERAGE_TESTING "Enable/disable gcov" OFF)
   if(EIGEN_COVERAGE_TESTING)
     set(COVERAGE_FLAGS "-fprofile-arcs -ftest-coverage")
     set(CTEST_CUSTOM_COVERAGE_EXCLUDE "/test/")
-  else(EIGEN_COVERAGE_TESTING)
-    set(COVERAGE_FLAGS "")
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${COVERAGE_FLAGS}")
   endif(EIGEN_COVERAGE_TESTING)
-  if(EIGEN_TEST_C++0x)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=gnu++0x")
-  endif(EIGEN_TEST_C++0x)
-  if(CMAKE_SYSTEM_NAME MATCHES Linux)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${COVERAGE_FLAGS} -g2")
-    set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "${CMAKE_CXX_FLAGS_RELWITHDEBINFO} ${COVERAGE_FLAGS} -O2 -g2")
-    set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} ${COVERAGE_FLAGS} -fno-inline-functions")
-    set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ${COVERAGE_FLAGS} -O0 -g3")
-  endif(CMAKE_SYSTEM_NAME MATCHES Linux)
+  
 elseif(MSVC)
   set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /D_CRT_SECURE_NO_WARNINGS /D_SCL_SECURE_NO_WARNINGS")
 endif(CMAKE_COMPILER_IS_GNUCXX)
+
+
+check_cxx_compiler_flag("-std=c++11" EIGEN_COMPILER_SUPPORT_CXX11)
+
+if(EIGEN_TEST_CXX11 AND EIGEN_COMPILER_SUPPORT_CXX11)
+  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
+endif()

Index: 3rd_party/eigen/cmake/EigenDetermineOSVersion.cmake
==================================================================
--- 3rd_party/eigen/cmake/EigenDetermineOSVersion.cmake
+++ 3rd_party/eigen/cmake/EigenDetermineOSVersion.cmake
@@ -24,11 +24,11 @@
    endif()
    set(${WIN_VERSION} ${_version} PARENT_SCOPE)
 endfunction()
 
 function(DetermineOSVersion OS_VERSION)
-  if (WIN32)
+  if (WIN32 AND CMAKE_HOST_SYSTEM_NAME MATCHES Windows)
     file (TO_NATIVE_PATH "$ENV{COMSPEC}" SHELL)
     exec_program( ${SHELL} ARGS "/c" "ver" OUTPUT_VARIABLE ver_output)
 				
       string(REGEX MATCHALL "[0-9]+"
            ver_list "${ver_output}")

Index: 3rd_party/eigen/cmake/EigenDetermineVSServicePack.cmake
==================================================================
--- 3rd_party/eigen/cmake/EigenDetermineVSServicePack.cmake
+++ 3rd_party/eigen/cmake/EigenDetermineVSServicePack.cmake
@@ -2,26 +2,40 @@
 
 # The code is almost identical to the CMake version. The only difference is that we remove
 # _DetermineVSServicePack_FastCheckVersionWithCompiler which lead to errors on some systems.
 function(EigenDetermineVSServicePack _pack)
     if(NOT DETERMINED_VS_SERVICE_PACK OR NOT ${_pack})
-
         if(NOT DETERMINED_VS_SERVICE_PACK)
             _DetermineVSServicePack_CheckVersionWithTryCompile(DETERMINED_VS_SERVICE_PACK _cl_version)
             if(NOT DETERMINED_VS_SERVICE_PACK)
                 _DetermineVSServicePack_CheckVersionWithTryRun(DETERMINED_VS_SERVICE_PACK _cl_version)
             endif()
         endif()
 
         if(DETERMINED_VS_SERVICE_PACK)
-
             if(_cl_version)
                 # Call helper function to determine VS version
                 _DetermineVSServicePackFromCompiler(_sp "${_cl_version}")
+              
+                # temporary fix, until CMake catches up
+                if (NOT _sp)
+                    if(${_cl_version} VERSION_EQUAL "17.00.50727.1")
+                        set(_sp "vc110")
+                    elseif(${_cl_version} VERSION_EQUAL "17.00.51106.1")
+                        set(_sp "vc110sp1")
+                    elseif(${_cl_version} VERSION_EQUAL "17.00.60315.1")
+                        set(_sp "vc110sp2")
+                    elseif(${_cl_version} VERSION_EQUAL "17.00.60610.1")
+                        set(_sp "vc110sp3")
+                    else()
+                        set(_sp ${CMAKE_CXX_COMPILER_VERSION})
+                    endif()
+                endif()
+                
                 if(_sp)
                     set(${_pack} ${_sp} CACHE INTERNAL
                         "The Visual Studio Release with Service Pack")
                 endif()
             endif()
         endif()
     endif()
 endfunction()

Index: 3rd_party/eigen/cmake/EigenTesting.cmake
==================================================================
--- 3rd_party/eigen/cmake/EigenTesting.cmake
+++ 3rd_party/eigen/cmake/EigenTesting.cmake
@@ -1,21 +1,145 @@
 
 macro(ei_add_property prop value)
-  get_property(previous GLOBAL PROPERTY ${prop})  
+  get_property(previous GLOBAL PROPERTY ${prop})
   if ((NOT previous) OR (previous STREQUAL ""))
     set_property(GLOBAL PROPERTY ${prop} "${value}")
   else()
     set_property(GLOBAL PROPERTY ${prop} "${previous} ${value}")
-  endif()  
+  endif()
 endmacro(ei_add_property)
 
 #internal. See documentation of ei_add_test for details.
 macro(ei_add_test_internal testname testname_with_suffix)
   set(targetname ${testname_with_suffix})
 
-  set(filename ${testname}.cpp)
-  add_executable(${targetname} ${filename})
+  if(EIGEN_ADD_TEST_FILENAME_EXTENSION)
+    set(filename ${testname}.${EIGEN_ADD_TEST_FILENAME_EXTENSION})
+  else()
+    set(filename ${testname}.cpp)
+  endif()
+
+  if(EIGEN_ADD_TEST_FILENAME_EXTENSION STREQUAL cu)
+    if(EIGEN_TEST_CUDA_CLANG)
+      set_source_files_properties(${filename} PROPERTIES LANGUAGE CXX)
+      if(CUDA_64_BIT_DEVICE_CODE)
+        link_directories("${CUDA_TOOLKIT_ROOT_DIR}/lib64")
+      else()
+        link_directories("${CUDA_TOOLKIT_ROOT_DIR}/lib")
+      endif()
+      if (${ARGC} GREATER 2)
+        add_executable(${targetname} ${filename})
+      else()
+        add_executable(${targetname} ${filename} OPTIONS ${ARGV2})
+      endif()
+      target_link_libraries(${targetname} "cudart_static" "cuda" "dl" "rt" "pthread")
+    else()
+      if (${ARGC} GREATER 2)
+        cuda_add_executable(${targetname} ${filename} OPTIONS ${ARGV2})
+      else()
+        cuda_add_executable(${targetname} ${filename})
+      endif()
+    endif()
+  else()
+    add_executable(${targetname} ${filename})
+  endif()
+
+  if (targetname MATCHES "^eigen2_")
+    add_dependencies(eigen2_buildtests ${targetname})
+  else()
+    add_dependencies(buildtests ${targetname})
+  endif()
+
+  if(EIGEN_NO_ASSERTION_CHECKING)
+    ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_NO_ASSERTION_CHECKING=1")
+  else(EIGEN_NO_ASSERTION_CHECKING)
+    if(EIGEN_DEBUG_ASSERTS)
+      ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_DEBUG_ASSERTS=1")
+    endif(EIGEN_DEBUG_ASSERTS)
+  endif(EIGEN_NO_ASSERTION_CHECKING)
+
+  ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_TEST_MAX_SIZE=${EIGEN_TEST_MAX_SIZE}")
+
+  ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_TEST_FUNC=${testname}")
+
+  if(MSVC)
+    ei_add_target_property(${targetname} COMPILE_FLAGS "/bigobj")
+  endif()
+
+  # let the user pass flags.
+  if(${ARGC} GREATER 2)
+    ei_add_target_property(${targetname} COMPILE_FLAGS "${ARGV2}")
+  endif(${ARGC} GREATER 2)
+
+  if(EIGEN_TEST_CUSTOM_CXX_FLAGS)
+    ei_add_target_property(${targetname} COMPILE_FLAGS "${EIGEN_TEST_CUSTOM_CXX_FLAGS}")
+  endif()
+
+  if(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO)
+    target_link_libraries(${targetname} ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO})
+  endif()
+  if(EXTERNAL_LIBS)
+    target_link_libraries(${targetname} ${EXTERNAL_LIBS})
+  endif()
+  if(EIGEN_TEST_CUSTOM_LINKER_FLAGS)
+    target_link_libraries(${targetname} ${EIGEN_TEST_CUSTOM_LINKER_FLAGS})
+  endif()
+
+  if(${ARGC} GREATER 3)
+    set(libs_to_link ${ARGV3})
+    # it could be that some cmake module provides a bad library string " "  (just spaces),
+    # and that severely breaks target_link_libraries ("can't link to -l-lstdc++" errors).
+    # so we check for strings containing only spaces.
+    string(STRIP "${libs_to_link}" libs_to_link_stripped)
+    string(LENGTH "${libs_to_link_stripped}" libs_to_link_stripped_length)
+    if(${libs_to_link_stripped_length} GREATER 0)
+      # notice: no double quotes around ${libs_to_link} here. It may be a list.
+      target_link_libraries(${targetname} ${libs_to_link})
+    endif()
+  endif()
+
+  add_test(${testname_with_suffix} "${targetname}")
+
+  # Specify target and test labels accoirding to EIGEN_CURRENT_SUBPROJECT
+  get_property(current_subproject GLOBAL PROPERTY EIGEN_CURRENT_SUBPROJECT)
+  if ((current_subproject) AND (NOT (current_subproject STREQUAL "")))
+    set_property(TARGET ${targetname} PROPERTY LABELS "Build${current_subproject}")
+    add_dependencies("Build${current_subproject}" ${targetname})
+    set_property(TEST ${testname_with_suffix} PROPERTY LABELS "${current_subproject}")
+  endif()
+
+endmacro(ei_add_test_internal)
+
+# SYCL
+macro(ei_add_test_internal_sycl testname testname_with_suffix)
+  include_directories( SYSTEM ${COMPUTECPP_PACKAGE_ROOT_DIR}/include)
+  set(targetname ${testname_with_suffix})
+
+  if(EIGEN_ADD_TEST_FILENAME_EXTENSION)
+    set(filename ${testname}.${EIGEN_ADD_TEST_FILENAME_EXTENSION})
+  else()
+    set(filename ${testname}.cpp)
+  endif()
+
+  set( include_file ${CMAKE_CURRENT_BINARY_DIR}/inc_${filename})
+  set( bc_file ${CMAKE_CURRENT_BINARY_DIR}/${filename})
+  set( host_file ${CMAKE_CURRENT_SOURCE_DIR}/${filename})
+
+  ADD_CUSTOM_COMMAND(
+    OUTPUT ${include_file}
+    COMMAND ${CMAKE_COMMAND} -E echo "\\#include \\\"${host_file}\\\"" > ${include_file}
+    COMMAND ${CMAKE_COMMAND} -E echo "\\#include \\\"${bc_file}.sycl\\\"" >> ${include_file}
+    DEPENDS ${filename} ${bc_file}.sycl
+    COMMENT "Building ComputeCpp integration header file ${include_file}"
+  )
+  # Add a custom target for the generated integration header
+  add_custom_target(${testname}_integration_header_sycl DEPENDS ${include_file})
+
+  add_executable(${targetname} ${include_file})
+  add_dependencies(${targetname} ${testname}_integration_header_sycl)
+  add_sycl_to_target(${targetname} ${filename} ${CMAKE_CURRENT_BINARY_DIR})
+
   if (targetname MATCHES "^eigen2_")
     add_dependencies(eigen2_buildtests ${targetname})
   else()
     add_dependencies(buildtests ${targetname})
   endif()
@@ -25,24 +149,24 @@
   else(EIGEN_NO_ASSERTION_CHECKING)
     if(EIGEN_DEBUG_ASSERTS)
       ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_DEBUG_ASSERTS=1")
     endif(EIGEN_DEBUG_ASSERTS)
   endif(EIGEN_NO_ASSERTION_CHECKING)
-  
+
   ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_TEST_MAX_SIZE=${EIGEN_TEST_MAX_SIZE}")
 
   ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_TEST_FUNC=${testname}")
-  
+
   if(MSVC AND NOT EIGEN_SPLIT_LARGE_TESTS)
     ei_add_target_property(${targetname} COMPILE_FLAGS "/bigobj")
-  endif()  
+  endif()
 
   # let the user pass flags.
   if(${ARGC} GREATER 2)
     ei_add_target_property(${targetname} COMPILE_FLAGS "${ARGV2}")
   endif(${ARGC} GREATER 2)
-  
+
   if(EIGEN_TEST_CUSTOM_CXX_FLAGS)
     ei_add_target_property(${targetname} COMPILE_FLAGS "${EIGEN_TEST_CUSTOM_CXX_FLAGS}")
   endif()
 
   if(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO)
@@ -64,27 +188,25 @@
     string(LENGTH "${libs_to_link_stripped}" libs_to_link_stripped_length)
     if(${libs_to_link_stripped_length} GREATER 0)
       # notice: no double quotes around ${libs_to_link} here. It may be a list.
       target_link_libraries(${targetname} ${libs_to_link})
     endif()
-  endif() 
-
-  if(EIGEN_BIN_BASH_EXISTS)
-    add_test(${testname_with_suffix} "${Eigen_SOURCE_DIR}/test/runtest.sh" "${testname_with_suffix}")
-  else()
-    add_test(${testname_with_suffix} "${targetname}")
-  endif()
-  
-  # Specify target and test labels accoirding to EIGEN_CURRENT_SUBPROJECT
-  get_property(current_subproject GLOBAL PROPERTY EIGEN_CURRENT_SUBPROJECT)  
+  endif()
+
+  add_test(${testname_with_suffix} "${targetname}")
+
+  # Specify target and test labels according to EIGEN_CURRENT_SUBPROJECT
+  get_property(current_subproject GLOBAL PROPERTY EIGEN_CURRENT_SUBPROJECT)
   if ((current_subproject) AND (NOT (current_subproject STREQUAL "")))
     set_property(TARGET ${targetname} PROPERTY LABELS "Build${current_subproject}")
     add_dependencies("Build${current_subproject}" ${targetname})
     set_property(TEST ${testname_with_suffix} PROPERTY LABELS "${current_subproject}")
   endif()
 
-endmacro(ei_add_test_internal)
+
+endmacro(ei_add_test_internal_sycl)
+
 
 # Macro to add a test
 #
 # the unique mandatory parameter testname must correspond to a file
 # <testname>.cpp which follows this pattern:
@@ -129,11 +251,17 @@
 macro(ei_add_test testname)
   get_property(EIGEN_TESTS_LIST GLOBAL PROPERTY EIGEN_TESTS_LIST)
   set(EIGEN_TESTS_LIST "${EIGEN_TESTS_LIST}${testname}\n")
   set_property(GLOBAL PROPERTY EIGEN_TESTS_LIST "${EIGEN_TESTS_LIST}")
 
-  file(READ "${testname}.cpp" test_source)
+  if(EIGEN_ADD_TEST_FILENAME_EXTENSION)
+    set(filename ${testname}.${EIGEN_ADD_TEST_FILENAME_EXTENSION})
+  else()
+    set(filename ${testname}.cpp)
+  endif()
+
+  file(READ "${filename}" test_source)
   set(parts 0)
   string(REGEX MATCHALL "CALL_SUBTEST_[0-9]+|EIGEN_TEST_PART_[0-9]+|EIGEN_SUFFIXES(;[0-9]+)+"
          occurences "${test_source}")
   string(REGEX REPLACE "CALL_SUBTEST_|EIGEN_TEST_PART_|EIGEN_SUFFIXES" "" suffixes "${occurences}")
   list(REMOVE_DUPLICATES suffixes)
@@ -152,10 +280,43 @@
     endforeach(suffix)
     ei_add_test_internal(${testname} ${testname} "${ARGV1} ${symbols_to_enable_all_parts}" "${ARGV2}")
   endif(EIGEN_SPLIT_LARGE_TESTS AND suffixes)
 endmacro(ei_add_test)
 
+macro(ei_add_test_sycl testname)
+  get_property(EIGEN_TESTS_LIST GLOBAL PROPERTY EIGEN_TESTS_LIST)
+  set(EIGEN_TESTS_LIST "${EIGEN_TESTS_LIST}${testname}\n")
+  set_property(GLOBAL PROPERTY EIGEN_TESTS_LIST "${EIGEN_TESTS_LIST}")
+
+  if(EIGEN_ADD_TEST_FILENAME_EXTENSION)
+    set(filename ${testname}.${EIGEN_ADD_TEST_FILENAME_EXTENSION})
+  else()
+    set(filename ${testname}.cpp)
+  endif()
+
+  file(READ "${filename}" test_source)
+  set(parts 0)
+  string(REGEX MATCHALL "CALL_SUBTEST_[0-9]+|EIGEN_TEST_PART_[0-9]+|EIGEN_SUFFIXES(;[0-9]+)+"
+         occurences "${test_source}")
+  string(REGEX REPLACE "CALL_SUBTEST_|EIGEN_TEST_PART_|EIGEN_SUFFIXES" "" suffixes "${occurences}")
+  list(REMOVE_DUPLICATES suffixes)
+  if(EIGEN_SPLIT_LARGE_TESTS AND suffixes)
+    add_custom_target(${testname})
+    foreach(suffix ${suffixes})
+      ei_add_test_internal_sycl(${testname} ${testname}_${suffix}
+        "${ARGV1} -DEIGEN_TEST_PART_${suffix}=1" "${ARGV2}")
+      add_dependencies(${testname} ${testname}_${suffix})
+    endforeach(suffix)
+  else(EIGEN_SPLIT_LARGE_TESTS AND suffixes)
+    set(symbols_to_enable_all_parts "")
+    foreach(suffix ${suffixes})
+      set(symbols_to_enable_all_parts
+        "${symbols_to_enable_all_parts} -DEIGEN_TEST_PART_${suffix}=1")
+    endforeach(suffix)
+    ei_add_test_internal_sycl(${testname} ${testname} "${ARGV1} ${symbols_to_enable_all_parts}" "${ARGV2}")
+  endif(EIGEN_SPLIT_LARGE_TESTS AND suffixes)
+endmacro(ei_add_test_sycl)
 
 # adds a failtest, i.e. a test that succeed if the program fails to compile
 # note that the test runner for these is CMake itself, when passed -DEIGEN_FAILTEST=ON
 # so here we're just running CMake commands immediately, we're not adding any targets.
 macro(ei_add_failtest testname)
@@ -216,11 +377,11 @@
   if(EIGEN_TEST_NO_EXPLICIT_ALIGNMENT)
     message(STATUS "Explicit alignment (hence vectorization) disabled")
   elseif(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
     message(STATUS "Explicit vectorization disabled (alignment kept enabled)")
   else()
-  
+
   message(STATUS "Maximal matrix/vector size: ${EIGEN_TEST_MAX_SIZE}")
 
     if(EIGEN_TEST_SSE2)
       message(STATUS "SSE2:              ON")
     else()
@@ -248,22 +409,79 @@
     if(EIGEN_TEST_SSE4_2)
       message(STATUS "SSE4.2:            ON")
     else()
       message(STATUS "SSE4.2:            Using architecture defaults")
     endif()
+
+    if(EIGEN_TEST_AVX)
+      message(STATUS "AVX:               ON")
+    else()
+      message(STATUS "AVX:               Using architecture defaults")
+    endif()
+
+    if(EIGEN_TEST_FMA)
+      message(STATUS "FMA:               ON")
+    else()
+      message(STATUS "FMA:               Using architecture defaults")
+    endif()
+
+    if(EIGEN_TEST_AVX512)
+      message(STATUS "AVX512:            ON")
+    else()
+      message(STATUS "AVX512:            Using architecture defaults")
+    endif()
 
     if(EIGEN_TEST_ALTIVEC)
       message(STATUS "Altivec:           ON")
     else()
       message(STATUS "Altivec:           Using architecture defaults")
     endif()
+
+    if(EIGEN_TEST_VSX)
+      message(STATUS "VSX:               ON")
+    else()
+      message(STATUS "VSX:               Using architecture defaults")
+    endif()
 
     if(EIGEN_TEST_NEON)
       message(STATUS "ARM NEON:          ON")
     else()
       message(STATUS "ARM NEON:          Using architecture defaults")
     endif()
+
+    if(EIGEN_TEST_NEON64)
+      message(STATUS "ARMv8 NEON:        ON")
+    else()
+      message(STATUS "ARMv8 NEON:        Using architecture defaults")
+    endif()
+
+    if(EIGEN_TEST_ZVECTOR)
+      message(STATUS "S390X ZVECTOR:     ON")
+    else()
+      message(STATUS "S390X ZVECTOR:     Using architecture defaults")
+    endif()
+
+    if(EIGEN_TEST_CXX11)
+      message(STATUS "C++11:             ON")
+    else()
+      message(STATUS "C++11:             OFF")
+    endif()
+
+    if(EIGEN_TEST_SYCL)
+      message(STATUS "SYCL:              ON")
+    else()
+      message(STATUS "SYCL:              OFF")
+    endif()
+    if(EIGEN_TEST_CUDA)
+      if(EIGEN_TEST_CUDA_CLANG)
+        message(STATUS "CUDA:              ON (using clang)")
+      else()
+        message(STATUS "CUDA:              ON (using nvcc)")
+      endif()
+    else()
+      message(STATUS "CUDA:              OFF")
+    endif()
 
   endif() # vectorization / alignment options
 
   message(STATUS "\n${EIGEN_TESTING_SUMMARY}")
 
@@ -285,89 +503,90 @@
   define_property(GLOBAL PROPERTY EIGEN_FAILTEST_FAILURE_COUNT BRIEF_DOCS " " FULL_DOCS " ")
   define_property(GLOBAL PROPERTY EIGEN_FAILTEST_COUNT BRIEF_DOCS " " FULL_DOCS " ")
 
   set_property(GLOBAL PROPERTY EIGEN_FAILTEST_FAILURE_COUNT "0")
   set_property(GLOBAL PROPERTY EIGEN_FAILTEST_COUNT "0")
-  
+
   # uncomment anytime you change the ei_get_compilerver_from_cxx_version_string macro
   # ei_test_get_compilerver_from_cxx_version_string()
 endmacro(ei_init_testing)
 
 macro(ei_set_sitename)
   # if the sitename is not yet set, try to set it
   if(NOT ${SITE} OR ${SITE} STREQUAL "")
     set(eigen_computername $ENV{COMPUTERNAME})
-	set(eigen_hostname $ENV{HOSTNAME})
+    set(eigen_hostname $ENV{HOSTNAME})
     if(eigen_hostname)
       set(SITE ${eigen_hostname})
-	elseif(eigen_computername)
-	  set(SITE ${eigen_computername})
+    elseif(eigen_computername)
+      set(SITE ${eigen_computername})
     endif()
   endif()
   # in case it is already set, enforce lower case
   if(SITE)
     string(TOLOWER ${SITE} SITE)
-  endif()  
+  endif()
 endmacro(ei_set_sitename)
 
 macro(ei_get_compilerver VAR)
-  if(MSVC)
-    # on windows system, we use a modified CMake script  
-    include(EigenDetermineVSServicePack)
-    EigenDetermineVSServicePack( my_service_pack )
-
-    if( my_service_pack )
-      set(${VAR} ${my_service_pack})
-    else()
-      set(${VAR} "na")
-    endif()
-  else()
+    if(MSVC)
+      # on windows system, we use a modified CMake script
+      include(EigenDetermineVSServicePack)
+      EigenDetermineVSServicePack( my_service_pack )
+
+      if( my_service_pack )
+        set(${VAR} ${my_service_pack})
+      else()
+        set(${VAR} "na")
+      endif()
+    else()
     # on all other system we rely on ${CMAKE_CXX_COMPILER}
-    # supporting a "--version" flag
-    
-    # check whether the head command exists
-    find_program(HEAD_EXE head NO_CMAKE_ENVIRONMENT_PATH NO_CMAKE_PATH NO_CMAKE_SYSTEM_PATH)
-    if(HEAD_EXE)
-      execute_process(COMMAND ${CMAKE_CXX_COMPILER} --version
-                      COMMAND head -n 1
-                      OUTPUT_VARIABLE eigen_cxx_compiler_version_string OUTPUT_STRIP_TRAILING_WHITESPACE)
+    # supporting a "--version" or "/version" flag
+
+    if(WIN32 AND ${CMAKE_CXX_COMPILER_ID} EQUAL "Intel")
+      set(EIGEN_CXX_FLAG_VERSION "/version")
     else()
-      execute_process(COMMAND ${CMAKE_CXX_COMPILER} --version
-                      OUTPUT_VARIABLE eigen_cxx_compiler_version_string OUTPUT_STRIP_TRAILING_WHITESPACE)
-      string(REGEX REPLACE "[\n\r].*"  ""  eigen_cxx_compiler_version_string  ${eigen_cxx_compiler_version_string})
+      set(EIGEN_CXX_FLAG_VERSION "--version")
     endif()
-    
+
+    execute_process(COMMAND ${CMAKE_CXX_COMPILER} ${EIGEN_CXX_FLAG_VERSION}
+                    OUTPUT_VARIABLE eigen_cxx_compiler_version_string OUTPUT_STRIP_TRAILING_WHITESPACE)
+    string(REGEX REPLACE "[\n\r].*"  ""  eigen_cxx_compiler_version_string  ${eigen_cxx_compiler_version_string})
+
     ei_get_compilerver_from_cxx_version_string("${eigen_cxx_compiler_version_string}" CNAME CVER)
     set(${VAR} "${CNAME}-${CVER}")
+
   endif()
 endmacro(ei_get_compilerver)
 
 # Extract compiler name and version from a raw version string
 # WARNING: if you edit thid macro, then please test it by  uncommenting
 # the testing macro call in ei_init_testing() of the EigenTesting.cmake file.
 # See also the ei_test_get_compilerver_from_cxx_version_string macro at the end of the file
 macro(ei_get_compilerver_from_cxx_version_string VERSTRING CNAME CVER)
-  # extract possible compiler names  
+  # extract possible compiler names
   string(REGEX MATCH "g\\+\\+"      ei_has_gpp    ${VERSTRING})
   string(REGEX MATCH "llvm|LLVM"    ei_has_llvm   ${VERSTRING})
   string(REGEX MATCH "gcc|GCC"      ei_has_gcc    ${VERSTRING})
   string(REGEX MATCH "icpc|ICC"     ei_has_icpc   ${VERSTRING})
   string(REGEX MATCH "clang|CLANG"  ei_has_clang  ${VERSTRING})
-  
+
   # combine them
   if((ei_has_llvm) AND (ei_has_gpp OR ei_has_gcc))
     set(${CNAME} "llvm-g++")
   elseif((ei_has_llvm) AND (ei_has_clang))
     set(${CNAME} "llvm-clang++")
+  elseif(ei_has_clang)
+    set(${CNAME} "clang++")
   elseif(ei_has_icpc)
     set(${CNAME} "icpc")
   elseif(ei_has_gpp OR ei_has_gcc)
     set(${CNAME} "g++")
   else()
     set(${CNAME} "_")
   endif()
-  
+
   # extract possible version numbers
   # first try to extract 3 isolated numbers:
   string(REGEX MATCH " [0-9]+\\.[0-9]+\\.[0-9]+" eicver ${VERSTRING})
   if(NOT eicver)
     # try to extract 2 isolated ones:
@@ -381,55 +600,65 @@
       else()
         set(eicver " _")
       endif()
     endif()
   endif()
-  
+
   string(REGEX REPLACE ".(.*)" "\\1" ${CVER} ${eicver})
-  
+
 endmacro(ei_get_compilerver_from_cxx_version_string)
 
 macro(ei_get_cxxflags VAR)
   set(${VAR} "")
   ei_is_64bit_env(IS_64BIT_ENV)
   if(EIGEN_TEST_NEON)
     set(${VAR} NEON)
+  elseif(EIGEN_TEST_NEON64)
+    set(${VAR} NEON)
+  elseif(EIGEN_TEST_ZVECTOR)
+    set(${VAR} ZVECTOR)
+  elseif(EIGEN_TEST_VSX)
+    set(${VAR} VSX)
   elseif(EIGEN_TEST_ALTIVEC)
     set(${VAR} ALVEC)
+  elseif(EIGEN_TEST_FMA)
+    set(${VAR} FMA)
+  elseif(EIGEN_TEST_AVX)
+    set(${VAR} AVX)
   elseif(EIGEN_TEST_SSE4_2)
     set(${VAR} SSE42)
   elseif(EIGEN_TEST_SSE4_1)
     set(${VAR} SSE41)
   elseif(EIGEN_TEST_SSSE3)
     set(${VAR} SSSE3)
   elseif(EIGEN_TEST_SSE3)
     set(${VAR} SSE3)
   elseif(EIGEN_TEST_SSE2 OR IS_64BIT_ENV)
-    set(${VAR} SSE2)  
+    set(${VAR} SSE2)
   endif()
 
   if(EIGEN_TEST_OPENMP)
     if (${VAR} STREQUAL "")
-	  set(${VAR} OMP)
-	else()
-	  set(${VAR} ${${VAR}}-OMP)
-	endif()
+      set(${VAR} OMP)
+    else()
+      set(${VAR} ${${VAR}}-OMP)
+    endif()
   endif()
-  
+
   if(EIGEN_DEFAULT_TO_ROW_MAJOR)
     if (${VAR} STREQUAL "")
-	  set(${VAR} ROW)
-	else()
-	  set(${VAR} ${${VAR}}-ROWMAJ)
-	endif()  
+      set(${VAR} ROW)
+    else()
+      set(${VAR} ${${VAR}}-ROWMAJ)
+    endif()
   endif()
 endmacro(ei_get_cxxflags)
 
 macro(ei_set_build_string)
   ei_get_compilerver(LOCAL_COMPILER_VERSION)
   ei_get_cxxflags(LOCAL_COMPILER_FLAGS)
-  
+
   include(EigenDetermineOSVersion)
   DetermineOSVersion(OS_VERSION)
 
   set(TMP_BUILD_STRING ${OS_VERSION}-${LOCAL_COMPILER_VERSION})
 
@@ -441,11 +670,15 @@
   if(NOT IS_64BIT_ENV)
     set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-32bit)
   else()
     set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-64bit)
   endif()
-  
+
+  if(EIGEN_TEST_CXX11)
+    set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-cxx11)
+  endif()
+
   if(EIGEN_BUILD_STRING_SUFFIX)
     set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-${EIGEN_BUILD_STRING_SUFFIX})
   endif()
 
   string(TOLOWER ${TMP_BUILD_STRING} BUILDNAME)

ADDED   3rd_party/eigen/cmake/EigenUninstall.cmake
Index: 3rd_party/eigen/cmake/EigenUninstall.cmake
==================================================================
--- 3rd_party/eigen/cmake/EigenUninstall.cmake
+++ 3rd_party/eigen/cmake/EigenUninstall.cmake
@@ -0,0 +1,40 @@
+################ CMake Uninstall Template #######################
+# CMake Template file for uninstallation of files
+# mentioned in 'install_manifest.txt'
+#
+# Used by uinstall target
+#################################################################
+
+set(MANIFEST "${CMAKE_CURRENT_BINARY_DIR}/install_manifest.txt")
+
+if(EXISTS ${MANIFEST})
+  message(STATUS "============== Uninstalling Eigen  ===================")
+
+  file(STRINGS ${MANIFEST} files)
+  foreach(file ${files})
+    if(EXISTS ${file})
+      message(STATUS "Removing file: '${file}'")
+
+      execute_process(
+        COMMAND ${CMAKE_COMMAND} -E remove ${file}
+        OUTPUT_VARIABLE rm_out
+        RESULT_VARIABLE rm_retval
+        )
+
+      if(NOT "${rm_retval}" STREQUAL 0)
+        message(FATAL_ERROR "Failed to remove file: '${file}'.")
+      endif()
+    else()
+      message(STATUS "File '${file}' does not exist.")
+    endif()
+  endforeach(file)
+
+  message(STATUS "========== Finished Uninstalling Eigen  ==============")
+else()
+  message(STATUS "Cannot find install manifest: '${MANIFEST}'")
+  message(STATUS "Probably make install has not been performed")
+  message(STATUS "   or install_manifest.txt has been deleted.")
+endif()
+
+
+

Index: 3rd_party/eigen/cmake/FindAdolc.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindAdolc.cmake
+++ 3rd_party/eigen/cmake/FindAdolc.cmake
@@ -3,11 +3,11 @@
   set(ADOLC_FIND_QUIETLY TRUE)
 endif (ADOLC_INCLUDES AND ADOLC_LIBRARIES)
 
 find_path(ADOLC_INCLUDES
   NAMES
-  adolc/adouble.h
+  adolc/adtl.h
   PATHS
   $ENV{ADOLCDIR}
   ${INCLUDE_INSTALL_DIR}
 )
 

Index: 3rd_party/eigen/cmake/FindBLAS.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindBLAS.cmake
+++ 3rd_party/eigen/cmake/FindBLAS.cmake
@@ -1,419 +1,1406 @@
-# Find BLAS library
+###
+#
+# @copyright (c) 2009-2014 The University of Tennessee and The University
+#                          of Tennessee Research Foundation.
+#                          All rights reserved.
+# @copyright (c) 2012-2016 Inria. All rights reserved.
+# @copyright (c) 2012-2014 Bordeaux INP, CNRS (LaBRI UMR 5800), Inria, Univ. Bordeaux. All rights reserved.
+#
+###
 #
-# This module finds an installed library that implements the BLAS
+# - Find BLAS library
+# This module finds an installed fortran library that implements the BLAS
 # linear-algebra interface (see http://www.netlib.org/blas/).
-# The list of libraries searched for is mainly taken
+# The list of libraries searched for is taken
 # from the autoconf macro file, acx_blas.m4 (distributed at
 # http://ac-archive.sourceforge.net/ac-archive/acx_blas.html).
 #
 # This module sets the following variables:
 #  BLAS_FOUND - set to true if a library implementing the BLAS interface
 #    is found
-#  BLAS_INCLUDE_DIR - Directories containing the BLAS header files
-#  BLAS_DEFINITIONS - Compilation options to use BLAS
-#  BLAS_LINKER_FLAGS - Linker flags to use BLAS (excluding -l
+#  BLAS_LINKER_FLAGS - uncached list of required linker flags (excluding -l
 #    and -L).
-#  BLAS_LIBRARIES_DIR - Directories containing the BLAS libraries.
-#     May be null if BLAS_LIBRARIES contains libraries name using full path.
-#  BLAS_LIBRARIES - List of libraries to link against BLAS interface.
-#     May be null if the compiler supports auto-link (e.g. VC++).
-#  BLAS_USE_FILE - The name of the cmake module to include to compile
-#     applications or libraries using BLAS.
-#
-# This module was modified by CGAL team:
-# - find libraries for a C++ compiler, instead of Fortran
-# - added BLAS_INCLUDE_DIR, BLAS_DEFINITIONS and BLAS_LIBRARIES_DIR
-# - removed BLAS95_LIBRARIES
+#  BLAS_COMPILER_FLAGS - uncached list of required compiler flags (including -I for mkl headers).
+#  BLAS_LIBRARIES - uncached list of libraries (using full path name) to
+#    link against to use BLAS
+#  BLAS95_LIBRARIES - uncached list of libraries (using full path name)
+#    to link against to use BLAS95 interface
+#  BLAS95_FOUND - set to true if a library implementing the BLAS f95 interface
+#    is found
+#  BLA_STATIC  if set on this determines what kind of linkage we do (static)
+#  BLA_VENDOR  if set checks only the specified vendor, if not set checks
+#     all the possibilities
+#  BLAS_VENDOR_FOUND stores the BLAS vendor found 
+#  BLA_F95     if set on tries to find the f95 interfaces for BLAS/LAPACK
+# The user can give specific paths where to find the libraries adding cmake
+# options at configure (ex: cmake path/to/project -DBLAS_DIR=path/to/blas):
+#  BLAS_DIR            - Where to find the base directory of blas
+#  BLAS_INCDIR         - Where to find the header files
+#  BLAS_LIBDIR         - Where to find the library files
+# The module can also look for the following environment variables if paths
+# are not given as cmake variable: BLAS_DIR, BLAS_INCDIR, BLAS_LIBDIR
+# For MKL case and if no paths are given as hints, we will try to use the MKLROOT
+# environment variable
+#  BLAS_VERBOSE Print some additional information during BLAS libraries detection
+##########
+### List of vendors (BLA_VENDOR) valid in this module
+########## List of vendors (BLA_VENDOR) valid in this module
+##  Open (for OpenBlas), Eigen (for EigenBlas), Goto, ATLAS PhiPACK,
+##  CXML, DXML, SunPerf, SCSL, SGIMATH, IBMESSL, IBMESSLMT
+##  Intel10_32 (intel mkl v10 32 bit), Intel10_64lp (intel mkl v10 64 bit,lp thread model, lp64 model),
+##  Intel10_64lp_seq (intel mkl v10 64 bit,sequential code, lp64 model),
+##  Intel( older versions of mkl 32 and 64 bit),
+##  ACML, ACML_MP, ACML_GPU, Apple, NAS, Generic
+# C/CXX should be enabled to use Intel mkl
+###
+# We handle different modes to find the dependency
+#
+# - Detection if already installed on the system
+#   - BLAS libraries can be detected from different ways
+#     Here is the order of precedence:
+#     1) we look in cmake variable BLAS_LIBDIR or BLAS_DIR (we guess the libdirs) if defined
+#     2) we look in environment variable BLAS_LIBDIR or BLAS_DIR (we guess the libdirs) if defined
+#     3) we look in common environnment variables depending on the system (INCLUDE, C_INCLUDE_PATH, CPATH - LIB, DYLD_LIBRARY_PATH, LD_LIBRARY_PATH)
+#     4) we look in common system paths depending on the system, see for example paths contained in the following cmake variables:
+#       - CMAKE_PLATFORM_IMPLICIT_INCLUDE_DIRECTORIES, CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES
+#       - CMAKE_C_IMPLICIT_INCLUDE_DIRECTORIES, CMAKE_C_IMPLICIT_LINK_DIRECTORIES
+#
+
+#=============================================================================
+# Copyright 2007-2009 Kitware, Inc.
+#
+# Distributed under the OSI-approved BSD License (the "License");
+# see accompanying file Copyright.txt for details.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without even the
+# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the License for more information.
+#=============================================================================
+# (To distribute this file outside of CMake, substitute the full
+#  License text for the above reference.)
+
+## Some macros to print status when search for headers and libs
+# This macro informs why the _lib_to_find file has not been found
+macro(Print_Find_Library_Blas_Status _libname _lib_to_find)
+
+  # save _libname upper/lower case
+  string(TOUPPER ${_libname} LIBNAME)
+  string(TOLOWER ${_libname} libname)
+
+  # print status
+  #message(" ")
+  if(${LIBNAME}_LIBDIR)
+    message("${Yellow}${LIBNAME}_LIBDIR is defined but ${_lib_to_find}"
+      "has not been found in ${ARGN}${ColourReset}")
+  else()
+    if(${LIBNAME}_DIR)
+      message("${Yellow}${LIBNAME}_DIR is defined but ${_lib_to_find}"
+	"has not been found in ${ARGN}${ColourReset}")
+    else()
+      message("${Yellow}${_lib_to_find} not found."
+	"Nor ${LIBNAME}_DIR neither ${LIBNAME}_LIBDIR"
+	"are defined so that we look for ${_lib_to_find} in"
+	"system paths (Linux: LD_LIBRARY_PATH, Windows: LIB,"
+	"Mac: DYLD_LIBRARY_PATH,"
+	"CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES,"
+	"CMAKE_C_IMPLICIT_LINK_DIRECTORIES)${ColourReset}")
+      if(_lib_env)
+	message("${Yellow}${_lib_to_find} has not been found in"
+	  "${_lib_env}${ColourReset}")
+      endif()
+    endif()
+  endif()
+  message("${BoldYellow}Please indicate where to find ${_lib_to_find}. You have three options:\n"
+    "- Option 1: Provide the Installation directory of BLAS library with cmake option: -D${LIBNAME}_DIR=your/path/to/${libname}/\n"
+    "- Option 2: Provide the directory where to find the library with cmake option: -D${LIBNAME}_LIBDIR=your/path/to/${libname}/lib/\n"
+    "- Option 3: Update your environment variable (Linux: LD_LIBRARY_PATH, Windows: LIB, Mac: DYLD_LIBRARY_PATH)\n"
+    "- Option 4: If your library provides a PkgConfig file, make sure pkg-config finds your library${ColourReset}")
+
+endmacro()
+
+# This macro informs why the _lib_to_find file has not been found
+macro(Print_Find_Library_Blas_CheckFunc_Status _name)
+
+  # save _libname upper/lower case
+  string(TOUPPER ${_name} FUNCNAME)
+  string(TOLOWER ${_name} funcname)
+
+  # print status
+  #message(" ")
+  message("${Red}Libs have been found but check of symbol ${_name} failed "
+    "with following libraries ${ARGN}${ColourReset}")
+  message("${BoldRed}Please open your error file CMakeFiles/CMakeError.log"
+    "to figure out why it fails${ColourReset}")
+  #message(" ")
+
+endmacro()
+
+if (NOT BLAS_FOUND)
+  set(BLAS_DIR "" CACHE PATH "Installation directory of BLAS library")
+  if (NOT BLAS_FIND_QUIETLY)
+    message(STATUS "A cache variable, namely BLAS_DIR, has been set to specify the install directory of BLAS")
+  endif()
+endif()
+
+option(BLAS_VERBOSE "Print some additional information during BLAS libraries detection" OFF)
+mark_as_advanced(BLAS_VERBOSE)
 
 include(CheckFunctionExists)
-
-
-# This macro checks for the existence of the combination of fortran libraries
-# given by _list.  If the combination is found, this macro checks (using the
-# check_function_exists macro) whether can link against that library
-# combination using the name of a routine given by _name using the linker
-# flags given by _flags.  If the combination of libraries is found and passes
-# the link test, LIBRARIES is set to the list of complete library paths that
-# have been found and DEFINITIONS to the required definitions.
-# Otherwise, LIBRARIES is set to FALSE.
-# N.B. _prefix is the prefix applied to the names of all cached variables that
-# are generated internally and marked advanced by this macro.
-macro(check_fortran_libraries DEFINITIONS LIBRARIES _prefix _name _flags _list _path)
-  #message("DEBUG: check_fortran_libraries(${_list} in ${_path})")
-
-  # Check for the existence of the libraries given by _list
-  set(_libraries_found TRUE)
-  set(_libraries_work FALSE)
-  set(${DEFINITIONS} "")
-  set(${LIBRARIES} "")
+include(CheckFortranFunctionExists)
+
+set(_blas_ORIG_CMAKE_FIND_LIBRARY_SUFFIXES ${CMAKE_FIND_LIBRARY_SUFFIXES})
+
+# Check the language being used
+get_property( _LANGUAGES_ GLOBAL PROPERTY ENABLED_LANGUAGES )
+if( _LANGUAGES_ MATCHES Fortran )
+  set( _CHECK_FORTRAN TRUE )
+elseif( (_LANGUAGES_ MATCHES C) OR (_LANGUAGES_ MATCHES CXX) )
+  set( _CHECK_FORTRAN FALSE )
+else()
+  if(BLAS_FIND_REQUIRED)
+    message(FATAL_ERROR "FindBLAS requires Fortran, C, or C++ to be enabled.")
+  else()
+    message(STATUS "Looking for BLAS... - NOT found (Unsupported languages)")
+    return()
+  endif()
+endif()
+
+macro(Check_Fortran_Libraries LIBRARIES _prefix _name _flags _list _thread)
+  # This macro checks for the existence of the combination of fortran libraries
+  # given by _list.  If the combination is found, this macro checks (using the
+  # Check_Fortran_Function_Exists macro) whether can link against that library
+  # combination using the name of a routine given by _name using the linker
+  # flags given by _flags.  If the combination of libraries is found and passes
+  # the link test, LIBRARIES is set to the list of complete library paths that
+  # have been found.  Otherwise, LIBRARIES is set to FALSE.
+
+  # N.B. _prefix is the prefix applied to the names of all cached variables that
+  # are generated internally and marked advanced by this macro.
+
+  set(_libdir ${ARGN})
+
+  set(_libraries_work TRUE)
+  set(${LIBRARIES})
   set(_combined_name)
+  set(ENV_MKLROOT "$ENV{MKLROOT}")
+  set(ENV_BLAS_DIR "$ENV{BLAS_DIR}")
+  set(ENV_BLAS_LIBDIR "$ENV{BLAS_LIBDIR}")
+  if (NOT _libdir)
+    if (BLAS_LIBDIR)
+      list(APPEND _libdir "${BLAS_LIBDIR}")
+    elseif (BLAS_DIR)
+      list(APPEND _libdir "${BLAS_DIR}")
+      list(APPEND _libdir "${BLAS_DIR}/lib")
+      if("${CMAKE_SIZEOF_VOID_P}" EQUAL "8")
+	list(APPEND _libdir "${BLAS_DIR}/lib64")
+	list(APPEND _libdir "${BLAS_DIR}/lib/intel64")
+      else()
+	list(APPEND _libdir "${BLAS_DIR}/lib32")
+	list(APPEND _libdir "${BLAS_DIR}/lib/ia32")
+      endif()
+    elseif(ENV_BLAS_LIBDIR)
+      list(APPEND _libdir "${ENV_BLAS_LIBDIR}")
+    elseif(ENV_BLAS_DIR)
+      list(APPEND _libdir "${ENV_BLAS_DIR}")
+      list(APPEND _libdir "${ENV_BLAS_DIR}/lib")
+      if("${CMAKE_SIZEOF_VOID_P}" EQUAL "8")
+	list(APPEND _libdir "${ENV_BLAS_DIR}/lib64")
+	list(APPEND _libdir "${ENV_BLAS_DIR}/lib/intel64")
+      else()
+	list(APPEND _libdir "${ENV_BLAS_DIR}/lib32")
+	list(APPEND _libdir "${ENV_BLAS_DIR}/lib/ia32")
+      endif()
+    else()
+      if (ENV_MKLROOT)
+	list(APPEND _libdir "${ENV_MKLROOT}/lib")
+	if("${CMAKE_SIZEOF_VOID_P}" EQUAL "8")
+	  list(APPEND _libdir "${ENV_MKLROOT}/lib64")
+	  list(APPEND _libdir "${ENV_MKLROOT}/lib/intel64")
+	else()
+	  list(APPEND _libdir "${ENV_MKLROOT}/lib32")
+	  list(APPEND _libdir "${ENV_MKLROOT}/lib/ia32")
+	endif()
+      endif()
+      if (WIN32)
+	string(REPLACE ":" ";" _libdir2 "$ENV{LIB}")
+      elseif (APPLE)
+	string(REPLACE ":" ";" _libdir2 "$ENV{DYLD_LIBRARY_PATH}")
+      else ()
+	string(REPLACE ":" ";" _libdir2 "$ENV{LD_LIBRARY_PATH}")
+      endif ()
+      list(APPEND _libdir "${_libdir2}")
+      list(APPEND _libdir "${CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES}")
+      list(APPEND _libdir "${CMAKE_C_IMPLICIT_LINK_DIRECTORIES}")
+    endif()
+  endif ()
+
+  if (BLAS_VERBOSE)
+    message("${Cyan}Try to find BLAS libraries: ${_list}")
+  endif ()
+
   foreach(_library ${_list})
     set(_combined_name ${_combined_name}_${_library})
 
-    if(_libraries_found)
-      # search first in ${_path}
-      find_library(${_prefix}_${_library}_LIBRARY
-                  NAMES ${_library}
-                  PATHS ${_path} NO_DEFAULT_PATH
-                  )
-      # if not found, search in environment variables and system
-      if ( WIN32 )
-        find_library(${_prefix}_${_library}_LIBRARY
-                    NAMES ${_library}
-                    PATHS ENV LIB
-                    )
-      elseif ( APPLE )
-        find_library(${_prefix}_${_library}_LIBRARY
-                    NAMES ${_library}
-                    PATHS /usr/local/lib /usr/lib /usr/local/lib64 /usr/lib64 ENV DYLD_LIBRARY_PATH
-                    )
+    if(_libraries_work)
+      if (BLA_STATIC)
+	if (WIN32)
+	  set(CMAKE_FIND_LIBRARY_SUFFIXES .lib ${CMAKE_FIND_LIBRARY_SUFFIXES})
+	endif ()
+	if (APPLE)
+	  set(CMAKE_FIND_LIBRARY_SUFFIXES .lib ${CMAKE_FIND_LIBRARY_SUFFIXES})
+	else ()
+	  set(CMAKE_FIND_LIBRARY_SUFFIXES .a ${CMAKE_FIND_LIBRARY_SUFFIXES})
+	endif ()
       else ()
-        find_library(${_prefix}_${_library}_LIBRARY
-                    NAMES ${_library}
-                    PATHS /usr/local/lib /usr/lib /usr/local/lib64 /usr/lib64 ENV LD_LIBRARY_PATH
-                    )
-      endif()
+	if (CMAKE_SYSTEM_NAME STREQUAL "Linux")
+	  # for ubuntu's libblas3gf and liblapack3gf packages
+	  set(CMAKE_FIND_LIBRARY_SUFFIXES ${CMAKE_FIND_LIBRARY_SUFFIXES} .so.3gf)
+	endif ()
+      endif ()
+      find_library(${_prefix}_${_library}_LIBRARY
+	NAMES ${_library}
+	HINTS ${_libdir}
+	NO_DEFAULT_PATH
+	)
       mark_as_advanced(${_prefix}_${_library}_LIBRARY)
+      # Print status if not found
+      # -------------------------
+      if (NOT ${_prefix}_${_library}_LIBRARY AND NOT BLAS_FIND_QUIETLY AND BLAS_VERBOSE)
+	Print_Find_Library_Blas_Status(blas ${_library} ${_libdir})
+      endif ()
       set(${LIBRARIES} ${${LIBRARIES}} ${${_prefix}_${_library}_LIBRARY})
-      set(_libraries_found ${${_prefix}_${_library}_LIBRARY})
-    endif(_libraries_found)
+      set(_libraries_work ${${_prefix}_${_library}_LIBRARY})
+    endif(_libraries_work)
   endforeach(_library ${_list})
-  if(_libraries_found)
-    set(_libraries_found ${${LIBRARIES}})
-  endif()
-
-  # Test this combination of libraries with the Fortran/f2c interface.
-  # We test the Fortran interface first as it is well standardized.
-  if(_libraries_found AND NOT _libraries_work)
-    set(${DEFINITIONS}  "-D${_prefix}_USE_F2C")
-    set(${LIBRARIES}    ${_libraries_found})
-    # Some C++ linkers require the f2c library to link with Fortran libraries.
-    # I do not know which ones, thus I just add the f2c library if it is available.
-    find_package( F2C QUIET )
-    if ( F2C_FOUND )
-      set(${DEFINITIONS}  ${${DEFINITIONS}} ${F2C_DEFINITIONS})
-      set(${LIBRARIES}    ${${LIBRARIES}} ${F2C_LIBRARIES})
-    endif()
-    set(CMAKE_REQUIRED_DEFINITIONS  ${${DEFINITIONS}})
-    set(CMAKE_REQUIRED_LIBRARIES    ${_flags} ${${LIBRARIES}})
-    #message("DEBUG: CMAKE_REQUIRED_DEFINITIONS = ${CMAKE_REQUIRED_DEFINITIONS}")
-    #message("DEBUG: CMAKE_REQUIRED_LIBRARIES = ${CMAKE_REQUIRED_LIBRARIES}")
-    # Check if function exists with f2c calling convention (ie a trailing underscore)
-    check_function_exists(${_name}_ ${_prefix}_${_name}_${_combined_name}_f2c_WORKS)
-    set(CMAKE_REQUIRED_DEFINITIONS} "")
-    set(CMAKE_REQUIRED_LIBRARIES    "")
-    mark_as_advanced(${_prefix}_${_name}_${_combined_name}_f2c_WORKS)
-    set(_libraries_work ${${_prefix}_${_name}_${_combined_name}_f2c_WORKS})
-  endif(_libraries_found AND NOT _libraries_work)
-
-  # If not found, test this combination of libraries with a C interface.
-  # A few implementations (ie ACML) provide a C interface. Unfortunately, there is no standard.
-  if(_libraries_found AND NOT _libraries_work)
-    set(${DEFINITIONS} "")
-    set(${LIBRARIES}   ${_libraries_found})
-    set(CMAKE_REQUIRED_DEFINITIONS "")
-    set(CMAKE_REQUIRED_LIBRARIES   ${_flags} ${${LIBRARIES}})
-    #message("DEBUG: CMAKE_REQUIRED_LIBRARIES = ${CMAKE_REQUIRED_LIBRARIES}")
-    check_function_exists(${_name} ${_prefix}_${_name}${_combined_name}_WORKS)
-    set(CMAKE_REQUIRED_LIBRARIES "")
-    mark_as_advanced(${_prefix}_${_name}${_combined_name}_WORKS)
-    set(_libraries_work ${${_prefix}_${_name}${_combined_name}_WORKS})
-  endif(_libraries_found AND NOT _libraries_work)
-
-  # on failure
-  if(NOT _libraries_work)
-    set(${DEFINITIONS} "")
-    set(${LIBRARIES}   FALSE)
-  endif()
-  #message("DEBUG: ${DEFINITIONS} = ${${DEFINITIONS}}")
-  #message("DEBUG: ${LIBRARIES} = ${${LIBRARIES}}")
-endmacro(check_fortran_libraries)
-
-
-#
-# main
-#
-
-# Is it already configured?
-if (BLAS_LIBRARIES_DIR OR BLAS_LIBRARIES)
-
-  set(BLAS_FOUND TRUE)
-
-else()
-
-  # reset variables
-  set( BLAS_INCLUDE_DIR "" )
-  set( BLAS_DEFINITIONS "" )
-  set( BLAS_LINKER_FLAGS "" )
-  set( BLAS_LIBRARIES "" )
-  set( BLAS_LIBRARIES_DIR "" )
-
-    #
-    # If Unix, search for BLAS function in possible libraries
-    #
-
+
+  if(_libraries_work)
+    # Test this combination of libraries.
+    if (CMAKE_SYSTEM_NAME STREQUAL "Linux" AND BLA_STATIC)
+      list(INSERT ${LIBRARIES} 0 "-Wl,--start-group")
+      list(APPEND ${LIBRARIES} "-Wl,--end-group")
+    endif()
+    set(CMAKE_REQUIRED_LIBRARIES "${_flags};${${LIBRARIES}};${_thread}")
+    set(CMAKE_REQUIRED_FLAGS "${BLAS_COMPILER_FLAGS}")
+    if (BLAS_VERBOSE)
+      message("${Cyan}BLAS libs found for BLA_VENDOR ${BLA_VENDOR}."
+	"Try to compile symbol ${_name} with following libraries:"
+	"${CMAKE_REQUIRED_LIBRARIES}")
+    endif ()
+    if(NOT BLAS_FOUND)
+      unset(${_prefix}${_combined_name}_WORKS CACHE)
+    endif()
+    if (_CHECK_FORTRAN)
+      if (CMAKE_Fortran_COMPILER_ID STREQUAL "GNU")
+	string(REPLACE "mkl_intel_lp64" "mkl_gf_lp64" CMAKE_REQUIRED_LIBRARIES "${CMAKE_REQUIRED_LIBRARIES}")
+	string(REPLACE "mkl_intel_ilp64" "mkl_gf_ilp64" CMAKE_REQUIRED_LIBRARIES "${CMAKE_REQUIRED_LIBRARIES}")
+      endif()
+      check_fortran_function_exists("${_name}" ${_prefix}${_combined_name}_WORKS)
+    else()
+      check_function_exists("${_name}_" ${_prefix}${_combined_name}_WORKS)
+    endif()
+    mark_as_advanced(${_prefix}${_combined_name}_WORKS)
+    set(_libraries_work ${${_prefix}${_combined_name}_WORKS})
+    # Print status if not found
+    # -------------------------
+    if (NOT _libraries_work AND NOT BLAS_FIND_QUIETLY AND BLAS_VERBOSE)
+      Print_Find_Library_Blas_CheckFunc_Status(${_name} ${CMAKE_REQUIRED_LIBRARIES})
+    endif ()
+    set(CMAKE_REQUIRED_LIBRARIES)
+  endif()
+
+  if(_libraries_work)
+    set(${LIBRARIES} ${${LIBRARIES}} ${_thread})
+  else(_libraries_work)
+    set(${LIBRARIES} FALSE)
+  endif(_libraries_work)
+
+endmacro(Check_Fortran_Libraries)
+
+
+set(BLAS_LINKER_FLAGS)
+set(BLAS_LIBRARIES)
+set(BLAS95_LIBRARIES)
+if ($ENV{BLA_VENDOR} MATCHES ".+")
+  set(BLA_VENDOR $ENV{BLA_VENDOR})
+else ()
+  if(NOT BLA_VENDOR)
+    set(BLA_VENDOR "All")
+  endif()
+endif ()
+
+#BLAS in intel mkl 10 library? (em64t 64bit)
+if (BLA_VENDOR MATCHES "Intel*" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES OR BLA_VENDOR MATCHES "Intel*")
+    # Looking for include
+    # -------------------
+
+    # Add system include paths to search include
+    # ------------------------------------------
+    unset(_inc_env)
+    set(ENV_MKLROOT "$ENV{MKLROOT}")
+    set(ENV_BLAS_DIR "$ENV{BLAS_DIR}")
+    set(ENV_BLAS_INCDIR "$ENV{BLAS_INCDIR}")
+    if(ENV_BLAS_INCDIR)
+      list(APPEND _inc_env "${ENV_BLAS_INCDIR}")
+    elseif(ENV_BLAS_DIR)
+      list(APPEND _inc_env "${ENV_BLAS_DIR}")
+      list(APPEND _inc_env "${ENV_BLAS_DIR}/include")
+    else()
+      if (ENV_MKLROOT)
+	list(APPEND _inc_env "${ENV_MKLROOT}/include")
+      endif()
+      # system variables
+      if(WIN32)
+	string(REPLACE ":" ";" _path_env "$ENV{INCLUDE}")
+	list(APPEND _inc_env "${_path_env}")
+      else()
+	string(REPLACE ":" ";" _path_env "$ENV{INCLUDE}")
+	list(APPEND _inc_env "${_path_env}")
+	string(REPLACE ":" ";" _path_env "$ENV{C_INCLUDE_PATH}")
+	list(APPEND _inc_env "${_path_env}")
+	string(REPLACE ":" ";" _path_env "$ENV{CPATH}")
+	list(APPEND _inc_env "${_path_env}")
+	string(REPLACE ":" ";" _path_env "$ENV{INCLUDE_PATH}")
+	list(APPEND _inc_env "${_path_env}")
+      endif()
+    endif()
+    list(APPEND _inc_env "${CMAKE_PLATFORM_IMPLICIT_INCLUDE_DIRECTORIES}")
+    list(APPEND _inc_env "${CMAKE_C_IMPLICIT_INCLUDE_DIRECTORIES}")
+    list(REMOVE_DUPLICATES _inc_env)
+
+    # set paths where to look for
+    set(PATH_TO_LOOK_FOR "${_inc_env}")
+
+    # Try to find the fftw header in the given paths
+    # -------------------------------------------------
+    # call cmake macro to find the header path
+    if(BLAS_INCDIR)
+      set(BLAS_mkl.h_DIRS "BLAS_mkl.h_DIRS-NOTFOUND")
+      find_path(BLAS_mkl.h_DIRS
+	NAMES mkl.h
+	HINTS ${BLAS_INCDIR})
+    else()
+      if(BLAS_DIR)
+	set(BLAS_mkl.h_DIRS "BLAS_mkl.h_DIRS-NOTFOUND")
+	find_path(BLAS_mkl.h_DIRS
+	  NAMES mkl.h
+	  HINTS ${BLAS_DIR}
+	  PATH_SUFFIXES "include")
+      else()
+	set(BLAS_mkl.h_DIRS "BLAS_mkl.h_DIRS-NOTFOUND")
+	find_path(BLAS_mkl.h_DIRS
+	  NAMES mkl.h
+	  HINTS ${PATH_TO_LOOK_FOR})
+      endif()
+    endif()
+    mark_as_advanced(BLAS_mkl.h_DIRS)
+
+    # If found, add path to cmake variable
+    # ------------------------------------
+    if (BLAS_mkl.h_DIRS)
+      set(BLAS_INCLUDE_DIRS "${BLAS_mkl.h_DIRS}")
+    else ()
+      set(BLAS_INCLUDE_DIRS "BLAS_INCLUDE_DIRS-NOTFOUND")
+      if(NOT BLAS_FIND_QUIETLY)
+	message(STATUS "Looking for BLAS -- mkl.h not found")
+      endif()
+    endif()
+
+    if (WIN32)
+      string(REPLACE ":" ";" _libdir "$ENV{LIB}")
+    elseif (APPLE)
+      string(REPLACE ":" ";" _libdir "$ENV{DYLD_LIBRARY_PATH}")
+    else ()
+      string(REPLACE ":" ";" _libdir "$ENV{LD_LIBRARY_PATH}")
+    endif ()
+    list(APPEND _libdir "${CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES}")
+    list(APPEND _libdir "${CMAKE_C_IMPLICIT_LINK_DIRECTORIES}")
+    # libiomp5
+    # --------
+    set(OMP_iomp5_LIBRARY "OMP_iomp5_LIBRARY-NOTFOUND")
+    find_library(OMP_iomp5_LIBRARY
+      NAMES iomp5
+      HINTS ${_libdir}
+      )
+    mark_as_advanced(OMP_iomp5_LIBRARY)
+    set(OMP_LIB "")
+    # libgomp
+    # -------
+    set(OMP_gomp_LIBRARY "OMP_gomp_LIBRARY-NOTFOUND")
+    find_library(OMP_gomp_LIBRARY
+      NAMES gomp
+      HINTS ${_libdir}
+      )
+    mark_as_advanced(OMP_gomp_LIBRARY)
+    # choose one or another depending on the compilo
+    if (CMAKE_C_COMPILER_ID STREQUAL "GNU")
+      if (OMP_gomp_LIBRARY)
+	set(OMP_LIB "${OMP_gomp_LIBRARY}")
+      endif()
+    else(CMAKE_C_COMPILER_ID STREQUAL "Intel")
+      if (OMP_iomp5_LIBRARY)
+	set(OMP_LIB "${OMP_iomp5_LIBRARY}")
+      endif()
+    endif()
+
+    if (UNIX AND NOT WIN32)
+      # m
+      find_library(M_LIBRARY
+	NAMES m
+	HINTS ${_libdir})
+      mark_as_advanced(M_LIBRARY)
+      if(M_LIBRARY)
+	set(LM "-lm")
+      else()
+	set(LM "")
+      endif()
+      # Fortran
+      set(LGFORTRAN "")
+      if (CMAKE_C_COMPILER_ID MATCHES "GNU")
+	find_library(
+	  FORTRAN_gfortran_LIBRARY
+	  NAMES gfortran
+	  HINTS ${_libdir}
+	  )
+	mark_as_advanced(FORTRAN_gfortran_LIBRARY)
+	if (FORTRAN_gfortran_LIBRARY)
+	  set(LGFORTRAN "${FORTRAN_gfortran_LIBRARY}")
+	endif()
+      elseif (CMAKE_C_COMPILER_ID MATCHES "Intel")
+	find_library(
+	  FORTRAN_ifcore_LIBRARY
+	  NAMES ifcore
+	  HINTS ${_libdir}
+	  )
+	mark_as_advanced(FORTRAN_ifcore_LIBRARY)
+	if (FORTRAN_ifcore_LIBRARY)
+	  set(LGFORTRAN "{FORTRAN_ifcore_LIBRARY}")
+	endif()
+      endif()
+      set(BLAS_COMPILER_FLAGS "")
+      if (NOT BLA_VENDOR STREQUAL "Intel10_64lp_seq")
+	if (CMAKE_C_COMPILER_ID STREQUAL "Intel")
+	  list(APPEND BLAS_COMPILER_FLAGS "-openmp")
+	endif()
+	if (CMAKE_C_COMPILER_ID STREQUAL "GNU")
+	  list(APPEND BLAS_COMPILER_FLAGS "-fopenmp")
+	endif()
+      endif()
+      if (CMAKE_C_COMPILER_ID STREQUAL "GNU")
+	if (BLA_VENDOR STREQUAL "Intel10_32")
+	  list(APPEND BLAS_COMPILER_FLAGS "-m32")
+	else()
+	  list(APPEND BLAS_COMPILER_FLAGS "-m64")
+	endif()
+	if (NOT BLA_VENDOR STREQUAL "Intel10_64lp_seq")
+	  list(APPEND OMP_LIB "-ldl")
+	endif()
+	if (ENV_MKLROOT)
+	  list(APPEND BLAS_COMPILER_FLAGS "-I${ENV_MKLROOT}/include")
+	endif()
+      endif()
+
+      set(additional_flags "")
+      if (CMAKE_C_COMPILER_ID STREQUAL "GNU" AND CMAKE_SYSTEM_NAME STREQUAL "Linux")
+	set(additional_flags "-Wl,--no-as-needed")
+      endif()
+    endif ()
+
+    if (_LANGUAGES_ MATCHES C OR _LANGUAGES_ MATCHES CXX)
+      if(BLAS_FIND_QUIETLY OR NOT BLAS_FIND_REQUIRED)
+	find_package(Threads)
+      else()
+	find_package(Threads REQUIRED)
+      endif()
+
+      set(BLAS_SEARCH_LIBS "")
+
+      if(BLA_F95)
+
+	set(BLAS_mkl_SEARCH_SYMBOL SGEMM)
+	set(_LIBRARIES BLAS95_LIBRARIES)
+	if (WIN32)
+	  if (BLA_STATIC)
+	    set(BLAS_mkl_DLL_SUFFIX "")
+	  else()
+	    set(BLAS_mkl_DLL_SUFFIX "_dll")
+	  endif()
+
+	  # Find the main file (32-bit or 64-bit)
+	  set(BLAS_SEARCH_LIBS_WIN_MAIN "")
+	  if (BLA_VENDOR STREQUAL "Intel10_32" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_MAIN
+	      "mkl_blas95${BLAS_mkl_DLL_SUFFIX} mkl_intel_c${BLAS_mkl_DLL_SUFFIX}")
+	  endif()
+	  if (BLA_VENDOR STREQUAL "Intel10_64lp*" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_MAIN
+	      "mkl_blas95_lp64${BLAS_mkl_DLL_SUFFIX} mkl_intel_lp64${BLAS_mkl_DLL_SUFFIX}")
+	  endif ()
+
+	  # Add threading/sequential libs
+	  set(BLAS_SEARCH_LIBS_WIN_THREAD "")
+	  if (BLA_VENDOR STREQUAL "*_seq" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_THREAD
+	      "mkl_sequential${BLAS_mkl_DLL_SUFFIX}")
+	  endif()
+	  if (NOT BLA_VENDOR STREQUAL "*_seq" OR BLA_VENDOR STREQUAL "All")
+	    # old version
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_THREAD
+	      "libguide40 mkl_intel_thread${BLAS_mkl_DLL_SUFFIX}")
+	    # mkl >= 10.3
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_THREAD
+	      "libiomp5md mkl_intel_thread${BLAS_mkl_DLL_SUFFIX}")
+	  endif()
+
+	  # Cartesian product of the above
+	  foreach (MAIN ${BLAS_SEARCH_LIBS_WIN_MAIN})
+	    foreach (THREAD ${BLAS_SEARCH_LIBS_WIN_THREAD})
+	      list(APPEND BLAS_SEARCH_LIBS
+		"${MAIN} ${THREAD} mkl_core${BLAS_mkl_DLL_SUFFIX}")
+	    endforeach()
+	  endforeach()
+	else (WIN32)
+	  if (BLA_VENDOR STREQUAL "Intel10_32" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl_blas95 mkl_intel mkl_intel_thread mkl_core guide")
+	  endif ()
+	  if (BLA_VENDOR STREQUAL "Intel10_64lp" OR BLA_VENDOR STREQUAL "All")
+	    # old version
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl_blas95 mkl_intel_lp64 mkl_intel_thread mkl_core guide")
+	    # mkl >= 10.3
+	    if (CMAKE_C_COMPILER_ID STREQUAL "Intel")
+	      list(APPEND BLAS_SEARCH_LIBS
+		"mkl_blas95_lp64 mkl_intel_lp64 mkl_intel_thread mkl_core")
+	    endif()
+	    if (CMAKE_C_COMPILER_ID STREQUAL "GNU")
+	      list(APPEND BLAS_SEARCH_LIBS
+		"mkl_blas95_lp64 mkl_intel_lp64 mkl_gnu_thread mkl_core")
+	    endif()
+	  endif ()
+	  if (BLA_VENDOR STREQUAL "Intel10_64lp_seq" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl_intel_lp64 mkl_sequential mkl_core")
+	    if (BLA_VENDOR STREQUAL "Intel10_64lp_seq")
+	      set(OMP_LIB "")
+	    endif()
+	  endif ()
+	endif (WIN32)
+
+      else (BLA_F95)
+
+	set(BLAS_mkl_SEARCH_SYMBOL sgemm)
+	set(_LIBRARIES BLAS_LIBRARIES)
+	if (WIN32)
+	  if (BLA_STATIC)
+	    set(BLAS_mkl_DLL_SUFFIX "")
+	  else()
+	    set(BLAS_mkl_DLL_SUFFIX "_dll")
+	  endif()
+
+	  # Find the main file (32-bit or 64-bit)
+	  set(BLAS_SEARCH_LIBS_WIN_MAIN "")
+	  if (BLA_VENDOR STREQUAL "Intel10_32" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_MAIN
+	      "mkl_intel_c${BLAS_mkl_DLL_SUFFIX}")
+	  endif()
+	  if (BLA_VENDOR STREQUAL "Intel10_64lp*" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_MAIN
+	      "mkl_intel_lp64${BLAS_mkl_DLL_SUFFIX}")
+	  endif ()
+
+	  # Add threading/sequential libs
+	  set(BLAS_SEARCH_LIBS_WIN_THREAD "")
+	  if (NOT BLA_VENDOR STREQUAL "*_seq" OR BLA_VENDOR STREQUAL "All")
+	    # old version
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_THREAD
+	      "libguide40 mkl_intel_thread${BLAS_mkl_DLL_SUFFIX}")
+	    # mkl >= 10.3
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_THREAD
+	      "libiomp5md mkl_intel_thread${BLAS_mkl_DLL_SUFFIX}")
+	  endif()
+	  if (BLA_VENDOR STREQUAL "*_seq" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS_WIN_THREAD
+	      "mkl_sequential${BLAS_mkl_DLL_SUFFIX}")
+	  endif()
+
+	  # Cartesian product of the above
+	  foreach (MAIN ${BLAS_SEARCH_LIBS_WIN_MAIN})
+	    foreach (THREAD ${BLAS_SEARCH_LIBS_WIN_THREAD})
+	      list(APPEND BLAS_SEARCH_LIBS
+		"${MAIN} ${THREAD} mkl_core${BLAS_mkl_DLL_SUFFIX}")
+	    endforeach()
+	  endforeach()
+	else (WIN32)
+	  if (BLA_VENDOR STREQUAL "Intel10_32" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl_intel mkl_intel_thread mkl_core guide")
+	  endif ()
+	  if (BLA_VENDOR STREQUAL "Intel10_64lp" OR BLA_VENDOR STREQUAL "All")
+	    # old version
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl_intel_lp64 mkl_intel_thread mkl_core guide")
+	    # mkl >= 10.3
+	    if (CMAKE_C_COMPILER_ID STREQUAL "Intel")
+	      list(APPEND BLAS_SEARCH_LIBS
+		"mkl_intel_lp64 mkl_intel_thread mkl_core")
+	    endif()
+	    if (CMAKE_C_COMPILER_ID STREQUAL "GNU")
+	      list(APPEND BLAS_SEARCH_LIBS
+		"mkl_intel_lp64 mkl_gnu_thread mkl_core")
+	    endif()
+	  endif ()
+	  if (BLA_VENDOR STREQUAL "Intel10_64lp_seq" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl_intel_lp64 mkl_sequential mkl_core")
+	    if (BLA_VENDOR STREQUAL "Intel10_64lp_seq")
+	      set(OMP_LIB "")
+	    endif()
+	  endif ()
+	  #older vesions of intel mkl libs
+	  if (BLA_VENDOR STREQUAL "Intel" OR BLA_VENDOR STREQUAL "All")
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl")
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl_ia32")
+	    list(APPEND BLAS_SEARCH_LIBS
+	      "mkl_em64t")
+	  endif ()
+	endif (WIN32)
+
+      endif (BLA_F95)
+
+      foreach (IT ${BLAS_SEARCH_LIBS})
+	string(REPLACE " " ";" SEARCH_LIBS ${IT})
+	if (${_LIBRARIES})
+	else ()
+	  check_fortran_libraries(
+	    ${_LIBRARIES}
+	    BLAS
+	    ${BLAS_mkl_SEARCH_SYMBOL}
+	    "${additional_flags}"
+	    "${SEARCH_LIBS}"
+	    "${OMP_LIB};${CMAKE_THREAD_LIBS_INIT};${LM}"
+	    )
+	  if(_LIBRARIES)
+	    set(BLAS_LINKER_FLAGS "${additional_flags}")
+	  endif()
+	endif()
+      endforeach ()
+      if(NOT BLAS_FIND_QUIETLY)
+        if(${_LIBRARIES})
+          message(STATUS "Looking for MKL BLAS: found")
+        else()
+          message(STATUS "Looking for MKL BLAS: not found")
+        endif()
+      endif()
+      if (${_LIBRARIES} AND NOT BLAS_VENDOR_FOUND)
+          set (BLAS_VENDOR_FOUND "Intel MKL")
+      endif()
+    endif (_LANGUAGES_ MATCHES C OR _LANGUAGES_ MATCHES CXX)
+  endif(NOT BLAS_LIBRARIES OR BLA_VENDOR MATCHES "Intel*")
+endif (BLA_VENDOR MATCHES "Intel*" OR BLA_VENDOR STREQUAL "All")
+
+
+if (BLA_VENDOR STREQUAL "Goto" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    # gotoblas (http://www.tacc.utexas.edu/tacc-projects/gotoblas2)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "goto2"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for Goto BLAS: found")
+      else()
+	message(STATUS "Looking for Goto BLAS: not found")
+      endif()
+    endif()
+  endif()
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "Goto")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "Goto" OR BLA_VENDOR STREQUAL "All")
+
+
+# OpenBlas
+if (BLA_VENDOR STREQUAL "Open" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    # openblas (http://www.openblas.net/)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "openblas"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for Open BLAS: found")
+      else()
+	message(STATUS "Looking for Open BLAS: not found")
+      endif()
+    endif()
+  endif()
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "Openblas")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "Open" OR BLA_VENDOR STREQUAL "All")
+
+
+# EigenBlas
+if (BLA_VENDOR STREQUAL "Eigen" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    # eigenblas (http://eigen.tuxfamily.org/index.php?title=Main_Page)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "eigen_blas"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+	message(STATUS "Looking for Eigen BLAS: found")
+      else()
+	message(STATUS "Looking for Eigen BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if(NOT BLAS_LIBRARIES)
+    # eigenblas (http://eigen.tuxfamily.org/index.php?title=Main_Page)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "eigen_blas_static"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for Eigen BLAS: found")
+      else()
+	message(STATUS "Looking for Eigen BLAS: not found")
+      endif()
+    endif()
+  endif()
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "Eigen")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "Eigen" OR BLA_VENDOR STREQUAL "All")
+
+
+if (BLA_VENDOR STREQUAL "ATLAS" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
     # BLAS in ATLAS library? (http://math-atlas.sourceforge.net/)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
+    check_fortran_libraries(
       BLAS_LIBRARIES
       BLAS
-      sgemm
-      ""
-      "cblas;f77blas;atlas"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    # BLAS in PhiPACK libraries? (requires generic BLAS lib, too)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
+      dgemm
+      ""
+      "f77blas;atlas"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for Atlas BLAS: found")
+      else()
+	message(STATUS "Looking for Atlas BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "Atlas")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "ATLAS" OR BLA_VENDOR STREQUAL "All")
+
+
+# BLAS in PhiPACK libraries? (requires generic BLAS lib, too)
+if (BLA_VENDOR STREQUAL "PhiPACK" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
       BLAS_LIBRARIES
       BLAS
       sgemm
       ""
       "sgemm;dgemm;blas"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    # BLAS in Alpha CXML library?
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for PhiPACK BLAS: found")
+      else()
+	message(STATUS "Looking for PhiPACK BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "PhiPACK")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "PhiPACK" OR BLA_VENDOR STREQUAL "All")
+
+
+# BLAS in Alpha CXML library?
+if (BLA_VENDOR STREQUAL "CXML" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
       BLAS_LIBRARIES
       BLAS
       sgemm
       ""
       "cxml"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    # BLAS in Alpha DXML library? (now called CXML, see above)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for CXML BLAS: found")
+      else()
+	message(STATUS "Looking for CXML BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "CXML")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "CXML" OR BLA_VENDOR STREQUAL "All")
+
+
+# BLAS in Alpha DXML library? (now called CXML, see above)
+if (BLA_VENDOR STREQUAL "DXML" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
       BLAS_LIBRARIES
       BLAS
       sgemm
       ""
       "dxml"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    # BLAS in Sun Performance library?
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for DXML BLAS: found")
+      else()
+	message(STATUS "Looking for DXML BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "DXML")
+  endif()
+  
+endif (BLA_VENDOR STREQUAL "DXML" OR BLA_VENDOR STREQUAL "All")
+
+
+# BLAS in Sun Performance library?
+if (BLA_VENDOR STREQUAL "SunPerf" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
       BLAS_LIBRARIES
       BLAS
       sgemm
       "-xlic_lib=sunperf"
       "sunperf;sunmath"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
+      ""
       )
+    if(BLAS_LIBRARIES)
+      set(BLAS_LINKER_FLAGS "-xlic_lib=sunperf")
+    endif()
+    if(NOT BLAS_FIND_QUIETLY)
       if(BLAS_LIBRARIES)
-        # Extra linker flag
-        set(BLAS_LINKER_FLAGS "-xlic_lib=sunperf")
+	message(STATUS "Looking for SunPerf BLAS: found")
+      else()
+	message(STATUS "Looking for SunPerf BLAS: not found")
       endif()
     endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "SunPerf")
+  endif()
+
+endif ()
+
+
+# BLAS in SCSL library?  (SGI/Cray Scientific Library)
+if (BLA_VENDOR STREQUAL "SCSL" OR BLA_VENDOR STREQUAL "All")
 
-    # BLAS in SCSL library?  (SGI/Cray Scientific Library)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
       BLAS_LIBRARIES
       BLAS
       sgemm
       ""
       "scsl"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    # BLAS in SGIMATH library?
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for SCSL BLAS: found")
+      else()
+	message(STATUS "Looking for SCSL BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "SunPerf")
+  endif()
+
+endif ()
+
+
+# BLAS in SGIMATH library?
+if (BLA_VENDOR STREQUAL "SGIMATH" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
       BLAS_LIBRARIES
       BLAS
       sgemm
       ""
       "complib.sgimath"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    # BLAS in IBM ESSL library? (requires generic BLAS lib, too)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "essl;blas"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    #BLAS in intel mkl 10 library? (em64t 64bit)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "mkl_intel_lp64;mkl_intel_thread;mkl_core;guide;pthread"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    ### windows version of intel mkl 10?
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      SGEMM
-      ""
-      "mkl_c_dll;mkl_intel_thread_dll;mkl_core_dll;libguide40"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    #older versions of intel mkl libs
-
-    # BLAS in intel mkl library? (shared)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "mkl;guide;pthread"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    #BLAS in intel mkl library? (static, 32bit)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "mkl_ia32;guide;pthread"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    #BLAS in intel mkl library? (static, em64t 64bit)
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "mkl_em64t;guide;pthread"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    #BLAS in acml library?
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "acml"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    # Apple BLAS library?
-    if(NOT BLAS_LIBRARIES)
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "Accelerate"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-    if ( NOT BLAS_LIBRARIES )
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "vecLib"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif ( NOT BLAS_LIBRARIES )
-
-    # Generic BLAS library?
-    # This configuration *must* be the last try as this library is notably slow.
-    if ( NOT BLAS_LIBRARIES )
-      check_fortran_libraries(
-      BLAS_DEFINITIONS
-      BLAS_LIBRARIES
-      BLAS
-      sgemm
-      ""
-      "blas"
-      "${CGAL_TAUCS_LIBRARIES_DIR} ENV BLAS_LIB_DIR"
-      )
-    endif()
-
-  if(BLAS_LIBRARIES_DIR OR BLAS_LIBRARIES)
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for SGIMATH BLAS: found")
+      else()
+	message(STATUS "Looking for SGIMATH BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "SGIMATH")
+  endif()
+
+endif ()
+
+
+# BLAS in IBM ESSL library (requires generic BLAS lib, too)
+if (BLA_VENDOR STREQUAL "IBMESSL" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "essl;xlfmath;xlf90_r;blas"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for IBM ESSL BLAS: found")
+      else()
+	message(STATUS "Looking for IBM ESSL BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "IBM ESSL")
+  endif()
+
+endif ()
+
+# BLAS in IBM ESSL_MT library (requires generic BLAS lib, too)
+if (BLA_VENDOR STREQUAL "IBMESSLMT" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "esslsmp;xlsmp;xlfmath;xlf90_r;blas"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for IBM ESSL MT BLAS: found")
+      else()
+	message(STATUS "Looking for IBM ESSL MT BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "IBM ESSL MT")
+  endif()
+
+endif ()
+
+
+#BLAS in acml library?
+if (BLA_VENDOR MATCHES "ACML.*" OR BLA_VENDOR STREQUAL "All")
+
+  if( ((BLA_VENDOR STREQUAL "ACML") AND (NOT BLAS_ACML_LIB_DIRS)) OR
+      ((BLA_VENDOR STREQUAL "ACML_MP") AND (NOT BLAS_ACML_MP_LIB_DIRS)) OR
+      ((BLA_VENDOR STREQUAL "ACML_GPU") AND (NOT BLAS_ACML_GPU_LIB_DIRS)))
+
+    # try to find acml in "standard" paths
+    if( WIN32 )
+      file( GLOB _ACML_ROOT "C:/AMD/acml*/ACML-EULA.txt" )
+    else()
+      file( GLOB _ACML_ROOT "/opt/acml*/ACML-EULA.txt" )
+    endif()
+    if( WIN32 )
+      file( GLOB _ACML_GPU_ROOT "C:/AMD/acml*/GPGPUexamples" )
+    else()
+      file( GLOB _ACML_GPU_ROOT "/opt/acml*/GPGPUexamples" )
+    endif()
+    list(GET _ACML_ROOT 0 _ACML_ROOT)
+    list(GET _ACML_GPU_ROOT 0 _ACML_GPU_ROOT)
+
+    if( _ACML_ROOT )
+
+      get_filename_component( _ACML_ROOT ${_ACML_ROOT} PATH )
+      if( SIZEOF_INTEGER EQUAL 8 )
+	set( _ACML_PATH_SUFFIX "_int64" )
+      else()
+	set( _ACML_PATH_SUFFIX "" )
+      endif()
+      if( CMAKE_Fortran_COMPILER_ID STREQUAL "Intel" )
+	set( _ACML_COMPILER32 "ifort32" )
+	set( _ACML_COMPILER64 "ifort64" )
+      elseif( CMAKE_Fortran_COMPILER_ID STREQUAL "SunPro" )
+	set( _ACML_COMPILER32 "sun32" )
+	set( _ACML_COMPILER64 "sun64" )
+      elseif( CMAKE_Fortran_COMPILER_ID STREQUAL "PGI" )
+	set( _ACML_COMPILER32 "pgi32" )
+	if( WIN32 )
+	  set( _ACML_COMPILER64 "win64" )
+	else()
+	  set( _ACML_COMPILER64 "pgi64" )
+	endif()
+      elseif( CMAKE_Fortran_COMPILER_ID STREQUAL "Open64" )
+	# 32 bit builds not supported on Open64 but for code simplicity
+	# We'll just use the same directory twice
+	set( _ACML_COMPILER32 "open64_64" )
+	set( _ACML_COMPILER64 "open64_64" )
+      elseif( CMAKE_Fortran_COMPILER_ID STREQUAL "NAG" )
+	set( _ACML_COMPILER32 "nag32" )
+	set( _ACML_COMPILER64 "nag64" )
+      else()
+	set( _ACML_COMPILER32 "gfortran32" )
+	set( _ACML_COMPILER64 "gfortran64" )
+      endif()
+
+      if( BLA_VENDOR STREQUAL "ACML_MP" )
+	set(_ACML_MP_LIB_DIRS
+	  "${_ACML_ROOT}/${_ACML_COMPILER32}_mp${_ACML_PATH_SUFFIX}/lib"
+	  "${_ACML_ROOT}/${_ACML_COMPILER64}_mp${_ACML_PATH_SUFFIX}/lib" )
+      else()
+	set(_ACML_LIB_DIRS
+	  "${_ACML_ROOT}/${_ACML_COMPILER32}${_ACML_PATH_SUFFIX}/lib"
+	  "${_ACML_ROOT}/${_ACML_COMPILER64}${_ACML_PATH_SUFFIX}/lib" )
+      endif()
+
+    endif(_ACML_ROOT)
+
+  elseif(BLAS_${BLA_VENDOR}_LIB_DIRS)
+
+    set(_${BLA_VENDOR}_LIB_DIRS ${BLAS_${BLA_VENDOR}_LIB_DIRS})
+
+  endif()
+
+  if( BLA_VENDOR STREQUAL "ACML_MP" )
+    foreach( BLAS_ACML_MP_LIB_DIRS ${_ACML_MP_LIB_DIRS})
+      check_fortran_libraries (
+	BLAS_LIBRARIES
+	BLAS
+	sgemm
+	"" "acml_mp;acml_mv" "" ${BLAS_ACML_MP_LIB_DIRS}
+	)
+      if( BLAS_LIBRARIES )
+	break()
+      endif()
+    endforeach()
+  elseif( BLA_VENDOR STREQUAL "ACML_GPU" )
+    foreach( BLAS_ACML_GPU_LIB_DIRS ${_ACML_GPU_LIB_DIRS})
+      check_fortran_libraries (
+	BLAS_LIBRARIES
+	BLAS
+	sgemm
+	"" "acml;acml_mv;CALBLAS" "" ${BLAS_ACML_GPU_LIB_DIRS}
+	)
+      if( BLAS_LIBRARIES )
+	break()
+      endif()
+    endforeach()
+  else()
+    foreach( BLAS_ACML_LIB_DIRS ${_ACML_LIB_DIRS} )
+      check_fortran_libraries (
+	BLAS_LIBRARIES
+	BLAS
+	sgemm
+	"" "acml;acml_mv" "" ${BLAS_ACML_LIB_DIRS}
+	)
+      if( BLAS_LIBRARIES )
+	break()
+      endif()
+    endforeach()
+  endif()
+
+  # Either acml or acml_mp should be in LD_LIBRARY_PATH but not both
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "acml;acml_mv"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for ACML BLAS: found")
+      else()
+	message(STATUS "Looking for ACML BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "acml_mp;acml_mv"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for ACML BLAS: found")
+      else()
+	message(STATUS "Looking for ACML BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      sgemm
+      ""
+      "acml;acml_mv;CALBLAS"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for ACML BLAS: found")
+      else()
+	message(STATUS "Looking for ACML BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "ACML")
+  endif()
+
+endif (BLA_VENDOR MATCHES "ACML.*" OR BLA_VENDOR STREQUAL "All") # ACML
+
+
+# Apple BLAS library?
+if (BLA_VENDOR STREQUAL "Apple" OR BLA_VENDOR STREQUAL "All")
+
+  if(NOT BLAS_LIBRARIES)
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      dgemm
+      ""
+      "Accelerate"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for Apple BLAS: found")
+      else()
+	message(STATUS "Looking for Apple BLAS: not found")
+      endif()
+    endif()
+  endif()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "Apple Accelerate")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "Apple" OR BLA_VENDOR STREQUAL "All")
+
+
+if (BLA_VENDOR STREQUAL "NAS" OR BLA_VENDOR STREQUAL "All")
+
+  if ( NOT BLAS_LIBRARIES )
+    check_fortran_libraries(
+      BLAS_LIBRARIES
+      BLAS
+      dgemm
+      ""
+      "vecLib"
+      ""
+      )
+    if(NOT BLAS_FIND_QUIETLY)
+      if(BLAS_LIBRARIES)
+	message(STATUS "Looking for NAS BLAS: found")
+      else()
+	message(STATUS "Looking for NAS BLAS: not found")
+      endif()
+    endif()
+  endif ()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "NAS")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "NAS" OR BLA_VENDOR STREQUAL "All")
+
+
+# Generic BLAS library?
+if (BLA_VENDOR STREQUAL "Generic" OR BLA_VENDOR STREQUAL "All")
+
+  set(BLAS_SEARCH_LIBS "blas;blas_LINUX;blas_MAC;blas_WINDOWS;refblas")
+  foreach (SEARCH_LIB ${BLAS_SEARCH_LIBS})
+    if (BLAS_LIBRARIES)
+    else ()
+      check_fortran_libraries(
+	BLAS_LIBRARIES
+	BLAS
+	sgemm
+	""
+	"${SEARCH_LIB}"
+	"${LGFORTRAN}"
+	)
+      if(NOT BLAS_FIND_QUIETLY)
+	if(BLAS_LIBRARIES)
+	  message(STATUS "Looking for Generic BLAS: found")
+	else()
+	  message(STATUS "Looking for Generic BLAS: not found")
+	endif()
+      endif()
+    endif()
+  endforeach ()
+
+  if (BLAS_LIBRARIES AND NOT BLAS_VENDOR_FOUND)
+      set (BLAS_VENDOR_FOUND "Netlib or other Generic libblas")
+  endif()
+
+endif (BLA_VENDOR STREQUAL "Generic" OR BLA_VENDOR STREQUAL "All")
+
+
+if(BLA_F95)
+
+  if(BLAS95_LIBRARIES)
+    set(BLAS95_FOUND TRUE)
+  else()
+    set(BLAS95_FOUND FALSE)
+  endif()
+
+  if(NOT BLAS_FIND_QUIETLY)
+    if(BLAS95_FOUND)
+      message(STATUS "A library with BLAS95 API found.")
+      message(STATUS "BLAS_LIBRARIES ${BLAS_LIBRARIES}")
+    else(BLAS95_FOUND)
+      message(WARNING "BLA_VENDOR has been set to ${BLA_VENDOR} but blas 95 libraries could not be found or check of symbols failed."
+	"\nPlease indicate where to find blas libraries. You have three options:\n"
+	"- Option 1: Provide the installation directory of BLAS library with cmake option: -DBLAS_DIR=your/path/to/blas\n"
+	"- Option 2: Provide the directory where to find BLAS libraries with cmake option: -DBLAS_LIBDIR=your/path/to/blas/libs\n"
+	"- Option 3: Update your environment variable (Linux: LD_LIBRARY_PATH, Windows: LIB, Mac: DYLD_LIBRARY_PATH)\n"
+	"\nTo follow libraries detection more precisely you can activate a verbose mode with -DBLAS_VERBOSE=ON at cmake configure."
+	"\nYou could also specify a BLAS vendor to look for by setting -DBLA_VENDOR=blas_vendor_name."
+	"\nList of possible BLAS vendor: Goto, ATLAS PhiPACK, CXML, DXML, SunPerf, SCSL, SGIMATH, IBMESSL, Intel10_32 (intel mkl v10 32 bit),"
+	"Intel10_64lp (intel mkl v10 64 bit, lp thread model, lp64 model), Intel10_64lp_seq (intel mkl v10 64 bit, sequential code, lp64 model),"
+	"Intel( older versions of mkl 32 and 64 bit), ACML, ACML_MP, ACML_GPU, Apple, NAS, Generic")
+      if(BLAS_FIND_REQUIRED)
+	message(FATAL_ERROR
+	  "A required library with BLAS95 API not found. Please specify library location.")
+      else()
+	message(STATUS
+	  "A library with BLAS95 API not found. Please specify library location.")
+      endif()
+    endif(BLAS95_FOUND)
+  endif(NOT BLAS_FIND_QUIETLY)
+
+  set(BLAS_FOUND TRUE)
+  set(BLAS_LIBRARIES "${BLAS95_LIBRARIES}")
+
+else(BLA_F95)
+
+  if(BLAS_LIBRARIES)
     set(BLAS_FOUND TRUE)
   else()
     set(BLAS_FOUND FALSE)
   endif()
 
   if(NOT BLAS_FIND_QUIETLY)
     if(BLAS_FOUND)
       message(STATUS "A library with BLAS API found.")
+      message(STATUS "BLAS_LIBRARIES ${BLAS_LIBRARIES}")
     else(BLAS_FOUND)
+      message(WARNING "BLA_VENDOR has been set to ${BLA_VENDOR} but blas libraries could not be found or check of symbols failed."
+	"\nPlease indicate where to find blas libraries. You have three options:\n"
+	"- Option 1: Provide the installation directory of BLAS library with cmake option: -DBLAS_DIR=your/path/to/blas\n"
+	"- Option 2: Provide the directory where to find BLAS libraries with cmake option: -DBLAS_LIBDIR=your/path/to/blas/libs\n"
+	"- Option 3: Update your environment variable (Linux: LD_LIBRARY_PATH, Windows: LIB, Mac: DYLD_LIBRARY_PATH)\n"
+	"\nTo follow libraries detection more precisely you can activate a verbose mode with -DBLAS_VERBOSE=ON at cmake configure."
+	"\nYou could also specify a BLAS vendor to look for by setting -DBLA_VENDOR=blas_vendor_name."
+	"\nList of possible BLAS vendor: Goto, ATLAS PhiPACK, CXML, DXML, SunPerf, SCSL, SGIMATH, IBMESSL, Intel10_32 (intel mkl v10 32 bit),"
+	"Intel10_64lp (intel mkl v10 64 bit, lp thread model, lp64 model), Intel10_64lp_seq (intel mkl v10 64 bit, sequential code, lp64 model),"
+	"Intel( older versions of mkl 32 and 64 bit), ACML, ACML_MP, ACML_GPU, Apple, NAS, Generic")
       if(BLAS_FIND_REQUIRED)
-        message(FATAL_ERROR "A required library with BLAS API not found. Please specify library location.")
+	message(FATAL_ERROR
+	  "A required library with BLAS API not found. Please specify library location.")
       else()
-        message(STATUS "A library with BLAS API not found. Please specify library location.")
+	message(STATUS
+	  "A library with BLAS API not found. Please specify library location.")
       endif()
     endif(BLAS_FOUND)
   endif(NOT BLAS_FIND_QUIETLY)
 
-  # Add variables to cache
-  set( BLAS_INCLUDE_DIR   "${BLAS_INCLUDE_DIR}"
-                          CACHE PATH "Directories containing the BLAS header files" FORCE )
-  set( BLAS_DEFINITIONS   "${BLAS_DEFINITIONS}"
-                          CACHE STRING "Compilation options to use BLAS" FORCE )
-  set( BLAS_LINKER_FLAGS  "${BLAS_LINKER_FLAGS}"
-                          CACHE STRING "Linker flags to use BLAS" FORCE )
-  set( BLAS_LIBRARIES     "${BLAS_LIBRARIES}"
-                          CACHE FILEPATH "BLAS libraries name" FORCE )
-  set( BLAS_LIBRARIES_DIR "${BLAS_LIBRARIES_DIR}"
-                          CACHE PATH "Directories containing the BLAS libraries" FORCE )
-
-  #message("DEBUG: BLAS_INCLUDE_DIR = ${BLAS_INCLUDE_DIR}")
-  #message("DEBUG: BLAS_DEFINITIONS = ${BLAS_DEFINITIONS}")
-  #message("DEBUG: BLAS_LINKER_FLAGS = ${BLAS_LINKER_FLAGS}")
-  #message("DEBUG: BLAS_LIBRARIES = ${BLAS_LIBRARIES}")
-  #message("DEBUG: BLAS_LIBRARIES_DIR = ${BLAS_LIBRARIES_DIR}")
-  #message("DEBUG: BLAS_FOUND = ${BLAS_FOUND}")
-
-endif(BLAS_LIBRARIES_DIR OR BLAS_LIBRARIES)
+endif(BLA_F95)
+
+set(CMAKE_FIND_LIBRARY_SUFFIXES ${_blas_ORIG_CMAKE_FIND_LIBRARY_SUFFIXES})
+
+if (BLAS_FOUND)
+  list(GET BLAS_LIBRARIES 0 first_lib)
+  get_filename_component(first_lib_path "${first_lib}" PATH)
+  if (${first_lib_path} MATCHES "(/lib(32|64)?$)|(/lib/intel64$|/lib/ia32$)")
+    string(REGEX REPLACE "(/lib(32|64)?$)|(/lib/intel64$|/lib/ia32$)" "" not_cached_dir "${first_lib_path}")
+    set(BLAS_DIR_FOUND "${not_cached_dir}" CACHE PATH "Installation directory of BLAS library" FORCE)
+  else()
+    set(BLAS_DIR_FOUND "${first_lib_path}" CACHE PATH "Installation directory of BLAS library" FORCE)
+  endif()
+endif()
+mark_as_advanced(BLAS_DIR)
+mark_as_advanced(BLAS_DIR_FOUND)

ADDED   3rd_party/eigen/cmake/FindBLASEXT.cmake
Index: 3rd_party/eigen/cmake/FindBLASEXT.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindBLASEXT.cmake
+++ 3rd_party/eigen/cmake/FindBLASEXT.cmake
@@ -0,0 +1,380 @@
+###
+#
+# @copyright (c) 2009-2014 The University of Tennessee and The University
+#                          of Tennessee Research Foundation.
+#                          All rights reserved.
+# @copyright (c) 2012-2016 Inria. All rights reserved.
+# @copyright (c) 2012-2014 Bordeaux INP, CNRS (LaBRI UMR 5800), Inria, Univ. Bordeaux. All rights reserved.
+#
+###
+#
+# - Find BLAS EXTENDED for MORSE projects: find include dirs and libraries
+#
+# This module allows to find BLAS libraries by calling the official FindBLAS module
+# and handles the creation of different library lists whether the user wishes to link
+# with a sequential BLAS or a multihreaded (BLAS_SEQ_LIBRARIES and BLAS_PAR_LIBRARIES).
+# BLAS is detected with a FindBLAS call then if the BLAS vendor is Intel10_64lp, ACML
+# or IBMESSLMT then the module attempts to find the corresponding multithreaded libraries.
+#
+# The following variables have been added to manage links with sequential or multithreaded
+# versions:
+#  BLAS_INCLUDE_DIRS  - BLAS include directories
+#  BLAS_LIBRARY_DIRS  - Link directories for BLAS libraries
+#  BLAS_SEQ_LIBRARIES - BLAS component libraries to be linked (sequential)
+#  BLAS_PAR_LIBRARIES - BLAS component libraries to be linked (multithreaded)
+
+#=============================================================================
+# Copyright 2012-2013 Inria
+# Copyright 2012-2013 Emmanuel Agullo
+# Copyright 2012-2013 Mathieu Faverge
+# Copyright 2012      Cedric Castagnede
+# Copyright 2013-2016 Florent Pruvost
+#
+# Distributed under the OSI-approved BSD License (the "License");
+# see accompanying file MORSE-Copyright.txt for details.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without even the
+# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the License for more information.
+#=============================================================================
+# (To distribute this file outside of Morse, substitute the full
+#  License text for the above reference.)
+
+# macro to factorize this call
+macro(find_package_blas)
+  if(BLASEXT_FIND_REQUIRED)
+    if(BLASEXT_FIND_QUIETLY)
+      find_package(BLAS REQUIRED QUIET)
+    else()
+      find_package(BLAS REQUIRED)
+    endif()
+  else()
+    if(BLASEXT_FIND_QUIETLY)
+      find_package(BLAS QUIET)
+    else()
+      find_package(BLAS)
+    endif()
+  endif()
+endmacro()
+
+# add a cache variable to let the user specify the BLAS vendor
+set(BLA_VENDOR "" CACHE STRING "list of possible BLAS vendor:
+    Open, Eigen, Goto, ATLAS PhiPACK, CXML, DXML, SunPerf, SCSL, SGIMATH, IBMESSL, IBMESSLMT,
+    Intel10_32 (intel mkl v10 32 bit),
+    Intel10_64lp (intel mkl v10 64 bit, lp thread model, lp64 model),
+    Intel10_64lp_seq (intel mkl v10 64 bit, sequential code, lp64 model),
+    Intel( older versions of mkl 32 and 64 bit),
+    ACML, ACML_MP, ACML_GPU, Apple, NAS, Generic")
+
+if(NOT BLASEXT_FIND_QUIETLY)
+  message(STATUS "In FindBLASEXT")
+  message(STATUS "If you want to force the use of one specific library, "
+    "\n   please specify the BLAS vendor by setting -DBLA_VENDOR=blas_vendor_name"
+    "\n   at cmake configure.")
+  message(STATUS "List of possible BLAS vendor: Goto, ATLAS PhiPACK, CXML, "
+    "\n   DXML, SunPerf, SCSL, SGIMATH, IBMESSL, IBMESSLMT, Intel10_32 (intel mkl v10 32 bit),"
+    "\n   Intel10_64lp (intel mkl v10 64 bit, lp thread model, lp64 model),"
+    "\n   Intel10_64lp_seq (intel mkl v10 64 bit, sequential code, lp64 model),"
+    "\n   Intel( older versions of mkl 32 and 64 bit),"
+    "\n   ACML, ACML_MP, ACML_GPU, Apple, NAS, Generic")
+endif()
+
+if (NOT BLAS_FOUND)
+  # First try to detect two cases:
+  # 1: only SEQ libs are handled
+  # 2: both SEQ and PAR libs are handled
+  find_package_blas()
+endif ()
+
+# detect the cases where SEQ and PAR libs are handled
+if(BLA_VENDOR STREQUAL "All" AND
+    (BLAS_mkl_core_LIBRARY OR BLAS_mkl_core_dll_LIBRARY)
+    )
+  set(BLA_VENDOR "Intel")
+  if(BLAS_mkl_intel_LIBRARY)
+    set(BLA_VENDOR "Intel10_32")
+  endif()
+  if(BLAS_mkl_intel_lp64_LIBRARY)
+    set(BLA_VENDOR "Intel10_64lp")
+  endif()
+  if(NOT BLASEXT_FIND_QUIETLY)
+    message(STATUS "A BLAS library has been found (${BLAS_LIBRARIES}) but we"
+      "\n   have also potentially detected some multithreaded BLAS libraries from the MKL."
+      "\n   We try to find both libraries lists (Sequential/Multithreaded).")
+  endif()
+  set(BLAS_FOUND "")
+elseif(BLA_VENDOR STREQUAL "All" AND BLAS_acml_LIBRARY)
+  set(BLA_VENDOR "ACML")
+  if(NOT BLASEXT_FIND_QUIETLY)
+    message(STATUS "A BLAS library has been found (${BLAS_LIBRARIES}) but we"
+      "\n   have also potentially detected some multithreaded BLAS libraries from the ACML."
+      "\n   We try to find both libraries lists (Sequential/Multithreaded).")
+  endif()
+  set(BLAS_FOUND "")
+elseif(BLA_VENDOR STREQUAL "All" AND BLAS_essl_LIBRARY)
+  set(BLA_VENDOR "IBMESSL")
+  if(NOT BLASEXT_FIND_QUIETLY)
+    message(STATUS "A BLAS library has been found (${BLAS_LIBRARIES}) but we"
+      "\n   have also potentially detected some multithreaded BLAS libraries from the ESSL."
+      "\n   We try to find both libraries lists (Sequential/Multithreaded).")
+  endif()
+  set(BLAS_FOUND "")
+endif()
+
+# Intel case
+if(BLA_VENDOR MATCHES "Intel*")
+
+  ###
+  # look for include path if the BLAS vendor is Intel
+  ###
+
+  # gather system include paths
+  unset(_inc_env)
+  if(WIN32)
+    string(REPLACE ":" ";" _inc_env "$ENV{INCLUDE}")
+  else()
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{C_INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{CPATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+  endif()
+  list(APPEND _inc_env "${CMAKE_PLATFORM_IMPLICIT_INCLUDE_DIRECTORIES}")
+  list(APPEND _inc_env "${CMAKE_C_IMPLICIT_INCLUDE_DIRECTORIES}")
+  set(ENV_MKLROOT "$ENV{MKLROOT}")
+  if (ENV_MKLROOT)
+    list(APPEND _inc_env "${ENV_MKLROOT}/include")
+  endif()
+  list(REMOVE_DUPLICATES _inc_env)
+
+  # find mkl.h inside known include paths
+  set(BLAS_mkl.h_INCLUDE_DIRS "BLAS_mkl.h_INCLUDE_DIRS-NOTFOUND")
+  if(BLAS_INCDIR)
+    set(BLAS_mkl.h_INCLUDE_DIRS "BLAS_mkl.h_INCLUDE_DIRS-NOTFOUND")
+    find_path(BLAS_mkl.h_INCLUDE_DIRS
+      NAMES mkl.h
+      HINTS ${BLAS_INCDIR})
+  else()
+    if(BLAS_DIR)
+      set(BLAS_mkl.h_INCLUDE_DIRS "BLAS_mkl.h_INCLUDE_DIRS-NOTFOUND")
+      find_path(BLAS_mkl.h_INCLUDE_DIRS
+	NAMES mkl.h
+	HINTS ${BLAS_DIR}
+	PATH_SUFFIXES include)
+    else()
+      set(BLAS_mkl.h_INCLUDE_DIRS "BLAS_mkl.h_INCLUDE_DIRS-NOTFOUND")
+      find_path(BLAS_mkl.h_INCLUDE_DIRS
+	NAMES mkl.h
+	HINTS ${_inc_env})
+    endif()
+  endif()
+  mark_as_advanced(BLAS_mkl.h_INCLUDE_DIRS)
+  ## Print status if not found
+  ## -------------------------
+  #if (NOT BLAS_mkl.h_INCLUDE_DIRS AND MORSE_VERBOSE)
+  #    Print_Find_Header_Status(blas mkl.h)
+  #endif ()
+  set(BLAS_INCLUDE_DIRS "")
+  if(BLAS_mkl.h_INCLUDE_DIRS)
+    list(APPEND BLAS_INCLUDE_DIRS "${BLAS_mkl.h_INCLUDE_DIRS}" )
+  endif()
+
+  ###
+  # look for libs
+  ###
+  # if Intel 10 64 bit -> look for sequential and multithreaded versions
+  if(BLA_VENDOR MATCHES "Intel10_64lp*")
+
+    ## look for the sequential version
+    set(BLA_VENDOR "Intel10_64lp_seq")
+    if(NOT BLASEXT_FIND_QUIETLY)
+      message(STATUS "Look for the sequential version Intel10_64lp_seq")
+    endif()
+    find_package_blas()
+    if(BLAS_FOUND)
+      set(BLAS_SEQ_LIBRARIES "${BLAS_LIBRARIES}")
+    else()
+      set(BLAS_SEQ_LIBRARIES "${BLAS_SEQ_LIBRARIES-NOTFOUND}")
+    endif()
+
+    ## look for the multithreaded version
+    set(BLA_VENDOR "Intel10_64lp")
+    if(NOT BLASEXT_FIND_QUIETLY)
+      message(STATUS "Look for the multithreaded version Intel10_64lp")
+    endif()
+    find_package_blas()
+    if(BLAS_FOUND)
+      set(BLAS_PAR_LIBRARIES "${BLAS_LIBRARIES}")
+    else()
+      set(BLAS_PAR_LIBRARIES "${BLAS_PAR_LIBRARIES-NOTFOUND}")
+    endif()
+
+  else()
+
+    if(BLAS_FOUND)
+      set(BLAS_SEQ_LIBRARIES "${BLAS_LIBRARIES}")
+    else()
+      set(BLAS_SEQ_LIBRARIES "${BLAS_SEQ_LIBRARIES-NOTFOUND}")
+    endif()
+
+  endif()
+
+  # ACML case
+elseif(BLA_VENDOR MATCHES "ACML*")
+
+  ## look for the sequential version
+  set(BLA_VENDOR "ACML")
+  find_package_blas()
+  if(BLAS_FOUND)
+    set(BLAS_SEQ_LIBRARIES "${BLAS_LIBRARIES}")
+  else()
+    set(BLAS_SEQ_LIBRARIES "${BLAS_SEQ_LIBRARIES-NOTFOUND}")
+  endif()
+
+  ## look for the multithreaded version
+  set(BLA_VENDOR "ACML_MP")
+  find_package_blas()
+  if(BLAS_FOUND)
+    set(BLAS_PAR_LIBRARIES "${BLAS_LIBRARIES}")
+  else()
+    set(BLAS_PAR_LIBRARIES "${BLAS_PAR_LIBRARIES-NOTFOUND}")
+  endif()
+
+  # IBMESSL case
+elseif(BLA_VENDOR MATCHES "IBMESSL*")
+
+  ## look for the sequential version
+  set(BLA_VENDOR "IBMESSL")
+  find_package_blas()
+  if(BLAS_FOUND)
+    set(BLAS_SEQ_LIBRARIES "${BLAS_LIBRARIES}")
+  else()
+    set(BLAS_SEQ_LIBRARIES "${BLAS_SEQ_LIBRARIES-NOTFOUND}")
+  endif()
+
+  ## look for the multithreaded version
+  set(BLA_VENDOR "IBMESSLMT")
+  find_package_blas()
+  if(BLAS_FOUND)
+    set(BLAS_PAR_LIBRARIES "${BLAS_LIBRARIES}")
+  else()
+    set(BLAS_PAR_LIBRARIES "${BLAS_PAR_LIBRARIES-NOTFOUND}")
+  endif()
+
+else()
+
+  if(BLAS_FOUND)
+    # define the SEQ libs as the BLAS_LIBRARIES
+    set(BLAS_SEQ_LIBRARIES "${BLAS_LIBRARIES}")
+  else()
+    set(BLAS_SEQ_LIBRARIES "${BLAS_SEQ_LIBRARIES-NOTFOUND}")
+  endif()
+  set(BLAS_PAR_LIBRARIES "${BLAS_PAR_LIBRARIES-NOTFOUND}")
+
+endif()
+
+
+if(BLAS_SEQ_LIBRARIES)
+  set(BLAS_LIBRARIES "${BLAS_SEQ_LIBRARIES}")
+endif()
+
+# extract libs paths
+# remark: because it is not given by find_package(BLAS)
+set(BLAS_LIBRARY_DIRS "")
+string(REPLACE " " ";" BLAS_LIBRARIES "${BLAS_LIBRARIES}")
+foreach(blas_lib ${BLAS_LIBRARIES})
+  if (EXISTS "${blas_lib}")
+    get_filename_component(a_blas_lib_dir "${blas_lib}" PATH)
+    list(APPEND BLAS_LIBRARY_DIRS "${a_blas_lib_dir}" )
+  else()
+    string(REPLACE "-L" "" blas_lib "${blas_lib}")
+    if (EXISTS "${blas_lib}")
+      list(APPEND BLAS_LIBRARY_DIRS "${blas_lib}" )
+    else()
+      get_filename_component(a_blas_lib_dir "${blas_lib}" PATH)
+      if (EXISTS "${a_blas_lib_dir}")
+	list(APPEND BLAS_LIBRARY_DIRS "${a_blas_lib_dir}" )
+      endif()
+    endif()
+  endif()
+endforeach()
+if (BLAS_LIBRARY_DIRS)
+  list(REMOVE_DUPLICATES BLAS_LIBRARY_DIRS)
+endif ()
+
+# check that BLAS has been found
+# ---------------------------------
+include(FindPackageHandleStandardArgs)
+if(BLA_VENDOR MATCHES "Intel*")
+  if(BLA_VENDOR MATCHES "Intel10_64lp*")
+    if(NOT BLASEXT_FIND_QUIETLY)
+      message(STATUS "BLAS found is Intel MKL:"
+	"\n   we manage two lists of libs, one sequential and one parallel if found"
+	"\n   (see BLAS_SEQ_LIBRARIES and BLAS_PAR_LIBRARIES)")
+      message(STATUS "BLAS sequential libraries stored in BLAS_SEQ_LIBRARIES")
+    endif()
+    find_package_handle_standard_args(BLAS DEFAULT_MSG
+      BLAS_SEQ_LIBRARIES
+      BLAS_LIBRARY_DIRS
+      BLAS_INCLUDE_DIRS)
+    if(BLAS_PAR_LIBRARIES)
+      if(NOT BLASEXT_FIND_QUIETLY)
+	message(STATUS "BLAS parallel libraries stored in BLAS_PAR_LIBRARIES")
+      endif()
+      find_package_handle_standard_args(BLAS DEFAULT_MSG
+	BLAS_PAR_LIBRARIES)
+    endif()
+  else()
+    if(NOT BLASEXT_FIND_QUIETLY)
+      message(STATUS "BLAS sequential libraries stored in BLAS_SEQ_LIBRARIES")
+    endif()
+    find_package_handle_standard_args(BLAS DEFAULT_MSG
+      BLAS_SEQ_LIBRARIES
+      BLAS_LIBRARY_DIRS
+      BLAS_INCLUDE_DIRS)
+  endif()
+elseif(BLA_VENDOR MATCHES "ACML*")
+  if(NOT BLASEXT_FIND_QUIETLY)
+    message(STATUS "BLAS found is ACML:"
+      "\n   we manage two lists of libs, one sequential and one parallel if found"
+      "\n   (see BLAS_SEQ_LIBRARIES and BLAS_PAR_LIBRARIES)")
+    message(STATUS "BLAS sequential libraries stored in BLAS_SEQ_LIBRARIES")
+  endif()
+  find_package_handle_standard_args(BLAS DEFAULT_MSG
+    BLAS_SEQ_LIBRARIES
+    BLAS_LIBRARY_DIRS)
+  if(BLAS_PAR_LIBRARIES)
+    if(NOT BLASEXT_FIND_QUIETLY)
+      message(STATUS "BLAS parallel libraries stored in BLAS_PAR_LIBRARIES")
+    endif()
+    find_package_handle_standard_args(BLAS DEFAULT_MSG
+      BLAS_PAR_LIBRARIES)
+  endif()
+elseif(BLA_VENDOR MATCHES "IBMESSL*")
+  if(NOT BLASEXT_FIND_QUIETLY)
+    message(STATUS "BLAS found is ESSL:"
+      "\n   we manage two lists of libs, one sequential and one parallel if found"
+      "\n   (see BLAS_SEQ_LIBRARIES and BLAS_PAR_LIBRARIES)")
+    message(STATUS "BLAS sequential libraries stored in BLAS_SEQ_LIBRARIES")
+  endif()
+  find_package_handle_standard_args(BLAS DEFAULT_MSG
+    BLAS_SEQ_LIBRARIES
+    BLAS_LIBRARY_DIRS)
+  if(BLAS_PAR_LIBRARIES)
+    if(NOT BLASEXT_FIND_QUIETLY)
+      message(STATUS "BLAS parallel libraries stored in BLAS_PAR_LIBRARIES")
+    endif()
+    find_package_handle_standard_args(BLAS DEFAULT_MSG
+      BLAS_PAR_LIBRARIES)
+  endif()
+else()
+  if(NOT BLASEXT_FIND_QUIETLY)
+    message(STATUS "BLAS sequential libraries stored in BLAS_SEQ_LIBRARIES")
+  endif()
+  find_package_handle_standard_args(BLAS DEFAULT_MSG
+    BLAS_SEQ_LIBRARIES
+    BLAS_LIBRARY_DIRS)
+endif()

ADDED   3rd_party/eigen/cmake/FindComputeCpp.cmake
Index: 3rd_party/eigen/cmake/FindComputeCpp.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindComputeCpp.cmake
+++ 3rd_party/eigen/cmake/FindComputeCpp.cmake
@@ -0,0 +1,245 @@
+#.rst:
+# FindComputeCpp
+#---------------
+#
+#   Copyright 2016 Codeplay Software Ltd.
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use these files except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+
+#########################
+#  FindComputeCpp.cmake
+#########################
+#
+#  Tools for finding and building with ComputeCpp.
+#
+#  User must define COMPUTECPP_PACKAGE_ROOT_DIR pointing to the ComputeCpp
+#   installation.
+#
+#  Latest version of this file can be found at:
+#    https://github.com/codeplaysoftware/computecpp-sdk
+
+# Require CMake version 3.2.2 or higher
+cmake_minimum_required(VERSION 3.2.2)
+
+# Check that a supported host compiler can be found
+if(CMAKE_COMPILER_IS_GNUCXX)
+    # Require at least gcc 4.8
+    if (CMAKE_CXX_COMPILER_VERSION VERSION_LESS 4.8)
+      message(FATAL_ERROR
+        "host compiler - Not found! (gcc version must be at least 4.8)")
+    # Require the GCC dual ABI to be disabled for 5.1 or higher
+    elseif (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 5.1)
+      set(COMPUTECPP_DISABLE_GCC_DUAL_ABI "True")
+      message(STATUS
+        "host compiler - gcc ${CMAKE_CXX_COMPILER_VERSION} (note pre 5.1 gcc ABI enabled)")
+    else()
+      message(STATUS "host compiler - gcc ${CMAKE_CXX_COMPILER_VERSION}")
+    endif()
+elseif ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang")
+    # Require at least clang 3.6
+    if (${CMAKE_CXX_COMPILER_VERSION} VERSION_LESS 3.6)
+      message(FATAL_ERROR
+        "host compiler - Not found! (clang version must be at least 3.6)")
+    else()
+      message(STATUS "host compiler - clang ${CMAKE_CXX_COMPILER_VERSION}")
+    endif()
+else()
+  message(WARNING
+    "host compiler - Not found! (ComputeCpp supports GCC and Clang, see readme)")
+endif()
+
+set(COMPUTECPP_64_BIT_DEFAULT ON)
+option(COMPUTECPP_64_BIT_CODE "Compile device code in 64 bit mode"
+        ${COMPUTECPP_64_BIT_DEFAULT})
+mark_as_advanced(COMPUTECPP_64_BIT_CODE)
+
+# Find OpenCL package
+find_package(OpenCL REQUIRED)
+
+# Find ComputeCpp packagee
+if(NOT COMPUTECPP_PACKAGE_ROOT_DIR)
+  message(FATAL_ERROR
+    "ComputeCpp package - Not found! (please set COMPUTECPP_PACKAGE_ROOT_DIR")
+else()
+  message(STATUS "ComputeCpp package - Found")
+endif()
+option(COMPUTECPP_PACKAGE_ROOT_DIR "Path to the ComputeCpp Package")
+
+# Obtain the path to compute++
+find_program(COMPUTECPP_DEVICE_COMPILER compute++ PATHS
+  ${COMPUTECPP_PACKAGE_ROOT_DIR} PATH_SUFFIXES bin)
+if (EXISTS ${COMPUTECPP_DEVICE_COMPILER})
+  mark_as_advanced(COMPUTECPP_DEVICE_COMPILER)
+  message(STATUS "compute++ - Found")
+else()
+  message(FATAL_ERROR "compute++ - Not found! (${COMPUTECPP_DEVICE_COMPILER})")
+endif()
+
+# Obtain the path to computecpp_info
+find_program(COMPUTECPP_INFO_TOOL computecpp_info PATHS
+  ${COMPUTECPP_PACKAGE_ROOT_DIR} PATH_SUFFIXES bin)
+if (EXISTS ${COMPUTECPP_INFO_TOOL})
+  mark_as_advanced(${COMPUTECPP_INFO_TOOL})
+  message(STATUS "computecpp_info - Found")
+else()
+  message(FATAL_ERROR "computecpp_info - Not found! (${COMPUTECPP_INFO_TOOL})")
+endif()
+
+# Obtain the path to the ComputeCpp runtime library
+find_library(COMPUTECPP_RUNTIME_LIBRARY ComputeCpp PATHS ${COMPUTECPP_PACKAGE_ROOT_DIR}
+  HINTS ${COMPUTECPP_PACKAGE_ROOT_DIR}/lib PATH_SUFFIXES lib
+  DOC "ComputeCpp Runtime Library" NO_DEFAULT_PATH)
+
+if (EXISTS ${COMPUTECPP_RUNTIME_LIBRARY})
+  mark_as_advanced(COMPUTECPP_RUNTIME_LIBRARY)
+  message(STATUS "libComputeCpp.so - Found")
+else()
+  message(FATAL_ERROR "libComputeCpp.so - Not found!")
+endif()
+
+# Obtain the ComputeCpp include directory
+set(COMPUTECPP_INCLUDE_DIRECTORY ${COMPUTECPP_PACKAGE_ROOT_DIR}/include/)
+if (NOT EXISTS ${COMPUTECPP_INCLUDE_DIRECTORY})
+  message(FATAL_ERROR "ComputeCpp includes - Not found!")
+else()
+  message(STATUS "ComputeCpp includes - Found")
+endif()
+
+# Obtain the package version
+execute_process(COMMAND ${COMPUTECPP_INFO_TOOL} "--dump-version"
+  OUTPUT_VARIABLE COMPUTECPP_PACKAGE_VERSION
+  RESULT_VARIABLE COMPUTECPP_INFO_TOOL_RESULT OUTPUT_STRIP_TRAILING_WHITESPACE)
+if(NOT COMPUTECPP_INFO_TOOL_RESULT EQUAL "0")
+  message(FATAL_ERROR "Package version - Error obtaining version!")
+else()
+  mark_as_advanced(COMPUTECPP_PACKAGE_VERSION)
+  message(STATUS "Package version - ${COMPUTECPP_PACKAGE_VERSION}")
+endif()
+
+# Obtain the device compiler flags
+execute_process(COMMAND ${COMPUTECPP_INFO_TOOL} "--dump-device-compiler-flags"
+  OUTPUT_VARIABLE COMPUTECPP_DEVICE_COMPILER_FLAGS
+  RESULT_VARIABLE COMPUTECPP_INFO_TOOL_RESULT OUTPUT_STRIP_TRAILING_WHITESPACE)
+if(NOT COMPUTECPP_INFO_TOOL_RESULT EQUAL "0")
+  message(FATAL_ERROR "compute++ flags - Error obtaining compute++ flags!")
+else()
+  mark_as_advanced(COMPUTECPP_COMPILER_FLAGS)
+  message(STATUS "compute++ flags - ${COMPUTECPP_DEVICE_COMPILER_FLAGS}")
+endif()
+
+set(COMPUTECPP_DEVICE_COMPILER_FLAGS ${COMPUTECPP_DEVICE_COMPILER_FLAGS} -sycl-compress-name -no-serial-memop -DEIGEN_NO_ASSERTION_CHECKING=1)
+
+# Check if the platform is supported
+execute_process(COMMAND ${COMPUTECPP_INFO_TOOL} "--dump-is-supported"
+  OUTPUT_VARIABLE COMPUTECPP_PLATFORM_IS_SUPPORTED
+  RESULT_VARIABLE COMPUTECPP_INFO_TOOL_RESULT OUTPUT_STRIP_TRAILING_WHITESPACE)
+if(NOT COMPUTECPP_INFO_TOOL_RESULT EQUAL "0")
+  message(FATAL_ERROR "platform - Error checking platform support!")
+else()
+  mark_as_advanced(COMPUTECPP_PLATFORM_IS_SUPPORTED)
+  if (COMPUTECPP_PLATFORM_IS_SUPPORTED)
+    message(STATUS "platform - your system can support ComputeCpp")
+  else()
+    message(STATUS "platform - your system CANNOT support ComputeCpp")
+  endif()
+endif()
+
+####################
+#   __build_sycl
+####################
+#
+#  Adds a custom target for running compute++ and adding a dependency for the
+#  resulting integration header.
+#
+#  targetName : Name of the target.
+#  sourceFile : Source file to be compiled.
+#  binaryDir : Intermediate directory to output the integration header.
+#
+function(__build_spir targetName sourceFile binaryDir)
+
+  # Retrieve source file name.
+  get_filename_component(sourceFileName ${sourceFile} NAME)
+
+  # Set the path to the Sycl file.
+  set(outputSyclFile ${binaryDir}/${sourceFileName}.sycl)
+
+  # Add any user-defined include to the device compiler
+  get_property(includeDirectories DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} PROPERTY
+    INCLUDE_DIRECTORIES)
+  set(device_compiler_includes "")
+  foreach(directory ${includeDirectories})
+    set(device_compiler_includes "-I${directory}" ${device_compiler_includes})
+  endforeach()
+  if (CMAKE_INCLUDE_PATH)
+    foreach(directory ${CMAKE_INCLUDE_PATH})
+      set(device_compiler_includes "-I${directory}"
+        ${device_compiler_includes})
+    endforeach()
+  endif()
+
+  # Convert argument list format
+  separate_arguments(COMPUTECPP_DEVICE_COMPILER_FLAGS)
+
+  # Add custom command for running compute++
+  add_custom_command(
+    OUTPUT ${outputSyclFile}
+    COMMAND ${COMPUTECPP_DEVICE_COMPILER}
+            ${COMPUTECPP_DEVICE_COMPILER_FLAGS}
+            -isystem ${COMPUTECPP_INCLUDE_DIRECTORY}
+            ${COMPUTECPP_PLATFORM_SPECIFIC_ARGS}
+            ${device_compiler_includes}
+            -o ${outputSyclFile}
+            -c ${CMAKE_CURRENT_SOURCE_DIR}/${sourceFile}
+    DEPENDS ${sourceFile}
+    WORKING_DIRECTORY ${binaryDir}
+  COMMENT "Building ComputeCpp integration header file ${outputSyclFile}")
+
+  # Add a custom target for the generated integration header
+  add_custom_target(${targetName}_integration_header DEPENDS ${outputSyclFile})
+
+  # Add a dependency on the integration header
+  add_dependencies(${targetName} ${targetName}_integration_header)
+
+  # Set the host compiler C++ standard to C++11
+  set_property(TARGET ${targetName} PROPERTY CXX_STANDARD 11)
+
+  # Disable GCC dual ABI on GCC 5.1 and higher
+  if(COMPUTECPP_DISABLE_GCC_DUAL_ABI)
+    set_property(TARGET ${targetName} APPEND PROPERTY COMPILE_DEFINITIONS
+      "_GLIBCXX_USE_CXX11_ABI=0")
+  endif()
+
+endfunction()
+
+#######################
+#  add_sycl_to_target
+#######################
+#
+#  Adds a SYCL compilation custom command associated with an existing
+#  target and sets a dependancy on that new command.
+#
+#  targetName : Name of the target to add a SYCL to.
+#  sourceFile : Source file to be compiled for SYCL.
+#  binaryDir : Intermediate directory to output the integration header.
+#
+function(add_sycl_to_target targetName sourceFile binaryDir)
+
+  # Add custom target to run compute++ and generate the integration header
+  __build_spir(${targetName} ${sourceFile} ${binaryDir})
+
+  # Link with the ComputeCpp runtime library
+  target_link_libraries(${targetName} PUBLIC ${COMPUTECPP_RUNTIME_LIBRARY}
+                        PUBLIC ${OpenCL_LIBRARIES})
+
+endfunction(add_sycl_to_target)

Index: 3rd_party/eigen/cmake/FindEigen3.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindEigen3.cmake
+++ 3rd_party/eigen/cmake/FindEigen3.cmake
@@ -7,10 +7,16 @@
 # Once done this will define
 #
 #  EIGEN3_FOUND - system has eigen lib with correct version
 #  EIGEN3_INCLUDE_DIR - the eigen include directory
 #  EIGEN3_VERSION - eigen version
+#
+# This module reads hints about search locations from 
+# the following enviroment variables:
+#
+# EIGEN3_ROOT
+# EIGEN3_ROOT_DIR
 
 # Copyright (c) 2006, 2007 Montel Laurent, <montel@kde.org>
 # Copyright (c) 2008, 2009 Gael Guennebaud, <g.gael@free.fr>
 # Copyright (c) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 # Redistribution and use is allowed according to the terms of the 2-clause BSD license.
@@ -58,17 +64,27 @@
   # in cache already
   _eigen3_check_version()
   set(EIGEN3_FOUND ${EIGEN3_VERSION_OK})
 
 else (EIGEN3_INCLUDE_DIR)
+  
+  # search first if an Eigen3Config.cmake is available in the system,
+  # if successful this would set EIGEN3_INCLUDE_DIR and the rest of
+  # the script will work as usual
+  find_package(Eigen3 ${Eigen3_FIND_VERSION} NO_MODULE QUIET)
 
-  find_path(EIGEN3_INCLUDE_DIR NAMES signature_of_eigen3_matrix_library
-      PATHS
-      ${CMAKE_INSTALL_PREFIX}/include
-      ${KDE4_INCLUDE_DIR}
-      PATH_SUFFIXES eigen3 eigen
-    )
+  if(NOT EIGEN3_INCLUDE_DIR)
+    find_path(EIGEN3_INCLUDE_DIR NAMES signature_of_eigen3_matrix_library
+        HINTS
+        ENV EIGEN3_ROOT 
+        ENV EIGEN3_ROOT_DIR
+        PATHS
+        ${CMAKE_INSTALL_PREFIX}/include
+        ${KDE4_INCLUDE_DIR}
+        PATH_SUFFIXES eigen3 eigen
+      )
+  endif(NOT EIGEN3_INCLUDE_DIR)
 
   if(EIGEN3_INCLUDE_DIR)
     _eigen3_check_version()
   endif(EIGEN3_INCLUDE_DIR)
 

ADDED   3rd_party/eigen/cmake/FindHWLOC.cmake
Index: 3rd_party/eigen/cmake/FindHWLOC.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindHWLOC.cmake
+++ 3rd_party/eigen/cmake/FindHWLOC.cmake
@@ -0,0 +1,331 @@
+###
+#
+# @copyright (c) 2009-2014 The University of Tennessee and The University
+#                          of Tennessee Research Foundation.
+#                          All rights reserved.
+# @copyright (c) 2012-2014 Inria. All rights reserved.
+# @copyright (c) 2012-2014 Bordeaux INP, CNRS (LaBRI UMR 5800), Inria, Univ. Bordeaux. All rights reserved.
+#
+###
+#
+# - Find HWLOC include dirs and libraries
+# Use this module by invoking find_package with the form:
+#  find_package(HWLOC
+#               [REQUIRED]) # Fail with error if hwloc is not found
+#
+# This module finds headers and hwloc library.
+# Results are reported in variables:
+#  HWLOC_FOUND           - True if headers and requested libraries were found
+#  HWLOC_INCLUDE_DIRS    - hwloc include directories
+#  HWLOC_LIBRARY_DIRS    - Link directories for hwloc libraries
+#  HWLOC_LIBRARIES       - hwloc component libraries to be linked
+#
+# The user can give specific paths where to find the libraries adding cmake
+# options at configure (ex: cmake path/to/project -DHWLOC_DIR=path/to/hwloc):
+#  HWLOC_DIR             - Where to find the base directory of hwloc
+#  HWLOC_INCDIR          - Where to find the header files
+#  HWLOC_LIBDIR          - Where to find the library files
+# The module can also look for the following environment variables if paths
+# are not given as cmake variable: HWLOC_DIR, HWLOC_INCDIR, HWLOC_LIBDIR
+
+#=============================================================================
+# Copyright 2012-2013 Inria
+# Copyright 2012-2013 Emmanuel Agullo
+# Copyright 2012-2013 Mathieu Faverge
+# Copyright 2012      Cedric Castagnede
+# Copyright 2013      Florent Pruvost
+#
+# Distributed under the OSI-approved BSD License (the "License");
+# see accompanying file MORSE-Copyright.txt for details.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without even the
+# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the License for more information.
+#=============================================================================
+# (To distribute this file outside of Morse, substitute the full
+#  License text for the above reference.)
+
+include(CheckStructHasMember)
+include(CheckCSourceCompiles)
+
+if (NOT HWLOC_FOUND)
+  set(HWLOC_DIR "" CACHE PATH "Installation directory of HWLOC library")
+  if (NOT HWLOC_FIND_QUIETLY)
+    message(STATUS "A cache variable, namely HWLOC_DIR, has been set to specify the install directory of HWLOC")
+  endif()
+endif()
+
+set(ENV_HWLOC_DIR "$ENV{HWLOC_DIR}")
+set(ENV_HWLOC_INCDIR "$ENV{HWLOC_INCDIR}")
+set(ENV_HWLOC_LIBDIR "$ENV{HWLOC_LIBDIR}")
+set(HWLOC_GIVEN_BY_USER "FALSE")
+if ( HWLOC_DIR OR ( HWLOC_INCDIR AND HWLOC_LIBDIR) OR ENV_HWLOC_DIR OR (ENV_HWLOC_INCDIR AND ENV_HWLOC_LIBDIR) )
+  set(HWLOC_GIVEN_BY_USER "TRUE")
+endif()
+
+# Optionally use pkg-config to detect include/library dirs (if pkg-config is available)
+# -------------------------------------------------------------------------------------
+include(FindPkgConfig)
+find_package(PkgConfig QUIET)
+if( PKG_CONFIG_EXECUTABLE AND NOT HWLOC_GIVEN_BY_USER )
+
+  pkg_search_module(HWLOC hwloc)
+  if (NOT HWLOC_FIND_QUIETLY)
+    if (HWLOC_FOUND AND HWLOC_LIBRARIES)
+      message(STATUS "Looking for HWLOC - found using PkgConfig")
+      #if(NOT HWLOC_INCLUDE_DIRS)
+      #    message("${Magenta}HWLOC_INCLUDE_DIRS is empty using PkgConfig."
+      #        "Perhaps the path to hwloc headers is already present in your"
+      #        "C(PLUS)_INCLUDE_PATH environment variable.${ColourReset}")
+      #endif()
+    else()
+      message(STATUS "${Magenta}Looking for HWLOC - not found using PkgConfig."
+	"\n   Perhaps you should add the directory containing hwloc.pc to"
+	"\n   the PKG_CONFIG_PATH environment variable.${ColourReset}")
+    endif()
+  endif()
+
+endif( PKG_CONFIG_EXECUTABLE AND NOT HWLOC_GIVEN_BY_USER )
+
+if( (NOT PKG_CONFIG_EXECUTABLE) OR (PKG_CONFIG_EXECUTABLE AND NOT HWLOC_FOUND) OR (HWLOC_GIVEN_BY_USER) )
+
+  if (NOT HWLOC_FIND_QUIETLY)
+    message(STATUS "Looking for HWLOC - PkgConfig not used")
+  endif()
+
+  # Looking for include
+  # -------------------
+
+  # Add system include paths to search include
+  # ------------------------------------------
+  unset(_inc_env)
+  if(ENV_HWLOC_INCDIR)
+    list(APPEND _inc_env "${ENV_HWLOC_INCDIR}")
+  elseif(ENV_HWLOC_DIR)
+    list(APPEND _inc_env "${ENV_HWLOC_DIR}")
+    list(APPEND _inc_env "${ENV_HWLOC_DIR}/include")
+    list(APPEND _inc_env "${ENV_HWLOC_DIR}/include/hwloc")
+  else()
+    if(WIN32)
+      string(REPLACE ":" ";" _inc_env "$ENV{INCLUDE}")
+    else()
+      string(REPLACE ":" ";" _path_env "$ENV{INCLUDE}")
+      list(APPEND _inc_env "${_path_env}")
+      string(REPLACE ":" ";" _path_env "$ENV{C_INCLUDE_PATH}")
+      list(APPEND _inc_env "${_path_env}")
+      string(REPLACE ":" ";" _path_env "$ENV{CPATH}")
+      list(APPEND _inc_env "${_path_env}")
+      string(REPLACE ":" ";" _path_env "$ENV{INCLUDE_PATH}")
+      list(APPEND _inc_env "${_path_env}")
+    endif()
+  endif()
+  list(APPEND _inc_env "${CMAKE_PLATFORM_IMPLICIT_INCLUDE_DIRECTORIES}")
+  list(APPEND _inc_env "${CMAKE_C_IMPLICIT_INCLUDE_DIRECTORIES}")
+  list(REMOVE_DUPLICATES _inc_env)
+
+  # set paths where to look for
+  set(PATH_TO_LOOK_FOR "${_inc_env}")
+
+  # Try to find the hwloc header in the given paths
+  # -------------------------------------------------
+  # call cmake macro to find the header path
+  if(HWLOC_INCDIR)
+    set(HWLOC_hwloc.h_DIRS "HWLOC_hwloc.h_DIRS-NOTFOUND")
+    find_path(HWLOC_hwloc.h_DIRS
+      NAMES hwloc.h
+      HINTS ${HWLOC_INCDIR})
+  else()
+    if(HWLOC_DIR)
+      set(HWLOC_hwloc.h_DIRS "HWLOC_hwloc.h_DIRS-NOTFOUND")
+      find_path(HWLOC_hwloc.h_DIRS
+	NAMES hwloc.h
+	HINTS ${HWLOC_DIR}
+	PATH_SUFFIXES "include" "include/hwloc")
+    else()
+      set(HWLOC_hwloc.h_DIRS "HWLOC_hwloc.h_DIRS-NOTFOUND")
+      find_path(HWLOC_hwloc.h_DIRS
+	NAMES hwloc.h
+	HINTS ${PATH_TO_LOOK_FOR}
+	PATH_SUFFIXES "hwloc")
+    endif()
+  endif()
+  mark_as_advanced(HWLOC_hwloc.h_DIRS)
+
+  # Add path to cmake variable
+  # ------------------------------------
+  if (HWLOC_hwloc.h_DIRS)
+    set(HWLOC_INCLUDE_DIRS "${HWLOC_hwloc.h_DIRS}")
+  else ()
+    set(HWLOC_INCLUDE_DIRS "HWLOC_INCLUDE_DIRS-NOTFOUND")
+    if(NOT HWLOC_FIND_QUIETLY)
+      message(STATUS "Looking for hwloc -- hwloc.h not found")
+    endif()
+  endif ()
+
+  if (HWLOC_INCLUDE_DIRS)
+    list(REMOVE_DUPLICATES HWLOC_INCLUDE_DIRS)
+  endif ()
+
+
+  # Looking for lib
+  # ---------------
+
+  # Add system library paths to search lib
+  # --------------------------------------
+  unset(_lib_env)
+  if(ENV_HWLOC_LIBDIR)
+    list(APPEND _lib_env "${ENV_HWLOC_LIBDIR}")
+  elseif(ENV_HWLOC_DIR)
+    list(APPEND _lib_env "${ENV_HWLOC_DIR}")
+    list(APPEND _lib_env "${ENV_HWLOC_DIR}/lib")
+  else()
+    if(WIN32)
+      string(REPLACE ":" ";" _lib_env "$ENV{LIB}")
+    else()
+      if(APPLE)
+	string(REPLACE ":" ";" _lib_env "$ENV{DYLD_LIBRARY_PATH}")
+      else()
+	string(REPLACE ":" ";" _lib_env "$ENV{LD_LIBRARY_PATH}")
+      endif()
+      list(APPEND _lib_env "${CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES}")
+      list(APPEND _lib_env "${CMAKE_C_IMPLICIT_LINK_DIRECTORIES}")
+    endif()
+  endif()
+  list(REMOVE_DUPLICATES _lib_env)
+
+  # set paths where to look for
+  set(PATH_TO_LOOK_FOR "${_lib_env}")
+
+  # Try to find the hwloc lib in the given paths
+  # ----------------------------------------------
+
+  # call cmake macro to find the lib path
+  if(HWLOC_LIBDIR)
+    set(HWLOC_hwloc_LIBRARY "HWLOC_hwloc_LIBRARY-NOTFOUND")
+    find_library(HWLOC_hwloc_LIBRARY
+      NAMES hwloc
+      HINTS ${HWLOC_LIBDIR})
+  else()
+    if(HWLOC_DIR)
+      set(HWLOC_hwloc_LIBRARY "HWLOC_hwloc_LIBRARY-NOTFOUND")
+      find_library(HWLOC_hwloc_LIBRARY
+	NAMES hwloc
+	HINTS ${HWLOC_DIR}
+	PATH_SUFFIXES lib lib32 lib64)
+    else()
+      set(HWLOC_hwloc_LIBRARY "HWLOC_hwloc_LIBRARY-NOTFOUND")
+      find_library(HWLOC_hwloc_LIBRARY
+	NAMES hwloc
+	HINTS ${PATH_TO_LOOK_FOR})
+    endif()
+  endif()
+  mark_as_advanced(HWLOC_hwloc_LIBRARY)
+
+  # If found, add path to cmake variable
+  # ------------------------------------
+  if (HWLOC_hwloc_LIBRARY)
+    get_filename_component(hwloc_lib_path ${HWLOC_hwloc_LIBRARY} PATH)
+    # set cmake variables (respects naming convention)
+    set(HWLOC_LIBRARIES    "${HWLOC_hwloc_LIBRARY}")
+    set(HWLOC_LIBRARY_DIRS "${hwloc_lib_path}")
+  else ()
+    set(HWLOC_LIBRARIES    "HWLOC_LIBRARIES-NOTFOUND")
+    set(HWLOC_LIBRARY_DIRS "HWLOC_LIBRARY_DIRS-NOTFOUND")
+    if(NOT HWLOC_FIND_QUIETLY)
+      message(STATUS "Looking for hwloc -- lib hwloc not found")
+    endif()
+  endif ()
+
+  if (HWLOC_LIBRARY_DIRS)
+    list(REMOVE_DUPLICATES HWLOC_LIBRARY_DIRS)
+  endif ()
+
+  # check a function to validate the find
+  if(HWLOC_LIBRARIES)
+
+    set(REQUIRED_INCDIRS)
+    set(REQUIRED_LIBDIRS)
+    set(REQUIRED_LIBS)
+
+    # HWLOC
+    if (HWLOC_INCLUDE_DIRS)
+      set(REQUIRED_INCDIRS "${HWLOC_INCLUDE_DIRS}")
+    endif()
+    if (HWLOC_LIBRARY_DIRS)
+      set(REQUIRED_LIBDIRS "${HWLOC_LIBRARY_DIRS}")
+    endif()
+    set(REQUIRED_LIBS "${HWLOC_LIBRARIES}")
+
+    # set required libraries for link
+    set(CMAKE_REQUIRED_INCLUDES "${REQUIRED_INCDIRS}")
+    set(CMAKE_REQUIRED_LIBRARIES)
+    foreach(lib_dir ${REQUIRED_LIBDIRS})
+      list(APPEND CMAKE_REQUIRED_LIBRARIES "-L${lib_dir}")
+    endforeach()
+    list(APPEND CMAKE_REQUIRED_LIBRARIES "${REQUIRED_LIBS}")
+    string(REGEX REPLACE "^ -" "-" CMAKE_REQUIRED_LIBRARIES "${CMAKE_REQUIRED_LIBRARIES}")
+
+    # test link
+    unset(HWLOC_WORKS CACHE)
+    include(CheckFunctionExists)
+    check_function_exists(hwloc_topology_init HWLOC_WORKS)
+    mark_as_advanced(HWLOC_WORKS)
+
+    if(NOT HWLOC_WORKS)
+      if(NOT HWLOC_FIND_QUIETLY)
+	message(STATUS "Looking for hwloc : test of hwloc_topology_init with hwloc library fails")
+	message(STATUS "CMAKE_REQUIRED_LIBRARIES: ${CMAKE_REQUIRED_LIBRARIES}")
+	message(STATUS "CMAKE_REQUIRED_INCLUDES: ${CMAKE_REQUIRED_INCLUDES}")
+	message(STATUS "Check in CMakeFiles/CMakeError.log to figure out why it fails")
+      endif()
+    endif()
+    set(CMAKE_REQUIRED_INCLUDES)
+    set(CMAKE_REQUIRED_FLAGS)
+    set(CMAKE_REQUIRED_LIBRARIES)
+  endif(HWLOC_LIBRARIES)
+
+endif( (NOT PKG_CONFIG_EXECUTABLE) OR (PKG_CONFIG_EXECUTABLE AND NOT HWLOC_FOUND) OR (HWLOC_GIVEN_BY_USER) )
+
+if (HWLOC_LIBRARIES)
+  if (HWLOC_LIBRARY_DIRS)
+    list(GET HWLOC_LIBRARY_DIRS 0 first_lib_path)
+  else()
+    list(GET HWLOC_LIBRARIES 0 first_lib)
+    get_filename_component(first_lib_path "${first_lib}" PATH)
+  endif()
+  if (${first_lib_path} MATCHES "/lib(32|64)?$")
+    string(REGEX REPLACE "/lib(32|64)?$" "" not_cached_dir "${first_lib_path}")
+    set(HWLOC_DIR_FOUND "${not_cached_dir}" CACHE PATH "Installation directory of HWLOC library" FORCE)
+  else()
+    set(HWLOC_DIR_FOUND "${first_lib_path}" CACHE PATH "Installation directory of HWLOC library" FORCE)
+  endif()
+endif()
+mark_as_advanced(HWLOC_DIR)
+mark_as_advanced(HWLOC_DIR_FOUND)
+
+# check that HWLOC has been found
+# -------------------------------
+include(FindPackageHandleStandardArgs)
+if (PKG_CONFIG_EXECUTABLE AND HWLOC_FOUND)
+  find_package_handle_standard_args(HWLOC DEFAULT_MSG
+    HWLOC_LIBRARIES)
+else()
+  find_package_handle_standard_args(HWLOC DEFAULT_MSG
+    HWLOC_LIBRARIES
+    HWLOC_WORKS)
+endif()
+
+if (HWLOC_FOUND)
+  set(HWLOC_SAVE_CMAKE_REQUIRED_INCLUDES ${CMAKE_REQUIRED_INCLUDES})
+  list(APPEND CMAKE_REQUIRED_INCLUDES ${HWLOC_INCLUDE_DIRS})
+
+  # test headers to guess the version
+  check_struct_has_member( "struct hwloc_obj" parent hwloc.h HAVE_HWLOC_PARENT_MEMBER )
+  check_struct_has_member( "struct hwloc_cache_attr_s" size hwloc.h HAVE_HWLOC_CACHE_ATTR )
+  check_c_source_compiles( "#include <hwloc.h>
+	    int main(void) { hwloc_obj_t o; o->type = HWLOC_OBJ_PU; return 0;}" HAVE_HWLOC_OBJ_PU)
+  include(CheckLibraryExists)
+  check_library_exists(${HWLOC_LIBRARIES} hwloc_bitmap_free "" HAVE_HWLOC_BITMAP)
+
+  set(CMAKE_REQUIRED_INCLUDES ${HWLOC_SAVE_CMAKE_REQUIRED_INCLUDES})
+endif()

Index: 3rd_party/eigen/cmake/FindMetis.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindMetis.cmake
+++ 3rd_party/eigen/cmake/FindMetis.cmake
@@ -1,59 +1,264 @@
-# Pastix requires METIS or METIS (partitioning and reordering tools)
-
-if (METIS_INCLUDES AND METIS_LIBRARIES)
-  set(METIS_FIND_QUIETLY TRUE)
-endif (METIS_INCLUDES AND METIS_LIBRARIES)
-
-find_path(METIS_INCLUDES 
-  NAMES 
-  metis.h 
-  PATHS 
-  $ENV{METISDIR} 
-  ${INCLUDE_INSTALL_DIR} 
-  PATH_SUFFIXES
-  .
-  metis
-  include
-)
-
-macro(_metis_check_version)
-  file(READ "${METIS_INCLUDES}/metis.h" _metis_version_header)
-
-  string(REGEX MATCH "define[ \t]+METIS_VER_MAJOR[ \t]+([0-9]+)" _metis_major_version_match "${_metis_version_header}")
-  set(METIS_MAJOR_VERSION "${CMAKE_MATCH_1}")
-  string(REGEX MATCH "define[ \t]+METIS_VER_MINOR[ \t]+([0-9]+)" _metis_minor_version_match "${_metis_version_header}")
-  set(METIS_MINOR_VERSION "${CMAKE_MATCH_1}")
-  string(REGEX MATCH "define[ \t]+METIS_VER_SUBMINOR[ \t]+([0-9]+)" _metis_subminor_version_match "${_metis_version_header}")
-  set(METIS_SUBMINOR_VERSION "${CMAKE_MATCH_1}")
-  if(NOT METIS_MAJOR_VERSION)
-    message(WARNING "Could not determine Metis version. Assuming version 4.0.0")
-    set(METIS_VERSION 4.0.0)
-  else()
-    set(METIS_VERSION ${METIS_MAJOR_VERSION}.${METIS_MINOR_VERSION}.${METIS_SUBMINOR_VERSION})
-  endif()
-  if(${METIS_VERSION} VERSION_LESS ${Metis_FIND_VERSION})
-    set(METIS_VERSION_OK FALSE)
-  else()
-    set(METIS_VERSION_OK TRUE)
-  endif()
-
-  if(NOT METIS_VERSION_OK)
-    message(STATUS "Metis version ${METIS_VERSION} found in ${METIS_INCLUDES}, "
-                   "but at least version ${Metis_FIND_VERSION} is required")
-  endif(NOT METIS_VERSION_OK)
-endmacro(_metis_check_version)
-
-  if(METIS_INCLUDES AND Metis_FIND_VERSION)
-    _metis_check_version()
-  else()
-    set(METIS_VERSION_OK TRUE)
-  endif()
-
-
-find_library(METIS_LIBRARIES metis PATHS $ENV{METISDIR} ${LIB_INSTALL_DIR} PATH_SUFFIXES lib)
-
+###
+#
+# @copyright (c) 2009-2014 The University of Tennessee and The University
+#                          of Tennessee Research Foundation.
+#                          All rights reserved.
+# @copyright (c) 2012-2014 Inria. All rights reserved.
+# @copyright (c) 2012-2014 Bordeaux INP, CNRS (LaBRI UMR 5800), Inria, Univ. Bordeaux. All rights reserved.
+#
+###
+#
+# - Find METIS include dirs and libraries
+# Use this module by invoking find_package with the form:
+#  find_package(METIS
+#               [REQUIRED]             # Fail with error if metis is not found
+#              )
+#
+# This module finds headers and metis library.
+# Results are reported in variables:
+#  METIS_FOUND           - True if headers and requested libraries were found
+#  METIS_INCLUDE_DIRS    - metis include directories
+#  METIS_LIBRARY_DIRS    - Link directories for metis libraries
+#  METIS_LIBRARIES       - metis component libraries to be linked
+#
+# The user can give specific paths where to find the libraries adding cmake
+# options at configure (ex: cmake path/to/project -DMETIS_DIR=path/to/metis):
+#  METIS_DIR             - Where to find the base directory of metis
+#  METIS_INCDIR          - Where to find the header files
+#  METIS_LIBDIR          - Where to find the library files
+# The module can also look for the following environment variables if paths
+# are not given as cmake variable: METIS_DIR, METIS_INCDIR, METIS_LIBDIR
+
+#=============================================================================
+# Copyright 2012-2013 Inria
+# Copyright 2012-2013 Emmanuel Agullo
+# Copyright 2012-2013 Mathieu Faverge
+# Copyright 2012      Cedric Castagnede
+# Copyright 2013      Florent Pruvost
+#
+# Distributed under the OSI-approved BSD License (the "License");
+# see accompanying file MORSE-Copyright.txt for details.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without even the
+# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the License for more information.
+#=============================================================================
+# (To distribute this file outside of Morse, substitute the full
+#  License text for the above reference.)
+
+if (NOT METIS_FOUND)
+  set(METIS_DIR "" CACHE PATH "Installation directory of METIS library")
+  if (NOT METIS_FIND_QUIETLY)
+    message(STATUS "A cache variable, namely METIS_DIR, has been set to specify the install directory of METIS")
+  endif()
+endif()
+
+# Looking for include
+# -------------------
+
+# Add system include paths to search include
+# ------------------------------------------
+unset(_inc_env)
+set(ENV_METIS_DIR "$ENV{METIS_DIR}")
+set(ENV_METIS_INCDIR "$ENV{METIS_INCDIR}")
+if(ENV_METIS_INCDIR)
+  list(APPEND _inc_env "${ENV_METIS_INCDIR}")
+elseif(ENV_METIS_DIR)
+  list(APPEND _inc_env "${ENV_METIS_DIR}")
+  list(APPEND _inc_env "${ENV_METIS_DIR}/include")
+  list(APPEND _inc_env "${ENV_METIS_DIR}/include/metis")
+else()
+  if(WIN32)
+    string(REPLACE ":" ";" _inc_env "$ENV{INCLUDE}")
+  else()
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{C_INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{CPATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+  endif()
+endif()
+list(APPEND _inc_env "${CMAKE_PLATFORM_IMPLICIT_INCLUDE_DIRECTORIES}")
+list(APPEND _inc_env "${CMAKE_C_IMPLICIT_INCLUDE_DIRECTORIES}")
+list(REMOVE_DUPLICATES _inc_env)
+
+
+# Try to find the metis header in the given paths
+# -------------------------------------------------
+# call cmake macro to find the header path
+if(METIS_INCDIR)
+  set(METIS_metis.h_DIRS "METIS_metis.h_DIRS-NOTFOUND")
+  find_path(METIS_metis.h_DIRS
+    NAMES metis.h
+    HINTS ${METIS_INCDIR})
+else()
+  if(METIS_DIR)
+    set(METIS_metis.h_DIRS "METIS_metis.h_DIRS-NOTFOUND")
+    find_path(METIS_metis.h_DIRS
+      NAMES metis.h
+      HINTS ${METIS_DIR}
+      PATH_SUFFIXES "include" "include/metis")
+  else()
+    set(METIS_metis.h_DIRS "METIS_metis.h_DIRS-NOTFOUND")
+    find_path(METIS_metis.h_DIRS
+      NAMES metis.h
+      HINTS ${_inc_env})
+  endif()
+endif()
+mark_as_advanced(METIS_metis.h_DIRS)
+
+
+# If found, add path to cmake variable
+# ------------------------------------
+if (METIS_metis.h_DIRS)
+  set(METIS_INCLUDE_DIRS "${METIS_metis.h_DIRS}")
+else ()
+  set(METIS_INCLUDE_DIRS "METIS_INCLUDE_DIRS-NOTFOUND")
+  if(NOT METIS_FIND_QUIETLY)
+    message(STATUS "Looking for metis -- metis.h not found")
+  endif()
+endif()
+
+
+# Looking for lib
+# ---------------
+
+# Add system library paths to search lib
+# --------------------------------------
+unset(_lib_env)
+set(ENV_METIS_LIBDIR "$ENV{METIS_LIBDIR}")
+if(ENV_METIS_LIBDIR)
+  list(APPEND _lib_env "${ENV_METIS_LIBDIR}")
+elseif(ENV_METIS_DIR)
+  list(APPEND _lib_env "${ENV_METIS_DIR}")
+  list(APPEND _lib_env "${ENV_METIS_DIR}/lib")
+else()
+  if(WIN32)
+    string(REPLACE ":" ";" _lib_env "$ENV{LIB}")
+  else()
+    if(APPLE)
+      string(REPLACE ":" ";" _lib_env "$ENV{DYLD_LIBRARY_PATH}")
+    else()
+      string(REPLACE ":" ";" _lib_env "$ENV{LD_LIBRARY_PATH}")
+    endif()
+    list(APPEND _lib_env "${CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES}")
+    list(APPEND _lib_env "${CMAKE_C_IMPLICIT_LINK_DIRECTORIES}")
+  endif()
+endif()
+list(REMOVE_DUPLICATES _lib_env)
+
+# Try to find the metis lib in the given paths
+# ----------------------------------------------
+# call cmake macro to find the lib path
+if(METIS_LIBDIR)
+  set(METIS_metis_LIBRARY "METIS_metis_LIBRARY-NOTFOUND")
+  find_library(METIS_metis_LIBRARY
+    NAMES metis
+    HINTS ${METIS_LIBDIR})
+else()
+  if(METIS_DIR)
+    set(METIS_metis_LIBRARY "METIS_metis_LIBRARY-NOTFOUND")
+    find_library(METIS_metis_LIBRARY
+      NAMES metis
+      HINTS ${METIS_DIR}
+      PATH_SUFFIXES lib lib32 lib64)
+  else()
+    set(METIS_metis_LIBRARY "METIS_metis_LIBRARY-NOTFOUND")
+    find_library(METIS_metis_LIBRARY
+      NAMES metis
+      HINTS ${_lib_env})
+  endif()
+endif()
+mark_as_advanced(METIS_metis_LIBRARY)
+
+
+# If found, add path to cmake variable
+# ------------------------------------
+if (METIS_metis_LIBRARY)
+  get_filename_component(metis_lib_path "${METIS_metis_LIBRARY}" PATH)
+  # set cmake variables
+  set(METIS_LIBRARIES    "${METIS_metis_LIBRARY}")
+  set(METIS_LIBRARY_DIRS "${metis_lib_path}")
+else ()
+  set(METIS_LIBRARIES    "METIS_LIBRARIES-NOTFOUND")
+  set(METIS_LIBRARY_DIRS "METIS_LIBRARY_DIRS-NOTFOUND")
+  if(NOT METIS_FIND_QUIETLY)
+    message(STATUS "Looking for metis -- lib metis not found")
+  endif()
+endif ()
+
+# check a function to validate the find
+if(METIS_LIBRARIES)
+
+  set(REQUIRED_INCDIRS)
+  set(REQUIRED_LIBDIRS)
+  set(REQUIRED_LIBS)
+
+  # METIS
+  if (METIS_INCLUDE_DIRS)
+    set(REQUIRED_INCDIRS  "${METIS_INCLUDE_DIRS}")
+  endif()
+  if (METIS_LIBRARY_DIRS)
+    set(REQUIRED_LIBDIRS "${METIS_LIBRARY_DIRS}")
+  endif()
+  set(REQUIRED_LIBS "${METIS_LIBRARIES}")
+  # m
+  find_library(M_LIBRARY NAMES m)
+  mark_as_advanced(M_LIBRARY)
+  if(M_LIBRARY)
+    list(APPEND REQUIRED_LIBS "-lm")
+  endif()
+
+  # set required libraries for link
+  set(CMAKE_REQUIRED_INCLUDES "${REQUIRED_INCDIRS}")
+  set(CMAKE_REQUIRED_LIBRARIES)
+  foreach(lib_dir ${REQUIRED_LIBDIRS})
+    list(APPEND CMAKE_REQUIRED_LIBRARIES "-L${lib_dir}")
+  endforeach()
+  list(APPEND CMAKE_REQUIRED_LIBRARIES "${REQUIRED_LIBS}")
+  string(REGEX REPLACE "^ -" "-" CMAKE_REQUIRED_LIBRARIES "${CMAKE_REQUIRED_LIBRARIES}")
+
+  # test link
+  unset(METIS_WORKS CACHE)
+  include(CheckFunctionExists)
+  check_function_exists(METIS_NodeND METIS_WORKS)
+  mark_as_advanced(METIS_WORKS)
+
+  if(NOT METIS_WORKS)
+    if(NOT METIS_FIND_QUIETLY)
+      message(STATUS "Looking for METIS : test of METIS_NodeND with METIS library fails")
+      message(STATUS "CMAKE_REQUIRED_LIBRARIES: ${CMAKE_REQUIRED_LIBRARIES}")
+      message(STATUS "CMAKE_REQUIRED_INCLUDES: ${CMAKE_REQUIRED_INCLUDES}")
+      message(STATUS "Check in CMakeFiles/CMakeError.log to figure out why it fails")
+    endif()
+  endif()
+  set(CMAKE_REQUIRED_INCLUDES)
+  set(CMAKE_REQUIRED_FLAGS)
+  set(CMAKE_REQUIRED_LIBRARIES)
+endif(METIS_LIBRARIES)
+
+if (METIS_LIBRARIES)
+  list(GET METIS_LIBRARIES 0 first_lib)
+  get_filename_component(first_lib_path "${first_lib}" PATH)
+  if (${first_lib_path} MATCHES "/lib(32|64)?$")
+    string(REGEX REPLACE "/lib(32|64)?$" "" not_cached_dir "${first_lib_path}")
+    set(METIS_DIR_FOUND "${not_cached_dir}" CACHE PATH "Installation directory of METIS library" FORCE)
+  else()
+    set(METIS_DIR_FOUND "${first_lib_path}" CACHE PATH "Installation directory of METIS library" FORCE)
+  endif()
+endif()
+mark_as_advanced(METIS_DIR)
+mark_as_advanced(METIS_DIR_FOUND)
+
+# check that METIS has been found
+# ---------------------------------
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(METIS DEFAULT_MSG
-                                  METIS_INCLUDES METIS_LIBRARIES METIS_VERSION_OK)
-
-mark_as_advanced(METIS_INCLUDES METIS_LIBRARIES)
+  METIS_LIBRARIES
+  METIS_WORKS)
+#
+# TODO: Add possibility to check for specific functions in the library
+#

ADDED   3rd_party/eigen/cmake/FindPTSCOTCH.cmake
Index: 3rd_party/eigen/cmake/FindPTSCOTCH.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindPTSCOTCH.cmake
+++ 3rd_party/eigen/cmake/FindPTSCOTCH.cmake
@@ -0,0 +1,423 @@
+###
+#
+# @copyright (c) 2009-2014 The University of Tennessee and The University
+#                          of Tennessee Research Foundation.
+#                          All rights reserved.
+# @copyright (c) 2012-2016 Inria. All rights reserved.
+# @copyright (c) 2012-2014 Bordeaux INP, CNRS (LaBRI UMR 5800), Inria, Univ. Bordeaux. All rights reserved.
+#
+###
+#
+# - Find PTSCOTCH include dirs and libraries
+# Use this module by invoking find_package with the form:
+#  find_package(PTSCOTCH
+#               [REQUIRED]             # Fail with error if ptscotch is not found
+#               [COMPONENTS <comp1> <comp2> ...] # dependencies
+#              )
+#
+#  PTSCOTCH depends on the following libraries:
+#   - Threads
+#   - MPI
+#
+#  COMPONENTS can be some of the following:
+#   - ESMUMPS: to activate detection of PT-Scotch with the esmumps interface
+#
+# This module finds headers and ptscotch library.
+# Results are reported in variables:
+#  PTSCOTCH_FOUND            - True if headers and requested libraries were found
+#  PTSCOTCH_LINKER_FLAGS     - list of required linker flags (excluding -l and -L)
+#  PTSCOTCH_INCLUDE_DIRS     - ptscotch include directories
+#  PTSCOTCH_LIBRARY_DIRS     - Link directories for ptscotch libraries
+#  PTSCOTCH_LIBRARIES        - ptscotch component libraries to be linked
+#  PTSCOTCH_INCLUDE_DIRS_DEP - ptscotch + dependencies include directories
+#  PTSCOTCH_LIBRARY_DIRS_DEP - ptscotch + dependencies link directories
+#  PTSCOTCH_LIBRARIES_DEP    - ptscotch libraries + dependencies
+#  PTSCOTCH_INTSIZE          - Number of octets occupied by a SCOTCH_Num
+#
+# The user can give specific paths where to find the libraries adding cmake
+# options at configure (ex: cmake path/to/project -DPTSCOTCH=path/to/ptscotch):
+#  PTSCOTCH_DIR              - Where to find the base directory of ptscotch
+#  PTSCOTCH_INCDIR           - Where to find the header files
+#  PTSCOTCH_LIBDIR           - Where to find the library files
+# The module can also look for the following environment variables if paths
+# are not given as cmake variable: PTSCOTCH_DIR, PTSCOTCH_INCDIR, PTSCOTCH_LIBDIR
+
+#=============================================================================
+# Copyright 2012-2013 Inria
+# Copyright 2012-2013 Emmanuel Agullo
+# Copyright 2012-2013 Mathieu Faverge
+# Copyright 2012      Cedric Castagnede
+# Copyright 2013-2016 Florent Pruvost
+#
+# Distributed under the OSI-approved BSD License (the "License");
+# see accompanying file MORSE-Copyright.txt for details.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without even the
+# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the License for more information.
+#=============================================================================
+# (To distribute this file outside of Morse, substitute the full
+#  License text for the above reference.)
+
+if (NOT PTSCOTCH_FOUND)
+  set(PTSCOTCH_DIR "" CACHE PATH "Installation directory of PTSCOTCH library")
+  if (NOT PTSCOTCH_FIND_QUIETLY)
+    message(STATUS "A cache variable, namely PTSCOTCH_DIR, has been set to specify the install directory of PTSCOTCH")
+  endif()
+endif()
+
+# Set the version to find
+set(PTSCOTCH_LOOK_FOR_ESMUMPS OFF)
+
+if( PTSCOTCH_FIND_COMPONENTS )
+  foreach( component ${PTSCOTCH_FIND_COMPONENTS} )
+    if (${component} STREQUAL "ESMUMPS")
+      # means we look for esmumps library
+      set(PTSCOTCH_LOOK_FOR_ESMUMPS ON)
+    endif()
+  endforeach()
+endif()
+
+# PTSCOTCH depends on Threads, try to find it
+if (NOT THREADS_FOUND)
+  if (PTSCOTCH_FIND_REQUIRED)
+    find_package(Threads REQUIRED)
+  else()
+    find_package(Threads)
+  endif()
+endif()
+
+# PTSCOTCH depends on MPI, try to find it
+if (NOT MPI_FOUND)
+  if (PTSCOTCH_FIND_REQUIRED)
+    find_package(MPI REQUIRED)
+  else()
+    find_package(MPI)
+  endif()
+endif()
+
+# Looking for include
+# -------------------
+
+# Add system include paths to search include
+# ------------------------------------------
+unset(_inc_env)
+set(ENV_PTSCOTCH_DIR "$ENV{PTSCOTCH_DIR}")
+set(ENV_PTSCOTCH_INCDIR "$ENV{PTSCOTCH_INCDIR}")
+if(ENV_PTSCOTCH_INCDIR)
+  list(APPEND _inc_env "${ENV_PTSCOTCH_INCDIR}")
+elseif(ENV_PTSCOTCH_DIR)
+  list(APPEND _inc_env "${ENV_PTSCOTCH_DIR}")
+  list(APPEND _inc_env "${ENV_PTSCOTCH_DIR}/include")
+  list(APPEND _inc_env "${ENV_PTSCOTCH_DIR}/include/ptscotch")
+else()
+  if(WIN32)
+    string(REPLACE ":" ";" _inc_env "$ENV{INCLUDE}")
+  else()
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{C_INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{CPATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+  endif()
+endif()
+list(APPEND _inc_env "${CMAKE_PLATFORM_IMPLICIT_INCLUDE_DIRECTORIES}")
+list(APPEND _inc_env "${CMAKE_C_IMPLICIT_INCLUDE_DIRECTORIES}")
+list(REMOVE_DUPLICATES _inc_env)
+
+
+# Try to find the ptscotch header in the given paths
+# -------------------------------------------------
+
+set(PTSCOTCH_hdrs_to_find "ptscotch.h;scotch.h")
+
+# call cmake macro to find the header path
+if(PTSCOTCH_INCDIR)
+  foreach(ptscotch_hdr ${PTSCOTCH_hdrs_to_find})
+    set(PTSCOTCH_${ptscotch_hdr}_DIRS "PTSCOTCH_${ptscotch_hdr}_DIRS-NOTFOUND")
+    find_path(PTSCOTCH_${ptscotch_hdr}_DIRS
+      NAMES ${ptscotch_hdr}
+      HINTS ${PTSCOTCH_INCDIR})
+    mark_as_advanced(PTSCOTCH_${ptscotch_hdr}_DIRS)
+  endforeach()
+else()
+  if(PTSCOTCH_DIR)
+    foreach(ptscotch_hdr ${PTSCOTCH_hdrs_to_find})
+      set(PTSCOTCH_${ptscotch_hdr}_DIRS "PTSCOTCH_${ptscotch_hdr}_DIRS-NOTFOUND")
+      find_path(PTSCOTCH_${ptscotch_hdr}_DIRS
+	NAMES ${ptscotch_hdr}
+	HINTS ${PTSCOTCH_DIR}
+	PATH_SUFFIXES "include" "include/scotch")
+      mark_as_advanced(PTSCOTCH_${ptscotch_hdr}_DIRS)
+    endforeach()
+  else()
+    foreach(ptscotch_hdr ${PTSCOTCH_hdrs_to_find})
+      set(PTSCOTCH_${ptscotch_hdr}_DIRS "PTSCOTCH_${ptscotch_hdr}_DIRS-NOTFOUND")
+      find_path(PTSCOTCH_${ptscotch_hdr}_DIRS
+	NAMES ${ptscotch_hdr}
+	HINTS ${_inc_env}
+	PATH_SUFFIXES "scotch")
+      mark_as_advanced(PTSCOTCH_${ptscotch_hdr}_DIRS)
+    endforeach()
+  endif()
+endif()
+
+# If found, add path to cmake variable
+# ------------------------------------
+foreach(ptscotch_hdr ${PTSCOTCH_hdrs_to_find})
+  if (PTSCOTCH_${ptscotch_hdr}_DIRS)
+    list(APPEND PTSCOTCH_INCLUDE_DIRS "${PTSCOTCH_${ptscotch_hdr}_DIRS}")
+  else ()
+    set(PTSCOTCH_INCLUDE_DIRS "PTSCOTCH_INCLUDE_DIRS-NOTFOUND")
+    if (NOT PTSCOTCH_FIND_QUIETLY)
+      message(STATUS "Looking for ptscotch -- ${ptscotch_hdr} not found")
+    endif()
+  endif()
+endforeach()
+list(REMOVE_DUPLICATES PTSCOTCH_INCLUDE_DIRS)
+
+# Looking for lib
+# ---------------
+
+# Add system library paths to search lib
+# --------------------------------------
+unset(_lib_env)
+set(ENV_PTSCOTCH_LIBDIR "$ENV{PTSCOTCH_LIBDIR}")
+if(ENV_PTSCOTCH_LIBDIR)
+  list(APPEND _lib_env "${ENV_PTSCOTCH_LIBDIR}")
+elseif(ENV_PTSCOTCH_DIR)
+  list(APPEND _lib_env "${ENV_PTSCOTCH_DIR}")
+  list(APPEND _lib_env "${ENV_PTSCOTCH_DIR}/lib")
+else()
+  if(WIN32)
+    string(REPLACE ":" ";" _lib_env "$ENV{LIB}")
+  else()
+    if(APPLE)
+      string(REPLACE ":" ";" _lib_env "$ENV{DYLD_LIBRARY_PATH}")
+    else()
+      string(REPLACE ":" ";" _lib_env "$ENV{LD_LIBRARY_PATH}")
+    endif()
+    list(APPEND _lib_env "${CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES}")
+    list(APPEND _lib_env "${CMAKE_C_IMPLICIT_LINK_DIRECTORIES}")
+  endif()
+endif()
+list(REMOVE_DUPLICATES _lib_env)
+
+# Try to find the ptscotch lib in the given paths
+# ----------------------------------------------
+
+set(PTSCOTCH_libs_to_find "ptscotch;ptscotcherr")
+if (PTSCOTCH_LOOK_FOR_ESMUMPS)
+  list(INSERT PTSCOTCH_libs_to_find 0 "ptesmumps")
+  list(APPEND PTSCOTCH_libs_to_find   "esmumps"  )
+endif()
+list(APPEND PTSCOTCH_libs_to_find "scotch;scotcherr")
+
+# call cmake macro to find the lib path
+if(PTSCOTCH_LIBDIR)
+  foreach(ptscotch_lib ${PTSCOTCH_libs_to_find})
+    set(PTSCOTCH_${ptscotch_lib}_LIBRARY "PTSCOTCH_${ptscotch_lib}_LIBRARY-NOTFOUND")
+    find_library(PTSCOTCH_${ptscotch_lib}_LIBRARY
+      NAMES ${ptscotch_lib}
+      HINTS ${PTSCOTCH_LIBDIR})
+  endforeach()
+else()
+  if(PTSCOTCH_DIR)
+    foreach(ptscotch_lib ${PTSCOTCH_libs_to_find})
+      set(PTSCOTCH_${ptscotch_lib}_LIBRARY "PTSCOTCH_${ptscotch_lib}_LIBRARY-NOTFOUND")
+      find_library(PTSCOTCH_${ptscotch_lib}_LIBRARY
+	NAMES ${ptscotch_lib}
+	HINTS ${PTSCOTCH_DIR}
+	PATH_SUFFIXES lib lib32 lib64)
+    endforeach()
+  else()
+    foreach(ptscotch_lib ${PTSCOTCH_libs_to_find})
+      set(PTSCOTCH_${ptscotch_lib}_LIBRARY "PTSCOTCH_${ptscotch_lib}_LIBRARY-NOTFOUND")
+      find_library(PTSCOTCH_${ptscotch_lib}_LIBRARY
+	NAMES ${ptscotch_lib}
+	HINTS ${_lib_env})
+    endforeach()
+  endif()
+endif()
+
+set(PTSCOTCH_LIBRARIES "")
+set(PTSCOTCH_LIBRARY_DIRS "")
+# If found, add path to cmake variable
+# ------------------------------------
+foreach(ptscotch_lib ${PTSCOTCH_libs_to_find})
+
+  if (PTSCOTCH_${ptscotch_lib}_LIBRARY)
+    get_filename_component(${ptscotch_lib}_lib_path "${PTSCOTCH_${ptscotch_lib}_LIBRARY}" PATH)
+    # set cmake variables
+    list(APPEND PTSCOTCH_LIBRARIES "${PTSCOTCH_${ptscotch_lib}_LIBRARY}")
+    list(APPEND PTSCOTCH_LIBRARY_DIRS "${${ptscotch_lib}_lib_path}")
+  else ()
+    list(APPEND PTSCOTCH_LIBRARIES "${PTSCOTCH_${ptscotch_lib}_LIBRARY}")
+    if (NOT PTSCOTCH_FIND_QUIETLY)
+      message(STATUS "Looking for ptscotch -- lib ${ptscotch_lib} not found")
+    endif()
+  endif ()
+
+  mark_as_advanced(PTSCOTCH_${ptscotch_lib}_LIBRARY)
+
+endforeach()
+list(REMOVE_DUPLICATES PTSCOTCH_LIBRARY_DIRS)
+
+# check a function to validate the find
+if(PTSCOTCH_LIBRARIES)
+
+  set(REQUIRED_LDFLAGS)
+  set(REQUIRED_INCDIRS)
+  set(REQUIRED_LIBDIRS)
+  set(REQUIRED_LIBS)
+
+  # PTSCOTCH
+  if (PTSCOTCH_INCLUDE_DIRS)
+    set(REQUIRED_INCDIRS  "${PTSCOTCH_INCLUDE_DIRS}")
+  endif()
+  if (PTSCOTCH_LIBRARY_DIRS)
+    set(REQUIRED_LIBDIRS "${PTSCOTCH_LIBRARY_DIRS}")
+  endif()
+  set(REQUIRED_LIBS "${PTSCOTCH_LIBRARIES}")
+  # MPI
+  if (MPI_FOUND)
+    if (MPI_C_INCLUDE_PATH)
+      list(APPEND CMAKE_REQUIRED_INCLUDES "${MPI_C_INCLUDE_PATH}")
+    endif()
+    if (MPI_C_LINK_FLAGS)
+      if (${MPI_C_LINK_FLAGS} MATCHES "  -")
+	string(REGEX REPLACE " -" "-" MPI_C_LINK_FLAGS ${MPI_C_LINK_FLAGS})
+      endif()
+      list(APPEND REQUIRED_LDFLAGS "${MPI_C_LINK_FLAGS}")
+    endif()
+    list(APPEND REQUIRED_LIBS "${MPI_C_LIBRARIES}")
+  endif()
+  # THREADS
+  if(CMAKE_THREAD_LIBS_INIT)
+    list(APPEND REQUIRED_LIBS "${CMAKE_THREAD_LIBS_INIT}")
+  endif()
+  set(Z_LIBRARY "Z_LIBRARY-NOTFOUND")
+  find_library(Z_LIBRARY NAMES z)
+  mark_as_advanced(Z_LIBRARY)
+  if(Z_LIBRARY)
+    list(APPEND REQUIRED_LIBS "-lz")
+  endif()
+  set(M_LIBRARY "M_LIBRARY-NOTFOUND")
+  find_library(M_LIBRARY NAMES m)
+  mark_as_advanced(M_LIBRARY)
+  if(M_LIBRARY)
+    list(APPEND REQUIRED_LIBS "-lm")
+  endif()
+  set(RT_LIBRARY "RT_LIBRARY-NOTFOUND")
+  find_library(RT_LIBRARY NAMES rt)
+  mark_as_advanced(RT_LIBRARY)
+  if(RT_LIBRARY)
+    list(APPEND REQUIRED_LIBS "-lrt")
+  endif()
+
+  # set required libraries for link
+  set(CMAKE_REQUIRED_INCLUDES "${REQUIRED_INCDIRS}")
+  set(CMAKE_REQUIRED_LIBRARIES)
+  list(APPEND CMAKE_REQUIRED_LIBRARIES "${REQUIRED_LDFLAGS}")
+  foreach(lib_dir ${REQUIRED_LIBDIRS})
+    list(APPEND CMAKE_REQUIRED_LIBRARIES "-L${lib_dir}")
+  endforeach()
+  list(APPEND CMAKE_REQUIRED_LIBRARIES "${REQUIRED_LIBS}")
+  list(APPEND CMAKE_REQUIRED_FLAGS "${REQUIRED_FLAGS}")
+  string(REGEX REPLACE "^ -" "-" CMAKE_REQUIRED_LIBRARIES "${CMAKE_REQUIRED_LIBRARIES}")
+
+  # test link
+  unset(PTSCOTCH_WORKS CACHE)
+  include(CheckFunctionExists)
+  check_function_exists(SCOTCH_dgraphInit PTSCOTCH_WORKS)
+  mark_as_advanced(PTSCOTCH_WORKS)
+
+  if(PTSCOTCH_WORKS)
+    # save link with dependencies
+    set(PTSCOTCH_LIBRARIES_DEP "${REQUIRED_LIBS}")
+    set(PTSCOTCH_LIBRARY_DIRS_DEP "${REQUIRED_LIBDIRS}")
+    set(PTSCOTCH_INCLUDE_DIRS_DEP "${REQUIRED_INCDIRS}")
+    set(PTSCOTCH_LINKER_FLAGS "${REQUIRED_LDFLAGS}")
+    list(REMOVE_DUPLICATES PTSCOTCH_LIBRARY_DIRS_DEP)
+    list(REMOVE_DUPLICATES PTSCOTCH_INCLUDE_DIRS_DEP)
+    list(REMOVE_DUPLICATES PTSCOTCH_LINKER_FLAGS)
+  else()
+    if(NOT PTSCOTCH_FIND_QUIETLY)
+      message(STATUS "Looking for PTSCOTCH : test of SCOTCH_dgraphInit with PTSCOTCH library fails")
+      message(STATUS "CMAKE_REQUIRED_LIBRARIES: ${CMAKE_REQUIRED_LIBRARIES}")
+      message(STATUS "CMAKE_REQUIRED_INCLUDES: ${CMAKE_REQUIRED_INCLUDES}")
+      message(STATUS "Check in CMakeFiles/CMakeError.log to figure out why it fails")
+    endif()
+  endif()
+  set(CMAKE_REQUIRED_INCLUDES)
+  set(CMAKE_REQUIRED_FLAGS)
+  set(CMAKE_REQUIRED_LIBRARIES)
+endif(PTSCOTCH_LIBRARIES)
+
+if (PTSCOTCH_LIBRARIES)
+  list(GET PTSCOTCH_LIBRARIES 0 first_lib)
+  get_filename_component(first_lib_path "${first_lib}" PATH)
+  if (${first_lib_path} MATCHES "/lib(32|64)?$")
+    string(REGEX REPLACE "/lib(32|64)?$" "" not_cached_dir "${first_lib_path}")
+    set(PTSCOTCH_DIR_FOUND "${not_cached_dir}" CACHE PATH "Installation directory of PTSCOTCH library" FORCE)
+  else()
+    set(PTSCOTCH_DIR_FOUND "${first_lib_path}" CACHE PATH "Installation directory of PTSCOTCH library" FORCE)
+  endif()
+endif()
+mark_as_advanced(PTSCOTCH_DIR)
+mark_as_advanced(PTSCOTCH_DIR_FOUND)
+
+# Check the size of SCOTCH_Num
+# ---------------------------------
+set(CMAKE_REQUIRED_INCLUDES ${PTSCOTCH_INCLUDE_DIRS})
+
+include(CheckCSourceRuns)
+#stdio.h and stdint.h should be included by scotch.h directly
+set(PTSCOTCH_C_TEST_SCOTCH_Num_4 "
+#include <stdio.h>
+#include <stdint.h>
+#include <ptscotch.h>
+int main(int argc, char **argv) {
+  if (sizeof(SCOTCH_Num) == 4)
+    return 0;
+  else
+    return 1;
+}
+")
+
+set(PTSCOTCH_C_TEST_SCOTCH_Num_8 "
+#include <stdio.h>
+#include <stdint.h>
+#include <ptscotch.h>
+int main(int argc, char **argv) {
+  if (sizeof(SCOTCH_Num) == 8)
+    return 0;
+  else
+    return 1;
+}
+")
+check_c_source_runs("${PTSCOTCH_C_TEST_SCOTCH_Num_4}" PTSCOTCH_Num_4)
+if(NOT PTSCOTCH_Num_4)
+  check_c_source_runs("${PTSCOTCH_C_TEST_SCOTCH_Num_8}" PTSCOTCH_Num_8)
+  if(NOT PTSCOTCH_Num_8)
+    set(PTSCOTCH_INTSIZE -1)
+  else()
+    set(PTSCOTCH_INTSIZE 8)
+  endif()
+else()
+  set(PTSCOTCH_INTSIZE 4)
+endif()
+set(CMAKE_REQUIRED_INCLUDES "")
+
+# check that PTSCOTCH has been found
+# ---------------------------------
+include(FindPackageHandleStandardArgs)
+find_package_handle_standard_args(PTSCOTCH DEFAULT_MSG
+  PTSCOTCH_LIBRARIES
+  PTSCOTCH_WORKS)
+#
+# TODO: Add possibility to check for specific functions in the library
+#

Index: 3rd_party/eigen/cmake/FindPastix.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindPastix.cmake
+++ 3rd_party/eigen/cmake/FindPastix.cmake
@@ -1,25 +1,704 @@
-# Pastix lib requires linking to a blas library.
-# It is up to the user of this module to find a BLAS and link to it.
-# Pastix requires SCOTCH or METIS (partitioning and reordering tools) as well
-
-if (PASTIX_INCLUDES AND PASTIX_LIBRARIES)
-  set(PASTIX_FIND_QUIETLY TRUE)
-endif (PASTIX_INCLUDES AND PASTIX_LIBRARIES)
-
-find_path(PASTIX_INCLUDES
-  NAMES
-  pastix_nompi.h
-  PATHS
-  $ENV{PASTIXDIR}
-  ${INCLUDE_INSTALL_DIR}
-)
-
-find_library(PASTIX_LIBRARIES pastix PATHS $ENV{PASTIXDIR} ${LIB_INSTALL_DIR})
-
-
-
+###
+#
+# @copyright (c) 2009-2014 The University of Tennessee and The University
+#                          of Tennessee Research Foundation.
+#                          All rights reserved.
+# @copyright (c) 2012-2014 Inria. All rights reserved.
+# @copyright (c) 2012-2014 Bordeaux INP, CNRS (LaBRI UMR 5800), Inria, Univ. Bordeaux. All rights reserved.
+#
+###
+#
+# - Find PASTIX include dirs and libraries
+# Use this module by invoking find_package with the form:
+#  find_package(PASTIX
+#               [REQUIRED] # Fail with error if pastix is not found
+#               [COMPONENTS <comp1> <comp2> ...] # dependencies
+#              )
+#
+#  PASTIX depends on the following libraries:
+#   - Threads, m, rt
+#   - MPI
+#   - HWLOC
+#   - BLAS
+#
+#  COMPONENTS are optional libraries PASTIX could be linked with,
+#  Use it to drive detection of a specific compilation chain
+#  COMPONENTS can be some of the following:
+#   - MPI: to activate detection of the parallel MPI version (default)
+#        it looks for Threads, HWLOC, BLAS, MPI and ScaLAPACK libraries
+#   - SEQ: to activate detection of the sequential version (exclude MPI version)
+#   - STARPU: to activate detection of StarPU version
+#   it looks for MPI version of StarPU (default behaviour)
+#   if SEQ and STARPU are given, it looks for a StarPU without MPI
+#   - STARPU_CUDA: to activate detection of StarPU with CUDA
+#   - STARPU_FXT: to activate detection of StarPU with FxT
+#   - SCOTCH: to activate detection of PASTIX linked with SCOTCH
+#   - PTSCOTCH: to activate detection of PASTIX linked with SCOTCH
+#   - METIS: to activate detection of PASTIX linked with SCOTCH
+#
+# This module finds headers and pastix library.
+# Results are reported in variables:
+#  PASTIX_FOUND            - True if headers and requested libraries were found
+#  PASTIX_LINKER_FLAGS     - list of required linker flags (excluding -l and -L)
+#  PASTIX_INCLUDE_DIRS     - pastix include directories
+#  PASTIX_LIBRARY_DIRS     - Link directories for pastix libraries
+#  PASTIX_LIBRARIES        - pastix libraries
+#  PASTIX_INCLUDE_DIRS_DEP - pastix + dependencies include directories
+#  PASTIX_LIBRARY_DIRS_DEP - pastix + dependencies link directories
+#  PASTIX_LIBRARIES_DEP    - pastix libraries + dependencies
+#
+# The user can give specific paths where to find the libraries adding cmake
+# options at configure (ex: cmake path/to/project -DPASTIX_DIR=path/to/pastix):
+#  PASTIX_DIR              - Where to find the base directory of pastix
+#  PASTIX_INCDIR           - Where to find the header files
+#  PASTIX_LIBDIR           - Where to find the library files
+# The module can also look for the following environment variables if paths
+# are not given as cmake variable: PASTIX_DIR, PASTIX_INCDIR, PASTIX_LIBDIR
+
+#=============================================================================
+# Copyright 2012-2013 Inria
+# Copyright 2012-2013 Emmanuel Agullo
+# Copyright 2012-2013 Mathieu Faverge
+# Copyright 2012      Cedric Castagnede
+# Copyright 2013      Florent Pruvost
+#
+# Distributed under the OSI-approved BSD License (the "License");
+# see accompanying file MORSE-Copyright.txt for details.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without even the
+# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the License for more information.
+#=============================================================================
+# (To distribute this file outside of Morse, substitute the full
+#  License text for the above reference.)
+
+
+if (NOT PASTIX_FOUND)
+  set(PASTIX_DIR "" CACHE PATH "Installation directory of PASTIX library")
+  if (NOT PASTIX_FIND_QUIETLY)
+    message(STATUS "A cache variable, namely PASTIX_DIR, has been set to specify the install directory of PASTIX")
+  endif()
+endif()
+
+# Set the version to find
+set(PASTIX_LOOK_FOR_MPI ON)
+set(PASTIX_LOOK_FOR_SEQ OFF)
+set(PASTIX_LOOK_FOR_STARPU OFF)
+set(PASTIX_LOOK_FOR_STARPU_CUDA OFF)
+set(PASTIX_LOOK_FOR_STARPU_FXT OFF)
+set(PASTIX_LOOK_FOR_SCOTCH ON)
+set(PASTIX_LOOK_FOR_PTSCOTCH OFF)
+set(PASTIX_LOOK_FOR_METIS OFF)
+
+if( PASTIX_FIND_COMPONENTS )
+  foreach( component ${PASTIX_FIND_COMPONENTS} )
+    if (${component} STREQUAL "SEQ")
+      # means we look for the sequential version of PaStiX (without MPI)
+      set(PASTIX_LOOK_FOR_SEQ ON)
+      set(PASTIX_LOOK_FOR_MPI OFF)
+    endif()
+    if (${component} STREQUAL "MPI")
+      # means we look for the MPI version of PaStiX (default)
+      set(PASTIX_LOOK_FOR_SEQ OFF)
+      set(PASTIX_LOOK_FOR_MPI ON)
+    endif()
+    if (${component} STREQUAL "STARPU")
+      # means we look for PaStiX with StarPU
+      set(PASTIX_LOOK_FOR_STARPU ON)
+    endif()
+    if (${component} STREQUAL "STARPU_CUDA")
+      # means we look for PaStiX with StarPU + CUDA
+      set(PASTIX_LOOK_FOR_STARPU ON)
+      set(PASTIX_LOOK_FOR_STARPU_CUDA ON)
+    endif()
+    if (${component} STREQUAL "STARPU_FXT")
+      # means we look for PaStiX with StarPU + FxT
+      set(PASTIX_LOOK_FOR_STARPU_FXT ON)
+    endif()
+    if (${component} STREQUAL "SCOTCH")
+      set(PASTIX_LOOK_FOR_SCOTCH ON)
+    endif()
+    if (${component} STREQUAL "SCOTCH")
+      set(PASTIX_LOOK_FOR_PTSCOTCH ON)
+    endif()
+    if (${component} STREQUAL "METIS")
+      set(PASTIX_LOOK_FOR_METIS ON)
+    endif()
+  endforeach()
+endif()
+
+# Dependencies detection
+# ----------------------
+
+
+# Required dependencies
+# ---------------------
+
+if (NOT PASTIX_FIND_QUIETLY)
+  message(STATUS "Looking for PASTIX - Try to detect pthread")
+endif()
+if (PASTIX_FIND_REQUIRED)
+  find_package(Threads REQUIRED QUIET)
+else()
+  find_package(Threads QUIET)
+endif()
+set(PASTIX_EXTRA_LIBRARIES "")
+if( THREADS_FOUND )
+  list(APPEND PASTIX_EXTRA_LIBRARIES ${CMAKE_THREAD_LIBS_INIT})
+endif ()
+
+# Add math library to the list of extra
+# it normally exists on all common systems provided with a C compiler
+if (NOT PASTIX_FIND_QUIETLY)
+  message(STATUS "Looking for PASTIX - Try to detect libm")
+endif()
+set(PASTIX_M_LIBRARIES "")
+if(UNIX OR WIN32)
+  find_library(
+    PASTIX_M_m_LIBRARY
+    NAMES m
+    )
+  mark_as_advanced(PASTIX_M_m_LIBRARY)
+  if (PASTIX_M_m_LIBRARY)
+    list(APPEND PASTIX_M_LIBRARIES "${PASTIX_M_m_LIBRARY}")
+    list(APPEND PASTIX_EXTRA_LIBRARIES "${PASTIX_M_m_LIBRARY}")
+  else()
+    if (PASTIX_FIND_REQUIRED)
+      message(FATAL_ERROR "Could NOT find libm on your system."
+	"Are you sure to a have a C compiler installed?")
+    endif()
+  endif()
+endif()
+
+# Try to find librt (libposix4 - POSIX.1b Realtime Extensions library)
+# on Unix systems except Apple ones because it does not exist on it
+if (NOT PASTIX_FIND_QUIETLY)
+  message(STATUS "Looking for PASTIX - Try to detect librt")
+endif()
+set(PASTIX_RT_LIBRARIES "")
+if(UNIX AND NOT APPLE)
+  find_library(
+    PASTIX_RT_rt_LIBRARY
+    NAMES rt
+    )
+  mark_as_advanced(PASTIX_RT_rt_LIBRARY)
+  if (PASTIX_RT_rt_LIBRARY)
+    list(APPEND PASTIX_RT_LIBRARIES "${PASTIX_RT_rt_LIBRARY}")
+    list(APPEND PASTIX_EXTRA_LIBRARIES "${PASTIX_RT_rt_LIBRARY}")
+  else()
+    if (PASTIX_FIND_REQUIRED)
+      message(FATAL_ERROR "Could NOT find librt on your system")
+    endif()
+  endif()
+endif()
+
+# PASTIX depends on HWLOC
+#------------------------
+if (NOT PASTIX_FIND_QUIETLY)
+  message(STATUS "Looking for PASTIX - Try to detect HWLOC")
+endif()
+if (PASTIX_FIND_REQUIRED)
+  find_package(HWLOC REQUIRED QUIET)
+else()
+  find_package(HWLOC QUIET)
+endif()
+
+# PASTIX depends on BLAS
+#-----------------------
+if (NOT PASTIX_FIND_QUIETLY)
+  message(STATUS "Looking for PASTIX - Try to detect BLAS")
+endif()
+if (PASTIX_FIND_REQUIRED)
+  find_package(BLASEXT REQUIRED QUIET)
+else()
+  find_package(BLASEXT QUIET)
+endif()
+
+# Optional dependencies
+# ---------------------
+
+# PASTIX may depend on MPI
+#-------------------------
+if (NOT MPI_FOUND AND PASTIX_LOOK_FOR_MPI)
+  if (NOT PASTIX_FIND_QUIETLY)
+    message(STATUS "Looking for PASTIX - Try to detect MPI")
+  endif()
+  # allows to use an external mpi compilation by setting compilers with
+  # -DMPI_C_COMPILER=path/to/mpicc -DMPI_Fortran_COMPILER=path/to/mpif90
+  # at cmake configure
+  if(NOT MPI_C_COMPILER)
+    set(MPI_C_COMPILER mpicc)
+  endif()
+  if (PASTIX_FIND_REQUIRED AND PASTIX_FIND_REQUIRED_MPI)
+    find_package(MPI REQUIRED QUIET)
+  else()
+    find_package(MPI QUIET)
+  endif()
+  if (MPI_FOUND)
+    mark_as_advanced(MPI_LIBRARY)
+    mark_as_advanced(MPI_EXTRA_LIBRARY)
+  endif()
+endif (NOT MPI_FOUND AND PASTIX_LOOK_FOR_MPI)
+
+# PASTIX may depend on STARPU
+#----------------------------
+if( NOT STARPU_FOUND AND PASTIX_LOOK_FOR_STARPU)
+
+  if (NOT PASTIX_FIND_QUIETLY)
+    message(STATUS "Looking for PASTIX - Try to detect StarPU")
+  endif()
+
+  set(PASTIX_STARPU_VERSION "1.1" CACHE STRING "oldest STARPU version desired")
+
+  # create list of components in order to make a single call to find_package(starpu...)
+  # we explicitly need a StarPU version built with hwloc
+  set(STARPU_COMPONENT_LIST "HWLOC")
+
+  # StarPU may depend on MPI
+  # allows to use an external mpi compilation by setting compilers with
+  # -DMPI_C_COMPILER=path/to/mpicc -DMPI_Fortran_COMPILER=path/to/mpif90
+  # at cmake configure
+  if (PASTIX_LOOK_FOR_MPI)
+    if(NOT MPI_C_COMPILER)
+      set(MPI_C_COMPILER mpicc)
+    endif()
+    list(APPEND STARPU_COMPONENT_LIST "MPI")
+  endif()
+  if (PASTIX_LOOK_FOR_STARPU_CUDA)
+    list(APPEND STARPU_COMPONENT_LIST "CUDA")
+  endif()
+  if (PASTIX_LOOK_FOR_STARPU_FXT)
+    list(APPEND STARPU_COMPONENT_LIST "FXT")
+  endif()
+  # set the list of optional dependencies we may discover
+  if (PASTIX_FIND_REQUIRED AND PASTIX_FIND_REQUIRED_STARPU)
+    find_package(STARPU ${PASTIX_STARPU_VERSION} REQUIRED
+      COMPONENTS ${STARPU_COMPONENT_LIST})
+  else()
+    find_package(STARPU ${PASTIX_STARPU_VERSION}
+      COMPONENTS ${STARPU_COMPONENT_LIST})
+  endif()
+
+endif( NOT STARPU_FOUND AND PASTIX_LOOK_FOR_STARPU)
+
+# PASTIX may depends on SCOTCH
+#-----------------------------
+if (NOT SCOTCH_FOUND AND PASTIX_LOOK_FOR_SCOTCH)
+  if (NOT PASTIX_FIND_QUIETLY)
+    message(STATUS "Looking for PASTIX - Try to detect SCOTCH")
+  endif()
+  if (PASTIX_FIND_REQUIRED AND PASTIX_FIND_REQUIRED_SCOTCH)
+    find_package(SCOTCH REQUIRED QUIET)
+  else()
+    find_package(SCOTCH QUIET)
+  endif()
+endif()
+
+# PASTIX may depends on PTSCOTCH
+#-------------------------------
+if (NOT PTSCOTCH_FOUND AND PASTIX_LOOK_FOR_PTSCOTCH)
+  if (NOT PASTIX_FIND_QUIETLY)
+    message(STATUS "Looking for PASTIX - Try to detect PTSCOTCH")
+  endif()
+  if (PASTIX_FIND_REQUIRED AND PASTIX_FIND_REQUIRED_PTSCOTCH)
+    find_package(PTSCOTCH REQUIRED QUIET)
+  else()
+    find_package(PTSCOTCH QUIET)
+  endif()
+endif()
+
+# PASTIX may depends on METIS
+#----------------------------
+if (NOT METIS_FOUND AND PASTIX_LOOK_FOR_METIS)
+  if (NOT PASTIX_FIND_QUIETLY)
+    message(STATUS "Looking for PASTIX - Try to detect METIS")
+  endif()
+  if (PASTIX_FIND_REQUIRED AND PASTIX_FIND_REQUIRED_METIS)
+    find_package(METIS REQUIRED QUIET)
+  else()
+    find_package(METIS QUIET)
+  endif()
+endif()
+
+# Error if pastix required and no partitioning lib found
+if (PASTIX_FIND_REQUIRED AND NOT SCOTCH_FOUND AND NOT PTSCOTCH_FOUND AND NOT METIS_FOUND)
+  message(FATAL_ERROR "Could NOT find any partitioning library on your system"
+    " (install scotch, ptscotch or metis)")
+endif()
+
+
+# Looking for PaStiX
+# ------------------
+
+# Looking for include
+# -------------------
+
+# Add system include paths to search include
+# ------------------------------------------
+unset(_inc_env)
+set(ENV_PASTIX_DIR "$ENV{PASTIX_DIR}")
+set(ENV_PASTIX_INCDIR "$ENV{PASTIX_INCDIR}")
+if(ENV_PASTIX_INCDIR)
+  list(APPEND _inc_env "${ENV_PASTIX_INCDIR}")
+elseif(ENV_PASTIX_DIR)
+  list(APPEND _inc_env "${ENV_PASTIX_DIR}")
+  list(APPEND _inc_env "${ENV_PASTIX_DIR}/include")
+  list(APPEND _inc_env "${ENV_PASTIX_DIR}/include/pastix")
+else()
+  if(WIN32)
+    string(REPLACE ":" ";" _inc_env "$ENV{INCLUDE}")
+  else()
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{C_INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{CPATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+  endif()
+endif()
+list(APPEND _inc_env "${CMAKE_PLATFORM_IMPLICIT_INCLUDE_DIRECTORIES}")
+list(APPEND _inc_env "${CMAKE_C_IMPLICIT_INCLUDE_DIRECTORIES}")
+list(REMOVE_DUPLICATES _inc_env)
+
+
+# Try to find the pastix header in the given paths
+# ---------------------------------------------------
+# call cmake macro to find the header path
+if(PASTIX_INCDIR)
+  set(PASTIX_pastix.h_DIRS "PASTIX_pastix.h_DIRS-NOTFOUND")
+  find_path(PASTIX_pastix.h_DIRS
+    NAMES pastix.h
+    HINTS ${PASTIX_INCDIR})
+else()
+  if(PASTIX_DIR)
+    set(PASTIX_pastix.h_DIRS "PASTIX_pastix.h_DIRS-NOTFOUND")
+    find_path(PASTIX_pastix.h_DIRS
+      NAMES pastix.h
+      HINTS ${PASTIX_DIR}
+      PATH_SUFFIXES "include" "include/pastix")
+  else()
+    set(PASTIX_pastix.h_DIRS "PASTIX_pastix.h_DIRS-NOTFOUND")
+    find_path(PASTIX_pastix.h_DIRS
+      NAMES pastix.h
+      HINTS ${_inc_env}
+      PATH_SUFFIXES "pastix")
+  endif()
+endif()
+mark_as_advanced(PASTIX_pastix.h_DIRS)
+
+# If found, add path to cmake variable
+# ------------------------------------
+if (PASTIX_pastix.h_DIRS)
+  set(PASTIX_INCLUDE_DIRS "${PASTIX_pastix.h_DIRS}")
+else ()
+  set(PASTIX_INCLUDE_DIRS "PASTIX_INCLUDE_DIRS-NOTFOUND")
+  if(NOT PASTIX_FIND_QUIETLY)
+    message(STATUS "Looking for pastix -- pastix.h not found")
+  endif()
+endif()
+
+
+# Looking for lib
+# ---------------
+
+# Add system library paths to search lib
+# --------------------------------------
+unset(_lib_env)
+set(ENV_PASTIX_LIBDIR "$ENV{PASTIX_LIBDIR}")
+if(ENV_PASTIX_LIBDIR)
+  list(APPEND _lib_env "${ENV_PASTIX_LIBDIR}")
+elseif(ENV_PASTIX_DIR)
+  list(APPEND _lib_env "${ENV_PASTIX_DIR}")
+  list(APPEND _lib_env "${ENV_PASTIX_DIR}/lib")
+else()
+  if(WIN32)
+    string(REPLACE ":" ";" _lib_env "$ENV{LIB}")
+  else()
+    if(APPLE)
+      string(REPLACE ":" ";" _lib_env "$ENV{DYLD_LIBRARY_PATH}")
+    else()
+      string(REPLACE ":" ";" _lib_env "$ENV{LD_LIBRARY_PATH}")
+    endif()
+    list(APPEND _lib_env "${CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES}")
+    list(APPEND _lib_env "${CMAKE_C_IMPLICIT_LINK_DIRECTORIES}")
+  endif()
+endif()
+list(REMOVE_DUPLICATES _lib_env)
+
+# Try to find the pastix lib in the given paths
+# ------------------------------------------------
+
+# create list of libs to find
+set(PASTIX_libs_to_find "pastix_murge;pastix")
+
+# call cmake macro to find the lib path
+if(PASTIX_LIBDIR)
+  foreach(pastix_lib ${PASTIX_libs_to_find})
+    set(PASTIX_${pastix_lib}_LIBRARY "PASTIX_${pastix_lib}_LIBRARY-NOTFOUND")
+    find_library(PASTIX_${pastix_lib}_LIBRARY
+      NAMES ${pastix_lib}
+      HINTS ${PASTIX_LIBDIR})
+  endforeach()
+else()
+  if(PASTIX_DIR)
+    foreach(pastix_lib ${PASTIX_libs_to_find})
+      set(PASTIX_${pastix_lib}_LIBRARY "PASTIX_${pastix_lib}_LIBRARY-NOTFOUND")
+      find_library(PASTIX_${pastix_lib}_LIBRARY
+	NAMES ${pastix_lib}
+	HINTS ${PASTIX_DIR}
+	PATH_SUFFIXES lib lib32 lib64)
+    endforeach()
+  else()
+    foreach(pastix_lib ${PASTIX_libs_to_find})
+      set(PASTIX_${pastix_lib}_LIBRARY "PASTIX_${pastix_lib}_LIBRARY-NOTFOUND")
+      find_library(PASTIX_${pastix_lib}_LIBRARY
+	NAMES ${pastix_lib}
+	HINTS ${_lib_env})
+    endforeach()
+  endif()
+endif()
+
+# If found, add path to cmake variable
+# ------------------------------------
+foreach(pastix_lib ${PASTIX_libs_to_find})
+
+  get_filename_component(${pastix_lib}_lib_path ${PASTIX_${pastix_lib}_LIBRARY} PATH)
+  # set cmake variables (respects naming convention)
+  if (PASTIX_LIBRARIES)
+    list(APPEND PASTIX_LIBRARIES "${PASTIX_${pastix_lib}_LIBRARY}")
+  else()
+    set(PASTIX_LIBRARIES "${PASTIX_${pastix_lib}_LIBRARY}")
+  endif()
+  if (PASTIX_LIBRARY_DIRS)
+    list(APPEND PASTIX_LIBRARY_DIRS "${${pastix_lib}_lib_path}")
+  else()
+    set(PASTIX_LIBRARY_DIRS "${${pastix_lib}_lib_path}")
+  endif()
+  mark_as_advanced(PASTIX_${pastix_lib}_LIBRARY)
+
+endforeach(pastix_lib ${PASTIX_libs_to_find})
+
+# check a function to validate the find
+if(PASTIX_LIBRARIES)
+
+  set(REQUIRED_LDFLAGS)
+  set(REQUIRED_INCDIRS)
+  set(REQUIRED_LIBDIRS)
+  set(REQUIRED_LIBS)
+
+  # PASTIX
+  if (PASTIX_INCLUDE_DIRS)
+    set(REQUIRED_INCDIRS "${PASTIX_INCLUDE_DIRS}")
+  endif()
+  foreach(libdir ${PASTIX_LIBRARY_DIRS})
+    if (libdir)
+      list(APPEND REQUIRED_LIBDIRS "${libdir}")
+    endif()
+  endforeach()
+  set(REQUIRED_LIBS "${PASTIX_LIBRARIES}")
+  # STARPU
+  if (PASTIX_LOOK_FOR_STARPU AND STARPU_FOUND)
+    if (STARPU_INCLUDE_DIRS_DEP)
+      list(APPEND REQUIRED_INCDIRS "${STARPU_INCLUDE_DIRS_DEP}")
+    elseif (STARPU_INCLUDE_DIRS)
+      list(APPEND REQUIRED_INCDIRS "${STARPU_INCLUDE_DIRS}")
+    endif()
+    if(STARPU_LIBRARY_DIRS_DEP)
+      list(APPEND REQUIRED_LIBDIRS "${STARPU_LIBRARY_DIRS_DEP}")
+    elseif(STARPU_LIBRARY_DIRS)
+      list(APPEND REQUIRED_LIBDIRS "${STARPU_LIBRARY_DIRS}")
+    endif()
+    if (STARPU_LIBRARIES_DEP)
+      list(APPEND REQUIRED_LIBS "${STARPU_LIBRARIES_DEP}")
+    elseif (STARPU_LIBRARIES)
+      foreach(lib ${STARPU_LIBRARIES})
+	if (EXISTS ${lib} OR ${lib} MATCHES "^-")
+	  list(APPEND REQUIRED_LIBS "${lib}")
+	else()
+	  list(APPEND REQUIRED_LIBS "-l${lib}")
+	endif()
+      endforeach()
+    endif()
+  endif()
+  # CUDA
+  if (PASTIX_LOOK_FOR_STARPU_CUDA AND CUDA_FOUND)
+    if (CUDA_INCLUDE_DIRS)
+      list(APPEND REQUIRED_INCDIRS "${CUDA_INCLUDE_DIRS}")
+    endif()
+    foreach(libdir ${CUDA_LIBRARY_DIRS})
+      if (libdir)
+	list(APPEND REQUIRED_LIBDIRS "${libdir}")
+      endif()
+    endforeach()
+    list(APPEND REQUIRED_LIBS "${CUDA_CUBLAS_LIBRARIES};${CUDA_LIBRARIES}")
+  endif()
+  # MPI
+  if (PASTIX_LOOK_FOR_MPI AND MPI_FOUND)
+    if (MPI_C_INCLUDE_PATH)
+      list(APPEND REQUIRED_INCDIRS "${MPI_C_INCLUDE_PATH}")
+    endif()
+    if (MPI_C_LINK_FLAGS)
+      if (${MPI_C_LINK_FLAGS} MATCHES "  -")
+	string(REGEX REPLACE " -" "-" MPI_C_LINK_FLAGS ${MPI_C_LINK_FLAGS})
+      endif()
+      list(APPEND REQUIRED_LDFLAGS "${MPI_C_LINK_FLAGS}")
+    endif()
+    list(APPEND REQUIRED_LIBS "${MPI_C_LIBRARIES}")
+  endif()
+  # HWLOC
+  if (HWLOC_FOUND)
+    if (HWLOC_INCLUDE_DIRS)
+      list(APPEND REQUIRED_INCDIRS "${HWLOC_INCLUDE_DIRS}")
+    endif()
+    foreach(libdir ${HWLOC_LIBRARY_DIRS})
+      if (libdir)
+	list(APPEND REQUIRED_LIBDIRS "${libdir}")
+      endif()
+    endforeach()
+    foreach(lib ${HWLOC_LIBRARIES})
+      if (EXISTS ${lib} OR ${lib} MATCHES "^-")
+	list(APPEND REQUIRED_LIBS "${lib}")
+      else()
+	list(APPEND REQUIRED_LIBS "-l${lib}")
+      endif()
+    endforeach()
+  endif()
+  # BLAS
+  if (BLAS_FOUND)
+    if (BLAS_INCLUDE_DIRS)
+      list(APPEND REQUIRED_INCDIRS "${BLAS_INCLUDE_DIRS}")
+    endif()
+    foreach(libdir ${BLAS_LIBRARY_DIRS})
+      if (libdir)
+	list(APPEND REQUIRED_LIBDIRS "${libdir}")
+      endif()
+    endforeach()
+    list(APPEND REQUIRED_LIBS "${BLAS_LIBRARIES}")
+    if (BLAS_LINKER_FLAGS)
+      list(APPEND REQUIRED_LDFLAGS "${BLAS_LINKER_FLAGS}")
+    endif()
+  endif()
+  # SCOTCH
+  if (PASTIX_LOOK_FOR_SCOTCH AND SCOTCH_FOUND)
+    if (SCOTCH_INCLUDE_DIRS)
+      list(APPEND REQUIRED_INCDIRS "${SCOTCH_INCLUDE_DIRS}")
+    endif()
+    foreach(libdir ${SCOTCH_LIBRARY_DIRS})
+      if (libdir)
+	list(APPEND REQUIRED_LIBDIRS "${libdir}")
+      endif()
+    endforeach()
+    list(APPEND REQUIRED_LIBS "${SCOTCH_LIBRARIES}")
+  endif()
+  # PTSCOTCH
+  if (PASTIX_LOOK_FOR_PTSCOTCH AND PTSCOTCH_FOUND)
+    if (PTSCOTCH_INCLUDE_DIRS)
+      list(APPEND REQUIRED_INCDIRS "${PTSCOTCH_INCLUDE_DIRS}")
+    endif()
+    foreach(libdir ${PTSCOTCH_LIBRARY_DIRS})
+      if (libdir)
+	list(APPEND REQUIRED_LIBDIRS "${libdir}")
+      endif()
+    endforeach()
+    list(APPEND REQUIRED_LIBS "${PTSCOTCH_LIBRARIES}")
+  endif()
+  # METIS
+  if (PASTIX_LOOK_FOR_METIS AND METIS_FOUND)
+    if (METIS_INCLUDE_DIRS)
+      list(APPEND REQUIRED_INCDIRS "${METIS_INCLUDE_DIRS}")
+    endif()
+    foreach(libdir ${METIS_LIBRARY_DIRS})
+      if (libdir)
+	list(APPEND REQUIRED_LIBDIRS "${libdir}")
+      endif()
+    endforeach()
+    list(APPEND REQUIRED_LIBS "${METIS_LIBRARIES}")
+  endif()
+  # Fortran
+  if (CMAKE_C_COMPILER_ID MATCHES "GNU")
+    find_library(
+      FORTRAN_gfortran_LIBRARY
+      NAMES gfortran
+      HINTS ${_lib_env}
+      )
+    mark_as_advanced(FORTRAN_gfortran_LIBRARY)
+    if (FORTRAN_gfortran_LIBRARY)
+      list(APPEND REQUIRED_LIBS "${FORTRAN_gfortran_LIBRARY}")
+    endif()
+  elseif (CMAKE_C_COMPILER_ID MATCHES "Intel")
+    find_library(
+      FORTRAN_ifcore_LIBRARY
+      NAMES ifcore
+      HINTS ${_lib_env}
+      )
+    mark_as_advanced(FORTRAN_ifcore_LIBRARY)
+    if (FORTRAN_ifcore_LIBRARY)
+      list(APPEND REQUIRED_LIBS "${FORTRAN_ifcore_LIBRARY}")
+    endif()
+  endif()
+  # EXTRA LIBS such that pthread, m, rt
+  list(APPEND REQUIRED_LIBS ${PASTIX_EXTRA_LIBRARIES})
+
+  # set required libraries for link
+  set(CMAKE_REQUIRED_INCLUDES "${REQUIRED_INCDIRS}")
+  set(CMAKE_REQUIRED_LIBRARIES)
+  list(APPEND CMAKE_REQUIRED_LIBRARIES "${REQUIRED_LDFLAGS}")
+  foreach(lib_dir ${REQUIRED_LIBDIRS})
+    list(APPEND CMAKE_REQUIRED_LIBRARIES "-L${lib_dir}")
+  endforeach()
+  list(APPEND CMAKE_REQUIRED_LIBRARIES "${REQUIRED_LIBS}")
+  list(APPEND CMAKE_REQUIRED_FLAGS "${REQUIRED_FLAGS}")
+  string(REGEX REPLACE "^ -" "-" CMAKE_REQUIRED_LIBRARIES "${CMAKE_REQUIRED_LIBRARIES}")
+
+  # test link
+  unset(PASTIX_WORKS CACHE)
+  include(CheckFunctionExists)
+  check_function_exists(pastix PASTIX_WORKS)
+  mark_as_advanced(PASTIX_WORKS)
+
+  if(PASTIX_WORKS)
+    # save link with dependencies
+    set(PASTIX_LIBRARIES_DEP "${REQUIRED_LIBS}")
+    set(PASTIX_LIBRARY_DIRS_DEP "${REQUIRED_LIBDIRS}")
+    set(PASTIX_INCLUDE_DIRS_DEP "${REQUIRED_INCDIRS}")
+    set(PASTIX_LINKER_FLAGS "${REQUIRED_LDFLAGS}")
+    list(REMOVE_DUPLICATES PASTIX_LIBRARY_DIRS_DEP)
+    list(REMOVE_DUPLICATES PASTIX_INCLUDE_DIRS_DEP)
+    list(REMOVE_DUPLICATES PASTIX_LINKER_FLAGS)
+  else()
+    if(NOT PASTIX_FIND_QUIETLY)
+      message(STATUS "Looking for PASTIX : test of pastix() fails")
+      message(STATUS "CMAKE_REQUIRED_LIBRARIES: ${CMAKE_REQUIRED_LIBRARIES}")
+      message(STATUS "CMAKE_REQUIRED_INCLUDES: ${CMAKE_REQUIRED_INCLUDES}")
+      message(STATUS "Check in CMakeFiles/CMakeError.log to figure out why it fails")
+      message(STATUS "Maybe PASTIX is linked with specific libraries. "
+	"Have you tried with COMPONENTS (MPI/SEQ, STARPU, STARPU_CUDA, SCOTCH, PTSCOTCH, METIS)? "
+	"See the explanation in FindPASTIX.cmake.")
+    endif()
+  endif()
+  set(CMAKE_REQUIRED_INCLUDES)
+  set(CMAKE_REQUIRED_FLAGS)
+  set(CMAKE_REQUIRED_LIBRARIES)
+endif(PASTIX_LIBRARIES)
+
+if (PASTIX_LIBRARIES)
+  list(GET PASTIX_LIBRARIES 0 first_lib)
+  get_filename_component(first_lib_path "${first_lib}" PATH)
+  if (${first_lib_path} MATCHES "/lib(32|64)?$")
+    string(REGEX REPLACE "/lib(32|64)?$" "" not_cached_dir "${first_lib_path}")
+    set(PASTIX_DIR_FOUND "${not_cached_dir}" CACHE PATH "Installation directory of PASTIX library" FORCE)
+  else()
+    set(PASTIX_DIR_FOUND "${first_lib_path}" CACHE PATH "Installation directory of PASTIX library" FORCE)
+  endif()
+endif()
+mark_as_advanced(PASTIX_DIR)
+mark_as_advanced(PASTIX_DIR_FOUND)
+
+# check that PASTIX has been found
+# ---------------------------------
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(PASTIX DEFAULT_MSG
-                                  PASTIX_INCLUDES PASTIX_LIBRARIES)
-
-mark_as_advanced(PASTIX_INCLUDES PASTIX_LIBRARIES)
+  PASTIX_LIBRARIES
+  PASTIX_WORKS)

Index: 3rd_party/eigen/cmake/FindSPQR.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindSPQR.cmake
+++ 3rd_party/eigen/cmake/FindSPQR.cmake
@@ -24,13 +24,18 @@
 if(SPQR_LIBRARIES)
 
   find_library(SUITESPARSE_LIBRARY SuiteSparse PATHS $ENV{SPQRDIR} ${LIB_INSTALL_DIR})
   if (SUITESPARSE_LIBRARY)
     set(SPQR_LIBRARIES ${SPQR_LIBRARIES} ${SUITESPARSE_LIBRARY})
-  endif (SUITESPARSE_LIBRARY)
+  endif()
+
+  find_library(CHOLMOD_LIBRARY cholmod PATHS $ENV{UMFPACK_LIBDIR} $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
+  if(CHOLMOD_LIBRARY)
+    set(SPQR_LIBRARIES ${SPQR_LIBRARIES} ${CHOLMOD_LIBRARY})
+  endif()
   
 endif(SPQR_LIBRARIES)
 
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(SPQR DEFAULT_MSG SPQR_INCLUDES SPQR_LIBRARIES)
 
 mark_as_advanced(SPQR_INCLUDES SPQR_LIBRARIES)

Index: 3rd_party/eigen/cmake/FindScotch.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindScotch.cmake
+++ 3rd_party/eigen/cmake/FindScotch.cmake
@@ -1,24 +1,369 @@
-# Pastix requires SCOTCH or METIS (partitioning and reordering tools)
-
-if (SCOTCH_INCLUDES AND SCOTCH_LIBRARIES)
-  set(SCOTCH_FIND_QUIETLY TRUE)
-endif (SCOTCH_INCLUDES AND SCOTCH_LIBRARIES)
-
-find_path(SCOTCH_INCLUDES 
-  NAMES 
-  scotch.h 
-  PATHS 
-  $ENV{SCOTCHDIR} 
-  ${INCLUDE_INSTALL_DIR} 
-  PATH_SUFFIXES 
-  scotch
-)
-
-
-find_library(SCOTCH_LIBRARIES scotch PATHS $ENV{SCOTCHDIR} ${LIB_INSTALL_DIR})
-
+###
+#
+# @copyright (c) 2009-2014 The University of Tennessee and The University
+#                          of Tennessee Research Foundation.
+#                          All rights reserved.
+# @copyright (c) 2012-2014 Inria. All rights reserved.
+# @copyright (c) 2012-2014 Bordeaux INP, CNRS (LaBRI UMR 5800), Inria, Univ. Bordeaux. All rights reserved.
+#
+###
+#
+# - Find SCOTCH include dirs and libraries
+# Use this module by invoking find_package with the form:
+#  find_package(SCOTCH
+#               [REQUIRED]             # Fail with error if scotch is not found
+#               [COMPONENTS <comp1> <comp2> ...] # dependencies
+#              )
+#
+#  COMPONENTS can be some of the following:
+#   - ESMUMPS: to activate detection of Scotch with the esmumps interface
+#
+# This module finds headers and scotch library.
+# Results are reported in variables:
+#  SCOTCH_FOUND           - True if headers and requested libraries were found
+#  SCOTCH_INCLUDE_DIRS    - scotch include directories
+#  SCOTCH_LIBRARY_DIRS    - Link directories for scotch libraries
+#  SCOTCH_LIBRARIES       - scotch component libraries to be linked
+#  SCOTCH_INTSIZE         - Number of octets occupied by a SCOTCH_Num
+#
+# The user can give specific paths where to find the libraries adding cmake
+# options at configure (ex: cmake path/to/project -DSCOTCH=path/to/scotch):
+#  SCOTCH_DIR             - Where to find the base directory of scotch
+#  SCOTCH_INCDIR          - Where to find the header files
+#  SCOTCH_LIBDIR          - Where to find the library files
+# The module can also look for the following environment variables if paths
+# are not given as cmake variable: SCOTCH_DIR, SCOTCH_INCDIR, SCOTCH_LIBDIR
+
+#=============================================================================
+# Copyright 2012-2013 Inria
+# Copyright 2012-2013 Emmanuel Agullo
+# Copyright 2012-2013 Mathieu Faverge
+# Copyright 2012      Cedric Castagnede
+# Copyright 2013      Florent Pruvost
+#
+# Distributed under the OSI-approved BSD License (the "License");
+# see accompanying file MORSE-Copyright.txt for details.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without even the
+# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the License for more information.
+#=============================================================================
+# (To distribute this file outside of Morse, substitute the full
+#  License text for the above reference.)
+
+if (NOT SCOTCH_FOUND)
+  set(SCOTCH_DIR "" CACHE PATH "Installation directory of SCOTCH library")
+  if (NOT SCOTCH_FIND_QUIETLY)
+    message(STATUS "A cache variable, namely SCOTCH_DIR, has been set to specify the install directory of SCOTCH")
+  endif()
+endif()
+
+# Set the version to find
+set(SCOTCH_LOOK_FOR_ESMUMPS OFF)
+
+if( SCOTCH_FIND_COMPONENTS )
+  foreach( component ${SCOTCH_FIND_COMPONENTS} )
+    if (${component} STREQUAL "ESMUMPS")
+      # means we look for esmumps library
+      set(SCOTCH_LOOK_FOR_ESMUMPS ON)
+    endif()
+  endforeach()
+endif()
+
+# SCOTCH may depend on Threads, try to find it
+if (NOT THREADS_FOUND)
+  if (SCOTCH_FIND_REQUIRED)
+    find_package(Threads REQUIRED)
+  else()
+    find_package(Threads)
+  endif()
+endif()
+
+# Looking for include
+# -------------------
+
+# Add system include paths to search include
+# ------------------------------------------
+unset(_inc_env)
+set(ENV_SCOTCH_DIR "$ENV{SCOTCH_DIR}")
+set(ENV_SCOTCH_INCDIR "$ENV{SCOTCH_INCDIR}")
+if(ENV_SCOTCH_INCDIR)
+  list(APPEND _inc_env "${ENV_SCOTCH_INCDIR}")
+elseif(ENV_SCOTCH_DIR)
+  list(APPEND _inc_env "${ENV_SCOTCH_DIR}")
+  list(APPEND _inc_env "${ENV_SCOTCH_DIR}/include")
+  list(APPEND _inc_env "${ENV_SCOTCH_DIR}/include/scotch")
+else()
+  if(WIN32)
+    string(REPLACE ":" ";" _inc_env "$ENV{INCLUDE}")
+  else()
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{C_INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{CPATH}")
+    list(APPEND _inc_env "${_path_env}")
+    string(REPLACE ":" ";" _path_env "$ENV{INCLUDE_PATH}")
+    list(APPEND _inc_env "${_path_env}")
+  endif()
+endif()
+list(APPEND _inc_env "${CMAKE_PLATFORM_IMPLICIT_INCLUDE_DIRECTORIES}")
+list(APPEND _inc_env "${CMAKE_C_IMPLICIT_INCLUDE_DIRECTORIES}")
+list(REMOVE_DUPLICATES _inc_env)
+
+
+# Try to find the scotch header in the given paths
+# -------------------------------------------------
+# call cmake macro to find the header path
+if(SCOTCH_INCDIR)
+  set(SCOTCH_scotch.h_DIRS "SCOTCH_scotch.h_DIRS-NOTFOUND")
+  find_path(SCOTCH_scotch.h_DIRS
+    NAMES scotch.h
+    HINTS ${SCOTCH_INCDIR})
+else()
+  if(SCOTCH_DIR)
+    set(SCOTCH_scotch.h_DIRS "SCOTCH_scotch.h_DIRS-NOTFOUND")
+    find_path(SCOTCH_scotch.h_DIRS
+      NAMES scotch.h
+      HINTS ${SCOTCH_DIR}
+      PATH_SUFFIXES "include" "include/scotch")
+  else()
+    set(SCOTCH_scotch.h_DIRS "SCOTCH_scotch.h_DIRS-NOTFOUND")
+    find_path(SCOTCH_scotch.h_DIRS
+      NAMES scotch.h
+      HINTS ${_inc_env}
+      PATH_SUFFIXES "scotch")
+  endif()
+endif()
+mark_as_advanced(SCOTCH_scotch.h_DIRS)
+
+# If found, add path to cmake variable
+# ------------------------------------
+if (SCOTCH_scotch.h_DIRS)
+  set(SCOTCH_INCLUDE_DIRS "${SCOTCH_scotch.h_DIRS}")
+else ()
+  set(SCOTCH_INCLUDE_DIRS "SCOTCH_INCLUDE_DIRS-NOTFOUND")
+  if (NOT SCOTCH_FIND_QUIETLY)
+    message(STATUS "Looking for scotch -- scotch.h not found")
+  endif()
+endif()
+list(REMOVE_DUPLICATES SCOTCH_INCLUDE_DIRS)
+
+# Looking for lib
+# ---------------
+
+# Add system library paths to search lib
+# --------------------------------------
+unset(_lib_env)
+set(ENV_SCOTCH_LIBDIR "$ENV{SCOTCH_LIBDIR}")
+if(ENV_SCOTCH_LIBDIR)
+  list(APPEND _lib_env "${ENV_SCOTCH_LIBDIR}")
+elseif(ENV_SCOTCH_DIR)
+  list(APPEND _lib_env "${ENV_SCOTCH_DIR}")
+  list(APPEND _lib_env "${ENV_SCOTCH_DIR}/lib")
+else()
+  if(WIN32)
+    string(REPLACE ":" ";" _lib_env "$ENV{LIB}")
+  else()
+    if(APPLE)
+      string(REPLACE ":" ";" _lib_env "$ENV{DYLD_LIBRARY_PATH}")
+    else()
+      string(REPLACE ":" ";" _lib_env "$ENV{LD_LIBRARY_PATH}")
+    endif()
+    list(APPEND _lib_env "${CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES}")
+    list(APPEND _lib_env "${CMAKE_C_IMPLICIT_LINK_DIRECTORIES}")
+  endif()
+endif()
+list(REMOVE_DUPLICATES _lib_env)
+
+# Try to find the scotch lib in the given paths
+# ----------------------------------------------
+
+set(SCOTCH_libs_to_find "scotch;scotcherrexit")
+if (SCOTCH_LOOK_FOR_ESMUMPS)
+  list(INSERT SCOTCH_libs_to_find 0 "esmumps")
+endif()
+
+# call cmake macro to find the lib path
+if(SCOTCH_LIBDIR)
+  foreach(scotch_lib ${SCOTCH_libs_to_find})
+    set(SCOTCH_${scotch_lib}_LIBRARY "SCOTCH_${scotch_lib}_LIBRARY-NOTFOUND")
+    find_library(SCOTCH_${scotch_lib}_LIBRARY
+      NAMES ${scotch_lib}
+      HINTS ${SCOTCH_LIBDIR})
+  endforeach()
+else()
+  if(SCOTCH_DIR)
+    foreach(scotch_lib ${SCOTCH_libs_to_find})
+      set(SCOTCH_${scotch_lib}_LIBRARY "SCOTCH_${scotch_lib}_LIBRARY-NOTFOUND")
+      find_library(SCOTCH_${scotch_lib}_LIBRARY
+	NAMES ${scotch_lib}
+	HINTS ${SCOTCH_DIR}
+	PATH_SUFFIXES lib lib32 lib64)
+    endforeach()
+  else()
+    foreach(scotch_lib ${SCOTCH_libs_to_find})
+      set(SCOTCH_${scotch_lib}_LIBRARY "SCOTCH_${scotch_lib}_LIBRARY-NOTFOUND")
+      find_library(SCOTCH_${scotch_lib}_LIBRARY
+	NAMES ${scotch_lib}
+	HINTS ${_lib_env})
+    endforeach()
+  endif()
+endif()
+
+set(SCOTCH_LIBRARIES "")
+set(SCOTCH_LIBRARY_DIRS "")
+# If found, add path to cmake variable
+# ------------------------------------
+foreach(scotch_lib ${SCOTCH_libs_to_find})
+
+  if (SCOTCH_${scotch_lib}_LIBRARY)
+    get_filename_component(${scotch_lib}_lib_path "${SCOTCH_${scotch_lib}_LIBRARY}" PATH)
+    # set cmake variables
+    list(APPEND SCOTCH_LIBRARIES "${SCOTCH_${scotch_lib}_LIBRARY}")
+    list(APPEND SCOTCH_LIBRARY_DIRS "${${scotch_lib}_lib_path}")
+  else ()
+    list(APPEND SCOTCH_LIBRARIES "${SCOTCH_${scotch_lib}_LIBRARY}")
+    if (NOT SCOTCH_FIND_QUIETLY)
+      message(STATUS "Looking for scotch -- lib ${scotch_lib} not found")
+    endif()
+  endif ()
+
+  mark_as_advanced(SCOTCH_${scotch_lib}_LIBRARY)
+
+endforeach()
+list(REMOVE_DUPLICATES SCOTCH_LIBRARY_DIRS)
+
+# check a function to validate the find
+if(SCOTCH_LIBRARIES)
+
+  set(REQUIRED_INCDIRS)
+  set(REQUIRED_LIBDIRS)
+  set(REQUIRED_LIBS)
+
+  # SCOTCH
+  if (SCOTCH_INCLUDE_DIRS)
+    set(REQUIRED_INCDIRS  "${SCOTCH_INCLUDE_DIRS}")
+  endif()
+  if (SCOTCH_LIBRARY_DIRS)
+    set(REQUIRED_LIBDIRS "${SCOTCH_LIBRARY_DIRS}")
+  endif()
+  set(REQUIRED_LIBS "${SCOTCH_LIBRARIES}")
+  # THREADS
+  if(CMAKE_THREAD_LIBS_INIT)
+    list(APPEND REQUIRED_LIBS "${CMAKE_THREAD_LIBS_INIT}")
+  endif()
+  set(Z_LIBRARY "Z_LIBRARY-NOTFOUND")
+  find_library(Z_LIBRARY NAMES z)
+  mark_as_advanced(Z_LIBRARY)
+  if(Z_LIBRARY)
+    list(APPEND REQUIRED_LIBS "-lz")
+  endif()
+  set(M_LIBRARY "M_LIBRARY-NOTFOUND")
+  find_library(M_LIBRARY NAMES m)
+  mark_as_advanced(M_LIBRARY)
+  if(M_LIBRARY)
+    list(APPEND REQUIRED_LIBS "-lm")
+  endif()
+  set(RT_LIBRARY "RT_LIBRARY-NOTFOUND")
+  find_library(RT_LIBRARY NAMES rt)
+  mark_as_advanced(RT_LIBRARY)
+  if(RT_LIBRARY)
+    list(APPEND REQUIRED_LIBS "-lrt")
+  endif()
+
+  # set required libraries for link
+  set(CMAKE_REQUIRED_INCLUDES "${REQUIRED_INCDIRS}")
+  set(CMAKE_REQUIRED_LIBRARIES)
+  foreach(lib_dir ${REQUIRED_LIBDIRS})
+    list(APPEND CMAKE_REQUIRED_LIBRARIES "-L${lib_dir}")
+  endforeach()
+  list(APPEND CMAKE_REQUIRED_LIBRARIES "${REQUIRED_LIBS}")
+  string(REGEX REPLACE "^ -" "-" CMAKE_REQUIRED_LIBRARIES "${CMAKE_REQUIRED_LIBRARIES}")
+
+  # test link
+  unset(SCOTCH_WORKS CACHE)
+  include(CheckFunctionExists)
+  check_function_exists(SCOTCH_graphInit SCOTCH_WORKS)
+  mark_as_advanced(SCOTCH_WORKS)
+
+  if(SCOTCH_WORKS)
+    # save link with dependencies
+    set(SCOTCH_LIBRARIES "${REQUIRED_LIBS}")
+  else()
+    if(NOT SCOTCH_FIND_QUIETLY)
+      message(STATUS "Looking for SCOTCH : test of SCOTCH_graphInit with SCOTCH library fails")
+      message(STATUS "CMAKE_REQUIRED_LIBRARIES: ${CMAKE_REQUIRED_LIBRARIES}")
+      message(STATUS "CMAKE_REQUIRED_INCLUDES: ${CMAKE_REQUIRED_INCLUDES}")
+      message(STATUS "Check in CMakeFiles/CMakeError.log to figure out why it fails")
+    endif()
+  endif()
+  set(CMAKE_REQUIRED_INCLUDES)
+  set(CMAKE_REQUIRED_FLAGS)
+  set(CMAKE_REQUIRED_LIBRARIES)
+endif(SCOTCH_LIBRARIES)
+
+if (SCOTCH_LIBRARIES)
+  list(GET SCOTCH_LIBRARIES 0 first_lib)
+  get_filename_component(first_lib_path "${first_lib}" PATH)
+  if (${first_lib_path} MATCHES "/lib(32|64)?$")
+    string(REGEX REPLACE "/lib(32|64)?$" "" not_cached_dir "${first_lib_path}")
+    set(SCOTCH_DIR_FOUND "${not_cached_dir}" CACHE PATH "Installation directory of SCOTCH library" FORCE)
+  else()
+    set(SCOTCH_DIR_FOUND "${first_lib_path}" CACHE PATH "Installation directory of SCOTCH library" FORCE)
+  endif()
+endif()
+mark_as_advanced(SCOTCH_DIR)
+mark_as_advanced(SCOTCH_DIR_FOUND)
+
+# Check the size of SCOTCH_Num
+# ---------------------------------
+set(CMAKE_REQUIRED_INCLUDES ${SCOTCH_INCLUDE_DIRS})
+
+include(CheckCSourceRuns)
+#stdio.h and stdint.h should be included by scotch.h directly
+set(SCOTCH_C_TEST_SCOTCH_Num_4 "
+#include <stdio.h>
+#include <stdint.h>
+#include <scotch.h>
+int main(int argc, char **argv) {
+  if (sizeof(SCOTCH_Num) == 4)
+    return 0;
+  else
+    return 1;
+}
+")
+
+set(SCOTCH_C_TEST_SCOTCH_Num_8 "
+#include <stdio.h>
+#include <stdint.h>
+#include <scotch.h>
+int main(int argc, char **argv) {
+  if (sizeof(SCOTCH_Num) == 8)
+    return 0;
+  else
+    return 1;
+}
+")
+check_c_source_runs("${SCOTCH_C_TEST_SCOTCH_Num_4}" SCOTCH_Num_4)
+if(NOT SCOTCH_Num_4)
+  check_c_source_runs("${SCOTCH_C_TEST_SCOTCH_Num_8}" SCOTCH_Num_8)
+  if(NOT SCOTCH_Num_8)
+    set(SCOTCH_INTSIZE -1)
+  else()
+    set(SCOTCH_INTSIZE 8)
+  endif()
+else()
+  set(SCOTCH_INTSIZE 4)
+endif()
+set(CMAKE_REQUIRED_INCLUDES "")
+
+# check that SCOTCH has been found
+# ---------------------------------
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(SCOTCH DEFAULT_MSG
-                                  SCOTCH_INCLUDES SCOTCH_LIBRARIES)
-
-mark_as_advanced(SCOTCH_INCLUDES SCOTCH_LIBRARIES)
+  SCOTCH_LIBRARIES
+  SCOTCH_WORKS)
+#
+# TODO: Add possibility to check for specific functions in the library
+#

Index: 3rd_party/eigen/cmake/FindSuperLU.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindSuperLU.cmake
+++ 3rd_party/eigen/cmake/FindSuperLU.cmake
@@ -15,12 +15,83 @@
   PATH_SUFFIXES
   superlu
   SRC
 )
 
-find_library(SUPERLU_LIBRARIES superlu PATHS $ENV{SUPERLUDIR} ${LIB_INSTALL_DIR} PATH_SUFFIXES lib)
-  
+find_library(SUPERLU_LIBRARIES
+  NAMES "superlu_5.2.1" "superlu_5.2" "superlu_5.1.1" "superlu_5.1" "superlu_5.0" "superlu_4.3" "superlu_4.2" "superlu_4.1" "superlu_4.0" "superlu_3.1" "superlu_3.0" "superlu"
+  PATHS $ENV{SUPERLUDIR} ${LIB_INSTALL_DIR}
+  PATH_SUFFIXES lib)
+
+if(SUPERLU_INCLUDES AND SUPERLU_LIBRARIES)
+
+include(CheckCXXSourceCompiles)
+include(CMakePushCheckState)
+cmake_push_check_state()
+
+set(CMAKE_REQUIRED_INCLUDES ${CMAKE_REQUIRED_INCLUDES} ${SUPERLU_INCLUDES})
+
+# check whether struct mem_usage_t is globally defined
+check_cxx_source_compiles("
+typedef int int_t;
+#include <supermatrix.h>
+#include <slu_util.h>
+int main() {
+  mem_usage_t mem;
+  return 0;
+}"
+SUPERLU_HAS_GLOBAL_MEM_USAGE_T)
+
+
+check_cxx_source_compiles("
+typedef int int_t;
+#include <supermatrix.h>
+#include <superlu_enum_consts.h>
+int main() {
+  return SLU_SINGLE;
+}"
+SUPERLU_HAS_CLEAN_ENUMS)
+
+check_cxx_source_compiles("
+typedef int int_t;
+#include <supermatrix.h>
+#include <slu_util.h>
+int main(void)
+{
+  GlobalLU_t glu;
+  return 0;
+}"
+SUPERLU_HAS_GLOBALLU_T)
+
+if(SUPERLU_HAS_GLOBALLU_T)
+  # at least 5.0
+  set(SUPERLU_VERSION_VAR "5.0")
+elseif(SUPERLU_HAS_CLEAN_ENUMS)
+  # at least 4.3
+  set(SUPERLU_VERSION_VAR "4.3")
+elseif(SUPERLU_HAS_GLOBAL_MEM_USAGE_T)
+  # at least 4.0
+  set(SUPERLU_VERSION_VAR "4.0")
+else()
+  set(SUPERLU_VERSION_VAR "3.0")
+endif()
+
+cmake_pop_check_state()
+
+if(SuperLU_FIND_VERSION)
+  if(${SUPERLU_VERSION_VAR} VERSION_LESS ${SuperLU_FIND_VERSION})
+    set(SUPERLU_VERSION_OK FALSE)
+  else()
+    set(SUPERLU_VERSION_OK TRUE)
+  endif()
+else()
+  set(SUPERLU_VERSION_OK TRUE)
+endif()
+
+endif()
+
 include(FindPackageHandleStandardArgs)
-find_package_handle_standard_args(SUPERLU DEFAULT_MSG
-                                  SUPERLU_INCLUDES SUPERLU_LIBRARIES)
+find_package_handle_standard_args(SUPERLU
+                                  REQUIRED_VARS SUPERLU_INCLUDES SUPERLU_LIBRARIES SUPERLU_VERSION_OK
+                                  VERSION_VAR SUPERLU_VERSION_VAR)
 
 mark_as_advanced(SUPERLU_INCLUDES SUPERLU_LIBRARIES)

Index: 3rd_party/eigen/cmake/FindUmfpack.cmake
==================================================================
--- 3rd_party/eigen/cmake/FindUmfpack.cmake
+++ 3rd_party/eigen/cmake/FindUmfpack.cmake
@@ -18,31 +18,36 @@
 
 find_library(UMFPACK_LIBRARIES umfpack PATHS $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
 
 if(UMFPACK_LIBRARIES)
 
-  if (NOT UMFPACK_LIBDIR)
+  if(NOT UMFPACK_LIBDIR)
     get_filename_component(UMFPACK_LIBDIR ${UMFPACK_LIBRARIES} PATH)
   endif(NOT UMFPACK_LIBDIR)
 
   find_library(COLAMD_LIBRARY colamd PATHS ${UMFPACK_LIBDIR} $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
-  if (COLAMD_LIBRARY)
+  if(COLAMD_LIBRARY)
     set(UMFPACK_LIBRARIES ${UMFPACK_LIBRARIES} ${COLAMD_LIBRARY})
-  endif (COLAMD_LIBRARY)
+  endif ()
   
   find_library(AMD_LIBRARY amd PATHS ${UMFPACK_LIBDIR} $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
-  if (AMD_LIBRARY)
+  if(AMD_LIBRARY)
     set(UMFPACK_LIBRARIES ${UMFPACK_LIBRARIES} ${AMD_LIBRARY})
-  endif (AMD_LIBRARY)
+  endif ()
 
   find_library(SUITESPARSE_LIBRARY SuiteSparse PATHS ${UMFPACK_LIBDIR} $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
-  if (SUITESPARSE_LIBRARY)
+  if(SUITESPARSE_LIBRARY)
     set(UMFPACK_LIBRARIES ${UMFPACK_LIBRARIES} ${SUITESPARSE_LIBRARY})
-  endif (SUITESPARSE_LIBRARY)
+  endif ()
+
+  find_library(CHOLMOD_LIBRARY cholmod PATHS $ENV{UMFPACK_LIBDIR} $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
+  if(CHOLMOD_LIBRARY)
+    set(UMFPACK_LIBRARIES ${UMFPACK_LIBRARIES} ${CHOLMOD_LIBRARY})
+  endif()
 
 endif(UMFPACK_LIBRARIES)
 
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(UMFPACK DEFAULT_MSG
                                   UMFPACK_INCLUDES UMFPACK_LIBRARIES)
 
-mark_as_advanced(UMFPACK_INCLUDES UMFPACK_LIBRARIES AMD_LIBRARY COLAMD_LIBRARY SUITESPARSE_LIBRARY)
+mark_as_advanced(UMFPACK_INCLUDES UMFPACK_LIBRARIES AMD_LIBRARY COLAMD_LIBRARY CHOLMOD_LIBRARY SUITESPARSE_LIBRARY)

ADDED   3rd_party/eigen/cmake/UseEigen3.cmake
Index: 3rd_party/eigen/cmake/UseEigen3.cmake
==================================================================
--- 3rd_party/eigen/cmake/UseEigen3.cmake
+++ 3rd_party/eigen/cmake/UseEigen3.cmake
@@ -0,0 +1,6 @@
+#                                               -*- cmake -*-
+#
+#  UseEigen3.cmake
+
+add_definitions     ( ${EIGEN3_DEFINITIONS} )
+include_directories ( ${EIGEN3_INCLUDE_DIRS} )

Index: 3rd_party/eigen/cmake/language_support.cmake
==================================================================
--- 3rd_party/eigen/cmake/language_support.cmake
+++ 3rd_party/eigen/cmake/language_support.cmake
@@ -41,11 +41,11 @@
     )
 
   if(return_code EQUAL 0)
     # Second run
     execute_process (
-      COMMAND ${CMAKE_COMMAND} .
+      COMMAND ${CMAKE_COMMAND} . -G "${CMAKE_GENERATOR}"
       WORKING_DIRECTORY ${CMAKE_BINARY_DIR}/language_tests/${language}
       RESULT_VARIABLE return_code
       OUTPUT_QUIET
       ERROR_QUIET
       )
@@ -62,5 +62,6 @@
 # Temporary tests of the above function.
 #workaround_9220(CXX CXX_language_works)
 #message("CXX_language_works = ${CXX_language_works}")
 #workaround_9220(CXXp CXXp_language_works)
 #message("CXXp_language_works = ${CXXp_language_works}")
+

Index: 3rd_party/eigen/debug/gdb/printers.py
==================================================================
--- 3rd_party/eigen/debug/gdb/printers.py
+++ 3rd_party/eigen/debug/gdb/printers.py
@@ -47,11 +47,11 @@
 		self.type = type.unqualified().strip_typedefs()
 		tag = self.type.tag
 		regex = re.compile('\<.*\>')
 		m = regex.findall(tag)[0][1:-1]
 		template_params = m.split(',')
-		template_params = map(lambda x:x.replace(" ", ""), template_params)
+		template_params = [x.replace(" ", "") for x in template_params]
 		
 		if template_params[1] == '-0x00000000000000001' or template_params[1] == '-0x000000001' or template_params[1] == '-1':
 			self.rows = val['m_storage']['m_rows']
 		else:
 			self.rows = int(template_params[1])
@@ -86,12 +86,15 @@
 			self.currentCol = 0
 			self.rowMajor = rowMajor
 			
 		def __iter__ (self):
 			return self
-			
+
 		def next(self):
+                        return self.__next__()  # Python 2.x compatibility
+
+		def __next__(self):
 			
 			row = self.currentRow
 			col = self.currentCol
 			if self.rowMajor == 0:
 				if self.currentCol >= self.cols:
@@ -149,12 +152,15 @@
 			self.currentElement = 0
 			self.elementNames = ['x', 'y', 'z', 'w']
 			
 		def __iter__ (self):
 			return self
-			
+	
 		def next(self):
+                        return self.__next__()  # Python 2.x compatibility
+
+		def __next__(self):
 			element = self.currentElement
 			
 			if self.currentElement >= 4: #there are 4 elements in a quanternion
 				raise StopIteration
 			

Index: 3rd_party/eigen/demos/opengl/quaternion_demo.cpp
==================================================================
--- 3rd_party/eigen/demos/opengl/quaternion_demo.cpp
+++ 3rd_party/eigen/demos/opengl/quaternion_demo.cpp
@@ -232,11 +232,11 @@
   gpu.drawVector(Vector3f::Zero(), length*Vector3f::UnitX(), Color(1,0,0,1));
   gpu.drawVector(Vector3f::Zero(), length*Vector3f::UnitY(), Color(0,1,0,1));
   gpu.drawVector(Vector3f::Zero(), length*Vector3f::UnitZ(), Color(0,0,1,1));
 
   // draw the fractal object
-  float sqrt3 = internal::sqrt(3.);
+  float sqrt3 = std::sqrt(3.);
   glLightfv(GL_LIGHT0, GL_AMBIENT, Vector4f(0.5,0.5,0.5,1).data());
   glLightfv(GL_LIGHT0, GL_DIFFUSE, Vector4f(0.5,1,0.5,1).data());
   glLightfv(GL_LIGHT0, GL_SPECULAR, Vector4f(1,1,1,1).data());
   glLightfv(GL_LIGHT0, GL_POSITION, Vector4f(-sqrt3,-sqrt3,sqrt3,0).data());
 

Index: 3rd_party/eigen/demos/opengl/trackball.cpp
==================================================================
--- 3rd_party/eigen/demos/opengl/trackball.cpp
+++ 3rd_party/eigen/demos/opengl/trackball.cpp
@@ -21,11 +21,11 @@
 
   if (mLastPointOk && newPointOk)
   {
     Vector3f axis = mLastPoint3D.cross(newPoint3D).normalized();
     float cos_angle = mLastPoint3D.dot(newPoint3D);
-    if ( internal::abs(cos_angle) < 1.0 )
+    if ( std::abs(cos_angle) < 1.0 )
     {
       float angle = 2. * acos(cos_angle);
       if (mMode==Around)
         mpCamera->rotateAroundTarget(Quaternionf(AngleAxisf(angle, axis)));
       else

Index: 3rd_party/eigen/doc/A05_PortingFrom2To3.dox
==================================================================
--- 3rd_party/eigen/doc/A05_PortingFrom2To3.dox
+++ 3rd_party/eigen/doc/A05_PortingFrom2To3.dox
@@ -1,23 +1,18 @@
 namespace Eigen {
 
 /** \page Eigen2ToEigen3 Porting from Eigen2 to Eigen3
 
-<div class="bigwarning">Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3.</div>
-
 This page lists the most important API changes between Eigen2 and Eigen3,
 and gives tips to help porting your application from Eigen2 to Eigen3.
 
 \eigenAutoToc
 
 \section CompatibilitySupport Eigen2 compatibility support
 
-In order to ease the switch from Eigen2 to Eigen3, Eigen3 features \subpage Eigen2SupportModes "Eigen2 support modes".
-
-The quick way to enable this is to define the \c EIGEN2_SUPPORT preprocessor token \b before including any Eigen header (typically it should be set in your project options).
-
-A more powerful, \em staged migration path is also provided, which may be useful to migrate larger projects from Eigen2 to Eigen3. This is explained in the \ref Eigen2SupportModes "Eigen 2 support modes" page. 
+Up to version 3.2 %Eigen provides <a href="http://eigen.tuxfamily.org/dox-3.2/Eigen2SupportModes.html">Eigen2 support modes</a>. These are removed now, because they were barely used anymore and became hard to maintain after internal re-designs.
+You can still use them by first <a href="http://eigen.tuxfamily.org/dox-3.2/Eigen2ToEigen3.html">porting your code to Eigen 3.2</a>.
 
 \section Using The USING_PART_OF_NAMESPACE_EIGEN macro
 
 The USING_PART_OF_NAMESPACE_EIGEN macro has been removed. In Eigen 3, just do:
 \code
@@ -226,11 +221,11 @@
 triangular part to work on</td></tr>
 </table>
 
 \section GeometryModule Changes in the Geometry module
 
-The Geometry module is the one that changed the most. If you rely heavily on it, it's probably a good idea to use the \ref Eigen2SupportModes "Eigen 2 support modes" to perform your migration.
+The Geometry module is the one that changed the most. If you rely heavily on it, it's probably a good idea to use the <a href="http://eigen.tuxfamily.org/dox-3.2/Eigen2SupportModes.html">"Eigen 2 support modes"</a> to perform your migration.
 
 \section Transform The Transform class
 
 In Eigen 2, the Transform class didn't really know whether it was a projective or affine transformation. In Eigen 3, it takes a new \a Mode template parameter, which indicates whether it's \a Projective or \a Affine transform. There is no default value.
 
@@ -264,11 +259,11 @@
 
 \section AlignMacros Alignment-related macros
 
 The EIGEN_ALIGN_128 macro has been renamed to EIGEN_ALIGN16. Don't be surprised, it's just that we switched to counting in bytes ;-)
 
-The EIGEN_DONT_ALIGN option still exists in Eigen 3, but it has a new cousin: EIGEN_DONT_ALIGN_STATICALLY. It allows to get rid of all static alignment issues while keeping alignment of dynamic-size heap-allocated arrays, thus keeping vectorization for dynamic-size objects.
+The \link TopicPreprocessorDirectivesPerformance EIGEN_DONT_ALIGN \endlink option still exists in Eigen 3, but it has a new cousin: \link TopicPreprocessorDirectivesPerformance  EIGEN_DONT_ALIGN_STATICALLY.\endlink It allows to get rid of all static alignment issues while keeping alignment of dynamic-size heap-allocated arrays. Vectorization of statically allocated arrays is still preserved (unless you define \link TopicPreprocessorDirectivesPerformance EIGEN_UNALIGNED_VECTORIZE \endlink =0), at the cost of unaligned memory stores.
 
 \section AlignedMap Aligned Map objects
 
 A common issue with Eigen 2 was that when mapping an array with Map, there was no way to tell Eigen that your array was aligned. There was a ForceAligned option but it didn't mean that; it was just confusing and has been removed.
 
@@ -281,11 +276,11 @@
 result = Vector4f::MapAligned(some_aligned_array);
 \endcode
 
 \section StdContainers STL Containers
 
-In Eigen2, <tt>#include<Eigen/StdVector></tt> tweaked std::vector to automatically align elements. The problem was that that was quite invasive. In Eigen3, we only override standard behavior if you use Eigen::aligned_allocator<T> as your allocator type. So for example, if you use std::vector<Matrix4f>, you need to do the following change (note that aligned_allocator is under namespace Eigen):
+In Eigen2, <tt>\#include\<Eigen/StdVector\></tt> tweaked std::vector to automatically align elements. The problem was that that was quite invasive. In Eigen3, we only override standard behavior if you use Eigen::aligned_allocator<T> as your allocator type. So for example, if you use std::vector<Matrix4f>, you need to do the following change (note that aligned_allocator is under namespace Eigen):
 
 <table class="manual">
 <tr><th>Eigen 2</th><th>Eigen 3</th></tr>
 <tr>
   <td> \code std::vector<Matrix4f> \endcode </td>

DELETED 3rd_party/eigen/doc/A10_Eigen2SupportModes.dox
Index: 3rd_party/eigen/doc/A10_Eigen2SupportModes.dox
==================================================================
--- 3rd_party/eigen/doc/A10_Eigen2SupportModes.dox
+++ 3rd_party/eigen/doc/A10_Eigen2SupportModes.dox
@@ -1,95 +0,0 @@
-namespace Eigen {
-
-/** \page Eigen2SupportModes Eigen 2 support modes
-
-<div class="bigwarning">Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3.</div>
-
-This page documents the Eigen2 support modes, a powerful tool to help migrating your project from Eigen 2 to Eigen 3.
-Don't miss our page on \ref Eigen2ToEigen3 "API changes" between Eigen 2 and Eigen 3.
-
-\eigenAutoToc
-
-\section EIGEN2_SUPPORT_Macro The quick way: define EIGEN2_SUPPORT
-
-By defining EIGEN2_SUPPORT before including any Eigen 3 header, you get back a large part of the Eigen 2 API, while keeping the Eigen 3 API and ABI unchanged.
-
-This defaults to the \ref Stage30 "stage 30" described below.
-
-The rest of this page describes an optional, more powerful \em staged migration path.
-
-\section StagedMigrationPathOverview Overview of the staged migration path
-
-The primary reason why EIGEN2_SUPPORT alone may not be enough to migrate a large project from Eigen 2 to Eigen 3 is that some of the Eigen 2 API is inherently incompatible with the Eigen 3 API. This happens when the same identifier is used in Eigen 2 and in Eigen 3 with different meanings. To help migrate projects that rely on such API, we provide a staged migration path allowing to perform the migration \em incrementally.
-
-It goes as follows:
-\li Step 0: start with a project using Eigen 2.
-\li Step 1: build your project against Eigen 3 with \ref Stage10 "Eigen 2 support stage 10". This mode enables maximum compatibility with the Eigen 2 API, with just a few exceptions.
-\li Step 2: build your project against Eigen 3 with \ref Stage20 "Eigen 2 support stage 20". This mode forces you to add eigen2_ prefixes to the Eigen2 identifiers that conflict with Eigen 3 API.
-\li Step 3: build your project against Eigen 3 with \ref Stage30 "Eigen 2 support stage 30". This mode enables the full Eigen 3 API.
-\li Step 4: build your project against Eigen 3 with \ref Stage40 "Eigen 2 support stage 40". This mode enables the full Eigen 3 strictness on matters, such as const-correctness, where Eigen 2 was looser.
-\li Step 5: build your project against Eigen 3 without any Eigen 2 support mode.
-
-\section Stage10 Stage 10: define EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API
-
-Enable this mode by defining the EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API preprocessor macro before including any Eigen 3 header.
-
-This mode maximizes support for the Eigen 2 API. As a result, it does not offer the full Eigen 3 API. Also, it doesn't offer quite 100% of the Eigen 2 API.
-
-The part of the Eigen 3 API that is not present in this mode, is Eigen 3's Geometry module. Indeed, this mode completely replaces it by a copy of Eigen 2's Geometry module.
-
-The parts of the API that are still not 100% Eigen 2 compatible in this mode are:
-\li Dot products over complex numbers. Eigen 2's dot product was linear in the first variable. Eigen 3's dot product is linear in the second variable. In other words, the Eigen 2 code \code x.dot(y) \endcode is equivalent to the Eigen 3 code \code y.dot(x) \endcode In yet other words, dot products are complex-conjugated in Eigen 3 compared to Eigen 2. The switch to the new convention was commanded by common usage, especially with the notation \f$ x^Ty \f$ for dot products of column-vectors.
-\li The Sparse module.
-\li Certain fine details of linear algebraic decompositions. For example, LDLT decomposition is now pivoting in Eigen 3 whereas it wasn't in Eigen 2, so code that was relying on its underlying matrix structure will break.
-\li Usage of Eigen types in STL containers, \ref Eigen2ToEigen3 "as explained on this page".
-
-\section Stage20 Stage 20: define EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS
-
-Enable this mode by defining the EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API preprocessor macro before including any Eigen 3 header.
-
-This mode removes the Eigen 2 API that is directly conflicting with Eigen 3 API. Instead, these bits of Eigen 2 API remain available with eigen2_ prefixes. The main examples of such API are:
-\li the whole Geometry module. For example, replace \c Quaternion by \c eigen2_Quaternion, replace \c Transform3f by \c eigen2_Transform3f, etc.
-\li the lu() method to obtain a LU decomposition. Replace by eigen2_lu().
-
-There is also one more eigen2_-prefixed identifier that you should know about, even though its use is not checked at compile time by this mode: the dot() method. As was discussed above, over complex numbers, its meaning is different between Eigen 2 and Eigen 3. You can use eigen2_dot() to get the Eigen 2 behavior.
-
-\section Stage30 Stage 30: define EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
-
-Enable this mode by defining the EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API preprocessor macro before including any Eigen 3 header. Also, this mode is what you get by default when you just define EIGEN2_SUPPORT.
-
-This mode gives you the full unaltered Eigen 3 API, while still keeping as much support as possible for the Eigen 2 API.
-
-The eigen2_-prefixed identifiers are still available, but at this stage you should now replace them by Eigen 3 identifiers. Have a look at our page on \ref Eigen2ToEigen3 "API changes" between Eigen 2 and Eigen 3.
-
-\section Stage40 Stage 40: define EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS
-
-Enable this mode by defining the EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS preprocessor macro before including any Eigen 3 header.
-
-This mode tightens the last bits of strictness, especially const-correctness, that had to be loosened to support what Eigen 2 allowed. For example, this code compiled in Eigen 2:
-\code
-const float array[4];
-x = Map<Vector4f>(array);
-\endcode
-That allowed to circumvent constness. This is no longer allowed in Eigen 3. If you have to map const data in Eigen 3, map it as a const-qualified type. However, rather than explictly constructing Map objects, we strongly encourage you to use the static Map methods instead, as they take care of all of this for you:
-\code
-const float array[4];
-x = Vector4f::Map(array);
-\endcode
-This lets Eigen do the right thing for you and works equally well in Eigen 2 and in Eigen 3.
-
-\section FinallyDropAllEigen2Support Finally drop all Eigen 2 support
-
-Stage 40 is the first where it's "comfortable" to stay for a little longer period, since it preserves 100% Eigen 3 compatibility. However, we still encourage you to complete your migration as quickly as possible. While we do run the Eigen 2 test suite against Eigen 3's stage 10 support mode, we can't guarantee the same level of support and quality assurance for Eigen 2 support as we do for Eigen 3 itself, especially not in the long term. \ref Eigen2ToEigen3 "This page" describes a large part of the changes that you may need to perform.
-
-\section ABICompatibility What about ABI compatibility?
-
-It goes as follows:
-\li Stage 10 already is ABI compatible with Eigen 3 for the basic (Matrix, Array, SparseMatrix...) types. However, since this stage uses a copy of Eigen 2's Geometry module instead of Eigen 3's own Geometry module, the ABI in the Geometry module is not Eigen 3 compatible.
-\li Stage 20 removes the Eigen 3-incompatible Eigen 2 Geometry module (it remains available with eigen2_ prefix). So at this stage, all the identifiers that exist in Eigen 3 have the Eigen 3 ABI (and API).
-\li Stage 30 introduces the remaining Eigen 3 identifiers. So at this stage, you have the full Eigen 3 ABI.
-\li Stage 40 is no different than Stage 30 in these matters.
-
-
-*/
-
-}

Index: 3rd_party/eigen/doc/AsciiQuickReference.txt
==================================================================
--- 3rd_party/eigen/doc/AsciiQuickReference.txt
+++ 3rd_party/eigen/doc/AsciiQuickReference.txt
@@ -30,21 +30,23 @@
      4, 5, 6,     // matrices, which are stacked along cols
      7, 8, 9;     // and then the rows are stacked.
 B << A, A, A;     // B is three horizontally stacked A's.
 A.fill(10);       // Fill A with all 10's.
 
-// Eigen                            // Matlab
-MatrixXd::Identity(rows,cols)       // eye(rows,cols)
-C.setIdentity(rows,cols)            // C = eye(rows,cols)
-MatrixXd::Zero(rows,cols)           // zeros(rows,cols)
-C.setZero(rows,cols)                // C = ones(rows,cols)
-MatrixXd::Ones(rows,cols)           // ones(rows,cols)
-C.setOnes(rows,cols)                // C = ones(rows,cols)
-MatrixXd::Random(rows,cols)         // rand(rows,cols)*2-1        // MatrixXd::Random returns uniform random numbers in (-1, 1).
-C.setRandom(rows,cols)              // C = rand(rows,cols)*2-1
-VectorXd::LinSpaced(size,low,high)   // linspace(low,high,size)'
-v.setLinSpaced(size,low,high)        // v = linspace(low,high,size)'
+// Eigen                                    // Matlab
+MatrixXd::Identity(rows,cols)               // eye(rows,cols)
+C.setIdentity(rows,cols)                    // C = eye(rows,cols)
+MatrixXd::Zero(rows,cols)                   // zeros(rows,cols)
+C.setZero(rows,cols)                        // C = zeros(rows,cols)
+MatrixXd::Ones(rows,cols)                   // ones(rows,cols)
+C.setOnes(rows,cols)                        // C = ones(rows,cols)
+MatrixXd::Random(rows,cols)                 // rand(rows,cols)*2-1            // MatrixXd::Random returns uniform random numbers in (-1, 1).
+C.setRandom(rows,cols)                      // C = rand(rows,cols)*2-1
+VectorXd::LinSpaced(size,low,high)          // linspace(low,high,size)'
+v.setLinSpaced(size,low,high)               // v = linspace(low,high,size)'
+VectorXi::LinSpaced(((hi-low)/step)+1,      // low:step:hi
+                    low,low+step*(size-1))  //
 
 
 // Matrix slicing and blocks. All expressions listed here are read/write.
 // Templated size versions are faster. Note that Matlab is 1-based (a size N
 // vector is x(1)...x(N)).
@@ -80,21 +82,24 @@
 P.bottomLeftCorner<rows,cols>()    // P(end-rows+1:end, 1:cols)
 P.bottomRightCorner<rows,cols>()   // P(end-rows+1:end, end-cols+1:end)
 
 // Of particular note is Eigen's swap function which is highly optimized.
 // Eigen                           // Matlab
-R.row(i) = P.col(j);               // R(i, :) = P(:, i)
+R.row(i) = P.col(j);               // R(i, :) = P(:, j)
 R.col(j1).swap(mat1.col(j2));      // R(:, [j1 j2]) = R(:, [j2, j1])
 
-// Views, transpose, etc; all read-write except for .adjoint().
+// Views, transpose, etc;
 // Eigen                           // Matlab
 R.adjoint()                        // R'
-R.transpose()                      // R.' or conj(R')
-R.diagonal()                       // diag(R)
+R.transpose()                      // R.' or conj(R')       // Read-write
+R.diagonal()                       // diag(R)               // Read-write
 x.asDiagonal()                     // diag(x)
-R.transpose().colwise().reverse(); // rot90(R)
-R.conjugate()                      // conj(R)
+R.transpose().colwise().reverse()  // rot90(R)              // Read-write
+R.rowwise().reverse()              // fliplr(R)
+R.colwise().reverse()              // flipud(R)
+R.replicate(i,j)                   // repmat(P,i,j)
+
 
 // All the same as Matlab, but matlab doesn't have *= style operators.
 // Matrix-vector.  Matrix-matrix.   Matrix-scalar.
 y  = M*x;          R  = P*Q;        R  = P*s;
 a  = b*M;          R  = P - Q;      R  = s*P;
@@ -102,41 +107,44 @@
                    R *= Q;          R  = s*P;
                    R += Q;          R *= s;
                    R -= Q;          R /= s;
 
 // Vectorized operations on each element independently
-// Eigen                  // Matlab
-R = P.cwiseProduct(Q);    // R = P .* Q
-R = P.array() * s.array();// R = P .* s
-R = P.cwiseQuotient(Q);   // R = P ./ Q
-R = P.array() / Q.array();// R = P ./ Q
-R = P.array() + s.array();// R = P + s
-R = P.array() - s.array();// R = P - s
-R.array() += s;           // R = R + s
-R.array() -= s;           // R = R - s
-R.array() < Q.array();    // R < Q
-R.array() <= Q.array();   // R <= Q
-R.cwiseInverse();         // 1 ./ P
-R.array().inverse();      // 1 ./ P
-R.array().sin()           // sin(P)
-R.array().cos()           // cos(P)
-R.array().pow(s)          // P .^ s
-R.array().square()        // P .^ 2
-R.array().cube()          // P .^ 3
-R.cwiseSqrt()             // sqrt(P)
-R.array().sqrt()          // sqrt(P)
-R.array().exp()           // exp(P)
-R.array().log()           // log(P)
-R.cwiseMax(P)             // max(R, P)
-R.array().max(P.array())  // max(R, P)
-R.cwiseMin(P)             // min(R, P)
-R.array().min(P.array())  // min(R, P)
-R.cwiseAbs()              // abs(P)
-R.array().abs()           // abs(P)
-R.cwiseAbs2()             // abs(P.^2)
-R.array().abs2()          // abs(P.^2)
-(R.array() < s).select(P,Q);  // (R < s ? P : Q)
+// Eigen                       // Matlab
+R = P.cwiseProduct(Q);         // R = P .* Q
+R = P.array() * s.array();     // R = P .* s
+R = P.cwiseQuotient(Q);        // R = P ./ Q
+R = P.array() / Q.array();     // R = P ./ Q
+R = P.array() + s.array();     // R = P + s
+R = P.array() - s.array();     // R = P - s
+R.array() += s;                // R = R + s
+R.array() -= s;                // R = R - s
+R.array() < Q.array();         // R < Q
+R.array() <= Q.array();        // R <= Q
+R.cwiseInverse();              // 1 ./ P
+R.array().inverse();           // 1 ./ P
+R.array().sin()                // sin(P)
+R.array().cos()                // cos(P)
+R.array().pow(s)               // P .^ s
+R.array().square()             // P .^ 2
+R.array().cube()               // P .^ 3
+R.cwiseSqrt()                  // sqrt(P)
+R.array().sqrt()               // sqrt(P)
+R.array().exp()                // exp(P)
+R.array().log()                // log(P)
+R.cwiseMax(P)                  // max(R, P)
+R.array().max(P.array())       // max(R, P)
+R.cwiseMin(P)                  // min(R, P)
+R.array().min(P.array())       // min(R, P)
+R.cwiseAbs()                   // abs(P)
+R.array().abs()                // abs(P)
+R.cwiseAbs2()                  // abs(P.^2)
+R.array().abs2()               // abs(P.^2)
+(R.array() < s).select(P,Q );  // (R < s ? P : Q)
+R = (Q.array()==0).select(P,R) // R(Q==0) = P(Q==0)
+R = P.unaryExpr(ptr_fun(func)) // R = arrayfun(func, P)   // with: scalar func(const scalar &x);
+
 
 // Reductions.
 int r, c;
 // Eigen                  // Matlab
 R.minCoeff()              // min(R(:))
@@ -163,16 +171,16 @@
 x.squaredNorm()           // dot(x, x)   Note the equivalence is not true for complex
 x.dot(y)                  // dot(x, y)
 x.cross(y)                // cross(x, y) Requires #include <Eigen/Geometry>
 
 //// Type conversion
-// Eigen                           // Matlab
-A.cast<double>();                  // double(A)
-A.cast<float>();                   // single(A)
-A.cast<int>();                     // int32(A)
-A.real();                          // real(A)
-A.imag();                          // imag(A)
+// Eigen                  // Matlab
+A.cast<double>();         // double(A)
+A.cast<float>();          // single(A)
+A.cast<int>();            // int32(A)
+A.real();                 // real(A)
+A.imag();                 // imag(A)
 // if the original type equals destination type, no work is done
 
 // Note that for most operations Eigen requires all operands to have the same type:
 MatrixXf F = MatrixXf::Zero(3,3);
 A += F;                // illegal in Eigen. In Matlab A = A+F is allowed

Index: 3rd_party/eigen/doc/B01_Experimental.dox
==================================================================
--- 3rd_party/eigen/doc/B01_Experimental.dox
+++ 3rd_party/eigen/doc/B01_Experimental.dox
@@ -2,11 +2,11 @@
 
 /** \page Experimental Experimental parts of Eigen
 
 \eigenAutoToc
 
-\section summary Summary
+\section Experimental_summary Summary
 
 With the 2.0 release, Eigen's API is, to a large extent, stable. However, we wish to retain the freedom to make API incompatible changes. To that effect, we call many parts of Eigen "experimental" which means that they are not subject to API stability guarantee.
 
 Our goal is that for the 2.1 release (expected in July 2009) most of these parts become API-stable too.
 
@@ -15,20 +15,20 @@
 Experimental features may at any time:
 \li be removed;
 \li be subject to an API incompatible change;
 \li introduce API or ABI incompatible changes in your own code if you let them affect your API or ABI.
 
-\section modules Experimental modules
+\section Experimental_modules Experimental modules
 
 The following modules are considered entirely experimental, and we make no firm API stability guarantee about them for the time being:
 \li SVD
 \li QR
 \li Cholesky
 \li Sparse
 \li Geometry (this one should be mostly stable, but it's a little too early to make a formal guarantee)
 
-\section core Experimental parts of the Core module
+\section Experimental_core Experimental parts of the Core module
 
 In the Core module, the only classes subject to ABI stability guarantee (meaning that you can use it for data members in your public ABI) is:
 \li Matrix
 \li Map
 

Index: 3rd_party/eigen/doc/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/doc/CMakeLists.txt
+++ 3rd_party/eigen/doc/CMakeLists.txt
@@ -7,17 +7,25 @@
 if(CMAKE_COMPILER_IS_GNUCXX)
   if(CMAKE_SYSTEM_NAME MATCHES Linux)
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O1 -g1")
   endif(CMAKE_SYSTEM_NAME MATCHES Linux)
 endif(CMAKE_COMPILER_IS_GNUCXX)
+
+option(EIGEN_INTERNAL_DOCUMENTATION "Build internal documentation" OFF)
+
 
 # Set some Doxygen flags
 set(EIGEN_DOXY_PROJECT_NAME             "Eigen")
 set(EIGEN_DOXY_OUTPUT_DIRECTORY_SUFFIX  "")
 set(EIGEN_DOXY_INPUT                    "\"${Eigen_SOURCE_DIR}/Eigen\" \"${Eigen_SOURCE_DIR}/doc\"")
 set(EIGEN_DOXY_HTML_COLORSTYLE_HUE      "220")
 set(EIGEN_DOXY_TAGFILES                 "")
+if(EIGEN_INTERNAL_DOCUMENTATION)
+  set(EIGEN_DOXY_INTERNAL                 "YES")
+else(EIGEN_INTERNAL_DOCUMENTATION)
+  set(EIGEN_DOXY_INTERNAL                 "NO")
+endif(EIGEN_INTERNAL_DOCUMENTATION)
 
 configure_file(
   ${CMAKE_CURRENT_SOURCE_DIR}/Doxyfile.in
   ${CMAKE_CURRENT_BINARY_DIR}/Doxyfile
 )
@@ -68,10 +76,12 @@
   doc-eigen-prerequisites
   ALL
   COMMAND ${CMAKE_COMMAND} -E make_directory ${CMAKE_CURRENT_BINARY_DIR}/html/
   COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/eigen_navtree_hacks.js           ${CMAKE_CURRENT_BINARY_DIR}/html/
   COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/Eigen_Silly_Professor_64x64.png  ${CMAKE_CURRENT_BINARY_DIR}/html/
+  COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/ftv2pnode.png                    ${CMAKE_CURRENT_BINARY_DIR}/html/
+  COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/ftv2node.png                     ${CMAKE_CURRENT_BINARY_DIR}/html/
   COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/AsciiQuickReference.txt          ${CMAKE_CURRENT_BINARY_DIR}/html/
   WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
 )
 
 add_custom_target(
@@ -78,21 +88,25 @@
   doc-unsupported-prerequisites
   ALL
   COMMAND ${CMAKE_COMMAND} -E make_directory ${Eigen_BINARY_DIR}/doc/html/unsupported
   COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/eigen_navtree_hacks.js           ${CMAKE_CURRENT_BINARY_DIR}/html/unsupported/
   COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/Eigen_Silly_Professor_64x64.png  ${CMAKE_CURRENT_BINARY_DIR}/html/unsupported/
+  COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/ftv2pnode.png                    ${CMAKE_CURRENT_BINARY_DIR}/html/unsupported/
+  COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_CURRENT_SOURCE_DIR}/ftv2node.png                     ${CMAKE_CURRENT_BINARY_DIR}/html/unsupported/
   WORKING_DIRECTORY ${Eigen_BINARY_DIR}/doc
 )
 
 add_dependencies(doc-eigen-prerequisites all_snippets all_examples)
 add_dependencies(doc-unsupported-prerequisites unsupported_snippets unsupported_examples)
 
 add_custom_target(doc ALL
   COMMAND doxygen
   COMMAND doxygen Doxyfile-unsupported
+  COMMAND ${CMAKE_COMMAND} -E copy ${Eigen_BINARY_DIR}/doc/html/group__TopicUnalignedArrayAssert.html ${Eigen_BINARY_DIR}/doc/html/TopicUnalignedArrayAssert.html
   COMMAND ${CMAKE_COMMAND} -E rename html eigen-doc
   COMMAND ${CMAKE_COMMAND} -E remove eigen-doc/eigen-doc.tgz
-  COMMAND ${CMAKE_COMMAND} -E tar cfz eigen-doc/eigen-doc.tgz eigen-doc
+  COMMAND ${CMAKE_COMMAND} -E tar cfz eigen-doc.tgz eigen-doc
+  COMMAND ${CMAKE_COMMAND} -E rename eigen-doc.tgz eigen-doc/eigen-doc.tgz
   COMMAND ${CMAKE_COMMAND} -E rename eigen-doc html
   WORKING_DIRECTORY ${Eigen_BINARY_DIR}/doc)
 
 add_dependencies(doc doc-eigen-prerequisites doc-unsupported-prerequisites)

ADDED   3rd_party/eigen/doc/CoeffwiseMathFunctionsTable.dox
Index: 3rd_party/eigen/doc/CoeffwiseMathFunctionsTable.dox
==================================================================
--- 3rd_party/eigen/doc/CoeffwiseMathFunctionsTable.dox
+++ 3rd_party/eigen/doc/CoeffwiseMathFunctionsTable.dox
@@ -0,0 +1,525 @@
+namespace Eigen {
+
+/** \eigenManualPage CoeffwiseMathFunctions Catalog of coefficient-wise math functions
+
+
+<!-- <span style="font-size:300%; color:red; font-weight: 900;">!WORK IN PROGRESS!</span> -->
+
+This table presents a catalog of the coefficient-wise math functions supported by %Eigen.
+In this table, \c a, \c b, refer to Array objects or expressions, and \c m refers to a linear algebra Matrix/Vector object. Standard scalar types are abbreviated as follows:
+  - \c int: \c i32
+  - \c float: \c f
+  - \c double: \c d
+  - \c std::complex<float>: \c cf
+  - \c std::complex<double>: \c cd
+
+For each row, the first column list the equivalent calls for arrays, and matrices when supported. Of course, all functions are available for matrices by first casting it as an array: \c m.array().
+
+The third column gives some hints in the underlying scalar implementation. In most cases, %Eigen does not implement itself the math function but relies on the STL for standard scalar types, or user-provided functions for custom scalar types.
+For instance, some simply calls the respective function of the STL while preserving <a href="http://en.cppreference.com/w/cpp/language/adl">argument-dependent lookup</a> for custom types.
+The following:
+\code
+using std::foo;
+foo(a[i]);
+\endcode
+means that the STL's function \c std::foo will be potentially called if it is compatible with the underlying scalar type. If not, then the user must ensure that an overload of the function foo is available for the given scalar type (usually defined in the same namespace as the given scalar type).
+This also means that, unless specified, if the function \c std::foo is available only in some recent c++ versions (e.g., c++11), then the respective %Eigen's function/method will be usable on standard types only if the compiler support the required c++ version.
+
+<table class="manual-hl">
+<tr>
+<th>API</th><th>Description</th><th>Default scalar implementation</th><th>SIMD</th>
+</tr>
+<tr><td colspan="4"></td></tr>
+<tr><th colspan="4">Basic operations</th></tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_abs
+  a.\link ArrayBase::abs abs\endlink(); \n
+  \link Eigen::abs abs\endlink(a); \n
+  m.\link MatrixBase::cwiseAbs cwiseAbs\endlink();
+  </td>
+  <td>absolute value (\f$ |a_i| \f$) </td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/fabs">std::abs</a>; \n
+  abs(a[i]);
+  </td>
+  <td>SSE2, AVX (i32,f,d)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_inverse
+  a.\link ArrayBase::inverse inverse\endlink(); \n
+  \link Eigen::inverse inverse\endlink(a); \n
+  m.\link MatrixBase::cwiseInverse cwiseInverse\endlink();
+  </td>
+  <td>inverse value (\f$ 1/a_i \f$) </td>
+  <td class="code">
+  1/a[i];
+  </td>
+  <td>All engines (f,d,fc,fd)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_conj
+  a.\link ArrayBase::conjugate conjugate\endlink(); \n
+  \link Eigen::conj conj\endlink(a); \n
+  m.\link MatrixBase::conjugate conjugate();
+  </td>
+  <td><a href="https://en.wikipedia.org/wiki/Complex_conjugate">complex conjugate</a> (\f$ \bar{a_i} \f$),\n
+  no-op for real </td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/complex/conj">std::conj</a>; \n
+  conj(a[i]);
+  </td>
+  <td>All engines (fc,fd)</td>
+</tr>
+<tr>
+<th colspan="4">Exponential functions</th>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_exp
+  a.\link ArrayBase::exp exp\endlink(); \n
+  \link Eigen::exp exp\endlink(a);
+  </td>
+  <td>\f$ e \f$ raised to the given power (\f$ e^{a_i} \f$) </td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/exp">std::exp</a>; \n
+  exp(a[i]);
+  </td>
+  <td>SSE2, AVX (f,d)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_log
+  a.\link ArrayBase::log log\endlink(); \n
+  \link Eigen::log log\endlink(a);
+  </td>
+  <td>natural (base \f$ e \f$) logarithm (\f$ \ln({a_i}) \f$)</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/log">std::log</a>; \n
+  log(a[i]);
+  </td>
+  <td>SSE2, AVX (f)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_log1p
+  a.\link ArrayBase::log1p log1p\endlink(); \n
+  \link Eigen::log1p log1p\endlink(a);
+  </td>
+  <td>natural (base \f$ e \f$) logarithm of 1 plus \n the given number (\f$ \ln({1+a_i}) \f$)</td>
+  <td>built-in generic implementation based on \c log,\n
+  plus \c using <a href="http://en.cppreference.com/w/cpp/numeric/math/log1p">\c std::log1p </a>; \cpp11</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_log10
+  a.\link ArrayBase::log10 log10\endlink(); \n
+  \link Eigen::log10 log10\endlink(a);
+  </td>
+  <td>base 10 logarithm (\f$ \log_{10}({a_i}) \f$)</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/log10">std::log10</a>; \n
+  log10(a[i]);
+  </td>
+  <td></td>
+</tr>
+<tr>
+<th colspan="4">Power functions</th>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_pow
+  a.\link ArrayBase::pow pow\endlink(b); \n
+  \link Eigen::pow pow\endlink(a,b);
+  </td>
+  <td>raises a number to the given power (\f$ a_i ^ {b_i} \f$) \n \c a and \c b can be either an array or scalar.</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/pow">std::pow</a>; \n
+  pow(a[i],b[i]);\n
+  (plus builtin for integer types)</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_sqrt
+  a.\link ArrayBase::sqrt sqrt\endlink(); \n
+  \link Eigen::sqrt sqrt\endlink(a);\n
+  m.\link MatrixBase::cwiseSqrt cwiseSqrt\endlink();
+  </td>
+  <td>computes square root (\f$ \sqrt a_i \f$)</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/sqrt">std::sqrt</a>; \n
+  sqrt(a[i]);</td>
+  <td>SSE2, AVX (f,d)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_rsqrt
+  a.\link ArrayBase::rsqrt rsqrt\endlink(); \n
+  \link Eigen::rsqrt rsqrt\endlink(a);
+  </td>
+  <td><a href="https://en.wikipedia.org/wiki/Fast_inverse_square_root">reciprocal square root</a> (\f$ 1/{\sqrt a_i} \f$)</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/sqrt">std::sqrt</a>; \n
+  1/sqrt(a[i]); \n
+  </td>
+  <td>SSE2, AVX, AltiVec, ZVector (f,d)\n
+  (approx + 1 Newton iteration)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_square
+  a.\link ArrayBase::square square\endlink(); \n
+  \link Eigen::square square\endlink(a);
+  </td>
+  <td>computes square power (\f$ a_i^2 \f$)</td>
+  <td class="code">
+  a[i]*a[i]</td>
+  <td>All (i32,f,d,cf,cd)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_cube
+  a.\link ArrayBase::cube cube\endlink(); \n
+  \link Eigen::cube cube\endlink(a);
+  </td>
+  <td>computes cubic power (\f$ a_i^3 \f$)</td>
+  <td class="code">
+  a[i]*a[i]*a[i]</td>
+  <td>All (i32,f,d,cf,cd)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_abs2
+  a.\link ArrayBase::abs2 abs2\endlink(); \n
+  \link Eigen::abs2 abs2\endlink(a);\n
+  m.\link MatrixBase::cwiseAbs2 cwiseAbs2\endlink();
+  </td>
+  <td>computes the squared absolute value (\f$ |a_i|^2 \f$)</td>
+  <td class="code">
+  real:    a[i]*a[i] \n
+  complex:  real(a[i])*real(a[i]) \n
+  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; + imag(a[i])*imag(a[i])</td>
+  <td>All (i32,f,d)</td>
+</tr>
+<tr>
+<th colspan="4">Trigonometric functions</th>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_sin
+  a.\link ArrayBase::sin sin\endlink(); \n
+  \link Eigen::sin sin\endlink(a);
+  </td>
+  <td>computes sine</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/sin">std::sin</a>; \n
+  sin(a[i]);</td>
+  <td>SSE2, AVX (f)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_cos
+  a.\link ArrayBase::cos cos\endlink(); \n
+  \link Eigen::cos cos\endlink(a);
+  </td>
+  <td>computes cosine</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/cos">std::cos</a>; \n
+  cos(a[i]);</td>
+  <td>SSE2, AVX (f)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_tan
+  a.\link ArrayBase::tan tan\endlink(); \n
+  \link Eigen::tan tan\endlink(a);
+  </td>
+  <td>computes tangent</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/tan">std::tan</a>; \n
+  tan(a[i]);</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_asin
+  a.\link ArrayBase::asin asin\endlink(); \n
+  \link Eigen::asin asin\endlink(a);
+  </td>
+  <td>computes arc sine (\f$ \sin^{-1} a_i \f$)</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/asin">std::asin</a>; \n
+  asin(a[i]);</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_acos
+  a.\link ArrayBase::acos acos\endlink(); \n
+  \link Eigen::acos acos\endlink(a);
+  </td>
+  <td>computes arc cosine  (\f$ \cos^{-1} a_i \f$)</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/acos">std::acos</a>; \n
+  acos(a[i]);</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_atan
+  a.\link ArrayBase::atan tan\endlink(); \n
+  \link Eigen::atan atan\endlink(a);
+  </td>
+  <td>computes arc tangent (\f$ \tan^{-1} a_i \f$)</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/atan">std::atan</a>; \n
+  atan(a[i]);</td>
+  <td></td>
+</tr>
+<tr>
+<th colspan="4">Hyperbolic functions</th>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_sinh
+  a.\link ArrayBase::sinh sinh\endlink(); \n
+  \link Eigen::sinh sinh\endlink(a);
+  </td>
+  <td>computes hyperbolic sine</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/sinh">std::sinh</a>; \n
+  sinh(a[i]);</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_cosh
+  a.\link ArrayBase::cosh cohs\endlink(); \n
+  \link Eigen::cosh cosh\endlink(a);
+  </td>
+  <td>computes hyperbolic cosine</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/cosh">std::cosh</a>; \n
+  cosh(a[i]);</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_tanh
+  a.\link ArrayBase::tanh tanh\endlink(); \n
+  \link Eigen::tanh tanh\endlink(a);
+  </td>
+  <td>computes hyperbolic tangent</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/tanh">std::tanh</a>; \n
+  tanh(a[i]);</td>
+  <td></td>
+</tr>
+<tr>
+<th colspan="4">Nearest integer floating point operations</th>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_ceil
+  a.\link ArrayBase::ceil ceil\endlink(); \n
+  \link Eigen::ceil ceil\endlink(a);
+  </td>
+  <td>nearest integer not less than the given value</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/ceil">std::ceil</a>; \n
+  ceil(a[i]);</td>
+  <td>SSE4,AVX,ZVector (f,d)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_floor
+  a.\link ArrayBase::floor floor\endlink(); \n
+  \link Eigen::floor floor\endlink(a);
+  </td>
+  <td>nearest integer not greater than the given value</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/floor">std::floor</a>; \n
+  floor(a[i]);</td>
+  <td>SSE4,AVX,ZVector (f,d)</td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_round
+  a.\link ArrayBase::round round\endlink(); \n
+  \link Eigen::round round\endlink(a);
+  </td>
+  <td>nearest integer, \n rounding away from zero in halfway cases</td>
+  <td>built-in generic implementation \n based on \c floor and \c ceil,\n
+  plus \c using <a href="http://en.cppreference.com/w/cpp/numeric/math/round">\c std::round </a>; \cpp11</td>
+  <td>SSE4,AVX,ZVector (f,d)</td>
+</tr>
+<tr>
+<th colspan="4">Floating point manipulation functions</th>
+</tr>
+<tr>
+<th colspan="4">Classification and comparison</th>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_isfinite
+  a.\link ArrayBase::isFinite isFinite\endlink(); \n
+  \link Eigen::isfinite isfinite\endlink(a);
+  </td>
+  <td>checks if the given number has finite value</td>
+  <td>built-in generic implementation,\n
+  plus \c using <a href="http://en.cppreference.com/w/cpp/numeric/math/isfinite">\c std::isfinite </a>; \cpp11</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_isinf
+  a.\link ArrayBase::isInf isInf\endlink(); \n
+  \link Eigen::isinf isinf\endlink(a);
+  </td>
+  <td>checks if the given number is infinite</td>
+  <td>built-in generic implementation,\n
+  plus \c using <a href="http://en.cppreference.com/w/cpp/numeric/math/isinf">\c std::isinf </a>; \cpp11</td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_isnan
+  a.\link ArrayBase::isNaN isNaN\endlink(); \n
+  \link Eigen::isnan isnan\endlink(a);
+  </td>
+  <td>checks if the given number is not a number</td>
+  <td>built-in generic implementation,\n
+  plus \c using <a href="http://en.cppreference.com/w/cpp/numeric/math/isnan">\c std::isnan </a>; \cpp11</td>
+  <td></td>
+</tr>
+<tr>
+<th colspan="4">Error and gamma functions</th>
+</tr>
+<tr> <td colspan="4">  Require \c \#include \c <unsupported/Eigen/SpecialFunctions> </td></tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_erf
+  a.\link ArrayBase::erf erf\endlink(); \n
+  \link Eigen::erf erf\endlink(a);
+  </td>
+  <td>error function</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/erf">std::erf</a>; \cpp11 \n
+  erf(a[i]);
+  </td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_erfc
+  a.\link ArrayBase::erfc erfc\endlink(); \n
+  \link Eigen::erfc erfc\endlink(a);
+  </td>
+  <td>complementary error function</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/erfc">std::erfc</a>; \cpp11 \n
+  erfc(a[i]);
+  </td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_lgamma
+  a.\link ArrayBase::lgamma lgamma\endlink(); \n
+  \link Eigen::lgamma lgamma\endlink(a);
+  </td>
+  <td>natural logarithm of the gamma function</td>
+  <td class="code">
+  using <a href="http://en.cppreference.com/w/cpp/numeric/math/lgamma">std::lgamma</a>; \cpp11 \n
+  lgamma(a[i]);
+  </td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_digamma
+  a.\link ArrayBase::digamma digamma\endlink(); \n
+  \link Eigen::digamma digamma\endlink(a);
+  </td>
+  <td><a href="https://en.wikipedia.org/wiki/Digamma_function">logarithmic derivative of the gamma function</a></td>
+  <td>
+  built-in for float and double
+  </td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_igamma
+  \link Eigen::igamma igamma\endlink(a,x);
+  </td>
+  <td><a href="https://en.wikipedia.org/wiki/Incomplete_gamma_function">lower incomplete gamma integral</a>
+  \n \f$ \gamma(a_i,x_i)= \frac{1}{|a_i|} \int_{0}^{x_i}e^{\text{-}t} t^{a_i-1} \mathrm{d} t \f$</td>
+  <td>
+  built-in for float and double,\n but requires \cpp11
+  </td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_igammac
+  \link Eigen::igammac igammac\endlink(a,x);
+  </td>
+  <td><a href="https://en.wikipedia.org/wiki/Incomplete_gamma_function">upper incomplete gamma integral</a>
+  \n \f$ \Gamma(a_i,x_i) = \frac{1}{|a_i|} \int_{x_i}^{\infty}e^{\text{-}t} t^{a_i-1} \mathrm{d} t \f$</td>
+  <td>
+  built-in for float and double,\n but requires \cpp11
+  </td>
+  <td></td>
+</tr>
+<tr>
+<th colspan="4">Special functions</th>
+</tr>
+<tr> <td colspan="4">  Require \c \#include \c <unsupported/Eigen/SpecialFunctions> </td></tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_polygamma
+  \link Eigen::polygamma polygamma\endlink(n,x);
+  </td>
+  <td><a href="https://en.wikipedia.org/wiki/Polygamma_function">n-th derivative of digamma at x</a></td>
+  <td>
+  built-in generic based on\n <a href="#cwisetable_lgamma">\c lgamma </a>,
+  <a href="#cwisetable_digamma"> \c digamma </a>
+  and <a href="#cwisetable_zeta">\c zeta </a>.
+  </td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_betainc
+  \link Eigen::betainc betainc\endlink(a,b,x);
+  </td>
+  <td><a href="https://en.wikipedia.org/wiki/Beta_function#Incomplete_beta_function">Incomplete beta function</a></td>
+  <td>
+  built-in for float and double,\n but requires \cpp11
+  </td>
+  <td></td>
+</tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_zeta
+  \link Eigen::zeta zeta\endlink(a,b);
+  </td>
+  <td><a href="https://en.wikipedia.org/wiki/Hurwitz_zeta_function">Hurwitz zeta function</a>
+  \n \f$ \zeta(a_i,b_i)=\sum_{k=0}^{\infty}(b_i+k)^{\text{-}a_i} \f$</td>
+  <td>
+  built-in for float and double
+  </td>
+  <td></td>
+</tr>
+<tr><td colspan="4"></td></tr>
+</table>
+
+\n
+
+*/
+
+}

DELETED 3rd_party/eigen/doc/CustomizingEigen.dox
Index: 3rd_party/eigen/doc/CustomizingEigen.dox
==================================================================
--- 3rd_party/eigen/doc/CustomizingEigen.dox
+++ 3rd_party/eigen/doc/CustomizingEigen.dox
@@ -1,188 +0,0 @@
-namespace Eigen {
-
-/** \page TopicCustomizingEigen Customizing/Extending Eigen
-
-Eigen can be extended in several ways, for instance, by defining global methods, \ref ExtendingMatrixBase "by adding custom methods to MatrixBase", adding support to \ref CustomScalarType "custom types" etc.
-
-\eigenAutoToc
-
-\section ExtendingMatrixBase Extending MatrixBase (and other classes)
-
-In this section we will see how to add custom methods to MatrixBase. Since all expressions and matrix types inherit MatrixBase, adding a method to MatrixBase make it immediately available to all expressions ! A typical use case is, for instance, to make Eigen compatible with another API.
-
-You certainly know that in C++ it is not possible to add methods to an existing class. So how that's possible ? Here the trick is to include in the declaration of MatrixBase a file defined by the preprocessor token \c EIGEN_MATRIXBASE_PLUGIN:
-\code
-class MatrixBase {
-  // ...
-  #ifdef EIGEN_MATRIXBASE_PLUGIN
-  #include EIGEN_MATRIXBASE_PLUGIN
-  #endif
-};
-\endcode
-Therefore to extend MatrixBase with your own methods you just have to create a file with your method declaration and define EIGEN_MATRIXBASE_PLUGIN before you include any Eigen's header file.
-
-You can extend many of the other classes used in Eigen by defining similarly named preprocessor symbols. For instance, define \c EIGEN_ARRAYBASE_PLUGIN if you want to extend the ArrayBase class. A full list of classes that can be extended in this way and the corresponding preprocessor symbols can be found on our page \ref TopicPreprocessorDirectives.
-
-Here is an example of an extension file for adding methods to MatrixBase: \n
-\b MatrixBaseAddons.h
-\code
-inline Scalar at(uint i, uint j) const { return this->operator()(i,j); }
-inline Scalar& at(uint i, uint j) { return this->operator()(i,j); }
-inline Scalar at(uint i) const { return this->operator[](i); }
-inline Scalar& at(uint i) { return this->operator[](i); }
-
-inline RealScalar squaredLength() const { return squaredNorm(); }
-inline RealScalar length() const { return norm(); }
-inline RealScalar invLength(void) const { return fast_inv_sqrt(squaredNorm()); }
-
-template<typename OtherDerived>
-inline Scalar squaredDistanceTo(const MatrixBase<OtherDerived>& other) const
-{ return (derived() - other.derived()).squaredNorm(); }
-
-template<typename OtherDerived>
-inline RealScalar distanceTo(const MatrixBase<OtherDerived>& other) const
-{ return internal::sqrt(derived().squaredDistanceTo(other)); }
-
-inline void scaleTo(RealScalar l) { RealScalar vl = norm(); if (vl>1e-9) derived() *= (l/vl); }
-
-inline Transpose<Derived> transposed() {return this->transpose();}
-inline const Transpose<Derived> transposed() const {return this->transpose();}
-
-inline uint minComponentId(void) const  { int i; this->minCoeff(&i); return i; }
-inline uint maxComponentId(void) const  { int i; this->maxCoeff(&i); return i; }
-
-template<typename OtherDerived>
-void makeFloor(const MatrixBase<OtherDerived>& other) { derived() = derived().cwiseMin(other.derived()); }
-template<typename OtherDerived>
-void makeCeil(const MatrixBase<OtherDerived>& other) { derived() = derived().cwiseMax(other.derived()); }
-
-const CwiseUnaryOp<internal::scalar_add_op<Scalar>, Derived>
-operator+(const Scalar& scalar) const
-{ return CwiseUnaryOp<internal::scalar_add_op<Scalar>, Derived>(derived(), internal::scalar_add_op<Scalar>(scalar)); }
-
-friend const CwiseUnaryOp<internal::scalar_add_op<Scalar>, Derived>
-operator+(const Scalar& scalar, const MatrixBase<Derived>& mat)
-{ return CwiseUnaryOp<internal::scalar_add_op<Scalar>, Derived>(mat.derived(), internal::scalar_add_op<Scalar>(scalar)); }
-\endcode
-
-Then one can the following declaration in the config.h or whatever prerequisites header file of his project:
-\code
-#define EIGEN_MATRIXBASE_PLUGIN "MatrixBaseAddons.h"
-\endcode
-
-\section InheritingFromMatrix Inheriting from Matrix
-
-Before inheriting from Matrix, be really, i mean REALLY sure that using
-EIGEN_MATRIX_PLUGIN is not what you really want (see previous section).
-If you just need to add few members to Matrix, this is the way to go.
-
-An example of when you actually need to inherit Matrix, is when you have
-several layers of heritage such as  MyVerySpecificVector1,MyVerySpecificVector1 -> MyVector1 -> Matrix and.
-MyVerySpecificVector3,MyVerySpecificVector4 -> MyVector2 -> Matrix.
-
-In order for your object to work within the %Eigen framework, you need to
-define a few members in your inherited class.
-
-Here is a minimalistic example:\n
-\code
-class MyVectorType : public  Eigen::VectorXd
-{
-public:
-    MyVectorType(void):Eigen::VectorXd() {}
-
-    typedef Eigen::VectorXd Base;
-
-    // This constructor allows you to construct MyVectorType from Eigen expressions
-    template<typename OtherDerived>
-    MyVectorType(const Eigen::MatrixBase<OtherDerived>& other)
-        : Eigen::Vector3d(other)
-    { }
-
-    // This method allows you to assign Eigen expressions to MyVectorType
-    template<typename OtherDerived>
-    MyVectorType & operator= (const Eigen::MatrixBase <OtherDerived>& other)
-    {
-        this->Base::operator=(other);
-        return *this;
-    }
-};
-\endcode
-
-This is the kind of error you can get if you don't provide those methods
-\code
-error: no match for ‘operator=’ in ‘delta =
-(((Eigen::MatrixBase<Eigen::Matrix<std::complex<float>, 10000, 1, 2, 10000,
-1> >*)(& delta)) + 8u)->Eigen::MatrixBase<Derived>::cwise [with Derived =
-Eigen::Matrix<std::complex<float>, 10000, 1, 2, 10000,
-1>]().Eigen::Cwise<ExpressionType>::operator* [with OtherDerived =
-Eigen::Matrix<std::complex<float>, 10000, 1, 2, 10000, 1>, ExpressionType =
-Eigen::Matrix<std::complex<float>, 10000, 1, 2, 10000, 1>](((const
-Eigen::MatrixBase<Eigen::Matrix<std::complex<float>, 10000, 1, 2, 10000, 1>
->&)(((const Eigen::MatrixBase<Eigen::Matrix<std::complex<float>, 10000, 1,
->2, 10000, 1> >*)((const spectral1d*)where)) + 8u)))’                                                    
-\endcode
-
-\anchor user_defined_scalars \section CustomScalarType Using custom scalar types
-
-By default, Eigen currently supports standard floating-point types (\c float, \c double, \c std::complex<float>, \c std::complex<double>, \c long \c double), as well as all native integer types (e.g., \c int, \c unsigned \c int, \c short, etc.), and \c bool.
-On x86-64 systems, \c long \c double permits to locally enforces the use of x87 registers with extended accuracy (in comparison to SSE).
-
-In order to add support for a custom type \c T you need:
--# make sure the common operator (+,-,*,/,etc.) are supported by the type \c T
--# add a specialization of struct Eigen::NumTraits<T> (see \ref NumTraits)
--# define the math functions that makes sense for your type. This includes standard ones like sqrt, pow, sin, tan, conj, real, imag, etc, as well as abs2 which is Eigen specific.
-     (see the file Eigen/src/Core/MathFunctions.h)
-
-The math function should be defined in the same namespace than \c T, or in the \c std namespace though that second approach is not recommended.
-
-Here is a concrete example adding support for the Adolc's \c adouble type. <a href="https://projects.coin-or.org/ADOL-C">Adolc</a> is an automatic differentiation library. The type \c adouble is basically a real value tracking the values of any number of partial derivatives.
-
-\code
-#ifndef ADOLCSUPPORT_H
-#define ADOLCSUPPORT_H
-
-#define ADOLC_TAPELESS
-#include <adolc/adouble.h>
-#include <Eigen/Core>
-
-namespace Eigen {
-
-template<> struct NumTraits<adtl::adouble>
- : NumTraits<double> // permits to get the epsilon, dummy_precision, lowest, highest functions
-{
-  typedef adtl::adouble Real;
-  typedef adtl::adouble NonInteger;
-  typedef adtl::adouble Nested;
-
-  enum {
-    IsComplex = 0,
-    IsInteger = 0,
-    IsSigned = 1,
-    RequireInitialization = 1,
-    ReadCost = 1,
-    AddCost = 3,
-    MulCost = 3
-  };
-};
-
-}
-
-namespace adtl {
-
-inline const adouble& conj(const adouble& x)  { return x; }
-inline const adouble& real(const adouble& x)  { return x; }
-inline adouble imag(const adouble&)    { return 0.; }
-inline adouble abs(const adouble&  x)  { return fabs(x); }
-inline adouble abs2(const adouble& x)  { return x*x; }
-
-}
-
-#endif // ADOLCSUPPORT_H
-\endcode
-
-
-\sa \ref TopicPreprocessorDirectives
-
-*/
-
-}

ADDED   3rd_party/eigen/doc/CustomizingEigen_CustomScalar.dox
Index: 3rd_party/eigen/doc/CustomizingEigen_CustomScalar.dox
==================================================================
--- 3rd_party/eigen/doc/CustomizingEigen_CustomScalar.dox
+++ 3rd_party/eigen/doc/CustomizingEigen_CustomScalar.dox
@@ -0,0 +1,120 @@
+namespace Eigen {
+
+/** \page TopicCustomizing_CustomScalar Using custom scalar types
+\anchor user_defined_scalars
+
+By default, Eigen currently supports standard floating-point types (\c float, \c double, \c std::complex<float>, \c std::complex<double>, \c long \c double), as well as all native integer types (e.g., \c int, \c unsigned \c int, \c short, etc.), and \c bool.
+On x86-64 systems, \c long \c double permits to locally enforces the use of x87 registers with extended accuracy (in comparison to SSE).
+
+In order to add support for a custom type \c T you need:
+-# make sure the common operator (+,-,*,/,etc.) are supported by the type \c T
+-# add a specialization of struct Eigen::NumTraits<T> (see \ref NumTraits)
+-# define the math functions that makes sense for your type. This includes standard ones like sqrt, pow, sin, tan, conj, real, imag, etc, as well as abs2 which is Eigen specific.
+     (see the file Eigen/src/Core/MathFunctions.h)
+
+The math function should be defined in the same namespace than \c T, or in the \c std namespace though that second approach is not recommended.
+
+Here is a concrete example adding support for the Adolc's \c adouble type. <a href="https://projects.coin-or.org/ADOL-C">Adolc</a> is an automatic differentiation library. The type \c adouble is basically a real value tracking the values of any number of partial derivatives.
+
+\code
+#ifndef ADOLCSUPPORT_H
+#define ADOLCSUPPORT_H
+
+#define ADOLC_TAPELESS
+#include <adolc/adouble.h>
+#include <Eigen/Core>
+
+namespace Eigen {
+
+template<> struct NumTraits<adtl::adouble>
+ : NumTraits<double> // permits to get the epsilon, dummy_precision, lowest, highest functions
+{
+  typedef adtl::adouble Real;
+  typedef adtl::adouble NonInteger;
+  typedef adtl::adouble Nested;
+
+  enum {
+    IsComplex = 0,
+    IsInteger = 0,
+    IsSigned = 1,
+    RequireInitialization = 1,
+    ReadCost = 1,
+    AddCost = 3,
+    MulCost = 3
+  };
+};
+
+}
+
+namespace adtl {
+
+inline const adouble& conj(const adouble& x)  { return x; }
+inline const adouble& real(const adouble& x)  { return x; }
+inline adouble imag(const adouble&)    { return 0.; }
+inline adouble abs(const adouble&  x)  { return fabs(x); }
+inline adouble abs2(const adouble& x)  { return x*x; }
+
+}
+
+#endif // ADOLCSUPPORT_H
+\endcode
+
+This other example adds support for the \c mpq_class type from <a href="https://gmplib.org/">GMP</a>. It shows in particular how to change the way Eigen picks the best pivot during LU factorization. It selects the coefficient with the highest score, where the score is by default the absolute value of a number, but we can define a different score, for instance to prefer pivots with a more compact representation (this is an example, not a recommendation). Note that the scores should always be non-negative and only zero is allowed to have a score of zero. Also, this can interact badly with thresholds for inexact scalar types.
+
+\code
+#include <gmpxx.h>
+#include <Eigen/Core>
+#include <boost/operators.hpp>
+
+namespace Eigen {
+  template<> struct NumTraits<mpq_class> : GenericNumTraits<mpq_class>
+  {
+    typedef mpq_class Real;
+    typedef mpq_class NonInteger;
+    typedef mpq_class Nested;
+
+    static inline Real epsilon() { return 0; }
+    static inline Real dummy_precision() { return 0; }
+    static inline Real digits10() { return 0; }
+
+    enum {
+      IsInteger = 0,
+      IsSigned = 1,
+      IsComplex = 0,
+      RequireInitialization = 1,
+      ReadCost = 6,
+      AddCost = 150,
+      MulCost = 100
+    };
+  };
+
+  namespace internal {
+
+    template<> struct scalar_score_coeff_op<mpq_class> {
+      struct result_type : boost::totally_ordered1<result_type> {
+        std::size_t len;
+        result_type(int i = 0) : len(i) {} // Eigen uses Score(0) and Score()
+        result_type(mpq_class const& q) :
+          len(mpz_size(q.get_num_mpz_t())+
+              mpz_size(q.get_den_mpz_t())-1) {}
+        friend bool operator<(result_type x, result_type y) {
+          // 0 is the worst possible pivot
+          if (x.len == 0) return y.len > 0;
+          if (y.len == 0) return false;
+          // Prefer a pivot with a small representation
+          return x.len > y.len;
+        }
+        friend bool operator==(result_type x, result_type y) {
+          // Only used to test if the score is 0
+          return x.len == y.len;
+        }
+      };
+      result_type operator()(mpq_class const& x) const { return x; }
+    };
+  }
+}
+\endcode
+
+*/
+
+}

ADDED   3rd_party/eigen/doc/CustomizingEigen_InheritingMatrix.dox
Index: 3rd_party/eigen/doc/CustomizingEigen_InheritingMatrix.dox
==================================================================
--- 3rd_party/eigen/doc/CustomizingEigen_InheritingMatrix.dox
+++ 3rd_party/eigen/doc/CustomizingEigen_InheritingMatrix.dox
@@ -0,0 +1,34 @@
+namespace Eigen {
+
+/** \page TopicCustomizing_InheritingMatrix Inheriting from Matrix
+
+Before inheriting from Matrix, be really, I mean REALLY, sure that using
+EIGEN_MATRIX_PLUGIN is not what you really want (see previous section).
+If you just need to add few members to Matrix, this is the way to go.
+
+An example of when you actually need to inherit Matrix, is when you
+have several layers of heritage such as 
+MyVerySpecificVector1, MyVerySpecificVector2 -> MyVector1 -> Matrix and
+MyVerySpecificVector3, MyVerySpecificVector4 -> MyVector2 -> Matrix.
+
+In order for your object to work within the %Eigen framework, you need to
+define a few members in your inherited class.
+
+Here is a minimalistic example:
+
+\include CustomizingEigen_Inheritance.cpp
+
+Output: \verbinclude CustomizingEigen_Inheritance.out
+
+This is the kind of error you can get if you don't provide those methods
+\verbatim
+error: no match for ‘operator=’ in ‘v = Eigen::operator*(
+const Eigen::MatrixBase<Eigen::Matrix<double, -0x000000001, 1, 0, -0x000000001, 1> >::Scalar&, 
+const Eigen::MatrixBase<Eigen::Matrix<double, -0x000000001, 1> >::StorageBaseType&)
+(((const Eigen::MatrixBase<Eigen::Matrix<double, -0x000000001, 1> >::StorageBaseType&)
+((const Eigen::MatrixBase<Eigen::Matrix<double, -0x000000001, 1> >::StorageBaseType*)(& v))))’
+\endverbatim
+
+*/
+
+}

ADDED   3rd_party/eigen/doc/CustomizingEigen_NullaryExpr.dox
Index: 3rd_party/eigen/doc/CustomizingEigen_NullaryExpr.dox
==================================================================
--- 3rd_party/eigen/doc/CustomizingEigen_NullaryExpr.dox
+++ 3rd_party/eigen/doc/CustomizingEigen_NullaryExpr.dox
@@ -0,0 +1,86 @@
+namespace Eigen {
+
+/** \page TopicCustomizing_NullaryExpr Matrix manipulation via nullary-expressions
+
+
+The main purpose of the class CwiseNullaryOp is to define \em procedural matrices such as constant or random matrices as returned by the Ones(), Zero(), Constant(), Identity() and Random() methods.
+Nevertheless, with some imagination it is possible to accomplish very sophisticated matrix manipulation with minimal efforts such that \ref TopicNewExpressionType "implementing new expression" is rarely needed.
+
+\section NullaryExpr_Circulant Example 1: circulant matrix
+
+To explore these possibilities let us start with the  \em circulant example of the \ref TopicNewExpressionType "implementing new expression" topic.
+Let us recall that a circulant matrix is a matrix where each column is the same as the
+column to the left, except that it is cyclically shifted downwards.
+For example, here is a 4-by-4 circulant matrix:
+\f[ \begin{bmatrix}
+    1 & 8 & 4 & 2 \\
+    2 & 1 & 8 & 4 \\
+    4 & 2 & 1 & 8 \\
+    8 & 4 & 2 & 1
+\end{bmatrix} \f]
+A circulant matrix is uniquely determined by its first column. We wish
+to write a function \c makeCirculant which, given the first column,
+returns an expression representing the circulant matrix.
+
+For this exercise, the return type of \c makeCirculant will be a CwiseNullaryOp that we need to instantiate with:
+1 - a proper \c circulant_functor storing the input vector and implementing the adequate coefficient accessor \c operator(i,j)
+2 - a template instantiation of class Matrix conveying compile-time information such as the scalar type, sizes, and preferred storage layout.
+
+Calling \c ArgType the type of the input vector, we can construct the equivalent squared Matrix type as follows:
+
+\snippet make_circulant2.cpp square
+
+This little helper structure will help us to implement our \c makeCirculant function as follows:
+
+\snippet make_circulant2.cpp makeCirculant
+
+As usual, our function takes as argument a \c MatrixBase (see this \ref TopicFunctionTakingEigenTypes "page" for more details).
+Then, the CwiseNullaryOp object is constructed through the DenseBase::NullaryExpr static method with the adequate runtime sizes.
+
+Then, we need to implement our \c circulant_functor, which is a straightforward exercise:
+
+\snippet make_circulant2.cpp circulant_func
+
+We are now all set to try our new feature:
+
+\snippet make_circulant2.cpp main
+
+
+If all the fragments are combined, the following output is produced,
+showing that the program works as expected:
+
+\include make_circulant2.out
+
+This implementation of \c makeCirculant is much simpler than \ref TopicNewExpressionType "defining a new expression" from scratch.
+
+
+\section NullaryExpr_Indexing Example 2: indexing rows and columns
+
+The goal here is to mimic MatLab's ability to index a matrix through two vectors of indices referencing the rows and columns to be picked respectively, like this:
+
+\snippet nullary_indexing.out main1
+
+To this end, let us first write a nullary-functor storing references to the input matrix and to the two arrays of indices, and implementing the required \c operator()(i,j):
+
+\snippet nullary_indexing.cpp functor
+
+Then, let's create an \c indexing(A,rows,cols) function creating the nullary expression:
+
+\snippet nullary_indexing.cpp function
+
+Finally, here is an example of how this function can be used:
+
+\snippet nullary_indexing.cpp main1
+
+This straightforward implementation is already quite powerful as the row or column index arrays can also be expressions to perform offsetting, modulo, striding, reverse, etc.
+
+\snippet nullary_indexing.cpp main2
+
+and the output is:
+
+\snippet nullary_indexing.out main2
+
+*/
+
+}
+

ADDED   3rd_party/eigen/doc/CustomizingEigen_Plugins.dox
Index: 3rd_party/eigen/doc/CustomizingEigen_Plugins.dox
==================================================================
--- 3rd_party/eigen/doc/CustomizingEigen_Plugins.dox
+++ 3rd_party/eigen/doc/CustomizingEigen_Plugins.dox
@@ -0,0 +1,69 @@
+namespace Eigen {
+
+/** \page TopicCustomizing_Plugins Extending MatrixBase (and other classes)
+
+In this section we will see how to add custom methods to MatrixBase. Since all expressions and matrix types inherit MatrixBase, adding a method to MatrixBase make it immediately available to all expressions ! A typical use case is, for instance, to make Eigen compatible with another API.
+
+You certainly know that in C++ it is not possible to add methods to an existing class. So how that's possible ? Here the trick is to include in the declaration of MatrixBase a file defined by the preprocessor token \c EIGEN_MATRIXBASE_PLUGIN:
+\code
+class MatrixBase {
+  // ...
+  #ifdef EIGEN_MATRIXBASE_PLUGIN
+  #include EIGEN_MATRIXBASE_PLUGIN
+  #endif
+};
+\endcode
+Therefore to extend MatrixBase with your own methods you just have to create a file with your method declaration and define EIGEN_MATRIXBASE_PLUGIN before you include any Eigen's header file.
+
+You can extend many of the other classes used in Eigen by defining similarly named preprocessor symbols. For instance, define \c EIGEN_ARRAYBASE_PLUGIN if you want to extend the ArrayBase class. A full list of classes that can be extended in this way and the corresponding preprocessor symbols can be found on our page \ref TopicPreprocessorDirectives.
+
+Here is an example of an extension file for adding methods to MatrixBase: \n
+\b MatrixBaseAddons.h
+\code
+inline Scalar at(uint i, uint j) const { return this->operator()(i,j); }
+inline Scalar& at(uint i, uint j) { return this->operator()(i,j); }
+inline Scalar at(uint i) const { return this->operator[](i); }
+inline Scalar& at(uint i) { return this->operator[](i); }
+
+inline RealScalar squaredLength() const { return squaredNorm(); }
+inline RealScalar length() const { return norm(); }
+inline RealScalar invLength(void) const { return fast_inv_sqrt(squaredNorm()); }
+
+template<typename OtherDerived>
+inline Scalar squaredDistanceTo(const MatrixBase<OtherDerived>& other) const
+{ return (derived() - other.derived()).squaredNorm(); }
+
+template<typename OtherDerived>
+inline RealScalar distanceTo(const MatrixBase<OtherDerived>& other) const
+{ return internal::sqrt(derived().squaredDistanceTo(other)); }
+
+inline void scaleTo(RealScalar l) { RealScalar vl = norm(); if (vl>1e-9) derived() *= (l/vl); }
+
+inline Transpose<Derived> transposed() {return this->transpose();}
+inline const Transpose<Derived> transposed() const {return this->transpose();}
+
+inline uint minComponentId(void) const  { int i; this->minCoeff(&i); return i; }
+inline uint maxComponentId(void) const  { int i; this->maxCoeff(&i); return i; }
+
+template<typename OtherDerived>
+void makeFloor(const MatrixBase<OtherDerived>& other) { derived() = derived().cwiseMin(other.derived()); }
+template<typename OtherDerived>
+void makeCeil(const MatrixBase<OtherDerived>& other) { derived() = derived().cwiseMax(other.derived()); }
+
+const CwiseBinaryOp<internal::scalar_sum_op<Scalar>, const Derived, const ConstantReturnType>
+operator+(const Scalar& scalar) const
+{ return CwiseBinaryOp<internal::scalar_sum_op<Scalar>, const Derived, const ConstantReturnType>(derived(), Constant(rows(),cols(),scalar)); }
+
+friend const CwiseBinaryOp<internal::scalar_sum_op<Scalar>, const ConstantReturnType, Derived>
+operator+(const Scalar& scalar, const MatrixBase<Derived>& mat)
+{ return CwiseBinaryOp<internal::scalar_sum_op<Scalar>, const ConstantReturnType, Derived>(Constant(rows(),cols(),scalar), mat.derived()); }
+\endcode
+
+Then one can the following declaration in the config.h or whatever prerequisites header file of his project:
+\code
+#define EIGEN_MATRIXBASE_PLUGIN "MatrixBaseAddons.h"
+\endcode
+
+*/
+
+}

ADDED   3rd_party/eigen/doc/DenseDecompositionBenchmark.dox
Index: 3rd_party/eigen/doc/DenseDecompositionBenchmark.dox
==================================================================
--- 3rd_party/eigen/doc/DenseDecompositionBenchmark.dox
+++ 3rd_party/eigen/doc/DenseDecompositionBenchmark.dox
@@ -0,0 +1,42 @@
+namespace Eigen {
+
+/** \eigenManualPage DenseDecompositionBenchmark Benchmark of dense decompositions
+
+This page presents a speed comparison of the dense matrix decompositions offered by %Eigen for a wide range of square matrices and overconstrained problems.
+
+For a more general overview on the features and numerical robustness of linear solvers and decompositions, check this \link TopicLinearAlgebraDecompositions table \endlink.
+
+This benchmark has been run on a laptop equipped with an Intel core i7 \@ 2,6 GHz, and compiled with clang with \b AVX and \b FMA instruction sets enabled but without multi-threading.
+It uses \b single \b precision \b float numbers. For double, you can get a good estimate by multiplying the timings by a factor 2.
+
+The square matrices are symmetric, and for the overconstrained matrices, the reported timmings include the cost to compute the symmetric covariance matrix \f$ A^T A \f$ for the first four solvers based on Cholesky and LU, as denoted by the \b * symbol (top-right corner part of the table).
+Timings are in \b milliseconds, and factors are relative to the LLT decomposition which is the fastest but also the least general and robust.
+
+<table class="manual">
+<tr><th>solver/size</th>
+  <th>8x8</th>  <th>100x100</th>  <th>1000x1000</th>  <th>4000x4000</th>  <th>10000x8</th>  <th>10000x100</th>  <th>10000x1000</th>  <th>10000x4000</th></tr>
+<tr><td>LLT</td><td>0.05</td><td>0.42</td><td>5.83</td><td>374.55</td><td>6.79 <sup><a href="#note_ls">*</a></sup></td><td>30.15 <sup><a href="#note_ls">*</a></sup></td><td>236.34 <sup><a href="#note_ls">*</a></sup></td><td>3847.17 <sup><a href="#note_ls">*</a></sup></td></tr>
+<tr class="alt"><td>LDLT</td><td>0.07 (x1.3)</td><td>0.65 (x1.5)</td><td>26.86 (x4.6)</td><td>2361.18 (x6.3)</td><td>6.81 (x1) <sup><a href="#note_ls">*</a></sup></td><td>31.91 (x1.1) <sup><a href="#note_ls">*</a></sup></td><td>252.61 (x1.1) <sup><a href="#note_ls">*</a></sup></td><td>5807.66 (x1.5) <sup><a href="#note_ls">*</a></sup></td></tr>
+<tr><td>PartialPivLU</td><td>0.08 (x1.5)</td><td>0.69 (x1.6)</td><td>15.63 (x2.7)</td><td>709.32 (x1.9)</td><td>6.81 (x1) <sup><a href="#note_ls">*</a></sup></td><td>31.32 (x1) <sup><a href="#note_ls">*</a></sup></td><td>241.68 (x1) <sup><a href="#note_ls">*</a></sup></td><td>4270.48 (x1.1) <sup><a href="#note_ls">*</a></sup></td></tr>
+<tr class="alt"><td>FullPivLU</td><td>0.1 (x1.9)</td><td>4.48 (x10.6)</td><td>281.33 (x48.2)</td><td>-</td><td>6.83 (x1) <sup><a href="#note_ls">*</a></sup></td><td>32.67 (x1.1) <sup><a href="#note_ls">*</a></sup></td><td>498.25 (x2.1) <sup><a href="#note_ls">*</a></sup></td><td>-</td></tr>
+<tr><td>HouseholderQR</td><td>0.19 (x3.5)</td><td>2.18 (x5.2)</td><td>23.42 (x4)</td><td>1337.52 (x3.6)</td><td>34.26 (x5)</td><td>129.01 (x4.3)</td><td>377.37 (x1.6)</td><td>4839.1 (x1.3)</td></tr>
+<tr class="alt"><td>ColPivHouseholderQR</td><td>0.23 (x4.3)</td><td>2.23 (x5.3)</td><td>103.34 (x17.7)</td><td>9987.16 (x26.7)</td><td>36.05 (x5.3)</td><td>163.18 (x5.4)</td><td>2354.08 (x10)</td><td>37860.5 (x9.8)</td></tr>
+<tr><td>CompleteOrthogonalDecomposition</td><td>0.23 (x4.3)</td><td>2.22 (x5.2)</td><td>99.44 (x17.1)</td><td>10555.3 (x28.2)</td><td>35.75 (x5.3)</td><td>169.39 (x5.6)</td><td>2150.56 (x9.1)</td><td>36981.8 (x9.6)</td></tr>
+<tr class="alt"><td>FullPivHouseholderQR</td><td>0.23 (x4.3)</td><td>4.64 (x11)</td><td>289.1 (x49.6)</td><td>-</td><td>69.38 (x10.2)</td><td>446.73 (x14.8)</td><td>4852.12 (x20.5)</td><td>-</td></tr>
+<tr><td>JacobiSVD</td><td>1.01 (x18.6)</td><td>71.43 (x168.4)</td><td>-</td><td>-</td><td>113.81 (x16.7)</td><td>1179.66 (x39.1)</td><td>-</td><td>-</td></tr>
+<tr class="alt"><td>BDCSVD</td><td>1.07 (x19.7)</td><td>21.83 (x51.5)</td><td>331.77 (x56.9)</td><td>18587.9 (x49.6)</td><td>110.53 (x16.3)</td><td>397.67 (x13.2)</td><td>2975 (x12.6)</td><td>48593.2 (x12.6)</td></tr>
+</table>
+
+<a name="note_ls">\b *: </a> This decomposition do not support direct least-square solving for over-constrained problems, and the reported timing include the cost to form the symmetric covariance matrix \f$ A^T A \f$.
+
+\b Observations:
+ + LLT is always the fastest solvers.
+ + For largely over-constrained problems, the cost of Cholesky/LU decompositions is dominated by the computation of the symmetric covariance matrix.
+ + For large problem sizes, only the decomposition implementing a cache-friendly blocking strategy scale well. Those include LLT, PartialPivLU, HouseholderQR, and BDCSVD. This explain why for a 4k x 4k matrix, HouseholderQR is faster than LDLT. In the future, LDLT and ColPivHouseholderQR will also implement blocking strategies.
+ + CompleteOrthogonalDecomposition is based on ColPivHouseholderQR and they thus achieve the same level of performance.
+
+The above table has been generated by the <a href="https://bitbucket.org/eigen/eigen/raw/default/bench/dense_solvers.cpp">bench/dense_solvers.cpp</a> file, feel-free to hack it to generate a table matching your hardware, compiler, and favorite problem sizes.
+
+*/
+
+}

Index: 3rd_party/eigen/doc/Doxyfile.in
==================================================================
--- 3rd_party/eigen/doc/Doxyfile.in
+++ 3rd_party/eigen/doc/Doxyfile.in
@@ -123,11 +123,11 @@
 # If the INLINE_INHERITED_MEMB tag is set to YES, doxygen will show all
 # inherited members of a class in the documentation of that class as if those
 # members were ordinary class members. Constructors, destructors and assignment
 # operators of the base classes will not be shown.
 
-INLINE_INHERITED_MEMB  = YES
+INLINE_INHERITED_MEMB  = NO
 
 # If the FULL_PATH_NAMES tag is set to YES then Doxygen will prepend the full
 # path before files name in the file list and in the header files. If set
 # to NO the shortest path that makes the file name unique will be used.
 
@@ -204,27 +204,35 @@
 # put the command \sideeffect (or @sideeffect) in the documentation, which
 # will result in a user-defined paragraph with heading "Side Effects:".
 # You can put \n's in the value part of an alias to insert newlines.
 
 ALIASES                = "only_for_vectors=This is only for vectors (either row-vectors or column-vectors), i.e. matrices which are known at compile-time to have either one row or one column." \
+                         "not_reentrant=\warning This function is not re-entrant." \
                          "array_module=This is defined in the %Array module. \code #include <Eigen/Array> \endcode" \
                          "cholesky_module=This is defined in the %Cholesky module. \code #include <Eigen/Cholesky> \endcode" \
                          "eigenvalues_module=This is defined in the %Eigenvalues module. \code #include <Eigen/Eigenvalues> \endcode" \
                          "geometry_module=This is defined in the %Geometry module. \code #include <Eigen/Geometry> \endcode" \
                          "householder_module=This is defined in the %Householder module. \code #include <Eigen/Householder> \endcode" \
                          "jacobi_module=This is defined in the %Jacobi module. \code #include <Eigen/Jacobi> \endcode" \
                          "lu_module=This is defined in the %LU module. \code #include <Eigen/LU> \endcode" \
                          "qr_module=This is defined in the %QR module. \code #include <Eigen/QR> \endcode" \
                          "svd_module=This is defined in the %SVD module. \code #include <Eigen/SVD> \endcode" \
+                         "specialfunctions_module=This is defined in the \b unsupported SpecialFunctions module. \code #include <Eigen/SpecialFunctions> \endcode" \
                          "label=\bug" \
                          "matrixworld=<a href='#matrixonly' style='color:green;text-decoration: none;'>*</a>" \
                          "arrayworld=<a href='#arrayonly' style='color:blue;text-decoration: none;'>*</a>" \
                          "note_about_arbitrary_choice_of_solution=If there exists more than one solution, this method will arbitrarily choose one." \
                          "note_about_using_kernel_to_study_multiple_solutions=If you need a complete analysis of the space of solutions, take the one solution obtained by this method and add to it elements of the kernel, as determined by kernel()." \
                          "note_about_checking_solutions=This method just tries to find as good a solution as possible. If you want to check whether a solution exists or if it is accurate, just call this function to get a result and then compute the error of this result, or use MatrixBase::isApprox() directly, for instance like this: \code bool a_solution_exists = (A*result).isApprox(b, precision); \endcode This method avoids dividing by zero, so that the non-existence of a solution doesn't by itself mean that you'll get \c inf or \c nan values." \
                          "note_try_to_help_rvo=This function returns the result by value. In order to make that efficient, it is implemented as just a return statement using a special constructor, hopefully allowing the compiler to perform a RVO (return value optimization)." \
-                         "nonstableyet=\warning This is not considered to be part of the stable public API yet. Changes may happen in future releases. See \ref Experimental \"Experimental parts of Eigen\"
+                         "nonstableyet=\warning This is not considered to be part of the stable public API yet. Changes may happen in future releases. See \ref Experimental \"Experimental parts of Eigen\"" \
+                         "implsparsesolverconcept=This class follows the \link TutorialSparseSolverConcept sparse solver concept \endlink." \
+                         "blank= " \
+                         "cpp11=<span class='cpp11'>[c++11]</span>" \
+                         "cpp14=<span class='cpp14'>[c++14]</span>" \
+                         "cpp17=<span class='cpp17'>[c++17]</span>"
+                         
 
 ALIASES += "eigenAutoToc=  "
 ALIASES += "eigenManualPage=\defgroup"
 
 # This tag can be used to specify a number of word-keyword mappings (TCL only).
@@ -268,11 +276,11 @@
 # C++, D, PHP, Objective-C, Python, Fortran, VHDL, C, C++. For instance to make
 # doxygen treat .inc files as Fortran files (default is PHP), and .f files as C
 # (default is Fortran), use: inc=Fortran f=C. Note that for custom extensions
 # you also need to set FILE_PATTERNS otherwise the files are not read by doxygen.
 
-EXTENSION_MAPPING      =
+EXTENSION_MAPPING      = .h=C++ no_extension=C++
 
 # If MARKDOWN_SUPPORT is enabled (the default) then doxygen pre-processes all
 # comments according to the Markdown format, which allows for more readable
 # documentation. See http://daringfireball.net/projects/markdown/ for details.
 # The output of markdown processing is further processed by doxygen, so you
@@ -313,11 +321,11 @@
 # If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC
 # tag is set to YES, then doxygen will reuse the documentation of the first
 # member in the group (if any) for the other members of the group. By default
 # all members of a group must be documented explicitly.
 
-DISTRIBUTE_GROUP_DOC   = NO
+DISTRIBUTE_GROUP_DOC   = YES
 
 # Set the SUBGROUPING tag to YES (the default) to allow class member groups of
 # the same type (for instance a group of public functions) to be put as a
 # subgroup of that type (e.g. under the Public Functions section). Set it to
 # NO to prevent subgrouping. Alternatively, this can be done per class using
@@ -363,11 +371,11 @@
 # a logarithmic scale so increasing the size by one will roughly double the
 # memory usage. The cache size is given by this formula:
 # 2^(16+SYMBOL_CACHE_SIZE). The valid range is 0..9, the default is 0,
 # corresponding to a cache size of 2^16 = 65536 symbols.
 
-SYMBOL_CACHE_SIZE      = 0
+# SYMBOL_CACHE_SIZE      = 0
 
 # Similar to the SYMBOL_CACHE_SIZE the size of the symbol lookup cache can be
 # set using LOOKUP_CACHE_SIZE. This cache is used to resolve symbols given
 # their name and scope. Since this can be an expensive process and often the
 # same symbol appear multiple times in the code, doxygen keeps a cache of
@@ -456,11 +464,11 @@
 # The INTERNAL_DOCS tag determines if documentation
 # that is typed after a \internal command is included. If the tag is set
 # to NO (the default) then the documentation will be excluded.
 # Set it to YES to include the internal documentation.
 
-INTERNAL_DOCS          = NO
+INTERNAL_DOCS          = ${EIGEN_DOXY_INTERNAL}
 
 # If the CASE_SENSE_NAMES tag is set to NO then Doxygen will only generate
 # file names in lower-case letters. If set to YES upper-case letters are also
 # allowed. This is useful if you have classes or files whose names only differ
 # in case and if your file system supports case sensitive file names. Windows
@@ -470,17 +478,17 @@
 
 # If the HIDE_SCOPE_NAMES tag is set to NO (the default) then Doxygen
 # will show members with their full class and namespace scopes in the
 # documentation. If set to YES the scope will be hidden.
 
-HIDE_SCOPE_NAMES       = YES
+HIDE_SCOPE_NAMES       = NO
 
 # If the SHOW_INCLUDE_FILES tag is set to YES (the default) then Doxygen
 # will put a list of the files that are included by a file in the documentation
 # of that file.
 
-SHOW_INCLUDE_FILES     = NO
+SHOW_INCLUDE_FILES     = ${EIGEN_DOXY_INTERNAL}
 
 # If the FORCE_LOCAL_INCLUDES tag is set to YES then Doxygen
 # will list include files with double quotes in the documentation
 # rather than with sharp brackets.
 
@@ -542,11 +550,11 @@
 
 # The GENERATE_TODOLIST tag can be used to enable (YES) or
 # disable (NO) the todo list. This list is created by putting \todo
 # commands in the documentation.
 
-GENERATE_TODOLIST      = NO
+GENERATE_TODOLIST      = ${EIGEN_DOXY_INTERNAL}
 
 # The GENERATE_TESTLIST tag can be used to enable (YES) or
 # disable (NO) the test list. This list is created by putting \test
 # commands in the documentation.
 
@@ -554,17 +562,17 @@
 
 # The GENERATE_BUGLIST tag can be used to enable (YES) or
 # disable (NO) the bug list. This list is created by putting \bug
 # commands in the documentation.
 
-GENERATE_BUGLIST       = NO
+GENERATE_BUGLIST       = ${EIGEN_DOXY_INTERNAL}
 
 # The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or
 # disable (NO) the deprecated list. This list is created by putting
 # \deprecated commands in the documentation.
 
-GENERATE_DEPRECATEDLIST= NO
+GENERATE_DEPRECATEDLIST= YES
 
 # The ENABLED_SECTIONS tag can be used to enable conditional
 # documentation sections, marked by \if sectionname ... \endif.
 
 ENABLED_SECTIONS       =
@@ -717,11 +725,12 @@
 # excluded from the INPUT source files. This way you can easily exclude a
 # subdirectory from a directory tree whose root is specified with the INPUT tag.
 # Note that relative paths are relative to the directory from which doxygen is
 # run.
 
-EXCLUDE                = "${Eigen_SOURCE_DIR}/Eigen/Eigen2Support" \
+EXCLUDE                = "${Eigen_SOURCE_DIR}/Eigen/src/Core/products" \
+                         "${Eigen_SOURCE_DIR}/Eigen/Eigen2Support" \
                          "${Eigen_SOURCE_DIR}/Eigen/src/Eigen2Support" \
                          "${Eigen_SOURCE_DIR}/doc/examples" \
                          "${Eigen_SOURCE_DIR}/doc/special_examples" \
                          "${Eigen_SOURCE_DIR}/doc/snippets" \
                          "${Eigen_SOURCE_DIR}/unsupported/doc/examples" \
@@ -798,11 +807,11 @@
 
 # The IMAGE_PATH tag can be used to specify one or more files or
 # directories that contain image that are included in the documentation (see
 # the \image command).
 
-IMAGE_PATH             =
+IMAGE_PATH             = ${Eigen_BINARY_DIR}/doc/html
 
 # The INPUT_FILTER tag can be used to specify a program that doxygen should
 # invoke to filter for each input file. Doxygen will invoke the filter program
 # by executing (via popen()) the command <filter> <input-file>, where <filter>
 # is the value of the INPUT_FILTER tag, and <input-file> is the name of an
@@ -862,17 +871,17 @@
 
 # If the REFERENCED_BY_RELATION tag is set to YES
 # then for each documented function all documented
 # functions referencing it will be listed.
 
-REFERENCED_BY_RELATION = YES
+REFERENCED_BY_RELATION = NO
 
 # If the REFERENCES_RELATION tag is set to YES
 # then for each documented function all documented entities
 # called/used by that function will be listed.
 
-REFERENCES_RELATION    = YES
+REFERENCES_RELATION    = NO
 
 # If the REFERENCES_LINK_SOURCE tag is set to YES (the default)
 # and SOURCE_BROWSER tag is set to YES, then the hyperlinks from
 # functions in REFERENCES_RELATION and REFERENCED_BY_RELATION lists will
 # link to the source code.
@@ -1463,17 +1472,17 @@
 
 # The XML_SCHEMA tag can be used to specify an XML schema,
 # which can be used by a validating XML parser to check the
 # syntax of the XML files.
 
-XML_SCHEMA             =
+# XML_SCHEMA             =
 
 # The XML_DTD tag can be used to specify an XML DTD,
 # which can be used by a validating XML parser to check the
 # syntax of the XML files.
 
-XML_DTD                =
+# XML_DTD                =
 
 # If the XML_PROGRAMLISTING tag is set to YES Doxygen will
 # dump the program listings (including syntax highlighting
 # and cross-referencing information) to the XML output. Note that
 # enabling this will significantly increase the size of the XML output.
@@ -1579,13 +1588,18 @@
 PREDEFINED             = EIGEN_EMPTY_STRUCT \
                          EIGEN_PARSED_BY_DOXYGEN \
                          EIGEN_VECTORIZE \
                          EIGEN_QT_SUPPORT \
                          EIGEN_STRONG_INLINE=inline \
-                         "EIGEN2_SUPPORT_STAGE=99" \
+                         EIGEN_DEVICE_FUNC= \
                          "EIGEN_MAKE_CWISE_BINARY_OP(METHOD,FUNCTOR)=template<typename OtherDerived> const CwiseBinaryOp<FUNCTOR<Scalar>, const Derived, const OtherDerived> METHOD(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const;" \
-                         "EIGEN_CWISE_PRODUCT_RETURN_TYPE(LHS,RHS)=CwiseBinaryOp<internal::scalar_product_op<typename LHS::Scalar, typename RHS::Scalar >, const LHS, const RHS>"
+                         "EIGEN_CWISE_PRODUCT_RETURN_TYPE(LHS,RHS)=CwiseBinaryOp<internal::scalar_product_op<LHS::Scalar,RHS::Scalar>, const LHS, const RHS>"\
+                         "EIGEN_CAT2(a,b)= a ## b"\
+                         "EIGEN_CAT(a,b)=EIGEN_CAT2(a,b)"\
+                         "EIGEN_CWISE_BINARY_RETURN_TYPE(LHS,RHS,OPNAME)=CwiseBinaryOp<EIGEN_CAT(EIGEN_CAT(internal::scalar_,OPNAME),_op)<LHS::Scalar, RHS::Scalar>, const LHS, const RHS>"\
+                         DOXCOMMA=,
+
 
 # If the MACRO_EXPANSION and EXPAND_ONLY_PREDEF tags are set to YES then
 # this tag can be used to specify a list of macro names that should be expanded.
 # The macro definition that is found in the sources will be used.
 # Use the PREDEFINED tag if you want to use a different macro definition that
@@ -1597,11 +1611,19 @@
                          EIGEN_CWISE_UNOP_RETURN_TYPE \
                          EIGEN_CWISE_BINOP_RETURN_TYPE \
                          EIGEN_CURRENT_STORAGE_BASE_CLASS \
                          EIGEN_MATHFUNC_IMPL \
                          _EIGEN_GENERIC_PUBLIC_INTERFACE \
-                         EIGEN2_SUPPORT
+                         EIGEN_ARRAY_DECLARE_GLOBAL_UNARY \
+                         EIGEN_EMPTY \
+                         EIGEN_EULER_ANGLES_TYPEDEFS \
+                         EIGEN_EULER_ANGLES_SINGLE_TYPEDEF \
+                         EIGEN_EULER_SYSTEM_TYPEDEF \
+                         EIGEN_DOC_UNARY_ADDONS \
+                         EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL \
+                         EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF
+
 
 # If the SKIP_FUNCTION_MACROS tag is set to YES (the default) then
 # doxygen's preprocessor will remove all references to function-like macros
 # that are alone on a line, have an all uppercase name, and do not end with a
 # semicolon, because these will confuse the parser if not removed.
@@ -1697,11 +1719,11 @@
 # the font name using DOT_FONTNAME. You need to make sure dot is able to find
 # the font, which can be done by putting it in a standard location or by setting
 # the DOTFONTPATH environment variable or by setting DOT_FONTPATH to the
 # directory containing the font.
 
-DOT_FONTNAME           = FreeSans
+DOT_FONTNAME           = 
 
 # The DOT_FONTSIZE tag can be used to set the size of the font of dot graphs.
 # The default size is 10pt.
 
 DOT_FONTSIZE           = 10

Index: 3rd_party/eigen/doc/FixedSizeVectorizable.dox
==================================================================
--- 3rd_party/eigen/doc/FixedSizeVectorizable.dox
+++ 3rd_party/eigen/doc/FixedSizeVectorizable.dox
@@ -2,11 +2,11 @@
 
 /** \eigenManualPage TopicFixedSizeVectorizable Fixed-size vectorizable Eigen objects
 
 The goal of this page is to explain what we mean by "fixed-size vectorizable".
 
-\section summary Executive Summary
+\section FixedSizeVectorizable_summary Executive Summary
 
 An Eigen object is called "fixed-size vectorizable" if it has fixed size and that size is a multiple of 16 bytes.
 
 Examples include:
 \li Eigen::Vector2d
@@ -19,11 +19,11 @@
 \li Eigen::Affine3d
 \li Eigen::Affine3f
 \li Eigen::Quaterniond
 \li Eigen::Quaternionf
 
-\section explanation Explanation
+\section FixedSizeVectorizable_explanation Explanation
 
 First, "fixed-size" should be clear: an Eigen object has fixed size if its number of rows and its number of columns are fixed at compile-time. So for example Matrix3f has fixed size, but MatrixXf doesn't (the opposite of fixed-size is dynamic-size).
 
 The array of coefficients of a fixed-size Eigen object is a plain "static array", it is not dynamically allocated. For example, the data behind a Matrix4f is just a "float array[16]".
 

ADDED   3rd_party/eigen/doc/InplaceDecomposition.dox
Index: 3rd_party/eigen/doc/InplaceDecomposition.dox
==================================================================
--- 3rd_party/eigen/doc/InplaceDecomposition.dox
+++ 3rd_party/eigen/doc/InplaceDecomposition.dox
@@ -0,0 +1,115 @@
+namespace Eigen {
+
+/** \eigenManualPage InplaceDecomposition Inplace matrix decompositions
+
+Starting from %Eigen 3.3, the LU, Cholesky, and QR decompositions can operate \em inplace, that is, directly within the given input matrix.
+This feature is especially useful when dealing with huge matrices, and or when the available memory is very limited (embedded systems).
+
+To this end, the respective decomposition class must be instantiated with a Ref<> matrix type, and the decomposition object must be constructed with the input matrix as argument. As an example, let us consider an inplace LU decomposition with partial pivoting.
+
+Let's start with the basic inclusions, and declaration of a 2x2 matrix \c A:
+
+<table class="example">
+<tr><th>code</th><th>output</th></tr>
+<tr>
+  <td>\snippet TutorialInplaceLU.cpp init
+  </td>
+  <td>\snippet TutorialInplaceLU.out init
+  </td>
+</tr>
+</table>
+
+No surprise here! Then, let's declare our inplace LU object \c lu, and check the content of the matrix \c A:
+
+<table class="example">
+<tr>
+  <td>\snippet TutorialInplaceLU.cpp declaration
+  </td>
+  <td>\snippet TutorialInplaceLU.out declaration
+  </td>
+</tr>
+</table>
+
+Here, the \c lu object computes and stores the \c L and \c U factors within the memory held by the matrix \c A.
+The coefficients of \c A have thus been destroyed during the factorization, and replaced by the L and U factors as one can verify:
+
+<table class="example">
+<tr>
+  <td>\snippet TutorialInplaceLU.cpp matrixLU
+  </td>
+  <td>\snippet TutorialInplaceLU.out matrixLU
+  </td>
+</tr>
+</table>
+
+Then, one can use the \c lu object as usual, for instance to solve the Ax=b problem:
+<table class="example">
+<tr>
+  <td>\snippet TutorialInplaceLU.cpp solve
+  </td>
+  <td>\snippet TutorialInplaceLU.out solve
+  </td>
+</tr>
+</table>
+
+Here, since the content of the original matrix \c A has been lost, we had to declared a new matrix \c A0 to verify the result.
+
+Since the memory is shared between \c A and \c lu, modifying the matrix \c A will make \c lu invalid.
+This can easily be verified by modifying the content of \c A and trying to solve the initial problem again:
+
+<table class="example">
+<tr>
+  <td>\snippet TutorialInplaceLU.cpp modifyA
+  </td>
+  <td>\snippet TutorialInplaceLU.out modifyA
+  </td>
+</tr>
+</table>
+
+Note that there is no shared pointer under the hood, it is the \b responsibility \b of \b the \b user to keep the input matrix \c A in life as long as \c lu is living.
+
+If one wants to update the factorization with the modified A, one has to call the compute method as usual:
+<table class="example">
+<tr>
+  <td>\snippet TutorialInplaceLU.cpp recompute
+  </td>
+  <td>\snippet TutorialInplaceLU.out recompute
+  </td>
+</tr>
+</table>
+
+Note that calling compute does not change the memory which is referenced by the \c lu object. Therefore, if the compute method is called with another matrix \c A1 different than \c A, then the content of \c A1 won't be modified. This is still the content of \c A that will be used to store the L and U factors of the matrix \c A1.
+This can easily be verified as follows:
+<table class="example">
+<tr>
+  <td>\snippet TutorialInplaceLU.cpp recompute_bis0
+ </td>
+  <td>\snippet TutorialInplaceLU.out recompute_bis0
+ </td>
+</tr>
+</table>
+The matrix \c A1 is unchanged, and one can thus solve A1*x=b, and directly check the residual without any copy of \c A1:
+<table class="example">
+<tr>
+  <td>\snippet TutorialInplaceLU.cpp recompute_bis1
+  </td>
+  <td>\snippet TutorialInplaceLU.out recompute_bis1
+ </td>
+</tr>
+</table>
+
+
+Here is the list of matrix decompositions supporting this inplace mechanism:
+
+- class LLT
+- class LDLT
+- class PartialPivLU
+- class FullPivLU
+- class HouseholderQR
+- class ColPivHouseholderQR
+- class FullPivHouseholderQR
+- class CompleteOrthogonalDecomposition
+
+*/
+
+}

ADDED   3rd_party/eigen/doc/LeastSquares.dox
Index: 3rd_party/eigen/doc/LeastSquares.dox
==================================================================
--- 3rd_party/eigen/doc/LeastSquares.dox
+++ 3rd_party/eigen/doc/LeastSquares.dox
@@ -0,0 +1,70 @@
+namespace Eigen {
+
+/** \eigenManualPage LeastSquares Solving linear least squares systems
+
+This page describes how to solve linear least squares systems using %Eigen. An overdetermined system
+of equations, say \a Ax = \a b, has no solutions. In this case, it makes sense to search for the
+vector \a x which is closest to being a solution, in the sense that the difference \a Ax - \a b is
+as small as possible. This \a x is called the least square solution (if the Euclidean norm is used).
+
+The three methods discussed on this page are the SVD decomposition, the QR decomposition and normal
+equations. Of these, the SVD decomposition is generally the most accurate but the slowest, normal
+equations is the fastest but least accurate, and the QR decomposition is in between.
+
+\eigenAutoToc
+
+
+\section LeastSquaresSVD Using the SVD decomposition
+
+The \link JacobiSVD::solve() solve() \endlink method in the JacobiSVD class can be directly used to
+solve linear squares systems. It is not enough to compute only the singular values (the default for
+this class); you also need the singular vectors but the thin SVD decomposition suffices for
+computing least squares solutions:
+
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr>
+  <td>\include TutorialLinAlgSVDSolve.cpp </td>
+  <td>\verbinclude TutorialLinAlgSVDSolve.out </td>
+</tr>
+</table>
+
+This is example from the page \link TutorialLinearAlgebra Linear algebra and decompositions \endlink.
+
+
+\section LeastSquaresQR Using the QR decomposition
+
+The solve() method in QR decomposition classes also computes the least squares solution. There are
+three QR decomposition classes: HouseholderQR (no pivoting, so fast but unstable),
+ColPivHouseholderQR (column pivoting, thus a bit slower but more accurate) and FullPivHouseholderQR
+(full pivoting, so slowest and most stable). Here is an example with column pivoting:
+
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr>
+  <td>\include LeastSquaresQR.cpp </td>
+  <td>\verbinclude LeastSquaresQR.out </td>
+</tr>
+</table>
+
+
+\section LeastSquaresNormalEquations Using normal equations
+
+Finding the least squares solution of \a Ax = \a b is equivalent to solving the normal equation
+<i>A</i><sup>T</sup><i>Ax</i> = <i>A</i><sup>T</sup><i>b</i>. This leads to the following code
+
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr>
+  <td>\include LeastSquaresNormalEquations.cpp </td>
+  <td>\verbinclude LeastSquaresNormalEquations.out </td>
+</tr>
+</table>
+
+If the matrix \a A is ill-conditioned, then this is not a good method, because the condition number
+of <i>A</i><sup>T</sup><i>A</i> is the square of the condition number of \a A. This means that you
+lose twice as many digits using normal equation than if you use the other methods.
+
+*/
+
+}

Index: 3rd_party/eigen/doc/Manual.dox
==================================================================
--- 3rd_party/eigen/doc/Manual.dox
+++ 3rd_party/eigen/doc/Manual.dox
@@ -1,22 +1,36 @@
 
 // This file strutures pages and modules into a convenient hierarchical structure.
 
 namespace Eigen {
+
+/** \page UserManual_CustomizingEigen Extending/Customizing Eigen
+  %Eigen can be extended in several ways, for instance, by defining global methods, by inserting custom methods within main %Eigen's classes through the \ref TopicCustomizing_Plugins "plugin" mechanism, by adding support to \ref TopicCustomizing_CustomScalar "custom scalar types" etc. See below for the respective sub-topics.
+  - \subpage TopicCustomizing_Plugins
+  - \subpage TopicCustomizing_InheritingMatrix
+  - \subpage TopicCustomizing_CustomScalar
+  - \subpage TopicCustomizing_NullaryExpr
+  - \subpage TopicNewExpressionType
+  \sa \ref TopicPreprocessorDirectives
+*/
+
 
 /** \page UserManual_Generalities General topics
   - \subpage Eigen2ToEigen3
   - \subpage TopicFunctionTakingEigenTypes
   - \subpage TopicPreprocessorDirectives
   - \subpage TopicAssertions
-  - \subpage TopicCustomizingEigen
   - \subpage TopicMultiThreading
+  - \subpage TopicUsingBlasLapack
   - \subpage TopicUsingIntelMKL
+  - \subpage TopicCUDA
+  - \subpage TopicPitfalls
   - \subpage TopicTemplateKeyword
   - \subpage UserManual_UnderstandingEigen
+  - \subpage TopicCMakeGuide
 */
-  
+
 /** \page UserManual_UnderstandingEigen Understanding Eigen
   - \subpage TopicInsideEigenExample
   - \subpage TopicClassHierarchy
   - \subpage TopicLazyEvaluation
 */
@@ -54,10 +68,12 @@
     \ingroup DenseMatrixManipulation_chapter */
 /** \addtogroup TutorialReductionsVisitorsBroadcasting
     \ingroup DenseMatrixManipulation_chapter */
 /** \addtogroup TutorialMapClass
     \ingroup DenseMatrixManipulation_chapter */
+/** \addtogroup TutorialReshapeSlicing
+    \ingroup DenseMatrixManipulation_chapter */
 /** \addtogroup TopicAliasing
     \ingroup DenseMatrixManipulation_chapter */
 /** \addtogroup TopicStorageOrders
     \ingroup DenseMatrixManipulation_chapter */
     
@@ -83,10 +99,13 @@
 /** \addtogroup Jacobi_Module
     \ingroup DenseMatrixManipulation_Reference */ 
 /** \addtogroup Householder_Module
     \ingroup DenseMatrixManipulation_Reference */ 
 
+/** \addtogroup CoeffwiseMathFunctions
+    \ingroup DenseMatrixManipulation_chapter */
+
 /** \addtogroup QuickRefPage
     \ingroup DenseMatrixManipulation_chapter */
 
 
 /** \defgroup DenseLinearSolvers_chapter Dense linear problems and decompositions */
@@ -94,10 +113,16 @@
 
 /** \addtogroup TutorialLinearAlgebra
     \ingroup DenseLinearSolvers_chapter */
 /** \addtogroup TopicLinearAlgebraDecompositions
     \ingroup DenseLinearSolvers_chapter */
+/** \addtogroup LeastSquares 
+    \ingroup DenseLinearSolvers_chapter */
+/** \addtogroup InplaceDecomposition
+    \ingroup DenseLinearSolvers_chapter */
+/** \addtogroup DenseDecompositionBenchmark
+    \ingroup DenseLinearSolvers_chapter */
 
 /** \addtogroup DenseLinearSolvers_Reference
     \ingroup DenseLinearSolvers_chapter */
 /** \addtogroup Cholesky_Module
     \ingroup DenseLinearSolvers_Reference */
@@ -117,10 +142,12 @@
 /** \defgroup Sparse_Reference Reference */
 
 /** \addtogroup TutorialSparse
     \ingroup Sparse_chapter */
 /** \addtogroup TopicSparseSystems
+    \ingroup Sparse_chapter */
+/** \addtogroup MatrixfreeSolverExample
     \ingroup Sparse_chapter */
 
 /** \addtogroup Sparse_Reference
     \ingroup Sparse_chapter */
 /** \addtogroup SparseCore_Module
@@ -154,6 +181,9 @@
     \ingroup Geometry_chapter */
 /** \addtogroup Geometry_Module
     \ingroup Geometry_Reference */
 /** \addtogroup Splines_Module
     \ingroup Geometry_Reference */
+
+/** \internal \brief Namespace containing low-level routines from the %Eigen library. */
+namespace internal {}
 }

ADDED   3rd_party/eigen/doc/MatrixfreeSolverExample.dox
Index: 3rd_party/eigen/doc/MatrixfreeSolverExample.dox
==================================================================
--- 3rd_party/eigen/doc/MatrixfreeSolverExample.dox
+++ 3rd_party/eigen/doc/MatrixfreeSolverExample.dox
@@ -0,0 +1,20 @@
+
+namespace Eigen {
+
+/**
+
+\eigenManualPage MatrixfreeSolverExample Matrix-free solvers
+
+Iterative solvers such as ConjugateGradient and BiCGSTAB can be used in a matrix free context. To this end, user must provide a wrapper class inheriting EigenBase<> and implementing the following methods:
+ - \c Index \c rows() and \c Index \c cols(): returns number of rows and columns respectively
+ - \c operator* with your type and an %Eigen dense column vector (its actual implementation goes in a specialization of the internal::generic_product_impl class)
+
+\c Eigen::internal::traits<> must also be specialized for the wrapper type.
+
+Here is a complete example wrapping an Eigen::SparseMatrix:
+\include matrixfree_cg.cpp
+Output: \verbinclude matrixfree_cg.out
+
+*/
+
+}

ADDED   3rd_party/eigen/doc/NewExpressionType.dox
Index: 3rd_party/eigen/doc/NewExpressionType.dox
==================================================================
--- 3rd_party/eigen/doc/NewExpressionType.dox
+++ 3rd_party/eigen/doc/NewExpressionType.dox
@@ -0,0 +1,143 @@
+namespace Eigen {
+
+/** \page TopicNewExpressionType Adding a new expression type
+
+<!--<span style="font-size:130%; color:red; font-weight: 900;"></span>-->
+\warning
+Disclaimer: this page is tailored to very advanced users who are not afraid of dealing with some %Eigen's internal aspects.
+In most cases, a custom expression can be avoided by either using custom \ref MatrixBase::unaryExpr "unary" or \ref MatrixBase::binaryExpr "binary" functors,
+while extremely complex matrix manipulations can be achieved by a nullary functors as described in the \ref TopicCustomizing_NullaryExpr "previous page".
+
+This page describes with the help of an example how to implement a new
+light-weight expression type in %Eigen. This consists of three parts:
+the expression type itself, a traits class containing compile-time
+information about the expression, and the evaluator class which is
+used to evaluate the expression to a matrix.
+
+\b TO \b DO: Write a page explaining the design, with details on
+vectorization etc., and refer to that page here.
+
+
+\eigenAutoToc
+
+\section TopicSetting The setting
+
+A circulant matrix is a matrix where each column is the same as the
+column to the left, except that it is cyclically shifted downwards.
+For example, here is a 4-by-4 circulant matrix:
+\f[ \begin{bmatrix} 
+    1 & 8 & 4 & 2 \\ 
+    2 & 1 & 8 & 4 \\
+    4 & 2 & 1 & 8 \\
+    8 & 4 & 2 & 1
+\end{bmatrix} \f]
+A circulant matrix is uniquely determined by its first column. We wish
+to write a function \c makeCirculant which, given the first column,
+returns an expression representing the circulant matrix.
+
+For simplicity, we restrict the \c makeCirculant function to dense
+matrices. It may make sense to also allow arrays, or sparse matrices,
+but we will not do so here. We also do not want to support
+vectorization.
+
+
+\section TopicPreamble Getting started
+
+We will present the file implementing the \c makeCirculant function
+part by part. We start by including the appropriate header files and
+forward declaring the expression class, which we will call
+\c Circulant. The \c makeCirculant function will return an object of
+this type. The class \c Circulant is in fact a class template; the
+template argument \c ArgType refers to the type of the vector passed
+to the \c makeCirculant function.
+
+\include make_circulant.cpp.preamble
+
+
+\section TopicTraits The traits class
+
+For every expression class \c X, there should be a traits class 
+\c Traits<X> in the \c Eigen::internal namespace containing
+information about \c X known as compile time.
+
+As explained in \ref TopicSetting, we designed the \c Circulant
+expression class to refer to dense matrices. The entries of the
+circulant matrix have the same type as the entries of the vector
+passed to the \c makeCirculant function. The type used to index the
+entries is also the same. Again for simplicity, we will only return
+column-major matrices. Finally, the circulant matrix is a square
+matrix (number of rows equals number of columns), and the number of
+rows equals the number of rows of the column vector passed to the
+\c makeCirculant function. If this is a dynamic-size vector, then the
+size of the circulant matrix is not known at compile-time.
+
+This leads to the following code:
+
+\include make_circulant.cpp.traits
+
+
+\section TopicExpression The expression class
+
+The next step is to define the expression class itself. In our case,
+we want to inherit from \c MatrixBase in order to expose the interface
+for dense matrices. In the constructor, we check that we are passed a
+column vector (see \ref TopicAssertions) and we store the vector from
+which we are going to build the circulant matrix in the member
+variable \c m_arg. Finally, the expression class should compute the
+size of the corresponding circulant matrix. As explained above, this
+is a square matrix with as many columns as the vector used to
+construct the matrix.
+
+\b TO \b DO: What about the \c Nested typedef? It seems to be
+necessary; is this only temporary?
+
+\include make_circulant.cpp.expression
+
+
+\section TopicEvaluator The evaluator
+
+The last big fragment implements the evaluator for the \c Circulant
+expression. The evaluator computes the entries of the circulant
+matrix; this is done in the \c .coeff() member function. The entries
+are computed by finding the corresponding entry of the vector from
+which the circulant matrix is constructed. Getting this entry may
+actually be non-trivial when the circulant matrix is constructed from
+a vector which is given by a complicated expression, so we use the
+evaluator which corresponds to the vector.
+
+The \c CoeffReadCost constant records the cost of computing an entry
+of the circulant matrix; we ignore the index computation and say that
+this is the same as the cost of computing an entry of the vector from
+which the circulant matrix is constructed.
+
+In the constructor, we save the evaluator for the column vector which
+defined the circulant matrix. We also save the size of that vector;
+remember that we can query an expression object to find the size but
+not the evaluator. 
+
+\include make_circulant.cpp.evaluator
+
+
+\section TopicEntry The entry point
+
+After all this, the \c makeCirculant function is very simple. It
+simply creates an expression object and returns it.
+
+\include make_circulant.cpp.entry
+
+
+\section TopicMain A simple main function for testing
+
+Finally, a short \c main function that shows how the \c makeCirculant
+function can be called.
+
+\include make_circulant.cpp.main
+
+If all the fragments are combined, the following output is produced,
+showing that the program works as expected:
+
+\include make_circulant.out
+
+*/
+}
+

Index: 3rd_party/eigen/doc/Overview.dox
==================================================================
--- 3rd_party/eigen/doc/Overview.dox
+++ 3rd_party/eigen/doc/Overview.dox
@@ -15,14 +15,16 @@
 You're a MatLab user? There is also a <a href="AsciiQuickReference.txt">short ASCII reference</a> with Matlab translations.
   
 The \b main \b documentation is organized into \em chapters covering different domains of features.
 They are themselves composed of \em user \em manual pages describing the different features in a comprehensive way, and \em reference pages that gives you access to the API documentation through the related Eigen's \em modules and \em classes.
 
-Under the  \subpage UserManual_Generalities section, you will find documentation on more general topics such as preprocessor directives, controlling assertions, multi-threading, MKL support, some Eigen's internal insights, and much more...
+Under the \subpage UserManual_CustomizingEigen section, you will find discussions and examples on extending %Eigen's features and supporting custom scalar types.
+
+Under the \subpage UserManual_Generalities section, you will find documentation on more general topics such as preprocessor directives, controlling assertions, multi-threading, MKL support, some Eigen's internal insights, and much more...
 
 Finally, do not miss the search engine, useful to quickly get to the documentation of a given class or function.
 
 Want more? Checkout the <a href="unsupported/index.html">\em unsupported \em modules </a> documentation.
 
 */
 
 }

ADDED   3rd_party/eigen/doc/Pitfalls.dox
Index: 3rd_party/eigen/doc/Pitfalls.dox
==================================================================
--- 3rd_party/eigen/doc/Pitfalls.dox
+++ 3rd_party/eigen/doc/Pitfalls.dox
@@ -0,0 +1,38 @@
+namespace Eigen {
+
+/** \page TopicPitfalls Common pitfalls
+
+\section TopicPitfalls_template_keyword Compilation error with template methods
+
+See this \link TopicTemplateKeyword page \endlink.
+
+\section TopicPitfalls_auto_keyword C++11 and the auto keyword
+
+In short: do not use the auto keywords with Eigen's expressions, unless you are 100% sure about what you are doing. In particular, do not use the auto keyword as a replacement for a Matrix<> type. Here is an example:
+
+\code
+MatrixXd A, B;
+auto C = A*B;
+for(...) { ... w = C * v;  ...}
+\endcode
+
+In this example, the type of C is not a MatrixXd but an abstract expression representing a matrix product and storing references to A and B. Therefore, the product of A*B will be carried out multiple times, once per iteration of the for loop. Moreover, if the coefficients of A or B change during the iteration, then C will evaluate to different values.
+
+Here is another example leading to a segfault:
+\code
+auto C = ((A+B).eval()).transpose();
+// do something with C
+\endcode
+The problem is that eval() returns a temporary object (in this case a MatrixXd) which is then referenced by the Transpose<> expression. However, this temporary is deleted right after the first line, and there the C expression reference a dead object. The same issue might occur when sub expressions are automatically evaluated by Eigen as in the following example:
+\code
+VectorXd u, v;
+auto C = u + (A*v).normalized();
+// do something with C
+\endcode
+where the normalized() method has to evaluate the expensive product A*v to avoid evaluating it twice. On the other hand, the following example is perfectly fine:
+\code
+auto C = (u + (A*v).normalized()).eval();
+\endcode
+In this case, C will be a regular VectorXd object.
+*/
+}

Index: 3rd_party/eigen/doc/PreprocessorDirectives.dox
==================================================================
--- 3rd_party/eigen/doc/PreprocessorDirectives.dox
+++ 3rd_party/eigen/doc/PreprocessorDirectives.dox
@@ -3,11 +3,11 @@
 /** \page TopicPreprocessorDirectives Preprocessor directives
 
 You can control some aspects of %Eigen by defining the preprocessor tokens using \c \#define. These macros
 should be defined before any %Eigen headers are included. Often they are best set in the project options.
 
-This page lists the preprocesor tokens recognised by %Eigen.
+This page lists the preprocessor tokens recognized by %Eigen.
 
 \eigenAutoToc
 
 
 \section TopicPreprocessorDirectivesMajor Macros with major effects
@@ -16,28 +16,70 @@
 ABI (Application Binary Interface). This can be rather dangerous: if parts of your program are compiled with
 one option, and other parts (or libraries that you use) are compiled with another option, your program may
 fail to link or exhibit subtle bugs. Nevertheless, these options can be useful for people who know what they
 are doing.
 
- - \b EIGEN2_SUPPORT - if defined, enables the Eigen2 compatibility mode. This is meant to ease the transition
-   of Eigen2 to Eigen3 (see \ref Eigen2ToEigen3). Not defined by default.
- - \b EIGEN2_SUPPORT_STAGEnn_xxx (for various values of nn and xxx) - staged migration path from Eigen2 to
-   Eigen3; see \ref Eigen2SupportModes.
+ - \b EIGEN2_SUPPORT and \b EIGEN2_SUPPORT_STAGEnn_xxx are disabled starting from the 3.3 release.
+   Defining one of these will raise a compile-error. If you need to compile Eigen2 code,
+   <a href="http://eigen.tuxfamily.org/index.php?title=Eigen2">check this site</a>.
  - \b EIGEN_DEFAULT_DENSE_INDEX_TYPE - the type for column and row indices in matrices, vectors and array
    (DenseBase::Index). Set to \c std::ptrdiff_t by default.
  - \b EIGEN_DEFAULT_IO_FORMAT - the IOFormat to use when printing a matrix if no %IOFormat is specified.
    Defaults to the %IOFormat constructed by the default constructor IOFormat::IOFormat().
  - \b EIGEN_INITIALIZE_MATRICES_BY_ZERO - if defined, all entries of newly constructed matrices and arrays are
    initialized to zero, as are new entries in matrices and arrays after resizing. Not defined by default.
+   \warning The unary (resp. binary) constructor of \c 1x1 (resp. \c 2x1 or \c 1x2) fixed size matrices is
+   always interpreted as an initialization constructor where the argument(s) are the coefficient values
+   and not the sizes. For instance, \code Vector2d v(2,1); \endcode will create a vector with coeficients [2,1],
+   and \b not a \c 2x1 vector initialized with zeros (i.e., [0,0]). If such cases might occur, then it is
+   recommended to use the default constructor with a explicit call to resize:
+   \code
+   Matrix<?,SizeAtCompileTime,1> v;
+   v.resize(size);
+   Matrix<?,RowsAtCompileTime,ColsAtCompileTime> m;
+   m.resize(rows,cols);
+   \endcode
  - \b EIGEN_INITIALIZE_MATRICES_BY_NAN - if defined, all entries of newly constructed matrices and arrays are
    initialized to NaN, as are new entries in matrices and arrays after resizing. This option is especially
    useful for debugging purpose, though a memory tool like <a href="http://valgrind.org/">valgrind</a> is
    preferable. Not defined by default.
+   \warning See the documentation of \c EIGEN_INITIALIZE_MATRICES_BY_ZERO for a discussion on a limitations
+   of these macros when applied to \c 1x1, \c 1x2, and \c 2x1 fixed-size matrices.
  - \b EIGEN_NO_AUTOMATIC_RESIZING - if defined, the matrices (or arrays) on both sides of an assignment 
    <tt>a = b</tt> have to be of the same size; otherwise, %Eigen automatically resizes \c a so that it is of
    the correct size. Not defined by default.
 
+
+\section TopicPreprocessorDirectivesCppVersion C++ standard features
+
+By default, %Eigen strive to automatically detect and enable langage features at compile-time based on
+the information provided by the compiler.
+
+ - \b EIGEN_MAX_CPP_VER - disables usage of C++ features requiring a version greater than EIGEN_MAX_CPP_VER.
+   Possible values are: 03, 11, 14, 17, etc. If not defined (the default), %Eigen enables all features supported
+   by the compiler.
+
+Individual features can be explicitly enabled or disabled by defining the following token to 0 or 1 respectively.
+For instance, one might limit the C++ version to C++03 by defining EIGEN_MAX_CPP_VER=03, but still enable C99 math
+functions by defining EIGEN_HAS_C99_MATH=1.
+
+ - \b EIGEN_HAS_C99_MATH - controls the usage of C99 math functions such as erf, erfc, lgamma, etc.
+   Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
+ - \b EIGEN_HAS_CXX11_MATH - controls the implementation of some functions such as round, logp1, isinf, isnan, etc.
+   Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
+ - \b EIGEN_HAS_RVALUE_REFERENCES - defines whetehr rvalue references are supported
+   Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
+ - \b EIGEN_HAS_STD_RESULT_OF - defines whether std::result_of is supported
+   Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
+ - \b EIGEN_HAS_VARIADIC_TEMPLATES - defines whether variadic templates are supported
+   Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
+ - \b EIGEN_HAS_CONSTEXPR - defines whether relaxed const expression are supported
+   Automatic detection disabled if EIGEN_MAX_CPP_VER<14.
+ - \b EIGEN_HAS_CXX11_CONTAINERS - defines whether STL's containers follows C++11 specifications
+   Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
+ - \b EIGEN_HAS_CXX11_NOEXCEPT - defines whether noexcept is supported
+   Automatic detection disabled if EIGEN_MAX_CPP_VER<11.
 
 \section TopicPreprocessorDirectivesAssertions Assertions
 
 The %Eigen library contains many assertions to guard against programming errors, both at compile time and at
 run time. However, these assertions do cost time and can thus be turned off.
@@ -53,36 +95,43 @@
    are still under the LGPL.
 
 
 \section TopicPreprocessorDirectivesPerformance Alignment, vectorization and performance tweaking
 
- - \b EIGEN_MALLOC_ALREADY_ALIGNED - Can be set to 0 or 1 to tell whether default system malloc already
+ - \b \c EIGEN_MALLOC_ALREADY_ALIGNED - Can be set to 0 or 1 to tell whether default system \c malloc already
    returns aligned buffers. In not defined, then this information is automatically deduced from the compiler
    and system preprocessor tokens.
- - \b EIGEN_DONT_ALIGN - disables alignment completely. %Eigen will not try to align its objects and does not
-   expect that any objects passed to it are aligned. This will turn off vectorization. Not defined by default.
- - \b EIGEN_DONT_ALIGN_STATICALLY - disables alignment of arrays on the stack. Not defined by default, unless
-   \c EIGEN_DONT_ALIGN is defined.
- - \b EIGEN_DONT_PARALLELIZE - if defined, this disables multi-threading. This is only relevant if you enabled OpenMP.
+ - \b \c EIGEN_MAX_ALIGN_BYTES - Must be a power of two, or 0. Defines an upper bound on the memory boundary in bytes on which dynamically and statically allocated data may be aligned by %Eigen. If not defined, a default value is automatically computed based on architecture, compiler, and OS.
+ This option is typically used to enforce binary compatibility between code/libraries compiled with different SIMD options. For instance, one may compile AVX code and enforce ABI compatibility with existing SSE code by defining \c EIGEN_MAX_ALIGN_BYTES=16. In the other way round, since by default AVX implies 32 bytes alignment for best performance, one can compile SSE code to be ABI compatible with AVX code by defining \c EIGEN_MAX_ALIGN_BYTES=32.
+ - \b \c EIGEN_MAX_STATIC_ALIGN_BYTES - Same as \c EIGEN_MAX_ALIGN_BYTES but for statically allocated data only. By default, if only  \c EIGEN_MAX_ALIGN_BYTES is defined, then \c EIGEN_MAX_STATIC_ALIGN_BYTES == \c EIGEN_MAX_ALIGN_BYTES, otherwise a default value is automatically computed based on architecture, compiler, and OS (can be smaller than the default value of EIGEN_MAX_ALIGN_BYTES on architectures that do not support stack alignment).
+ Let us emphasize that \c EIGEN_MAX_*_ALIGN_BYTES define only a diserable upper bound. In practice data is aligned to largest power-of-two common divisor of \c EIGEN_MAX_STATIC_ALIGN_BYTES and the size of the data, such that memory is not wasted.
+ - \b \c EIGEN_DONT_PARALLELIZE - if defined, this disables multi-threading. This is only relevant if you enabled OpenMP.
    See \ref TopicMultiThreading for details.
  - \b EIGEN_DONT_VECTORIZE - disables explicit vectorization when defined. Not defined by default, unless 
    alignment is disabled by %Eigen's platform test or the user defining \c EIGEN_DONT_ALIGN.
- - \b EIGEN_FAST_MATH - enables some optimizations which might affect the accuracy of the result. This currently
+ - \b \c EIGEN_UNALIGNED_VECTORIZE - disables/enables vectorization with unaligned stores. Default is 1 (enabled).
+   If set to 0 (disabled), then expression for which the destination cannot be aligned are not vectorized (e.g., unaligned
+   small fixed size vectors or matrices)
+ - \b \c EIGEN_FAST_MATH - enables some optimizations which might affect the accuracy of the result. This currently
    enables the SSE vectorization of sin() and cos(), and speedups sqrt() for single precision. Defined to 1 by default.
    Define it to 0 to disable.
- - \b EIGEN_UNROLLING_LIMIT - defines the size of a loop to enable meta unrolling. Set it to zero to disable
+ - \b \c EIGEN_UNROLLING_LIMIT - defines the size of a loop to enable meta unrolling. Set it to zero to disable
    unrolling. The size of a loop here is expressed in %Eigen's own notion of "number of FLOPS", it does not
    correspond to the number of iterations or the number of instructions. The default is value 100.
- - \b EIGEN_STACK_ALLOCATION_LIMIT - defines the maximum bytes for a buffer to be allocated on the stack. For internal
+ - \b \c EIGEN_STACK_ALLOCATION_LIMIT - defines the maximum bytes for a buffer to be allocated on the stack. For internal
    temporary buffers, dynamic memory allocation is employed as a fall back. For fixed-size matrices or arrays, exceeding
    this threshold raises a compile time assertion. Use 0 to set no limit. Default is 128 KB.
 
+
+ - \c EIGEN_DONT_ALIGN - Deprecated, it is a synonym for \c EIGEN_MAX_ALIGN_BYTES=0. It disables alignment completely. %Eigen will not try to align its objects and does not expect that any objects passed to it are aligned. This will turn off vectorization if \b EIGEN_UNALIGNED_VECTORIZE=1. Not defined by default.
+ - \c EIGEN_DONT_ALIGN_STATICALLY - Deprecated, it is a synonym for \c EIGEN_MAX_STATIC_ALIGN_BYTES=0. It disables alignment of arrays on the stack. Not defined by default, unless \c EIGEN_DONT_ALIGN is defined.
+
 
 \section TopicPreprocessorDirectivesPlugins Plugins
 
 It is possible to add new methods to many fundamental classes in %Eigen by writing a plugin. As explained in
-the section \ref ExtendingMatrixBase, the plugin is specified by defining a \c EIGEN_xxx_PLUGIN macro. The
+the section \ref TopicCustomizing_Plugins, the plugin is specified by defining a \c EIGEN_xxx_PLUGIN macro. The
 following macros are supported; none of them are defined by default.
 
  - \b EIGEN_ARRAY_PLUGIN - filename of plugin for extending the Array class.
  - \b EIGEN_ARRAYBASE_PLUGIN - filename of plugin for extending the ArrayBase class.
  - \b EIGEN_CWISE_PLUGIN - filename of plugin for extending the Cwise class.
@@ -89,10 +138,12 @@
  - \b EIGEN_DENSEBASE_PLUGIN - filename of plugin for extending the DenseBase class.
  - \b EIGEN_DYNAMICSPARSEMATRIX_PLUGIN - filename of plugin for extending the DynamicSparseMatrix class.
  - \b EIGEN_MATRIX_PLUGIN - filename of plugin for extending the Matrix class.
  - \b EIGEN_MATRIXBASE_PLUGIN - filename of plugin for extending the MatrixBase class.
  - \b EIGEN_PLAINOBJECTBASE_PLUGIN - filename of plugin for extending the PlainObjectBase class.
+ - \b EIGEN_MAPBASE_PLUGIN - filename of plugin for extending the MapBase class.
+ - \b EIGEN_QUATERNION_PLUGIN - filename of plugin for extending the Quaternion class.
  - \b EIGEN_QUATERNIONBASE_PLUGIN - filename of plugin for extending the QuaternionBase class.
  - \b EIGEN_SPARSEMATRIX_PLUGIN - filename of plugin for extending the SparseMatrix class.
  - \b EIGEN_SPARSEMATRIXBASE_PLUGIN - filename of plugin for extending the SparseMatrixBase class.
  - \b EIGEN_SPARSEVECTOR_PLUGIN - filename of plugin for extending the SparseVector class.
  - \b EIGEN_TRANSFORM_PLUGIN - filename of plugin for extending the Transform class.

Index: 3rd_party/eigen/doc/QuickReference.dox
==================================================================
--- 3rd_party/eigen/doc/QuickReference.dox
+++ 3rd_party/eigen/doc/QuickReference.dox
@@ -11,21 +11,21 @@
 
 The Eigen library is divided in a Core module and several additional modules. Each module has a corresponding header file which has to be included in order to use the module. The \c %Dense and \c Eigen header files are provided to conveniently gain access to several modules at once.
 
 <table class="manual">
 <tr><th>Module</th><th>Header file</th><th>Contents</th></tr>
-<tr><td>\link Core_Module Core \endlink</td><td>\code#include <Eigen/Core>\endcode</td><td>Matrix and Array classes, basic linear algebra (including triangular and selfadjoint products), array manipulation</td></tr>
+<tr            ><td>\link Core_Module Core \endlink</td><td>\code#include <Eigen/Core>\endcode</td><td>Matrix and Array classes, basic linear algebra (including triangular and selfadjoint products), array manipulation</td></tr>
 <tr class="alt"><td>\link Geometry_Module Geometry \endlink</td><td>\code#include <Eigen/Geometry>\endcode</td><td>Transform, Translation, Scaling, Rotation2D and 3D rotations (Quaternion, AngleAxis)</td></tr>
-<tr><td>\link LU_Module LU \endlink</td><td>\code#include <Eigen/LU>\endcode</td><td>Inverse, determinant, LU decompositions with solver (FullPivLU, PartialPivLU)</td></tr>
-<tr><td>\link Cholesky_Module Cholesky \endlink</td><td>\code#include <Eigen/Cholesky>\endcode</td><td>LLT and LDLT Cholesky factorization with solver</td></tr>
-<tr class="alt"><td>\link Householder_Module Householder \endlink</td><td>\code#include <Eigen/Householder>\endcode</td><td>Householder transformations; this module is used by several linear algebra modules</td></tr>
-<tr><td>\link SVD_Module SVD \endlink</td><td>\code#include <Eigen/SVD>\endcode</td><td>SVD decomposition with least-squares solver (JacobiSVD)</td></tr>
-<tr class="alt"><td>\link QR_Module QR \endlink</td><td>\code#include <Eigen/QR>\endcode</td><td>QR decomposition with solver (HouseholderQR, ColPivHouseholderQR, FullPivHouseholderQR)</td></tr>
-<tr><td>\link Eigenvalues_Module Eigenvalues \endlink</td><td>\code#include <Eigen/Eigenvalues>\endcode</td><td>Eigenvalue, eigenvector decompositions (EigenSolver, SelfAdjointEigenSolver, ComplexEigenSolver)</td></tr>
-<tr class="alt"><td>\link Sparse_modules Sparse \endlink</td><td>\code#include <Eigen/Sparse>\endcode</td><td>%Sparse matrix storage and related basic linear algebra (SparseMatrix, DynamicSparseMatrix, SparseVector)</td></tr>
-<tr><td></td><td>\code#include <Eigen/Dense>\endcode</td><td>Includes Core, Geometry, LU, Cholesky, SVD, QR, and Eigenvalues header files</td></tr>
-<tr class="alt"><td></td><td>\code#include <Eigen/Eigen>\endcode</td><td>Includes %Dense and %Sparse header files (the whole Eigen library)</td></tr>
+<tr            ><td>\link LU_Module LU \endlink</td><td>\code#include <Eigen/LU>\endcode</td><td>Inverse, determinant, LU decompositions with solver (FullPivLU, PartialPivLU)</td></tr>
+<tr class="alt"><td>\link Cholesky_Module Cholesky \endlink</td><td>\code#include <Eigen/Cholesky>\endcode</td><td>LLT and LDLT Cholesky factorization with solver</td></tr>
+<tr            ><td>\link Householder_Module Householder \endlink</td><td>\code#include <Eigen/Householder>\endcode</td><td>Householder transformations; this module is used by several linear algebra modules</td></tr>
+<tr class="alt"><td>\link SVD_Module SVD \endlink</td><td>\code#include <Eigen/SVD>\endcode</td><td>SVD decompositions with least-squares solver (JacobiSVD, BDCSVD)</td></tr>
+<tr            ><td>\link QR_Module QR \endlink</td><td>\code#include <Eigen/QR>\endcode</td><td>QR decomposition with solver (HouseholderQR, ColPivHouseholderQR, FullPivHouseholderQR)</td></tr>
+<tr class="alt"><td>\link Eigenvalues_Module Eigenvalues \endlink</td><td>\code#include <Eigen/Eigenvalues>\endcode</td><td>Eigenvalue, eigenvector decompositions (EigenSolver, SelfAdjointEigenSolver, ComplexEigenSolver)</td></tr>
+<tr            ><td>\link Sparse_Module Sparse \endlink</td><td>\code#include <Eigen/Sparse>\endcode</td><td>%Sparse matrix storage and related basic linear algebra (SparseMatrix, SparseVector) \n (see \ref SparseQuickRefPage for details on sparse modules)</td></tr>
+<tr class="alt"><td></td><td>\code#include <Eigen/Dense>\endcode</td><td>Includes Core, Geometry, LU, Cholesky, SVD, QR, and Eigenvalues header files</td></tr>
+<tr            ><td></td><td>\code#include <Eigen/Eigen>\endcode</td><td>Includes %Dense and %Sparse header files (the whole Eigen library)</td></tr>
 </table>
 
 <a href="#" class="top">top</a>
 \section QuickRef_Types Array, matrix and vector types
 
@@ -338,11 +338,11 @@
 mat1 = mat2.transpose();      mat1.transposeInPlace();
 mat1 = mat2.adjoint();        mat1.adjointInPlace();
 \endcode
 </td></tr>
 <tr><td>
-\link MatrixBase::dot() dot \endlink product \n inner product \matrixworld</td><td>\code
+\link MatrixBase::dot dot \endlink product \n inner product \matrixworld</td><td>\code
 scalar = vec1.dot(vec2);
 scalar = col1.adjoint() * col2;
 scalar = (col1.adjoint() * col2).value();\endcode
 </td></tr>
 <tr class="alt"><td>
@@ -362,36 +362,14 @@
 vec3 = vec1.cross(vec2);\endcode</td></tr>
 </table>
 
 <a href="#" class="top">top</a>
 \section QuickRef_Coeffwise Coefficient-wise \& Array operators
-Coefficient-wise operators for matrices and vectors:
-<table class="manual">
-<tr><th>Matrix API \matrixworld</th><th>Via Array conversions</th></tr>
-<tr><td>\code
-mat1.cwiseMin(mat2)
-mat1.cwiseMax(mat2)
-mat1.cwiseAbs2()
-mat1.cwiseAbs()
-mat1.cwiseSqrt()
-mat1.cwiseProduct(mat2)
-mat1.cwiseQuotient(mat2)\endcode
-</td><td>\code
-mat1.array().min(mat2.array())
-mat1.array().max(mat2.array())
-mat1.array().abs2()
-mat1.array().abs()
-mat1.array().sqrt()
-mat1.array() * mat2.array()
-mat1.array() / mat2.array()
-\endcode</td></tr>
-</table>
-
-It is also very simple to apply any user defined function \c foo using DenseBase::unaryExpr together with std::ptr_fun:
-\code mat1.unaryExpr(std::ptr_fun(foo))\endcode
-
-Array operators:\arrayworld
+
+In addition to the aforementioned operators, Eigen supports numerous coefficient-wise operator and functions.
+Most of them unambiguously makes sense in array-world\arrayworld. The following operators are readily available for arrays,
+or available through .array() for vectors and matrices:
 
 <table class="manual">
 <tr><td>Arithmetic operators</td><td>\code
 array1 * array2     array1 / array2     array1 *= array2    array1 /= array2
 array1 + scalar     array1 - scalar     array1 += scalar    array1 -= scalar
@@ -398,31 +376,111 @@
 \endcode</td></tr>
 <tr><td>Comparisons</td><td>\code
 array1 < array2     array1 > array2     array1 < scalar     array1 > scalar
 array1 <= array2    array1 >= array2    array1 <= scalar    array1 >= scalar
 array1 == array2    array1 != array2    array1 == scalar    array1 != scalar
+array1.min(array2)  array1.max(array2)  array1.min(scalar)  array1.max(scalar)
 \endcode</td></tr>
-<tr><td>Trigo, power, and \n misc functions \n and the STL variants</td><td>\code
-array1.min(array2)            
-array1.max(array2)            
+<tr><td>Trigo, power, and \n misc functions \n and the STL-like variants</td><td>\code
 array1.abs2()
 array1.abs()                  abs(array1)
 array1.sqrt()                 sqrt(array1)
 array1.log()                  log(array1)
+array1.log10()                log10(array1)
 array1.exp()                  exp(array1)
-array1.pow(exponent)          pow(array1,exponent)
+array1.pow(array2)            pow(array1,array2)
+array1.pow(scalar)            pow(array1,scalar)
+                              pow(scalar,array2)
 array1.square()
 array1.cube()
 array1.inverse()
+
 array1.sin()                  sin(array1)
 array1.cos()                  cos(array1)
 array1.tan()                  tan(array1)
 array1.asin()                 asin(array1)
 array1.acos()                 acos(array1)
+array1.atan()                 atan(array1)
+array1.sinh()                 sinh(array1)
+array1.cosh()                 cosh(array1)
+array1.tanh()                 tanh(array1)
+array1.arg()                  arg(array1)
+
+array1.floor()                floor(array1)
+array1.ceil()                 ceil(array1)
+array1.round()                round(aray1)
+
+array1.isFinite()             isfinite(array1)
+array1.isInf()                isinf(array1)
+array1.isNaN()                isnan(array1)
+\endcode
+</td></tr>
+</table>
+
+
+The following coefficient-wise operators are available for all kind of expressions (matrices, vectors, and arrays), and for both real or complex scalar types:
+
+<table class="manual">
+<tr><th>Eigen's API</th><th>STL-like APIs\arrayworld </th><th>Comments</th></tr>
+<tr><td>\code
+mat1.real()
+mat1.imag()
+mat1.conjugate()
+\endcode
+</td><td>\code
+real(array1)
+imag(array1)
+conj(array1)
+\endcode
+</td><td>
+\code
+ // read-write, no-op for real expressions
+ // read-only for real, read-write for complexes
+ // no-op for real expressions
 \endcode
 </td></tr>
 </table>
+
+Some coefficient-wise operators are readily available for for matrices and vectors through the following cwise* methods:
+<table class="manual">
+<tr><th>Matrix API \matrixworld</th><th>Via Array conversions</th></tr>
+<tr><td>\code
+mat1.cwiseMin(mat2)         mat1.cwiseMin(scalar)
+mat1.cwiseMax(mat2)         mat1.cwiseMax(scalar)
+mat1.cwiseAbs2()
+mat1.cwiseAbs()
+mat1.cwiseSqrt()
+mat1.cwiseInverse()
+mat1.cwiseProduct(mat2)
+mat1.cwiseQuotient(mat2)
+mat1.cwiseEqual(mat2)       mat1.cwiseEqual(scalar)
+mat1.cwiseNotEqual(mat2)
+\endcode
+</td><td>\code
+mat1.array().min(mat2.array())    mat1.array().min(scalar)
+mat1.array().max(mat2.array())    mat1.array().max(scalar)
+mat1.array().abs2()
+mat1.array().abs()
+mat1.array().sqrt()
+mat1.array().inverse()
+mat1.array() * mat2.array()
+mat1.array() / mat2.array()
+mat1.array() == mat2.array()      mat1.array() == scalar
+mat1.array() != mat2.array()
+\endcode</td></tr>
+</table>
+The main difference between the two API is that the one based on cwise* methods returns an expression in the matrix world,
+while the second one (based on .array()) returns an array expression.
+Recall that .array() has no cost, it only changes the available API and interpretation of the data.
+
+It is also very simple to apply any user defined function \c foo using DenseBase::unaryExpr together with <a href="http://en.cppreference.com/w/cpp/utility/functional/ptr_fun">std::ptr_fun</a> (c++03), <a href="http://en.cppreference.com/w/cpp/utility/functional/ref">std::ref</a> (c++11), or <a href="http://en.cppreference.com/w/cpp/language/lambda">lambdas</a> (c++11):
+\code
+mat1.unaryExpr(std::ptr_fun(foo));
+mat1.unaryExpr(std::ref(foo));
+mat1.unaryExpr([](double x) { return foo(x); });
+\endcode
+
 
 <a href="#" class="top">top</a>
 \section QuickRef_Reductions Reductions
 
 Eigen provides several reduction methods such as:

Index: 3rd_party/eigen/doc/SparseLinearSystems.dox
==================================================================
--- 3rd_party/eigen/doc/SparseLinearSystems.dox
+++ 3rd_party/eigen/doc/SparseLinearSystems.dox
@@ -2,55 +2,90 @@
 /** \eigenManualPage TopicSparseSystems Solving Sparse Linear Systems
 In Eigen, there are several methods available to solve linear systems when the coefficient matrix is sparse. Because of the special representation of this class of matrices, special care should be taken in order to get a good performance. See \ref TutorialSparse for a detailed introduction about sparse matrices in Eigen. This page lists the sparse solvers available in Eigen. The main steps that are common to all these linear solvers are introduced as well. Depending on the properties of the matrix, the desired accuracy, the end-user is able to tune those steps in order to improve the performance of its code. Note that it is not required to know deeply what's hiding behind these steps: the last section presents a benchmark routine that can be easily used to get an insight on the performance of all the available solvers. 
 
 \eigenAutoToc
 
-\section TutorialSparseDirectSolvers Sparse solvers
+\section TutorialSparseSolverList List of sparse solvers
+
+%Eigen currently provides a wide set of built-in solvers, as well as wrappers to external solver libraries.
+They are summarized in the following tables:
+
+\subsection TutorialSparseSolverList_Direct Built-in direct solvers
+
+<table class="manual">
+<tr><th>Class</th><th>Solver kind</th><th>Matrix kind</th><th>Features related to performance</th>
+    <th>License</th><th class="width20em"><p>Notes</p></th></tr>
+
+<tr><td>SimplicialLLT \n <tt>\#include<Eigen/\link SparseCholesky_Module SparseCholesky\endlink></tt></td><td>Direct LLt factorization</td><td>SPD</td><td>Fill-in reducing</td>
+    <td>LGPL</td>
+    <td>SimplicialLDLT is often preferable</td></tr>
+
+<tr><td>SimplicialLDLT \n <tt>\#include<Eigen/\link SparseCholesky_Module SparseCholesky\endlink></tt></td><td>Direct LDLt factorization</td><td>SPD</td><td>Fill-in reducing</td>
+    <td>LGPL</td>
+    <td>Recommended for very sparse and not too large problems (e.g., 2D Poisson eq.)</td></tr>
+
+<tr><td>SparseLU \n <tt>\#include<Eigen/\link SparseLU_Module SparseLU\endlink></tt></td> <td>LU factorization </td>
+    <td>Square </td><td>Fill-in reducing, Leverage fast dense algebra</td>
+    <td>MPL2</td>
+    <td>optimized for small and large problems with irregular patterns </td></tr>
+
+<tr><td>SparseQR \n <tt>\#include<Eigen/\link SparseQR_Module SparseQR\endlink></tt></td> <td> QR factorization</td>
+    <td>Any, rectangular</td><td> Fill-in reducing</td>
+    <td>MPL2</td>
+    <td>recommended for least-square problems, has a basic rank-revealing feature</td></tr>
+ </table>
+
+\subsection TutorialSparseSolverList_Iterative Built-in iterative solvers
+
+<table class="manual">
+<tr><th>Class</th><th>Solver kind</th><th>Matrix kind</th><th>Supported preconditioners, [default]</th>
+    <th>License</th><th class="width20em"><p>Notes</p></th></tr>
+
+<tr><td>ConjugateGradient \n <tt>\#include<Eigen/\link IterativeLinearSolvers_Module IterativeLinearSolvers\endlink></tt></td> <td>Classic iterative CG</td><td>SPD</td>
+    <td>IdentityPreconditioner, [DiagonalPreconditioner], IncompleteCholesky</td>
+    <td>MPL2</td>
+    <td>Recommended for large symmetric problems (e.g., 3D Poisson eq.)</td></tr>
+
+<tr><td>LeastSquaresConjugateGradient \n <tt>\#include<Eigen/\link IterativeLinearSolvers_Module IterativeLinearSolvers\endlink></tt></td><td>CG for rectangular least-square problem</td><td>Rectangular</td>
+    <td>IdentityPreconditioner, [LeastSquareDiagonalPreconditioner]</td>
+    <td>MPL2</td>
+    <td>Solve for min |A'Ax-b|^2 without forming A'A</td></tr>
+
+<tr><td>BiCGSTAB \n <tt>\#include<Eigen/\link IterativeLinearSolvers_Module IterativeLinearSolvers\endlink></tt></td><td>Iterative stabilized bi-conjugate gradient</td><td>Square</td>
+    <td>IdentityPreconditioner, [DiagonalPreconditioner], IncompleteLUT</td>
+    <td>MPL2</td>
+    <td>To speedup the convergence, try it with the \ref IncompleteLUT preconditioner.</td></tr>
+</table>
 
-%Eigen currently provides a limited set of built-in solvers, as well as wrappers to external solver libraries.
-They are summarized in the following table:
+\subsection TutorialSparseSolverList_Wrapper Wrappers to external solvers
 
 <table class="manual">
 <tr><th>Class</th><th>Module</th><th>Solver kind</th><th>Matrix kind</th><th>Features related to performance</th>
     <th>Dependencies,License</th><th class="width20em"><p>Notes</p></th></tr>
-<tr><td>SimplicialLLT    </td><td>\link SparseCholesky_Module SparseCholesky \endlink</td><td>Direct LLt factorization</td><td>SPD</td><td>Fill-in reducing</td>
-    <td>built-in, LGPL</td>
-    <td>SimplicialLDLT is often preferable</td></tr>
-<tr><td>SimplicialLDLT   </td><td>\link SparseCholesky_Module SparseCholesky \endlink</td><td>Direct LDLt factorization</td><td>SPD</td><td>Fill-in reducing</td>
-    <td>built-in, LGPL</td>
-    <td>Recommended for very sparse and not too large problems (e.g., 2D Poisson eq.)</td></tr>
-<tr><td>ConjugateGradient</td><td>\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink</td><td>Classic iterative CG</td><td>SPD</td><td>Preconditionning</td>
-    <td>built-in, MPL2</td>
-    <td>Recommended for large symmetric problems (e.g., 3D Poisson eq.)</td></tr>
-<tr><td>BiCGSTAB</td><td>\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink</td><td>Iterative stabilized bi-conjugate gradient</td><td>Square</td><td>Preconditionning</td>
-    <td>built-in, MPL2</td>
-    <td>To speedup the convergence, try it with the \ref IncompleteLUT preconditioner.</td></tr>
-<tr><td>SparseLU</td> <td>\link SparseLU_Module SparseLU \endlink </td> <td>LU factorization </td>
-    <td>Square </td><td>Fill-in reducing, Leverage fast dense algebra</td>
-    <td> built-in, MPL2</td> <td>optimized for small and large problems with irregular patterns </td></tr>
-<tr><td>SparseQR</td> <td>\link SparseQR_Module SparseQR \endlink</td> <td> QR factorization</td>
-    <td>Any, rectangular</td><td> Fill-in reducing</td>
-    <td>built-in, MPL2</td><td>recommended for least-square problems, has a basic rank-revealing feature</td></tr>
-<tr> <th colspan="7"> Wrappers to external solvers </th></tr>
 <tr><td>PastixLLT \n PastixLDLT \n PastixLU</td><td>\link PaStiXSupport_Module PaStiXSupport \endlink</td><td>Direct LLt, LDLt, LU factorizations</td><td>SPD \n SPD \n Square</td><td>Fill-in reducing, Leverage fast dense algebra, Multithreading</td>
     <td>Requires the <a href="http://pastix.gforge.inria.fr">PaStiX</a> package, \b CeCILL-C </td>
     <td>optimized for tough problems and symmetric patterns</td></tr>
 <tr><td>CholmodSupernodalLLT</td><td>\link CholmodSupport_Module CholmodSupport \endlink</td><td>Direct LLt factorization</td><td>SPD</td><td>Fill-in reducing, Leverage fast dense algebra</td>
-    <td>Requires the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">SuiteSparse</a> package, \b GPL </td>
+    <td>Requires the <a href="http://www.suitesparse.com">SuiteSparse</a> package, \b GPL </td>
     <td></td></tr>
 <tr><td>UmfPackLU</td><td>\link UmfPackSupport_Module UmfPackSupport \endlink</td><td>Direct LU factorization</td><td>Square</td><td>Fill-in reducing, Leverage fast dense algebra</td>
-    <td>Requires the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">SuiteSparse</a> package, \b GPL </td>
+    <td>Requires the <a href="http://www.suitesparse.com">SuiteSparse</a> package, \b GPL </td>
     <td></td></tr>
 <tr><td>SuperLU</td><td>\link SuperLUSupport_Module SuperLUSupport \endlink</td><td>Direct LU factorization</td><td>Square</td><td>Fill-in reducing, Leverage fast dense algebra</td>
     <td>Requires the <a href="http://crd-legacy.lbl.gov/~xiaoye/SuperLU/">SuperLU</a> library, (BSD-like)</td>
     <td></td></tr>
 <tr><td>SPQR</td><td>\link SPQRSupport_Module SPQRSupport \endlink  </td> <td> QR factorization </td> 
     <td> Any, rectangular</td><td>fill-in reducing, multithreaded, fast dense algebra</td>
-    <td> requires the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">SuiteSparse</a> package, \b GPL </td><td>recommended for linear least-squares problems, has a rank-revealing feature</tr>
+    <td> requires the <a href="http://www.suitesparse.com">SuiteSparse</a> package, \b GPL </td><td>recommended for linear least-squares problems, has a rank-revealing feature</tr>
+<tr><td>PardisoLLT \n PardisoLDLT \n PardisoLU</td><td>\link PardisoSupport_Module PardisoSupport \endlink</td><td>Direct LLt, LDLt, LU factorizations</td><td>SPD \n SPD \n Square</td><td>Fill-in reducing, Leverage fast dense algebra, Multithreading</td>
+    <td>Requires the <a href="http://eigen.tuxfamily.org/Counter/redirect_to_mkl.php">Intel MKL</a> package, \b Proprietary </td>
+    <td>optimized for tough problems patterns, see also \link TopicUsingIntelMKL using MKL with Eigen \endlink</td></tr>
 </table>
 
 Here \c SPD means symmetric positive definite.
+
+\section TutorialSparseSolverConcept Sparse solver concept
 
 All these solvers follow the same general concept.
 Here is a typical and general example:
 \code
 #include <Eigen/RequiredModuleName>
@@ -99,12 +134,14 @@
 x2 = solver.solve(b2);
 ...
 \endcode
 The compute() method is equivalent to calling both analyzePattern() and factorize().
 
-Finally, each solver provides some specific features, such as determinant, access to the factors, controls of the iterations, and so on.
-More details are availble in the documentations of the respective classes.
+Each solver provides some specific features, such as determinant, access to the factors, controls of the iterations, and so on.
+More details are available in the documentations of the respective classes.
+
+Finally, most of the iterative solvers, can also be used in a \b matrix-free context, see the following \link MatrixfreeSolverExample example \endlink.
 
 \section TheSparseCompute The Compute Step
 In the compute() function, the matrix is generally factorized: LLT for self-adjoint matrices, LDLT for general hermitian matrices, LU for non hermitian matrices and QR for rectangular matrices. These are the results of using direct solvers. For this class of solvers precisely, the compute step is further subdivided into analyzePattern() and factorize(). 
 
 The goal of analyzePattern() is to reorder the nonzero elements of the matrix, such that the factorization step creates less fill-in. This step exploits only the structure of the matrix. Hence, the results of this step can be used for other linear systems where the matrix has the same structure. Note however that sometimes, some external solvers (like SuperLU) require that the values of the matrix are set in this step, for instance to equilibrate the rows and columns of the matrix. In this situation, the results of this step should not be used with other matrices.
@@ -138,11 +175,20 @@
 //  ...
 \endcode
 For direct methods, the solution are computed at the machine precision. Sometimes, the solution need not be too accurate. In this case, the iterative methods are more suitable and the desired accuracy can be set before the solve step using \b setTolerance(). For all the available functions, please, refer to the documentation of the \link IterativeLinearSolvers_Module Iterative solvers module \endlink. 
 
 \section BenchmarkRoutine
-Most of the time, all you need is to know how much time it will take to qolve your system, and hopefully, what is the most suitable solver. In Eigen, we provide a benchmark routine that can be used for this purpose. It is very easy to use. In the build directory, navigate to bench/spbench and compile the routine by typing \b make \e spbenchsolver. Run it with --help option to get the list of all available options. Basically, the matrices to test should be in <a href="http://math.nist.gov/MatrixMarket/formats.html">MatrixMarket Coordinate format</a>, and the routine returns the statistics from all available solvers in Eigen. 
+Most of the time, all you need is to know how much time it will take to solve your system, and hopefully, what is the most suitable solver. In Eigen, we provide a benchmark routine that can be used for this purpose. It is very easy to use. In the build directory, navigate to bench/spbench and compile the routine by typing \b make \e spbenchsolver. Run it with --help option to get the list of all available options. Basically, the matrices to test should be in <a href="http://math.nist.gov/MatrixMarket/formats.html">MatrixMarket Coordinate format</a>, and the routine returns the statistics from all available solvers in Eigen.
+
+To export your matrices and right-hand-side vectors in the matrix-market format, you can the the unsupported SparseExtra module:
+\code
+#include <unsupported/Eigen/SparseExtra>
+...
+Eigen::saveMarket(A, "filename.mtx");
+Eigen::saveMarket(A, "filename_SPD.mtx", Eigen::Symmetric); // if A is symmetric-positive-definite
+Eigen::saveMarketVector(B, "filename_b.mtx");
+\endcode
 
 The following table gives an example of XML statistics from several Eigen built-in and external solvers. 
 <TABLE border="1">
  <TR><TH>Matrix <TH> N <TH> NNZ <TH>  <TH > UMFPACK <TH > SUPERLU <TH > PASTIX LU <TH >BiCGSTAB <TH > BiCGSTAB+ILUT <TH >GMRES+ILUT<TH > LDLT <TH> CHOLMOD LDLT <TH > PASTIX LDLT <TH > LLT <TH > CHOLMOD SP LLT <TH > CHOLMOD LLT <TH > PASTIX LLT <TH> CG</TR>
 <TR><TH rowspan="4">vector_graphics <TD rowspan="4"> 12855 <TD rowspan="4"> 72069 <TH>Compute Time <TD>0.0254549<TD>0.0215677<TD>0.0701827<TD>0.000153388<TD>0.0140107<TD>0.0153709<TD>0.0101601<TD style="background-color:red">0.00930502<TD>0.0649689

Index: 3rd_party/eigen/doc/SparseQuickReference.dox
==================================================================
--- 3rd_party/eigen/doc/SparseQuickReference.dox
+++ 3rd_party/eigen/doc/SparseQuickReference.dox
@@ -19,11 +19,11 @@
 </td> <td> Default is ColMajor</td> </tr>
 <tr class="alt">
 <td> Resize/Reserve</td>
 <td> 
  \code
-    sm1.resize(m,n);      //Change sm1 to a m x n matrix. 
+    sm1.resize(m,n);      // Change sm1 to a m x n matrix.
     sm1.reserve(nnz);     // Allocate room for nnz nonzeros elements.   
   \endcode 
 </td>
 <td> Note that when calling reserve(), it is not required that nnz is the exact number of nonzero elements in the final matrix. However, an exact estimation will avoid multiple reallocations during the insertion phase. </td>
 </tr>
@@ -149,14 +149,14 @@
 </tr> 
 <tr>
 <td> Permutation </td>
 <td> 
 \code 
-perm.indices(); // Reference to the vector of indices
+perm.indices();      // Reference to the vector of indices
 sm1.twistedBy(perm); // Permute rows and columns
-sm2 = sm1 * perm; //Permute the columns
-sm2 = perm * sm1; // Permute the columns
+sm2 = sm1 * perm;    // Permute the columns
+sm2 = perm * sm1;    // Permute the columns
 \endcode 
 </td>
 <td> 
 
 </td>
@@ -179,41 +179,47 @@
 </tr>
 </table>
 
 \section sparseotherops Other supported operations
 <table class="manual">
-<tr><th>Operations</th> <th> Code </th> <th> Notes</th> </tr>
+<tr><th style="min-width:initial"> Code </th> <th> Notes</th> </tr>
+<tr><td colspan="2">Sub-matrices</td></tr>
 <tr>
-<td>Sub-matrices</td> 
 <td> 
 \code 
   sm1.block(startRow, startCol, rows, cols); 
   sm1.block(startRow, startCol); 
   sm1.topLeftCorner(rows, cols); 
   sm1.topRightCorner(rows, cols);
   sm1.bottomLeftCorner( rows, cols);
   sm1.bottomRightCorner( rows, cols);
   \endcode
-</td> <td>  </td>
+</td><td>
+Contrary to dense matrices, here <strong>all these methods are read-only</strong>.\n
+See \ref TutorialSparse_SubMatrices and below for read-write sub-matrices.
+</td>
 </tr>
-<tr> 
-<td> Range </td>
+<tr class="alt"><td colspan="2"> Range </td></tr>
+<tr class="alt">
 <td> 
 \code 
-  sm1.innerVector(outer); 
-  sm1.innerVectors(start, size);
-  sm1.leftCols(size);
-  sm2.rightCols(size);
-  sm1.middleRows(start, numRows);
-  sm1.middleCols(start, numCols);
-  sm1.col(j);
+  sm1.innerVector(outer);           // RW
+  sm1.innerVectors(start, size);    // RW
+  sm1.leftCols(size);               // RW
+  sm2.rightCols(size);              // RO because sm2 is row-major
+  sm1.middleRows(start, numRows);   // RO because sm1 is column-major
+  sm1.middleCols(start, numCols);   // RW
+  sm1.col(j);                       // RW
 \endcode
 </td>
-<td>A inner vector is either a row (for row-major) or a column (for column-major). As stated earlier, the evaluation can be done in a matrix with different storage order </td>
+<td>
+A inner vector is either a row (for row-major) or a column (for column-major).\n
+As stated earlier, for a read-write sub-matrix (RW), the evaluation can be done in a matrix with different storage order.
+</td>
 </tr>
+<tr><td colspan="2"> Triangular and selfadjoint views</td></tr>
 <tr>
-<td> Triangular and selfadjoint views</td>
 <td> 
 \code
   sm2 = sm1.triangularview<Lower>();
   sm2 = sm1.selfadjointview<Lower>();
 \endcode
@@ -220,29 +226,47 @@
 </td>
 <td> Several combination between triangular views and blocks views are possible
 \code 
   \endcode </td>
 </tr>
-<tr> 
-<td>Triangular solve </td>
+<tr class="alt"><td colspan="2">Triangular solve </td></tr>
+<tr class="alt">
 <td> 
 \code 
  dv2 = sm1.triangularView<Upper>().solve(dv1);
- dv2 = sm1.topLeftCorner(size, size).triangularView<Lower>().solve(dv1);
+ dv2 = sm1.topLeftCorner(size, size)
+          .triangularView<Lower>().solve(dv1);
 \endcode 
 </td>
 <td> For general sparse solve, Use any suitable module described at \ref TopicSparseSystems </td>
 </tr>
+<tr><td colspan="2"> Low-level API</td></tr>
 <tr>
-<td> Low-level API</td>
+<td>
+\code
+sm1.valuePtr();      // Pointer to the values
+sm1.innerIndextr();  // Pointer to the indices.
+sm1.outerIndexPtr(); // Pointer to the beginning of each inner vector
+\endcode
+</td>
+<td>
+If the matrix is not in compressed form, makeCompressed() should be called before.\n
+Note that these functions are mostly provided for interoperability purposes with external libraries.\n
+A better access to the values of the matrix is done by using the InnerIterator class as described in \link TutorialSparse the Tutorial Sparse \endlink section</td>
+</tr>
+<tr class="alt"><td colspan="2">Mapping external buffers</td></tr>
+<tr class="alt">
 <td>
 \code
-sm1.valuePtr(); // Pointer to the values
-sm1.innerIndextr(); // Pointer to the indices.
-sm1.outerIndexPtr(); //Pointer to the beginning of each inner vector
+int outerIndexPtr[cols+1];
+int innerIndices[nnz];
+double values[nnz];
+Map<SparseMatrix<double> > sm1(rows,cols,nnz,outerIndexPtr, // read-write
+                               innerIndices,values);
+Map<const SparseMatrix<double> > sm2(...);                  // read-only
 \endcode
 </td>
-<td> If the matrix is not in compressed form, makeCompressed() should be called before. Note that these functions are mostly provided for interoperability purposes with external libraries. A better access to the values of the matrix is done by using the InnerIterator class as described in \link TutorialSparse the Tutorial Sparse \endlink section</td>
+<td>As for dense matrices, class Map<SparseMatrixType> can be used to see external buffers as an %Eigen's SparseMatrix object. </td>
 </tr>
 </table>
 */
 }

Index: 3rd_party/eigen/doc/StlContainers.dox
==================================================================
--- 3rd_party/eigen/doc/StlContainers.dox
+++ 3rd_party/eigen/doc/StlContainers.dox
@@ -2,11 +2,11 @@
 
 /** \eigenManualPage TopicStlContainers Using STL Containers with Eigen
 
 \eigenAutoToc
 
-\section summary Executive summary
+\section StlContainers_summary Executive summary
 
 Using STL containers on \ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen types", or classes having members of such types, requires taking the following two steps:
 
 \li A 16-byte-aligned allocator must be used. Eigen does provide one ready for use: aligned_allocator.
 \li If you want to use the std::vector container, you need to \#include <Eigen/StdVector>.
@@ -26,11 +26,11 @@
 std::map<int, Eigen::Vector4f, std::less<int>, 
          Eigen::aligned_allocator<std::pair<const int, Eigen::Vector4f> > >
 \endcode
 Note that the third parameter "std::less<int>" is just the default value, but we have to include it because we want to specify the fourth parameter, which is the allocator type.
 
-\section vector The case of std::vector
+\section StlContainers_vector The case of std::vector
 
 The situation with std::vector was even worse (explanation below) so we had to specialize it for the Eigen::aligned_allocator type. In practice you \b must use the Eigen::aligned_allocator (not another aligned allocator), \b and \#include <Eigen/StdVector>.
 
 Here is an example:
 \code

Index: 3rd_party/eigen/doc/StructHavingEigenMembers.dox
==================================================================
--- 3rd_party/eigen/doc/StructHavingEigenMembers.dox
+++ 3rd_party/eigen/doc/StructHavingEigenMembers.dox
@@ -2,15 +2,15 @@
 
 /** \eigenManualPage TopicStructHavingEigenMembers Structures Having Eigen Members
 
 \eigenAutoToc
 
-\section summary Executive Summary
+\section StructHavingEigenMembers_summary Executive Summary
 
-If you define a structure having members of \ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen types", you must overload its "operator new" so that it generates 16-bytes-aligned pointers. Fortunately, Eigen provides you with a macro EIGEN_MAKE_ALIGNED_OPERATOR_NEW that does that for you.
+If you define a structure having members of \ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen types", you must overload its "operator new" so that it generates 16-bytes-aligned pointers. Fortunately, %Eigen provides you with a macro EIGEN_MAKE_ALIGNED_OPERATOR_NEW that does that for you.
 
-\section what What kind of code needs to be changed?
+\section StructHavingEigenMembers_what What kind of code needs to be changed?
 
 The kind of code that needs to be changed is this:
 
 \code
 class Foo
@@ -25,11 +25,11 @@
 Foo *foo = new Foo;
 \endcode
 
 In other words: you have a class that has as a member a \ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen object", and then you dynamically create an object of that class.
 
-\section how How should such code be modified?
+\section StructHavingEigenMembers_how How should such code be modified?
 
 Very easy, you just need to put a EIGEN_MAKE_ALIGNED_OPERATOR_NEW macro in a public part of your class, like this:
 
 \code
 class Foo
@@ -46,13 +46,13 @@
 Foo *foo = new Foo;
 \endcode
 
 This macro makes "new Foo" always return an aligned pointer.
 
-If this approach is too intrusive, see also the \ref othersolutions.
+If this approach is too intrusive, see also the \ref StructHavingEigenMembers_othersolutions "other solutions".
 
-\section why Why is this needed?
+\section StructHavingEigenMembers_why Why is this needed?
 
 OK let's say that your code looks like this:
 
 \code
 class Foo
@@ -65,11 +65,11 @@
 ...
 
 Foo *foo = new Foo;
 \endcode
 
-A Eigen::Vector2d consists of 2 doubles, which is 128 bits. Which is exactly the size of a SSE packet, which makes it possible to use SSE for all sorts of operations on this vector. But SSE instructions (at least the ones that Eigen uses, which are the fast ones) require 128-bit alignment. Otherwise you get a segmentation fault.
+A Eigen::Vector2d consists of 2 doubles, which is 128 bits. Which is exactly the size of a SSE packet, which makes it possible to use SSE for all sorts of operations on this vector. But SSE instructions (at least the ones that %Eigen uses, which are the fast ones) require 128-bit alignment. Otherwise you get a segmentation fault.
 
 For this reason, Eigen takes care by itself to require 128-bit alignment for Eigen::Vector2d, by doing two things:
 \li Eigen requires 128-bit alignment for the Eigen::Vector2d's array (of 2 doubles). With GCC, this is done with a __attribute__ ((aligned(16))).
 \li Eigen overloads the "operator new" of Eigen::Vector2d so it will always return 128-bit aligned pointers.
 
@@ -79,11 +79,11 @@
 
 The alignment attribute of the member v is then relative to the start of the class, foo. If the foo pointer wasn't aligned, then foo->v won't be aligned either!
 
 The solution is to let class Foo have an aligned "operator new", as we showed in the previous section.
 
-\section movetotop Should I then put all the members of Eigen types at the beginning of my class?
+\section StructHavingEigenMembers_movetotop Should I then put all the members of Eigen types at the beginning of my class?
 
 That's not required. Since Eigen takes care of declaring 128-bit alignment, all members that need it are automatically 128-bit aligned relatively to the class. So code like this works fine:
 
 \code
 class Foo
@@ -93,19 +93,19 @@
 public:
   EIGEN_MAKE_ALIGNED_OPERATOR_NEW
 };
 \endcode
 
-\section dynamicsize What about dynamic-size matrices and vectors?
+\section StructHavingEigenMembers_dynamicsize What about dynamic-size matrices and vectors?
 
 Dynamic-size matrices and vectors, such as Eigen::VectorXd, allocate dynamically their own array of coefficients, so they take care of requiring absolute alignment automatically. So they don't cause this issue. The issue discussed here is only with \ref TopicFixedSizeVectorizable  "fixed-size vectorizable matrices and vectors".
 
-\section bugineigen So is this a bug in Eigen?
+\section StructHavingEigenMembers_bugineigen So is this a bug in Eigen?
 
 No, it's not our bug. It's more like an inherent problem of the C++98 language specification, and seems to be taken care of in the upcoming language revision: <a href="http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2007/n2341.pdf">see this document</a>.
 
-\section conditional What if I want to do this conditionnally (depending on template parameters) ?
+\section StructHavingEigenMembers_conditional What if I want to do this conditionnally (depending on template parameters) ?
 
 For this situation, we offer the macro EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign). It will generate aligned operators like EIGEN_MAKE_ALIGNED_OPERATOR_NEW if NeedsToAlign is true. It will generate operators with the default alignment if NeedsToAlign is false.
 
 Example:
 
@@ -126,11 +126,11 @@
 Foo<4> *foo4 = new Foo<4>; // foo4 is guaranteed to be 128bit-aligned
 Foo<3> *foo3 = new Foo<3>; // foo3 has only the system default alignment guarantee
 \endcode
 
 
-\section othersolutions Other solutions
+\section StructHavingEigenMembers_othersolutions Other solutions
 
 In case putting the EIGEN_MAKE_ALIGNED_OPERATOR_NEW macro everywhere is too intrusive, there exists at least two other solutions.
 
 \subsection othersolutions1 Disabling alignment
 

Index: 3rd_party/eigen/doc/TemplateKeyword.dox
==================================================================
--- 3rd_party/eigen/doc/TemplateKeyword.dox
+++ 3rd_party/eigen/doc/TemplateKeyword.dox
@@ -3,11 +3,12 @@
 /** \page TopicTemplateKeyword The template and typename keywords in C++
 
 There are two uses for the \c template and \c typename keywords in C++. One of them is fairly well known
 amongst programmers: to define templates. The other use is more obscure: to specify that an expression refers
 to a template function or a type. This regularly trips up programmers that use the %Eigen library, often
-leading to error messages from the compiler that are difficult to understand.
+leading to error messages from the compiler that are difficult to understand, such as "expected expression" or
+"no match for operator<".
 
 \eigenAutoToc
 
 
 \section TopicTemplateKeywordToDefineTemplates Using the template and typename keywords to define templates
@@ -70,27 +71,27 @@
 \section TopicTemplateKeywordExplanation Explanation
 
 The reason that the \c template keyword is necessary in the last example has to do with the rules for how
 templates are supposed to be compiled in C++. The compiler has to check the code for correct syntax at the
 point where the template is defined, without knowing the actual value of the template arguments (\c Derived1
-and \c Derived2 in the example). That means that the compiler cannot know that <tt>dst.triangularPart</tt> is
+and \c Derived2 in the example). That means that the compiler cannot know that <tt>dst.triangularView</tt> is
 a member template and that the following &lt; symbol is part of the delimiter for the template
-parameter. Another possibility would be that <tt>dst.triangularPart</tt> is a member variable with the &lt;
+parameter. Another possibility would be that <tt>dst.triangularView</tt> is a member variable with the &lt;
 symbol refering to the <tt>operator&lt;()</tt> function. In fact, the compiler should choose the second
-possibility, according to the standard. If <tt>dst.triangularPart</tt> is a member template (as in our case),
+possibility, according to the standard. If <tt>dst.triangularView</tt> is a member template (as in our case),
 the programmer should specify this explicitly with the \c template keyword and write <tt>dst.template
-triangularPart</tt>.
+triangularView</tt>.
 
 The precise rules are rather complicated, but ignoring some subtleties we can summarize them as follows:
 - A <em>dependent name</em> is name that depends (directly or indirectly) on a template parameter. In the
   example, \c dst is a dependent name because it is of type <tt>MatrixBase&lt;Derived1&gt;</tt> which depends
   on the template parameter \c Derived1.
-- If the code contains either one of the contructions <tt>xxx.yyy</tt> or <tt>xxx-&gt;yyy</tt> and \c xxx is a
+- If the code contains either one of the constructs <tt>xxx.yyy</tt> or <tt>xxx-&gt;yyy</tt> and \c xxx is a
   dependent name and \c yyy refers to a member template, then the \c template keyword must be used before 
   \c yyy, leading to <tt>xxx.template yyy</tt> or <tt>xxx-&gt;template yyy</tt>.
-- If the code contains the contruction <tt>xxx::yyy</tt> and \c xxx is a dependent name and \c yyy refers to a
-  member typedef, then the \c typename keyword must be used before the whole construction, leading to
+- If the code contains the construct <tt>xxx::yyy</tt> and \c xxx is a dependent name and \c yyy refers to a
+  member typedef, then the \c typename keyword must be used before the whole construct, leading to
   <tt>typename xxx::yyy</tt>.
 
 As an example where the \c typename keyword is required, consider the following code in \ref TutorialSparse
 for iterating over the non-zero entries of a sparse matrix type:
 

Index: 3rd_party/eigen/doc/TopicAliasing.dox
==================================================================
--- 3rd_party/eigen/doc/TopicAliasing.dox
+++ 3rd_party/eigen/doc/TopicAliasing.dox
@@ -151,14 +151,15 @@
 not necessary to evaluate the right-hand side explicitly.
 
 
 \section TopicAliasingMatrixMult Aliasing and matrix multiplication
 
-Matrix multiplication is the only operation in %Eigen that assumes aliasing by default. Thus, if \c matA is a
-matrix, then the statement <tt>matA = matA * matA;</tt> is safe. All other operations in %Eigen assume that
-there are no aliasing problems, either because the result is assigned to a different matrix or because it is a
-component-wise operation.
+Matrix multiplication is the only operation in %Eigen that assumes aliasing by default, <strong>under the
+condition that the destination matrix is not resized</strong>.
+Thus, if \c matA is a \b squared matrix, then the statement <tt>matA = matA * matA;</tt> is safe.
+All other operations in %Eigen assume that there are no aliasing problems,
+either because the result is assigned to a different matrix or because it is a component-wise operation.
 
 <table class="example">
 <tr><th>Example</th><th>Output</th></tr>
 <tr><td>
 \include TopicAliasing_mult1.cpp
@@ -196,10 +197,31 @@
 </td>
 <td>
 \verbinclude TopicAliasing_mult3.out
 </td></tr></table>
 
+Moreover, starting in Eigen 3.3, aliasing is \b not assumed if the destination matrix is resized and the product is not directly assigned to the destination.
+Therefore, the following example is also wrong:
+
+<table class="example">
+<tr><th>Example</th><th>Output</th></tr>
+<tr><td>
+\include TopicAliasing_mult4.cpp
+</td>
+<td>
+\verbinclude TopicAliasing_mult4.out
+</td></tr></table>
+
+As for any aliasing issue, you can resolve it by explicitly evaluating the expression prior to assignment:
+<table class="example">
+<tr><th>Example</th><th>Output</th></tr>
+<tr><td>
+\include TopicAliasing_mult5.cpp
+</td>
+<td>
+\verbinclude TopicAliasing_mult5.out
+</td></tr></table>
 
 \section TopicAliasingSummary Summary
 
 Aliasing occurs when the same matrix or array coefficients appear both on the left- and the right-hand side of
 an assignment operator.

Index: 3rd_party/eigen/doc/TopicAssertions.dox
==================================================================
--- 3rd_party/eigen/doc/TopicAssertions.dox
+++ 3rd_party/eigen/doc/TopicAssertions.dox
@@ -14,11 +14,11 @@
 
 \code
 #include <stdexcept>
 #undef eigen_assert
 #define eigen_assert(x) \
-  if (!x) { throw (std::runtime_error("Put your message here")); }
+  if (!(x)) { throw (std::runtime_error("Put your message here")); }
 \endcode
 
 \subsection DisableAssert Disabling assertions
 
 Assertions cost run time and can be turned off. You can suppress eigen_assert by defining \c EIGEN_NO_DEBUG \b before including Eigen headers. \c EIGEN_NO_DEBUG is undefined by default unless \c NDEBUG is defined.

ADDED   3rd_party/eigen/doc/TopicCMakeGuide.dox
Index: 3rd_party/eigen/doc/TopicCMakeGuide.dox
==================================================================
--- 3rd_party/eigen/doc/TopicCMakeGuide.dox
+++ 3rd_party/eigen/doc/TopicCMakeGuide.dox
@@ -0,0 +1,52 @@
+namespace Eigen {
+
+/**
+
+\page TopicCMakeGuide Using %Eigen in CMake Projects
+
+%Eigen provides native CMake support which allows the library to be easily
+used in CMake projects.
+
+\note %CMake 3.0 (or later) is required to enable this functionality.
+
+%Eigen exports a CMake target called `Eigen3::Eigen` which can be imported
+using the `find_package` CMake command and used by calling
+`target_link_libraries` as in the following example:
+\code{.cmake}
+cmake_minimum_required (VERSION 3.0)
+project (myproject)
+
+find_package (Eigen3 3.3 REQUIRED NO_MODULE)
+
+add_executable (example example.cpp)
+target_link_libraries (example Eigen3::Eigen)
+\endcode
+
+The above code snippet must be placed in a file called `CMakeLists.txt` alongside
+`example.cpp`. After running
+\code{.sh}
+$ cmake path-to-example-directory
+\endcode
+CMake will produce project files that generate an executable called `example`
+which requires at least version 3.3 of %Eigen. Here, `path-to-example-directory`
+is the path to the directory that contains both `CMakeLists.txt` and
+`example.cpp`.
+
+If you have multiple installed version of %Eigen, you can pick your favorite one by setting the \c Eigen3_DIR cmake's variable to the respective path containing the \c Eigen3*.cmake files. For instance:
+\code
+cmake path-to-example-directory -DEigen3_DIR=$HOME/mypackages/share/eigen3/cmake/
+\endcode
+
+If the `REQUIRED` option is omitted when locating %Eigen using
+`find_package`, one can check whether the package was found as follows:
+\code{.cmake}
+find_package (Eigen3 3.3 NO_MODULE)
+
+if (TARGET Eigen3::Eigen)
+  # Use the imported target
+endif (TARGET Eigen3::Eigen)
+\endcode
+
+*/
+
+}

Index: 3rd_party/eigen/doc/TopicLazyEvaluation.dox
==================================================================
--- 3rd_party/eigen/doc/TopicLazyEvaluation.dox
+++ 3rd_party/eigen/doc/TopicLazyEvaluation.dox
@@ -34,11 +34,11 @@
 
 \code matrix1 = -matrix2 + matrix3 + 5 * matrix4; \endcode
 
 Eigen chooses lazy evaluation at every stage in that example, which is clearly the correct choice. In fact, lazy evaluation is the "default choice" and Eigen will choose it except in a few circumstances.
 
-<b>The first circumstance</b> in which Eigen chooses immediate evaluation, is when it sees an assignment <tt>a = b;</tt> and the expression \c b has the evaluate-before-assigning \link flags flag\endlink. The most important example of such an expression is the \link GeneralProduct matrix product expression\endlink. For example, when you do
+<b>The first circumstance</b> in which Eigen chooses immediate evaluation, is when it sees an assignment <tt>a = b;</tt> and the expression \c b has the evaluate-before-assigning \link flags flag\endlink. The most important example of such an expression is the \link Product matrix product expression\endlink. For example, when you do
 
 \code matrix = matrix * matrix; \endcode
 
 Eigen first evaluates <tt>matrix * matrix</tt> into a temporary matrix, and then copies it into the original \c matrix. This guarantees a correct result as we saw above that lazy evaluation gives wrong results with matrix products. It also doesn't cost much, as the cost of the matrix product itself is much higher.
 
@@ -46,11 +46,11 @@
 
 \code matrix1.noalias() = matrix2 * matrix2; \endcode
 
 Here, since we know that matrix2 is not the same matrix as matrix1, we know that lazy evaluation is not dangerous, so we may force lazy evaluation. Concretely, the effect of noalias() here is to bypass the evaluate-before-assigning \link flags flag\endlink.
 
-<b>The second circumstance</b> in which Eigen chooses immediate evaluation, is when it sees a nested expression such as <tt>a + b</tt> where \c b is already an expression having the evaluate-before-nesting \link flags flag\endlink. Again, the most important example of such an expression is the \link GeneralProduct matrix product expression\endlink. For example, when you do
+<b>The second circumstance</b> in which Eigen chooses immediate evaluation, is when it sees a nested expression such as <tt>a + b</tt> where \c b is already an expression having the evaluate-before-nesting \link flags flag\endlink. Again, the most important example of such an expression is the \link Product matrix product expression\endlink. For example, when you do
 
 \code matrix1 = matrix2 + matrix3 * matrix4; \endcode
 
 the product <tt>matrix3 * matrix4</tt> gets evaluated immediately into a temporary matrix. Indeed, experiments showed that it is often beneficial for performance to evaluate immediately matrix products when they are nested into bigger expressions.
 

Index: 3rd_party/eigen/doc/TopicLinearAlgebraDecompositions.dox
==================================================================
--- 3rd_party/eigen/doc/TopicLinearAlgebraDecompositions.dox
+++ 3rd_party/eigen/doc/TopicLinearAlgebraDecompositions.dox
@@ -2,10 +2,11 @@
 
 /** \eigenManualPage TopicLinearAlgebraDecompositions Catalogue of dense decompositions
 
 This page presents a catalogue of the dense matrix decompositions offered by Eigen.
 For an introduction on linear solvers and decompositions, check this \link TutorialLinearAlgebra page \endlink.
+To get an overview of the true relative speed of the different decomposition, check this \link DenseDecompositionBenchmark benchmark \endlink.
 
 \section TopicLinAlgBigTable Catalogue of decompositions offered by Eigen
 
 <table class="manual-vl">
     <tr>
@@ -114,11 +115,11 @@
 
     <tr>
         <td>JacobiSVD (two-sided)</td>
         <td>-</td>
         <td>Slow (but fast for small matrices)</td>
-        <td>Excellent-Proven<sup><a href="#note3">3</a></sup></td>
+        <td>Proven<sup><a href="#note3">3</a></sup></td>
         <td>Yes</td>
         <td>Singular values/vectors, least squares</td>
         <td>Yes (and does least squares)</td>
         <td>Excellent</td>
         <td>R-SVD</td>
@@ -130,11 +131,11 @@
         <td>Fast-average<sup><a href="#note2">2</a></sup></td>
         <td>Good</td>
         <td>Yes</td>
         <td>Eigenvalues/vectors</td>
         <td>-</td>
-        <td>Good</td>
+        <td>Excellent</td>
         <td><em>Closed forms for 2x2 and 3x3</em></td>
     </tr>
 
     <tr>
         <td>ComplexEigenSolver</td>
@@ -247,15 +248,16 @@
   <dt><b>Blocking</b></dt>
     <dd>Means the algorithm can work per block, whence guaranteeing a good scaling of the performance for large matrices.</dd>
   <dt><b>Implicit Multi Threading (MT)</b></dt>
     <dd>Means the algorithm can take advantage of multicore processors via OpenMP. "Implicit" means the algortihm itself is not parallelized, but that it relies on parallelized matrix-matrix product rountines.</dd>
   <dt><b>Explicit Multi Threading (MT)</b></dt>
-    <dd>Means the algorithm is explicitely parallelized to take advantage of multicore processors via OpenMP.</dd>
+    <dd>Means the algorithm is explicitly parallelized to take advantage of multicore processors via OpenMP.</dd>
   <dt><b>Meta-unroller</b></dt>
     <dd>Means the algorithm is automatically and explicitly unrolled for very small fixed size matrices.</dd>
   <dt><b></b></dt>
     <dd></dd>
 </dl>
+
 
 */
 
 }

Index: 3rd_party/eigen/doc/TopicMultithreading.dox
==================================================================
--- 3rd_party/eigen/doc/TopicMultithreading.dox
+++ 3rd_party/eigen/doc/TopicMultithreading.dox
@@ -6,26 +6,30 @@
 
 Some Eigen's algorithms can exploit the multiple cores present in your hardware. To this end, it is enough to enable OpenMP on your compiler, for instance:
  * GCC: \c -fopenmp
  * ICC: \c -openmp
  * MSVC: check the respective option in the build properties.
-You can control the number of thread that will be used using either the OpenMP API or Eiegn's API using the following priority:
+You can control the number of thread that will be used using either the OpenMP API or Eigen's API using the following priority:
 \code
  OMP_NUM_THREADS=n ./my_program
  omp_set_num_threads(n);
  Eigen::setNbThreads(n);
 \endcode
-Unless setNbThreads has been called, Eigen uses the number of threads specified by OpenMP. You can restore this bahavior by calling \code setNbThreads(0); \endcode
+Unless setNbThreads has been called, Eigen uses the number of threads specified by OpenMP. You can restore this behavior by calling \code setNbThreads(0); \endcode
 You can query the number of threads that will be used with:
 \code
-n = Eigen::nbThreads(n);
+n = Eigen::nbThreads( );
 \endcode
 You can disable Eigen's multi threading at compile time by defining the EIGEN_DONT_PARALLELIZE preprocessor token.
 
 Currently, the following algorithms can make use of multi-threading:
- * general matrix - matrix products
- * PartialPivLU
+ - general dense matrix - matrix products
+ - PartialPivLU
+ - row-major-sparse * dense vector/matrix products
+ - ConjugateGradient with \c Lower|Upper as the \c UpLo template parameter.
+ - BiCGSTAB with a row-major sparse matrix format.
+ - LeastSquaresConjugateGradient
 
 \section TopicMultiThreading_UsingEigenWithMT Using Eigen in a multi-threaded application
 
 In the case your own application is multithreaded, and multiple threads make calls to Eigen, then you have to initialize Eigen by calling the following routine \b before creating the threads:
 \code
@@ -37,10 +41,14 @@
   
   ...
 }
 \endcode
 
+\note With Eigen 3.3, and a fully C++11 compliant compiler (i.e., <a href="http://en.cppreference.com/w/cpp/language/storage_duration#Static_local_variables">thread-safe static local variable initialization</a>), then calling \c initParallel() is optional.
+
+\warning note that all functions generating random matrices are \b not re-entrant nor thread-safe. Those include DenseBase::Random(), and DenseBase::setRandom() despite a call to Eigen::initParallel(). This is because these functions are based on std::rand which is not re-entrant. For thread-safe random generator, we recommend the use of boost::random or c++11 random feature.
+
 In the case your application is parallelized with OpenMP, you might want to disable Eigen's own parallization as detailed in the previous section.
 
 */
 
 }

Index: 3rd_party/eigen/doc/TutorialArrayClass.dox
==================================================================
--- 3rd_party/eigen/doc/TutorialArrayClass.dox
+++ 3rd_party/eigen/doc/TutorialArrayClass.dox
@@ -155,11 +155,11 @@
 \link MatrixBase::array() .array() \endlink method. For example, the statement 
 <tt>result = m.array() * n.array()</tt> takes two matrices \c m and \c n, converts them both to an array, uses
 * to multiply them coefficient-wise and assigns the result to the matrix variable \c result (this is legal
 because Eigen allows assigning array expressions to matrix variables). 
 
-As a matter of fact, this usage case is so common that Eigen provides a \link MatrixBase::cwiseProduct() const
+As a matter of fact, this usage case is so common that Eigen provides a \link MatrixBase::cwiseProduct const
 .cwiseProduct(.) \endlink method for matrices to compute the coefficient-wise product. This is also shown in
 the example program.
 
 <table class="example">
 <tr><th>Example:</th><th>Output:</th></tr>

Index: 3rd_party/eigen/doc/TutorialGeometry.dox
==================================================================
--- 3rd_party/eigen/doc/TutorialGeometry.dox
+++ 3rd_party/eigen/doc/TutorialGeometry.dox
@@ -124,15 +124,16 @@
 <tr class="alt"><td>
 Apply the transformation to a \b vector </td><td>\code
 VectorNf vec1, vec2;
 vec2 = t.linear() * vec1;\endcode</td></tr>
 <tr><td>
-Apply a \em general transformation \n to a \b normal \b vector
-(<a href="http://femto.cs.uiuc.edu/faqs/cga-faq.html#S5.27">explanations</a>)</td><td>\code
+Apply a \em general transformation \n to a \b normal \b vector \n
+</td><td>\code
 VectorNf n1, n2;
 MatrixNf normalMatrix = t.linear().inverse().transpose();
 n2 = (normalMatrix * n1).normalized();\endcode</td></tr>
+<tr><td colspan="2">(See subject 5.27 of this <a href="http://www.faqs.org/faqs/graphics/algorithms-faq">faq</a> for the explanations)</td></tr>
 <tr class="alt"><td>
 Apply a transformation with \em pure \em rotation \n to a \b normal \b vector
 (no scaling, no shear)</td><td>\code
 n2 = t.linear() * n1;\endcode</td></tr>
 <tr><td>
@@ -229,13 +230,13 @@
 Euler angles might be convenient to create rotation objects.
 On the other hand, since there exist 24 different conventions, they are pretty confusing to use. This example shows how
 to create a rotation matrix according to the 2-1-2 convention.</td><td>\code
 Matrix3f m;
 m = AngleAxisf(angle1, Vector3f::UnitZ())
-*  * AngleAxisf(angle2, Vector3f::UnitY())
-*  * AngleAxisf(angle3, Vector3f::UnitZ());
+  * AngleAxisf(angle2, Vector3f::UnitY())
+  * AngleAxisf(angle3, Vector3f::UnitZ());
 \endcode</td></tr>
 </table>
 
 */
 
 }

Index: 3rd_party/eigen/doc/TutorialLinearAlgebra.dox
==================================================================
--- 3rd_party/eigen/doc/TutorialLinearAlgebra.dox
+++ 3rd_party/eigen/doc/TutorialLinearAlgebra.dox
@@ -38,69 +38,85 @@
 
 <table class="manual">
     <tr>
         <th>Decomposition</th>
         <th>Method</th>
-        <th>Requirements on the matrix</th>
-        <th>Speed</th>
+        <th>Requirements<br/>on the matrix</th>
+        <th>Speed<br/> (small-to-medium)</th>
+        <th>Speed<br/> (large)</th>
         <th>Accuracy</th>
     </tr>
     <tr>
         <td>PartialPivLU</td>
         <td>partialPivLu()</td>
         <td>Invertible</td>
+        <td>++</td>
         <td>++</td>
         <td>+</td>
     </tr>
     <tr class="alt">
         <td>FullPivLU</td>
         <td>fullPivLu()</td>
         <td>None</td>
         <td>-</td>
+        <td>- -</td>
         <td>+++</td>
     </tr>
     <tr>
         <td>HouseholderQR</td>
         <td>householderQr()</td>
         <td>None</td>
+        <td>++</td>
         <td>++</td>
         <td>+</td>
     </tr>
     <tr class="alt">
         <td>ColPivHouseholderQR</td>
         <td>colPivHouseholderQr()</td>
         <td>None</td>
-        <td>+</td>
         <td>++</td>
+        <td>-</td>
+        <td>+++</td>
     </tr>
     <tr>
         <td>FullPivHouseholderQR</td>
         <td>fullPivHouseholderQr()</td>
         <td>None</td>
         <td>-</td>
+        <td>- -</td>
         <td>+++</td>
     </tr>
     <tr class="alt">
         <td>LLT</td>
         <td>llt()</td>
         <td>Positive definite</td>
         <td>+++</td>
+        <td>+++</td>
         <td>+</td>
     </tr>
     <tr>
         <td>LDLT</td>
         <td>ldlt()</td>
-        <td>Positive or negative semidefinite</td>
+        <td>Positive or negative<br/> semidefinite</td>
         <td>+++</td>
+        <td>+</td>
         <td>++</td>
+    </tr>
+    <tr class="alt">
+        <td>JacobiSVD</td>
+        <td>jacobiSvd()</td>
+        <td>None</td>
+        <td>- -</td>
+        <td>- - -</td>
+        <td>+++</td>
     </tr>
 </table>
 
 All of these decompositions offer a solve() method that works as in the above example.
 
 For example, if your matrix is positive definite, the above table says that a very good
-choice is then the LDLT decomposition. Here's an example, also demonstrating that using a general
+choice is then the LLT or LDLT decomposition. Here's an example, also demonstrating that using a general
 matrix (not a vector) as right hand side is possible.
 
 <table class="example">
 <tr><th>Example:</th><th>Output:</th></tr>
 <tr>
@@ -165,12 +181,12 @@
 </tr>
 </table>
 
 \section TutorialLinAlgLeastsquares Least squares solving
 
-The best way to do least squares solving is with a SVD decomposition. Eigen provides one as the JacobiSVD class, and its solve()
-is doing least-squares solving.
+The most accurate method to do least squares solving is with a SVD decomposition. Eigen provides one
+as the JacobiSVD class, and its solve() is doing least-squares solving.
 
 Here is an example:
 <table class="example">
 <tr><th>Example:</th><th>Output:</th></tr>
 <tr>
@@ -177,13 +193,14 @@
   <td>\include TutorialLinAlgSVDSolve.cpp </td>
   <td>\verbinclude TutorialLinAlgSVDSolve.out </td>
 </tr>
 </table>
 
-Another way, potentially faster but less reliable, is to use a LDLT decomposition
-of the normal matrix. In any case, just read any reference text on least squares, and it will be very easy for you
-to implement any linear least squares computation on top of Eigen.
+Another methods, potentially faster but less reliable, are to use a Cholesky decomposition of the
+normal matrix or a QR decomposition. Our page on \link LeastSquares least squares solving \endlink
+has more details.
+
 
 \section TutorialLinAlgSeparateComputation Separating the computation from the construction
 
 In the above examples, the decomposition was computed at the same time that the decomposition object was constructed.
 There are however situations where you might want to separate these two things, for example if you don't know,

Index: 3rd_party/eigen/doc/TutorialReductionsVisitorsBroadcasting.dox
==================================================================
--- 3rd_party/eigen/doc/TutorialReductionsVisitorsBroadcasting.dox
+++ 3rd_party/eigen/doc/TutorialReductionsVisitorsBroadcasting.dox
@@ -30,11 +30,11 @@
 
 Eigen also provides the \link MatrixBase::norm() norm() \endlink method, which returns the square root of \link MatrixBase::squaredNorm() squaredNorm() \endlink.
 
 These operations can also operate on matrices; in that case, a n-by-p matrix is seen as a vector of size (n*p), so for example the \link MatrixBase::norm() norm() \endlink method returns the "Frobenius" or "Hilbert-Schmidt" norm. We refrain from speaking of the \f$\ell^2\f$ norm of a matrix because that can mean different things.
 
-If you want other \f$\ell^p\f$ norms, use the \link MatrixBase::lpNorm() lpNnorm<p>() \endlink method. The template parameter \a p can take the special value \a Infinity if you want the \f$\ell^\infty\f$ norm, which is the maximum of the absolute values of the coefficients.
+If you want other coefficient-wise \f$\ell^p\f$ norms, use the \link MatrixBase::lpNorm lpNorm<p>() \endlink method. The template parameter \a p can take the special value \a Infinity if you want the \f$\ell^\infty\f$ norm, which is the maximum of the absolute values of the coefficients.
 
 The following example demonstrates these methods.
 
 <table class="example">
 <tr><th>Example:</th><th>Output:</th></tr>
@@ -42,10 +42,21 @@
 \include Tutorial_ReductionsVisitorsBroadcasting_reductions_norm.cpp
 </td>
 <td>
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_reductions_norm.out
 </td></tr></table>
+
+\b Operator \b norm: The 1-norm and \f$\infty\f$-norm <a href="https://en.wikipedia.org/wiki/Operator_norm">matrix operator norms</a> can easily be computed as follows:
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.cpp
+</td>
+<td>
+\verbinclude Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.out
+</td></tr></table>
+See below for more explanations on the syntax of these expressions.
 
 \subsection TutorialReductionsVisitorsBroadcastingReductionsBool Boolean reductions
 
 The following reductions operate on boolean values:
   - \link DenseBase::all() all() \endlink returns \b true if all of the coefficients in a given Matrix or Array evaluate to \b true .
@@ -77,11 +88,11 @@
 the location of the greatest or smallest coefficient in a Matrix or 
 Array.
 
 The arguments passed to a visitor are pointers to the variables where the
 row and column position are to be stored. These variables should be of type
-\link DenseBase::Index Index \endlink, as shown below:
+\link Eigen::Index Index \endlink, as shown below:
 
 <table class="example">
 <tr><th>Example:</th><th>Output:</th></tr>
 <tr><td>
 \include Tutorial_ReductionsVisitorsBroadcasting_visitors.cpp
@@ -88,21 +99,20 @@
 </td>
 <td>
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_visitors.out
 </td></tr></table>
 
-Note that both functions also return the value of the minimum or maximum coefficient if needed,
-as if it was a typical reduction operation.
+Both functions also return the value of the minimum or maximum coefficient.
 
 \section TutorialReductionsVisitorsBroadcastingPartialReductions Partial reductions
 Partial reductions are reductions that can operate column- or row-wise on a Matrix or 
 Array, applying the reduction operation on each column or row and 
-returning a column or row-vector with the corresponding values. Partial reductions are applied 
+returning a column or row vector with the corresponding values. Partial reductions are applied 
 with \link DenseBase::colwise() colwise() \endlink or \link DenseBase::rowwise() rowwise() \endlink.
 
 A simple example is obtaining the maximum of the elements 
-in each column in a given matrix, storing the result in a row-vector:
+in each column in a given matrix, storing the result in a row vector:
 
 <table class="example">
 <tr><th>Example:</th><th>Output:</th></tr>
 <tr><td>
 \include Tutorial_ReductionsVisitorsBroadcasting_colwise.cpp
@@ -120,12 +130,11 @@
 </td>
 <td>
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_rowwise.out
 </td></tr></table>
 
-<b>Note that column-wise operations return a 'row-vector' while row-wise operations
-return a 'column-vector'</b>
+<b>Note that column-wise operations return a row vector, while row-wise operations return a column vector.</b>
 
 \subsection TutorialReductionsVisitorsBroadcastingPartialReductionsCombined Combining partial reductions with other operations
 It is also possible to use the result of a partial reduction to do further processing.
 Here is another example that finds the column whose sum of elements is the maximum
  within a matrix. With column-wise partial reductions this can be coded as:
@@ -163,11 +172,11 @@
 \section TutorialReductionsVisitorsBroadcastingBroadcasting Broadcasting
 The concept behind broadcasting is similar to partial reductions, with the difference that broadcasting 
 constructs an expression where a vector (column or row) is interpreted as a matrix by replicating it in 
 one direction.
 
-A simple example is to add a certain column-vector to each column in a matrix. 
+A simple example is to add a certain column vector to each column in a matrix. 
 This can be accomplished with:
 
 <table class="example">
 <tr><th>Example:</th><th>Output:</th></tr>
 <tr><td>
@@ -240,11 +249,11 @@
      0 & 8  & 4 & -1
   \end{bmatrix}
 \f]
 
   - <tt>(m.colwise() - v).colwise().squaredNorm()</tt> is a partial reduction, computing the squared norm column-wise. The result of
-this operation is a row-vector where each coefficient is the squared Euclidean distance between each column in <tt>m</tt> and <tt>v</tt>: \f[
+this operation is a row vector where each coefficient is the squared Euclidean distance between each column in <tt>m</tt> and <tt>v</tt>: \f[
   \mbox{(m.colwise() - v).colwise().squaredNorm()} =
   \begin{bmatrix}
      1 & 505 & 32 & 50
   \end{bmatrix}
 \f]

ADDED   3rd_party/eigen/doc/TutorialReshapeSlicing.dox
Index: 3rd_party/eigen/doc/TutorialReshapeSlicing.dox
==================================================================
--- 3rd_party/eigen/doc/TutorialReshapeSlicing.dox
+++ 3rd_party/eigen/doc/TutorialReshapeSlicing.dox
@@ -0,0 +1,65 @@
+namespace Eigen {
+
+/** \eigenManualPage TutorialReshapeSlicing Reshape and Slicing
+
+%Eigen does not expose convenient methods to take slices or to reshape a matrix yet.
+Nonetheless, such features can easily be emulated using the Map class.
+
+\eigenAutoToc
+
+\section TutorialReshape Reshape
+
+A reshape operation consists in modifying the sizes of a matrix while keeping the same coefficients.
+Instead of modifying the input matrix itself, which is not possible for compile-time sizes, the approach consist in creating a different \em view on the storage using class Map.
+Here is a typical example creating a 1D linear view of a matrix:
+
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReshapeMat2Vec.cpp
+</td>
+<td>
+\verbinclude Tutorial_ReshapeMat2Vec.out
+</td></tr></table>
+
+Remark how the storage order of the input matrix modifies the order of the coefficients in the linear view.
+Here is another example reshaping a 2x6 matrix to a 6x2 one:
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReshapeMat2Mat.cpp
+</td>
+<td>
+\verbinclude Tutorial_ReshapeMat2Mat.out
+</td></tr></table>
+
+
+
+\section TutorialSlicing Slicing
+
+Slicing consists in taking a set of rows, columns, or elements, uniformly spaced within a matrix.
+Again, the class Map allows to easily mimic this feature.
+
+For instance, one can skip every P elements in a vector:
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_SlicingVec.cpp
+</td>
+<td>
+\verbinclude Tutorial_SlicingVec.out
+</td></tr></table>
+
+One can olso take one column over three using an adequate outer-stride or inner-stride depending on the actual storage order:
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_SlicingCol.cpp
+</td>
+<td>
+\verbinclude Tutorial_SlicingCol.out
+</td></tr></table>
+
+*/
+
+}

Index: 3rd_party/eigen/doc/TutorialSparse.dox
==================================================================
--- 3rd_party/eigen/doc/TutorialSparse.dox
+++ 3rd_party/eigen/doc/TutorialSparse.dox
@@ -81,11 +81,11 @@
 There is no notion of compressed/uncompressed mode for a SparseVector.
 
 
 \section TutorialSparseExample First example
 
-Before describing each individual class, let's start with the following typical example: solving the Laplace equation \f$ \nabla u = 0 \f$ on a regular 2D grid using a finite difference scheme and Dirichlet boundary conditions.
+Before describing each individual class, let's start with the following typical example: solving the Laplace equation \f$ \Delta u = 0 \f$ on a regular 2D grid using a finite difference scheme and Dirichlet boundary conditions.
 Such problem can be mathematically expressed as a linear problem of the form \f$ Ax=b \f$ where \f$ x \f$ is the vector of \c m unknowns (in our case, the values of the pixels), \f$ b \f$ is the right hand side vector resulting from the boundary conditions, and \f$ A \f$ is an \f$ m \times m \f$ matrix containing only a few non-zero elements resulting from the discretization of the Laplacian operator.
 
 <table class="manual">
 <tr><td>
 \include Tutorial_sparse_example.cpp
@@ -239,31 +239,35 @@
 %Sparse expressions support most of the unary and binary coefficient wise operations:
 \code
 sm1.real()   sm1.imag()   -sm1                    0.5*sm1
 sm1+sm2      sm1-sm2      sm1.cwiseProduct(sm2)
 \endcode
-However, a strong restriction is that the storage orders must match. For instance, in the following example:
+However, <strong>a strong restriction is that the storage orders must match</strong>. For instance, in the following example:
 \code
 sm4 = sm1 + sm2 + sm3;
 \endcode
-sm1, sm2, and sm3 must all be row-major or all column major.
+sm1, sm2, and sm3 must all be row-major or all column-major.
 On the other hand, there is no restriction on the target matrix sm4.
 For instance, this means that for computing \f$ A^T + A \f$, the matrix \f$ A^T \f$ must be evaluated into a temporary matrix of compatible storage order:
 \code
 SparseMatrix<double> A, B;
 B = SparseMatrix<double>(A.transpose()) + A;
 \endcode
 
-Some binary coefficient-wise operators can also mix sparse and dense expressions:
+Binary coefficient wise operators can also mix sparse and dense expressions:
 \code
 sm2 = sm1.cwiseProduct(dm1);
-dm1 += sm1;
+dm2 = sm1 + dm1;
+dm2 = dm1 - sm1;
+\endcode
+Performance-wise, the adding/subtracting sparse and dense matrices is better performed in two steps. For instance, instead of doing <tt>dm2 = sm1 + dm1</tt>, better write:
+\code
+dm2 = dm1;
+dm2 += sm1;
 \endcode
+This version has the advantage to fully exploit the higher performance of dense storage (no indirection, SIMD, etc.), and to pay the cost of slow sparse evaluation on the few non-zeros of the sparse matrix only.
 
-However, it is not yet possible to add a sparse and a dense matrix as in <tt>dm2 = sm1 + dm1</tt>.
-Please write this as the equivalent <tt>dm2 = dm1; dm2 += sm1</tt> (we plan to lift this restriction
-in the next release of %Eigen).
 
 %Sparse expressions also support transposition:
 \code
 sm1 = sm2.transpose();
 sm1 = sm2.adjoint();
@@ -305,10 +309,30 @@
 sm2 = sm1 * P.inverse();
 sm2 = sm1.transpose() * P;
     \endcode
 
 
+\subsection TutorialSparse_SubMatrices Block operations
+
+Regarding read-access, sparse matrices expose the same API than for dense matrices to access to sub-matrices such as blocks, columns, and rows. See \ref TutorialBlockOperations for a detailed introduction.
+However, for performance reasons, writing to a sub-sparse-matrix is much more limited, and currently only contiguous sets of columns (resp. rows) of a column-major (resp. row-major) SparseMatrix are writable. Moreover, this information has to be known at compile-time, leaving out methods such as <tt>block(...)</tt> and <tt>corner*(...)</tt>. The available API for write-access to a SparseMatrix are summarized below:
+\code
+SparseMatrix<double,ColMajor> sm1;
+sm1.col(j) = ...;
+sm1.leftCols(ncols) = ...;
+sm1.middleCols(j,ncols) = ...;
+sm1.rightCols(ncols) = ...;
+
+SparseMatrix<double,RowMajor> sm2;
+sm2.row(i) = ...;
+sm2.topRows(nrows) = ...;
+sm2.middleRows(i,nrows) = ...;
+sm2.bottomRows(nrows) = ...;
+\endcode
+
+In addition, sparse matrices expose the SparseMatrixBase::innerVector() and SparseMatrixBase::innerVectors() methods, which are aliases to the col/middleCols methods for a column-major storage, and to the row/middleRows methods for a row-major storage.
+
 \subsection TutorialSparse_TriangularSelfadjoint Triangular and selfadjoint views
 
 Just as with dense matrices, the triangularView() function can be used to address a triangular part of the matrix, and perform triangular solves with a dense right hand side:
 \code
 dm2 = sm1.triangularView<Lower>(dm1);

Index: 3rd_party/eigen/doc/UnalignedArrayAssert.dox
==================================================================
--- 3rd_party/eigen/doc/UnalignedArrayAssert.dox
+++ 3rd_party/eigen/doc/UnalignedArrayAssert.dox
@@ -5,12 +5,12 @@
 Hello! You are seeing this webpage because your program terminated on an assertion failure like this one:
 <pre>
 my_program: path/to/eigen/Eigen/src/Core/DenseStorage.h:44:
 Eigen::internal::matrix_array<T, Size, MatrixOptions, Align>::internal::matrix_array()
 [with T = double, int Size = 2, int MatrixOptions = 2, bool Align = true]:
-Assertion `(reinterpret_cast<size_t>(array) & 0xf) == 0 && "this assertion
-is explained here: http://eigen.tuxfamily.org/dox/UnalignedArrayAssert.html
+Assertion `(reinterpret_cast<size_t>(array) & (sizemask)) == 0 && "this assertion
+is explained here: http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html
 **** READ THIS WEB PAGE !!! ****"' failed.
 </pre>
 
 There are 4 known causes for this issue. Please read on to understand them and learn how to fix them.
 
@@ -44,13 +44,13 @@
 
 then you need to read this separate page: \ref TopicStructHavingEigenMembers "Structures Having Eigen Members".
 
 Note that here, Eigen::Vector2d is only used as an example, more generally the issue arises for all \ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen types".
 
-\section c2 Cause 2: STL Containers
+\section c2 Cause 2: STL Containers or manual memory allocation
 
-If you use STL Containers such as std::vector, std::map, ..., with Eigen objects, or with classes containing Eigen objects, like this,
+If you use STL Containers such as std::vector, std::map, ..., with %Eigen objects, or with classes containing %Eigen objects, like this,
 
 \code
 std::vector<Eigen::Matrix2f> my_vector;
 struct my_class { ... Eigen::Matrix2f m; ... };
 std::map<int, my_class> my_map;
@@ -57,10 +57,12 @@
 \endcode
 
 then you need to read this separate page: \ref TopicStlContainers "Using STL Containers with Eigen".
 
 Note that here, Eigen::Matrix2f is only used as an example, more generally the issue arises for all \ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen types" and \ref TopicStructHavingEigenMembers "structures having such Eigen objects as member".
+
+The same issue will be exhibited by any classes/functions by-passing operator new to allocate memory, that is, by performing custom memory allocation followed by calls to the placement new operator. This is for instance typically the case of \c std::make_shared or \c std::allocate_shared for which is the solution is to use an \ref aligned_allocator "aligned allocator" as detailed in the \ref TopicStlContainers "solution for STL containers".
 
 \section c3 Cause 3: Passing Eigen objects by value
 
 If some function in your code is getting an Eigen object passed by value, like this,
 
@@ -88,27 +90,31 @@
 
 Note that here, Eigen::Quaternionf is only used as an example, more generally the issue arises for all \ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen types".
 
 \section explanation General explanation of this assertion
 
-\ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen objects" must absolutely be created at 16-byte-aligned locations, otherwise SIMD instructions adressing them will crash.
+\ref TopicFixedSizeVectorizable "fixed-size vectorizable Eigen objects" must absolutely be created at 16-byte-aligned locations, otherwise SIMD instructions addressing them will crash.
 
 Eigen normally takes care of these alignment issues for you, by setting an alignment attribute on them and by overloading their "operator new".
 
 However there are a few corner cases where these alignment settings get overridden: they are the possible causes for this assertion.
 
-\section getrid I don't care about vectorization, how do I get rid of that stuff?
+\section getrid I don't care about optimal vectorization, how do I get rid of that stuff?
 
-Two possibilities:
+Three possibilities:
 <ul>
-  <li>Define EIGEN_DONT_ALIGN_STATICALLY. That disables all 128-bit static alignment code, while keeping 128-bit heap alignment. This has the effect of
-      disabling vectorization for fixed-size objects (like Matrix4d) while keeping vectorization of dynamic-size objects
-      (like MatrixXd). But do note that this breaks ABI compatibility with the default behavior of 128-bit static alignment.</li>
-  <li>Or define both EIGEN_DONT_VECTORIZE and EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT. This keeps the
-      128-bit alignment code and thus preserves ABI compatibility, but completely disables vectorization.</li>
+  <li>Use the \c DontAlign option to Matrix, Array, Quaternion, etc. objects that gives you trouble. This way Eigen won't try to align them, and thus won"t assume any special alignment. On the down side, you will pay the cost of unaligned loads/stores for them, but on modern CPUs, the overhead is either null or marginal. See \link StructHavingEigenMembers_othersolutions here \endlink for an example.</li>
+  <li>Define \link TopicPreprocessorDirectivesPerformance EIGEN_DONT_ALIGN_STATICALLY \endlink. That disables all 16-byte (and above) static alignment code, while keeping 16-byte (or above) heap alignment. This has the effect of
+      vectorizing fixed-size objects (like Matrix4d) through unaligned stores (as controlled by \link TopicPreprocessorDirectivesPerformance EIGEN_UNALIGNED_VECTORIZE \endlink), while keeping unchanged the vectorization of dynamic-size objects
+      (like MatrixXd). But do note that this breaks ABI compatibility with the default behavior of static alignment.</li>
+  <li>Or define both \link TopicPreprocessorDirectivesPerformance  EIGEN_DONT_VECTORIZE \endlink and EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT. This keeps the
+      16-byte alignment code and thus preserves ABI compatibility, but completely disables vectorization.</li>
 </ul>
 
-For more information, see <a href="http://eigen.tuxfamily.org/index.php?title=FAQ#I_disabled_vectorization.2C_but_I.27m_still_getting_annoyed_about_alignment_issues.21">this FAQ</a>.
+If you want to know why defining EIGEN_DONT_VECTORIZE does not by itself disable 16-byte alignment and the assertion, here's the explanation:
+
+It doesn't disable the assertion, because otherwise code that runs fine without vectorization would suddenly crash when enabling vectorization.
+It doesn't disable 16-byte alignment, because that would mean that vectorized and non-vectorized code are not mutually ABI-compatible. This ABI compatibility is very important, even for people who develop only an in-house application, as for instance one may want to have in the same application a vectorized path and a non-vectorized path.
 
 */
 
 }

ADDED   3rd_party/eigen/doc/UsingBlasLapackBackends.dox
Index: 3rd_party/eigen/doc/UsingBlasLapackBackends.dox
==================================================================
--- 3rd_party/eigen/doc/UsingBlasLapackBackends.dox
+++ 3rd_party/eigen/doc/UsingBlasLapackBackends.dox
@@ -0,0 +1,133 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+ Copyright (C) 2011-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Documentation on the use of BLAS/LAPACK libraries through Eigen
+ ********************************************************************************
+*/
+
+namespace Eigen {
+
+/** \page TopicUsingBlasLapack Using BLAS/LAPACK from %Eigen
+
+
+Since %Eigen version 3.3 and later, any F77 compatible BLAS or LAPACK libraries can be used as backends for dense matrix products and dense matrix decompositions.
+For instance, one can use <a href="http://eigen.tuxfamily.org/Counter/redirect_to_mkl.php">Intel® MKL</a>, Apple's Accelerate framework on OSX, <a href="http://www.openblas.net/">OpenBLAS</a>, <a href="http://www.netlib.org/lapack">Netlib LAPACK</a>, etc.
+
+Do not miss this \link TopicUsingIntelMKL page \endlink for further discussions on the specific use of Intel® MKL (also includes VML, PARDISO, etc.)
+
+In order to use an external BLAS and/or LAPACK library, you must link you own application to the respective libraries and their dependencies.
+For LAPACK, you must also link to the standard <a href="http://www.netlib.org/lapack/lapacke.html">Lapacke</a> library, which is used as a convenient think layer between %Eigen's C++ code and LAPACK F77 interface. Then you must activate their usage by defining one or multiple of the following macros (\b before including any %Eigen's header):
+
+\note For Mac users, in order to use the lapack version shipped with the Accelerate framework, you also need the lapacke library.
+Using <a href="https://www.macports.org/">MacPorts</a>, this is as easy as:
+\code
+sudo port install lapack
+\endcode
+and then use the following link flags: \c -framework \c Accelerate \c /opt/local/lib/lapack/liblapacke.dylib
+
+<table class="manual">
+<tr><td>\c EIGEN_USE_BLAS </td><td>Enables the use of external BLAS level 2 and 3 routines (compatible with any F77 BLAS interface)</td></tr>
+<tr class="alt"><td>\c EIGEN_USE_LAPACKE </td><td>Enables the use of external Lapack routines via the <a href="http://www.netlib.org/lapack/lapacke.html">Lapacke</a> C interface to Lapack (compatible with any F77 LAPACK interface)</td></tr>
+<tr><td>\c EIGEN_USE_LAPACKE_STRICT </td><td>Same as \c EIGEN_USE_LAPACKE but algorithms of lower numerical robustness are disabled. \n This currently concerns only JacobiSVD which otherwise would be replaced by \c gesvd that is less robust than Jacobi rotations.</td></tr>
+</table>
+
+When doing so, a number of %Eigen's algorithms are silently substituted with calls to BLAS or LAPACK routines.
+These substitutions apply only for \b Dynamic \b or \b large enough objects with one of the following four standard scalar types: \c float, \c double, \c complex<float>, and \c complex<double>.
+Operations on other scalar types or mixing reals and complexes will continue to use the built-in algorithms.
+
+The breadth of %Eigen functionality that can be substituted is listed in the table below.
+<table class="manual">
+<tr><th>Functional domain</th><th>Code example</th><th>BLAS/LAPACK routines</th></tr>
+<tr><td>Matrix-matrix operations \n \c EIGEN_USE_BLAS </td><td>\code
+m1*m2.transpose();
+m1.selfadjointView<Lower>()*m2;
+m1*m2.triangularView<Upper>();
+m1.selfadjointView<Lower>().rankUpdate(m2,1.0);
+\endcode</td><td>\code
+?gemm
+?symm/?hemm
+?trmm
+dsyrk/ssyrk
+\endcode</td></tr>
+<tr class="alt"><td>Matrix-vector operations \n \c EIGEN_USE_BLAS </td><td>\code
+m1.adjoint()*b;
+m1.selfadjointView<Lower>()*b;
+m1.triangularView<Upper>()*b;
+\endcode</td><td>\code
+?gemv
+?symv/?hemv
+?trmv
+\endcode</td></tr>
+<tr><td>LU decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
+v1 = m1.lu().solve(v2);
+\endcode</td><td>\code
+?getrf
+\endcode</td></tr>
+<tr class="alt"><td>Cholesky decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
+v1 = m2.selfadjointView<Upper>().llt().solve(v2);
+\endcode</td><td>\code
+?potrf
+\endcode</td></tr>
+<tr><td>QR decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
+m1.householderQr();
+m1.colPivHouseholderQr();
+\endcode</td><td>\code
+?geqrf
+?geqp3
+\endcode</td></tr>
+<tr class="alt"><td>Singular value decomposition \n \c EIGEN_USE_LAPACKE </td><td>\code
+JacobiSVD<MatrixXd> svd;
+svd.compute(m1, ComputeThinV);
+\endcode</td><td>\code
+?gesvd
+\endcode</td></tr>
+<tr><td>Eigen-value decompositions \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
+EigenSolver<MatrixXd> es(m1);
+ComplexEigenSolver<MatrixXcd> ces(m1);
+SelfAdjointEigenSolver<MatrixXd> saes(m1+m1.transpose());
+GeneralizedSelfAdjointEigenSolver<MatrixXd>
+    gsaes(m1+m1.transpose(),m2+m2.transpose());
+\endcode</td><td>\code
+?gees
+?gees
+?syev/?heev
+?syev/?heev,
+?potrf
+\endcode</td></tr>
+<tr class="alt"><td>Schur decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
+RealSchur<MatrixXd> schurR(m1);
+ComplexSchur<MatrixXcd> schurC(m1);
+\endcode</td><td>\code
+?gees
+\endcode</td></tr>
+</table>
+In the examples, m1 and m2 are dense matrices and v1 and v2 are dense vectors.
+
+*/
+
+}

Index: 3rd_party/eigen/doc/UsingIntelMKL.dox
==================================================================
--- 3rd_party/eigen/doc/UsingIntelMKL.dox
+++ 3rd_party/eigen/doc/UsingIntelMKL.dox
@@ -30,110 +30,49 @@
  ********************************************************************************
 */
 
 namespace Eigen {
 
-/** \page TopicUsingIntelMKL Using Intel® Math Kernel Library from Eigen
+/** \page TopicUsingIntelMKL Using Intel® MKL from %Eigen
 
-\section TopicUsingIntelMKL_Intro Eigen and Intel® Math Kernel Library (Intel® MKL)
+<!-- \section TopicUsingIntelMKL_Intro Eigen and Intel® Math Kernel Library (Intel® MKL) -->
 
-Since Eigen version 3.1 and later, users can benefit from built-in Intel MKL optimizations with an installed copy of Intel MKL 10.3 (or later).
+Since %Eigen version 3.1 and later, users can benefit from built-in Intel® Math Kernel Library (MKL) optimizations with an installed copy of Intel MKL 10.3 (or later).
+
 <a href="http://eigen.tuxfamily.org/Counter/redirect_to_mkl.php"> Intel MKL </a> provides highly optimized multi-threaded mathematical routines for x86-compatible architectures.
 Intel MKL is available on Linux, Mac and Windows for both Intel64 and IA32 architectures.
 
-\warning Be aware that Intel® MKL is a proprietary software. It is the responsibility of the users to buy MKL licenses for their products. Moreover, the license of the user product has to allow linking to proprietary software that excludes any unmodified versions of the GPL.
+\note
+Intel® MKL is a proprietary software and it is the responsibility of users to buy or register for community (free) Intel MKL licenses for their products. Moreover, the license of the user product has to allow linking to proprietary software that excludes any unmodified versions of the GPL.
 
-Using Intel MKL through Eigen is easy:
--# define the \c EIGEN_USE_MKL_ALL macro before including any Eigen's header
+Using Intel MKL through %Eigen is easy:
+-# define the \c EIGEN_USE_MKL_ALL macro before including any %Eigen's header
 -# link your program to MKL libraries (see the <a href="http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor/">MKL linking advisor</a>)
 -# on a 64bits system, you must use the LP64 interface (not the ILP64 one)
 
-When doing so, a number of Eigen's algorithms are silently substituted with calls to Intel MKL routines.
+When doing so, a number of %Eigen's algorithms are silently substituted with calls to Intel MKL routines.
 These substitutions apply only for \b Dynamic \b or \b large enough objects with one of the following four standard scalar types: \c float, \c double, \c complex<float>, and \c complex<double>.
 Operations on other scalar types or mixing reals and complexes will continue to use the built-in algorithms.
 
-In addition you can coarsely select choose which parts will be substituted by defining one or multiple of the following macros:
+In addition you can choose which parts will be substituted by defining one or multiple of the following macros:
 
 <table class="manual">
-<tr><td>\c EIGEN_USE_BLAS </td><td>Enables the use of external BLAS level 2 and 3 routines (currently works with Intel MKL only)</td></tr>
-<tr class="alt"><td>\c EIGEN_USE_LAPACKE </td><td>Enables the use of external Lapack routines via the <a href="http://www.netlib.org/lapack/lapacke.html">Intel Lapacke</a> C interface to Lapack (currently works with Intel MKL only)</td></tr>
-<tr><td>\c EIGEN_USE_LAPACKE_STRICT </td><td>Same as \c EIGEN_USE_LAPACKE but algorithm of lower robustness are disabled. This currently concerns only JacobiSVD which otherwise would be replaced by \c gesvd that is less robust than Jacobi rotations.</td></tr>
+<tr><td>\c EIGEN_USE_BLAS </td><td>Enables the use of external BLAS level 2 and 3 routines</td></tr>
+<tr class="alt"><td>\c EIGEN_USE_LAPACKE </td><td>Enables the use of external Lapack routines via the <a href="http://www.netlib.org/lapack/lapacke.html">Lapacke</a> C interface to Lapack</td></tr>
+<tr><td>\c EIGEN_USE_LAPACKE_STRICT </td><td>Same as \c EIGEN_USE_LAPACKE but algorithm of lower robustness are disabled. \n This currently concerns only JacobiSVD which otherwise would be replaced by \c gesvd that is less robust than Jacobi rotations.</td></tr>
 <tr class="alt"><td>\c EIGEN_USE_MKL_VML </td><td>Enables the use of Intel VML (vector operations)</td></tr>
 <tr><td>\c EIGEN_USE_MKL_ALL </td><td>Defines \c EIGEN_USE_BLAS, \c EIGEN_USE_LAPACKE, and \c EIGEN_USE_MKL_VML </td></tr>
 </table>
+
+Note that the BLAS and LAPACKE backends can be enabled for any F77 compatible BLAS and LAPACK libraries. See this \link TopicUsingBlasLapack page \endlink for the details.
 
 Finally, the PARDISO sparse solver shipped with Intel MKL can be used through the \ref PardisoLU, \ref PardisoLLT and \ref PardisoLDLT classes of the \ref PardisoSupport_Module.
 
-
-\section TopicUsingIntelMKL_SupportedFeatures List of supported features
-
-The breadth of Eigen functionality covered by Intel MKL is listed in the table below.
+The following table summarizes the list of functions covered by \c EIGEN_USE_MKL_VML:
 <table class="manual">
-<tr><th>Functional domain</th><th>Code example</th><th>MKL routines</th></tr>
-<tr><td>Matrix-matrix operations \n \c EIGEN_USE_BLAS </td><td>\code
-m1*m2.transpose();
-m1.selfadjointView<Lower>()*m2;
-m1*m2.triangularView<Upper>();
-m1.selfadjointView<Lower>().rankUpdate(m2,1.0);
-\endcode</td><td>\code
-?gemm
-?symm/?hemm
-?trmm
-dsyrk/ssyrk
-\endcode</td></tr>
-<tr class="alt"><td>Matrix-vector operations \n \c EIGEN_USE_BLAS </td><td>\code
-m1.adjoint()*b;
-m1.selfadjointView<Lower>()*b;
-m1.triangularView<Upper>()*b;
-\endcode</td><td>\code
-?gemv
-?symv/?hemv
-?trmv
-\endcode</td></tr>
-<tr><td>LU decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
-v1 = m1.lu().solve(v2);
-\endcode</td><td>\code
-?getrf
-\endcode</td></tr>
-<tr class="alt"><td>Cholesky decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
-v1 = m2.selfadjointView<Upper>().llt().solve(v2);
-\endcode</td><td>\code
-?potrf
-\endcode</td></tr>
-<tr><td>QR decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
-m1.householderQr();
-m1.colPivHouseholderQr();
-\endcode</td><td>\code
-?geqrf
-?geqp3
-\endcode</td></tr>
-<tr class="alt"><td>Singular value decomposition \n \c EIGEN_USE_LAPACKE </td><td>\code
-JacobiSVD<MatrixXd> svd;
-svd.compute(m1, ComputeThinV);
-\endcode</td><td>\code
-?gesvd
-\endcode</td></tr>
-<tr><td>Eigen-value decompositions \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
-EigenSolver<MatrixXd> es(m1);
-ComplexEigenSolver<MatrixXcd> ces(m1);
-SelfAdjointEigenSolver<MatrixXd> saes(m1+m1.transpose());
-GeneralizedSelfAdjointEigenSolver<MatrixXd>
-    gsaes(m1+m1.transpose(),m2+m2.transpose());
-\endcode</td><td>\code
-?gees
-?gees
-?syev/?heev
-?syev/?heev,
-?potrf
-\endcode</td></tr>
-<tr class="alt"><td>Schur decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
-RealSchur<MatrixXd> schurR(m1);
-ComplexSchur<MatrixXcd> schurC(m1);
-\endcode</td><td>\code
-?gees
-\endcode</td></tr>
-<tr><td>Vector Math \n \c EIGEN_USE_MKL_VML </td><td>\code
+<tr><th>Code example</th><th>MKL routines</th></tr>
+<tr><td>\code
 v2=v1.array().sin();
 v2=v1.array().asin();
 v2=v1.array().cos();
 v2=v1.array().acos();
 v2=v1.array().tan();
@@ -153,11 +92,11 @@
 v?Sqrt
 v?Sqr
 v?Powx
 \endcode</td></tr>
 </table>
-In the examples, m1 and m2 are dense matrices and v1 and v2 are dense vectors.
+In the examples, v1 and v2 are dense vectors.
 
 
 \section TopicUsingIntelMKL_Links Links
 - Intel MKL can be purchased and downloaded <a href="http://eigen.tuxfamily.org/Counter/redirect_to_mkl.php">here</a>.
 - Intel MKL is also bundled with <a href="http://software.intel.com/en-us/articles/intel-composer-xe/">Intel Composer XE</a>.

ADDED   3rd_party/eigen/doc/UsingNVCC.dox
Index: 3rd_party/eigen/doc/UsingNVCC.dox
==================================================================
--- 3rd_party/eigen/doc/UsingNVCC.dox
+++ 3rd_party/eigen/doc/UsingNVCC.dox
@@ -0,0 +1,32 @@
+
+namespace Eigen {
+
+/** \page TopicCUDA Using Eigen in CUDA kernels
+
+\b Disclaimer: this page is about an \b experimental feature in %Eigen.
+
+Staring from CUDA 5.0, the CUDA compiler, \c nvcc, is able to properly parse %Eigen's code (almost).
+A few adaptations of the %Eigen's code already allows to use some parts of %Eigen in your own CUDA kernels.
+To this end you need the devel branch of %Eigen, CUDA 5.0 or greater with GCC.
+
+Known issues:
+
+ - \c nvcc with MS Visual Studio does not work (patch welcome)
+ 
+ - \c nvcc with \c clang does not work (patch welcome)
+ 
+ - \c nvcc 5.5 with gcc-4.7 (or greater) has issues with the standard \c \<limits\> header file. To workaround this, you can add the following before including any other files:
+   \code
+    // workaround issue between gcc >= 4.7 and cuda 5.5
+    #if (defined __GNUC__) && (__GNUC__>4 || __GNUC_MINOR__>=7)
+      #undef _GLIBCXX_ATOMIC_BUILTINS
+      #undef _GLIBCXX_USE_INT128
+    #endif
+   \endcode
+   
+ - On 64bits system Eigen uses \c long \c int as the default type for indexes and sizes. On CUDA device, it would make sense to default to 32 bits \c int.
+   However, to keep host and CUDA code compatible, this cannot be done automatically by %Eigen, and the user is thus required to define \c EIGEN_DEFAULT_DENSE_INDEX_TYPE to \c int throughout his code (or only for CUDA code if there is no interaction between host and CUDA code through %Eigen's object).
+
+*/
+
+}

Index: 3rd_party/eigen/doc/eigendoxy.css
==================================================================
--- 3rd_party/eigen/doc/eigendoxy.css
+++ 3rd_party/eigen/doc/eigendoxy.css
@@ -43,11 +43,11 @@
 
 
 
 /* Common style for all Eigen's tables */
 
-table.example, table.manual, table.manual-vl {
+table.example, table.manual, table.manual-vl, table.manual-hl {
     max-width:100%;
     border-collapse: collapse;
     border-style: solid;
     border-width: 1px;
     border-color: #cccccc;
@@ -56,11 +56,11 @@
     box-shadow: 5px 5px 5px rgba(0, 0, 0, 0.15);
     -moz-box-shadow: 5px 5px 5px rgba(0, 0, 0, 0.15);
     -webkit-box-shadow: 5px 5px 5px rgba(0, 0, 0, 0.15);
 }
 
-table.example th, table.manual th, table.manual-vl th {
+table.example th, table.manual th, table.manual-vl th, table.manual-hl th {
   padding: 0.5em 0.5em 0.5em 0.5em;
   text-align: left;
   padding-right: 1em;
   color: #555555;
   background-color: #F4F4E5;
@@ -68,11 +68,11 @@
   background-image: -webkit-gradient(linear,center top,center bottom,from(#FFFFFF), color-stop(0.3,#FFFFFF), color-stop(0.30,#FFFFFF), color-stop(0.98,#F4F4E5), to(#ECECDE));
   background-image: -moz-linear-gradient(center top, #FFFFFF 0%, #FFFFFF 30%, #F4F4E5 98%, #ECECDE);
   filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#FFFFFF', endColorstr='#F4F4E5');
 }
 
-table.example td, table.manual td, table.manual-vl td {
+table.example td, table.manual td, table.manual-vl td, table.manual-hl td {
   vertical-align:top;
   border-width: 1px;
   border-color: #cccccc;
 }
 
@@ -106,19 +106,19 @@
   vertical-align:top;
 }
 
 /* standard class for the manual */
 
-table.manual, table.manual-vl {
+table.manual, table.manual-vl, table.manual-hl {
     padding: 0.2em 0em 0.5em 0em;
 }
 
-table.manual th, table.manual-vl th {
+table.manual th, table.manual-vl th, table.manual-hl th {
   margin: 0em 0em 0.3em 0em;
 }
 
-table.manual td, table.manual-vl td {
+table.manual td, table.manual-vl td, table.manual-hl td {
   padding: 0.3em 0.5em 0.3em 0.5em;
   vertical-align:top;
   border-width: 1px;
 }
 
@@ -133,10 +133,20 @@
 }
 
 table.manual-vl th.inter {
   border-style: solid solid solid solid;
 }
+
+table.manual-hl td {
+  border-color: #cccccc;
+  border-width: 1px;
+  border-style: solid none solid none;
+}
+
+table td.code {
+  font-family: monospace;
+}
 
 h2 {
   margin-top:2em;
   border-style: none none solid none;
   border-width: 1px;
@@ -163,10 +173,15 @@
 }
 
 div.toc ul {
   margin: 0.2em 0 0.4em 0.5em;
 }
+
+span.cpp11,span.cpp14,span.cpp17 {
+  color: #119911;
+  font-weight: bold;
+}
 
 /**** old Eigen's styles ****/
 
 
 table.tutorial_code td {
@@ -175,12 +190,12 @@
   vertical-align: top;
 }
 
 
 /* Whenever doxygen meets a '\n' or a '<BR/>', it will put 
- * the text containing the characted into a <p class="starttd">.
- * This little hack togehter with table.tutorial_code td.note
+ * the text containing the character into a <p class="starttd">.
+ * This little hack together with table.tutorial_code td.note
  * aims at fixing this issue. */
 table.tutorial_code td.note p.starttd {
   margin: 0px;
   border: none;
   padding: 0px;
@@ -197,15 +212,5 @@
 
 
 td.width20em p.endtd {
   width:  20em;
 }
-
-.bigwarning {
-  font-size:2em;
-  font-weight:bold;
-  margin:1em;
-  padding:1em;
-  color:red;
-  border:solid;
-}
-

Index: 3rd_party/eigen/doc/examples/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/doc/examples/CMakeLists.txt
+++ 3rd_party/eigen/doc/examples/CMakeLists.txt
@@ -12,5 +12,10 @@
     COMMAND ${example}
     ARGS >${CMAKE_CURRENT_BINARY_DIR}/${example}.out
   )
   add_dependencies(all_examples ${example})
 endforeach(example_src)
+
+check_cxx_compiler_flag("-std=c++11" EIGEN_COMPILER_SUPPORT_CPP11)
+if(EIGEN_COMPILER_SUPPORT_CPP11)
+ei_add_target_property(nullary_indexing COMPILE_FLAGS "-std=c++11")
+endif()

ADDED   3rd_party/eigen/doc/examples/CustomizingEigen_Inheritance.cpp
Index: 3rd_party/eigen/doc/examples/CustomizingEigen_Inheritance.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/CustomizingEigen_Inheritance.cpp
+++ 3rd_party/eigen/doc/examples/CustomizingEigen_Inheritance.cpp
@@ -0,0 +1,30 @@
+#include <Eigen/Core>
+#include <iostream>
+
+class MyVectorType : public Eigen::VectorXd
+{
+public:
+    MyVectorType(void):Eigen::VectorXd() {}
+
+    // This constructor allows you to construct MyVectorType from Eigen expressions
+    template<typename OtherDerived>
+    MyVectorType(const Eigen::MatrixBase<OtherDerived>& other)
+        : Eigen::VectorXd(other)
+    { }
+
+    // This method allows you to assign Eigen expressions to MyVectorType
+    template<typename OtherDerived>
+    MyVectorType& operator=(const Eigen::MatrixBase <OtherDerived>& other)
+    {
+        this->Eigen::VectorXd::operator=(other);
+        return *this;
+    }
+};
+
+int main()
+{
+  MyVectorType v = MyVectorType::Ones(4);
+  v(2) += 10;
+  v = 2 * v;
+  std::cout << v.transpose() << std::endl;
+}

ADDED   3rd_party/eigen/doc/examples/Cwise_erf.cpp
Index: 3rd_party/eigen/doc/examples/Cwise_erf.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/Cwise_erf.cpp
+++ 3rd_party/eigen/doc/examples/Cwise_erf.cpp
@@ -0,0 +1,9 @@
+#include <Eigen/Core>
+#include <unsupported/Eigen/SpecialFunctions>
+#include <iostream>
+using namespace Eigen;
+int main()
+{
+  Array4d v(-0.5,2,0,-7);
+  std::cout << v.erf() << std::endl;
+}

ADDED   3rd_party/eigen/doc/examples/Cwise_erfc.cpp
Index: 3rd_party/eigen/doc/examples/Cwise_erfc.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/Cwise_erfc.cpp
+++ 3rd_party/eigen/doc/examples/Cwise_erfc.cpp
@@ -0,0 +1,9 @@
+#include <Eigen/Core>
+#include <unsupported/Eigen/SpecialFunctions>
+#include <iostream>
+using namespace Eigen;
+int main()
+{
+  Array4d v(-0.5,2,0,-7);
+  std::cout << v.erfc() << std::endl;
+}

ADDED   3rd_party/eigen/doc/examples/Cwise_lgamma.cpp
Index: 3rd_party/eigen/doc/examples/Cwise_lgamma.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/Cwise_lgamma.cpp
+++ 3rd_party/eigen/doc/examples/Cwise_lgamma.cpp
@@ -0,0 +1,9 @@
+#include <Eigen/Core>
+#include <unsupported/Eigen/SpecialFunctions>
+#include <iostream>
+using namespace Eigen;
+int main()
+{
+  Array4d v(0.5,10,0,-1);
+  std::cout << v.lgamma() << std::endl;
+}

DELETED 3rd_party/eigen/doc/examples/MatrixBase_cwise_const.cpp
Index: 3rd_party/eigen/doc/examples/MatrixBase_cwise_const.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/MatrixBase_cwise_const.cpp
+++ 3rd_party/eigen/doc/examples/MatrixBase_cwise_const.cpp
@@ -1,18 +0,0 @@
-#define EIGEN2_SUPPORT
-#include <Eigen/Core>
-#include <iostream>
-
-using namespace Eigen;
-using namespace std;
-
-int main()
-{
-  Matrix3i m = Matrix3i::Random();
-  cout << "Here is the matrix m:" << endl << m << endl;
-  Matrix3i n = Matrix3i::Random();
-  cout << "And here is the matrix n:" << endl << n << endl;
-  cout << "The coefficient-wise product of m and n is:" << endl;
-  cout << m.cwise() * n << endl;
-  cout << "Taking the cube of the coefficients of m yields:" << endl;
-  cout << m.cwise().pow(3) << endl;
-}

ADDED   3rd_party/eigen/doc/examples/TutorialInplaceLU.cpp
Index: 3rd_party/eigen/doc/examples/TutorialInplaceLU.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/TutorialInplaceLU.cpp
+++ 3rd_party/eigen/doc/examples/TutorialInplaceLU.cpp
@@ -0,0 +1,61 @@
+#include <iostream>
+struct init {
+  init() { std::cout << "[" << "init" << "]" << std::endl; }
+};
+init init_obj;
+// [init]
+#include <iostream>
+#include <Eigen/Dense>
+
+using namespace std;
+using namespace Eigen;
+
+int main()
+{
+  MatrixXd A(2,2);
+  A << 2, -1, 1, 3;
+  cout << "Here is the input matrix A before decomposition:\n" << A << endl;
+cout << "[init]" << endl;
+
+cout << "[declaration]" << endl;
+  PartialPivLU<Ref<MatrixXd> > lu(A);
+  cout << "Here is the input matrix A after decomposition:\n" << A << endl;
+cout << "[declaration]" << endl;
+
+cout << "[matrixLU]" << endl;
+  cout << "Here is the matrix storing the L and U factors:\n" << lu.matrixLU() << endl;
+cout << "[matrixLU]" << endl;
+
+cout << "[solve]" << endl;
+  MatrixXd A0(2,2); A0 << 2, -1, 1, 3;
+  VectorXd b(2);    b << 1, 2;
+  VectorXd x = lu.solve(b);
+  cout << "Residual: " << (A0 * x - b).norm() << endl;
+cout << "[solve]" << endl;
+
+cout << "[modifyA]" << endl;
+  A << 3, 4, -2, 1;
+  x = lu.solve(b);
+  cout << "Residual: " << (A0 * x - b).norm() << endl;
+cout << "[modifyA]" << endl;
+
+cout << "[recompute]" << endl;
+  A0 = A; // save A
+  lu.compute(A);
+  x = lu.solve(b);
+  cout << "Residual: " << (A0 * x - b).norm() << endl;
+cout << "[recompute]" << endl;
+
+cout << "[recompute_bis0]" << endl;
+  MatrixXd A1(2,2);
+  A1 << 5,-2,3,4;
+  lu.compute(A1);
+  cout << "Here is the input matrix A1 after decomposition:\n" << A1 << endl;
+cout << "[recompute_bis0]" << endl;
+
+cout << "[recompute_bis1]" << endl;
+  x = lu.solve(b);
+  cout << "Residual: " << (A1 * x - b).norm() << endl;
+cout << "[recompute_bis1]" << endl;
+
+}

Index: 3rd_party/eigen/doc/examples/TutorialLinAlgInverseDeterminant.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/TutorialLinAlgInverseDeterminant.cpp
+++ 3rd_party/eigen/doc/examples/TutorialLinAlgInverseDeterminant.cpp

ADDED   3rd_party/eigen/doc/examples/Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.cpp
Index: 3rd_party/eigen/doc/examples/Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.cpp
+++ 3rd_party/eigen/doc/examples/Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.cpp
@@ -0,0 +1,18 @@
+#include <Eigen/Dense>
+#include <iostream>
+
+using namespace Eigen;
+using namespace std;
+
+int main()
+{
+  MatrixXf m(2,2);
+  m << 1,-2,
+       -3,4;
+
+  cout << "1-norm(m)     = " << m.cwiseAbs().colwise().sum().maxCoeff()
+       << " == "             << m.colwise().lpNorm<1>().maxCoeff() << endl;
+
+  cout << "infty-norm(m) = " << m.cwiseAbs().rowwise().sum().maxCoeff()
+       << " == "             << m.rowwise().lpNorm<1>().maxCoeff() << endl;
+}

ADDED   3rd_party/eigen/doc/examples/make_circulant.cpp
Index: 3rd_party/eigen/doc/examples/make_circulant.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/make_circulant.cpp
+++ 3rd_party/eigen/doc/examples/make_circulant.cpp
@@ -0,0 +1,11 @@
+/*
+This program is presented in several fragments in the doc page.
+Every fragment is in its own file; this file simply combines them.
+*/
+
+#include "make_circulant.cpp.preamble"
+#include "make_circulant.cpp.traits"
+#include "make_circulant.cpp.expression"
+#include "make_circulant.cpp.evaluator"
+#include "make_circulant.cpp.entry"
+#include "make_circulant.cpp.main"

ADDED   3rd_party/eigen/doc/examples/make_circulant.cpp.entry
Index: 3rd_party/eigen/doc/examples/make_circulant.cpp.entry
==================================================================
--- 3rd_party/eigen/doc/examples/make_circulant.cpp.entry
+++ 3rd_party/eigen/doc/examples/make_circulant.cpp.entry
@@ -0,0 +1,5 @@
+template <class ArgType>
+Circulant<ArgType> makeCirculant(const Eigen::MatrixBase<ArgType>& arg)
+{
+  return Circulant<ArgType>(arg.derived());
+}

ADDED   3rd_party/eigen/doc/examples/make_circulant.cpp.evaluator
Index: 3rd_party/eigen/doc/examples/make_circulant.cpp.evaluator
==================================================================
--- 3rd_party/eigen/doc/examples/make_circulant.cpp.evaluator
+++ 3rd_party/eigen/doc/examples/make_circulant.cpp.evaluator
@@ -0,0 +1,32 @@
+namespace Eigen {
+  namespace internal {
+    template<typename ArgType>
+    struct evaluator<Circulant<ArgType> >
+      : evaluator_base<Circulant<ArgType> >
+    {
+      typedef Circulant<ArgType> XprType;
+      typedef typename nested_eval<ArgType, XprType::ColsAtCompileTime>::type ArgTypeNested;
+      typedef typename remove_all<ArgTypeNested>::type ArgTypeNestedCleaned;
+      typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+      enum { 
+        CoeffReadCost = evaluator<ArgTypeNestedCleaned>::CoeffReadCost,
+        Flags = Eigen::ColMajor 
+      };
+      
+      evaluator(const XprType& xpr)
+        : m_argImpl(xpr.m_arg), m_rows(xpr.rows())
+      { }
+
+      CoeffReturnType coeff(Index row, Index col) const
+      {
+        Index index = row - col;
+        if (index < 0) index += m_rows;
+        return m_argImpl.coeff(index);
+      }
+
+      evaluator<ArgTypeNestedCleaned> m_argImpl;
+      const Index m_rows;
+    };
+  }
+}

ADDED   3rd_party/eigen/doc/examples/make_circulant.cpp.expression
Index: 3rd_party/eigen/doc/examples/make_circulant.cpp.expression
==================================================================
--- 3rd_party/eigen/doc/examples/make_circulant.cpp.expression
+++ 3rd_party/eigen/doc/examples/make_circulant.cpp.expression
@@ -0,0 +1,20 @@
+template <class ArgType>
+class Circulant : public Eigen::MatrixBase<Circulant<ArgType> >
+{
+public:
+  Circulant(const ArgType& arg)
+    : m_arg(arg)
+  { 
+    EIGEN_STATIC_ASSERT(ArgType::ColsAtCompileTime == 1,
+                        YOU_TRIED_CALLING_A_VECTOR_METHOD_ON_A_MATRIX);
+  }
+
+  typedef typename Eigen::internal::ref_selector<Circulant>::type Nested; 
+
+  typedef Eigen::Index Index;
+  Index rows() const { return m_arg.rows(); }
+  Index cols() const { return m_arg.rows(); }
+
+  typedef typename Eigen::internal::ref_selector<ArgType>::type ArgTypeNested;
+  ArgTypeNested m_arg;
+};

ADDED   3rd_party/eigen/doc/examples/make_circulant.cpp.main
Index: 3rd_party/eigen/doc/examples/make_circulant.cpp.main
==================================================================
--- 3rd_party/eigen/doc/examples/make_circulant.cpp.main
+++ 3rd_party/eigen/doc/examples/make_circulant.cpp.main
@@ -0,0 +1,8 @@
+int main()
+{
+  Eigen::VectorXd vec(4);
+  vec << 1, 2, 4, 8;
+  Eigen::MatrixXd mat;
+  mat = makeCirculant(vec);
+  std::cout << mat << std::endl;
+}

ADDED   3rd_party/eigen/doc/examples/make_circulant.cpp.preamble
Index: 3rd_party/eigen/doc/examples/make_circulant.cpp.preamble
==================================================================
--- 3rd_party/eigen/doc/examples/make_circulant.cpp.preamble
+++ 3rd_party/eigen/doc/examples/make_circulant.cpp.preamble
@@ -0,0 +1,4 @@
+#include <Eigen/Core>
+#include <iostream>
+
+template <class ArgType> class Circulant;

ADDED   3rd_party/eigen/doc/examples/make_circulant.cpp.traits
Index: 3rd_party/eigen/doc/examples/make_circulant.cpp.traits
==================================================================
--- 3rd_party/eigen/doc/examples/make_circulant.cpp.traits
+++ 3rd_party/eigen/doc/examples/make_circulant.cpp.traits
@@ -0,0 +1,19 @@
+namespace Eigen {
+  namespace internal {
+    template <class ArgType>
+    struct traits<Circulant<ArgType> >
+    {
+      typedef Eigen::Dense StorageKind;
+      typedef Eigen::MatrixXpr XprKind;
+      typedef typename ArgType::StorageIndex StorageIndex;
+      typedef typename ArgType::Scalar Scalar;
+      enum { 
+        Flags = Eigen::ColMajor,
+        RowsAtCompileTime = ArgType::RowsAtCompileTime,
+        ColsAtCompileTime = ArgType::RowsAtCompileTime,
+        MaxRowsAtCompileTime = ArgType::MaxRowsAtCompileTime,
+        MaxColsAtCompileTime = ArgType::MaxRowsAtCompileTime
+      };
+    };
+  }
+}

ADDED   3rd_party/eigen/doc/examples/make_circulant2.cpp
Index: 3rd_party/eigen/doc/examples/make_circulant2.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/make_circulant2.cpp
+++ 3rd_party/eigen/doc/examples/make_circulant2.cpp
@@ -0,0 +1,52 @@
+#include <Eigen/Core>
+#include <iostream>
+
+using namespace Eigen;
+
+// [circulant_func]
+template<class ArgType>
+class circulant_functor {
+  const ArgType &m_vec;
+public:
+  circulant_functor(const ArgType& arg) : m_vec(arg) {}
+
+  const typename ArgType::Scalar& operator() (Index row, Index col) const {
+    Index index = row - col;
+    if (index < 0) index += m_vec.size();
+    return m_vec(index);
+  }
+};
+// [circulant_func]
+
+// [square]
+template<class ArgType>
+struct circulant_helper {
+  typedef Matrix<typename ArgType::Scalar,
+                 ArgType::SizeAtCompileTime,
+                 ArgType::SizeAtCompileTime,
+                 ColMajor,
+                 ArgType::MaxSizeAtCompileTime,
+                 ArgType::MaxSizeAtCompileTime> MatrixType;
+};
+// [square]
+
+// [makeCirculant]
+template <class ArgType>
+CwiseNullaryOp<circulant_functor<ArgType>, typename circulant_helper<ArgType>::MatrixType>
+makeCirculant(const Eigen::MatrixBase<ArgType>& arg)
+{
+  typedef typename circulant_helper<ArgType>::MatrixType MatrixType;
+  return MatrixType::NullaryExpr(arg.size(), arg.size(), circulant_functor<ArgType>(arg.derived()));
+}
+// [makeCirculant]
+
+// [main]
+int main()
+{
+  Eigen::VectorXd vec(4);
+  vec << 1, 2, 4, 8;
+  Eigen::MatrixXd mat;
+  mat = makeCirculant(vec);
+  std::cout << mat << std::endl;
+}
+// [main]

ADDED   3rd_party/eigen/doc/examples/matrixfree_cg.cpp
Index: 3rd_party/eigen/doc/examples/matrixfree_cg.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/matrixfree_cg.cpp
+++ 3rd_party/eigen/doc/examples/matrixfree_cg.cpp
@@ -0,0 +1,128 @@
+#include <iostream>
+#include <Eigen/Core>
+#include <Eigen/Dense>
+#include <Eigen/IterativeLinearSolvers>
+#include <unsupported/Eigen/IterativeSolvers>
+
+class MatrixReplacement;
+using Eigen::SparseMatrix;
+
+namespace Eigen {
+namespace internal {
+  // MatrixReplacement looks-like a SparseMatrix, so let's inherits its traits:
+  template<>
+  struct traits<MatrixReplacement> :  public Eigen::internal::traits<Eigen::SparseMatrix<double> >
+  {};
+}
+}
+
+// Example of a matrix-free wrapper from a user type to Eigen's compatible type
+// For the sake of simplicity, this example simply wrap a Eigen::SparseMatrix.
+class MatrixReplacement : public Eigen::EigenBase<MatrixReplacement> {
+public:
+  // Required typedefs, constants, and method:
+  typedef double Scalar;
+  typedef double RealScalar;
+  typedef int StorageIndex;
+  enum {
+    ColsAtCompileTime = Eigen::Dynamic,
+    MaxColsAtCompileTime = Eigen::Dynamic,
+    IsRowMajor = false
+  };
+
+  Index rows() const { return mp_mat->rows(); }
+  Index cols() const { return mp_mat->cols(); }
+
+  template<typename Rhs>
+  Eigen::Product<MatrixReplacement,Rhs,Eigen::AliasFreeProduct> operator*(const Eigen::MatrixBase<Rhs>& x) const {
+    return Eigen::Product<MatrixReplacement,Rhs,Eigen::AliasFreeProduct>(*this, x.derived());
+  }
+
+  // Custom API:
+  MatrixReplacement() : mp_mat(0) {}
+
+  void attachMyMatrix(const SparseMatrix<double> &mat) {
+    mp_mat = &mat;
+  }
+  const SparseMatrix<double> my_matrix() const { return *mp_mat; }
+
+private:
+  const SparseMatrix<double> *mp_mat;
+};
+
+
+// Implementation of MatrixReplacement * Eigen::DenseVector though a specialization of internal::generic_product_impl:
+namespace Eigen {
+namespace internal {
+
+  template<typename Rhs>
+  struct generic_product_impl<MatrixReplacement, Rhs, SparseShape, DenseShape, GemvProduct> // GEMV stands for matrix-vector
+  : generic_product_impl_base<MatrixReplacement,Rhs,generic_product_impl<MatrixReplacement,Rhs> >
+  {
+    typedef typename Product<MatrixReplacement,Rhs>::Scalar Scalar;
+
+    template<typename Dest>
+    static void scaleAndAddTo(Dest& dst, const MatrixReplacement& lhs, const Rhs& rhs, const Scalar& alpha)
+    {
+      // This method should implement "dst += alpha * lhs * rhs" inplace,
+      // however, for iterative solvers, alpha is always equal to 1, so let's not bother about it.
+      assert(alpha==Scalar(1) && "scaling is not implemented");
+
+      // Here we could simply call dst.noalias() += lhs.my_matrix() * rhs,
+      // but let's do something fancier (and less efficient):
+      for(Index i=0; i<lhs.cols(); ++i)
+        dst += rhs(i) * lhs.my_matrix().col(i);
+    }
+  };
+
+}
+}
+
+int main()
+{
+  int n = 10;
+  Eigen::SparseMatrix<double> S = Eigen::MatrixXd::Random(n,n).sparseView(0.5,1);
+  S = S.transpose()*S;
+
+  MatrixReplacement A;
+  A.attachMyMatrix(S);
+
+  Eigen::VectorXd b(n), x;
+  b.setRandom();
+
+  // Solve Ax = b using various iterative solver with matrix-free version:
+  {
+    Eigen::ConjugateGradient<MatrixReplacement, Eigen::Lower|Eigen::Upper, Eigen::IdentityPreconditioner> cg;
+    cg.compute(A);
+    x = cg.solve(b);
+    std::cout << "CG:       #iterations: " << cg.iterations() << ", estimated error: " << cg.error() << std::endl;
+  }
+
+  {
+    Eigen::BiCGSTAB<MatrixReplacement, Eigen::IdentityPreconditioner> bicg;
+    bicg.compute(A);
+    x = bicg.solve(b);
+    std::cout << "BiCGSTAB: #iterations: " << bicg.iterations() << ", estimated error: " << bicg.error() << std::endl;
+  }
+
+  {
+    Eigen::GMRES<MatrixReplacement, Eigen::IdentityPreconditioner> gmres;
+    gmres.compute(A);
+    x = gmres.solve(b);
+    std::cout << "GMRES:    #iterations: " << gmres.iterations() << ", estimated error: " << gmres.error() << std::endl;
+  }
+
+  {
+    Eigen::DGMRES<MatrixReplacement, Eigen::IdentityPreconditioner> gmres;
+    gmres.compute(A);
+    x = gmres.solve(b);
+    std::cout << "DGMRES:   #iterations: " << gmres.iterations() << ", estimated error: " << gmres.error() << std::endl;
+  }
+
+  {
+    Eigen::MINRES<MatrixReplacement, Eigen::Lower|Eigen::Upper, Eigen::IdentityPreconditioner> minres;
+    minres.compute(A);
+    x = minres.solve(b);
+    std::cout << "MINRES:   #iterations: " << minres.iterations() << ", estimated error: " << minres.error() << std::endl;
+  }
+}

ADDED   3rd_party/eigen/doc/examples/nullary_indexing.cpp
Index: 3rd_party/eigen/doc/examples/nullary_indexing.cpp
==================================================================
--- 3rd_party/eigen/doc/examples/nullary_indexing.cpp
+++ 3rd_party/eigen/doc/examples/nullary_indexing.cpp
@@ -0,0 +1,66 @@
+#include <Eigen/Core>
+#include <iostream>
+
+using namespace Eigen;
+
+// [functor]
+template<class ArgType, class RowIndexType, class ColIndexType>
+class indexing_functor {
+  const ArgType &m_arg;
+  const RowIndexType &m_rowIndices;
+  const ColIndexType &m_colIndices;
+public:
+  typedef Matrix<typename ArgType::Scalar,
+                 RowIndexType::SizeAtCompileTime,
+                 ColIndexType::SizeAtCompileTime,
+                 ArgType::Flags&RowMajorBit?RowMajor:ColMajor,
+                 RowIndexType::MaxSizeAtCompileTime,
+                 ColIndexType::MaxSizeAtCompileTime> MatrixType;
+
+  indexing_functor(const ArgType& arg, const RowIndexType& row_indices, const ColIndexType& col_indices)
+    : m_arg(arg), m_rowIndices(row_indices), m_colIndices(col_indices)
+  {}
+
+  const typename ArgType::Scalar& operator() (Index row, Index col) const {
+    return m_arg(m_rowIndices[row], m_colIndices[col]);
+  }
+};
+// [functor]
+
+// [function]
+template <class ArgType, class RowIndexType, class ColIndexType>
+CwiseNullaryOp<indexing_functor<ArgType,RowIndexType,ColIndexType>, typename indexing_functor<ArgType,RowIndexType,ColIndexType>::MatrixType>
+indexing(const Eigen::MatrixBase<ArgType>& arg, const RowIndexType& row_indices, const ColIndexType& col_indices)
+{
+  typedef indexing_functor<ArgType,RowIndexType,ColIndexType> Func;
+  typedef typename Func::MatrixType MatrixType;
+  return MatrixType::NullaryExpr(row_indices.size(), col_indices.size(), Func(arg.derived(), row_indices, col_indices));
+}
+// [function]
+
+
+int main()
+{
+  std::cout << "[main1]\n";
+  Eigen::MatrixXi A = Eigen::MatrixXi::Random(4,4);
+  Array3i ri(1,2,1);
+  ArrayXi ci(6); ci << 3,2,1,0,0,2;
+  Eigen::MatrixXi B = indexing(A, ri, ci);
+  std::cout << "A =" << std::endl;
+  std::cout << A << std::endl << std::endl;
+  std::cout << "A([" << ri.transpose() << "], [" << ci.transpose() << "]) =" << std::endl;
+  std::cout << B << std::endl;
+  std::cout << "[main1]\n";
+
+  std::cout << "[main2]\n";
+  B =  indexing(A, ri+1, ci);
+  std::cout << "A(ri+1,ci) =" << std::endl;
+  std::cout << B << std::endl << std::endl;
+#if __cplusplus >= 201103L
+  B =  indexing(A, ArrayXi::LinSpaced(13,0,12).unaryExpr([](int x){return x%4;}), ArrayXi::LinSpaced(4,0,3));
+  std::cout << "A(ArrayXi::LinSpaced(13,0,12).unaryExpr([](int x){return x%4;}), ArrayXi::LinSpaced(4,0,3)) =" << std::endl;
+  std::cout << B << std::endl << std::endl;
+#endif
+  std::cout << "[main2]\n";
+}
+

ADDED   3rd_party/eigen/doc/ftv2node.png
Index: 3rd_party/eigen/doc/ftv2node.png
==================================================================
--- 3rd_party/eigen/doc/ftv2node.png
+++ 3rd_party/eigen/doc/ftv2node.png
cannot compute difference between binary files

ADDED   3rd_party/eigen/doc/ftv2pnode.png
Index: 3rd_party/eigen/doc/ftv2pnode.png
==================================================================
--- 3rd_party/eigen/doc/ftv2pnode.png
+++ 3rd_party/eigen/doc/ftv2pnode.png
cannot compute difference between binary files

ADDED   3rd_party/eigen/doc/snippets/BiCGSTAB_simple.cpp
Index: 3rd_party/eigen/doc/snippets/BiCGSTAB_simple.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/BiCGSTAB_simple.cpp
+++ 3rd_party/eigen/doc/snippets/BiCGSTAB_simple.cpp
@@ -0,0 +1,11 @@
+  int n = 10000;
+  VectorXd x(n), b(n);
+  SparseMatrix<double> A(n,n);
+  /* ... fill A and b ... */ 
+  BiCGSTAB<SparseMatrix<double> > solver;
+  solver.compute(A);
+  x = solver.solve(b);
+  std::cout << "#iterations:     " << solver.iterations() << std::endl;
+  std::cout << "estimated error: " << solver.error()      << std::endl;
+  /* ... update b ... */
+  x = solver.solve(b); // solve again

ADDED   3rd_party/eigen/doc/snippets/BiCGSTAB_step_by_step.cpp
Index: 3rd_party/eigen/doc/snippets/BiCGSTAB_step_by_step.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/BiCGSTAB_step_by_step.cpp
+++ 3rd_party/eigen/doc/snippets/BiCGSTAB_step_by_step.cpp
@@ -0,0 +1,14 @@
+  int n = 10000;
+  VectorXd x(n), b(n);
+  SparseMatrix<double> A(n,n);
+  /* ... fill A and b ... */ 
+  BiCGSTAB<SparseMatrix<double> > solver(A);
+  // start from a random solution
+  x = VectorXd::Random(n);
+  solver.setMaxIterations(1);
+  int i = 0;
+  do {
+    x = solver.solveWithGuess(b,x);
+    std::cout << i << " : " << solver.error() << std::endl;
+    ++i;
+  } while (solver.info()!=Success && i<100);

Index: 3rd_party/eigen/doc/snippets/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/doc/snippets/CMakeLists.txt
+++ 3rd_party/eigen/doc/snippets/CMakeLists.txt
@@ -22,7 +22,5 @@
   )
   add_dependencies(all_snippets ${compile_snippet_target})
   set_source_files_properties(${CMAKE_CURRENT_BINARY_DIR}/${compile_snippet_src}
                               PROPERTIES OBJECT_DEPENDS ${snippet_src})
 endforeach(snippet_src)
-
-ei_add_target_property(compile_tut_arithmetic_transpose_aliasing COMPILE_FLAGS -DEIGEN_NO_DEBUG)

ADDED   3rd_party/eigen/doc/snippets/Cwise_arg.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_arg.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_arg.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_arg.cpp
@@ -0,0 +1,3 @@
+ArrayXcf v = ArrayXcf::Random(3);
+cout << v << endl << endl;
+cout << arg(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_array_power_array.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_array_power_array.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_array_power_array.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_array_power_array.cpp
@@ -0,0 +1,4 @@
+Array<double,1,3> x(8,25,3),
+                  e(1./3.,0.5,2.);
+cout << "[" << x << "]^[" << e << "] = " << x.pow(e) << endl; // using ArrayBase::pow
+cout << "[" << x << "]^[" << e << "] = " << pow(x,e) << endl; // using Eigen::pow

ADDED   3rd_party/eigen/doc/snippets/Cwise_atan.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_atan.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_atan.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_atan.cpp
@@ -0,0 +1,2 @@
+ArrayXd v = ArrayXd::LinSpaced(5,0,1);
+cout << v.atan() << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_boolean_not.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_boolean_not.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_boolean_not.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_boolean_not.cpp
@@ -0,0 +1,5 @@
+Array3d v(1,2,3);
+v(1) *= 0.0/0.0;
+v(2) /= 0.0;
+cout << v << endl << endl;
+cout << !isfinite(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_boolean_xor.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_boolean_xor.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_boolean_xor.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_boolean_xor.cpp
@@ -0,0 +1,2 @@
+Array3d v(-1,2,1), w(-3,2,3);
+cout << ((v<w) ^ (v<0)) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_ceil.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_ceil.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_ceil.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_ceil.cpp
@@ -0,0 +1,3 @@
+ArrayXd v = ArrayXd::LinSpaced(7,-2,2);
+cout << v << endl << endl;
+cout << ceil(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_cosh.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_cosh.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_cosh.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_cosh.cpp
@@ -0,0 +1,2 @@
+ArrayXd v = ArrayXd::LinSpaced(5,0,1);
+cout << cosh(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_floor.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_floor.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_floor.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_floor.cpp
@@ -0,0 +1,3 @@
+ArrayXd v = ArrayXd::LinSpaced(7,-2,2);
+cout << v << endl << endl;
+cout << floor(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_isFinite.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_isFinite.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_isFinite.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_isFinite.cpp
@@ -0,0 +1,5 @@
+Array3d v(1,2,3);
+v(1) *= 0.0/0.0;
+v(2) /= 0.0;
+cout << v << endl << endl;
+cout << isfinite(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_isInf.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_isInf.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_isInf.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_isInf.cpp
@@ -0,0 +1,5 @@
+Array3d v(1,2,3);
+v(1) *= 0.0/0.0;
+v(2) /= 0.0;
+cout << v << endl << endl;
+cout << isinf(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_isNaN.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_isNaN.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_isNaN.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_isNaN.cpp
@@ -0,0 +1,5 @@
+Array3d v(1,2,3);
+v(1) *= 0.0/0.0;
+v(2) /= 0.0;
+cout << v << endl << endl;
+cout << isnan(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_log10.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_log10.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_log10.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_log10.cpp
@@ -0,0 +1,2 @@
+Array4d v(-1,0,1,2);
+cout << log10(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_round.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_round.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_round.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_round.cpp
@@ -0,0 +1,3 @@
+ArrayXd v = ArrayXd::LinSpaced(7,-2,2);
+cout << v << endl << endl;
+cout << round(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_scalar_power_array.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_scalar_power_array.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_scalar_power_array.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_scalar_power_array.cpp
@@ -0,0 +1,2 @@
+Array<double,1,3> e(2,-3,1./3.);
+cout << "10^[" << e << "] = " << pow(10,e) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_sign.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_sign.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_sign.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_sign.cpp
@@ -0,0 +1,2 @@
+Array3d v(-3,5,0);
+cout << v.sign() << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_sinh.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_sinh.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_sinh.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_sinh.cpp
@@ -0,0 +1,2 @@
+ArrayXd v = ArrayXd::LinSpaced(5,0,1);
+cout << sinh(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/Cwise_tanh.cpp
Index: 3rd_party/eigen/doc/snippets/Cwise_tanh.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Cwise_tanh.cpp
+++ 3rd_party/eigen/doc/snippets/Cwise_tanh.cpp
@@ -0,0 +1,2 @@
+ArrayXd v = ArrayXd::LinSpaced(5,0,1);
+cout << tanh(v) << endl;

ADDED   3rd_party/eigen/doc/snippets/DenseBase_LinSpacedInt.cpp
Index: 3rd_party/eigen/doc/snippets/DenseBase_LinSpacedInt.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/DenseBase_LinSpacedInt.cpp
+++ 3rd_party/eigen/doc/snippets/DenseBase_LinSpacedInt.cpp
@@ -0,0 +1,8 @@
+cout << "Even spacing inputs:" << endl;
+cout << VectorXi::LinSpaced(8,1,4).transpose() << endl;
+cout << VectorXi::LinSpaced(8,1,8).transpose() << endl;
+cout << VectorXi::LinSpaced(8,1,15).transpose() << endl;
+cout << "Uneven spacing inputs:" << endl;
+cout << VectorXi::LinSpaced(8,1,7).transpose() << endl;
+cout << VectorXi::LinSpaced(8,1,9).transpose() << endl;
+cout << VectorXi::LinSpaced(8,1,16).transpose() << endl;

ADDED   3rd_party/eigen/doc/snippets/DirectionWise_hnormalized.cpp
Index: 3rd_party/eigen/doc/snippets/DirectionWise_hnormalized.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/DirectionWise_hnormalized.cpp
+++ 3rd_party/eigen/doc/snippets/DirectionWise_hnormalized.cpp
@@ -0,0 +1,7 @@
+typedef Matrix<double,4,Dynamic> Matrix4Xd;
+Matrix4Xd M = Matrix4Xd::Random(4,5);
+Projective3d P(Matrix4d::Random());
+cout << "The matrix M is:" << endl << M << endl << endl;
+cout << "M.colwise().hnormalized():" << endl << M.colwise().hnormalized() << endl << endl;
+cout << "P*M:" << endl << P*M << endl << endl;
+cout << "(P*M).colwise().hnormalized():" << endl << (P*M).colwise().hnormalized() << endl << endl;

Index: 3rd_party/eigen/doc/snippets/EigenSolver_eigenvectors.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/EigenSolver_eigenvectors.cpp
+++ 3rd_party/eigen/doc/snippets/EigenSolver_eigenvectors.cpp
@@ -1,4 +1,4 @@
 MatrixXd ones = MatrixXd::Ones(3,3);
 EigenSolver<MatrixXd> es(ones);
-cout << "The first eigenvector of the 3x3 matrix of ones is:" 
-     << endl << es.eigenvectors().col(1) << endl;
+cout << "The first eigenvector of the 3x3 matrix of ones is:"
+     << endl << es.eigenvectors().col(0) << endl;

ADDED   3rd_party/eigen/doc/snippets/LeastSquaresNormalEquations.cpp
Index: 3rd_party/eigen/doc/snippets/LeastSquaresNormalEquations.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/LeastSquaresNormalEquations.cpp
+++ 3rd_party/eigen/doc/snippets/LeastSquaresNormalEquations.cpp
@@ -0,0 +1,4 @@
+MatrixXf A = MatrixXf::Random(3, 2);
+VectorXf b = VectorXf::Random(3);
+cout << "The solution using normal equations is:\n"
+     << (A.transpose() * A).ldlt().solve(A.transpose() * b) << endl;

ADDED   3rd_party/eigen/doc/snippets/LeastSquaresQR.cpp
Index: 3rd_party/eigen/doc/snippets/LeastSquaresQR.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/LeastSquaresQR.cpp
+++ 3rd_party/eigen/doc/snippets/LeastSquaresQR.cpp
@@ -0,0 +1,4 @@
+MatrixXf A = MatrixXf::Random(3, 2);
+VectorXf b = VectorXf::Random(3);
+cout << "The solution using the QR decomposition is:\n"
+     << A.colPivHouseholderQr().solve(b) << endl;

ADDED   3rd_party/eigen/doc/snippets/MatrixBase_cwiseSign.cpp
Index: 3rd_party/eigen/doc/snippets/MatrixBase_cwiseSign.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/MatrixBase_cwiseSign.cpp
+++ 3rd_party/eigen/doc/snippets/MatrixBase_cwiseSign.cpp
@@ -0,0 +1,4 @@
+MatrixXd m(2,3);
+m <<  2, -4, 6,
+     -5,  1, 0;
+cout << m.cwiseSign() << endl;

DELETED 3rd_party/eigen/doc/snippets/MatrixBase_extract.cpp
Index: 3rd_party/eigen/doc/snippets/MatrixBase_extract.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/MatrixBase_extract.cpp
+++ 3rd_party/eigen/doc/snippets/MatrixBase_extract.cpp
@@ -1,13 +0,0 @@
-#ifndef _MSC_VER
-  #warning deprecated
-#endif
-/* deprecated
-Matrix3i m = Matrix3i::Random();
-cout << "Here is the matrix m:" << endl << m << endl;
-cout << "Here is the upper-triangular matrix extracted from m:" << endl
-     << m.part<Eigen::UpperTriangular>() << endl;
-cout << "Here is the strictly-upper-triangular matrix extracted from m:" << endl
-     << m.part<Eigen::StrictlyUpperTriangular>() << endl;
-cout << "Here is the unit-lower-triangular matrix extracted from m:" << endl
-     << m.part<Eigen::UnitLowerTriangular>() << endl;
-*/

ADDED   3rd_party/eigen/doc/snippets/MatrixBase_hnormalized.cpp
Index: 3rd_party/eigen/doc/snippets/MatrixBase_hnormalized.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/MatrixBase_hnormalized.cpp
+++ 3rd_party/eigen/doc/snippets/MatrixBase_hnormalized.cpp
@@ -0,0 +1,6 @@
+Vector4d v = Vector4d::Random();
+Projective3d P(Matrix4d::Random());
+cout << "v                   = " << v.transpose() << "]^T" << endl;
+cout << "v.hnormalized()     = " << v.hnormalized().transpose() << "]^T" << endl;
+cout << "P*v                 = " << (P*v).transpose() << "]^T" << endl;
+cout << "(P*v).hnormalized() = " << (P*v).hnormalized().transpose() << "]^T" << endl;

ADDED   3rd_party/eigen/doc/snippets/MatrixBase_homogeneous.cpp
Index: 3rd_party/eigen/doc/snippets/MatrixBase_homogeneous.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/MatrixBase_homogeneous.cpp
+++ 3rd_party/eigen/doc/snippets/MatrixBase_homogeneous.cpp
@@ -0,0 +1,6 @@
+Vector3d v = Vector3d::Random(), w;
+Projective3d P(Matrix4d::Random());
+cout << "v                                   = [" << v.transpose() << "]^T" << endl;
+cout << "h.homogeneous()                     = [" << v.homogeneous().transpose() << "]^T" << endl;
+cout << "(P * v.homogeneous())               = [" << (P * v.homogeneous()).transpose() << "]^T" << endl;
+cout << "(P * v.homogeneous()).hnormalized() = [" << (P * v.homogeneous()).eval().hnormalized().transpose() << "]^T" << endl;

DELETED 3rd_party/eigen/doc/snippets/MatrixBase_marked.cpp
Index: 3rd_party/eigen/doc/snippets/MatrixBase_marked.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/MatrixBase_marked.cpp
+++ 3rd_party/eigen/doc/snippets/MatrixBase_marked.cpp
@@ -1,14 +0,0 @@
-#ifndef _MSC_VER
-  #warning deprecated
-#endif
-/*
-Matrix3d m = Matrix3d::Zero();
-m.part<Eigen::UpperTriangular>().setOnes();
-cout << "Here is the matrix m:" << endl << m << endl;
-Matrix3d n = Matrix3d::Ones();
-n.part<Eigen::LowerTriangular>() *= 2;
-cout << "Here is the matrix n:" << endl << n << endl;
-cout << "And now here is m.inverse()*n, taking advantage of the fact that"
-        " m is upper-triangular:" << endl
-     << m.marked<Eigen::UpperTriangular>().solveTriangular(n);
-*/

DELETED 3rd_party/eigen/doc/snippets/MatrixBase_part.cpp
Index: 3rd_party/eigen/doc/snippets/MatrixBase_part.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/MatrixBase_part.cpp
+++ 3rd_party/eigen/doc/snippets/MatrixBase_part.cpp
@@ -1,13 +0,0 @@
-#ifndef _MSC_VER
-  #warning deprecated
-#endif
-/*
-Matrix3d m = Matrix3d::Zero();
-m.part<Eigen::StrictlyUpperTriangular>().setOnes();
-cout << "Here is the matrix m:" << endl << m << endl;
-cout << "And let us now compute m*m.adjoint() in a very optimized way" << endl
-     << "taking advantage of the symmetry." << endl;
-Matrix3d n;
-n.part<Eigen::SelfAdjoint>() = (m*m.adjoint()).lazy();
-cout << "The result is:" << endl << n << endl;
-*/

ADDED   3rd_party/eigen/doc/snippets/MatrixBase_selfadjointView.cpp
Index: 3rd_party/eigen/doc/snippets/MatrixBase_selfadjointView.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/MatrixBase_selfadjointView.cpp
+++ 3rd_party/eigen/doc/snippets/MatrixBase_selfadjointView.cpp
@@ -0,0 +1,6 @@
+Matrix3i m = Matrix3i::Random();
+cout << "Here is the matrix m:" << endl << m << endl;
+cout << "Here is the symmetric matrix extracted from the upper part of m:" << endl
+     << Matrix3i(m.selfadjointView<Upper>()) << endl;
+cout << "Here is the symmetric matrix extracted from the lower part of m:" << endl
+     << Matrix3i(m.selfadjointView<Lower>()) << endl;

ADDED   3rd_party/eigen/doc/snippets/MatrixBase_triangularView.cpp
Index: 3rd_party/eigen/doc/snippets/MatrixBase_triangularView.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/MatrixBase_triangularView.cpp
+++ 3rd_party/eigen/doc/snippets/MatrixBase_triangularView.cpp
@@ -0,0 +1,9 @@
+Matrix3i m = Matrix3i::Random();
+cout << "Here is the matrix m:" << endl << m << endl;
+cout << "Here is the upper-triangular matrix extracted from m:" << endl
+     << Matrix3i(m.triangularView<Eigen::Upper>()) << endl;
+cout << "Here is the strictly-upper-triangular matrix extracted from m:" << endl
+     << Matrix3i(m.triangularView<Eigen::StrictlyUpper>()) << endl;
+cout << "Here is the unit-lower-triangular matrix extracted from m:" << endl
+     << Matrix3i(m.triangularView<Eigen::UnitLower>()) << endl;
+// FIXME need to implement output for triangularViews (Bug 885)

Index: 3rd_party/eigen/doc/snippets/PartialRedux_count.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/PartialRedux_count.cpp
+++ 3rd_party/eigen/doc/snippets/PartialRedux_count.cpp
@@ -1,3 +1,5 @@
 Matrix3d m = Matrix3d::Random();
 cout << "Here is the matrix m:" << endl << m << endl;
-cout << "Here is the count of elements larger or equal than 0.5 of each row:" << endl << (m.array() >= 0.5).rowwise().count() << endl;
+Matrix<ptrdiff_t, 3, 1> res = (m.array() >= 0.5).rowwise().count();
+cout << "Here is the count of elements larger or equal than 0.5 of each row:" << endl;
+cout << res << endl;

ADDED   3rd_party/eigen/doc/snippets/SparseMatrix_coeffs.cpp
Index: 3rd_party/eigen/doc/snippets/SparseMatrix_coeffs.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/SparseMatrix_coeffs.cpp
+++ 3rd_party/eigen/doc/snippets/SparseMatrix_coeffs.cpp
@@ -0,0 +1,9 @@
+SparseMatrix<double> A(3,3);
+A.insert(1,2) = 0;
+A.insert(0,1) = 1;
+A.insert(2,0) = 2;
+A.makeCompressed();
+cout << "The matrix A is:" << endl << MatrixXd(A) << endl;
+cout << "it has " << A.nonZeros() << " stored non zero coefficients that are: " << A.coeffs().transpose() << endl;
+A.coeffs() += 10;
+cout << "After adding 10 to every stored non zero coefficient, the matrix A is:" << endl << MatrixXd(A) << endl;

ADDED   3rd_party/eigen/doc/snippets/TopicAliasing_mult4.cpp
Index: 3rd_party/eigen/doc/snippets/TopicAliasing_mult4.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/TopicAliasing_mult4.cpp
+++ 3rd_party/eigen/doc/snippets/TopicAliasing_mult4.cpp
@@ -0,0 +1,5 @@
+MatrixXf A(2,2), B(3,2);
+B << 2, 0,  0, 3, 1, 1;
+A << 2, 0, 0, -2;
+A = (B * A).cwiseAbs();
+cout << A;

ADDED   3rd_party/eigen/doc/snippets/TopicAliasing_mult5.cpp
Index: 3rd_party/eigen/doc/snippets/TopicAliasing_mult5.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/TopicAliasing_mult5.cpp
+++ 3rd_party/eigen/doc/snippets/TopicAliasing_mult5.cpp
@@ -0,0 +1,5 @@
+MatrixXf A(2,2), B(3,2);
+B << 2, 0,  0, 3, 1, 1;
+A << 2, 0, 0, -2;
+A = (B * A).eval().cwiseAbs();
+cout << A;

ADDED   3rd_party/eigen/doc/snippets/Triangular_solve.cpp
Index: 3rd_party/eigen/doc/snippets/Triangular_solve.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Triangular_solve.cpp
+++ 3rd_party/eigen/doc/snippets/Triangular_solve.cpp
@@ -0,0 +1,11 @@
+Matrix3d m = Matrix3d::Zero();
+m.triangularView<Eigen::Upper>().setOnes();
+cout << "Here is the matrix m:\n" << m << endl;
+Matrix3d n = Matrix3d::Ones();
+n.triangularView<Eigen::Lower>() *= 2;
+cout << "Here is the matrix n:\n" << n << endl;
+cout << "And now here is m.inverse()*n, taking advantage of the fact that"
+        " m is upper-triangular:\n"
+     << m.triangularView<Eigen::Upper>().solve(n) << endl;
+cout << "And this is n*m.inverse():\n"
+     << m.triangularView<Eigen::Upper>().solve<Eigen::OnTheRight>(n);

Index: 3rd_party/eigen/doc/snippets/Tutorial_AdvancedInitialization_Join.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Tutorial_AdvancedInitialization_Join.cpp
+++ 3rd_party/eigen/doc/snippets/Tutorial_AdvancedInitialization_Join.cpp
@@ -1,11 +1,11 @@
 RowVectorXd vec1(3);
 vec1 << 1, 2, 3;
 std::cout << "vec1 = " << vec1 << std::endl;
 
 RowVectorXd vec2(4);
-vec2 << 1, 4, 9, 16;;
+vec2 << 1, 4, 9, 16;
 std::cout << "vec2 = " << vec2 << std::endl;
 
 RowVectorXd joined(7);
 joined << vec1, vec2;
 std::cout << "joined = " << joined << std::endl;

ADDED   3rd_party/eigen/doc/snippets/Tutorial_ReshapeMat2Mat.cpp
Index: 3rd_party/eigen/doc/snippets/Tutorial_ReshapeMat2Mat.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Tutorial_ReshapeMat2Mat.cpp
+++ 3rd_party/eigen/doc/snippets/Tutorial_ReshapeMat2Mat.cpp
@@ -0,0 +1,6 @@
+MatrixXf M1(2,6);    // Column-major storage
+M1 << 1, 2, 3,  4,  5,  6,
+      7, 8, 9, 10, 11, 12;
+
+Map<MatrixXf> M2(M1.data(), 6,2);
+cout << "M2:" << endl << M2 << endl;

ADDED   3rd_party/eigen/doc/snippets/Tutorial_ReshapeMat2Vec.cpp
Index: 3rd_party/eigen/doc/snippets/Tutorial_ReshapeMat2Vec.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Tutorial_ReshapeMat2Vec.cpp
+++ 3rd_party/eigen/doc/snippets/Tutorial_ReshapeMat2Vec.cpp
@@ -0,0 +1,11 @@
+MatrixXf M1(3,3);    // Column-major storage
+M1 << 1, 2, 3,
+      4, 5, 6,
+      7, 8, 9;
+
+Map<RowVectorXf> v1(M1.data(), M1.size());
+cout << "v1:" << endl << v1 << endl;
+
+Matrix<float,Dynamic,Dynamic,RowMajor> M2(M1);
+Map<RowVectorXf> v2(M2.data(), M2.size());
+cout << "v2:" << endl << v2 << endl;

ADDED   3rd_party/eigen/doc/snippets/Tutorial_SlicingCol.cpp
Index: 3rd_party/eigen/doc/snippets/Tutorial_SlicingCol.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Tutorial_SlicingCol.cpp
+++ 3rd_party/eigen/doc/snippets/Tutorial_SlicingCol.cpp
@@ -0,0 +1,11 @@
+MatrixXf M1 = MatrixXf::Random(3,8);
+cout << "Column major input:" << endl << M1 << "\n";
+Map<MatrixXf,0,OuterStride<> > M2(M1.data(), M1.rows(), (M1.cols()+2)/3, OuterStride<>(M1.outerStride()*3));
+cout << "1 column over 3:" << endl << M2 << "\n";
+
+typedef Matrix<float,Dynamic,Dynamic,RowMajor> RowMajorMatrixXf;
+RowMajorMatrixXf M3(M1);
+cout << "Row major input:" << endl << M3 << "\n";
+Map<RowMajorMatrixXf,0,Stride<Dynamic,3> > M4(M3.data(), M3.rows(), (M3.cols()+2)/3,
+                                              Stride<Dynamic,3>(M3.outerStride(),3));
+cout << "1 column over 3:" << endl << M4 << "\n";

ADDED   3rd_party/eigen/doc/snippets/Tutorial_SlicingVec.cpp
Index: 3rd_party/eigen/doc/snippets/Tutorial_SlicingVec.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/Tutorial_SlicingVec.cpp
+++ 3rd_party/eigen/doc/snippets/Tutorial_SlicingVec.cpp
@@ -0,0 +1,4 @@
+RowVectorXf v = RowVectorXf::LinSpaced(20,0,19);
+cout << "Input:" << endl << v << endl;
+Map<RowVectorXf,0,InnerStride<2> > v2(v.data(), v.size()/2);
+cout << "Even:" << v2 << endl;

ADDED   3rd_party/eigen/doc/snippets/VectorwiseOp_homogeneous.cpp
Index: 3rd_party/eigen/doc/snippets/VectorwiseOp_homogeneous.cpp
==================================================================
--- 3rd_party/eigen/doc/snippets/VectorwiseOp_homogeneous.cpp
+++ 3rd_party/eigen/doc/snippets/VectorwiseOp_homogeneous.cpp
@@ -0,0 +1,7 @@
+typedef Matrix<double,3,Dynamic> Matrix3Xd;
+Matrix3Xd M = Matrix3Xd::Random(3,5);
+Projective3d P(Matrix4d::Random());
+cout << "The matrix M is:" << endl << M << endl << endl;
+cout << "M.colwise().homogeneous():" << endl << M.colwise().homogeneous() << endl << endl;
+cout << "P * M.colwise().homogeneous():" << endl << P * M.colwise().homogeneous() << endl << endl;
+cout << "P * M.colwise().homogeneous().hnormalized(): " << endl << (P * M.colwise().homogeneous()).colwise().hnormalized() << endl << endl;

Index: 3rd_party/eigen/doc/snippets/compile_snippet.cpp.in
==================================================================
--- 3rd_party/eigen/doc/snippets/compile_snippet.cpp.in
+++ 3rd_party/eigen/doc/snippets/compile_snippet.cpp.in
@@ -1,7 +1,15 @@
-#include <Eigen/Dense>
+static bool eigen_did_assert = false;
+#define eigen_assert(X) if(!eigen_did_assert && !(X)){ std::cout << "### Assertion raised in " << __FILE__ << ":" << __LINE__ << ":\n" #X << "\n### The following would happen without assertions:\n"; eigen_did_assert = true;}
+
 #include <iostream>
+#include <Eigen/Eigen>
+
+#ifndef M_PI
+#define M_PI 3.1415926535897932384626433832795
+#endif
+
 
 using namespace Eigen;
 using namespace std;
 
 int main(int, char**)

Index: 3rd_party/eigen/doc/special_examples/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/doc/special_examples/CMakeLists.txt
+++ 3rd_party/eigen/doc/special_examples/CMakeLists.txt
@@ -8,13 +8,28 @@
 if(QT4_FOUND)
   add_executable(Tutorial_sparse_example Tutorial_sparse_example.cpp Tutorial_sparse_example_details.cpp)
   target_link_libraries(Tutorial_sparse_example ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO} ${QT_QTCORE_LIBRARY} ${QT_QTGUI_LIBRARY})
 
   add_custom_command(
-      TARGET Tutorial_sparse_example
-      POST_BUILD
-      COMMAND Tutorial_sparse_example ARGS ${CMAKE_CURRENT_BINARY_DIR}/../html/Tutorial_sparse_example.jpeg
+    TARGET Tutorial_sparse_example
+    POST_BUILD
+    COMMAND ${CMAKE_COMMAND} -E make_directory ${CMAKE_CURRENT_BINARY_DIR}/../html/
+    COMMAND Tutorial_sparse_example ARGS ${CMAKE_CURRENT_BINARY_DIR}/../html/Tutorial_sparse_example.jpeg
   )
 
   add_dependencies(all_examples Tutorial_sparse_example)
 endif(QT4_FOUND)
 
+check_cxx_compiler_flag("-std=c++11" EIGEN_COMPILER_SUPPORT_CPP11)
+if(EIGEN_COMPILER_SUPPORT_CPP11)
+  add_executable(random_cpp11 random_cpp11.cpp)
+  target_link_libraries(random_cpp11 ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO})
+  add_dependencies(all_examples random_cpp11)
+  ei_add_target_property(random_cpp11 COMPILE_FLAGS "-std=c++11")
+
+  add_custom_command(
+    TARGET random_cpp11
+    POST_BUILD
+    COMMAND random_cpp11
+    ARGS >${CMAKE_CURRENT_BINARY_DIR}/random_cpp11.out
+  )
+endif()

Index: 3rd_party/eigen/doc/special_examples/Tutorial_sparse_example.cpp
==================================================================
--- 3rd_party/eigen/doc/special_examples/Tutorial_sparse_example.cpp
+++ 3rd_party/eigen/doc/special_examples/Tutorial_sparse_example.cpp
@@ -7,10 +7,12 @@
 void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n);
 void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename);
 
 int main(int argc, char** argv)
 {
+  assert(argc==2);
+  
   int n = 300;  // size of the image
   int m = n*n;  // number of unknows (=number of pixels)
 
   // Assembly:
   std::vector<T> coefficients;            // list of non-zeros coefficients

Index: 3rd_party/eigen/doc/special_examples/Tutorial_sparse_example_details.cpp
==================================================================
--- 3rd_party/eigen/doc/special_examples/Tutorial_sparse_example_details.cpp
+++ 3rd_party/eigen/doc/special_examples/Tutorial_sparse_example_details.cpp
@@ -6,11 +6,11 @@
 typedef Eigen::Triplet<double> T;
 
 void insertCoefficient(int id, int i, int j, double w, std::vector<T>& coeffs,
                        Eigen::VectorXd& b, const Eigen::VectorXd& boundary)
 {
-  int n = boundary.size();
+  int n = int(boundary.size());
   int id1 = i+j*n;
 
         if(i==-1 || i==n) b(id) -= w * boundary(j); // constrained coefficient
   else  if(j==-1 || j==n) b(id) -= w * boundary(i); // constrained coefficient
   else  coeffs.push_back(T(id,id1,w));              // unknown coefficient

ADDED   3rd_party/eigen/doc/special_examples/random_cpp11.cpp
Index: 3rd_party/eigen/doc/special_examples/random_cpp11.cpp
==================================================================
--- 3rd_party/eigen/doc/special_examples/random_cpp11.cpp
+++ 3rd_party/eigen/doc/special_examples/random_cpp11.cpp
@@ -0,0 +1,14 @@
+#include <Eigen/Core>
+#include <iostream>
+#include <random>
+
+using namespace Eigen;
+
+int main() {
+  std::default_random_engine generator;
+  std::poisson_distribution<int> distribution(4.1);
+  auto poisson = [&] () {return distribution(generator);};
+
+  RowVectorXi v = RowVectorXi::NullaryExpr(10, poisson );
+  std::cout << v << "\n";
+}

Index: 3rd_party/eigen/eigen3.pc.in
==================================================================
--- 3rd_party/eigen/eigen3.pc.in
+++ 3rd_party/eigen/eigen3.pc.in
@@ -1,6 +1,9 @@
+prefix=@CMAKE_INSTALL_PREFIX@
+exec_prefix=${prefix}
+
 Name: Eigen3
 Description: A C++ template library for linear algebra: vectors, matrices, and related algorithms
 Requires:
-Version: ${EIGEN_VERSION_NUMBER}
+Version: @EIGEN_VERSION_NUMBER@
 Libs:
-Cflags: -I${INCLUDE_INSTALL_DIR}
+Cflags: -I${prefix}/@INCLUDE_INSTALL_DIR@

Index: 3rd_party/eigen/failtest/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/failtest/CMakeLists.txt
+++ 3rd_party/eigen/failtest/CMakeLists.txt
@@ -5,10 +5,13 @@
 ei_add_failtest("block_nonconst_ctor_on_const_xpr_0")
 ei_add_failtest("block_nonconst_ctor_on_const_xpr_1")
 ei_add_failtest("block_nonconst_ctor_on_const_xpr_2")
 ei_add_failtest("transpose_nonconst_ctor_on_const_xpr")
 ei_add_failtest("diagonal_nonconst_ctor_on_const_xpr")
+ei_add_failtest("cwiseunaryview_nonconst_ctor_on_const_xpr")
+ei_add_failtest("triangularview_nonconst_ctor_on_const_xpr")
+ei_add_failtest("selfadjointview_nonconst_ctor_on_const_xpr")
 
 ei_add_failtest("const_qualified_block_method_retval_0")
 ei_add_failtest("const_qualified_block_method_retval_1")
 ei_add_failtest("const_qualified_transpose_method_retval")
 ei_add_failtest("const_qualified_diagonal_method_retval")
@@ -23,21 +26,50 @@
 ei_add_failtest("map_on_const_type_actually_const_1")
 ei_add_failtest("block_on_const_type_actually_const_0")
 ei_add_failtest("block_on_const_type_actually_const_1")
 ei_add_failtest("transpose_on_const_type_actually_const")
 ei_add_failtest("diagonal_on_const_type_actually_const")
+ei_add_failtest("cwiseunaryview_on_const_type_actually_const")
+ei_add_failtest("triangularview_on_const_type_actually_const")
+ei_add_failtest("selfadjointview_on_const_type_actually_const")
 
 ei_add_failtest("ref_1")
 ei_add_failtest("ref_2")
 ei_add_failtest("ref_3")
 ei_add_failtest("ref_4")
 ei_add_failtest("ref_5")
 
+ei_add_failtest("swap_1")
+ei_add_failtest("swap_2")
+
+ei_add_failtest("ternary_1")
+ei_add_failtest("ternary_2")
+
+ei_add_failtest("sparse_ref_1")
+ei_add_failtest("sparse_ref_2")
+ei_add_failtest("sparse_ref_3")
+ei_add_failtest("sparse_ref_4")
+ei_add_failtest("sparse_ref_5")
+
+ei_add_failtest("sparse_storage_mismatch")
+
+ei_add_failtest("partialpivlu_int")
+ei_add_failtest("fullpivlu_int")
+ei_add_failtest("llt_int")
+ei_add_failtest("ldlt_int")
+ei_add_failtest("qr_int")
+ei_add_failtest("colpivqr_int")
+ei_add_failtest("fullpivqr_int")
+ei_add_failtest("jacobisvd_int")
+ei_add_failtest("bdcsvd_int")
+ei_add_failtest("eigensolver_int")
+ei_add_failtest("eigensolver_cplx")
+
 if (EIGEN_FAILTEST_FAILURE_COUNT)
   message(FATAL_ERROR
           "${EIGEN_FAILTEST_FAILURE_COUNT} out of ${EIGEN_FAILTEST_COUNT} failtests FAILED. "
           "To debug these failures, manually compile these programs in ${CMAKE_CURRENT_SOURCE_DIR}, "
           "with and without #define EIGEN_SHOULD_FAIL_TO_BUILD.")
 else()
   message(STATUS "Failtest SUCCESS: all ${EIGEN_FAILTEST_COUNT} failtests passed.")
   message(STATUS "")
 endif()

ADDED   3rd_party/eigen/failtest/bdcsvd_int.cpp
Index: 3rd_party/eigen/failtest/bdcsvd_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/bdcsvd_int.cpp
+++ 3rd_party/eigen/failtest/bdcsvd_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/SVD"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  BDCSVD<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/colpivqr_int.cpp
Index: 3rd_party/eigen/failtest/colpivqr_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/colpivqr_int.cpp
+++ 3rd_party/eigen/failtest/colpivqr_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/QR"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  ColPivHouseholderQR<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/cwiseunaryview_nonconst_ctor_on_const_xpr.cpp
Index: 3rd_party/eigen/failtest/cwiseunaryview_nonconst_ctor_on_const_xpr.cpp
==================================================================
--- 3rd_party/eigen/failtest/cwiseunaryview_nonconst_ctor_on_const_xpr.cpp
+++ 3rd_party/eigen/failtest/cwiseunaryview_nonconst_ctor_on_const_xpr.cpp
@@ -0,0 +1,15 @@
+#include "../Eigen/Core"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define CV_QUALIFIER const
+#else
+#define CV_QUALIFIER
+#endif
+
+using namespace Eigen;
+
+void foo(CV_QUALIFIER Matrix3d &m){
+    CwiseUnaryView<internal::scalar_real_ref_op<double>,Matrix3d> t(m);
+}
+
+int main() {}

ADDED   3rd_party/eigen/failtest/cwiseunaryview_on_const_type_actually_const.cpp
Index: 3rd_party/eigen/failtest/cwiseunaryview_on_const_type_actually_const.cpp
==================================================================
--- 3rd_party/eigen/failtest/cwiseunaryview_on_const_type_actually_const.cpp
+++ 3rd_party/eigen/failtest/cwiseunaryview_on_const_type_actually_const.cpp
@@ -0,0 +1,16 @@
+#include "../Eigen/Core"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define CV_QUALIFIER const
+#else
+#define CV_QUALIFIER
+#endif
+
+using namespace Eigen;
+
+void foo(){
+    MatrixXf m;
+    CwiseUnaryView<internal::scalar_real_ref_op<double>,CV_QUALIFIER MatrixXf>(m).coeffRef(0, 0) = 1.0f;
+}
+
+int main() {}

ADDED   3rd_party/eigen/failtest/eigensolver_cplx.cpp
Index: 3rd_party/eigen/failtest/eigensolver_cplx.cpp
==================================================================
--- 3rd_party/eigen/failtest/eigensolver_cplx.cpp
+++ 3rd_party/eigen/failtest/eigensolver_cplx.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/Eigenvalues"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR std::complex<double>
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  EigenSolver<Matrix<SCALAR,Dynamic,Dynamic> > eig(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/eigensolver_int.cpp
Index: 3rd_party/eigen/failtest/eigensolver_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/eigensolver_int.cpp
+++ 3rd_party/eigen/failtest/eigensolver_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/Eigenvalues"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  EigenSolver<Matrix<SCALAR,Dynamic,Dynamic> > eig(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/fullpivlu_int.cpp
Index: 3rd_party/eigen/failtest/fullpivlu_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/fullpivlu_int.cpp
+++ 3rd_party/eigen/failtest/fullpivlu_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/LU"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  FullPivLU<Matrix<SCALAR,Dynamic,Dynamic> > lu(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/fullpivqr_int.cpp
Index: 3rd_party/eigen/failtest/fullpivqr_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/fullpivqr_int.cpp
+++ 3rd_party/eigen/failtest/fullpivqr_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/QR"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  FullPivHouseholderQR<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/jacobisvd_int.cpp
Index: 3rd_party/eigen/failtest/jacobisvd_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/jacobisvd_int.cpp
+++ 3rd_party/eigen/failtest/jacobisvd_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/SVD"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  JacobiSVD<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/ldlt_int.cpp
Index: 3rd_party/eigen/failtest/ldlt_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/ldlt_int.cpp
+++ 3rd_party/eigen/failtest/ldlt_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/Cholesky"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  LDLT<Matrix<SCALAR,Dynamic,Dynamic> > ldlt(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/llt_int.cpp
Index: 3rd_party/eigen/failtest/llt_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/llt_int.cpp
+++ 3rd_party/eigen/failtest/llt_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/Cholesky"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  LLT<Matrix<SCALAR,Dynamic,Dynamic> > llt(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/partialpivlu_int.cpp
Index: 3rd_party/eigen/failtest/partialpivlu_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/partialpivlu_int.cpp
+++ 3rd_party/eigen/failtest/partialpivlu_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/LU"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  PartialPivLU<Matrix<SCALAR,Dynamic,Dynamic> > lu(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/qr_int.cpp
Index: 3rd_party/eigen/failtest/qr_int.cpp
==================================================================
--- 3rd_party/eigen/failtest/qr_int.cpp
+++ 3rd_party/eigen/failtest/qr_int.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/QR"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define SCALAR int
+#else
+#define SCALAR float
+#endif
+
+using namespace Eigen;
+
+int main()
+{
+  HouseholderQR<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
+}

ADDED   3rd_party/eigen/failtest/selfadjointview_nonconst_ctor_on_const_xpr.cpp
Index: 3rd_party/eigen/failtest/selfadjointview_nonconst_ctor_on_const_xpr.cpp
==================================================================
--- 3rd_party/eigen/failtest/selfadjointview_nonconst_ctor_on_const_xpr.cpp
+++ 3rd_party/eigen/failtest/selfadjointview_nonconst_ctor_on_const_xpr.cpp
@@ -0,0 +1,15 @@
+#include "../Eigen/Core"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define CV_QUALIFIER const
+#else
+#define CV_QUALIFIER
+#endif
+
+using namespace Eigen;
+
+void foo(CV_QUALIFIER Matrix3d &m){
+    SelfAdjointView<Matrix3d,Upper> t(m);
+}
+
+int main() {}

ADDED   3rd_party/eigen/failtest/selfadjointview_on_const_type_actually_const.cpp
Index: 3rd_party/eigen/failtest/selfadjointview_on_const_type_actually_const.cpp
==================================================================
--- 3rd_party/eigen/failtest/selfadjointview_on_const_type_actually_const.cpp
+++ 3rd_party/eigen/failtest/selfadjointview_on_const_type_actually_const.cpp
@@ -0,0 +1,16 @@
+#include "../Eigen/Core"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define CV_QUALIFIER const
+#else
+#define CV_QUALIFIER
+#endif
+
+using namespace Eigen;
+
+void foo(){
+    MatrixXf m;
+    SelfAdjointView<CV_QUALIFIER MatrixXf,Upper>(m).coeffRef(0, 0) = 1.0f;
+}
+
+int main() {}

ADDED   3rd_party/eigen/failtest/sparse_ref_1.cpp
Index: 3rd_party/eigen/failtest/sparse_ref_1.cpp
==================================================================
--- 3rd_party/eigen/failtest/sparse_ref_1.cpp
+++ 3rd_party/eigen/failtest/sparse_ref_1.cpp
@@ -0,0 +1,18 @@
+#include "../Eigen/Sparse"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define CV_QUALIFIER const
+#else
+#define CV_QUALIFIER
+#endif
+
+using namespace Eigen;
+
+void call_ref(Ref<SparseMatrix<float> > a) { }
+
+int main()
+{
+  SparseMatrix<float> a(10,10);
+  CV_QUALIFIER SparseMatrix<float>& ac(a);
+  call_ref(ac);
+}

ADDED   3rd_party/eigen/failtest/sparse_ref_2.cpp
Index: 3rd_party/eigen/failtest/sparse_ref_2.cpp
==================================================================
--- 3rd_party/eigen/failtest/sparse_ref_2.cpp
+++ 3rd_party/eigen/failtest/sparse_ref_2.cpp
@@ -0,0 +1,15 @@
+#include "../Eigen/Sparse"
+
+using namespace Eigen;
+
+void call_ref(Ref<SparseMatrix<float> > a) { }
+
+int main()
+{
+  SparseMatrix<float> A(10,10);
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+  call_ref(A.row(3));
+#else
+  call_ref(A.col(3));
+#endif
+}

ADDED   3rd_party/eigen/failtest/sparse_ref_3.cpp
Index: 3rd_party/eigen/failtest/sparse_ref_3.cpp
==================================================================
--- 3rd_party/eigen/failtest/sparse_ref_3.cpp
+++ 3rd_party/eigen/failtest/sparse_ref_3.cpp
@@ -0,0 +1,15 @@
+#include "../Eigen/Sparse"
+
+using namespace Eigen;
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+void call_ref(Ref<SparseMatrix<float> > a) { }
+#else
+void call_ref(const Ref<const SparseMatrix<float> > &a) { }
+#endif
+
+int main()
+{
+  SparseMatrix<float> a(10,10);
+  call_ref(a+a);
+}

ADDED   3rd_party/eigen/failtest/sparse_ref_4.cpp
Index: 3rd_party/eigen/failtest/sparse_ref_4.cpp
==================================================================
--- 3rd_party/eigen/failtest/sparse_ref_4.cpp
+++ 3rd_party/eigen/failtest/sparse_ref_4.cpp
@@ -0,0 +1,15 @@
+#include "../Eigen/Sparse"
+
+using namespace Eigen;
+
+void call_ref(Ref<SparseMatrix<float> > a) {}
+
+int main()
+{
+  SparseMatrix<float> A(10,10);
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+  call_ref(A.transpose());
+#else
+  call_ref(A);
+#endif
+}

ADDED   3rd_party/eigen/failtest/sparse_ref_5.cpp
Index: 3rd_party/eigen/failtest/sparse_ref_5.cpp
==================================================================
--- 3rd_party/eigen/failtest/sparse_ref_5.cpp
+++ 3rd_party/eigen/failtest/sparse_ref_5.cpp
@@ -0,0 +1,16 @@
+#include "../Eigen/Sparse"
+
+using namespace Eigen;
+
+void call_ref(Ref<SparseMatrix<float> > a) { }
+
+int main()
+{
+  SparseMatrix<float> a(10,10);
+  SparseMatrixBase<SparseMatrix<float> > &ac(a);
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+  call_ref(ac);
+#else
+  call_ref(ac.derived());
+#endif
+}

ADDED   3rd_party/eigen/failtest/sparse_storage_mismatch.cpp
Index: 3rd_party/eigen/failtest/sparse_storage_mismatch.cpp
==================================================================
--- 3rd_party/eigen/failtest/sparse_storage_mismatch.cpp
+++ 3rd_party/eigen/failtest/sparse_storage_mismatch.cpp
@@ -0,0 +1,16 @@
+#include "../Eigen/Sparse"
+using namespace Eigen;
+
+typedef SparseMatrix<double,ColMajor> Mat1;
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+typedef SparseMatrix<double,RowMajor> Mat2;
+#else
+typedef SparseMatrix<double,ColMajor> Mat2;
+#endif
+
+int main()
+{
+  Mat1 a(10,10);
+  Mat2 b(10,10);
+  a += b;
+}

ADDED   3rd_party/eigen/failtest/swap_1.cpp
Index: 3rd_party/eigen/failtest/swap_1.cpp
==================================================================
--- 3rd_party/eigen/failtest/swap_1.cpp
+++ 3rd_party/eigen/failtest/swap_1.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/Core"
+
+using namespace Eigen;
+
+int main()
+{
+  VectorXf a(10), b(10);
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+  const DenseBase<VectorXf> &ac(a);
+#else
+  DenseBase<VectorXf> &ac(a);
+#endif
+  b.swap(ac);
+}

ADDED   3rd_party/eigen/failtest/swap_2.cpp
Index: 3rd_party/eigen/failtest/swap_2.cpp
==================================================================
--- 3rd_party/eigen/failtest/swap_2.cpp
+++ 3rd_party/eigen/failtest/swap_2.cpp
@@ -0,0 +1,14 @@
+#include "../Eigen/Core"
+
+using namespace Eigen;
+
+int main()
+{
+  VectorXf a(10), b(10);
+  VectorXf const &ac(a);
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+  b.swap(ac);
+#else
+  b.swap(ac.const_cast_derived());
+#endif
+}

ADDED   3rd_party/eigen/failtest/ternary_1.cpp
Index: 3rd_party/eigen/failtest/ternary_1.cpp
==================================================================
--- 3rd_party/eigen/failtest/ternary_1.cpp
+++ 3rd_party/eigen/failtest/ternary_1.cpp
@@ -0,0 +1,13 @@
+#include "../Eigen/Core"
+
+using namespace Eigen;
+
+int main(int argc,char **)
+{
+  VectorXf a(10), b(10);
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+  b = argc>1 ? 2*a : -a;
+#else
+  b = argc>1 ? 2*a : VectorXf(-a);
+#endif
+}

ADDED   3rd_party/eigen/failtest/ternary_2.cpp
Index: 3rd_party/eigen/failtest/ternary_2.cpp
==================================================================
--- 3rd_party/eigen/failtest/ternary_2.cpp
+++ 3rd_party/eigen/failtest/ternary_2.cpp
@@ -0,0 +1,13 @@
+#include "../Eigen/Core"
+
+using namespace Eigen;
+
+int main(int argc,char **)
+{
+  VectorXf a(10), b(10);
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+  b = argc>1 ? 2*a : a+a;
+#else
+  b = argc>1 ? VectorXf(2*a) : VectorXf(a+a);
+#endif
+}

ADDED   3rd_party/eigen/failtest/triangularview_nonconst_ctor_on_const_xpr.cpp
Index: 3rd_party/eigen/failtest/triangularview_nonconst_ctor_on_const_xpr.cpp
==================================================================
--- 3rd_party/eigen/failtest/triangularview_nonconst_ctor_on_const_xpr.cpp
+++ 3rd_party/eigen/failtest/triangularview_nonconst_ctor_on_const_xpr.cpp
@@ -0,0 +1,15 @@
+#include "../Eigen/Core"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define CV_QUALIFIER const
+#else
+#define CV_QUALIFIER
+#endif
+
+using namespace Eigen;
+
+void foo(CV_QUALIFIER Matrix3d &m){
+  TriangularView<Matrix3d,Upper> t(m);
+}
+
+int main() {}

ADDED   3rd_party/eigen/failtest/triangularview_on_const_type_actually_const.cpp
Index: 3rd_party/eigen/failtest/triangularview_on_const_type_actually_const.cpp
==================================================================
--- 3rd_party/eigen/failtest/triangularview_on_const_type_actually_const.cpp
+++ 3rd_party/eigen/failtest/triangularview_on_const_type_actually_const.cpp
@@ -0,0 +1,16 @@
+#include "../Eigen/Core"
+
+#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
+#define CV_QUALIFIER const
+#else
+#define CV_QUALIFIER
+#endif
+
+using namespace Eigen;
+
+void foo(){
+    MatrixXf m;
+    TriangularView<CV_QUALIFIER MatrixXf,Upper>(m).coeffRef(0, 0) = 1.0f;
+}
+
+int main() {}

Index: 3rd_party/eigen/lapack/complex_double.cpp
==================================================================
--- 3rd_party/eigen/lapack/complex_double.cpp
+++ 3rd_party/eigen/lapack/complex_double.cpp
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -13,5 +13,6 @@
 #define REAL_SCALAR_SUFFIX d
 #define ISCOMPLEX     1
 
 #include "cholesky.cpp"
 #include "lu.cpp"
+#include "svd.cpp"

Index: 3rd_party/eigen/lapack/complex_single.cpp
==================================================================
--- 3rd_party/eigen/lapack/complex_single.cpp
+++ 3rd_party/eigen/lapack/complex_single.cpp
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -13,5 +13,6 @@
 #define REAL_SCALAR_SUFFIX s
 #define ISCOMPLEX     1
 
 #include "cholesky.cpp"
 #include "lu.cpp"
+#include "svd.cpp"

Index: 3rd_party/eigen/lapack/double.cpp
==================================================================
--- 3rd_party/eigen/lapack/double.cpp
+++ 3rd_party/eigen/lapack/double.cpp
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -13,5 +13,6 @@
 #define ISCOMPLEX     0
 
 #include "cholesky.cpp"
 #include "lu.cpp"
 #include "eigenvalues.cpp"
+#include "svd.cpp"

Index: 3rd_party/eigen/lapack/eigenvalues.cpp
==================================================================
--- 3rd_party/eigen/lapack/eigenvalues.cpp
+++ 3rd_party/eigen/lapack/eigenvalues.cpp
@@ -5,14 +5,14 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
-#include "common.h"
+#include "lapack_common.h"
 #include <Eigen/Eigenvalues>
 
-// computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
+// computes eigen values and vectors of a general N-by-N matrix A
 EIGEN_LAPACK_FUNC(syev,(char *jobz, char *uplo, int* n, Scalar* a, int *lda, Scalar* w, Scalar* /*work*/, int* lwork, int *info))
 {
   // TODO exploit the work buffer
   bool query_size = *lwork==-1;
   
@@ -20,28 +20,11 @@
         if(*jobz!='N' && *jobz!='V')                    *info = -1;
   else  if(UPLO(*uplo)==INVALID)                        *info = -2;
   else  if(*n<0)                                        *info = -3;
   else  if(*lda<std::max(1,*n))                         *info = -5;
   else  if((!query_size) && *lwork<std::max(1,3**n-1))  *info = -8;
-  
-//   if(*info==0)
-//   {
-//     int nb = ILAENV( 1, 'SSYTRD', UPLO, N, -1, -1, -1 )
-//          LWKOPT = MAX( 1, ( NB+2 )*N )
-//          WORK( 1 ) = LWKOPT
-// *
-//          IF( LWORK.LT.MAX( 1, 3*N-1 ) .AND. .NOT.LQUERY )
-//      $      INFO = -8
-//       END IF
-// *
-//       IF( INFO.NE.0 ) THEN
-//          CALL XERBLA( 'SSYEV ', -INFO )
-//          RETURN
-//       ELSE IF( LQUERY ) THEN
-//          RETURN
-//       END IF
-  
+    
   if(*info!=0)
   {
     int e = -*info;
     return xerbla_(SCALAR_SUFFIX_UP"SYEV ", &e, 6);
   }
@@ -62,18 +45,18 @@
   bool computeVectors = *jobz=='V' || *jobz=='v';
   SelfAdjointEigenSolver<PlainMatrixType> eig(mat,computeVectors?ComputeEigenvectors:EigenvaluesOnly);
   
   if(eig.info()==NoConvergence)
   {
-    vector(w,*n).setZero();
+    make_vector(w,*n).setZero();
     if(computeVectors)
       matrix(a,*n,*n,*lda).setIdentity();
     //*info = 1;
     return 0;
   }
   
-  vector(w,*n) = eig.eigenvalues();
+  make_vector(w,*n) = eig.eigenvalues();
   if(computeVectors)
     matrix(a,*n,*n,*lda) = eig.eigenvectors();
   
   return 0;
 }

Index: 3rd_party/eigen/lapack/lapack_common.h
==================================================================
--- 3rd_party/eigen/lapack/lapack_common.h
+++ 3rd_party/eigen/lapack/lapack_common.h
@@ -1,23 +1,29 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2010-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_LAPACK_COMMON_H
 #define EIGEN_LAPACK_COMMON_H
 
 #include "../blas/common.h"
+#include "../Eigen/src/misc/lapack.h"
 
 #define EIGEN_LAPACK_FUNC(FUNC,ARGLIST)               \
   extern "C" { int EIGEN_BLAS_FUNC(FUNC) ARGLIST; }   \
   int EIGEN_BLAS_FUNC(FUNC) ARGLIST
 
 typedef Eigen::Map<Eigen::Transpositions<Eigen::Dynamic,Eigen::Dynamic,int> > PivotsType;
 
+#if ISCOMPLEX
+#define EIGEN_LAPACK_ARG_IF_COMPLEX(X) X,
+#else
+#define EIGEN_LAPACK_ARG_IF_COMPLEX(X)
+#endif
 
 
 #endif // EIGEN_LAPACK_COMMON_H

Index: 3rd_party/eigen/lapack/single.cpp
==================================================================
--- 3rd_party/eigen/lapack/single.cpp
+++ 3rd_party/eigen/lapack/single.cpp
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -13,5 +13,6 @@
 #define ISCOMPLEX     0
 
 #include "cholesky.cpp"
 #include "lu.cpp"
 #include "eigenvalues.cpp"
+#include "svd.cpp"

ADDED   3rd_party/eigen/lapack/svd.cpp
Index: 3rd_party/eigen/lapack/svd.cpp
==================================================================
--- 3rd_party/eigen/lapack/svd.cpp
+++ 3rd_party/eigen/lapack/svd.cpp
@@ -0,0 +1,138 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "lapack_common.h"
+#include <Eigen/SVD>
+
+// computes the singular values/vectors a general M-by-N matrix A using divide-and-conquer
+EIGEN_LAPACK_FUNC(gesdd,(char *jobz, int *m, int* n, Scalar* a, int *lda, RealScalar *s, Scalar *u, int *ldu, Scalar *vt, int *ldvt, Scalar* /*work*/, int* lwork,
+                         EIGEN_LAPACK_ARG_IF_COMPLEX(RealScalar */*rwork*/) int * /*iwork*/, int *info))
+{
+  // TODO exploit the work buffer
+  bool query_size = *lwork==-1;
+  int diag_size = (std::min)(*m,*n);
+  
+  *info = 0;
+        if(*jobz!='A' && *jobz!='S' && *jobz!='O' && *jobz!='N')  *info = -1;
+  else  if(*m<0)                                                  *info = -2;
+  else  if(*n<0)                                                  *info = -3;
+  else  if(*lda<std::max(1,*m))                                   *info = -5;
+  else  if(*lda<std::max(1,*m))                                   *info = -8;
+  else  if(*ldu <1 || (*jobz=='A' && *ldu <*m)
+                   || (*jobz=='O' && *m<*n && *ldu<*m))           *info = -8;
+  else  if(*ldvt<1 || (*jobz=='A' && *ldvt<*n)
+                   || (*jobz=='S' && *ldvt<diag_size)
+                   || (*jobz=='O' && *m>=*n && *ldvt<*n))         *info = -10;
+  
+  if(*info!=0)
+  {
+    int e = -*info;
+    return xerbla_(SCALAR_SUFFIX_UP"GESDD ", &e, 6);
+  }
+  
+  if(query_size)
+  {
+    *lwork = 0;
+    return 0;
+  }
+  
+  if(*n==0 || *m==0)
+    return 0;
+  
+  PlainMatrixType mat(*m,*n);
+  mat = matrix(a,*m,*n,*lda);
+  
+  int option = *jobz=='A' ? ComputeFullU|ComputeFullV
+             : *jobz=='S' ? ComputeThinU|ComputeThinV
+             : *jobz=='O' ? ComputeThinU|ComputeThinV
+             : 0;
+
+  BDCSVD<PlainMatrixType> svd(mat,option);
+  
+  make_vector(s,diag_size) = svd.singularValues().head(diag_size);
+
+  if(*jobz=='A')
+  {
+    matrix(u,*m,*m,*ldu)   = svd.matrixU();
+    matrix(vt,*n,*n,*ldvt) = svd.matrixV().adjoint();
+  }
+  else if(*jobz=='S')
+  {
+    matrix(u,*m,diag_size,*ldu)   = svd.matrixU();
+    matrix(vt,diag_size,*n,*ldvt) = svd.matrixV().adjoint();
+  }
+  else if(*jobz=='O' && *m>=*n)
+  {
+    matrix(a,*m,*n,*lda)   = svd.matrixU();
+    matrix(vt,*n,*n,*ldvt) = svd.matrixV().adjoint();
+  }
+  else if(*jobz=='O')
+  {
+    matrix(u,*m,*m,*ldu)        = svd.matrixU();
+    matrix(a,diag_size,*n,*lda) = svd.matrixV().adjoint();
+  }
+    
+  return 0;
+}
+
+// computes the singular values/vectors a general M-by-N matrix A using two sided jacobi algorithm
+EIGEN_LAPACK_FUNC(gesvd,(char *jobu, char *jobv, int *m, int* n, Scalar* a, int *lda, RealScalar *s, Scalar *u, int *ldu, Scalar *vt, int *ldvt, Scalar* /*work*/, int* lwork,
+                         EIGEN_LAPACK_ARG_IF_COMPLEX(RealScalar */*rwork*/) int *info))
+{
+  // TODO exploit the work buffer
+  bool query_size = *lwork==-1;
+  int diag_size = (std::min)(*m,*n);
+  
+  *info = 0;
+        if( *jobu!='A' && *jobu!='S' && *jobu!='O' && *jobu!='N') *info = -1;
+  else  if((*jobv!='A' && *jobv!='S' && *jobv!='O' && *jobv!='N')
+           || (*jobu=='O' && *jobv=='O'))                         *info = -2;
+  else  if(*m<0)                                                  *info = -3;
+  else  if(*n<0)                                                  *info = -4;
+  else  if(*lda<std::max(1,*m))                                   *info = -6;
+  else  if(*ldu <1 || ((*jobu=='A' || *jobu=='S') && *ldu<*m))    *info = -9;
+  else  if(*ldvt<1 || (*jobv=='A' && *ldvt<*n)
+                   || (*jobv=='S' && *ldvt<diag_size))            *info = -11;
+  
+  if(*info!=0)
+  {
+    int e = -*info;
+    return xerbla_(SCALAR_SUFFIX_UP"GESVD ", &e, 6);
+  }
+  
+  if(query_size)
+  {
+    *lwork = 0;
+    return 0;
+  }
+  
+  if(*n==0 || *m==0)
+    return 0;
+  
+  PlainMatrixType mat(*m,*n);
+  mat = matrix(a,*m,*n,*lda);
+  
+  int option = (*jobu=='A' ? ComputeFullU : *jobu=='S' || *jobu=='O' ? ComputeThinU : 0)
+             | (*jobv=='A' ? ComputeFullV : *jobv=='S' || *jobv=='O' ? ComputeThinV : 0);
+  
+  JacobiSVD<PlainMatrixType> svd(mat,option);
+  
+  make_vector(s,diag_size) = svd.singularValues().head(diag_size);
+  {
+        if(*jobu=='A') matrix(u,*m,*m,*ldu)           = svd.matrixU();
+  else  if(*jobu=='S') matrix(u,*m,diag_size,*ldu)    = svd.matrixU();
+  else  if(*jobu=='O') matrix(a,*m,diag_size,*lda)    = svd.matrixU();
+  }
+  {
+        if(*jobv=='A') matrix(vt,*n,*n,*ldvt)         = svd.matrixV().adjoint();
+  else  if(*jobv=='S') matrix(vt,diag_size,*n,*ldvt)  = svd.matrixV().adjoint();
+  else  if(*jobv=='O') matrix(a,diag_size,*n,*lda)    = svd.matrixV().adjoint();
+  }
+  return 0;
+}

Index: 3rd_party/eigen/scripts/buildtests.in
==================================================================
--- 3rd_party/eigen/scripts/buildtests.in
+++ 3rd_party/eigen/scripts/buildtests.in
@@ -1,10 +1,10 @@
 #!/bin/bash
 
 if [[ $# != 1 || $1 == *help ]]
 then
-  echo "usage: ./check regexp"
+  echo "usage: $0 regexp"
   echo "  Builds tests matching the regexp."
   echo "  The EIGEN_MAKE_ARGS environment variable allows to pass args to 'make'."
   echo "    For example, to launch 5 concurrent builds, use EIGEN_MAKE_ARGS='-j5'"
   exit 0
 fi
@@ -12,11 +12,11 @@
 TESTSLIST="@EIGEN_TESTS_LIST@"
 targets_to_make=`echo "$TESTSLIST" | egrep "$1" | xargs echo`
 
 if [ -n "${EIGEN_MAKE_ARGS:+x}" ]
 then
-  make $targets_to_make ${EIGEN_MAKE_ARGS}
+  @CMAKE_MAKE_PROGRAM@ $targets_to_make ${EIGEN_MAKE_ARGS}
 else
-  make $targets_to_make
+  @CMAKE_MAKE_PROGRAM@ $targets_to_make @EIGEN_TEST_BUILD_FLAGS@
 fi
 exit $?
 

Index: 3rd_party/eigen/scripts/check.in
==================================================================
--- 3rd_party/eigen/scripts/check.in
+++ 3rd_party/eigen/scripts/check.in
@@ -1,11 +1,11 @@
 #!/bin/bash
 # check : shorthand for make and ctest -R
 
 if [[ $# != 1 || $1 == *help ]]
 then
-  echo "usage: ./check regexp"
+  echo "usage: $0 regexp"
   echo "  Builds and runs tests matching the regexp."
   echo "  The EIGEN_MAKE_ARGS environment variable allows to pass args to 'make'."
   echo "    For example, to launch 5 concurrent builds, use EIGEN_MAKE_ARGS='-j5'"
   echo "  The EIGEN_CTEST_ARGS environment variable allows to pass args to 'ctest'."
   echo "    For example, with CTest 2.8, you can use EIGEN_CTEST_ARGS='-j5'."

Index: 3rd_party/eigen/scripts/eigen_gen_docs
==================================================================
--- 3rd_party/eigen/scripts/eigen_gen_docs
+++ 3rd_party/eigen/scripts/eigen_gen_docs
@@ -2,11 +2,11 @@
 
 # configuration
 # You should call this script with USER set as you want, else some default
 # will be used
 USER=${USER:-'orzel'}
-UPLOAD_DIR=dox
+UPLOAD_DIR=dox-devel
 
 #ulimit -v 1024000
 
 # step 1 : build
 rm build/doc/html -Rf

Index: 3rd_party/eigen/test/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/test/CMakeLists.txt
+++ 3rd_party/eigen/test/CMakeLists.txt
@@ -1,24 +1,40 @@
-
-# generate split test header file
-message(STATUS ${CMAKE_CURRENT_BINARY_DIR})
-file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h "")
-foreach(i RANGE 1 999)
-  file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h
-    "#ifdef EIGEN_TEST_PART_${i}\n"
-    "#define CALL_SUBTEST_${i}(FUNC) CALL_SUBTEST(FUNC)\n"
-    "#else\n"
-    "#define CALL_SUBTEST_${i}(FUNC)\n"
-    "#endif\n\n"
-    )
-endforeach()
+# generate split test header file only if it does not yet exist
+# in order to prevent a rebuild everytime cmake is configured
+if(NOT EXISTS ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h)  
+  file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h "")
+  foreach(i RANGE 1 999)
+    file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h
+      "#ifdef EIGEN_TEST_PART_${i}\n"
+      "#define CALL_SUBTEST_${i}(FUNC) CALL_SUBTEST(FUNC)\n"
+      "#else\n"
+      "#define CALL_SUBTEST_${i}(FUNC)\n"
+      "#endif\n\n"
+    )
+  endforeach()
+endif()
+
+# check if we have a Fortran compiler
+include("../cmake/language_support.cmake")
+
+workaround_9220(Fortran EIGEN_Fortran_COMPILER_WORKS)
+
+if(EIGEN_Fortran_COMPILER_WORKS)
+  enable_language(Fortran OPTIONAL)
+  if(NOT CMAKE_Fortran_COMPILER)
+    set(EIGEN_Fortran_COMPILER_WORKS OFF)
+  endif()
+endif()
+
+if(NOT EIGEN_Fortran_COMPILER_WORKS)
+  # search for a default Lapack library to complete Eigen's one
+  find_package(LAPACK QUIET)
+endif()
 
 # configure blas/lapack (use Eigen's ones)
-set(BLAS_FOUND TRUE)
-set(LAPACK_FOUND TRUE)
-set(BLAS_LIBRARIES eigen_blas)
-set(LAPACK_LIBRARIES eigen_lapack)
+set(EIGEN_BLAS_LIBRARIES eigen_blas)
+set(EIGEN_LAPACK_LIBRARIES eigen_lapack)
 
 set(EIGEN_TEST_MATRIX_DIR "" CACHE STRING "Enable testing of realword sparse matrices contained in the specified path")
 if(EIGEN_TEST_MATRIX_DIR)
   if(NOT WIN32)
     message(STATUS "Test realworld sparse matrices: ${EIGEN_TEST_MATRIX_DIR}")
@@ -29,84 +45,89 @@
 endif(EIGEN_TEST_MATRIX_DIR)
 
 set(SPARSE_LIBS " ")
 
 find_package(Cholmod)
-if(CHOLMOD_FOUND AND BLAS_FOUND AND LAPACK_FOUND)
+if(CHOLMOD_FOUND)
   add_definitions("-DEIGEN_CHOLMOD_SUPPORT")
   include_directories(${CHOLMOD_INCLUDES})
-  set(SPARSE_LIBS ${SPARSE_LIBS} ${CHOLMOD_LIBRARIES} ${BLAS_LIBRARIES} ${LAPACK_LIBRARIES})
-  set(CHOLMOD_ALL_LIBS  ${CHOLMOD_LIBRARIES} ${BLAS_LIBRARIES} ${LAPACK_LIBRARIES})
+  set(SPARSE_LIBS ${SPARSE_LIBS} ${CHOLMOD_LIBRARIES} ${EIGEN_BLAS_LIBRARIES} ${EIGEN_LAPACK_LIBRARIES})
+  set(CHOLMOD_ALL_LIBS  ${CHOLMOD_LIBRARIES} ${EIGEN_BLAS_LIBRARIES} ${EIGEN_LAPACK_LIBRARIES})
   ei_add_property(EIGEN_TESTED_BACKENDS "Cholmod, ")
 else()
   ei_add_property(EIGEN_MISSING_BACKENDS "Cholmod, ")
 endif()
 
 find_package(Umfpack)
-if(UMFPACK_FOUND AND BLAS_FOUND)
+if(UMFPACK_FOUND)
   add_definitions("-DEIGEN_UMFPACK_SUPPORT")
   include_directories(${UMFPACK_INCLUDES})
-  set(SPARSE_LIBS ${SPARSE_LIBS} ${UMFPACK_LIBRARIES} ${BLAS_LIBRARIES})
-  set(UMFPACK_ALL_LIBS ${UMFPACK_LIBRARIES} ${BLAS_LIBRARIES})
+  set(SPARSE_LIBS ${SPARSE_LIBS} ${UMFPACK_LIBRARIES} ${EIGEN_BLAS_LIBRARIES})
+  set(UMFPACK_ALL_LIBS ${UMFPACK_LIBRARIES} ${EIGEN_BLAS_LIBRARIES})
   ei_add_property(EIGEN_TESTED_BACKENDS "UmfPack, ")
 else()
   ei_add_property(EIGEN_MISSING_BACKENDS "UmfPack, ")
 endif()
 
-find_package(SuperLU)
-if(SUPERLU_FOUND AND BLAS_FOUND)
+find_package(SuperLU 4.0)
+if(SUPERLU_FOUND)
   add_definitions("-DEIGEN_SUPERLU_SUPPORT")
   include_directories(${SUPERLU_INCLUDES})
-  set(SPARSE_LIBS ${SPARSE_LIBS} ${SUPERLU_LIBRARIES} ${BLAS_LIBRARIES})
-  set(SUPERLU_ALL_LIBS ${SUPERLU_LIBRARIES} ${BLAS_LIBRARIES})
+  set(SPARSE_LIBS ${SPARSE_LIBS} ${SUPERLU_LIBRARIES} ${EIGEN_BLAS_LIBRARIES})
+  set(SUPERLU_ALL_LIBS ${SUPERLU_LIBRARIES} ${EIGEN_BLAS_LIBRARIES})
   ei_add_property(EIGEN_TESTED_BACKENDS  "SuperLU, ")
 else()
   ei_add_property(EIGEN_MISSING_BACKENDS  "SuperLU, ")
 endif()
 
 
-find_package(Pastix)
-find_package(Scotch)
-find_package(Metis 5.0 REQUIRED)
-if(PASTIX_FOUND AND BLAS_FOUND)
+find_package(PASTIX QUIET COMPONENTS METIS SCOTCH)
+# check that the PASTIX found is a version without MPI
+find_path(PASTIX_pastix_nompi.h_INCLUDE_DIRS
+  NAMES pastix_nompi.h
+  HINTS ${PASTIX_INCLUDE_DIRS}
+)
+if (NOT PASTIX_pastix_nompi.h_INCLUDE_DIRS)
+  message(STATUS "A version of Pastix has been found but pastix_nompi.h does not exist in the include directory."
+                 " Because Eigen tests require a version without MPI, we disable the Pastix backend.")
+endif()
+if(PASTIX_FOUND AND PASTIX_pastix_nompi.h_INCLUDE_DIRS)
   add_definitions("-DEIGEN_PASTIX_SUPPORT")
-  include_directories(${PASTIX_INCLUDES})
+  include_directories(${PASTIX_INCLUDE_DIRS_DEP})
   if(SCOTCH_FOUND)
-    include_directories(${SCOTCH_INCLUDES})
+    include_directories(${SCOTCH_INCLUDE_DIRS})
     set(PASTIX_LIBRARIES ${PASTIX_LIBRARIES} ${SCOTCH_LIBRARIES})
   elseif(METIS_FOUND)
-    include_directories(${METIS_INCLUDES})
+    include_directories(${METIS_INCLUDE_DIRS})
     set(PASTIX_LIBRARIES ${PASTIX_LIBRARIES} ${METIS_LIBRARIES})
   else(SCOTCH_FOUND)
     ei_add_property(EIGEN_MISSING_BACKENDS  "PaStiX, ")
   endif(SCOTCH_FOUND)
-  set(SPARSE_LIBS ${SPARSE_LIBS} ${PASTIX_LIBRARIES} ${ORDERING_LIBRARIES} ${BLAS_LIBRARIES})
-  set(PASTIX_ALL_LIBS ${PASTIX_LIBRARIES} ${BLAS_LIBRARIES})
+  set(SPARSE_LIBS ${SPARSE_LIBS} ${PASTIX_LIBRARIES_DEP} ${ORDERING_LIBRARIES})
+  set(PASTIX_ALL_LIBS ${PASTIX_LIBRARIES_DEP})
   ei_add_property(EIGEN_TESTED_BACKENDS  "PaStiX, ")
 else()
   ei_add_property(EIGEN_MISSING_BACKENDS  "PaStiX, ")
 endif()
 
 if(METIS_FOUND)
   add_definitions("-DEIGEN_METIS_SUPPORT")
-  include_directories(${METIS_INCLUDES})
+  include_directories(${METIS_INCLUDE_DIRS})
   ei_add_property(EIGEN_TESTED_BACKENDS "METIS, ")
 else()
   ei_add_property(EIGEN_MISSING_BACKENDS "METIS, ")
 endif()
 
 find_package(SPQR)
-if(SPQR_FOUND AND BLAS_FOUND AND LAPACK_FOUND)
-  if(CHOLMOD_FOUND)
-    add_definitions("-DEIGEN_SPQR_SUPPORT")
-    include_directories(${SPQR_INCLUDES})
-    set(SPQR_ALL_LIBS ${SPQR_LIBRARIES} ${CHOLMOD_LIBRARIES} ${LAPACK_LIBRARIES} ${BLAS_LIBRARIES})
-    set(SPARSE_LIBS ${SPARSE_LIBS} ${SPQR_ALL_LIBS})
-    ei_add_property(EIGEN_TESTED_BACKENDS "SPQR, ")
-  else(CHOLMOD_FOUND)
-    ei_add_property(EIGEN_MISSING_BACKENDS "SPQR, ")
-  endif(CHOLMOD_FOUND)
+if(SPQR_FOUND AND CHOLMOD_FOUND AND (EIGEN_Fortran_COMPILER_WORKS OR LAPACK_FOUND) )
+  add_definitions("-DEIGEN_SPQR_SUPPORT")
+  include_directories(${SPQR_INCLUDES})
+  set(SPQR_ALL_LIBS ${SPQR_LIBRARIES} ${CHOLMOD_LIBRARIES} ${EIGEN_LAPACK_LIBRARIES} ${EIGEN_BLAS_LIBRARIES} ${LAPACK_LIBRARIES})
+  set(SPARSE_LIBS ${SPARSE_LIBS} ${SPQR_ALL_LIBS})
+  ei_add_property(EIGEN_TESTED_BACKENDS "SPQR, ")
+else()
+  ei_add_property(EIGEN_MISSING_BACKENDS "SPQR, ")
 endif()
 
 option(EIGEN_TEST_NOQT "Disable Qt support in unit tests" OFF)
 if(NOT EIGEN_TEST_NOQT)
   find_package(Qt4)
@@ -123,29 +144,37 @@
 endif(TEST_LIB)
 
 set_property(GLOBAL PROPERTY EIGEN_CURRENT_SUBPROJECT "Official")
 add_custom_target(BuildOfficial)
 
+ei_add_test(rand)
 ei_add_test(meta)
+ei_add_test(numext)
 ei_add_test(sizeof)
 ei_add_test(dynalloc)
 ei_add_test(nomalloc)
 ei_add_test(first_aligned)
+ei_add_test(nullary)
 ei_add_test(mixingtypes)
-ei_add_test(packetmath)
+ei_add_test(packetmath "-DEIGEN_FAST_MATH=1")
 ei_add_test(unalignedassert)
 ei_add_test(vectorization_logic)
 ei_add_test(basicstuff)
+ei_add_test(constructor)
 ei_add_test(linearstructure)
 ei_add_test(integer_types)
-ei_add_test(cwiseop)
 ei_add_test(unalignedcount)
-ei_add_test(exceptions)
+if(NOT EIGEN_TEST_NO_EXCEPTIONS)
+  ei_add_test(exceptions)
+endif()
 ei_add_test(redux)
 ei_add_test(visitor)
 ei_add_test(block)
 ei_add_test(corners)
+ei_add_test(swap)
+ei_add_test(resize)
+ei_add_test(conservative_resize)
 ei_add_test(product_small)
 ei_add_test(product_large)
 ei_add_test(product_extra)
 ei_add_test(diagonalmatrices)
 ei_add_test(adjoint)
@@ -159,10 +188,11 @@
 ei_add_test(array)
 ei_add_test(array_for_matrix)
 ei_add_test(array_replicate)
 ei_add_test(array_reverse)
 ei_add_test(ref)
+ei_add_test(is_same_dense)
 ei_add_test(triangular)
 ei_add_test(selfadjoint)
 ei_add_test(product_selfadjoint)
 ei_add_test(product_symm)
 ei_add_test(product_syrk)
@@ -170,10 +200,11 @@
 ei_add_test(product_trmm)
 ei_add_test(product_trsolve)
 ei_add_test(product_mmtr)
 ei_add_test(product_notemporary)
 ei_add_test(stable_norm)
+ei_add_test(permutationmatrices)
 ei_add_test(bandmatrix)
 ei_add_test(cholesky)
 ei_add_test(lu)
 ei_add_test(determinant)
 ei_add_test(inverse)
@@ -189,56 +220,79 @@
 ei_add_test(eigensolver_complex)
 ei_add_test(real_qz)
 ei_add_test(eigensolver_generalized_real)
 ei_add_test(jacobi)
 ei_add_test(jacobisvd)
+ei_add_test(bdcsvd)
+ei_add_test(householder)
 ei_add_test(geo_orthomethods)
-ei_add_test(geo_homogeneous)
 ei_add_test(geo_quaternion)
-ei_add_test(geo_transformations)
 ei_add_test(geo_eulerangles)
-ei_add_test(geo_hyperplane)
 ei_add_test(geo_parametrizedline)
 ei_add_test(geo_alignedbox)
+ei_add_test(geo_hyperplane)
+ei_add_test(geo_transformations)
+ei_add_test(geo_homogeneous)
 ei_add_test(stdvector)
 ei_add_test(stdvector_overload)
 ei_add_test(stdlist)
+ei_add_test(stdlist_overload)
 ei_add_test(stddeque)
-ei_add_test(resize)
-ei_add_test(sparse_vector)
+ei_add_test(stddeque_overload)
 ei_add_test(sparse_basic)
+ei_add_test(sparse_block)
+ei_add_test(sparse_vector)
 ei_add_test(sparse_product)
+ei_add_test(sparse_ref)
 ei_add_test(sparse_solvers)
-ei_add_test(umeyama)
-ei_add_test(householder)
-ei_add_test(swap)
-ei_add_test(conservative_resize)
-ei_add_test(permutationmatrices)
 ei_add_test(sparse_permutations)
-ei_add_test(nullary)
+ei_add_test(simplicial_cholesky)
+ei_add_test(conjugate_gradient)
+ei_add_test(incomplete_cholesky)
+ei_add_test(bicgstab)
+ei_add_test(lscg)
+ei_add_test(sparselu)
+ei_add_test(sparseqr)
+ei_add_test(umeyama)
 ei_add_test(nesting_ops "${CMAKE_CXX_FLAGS_DEBUG}")
 ei_add_test(zerosized)
 ei_add_test(dontalign)
-ei_add_test(sizeoverflow)
+ei_add_test(evaluators)
+if(NOT EIGEN_TEST_NO_EXCEPTIONS)
+  ei_add_test(sizeoverflow)
+endif()
 ei_add_test(prec_inverse_4x4)
 ei_add_test(vectorwiseop)
 ei_add_test(special_numbers)
-
-ei_add_test(simplicial_cholesky)
-ei_add_test(conjugate_gradient)
-ei_add_test(bicgstab)
-ei_add_test(sparselu)
-ei_add_test(sparseqr)
-
-# ei_add_test(denseLM)
+ei_add_test(rvalue_types)
+ei_add_test(dense_storage)
+ei_add_test(ctorleak)
+ei_add_test(mpl2only)
+ei_add_test(inplace_decomposition)
+ei_add_test(half_float)
+ei_add_test(array_of_string)
+
+add_executable(bug1213 bug1213.cpp bug1213_main.cpp)
+
+check_cxx_compiler_flag("-ffast-math" COMPILER_SUPPORT_FASTMATH)
+if(COMPILER_SUPPORT_FASTMATH)
+  set(EIGEN_FASTMATH_FLAGS "-ffast-math")
+else()
+  check_cxx_compiler_flag("/fp:fast" COMPILER_SUPPORT_FPFAST)
+  if(COMPILER_SUPPORT_FPFAST)
+    set(EIGEN_FASTMATH_FLAGS "/fp:fast")
+  endif()
+endif()
+
+ei_add_test(fastmath " ${EIGEN_FASTMATH_FLAGS} ")
+
+# # ei_add_test(denseLM)
 
 if(QT4_FOUND)
   ei_add_test(qtvector "" "${QT_QTCORE_LIBRARY}")
 endif(QT4_FOUND)
 
-ei_add_test(eigen2support)
-
 if(UMFPACK_FOUND)
   ei_add_test(umfpack_support "" "${UMFPACK_ALL_LIBS}")
 endif()
 
 if(SUPERLU_FOUND)
@@ -279,7 +333,58 @@
 ei_add_property(EIGEN_TESTING_SUMMARY "Sparse lib flags:  ${SPARSE_LIBS}\n")
 
 option(EIGEN_TEST_EIGEN2 "Run whole Eigen2 test suite against EIGEN2_SUPPORT" OFF)
 mark_as_advanced(EIGEN_TEST_EIGEN2)
 if(EIGEN_TEST_EIGEN2)
-  add_subdirectory(eigen2)
+  message(WARNING "The Eigen2 test suite has been removed")
+endif()
+
+# boost MP unit test
+find_package(Boost)
+if(Boost_FOUND)
+  include_directories(${Boost_INCLUDE_DIRS})
+  ei_add_test(boostmultiprec "" "${Boost_LIBRARIES}")
+  ei_add_property(EIGEN_TESTED_BACKENDS "Boost.Multiprecision, ")
+else()
+  ei_add_property(EIGEN_MISSING_BACKENDS "Boost.Multiprecision, ")
+endif()
+
+
+# CUDA unit tests
+option(EIGEN_TEST_CUDA "Enable CUDA support in unit tests" OFF)
+option(EIGEN_TEST_CUDA_CLANG "Use clang instead of nvcc to compile the CUDA tests" OFF)
+
+if(EIGEN_TEST_CUDA_CLANG AND NOT CMAKE_CXX_COMPILER MATCHES "clang")
+  message(WARNING "EIGEN_TEST_CUDA_CLANG is set, but CMAKE_CXX_COMPILER does not appear to be clang.")
 endif()
+
+if(EIGEN_TEST_CUDA)
+
+find_package(CUDA 5.0)
+if(CUDA_FOUND)
+  
+  set(CUDA_PROPAGATE_HOST_FLAGS OFF)
+  if("${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang") 
+    set(CUDA_NVCC_FLAGS "-ccbin ${CMAKE_C_COMPILER}" CACHE STRING "nvcc flags" FORCE)
+  endif()
+  if(EIGEN_TEST_CUDA_CLANG)
+   set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 --cuda-gpu-arch=sm_30")
+  endif()
+  cuda_include_directories(${CMAKE_CURRENT_BINARY_DIR})
+  set(EIGEN_ADD_TEST_FILENAME_EXTENSION  "cu")
+  
+  ei_add_test(cuda_basic)
+  
+  unset(EIGEN_ADD_TEST_FILENAME_EXTENSION)
+
+endif(CUDA_FOUND)
+
+endif(EIGEN_TEST_CUDA)
+
+
+file(MAKE_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/failtests)    
+add_test(NAME failtests WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/failtests COMMAND ${CMAKE_COMMAND} ${Eigen_SOURCE_DIR} -G "${CMAKE_GENERATOR}" -DEIGEN_FAILTEST=ON)
+
+option(EIGEN_TEST_BUILD_DOCUMENTATION "Test building the doxygen documentation" OFF)
+IF(EIGEN_TEST_BUILD_DOCUMENTATION)
+  add_dependencies(buildtests doc)
+ENDIF()

Index: 3rd_party/eigen/test/adjoint.cpp
==================================================================
--- 3rd_party/eigen/test/adjoint.cpp
+++ 3rd_party/eigen/test/adjoint.cpp
@@ -40,10 +40,21 @@
     v3 = v1;
     v3.normalize();
     VERIFY_IS_APPROX(v1, v1.norm() * v3);
     VERIFY_IS_APPROX(v3, v1.normalized());
     VERIFY_IS_APPROX(v3.norm(), RealScalar(1));
+
+    // check null inputs
+    VERIFY_IS_APPROX((v1*0).normalized(), (v1*0));
+#if (!EIGEN_ARCH_i386) || defined(EIGEN_VECTORIZE)
+    RealScalar very_small = (std::numeric_limits<RealScalar>::min)();
+    VERIFY( (v1*very_small).norm() == 0 );
+    VERIFY_IS_APPROX((v1*very_small).normalized(), (v1*very_small));
+    v3 = v1*very_small;
+    v3.normalize();
+    VERIFY_IS_APPROX(v3, (v1*very_small));
+#endif
     
     // check compatibility of dot and adjoint
     ref = NumTraits<Scalar>::IsInteger ? 0 : (std::max)((std::max)(v1.norm(),v2.norm()),(std::max)((square * v2).norm(),(square.adjoint() * v1).norm()));
     VERIFY(internal::isMuchSmallerThan(abs(v1.dot(square * v2) - (square.adjoint() * v1).dot(v2)), ref, test_precision<Scalar>()));
     
@@ -62,10 +73,11 @@
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
+  const Index PacketSize = internal::packet_traits<Scalar>::size;
   
   Index rows = m.rows();
   Index cols = m.cols();
 
   MatrixType m1 = MatrixType::Random(rows, cols),
@@ -106,10 +118,21 @@
   m3 = m1;
   m3.transposeInPlace();
   VERIFY_IS_APPROX(m3,m1.transpose());
   m3.transposeInPlace();
   VERIFY_IS_APPROX(m3,m1);
+  
+  if(PacketSize<m3.rows() && PacketSize<m3.cols())
+  {
+    m3 = m1;
+    Index i = internal::random<Index>(0,m3.rows()-PacketSize);
+    Index j = internal::random<Index>(0,m3.cols()-PacketSize);
+    m3.template block<PacketSize,PacketSize>(i,j).transposeInPlace();
+    VERIFY_IS_APPROX( (m3.template block<PacketSize,PacketSize>(i,j)), (m1.template block<PacketSize,PacketSize>(i,j).transpose()) );
+    m3.template block<PacketSize,PacketSize>(i,j).transposeInPlace();
+    VERIFY_IS_APPROX(m3,m1);
+  }
 
   // check inplace adjoint
   m3 = m1;
   m3.adjointInPlace();
   VERIFY_IS_APPROX(m3,m1.adjoint());
@@ -127,18 +150,28 @@
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( adjoint(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_2( adjoint(Matrix3d()) );
     CALL_SUBTEST_3( adjoint(Matrix4f()) );
+    
     CALL_SUBTEST_4( adjoint(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
     CALL_SUBTEST_5( adjoint(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_6( adjoint(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    
+    // Complement for 128 bits vectorization:
+    CALL_SUBTEST_8( adjoint(Matrix2d()) );
+    CALL_SUBTEST_9( adjoint(Matrix<int,4,4>()) );
+    
+    // 256 bits vectorization:
+    CALL_SUBTEST_10( adjoint(Matrix<float,8,8>()) );
+    CALL_SUBTEST_11( adjoint(Matrix<double,4,4>()) );
+    CALL_SUBTEST_12( adjoint(Matrix<int,8,8>()) );
   }
   // test a large static matrix only once
   CALL_SUBTEST_7( adjoint(Matrix<float, 100, 100>()) );
 
-#ifdef EIGEN_TEST_PART_4
+#ifdef EIGEN_TEST_PART_13
   {
     MatrixXcf a(10,10), b(10,10);
     VERIFY_RAISES_ASSERT(a = a.transpose());
     VERIFY_RAISES_ASSERT(a = a.transpose() + b);
     VERIFY_RAISES_ASSERT(a = b + a.transpose());
@@ -152,9 +185,16 @@
     a.transpose() += a.transpose();
     a.transpose() += a.transpose() + b;
     a.transpose() = a.adjoint();
     a.transpose() += a.adjoint();
     a.transpose() += a.adjoint() + b;
+
+    // regression tests for check_for_aliasing
+    MatrixXd c(10,10);
+    c = 1.0 * MatrixXd::Ones(10,10) + c;
+    c = MatrixXd::Ones(10,10) * 1.0 + c;
+    c = c + MatrixXd::Ones(10,10) .cwiseProduct( MatrixXd::Zero(10,10) );
+    c = MatrixXd::Ones(10,10) * MatrixXd::Zero(10,10);
   }
 #endif
 }
 

Index: 3rd_party/eigen/test/array.cpp
==================================================================
--- 3rd_party/eigen/test/array.cpp
+++ 3rd_party/eigen/test/array.cpp
@@ -11,19 +11,22 @@
 
 template<typename ArrayType> void array(const ArrayType& m)
 {
   typedef typename ArrayType::Index Index;
   typedef typename ArrayType::Scalar Scalar;
+  typedef typename ArrayType::RealScalar RealScalar;
   typedef Array<Scalar, ArrayType::RowsAtCompileTime, 1> ColVectorType;
   typedef Array<Scalar, 1, ArrayType::ColsAtCompileTime> RowVectorType;
 
   Index rows = m.rows();
   Index cols = m.cols(); 
 
   ArrayType m1 = ArrayType::Random(rows, cols),
              m2 = ArrayType::Random(rows, cols),
              m3(rows, cols);
+  ArrayType m4 = m1; // copy constructor
+  VERIFY_IS_APPROX(m1, m4);
 
   ColVectorType cv1 = ColVectorType::Random(rows);
   RowVectorType rv1 = RowVectorType::Random(cols);
 
   Scalar  s1 = internal::random<Scalar>(),
@@ -68,11 +71,11 @@
   using std::abs;
   VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.colwise().sum().sum() - m1.sum()), m1.abs().sum());
   VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.rowwise().sum().sum() - m1.sum()), m1.abs().sum());
   if (!internal::isMuchSmallerThan(abs(m1.sum() - (m1+m2).sum()), m1.abs().sum(), test_precision<Scalar>()))
       VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum());
-  VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar>()));
+  VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>()));
 
   // vector-wise ops
   m3 = m1;
   VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1);
   m3 = m1;
@@ -79,10 +82,51 @@
   VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1);
   m3 = m1;
   VERIFY_IS_APPROX(m3.rowwise() += rv1, m1.rowwise() + rv1);
   m3 = m1;
   VERIFY_IS_APPROX(m3.rowwise() -= rv1, m1.rowwise() - rv1);
+  
+  // Conversion from scalar
+  VERIFY_IS_APPROX((m3 = s1), ArrayType::Constant(rows,cols,s1));
+  VERIFY_IS_APPROX((m3 = 1),  ArrayType::Constant(rows,cols,1));
+  VERIFY_IS_APPROX((m3.topLeftCorner(rows,cols) = 1),  ArrayType::Constant(rows,cols,1));
+  typedef Array<Scalar,
+                ArrayType::RowsAtCompileTime==Dynamic?2:ArrayType::RowsAtCompileTime,
+                ArrayType::ColsAtCompileTime==Dynamic?2:ArrayType::ColsAtCompileTime,
+                ArrayType::Options> FixedArrayType;
+  FixedArrayType f1(s1);
+  VERIFY_IS_APPROX(f1, FixedArrayType::Constant(s1));
+  FixedArrayType f2(numext::real(s1));
+  VERIFY_IS_APPROX(f2, FixedArrayType::Constant(numext::real(s1)));
+  FixedArrayType f3((int)100*numext::real(s1));
+  VERIFY_IS_APPROX(f3, FixedArrayType::Constant((int)100*numext::real(s1)));
+  f1.setRandom();
+  FixedArrayType f4(f1.data());
+  VERIFY_IS_APPROX(f4, f1);
+  
+  // pow
+  VERIFY_IS_APPROX(m1.pow(2), m1.square());
+  VERIFY_IS_APPROX(pow(m1,2), m1.square());
+  VERIFY_IS_APPROX(m1.pow(3), m1.cube());
+  VERIFY_IS_APPROX(pow(m1,3), m1.cube());
+  VERIFY_IS_APPROX((-m1).pow(3), -m1.cube());
+  VERIFY_IS_APPROX(pow(2*m1,3), 8*m1.cube());
+  ArrayType exponents = ArrayType::Constant(rows, cols, RealScalar(2));
+  VERIFY_IS_APPROX(Eigen::pow(m1,exponents), m1.square());
+  VERIFY_IS_APPROX(m1.pow(exponents), m1.square());
+  VERIFY_IS_APPROX(Eigen::pow(2*m1,exponents), 4*m1.square());
+  VERIFY_IS_APPROX((2*m1).pow(exponents), 4*m1.square());
+  VERIFY_IS_APPROX(Eigen::pow(m1,2*exponents), m1.square().square());
+  VERIFY_IS_APPROX(m1.pow(2*exponents), m1.square().square());
+  VERIFY_IS_APPROX(Eigen::pow(m1(0,0), exponents), ArrayType::Constant(rows,cols,m1(0,0)*m1(0,0)));
+
+  // Check possible conflicts with 1D ctor
+  typedef Array<Scalar, Dynamic, 1> OneDArrayType;
+  OneDArrayType o1(rows);
+  VERIFY(o1.size()==rows);
+  OneDArrayType o4((int)rows);
+  VERIFY(o4.size()==rows);
 }
 
 template<typename ArrayType> void comparisons(const ArrayType& m)
 {
   using std::abs;
@@ -95,12 +139,15 @@
 
   Index r = internal::random<Index>(0, rows-1),
         c = internal::random<Index>(0, cols-1);
 
   ArrayType m1 = ArrayType::Random(rows, cols),
-             m2 = ArrayType::Random(rows, cols),
-             m3(rows, cols);            
+            m2 = ArrayType::Random(rows, cols),
+            m3(rows, cols),
+            m4 = m1;
+  
+  m4 = (m4.abs()==Scalar(0)).select(1,m4);
 
   VERIFY(((m1 + Scalar(1)) > m1).all());
   VERIFY(((m1 - Scalar(1)) < m1).all());
   if (rows*cols>1)
   {
@@ -107,16 +154,24 @@
     m3 = m1;
     m3(r,c) += 1;
     VERIFY(! (m1 < m3).all() );
     VERIFY(! (m1 > m3).all() );
   }
+  VERIFY(!(m1 > m2 && m1 < m2).any());
+  VERIFY((m1 <= m2 || m1 >= m2).all());
 
-  // comparisons to scalar
+  // comparisons array to scalar
   VERIFY( (m1 != (m1(r,c)+1) ).any() );
-  VERIFY( (m1 > (m1(r,c)-1) ).any() );
-  VERIFY( (m1 < (m1(r,c)+1) ).any() );
-  VERIFY( (m1 == m1(r,c) ).any() );
+  VERIFY( (m1 >  (m1(r,c)-1) ).any() );
+  VERIFY( (m1 <  (m1(r,c)+1) ).any() );
+  VERIFY( (m1 ==  m1(r,c)    ).any() );
+
+  // comparisons scalar to array
+  VERIFY( ( (m1(r,c)+1) != m1).any() );
+  VERIFY( ( (m1(r,c)-1) <  m1).any() );
+  VERIFY( ( (m1(r,c)+1) >  m1).any() );
+  VERIFY( (  m1(r,c)    == m1).any() );
 
   // test Select
   VERIFY_IS_APPROX( (m1<m2).select(m1,m2), m1.cwiseMin(m2) );
   VERIFY_IS_APPROX( (m1>m2).select(m1,m2), m1.cwiseMax(m2) );
   Scalar mid = (m1.cwiseAbs().minCoeff() + m1.cwiseAbs().maxCoeff())/Scalar(2);
@@ -160,79 +215,213 @@
   Index rows = m.rows();
   Index cols = m.cols();
 
   ArrayType m1 = ArrayType::Random(rows, cols),
             m2 = ArrayType::Random(rows, cols),
-            m3(rows, cols);
+            m3(rows, cols),
+            m4 = m1;
+
+  m4 = (m4.abs()==Scalar(0)).select(1,m4);
 
   Scalar  s1 = internal::random<Scalar>();
 
-  // these tests are mostly to check possible compilation issues.
+  // these tests are mostly to check possible compilation issues with free-functions.
   VERIFY_IS_APPROX(m1.sin(), sin(m1));
   VERIFY_IS_APPROX(m1.cos(), cos(m1));
+  VERIFY_IS_APPROX(m1.tan(), tan(m1));
   VERIFY_IS_APPROX(m1.asin(), asin(m1));
   VERIFY_IS_APPROX(m1.acos(), acos(m1));
-  VERIFY_IS_APPROX(m1.tan(), tan(m1));
-  
+  VERIFY_IS_APPROX(m1.atan(), atan(m1));
+  VERIFY_IS_APPROX(m1.sinh(), sinh(m1));
+  VERIFY_IS_APPROX(m1.cosh(), cosh(m1));
+  VERIFY_IS_APPROX(m1.tanh(), tanh(m1));
+
+  VERIFY_IS_APPROX(m1.arg(), arg(m1));
+  VERIFY_IS_APPROX(m1.round(), round(m1));
+  VERIFY_IS_APPROX(m1.floor(), floor(m1));
+  VERIFY_IS_APPROX(m1.ceil(), ceil(m1));
+  VERIFY((m1.isNaN() == (Eigen::isnan)(m1)).all());
+  VERIFY((m1.isInf() == (Eigen::isinf)(m1)).all());
+  VERIFY((m1.isFinite() == (Eigen::isfinite)(m1)).all());
+  VERIFY_IS_APPROX(m1.inverse(), inverse(m1));
+  VERIFY_IS_APPROX(m1.abs(), abs(m1));
+  VERIFY_IS_APPROX(m1.abs2(), abs2(m1));
+  VERIFY_IS_APPROX(m1.square(), square(m1));
+  VERIFY_IS_APPROX(m1.cube(), cube(m1));
   VERIFY_IS_APPROX(cos(m1+RealScalar(3)*m2), cos((m1+RealScalar(3)*m2).eval()));
+  VERIFY_IS_APPROX(m1.sign(), sign(m1));
+
+
+  // avoid NaNs with abs() so verification doesn't fail
+  m3 = m1.abs();
+  VERIFY_IS_APPROX(m3.sqrt(), sqrt(abs(m1)));
+  VERIFY_IS_APPROX(m3.rsqrt(), Scalar(1)/sqrt(abs(m1)));
+  VERIFY_IS_APPROX(rsqrt(m3), Scalar(1)/sqrt(abs(m1)));
+  VERIFY_IS_APPROX(m3.log(), log(m3));
+  VERIFY_IS_APPROX(m3.log1p(), log1p(m3));
+  VERIFY_IS_APPROX(m3.log10(), log10(m3));
+
+
+  VERIFY((!(m1>m2) == (m1<=m2)).all());
 
-  VERIFY_IS_APPROX(m1.abs().sqrt(), sqrt(abs(m1)));
-  VERIFY_IS_APPROX(m1.abs(), sqrt(numext::abs2(m1)));
+  VERIFY_IS_APPROX(sin(m1.asin()), m1);
+  VERIFY_IS_APPROX(cos(m1.acos()), m1);
+  VERIFY_IS_APPROX(tan(m1.atan()), m1);
+  VERIFY_IS_APPROX(sinh(m1), 0.5*(exp(m1)-exp(-m1)));
+  VERIFY_IS_APPROX(cosh(m1), 0.5*(exp(m1)+exp(-m1)));
+  VERIFY_IS_APPROX(tanh(m1), (0.5*(exp(m1)-exp(-m1)))/(0.5*(exp(m1)+exp(-m1))));
+  VERIFY_IS_APPROX(arg(m1), ((m1<0).template cast<Scalar>())*std::acos(-1.0));
+  VERIFY((round(m1) <= ceil(m1) && round(m1) >= floor(m1)).all());
+  VERIFY((Eigen::isnan)((m1*0.0)/0.0).all());
+  VERIFY((Eigen::isinf)(m4/0.0).all());
+  VERIFY(((Eigen::isfinite)(m1) && (!(Eigen::isfinite)(m1*0.0/0.0)) && (!(Eigen::isfinite)(m4/0.0))).all());
+  VERIFY_IS_APPROX(inverse(inverse(m1)),m1);
+  VERIFY((abs(m1) == m1 || abs(m1) == -m1).all());
+  VERIFY_IS_APPROX(m3, sqrt(abs2(m1)));
+  VERIFY_IS_APPROX( m1.sign(), -(-m1).sign() );
+  VERIFY_IS_APPROX( m1*m1.sign(),m1.abs());
+  VERIFY_IS_APPROX(m1.sign() * m1.abs(), m1);
 
   VERIFY_IS_APPROX(numext::abs2(numext::real(m1)) + numext::abs2(numext::imag(m1)), numext::abs2(m1));
   VERIFY_IS_APPROX(numext::abs2(real(m1)) + numext::abs2(imag(m1)), numext::abs2(m1));
   if(!NumTraits<Scalar>::IsComplex)
     VERIFY_IS_APPROX(numext::real(m1), m1);
 
   // shift argument of logarithm so that it is not zero
   Scalar smallNumber = NumTraits<Scalar>::dummy_precision();
-  VERIFY_IS_APPROX((m1.abs() + smallNumber).log() , log(abs(m1) + smallNumber));
+  VERIFY_IS_APPROX((m3 + smallNumber).log() , log(abs(m1) + smallNumber));
+  VERIFY_IS_APPROX((m3 + smallNumber + 1).log() , log1p(abs(m1) + smallNumber));
 
   VERIFY_IS_APPROX(m1.exp() * m2.exp(), exp(m1+m2));
   VERIFY_IS_APPROX(m1.exp(), exp(m1));
   VERIFY_IS_APPROX(m1.exp() / m2.exp(),(m1-m2).exp());
 
-  VERIFY_IS_APPROX(m1.pow(2), m1.square());
-  VERIFY_IS_APPROX(pow(m1,2), m1.square());
-
-  ArrayType exponents = ArrayType::Constant(rows, cols, RealScalar(2));
-  VERIFY_IS_APPROX(Eigen::pow(m1,exponents), m1.square());
-
-  m3 = m1.abs();
   VERIFY_IS_APPROX(m3.pow(RealScalar(0.5)), m3.sqrt());
   VERIFY_IS_APPROX(pow(m3,RealScalar(0.5)), m3.sqrt());
+
+  VERIFY_IS_APPROX(m3.pow(RealScalar(-0.5)), m3.rsqrt());
+  VERIFY_IS_APPROX(pow(m3,RealScalar(-0.5)), m3.rsqrt());
+
+  VERIFY_IS_APPROX(log10(m3), log(m3)/log(10));
 
   // scalar by array division
   const RealScalar tiny = sqrt(std::numeric_limits<RealScalar>::epsilon());
   s1 += Scalar(tiny);
   m1 += ArrayType::Constant(rows,cols,Scalar(tiny));
   VERIFY_IS_APPROX(s1/m1, s1 * m1.inverse());
-  
+
   // check inplace transpose
   m3 = m1;
   m3.transposeInPlace();
-  VERIFY_IS_APPROX(m3,m1.transpose());
+  VERIFY_IS_APPROX(m3, m1.transpose());
   m3.transposeInPlace();
-  VERIFY_IS_APPROX(m3,m1);
+  VERIFY_IS_APPROX(m3, m1);
 }
 
 template<typename ArrayType> void array_complex(const ArrayType& m)
 {
   typedef typename ArrayType::Index Index;
+  typedef typename ArrayType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
 
   Index rows = m.rows();
   Index cols = m.cols();
 
   ArrayType m1 = ArrayType::Random(rows, cols),
-            m2(rows, cols);
+            m2(rows, cols),
+            m4 = m1;
+  
+  m4.real() = (m4.real().abs()==RealScalar(0)).select(RealScalar(1),m4.real());
+  m4.imag() = (m4.imag().abs()==RealScalar(0)).select(RealScalar(1),m4.imag());
+
+  Array<RealScalar, -1, -1> m3(rows, cols);
 
   for (Index i = 0; i < m.rows(); ++i)
     for (Index j = 0; j < m.cols(); ++j)
       m2(i,j) = sqrt(m1(i,j));
 
-  VERIFY_IS_APPROX(m1.sqrt(), m2);
-  VERIFY_IS_APPROX(m1.sqrt(), Eigen::sqrt(m1));
+  // these tests are mostly to check possible compilation issues with free-functions.
+  VERIFY_IS_APPROX(m1.sin(), sin(m1));
+  VERIFY_IS_APPROX(m1.cos(), cos(m1));
+  VERIFY_IS_APPROX(m1.tan(), tan(m1));
+  VERIFY_IS_APPROX(m1.sinh(), sinh(m1));
+  VERIFY_IS_APPROX(m1.cosh(), cosh(m1));
+  VERIFY_IS_APPROX(m1.tanh(), tanh(m1));
+  VERIFY_IS_APPROX(m1.arg(), arg(m1));
+  VERIFY((m1.isNaN() == (Eigen::isnan)(m1)).all());
+  VERIFY((m1.isInf() == (Eigen::isinf)(m1)).all());
+  VERIFY((m1.isFinite() == (Eigen::isfinite)(m1)).all());
+  VERIFY_IS_APPROX(m1.inverse(), inverse(m1));
+  VERIFY_IS_APPROX(m1.log(), log(m1));
+  VERIFY_IS_APPROX(m1.log10(), log10(m1));
+  VERIFY_IS_APPROX(m1.abs(), abs(m1));
+  VERIFY_IS_APPROX(m1.abs2(), abs2(m1));
+  VERIFY_IS_APPROX(m1.sqrt(), sqrt(m1));
+  VERIFY_IS_APPROX(m1.square(), square(m1));
+  VERIFY_IS_APPROX(m1.cube(), cube(m1));
+  VERIFY_IS_APPROX(cos(m1+RealScalar(3)*m2), cos((m1+RealScalar(3)*m2).eval()));
+  VERIFY_IS_APPROX(m1.sign(), sign(m1));
+
+
+  VERIFY_IS_APPROX(m1.exp() * m2.exp(), exp(m1+m2));
+  VERIFY_IS_APPROX(m1.exp(), exp(m1));
+  VERIFY_IS_APPROX(m1.exp() / m2.exp(),(m1-m2).exp());
+
+  VERIFY_IS_APPROX(sinh(m1), 0.5*(exp(m1)-exp(-m1)));
+  VERIFY_IS_APPROX(cosh(m1), 0.5*(exp(m1)+exp(-m1)));
+  VERIFY_IS_APPROX(tanh(m1), (0.5*(exp(m1)-exp(-m1)))/(0.5*(exp(m1)+exp(-m1))));
+
+  for (Index i = 0; i < m.rows(); ++i)
+    for (Index j = 0; j < m.cols(); ++j)
+      m3(i,j) = std::atan2(imag(m1(i,j)), real(m1(i,j)));
+  VERIFY_IS_APPROX(arg(m1), m3);
+
+  std::complex<RealScalar> zero(0.0,0.0);
+  VERIFY((Eigen::isnan)(m1*zero/zero).all());
+#if EIGEN_COMP_MSVC
+  // msvc complex division is not robust
+  VERIFY((Eigen::isinf)(m4/RealScalar(0)).all());
+#else
+#if EIGEN_COMP_CLANG
+  // clang's complex division is notoriously broken too
+  if((numext::isinf)(m4(0,0)/RealScalar(0))) {
+#endif
+    VERIFY((Eigen::isinf)(m4/zero).all());
+#if EIGEN_COMP_CLANG
+  }
+  else
+  {
+    VERIFY((Eigen::isinf)(m4.real()/zero.real()).all());
+  }
+#endif
+#endif // MSVC
+
+  VERIFY(((Eigen::isfinite)(m1) && (!(Eigen::isfinite)(m1*zero/zero)) && (!(Eigen::isfinite)(m1/zero))).all());
+
+  VERIFY_IS_APPROX(inverse(inverse(m1)),m1);
+  VERIFY_IS_APPROX(conj(m1.conjugate()), m1);
+  VERIFY_IS_APPROX(abs(m1), sqrt(square(real(m1))+square(imag(m1))));
+  VERIFY_IS_APPROX(abs(m1), sqrt(abs2(m1)));
+  VERIFY_IS_APPROX(log10(m1), log(m1)/log(10));
+
+  VERIFY_IS_APPROX( m1.sign(), -(-m1).sign() );
+  VERIFY_IS_APPROX( m1.sign() * m1.abs(), m1);
+
+  // scalar by array division
+  Scalar  s1 = internal::random<Scalar>();
+  const RealScalar tiny = std::sqrt(std::numeric_limits<RealScalar>::epsilon());
+  s1 += Scalar(tiny);
+  m1 += ArrayType::Constant(rows,cols,Scalar(tiny));
+  VERIFY_IS_APPROX(s1/m1, s1 * m1.inverse());
+
+  // check inplace transpose
+  m2 = m1;
+  m2.transposeInPlace();
+  VERIFY_IS_APPROX(m2, m1.transpose());
+  m2.transposeInPlace();
+  VERIFY_IS_APPROX(m2, m1);
+
 }
 
 template<typename ArrayType> void min_max(const ArrayType& m)
 {
   typedef typename ArrayType::Index Index;
@@ -297,10 +486,10 @@
   }
 
   VERIFY((internal::is_same< internal::global_math_functions_filtering_base<int>::type, int >::value));
   VERIFY((internal::is_same< internal::global_math_functions_filtering_base<float>::type, float >::value));
   VERIFY((internal::is_same< internal::global_math_functions_filtering_base<Array2i>::type, ArrayBase<Array2i> >::value));
-  typedef CwiseUnaryOp<internal::scalar_sum_op<double>, ArrayXd > Xpr;
+  typedef CwiseUnaryOp<internal::scalar_abs_op<double>, ArrayXd > Xpr;
   VERIFY((internal::is_same< internal::global_math_functions_filtering_base<Xpr>::type,
                            ArrayBase<Xpr>
                          >::value));
 }

Index: 3rd_party/eigen/test/array_for_matrix.cpp
==================================================================
--- 3rd_party/eigen/test/array_for_matrix.cpp
+++ 3rd_party/eigen/test/array_for_matrix.cpp
@@ -43,11 +43,11 @@
   // reductions
   VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum().sum() - m1.sum(), m1.squaredNorm());
   VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum().sum() - m1.sum(), m1.squaredNorm());
   VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum() + m2.colwise().sum() - (m1+m2).colwise().sum(), (m1+m2).squaredNorm());
   VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum() - m2.rowwise().sum() - (m1-m2).rowwise().sum(), (m1-m2).squaredNorm());
-  VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar>()));
+  VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>()));
 
   // vector-wise ops
   m3 = m1;
   VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1);
   m3 = m1;
@@ -66,10 +66,20 @@
   const Scalar& ref_m2 = m.matrix().array().coeffRef(0,0);
   const Scalar& ref_a1 = m.array().matrix().coeffRef(0);
   const Scalar& ref_a2 = m.array().matrix().coeffRef(0,0);
   VERIFY(&ref_a1 == &ref_m1);
   VERIFY(&ref_a2 == &ref_m2);
+
+  // Check write accessors:
+  m1.array().coeffRef(0,0) = 1;
+  VERIFY_IS_APPROX(m1(0,0),Scalar(1));
+  m1.array()(0,0) = 2;
+  VERIFY_IS_APPROX(m1(0,0),Scalar(2));
+  m1.array().matrix().coeffRef(0,0) = 3;
+  VERIFY_IS_APPROX(m1(0,0),Scalar(3));
+  m1.array().matrix()(0,0) = 4;
+  VERIFY_IS_APPROX(m1(0,0),Scalar(4));
 }
 
 template<typename MatrixType> void comparisons(const MatrixType& m)
 {
   using std::abs;
@@ -100,10 +110,11 @@
   // comparisons to scalar
   VERIFY( (m1.array() != (m1(r,c)+1) ).any() );
   VERIFY( (m1.array() > (m1(r,c)-1) ).any() );
   VERIFY( (m1.array() < (m1(r,c)+1) ).any() );
   VERIFY( (m1.array() == m1(r,c) ).any() );
+  VERIFY( m1.cwiseEqual(m1(r,c)).any() );
 
   // test Select
   VERIFY_IS_APPROX( (m1.array()<m2.array()).select(m1,m2), m1.cwiseMin(m2) );
   VERIFY_IS_APPROX( (m1.array()>m2.array()).select(m1,m2), m1.cwiseMax(m2) );
   Scalar mid = (m1.cwiseAbs().minCoeff() + m1.cwiseAbs().maxCoeff())/Scalar(2);
@@ -121,10 +132,16 @@
   VERIFY_IS_APPROX( (m1.array().abs()<mid).select(0,m1), m3);
 
   // count
   VERIFY(((m1.array().abs()+1)>RealScalar(0.1)).count() == rows*cols);
 
+  // and/or
+  VERIFY( ((m1.array()<RealScalar(0)).matrix() && (m1.array()>RealScalar(0)).matrix()).count() == 0);
+  VERIFY( ((m1.array()<RealScalar(0)).matrix() || (m1.array()>=RealScalar(0)).matrix()).count() == rows*cols);
+  RealScalar a = m1.cwiseAbs().mean();
+  VERIFY( ((m1.array()<-a).matrix() || (m1.array()>a).matrix()).count() == (m1.cwiseAbs().array()>a).count());
+
   typedef Matrix<typename MatrixType::Index, Dynamic, 1> VectorOfIndices;
 
   // TODO allows colwise/rowwise for array
   VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), VectorOfIndices::Constant(cols,rows).transpose());
   VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorOfIndices::Constant(rows, cols));
@@ -131,13 +148,25 @@
 }
 
 template<typename VectorType> void lpNorm(const VectorType& v)
 {
   using std::sqrt;
+  typedef typename VectorType::RealScalar RealScalar;
   VectorType u = VectorType::Random(v.size());
 
-  VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwiseAbs().maxCoeff());
+  if(v.size()==0)
+  {
+    VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), RealScalar(0));
+    VERIFY_IS_APPROX(u.template lpNorm<1>(), RealScalar(0));
+    VERIFY_IS_APPROX(u.template lpNorm<2>(), RealScalar(0));
+    VERIFY_IS_APPROX(u.template lpNorm<5>(), RealScalar(0));
+  }
+  else
+  {
+    VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwiseAbs().maxCoeff());
+  }
+
   VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwiseAbs().sum());
   VERIFY_IS_APPROX(u.template lpNorm<2>(), sqrt(u.array().abs().square().sum()));
   VERIFY_IS_APPROX(numext::pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.array().abs().pow(5).sum());
 }
 
@@ -204,15 +233,34 @@
   VERIFY(v.size()==cols);
   a1.matrix().resize(cols);
   VERIFY(a1.size()==cols);
 }
 
+template<int>
 void regression_bug_654()
 {
   ArrayXf a = RowVectorXf(3);
   VectorXf v = Array<float,1,Dynamic>(3);
 }
+
+// Check propagation of LvalueBit through Array/Matrix-Wrapper
+template<int>
+void regrrssion_bug_1410()
+{
+  const Matrix4i M;
+  const Array4i A;
+  ArrayWrapper<const Matrix4i> MA = M.array();
+  MA.row(0);
+  MatrixWrapper<const Array4i> AM = A.matrix();
+  AM.row(0);
+
+  VERIFY((internal::traits<ArrayWrapper<const Matrix4i> >::Flags&LvalueBit)==0);
+  VERIFY((internal::traits<MatrixWrapper<const Array4i> >::Flags&LvalueBit)==0);
+
+  VERIFY((internal::traits<ArrayWrapper<Matrix4i> >::Flags&LvalueBit)==LvalueBit);
+  VERIFY((internal::traits<MatrixWrapper<Array4i> >::Flags&LvalueBit)==LvalueBit);
+}
 
 void test_array_for_matrix()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( array_for_matrix(Matrix<float, 1, 1>()) );
@@ -242,12 +290,15 @@
     CALL_SUBTEST_7( lpNorm(Vector3d()) );
     CALL_SUBTEST_8( lpNorm(Vector4f()) );
     CALL_SUBTEST_5( lpNorm(VectorXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_4( lpNorm(VectorXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
   }
+  CALL_SUBTEST_5( lpNorm(VectorXf(0)) );
+  CALL_SUBTEST_4( lpNorm(VectorXcf(0)) );
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_4( resize(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_5( resize(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_6( resize(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
   }
-  CALL_SUBTEST_6( regression_bug_654() );
+  CALL_SUBTEST_6( regression_bug_654<0>() );
+  CALL_SUBTEST_6( regrrssion_bug_1410<0>() );
 }

ADDED   3rd_party/eigen/test/array_of_string.cpp
Index: 3rd_party/eigen/test/array_of_string.cpp
==================================================================
--- 3rd_party/eigen/test/array_of_string.cpp
+++ 3rd_party/eigen/test/array_of_string.cpp
@@ -0,0 +1,32 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+void test_array_of_string()
+{
+  typedef Array<std::string,1,Dynamic> ArrayXs;
+  ArrayXs a1(3), a2(3), a3(3), a3ref(3);
+  a1 << "one", "two", "three";
+  a2 << "1", "2", "3";
+  a3ref << "one (1)", "two (2)", "three (3)";
+  std::stringstream s1;
+  s1 << a1;
+  VERIFY_IS_EQUAL(s1.str(), std::string("  one    two  three"));
+  a3 = a1 + std::string(" (") + a2 + std::string(")");
+  VERIFY((a3==a3ref).all());
+
+  a3 = a1;
+  a3 += std::string(" (") + a2 + std::string(")");
+  VERIFY((a3==a3ref).all());
+
+  a1.swap(a3);
+  VERIFY((a1==a3ref).all());
+  VERIFY((a3!=a3ref).all());
+}

Index: 3rd_party/eigen/test/array_replicate.cpp
==================================================================
--- 3rd_party/eigen/test/array_replicate.cpp
+++ 3rd_party/eigen/test/array_replicate.cpp
@@ -42,10 +42,23 @@
 
   x2.resize(2*rows,3*cols);
   x2 << m2, m2, m2,
         m2, m2, m2;
   VERIFY_IS_APPROX(x2, (m2.template replicate<2,3>()));
+  
+  x2.resize(rows,3*cols);
+  x2 << m2, m2, m2;
+  VERIFY_IS_APPROX(x2, (m2.template replicate<1,3>()));
+  
+  vx1.resize(3*rows,cols);
+  vx1 << m2, m2, m2;
+  VERIFY_IS_APPROX(vx1+vx1, vx1+(m2.template replicate<3,1>()));
+  
+  vx1=m2+(m2.colwise().replicate(1));
+  
+  if(m2.cols()==1)
+    VERIFY_IS_APPROX(m2.coeff(0), (m2.template replicate<3,1>().coeff(m2.rows())));
 
   x2.resize(rows,f1);
   for (int j=0; j<f1; ++j)
     x2.col(j) = v1;
   VERIFY_IS_APPROX(x2, v1.rowwise().replicate(f1));

Index: 3rd_party/eigen/test/array_reverse.cpp
==================================================================
--- 3rd_party/eigen/test/array_reverse.cpp
+++ 3rd_party/eigen/test/array_reverse.cpp
@@ -22,11 +22,11 @@
   Index rows = m.rows();
   Index cols = m.cols();
 
   // this test relies a lot on Random.h, and there's not much more that we can do
   // to test it, hence I consider that we will have tested Random.h
-  MatrixType m1 = MatrixType::Random(rows, cols);
+  MatrixType m1 = MatrixType::Random(rows, cols), m2;
   VectorType v1 = VectorType::Random(rows);
 
   MatrixType m1_r = m1.reverse();
   // Verify that MatrixBase::reverse() works
   for ( int i = 0; i < rows; i++ ) {
@@ -94,35 +94,53 @@
   Index r = internal::random<Index>(0, rows-1),
         c = internal::random<Index>(0, cols-1);
 
   m1.reverse()(r, c) = x;
   VERIFY_IS_APPROX(x, m1(rows - 1 - r, cols - 1 - c));
+  
+  m2 = m1;
+  m2.reverseInPlace();
+  VERIFY_IS_APPROX(m2,m1.reverse().eval());
+  
+  m2 = m1;
+  m2.col(0).reverseInPlace();
+  VERIFY_IS_APPROX(m2.col(0),m1.col(0).reverse().eval());
+  
+  m2 = m1;
+  m2.row(0).reverseInPlace();
+  VERIFY_IS_APPROX(m2.row(0),m1.row(0).reverse().eval());
+  
+  m2 = m1;
+  m2.rowwise().reverseInPlace();
+  VERIFY_IS_APPROX(m2,m1.rowwise().reverse().eval());
+  
+  m2 = m1;
+  m2.colwise().reverseInPlace();
+  VERIFY_IS_APPROX(m2,m1.colwise().reverse().eval());
 
-  /*
   m1.colwise().reverse()(r, c) = x;
   VERIFY_IS_APPROX(x, m1(rows - 1 - r, c));
 
   m1.rowwise().reverse()(r, c) = x;
   VERIFY_IS_APPROX(x, m1(r, cols - 1 - c));
-  */
 }
 
 void test_array_reverse()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( reverse(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_2( reverse(Matrix2f()) );
     CALL_SUBTEST_3( reverse(Matrix4f()) );
     CALL_SUBTEST_4( reverse(Matrix4d()) );
-    CALL_SUBTEST_5( reverse(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_6( reverse(MatrixXi(6, 3)) );
-    CALL_SUBTEST_7( reverse(MatrixXcd(20, 20)) );
+    CALL_SUBTEST_5( reverse(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_6( reverse(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_7( reverse(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_8( reverse(Matrix<float, 100, 100>()) );
-    CALL_SUBTEST_9( reverse(Matrix<float,Dynamic,Dynamic,RowMajor>(6,3)) );
+    CALL_SUBTEST_9( reverse(Matrix<float,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
   }
 #ifdef EIGEN_TEST_PART_3
   Vector4f x; x << 1, 2, 3, 4;
   Vector4f y; y << 4, 3, 2, 1;
   VERIFY(x.reverse()[1] == 3);
   VERIFY(x.reverse() == y);
 #endif
 }

Index: 3rd_party/eigen/test/bandmatrix.cpp
==================================================================
--- 3rd_party/eigen/test/bandmatrix.cpp
+++ 3rd_party/eigen/test/bandmatrix.cpp
@@ -9,11 +9,10 @@
 
 #include "main.h"
 
 template<typename MatrixType> void bandmatrix(const MatrixType& _m)
 {
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrixType;
 
   Index rows = _m.rows();
@@ -60,15 +59,13 @@
 
 using Eigen::internal::BandMatrix;
 
 void test_bandmatrix()
 {
-  typedef BandMatrix<float>::Index Index;
-
   for(int i = 0; i < 10*g_repeat ; i++) {
     Index rows = internal::random<Index>(1,10);
     Index cols = internal::random<Index>(1,10);
     Index sups = internal::random<Index>(0,cols-1);
     Index subs = internal::random<Index>(0,rows-1);
     CALL_SUBTEST(bandmatrix(BandMatrix<float>(rows,cols,sups,subs)) );
   }
 }

Index: 3rd_party/eigen/test/basicstuff.cpp
==================================================================
--- 3rd_party/eigen/test/basicstuff.cpp
+++ 3rd_party/eigen/test/basicstuff.cpp
@@ -124,10 +124,24 @@
   
   sm2.setZero();
   for(typename MatrixType::Index i=0;i<rows;++i)
     sm2.col(i).noalias() -= sm1.row(i);
   VERIFY_IS_APPROX(sm2,-sm1.transpose());
+  
+  // check ternary usage
+  {
+    bool b = internal::random<int>(0,10)>5;
+    m3 = b ? m1 : m2;
+    if(b) VERIFY_IS_APPROX(m3,m1);
+    else  VERIFY_IS_APPROX(m3,m2);
+    m3 = b ? -m1 : m2;
+    if(b) VERIFY_IS_APPROX(m3,-m1);
+    else  VERIFY_IS_APPROX(m3,m2);
+    m3 = b ? m1 : -m2;
+    if(b) VERIFY_IS_APPROX(m3,m1);
+    else  VERIFY_IS_APPROX(m3,-m2);
+  }
 }
 
 template<typename MatrixType> void basicStuffComplex(const MatrixType& m)
 {
   typedef typename MatrixType::Index Index;
@@ -178,19 +192,68 @@
 #endif
 
 template <typename Scalar>
 void fixedSizeMatrixConstruction()
 {
-  const Scalar raw[3] = {1,2,3};
-  Matrix<Scalar,3,1> m(raw);
-  Array<Scalar,3,1> a(raw);
-  VERIFY(m(0) == 1);
-  VERIFY(m(1) == 2);
-  VERIFY(m(2) == 3);
-  VERIFY(a(0) == 1);
-  VERIFY(a(1) == 2);
-  VERIFY(a(2) == 3);  
+  Scalar raw[4];
+  for(int k=0; k<4; ++k)
+    raw[k] = internal::random<Scalar>();
+  
+  {
+    Matrix<Scalar,4,1> m(raw);
+    Array<Scalar,4,1> a(raw);
+    for(int k=0; k<4; ++k) VERIFY(m(k) == raw[k]);
+    for(int k=0; k<4; ++k) VERIFY(a(k) == raw[k]);    
+    VERIFY_IS_EQUAL(m,(Matrix<Scalar,4,1>(raw[0],raw[1],raw[2],raw[3])));
+    VERIFY((a==(Array<Scalar,4,1>(raw[0],raw[1],raw[2],raw[3]))).all());
+  }
+  {
+    Matrix<Scalar,3,1> m(raw);
+    Array<Scalar,3,1> a(raw);
+    for(int k=0; k<3; ++k) VERIFY(m(k) == raw[k]);
+    for(int k=0; k<3; ++k) VERIFY(a(k) == raw[k]);
+    VERIFY_IS_EQUAL(m,(Matrix<Scalar,3,1>(raw[0],raw[1],raw[2])));
+    VERIFY((a==Array<Scalar,3,1>(raw[0],raw[1],raw[2])).all());
+  }
+  {
+    Matrix<Scalar,2,1> m(raw), m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
+    Array<Scalar,2,1> a(raw),  a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
+    for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
+    for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
+    VERIFY_IS_EQUAL(m,(Matrix<Scalar,2,1>(raw[0],raw[1])));
+    VERIFY((a==Array<Scalar,2,1>(raw[0],raw[1])).all());
+    for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
+    for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
+  }
+  {
+    Matrix<Scalar,1,2> m(raw),
+                       m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ),
+                       m3( (int(raw[0])), (int(raw[1])) ),
+                       m4( (float(raw[0])), (float(raw[1])) );
+    Array<Scalar,1,2> a(raw),  a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
+    for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
+    for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
+    VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,2>(raw[0],raw[1])));
+    VERIFY((a==Array<Scalar,1,2>(raw[0],raw[1])).all());
+    for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
+    for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
+    for(int k=0; k<2; ++k) VERIFY(m3(k) == int(raw[k]));
+    for(int k=0; k<2; ++k) VERIFY((m4(k)) == Scalar(float(raw[k])));
+  }
+  {
+    Matrix<Scalar,1,1> m(raw), m1(raw[0]), m2( (DenseIndex(raw[0])) ), m3( (int(raw[0])) );
+    Array<Scalar,1,1> a(raw), a1(raw[0]), a2( (DenseIndex(raw[0])) );
+    VERIFY(m(0) == raw[0]);
+    VERIFY(a(0) == raw[0]);
+    VERIFY(m1(0) == raw[0]);
+    VERIFY(a1(0) == raw[0]);
+    VERIFY(m2(0) == DenseIndex(raw[0]));
+    VERIFY(a2(0) == DenseIndex(raw[0]));
+    VERIFY(m3(0) == int(raw[0]));
+    VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,1>(raw[0])));
+    VERIFY((a==Array<Scalar,1,1>(raw[0])).all());
+  }
 }
 
 void test_basicstuff()
 {
   for(int i = 0; i < g_repeat; i++) {
@@ -205,10 +268,13 @@
     CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
   }
 
   CALL_SUBTEST_1(fixedSizeMatrixConstruction<unsigned char>());
-  CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
+  CALL_SUBTEST_1(fixedSizeMatrixConstruction<float>());
   CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
+  CALL_SUBTEST_1(fixedSizeMatrixConstruction<int>());
+  CALL_SUBTEST_1(fixedSizeMatrixConstruction<long int>());
+  CALL_SUBTEST_1(fixedSizeMatrixConstruction<std::ptrdiff_t>());
 
   CALL_SUBTEST_2(casting());
 }

ADDED   3rd_party/eigen/test/bdcsvd.cpp
Index: 3rd_party/eigen/test/bdcsvd.cpp
==================================================================
--- 3rd_party/eigen/test/bdcsvd.cpp
+++ 3rd_party/eigen/test/bdcsvd.cpp
@@ -0,0 +1,111 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com>
+// Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr>
+// Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr>
+// Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/
+
+// discard stack allocation as that too bypasses malloc
+#define EIGEN_STACK_ALLOCATION_LIMIT 0
+#define EIGEN_RUNTIME_NO_MALLOC
+
+#include "main.h"
+#include <Eigen/SVD>
+#include <iostream>
+#include <Eigen/LU>
+
+
+#define SVD_DEFAULT(M) BDCSVD<M>
+#define SVD_FOR_MIN_NORM(M) BDCSVD<M>
+#include "svd_common.h"
+
+// Check all variants of JacobiSVD
+template<typename MatrixType>
+void bdcsvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
+{
+  MatrixType m = a;
+  if(pickrandom)
+    svd_fill_random(m);
+
+  CALL_SUBTEST(( svd_test_all_computation_options<BDCSVD<MatrixType> >(m, false)  ));
+}
+
+template<typename MatrixType>
+void bdcsvd_method()
+{
+  enum { Size = MatrixType::RowsAtCompileTime };
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef Matrix<RealScalar, Size, 1> RealVecType;
+  MatrixType m = MatrixType::Identity();
+  VERIFY_IS_APPROX(m.bdcSvd().singularValues(), RealVecType::Ones());
+  VERIFY_RAISES_ASSERT(m.bdcSvd().matrixU());
+  VERIFY_RAISES_ASSERT(m.bdcSvd().matrixV());
+  VERIFY_IS_APPROX(m.bdcSvd(ComputeFullU|ComputeFullV).solve(m), m);
+}
+
+// compare the Singular values returned with Jacobi and Bdc
+template<typename MatrixType> 
+void compare_bdc_jacobi(const MatrixType& a = MatrixType(), unsigned int computationOptions = 0)
+{
+  MatrixType m = MatrixType::Random(a.rows(), a.cols());
+  BDCSVD<MatrixType> bdc_svd(m);
+  JacobiSVD<MatrixType> jacobi_svd(m);
+  VERIFY_IS_APPROX(bdc_svd.singularValues(), jacobi_svd.singularValues());
+  if(computationOptions & ComputeFullU) VERIFY_IS_APPROX(bdc_svd.matrixU(), jacobi_svd.matrixU());
+  if(computationOptions & ComputeThinU) VERIFY_IS_APPROX(bdc_svd.matrixU(), jacobi_svd.matrixU());
+  if(computationOptions & ComputeFullV) VERIFY_IS_APPROX(bdc_svd.matrixV(), jacobi_svd.matrixV());
+  if(computationOptions & ComputeThinV) VERIFY_IS_APPROX(bdc_svd.matrixV(), jacobi_svd.matrixV());
+}
+
+void test_bdcsvd()
+{
+  CALL_SUBTEST_3(( svd_verify_assert<BDCSVD<Matrix3f>  >(Matrix3f()) ));
+  CALL_SUBTEST_4(( svd_verify_assert<BDCSVD<Matrix4d>  >(Matrix4d()) ));
+  CALL_SUBTEST_7(( svd_verify_assert<BDCSVD<MatrixXf>  >(MatrixXf(10,12)) ));
+  CALL_SUBTEST_8(( svd_verify_assert<BDCSVD<MatrixXcd> >(MatrixXcd(7,5)) ));
+  
+  CALL_SUBTEST_101(( svd_all_trivial_2x2(bdcsvd<Matrix2cd>) ));
+  CALL_SUBTEST_102(( svd_all_trivial_2x2(bdcsvd<Matrix2d>) ));
+
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_3(( bdcsvd<Matrix3f>() ));
+    CALL_SUBTEST_4(( bdcsvd<Matrix4d>() ));
+    CALL_SUBTEST_5(( bdcsvd<Matrix<float,3,5> >() ));
+
+    int r = internal::random<int>(1, EIGEN_TEST_MAX_SIZE/2),
+        c = internal::random<int>(1, EIGEN_TEST_MAX_SIZE/2);
+    
+    TEST_SET_BUT_UNUSED_VARIABLE(r)
+    TEST_SET_BUT_UNUSED_VARIABLE(c)
+    
+    CALL_SUBTEST_6((  bdcsvd(Matrix<double,Dynamic,2>(r,2)) ));
+    CALL_SUBTEST_7((  bdcsvd(MatrixXf(r,c)) ));
+    CALL_SUBTEST_7((  compare_bdc_jacobi(MatrixXf(r,c)) ));
+    CALL_SUBTEST_10(( bdcsvd(MatrixXd(r,c)) ));
+    CALL_SUBTEST_10(( compare_bdc_jacobi(MatrixXd(r,c)) ));
+    CALL_SUBTEST_8((  bdcsvd(MatrixXcd(r,c)) ));
+    CALL_SUBTEST_8((  compare_bdc_jacobi(MatrixXcd(r,c)) ));
+
+    // Test on inf/nan matrix
+    CALL_SUBTEST_7(  (svd_inf_nan<BDCSVD<MatrixXf>, MatrixXf>()) );
+    CALL_SUBTEST_10( (svd_inf_nan<BDCSVD<MatrixXd>, MatrixXd>()) );
+  }
+
+  // test matrixbase method
+  CALL_SUBTEST_1(( bdcsvd_method<Matrix2cd>() ));
+  CALL_SUBTEST_3(( bdcsvd_method<Matrix3f>() ));
+
+  // Test problem size constructors
+  CALL_SUBTEST_7( BDCSVD<MatrixXf>(10,10) );
+
+  // Check that preallocation avoids subsequent mallocs
+  CALL_SUBTEST_9( svd_preallocate<void>() );
+
+  CALL_SUBTEST_2( svd_underoverflow<void>() );
+}
+

Index: 3rd_party/eigen/test/bicgstab.cpp
==================================================================
--- 3rd_party/eigen/test/bicgstab.cpp
+++ 3rd_party/eigen/test/bicgstab.cpp
@@ -8,23 +8,27 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "sparse_solver.h"
 #include <Eigen/IterativeLinearSolvers>
 
-template<typename T> void test_bicgstab_T()
+template<typename T, typename I> void test_bicgstab_T()
 {
-  BiCGSTAB<SparseMatrix<T>, DiagonalPreconditioner<T> > bicgstab_colmajor_diag;
-  BiCGSTAB<SparseMatrix<T>, IdentityPreconditioner    > bicgstab_colmajor_I;
-  BiCGSTAB<SparseMatrix<T>, IncompleteLUT<T> >           bicgstab_colmajor_ilut;
+  BiCGSTAB<SparseMatrix<T,0,I>, DiagonalPreconditioner<T> >     bicgstab_colmajor_diag;
+  BiCGSTAB<SparseMatrix<T,0,I>, IdentityPreconditioner    >     bicgstab_colmajor_I;
+  BiCGSTAB<SparseMatrix<T,0,I>, IncompleteLUT<T,I> >              bicgstab_colmajor_ilut;
   //BiCGSTAB<SparseMatrix<T>, SSORPreconditioner<T> >     bicgstab_colmajor_ssor;
 
+  bicgstab_colmajor_diag.setTolerance(NumTraits<T>::epsilon()*4);
+  bicgstab_colmajor_ilut.setTolerance(NumTraits<T>::epsilon()*4);
+  
   CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_diag)  );
 //   CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_I)     );
   CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_ilut)     );
   //CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_ssor)     );
 }
 
 void test_bicgstab()
 {
-  CALL_SUBTEST_1(test_bicgstab_T<double>());
-  CALL_SUBTEST_2(test_bicgstab_T<std::complex<double> >());
+  CALL_SUBTEST_1((test_bicgstab_T<double,int>()) );
+  CALL_SUBTEST_2((test_bicgstab_T<std::complex<double>, int>()));
+  CALL_SUBTEST_3((test_bicgstab_T<double,long int>()));
 }

Index: 3rd_party/eigen/test/block.cpp
==================================================================
--- 3rd_party/eigen/test/block.cpp
+++ 3rd_party/eigen/test/block.cpp
@@ -128,10 +128,18 @@
   VERIFY(numext::real(ones.col(c1).sum()) == RealScalar(rows));
   VERIFY(numext::real(ones.row(r1).sum()) == RealScalar(cols));
 
   VERIFY(numext::real(ones.col(c1).dot(ones.col(c2))) == RealScalar(rows));
   VERIFY(numext::real(ones.row(r1).dot(ones.row(r2))) == RealScalar(cols));
+  
+  // chekc that linear acccessors works on blocks
+  m1 = m1_copy;
+  if((MatrixType::Flags&RowMajorBit)==0)
+    VERIFY_IS_EQUAL(m1.leftCols(c1).coeff(r1+c1*rows), m1(r1,c1));
+  else
+    VERIFY_IS_EQUAL(m1.topRows(r1).coeff(c1+r1*cols), m1(r1,c1));
+  
 
   // now test some block-inside-of-block.
   
   // expressions with direct access
   VERIFY_IS_EQUAL( (m1.block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2)) , (m1.block(r2,c2,rows-r2,cols-c2)) );
@@ -139,15 +147,15 @@
   VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , (m1.col(c1).segment(r1,r2-r1+1)) );
   VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , (m1.row(r1).segment(c1,c2-c1+1)).transpose() );
   VERIFY_IS_EQUAL( (m1.transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , (m1.row(r1).segment(c1,c2-c1+1)).transpose() );
 
   // expressions without direct access
-  VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2)) , ((m1+m2).block(r2,c2,rows-r2,cols-c2)) );
-  VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).row(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)) );
-  VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , ((m1+m2).col(c1).segment(r1,r2-r1+1)) );
-  VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)).transpose() );
-  VERIFY_IS_EQUAL( ((m1+m2).transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)).transpose() );
+  VERIFY_IS_APPROX( ((m1+m2).block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2)) , ((m1+m2).block(r2,c2,rows-r2,cols-c2)) );
+  VERIFY_IS_APPROX( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).row(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)) );
+  VERIFY_IS_APPROX( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , ((m1+m2).col(c1).segment(r1,r2-r1+1)) );
+  VERIFY_IS_APPROX( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)).transpose() );
+  VERIFY_IS_APPROX( ((m1+m2).transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)).transpose() );
 
   // evaluation into plain matrices from expressions with direct access (stress MapBase)
   DynamicMatrixType dm;
   DynamicVectorType dv;
   dm.setZero();
@@ -171,10 +179,23 @@
   dm.setZero();
   dv.setZero();
   dm = m1.row(r1).segment(c1,c2-c1+1).transpose();
   dv = m1.transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0);
   VERIFY_IS_EQUAL(dv, dm);
+
+  VERIFY_IS_EQUAL( (m1.template block<Dynamic,1>(1,0,0,1)), m1.block(1,0,0,1));
+  VERIFY_IS_EQUAL( (m1.template block<1,Dynamic>(0,1,1,0)), m1.block(0,1,1,0));
+  VERIFY_IS_EQUAL( ((m1*1).template block<Dynamic,1>(1,0,0,1)), m1.block(1,0,0,1));
+  VERIFY_IS_EQUAL( ((m1*1).template block<1,Dynamic>(0,1,1,0)), m1.block(0,1,1,0));
+
+  if (rows>=2 && cols>=2)
+  {
+    VERIFY_RAISES_ASSERT( m1 += m1.col(0) );
+    VERIFY_RAISES_ASSERT( m1 -= m1.col(0) );
+    VERIFY_RAISES_ASSERT( m1.array() *= m1.col(0).array() );
+    VERIFY_RAISES_ASSERT( m1.array() /= m1.col(0).array() );
+  }
 }
 
 
 template<typename MatrixType>
 void compare_using_data_and_stride(const MatrixType& m)

ADDED   3rd_party/eigen/test/boostmultiprec.cpp
Index: 3rd_party/eigen/test/boostmultiprec.cpp
==================================================================
--- 3rd_party/eigen/test/boostmultiprec.cpp
+++ 3rd_party/eigen/test/boostmultiprec.cpp
@@ -0,0 +1,201 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include <sstream>
+
+#ifdef EIGEN_TEST_MAX_SIZE
+#undef EIGEN_TEST_MAX_SIZE
+#endif
+
+#define EIGEN_TEST_MAX_SIZE 50
+
+#ifdef EIGEN_TEST_PART_1
+#include "cholesky.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_2
+#include "lu.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_3
+#include "qr.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_4
+#include "qr_colpivoting.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_5
+#include "qr_fullpivoting.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_6
+#include "eigensolver_selfadjoint.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_7
+#include "eigensolver_generic.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_8
+#include "eigensolver_generalized_real.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_9
+#include "jacobisvd.cpp"
+#endif
+
+#ifdef EIGEN_TEST_PART_10
+#include "bdcsvd.cpp"
+#endif
+
+#include <Eigen/Dense>
+
+#undef min
+#undef max
+#undef isnan
+#undef isinf
+#undef isfinite
+
+#include <boost/multiprecision/cpp_dec_float.hpp>
+#include <boost/multiprecision/number.hpp>
+#include <boost/math/special_functions.hpp>
+#include <boost/math/complex.hpp>
+
+namespace mp = boost::multiprecision;
+typedef mp::number<mp::cpp_dec_float<100>, mp::et_on> Real;
+
+namespace Eigen {
+  template<> struct NumTraits<Real> : GenericNumTraits<Real> {
+    static inline Real dummy_precision() { return 1e-50; }
+  };
+
+  template<typename T1,typename T2,typename T3,typename T4,typename T5>
+  struct NumTraits<boost::multiprecision::detail::expression<T1,T2,T3,T4,T5> > : NumTraits<Real> {};
+
+  template<>
+  Real test_precision<Real>() { return 1e-50; }
+
+  // needed in C++93 mode where number does not support explicit cast.
+  namespace internal {
+    template<typename NewType>
+    struct cast_impl<Real,NewType> {
+      static inline NewType run(const Real& x) {
+        return x.template convert_to<NewType>();
+      }
+    };
+
+    template<>
+    struct cast_impl<Real,std::complex<Real> > {
+      static inline std::complex<Real>  run(const Real& x) {
+        return std::complex<Real>(x);
+      }
+    };
+  }
+}
+
+namespace boost {
+namespace multiprecision {
+  // to make ADL works as expected:
+  using boost::math::isfinite;
+  using boost::math::isnan;
+  using boost::math::isinf;
+  using boost::math::copysign;
+  using boost::math::hypot;
+
+  // The following is needed for std::complex<Real>:
+  Real fabs(const Real& a) { return abs EIGEN_NOT_A_MACRO (a); }
+  Real fmax(const Real& a, const Real& b) { using std::max; return max(a,b); }
+
+  // some specialization for the unit tests:
+  inline bool test_isMuchSmallerThan(const Real& a, const Real& b) {
+    return internal::isMuchSmallerThan(a, b, test_precision<Real>());
+  }
+
+  inline bool test_isApprox(const Real& a, const Real& b) {
+    return internal::isApprox(a, b, test_precision<Real>());
+  }
+
+  inline bool test_isApproxOrLessThan(const Real& a, const Real& b) {
+    return internal::isApproxOrLessThan(a, b, test_precision<Real>());
+  }
+
+  Real get_test_precision(const Real&) {
+    return test_precision<Real>();
+  }
+
+  Real test_relative_error(const Real &a, const Real &b) {
+    using Eigen::numext::abs2;
+    return sqrt(abs2<Real>(a-b)/Eigen::numext::mini<Real>(abs2(a),abs2(b)));
+  }
+}
+}
+
+namespace Eigen {
+
+}
+
+void test_boostmultiprec()
+{
+  typedef Matrix<Real,Dynamic,Dynamic> Mat;
+  typedef Matrix<std::complex<Real>,Dynamic,Dynamic> MatC;
+
+  std::cout << "NumTraits<Real>::epsilon()         = " << NumTraits<Real>::epsilon() << std::endl;
+  std::cout << "NumTraits<Real>::dummy_precision() = " << NumTraits<Real>::dummy_precision() << std::endl;
+  std::cout << "NumTraits<Real>::lowest()          = " << NumTraits<Real>::lowest() << std::endl;
+  std::cout << "NumTraits<Real>::highest()         = " << NumTraits<Real>::highest() << std::endl;
+  std::cout << "NumTraits<Real>::digits10()        = " << NumTraits<Real>::digits10() << std::endl;
+
+  // chekc stream output
+  {
+    Mat A(10,10);
+    A.setRandom();
+    std::stringstream ss;
+    ss << A;
+  }
+  {
+    MatC A(10,10);
+    A.setRandom();
+    std::stringstream ss;
+    ss << A;
+  }
+
+  for(int i = 0; i < g_repeat; i++) {
+    int s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
+
+    CALL_SUBTEST_1( cholesky(Mat(s,s)) );
+
+    CALL_SUBTEST_2( lu_non_invertible<Mat>() );
+    CALL_SUBTEST_2( lu_invertible<Mat>() );
+    CALL_SUBTEST_2( lu_non_invertible<MatC>() );
+    CALL_SUBTEST_2( lu_invertible<MatC>() );
+
+    CALL_SUBTEST_3( qr(Mat(internal::random<int>(1,EIGEN_TEST_MAX_SIZE),internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_3( qr_invertible<Mat>() );
+
+    CALL_SUBTEST_4( qr<Mat>() );
+    CALL_SUBTEST_4( cod<Mat>() );
+    CALL_SUBTEST_4( qr_invertible<Mat>() );
+
+    CALL_SUBTEST_5( qr<Mat>() );
+    CALL_SUBTEST_5( qr_invertible<Mat>() );
+
+    CALL_SUBTEST_6( selfadjointeigensolver(Mat(s,s)) );
+
+    CALL_SUBTEST_7( eigensolver(Mat(s,s)) );
+
+    CALL_SUBTEST_8( generalized_eigensolver_real(Mat(s,s)) );
+
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+  }
+
+  CALL_SUBTEST_9(( jacobisvd(Mat(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) ));
+  CALL_SUBTEST_10(( bdcsvd(Mat(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) ));
+}
+

ADDED   3rd_party/eigen/test/bug1213.cpp
Index: 3rd_party/eigen/test/bug1213.cpp
==================================================================
--- 3rd_party/eigen/test/bug1213.cpp
+++ 3rd_party/eigen/test/bug1213.cpp
@@ -0,0 +1,13 @@
+
+// This anonymous enum is essential to trigger the linking issue
+enum {
+  Foo
+};
+
+#include "bug1213.h"
+
+bool bug1213_1(const Eigen::Vector3f& x)
+{
+  return bug1213_2(x);
+}
+

ADDED   3rd_party/eigen/test/bug1213.h
Index: 3rd_party/eigen/test/bug1213.h
==================================================================
--- 3rd_party/eigen/test/bug1213.h
+++ 3rd_party/eigen/test/bug1213.h
@@ -0,0 +1,8 @@
+
+#include <Eigen/Core>
+
+template<typename T, int dim>
+bool bug1213_2(const Eigen::Matrix<T,dim,1>& x);
+
+bool bug1213_1(const Eigen::Vector3f& x);
+

ADDED   3rd_party/eigen/test/bug1213_main.cpp
Index: 3rd_party/eigen/test/bug1213_main.cpp
==================================================================
--- 3rd_party/eigen/test/bug1213_main.cpp
+++ 3rd_party/eigen/test/bug1213_main.cpp
@@ -0,0 +1,18 @@
+
+// This is a regression unit regarding a weird linking issue with gcc.
+
+#include "bug1213.h"
+
+int main()
+{
+  return 0;
+}
+
+
+template<typename T, int dim>
+bool bug1213_2(const Eigen::Matrix<T,dim,1>& )
+{
+  return true;
+}
+
+template bool bug1213_2<float,3>(const Eigen::Vector3f&);

Index: 3rd_party/eigen/test/cholesky.cpp
==================================================================
--- 3rd_party/eigen/test/cholesky.cpp
+++ 3rd_party/eigen/test/cholesky.cpp
@@ -9,24 +9,21 @@
 
 #ifndef EIGEN_NO_ASSERTION_CHECKING
 #define EIGEN_NO_ASSERTION_CHECKING
 #endif
 
-static int nb_temporaries;
-
-#define EIGEN_DENSE_STORAGE_CTOR_PLUGIN { if(size!=0) nb_temporaries++; }
+#define TEST_ENABLE_TEMPORARY_TRACKING
 
 #include "main.h"
 #include <Eigen/Cholesky>
 #include <Eigen/QR>
 
-#define VERIFY_EVALUATION_COUNT(XPR,N) {\
-    nb_temporaries = 0; \
-    XPR; \
-    if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
-    VERIFY( (#XPR) && nb_temporaries==N ); \
-  }
+template<typename MatrixType, int UpLo>
+typename MatrixType::RealScalar matrix_l1_norm(const MatrixType& m) {
+  MatrixType symm = m.template selfadjointView<UpLo>();
+  return symm.cwiseAbs().colwise().sum().maxCoeff();
+}
 
 template<typename MatrixType,template <typename,int> class CholType> void test_chol_update(const MatrixType& symm)
 {
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
@@ -81,42 +78,55 @@
   {
     MatrixType a1 = MatrixType::Random(rows,cols);
     symm += a1 * a1.adjoint();
   }
 
-  // to test if really Cholesky only uses the upper triangular part, uncomment the following
-  // FIXME: currently that fails !!
-  //symm.template part<StrictlyLower>().setZero();
-
   {
     SquareMatrixType symmUp = symm.template triangularView<Upper>();
     SquareMatrixType symmLo = symm.template triangularView<Lower>();
-    
+
     LLT<SquareMatrixType,Lower> chollo(symmLo);
     VERIFY_IS_APPROX(symm, chollo.reconstructedMatrix());
     vecX = chollo.solve(vecB);
     VERIFY_IS_APPROX(symm * vecX, vecB);
     matX = chollo.solve(matB);
     VERIFY_IS_APPROX(symm * matX, matB);
+
+    const MatrixType symmLo_inverse = chollo.solve(MatrixType::Identity(rows,cols));
+    RealScalar rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Lower>(symmLo)) /
+                             matrix_l1_norm<MatrixType, Lower>(symmLo_inverse);
+    RealScalar rcond_est = chollo.rcond();
+    // Verify that the estimated condition number is within a factor of 10 of the
+    // truth.
+    VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
 
     // test the upper mode
     LLT<SquareMatrixType,Upper> cholup(symmUp);
     VERIFY_IS_APPROX(symm, cholup.reconstructedMatrix());
     vecX = cholup.solve(vecB);
     VERIFY_IS_APPROX(symm * vecX, vecB);
     matX = cholup.solve(matB);
     VERIFY_IS_APPROX(symm * matX, matB);
+
+    // Verify that the estimated condition number is within a factor of 10 of the
+    // truth.
+    const MatrixType symmUp_inverse = cholup.solve(MatrixType::Identity(rows,cols));
+    rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Upper>(symmUp)) /
+                             matrix_l1_norm<MatrixType, Upper>(symmUp_inverse);
+    rcond_est = cholup.rcond();
+    VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
+
 
     MatrixType neg = -symmLo;
     chollo.compute(neg);
     VERIFY(chollo.info()==NumericalIssue);
 
     VERIFY_IS_APPROX(MatrixType(chollo.matrixL().transpose().conjugate()), MatrixType(chollo.matrixU()));
     VERIFY_IS_APPROX(MatrixType(chollo.matrixU().transpose().conjugate()), MatrixType(chollo.matrixL()));
     VERIFY_IS_APPROX(MatrixType(cholup.matrixL().transpose().conjugate()), MatrixType(cholup.matrixU()));
     VERIFY_IS_APPROX(MatrixType(cholup.matrixU().transpose().conjugate()), MatrixType(cholup.matrixL()));
-    
+
     // test some special use cases of SelfCwiseBinaryOp:
     MatrixType m1 = MatrixType::Random(rows,cols), m2(rows,cols);
     m2 = m1;
     m2 += symmLo.template selfadjointView<Lower>().llt().solve(matB);
     VERIFY_IS_APPROX(m2, m1 + symmLo.template selfadjointView<Lower>().llt().solve(matB));
@@ -142,22 +152,41 @@
 
     SquareMatrixType symmUp = symm.template triangularView<Upper>();
     SquareMatrixType symmLo = symm.template triangularView<Lower>();
 
     LDLT<SquareMatrixType,Lower> ldltlo(symmLo);
+    VERIFY(ldltlo.info()==Success);
     VERIFY_IS_APPROX(symm, ldltlo.reconstructedMatrix());
     vecX = ldltlo.solve(vecB);
     VERIFY_IS_APPROX(symm * vecX, vecB);
     matX = ldltlo.solve(matB);
     VERIFY_IS_APPROX(symm * matX, matB);
+
+    const MatrixType symmLo_inverse = ldltlo.solve(MatrixType::Identity(rows,cols));
+    RealScalar rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Lower>(symmLo)) /
+                             matrix_l1_norm<MatrixType, Lower>(symmLo_inverse);
+    RealScalar rcond_est = ldltlo.rcond();
+    // Verify that the estimated condition number is within a factor of 10 of the
+    // truth.
+    VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
+
 
     LDLT<SquareMatrixType,Upper> ldltup(symmUp);
+    VERIFY(ldltup.info()==Success);
     VERIFY_IS_APPROX(symm, ldltup.reconstructedMatrix());
     vecX = ldltup.solve(vecB);
     VERIFY_IS_APPROX(symm * vecX, vecB);
     matX = ldltup.solve(matB);
     VERIFY_IS_APPROX(symm * matX, matB);
+
+    // Verify that the estimated condition number is within a factor of 10 of the
+    // truth.
+    const MatrixType symmUp_inverse = ldltup.solve(MatrixType::Identity(rows,cols));
+    rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Upper>(symmUp)) /
+                             matrix_l1_norm<MatrixType, Upper>(symmUp_inverse);
+    rcond_est = ldltup.rcond();
+    VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
 
     VERIFY_IS_APPROX(MatrixType(ldltlo.matrixL().transpose().conjugate()), MatrixType(ldltlo.matrixU()));
     VERIFY_IS_APPROX(MatrixType(ldltlo.matrixU().transpose().conjugate()), MatrixType(ldltlo.matrixL()));
     VERIFY_IS_APPROX(MatrixType(ldltup.matrixL().transpose().conjugate()), MatrixType(ldltup.matrixU()));
     VERIFY_IS_APPROX(MatrixType(ldltup.matrixU().transpose().conjugate()), MatrixType(ldltup.matrixL()));
@@ -183,11 +212,11 @@
 
     // check matrices coming from linear constraints with Lagrange multipliers
     if(rows>=3)
     {
       SquareMatrixType A = symm;
-      int c = internal::random<int>(0,rows-2);
+      Index c = internal::random<Index>(0,rows-2);
       A.bottomRightCorner(c,c).setZero();
       // Make sure a solution exists:
       vecX.setRandom();
       vecB = A * vecX;
       vecX.setZero();
@@ -194,15 +223,15 @@
       ldltlo.compute(A);
       VERIFY_IS_APPROX(A, ldltlo.reconstructedMatrix());
       vecX = ldltlo.solve(vecB);
       VERIFY_IS_APPROX(A * vecX, vecB);
     }
-    
+
     // check non-full rank matrices
     if(rows>=3)
     {
-      int r = internal::random<int>(1,rows-1);
+      Index r = internal::random<Index>(1,rows-1);
       Matrix<Scalar,Dynamic,Dynamic> a = Matrix<Scalar,Dynamic,Dynamic>::Random(rows,r);
       SquareMatrixType A = a * a.adjoint();
       // Make sure a solution exists:
       vecX.setRandom();
       vecB = A * vecX;
@@ -210,28 +239,43 @@
       ldltlo.compute(A);
       VERIFY_IS_APPROX(A, ldltlo.reconstructedMatrix());
       vecX = ldltlo.solve(vecB);
       VERIFY_IS_APPROX(A * vecX, vecB);
     }
-    
+
     // check matrices with a wide spectrum
     if(rows>=3)
     {
+      using std::pow;
+      using std::sqrt;
       RealScalar s = (std::min)(16,std::numeric_limits<RealScalar>::max_exponent10/8);
       Matrix<Scalar,Dynamic,Dynamic> a = Matrix<Scalar,Dynamic,Dynamic>::Random(rows,rows);
       Matrix<RealScalar,Dynamic,1> d =  Matrix<RealScalar,Dynamic,1>::Random(rows);
-      for(int k=0; k<rows; ++k)
-        d(k) = d(k)*std::pow(RealScalar(10),internal::random<RealScalar>(-s,s));
+      for(Index k=0; k<rows; ++k)
+        d(k) = d(k)*pow(RealScalar(10),internal::random<RealScalar>(-s,s));
       SquareMatrixType A = a * d.asDiagonal() * a.adjoint();
       // Make sure a solution exists:
       vecX.setRandom();
       vecB = A * vecX;
       vecX.setZero();
       ldltlo.compute(A);
       VERIFY_IS_APPROX(A, ldltlo.reconstructedMatrix());
       vecX = ldltlo.solve(vecB);
-      VERIFY_IS_APPROX(A * vecX, vecB);
+
+      if(ldltlo.vectorD().real().cwiseAbs().minCoeff()>RealScalar(0))
+      {
+        VERIFY_IS_APPROX(A * vecX,vecB);
+      }
+      else
+      {
+        RealScalar large_tol =  sqrt(test_precision<RealScalar>());
+        VERIFY((A * vecX).isApprox(vecB, large_tol));
+
+        ++g_test_level;
+        VERIFY_IS_APPROX(A * vecX,vecB);
+        --g_test_level;
+      }
     }
   }
 
   // update/downdate
   CALL_SUBTEST(( test_chol_update<SquareMatrixType,LLT>(symm)  ));
@@ -287,10 +331,11 @@
     }
 
     RealMatrixType symmLo = symm.template triangularView<Lower>();
 
     LDLT<RealMatrixType,Lower> ldltlo(symmLo);
+    VERIFY(ldltlo.info()==Success);
     VERIFY_IS_APPROX(symm, ldltlo.reconstructedMatrix());
     vecX = ldltlo.solve(vecB);
     VERIFY_IS_APPROX(symm * vecX, vecB);
 //     matX = ldltlo.solve(matB);
 //     VERIFY_IS_APPROX(symm * matX, matB);
@@ -312,49 +357,104 @@
   VectorType vecX = matA.ldlt().solve(vecB);
   VERIFY_IS_APPROX(matA * vecX, vecB);
 }
 
 // LDLT is not guaranteed to work for indefinite matrices, but happens to work fine if matrix is diagonal.
-// This test checks that LDLT reports correctly that matrix is indefinite. 
+// This test checks that LDLT reports correctly that matrix is indefinite.
 // See http://forum.kde.org/viewtopic.php?f=74&t=106942 and bug 736
 template<typename MatrixType> void cholesky_definiteness(const MatrixType& m)
 {
   eigen_assert(m.rows() == 2 && m.cols() == 2);
   MatrixType mat;
   LDLT<MatrixType> ldlt(2);
-  
+
   {
     mat << 1, 0, 0, -1;
     ldlt.compute(mat);
+    VERIFY(ldlt.info()==Success);
     VERIFY(!ldlt.isNegative());
     VERIFY(!ldlt.isPositive());
   }
   {
     mat << 1, 2, 2, 1;
     ldlt.compute(mat);
+    VERIFY(ldlt.info()==Success);
     VERIFY(!ldlt.isNegative());
     VERIFY(!ldlt.isPositive());
   }
   {
     mat << 0, 0, 0, 0;
     ldlt.compute(mat);
+    VERIFY(ldlt.info()==Success);
     VERIFY(ldlt.isNegative());
     VERIFY(ldlt.isPositive());
   }
   {
     mat << 0, 0, 0, 1;
     ldlt.compute(mat);
+    VERIFY(ldlt.info()==Success);
     VERIFY(!ldlt.isNegative());
     VERIFY(ldlt.isPositive());
   }
   {
     mat << -1, 0, 0, 0;
     ldlt.compute(mat);
+    VERIFY(ldlt.info()==Success);
     VERIFY(ldlt.isNegative());
     VERIFY(!ldlt.isPositive());
   }
 }
+
+template<typename>
+void cholesky_faillure_cases()
+{
+  MatrixXd mat;
+  LDLT<MatrixXd> ldlt;
+
+  {
+    mat.resize(2,2);
+    mat << 0, 1, 1, 0;
+    ldlt.compute(mat);
+    VERIFY_IS_NOT_APPROX(mat,ldlt.reconstructedMatrix());
+    VERIFY(ldlt.info()==NumericalIssue);
+  }
+#if (!EIGEN_ARCH_i386) || defined(EIGEN_VECTORIZE_SSE2)
+  {
+    mat.resize(3,3);
+    mat << -1, -3, 3,
+           -3, -8.9999999999999999999, 1,
+            3, 1, 0;
+    ldlt.compute(mat);
+    VERIFY(ldlt.info()==NumericalIssue);
+    VERIFY_IS_NOT_APPROX(mat,ldlt.reconstructedMatrix());
+  }
+#endif
+  {
+    mat.resize(3,3);
+    mat <<  1, 2, 3,
+            2, 4, 1,
+            3, 1, 0;
+    ldlt.compute(mat);
+    VERIFY(ldlt.info()==NumericalIssue);
+    VERIFY_IS_NOT_APPROX(mat,ldlt.reconstructedMatrix());
+  }
+
+  {
+    mat.resize(8,8);
+    mat <<  0.1, 0, -0.1, 0, 0, 0, 1, 0,
+            0, 4.24667, 0, 2.00333, 0, 0, 0, 0,
+            -0.1, 0, 0.2, 0, -0.1, 0, 0, 0,
+            0, 2.00333, 0, 8.49333, 0, 2.00333, 0, 0,
+            0, 0, -0.1, 0, 0.1, 0, 0, 1,
+            0, 0, 0, 2.00333, 0, 4.24667, 0, 0,
+            1, 0, 0, 0, 0, 0, 0, 0,
+            0, 0, 0, 0, 1, 0, 0, 0;
+    ldlt.compute(mat);
+    VERIFY(ldlt.info()==NumericalIssue);
+    VERIFY_IS_NOT_APPROX(mat,ldlt.reconstructedMatrix());
+  }
+}
 
 template<typename MatrixType> void cholesky_verify_assert()
 {
   MatrixType tmp;
 
@@ -382,14 +482,18 @@
     CALL_SUBTEST_3( cholesky(Matrix2d()) );
     CALL_SUBTEST_3( cholesky_bug241(Matrix2d()) );
     CALL_SUBTEST_3( cholesky_definiteness(Matrix2d()) );
     CALL_SUBTEST_4( cholesky(Matrix3f()) );
     CALL_SUBTEST_5( cholesky(Matrix4d()) );
+
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
     CALL_SUBTEST_2( cholesky(MatrixXd(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_6( cholesky_cplx(MatrixXcd(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
   }
 
   CALL_SUBTEST_4( cholesky_verify_assert<Matrix3f>() );
   CALL_SUBTEST_7( cholesky_verify_assert<Matrix3d>() );
   CALL_SUBTEST_8( cholesky_verify_assert<MatrixXf>() );
@@ -396,9 +500,10 @@
   CALL_SUBTEST_2( cholesky_verify_assert<MatrixXd>() );
 
   // Test problem size constructors
   CALL_SUBTEST_9( LLT<MatrixXf>(10) );
   CALL_SUBTEST_9( LDLT<MatrixXf>(10) );
-  
-  TEST_SET_BUT_UNUSED_VARIABLE(s)
+
+  CALL_SUBTEST_2( cholesky_faillure_cases<void>() );
+
   TEST_SET_BUT_UNUSED_VARIABLE(nb_temporaries)
 }

Index: 3rd_party/eigen/test/cholmod_support.cpp
==================================================================
--- 3rd_party/eigen/test/cholmod_support.cpp
+++ 3rd_party/eigen/test/cholmod_support.cpp
@@ -5,10 +5,11 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#define EIGEN_NO_DEBUG_SMALL_PRODUCT_BLOCKS
 #include "sparse_solver.h"
 
 #include <Eigen/CholmodSupport>
 
 template<typename T> void test_cholmod_T()
@@ -38,19 +39,19 @@
   check_sparse_spd_solving(chol_colmajor_upper);
   check_sparse_spd_solving(llt_colmajor_lower);
   check_sparse_spd_solving(llt_colmajor_upper);
   check_sparse_spd_solving(ldlt_colmajor_lower);
   check_sparse_spd_solving(ldlt_colmajor_upper);
-  
-//  check_sparse_spd_determinant(chol_colmajor_lower);
-//  check_sparse_spd_determinant(chol_colmajor_upper);
-//  check_sparse_spd_determinant(llt_colmajor_lower);
-//  check_sparse_spd_determinant(llt_colmajor_upper);
-//  check_sparse_spd_determinant(ldlt_colmajor_lower);
-//  check_sparse_spd_determinant(ldlt_colmajor_upper);
+
+  check_sparse_spd_determinant(chol_colmajor_lower);
+  check_sparse_spd_determinant(chol_colmajor_upper);
+  check_sparse_spd_determinant(llt_colmajor_lower);
+  check_sparse_spd_determinant(llt_colmajor_upper);
+  check_sparse_spd_determinant(ldlt_colmajor_lower);
+  check_sparse_spd_determinant(ldlt_colmajor_upper);
 }
 
 void test_cholmod_support()
 {
   CALL_SUBTEST_1(test_cholmod_T<double>());
   CALL_SUBTEST_2(test_cholmod_T<std::complex<double> >());
 }

Index: 3rd_party/eigen/test/commainitializer.cpp
==================================================================
--- 3rd_party/eigen/test/commainitializer.cpp
+++ 3rd_party/eigen/test/commainitializer.cpp
@@ -7,10 +7,66 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
 
+
+template<int M1, int M2, int N1, int N2>
+void test_blocks()
+{
+  Matrix<int, M1+M2, N1+N2> m_fixed;
+  MatrixXi m_dynamic(M1+M2, N1+N2);
+
+  Matrix<int, M1, N1> mat11; mat11.setRandom();
+  Matrix<int, M1, N2> mat12; mat12.setRandom();
+  Matrix<int, M2, N1> mat21; mat21.setRandom();
+  Matrix<int, M2, N2> mat22; mat22.setRandom();
+
+  MatrixXi matx11 = mat11, matx12 = mat12, matx21 = mat21, matx22 = mat22;
+
+  {
+    VERIFY_IS_EQUAL((m_fixed << mat11, mat12, mat21, matx22).finished(), (m_dynamic << mat11, matx12, mat21, matx22).finished());
+    VERIFY_IS_EQUAL((m_fixed.template topLeftCorner<M1,N1>()), mat11);
+    VERIFY_IS_EQUAL((m_fixed.template topRightCorner<M1,N2>()), mat12);
+    VERIFY_IS_EQUAL((m_fixed.template bottomLeftCorner<M2,N1>()), mat21);
+    VERIFY_IS_EQUAL((m_fixed.template bottomRightCorner<M2,N2>()), mat22);
+    VERIFY_IS_EQUAL((m_fixed << mat12, mat11, matx21, mat22).finished(), (m_dynamic << mat12, matx11, matx21, mat22).finished());
+  }
+
+  if(N1 > 0)
+  {
+    VERIFY_RAISES_ASSERT((m_fixed << mat11, mat12, mat11, mat21, mat22));
+    VERIFY_RAISES_ASSERT((m_fixed << mat11, mat12, mat21, mat21, mat22));
+  }
+  else
+  {
+    // allow insertion of zero-column blocks:
+    VERIFY_IS_EQUAL((m_fixed << mat11, mat12, mat11, mat11, mat21, mat21, mat22).finished(), (m_dynamic << mat12, mat22).finished());
+  }
+  if(M1 != M2)
+  {
+    VERIFY_RAISES_ASSERT((m_fixed << mat11, mat21, mat12, mat22));
+  }
+}
+
+
+template<int N>
+struct test_block_recursion
+{
+  static void run()
+  {
+    test_blocks<(N>>6)&3, (N>>4)&3, (N>>2)&3, N & 3>();
+    test_block_recursion<N-1>::run();
+  }
+};
+
+template<>
+struct test_block_recursion<-1>
+{
+  static void run() { }
+};
+
 void test_commainitializer()
 {
   Matrix3d m3;
   Matrix4d m4;
 
@@ -41,6 +97,10 @@
   m3 = Matrix3d::Random();
   m3 << vec[0].transpose(),
         4, 5, 6,
         vec[2].transpose();
   VERIFY_IS_APPROX(m3, ref);
+
+
+  // recursively test all block-sizes from 0 to 3:
+  test_block_recursion<(1<<8) - 1>();
 }

Index: 3rd_party/eigen/test/conjugate_gradient.cpp
==================================================================
--- 3rd_party/eigen/test/conjugate_gradient.cpp
+++ 3rd_party/eigen/test/conjugate_gradient.cpp
@@ -8,23 +8,27 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "sparse_solver.h"
 #include <Eigen/IterativeLinearSolvers>
 
-template<typename T> void test_conjugate_gradient_T()
+template<typename T, typename I> void test_conjugate_gradient_T()
 {
-  ConjugateGradient<SparseMatrix<T>, Lower> cg_colmajor_lower_diag;
-  ConjugateGradient<SparseMatrix<T>, Upper> cg_colmajor_upper_diag;
-  ConjugateGradient<SparseMatrix<T>, Lower, IdentityPreconditioner> cg_colmajor_lower_I;
-  ConjugateGradient<SparseMatrix<T>, Upper, IdentityPreconditioner> cg_colmajor_upper_I;
+  typedef SparseMatrix<T,0,I> SparseMatrixType;
+  ConjugateGradient<SparseMatrixType, Lower      > cg_colmajor_lower_diag;
+  ConjugateGradient<SparseMatrixType, Upper      > cg_colmajor_upper_diag;
+  ConjugateGradient<SparseMatrixType, Lower|Upper> cg_colmajor_loup_diag;
+  ConjugateGradient<SparseMatrixType, Lower, IdentityPreconditioner> cg_colmajor_lower_I;
+  ConjugateGradient<SparseMatrixType, Upper, IdentityPreconditioner> cg_colmajor_upper_I;
 
   CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_diag)  );
   CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_diag)  );
+  CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_loup_diag)   );
   CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_I)     );
   CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_I)     );
 }
 
 void test_conjugate_gradient()
 {
-  CALL_SUBTEST_1(test_conjugate_gradient_T<double>());
-  CALL_SUBTEST_2(test_conjugate_gradient_T<std::complex<double> >());
+  CALL_SUBTEST_1(( test_conjugate_gradient_T<double,int>() ));
+  CALL_SUBTEST_2(( test_conjugate_gradient_T<std::complex<double>, int>() ));
+  CALL_SUBTEST_3(( test_conjugate_gradient_T<double,long int>() ));
 }

ADDED   3rd_party/eigen/test/constructor.cpp
Index: 3rd_party/eigen/test/constructor.cpp
==================================================================
--- 3rd_party/eigen/test/constructor.cpp
+++ 3rd_party/eigen/test/constructor.cpp
@@ -0,0 +1,84 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2017 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+
+#define TEST_ENABLE_TEMPORARY_TRACKING
+
+#include "main.h"
+
+template<typename MatrixType> struct Wrapper
+{
+  MatrixType m_mat;
+  inline Wrapper(const MatrixType &x) : m_mat(x) {}
+  inline operator const MatrixType& () const { return m_mat; }
+  inline operator MatrixType& () { return m_mat; }
+};
+
+template<typename MatrixType> void ctor_init1(const MatrixType& m)
+{
+  // Check logic in PlainObjectBase::_init1
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  MatrixType m0 = MatrixType::Random(rows,cols);
+
+  VERIFY_EVALUATION_COUNT( MatrixType m1(m0), 1);
+  VERIFY_EVALUATION_COUNT( MatrixType m2(m0+m0), 1);
+  VERIFY_EVALUATION_COUNT( MatrixType m2(m0.block(0,0,rows,cols)) , 1);
+
+  Wrapper<MatrixType> wrapper(m0);
+  VERIFY_EVALUATION_COUNT( MatrixType m3(wrapper) , 1);
+}
+
+
+void test_constructor()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( ctor_init1(Matrix<float, 1, 1>()) );
+    CALL_SUBTEST_1( ctor_init1(Matrix4d()) );
+    CALL_SUBTEST_1( ctor_init1(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_1( ctor_init1(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+  }
+  {
+    Matrix<Index,1,1> a(123);
+    VERIFY_IS_EQUAL(a[0], 123);
+  }
+  {
+    Matrix<Index,1,1> a(123.0);
+    VERIFY_IS_EQUAL(a[0], 123);
+  }
+  {
+    Matrix<float,1,1> a(123);
+    VERIFY_IS_EQUAL(a[0], 123.f);
+  }
+  {
+    Array<Index,1,1> a(123);
+    VERIFY_IS_EQUAL(a[0], 123);
+  }
+  {
+    Array<Index,1,1> a(123.0);
+    VERIFY_IS_EQUAL(a[0], 123);
+  }
+  {
+    Array<float,1,1> a(123);
+    VERIFY_IS_EQUAL(a[0], 123.f);
+  }
+  {
+    Array<Index,3,3> a(123);
+    VERIFY_IS_EQUAL(a(4), 123);
+  }
+  {
+    Array<Index,3,3> a(123.0);
+    VERIFY_IS_EQUAL(a(4), 123);
+  }
+  {
+    Array<float,3,3> a(123);
+    VERIFY_IS_EQUAL(a(4), 123.f);
+  }
+}

ADDED   3rd_party/eigen/test/ctorleak.cpp
Index: 3rd_party/eigen/test/ctorleak.cpp
==================================================================
--- 3rd_party/eigen/test/ctorleak.cpp
+++ 3rd_party/eigen/test/ctorleak.cpp
@@ -0,0 +1,69 @@
+#include "main.h"
+
+#include <exception>  // std::exception
+
+struct Foo
+{
+  static Index object_count;
+  static Index object_limit;
+  int dummy;
+
+  Foo()
+  {
+#ifdef EIGEN_EXCEPTIONS
+    // TODO: Is this the correct way to handle this?
+    if (Foo::object_count > Foo::object_limit) { std::cout << "\nThrow!\n"; throw Foo::Fail(); }
+#endif
+	  std::cout << '+';
+    ++Foo::object_count;
+  }
+
+  ~Foo()
+  {
+	  std::cout << '-';
+    --Foo::object_count;
+  }
+
+  class Fail : public std::exception {};
+};
+
+Index Foo::object_count = 0;
+Index Foo::object_limit = 0;
+
+#undef EIGEN_TEST_MAX_SIZE
+#define EIGEN_TEST_MAX_SIZE 3
+
+void test_ctorleak()
+{
+  typedef Matrix<Foo, Dynamic, Dynamic> MatrixX;
+  typedef Matrix<Foo, Dynamic, 1> VectorX;
+  Foo::object_count = 0;
+  for(int i = 0; i < g_repeat; i++) {
+    Index rows = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE);
+    Foo::object_limit = internal::random<Index>(0, rows*cols - 2);
+    std::cout << "object_limit =" << Foo::object_limit << std::endl;
+#ifdef EIGEN_EXCEPTIONS
+    try
+    {
+#endif
+    	std::cout <<       "\nMatrixX m(" << rows << ", " << cols << ");\n";
+      MatrixX m(rows, cols);
+#ifdef EIGEN_EXCEPTIONS
+      VERIFY(false);  // not reached if exceptions are enabled
+    }
+    catch (const Foo::Fail&) { /* ignore */ }
+#endif
+    VERIFY_IS_EQUAL(Index(0), Foo::object_count);
+
+    {
+      Foo::object_limit = (rows+1)*(cols+1);
+      MatrixX A(rows, cols);
+      VERIFY_IS_EQUAL(Foo::object_count, rows*cols);
+      VectorX v=A.row(0);
+      VERIFY_IS_EQUAL(Foo::object_count, (rows+1)*cols);
+      v = A.col(0);
+      VERIFY_IS_EQUAL(Foo::object_count, rows*(cols+1));
+    }
+    VERIFY_IS_EQUAL(Index(0), Foo::object_count);
+  }
+}

ADDED   3rd_party/eigen/test/cuda_basic.cu
Index: 3rd_party/eigen/test/cuda_basic.cu
==================================================================
--- 3rd_party/eigen/test/cuda_basic.cu
+++ 3rd_party/eigen/test/cuda_basic.cu
@@ -0,0 +1,173 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+// workaround issue between gcc >= 4.7 and cuda 5.5
+#if (defined __GNUC__) && (__GNUC__>4 || __GNUC_MINOR__>=7)
+  #undef _GLIBCXX_ATOMIC_BUILTINS
+  #undef _GLIBCXX_USE_INT128
+#endif
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cuda_basic
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+
+#include <math_constants.h>
+#include <cuda.h>
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include "cuda_common.h"
+
+// Check that dense modules can be properly parsed by nvcc
+#include <Eigen/Dense>
+
+// struct Foo{
+//   EIGEN_DEVICE_FUNC
+//   void operator()(int i, const float* mats, float* vecs) const {
+//     using namespace Eigen;
+//   //   Matrix3f M(data);
+//   //   Vector3f x(data+9);
+//   //   Map<Vector3f>(data+9) = M.inverse() * x;
+//     Matrix3f M(mats+i/16);
+//     Vector3f x(vecs+i*3);
+//   //   using std::min;
+//   //   using std::sqrt;
+//     Map<Vector3f>(vecs+i*3) << x.minCoeff(), 1, 2;// / x.dot(x);//(M.inverse() *  x) / x.x();
+//     //x = x*2 + x.y() * x + x * x.maxCoeff() - x / x.sum();
+//   }
+// };
+
+template<typename T>
+struct coeff_wise {
+  EIGEN_DEVICE_FUNC
+  void operator()(int i, const typename T::Scalar* in, typename T::Scalar* out) const
+  {
+    using namespace Eigen;
+    T x1(in+i);
+    T x2(in+i+1);
+    T x3(in+i+2);
+    Map<T> res(out+i*T::MaxSizeAtCompileTime);
+    
+    res.array() += (in[0] * x1 + x2).array() * x3.array();
+  }
+};
+
+template<typename T>
+struct replicate {
+  EIGEN_DEVICE_FUNC
+  void operator()(int i, const typename T::Scalar* in, typename T::Scalar* out) const
+  {
+    using namespace Eigen;
+    T x1(in+i);
+    int step   = x1.size() * 4;
+    int stride = 3 * step;
+    
+    typedef Map<Array<typename T::Scalar,Dynamic,Dynamic> > MapType;
+    MapType(out+i*stride+0*step, x1.rows()*2, x1.cols()*2) = x1.replicate(2,2);
+    MapType(out+i*stride+1*step, x1.rows()*3, x1.cols()) = in[i] * x1.colwise().replicate(3);
+    MapType(out+i*stride+2*step, x1.rows(), x1.cols()*3) = in[i] * x1.rowwise().replicate(3);
+  }
+};
+
+template<typename T>
+struct redux {
+  EIGEN_DEVICE_FUNC
+  void operator()(int i, const typename T::Scalar* in, typename T::Scalar* out) const
+  {
+    using namespace Eigen;
+    int N = 10;
+    T x1(in+i);
+    out[i*N+0] = x1.minCoeff();
+    out[i*N+1] = x1.maxCoeff();
+    out[i*N+2] = x1.sum();
+    out[i*N+3] = x1.prod();
+    out[i*N+4] = x1.matrix().squaredNorm();
+    out[i*N+5] = x1.matrix().norm();
+    out[i*N+6] = x1.colwise().sum().maxCoeff();
+    out[i*N+7] = x1.rowwise().maxCoeff().sum();
+    out[i*N+8] = x1.matrix().colwise().squaredNorm().sum();
+  }
+};
+
+template<typename T1, typename T2>
+struct prod_test {
+  EIGEN_DEVICE_FUNC
+  void operator()(int i, const typename T1::Scalar* in, typename T1::Scalar* out) const
+  {
+    using namespace Eigen;
+    typedef Matrix<typename T1::Scalar, T1::RowsAtCompileTime, T2::ColsAtCompileTime> T3;
+    T1 x1(in+i);
+    T2 x2(in+i+1);
+    Map<T3> res(out+i*T3::MaxSizeAtCompileTime);
+    res += in[i] * x1 * x2;
+  }
+};
+
+template<typename T1, typename T2>
+struct diagonal {
+  EIGEN_DEVICE_FUNC
+  void operator()(int i, const typename T1::Scalar* in, typename T1::Scalar* out) const
+  {
+    using namespace Eigen;
+    T1 x1(in+i);
+    Map<T2> res(out+i*T2::MaxSizeAtCompileTime);
+    res += x1.diagonal();
+  }
+};
+
+template<typename T>
+struct eigenvalues {
+  EIGEN_DEVICE_FUNC
+  void operator()(int i, const typename T::Scalar* in, typename T::Scalar* out) const
+  {
+    using namespace Eigen;
+    typedef Matrix<typename T::Scalar, T::RowsAtCompileTime, 1> Vec;
+    T M(in+i);
+    Map<Vec> res(out+i*Vec::MaxSizeAtCompileTime);
+    T A = M*M.adjoint();
+    SelfAdjointEigenSolver<T> eig;
+    eig.computeDirect(M);
+    res = eig.eigenvalues();
+  }
+};
+
+void test_cuda_basic()
+{
+  ei_test_init_cuda();
+  
+  int nthreads = 100;
+  Eigen::VectorXf in, out;
+  
+  #ifndef __CUDA_ARCH__
+  int data_size = nthreads * 512;
+  in.setRandom(data_size);
+  out.setRandom(data_size);
+  #endif
+  
+  CALL_SUBTEST( run_and_compare_to_cuda(coeff_wise<Vector3f>(), nthreads, in, out) );
+  CALL_SUBTEST( run_and_compare_to_cuda(coeff_wise<Array44f>(), nthreads, in, out) );
+  
+  CALL_SUBTEST( run_and_compare_to_cuda(replicate<Array4f>(), nthreads, in, out) );
+  CALL_SUBTEST( run_and_compare_to_cuda(replicate<Array33f>(), nthreads, in, out) );
+  
+  CALL_SUBTEST( run_and_compare_to_cuda(redux<Array4f>(), nthreads, in, out) );
+  CALL_SUBTEST( run_and_compare_to_cuda(redux<Matrix3f>(), nthreads, in, out) );
+  
+  CALL_SUBTEST( run_and_compare_to_cuda(prod_test<Matrix3f,Matrix3f>(), nthreads, in, out) );
+  CALL_SUBTEST( run_and_compare_to_cuda(prod_test<Matrix4f,Vector4f>(), nthreads, in, out) );
+  
+  CALL_SUBTEST( run_and_compare_to_cuda(diagonal<Matrix3f,Vector3f>(), nthreads, in, out) );
+  CALL_SUBTEST( run_and_compare_to_cuda(diagonal<Matrix4f,Vector4f>(), nthreads, in, out) );
+  
+  CALL_SUBTEST( run_and_compare_to_cuda(eigenvalues<Matrix3f>(), nthreads, in, out) );
+  CALL_SUBTEST( run_and_compare_to_cuda(eigenvalues<Matrix2f>(), nthreads, in, out) );
+
+}

ADDED   3rd_party/eigen/test/cuda_common.h
Index: 3rd_party/eigen/test/cuda_common.h
==================================================================
--- 3rd_party/eigen/test/cuda_common.h
+++ 3rd_party/eigen/test/cuda_common.h
@@ -0,0 +1,101 @@
+
+#ifndef EIGEN_TEST_CUDA_COMMON_H
+#define EIGEN_TEST_CUDA_COMMON_H
+
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <cuda_runtime_api.h>
+#include <iostream>
+
+#ifndef __CUDACC__
+dim3 threadIdx, blockDim, blockIdx;
+#endif
+
+template<typename Kernel, typename Input, typename Output>
+void run_on_cpu(const Kernel& ker, int n, const Input& in, Output& out)
+{
+  for(int i=0; i<n; i++)
+    ker(i, in.data(), out.data());
+}
+
+
+template<typename Kernel, typename Input, typename Output>
+__global__
+void run_on_cuda_meta_kernel(const Kernel ker, int n, const Input* in, Output* out)
+{
+  int i = threadIdx.x + blockIdx.x*blockDim.x;
+  if(i<n) {
+    ker(i, in, out);
+  }
+}
+
+
+template<typename Kernel, typename Input, typename Output>
+void run_on_cuda(const Kernel& ker, int n, const Input& in, Output& out)
+{
+  typename Input::Scalar*  d_in;
+  typename Output::Scalar* d_out;
+  std::ptrdiff_t in_bytes  = in.size()  * sizeof(typename Input::Scalar);
+  std::ptrdiff_t out_bytes = out.size() * sizeof(typename Output::Scalar);
+  
+  cudaMalloc((void**)(&d_in),  in_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+  
+  cudaMemcpy(d_in,  in.data(),  in_bytes,  cudaMemcpyHostToDevice);
+  cudaMemcpy(d_out, out.data(), out_bytes, cudaMemcpyHostToDevice);
+  
+  // Simple and non-optimal 1D mapping assuming n is not too large
+  // That's only for unit testing!
+  dim3 Blocks(128);
+  dim3 Grids( (n+int(Blocks.x)-1)/int(Blocks.x) );
+
+  cudaThreadSynchronize();
+  run_on_cuda_meta_kernel<<<Grids,Blocks>>>(ker, n, d_in, d_out);
+  cudaThreadSynchronize();
+  
+  // check inputs have not been modified
+  cudaMemcpy(const_cast<typename Input::Scalar*>(in.data()),  d_in,  in_bytes,  cudaMemcpyDeviceToHost);
+  cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost);
+  
+  cudaFree(d_in);
+  cudaFree(d_out);
+}
+
+
+template<typename Kernel, typename Input, typename Output>
+void run_and_compare_to_cuda(const Kernel& ker, int n, const Input& in, Output& out)
+{
+  Input  in_ref,  in_cuda;
+  Output out_ref, out_cuda;
+  #ifndef __CUDA_ARCH__
+  in_ref = in_cuda = in;
+  out_ref = out_cuda = out;
+  #endif
+  run_on_cpu (ker, n, in_ref,  out_ref);
+  run_on_cuda(ker, n, in_cuda, out_cuda);
+  #ifndef __CUDA_ARCH__
+  VERIFY_IS_APPROX(in_ref, in_cuda);
+  VERIFY_IS_APPROX(out_ref, out_cuda);
+  #endif
+}
+
+
+void ei_test_init_cuda()
+{
+  int device = 0;
+  cudaDeviceProp deviceProp;
+  cudaGetDeviceProperties(&deviceProp, device);
+  std::cout << "CUDA device info:\n";
+  std::cout << "  name:                        " << deviceProp.name << "\n";
+  std::cout << "  capability:                  " << deviceProp.major << "." << deviceProp.minor << "\n";
+  std::cout << "  multiProcessorCount:         " << deviceProp.multiProcessorCount << "\n";
+  std::cout << "  maxThreadsPerMultiProcessor: " << deviceProp.maxThreadsPerMultiProcessor << "\n";
+  std::cout << "  warpSize:                    " << deviceProp.warpSize << "\n";
+  std::cout << "  regsPerBlock:                " << deviceProp.regsPerBlock << "\n";
+  std::cout << "  concurrentKernels:           " << deviceProp.concurrentKernels << "\n";
+  std::cout << "  clockRate:                   " << deviceProp.clockRate << "\n";
+  std::cout << "  canMapHostMemory:            " << deviceProp.canMapHostMemory << "\n";
+  std::cout << "  computeMode:                 " << deviceProp.computeMode << "\n";
+}
+
+#endif // EIGEN_TEST_CUDA_COMMON_H

DELETED 3rd_party/eigen/test/cwiseop.cpp
Index: 3rd_party/eigen/test/cwiseop.cpp
==================================================================
--- 3rd_party/eigen/test/cwiseop.cpp
+++ 3rd_party/eigen/test/cwiseop.cpp
@@ -1,184 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#define EIGEN2_SUPPORT
-#define EIGEN_NO_EIGEN2_DEPRECATED_WARNING
-
-#define EIGEN_NO_STATIC_ASSERT
-#include "main.h"
-#include <functional>
-
-#ifdef min
-#undef min
-#endif
-
-#ifdef max
-#undef max
-#endif
-
-using namespace std;
-
-template<typename Scalar> struct AddIfNull {
-    const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;}
-    enum { Cost = NumTraits<Scalar>::AddCost };
-};
-
-template<typename MatrixType>
-typename Eigen::internal::enable_if<!NumTraits<typename MatrixType::Scalar>::IsInteger,typename MatrixType::Scalar>::type
-cwiseops_real_only(MatrixType& m1, MatrixType& m2, MatrixType& m3, MatrixType& mones)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  
-  VERIFY_IS_APPROX(m1.cwise() / m2,    m1.cwise() * (m2.cwise().inverse()));
-  m3 = m1.cwise().abs().cwise().sqrt();
-  VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs());
-  VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs());
-  VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs());
-
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
-  m3 = (m1.cwise().abs().cwise()<=RealScalar(0.01)).select(mones,m1);
-  VERIFY_IS_APPROX(m3.cwise().pow(-1), m3.cwise().inverse());
-  m3 = m1.cwise().abs();
-  VERIFY_IS_APPROX(m3.cwise().pow(RealScalar(0.5)), m3.cwise().sqrt());
-
-//   VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos());
-  VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square());
-  m3 = m1;
-  m3.cwise() /= m2;
-  VERIFY_IS_APPROX(m3, m1.cwise() / m2);
-  
-  return Scalar(0);
-}
-
-template<typename MatrixType>
-typename Eigen::internal::enable_if<NumTraits<typename MatrixType::Scalar>::IsInteger,typename MatrixType::Scalar>::type
-cwiseops_real_only(MatrixType& , MatrixType& , MatrixType& , MatrixType& )
-{
-  return 0;
-}
-
-template<typename MatrixType> void cwiseops(const MatrixType& m)
-{
-  typedef typename MatrixType::Index Index;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m1bis = m1,
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             m4(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             mones = MatrixType::Ones(rows, cols),
-             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Identity(rows, rows);
-  VectorType vzero = VectorType::Zero(rows),
-             vones = VectorType::Ones(rows),
-             v3(rows);
-
-  Index r = internal::random<Index>(0, rows-1),
-        c = internal::random<Index>(0, cols-1);
-
-  Scalar s1 = internal::random<Scalar>();
-
-  // test Zero, Ones, Constant, and the set* variants
-  m3 = MatrixType::Constant(rows, cols, s1);
-  for (int j=0; j<cols; ++j)
-    for (int i=0; i<rows; ++i)
-    {
-      VERIFY_IS_APPROX(mzero(i,j), Scalar(0));
-      VERIFY_IS_APPROX(mones(i,j), Scalar(1));
-      VERIFY_IS_APPROX(m3(i,j), s1);
-    }
-  VERIFY(mzero.isZero());
-  VERIFY(mones.isOnes());
-  VERIFY(m3.isConstant(s1));
-  VERIFY(identity.isIdentity());
-  VERIFY_IS_APPROX(m4.setConstant(s1), m3);
-  VERIFY_IS_APPROX(m4.setConstant(rows,cols,s1), m3);
-  VERIFY_IS_APPROX(m4.setZero(), mzero);
-  VERIFY_IS_APPROX(m4.setZero(rows,cols), mzero);
-  VERIFY_IS_APPROX(m4.setOnes(), mones);
-  VERIFY_IS_APPROX(m4.setOnes(rows,cols), mones);
-  m4.fill(s1);
-  VERIFY_IS_APPROX(m4, m3);
-
-  VERIFY_IS_APPROX(v3.setConstant(rows, s1), VectorType::Constant(rows,s1));
-  VERIFY_IS_APPROX(v3.setZero(rows), vzero);
-  VERIFY_IS_APPROX(v3.setOnes(rows), vones);
-
-  m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
-
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2());
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
-  VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube());
-
-  VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1));
-  VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1));
-  m3 = m1; m3.cwise() += 1;
-  VERIFY_IS_APPROX(m1 + mones, m3);
-  m3 = m1; m3.cwise() -= 1;
-  VERIFY_IS_APPROX(m1 - mones, m3);
-
-  VERIFY_IS_APPROX(m2, m2.cwise() * mones);
-  VERIFY_IS_APPROX(m1.cwise() * m2,  m2.cwise() * m1);
-  m3 = m1;
-  m3.cwise() *= m2;
-  VERIFY_IS_APPROX(m3, m1.cwise() * m2);
-
-  VERIFY_IS_APPROX(mones,    m2.cwise()/m2);
-
-  // check min
-  VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) );
-  VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 );
-  VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones );
-
-  // check max
-  VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) );
-  VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 );
-  VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones );
-
-  VERIFY( (m1.cwise() == m1).all() );
-  VERIFY( (m1.cwise() != m2).any() );
-  VERIFY(!(m1.cwise() == (m1+mones)).any() );
-  if (rows*cols>1)
-  {
-    m3 = m1;
-    m3(r,c) += 1;
-    VERIFY( (m1.cwise() == m3).any() );
-    VERIFY( !(m1.cwise() == m3).all() );
-  }
-  VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() );
-  VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() );
-  VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() );
-  VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() );
-
-  VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
-  VERIFY( !(m1.cwise()<m1bis.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
-  VERIFY( !(m1.cwise()>m1bis.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
-  
-  cwiseops_real_only(m1, m2, m3, mones);
-}
-
-void test_cwiseop()
-{
-  for(int i = 0; i < g_repeat ; i++) {
-    CALL_SUBTEST_1( cwiseops(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( cwiseops(Matrix4d()) );
-    CALL_SUBTEST_3( cwiseops(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
-    CALL_SUBTEST_4( cwiseops(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
-    CALL_SUBTEST_5( cwiseops(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
-    CALL_SUBTEST_6( cwiseops(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
-  }
-}

ADDED   3rd_party/eigen/test/dense_storage.cpp
Index: 3rd_party/eigen/test/dense_storage.cpp
==================================================================
--- 3rd_party/eigen/test/dense_storage.cpp
+++ 3rd_party/eigen/test/dense_storage.cpp
@@ -0,0 +1,76 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Hauke Heibel <hauke.heibel@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/Core>
+
+template <typename T, int Rows, int Cols>
+void dense_storage_copy()
+{
+  static const int Size = ((Rows==Dynamic || Cols==Dynamic) ? Dynamic : Rows*Cols);
+  typedef DenseStorage<T,Size, Rows,Cols, 0> DenseStorageType;
+  
+  const int rows = (Rows==Dynamic) ? 4 : Rows;
+  const int cols = (Cols==Dynamic) ? 3 : Cols;
+  const int size = rows*cols;
+  DenseStorageType reference(size, rows, cols);
+  T* raw_reference = reference.data();
+  for (int i=0; i<size; ++i)
+    raw_reference[i] = static_cast<T>(i);
+    
+  DenseStorageType copied_reference(reference);
+  const T* raw_copied_reference = copied_reference.data();
+  for (int i=0; i<size; ++i)
+    VERIFY_IS_EQUAL(raw_reference[i], raw_copied_reference[i]);
+}
+
+template <typename T, int Rows, int Cols>
+void dense_storage_assignment()
+{
+  static const int Size = ((Rows==Dynamic || Cols==Dynamic) ? Dynamic : Rows*Cols);
+  typedef DenseStorage<T,Size, Rows,Cols, 0> DenseStorageType;
+  
+  const int rows = (Rows==Dynamic) ? 4 : Rows;
+  const int cols = (Cols==Dynamic) ? 3 : Cols;
+  const int size = rows*cols;
+  DenseStorageType reference(size, rows, cols);
+  T* raw_reference = reference.data();
+  for (int i=0; i<size; ++i)
+    raw_reference[i] = static_cast<T>(i);
+    
+  DenseStorageType copied_reference;
+  copied_reference = reference;
+  const T* raw_copied_reference = copied_reference.data();
+  for (int i=0; i<size; ++i)
+    VERIFY_IS_EQUAL(raw_reference[i], raw_copied_reference[i]);
+}
+
+void test_dense_storage()
+{
+  dense_storage_copy<int,Dynamic,Dynamic>();  
+  dense_storage_copy<int,Dynamic,3>();
+  dense_storage_copy<int,4,Dynamic>();
+  dense_storage_copy<int,4,3>();
+
+  dense_storage_copy<float,Dynamic,Dynamic>();
+  dense_storage_copy<float,Dynamic,3>();
+  dense_storage_copy<float,4,Dynamic>();  
+  dense_storage_copy<float,4,3>();
+  
+  dense_storage_assignment<int,Dynamic,Dynamic>();  
+  dense_storage_assignment<int,Dynamic,3>();
+  dense_storage_assignment<int,4,Dynamic>();
+  dense_storage_assignment<int,4,3>();
+
+  dense_storage_assignment<float,Dynamic,Dynamic>();
+  dense_storage_assignment<float,Dynamic,3>();
+  dense_storage_assignment<float,4,Dynamic>();  
+  dense_storage_assignment<float,4,3>();  
+}

Index: 3rd_party/eigen/test/diagonal.cpp
==================================================================
--- 3rd_party/eigen/test/diagonal.cpp
+++ 3rd_party/eigen/test/diagonal.cpp
@@ -18,10 +18,12 @@
   Index cols = m.cols();
 
   MatrixType m1 = MatrixType::Random(rows, cols),
              m2 = MatrixType::Random(rows, cols);
 
+  Scalar s1 = internal::random<Scalar>();
+
   //check diagonal()
   VERIFY_IS_APPROX(m1.diagonal(), m1.transpose().diagonal());
   m2.diagonal() = 2 * m1.diagonal();
   m2.diagonal()[0] *= 3;
 
@@ -56,10 +58,30 @@
 
     m2.diagonal(N2) = 2 * m1.diagonal(N2);
     VERIFY_IS_APPROX(m2.template diagonal<N2>(), static_cast<Scalar>(2) * m1.diagonal(N2));
     m2.diagonal(N2)[0] *= 3;
     VERIFY_IS_APPROX(m2.diagonal(N2)[0], static_cast<Scalar>(6) * m1.diagonal(N2)[0]);
+
+    m2.diagonal(N2).x() = s1;
+    VERIFY_IS_APPROX(m2.diagonal(N2).x(), s1);
+    m2.diagonal(N2).coeffRef(0) = Scalar(2)*s1;
+    VERIFY_IS_APPROX(m2.diagonal(N2).coeff(0), Scalar(2)*s1);
+  }
+}
+
+template<typename MatrixType> void diagonal_assert(const MatrixType& m) {
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  MatrixType m1 = MatrixType::Random(rows, cols);
+
+  if (rows>=2 && cols>=2)
+  {
+    VERIFY_RAISES_ASSERT( m1 += m1.diagonal() );
+    VERIFY_RAISES_ASSERT( m1 -= m1.diagonal() );
+    VERIFY_RAISES_ASSERT( m1.array() *= m1.diagonal().array() );
+    VERIFY_RAISES_ASSERT( m1.array() /= m1.diagonal().array() );
   }
 }
 
 void test_diagonal()
 {
@@ -72,6 +94,8 @@
     CALL_SUBTEST_2( diagonal(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_2( diagonal(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_1( diagonal(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_1( diagonal(Matrix<float,Dynamic,4>(3, 4)) );
   }
+
+  CALL_SUBTEST_1( diagonal_assert(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
 }

Index: 3rd_party/eigen/test/diagonalmatrices.cpp
==================================================================
--- 3rd_party/eigen/test/diagonalmatrices.cpp
+++ 3rd_party/eigen/test/diagonalmatrices.cpp
@@ -15,10 +15,11 @@
   typedef typename MatrixType::Scalar Scalar;
   enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
   typedef Matrix<Scalar, Rows, 1> VectorType;
   typedef Matrix<Scalar, 1, Cols> RowVectorType;
   typedef Matrix<Scalar, Rows, Rows> SquareMatrixType;
+  typedef Matrix<Scalar, Dynamic, Dynamic> DynMatrixType;
   typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix;
   typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix;
   typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix;
   Index rows = m.rows();
   Index cols = m.cols();
@@ -62,10 +63,17 @@
   VERIFY_IS_APPROX( ((m1 * rv1.asDiagonal())(i,j))  , rv1(j) * m1(i,j) );
   VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * m1)(i,j))  , (v1+v2)(i) * m1(i,j) );
   VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * (m1+m2))(i,j))  , (v1+v2)(i) * (m1+m2)(i,j) );
   VERIFY_IS_APPROX( ((m1 * (rv1+rv2).asDiagonal())(i,j))  , (rv1+rv2)(j) * m1(i,j) );
   VERIFY_IS_APPROX( (((m1+m2) * (rv1+rv2).asDiagonal())(i,j))  , (rv1+rv2)(j) * (m1+m2)(i,j) );
+  
+  if(rows>1)
+  {
+    DynMatrixType tmp = m1.topRows(rows/2), res;
+    VERIFY_IS_APPROX( (res = m1.topRows(rows/2) * rv1.asDiagonal()), tmp * rv1.asDiagonal() );
+    VERIFY_IS_APPROX( (res = v1.head(rows/2).asDiagonal()*m1.topRows(rows/2)), v1.head(rows/2).asDiagonal()*tmp );
+  }
 
   BigMatrix big;
   big.setZero(2*rows, 2*cols);
   
   big.block(i,j,rows,cols) = m1;
@@ -82,10 +90,28 @@
   VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1*s1).diagonal(), ldm1.diagonal() * s1);
   VERIFY_IS_APPROX(LeftDiagonalMatrix(s1*ldm1).diagonal(), s1 * ldm1.diagonal());
   
   VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1);
   VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1);
+  
+  // Diagonal to dense
+  sq_m1.setRandom();
+  sq_m2 = sq_m1;
+  VERIFY_IS_APPROX( (sq_m1 += (s1*v1).asDiagonal()), sq_m2 += (s1*v1).asDiagonal().toDenseMatrix() );
+  VERIFY_IS_APPROX( (sq_m1 -= (s1*v1).asDiagonal()), sq_m2 -= (s1*v1).asDiagonal().toDenseMatrix() );
+  VERIFY_IS_APPROX( (sq_m1 = (s1*v1).asDiagonal()), (s1*v1).asDiagonal().toDenseMatrix() );
+}
+
+template<int>
+void bug987()
+{
+  Matrix3Xd points = Matrix3Xd::Random(3, 3);
+  Vector2d diag = Vector2d::Random();
+  Matrix2Xd tmp1 = points.topRows<2>(), res1, res2;
+  VERIFY_IS_APPROX( res1 = diag.asDiagonal() * points.topRows<2>(), res2 = diag.asDiagonal() * tmp1 );
+  Matrix2d tmp2 = points.topLeftCorner<2,2>();
+  VERIFY_IS_APPROX(( res1 = points.topLeftCorner<2,2>()*diag.asDiagonal()) , res2 = tmp2*diag.asDiagonal() );
 }
 
 void test_diagonalmatrices()
 {
   for(int i = 0; i < g_repeat; i++) {
@@ -97,6 +123,7 @@
     CALL_SUBTEST_6( diagonalmatrices(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_7( diagonalmatrices(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_8( diagonalmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_9( diagonalmatrices(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
   }
+  CALL_SUBTEST_10( bug987<0>() );
 }

Index: 3rd_party/eigen/test/dynalloc.cpp
==================================================================
--- 3rd_party/eigen/test/dynalloc.cpp
+++ 3rd_party/eigen/test/dynalloc.cpp
@@ -7,58 +7,60 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
 
-#if EIGEN_ALIGN
-#define ALIGNMENT 16
+#if EIGEN_MAX_ALIGN_BYTES>0
+#define ALIGNMENT EIGEN_MAX_ALIGN_BYTES
 #else
 #define ALIGNMENT 1
 #endif
+
+typedef Matrix<float,8,1> Vector8f;
 
 void check_handmade_aligned_malloc()
 {
   for(int i = 1; i < 1000; i++)
   {
     char *p = (char*)internal::handmade_aligned_malloc(i);
-    VERIFY(size_t(p)%ALIGNMENT==0);
+    VERIFY(internal::UIntPtr(p)%ALIGNMENT==0);
     // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
     for(int j = 0; j < i; j++) p[j]=0;
     internal::handmade_aligned_free(p);
   }
 }
 
 void check_aligned_malloc()
 {
-  for(int i = 1; i < 1000; i++)
+  for(int i = ALIGNMENT; i < 1000; i++)
   {
     char *p = (char*)internal::aligned_malloc(i);
-    VERIFY(size_t(p)%ALIGNMENT==0);
+    VERIFY(internal::UIntPtr(p)%ALIGNMENT==0);
     // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
     for(int j = 0; j < i; j++) p[j]=0;
     internal::aligned_free(p);
   }
 }
 
 void check_aligned_new()
 {
-  for(int i = 1; i < 1000; i++)
+  for(int i = ALIGNMENT; i < 1000; i++)
   {
     float *p = internal::aligned_new<float>(i);
-    VERIFY(size_t(p)%ALIGNMENT==0);
+    VERIFY(internal::UIntPtr(p)%ALIGNMENT==0);
     // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
     for(int j = 0; j < i; j++) p[j]=0;
     internal::aligned_delete(p,i);
   }
 }
 
 void check_aligned_stack_alloc()
 {
-  for(int i = 1; i < 400; i++)
+  for(int i = ALIGNMENT; i < 400; i++)
   {
     ei_declare_aligned_stack_constructed_variable(float,p,i,0);
-    VERIFY(size_t(p)%ALIGNMENT==0);
+    VERIFY(internal::UIntPtr(p)%ALIGNMENT==0);
     // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
     for(int j = 0; j < i; j++) p[j]=0;
   }
 }
 
@@ -66,27 +68,57 @@
 // test compilation with both a struct and a class...
 struct MyStruct
 {
   EIGEN_MAKE_ALIGNED_OPERATOR_NEW
   char dummychar;
-  Vector4f avec;
+  Vector8f avec;
 };
 
 class MyClassA
 {
   public:
     EIGEN_MAKE_ALIGNED_OPERATOR_NEW
     char dummychar;
-    Vector4f avec;
+    Vector8f avec;
 };
 
 template<typename T> void check_dynaligned()
 {
-  T* obj = new T;
-  VERIFY(T::NeedsToAlign==1);
-  VERIFY(size_t(obj)%ALIGNMENT==0);
-  delete obj;
+  // TODO have to be updated once we support multiple alignment values
+  if(T::SizeAtCompileTime % ALIGNMENT == 0)
+  {
+    T* obj = new T;
+    VERIFY(T::NeedsToAlign==1);
+    VERIFY(internal::UIntPtr(obj)%ALIGNMENT==0);
+    delete obj;
+  }
+}
+
+template<typename T> void check_custom_new_delete()
+{
+  {
+    T* t = new T;
+    delete t;
+  }
+  
+  {
+    std::size_t N = internal::random<std::size_t>(1,10);
+    T* t = new T[N];
+    delete[] t;
+  }
+  
+#if EIGEN_MAX_ALIGN_BYTES>0
+  {
+    T* t = static_cast<T *>((T::operator new)(sizeof(T)));
+    (T::operator delete)(t, sizeof(T));
+  }
+  
+  {
+    T* t = static_cast<T *>((T::operator new)(sizeof(T)));
+    (T::operator delete)(t);
+  }
+#endif
 }
 
 void test_dynalloc()
 {
   // low level dynamic memory allocation
@@ -94,41 +126,50 @@
   CALL_SUBTEST(check_aligned_malloc());
   CALL_SUBTEST(check_aligned_new());
   CALL_SUBTEST(check_aligned_stack_alloc());
 
   for (int i=0; i<g_repeat*100; ++i)
+  {
+    CALL_SUBTEST( check_custom_new_delete<Vector4f>() );
+    CALL_SUBTEST( check_custom_new_delete<Vector2f>() );
+    CALL_SUBTEST( check_custom_new_delete<Matrix4f>() );
+    CALL_SUBTEST( check_custom_new_delete<MatrixXi>() );
+  }
+  
+  // check static allocation, who knows ?
+  #if EIGEN_MAX_STATIC_ALIGN_BYTES
+  for (int i=0; i<g_repeat*100; ++i)
   {
     CALL_SUBTEST(check_dynaligned<Vector4f>() );
     CALL_SUBTEST(check_dynaligned<Vector2d>() );
     CALL_SUBTEST(check_dynaligned<Matrix4f>() );
     CALL_SUBTEST(check_dynaligned<Vector4d>() );
     CALL_SUBTEST(check_dynaligned<Vector4i>() );
+    CALL_SUBTEST(check_dynaligned<Vector8f>() );
   }
-  
-  // check static allocation, who knows ?
-  #if EIGEN_ALIGN_STATICALLY
+
   {
-    MyStruct foo0;  VERIFY(size_t(foo0.avec.data())%ALIGNMENT==0);
-    MyClassA fooA;  VERIFY(size_t(fooA.avec.data())%ALIGNMENT==0);
+    MyStruct foo0;  VERIFY(internal::UIntPtr(foo0.avec.data())%ALIGNMENT==0);
+    MyClassA fooA;  VERIFY(internal::UIntPtr(fooA.avec.data())%ALIGNMENT==0);
   }
   
   // dynamic allocation, single object
   for (int i=0; i<g_repeat*100; ++i)
   {
-    MyStruct *foo0 = new MyStruct();  VERIFY(size_t(foo0->avec.data())%ALIGNMENT==0);
-    MyClassA *fooA = new MyClassA();  VERIFY(size_t(fooA->avec.data())%ALIGNMENT==0);
+    MyStruct *foo0 = new MyStruct();  VERIFY(internal::UIntPtr(foo0->avec.data())%ALIGNMENT==0);
+    MyClassA *fooA = new MyClassA();  VERIFY(internal::UIntPtr(fooA->avec.data())%ALIGNMENT==0);
     delete foo0;
     delete fooA;
   }
 
   // dynamic allocation, array
   const int N = 10;
   for (int i=0; i<g_repeat*100; ++i)
   {
-    MyStruct *foo0 = new MyStruct[N];  VERIFY(size_t(foo0->avec.data())%ALIGNMENT==0);
-    MyClassA *fooA = new MyClassA[N];  VERIFY(size_t(fooA->avec.data())%ALIGNMENT==0);
+    MyStruct *foo0 = new MyStruct[N];  VERIFY(internal::UIntPtr(foo0->avec.data())%ALIGNMENT==0);
+    MyClassA *fooA = new MyClassA[N];  VERIFY(internal::UIntPtr(fooA->avec.data())%ALIGNMENT==0);
     delete[] foo0;
     delete[] fooA;
   }
   #endif
   
 }

DELETED 3rd_party/eigen/test/eigen2/CMakeLists.txt
Index: 3rd_party/eigen/test/eigen2/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/test/eigen2/CMakeLists.txt
+++ 3rd_party/eigen/test/eigen2/CMakeLists.txt
@@ -1,61 +0,0 @@
-add_custom_target(eigen2_buildtests)
-add_custom_target(eigen2_check COMMAND "ctest -R eigen2")
-add_dependencies(eigen2_check eigen2_buildtests)
-add_dependencies(buildtests eigen2_buildtests)
-
-add_definitions("-DEIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API")
-add_definitions("-DEIGEN_NO_EIGEN2_DEPRECATED_WARNING")
-
-ei_add_test(eigen2_meta)
-ei_add_test(eigen2_sizeof)
-ei_add_test(eigen2_dynalloc)
-ei_add_test(eigen2_nomalloc)
-#ei_add_test(eigen2_first_aligned)
-ei_add_test(eigen2_mixingtypes)
-#ei_add_test(eigen2_packetmath)
-ei_add_test(eigen2_unalignedassert)
-#ei_add_test(eigen2_vectorization_logic)
-ei_add_test(eigen2_basicstuff)
-ei_add_test(eigen2_linearstructure)
-ei_add_test(eigen2_cwiseop)
-ei_add_test(eigen2_sum)
-ei_add_test(eigen2_product_small)
-ei_add_test(eigen2_product_large ${EI_OFLAG})
-ei_add_test(eigen2_adjoint)
-ei_add_test(eigen2_submatrices)
-ei_add_test(eigen2_miscmatrices)
-ei_add_test(eigen2_commainitializer)
-ei_add_test(eigen2_smallvectors)
-ei_add_test(eigen2_map)
-ei_add_test(eigen2_array)
-ei_add_test(eigen2_triangular)
-ei_add_test(eigen2_cholesky " " "${GSL_LIBRARIES}")
-ei_add_test(eigen2_lu ${EI_OFLAG})
-ei_add_test(eigen2_determinant ${EI_OFLAG})
-ei_add_test(eigen2_inverse)
-ei_add_test(eigen2_qr)
-ei_add_test(eigen2_eigensolver " " "${GSL_LIBRARIES}")
-ei_add_test(eigen2_svd)
-ei_add_test(eigen2_geometry)
-ei_add_test(eigen2_geometry_with_eigen2_prefix)
-ei_add_test(eigen2_hyperplane)
-ei_add_test(eigen2_parametrizedline)
-ei_add_test(eigen2_alignedbox)
-ei_add_test(eigen2_regression)
-ei_add_test(eigen2_stdvector)
-ei_add_test(eigen2_newstdvector)
-if(QT4_FOUND)
-  ei_add_test(eigen2_qtvector " " "${QT_QTCORE_LIBRARY}")
-endif(QT4_FOUND)
-# no support for eigen2 sparse module
-# if(NOT EIGEN_DEFAULT_TO_ROW_MAJOR)
-#   ei_add_test(eigen2_sparse_vector)
-#   ei_add_test(eigen2_sparse_basic)
-#   ei_add_test(eigen2_sparse_solvers " " "${SPARSE_LIBS}")
-#   ei_add_test(eigen2_sparse_product)
-# endif()
-ei_add_test(eigen2_swap)
-ei_add_test(eigen2_visitor)
-ei_add_test(eigen2_bug_132)
-
-ei_add_test(eigen2_prec_inverse_4x4 ${EI_OFLAG})

DELETED 3rd_party/eigen/test/eigen2/eigen2_adjoint.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_adjoint.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_adjoint.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_adjoint.cpp
@@ -1,99 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename MatrixType> void adjoint(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Transpose.h Conjugate.h Dot.h
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
-  int rows = m.rows();
-  int cols = m.cols();
-
-  RealScalar largerEps = test_precision<RealScalar>();
-  if (ei_is_same_type<RealScalar,float>::ret)
-    largerEps = RealScalar(1e-3f);
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             square = SquareMatrixType::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows),
-             v2 = VectorType::Random(rows),
-             v3 = VectorType::Random(rows),
-             vzero = VectorType::Zero(rows);
-
-  Scalar s1 = ei_random<Scalar>(),
-         s2 = ei_random<Scalar>();
-
-  // check basic compatibility of adjoint, transpose, conjugate
-  VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(),    m1);
-  VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(),    m1);
-
-  // check multiplicative behavior
-  VERIFY_IS_APPROX((m1.adjoint() * m2).adjoint(),           m2.adjoint() * m1);
-  VERIFY_IS_APPROX((s1 * m1).adjoint(),                     ei_conj(s1) * m1.adjoint());
-
-  // check basic properties of dot, norm, norm2
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  VERIFY(ei_isApprox((s1 * v1 + s2 * v2).eigen2_dot(v3),   s1 * v1.eigen2_dot(v3) + s2 * v2.eigen2_dot(v3), largerEps));
-  VERIFY(ei_isApprox(v3.eigen2_dot(s1 * v1 + s2 * v2),     ei_conj(s1)*v3.eigen2_dot(v1)+ei_conj(s2)*v3.eigen2_dot(v2), largerEps));
-  VERIFY_IS_APPROX(ei_conj(v1.eigen2_dot(v2)),               v2.eigen2_dot(v1));
-  VERIFY_IS_APPROX(ei_real(v1.eigen2_dot(v1)),               v1.squaredNorm());
-  if(NumTraits<Scalar>::HasFloatingPoint)
-    VERIFY_IS_APPROX(v1.squaredNorm(),                      v1.norm() * v1.norm());
-  VERIFY_IS_MUCH_SMALLER_THAN(ei_abs(vzero.eigen2_dot(v1)),  static_cast<RealScalar>(1));
-  if(NumTraits<Scalar>::HasFloatingPoint)
-    VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(),         static_cast<RealScalar>(1));
-
-  // check compatibility of dot and adjoint
-  VERIFY(ei_isApprox(v1.eigen2_dot(square * v2), (square.adjoint() * v1).eigen2_dot(v2), largerEps));
-
-  // like in testBasicStuff, test operator() to check const-qualification
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-  VERIFY_IS_APPROX(m1.conjugate()(r,c), ei_conj(m1(r,c)));
-  VERIFY_IS_APPROX(m1.adjoint()(c,r), ei_conj(m1(r,c)));
-
-  if(NumTraits<Scalar>::HasFloatingPoint)
-  {
-    // check that Random().normalized() works: tricky as the random xpr must be evaluated by
-    // normalized() in order to produce a consistent result.
-    VERIFY_IS_APPROX(VectorType::Random(rows).normalized().norm(), RealScalar(1));
-  }
-
-  // check inplace transpose
-  m3 = m1;
-  m3.transposeInPlace();
-  VERIFY_IS_APPROX(m3,m1.transpose());
-  m3.transposeInPlace();
-  VERIFY_IS_APPROX(m3,m1);
-  
-}
-
-void test_eigen2_adjoint()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( adjoint(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( adjoint(Matrix3d()) );
-    CALL_SUBTEST_3( adjoint(Matrix4f()) );
-    CALL_SUBTEST_4( adjoint(MatrixXcf(4, 4)) );
-    CALL_SUBTEST_5( adjoint(MatrixXi(8, 12)) );
-    CALL_SUBTEST_6( adjoint(MatrixXf(21, 21)) );
-  }
-  // test a large matrix only once
-  CALL_SUBTEST_7( adjoint(Matrix<float, 100, 100>()) );
-}
-

DELETED 3rd_party/eigen/test/eigen2/eigen2_alignedbox.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_alignedbox.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_alignedbox.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_alignedbox.cpp
@@ -1,60 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/Geometry>
-#include <Eigen/LU>
-#include <Eigen/QR>
-
-template<typename BoxType> void alignedbox(const BoxType& _box)
-{
-  /* this test covers the following files:
-     AlignedBox.h
-  */
-
-  const int dim = _box.dim();
-  typedef typename BoxType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, BoxType::AmbientDimAtCompileTime, 1> VectorType;
-
-  VectorType p0 = VectorType::Random(dim);
-  VectorType p1 = VectorType::Random(dim);
-  RealScalar s1 = ei_random<RealScalar>(0,1);
-
-  BoxType b0(dim);
-  BoxType b1(VectorType::Random(dim),VectorType::Random(dim));
-  BoxType b2;
-
-  b0.extend(p0);
-  b0.extend(p1);
-  VERIFY(b0.contains(p0*s1+(Scalar(1)-s1)*p1));
-  VERIFY(!b0.contains(p0 + (1+s1)*(p1-p0)));
-
-  (b2 = b0).extend(b1);
-  VERIFY(b2.contains(b0));
-  VERIFY(b2.contains(b1));
-  VERIFY_IS_APPROX(b2.clamp(b0), b0);
-
-  // casting
-  const int Dim = BoxType::AmbientDimAtCompileTime;
-  typedef typename GetDifferentType<Scalar>::type OtherScalar;
-  AlignedBox<OtherScalar,Dim> hp1f = b0.template cast<OtherScalar>();
-  VERIFY_IS_APPROX(hp1f.template cast<Scalar>(),b0);
-  AlignedBox<Scalar,Dim> hp1d = b0.template cast<Scalar>();
-  VERIFY_IS_APPROX(hp1d.template cast<Scalar>(),b0);
-}
-
-void test_eigen2_alignedbox()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( alignedbox(AlignedBox<float,2>()) );
-    CALL_SUBTEST_2( alignedbox(AlignedBox<float,3>()) );
-    CALL_SUBTEST_3( alignedbox(AlignedBox<double,4>()) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_array.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_array.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_array.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_array.cpp
@@ -1,142 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/Array>
-
-template<typename MatrixType> void array(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Array.cpp
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols);
-
-  Scalar  s1 = ei_random<Scalar>(),
-          s2 = ei_random<Scalar>();
-
-  // scalar addition
-  VERIFY_IS_APPROX(m1.cwise() + s1, s1 + m1.cwise());
-  VERIFY_IS_APPROX(m1.cwise() + s1, MatrixType::Constant(rows,cols,s1) + m1);
-  VERIFY_IS_APPROX((m1*Scalar(2)).cwise() - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) );
-  m3 = m1;
-  m3.cwise() += s2;
-  VERIFY_IS_APPROX(m3, m1.cwise() + s2);
-  m3 = m1;
-  m3.cwise() -= s1;
-  VERIFY_IS_APPROX(m3, m1.cwise() - s1);
-
-  // reductions
-  VERIFY_IS_APPROX(m1.colwise().sum().sum(), m1.sum());
-  VERIFY_IS_APPROX(m1.rowwise().sum().sum(), m1.sum());
-  if (!ei_isApprox(m1.sum(), (m1+m2).sum()))
-    VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum());
-  VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar>()));
-}
-
-template<typename MatrixType> void comparisons(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols);
-
-  VERIFY(((m1.cwise() + Scalar(1)).cwise() > m1).all());
-  VERIFY(((m1.cwise() - Scalar(1)).cwise() < m1).all());
-  if (rows*cols>1)
-  {
-    m3 = m1;
-    m3(r,c) += 1;
-    VERIFY(! (m1.cwise() < m3).all() );
-    VERIFY(! (m1.cwise() > m3).all() );
-  }
-  
-  // comparisons to scalar
-  VERIFY( (m1.cwise() != (m1(r,c)+1) ).any() );
-  VERIFY( (m1.cwise() > (m1(r,c)-1) ).any() );
-  VERIFY( (m1.cwise() < (m1(r,c)+1) ).any() );
-  VERIFY( (m1.cwise() == m1(r,c) ).any() );
-  
-  // test Select
-  VERIFY_IS_APPROX( (m1.cwise()<m2).select(m1,m2), m1.cwise().min(m2) );
-  VERIFY_IS_APPROX( (m1.cwise()>m2).select(m1,m2), m1.cwise().max(m2) );
-  Scalar mid = (m1.cwise().abs().minCoeff() + m1.cwise().abs().maxCoeff())/Scalar(2);
-  for (int j=0; j<cols; ++j)
-  for (int i=0; i<rows; ++i)
-    m3(i,j) = ei_abs(m1(i,j))<mid ? 0 : m1(i,j);
-  VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<MatrixType::Constant(rows,cols,mid))
-                        .select(MatrixType::Zero(rows,cols),m1), m3);
-  // shorter versions:
-  VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<MatrixType::Constant(rows,cols,mid))
-                        .select(0,m1), m3);
-  VERIFY_IS_APPROX( (m1.cwise().abs().cwise()>=MatrixType::Constant(rows,cols,mid))
-                        .select(m1,0), m3);
-  // even shorter version:
-  VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<mid).select(0,m1), m3);
-  
-  // count
-  VERIFY(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).count() == rows*cols);
-  VERIFY_IS_APPROX(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).colwise().count().template cast<int>(), RowVectorXi::Constant(cols,rows));
-  VERIFY_IS_APPROX(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).rowwise().count().template cast<int>(), VectorXi::Constant(rows, cols));
-}
-
-template<typename VectorType> void lpNorm(const VectorType& v)
-{
-  VectorType u = VectorType::Random(v.size());
-
-  VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwise().abs().maxCoeff());
-  VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwise().abs().sum());
-  VERIFY_IS_APPROX(u.template lpNorm<2>(), ei_sqrt(u.cwise().abs().cwise().square().sum()));
-  VERIFY_IS_APPROX(ei_pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.cwise().abs().cwise().pow(5).sum());
-}
-
-void test_eigen2_array()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( array(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( array(Matrix2f()) );
-    CALL_SUBTEST_3( array(Matrix4d()) );
-    CALL_SUBTEST_4( array(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_5( array(MatrixXf(8, 12)) );
-    CALL_SUBTEST_6( array(MatrixXi(8, 12)) );
-  }
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( comparisons(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( comparisons(Matrix2f()) );
-    CALL_SUBTEST_3( comparisons(Matrix4d()) );
-    CALL_SUBTEST_5( comparisons(MatrixXf(8, 12)) );
-    CALL_SUBTEST_6( comparisons(MatrixXi(8, 12)) );
-  }
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( lpNorm(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( lpNorm(Vector2f()) );
-    CALL_SUBTEST_3( lpNorm(Vector3d()) );
-    CALL_SUBTEST_4( lpNorm(Vector4f()) );
-    CALL_SUBTEST_5( lpNorm(VectorXf(16)) );
-    CALL_SUBTEST_7( lpNorm(VectorXcd(10)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_basicstuff.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_basicstuff.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_basicstuff.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_basicstuff.cpp
@@ -1,105 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename MatrixType> void basicStuff(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  // this test relies a lot on Random.h, and there's not much more that we can do
-  // to test it, hence I consider that we will have tested Random.h
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows),
-             vzero = VectorType::Zero(rows);
-
-  Scalar x = ei_random<Scalar>();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  m1.coeffRef(r,c) = x;
-  VERIFY_IS_APPROX(x, m1.coeff(r,c));
-  m1(r,c) = x;
-  VERIFY_IS_APPROX(x, m1(r,c));
-  v1.coeffRef(r) = x;
-  VERIFY_IS_APPROX(x, v1.coeff(r));
-  v1(r) = x;
-  VERIFY_IS_APPROX(x, v1(r));
-  v1[r] = x;
-  VERIFY_IS_APPROX(x, v1[r]);
-
-  VERIFY_IS_APPROX(               v1,    v1);
-  VERIFY_IS_NOT_APPROX(           v1,    2*v1);
-  VERIFY_IS_MUCH_SMALLER_THAN(    vzero, v1);
-  if(NumTraits<Scalar>::HasFloatingPoint)
-    VERIFY_IS_MUCH_SMALLER_THAN(  vzero, v1.norm());
-  VERIFY_IS_NOT_MUCH_SMALLER_THAN(v1,    v1);
-  VERIFY_IS_APPROX(               vzero, v1-v1);
-  VERIFY_IS_APPROX(               m1,    m1);
-  VERIFY_IS_NOT_APPROX(           m1,    2*m1);
-  VERIFY_IS_MUCH_SMALLER_THAN(    mzero, m1);
-  VERIFY_IS_NOT_MUCH_SMALLER_THAN(m1,    m1);
-  VERIFY_IS_APPROX(               mzero, m1-m1);
-
-  // always test operator() on each read-only expression class,
-  // in order to check const-qualifiers.
-  // indeed, if an expression class (here Zero) is meant to be read-only,
-  // hence has no _write() method, the corresponding MatrixBase method (here zero())
-  // should return a const-qualified object so that it is the const-qualified
-  // operator() that gets called, which in turn calls _read().
-  VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows,cols)(r,c), static_cast<Scalar>(1));
-
-  // now test copying a row-vector into a (column-)vector and conversely.
-  square.col(r) = square.row(r).eval();
-  Matrix<Scalar, 1, MatrixType::RowsAtCompileTime> rv(rows);
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> cv(rows);
-  rv = square.row(r);
-  cv = square.col(r);
-  VERIFY_IS_APPROX(rv, cv.transpose());
-
-  if(cols!=1 && rows!=1 && MatrixType::SizeAtCompileTime!=Dynamic)
-  {
-    VERIFY_RAISES_ASSERT(m1 = (m2.block(0,0, rows-1, cols-1)));
-  }
-
-  VERIFY_IS_APPROX(m3 = m1,m1);
-  MatrixType m4;
-  VERIFY_IS_APPROX(m4 = m1,m1);
-
-  // test swap
-  m3 = m1;
-  m1.swap(m2);
-  VERIFY_IS_APPROX(m3, m2);
-  if(rows*cols>=3)
-  {
-    VERIFY_IS_NOT_APPROX(m3, m1);
-  }
-}
-
-void test_eigen2_basicstuff()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( basicStuff(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( basicStuff(Matrix4d()) );
-    CALL_SUBTEST_3( basicStuff(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_4( basicStuff(MatrixXi(8, 12)) );
-    CALL_SUBTEST_5( basicStuff(MatrixXcd(20, 20)) );
-    CALL_SUBTEST_6( basicStuff(Matrix<float, 100, 100>()) );
-    CALL_SUBTEST_7( basicStuff(Matrix<long double,Dynamic,Dynamic>(10,10)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_bug_132.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_bug_132.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_bug_132.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_bug_132.cpp
@@ -1,26 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-void test_eigen2_bug_132() {
-  int size = 100;
-  MatrixXd A(size, size);
-  VectorXd b(size), c(size);
-  {
-    VectorXd y = A.transpose() * (b-c);  // bug 132: infinite recursion in coeffRef
-    VectorXd z = (b-c).transpose() * A;  // bug 132: infinite recursion in coeffRef
-  }
-
-  // the following ones weren't failing, but let's include them for completeness:
-  {
-    VectorXd y = A * (b-c);
-    VectorXd z = (b-c).transpose() * A.transpose();
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_cholesky.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_cholesky.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_cholesky.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_cholesky.cpp
@@ -1,113 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#define EIGEN_NO_ASSERTION_CHECKING
-#include "main.h"
-#include <Eigen/Cholesky>
-#include <Eigen/LU>
-
-#ifdef HAS_GSL
-#include "gsl_helper.h"
-#endif
-
-template<typename MatrixType> void cholesky(const MatrixType& m)
-{
-  /* this test covers the following files:
-     LLT.h LDLT.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  MatrixType a0 = MatrixType::Random(rows,cols);
-  VectorType vecB = VectorType::Random(rows), vecX(rows);
-  MatrixType matB = MatrixType::Random(rows,cols), matX(rows,cols);
-  SquareMatrixType symm =  a0 * a0.adjoint();
-  // let's make sure the matrix is not singular or near singular
-  MatrixType a1 = MatrixType::Random(rows,cols);
-  symm += a1 * a1.adjoint();
-
-  #ifdef HAS_GSL
-  if (ei_is_same_type<RealScalar,double>::ret)
-  {
-    typedef GslTraits<Scalar> Gsl;
-    typename Gsl::Matrix gMatA=0, gSymm=0;
-    typename Gsl::Vector gVecB=0, gVecX=0;
-    convert<MatrixType>(symm, gSymm);
-    convert<MatrixType>(symm, gMatA);
-    convert<VectorType>(vecB, gVecB);
-    convert<VectorType>(vecB, gVecX);
-    Gsl::cholesky(gMatA);
-    Gsl::cholesky_solve(gMatA, gVecB, gVecX);
-    VectorType vecX(rows), _vecX, _vecB;
-    convert(gVecX, _vecX);
-    symm.llt().solve(vecB, &vecX);
-    Gsl::prod(gSymm, gVecX, gVecB);
-    convert(gVecB, _vecB);
-    // test gsl itself !
-    VERIFY_IS_APPROX(vecB, _vecB);
-    VERIFY_IS_APPROX(vecX, _vecX);
-
-    Gsl::free(gMatA);
-    Gsl::free(gSymm);
-    Gsl::free(gVecB);
-    Gsl::free(gVecX);
-  }
-  #endif
-
-  {
-    LDLT<SquareMatrixType> ldlt(symm);
-    VERIFY(ldlt.isPositiveDefinite());
-    // in eigen3, LDLT is pivoting
-    //VERIFY_IS_APPROX(symm, ldlt.matrixL() * ldlt.vectorD().asDiagonal() * ldlt.matrixL().adjoint());
-    ldlt.solve(vecB, &vecX);
-    VERIFY_IS_APPROX(symm * vecX, vecB);
-    ldlt.solve(matB, &matX);
-    VERIFY_IS_APPROX(symm * matX, matB);
-  }
-
-  {
-    LLT<SquareMatrixType> chol(symm);
-    VERIFY(chol.isPositiveDefinite());
-    VERIFY_IS_APPROX(symm, chol.matrixL() * chol.matrixL().adjoint());
-    chol.solve(vecB, &vecX);
-    VERIFY_IS_APPROX(symm * vecX, vecB);
-    chol.solve(matB, &matX);
-    VERIFY_IS_APPROX(symm * matX, matB);
-  }
-
-#if 0 // cholesky is not rank-revealing anyway
-  // test isPositiveDefinite on non definite matrix
-  if (rows>4)
-  {
-    SquareMatrixType symm =  a0.block(0,0,rows,cols-4) * a0.block(0,0,rows,cols-4).adjoint();
-    LLT<SquareMatrixType> chol(symm);
-    VERIFY(!chol.isPositiveDefinite());
-    LDLT<SquareMatrixType> cholnosqrt(symm);
-    VERIFY(!cholnosqrt.isPositiveDefinite());
-  }
-#endif
-}
-
-void test_eigen2_cholesky()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( cholesky(Matrix<double,1,1>()) );
-    CALL_SUBTEST_2( cholesky(Matrix2d()) );
-    CALL_SUBTEST_3( cholesky(Matrix3f()) );
-    CALL_SUBTEST_4( cholesky(Matrix4d()) );
-    CALL_SUBTEST_5( cholesky(MatrixXcd(7,7)) );
-    CALL_SUBTEST_6( cholesky(MatrixXf(17,17)) );
-    CALL_SUBTEST_7( cholesky(MatrixXd(33,33)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_commainitializer.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_commainitializer.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_commainitializer.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_commainitializer.cpp
@@ -1,46 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-void test_eigen2_commainitializer()
-{
-  Matrix3d m3;
-  Matrix4d m4;
-
-  VERIFY_RAISES_ASSERT( (m3 << 1, 2, 3, 4, 5, 6, 7, 8) );
-  
-  #ifndef _MSC_VER
-  VERIFY_RAISES_ASSERT( (m3 << 1, 2, 3, 4, 5, 6, 7, 8, 9, 10) );
-  #endif
-
-  double data[] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
-  Matrix3d ref = Map<Matrix<double,3,3,RowMajor> >(data);
-
-  m3 = Matrix3d::Random();
-  m3 << 1, 2, 3, 4, 5, 6, 7, 8, 9;
-  VERIFY_IS_APPROX(m3, ref );
-
-  Vector3d vec[3];
-  vec[0] << 1, 4, 7;
-  vec[1] << 2, 5, 8;
-  vec[2] << 3, 6, 9;
-  m3 = Matrix3d::Random();
-  m3 << vec[0], vec[1], vec[2];
-  VERIFY_IS_APPROX(m3, ref);
-
-  vec[0] << 1, 2, 3;
-  vec[1] << 4, 5, 6;
-  vec[2] << 7, 8, 9;
-  m3 = Matrix3d::Random();
-  m3 << vec[0].transpose(),
-        4, 5, 6,
-        vec[2].transpose();
-  VERIFY_IS_APPROX(m3, ref);
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_cwiseop.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_cwiseop.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_cwiseop.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_cwiseop.cpp
@@ -1,155 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <functional>
-#include <Eigen/Array>
-
-using namespace std;
-
-template<typename Scalar> struct AddIfNull {
-    const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;}
-    enum { Cost = NumTraits<Scalar>::AddCost };
-};
-
-template<typename MatrixType> void cwiseops(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             m4(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             mones = MatrixType::Ones(rows, cols),
-             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Identity(rows, rows);
-  VectorType vzero = VectorType::Zero(rows),
-             vones = VectorType::Ones(rows),
-             v3(rows);
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-  
-  Scalar s1 = ei_random<Scalar>();
-  
-  // test Zero, Ones, Constant, and the set* variants
-  m3 = MatrixType::Constant(rows, cols, s1);
-  for (int j=0; j<cols; ++j)
-    for (int i=0; i<rows; ++i)
-    {
-      VERIFY_IS_APPROX(mzero(i,j), Scalar(0));
-      VERIFY_IS_APPROX(mones(i,j), Scalar(1));
-      VERIFY_IS_APPROX(m3(i,j), s1);
-    }
-  VERIFY(mzero.isZero());
-  VERIFY(mones.isOnes());
-  VERIFY(m3.isConstant(s1));
-  VERIFY(identity.isIdentity());
-  VERIFY_IS_APPROX(m4.setConstant(s1), m3);
-  VERIFY_IS_APPROX(m4.setConstant(rows,cols,s1), m3);
-  VERIFY_IS_APPROX(m4.setZero(), mzero);
-  VERIFY_IS_APPROX(m4.setZero(rows,cols), mzero);
-  VERIFY_IS_APPROX(m4.setOnes(), mones);
-  VERIFY_IS_APPROX(m4.setOnes(rows,cols), mones);
-  m4.fill(s1);
-  VERIFY_IS_APPROX(m4, m3);
-  
-  VERIFY_IS_APPROX(v3.setConstant(rows, s1), VectorType::Constant(rows,s1));
-  VERIFY_IS_APPROX(v3.setZero(rows), vzero);
-  VERIFY_IS_APPROX(v3.setOnes(rows), vones);
-
-  m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
-
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2());
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
-  VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube());
-
-  VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1));
-  VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1));
-  m3 = m1; m3.cwise() += 1;
-  VERIFY_IS_APPROX(m1 + mones, m3);
-  m3 = m1; m3.cwise() -= 1;
-  VERIFY_IS_APPROX(m1 - mones, m3);
-
-  VERIFY_IS_APPROX(m2, m2.cwise() * mones);
-  VERIFY_IS_APPROX(m1.cwise() * m2,  m2.cwise() * m1);
-  m3 = m1;
-  m3.cwise() *= m2;
-  VERIFY_IS_APPROX(m3, m1.cwise() * m2);
-  
-  VERIFY_IS_APPROX(mones,    m2.cwise()/m2);
-  if(NumTraits<Scalar>::HasFloatingPoint)
-  {
-    VERIFY_IS_APPROX(m1.cwise() / m2,    m1.cwise() * (m2.cwise().inverse()));
-    m3 = m1.cwise().abs().cwise().sqrt();
-    VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs());
-    VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs());
-    VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs());
-
-    VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
-    m3 = (m1.cwise().abs().cwise()<=RealScalar(0.01)).select(mones,m1);
-    VERIFY_IS_APPROX(m3.cwise().pow(-1), m3.cwise().inverse());
-    m3 = m1.cwise().abs();
-    VERIFY_IS_APPROX(m3.cwise().pow(RealScalar(0.5)), m3.cwise().sqrt());
-    
-//     VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos());
-    VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square());
-    m3 = m1;
-    m3.cwise() /= m2;
-    VERIFY_IS_APPROX(m3, m1.cwise() / m2);
-  }
-
-  // check min
-  VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) );
-  VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 );
-  VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones );
-
-  // check max
-  VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) );
-  VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 );
-  VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones );
-  
-  VERIFY( (m1.cwise() == m1).all() );
-  VERIFY( (m1.cwise() != m2).any() );
-  VERIFY(!(m1.cwise() == (m1+mones)).any() );
-  if (rows*cols>1)
-  {
-    m3 = m1;
-    m3(r,c) += 1;
-    VERIFY( (m1.cwise() == m3).any() );
-    VERIFY( !(m1.cwise() == m3).all() );
-  }
-  VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() );
-  VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() );
-  VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() );
-  VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() );
-
-  VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
-  VERIFY( !(m1.cwise()<m1.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
-  VERIFY( !(m1.cwise()>m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
-}
-
-void test_eigen2_cwiseop()
-{
-  for(int i = 0; i < g_repeat ; i++) {
-    CALL_SUBTEST_1( cwiseops(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( cwiseops(Matrix4d()) );
-    CALL_SUBTEST_3( cwiseops(MatrixXf(3, 3)) );
-    CALL_SUBTEST_3( cwiseops(MatrixXf(22, 22)) );
-    CALL_SUBTEST_4( cwiseops(MatrixXi(8, 12)) );
-    CALL_SUBTEST_5( cwiseops(MatrixXd(20, 20)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_determinant.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_determinant.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_determinant.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_determinant.cpp
@@ -1,61 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/LU>
-
-template<typename MatrixType> void determinant(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Determinant.h
-  */
-  int size = m.rows();
-
-  MatrixType m1(size, size), m2(size, size);
-  m1.setRandom();
-  m2.setRandom();
-  typedef typename MatrixType::Scalar Scalar;
-  Scalar x = ei_random<Scalar>();
-  VERIFY_IS_APPROX(MatrixType::Identity(size, size).determinant(), Scalar(1));
-  VERIFY_IS_APPROX((m1*m2).determinant(), m1.determinant() * m2.determinant());
-  if(size==1) return;
-  int i = ei_random<int>(0, size-1);
-  int j;
-  do {
-    j = ei_random<int>(0, size-1);
-  } while(j==i);
-  m2 = m1;
-  m2.row(i).swap(m2.row(j));
-  VERIFY_IS_APPROX(m2.determinant(), -m1.determinant());
-  m2 = m1;
-  m2.col(i).swap(m2.col(j));
-  VERIFY_IS_APPROX(m2.determinant(), -m1.determinant());
-  VERIFY_IS_APPROX(m2.determinant(), m2.transpose().determinant());
-  VERIFY_IS_APPROX(ei_conj(m2.determinant()), m2.adjoint().determinant());
-  m2 = m1;
-  m2.row(i) += x*m2.row(j);
-  VERIFY_IS_APPROX(m2.determinant(), m1.determinant());
-  m2 = m1;
-  m2.row(i) *= x;
-  VERIFY_IS_APPROX(m2.determinant(), m1.determinant() * x);
-}
-
-void test_eigen2_determinant()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( determinant(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( determinant(Matrix<double, 2, 2>()) );
-    CALL_SUBTEST_3( determinant(Matrix<double, 3, 3>()) );
-    CALL_SUBTEST_4( determinant(Matrix<double, 4, 4>()) );
-    CALL_SUBTEST_5( determinant(Matrix<std::complex<double>, 10, 10>()) );
-    CALL_SUBTEST_6( determinant(MatrixXd(20, 20)) );
-  }
-  CALL_SUBTEST_6( determinant(MatrixXd(200, 200)) );
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_dynalloc.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_dynalloc.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_dynalloc.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_dynalloc.cpp
@@ -1,131 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-#if EIGEN_ARCH_WANTS_ALIGNMENT
-#define ALIGNMENT 16
-#else
-#define ALIGNMENT 1
-#endif
-
-void check_handmade_aligned_malloc()
-{
-  for(int i = 1; i < 1000; i++)
-  {
-    char *p = (char*)ei_handmade_aligned_malloc(i);
-    VERIFY(std::size_t(p)%ALIGNMENT==0);
-    // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
-    for(int j = 0; j < i; j++) p[j]=0;
-    ei_handmade_aligned_free(p);
-  }
-}
-
-void check_aligned_malloc()
-{
-  for(int i = 1; i < 1000; i++)
-  {
-    char *p = (char*)ei_aligned_malloc(i);
-    VERIFY(std::size_t(p)%ALIGNMENT==0);
-    // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
-    for(int j = 0; j < i; j++) p[j]=0;
-    ei_aligned_free(p);
-  }
-}
-
-void check_aligned_new()
-{
-  for(int i = 1; i < 1000; i++)
-  {
-    float *p = ei_aligned_new<float>(i);
-    VERIFY(std::size_t(p)%ALIGNMENT==0);
-    // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
-    for(int j = 0; j < i; j++) p[j]=0;
-    ei_aligned_delete(p,i);
-  }
-}
-
-void check_aligned_stack_alloc()
-{
-  for(int i = 1; i < 1000; i++)
-  {
-    ei_declare_aligned_stack_constructed_variable(float, p, i, 0);
-    VERIFY(std::size_t(p)%ALIGNMENT==0);
-    // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
-    for(int j = 0; j < i; j++) p[j]=0;
-  }
-}
-
-
-// test compilation with both a struct and a class...
-struct MyStruct
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  char dummychar;
-  Vector4f avec;
-};
-
-class MyClassA
-{
-  public:
-    EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-    char dummychar;
-    Vector4f avec;
-};
-
-template<typename T> void check_dynaligned()
-{
-  T* obj = new T;
-  VERIFY(std::size_t(obj)%ALIGNMENT==0);
-  delete obj;
-}
-
-void test_eigen2_dynalloc()
-{
-  // low level dynamic memory allocation
-  CALL_SUBTEST(check_handmade_aligned_malloc());
-  CALL_SUBTEST(check_aligned_malloc());
-  CALL_SUBTEST(check_aligned_new());
-  CALL_SUBTEST(check_aligned_stack_alloc());
-
-  for (int i=0; i<g_repeat*100; ++i)
-  {
-    CALL_SUBTEST( check_dynaligned<Vector4f>() );
-    CALL_SUBTEST( check_dynaligned<Vector2d>() );
-    CALL_SUBTEST( check_dynaligned<Matrix4f>() );
-    CALL_SUBTEST( check_dynaligned<Vector4d>() );
-    CALL_SUBTEST( check_dynaligned<Vector4i>() );
-  }
-  
-  // check static allocation, who knows ?
-  {
-    MyStruct foo0;  VERIFY(std::size_t(foo0.avec.data())%ALIGNMENT==0);
-    MyClassA fooA;  VERIFY(std::size_t(fooA.avec.data())%ALIGNMENT==0);
-  }
-
-  // dynamic allocation, single object
-  for (int i=0; i<g_repeat*100; ++i)
-  {
-    MyStruct *foo0 = new MyStruct();  VERIFY(std::size_t(foo0->avec.data())%ALIGNMENT==0);
-    MyClassA *fooA = new MyClassA();  VERIFY(std::size_t(fooA->avec.data())%ALIGNMENT==0);
-    delete foo0;
-    delete fooA;
-  }
-
-  // dynamic allocation, array
-  const int N = 10;
-  for (int i=0; i<g_repeat*100; ++i)
-  {
-    MyStruct *foo0 = new MyStruct[N];  VERIFY(std::size_t(foo0->avec.data())%ALIGNMENT==0);
-    MyClassA *fooA = new MyClassA[N];  VERIFY(std::size_t(fooA->avec.data())%ALIGNMENT==0);
-    delete[] foo0;
-    delete[] fooA;
-  }
-  
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_eigensolver.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_eigensolver.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_eigensolver.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_eigensolver.cpp
@@ -1,146 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/QR>
-
-#ifdef HAS_GSL
-#include "gsl_helper.h"
-#endif
-
-template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
-{
-  /* this test covers the following files:
-     EigenSolver.h, SelfAdjointEigenSolver.h (and indirectly: Tridiagonalization.h)
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
-  typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
-
-  RealScalar largerEps = 10*test_precision<RealScalar>();
-
-  MatrixType a = MatrixType::Random(rows,cols);
-  MatrixType a1 = MatrixType::Random(rows,cols);
-  MatrixType symmA =  a.adjoint() * a + a1.adjoint() * a1;
-
-  MatrixType b = MatrixType::Random(rows,cols);
-  MatrixType b1 = MatrixType::Random(rows,cols);
-  MatrixType symmB = b.adjoint() * b + b1.adjoint() * b1;
-
-  SelfAdjointEigenSolver<MatrixType> eiSymm(symmA);
-  // generalized eigen pb
-  SelfAdjointEigenSolver<MatrixType> eiSymmGen(symmA, symmB);
-
-  #ifdef HAS_GSL
-  if (ei_is_same_type<RealScalar,double>::ret)
-  {
-    typedef GslTraits<Scalar> Gsl;
-    typename Gsl::Matrix gEvec=0, gSymmA=0, gSymmB=0;
-    typename GslTraits<RealScalar>::Vector gEval=0;
-    RealVectorType _eval;
-    MatrixType _evec;
-    convert<MatrixType>(symmA, gSymmA);
-    convert<MatrixType>(symmB, gSymmB);
-    convert<MatrixType>(symmA, gEvec);
-    gEval = GslTraits<RealScalar>::createVector(rows);
-
-    Gsl::eigen_symm(gSymmA, gEval, gEvec);
-    convert(gEval, _eval);
-    convert(gEvec, _evec);
-
-    // test gsl itself !
-    VERIFY((symmA * _evec).isApprox(_evec * _eval.asDiagonal(), largerEps));
-
-    // compare with eigen
-    VERIFY_IS_APPROX(_eval, eiSymm.eigenvalues());
-    VERIFY_IS_APPROX(_evec.cwise().abs(), eiSymm.eigenvectors().cwise().abs());
-
-    // generalized pb
-    Gsl::eigen_symm_gen(gSymmA, gSymmB, gEval, gEvec);
-    convert(gEval, _eval);
-    convert(gEvec, _evec);
-    // test GSL itself:
-    VERIFY((symmA * _evec).isApprox(symmB * (_evec * _eval.asDiagonal()), largerEps));
-
-    // compare with eigen
-    MatrixType normalized_eivec = eiSymmGen.eigenvectors()*eiSymmGen.eigenvectors().colwise().norm().asDiagonal().inverse();
-    VERIFY_IS_APPROX(_eval, eiSymmGen.eigenvalues());
-    VERIFY_IS_APPROX(_evec.cwiseAbs(), normalized_eivec.cwiseAbs());
-
-    Gsl::free(gSymmA);
-    Gsl::free(gSymmB);
-    GslTraits<RealScalar>::free(gEval);
-    Gsl::free(gEvec);
-  }
-  #endif
-
-  VERIFY((symmA * eiSymm.eigenvectors()).isApprox(
-          eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal(), largerEps));
-
-  // generalized eigen problem Ax = lBx
-  VERIFY((symmA * eiSymmGen.eigenvectors()).isApprox(
-          symmB * (eiSymmGen.eigenvectors() * eiSymmGen.eigenvalues().asDiagonal()), largerEps));
-
-  MatrixType sqrtSymmA = eiSymm.operatorSqrt();
-  VERIFY_IS_APPROX(symmA, sqrtSymmA*sqrtSymmA);
-  VERIFY_IS_APPROX(sqrtSymmA, symmA*eiSymm.operatorInverseSqrt());
-}
-
-template<typename MatrixType> void eigensolver(const MatrixType& m)
-{
-  /* this test covers the following files:
-     EigenSolver.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
-  typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
-
-  // RealScalar largerEps = 10*test_precision<RealScalar>();
-
-  MatrixType a = MatrixType::Random(rows,cols);
-  MatrixType a1 = MatrixType::Random(rows,cols);
-  MatrixType symmA =  a.adjoint() * a + a1.adjoint() * a1;
-
-  EigenSolver<MatrixType> ei0(symmA);
-  VERIFY_IS_APPROX(symmA * ei0.pseudoEigenvectors(), ei0.pseudoEigenvectors() * ei0.pseudoEigenvalueMatrix());
-  VERIFY_IS_APPROX((symmA.template cast<Complex>()) * (ei0.pseudoEigenvectors().template cast<Complex>()),
-    (ei0.pseudoEigenvectors().template cast<Complex>()) * (ei0.eigenvalues().asDiagonal()));
-
-  EigenSolver<MatrixType> ei1(a);
-  VERIFY_IS_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
-  VERIFY_IS_APPROX(a.template cast<Complex>() * ei1.eigenvectors(),
-                   ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
-
-}
-
-void test_eigen2_eigensolver()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    // very important to test a 3x3 matrix since we provide a special path for it
-    CALL_SUBTEST_1( selfadjointeigensolver(Matrix3f()) );
-    CALL_SUBTEST_2( selfadjointeigensolver(Matrix4d()) );
-    CALL_SUBTEST_3( selfadjointeigensolver(MatrixXf(7,7)) );
-    CALL_SUBTEST_4( selfadjointeigensolver(MatrixXcd(5,5)) );
-    CALL_SUBTEST_5( selfadjointeigensolver(MatrixXd(19,19)) );
-
-    CALL_SUBTEST_6( eigensolver(Matrix4f()) );
-    CALL_SUBTEST_5( eigensolver(MatrixXd(17,17)) );
-  }
-}
-

DELETED 3rd_party/eigen/test/eigen2/eigen2_first_aligned.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_first_aligned.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_first_aligned.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_first_aligned.cpp
@@ -1,49 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename Scalar>
-void test_eigen2_first_aligned_helper(Scalar *array, int size)
-{
-  const int packet_size = sizeof(Scalar) * ei_packet_traits<Scalar>::size;
-  VERIFY(((std::size_t(array) + sizeof(Scalar) * ei_alignmentOffset(array, size)) % packet_size) == 0);
-}
-
-template<typename Scalar>
-void test_eigen2_none_aligned_helper(Scalar *array, int size)
-{
-  VERIFY(ei_packet_traits<Scalar>::size == 1 || ei_alignmentOffset(array, size) == size);
-}
-
-struct some_non_vectorizable_type { float x; };
-
-void test_eigen2_first_aligned()
-{
-  EIGEN_ALIGN_128 float array_float[100];
-  test_first_aligned_helper(array_float, 50);
-  test_first_aligned_helper(array_float+1, 50);
-  test_first_aligned_helper(array_float+2, 50);
-  test_first_aligned_helper(array_float+3, 50);
-  test_first_aligned_helper(array_float+4, 50);
-  test_first_aligned_helper(array_float+5, 50);
-  
-  EIGEN_ALIGN_128 double array_double[100];
-  test_first_aligned_helper(array_double, 50);
-  test_first_aligned_helper(array_double+1, 50);
-  test_first_aligned_helper(array_double+2, 50);
-  
-  double *array_double_plus_4_bytes = (double*)(std::size_t(array_double)+4);
-  test_none_aligned_helper(array_double_plus_4_bytes, 50);
-  test_none_aligned_helper(array_double_plus_4_bytes+1, 50);
-  
-  some_non_vectorizable_type array_nonvec[100];
-  test_first_aligned_helper(array_nonvec, 100);
-  test_none_aligned_helper(array_nonvec, 100);
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_geometry.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_geometry.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_geometry.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_geometry.cpp
@@ -1,432 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/Geometry>
-#include <Eigen/LU>
-#include <Eigen/SVD>
-
-template<typename Scalar> void geometry(void)
-{
-  /* this test covers the following files:
-     Cross.h Quaternion.h, Transform.cpp
-  */
-
-  typedef Matrix<Scalar,2,2> Matrix2;
-  typedef Matrix<Scalar,3,3> Matrix3;
-  typedef Matrix<Scalar,4,4> Matrix4;
-  typedef Matrix<Scalar,2,1> Vector2;
-  typedef Matrix<Scalar,3,1> Vector3;
-  typedef Matrix<Scalar,4,1> Vector4;
-  typedef Quaternion<Scalar> Quaternionx;
-  typedef AngleAxis<Scalar> AngleAxisx;
-  typedef Transform<Scalar,2> Transform2;
-  typedef Transform<Scalar,3> Transform3;
-  typedef Scaling<Scalar,2> Scaling2;
-  typedef Scaling<Scalar,3> Scaling3;
-  typedef Translation<Scalar,2> Translation2;
-  typedef Translation<Scalar,3> Translation3;
-
-  Scalar largeEps = test_precision<Scalar>();
-  if (ei_is_same_type<Scalar,float>::ret)
-    largeEps = 1e-2f;
-
-  Vector3 v0 = Vector3::Random(),
-    v1 = Vector3::Random(),
-    v2 = Vector3::Random();
-  Vector2 u0 = Vector2::Random();
-  Matrix3 matrot1;
-
-  Scalar a = ei_random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-
-  // cross product
-  VERIFY_IS_MUCH_SMALLER_THAN(v1.cross(v2).eigen2_dot(v1), Scalar(1));
-  Matrix3 m;
-  m << v0.normalized(),
-      (v0.cross(v1)).normalized(),
-      (v0.cross(v1).cross(v0)).normalized();
-  VERIFY(m.isUnitary());
-
-  // Quaternion: Identity(), setIdentity();
-  Quaternionx q1, q2;
-  q2.setIdentity();
-  VERIFY_IS_APPROX(Quaternionx(Quaternionx::Identity()).coeffs(), q2.coeffs());
-  q1.coeffs().setRandom();
-  VERIFY_IS_APPROX(q1.coeffs(), (q1*q2).coeffs());
-
-  // unitOrthogonal
-  VERIFY_IS_MUCH_SMALLER_THAN(u0.unitOrthogonal().eigen2_dot(u0), Scalar(1));
-  VERIFY_IS_MUCH_SMALLER_THAN(v0.unitOrthogonal().eigen2_dot(v0), Scalar(1));
-  VERIFY_IS_APPROX(u0.unitOrthogonal().norm(), Scalar(1));
-  VERIFY_IS_APPROX(v0.unitOrthogonal().norm(), Scalar(1));
-
-
-  VERIFY_IS_APPROX(v0, AngleAxisx(a, v0.normalized()) * v0);
-  VERIFY_IS_APPROX(-v0, AngleAxisx(Scalar(M_PI), v0.unitOrthogonal()) * v0);
-  VERIFY_IS_APPROX(ei_cos(a)*v0.squaredNorm(), v0.eigen2_dot(AngleAxisx(a, v0.unitOrthogonal()) * v0));
-  m = AngleAxisx(a, v0.normalized()).toRotationMatrix().adjoint();
-  VERIFY_IS_APPROX(Matrix3::Identity(), m * AngleAxisx(a, v0.normalized()));
-  VERIFY_IS_APPROX(Matrix3::Identity(), AngleAxisx(a, v0.normalized()) * m);
-
-  q1 = AngleAxisx(a, v0.normalized());
-  q2 = AngleAxisx(a, v1.normalized());
-
-  // angular distance
-  Scalar refangle = ei_abs(AngleAxisx(q1.inverse()*q2).angle());
-  if (refangle>Scalar(M_PI))
-    refangle = Scalar(2)*Scalar(M_PI) - refangle;
-  
-  if((q1.coeffs()-q2.coeffs()).norm() > 10*largeEps)
-  {
-    VERIFY(ei_isApprox(q1.angularDistance(q2), refangle, largeEps));
-  }
-
-  // rotation matrix conversion
-  VERIFY_IS_APPROX(q1 * v2, q1.toRotationMatrix() * v2);
-  VERIFY_IS_APPROX(q1 * q2 * v2,
-    q1.toRotationMatrix() * q2.toRotationMatrix() * v2);
-
-  VERIFY( (q2*q1).isApprox(q1*q2, largeEps) || !(q2 * q1 * v2).isApprox(
-    q1.toRotationMatrix() * q2.toRotationMatrix() * v2));
-
-  q2 = q1.toRotationMatrix();
-  VERIFY_IS_APPROX(q1*v1,q2*v1);
-
-  matrot1 = AngleAxisx(Scalar(0.1), Vector3::UnitX())
-          * AngleAxisx(Scalar(0.2), Vector3::UnitY())
-          * AngleAxisx(Scalar(0.3), Vector3::UnitZ());
-  VERIFY_IS_APPROX(matrot1 * v1,
-       AngleAxisx(Scalar(0.1), Vector3(1,0,0)).toRotationMatrix()
-    * (AngleAxisx(Scalar(0.2), Vector3(0,1,0)).toRotationMatrix()
-    * (AngleAxisx(Scalar(0.3), Vector3(0,0,1)).toRotationMatrix() * v1)));
-
-  // angle-axis conversion
-  AngleAxisx aa = q1;
-  VERIFY_IS_APPROX(q1 * v1, Quaternionx(aa) * v1);
-  VERIFY_IS_NOT_APPROX(q1 * v1, Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1);
-
-  // from two vector creation
-  VERIFY_IS_APPROX(v2.normalized(),(q2.setFromTwoVectors(v1,v2)*v1).normalized());
-  VERIFY_IS_APPROX(v2.normalized(),(q2.setFromTwoVectors(v1,v2)*v1).normalized());
-
-  // inverse and conjugate
-  VERIFY_IS_APPROX(q1 * (q1.inverse() * v1), v1);
-  VERIFY_IS_APPROX(q1 * (q1.conjugate() * v1), v1);
-
-  // AngleAxis
-  VERIFY_IS_APPROX(AngleAxisx(a,v1.normalized()).toRotationMatrix(),
-    Quaternionx(AngleAxisx(a,v1.normalized())).toRotationMatrix());
-
-  AngleAxisx aa1;
-  m = q1.toRotationMatrix();
-  aa1 = m;
-  VERIFY_IS_APPROX(AngleAxisx(m).toRotationMatrix(),
-    Quaternionx(m).toRotationMatrix());
-
-  // Transform
-  // TODO complete the tests !
-  a = 0;
-  while (ei_abs(a)<Scalar(0.1))
-    a = ei_random<Scalar>(-Scalar(0.4)*Scalar(M_PI), Scalar(0.4)*Scalar(M_PI));
-  q1 = AngleAxisx(a, v0.normalized());
-  Transform3 t0, t1, t2;
-  // first test setIdentity() and Identity()
-  t0.setIdentity();
-  VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
-  t0.matrix().setZero();
-  t0 = Transform3::Identity();
-  VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
-
-  t0.linear() = q1.toRotationMatrix();
-  t1.setIdentity();
-  t1.linear() = q1.toRotationMatrix();
-
-  v0 << 50, 2, 1;//= ei_random_matrix<Vector3>().cwiseProduct(Vector3(10,2,0.5));
-  t0.scale(v0);
-  t1.prescale(v0);
-
-  VERIFY_IS_APPROX( (t0 * Vector3(1,0,0)).norm(), v0.x());
-  //VERIFY(!ei_isApprox((t1 * Vector3(1,0,0)).norm(), v0.x()));
-
-  t0.setIdentity();
-  t1.setIdentity();
-  v1 << 1, 2, 3;
-  t0.linear() = q1.toRotationMatrix();
-  t0.pretranslate(v0);
-  t0.scale(v1);
-  t1.linear() = q1.conjugate().toRotationMatrix();
-  t1.prescale(v1.cwise().inverse());
-  t1.translate(-v0);
-
-  VERIFY((t0.matrix() * t1.matrix()).isIdentity(test_precision<Scalar>()));
-
-  t1.fromPositionOrientationScale(v0, q1, v1);
-  VERIFY_IS_APPROX(t1.matrix(), t0.matrix());
-  VERIFY_IS_APPROX(t1*v1, t0*v1);
-
-  t0.setIdentity(); t0.scale(v0).rotate(q1.toRotationMatrix());
-  t1.setIdentity(); t1.scale(v0).rotate(q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity(); t0.scale(v0).rotate(AngleAxisx(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  VERIFY_IS_APPROX(t0.scale(a).matrix(), t1.scale(Vector3::Constant(a)).matrix());
-  VERIFY_IS_APPROX(t0.prescale(a).matrix(), t1.prescale(Vector3::Constant(a)).matrix());
-
-  // More transform constructors, operator=, operator*=
-
-  Matrix3 mat3 = Matrix3::Random();
-  Matrix4 mat4;
-  mat4 << mat3 , Vector3::Zero() , Vector4::Zero().transpose();
-  Transform3 tmat3(mat3), tmat4(mat4);
-  tmat4.matrix()(3,3) = Scalar(1);
-  VERIFY_IS_APPROX(tmat3.matrix(), tmat4.matrix());
-
-  Scalar a3 = ei_random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-  Vector3 v3 = Vector3::Random().normalized();
-  AngleAxisx aa3(a3, v3);
-  Transform3 t3(aa3);
-  Transform3 t4;
-  t4 = aa3;
-  VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
-  t4.rotate(AngleAxisx(-a3,v3));
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= aa3;
-  VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
-
-  v3 = Vector3::Random();
-  Translation3 tv3(v3);
-  Transform3 t5(tv3);
-  t4 = tv3;
-  VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-  t4.translate(-v3);
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= tv3;
-  VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-
-  Scaling3 sv3(v3);
-  Transform3 t6(sv3);
-  t4 = sv3;
-  VERIFY_IS_APPROX(t6.matrix(), t4.matrix());
-  t4.scale(v3.cwise().inverse());
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= sv3;
-  VERIFY_IS_APPROX(t6.matrix(), t4.matrix());
-
-  // matrix * transform
-  VERIFY_IS_APPROX(Transform3(t3.matrix()*t4).matrix(), Transform3(t3*t4).matrix());
-
-  // chained Transform product
-  VERIFY_IS_APPROX(((t3*t4)*t5).matrix(), (t3*(t4*t5)).matrix());
-
-  // check that Transform product doesn't have aliasing problems
-  t5 = t4;
-  t5 = t5*t5;
-  VERIFY_IS_APPROX(t5, t4*t4);
-
-  // 2D transformation
-  Transform2 t20, t21;
-  Vector2 v20 = Vector2::Random();
-  Vector2 v21 = Vector2::Random();
-  for (int k=0; k<2; ++k)
-    if (ei_abs(v21[k])<Scalar(1e-3)) v21[k] = Scalar(1e-3);
-  t21.setIdentity();
-  t21.linear() = Rotation2D<Scalar>(a).toRotationMatrix();
-  VERIFY_IS_APPROX(t20.fromPositionOrientationScale(v20,a,v21).matrix(),
-    t21.pretranslate(v20).scale(v21).matrix());
-
-  t21.setIdentity();
-  t21.linear() = Rotation2D<Scalar>(-a).toRotationMatrix();
-  VERIFY( (t20.fromPositionOrientationScale(v20,a,v21)
-        * (t21.prescale(v21.cwise().inverse()).translate(-v20))).matrix().isIdentity(test_precision<Scalar>()) );
-
-  // Transform - new API
-  // 3D
-  t0.setIdentity();
-  t0.rotate(q1).scale(v0).translate(v0);
-  // mat * scaling and mat * translation
-  t1 = (Matrix3(q1) * Scaling3(v0)) * Translation3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // mat * transformation and scaling * translation
-  t1 = Matrix3(q1) * (Scaling3(v0) * Translation3(v0));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity();
-  t0.prerotate(q1).prescale(v0).pretranslate(v0);
-  // translation * scaling and transformation * mat
-  t1 = (Translation3(v0) * Scaling3(v0)) * Matrix3(q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // scaling * mat and translation * mat
-  t1 = Translation3(v0) * (Scaling3(v0) * Matrix3(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity();
-  t0.scale(v0).translate(v0).rotate(q1);
-  // translation * mat and scaling * transformation
-  t1 = Scaling3(v0) * (Translation3(v0) * Matrix3(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // transformation * scaling
-  t0.scale(v0);
-  t1 = t1 * Scaling3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // transformation * translation
-  t0.translate(v0);
-  t1 = t1 * Translation3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // translation * transformation
-  t0.pretranslate(v0);
-  t1 = Translation3(v0) * t1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // transform * quaternion
-  t0.rotate(q1);
-  t1 = t1 * q1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // translation * quaternion
-  t0.translate(v1).rotate(q1);
-  t1 = t1 * (Translation3(v1) * q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // scaling * quaternion
-  t0.scale(v1).rotate(q1);
-  t1 = t1 * (Scaling3(v1) * q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * transform
-  t0.prerotate(q1);
-  t1 = q1 * t1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * translation
-  t0.rotate(q1).translate(v1);
-  t1 = t1 * (q1 * Translation3(v1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * scaling
-  t0.rotate(q1).scale(v1);
-  t1 = t1 * (q1 * Scaling3(v1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // translation * vector
-  t0.setIdentity();
-  t0.translate(v0);
-  VERIFY_IS_APPROX(t0 * v1, Translation3(v0) * v1);
-
-  // scaling * vector
-  t0.setIdentity();
-  t0.scale(v0);
-  VERIFY_IS_APPROX(t0 * v1, Scaling3(v0) * v1);
-
-  // test transform inversion
-  t0.setIdentity();
-  t0.translate(v0);
-  t0.linear().setRandom();
-  VERIFY_IS_APPROX(t0.inverse(Affine), t0.matrix().inverse());
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1);
-  VERIFY_IS_APPROX(t0.inverse(Isometry), t0.matrix().inverse());
-
-  // test extract rotation and scaling
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1).scale(v1);
-  VERIFY_IS_APPROX(t0.rotation() * v1, Matrix3(q1) * v1);
-
-  Matrix3 mat_rotation, mat_scaling;
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1).scale(v1);
-  t0.computeRotationScaling(&mat_rotation, &mat_scaling);
-  VERIFY_IS_APPROX(t0.linear(), mat_rotation * mat_scaling);
-  VERIFY_IS_APPROX(mat_rotation*mat_rotation.adjoint(), Matrix3::Identity());
-  VERIFY_IS_APPROX(mat_rotation.determinant(), Scalar(1));
-  t0.computeScalingRotation(&mat_scaling, &mat_rotation);
-  VERIFY_IS_APPROX(t0.linear(), mat_scaling * mat_rotation);
-  VERIFY_IS_APPROX(mat_rotation*mat_rotation.adjoint(), Matrix3::Identity());
-  VERIFY_IS_APPROX(mat_rotation.determinant(), Scalar(1));
-
-  // test casting
-  Transform<float,3> t1f = t1.template cast<float>();
-  VERIFY_IS_APPROX(t1f.template cast<Scalar>(),t1);
-  Transform<double,3> t1d = t1.template cast<double>();
-  VERIFY_IS_APPROX(t1d.template cast<Scalar>(),t1);
-
-  Translation3 tr1(v0);
-  Translation<float,3> tr1f = tr1.template cast<float>();
-  VERIFY_IS_APPROX(tr1f.template cast<Scalar>(),tr1);
-  Translation<double,3> tr1d = tr1.template cast<double>();
-  VERIFY_IS_APPROX(tr1d.template cast<Scalar>(),tr1);
-
-  Scaling3 sc1(v0);
-  Scaling<float,3> sc1f = sc1.template cast<float>();
-  VERIFY_IS_APPROX(sc1f.template cast<Scalar>(),sc1);
-  Scaling<double,3> sc1d = sc1.template cast<double>();
-  VERIFY_IS_APPROX(sc1d.template cast<Scalar>(),sc1);
-
-  Quaternion<float> q1f = q1.template cast<float>();
-  VERIFY_IS_APPROX(q1f.template cast<Scalar>(),q1);
-  Quaternion<double> q1d = q1.template cast<double>();
-  VERIFY_IS_APPROX(q1d.template cast<Scalar>(),q1);
-
-  AngleAxis<float> aa1f = aa1.template cast<float>();
-  VERIFY_IS_APPROX(aa1f.template cast<Scalar>(),aa1);
-  AngleAxis<double> aa1d = aa1.template cast<double>();
-  VERIFY_IS_APPROX(aa1d.template cast<Scalar>(),aa1);
-
-  Rotation2D<Scalar> r2d1(ei_random<Scalar>());
-  Rotation2D<float> r2d1f = r2d1.template cast<float>();
-  VERIFY_IS_APPROX(r2d1f.template cast<Scalar>(),r2d1);
-  Rotation2D<double> r2d1d = r2d1.template cast<double>();
-  VERIFY_IS_APPROX(r2d1d.template cast<Scalar>(),r2d1);
-
-  m = q1;
-//   m.col(1) = Vector3(0,ei_random<Scalar>(),ei_random<Scalar>()).normalized();
-//   m.col(0) = Vector3(-1,0,0).normalized();
-//   m.col(2) = m.col(0).cross(m.col(1));
-  #define VERIFY_EULER(I,J,K, X,Y,Z) { \
-    Vector3 ea = m.eulerAngles(I,J,K); \
-    Matrix3 m1 = Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z())); \
-    VERIFY_IS_APPROX(m, m1); \
-    VERIFY_IS_APPROX(m,  Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z()))); \
-  }
-  VERIFY_EULER(0,1,2, X,Y,Z);
-  VERIFY_EULER(0,1,0, X,Y,X);
-  VERIFY_EULER(0,2,1, X,Z,Y);
-  VERIFY_EULER(0,2,0, X,Z,X);
-
-  VERIFY_EULER(1,2,0, Y,Z,X);
-  VERIFY_EULER(1,2,1, Y,Z,Y);
-  VERIFY_EULER(1,0,2, Y,X,Z);
-  VERIFY_EULER(1,0,1, Y,X,Y);
-
-  VERIFY_EULER(2,0,1, Z,X,Y);
-  VERIFY_EULER(2,0,2, Z,X,Z);
-  VERIFY_EULER(2,1,0, Z,Y,X);
-  VERIFY_EULER(2,1,2, Z,Y,Z);
-
-  // colwise/rowwise cross product
-  mat3.setRandom();
-  Vector3 vec3 = Vector3::Random();
-  Matrix3 mcross;
-  int i = ei_random<int>(0,2);
-  mcross = mat3.colwise().cross(vec3);
-  VERIFY_IS_APPROX(mcross.col(i), mat3.col(i).cross(vec3));
-  mcross = mat3.rowwise().cross(vec3);
-  VERIFY_IS_APPROX(mcross.row(i), mat3.row(i).cross(vec3));
-
-
-}
-
-void test_eigen2_geometry()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( geometry<float>() );
-    CALL_SUBTEST_2( geometry<double>() );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_geometry_with_eigen2_prefix.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_geometry_with_eigen2_prefix.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_geometry_with_eigen2_prefix.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_geometry_with_eigen2_prefix.cpp
@@ -1,435 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#define EIGEN2_SUPPORT_STAGE15_RESOLVE_API_CONFLICTS_WARN
-
-#include "main.h"
-#include <Eigen/Geometry>
-#include <Eigen/LU>
-#include <Eigen/SVD>
-
-template<typename Scalar> void geometry(void)
-{
-  /* this test covers the following files:
-     Cross.h Quaternion.h, Transform.cpp
-  */
-
-  typedef Matrix<Scalar,2,2> Matrix2;
-  typedef Matrix<Scalar,3,3> Matrix3;
-  typedef Matrix<Scalar,4,4> Matrix4;
-  typedef Matrix<Scalar,2,1> Vector2;
-  typedef Matrix<Scalar,3,1> Vector3;
-  typedef Matrix<Scalar,4,1> Vector4;
-  typedef eigen2_Quaternion<Scalar> Quaternionx;
-  typedef eigen2_AngleAxis<Scalar> AngleAxisx;
-  typedef eigen2_Transform<Scalar,2> Transform2;
-  typedef eigen2_Transform<Scalar,3> Transform3;
-  typedef eigen2_Scaling<Scalar,2> Scaling2;
-  typedef eigen2_Scaling<Scalar,3> Scaling3;
-  typedef eigen2_Translation<Scalar,2> Translation2;
-  typedef eigen2_Translation<Scalar,3> Translation3;
-
-  Scalar largeEps = test_precision<Scalar>();
-  if (ei_is_same_type<Scalar,float>::ret)
-    largeEps = 1e-2f;
-
-  Vector3 v0 = Vector3::Random(),
-    v1 = Vector3::Random(),
-    v2 = Vector3::Random();
-  Vector2 u0 = Vector2::Random();
-  Matrix3 matrot1;
-
-  Scalar a = ei_random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-
-  // cross product
-  VERIFY_IS_MUCH_SMALLER_THAN(v1.cross(v2).eigen2_dot(v1), Scalar(1));
-  Matrix3 m;
-  m << v0.normalized(),
-      (v0.cross(v1)).normalized(),
-      (v0.cross(v1).cross(v0)).normalized();
-  VERIFY(m.isUnitary());
-
-  // Quaternion: Identity(), setIdentity();
-  Quaternionx q1, q2;
-  q2.setIdentity();
-  VERIFY_IS_APPROX(Quaternionx(Quaternionx::Identity()).coeffs(), q2.coeffs());
-  q1.coeffs().setRandom();
-  VERIFY_IS_APPROX(q1.coeffs(), (q1*q2).coeffs());
-
-  // unitOrthogonal
-  VERIFY_IS_MUCH_SMALLER_THAN(u0.unitOrthogonal().eigen2_dot(u0), Scalar(1));
-  VERIFY_IS_MUCH_SMALLER_THAN(v0.unitOrthogonal().eigen2_dot(v0), Scalar(1));
-  VERIFY_IS_APPROX(u0.unitOrthogonal().norm(), Scalar(1));
-  VERIFY_IS_APPROX(v0.unitOrthogonal().norm(), Scalar(1));
-
-
-  VERIFY_IS_APPROX(v0, AngleAxisx(a, v0.normalized()) * v0);
-  VERIFY_IS_APPROX(-v0, AngleAxisx(Scalar(M_PI), v0.unitOrthogonal()) * v0);
-  VERIFY_IS_APPROX(ei_cos(a)*v0.squaredNorm(), v0.eigen2_dot(AngleAxisx(a, v0.unitOrthogonal()) * v0));
-  m = AngleAxisx(a, v0.normalized()).toRotationMatrix().adjoint();
-  VERIFY_IS_APPROX(Matrix3::Identity(), m * AngleAxisx(a, v0.normalized()));
-  VERIFY_IS_APPROX(Matrix3::Identity(), AngleAxisx(a, v0.normalized()) * m);
-
-  q1 = AngleAxisx(a, v0.normalized());
-  q2 = AngleAxisx(a, v1.normalized());
-
-  // angular distance
-  Scalar refangle = ei_abs(AngleAxisx(q1.inverse()*q2).angle());
-  if (refangle>Scalar(M_PI))
-    refangle = Scalar(2)*Scalar(M_PI) - refangle;
-  
-  if((q1.coeffs()-q2.coeffs()).norm() > 10*largeEps)
-  {
-    VERIFY(ei_isApprox(q1.angularDistance(q2), refangle, largeEps));
-  }
-
-  // rotation matrix conversion
-  VERIFY_IS_APPROX(q1 * v2, q1.toRotationMatrix() * v2);
-  VERIFY_IS_APPROX(q1 * q2 * v2,
-    q1.toRotationMatrix() * q2.toRotationMatrix() * v2);
-
-  VERIFY( (q2*q1).isApprox(q1*q2, largeEps) || !(q2 * q1 * v2).isApprox(
-    q1.toRotationMatrix() * q2.toRotationMatrix() * v2));
-
-  q2 = q1.toRotationMatrix();
-  VERIFY_IS_APPROX(q1*v1,q2*v1);
-
-  matrot1 = AngleAxisx(Scalar(0.1), Vector3::UnitX())
-          * AngleAxisx(Scalar(0.2), Vector3::UnitY())
-          * AngleAxisx(Scalar(0.3), Vector3::UnitZ());
-  VERIFY_IS_APPROX(matrot1 * v1,
-       AngleAxisx(Scalar(0.1), Vector3(1,0,0)).toRotationMatrix()
-    * (AngleAxisx(Scalar(0.2), Vector3(0,1,0)).toRotationMatrix()
-    * (AngleAxisx(Scalar(0.3), Vector3(0,0,1)).toRotationMatrix() * v1)));
-
-  // angle-axis conversion
-  AngleAxisx aa = q1;
-  VERIFY_IS_APPROX(q1 * v1, Quaternionx(aa) * v1);
-  VERIFY_IS_NOT_APPROX(q1 * v1, Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1);
-
-  // from two vector creation
-  VERIFY_IS_APPROX(v2.normalized(),(q2.setFromTwoVectors(v1,v2)*v1).normalized());
-  VERIFY_IS_APPROX(v2.normalized(),(q2.setFromTwoVectors(v1,v2)*v1).normalized());
-
-  // inverse and conjugate
-  VERIFY_IS_APPROX(q1 * (q1.inverse() * v1), v1);
-  VERIFY_IS_APPROX(q1 * (q1.conjugate() * v1), v1);
-
-  // AngleAxis
-  VERIFY_IS_APPROX(AngleAxisx(a,v1.normalized()).toRotationMatrix(),
-    Quaternionx(AngleAxisx(a,v1.normalized())).toRotationMatrix());
-
-  AngleAxisx aa1;
-  m = q1.toRotationMatrix();
-  aa1 = m;
-  VERIFY_IS_APPROX(AngleAxisx(m).toRotationMatrix(),
-    Quaternionx(m).toRotationMatrix());
-
-  // Transform
-  // TODO complete the tests !
-  a = 0;
-  while (ei_abs(a)<Scalar(0.1))
-    a = ei_random<Scalar>(-Scalar(0.4)*Scalar(M_PI), Scalar(0.4)*Scalar(M_PI));
-  q1 = AngleAxisx(a, v0.normalized());
-  Transform3 t0, t1, t2;
-  // first test setIdentity() and Identity()
-  t0.setIdentity();
-  VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
-  t0.matrix().setZero();
-  t0 = Transform3::Identity();
-  VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
-
-  t0.linear() = q1.toRotationMatrix();
-  t1.setIdentity();
-  t1.linear() = q1.toRotationMatrix();
-
-  v0 << 50, 2, 1;//= ei_random_matrix<Vector3>().cwiseProduct(Vector3(10,2,0.5));
-  t0.scale(v0);
-  t1.prescale(v0);
-
-  VERIFY_IS_APPROX( (t0 * Vector3(1,0,0)).norm(), v0.x());
-  //VERIFY(!ei_isApprox((t1 * Vector3(1,0,0)).norm(), v0.x()));
-
-  t0.setIdentity();
-  t1.setIdentity();
-  v1 << 1, 2, 3;
-  t0.linear() = q1.toRotationMatrix();
-  t0.pretranslate(v0);
-  t0.scale(v1);
-  t1.linear() = q1.conjugate().toRotationMatrix();
-  t1.prescale(v1.cwise().inverse());
-  t1.translate(-v0);
-
-  VERIFY((t0.matrix() * t1.matrix()).isIdentity(test_precision<Scalar>()));
-
-  t1.fromPositionOrientationScale(v0, q1, v1);
-  VERIFY_IS_APPROX(t1.matrix(), t0.matrix());
-  VERIFY_IS_APPROX(t1*v1, t0*v1);
-
-  t0.setIdentity(); t0.scale(v0).rotate(q1.toRotationMatrix());
-  t1.setIdentity(); t1.scale(v0).rotate(q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity(); t0.scale(v0).rotate(AngleAxisx(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  VERIFY_IS_APPROX(t0.scale(a).matrix(), t1.scale(Vector3::Constant(a)).matrix());
-  VERIFY_IS_APPROX(t0.prescale(a).matrix(), t1.prescale(Vector3::Constant(a)).matrix());
-
-  // More transform constructors, operator=, operator*=
-
-  Matrix3 mat3 = Matrix3::Random();
-  Matrix4 mat4;
-  mat4 << mat3 , Vector3::Zero() , Vector4::Zero().transpose();
-  Transform3 tmat3(mat3), tmat4(mat4);
-  tmat4.matrix()(3,3) = Scalar(1);
-  VERIFY_IS_APPROX(tmat3.matrix(), tmat4.matrix());
-
-  Scalar a3 = ei_random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-  Vector3 v3 = Vector3::Random().normalized();
-  AngleAxisx aa3(a3, v3);
-  Transform3 t3(aa3);
-  Transform3 t4;
-  t4 = aa3;
-  VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
-  t4.rotate(AngleAxisx(-a3,v3));
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= aa3;
-  VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
-
-  v3 = Vector3::Random();
-  Translation3 tv3(v3);
-  Transform3 t5(tv3);
-  t4 = tv3;
-  VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-  t4.translate(-v3);
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= tv3;
-  VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-
-  Scaling3 sv3(v3);
-  Transform3 t6(sv3);
-  t4 = sv3;
-  VERIFY_IS_APPROX(t6.matrix(), t4.matrix());
-  t4.scale(v3.cwise().inverse());
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= sv3;
-  VERIFY_IS_APPROX(t6.matrix(), t4.matrix());
-
-  // matrix * transform
-  VERIFY_IS_APPROX(Transform3(t3.matrix()*t4).matrix(), Transform3(t3*t4).matrix());
-
-  // chained Transform product
-  VERIFY_IS_APPROX(((t3*t4)*t5).matrix(), (t3*(t4*t5)).matrix());
-
-  // check that Transform product doesn't have aliasing problems
-  t5 = t4;
-  t5 = t5*t5;
-  VERIFY_IS_APPROX(t5, t4*t4);
-
-  // 2D transformation
-  Transform2 t20, t21;
-  Vector2 v20 = Vector2::Random();
-  Vector2 v21 = Vector2::Random();
-  for (int k=0; k<2; ++k)
-    if (ei_abs(v21[k])<Scalar(1e-3)) v21[k] = Scalar(1e-3);
-  t21.setIdentity();
-  t21.linear() = Rotation2D<Scalar>(a).toRotationMatrix();
-  VERIFY_IS_APPROX(t20.fromPositionOrientationScale(v20,a,v21).matrix(),
-    t21.pretranslate(v20).scale(v21).matrix());
-
-  t21.setIdentity();
-  t21.linear() = Rotation2D<Scalar>(-a).toRotationMatrix();
-  VERIFY( (t20.fromPositionOrientationScale(v20,a,v21)
-        * (t21.prescale(v21.cwise().inverse()).translate(-v20))).matrix().isIdentity(test_precision<Scalar>()) );
-
-  // Transform - new API
-  // 3D
-  t0.setIdentity();
-  t0.rotate(q1).scale(v0).translate(v0);
-  // mat * scaling and mat * translation
-  t1 = (Matrix3(q1) * Scaling3(v0)) * Translation3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // mat * transformation and scaling * translation
-  t1 = Matrix3(q1) * (Scaling3(v0) * Translation3(v0));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity();
-  t0.prerotate(q1).prescale(v0).pretranslate(v0);
-  // translation * scaling and transformation * mat
-  t1 = (Translation3(v0) * Scaling3(v0)) * Matrix3(q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // scaling * mat and translation * mat
-  t1 = Translation3(v0) * (Scaling3(v0) * Matrix3(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity();
-  t0.scale(v0).translate(v0).rotate(q1);
-  // translation * mat and scaling * transformation
-  t1 = Scaling3(v0) * (Translation3(v0) * Matrix3(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // transformation * scaling
-  t0.scale(v0);
-  t1 = t1 * Scaling3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // transformation * translation
-  t0.translate(v0);
-  t1 = t1 * Translation3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // translation * transformation
-  t0.pretranslate(v0);
-  t1 = Translation3(v0) * t1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // transform * quaternion
-  t0.rotate(q1);
-  t1 = t1 * q1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // translation * quaternion
-  t0.translate(v1).rotate(q1);
-  t1 = t1 * (Translation3(v1) * q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // scaling * quaternion
-  t0.scale(v1).rotate(q1);
-  t1 = t1 * (Scaling3(v1) * q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * transform
-  t0.prerotate(q1);
-  t1 = q1 * t1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * translation
-  t0.rotate(q1).translate(v1);
-  t1 = t1 * (q1 * Translation3(v1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * scaling
-  t0.rotate(q1).scale(v1);
-  t1 = t1 * (q1 * Scaling3(v1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // translation * vector
-  t0.setIdentity();
-  t0.translate(v0);
-  VERIFY_IS_APPROX(t0 * v1, Translation3(v0) * v1);
-
-  // scaling * vector
-  t0.setIdentity();
-  t0.scale(v0);
-  VERIFY_IS_APPROX(t0 * v1, Scaling3(v0) * v1);
-
-  // test transform inversion
-  t0.setIdentity();
-  t0.translate(v0);
-  t0.linear().setRandom();
-  VERIFY_IS_APPROX(t0.inverse(Affine), t0.matrix().inverse());
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1);
-  VERIFY_IS_APPROX(t0.inverse(Isometry), t0.matrix().inverse());
-
-  // test extract rotation and scaling
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1).scale(v1);
-  VERIFY_IS_APPROX(t0.rotation() * v1, Matrix3(q1) * v1);
-
-  Matrix3 mat_rotation, mat_scaling;
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1).scale(v1);
-  t0.computeRotationScaling(&mat_rotation, &mat_scaling);
-  VERIFY_IS_APPROX(t0.linear(), mat_rotation * mat_scaling);
-  VERIFY_IS_APPROX(mat_rotation*mat_rotation.adjoint(), Matrix3::Identity());
-  VERIFY_IS_APPROX(mat_rotation.determinant(), Scalar(1));
-  t0.computeScalingRotation(&mat_scaling, &mat_rotation);
-  VERIFY_IS_APPROX(t0.linear(), mat_scaling * mat_rotation);
-  VERIFY_IS_APPROX(mat_rotation*mat_rotation.adjoint(), Matrix3::Identity());
-  VERIFY_IS_APPROX(mat_rotation.determinant(), Scalar(1));
-
-  // test casting
-  eigen2_Transform<float,3> t1f = t1.template cast<float>();
-  VERIFY_IS_APPROX(t1f.template cast<Scalar>(),t1);
-  eigen2_Transform<double,3> t1d = t1.template cast<double>();
-  VERIFY_IS_APPROX(t1d.template cast<Scalar>(),t1);
-
-  Translation3 tr1(v0);
-  eigen2_Translation<float,3> tr1f = tr1.template cast<float>();
-  VERIFY_IS_APPROX(tr1f.template cast<Scalar>(),tr1);
-  eigen2_Translation<double,3> tr1d = tr1.template cast<double>();
-  VERIFY_IS_APPROX(tr1d.template cast<Scalar>(),tr1);
-
-  Scaling3 sc1(v0);
-  eigen2_Scaling<float,3> sc1f = sc1.template cast<float>();
-  VERIFY_IS_APPROX(sc1f.template cast<Scalar>(),sc1);
-  eigen2_Scaling<double,3> sc1d = sc1.template cast<double>();
-  VERIFY_IS_APPROX(sc1d.template cast<Scalar>(),sc1);
-
-  eigen2_Quaternion<float> q1f = q1.template cast<float>();
-  VERIFY_IS_APPROX(q1f.template cast<Scalar>(),q1);
-  eigen2_Quaternion<double> q1d = q1.template cast<double>();
-  VERIFY_IS_APPROX(q1d.template cast<Scalar>(),q1);
-
-  eigen2_AngleAxis<float> aa1f = aa1.template cast<float>();
-  VERIFY_IS_APPROX(aa1f.template cast<Scalar>(),aa1);
-  eigen2_AngleAxis<double> aa1d = aa1.template cast<double>();
-  VERIFY_IS_APPROX(aa1d.template cast<Scalar>(),aa1);
-
-  eigen2_Rotation2D<Scalar> r2d1(ei_random<Scalar>());
-  eigen2_Rotation2D<float> r2d1f = r2d1.template cast<float>();
-  VERIFY_IS_APPROX(r2d1f.template cast<Scalar>(),r2d1);
-  eigen2_Rotation2D<double> r2d1d = r2d1.template cast<double>();
-  VERIFY_IS_APPROX(r2d1d.template cast<Scalar>(),r2d1);
-
-  m = q1;
-//   m.col(1) = Vector3(0,ei_random<Scalar>(),ei_random<Scalar>()).normalized();
-//   m.col(0) = Vector3(-1,0,0).normalized();
-//   m.col(2) = m.col(0).cross(m.col(1));
-  #define VERIFY_EULER(I,J,K, X,Y,Z) { \
-    Vector3 ea = m.eulerAngles(I,J,K); \
-    Matrix3 m1 = Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z())); \
-    VERIFY_IS_APPROX(m, m1); \
-    VERIFY_IS_APPROX(m,  Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z()))); \
-  }
-  VERIFY_EULER(0,1,2, X,Y,Z);
-  VERIFY_EULER(0,1,0, X,Y,X);
-  VERIFY_EULER(0,2,1, X,Z,Y);
-  VERIFY_EULER(0,2,0, X,Z,X);
-
-  VERIFY_EULER(1,2,0, Y,Z,X);
-  VERIFY_EULER(1,2,1, Y,Z,Y);
-  VERIFY_EULER(1,0,2, Y,X,Z);
-  VERIFY_EULER(1,0,1, Y,X,Y);
-
-  VERIFY_EULER(2,0,1, Z,X,Y);
-  VERIFY_EULER(2,0,2, Z,X,Z);
-  VERIFY_EULER(2,1,0, Z,Y,X);
-  VERIFY_EULER(2,1,2, Z,Y,Z);
-
-  // colwise/rowwise cross product
-  mat3.setRandom();
-  Vector3 vec3 = Vector3::Random();
-  Matrix3 mcross;
-  int i = ei_random<int>(0,2);
-  mcross = mat3.colwise().cross(vec3);
-  VERIFY_IS_APPROX(mcross.col(i), mat3.col(i).cross(vec3));
-  mcross = mat3.rowwise().cross(vec3);
-  VERIFY_IS_APPROX(mcross.row(i), mat3.row(i).cross(vec3));
-
-
-}
-
-void test_eigen2_geometry_with_eigen2_prefix()
-{
-  std::cout << "eigen2 support: " << EIGEN2_SUPPORT_STAGE << std::endl;
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( geometry<float>() );
-    CALL_SUBTEST_2( geometry<double>() );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_hyperplane.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_hyperplane.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_hyperplane.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_hyperplane.cpp
@@ -1,126 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/Geometry>
-#include <Eigen/LU>
-#include <Eigen/QR>
-
-template<typename HyperplaneType> void hyperplane(const HyperplaneType& _plane)
-{
-  /* this test covers the following files:
-     Hyperplane.h
-  */
-
-  const int dim = _plane.dim();
-  typedef typename HyperplaneType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, HyperplaneType::AmbientDimAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, HyperplaneType::AmbientDimAtCompileTime,
-                         HyperplaneType::AmbientDimAtCompileTime> MatrixType;
-
-  VectorType p0 = VectorType::Random(dim);
-  VectorType p1 = VectorType::Random(dim);
-
-  VectorType n0 = VectorType::Random(dim).normalized();
-  VectorType n1 = VectorType::Random(dim).normalized();
-
-  HyperplaneType pl0(n0, p0);
-  HyperplaneType pl1(n1, p1);
-  HyperplaneType pl2 = pl1;
-
-  Scalar s0 = ei_random<Scalar>();
-  Scalar s1 = ei_random<Scalar>();
-
-  VERIFY_IS_APPROX( n1.eigen2_dot(n1), Scalar(1) );
-
-  VERIFY_IS_MUCH_SMALLER_THAN( pl0.absDistance(p0), Scalar(1) );
-  VERIFY_IS_APPROX( pl1.signedDistance(p1 + n1 * s0), s0 );
-  VERIFY_IS_MUCH_SMALLER_THAN( pl1.signedDistance(pl1.projection(p0)), Scalar(1) );
-  VERIFY_IS_MUCH_SMALLER_THAN( pl1.absDistance(p1 +  pl1.normal().unitOrthogonal() * s1), Scalar(1) );
-
-  // transform
-  if (!NumTraits<Scalar>::IsComplex)
-  {
-    MatrixType rot = MatrixType::Random(dim,dim).qr().matrixQ();
-    Scaling<Scalar,HyperplaneType::AmbientDimAtCompileTime> scaling(VectorType::Random());
-    Translation<Scalar,HyperplaneType::AmbientDimAtCompileTime> translation(VectorType::Random());
-
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot).absDistance(rot * p1), Scalar(1) );
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot,Isometry).absDistance(rot * p1), Scalar(1) );
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*scaling).absDistance((rot*scaling) * p1), Scalar(1) );
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*scaling*translation)
-                                 .absDistance((rot*scaling*translation) * p1), Scalar(1) );
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*translation,Isometry)
-                                 .absDistance((rot*translation) * p1), Scalar(1) );
-  }
-
-  // casting
-  const int Dim = HyperplaneType::AmbientDimAtCompileTime;
-  typedef typename GetDifferentType<Scalar>::type OtherScalar;
-  Hyperplane<OtherScalar,Dim> hp1f = pl1.template cast<OtherScalar>();
-  VERIFY_IS_APPROX(hp1f.template cast<Scalar>(),pl1);
-  Hyperplane<Scalar,Dim> hp1d = pl1.template cast<Scalar>();
-  VERIFY_IS_APPROX(hp1d.template cast<Scalar>(),pl1);
-}
-
-template<typename Scalar> void lines()
-{
-  typedef Hyperplane<Scalar, 2> HLine;
-  typedef ParametrizedLine<Scalar, 2> PLine;
-  typedef Matrix<Scalar,2,1> Vector;
-  typedef Matrix<Scalar,3,1> CoeffsType;
-
-  for(int i = 0; i < 10; i++)
-  {
-    Vector center = Vector::Random();
-    Vector u = Vector::Random();
-    Vector v = Vector::Random();
-    Scalar a = ei_random<Scalar>();
-    while (ei_abs(a-1) < 1e-4) a = ei_random<Scalar>();
-    while (u.norm() < 1e-4) u = Vector::Random();
-    while (v.norm() < 1e-4) v = Vector::Random();
-
-    HLine line_u = HLine::Through(center + u, center + a*u);
-    HLine line_v = HLine::Through(center + v, center + a*v);
-
-    // the line equations should be normalized so that a^2+b^2=1
-    VERIFY_IS_APPROX(line_u.normal().norm(), Scalar(1));
-    VERIFY_IS_APPROX(line_v.normal().norm(), Scalar(1));
-
-    Vector result = line_u.intersection(line_v);
-
-    // the lines should intersect at the point we called "center"
-    VERIFY_IS_APPROX(result, center);
-
-    // check conversions between two types of lines
-    PLine pl(line_u); // gcc 3.3 will commit suicide if we don't name this variable
-    CoeffsType converted_coeffs(HLine(pl).coeffs());
-    converted_coeffs *= line_u.coeffs()(0)/converted_coeffs(0);
-    VERIFY(line_u.coeffs().isApprox(converted_coeffs));
-  }
-}
-
-void test_eigen2_hyperplane()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( hyperplane(Hyperplane<float,2>()) );
-    CALL_SUBTEST_2( hyperplane(Hyperplane<float,3>()) );
-    CALL_SUBTEST_3( hyperplane(Hyperplane<double,4>()) );
-    CALL_SUBTEST_4( hyperplane(Hyperplane<std::complex<double>,5>()) );
-    CALL_SUBTEST_5( lines<float>() );
-    CALL_SUBTEST_6( lines<double>() );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_inverse.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_inverse.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_inverse.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_inverse.cpp
@@ -1,62 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/LU>
-
-template<typename MatrixType> void inverse(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Inverse.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2(rows, cols),
-             identity = MatrixType::Identity(rows, rows);
-
-  while(ei_abs(m1.determinant()) < RealScalar(0.1) && rows <= 8)
-  {
-    m1 = MatrixType::Random(rows, cols);
-  }
-
-  m2 = m1.inverse();
-  VERIFY_IS_APPROX(m1, m2.inverse() );
-
-  m1.computeInverse(&m2);
-  VERIFY_IS_APPROX(m1, m2.inverse() );
-
-  VERIFY_IS_APPROX((Scalar(2)*m2).inverse(), m2.inverse()*Scalar(0.5));
-
-  VERIFY_IS_APPROX(identity, m1.inverse() * m1 );
-  VERIFY_IS_APPROX(identity, m1 * m1.inverse() );
-
-  VERIFY_IS_APPROX(m1, m1.inverse().inverse() );
-
-  // since for the general case we implement separately row-major and col-major, test that
-  VERIFY_IS_APPROX(m1.transpose().inverse(), m1.inverse().transpose());
-}
-
-void test_eigen2_inverse()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( inverse(Matrix<double,1,1>()) );
-    CALL_SUBTEST_2( inverse(Matrix2d()) );
-    CALL_SUBTEST_3( inverse(Matrix3f()) );
-    CALL_SUBTEST_4( inverse(Matrix4f()) );
-    CALL_SUBTEST_5( inverse(MatrixXf(8,8)) );
-    CALL_SUBTEST_6( inverse(MatrixXcd(7,7)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_linearstructure.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_linearstructure.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_linearstructure.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_linearstructure.cpp
@@ -1,83 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename MatrixType> void linearStructure(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Sum.h Difference.h Opposite.h ScalarMultiple.h
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  // this test relies a lot on Random.h, and there's not much more that we can do
-  // to test it, hence I consider that we will have tested Random.h
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols);
-
-  Scalar s1 = ei_random<Scalar>();
-  while (ei_abs(s1)<1e-3) s1 = ei_random<Scalar>();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  VERIFY_IS_APPROX(-(-m1),                  m1);
-  VERIFY_IS_APPROX(m1+m1,                   2*m1);
-  VERIFY_IS_APPROX(m1+m2-m1,                m2);
-  VERIFY_IS_APPROX(-m2+m1+m2,               m1);
-  VERIFY_IS_APPROX(m1*s1,                   s1*m1);
-  VERIFY_IS_APPROX((m1+m2)*s1,              s1*m1+s1*m2);
-  VERIFY_IS_APPROX((-m1+m2)*s1,             -s1*m1+s1*m2);
-  m3 = m2; m3 += m1;
-  VERIFY_IS_APPROX(m3,                      m1+m2);
-  m3 = m2; m3 -= m1;
-  VERIFY_IS_APPROX(m3,                      m2-m1);
-  m3 = m2; m3 *= s1;
-  VERIFY_IS_APPROX(m3,                      s1*m2);
-  if(NumTraits<Scalar>::HasFloatingPoint)
-  {
-    m3 = m2; m3 /= s1;
-    VERIFY_IS_APPROX(m3,                    m2/s1);
-  }
-
-  // again, test operator() to check const-qualification
-  VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c)));
-  VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c)));
-  VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
-  VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c)));
-  VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1);
-  if(NumTraits<Scalar>::HasFloatingPoint)
-    VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1);
-
-  // use .block to disable vectorization and compare to the vectorized version
-  VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
-  VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
-  VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
-  VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1);
-}
-
-void test_eigen2_linearstructure()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( linearStructure(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( linearStructure(Matrix2f()) );
-    CALL_SUBTEST_3( linearStructure(Vector3d()) );
-    CALL_SUBTEST_4( linearStructure(Matrix4d()) );
-    CALL_SUBTEST_5( linearStructure(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_6( linearStructure(MatrixXf(8, 12)) );
-    CALL_SUBTEST_7( linearStructure(MatrixXi(8, 12)) );
-    CALL_SUBTEST_8( linearStructure(MatrixXcd(20, 20)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_lu.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_lu.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_lu.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_lu.cpp
@@ -1,122 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/LU>
-
-template<typename Derived>
-void doSomeRankPreservingOperations(Eigen::MatrixBase<Derived>& m)
-{
-  typedef typename Derived::RealScalar RealScalar;
-  for(int a = 0; a < 3*(m.rows()+m.cols()); a++)
-  {
-    RealScalar d = Eigen::ei_random<RealScalar>(-1,1);
-    int i = Eigen::ei_random<int>(0,m.rows()-1); // i is a random row number
-    int j;
-    do {
-      j = Eigen::ei_random<int>(0,m.rows()-1);
-    } while (i==j); // j is another one (must be different)
-    m.row(i) += d * m.row(j);
-
-    i = Eigen::ei_random<int>(0,m.cols()-1); // i is a random column number
-    do {
-      j = Eigen::ei_random<int>(0,m.cols()-1);
-    } while (i==j); // j is another one (must be different)
-    m.col(i) += d * m.col(j);
-  }
-}
-
-template<typename MatrixType> void lu_non_invertible()
-{
-  /* this test covers the following files:
-     LU.h
-  */
-  // NOTE there seems to be a problem with too small sizes -- could easily lie in the doSomeRankPreservingOperations function
-  int rows = ei_random<int>(20,200), cols = ei_random<int>(20,200), cols2 = ei_random<int>(20,200);
-  int rank = ei_random<int>(1, std::min(rows, cols)-1);
-
-  MatrixType m1(rows, cols), m2(cols, cols2), m3(rows, cols2), k(1,1);
-  m1 = MatrixType::Random(rows,cols);
-  if(rows <= cols)
-    for(int i = rank; i < rows; i++) m1.row(i).setZero();
-  else
-    for(int i = rank; i < cols; i++) m1.col(i).setZero();
-  doSomeRankPreservingOperations(m1);
-
-  LU<MatrixType> lu(m1);
-  typename LU<MatrixType>::KernelResultType m1kernel = lu.kernel();
-  typename LU<MatrixType>::ImageResultType m1image = lu.image();
-
-  VERIFY(rank == lu.rank());
-  VERIFY(cols - lu.rank() == lu.dimensionOfKernel());
-  VERIFY(!lu.isInjective());
-  VERIFY(!lu.isInvertible());
-  VERIFY(lu.isSurjective() == (lu.rank() == rows));
-  VERIFY((m1 * m1kernel).isMuchSmallerThan(m1));
-  VERIFY(m1image.lu().rank() == rank);
-  MatrixType sidebyside(m1.rows(), m1.cols() + m1image.cols());
-  sidebyside << m1, m1image;
-  VERIFY(sidebyside.lu().rank() == rank);
-  m2 = MatrixType::Random(cols,cols2);
-  m3 = m1*m2;
-  m2 = MatrixType::Random(cols,cols2);
-  lu.solve(m3, &m2);
-  VERIFY_IS_APPROX(m3, m1*m2);
-  /* solve now always returns true
-  m3 = MatrixType::Random(rows,cols2);
-  VERIFY(!lu.solve(m3, &m2));
-  */
-}
-
-template<typename MatrixType> void lu_invertible()
-{
-  /* this test covers the following files:
-     LU.h
-  */
-  typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-  int size = ei_random<int>(10,200);
-
-  MatrixType m1(size, size), m2(size, size), m3(size, size);
-  m1 = MatrixType::Random(size,size);
-
-  if (ei_is_same_type<RealScalar,float>::ret)
-  {
-    // let's build a matrix more stable to inverse
-    MatrixType a = MatrixType::Random(size,size*2);
-    m1 += a * a.adjoint();
-  }
-
-  LU<MatrixType> lu(m1);
-  VERIFY(0 == lu.dimensionOfKernel());
-  VERIFY(size == lu.rank());
-  VERIFY(lu.isInjective());
-  VERIFY(lu.isSurjective());
-  VERIFY(lu.isInvertible());
-  VERIFY(lu.image().lu().isInvertible());
-  m3 = MatrixType::Random(size,size);
-  lu.solve(m3, &m2);
-  VERIFY_IS_APPROX(m3, m1*m2);
-  VERIFY_IS_APPROX(m2, lu.inverse()*m3);
-  m3 = MatrixType::Random(size,size);
-  VERIFY(lu.solve(m3, &m2));
-}
-
-void test_eigen2_lu()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( lu_non_invertible<MatrixXf>() );
-    CALL_SUBTEST_2( lu_non_invertible<MatrixXd>() );
-    CALL_SUBTEST_3( lu_non_invertible<MatrixXcf>() );
-    CALL_SUBTEST_4( lu_non_invertible<MatrixXcd>() );
-    CALL_SUBTEST_1( lu_invertible<MatrixXf>() );
-    CALL_SUBTEST_2( lu_invertible<MatrixXd>() );
-    CALL_SUBTEST_3( lu_invertible<MatrixXcf>() );
-    CALL_SUBTEST_4( lu_invertible<MatrixXcd>() );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_map.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_map.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_map.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_map.cpp
@@ -1,114 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename VectorType> void map_class_vector(const VectorType& m)
-{
-  typedef typename VectorType::Scalar Scalar;
-
-  int size = m.size();
-
-  // test Map.h
-  Scalar* array1 = ei_aligned_new<Scalar>(size);
-  Scalar* array2 = ei_aligned_new<Scalar>(size);
-  Scalar* array3 = new Scalar[size+1];
-  Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
-  
-  Map<VectorType, Aligned>(array1, size) = VectorType::Random(size);
-  Map<VectorType>(array2, size) = Map<VectorType>(array1, size);
-  Map<VectorType>(array3unaligned, size) = Map<VectorType>((const Scalar*)array1, size); // test non-const-correctness support in eigen2
-  VectorType ma1 = Map<VectorType>(array1, size);
-  VectorType ma2 = Map<VectorType, Aligned>(array2, size);
-  VectorType ma3 = Map<VectorType>(array3unaligned, size);
-  VERIFY_IS_APPROX(ma1, ma2);
-  VERIFY_IS_APPROX(ma1, ma3);
-  
-  ei_aligned_delete(array1, size);
-  ei_aligned_delete(array2, size);
-  delete[] array3;
-}
-
-template<typename MatrixType> void map_class_matrix(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-
-  int rows = m.rows(), cols = m.cols(), size = rows*cols;
-
-  // test Map.h
-  Scalar* array1 = ei_aligned_new<Scalar>(size);
-  for(int i = 0; i < size; i++) array1[i] = Scalar(1);
-  Scalar* array2 = ei_aligned_new<Scalar>(size);
-  for(int i = 0; i < size; i++) array2[i] = Scalar(1);
-  Scalar* array3 = new Scalar[size+1];
-  for(int i = 0; i < size+1; i++) array3[i] = Scalar(1);
-  Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
-  Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols);
-  Map<MatrixType>(array2, rows, cols) = Map<MatrixType>((const Scalar*)array1, rows, cols); // test non-const-correctness support in eigen2
-  Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols);
-  MatrixType ma1 = Map<MatrixType>(array1, rows, cols);
-  MatrixType ma2 = Map<MatrixType, Aligned>(array2, rows, cols);
-  VERIFY_IS_APPROX(ma1, ma2);
-  MatrixType ma3 = Map<MatrixType>(array3unaligned, rows, cols);
-  VERIFY_IS_APPROX(ma1, ma3);
-  
-  ei_aligned_delete(array1, size);
-  ei_aligned_delete(array2, size);
-  delete[] array3;
-}
-
-template<typename VectorType> void map_static_methods(const VectorType& m)
-{
-  typedef typename VectorType::Scalar Scalar;
-
-  int size = m.size();
-
-  // test Map.h
-  Scalar* array1 = ei_aligned_new<Scalar>(size);
-  Scalar* array2 = ei_aligned_new<Scalar>(size);
-  Scalar* array3 = new Scalar[size+1];
-  Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
-  
-  VectorType::MapAligned(array1, size) = VectorType::Random(size);
-  VectorType::Map(array2, size) = VectorType::Map(array1, size);
-  VectorType::Map(array3unaligned, size) = VectorType::Map(array1, size);
-  VectorType ma1 = VectorType::Map(array1, size);
-  VectorType ma2 = VectorType::MapAligned(array2, size);
-  VectorType ma3 = VectorType::Map(array3unaligned, size);
-  VERIFY_IS_APPROX(ma1, ma2);
-  VERIFY_IS_APPROX(ma1, ma3);
-  
-  ei_aligned_delete(array1, size);
-  ei_aligned_delete(array2, size);
-  delete[] array3;
-}
-
-
-void test_eigen2_map()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( map_class_vector(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( map_class_vector(Vector4d()) );
-    CALL_SUBTEST_3( map_class_vector(RowVector4f()) );
-    CALL_SUBTEST_4( map_class_vector(VectorXcf(8)) );
-    CALL_SUBTEST_5( map_class_vector(VectorXi(12)) );
-
-    CALL_SUBTEST_1( map_class_matrix(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( map_class_matrix(Matrix4d()) );
-    CALL_SUBTEST_6( map_class_matrix(Matrix<float,3,5>()) );
-    CALL_SUBTEST_4( map_class_matrix(MatrixXcf(ei_random<int>(1,10),ei_random<int>(1,10))) );
-    CALL_SUBTEST_5( map_class_matrix(MatrixXi(ei_random<int>(1,10),ei_random<int>(1,10))) );
-
-    CALL_SUBTEST_1( map_static_methods(Matrix<double, 1, 1>()) );
-    CALL_SUBTEST_2( map_static_methods(Vector3f()) );
-    CALL_SUBTEST_7( map_static_methods(RowVector3d()) );
-    CALL_SUBTEST_4( map_static_methods(VectorXcd(8)) );
-    CALL_SUBTEST_5( map_static_methods(VectorXf(12)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_meta.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_meta.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_meta.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_meta.cpp
@@ -1,60 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-void test_eigen2_meta()
-{
-  typedef float & FloatRef;
-  typedef const float & ConstFloatRef;
-  
-  VERIFY((ei_meta_if<(3<4),ei_meta_true, ei_meta_false>::ret::ret));
-  VERIFY(( ei_is_same_type<float,float>::ret));
-  VERIFY((!ei_is_same_type<float,double>::ret));
-  VERIFY((!ei_is_same_type<float,float&>::ret));
-  VERIFY((!ei_is_same_type<float,const float&>::ret));
-  
-  VERIFY(( ei_is_same_type<float,ei_cleantype<const float&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<const float*>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<const float*&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<float**>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<float**&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<float* const *&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<float* const>::type >::ret));
-
-  VERIFY(( ei_is_same_type<float*,ei_unconst<const float*>::type >::ret));
-  VERIFY(( ei_is_same_type<float&,ei_unconst<const float&>::type >::ret));
-  VERIFY(( ei_is_same_type<float&,ei_unconst<ConstFloatRef>::type >::ret));
-  
-  VERIFY(( ei_is_same_type<float&,ei_unconst<float&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_unref<float&>::type >::ret));
-  VERIFY(( ei_is_same_type<const float,ei_unref<const float&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_unpointer<float*>::type >::ret));
-  VERIFY(( ei_is_same_type<const float,ei_unpointer<const float*>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_unpointer<float* const >::type >::ret));
-  
-  VERIFY(ei_meta_sqrt<1>::ret == 1);
-  #define VERIFY_META_SQRT(X) VERIFY(ei_meta_sqrt<X>::ret == int(ei_sqrt(double(X))))
-  VERIFY_META_SQRT(2);
-  VERIFY_META_SQRT(3);
-  VERIFY_META_SQRT(4);
-  VERIFY_META_SQRT(5);
-  VERIFY_META_SQRT(6);
-  VERIFY_META_SQRT(8);
-  VERIFY_META_SQRT(9);
-  VERIFY_META_SQRT(15);
-  VERIFY_META_SQRT(16);
-  VERIFY_META_SQRT(17);
-  VERIFY_META_SQRT(255);
-  VERIFY_META_SQRT(256);
-  VERIFY_META_SQRT(257);
-  VERIFY_META_SQRT(1023);
-  VERIFY_META_SQRT(1024);
-  VERIFY_META_SQRT(1025);
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_miscmatrices.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_miscmatrices.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_miscmatrices.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_miscmatrices.cpp
@@ -1,48 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename MatrixType> void miscMatrices(const MatrixType& m)
-{
-  /* this test covers the following files:
-     DiagonalMatrix.h Ones.h
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
-  int rows = m.rows();
-  int cols = m.cols();
-
-  int r = ei_random<int>(0, rows-1), r2 = ei_random<int>(0, rows-1), c = ei_random<int>(0, cols-1);
-  VERIFY_IS_APPROX(MatrixType::Ones(rows,cols)(r,c), static_cast<Scalar>(1));
-  MatrixType m1 = MatrixType::Ones(rows,cols);
-  VERIFY_IS_APPROX(m1(r,c), static_cast<Scalar>(1));
-  VectorType v1 = VectorType::Random(rows);
-  v1[0];
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-  square = v1.asDiagonal();
-  if(r==r2) VERIFY_IS_APPROX(square(r,r2), v1[r]);
-  else VERIFY_IS_MUCH_SMALLER_THAN(square(r,r2), static_cast<Scalar>(1));
-  square = MatrixType::Zero(rows, rows);
-  square.diagonal() = VectorType::Ones(rows);
-  VERIFY_IS_APPROX(square, MatrixType::Identity(rows, rows));
-}
-
-void test_eigen2_miscmatrices()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( miscMatrices(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( miscMatrices(Matrix4d()) );
-    CALL_SUBTEST_3( miscMatrices(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_4( miscMatrices(MatrixXi(8, 12)) );
-    CALL_SUBTEST_5( miscMatrices(MatrixXcd(20, 20)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_mixingtypes.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_mixingtypes.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_mixingtypes.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_mixingtypes.cpp
@@ -1,77 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_NO_STATIC_ASSERT
-#define EIGEN_NO_STATIC_ASSERT // turn static asserts into runtime asserts in order to check them
-#endif
-
-#ifndef EIGEN_DONT_VECTORIZE
-#define EIGEN_DONT_VECTORIZE // SSE intrinsics aren't designed to allow mixing types
-#endif
-
-#include "main.h"
-
-
-template<int SizeAtCompileType> void mixingtypes(int size = SizeAtCompileType)
-{
-  typedef Matrix<float, SizeAtCompileType, SizeAtCompileType> Mat_f;
-  typedef Matrix<double, SizeAtCompileType, SizeAtCompileType> Mat_d;
-  typedef Matrix<std::complex<float>, SizeAtCompileType, SizeAtCompileType> Mat_cf;
-  typedef Matrix<std::complex<double>, SizeAtCompileType, SizeAtCompileType> Mat_cd;
-  typedef Matrix<float, SizeAtCompileType, 1> Vec_f;
-  typedef Matrix<double, SizeAtCompileType, 1> Vec_d;
-  typedef Matrix<std::complex<float>, SizeAtCompileType, 1> Vec_cf;
-  typedef Matrix<std::complex<double>, SizeAtCompileType, 1> Vec_cd;
-
-  Mat_f mf(size,size);
-  Mat_d md(size,size);
-  Mat_cf mcf(size,size);
-  Mat_cd mcd(size,size);
-  Vec_f vf(size,1);
-  Vec_d vd(size,1);
-  Vec_cf vcf(size,1);
-  Vec_cd vcd(size,1);
-
-  mf+mf;
-  VERIFY_RAISES_ASSERT(mf+md);
-  VERIFY_RAISES_ASSERT(mf+mcf);
-  VERIFY_RAISES_ASSERT(vf=vd);
-  VERIFY_RAISES_ASSERT(vf+=vd);
-  VERIFY_RAISES_ASSERT(mcd=md);
-
-  mf*mf;
-  md*mcd;
-  mcd*md;
-  mf*vcf;
-  mcf*vf;
-  mcf *= mf;
-  vcd = md*vcd;
-  vcf = mcf*vf;
-#if 0
-  // these are know generating hard build errors in eigen3
-  VERIFY_RAISES_ASSERT(mf*md);
-  VERIFY_RAISES_ASSERT(mcf*mcd);
-  VERIFY_RAISES_ASSERT(mcf*vcd);
-  VERIFY_RAISES_ASSERT(vcf = mf*vf);
-
-  vf.eigen2_dot(vf);
-  VERIFY_RAISES_ASSERT(vd.eigen2_dot(vf));
-  VERIFY_RAISES_ASSERT(vcf.eigen2_dot(vf)); // yeah eventually we should allow this but i'm too lazy to make that change now in Dot.h
-  // especially as that might be rewritten as cwise product .sum() which would make that automatic.
-#endif
-}
-
-void test_eigen2_mixingtypes()
-{
-  // check that our operator new is indeed called:
-  CALL_SUBTEST_1(mixingtypes<3>());
-  CALL_SUBTEST_2(mixingtypes<4>());
-  CALL_SUBTEST_3(mixingtypes<Dynamic>(20));
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_newstdvector.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_newstdvector.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_newstdvector.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_newstdvector.cpp
@@ -1,149 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#define EIGEN_USE_NEW_STDVECTOR
-#include "main.h"
-#include <Eigen/StdVector>
-#include <Eigen/Geometry>
-
-template<typename MatrixType>
-void check_stdvector_matrix(const MatrixType& m)
-{
-  int rows = m.rows();
-  int cols = m.cols();
-  MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
-  std::vector<MatrixType,Eigen::aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(MatrixType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  MatrixType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i]==w[(i-23)%w.size()]);
-  }
-}
-
-template<typename TransformType>
-void check_stdvector_transform(const TransformType&)
-{
-  typedef typename TransformType::MatrixType MatrixType;
-  TransformType x(MatrixType::Random()), y(MatrixType::Random());
-  std::vector<TransformType,Eigen::aligned_allocator<TransformType> > v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(TransformType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  TransformType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i].matrix()==w[(i-23)%w.size()].matrix());
-  }
-}
-
-template<typename QuaternionType>
-void check_stdvector_quaternion(const QuaternionType&)
-{
-  typedef typename QuaternionType::Coefficients Coefficients;
-  QuaternionType x(Coefficients::Random()), y(Coefficients::Random());
-  std::vector<QuaternionType,Eigen::aligned_allocator<QuaternionType> > v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(QuaternionType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  QuaternionType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i].coeffs()==w[(i-23)%w.size()].coeffs());
-  }
-}
-
-void test_eigen2_newstdvector()
-{
-  // some non vectorizable fixed sizes
-  CALL_SUBTEST_1(check_stdvector_matrix(Vector2f()));
-  CALL_SUBTEST_1(check_stdvector_matrix(Matrix3f()));
-  CALL_SUBTEST_1(check_stdvector_matrix(Matrix3d()));
-
-  // some vectorizable fixed sizes
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix2f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Vector4f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix4f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix4d()));
-
-  // some dynamic sizes
-  CALL_SUBTEST_3(check_stdvector_matrix(MatrixXd(1,1)));
-  CALL_SUBTEST_3(check_stdvector_matrix(VectorXd(20)));
-  CALL_SUBTEST_3(check_stdvector_matrix(RowVectorXf(20)));
-  CALL_SUBTEST_3(check_stdvector_matrix(MatrixXcf(10,10)));
-
-  // some Transform
-  CALL_SUBTEST_4(check_stdvector_transform(Transform2f()));
-  CALL_SUBTEST_4(check_stdvector_transform(Transform3f()));
-  CALL_SUBTEST_4(check_stdvector_transform(Transform3d()));
-  //CALL_SUBTEST(check_stdvector_transform(Transform4d()));
-
-  // some Quaternion
-  CALL_SUBTEST_5(check_stdvector_quaternion(Quaternionf()));
-  CALL_SUBTEST_5(check_stdvector_quaternion(Quaterniond()));
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_nomalloc.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_nomalloc.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_nomalloc.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_nomalloc.cpp
@@ -1,53 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// this hack is needed to make this file compiles with -pedantic (gcc)
-#ifdef __GNUC__
-#define throw(X)
-#endif
-// discard stack allocation as that too bypasses malloc
-#define EIGEN_STACK_ALLOCATION_LIMIT 0
-// any heap allocation will raise an assert
-#define EIGEN_NO_MALLOC
-
-#include "main.h"
-
-template<typename MatrixType> void nomalloc(const MatrixType& m)
-{
-  /* this test check no dynamic memory allocation are issued with fixed-size matrices
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols);
-
-  Scalar s1 = ei_random<Scalar>();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  VERIFY_IS_APPROX((m1+m2)*s1,              s1*m1+s1*m2);
-  VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
-  VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
-  VERIFY_IS_APPROX((m1*m1.transpose())*m2,  m1*(m1.transpose()*m2));
-}
-
-void test_eigen2_nomalloc()
-{
-  // check that our operator new is indeed called:
-  VERIFY_RAISES_ASSERT(MatrixXd dummy = MatrixXd::Random(3,3));
-  CALL_SUBTEST_1( nomalloc(Matrix<float, 1, 1>()) );
-  CALL_SUBTEST_2( nomalloc(Matrix4d()) );
-  CALL_SUBTEST_3( nomalloc(Matrix<float,32,32>()) );
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_packetmath.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_packetmath.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_packetmath.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_packetmath.cpp
@@ -1,132 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-// using namespace Eigen;
-
-template<typename Scalar> bool areApprox(const Scalar* a, const Scalar* b, int size)
-{
-  for (int i=0; i<size; ++i)
-    if (!ei_isApprox(a[i],b[i])) return false;
-  return true;
-}
-
-#define CHECK_CWISE(REFOP, POP) { \
-  for (int i=0; i<PacketSize; ++i) \
-    ref[i] = REFOP(data1[i], data1[i+PacketSize]); \
-  ei_pstore(data2, POP(ei_pload(data1), ei_pload(data1+PacketSize))); \
-  VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
-}
-
-#define REF_ADD(a,b) ((a)+(b))
-#define REF_SUB(a,b) ((a)-(b))
-#define REF_MUL(a,b) ((a)*(b))
-#define REF_DIV(a,b) ((a)/(b))
-
-namespace std {
-
-template<> const complex<float>& min(const complex<float>& a, const complex<float>& b)
-{ return a.real() < b.real() ? a : b; }
-
-template<> const complex<float>& max(const complex<float>& a, const complex<float>& b)
-{ return a.real() < b.real() ? b : a; }
-
-}
-
-template<typename Scalar> void packetmath()
-{
-  typedef typename ei_packet_traits<Scalar>::type Packet;
-  const int PacketSize = ei_packet_traits<Scalar>::size;
-
-  const int size = PacketSize*4;
-  EIGEN_ALIGN_128 Scalar data1[ei_packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN_128 Scalar data2[ei_packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN_128 Packet packets[PacketSize*2];
-  EIGEN_ALIGN_128 Scalar ref[ei_packet_traits<Scalar>::size*4];
-  for (int i=0; i<size; ++i)
-  {
-    data1[i] = ei_random<Scalar>();
-    data2[i] = ei_random<Scalar>();
-  }
-
-  ei_pstore(data2, ei_pload(data1));
-  VERIFY(areApprox(data1, data2, PacketSize) && "aligned load/store");
-
-  for (int offset=0; offset<PacketSize; ++offset)
-  {
-    ei_pstore(data2, ei_ploadu(data1+offset));
-    VERIFY(areApprox(data1+offset, data2, PacketSize) && "ei_ploadu");
-  }
-
-  for (int offset=0; offset<PacketSize; ++offset)
-  {
-    ei_pstoreu(data2+offset, ei_pload(data1));
-    VERIFY(areApprox(data1, data2+offset, PacketSize) && "ei_pstoreu");
-  }
-
-  for (int offset=0; offset<PacketSize; ++offset)
-  {
-    packets[0] = ei_pload(data1);
-    packets[1] = ei_pload(data1+PacketSize);
-         if (offset==0) ei_palign<0>(packets[0], packets[1]);
-    else if (offset==1) ei_palign<1>(packets[0], packets[1]);
-    else if (offset==2) ei_palign<2>(packets[0], packets[1]);
-    else if (offset==3) ei_palign<3>(packets[0], packets[1]);
-    ei_pstore(data2, packets[0]);
-
-    for (int i=0; i<PacketSize; ++i)
-      ref[i] = data1[i+offset];
-
-    typedef Matrix<Scalar, PacketSize, 1> Vector;
-    VERIFY(areApprox(ref, data2, PacketSize) && "ei_palign");
-  }
-
-  CHECK_CWISE(REF_ADD,  ei_padd);
-  CHECK_CWISE(REF_SUB,  ei_psub);
-  CHECK_CWISE(REF_MUL,  ei_pmul);
-  #ifndef EIGEN_VECTORIZE_ALTIVEC
-  if (!ei_is_same_type<Scalar,int>::ret)
-    CHECK_CWISE(REF_DIV,  ei_pdiv);
-  #endif
-  CHECK_CWISE(std::min, ei_pmin);
-  CHECK_CWISE(std::max, ei_pmax);
-
-  for (int i=0; i<PacketSize; ++i)
-    ref[i] = data1[0];
-  ei_pstore(data2, ei_pset1(data1[0]));
-  VERIFY(areApprox(ref, data2, PacketSize) && "ei_pset1");
-
-  VERIFY(ei_isApprox(data1[0], ei_pfirst(ei_pload(data1))) && "ei_pfirst");
-
-  ref[0] = 0;
-  for (int i=0; i<PacketSize; ++i)
-    ref[0] += data1[i];
-  VERIFY(ei_isApprox(ref[0], ei_predux(ei_pload(data1))) && "ei_predux");
-
-  for (int j=0; j<PacketSize; ++j)
-  {
-    ref[j] = 0;
-    for (int i=0; i<PacketSize; ++i)
-      ref[j] += data1[i+j*PacketSize];
-    packets[j] = ei_pload(data1+j*PacketSize);
-  }
-  ei_pstore(data2, ei_preduxp(packets));
-  VERIFY(areApprox(ref, data2, PacketSize) && "ei_preduxp");
-}
-
-void test_eigen2_packetmath()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( packetmath<float>() );
-    CALL_SUBTEST_2( packetmath<double>() );
-    CALL_SUBTEST_3( packetmath<int>() );
-    CALL_SUBTEST_4( packetmath<std::complex<float> >() );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_parametrizedline.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_parametrizedline.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_parametrizedline.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_parametrizedline.cpp
@@ -1,62 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/Geometry>
-#include <Eigen/LU>
-#include <Eigen/QR>
-
-template<typename LineType> void parametrizedline(const LineType& _line)
-{
-  /* this test covers the following files:
-     ParametrizedLine.h
-  */
-
-  const int dim = _line.dim();
-  typedef typename LineType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, LineType::AmbientDimAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, LineType::AmbientDimAtCompileTime,
-                         LineType::AmbientDimAtCompileTime> MatrixType;
-
-  VectorType p0 = VectorType::Random(dim);
-  VectorType p1 = VectorType::Random(dim);
-
-  VectorType d0 = VectorType::Random(dim).normalized();
-
-  LineType l0(p0, d0);
-
-  Scalar s0 = ei_random<Scalar>();
-  Scalar s1 = ei_abs(ei_random<Scalar>());
-
-  VERIFY_IS_MUCH_SMALLER_THAN( l0.distance(p0), RealScalar(1) );
-  VERIFY_IS_MUCH_SMALLER_THAN( l0.distance(p0+s0*d0), RealScalar(1) );
-  VERIFY_IS_APPROX( (l0.projection(p1)-p1).norm(), l0.distance(p1) );
-  VERIFY_IS_MUCH_SMALLER_THAN( l0.distance(l0.projection(p1)), RealScalar(1) );
-  VERIFY_IS_APPROX( Scalar(l0.distance((p0+s0*d0) + d0.unitOrthogonal() * s1)), s1 );
-
-  // casting
-  const int Dim = LineType::AmbientDimAtCompileTime;
-  typedef typename GetDifferentType<Scalar>::type OtherScalar;
-  ParametrizedLine<OtherScalar,Dim> hp1f = l0.template cast<OtherScalar>();
-  VERIFY_IS_APPROX(hp1f.template cast<Scalar>(),l0);
-  ParametrizedLine<Scalar,Dim> hp1d = l0.template cast<Scalar>();
-  VERIFY_IS_APPROX(hp1d.template cast<Scalar>(),l0);
-}
-
-void test_eigen2_parametrizedline()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( parametrizedline(ParametrizedLine<float,2>()) );
-    CALL_SUBTEST_2( parametrizedline(ParametrizedLine<float,3>()) );
-    CALL_SUBTEST_3( parametrizedline(ParametrizedLine<double,4>()) );
-    CALL_SUBTEST_4( parametrizedline(ParametrizedLine<std::complex<double>,5>()) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_prec_inverse_4x4.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_prec_inverse_4x4.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_prec_inverse_4x4.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_prec_inverse_4x4.cpp
@@ -1,84 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/LU>
-#include <algorithm>
-
-template<typename T> std::string type_name() { return "other"; }
-template<> std::string type_name<float>() { return "float"; }
-template<> std::string type_name<double>() { return "double"; }
-template<> std::string type_name<int>() { return "int"; }
-template<> std::string type_name<std::complex<float> >() { return "complex<float>"; }
-template<> std::string type_name<std::complex<double> >() { return "complex<double>"; }
-template<> std::string type_name<std::complex<int> >() { return "complex<int>"; }
-
-#define EIGEN_DEBUG_VAR(x) std::cerr << #x << " = " << x << std::endl;
-
-template<typename T> inline typename NumTraits<T>::Real epsilon()
-{
- return std::numeric_limits<typename NumTraits<T>::Real>::epsilon();
-}
-
-template<typename MatrixType> void inverse_permutation_4x4()
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  Vector4i indices(0,1,2,3);
-  for(int i = 0; i < 24; ++i)
-  {
-    MatrixType m = MatrixType::Zero();
-    m(indices(0),0) = 1;
-    m(indices(1),1) = 1;
-    m(indices(2),2) = 1;
-    m(indices(3),3) = 1;
-    MatrixType inv = m.inverse();
-    double error = double( (m*inv-MatrixType::Identity()).norm() / epsilon<Scalar>() );
-    VERIFY(error == 0.0);
-    std::next_permutation(indices.data(),indices.data()+4);
-  }
-}
-
-template<typename MatrixType> void inverse_general_4x4(int repeat)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  double error_sum = 0., error_max = 0.;
-  for(int i = 0; i < repeat; ++i)
-  {
-    MatrixType m;
-    RealScalar absdet;
-    do {
-      m = MatrixType::Random();
-      absdet = ei_abs(m.determinant());
-    } while(absdet < 10 * epsilon<Scalar>());
-    MatrixType inv = m.inverse();
-    double error = double( (m*inv-MatrixType::Identity()).norm() * absdet / epsilon<Scalar>() );
-    error_sum += error;
-    error_max = std::max(error_max, error);
-  }
-  std::cerr << "inverse_general_4x4, Scalar = " << type_name<Scalar>() << std::endl;
-  double error_avg = error_sum / repeat;
-  EIGEN_DEBUG_VAR(error_avg);
-  EIGEN_DEBUG_VAR(error_max);
-  VERIFY(error_avg < (NumTraits<Scalar>::IsComplex ? 8.0 : 1.25));
-  VERIFY(error_max < (NumTraits<Scalar>::IsComplex ? 64.0 : 20.0));
-}
-
-void test_eigen2_prec_inverse_4x4()
-{
-  CALL_SUBTEST_1((inverse_permutation_4x4<Matrix4f>()));
-  CALL_SUBTEST_1(( inverse_general_4x4<Matrix4f>(200000 * g_repeat) ));
-
-  CALL_SUBTEST_2((inverse_permutation_4x4<Matrix<double,4,4,RowMajor> >()));
-  CALL_SUBTEST_2(( inverse_general_4x4<Matrix<double,4,4,RowMajor> >(200000 * g_repeat) ));
-
-  CALL_SUBTEST_3((inverse_permutation_4x4<Matrix4cf>()));
-  CALL_SUBTEST_3((inverse_general_4x4<Matrix4cf>(50000 * g_repeat)));
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_product_large.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_product_large.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_product_large.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_product_large.cpp
@@ -1,45 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "product.h"
-
-void test_eigen2_product_large()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( product(MatrixXf(ei_random<int>(1,320), ei_random<int>(1,320))) );
-    CALL_SUBTEST_2( product(MatrixXd(ei_random<int>(1,320), ei_random<int>(1,320))) );
-    CALL_SUBTEST_3( product(MatrixXi(ei_random<int>(1,320), ei_random<int>(1,320))) );
-    CALL_SUBTEST_4( product(MatrixXcf(ei_random<int>(1,50), ei_random<int>(1,50))) );
-    CALL_SUBTEST_5( product(Matrix<float,Dynamic,Dynamic,RowMajor>(ei_random<int>(1,320), ei_random<int>(1,320))) );
-  }
-
-#ifdef EIGEN_TEST_PART_6
-  {
-    // test a specific issue in DiagonalProduct
-    int N = 1000000;
-    VectorXf v = VectorXf::Ones(N);
-    MatrixXf m = MatrixXf::Ones(N,3);
-    m = (v+v).asDiagonal() * m;
-    VERIFY_IS_APPROX(m, MatrixXf::Constant(N,3,2));
-  }
-
-  {
-    // test deferred resizing in Matrix::operator=
-    MatrixXf a = MatrixXf::Random(10,4), b = MatrixXf::Random(4,10), c = a;
-    VERIFY_IS_APPROX((a = a * b), (c * b).eval());
-  }
-
-  {
-    MatrixXf mat1(10,10); mat1.setRandom();
-    MatrixXf mat2(32,10); mat2.setRandom();
-    MatrixXf result = mat1.row(2)*mat2.transpose();
-    VERIFY_IS_APPROX(result, (mat1.row(2)*mat2.transpose()).eval());
-  }
-#endif
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_product_small.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_product_small.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_product_small.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_product_small.cpp
@@ -1,22 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#define EIGEN_NO_STATIC_ASSERT
-#include "product.h"
-
-void test_eigen2_product_small()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( product(Matrix<float, 3, 2>()) );
-    CALL_SUBTEST_2( product(Matrix<int, 3, 5>()) );
-    CALL_SUBTEST_3( product(Matrix3d()) );
-    CALL_SUBTEST_4( product(Matrix4d()) );
-    CALL_SUBTEST_5( product(Matrix4f()) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_qr.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_qr.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_qr.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_qr.cpp
@@ -1,69 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/QR>
-
-template<typename MatrixType> void qr(const MatrixType& m)
-{
-  /* this test covers the following files:
-     QR.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> SquareMatrixType;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
-
-  MatrixType a = MatrixType::Random(rows,cols);
-  QR<MatrixType> qrOfA(a);
-  VERIFY_IS_APPROX(a, qrOfA.matrixQ() * qrOfA.matrixR());
-  VERIFY_IS_NOT_APPROX(a+MatrixType::Identity(rows, cols), qrOfA.matrixQ() * qrOfA.matrixR());
-
-  #if 0 // eigenvalues module not yet ready
-  SquareMatrixType b = a.adjoint() * a;
-
-  // check tridiagonalization
-  Tridiagonalization<SquareMatrixType> tridiag(b);
-  VERIFY_IS_APPROX(b, tridiag.matrixQ() * tridiag.matrixT() * tridiag.matrixQ().adjoint());
-
-  // check hessenberg decomposition
-  HessenbergDecomposition<SquareMatrixType> hess(b);
-  VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
-  VERIFY_IS_APPROX(tridiag.matrixT(), hess.matrixH());
-  b = SquareMatrixType::Random(cols,cols);
-  hess.compute(b);
-  VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
-  #endif
-}
-
-void test_eigen2_qr()
-{
-  for(int i = 0; i < 1; i++) {
-    CALL_SUBTEST_1( qr(Matrix2f()) );
-    CALL_SUBTEST_2( qr(Matrix4d()) );
-    CALL_SUBTEST_3( qr(MatrixXf(12,8)) );
-    CALL_SUBTEST_4( qr(MatrixXcd(5,5)) );
-    CALL_SUBTEST_4( qr(MatrixXcd(7,3)) );
-  }
-
-#ifdef EIGEN_TEST_PART_5
-  // small isFullRank test
-  {
-    Matrix3d mat;
-    mat << 1, 45, 1, 2, 2, 2, 1, 2, 3;
-    VERIFY(mat.qr().isFullRank());
-    mat << 1, 1, 1, 2, 2, 2, 1, 2, 3;
-    //always returns true in eigen2support
-    //VERIFY(!mat.qr().isFullRank());
-  }
-
-#endif
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_qtvector.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_qtvector.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_qtvector.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_qtvector.cpp
@@ -1,158 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#define EIGEN_WORK_AROUND_QT_BUG_CALLING_WRONG_OPERATOR_NEW_FIXED_IN_QT_4_5
-
-#include "main.h"
-
-#include <Eigen/Geometry>
-#include <Eigen/QtAlignedMalloc>
-
-#include <QtCore/QVector>
-
-template<typename MatrixType>
-void check_qtvector_matrix(const MatrixType& m)
-{
-  int rows = m.rows();
-  int cols = m.cols();
-  MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
-  QVector<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], y);
-  }
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.fill(y,22);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(MatrixType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  MatrixType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i]==w[(i-23)%w.size()]);
-  }
-}
-
-template<typename TransformType>
-void check_qtvector_transform(const TransformType&)
-{
-  typedef typename TransformType::MatrixType MatrixType;
-  TransformType x(MatrixType::Random()), y(MatrixType::Random());
-  QVector<TransformType> v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.fill(y,22);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(TransformType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  TransformType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; int(i)<v.size(); ++i)
-  {
-    VERIFY(v[i].matrix()==w[(i-23)%w.size()].matrix());
-  }
-}
-
-template<typename QuaternionType>
-void check_qtvector_quaternion(const QuaternionType&)
-{
-  typedef typename QuaternionType::Coefficients Coefficients;
-  QuaternionType x(Coefficients::Random()), y(Coefficients::Random());
-  QVector<QuaternionType> v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.fill(y,22);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(QuaternionType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  QuaternionType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; int(i)<v.size(); ++i)
-  {
-    VERIFY(v[i].coeffs()==w[(i-23)%w.size()].coeffs());
-  }
-}
-
-void test_eigen2_qtvector()
-{
-  // some non vectorizable fixed sizes
-  CALL_SUBTEST_1(check_qtvector_matrix(Vector2f()));
-  CALL_SUBTEST_1(check_qtvector_matrix(Matrix3f()));
-  CALL_SUBTEST_1(check_qtvector_matrix(Matrix3d()));
-
-  // some vectorizable fixed sizes
-  CALL_SUBTEST_2(check_qtvector_matrix(Matrix2f()));
-  CALL_SUBTEST_2(check_qtvector_matrix(Vector4f()));
-  CALL_SUBTEST_2(check_qtvector_matrix(Matrix4f()));
-  CALL_SUBTEST_2(check_qtvector_matrix(Matrix4d()));
-
-  // some dynamic sizes
-  CALL_SUBTEST_3(check_qtvector_matrix(MatrixXd(1,1)));
-  CALL_SUBTEST_3(check_qtvector_matrix(VectorXd(20)));
-  CALL_SUBTEST_3(check_qtvector_matrix(RowVectorXf(20)));
-  CALL_SUBTEST_3(check_qtvector_matrix(MatrixXcf(10,10)));
-
-  // some Transform
-  CALL_SUBTEST_4(check_qtvector_transform(Transform2f()));
-  CALL_SUBTEST_4(check_qtvector_transform(Transform3f()));
-  CALL_SUBTEST_4(check_qtvector_transform(Transform3d()));
-  //CALL_SUBTEST_4(check_qtvector_transform(Transform4d()));
-
-  // some Quaternion
-  CALL_SUBTEST_5(check_qtvector_quaternion(Quaternionf()));
-  CALL_SUBTEST_5(check_qtvector_quaternion(Quaternionf()));
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_regression.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_regression.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_regression.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_regression.cpp
@@ -1,136 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/LeastSquares>
-
-template<typename VectorType,
-         typename HyperplaneType>
-void makeNoisyCohyperplanarPoints(int numPoints,
-                                  VectorType **points,
-                                  HyperplaneType *hyperplane,
-                                  typename VectorType::Scalar noiseAmplitude)
-{
-  typedef typename VectorType::Scalar Scalar;
-  const int size = points[0]->size();
-  // pick a random hyperplane, store the coefficients of its equation
-  hyperplane->coeffs().resize(size + 1);
-  for(int j = 0; j < size + 1; j++)
-  {
-    do {
-      hyperplane->coeffs().coeffRef(j) = ei_random<Scalar>();
-    } while(ei_abs(hyperplane->coeffs().coeff(j)) < 0.5);
-  }
-
-  // now pick numPoints random points on this hyperplane
-  for(int i = 0; i < numPoints; i++)
-  {
-    VectorType& cur_point = *(points[i]);
-    do
-    {
-      cur_point = VectorType::Random(size)/*.normalized()*/;
-      // project cur_point onto the hyperplane
-      Scalar x = - (hyperplane->coeffs().start(size).cwise()*cur_point).sum();
-      cur_point *= hyperplane->coeffs().coeff(size) / x;
-    } while( cur_point.norm() < 0.5
-          || cur_point.norm() > 2.0 );
-  }
-
-  // add some noise to these points
-  for(int i = 0; i < numPoints; i++ )
-    *(points[i]) += noiseAmplitude * VectorType::Random(size);
-}
-
-template<typename VectorType>
-void check_linearRegression(int numPoints,
-                            VectorType **points,
-                            const VectorType& original,
-                            typename VectorType::Scalar tolerance)
-{
-  int size = points[0]->size();
-  assert(size==2);
-  VectorType result(size);
-  linearRegression(numPoints, points, &result, 1);
-  typename VectorType::Scalar error = (result - original).norm() / original.norm();
-  VERIFY(ei_abs(error) < ei_abs(tolerance));
-}
-
-template<typename VectorType,
-         typename HyperplaneType>
-void check_fitHyperplane(int numPoints,
-                         VectorType **points,
-                         const HyperplaneType& original,
-                         typename VectorType::Scalar tolerance)
-{
-  int size = points[0]->size();
-  HyperplaneType result(size);
-  fitHyperplane(numPoints, points, &result);
-  result.coeffs() *= original.coeffs().coeff(size)/result.coeffs().coeff(size);
-  typename VectorType::Scalar error = (result.coeffs() - original.coeffs()).norm() / original.coeffs().norm();
-  std::cout << ei_abs(error) << "  xxx   " << ei_abs(tolerance) << std::endl;
-  VERIFY(ei_abs(error) < ei_abs(tolerance));
-}
-
-void test_eigen2_regression()
-{
-  for(int i = 0; i < g_repeat; i++)
-  {
-#ifdef EIGEN_TEST_PART_1
-    {
-      Vector2f points2f [1000];
-      Vector2f *points2f_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points2f_ptrs[i] = &(points2f[i]);
-      Vector2f coeffs2f;
-      Hyperplane<float,2> coeffs3f;
-      makeNoisyCohyperplanarPoints(1000, points2f_ptrs, &coeffs3f, 0.01f);
-      coeffs2f[0] = -coeffs3f.coeffs()[0]/coeffs3f.coeffs()[1];
-      coeffs2f[1] = -coeffs3f.coeffs()[2]/coeffs3f.coeffs()[1];
-      CALL_SUBTEST(check_linearRegression(10, points2f_ptrs, coeffs2f, 0.05f));
-      CALL_SUBTEST(check_linearRegression(100, points2f_ptrs, coeffs2f, 0.01f));
-      CALL_SUBTEST(check_linearRegression(1000, points2f_ptrs, coeffs2f, 0.002f));
-    }
-#endif
-#ifdef EIGEN_TEST_PART_2
-    {
-      Vector2f points2f [1000];
-      Vector2f *points2f_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points2f_ptrs[i] = &(points2f[i]);
-      Hyperplane<float,2> coeffs3f;
-      makeNoisyCohyperplanarPoints(1000, points2f_ptrs, &coeffs3f, 0.01f);
-      CALL_SUBTEST(check_fitHyperplane(10, points2f_ptrs, coeffs3f, 0.05f));
-      CALL_SUBTEST(check_fitHyperplane(100, points2f_ptrs, coeffs3f, 0.01f));
-      CALL_SUBTEST(check_fitHyperplane(1000, points2f_ptrs, coeffs3f, 0.002f));
-    }
-#endif
-#ifdef EIGEN_TEST_PART_3
-    {
-      Vector4d points4d [1000];
-      Vector4d *points4d_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points4d_ptrs[i] = &(points4d[i]);
-      Hyperplane<double,4> coeffs5d;
-      makeNoisyCohyperplanarPoints(1000, points4d_ptrs, &coeffs5d, 0.01);
-      CALL_SUBTEST(check_fitHyperplane(10, points4d_ptrs, coeffs5d, 0.05));
-      CALL_SUBTEST(check_fitHyperplane(100, points4d_ptrs, coeffs5d, 0.01));
-      CALL_SUBTEST(check_fitHyperplane(1000, points4d_ptrs, coeffs5d, 0.002));
-    }
-#endif
-#ifdef EIGEN_TEST_PART_4
-    {
-      VectorXcd *points11cd_ptrs[1000];
-      for(int i = 0; i < 1000; i++) points11cd_ptrs[i] = new VectorXcd(11);
-      Hyperplane<std::complex<double>,Dynamic> *coeffs12cd = new Hyperplane<std::complex<double>,Dynamic>(11);
-      makeNoisyCohyperplanarPoints(1000, points11cd_ptrs, coeffs12cd, 0.01);
-      CALL_SUBTEST(check_fitHyperplane(100, points11cd_ptrs, *coeffs12cd, 0.025));
-      CALL_SUBTEST(check_fitHyperplane(1000, points11cd_ptrs, *coeffs12cd, 0.006));
-      delete coeffs12cd;
-      for(int i = 0; i < 1000; i++) delete points11cd_ptrs[i];
-    }
-#endif
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_sizeof.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_sizeof.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_sizeof.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_sizeof.cpp
@@ -1,31 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename MatrixType> void verifySizeOf(const MatrixType&)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  if (MatrixType::RowsAtCompileTime!=Dynamic && MatrixType::ColsAtCompileTime!=Dynamic)
-    VERIFY(sizeof(MatrixType)==sizeof(Scalar)*MatrixType::SizeAtCompileTime);
-  else
-    VERIFY(sizeof(MatrixType)==sizeof(Scalar*) + 2 * sizeof(typename MatrixType::Index));
-}
-
-void test_eigen2_sizeof()
-{
-  CALL_SUBTEST( verifySizeOf(Matrix<float, 1, 1>()) );
-  CALL_SUBTEST( verifySizeOf(Matrix4d()) );
-  CALL_SUBTEST( verifySizeOf(Matrix<double, 4, 2>()) );
-  CALL_SUBTEST( verifySizeOf(Matrix<bool, 7, 5>()) );
-  CALL_SUBTEST( verifySizeOf(MatrixXcf(3, 3)) );
-  CALL_SUBTEST( verifySizeOf(MatrixXi(8, 12)) );
-  CALL_SUBTEST( verifySizeOf(MatrixXcd(20, 20)) );
-  CALL_SUBTEST( verifySizeOf(Matrix<float, 100, 100>()) );
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_smallvectors.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_smallvectors.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_smallvectors.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_smallvectors.cpp
@@ -1,42 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename Scalar> void smallVectors()
-{
-  typedef Matrix<Scalar, 1, 2> V2;
-  typedef Matrix<Scalar, 3, 1> V3;
-  typedef Matrix<Scalar, 1, 4> V4;
-  Scalar x1 = ei_random<Scalar>(),
-         x2 = ei_random<Scalar>(),
-         x3 = ei_random<Scalar>(),
-         x4 = ei_random<Scalar>();
-  V2 v2(x1, x2);
-  V3 v3(x1, x2, x3);
-  V4 v4(x1, x2, x3, x4);
-  VERIFY_IS_APPROX(x1, v2.x());
-  VERIFY_IS_APPROX(x1, v3.x());
-  VERIFY_IS_APPROX(x1, v4.x());
-  VERIFY_IS_APPROX(x2, v2.y());
-  VERIFY_IS_APPROX(x2, v3.y());
-  VERIFY_IS_APPROX(x2, v4.y());
-  VERIFY_IS_APPROX(x3, v3.z());
-  VERIFY_IS_APPROX(x3, v4.z());
-  VERIFY_IS_APPROX(x4, v4.w());
-}
-
-void test_eigen2_smallvectors()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST( smallVectors<int>() );
-    CALL_SUBTEST( smallVectors<float>() );
-    CALL_SUBTEST( smallVectors<double>() );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_sparse_basic.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_sparse_basic.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_sparse_basic.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_sparse_basic.cpp
@@ -1,317 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "sparse.h"
-
-template<typename SetterType,typename DenseType, typename Scalar, int Options>
-bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
-{
-  typedef SparseMatrix<Scalar,Options> SparseType;
-  {
-    sm.setZero();
-    SetterType w(sm);
-    std::vector<Vector2i> remaining = nonzeroCoords;
-    while(!remaining.empty())
-    {
-      int i = ei_random<int>(0,remaining.size()-1);
-      w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
-      remaining[i] = remaining.back();
-      remaining.pop_back();
-    }
-  }
-  return sm.isApprox(ref);
-}
-
-template<typename SetterType,typename DenseType, typename T>
-bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
-{
-  sm.setZero();
-  std::vector<Vector2i> remaining = nonzeroCoords;
-  while(!remaining.empty())
-  {
-    int i = ei_random<int>(0,remaining.size()-1);
-    sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
-    remaining[i] = remaining.back();
-    remaining.pop_back();
-  }
-  return sm.isApprox(ref);
-}
-
-template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
-{
-  const int rows = ref.rows();
-  const int cols = ref.cols();
-  typedef typename SparseMatrixType::Scalar Scalar;
-  enum { Flags = SparseMatrixType::Flags };
-  
-  double density = std::max(8./(rows*cols), 0.01);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  Scalar eps = 1e-6;
-
-  SparseMatrixType m(rows, cols);
-  DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
-  DenseVector vec1 = DenseVector::Random(rows);
-  Scalar s1 = ei_random<Scalar>();
-
-  std::vector<Vector2i> zeroCoords;
-  std::vector<Vector2i> nonzeroCoords;
-  initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
-  
-  if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
-    return;
-
-  // test coeff and coeffRef
-  for (int i=0; i<(int)zeroCoords.size(); ++i)
-  {
-    VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
-    if(ei_is_same_type<SparseMatrixType,SparseMatrix<Scalar,Flags> >::ret)
-      VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
-  }
-  VERIFY_IS_APPROX(m, refMat);
-
-  m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
-  refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
-
-  VERIFY_IS_APPROX(m, refMat);
-  /*
-  // test InnerIterators and Block expressions
-  for (int t=0; t<10; ++t)
-  {
-    int j = ei_random<int>(0,cols-1);
-    int i = ei_random<int>(0,rows-1);
-    int w = ei_random<int>(1,cols-j-1);
-    int h = ei_random<int>(1,rows-i-1);
-
-//     VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
-    for(int c=0; c<w; c++)
-    {
-      VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
-      for(int r=0; r<h; r++)
-      {
-//         VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
-      }
-    }
-//     for(int r=0; r<h; r++)
-//     {
-//       VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
-//       for(int c=0; c<w; c++)
-//       {
-//         VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
-//       }
-//     }
-  }
-
-  for(int c=0; c<cols; c++)
-  {
-    VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c));
-    VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c));
-  }
-
-  for(int r=0; r<rows; r++)
-  {
-    VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
-    VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
-  }
-  */
-
-  // test SparseSetters
-  // coherent setter
-  // TODO extend the MatrixSetter
-//   {
-//     m.setZero();
-//     VERIFY_IS_NOT_APPROX(m, refMat);
-//     SparseSetter<SparseMatrixType, FullyCoherentAccessPattern> w(m);
-//     for (int i=0; i<nonzeroCoords.size(); ++i)
-//     {
-//       w->coeffRef(nonzeroCoords[i].x(),nonzeroCoords[i].y()) = refMat.coeff(nonzeroCoords[i].x(),nonzeroCoords[i].y());
-//     }
-//   }
-//   VERIFY_IS_APPROX(m, refMat);
-
-  // random setter
-//   {
-//     m.setZero();
-//     VERIFY_IS_NOT_APPROX(m, refMat);
-//     SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
-//     std::vector<Vector2i> remaining = nonzeroCoords;
-//     while(!remaining.empty())
-//     {
-//       int i = ei_random<int>(0,remaining.size()-1);
-//       w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
-//       remaining[i] = remaining.back();
-//       remaining.pop_back();
-//     }
-//   }
-//   VERIFY_IS_APPROX(m, refMat);
-
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) ));
-    #ifdef EIGEN_UNORDERED_MAP_SUPPORT
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-    #ifdef _DENSE_HASH_MAP_H_
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-    #ifdef _SPARSE_HASH_MAP_H_
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-
-    // test fillrand
-    {
-      DenseMatrix m1(rows,cols);
-      m1.setZero();
-      SparseMatrixType m2(rows,cols);
-      m2.startFill();
-      for (int j=0; j<cols; ++j)
-      {
-        for (int k=0; k<rows/2; ++k)
-        {
-          int i = ei_random<int>(0,rows-1);
-          if (m1.coeff(i,j)==Scalar(0))
-            m2.fillrand(i,j) = m1(i,j) = ei_random<Scalar>();
-        }
-      }
-      m2.endFill();
-      VERIFY_IS_APPROX(m2,m1);
-    }
-  
-  // test RandomSetter
-  /*{
-    SparseMatrixType m1(rows,cols), m2(rows,cols);
-    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
-    initSparse<Scalar>(density, refM1, m1);
-    {
-      Eigen::RandomSetter<SparseMatrixType > setter(m2);
-      for (int j=0; j<m1.outerSize(); ++j)
-        for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
-          setter(i.index(), j) = i.value();
-    }
-    VERIFY_IS_APPROX(m1, m2);
-  }*/
-//   std::cerr << m.transpose() << "\n\n"  << refMat.transpose() << "\n\n";
-//   VERIFY_IS_APPROX(m, refMat);
-
-  // test basic computations
-  {
-    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM4 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m1(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    SparseMatrixType m3(rows, rows);
-    SparseMatrixType m4(rows, rows);
-    initSparse<Scalar>(density, refM1, m1);
-    initSparse<Scalar>(density, refM2, m2);
-    initSparse<Scalar>(density, refM3, m3);
-    initSparse<Scalar>(density, refM4, m4);
-
-    VERIFY_IS_APPROX(m1+m2, refM1+refM2);
-    VERIFY_IS_APPROX(m1+m2+m3, refM1+refM2+refM3);
-    VERIFY_IS_APPROX(m3.cwise()*(m1+m2), refM3.cwise()*(refM1+refM2));
-    VERIFY_IS_APPROX(m1*s1-m2, refM1*s1-refM2);
-
-    VERIFY_IS_APPROX(m1*=s1, refM1*=s1);
-    VERIFY_IS_APPROX(m1/=s1, refM1/=s1);
-    
-    VERIFY_IS_APPROX(m1+=m2, refM1+=refM2);
-    VERIFY_IS_APPROX(m1-=m2, refM1-=refM2);
-    
-    VERIFY_IS_APPROX(m1.col(0).eigen2_dot(refM2.row(0)), refM1.col(0).eigen2_dot(refM2.row(0)));
-    
-    refM4.setRandom();
-    // sparse cwise* dense
-    VERIFY_IS_APPROX(m3.cwise()*refM4, refM3.cwise()*refM4);
-//     VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
-  }
-
-  // test innerVector()
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    int j0 = ei_random(0,rows-1);
-    int j1 = ei_random(0,rows-1);
-    VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0));
-    VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1));
-    //m2.innerVector(j0) = 2*m2.innerVector(j1);
-    //refMat2.col(j0) = 2*refMat2.col(j1);
-    //VERIFY_IS_APPROX(m2, refMat2);
-  }
-  
-  // test innerVectors()
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    int j0 = ei_random(0,rows-2);
-    int j1 = ei_random(0,rows-2);
-    int n0 = ei_random<int>(1,rows-std::max(j0,j1));
-    VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0));
-    VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
-                     refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
-    //m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0);
-    //refMat2.block(0,j0,rows,n0) = refMat2.block(0,j0,rows,n0) + refMat2.block(0,j1,rows,n0);
-  }
-
-  // test transpose
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
-    VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
-  }
-  
-  // test prune
-  {
-    SparseMatrixType m2(rows, rows);
-    DenseMatrix refM2(rows, rows);
-    refM2.setZero();
-    int countFalseNonZero = 0;
-    int countTrueNonZero = 0;
-    m2.startFill();
-    for (int j=0; j<m2.outerSize(); ++j)
-      for (int i=0; i<m2.innerSize(); ++i)
-      {
-        float x = ei_random<float>(0,1);
-        if (x<0.1)
-        {
-          // do nothing
-        }
-        else if (x<0.5)
-        {
-          countFalseNonZero++;
-          m2.fill(i,j) = Scalar(0);
-        }
-        else
-        {
-          countTrueNonZero++;
-          m2.fill(i,j) = refM2(i,j) = Scalar(1);
-        }
-      }
-    m2.endFill();
-    VERIFY(countFalseNonZero+countTrueNonZero == m2.nonZeros());
-    VERIFY_IS_APPROX(m2, refM2);
-    m2.prune(1);
-    VERIFY(countTrueNonZero==m2.nonZeros());
-    VERIFY_IS_APPROX(m2, refM2);
-  }
-}
-
-void test_eigen2_sparse_basic()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_basic(SparseMatrix<double>(8, 8)) );
-    CALL_SUBTEST_2( sparse_basic(SparseMatrix<std::complex<double> >(16, 16)) );
-    CALL_SUBTEST_1( sparse_basic(SparseMatrix<double>(33, 33)) );
-    
-    CALL_SUBTEST_3( sparse_basic(DynamicSparseMatrix<double>(8, 8)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_sparse_product.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_sparse_product.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_sparse_product.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_sparse_product.cpp
@@ -1,115 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "sparse.h"
-
-template<typename SparseMatrixType> void sparse_product(const SparseMatrixType& ref)
-{
-  const int rows = ref.rows();
-  const int cols = ref.cols();
-  typedef typename SparseMatrixType::Scalar Scalar;
-  enum { Flags = SparseMatrixType::Flags };
-
-  double density = std::max(8./(rows*cols), 0.01);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-
-  // test matrix-matrix product
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refMat3 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refMat4 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix dm4 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    SparseMatrixType m3(rows, rows);
-    SparseMatrixType m4(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    initSparse<Scalar>(density, refMat3, m3);
-    initSparse<Scalar>(density, refMat4, m4);
-    VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3);
-    VERIFY_IS_APPROX(m4=m2.transpose()*m3, refMat4=refMat2.transpose()*refMat3);
-    VERIFY_IS_APPROX(m4=m2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
-    VERIFY_IS_APPROX(m4=m2*m3.transpose(), refMat4=refMat2*refMat3.transpose());
-
-    // sparse * dense
-    VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
-    VERIFY_IS_APPROX(dm4=m2*refMat3.transpose(), refMat4=refMat2*refMat3.transpose());
-    VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3, refMat4=refMat2.transpose()*refMat3);
-    VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
-
-    // dense * sparse
-    VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
-    VERIFY_IS_APPROX(dm4=refMat2*m3.transpose(), refMat4=refMat2*refMat3.transpose());
-    VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3, refMat4=refMat2.transpose()*refMat3);
-    VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
-
-    VERIFY_IS_APPROX(m3=m3*m3, refMat3=refMat3*refMat3);
-  }
-
-  // test matrix - diagonal product
-  if(false) // it compiles, but the precision is terrible. probably doesn't matter in this branch....
-  {
-    DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
-    DiagonalMatrix<DenseVector> d1(DenseVector::Random(rows));
-    SparseMatrixType m2(rows, rows);
-    SparseMatrixType m3(rows, rows);
-    initSparse<Scalar>(density, refM2, m2);
-    initSparse<Scalar>(density, refM3, m3);
-    VERIFY_IS_APPROX(m3=m2*d1, refM3=refM2*d1);
-    VERIFY_IS_APPROX(m3=m2.transpose()*d1, refM3=refM2.transpose()*d1);
-    VERIFY_IS_APPROX(m3=d1*m2, refM3=d1*refM2);
-    VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1 * refM2.transpose());
-  }
-
-  // test self adjoint products
-  {
-    DenseMatrix b = DenseMatrix::Random(rows, rows);
-    DenseMatrix x = DenseMatrix::Random(rows, rows);
-    DenseMatrix refX = DenseMatrix::Random(rows, rows);
-    DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refS = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType mUp(rows, rows);
-    SparseMatrixType mLo(rows, rows);
-    SparseMatrixType mS(rows, rows);
-    do {
-      initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
-    } while (refUp.isZero());
-    refLo = refUp.transpose().conjugate();
-    mLo = mUp.transpose().conjugate();
-    refS = refUp + refLo;
-    refS.diagonal() *= 0.5;
-    mS = mUp + mLo;
-    for (int k=0; k<mS.outerSize(); ++k)
-      for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
-        if (it.index() == k)
-          it.valueRef() *= 0.5;
-
-    VERIFY_IS_APPROX(refS.adjoint(), refS);
-    VERIFY_IS_APPROX(mS.transpose().conjugate(), mS);
-    VERIFY_IS_APPROX(mS, refS);
-    VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
-    VERIFY_IS_APPROX(x=mUp.template marked<UpperTriangular|SelfAdjoint>()*b, refX=refS*b);
-    VERIFY_IS_APPROX(x=mLo.template marked<LowerTriangular|SelfAdjoint>()*b, refX=refS*b);
-    VERIFY_IS_APPROX(x=mS.template marked<SelfAdjoint>()*b, refX=refS*b);
-  }
-
-}
-
-void test_eigen2_sparse_product()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_product(SparseMatrix<double>(8, 8)) );
-    CALL_SUBTEST_2( sparse_product(SparseMatrix<std::complex<double> >(16, 16)) );
-    CALL_SUBTEST_1( sparse_product(SparseMatrix<double>(33, 33)) );
-
-    CALL_SUBTEST_3( sparse_product(DynamicSparseMatrix<double>(8, 8)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_sparse_solvers.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_sparse_solvers.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_sparse_solvers.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_sparse_solvers.cpp
@@ -1,200 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "sparse.h"
-
-template<typename Scalar> void
-initSPD(double density,
-        Matrix<Scalar,Dynamic,Dynamic>& refMat,
-        SparseMatrix<Scalar>& sparseMat)
-{
-  Matrix<Scalar,Dynamic,Dynamic> aux(refMat.rows(),refMat.cols());
-  initSparse(density,refMat,sparseMat);
-  refMat = refMat * refMat.adjoint();
-  for (int k=0; k<2; ++k)
-  {
-    initSparse(density,aux,sparseMat,ForceNonZeroDiag);
-    refMat += aux * aux.adjoint();
-  }
-  sparseMat.startFill();
-  for (int j=0 ; j<sparseMat.cols(); ++j)
-    for (int i=j ; i<sparseMat.rows(); ++i)
-      if (refMat(i,j)!=Scalar(0))
-        sparseMat.fill(i,j) = refMat(i,j);
-  sparseMat.endFill();
-}
-
-template<typename Scalar> void sparse_solvers(int rows, int cols)
-{
-  double density = std::max(8./(rows*cols), 0.01);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  // Scalar eps = 1e-6;
-
-  DenseVector vec1 = DenseVector::Random(rows);
-
-  std::vector<Vector2i> zeroCoords;
-  std::vector<Vector2i> nonzeroCoords;
-
-  // test triangular solver
-  {
-    DenseVector vec2 = vec1, vec3 = vec1;
-    SparseMatrix<Scalar> m2(rows, cols);
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
-
-    // lower
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
-    VERIFY_IS_APPROX(refMat2.template marked<LowerTriangular>().solveTriangular(vec2),
-                     m2.template marked<LowerTriangular>().solveTriangular(vec3));
-
-    // lower - transpose
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
-    VERIFY_IS_APPROX(refMat2.template marked<LowerTriangular>().transpose().solveTriangular(vec2),
-                     m2.template marked<LowerTriangular>().transpose().solveTriangular(vec3));
-
-    // upper
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords);
-    VERIFY_IS_APPROX(refMat2.template marked<UpperTriangular>().solveTriangular(vec2),
-                     m2.template marked<UpperTriangular>().solveTriangular(vec3));
-
-    // upper - transpose
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords);
-    VERIFY_IS_APPROX(refMat2.template marked<UpperTriangular>().transpose().solveTriangular(vec2),
-                     m2.template marked<UpperTriangular>().transpose().solveTriangular(vec3));
-  }
-
-  // test LLT
-  {
-    // TODO fix the issue with complex (see SparseLLT::solveInPlace)
-    SparseMatrix<Scalar> m2(rows, cols);
-    DenseMatrix refMat2(rows, cols);
-
-    DenseVector b = DenseVector::Random(cols);
-    DenseVector refX(cols), x(cols);
-
-    initSPD(density, refMat2, m2);
-
-    refMat2.llt().solve(b, &refX);
-    typedef SparseMatrix<Scalar,LowerTriangular|SelfAdjoint> SparseSelfAdjointMatrix;
-    if (!NumTraits<Scalar>::IsComplex)
-    {
-      x = b;
-      SparseLLT<SparseSelfAdjointMatrix> (m2).solveInPlace(x);
-      VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: default");
-    }
-    #ifdef EIGEN_CHOLMOD_SUPPORT
-    x = b;
-    SparseLLT<SparseSelfAdjointMatrix,Cholmod>(m2).solveInPlace(x);
-    VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: cholmod");
-    #endif
-    if (!NumTraits<Scalar>::IsComplex)
-    {
-      #ifdef EIGEN_TAUCS_SUPPORT
-      x = b;
-      SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
-      VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
-      x = b;
-      SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
-      VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
-      x = b;
-      SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
-      VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
-      #endif
-    }
-  }
-
-  // test LDLT
-  if (!NumTraits<Scalar>::IsComplex)
-  {
-    // TODO fix the issue with complex (see SparseLDLT::solveInPlace)
-    SparseMatrix<Scalar> m2(rows, cols);
-    DenseMatrix refMat2(rows, cols);
-
-    DenseVector b = DenseVector::Random(cols);
-    DenseVector refX(cols), x(cols);
-
-    //initSPD(density, refMat2, m2);
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0);
-    refMat2 += refMat2.adjoint();
-    refMat2.diagonal() *= 0.5;
-
-    refMat2.ldlt().solve(b, &refX);
-    typedef SparseMatrix<Scalar,UpperTriangular|SelfAdjoint> SparseSelfAdjointMatrix;
-    x = b;
-    SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2);
-    if (ldlt.succeeded())
-      ldlt.solveInPlace(x);
-    VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
-  }
-
-  // test LU
-  {
-    static int count = 0;
-    SparseMatrix<Scalar> m2(rows, cols);
-    DenseMatrix refMat2(rows, cols);
-
-    DenseVector b = DenseVector::Random(cols);
-    DenseVector refX(cols), x(cols);
-
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag, &zeroCoords, &nonzeroCoords);
-
-    LU<DenseMatrix> refLu(refMat2);
-    refLu.solve(b, &refX);
-    #if defined(EIGEN_SUPERLU_SUPPORT) || defined(EIGEN_UMFPACK_SUPPORT)
-    Scalar refDet = refLu.determinant();
-    #endif
-    x.setZero();
-    // // SparseLU<SparseMatrix<Scalar> > (m2).solve(b,&x);
-    // // VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: default");
-    #ifdef EIGEN_SUPERLU_SUPPORT
-    {
-      x.setZero();
-      SparseLU<SparseMatrix<Scalar>,SuperLU> slu(m2);
-      if (slu.succeeded())
-      {
-        if (slu.solve(b,&x)) {
-          VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: SuperLU");
-        }
-        // std::cerr << refDet << " == " << slu.determinant() << "\n";
-        if (count==0) {
-          VERIFY_IS_APPROX(refDet,slu.determinant()); // FIXME det is not very stable for complex
-        }
-      }
-    }
-    #endif
-    #ifdef EIGEN_UMFPACK_SUPPORT
-    {
-      // check solve
-      x.setZero();
-      SparseLU<SparseMatrix<Scalar>,UmfPack> slu(m2);
-      if (slu.succeeded()) {
-        if (slu.solve(b,&x)) {
-          if (count==0) {
-            VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: umfpack");  // FIXME solve is not very stable for complex
-          }
-        }
-        VERIFY_IS_APPROX(refDet,slu.determinant());
-        // TODO check the extracted data
-        //std::cerr << slu.matrixL() << "\n";
-      }
-    }
-    #endif
-    count++;
-  }
-
-}
-
-void test_eigen2_sparse_solvers()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_solvers<double>(8, 8) );
-    CALL_SUBTEST_2( sparse_solvers<std::complex<double> >(16, 16) );
-    CALL_SUBTEST_1( sparse_solvers<double>(101, 101) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_sparse_vector.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_sparse_vector.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_sparse_vector.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_sparse_vector.cpp
@@ -1,84 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "sparse.h"
-
-template<typename Scalar> void sparse_vector(int rows, int cols)
-{
-  double densityMat = std::max(8./(rows*cols), 0.01);
-  double densityVec = std::max(8./float(rows), 0.1);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  typedef SparseVector<Scalar> SparseVectorType;
-  typedef SparseMatrix<Scalar> SparseMatrixType;
-  Scalar eps = 1e-6;
-
-  SparseMatrixType m1(rows,cols);
-  SparseVectorType v1(rows), v2(rows), v3(rows);
-  DenseMatrix refM1 = DenseMatrix::Zero(rows, cols);
-  DenseVector refV1 = DenseVector::Random(rows),
-    refV2 = DenseVector::Random(rows),
-    refV3 = DenseVector::Random(rows);
-
-  std::vector<int> zerocoords, nonzerocoords;
-  initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords);
-  initSparse<Scalar>(densityMat, refM1, m1);
-
-  initSparse<Scalar>(densityVec, refV2, v2);
-  initSparse<Scalar>(densityVec, refV3, v3);
-
-  Scalar s1 = ei_random<Scalar>();
-
-  // test coeff and coeffRef
-  for (unsigned int i=0; i<zerocoords.size(); ++i)
-  {
-    VERIFY_IS_MUCH_SMALLER_THAN( v1.coeff(zerocoords[i]), eps );
-    //VERIFY_RAISES_ASSERT( v1.coeffRef(zerocoords[i]) = 5 );
-  }
-  {
-    VERIFY(int(nonzerocoords.size()) == v1.nonZeros());
-    int j=0;
-    for (typename SparseVectorType::InnerIterator it(v1); it; ++it,++j)
-    {
-      VERIFY(nonzerocoords[j]==it.index());
-      VERIFY(it.value()==v1.coeff(it.index()));
-      VERIFY(it.value()==refV1.coeff(it.index()));
-    }
-  }
-  VERIFY_IS_APPROX(v1, refV1);
-
-  v1.coeffRef(nonzerocoords[0]) = Scalar(5);
-  refV1.coeffRef(nonzerocoords[0]) = Scalar(5);
-  VERIFY_IS_APPROX(v1, refV1);
-
-  VERIFY_IS_APPROX(v1+v2, refV1+refV2);
-  VERIFY_IS_APPROX(v1+v2+v3, refV1+refV2+refV3);
-
-  VERIFY_IS_APPROX(v1*s1-v2, refV1*s1-refV2);
-
-  VERIFY_IS_APPROX(v1*=s1, refV1*=s1);
-  VERIFY_IS_APPROX(v1/=s1, refV1/=s1);
-  
-  VERIFY_IS_APPROX(v1+=v2, refV1+=refV2);
-  VERIFY_IS_APPROX(v1-=v2, refV1-=refV2);
-
-  VERIFY_IS_APPROX(v1.eigen2_dot(v2), refV1.eigen2_dot(refV2));
-  VERIFY_IS_APPROX(v1.eigen2_dot(refV2), refV1.eigen2_dot(refV2));
-
-}
-
-void test_eigen2_sparse_vector()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_vector<double>(8, 8) );
-    CALL_SUBTEST_2( sparse_vector<std::complex<double> >(16, 16) );
-    CALL_SUBTEST_1( sparse_vector<double>(299, 535) );
-  }
-}
-

DELETED 3rd_party/eigen/test/eigen2/eigen2_stdvector.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_stdvector.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_stdvector.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_stdvector.cpp
@@ -1,148 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include <Eigen/StdVector>
-#include "main.h"
-#include <Eigen/Geometry>
-
-template<typename MatrixType>
-void check_stdvector_matrix(const MatrixType& m)
-{
-  int rows = m.rows();
-  int cols = m.cols();
-  MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
-  std::vector<MatrixType, aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(MatrixType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  MatrixType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i]==w[(i-23)%w.size()]);
-  }
-}
-
-template<typename TransformType>
-void check_stdvector_transform(const TransformType&)
-{
-  typedef typename TransformType::MatrixType MatrixType;
-  TransformType x(MatrixType::Random()), y(MatrixType::Random());
-  std::vector<TransformType, aligned_allocator<TransformType> > v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(TransformType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  TransformType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i].matrix()==w[(i-23)%w.size()].matrix());
-  }
-}
-
-template<typename QuaternionType>
-void check_stdvector_quaternion(const QuaternionType&)
-{
-  typedef typename QuaternionType::Coefficients Coefficients;
-  QuaternionType x(Coefficients::Random()), y(Coefficients::Random());
-  std::vector<QuaternionType, aligned_allocator<QuaternionType> > v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(QuaternionType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  QuaternionType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i].coeffs()==w[(i-23)%w.size()].coeffs());
-  }
-}
-
-void test_eigen2_stdvector()
-{
-  // some non vectorizable fixed sizes
-  CALL_SUBTEST_1(check_stdvector_matrix(Vector2f()));
-  CALL_SUBTEST_1(check_stdvector_matrix(Matrix3f()));
-  CALL_SUBTEST_1(check_stdvector_matrix(Matrix3d()));
-
-  // some vectorizable fixed sizes
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix2f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Vector4f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix4f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix4d()));
-
-  // some dynamic sizes
-  CALL_SUBTEST_3(check_stdvector_matrix(MatrixXd(1,1)));
-  CALL_SUBTEST_3(check_stdvector_matrix(VectorXd(20)));
-  CALL_SUBTEST_3(check_stdvector_matrix(RowVectorXf(20)));
-  CALL_SUBTEST_3(check_stdvector_matrix(MatrixXcf(10,10)));
-
-  // some Transform
-  CALL_SUBTEST_4(check_stdvector_transform(Transform2f()));
-  CALL_SUBTEST_4(check_stdvector_transform(Transform3f()));
-  CALL_SUBTEST_4(check_stdvector_transform(Transform3d()));
-  //CALL_SUBTEST_4(check_stdvector_transform(Transform4d()));
-
-  // some Quaternion
-  CALL_SUBTEST_5(check_stdvector_quaternion(Quaternionf()));
-  CALL_SUBTEST_5(check_stdvector_quaternion(Quaternionf()));
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_submatrices.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_submatrices.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_submatrices.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_submatrices.cpp
@@ -1,142 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-// check minor separately in order to avoid the possible creation of a zero-sized
-// array. Comes from a compilation error with gcc-3.4 or gcc-4 with -ansi -pedantic.
-// Another solution would be to declare the array like this: T m_data[Size==0?1:Size]; in ei_matrix_storage
-// but this is probably not bad to raise such an error at compile time...
-template<typename Scalar, int _Rows, int _Cols> struct CheckMinor
-{
-    typedef Matrix<Scalar, _Rows, _Cols> MatrixType;
-    CheckMinor(MatrixType& m1, int r1, int c1)
-    {
-        int rows = m1.rows();
-        int cols = m1.cols();
-
-        Matrix<Scalar, Dynamic, Dynamic> mi = m1.minor(0,0).eval();
-        VERIFY_IS_APPROX(mi, m1.block(1,1,rows-1,cols-1));
-        mi = m1.minor(r1,c1);
-        VERIFY_IS_APPROX(mi.transpose(), m1.transpose().minor(c1,r1));
-        //check operator(), both constant and non-constant, on minor()
-        m1.minor(r1,c1)(0,0) = m1.minor(0,0)(0,0);
-    }
-};
-
-template<typename Scalar> struct CheckMinor<Scalar,1,1>
-{
-    typedef Matrix<Scalar, 1, 1> MatrixType;
-    CheckMinor(MatrixType&, int, int) {}
-};
-
-template<typename MatrixType> void submatrices(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Row.h Column.h Block.h Minor.h DiagonalCoeffs.h
-  */
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             ones = MatrixType::Ones(rows, cols),
-             square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows);
-
-  Scalar s1 = ei_random<Scalar>();
-
-  int r1 = ei_random<int>(0,rows-1);
-  int r2 = ei_random<int>(r1,rows-1);
-  int c1 = ei_random<int>(0,cols-1);
-  int c2 = ei_random<int>(c1,cols-1);
-
-  //check row() and col()
-  VERIFY_IS_APPROX(m1.col(c1).transpose(), m1.transpose().row(c1));
-  VERIFY_IS_APPROX(square.row(r1).eigen2_dot(m1.col(c1)), (square.lazy() * m1.conjugate())(r1,c1));
-  //check operator(), both constant and non-constant, on row() and col()
-  m1.row(r1) += s1 * m1.row(r2);
-  m1.col(c1) += s1 * m1.col(c2);
-
-  //check block()
-  Matrix<Scalar,Dynamic,Dynamic> b1(1,1); b1(0,0) = m1(r1,c1);
-  RowVectorType br1(m1.block(r1,0,1,cols));
-  VectorType bc1(m1.block(0,c1,rows,1));
-  VERIFY_IS_APPROX(b1, m1.block(r1,c1,1,1));
-  VERIFY_IS_APPROX(m1.row(r1), br1);
-  VERIFY_IS_APPROX(m1.col(c1), bc1);
-  //check operator(), both constant and non-constant, on block()
-  m1.block(r1,c1,r2-r1+1,c2-c1+1) = s1 * m2.block(0, 0, r2-r1+1,c2-c1+1);
-  m1.block(r1,c1,r2-r1+1,c2-c1+1)(r2-r1,c2-c1) = m2.block(0, 0, r2-r1+1,c2-c1+1)(0,0);
-
-  //check minor()
-  CheckMinor<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> checkminor(m1,r1,c1);
-
-  //check diagonal()
-  VERIFY_IS_APPROX(m1.diagonal(), m1.transpose().diagonal());
-  m2.diagonal() = 2 * m1.diagonal();
-  m2.diagonal()[0] *= 3;
-  VERIFY_IS_APPROX(m2.diagonal()[0], static_cast<Scalar>(6) * m1.diagonal()[0]);
-
-  enum {
-    BlockRows = EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::RowsAtCompileTime,2),
-    BlockCols = EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::ColsAtCompileTime,5)
-  };
-  if (rows>=5 && cols>=8)
-  {
-    // test fixed block() as lvalue
-    m1.template block<BlockRows,BlockCols>(1,1) *= s1;
-    // test operator() on fixed block() both as constant and non-constant
-    m1.template block<BlockRows,BlockCols>(1,1)(0, 3) = m1.template block<2,5>(1,1)(1,2);
-    // check that fixed block() and block() agree
-    Matrix<Scalar,Dynamic,Dynamic> b = m1.template block<BlockRows,BlockCols>(3,3);
-    VERIFY_IS_APPROX(b, m1.block(3,3,BlockRows,BlockCols));
-  }
-
-  if (rows>2)
-  {
-    // test sub vectors
-    VERIFY_IS_APPROX(v1.template start<2>(), v1.block(0,0,2,1));
-    VERIFY_IS_APPROX(v1.template start<2>(), v1.start(2));
-    VERIFY_IS_APPROX(v1.template start<2>(), v1.segment(0,2));
-    VERIFY_IS_APPROX(v1.template start<2>(), v1.template segment<2>(0));
-    int i = rows-2;
-    VERIFY_IS_APPROX(v1.template end<2>(), v1.block(i,0,2,1));
-    VERIFY_IS_APPROX(v1.template end<2>(), v1.end(2));
-    VERIFY_IS_APPROX(v1.template end<2>(), v1.segment(i,2));
-    VERIFY_IS_APPROX(v1.template end<2>(), v1.template segment<2>(i));
-    i = ei_random(0,rows-2);
-    VERIFY_IS_APPROX(v1.segment(i,2), v1.template segment<2>(i));
-  }
-
-  // stress some basic stuffs with block matrices
-  VERIFY(ei_real(ones.col(c1).sum()) == RealScalar(rows));
-  VERIFY(ei_real(ones.row(r1).sum()) == RealScalar(cols));
-
-  VERIFY(ei_real(ones.col(c1).eigen2_dot(ones.col(c2))) == RealScalar(rows));
-  VERIFY(ei_real(ones.row(r1).eigen2_dot(ones.row(r2))) == RealScalar(cols));
-}
-
-void test_eigen2_submatrices()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( submatrices(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( submatrices(Matrix4d()) );
-    CALL_SUBTEST_3( submatrices(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_4( submatrices(MatrixXi(8, 12)) );
-    CALL_SUBTEST_5( submatrices(MatrixXcd(20, 20)) );
-    CALL_SUBTEST_6( submatrices(MatrixXf(20, 20)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_sum.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_sum.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_sum.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_sum.cpp
@@ -1,71 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename MatrixType> void matrixSum(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols);
-
-  VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
-  VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy
-  Scalar x = Scalar(0);
-  for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) x += m1(i,j);
-  VERIFY_IS_APPROX(m1.sum(), x);
-}
-
-template<typename VectorType> void vectorSum(const VectorType& w)
-{
-  typedef typename VectorType::Scalar Scalar;
-  int size = w.size();
-
-  VectorType v = VectorType::Random(size);
-  for(int i = 1; i < size; i++)
-  {
-    Scalar s = Scalar(0);
-    for(int j = 0; j < i; j++) s += v[j];
-    VERIFY_IS_APPROX(s, v.start(i).sum());
-  }
-
-  for(int i = 0; i < size-1; i++)
-  {
-    Scalar s = Scalar(0);
-    for(int j = i; j < size; j++) s += v[j];
-    VERIFY_IS_APPROX(s, v.end(size-i).sum());
-  }
-
-  for(int i = 0; i < size/2; i++)
-  {
-    Scalar s = Scalar(0);
-    for(int j = i; j < size-i; j++) s += v[j];
-    VERIFY_IS_APPROX(s, v.segment(i, size-2*i).sum());
-  }
-}
-
-void test_eigen2_sum()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( matrixSum(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( matrixSum(Matrix2f()) );
-    CALL_SUBTEST_3( matrixSum(Matrix4d()) );
-    CALL_SUBTEST_4( matrixSum(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_5( matrixSum(MatrixXf(8, 12)) );
-    CALL_SUBTEST_6( matrixSum(MatrixXi(8, 12)) );
-  }
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_5( vectorSum(VectorXf(5)) );
-    CALL_SUBTEST_7( vectorSum(VectorXd(10)) );
-    CALL_SUBTEST_5( vectorSum(VectorXf(33)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_svd.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_svd.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_svd.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_svd.cpp
@@ -1,87 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/SVD>
-
-template<typename MatrixType> void svd(const MatrixType& m)
-{
-  /* this test covers the following files:
-     SVD.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  MatrixType a = MatrixType::Random(rows,cols);
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> b =
-    Matrix<Scalar, MatrixType::RowsAtCompileTime, 1>::Random(rows,1);
-  Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> x(cols,1), x2(cols,1);
-
-  RealScalar largerEps = test_precision<RealScalar>();
-  if (ei_is_same_type<RealScalar,float>::ret)
-    largerEps = 1e-3f;
-
-  {
-    SVD<MatrixType> svd(a);
-    MatrixType sigma = MatrixType::Zero(rows,cols);
-    MatrixType matU  = MatrixType::Zero(rows,rows);
-    sigma.block(0,0,cols,cols) = svd.singularValues().asDiagonal();
-    matU.block(0,0,rows,cols) = svd.matrixU();
-    VERIFY_IS_APPROX(a, matU * sigma * svd.matrixV().transpose());
-  }
-
-
-  if (rows==cols)
-  {
-    if (ei_is_same_type<RealScalar,float>::ret)
-    {
-      MatrixType a1 = MatrixType::Random(rows,cols);
-      a += a * a.adjoint() + a1 * a1.adjoint();
-    }
-    SVD<MatrixType> svd(a);
-    svd.solve(b, &x);
-    VERIFY_IS_APPROX(a * x,b);
-  }
-
-
-  if(rows==cols)
-  {
-    SVD<MatrixType> svd(a);
-    MatrixType unitary, positive;
-    svd.computeUnitaryPositive(&unitary, &positive);
-    VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows()));
-    VERIFY_IS_APPROX(positive, positive.adjoint());
-    for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity
-    VERIFY_IS_APPROX(unitary*positive, a);
-
-    svd.computePositiveUnitary(&positive, &unitary);
-    VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows()));
-    VERIFY_IS_APPROX(positive, positive.adjoint());
-    for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity
-    VERIFY_IS_APPROX(positive*unitary, a);
-  }
-}
-
-void test_eigen2_svd()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( svd(Matrix3f()) );
-    CALL_SUBTEST_2( svd(Matrix4d()) );
-    CALL_SUBTEST_3( svd(MatrixXf(7,7)) );
-    CALL_SUBTEST_4( svd(MatrixXd(14,7)) );
-    // complex are not implemented yet
-//     CALL_SUBTEST( svd(MatrixXcd(6,6)) );
-//     CALL_SUBTEST( svd(MatrixXcf(3,3)) );
-    SVD<MatrixXf> s;
-    MatrixXf m = MatrixXf::Random(10,1);
-    s.compute(m);
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_swap.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_swap.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_swap.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_swap.cpp
@@ -1,83 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#define EIGEN_NO_STATIC_ASSERT
-#include "main.h"
-
-template<typename T>
-struct other_matrix_type
-{
-  typedef int type;
-};
-
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct other_matrix_type<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-{
-  typedef Matrix<_Scalar, _Rows, _Cols, _Options^RowMajor, _MaxRows, _MaxCols> type;
-};
-
-template<typename MatrixType> void swap(const MatrixType& m)
-{
-  typedef typename other_matrix_type<MatrixType>::type OtherMatrixType;
-  typedef typename MatrixType::Scalar Scalar;
-
-  ei_assert((!ei_is_same_type<MatrixType,OtherMatrixType>::ret));
-  int rows = m.rows();
-  int cols = m.cols();
-  
-  // construct 3 matrix guaranteed to be distinct
-  MatrixType m1 = MatrixType::Random(rows,cols);
-  MatrixType m2 = MatrixType::Random(rows,cols) + Scalar(100) * MatrixType::Identity(rows,cols);
-  OtherMatrixType m3 = OtherMatrixType::Random(rows,cols) + Scalar(200) * OtherMatrixType::Identity(rows,cols);
-  
-  MatrixType m1_copy = m1;
-  MatrixType m2_copy = m2;
-  OtherMatrixType m3_copy = m3;
-  
-  // test swapping 2 matrices of same type
-  m1.swap(m2);
-  VERIFY_IS_APPROX(m1,m2_copy);
-  VERIFY_IS_APPROX(m2,m1_copy);
-  m1 = m1_copy;
-  m2 = m2_copy;
-  
-  // test swapping 2 matrices of different types
-  m1.swap(m3);
-  VERIFY_IS_APPROX(m1,m3_copy);
-  VERIFY_IS_APPROX(m3,m1_copy);
-  m1 = m1_copy;
-  m3 = m3_copy;
-  
-  // test swapping matrix with expression
-  m1.swap(m2.block(0,0,rows,cols));
-  VERIFY_IS_APPROX(m1,m2_copy);
-  VERIFY_IS_APPROX(m2,m1_copy);
-  m1 = m1_copy;
-  m2 = m2_copy;
-
-  // test swapping two expressions of different types
-  m1.transpose().swap(m3.transpose());
-  VERIFY_IS_APPROX(m1,m3_copy);
-  VERIFY_IS_APPROX(m3,m1_copy);
-  m1 = m1_copy;
-  m3 = m3_copy;
-  
-  // test assertion on mismatching size -- matrix case
-  VERIFY_RAISES_ASSERT(m1.swap(m1.row(0)));
-  // test assertion on mismatching size -- xpr case
-  VERIFY_RAISES_ASSERT(m1.row(0).swap(m1));
-}
-
-void test_eigen2_swap()
-{
-  CALL_SUBTEST_1( swap(Matrix3f()) ); // fixed size, no vectorization 
-  CALL_SUBTEST_1( swap(Matrix4d()) ); // fixed size, possible vectorization 
-  CALL_SUBTEST_1( swap(MatrixXd(3,3)) ); // dyn size, no vectorization 
-  CALL_SUBTEST_1( swap(MatrixXf(30,30)) ); // dyn size, possible vectorization 
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_triangular.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_triangular.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_triangular.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_triangular.cpp
@@ -1,148 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename MatrixType> void triangular(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-
-  RealScalar largerEps = 10*test_precision<RealScalar>();
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             m4(rows, cols),
-             r1(rows, cols),
-             r2(rows, cols);
-
-  MatrixType m1up = m1.template part<Eigen::UpperTriangular>();
-  MatrixType m2up = m2.template part<Eigen::UpperTriangular>();
-
-  if (rows*cols>1)
-  {
-    VERIFY(m1up.isUpperTriangular());
-    VERIFY(m2up.transpose().isLowerTriangular());
-    VERIFY(!m2.isLowerTriangular());
-  }
-
-//   VERIFY_IS_APPROX(m1up.transpose() * m2, m1.upper().transpose().lower() * m2);
-
-  // test overloaded operator+=
-  r1.setZero();
-  r2.setZero();
-  r1.template part<Eigen::UpperTriangular>() +=  m1;
-  r2 += m1up;
-  VERIFY_IS_APPROX(r1,r2);
-
-  // test overloaded operator=
-  m1.setZero();
-  m1.template part<Eigen::UpperTriangular>() = (m2.transpose() * m2).lazy();
-  m3 = m2.transpose() * m2;
-  VERIFY_IS_APPROX(m3.template part<Eigen::LowerTriangular>().transpose(), m1);
-
-  // test overloaded operator=
-  m1.setZero();
-  m1.template part<Eigen::LowerTriangular>() = (m2.transpose() * m2).lazy();
-  VERIFY_IS_APPROX(m3.template part<Eigen::LowerTriangular>(), m1);
-
-  VERIFY_IS_APPROX(m3.template part<Diagonal>(), m3.diagonal().asDiagonal());
-
-  m1 = MatrixType::Random(rows, cols);
-  for (int i=0; i<rows; ++i)
-    while (ei_abs2(m1(i,i))<1e-3) m1(i,i) = ei_random<Scalar>();
-
-  Transpose<MatrixType> trm4(m4);
-  // test back and forward subsitution
-  m3 = m1.template part<Eigen::LowerTriangular>();
-  VERIFY(m3.template marked<Eigen::LowerTriangular>().solveTriangular(m3).cwise().abs().isIdentity(test_precision<RealScalar>()));
-  VERIFY(m3.transpose().template marked<Eigen::UpperTriangular>()
-    .solveTriangular(m3.transpose()).cwise().abs().isIdentity(test_precision<RealScalar>()));
-  // check M * inv(L) using in place API
-  m4 = m3;
-  m3.transpose().template marked<Eigen::UpperTriangular>().solveTriangularInPlace(trm4);
-  VERIFY(m4.cwise().abs().isIdentity(test_precision<RealScalar>()));
-
-  m3 = m1.template part<Eigen::UpperTriangular>();
-  VERIFY(m3.template marked<Eigen::UpperTriangular>().solveTriangular(m3).cwise().abs().isIdentity(test_precision<RealScalar>()));
-  VERIFY(m3.transpose().template marked<Eigen::LowerTriangular>()
-    .solveTriangular(m3.transpose()).cwise().abs().isIdentity(test_precision<RealScalar>()));
-  // check M * inv(U) using in place API
-  m4 = m3;
-  m3.transpose().template marked<Eigen::LowerTriangular>().solveTriangularInPlace(trm4);
-  VERIFY(m4.cwise().abs().isIdentity(test_precision<RealScalar>()));
-
-  m3 = m1.template part<Eigen::UpperTriangular>();
-  VERIFY(m2.isApprox(m3 * (m3.template marked<Eigen::UpperTriangular>().solveTriangular(m2)), largerEps));
-  m3 = m1.template part<Eigen::LowerTriangular>();
-  VERIFY(m2.isApprox(m3 * (m3.template marked<Eigen::LowerTriangular>().solveTriangular(m2)), largerEps));
-
-  VERIFY((m1.template part<Eigen::UpperTriangular>() * m2.template part<Eigen::UpperTriangular>()).isUpperTriangular());
-
-  // test swap
-  m1.setOnes();
-  m2.setZero();
-  m2.template part<Eigen::UpperTriangular>().swap(m1);
-  m3.setZero();
-  m3.template part<Eigen::UpperTriangular>().setOnes();
-  VERIFY_IS_APPROX(m2,m3);
-
-}
-
-void selfadjoint()
-{
-  Matrix2i m;
-  m << 1, 2,
-       3, 4;
-
-  Matrix2i m1 = Matrix2i::Zero();
-  m1.part<SelfAdjoint>() = m;
-  Matrix2i ref1;
-  ref1 << 1, 2,
-          2, 4;
-  VERIFY(m1 == ref1);
-  
-  Matrix2i m2 = Matrix2i::Zero();
-  m2.part<SelfAdjoint>() = m.part<UpperTriangular>();
-  Matrix2i ref2;
-  ref2 << 1, 2,
-          2, 4;
-  VERIFY(m2 == ref2);
- 
-  Matrix2i m3 = Matrix2i::Zero();
-  m3.part<SelfAdjoint>() = m.part<LowerTriangular>();
-  Matrix2i ref3;
-  ref3 << 1, 0,
-          0, 4;
-  VERIFY(m3 == ref3);
-  
-  // example inspired from bug 159
-  int array[] = {1, 2, 3, 4};
-  Matrix2i::Map(array).part<SelfAdjoint>() = Matrix2i::Random().part<LowerTriangular>();
-  
-  std::cout << "hello\n" << array << std::endl;
-}
-
-void test_eigen2_triangular()
-{
-  CALL_SUBTEST_8( selfadjoint() );
-  for(int i = 0; i < g_repeat ; i++) {
-    CALL_SUBTEST_1( triangular(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( triangular(Matrix<float, 2, 2>()) );
-    CALL_SUBTEST_3( triangular(Matrix3d()) );
-    CALL_SUBTEST_4( triangular(MatrixXcf(4, 4)) );
-    CALL_SUBTEST_5( triangular(Matrix<std::complex<float>,8, 8>()) );
-    CALL_SUBTEST_6( triangular(MatrixXd(17,17)) );
-    CALL_SUBTEST_7( triangular(Matrix<float,Dynamic,Dynamic,RowMajor>(5, 5)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_unalignedassert.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_unalignedassert.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_unalignedassert.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_unalignedassert.cpp
@@ -1,116 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-struct Good1
-{
-  MatrixXd m; // good: m will allocate its own array, taking care of alignment.
-  Good1() : m(20,20) {}
-};
-
-struct Good2
-{
-  Matrix3d m; // good: m's size isn't a multiple of 16 bytes, so m doesn't have to be aligned
-};
-
-struct Good3
-{
-  Vector2f m; // good: same reason
-};
-
-struct Bad4
-{
-  Vector2d m; // bad: sizeof(m)%16==0 so alignment is required
-};
-
-struct Bad5
-{
-  Matrix<float, 2, 6> m; // bad: same reason
-};
-
-struct Bad6
-{
-  Matrix<double, 3, 4> m; // bad: same reason
-};
-
-struct Good7
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  Vector2d m;
-  float f; // make the struct have sizeof%16!=0 to make it a little more tricky when we allow an array of 2 such objects
-};
-
-struct Good8
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  float f; // try the f at first -- the EIGEN_ALIGN_128 attribute of m should make that still work
-  Matrix4f m;
-};
-
-struct Good9
-{
-  Matrix<float,2,2,DontAlign> m; // good: no alignment requested
-  float f;
-};
-
-template<bool Align> struct Depends
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(Align)
-  Vector2d m;
-  float f;
-};
-
-template<typename T>
-void check_unalignedassert_good()
-{
-  T *x, *y;
-  x = new T;
-  delete x;
-  y = new T[2];
-  delete[] y;
-}
-
-#if EIGEN_ARCH_WANTS_ALIGNMENT
-template<typename T>
-void check_unalignedassert_bad()
-{
-  float buf[sizeof(T)+16];
-  float *unaligned = buf;
-  while((reinterpret_cast<std::size_t>(unaligned)&0xf)==0) ++unaligned; // make sure unaligned is really unaligned
-  T *x = ::new(static_cast<void*>(unaligned)) T;
-  x->~T();
-}
-#endif
-
-void unalignedassert()
-{
-  check_unalignedassert_good<Good1>();
-  check_unalignedassert_good<Good2>();
-  check_unalignedassert_good<Good3>();
-#if EIGEN_ARCH_WANTS_ALIGNMENT
-  VERIFY_RAISES_ASSERT(check_unalignedassert_bad<Bad4>());
-  VERIFY_RAISES_ASSERT(check_unalignedassert_bad<Bad5>());
-  VERIFY_RAISES_ASSERT(check_unalignedassert_bad<Bad6>());
-#endif
-
-  check_unalignedassert_good<Good7>();
-  check_unalignedassert_good<Good8>();
-  check_unalignedassert_good<Good9>();
-  check_unalignedassert_good<Depends<true> >();
-
-#if EIGEN_ARCH_WANTS_ALIGNMENT
-  VERIFY_RAISES_ASSERT(check_unalignedassert_bad<Depends<false> >());
-#endif
-}
-
-void test_eigen2_unalignedassert()
-{
-  CALL_SUBTEST(unalignedassert());
-}

DELETED 3rd_party/eigen/test/eigen2/eigen2_visitor.cpp
Index: 3rd_party/eigen/test/eigen2/eigen2_visitor.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2/eigen2_visitor.cpp
+++ 3rd_party/eigen/test/eigen2/eigen2_visitor.cpp
@@ -1,116 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-
-template<typename MatrixType> void matrixVisitor(const MatrixType& p)
-{
-  typedef typename MatrixType::Scalar Scalar;
-
-  int rows = p.rows();
-  int cols = p.cols();
-
-  // construct a random matrix where all coefficients are different
-  MatrixType m;
-  m = MatrixType::Random(rows, cols);
-  for(int i = 0; i < m.size(); i++)
-    for(int i2 = 0; i2 < i; i2++)
-      while(m(i) == m(i2)) // yes, ==
-        m(i) = ei_random<Scalar>();
-  
-  Scalar minc = Scalar(1000), maxc = Scalar(-1000);
-  int minrow=0,mincol=0,maxrow=0,maxcol=0;
-  for(int j = 0; j < cols; j++)
-  for(int i = 0; i < rows; i++)
-  {
-    if(m(i,j) < minc)
-    {
-      minc = m(i,j);
-      minrow = i;
-      mincol = j;
-    }
-    if(m(i,j) > maxc)
-    {
-      maxc = m(i,j);
-      maxrow = i;
-      maxcol = j;
-    }
-  }
-  int eigen_minrow, eigen_mincol, eigen_maxrow, eigen_maxcol;
-  Scalar eigen_minc, eigen_maxc;
-  eigen_minc = m.minCoeff(&eigen_minrow,&eigen_mincol);
-  eigen_maxc = m.maxCoeff(&eigen_maxrow,&eigen_maxcol);
-  VERIFY(minrow == eigen_minrow);
-  VERIFY(maxrow == eigen_maxrow);
-  VERIFY(mincol == eigen_mincol);
-  VERIFY(maxcol == eigen_maxcol);
-  VERIFY_IS_APPROX(minc, eigen_minc);
-  VERIFY_IS_APPROX(maxc, eigen_maxc);
-  VERIFY_IS_APPROX(minc, m.minCoeff());
-  VERIFY_IS_APPROX(maxc, m.maxCoeff());
-}
-
-template<typename VectorType> void vectorVisitor(const VectorType& w)
-{
-  typedef typename VectorType::Scalar Scalar;
-
-  int size = w.size();
-
-  // construct a random vector where all coefficients are different
-  VectorType v;
-  v = VectorType::Random(size);
-  for(int i = 0; i < size; i++)
-    for(int i2 = 0; i2 < i; i2++)
-      while(v(i) == v(i2)) // yes, ==
-        v(i) = ei_random<Scalar>();
-  
-  Scalar minc = Scalar(1000), maxc = Scalar(-1000);
-  int minidx=0,maxidx=0;
-  for(int i = 0; i < size; i++)
-  {
-    if(v(i) < minc)
-    {
-      minc = v(i);
-      minidx = i;
-    }
-    if(v(i) > maxc)
-    {
-      maxc = v(i);
-      maxidx = i;
-    }
-  }
-  int eigen_minidx, eigen_maxidx;
-  Scalar eigen_minc, eigen_maxc;
-  eigen_minc = v.minCoeff(&eigen_minidx);
-  eigen_maxc = v.maxCoeff(&eigen_maxidx);
-  VERIFY(minidx == eigen_minidx);
-  VERIFY(maxidx == eigen_maxidx);
-  VERIFY_IS_APPROX(minc, eigen_minc);
-  VERIFY_IS_APPROX(maxc, eigen_maxc);
-  VERIFY_IS_APPROX(minc, v.minCoeff());
-  VERIFY_IS_APPROX(maxc, v.maxCoeff());
-}
-
-void test_eigen2_visitor()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( matrixVisitor(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( matrixVisitor(Matrix2f()) );
-    CALL_SUBTEST_3( matrixVisitor(Matrix4d()) );
-    CALL_SUBTEST_4( matrixVisitor(MatrixXd(8, 12)) );
-    CALL_SUBTEST_5( matrixVisitor(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 20)) );
-    CALL_SUBTEST_6( matrixVisitor(MatrixXi(8, 12)) );
-  }
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_7( vectorVisitor(Vector4f()) );
-    CALL_SUBTEST_4( vectorVisitor(VectorXd(10)) );
-    CALL_SUBTEST_4( vectorVisitor(RowVectorXd(10)) );
-    CALL_SUBTEST_8( vectorVisitor(VectorXf(33)) );
-  }
-}

DELETED 3rd_party/eigen/test/eigen2/gsl_helper.h
Index: 3rd_party/eigen/test/eigen2/gsl_helper.h
==================================================================
--- 3rd_party/eigen/test/eigen2/gsl_helper.h
+++ 3rd_party/eigen/test/eigen2/gsl_helper.h
@@ -1,175 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_GSL_HELPER
-#define EIGEN_GSL_HELPER
-
-#include <Eigen/Core>
-
-#include <gsl/gsl_blas.h>
-#include <gsl/gsl_multifit.h>
-#include <gsl/gsl_eigen.h>
-#include <gsl/gsl_linalg.h>
-#include <gsl/gsl_complex.h>
-#include <gsl/gsl_complex_math.h>
-
-namespace Eigen {
-
-template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex> struct GslTraits
-{
-  typedef gsl_matrix* Matrix;
-  typedef gsl_vector* Vector;
-  static Matrix createMatrix(int rows, int cols) { return gsl_matrix_alloc(rows,cols); }
-  static Vector createVector(int size) { return gsl_vector_alloc(size); }
-  static void free(Matrix& m) { gsl_matrix_free(m); m=0; }
-  static void free(Vector& m) { gsl_vector_free(m); m=0; }
-  static void prod(const Matrix& m, const Vector& v, Vector& x) { gsl_blas_dgemv(CblasNoTrans,1,m,v,0,x); }
-  static void cholesky(Matrix& m) { gsl_linalg_cholesky_decomp(m); }
-  static void cholesky_solve(const Matrix& m, const Vector& b, Vector& x) { gsl_linalg_cholesky_solve(m,b,x); }
-  static void eigen_symm(const Matrix& m, Vector& eval, Matrix& evec)
-  {
-    gsl_eigen_symmv_workspace * w = gsl_eigen_symmv_alloc(m->size1);
-    Matrix a = createMatrix(m->size1, m->size2);
-    gsl_matrix_memcpy(a, m);
-    gsl_eigen_symmv(a,eval,evec,w);
-    gsl_eigen_symmv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC);
-    gsl_eigen_symmv_free(w);
-    free(a);
-  }
-  static void eigen_symm_gen(const Matrix& m, const Matrix& _b, Vector& eval, Matrix& evec)
-  {
-    gsl_eigen_gensymmv_workspace * w = gsl_eigen_gensymmv_alloc(m->size1);
-    Matrix a = createMatrix(m->size1, m->size2);
-    Matrix b = createMatrix(_b->size1, _b->size2);
-    gsl_matrix_memcpy(a, m);
-    gsl_matrix_memcpy(b, _b);
-    gsl_eigen_gensymmv(a,b,eval,evec,w);
-    gsl_eigen_symmv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC);
-    gsl_eigen_gensymmv_free(w);
-    free(a);
-  }
-};
-
-template<typename Scalar> struct GslTraits<Scalar,true>
-{
-  typedef gsl_matrix_complex* Matrix;
-  typedef gsl_vector_complex* Vector;
-  static Matrix createMatrix(int rows, int cols) { return gsl_matrix_complex_alloc(rows,cols); }
-  static Vector createVector(int size) { return gsl_vector_complex_alloc(size); }
-  static void free(Matrix& m) { gsl_matrix_complex_free(m); m=0; }
-  static void free(Vector& m) { gsl_vector_complex_free(m); m=0; }
-  static void cholesky(Matrix& m) { gsl_linalg_complex_cholesky_decomp(m); }
-  static void cholesky_solve(const Matrix& m, const Vector& b, Vector& x) { gsl_linalg_complex_cholesky_solve(m,b,x); }
-  static void prod(const Matrix& m, const Vector& v, Vector& x)
-  { gsl_blas_zgemv(CblasNoTrans,gsl_complex_rect(1,0),m,v,gsl_complex_rect(0,0),x); }
-  static void eigen_symm(const Matrix& m, gsl_vector* &eval, Matrix& evec)
-  {
-    gsl_eigen_hermv_workspace * w = gsl_eigen_hermv_alloc(m->size1);
-    Matrix a = createMatrix(m->size1, m->size2);
-    gsl_matrix_complex_memcpy(a, m);
-    gsl_eigen_hermv(a,eval,evec,w);
-    gsl_eigen_hermv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC);
-    gsl_eigen_hermv_free(w);
-    free(a);
-  }
-  static void eigen_symm_gen(const Matrix& m, const Matrix& _b, gsl_vector* &eval, Matrix& evec)
-  {
-    gsl_eigen_genhermv_workspace * w = gsl_eigen_genhermv_alloc(m->size1);
-    Matrix a = createMatrix(m->size1, m->size2);
-    Matrix b = createMatrix(_b->size1, _b->size2);
-    gsl_matrix_complex_memcpy(a, m);
-    gsl_matrix_complex_memcpy(b, _b);
-    gsl_eigen_genhermv(a,b,eval,evec,w);
-    gsl_eigen_hermv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC);
-    gsl_eigen_genhermv_free(w);
-    free(a);
-  }
-};
-
-template<typename MatrixType>
-void convert(const MatrixType& m, gsl_matrix* &res)
-{
-//   if (res)
-//     gsl_matrix_free(res);
-  res = gsl_matrix_alloc(m.rows(), m.cols());
-  for (int i=0 ; i<m.rows() ; ++i)
-    for (int j=0 ; j<m.cols(); ++j)
-      gsl_matrix_set(res, i, j, m(i,j));
-}
-
-template<typename MatrixType>
-void convert(const gsl_matrix* m, MatrixType& res)
-{
-  res.resize(int(m->size1), int(m->size2));
-  for (int i=0 ; i<res.rows() ; ++i)
-    for (int j=0 ; j<res.cols(); ++j)
-      res(i,j) = gsl_matrix_get(m,i,j);
-}
-
-template<typename VectorType>
-void convert(const VectorType& m, gsl_vector* &res)
-{
-  if (res) gsl_vector_free(res);
-  res = gsl_vector_alloc(m.size());
-  for (int i=0 ; i<m.size() ; ++i)
-      gsl_vector_set(res, i, m[i]);
-}
-
-template<typename VectorType>
-void convert(const gsl_vector* m, VectorType& res)
-{
-  res.resize (m->size);
-  for (int i=0 ; i<res.rows() ; ++i)
-    res[i] = gsl_vector_get(m, i);
-}
-
-template<typename MatrixType>
-void convert(const MatrixType& m, gsl_matrix_complex* &res)
-{
-  res = gsl_matrix_complex_alloc(m.rows(), m.cols());
-  for (int i=0 ; i<m.rows() ; ++i)
-    for (int j=0 ; j<m.cols(); ++j)
-    {
-      gsl_matrix_complex_set(res, i, j,
-        gsl_complex_rect(m(i,j).real(), m(i,j).imag()));
-    }
-}
-
-template<typename MatrixType>
-void convert(const gsl_matrix_complex* m, MatrixType& res)
-{
-  res.resize(int(m->size1), int(m->size2));
-  for (int i=0 ; i<res.rows() ; ++i)
-    for (int j=0 ; j<res.cols(); ++j)
-      res(i,j) = typename MatrixType::Scalar(
-        GSL_REAL(gsl_matrix_complex_get(m,i,j)),
-        GSL_IMAG(gsl_matrix_complex_get(m,i,j)));
-}
-
-template<typename VectorType>
-void convert(const VectorType& m, gsl_vector_complex* &res)
-{
-  res = gsl_vector_complex_alloc(m.size());
-  for (int i=0 ; i<m.size() ; ++i)
-      gsl_vector_complex_set(res, i, gsl_complex_rect(m[i].real(), m[i].imag()));
-}
-
-template<typename VectorType>
-void convert(const gsl_vector_complex* m, VectorType& res)
-{
-  res.resize(m->size);
-  for (int i=0 ; i<res.rows() ; ++i)
-    res[i] = typename VectorType::Scalar(
-        GSL_REAL(gsl_vector_complex_get(m, i)),
-        GSL_IMAG(gsl_vector_complex_get(m, i)));
-}
-
-}
-
-#endif // EIGEN_GSL_HELPER

DELETED 3rd_party/eigen/test/eigen2/main.h
Index: 3rd_party/eigen/test/eigen2/main.h
==================================================================
--- 3rd_party/eigen/test/eigen2/main.h
+++ 3rd_party/eigen/test/eigen2/main.h
@@ -1,399 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include <cstdlib>
-#include <ctime>
-#include <iostream>
-#include <string>
-#include <vector>
-
-#ifndef EIGEN_TEST_FUNC
-#error EIGEN_TEST_FUNC must be defined
-#endif
-
-#define DEFAULT_REPEAT 10
-
-namespace Eigen
-{
-  static std::vector<std::string> g_test_stack;
-  static int g_repeat;
-}
-
-#define EI_PP_MAKE_STRING2(S) #S
-#define EI_PP_MAKE_STRING(S) EI_PP_MAKE_STRING2(S)
-
-#define EI_PP_CAT2(a,b) a ## b
-#define EI_PP_CAT(a,b) EI_PP_CAT2(a,b)
-
-#ifndef EIGEN_NO_ASSERTION_CHECKING
-
-  namespace Eigen
-  {
-    static const bool should_raise_an_assert = false;
-
-    // Used to avoid to raise two exceptions at a time in which
-    // case the exception is not properly caught.
-    // This may happen when a second exceptions is raise in a destructor.
-    static bool no_more_assert = false;
-
-    struct eigen_assert_exception
-    {
-      eigen_assert_exception(void) {}
-      ~eigen_assert_exception() { Eigen::no_more_assert = false; }
-    };
-  }
-
-  // If EIGEN_DEBUG_ASSERTS is defined and if no assertion is raised while
-  // one should have been, then the list of excecuted assertions is printed out.
-  //
-  // EIGEN_DEBUG_ASSERTS is not enabled by default as it
-  // significantly increases the compilation time
-  // and might even introduce side effects that would hide
-  // some memory errors.
-  #ifdef EIGEN_DEBUG_ASSERTS
-
-    namespace Eigen
-    {
-      static bool ei_push_assert = false;
-      static std::vector<std::string> eigen_assert_list;
-    }
-
-    #define eigen_assert(a)                       \
-      if( (!(a)) && (!no_more_assert) )     \
-      {                                     \
-        Eigen::no_more_assert = true;       \
-        throw Eigen::eigen_assert_exception(); \
-      }                                     \
-      else if (Eigen::ei_push_assert)       \
-      {                                     \
-        eigen_assert_list.push_back(std::string(EI_PP_MAKE_STRING(__FILE__)" ("EI_PP_MAKE_STRING(__LINE__)") : "#a) ); \
-      }
-
-    #define VERIFY_RAISES_ASSERT(a)                                               \
-      {                                                                           \
-        Eigen::no_more_assert = false;                                            \
-        try {                                                                     \
-          Eigen::eigen_assert_list.clear();                                          \
-          Eigen::ei_push_assert = true;                                           \
-          a;                                                                      \
-          Eigen::ei_push_assert = false;                                          \
-          std::cerr << "One of the following asserts should have been raised:\n"; \
-          for (uint ai=0 ; ai<eigen_assert_list.size() ; ++ai)                       \
-            std::cerr << "  " << eigen_assert_list[ai] << "\n";                      \
-          VERIFY(Eigen::should_raise_an_assert && # a);                           \
-        } catch (Eigen::eigen_assert_exception e) {                                  \
-          Eigen::ei_push_assert = false; VERIFY(true);                            \
-        }                                                                         \
-      }
-
-  #else // EIGEN_DEBUG_ASSERTS
-
-    #undef eigen_assert
-
-    // see bug 89. The copy_bool here is working around a bug in gcc <= 4.3
-    #define eigen_assert(a) \
-      if( (!Eigen::internal::copy_bool(a)) && (!no_more_assert) )	\
-      {                                     \
-        Eigen::no_more_assert = true;       \
-        throw Eigen::eigen_assert_exception(); \
-      }
-
-    #define VERIFY_RAISES_ASSERT(a) {                             \
-        Eigen::no_more_assert = false;                            \
-        try { a; VERIFY(Eigen::should_raise_an_assert && # a); }  \
-        catch (Eigen::eigen_assert_exception e) { VERIFY(true); }    \
-      }
-
-  #endif // EIGEN_DEBUG_ASSERTS
-
-  #define EIGEN_USE_CUSTOM_ASSERT
-
-#else // EIGEN_NO_ASSERTION_CHECKING
-
-  #define VERIFY_RAISES_ASSERT(a) {}
-
-#endif // EIGEN_NO_ASSERTION_CHECKING
-
-
-#define EIGEN_INTERNAL_DEBUGGING
-#define EIGEN_NICE_RANDOM
-#include <Eigen/Array>
-
-
-#define VERIFY(a) do { if (!(a)) { \
-    std::cerr << "Test " << g_test_stack.back() << " failed in "EI_PP_MAKE_STRING(__FILE__) << " (" << EI_PP_MAKE_STRING(__LINE__) << ")" \
-      << std::endl << "    " << EI_PP_MAKE_STRING(a) << std::endl << std::endl; \
-    abort(); \
-  } } while (0)
-
-#define VERIFY_IS_APPROX(a, b) VERIFY(test_ei_isApprox(a, b))
-#define VERIFY_IS_NOT_APPROX(a, b) VERIFY(!test_ei_isApprox(a, b))
-#define VERIFY_IS_MUCH_SMALLER_THAN(a, b) VERIFY(test_ei_isMuchSmallerThan(a, b))
-#define VERIFY_IS_NOT_MUCH_SMALLER_THAN(a, b) VERIFY(!test_ei_isMuchSmallerThan(a, b))
-#define VERIFY_IS_APPROX_OR_LESS_THAN(a, b) VERIFY(test_ei_isApproxOrLessThan(a, b))
-#define VERIFY_IS_NOT_APPROX_OR_LESS_THAN(a, b) VERIFY(!test_ei_isApproxOrLessThan(a, b))
-
-#define CALL_SUBTEST(FUNC) do { \
-    g_test_stack.push_back(EI_PP_MAKE_STRING(FUNC)); \
-    FUNC; \
-    g_test_stack.pop_back(); \
-  } while (0)
-
-namespace Eigen {
-
-template<typename T> inline typename NumTraits<T>::Real test_precision();
-template<> inline int test_precision<int>() { return 0; }
-template<> inline float test_precision<float>() { return 1e-3f; }
-template<> inline double test_precision<double>() { return 1e-6; }
-template<> inline float test_precision<std::complex<float> >() { return test_precision<float>(); }
-template<> inline double test_precision<std::complex<double> >() { return test_precision<double>(); }
-template<> inline long double test_precision<long double>() { return 1e-6; }
-
-inline bool test_ei_isApprox(const int& a, const int& b)
-{ return ei_isApprox(a, b, test_precision<int>()); }
-inline bool test_ei_isMuchSmallerThan(const int& a, const int& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<int>()); }
-inline bool test_ei_isApproxOrLessThan(const int& a, const int& b)
-{ return ei_isApproxOrLessThan(a, b, test_precision<int>()); }
-
-inline bool test_ei_isApprox(const float& a, const float& b)
-{ return ei_isApprox(a, b, test_precision<float>()); }
-inline bool test_ei_isMuchSmallerThan(const float& a, const float& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<float>()); }
-inline bool test_ei_isApproxOrLessThan(const float& a, const float& b)
-{ return ei_isApproxOrLessThan(a, b, test_precision<float>()); }
-
-inline bool test_ei_isApprox(const double& a, const double& b)
-{ return ei_isApprox(a, b, test_precision<double>()); }
-inline bool test_ei_isMuchSmallerThan(const double& a, const double& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<double>()); }
-inline bool test_ei_isApproxOrLessThan(const double& a, const double& b)
-{ return ei_isApproxOrLessThan(a, b, test_precision<double>()); }
-
-inline bool test_ei_isApprox(const std::complex<float>& a, const std::complex<float>& b)
-{ return ei_isApprox(a, b, test_precision<std::complex<float> >()); }
-inline bool test_ei_isMuchSmallerThan(const std::complex<float>& a, const std::complex<float>& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<std::complex<float> >()); }
-
-inline bool test_ei_isApprox(const std::complex<double>& a, const std::complex<double>& b)
-{ return ei_isApprox(a, b, test_precision<std::complex<double> >()); }
-inline bool test_ei_isMuchSmallerThan(const std::complex<double>& a, const std::complex<double>& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<std::complex<double> >()); }
-
-inline bool test_ei_isApprox(const long double& a, const long double& b)
-{ return ei_isApprox(a, b, test_precision<long double>()); }
-inline bool test_ei_isMuchSmallerThan(const long double& a, const long double& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<long double>()); }
-inline bool test_ei_isApproxOrLessThan(const long double& a, const long double& b)
-{ return ei_isApproxOrLessThan(a, b, test_precision<long double>()); }
-
-template<typename Type1, typename Type2>
-inline bool test_ei_isApprox(const Type1& a, const Type2& b)
-{
-  return a.isApprox(b, test_precision<typename Type1::Scalar>());
-}
-
-template<typename Derived1, typename Derived2>
-inline bool test_ei_isMuchSmallerThan(const MatrixBase<Derived1>& m1,
-                                   const MatrixBase<Derived2>& m2)
-{
-  return m1.isMuchSmallerThan(m2, test_precision<typename ei_traits<Derived1>::Scalar>());
-}
-
-template<typename Derived>
-inline bool test_ei_isMuchSmallerThan(const MatrixBase<Derived>& m,
-                                   const typename NumTraits<typename ei_traits<Derived>::Scalar>::Real& s)
-{
-  return m.isMuchSmallerThan(s, test_precision<typename ei_traits<Derived>::Scalar>());
-}
-
-} // end namespace Eigen
-
-template<typename T> struct GetDifferentType;
-
-template<> struct GetDifferentType<float> { typedef double type; };
-template<> struct GetDifferentType<double> { typedef float type; };
-template<typename T> struct GetDifferentType<std::complex<T> >
-{ typedef std::complex<typename GetDifferentType<T>::type> type; };
-
-// forward declaration of the main test function
-void EI_PP_CAT(test_,EIGEN_TEST_FUNC)();
-
-using namespace Eigen;
-
-#ifdef EIGEN_TEST_PART_1
-#define CALL_SUBTEST_1(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_1(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_2
-#define CALL_SUBTEST_2(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_2(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_3
-#define CALL_SUBTEST_3(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_3(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_4
-#define CALL_SUBTEST_4(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_4(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_5
-#define CALL_SUBTEST_5(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_5(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_6
-#define CALL_SUBTEST_6(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_6(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_7
-#define CALL_SUBTEST_7(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_7(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_8
-#define CALL_SUBTEST_8(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_8(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_9
-#define CALL_SUBTEST_9(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_9(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_10
-#define CALL_SUBTEST_10(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_10(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_11
-#define CALL_SUBTEST_11(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_11(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_12
-#define CALL_SUBTEST_12(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_12(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_13
-#define CALL_SUBTEST_13(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_13(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_14
-#define CALL_SUBTEST_14(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_14(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_15
-#define CALL_SUBTEST_15(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_15(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_16
-#define CALL_SUBTEST_16(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_16(FUNC)
-#endif
-
-
-
-int main(int argc, char *argv[])
-{
-    bool has_set_repeat = false;
-    bool has_set_seed = false;
-    bool need_help = false;
-    unsigned int seed = 0;
-    int repeat = DEFAULT_REPEAT;
-
-    for(int i = 1; i < argc; i++)
-    {
-      if(argv[i][0] == 'r')
-      {
-        if(has_set_repeat)
-        {
-          std::cout << "Argument " << argv[i] << " conflicting with a former argument" << std::endl;
-          return 1;
-        }
-        repeat = std::atoi(argv[i]+1);
-        has_set_repeat = true;
-        if(repeat <= 0)
-        {
-          std::cout << "Invalid \'repeat\' value " << argv[i]+1 << std::endl;
-          return 1;
-        }
-      }
-      else if(argv[i][0] == 's')
-      {
-        if(has_set_seed)
-        {
-          std::cout << "Argument " << argv[i] << " conflicting with a former argument" << std::endl;
-          return 1;
-        }
-        seed = int(std::strtoul(argv[i]+1, 0, 10));
-        has_set_seed = true;
-        bool ok = seed!=0;
-        if(!ok)
-        {
-          std::cout << "Invalid \'seed\' value " << argv[i]+1 << std::endl;
-          return 1;
-        }
-      }
-      else
-      {
-        need_help = true;
-      }
-    }
-
-    if(need_help)
-    {
-      std::cout << "This test application takes the following optional arguments:" << std::endl;
-      std::cout << "  rN     Repeat each test N times (default: " << DEFAULT_REPEAT << ")" << std::endl;
-      std::cout << "  sN     Use N as seed for random numbers (default: based on current time)" << std::endl;
-      return 1;
-    }
-
-    if(!has_set_seed) seed = (unsigned int) std::time(NULL);
-    if(!has_set_repeat) repeat = DEFAULT_REPEAT;
-
-    std::cout << "Initializing random number generator with seed " << seed << std::endl;
-	std::srand(seed);
-    std::cout << "Repeating each test " << repeat << " times" << std::endl;
-
-    Eigen::g_repeat = repeat;
-    Eigen::g_test_stack.push_back(EI_PP_MAKE_STRING(EIGEN_TEST_FUNC));
-
-    EI_PP_CAT(test_,EIGEN_TEST_FUNC)();
-    return 0;
-}
-
-
-

DELETED 3rd_party/eigen/test/eigen2/product.h
Index: 3rd_party/eigen/test/eigen2/product.h
==================================================================
--- 3rd_party/eigen/test/eigen2/product.h
+++ 3rd_party/eigen/test/eigen2/product.h
@@ -1,129 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "main.h"
-#include <Eigen/Array>
-#include <Eigen/QR>
-
-template<typename Derived1, typename Derived2>
-bool areNotApprox(const MatrixBase<Derived1>& m1, const MatrixBase<Derived2>& m2, typename Derived1::RealScalar epsilon = precision<typename Derived1::RealScalar>())
-{
-  return !((m1-m2).cwise().abs2().maxCoeff() < epsilon * epsilon
-                          * std::max(m1.cwise().abs2().maxCoeff(), m2.cwise().abs2().maxCoeff()));
-}
-
-template<typename MatrixType> void product(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Identity.h Product.h
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::FloatingPoint FloatingPoint;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> RowVectorType;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> ColVectorType;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> RowSquareMatrixType;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> ColSquareMatrixType;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime,
-                         MatrixType::Options^RowMajor> OtherMajorMatrixType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  // this test relies a lot on Random.h, and there's not much more that we can do
-  // to test it, hence I consider that we will have tested Random.h
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols);
-  RowSquareMatrixType
-             identity = RowSquareMatrixType::Identity(rows, rows),
-             square = RowSquareMatrixType::Random(rows, rows),
-             res = RowSquareMatrixType::Random(rows, rows);
-  ColSquareMatrixType
-             square2 = ColSquareMatrixType::Random(cols, cols),
-             res2 = ColSquareMatrixType::Random(cols, cols);
-  RowVectorType v1 = RowVectorType::Random(rows);
-  ColVectorType vc2 = ColVectorType::Random(cols), vcres(cols);
-  OtherMajorMatrixType tm1 = m1;
-
-  Scalar s1 = ei_random<Scalar>();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  // begin testing Product.h: only associativity for now
-  // (we use Transpose.h but this doesn't count as a test for it)
-
-  VERIFY_IS_APPROX((m1*m1.transpose())*m2,  m1*(m1.transpose()*m2));
-  m3 = m1;
-  m3 *= m1.transpose() * m2;
-  VERIFY_IS_APPROX(m3,                      m1 * (m1.transpose()*m2));
-  VERIFY_IS_APPROX(m3,                      m1.lazy() * (m1.transpose()*m2));
-
-  // continue testing Product.h: distributivity
-  VERIFY_IS_APPROX(square*(m1 + m2),        square*m1+square*m2);
-  VERIFY_IS_APPROX(square*(m1 - m2),        square*m1-square*m2);
-
-  // continue testing Product.h: compatibility with ScalarMultiple.h
-  VERIFY_IS_APPROX(s1*(square*m1),          (s1*square)*m1);
-  VERIFY_IS_APPROX(s1*(square*m1),          square*(m1*s1));
-
-  // again, test operator() to check const-qualification
-  s1 += (square.lazy() * m1)(r,c);
-
-  // test Product.h together with Identity.h
-  VERIFY_IS_APPROX(v1,                      identity*v1);
-  VERIFY_IS_APPROX(v1.transpose(),          v1.transpose() * identity);
-  // again, test operator() to check const-qualification
-  VERIFY_IS_APPROX(MatrixType::Identity(rows, cols)(r,c), static_cast<Scalar>(r==c));
-
-  if (rows!=cols)
-     VERIFY_RAISES_ASSERT(m3 = m1*m1);
-
-  // test the previous tests were not screwed up because operator* returns 0
-  // (we use the more accurate default epsilon)
-  if (NumTraits<Scalar>::HasFloatingPoint && std::min(rows,cols)>1)
-  {
-    VERIFY(areNotApprox(m1.transpose()*m2,m2.transpose()*m1));
-  }
-
-  // test optimized operator+= path
-  res = square;
-  res += (m1 * m2.transpose()).lazy();
-  VERIFY_IS_APPROX(res, square + m1 * m2.transpose());
-  if (NumTraits<Scalar>::HasFloatingPoint && std::min(rows,cols)>1)
-  {
-    VERIFY(areNotApprox(res,square + m2 * m1.transpose()));
-  }
-  vcres = vc2;
-  vcres += (m1.transpose() * v1).lazy();
-  VERIFY_IS_APPROX(vcres, vc2 + m1.transpose() * v1);
-  tm1 = m1;
-  VERIFY_IS_APPROX(tm1.transpose() * v1, m1.transpose() * v1);
-  VERIFY_IS_APPROX(v1.transpose() * tm1, v1.transpose() * m1);
-
-  // test submatrix and matrix/vector product
-  for (int i=0; i<rows; ++i)
-    res.row(i) = m1.row(i) * m2.transpose();
-  VERIFY_IS_APPROX(res, m1 * m2.transpose());
-  // the other way round:
-  for (int i=0; i<rows; ++i)
-    res.col(i) = m1 * m2.transpose().col(i);
-  VERIFY_IS_APPROX(res, m1 * m2.transpose());
-
-  res2 = square2;
-  res2 += (m1.transpose() * m2).lazy();
-  VERIFY_IS_APPROX(res2, square2 + m1.transpose() * m2);
-
-  if (NumTraits<Scalar>::HasFloatingPoint && std::min(rows,cols)>1)
-  {
-    VERIFY(areNotApprox(res2,square2 + m2.transpose() * m1));
-  }
-}
-

DELETED 3rd_party/eigen/test/eigen2/runtest.sh
Index: 3rd_party/eigen/test/eigen2/runtest.sh
==================================================================
--- 3rd_party/eigen/test/eigen2/runtest.sh
+++ 3rd_party/eigen/test/eigen2/runtest.sh
@@ -1,28 +0,0 @@
-#!/bin/bash
-
-black='\E[30m'
-red='\E[31m'
-green='\E[32m'
-yellow='\E[33m'
-blue='\E[34m'
-magenta='\E[35m'
-cyan='\E[36m'
-white='\E[37m'
-
-if make test_$1 > /dev/null  2> .runtest.log ; then
-  if ! ./test_$1 r20 > /dev/null 2> .runtest.log ; then
-    echo -e  $red Test $1 failed: $black
-    echo -e $blue
-    cat .runtest.log
-    echo -e $black
-    exit 1
-  else
-  echo -e $green Test $1 passed$black
-  fi
-else
-  echo -e  $red Build of target $1 failed: $black
-  echo -e $blue
-  cat .runtest.log
-  echo -e $black
-  exit 1
-fi

DELETED 3rd_party/eigen/test/eigen2/sparse.h
Index: 3rd_party/eigen/test/eigen2/sparse.h
==================================================================
--- 3rd_party/eigen/test/eigen2/sparse.h
+++ 3rd_party/eigen/test/eigen2/sparse.h
@@ -1,154 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_TESTSPARSE_H
-
-#include "main.h"
-
-#if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC
-#include <tr1/unordered_map>
-#define EIGEN_UNORDERED_MAP_SUPPORT
-namespace std {
-  using std::tr1::unordered_map;
-}
-#endif
-
-#ifdef EIGEN_GOOGLEHASH_SUPPORT
-  #include <google/sparse_hash_map>
-#endif
-
-#include <Eigen/Cholesky>
-#include <Eigen/LU>
-#include <Eigen/Sparse>
-
-enum {
-  ForceNonZeroDiag = 1,
-  MakeLowerTriangular = 2,
-  MakeUpperTriangular = 4,
-  ForceRealDiag = 8
-};
-
-/* Initializes both a sparse and dense matrix with same random values,
- * and a ratio of \a density non zero entries.
- * \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular
- *        allowing to control the shape of the matrix.
- * \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
- *        and zero coefficients respectively.
- */
-template<typename Scalar> void
-initSparse(double density,
-           Matrix<Scalar,Dynamic,Dynamic>& refMat,
-           SparseMatrix<Scalar>& sparseMat,
-           int flags = 0,
-           std::vector<Vector2i>* zeroCoords = 0,
-           std::vector<Vector2i>* nonzeroCoords = 0)
-{
-  sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
-  for(int j=0; j<refMat.cols(); j++)
-  {
-    for(int i=0; i<refMat.rows(); i++)
-    {
-      Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
-      if ((flags&ForceNonZeroDiag) && (i==j))
-      {
-        v = ei_random<Scalar>()*Scalar(3.);
-        v = v*v + Scalar(5.);
-      }
-      if ((flags & MakeLowerTriangular) && j>i)
-        v = Scalar(0);
-      else if ((flags & MakeUpperTriangular) && j<i)
-        v = Scalar(0);
-      
-      if ((flags&ForceRealDiag) && (i==j))
-        v = ei_real(v);
-        
-      if (v!=Scalar(0))
-      {
-        sparseMat.fill(i,j) = v;
-        if (nonzeroCoords)
-          nonzeroCoords->push_back(Vector2i(i,j));
-      }
-      else if (zeroCoords)
-      {
-        zeroCoords->push_back(Vector2i(i,j));
-      }
-      refMat(i,j) = v;
-    }
-  }
-  sparseMat.endFill();
-}
-
-template<typename Scalar> void
-initSparse(double density,
-           Matrix<Scalar,Dynamic,Dynamic>& refMat,
-           DynamicSparseMatrix<Scalar>& sparseMat,
-           int flags = 0,
-           std::vector<Vector2i>* zeroCoords = 0,
-           std::vector<Vector2i>* nonzeroCoords = 0)
-{
-  sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
-  for(int j=0; j<refMat.cols(); j++)
-  {
-    for(int i=0; i<refMat.rows(); i++)
-    {
-      Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
-      if ((flags&ForceNonZeroDiag) && (i==j))
-      {
-        v = ei_random<Scalar>()*Scalar(3.);
-        v = v*v + Scalar(5.);
-      }
-      if ((flags & MakeLowerTriangular) && j>i)
-        v = Scalar(0);
-      else if ((flags & MakeUpperTriangular) && j<i)
-        v = Scalar(0);
-      
-      if ((flags&ForceRealDiag) && (i==j))
-        v = ei_real(v);
-        
-      if (v!=Scalar(0))
-      {
-        sparseMat.fill(i,j) = v;
-        if (nonzeroCoords)
-          nonzeroCoords->push_back(Vector2i(i,j));
-      }
-      else if (zeroCoords)
-      {
-        zeroCoords->push_back(Vector2i(i,j));
-      }
-      refMat(i,j) = v;
-    }
-  }
-  sparseMat.endFill();
-}
-
-template<typename Scalar> void
-initSparse(double density,
-           Matrix<Scalar,Dynamic,1>& refVec,
-           SparseVector<Scalar>& sparseVec,
-           std::vector<int>* zeroCoords = 0,
-           std::vector<int>* nonzeroCoords = 0)
-{
-  sparseVec.reserve(int(refVec.size()*density));
-  sparseVec.setZero();
-  for(int i=0; i<refVec.size(); i++)
-  {
-    Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
-    if (v!=Scalar(0))
-    {
-      sparseVec.fill(i) = v;
-      if (nonzeroCoords)
-        nonzeroCoords->push_back(i);
-    }
-    else if (zeroCoords)
-        zeroCoords->push_back(i);
-    refVec[i] = v;
-  }
-}
-
-#endif // EIGEN_TESTSPARSE_H

DELETED 3rd_party/eigen/test/eigen2/testsuite.cmake
Index: 3rd_party/eigen/test/eigen2/testsuite.cmake
==================================================================
--- 3rd_party/eigen/test/eigen2/testsuite.cmake
+++ 3rd_party/eigen/test/eigen2/testsuite.cmake
@@ -1,197 +0,0 @@
-
-####################################################################
-#
-# Usage:
-#  - create a new folder, let's call it cdash
-#  - in that folder, do:
-#    ctest -S path/to/eigen2/test/testsuite.cmake[,option1=value1[,option2=value2]]
-#
-# Options:
-#  - EIGEN_CXX: compiler, eg.: g++-4.2
-#      default: default c++ compiler
-#  - EIGEN_SITE: eg, INRIA-Bdx_pc-gael, or the name of the contributor, etc.
-#      default: hostname
-#  - EIGEN_BUILD_STRING: a string which identify the system/compiler. It should be formed like that:
-#        <OS_name>-<OS_version>-<arch>-<compiler-version>
-#      with:
-#        <OS_name> = opensuse, debian, osx, windows, cygwin, freebsd, solaris, etc.
-#        <OS_version> = 11.1, XP, vista, leopard, etc.
-#        <arch> = i386, x86_64, ia64, powerpc, etc.
-#        <compiler-version> = gcc-4.3.2, icc-11.0, MSVC-2008, etc.
-#  - EIGEN_EXPLICIT_VECTORIZATION: novec, SSE2, Altivec
-#       default: SSE2 for x86_64 systems, novec otherwise
-#       Its value is automatically appended to EIGEN_BUILD_STRING
-#  - EIGEN_CMAKE_DIR: path to cmake executable
-#  - EIGEN_MODE: dashboard model, can be Experimental, Nightly, or Continuous
-#      default: Nightly
-#  - EIGEN_WORK_DIR: directory used to download the source files and make the builds
-#      default: folder which contains this script
-#  - EIGEN_CMAKE_ARGS: additional arguments passed to cmake
-#  - CTEST_SOURCE_DIRECTORY: path to eigen's src (use a new and empty folder, not the one you are working on)
-#      default: <EIGEN_WORK_DIR>/src
-#  - CTEST_BINARY_DIRECTORY: build directory
-#      default: <EIGEN_WORK_DIR>/nightly-<EIGEN_CXX>
-#
-# Here is an example running several compilers on a linux system:
-# #!/bin/bash
-# ARCH=`uname -m`
-# SITE=`hostname`
-# VERSION=opensuse-11.1
-# WORK_DIR=/home/gael/Coding/eigen2/cdash
-# # get the last version of the script
-# wget http://bitbucket.org/eigen/eigen/raw/tip/test/testsuite.cmake -o $WORK_DIR/testsuite.cmake
-# COMMON="ctest -S $WORK_DIR/testsuite.cmake,EIGEN_WORK_DIR=$WORK_DIR,EIGEN_SITE=$SITE,EIGEN_MODE=$1,EIGEN_BUILD_STRING=$OS_VERSION-$ARCH"
-# $COMMON-gcc-3.4.6,EIGEN_CXX=g++-3.4
-# $COMMON-gcc-4.0.1,EIGEN_CXX=g++-4.0.1
-# $COMMON-gcc-4.3.2,EIGEN_CXX=g++-4.3,EIGEN_EXPLICIT_VECTORIZATION=novec
-# $COMMON-gcc-4.3.2,EIGEN_CXX=g++-4.3,EIGEN_EXPLICIT_VECTORIZATION=SSE2
-# $COMMON-icc-11.0,EIGEN_CXX=icpc
-#
-####################################################################
-
-# process the arguments
-
-set(ARGLIST ${CTEST_SCRIPT_ARG})
-while(${ARGLIST} MATCHES  ".+.*")
-
-  # pick first
-  string(REGEX MATCH "([^,]*)(,.*)?" DUMMY ${ARGLIST})
-  SET(TOP ${CMAKE_MATCH_1})
-
-  # remove first
-  string(REGEX MATCHALL "[^,]*,(.*)" DUMMY ${ARGLIST})
-  SET(ARGLIST ${CMAKE_MATCH_1})
-
-  # decompose as a pair key=value
-  string(REGEX MATCH "([^=]*)(=.*)?" DUMMY ${TOP})
-  SET(KEY ${CMAKE_MATCH_1})
-
-  string(REGEX MATCH "[^=]*=(.*)" DUMMY ${TOP})
-  SET(VALUE ${CMAKE_MATCH_1})
-
-  # set the variable to the specified value
-  if(VALUE)
-    SET(${KEY} ${VALUE})
-  else(VALUE)
-    SET(${KEY} ON)
-  endif(VALUE)
-
-endwhile(${ARGLIST} MATCHES ".+.*")
-
-####################################################################
-# Automatically set some user variables if they have not been defined manually
-####################################################################
-cmake_minimum_required(VERSION 2.6 FATAL_ERROR)
-
-if(NOT EIGEN_SITE)
-  site_name(EIGEN_SITE)
-endif(NOT EIGEN_SITE)
-
-if(NOT EIGEN_CMAKE_DIR)
-  SET(EIGEN_CMAKE_DIR "")
-endif(NOT EIGEN_CMAKE_DIR)
-
-if(NOT EIGEN_BUILD_STRING)
-
-  # let's try to find all information we need to make the build string ourself
-
-  # OS
-  build_name(EIGEN_OS_VERSION)
-
-  # arch
-  set(EIGEN_ARCH ${CMAKE_SYSTEM_PROCESSOR})
-  if(WIN32)
-    set(EIGEN_ARCH $ENV{PROCESSOR_ARCHITECTURE})
-  else(WIN32)
-    execute_process(COMMAND uname -m OUTPUT_VARIABLE EIGEN_ARCH OUTPUT_STRIP_TRAILING_WHITESPACE)
-  endif(WIN32)
-
-  set(EIGEN_BUILD_STRING ${EIGEN_OS_VERSION}${EIGEN_ARCH}-${EIGEN_CXX})
-
-endif(NOT EIGEN_BUILD_STRING)
-
-if(DEFINED EIGEN_EXPLICIT_VECTORIZATION)
-  set(EIGEN_BUILD_STRING ${EIGEN_BUILD_STRING}-${EIGEN_EXPLICIT_VECTORIZATION})
-endif(DEFINED EIGEN_EXPLICIT_VECTORIZATION)
-
-if(NOT EIGEN_WORK_DIR)
-  set(EIGEN_WORK_DIR ${CTEST_SCRIPT_DIRECTORY})
-endif(NOT EIGEN_WORK_DIR)
-
-if(NOT CTEST_SOURCE_DIRECTORY)
-  SET (CTEST_SOURCE_DIRECTORY "${EIGEN_WORK_DIR}/src")
-endif(NOT CTEST_SOURCE_DIRECTORY)
-
-if(NOT CTEST_BINARY_DIRECTORY)
-  SET (CTEST_BINARY_DIRECTORY "${EIGEN_WORK_DIR}/nightly_${EIGEN_CXX}")
-endif(NOT CTEST_BINARY_DIRECTORY)
-
-if(NOT EIGEN_MODE)
-  set(EIGEN_MODE Nightly)
-endif(NOT EIGEN_MODE)
-
-## mandatory variables (the default should be ok in most cases):
-
-SET (CTEST_CVS_COMMAND "hg")
-SET (CTEST_CVS_CHECKOUT "${CTEST_CVS_COMMAND} clone -r 2.0 http://bitbucket.org/eigen/eigen \"${CTEST_SOURCE_DIRECTORY}\"")
-
-# which ctest command to use for running the dashboard
-SET (CTEST_COMMAND "${EIGEN_CMAKE_DIR}ctest -D ${EIGEN_MODE}")
-
-# what cmake command to use for configuring this dashboard
-SET (CTEST_CMAKE_COMMAND "${EIGEN_CMAKE_DIR}cmake -DEIGEN_BUILD_TESTS=on ")
-
-####################################################################
-# The values in this section are optional you can either
-# have them or leave them commented out
-####################################################################
-
-# this make sure we get consistent outputs
-SET($ENV{LC_MESSAGES} "en_EN")
-
-# should ctest wipe the binary tree before running
-SET(CTEST_START_WITH_EMPTY_BINARY_DIRECTORY TRUE)
-SET(CTEST_BACKUP_AND_RESTORE TRUE)
-
-# this is the initial cache to use for the binary tree, be careful to escape
-# any quotes inside of this string if you use it
-if(WIN32 AND NOT UNIX)
-  #message(SEND_ERROR "win32")
-  set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -G \"NMake Makefiles\" -DCMAKE_MAKE_PROGRAM=nmake")
-  SET (CTEST_INITIAL_CACHE "
-    MAKECOMMAND:STRING=nmake -i
-    CMAKE_MAKE_PROGRAM:FILEPATH=nmake
-    CMAKE_GENERATOR:INTERNAL=NMake Makefiles
-    BUILDNAME:STRING=${EIGEN_BUILD_STRING}
-    SITE:STRING=${EIGEN_SITE}
-  ")
-else(WIN32 AND NOT UNIX)
-  SET (CTEST_INITIAL_CACHE "
-    BUILDNAME:STRING=${EIGEN_BUILD_STRING}
-    SITE:STRING=${EIGEN_SITE}
-  ")
-endif(WIN32 AND NOT UNIX)
-
-# set any extra environment variables to use during the execution of the script here:
-
-if(EIGEN_CXX)
-  set(CTEST_ENVIRONMENT "CXX=${EIGEN_CXX}")
-endif(EIGEN_CXX)
-
-if(DEFINED EIGEN_EXPLICIT_VECTORIZATION)
-  if(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE2)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_SSE2=ON")
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE3)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_SSE2=ON -DEIGEN_TEST_SSE3=ON")
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES Altivec)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_ALTIVEC=ON")
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES novec)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_NO_EXPLICIT_VECTORIZATION=ON")
-  else(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE2)
-    message(FATAL_ERROR "Invalid value for EIGEN_EXPLICIT_VECTORIZATION (${EIGEN_EXPLICIT_VECTORIZATION}), must be: novec, SSE2, SSE3, Altivec")
-  endif(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE2)
-endif(DEFINED EIGEN_EXPLICIT_VECTORIZATION)
-
-if(DEFINED EIGEN_CMAKE_ARGS)
-  set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} ${EIGEN_CMAKE_ARGS}")
-endif(DEFINED EIGEN_CMAKE_ARGS)

Index: 3rd_party/eigen/test/eigen2support.cpp
==================================================================
--- 3rd_party/eigen/test/eigen2support.cpp
+++ 3rd_party/eigen/test/eigen2support.cpp
@@ -6,11 +6,10 @@
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #define EIGEN2_SUPPORT
-#define EIGEN_NO_EIGEN2_DEPRECATED_WARNING
 
 #include "main.h"
 
 template<typename MatrixType> void eigen2support(const MatrixType& m)
 {

Index: 3rd_party/eigen/test/eigensolver_complex.cpp
==================================================================
--- 3rd_party/eigen/test/eigensolver_complex.cpp
+++ 3rd_party/eigen/test/eigensolver_complex.cpp
@@ -11,24 +11,63 @@
 #include "main.h"
 #include <limits>
 #include <Eigen/Eigenvalues>
 #include <Eigen/LU>
 
-/* Check that two column vectors are approximately equal upto permutations,
-   by checking that the k-th power sums are equal for k = 1, ..., vec1.rows() */
+template<typename MatrixType> bool find_pivot(typename MatrixType::Scalar tol, MatrixType &diffs, Index col=0)
+{
+  bool match = diffs.diagonal().sum() <= tol;
+  if(match || col==diffs.cols())
+  {
+    return match;
+  }
+  else
+  {
+    Index n = diffs.cols();
+    std::vector<std::pair<Index,Index> > transpositions;
+    for(Index i=col; i<n; ++i)
+    {
+      Index best_index(0);
+      if(diffs.col(col).segment(col,n-i).minCoeff(&best_index) > tol)
+        break;
+      
+      best_index += col;
+      
+      diffs.row(col).swap(diffs.row(best_index));
+      if(find_pivot(tol,diffs,col+1)) return true;
+      diffs.row(col).swap(diffs.row(best_index));
+      
+      // move current pivot to the end
+      diffs.row(n-(i-col)-1).swap(diffs.row(best_index));
+      transpositions.push_back(std::pair<Index,Index>(n-(i-col)-1,best_index));
+    }
+    // restore
+    for(Index k=transpositions.size()-1; k>=0; --k)
+      diffs.row(transpositions[k].first).swap(diffs.row(transpositions[k].second));
+  }
+  return false;
+}
+
+/* Check that two column vectors are approximately equal upto permutations.
+ * Initially, this method checked that the k-th power sums are equal for all k = 1, ..., vec1.rows(),
+ * however this strategy is numerically inacurate because of numerical cancellation issues.
+ */
 template<typename VectorType>
 void verify_is_approx_upto_permutation(const VectorType& vec1, const VectorType& vec2)
 {
-  typedef typename NumTraits<typename VectorType::Scalar>::Real RealScalar;
+  typedef typename VectorType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
 
   VERIFY(vec1.cols() == 1);
   VERIFY(vec2.cols() == 1);
   VERIFY(vec1.rows() == vec2.rows());
-  for (int k = 1; k <= vec1.rows(); ++k)
-  {
-    VERIFY_IS_APPROX(vec1.array().pow(RealScalar(k)).sum(), vec2.array().pow(RealScalar(k)).sum());
-  }
+  
+  Index n = vec1.rows();
+  RealScalar tol = test_precision<RealScalar>()*test_precision<RealScalar>()*numext::maxi(vec1.squaredNorm(),vec2.squaredNorm());
+  Matrix<RealScalar,Dynamic,Dynamic> diffs = (vec1.rowwise().replicate(n) - vec2.rowwise().replicate(n).transpose()).cwiseAbs2();
+  
+  VERIFY( find_pivot(tol, diffs) );
 }
 
 
 template<typename MatrixType> void eigensolver(const MatrixType& m)
 {
@@ -77,17 +116,32 @@
   VERIFY((eiz.eigenvalues().cwiseEqual(0)).all());
 
   MatrixType id = MatrixType::Identity(rows, cols);
   VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
 
-  if (rows > 1)
+  if (rows > 1 && rows < 20)
   {
     // Test matrix with NaN
     a(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
     ComplexEigenSolver<MatrixType> eiNaN(a);
     VERIFY_IS_EQUAL(eiNaN.info(), NoConvergence);
   }
+
+  // regression test for bug 1098
+  {
+    ComplexEigenSolver<MatrixType> eig(a.adjoint() * a);
+    eig.compute(a.adjoint() * a);
+  }
+
+  // regression test for bug 478
+  {
+    a.setZero();
+    ComplexEigenSolver<MatrixType> ei3(a);
+    VERIFY_IS_EQUAL(ei3.info(), Success);
+    VERIFY_IS_MUCH_SMALLER_THAN(ei3.eigenvalues().norm(),RealScalar(1));
+    VERIFY((ei3.eigenvectors().transpose()*ei3.eigenvectors().transpose()).eval().isIdentity());
+  }
 }
 
 template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m)
 {
   ComplexEigenSolver<MatrixType> eig;
@@ -106,10 +160,11 @@
     CALL_SUBTEST_1( eigensolver(Matrix4cf()) );
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
     CALL_SUBTEST_2( eigensolver(MatrixXcd(s,s)) );
     CALL_SUBTEST_3( eigensolver(Matrix<std::complex<float>, 1, 1>()) );
     CALL_SUBTEST_4( eigensolver(Matrix3f()) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
   }
   CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4cf()) );
   s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
   CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXcd(s,s)) );
   CALL_SUBTEST_3( eigensolver_verify_assert(Matrix<std::complex<float>, 1, 1>()) );

Index: 3rd_party/eigen/test/eigensolver_generalized_real.cpp
==================================================================
--- 3rd_party/eigen/test/eigensolver_generalized_real.cpp
+++ 3rd_party/eigen/test/eigensolver_generalized_real.cpp
@@ -1,17 +1,19 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2012-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#define EIGEN_RUNTIME_NO_MALLOC
 #include "main.h"
 #include <limits>
 #include <Eigen/Eigenvalues>
+#include <Eigen/LU>
 
 template<typename MatrixType> void generalized_eigensolver_real(const MatrixType& m)
 {
   typedef typename MatrixType::Index Index;
   /* this test covers the following files:
@@ -19,10 +21,11 @@
   */
   Index rows = m.rows();
   Index cols = m.cols();
 
   typedef typename MatrixType::Scalar Scalar;
+  typedef std::complex<Scalar> ComplexScalar;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
 
   MatrixType a = MatrixType::Random(rows,cols);
   MatrixType b = MatrixType::Random(rows,cols);
   MatrixType a1 = MatrixType::Random(rows,cols);
@@ -29,18 +32,53 @@
   MatrixType b1 = MatrixType::Random(rows,cols);
   MatrixType spdA =  a.adjoint() * a + a1.adjoint() * a1;
   MatrixType spdB =  b.adjoint() * b + b1.adjoint() * b1;
 
   // lets compare to GeneralizedSelfAdjointEigenSolver
-  GeneralizedSelfAdjointEigenSolver<MatrixType> symmEig(spdA, spdB);
-  GeneralizedEigenSolver<MatrixType> eig(spdA, spdB);
-
-  VERIFY_IS_EQUAL(eig.eigenvalues().imag().cwiseAbs().maxCoeff(), 0);
-
-  VectorType realEigenvalues = eig.eigenvalues().real();
-  std::sort(realEigenvalues.data(), realEigenvalues.data()+realEigenvalues.size());
-  VERIFY_IS_APPROX(realEigenvalues, symmEig.eigenvalues());
+  {
+    GeneralizedSelfAdjointEigenSolver<MatrixType> symmEig(spdA, spdB);
+    GeneralizedEigenSolver<MatrixType> eig(spdA, spdB);
+
+    VERIFY_IS_EQUAL(eig.eigenvalues().imag().cwiseAbs().maxCoeff(), 0);
+
+    VectorType realEigenvalues = eig.eigenvalues().real();
+    std::sort(realEigenvalues.data(), realEigenvalues.data()+realEigenvalues.size());
+    VERIFY_IS_APPROX(realEigenvalues, symmEig.eigenvalues());
+
+    // check eigenvectors
+    typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType D = eig.eigenvalues().asDiagonal();
+    typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType V = eig.eigenvectors();
+    VERIFY_IS_APPROX(spdA*V, spdB*V*D);
+  }
+
+  // non symmetric case:
+  {
+    GeneralizedEigenSolver<MatrixType> eig(rows);
+    // TODO enable full-prealocation of required memory, this probably requires an in-place mode for HessenbergDecomposition
+    //Eigen::internal::set_is_malloc_allowed(false);
+    eig.compute(a,b);
+    //Eigen::internal::set_is_malloc_allowed(true);
+    for(Index k=0; k<cols; ++k)
+    {
+      Matrix<ComplexScalar,Dynamic,Dynamic> tmp = (eig.betas()(k)*a).template cast<ComplexScalar>() - eig.alphas()(k)*b;
+      if(tmp.size()>1 && tmp.norm()>(std::numeric_limits<Scalar>::min)())
+        tmp /= tmp.norm();
+      VERIFY_IS_MUCH_SMALLER_THAN( std::abs(tmp.determinant()), Scalar(1) );
+    }
+    // check eigenvectors
+    typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType D = eig.eigenvalues().asDiagonal();
+    typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType V = eig.eigenvectors();
+    VERIFY_IS_APPROX(a*V, b*V*D);
+  }
+
+  // regression test for bug 1098
+  {
+    GeneralizedSelfAdjointEigenSolver<MatrixType> eig1(a.adjoint() * a,b.adjoint() * b);
+    eig1.compute(a.adjoint() * a,b.adjoint() * b);
+    GeneralizedEigenSolver<MatrixType> eig2(a.adjoint() * a,b.adjoint() * b);
+    eig2.compute(a.adjoint() * a,b.adjoint() * b);
+  }
 }
 
 void test_eigensolver_generalized_real()
 {
   for(int i = 0; i < g_repeat; i++) {
@@ -47,13 +85,13 @@
     int s = 0;
     CALL_SUBTEST_1( generalized_eigensolver_real(Matrix4f()) );
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
     CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(s,s)) );
 
-    // some trivial but implementation-wise tricky cases
+    // some trivial but implementation-wise special cases
     CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(1,1)) );
     CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(2,2)) );
     CALL_SUBTEST_3( generalized_eigensolver_real(Matrix<double,1,1>()) );
     CALL_SUBTEST_4( generalized_eigensolver_real(Matrix2d()) );
     TEST_SET_BUT_UNUSED_VARIABLE(s)
   }
 }

Index: 3rd_party/eigen/test/eigensolver_generic.cpp
==================================================================
--- 3rd_party/eigen/test/eigensolver_generic.cpp
+++ 3rd_party/eigen/test/eigensolver_generic.cpp
@@ -61,17 +61,32 @@
   VERIFY_IS_APPROX(ei1.pseudoEigenvalueMatrix(), eiNoEivecs.pseudoEigenvalueMatrix());
 
   MatrixType id = MatrixType::Identity(rows, cols);
   VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
 
-  if (rows > 2)
+  if (rows > 2 && rows < 20)
   {
     // Test matrix with NaN
     a(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
     EigenSolver<MatrixType> eiNaN(a);
     VERIFY_IS_EQUAL(eiNaN.info(), NoConvergence);
   }
+
+  // regression test for bug 1098
+  {
+    EigenSolver<MatrixType> eig(a.adjoint() * a);
+    eig.compute(a.adjoint() * a);
+  }
+
+  // regression test for bug 478
+  {
+    a.setZero();
+    EigenSolver<MatrixType> ei3(a);
+    VERIFY_IS_EQUAL(ei3.info(), Success);
+    VERIFY_IS_MUCH_SMALLER_THAN(ei3.eigenvalues().norm(),RealScalar(1));
+    VERIFY((ei3.eigenvectors().transpose()*ei3.eigenvectors().transpose()).eval().isIdentity());
+  }
 }
 
 template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m)
 {
   EigenSolver<MatrixType> eig;
@@ -91,10 +106,11 @@
   int s = 0;
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( eigensolver(Matrix4f()) );
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
     CALL_SUBTEST_2( eigensolver(MatrixXd(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
 
     // some trivial but implementation-wise tricky cases
     CALL_SUBTEST_2( eigensolver(MatrixXd(1,1)) );
     CALL_SUBTEST_2( eigensolver(MatrixXd(2,2)) );
     CALL_SUBTEST_3( eigensolver(Matrix<double,1,1>()) );
@@ -112,14 +128,39 @@
 
   // regression test for bug 410
   CALL_SUBTEST_2(
   {
      MatrixXd A(1,1);
-     A(0,0) = std::sqrt(-1.);
+     A(0,0) = std::sqrt(-1.); // is Not-a-Number
      Eigen::EigenSolver<MatrixXd> solver(A);
-     MatrixXd V(1, 1);
-     V(0,0) = solver.eigenvectors()(0,0).real();
+     VERIFY_IS_EQUAL(solver.info(), NumericalIssue);
   }
   );
+  
+#ifdef EIGEN_TEST_PART_2
+  {
+    // regression test for bug 793
+    MatrixXd a(3,3);
+    a << 0,  0,  1,
+        1,  1, 1,
+        1, 1e+200,  1;
+    Eigen::EigenSolver<MatrixXd> eig(a);
+    double scale = 1e-200; // scale to avoid overflow during the comparisons
+    VERIFY_IS_APPROX(a * eig.pseudoEigenvectors()*scale, eig.pseudoEigenvectors() * eig.pseudoEigenvalueMatrix()*scale);
+    VERIFY_IS_APPROX(a * eig.eigenvectors()*scale, eig.eigenvectors() * eig.eigenvalues().asDiagonal()*scale);
+  }
+  {
+    // check a case where all eigenvalues are null.
+    MatrixXd a(2,2);
+    a << 1,  1,
+        -1, -1;
+    Eigen::EigenSolver<MatrixXd> eig(a);
+    VERIFY_IS_APPROX(eig.pseudoEigenvectors().squaredNorm(), 2.);
+    VERIFY_IS_APPROX((a * eig.pseudoEigenvectors()).norm()+1., 1.);
+    VERIFY_IS_APPROX((eig.pseudoEigenvectors() * eig.pseudoEigenvalueMatrix()).norm()+1., 1.);
+    VERIFY_IS_APPROX((a * eig.eigenvectors()).norm()+1., 1.);
+    VERIFY_IS_APPROX((eig.eigenvectors() * eig.eigenvalues().asDiagonal()).norm()+1., 1.);
+  }
+#endif
   
   TEST_SET_BUT_UNUSED_VARIABLE(s)
 }

Index: 3rd_party/eigen/test/eigensolver_selfadjoint.cpp
==================================================================
--- 3rd_party/eigen/test/eigensolver_selfadjoint.cpp
+++ 3rd_party/eigen/test/eigensolver_selfadjoint.cpp
@@ -7,12 +7,66 @@
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
+#include "svd_fill.h"
 #include <limits>
 #include <Eigen/Eigenvalues>
+#include <Eigen/SparseCore>
+
+
+template<typename MatrixType> void selfadjointeigensolver_essential_check(const MatrixType& m)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  RealScalar eival_eps = numext::mini<RealScalar>(test_precision<RealScalar>(),  NumTraits<Scalar>::dummy_precision()*20000);
+  
+  SelfAdjointEigenSolver<MatrixType> eiSymm(m);
+  VERIFY_IS_EQUAL(eiSymm.info(), Success);
+
+  RealScalar scaling = m.cwiseAbs().maxCoeff();
+
+  if(scaling<(std::numeric_limits<RealScalar>::min)())
+  {
+    VERIFY(eiSymm.eigenvalues().cwiseAbs().maxCoeff() <= (std::numeric_limits<RealScalar>::min)());
+  }
+  else
+  {
+    VERIFY_IS_APPROX((m.template selfadjointView<Lower>() * eiSymm.eigenvectors())/scaling,
+                     (eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal())/scaling);
+  }
+  VERIFY_IS_APPROX(m.template selfadjointView<Lower>().eigenvalues(), eiSymm.eigenvalues());
+  VERIFY_IS_UNITARY(eiSymm.eigenvectors());
+
+  if(m.cols()<=4)
+  {
+    SelfAdjointEigenSolver<MatrixType> eiDirect;
+    eiDirect.computeDirect(m);  
+    VERIFY_IS_EQUAL(eiDirect.info(), Success);
+    if(! eiSymm.eigenvalues().isApprox(eiDirect.eigenvalues(), eival_eps) )
+    {
+      std::cerr << "reference eigenvalues: " << eiSymm.eigenvalues().transpose() << "\n"
+                << "obtained eigenvalues:  " << eiDirect.eigenvalues().transpose() << "\n"
+                << "diff:                  " << (eiSymm.eigenvalues()-eiDirect.eigenvalues()).transpose() << "\n"
+                << "error (eps):           " << (eiSymm.eigenvalues()-eiDirect.eigenvalues()).norm() / eiSymm.eigenvalues().norm() << "  (" << eival_eps << ")\n";
+    }
+    if(scaling<(std::numeric_limits<RealScalar>::min)())
+    {
+      VERIFY(eiDirect.eigenvalues().cwiseAbs().maxCoeff() <= (std::numeric_limits<RealScalar>::min)());
+    }
+    else
+    {
+      VERIFY_IS_APPROX(eiSymm.eigenvalues()/scaling, eiDirect.eigenvalues()/scaling);
+      VERIFY_IS_APPROX((m.template selfadjointView<Lower>() * eiDirect.eigenvectors())/scaling,
+                       (eiDirect.eigenvectors() * eiDirect.eigenvalues().asDiagonal())/scaling);
+      VERIFY_IS_APPROX(m.template selfadjointView<Lower>().eigenvalues()/scaling, eiDirect.eigenvalues()/scaling);
+    }
+
+    VERIFY_IS_UNITARY(eiDirect.eigenvectors());
+  }
+}
 
 template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
 {
   typedef typename MatrixType::Index Index;
   /* this test covers the following files:
@@ -29,45 +83,26 @@
   MatrixType a = MatrixType::Random(rows,cols);
   MatrixType a1 = MatrixType::Random(rows,cols);
   MatrixType symmA =  a.adjoint() * a + a1.adjoint() * a1;
   MatrixType symmC = symmA;
   
-  // randomly nullify some rows/columns
-  {
-    Index count = 1;//internal::random<Index>(-cols,cols);
-    for(Index k=0; k<count; ++k)
-    {
-      Index i = internal::random<Index>(0,cols-1);
-      symmA.row(i).setZero();
-      symmA.col(i).setZero();
-    }
-  }
-  
+  svd_fill_random(symmA,Symmetric);
+
   symmA.template triangularView<StrictlyUpper>().setZero();
   symmC.template triangularView<StrictlyUpper>().setZero();
 
   MatrixType b = MatrixType::Random(rows,cols);
   MatrixType b1 = MatrixType::Random(rows,cols);
   MatrixType symmB = b.adjoint() * b + b1.adjoint() * b1;
   symmB.template triangularView<StrictlyUpper>().setZero();
+  
+  CALL_SUBTEST( selfadjointeigensolver_essential_check(symmA) );
 
   SelfAdjointEigenSolver<MatrixType> eiSymm(symmA);
-  SelfAdjointEigenSolver<MatrixType> eiDirect;
-  eiDirect.computeDirect(symmA);
   // generalized eigen pb
   GeneralizedSelfAdjointEigenSolver<MatrixType> eiSymmGen(symmC, symmB);
 
-  VERIFY_IS_EQUAL(eiSymm.info(), Success);
-  VERIFY((symmA.template selfadjointView<Lower>() * eiSymm.eigenvectors()).isApprox(
-          eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal(), largerEps));
-  VERIFY_IS_APPROX(symmA.template selfadjointView<Lower>().eigenvalues(), eiSymm.eigenvalues());
-  
-  VERIFY_IS_EQUAL(eiDirect.info(), Success);
-  VERIFY((symmA.template selfadjointView<Lower>() * eiDirect.eigenvectors()).isApprox(
-          eiDirect.eigenvectors() * eiDirect.eigenvalues().asDiagonal(), largerEps));
-  VERIFY_IS_APPROX(symmA.template selfadjointView<Lower>().eigenvalues(), eiDirect.eigenvalues());
-
   SelfAdjointEigenSolver<MatrixType> eiSymmNoEivecs(symmA, false);
   VERIFY_IS_EQUAL(eiSymmNoEivecs.info(), Success);
   VERIFY_IS_APPROX(eiSymm.eigenvalues(), eiSymmNoEivecs.eigenvalues());
   
   // generalized eigen problem Ax = lBx
@@ -109,52 +144,131 @@
   VERIFY_RAISES_ASSERT(eiSymmUninitialized.operatorSqrt());
   VERIFY_RAISES_ASSERT(eiSymmUninitialized.operatorInverseSqrt());
 
   // test Tridiagonalization's methods
   Tridiagonalization<MatrixType> tridiag(symmC);
-  // FIXME tridiag.matrixQ().adjoint() does not work
+  VERIFY_IS_APPROX(tridiag.diagonal(), tridiag.matrixT().diagonal());
+  VERIFY_IS_APPROX(tridiag.subDiagonal(), tridiag.matrixT().template diagonal<-1>());
+  Matrix<RealScalar,Dynamic,Dynamic> T = tridiag.matrixT();
+  if(rows>1 && cols>1) {
+    // FIXME check that upper and lower part are 0:
+    //VERIFY(T.topRightCorner(rows-2, cols-2).template triangularView<Upper>().isZero());
+  }
+  VERIFY_IS_APPROX(tridiag.diagonal(), T.diagonal());
+  VERIFY_IS_APPROX(tridiag.subDiagonal(), T.template diagonal<1>());
   VERIFY_IS_APPROX(MatrixType(symmC.template selfadjointView<Lower>()), tridiag.matrixQ() * tridiag.matrixT().eval() * MatrixType(tridiag.matrixQ()).adjoint());
+  VERIFY_IS_APPROX(MatrixType(symmC.template selfadjointView<Lower>()), tridiag.matrixQ() * tridiag.matrixT() * tridiag.matrixQ().adjoint());
   
-  if (rows > 1)
+  // Test computation of eigenvalues from tridiagonal matrix
+  if(rows > 1)
+  {
+    SelfAdjointEigenSolver<MatrixType> eiSymmTridiag;
+    eiSymmTridiag.computeFromTridiagonal(tridiag.matrixT().diagonal(), tridiag.matrixT().diagonal(-1), ComputeEigenvectors);
+    VERIFY_IS_APPROX(eiSymm.eigenvalues(), eiSymmTridiag.eigenvalues());
+    VERIFY_IS_APPROX(tridiag.matrixT(), eiSymmTridiag.eigenvectors().real() * eiSymmTridiag.eigenvalues().asDiagonal() * eiSymmTridiag.eigenvectors().real().transpose());
+  }
+
+  if (rows > 1 && rows < 20)
   {
     // Test matrix with NaN
     symmC(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
     SelfAdjointEigenSolver<MatrixType> eiSymmNaN(symmC);
     VERIFY_IS_EQUAL(eiSymmNaN.info(), NoConvergence);
   }
+
+  // regression test for bug 1098
+  {
+    SelfAdjointEigenSolver<MatrixType> eig(a.adjoint() * a);
+    eig.compute(a.adjoint() * a);
+  }
+
+  // regression test for bug 478
+  {
+    a.setZero();
+    SelfAdjointEigenSolver<MatrixType> ei3(a);
+    VERIFY_IS_EQUAL(ei3.info(), Success);
+    VERIFY_IS_MUCH_SMALLER_THAN(ei3.eigenvalues().norm(),RealScalar(1));
+    VERIFY((ei3.eigenvectors().transpose()*ei3.eigenvectors().transpose()).eval().isIdentity());
+  }
+}
+
+template<int>
+void bug_854()
+{
+  Matrix3d m;
+  m << 850.961, 51.966, 0,
+       51.966, 254.841, 0,
+            0,       0, 0;
+  selfadjointeigensolver_essential_check(m);
+}
+
+template<int>
+void bug_1014()
+{
+  Matrix3d m;
+  m <<        0.11111111111111114658, 0, 0,
+       0,     0.11111111111111109107, 0,
+       0, 0,  0.11111111111111107719;
+  selfadjointeigensolver_essential_check(m);
+}
+
+template<int>
+void bug_1225()
+{
+  Matrix3d m1, m2;
+  m1.setRandom();
+  m1 = m1*m1.transpose();
+  m2 = m1.triangularView<Upper>();
+  SelfAdjointEigenSolver<Matrix3d> eig1(m1);
+  SelfAdjointEigenSolver<Matrix3d> eig2(m2.selfadjointView<Upper>());
+  VERIFY_IS_APPROX(eig1.eigenvalues(), eig2.eigenvalues());
+}
+
+template<int>
+void bug_1204()
+{
+  SparseMatrix<double> A(2,2);
+  A.setIdentity();
+  SelfAdjointEigenSolver<Eigen::SparseMatrix<double> > eig(A);
 }
 
 void test_eigensolver_selfadjoint()
 {
   int s = 0;
   for(int i = 0; i < g_repeat; i++) {
+    // trivial test for 1x1 matrices:
+    CALL_SUBTEST_1( selfadjointeigensolver(Matrix<float, 1, 1>()));
+    CALL_SUBTEST_1( selfadjointeigensolver(Matrix<double, 1, 1>()));
     // very important to test 3x3 and 2x2 matrices since we provide special paths for them
-    CALL_SUBTEST_1( selfadjointeigensolver(Matrix2f()) );
-    CALL_SUBTEST_1( selfadjointeigensolver(Matrix2d()) );
-    CALL_SUBTEST_1( selfadjointeigensolver(Matrix3f()) );
-    CALL_SUBTEST_1( selfadjointeigensolver(Matrix3d()) );
+    CALL_SUBTEST_12( selfadjointeigensolver(Matrix2f()) );
+    CALL_SUBTEST_12( selfadjointeigensolver(Matrix2d()) );
+    CALL_SUBTEST_13( selfadjointeigensolver(Matrix3f()) );
+    CALL_SUBTEST_13( selfadjointeigensolver(Matrix3d()) );
     CALL_SUBTEST_2( selfadjointeigensolver(Matrix4d()) );
+    
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
     CALL_SUBTEST_3( selfadjointeigensolver(MatrixXf(s,s)) );
-    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
     CALL_SUBTEST_4( selfadjointeigensolver(MatrixXd(s,s)) );
-    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
     CALL_SUBTEST_5( selfadjointeigensolver(MatrixXcd(s,s)) );
-    
-    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
     CALL_SUBTEST_9( selfadjointeigensolver(Matrix<std::complex<double>,Dynamic,Dynamic,RowMajor>(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
 
     // some trivial but implementation-wise tricky cases
     CALL_SUBTEST_4( selfadjointeigensolver(MatrixXd(1,1)) );
     CALL_SUBTEST_4( selfadjointeigensolver(MatrixXd(2,2)) );
     CALL_SUBTEST_6( selfadjointeigensolver(Matrix<double,1,1>()) );
     CALL_SUBTEST_7( selfadjointeigensolver(Matrix<double,2,2>()) );
   }
+  
+  CALL_SUBTEST_13( bug_854<0>() );
+  CALL_SUBTEST_13( bug_1014<0>() );
+  CALL_SUBTEST_13( bug_1204<0>() );
+  CALL_SUBTEST_13( bug_1225<0>() );
 
   // Test problem size constructors
   s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
   CALL_SUBTEST_8(SelfAdjointEigenSolver<MatrixXf> tmp1(s));
   CALL_SUBTEST_8(Tridiagonalization<MatrixXf> tmp2(s));
   
   TEST_SET_BUT_UNUSED_VARIABLE(s)
 }
 

ADDED   3rd_party/eigen/test/evaluator_common.h
Index: 3rd_party/eigen/test/evaluator_common.h
==================================================================
--- 3rd_party/eigen/test/evaluator_common.h
+++ 3rd_party/eigen/test/evaluator_common.h

ADDED   3rd_party/eigen/test/evaluators.cpp
Index: 3rd_party/eigen/test/evaluators.cpp
==================================================================
--- 3rd_party/eigen/test/evaluators.cpp
+++ 3rd_party/eigen/test/evaluators.cpp
@@ -0,0 +1,499 @@
+
+#include "main.h"
+
+namespace Eigen {
+
+  template<typename Lhs,typename Rhs>
+  const Product<Lhs,Rhs>
+  prod(const Lhs& lhs, const Rhs& rhs)
+  {
+    return Product<Lhs,Rhs>(lhs,rhs);
+  }
+
+  template<typename Lhs,typename Rhs>
+  const Product<Lhs,Rhs,LazyProduct>
+  lazyprod(const Lhs& lhs, const Rhs& rhs)
+  {
+    return Product<Lhs,Rhs,LazyProduct>(lhs,rhs);
+  }
+  
+  template<typename DstXprType, typename SrcXprType>
+  EIGEN_STRONG_INLINE
+  DstXprType& copy_using_evaluator(const EigenBase<DstXprType> &dst, const SrcXprType &src)
+  {
+    call_assignment(dst.const_cast_derived(), src.derived(), internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>());
+    return dst.const_cast_derived();
+  }
+  
+  template<typename DstXprType, template <typename> class StorageBase, typename SrcXprType>
+  EIGEN_STRONG_INLINE
+  const DstXprType& copy_using_evaluator(const NoAlias<DstXprType, StorageBase>& dst, const SrcXprType &src)
+  {
+    call_assignment(dst, src.derived(), internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>());
+    return dst.expression();
+  }
+  
+  template<typename DstXprType, typename SrcXprType>
+  EIGEN_STRONG_INLINE
+  DstXprType& copy_using_evaluator(const PlainObjectBase<DstXprType> &dst, const SrcXprType &src)
+  {
+    #ifdef EIGEN_NO_AUTOMATIC_RESIZING
+    eigen_assert((dst.size()==0 || (IsVectorAtCompileTime ? (dst.size() == src.size())
+                                                          : (dst.rows() == src.rows() && dst.cols() == src.cols())))
+                && "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined");
+  #else
+    dst.const_cast_derived().resizeLike(src.derived());
+  #endif
+    
+    call_assignment(dst.const_cast_derived(), src.derived(), internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>());
+    return dst.const_cast_derived();
+  }
+
+  template<typename DstXprType, typename SrcXprType>
+  void add_assign_using_evaluator(const DstXprType& dst, const SrcXprType& src)
+  {
+    typedef typename DstXprType::Scalar Scalar;
+    call_assignment(const_cast<DstXprType&>(dst), src.derived(), internal::add_assign_op<Scalar,typename SrcXprType::Scalar>());
+  }
+
+  template<typename DstXprType, typename SrcXprType>
+  void subtract_assign_using_evaluator(const DstXprType& dst, const SrcXprType& src)
+  {
+    typedef typename DstXprType::Scalar Scalar;
+    call_assignment(const_cast<DstXprType&>(dst), src.derived(), internal::sub_assign_op<Scalar,typename SrcXprType::Scalar>());
+  }
+
+  template<typename DstXprType, typename SrcXprType>
+  void multiply_assign_using_evaluator(const DstXprType& dst, const SrcXprType& src)
+  {
+    typedef typename DstXprType::Scalar Scalar;
+    call_assignment(dst.const_cast_derived(), src.derived(), internal::mul_assign_op<Scalar,typename SrcXprType::Scalar>());
+  }
+
+  template<typename DstXprType, typename SrcXprType>
+  void divide_assign_using_evaluator(const DstXprType& dst, const SrcXprType& src)
+  {
+    typedef typename DstXprType::Scalar Scalar;
+    call_assignment(dst.const_cast_derived(), src.derived(), internal::div_assign_op<Scalar,typename SrcXprType::Scalar>());
+  }
+  
+  template<typename DstXprType, typename SrcXprType>
+  void swap_using_evaluator(const DstXprType& dst, const SrcXprType& src)
+  {
+    typedef typename DstXprType::Scalar Scalar;
+    call_assignment(dst.const_cast_derived(), src.const_cast_derived(), internal::swap_assign_op<Scalar>());
+  }
+
+  namespace internal {
+    template<typename Dst, template <typename> class StorageBase, typename Src, typename Func>
+    EIGEN_DEVICE_FUNC void call_assignment(const NoAlias<Dst,StorageBase>& dst, const Src& src, const Func& func)
+    {
+      call_assignment_no_alias(dst.expression(), src, func);
+    }
+  }
+  
+}
+
+template<typename XprType> long get_cost(const XprType& ) { return Eigen::internal::evaluator<XprType>::CoeffReadCost; }
+
+using namespace std;
+
+#define VERIFY_IS_APPROX_EVALUATOR(DEST,EXPR) VERIFY_IS_APPROX(copy_using_evaluator(DEST,(EXPR)), (EXPR).eval());
+#define VERIFY_IS_APPROX_EVALUATOR2(DEST,EXPR,REF) VERIFY_IS_APPROX(copy_using_evaluator(DEST,(EXPR)), (REF).eval());
+
+void test_evaluators()
+{
+  // Testing Matrix evaluator and Transpose
+  Vector2d v = Vector2d::Random();
+  const Vector2d v_const(v);
+  Vector2d v2;
+  RowVector2d w;
+
+  VERIFY_IS_APPROX_EVALUATOR(v2, v);
+  VERIFY_IS_APPROX_EVALUATOR(v2, v_const);
+
+  // Testing Transpose
+  VERIFY_IS_APPROX_EVALUATOR(w, v.transpose()); // Transpose as rvalue
+  VERIFY_IS_APPROX_EVALUATOR(w, v_const.transpose());
+
+  copy_using_evaluator(w.transpose(), v); // Transpose as lvalue
+  VERIFY_IS_APPROX(w,v.transpose().eval());
+
+  copy_using_evaluator(w.transpose(), v_const);
+  VERIFY_IS_APPROX(w,v_const.transpose().eval());
+
+  // Testing Array evaluator
+  {
+    ArrayXXf a(2,3);
+    ArrayXXf b(3,2);
+    a << 1,2,3, 4,5,6;
+    const ArrayXXf a_const(a);
+
+    VERIFY_IS_APPROX_EVALUATOR(b, a.transpose());
+
+    VERIFY_IS_APPROX_EVALUATOR(b, a_const.transpose());
+
+    // Testing CwiseNullaryOp evaluator
+    copy_using_evaluator(w, RowVector2d::Random());
+    VERIFY((w.array() >= -1).all() && (w.array() <= 1).all()); // not easy to test ...
+
+    VERIFY_IS_APPROX_EVALUATOR(w, RowVector2d::Zero());
+
+    VERIFY_IS_APPROX_EVALUATOR(w, RowVector2d::Constant(3));
+    
+    // mix CwiseNullaryOp and transpose
+    VERIFY_IS_APPROX_EVALUATOR(w, Vector2d::Zero().transpose());
+  }
+
+  {
+    // test product expressions
+    int s = internal::random<int>(1,100);
+    MatrixXf a(s,s), b(s,s), c(s,s), d(s,s);
+    a.setRandom();
+    b.setRandom();
+    c.setRandom();
+    d.setRandom();
+    VERIFY_IS_APPROX_EVALUATOR(d, (a + b));
+    VERIFY_IS_APPROX_EVALUATOR(d, (a + b).transpose());
+    VERIFY_IS_APPROX_EVALUATOR2(d, prod(a,b), a*b);
+    VERIFY_IS_APPROX_EVALUATOR2(d.noalias(), prod(a,b), a*b);
+    VERIFY_IS_APPROX_EVALUATOR2(d, prod(a,b) + c, a*b + c);
+    VERIFY_IS_APPROX_EVALUATOR2(d, s * prod(a,b), s * a*b);
+    VERIFY_IS_APPROX_EVALUATOR2(d, prod(a,b).transpose(), (a*b).transpose());
+    VERIFY_IS_APPROX_EVALUATOR2(d, prod(a,b) + prod(b,c), a*b + b*c);
+
+    // check that prod works even with aliasing present
+    c = a*a;
+    copy_using_evaluator(a, prod(a,a));
+    VERIFY_IS_APPROX(a,c);
+
+    // check compound assignment of products
+    d = c;
+    add_assign_using_evaluator(c.noalias(), prod(a,b));
+    d.noalias() += a*b;
+    VERIFY_IS_APPROX(c, d);
+
+    d = c;
+    subtract_assign_using_evaluator(c.noalias(), prod(a,b));
+    d.noalias() -= a*b;
+    VERIFY_IS_APPROX(c, d);
+  }
+
+  {
+    // test product with all possible sizes
+    int s = internal::random<int>(1,100);
+    Matrix<float,      1,      1> m11, res11;  m11.setRandom(1,1);
+    Matrix<float,      1,      4> m14, res14;  m14.setRandom(1,4);
+    Matrix<float,      1,Dynamic> m1X, res1X;  m1X.setRandom(1,s);
+    Matrix<float,      4,      1> m41, res41;  m41.setRandom(4,1);
+    Matrix<float,      4,      4> m44, res44;  m44.setRandom(4,4);
+    Matrix<float,      4,Dynamic> m4X, res4X;  m4X.setRandom(4,s);
+    Matrix<float,Dynamic,      1> mX1, resX1;  mX1.setRandom(s,1);
+    Matrix<float,Dynamic,      4> mX4, resX4;  mX4.setRandom(s,4);
+    Matrix<float,Dynamic,Dynamic> mXX, resXX;  mXX.setRandom(s,s);
+
+    VERIFY_IS_APPROX_EVALUATOR2(res11, prod(m11,m11), m11*m11);
+    VERIFY_IS_APPROX_EVALUATOR2(res11, prod(m14,m41), m14*m41);
+    VERIFY_IS_APPROX_EVALUATOR2(res11, prod(m1X,mX1), m1X*mX1);
+    VERIFY_IS_APPROX_EVALUATOR2(res14, prod(m11,m14), m11*m14);
+    VERIFY_IS_APPROX_EVALUATOR2(res14, prod(m14,m44), m14*m44);
+    VERIFY_IS_APPROX_EVALUATOR2(res14, prod(m1X,mX4), m1X*mX4);
+    VERIFY_IS_APPROX_EVALUATOR2(res1X, prod(m11,m1X), m11*m1X);
+    VERIFY_IS_APPROX_EVALUATOR2(res1X, prod(m14,m4X), m14*m4X);
+    VERIFY_IS_APPROX_EVALUATOR2(res1X, prod(m1X,mXX), m1X*mXX);
+    VERIFY_IS_APPROX_EVALUATOR2(res41, prod(m41,m11), m41*m11);
+    VERIFY_IS_APPROX_EVALUATOR2(res41, prod(m44,m41), m44*m41);
+    VERIFY_IS_APPROX_EVALUATOR2(res41, prod(m4X,mX1), m4X*mX1);
+    VERIFY_IS_APPROX_EVALUATOR2(res44, prod(m41,m14), m41*m14);
+    VERIFY_IS_APPROX_EVALUATOR2(res44, prod(m44,m44), m44*m44);
+    VERIFY_IS_APPROX_EVALUATOR2(res44, prod(m4X,mX4), m4X*mX4);
+    VERIFY_IS_APPROX_EVALUATOR2(res4X, prod(m41,m1X), m41*m1X);
+    VERIFY_IS_APPROX_EVALUATOR2(res4X, prod(m44,m4X), m44*m4X);
+    VERIFY_IS_APPROX_EVALUATOR2(res4X, prod(m4X,mXX), m4X*mXX);
+    VERIFY_IS_APPROX_EVALUATOR2(resX1, prod(mX1,m11), mX1*m11);
+    VERIFY_IS_APPROX_EVALUATOR2(resX1, prod(mX4,m41), mX4*m41);
+    VERIFY_IS_APPROX_EVALUATOR2(resX1, prod(mXX,mX1), mXX*mX1);
+    VERIFY_IS_APPROX_EVALUATOR2(resX4, prod(mX1,m14), mX1*m14);
+    VERIFY_IS_APPROX_EVALUATOR2(resX4, prod(mX4,m44), mX4*m44);
+    VERIFY_IS_APPROX_EVALUATOR2(resX4, prod(mXX,mX4), mXX*mX4);
+    VERIFY_IS_APPROX_EVALUATOR2(resXX, prod(mX1,m1X), mX1*m1X);
+    VERIFY_IS_APPROX_EVALUATOR2(resXX, prod(mX4,m4X), mX4*m4X);
+    VERIFY_IS_APPROX_EVALUATOR2(resXX, prod(mXX,mXX), mXX*mXX);
+  }
+
+  {
+    ArrayXXf a(2,3);
+    ArrayXXf b(3,2);
+    a << 1,2,3, 4,5,6;
+    const ArrayXXf a_const(a);
+    
+    // this does not work because Random is eval-before-nested: 
+    // copy_using_evaluator(w, Vector2d::Random().transpose());
+
+    // test CwiseUnaryOp
+    VERIFY_IS_APPROX_EVALUATOR(v2, 3 * v);
+    VERIFY_IS_APPROX_EVALUATOR(w, (3 * v).transpose());
+    VERIFY_IS_APPROX_EVALUATOR(b, (a + 3).transpose());
+    VERIFY_IS_APPROX_EVALUATOR(b, (2 * a_const + 3).transpose());
+
+    // test CwiseBinaryOp
+    VERIFY_IS_APPROX_EVALUATOR(v2, v + Vector2d::Ones());
+    VERIFY_IS_APPROX_EVALUATOR(w, (v + Vector2d::Ones()).transpose().cwiseProduct(RowVector2d::Constant(3)));
+
+    // dynamic matrices and arrays
+    MatrixXd mat1(6,6), mat2(6,6);
+    VERIFY_IS_APPROX_EVALUATOR(mat1, MatrixXd::Identity(6,6));
+    VERIFY_IS_APPROX_EVALUATOR(mat2, mat1);
+    copy_using_evaluator(mat2.transpose(), mat1);
+    VERIFY_IS_APPROX(mat2.transpose(), mat1);
+
+    ArrayXXd arr1(6,6), arr2(6,6);
+    VERIFY_IS_APPROX_EVALUATOR(arr1, ArrayXXd::Constant(6,6, 3.0));
+    VERIFY_IS_APPROX_EVALUATOR(arr2, arr1);
+    
+    // test automatic resizing
+    mat2.resize(3,3);
+    VERIFY_IS_APPROX_EVALUATOR(mat2, mat1);
+    arr2.resize(9,9);
+    VERIFY_IS_APPROX_EVALUATOR(arr2, arr1);
+
+    // test direct traversal
+    Matrix3f m3;
+    Array33f a3;
+    VERIFY_IS_APPROX_EVALUATOR(m3, Matrix3f::Identity());  // matrix, nullary
+    // TODO: find a way to test direct traversal with array
+    VERIFY_IS_APPROX_EVALUATOR(m3.transpose(), Matrix3f::Identity().transpose());  // transpose
+    VERIFY_IS_APPROX_EVALUATOR(m3, 2 * Matrix3f::Identity());  // unary
+    VERIFY_IS_APPROX_EVALUATOR(m3, Matrix3f::Identity() + Matrix3f::Zero());  // binary
+    VERIFY_IS_APPROX_EVALUATOR(m3.block(0,0,2,2), Matrix3f::Identity().block(1,1,2,2));  // block
+
+    // test linear traversal
+    VERIFY_IS_APPROX_EVALUATOR(m3, Matrix3f::Zero());  // matrix, nullary
+    VERIFY_IS_APPROX_EVALUATOR(a3, Array33f::Zero());  // array
+    VERIFY_IS_APPROX_EVALUATOR(m3.transpose(), Matrix3f::Zero().transpose());  // transpose
+    VERIFY_IS_APPROX_EVALUATOR(m3, 2 * Matrix3f::Zero());  // unary
+    VERIFY_IS_APPROX_EVALUATOR(m3, Matrix3f::Zero() + m3);  // binary  
+
+    // test inner vectorization
+    Matrix4f m4, m4src = Matrix4f::Random();
+    Array44f a4, a4src = Matrix4f::Random();
+    VERIFY_IS_APPROX_EVALUATOR(m4, m4src);  // matrix
+    VERIFY_IS_APPROX_EVALUATOR(a4, a4src);  // array
+    VERIFY_IS_APPROX_EVALUATOR(m4.transpose(), m4src.transpose());  // transpose
+    // TODO: find out why Matrix4f::Zero() does not allow inner vectorization
+    VERIFY_IS_APPROX_EVALUATOR(m4, 2 * m4src);  // unary
+    VERIFY_IS_APPROX_EVALUATOR(m4, m4src + m4src);  // binary
+
+    // test linear vectorization
+    MatrixXf mX(6,6), mXsrc = MatrixXf::Random(6,6);
+    ArrayXXf aX(6,6), aXsrc = ArrayXXf::Random(6,6);
+    VERIFY_IS_APPROX_EVALUATOR(mX, mXsrc);  // matrix
+    VERIFY_IS_APPROX_EVALUATOR(aX, aXsrc);  // array
+    VERIFY_IS_APPROX_EVALUATOR(mX.transpose(), mXsrc.transpose());  // transpose
+    VERIFY_IS_APPROX_EVALUATOR(mX, MatrixXf::Zero(6,6));  // nullary
+    VERIFY_IS_APPROX_EVALUATOR(mX, 2 * mXsrc);  // unary
+    VERIFY_IS_APPROX_EVALUATOR(mX, mXsrc + mXsrc);  // binary
+
+    // test blocks and slice vectorization
+    VERIFY_IS_APPROX_EVALUATOR(m4, (mXsrc.block<4,4>(1,0)));
+    VERIFY_IS_APPROX_EVALUATOR(aX, ArrayXXf::Constant(10, 10, 3.0).block(2, 3, 6, 6));
+
+    Matrix4f m4ref = m4;
+    copy_using_evaluator(m4.block(1, 1, 2, 3), m3.bottomRows(2));
+    m4ref.block(1, 1, 2, 3) = m3.bottomRows(2);
+    VERIFY_IS_APPROX(m4, m4ref);
+
+    mX.setIdentity(20,20);
+    MatrixXf mXref = MatrixXf::Identity(20,20);
+    mXsrc = MatrixXf::Random(9,12);
+    copy_using_evaluator(mX.block(4, 4, 9, 12), mXsrc);
+    mXref.block(4, 4, 9, 12) = mXsrc;
+    VERIFY_IS_APPROX(mX, mXref);
+
+    // test Map
+    const float raw[3] = {1,2,3};
+    float buffer[3] = {0,0,0};
+    Vector3f v3;
+    Array3f a3f;
+    VERIFY_IS_APPROX_EVALUATOR(v3, Map<const Vector3f>(raw));
+    VERIFY_IS_APPROX_EVALUATOR(a3f, Map<const Array3f>(raw));
+    Vector3f::Map(buffer) = 2*v3;
+    VERIFY(buffer[0] == 2);
+    VERIFY(buffer[1] == 4);
+    VERIFY(buffer[2] == 6);
+
+    // test CwiseUnaryView
+    mat1.setRandom();
+    mat2.setIdentity();
+    MatrixXcd matXcd(6,6), matXcd_ref(6,6);
+    copy_using_evaluator(matXcd.real(), mat1);
+    copy_using_evaluator(matXcd.imag(), mat2);
+    matXcd_ref.real() = mat1;
+    matXcd_ref.imag() = mat2;
+    VERIFY_IS_APPROX(matXcd, matXcd_ref);
+
+    // test Select
+    VERIFY_IS_APPROX_EVALUATOR(aX, (aXsrc > 0).select(aXsrc, -aXsrc));
+
+    // test Replicate
+    mXsrc = MatrixXf::Random(6, 6);
+    VectorXf vX = VectorXf::Random(6);
+    mX.resize(6, 6);
+    VERIFY_IS_APPROX_EVALUATOR(mX, mXsrc.colwise() + vX);
+    matXcd.resize(12, 12);
+    VERIFY_IS_APPROX_EVALUATOR(matXcd, matXcd_ref.replicate(2,2));
+    VERIFY_IS_APPROX_EVALUATOR(matXcd, (matXcd_ref.replicate<2,2>()));
+
+    // test partial reductions
+    VectorXd vec1(6);
+    VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.rowwise().sum());
+    VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.colwise().sum().transpose());
+
+    // test MatrixWrapper and ArrayWrapper
+    mat1.setRandom(6,6);
+    arr1.setRandom(6,6);
+    VERIFY_IS_APPROX_EVALUATOR(mat2, arr1.matrix());
+    VERIFY_IS_APPROX_EVALUATOR(arr2, mat1.array());
+    VERIFY_IS_APPROX_EVALUATOR(mat2, (arr1 + 2).matrix());
+    VERIFY_IS_APPROX_EVALUATOR(arr2, mat1.array() + 2);
+    mat2.array() = arr1 * arr1;
+    VERIFY_IS_APPROX(mat2, (arr1 * arr1).matrix());
+    arr2.matrix() = MatrixXd::Identity(6,6);
+    VERIFY_IS_APPROX(arr2, MatrixXd::Identity(6,6).array());
+
+    // test Reverse
+    VERIFY_IS_APPROX_EVALUATOR(arr2, arr1.reverse());
+    VERIFY_IS_APPROX_EVALUATOR(arr2, arr1.colwise().reverse());
+    VERIFY_IS_APPROX_EVALUATOR(arr2, arr1.rowwise().reverse());
+    arr2.reverse() = arr1;
+    VERIFY_IS_APPROX(arr2, arr1.reverse());
+    mat2.array() = mat1.array().reverse();
+    VERIFY_IS_APPROX(mat2.array(), mat1.array().reverse());
+
+    // test Diagonal
+    VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal());
+    vec1.resize(5);
+    VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal(1));
+    VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal<-1>());
+    vec1.setRandom();
+
+    mat2 = mat1;
+    copy_using_evaluator(mat1.diagonal(1), vec1);
+    mat2.diagonal(1) = vec1;
+    VERIFY_IS_APPROX(mat1, mat2);
+
+    copy_using_evaluator(mat1.diagonal<-1>(), mat1.diagonal(1));
+    mat2.diagonal<-1>() = mat2.diagonal(1);
+    VERIFY_IS_APPROX(mat1, mat2);
+  }
+  
+  {
+    // test swapping
+    MatrixXd mat1, mat2, mat1ref, mat2ref;
+    mat1ref = mat1 = MatrixXd::Random(6, 6);
+    mat2ref = mat2 = 2 * mat1 + MatrixXd::Identity(6, 6);
+    swap_using_evaluator(mat1, mat2);
+    mat1ref.swap(mat2ref);
+    VERIFY_IS_APPROX(mat1, mat1ref);
+    VERIFY_IS_APPROX(mat2, mat2ref);
+
+    swap_using_evaluator(mat1.block(0, 0, 3, 3), mat2.block(3, 3, 3, 3));
+    mat1ref.block(0, 0, 3, 3).swap(mat2ref.block(3, 3, 3, 3));
+    VERIFY_IS_APPROX(mat1, mat1ref);
+    VERIFY_IS_APPROX(mat2, mat2ref);
+
+    swap_using_evaluator(mat1.row(2), mat2.col(3).transpose());
+    mat1.row(2).swap(mat2.col(3).transpose());
+    VERIFY_IS_APPROX(mat1, mat1ref);
+    VERIFY_IS_APPROX(mat2, mat2ref);
+  }
+
+  {
+    // test compound assignment
+    const Matrix4d mat_const = Matrix4d::Random(); 
+    Matrix4d mat, mat_ref;
+    mat = mat_ref = Matrix4d::Identity();
+    add_assign_using_evaluator(mat, mat_const);
+    mat_ref += mat_const;
+    VERIFY_IS_APPROX(mat, mat_ref);
+
+    subtract_assign_using_evaluator(mat.row(1), 2*mat.row(2));
+    mat_ref.row(1) -= 2*mat_ref.row(2);
+    VERIFY_IS_APPROX(mat, mat_ref);
+
+    const ArrayXXf arr_const = ArrayXXf::Random(5,3); 
+    ArrayXXf arr, arr_ref;
+    arr = arr_ref = ArrayXXf::Constant(5, 3, 0.5);
+    multiply_assign_using_evaluator(arr, arr_const);
+    arr_ref *= arr_const;
+    VERIFY_IS_APPROX(arr, arr_ref);
+
+    divide_assign_using_evaluator(arr.row(1), arr.row(2) + 1);
+    arr_ref.row(1) /= (arr_ref.row(2) + 1);
+    VERIFY_IS_APPROX(arr, arr_ref);
+  }
+  
+  {
+    // test triangular shapes
+    MatrixXd A = MatrixXd::Random(6,6), B(6,6), C(6,6), D(6,6);
+    A.setRandom();B.setRandom();
+    VERIFY_IS_APPROX_EVALUATOR2(B, A.triangularView<Upper>(), MatrixXd(A.triangularView<Upper>()));
+    
+    A.setRandom();B.setRandom();
+    VERIFY_IS_APPROX_EVALUATOR2(B, A.triangularView<UnitLower>(), MatrixXd(A.triangularView<UnitLower>()));
+    
+    A.setRandom();B.setRandom();
+    VERIFY_IS_APPROX_EVALUATOR2(B, A.triangularView<UnitUpper>(), MatrixXd(A.triangularView<UnitUpper>()));
+    
+    A.setRandom();B.setRandom();
+    C = B; C.triangularView<Upper>() = A;
+    copy_using_evaluator(B.triangularView<Upper>(), A);
+    VERIFY(B.isApprox(C) && "copy_using_evaluator(B.triangularView<Upper>(), A)");
+    
+    A.setRandom();B.setRandom();
+    C = B; C.triangularView<Lower>() = A.triangularView<Lower>();
+    copy_using_evaluator(B.triangularView<Lower>(), A.triangularView<Lower>());
+    VERIFY(B.isApprox(C) && "copy_using_evaluator(B.triangularView<Lower>(), A.triangularView<Lower>())");
+    
+    
+    A.setRandom();B.setRandom();
+    C = B; C.triangularView<Lower>() = A.triangularView<Upper>().transpose();
+    copy_using_evaluator(B.triangularView<Lower>(), A.triangularView<Upper>().transpose());
+    VERIFY(B.isApprox(C) && "copy_using_evaluator(B.triangularView<Lower>(), A.triangularView<Lower>().transpose())");
+    
+    
+    A.setRandom();B.setRandom(); C = B; D = A;
+    C.triangularView<Upper>().swap(D.triangularView<Upper>());
+    swap_using_evaluator(B.triangularView<Upper>(), A.triangularView<Upper>());
+    VERIFY(B.isApprox(C) && "swap_using_evaluator(B.triangularView<Upper>(), A.triangularView<Upper>())");
+    
+    
+    VERIFY_IS_APPROX_EVALUATOR2(B, prod(A.triangularView<Upper>(),A), MatrixXd(A.triangularView<Upper>()*A));
+    
+    VERIFY_IS_APPROX_EVALUATOR2(B, prod(A.selfadjointView<Upper>(),A), MatrixXd(A.selfadjointView<Upper>()*A));
+  }
+
+  {
+    // test diagonal shapes
+    VectorXd d = VectorXd::Random(6);
+    MatrixXd A = MatrixXd::Random(6,6), B(6,6);
+    A.setRandom();B.setRandom();
+    
+    VERIFY_IS_APPROX_EVALUATOR2(B, lazyprod(d.asDiagonal(),A), MatrixXd(d.asDiagonal()*A));
+    VERIFY_IS_APPROX_EVALUATOR2(B, lazyprod(A,d.asDiagonal()), MatrixXd(A*d.asDiagonal()));
+  }
+
+  {
+    // test CoeffReadCost
+    Matrix4d a, b;
+    VERIFY_IS_EQUAL( get_cost(a), 1 );
+    VERIFY_IS_EQUAL( get_cost(a+b), 3);
+    VERIFY_IS_EQUAL( get_cost(2*a+b), 4);
+    VERIFY_IS_EQUAL( get_cost(a*b), 1);
+    VERIFY_IS_EQUAL( get_cost(a.lazyProduct(b)), 15);
+    VERIFY_IS_EQUAL( get_cost(a*(a*b)), 1);
+    VERIFY_IS_EQUAL( get_cost(a.lazyProduct(a*b)), 15);
+    VERIFY_IS_EQUAL( get_cost(a*(a+b)), 1);
+    VERIFY_IS_EQUAL( get_cost(a.lazyProduct(a+b)), 15);
+  }
+}

ADDED   3rd_party/eigen/test/fastmath.cpp
Index: 3rd_party/eigen/test/fastmath.cpp
==================================================================
--- 3rd_party/eigen/test/fastmath.cpp
+++ 3rd_party/eigen/test/fastmath.cpp
@@ -0,0 +1,99 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+void check(bool b, bool ref)
+{
+  std::cout << b;
+  if(b==ref)
+    std::cout << " OK  ";
+  else
+    std::cout << " BAD ";
+}
+
+#if EIGEN_COMP_MSVC && EIGEN_COMP_MSVC < 1800
+namespace std {
+  template<typename T> bool (isfinite)(T x) { return _finite(x); }
+  template<typename T> bool (isnan)(T x) { return _isnan(x); }
+  template<typename T> bool (isinf)(T x) { return _fpclass(x)==_FPCLASS_NINF || _fpclass(x)==_FPCLASS_PINF; }
+}
+#endif
+
+template<typename T>
+void check_inf_nan(bool dryrun) {
+  Matrix<T,Dynamic,1> m(10);
+  m.setRandom();
+  m(3) = std::numeric_limits<T>::quiet_NaN();
+
+  if(dryrun)
+  {
+    std::cout << "std::isfinite(" << m(3) << ") = "; check((std::isfinite)(m(3)),false); std::cout << "  ; numext::isfinite = "; check((numext::isfinite)(m(3)), false); std::cout << "\n";
+    std::cout << "std::isinf(" << m(3) << ")    = "; check((std::isinf)(m(3)),false);    std::cout << "  ; numext::isinf    = "; check((numext::isinf)(m(3)), false); std::cout << "\n";
+    std::cout << "std::isnan(" << m(3) << ")    = "; check((std::isnan)(m(3)),true);     std::cout << "  ; numext::isnan    = "; check((numext::isnan)(m(3)), true); std::cout << "\n";
+    std::cout << "allFinite: "; check(m.allFinite(), 0); std::cout << "\n";
+    std::cout << "hasNaN:    "; check(m.hasNaN(), 1);    std::cout << "\n";
+    std::cout << "\n";
+  }
+  else
+  {
+    VERIFY( !(numext::isfinite)(m(3)) );
+    VERIFY( !(numext::isinf)(m(3)) );
+    VERIFY(  (numext::isnan)(m(3)) );
+    VERIFY( !m.allFinite() );
+    VERIFY(  m.hasNaN() );
+  }
+  T hidden_zero = (std::numeric_limits<T>::min)()*(std::numeric_limits<T>::min)();
+  m(4) /= hidden_zero;
+  if(dryrun)
+  {
+    std::cout << "std::isfinite(" << m(4) << ") = "; check((std::isfinite)(m(4)),false); std::cout << "  ; numext::isfinite = "; check((numext::isfinite)(m(4)), false); std::cout << "\n";
+    std::cout << "std::isinf(" << m(4) << ")    = "; check((std::isinf)(m(4)),true);     std::cout << "  ; numext::isinf    = "; check((numext::isinf)(m(4)), true); std::cout << "\n";
+    std::cout << "std::isnan(" << m(4) << ")    = "; check((std::isnan)(m(4)),false);    std::cout << "  ; numext::isnan    = "; check((numext::isnan)(m(4)), false); std::cout << "\n";
+    std::cout << "allFinite: "; check(m.allFinite(), 0); std::cout << "\n";
+    std::cout << "hasNaN:    "; check(m.hasNaN(), 1);    std::cout << "\n";
+    std::cout << "\n";
+  }
+  else
+  {
+    VERIFY( !(numext::isfinite)(m(4)) );
+    VERIFY(  (numext::isinf)(m(4)) );
+    VERIFY( !(numext::isnan)(m(4)) );
+    VERIFY( !m.allFinite() );
+    VERIFY(  m.hasNaN() );
+  }
+  m(3) = 0;
+  if(dryrun)
+  {
+    std::cout << "std::isfinite(" << m(3) << ") = "; check((std::isfinite)(m(3)),true); std::cout << "  ; numext::isfinite = "; check((numext::isfinite)(m(3)), true); std::cout << "\n";
+    std::cout << "std::isinf(" << m(3) << ")    = "; check((std::isinf)(m(3)),false);    std::cout << "  ; numext::isinf    = "; check((numext::isinf)(m(3)), false); std::cout << "\n";
+    std::cout << "std::isnan(" << m(3) << ")    = "; check((std::isnan)(m(3)),false);     std::cout << "  ; numext::isnan    = "; check((numext::isnan)(m(3)), false); std::cout << "\n";
+    std::cout << "allFinite: "; check(m.allFinite(), 0); std::cout << "\n";
+    std::cout << "hasNaN:    "; check(m.hasNaN(), 0);    std::cout << "\n";
+    std::cout << "\n\n";
+  }
+  else
+  {
+    VERIFY(  (numext::isfinite)(m(3)) );
+    VERIFY( !(numext::isinf)(m(3)) );
+    VERIFY( !(numext::isnan)(m(3)) );
+    VERIFY( !m.allFinite() );
+    VERIFY( !m.hasNaN() );
+  }
+}
+
+void test_fastmath() {
+  std::cout << "*** float *** \n\n"; check_inf_nan<float>(true);
+  std::cout << "*** double ***\n\n"; check_inf_nan<double>(true);
+  std::cout << "*** long double *** \n\n"; check_inf_nan<long double>(true);
+
+  check_inf_nan<float>(false);
+  check_inf_nan<double>(false);
+  check_inf_nan<long double>(false);
+}

Index: 3rd_party/eigen/test/first_aligned.cpp
==================================================================
--- 3rd_party/eigen/test/first_aligned.cpp
+++ 3rd_party/eigen/test/first_aligned.cpp
@@ -11,19 +11,19 @@
 
 template<typename Scalar>
 void test_first_aligned_helper(Scalar *array, int size)
 {
   const int packet_size = sizeof(Scalar) * internal::packet_traits<Scalar>::size;
-  VERIFY(((size_t(array) + sizeof(Scalar) * internal::first_aligned(array, size)) % packet_size) == 0);
+  VERIFY(((size_t(array) + sizeof(Scalar) * internal::first_default_aligned(array, size)) % packet_size) == 0);
 }
 
 template<typename Scalar>
 void test_none_aligned_helper(Scalar *array, int size)
 {
   EIGEN_UNUSED_VARIABLE(array);
   EIGEN_UNUSED_VARIABLE(size);
-  VERIFY(internal::packet_traits<Scalar>::size == 1 || internal::first_aligned(array, size) == size);
+  VERIFY(internal::packet_traits<Scalar>::size == 1 || internal::first_default_aligned(array, size) == size);
 }
 
 struct some_non_vectorizable_type { float x; };
 
 void test_first_aligned()
@@ -39,13 +39,13 @@
   EIGEN_ALIGN16 double array_double[100];
   test_first_aligned_helper(array_double, 50);
   test_first_aligned_helper(array_double+1, 50);
   test_first_aligned_helper(array_double+2, 50);
   
-  double *array_double_plus_4_bytes = (double*)(size_t(array_double)+4);
+  double *array_double_plus_4_bytes = (double*)(internal::UIntPtr(array_double)+4);
   test_none_aligned_helper(array_double_plus_4_bytes, 50);
   test_none_aligned_helper(array_double_plus_4_bytes+1, 50);
   
   some_non_vectorizable_type array_nonvec[100];
   test_first_aligned_helper(array_nonvec, 100);
   test_none_aligned_helper(array_nonvec, 100);
 }

Index: 3rd_party/eigen/test/geo_alignedbox.cpp
==================================================================
--- 3rd_party/eigen/test/geo_alignedbox.cpp
+++ 3rd_party/eigen/test/geo_alignedbox.cpp
@@ -14,11 +14,11 @@
 
 #include<iostream>
 using namespace std;
 
 template<typename T> EIGEN_DONT_INLINE
-void kill_extra_precision(T& x) { eigen_assert(&x != 0); }
+void kill_extra_precision(T& x) { eigen_assert((void*)(&x) != (void*)0); }
 
 
 template<typename BoxType> void alignedbox(const BoxType& _box)
 {
   /* this test covers the following files:
@@ -46,16 +46,25 @@
   kill_extra_precision(p1);
 
   b0.extend(p0);
   b0.extend(p1);
   VERIFY(b0.contains(p0*s1+(Scalar(1)-s1)*p1));
+  VERIFY(b0.contains(b0.center()));
+  VERIFY_IS_APPROX(b0.center(),(p0+p1)/Scalar(2));
 
   (b2 = b0).extend(b1);
   VERIFY(b2.contains(b0));
   VERIFY(b2.contains(b1));
   VERIFY_IS_APPROX(b2.clamp(b0), b0);
 
+  // intersection
+  BoxType box1(VectorType::Random(dim));
+  box1.extend(VectorType::Random(dim));
+  BoxType box2(VectorType::Random(dim));
+  box2.extend(VectorType::Random(dim));
+
+  VERIFY(box1.intersects(box2) == !box1.intersection(box2).isEmpty()); 
 
   // alignment -- make sure there is no memory alignment assertion
   BoxType *bp0 = new BoxType(dim);
   BoxType *bp1 = new BoxType(dim);
   bp0->extend(*bp1);
@@ -170,9 +179,11 @@
     CALL_SUBTEST_8( alignedboxCastTests(AlignedBox1d()) );
 
     CALL_SUBTEST_9( alignedbox(AlignedBox1i()) );
     CALL_SUBTEST_10( alignedbox(AlignedBox2i()) );
     CALL_SUBTEST_11( alignedbox(AlignedBox3i()) );
+
+    CALL_SUBTEST_14( alignedbox(AlignedBox<double,Dynamic>(4)) );
   }
   CALL_SUBTEST_12( specificTest1() );
   CALL_SUBTEST_13( specificTest2() );
 }

Index: 3rd_party/eigen/test/geo_eulerangles.cpp
==================================================================
--- 3rd_party/eigen/test/geo_eulerangles.cpp
+++ 3rd_party/eigen/test/geo_eulerangles.cpp
@@ -24,20 +24,20 @@
   Vector3 eabis = m.eulerAngles(i, j, k);
   Matrix3 mbis(AngleAxisx(eabis[0], Vector3::Unit(i)) * AngleAxisx(eabis[1], Vector3::Unit(j)) * AngleAxisx(eabis[2], Vector3::Unit(k))); 
   VERIFY_IS_APPROX(m,  mbis); 
   /* If I==K, and ea[1]==0, then there no unique solution. */ 
   /* The remark apply in the case where I!=K, and |ea[1]| is close to pi/2. */ 
-  if( (i!=k || ea[1]!=0) && (i==k || !internal::isApprox(abs(ea[1]),Scalar(M_PI/2),test_precision<Scalar>())) ) 
+  if( (i!=k || ea[1]!=0) && (i==k || !internal::isApprox(abs(ea[1]),Scalar(EIGEN_PI/2),test_precision<Scalar>())) ) 
     VERIFY((ea-eabis).norm() <= test_precision<Scalar>());
   
   // approx_or_less_than does not work for 0
   VERIFY(0 < eabis[0] || test_isMuchSmallerThan(eabis[0], Scalar(1)));
-  VERIFY_IS_APPROX_OR_LESS_THAN(eabis[0], Scalar(M_PI));
-  VERIFY_IS_APPROX_OR_LESS_THAN(-Scalar(M_PI), eabis[1]);
-  VERIFY_IS_APPROX_OR_LESS_THAN(eabis[1], Scalar(M_PI));
-  VERIFY_IS_APPROX_OR_LESS_THAN(-Scalar(M_PI), eabis[2]);
-  VERIFY_IS_APPROX_OR_LESS_THAN(eabis[2], Scalar(M_PI));
+  VERIFY_IS_APPROX_OR_LESS_THAN(eabis[0], Scalar(EIGEN_PI));
+  VERIFY_IS_APPROX_OR_LESS_THAN(-Scalar(EIGEN_PI), eabis[1]);
+  VERIFY_IS_APPROX_OR_LESS_THAN(eabis[1], Scalar(EIGEN_PI));
+  VERIFY_IS_APPROX_OR_LESS_THAN(-Scalar(EIGEN_PI), eabis[2]);
+  VERIFY_IS_APPROX_OR_LESS_THAN(eabis[2], Scalar(EIGEN_PI));
 }
 
 template<typename Scalar> void check_all_var(const Matrix<Scalar,3,1>& ea)
 {
   verify_euler(ea, 0,1,2);
@@ -62,11 +62,11 @@
   typedef Matrix<Scalar,3,1> Vector3;
   typedef Array<Scalar,3,1> Array3;
   typedef Quaternion<Scalar> Quaternionx;
   typedef AngleAxis<Scalar> AngleAxisx;
 
-  Scalar a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
+  Scalar a = internal::random<Scalar>(-Scalar(EIGEN_PI), Scalar(EIGEN_PI));
   Quaternionx q1;
   q1 = AngleAxisx(a, Vector3::Random().normalized());
   Matrix3 m;
   m = q1;
   
@@ -82,17 +82,17 @@
   check_all_var(ea);
   ea = m.eulerAngles(0,1,0);
   check_all_var(ea);
   
   // Check with random angles in range [0:pi]x[-pi:pi]x[-pi:pi].
-  ea = (Array3::Random() + Array3(1,0,0))*Scalar(M_PI)*Array3(0.5,1,1);
+  ea = (Array3::Random() + Array3(1,0,0))*Scalar(EIGEN_PI)*Array3(0.5,1,1);
   check_all_var(ea);
   
-  ea[2] = ea[0] = internal::random<Scalar>(0,Scalar(M_PI));
+  ea[2] = ea[0] = internal::random<Scalar>(0,Scalar(EIGEN_PI));
   check_all_var(ea);
   
-  ea[0] = ea[1] = internal::random<Scalar>(0,Scalar(M_PI));
+  ea[0] = ea[1] = internal::random<Scalar>(0,Scalar(EIGEN_PI));
   check_all_var(ea);
   
   ea[1] = 0;
   check_all_var(ea);
   

Index: 3rd_party/eigen/test/geo_homogeneous.cpp
==================================================================
--- 3rd_party/eigen/test/geo_homogeneous.cpp
+++ 3rd_party/eigen/test/geo_homogeneous.cpp
@@ -36,10 +36,14 @@
   HMatrixType hm0 = HMatrixType::Random();
 
   hv0 << v0, 1;
   VERIFY_IS_APPROX(v0.homogeneous(), hv0);
   VERIFY_IS_APPROX(v0, hv0.hnormalized());
+  
+  VERIFY_IS_APPROX(v0.homogeneous().sum(), hv0.sum());
+  VERIFY_IS_APPROX(v0.homogeneous().minCoeff(), hv0.minCoeff());
+  VERIFY_IS_APPROX(v0.homogeneous().maxCoeff(), hv0.maxCoeff());
 
   hm0 << m0, ones.transpose();
   VERIFY_IS_APPROX(m0.colwise().homogeneous(), hm0);
   VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized());
   hm0.row(Size-1).setRandom();
@@ -52,14 +56,15 @@
   VERIFY_IS_APPROX(t1 * (m0.colwise().homogeneous().eval()), t1 * m0.colwise().homogeneous());
 
   T2MatrixType t2 = T2MatrixType::Random();
   VERIFY_IS_APPROX(t2 * (v0.homogeneous().eval()), t2 * v0.homogeneous());
   VERIFY_IS_APPROX(t2 * (m0.colwise().homogeneous().eval()), t2 * m0.colwise().homogeneous());
+  VERIFY_IS_APPROX(t2 * (v0.homogeneous().asDiagonal()), t2 * hv0.asDiagonal());
+  VERIFY_IS_APPROX((v0.homogeneous().asDiagonal()) * t2, hv0.asDiagonal() * t2);
 
   VERIFY_IS_APPROX((v0.transpose().rowwise().homogeneous().eval()) * t2,
                     v0.transpose().rowwise().homogeneous() * t2);
-                    m0.transpose().rowwise().homogeneous().eval();
   VERIFY_IS_APPROX((m0.transpose().rowwise().homogeneous().eval()) * t2,
                     m0.transpose().rowwise().homogeneous() * t2);
 
   T3MatrixType t3 = T3MatrixType::Random();
   VERIFY_IS_APPROX((v0.transpose().rowwise().homogeneous().eval()) * t3,
@@ -80,19 +85,36 @@
   
   pts1 = pts.colwise().homogeneous();
   VERIFY_IS_APPROX(aff  * pts.colwise().homogeneous(), (aff  * pts1).colwise().hnormalized());
   VERIFY_IS_APPROX(caff * pts.colwise().homogeneous(), (caff * pts1).colwise().hnormalized());
   VERIFY_IS_APPROX(proj * pts.colwise().homogeneous(), (proj * pts1));
-  
+
   VERIFY_IS_APPROX((aff  * pts1).colwise().hnormalized(),  aff  * pts);
   VERIFY_IS_APPROX((caff * pts1).colwise().hnormalized(), caff * pts);
   
   pts2 = pts1;
   pts2.row(Size).setRandom();
   VERIFY_IS_APPROX((aff  * pts2).colwise().hnormalized(), aff  * pts2.colwise().hnormalized());
   VERIFY_IS_APPROX((caff * pts2).colwise().hnormalized(), caff * pts2.colwise().hnormalized());
   VERIFY_IS_APPROX((proj * pts2).colwise().hnormalized(), (proj * pts2.colwise().hnormalized().colwise().homogeneous()).colwise().hnormalized());
+  
+  // Test combination of homogeneous
+  
+  VERIFY_IS_APPROX( (t2 * v0.homogeneous()).hnormalized(),
+                       (t2.template topLeftCorner<Size,Size>() * v0 + t2.template topRightCorner<Size,1>())
+                     / ((t2.template bottomLeftCorner<1,Size>()*v0).value() + t2(Size,Size)) );
+  
+  VERIFY_IS_APPROX( (t2 * pts.colwise().homogeneous()).colwise().hnormalized(),
+                    (Matrix<Scalar, Size+1, Dynamic>(t2 * pts1).colwise().hnormalized()) );
+  
+  VERIFY_IS_APPROX( (t2 .lazyProduct( v0.homogeneous() )).hnormalized(), (t2 * v0.homogeneous()).hnormalized() );
+  VERIFY_IS_APPROX( (t2 .lazyProduct  ( pts.colwise().homogeneous() )).colwise().hnormalized(), (t2 * pts1).colwise().hnormalized() );
+  
+  VERIFY_IS_APPROX( (v0.transpose().homogeneous() .lazyProduct( t2 )).hnormalized(), (v0.transpose().homogeneous()*t2).hnormalized() );
+  VERIFY_IS_APPROX( (pts.transpose().rowwise().homogeneous() .lazyProduct( t2 )).rowwise().hnormalized(), (pts1.transpose()*t2).rowwise().hnormalized() );
+
+  VERIFY_IS_APPROX( (t2.template triangularView<Lower>() * v0.homogeneous()).eval(), (t2.template triangularView<Lower>()*hv0) );
 }
 
 void test_geo_homogeneous()
 {
   for(int i = 0; i < g_repeat; i++) {

Index: 3rd_party/eigen/test/geo_hyperplane.cpp
==================================================================
--- 3rd_party/eigen/test/geo_hyperplane.cpp
+++ 3rd_party/eigen/test/geo_hyperplane.cpp
@@ -16,14 +16,16 @@
 template<typename HyperplaneType> void hyperplane(const HyperplaneType& _plane)
 {
   /* this test covers the following files:
      Hyperplane.h
   */
+  using std::abs;
   typedef typename HyperplaneType::Index Index;
   const Index dim = _plane.dim();
   enum { Options = HyperplaneType::Options };
   typedef typename HyperplaneType::Scalar Scalar;
+  typedef typename HyperplaneType::RealScalar RealScalar;
   typedef Matrix<Scalar, HyperplaneType::AmbientDimAtCompileTime, 1> VectorType;
   typedef Matrix<Scalar, HyperplaneType::AmbientDimAtCompileTime,
                          HyperplaneType::AmbientDimAtCompileTime> MatrixType;
 
   VectorType p0 = VectorType::Random(dim);
@@ -40,33 +42,41 @@
   Scalar s1 = internal::random<Scalar>();
 
   VERIFY_IS_APPROX( n1.dot(n1), Scalar(1) );
 
   VERIFY_IS_MUCH_SMALLER_THAN( pl0.absDistance(p0), Scalar(1) );
-  VERIFY_IS_APPROX( pl1.signedDistance(p1 + n1 * s0), s0 );
+  if(numext::abs2(s0)>RealScalar(1e-6))
+    VERIFY_IS_APPROX( pl1.signedDistance(p1 + n1 * s0), s0);
+  else
+    VERIFY_IS_MUCH_SMALLER_THAN( abs(pl1.signedDistance(p1 + n1 * s0) - s0), Scalar(1) );
   VERIFY_IS_MUCH_SMALLER_THAN( pl1.signedDistance(pl1.projection(p0)), Scalar(1) );
   VERIFY_IS_MUCH_SMALLER_THAN( pl1.absDistance(p1 +  pl1.normal().unitOrthogonal() * s1), Scalar(1) );
 
   // transform
   if (!NumTraits<Scalar>::IsComplex)
   {
     MatrixType rot = MatrixType::Random(dim,dim).householderQr().householderQ();
     DiagonalMatrix<Scalar,HyperplaneType::AmbientDimAtCompileTime> scaling(VectorType::Random());
     Translation<Scalar,HyperplaneType::AmbientDimAtCompileTime> translation(VectorType::Random());
+    
+    while(scaling.diagonal().cwiseAbs().minCoeff()<RealScalar(1e-4)) scaling.diagonal() = VectorType::Random();
 
     pl2 = pl1;
     VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot).absDistance(rot * p1), Scalar(1) );
     pl2 = pl1;
     VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot,Isometry).absDistance(rot * p1), Scalar(1) );
     pl2 = pl1;
     VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*scaling).absDistance((rot*scaling) * p1), Scalar(1) );
+    VERIFY_IS_APPROX( pl2.normal().norm(), RealScalar(1) );
     pl2 = pl1;
     VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*scaling*translation)
-                                 .absDistance((rot*scaling*translation) * p1), Scalar(1) );
+                                  .absDistance((rot*scaling*translation) * p1), Scalar(1) );
+    VERIFY_IS_APPROX( pl2.normal().norm(), RealScalar(1) );
     pl2 = pl1;
     VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*translation,Isometry)
                                  .absDistance((rot*translation) * p1), Scalar(1) );
+    VERIFY_IS_APPROX( pl2.normal().norm(), RealScalar(1) );
   }
 
   // casting
   const int Dim = HyperplaneType::AmbientDimAtCompileTime;
   typedef typename GetDifferentType<Scalar>::type OtherScalar;
@@ -88,13 +98,13 @@
   {
     Vector center = Vector::Random();
     Vector u = Vector::Random();
     Vector v = Vector::Random();
     Scalar a = internal::random<Scalar>();
-    while (abs(a-1) < 1e-4) a = internal::random<Scalar>();
-    while (u.norm() < 1e-4) u = Vector::Random();
-    while (v.norm() < 1e-4) v = Vector::Random();
+    while (abs(a-1) < Scalar(1e-4)) a = internal::random<Scalar>();
+    while (u.norm() < Scalar(1e-4)) u = Vector::Random();
+    while (v.norm() < Scalar(1e-4)) v = Vector::Random();
 
     HLine line_u = HLine::Through(center + u, center + a*u);
     HLine line_v = HLine::Through(center + v, center + a*v);
 
     // the line equations should be normalized so that a^2+b^2=1
@@ -102,16 +112,19 @@
     VERIFY_IS_APPROX(line_v.normal().norm(), Scalar(1));
 
     Vector result = line_u.intersection(line_v);
 
     // the lines should intersect at the point we called "center"
-    VERIFY_IS_APPROX(result, center);
+    if(abs(a-1) > Scalar(1e-2) && abs(v.normalized().dot(u.normalized()))<Scalar(0.9))
+      VERIFY_IS_APPROX(result, center);
 
     // check conversions between two types of lines
     PLine pl(line_u); // gcc 3.3 will commit suicide if we don't name this variable
-    CoeffsType converted_coeffs = HLine(pl).coeffs();
-    converted_coeffs *= (line_u.coeffs()[0])/(converted_coeffs[0]);
+    HLine line_u2(pl);
+    CoeffsType converted_coeffs = line_u2.coeffs();
+    if(line_u2.normal().dot(line_u.normal())<Scalar(0))
+      converted_coeffs = -line_u2.coeffs();
     VERIFY(line_u.coeffs().isApprox(converted_coeffs));
   }
 }
 
 template<typename Scalar> void planes()
@@ -143,13 +156,13 @@
 template<typename Scalar> void hyperplane_alignment()
 {
   typedef Hyperplane<Scalar,3,AutoAlign> Plane3a;
   typedef Hyperplane<Scalar,3,DontAlign> Plane3u;
 
-  EIGEN_ALIGN16 Scalar array1[4];
-  EIGEN_ALIGN16 Scalar array2[4];
-  EIGEN_ALIGN16 Scalar array3[4+1];
+  EIGEN_ALIGN_MAX Scalar array1[4];
+  EIGEN_ALIGN_MAX Scalar array2[4];
+  EIGEN_ALIGN_MAX Scalar array3[4+1];
   Scalar* array3u = array3+1;
 
   Plane3a *p1 = ::new(reinterpret_cast<void*>(array1)) Plane3a;
   Plane3u *p2 = ::new(reinterpret_cast<void*>(array2)) Plane3u;
   Plane3u *p3 = ::new(reinterpret_cast<void*>(array3u)) Plane3u;
@@ -159,12 +172,12 @@
   *p3 = *p1;
 
   VERIFY_IS_APPROX(p1->coeffs(), p2->coeffs());
   VERIFY_IS_APPROX(p1->coeffs(), p3->coeffs());
   
-  #if defined(EIGEN_VECTORIZE) && EIGEN_ALIGN_STATICALLY
-  if(internal::packet_traits<Scalar>::Vectorizable)
+  #if defined(EIGEN_VECTORIZE) && EIGEN_MAX_STATIC_ALIGN_BYTES > 0
+  if(internal::packet_traits<Scalar>::Vectorizable && internal::packet_traits<Scalar>::size<=4)
     VERIFY_RAISES_ASSERT((::new(reinterpret_cast<void*>(array3u)) Plane3a));
   #endif
 }
 
 

Index: 3rd_party/eigen/test/geo_orthomethods.cpp
==================================================================
--- 3rd_party/eigen/test/geo_orthomethods.cpp
+++ 3rd_party/eigen/test/geo_orthomethods.cpp
@@ -31,24 +31,35 @@
   // cross product
   VERIFY_IS_MUCH_SMALLER_THAN(v1.cross(v2).dot(v1), Scalar(1));
   VERIFY_IS_MUCH_SMALLER_THAN(v1.dot(v1.cross(v2)), Scalar(1));
   VERIFY_IS_MUCH_SMALLER_THAN(v1.cross(v2).dot(v2), Scalar(1));
   VERIFY_IS_MUCH_SMALLER_THAN(v2.dot(v1.cross(v2)), Scalar(1));
+  VERIFY_IS_MUCH_SMALLER_THAN(v1.cross(Vector3::Random()).dot(v1), Scalar(1));
   Matrix3 mat3;
   mat3 << v0.normalized(),
          (v0.cross(v1)).normalized(),
          (v0.cross(v1).cross(v0)).normalized();
   VERIFY(mat3.isUnitary());
-
+  
+  mat3.setRandom();
+  VERIFY_IS_APPROX(v0.cross(mat3*v1), -(mat3*v1).cross(v0));
+  VERIFY_IS_APPROX(v0.cross(mat3.lazyProduct(v1)), -(mat3.lazyProduct(v1)).cross(v0));
 
   // colwise/rowwise cross product
   mat3.setRandom();
   Vector3 vec3 = Vector3::Random();
   Matrix3 mcross;
   int i = internal::random<int>(0,2);
   mcross = mat3.colwise().cross(vec3);
   VERIFY_IS_APPROX(mcross.col(i), mat3.col(i).cross(vec3));
+  
+  VERIFY_IS_MUCH_SMALLER_THAN((mat3.adjoint() * mat3.colwise().cross(vec3)).diagonal().cwiseAbs().sum(), Scalar(1));
+  VERIFY_IS_MUCH_SMALLER_THAN((mat3.adjoint() * mat3.colwise().cross(Vector3::Random())).diagonal().cwiseAbs().sum(), Scalar(1));
+  
+  VERIFY_IS_MUCH_SMALLER_THAN((vec3.adjoint() * mat3.colwise().cross(vec3)).cwiseAbs().sum(), Scalar(1));
+  VERIFY_IS_MUCH_SMALLER_THAN((vec3.adjoint() * Matrix3::Random().colwise().cross(vec3)).cwiseAbs().sum(), Scalar(1));
+  
   mcross = mat3.rowwise().cross(vec3);
   VERIFY_IS_APPROX(mcross.row(i), mat3.row(i).cross(vec3));
 
   // cross3
   Vector4 v40 = Vector4::Random(),
@@ -55,10 +66,11 @@
           v41 = Vector4::Random(),
           v42 = Vector4::Random();
   v40.w() = v41.w() = v42.w() = 0;
   v42.template head<3>() = v40.template head<3>().cross(v41.template head<3>());
   VERIFY_IS_APPROX(v40.cross3(v41), v42);
+  VERIFY_IS_MUCH_SMALLER_THAN(v40.cross3(Vector4::Random()).dot(v40), Scalar(1));
   
   // check mixed product
   typedef Matrix<RealScalar, 3, 1> RealVector3;
   RealVector3 rv1 = RealVector3::Random();
   VERIFY_IS_APPROX(v1.cross(rv1.template cast<Scalar>()), v1.cross(rv1));

Index: 3rd_party/eigen/test/geo_parametrizedline.cpp
==================================================================
--- 3rd_party/eigen/test/geo_parametrizedline.cpp
+++ 3rd_party/eigen/test/geo_parametrizedline.cpp
@@ -64,13 +64,13 @@
 template<typename Scalar> void parametrizedline_alignment()
 {
   typedef ParametrizedLine<Scalar,4,AutoAlign> Line4a;
   typedef ParametrizedLine<Scalar,4,DontAlign> Line4u;
 
-  EIGEN_ALIGN16 Scalar array1[8];
-  EIGEN_ALIGN16 Scalar array2[8];
-  EIGEN_ALIGN16 Scalar array3[8+1];
+  EIGEN_ALIGN_MAX Scalar array1[16];
+  EIGEN_ALIGN_MAX Scalar array2[16];
+  EIGEN_ALIGN_MAX Scalar array3[16+1];
   Scalar* array3u = array3+1;
 
   Line4a *p1 = ::new(reinterpret_cast<void*>(array1)) Line4a;
   Line4u *p2 = ::new(reinterpret_cast<void*>(array2)) Line4u;
   Line4u *p3 = ::new(reinterpret_cast<void*>(array3u)) Line4u;
@@ -83,12 +83,12 @@
   VERIFY_IS_APPROX(p1->origin(), p2->origin());
   VERIFY_IS_APPROX(p1->origin(), p3->origin());
   VERIFY_IS_APPROX(p1->direction(), p2->direction());
   VERIFY_IS_APPROX(p1->direction(), p3->direction());
   
-  #if defined(EIGEN_VECTORIZE) && EIGEN_ALIGN_STATICALLY
-  if(internal::packet_traits<Scalar>::Vectorizable)
+  #if defined(EIGEN_VECTORIZE) && EIGEN_MAX_STATIC_ALIGN_BYTES>0
+  if(internal::packet_traits<Scalar>::Vectorizable && internal::packet_traits<Scalar>::size<=4)
     VERIFY_RAISES_ASSERT((::new(reinterpret_cast<void*>(array3u)) Line4a));
   #endif
 }
 
 void test_geo_parametrizedline()

Index: 3rd_party/eigen/test/geo_quaternion.cpp
==================================================================
--- 3rd_party/eigen/test/geo_quaternion.cpp
+++ 3rd_party/eigen/test/geo_quaternion.cpp
@@ -28,12 +28,12 @@
   typedef AngleAxis<Scalar> AA;
 
   Scalar largeEps = test_precision<Scalar>();
 
   Scalar theta_tot = AA(q1*q0.inverse()).angle();
-  if(theta_tot>M_PI)
-    theta_tot = Scalar(2.*M_PI)-theta_tot;
+  if(theta_tot>Scalar(EIGEN_PI))
+    theta_tot = Scalar(2.)*Scalar(EIGEN_PI)-theta_tot;
   for(Scalar t=0; t<=Scalar(1.001); t+=Scalar(0.1))
   {
     QuatType q = q0.slerp(t,q1);
     Scalar theta = AA(q*q0.inverse()).angle();
     VERIFY(abs(q.norm() - 1) < largeEps);
@@ -47,27 +47,27 @@
   /* this test covers the following files:
      Quaternion.h
   */
   using std::abs;
   typedef Matrix<Scalar,3,1> Vector3;
-  typedef Matrix<Scalar,4,1> Vector4;
+  typedef Matrix<Scalar,3,3> Matrix3;
   typedef Quaternion<Scalar,Options> Quaternionx;
   typedef AngleAxis<Scalar> AngleAxisx;
 
   Scalar largeEps = test_precision<Scalar>();
   if (internal::is_same<Scalar,float>::value)
-    largeEps = 1e-3f;
+    largeEps = Scalar(1e-3);
 
   Scalar eps = internal::random<Scalar>() * Scalar(1e-2);
 
   Vector3 v0 = Vector3::Random(),
           v1 = Vector3::Random(),
           v2 = Vector3::Random(),
           v3 = Vector3::Random();
 
-  Scalar  a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI)),
-          b = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
+  Scalar  a = internal::random<Scalar>(-Scalar(EIGEN_PI), Scalar(EIGEN_PI)),
+          b = internal::random<Scalar>(-Scalar(EIGEN_PI), Scalar(EIGEN_PI));
 
   // Quaternion: Identity(), setIdentity();
   Quaternionx q1, q2;
   q2.setIdentity();
   VERIFY_IS_APPROX(Quaternionx(Quaternionx::Identity()).coeffs(), q2.coeffs());
@@ -80,12 +80,12 @@
   q1 = AngleAxisx(a, v0.normalized());
   q2 = AngleAxisx(a, v1.normalized());
 
   // angular distance
   Scalar refangle = abs(AngleAxisx(q1.inverse()*q2).angle());
-  if (refangle>Scalar(M_PI))
-    refangle = Scalar(2)*Scalar(M_PI) - refangle;
+  if (refangle>Scalar(EIGEN_PI))
+    refangle = Scalar(2)*Scalar(EIGEN_PI) - refangle;
 
   if((q1.coeffs()-q2.coeffs()).norm() > 10*largeEps)
   {
     VERIFY_IS_MUCH_SMALLER_THAN(abs(q1.angularDistance(q2) - refangle), Scalar(1));
   }
@@ -99,20 +99,25 @@
         || !(q2 * q1 * v2).isApprox(q1.toRotationMatrix() * q2.toRotationMatrix() * v2));
 
   q2 = q1.toRotationMatrix();
   VERIFY_IS_APPROX(q1*v1,q2*v1);
 
+  Matrix3 rot1(q1);
+  VERIFY_IS_APPROX(q1*v1,rot1*v1);
+  Quaternionx q3(rot1.transpose()*rot1);
+  VERIFY_IS_APPROX(q3*v1,v1);
+
 
   // angle-axis conversion
   AngleAxisx aa = AngleAxisx(q1);
   VERIFY_IS_APPROX(q1 * v1, Quaternionx(aa) * v1);
 
   // Do not execute the test if the rotation angle is almost zero, or
   // the rotation axis and v1 are almost parallel.
   if (abs(aa.angle()) > 5*test_precision<Scalar>()
-      && (aa.axis() - v1.normalized()).norm() < 1.99
-      && (aa.axis() + v1.normalized()).norm() < 1.99) 
+      && (aa.axis() - v1.normalized()).norm() < Scalar(1.99)
+      && (aa.axis() + v1.normalized()).norm() < Scalar(1.99))
   {
     VERIFY_IS_NOT_APPROX(q1 * v1, Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1);
   }
 
   // from two vector creation
@@ -149,23 +154,23 @@
 
   // test bug 369 - improper alignment.
   Quaternionx *q = new Quaternionx;
   delete q;
 
-  q1 = AngleAxisx(a, v0.normalized());
-  q2 = AngleAxisx(b, v1.normalized());
+  q1 = Quaternionx::UnitRandom();
+  q2 = Quaternionx::UnitRandom();
   check_slerp(q1,q2);
 
   q1 = AngleAxisx(b, v1.normalized());
-  q2 = AngleAxisx(b+Scalar(M_PI), v1.normalized());
+  q2 = AngleAxisx(b+Scalar(EIGEN_PI), v1.normalized());
   check_slerp(q1,q2);
 
   q1 = AngleAxisx(b,  v1.normalized());
   q2 = AngleAxisx(-b, -v1.normalized());
   check_slerp(q1,q2);
 
-  q1.coeffs() = Vector4::Random().normalized();
+  q1 = Quaternionx::UnitRandom();
   q2.coeffs() = -q1.coeffs();
   check_slerp(q1,q2);
 }
 
 template<typename Scalar> void mapQuaternion(void){
@@ -177,15 +182,15 @@
   typedef Matrix<Scalar,3,1> Vector3;
   typedef AngleAxis<Scalar> AngleAxisx;
   
   Vector3 v0 = Vector3::Random(),
           v1 = Vector3::Random();
-  Scalar  a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
+  Scalar  a = internal::random<Scalar>(-Scalar(EIGEN_PI), Scalar(EIGEN_PI));
 
-  EIGEN_ALIGN16 Scalar array1[4];
-  EIGEN_ALIGN16 Scalar array2[4];
-  EIGEN_ALIGN16 Scalar array3[4+1];
+  EIGEN_ALIGN_MAX Scalar array1[4];
+  EIGEN_ALIGN_MAX Scalar array2[4];
+  EIGEN_ALIGN_MAX Scalar array3[4+1];
   Scalar* array3unaligned = array3+1;
   
   MQuaternionA    mq1(array1);
   MCQuaternionA   mcq1(array1);
   MQuaternionA    mq2(array2);
@@ -230,13 +235,13 @@
 
 template<typename Scalar> void quaternionAlignment(void){
   typedef Quaternion<Scalar,AutoAlign> QuaternionA;
   typedef Quaternion<Scalar,DontAlign> QuaternionUA;
 
-  EIGEN_ALIGN16 Scalar array1[4];
-  EIGEN_ALIGN16 Scalar array2[4];
-  EIGEN_ALIGN16 Scalar array3[4+1];
+  EIGEN_ALIGN_MAX Scalar array1[4];
+  EIGEN_ALIGN_MAX Scalar array2[4];
+  EIGEN_ALIGN_MAX Scalar array3[4+1];
   Scalar* arrayunaligned = array3+1;
 
   QuaternionA *q1 = ::new(reinterpret_cast<void*>(array1)) QuaternionA;
   QuaternionUA *q2 = ::new(reinterpret_cast<void*>(array2)) QuaternionUA;
   QuaternionUA *q3 = ::new(reinterpret_cast<void*>(arrayunaligned)) QuaternionUA;
@@ -245,12 +250,12 @@
   *q2 = *q1;
   *q3 = *q1;
 
   VERIFY_IS_APPROX(q1->coeffs(), q2->coeffs());
   VERIFY_IS_APPROX(q1->coeffs(), q3->coeffs());
-  #if defined(EIGEN_VECTORIZE) && EIGEN_ALIGN_STATICALLY
-  if(internal::packet_traits<Scalar>::Vectorizable)
+  #if defined(EIGEN_VECTORIZE) && EIGEN_MAX_STATIC_ALIGN_BYTES>0
+  if(internal::packet_traits<Scalar>::Vectorizable && internal::packet_traits<Scalar>::size<=4)
     VERIFY_RAISES_ASSERT((::new(reinterpret_cast<void*>(arrayunaligned)) QuaternionA));
   #endif
 }
 
 template<typename PlainObjectType> void check_const_correctness(const PlainObjectType&)

Index: 3rd_party/eigen/test/geo_transformations.cpp
==================================================================
--- 3rd_party/eigen/test/geo_transformations.cpp
+++ 3rd_party/eigen/test/geo_transformations.cpp
@@ -10,10 +10,21 @@
 #include "main.h"
 #include <Eigen/Geometry>
 #include <Eigen/LU>
 #include <Eigen/SVD>
 
+template<typename T>
+Matrix<T,2,1> angleToVec(T a)
+{
+  return Matrix<T,2,1>(std::cos(a), std::sin(a));
+}
+
+// This permits to workaround a bug in clang/llvm code generation.
+template<typename T>
+EIGEN_DONT_INLINE
+void dont_over_optimize(T& x) { volatile typename T::Scalar tmp = x(0); x(0) = tmp; }
+
 template<typename Scalar, int Mode, int Options> void non_projective_only()
 {
     /* this test covers the following files:
      Cross.h Quaternion.h, Transform.cpp
   */
@@ -27,11 +38,11 @@
   Vector3 v0 = Vector3::Random(),
           v1 = Vector3::Random();
 
   Transform3 t0, t1, t2;
 
-  Scalar a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
+  Scalar a = internal::random<Scalar>(-Scalar(EIGEN_PI), Scalar(EIGEN_PI));
 
   Quaternionx q1, q2;
 
   q1 = AngleAxisx(a, v0.normalized());
 
@@ -95,20 +106,18 @@
 
   Vector3 v0 = Vector3::Random(),
           v1 = Vector3::Random();
   Matrix3 matrot1, m;
 
-  Scalar a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-  Scalar s0 = internal::random<Scalar>(),
-         s1 = internal::random<Scalar>();
+  Scalar a = internal::random<Scalar>(-Scalar(EIGEN_PI), Scalar(EIGEN_PI));
+  Scalar s0 = internal::random<Scalar>(), s1 = internal::random<Scalar>();
   
   while(v0.norm() < test_precision<Scalar>()) v0 = Vector3::Random();
   while(v1.norm() < test_precision<Scalar>()) v1 = Vector3::Random();
-    
 
   VERIFY_IS_APPROX(v0, AngleAxisx(a, v0.normalized()) * v0);
-  VERIFY_IS_APPROX(-v0, AngleAxisx(Scalar(M_PI), v0.unitOrthogonal()) * v0);
+  VERIFY_IS_APPROX(-v0, AngleAxisx(Scalar(EIGEN_PI), v0.unitOrthogonal()) * v0);
   if(abs(cos(a)) > test_precision<Scalar>())
   {
     VERIFY_IS_APPROX(cos(a)*v0.squaredNorm(), v0.dot(AngleAxisx(a, v0.unitOrthogonal()) * v0));
   }
   m = AngleAxisx(a, v0.normalized()).toRotationMatrix().adjoint();
@@ -130,18 +139,20 @@
 
   // angle-axis conversion
   AngleAxisx aa = AngleAxisx(q1);
   VERIFY_IS_APPROX(q1 * v1, Quaternionx(aa) * v1);
   
-  if(abs(aa.angle()) > NumTraits<Scalar>::dummy_precision())
+  // The following test is stable only if 2*angle != angle and v1 is not colinear with axis
+  if( (abs(aa.angle()) > test_precision<Scalar>()) && (abs(aa.axis().dot(v1.normalized()))<(Scalar(1)-Scalar(4)*test_precision<Scalar>())) )
   {
     VERIFY( !(q1 * v1).isApprox(Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1) );
   }
 
   aa.fromRotationMatrix(aa.toRotationMatrix());
   VERIFY_IS_APPROX(q1 * v1, Quaternionx(aa) * v1);
-  if(abs(aa.angle()) > NumTraits<Scalar>::dummy_precision())
+  // The following test is stable only if 2*angle != angle and v1 is not colinear with axis
+  if( (abs(aa.angle()) > test_precision<Scalar>()) && (abs(aa.axis().dot(v1.normalized()))<(Scalar(1)-Scalar(4)*test_precision<Scalar>())) )
   {
     VERIFY( !(q1 * v1).isApprox(Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1) );
   }
 
   // AngleAxis
@@ -156,11 +167,11 @@
 
   // Transform
   // TODO complete the tests !
   a = 0;
   while (abs(a)<Scalar(0.1))
-    a = internal::random<Scalar>(-Scalar(0.4)*Scalar(M_PI), Scalar(0.4)*Scalar(M_PI));
+    a = internal::random<Scalar>(-Scalar(0.4)*Scalar(EIGEN_PI), Scalar(0.4)*Scalar(EIGEN_PI));
   q1 = AngleAxisx(a, v0.normalized());
   Transform3 t0, t1, t2;
 
   // first test setIdentity() and Identity()
   t0.setIdentity();
@@ -202,11 +213,11 @@
   Transform3 tmat3(mat3), tmat4(mat4);
   if(Mode!=int(AffineCompact))
     tmat4.matrix()(3,3) = Scalar(1);
   VERIFY_IS_APPROX(tmat3.matrix(), tmat4.matrix());
 
-  Scalar a3 = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
+  Scalar a3 = internal::random<Scalar>(-Scalar(EIGEN_PI), Scalar(EIGEN_PI));
   Vector3 v3 = Vector3::Random().normalized();
   AngleAxisx aa3(a3, v3);
   Transform3 t3(aa3);
   Transform3 t4;
   t4 = aa3;
@@ -214,16 +225,19 @@
   t4.rotate(AngleAxisx(-a3,v3));
   VERIFY_IS_APPROX(t4.matrix(), MatrixType::Identity());
   t4 *= aa3;
   VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
 
-  v3 = Vector3::Random();
+  do {
+    v3 = Vector3::Random();
+    dont_over_optimize(v3);
+  } while (v3.cwiseAbs().minCoeff()<NumTraits<Scalar>::epsilon());
   Translation3 tv3(v3);
   Transform3 t5(tv3);
   t4 = tv3;
   VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-  t4.translate(-v3);
+  t4.translate((-v3).eval());
   VERIFY_IS_APPROX(t4.matrix(), MatrixType::Identity());
   t4 *= tv3;
   VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
 
   AlignedScaling3 sv3(v3);
@@ -317,10 +331,13 @@
   t1 = AlignedScaling3(v0) * (Translation3(v0) * Transform3(q1));
   VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
   // transformation * aligned scaling
   t0.scale(v0);
   t1 *= AlignedScaling3(v0);
+  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
+  t1 = AlignedScaling3(v0) * (Translation3(v0) * Transform3(q1));
+  t1 = t1 * v0.asDiagonal();
   VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
   // transformation * translation
   t0.translate(v0);
   t1 = t1 * Translation3(v0);
   VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
@@ -408,47 +425,151 @@
   Rotation2D<Scalar> r2d1(internal::random<Scalar>());
   Rotation2D<float> r2d1f = r2d1.template cast<float>();
   VERIFY_IS_APPROX(r2d1f.template cast<Scalar>(),r2d1);
   Rotation2D<double> r2d1d = r2d1.template cast<double>();
   VERIFY_IS_APPROX(r2d1d.template cast<Scalar>(),r2d1);
-
-  t20 = Translation2(v20) * (Rotation2D<Scalar>(s0) * Eigen::Scaling(s0));
-  t21 = Translation2(v20) * Rotation2D<Scalar>(s0) * Eigen::Scaling(s0);
-  VERIFY_IS_APPROX(t20,t21);
   
+  for(int k=0; k<100; ++k)
+  {
+    Scalar angle = internal::random<Scalar>(-100,100);
+    Rotation2D<Scalar> rot2(angle);
+    VERIFY( rot2.smallestPositiveAngle() >= 0 );
+    VERIFY( rot2.smallestPositiveAngle() <= Scalar(2)*Scalar(EIGEN_PI) );
+    VERIFY_IS_APPROX( angleToVec(rot2.smallestPositiveAngle()), angleToVec(rot2.angle()) );
+    
+    VERIFY( rot2.smallestAngle() >= -Scalar(EIGEN_PI) );
+    VERIFY( rot2.smallestAngle() <=  Scalar(EIGEN_PI) );
+    VERIFY_IS_APPROX( angleToVec(rot2.smallestAngle()), angleToVec(rot2.angle()) );
+
+    Matrix<Scalar,2,2> rot2_as_mat(rot2);
+    Rotation2D<Scalar> rot3(rot2_as_mat);
+    VERIFY_IS_APPROX( angleToVec(rot2.smallestAngle()),  angleToVec(rot3.angle()) );
+  }
+
+  s0 = internal::random<Scalar>(-100,100);
+  s1 = internal::random<Scalar>(-100,100);
   Rotation2D<Scalar> R0(s0), R1(s1);
+  
   t20 = Translation2(v20) * (R0 * Eigen::Scaling(s0));
   t21 = Translation2(v20) * R0 * Eigen::Scaling(s0);
   VERIFY_IS_APPROX(t20,t21);
   
   t20 = Translation2(v20) * (R0 * R0.inverse() * Eigen::Scaling(s0));
   t21 = Translation2(v20) * Eigen::Scaling(s0);
   VERIFY_IS_APPROX(t20,t21);
   
   VERIFY_IS_APPROX(s0, (R0.slerp(0, R1)).angle());
-  VERIFY_IS_APPROX(s1, (R0.slerp(1, R1)).angle());
-  VERIFY_IS_APPROX(s0, (R0.slerp(0.5, R0)).angle());
-  VERIFY_IS_APPROX(Scalar(0), (R0.slerp(0.5, R0.inverse())).angle());
+  VERIFY_IS_APPROX( angleToVec(R1.smallestPositiveAngle()), angleToVec((R0.slerp(1, R1)).smallestPositiveAngle()) );
+  VERIFY_IS_APPROX(R0.smallestPositiveAngle(), (R0.slerp(0.5, R0)).smallestPositiveAngle());
+
+  if(std::cos(s0)>0)
+    VERIFY_IS_MUCH_SMALLER_THAN((R0.slerp(0.5, R0.inverse())).smallestAngle(), Scalar(1));
+  else
+    VERIFY_IS_APPROX(Scalar(EIGEN_PI), (R0.slerp(0.5, R0.inverse())).smallestPositiveAngle());
+  
+  // Check path length
+  Scalar l = 0;
+  int path_steps = 100;
+  for(int k=0; k<path_steps; ++k)
+  {
+    Scalar a1 = R0.slerp(Scalar(k)/Scalar(path_steps), R1).angle();
+    Scalar a2 = R0.slerp(Scalar(k+1)/Scalar(path_steps), R1).angle();
+    l += std::abs(a2-a1);
+  }
+  VERIFY(l<=Scalar(EIGEN_PI)*(Scalar(1)+NumTraits<Scalar>::epsilon()*Scalar(path_steps/2)));
   
   // check basic features
   {
     Rotation2D<Scalar> r1;           // default ctor
     r1 = Rotation2D<Scalar>(s0);     // copy assignment
     VERIFY_IS_APPROX(r1.angle(),s0);
     Rotation2D<Scalar> r2(r1);       // copy ctor
     VERIFY_IS_APPROX(r2.angle(),s0);
   }
+
+  {
+    Transform3 t32(Matrix4::Random()), t33, t34;
+    t34 = t33 = t32;
+    t32.scale(v0);
+    t33*=AlignedScaling3(v0);
+    VERIFY_IS_APPROX(t32.matrix(), t33.matrix());
+    t33 = t34 * AlignedScaling3(v0);
+    VERIFY_IS_APPROX(t32.matrix(), t33.matrix());
+  }
+
+}
+
+template<typename A1, typename A2, typename P, typename Q, typename V, typename H>
+void transform_associativity_left(const A1& a1, const A2& a2, const P& p, const Q& q, const V& v, const H& h)
+{
+  VERIFY_IS_APPROX( q*(a1*v), (q*a1)*v );
+  VERIFY_IS_APPROX( q*(a2*v), (q*a2)*v );
+  VERIFY_IS_APPROX( q*(p*h).hnormalized(),  ((q*p)*h).hnormalized() );
+}
+
+template<typename A1, typename A2, typename P, typename Q, typename V, typename H>
+void transform_associativity2(const A1& a1, const A2& a2, const P& p, const Q& q, const V& v, const H& h)
+{
+  VERIFY_IS_APPROX( a1*(q*v), (a1*q)*v );
+  VERIFY_IS_APPROX( a2*(q*v), (a2*q)*v );
+  VERIFY_IS_APPROX( p *(q*v).homogeneous(), (p *q)*v.homogeneous() );
+
+  transform_associativity_left(a1, a2,p, q, v, h);
+}
+
+template<typename Scalar, int Dim, int Options,typename RotationType>
+void transform_associativity(const RotationType& R)
+{
+  typedef Matrix<Scalar,Dim,1> VectorType;
+  typedef Matrix<Scalar,Dim+1,1> HVectorType;
+  typedef Matrix<Scalar,Dim,Dim> LinearType;
+  typedef Matrix<Scalar,Dim+1,Dim+1> MatrixType;
+  typedef Transform<Scalar,Dim,AffineCompact,Options> AffineCompactType;
+  typedef Transform<Scalar,Dim,Affine,Options> AffineType;
+  typedef Transform<Scalar,Dim,Projective,Options> ProjectiveType;
+  typedef DiagonalMatrix<Scalar,Dim> ScalingType;
+  typedef Translation<Scalar,Dim> TranslationType;
+
+  AffineCompactType A1c; A1c.matrix().setRandom();
+  AffineCompactType A2c; A2c.matrix().setRandom();
+  AffineType A1(A1c);
+  AffineType A2(A2c);
+  ProjectiveType P1; P1.matrix().setRandom();
+  VectorType v1 = VectorType::Random();
+  VectorType v2 = VectorType::Random();
+  HVectorType h1 = HVectorType::Random();
+  Scalar s1 = internal::random<Scalar>();
+  LinearType L = LinearType::Random();
+  MatrixType M = MatrixType::Random();
+
+  CALL_SUBTEST( transform_associativity2(A1c, A1, P1, A2, v2, h1) );
+  CALL_SUBTEST( transform_associativity2(A1c, A1, P1, A2c, v2, h1) );
+  CALL_SUBTEST( transform_associativity2(A1c, A1, P1, v1.asDiagonal(), v2, h1) );
+  CALL_SUBTEST( transform_associativity2(A1c, A1, P1, ScalingType(v1), v2, h1) );
+  CALL_SUBTEST( transform_associativity2(A1c, A1, P1, Scaling(v1), v2, h1) );
+  CALL_SUBTEST( transform_associativity2(A1c, A1, P1, Scaling(s1), v2, h1) );
+  CALL_SUBTEST( transform_associativity2(A1c, A1, P1, TranslationType(v1), v2, h1) );
+  CALL_SUBTEST( transform_associativity_left(A1c, A1, P1, L, v2, h1) );
+  CALL_SUBTEST( transform_associativity2(A1c, A1, P1, R, v2, h1) );
+
+  VERIFY_IS_APPROX( A1*(M*h1), (A1*M)*h1 );
+  VERIFY_IS_APPROX( A1c*(M*h1), (A1c*M)*h1 );
+  VERIFY_IS_APPROX( P1*(M*h1), (P1*M)*h1 );
+
+  VERIFY_IS_APPROX( M*(A1*h1), (M*A1)*h1 );
+  VERIFY_IS_APPROX( M*(A1c*h1), (M*A1c)*h1 );
+  VERIFY_IS_APPROX( M*(P1*h1),  ((M*P1)*h1) );
 }
 
 template<typename Scalar> void transform_alignment()
 {
   typedef Transform<Scalar,3,Projective,AutoAlign> Projective3a;
   typedef Transform<Scalar,3,Projective,DontAlign> Projective3u;
 
-  EIGEN_ALIGN16 Scalar array1[16];
-  EIGEN_ALIGN16 Scalar array2[16];
-  EIGEN_ALIGN16 Scalar array3[16+1];
+  EIGEN_ALIGN_MAX Scalar array1[16];
+  EIGEN_ALIGN_MAX Scalar array2[16];
+  EIGEN_ALIGN_MAX Scalar array3[16+1];
   Scalar* array3u = array3+1;
 
   Projective3a *p1 = ::new(reinterpret_cast<void*>(array1)) Projective3a;
   Projective3u *p2 = ::new(reinterpret_cast<void*>(array2)) Projective3u;
   Projective3u *p3 = ::new(reinterpret_cast<void*>(array3u)) Projective3u;
@@ -460,11 +581,11 @@
   VERIFY_IS_APPROX(p1->matrix(), p2->matrix());
   VERIFY_IS_APPROX(p1->matrix(), p3->matrix());
   
   VERIFY_IS_APPROX( (*p1) * (*p1), (*p2)*(*p3));
   
-  #if defined(EIGEN_VECTORIZE) && EIGEN_ALIGN_STATICALLY
+  #if defined(EIGEN_VECTORIZE) && EIGEN_MAX_STATIC_ALIGN_BYTES>0
   if(internal::packet_traits<Scalar>::Vectorizable)
     VERIFY_RAISES_ASSERT((::new(reinterpret_cast<void*>(array3u)) Projective3a));
   #endif
 }
 
@@ -515,7 +636,10 @@
     CALL_SUBTEST_6(( transformations<double,Projective,RowMajor|DontAlign>() ));
 
 
     CALL_SUBTEST_7(( transform_products<double,3,RowMajor|AutoAlign>() ));
     CALL_SUBTEST_7(( transform_products<float,2,AutoAlign>() ));
+
+    CALL_SUBTEST_8(( transform_associativity<double,2,ColMajor>(Rotation2D<double>(internal::random<double>()*double(EIGEN_PI))) ));
+    CALL_SUBTEST_8(( transform_associativity<double,3,ColMajor>(Quaterniond::UnitRandom()) ));
   }
 }

ADDED   3rd_party/eigen/test/half_float.cpp
Index: 3rd_party/eigen/test/half_float.cpp
==================================================================
--- 3rd_party/eigen/test/half_float.cpp
+++ 3rd_party/eigen/test/half_float.cpp
@@ -0,0 +1,264 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include <sstream>
+
+#include "main.h"
+
+#include <Eigen/src/Core/arch/CUDA/Half.h>
+
+// Make sure it's possible to forward declare Eigen::half
+namespace Eigen {
+struct half;
+}
+
+using Eigen::half;
+
+void test_conversion()
+{
+  using Eigen::half_impl::__half;
+
+  // Conversion from float.
+  VERIFY_IS_EQUAL(half(1.0f).x, 0x3c00);
+  VERIFY_IS_EQUAL(half(0.5f).x, 0x3800);
+  VERIFY_IS_EQUAL(half(0.33333f).x, 0x3555);
+  VERIFY_IS_EQUAL(half(0.0f).x, 0x0000);
+  VERIFY_IS_EQUAL(half(-0.0f).x, 0x8000);
+  VERIFY_IS_EQUAL(half(65504.0f).x, 0x7bff);
+  VERIFY_IS_EQUAL(half(65536.0f).x, 0x7c00);  // Becomes infinity.
+
+  // Denormals.
+  VERIFY_IS_EQUAL(half(-5.96046e-08f).x, 0x8001);
+  VERIFY_IS_EQUAL(half(5.96046e-08f).x, 0x0001);
+  VERIFY_IS_EQUAL(half(1.19209e-07f).x, 0x0002);
+
+  // Verify round-to-nearest-even behavior.
+  float val1 = float(half(__half(0x3c00)));
+  float val2 = float(half(__half(0x3c01)));
+  float val3 = float(half(__half(0x3c02)));
+  VERIFY_IS_EQUAL(half(0.5f * (val1 + val2)).x, 0x3c00);
+  VERIFY_IS_EQUAL(half(0.5f * (val2 + val3)).x, 0x3c02);
+
+  // Conversion from int.
+  VERIFY_IS_EQUAL(half(-1).x, 0xbc00);
+  VERIFY_IS_EQUAL(half(0).x, 0x0000);
+  VERIFY_IS_EQUAL(half(1).x, 0x3c00);
+  VERIFY_IS_EQUAL(half(2).x, 0x4000);
+  VERIFY_IS_EQUAL(half(3).x, 0x4200);
+
+  // Conversion from bool.
+  VERIFY_IS_EQUAL(half(false).x, 0x0000);
+  VERIFY_IS_EQUAL(half(true).x, 0x3c00);
+
+  // Conversion to float.
+  VERIFY_IS_EQUAL(float(half(__half(0x0000))), 0.0f);
+  VERIFY_IS_EQUAL(float(half(__half(0x3c00))), 1.0f);
+
+  // Denormals.
+  VERIFY_IS_APPROX(float(half(__half(0x8001))), -5.96046e-08f);
+  VERIFY_IS_APPROX(float(half(__half(0x0001))), 5.96046e-08f);
+  VERIFY_IS_APPROX(float(half(__half(0x0002))), 1.19209e-07f);
+
+  // NaNs and infinities.
+  VERIFY(!(numext::isinf)(float(half(65504.0f))));  // Largest finite number.
+  VERIFY(!(numext::isnan)(float(half(0.0f))));
+  VERIFY((numext::isinf)(float(half(__half(0xfc00)))));
+  VERIFY((numext::isnan)(float(half(__half(0xfc01)))));
+  VERIFY((numext::isinf)(float(half(__half(0x7c00)))));
+  VERIFY((numext::isnan)(float(half(__half(0x7c01)))));
+
+#if !EIGEN_COMP_MSVC
+  // Visual Studio errors out on divisions by 0
+  VERIFY((numext::isnan)(float(half(0.0 / 0.0))));
+  VERIFY((numext::isinf)(float(half(1.0 / 0.0))));
+  VERIFY((numext::isinf)(float(half(-1.0 / 0.0))));
+#endif
+
+  // Exactly same checks as above, just directly on the half representation.
+  VERIFY(!(numext::isinf)(half(__half(0x7bff))));
+  VERIFY(!(numext::isnan)(half(__half(0x0000))));
+  VERIFY((numext::isinf)(half(__half(0xfc00))));
+  VERIFY((numext::isnan)(half(__half(0xfc01))));
+  VERIFY((numext::isinf)(half(__half(0x7c00))));
+  VERIFY((numext::isnan)(half(__half(0x7c01))));
+
+#if !EIGEN_COMP_MSVC
+  // Visual Studio errors out on divisions by 0
+  VERIFY((numext::isnan)(half(0.0 / 0.0)));
+  VERIFY((numext::isinf)(half(1.0 / 0.0)));
+  VERIFY((numext::isinf)(half(-1.0 / 0.0)));
+#endif
+}
+
+void test_numtraits()
+{
+  std::cout << "epsilon       = " << NumTraits<half>::epsilon() << "  (0x" << std::hex << NumTraits<half>::epsilon().x << ")" << std::endl;
+  std::cout << "highest       = " << NumTraits<half>::highest() << "  (0x" << std::hex << NumTraits<half>::highest().x << ")" << std::endl;
+  std::cout << "lowest        = " << NumTraits<half>::lowest() << "  (0x" << std::hex << NumTraits<half>::lowest().x << ")" << std::endl;
+  std::cout << "min           = " << (std::numeric_limits<half>::min)() << "  (0x" << std::hex << half((std::numeric_limits<half>::min)()).x << ")" << std::endl;
+  std::cout << "denorm min    = " << (std::numeric_limits<half>::denorm_min)() << "  (0x" << std::hex << half((std::numeric_limits<half>::denorm_min)()).x << ")" << std::endl;
+  std::cout << "infinity      = " << NumTraits<half>::infinity() << "  (0x" << std::hex << NumTraits<half>::infinity().x << ")" << std::endl;
+  std::cout << "quiet nan     = " << NumTraits<half>::quiet_NaN() << "  (0x" << std::hex << NumTraits<half>::quiet_NaN().x << ")" << std::endl;
+  std::cout << "signaling nan = " << std::numeric_limits<half>::signaling_NaN() << "  (0x" << std::hex << std::numeric_limits<half>::signaling_NaN().x << ")" << std::endl;
+
+  VERIFY(NumTraits<half>::IsSigned);
+
+  VERIFY_IS_EQUAL( std::numeric_limits<half>::infinity().x, half(std::numeric_limits<float>::infinity()).x );
+  VERIFY_IS_EQUAL( std::numeric_limits<half>::quiet_NaN().x, half(std::numeric_limits<float>::quiet_NaN()).x );
+  VERIFY_IS_EQUAL( std::numeric_limits<half>::signaling_NaN().x, half(std::numeric_limits<float>::signaling_NaN()).x );
+  VERIFY( (std::numeric_limits<half>::min)() > half(0.f) );
+  VERIFY( (std::numeric_limits<half>::denorm_min)() > half(0.f) );
+  VERIFY( (std::numeric_limits<half>::min)()/half(2) > half(0.f) );
+  VERIFY_IS_EQUAL( (std::numeric_limits<half>::denorm_min)()/half(2), half(0.f) );
+}
+
+void test_arithmetic()
+{
+  VERIFY_IS_EQUAL(float(half(2) + half(2)), 4);
+  VERIFY_IS_EQUAL(float(half(2) + half(-2)), 0);
+  VERIFY_IS_APPROX(float(half(0.33333f) + half(0.66667f)), 1.0f);
+  VERIFY_IS_EQUAL(float(half(2.0f) * half(-5.5f)), -11.0f);
+  VERIFY_IS_APPROX(float(half(1.0f) / half(3.0f)), 0.33333f);
+  VERIFY_IS_EQUAL(float(-half(4096.0f)), -4096.0f);
+  VERIFY_IS_EQUAL(float(-half(-4096.0f)), 4096.0f);
+}
+
+void test_comparison()
+{
+  VERIFY(half(1.0f) > half(0.5f));
+  VERIFY(half(0.5f) < half(1.0f));
+  VERIFY(!(half(1.0f) < half(0.5f)));
+  VERIFY(!(half(0.5f) > half(1.0f)));
+
+  VERIFY(!(half(4.0f) > half(4.0f)));
+  VERIFY(!(half(4.0f) < half(4.0f)));
+
+  VERIFY(!(half(0.0f) < half(-0.0f)));
+  VERIFY(!(half(-0.0f) < half(0.0f)));
+  VERIFY(!(half(0.0f) > half(-0.0f)));
+  VERIFY(!(half(-0.0f) > half(0.0f)));
+
+  VERIFY(half(0.2f) > half(-1.0f));
+  VERIFY(half(-1.0f) < half(0.2f));
+  VERIFY(half(-16.0f) < half(-15.0f));
+
+  VERIFY(half(1.0f) == half(1.0f));
+  VERIFY(half(1.0f) != half(2.0f));
+
+  // Comparisons with NaNs and infinities.
+#if !EIGEN_COMP_MSVC
+  // Visual Studio errors out on divisions by 0
+  VERIFY(!(half(0.0 / 0.0) == half(0.0 / 0.0)));
+  VERIFY(half(0.0 / 0.0) != half(0.0 / 0.0));
+
+  VERIFY(!(half(1.0) == half(0.0 / 0.0)));
+  VERIFY(!(half(1.0) < half(0.0 / 0.0)));
+  VERIFY(!(half(1.0) > half(0.0 / 0.0)));
+  VERIFY(half(1.0) != half(0.0 / 0.0));
+
+  VERIFY(half(1.0) < half(1.0 / 0.0));
+  VERIFY(half(1.0) > half(-1.0 / 0.0));
+#endif
+}
+
+void test_basic_functions()
+{
+  VERIFY_IS_EQUAL(float(numext::abs(half(3.5f))), 3.5f);
+  VERIFY_IS_EQUAL(float(abs(half(3.5f))), 3.5f);
+  VERIFY_IS_EQUAL(float(numext::abs(half(-3.5f))), 3.5f);
+  VERIFY_IS_EQUAL(float(abs(half(-3.5f))), 3.5f);
+
+  VERIFY_IS_EQUAL(float(numext::floor(half(3.5f))), 3.0f);
+  VERIFY_IS_EQUAL(float(floor(half(3.5f))), 3.0f);
+  VERIFY_IS_EQUAL(float(numext::floor(half(-3.5f))), -4.0f);
+  VERIFY_IS_EQUAL(float(floor(half(-3.5f))), -4.0f);
+
+  VERIFY_IS_EQUAL(float(numext::ceil(half(3.5f))), 4.0f);
+  VERIFY_IS_EQUAL(float(ceil(half(3.5f))), 4.0f);
+  VERIFY_IS_EQUAL(float(numext::ceil(half(-3.5f))), -3.0f);
+  VERIFY_IS_EQUAL(float(ceil(half(-3.5f))), -3.0f);
+
+  VERIFY_IS_APPROX(float(numext::sqrt(half(0.0f))), 0.0f);
+  VERIFY_IS_APPROX(float(sqrt(half(0.0f))), 0.0f);
+  VERIFY_IS_APPROX(float(numext::sqrt(half(4.0f))), 2.0f);
+  VERIFY_IS_APPROX(float(sqrt(half(4.0f))), 2.0f);
+
+  VERIFY_IS_APPROX(float(numext::pow(half(0.0f), half(1.0f))), 0.0f);
+  VERIFY_IS_APPROX(float(pow(half(0.0f), half(1.0f))), 0.0f);
+  VERIFY_IS_APPROX(float(numext::pow(half(2.0f), half(2.0f))), 4.0f);
+  VERIFY_IS_APPROX(float(pow(half(2.0f), half(2.0f))), 4.0f);
+
+  VERIFY_IS_EQUAL(float(numext::exp(half(0.0f))), 1.0f);
+  VERIFY_IS_EQUAL(float(exp(half(0.0f))), 1.0f);
+  VERIFY_IS_APPROX(float(numext::exp(half(EIGEN_PI))), 20.f + float(EIGEN_PI));
+  VERIFY_IS_APPROX(float(exp(half(EIGEN_PI))), 20.f + float(EIGEN_PI));
+
+  VERIFY_IS_EQUAL(float(numext::log(half(1.0f))), 0.0f);
+  VERIFY_IS_EQUAL(float(log(half(1.0f))), 0.0f);
+  VERIFY_IS_APPROX(float(numext::log(half(10.0f))), 2.30273f);
+  VERIFY_IS_APPROX(float(log(half(10.0f))), 2.30273f);
+
+  VERIFY_IS_EQUAL(float(numext::log1p(half(0.0f))), 0.0f);
+  VERIFY_IS_EQUAL(float(log1p(half(0.0f))), 0.0f);
+  VERIFY_IS_APPROX(float(numext::log1p(half(10.0f))), 2.3978953f);
+  VERIFY_IS_APPROX(float(log1p(half(10.0f))), 2.3978953f);
+}
+
+void test_trigonometric_functions()
+{
+  VERIFY_IS_APPROX(numext::cos(half(0.0f)), half(cosf(0.0f)));
+  VERIFY_IS_APPROX(cos(half(0.0f)), half(cosf(0.0f)));
+  VERIFY_IS_APPROX(numext::cos(half(EIGEN_PI)), half(cosf(EIGEN_PI)));
+  //VERIFY_IS_APPROX(numext::cos(half(EIGEN_PI/2)), half(cosf(EIGEN_PI/2)));
+  //VERIFY_IS_APPROX(numext::cos(half(3*EIGEN_PI/2)), half(cosf(3*EIGEN_PI/2)));
+  VERIFY_IS_APPROX(numext::cos(half(3.5f)), half(cosf(3.5f)));
+
+  VERIFY_IS_APPROX(numext::sin(half(0.0f)), half(sinf(0.0f)));
+  VERIFY_IS_APPROX(sin(half(0.0f)), half(sinf(0.0f)));
+  //  VERIFY_IS_APPROX(numext::sin(half(EIGEN_PI)), half(sinf(EIGEN_PI)));
+  VERIFY_IS_APPROX(numext::sin(half(EIGEN_PI/2)), half(sinf(EIGEN_PI/2)));
+  VERIFY_IS_APPROX(numext::sin(half(3*EIGEN_PI/2)), half(sinf(3*EIGEN_PI/2)));
+  VERIFY_IS_APPROX(numext::sin(half(3.5f)), half(sinf(3.5f)));
+
+  VERIFY_IS_APPROX(numext::tan(half(0.0f)), half(tanf(0.0f)));
+  VERIFY_IS_APPROX(tan(half(0.0f)), half(tanf(0.0f)));
+  //  VERIFY_IS_APPROX(numext::tan(half(EIGEN_PI)), half(tanf(EIGEN_PI)));
+  //  VERIFY_IS_APPROX(numext::tan(half(EIGEN_PI/2)), half(tanf(EIGEN_PI/2)));
+  //VERIFY_IS_APPROX(numext::tan(half(3*EIGEN_PI/2)), half(tanf(3*EIGEN_PI/2)));
+  VERIFY_IS_APPROX(numext::tan(half(3.5f)), half(tanf(3.5f)));
+}
+
+void test_array()
+{
+  typedef Array<half,1,Dynamic> ArrayXh;
+  Index size = internal::random<Index>(1,10);
+  Index i = internal::random<Index>(0,size-1);
+  ArrayXh a1 = ArrayXh::Random(size), a2 = ArrayXh::Random(size);
+  VERIFY_IS_APPROX( a1+a1, half(2)*a1 );
+  VERIFY( (a1.abs() >= half(0)).all() );
+  VERIFY_IS_APPROX( (a1*a1).sqrt(), a1.abs() );
+
+  VERIFY( ((a1.min)(a2) <= (a1.max)(a2)).all() );
+  a1(i) = half(-10.);
+  VERIFY_IS_EQUAL( a1.minCoeff(), half(-10.) );
+  a1(i) = half(10.);
+  VERIFY_IS_EQUAL( a1.maxCoeff(), half(10.) );
+
+  std::stringstream ss;
+  ss << a1;
+}
+
+void test_half_float()
+{
+  CALL_SUBTEST(test_conversion());
+  CALL_SUBTEST(test_numtraits());
+  CALL_SUBTEST(test_arithmetic());
+  CALL_SUBTEST(test_comparison());
+  CALL_SUBTEST(test_basic_functions());
+  CALL_SUBTEST(test_trigonometric_functions());
+  CALL_SUBTEST(test_array());
+}

ADDED   3rd_party/eigen/test/incomplete_cholesky.cpp
Index: 3rd_party/eigen/test/incomplete_cholesky.cpp
==================================================================
--- 3rd_party/eigen/test/incomplete_cholesky.cpp
+++ 3rd_party/eigen/test/incomplete_cholesky.cpp
@@ -0,0 +1,65 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+// #define EIGEN_DONT_VECTORIZE
+// #define EIGEN_MAX_ALIGN_BYTES 0
+#include "sparse_solver.h"
+#include <Eigen/IterativeLinearSolvers>
+#include <unsupported/Eigen/IterativeSolvers>
+
+template<typename T, typename I> void test_incomplete_cholesky_T()
+{
+  typedef SparseMatrix<T,0,I> SparseMatrixType;
+  ConjugateGradient<SparseMatrixType, Lower, IncompleteCholesky<T, Lower, AMDOrdering<I> > >        cg_illt_lower_amd;
+  ConjugateGradient<SparseMatrixType, Lower, IncompleteCholesky<T, Lower, NaturalOrdering<I> > >    cg_illt_lower_nat;
+  ConjugateGradient<SparseMatrixType, Upper, IncompleteCholesky<T, Upper, AMDOrdering<I> > >        cg_illt_upper_amd;
+  ConjugateGradient<SparseMatrixType, Upper, IncompleteCholesky<T, Upper, NaturalOrdering<I> > >    cg_illt_upper_nat;
+  ConjugateGradient<SparseMatrixType, Upper|Lower, IncompleteCholesky<T, Lower, AMDOrdering<I> > >  cg_illt_uplo_amd;
+  
+
+  CALL_SUBTEST( check_sparse_spd_solving(cg_illt_lower_amd) );
+  CALL_SUBTEST( check_sparse_spd_solving(cg_illt_lower_nat) );
+  CALL_SUBTEST( check_sparse_spd_solving(cg_illt_upper_amd) );
+  CALL_SUBTEST( check_sparse_spd_solving(cg_illt_upper_nat) );
+  CALL_SUBTEST( check_sparse_spd_solving(cg_illt_uplo_amd) );
+}
+
+void test_incomplete_cholesky()
+{
+  CALL_SUBTEST_1(( test_incomplete_cholesky_T<double,int>() ));
+  CALL_SUBTEST_2(( test_incomplete_cholesky_T<std::complex<double>, int>() ));
+  CALL_SUBTEST_3(( test_incomplete_cholesky_T<double,long int>() ));
+
+#ifdef EIGEN_TEST_PART_1
+    // regression for bug 1150
+  for(int N = 1; N<20; ++N)
+  {
+    Eigen::MatrixXd b( N, N );
+    b.setOnes();
+
+    Eigen::SparseMatrix<double> m( N, N );
+    m.reserve(Eigen::VectorXi::Constant(N,4));
+    for( int i = 0; i < N; ++i )
+    {
+        m.insert( i, i ) = 1;
+        m.coeffRef( i, i / 2 ) = 2;
+        m.coeffRef( i, i / 3 ) = 2;
+        m.coeffRef( i, i / 4 ) = 2;
+    }
+
+    Eigen::SparseMatrix<double> A;
+    A = m * m.transpose();
+
+    Eigen::ConjugateGradient<Eigen::SparseMatrix<double>,
+        Eigen::Lower | Eigen::Upper,
+        Eigen::IncompleteCholesky<double> > solver( A );
+    VERIFY(solver.preconditioner().info() == Eigen::Success);
+    VERIFY(solver.info() == Eigen::Success);
+  }
+#endif
+}

ADDED   3rd_party/eigen/test/inplace_decomposition.cpp
Index: 3rd_party/eigen/test/inplace_decomposition.cpp
==================================================================
--- 3rd_party/eigen/test/inplace_decomposition.cpp
+++ 3rd_party/eigen/test/inplace_decomposition.cpp
@@ -0,0 +1,110 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <Eigen/LU>
+#include <Eigen/Cholesky>
+#include <Eigen/QR>
+
+// This file test inplace decomposition through Ref<>, as supported by Cholesky, LU, and QR decompositions.
+
+template<typename DecType,typename MatrixType> void inplace(bool square = false, bool SPD = false)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> RhsType;
+  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> ResType;
+
+  Index rows = MatrixType::RowsAtCompileTime==Dynamic ? internal::random<Index>(2,EIGEN_TEST_MAX_SIZE/2) : Index(MatrixType::RowsAtCompileTime);
+  Index cols = MatrixType::ColsAtCompileTime==Dynamic ? (square?rows:internal::random<Index>(2,rows))    : Index(MatrixType::ColsAtCompileTime);
+
+  MatrixType A = MatrixType::Random(rows,cols);
+  RhsType b = RhsType::Random(rows);
+  ResType x(cols);
+
+  if(SPD)
+  {
+    assert(square);
+    A.topRows(cols) = A.topRows(cols).adjoint() * A.topRows(cols);
+    A.diagonal().array() += 1e-3;
+  }
+
+  MatrixType A0 = A;
+  MatrixType A1 = A;
+
+  DecType dec(A);
+
+  // Check that the content of A has been modified
+  VERIFY_IS_NOT_APPROX( A, A0 );
+
+  // Check that the decomposition is correct:
+  if(rows==cols)
+  {
+    VERIFY_IS_APPROX( A0 * (x = dec.solve(b)), b );
+  }
+  else
+  {
+    VERIFY_IS_APPROX( A0.transpose() * A0 * (x = dec.solve(b)), A0.transpose() * b );
+  }
+
+  // Check that modifying A breaks the current dec:
+  A.setRandom();
+  if(rows==cols)
+  {
+    VERIFY_IS_NOT_APPROX( A0 * (x = dec.solve(b)), b );
+  }
+  else
+  {
+    VERIFY_IS_NOT_APPROX( A0.transpose() * A0 * (x = dec.solve(b)), A0.transpose() * b );
+  }
+
+  // Check that calling compute(A1) does not modify A1:
+  A = A0;
+  dec.compute(A1);
+  VERIFY_IS_EQUAL(A0,A1);
+  VERIFY_IS_NOT_APPROX( A, A0 );
+  if(rows==cols)
+  {
+    VERIFY_IS_APPROX( A0 * (x = dec.solve(b)), b );
+  }
+  else
+  {
+    VERIFY_IS_APPROX( A0.transpose() * A0 * (x = dec.solve(b)), A0.transpose() * b );
+  }
+}
+
+
+void test_inplace_decomposition()
+{
+  EIGEN_UNUSED typedef Matrix<double,4,3> Matrix43d;
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1(( inplace<LLT<Ref<MatrixXd> >, MatrixXd>(true,true) ));
+    CALL_SUBTEST_1(( inplace<LLT<Ref<Matrix4d> >, Matrix4d>(true,true) ));
+
+    CALL_SUBTEST_2(( inplace<LDLT<Ref<MatrixXd> >, MatrixXd>(true,true) ));
+    CALL_SUBTEST_2(( inplace<LDLT<Ref<Matrix4d> >, Matrix4d>(true,true) ));
+
+    CALL_SUBTEST_3(( inplace<PartialPivLU<Ref<MatrixXd> >, MatrixXd>(true,false) ));
+    CALL_SUBTEST_3(( inplace<PartialPivLU<Ref<Matrix4d> >, Matrix4d>(true,false) ));
+
+    CALL_SUBTEST_4(( inplace<FullPivLU<Ref<MatrixXd> >, MatrixXd>(true,false) ));
+    CALL_SUBTEST_4(( inplace<FullPivLU<Ref<Matrix4d> >, Matrix4d>(true,false) ));
+
+    CALL_SUBTEST_5(( inplace<HouseholderQR<Ref<MatrixXd> >, MatrixXd>(false,false) ));
+    CALL_SUBTEST_5(( inplace<HouseholderQR<Ref<Matrix43d> >, Matrix43d>(false,false) ));
+
+    CALL_SUBTEST_6(( inplace<ColPivHouseholderQR<Ref<MatrixXd> >, MatrixXd>(false,false) ));
+    CALL_SUBTEST_6(( inplace<ColPivHouseholderQR<Ref<Matrix43d> >, Matrix43d>(false,false) ));
+
+    CALL_SUBTEST_7(( inplace<FullPivHouseholderQR<Ref<MatrixXd> >, MatrixXd>(false,false) ));
+    CALL_SUBTEST_7(( inplace<FullPivHouseholderQR<Ref<Matrix43d> >, Matrix43d>(false,false) ));
+
+    CALL_SUBTEST_8(( inplace<CompleteOrthogonalDecomposition<Ref<MatrixXd> >, MatrixXd>(false,false) ));
+    CALL_SUBTEST_8(( inplace<CompleteOrthogonalDecomposition<Ref<Matrix43d> >, Matrix43d>(false,false) ));
+  }
+}

Index: 3rd_party/eigen/test/integer_types.cpp
==================================================================
--- 3rd_party/eigen/test/integer_types.cpp
+++ 3rd_party/eigen/test/integer_types.cpp
@@ -156,6 +156,14 @@
     CALL_SUBTEST_7( integer_type_tests(Matrix<long long, 11, 13>()) );
     CALL_SUBTEST_7( signed_integer_type_tests(Matrix<long long, 11, 13>()) );
 
     CALL_SUBTEST_8( integer_type_tests(Matrix<unsigned long long, Dynamic, 5>(1, 5)) );
   }
+#ifdef EIGEN_TEST_PART_9
+  VERIFY_IS_EQUAL(internal::scalar_div_cost<int>::value, 8);
+  VERIFY_IS_EQUAL(internal::scalar_div_cost<unsigned int>::value, 8);
+  if(sizeof(long)>sizeof(int)) {
+    VERIFY(internal::scalar_div_cost<long>::value > internal::scalar_div_cost<int>::value);
+    VERIFY(internal::scalar_div_cost<unsigned long>::value > internal::scalar_div_cost<int>::value);
+  }
+#endif
 }

Index: 3rd_party/eigen/test/inverse.cpp
==================================================================
--- 3rd_party/eigen/test/inverse.cpp
+++ 3rd_party/eigen/test/inverse.cpp
@@ -66,10 +66,19 @@
   m3.computeInverseAndDetWithCheck(m4, det, invertible);
   VERIFY( rows==1 ? invertible : !invertible );
   VERIFY_IS_MUCH_SMALLER_THAN(abs(det-m3.determinant()), RealScalar(1));
   m3.computeInverseWithCheck(m4, invertible);
   VERIFY( rows==1 ? invertible : !invertible );
+  
+  // check with submatrices
+  {
+    Matrix<Scalar, MatrixType::RowsAtCompileTime+1, MatrixType::RowsAtCompileTime+1, MatrixType::Options> m5;
+    m5.setRandom();
+    m5.topLeftCorner(rows,rows) = m1;
+    m2 = m5.template topLeftCorner<MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime>().inverse();
+    VERIFY_IS_APPROX( (m5.template topLeftCorner<MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime>()), m2.inverse() );
+  }
 #endif
 
   // check in-place inversion
   if(MatrixType::RowsAtCompileTime>=2 && MatrixType::RowsAtCompileTime<=4)
   {
@@ -91,14 +100,18 @@
     CALL_SUBTEST_1( inverse(Matrix<double,1,1>()) );
     CALL_SUBTEST_2( inverse(Matrix2d()) );
     CALL_SUBTEST_3( inverse(Matrix3f()) );
     CALL_SUBTEST_4( inverse(Matrix4f()) );
     CALL_SUBTEST_4( inverse(Matrix<float,4,4,DontAlign>()) );
+    
     s = internal::random<int>(50,320); 
     CALL_SUBTEST_5( inverse(MatrixXf(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+    
     s = internal::random<int>(25,100);
     CALL_SUBTEST_6( inverse(MatrixXcd(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+    
     CALL_SUBTEST_7( inverse(Matrix4d()) );
     CALL_SUBTEST_7( inverse(Matrix<double,4,4,DontAlign>()) );
   }
-  TEST_SET_BUT_UNUSED_VARIABLE(s)
 }

ADDED   3rd_party/eigen/test/is_same_dense.cpp
Index: 3rd_party/eigen/test/is_same_dense.cpp
==================================================================
--- 3rd_party/eigen/test/is_same_dense.cpp
+++ 3rd_party/eigen/test/is_same_dense.cpp
@@ -0,0 +1,33 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+using internal::is_same_dense;
+
+void test_is_same_dense()
+{
+  typedef Matrix<double,Dynamic,Dynamic,ColMajor> ColMatrixXd;
+  ColMatrixXd m1(10,10);
+  Ref<ColMatrixXd> ref_m1(m1);
+  Ref<const ColMatrixXd> const_ref_m1(m1);
+  VERIFY(is_same_dense(m1,m1));
+  VERIFY(is_same_dense(m1,ref_m1));
+  VERIFY(is_same_dense(const_ref_m1,m1));
+  VERIFY(is_same_dense(const_ref_m1,ref_m1));
+  
+  VERIFY(is_same_dense(m1.block(0,0,m1.rows(),m1.cols()),m1));
+  VERIFY(!is_same_dense(m1.row(0),m1.col(0)));
+  
+  Ref<const ColMatrixXd> const_ref_m1_row(m1.row(1));
+  VERIFY(!is_same_dense(m1.row(1),const_ref_m1_row));
+  
+  Ref<const ColMatrixXd> const_ref_m1_col(m1.col(1));
+  VERIFY(is_same_dense(m1.col(1),const_ref_m1_col));
+}

Index: 3rd_party/eigen/test/jacobisvd.cpp
==================================================================
--- 3rd_party/eigen/test/jacobisvd.cpp
+++ 3rd_party/eigen/test/jacobisvd.cpp
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -12,282 +12,50 @@
 #define EIGEN_STACK_ALLOCATION_LIMIT 0
 #define EIGEN_RUNTIME_NO_MALLOC
 #include "main.h"
 #include <Eigen/SVD>
 
-template<typename MatrixType, int QRPreconditioner>
-void jacobisvd_check_full(const MatrixType& m, const JacobiSVD<MatrixType, QRPreconditioner>& svd)
-{
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime
-  };
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime> MatrixUType;
-  typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime> MatrixVType;
-
-  MatrixType sigma = MatrixType::Zero(rows,cols);
-  sigma.diagonal() = svd.singularValues().template cast<Scalar>();
-  MatrixUType u = svd.matrixU();
-  MatrixVType v = svd.matrixV();
-
-  VERIFY_IS_APPROX(m, u * sigma * v.adjoint());
-  VERIFY_IS_UNITARY(u);
-  VERIFY_IS_UNITARY(v);
-}
-
-template<typename MatrixType, int QRPreconditioner>
-void jacobisvd_compare_to_full(const MatrixType& m,
-                               unsigned int computationOptions,
-                               const JacobiSVD<MatrixType, QRPreconditioner>& referenceSvd)
-{
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-  Index diagSize = (std::min)(rows, cols);
-
-  JacobiSVD<MatrixType, QRPreconditioner> svd(m, computationOptions);
-
-  VERIFY_IS_APPROX(svd.singularValues(), referenceSvd.singularValues());
-  if(computationOptions & ComputeFullU)
-    VERIFY_IS_APPROX(svd.matrixU(), referenceSvd.matrixU());
-  if(computationOptions & ComputeThinU)
-    VERIFY_IS_APPROX(svd.matrixU(), referenceSvd.matrixU().leftCols(diagSize));
-  if(computationOptions & ComputeFullV)
-    VERIFY_IS_APPROX(svd.matrixV(), referenceSvd.matrixV());
-  if(computationOptions & ComputeThinV)
-    VERIFY_IS_APPROX(svd.matrixV(), referenceSvd.matrixV().leftCols(diagSize));
-}
-
-template<typename MatrixType, int QRPreconditioner>
-void jacobisvd_solve(const MatrixType& m, unsigned int computationOptions)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime
-  };
-
-  typedef Matrix<Scalar, RowsAtCompileTime, Dynamic> RhsType;
-  typedef Matrix<Scalar, ColsAtCompileTime, Dynamic> SolutionType;
-
-  RhsType rhs = RhsType::Random(rows, internal::random<Index>(1, cols));
-  JacobiSVD<MatrixType, QRPreconditioner> svd(m, computationOptions);
-
-       if(internal::is_same<RealScalar,double>::value) svd.setThreshold(1e-8);
-  else if(internal::is_same<RealScalar,float>::value)  svd.setThreshold(1e-4);
-  
-  SolutionType x = svd.solve(rhs);
-  
-  RealScalar residual = (m*x-rhs).norm();
-  // Check that there is no significantly better solution in the neighborhood of x
-  if(!test_isMuchSmallerThan(residual,rhs.norm()))
-  {
-    // If the residual is very small, then we have an exact solution, so we are already good.
-    for(int k=0;k<x.rows();++k)
-    {
-      SolutionType y(x);
-      y.row(k).array() += 2*NumTraits<RealScalar>::epsilon();
-      RealScalar residual_y = (m*y-rhs).norm();
-      VERIFY( test_isApprox(residual_y,residual) || residual < residual_y );
-      
-      y.row(k) = x.row(k).array() - 2*NumTraits<RealScalar>::epsilon();
-      residual_y = (m*y-rhs).norm();
-      VERIFY( test_isApprox(residual_y,residual) || residual < residual_y );
-    }
-  }
-  
-  // evaluate normal equation which works also for least-squares solutions
-  if(internal::is_same<RealScalar,double>::value)
-  {
-    // This test is not stable with single precision.
-    // This is probably because squaring m signicantly affects the precision.
-    VERIFY_IS_APPROX(m.adjoint()*m*x,m.adjoint()*rhs);
-  }
-  
-  // check minimal norm solutions
-  {
-    // generate a full-rank m x n problem with m<n
-    enum {
-      RankAtCompileTime2 = ColsAtCompileTime==Dynamic ? Dynamic : (ColsAtCompileTime)/2+1,
-      RowsAtCompileTime3 = ColsAtCompileTime==Dynamic ? Dynamic : ColsAtCompileTime+1
-    };
-    typedef Matrix<Scalar, RankAtCompileTime2, ColsAtCompileTime> MatrixType2;
-    typedef Matrix<Scalar, RankAtCompileTime2, 1> RhsType2;
-    typedef Matrix<Scalar, ColsAtCompileTime, RankAtCompileTime2> MatrixType2T;
-    Index rank = RankAtCompileTime2==Dynamic ? internal::random<Index>(1,cols) : Index(RankAtCompileTime2);
-    MatrixType2 m2(rank,cols);
-    int guard = 0;
-    do {
-      m2.setRandom();
-    } while(m2.jacobiSvd().setThreshold(test_precision<Scalar>()).rank()!=rank && (++guard)<10);
-    VERIFY(guard<10);
-    RhsType2 rhs2 = RhsType2::Random(rank);
-    // use QR to find a reference minimal norm solution
-    HouseholderQR<MatrixType2T> qr(m2.adjoint());
-    Matrix<Scalar,Dynamic,1> tmp = qr.matrixQR().topLeftCorner(rank,rank).template triangularView<Upper>().adjoint().solve(rhs2);
-    tmp.conservativeResize(cols);
-    tmp.tail(cols-rank).setZero();
-    SolutionType x21 = qr.householderQ() * tmp;
-    // now check with SVD
-    JacobiSVD<MatrixType2, ColPivHouseholderQRPreconditioner> svd2(m2, computationOptions);
-    SolutionType x22 = svd2.solve(rhs2);
-    VERIFY_IS_APPROX(m2*x21, rhs2);
-    VERIFY_IS_APPROX(m2*x22, rhs2);
-    VERIFY_IS_APPROX(x21, x22);
-    
-    // Now check with a rank deficient matrix
-    typedef Matrix<Scalar, RowsAtCompileTime3, ColsAtCompileTime> MatrixType3;
-    typedef Matrix<Scalar, RowsAtCompileTime3, 1> RhsType3;
-    Index rows3 = RowsAtCompileTime3==Dynamic ? internal::random<Index>(rank+1,2*cols) : Index(RowsAtCompileTime3);
-    Matrix<Scalar,RowsAtCompileTime3,Dynamic> C = Matrix<Scalar,RowsAtCompileTime3,Dynamic>::Random(rows3,rank);
-    MatrixType3 m3 = C * m2;
-    RhsType3 rhs3 = C * rhs2;
-    JacobiSVD<MatrixType3, ColPivHouseholderQRPreconditioner> svd3(m3, computationOptions);
-    SolutionType x3 = svd3.solve(rhs3);
-    if(svd3.rank()!=rank) {
-      std::cout << m3 << "\n\n";
-      std::cout << svd3.singularValues().transpose() << "\n";
-    std::cout << svd3.rank() << " == " << rank << "\n";
-    std::cout << x21.norm() << " == " << x3.norm() << "\n";
-    }
-//     VERIFY_IS_APPROX(m3*x3, rhs3);
-    VERIFY_IS_APPROX(m3*x21, rhs3);
-    VERIFY_IS_APPROX(m2*x3, rhs2);
-    
-    VERIFY_IS_APPROX(x21, x3);
-  }
-}
-
-template<typename MatrixType, int QRPreconditioner>
-void jacobisvd_test_all_computation_options(const MatrixType& m)
-{
-  if (QRPreconditioner == NoQRPreconditioner && m.rows() != m.cols())
-    return;
-  JacobiSVD<MatrixType, QRPreconditioner> fullSvd(m, ComputeFullU|ComputeFullV);
-  CALL_SUBTEST(( jacobisvd_check_full(m, fullSvd) ));
-  CALL_SUBTEST(( jacobisvd_solve<MatrixType, QRPreconditioner>(m, ComputeFullU | ComputeFullV) ));
-  
-  #if defined __INTEL_COMPILER
-  // remark #111: statement is unreachable
-  #pragma warning disable 111
-  #endif
-  if(QRPreconditioner == FullPivHouseholderQRPreconditioner)
-    return;
-
-  CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeFullU, fullSvd) ));
-  CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeFullV, fullSvd) ));
-  CALL_SUBTEST(( jacobisvd_compare_to_full(m, 0, fullSvd) ));
-
-  if (MatrixType::ColsAtCompileTime == Dynamic) {
-    // thin U/V are only available with dynamic number of columns
-    CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeFullU|ComputeThinV, fullSvd) ));
-    CALL_SUBTEST(( jacobisvd_compare_to_full(m,              ComputeThinV, fullSvd) ));
-    CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeThinU|ComputeFullV, fullSvd) ));
-    CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeThinU             , fullSvd) ));
-    CALL_SUBTEST(( jacobisvd_compare_to_full(m, ComputeThinU|ComputeThinV, fullSvd) ));
-    CALL_SUBTEST(( jacobisvd_solve<MatrixType, QRPreconditioner>(m, ComputeFullU | ComputeThinV) ));
-    CALL_SUBTEST(( jacobisvd_solve<MatrixType, QRPreconditioner>(m, ComputeThinU | ComputeFullV) ));
-    CALL_SUBTEST(( jacobisvd_solve<MatrixType, QRPreconditioner>(m, ComputeThinU | ComputeThinV) ));
-
-    // test reconstruction
-    typedef typename MatrixType::Index Index;
-    Index diagSize = (std::min)(m.rows(), m.cols());
-    JacobiSVD<MatrixType, QRPreconditioner> svd(m, ComputeThinU | ComputeThinV);
-    VERIFY_IS_APPROX(m, svd.matrixU().leftCols(diagSize) * svd.singularValues().asDiagonal() * svd.matrixV().leftCols(diagSize).adjoint());
-  }
-}
-
-template<typename MatrixType>
-void jacobisvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
-{
-  MatrixType m = a;
-  if(pickrandom)
-  {
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
-    Index diagSize = (std::min)(a.rows(), a.cols());
-    RealScalar s = std::numeric_limits<RealScalar>::max_exponent10/4;
-    s = internal::random<RealScalar>(1,s);
-    Matrix<RealScalar,Dynamic,1> d =  Matrix<RealScalar,Dynamic,1>::Random(diagSize);
-    for(Index k=0; k<diagSize; ++k)
-      d(k) = d(k)*std::pow(RealScalar(10),internal::random<RealScalar>(-s,s));
-    m = Matrix<Scalar,Dynamic,Dynamic>::Random(a.rows(),diagSize) * d.asDiagonal() * Matrix<Scalar,Dynamic,Dynamic>::Random(diagSize,a.cols());
-    // cancel some coeffs
-    Index n  = internal::random<Index>(0,m.size()-1);
-    for(Index i=0; i<n; ++i)
-      m(internal::random<Index>(0,m.rows()-1), internal::random<Index>(0,m.cols()-1)) = Scalar(0);
-  }
-
-  CALL_SUBTEST(( jacobisvd_test_all_computation_options<MatrixType, FullPivHouseholderQRPreconditioner>(m) ));
-  CALL_SUBTEST(( jacobisvd_test_all_computation_options<MatrixType, ColPivHouseholderQRPreconditioner>(m) ));
-  CALL_SUBTEST(( jacobisvd_test_all_computation_options<MatrixType, HouseholderQRPreconditioner>(m) ));
-  CALL_SUBTEST(( jacobisvd_test_all_computation_options<MatrixType, NoQRPreconditioner>(m) ));
-}
-
-template<typename MatrixType> void jacobisvd_verify_assert(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime
-  };
-
-  typedef Matrix<Scalar, RowsAtCompileTime, 1> RhsType;
-
-  RhsType rhs(rows);
-
-  JacobiSVD<MatrixType> svd;
-  VERIFY_RAISES_ASSERT(svd.matrixU())
-  VERIFY_RAISES_ASSERT(svd.singularValues())
-  VERIFY_RAISES_ASSERT(svd.matrixV())
-  VERIFY_RAISES_ASSERT(svd.solve(rhs))
-
-  MatrixType a = MatrixType::Zero(rows, cols);
-  a.setZero();
-  svd.compute(a, 0);
-  VERIFY_RAISES_ASSERT(svd.matrixU())
-  VERIFY_RAISES_ASSERT(svd.matrixV())
-  svd.singularValues();
-  VERIFY_RAISES_ASSERT(svd.solve(rhs))
-
-  if (ColsAtCompileTime == Dynamic)
-  {
-    svd.compute(a, ComputeThinU);
-    svd.matrixU();
-    VERIFY_RAISES_ASSERT(svd.matrixV())
-    VERIFY_RAISES_ASSERT(svd.solve(rhs))
-
-    svd.compute(a, ComputeThinV);
-    svd.matrixV();
-    VERIFY_RAISES_ASSERT(svd.matrixU())
-    VERIFY_RAISES_ASSERT(svd.solve(rhs))
-
-    JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner> svd_fullqr;
-    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeFullU|ComputeThinV))
-    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeThinV))
-    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeFullV))
-  }
-  else
-  {
-    VERIFY_RAISES_ASSERT(svd.compute(a, ComputeThinU))
-    VERIFY_RAISES_ASSERT(svd.compute(a, ComputeThinV))
+#define SVD_DEFAULT(M) JacobiSVD<M>
+#define SVD_FOR_MIN_NORM(M) JacobiSVD<M,ColPivHouseholderQRPreconditioner>
+#include "svd_common.h"
+
+// Check all variants of JacobiSVD
+template<typename MatrixType>
+void jacobisvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
+{
+  MatrixType m = a;
+  if(pickrandom)
+    svd_fill_random(m);
+
+  CALL_SUBTEST(( svd_test_all_computation_options<JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner> >(m, true)  )); // check full only
+  CALL_SUBTEST(( svd_test_all_computation_options<JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>  >(m, false) ));
+  CALL_SUBTEST(( svd_test_all_computation_options<JacobiSVD<MatrixType, HouseholderQRPreconditioner>        >(m, false) ));
+  if(m.rows()==m.cols())
+    CALL_SUBTEST(( svd_test_all_computation_options<JacobiSVD<MatrixType, NoQRPreconditioner>               >(m, false) ));
+}
+
+template<typename MatrixType> void jacobisvd_verify_assert(const MatrixType& m)
+{
+  svd_verify_assert<JacobiSVD<MatrixType> >(m);
+  typedef typename MatrixType::Index Index;
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  enum {
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime
+  };
+
+
+  MatrixType a = MatrixType::Zero(rows, cols);
+  a.setZero();
+
+  if (ColsAtCompileTime == Dynamic)
+  {
+    JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner> svd_fullqr;
+    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeFullU|ComputeThinV))
+    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeThinV))
+    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeFullV))
   }
 }
 
 template<typename MatrixType>
 void jacobisvd_method()
@@ -300,130 +68,21 @@
   VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixU());
   VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixV());
   VERIFY_IS_APPROX(m.jacobiSvd(ComputeFullU|ComputeFullV).solve(m), m);
 }
 
-// work around stupid msvc error when constructing at compile time an expression that involves
-// a division by zero, even if the numeric type has floating point
-template<typename Scalar>
-EIGEN_DONT_INLINE Scalar zero() { return Scalar(0); }
-
-// workaround aggressive optimization in ICC
-template<typename T> EIGEN_DONT_INLINE  T sub(T a, T b) { return a - b; }
-
-template<typename MatrixType>
-void jacobisvd_inf_nan()
-{
-  // all this function does is verify we don't iterate infinitely on nan/inf values
-
-  JacobiSVD<MatrixType> svd;
-  typedef typename MatrixType::Scalar Scalar;
-  Scalar some_inf = Scalar(1) / zero<Scalar>();
-  VERIFY(sub(some_inf, some_inf) != sub(some_inf, some_inf));
-  svd.compute(MatrixType::Constant(10,10,some_inf), ComputeFullU | ComputeFullV);
-
-  Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
-  VERIFY(nan != nan);
-  svd.compute(MatrixType::Constant(10,10,nan), ComputeFullU | ComputeFullV);
-
-  MatrixType m = MatrixType::Zero(10,10);
-  m(internal::random<int>(0,9), internal::random<int>(0,9)) = some_inf;
-  svd.compute(m, ComputeFullU | ComputeFullV);
-
-  m = MatrixType::Zero(10,10);
-  m(internal::random<int>(0,9), internal::random<int>(0,9)) = nan;
-  svd.compute(m, ComputeFullU | ComputeFullV);
-  
-  // regression test for bug 791
-  m.resize(3,3);
-  m << 0,    2*NumTraits<Scalar>::epsilon(),  0.5,
-       0,   -0.5,                             0,
-       nan,  0,                               0;
-  svd.compute(m, ComputeFullU | ComputeFullV);
-}
-
-// Regression test for bug 286: JacobiSVD loops indefinitely with some
-// matrices containing denormal numbers.
-void jacobisvd_bug286()
-{
-#if defined __INTEL_COMPILER
-// shut up warning #239: floating point underflow
-#pragma warning push
-#pragma warning disable 239
-#endif
-  Matrix2d M;
-  M << -7.90884e-313, -4.94e-324,
-                 0, 5.60844e-313;
-#if defined __INTEL_COMPILER
-#pragma warning pop
-#endif
-  JacobiSVD<Matrix2d> svd;
-  svd.compute(M); // just check we don't loop indefinitely
-}
-
-void jacobisvd_preallocate()
-{
-  Vector3f v(3.f, 2.f, 1.f);
-  MatrixXf m = v.asDiagonal();
-
-  internal::set_is_malloc_allowed(false);
-  VERIFY_RAISES_ASSERT(VectorXf tmp(10);)
-  JacobiSVD<MatrixXf> svd;
-  internal::set_is_malloc_allowed(true);
-  svd.compute(m);
-  VERIFY_IS_APPROX(svd.singularValues(), v);
-
-  JacobiSVD<MatrixXf> svd2(3,3);
-  internal::set_is_malloc_allowed(false);
-  svd2.compute(m);
-  internal::set_is_malloc_allowed(true);
-  VERIFY_IS_APPROX(svd2.singularValues(), v);
-  VERIFY_RAISES_ASSERT(svd2.matrixU());
-  VERIFY_RAISES_ASSERT(svd2.matrixV());
-  svd2.compute(m, ComputeFullU | ComputeFullV);
-  VERIFY_IS_APPROX(svd2.matrixU(), Matrix3f::Identity());
-  VERIFY_IS_APPROX(svd2.matrixV(), Matrix3f::Identity());
-  internal::set_is_malloc_allowed(false);
-  svd2.compute(m);
-  internal::set_is_malloc_allowed(true);
-
-  JacobiSVD<MatrixXf> svd3(3,3,ComputeFullU|ComputeFullV);
-  internal::set_is_malloc_allowed(false);
-  svd2.compute(m);
-  internal::set_is_malloc_allowed(true);
-  VERIFY_IS_APPROX(svd2.singularValues(), v);
-  VERIFY_IS_APPROX(svd2.matrixU(), Matrix3f::Identity());
-  VERIFY_IS_APPROX(svd2.matrixV(), Matrix3f::Identity());
-  internal::set_is_malloc_allowed(false);
-  svd2.compute(m, ComputeFullU|ComputeFullV);
-  internal::set_is_malloc_allowed(true);
-}
-
 void test_jacobisvd()
 {
   CALL_SUBTEST_3(( jacobisvd_verify_assert(Matrix3f()) ));
   CALL_SUBTEST_4(( jacobisvd_verify_assert(Matrix4d()) ));
   CALL_SUBTEST_7(( jacobisvd_verify_assert(MatrixXf(10,12)) ));
   CALL_SUBTEST_8(( jacobisvd_verify_assert(MatrixXcd(7,5)) ));
+  
+  CALL_SUBTEST_11(svd_all_trivial_2x2(jacobisvd<Matrix2cd>));
+  CALL_SUBTEST_12(svd_all_trivial_2x2(jacobisvd<Matrix2d>));
 
   for(int i = 0; i < g_repeat; i++) {
-    Matrix2cd m;
-    m << 0, 1,
-         0, 1;
-    CALL_SUBTEST_1(( jacobisvd(m, false) ));
-    m << 1, 0,
-         1, 0;
-    CALL_SUBTEST_1(( jacobisvd(m, false) ));
-
-    Matrix2d n;
-    n << 0, 0,
-         0, 0;
-    CALL_SUBTEST_2(( jacobisvd(n, false) ));
-    n << 0, 0,
-         0, 1;
-    CALL_SUBTEST_2(( jacobisvd(n, false) ));
-    
     CALL_SUBTEST_3(( jacobisvd<Matrix3f>() ));
     CALL_SUBTEST_4(( jacobisvd<Matrix4d>() ));
     CALL_SUBTEST_5(( jacobisvd<Matrix<float,3,5> >() ));
     CALL_SUBTEST_6(( jacobisvd<Matrix<double,Dynamic,2> >(Matrix<double,Dynamic,2>(10,2)) ));
 
@@ -438,12 +97,18 @@
     CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(r,c)) ));
     (void) r;
     (void) c;
 
     // Test on inf/nan matrix
-    CALL_SUBTEST_7( jacobisvd_inf_nan<MatrixXf>() );
-    CALL_SUBTEST_10( jacobisvd_inf_nan<MatrixXd>() );
+    CALL_SUBTEST_7(  (svd_inf_nan<JacobiSVD<MatrixXf>, MatrixXf>()) );
+    CALL_SUBTEST_10( (svd_inf_nan<JacobiSVD<MatrixXd>, MatrixXd>()) );
+
+    // bug1395 test compile-time vectors as input
+    CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,6,1>()) ));
+    CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,1,6>()) ));
+    CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,Dynamic,1>(r)) ));
+    CALL_SUBTEST_13(( jacobisvd_verify_assert(Matrix<double,1,Dynamic>(c)) ));
   }
 
   CALL_SUBTEST_7(( jacobisvd<MatrixXf>(MatrixXf(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) ));
   CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3))) ));
 
@@ -453,10 +118,9 @@
 
   // Test problem size constructors
   CALL_SUBTEST_7( JacobiSVD<MatrixXf>(10,10) );
 
   // Check that preallocation avoids subsequent mallocs
-  CALL_SUBTEST_9( jacobisvd_preallocate() );
+  CALL_SUBTEST_9( svd_preallocate<void>() );
 
-  // Regression check for bug 286
-  CALL_SUBTEST_2( jacobisvd_bug286() );
+  CALL_SUBTEST_2( svd_underoverflow<void>() );
 }

Index: 3rd_party/eigen/test/linearstructure.cpp
==================================================================
--- 3rd_party/eigen/test/linearstructure.cpp
+++ 3rd_party/eigen/test/linearstructure.cpp
@@ -1,14 +1,18 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+static bool g_called;
+#define EIGEN_SCALAR_BINARY_OP_PLUGIN { g_called |= (!internal::is_same<LhsScalar,RhsScalar>::value); }
+
 #include "main.h"
 
 template<typename MatrixType> void linearStructure(const MatrixType& m)
 {
   using std::abs;
@@ -15,10 +19,11 @@
   /* this test covers the following files:
      CwiseUnaryOp.h, CwiseBinaryOp.h, SelfCwiseBinaryOp.h 
   */
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
 
   Index rows = m.rows();
   Index cols = m.cols();
 
   // this test relies a lot on Random.h, and there's not much more that we can do
@@ -26,11 +31,11 @@
   MatrixType m1 = MatrixType::Random(rows, cols),
              m2 = MatrixType::Random(rows, cols),
              m3(rows, cols);
 
   Scalar s1 = internal::random<Scalar>();
-  while (abs(s1)<1e-3) s1 = internal::random<Scalar>();
+  while (abs(s1)<RealScalar(1e-3)) s1 = internal::random<Scalar>();
 
   Index r = internal::random<Index>(0, rows-1),
         c = internal::random<Index>(0, cols-1);
 
   VERIFY_IS_APPROX(-(-m1),                  m1);
@@ -65,13 +70,53 @@
   VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
   VERIFY_IS_APPROX(m1.cwiseProduct(m1.block(0,0,rows,cols)), m1.cwiseProduct(m1));
   VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
   VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1);
 }
+
+// Make sure that complex * real and real * complex are properly optimized
+template<typename MatrixType> void real_complex(DenseIndex rows = MatrixType::RowsAtCompileTime, DenseIndex cols = MatrixType::ColsAtCompileTime)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  
+  RealScalar s = internal::random<RealScalar>();
+  MatrixType m1 = MatrixType::Random(rows, cols);
+  
+  g_called = false;
+  VERIFY_IS_APPROX(s*m1, Scalar(s)*m1);
+  VERIFY(g_called && "real * matrix<complex> not properly optimized");
+  
+  g_called = false;
+  VERIFY_IS_APPROX(m1*s, m1*Scalar(s));
+  VERIFY(g_called && "matrix<complex> * real not properly optimized");
+  
+  g_called = false;
+  VERIFY_IS_APPROX(m1/s, m1/Scalar(s));
+  VERIFY(g_called && "matrix<complex> / real not properly optimized");
+
+  g_called = false;
+  VERIFY_IS_APPROX(s+m1.array(), Scalar(s)+m1.array());
+  VERIFY(g_called && "real + matrix<complex> not properly optimized");
+
+  g_called = false;
+  VERIFY_IS_APPROX(m1.array()+s, m1.array()+Scalar(s));
+  VERIFY(g_called && "matrix<complex> + real not properly optimized");
+
+  g_called = false;
+  VERIFY_IS_APPROX(s-m1.array(), Scalar(s)-m1.array());
+  VERIFY(g_called && "real - matrix<complex> not properly optimized");
+
+  g_called = false;
+  VERIFY_IS_APPROX(m1.array()-s, m1.array()-Scalar(s));
+  VERIFY(g_called && "matrix<complex> - real not properly optimized");
+}
 
 void test_linearstructure()
 {
+  g_called = true;
+  VERIFY(g_called); // avoid `unneeded-internal-declaration` warning.
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( linearStructure(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_2( linearStructure(Matrix2f()) );
     CALL_SUBTEST_3( linearStructure(Vector3d()) );
     CALL_SUBTEST_4( linearStructure(Matrix4d()) );
@@ -78,7 +123,27 @@
     CALL_SUBTEST_5( linearStructure(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
     CALL_SUBTEST_6( linearStructure(MatrixXf (internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_7( linearStructure(MatrixXi (internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_8( linearStructure(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
     CALL_SUBTEST_9( linearStructure(ArrayXXf (internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_10( linearStructure(ArrayXXcf (internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    
+    CALL_SUBTEST_11( real_complex<Matrix4cd>() );
+    CALL_SUBTEST_11( real_complex<MatrixXcf>(10,10) );
+    CALL_SUBTEST_11( real_complex<ArrayXXcf>(10,10) );
+  }
+  
+#ifdef EIGEN_TEST_PART_4
+  {
+    // make sure that /=scalar and /scalar do not overflow
+    // rational: 1.0/4.94e-320 overflow, but m/4.94e-320 should not
+    Matrix4d m2, m3;
+    m3 = m2 =  Matrix4d::Random()*1e-20;
+    m2 = m2 / 4.9e-320;
+    VERIFY_IS_APPROX(m2.cwiseQuotient(m2), Matrix4d::Ones());
+    m3 /= 4.9e-320;
+    VERIFY_IS_APPROX(m3.cwiseQuotient(m3), Matrix4d::Ones());
+    
+    
   }
+#endif
 }

ADDED   3rd_party/eigen/test/lscg.cpp
Index: 3rd_party/eigen/test/lscg.cpp
==================================================================
--- 3rd_party/eigen/test/lscg.cpp
+++ 3rd_party/eigen/test/lscg.cpp
@@ -0,0 +1,37 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Gael Guennebaud <g.gael@free.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "sparse_solver.h"
+#include <Eigen/IterativeLinearSolvers>
+
+template<typename T> void test_lscg_T()
+{
+  LeastSquaresConjugateGradient<SparseMatrix<T> > lscg_colmajor_diag;
+  LeastSquaresConjugateGradient<SparseMatrix<T>, IdentityPreconditioner> lscg_colmajor_I;
+  LeastSquaresConjugateGradient<SparseMatrix<T,RowMajor> > lscg_rowmajor_diag;
+  LeastSquaresConjugateGradient<SparseMatrix<T,RowMajor>, IdentityPreconditioner> lscg_rowmajor_I;
+
+  CALL_SUBTEST( check_sparse_square_solving(lscg_colmajor_diag)  );
+  CALL_SUBTEST( check_sparse_square_solving(lscg_colmajor_I)     );
+  
+  CALL_SUBTEST( check_sparse_leastsquare_solving(lscg_colmajor_diag)  );
+  CALL_SUBTEST( check_sparse_leastsquare_solving(lscg_colmajor_I)     );
+
+  CALL_SUBTEST( check_sparse_square_solving(lscg_rowmajor_diag)  );
+  CALL_SUBTEST( check_sparse_square_solving(lscg_rowmajor_I)     );
+
+  CALL_SUBTEST( check_sparse_leastsquare_solving(lscg_rowmajor_diag)  );
+  CALL_SUBTEST( check_sparse_leastsquare_solving(lscg_rowmajor_I)     );
+}
+
+void test_lscg()
+{
+  CALL_SUBTEST_1(test_lscg_T<double>());
+  CALL_SUBTEST_2(test_lscg_T<std::complex<double> >());
+}

Index: 3rd_party/eigen/test/lu.cpp
==================================================================
--- 3rd_party/eigen/test/lu.cpp
+++ 3rd_party/eigen/test/lu.cpp
@@ -8,10 +8,15 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
 #include <Eigen/LU>
 using namespace std;
+
+template<typename MatrixType>
+typename MatrixType::RealScalar matrix_l1_norm(const MatrixType& m) {
+  return m.cwiseAbs().colwise().sum().maxCoeff();
+}
 
 template<typename MatrixType> void lu_non_invertible()
 {
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::RealScalar RealScalar;
@@ -90,19 +95,41 @@
   m3 = m1*m2;
   m2 = CMatrixType::Random(cols,cols2);
   // test that the code, which does resize(), may be applied to an xpr
   m2.block(0,0,m2.rows(),m2.cols()) = lu.solve(m3);
   VERIFY_IS_APPROX(m3, m1*m2);
+
+  // test solve with transposed
+  m3 = MatrixType::Random(rows,cols2);
+  m2 = m1.transpose()*m3;
+  m3 = MatrixType::Random(rows,cols2);
+  lu.template _solve_impl_transposed<false>(m2, m3);
+  VERIFY_IS_APPROX(m2, m1.transpose()*m3);
+  m3 = MatrixType::Random(rows,cols2);
+  m3 = lu.transpose().solve(m2);
+  VERIFY_IS_APPROX(m2, m1.transpose()*m3);
+
+  // test solve with conjugate transposed
+  m3 = MatrixType::Random(rows,cols2);
+  m2 = m1.adjoint()*m3;
+  m3 = MatrixType::Random(rows,cols2);
+  lu.template _solve_impl_transposed<true>(m2, m3);
+  VERIFY_IS_APPROX(m2, m1.adjoint()*m3);
+  m3 = MatrixType::Random(rows,cols2);
+  m3 = lu.adjoint().solve(m2);
+  VERIFY_IS_APPROX(m2, m1.adjoint()*m3);
 }
 
 template<typename MatrixType> void lu_invertible()
 {
   /* this test covers the following files:
      LU.h
   */
   typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-  int size = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
+  Index size = MatrixType::RowsAtCompileTime;
+  if( size==Dynamic)
+    size = internal::random<Index>(1,EIGEN_TEST_MAX_SIZE);
 
   MatrixType m1(size, size), m2(size, size), m3(size, size);
   FullPivLU<MatrixType> lu;
   lu.setThreshold(RealScalar(0.01));
   do {
@@ -119,27 +146,77 @@
   VERIFY(lu.isInvertible());
   VERIFY(lu.image(m1).fullPivLu().isInvertible());
   m3 = MatrixType::Random(size,size);
   m2 = lu.solve(m3);
   VERIFY_IS_APPROX(m3, m1*m2);
-  VERIFY_IS_APPROX(m2, lu.inverse()*m3);
+  MatrixType m1_inverse = lu.inverse();
+  VERIFY_IS_APPROX(m2, m1_inverse*m3);
+
+  RealScalar rcond = (RealScalar(1) / matrix_l1_norm(m1)) / matrix_l1_norm(m1_inverse);
+  const RealScalar rcond_est = lu.rcond();
+  // Verify that the estimated condition number is within a factor of 10 of the
+  // truth.
+  VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
+
+  // test solve with transposed
+  lu.template _solve_impl_transposed<false>(m3, m2);
+  VERIFY_IS_APPROX(m3, m1.transpose()*m2);
+  m3 = MatrixType::Random(size,size);
+  m3 = lu.transpose().solve(m2);
+  VERIFY_IS_APPROX(m2, m1.transpose()*m3);
+
+  // test solve with conjugate transposed
+  lu.template _solve_impl_transposed<true>(m3, m2);
+  VERIFY_IS_APPROX(m3, m1.adjoint()*m2);
+  m3 = MatrixType::Random(size,size);
+  m3 = lu.adjoint().solve(m2);
+  VERIFY_IS_APPROX(m2, m1.adjoint()*m3);
+
+  // Regression test for Bug 302
+  MatrixType m4 = MatrixType::Random(size,size);
+  VERIFY_IS_APPROX(lu.solve(m3*m4), lu.solve(m3)*m4);
 }
 
 template<typename MatrixType> void lu_partial_piv()
 {
   /* this test covers the following files:
      PartialPivLU.h
   */
   typedef typename MatrixType::Index Index;
-  Index rows = internal::random<Index>(1,4);
-  Index cols = rows;
+  typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+  Index size = internal::random<Index>(1,4);
 
-  MatrixType m1(cols, rows);
+  MatrixType m1(size, size), m2(size, size), m3(size, size);
   m1.setRandom();
   PartialPivLU<MatrixType> plu(m1);
 
   VERIFY_IS_APPROX(m1, plu.reconstructedMatrix());
+
+  m3 = MatrixType::Random(size,size);
+  m2 = plu.solve(m3);
+  VERIFY_IS_APPROX(m3, m1*m2);
+  MatrixType m1_inverse = plu.inverse();
+  VERIFY_IS_APPROX(m2, m1_inverse*m3);
+
+  RealScalar rcond = (RealScalar(1) / matrix_l1_norm(m1)) / matrix_l1_norm(m1_inverse);
+  const RealScalar rcond_est = plu.rcond();
+  // Verify that the estimate is within a factor of 10 of the truth.
+  VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10);
+
+  // test solve with transposed
+  plu.template _solve_impl_transposed<false>(m3, m2);
+  VERIFY_IS_APPROX(m3, m1.transpose()*m2);
+  m3 = MatrixType::Random(size,size);
+  m3 = plu.transpose().solve(m2);
+  VERIFY_IS_APPROX(m2, m1.transpose()*m3);
+
+  // test solve with conjugate transposed
+  plu.template _solve_impl_transposed<true>(m3, m2);
+  VERIFY_IS_APPROX(m3, m1.adjoint()*m2);
+  m3 = MatrixType::Random(size,size);
+  m3 = plu.adjoint().solve(m2);
+  VERIFY_IS_APPROX(m2, m1.adjoint()*m3);
 }
 
 template<typename MatrixType> void lu_verify_assert()
 {
   MatrixType tmp;
@@ -169,10 +246,11 @@
 
 void test_lu()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( lu_non_invertible<Matrix3f>() );
+    CALL_SUBTEST_1( lu_invertible<Matrix3f>() );
     CALL_SUBTEST_1( lu_verify_assert<Matrix3f>() );
 
     CALL_SUBTEST_2( (lu_non_invertible<Matrix<double, 4, 6> >()) );
     CALL_SUBTEST_2( (lu_verify_assert<Matrix<double, 4, 6> >()) );
 

Index: 3rd_party/eigen/test/main.h
==================================================================
--- 3rd_party/eigen/test/main.h
+++ 3rd_party/eigen/test/main.h
@@ -39,26 +39,67 @@
 #include <limits>
 #include <algorithm>
 #include <complex>
 #include <deque>
 #include <queue>
+#include <cassert>
 #include <list>
+#if __cplusplus >= 201103L
+#include <random>
+#ifdef EIGEN_USE_THREADS
+#include <future>
+#endif
+#endif
 
 // To test that all calls from Eigen code to std::min() and std::max() are
 // protected by parenthesis against macro expansion, the min()/max() macros
 // are defined here and any not-parenthesized min/max call will cause a
 // compiler error.
 #define min(A,B) please_protect_your_min_with_parentheses
 #define max(A,B) please_protect_your_max_with_parentheses
+#define isnan(X) please_protect_your_isnan_with_parentheses
+#define isinf(X) please_protect_your_isinf_with_parentheses
+#define isfinite(X) please_protect_your_isfinite_with_parentheses
+#ifdef M_PI
+#undef M_PI
+#endif
+#define M_PI please_use_EIGEN_PI_instead_of_M_PI
 
 #define FORBIDDEN_IDENTIFIER (this_identifier_is_forbidden_to_avoid_clashes) this_identifier_is_forbidden_to_avoid_clashes
 // B0 is defined in POSIX header termios.h
 #define B0 FORBIDDEN_IDENTIFIER
 
+// Unit tests calling Eigen's blas library must preserve the default blocking size
+// to avoid troubles.
+#ifndef EIGEN_NO_DEBUG_SMALL_PRODUCT_BLOCKS
+#define EIGEN_DEBUG_SMALL_PRODUCT_BLOCKS
+#endif
 
 // shuts down ICC's remark #593: variable "XXX" was set but never used
-#define TEST_SET_BUT_UNUSED_VARIABLE(X) X = X + 0;
+#define TEST_SET_BUT_UNUSED_VARIABLE(X) EIGEN_UNUSED_VARIABLE(X)
+
+#ifdef TEST_ENABLE_TEMPORARY_TRACKING
+
+static long int nb_temporaries;
+static long int nb_temporaries_on_assert = -1;
+
+inline void on_temporary_creation(long int size) {
+  // here's a great place to set a breakpoint when debugging failures in this test!
+  if(size!=0) nb_temporaries++;
+  if(nb_temporaries_on_assert>0) assert(nb_temporaries<nb_temporaries_on_assert);
+}
+
+#define EIGEN_DENSE_STORAGE_CTOR_PLUGIN { on_temporary_creation(size); }
+
+#define VERIFY_EVALUATION_COUNT(XPR,N) {\
+    nb_temporaries = 0; \
+    XPR; \
+    if(nb_temporaries!=N) { std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; }\
+    VERIFY( (#XPR) && nb_temporaries==N ); \
+  }
+  
+#endif
 
 // the following file is automatically generated by cmake
 #include "split_test_helper.h"
 
 #ifdef NDEBUG
@@ -69,11 +110,11 @@
 #ifndef DEBUG
 #define DEBUG
 #endif
 
 // bounds integer values for AltiVec
-#ifdef __ALTIVEC__
+#if defined(__ALTIVEC__) || defined(__VSX__)
 #define EIGEN_MAKING_DOCS
 #endif
 
 #ifndef EIGEN_TEST_FUNC
 #error EIGEN_TEST_FUNC must be defined
@@ -82,19 +123,29 @@
 #define DEFAULT_REPEAT 10
 
 namespace Eigen
 {
   static std::vector<std::string> g_test_stack;
+  // level == 0 <=> abort if test fail
+  // level >= 1 <=> warning message to std::cerr if test fail
+  static int g_test_level = 0;
   static int g_repeat;
   static unsigned int g_seed;
   static bool g_has_set_repeat, g_has_set_seed;
 }
+
+#define TRACK std::cerr << __FILE__ << " " << __LINE__ << std::endl
+// #define TRACK while()
 
 #define EI_PP_MAKE_STRING2(S) #S
 #define EI_PP_MAKE_STRING(S) EI_PP_MAKE_STRING2(S)
 
 #define EIGEN_DEFAULT_IO_FORMAT IOFormat(4, 0, "  ", "\n", "", "", "", "")
+
+#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__)
+  #define EIGEN_EXCEPTIONS
+#endif
 
 #ifndef EIGEN_NO_ASSERTION_CHECKING
 
   namespace Eigen
   {
@@ -133,61 +184,71 @@
       if( (!(a)) && (!no_more_assert) )     \
       { \
         if(report_on_cerr_on_assert_failure) \
           std::cerr <<  #a << " " __FILE__ << "(" << __LINE__ << ")\n"; \
         Eigen::no_more_assert = true;       \
-        throw Eigen::eigen_assert_exception(); \
+        EIGEN_THROW_X(Eigen::eigen_assert_exception()); \
       }                                     \
       else if (Eigen::internal::push_assert)       \
       {                                     \
         eigen_assert_list.push_back(std::string(EI_PP_MAKE_STRING(__FILE__) " (" EI_PP_MAKE_STRING(__LINE__) ") : " #a) ); \
       }
 
+    #ifdef EIGEN_EXCEPTIONS
     #define VERIFY_RAISES_ASSERT(a)                                                   \
       {                                                                               \
         Eigen::no_more_assert = false;                                                \
-        Eigen::eigen_assert_list.clear();                                                \
-        Eigen::internal::push_assert = true;                                                 \
+        Eigen::eigen_assert_list.clear();                                             \
+        Eigen::internal::push_assert = true;                                          \
         Eigen::report_on_cerr_on_assert_failure = false;                              \
         try {                                                                         \
           a;                                                                          \
           std::cerr << "One of the following asserts should have been triggered:\n";  \
-          for (uint ai=0 ; ai<eigen_assert_list.size() ; ++ai)                           \
-            std::cerr << "  " << eigen_assert_list[ai] << "\n";                          \
+          for (uint ai=0 ; ai<eigen_assert_list.size() ; ++ai)                        \
+            std::cerr << "  " << eigen_assert_list[ai] << "\n";                       \
           VERIFY(Eigen::should_raise_an_assert && # a);                               \
-        } catch (Eigen::eigen_assert_exception) {                                        \
-          Eigen::internal::push_assert = false; VERIFY(true);                                \
+        } catch (Eigen::eigen_assert_exception) {                                     \
+          Eigen::internal::push_assert = false; VERIFY(true);                         \
         }                                                                             \
         Eigen::report_on_cerr_on_assert_failure = true;                               \
-        Eigen::internal::push_assert = false;                                                \
+        Eigen::internal::push_assert = false;                                         \
       }
+    #endif //EIGEN_EXCEPTIONS
 
-  #else // EIGEN_DEBUG_ASSERTS
+  #elif !defined(__CUDACC__) // EIGEN_DEBUG_ASSERTS
     // see bug 89. The copy_bool here is working around a bug in gcc <= 4.3
     #define eigen_assert(a) \
       if( (!Eigen::internal::copy_bool(a)) && (!no_more_assert) )\
       {                                       \
         Eigen::no_more_assert = true;         \
         if(report_on_cerr_on_assert_failure)  \
           eigen_plain_assert(a);              \
         else                                  \
-          throw Eigen::eigen_assert_exception(); \
+          EIGEN_THROW_X(Eigen::eigen_assert_exception()); \
       }
-    #define VERIFY_RAISES_ASSERT(a) {                             \
+    #ifdef EIGEN_EXCEPTIONS
+      #define VERIFY_RAISES_ASSERT(a) {                           \
         Eigen::no_more_assert = false;                            \
         Eigen::report_on_cerr_on_assert_failure = false;          \
         try {                                                     \
           a;                                                      \
           VERIFY(Eigen::should_raise_an_assert && # a);           \
         }                                                         \
-        catch (Eigen::eigen_assert_exception&) { VERIFY(true); }     \
+        catch (Eigen::eigen_assert_exception&) { VERIFY(true); }  \
         Eigen::report_on_cerr_on_assert_failure = true;           \
       }
-
+    #endif //EIGEN_EXCEPTIONS
   #endif // EIGEN_DEBUG_ASSERTS
 
+#ifndef VERIFY_RAISES_ASSERT
+  #define VERIFY_RAISES_ASSERT(a) \
+    std::cout << "Can't VERIFY_RAISES_ASSERT( " #a " ) with exceptions disabled\n";
+#endif
+    
+  #if !defined(__CUDACC__)
   #define EIGEN_USE_CUSTOM_ASSERT
+  #endif
 
 #else // EIGEN_NO_ASSERTION_CHECKING
 
   #define VERIFY_RAISES_ASSERT(a) {}
 
@@ -199,25 +260,33 @@
 
 inline void verify_impl(bool condition, const char *testname, const char *file, int line, const char *condition_as_string)
 {
   if (!condition)
   {
+    if(Eigen::g_test_level>0)
+      std::cerr << "WARNING: ";
     std::cerr << "Test " << testname << " failed in " << file << " (" << line << ")"
       << std::endl << "    " << condition_as_string << std::endl;
     std::cerr << "Stack:\n";
     const int test_stack_size = static_cast<int>(Eigen::g_test_stack.size());
     for(int i=test_stack_size-1; i>=0; --i)
       std::cerr << "  - " << Eigen::g_test_stack[i] << "\n";
     std::cerr << "\n";
-    abort();
+    if(Eigen::g_test_level==0)
+      abort();
   }
 }
 
 #define VERIFY(a) ::verify_impl(a, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a))
 
-#define VERIFY_IS_EQUAL(a, b) VERIFY(test_is_equal(a, b))
-#define VERIFY_IS_APPROX(a, b) VERIFY(test_isApprox(a, b))
+#define VERIFY_GE(a, b) ::verify_impl(a >= b, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a >= b))
+#define VERIFY_LE(a, b) ::verify_impl(a <= b, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a <= b))
+
+
+#define VERIFY_IS_EQUAL(a, b) VERIFY(test_is_equal(a, b, true))
+#define VERIFY_IS_NOT_EQUAL(a, b) VERIFY(test_is_equal(a, b, false))
+#define VERIFY_IS_APPROX(a, b) VERIFY(verifyIsApprox(a, b))
 #define VERIFY_IS_NOT_APPROX(a, b) VERIFY(!test_isApprox(a, b))
 #define VERIFY_IS_MUCH_SMALLER_THAN(a, b) VERIFY(test_isMuchSmallerThan(a, b))
 #define VERIFY_IS_NOT_MUCH_SMALLER_THAN(a, b) VERIFY(!test_isMuchSmallerThan(a, b))
 #define VERIFY_IS_APPROX_OR_LESS_THAN(a, b) VERIFY(test_isApproxOrLessThan(a, b))
 #define VERIFY_IS_NOT_APPROX_OR_LESS_THAN(a, b) VERIFY(!test_isApproxOrLessThan(a, b))
@@ -234,13 +303,25 @@
 namespace Eigen {
 
 template<typename T> inline typename NumTraits<T>::Real test_precision() { return NumTraits<T>::dummy_precision(); }
 template<> inline float test_precision<float>() { return 1e-3f; }
 template<> inline double test_precision<double>() { return 1e-6; }
+template<> inline long double test_precision<long double>() { return 1e-6l; }
 template<> inline float test_precision<std::complex<float> >() { return test_precision<float>(); }
 template<> inline double test_precision<std::complex<double> >() { return test_precision<double>(); }
-template<> inline long double test_precision<long double>() { return 1e-6; }
+template<> inline long double test_precision<std::complex<long double> >() { return test_precision<long double>(); }
+
+inline bool test_isApprox(const short& a, const short& b)
+{ return internal::isApprox(a, b, test_precision<short>()); }
+inline bool test_isApprox(const unsigned short& a, const unsigned short& b)
+{ return internal::isApprox(a, b, test_precision<unsigned long>()); }
+inline bool test_isApprox(const unsigned int& a, const unsigned int& b)
+{ return internal::isApprox(a, b, test_precision<unsigned int>()); }
+inline bool test_isApprox(const long& a, const long& b)
+{ return internal::isApprox(a, b, test_precision<long>()); }
+inline bool test_isApprox(const unsigned long& a, const unsigned long& b)
+{ return internal::isApprox(a, b, test_precision<unsigned long>()); }
 
 inline bool test_isApprox(const int& a, const int& b)
 { return internal::isApprox(a, b, test_precision<int>()); }
 inline bool test_isMuchSmallerThan(const int& a, const int& b)
 { return internal::isMuchSmallerThan(a, b, test_precision<int>()); }
@@ -251,18 +332,19 @@
 { return internal::isApprox(a, b, test_precision<float>()); }
 inline bool test_isMuchSmallerThan(const float& a, const float& b)
 { return internal::isMuchSmallerThan(a, b, test_precision<float>()); }
 inline bool test_isApproxOrLessThan(const float& a, const float& b)
 { return internal::isApproxOrLessThan(a, b, test_precision<float>()); }
+
 inline bool test_isApprox(const double& a, const double& b)
 { return internal::isApprox(a, b, test_precision<double>()); }
-
 inline bool test_isMuchSmallerThan(const double& a, const double& b)
 { return internal::isMuchSmallerThan(a, b, test_precision<double>()); }
 inline bool test_isApproxOrLessThan(const double& a, const double& b)
 { return internal::isApproxOrLessThan(a, b, test_precision<double>()); }
 
+#ifndef EIGEN_TEST_NO_COMPLEX
 inline bool test_isApprox(const std::complex<float>& a, const std::complex<float>& b)
 { return internal::isApprox(a, b, test_precision<std::complex<float> >()); }
 inline bool test_isMuchSmallerThan(const std::complex<float>& a, const std::complex<float>& b)
 { return internal::isMuchSmallerThan(a, b, test_precision<std::complex<float> >()); }
 
@@ -269,10 +351,19 @@
 inline bool test_isApprox(const std::complex<double>& a, const std::complex<double>& b)
 { return internal::isApprox(a, b, test_precision<std::complex<double> >()); }
 inline bool test_isMuchSmallerThan(const std::complex<double>& a, const std::complex<double>& b)
 { return internal::isMuchSmallerThan(a, b, test_precision<std::complex<double> >()); }
 
+#ifndef EIGEN_TEST_NO_LONGDOUBLE
+inline bool test_isApprox(const std::complex<long double>& a, const std::complex<long double>& b)
+{ return internal::isApprox(a, b, test_precision<std::complex<long double> >()); }
+inline bool test_isMuchSmallerThan(const std::complex<long double>& a, const std::complex<long double>& b)
+{ return internal::isMuchSmallerThan(a, b, test_precision<std::complex<long double> >()); }
+#endif
+#endif
+
+#ifndef EIGEN_TEST_NO_LONGDOUBLE
 inline bool test_isApprox(const long double& a, const long double& b)
 {
     bool ret = internal::isApprox(a, b, test_precision<long double>());
     if (!ret) std::cerr
         << std::endl << "    actual   = " << a
@@ -282,16 +373,130 @@
 
 inline bool test_isMuchSmallerThan(const long double& a, const long double& b)
 { return internal::isMuchSmallerThan(a, b, test_precision<long double>()); }
 inline bool test_isApproxOrLessThan(const long double& a, const long double& b)
 { return internal::isApproxOrLessThan(a, b, test_precision<long double>()); }
+#endif // EIGEN_TEST_NO_LONGDOUBLE
+
+inline bool test_isApprox(const half& a, const half& b)
+{ return internal::isApprox(a, b, test_precision<half>()); }
+inline bool test_isMuchSmallerThan(const half& a, const half& b)
+{ return internal::isMuchSmallerThan(a, b, test_precision<half>()); }
+inline bool test_isApproxOrLessThan(const half& a, const half& b)
+{ return internal::isApproxOrLessThan(a, b, test_precision<half>()); }
+
+// test_relative_error returns the relative difference between a and b as a real scalar as used in isApprox.
+template<typename T1,typename T2>
+typename NumTraits<typename T1::RealScalar>::NonInteger test_relative_error(const EigenBase<T1> &a, const EigenBase<T2> &b)
+{
+  using std::sqrt;
+  typedef typename NumTraits<typename T1::RealScalar>::NonInteger RealScalar;
+  typename internal::nested_eval<T1,2>::type ea(a.derived());
+  typename internal::nested_eval<T2,2>::type eb(b.derived());
+  return sqrt(RealScalar((ea-eb).cwiseAbs2().sum()) / RealScalar((std::min)(eb.cwiseAbs2().sum(),ea.cwiseAbs2().sum())));
+}
+
+template<typename T1,typename T2>
+typename T1::RealScalar test_relative_error(const T1 &a, const T2 &b, const typename T1::Coefficients* = 0)
+{
+  return test_relative_error(a.coeffs(), b.coeffs());
+}
+
+template<typename T1,typename T2>
+typename T1::Scalar test_relative_error(const T1 &a, const T2 &b, const typename T1::MatrixType* = 0)
+{
+  return test_relative_error(a.matrix(), b.matrix());
+}
+
+template<typename S, int D>
+S test_relative_error(const Translation<S,D> &a, const Translation<S,D> &b)
+{
+  return test_relative_error(a.vector(), b.vector());
+}
+
+template <typename S, int D, int O>
+S test_relative_error(const ParametrizedLine<S,D,O> &a, const ParametrizedLine<S,D,O> &b)
+{
+  return (std::max)(test_relative_error(a.origin(), b.origin()), test_relative_error(a.origin(), b.origin()));
+}
+
+template <typename S, int D>
+S test_relative_error(const AlignedBox<S,D> &a, const AlignedBox<S,D> &b)
+{
+  return (std::max)(test_relative_error((a.min)(), (b.min)()), test_relative_error((a.max)(), (b.max)()));
+}
+
+template<typename Derived> class SparseMatrixBase;
+template<typename T1,typename T2>
+typename T1::RealScalar test_relative_error(const MatrixBase<T1> &a, const SparseMatrixBase<T2> &b)
+{
+  return test_relative_error(a,b.toDense());
+}
+
+template<typename Derived> class SparseMatrixBase;
+template<typename T1,typename T2>
+typename T1::RealScalar test_relative_error(const SparseMatrixBase<T1> &a, const MatrixBase<T2> &b)
+{
+  return test_relative_error(a.toDense(),b);
+}
+
+template<typename Derived> class SparseMatrixBase;
+template<typename T1,typename T2>
+typename T1::RealScalar test_relative_error(const SparseMatrixBase<T1> &a, const SparseMatrixBase<T2> &b)
+{
+  return test_relative_error(a.toDense(),b.toDense());
+}
+
+template<typename T1,typename T2>
+typename NumTraits<typename NumTraits<T1>::Real>::NonInteger test_relative_error(const T1 &a, const T2 &b, typename internal::enable_if<internal::is_arithmetic<typename NumTraits<T1>::Real>::value, T1>::type* = 0)
+{
+  typedef typename NumTraits<typename NumTraits<T1>::Real>::NonInteger RealScalar;
+  return numext::sqrt(RealScalar(numext::abs2(a-b))/RealScalar((numext::mini)(numext::abs2(a),numext::abs2(b))));
+}
+
+template<typename T>
+T test_relative_error(const Rotation2D<T> &a, const Rotation2D<T> &b)
+{
+  return test_relative_error(a.angle(), b.angle());
+}
+
+template<typename T>
+T test_relative_error(const AngleAxis<T> &a, const AngleAxis<T> &b)
+{
+  return (std::max)(test_relative_error(a.angle(), b.angle()), test_relative_error(a.axis(), b.axis()));
+}
 
 template<typename Type1, typename Type2>
-inline bool test_isApprox(const Type1& a, const Type2& b)
+inline bool test_isApprox(const Type1& a, const Type2& b, typename Type1::Scalar* = 0) // Enabled for Eigen's type only
 {
   return a.isApprox(b, test_precision<typename Type1::Scalar>());
 }
+
+// get_test_precision is a small wrapper to test_precision allowing to return the scalar precision for either scalars or expressions
+template<typename T>
+typename NumTraits<typename T::Scalar>::Real get_test_precision(const T&, const typename T::Scalar* = 0)
+{
+  return test_precision<typename NumTraits<typename T::Scalar>::Real>();
+}
+
+template<typename T>
+typename NumTraits<T>::Real get_test_precision(const T&,typename internal::enable_if<internal::is_arithmetic<typename NumTraits<T>::Real>::value, T>::type* = 0)
+{
+  return test_precision<typename NumTraits<T>::Real>();
+}
+
+// verifyIsApprox is a wrapper to test_isApprox that outputs the relative difference magnitude if the test fails.
+template<typename Type1, typename Type2>
+inline bool verifyIsApprox(const Type1& a, const Type2& b)
+{
+  bool ret = test_isApprox(a,b);
+  if(!ret)
+  {
+    std::cerr << "Difference too large wrt tolerance " << get_test_precision(a)  << ", relative error is: " << test_relative_error(a,b) << std::endl;
+  }
+  return ret;
+}
 
 // The idea behind this function is to compare the two scalars a and b where
 // the scalar ref is a hint about the expected order of magnitude of a and b.
 // WARNING: the scalar a and b must be positive
 // Therefore, if for some reason a and b are very small compared to ref,
@@ -324,21 +529,21 @@
   return m.isUnitary(test_precision<typename internal::traits<Derived>::Scalar>());
 }
 
 // Forward declaration to avoid ICC warning
 template<typename T, typename U>
-bool test_is_equal(const T& actual, const U& expected);
+bool test_is_equal(const T& actual, const U& expected, bool expect_equal=true);
 
 template<typename T, typename U>
-bool test_is_equal(const T& actual, const U& expected)
+bool test_is_equal(const T& actual, const U& expected, bool expect_equal)
 {
-    if (actual==expected)
+    if ((actual==expected) == expect_equal)
         return true;
     // false:
     std::cerr
-        << std::endl << "    actual   = " << actual
-        << std::endl << "    expected = " << expected << std::endl << std::endl;
+        << "\n    actual   = " << actual
+        << "\n    expected " << (expect_equal ? "= " : "!=") << expected << "\n\n";
     return false;
 }
 
 /** Creates a random Partial Isometry matrix of given rank.
   *
@@ -345,15 +550,14 @@
   * A partial isometry is a matrix all of whose singular values are either 0 or 1.
   * This is very useful to test rank-revealing algorithms.
   */
 // Forward declaration to avoid ICC warning
 template<typename MatrixType>
-void createRandomPIMatrixOfRank(typename MatrixType::Index desired_rank, typename MatrixType::Index rows, typename MatrixType::Index cols, MatrixType& m);
+void createRandomPIMatrixOfRank(Index desired_rank, Index rows, Index cols, MatrixType& m);
 template<typename MatrixType>
-void createRandomPIMatrixOfRank(typename MatrixType::Index desired_rank, typename MatrixType::Index rows, typename MatrixType::Index cols, MatrixType& m)
+void createRandomPIMatrixOfRank(Index desired_rank, Index rows, Index cols, MatrixType& m)
 {
-  typedef typename internal::traits<MatrixType>::Index Index;
   typedef typename internal::traits<MatrixType>::Scalar Scalar;
   enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
 
   typedef Matrix<Scalar, Dynamic, 1> VectorType;
   typedef Matrix<Scalar, Rows, Rows> MatrixAType;
@@ -386,15 +590,14 @@
   m = qra.householderQ() * d * qrb.householderQ();
 }
 
 // Forward declaration to avoid ICC warning
 template<typename PermutationVectorType>
-void randomPermutationVector(PermutationVectorType& v, typename PermutationVectorType::Index size);
+void randomPermutationVector(PermutationVectorType& v, Index size);
 template<typename PermutationVectorType>
-void randomPermutationVector(PermutationVectorType& v, typename PermutationVectorType::Index size)
+void randomPermutationVector(PermutationVectorType& v, Index size)
 {
-  typedef typename PermutationVectorType::Index Index;
   typedef typename PermutationVectorType::Scalar Scalar;
   v.resize(size);
   for(Index i = 0; i < size; ++i) v(i) = Scalar(i);
   if(size == 1) return;
   for(Index n = 0; n < 3 * size; ++n)
@@ -409,16 +612,11 @@
 template<typename T> bool isNotNaN(const T& x)
 {
   return x==x;
 }
 
-template<typename T> bool isNaN(const T& x)
-{
-  return x!=x;
-}
-
-template<typename T> bool isInf(const T& x)
+template<typename T> bool isPlusInf(const T& x)
 {
   return x > NumTraits<T>::highest();
 }
 
 template<typename T> bool isMinusInf(const T& x)
@@ -435,17 +633,19 @@
 template<typename T> struct GetDifferentType<std::complex<T> >
 { typedef std::complex<typename GetDifferentType<T>::type> type; };
 
 // Forward declaration to avoid ICC warning
 template<typename T> std::string type_name();
-template<typename T> std::string type_name()              { return "other"; }
-template<> std::string type_name<float>()                 { return "float"; }
-template<> std::string type_name<double>()                { return "double"; }
-template<> std::string type_name<int>()                   { return "int"; }
-template<> std::string type_name<std::complex<float> >()  { return "complex<float>"; }
-template<> std::string type_name<std::complex<double> >() { return "complex<double>"; }
-template<> std::string type_name<std::complex<int> >()    { return "complex<int>"; }
+template<typename T> std::string type_name()                    { return "other"; }
+template<> std::string type_name<float>()                       { return "float"; }
+template<> std::string type_name<double>()                      { return "double"; }
+template<> std::string type_name<long double>()                 { return "long double"; }
+template<> std::string type_name<int>()                         { return "int"; }
+template<> std::string type_name<std::complex<float> >()        { return "complex<float>"; }
+template<> std::string type_name<std::complex<double> >()       { return "complex<double>"; }
+template<> std::string type_name<std::complex<long double> >()  { return "complex<long double>"; }
+template<> std::string type_name<std::complex<int> >()          { return "complex<int>"; }
 
 // forward declaration of the main test function
 void EIGEN_CAT(test_,EIGEN_TEST_FUNC)();
 
 using namespace Eigen;
@@ -548,5 +748,10 @@
   //  -> this warning is raised for all our test functions. Declaring them static would fix the issue.
   // warning #279: controlling expression is constant
   // remark #1572: floating-point equality and inequality comparisons are unreliable
   #pragma warning disable 279 383 1418 1572
 #endif
+
+#ifdef _MSC_VER
+  // 4503 - decorated name length exceeded, name was truncated
+  #pragma warning( disable : 4503)
+#endif

Index: 3rd_party/eigen/test/mapped_matrix.cpp
==================================================================
--- 3rd_party/eigen/test/mapped_matrix.cpp
+++ 3rd_party/eigen/test/mapped_matrix.cpp
@@ -10,35 +10,40 @@
 #ifndef EIGEN_NO_STATIC_ASSERT
 #define EIGEN_NO_STATIC_ASSERT // turn static asserts into runtime asserts in order to check them
 #endif
 
 #include "main.h"
+
+#define EIGEN_TESTMAP_MAX_SIZE 256
 
 template<typename VectorType> void map_class_vector(const VectorType& m)
 {
   typedef typename VectorType::Index Index;
   typedef typename VectorType::Scalar Scalar;
 
   Index size = m.size();
 
-  // test Map.h
   Scalar* array1 = internal::aligned_new<Scalar>(size);
   Scalar* array2 = internal::aligned_new<Scalar>(size);
   Scalar* array3 = new Scalar[size+1];
-  Scalar* array3unaligned = size_t(array3)%16 == 0 ? array3+1 : array3;
+  Scalar* array3unaligned = (internal::UIntPtr(array3)%EIGEN_MAX_ALIGN_BYTES) == 0 ? array3+1 : array3;
+  Scalar  array4[EIGEN_TESTMAP_MAX_SIZE];
 
-  Map<VectorType, Aligned>(array1, size) = VectorType::Random(size);
-  Map<VectorType, Aligned>(array2, size) = Map<VectorType,Aligned>(array1, size);
+  Map<VectorType, AlignedMax>(array1, size) = VectorType::Random(size);
+  Map<VectorType, AlignedMax>(array2, size) = Map<VectorType,AlignedMax>(array1, size);
   Map<VectorType>(array3unaligned, size) = Map<VectorType>(array1, size);
-  VectorType ma1 = Map<VectorType, Aligned>(array1, size);
-  VectorType ma2 = Map<VectorType, Aligned>(array2, size);
+  Map<VectorType>(array4, size)          = Map<VectorType,AlignedMax>(array1, size);
+  VectorType ma1 = Map<VectorType, AlignedMax>(array1, size);
+  VectorType ma2 = Map<VectorType, AlignedMax>(array2, size);
   VectorType ma3 = Map<VectorType>(array3unaligned, size);
+  VectorType ma4 = Map<VectorType>(array4, size);
   VERIFY_IS_EQUAL(ma1, ma2);
   VERIFY_IS_EQUAL(ma1, ma3);
+  VERIFY_IS_EQUAL(ma1, ma4);
   #ifdef EIGEN_VECTORIZE
-  if(internal::packet_traits<Scalar>::Vectorizable)
-    VERIFY_RAISES_ASSERT((Map<VectorType,Aligned>(array3unaligned, size)))
+  if(internal::packet_traits<Scalar>::Vectorizable && size>=AlignedMax)
+    VERIFY_RAISES_ASSERT((Map<VectorType,AlignedMax>(array3unaligned, size)))
   #endif
 
   internal::aligned_delete(array1, size);
   internal::aligned_delete(array2, size);
   delete[] array3;
@@ -48,27 +53,68 @@
 {
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
 
   Index rows = m.rows(), cols = m.cols(), size = rows*cols;
+  Scalar s1 = internal::random<Scalar>();
 
-  // test Map.h
+  // array1 and array2 -> aligned heap allocation
   Scalar* array1 = internal::aligned_new<Scalar>(size);
   for(int i = 0; i < size; i++) array1[i] = Scalar(1);
   Scalar* array2 = internal::aligned_new<Scalar>(size);
   for(int i = 0; i < size; i++) array2[i] = Scalar(1);
+  // array3unaligned -> unaligned pointer to heap
   Scalar* array3 = new Scalar[size+1];
   for(int i = 0; i < size+1; i++) array3[i] = Scalar(1);
-  Scalar* array3unaligned = size_t(array3)%16 == 0 ? array3+1 : array3;
-  Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols);
-  Map<MatrixType>(array2, rows, cols) = Map<MatrixType>(array1, rows, cols);
-  Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols);
-  MatrixType ma1 = Map<MatrixType>(array1, rows, cols);
-  MatrixType ma2 = Map<MatrixType, Aligned>(array2, rows, cols);
+  Scalar* array3unaligned = internal::UIntPtr(array3)%EIGEN_MAX_ALIGN_BYTES == 0 ? array3+1 : array3;
+  Scalar array4[256];
+  if(size<=256)
+    for(int i = 0; i < size; i++) array4[i] = Scalar(1);
+  
+  Map<MatrixType> map1(array1, rows, cols);
+  Map<MatrixType, AlignedMax> map2(array2, rows, cols);
+  Map<MatrixType> map3(array3unaligned, rows, cols);
+  Map<MatrixType> map4(array4, rows, cols);
+  
+  VERIFY_IS_EQUAL(map1, MatrixType::Ones(rows,cols));
+  VERIFY_IS_EQUAL(map2, MatrixType::Ones(rows,cols));
+  VERIFY_IS_EQUAL(map3, MatrixType::Ones(rows,cols));
+  map1 = MatrixType::Random(rows,cols);
+  map2 = map1;
+  map3 = map1;
+  MatrixType ma1 = map1;
+  MatrixType ma2 = map2;
+  MatrixType ma3 = map3;
+  VERIFY_IS_EQUAL(map1, map2);
+  VERIFY_IS_EQUAL(map1, map3);
   VERIFY_IS_EQUAL(ma1, ma2);
-  MatrixType ma3 = Map<MatrixType>(array3unaligned, rows, cols);
   VERIFY_IS_EQUAL(ma1, ma3);
+  VERIFY_IS_EQUAL(ma1, map3);
+  
+  VERIFY_IS_APPROX(s1*map1, s1*map2);
+  VERIFY_IS_APPROX(s1*ma1, s1*ma2);
+  VERIFY_IS_EQUAL(s1*ma1, s1*ma3);
+  VERIFY_IS_APPROX(s1*map1, s1*map3);
+  
+  map2 *= s1;
+  map3 *= s1;
+  VERIFY_IS_APPROX(s1*map1, map2);
+  VERIFY_IS_APPROX(s1*map1, map3);
+  
+  if(size<=256)
+  {
+    VERIFY_IS_EQUAL(map4, MatrixType::Ones(rows,cols));
+    map4 = map1;
+    MatrixType ma4 = map4;
+    VERIFY_IS_EQUAL(map1, map4);
+    VERIFY_IS_EQUAL(ma1, map4);
+    VERIFY_IS_EQUAL(ma1, ma4);
+    VERIFY_IS_APPROX(s1*map1, s1*map4);
+    
+    map4 *= s1;
+    VERIFY_IS_APPROX(s1*map1, map4);
+  }
 
   internal::aligned_delete(array1, size);
   internal::aligned_delete(array2, size);
   delete[] array3;
 }
@@ -78,15 +124,14 @@
   typedef typename VectorType::Index Index;
   typedef typename VectorType::Scalar Scalar;
 
   Index size = m.size();
 
-  // test Map.h
   Scalar* array1 = internal::aligned_new<Scalar>(size);
   Scalar* array2 = internal::aligned_new<Scalar>(size);
   Scalar* array3 = new Scalar[size+1];
-  Scalar* array3unaligned = size_t(array3)%16 == 0 ? array3+1 : array3;
+  Scalar* array3unaligned = internal::UIntPtr(array3)%EIGEN_MAX_ALIGN_BYTES == 0 ? array3+1 : array3;
 
   VectorType::MapAligned(array1, size) = VectorType::Random(size);
   VectorType::Map(array2, size) = VectorType::Map(array1, size);
   VectorType::Map(array3unaligned, size) = VectorType::Map(array1, size);
   VectorType ma1 = VectorType::Map(array1, size);
@@ -107,21 +152,44 @@
   // CMake can help with that.
 
   // verify that map-to-const don't have LvalueBit
   typedef typename internal::add_const<PlainObjectType>::type ConstPlainObjectType;
   VERIFY( !(internal::traits<Map<ConstPlainObjectType> >::Flags & LvalueBit) );
-  VERIFY( !(internal::traits<Map<ConstPlainObjectType, Aligned> >::Flags & LvalueBit) );
+  VERIFY( !(internal::traits<Map<ConstPlainObjectType, AlignedMax> >::Flags & LvalueBit) );
   VERIFY( !(Map<ConstPlainObjectType>::Flags & LvalueBit) );
-  VERIFY( !(Map<ConstPlainObjectType, Aligned>::Flags & LvalueBit) );
+  VERIFY( !(Map<ConstPlainObjectType, AlignedMax>::Flags & LvalueBit) );
+}
+
+template<typename Scalar>
+void map_not_aligned_on_scalar()
+{
+  typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
+  typedef typename MatrixType::Index Index;
+  Index size = 11;
+  Scalar* array1 = internal::aligned_new<Scalar>((size+1)*(size+1)+1);
+  Scalar* array2 = reinterpret_cast<Scalar*>(sizeof(Scalar)/2+std::size_t(array1));
+  Map<MatrixType,0,OuterStride<> > map2(array2, size, size, OuterStride<>(size+1));
+  MatrixType m2 = MatrixType::Random(size,size);
+  map2 = m2;
+  VERIFY_IS_EQUAL(m2, map2);
+  
+  typedef Matrix<Scalar,Dynamic,1> VectorType;
+  Map<VectorType> map3(array2, size);
+  MatrixType v3 = VectorType::Random(size);
+  map3 = v3;
+  VERIFY_IS_EQUAL(v3, map3);
+  
+  internal::aligned_delete(array1, (size+1)*(size+1)+1);
 }
 
 void test_mapped_matrix()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( map_class_vector(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_1( check_const_correctness(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_2( map_class_vector(Vector4d()) );
+    CALL_SUBTEST_2( map_class_vector(VectorXd(13)) );
     CALL_SUBTEST_2( check_const_correctness(Matrix4d()) );
     CALL_SUBTEST_3( map_class_vector(RowVector4f()) );
     CALL_SUBTEST_4( map_class_vector(VectorXcf(8)) );
     CALL_SUBTEST_5( map_class_vector(VectorXi(12)) );
     CALL_SUBTEST_5( check_const_correctness(VectorXi(12)) );
@@ -135,7 +203,9 @@
     CALL_SUBTEST_6( map_static_methods(Matrix<double, 1, 1>()) );
     CALL_SUBTEST_7( map_static_methods(Vector3f()) );
     CALL_SUBTEST_8( map_static_methods(RowVector3d()) );
     CALL_SUBTEST_9( map_static_methods(VectorXcd(8)) );
     CALL_SUBTEST_10( map_static_methods(VectorXf(12)) );
+    
+    CALL_SUBTEST_11( map_not_aligned_on_scalar<double>() );
   }
 }

Index: 3rd_party/eigen/test/mapstaticmethods.cpp
==================================================================
--- 3rd_party/eigen/test/mapstaticmethods.cpp
+++ 3rd_party/eigen/test/mapstaticmethods.cpp
@@ -67,11 +67,12 @@
 template<typename PlainObjectType>
 struct mapstaticmethods_impl<PlainObjectType, true, false>
 {
   static void run(const PlainObjectType& m)
   {
-    int rows = m.rows(), cols = m.cols();
+    typedef typename PlainObjectType::Index Index;
+    Index rows = m.rows(), cols = m.cols();
 
     int i = internal::random<int>(2,5), j = internal::random<int>(2,5);
 
     PlainObjectType::Map(ptr, rows, cols).setZero();
     PlainObjectType::MapAligned(ptr, rows, cols).setZero();
@@ -113,11 +114,12 @@
 template<typename PlainObjectType>
 struct mapstaticmethods_impl<PlainObjectType, true, true>
 {
   static void run(const PlainObjectType& v)
   {
-    int size = v.size();
+    typedef typename PlainObjectType::Index Index;
+    Index size = v.size();
 
     int i = internal::random<int>(2,5);
 
     PlainObjectType::Map(ptr, size).setZero();
     PlainObjectType::MapAligned(ptr, size).setZero();

Index: 3rd_party/eigen/test/mapstride.cpp
==================================================================
--- 3rd_party/eigen/test/mapstride.cpp
+++ 3rd_party/eigen/test/mapstride.cpp
@@ -21,11 +21,11 @@
   Index arraysize = 3*size;
   
   Scalar* a_array = internal::aligned_new<Scalar>(arraysize+1);
   Scalar* array = a_array;
   if(Alignment!=Aligned)
-    array = (Scalar*)(ptrdiff_t(a_array) + (internal::packet_traits<Scalar>::AlignedOnScalar?sizeof(Scalar):sizeof(typename NumTraits<Scalar>::Real)));
+    array = (Scalar*)(internal::IntPtr(a_array) + (internal::packet_traits<Scalar>::AlignedOnScalar?sizeof(Scalar):sizeof(typename NumTraits<Scalar>::Real)));
 
   {
     Map<VectorType, Alignment, InnerStride<3> > map(array, size);
     map = v;
     for(int i = 0; i < size; ++i)
@@ -54,34 +54,56 @@
   typedef typename MatrixType::Scalar Scalar;
 
   Index rows = _m.rows(), cols = _m.cols();
 
   MatrixType m = MatrixType::Random(rows,cols);
+  Scalar s1 = internal::random<Scalar>();
 
   Index arraysize = 2*(rows+4)*(cols+4);
 
-  Scalar* a_array = internal::aligned_new<Scalar>(arraysize+1);
-  Scalar* array = a_array;
+  Scalar* a_array1 = internal::aligned_new<Scalar>(arraysize+1);
+  Scalar* array1 = a_array1;
   if(Alignment!=Aligned)
-    array = (Scalar*)(ptrdiff_t(a_array) + (internal::packet_traits<Scalar>::AlignedOnScalar?sizeof(Scalar):sizeof(typename NumTraits<Scalar>::Real)));
+    array1 = (Scalar*)(internal::IntPtr(a_array1) + (internal::packet_traits<Scalar>::AlignedOnScalar?sizeof(Scalar):sizeof(typename NumTraits<Scalar>::Real)));
 
+  Scalar a_array2[256];
+  Scalar* array2 = a_array2;
+  if(Alignment!=Aligned)
+    array2 = (Scalar*)(internal::IntPtr(a_array2) + (internal::packet_traits<Scalar>::AlignedOnScalar?sizeof(Scalar):sizeof(typename NumTraits<Scalar>::Real)));
+  else
+    array2 = (Scalar*)(((internal::UIntPtr(a_array2)+EIGEN_MAX_ALIGN_BYTES-1)/EIGEN_MAX_ALIGN_BYTES)*EIGEN_MAX_ALIGN_BYTES);
+  Index maxsize2 = a_array2 - array2 + 256;
+  
   // test no inner stride and some dynamic outer stride
+  for(int k=0; k<2; ++k)
   {
+    if(k==1 && (m.innerSize()+1)*m.outerSize() > maxsize2)
+      break;
+    Scalar* array = (k==0 ? array1 : array2);
+    
     Map<MatrixType, Alignment, OuterStride<Dynamic> > map(array, rows, cols, OuterStride<Dynamic>(m.innerSize()+1));
     map = m;
     VERIFY(map.outerStride() == map.innerSize()+1);
     for(int i = 0; i < m.outerSize(); ++i)
       for(int j = 0; j < m.innerSize(); ++j)
       {
         VERIFY(array[map.outerStride()*i+j] == m.coeffByOuterInner(i,j));
         VERIFY(map.coeffByOuterInner(i,j) == m.coeffByOuterInner(i,j));
       }
+    VERIFY_IS_APPROX(s1*map,s1*m);
+    map *= s1;
+    VERIFY_IS_APPROX(map,s1*m);
   }
 
   // test no inner stride and an outer stride of +4. This is quite important as for fixed-size matrices,
   // this allows to hit the special case where it's vectorizable.
+  for(int k=0; k<2; ++k)
   {
+    if(k==1 && (m.innerSize()+4)*m.outerSize() > maxsize2)
+      break;
+    Scalar* array = (k==0 ? array1 : array2);
+    
     enum {
       InnerSize = MatrixType::InnerSizeAtCompileTime,
       OuterStrideAtCompileTime = InnerSize==Dynamic ? Dynamic : InnerSize+4
     };
     Map<MatrixType, Alignment, OuterStride<OuterStrideAtCompileTime> >
@@ -92,14 +114,22 @@
       for(int j = 0; j < m.innerSize(); ++j)
       {
         VERIFY(array[map.outerStride()*i+j] == m.coeffByOuterInner(i,j));
         VERIFY(map.coeffByOuterInner(i,j) == m.coeffByOuterInner(i,j));
       }
+    VERIFY_IS_APPROX(s1*map,s1*m);
+    map *= s1;
+    VERIFY_IS_APPROX(map,s1*m);
   }
 
   // test both inner stride and outer stride
+  for(int k=0; k<2; ++k)
   {
+    if(k==1 && (2*m.innerSize()+1)*(m.outerSize()*2) > maxsize2)
+      break;
+    Scalar* array = (k==0 ? array1 : array2);
+    
     Map<MatrixType, Alignment, Stride<Dynamic,Dynamic> > map(array, rows, cols, Stride<Dynamic,Dynamic>(2*m.innerSize()+1, 2));
     map = m;
     VERIFY(map.outerStride() == 2*map.innerSize()+1);
     VERIFY(map.innerStride() == 2);
     for(int i = 0; i < m.outerSize(); ++i)
@@ -106,13 +136,16 @@
       for(int j = 0; j < m.innerSize(); ++j)
       {
         VERIFY(array[map.outerStride()*i+map.innerStride()*j] == m.coeffByOuterInner(i,j));
         VERIFY(map.coeffByOuterInner(i,j) == m.coeffByOuterInner(i,j));
       }
+    VERIFY_IS_APPROX(s1*map,s1*m);
+    map *= s1;
+    VERIFY_IS_APPROX(map,s1*m);
   }
 
-  internal::aligned_delete(a_array, arraysize+1);
+  internal::aligned_delete(a_array1, arraysize+1);
 }
 
 void test_mapstride()
 {
   for(int i = 0; i < g_repeat; i++) {

Index: 3rd_party/eigen/test/meta.cpp
==================================================================
--- 3rd_party/eigen/test/meta.cpp
+++ 3rd_party/eigen/test/meta.cpp
@@ -6,10 +6,16 @@
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
+
+template<typename From, typename To>
+bool check_is_convertible(const From&, const To&)
+{
+  return internal::is_convertible<From,To>::value;
+}
 
 void test_meta()
 {
   VERIFY((internal::conditional<(3<4),internal::true_type, internal::false_type>::type::value));
   VERIFY(( internal::is_same<float,float>::value));
@@ -49,10 +55,28 @@
   VERIFY(( internal::is_same<float,internal::remove_reference<float&>::type >::value));
   VERIFY(( internal::is_same<const float,internal::remove_reference<const float&>::type >::value));
   VERIFY(( internal::is_same<float,internal::remove_pointer<float*>::type >::value));
   VERIFY(( internal::is_same<const float,internal::remove_pointer<const float*>::type >::value));
   VERIFY(( internal::is_same<float,internal::remove_pointer<float* const >::type >::value));
+  
+  VERIFY(( internal::is_convertible<float,double>::value ));
+  VERIFY(( internal::is_convertible<int,double>::value ));
+  VERIFY(( internal::is_convertible<double,int>::value ));
+  VERIFY((!internal::is_convertible<std::complex<double>,double>::value ));
+  VERIFY(( internal::is_convertible<Array33f,Matrix3f>::value ));
+//   VERIFY((!internal::is_convertible<Matrix3f,Matrix3d>::value )); //does not work because the conversion is prevented by a static assertion
+  VERIFY((!internal::is_convertible<Array33f,int>::value ));
+  VERIFY((!internal::is_convertible<MatrixXf,float>::value ));
+  {
+    float f;
+    MatrixXf A, B;
+    VectorXf a, b;
+    VERIFY(( check_is_convertible(a.dot(b), f) ));
+    VERIFY(( check_is_convertible(a.transpose()*b, f) ));
+    VERIFY((!check_is_convertible(A*B, f) ));
+    VERIFY(( check_is_convertible(A*B, A) ));
+  }
   
   VERIFY(internal::meta_sqrt<1>::ret == 1);
   #define VERIFY_META_SQRT(X) VERIFY(internal::meta_sqrt<X>::ret == int(std::sqrt(double(X))))
   VERIFY_META_SQRT(2);
   VERIFY_META_SQRT(3);

Index: 3rd_party/eigen/test/metis_support.cpp
==================================================================
--- 3rd_party/eigen/test/metis_support.cpp
+++ 3rd_party/eigen/test/metis_support.cpp
@@ -1,28 +1,14 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #include "sparse_solver.h"
 #include <Eigen/SparseLU>
 #include <Eigen/MetisSupport>
 #include <unsupported/Eigen/SparseExtra>
 

Index: 3rd_party/eigen/test/mixingtypes.cpp
==================================================================
--- 3rd_party/eigen/test/mixingtypes.cpp
+++ 3rd_party/eigen/test/mixingtypes.cpp
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
@@ -13,18 +13,30 @@
 
 #ifndef EIGEN_NO_STATIC_ASSERT
 #define EIGEN_NO_STATIC_ASSERT // turn static asserts into runtime asserts in order to check them
 #endif
 
-// #ifndef EIGEN_DONT_VECTORIZE
-// #define EIGEN_DONT_VECTORIZE // SSE intrinsics aren't designed to allow mixing types
-// #endif
+#if defined(EIGEN_TEST_PART_1) || defined(EIGEN_TEST_PART_2) || defined(EIGEN_TEST_PART_3)
+
+#ifndef EIGEN_DONT_VECTORIZE
+#define EIGEN_DONT_VECTORIZE
+#endif
+
+#endif
+
+static bool g_called;
+#define EIGEN_SCALAR_BINARY_OP_PLUGIN { g_called |= (!internal::is_same<LhsScalar,RhsScalar>::value); }
 
 #include "main.h"
 
 using namespace std;
 
+#define VERIFY_MIX_SCALAR(XPR,REF) \
+  g_called = false; \
+  VERIFY_IS_APPROX(XPR,REF); \
+  VERIFY( g_called && #XPR" not properly optimized");
+
 template<int SizeAtCompileType> void mixingtypes(int size = SizeAtCompileType)
 {
   typedef std::complex<float>   CF;
   typedef std::complex<double>  CD;
   typedef Matrix<float, SizeAtCompileType, SizeAtCompileType> Mat_f;
@@ -36,34 +48,76 @@
   typedef Matrix<std::complex<float>, SizeAtCompileType, 1> Vec_cf;
   typedef Matrix<std::complex<double>, SizeAtCompileType, 1> Vec_cd;
 
   Mat_f mf    = Mat_f::Random(size,size);
   Mat_d md    = mf.template cast<double>();
+  //Mat_d rd    = md;
   Mat_cf mcf  = Mat_cf::Random(size,size);
   Mat_cd mcd  = mcf.template cast<complex<double> >();
+  Mat_cd rcd = mcd;
   Vec_f vf    = Vec_f::Random(size,1);
   Vec_d vd    = vf.template cast<double>();
   Vec_cf vcf  = Vec_cf::Random(size,1);
   Vec_cd vcd  = vcf.template cast<complex<double> >();
   float           sf  = internal::random<float>();
   double          sd  = internal::random<double>();
   complex<float>  scf = internal::random<complex<float> >();
   complex<double> scd = internal::random<complex<double> >();
 
-
   mf+mf;
-  VERIFY_RAISES_ASSERT(mf+md);
-  VERIFY_RAISES_ASSERT(mf+mcf);
+
+  float  epsf = std::sqrt(std::numeric_limits<float> ::min EIGEN_EMPTY ());
+  double epsd = std::sqrt(std::numeric_limits<double>::min EIGEN_EMPTY ());
+
+  while(std::abs(sf )<epsf) sf  = internal::random<float>();
+  while(std::abs(sd )<epsd) sf  = internal::random<double>();
+  while(std::abs(scf)<epsf) scf = internal::random<CF>();
+  while(std::abs(scd)<epsd) scd = internal::random<CD>();
+
+//   VERIFY_RAISES_ASSERT(mf+md); // does not even compile
+
+#ifdef EIGEN_DONT_VECTORIZE
   VERIFY_RAISES_ASSERT(vf=vd);
   VERIFY_RAISES_ASSERT(vf+=vd);
-  VERIFY_RAISES_ASSERT(mcd=md);
-
+#endif
+  
   // check scalar products
-  VERIFY_IS_APPROX(vcf * sf , vcf * complex<float>(sf));
-  VERIFY_IS_APPROX(sd * vcd, complex<double>(sd) * vcd);
-  VERIFY_IS_APPROX(vf * scf , vf.template cast<complex<float> >() * scf);
-  VERIFY_IS_APPROX(scd * vd, scd * vd.template cast<complex<double> >());
+  VERIFY_MIX_SCALAR(vcf * sf , vcf * complex<float>(sf));
+  VERIFY_MIX_SCALAR(sd * vcd , complex<double>(sd) * vcd);
+  VERIFY_MIX_SCALAR(vf * scf , vf.template cast<complex<float> >() * scf);
+  VERIFY_MIX_SCALAR(scd * vd , scd * vd.template cast<complex<double> >());
+
+  VERIFY_MIX_SCALAR(vcf * 2 , vcf * complex<float>(2));
+  VERIFY_MIX_SCALAR(vcf * 2.1 , vcf * complex<float>(2.1));
+  VERIFY_MIX_SCALAR(2 * vcf, vcf * complex<float>(2));
+  VERIFY_MIX_SCALAR(2.1 * vcf , vcf * complex<float>(2.1));
+
+  // check scalar quotients
+  VERIFY_MIX_SCALAR(vcf / sf , vcf / complex<float>(sf));
+  VERIFY_MIX_SCALAR(vf / scf , vf.template cast<complex<float> >() / scf);
+  VERIFY_MIX_SCALAR(vf.array()  / scf, vf.template cast<complex<float> >().array() / scf);
+  VERIFY_MIX_SCALAR(scd / vd.array() , scd / vd.template cast<complex<double> >().array());
+
+  // check scalar increment
+  VERIFY_MIX_SCALAR(vcf.array() + sf , vcf.array() + complex<float>(sf));
+  VERIFY_MIX_SCALAR(sd  + vcd.array(), complex<double>(sd) + vcd.array());
+  VERIFY_MIX_SCALAR(vf.array()  + scf, vf.template cast<complex<float> >().array() + scf);
+  VERIFY_MIX_SCALAR(scd + vd.array() , scd + vd.template cast<complex<double> >().array());
+
+  // check scalar subtractions
+  VERIFY_MIX_SCALAR(vcf.array() - sf , vcf.array() - complex<float>(sf));
+  VERIFY_MIX_SCALAR(sd  - vcd.array(), complex<double>(sd) - vcd.array());
+  VERIFY_MIX_SCALAR(vf.array()  - scf, vf.template cast<complex<float> >().array() - scf);
+  VERIFY_MIX_SCALAR(scd - vd.array() , scd - vd.template cast<complex<double> >().array());
+
+  // check scalar powers
+  VERIFY_MIX_SCALAR( pow(vcf.array(), sf),        Eigen::pow(vcf.array(), complex<float>(sf)) );
+  VERIFY_MIX_SCALAR( vcf.array().pow(sf) ,        Eigen::pow(vcf.array(), complex<float>(sf)) );
+  VERIFY_MIX_SCALAR( pow(sd, vcd.array()),        Eigen::pow(complex<double>(sd), vcd.array()) );
+  VERIFY_MIX_SCALAR( Eigen::pow(vf.array(), scf), Eigen::pow(vf.template cast<complex<float> >().array(), scf) );
+  VERIFY_MIX_SCALAR( vf.array().pow(scf) ,        Eigen::pow(vf.template cast<complex<float> >().array(), scf) );
+  VERIFY_MIX_SCALAR( Eigen::pow(scd, vd.array()), Eigen::pow(scd, vd.template cast<complex<double> >().array()) );
 
   // check dot product
   vf.dot(vf);
 #if 0 // we get other compilation errors here than just static asserts
   VERIFY_RAISES_ASSERT(vd.dot(vf));
@@ -73,10 +127,11 @@
   // check diagonal product
   VERIFY_IS_APPROX(vf.asDiagonal() * mcf, vf.template cast<complex<float> >().asDiagonal() * mcf);
   VERIFY_IS_APPROX(vcd.asDiagonal() * md, vcd.asDiagonal() * md.template cast<complex<double> >());
   VERIFY_IS_APPROX(mcf * vf.asDiagonal(), mcf * vf.template cast<complex<float> >().asDiagonal());
   VERIFY_IS_APPROX(md * vcd.asDiagonal(), md.template cast<complex<double> >() * vcd.asDiagonal());
+
 //   vd.asDiagonal() * mf;    // does not even compile
 //   vcd.asDiagonal() * mf;   // does not even compile
 
   // check inner product
   VERIFY_IS_APPROX((vf.transpose() * vcf).value(), (vf.template cast<complex<float> >().transpose() * vcf).value());
@@ -90,20 +145,33 @@
 
   Mat_cd mcd2 = mcd;
   VERIFY_IS_APPROX(mcd.array() *= md.array(), mcd2.array() *= md.array().template cast<std::complex<double> >());
   
   // check matrix-matrix products
-
   VERIFY_IS_APPROX(sd*md*mcd, (sd*md).template cast<CD>().eval()*mcd);
   VERIFY_IS_APPROX(sd*mcd*md, sd*mcd*md.template cast<CD>());
   VERIFY_IS_APPROX(scd*md*mcd, scd*md.template cast<CD>().eval()*mcd);
   VERIFY_IS_APPROX(scd*mcd*md, scd*mcd*md.template cast<CD>());
 
   VERIFY_IS_APPROX(sf*mf*mcf, sf*mf.template cast<CF>()*mcf);
   VERIFY_IS_APPROX(sf*mcf*mf, sf*mcf*mf.template cast<CF>());
   VERIFY_IS_APPROX(scf*mf*mcf, scf*mf.template cast<CF>()*mcf);
   VERIFY_IS_APPROX(scf*mcf*mf, scf*mcf*mf.template cast<CF>());
+
+  VERIFY_IS_APPROX(sd*md.adjoint()*mcd, (sd*md).template cast<CD>().eval().adjoint()*mcd);
+  VERIFY_IS_APPROX(sd*mcd.adjoint()*md, sd*mcd.adjoint()*md.template cast<CD>());
+  VERIFY_IS_APPROX(sd*md.adjoint()*mcd.adjoint(), (sd*md).template cast<CD>().eval().adjoint()*mcd.adjoint());
+  VERIFY_IS_APPROX(sd*mcd.adjoint()*md.adjoint(), sd*mcd.adjoint()*md.template cast<CD>().adjoint());
+  VERIFY_IS_APPROX(sd*md*mcd.adjoint(), (sd*md).template cast<CD>().eval()*mcd.adjoint());
+  VERIFY_IS_APPROX(sd*mcd*md.adjoint(), sd*mcd*md.template cast<CD>().adjoint());
+
+  VERIFY_IS_APPROX(sf*mf.adjoint()*mcf, (sf*mf).template cast<CF>().eval().adjoint()*mcf);
+  VERIFY_IS_APPROX(sf*mcf.adjoint()*mf, sf*mcf.adjoint()*mf.template cast<CF>());
+  VERIFY_IS_APPROX(sf*mf.adjoint()*mcf.adjoint(), (sf*mf).template cast<CF>().eval().adjoint()*mcf.adjoint());
+  VERIFY_IS_APPROX(sf*mcf.adjoint()*mf.adjoint(), sf*mcf.adjoint()*mf.template cast<CF>().adjoint());
+  VERIFY_IS_APPROX(sf*mf*mcf.adjoint(), (sf*mf).template cast<CF>().eval()*mcf.adjoint());
+  VERIFY_IS_APPROX(sf*mcf*mf.adjoint(), sf*mcf*mf.template cast<CF>().adjoint());
 
   VERIFY_IS_APPROX(sf*mf*vcf, (sf*mf).template cast<CF>().eval()*vcf);
   VERIFY_IS_APPROX(scf*mf*vcf,(scf*mf.template cast<CF>()).eval()*vcf);
   VERIFY_IS_APPROX(sf*mcf*vf, sf*mcf*vf.template cast<CF>());
   VERIFY_IS_APPROX(scf*mcf*vf,scf*mcf*vf.template cast<CF>());
@@ -120,13 +188,113 @@
 
   VERIFY_IS_APPROX(sd*vcd.adjoint()*md,  sd*vcd.adjoint()*md.template cast<CD>().eval());
   VERIFY_IS_APPROX(scd*vcd.adjoint()*md, scd*vcd.adjoint()*md.template cast<CD>().eval());
   VERIFY_IS_APPROX(sd*vd.adjoint()*mcd,  sd*vd.adjoint().template cast<CD>().eval()*mcd);
   VERIFY_IS_APPROX(scd*vd.adjoint()*mcd, scd*vd.adjoint().template cast<CD>().eval()*mcd);
+
+  VERIFY_IS_APPROX( sd*vcd.adjoint()*md.template triangularView<Upper>(),  sd*vcd.adjoint()*md.template cast<CD>().eval().template triangularView<Upper>());
+  VERIFY_IS_APPROX(scd*vcd.adjoint()*md.template triangularView<Lower>(), scd*vcd.adjoint()*md.template cast<CD>().eval().template triangularView<Lower>());
+  VERIFY_IS_APPROX( sd*vcd.adjoint()*md.transpose().template triangularView<Upper>(),  sd*vcd.adjoint()*md.transpose().template cast<CD>().eval().template triangularView<Upper>());
+  VERIFY_IS_APPROX(scd*vcd.adjoint()*md.transpose().template triangularView<Lower>(), scd*vcd.adjoint()*md.transpose().template cast<CD>().eval().template triangularView<Lower>());
+  VERIFY_IS_APPROX( sd*vd.adjoint()*mcd.template triangularView<Lower>(),  sd*vd.adjoint().template cast<CD>().eval()*mcd.template triangularView<Lower>());
+  VERIFY_IS_APPROX(scd*vd.adjoint()*mcd.template triangularView<Upper>(), scd*vd.adjoint().template cast<CD>().eval()*mcd.template triangularView<Upper>());
+  VERIFY_IS_APPROX( sd*vd.adjoint()*mcd.transpose().template triangularView<Lower>(),  sd*vd.adjoint().template cast<CD>().eval()*mcd.transpose().template triangularView<Lower>());
+  VERIFY_IS_APPROX(scd*vd.adjoint()*mcd.transpose().template triangularView<Upper>(), scd*vd.adjoint().template cast<CD>().eval()*mcd.transpose().template triangularView<Upper>());
+
+  // Not supported yet: trmm
+//   VERIFY_IS_APPROX(sd*mcd*md.template triangularView<Lower>(),  sd*mcd*md.template cast<CD>().eval().template triangularView<Lower>());
+//   VERIFY_IS_APPROX(scd*mcd*md.template triangularView<Upper>(), scd*mcd*md.template cast<CD>().eval().template triangularView<Upper>());
+//   VERIFY_IS_APPROX(sd*md*mcd.template triangularView<Lower>(),  sd*md.template cast<CD>().eval()*mcd.template triangularView<Lower>());
+//   VERIFY_IS_APPROX(scd*md*mcd.template triangularView<Upper>(), scd*md.template cast<CD>().eval()*mcd.template triangularView<Upper>());
+
+  // Not supported yet: symv
+//   VERIFY_IS_APPROX(sd*vcd.adjoint()*md.template selfadjointView<Upper>(),  sd*vcd.adjoint()*md.template cast<CD>().eval().template selfadjointView<Upper>());
+//   VERIFY_IS_APPROX(scd*vcd.adjoint()*md.template selfadjointView<Lower>(), scd*vcd.adjoint()*md.template cast<CD>().eval().template selfadjointView<Lower>());
+//   VERIFY_IS_APPROX(sd*vd.adjoint()*mcd.template selfadjointView<Lower>(),  sd*vd.adjoint().template cast<CD>().eval()*mcd.template selfadjointView<Lower>());
+//   VERIFY_IS_APPROX(scd*vd.adjoint()*mcd.template selfadjointView<Upper>(), scd*vd.adjoint().template cast<CD>().eval()*mcd.template selfadjointView<Upper>());
+
+  // Not supported yet: symm
+//   VERIFY_IS_APPROX(sd*vcd.adjoint()*md.template selfadjointView<Upper>(),  sd*vcd.adjoint()*md.template cast<CD>().eval().template selfadjointView<Upper>());
+//   VERIFY_IS_APPROX(scd*vcd.adjoint()*md.template selfadjointView<Upper>(), scd*vcd.adjoint()*md.template cast<CD>().eval().template selfadjointView<Upper>());
+//   VERIFY_IS_APPROX(sd*vd.adjoint()*mcd.template selfadjointView<Upper>(),  sd*vd.adjoint().template cast<CD>().eval()*mcd.template selfadjointView<Upper>());
+//   VERIFY_IS_APPROX(scd*vd.adjoint()*mcd.template selfadjointView<Upper>(), scd*vd.adjoint().template cast<CD>().eval()*mcd.template selfadjointView<Upper>());
+
+  rcd.setZero();
+  VERIFY_IS_APPROX(Mat_cd(rcd.template triangularView<Upper>() = sd * mcd * md),
+                   Mat_cd((sd * mcd * md.template cast<CD>().eval()).template triangularView<Upper>()));
+  VERIFY_IS_APPROX(Mat_cd(rcd.template triangularView<Upper>() = sd * md * mcd),
+                   Mat_cd((sd * md.template cast<CD>().eval() * mcd).template triangularView<Upper>()));
+  VERIFY_IS_APPROX(Mat_cd(rcd.template triangularView<Upper>() = scd * mcd * md),
+                   Mat_cd((scd * mcd * md.template cast<CD>().eval()).template triangularView<Upper>()));
+  VERIFY_IS_APPROX(Mat_cd(rcd.template triangularView<Upper>() = scd * md * mcd),
+                   Mat_cd((scd * md.template cast<CD>().eval() * mcd).template triangularView<Upper>()));
+
+
+  VERIFY_IS_APPROX( md.array()  * mcd.array(), md.template cast<CD>().eval().array() * mcd.array() );
+  VERIFY_IS_APPROX( mcd.array() * md.array(),  mcd.array() * md.template cast<CD>().eval().array() );
+
+  VERIFY_IS_APPROX( md.array()  + mcd.array(), md.template cast<CD>().eval().array() + mcd.array() );
+  VERIFY_IS_APPROX( mcd.array() + md.array(),  mcd.array() + md.template cast<CD>().eval().array() );
+
+  VERIFY_IS_APPROX( md.array()  - mcd.array(), md.template cast<CD>().eval().array() - mcd.array() );
+  VERIFY_IS_APPROX( mcd.array() - md.array(),  mcd.array() - md.template cast<CD>().eval().array() );
+
+  if(mcd.array().abs().minCoeff()>epsd)
+  {
+    VERIFY_IS_APPROX( md.array() / mcd.array(), md.template cast<CD>().eval().array() / mcd.array() );
+  }
+  if(md.array().abs().minCoeff()>epsd)
+  {
+    VERIFY_IS_APPROX( mcd.array() / md.array(), mcd.array() / md.template cast<CD>().eval().array() );
+  }
+
+  if(md.array().abs().minCoeff()>epsd || mcd.array().abs().minCoeff()>epsd)
+  {
+    VERIFY_IS_APPROX( md.array().pow(mcd.array()), md.template cast<CD>().eval().array().pow(mcd.array()) );
+    VERIFY_IS_APPROX( mcd.array().pow(md.array()),  mcd.array().pow(md.template cast<CD>().eval().array()) );
+
+    VERIFY_IS_APPROX( pow(md.array(),mcd.array()), md.template cast<CD>().eval().array().pow(mcd.array()) );
+    VERIFY_IS_APPROX( pow(mcd.array(),md.array()),  mcd.array().pow(md.template cast<CD>().eval().array()) );
+  }
+
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd = md, md.template cast<CD>().eval() );
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd += md, mcd + md.template cast<CD>().eval() );
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd -= md, mcd - md.template cast<CD>().eval() );
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd.array() *= md.array(), mcd.array() * md.template cast<CD>().eval().array() );
+  rcd = mcd;
+  if(md.array().abs().minCoeff()>epsd)
+  {
+    VERIFY_IS_APPROX( rcd.array() /= md.array(), mcd.array() / md.template cast<CD>().eval().array() );
+  }
+
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd.noalias() += md + mcd*md, mcd + (md.template cast<CD>().eval()) + mcd*(md.template cast<CD>().eval()));
+
+  VERIFY_IS_APPROX( rcd.noalias()  = md*md,       ((md*md).eval().template cast<CD>()) );
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd.noalias() += md*md, mcd + ((md*md).eval().template cast<CD>()) );
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd.noalias() -= md*md, mcd - ((md*md).eval().template cast<CD>()) );
+
+  VERIFY_IS_APPROX( rcd.noalias()  = mcd + md*md,       mcd + ((md*md).eval().template cast<CD>()) );
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd.noalias() += mcd + md*md, mcd + mcd + ((md*md).eval().template cast<CD>()) );
+  rcd = mcd;
+  VERIFY_IS_APPROX( rcd.noalias() -= mcd + md*md,           - ((md*md).eval().template cast<CD>()) );
 }
 
 void test_mixingtypes()
 {
-  CALL_SUBTEST_1(mixingtypes<3>());
-  CALL_SUBTEST_2(mixingtypes<4>());
-  CALL_SUBTEST_3(mixingtypes<Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE)));
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1(mixingtypes<3>());
+    CALL_SUBTEST_2(mixingtypes<4>());
+    CALL_SUBTEST_3(mixingtypes<Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE)));
+
+    CALL_SUBTEST_4(mixingtypes<3>());
+    CALL_SUBTEST_5(mixingtypes<4>());
+    CALL_SUBTEST_6(mixingtypes<Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE)));
+  }
 }

ADDED   3rd_party/eigen/test/mpl2only.cpp
Index: 3rd_party/eigen/test/mpl2only.cpp
==================================================================
--- 3rd_party/eigen/test/mpl2only.cpp
+++ 3rd_party/eigen/test/mpl2only.cpp
@@ -0,0 +1,22 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_MPL2_ONLY
+#include <Eigen/Dense>
+#include <Eigen/SparseCore>
+#include <Eigen/SparseLU>
+#include <Eigen/SparseQR>
+#include <Eigen/Sparse>
+#include <Eigen/IterativeLinearSolvers>
+#include <Eigen/Eigen>
+
+int main()
+{
+  return 0;
+}

Index: 3rd_party/eigen/test/nesting_ops.cpp
==================================================================
--- 3rd_party/eigen/test/nesting_ops.cpp
+++ 3rd_party/eigen/test/nesting_ops.cpp
@@ -1,19 +1,40 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#define TEST_ENABLE_TEMPORARY_TRACKING
+
 #include "main.h"
 
-template <typename MatrixType> void run_nesting_ops(const MatrixType& _m)
+template <int N, typename XprType>
+void use_n_times(const XprType &xpr)
+{
+  typename internal::nested_eval<XprType,N>::type mat(xpr);
+  typename XprType::PlainObject res(mat.rows(), mat.cols());
+  nb_temporaries--; // remove res
+  res.setZero();
+  for(int i=0; i<N; ++i)
+    res += mat;
+}
+
+template <int N, typename ReferenceType, typename XprType>
+bool verify_eval_type(const XprType &, const ReferenceType&)
+{
+  typedef typename internal::nested_eval<XprType,N>::type EvalType;
+  return internal::is_same<typename internal::remove_all<EvalType>::type, typename internal::remove_all<ReferenceType>::type>::value;
+}
+
+template <typename MatrixType> void run_nesting_ops_1(const MatrixType& _m)
 {
-  typename MatrixType::Nested m(_m);
+  typename internal::nested_eval<MatrixType,2>::type m(_m);
 
   // Make really sure that we are in debug mode!
   VERIFY_RAISES_ASSERT(eigen_assert(false));
 
   // The only intention of these tests is to ensure that this code does
@@ -21,13 +42,66 @@
   VERIFY_IS_APPROX( (m.transpose() * m).diagonal().sum(), (m.transpose() * m).diagonal().sum() );
   VERIFY_IS_APPROX( (m.transpose() * m).diagonal().array().abs().sum(), (m.transpose() * m).diagonal().array().abs().sum() );
 
   VERIFY_IS_APPROX( (m.transpose() * m).array().abs().sum(), (m.transpose() * m).array().abs().sum() );
 }
+
+template <typename MatrixType> void run_nesting_ops_2(const MatrixType& _m)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  Index rows = _m.rows();
+  Index cols = _m.cols();
+  MatrixType m1 = MatrixType::Random(rows,cols);
+  Matrix<Scalar,MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime,ColMajor> m2;
+
+  if((MatrixType::SizeAtCompileTime==Dynamic))
+  {
+    VERIFY_EVALUATION_COUNT( use_n_times<1>(m1 + m1*m1), 1 );
+    VERIFY_EVALUATION_COUNT( use_n_times<10>(m1 + m1*m1), 1 );
+
+    VERIFY_EVALUATION_COUNT( use_n_times<1>(m1.template triangularView<Lower>().solve(m1.col(0))), 1 );
+    VERIFY_EVALUATION_COUNT( use_n_times<10>(m1.template triangularView<Lower>().solve(m1.col(0))), 1 );
+
+    VERIFY_EVALUATION_COUNT( use_n_times<1>(Scalar(2)*m1.template triangularView<Lower>().solve(m1.col(0))), 2 ); // FIXME could be one by applying the scaling in-place on the solve result
+    VERIFY_EVALUATION_COUNT( use_n_times<1>(m1.col(0)+m1.template triangularView<Lower>().solve(m1.col(0))), 2 ); // FIXME could be one by adding m1.col() inplace
+    VERIFY_EVALUATION_COUNT( use_n_times<10>(m1.col(0)+m1.template triangularView<Lower>().solve(m1.col(0))), 2 );
+  }
+
+  {
+    VERIFY( verify_eval_type<10>(m1, m1) );
+    if(!NumTraits<Scalar>::IsComplex)
+    {
+      VERIFY( verify_eval_type<3>(2*m1, 2*m1) );
+      VERIFY( verify_eval_type<4>(2*m1, m1) );
+    }
+    else
+    {
+      VERIFY( verify_eval_type<2>(2*m1, 2*m1) );
+      VERIFY( verify_eval_type<3>(2*m1, m1) );
+    }
+    VERIFY( verify_eval_type<2>(m1+m1, m1+m1) );
+    VERIFY( verify_eval_type<3>(m1+m1, m1) );
+    VERIFY( verify_eval_type<1>(m1*m1.transpose(), m2) );
+    VERIFY( verify_eval_type<1>(m1*(m1+m1).transpose(), m2) );
+    VERIFY( verify_eval_type<2>(m1*m1.transpose(), m2) );
+    VERIFY( verify_eval_type<1>(m1+m1*m1, m1) );
+
+    VERIFY( verify_eval_type<1>(m1.template triangularView<Lower>().solve(m1), m1) );
+    VERIFY( verify_eval_type<1>(m1+m1.template triangularView<Lower>().solve(m1), m1) );
+  }
+}
+
 
 void test_nesting_ops()
 {
-  CALL_SUBTEST_1(run_nesting_ops(MatrixXf::Random(25,25)));
-  CALL_SUBTEST_2(run_nesting_ops(MatrixXd::Random(25,25)));
-  CALL_SUBTEST_3(run_nesting_ops(Matrix4f::Random()));
-  CALL_SUBTEST_4(run_nesting_ops(Matrix4d::Random()));
+  CALL_SUBTEST_1(run_nesting_ops_1(MatrixXf::Random(25,25)));
+  CALL_SUBTEST_2(run_nesting_ops_1(MatrixXcd::Random(25,25)));
+  CALL_SUBTEST_3(run_nesting_ops_1(Matrix4f::Random()));
+  CALL_SUBTEST_4(run_nesting_ops_1(Matrix2d::Random()));
+
+  Index s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
+  CALL_SUBTEST_1( run_nesting_ops_2(MatrixXf(s,s)) );
+  CALL_SUBTEST_2( run_nesting_ops_2(MatrixXcd(s,s)) );
+  CALL_SUBTEST_3( run_nesting_ops_2(Matrix4f()) );
+  CALL_SUBTEST_4( run_nesting_ops_2(Matrix2d()) );
+  TEST_SET_BUT_UNUSED_VARIABLE(s)
 }

Index: 3rd_party/eigen/test/nomalloc.cpp
==================================================================
--- 3rd_party/eigen/test/nomalloc.cpp
+++ 3rd_party/eigen/test/nomalloc.cpp
@@ -6,24 +6,14 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
-// this hack is needed to make this file compiles with -pedantic (gcc)
-#ifdef __GNUC__
-#define throw(X)
-#endif
-
-#ifdef __INTEL_COMPILER
-  // disable "warning #76: argument to macro is empty" produced by the above hack
-  #pragma warning disable 76
-#endif
-
 // discard stack allocation as that too bypasses malloc
 #define EIGEN_STACK_ALLOCATION_LIMIT 0
-// any heap allocation will raise an assert
-#define EIGEN_NO_MALLOC
+// heap allocation will raise an assert if enabled at runtime
+#define EIGEN_RUNTIME_NO_MALLOC
 
 #include "main.h"
 #include <Eigen/Cholesky>
 #include <Eigen/Eigenvalues>
 #include <Eigen/LU>
@@ -86,18 +76,19 @@
   m2.row(0).noalias() -= m1.col(0).adjoint() * m1.template selfadjointView<Upper>();
   m2.row(0).noalias() -= m1.col(0).adjoint() * m1.adjoint().template selfadjointView<Upper>();
   VERIFY_IS_APPROX(m2,m2);
   
   m2.template selfadjointView<Lower>().rankUpdate(m1.col(0),-1);
-  m2.template selfadjointView<Lower>().rankUpdate(m1.row(0),-1);
+  m2.template selfadjointView<Upper>().rankUpdate(m1.row(0),-1);
+  m2.template selfadjointView<Lower>().rankUpdate(m1.col(0), m1.col(0)); // rank-2
 
   // The following fancy matrix-matrix products are not safe yet regarding static allocation
-//   m1 += m1.template triangularView<Upper>() * m2.col(;
-//   m1.template selfadjointView<Lower>().rankUpdate(m2);
-//   m1 += m1.template triangularView<Upper>() * m2;
-//   m1 += m1.template selfadjointView<Lower>() * m2;
-//   VERIFY_IS_APPROX(m1,m1);
+  m2.template selfadjointView<Lower>().rankUpdate(m1);
+  m2 += m2.template triangularView<Upper>() * m1;
+  m2.template triangularView<Upper>() = m2 * m2;
+  m1 += m1.template selfadjointView<Lower>() * m2;
+  VERIFY_IS_APPROX(m2,m2);
 }
 
 template<typename Scalar>
 void ctms_decompositions()
 {
@@ -169,11 +160,11 @@
   // default constructors:
   Eigen::MatrixXd A;
   Eigen::VectorXd v;
   // explicit zero-sized:
   Eigen::ArrayXXd A0(0,0);
-  Eigen::ArrayXd v0(std::ptrdiff_t(0)); // FIXME ArrayXd(0) is ambiguous
+  Eigen::ArrayXd v0(0);
 
   // assigning empty objects to each other:
   A=A0;
   v=v0;
 }
@@ -181,32 +172,58 @@
 template<typename MatrixType> void test_reference(const MatrixType& m) {
   typedef typename MatrixType::Scalar Scalar;
   enum { Flag          =  MatrixType::IsRowMajor ? Eigen::RowMajor : Eigen::ColMajor};
   enum { TransposeFlag = !MatrixType::IsRowMajor ? Eigen::RowMajor : Eigen::ColMajor};
   typename MatrixType::Index rows = m.rows(), cols=m.cols();
+  typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Flag         > MatrixX;
+  typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, TransposeFlag> MatrixXT;
   // Dynamic reference:
-  typedef Eigen::Ref<const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Flag         > > Ref;
-  typedef Eigen::Ref<const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, TransposeFlag> > RefT;
+  typedef Eigen::Ref<const MatrixX  > Ref;
+  typedef Eigen::Ref<const MatrixXT > RefT;
 
   Ref r1(m);
   Ref r2(m.block(rows/3, cols/4, rows/2, cols/2));
   RefT r3(m.transpose());
   RefT r4(m.topLeftCorner(rows/2, cols/2).transpose());
 
   VERIFY_RAISES_ASSERT(RefT r5(m));
   VERIFY_RAISES_ASSERT(Ref r6(m.transpose()));
   VERIFY_RAISES_ASSERT(Ref r7(Scalar(2) * m));
+
+  // Copy constructors shall also never malloc
+  Ref r8 = r1;
+  RefT r9 = r3;
+
+  // Initializing from a compatible Ref shall also never malloc
+  Eigen::Ref<const MatrixX, Unaligned, Stride<Dynamic, Dynamic> > r10=r8, r11=m;
+
+  // Initializing from an incompatible Ref will malloc:
+  typedef Eigen::Ref<const MatrixX, Aligned> RefAligned;
+  VERIFY_RAISES_ASSERT(RefAligned r12=r10);
+  VERIFY_RAISES_ASSERT(Ref r13=r10); // r10 has more dynamic strides
+
 }
 
 void test_nomalloc()
 {
+  // create some dynamic objects
+  Eigen::MatrixXd M1 = MatrixXd::Random(3,3);
+  Ref<const MatrixXd> R1 = 2.0*M1; // Ref requires temporary
+
+  // from here on prohibit malloc:
+  Eigen::internal::set_is_malloc_allowed(false);
+
   // check that our operator new is indeed called:
   VERIFY_RAISES_ASSERT(MatrixXd dummy(MatrixXd::Random(3,3)));
   CALL_SUBTEST_1(nomalloc(Matrix<float, 1, 1>()) );
   CALL_SUBTEST_2(nomalloc(Matrix4d()) );
   CALL_SUBTEST_3(nomalloc(Matrix<float,32,32>()) );
   
   // Check decomposition modules with dynamic matrices that have a known compile-time max size (ctms)
   CALL_SUBTEST_4(ctms_decompositions<float>());
+
   CALL_SUBTEST_5(test_zerosized());
+
   CALL_SUBTEST_6(test_reference(Matrix<float,32,32>()));
+  CALL_SUBTEST_7(test_reference(R1));
+  CALL_SUBTEST_8(Ref<MatrixXd> R2 = M1.topRows<2>(); test_reference(R2));
 }

Index: 3rd_party/eigen/test/nullary.cpp
==================================================================
--- 3rd_party/eigen/test/nullary.cpp
+++ 3rd_party/eigen/test/nullary.cpp
@@ -1,9 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2010-2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -10,11 +11,10 @@
 #include "main.h"
 
 template<typename MatrixType>
 bool equalsIdentity(const MatrixType& A)
 {
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   Scalar zero = static_cast<Scalar>(0);
 
   bool offDiagOK = true;
   for (Index i = 0; i < A.rows(); ++i) {
@@ -28,54 +28,107 @@
     }
   }
 
   bool diagOK = (A.diagonal().array() == 1).all();
   return offDiagOK && diagOK;
+
+}
+
+template<typename VectorType>
+void check_extremity_accuracy(const VectorType &v, const typename VectorType::Scalar &low, const typename VectorType::Scalar &high)
+{
+  typedef typename VectorType::Scalar Scalar;
+  typedef typename VectorType::RealScalar RealScalar;
+
+  RealScalar prec = internal::is_same<RealScalar,float>::value ? NumTraits<RealScalar>::dummy_precision()*10 : NumTraits<RealScalar>::dummy_precision()/10;
+  Index size = v.size();
+
+  if(size<20)
+    return;
+
+  for (int i=0; i<size; ++i)
+  {
+    if(i<5 || i>size-6)
+    {
+      Scalar ref = (low*RealScalar(size-i-1))/RealScalar(size-1) + (high*RealScalar(i))/RealScalar(size-1);
+      if(std::abs(ref)>1)
+      {
+        if(!internal::isApprox(v(i), ref, prec))
+          std::cout << v(i) << " != " << ref << "  ; relative error: " << std::abs((v(i)-ref)/ref) << "  ; required precision: " << prec << "  ; range: " << low << "," << high << "  ; i: " << i << "\n";
+        VERIFY(internal::isApprox(v(i), (low*RealScalar(size-i-1))/RealScalar(size-1) + (high*RealScalar(i))/RealScalar(size-1), prec));
+      }
+    }
+  }
 }
 
 template<typename VectorType>
 void testVectorType(const VectorType& base)
 {
-  typedef typename internal::traits<VectorType>::Index Index;
-  typedef typename internal::traits<VectorType>::Scalar Scalar;
+  typedef typename VectorType::Scalar Scalar;
+  typedef typename VectorType::RealScalar RealScalar;
 
   const Index size = base.size();
   
   Scalar high = internal::random<Scalar>(-500,500);
   Scalar low = (size == 1 ? high : internal::random<Scalar>(-500,500));
   if (low>high) std::swap(low,high);
 
+  // check low==high
+  if(internal::random<float>(0.f,1.f)<0.05f)
+    low = high;
+  // check abs(low) >> abs(high)
+  else if(size>2 && std::numeric_limits<RealScalar>::max_exponent10>0 && internal::random<float>(0.f,1.f)<0.1f)
+    low = -internal::random<Scalar>(1,2) * RealScalar(std::pow(RealScalar(10),std::numeric_limits<RealScalar>::max_exponent10/2));
+
   const Scalar step = ((size == 1) ? 1 : (high-low)/(size-1));
 
   // check whether the result yields what we expect it to do
   VectorType m(base);
   m.setLinSpaced(size,low,high);
 
-  VectorType n(size);
-  for (int i=0; i<size; ++i)
-    n(i) = low+i*step;
-
-  VERIFY_IS_APPROX(m,n);
-
-  // random access version
-  m = VectorType::LinSpaced(size,low,high);
-  VERIFY_IS_APPROX(m,n);
-
-  // Assignment of a RowVectorXd to a MatrixXd (regression test for bug #79).
-  VERIFY( (MatrixXd(RowVectorXd::LinSpaced(3, 0, 1)) - RowVector3d(0, 0.5, 1)).norm() < std::numeric_limits<Scalar>::epsilon() );
-
-  // These guys sometimes fail! This is not good. Any ideas how to fix them!?
-  //VERIFY( m(m.size()-1) == high );
-  //VERIFY( m(0) == low );
-
-  // sequential access version
-  m = VectorType::LinSpaced(Sequential,size,low,high);
-  VERIFY_IS_APPROX(m,n);
-
-  // These guys sometimes fail! This is not good. Any ideas how to fix them!?
-  //VERIFY( m(m.size()-1) == high );
-  //VERIFY( m(0) == low );
+  if(!NumTraits<Scalar>::IsInteger)
+  {
+    VectorType n(size);
+    for (int i=0; i<size; ++i)
+      n(i) = low+i*step;
+    VERIFY_IS_APPROX(m,n);
+
+    CALL_SUBTEST( check_extremity_accuracy(m, low, high) );
+  }
+
+  if((!NumTraits<Scalar>::IsInteger) || ((high-low)>=size && (Index(high-low)%(size-1))==0) || (Index(high-low+1)<size && (size%Index(high-low+1))==0))
+  {
+    VectorType n(size);
+    if((!NumTraits<Scalar>::IsInteger) || (high-low>=size))
+      for (int i=0; i<size; ++i)
+        n(i) = size==1 ? low : (low + ((high-low)*Scalar(i))/(size-1));
+    else
+      for (int i=0; i<size; ++i)
+        n(i) = size==1 ? low : low + Scalar((double(high-low+1)*double(i))/double(size));
+    VERIFY_IS_APPROX(m,n);
+
+    // random access version
+    m = VectorType::LinSpaced(size,low,high);
+    VERIFY_IS_APPROX(m,n);
+    VERIFY( internal::isApprox(m(m.size()-1),high) );
+    VERIFY( size==1 || internal::isApprox(m(0),low) );
+    VERIFY_IS_EQUAL(m(m.size()-1) , high);
+    if(!NumTraits<Scalar>::IsInteger)
+      CALL_SUBTEST( check_extremity_accuracy(m, low, high) );
+  }
+
+  VERIFY( m(m.size()-1) <= high );
+  VERIFY( (m.array() <= high).all() );
+  VERIFY( (m.array() >= low).all() );
+
+
+  VERIFY( m(m.size()-1) >= low );
+  if(size>=1)
+  {
+    VERIFY( internal::isApprox(m(0),low) );
+    VERIFY_IS_EQUAL(m(0) , low);
+  }
 
   // check whether everything works with row and col major vectors
   Matrix<Scalar,Dynamic,1> row_vector(size);
   Matrix<Scalar,1,Dynamic> col_vector(size);
   row_vector.setLinSpaced(size,low,high);
@@ -93,39 +146,159 @@
   scalar.setLinSpaced(1,low,high);
   VERIFY_IS_APPROX( scalar, ScalarMatrix::Constant(high) );
   VERIFY_IS_APPROX( ScalarMatrix::LinSpaced(1,low,high), ScalarMatrix::Constant(high) );
 
   // regression test for bug 526 (linear vectorized transversal)
-  if (size > 1) {
+  if (size > 1 && (!NumTraits<Scalar>::IsInteger)) {
     m.tail(size-1).setLinSpaced(low, high);
     VERIFY_IS_APPROX(m(size-1), high);
   }
+
+  // regression test for bug 1383 (LinSpaced with empty size/range)
+  {
+    Index n0 = VectorType::SizeAtCompileTime==Dynamic ? 0 : VectorType::SizeAtCompileTime;
+    low = internal::random<Scalar>();
+    m = VectorType::LinSpaced(n0,low,low-1);
+    VERIFY(m.size()==n0);
+
+    if(VectorType::SizeAtCompileTime==Dynamic)
+    {
+      VERIFY_IS_EQUAL(VectorType::LinSpaced(n0,0,Scalar(n0-1)).sum(),Scalar(0));
+      VERIFY_IS_EQUAL(VectorType::LinSpaced(n0,low,low-1).sum(),Scalar(0));
+    }
+
+    m.setLinSpaced(n0,0,Scalar(n0-1));
+    VERIFY(m.size()==n0);
+    m.setLinSpaced(n0,low,low-1);
+    VERIFY(m.size()==n0);
+
+    // empty range only:
+    VERIFY_IS_APPROX(VectorType::LinSpaced(size,low,low),VectorType::Constant(size,low));
+    m.setLinSpaced(size,low,low);
+    VERIFY_IS_APPROX(m,VectorType::Constant(size,low));
+
+    if(NumTraits<Scalar>::IsInteger)
+    {
+      VERIFY_IS_APPROX( VectorType::LinSpaced(size,low,Scalar(low+size-1)), VectorType::LinSpaced(size,Scalar(low+size-1),low).reverse() );
+
+      if(VectorType::SizeAtCompileTime==Dynamic)
+      {
+        // Check negative multiplicator path:
+        for(Index k=1; k<5; ++k)
+          VERIFY_IS_APPROX( VectorType::LinSpaced(size,low,Scalar(low+(size-1)*k)), VectorType::LinSpaced(size,Scalar(low+(size-1)*k),low).reverse() );
+        // Check negative divisor path:
+        for(Index k=1; k<5; ++k)
+          VERIFY_IS_APPROX( VectorType::LinSpaced(size*k,low,Scalar(low+size-1)), VectorType::LinSpaced(size*k,Scalar(low+size-1),low).reverse() );
+      }
+    }
+  }
 }
 
 template<typename MatrixType>
 void testMatrixType(const MatrixType& m)
 {
-  typedef typename MatrixType::Index Index;
+  using std::abs;
   const Index rows = m.rows();
   const Index cols = m.cols();
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+
+  Scalar s1;
+  do {
+    s1 = internal::random<Scalar>();
+  } while(abs(s1)<RealScalar(1e-5) && (!NumTraits<Scalar>::IsInteger));
 
   MatrixType A;
   A.setIdentity(rows, cols);
   VERIFY(equalsIdentity(A));
   VERIFY(equalsIdentity(MatrixType::Identity(rows, cols)));
+
+
+  A = MatrixType::Constant(rows,cols,s1);
+  Index i = internal::random<Index>(0,rows-1);
+  Index j = internal::random<Index>(0,cols-1);
+  VERIFY_IS_APPROX( MatrixType::Constant(rows,cols,s1)(i,j), s1 );
+  VERIFY_IS_APPROX( MatrixType::Constant(rows,cols,s1).coeff(i,j), s1 );
+  VERIFY_IS_APPROX( A(i,j), s1 );
 }
 
 void test_nullary()
 {
   CALL_SUBTEST_1( testMatrixType(Matrix2d()) );
   CALL_SUBTEST_2( testMatrixType(MatrixXcf(internal::random<int>(1,300),internal::random<int>(1,300))) );
   CALL_SUBTEST_3( testMatrixType(MatrixXf(internal::random<int>(1,300),internal::random<int>(1,300))) );
   
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_4( testVectorType(VectorXd(internal::random<int>(1,300))) );
+  for(int i = 0; i < g_repeat*10; i++) {
+    CALL_SUBTEST_4( testVectorType(VectorXd(internal::random<int>(1,30000))) );
     CALL_SUBTEST_5( testVectorType(Vector4d()) );  // regression test for bug 232
     CALL_SUBTEST_6( testVectorType(Vector3d()) );
-    CALL_SUBTEST_7( testVectorType(VectorXf(internal::random<int>(1,300))) );
+    CALL_SUBTEST_7( testVectorType(VectorXf(internal::random<int>(1,30000))) );
     CALL_SUBTEST_8( testVectorType(Vector3f()) );
+    CALL_SUBTEST_8( testVectorType(Vector4f()) );
+    CALL_SUBTEST_8( testVectorType(Matrix<float,8,1>()) );
     CALL_SUBTEST_8( testVectorType(Matrix<float,1,1>()) );
+
+    CALL_SUBTEST_9( testVectorType(VectorXi(internal::random<int>(1,10))) );
+    CALL_SUBTEST_9( testVectorType(VectorXi(internal::random<int>(9,300))) );
+    CALL_SUBTEST_9( testVectorType(Matrix<int,1,1>()) );
+  }
+
+#ifdef EIGEN_TEST_PART_6
+  // Assignment of a RowVectorXd to a MatrixXd (regression test for bug #79).
+  VERIFY( (MatrixXd(RowVectorXd::LinSpaced(3, 0, 1)) - RowVector3d(0, 0.5, 1)).norm() < std::numeric_limits<double>::epsilon() );
+#endif
+
+#ifdef EIGEN_TEST_PART_9
+  // Check possible overflow issue
+  {
+    int n = 60000;
+    ArrayXi a1(n), a2(n);
+    a1.setLinSpaced(n, 0, n-1);
+    for(int i=0; i<n; ++i)
+      a2(i) = i;
+    VERIFY_IS_APPROX(a1,a2);
+  }
+#endif
+
+#ifdef EIGEN_TEST_PART_10
+  // check some internal logic
+  VERIFY((  internal::has_nullary_operator<internal::scalar_constant_op<double> >::value ));
+  VERIFY(( !internal::has_unary_operator<internal::scalar_constant_op<double> >::value ));
+  VERIFY(( !internal::has_binary_operator<internal::scalar_constant_op<double> >::value ));
+  VERIFY((  internal::functor_has_linear_access<internal::scalar_constant_op<double> >::ret ));
+
+  VERIFY(( !internal::has_nullary_operator<internal::scalar_identity_op<double> >::value ));
+  VERIFY(( !internal::has_unary_operator<internal::scalar_identity_op<double> >::value ));
+  VERIFY((  internal::has_binary_operator<internal::scalar_identity_op<double> >::value ));
+  VERIFY(( !internal::functor_has_linear_access<internal::scalar_identity_op<double> >::ret ));
+
+  VERIFY(( !internal::has_nullary_operator<internal::linspaced_op<float,float> >::value ));
+  VERIFY((  internal::has_unary_operator<internal::linspaced_op<float,float> >::value ));
+  VERIFY(( !internal::has_binary_operator<internal::linspaced_op<float,float> >::value ));
+  VERIFY((  internal::functor_has_linear_access<internal::linspaced_op<float,float> >::ret ));
+
+  // Regression unit test for a weird MSVC bug.
+  // Search "nullary_wrapper_workaround_msvc" in CoreEvaluators.h for the details.
+  // See also traits<Ref>::match.
+  {
+    MatrixXf A = MatrixXf::Random(3,3);
+    Ref<const MatrixXf> R = 2.0*A;
+    VERIFY_IS_APPROX(R, A+A);
+
+    Ref<const MatrixXf> R1 = MatrixXf::Random(3,3)+A;
+
+    VectorXi V = VectorXi::Random(3);
+    Ref<const VectorXi> R2 = VectorXi::LinSpaced(3,1,3)+V;
+    VERIFY_IS_APPROX(R2, V+Vector3i(1,2,3));
+
+    VERIFY((  internal::has_nullary_operator<internal::scalar_constant_op<float> >::value ));
+    VERIFY(( !internal::has_unary_operator<internal::scalar_constant_op<float> >::value ));
+    VERIFY(( !internal::has_binary_operator<internal::scalar_constant_op<float> >::value ));
+    VERIFY((  internal::functor_has_linear_access<internal::scalar_constant_op<float> >::ret ));
+
+    VERIFY(( !internal::has_nullary_operator<internal::linspaced_op<int,int> >::value ));
+    VERIFY((  internal::has_unary_operator<internal::linspaced_op<int,int> >::value ));
+    VERIFY(( !internal::has_binary_operator<internal::linspaced_op<int,int> >::value ));
+    VERIFY((  internal::functor_has_linear_access<internal::linspaced_op<int,int> >::ret ));
   }
+#endif
 }

ADDED   3rd_party/eigen/test/numext.cpp
Index: 3rd_party/eigen/test/numext.cpp
==================================================================
--- 3rd_party/eigen/test/numext.cpp
+++ 3rd_party/eigen/test/numext.cpp
@@ -0,0 +1,53 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2017 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+template<typename T>
+void check_abs() {
+  typedef typename NumTraits<T>::Real Real;
+
+  if(NumTraits<T>::IsSigned)
+    VERIFY_IS_EQUAL(numext::abs(-T(1)), T(1));
+  VERIFY_IS_EQUAL(numext::abs(T(0)), T(0));
+  VERIFY_IS_EQUAL(numext::abs(T(1)), T(1));
+
+  for(int k=0; k<g_repeat*100; ++k)
+  {
+    T x = internal::random<T>();
+    if(!internal::is_same<T,bool>::value)
+      x = x/Real(2);
+    if(NumTraits<T>::IsSigned)
+    {
+      VERIFY_IS_EQUAL(numext::abs(x), numext::abs(-x));
+      VERIFY( numext::abs(-x) >= Real(0));
+    }
+    VERIFY( numext::abs(x) >= Real(0));
+    VERIFY_IS_APPROX( numext::abs2(x), numext::abs2(numext::abs(x)) );
+  }
+}
+
+void test_numext() {
+  CALL_SUBTEST( check_abs<bool>() );
+  CALL_SUBTEST( check_abs<signed char>() );
+  CALL_SUBTEST( check_abs<unsigned char>() );
+  CALL_SUBTEST( check_abs<short>() );
+  CALL_SUBTEST( check_abs<unsigned short>() );
+  CALL_SUBTEST( check_abs<int>() );
+  CALL_SUBTEST( check_abs<unsigned int>() );
+  CALL_SUBTEST( check_abs<long>() );
+  CALL_SUBTEST( check_abs<unsigned long>() );
+  CALL_SUBTEST( check_abs<half>() );
+  CALL_SUBTEST( check_abs<float>() );
+  CALL_SUBTEST( check_abs<double>() );
+  CALL_SUBTEST( check_abs<long double>() );
+
+  CALL_SUBTEST( check_abs<std::complex<float> >() );
+  CALL_SUBTEST( check_abs<std::complex<double> >() );
+}

Index: 3rd_party/eigen/test/packetmath.cpp
==================================================================
--- 3rd_party/eigen/test/packetmath.cpp
+++ 3rd_party/eigen/test/packetmath.cpp
@@ -7,20 +7,32 @@
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
+#include "unsupported/Eigen/SpecialFunctions"
 
+#if defined __GNUC__ && __GNUC__>=6
+  #pragma GCC diagnostic ignored "-Wignored-attributes"
+#endif
 // using namespace Eigen;
+
+#ifdef EIGEN_VECTORIZE_SSE
+const bool g_vectorize_sse = true;
+#else
+const bool g_vectorize_sse = false;
+#endif
 
 namespace Eigen {
 namespace internal {
 template<typename T> T negate(const T& x) { return -x; }
 }
 }
 
-template<typename Scalar> bool isApproxAbs(const Scalar& a, const Scalar& b, const typename NumTraits<Scalar>::Real& refvalue)
+// NOTE: we disbale inlining for this function to workaround a GCC issue when using -O3 and the i387 FPU.
+template<typename Scalar> EIGEN_DONT_INLINE
+bool isApproxAbs(const Scalar& a, const Scalar& b, const typename NumTraits<Scalar>::Real& refvalue)
 {
   return internal::isMuchSmallerThan(a-b, refvalue);
 }
 
 template<typename Scalar> bool areApproxAbs(const Scalar* a, const Scalar* b, int size, const typename NumTraits<Scalar>::Real& refvalue)
@@ -27,11 +39,11 @@
 {
   for (int i=0; i<size; ++i)
   {
     if (!isApproxAbs(a[i],b[i],refvalue))
     {
-      std::cout << "[" << Map<const Matrix<Scalar,1,Dynamic> >(a,size) << "]" << " != " << Map<const Matrix<Scalar,1,Dynamic> >(b,size) << "\n";
+      std::cout << "ref: [" << Map<const Matrix<Scalar,1,Dynamic> >(a,size) << "]" << " != vec: [" << Map<const Matrix<Scalar,1,Dynamic> >(b,size) << "]\n";
       return false;
     }
   }
   return true;
 }
@@ -40,25 +52,17 @@
 {
   for (int i=0; i<size; ++i)
   {
     if (a[i]!=b[i] && !internal::isApprox(a[i],b[i]))
     {
-      std::cout << "[" << Map<const Matrix<Scalar,1,Dynamic> >(a,size) << "]" << " != " << Map<const Matrix<Scalar,1,Dynamic> >(b,size) << "\n";
+      std::cout << "ref: [" << Map<const Matrix<Scalar,1,Dynamic> >(a,size) << "]" << " != vec: [" << Map<const Matrix<Scalar,1,Dynamic> >(b,size) << "]\n";
       return false;
     }
   }
   return true;
 }
 
-
-#define CHECK_CWISE2(REFOP, POP) { \
-  for (int i=0; i<PacketSize; ++i) \
-    ref[i] = REFOP(data1[i], data1[i+PacketSize]); \
-  internal::pstore(data2, POP(internal::pload<Packet>(data1), internal::pload<Packet>(data1+PacketSize))); \
-  VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
-}
-
 #define CHECK_CWISE1(REFOP, POP) { \
   for (int i=0; i<PacketSize; ++i) \
     ref[i] = REFOP(data1[i]); \
   internal::pstore(data2, POP(internal::pload<Packet>(data1))); \
   VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
@@ -89,28 +93,38 @@
   for (int i=0; i<PacketSize; ++i) \
     ref[i] = REFOP(data1[i]); \
   h.store(data2, POP(h.load(data1))); \
   VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
 }
+
+#define CHECK_CWISE2_IF(COND, REFOP, POP) if(COND) { \
+  packet_helper<COND,Packet> h; \
+  for (int i=0; i<PacketSize; ++i) \
+    ref[i] = REFOP(data1[i], data1[i+PacketSize]); \
+  h.store(data2, POP(h.load(data1),h.load(data1+PacketSize))); \
+  VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
+}
 
 #define REF_ADD(a,b) ((a)+(b))
 #define REF_SUB(a,b) ((a)-(b))
 #define REF_MUL(a,b) ((a)*(b))
 #define REF_DIV(a,b) ((a)/(b))
 
 template<typename Scalar> void packetmath()
 {
   using std::abs;
-  typedef typename internal::packet_traits<Scalar>::type Packet;
-  const int PacketSize = internal::packet_traits<Scalar>::size;
+  typedef internal::packet_traits<Scalar> PacketTraits;
+  typedef typename PacketTraits::type Packet;
+  const int PacketSize = PacketTraits::size;
   typedef typename NumTraits<Scalar>::Real RealScalar;
 
-  const int size = PacketSize*4;
-  EIGEN_ALIGN16 Scalar data1[internal::packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN16 Scalar data2[internal::packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN16 Packet packets[PacketSize*2];
-  EIGEN_ALIGN16 Scalar ref[internal::packet_traits<Scalar>::size*4];
+  const int max_size = PacketSize > 4 ? PacketSize : 4;
+  const int size = PacketSize*max_size;
+  EIGEN_ALIGN_MAX Scalar data1[size];
+  EIGEN_ALIGN_MAX Scalar data2[size];
+  EIGEN_ALIGN_MAX Packet packets[PacketSize*2];
+  EIGEN_ALIGN_MAX Scalar ref[size];
   RealScalar refvalue = 0;
   for (int i=0; i<size; ++i)
   {
     data1[i] = internal::random<Scalar>()/RealScalar(PacketSize);
     data2[i] = internal::random<Scalar>()/RealScalar(PacketSize);
@@ -138,25 +152,41 @@
     packets[1] = internal::pload<Packet>(data1+PacketSize);
          if (offset==0) internal::palign<0>(packets[0], packets[1]);
     else if (offset==1) internal::palign<1>(packets[0], packets[1]);
     else if (offset==2) internal::palign<2>(packets[0], packets[1]);
     else if (offset==3) internal::palign<3>(packets[0], packets[1]);
+    else if (offset==4) internal::palign<4>(packets[0], packets[1]);
+    else if (offset==5) internal::palign<5>(packets[0], packets[1]);
+    else if (offset==6) internal::palign<6>(packets[0], packets[1]);
+    else if (offset==7) internal::palign<7>(packets[0], packets[1]);
+    else if (offset==8) internal::palign<8>(packets[0], packets[1]);
+    else if (offset==9) internal::palign<9>(packets[0], packets[1]);
+    else if (offset==10) internal::palign<10>(packets[0], packets[1]);
+    else if (offset==11) internal::palign<11>(packets[0], packets[1]);
+    else if (offset==12) internal::palign<12>(packets[0], packets[1]);
+    else if (offset==13) internal::palign<13>(packets[0], packets[1]);
+    else if (offset==14) internal::palign<14>(packets[0], packets[1]);
+    else if (offset==15) internal::palign<15>(packets[0], packets[1]);
     internal::pstore(data2, packets[0]);
 
     for (int i=0; i<PacketSize; ++i)
       ref[i] = data1[i+offset];
 
     VERIFY(areApprox(ref, data2, PacketSize) && "internal::palign");
   }
 
-  CHECK_CWISE2(REF_ADD,  internal::padd);
-  CHECK_CWISE2(REF_SUB,  internal::psub);
-  CHECK_CWISE2(REF_MUL,  internal::pmul);
-  #ifndef EIGEN_VECTORIZE_ALTIVEC
-  if (!internal::is_same<Scalar,int>::value)
-    CHECK_CWISE2(REF_DIV,  internal::pdiv);
-  #endif
+  VERIFY((!PacketTraits::Vectorizable) || PacketTraits::HasAdd);
+  VERIFY((!PacketTraits::Vectorizable) || PacketTraits::HasSub);
+  VERIFY((!PacketTraits::Vectorizable) || PacketTraits::HasMul);
+  VERIFY((!PacketTraits::Vectorizable) || PacketTraits::HasNegate);
+  VERIFY((internal::is_same<Scalar,int>::value) || (!PacketTraits::Vectorizable) || PacketTraits::HasDiv);
+
+  CHECK_CWISE2_IF(PacketTraits::HasAdd, REF_ADD,  internal::padd);
+  CHECK_CWISE2_IF(PacketTraits::HasSub, REF_SUB,  internal::psub);
+  CHECK_CWISE2_IF(PacketTraits::HasMul, REF_MUL,  internal::pmul);
+  CHECK_CWISE2_IF(PacketTraits::HasDiv, REF_DIV, internal::pdiv);
+
   CHECK_CWISE1(internal::negate, internal::pnegate);
   CHECK_CWISE1(numext::conj, internal::pconj);
 
   for(int offset=0;offset<3;++offset)
   {
@@ -163,13 +193,35 @@
     for (int i=0; i<PacketSize; ++i)
       ref[i] = data1[offset];
     internal::pstore(data2, internal::pset1<Packet>(data1[offset]));
     VERIFY(areApprox(ref, data2, PacketSize) && "internal::pset1");
   }
-  
+
+  {
+    for (int i=0; i<PacketSize*4; ++i)
+      ref[i] = data1[i/PacketSize];
+    Packet A0, A1, A2, A3;
+    internal::pbroadcast4<Packet>(data1, A0, A1, A2, A3);
+    internal::pstore(data2+0*PacketSize, A0);
+    internal::pstore(data2+1*PacketSize, A1);
+    internal::pstore(data2+2*PacketSize, A2);
+    internal::pstore(data2+3*PacketSize, A3);
+    VERIFY(areApprox(ref, data2, 4*PacketSize) && "internal::pbroadcast4");
+  }
+
+  {
+    for (int i=0; i<PacketSize*2; ++i)
+      ref[i] = data1[i/PacketSize];
+    Packet A0, A1;
+    internal::pbroadcast2<Packet>(data1, A0, A1);
+    internal::pstore(data2+0*PacketSize, A0);
+    internal::pstore(data2+1*PacketSize, A1);
+    VERIFY(areApprox(ref, data2, 2*PacketSize) && "internal::pbroadcast2");
+  }
+
   VERIFY(internal::isApprox(data1[0], internal::pfirst(internal::pload<Packet>(data1))) && "internal::pfirst");
-  
+
   if(PacketSize>1)
   {
     for(int offset=0;offset<4;++offset)
     {
       for(int i=0;i<PacketSize/2;++i)
@@ -176,15 +228,35 @@
         ref[2*i+0] = ref[2*i+1] = data1[offset+i];
       internal::pstore(data2,internal::ploaddup<Packet>(data1+offset));
       VERIFY(areApprox(ref, data2, PacketSize) && "ploaddup");
     }
   }
+
+  if(PacketSize>2)
+  {
+    for(int offset=0;offset<4;++offset)
+    {
+      for(int i=0;i<PacketSize/4;++i)
+        ref[4*i+0] = ref[4*i+1] = ref[4*i+2] = ref[4*i+3] = data1[offset+i];
+      internal::pstore(data2,internal::ploadquad<Packet>(data1+offset));
+      VERIFY(areApprox(ref, data2, PacketSize) && "ploadquad");
+    }
+  }
 
   ref[0] = 0;
   for (int i=0; i<PacketSize; ++i)
     ref[0] += data1[i];
   VERIFY(isApproxAbs(ref[0], internal::predux(internal::pload<Packet>(data1)), refvalue) && "internal::predux");
+
+  {
+    for (int i=0; i<4; ++i)
+      ref[i] = 0;
+    for (int i=0; i<PacketSize; ++i)
+      ref[i%4] += data1[i];
+    internal::pstore(data2, internal::predux_downto4(internal::pload<Packet>(data1)));
+    VERIFY(areApprox(ref, data2, PacketSize>4?PacketSize/2:PacketSize) && "internal::predux_downto4");
+  }
 
   ref[0] = 1;
   for (int i=0; i<PacketSize; ++i)
     ref[0] *= data1[i];
   VERIFY(internal::isApprox(ref[0], internal::predux_mul(internal::pload<Packet>(data1))) && "internal::predux_mul");
@@ -201,128 +273,270 @@
 
   for (int i=0; i<PacketSize; ++i)
     ref[i] = data1[PacketSize-i-1];
   internal::pstore(data2, internal::preverse(internal::pload<Packet>(data1)));
   VERIFY(areApprox(ref, data2, PacketSize) && "internal::preverse");
+
+  internal::PacketBlock<Packet> kernel;
+  for (int i=0; i<PacketSize; ++i) {
+    kernel.packet[i] = internal::pload<Packet>(data1+i*PacketSize);
+  }
+  ptranspose(kernel);
+  for (int i=0; i<PacketSize; ++i) {
+    internal::pstore(data2, kernel.packet[i]);
+    for (int j = 0; j < PacketSize; ++j) {
+      VERIFY(isApproxAbs(data2[j], data1[i+j*PacketSize], refvalue) && "ptranspose");
+    }
+  }
+
+  if (PacketTraits::HasBlend) {
+    Packet thenPacket = internal::pload<Packet>(data1);
+    Packet elsePacket = internal::pload<Packet>(data2);
+    EIGEN_ALIGN_MAX internal::Selector<PacketSize> selector;
+    for (int i = 0; i < PacketSize; ++i) {
+      selector.select[i] = i;
+    }
+
+    Packet blend = internal::pblend(selector, thenPacket, elsePacket);
+    EIGEN_ALIGN_MAX Scalar result[size];
+    internal::pstore(result, blend);
+    for (int i = 0; i < PacketSize; ++i) {
+      VERIFY(isApproxAbs(result[i], (selector.select[i] ? data1[i] : data2[i]), refvalue));
+    }
+  }
+
+  if (PacketTraits::HasBlend || g_vectorize_sse) {
+    // pinsertfirst
+    for (int i=0; i<PacketSize; ++i)
+      ref[i] = data1[i];
+    Scalar s = internal::random<Scalar>();
+    ref[0] = s;
+    internal::pstore(data2, internal::pinsertfirst(internal::pload<Packet>(data1),s));
+    VERIFY(areApprox(ref, data2, PacketSize) && "internal::pinsertfirst");
+  }
+
+  if (PacketTraits::HasBlend || g_vectorize_sse) {
+    // pinsertlast
+    for (int i=0; i<PacketSize; ++i)
+      ref[i] = data1[i];
+    Scalar s = internal::random<Scalar>();
+    ref[PacketSize-1] = s;
+    internal::pstore(data2, internal::pinsertlast(internal::pload<Packet>(data1),s));
+    VERIFY(areApprox(ref, data2, PacketSize) && "internal::pinsertlast");
+  }
 }
 
 template<typename Scalar> void packetmath_real()
 {
   using std::abs;
-  typedef typename internal::packet_traits<Scalar>::type Packet;
-  const int PacketSize = internal::packet_traits<Scalar>::size;
+  typedef internal::packet_traits<Scalar> PacketTraits;
+  typedef typename PacketTraits::type Packet;
+  const int PacketSize = PacketTraits::size;
 
   const int size = PacketSize*4;
-  EIGEN_ALIGN16 Scalar data1[internal::packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN16 Scalar data2[internal::packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN16 Scalar ref[internal::packet_traits<Scalar>::size*4];
+  EIGEN_ALIGN_MAX Scalar data1[PacketTraits::size*4];
+  EIGEN_ALIGN_MAX Scalar data2[PacketTraits::size*4];
+  EIGEN_ALIGN_MAX Scalar ref[PacketTraits::size*4];
 
   for (int i=0; i<size; ++i)
   {
     data1[i] = internal::random<Scalar>(-1,1) * std::pow(Scalar(10), internal::random<Scalar>(-3,3));
     data2[i] = internal::random<Scalar>(-1,1) * std::pow(Scalar(10), internal::random<Scalar>(-3,3));
   }
-  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasSin, std::sin, internal::psin);
-  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasCos, std::cos, internal::pcos);
-  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasTan, std::tan, internal::ptan);
-  
+  CHECK_CWISE1_IF(PacketTraits::HasSin, std::sin, internal::psin);
+  CHECK_CWISE1_IF(PacketTraits::HasCos, std::cos, internal::pcos);
+  CHECK_CWISE1_IF(PacketTraits::HasTan, std::tan, internal::ptan);
+
+  CHECK_CWISE1_IF(PacketTraits::HasRound, numext::round, internal::pround);
+  CHECK_CWISE1_IF(PacketTraits::HasCeil, numext::ceil, internal::pceil);
+  CHECK_CWISE1_IF(PacketTraits::HasFloor, numext::floor, internal::pfloor);
+
   for (int i=0; i<size; ++i)
   {
     data1[i] = internal::random<Scalar>(-1,1);
     data2[i] = internal::random<Scalar>(-1,1);
   }
-  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasASin, std::asin, internal::pasin);
-  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasACos, std::acos, internal::pacos);
+  CHECK_CWISE1_IF(PacketTraits::HasASin, std::asin, internal::pasin);
+  CHECK_CWISE1_IF(PacketTraits::HasACos, std::acos, internal::pacos);
 
   for (int i=0; i<size; ++i)
   {
     data1[i] = internal::random<Scalar>(-87,88);
     data2[i] = internal::random<Scalar>(-87,88);
   }
-  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasExp, std::exp, internal::pexp);
+  CHECK_CWISE1_IF(PacketTraits::HasExp, std::exp, internal::pexp);
+  for (int i=0; i<size; ++i)
+  {
+    data1[i] = internal::random<Scalar>(-1,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
+    data2[i] = internal::random<Scalar>(-1,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
+  }
+  CHECK_CWISE1_IF(PacketTraits::HasTanh, std::tanh, internal::ptanh);
+  if(PacketTraits::HasExp && PacketTraits::size>=2)
+  {
+    data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
+    data1[1] = std::numeric_limits<Scalar>::epsilon();
+    packet_helper<PacketTraits::HasExp,Packet> h;
+    h.store(data2, internal::pexp(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
+    VERIFY_IS_EQUAL(std::exp(std::numeric_limits<Scalar>::epsilon()), data2[1]);
+
+    data1[0] = -std::numeric_limits<Scalar>::epsilon();
+    data1[1] = 0;
+    h.store(data2, internal::pexp(h.load(data1)));
+    VERIFY_IS_EQUAL(std::exp(-std::numeric_limits<Scalar>::epsilon()), data2[0]);
+    VERIFY_IS_EQUAL(std::exp(Scalar(0)), data2[1]);
+
+    data1[0] = (std::numeric_limits<Scalar>::min)();
+    data1[1] = -(std::numeric_limits<Scalar>::min)();
+    h.store(data2, internal::pexp(h.load(data1)));
+    VERIFY_IS_EQUAL(std::exp((std::numeric_limits<Scalar>::min)()), data2[0]);
+    VERIFY_IS_EQUAL(std::exp(-(std::numeric_limits<Scalar>::min)()), data2[1]);
+
+    data1[0] = std::numeric_limits<Scalar>::denorm_min();
+    data1[1] = -std::numeric_limits<Scalar>::denorm_min();
+    h.store(data2, internal::pexp(h.load(data1)));
+    VERIFY_IS_EQUAL(std::exp(std::numeric_limits<Scalar>::denorm_min()), data2[0]);
+    VERIFY_IS_EQUAL(std::exp(-std::numeric_limits<Scalar>::denorm_min()), data2[1]);
+  }
+
+  if (PacketTraits::HasTanh) {
+    // NOTE this test migh fail with GCC prior to 6.3, see MathFunctionsImpl.h for details.
+    data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
+    packet_helper<internal::packet_traits<Scalar>::HasTanh,Packet> h;
+    h.store(data2, internal::ptanh(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
+  }
+
+#if EIGEN_HAS_C99_MATH
+  {
+    data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
+    packet_helper<internal::packet_traits<Scalar>::HasLGamma,Packet> h;
+    h.store(data2, internal::plgamma(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
+  }
+  {
+    data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
+    packet_helper<internal::packet_traits<Scalar>::HasErf,Packet> h;
+    h.store(data2, internal::perf(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
+  }
   {
     data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
-    packet_helper<internal::packet_traits<Scalar>::HasExp,Packet> h;
-    h.store(data2, internal::pexp(h.load(data1))); 
-    VERIFY(isNaN(data2[0]));
+    packet_helper<internal::packet_traits<Scalar>::HasErfc,Packet> h;
+    h.store(data2, internal::perfc(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
   }
+#endif  // EIGEN_HAS_C99_MATH
 
   for (int i=0; i<size; ++i)
   {
     data1[i] = internal::random<Scalar>(0,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
     data2[i] = internal::random<Scalar>(0,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
   }
-  if(internal::random<float>(0,1)<0.1)
+
+  if(internal::random<float>(0,1)<0.1f)
     data1[internal::random<int>(0, PacketSize)] = 0;
-  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasSqrt, std::sqrt, internal::psqrt);
-  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasLog, std::log, internal::plog);
+  CHECK_CWISE1_IF(PacketTraits::HasSqrt, std::sqrt, internal::psqrt);
+  CHECK_CWISE1_IF(PacketTraits::HasLog, std::log, internal::plog);
+#if EIGEN_HAS_C99_MATH && (__cplusplus > 199711L)
+  CHECK_CWISE1_IF(PacketTraits::HasLog1p, std::log1p, internal::plog1p);
+  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasLGamma, std::lgamma, internal::plgamma);
+  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasErf, std::erf, internal::perf);
+  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasErfc, std::erfc, internal::perfc);
+#endif
+
+  if(PacketTraits::HasLog && PacketTraits::size>=2)
   {
     data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
-    packet_helper<internal::packet_traits<Scalar>::HasLog,Packet> h;
-    h.store(data2, internal::plog(h.load(data1)));
-    VERIFY(isNaN(data2[0]));
-    data1[0] = -1.0f;
-    h.store(data2, internal::plog(h.load(data1)));
-    VERIFY(isNaN(data2[0]));
-#if !EIGEN_FAST_MATH
-    h.store(data2, internal::psqrt(h.load(data1)));
-    VERIFY(isNaN(data2[0]));
-    VERIFY(isNaN(data2[1]));
-#endif
+    data1[1] = std::numeric_limits<Scalar>::epsilon();
+    packet_helper<PacketTraits::HasLog,Packet> h;
+    h.store(data2, internal::plog(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
+    VERIFY_IS_EQUAL(std::log(std::numeric_limits<Scalar>::epsilon()), data2[1]);
+
+    data1[0] = -std::numeric_limits<Scalar>::epsilon();
+    data1[1] = 0;
+    h.store(data2, internal::plog(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
+    VERIFY_IS_EQUAL(std::log(Scalar(0)), data2[1]);
+
+    data1[0] = (std::numeric_limits<Scalar>::min)();
+    data1[1] = -(std::numeric_limits<Scalar>::min)();
+    h.store(data2, internal::plog(h.load(data1)));
+    VERIFY_IS_EQUAL(std::log((std::numeric_limits<Scalar>::min)()), data2[0]);
+    VERIFY((numext::isnan)(data2[1]));
+
+    data1[0] = std::numeric_limits<Scalar>::denorm_min();
+    data1[1] = -std::numeric_limits<Scalar>::denorm_min();
+    h.store(data2, internal::plog(h.load(data1)));
+    // VERIFY_IS_EQUAL(std::log(std::numeric_limits<Scalar>::denorm_min()), data2[0]);
+    VERIFY((numext::isnan)(data2[1]));
+
+    data1[0] = Scalar(-1.0f);
+    h.store(data2, internal::plog(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
+    h.store(data2, internal::psqrt(h.load(data1)));
+    VERIFY((numext::isnan)(data2[0]));
+    VERIFY((numext::isnan)(data2[1]));
   }
 }
 
 template<typename Scalar> void packetmath_notcomplex()
 {
   using std::abs;
-  typedef typename internal::packet_traits<Scalar>::type Packet;
-  const int PacketSize = internal::packet_traits<Scalar>::size;
-
-  EIGEN_ALIGN16 Scalar data1[internal::packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN16 Scalar data2[internal::packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN16 Scalar ref[internal::packet_traits<Scalar>::size*4];
-  
-  Array<Scalar,Dynamic,1>::Map(data1, internal::packet_traits<Scalar>::size*4).setRandom();
+  typedef internal::packet_traits<Scalar> PacketTraits;
+  typedef typename PacketTraits::type Packet;
+  const int PacketSize = PacketTraits::size;
+
+  EIGEN_ALIGN_MAX Scalar data1[PacketTraits::size*4];
+  EIGEN_ALIGN_MAX Scalar data2[PacketTraits::size*4];
+  EIGEN_ALIGN_MAX Scalar ref[PacketTraits::size*4];
+
+  Array<Scalar,Dynamic,1>::Map(data1, PacketTraits::size*4).setRandom();
 
   ref[0] = data1[0];
   for (int i=0; i<PacketSize; ++i)
     ref[0] = (std::min)(ref[0],data1[i]);
   VERIFY(internal::isApprox(ref[0], internal::predux_min(internal::pload<Packet>(data1))) && "internal::predux_min");
 
-  CHECK_CWISE2((std::min), internal::pmin);
-  CHECK_CWISE2((std::max), internal::pmax);
+  VERIFY((!PacketTraits::Vectorizable) || PacketTraits::HasMin);
+  VERIFY((!PacketTraits::Vectorizable) || PacketTraits::HasMax);
+
+  CHECK_CWISE2_IF(PacketTraits::HasMin, (std::min), internal::pmin);
+  CHECK_CWISE2_IF(PacketTraits::HasMax, (std::max), internal::pmax);
   CHECK_CWISE1(abs, internal::pabs);
 
   ref[0] = data1[0];
   for (int i=0; i<PacketSize; ++i)
     ref[0] = (std::max)(ref[0],data1[i]);
   VERIFY(internal::isApprox(ref[0], internal::predux_max(internal::pload<Packet>(data1))) && "internal::predux_max");
-  
+
   for (int i=0; i<PacketSize; ++i)
     ref[i] = data1[0]+Scalar(i);
-  internal::pstore(data2, internal::plset(data1[0]));
+  internal::pstore(data2, internal::plset<Packet>(data1[0]));
   VERIFY(areApprox(ref, data2, PacketSize) && "internal::plset");
 }
 
 template<typename Scalar,bool ConjLhs,bool ConjRhs> void test_conj_helper(Scalar* data1, Scalar* data2, Scalar* ref, Scalar* pval)
 {
-  typedef typename internal::packet_traits<Scalar>::type Packet;
-  const int PacketSize = internal::packet_traits<Scalar>::size;
-  
+  typedef internal::packet_traits<Scalar> PacketTraits;
+  typedef typename PacketTraits::type Packet;
+  const int PacketSize = PacketTraits::size;
+
   internal::conj_if<ConjLhs> cj0;
   internal::conj_if<ConjRhs> cj1;
   internal::conj_helper<Scalar,Scalar,ConjLhs,ConjRhs> cj;
   internal::conj_helper<Packet,Packet,ConjLhs,ConjRhs> pcj;
-  
+
   for(int i=0;i<PacketSize;++i)
   {
     ref[i] = cj0(data1[i]) * cj1(data2[i]);
     VERIFY(internal::isApprox(ref[i], cj.pmul(data1[i],data2[i])) && "conj_helper pmul");
   }
   internal::pstore(pval,pcj.pmul(internal::pload<Packet>(data1),internal::pload<Packet>(data2)));
   VERIFY(areApprox(ref, pval, PacketSize) && "conj_helper pmul");
-  
+
   for(int i=0;i<PacketSize;++i)
   {
     Scalar tmp = ref[i];
     ref[i] += cj0(data1[i]) * cj1(data2[i]);
     VERIFY(internal::isApprox(ref[i], cj.pmadd(data1[i],data2[i],tmp)) && "conj_helper pmadd");
@@ -331,55 +545,97 @@
   VERIFY(areApprox(ref, pval, PacketSize) && "conj_helper pmadd");
 }
 
 template<typename Scalar> void packetmath_complex()
 {
-  typedef typename internal::packet_traits<Scalar>::type Packet;
-  const int PacketSize = internal::packet_traits<Scalar>::size;
+  typedef internal::packet_traits<Scalar> PacketTraits;
+  typedef typename PacketTraits::type Packet;
+  const int PacketSize = PacketTraits::size;
 
   const int size = PacketSize*4;
-  EIGEN_ALIGN16 Scalar data1[PacketSize*4];
-  EIGEN_ALIGN16 Scalar data2[PacketSize*4];
-  EIGEN_ALIGN16 Scalar ref[PacketSize*4];
-  EIGEN_ALIGN16 Scalar pval[PacketSize*4];
+  EIGEN_ALIGN_MAX Scalar data1[PacketSize*4];
+  EIGEN_ALIGN_MAX Scalar data2[PacketSize*4];
+  EIGEN_ALIGN_MAX Scalar ref[PacketSize*4];
+  EIGEN_ALIGN_MAX Scalar pval[PacketSize*4];
 
   for (int i=0; i<size; ++i)
   {
     data1[i] = internal::random<Scalar>() * Scalar(1e2);
     data2[i] = internal::random<Scalar>() * Scalar(1e2);
   }
-  
+
   test_conj_helper<Scalar,false,false> (data1,data2,ref,pval);
   test_conj_helper<Scalar,false,true>  (data1,data2,ref,pval);
   test_conj_helper<Scalar,true,false>  (data1,data2,ref,pval);
   test_conj_helper<Scalar,true,true>   (data1,data2,ref,pval);
-  
+
   {
     for(int i=0;i<PacketSize;++i)
       ref[i] = Scalar(std::imag(data1[i]),std::real(data1[i]));
     internal::pstore(pval,internal::pcplxflip(internal::pload<Packet>(data1)));
     VERIFY(areApprox(ref, pval, PacketSize) && "pcplxflip");
   }
-  
-  
+}
+
+template<typename Scalar> void packetmath_scatter_gather()
+{
+  typedef internal::packet_traits<Scalar> PacketTraits;
+  typedef typename PacketTraits::type Packet;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  const int PacketSize = PacketTraits::size;
+  EIGEN_ALIGN_MAX Scalar data1[PacketSize];
+  RealScalar refvalue = 0;
+  for (int i=0; i<PacketSize; ++i) {
+    data1[i] = internal::random<Scalar>()/RealScalar(PacketSize);
+  }
+
+  int stride = internal::random<int>(1,20);
+
+  EIGEN_ALIGN_MAX Scalar buffer[PacketSize*20];
+  memset(buffer, 0, 20*PacketSize*sizeof(Scalar));
+  Packet packet = internal::pload<Packet>(data1);
+  internal::pscatter<Scalar, Packet>(buffer, packet, stride);
+
+  for (int i = 0; i < PacketSize*20; ++i) {
+    if ((i%stride) == 0 && i<stride*PacketSize) {
+      VERIFY(isApproxAbs(buffer[i], data1[i/stride], refvalue) && "pscatter");
+    } else {
+      VERIFY(isApproxAbs(buffer[i], Scalar(0), refvalue) && "pscatter");
+    }
+  }
+
+  for (int i=0; i<PacketSize*7; ++i) {
+    buffer[i] = internal::random<Scalar>()/RealScalar(PacketSize);
+  }
+  packet = internal::pgather<Scalar, Packet>(buffer, 7);
+  internal::pstore(data1, packet);
+  for (int i = 0; i < PacketSize; ++i) {
+    VERIFY(isApproxAbs(data1[i], buffer[i*7], refvalue) && "pgather");
+  }
 }
 
 void test_packetmath()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( packetmath<float>() );
     CALL_SUBTEST_2( packetmath<double>() );
     CALL_SUBTEST_3( packetmath<int>() );
-    CALL_SUBTEST_1( packetmath<std::complex<float> >() );
-    CALL_SUBTEST_2( packetmath<std::complex<double> >() );
+    CALL_SUBTEST_4( packetmath<std::complex<float> >() );
+    CALL_SUBTEST_5( packetmath<std::complex<double> >() );
 
     CALL_SUBTEST_1( packetmath_notcomplex<float>() );
     CALL_SUBTEST_2( packetmath_notcomplex<double>() );
     CALL_SUBTEST_3( packetmath_notcomplex<int>() );
-    
+
     CALL_SUBTEST_1( packetmath_real<float>() );
     CALL_SUBTEST_2( packetmath_real<double>() );
 
-    CALL_SUBTEST_1( packetmath_complex<std::complex<float> >() );
-    CALL_SUBTEST_2( packetmath_complex<std::complex<double> >() );
+    CALL_SUBTEST_4( packetmath_complex<std::complex<float> >() );
+    CALL_SUBTEST_5( packetmath_complex<std::complex<double> >() );
+
+    CALL_SUBTEST_1( packetmath_scatter_gather<float>() );
+    CALL_SUBTEST_2( packetmath_scatter_gather<double>() );
+    CALL_SUBTEST_3( packetmath_scatter_gather<int>() );
+    CALL_SUBTEST_4( packetmath_scatter_gather<std::complex<float> >() );
+    CALL_SUBTEST_5( packetmath_scatter_gather<std::complex<double> >() );
   }
 }

Index: 3rd_party/eigen/test/pastix_support.cpp
==================================================================
--- 3rd_party/eigen/test/pastix_support.cpp
+++ 3rd_party/eigen/test/pastix_support.cpp
@@ -5,10 +5,12 @@
 // Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_NO_DEBUG_SMALL_PRODUCT_BLOCKS
 #include "sparse_solver.h"
 #include <Eigen/PaStiXSupport>
 #include <unsupported/Eigen/SparseExtra>
 
 
@@ -23,10 +25,18 @@
   check_sparse_spd_solving(pastix_llt_lower);
   check_sparse_spd_solving(pastix_ldlt_lower);
   check_sparse_spd_solving(pastix_llt_upper);
   check_sparse_spd_solving(pastix_ldlt_upper);
   check_sparse_square_solving(pastix_lu);
+
+  // Some compilation check:
+  pastix_llt_lower.iparm();
+  pastix_llt_lower.dparm();
+  pastix_ldlt_lower.iparm();
+  pastix_ldlt_lower.dparm();
+  pastix_lu.iparm();
+  pastix_lu.dparm();
 }
 
 // There is no support for selfadjoint matrices with PaStiX. 
 // Complex symmetric matrices should pass though
 template<typename T> void test_pastix_T_LU()

Index: 3rd_party/eigen/test/permutationmatrices.cpp
==================================================================
--- 3rd_party/eigen/test/permutationmatrices.cpp
+++ 3rd_party/eigen/test/permutationmatrices.cpp
@@ -5,10 +5,12 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#define TEST_ENABLE_TEMPORARY_TRACKING
+  
 #include "main.h"
 
 using namespace std;
 template<typename MatrixType> void permutationmatrices(const MatrixType& m)
 {
@@ -31,21 +33,27 @@
   randomPermutationVector(lv, rows);
   LeftPermutationType lp(lv);
   RightPermutationVectorType rv;
   randomPermutationVector(rv, cols);
   RightPermutationType rp(rv);
-  MatrixType m_permuted = lp * m_original * rp;
+  MatrixType m_permuted = MatrixType::Random(rows,cols);
+  
+  VERIFY_EVALUATION_COUNT(m_permuted = lp * m_original * rp, 1); // 1 temp for sub expression "lp * m_original"
 
   for (int i=0; i<rows; i++)
     for (int j=0; j<cols; j++)
         VERIFY_IS_APPROX(m_permuted(lv(i),j), m_original(i,rv(j)));
 
   Matrix<Scalar,Rows,Rows> lm(lp);
   Matrix<Scalar,Cols,Cols> rm(rp);
 
   VERIFY_IS_APPROX(m_permuted, lm*m_original*rm);
-
+  
+  m_permuted = m_original;
+  VERIFY_EVALUATION_COUNT(m_permuted = lp * m_permuted * rp, 1);
+  VERIFY_IS_APPROX(m_permuted, lm*m_original*rm);
+  
   VERIFY_IS_APPROX(lp.inverse()*m_permuted*rp.inverse(), m_original);
   VERIFY_IS_APPROX(lv.asPermutation().inverse()*m_permuted*rv.asPermutation().inverse(), m_original);
   VERIFY_IS_APPROX(MapLeftPerm(lv.data(),lv.size()).inverse()*m_permuted*MapRightPerm(rv.data(),rv.size()).inverse(), m_original);
   
   VERIFY((lp*lp.inverse()).toDenseMatrix().isIdentity());
@@ -61,26 +69,26 @@
   VERIFY_IS_APPROX((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv2.data(),lv2.size())).toDenseMatrix().template cast<Scalar>(), lm*lm2);
 
   LeftPermutationType identityp;
   identityp.setIdentity(rows);
   VERIFY_IS_APPROX(m_original, identityp*m_original);
-
+  
   // check inplace permutations
   m_permuted = m_original;
-  m_permuted = lp.inverse() * m_permuted;
+  VERIFY_EVALUATION_COUNT(m_permuted.noalias()= lp.inverse() * m_permuted, 1); // 1 temp to allocate the mask
   VERIFY_IS_APPROX(m_permuted, lp.inverse()*m_original);
-
+  
   m_permuted = m_original;
-  m_permuted = m_permuted * rp.inverse();
+  VERIFY_EVALUATION_COUNT(m_permuted.noalias() = m_permuted * rp.inverse(), 1); // 1 temp to allocate the mask
   VERIFY_IS_APPROX(m_permuted, m_original*rp.inverse());
-
+  
   m_permuted = m_original;
-  m_permuted = lp * m_permuted;
+  VERIFY_EVALUATION_COUNT(m_permuted.noalias() = lp * m_permuted, 1); // 1 temp to allocate the mask
   VERIFY_IS_APPROX(m_permuted, lp*m_original);
-
+  
   m_permuted = m_original;
-  m_permuted = m_permuted * rp;
+  VERIFY_EVALUATION_COUNT(m_permuted.noalias() = m_permuted * rp, 1); // 1 temp to allocate the mask
   VERIFY_IS_APPROX(m_permuted, m_original*rp);
 
   if(rows>1 && cols>1)
   {
     lp2 = lp;
@@ -97,11 +105,42 @@
     do j = internal::random<Index>(0, cols-1); while(j==i);
     rp2.applyTranspositionOnTheRight(i, j);
     rm = rp;
     rm.col(i).swap(rm.col(j));
     VERIFY_IS_APPROX(rm, rp2.toDenseMatrix().template cast<Scalar>());
-  }  
+  }
+
+  {
+    // simple compilation check
+    Matrix<Scalar, Cols, Cols> A = rp;
+    Matrix<Scalar, Cols, Cols> B = rp.transpose();
+    VERIFY_IS_APPROX(A, B.transpose());
+  }
+}
+
+template<typename T>
+void bug890()
+{
+  typedef Matrix<T, Dynamic, Dynamic> MatrixType;
+  typedef Matrix<T, Dynamic, 1> VectorType;
+  typedef Stride<Dynamic,Dynamic> S;
+  typedef Map<MatrixType, Aligned, S> MapType;
+  typedef PermutationMatrix<Dynamic> Perm;
+  
+  VectorType v1(2), v2(2), op(4), rhs(2);
+  v1 << 666,667;
+  op << 1,0,0,1;
+  rhs << 42,42;
+  
+  Perm P(2);
+  P.indices() << 1, 0;
+
+  MapType(v1.data(),2,1,S(1,1)) = P * MapType(rhs.data(),2,1,S(1,1));
+  VERIFY_IS_APPROX(v1, (P * rhs).eval());
+  
+  MapType(v1.data(),2,1,S(1,1)) = P.inverse() * MapType(rhs.data(),2,1,S(1,1));
+  VERIFY_IS_APPROX(v1, (P.inverse() * rhs).eval());
 }
 
 void test_permutationmatrices()
 {
   for(int i = 0; i < g_repeat; i++) {
@@ -111,6 +150,7 @@
     CALL_SUBTEST_4( permutationmatrices(Matrix4d()) );
     CALL_SUBTEST_5( permutationmatrices(Matrix<double,40,60>()) );
     CALL_SUBTEST_6( permutationmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 30)) );
     CALL_SUBTEST_7( permutationmatrices(MatrixXcf(15, 10)) );
   }
+  CALL_SUBTEST_5( bug890<double>() );
 }

Index: 3rd_party/eigen/test/prec_inverse_4x4.cpp
==================================================================
--- 3rd_party/eigen/test/prec_inverse_4x4.cpp
+++ 3rd_party/eigen/test/prec_inverse_4x4.cpp
@@ -51,18 +51,33 @@
   EIGEN_DEBUG_VAR(error_max);
    // FIXME that 1.25 used to be a 1.0 until the NumTraits changes on 28 April 2010, what's going wrong??
    // FIXME that 1.25 used to be 1.2 until we tested gcc 4.1 on 30 June 2010 and got 1.21.
   VERIFY(error_avg < (NumTraits<Scalar>::IsComplex ? 8.0 : 1.25));
   VERIFY(error_max < (NumTraits<Scalar>::IsComplex ? 64.0 : 20.0));
+
+  {
+    int s = 5;//internal::random<int>(4,10);
+    int i = 0;//internal::random<int>(0,s-4);
+    int j = 0;//internal::random<int>(0,s-4);
+    Matrix<Scalar,5,5> mat(s,s);
+    mat.setRandom();
+    MatrixType submat = mat.template block<4,4>(i,j);
+    MatrixType mat_inv = mat.template block<4,4>(i,j).inverse();
+    VERIFY_IS_APPROX(mat_inv, submat.inverse());
+    mat.template block<4,4>(i,j) = submat.inverse();
+    VERIFY_IS_APPROX(mat_inv, (mat.template block<4,4>(i,j)));
+  }
 }
 
 void test_prec_inverse_4x4()
 {
   CALL_SUBTEST_1((inverse_permutation_4x4<Matrix4f>()));
   CALL_SUBTEST_1(( inverse_general_4x4<Matrix4f>(200000 * g_repeat) ));
+  CALL_SUBTEST_1(( inverse_general_4x4<Matrix<float,4,4,RowMajor> >(200000 * g_repeat) ));
 
   CALL_SUBTEST_2((inverse_permutation_4x4<Matrix<double,4,4,RowMajor> >()));
+  CALL_SUBTEST_2(( inverse_general_4x4<Matrix<double,4,4,ColMajor> >(200000 * g_repeat) ));
   CALL_SUBTEST_2(( inverse_general_4x4<Matrix<double,4,4,RowMajor> >(200000 * g_repeat) ));
 
   CALL_SUBTEST_3((inverse_permutation_4x4<Matrix4cf>()));
   CALL_SUBTEST_3((inverse_general_4x4<Matrix4cf>(50000 * g_repeat)));
 }

Index: 3rd_party/eigen/test/product.h
==================================================================
--- 3rd_party/eigen/test/product.h
+++ 3rd_party/eigen/test/product.h
@@ -20,11 +20,10 @@
 template<typename MatrixType> void product(const MatrixType& m)
 {
   /* this test covers the following files:
      Identity.h Product.h
   */
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> RowVectorType;
   typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> ColVectorType;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> RowSquareMatrixType;
   typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> ColSquareMatrixType;
@@ -109,10 +108,27 @@
     VERIFY(areNotApprox(res,square - m2 * m1.transpose()));
   }
   vcres = vc2;
   vcres.noalias() -= m1.transpose() * v1;
   VERIFY_IS_APPROX(vcres, vc2 - m1.transpose() * v1);
+
+  // test d ?= a+b*c rules
+  res.noalias() = square + m1 * m2.transpose();
+  VERIFY_IS_APPROX(res, square + m1 * m2.transpose());
+  res.noalias() += square + m1 * m2.transpose();
+  VERIFY_IS_APPROX(res, 2*(square + m1 * m2.transpose()));
+  res.noalias() -= square + m1 * m2.transpose();
+  VERIFY_IS_APPROX(res, square + m1 * m2.transpose());
+
+  // test d ?= a-b*c rules
+  res.noalias() = square - m1 * m2.transpose();
+  VERIFY_IS_APPROX(res, square - m1 * m2.transpose());
+  res.noalias() += square - m1 * m2.transpose();
+  VERIFY_IS_APPROX(res, 2*(square - m1 * m2.transpose()));
+  res.noalias() -= square - m1 * m2.transpose();
+  VERIFY_IS_APPROX(res, square - m1 * m2.transpose());
+
 
   tm1 = m1;
   VERIFY_IS_APPROX(tm1.transpose() * v1, m1.transpose() * v1);
   VERIFY_IS_APPROX(v1.transpose() * tm1, v1.transpose() * m1);
 
@@ -133,18 +149,83 @@
     VERIFY(areNotApprox(res2,square2 + m2.transpose() * m1));
   }
 
   VERIFY_IS_APPROX(res.col(r).noalias() = square.adjoint() * square.col(r), (square.adjoint() * square.col(r)).eval());
   VERIFY_IS_APPROX(res.col(r).noalias() = square * square.col(r), (square * square.col(r)).eval());
+
+  // vector at runtime (see bug 1166)
+  {
+    RowSquareMatrixType ref(square);
+    ColSquareMatrixType ref2(square2);
+    ref = res = square;
+    VERIFY_IS_APPROX(res.block(0,0,1,rows).noalias() = m1.col(0).transpose() * square.transpose(),            (ref.row(0) = m1.col(0).transpose() * square.transpose()));
+    VERIFY_IS_APPROX(res.block(0,0,1,rows).noalias() = m1.block(0,0,rows,1).transpose() * square.transpose(), (ref.row(0) = m1.col(0).transpose() * square.transpose()));
+    VERIFY_IS_APPROX(res.block(0,0,1,rows).noalias() = m1.col(0).transpose() * square,                        (ref.row(0) = m1.col(0).transpose() * square));
+    VERIFY_IS_APPROX(res.block(0,0,1,rows).noalias() = m1.block(0,0,rows,1).transpose() * square,             (ref.row(0) = m1.col(0).transpose() * square));
+    ref2 = res2 = square2;
+    VERIFY_IS_APPROX(res2.block(0,0,1,cols).noalias() = m1.row(0) * square2.transpose(),                      (ref2.row(0) = m1.row(0) * square2.transpose()));
+    VERIFY_IS_APPROX(res2.block(0,0,1,cols).noalias() = m1.block(0,0,1,cols) * square2.transpose(),           (ref2.row(0) = m1.row(0) * square2.transpose()));
+    VERIFY_IS_APPROX(res2.block(0,0,1,cols).noalias() = m1.row(0) * square2,                                  (ref2.row(0) = m1.row(0) * square2));
+    VERIFY_IS_APPROX(res2.block(0,0,1,cols).noalias() = m1.block(0,0,1,cols) * square2,                       (ref2.row(0) = m1.row(0) * square2));
+  }
+
+  // vector.block() (see bug 1283)
+  {
+    RowVectorType w1(rows);
+    VERIFY_IS_APPROX(square * v1.block(0,0,rows,1), square * v1);
+    VERIFY_IS_APPROX(w1.noalias() = square * v1.block(0,0,rows,1), square * v1);
+    VERIFY_IS_APPROX(w1.block(0,0,rows,1).noalias() = square * v1.block(0,0,rows,1), square * v1);
+
+    Matrix<Scalar,1,MatrixType::ColsAtCompileTime> w2(cols);
+    VERIFY_IS_APPROX(vc2.block(0,0,cols,1).transpose() * square2, vc2.transpose() * square2);
+    VERIFY_IS_APPROX(w2.noalias() = vc2.block(0,0,cols,1).transpose() * square2, vc2.transpose() * square2);
+    VERIFY_IS_APPROX(w2.block(0,0,1,cols).noalias() = vc2.block(0,0,cols,1).transpose() * square2, vc2.transpose() * square2);
+
+    vc2 = square2.block(0,0,1,cols).transpose();
+    VERIFY_IS_APPROX(square2.block(0,0,1,cols) * square2, vc2.transpose() * square2);
+    VERIFY_IS_APPROX(w2.noalias() = square2.block(0,0,1,cols) * square2, vc2.transpose() * square2);
+    VERIFY_IS_APPROX(w2.block(0,0,1,cols).noalias() = square2.block(0,0,1,cols) * square2, vc2.transpose() * square2);
+
+    vc2 = square2.block(0,0,cols,1);
+    VERIFY_IS_APPROX(square2.block(0,0,cols,1).transpose() * square2, vc2.transpose() * square2);
+    VERIFY_IS_APPROX(w2.noalias() = square2.block(0,0,cols,1).transpose() * square2, vc2.transpose() * square2);
+    VERIFY_IS_APPROX(w2.block(0,0,1,cols).noalias() = square2.block(0,0,cols,1).transpose() * square2, vc2.transpose() * square2);
+  }
 
   // inner product
-  Scalar x = square2.row(c) * square2.col(c2);
-  VERIFY_IS_APPROX(x, square2.row(c).transpose().cwiseProduct(square2.col(c2)).sum());
-  
+  {
+    Scalar x = square2.row(c) * square2.col(c2);
+    VERIFY_IS_APPROX(x, square2.row(c).transpose().cwiseProduct(square2.col(c2)).sum());
+  }
+
   // outer product
-  VERIFY_IS_APPROX(m1.col(c) * m1.row(r), m1.block(0,c,rows,1) * m1.block(r,0,1,cols));
-  VERIFY_IS_APPROX(m1.row(r).transpose() * m1.col(c).transpose(), m1.block(r,0,1,cols).transpose() * m1.block(0,c,rows,1).transpose());
-  VERIFY_IS_APPROX(m1.block(0,c,rows,1) * m1.row(r), m1.block(0,c,rows,1) * m1.block(r,0,1,cols));
-  VERIFY_IS_APPROX(m1.col(c) * m1.block(r,0,1,cols), m1.block(0,c,rows,1) * m1.block(r,0,1,cols));
-  VERIFY_IS_APPROX(m1.leftCols(1) * m1.row(r), m1.block(0,0,rows,1) * m1.block(r,0,1,cols));
-  VERIFY_IS_APPROX(m1.col(c) * m1.topRows(1), m1.block(0,c,rows,1) * m1.block(0,0,1,cols));  
+  {
+    VERIFY_IS_APPROX(m1.col(c) * m1.row(r), m1.block(0,c,rows,1) * m1.block(r,0,1,cols));
+    VERIFY_IS_APPROX(m1.row(r).transpose() * m1.col(c).transpose(), m1.block(r,0,1,cols).transpose() * m1.block(0,c,rows,1).transpose());
+    VERIFY_IS_APPROX(m1.block(0,c,rows,1) * m1.row(r), m1.block(0,c,rows,1) * m1.block(r,0,1,cols));
+    VERIFY_IS_APPROX(m1.col(c) * m1.block(r,0,1,cols), m1.block(0,c,rows,1) * m1.block(r,0,1,cols));
+    VERIFY_IS_APPROX(m1.leftCols(1) * m1.row(r), m1.block(0,0,rows,1) * m1.block(r,0,1,cols));
+    VERIFY_IS_APPROX(m1.col(c) * m1.topRows(1), m1.block(0,c,rows,1) * m1.block(0,0,1,cols));
+  }
+
+  // Aliasing
+  {
+    ColVectorType x(cols); x.setRandom();
+    ColVectorType z(x);
+    ColVectorType y(cols); y.setZero();
+    ColSquareMatrixType A(cols,cols); A.setRandom();
+    // CwiseBinaryOp
+    VERIFY_IS_APPROX(x = y + A*x, A*z);
+    x = z;
+    // CwiseUnaryOp
+    VERIFY_IS_APPROX(x = Scalar(1.)*(A*x), A*z);
+  }
+
+  // regression for blas_trais
+  {
+    VERIFY_IS_APPROX(square * (square*square).transpose(), square * square.transpose() * square.transpose());
+    VERIFY_IS_APPROX(square * (-(square*square)), -square * square * square);
+    VERIFY_IS_APPROX(square * (s1*(square*square)), s1 * square * square * square);
+    VERIFY_IS_APPROX(square * (square*square).conjugate(), square * square.conjugate() * square.conjugate());
+  }
+
 }

Index: 3rd_party/eigen/test/product_extra.cpp
==================================================================
--- 3rd_party/eigen/test/product_extra.cpp
+++ 3rd_party/eigen/test/product_extra.cpp
@@ -96,10 +96,20 @@
   VERIFY_IS_APPROX(m1.block(i,0,r,m1.cols()) * m1.row(i2).adjoint(), m1.block(i,0,r,m1.cols()).eval() * m1.row(i2).adjoint().eval());
   
   // regression test
   MatrixType tmp = m1 * m1.adjoint() * s1;
   VERIFY_IS_APPROX(tmp, m1 * m1.adjoint() * s1);
+
+  // regression test for bug 1343, assignment to arrays
+  Array<Scalar,Dynamic,1> a1 = m1 * vc2;
+  VERIFY_IS_APPROX(a1.matrix(),m1*vc2);
+  Array<Scalar,Dynamic,1> a2 = s1 * (m1 * vc2);
+  VERIFY_IS_APPROX(a2.matrix(),s1*m1*vc2);
+  Array<Scalar,1,Dynamic> a3 = v1 * m1;
+  VERIFY_IS_APPROX(a3.matrix(),v1*m1);
+  Array<Scalar,Dynamic,Dynamic> a4 = m1 * m2.adjoint();
+  VERIFY_IS_APPROX(a4.matrix(),m1*m2.adjoint());
 }
 
 // Regression test for bug reported at http://forum.kde.org/viewtopic.php?f=74&t=96947
 void mat_mat_scalar_scalar_product()
 {
@@ -107,12 +117,72 @@
   dNdxy << -0.5, 0.5, 0,
            -0.3, 0, 0.3;
   double det = 6.0, wt = 0.5;
   VERIFY_IS_APPROX(dNdxy.transpose()*dNdxy*det*wt, det*wt*dNdxy.transpose()*dNdxy);
 }
+
+template <typename MatrixType> 
+void zero_sized_objects(const MatrixType& m)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  const int PacketSize  = internal::packet_traits<Scalar>::size;
+  const int PacketSize1 = PacketSize>1 ?  PacketSize-1 : 1;
+  Index rows = m.rows();
+  Index cols = m.cols();
+  
+  {
+    MatrixType res, a(rows,0), b(0,cols);
+    VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(rows,cols) );
+    VERIFY_IS_APPROX( (res=a*a.transpose()), MatrixType::Zero(rows,rows) );
+    VERIFY_IS_APPROX( (res=b.transpose()*b), MatrixType::Zero(cols,cols) );
+    VERIFY_IS_APPROX( (res=b.transpose()*a.transpose()), MatrixType::Zero(cols,rows) );
+  }
+  
+  {
+    MatrixType res, a(rows,cols), b(cols,0);
+    res = a*b;
+    VERIFY(res.rows()==rows && res.cols()==0);
+    b.resize(0,rows);
+    res = b*a;
+    VERIFY(res.rows()==0 && res.cols()==cols);
+  }
+  
+  {
+    Matrix<Scalar,PacketSize,0> a;
+    Matrix<Scalar,0,1> b;
+    Matrix<Scalar,PacketSize,1> res;
+    VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(PacketSize,1) );
+    VERIFY_IS_APPROX( (res=a.lazyProduct(b)), MatrixType::Zero(PacketSize,1) );
+  }
+  
+  {
+    Matrix<Scalar,PacketSize1,0> a;
+    Matrix<Scalar,0,1> b;
+    Matrix<Scalar,PacketSize1,1> res;
+    VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(PacketSize1,1) );
+    VERIFY_IS_APPROX( (res=a.lazyProduct(b)), MatrixType::Zero(PacketSize1,1) );
+  }
+  
+  {
+    Matrix<Scalar,PacketSize,Dynamic> a(PacketSize,0);
+    Matrix<Scalar,Dynamic,1> b(0,1);
+    Matrix<Scalar,PacketSize,1> res;
+    VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(PacketSize,1) );
+    VERIFY_IS_APPROX( (res=a.lazyProduct(b)), MatrixType::Zero(PacketSize,1) );
+  }
   
-void zero_sized_objects()
+  {
+    Matrix<Scalar,PacketSize1,Dynamic> a(PacketSize1,0);
+    Matrix<Scalar,Dynamic,1> b(0,1);
+    Matrix<Scalar,PacketSize1,1> res;
+    VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(PacketSize1,1) );
+    VERIFY_IS_APPROX( (res=a.lazyProduct(b)), MatrixType::Zero(PacketSize1,1) );
+  }
+}
+
+template<int>
+void bug_127()
 {
   // Bug 127
   //
   // a product of the form lhs*rhs with
   //
@@ -132,10 +202,20 @@
   Matrix<float,1,Dynamic,RowMajor,1,5> a(1,4);
   Matrix<float,Dynamic,Dynamic,ColMajor,5,1> b(4,0);
   a*b;
 }
 
+template<int> void bug_817()
+{
+  ArrayXXf B = ArrayXXf::Random(10,10), C;
+  VectorXf x = VectorXf::Random(10);
+  C = (x.transpose()*B.matrix());
+  B = (x.transpose()*B.matrix());
+  VERIFY_IS_APPROX(B,C);
+}
+
+template<int>
 void unaligned_objects()
 {
   // Regression test for the bug reported here:
   // http://forum.kde.org/viewtopic.php?f=74&t=107541
   // Recall the matrix*vector kernel avoid unaligned loads by loading two packets and then reassemble then.
@@ -160,18 +240,136 @@
         VERIFY_IS_APPROX(r2.segment(o,n), MatrixXf(v2) * M);
       }
     }
   }
 }
+
+template<typename T>
+EIGEN_DONT_INLINE
+Index test_compute_block_size(Index m, Index n, Index k)
+{
+  Index mc(m), nc(n), kc(k);
+  internal::computeProductBlockingSizes<T,T>(kc, mc, nc);
+  return kc+mc+nc;
+}
+
+template<typename T>
+Index compute_block_size()
+{
+  Index ret = 0;
+  ret += test_compute_block_size<T>(0,1,1);
+  ret += test_compute_block_size<T>(1,0,1);
+  ret += test_compute_block_size<T>(1,1,0);
+  ret += test_compute_block_size<T>(0,0,1);
+  ret += test_compute_block_size<T>(0,1,0);
+  ret += test_compute_block_size<T>(1,0,0);
+  ret += test_compute_block_size<T>(0,0,0);
+  return ret;
+}
+
+template<typename>
+void aliasing_with_resize()
+{
+  Index m = internal::random<Index>(10,50);
+  Index n = internal::random<Index>(10,50);
+  MatrixXd A, B, C(m,n), D(m,m);
+  VectorXd a, b, c(n);
+  C.setRandom();
+  D.setRandom();
+  c.setRandom();
+  double s = internal::random<double>(1,10);
+
+  A = C;
+  B = A * A.transpose();
+  A = A * A.transpose();
+  VERIFY_IS_APPROX(A,B);
+
+  A = C;
+  B = (A * A.transpose())/s;
+  A = (A * A.transpose())/s;
+  VERIFY_IS_APPROX(A,B);
+
+  A = C;
+  B = (A * A.transpose()) + D;
+  A = (A * A.transpose()) + D;
+  VERIFY_IS_APPROX(A,B);
+
+  A = C;
+  B = D + (A * A.transpose());
+  A = D + (A * A.transpose());
+  VERIFY_IS_APPROX(A,B);
+
+  A = C;
+  B = s * (A * A.transpose());
+  A = s * (A * A.transpose());
+  VERIFY_IS_APPROX(A,B);
+
+  A = C;
+  a = c;
+  b = (A * a)/s;
+  a = (A * a)/s;
+  VERIFY_IS_APPROX(a,b);
+}
+
+template<int>
+void bug_1308()
+{
+  int n = 10;
+  MatrixXd r(n,n);
+  VectorXd v = VectorXd::Random(n);
+  r = v * RowVectorXd::Ones(n);
+  VERIFY_IS_APPROX(r, v.rowwise().replicate(n));
+  r = VectorXd::Ones(n) * v.transpose();
+  VERIFY_IS_APPROX(r, v.rowwise().replicate(n).transpose());
+
+  Matrix4d ones44 = Matrix4d::Ones();
+  Matrix4d m44 = Matrix4d::Ones() * Matrix4d::Ones();
+  VERIFY_IS_APPROX(m44,Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(m44.noalias()=ones44*Matrix4d::Ones(), Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(m44.noalias()=ones44.transpose()*Matrix4d::Ones(), Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(m44.noalias()=Matrix4d::Ones()*ones44, Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(m44.noalias()=Matrix4d::Ones()*ones44.transpose(), Matrix4d::Constant(4));
+
+  typedef Matrix<double,4,4,RowMajor> RMatrix4d;
+  RMatrix4d r44 = Matrix4d::Ones() * Matrix4d::Ones();
+  VERIFY_IS_APPROX(r44,Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(r44.noalias()=ones44*Matrix4d::Ones(), Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(r44.noalias()=ones44.transpose()*Matrix4d::Ones(), Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(r44.noalias()=Matrix4d::Ones()*ones44, Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(r44.noalias()=Matrix4d::Ones()*ones44.transpose(), Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(r44.noalias()=ones44*RMatrix4d::Ones(), Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(r44.noalias()=ones44.transpose()*RMatrix4d::Ones(), Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(r44.noalias()=RMatrix4d::Ones()*ones44, Matrix4d::Constant(4));
+  VERIFY_IS_APPROX(r44.noalias()=RMatrix4d::Ones()*ones44.transpose(), Matrix4d::Constant(4));
+
+//   RowVector4d r4;
+  m44.setOnes();
+  r44.setZero();
+  VERIFY_IS_APPROX(r44.noalias() += m44.row(0).transpose() * RowVector4d::Ones(), ones44);
+  r44.setZero();
+  VERIFY_IS_APPROX(r44.noalias() += m44.col(0) * RowVector4d::Ones(), ones44);
+  r44.setZero();
+  VERIFY_IS_APPROX(r44.noalias() += Vector4d::Ones() * m44.row(0), ones44);
+  r44.setZero();
+  VERIFY_IS_APPROX(r44.noalias() += Vector4d::Ones() * m44.col(0).transpose(), ones44);
+}
 
 void test_product_extra()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( product_extra(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_2( product_extra(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_2( mat_mat_scalar_scalar_product() );
     CALL_SUBTEST_3( product_extra(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
     CALL_SUBTEST_4( product_extra(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
+    CALL_SUBTEST_1( zero_sized_objects(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
   }
-  CALL_SUBTEST_5( zero_sized_objects() );
-  CALL_SUBTEST_6( unaligned_objects() );
+  CALL_SUBTEST_5( bug_127<0>() );
+  CALL_SUBTEST_5( bug_817<0>() );
+  CALL_SUBTEST_5( bug_1308<0>() );
+  CALL_SUBTEST_6( unaligned_objects<0>() );
+  CALL_SUBTEST_7( compute_block_size<float>() );
+  CALL_SUBTEST_7( compute_block_size<double>() );
+  CALL_SUBTEST_7( compute_block_size<std::complex<double> >() );
+  CALL_SUBTEST_8( aliasing_with_resize<void>() );
+
 }

Index: 3rd_party/eigen/test/product_large.cpp
==================================================================
--- 3rd_party/eigen/test/product_large.cpp
+++ 3rd_party/eigen/test/product_large.cpp
@@ -6,19 +6,42 @@
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "product.h"
+
+template<typename T>
+void test_aliasing()
+{
+  int rows = internal::random<int>(1,12);
+  int cols = internal::random<int>(1,12);
+  typedef Matrix<T,Dynamic,Dynamic> MatrixType;
+  typedef Matrix<T,Dynamic,1> VectorType;
+  VectorType x(cols); x.setRandom();
+  VectorType z(x);
+  VectorType y(rows); y.setZero();
+  MatrixType A(rows,cols); A.setRandom();
+  // CwiseBinaryOp
+  VERIFY_IS_APPROX(x = y + A*x, A*z);     // OK because "y + A*x" is marked as "assume-aliasing"
+  x = z;
+  // CwiseUnaryOp
+  VERIFY_IS_APPROX(x = T(1.)*(A*x), A*z); // OK because 1*(A*x) is replaced by (1*A*x) which is a Product<> expression
+  x = z;
+  // VERIFY_IS_APPROX(x = y-A*x, -A*z);   // Not OK in 3.3 because x is resized before A*x gets evaluated
+  x = z;
+}
 
 void test_product_large()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( product(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_2( product(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_3( product(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_4( product(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
     CALL_SUBTEST_5( product(Matrix<float,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+
+    CALL_SUBTEST_1( test_aliasing<float>() );
   }
 
 #if defined EIGEN_TEST_PART_6
   {
     // test a specific issue in DiagonalProduct
@@ -37,19 +60,20 @@
 
   {
     // check the functions to setup blocking sizes compile and do not segfault
     // FIXME check they do what they are supposed to do !!
     std::ptrdiff_t l1 = internal::random<int>(10000,20000);
-    std::ptrdiff_t l2 = internal::random<int>(1000000,2000000);
-    setCpuCacheSizes(l1,l2);
+    std::ptrdiff_t l2 = internal::random<int>(100000,200000);
+    std::ptrdiff_t l3 = internal::random<int>(1000000,2000000);
+    setCpuCacheSizes(l1,l2,l3);
     VERIFY(l1==l1CacheSize());
     VERIFY(l2==l2CacheSize());
     std::ptrdiff_t k1 = internal::random<int>(10,100)*16;
     std::ptrdiff_t m1 = internal::random<int>(10,100)*16;
     std::ptrdiff_t n1 = internal::random<int>(10,100)*16;
     // only makes sure it compiles fine
-    internal::computeProductBlockingSizes<float,float>(k1,m1,n1);
+    internal::computeProductBlockingSizes<float,float,std::ptrdiff_t>(k1,m1,n1,1);
   }
 
   {
     // test regression in row-vector by matrix (bad Map type)
     MatrixXf mat1(10,32); mat1.setRandom();
@@ -58,7 +82,26 @@
     VERIFY_IS_APPROX(r1, (mat1.row(2)*mat2.transpose()).eval());
 
     MatrixXf r2 = mat1.row(2)*mat2;
     VERIFY_IS_APPROX(r2, (mat1.row(2)*mat2).eval());
   }
+
+  {
+    Eigen::MatrixXd A(10,10), B, C;
+    A.setRandom();
+    C = A;
+    for(int k=0; k<79; ++k)
+      C = C * A;
+    B.noalias() = (((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)) * ((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)))
+                * (((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)) * ((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)));
+    VERIFY_IS_APPROX(B,C);
+  }
+#endif
+
+  // Regression test for bug 714:
+#if defined EIGEN_HAS_OPENMP
+  omp_set_dynamic(1);
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_6( product(Matrix<float,Dynamic,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+  }
 #endif
 }

Index: 3rd_party/eigen/test/product_mmtr.cpp
==================================================================
--- 3rd_party/eigen/test/product_mmtr.cpp
+++ 3rd_party/eigen/test/product_mmtr.cpp
@@ -1,39 +1,49 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010-2017 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
 
 #define CHECK_MMTR(DEST, TRI, OP) {                   \
+    ref3 = DEST;                                      \
     ref2 = ref1 = DEST;                               \
     DEST.template triangularView<TRI>() OP;           \
     ref1 OP;                                          \
-    ref2.template triangularView<TRI>() = ref1;       \
+    ref2.template triangularView<TRI>()               \
+      = ref1.template triangularView<TRI>();          \
     VERIFY_IS_APPROX(DEST,ref2);                      \
+    \
+    DEST = ref3;                                      \
+    ref3 = ref2;                                      \
+    ref3.diagonal() = DEST.diagonal();                \
+    DEST.template triangularView<TRI|ZeroDiag>() OP;  \
+    VERIFY_IS_APPROX(DEST,ref3);                      \
   }
 
 template<typename Scalar> void mmtr(int size)
 {
   typedef Matrix<Scalar,Dynamic,Dynamic,ColMajor> MatrixColMaj;
   typedef Matrix<Scalar,Dynamic,Dynamic,RowMajor> MatrixRowMaj;
 
   DenseIndex othersize = internal::random<DenseIndex>(1,200);
   
-  MatrixColMaj matc(size, size);
-  MatrixRowMaj matr(size, size);
-  MatrixColMaj ref1(size, size), ref2(size, size);
+  MatrixColMaj matc = MatrixColMaj::Zero(size, size);
+  MatrixRowMaj matr = MatrixRowMaj::Zero(size, size);
+  MatrixColMaj ref1(size, size), ref2(size, size), ref3(size,size);
   
   MatrixColMaj soc(size,othersize); soc.setRandom();
   MatrixColMaj osc(othersize,size); osc.setRandom();
   MatrixRowMaj sor(size,othersize); sor.setRandom();
   MatrixRowMaj osr(othersize,size); osr.setRandom();
+  MatrixColMaj sqc(size,size); sqc.setRandom();
+  MatrixRowMaj sqr(size,size); sqr.setRandom();
   
   Scalar s = internal::random<Scalar>();
   
   CHECK_MMTR(matc, Lower, = s*soc*sor.adjoint());
   CHECK_MMTR(matc, Upper, = s*(soc*soc.adjoint()));
@@ -47,10 +57,33 @@
   
   CHECK_MMTR(matc, Lower, -= s*soc*soc.adjoint());
   CHECK_MMTR(matc, Upper, -= s*(osc.transpose()*osc.conjugate()));
   CHECK_MMTR(matr, Lower, -= s*soc*soc.adjoint());
   CHECK_MMTR(matr, Upper, -= soc*(s*soc.adjoint()));
+  
+  CHECK_MMTR(matc, Lower, -= s*sqr*sqc.template triangularView<Upper>());
+  CHECK_MMTR(matc, Upper, = s*sqc*sqr.template triangularView<Upper>());
+  CHECK_MMTR(matc, Lower, += s*sqr*sqc.template triangularView<Lower>());
+  CHECK_MMTR(matc, Upper, = s*sqc*sqc.template triangularView<Lower>());
+  
+  CHECK_MMTR(matc, Lower, = (s*sqr).template triangularView<Upper>()*sqc);
+  CHECK_MMTR(matc, Upper, -= (s*sqc).template triangularView<Upper>()*sqc);
+  CHECK_MMTR(matc, Lower, = (s*sqr).template triangularView<Lower>()*sqc);
+  CHECK_MMTR(matc, Upper, += (s*sqc).template triangularView<Lower>()*sqc);
+
+  // check aliasing
+  ref2 = ref1 = matc;
+  ref1 = sqc.adjoint() * matc * sqc;
+  ref2.template triangularView<Upper>() = ref1.template triangularView<Upper>();
+  matc.template triangularView<Upper>() = sqc.adjoint() * matc * sqc;
+  VERIFY_IS_APPROX(matc, ref2);
+
+  ref2 = ref1 = matc;
+  ref1 = sqc * matc * sqc.adjoint();
+  ref2.template triangularView<Lower>() = ref1.template triangularView<Lower>();
+  matc.template triangularView<Lower>() = sqc * matc * sqc.adjoint();
+  VERIFY_IS_APPROX(matc, ref2);
 }
 
 void test_product_mmtr()
 {
   for(int i = 0; i < g_repeat ; i++)

Index: 3rd_party/eigen/test/product_notemporary.cpp
==================================================================
--- 3rd_party/eigen/test/product_notemporary.cpp
+++ 3rd_party/eigen/test/product_notemporary.cpp
@@ -5,29 +5,14 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
-static int nb_temporaries;
-
-inline void on_temporary_creation(int size) {
-  // here's a great place to set a breakpoint when debugging failures in this test!
-  if(size!=0) nb_temporaries++;
-}
-  
-
-#define EIGEN_DENSE_STORAGE_CTOR_PLUGIN { on_temporary_creation(size); }
+#define TEST_ENABLE_TEMPORARY_TRACKING
 
 #include "main.h"
 
-#define VERIFY_EVALUATION_COUNT(XPR,N) {\
-    nb_temporaries = 0; \
-    XPR; \
-    if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
-    VERIFY( (#XPR) && nb_temporaries==N ); \
-  }
-
 template<typename MatrixType> void product_notemporary(const MatrixType& m)
 {
   /* This test checks the number of temporaries created
    * during the evaluation of a complex expression */
   typedef typename MatrixType::Index Index;
@@ -56,14 +41,28 @@
         c1 = internal::random<Index>(8,cols-c0),
         r0 = internal::random<Index>(4,cols-8),
         r1 = internal::random<Index>(8,rows-r0);
 
   VERIFY_EVALUATION_COUNT( m3 = (m1 * m2.adjoint()), 1);
+  VERIFY_EVALUATION_COUNT( m3 = (m1 * m2.adjoint()).transpose(), 1);
   VERIFY_EVALUATION_COUNT( m3.noalias() = m1 * m2.adjoint(), 0);
 
+  VERIFY_EVALUATION_COUNT( m3 = s1 * (m1 * m2.transpose()), 1);
+//   VERIFY_EVALUATION_COUNT( m3 = m3 + s1 * (m1 * m2.transpose()), 1);
   VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * (m1 * m2.transpose()), 0);
 
+  VERIFY_EVALUATION_COUNT( m3 = m3 + (m1 * m2.adjoint()), 1);
+  VERIFY_EVALUATION_COUNT( m3 = m3 - (m1 * m2.adjoint()), 1);
+
+  VERIFY_EVALUATION_COUNT( m3 = m3 + (m1 * m2.adjoint()).transpose(), 1);
+  VERIFY_EVALUATION_COUNT( m3.noalias() = m3 + m1 * m2.transpose(), 0);
+  VERIFY_EVALUATION_COUNT( m3.noalias() += m3 + m1 * m2.transpose(), 0);
+  VERIFY_EVALUATION_COUNT( m3.noalias() -= m3 + m1 * m2.transpose(), 0);
+  VERIFY_EVALUATION_COUNT( m3.noalias() =  m3 - m1 * m2.transpose(), 0);
+  VERIFY_EVALUATION_COUNT( m3.noalias() += m3 - m1 * m2.transpose(), 0);
+  VERIFY_EVALUATION_COUNT( m3.noalias() -= m3 - m1 * m2.transpose(), 0);
+
   VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * m2.adjoint(), 0);
   VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * (m1*s3+m2*s2).adjoint(), 1);
   VERIFY_EVALUATION_COUNT( m3.noalias() = (s1 * m1).adjoint() * s2 * m2, 0);
   VERIFY_EVALUATION_COUNT( m3.noalias() += s1 * (-m1*s3).adjoint() * (s2 * m2 * s3), 0);
   VERIFY_EVALUATION_COUNT( m3.noalias() -= s1 * (m1.transpose() * m2), 0);
@@ -75,11 +74,11 @@
   VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() = s1 * m1.block(r0,c0,r1,c1) * (s1*m2).block(c0,r0,c1,r1) ), 1);
 
   VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).template triangularView<Lower>() * m2, 0);
   VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<Upper>() * (m2+m2), 1);
   VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * m2.adjoint(), 0);
-  
+
   VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() = (m1 * m2.adjoint()), 0);
   VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() -= (m1 * m2.adjoint()), 0);
 
   // NOTE this is because the blas_traits require innerstride==1 to avoid a temporary, but that doesn't seem to be actually needed for the triangular products
   VERIFY_EVALUATION_COUNT( rm3.col(c0).noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * (s2*m2.row(c0)).adjoint(), 1);
@@ -112,30 +111,50 @@
   // ... and even no temporary for even deeply (>=2) nested products
   VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) /  (m3.transpose() * m3).diagonal().sum(), 0 );
   VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) /  (m3.transpose() * m3).diagonal().array().abs().sum(), 0 );
 
   // Zero temporaries for ... CoeffBasedProductMode
-  // - does not work with GCC because of the <..>, we'ld need variadic macros ...
-  //VERIFY_EVALUATION_COUNT( m3.col(0).head<5>() * m3.col(0).transpose() + m3.col(0).head<5>() * m3.col(0).transpose(), 0 );
+  VERIFY_EVALUATION_COUNT( m3.col(0).template head<5>() * m3.col(0).transpose() + m3.col(0).template head<5>() * m3.col(0).transpose(), 0 );
 
   // Check matrix * vectors
   VERIFY_EVALUATION_COUNT( cvres.noalias() = m1 * cv1, 0 );
   VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * cv1, 0 );
   VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.col(0), 0 );
   VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * rv1.adjoint(), 0 );
   VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.row(0).transpose(), 0 );
+
+  VERIFY_EVALUATION_COUNT( cvres.noalias() = (m1+m1) * cv1, 0 );
+  VERIFY_EVALUATION_COUNT( cvres.noalias() = (rm3+rm3) * cv1, 0 );
+  VERIFY_EVALUATION_COUNT( cvres.noalias() = (m1+m1) * (m1*cv1), 1 );
+  VERIFY_EVALUATION_COUNT( cvres.noalias() = (rm3+rm3) * (m1*cv1), 1 );
+
+  // Check outer products
+  m3 = cv1 * rv1;
+  VERIFY_EVALUATION_COUNT( m3.noalias() = cv1 * rv1, 0 );
+  VERIFY_EVALUATION_COUNT( m3.noalias() = (cv1+cv1) * (rv1+rv1), 1 );
+  VERIFY_EVALUATION_COUNT( m3.noalias() = (m1*cv1) * (rv1), 1 );
+  VERIFY_EVALUATION_COUNT( m3.noalias() += (m1*cv1) * (rv1), 1 );
+  VERIFY_EVALUATION_COUNT( rm3.noalias() = (cv1) * (rv1 * m1), 1 );
+  VERIFY_EVALUATION_COUNT( rm3.noalias() -= (cv1) * (rv1 * m1), 1 );
+  VERIFY_EVALUATION_COUNT( rm3.noalias() = (m1*cv1) * (rv1 * m1), 2 );
+  VERIFY_EVALUATION_COUNT( rm3.noalias() += (m1*cv1) * (rv1 * m1), 2 );
+
+  // Check nested products
+  VERIFY_EVALUATION_COUNT( cvres.noalias() = m1.adjoint() * m1 * cv1, 1 );
+  VERIFY_EVALUATION_COUNT( rvres.noalias() = rv1 * (m1 * m2.adjoint()), 1 );
 }
 
 void test_product_notemporary()
 {
   int s;
   for(int i = 0; i < g_repeat; i++) {
     s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE);
     CALL_SUBTEST_1( product_notemporary(MatrixXf(s, s)) );
-    s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE);
     CALL_SUBTEST_2( product_notemporary(MatrixXd(s, s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+    
     s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_3( product_notemporary(MatrixXcf(s,s)) );
-    s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_4( product_notemporary(MatrixXcd(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
   }
 }

Index: 3rd_party/eigen/test/product_selfadjoint.cpp
==================================================================
--- 3rd_party/eigen/test/product_selfadjoint.cpp
+++ 3rd_party/eigen/test/product_selfadjoint.cpp
@@ -65,16 +65,23 @@
   int s = 0;
   for(int i = 0; i < g_repeat ; i++) {
     CALL_SUBTEST_1( product_selfadjoint(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_2( product_selfadjoint(Matrix<float, 2, 2>()) );
     CALL_SUBTEST_3( product_selfadjoint(Matrix3d()) );
+    
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_4( product_selfadjoint(MatrixXcf(s, s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+    
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_5( product_selfadjoint(MatrixXcd(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+    
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
     CALL_SUBTEST_6( product_selfadjoint(MatrixXd(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+    
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
     CALL_SUBTEST_7( product_selfadjoint(Matrix<float,Dynamic,Dynamic,RowMajor>(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
   }
-  TEST_SET_BUT_UNUSED_VARIABLE(s)
 }

Index: 3rd_party/eigen/test/product_small.cpp
==================================================================
--- 3rd_party/eigen/test/product_small.cpp
+++ 3rd_party/eigen/test/product_small.cpp
@@ -7,12 +7,14 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #define EIGEN_NO_STATIC_ASSERT
 #include "product.h"
+#include <Eigen/LU>
 
 // regression test for bug 447
+template<int>
 void product1x1()
 {
   Matrix<float,1,3> matAstatic;
   Matrix<float,3,1> matBstatic;
   matAstatic.setRandom();
@@ -26,25 +28,266 @@
   matBdynamic.setRandom();
   VERIFY_IS_APPROX( (matAdynamic * matBdynamic).coeff(0,0), 
                     matAdynamic.cwiseProduct(matBdynamic.transpose()).sum() );
 }
 
+template<typename TC, typename TA, typename TB>
+const TC& ref_prod(TC &C, const TA &A, const TB &B)
+{
+  for(Index i=0;i<C.rows();++i)
+    for(Index j=0;j<C.cols();++j)
+      for(Index k=0;k<A.cols();++k)
+        C.coeffRef(i,j) += A.coeff(i,k) * B.coeff(k,j);
+  return C;
+}
+
+template<typename T, int Rows, int Cols, int Depth, int OC, int OA, int OB>
+typename internal::enable_if<! ( (Rows ==1&&Depth!=1&&OA==ColMajor)
+                              || (Depth==1&&Rows !=1&&OA==RowMajor)
+                              || (Cols ==1&&Depth!=1&&OB==RowMajor)
+                              || (Depth==1&&Cols !=1&&OB==ColMajor)
+                              || (Rows ==1&&Cols !=1&&OC==ColMajor)
+                              || (Cols ==1&&Rows !=1&&OC==RowMajor)),void>::type
+test_lazy_single(int rows, int cols, int depth)
+{
+  Matrix<T,Rows,Depth,OA> A(rows,depth); A.setRandom();
+  Matrix<T,Depth,Cols,OB> B(depth,cols); B.setRandom();
+  Matrix<T,Rows,Cols,OC>  C(rows,cols);  C.setRandom();
+  Matrix<T,Rows,Cols,OC>  D(C);
+  VERIFY_IS_APPROX(C+=A.lazyProduct(B), ref_prod(D,A,B));
+}
+
+template<typename T, int Rows, int Cols, int Depth, int OC, int OA, int OB>
+typename internal::enable_if<  ( (Rows ==1&&Depth!=1&&OA==ColMajor)
+                              || (Depth==1&&Rows !=1&&OA==RowMajor)
+                              || (Cols ==1&&Depth!=1&&OB==RowMajor)
+                              || (Depth==1&&Cols !=1&&OB==ColMajor)
+                              || (Rows ==1&&Cols !=1&&OC==ColMajor)
+                              || (Cols ==1&&Rows !=1&&OC==RowMajor)),void>::type
+test_lazy_single(int, int, int)
+{
+}
+
+template<typename T, int Rows, int Cols, int Depth>
+void test_lazy_all_layout(int rows=Rows, int cols=Cols, int depth=Depth)
+{
+  CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,ColMajor,ColMajor,ColMajor>(rows,cols,depth) ));
+  CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,RowMajor,ColMajor,ColMajor>(rows,cols,depth) ));
+  CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,ColMajor,RowMajor,ColMajor>(rows,cols,depth) ));
+  CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,RowMajor,RowMajor,ColMajor>(rows,cols,depth) ));
+  CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,ColMajor,ColMajor,RowMajor>(rows,cols,depth) ));
+  CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,RowMajor,ColMajor,RowMajor>(rows,cols,depth) ));
+  CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,ColMajor,RowMajor,RowMajor>(rows,cols,depth) ));
+  CALL_SUBTEST(( test_lazy_single<T,Rows,Cols,Depth,RowMajor,RowMajor,RowMajor>(rows,cols,depth) ));
+}
+
+template<typename T>
+void test_lazy_l1()
+{
+  int rows = internal::random<int>(1,12);
+  int cols = internal::random<int>(1,12);
+  int depth = internal::random<int>(1,12);
+
+  // Inner
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,1,1>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,1,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,1,3>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,1,8>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,1,9>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,1,-1>(1,1,depth) ));
+
+  // Outer
+  CALL_SUBTEST(( test_lazy_all_layout<T,2,1,1>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,2,1>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,2,2,1>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,3,3,1>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,4,1>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,8,1>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,-1,1>(4,cols) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,7,-1,1>(7,cols) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,-1,8,1>(rows) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,-1,3,1>(rows) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,-1,-1,1>(rows,cols) ));
+}
+
+template<typename T>
+void test_lazy_l2()
+{
+  int rows = internal::random<int>(1,12);
+  int cols = internal::random<int>(1,12);
+  int depth = internal::random<int>(1,12);
+
+  // mat-vec
+  CALL_SUBTEST(( test_lazy_all_layout<T,2,1,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,2,1,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,1,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,1,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,5,1,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,1,5>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,1,6>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,6,1,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,8,1,8>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,-1,1,4>(rows) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,1,-1>(4,1,depth) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,-1,1,-1>(rows,1,depth) ));
+
+  // vec-mat
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,2,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,2,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,4,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,4,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,5,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,4,5>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,4,6>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,6,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,8,8>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,-1, 4>(1,cols) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1, 4,-1>(1,4,depth) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,1,-1,-1>(1,cols,depth) ));
+}
+
+template<typename T>
+void test_lazy_l3()
+{
+  int rows = internal::random<int>(1,12);
+  int cols = internal::random<int>(1,12);
+  int depth = internal::random<int>(1,12);
+  // mat-mat
+  CALL_SUBTEST(( test_lazy_all_layout<T,2,4,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,2,6,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,3,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,8,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,5,6,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,2,5>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,7,6>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,6,8,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,8,3,8>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,-1,6,4>(rows) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,3,-1>(4,3,depth) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,-1,6,-1>(rows,6,depth) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,8,2,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,5,2,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,4,2>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,8,4,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,6,5,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,4,5>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,3,4,6>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,2,6,4>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,7,8,8>() ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,8,-1, 4>(8,cols) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,3, 4,-1>(3,4,depth) ));
+  CALL_SUBTEST(( test_lazy_all_layout<T,4,-1,-1>(4,cols,depth) ));
+}
+
+template<typename T,int N,int M,int K>
+void test_linear_but_not_vectorizable()
+{
+  // Check tricky cases for which the result of the product is a vector and thus must exhibit the LinearBit flag,
+  // but is not vectorizable along the linear dimension.
+  Index n = N==Dynamic ? internal::random<Index>(1,32) : N;
+  Index m = M==Dynamic ? internal::random<Index>(1,32) : M;
+  Index k = K==Dynamic ? internal::random<Index>(1,32) : K;
+
+  {
+    Matrix<T,N,M+1> A; A.setRandom(n,m+1);
+    Matrix<T,M*2,K> B; B.setRandom(m*2,k);
+    Matrix<T,1,K> C;
+    Matrix<T,1,K> R;
+
+    C.noalias() = A.template topLeftCorner<1,M>() * (B.template topRows<M>()+B.template bottomRows<M>());
+    R.noalias() = A.template topLeftCorner<1,M>() * (B.template topRows<M>()+B.template bottomRows<M>()).eval();
+    VERIFY_IS_APPROX(C,R);
+  }
+
+  {
+    Matrix<T,M+1,N,RowMajor> A; A.setRandom(m+1,n);
+    Matrix<T,K,M*2,RowMajor> B; B.setRandom(k,m*2);
+    Matrix<T,K,1> C;
+    Matrix<T,K,1> R;
+
+    C.noalias() = (B.template leftCols<M>()+B.template rightCols<M>())        * A.template topLeftCorner<M,1>();
+    R.noalias() = (B.template leftCols<M>()+B.template rightCols<M>()).eval() * A.template topLeftCorner<M,1>();
+    VERIFY_IS_APPROX(C,R);
+  }
+}
+
+template<int Rows>
+void bug_1311()
+{
+  Matrix< double, Rows, 2 > A;  A.setRandom();
+  Vector2d b = Vector2d::Random() ;
+  Matrix<double,Rows,1> res;
+  res.noalias() = 1. * (A * b);
+  VERIFY_IS_APPROX(res, A*b);
+  res.noalias() = 1.*A * b;
+  VERIFY_IS_APPROX(res, A*b);
+  res.noalias() = (1.*A).lazyProduct(b);
+  VERIFY_IS_APPROX(res, A*b);
+  res.noalias() = (1.*A).lazyProduct(1.*b);
+  VERIFY_IS_APPROX(res, A*b);
+  res.noalias() = (A).lazyProduct(1.*b);
+  VERIFY_IS_APPROX(res, A*b);
+}
 
 void test_product_small()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( product(Matrix<float, 3, 2>()) );
-    CALL_SUBTEST_2( product(Matrix<int, 3, 5>()) );
+    CALL_SUBTEST_2( product(Matrix<int, 3, 17>()) );
+    CALL_SUBTEST_8( product(Matrix<double, 3, 17>()) );
     CALL_SUBTEST_3( product(Matrix3d()) );
     CALL_SUBTEST_4( product(Matrix4d()) );
     CALL_SUBTEST_5( product(Matrix4f()) );
-    CALL_SUBTEST_6( product1x1() );
+    CALL_SUBTEST_6( product1x1<0>() );
+
+    CALL_SUBTEST_11( test_lazy_l1<float>() );
+    CALL_SUBTEST_12( test_lazy_l2<float>() );
+    CALL_SUBTEST_13( test_lazy_l3<float>() );
+
+    CALL_SUBTEST_21( test_lazy_l1<double>() );
+    CALL_SUBTEST_22( test_lazy_l2<double>() );
+    CALL_SUBTEST_23( test_lazy_l3<double>() );
+
+    CALL_SUBTEST_31( test_lazy_l1<std::complex<float> >() );
+    CALL_SUBTEST_32( test_lazy_l2<std::complex<float> >() );
+    CALL_SUBTEST_33( test_lazy_l3<std::complex<float> >() );
+
+    CALL_SUBTEST_41( test_lazy_l1<std::complex<double> >() );
+    CALL_SUBTEST_42( test_lazy_l2<std::complex<double> >() );
+    CALL_SUBTEST_43( test_lazy_l3<std::complex<double> >() );
+
+    CALL_SUBTEST_7(( test_linear_but_not_vectorizable<float,2,1,Dynamic>() ));
+    CALL_SUBTEST_7(( test_linear_but_not_vectorizable<float,3,1,Dynamic>() ));
+    CALL_SUBTEST_7(( test_linear_but_not_vectorizable<float,2,1,16>() ));
+
+    CALL_SUBTEST_6( bug_1311<3>() );
+    CALL_SUBTEST_6( bug_1311<5>() );
   }
 
 #ifdef EIGEN_TEST_PART_6
   {
     // test compilation of (outer_product) * vector
     Vector3f v = Vector3f::Random();
     VERIFY_IS_APPROX( (v * v.transpose()) * v, (v * v.transpose()).eval() * v);
   }
+  
+  {
+    // regression test for pull-request #93
+    Eigen::Matrix<double, 1, 1> A;  A.setRandom();
+    Eigen::Matrix<double, 18, 1> B; B.setRandom();
+    Eigen::Matrix<double, 1, 18> C; C.setRandom();
+    VERIFY_IS_APPROX(B * A.inverse(), B * A.inverse()[0]);
+    VERIFY_IS_APPROX(A.inverse() * C, A.inverse()[0] * C);
+  }
+
+  {
+    Eigen::Matrix<double, 10, 10> A, B, C;
+    A.setRandom();
+    C = A;
+    for(int k=0; k<79; ++k)
+      C = C * A;
+    B.noalias() = (((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)) * ((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)))
+                * (((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)) * ((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)));
+    VERIFY_IS_APPROX(B,C);
+  }
 #endif
 }

Index: 3rd_party/eigen/test/product_symm.cpp
==================================================================
--- 3rd_party/eigen/test/product_symm.cpp
+++ 3rd_party/eigen/test/product_symm.cpp
@@ -36,10 +36,28 @@
   m2 = m1.template triangularView<Lower>();
   m3 = m2.template selfadjointView<Lower>();
   VERIFY_IS_EQUAL(m1, m3);
   VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Lower>() * (s2*rhs1),
                    rhs13 = (s1*m1) * (s2*rhs1));
+
+  VERIFY_IS_APPROX(rhs12 = (s1*m2).transpose().template selfadjointView<Upper>() * (s2*rhs1),
+                   rhs13 = (s1*m1.transpose()) * (s2*rhs1));
+
+  VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Lower>().transpose() * (s2*rhs1),
+                   rhs13 = (s1*m1.transpose()) * (s2*rhs1));
+
+  VERIFY_IS_APPROX(rhs12 = (s1*m2).conjugate().template selfadjointView<Lower>() * (s2*rhs1),
+                   rhs13 = (s1*m1).conjugate() * (s2*rhs1));
+
+  VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Lower>().conjugate() * (s2*rhs1),
+                   rhs13 = (s1*m1).conjugate() * (s2*rhs1));
+
+  VERIFY_IS_APPROX(rhs12 = (s1*m2).adjoint().template selfadjointView<Upper>() * (s2*rhs1),
+                   rhs13 = (s1*m1).adjoint() * (s2*rhs1));
+
+  VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Lower>().adjoint() * (s2*rhs1),
+                   rhs13 = (s1*m1).adjoint() * (s2*rhs1));
 
   m2 = m1.template triangularView<Upper>(); rhs12.setRandom(); rhs13 = rhs12;
   m3 = m2.template selfadjointView<Upper>();
   VERIFY_IS_EQUAL(m1, m3);
   VERIFY_IS_APPROX(rhs12 += (s1*m2).template selfadjointView<Upper>() * (s2*rhs1),

Index: 3rd_party/eigen/test/product_syrk.cpp
==================================================================
--- 3rd_party/eigen/test/product_syrk.cpp
+++ 3rd_party/eigen/test/product_syrk.cpp
@@ -123,13 +123,14 @@
   for(int i = 0; i < g_repeat ; i++)
   {
     int s;
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
     CALL_SUBTEST_1( syrk(MatrixXf(s, s)) );
-    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
     CALL_SUBTEST_2( syrk(MatrixXd(s, s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+    
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) );
-    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
   }
 }

Index: 3rd_party/eigen/test/product_trmm.cpp
==================================================================
--- 3rd_party/eigen/test/product_trmm.cpp
+++ 3rd_party/eigen/test/product_trmm.cpp
@@ -6,15 +6,23 @@
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
+
+template<typename T>
+int get_random_size()
+{
+  const int factor = NumTraits<T>::ReadCost;
+  const int max_test_size = EIGEN_TEST_MAX_SIZE>2*factor ? EIGEN_TEST_MAX_SIZE/factor : EIGEN_TEST_MAX_SIZE;
+  return internal::random<int>(1,max_test_size);
+}
 
 template<typename Scalar, int Mode, int TriOrder, int OtherOrder, int ResOrder, int OtherCols>
-void trmm(int rows=internal::random<int>(1,EIGEN_TEST_MAX_SIZE),
-          int cols=internal::random<int>(1,EIGEN_TEST_MAX_SIZE),
-          int otherCols = OtherCols==Dynamic?internal::random<int>(1,EIGEN_TEST_MAX_SIZE):OtherCols)
+void trmm(int rows=get_random_size<Scalar>(),
+          int cols=get_random_size<Scalar>(),
+          int otherCols = OtherCols==Dynamic?get_random_size<Scalar>():OtherCols)
 {
   typedef Matrix<Scalar,Dynamic,Dynamic,TriOrder> TriMatrix;
   typedef Matrix<Scalar,Dynamic,OtherCols,OtherCols==1?ColMajor:OtherOrder> OnTheRight;
   typedef Matrix<Scalar,OtherCols,Dynamic,OtherCols==1?RowMajor:OtherOrder> OnTheLeft;
   
@@ -40,17 +48,17 @@
   VERIFY_IS_APPROX( ge_xs = mat.template triangularView<Mode>() * ge_right, tri * ge_right);
   VERIFY_IS_APPROX( ge_sx = ge_left * mat.template triangularView<Mode>(), ge_left * tri);
   
   VERIFY_IS_APPROX( ge_xs.noalias() = mat.template triangularView<Mode>() * ge_right, tri * ge_right);
   VERIFY_IS_APPROX( ge_sx.noalias() = ge_left * mat.template triangularView<Mode>(), ge_left * tri);
-  
+
   VERIFY_IS_APPROX( ge_xs.noalias() = (s1*mat.adjoint()).template triangularView<Mode>() * (s2*ge_left.transpose()), s1*triTr.conjugate() * (s2*ge_left.transpose()));
   VERIFY_IS_APPROX( ge_sx.noalias() = ge_right.transpose() * mat.adjoint().template triangularView<Mode>(), ge_right.transpose() * triTr.conjugate());
   
   VERIFY_IS_APPROX( ge_xs.noalias() = (s1*mat.adjoint()).template triangularView<Mode>() * (s2*ge_left.adjoint()), s1*triTr.conjugate() * (s2*ge_left.adjoint()));
   VERIFY_IS_APPROX( ge_sx.noalias() = ge_right.adjoint() * mat.adjoint().template triangularView<Mode>(), ge_right.adjoint() * triTr.conjugate());
-  
+
   ge_xs_save = ge_xs;
   VERIFY_IS_APPROX( (ge_xs_save + s1*triTr.conjugate() * (s2*ge_left.adjoint())).eval(), ge_xs.noalias() += (s1*mat.adjoint()).template triangularView<Mode>() * (s2*ge_left.adjoint()) );
   ge_sx.setRandom();
   ge_sx_save = ge_sx;
   VERIFY_IS_APPROX( ge_sx_save - (ge_right.adjoint() * (-s1 * triTr).conjugate()).eval(), ge_sx.noalias() -= (ge_right.adjoint() * (-s1 * mat).adjoint().template triangularView<Mode>()).eval());
@@ -59,17 +67,17 @@
   
   // TODO check with sub-matrix expressions ?
 }
 
 template<typename Scalar, int Mode, int TriOrder>
-void trmv(int rows=internal::random<int>(1,EIGEN_TEST_MAX_SIZE), int cols=internal::random<int>(1,EIGEN_TEST_MAX_SIZE))
+void trmv(int rows=get_random_size<Scalar>(), int cols=get_random_size<Scalar>())
 {
   trmm<Scalar,Mode,TriOrder,ColMajor,ColMajor,1>(rows,cols,1);
 }
 
 template<typename Scalar, int Mode, int TriOrder, int OtherOrder, int ResOrder>
-void trmm(int rows=internal::random<int>(1,EIGEN_TEST_MAX_SIZE), int cols=internal::random<int>(1,EIGEN_TEST_MAX_SIZE), int otherCols = internal::random<int>(1,EIGEN_TEST_MAX_SIZE))
+void trmm(int rows=get_random_size<Scalar>(), int cols=get_random_size<Scalar>(), int otherCols = get_random_size<Scalar>())
 {
   trmm<Scalar,Mode,TriOrder,OtherOrder,ResOrder,Dynamic>(rows,cols,otherCols);
 }
 
 #define CALL_ALL_ORDERS(NB,SCALAR,MODE)                                             \

Index: 3rd_party/eigen/test/product_trmv.cpp
==================================================================
--- 3rd_party/eigen/test/product_trmv.cpp
+++ 3rd_party/eigen/test/product_trmv.cpp
@@ -76,14 +76,16 @@
   int s = 0;
   for(int i = 0; i < g_repeat ; i++) {
     CALL_SUBTEST_1( trmv(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_2( trmv(Matrix<float, 2, 2>()) );
     CALL_SUBTEST_3( trmv(Matrix3d()) );
+    
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_4( trmv(MatrixXcf(s,s)) );
-    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
     CALL_SUBTEST_5( trmv(MatrixXcd(s,s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+    
     s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
     CALL_SUBTEST_6( trmv(Matrix<float,Dynamic,Dynamic,RowMajor>(s, s)) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
   }
-  TEST_SET_BUT_UNUSED_VARIABLE(s);
 }

Index: 3rd_party/eigen/test/product_trsolve.cpp
==================================================================
--- 3rd_party/eigen/test/product_trsolve.cpp
+++ 3rd_party/eigen/test/product_trsolve.cpp
@@ -82,12 +82,20 @@
     CALL_SUBTEST_2((trsolve<double,Dynamic,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE),internal::random<int>(1,EIGEN_TEST_MAX_SIZE))));
     CALL_SUBTEST_3((trsolve<std::complex<float>,Dynamic,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2),internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))));
     CALL_SUBTEST_4((trsolve<std::complex<double>,Dynamic,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2),internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))));
 
     // vectors
-    CALL_SUBTEST_1((trsolve<float,Dynamic,1>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))));
-    CALL_SUBTEST_5((trsolve<std::complex<double>,Dynamic,1>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))));
-    CALL_SUBTEST_6((trsolve<float,1,1>()));
-    CALL_SUBTEST_7((trsolve<float,1,2>()));
-    CALL_SUBTEST_8((trsolve<std::complex<float>,4,1>()));
+    CALL_SUBTEST_5((trsolve<float,Dynamic,1>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))));
+    CALL_SUBTEST_6((trsolve<double,Dynamic,1>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))));
+    CALL_SUBTEST_7((trsolve<std::complex<float>,Dynamic,1>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))));
+    CALL_SUBTEST_8((trsolve<std::complex<double>,Dynamic,1>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))));
+    
+    // meta-unrollers
+    CALL_SUBTEST_9((trsolve<float,4,1>()));
+    CALL_SUBTEST_10((trsolve<double,4,1>()));
+    CALL_SUBTEST_11((trsolve<std::complex<float>,4,1>()));
+    CALL_SUBTEST_12((trsolve<float,1,1>()));
+    CALL_SUBTEST_13((trsolve<float,1,2>()));
+    CALL_SUBTEST_14((trsolve<float,3,1>()));
+    
   }
 }

Index: 3rd_party/eigen/test/qr.cpp
==================================================================
--- 3rd_party/eigen/test/qr.cpp
+++ 3rd_party/eigen/test/qr.cpp
@@ -52,10 +52,12 @@
 
 template<typename MatrixType> void qr_invertible()
 {
   using std::log;
   using std::abs;
+  using std::pow;
+  using std::max;
   typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
   typedef typename MatrixType::Scalar Scalar;
 
   int size = internal::random<int>(10,50);
 
@@ -63,11 +65,11 @@
   m1 = MatrixType::Random(size,size);
 
   if (internal::is_same<RealScalar,float>::value)
   {
     // let's build a matrix more stable to inverse
-    MatrixType a = MatrixType::Random(size,size*2);
+    MatrixType a = MatrixType::Random(size,size*4);
     m1 += a * a.adjoint();
   }
 
   HouseholderQR<MatrixType> qr(m1);
   m3 = MatrixType::Random(size,size);
@@ -79,12 +81,15 @@
   for(int i = 0; i < size; i++) m1(i,i) = internal::random<Scalar>();
   RealScalar absdet = abs(m1.diagonal().prod());
   m3 = qr.householderQ(); // get a unitary
   m1 = m3 * m1 * m3;
   qr.compute(m1);
-  VERIFY_IS_APPROX(absdet, qr.absDeterminant());
   VERIFY_IS_APPROX(log(absdet), qr.logAbsDeterminant());
+  // This test is tricky if the determinant becomes too small.
+  // Since we generate random numbers with magnitude rrange [0,1], the average determinant is 0.5^size
+  VERIFY_IS_MUCH_SMALLER_THAN( abs(absdet-qr.absDeterminant()), numext::maxi(RealScalar(pow(0.5,size)),numext::maxi<RealScalar>(abs(absdet),abs(qr.absDeterminant()))) );
+  
 }
 
 template<typename MatrixType> void qr_verify_assert()
 {
   MatrixType tmp;

Index: 3rd_party/eigen/test/qr_colpivoting.cpp
==================================================================
--- 3rd_party/eigen/test/qr_colpivoting.cpp
+++ 3rd_party/eigen/test/qr_colpivoting.cpp
@@ -8,25 +8,107 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
 #include <Eigen/QR>
+#include <Eigen/SVD>
+
+template <typename MatrixType>
+void cod() {
+  typedef typename MatrixType::Index Index;
+
+  Index rows = internal::random<Index>(2, EIGEN_TEST_MAX_SIZE);
+  Index cols = internal::random<Index>(2, EIGEN_TEST_MAX_SIZE);
+  Index cols2 = internal::random<Index>(2, EIGEN_TEST_MAX_SIZE);
+  Index rank = internal::random<Index>(1, (std::min)(rows, cols) - 1);
+
+  typedef typename MatrixType::Scalar Scalar;
+  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime,
+                 MatrixType::RowsAtCompileTime>
+      MatrixQType;
+  MatrixType matrix;
+  createRandomPIMatrixOfRank(rank, rows, cols, matrix);
+  CompleteOrthogonalDecomposition<MatrixType> cod(matrix);
+  VERIFY(rank == cod.rank());
+  VERIFY(cols - cod.rank() == cod.dimensionOfKernel());
+  VERIFY(!cod.isInjective());
+  VERIFY(!cod.isInvertible());
+  VERIFY(!cod.isSurjective());
+
+  MatrixQType q = cod.householderQ();
+  VERIFY_IS_UNITARY(q);
+
+  MatrixType z = cod.matrixZ();
+  VERIFY_IS_UNITARY(z);
+
+  MatrixType t;
+  t.setZero(rows, cols);
+  t.topLeftCorner(rank, rank) =
+      cod.matrixT().topLeftCorner(rank, rank).template triangularView<Upper>();
+
+  MatrixType c = q * t * z * cod.colsPermutation().inverse();
+  VERIFY_IS_APPROX(matrix, c);
+
+  MatrixType exact_solution = MatrixType::Random(cols, cols2);
+  MatrixType rhs = matrix * exact_solution;
+  MatrixType cod_solution = cod.solve(rhs);
+  VERIFY_IS_APPROX(rhs, matrix * cod_solution);
+
+  // Verify that we get the same minimum-norm solution as the SVD.
+  JacobiSVD<MatrixType> svd(matrix, ComputeThinU | ComputeThinV);
+  MatrixType svd_solution = svd.solve(rhs);
+  VERIFY_IS_APPROX(cod_solution, svd_solution);
+
+  MatrixType pinv = cod.pseudoInverse();
+  VERIFY_IS_APPROX(cod_solution, pinv * rhs);
+}
+
+template <typename MatrixType, int Cols2>
+void cod_fixedsize() {
+  enum {
+    Rows = MatrixType::RowsAtCompileTime,
+    Cols = MatrixType::ColsAtCompileTime
+  };
+  typedef typename MatrixType::Scalar Scalar;
+  int rank = internal::random<int>(1, (std::min)(int(Rows), int(Cols)) - 1);
+  Matrix<Scalar, Rows, Cols> matrix;
+  createRandomPIMatrixOfRank(rank, Rows, Cols, matrix);
+  CompleteOrthogonalDecomposition<Matrix<Scalar, Rows, Cols> > cod(matrix);
+  VERIFY(rank == cod.rank());
+  VERIFY(Cols - cod.rank() == cod.dimensionOfKernel());
+  VERIFY(cod.isInjective() == (rank == Rows));
+  VERIFY(cod.isSurjective() == (rank == Cols));
+  VERIFY(cod.isInvertible() == (cod.isInjective() && cod.isSurjective()));
+
+  Matrix<Scalar, Cols, Cols2> exact_solution;
+  exact_solution.setRandom(Cols, Cols2);
+  Matrix<Scalar, Rows, Cols2> rhs = matrix * exact_solution;
+  Matrix<Scalar, Cols, Cols2> cod_solution = cod.solve(rhs);
+  VERIFY_IS_APPROX(rhs, matrix * cod_solution);
+
+  // Verify that we get the same minimum-norm solution as the SVD.
+  JacobiSVD<MatrixType> svd(matrix, ComputeFullU | ComputeFullV);
+  Matrix<Scalar, Cols, Cols2> svd_solution = svd.solve(rhs);
+  VERIFY_IS_APPROX(cod_solution, svd_solution);
+}
 
 template<typename MatrixType> void qr()
 {
+  using std::sqrt;
   typedef typename MatrixType::Index Index;
 
   Index rows = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols2 = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE);
   Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1);
 
   typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> MatrixQType;
   MatrixType m1;
   createRandomPIMatrixOfRank(rank,rows,cols,m1);
   ColPivHouseholderQR<MatrixType> qr(m1);
-  VERIFY(rank == qr.rank());
-  VERIFY(cols - qr.rank() == qr.dimensionOfKernel());
+  VERIFY_IS_EQUAL(rank, qr.rank());
+  VERIFY_IS_EQUAL(cols - qr.rank(), qr.dimensionOfKernel());
   VERIFY(!qr.isInjective());
   VERIFY(!qr.isInvertible());
   VERIFY(!qr.isSurjective());
 
   MatrixQType q = qr.householderQ();
@@ -33,31 +115,64 @@
   VERIFY_IS_UNITARY(q);
 
   MatrixType r = qr.matrixQR().template triangularView<Upper>();
   MatrixType c = q * r * qr.colsPermutation().inverse();
   VERIFY_IS_APPROX(m1, c);
+
+  // Verify that the absolute value of the diagonal elements in R are
+  // non-increasing until they reach the singularity threshold.
+  RealScalar threshold =
+      sqrt(RealScalar(rows)) * numext::abs(r(0, 0)) * NumTraits<Scalar>::epsilon();
+  for (Index i = 0; i < (std::min)(rows, cols) - 1; ++i) {
+    RealScalar x = numext::abs(r(i, i));
+    RealScalar y = numext::abs(r(i + 1, i + 1));
+    if (x < threshold && y < threshold) continue;
+    if (!test_isApproxOrLessThan(y, x)) {
+      for (Index j = 0; j < (std::min)(rows, cols); ++j) {
+        std::cout << "i = " << j << ", |r_ii| = " << numext::abs(r(j, j)) << std::endl;
+      }
+      std::cout << "Failure at i=" << i << ", rank=" << rank
+                << ", threshold=" << threshold << std::endl;
+    }
+    VERIFY_IS_APPROX_OR_LESS_THAN(y, x);
+  }
 
   MatrixType m2 = MatrixType::Random(cols,cols2);
   MatrixType m3 = m1*m2;
   m2 = MatrixType::Random(cols,cols2);
   m2 = qr.solve(m3);
   VERIFY_IS_APPROX(m3, m1*m2);
+
+  {
+    Index size = rows;
+    do {
+      m1 = MatrixType::Random(size,size);
+      qr.compute(m1);
+    } while(!qr.isInvertible());
+    MatrixType m1_inv = qr.inverse();
+    m3 = m1 * MatrixType::Random(size,cols2);
+    m2 = qr.solve(m3);
+    VERIFY_IS_APPROX(m2, m1_inv*m3);
+  }
 }
 
 template<typename MatrixType, int Cols2> void qr_fixedsize()
 {
+  using std::sqrt;
+  using std::abs;
   enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
   typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
   int rank = internal::random<int>(1, (std::min)(int(Rows), int(Cols))-1);
   Matrix<Scalar,Rows,Cols> m1;
   createRandomPIMatrixOfRank(rank,Rows,Cols,m1);
   ColPivHouseholderQR<Matrix<Scalar,Rows,Cols> > qr(m1);
-  VERIFY(rank == qr.rank());
-  VERIFY(Cols - qr.rank() == qr.dimensionOfKernel());
-  VERIFY(qr.isInjective() == (rank == Rows));
-  VERIFY(qr.isSurjective() == (rank == Cols));
-  VERIFY(qr.isInvertible() == (qr.isInjective() && qr.isSurjective()));
+  VERIFY_IS_EQUAL(rank, qr.rank());
+  VERIFY_IS_EQUAL(Cols - qr.rank(), qr.dimensionOfKernel());
+  VERIFY_IS_EQUAL(qr.isInjective(), (rank == Rows));
+  VERIFY_IS_EQUAL(qr.isSurjective(), (rank == Cols));
+  VERIFY_IS_EQUAL(qr.isInvertible(), (qr.isInjective() && qr.isSurjective()));
 
   Matrix<Scalar,Rows,Cols> r = qr.matrixQR().template triangularView<Upper>();
   Matrix<Scalar,Rows,Cols> c = qr.householderQ() * r * qr.colsPermutation().inverse();
   VERIFY_IS_APPROX(m1, c);
 
@@ -64,10 +179,75 @@
   Matrix<Scalar,Cols,Cols2> m2 = Matrix<Scalar,Cols,Cols2>::Random(Cols,Cols2);
   Matrix<Scalar,Rows,Cols2> m3 = m1*m2;
   m2 = Matrix<Scalar,Cols,Cols2>::Random(Cols,Cols2);
   m2 = qr.solve(m3);
   VERIFY_IS_APPROX(m3, m1*m2);
+  // Verify that the absolute value of the diagonal elements in R are
+  // non-increasing until they reache the singularity threshold.
+  RealScalar threshold =
+      sqrt(RealScalar(Rows)) * (std::abs)(r(0, 0)) * NumTraits<Scalar>::epsilon();
+  for (Index i = 0; i < (std::min)(int(Rows), int(Cols)) - 1; ++i) {
+    RealScalar x = numext::abs(r(i, i));
+    RealScalar y = numext::abs(r(i + 1, i + 1));
+    if (x < threshold && y < threshold) continue;
+    if (!test_isApproxOrLessThan(y, x)) {
+      for (Index j = 0; j < (std::min)(int(Rows), int(Cols)); ++j) {
+        std::cout << "i = " << j << ", |r_ii| = " << numext::abs(r(j, j)) << std::endl;
+      }
+      std::cout << "Failure at i=" << i << ", rank=" << rank
+                << ", threshold=" << threshold << std::endl;
+    }
+    VERIFY_IS_APPROX_OR_LESS_THAN(y, x);
+  }
+}
+
+// This test is meant to verify that pivots are chosen such that
+// even for a graded matrix, the diagonal of R falls of roughly
+// monotonically until it reaches the threshold for singularity.
+// We use the so-called Kahan matrix, which is a famous counter-example
+// for rank-revealing QR. See
+// http://www.netlib.org/lapack/lawnspdf/lawn176.pdf
+// page 3 for more detail.
+template<typename MatrixType> void qr_kahan_matrix()
+{
+  using std::sqrt;
+  using std::abs;
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+
+  Index rows = 300, cols = rows;
+
+  MatrixType m1;
+  m1.setZero(rows,cols);
+  RealScalar s = std::pow(NumTraits<RealScalar>::epsilon(), 1.0 / rows);
+  RealScalar c = std::sqrt(1 - s*s);
+  RealScalar pow_s_i(1.0); // pow(s,i)
+  for (Index i = 0; i < rows; ++i) {
+    m1(i, i) = pow_s_i;
+    m1.row(i).tail(rows - i - 1) = -pow_s_i * c * MatrixType::Ones(1, rows - i - 1);
+    pow_s_i *= s;
+  }
+  m1 = (m1 + m1.transpose()).eval();
+  ColPivHouseholderQR<MatrixType> qr(m1);
+  MatrixType r = qr.matrixQR().template triangularView<Upper>();
+
+  RealScalar threshold =
+      std::sqrt(RealScalar(rows)) * numext::abs(r(0, 0)) * NumTraits<Scalar>::epsilon();
+  for (Index i = 0; i < (std::min)(rows, cols) - 1; ++i) {
+    RealScalar x = numext::abs(r(i, i));
+    RealScalar y = numext::abs(r(i + 1, i + 1));
+    if (x < threshold && y < threshold) continue;
+    if (!test_isApproxOrLessThan(y, x)) {
+      for (Index j = 0; j < (std::min)(rows, cols); ++j) {
+        std::cout << "i = " << j << ", |r_ii| = " << numext::abs(r(j, j)) << std::endl;
+      }
+      std::cout << "Failure at i=" << i << ", rank=" << qr.rank()
+                << ", threshold=" << threshold << std::endl;
+    }
+    VERIFY_IS_APPROX_OR_LESS_THAN(y, x);
+  }
 }
 
 template<typename MatrixType> void qr_invertible()
 {
   using std::log;
@@ -128,10 +308,19 @@
     CALL_SUBTEST_3( qr<MatrixXcd>() );
     CALL_SUBTEST_4(( qr_fixedsize<Matrix<float,3,5>, 4 >() ));
     CALL_SUBTEST_5(( qr_fixedsize<Matrix<double,6,2>, 3 >() ));
     CALL_SUBTEST_5(( qr_fixedsize<Matrix<double,1,1>, 1 >() ));
   }
+
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( cod<MatrixXf>() );
+    CALL_SUBTEST_2( cod<MatrixXd>() );
+    CALL_SUBTEST_3( cod<MatrixXcd>() );
+    CALL_SUBTEST_4(( cod_fixedsize<Matrix<float,3,5>, 4 >() ));
+    CALL_SUBTEST_5(( cod_fixedsize<Matrix<double,6,2>, 3 >() ));
+    CALL_SUBTEST_5(( cod_fixedsize<Matrix<double,1,1>, 1 >() ));
+  }
 
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( qr_invertible<MatrixXf>() );
     CALL_SUBTEST_2( qr_invertible<MatrixXd>() );
     CALL_SUBTEST_6( qr_invertible<MatrixXcf>() );
@@ -145,6 +334,9 @@
   CALL_SUBTEST_6(qr_verify_assert<MatrixXcf>());
   CALL_SUBTEST_3(qr_verify_assert<MatrixXcd>());
 
   // Test problem size constructors
   CALL_SUBTEST_9(ColPivHouseholderQR<MatrixXf>(10, 20));
+
+  CALL_SUBTEST_1( qr_kahan_matrix<MatrixXf>() );
+  CALL_SUBTEST_2( qr_kahan_matrix<MatrixXd>() );
 }

Index: 3rd_party/eigen/test/qr_fullpivoting.cpp
==================================================================
--- 3rd_party/eigen/test/qr_fullpivoting.cpp
+++ 3rd_party/eigen/test/qr_fullpivoting.cpp
@@ -13,20 +13,24 @@
 
 template<typename MatrixType> void qr()
 {
   typedef typename MatrixType::Index Index;
 
-  Index rows = internal::random<Index>(20,200), cols = internal::random<int>(20,200), cols2 = internal::random<int>(20,200);
-  Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1);
+  Index max_size = EIGEN_TEST_MAX_SIZE;
+  Index min_size = numext::maxi(1,EIGEN_TEST_MAX_SIZE/10);
+  Index rows  = internal::random<Index>(min_size,max_size),
+        cols  = internal::random<Index>(min_size,max_size),
+        cols2 = internal::random<Index>(min_size,max_size),
+        rank  = internal::random<Index>(1, (std::min)(rows, cols)-1);
 
   typedef typename MatrixType::Scalar Scalar;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> MatrixQType;
   MatrixType m1;
   createRandomPIMatrixOfRank(rank,rows,cols,m1);
   FullPivHouseholderQR<MatrixType> qr(m1);
-  VERIFY(rank == qr.rank());
-  VERIFY(cols - qr.rank() == qr.dimensionOfKernel());
+  VERIFY_IS_EQUAL(rank, qr.rank());
+  VERIFY_IS_EQUAL(cols - qr.rank(), qr.dimensionOfKernel());
   VERIFY(!qr.isInjective());
   VERIFY(!qr.isInvertible());
   VERIFY(!qr.isSurjective());
 
   MatrixType r = qr.matrixQR();
@@ -38,26 +42,44 @@
   for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) if(i>j) r(i,j) = Scalar(0);
 
   MatrixType c = qr.matrixQ() * r * qr.colsPermutation().inverse();
 
   VERIFY_IS_APPROX(m1, c);
-
+  
+  // stress the ReturnByValue mechanism
+  MatrixType tmp;
+  VERIFY_IS_APPROX(tmp.noalias() = qr.matrixQ() * r, (qr.matrixQ() * r).eval());
+  
   MatrixType m2 = MatrixType::Random(cols,cols2);
   MatrixType m3 = m1*m2;
   m2 = MatrixType::Random(cols,cols2);
   m2 = qr.solve(m3);
   VERIFY_IS_APPROX(m3, m1*m2);
+
+  {
+    Index size = rows;
+    do {
+      m1 = MatrixType::Random(size,size);
+      qr.compute(m1);
+    } while(!qr.isInvertible());
+    MatrixType m1_inv = qr.inverse();
+    m3 = m1 * MatrixType::Random(size,cols2);
+    m2 = qr.solve(m3);
+    VERIFY_IS_APPROX(m2, m1_inv*m3);
+  }
 }
 
 template<typename MatrixType> void qr_invertible()
 {
   using std::log;
   using std::abs;
   typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
   typedef typename MatrixType::Scalar Scalar;
 
-  int size = internal::random<int>(10,50);
+  Index max_size = numext::mini(50,EIGEN_TEST_MAX_SIZE);
+  Index min_size = numext::maxi(1,EIGEN_TEST_MAX_SIZE/10);
+  Index size = internal::random<Index>(min_size,max_size);
 
   MatrixType m1(size, size), m2(size, size), m3(size, size);
   m1 = MatrixType::Random(size,size);
 
   if (internal::is_same<RealScalar,float>::value)

ADDED   3rd_party/eigen/test/rand.cpp
Index: 3rd_party/eigen/test/rand.cpp
==================================================================
--- 3rd_party/eigen/test/rand.cpp
+++ 3rd_party/eigen/test/rand.cpp
@@ -0,0 +1,118 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+typedef long long int64;
+
+template<typename Scalar> Scalar check_in_range(Scalar x, Scalar y)
+{
+  Scalar r = internal::random<Scalar>(x,y);
+  VERIFY(r>=x);
+  if(y>=x)
+  {
+    VERIFY(r<=y);
+  }
+  return r;
+}
+
+template<typename Scalar> void check_all_in_range(Scalar x, Scalar y)
+{
+  Array<int,1,Dynamic> mask(y-x+1);
+  mask.fill(0);
+  long n = (y-x+1)*32;
+  for(long k=0; k<n; ++k)
+  {
+    mask( check_in_range(x,y)-x )++;
+  }
+  for(Index i=0; i<mask.size(); ++i)
+    if(mask(i)==0)
+      std::cout << "WARNING: value " << x+i << " not reached." << std::endl;
+  VERIFY( (mask>0).all() );
+}
+
+template<typename Scalar> void check_histogram(Scalar x, Scalar y, int bins)
+{
+  Array<int,1,Dynamic> hist(bins);
+  hist.fill(0);
+  int f = 100000;
+  int n = bins*f;
+  int64 range = int64(y)-int64(x);
+  int divisor = int((range+1)/bins);
+  assert(((range+1)%bins)==0);
+  for(int k=0; k<n; ++k)
+  {
+    Scalar r = check_in_range(x,y);
+    hist( int((int64(r)-int64(x))/divisor) )++;
+  }
+  VERIFY( (((hist.cast<double>()/double(f))-1.0).abs()<0.02).all() );
+}
+
+void test_rand()
+{
+  long long_ref = NumTraits<long>::highest()/10;
+  signed char char_offset = (std::min)(g_repeat,64);
+  signed char short_offset = (std::min)(g_repeat,16000);
+
+  for(int i = 0; i < g_repeat*10000; i++) {
+    CALL_SUBTEST(check_in_range<float>(10,11));
+    CALL_SUBTEST(check_in_range<float>(1.24234523,1.24234523));
+    CALL_SUBTEST(check_in_range<float>(-1,1));
+    CALL_SUBTEST(check_in_range<float>(-1432.2352,-1432.2352));
+
+    CALL_SUBTEST(check_in_range<double>(10,11));
+    CALL_SUBTEST(check_in_range<double>(1.24234523,1.24234523));
+    CALL_SUBTEST(check_in_range<double>(-1,1));
+    CALL_SUBTEST(check_in_range<double>(-1432.2352,-1432.2352));
+
+    CALL_SUBTEST(check_in_range<int>(0,-1));
+    CALL_SUBTEST(check_in_range<short>(0,-1));
+    CALL_SUBTEST(check_in_range<long>(0,-1));
+    CALL_SUBTEST(check_in_range<int>(-673456,673456));
+    CALL_SUBTEST(check_in_range<int>(-RAND_MAX+10,RAND_MAX-10));
+    CALL_SUBTEST(check_in_range<short>(-24345,24345));
+    CALL_SUBTEST(check_in_range<long>(-long_ref,long_ref));
+  }
+
+  CALL_SUBTEST(check_all_in_range<signed char>(11,11));
+  CALL_SUBTEST(check_all_in_range<signed char>(11,11+char_offset));
+  CALL_SUBTEST(check_all_in_range<signed char>(-5,5));
+  CALL_SUBTEST(check_all_in_range<signed char>(-11-char_offset,-11));
+  CALL_SUBTEST(check_all_in_range<signed char>(-126,-126+char_offset));
+  CALL_SUBTEST(check_all_in_range<signed char>(126-char_offset,126));
+  CALL_SUBTEST(check_all_in_range<signed char>(-126,126));
+
+  CALL_SUBTEST(check_all_in_range<short>(11,11));
+  CALL_SUBTEST(check_all_in_range<short>(11,11+short_offset));
+  CALL_SUBTEST(check_all_in_range<short>(-5,5));
+  CALL_SUBTEST(check_all_in_range<short>(-11-short_offset,-11));
+  CALL_SUBTEST(check_all_in_range<short>(-24345,-24345+short_offset));
+  CALL_SUBTEST(check_all_in_range<short>(24345,24345+short_offset));
+
+  CALL_SUBTEST(check_all_in_range<int>(11,11));
+  CALL_SUBTEST(check_all_in_range<int>(11,11+g_repeat));
+  CALL_SUBTEST(check_all_in_range<int>(-5,5));
+  CALL_SUBTEST(check_all_in_range<int>(-11-g_repeat,-11));
+  CALL_SUBTEST(check_all_in_range<int>(-673456,-673456+g_repeat));
+  CALL_SUBTEST(check_all_in_range<int>(673456,673456+g_repeat));
+
+  CALL_SUBTEST(check_all_in_range<long>(11,11));
+  CALL_SUBTEST(check_all_in_range<long>(11,11+g_repeat));
+  CALL_SUBTEST(check_all_in_range<long>(-5,5));
+  CALL_SUBTEST(check_all_in_range<long>(-11-g_repeat,-11));
+  CALL_SUBTEST(check_all_in_range<long>(-long_ref,-long_ref+g_repeat));
+  CALL_SUBTEST(check_all_in_range<long>( long_ref, long_ref+g_repeat));
+
+  CALL_SUBTEST(check_histogram<int>(-5,5,11));
+  int bins = 100;
+  CALL_SUBTEST(check_histogram<int>(-3333,-3333+bins*(3333/bins)-1,bins));
+  bins = 1000;
+  CALL_SUBTEST(check_histogram<int>(-RAND_MAX+10,-RAND_MAX+10+bins*(RAND_MAX/bins)-1,bins));
+  CALL_SUBTEST(check_histogram<int>(-RAND_MAX+10,-int64(RAND_MAX)+10+bins*(2*int64(RAND_MAX)/bins)-1,bins));
+}

Index: 3rd_party/eigen/test/real_qz.cpp
==================================================================
--- 3rd_party/eigen/test/real_qz.cpp
+++ 3rd_party/eigen/test/real_qz.cpp
@@ -5,10 +5,11 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#define EIGEN_RUNTIME_NO_MALLOC
 #include "main.h"
 #include <limits>
 #include <Eigen/Eigenvalues>
 
 template<typename MatrixType> void real_qz(const MatrixType& m)
@@ -23,23 +24,52 @@
   Index dim = m.cols();
   
   MatrixType A = MatrixType::Random(dim,dim),
              B = MatrixType::Random(dim,dim);
 
-  RealQZ<MatrixType> qz(A,B);
+
+  // Regression test for bug 985: Randomly set rows or columns to zero
+  Index k=internal::random<Index>(0, dim-1);
+  switch(internal::random<int>(0,10)) {
+  case 0:
+    A.row(k).setZero(); break;
+  case 1:
+    A.col(k).setZero(); break;
+  case 2:
+    B.row(k).setZero(); break;
+  case 3:
+    B.col(k).setZero(); break;
+  default:
+    break;
+  }
+
+  RealQZ<MatrixType> qz(dim);
+  // TODO enable full-prealocation of required memory, this probably requires an in-place mode for HessenbergDecomposition
+  //Eigen::internal::set_is_malloc_allowed(false);
+  qz.compute(A,B);
+  //Eigen::internal::set_is_malloc_allowed(true);
   
   VERIFY_IS_EQUAL(qz.info(), Success);
   // check for zeros
   bool all_zeros = true;
   for (Index i=0; i<A.cols(); i++)
     for (Index j=0; j<i; j++) {
       if (abs(qz.matrixT()(i,j))!=Scalar(0.0))
+      {
+        std::cerr << "Error: T(" << i << "," << j << ") = " << qz.matrixT()(i,j) << std::endl;
         all_zeros = false;
+      }
       if (j<i-1 && abs(qz.matrixS()(i,j))!=Scalar(0.0))
+      {
+        std::cerr << "Error: S(" << i << "," << j << ") = " << qz.matrixS()(i,j) << std::endl;
         all_zeros = false;
+      }
       if (j==i-1 && j>0 && abs(qz.matrixS()(i,j))!=Scalar(0.0) && abs(qz.matrixS()(i-1,j-1))!=Scalar(0.0))
+      {
+        std::cerr << "Error: S(" << i << "," << j << ") = " << qz.matrixS()(i,j)  << " && S(" << i-1 << "," << j-1 << ") = " << qz.matrixS()(i-1,j-1) << std::endl;
         all_zeros = false;
+      }
     }
   VERIFY_IS_EQUAL(all_zeros, true);
   VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixS()*qz.matrixZ(), A);
   VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixT()*qz.matrixZ(), B);
   VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixQ().adjoint(), MatrixType::Identity(dim,dim));

Index: 3rd_party/eigen/test/redux.cpp
==================================================================
--- 3rd_party/eigen/test/redux.cpp
+++ 3rd_party/eigen/test/redux.cpp
@@ -1,13 +1,16 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define TEST_ENABLE_TEMPORARY_TRACKING
 
 #include "main.h"
 
 template<typename MatrixType> void matrixRedux(const MatrixType& m)
 {
@@ -19,11 +22,11 @@
   Index cols = m.cols();
 
   MatrixType m1 = MatrixType::Random(rows, cols);
 
   // The entries of m1 are uniformly distributed in [0,1], so m1.prod() is very small. This may lead to test
-  // failures if we underflow into denormals. Thus, we scale so that entires are close to 1.
+  // failures if we underflow into denormals. Thus, we scale so that entries are close to 1.
   MatrixType m1_for_prod = MatrixType::Ones(rows, cols) + RealScalar(0.2) * m1;
 
   VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
   VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy
   Scalar s(0), p(1), minc(numext::real(m1.coeff(0))), maxc(numext::real(m1.coeff(0)));
@@ -51,14 +54,28 @@
   VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).sum(), m1.block(r0,c0,r1,c1).eval().sum());
   VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).mean(), m1.block(r0,c0,r1,c1).eval().mean());
   VERIFY_IS_APPROX(m1_for_prod.block(r0,c0,r1,c1).prod(), m1_for_prod.block(r0,c0,r1,c1).eval().prod());
   VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).real().minCoeff(), m1.block(r0,c0,r1,c1).real().eval().minCoeff());
   VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).real().maxCoeff(), m1.block(r0,c0,r1,c1).real().eval().maxCoeff());
+
+  // regression for bug 1090
+  const int R1 = MatrixType::RowsAtCompileTime>=2 ? MatrixType::RowsAtCompileTime/2 : 6;
+  const int C1 = MatrixType::ColsAtCompileTime>=2 ? MatrixType::ColsAtCompileTime/2 : 6;
+  if(R1<=rows-r0 && C1<=cols-c0)
+  {
+    VERIFY_IS_APPROX( (m1.template block<R1,C1>(r0,c0).sum()), m1.block(r0,c0,R1,C1).sum() );
+  }
   
   // test empty objects
   VERIFY_IS_APPROX(m1.block(r0,c0,0,0).sum(),   Scalar(0));
   VERIFY_IS_APPROX(m1.block(r0,c0,0,0).prod(),  Scalar(1));
+
+  // test nesting complex expression
+  VERIFY_EVALUATION_COUNT( (m1.matrix()*m1.matrix().transpose()).sum(), (MatrixType::IsVectorAtCompileTime && MatrixType::SizeAtCompileTime!=1 ? 0 : 1) );
+  Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> m2(rows,rows);
+  m2.setRandom();
+  VERIFY_EVALUATION_COUNT( ((m1.matrix()*m1.matrix().transpose())+m2).sum(),(MatrixType::IsVectorAtCompileTime && MatrixType::SizeAtCompileTime!=1 ? 0 : 1));
 }
 
 template<typename VectorType> void vectorRedux(const VectorType& w)
 {
   using std::abs;
@@ -137,12 +154,14 @@
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( matrixRedux(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_1( matrixRedux(Array<float, 1, 1>()) );
     CALL_SUBTEST_2( matrixRedux(Matrix2f()) );
     CALL_SUBTEST_2( matrixRedux(Array2f()) );
+    CALL_SUBTEST_2( matrixRedux(Array22f()) );
     CALL_SUBTEST_3( matrixRedux(Matrix4d()) );
     CALL_SUBTEST_3( matrixRedux(Array4d()) );
+    CALL_SUBTEST_3( matrixRedux(Array44d()) );
     CALL_SUBTEST_4( matrixRedux(MatrixXcf(internal::random<int>(1,maxsize), internal::random<int>(1,maxsize))) );
     CALL_SUBTEST_4( matrixRedux(ArrayXXcf(internal::random<int>(1,maxsize), internal::random<int>(1,maxsize))) );
     CALL_SUBTEST_5( matrixRedux(MatrixXd (internal::random<int>(1,maxsize), internal::random<int>(1,maxsize))) );
     CALL_SUBTEST_5( matrixRedux(ArrayXXd (internal::random<int>(1,maxsize), internal::random<int>(1,maxsize))) );
     CALL_SUBTEST_6( matrixRedux(MatrixXi (internal::random<int>(1,maxsize), internal::random<int>(1,maxsize))) );

Index: 3rd_party/eigen/test/ref.cpp
==================================================================
--- 3rd_party/eigen/test/ref.cpp
+++ 3rd_party/eigen/test/ref.cpp
@@ -10,31 +10,27 @@
 // This unit test cannot be easily written to work with EIGEN_DEFAULT_TO_ROW_MAJOR
 #ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
 #undef EIGEN_DEFAULT_TO_ROW_MAJOR
 #endif
 
-static int nb_temporaries;
-
-inline void on_temporary_creation(int) {
-  // here's a great place to set a breakpoint when debugging failures in this test!
-  nb_temporaries++;
-}
-  
-
-#define EIGEN_DENSE_STORAGE_CTOR_PLUGIN { on_temporary_creation(size); }
+#define TEST_ENABLE_TEMPORARY_TRACKING
 
 #include "main.h"
-
-#define VERIFY_EVALUATION_COUNT(XPR,N) {\
-    nb_temporaries = 0; \
-    XPR; \
-    if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
-    VERIFY( (#XPR) && nb_temporaries==N ); \
-  }
-
 
 // test Ref.h
+
+// Deal with i387 extended precision
+#if EIGEN_ARCH_i386 && !(EIGEN_ARCH_x86_64)
+
+#if EIGEN_COMP_GNUC_STRICT && EIGEN_GNUC_AT_LEAST(4,4)
+#pragma GCC optimize ("-ffloat-store")
+#else
+#undef VERIFY_IS_EQUAL
+#define VERIFY_IS_EQUAL(X,Y) VERIFY_IS_APPROX(X,Y)
+#endif
+
+#endif
 
 template<typename MatrixType> void ref_matrix(const MatrixType& m)
 {
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
@@ -68,11 +64,10 @@
   VERIFY_IS_EQUAL(m1, m2);
   
   m2.block(i,j,brows,bcols).setRandom();
   rm2 = m2.block(i,j,brows,bcols);
   VERIFY_IS_EQUAL(m1, m2);
-  
   
   ConstRefDynMat rm3 = m1.block(i,j,brows,bcols);
   m1.block(i,j,brows,bcols) *= 2;
   m2.block(i,j,brows,bcols) *= 2;
   VERIFY_IS_EQUAL(rm3, m2.block(i,j,brows,bcols));
@@ -226,10 +221,41 @@
   VERIFY_EVALUATION_COUNT( call_ref_6(A.transpose(),A.transpose()), 1);      // evaluated into a temp because the storage orders do not match
   VERIFY_EVALUATION_COUNT( call_ref_6(A.block(1,1,2,2),A.block(1,1,2,2)), 0);
   
   VERIFY_EVALUATION_COUNT( call_ref_7(c,c), 0);
 }
+
+typedef Matrix<double,Dynamic,Dynamic,RowMajor> RowMatrixXd;
+int test_ref_overload_fun1(Ref<MatrixXd> )       { return 1; }
+int test_ref_overload_fun1(Ref<RowMatrixXd> )    { return 2; }
+int test_ref_overload_fun1(Ref<MatrixXf> )       { return 3; }
+
+int test_ref_overload_fun2(Ref<const MatrixXd> ) { return 4; }
+int test_ref_overload_fun2(Ref<const MatrixXf> ) { return 5; }
+
+void test_ref_ambiguous(const Ref<const ArrayXd> &A, Ref<ArrayXd> B)
+{
+  B = A;
+  B = A - A;
+}
+
+// See also bug 969
+void test_ref_overloads()
+{
+  MatrixXd Ad, Bd;
+  RowMatrixXd rAd, rBd;
+  VERIFY( test_ref_overload_fun1(Ad)==1 );
+  VERIFY( test_ref_overload_fun1(rAd)==2 );
+  
+  MatrixXf Af, Bf;
+  VERIFY( test_ref_overload_fun2(Ad)==4 );
+  VERIFY( test_ref_overload_fun2(Ad+Bd)==4 );
+  VERIFY( test_ref_overload_fun2(Af+Bf)==5 );
+  
+  ArrayXd A, B;
+  test_ref_ambiguous(A, B);
+}
 
 void test_ref()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( ref_vector(Matrix<float, 1, 1>()) );
@@ -247,6 +273,8 @@
     CALL_SUBTEST_4( ref_matrix(MatrixXcf(internal::random<int>(1,10),internal::random<int>(1,10))) );
     CALL_SUBTEST_4( ref_matrix(Matrix<std::complex<double>,10,15>()) );
     CALL_SUBTEST_5( ref_matrix(MatrixXi(internal::random<int>(1,10),internal::random<int>(1,10))) );
     CALL_SUBTEST_6( call_ref() );
   }
+  
+  CALL_SUBTEST_7( test_ref_overloads() );
 }

DELETED 3rd_party/eigen/test/runtest.sh
Index: 3rd_party/eigen/test/runtest.sh
==================================================================
--- 3rd_party/eigen/test/runtest.sh
+++ 3rd_party/eigen/test/runtest.sh
@@ -1,20 +0,0 @@
-#!/bin/bash
-
-black='\E[30m'
-red='\E[31m'
-green='\E[32m'
-yellow='\E[33m'
-blue='\E[34m'
-magenta='\E[35m'
-cyan='\E[36m'
-white='\E[37m'
-
-if ! ./$1 > /dev/null 2> .runtest.log ; then
-  echo -e  $red Test $1 failed: $black
-  echo -e $blue
-  cat .runtest.log
-  echo -e $black
-  exit 1
-else
-echo -e $green Test $1 passed$black
-fi

ADDED   3rd_party/eigen/test/rvalue_types.cpp
Index: 3rd_party/eigen/test/rvalue_types.cpp
==================================================================
--- 3rd_party/eigen/test/rvalue_types.cpp
+++ 3rd_party/eigen/test/rvalue_types.cpp
@@ -0,0 +1,64 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Hauke Heibel <hauke.heibel@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/Core>
+
+using internal::UIntPtr;
+
+#if EIGEN_HAS_RVALUE_REFERENCES
+template <typename MatrixType>
+void rvalue_copyassign(const MatrixType& m)
+{
+
+  typedef typename internal::traits<MatrixType>::Scalar Scalar;
+  
+  // create a temporary which we are about to destroy by moving
+  MatrixType tmp = m;
+  UIntPtr src_address = reinterpret_cast<UIntPtr>(tmp.data());
+  
+  // move the temporary to n
+  MatrixType n = std::move(tmp);
+  UIntPtr dst_address = reinterpret_cast<UIntPtr>(n.data());
+
+  if (MatrixType::RowsAtCompileTime==Dynamic|| MatrixType::ColsAtCompileTime==Dynamic)
+  {
+    // verify that we actually moved the guts
+    VERIFY_IS_EQUAL(src_address, dst_address);
+  }
+
+  // verify that the content did not change
+  Scalar abs_diff = (m-n).array().abs().sum();
+  VERIFY_IS_EQUAL(abs_diff, Scalar(0));
+}
+#else
+template <typename MatrixType>
+void rvalue_copyassign(const MatrixType&) {}
+#endif
+
+void test_rvalue_types()
+{
+  CALL_SUBTEST_1(rvalue_copyassign( MatrixXf::Random(50,50).eval() ));
+  CALL_SUBTEST_1(rvalue_copyassign( ArrayXXf::Random(50,50).eval() ));
+
+  CALL_SUBTEST_1(rvalue_copyassign( Matrix<float,1,Dynamic>::Random(50).eval() ));
+  CALL_SUBTEST_1(rvalue_copyassign( Array<float,1,Dynamic>::Random(50).eval() ));
+
+  CALL_SUBTEST_1(rvalue_copyassign( Matrix<float,Dynamic,1>::Random(50).eval() ));
+  CALL_SUBTEST_1(rvalue_copyassign( Array<float,Dynamic,1>::Random(50).eval() ));
+  
+  CALL_SUBTEST_2(rvalue_copyassign( Array<float,2,1>::Random().eval() ));
+  CALL_SUBTEST_2(rvalue_copyassign( Array<float,3,1>::Random().eval() ));
+  CALL_SUBTEST_2(rvalue_copyassign( Array<float,4,1>::Random().eval() ));
+
+  CALL_SUBTEST_2(rvalue_copyassign( Array<float,2,2>::Random().eval() ));
+  CALL_SUBTEST_2(rvalue_copyassign( Array<float,3,3>::Random().eval() ));
+  CALL_SUBTEST_2(rvalue_copyassign( Array<float,4,4>::Random().eval() ));
+}

Index: 3rd_party/eigen/test/schur_complex.cpp
==================================================================
--- 3rd_party/eigen/test/schur_complex.cpp
+++ 3rd_party/eigen/test/schur_complex.cpp
@@ -23,11 +23,11 @@
     VERIFY_IS_EQUAL(schurOfA.info(), Success);
     ComplexMatrixType U = schurOfA.matrixU();
     ComplexMatrixType T = schurOfA.matrixT();
     for(int row = 1; row < size; ++row) {
       for(int col = 0; col < row; ++col) {
-	VERIFY(T(row,col) == (typename MatrixType::Scalar)0);
+        VERIFY(T(row,col) == (typename MatrixType::Scalar)0);
       }
     }
     VERIFY_IS_APPROX(A.template cast<ComplexScalar>(), U * T * U.adjoint());
   }
 
@@ -68,11 +68,11 @@
   ComplexSchur<MatrixType> csOnlyT(A, false);
   VERIFY_IS_EQUAL(csOnlyT.info(), Success);
   VERIFY_IS_EQUAL(cs1.matrixT(), csOnlyT.matrixT());
   VERIFY_RAISES_ASSERT(csOnlyT.matrixU());
 
-  if (size > 1)
+  if (size > 1 && size < 20)
   {
     // Test matrix with NaN
     A(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
     ComplexSchur<MatrixType> csNaN(A);
     VERIFY_IS_EQUAL(csNaN.info(), NoConvergence);

Index: 3rd_party/eigen/test/schur_real.cpp
==================================================================
--- 3rd_party/eigen/test/schur_real.cpp
+++ 3rd_party/eigen/test/schur_real.cpp
@@ -80,20 +80,20 @@
 
   MatrixType Atriangular = A;
   Atriangular.template triangularView<StrictlyLower>().setZero(); 
   rs3.setMaxIterations(1).compute(Atriangular); // triangular matrices do not need any iterations
   VERIFY_IS_EQUAL(rs3.info(), Success);
-  VERIFY_IS_EQUAL(rs3.matrixT(), Atriangular);
+  VERIFY_IS_APPROX(rs3.matrixT(), Atriangular); // approx because of scaling...
   VERIFY_IS_EQUAL(rs3.matrixU(), MatrixType::Identity(size, size));
 
   // Test computation of only T, not U
   RealSchur<MatrixType> rsOnlyT(A, false);
   VERIFY_IS_EQUAL(rsOnlyT.info(), Success);
   VERIFY_IS_EQUAL(rs1.matrixT(), rsOnlyT.matrixT());
   VERIFY_RAISES_ASSERT(rsOnlyT.matrixU());
 
-  if (size > 2)
+  if (size > 2 && size < 20)
   {
     // Test matrix with NaN
     A(0,0) = std::numeric_limits<typename MatrixType::Scalar>::quiet_NaN();
     RealSchur<MatrixType> rsNaN(A);
     VERIFY_IS_EQUAL(rsNaN.info(), NoConvergence);

Index: 3rd_party/eigen/test/selfadjoint.cpp
==================================================================
--- 3rd_party/eigen/test/selfadjoint.cpp
+++ 3rd_party/eigen/test/selfadjoint.cpp
@@ -19,23 +19,34 @@
 
   Index rows = m.rows();
   Index cols = m.cols();
 
   MatrixType m1 = MatrixType::Random(rows, cols),
-             m3(rows, cols);
+             m2 = MatrixType::Random(rows, cols),
+             m3(rows, cols),
+             m4(rows, cols);
 
   m1.diagonal() = m1.diagonal().real().template cast<Scalar>();
 
   // check selfadjoint to dense
   m3 = m1.template selfadjointView<Upper>();
   VERIFY_IS_APPROX(MatrixType(m3.template triangularView<Upper>()), MatrixType(m1.template triangularView<Upper>()));
   VERIFY_IS_APPROX(m3, m3.adjoint());
 
-
   m3 = m1.template selfadjointView<Lower>();
   VERIFY_IS_APPROX(MatrixType(m3.template triangularView<Lower>()), MatrixType(m1.template triangularView<Lower>()));
   VERIFY_IS_APPROX(m3, m3.adjoint());
+
+  m3 = m1.template selfadjointView<Upper>();
+  m4 = m2;
+  m4 += m1.template selfadjointView<Upper>();
+  VERIFY_IS_APPROX(m4, m2+m3);
+
+  m3 = m1.template selfadjointView<Lower>();
+  m4 = m2;
+  m4 -= m1.template selfadjointView<Lower>();
+  VERIFY_IS_APPROX(m4, m2-m3);
 }
 
 void bug_159()
 {
   Matrix3d m = Matrix3d::Random().selfadjointView<Lower>();

Index: 3rd_party/eigen/test/simplicial_cholesky.cpp
==================================================================
--- 3rd_party/eigen/test/simplicial_cholesky.cpp
+++ 3rd_party/eigen/test/simplicial_cholesky.cpp
@@ -7,20 +7,21 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "sparse_solver.h"
 
-template<typename T> void test_simplicial_cholesky_T()
-{
-  SimplicialCholesky<SparseMatrix<T>, Lower> chol_colmajor_lower_amd;
-  SimplicialCholesky<SparseMatrix<T>, Upper> chol_colmajor_upper_amd;
-  SimplicialLLT<SparseMatrix<T>, Lower> llt_colmajor_lower_amd;
-  SimplicialLLT<SparseMatrix<T>, Upper> llt_colmajor_upper_amd;
-  SimplicialLDLT<SparseMatrix<T>, Lower> ldlt_colmajor_lower_amd;
-  SimplicialLDLT<SparseMatrix<T>, Upper> ldlt_colmajor_upper_amd;
-  SimplicialLDLT<SparseMatrix<T>, Lower, NaturalOrdering<int> > ldlt_colmajor_lower_nat;
-  SimplicialLDLT<SparseMatrix<T>, Upper, NaturalOrdering<int> > ldlt_colmajor_upper_nat;
+template<typename T, typename I> void test_simplicial_cholesky_T()
+{
+  typedef SparseMatrix<T,0,I> SparseMatrixType;
+  SimplicialCholesky<SparseMatrixType, Lower> chol_colmajor_lower_amd;
+  SimplicialCholesky<SparseMatrixType, Upper> chol_colmajor_upper_amd;
+  SimplicialLLT<     SparseMatrixType, Lower> llt_colmajor_lower_amd;
+  SimplicialLLT<     SparseMatrixType, Upper> llt_colmajor_upper_amd;
+  SimplicialLDLT<    SparseMatrixType, Lower> ldlt_colmajor_lower_amd;
+  SimplicialLDLT<    SparseMatrixType, Upper> ldlt_colmajor_upper_amd;
+  SimplicialLDLT<    SparseMatrixType, Lower, NaturalOrdering<I> > ldlt_colmajor_lower_nat;
+  SimplicialLDLT<    SparseMatrixType, Upper, NaturalOrdering<I> > ldlt_colmajor_upper_nat;
 
   check_sparse_spd_solving(chol_colmajor_lower_amd);
   check_sparse_spd_solving(chol_colmajor_upper_amd);
   check_sparse_spd_solving(llt_colmajor_lower_amd);
   check_sparse_spd_solving(llt_colmajor_upper_amd);
@@ -32,14 +33,15 @@
   check_sparse_spd_determinant(llt_colmajor_lower_amd);
   check_sparse_spd_determinant(llt_colmajor_upper_amd);
   check_sparse_spd_determinant(ldlt_colmajor_lower_amd);
   check_sparse_spd_determinant(ldlt_colmajor_upper_amd);
   
-  check_sparse_spd_solving(ldlt_colmajor_lower_nat);
-  check_sparse_spd_solving(ldlt_colmajor_upper_nat);
+  check_sparse_spd_solving(ldlt_colmajor_lower_nat, 300, 1000);
+  check_sparse_spd_solving(ldlt_colmajor_upper_nat, 300, 1000);
 }
 
 void test_simplicial_cholesky()
 {
-  CALL_SUBTEST_1(test_simplicial_cholesky_T<double>());
-  CALL_SUBTEST_2(test_simplicial_cholesky_T<std::complex<double> >());
+  CALL_SUBTEST_1(( test_simplicial_cholesky_T<double,int>() ));
+  CALL_SUBTEST_2(( test_simplicial_cholesky_T<std::complex<double>, int>() ));
+  CALL_SUBTEST_3(( test_simplicial_cholesky_T<double,long int>() ));
 }

Index: 3rd_party/eigen/test/sizeof.cpp
==================================================================
--- 3rd_party/eigen/test/sizeof.cpp
+++ 3rd_party/eigen/test/sizeof.cpp
@@ -11,18 +11,31 @@
 
 template<typename MatrixType> void verifySizeOf(const MatrixType&)
 {
   typedef typename MatrixType::Scalar Scalar;
   if (MatrixType::RowsAtCompileTime!=Dynamic && MatrixType::ColsAtCompileTime!=Dynamic)
-    VERIFY(std::ptrdiff_t(sizeof(MatrixType))==std::ptrdiff_t(sizeof(Scalar))*std::ptrdiff_t(MatrixType::SizeAtCompileTime));
+    VERIFY_IS_EQUAL(std::ptrdiff_t(sizeof(MatrixType)),std::ptrdiff_t(sizeof(Scalar))*std::ptrdiff_t(MatrixType::SizeAtCompileTime));
   else
-    VERIFY(sizeof(MatrixType)==sizeof(Scalar*) + 2 * sizeof(typename MatrixType::Index));
+    VERIFY_IS_EQUAL(sizeof(MatrixType),sizeof(Scalar*) + 2 * sizeof(typename MatrixType::Index));
 }
 
 void test_sizeof()
 {
   CALL_SUBTEST(verifySizeOf(Matrix<float, 1, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 2, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 3, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 4, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 5, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 6, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 7, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 8, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 9, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 10, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 11, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Array<float, 12, 1>()) );
+  CALL_SUBTEST(verifySizeOf(Vector2d()) );
+  CALL_SUBTEST(verifySizeOf(Vector4f()) );
   CALL_SUBTEST(verifySizeOf(Matrix4d()) );
   CALL_SUBTEST(verifySizeOf(Matrix<double, 4, 2>()) );
   CALL_SUBTEST(verifySizeOf(Matrix<bool, 7, 5>()) );
   CALL_SUBTEST(verifySizeOf(MatrixXcf(3, 3)) );
   CALL_SUBTEST(verifySizeOf(MatrixXi(8, 12)) );

Index: 3rd_party/eigen/test/sizeoverflow.cpp
==================================================================
--- 3rd_party/eigen/test/sizeoverflow.cpp
+++ 3rd_party/eigen/test/sizeoverflow.cpp
@@ -16,12 +16,10 @@
     }                                                         \
     catch (std::bad_alloc&) { threw = true; }                 \
     VERIFY(threw && "should have thrown bad_alloc: " #a);     \
   }
 
-typedef DenseIndex Index;
-
 template<typename MatrixType>
 void triggerMatrixBadAlloc(Index rows, Index cols)
 {
   VERIFY_THROWS_BADALLOC( MatrixType m(rows, cols) );
   VERIFY_THROWS_BADALLOC( MatrixType m; m.resize(rows, cols) );

Index: 3rd_party/eigen/test/sparse.h
==================================================================
--- 3rd_party/eigen/test/sparse.h
+++ 3rd_party/eigen/test/sparse.h
@@ -51,36 +51,39 @@
  * \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular
  *        allowing to control the shape of the matrix.
  * \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
  *        and zero coefficients respectively.
  */
-template<typename Scalar,int Opt1,int Opt2,typename Index> void
+template<typename Scalar,int Opt1,int Opt2,typename StorageIndex> void
 initSparse(double density,
            Matrix<Scalar,Dynamic,Dynamic,Opt1>& refMat,
-           SparseMatrix<Scalar,Opt2,Index>& sparseMat,
+           SparseMatrix<Scalar,Opt2,StorageIndex>& sparseMat,
            int flags = 0,
-           std::vector<Matrix<Index,2,1> >* zeroCoords = 0,
-           std::vector<Matrix<Index,2,1> >* nonzeroCoords = 0)
+           std::vector<Matrix<StorageIndex,2,1> >* zeroCoords = 0,
+           std::vector<Matrix<StorageIndex,2,1> >* nonzeroCoords = 0)
 {
-  enum { IsRowMajor = SparseMatrix<Scalar,Opt2,Index>::IsRowMajor };
+  enum { IsRowMajor = SparseMatrix<Scalar,Opt2,StorageIndex>::IsRowMajor };
   sparseMat.setZero();
   //sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
   sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), int((1.5*density)*(IsRowMajor?refMat.cols():refMat.rows()))));
   
   for(Index j=0; j<sparseMat.outerSize(); j++)
   {
     //sparseMat.startVec(j);
     for(Index i=0; i<sparseMat.innerSize(); i++)
     {
-      int ai(i), aj(j);
+      Index ai(i), aj(j);
       if(IsRowMajor)
         std::swap(ai,aj);
       Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
       if ((flags&ForceNonZeroDiag) && (i==j))
       {
+        // FIXME: the following is too conservative
         v = internal::random<Scalar>()*Scalar(3.);
-        v = v*v + Scalar(5.);
+        v = v*v;
+        if(numext::real(v)>0) v += Scalar(5);
+        else                  v -= Scalar(5);
       }
       if ((flags & MakeLowerTriangular) && aj>ai)
         v = Scalar(0);
       else if ((flags & MakeUpperTriangular) && aj<ai)
         v = Scalar(0);
@@ -91,15 +94,15 @@
       if (v!=Scalar(0))
       {
         //sparseMat.insertBackByOuterInner(j,i) = v;
         sparseMat.insertByOuterInner(j,i) = v;
         if (nonzeroCoords)
-          nonzeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
+          nonzeroCoords->push_back(Matrix<StorageIndex,2,1> (ai,aj));
       }
       else if (zeroCoords)
       {
-        zeroCoords->push_back(Matrix<Index,2,1> (ai,aj));
+        zeroCoords->push_back(Matrix<StorageIndex,2,1> (ai,aj));
       }
       refMat(ai,aj) = v;
     }
   }
   //sparseMat.finalize();
@@ -161,11 +164,11 @@
            std::vector<int>* zeroCoords = 0,
            std::vector<int>* nonzeroCoords = 0)
 {
   sparseVec.reserve(int(refVec.size()*density));
   sparseVec.setZero();
-  for(Index i=0; i<refVec.size(); i++)
+  for(int i=0; i<refVec.size(); i++)
   {
     Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
     if (v!=Scalar(0))
     {
       sparseVec.insertBack(i) = v;

Index: 3rd_party/eigen/test/sparse_basic.cpp
==================================================================
--- 3rd_party/eigen/test/sparse_basic.cpp
+++ 3rd_party/eigen/test/sparse_basic.cpp
@@ -7,20 +7,27 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+static long g_realloc_count = 0;
+#define EIGEN_SPARSE_COMPRESSED_STORAGE_REALLOCATE_PLUGIN g_realloc_count++;
+
 #include "sparse.h"
 
 template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
 {
-  typedef typename SparseMatrixType::Index Index;
-  typedef Matrix<Index,2,1> Vector2;
+  typedef typename SparseMatrixType::StorageIndex StorageIndex;
+  typedef Matrix<StorageIndex,2,1> Vector2;
   
   const Index rows = ref.rows();
   const Index cols = ref.cols();
+  //const Index inner = ref.innerSize();
+  //const Index outer = ref.outerSize();
+
   typedef typename SparseMatrixType::Scalar Scalar;
+  typedef typename SparseMatrixType::RealScalar RealScalar;
   enum { Flags = SparseMatrixType::Flags };
 
   double density = (std::max)(8./(rows*cols), 0.01);
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
   typedef Matrix<Scalar,Dynamic,1> DenseVector;
@@ -34,67 +41,26 @@
 
     std::vector<Vector2> zeroCoords;
     std::vector<Vector2> nonzeroCoords;
     initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
 
-    if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
-      return;
-
     // test coeff and coeffRef
-    for (int i=0; i<(int)zeroCoords.size(); ++i)
+    for (std::size_t i=0; i<zeroCoords.size(); ++i)
     {
       VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
       if(internal::is_same<SparseMatrixType,SparseMatrix<Scalar,Flags> >::value)
-        VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
-    }
-    VERIFY_IS_APPROX(m, refMat);
-
-    m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
-    refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
-
-    VERIFY_IS_APPROX(m, refMat);
-      /*
-      // test InnerIterators and Block expressions
-      for (int t=0; t<10; ++t)
-      {
-        int j = internal::random<int>(0,cols-1);
-        int i = internal::random<int>(0,rows-1);
-        int w = internal::random<int>(1,cols-j-1);
-        int h = internal::random<int>(1,rows-i-1);
-
-    //     VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
-        for(int c=0; c<w; c++)
-        {
-          VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
-          for(int r=0; r<h; r++)
-          {
-    //         VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
-          }
-        }
-    //     for(int r=0; r<h; r++)
-    //     {
-    //       VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
-    //       for(int c=0; c<w; c++)
-    //       {
-    //         VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
-    //       }
-    //     }
-      }
-
-      for(int c=0; c<cols; c++)
-      {
-        VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c));
-        VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c));
-      }
-
-      for(int r=0; r<rows; r++)
-      {
-        VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
-        VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
-      }
-      */
-      
+        VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[i].x(),zeroCoords[i].y()) = 5 );
+    }
+    VERIFY_IS_APPROX(m, refMat);
+
+    if(!nonzeroCoords.empty()) {
+      m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
+      refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
+    }
+
+    VERIFY_IS_APPROX(m, refMat);
+
       // test assertion
       VERIFY_RAISES_ASSERT( m.coeffRef(-1,1) = 0 );
       VERIFY_RAISES_ASSERT( m.coeffRef(0,m.cols()) = 0 );
     }
 
@@ -101,21 +67,35 @@
     // test insert (inner random)
     {
       DenseMatrix m1(rows,cols);
       m1.setZero();
       SparseMatrixType m2(rows,cols);
-      if(internal::random<int>()%2)
-        m2.reserve(VectorXi::Constant(m2.outerSize(), 2));
+      bool call_reserve = internal::random<int>()%2;
+      Index nnz = internal::random<int>(1,int(rows)/2);
+      if(call_reserve)
+      {
+        if(internal::random<int>()%2)
+          m2.reserve(VectorXi::Constant(m2.outerSize(), int(nnz)));
+        else
+          m2.reserve(m2.outerSize() * nnz);
+      }
+      g_realloc_count = 0;
       for (Index j=0; j<cols; ++j)
       {
-        for (Index k=0; k<rows/2; ++k)
+        for (Index k=0; k<nnz; ++k)
         {
           Index i = internal::random<Index>(0,rows-1);
           if (m1.coeff(i,j)==Scalar(0))
             m2.insert(i,j) = m1(i,j) = internal::random<Scalar>();
         }
       }
+      
+      if(call_reserve && !SparseMatrixType::IsRowMajor)
+      {
+        VERIFY(g_realloc_count==0);
+      }
+      
       m2.finalize();
       VERIFY_IS_APPROX(m2,m1);
     }
 
     // test insert (fully random)
@@ -145,13 +125,13 @@
     for(int mode=0;mode<4;++mode)
     {
       DenseMatrix m1(rows,cols);
       m1.setZero();
       SparseMatrixType m2(rows,cols);
-      VectorXi r(VectorXi::Constant(m2.outerSize(), ((mode%2)==0) ? m2.innerSize() : std::max<int>(1,m2.innerSize()/8)));
+      VectorXi r(VectorXi::Constant(m2.outerSize(), ((mode%2)==0) ? int(m2.innerSize()) : std::max<int>(1,int(m2.innerSize())/8)));
       m2.reserve(r);
-      for (int k=0; k<rows*cols; ++k)
+      for (Index k=0; k<rows*cols; ++k)
       {
         Index i = internal::random<Index>(0,rows-1);
         Index j = internal::random<Index>(0,cols-1);
         if (m1.coeff(i,j)==Scalar(0))
           m2.insert(i,j) = m1(i,j) = internal::random<Scalar>();
@@ -161,265 +141,323 @@
       if(internal::random<int>()%2)
         m2.makeCompressed();
       VERIFY_IS_APPROX(m2,m1);
     }
 
-  // test innerVector()
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    Index j0 = internal::random<Index>(0,rows-1);
-    Index j1 = internal::random<Index>(0,rows-1);
-    if(SparseMatrixType::IsRowMajor)
-      VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.row(j0));
-    else
-      VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0));
-
-    if(SparseMatrixType::IsRowMajor)
-      VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.row(j0)+refMat2.row(j1));
-    else
-      VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1));
-
-    SparseMatrixType m3(rows,rows);
-    m3.reserve(VectorXi::Constant(rows,rows/2));
-    for(Index j=0; j<rows; ++j)
-      for(Index k=0; k<j; ++k)
-        m3.insertByOuterInner(j,k) = k+1;
-    for(Index j=0; j<rows; ++j)
-    {
-      VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
-      if(j>0)
-        VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
-    }
-    m3.makeCompressed();
-    for(Index j=0; j<rows; ++j)
-    {
-      VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
-      if(j>0)
-        VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
-    }
-
-    //m2.innerVector(j0) = 2*m2.innerVector(j1);
-    //refMat2.col(j0) = 2*refMat2.col(j1);
-    //VERIFY_IS_APPROX(m2, refMat2);
-  }
-
-  // test innerVectors()
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    if(internal::random<float>(0,1)>0.5) m2.makeCompressed();
-    
-    Index j0 = internal::random<Index>(0,rows-2);
-    Index j1 = internal::random<Index>(0,rows-2);
-    Index n0 = internal::random<Index>(1,rows-(std::max)(j0,j1));
-    if(SparseMatrixType::IsRowMajor)
-      VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(j0,0,n0,cols));
-    else
-      VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0));
-    if(SparseMatrixType::IsRowMajor)
-      VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
-                       refMat2.middleRows(j0,n0)+refMat2.middleRows(j1,n0));
-    else
-      VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
-                      refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
-    
-    VERIFY_IS_APPROX(m2, refMat2);
-    
-    m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0);
-    if(SparseMatrixType::IsRowMajor)
-      refMat2.middleRows(j0,n0) = (refMat2.middleRows(j0,n0) + refMat2.middleRows(j1,n0)).eval();
-    else
-      refMat2.middleCols(j0,n0) = (refMat2.middleCols(j0,n0) + refMat2.middleCols(j1,n0)).eval();
-    
-    VERIFY_IS_APPROX(m2, refMat2);
-    
-  }
-  
   // test basic computations
   {
-    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM4 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m1(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    SparseMatrixType m3(rows, rows);
-    SparseMatrixType m4(rows, rows);
+    DenseMatrix refM1 = DenseMatrix::Zero(rows, cols);
+    DenseMatrix refM2 = DenseMatrix::Zero(rows, cols);
+    DenseMatrix refM3 = DenseMatrix::Zero(rows, cols);
+    DenseMatrix refM4 = DenseMatrix::Zero(rows, cols);
+    SparseMatrixType m1(rows, cols);
+    SparseMatrixType m2(rows, cols);
+    SparseMatrixType m3(rows, cols);
+    SparseMatrixType m4(rows, cols);
     initSparse<Scalar>(density, refM1, m1);
     initSparse<Scalar>(density, refM2, m2);
     initSparse<Scalar>(density, refM3, m3);
     initSparse<Scalar>(density, refM4, m4);
 
+    if(internal::random<bool>())
+      m1.makeCompressed();
+
+    Index m1_nnz = m1.nonZeros();
+
+    VERIFY_IS_APPROX(m1*s1, refM1*s1);
     VERIFY_IS_APPROX(m1+m2, refM1+refM2);
     VERIFY_IS_APPROX(m1+m2+m3, refM1+refM2+refM3);
     VERIFY_IS_APPROX(m3.cwiseProduct(m1+m2), refM3.cwiseProduct(refM1+refM2));
     VERIFY_IS_APPROX(m1*s1-m2, refM1*s1-refM2);
-
-    VERIFY_IS_APPROX(m1*=s1, refM1*=s1);
-    VERIFY_IS_APPROX(m1/=s1, refM1/=s1);
-
-    VERIFY_IS_APPROX(m1+=m2, refM1+=refM2);
-    VERIFY_IS_APPROX(m1-=m2, refM1-=refM2);
+    VERIFY_IS_APPROX(m4=m1/s1, refM1/s1);
+    VERIFY_IS_EQUAL(m4.nonZeros(), m1_nnz);
 
     if(SparseMatrixType::IsRowMajor)
       VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.row(0).dot(refM2.row(0)));
     else
-      VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.col(0).dot(refM2.row(0)));
+      VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.col(0)), refM1.col(0).dot(refM2.col(0)));
+
+    DenseVector rv = DenseVector::Random(m1.cols());
+    DenseVector cv = DenseVector::Random(m1.rows());
+    Index r = internal::random<Index>(0,m1.rows()-2);
+    Index c = internal::random<Index>(0,m1.cols()-1);
+    VERIFY_IS_APPROX(( m1.template block<1,Dynamic>(r,0,1,m1.cols()).dot(rv)) , refM1.row(r).dot(rv));
+    VERIFY_IS_APPROX(m1.row(r).dot(rv), refM1.row(r).dot(rv));
+    VERIFY_IS_APPROX(m1.col(c).dot(cv), refM1.col(c).dot(cv));
 
     VERIFY_IS_APPROX(m1.conjugate(), refM1.conjugate());
     VERIFY_IS_APPROX(m1.real(), refM1.real());
 
     refM4.setRandom();
     // sparse cwise* dense
     VERIFY_IS_APPROX(m3.cwiseProduct(refM4), refM3.cwiseProduct(refM4));
+    // dense cwise* sparse
+    VERIFY_IS_APPROX(refM4.cwiseProduct(m3), refM4.cwiseProduct(refM3));
 //     VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
+
+    VERIFY_IS_APPROX(refM4 + m3, refM4 + refM3);
+    VERIFY_IS_APPROX(m3 + refM4, refM3 + refM4);
+    VERIFY_IS_APPROX(refM4 - m3, refM4 - refM3);
+    VERIFY_IS_APPROX(m3 - refM4, refM3 - refM4);
+    VERIFY_IS_APPROX((RealScalar(0.5)*refM4 + RealScalar(0.5)*m3).eval(), RealScalar(0.5)*refM4 + RealScalar(0.5)*refM3);
+    VERIFY_IS_APPROX((RealScalar(0.5)*refM4 + m3*RealScalar(0.5)).eval(), RealScalar(0.5)*refM4 + RealScalar(0.5)*refM3);
+    VERIFY_IS_APPROX((RealScalar(0.5)*refM4 + m3.cwiseProduct(m3)).eval(), RealScalar(0.5)*refM4 + refM3.cwiseProduct(refM3));
+
+    VERIFY_IS_APPROX((RealScalar(0.5)*refM4 + RealScalar(0.5)*m3).eval(), RealScalar(0.5)*refM4 + RealScalar(0.5)*refM3);
+    VERIFY_IS_APPROX((RealScalar(0.5)*refM4 + m3*RealScalar(0.5)).eval(), RealScalar(0.5)*refM4 + RealScalar(0.5)*refM3);
+    VERIFY_IS_APPROX((RealScalar(0.5)*refM4 + (m3+m3)).eval(), RealScalar(0.5)*refM4 + (refM3+refM3));
+    VERIFY_IS_APPROX(((refM3+m3)+RealScalar(0.5)*m3).eval(), RealScalar(0.5)*refM3 + (refM3+refM3));
+    VERIFY_IS_APPROX((RealScalar(0.5)*refM4 + (refM3+m3)).eval(), RealScalar(0.5)*refM4 + (refM3+refM3));
+    VERIFY_IS_APPROX((RealScalar(0.5)*refM4 + (m3+refM3)).eval(), RealScalar(0.5)*refM4 + (refM3+refM3));
+
+
+    VERIFY_IS_APPROX(m1.sum(), refM1.sum());
+
+    m4 = m1; refM4 = m4;
+
+    VERIFY_IS_APPROX(m1*=s1, refM1*=s1);
+    VERIFY_IS_EQUAL(m1.nonZeros(), m1_nnz);
+    VERIFY_IS_APPROX(m1/=s1, refM1/=s1);
+    VERIFY_IS_EQUAL(m1.nonZeros(), m1_nnz);
+
+    VERIFY_IS_APPROX(m1+=m2, refM1+=refM2);
+    VERIFY_IS_APPROX(m1-=m2, refM1-=refM2);
+
+    if (rows>=2 && cols>=2)
+    {
+      VERIFY_RAISES_ASSERT( m1 += m1.innerVector(0) );
+      VERIFY_RAISES_ASSERT( m1 -= m1.innerVector(0) );
+      VERIFY_RAISES_ASSERT( refM1 -= m1.innerVector(0) );
+      VERIFY_RAISES_ASSERT( refM1 += m1.innerVector(0) );
+      m1 = m4; refM1 = refM4;
+    }
 
     // test aliasing
     VERIFY_IS_APPROX((m1 = -m1), (refM1 = -refM1));
+    VERIFY_IS_EQUAL(m1.nonZeros(), m1_nnz);
+    m1 = m4; refM1 = refM4;
     VERIFY_IS_APPROX((m1 = m1.transpose()), (refM1 = refM1.transpose().eval()));
+    VERIFY_IS_EQUAL(m1.nonZeros(), m1_nnz);
+    m1 = m4; refM1 = refM4;
     VERIFY_IS_APPROX((m1 = -m1.transpose()), (refM1 = -refM1.transpose().eval()));
+    VERIFY_IS_EQUAL(m1.nonZeros(), m1_nnz);
+    m1 = m4; refM1 = refM4;
     VERIFY_IS_APPROX((m1 += -m1), (refM1 += -refM1));
+    VERIFY_IS_EQUAL(m1.nonZeros(), m1_nnz);
+    m1 = m4; refM1 = refM4;
+
+    if(m1.isCompressed())
+    {
+      VERIFY_IS_APPROX(m1.coeffs().sum(), m1.sum());
+      m1.coeffs() += s1;
+      for(Index j = 0; j<m1.outerSize(); ++j)
+        for(typename SparseMatrixType::InnerIterator it(m1,j); it; ++it)
+          refM1(it.row(), it.col()) += s1;
+      VERIFY_IS_APPROX(m1, refM1);
+    }
+
+    // and/or
+    {
+      typedef SparseMatrix<bool, SparseMatrixType::Options, typename SparseMatrixType::StorageIndex> SpBool;
+      SpBool mb1 = m1.real().template cast<bool>();
+      SpBool mb2 = m2.real().template cast<bool>();
+      VERIFY_IS_EQUAL(mb1.template cast<int>().sum(), refM1.real().template cast<bool>().count());
+      VERIFY_IS_EQUAL((mb1 && mb2).template cast<int>().sum(), (refM1.real().template cast<bool>() && refM2.real().template cast<bool>()).count());
+      VERIFY_IS_EQUAL((mb1 || mb2).template cast<int>().sum(), (refM1.real().template cast<bool>() || refM2.real().template cast<bool>()).count());
+      SpBool mb3 = mb1 && mb2;
+      if(mb1.coeffs().all() && mb2.coeffs().all())
+      {
+        VERIFY_IS_EQUAL(mb3.nonZeros(), (refM1.real().template cast<bool>() && refM2.real().template cast<bool>()).count());
+      }
+    }
+  }
+
+  // test reverse iterators
+  {
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+    SparseMatrixType m2(rows, cols);
+    initSparse<Scalar>(density, refMat2, m2);
+    std::vector<Scalar> ref_value(m2.innerSize());
+    std::vector<Index> ref_index(m2.innerSize());
+    if(internal::random<bool>())
+      m2.makeCompressed();
+    for(Index j = 0; j<m2.outerSize(); ++j)
+    {
+      Index count_forward = 0;
+
+      for(typename SparseMatrixType::InnerIterator it(m2,j); it; ++it)
+      {
+        ref_value[ref_value.size()-1-count_forward] = it.value();
+        ref_index[ref_index.size()-1-count_forward] = it.index();
+        count_forward++;
+      }
+      Index count_reverse = 0;
+      for(typename SparseMatrixType::ReverseInnerIterator it(m2,j); it; --it)
+      {
+        VERIFY_IS_APPROX( std::abs(ref_value[ref_value.size()-count_forward+count_reverse])+1, std::abs(it.value())+1);
+        VERIFY_IS_EQUAL( ref_index[ref_index.size()-count_forward+count_reverse] , it.index());
+        count_reverse++;
+      }
+      VERIFY_IS_EQUAL(count_forward, count_reverse);
+    }
   }
 
   // test transpose
   {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+    SparseMatrixType m2(rows, cols);
     initSparse<Scalar>(density, refMat2, m2);
     VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
     VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
 
     VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
-  }
-
-  
-  
-  // test generic blocks
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    Index j0 = internal::random<Index>(0,rows-2);
-    Index j1 = internal::random<Index>(0,rows-2);
-    Index n0 = internal::random<Index>(1,rows-(std::max)(j0,j1));
-    if(SparseMatrixType::IsRowMajor)
-      VERIFY_IS_APPROX(m2.block(j0,0,n0,cols), refMat2.block(j0,0,n0,cols));
-    else
-      VERIFY_IS_APPROX(m2.block(0,j0,rows,n0), refMat2.block(0,j0,rows,n0));
-    
-    if(SparseMatrixType::IsRowMajor)
-      VERIFY_IS_APPROX(m2.block(j0,0,n0,cols)+m2.block(j1,0,n0,cols),
-                      refMat2.block(j0,0,n0,cols)+refMat2.block(j1,0,n0,cols));
-    else
-      VERIFY_IS_APPROX(m2.block(0,j0,rows,n0)+m2.block(0,j1,rows,n0),
-                      refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
-      
-    Index i = internal::random<Index>(0,m2.outerSize()-1);
-    if(SparseMatrixType::IsRowMajor) {
-      m2.innerVector(i) = m2.innerVector(i) * s1;
-      refMat2.row(i) = refMat2.row(i) * s1;
-      VERIFY_IS_APPROX(m2,refMat2);
-    } else {
-      m2.innerVector(i) = m2.innerVector(i) * s1;
-      refMat2.col(i) = refMat2.col(i) * s1;
-      VERIFY_IS_APPROX(m2,refMat2);
-    }
+    
+    // check isApprox handles opposite storage order
+    typename Transpose<SparseMatrixType>::PlainObject m3(m2);
+    VERIFY(m2.isApprox(m3));
   }
 
   // test prune
   {
-    SparseMatrixType m2(rows, rows);
-    DenseMatrix refM2(rows, rows);
+    SparseMatrixType m2(rows, cols);
+    DenseMatrix refM2(rows, cols);
     refM2.setZero();
     int countFalseNonZero = 0;
     int countTrueNonZero = 0;
-    for (Index j=0; j<m2.outerSize(); ++j)
+    m2.reserve(VectorXi::Constant(m2.outerSize(), int(m2.innerSize())));
+    for (Index j=0; j<m2.cols(); ++j)
     {
-      m2.startVec(j);
-      for (Index i=0; i<m2.innerSize(); ++i)
+      for (Index i=0; i<m2.rows(); ++i)
       {
         float x = internal::random<float>(0,1);
-        if (x<0.1)
+        if (x<0.1f)
         {
           // do nothing
         }
-        else if (x<0.5)
+        else if (x<0.5f)
         {
           countFalseNonZero++;
-          m2.insertBackByOuterInner(j,i) = Scalar(0);
+          m2.insert(i,j) = Scalar(0);
         }
         else
         {
           countTrueNonZero++;
-          m2.insertBackByOuterInner(j,i) = Scalar(1);
-          if(SparseMatrixType::IsRowMajor)
-            refM2(j,i) = Scalar(1);
-          else
-            refM2(i,j) = Scalar(1);
+          m2.insert(i,j) = Scalar(1);
+          refM2(i,j) = Scalar(1);
         }
       }
     }
-    m2.finalize();
+    if(internal::random<bool>())
+      m2.makeCompressed();
     VERIFY(countFalseNonZero+countTrueNonZero == m2.nonZeros());
-    VERIFY_IS_APPROX(m2, refM2);
+    if(countTrueNonZero>0)
+      VERIFY_IS_APPROX(m2, refM2);
     m2.prune(Scalar(1));
     VERIFY(countTrueNonZero==m2.nonZeros());
     VERIFY_IS_APPROX(m2, refM2);
   }
 
   // test setFromTriplets
   {
-    typedef Triplet<Scalar,Index> TripletType;
+    typedef Triplet<Scalar,StorageIndex> TripletType;
     std::vector<TripletType> triplets;
-    int ntriplets = rows*cols;
+    Index ntriplets = rows*cols;
     triplets.reserve(ntriplets);
-    DenseMatrix refMat(rows,cols);
-    refMat.setZero();
-    for(int i=0;i<ntriplets;++i)
+    DenseMatrix refMat_sum  = DenseMatrix::Zero(rows,cols);
+    DenseMatrix refMat_prod = DenseMatrix::Zero(rows,cols);
+    DenseMatrix refMat_last = DenseMatrix::Zero(rows,cols);
+
+    for(Index i=0;i<ntriplets;++i)
     {
-      Index r = internal::random<Index>(0,rows-1);
-      Index c = internal::random<Index>(0,cols-1);
+      StorageIndex r = internal::random<StorageIndex>(0,StorageIndex(rows-1));
+      StorageIndex c = internal::random<StorageIndex>(0,StorageIndex(cols-1));
       Scalar v = internal::random<Scalar>();
       triplets.push_back(TripletType(r,c,v));
-      refMat(r,c) += v;
+      refMat_sum(r,c) += v;
+      if(std::abs(refMat_prod(r,c))==0)
+        refMat_prod(r,c) = v;
+      else
+        refMat_prod(r,c) *= v;
+      refMat_last(r,c) = v;
     }
     SparseMatrixType m(rows,cols);
     m.setFromTriplets(triplets.begin(), triplets.end());
-    VERIFY_IS_APPROX(m, refMat);
+    VERIFY_IS_APPROX(m, refMat_sum);
+
+    m.setFromTriplets(triplets.begin(), triplets.end(), std::multiplies<Scalar>());
+    VERIFY_IS_APPROX(m, refMat_prod);
+#if (defined(__cplusplus) && __cplusplus >= 201103L)
+    m.setFromTriplets(triplets.begin(), triplets.end(), [] (Scalar,Scalar b) { return b; });
+    VERIFY_IS_APPROX(m, refMat_last);
+#endif
+  }
+  
+  // test Map
+  {
+    DenseMatrix refMat2(rows, cols), refMat3(rows, cols);
+    SparseMatrixType m2(rows, cols), m3(rows, cols);
+    initSparse<Scalar>(density, refMat2, m2);
+    initSparse<Scalar>(density, refMat3, m3);
+    {
+      Map<SparseMatrixType> mapMat2(m2.rows(), m2.cols(), m2.nonZeros(), m2.outerIndexPtr(), m2.innerIndexPtr(), m2.valuePtr(), m2.innerNonZeroPtr());
+      Map<SparseMatrixType> mapMat3(m3.rows(), m3.cols(), m3.nonZeros(), m3.outerIndexPtr(), m3.innerIndexPtr(), m3.valuePtr(), m3.innerNonZeroPtr());
+      VERIFY_IS_APPROX(mapMat2+mapMat3, refMat2+refMat3);
+      VERIFY_IS_APPROX(mapMat2+mapMat3, refMat2+refMat3);
+    }
+    {
+      MappedSparseMatrix<Scalar,SparseMatrixType::Options,StorageIndex> mapMat2(m2.rows(), m2.cols(), m2.nonZeros(), m2.outerIndexPtr(), m2.innerIndexPtr(), m2.valuePtr(), m2.innerNonZeroPtr());
+      MappedSparseMatrix<Scalar,SparseMatrixType::Options,StorageIndex> mapMat3(m3.rows(), m3.cols(), m3.nonZeros(), m3.outerIndexPtr(), m3.innerIndexPtr(), m3.valuePtr(), m3.innerNonZeroPtr());
+      VERIFY_IS_APPROX(mapMat2+mapMat3, refMat2+refMat3);
+      VERIFY_IS_APPROX(mapMat2+mapMat3, refMat2+refMat3);
+    }
+
+    Index i = internal::random<Index>(0,rows-1);
+    Index j = internal::random<Index>(0,cols-1);
+    m2.coeffRef(i,j) = 123;
+    if(internal::random<bool>())
+      m2.makeCompressed();
+    Map<SparseMatrixType> mapMat2(rows, cols, m2.nonZeros(), m2.outerIndexPtr(), m2.innerIndexPtr(), m2.valuePtr(),  m2.innerNonZeroPtr());
+    VERIFY_IS_EQUAL(m2.coeff(i,j),Scalar(123));
+    VERIFY_IS_EQUAL(mapMat2.coeff(i,j),Scalar(123));
+    mapMat2.coeffRef(i,j) = -123;
+    VERIFY_IS_EQUAL(m2.coeff(i,j),Scalar(-123));
   }
 
   // test triangularView
   {
-    DenseMatrix refMat2(rows, rows), refMat3(rows, rows);
-    SparseMatrixType m2(rows, rows), m3(rows, rows);
+    DenseMatrix refMat2(rows, cols), refMat3(rows, cols);
+    SparseMatrixType m2(rows, cols), m3(rows, cols);
     initSparse<Scalar>(density, refMat2, m2);
     refMat3 = refMat2.template triangularView<Lower>();
     m3 = m2.template triangularView<Lower>();
     VERIFY_IS_APPROX(m3, refMat3);
 
     refMat3 = refMat2.template triangularView<Upper>();
     m3 = m2.template triangularView<Upper>();
     VERIFY_IS_APPROX(m3, refMat3);
 
-    refMat3 = refMat2.template triangularView<UnitUpper>();
-    m3 = m2.template triangularView<UnitUpper>();
-    VERIFY_IS_APPROX(m3, refMat3);
+    {
+      refMat3 = refMat2.template triangularView<UnitUpper>();
+      m3 = m2.template triangularView<UnitUpper>();
+      VERIFY_IS_APPROX(m3, refMat3);
 
-    refMat3 = refMat2.template triangularView<UnitLower>();
-    m3 = m2.template triangularView<UnitLower>();
-    VERIFY_IS_APPROX(m3, refMat3);
+      refMat3 = refMat2.template triangularView<UnitLower>();
+      m3 = m2.template triangularView<UnitLower>();
+      VERIFY_IS_APPROX(m3, refMat3);
+    }
 
     refMat3 = refMat2.template triangularView<StrictlyUpper>();
     m3 = m2.template triangularView<StrictlyUpper>();
     VERIFY_IS_APPROX(m3, refMat3);
 
     refMat3 = refMat2.template triangularView<StrictlyLower>();
     m3 = m2.template triangularView<StrictlyLower>();
     VERIFY_IS_APPROX(m3, refMat3);
+
+    // check sparse-triangular to dense
+    refMat3 = m2.template triangularView<StrictlyUpper>();
+    VERIFY_IS_APPROX(refMat3, DenseMatrix(refMat2.template triangularView<StrictlyUpper>()));
   }
   
   // test selfadjointView
   if(!SparseMatrixType::IsRowMajor)
   {
@@ -427,40 +465,84 @@
     SparseMatrixType m2(rows, rows), m3(rows, rows);
     initSparse<Scalar>(density, refMat2, m2);
     refMat3 = refMat2.template selfadjointView<Lower>();
     m3 = m2.template selfadjointView<Lower>();
     VERIFY_IS_APPROX(m3, refMat3);
+
+    refMat3 += refMat2.template selfadjointView<Lower>();
+    m3 += m2.template selfadjointView<Lower>();
+    VERIFY_IS_APPROX(m3, refMat3);
+
+    refMat3 -= refMat2.template selfadjointView<Lower>();
+    m3 -= m2.template selfadjointView<Lower>();
+    VERIFY_IS_APPROX(m3, refMat3);
+
+    // selfadjointView only works for square matrices:
+    SparseMatrixType m4(rows, rows+1);
+    VERIFY_RAISES_ASSERT(m4.template selfadjointView<Lower>());
+    VERIFY_RAISES_ASSERT(m4.template selfadjointView<Upper>());
   }
   
   // test sparseView
   {
     DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
     SparseMatrixType m2(rows, rows);
     initSparse<Scalar>(density, refMat2, m2);
     VERIFY_IS_APPROX(m2.eval(), refMat2.sparseView().eval());
+
+    // sparse view on expressions:
+    VERIFY_IS_APPROX((s1*m2).eval(), (s1*refMat2).sparseView().eval());
+    VERIFY_IS_APPROX((m2+m2).eval(), (refMat2+refMat2).sparseView().eval());
+    VERIFY_IS_APPROX((m2*m2).eval(), (refMat2.lazyProduct(refMat2)).sparseView().eval());
+    VERIFY_IS_APPROX((m2*m2).eval(), (refMat2*refMat2).sparseView().eval());
   }
 
   // test diagonal
   {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+    SparseMatrixType m2(rows, cols);
     initSparse<Scalar>(density, refMat2, m2);
     VERIFY_IS_APPROX(m2.diagonal(), refMat2.diagonal().eval());
+    DenseVector d = m2.diagonal();
+    VERIFY_IS_APPROX(d, refMat2.diagonal().eval());
+    d = m2.diagonal().array();
+    VERIFY_IS_APPROX(d, refMat2.diagonal().eval());
+    VERIFY_IS_APPROX(const_cast<const SparseMatrixType&>(m2).diagonal(), refMat2.diagonal().eval());
+    
+    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag);
+    m2.diagonal()      += refMat2.diagonal();
+    refMat2.diagonal() += refMat2.diagonal();
+    VERIFY_IS_APPROX(m2, refMat2);
+  }
+  
+  // test diagonal to sparse
+  {
+    DenseVector d = DenseVector::Random(rows);
+    DenseMatrix refMat2 = d.asDiagonal();
+    SparseMatrixType m2(rows, rows);
+    m2 = d.asDiagonal();
+    VERIFY_IS_APPROX(m2, refMat2);
+    SparseMatrixType m3(d.asDiagonal());
+    VERIFY_IS_APPROX(m3, refMat2);
+    refMat2 += d.asDiagonal();
+    m2 += d.asDiagonal();
+    VERIFY_IS_APPROX(m2, refMat2);
   }
   
   // test conservative resize
   {
-      std::vector< std::pair<Index,Index> > inc;
-      inc.push_back(std::pair<Index,Index>(-3,-2));
-      inc.push_back(std::pair<Index,Index>(0,0));
-      inc.push_back(std::pair<Index,Index>(3,2));
-      inc.push_back(std::pair<Index,Index>(3,0));
-      inc.push_back(std::pair<Index,Index>(0,3));
+      std::vector< std::pair<StorageIndex,StorageIndex> > inc;
+      if(rows > 3 && cols > 2)
+        inc.push_back(std::pair<StorageIndex,StorageIndex>(-3,-2));
+      inc.push_back(std::pair<StorageIndex,StorageIndex>(0,0));
+      inc.push_back(std::pair<StorageIndex,StorageIndex>(3,2));
+      inc.push_back(std::pair<StorageIndex,StorageIndex>(3,0));
+      inc.push_back(std::pair<StorageIndex,StorageIndex>(0,3));
       
       for(size_t i = 0; i< inc.size(); i++) {
-        Index incRows = inc[i].first;
-        Index incCols = inc[i].second;
+        StorageIndex incRows = inc[i].first;
+        StorageIndex incCols = inc[i].second;
         SparseMatrixType m1(rows, cols);
         DenseMatrix refMat1 = DenseMatrix::Zero(rows, cols);
         initSparse<Scalar>(density, refMat1, m1);
         
         m1.conservativeResize(rows+incRows, cols+incCols);
@@ -486,24 +568,121 @@
   {
     DenseMatrix refMat1 = DenseMatrix::Identity(rows, rows);
     SparseMatrixType m1(rows, rows);
     m1.setIdentity();
     VERIFY_IS_APPROX(m1, refMat1);
+    for(int k=0; k<rows*rows/4; ++k)
+    {
+      Index i = internal::random<Index>(0,rows-1);
+      Index j = internal::random<Index>(0,rows-1);
+      Scalar v = internal::random<Scalar>();
+      m1.coeffRef(i,j) = v;
+      refMat1.coeffRef(i,j) = v;
+      VERIFY_IS_APPROX(m1, refMat1);
+      if(internal::random<Index>(0,10)<2)
+        m1.makeCompressed();
+    }
+    m1.setIdentity();
+    refMat1.setIdentity();
+    VERIFY_IS_APPROX(m1, refMat1);
+  }
+
+  // test array/vector of InnerIterator
+  {
+    typedef typename SparseMatrixType::InnerIterator IteratorType;
+
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+    SparseMatrixType m2(rows, cols);
+    initSparse<Scalar>(density, refMat2, m2);
+    IteratorType static_array[2];
+    static_array[0] = IteratorType(m2,0);
+    static_array[1] = IteratorType(m2,m2.outerSize()-1);
+    VERIFY( static_array[0] || m2.innerVector(static_array[0].outer()).nonZeros() == 0 );
+    VERIFY( static_array[1] || m2.innerVector(static_array[1].outer()).nonZeros() == 0 );
+    if(static_array[0] && static_array[1])
+    {
+      ++(static_array[1]);
+      static_array[1] = IteratorType(m2,0);
+      VERIFY( static_array[1] );
+      VERIFY( static_array[1].index() == static_array[0].index() );
+      VERIFY( static_array[1].outer() == static_array[0].outer() );
+      VERIFY( static_array[1].value() == static_array[0].value() );
+    }
+
+    std::vector<IteratorType> iters(2);
+    iters[0] = IteratorType(m2,0);
+    iters[1] = IteratorType(m2,m2.outerSize()-1);
+  }
+}
+
+
+template<typename SparseMatrixType>
+void big_sparse_triplet(Index rows, Index cols, double density) {
+  typedef typename SparseMatrixType::StorageIndex StorageIndex;
+  typedef typename SparseMatrixType::Scalar Scalar;
+  typedef Triplet<Scalar,Index> TripletType;
+  std::vector<TripletType> triplets;
+  double nelements = density * rows*cols;
+  VERIFY(nelements>=0 && nelements <  NumTraits<StorageIndex>::highest());
+  Index ntriplets = Index(nelements);
+  triplets.reserve(ntriplets);
+  Scalar sum = Scalar(0);
+  for(Index i=0;i<ntriplets;++i)
+  {
+    Index r = internal::random<Index>(0,rows-1);
+    Index c = internal::random<Index>(0,cols-1);
+    Scalar v = internal::random<Scalar>();
+    triplets.push_back(TripletType(r,c,v));
+    sum += v;
   }
+  SparseMatrixType m(rows,cols);
+  m.setFromTriplets(triplets.begin(), triplets.end());
+  VERIFY(m.nonZeros() <= ntriplets);
+  VERIFY_IS_APPROX(sum, m.sum());
 }
+
 
 void test_sparse_basic()
 {
   for(int i = 0; i < g_repeat; i++) {
-    int s = Eigen::internal::random<int>(1,50);
-    EIGEN_UNUSED_VARIABLE(s);
+    int r = Eigen::internal::random<int>(1,200), c = Eigen::internal::random<int>(1,200);
+    if(Eigen::internal::random<int>(0,4) == 0) {
+      r = c; // check square matrices in 25% of tries
+    }
+    EIGEN_UNUSED_VARIABLE(r+c);
+    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(1, 1)) ));
     CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(8, 8)) ));
-    CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, ColMajor>(s, s)) ));
-    CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, RowMajor>(s, s)) ));
-    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(s, s)) ));
-    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,long int>(s, s)) ));
-    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,long int>(s, s)) ));
-    
-    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(s), short(s))) ));
-    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(s), short(s))) ));
-  }
+    CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, ColMajor>(r, c)) ));
+    CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, RowMajor>(r, c)) ));
+    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(r, c)) ));
+    CALL_SUBTEST_5(( sparse_basic(SparseMatrix<double,ColMajor,long int>(r, c)) ));
+    CALL_SUBTEST_5(( sparse_basic(SparseMatrix<double,RowMajor,long int>(r, c)) ));
+    
+    r = Eigen::internal::random<int>(1,100);
+    c = Eigen::internal::random<int>(1,100);
+    if(Eigen::internal::random<int>(0,4) == 0) {
+      r = c; // check square matrices in 25% of tries
+    }
+    
+    CALL_SUBTEST_6(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(r), short(c))) ));
+    CALL_SUBTEST_6(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(r), short(c))) ));
+  }
+
+  // Regression test for bug 900: (manually insert higher values here, if you have enough RAM):
+  CALL_SUBTEST_3((big_sparse_triplet<SparseMatrix<float, RowMajor, int> >(10000, 10000, 0.125)));
+  CALL_SUBTEST_4((big_sparse_triplet<SparseMatrix<double, ColMajor, long int> >(10000, 10000, 0.125)));
+
+  // Regression test for bug 1105
+#ifdef EIGEN_TEST_PART_7
+  {
+    int n = Eigen::internal::random<int>(200,600);
+    SparseMatrix<std::complex<double>,0, long> mat(n, n);
+    std::complex<double> val;
+
+    for(int i=0; i<n; ++i)
+    {
+      mat.coeffRef(i, i%(n/10)) = val;
+      VERIFY(mat.data().allocatedSize()<20*n);
+    }
+  }
+#endif
 }

ADDED   3rd_party/eigen/test/sparse_block.cpp
Index: 3rd_party/eigen/test/sparse_block.cpp
==================================================================
--- 3rd_party/eigen/test/sparse_block.cpp
+++ 3rd_party/eigen/test/sparse_block.cpp
@@ -0,0 +1,317 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "sparse.h"
+
+template<typename T>
+typename Eigen::internal::enable_if<(T::Flags&RowMajorBit)==RowMajorBit, typename T::RowXpr>::type
+innervec(T& A, Index i)
+{
+  return A.row(i);
+}
+
+template<typename T>
+typename Eigen::internal::enable_if<(T::Flags&RowMajorBit)==0, typename T::ColXpr>::type
+innervec(T& A, Index i)
+{
+  return A.col(i);
+}
+
+template<typename SparseMatrixType> void sparse_block(const SparseMatrixType& ref)
+{
+  const Index rows = ref.rows();
+  const Index cols = ref.cols();
+  const Index inner = ref.innerSize();
+  const Index outer = ref.outerSize();
+
+  typedef typename SparseMatrixType::Scalar Scalar;
+  typedef typename SparseMatrixType::StorageIndex StorageIndex;
+
+  double density = (std::max)(8./(rows*cols), 0.01);
+  typedef Matrix<Scalar,Dynamic,Dynamic,SparseMatrixType::IsRowMajor?RowMajor:ColMajor> DenseMatrix;
+  typedef Matrix<Scalar,Dynamic,1> DenseVector;
+  typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
+  typedef SparseVector<Scalar> SparseVectorType;
+
+  Scalar s1 = internal::random<Scalar>();
+  {
+    SparseMatrixType m(rows, cols);
+    DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
+    initSparse<Scalar>(density, refMat, m);
+
+    VERIFY_IS_APPROX(m, refMat);
+
+    // test InnerIterators and Block expressions
+    for (int t=0; t<10; ++t)
+    {
+      Index j = internal::random<Index>(0,cols-2);
+      Index i = internal::random<Index>(0,rows-2);
+      Index w = internal::random<Index>(1,cols-j);
+      Index h = internal::random<Index>(1,rows-i);
+
+      VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
+      for(Index c=0; c<w; c++)
+      {
+        VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
+        for(Index r=0; r<h; r++)
+        {
+          VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
+          VERIFY_IS_APPROX(m.block(i,j,h,w).coeff(r,c), refMat.block(i,j,h,w).coeff(r,c));
+        }
+      }
+      for(Index r=0; r<h; r++)
+      {
+        VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
+        for(Index c=0; c<w; c++)
+        {
+          VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
+          VERIFY_IS_APPROX(m.block(i,j,h,w).coeff(r,c), refMat.block(i,j,h,w).coeff(r,c));
+        }
+      }
+      
+      VERIFY_IS_APPROX(m.middleCols(j,w), refMat.middleCols(j,w));
+      VERIFY_IS_APPROX(m.middleRows(i,h), refMat.middleRows(i,h));
+      for(Index r=0; r<h; r++)
+      {
+        VERIFY_IS_APPROX(m.middleCols(j,w).row(r), refMat.middleCols(j,w).row(r));
+        VERIFY_IS_APPROX(m.middleRows(i,h).row(r), refMat.middleRows(i,h).row(r));
+        for(Index c=0; c<w; c++)
+        {
+          VERIFY_IS_APPROX(m.col(c).coeff(r), refMat.col(c).coeff(r));
+          VERIFY_IS_APPROX(m.row(r).coeff(c), refMat.row(r).coeff(c));
+          
+          VERIFY_IS_APPROX(m.middleCols(j,w).coeff(r,c), refMat.middleCols(j,w).coeff(r,c));
+          VERIFY_IS_APPROX(m.middleRows(i,h).coeff(r,c), refMat.middleRows(i,h).coeff(r,c));
+          if(m.middleCols(j,w).coeff(r,c) != Scalar(0))
+          {
+            VERIFY_IS_APPROX(m.middleCols(j,w).coeffRef(r,c), refMat.middleCols(j,w).coeff(r,c));
+          }
+          if(m.middleRows(i,h).coeff(r,c) != Scalar(0))
+          {
+            VERIFY_IS_APPROX(m.middleRows(i,h).coeff(r,c), refMat.middleRows(i,h).coeff(r,c));
+          }
+        }
+      }
+      for(Index c=0; c<w; c++)
+      {
+        VERIFY_IS_APPROX(m.middleCols(j,w).col(c), refMat.middleCols(j,w).col(c));
+        VERIFY_IS_APPROX(m.middleRows(i,h).col(c), refMat.middleRows(i,h).col(c));
+      }
+    }
+
+    for(Index c=0; c<cols; c++)
+    {
+      VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c));
+      VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c));
+    }
+
+    for(Index r=0; r<rows; r++)
+    {
+      VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
+      VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
+    }
+  }
+
+  // test innerVector()
+  {
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+    SparseMatrixType m2(rows, cols);
+    initSparse<Scalar>(density, refMat2, m2);
+    Index j0 = internal::random<Index>(0,outer-1);
+    Index j1 = internal::random<Index>(0,outer-1);
+    Index r0 = internal::random<Index>(0,rows-1);
+    Index c0 = internal::random<Index>(0,cols-1);
+
+    VERIFY_IS_APPROX(m2.innerVector(j0), innervec(refMat2,j0));
+    VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), innervec(refMat2,j0)+innervec(refMat2,j1));
+
+    m2.innerVector(j0) *= Scalar(2);
+    innervec(refMat2,j0) *= Scalar(2);
+    VERIFY_IS_APPROX(m2, refMat2);
+
+    m2.row(r0) *= Scalar(3);
+    refMat2.row(r0) *= Scalar(3);
+    VERIFY_IS_APPROX(m2, refMat2);
+
+    m2.col(c0) *= Scalar(4);
+    refMat2.col(c0) *= Scalar(4);
+    VERIFY_IS_APPROX(m2, refMat2);
+
+    m2.row(r0) /= Scalar(3);
+    refMat2.row(r0) /= Scalar(3);
+    VERIFY_IS_APPROX(m2, refMat2);
+
+    m2.col(c0) /= Scalar(4);
+    refMat2.col(c0) /= Scalar(4);
+    VERIFY_IS_APPROX(m2, refMat2);
+
+    SparseVectorType v1;
+    VERIFY_IS_APPROX(v1 = m2.col(c0) * 4, refMat2.col(c0)*4);
+    VERIFY_IS_APPROX(v1 = m2.row(r0) * 4, refMat2.row(r0).transpose()*4);
+
+    SparseMatrixType m3(rows,cols);
+    m3.reserve(VectorXi::Constant(outer,int(inner/2)));
+    for(Index j=0; j<outer; ++j)
+      for(Index k=0; k<(std::min)(j,inner); ++k)
+        m3.insertByOuterInner(j,k) = internal::convert_index<StorageIndex>(k+1);
+    for(Index j=0; j<(std::min)(outer, inner); ++j)
+    {
+      VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
+      if(j>0)
+        VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
+    }
+    m3.makeCompressed();
+    for(Index j=0; j<(std::min)(outer, inner); ++j)
+    {
+      VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
+      if(j>0)
+        VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
+    }
+
+    VERIFY(m3.innerVector(j0).nonZeros() == m3.transpose().innerVector(j0).nonZeros());
+
+//     m2.innerVector(j0) = 2*m2.innerVector(j1);
+//     refMat2.col(j0) = 2*refMat2.col(j1);
+//     VERIFY_IS_APPROX(m2, refMat2);
+  }
+
+  // test innerVectors()
+  {
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+    SparseMatrixType m2(rows, cols);
+    initSparse<Scalar>(density, refMat2, m2);
+    if(internal::random<float>(0,1)>0.5f) m2.makeCompressed();
+    Index j0 = internal::random<Index>(0,outer-2);
+    Index j1 = internal::random<Index>(0,outer-2);
+    Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(j0,0,n0,cols));
+    else
+      VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0));
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
+                       refMat2.middleRows(j0,n0)+refMat2.middleRows(j1,n0));
+    else
+      VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
+                      refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
+    
+    VERIFY_IS_APPROX(m2, refMat2);
+    
+    VERIFY(m2.innerVectors(j0,n0).nonZeros() == m2.transpose().innerVectors(j0,n0).nonZeros());
+    
+    m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0);
+    if(SparseMatrixType::IsRowMajor)
+      refMat2.middleRows(j0,n0) = (refMat2.middleRows(j0,n0) + refMat2.middleRows(j1,n0)).eval();
+    else
+      refMat2.middleCols(j0,n0) = (refMat2.middleCols(j0,n0) + refMat2.middleCols(j1,n0)).eval();
+    
+    VERIFY_IS_APPROX(m2, refMat2);
+  }
+
+  // test generic blocks
+  {
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+    SparseMatrixType m2(rows, cols);
+    initSparse<Scalar>(density, refMat2, m2);
+    Index j0 = internal::random<Index>(0,outer-2);
+    Index j1 = internal::random<Index>(0,outer-2);
+    Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m2.block(j0,0,n0,cols), refMat2.block(j0,0,n0,cols));
+    else
+      VERIFY_IS_APPROX(m2.block(0,j0,rows,n0), refMat2.block(0,j0,rows,n0));
+    
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m2.block(j0,0,n0,cols)+m2.block(j1,0,n0,cols),
+                      refMat2.block(j0,0,n0,cols)+refMat2.block(j1,0,n0,cols));
+    else
+      VERIFY_IS_APPROX(m2.block(0,j0,rows,n0)+m2.block(0,j1,rows,n0),
+                      refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
+      
+    Index i = internal::random<Index>(0,m2.outerSize()-1);
+    if(SparseMatrixType::IsRowMajor) {
+      m2.innerVector(i) = m2.innerVector(i) * s1;
+      refMat2.row(i) = refMat2.row(i) * s1;
+      VERIFY_IS_APPROX(m2,refMat2);
+    } else {
+      m2.innerVector(i) = m2.innerVector(i) * s1;
+      refMat2.col(i) = refMat2.col(i) * s1;
+      VERIFY_IS_APPROX(m2,refMat2);
+    }
+    
+    Index r0 = internal::random<Index>(0,rows-2);
+    Index c0 = internal::random<Index>(0,cols-2);
+    Index r1 = internal::random<Index>(1,rows-r0);
+    Index c1 = internal::random<Index>(1,cols-c0);
+    
+    VERIFY_IS_APPROX(DenseVector(m2.col(c0)), refMat2.col(c0));
+    VERIFY_IS_APPROX(m2.col(c0), refMat2.col(c0));
+    
+    VERIFY_IS_APPROX(RowDenseVector(m2.row(r0)), refMat2.row(r0));
+    VERIFY_IS_APPROX(m2.row(r0), refMat2.row(r0));
+
+    VERIFY_IS_APPROX(m2.block(r0,c0,r1,c1), refMat2.block(r0,c0,r1,c1));
+    VERIFY_IS_APPROX((2*m2).block(r0,c0,r1,c1), (2*refMat2).block(r0,c0,r1,c1));
+
+    if(m2.nonZeros()>0)
+    {
+      VERIFY_IS_APPROX(m2, refMat2);
+      SparseMatrixType m3(rows, cols);
+      DenseMatrix refMat3(rows, cols); refMat3.setZero();
+      Index n = internal::random<Index>(1,10);
+      for(Index k=0; k<n; ++k)
+      {
+        Index o1 = internal::random<Index>(0,outer-1);
+        Index o2 = internal::random<Index>(0,outer-1);
+        if(SparseMatrixType::IsRowMajor)
+        {
+          m3.innerVector(o1) = m2.row(o2);
+          refMat3.row(o1) = refMat2.row(o2);
+        }
+        else
+        {
+          m3.innerVector(o1) = m2.col(o2);
+          refMat3.col(o1) = refMat2.col(o2);
+        }
+        if(internal::random<bool>())
+          m3.makeCompressed();
+      }
+      if(m3.nonZeros()>0)
+      VERIFY_IS_APPROX(m3, refMat3);
+    }
+  }
+}
+
+void test_sparse_block()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    int r = Eigen::internal::random<int>(1,200), c = Eigen::internal::random<int>(1,200);
+    if(Eigen::internal::random<int>(0,4) == 0) {
+      r = c; // check square matrices in 25% of tries
+    }
+    EIGEN_UNUSED_VARIABLE(r+c);
+    CALL_SUBTEST_1(( sparse_block(SparseMatrix<double>(1, 1)) ));
+    CALL_SUBTEST_1(( sparse_block(SparseMatrix<double>(8, 8)) ));
+    CALL_SUBTEST_1(( sparse_block(SparseMatrix<double>(r, c)) ));
+    CALL_SUBTEST_2(( sparse_block(SparseMatrix<std::complex<double>, ColMajor>(r, c)) ));
+    CALL_SUBTEST_2(( sparse_block(SparseMatrix<std::complex<double>, RowMajor>(r, c)) ));
+    
+    CALL_SUBTEST_3(( sparse_block(SparseMatrix<double,ColMajor,long int>(r, c)) ));
+    CALL_SUBTEST_3(( sparse_block(SparseMatrix<double,RowMajor,long int>(r, c)) ));
+    
+    r = Eigen::internal::random<int>(1,100);
+    c = Eigen::internal::random<int>(1,100);
+    if(Eigen::internal::random<int>(0,4) == 0) {
+      r = c; // check square matrices in 25% of tries
+    }
+    
+    CALL_SUBTEST_4(( sparse_block(SparseMatrix<double,ColMajor,short int>(short(r), short(c))) ));
+    CALL_SUBTEST_4(( sparse_block(SparseMatrix<double,RowMajor,short int>(short(r), short(c))) ));
+  }
+}

Index: 3rd_party/eigen/test/sparse_permutations.cpp
==================================================================
--- 3rd_party/eigen/test/sparse_permutations.cpp
+++ 3rd_party/eigen/test/sparse_permutations.cpp
@@ -1,27 +1,59 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+
+static long int nb_transposed_copies;
+#define EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN {nb_transposed_copies++;}
+#define VERIFY_TRANSPOSITION_COUNT(XPR,N) {\
+    nb_transposed_copies = 0; \
+    XPR; \
+    if(nb_transposed_copies!=N) std::cerr << "nb_transposed_copies == " << nb_transposed_copies << "\n"; \
+    VERIFY( (#XPR) && nb_transposed_copies==N ); \
+  }
+
 #include "sparse.h"
+
+template<typename T>
+bool is_sorted(const T& mat) {
+  for(Index k = 0; k<mat.outerSize(); ++k)
+  {
+    Index prev = -1;
+    for(typename T::InnerIterator it(mat,k); it; ++it)
+    {
+      if(prev>=it.index())
+        return false;
+      prev = it.index();
+    }
+  }
+  return true;
+}
+
+template<typename T>
+typename internal::nested_eval<T,1>::type eval(const T &xpr)
+{
+  VERIFY( int(internal::nested_eval<T,1>::type::Flags&RowMajorBit) == int(internal::evaluator<T>::Flags&RowMajorBit) );
+  return xpr;
+}
 
 template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(const SparseMatrixType& ref)
 {
-  typedef typename SparseMatrixType::Index Index;
-
   const Index rows = ref.rows();
   const Index cols = ref.cols();
   typedef typename SparseMatrixType::Scalar Scalar;
-  typedef typename SparseMatrixType::Index Index;
-  typedef SparseMatrix<Scalar, OtherStorage, Index> OtherSparseMatrixType;
+  typedef typename SparseMatrixType::StorageIndex StorageIndex;
+  typedef SparseMatrix<Scalar, OtherStorage, StorageIndex> OtherSparseMatrixType;
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Index,Dynamic,1> VectorI;
+  typedef Matrix<StorageIndex,Dynamic,1> VectorI;
+//   bool IsRowMajor1 = SparseMatrixType::IsRowMajor;
+//   bool IsRowMajor2 = OtherSparseMatrixType::IsRowMajor;
   
   double density = (std::max)(8./(rows*cols), 0.01);
   
   SparseMatrixType mat(rows, cols), up(rows,cols), lo(rows,cols);
   OtherSparseMatrixType res;
@@ -42,62 +74,73 @@
   PermutationMatrix<Dynamic> p, p_null;
   VectorI pi;
   randomPermutationVector(pi, cols);
   p.indices() = pi;
 
-  res = mat*p;
+  VERIFY( is_sorted( ::eval(mat*p) ));
+  VERIFY( is_sorted( res = mat*p ));
+  VERIFY_TRANSPOSITION_COUNT( ::eval(mat*p), 0);
+  //VERIFY_TRANSPOSITION_COUNT( res = mat*p, IsRowMajor ? 1 : 0 );
   res_d = mat_d*p;
   VERIFY(res.isApprox(res_d) && "mat*p");
 
-  res = p*mat;
+  VERIFY( is_sorted( ::eval(p*mat) ));
+  VERIFY( is_sorted( res = p*mat ));
+  VERIFY_TRANSPOSITION_COUNT( ::eval(p*mat), 0);
   res_d = p*mat_d;
   VERIFY(res.isApprox(res_d) && "p*mat");
 
-  res = mat*p.inverse();
+  VERIFY( is_sorted( (mat*p).eval() ));
+  VERIFY( is_sorted( res = mat*p.inverse() ));
+  VERIFY_TRANSPOSITION_COUNT( ::eval(mat*p.inverse()), 0);
   res_d = mat*p.inverse();
   VERIFY(res.isApprox(res_d) && "mat*inv(p)");
 
-  res = p.inverse()*mat;
+  VERIFY( is_sorted( (p*mat+p*mat).eval() ));
+  VERIFY( is_sorted( res = p.inverse()*mat ));
+  VERIFY_TRANSPOSITION_COUNT( ::eval(p.inverse()*mat), 0);
   res_d = p.inverse()*mat_d;
   VERIFY(res.isApprox(res_d) && "inv(p)*mat");
 
-  res = mat.twistedBy(p);
+  VERIFY( is_sorted( (p * mat * p.inverse()).eval() ));
+  VERIFY( is_sorted( res = mat.twistedBy(p) ));
+  VERIFY_TRANSPOSITION_COUNT( ::eval(p * mat * p.inverse()), 0);
   res_d = (p * mat_d) * p.inverse();
   VERIFY(res.isApprox(res_d) && "p*mat*inv(p)");
 
   
-  res = mat.template selfadjointView<Upper>().twistedBy(p_null);
+  VERIFY( is_sorted( res = mat.template selfadjointView<Upper>().twistedBy(p_null) ));
   res_d = up_sym_d;
   VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full");
   
-  res = mat.template selfadjointView<Lower>().twistedBy(p_null);
+  VERIFY( is_sorted( res = mat.template selfadjointView<Lower>().twistedBy(p_null) ));
   res_d = lo_sym_d;
   VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full");
   
   
-  res = up.template selfadjointView<Upper>().twistedBy(p_null);
+  VERIFY( is_sorted( res = up.template selfadjointView<Upper>().twistedBy(p_null) ));
   res_d = up_sym_d;
   VERIFY(res.isApprox(res_d) && "upper selfadjoint to full");
   
-  res = lo.template selfadjointView<Lower>().twistedBy(p_null);
+  VERIFY( is_sorted( res = lo.template selfadjointView<Lower>().twistedBy(p_null) ));
   res_d = lo_sym_d;
   VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
 
 
-  res = mat.template selfadjointView<Upper>();
+  VERIFY( is_sorted( res = mat.template selfadjointView<Upper>() ));
   res_d = up_sym_d;
   VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full");
 
-  res = mat.template selfadjointView<Lower>();
+  VERIFY( is_sorted( res = mat.template selfadjointView<Lower>() ));
   res_d = lo_sym_d;
   VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full");
 
-  res = up.template selfadjointView<Upper>();
+  VERIFY( is_sorted( res = up.template selfadjointView<Upper>() ));
   res_d = up_sym_d;
   VERIFY(res.isApprox(res_d) && "upper selfadjoint to full");
 
-  res = lo.template selfadjointView<Lower>();
+  VERIFY( is_sorted( res = lo.template selfadjointView<Lower>() ));
   res_d = lo_sym_d;
   VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
 
 
   res.template selfadjointView<Upper>() = mat.template selfadjointView<Upper>();
@@ -150,23 +193,23 @@
   res.template selfadjointView<Lower>() = up.template selfadjointView<Upper>().twistedBy(p);
   res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Lower>();
   VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to lower");
 
   
-  res = mat.template selfadjointView<Upper>().twistedBy(p);
+  VERIFY( is_sorted( res = mat.template selfadjointView<Upper>().twistedBy(p) ));
   res_d = (p * up_sym_d) * p.inverse();
   VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to full");
   
-  res = mat.template selfadjointView<Lower>().twistedBy(p);
+  VERIFY( is_sorted( res = mat.template selfadjointView<Lower>().twistedBy(p) ));
   res_d = (p * lo_sym_d) * p.inverse();
   VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to full");
   
-  res = up.template selfadjointView<Upper>().twistedBy(p);
+  VERIFY( is_sorted( res = up.template selfadjointView<Upper>().twistedBy(p) ));
   res_d = (p * up_sym_d) * p.inverse();
   VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to full");
   
-  res = lo.template selfadjointView<Lower>().twistedBy(p);
+  VERIFY( is_sorted( res = lo.template selfadjointView<Lower>().twistedBy(p) ));
   res_d = (p * lo_sym_d) * p.inverse();
   VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to full");
 }
 
 template<typename Scalar> void sparse_permutations_all(int size)
@@ -182,6 +225,12 @@
   for(int i = 0; i < g_repeat; i++) {
     int s = Eigen::internal::random<int>(1,50);
     CALL_SUBTEST_1((  sparse_permutations_all<double>(s) ));
     CALL_SUBTEST_2((  sparse_permutations_all<std::complex<double> >(s) ));
   }
+
+  VERIFY((internal::is_same<internal::permutation_matrix_product<SparseMatrix<double>,OnTheRight,false,SparseShape>::ReturnType,
+                            internal::nested_eval<Product<SparseMatrix<double>,PermutationMatrix<Dynamic,Dynamic>,AliasFreeProduct>,1>::type>::value));
+
+  VERIFY((internal::is_same<internal::permutation_matrix_product<SparseMatrix<double>,OnTheLeft,false,SparseShape>::ReturnType,
+                            internal::nested_eval<Product<PermutationMatrix<Dynamic,Dynamic>,SparseMatrix<double>,AliasFreeProduct>,1>::type>::value));
 }

Index: 3rd_party/eigen/test/sparse_product.cpp
==================================================================
--- 3rd_party/eigen/test/sparse_product.cpp
+++ 3rd_party/eigen/test/sparse_product.cpp
@@ -5,54 +5,46 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+static long int nb_temporaries;
+
+inline void on_temporary_creation() {
+  // here's a great place to set a breakpoint when debugging failures in this test!
+  nb_temporaries++;
+}
+
+#define EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN { on_temporary_creation(); }
+
 #include "sparse.h"
 
-template<typename SparseMatrixType, typename DenseMatrix, bool IsRowMajor=SparseMatrixType::IsRowMajor> struct test_outer;
-
-template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,false> {
-  static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
-    typedef typename SparseMatrixType::Index Index;
-    Index c  = internal::random<Index>(0,m2.cols()-1);
-    Index c1 = internal::random<Index>(0,m2.cols()-1);
-    VERIFY_IS_APPROX(m4=m2.col(c)*refMat2.col(c1).transpose(), refMat4=refMat2.col(c)*refMat2.col(c1).transpose());
-    VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.col(c).transpose(), refMat4=refMat2.col(c1)*refMat2.col(c).transpose());
-  }
-};
-
-template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,true> {
-  static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
-    typedef typename SparseMatrixType::Index Index;
-    Index r  = internal::random<Index>(0,m2.rows()-1);
-    Index c1 = internal::random<Index>(0,m2.cols()-1);
-    VERIFY_IS_APPROX(m4=m2.row(r).transpose()*refMat2.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*refMat2.col(c1).transpose());
-    VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.row(r), refMat4=refMat2.col(c1)*refMat2.row(r));
-  }
-};
-
-// (m2,m4,refMat2,refMat4,dv1);
-//     VERIFY_IS_APPROX(m4=m2.innerVector(c)*dv1.transpose(), refMat4=refMat2.colVector(c)*dv1.transpose());
-//     VERIFY_IS_APPROX(m4=dv1*mcm.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose());
+#define VERIFY_EVALUATION_COUNT(XPR,N) {\
+    nb_temporaries = 0; \
+    CALL_SUBTEST( XPR ); \
+    if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
+    VERIFY( (#XPR) && nb_temporaries==N ); \
+  }
+
+
 
 template<typename SparseMatrixType> void sparse_product()
 {
-  typedef typename SparseMatrixType::Index Index;
+  typedef typename SparseMatrixType::StorageIndex StorageIndex;
   Index n = 100;
   const Index rows  = internal::random<Index>(1,n);
   const Index cols  = internal::random<Index>(1,n);
   const Index depth = internal::random<Index>(1,n);
   typedef typename SparseMatrixType::Scalar Scalar;
   enum { Flags = SparseMatrixType::Flags };
 
-  double density = (std::max)(8./(rows*cols), 0.1);
+  double density = (std::max)(8./(rows*cols), 0.2);
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
   typedef Matrix<Scalar,Dynamic,1> DenseVector;
   typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
-  typedef SparseVector<Scalar,0,Index> ColSpVector;
-  typedef SparseVector<Scalar,RowMajor,Index> RowSpVector;
+  typedef SparseVector<Scalar,0,StorageIndex> ColSpVector;
+  typedef SparseVector<Scalar,RowMajor,StorageIndex> RowSpVector;
 
   Scalar s1 = internal::random<Scalar>();
   Scalar s2 = internal::random<Scalar>();
 
   // test matrix-matrix product
@@ -91,37 +83,128 @@
     VERIFY_IS_APPROX(m4=m2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
 
     VERIFY_IS_APPROX(m4 = m2*m3/s1, refMat4 = refMat2*refMat3/s1);
     VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
     VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1);
+    VERIFY_IS_APPROX(m4 = (m2+m2)*m3, refMat4 = (refMat2+refMat2)*refMat3);
+    VERIFY_IS_APPROX(m4 = m2*m3.leftCols(cols/2), refMat4 = refMat2*refMat3.leftCols(cols/2));
+    VERIFY_IS_APPROX(m4 = m2*(m3+m3).leftCols(cols/2), refMat4 = refMat2*(refMat3+refMat3).leftCols(cols/2));
 
     VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3);
     VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3);
     VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose());
     VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose());
 
+    // make sure the right product implementation is called:
+    if((!SparseMatrixType::IsRowMajor) && m2.rows()<=m3.cols())
+    {
+      VERIFY_EVALUATION_COUNT(m4 = m2*m3, 3); // 1 temp for the result + 2 for transposing and get a sorted result.
+      VERIFY_EVALUATION_COUNT(m4 = (m2*m3).pruned(0), 1);
+      VERIFY_EVALUATION_COUNT(m4 = (m2*m3).eval().pruned(0), 4);
+    }
+
+    // and that pruning is effective:
+    {
+      DenseMatrix Ad(2,2);
+      Ad << -1, 1, 1, 1;
+      SparseMatrixType As(Ad.sparseView()), B(2,2);
+      VERIFY_IS_EQUAL( (As*As.transpose()).eval().nonZeros(), 4);
+      VERIFY_IS_EQUAL( (Ad*Ad.transpose()).eval().sparseView().eval().nonZeros(), 2);
+      VERIFY_IS_EQUAL( (As*As.transpose()).pruned(1e-6).eval().nonZeros(), 2);
+    }
+
+    // dense ?= sparse * sparse
+    VERIFY_IS_APPROX(dm4 =m2*m3, refMat4 =refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4+=m2*m3, refMat4+=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4-=m2*m3, refMat4-=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4 =m2t.transpose()*m3, refMat4 =refMat2t.transpose()*refMat3);
+    VERIFY_IS_APPROX(dm4+=m2t.transpose()*m3, refMat4+=refMat2t.transpose()*refMat3);
+    VERIFY_IS_APPROX(dm4-=m2t.transpose()*m3, refMat4-=refMat2t.transpose()*refMat3);
+    VERIFY_IS_APPROX(dm4 =m2t.transpose()*m3t.transpose(), refMat4 =refMat2t.transpose()*refMat3t.transpose());
+    VERIFY_IS_APPROX(dm4+=m2t.transpose()*m3t.transpose(), refMat4+=refMat2t.transpose()*refMat3t.transpose());
+    VERIFY_IS_APPROX(dm4-=m2t.transpose()*m3t.transpose(), refMat4-=refMat2t.transpose()*refMat3t.transpose());
+    VERIFY_IS_APPROX(dm4 =m2*m3t.transpose(), refMat4 =refMat2*refMat3t.transpose());
+    VERIFY_IS_APPROX(dm4+=m2*m3t.transpose(), refMat4+=refMat2*refMat3t.transpose());
+    VERIFY_IS_APPROX(dm4-=m2*m3t.transpose(), refMat4-=refMat2*refMat3t.transpose());
+    VERIFY_IS_APPROX(dm4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
+
     // test aliasing
     m4 = m2; refMat4 = refMat2;
     VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3);
 
-    // sparse * dense
+    // sparse * dense matrix
     VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
     VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose());
     VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3, refMat4=refMat2t.transpose()*refMat3);
     VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
 
+    VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4=dm4+m2*refMat3, refMat4=refMat4+refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4+=m2*refMat3, refMat4+=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4-=m2*refMat3, refMat4-=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4.noalias()+=m2*refMat3, refMat4+=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4.noalias()-=m2*refMat3, refMat4-=refMat2*refMat3);
     VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3));
     VERIFY_IS_APPROX(dm4=m2t.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2t.transpose()*(refMat3+refMat5)*0.5);
+    
+    // sparse * dense vector
+    VERIFY_IS_APPROX(dm4.col(0)=m2*refMat3.col(0), refMat4.col(0)=refMat2*refMat3.col(0));
+    VERIFY_IS_APPROX(dm4.col(0)=m2*refMat3t.transpose().col(0), refMat4.col(0)=refMat2*refMat3t.transpose().col(0));
+    VERIFY_IS_APPROX(dm4.col(0)=m2t.transpose()*refMat3.col(0), refMat4.col(0)=refMat2t.transpose()*refMat3.col(0));
+    VERIFY_IS_APPROX(dm4.col(0)=m2t.transpose()*refMat3t.transpose().col(0), refMat4.col(0)=refMat2t.transpose()*refMat3t.transpose().col(0));
 
     // dense * sparse
     VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4=dm4+refMat2*m3, refMat4=refMat4+refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4+=refMat2*m3, refMat4+=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4-=refMat2*m3, refMat4-=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4.noalias()+=refMat2*m3, refMat4+=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4.noalias()-=refMat2*m3, refMat4-=refMat2*refMat3);
     VERIFY_IS_APPROX(dm4=refMat2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
     VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
     VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
 
     // sparse * dense and dense * sparse outer product
-    test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4);
+    {
+      Index c  = internal::random<Index>(0,depth-1);
+      Index r  = internal::random<Index>(0,rows-1);
+      Index c1 = internal::random<Index>(0,cols-1);
+      Index r1 = internal::random<Index>(0,depth-1);
+      DenseMatrix dm5  = DenseMatrix::Random(depth, cols);
+
+      VERIFY_IS_APPROX( m4=m2.col(c)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose());
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX( m4=m2.middleCols(c,1)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose());
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX(dm4=m2.col(c)*dm5.col(c1).transpose(), refMat4=refMat2.col(c)*dm5.col(c1).transpose());
+      
+      VERIFY_IS_APPROX(m4=dm5.col(c1)*m2.col(c).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose());
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX(m4=dm5.col(c1)*m2.middleCols(c,1).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose());
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX(dm4=dm5.col(c1)*m2.col(c).transpose(), refMat4=dm5.col(c1)*refMat2.col(c).transpose());
+
+      VERIFY_IS_APPROX( m4=dm5.row(r1).transpose()*m2.col(c).transpose(), refMat4=dm5.row(r1).transpose()*refMat2.col(c).transpose());
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX(dm4=dm5.row(r1).transpose()*m2.col(c).transpose(), refMat4=dm5.row(r1).transpose()*refMat2.col(c).transpose());
+
+      VERIFY_IS_APPROX( m4=m2.row(r).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose());
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX( m4=m2.middleRows(r,1).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose());
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX(dm4=m2.row(r).transpose()*dm5.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*dm5.col(c1).transpose());
+
+      VERIFY_IS_APPROX( m4=dm5.col(c1)*m2.row(r), refMat4=dm5.col(c1)*refMat2.row(r));
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX( m4=dm5.col(c1)*m2.middleRows(r,1), refMat4=dm5.col(c1)*refMat2.row(r));
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX(dm4=dm5.col(c1)*m2.row(r), refMat4=dm5.col(c1)*refMat2.row(r));
+
+      VERIFY_IS_APPROX( m4=dm5.row(r1).transpose()*m2.row(r), refMat4=dm5.row(r1).transpose()*refMat2.row(r));
+      VERIFY_IS_EQUAL(m4.nonZeros(), (refMat4.array()!=0).count());
+      VERIFY_IS_APPROX(dm4=dm5.row(r1).transpose()*m2.row(r), refMat4=dm5.row(r1).transpose()*refMat2.row(r));
+    }
 
     VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6);
     
     // sparse matrix * sparse vector
     ColSpVector cv0(cols), cv1;
@@ -129,15 +212,15 @@
     initSparse(2*density,dcv0, cv0);
     
     RowSpVector rv0(depth), rv1;
     RowDenseVector drv0(depth), drv1(rv1);
     initSparse(2*density,drv0, rv0);
-    
-    VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
+
+    VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);    
     VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3);
-    VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);
     VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0);
+    VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
     VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0);
   }
   
   // test matrix - diagonal product
   {
@@ -156,35 +239,42 @@
     VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1*refM2.transpose());
     
     // also check with a SparseWrapper:
     DenseVector v1 = DenseVector::Random(cols);
     DenseVector v2 = DenseVector::Random(rows);
+    DenseVector v3 = DenseVector::Random(rows);
     VERIFY_IS_APPROX(m3=m2*v1.asDiagonal(), refM3=refM2*v1.asDiagonal());
     VERIFY_IS_APPROX(m3=m2.transpose()*v2.asDiagonal(), refM3=refM2.transpose()*v2.asDiagonal());
     VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2, refM3=v2.asDiagonal()*refM2);
     VERIFY_IS_APPROX(m3=v1.asDiagonal()*m2.transpose(), refM3=v1.asDiagonal()*refM2.transpose());
     
     VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2*v1.asDiagonal(), refM3=v2.asDiagonal()*refM2*v1.asDiagonal());
+
+    VERIFY_IS_APPROX(v2=m2*v1.asDiagonal()*v1, refM2*v1.asDiagonal()*v1);
+    VERIFY_IS_APPROX(v3=v2.asDiagonal()*m2*v1, v2.asDiagonal()*refM2*v1);
     
     // evaluate to a dense matrix to check the .row() and .col() iterator functions
     VERIFY_IS_APPROX(d3=m2*d1, refM3=refM2*d1);
     VERIFY_IS_APPROX(d3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
     VERIFY_IS_APPROX(d3=d2*m2, refM3=d2*refM2);
     VERIFY_IS_APPROX(d3=d1*m2.transpose(), refM3=d1*refM2.transpose());
   }
 
-  // test self adjoint products
+  // test self-adjoint and triangular-view products
   {
     DenseMatrix b = DenseMatrix::Random(rows, rows);
     DenseMatrix x = DenseMatrix::Random(rows, rows);
     DenseMatrix refX = DenseMatrix::Random(rows, rows);
     DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
     DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
     DenseMatrix refS = DenseMatrix::Zero(rows, rows);
+    DenseMatrix refA = DenseMatrix::Zero(rows, rows);
     SparseMatrixType mUp(rows, rows);
     SparseMatrixType mLo(rows, rows);
     SparseMatrixType mS(rows, rows);
+    SparseMatrixType mA(rows, rows);
+    initSparse<Scalar>(density, refA, mA);
     do {
       initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
     } while (refUp.isZero());
     refLo = refUp.adjoint();
     mLo = mUp.adjoint();
@@ -193,30 +283,49 @@
     mS = mUp + mLo;
     // TODO be able to address the diagonal....
     for (int k=0; k<mS.outerSize(); ++k)
       for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
         if (it.index() == k)
-          it.valueRef() *= 0.5;
+          it.valueRef() *= Scalar(0.5);
 
     VERIFY_IS_APPROX(refS.adjoint(), refS);
     VERIFY_IS_APPROX(mS.adjoint(), mS);
     VERIFY_IS_APPROX(mS, refS);
     VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
 
+    // sparse selfadjointView with dense matrices
     VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b);
     VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b);
     VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b);
+
+    VERIFY_IS_APPROX(x=b * mUp.template selfadjointView<Upper>(),       refX=b*refS);
+    VERIFY_IS_APPROX(x=b * mLo.template selfadjointView<Lower>(),       refX=b*refS);
+    VERIFY_IS_APPROX(x=b * mS.template selfadjointView<Upper|Lower>(),  refX=b*refS);
+
+    VERIFY_IS_APPROX(x.noalias()+=mUp.template selfadjointView<Upper>()*b, refX+=refS*b);
+    VERIFY_IS_APPROX(x.noalias()-=mLo.template selfadjointView<Lower>()*b, refX-=refS*b);
+    VERIFY_IS_APPROX(x.noalias()+=mS.template selfadjointView<Upper|Lower>()*b, refX+=refS*b);
     
-    // sparse selfadjointView * sparse 
+    // sparse selfadjointView with sparse matrices
     SparseMatrixType mSres(rows,rows);
     VERIFY_IS_APPROX(mSres = mLo.template selfadjointView<Lower>()*mS,
                      refX = refLo.template selfadjointView<Lower>()*refS);
-    // sparse * sparse selfadjointview
     VERIFY_IS_APPROX(mSres = mS * mLo.template selfadjointView<Lower>(),
                      refX = refS * refLo.template selfadjointView<Lower>());
+    
+    // sparse triangularView with dense matrices
+    VERIFY_IS_APPROX(x=mA.template triangularView<Upper>()*b, refX=refA.template triangularView<Upper>()*b);
+    VERIFY_IS_APPROX(x=mA.template triangularView<Lower>()*b, refX=refA.template triangularView<Lower>()*b);
+    VERIFY_IS_APPROX(x=b*mA.template triangularView<Upper>(), refX=b*refA.template triangularView<Upper>());
+    VERIFY_IS_APPROX(x=b*mA.template triangularView<Lower>(), refX=b*refA.template triangularView<Lower>());
+    
+    // sparse triangularView with sparse matrices
+    VERIFY_IS_APPROX(mSres = mA.template triangularView<Lower>()*mS,   refX = refA.template triangularView<Lower>()*refS);
+    VERIFY_IS_APPROX(mSres = mS * mA.template triangularView<Lower>(), refX = refS * refA.template triangularView<Lower>());
+    VERIFY_IS_APPROX(mSres = mA.template triangularView<Upper>()*mS,   refX = refA.template triangularView<Upper>()*refS);
+    VERIFY_IS_APPROX(mSres = mS * mA.template triangularView<Upper>(), refX = refS * refA.template triangularView<Upper>());
   }
-  
 }
 
 // New test for Bug in SparseTimeDenseProduct
 template<typename SparseMatrixType, typename DenseMatrixType> void sparse_product_regression_test()
 {
@@ -236,17 +345,41 @@
   sm2.setZero();
   DenseMatrixType m4(sm2*m2);
 
   VERIFY_IS_APPROX( m4(0,0), 0.0 );
 }
+
+template<typename Scalar>
+void bug_942()
+{
+  typedef Matrix<Scalar, Dynamic, 1>     Vector;
+  typedef SparseMatrix<Scalar, ColMajor> ColSpMat;
+  typedef SparseMatrix<Scalar, RowMajor> RowSpMat;
+  ColSpMat cmA(1,1);
+  cmA.insert(0,0) = 1;
+
+  RowSpMat rmA(1,1);
+  rmA.insert(0,0) = 1;
+
+  Vector d(1);
+  d[0] = 2;
+  
+  double res = 2;
+  
+  VERIFY_IS_APPROX( ( cmA*d.asDiagonal() ).eval().coeff(0,0), res );
+  VERIFY_IS_APPROX( ( d.asDiagonal()*rmA ).eval().coeff(0,0), res );
+  VERIFY_IS_APPROX( ( rmA*d.asDiagonal() ).eval().coeff(0,0), res );
+  VERIFY_IS_APPROX( ( d.asDiagonal()*cmA ).eval().coeff(0,0), res );
+}
 
 void test_sparse_product()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,ColMajor> >()) );
     CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,RowMajor> >()) );
+    CALL_SUBTEST_1( (bug_942<double>()) );
     CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, ColMajor > >()) );
     CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, RowMajor > >()) );
     CALL_SUBTEST_3( (sparse_product<SparseMatrix<float,ColMajor,long int> >()) );
     CALL_SUBTEST_4( (sparse_product_regression_test<SparseMatrix<double,RowMajor>, Matrix<double, Dynamic, Dynamic, RowMajor> >()) );
   }
 }

ADDED   3rd_party/eigen/test/sparse_ref.cpp
Index: 3rd_party/eigen/test/sparse_ref.cpp
==================================================================
--- 3rd_party/eigen/test/sparse_ref.cpp
+++ 3rd_party/eigen/test/sparse_ref.cpp
@@ -0,0 +1,139 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 20015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+// This unit test cannot be easily written to work with EIGEN_DEFAULT_TO_ROW_MAJOR
+#ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
+#undef EIGEN_DEFAULT_TO_ROW_MAJOR
+#endif
+
+static long int nb_temporaries;
+
+inline void on_temporary_creation() {
+  // here's a great place to set a breakpoint when debugging failures in this test!
+  nb_temporaries++;
+}
+
+#define EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN { on_temporary_creation(); }
+
+#include "main.h"
+#include <Eigen/SparseCore>
+
+#define VERIFY_EVALUATION_COUNT(XPR,N) {\
+    nb_temporaries = 0; \
+    CALL_SUBTEST( XPR ); \
+    if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
+    VERIFY( (#XPR) && nb_temporaries==N ); \
+  }
+
+template<typename PlainObjectType> void check_const_correctness(const PlainObjectType&)
+{
+  // verify that ref-to-const don't have LvalueBit
+  typedef typename internal::add_const<PlainObjectType>::type ConstPlainObjectType;
+  VERIFY( !(internal::traits<Ref<ConstPlainObjectType> >::Flags & LvalueBit) );
+  VERIFY( !(internal::traits<Ref<ConstPlainObjectType, Aligned> >::Flags & LvalueBit) );
+  VERIFY( !(Ref<ConstPlainObjectType>::Flags & LvalueBit) );
+  VERIFY( !(Ref<ConstPlainObjectType, Aligned>::Flags & LvalueBit) );
+}
+
+template<typename B>
+EIGEN_DONT_INLINE void call_ref_1(Ref<SparseMatrix<float> > a, const B &b) { VERIFY_IS_EQUAL(a.toDense(),b.toDense()); }
+
+template<typename B>
+EIGEN_DONT_INLINE void call_ref_2(const Ref<const SparseMatrix<float> >& a, const B &b) { VERIFY_IS_EQUAL(a.toDense(),b.toDense()); }
+
+template<typename B>
+EIGEN_DONT_INLINE void call_ref_3(const Ref<const SparseMatrix<float>, StandardCompressedFormat>& a, const B &b) {
+  VERIFY(a.isCompressed());
+  VERIFY_IS_EQUAL(a.toDense(),b.toDense());
+}
+
+template<typename B>
+EIGEN_DONT_INLINE void call_ref_4(Ref<SparseVector<float> > a, const B &b) { VERIFY_IS_EQUAL(a.toDense(),b.toDense()); }
+
+template<typename B>
+EIGEN_DONT_INLINE void call_ref_5(const Ref<const SparseVector<float> >& a, const B &b) { VERIFY_IS_EQUAL(a.toDense(),b.toDense()); }
+
+void call_ref()
+{
+  SparseMatrix<float>               A = MatrixXf::Random(10,10).sparseView(0.5,1);
+  SparseMatrix<float,RowMajor>      B = MatrixXf::Random(10,10).sparseView(0.5,1);
+  SparseMatrix<float>               C = MatrixXf::Random(10,10).sparseView(0.5,1);
+  C.reserve(VectorXi::Constant(C.outerSize(), 2));
+  const SparseMatrix<float>&        Ac(A);
+  Block<SparseMatrix<float> >       Ab(A,0,1, 3,3);
+  const Block<SparseMatrix<float> > Abc(A,0,1,3,3);
+  SparseVector<float>               vc =  VectorXf::Random(10).sparseView(0.5,1);
+  SparseVector<float,RowMajor>      vr =  VectorXf::Random(10).sparseView(0.5,1);
+  SparseMatrix<float> AA = A*A;
+  
+
+  VERIFY_EVALUATION_COUNT( call_ref_1(A, A),  0);
+//   VERIFY_EVALUATION_COUNT( call_ref_1(Ac, Ac),  0); // does not compile on purpose
+  VERIFY_EVALUATION_COUNT( call_ref_2(A, A),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_3(A, A),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_2(A.transpose(), A.transpose()),  1);
+  VERIFY_EVALUATION_COUNT( call_ref_3(A.transpose(), A.transpose()),  1);
+  VERIFY_EVALUATION_COUNT( call_ref_2(Ac,Ac), 0);
+  VERIFY_EVALUATION_COUNT( call_ref_3(Ac,Ac), 0);
+  VERIFY_EVALUATION_COUNT( call_ref_2(A+A,2*Ac), 1);
+  VERIFY_EVALUATION_COUNT( call_ref_3(A+A,2*Ac), 1);
+  VERIFY_EVALUATION_COUNT( call_ref_2(B, B),  1);
+  VERIFY_EVALUATION_COUNT( call_ref_3(B, B),  1);
+  VERIFY_EVALUATION_COUNT( call_ref_2(B.transpose(), B.transpose()),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_3(B.transpose(), B.transpose()),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_2(A*A, AA),  3);
+  VERIFY_EVALUATION_COUNT( call_ref_3(A*A, AA),  3);
+  
+  VERIFY(!C.isCompressed());
+  VERIFY_EVALUATION_COUNT( call_ref_3(C, C),  1);
+  
+  Ref<SparseMatrix<float> > Ar(A);
+  VERIFY_IS_APPROX(Ar+Ar, A+A);
+  VERIFY_EVALUATION_COUNT( call_ref_1(Ar, A),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_2(Ar, A),  0);
+  
+  Ref<SparseMatrix<float,RowMajor> > Br(B);
+  VERIFY_EVALUATION_COUNT( call_ref_1(Br.transpose(), Br.transpose()),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_2(Br, Br),  1);
+  VERIFY_EVALUATION_COUNT( call_ref_2(Br.transpose(), Br.transpose()),  0);
+  
+  Ref<const SparseMatrix<float> > Arc(A);
+//   VERIFY_EVALUATION_COUNT( call_ref_1(Arc, Arc),  0); // does not compile on purpose
+  VERIFY_EVALUATION_COUNT( call_ref_2(Arc, Arc),  0);
+  
+  VERIFY_EVALUATION_COUNT( call_ref_2(A.middleCols(1,3), A.middleCols(1,3)),  0);
+  
+  VERIFY_EVALUATION_COUNT( call_ref_2(A.col(2), A.col(2)),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_2(vc, vc),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_2(vr.transpose(), vr.transpose()),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_2(vr, vr.transpose()),  0);
+  
+  VERIFY_EVALUATION_COUNT( call_ref_2(A.block(1,1,3,3), A.block(1,1,3,3)),  1); // should be 0 (allocate starts/nnz only)
+
+  VERIFY_EVALUATION_COUNT( call_ref_4(vc, vc),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_4(vr, vr.transpose()),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_5(vc, vc),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_5(vr, vr.transpose()),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_4(A.col(2), A.col(2)),  0);
+  VERIFY_EVALUATION_COUNT( call_ref_5(A.col(2), A.col(2)),  0);
+  // VERIFY_EVALUATION_COUNT( call_ref_4(A.row(2), A.row(2).transpose()),  1); // does not compile on purpose
+  VERIFY_EVALUATION_COUNT( call_ref_5(A.row(2), A.row(2).transpose()),  1);
+}
+
+void test_sparse_ref()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( check_const_correctness(SparseMatrix<float>()) );
+    CALL_SUBTEST_1( check_const_correctness(SparseMatrix<double,RowMajor>()) );
+    CALL_SUBTEST_2( call_ref() );
+
+    CALL_SUBTEST_3( check_const_correctness(SparseVector<float>()) );
+    CALL_SUBTEST_3( check_const_correctness(SparseVector<double,RowMajor>()) );
+  }
+}

Index: 3rd_party/eigen/test/sparse_solver.h
==================================================================
--- 3rd_party/eigen/test/sparse_solver.h
+++ 3rd_party/eigen/test/sparse_solver.h
@@ -7,106 +7,171 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "sparse.h"
 #include <Eigen/SparseCore>
+#include <sstream>
+
+template<typename Solver, typename Rhs, typename Guess,typename Result>
+void solve_with_guess(IterativeSolverBase<Solver>& solver, const MatrixBase<Rhs>& b, const Guess& g, Result &x) {
+  if(internal::random<bool>())
+  {
+    // With a temporary through evaluator<SolveWithGuess>
+    x = solver.derived().solveWithGuess(b,g) + Result::Zero(x.rows(), x.cols());
+  }
+  else
+  {
+    // direct evaluation within x through Assignment<Result,SolveWithGuess>
+    x = solver.derived().solveWithGuess(b.derived(),g);
+  }
+}
+
+template<typename Solver, typename Rhs, typename Guess,typename Result>
+void solve_with_guess(SparseSolverBase<Solver>& solver, const MatrixBase<Rhs>& b, const Guess& , Result& x) {
+  if(internal::random<bool>())
+    x = solver.derived().solve(b) + Result::Zero(x.rows(), x.cols());
+  else
+    x = solver.derived().solve(b);
+}
+
+template<typename Solver, typename Rhs, typename Guess,typename Result>
+void solve_with_guess(SparseSolverBase<Solver>& solver, const SparseMatrixBase<Rhs>& b, const Guess& , Result& x) {
+  x = solver.derived().solve(b);
+}
 
 template<typename Solver, typename Rhs, typename DenseMat, typename DenseRhs>
 void check_sparse_solving(Solver& solver, const typename Solver::MatrixType& A, const Rhs& b, const DenseMat& dA, const DenseRhs& db)
 {
   typedef typename Solver::MatrixType Mat;
   typedef typename Mat::Scalar Scalar;
+  typedef typename Mat::StorageIndex StorageIndex;
 
-  DenseRhs refX = dA.lu().solve(db);
+  DenseRhs refX = dA.householderQr().solve(db);
   {
-    Rhs x(b.rows(), b.cols());
+    Rhs x(A.cols(), b.cols());
     Rhs oldb = b;
 
     solver.compute(A);
     if (solver.info() != Success)
     {
-      std::cerr << "sparse solver testing: factorization failed (check_sparse_solving)\n";
-      exit(0);
-      return;
+      std::cerr << "ERROR | sparse solver testing, factorization failed (" << typeid(Solver).name() << ")\n";
+      VERIFY(solver.info() == Success);
     }
     x = solver.solve(b);
     if (solver.info() != Success)
     {
-      std::cerr << "sparse solver testing: solving failed\n";
+      std::cerr << "WARNING | sparse solver testing: solving failed (" << typeid(Solver).name() << ")\n";
       return;
     }
     VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!");
+    VERIFY(x.isApprox(refX,test_precision<Scalar>()));
 
+    x.setZero();
+    solve_with_guess(solver, b, x, x);
+    VERIFY(solver.info() == Success && "solving failed when using analyzePattern/factorize API");
+    VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!");
     VERIFY(x.isApprox(refX,test_precision<Scalar>()));
+    
     x.setZero();
     // test the analyze/factorize API
     solver.analyzePattern(A);
     solver.factorize(A);
-    if (solver.info() != Success)
-    {
-      std::cerr << "sparse solver testing: factorization failed (check_sparse_solving)\n";
-      exit(0);
-      return;
-    }
+    VERIFY(solver.info() == Success && "factorization failed when using analyzePattern/factorize API");
     x = solver.solve(b);
-    if (solver.info() != Success)
-    {
-      std::cerr << "sparse solver testing: solving failed\n";
-      return;
-    }
+    VERIFY(solver.info() == Success && "solving failed when using analyzePattern/factorize API");
     VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!");
-
-    VERIFY(x.isApprox(refX,test_precision<Scalar>()));
-  }
-  
-  // test dense Block as the result and rhs:
-  {
-    DenseRhs x(db.rows(), db.cols());
-    DenseRhs oldb(db);
-    x.setZero();
-    x.block(0,0,x.rows(),x.cols()) = solver.solve(db.block(0,0,db.rows(),db.cols()));
-    VERIFY(oldb.isApprox(db) && "sparse solver testing: the rhs should not be modified!");
-    VERIFY(x.isApprox(refX,test_precision<Scalar>()));
+    VERIFY(x.isApprox(refX,test_precision<Scalar>()));
+    
+    x.setZero();
+    // test with Map
+    MappedSparseMatrix<Scalar,Mat::Options,StorageIndex> Am(A.rows(), A.cols(), A.nonZeros(), const_cast<StorageIndex*>(A.outerIndexPtr()), const_cast<StorageIndex*>(A.innerIndexPtr()), const_cast<Scalar*>(A.valuePtr()));
+    solver.compute(Am);
+    VERIFY(solver.info() == Success && "factorization failed when using Map");
+    DenseRhs dx(refX);
+    dx.setZero();
+    Map<DenseRhs> xm(dx.data(), dx.rows(), dx.cols());
+    Map<const DenseRhs> bm(db.data(), db.rows(), db.cols());
+    xm = solver.solve(bm);
+    VERIFY(solver.info() == Success && "solving failed when using Map");
+    VERIFY(oldb.isApprox(bm) && "sparse solver testing: the rhs should not be modified!");
+    VERIFY(xm.isApprox(refX,test_precision<Scalar>()));
+  }
+  
+  // if not too large, do some extra check:
+  if(A.rows()<2000)
+  {
+    // test initialization ctor
+    {
+      Rhs x(b.rows(), b.cols());
+      Solver solver2(A);
+      VERIFY(solver2.info() == Success);
+      x = solver2.solve(b);
+      VERIFY(x.isApprox(refX,test_precision<Scalar>()));
+    }
+
+    // test dense Block as the result and rhs:
+    {
+      DenseRhs x(refX.rows(), refX.cols());
+      DenseRhs oldb(db);
+      x.setZero();
+      x.block(0,0,x.rows(),x.cols()) = solver.solve(db.block(0,0,db.rows(),db.cols()));
+      VERIFY(oldb.isApprox(db) && "sparse solver testing: the rhs should not be modified!");
+      VERIFY(x.isApprox(refX,test_precision<Scalar>()));
+    }
+
+    // test uncompressed inputs
+    {
+      Mat A2 = A;
+      A2.reserve((ArrayXf::Random(A.outerSize())+2).template cast<typename Mat::StorageIndex>().eval());
+      solver.compute(A2);
+      Rhs x = solver.solve(b);
+      VERIFY(x.isApprox(refX,test_precision<Scalar>()));
+    }
+
+    // test expression as input
+    {
+      solver.compute(0.5*(A+A));
+      Rhs x = solver.solve(b);
+      VERIFY(x.isApprox(refX,test_precision<Scalar>()));
+
+      Solver solver2(0.5*(A+A));
+      Rhs x2 = solver2.solve(b);
+      VERIFY(x2.isApprox(refX,test_precision<Scalar>()));
+    }
   }
 }
 
 template<typename Solver, typename Rhs>
-void check_sparse_solving_real_cases(Solver& solver, const typename Solver::MatrixType& A, const Rhs& b, const Rhs& refX)
+void check_sparse_solving_real_cases(Solver& solver, const typename Solver::MatrixType& A, const Rhs& b, const typename Solver::MatrixType& fullA, const Rhs& refX)
 {
   typedef typename Solver::MatrixType Mat;
   typedef typename Mat::Scalar Scalar;
   typedef typename Mat::RealScalar RealScalar;
   
-  Rhs x(b.rows(), b.cols());
-  
-  solver.compute(A);
-  if (solver.info() != Success)
-  {
-    std::cerr << "sparse solver testing: factorization failed (check_sparse_solving_real_cases)\n";
-    exit(0);
-    return;
-  }
-  x = solver.solve(b);
-  if (solver.info() != Success)
-  {
-    std::cerr << "sparse solver testing: solving failed\n";
-    return;
-  }
-  
-  RealScalar res_error;
-  // Compute the norm of the relative error
-  if(refX.size() != 0)
-    res_error = (refX - x).norm()/refX.norm();
-  else
-  { 
-    // Compute the relative residual norm
-    res_error = (b - A * x).norm()/b.norm();
-  }
-  if (res_error > test_precision<Scalar>() ){
-    std::cerr << "Test " << g_test_stack.back() << " failed in "EI_PP_MAKE_STRING(__FILE__) 
-    << " (" << EI_PP_MAKE_STRING(__LINE__) << ")" << std::endl << std::endl;
-    abort();
+  Rhs x(A.cols(), b.cols());
+
+  solver.compute(A);
+  if (solver.info() != Success)
+  {
+    std::cerr << "ERROR | sparse solver testing, factorization failed (" << typeid(Solver).name() << ")\n";
+    VERIFY(solver.info() == Success);
+  }
+  x = solver.solve(b);
+  
+  if (solver.info() != Success)
+  {
+    std::cerr << "WARNING | sparse solver testing, solving failed (" << typeid(Solver).name() << ")\n";
+    return;
+  }
+  
+  RealScalar res_error = (fullA*x-b).norm()/b.norm();  
+  VERIFY( (res_error <= test_precision<Scalar>() ) && "sparse solver failed without noticing it"); 
+
+  
+  if(refX.size() != 0 && (refX - x).norm()/refX.norm() > test_precision<Scalar>())
+  {
+    std::cerr << "WARNING | found solution is different from the provided reference one\n";
   }
   
 }
 template<typename Solver, typename DenseMat>
 void check_sparse_determinant(Solver& solver, const typename Solver::MatrixType& A, const DenseMat& dA)
@@ -115,11 +180,11 @@
   typedef typename Mat::Scalar Scalar;
   
   solver.compute(A);
   if (solver.info() != Success)
   {
-    std::cerr << "sparse solver testing: factorization failed (check_sparse_determinant)\n";
+    std::cerr << "WARNING | sparse solver testing: factorization failed (check_sparse_determinant)\n";
     return;
   }
 
   Scalar refDet = dA.determinant();
   VERIFY_IS_APPROX(refDet,solver.determinant());
@@ -132,11 +197,11 @@
   typedef typename Mat::Scalar Scalar;
   
   solver.compute(A);
   if (solver.info() != Success)
   {
-    std::cerr << "sparse solver testing: factorization failed (check_sparse_abs_determinant)\n";
+    std::cerr << "WARNING | sparse solver testing: factorization failed (check_sparse_abs_determinant)\n";
     return;
   }
 
   Scalar refDet = abs(dA.determinant());
   VERIFY_IS_APPROX(refDet,solver.absDeterminant());
@@ -159,11 +224,14 @@
 
   A = M * M.adjoint();
   dA = dM * dM.adjoint();
   
   halfA.resize(size,size);
-  halfA.template selfadjointView<Solver::UpLo>().rankUpdate(M);
+  if(Solver::UpLo==(Lower|Upper))
+    halfA = A;
+  else
+    halfA.template selfadjointView<Solver::UpLo>().rankUpdate(M);
   
   return size;
 }
 
 
@@ -176,40 +244,64 @@
     mat_folder  = mat_folder + static_cast<std::string>("/complex/");
   else
     mat_folder = mat_folder + static_cast<std::string>("/real/");
   return mat_folder;
 }
+std::string sym_to_string(int sym)
+{
+  if(sym==Symmetric) return "Symmetric ";
+  if(sym==SPD)       return "SPD ";
+  return "";
+}
+template<typename Derived>
+std::string solver_stats(const IterativeSolverBase<Derived> &solver)
+{
+  std::stringstream ss;
+  ss << solver.iterations() << " iters, error: " << solver.error();
+  return ss.str();
+}
+template<typename Derived>
+std::string solver_stats(const SparseSolverBase<Derived> &/*solver*/)
+{
+  return "";
+}
 #endif
 
-template<typename Solver> void check_sparse_spd_solving(Solver& solver)
+template<typename Solver> void check_sparse_spd_solving(Solver& solver, int maxSize = 300, int maxRealWorldSize = 100000)
 {
   typedef typename Solver::MatrixType Mat;
   typedef typename Mat::Scalar Scalar;
-  typedef SparseMatrix<Scalar,ColMajor> SpMat;
+  typedef typename Mat::StorageIndex StorageIndex;
+  typedef SparseMatrix<Scalar,ColMajor, StorageIndex> SpMat;
+  typedef SparseVector<Scalar, 0, StorageIndex> SpVec;
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
   typedef Matrix<Scalar,Dynamic,1> DenseVector;
 
   // generate the problem
   Mat A, halfA;
   DenseMatrix dA;
   for (int i = 0; i < g_repeat; i++) {
-    int size = generate_sparse_spd_problem(solver, A, halfA, dA);
+    int size = generate_sparse_spd_problem(solver, A, halfA, dA, maxSize);
 
     // generate the right hand sides
     int rhsCols = internal::random<int>(1,16);
     double density = (std::max)(8./(size*rhsCols), 0.1);
     SpMat B(size,rhsCols);
     DenseVector b = DenseVector::Random(size);
     DenseMatrix dB(size,rhsCols);
     initSparse<Scalar>(density, dB, B, ForceNonZeroDiag);
+    SpVec c = B.col(0);
+    DenseVector dc = dB.col(0);
   
-    check_sparse_solving(solver, A,     b,  dA, b);
-    check_sparse_solving(solver, halfA, b,  dA, b);
-    check_sparse_solving(solver, A,     dB, dA, dB);
-    check_sparse_solving(solver, halfA, dB, dA, dB);
-    check_sparse_solving(solver, A,     B,  dA, dB);
-    check_sparse_solving(solver, halfA, B,  dA, dB);
+    CALL_SUBTEST( check_sparse_solving(solver, A,     b,  dA, b)  );
+    CALL_SUBTEST( check_sparse_solving(solver, halfA, b,  dA, b)  );
+    CALL_SUBTEST( check_sparse_solving(solver, A,     dB, dA, dB) );
+    CALL_SUBTEST( check_sparse_solving(solver, halfA, dB, dA, dB) );
+    CALL_SUBTEST( check_sparse_solving(solver, A,     B,  dA, dB) );
+    CALL_SUBTEST( check_sparse_solving(solver, halfA, B,  dA, dB) );
+    CALL_SUBTEST( check_sparse_solving(solver, A,     c,  dA, dc) );
+    CALL_SUBTEST( check_sparse_solving(solver, halfA, c,  dA, dc) );
     
     // check only once
     if(i==0)
     {
       b = DenseVector::Zero(size);
@@ -216,29 +308,48 @@
       check_sparse_solving(solver, A, b, dA, b);
     }
   }
   
   // First, get the folder 
-#ifdef TEST_REAL_CASES  
-  if (internal::is_same<Scalar, float>::value 
-      || internal::is_same<Scalar, std::complex<float> >::value)
-    return ;
-  
-  std::string mat_folder = get_matrixfolder<Scalar>();
-  MatrixMarketIterator<Scalar> it(mat_folder);
-  for (; it; ++it)
-  {
-    if (it.sym() == SPD){
-      Mat halfA;
-      PermutationMatrix<Dynamic, Dynamic, Index> pnull;
-      halfA.template selfadjointView<Solver::UpLo>() = it.matrix().template triangularView<Eigen::Lower>().twistedBy(pnull);
-      
-      std::cout<< " ==== SOLVING WITH MATRIX " << it.matname() << " ==== \n";
-      check_sparse_solving_real_cases(solver, it.matrix(), it.rhs(), it.refX());
-      check_sparse_solving_real_cases(solver, halfA, it.rhs(), it.refX());
-    }
-  }
+#ifdef TEST_REAL_CASES
+  // Test real problems with double precision only
+  if (internal::is_same<typename NumTraits<Scalar>::Real, double>::value)
+  {
+    std::string mat_folder = get_matrixfolder<Scalar>();
+    MatrixMarketIterator<Scalar> it(mat_folder);
+    for (; it; ++it)
+    {
+      if (it.sym() == SPD){
+        A = it.matrix();
+        if(A.diagonal().size() <= maxRealWorldSize)
+        {
+          DenseVector b = it.rhs();
+          DenseVector refX = it.refX();
+          PermutationMatrix<Dynamic, Dynamic, StorageIndex> pnull;
+          halfA.resize(A.rows(), A.cols());
+          if(Solver::UpLo == (Lower|Upper))
+            halfA = A;
+          else
+            halfA.template selfadjointView<Solver::UpLo>() = A.template triangularView<Eigen::Lower>().twistedBy(pnull);
+          
+          std::cout << "INFO | Testing " << sym_to_string(it.sym()) << "sparse problem " << it.matname()
+                  << " (" << A.rows() << "x" << A.cols() << ") using " << typeid(Solver).name() << "..." << std::endl;
+          CALL_SUBTEST( check_sparse_solving_real_cases(solver, A,     b, A, refX) );
+          std::string stats = solver_stats(solver);
+          if(stats.size()>0)
+            std::cout << "INFO |  " << stats << std::endl;
+          CALL_SUBTEST( check_sparse_solving_real_cases(solver, halfA, b, A, refX) );
+        }
+        else
+        {
+          std::cout << "INFO | Skip sparse problem \"" << it.matname() << "\" (too large)" << std::endl;
+        }
+      }
+    }
+  }
+#else
+  EIGEN_UNUSED_VARIABLE(maxRealWorldSize);
 #endif
 }
 
 template<typename Solver> void check_sparse_spd_determinant(Solver& solver)
 {
@@ -256,89 +367,134 @@
     check_sparse_determinant(solver, halfA, dA );
   }
 }
 
 template<typename Solver, typename DenseMat>
-int generate_sparse_square_problem(Solver&, typename Solver::MatrixType& A, DenseMat& dA, int maxSize = 300)
+Index generate_sparse_square_problem(Solver&, typename Solver::MatrixType& A, DenseMat& dA, int maxSize = 300, int options = ForceNonZeroDiag)
 {
   typedef typename Solver::MatrixType Mat;
   typedef typename Mat::Scalar Scalar;
 
-  int size = internal::random<int>(1,maxSize);
+  Index size = internal::random<int>(1,maxSize);
   double density = (std::max)(8./(size*size), 0.01);
   
   A.resize(size,size);
   dA.resize(size,size);
 
-  initSparse<Scalar>(density, dA, A, ForceNonZeroDiag);
+  initSparse<Scalar>(density, dA, A, options);
   
   return size;
 }
 
-template<typename Solver> void check_sparse_square_solving(Solver& solver)
+
+struct prune_column {
+  Index m_col;
+  prune_column(Index col) : m_col(col) {}
+  template<class Scalar>
+  bool operator()(Index, Index col, const Scalar&) const {
+    return col != m_col;
+  }
+};
+
+
+template<typename Solver> void check_sparse_square_solving(Solver& solver, int maxSize = 300, int maxRealWorldSize = 100000, bool checkDeficient = false)
 {
   typedef typename Solver::MatrixType Mat;
   typedef typename Mat::Scalar Scalar;
-  typedef SparseMatrix<Scalar,ColMajor> SpMat;
+  typedef SparseMatrix<Scalar,ColMajor, typename Mat::StorageIndex> SpMat;
+  typedef SparseVector<Scalar, 0, typename Mat::StorageIndex> SpVec;
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
   typedef Matrix<Scalar,Dynamic,1> DenseVector;
 
   int rhsCols = internal::random<int>(1,16);
 
   Mat A;
   DenseMatrix dA;
   for (int i = 0; i < g_repeat; i++) {
-    int size = generate_sparse_square_problem(solver, A, dA);
+    Index size = generate_sparse_square_problem(solver, A, dA, maxSize);
 
     A.makeCompressed();
     DenseVector b = DenseVector::Random(size);
     DenseMatrix dB(size,rhsCols);
     SpMat B(size,rhsCols);
     double density = (std::max)(8./(size*rhsCols), 0.1);
     initSparse<Scalar>(density, dB, B, ForceNonZeroDiag);
     B.makeCompressed();
-    check_sparse_solving(solver, A, b,  dA, b);
-    check_sparse_solving(solver, A, dB, dA, dB);
-    check_sparse_solving(solver, A, B,  dA, dB);
+    SpVec c = B.col(0);
+    DenseVector dc = dB.col(0);
+    CALL_SUBTEST(check_sparse_solving(solver, A, b,  dA, b));
+    CALL_SUBTEST(check_sparse_solving(solver, A, dB, dA, dB));
+    CALL_SUBTEST(check_sparse_solving(solver, A, B,  dA, dB));
+    CALL_SUBTEST(check_sparse_solving(solver, A, c,  dA, dc));
     
     // check only once
     if(i==0)
     {
       b = DenseVector::Zero(size);
       check_sparse_solving(solver, A, b, dA, b);
     }
+    // regression test for Bug 792 (structurally rank deficient matrices):
+    if(checkDeficient && size>1) {
+      Index col = internal::random<int>(0,int(size-1));
+      A.prune(prune_column(col));
+      solver.compute(A);
+      VERIFY_IS_EQUAL(solver.info(), NumericalIssue);
+    }
   }
   
   // First, get the folder 
 #ifdef TEST_REAL_CASES
-  if (internal::is_same<Scalar, float>::value 
-      || internal::is_same<Scalar, std::complex<float> >::value)
-    return ;
-  
-  std::string mat_folder = get_matrixfolder<Scalar>();
-  MatrixMarketIterator<Scalar> it(mat_folder);
-  for (; it; ++it)
-  {
-    std::cout<< " ==== SOLVING WITH MATRIX " << it.matname() << " ==== \n";
-    check_sparse_solving_real_cases(solver, it.matrix(), it.rhs(), it.refX());
-  }
+  // Test real problems with double precision only
+  if (internal::is_same<typename NumTraits<Scalar>::Real, double>::value)
+  {
+    std::string mat_folder = get_matrixfolder<Scalar>();
+    MatrixMarketIterator<Scalar> it(mat_folder);
+    for (; it; ++it)
+    {
+      A = it.matrix();
+      if(A.diagonal().size() <= maxRealWorldSize)
+      {
+        DenseVector b = it.rhs();
+        DenseVector refX = it.refX();
+        std::cout << "INFO | Testing " << sym_to_string(it.sym()) << "sparse problem " << it.matname()
+                  << " (" << A.rows() << "x" << A.cols() << ") using " << typeid(Solver).name() << "..." << std::endl;
+        CALL_SUBTEST(check_sparse_solving_real_cases(solver, A, b, A, refX));
+        std::string stats = solver_stats(solver);
+        if(stats.size()>0)
+          std::cout << "INFO |  " << stats << std::endl;
+      }
+      else
+      {
+        std::cout << "INFO | SKIP sparse problem \"" << it.matname() << "\" (too large)" << std::endl;
+      }
+    }
+  }
+#else
+  EIGEN_UNUSED_VARIABLE(maxRealWorldSize);
 #endif
 
 }
 
 template<typename Solver> void check_sparse_square_determinant(Solver& solver)
 {
   typedef typename Solver::MatrixType Mat;
   typedef typename Mat::Scalar Scalar;
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-
-  // generate the problem
-  Mat A;
-  DenseMatrix dA;
-  generate_sparse_square_problem(solver, A, dA, 30);
-  A.makeCompressed();
+  
   for (int i = 0; i < g_repeat; i++) {
+    // generate the problem
+    Mat A;
+    DenseMatrix dA;
+    
+    int size = internal::random<int>(1,30);
+    dA.setRandom(size,size);
+    
+    dA = (dA.array().abs()<0.3).select(0,dA);
+    dA.diagonal() = (dA.diagonal().array()==0).select(1,dA.diagonal());
+    A = dA.sparseView();
+    A.makeCompressed();
+  
     check_sparse_determinant(solver, A, dA);
   }
 }
 
 template<typename Solver> void check_sparse_square_abs_determinant(Solver& solver)
@@ -345,15 +501,65 @@
 {
   typedef typename Solver::MatrixType Mat;
   typedef typename Mat::Scalar Scalar;
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
 
-  // generate the problem
-  Mat A;
-  DenseMatrix dA;
-  generate_sparse_square_problem(solver, A, dA, 30);
-  A.makeCompressed();
   for (int i = 0; i < g_repeat; i++) {
+    // generate the problem
+    Mat A;
+    DenseMatrix dA;
+    generate_sparse_square_problem(solver, A, dA, 30);
+    A.makeCompressed();
     check_sparse_abs_determinant(solver, A, dA);
   }
 }
 
+template<typename Solver, typename DenseMat>
+void generate_sparse_leastsquare_problem(Solver&, typename Solver::MatrixType& A, DenseMat& dA, int maxSize = 300, int options = ForceNonZeroDiag)
+{
+  typedef typename Solver::MatrixType Mat;
+  typedef typename Mat::Scalar Scalar;
+
+  int rows = internal::random<int>(1,maxSize);
+  int cols = internal::random<int>(1,rows);
+  double density = (std::max)(8./(rows*cols), 0.01);
+  
+  A.resize(rows,cols);
+  dA.resize(rows,cols);
+
+  initSparse<Scalar>(density, dA, A, options);
+}
+
+template<typename Solver> void check_sparse_leastsquare_solving(Solver& solver)
+{
+  typedef typename Solver::MatrixType Mat;
+  typedef typename Mat::Scalar Scalar;
+  typedef SparseMatrix<Scalar,ColMajor, typename Mat::StorageIndex> SpMat;
+  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
+  typedef Matrix<Scalar,Dynamic,1> DenseVector;
+
+  int rhsCols = internal::random<int>(1,16);
+
+  Mat A;
+  DenseMatrix dA;
+  for (int i = 0; i < g_repeat; i++) {
+    generate_sparse_leastsquare_problem(solver, A, dA);
+
+    A.makeCompressed();
+    DenseVector b = DenseVector::Random(A.rows());
+    DenseMatrix dB(A.rows(),rhsCols);
+    SpMat B(A.rows(),rhsCols);
+    double density = (std::max)(8./(A.rows()*rhsCols), 0.1);
+    initSparse<Scalar>(density, dB, B, ForceNonZeroDiag);
+    B.makeCompressed();
+    check_sparse_solving(solver, A, b,  dA, b);
+    check_sparse_solving(solver, A, dB, dA, dB);
+    check_sparse_solving(solver, A, B,  dA, dB);
+    
+    // check only once
+    if(i==0)
+    {
+      b = DenseVector::Zero(A.rows());
+      check_sparse_solving(solver, A, b, dA, b);
+    }
+  }
+}

Index: 3rd_party/eigen/test/sparse_vector.cpp
==================================================================
--- 3rd_party/eigen/test/sparse_vector.cpp
+++ 3rd_party/eigen/test/sparse_vector.cpp
@@ -7,26 +7,26 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "sparse.h"
 
-template<typename Scalar,typename Index> void sparse_vector(int rows, int cols)
+template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int cols)
 {
   double densityMat = (std::max)(8./(rows*cols), 0.01);
-  double densityVec = (std::max)(8./float(rows), 0.1);
+  double densityVec = (std::max)(8./(rows), 0.1);
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
   typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  typedef SparseVector<Scalar,0,Index> SparseVectorType;
-  typedef SparseMatrix<Scalar,0,Index> SparseMatrixType;
+  typedef SparseVector<Scalar,0,StorageIndex> SparseVectorType;
+  typedef SparseMatrix<Scalar,0,StorageIndex> SparseMatrixType;
   Scalar eps = 1e-6;
 
   SparseMatrixType m1(rows,rows);
   SparseVectorType v1(rows), v2(rows), v3(rows);
   DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
   DenseVector refV1 = DenseVector::Random(rows),
-    refV2 = DenseVector::Random(rows),
-    refV3 = DenseVector::Random(rows);
+              refV2 = DenseVector::Random(rows),
+              refV3 = DenseVector::Random(rows);
 
   std::vector<int> zerocoords, nonzerocoords;
   initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords);
   initSparse<Scalar>(densityMat, refM1, m1);
 
@@ -50,10 +50,24 @@
       VERIFY(it.value()==v1.coeff(it.index()));
       VERIFY(it.value()==refV1.coeff(it.index()));
     }
   }
   VERIFY_IS_APPROX(v1, refV1);
+  
+  // test coeffRef with reallocation
+  {
+    SparseVectorType v4(rows);
+    DenseVector v5 = DenseVector::Zero(rows);
+    for(int k=0; k<rows; ++k)
+    {
+      int i = internal::random<int>(0,rows-1);
+      Scalar v = internal::random<Scalar>();
+      v4.coeffRef(i) += v;
+      v5.coeffRef(i) += v;
+    }
+    VERIFY_IS_APPROX(v4,v5);
+  }
 
   v1.coeffRef(nonzerocoords[0]) = Scalar(5);
   refV1.coeffRef(nonzerocoords[0]) = Scalar(5);
   VERIFY_IS_APPROX(v1, refV1);
 
@@ -69,13 +83,16 @@
   VERIFY_IS_APPROX(v1-=v2, refV1-=refV2);
 
   VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2));
   VERIFY_IS_APPROX(v1.dot(refV2), refV1.dot(refV2));
 
+  VERIFY_IS_APPROX(m1*v2, refM1*refV2);
   VERIFY_IS_APPROX(v1.dot(m1*v2), refV1.dot(refM1*refV2));
-  int i = internal::random<int>(0,rows-1);
-  VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i)));
+  {
+    int i = internal::random<int>(0,rows-1);
+    VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i)));
+  }
 
 
   VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm());
   
   VERIFY_IS_APPROX(v1.blueNorm(), refV1.blueNorm());
@@ -94,17 +111,53 @@
   // check copy to dense vector with transpose
   refV3.resize(0);
   VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense()); 
   VERIFY_IS_APPROX(DenseVector(v1),v1.toDense()); 
 
+  // test conservative resize
+  {
+    std::vector<StorageIndex> inc;
+    if(rows > 3)
+      inc.push_back(-3);
+    inc.push_back(0);
+    inc.push_back(3);
+    inc.push_back(1);
+    inc.push_back(10);
+
+    for(std::size_t i = 0; i< inc.size(); i++) {
+      StorageIndex incRows = inc[i];
+      SparseVectorType vec1(rows);
+      DenseVector refVec1 = DenseVector::Zero(rows);
+      initSparse<Scalar>(densityVec, refVec1, vec1);
+
+      vec1.conservativeResize(rows+incRows);
+      refVec1.conservativeResize(rows+incRows);
+      if (incRows > 0) refVec1.tail(incRows).setZero();
+
+      VERIFY_IS_APPROX(vec1, refVec1);
+
+      // Insert new values
+      if (incRows > 0)
+        vec1.insert(vec1.rows()-1) = refVec1(refVec1.rows()-1) = 1;
+
+      VERIFY_IS_APPROX(vec1, refVec1);
+    }
+  }
+
 }
 
 void test_sparse_vector()
 {
   for(int i = 0; i < g_repeat; i++) {
+    int r = Eigen::internal::random<int>(1,500), c = Eigen::internal::random<int>(1,500);
+    if(Eigen::internal::random<int>(0,4) == 0) {
+      r = c; // check square matrices in 25% of tries
+    }
+    EIGEN_UNUSED_VARIABLE(r+c);
+
     CALL_SUBTEST_1(( sparse_vector<double,int>(8, 8) ));
-    CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(16, 16) ));
-    CALL_SUBTEST_1(( sparse_vector<double,long int>(299, 535) ));
-    CALL_SUBTEST_1(( sparse_vector<double,short>(299, 535) ));
+    CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(r, c) ));
+    CALL_SUBTEST_1(( sparse_vector<double,long int>(r, c) ));
+    CALL_SUBTEST_1(( sparse_vector<double,short>(r, c) ));
   }
 }
 

Index: 3rd_party/eigen/test/sparselu.cpp
==================================================================
--- 3rd_party/eigen/test/sparselu.cpp
+++ 3rd_party/eigen/test/sparselu.cpp
@@ -1,29 +1,13 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // SparseLU solve does not accept column major matrices for the destination.
 // However, as expected, the generic check_sparse_square_solving routines produces row-major
 // rhs and destination matrices when compiled with EIGEN_DEFAULT_TO_ROW_MAJOR
 
@@ -39,20 +23,23 @@
 {
   SparseLU<SparseMatrix<T, ColMajor> /*, COLAMDOrdering<int>*/ > sparselu_colamd; // COLAMDOrdering is the default
   SparseLU<SparseMatrix<T, ColMajor>, AMDOrdering<int> > sparselu_amd; 
   SparseLU<SparseMatrix<T, ColMajor, long int>, NaturalOrdering<long int> > sparselu_natural;
   
-  check_sparse_square_solving(sparselu_colamd); 
-  check_sparse_square_solving(sparselu_amd);
-  check_sparse_square_solving(sparselu_natural);
+  check_sparse_square_solving(sparselu_colamd,  300, 100000, true); 
+  check_sparse_square_solving(sparselu_amd,     300,  10000, true);
+  check_sparse_square_solving(sparselu_natural, 300,   2000, true);
   
   check_sparse_square_abs_determinant(sparselu_colamd);
   check_sparse_square_abs_determinant(sparselu_amd);
+  
+  check_sparse_square_determinant(sparselu_colamd);
+  check_sparse_square_determinant(sparselu_amd);
 }
 
 void test_sparselu()
 {
   CALL_SUBTEST_1(test_sparselu_T<float>()); 
   CALL_SUBTEST_2(test_sparselu_T<double>());
   CALL_SUBTEST_3(test_sparselu_T<std::complex<float> >()); 
   CALL_SUBTEST_4(test_sparselu_T<std::complex<double> >());
 }

Index: 3rd_party/eigen/test/sparseqr.cpp
==================================================================
--- 3rd_party/eigen/test/sparseqr.cpp
+++ 3rd_party/eigen/test/sparseqr.cpp
@@ -8,15 +8,16 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 #include "sparse.h"
 #include <Eigen/SparseQR>
 
 template<typename MatrixType,typename DenseMat>
-int generate_sparse_rectangular_problem(MatrixType& A, DenseMat& dA, int maxRows = 300)
+int generate_sparse_rectangular_problem(MatrixType& A, DenseMat& dA, int maxRows = 300, int maxCols = 150)
 {
+  eigen_assert(maxRows >= maxCols);
   typedef typename MatrixType::Scalar Scalar;
   int rows = internal::random<int>(1,maxRows);
-  int cols = internal::random<int>(1,rows);
+  int cols = internal::random<int>(1,maxCols);
   double density = (std::max)(8./(rows*cols), 0.01);
   
   A.resize(rows,cols);
   dA.resize(rows,cols);
   initSparse<Scalar>(density, dA, A,ForceNonZeroDiag);
@@ -51,11 +52,11 @@
   SparseQR<MatrixType, COLAMDOrdering<int> > solver; 
   generate_sparse_rectangular_problem(A,dA);
   
   b = dA * DenseVector::Random(A.cols());
   solver.compute(A);
-  if(internal::random<float>(0,1)>0.5)
+  if(internal::random<float>(0,1)>0.5f)
     solver.factorize(A);  // this checks that calling analyzePattern is not needed if the pattern do not change.
   if (solver.info() != Success)
   {
     std::cerr << "sparse QR factorization failed\n";
     exit(0);
@@ -86,10 +87,15 @@
   Q = solver.matrixQ();
   //Check  ||Q' * Q - I ||
   QtQ = Q * Q.adjoint();
   idM.resize(Q.rows(), Q.rows()); idM.setIdentity();
   VERIFY(idM.isApprox(QtQ));
+  
+  // Q to dense
+  DenseMat dQ;
+  dQ = solver.matrixQ();
+  VERIFY_IS_APPROX(Q, dQ);
 }
 void test_sparseqr()
 {
   for(int i=0; i<g_repeat; ++i)
   {

Index: 3rd_party/eigen/test/spqr_support.cpp
==================================================================
--- 3rd_party/eigen/test/spqr_support.cpp
+++ 3rd_party/eigen/test/spqr_support.cpp
@@ -3,10 +3,12 @@
 //
 // Copyright (C) 2012 Desire Nuentsa Wakam <desire.nuentsa_wakam@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
+
+#define EIGEN_NO_DEBUG_SMALL_PRODUCT_BLOCKS
 #include "sparse.h"
 #include <Eigen/SPQRSupport>
 
 
 template<typename MatrixType,typename DenseMat>
@@ -16,12 +18,12 @@
   typedef typename MatrixType::Scalar Scalar;
   int rows = internal::random<int>(1,maxRows);
   int cols = internal::random<int>(1,rows);
   double density = (std::max)(8./(rows*cols), 0.01);
   
-  A.resize(rows,rows);
-  dA.resize(rows,rows);
+  A.resize(rows,cols);
+  dA.resize(rows,cols);
   initSparse<Scalar>(density, dA, A,ForceNonZeroDiag);
   A.makeCompressed();
   return rows;
 }
 
@@ -33,11 +35,11 @@
   typedef Matrix<Scalar,Dynamic,1> DenseVector;
   DenseVector refX,x,b; 
   SPQR<MatrixType> solver; 
   generate_sparse_rectangular_problem(A,dA);
   
-  int m = A.rows();
+  Index m = A.rows();
   b = DenseVector::Random(m);
   solver.compute(A);
   if (solver.info() != Success)
   {
     std::cerr << "sparse QR factorization failed\n";

Index: 3rd_party/eigen/test/stable_norm.cpp
==================================================================
--- 3rd_party/eigen/test/stable_norm.cpp
+++ 3rd_party/eigen/test/stable_norm.cpp
@@ -1,24 +1,16 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
 
-// workaround aggressive optimization in ICC
-template<typename T> EIGEN_DONT_INLINE  T sub(T a, T b) { return a - b; }
-
-template<typename T> bool isFinite(const T& x)
-{
-  return isNotNaN(sub(x,x));
-}
-
 template<typename T> EIGEN_DONT_INLINE T copy(const T& x)
 {
   return x;
 }
 
@@ -30,10 +22,12 @@
   using std::sqrt;
   using std::abs;
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  
+  bool complex_real_product_ok = true;
 
   // Check the basic machine-dependent constants.
   {
     int ibeta, it, iemin, iemax;
 
@@ -42,10 +36,20 @@
     iemin = std::numeric_limits<RealScalar>::min_exponent;  // minimum exponent
     iemax = std::numeric_limits<RealScalar>::max_exponent;  // maximum exponent
 
     VERIFY( (!(iemin > 1 - 2*it || 1+it>iemax || (it==2 && ibeta<5) || (it<=4 && ibeta <= 3 ) || it<2))
            && "the stable norm algorithm cannot be guaranteed on this computer");
+    
+    Scalar inf = std::numeric_limits<RealScalar>::infinity();
+    if(NumTraits<Scalar>::IsComplex && (numext::isnan)(inf*RealScalar(1)) )
+    {
+      complex_real_product_ok = false;
+      static bool first = true;
+      if(first)
+        std::cerr << "WARNING: compiler mess up complex*real product, " << inf << " * " << 1.0 << " = " << inf*RealScalar(1) << std::endl;
+      first = false;
+    }
   }
 
 
   Index rows = m.rows();
   Index cols = m.cols();
@@ -74,23 +78,23 @@
   VERIFY_IS_APPROX(vrand.blueNorm(),        vrand.norm());
   VERIFY_IS_APPROX(vrand.hypotNorm(),       vrand.norm());
 
   RealScalar size = static_cast<RealScalar>(m.size());
 
-  // test isFinite
-  VERIFY(!isFinite( std::numeric_limits<RealScalar>::infinity()));
-  VERIFY(!isFinite(sqrt(-abs(big))));
+  // test numext::isfinite
+  VERIFY(!(numext::isfinite)( std::numeric_limits<RealScalar>::infinity()));
+  VERIFY(!(numext::isfinite)(sqrt(-abs(big))));
 
   // test overflow
-  VERIFY(isFinite(sqrt(size)*abs(big)));
+  VERIFY((numext::isfinite)(sqrt(size)*abs(big)));
   VERIFY_IS_NOT_APPROX(sqrt(copy(vbig.squaredNorm())), abs(sqrt(size)*big)); // here the default norm must fail
   VERIFY_IS_APPROX(vbig.stableNorm(), sqrt(size)*abs(big));
   VERIFY_IS_APPROX(vbig.blueNorm(),   sqrt(size)*abs(big));
   VERIFY_IS_APPROX(vbig.hypotNorm(),  sqrt(size)*abs(big));
 
   // test underflow
-  VERIFY(isFinite(sqrt(size)*abs(small)));
+  VERIFY((numext::isfinite)(sqrt(size)*abs(small)));
   VERIFY_IS_NOT_APPROX(sqrt(copy(vsmall.squaredNorm())),   abs(sqrt(size)*small)); // here the default norm must fail
   VERIFY_IS_APPROX(vsmall.stableNorm(), sqrt(size)*abs(small));
   VERIFY_IS_APPROX(vsmall.blueNorm(),   sqrt(size)*abs(small));
   VERIFY_IS_APPROX(vsmall.hypotNorm(),  sqrt(size)*abs(small));
 
@@ -99,10 +103,83 @@
   VERIFY_IS_APPROX(vrand.colwise().blueNorm(),        vrand.colwise().norm());
   VERIFY_IS_APPROX(vrand.colwise().hypotNorm(),       vrand.colwise().norm());
   VERIFY_IS_APPROX(vrand.rowwise().stableNorm(),      vrand.rowwise().norm());
   VERIFY_IS_APPROX(vrand.rowwise().blueNorm(),        vrand.rowwise().norm());
   VERIFY_IS_APPROX(vrand.rowwise().hypotNorm(),       vrand.rowwise().norm());
+  
+  // test NaN, +inf, -inf 
+  MatrixType v;
+  Index i = internal::random<Index>(0,rows-1);
+  Index j = internal::random<Index>(0,cols-1);
+
+  // NaN
+  {
+    v = vrand;
+    v(i,j) = std::numeric_limits<RealScalar>::quiet_NaN();
+    VERIFY(!(numext::isfinite)(v.squaredNorm()));   VERIFY((numext::isnan)(v.squaredNorm()));
+    VERIFY(!(numext::isfinite)(v.norm()));          VERIFY((numext::isnan)(v.norm()));
+    VERIFY(!(numext::isfinite)(v.stableNorm()));    VERIFY((numext::isnan)(v.stableNorm()));
+    VERIFY(!(numext::isfinite)(v.blueNorm()));      VERIFY((numext::isnan)(v.blueNorm()));
+    VERIFY(!(numext::isfinite)(v.hypotNorm()));     VERIFY((numext::isnan)(v.hypotNorm()));
+  }
+  
+  // +inf
+  {
+    v = vrand;
+    v(i,j) = std::numeric_limits<RealScalar>::infinity();
+    VERIFY(!(numext::isfinite)(v.squaredNorm()));   VERIFY(isPlusInf(v.squaredNorm()));
+    VERIFY(!(numext::isfinite)(v.norm()));          VERIFY(isPlusInf(v.norm()));
+    VERIFY(!(numext::isfinite)(v.stableNorm()));
+    if(complex_real_product_ok){
+      VERIFY(isPlusInf(v.stableNorm()));
+    }
+    VERIFY(!(numext::isfinite)(v.blueNorm()));      VERIFY(isPlusInf(v.blueNorm()));
+    VERIFY(!(numext::isfinite)(v.hypotNorm()));     VERIFY(isPlusInf(v.hypotNorm()));
+  }
+  
+  // -inf
+  {
+    v = vrand;
+    v(i,j) = -std::numeric_limits<RealScalar>::infinity();
+    VERIFY(!(numext::isfinite)(v.squaredNorm()));   VERIFY(isPlusInf(v.squaredNorm()));
+    VERIFY(!(numext::isfinite)(v.norm()));          VERIFY(isPlusInf(v.norm()));
+    VERIFY(!(numext::isfinite)(v.stableNorm()));
+    if(complex_real_product_ok) {
+      VERIFY(isPlusInf(v.stableNorm()));
+    }
+    VERIFY(!(numext::isfinite)(v.blueNorm()));      VERIFY(isPlusInf(v.blueNorm()));
+    VERIFY(!(numext::isfinite)(v.hypotNorm()));     VERIFY(isPlusInf(v.hypotNorm()));
+  }
+  
+  // mix
+  {
+    Index i2 = internal::random<Index>(0,rows-1);
+    Index j2 = internal::random<Index>(0,cols-1);
+    v = vrand;
+    v(i,j) = -std::numeric_limits<RealScalar>::infinity();
+    v(i2,j2) = std::numeric_limits<RealScalar>::quiet_NaN();
+    VERIFY(!(numext::isfinite)(v.squaredNorm()));   VERIFY((numext::isnan)(v.squaredNorm()));
+    VERIFY(!(numext::isfinite)(v.norm()));          VERIFY((numext::isnan)(v.norm()));
+    VERIFY(!(numext::isfinite)(v.stableNorm()));    VERIFY((numext::isnan)(v.stableNorm()));
+    VERIFY(!(numext::isfinite)(v.blueNorm()));      VERIFY((numext::isnan)(v.blueNorm()));
+    VERIFY(!(numext::isfinite)(v.hypotNorm()));     VERIFY((numext::isnan)(v.hypotNorm()));
+  }
+
+  // stableNormalize[d]
+  {
+    VERIFY_IS_APPROX(vrand.stableNormalized(), vrand.normalized());
+    MatrixType vcopy(vrand);
+    vcopy.stableNormalize();
+    VERIFY_IS_APPROX(vcopy, vrand.normalized());
+    VERIFY_IS_APPROX((vrand.stableNormalized()).norm(), RealScalar(1));
+    VERIFY_IS_APPROX(vcopy.norm(), RealScalar(1));
+    VERIFY_IS_APPROX((vbig.stableNormalized()).norm(), RealScalar(1));
+    VERIFY_IS_APPROX((vsmall.stableNormalized()).norm(), RealScalar(1));
+    RealScalar big_scaling = ((std::numeric_limits<RealScalar>::max)() * RealScalar(1e-4));
+    VERIFY_IS_APPROX(vbig/big_scaling, (vbig.stableNorm() * vbig.stableNormalized()).eval()/big_scaling);
+    VERIFY_IS_APPROX(vsmall, vsmall.stableNorm() * vsmall.stableNormalized());
+  }
 }
 
 void test_stable_norm()
 {
   for(int i = 0; i < g_repeat; i++) {

ADDED   3rd_party/eigen/test/stddeque_overload.cpp
Index: 3rd_party/eigen/test/stddeque_overload.cpp
==================================================================
--- 3rd_party/eigen/test/stddeque_overload.cpp
+++ 3rd_party/eigen/test/stddeque_overload.cpp
@@ -0,0 +1,158 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/StdDeque>
+#include <Eigen/Geometry>
+
+EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(Vector4f)
+
+EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(Matrix2f)
+EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(Matrix4f)
+EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(Matrix4d)
+
+EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(Affine3f)
+EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(Affine3d)
+
+EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(Quaternionf)
+EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(Quaterniond)
+
+template<typename MatrixType>
+void check_stddeque_matrix(const MatrixType& m)
+{
+  typename MatrixType::Index rows = m.rows();
+  typename MatrixType::Index cols = m.cols();
+  MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
+  std::deque<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
+  v[5] = x;
+  w[6] = v[5];
+  VERIFY_IS_APPROX(w[6], v[5]);
+  v = w;
+  for(int i = 0; i < 20; i++)
+  {
+    VERIFY_IS_APPROX(w[i], v[i]);
+  }
+
+  v.resize(21);
+  v[20] = x;
+  VERIFY_IS_APPROX(v[20], x);
+  v.resize(22,y);
+  VERIFY_IS_APPROX(v[21], y);
+  v.push_back(x);
+  VERIFY_IS_APPROX(v[22], x);
+
+  // do a lot of push_back such that the deque gets internally resized
+  // (with memory reallocation)
+  MatrixType* ref = &w[0];
+  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
+    v.push_back(w[i%w.size()]);
+  for(unsigned int i=23; i<v.size(); ++i)
+  {
+    VERIFY(v[i]==w[(i-23)%w.size()]);
+  }
+}
+
+template<typename TransformType>
+void check_stddeque_transform(const TransformType&)
+{
+  typedef typename TransformType::MatrixType MatrixType;
+  TransformType x(MatrixType::Random()), y(MatrixType::Random());
+  std::deque<TransformType> v(10), w(20, y);
+  v[5] = x;
+  w[6] = v[5];
+  VERIFY_IS_APPROX(w[6], v[5]);
+  v = w;
+  for(int i = 0; i < 20; i++)
+  {
+    VERIFY_IS_APPROX(w[i], v[i]);
+  }
+
+  v.resize(21);
+  v[20] = x;
+  VERIFY_IS_APPROX(v[20], x);
+  v.resize(22,y);
+  VERIFY_IS_APPROX(v[21], y);
+  v.push_back(x);
+  VERIFY_IS_APPROX(v[22], x);
+
+  // do a lot of push_back such that the deque gets internally resized
+  // (with memory reallocation)
+  TransformType* ref = &w[0];
+  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
+    v.push_back(w[i%w.size()]);
+  for(unsigned int i=23; i<v.size(); ++i)
+  {
+    VERIFY(v[i].matrix()==w[(i-23)%w.size()].matrix());
+  }
+}
+
+template<typename QuaternionType>
+void check_stddeque_quaternion(const QuaternionType&)
+{
+  typedef typename QuaternionType::Coefficients Coefficients;
+  QuaternionType x(Coefficients::Random()), y(Coefficients::Random());
+  std::deque<QuaternionType> v(10), w(20, y);
+  v[5] = x;
+  w[6] = v[5];
+  VERIFY_IS_APPROX(w[6], v[5]);
+  v = w;
+  for(int i = 0; i < 20; i++)
+  {
+    VERIFY_IS_APPROX(w[i], v[i]);
+  }
+
+  v.resize(21);
+  v[20] = x;
+  VERIFY_IS_APPROX(v[20], x);
+  v.resize(22,y);
+  VERIFY_IS_APPROX(v[21], y);
+  v.push_back(x);
+  VERIFY_IS_APPROX(v[22], x);
+
+  // do a lot of push_back such that the deque gets internally resized
+  // (with memory reallocation)
+  QuaternionType* ref = &w[0];
+  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
+    v.push_back(w[i%w.size()]);
+  for(unsigned int i=23; i<v.size(); ++i)
+  {
+    VERIFY(v[i].coeffs()==w[(i-23)%w.size()].coeffs());
+  }
+}
+
+void test_stddeque_overload()
+{
+  // some non vectorizable fixed sizes
+  CALL_SUBTEST_1(check_stddeque_matrix(Vector2f()));
+  CALL_SUBTEST_1(check_stddeque_matrix(Matrix3f()));
+  CALL_SUBTEST_2(check_stddeque_matrix(Matrix3d()));
+
+  // some vectorizable fixed sizes
+  CALL_SUBTEST_1(check_stddeque_matrix(Matrix2f()));
+  CALL_SUBTEST_1(check_stddeque_matrix(Vector4f()));
+  CALL_SUBTEST_1(check_stddeque_matrix(Matrix4f()));
+  CALL_SUBTEST_2(check_stddeque_matrix(Matrix4d()));
+
+  // some dynamic sizes
+  CALL_SUBTEST_3(check_stddeque_matrix(MatrixXd(1,1)));
+  CALL_SUBTEST_3(check_stddeque_matrix(VectorXd(20)));
+  CALL_SUBTEST_3(check_stddeque_matrix(RowVectorXf(20)));
+  CALL_SUBTEST_3(check_stddeque_matrix(MatrixXcf(10,10)));
+
+  // some Transform
+  CALL_SUBTEST_4(check_stddeque_transform(Affine2f())); // does not need the specialization (2+1)^2 = 9
+  CALL_SUBTEST_4(check_stddeque_transform(Affine3f()));
+  CALL_SUBTEST_4(check_stddeque_transform(Affine3d()));
+
+  // some Quaternion
+  CALL_SUBTEST_5(check_stddeque_quaternion(Quaternionf()));
+  CALL_SUBTEST_5(check_stddeque_quaternion(Quaterniond()));
+}

ADDED   3rd_party/eigen/test/stdlist_overload.cpp
Index: 3rd_party/eigen/test/stdlist_overload.cpp
==================================================================
--- 3rd_party/eigen/test/stdlist_overload.cpp
+++ 3rd_party/eigen/test/stdlist_overload.cpp
@@ -0,0 +1,192 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/StdList>
+#include <Eigen/Geometry>
+
+EIGEN_DEFINE_STL_LIST_SPECIALIZATION(Vector4f)
+
+EIGEN_DEFINE_STL_LIST_SPECIALIZATION(Matrix2f)
+EIGEN_DEFINE_STL_LIST_SPECIALIZATION(Matrix4f)
+EIGEN_DEFINE_STL_LIST_SPECIALIZATION(Matrix4d)
+
+EIGEN_DEFINE_STL_LIST_SPECIALIZATION(Affine3f)
+EIGEN_DEFINE_STL_LIST_SPECIALIZATION(Affine3d)
+
+EIGEN_DEFINE_STL_LIST_SPECIALIZATION(Quaternionf)
+EIGEN_DEFINE_STL_LIST_SPECIALIZATION(Quaterniond)
+
+template <class Container, class Position>
+typename Container::iterator get(Container & c, Position position)
+{
+  typename Container::iterator it = c.begin();
+  std::advance(it, position);
+  return it;
+}
+
+template <class Container, class Position, class Value>
+void set(Container & c, Position position, const Value & value)
+{
+  typename Container::iterator it = c.begin();
+  std::advance(it, position);
+  *it = value;
+}
+
+template<typename MatrixType>
+void check_stdlist_matrix(const MatrixType& m)
+{
+  typename MatrixType::Index rows = m.rows();
+  typename MatrixType::Index cols = m.cols();
+  MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
+  std::list<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
+  typename std::list<MatrixType>::iterator itv = get(v, 5);
+  typename std::list<MatrixType>::iterator itw = get(w, 6);
+  *itv = x;
+  *itw = *itv;
+  VERIFY_IS_APPROX(*itw, *itv);
+  v = w;
+  itv = v.begin();
+  itw = w.begin();
+  for(int i = 0; i < 20; i++)
+  {
+    VERIFY_IS_APPROX(*itw, *itv);
+    ++itv;
+    ++itw;
+  }
+
+  v.resize(21);
+  set(v, 20, x);
+  VERIFY_IS_APPROX(*get(v, 20), x);
+  v.resize(22,y);
+  VERIFY_IS_APPROX(*get(v, 21), y);
+  v.push_back(x);
+  VERIFY_IS_APPROX(*get(v, 22), x);
+
+  // do a lot of push_back such that the list gets internally resized
+  // (with memory reallocation)
+  MatrixType* ref = &(*get(w, 0));
+  for(int i=0; i<30 || ((ref==&(*get(w, 0))) && i<300); ++i)
+    v.push_back(*get(w, i%w.size()));
+  for(unsigned int i=23; i<v.size(); ++i)
+  {
+    VERIFY((*get(v, i))==(*get(w, (i-23)%w.size())));
+  }
+}
+
+template<typename TransformType>
+void check_stdlist_transform(const TransformType&)
+{
+  typedef typename TransformType::MatrixType MatrixType;
+  TransformType x(MatrixType::Random()), y(MatrixType::Random());
+  std::list<TransformType> v(10), w(20, y);
+  typename std::list<TransformType>::iterator itv = get(v, 5);
+  typename std::list<TransformType>::iterator itw = get(w, 6);
+  *itv = x;
+  *itw = *itv;
+  VERIFY_IS_APPROX(*itw, *itv);
+  v = w;
+  itv = v.begin();
+  itw = w.begin();
+  for(int i = 0; i < 20; i++)
+  {
+    VERIFY_IS_APPROX(*itw, *itv);
+    ++itv;
+    ++itw;
+  }
+
+  v.resize(21);
+  set(v, 20, x);
+  VERIFY_IS_APPROX(*get(v, 20), x);
+  v.resize(22,y);
+  VERIFY_IS_APPROX(*get(v, 21), y);
+  v.push_back(x);
+  VERIFY_IS_APPROX(*get(v, 22), x);
+
+  // do a lot of push_back such that the list gets internally resized
+  // (with memory reallocation)
+  TransformType* ref = &(*get(w, 0));
+  for(int i=0; i<30 || ((ref==&(*get(w, 0))) && i<300); ++i)
+    v.push_back(*get(w, i%w.size()));
+  for(unsigned int i=23; i<v.size(); ++i)
+  {
+    VERIFY(get(v, i)->matrix()==get(w, (i-23)%w.size())->matrix());
+  }
+}
+
+template<typename QuaternionType>
+void check_stdlist_quaternion(const QuaternionType&)
+{
+  typedef typename QuaternionType::Coefficients Coefficients;
+  QuaternionType x(Coefficients::Random()), y(Coefficients::Random());
+  std::list<QuaternionType> v(10), w(20, y);
+  typename std::list<QuaternionType>::iterator itv = get(v, 5);
+  typename std::list<QuaternionType>::iterator itw = get(w, 6);
+  *itv = x;
+  *itw = *itv;
+  VERIFY_IS_APPROX(*itw, *itv);
+  v = w;
+  itv = v.begin();
+  itw = w.begin();
+  for(int i = 0; i < 20; i++)
+  {
+    VERIFY_IS_APPROX(*itw, *itv);
+    ++itv;
+    ++itw;
+  }
+
+  v.resize(21);
+  set(v, 20, x);
+  VERIFY_IS_APPROX(*get(v, 20), x);
+  v.resize(22,y);
+  VERIFY_IS_APPROX(*get(v, 21), y);
+  v.push_back(x);
+  VERIFY_IS_APPROX(*get(v, 22), x);
+
+  // do a lot of push_back such that the list gets internally resized
+  // (with memory reallocation)
+  QuaternionType* ref = &(*get(w, 0));
+  for(int i=0; i<30 || ((ref==&(*get(w, 0))) && i<300); ++i)
+    v.push_back(*get(w, i%w.size()));
+  for(unsigned int i=23; i<v.size(); ++i)
+  {
+    VERIFY(get(v, i)->coeffs()==get(w, (i-23)%w.size())->coeffs());
+  }
+}
+
+void test_stdlist_overload()
+{
+  // some non vectorizable fixed sizes
+  CALL_SUBTEST_1(check_stdlist_matrix(Vector2f()));
+  CALL_SUBTEST_1(check_stdlist_matrix(Matrix3f()));
+  CALL_SUBTEST_2(check_stdlist_matrix(Matrix3d()));
+
+  // some vectorizable fixed sizes
+  CALL_SUBTEST_1(check_stdlist_matrix(Matrix2f()));
+  CALL_SUBTEST_1(check_stdlist_matrix(Vector4f()));
+  CALL_SUBTEST_1(check_stdlist_matrix(Matrix4f()));
+  CALL_SUBTEST_2(check_stdlist_matrix(Matrix4d()));
+
+  // some dynamic sizes
+  CALL_SUBTEST_3(check_stdlist_matrix(MatrixXd(1,1)));
+  CALL_SUBTEST_3(check_stdlist_matrix(VectorXd(20)));
+  CALL_SUBTEST_3(check_stdlist_matrix(RowVectorXf(20)));
+  CALL_SUBTEST_3(check_stdlist_matrix(MatrixXcf(10,10)));
+
+  // some Transform
+  CALL_SUBTEST_4(check_stdlist_transform(Affine2f())); // does not need the specialization (2+1)^2 = 9
+  CALL_SUBTEST_4(check_stdlist_transform(Affine3f()));
+  CALL_SUBTEST_4(check_stdlist_transform(Affine3d()));
+
+  // some Quaternion
+  CALL_SUBTEST_5(check_stdlist_quaternion(Quaternionf()));
+  CALL_SUBTEST_5(check_stdlist_quaternion(Quaterniond()));
+}

Index: 3rd_party/eigen/test/stdvector.cpp
==================================================================
--- 3rd_party/eigen/test/stdvector.cpp
+++ 3rd_party/eigen/test/stdvector.cpp
@@ -32,11 +32,11 @@
   VERIFY_IS_APPROX(v[20], x);
   v.resize(22,y);
   VERIFY_IS_APPROX(v[21], y);
   v.push_back(x);
   VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(MatrixType));
+  VERIFY((internal::UIntPtr)&(v[22]) == (internal::UIntPtr)&(v[21]) + sizeof(MatrixType));
 
   // do a lot of push_back such that the vector gets internally resized
   // (with memory reallocation)
   MatrixType* ref = &w[0];
   for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
@@ -67,11 +67,11 @@
   VERIFY_IS_APPROX(v[20], x);
   v.resize(22,y);
   VERIFY_IS_APPROX(v[21], y);
   v.push_back(x);
   VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(TransformType));
+  VERIFY((internal::UIntPtr)&(v[22]) == (internal::UIntPtr)&(v[21]) + sizeof(TransformType));
 
   // do a lot of push_back such that the vector gets internally resized
   // (with memory reallocation)
   TransformType* ref = &w[0];
   for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
@@ -102,11 +102,11 @@
   VERIFY_IS_APPROX(v[20], x);
   v.resize(22,y);
   VERIFY_IS_APPROX(v[21], y);
   v.push_back(x);
   VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(QuaternionType));
+  VERIFY((internal::UIntPtr)&(v[22]) == (internal::UIntPtr)&(v[21]) + sizeof(QuaternionType));
 
   // do a lot of push_back such that the vector gets internally resized
   // (with memory reallocation)
   QuaternionType* ref = &w[0];
   for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)

Index: 3rd_party/eigen/test/stdvector_overload.cpp
==================================================================
--- 3rd_party/eigen/test/stdvector_overload.cpp
+++ 3rd_party/eigen/test/stdvector_overload.cpp
@@ -46,11 +46,11 @@
   VERIFY_IS_APPROX(v[20], x);
   v.resize(22,y);
   VERIFY_IS_APPROX(v[21], y);
   v.push_back(x);
   VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(MatrixType));
+  VERIFY((internal::UIntPtr)&(v[22]) == (internal::UIntPtr)&(v[21]) + sizeof(MatrixType));
 
   // do a lot of push_back such that the vector gets internally resized
   // (with memory reallocation)
   MatrixType* ref = &w[0];
   for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
@@ -81,11 +81,11 @@
   VERIFY_IS_APPROX(v[20], x);
   v.resize(22,y);
   VERIFY_IS_APPROX(v[21], y);
   v.push_back(x);
   VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(TransformType));
+  VERIFY((internal::UIntPtr)&(v[22]) == (internal::UIntPtr)&(v[21]) + sizeof(TransformType));
 
   // do a lot of push_back such that the vector gets internally resized
   // (with memory reallocation)
   TransformType* ref = &w[0];
   for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
@@ -116,11 +116,11 @@
   VERIFY_IS_APPROX(v[20], x);
   v.resize(22,y);
   VERIFY_IS_APPROX(v[21], y);
   v.push_back(x);
   VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(QuaternionType));
+  VERIFY((internal::UIntPtr)&(v[22]) == (internal::UIntPtr)&(v[21]) + sizeof(QuaternionType));
 
   // do a lot of push_back such that the vector gets internally resized
   // (with memory reallocation)
   QuaternionType* ref = &w[0];
   for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)

Index: 3rd_party/eigen/test/superlu_support.cpp
==================================================================
--- 3rd_party/eigen/test/superlu_support.cpp
+++ 3rd_party/eigen/test/superlu_support.cpp
@@ -5,10 +5,11 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#define EIGEN_NO_DEBUG_SMALL_PRODUCT_BLOCKS
 #include "sparse_solver.h"
 
 #include <Eigen/SuperLUSupport>
 
 void test_superlu_support()

ADDED   3rd_party/eigen/test/svd_common.h
Index: 3rd_party/eigen/test/svd_common.h
==================================================================
--- 3rd_party/eigen/test/svd_common.h
+++ 3rd_party/eigen/test/svd_common.h
@@ -0,0 +1,483 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef SVD_DEFAULT
+#error a macro SVD_DEFAULT(MatrixType) must be defined prior to including svd_common.h
+#endif
+
+#ifndef SVD_FOR_MIN_NORM
+#error a macro SVD_FOR_MIN_NORM(MatrixType) must be defined prior to including svd_common.h
+#endif
+
+#include "svd_fill.h"
+
+// Check that the matrix m is properly reconstructed and that the U and V factors are unitary
+// The SVD must have already been computed.
+template<typename SvdType, typename MatrixType>
+void svd_check_full(const MatrixType& m, const SvdType& svd)
+{
+  typedef typename MatrixType::Index Index;
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  enum {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime
+  };
+
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime> MatrixUType;
+  typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime> MatrixVType;
+
+  MatrixType sigma = MatrixType::Zero(rows,cols);
+  sigma.diagonal() = svd.singularValues().template cast<Scalar>();
+  MatrixUType u = svd.matrixU();
+  MatrixVType v = svd.matrixV();
+  RealScalar scaling = m.cwiseAbs().maxCoeff();
+  if(scaling<(std::numeric_limits<RealScalar>::min)())
+  {
+    VERIFY(sigma.cwiseAbs().maxCoeff() <= (std::numeric_limits<RealScalar>::min)());
+  }
+  else
+  {
+    VERIFY_IS_APPROX(m/scaling, u * (sigma/scaling) * v.adjoint());
+  }
+  VERIFY_IS_UNITARY(u);
+  VERIFY_IS_UNITARY(v);
+}
+
+// Compare partial SVD defined by computationOptions to a full SVD referenceSvd
+template<typename SvdType, typename MatrixType>
+void svd_compare_to_full(const MatrixType& m,
+                         unsigned int computationOptions,
+                         const SvdType& referenceSvd)
+{
+  typedef typename MatrixType::RealScalar RealScalar;
+  Index rows = m.rows();
+  Index cols = m.cols();
+  Index diagSize = (std::min)(rows, cols);
+  RealScalar prec = test_precision<RealScalar>();
+
+  SvdType svd(m, computationOptions);
+
+  VERIFY_IS_APPROX(svd.singularValues(), referenceSvd.singularValues());
+  
+  if(computationOptions & (ComputeFullV|ComputeThinV))
+  {
+    VERIFY( (svd.matrixV().adjoint()*svd.matrixV()).isIdentity(prec) );
+    VERIFY_IS_APPROX( svd.matrixV().leftCols(diagSize) * svd.singularValues().asDiagonal() * svd.matrixV().leftCols(diagSize).adjoint(),
+                      referenceSvd.matrixV().leftCols(diagSize) * referenceSvd.singularValues().asDiagonal() * referenceSvd.matrixV().leftCols(diagSize).adjoint());
+  }
+  
+  if(computationOptions & (ComputeFullU|ComputeThinU))
+  {
+    VERIFY( (svd.matrixU().adjoint()*svd.matrixU()).isIdentity(prec) );
+    VERIFY_IS_APPROX( svd.matrixU().leftCols(diagSize) * svd.singularValues().cwiseAbs2().asDiagonal() * svd.matrixU().leftCols(diagSize).adjoint(),
+                      referenceSvd.matrixU().leftCols(diagSize) * referenceSvd.singularValues().cwiseAbs2().asDiagonal() * referenceSvd.matrixU().leftCols(diagSize).adjoint());
+  }
+  
+  // The following checks are not critical.
+  // For instance, with Dived&Conquer SVD, if only the factor 'V' is computedt then different matrix-matrix product implementation will be used
+  // and the resulting 'V' factor might be significantly different when the SVD decomposition is not unique, especially with single precision float.
+  ++g_test_level;
+  if(computationOptions & ComputeFullU)  VERIFY_IS_APPROX(svd.matrixU(), referenceSvd.matrixU());
+  if(computationOptions & ComputeThinU)  VERIFY_IS_APPROX(svd.matrixU(), referenceSvd.matrixU().leftCols(diagSize));
+  if(computationOptions & ComputeFullV)  VERIFY_IS_APPROX(svd.matrixV().cwiseAbs(), referenceSvd.matrixV().cwiseAbs());
+  if(computationOptions & ComputeThinV)  VERIFY_IS_APPROX(svd.matrixV(), referenceSvd.matrixV().leftCols(diagSize));
+  --g_test_level;
+}
+
+//
+template<typename SvdType, typename MatrixType>
+void svd_least_square(const MatrixType& m, unsigned int computationOptions)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename MatrixType::Index Index;
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  enum {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime
+  };
+
+  typedef Matrix<Scalar, RowsAtCompileTime, Dynamic> RhsType;
+  typedef Matrix<Scalar, ColsAtCompileTime, Dynamic> SolutionType;
+
+  RhsType rhs = RhsType::Random(rows, internal::random<Index>(1, cols));
+  SvdType svd(m, computationOptions);
+
+       if(internal::is_same<RealScalar,double>::value) svd.setThreshold(1e-8);
+  else if(internal::is_same<RealScalar,float>::value)  svd.setThreshold(2e-4);
+
+  SolutionType x = svd.solve(rhs);
+   
+  RealScalar residual = (m*x-rhs).norm();
+  RealScalar rhs_norm = rhs.norm();
+  if(!test_isMuchSmallerThan(residual,rhs.norm()))
+  {
+    // ^^^ If the residual is very small, then we have an exact solution, so we are already good.
+    
+    // evaluate normal equation which works also for least-squares solutions
+    if(internal::is_same<RealScalar,double>::value || svd.rank()==m.diagonal().size())
+    {
+      using std::sqrt;
+      // This test is not stable with single precision.
+      // This is probably because squaring m signicantly affects the precision.      
+      if(internal::is_same<RealScalar,float>::value) ++g_test_level;
+      
+      VERIFY_IS_APPROX(m.adjoint()*(m*x),m.adjoint()*rhs);
+      
+      if(internal::is_same<RealScalar,float>::value) --g_test_level;
+    }
+    
+    // Check that there is no significantly better solution in the neighborhood of x
+    for(Index k=0;k<x.rows();++k)
+    {
+      using std::abs;
+      
+      SolutionType y(x);
+      y.row(k) = (RealScalar(1)+2*NumTraits<RealScalar>::epsilon())*x.row(k);
+      RealScalar residual_y = (m*y-rhs).norm();
+      VERIFY( test_isMuchSmallerThan(abs(residual_y-residual), rhs_norm) || residual < residual_y );
+      if(internal::is_same<RealScalar,float>::value) ++g_test_level;
+      VERIFY( test_isApprox(residual_y,residual) || residual < residual_y );
+      if(internal::is_same<RealScalar,float>::value) --g_test_level;
+      
+      y.row(k) = (RealScalar(1)-2*NumTraits<RealScalar>::epsilon())*x.row(k);
+      residual_y = (m*y-rhs).norm();
+      VERIFY( test_isMuchSmallerThan(abs(residual_y-residual), rhs_norm) || residual < residual_y );
+      if(internal::is_same<RealScalar,float>::value) ++g_test_level;
+      VERIFY( test_isApprox(residual_y,residual) || residual < residual_y );
+      if(internal::is_same<RealScalar,float>::value) --g_test_level;
+    }
+  }
+}
+
+// check minimal norm solutions, the inoput matrix m is only used to recover problem size
+template<typename MatrixType>
+void svd_min_norm(const MatrixType& m, unsigned int computationOptions)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
+  Index cols = m.cols();
+
+  enum {
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime
+  };
+
+  typedef Matrix<Scalar, ColsAtCompileTime, Dynamic> SolutionType;
+
+  // generate a full-rank m x n problem with m<n
+  enum {
+    RankAtCompileTime2 = ColsAtCompileTime==Dynamic ? Dynamic : (ColsAtCompileTime)/2+1,
+    RowsAtCompileTime3 = ColsAtCompileTime==Dynamic ? Dynamic : ColsAtCompileTime+1
+  };
+  typedef Matrix<Scalar, RankAtCompileTime2, ColsAtCompileTime> MatrixType2;
+  typedef Matrix<Scalar, RankAtCompileTime2, 1> RhsType2;
+  typedef Matrix<Scalar, ColsAtCompileTime, RankAtCompileTime2> MatrixType2T;
+  Index rank = RankAtCompileTime2==Dynamic ? internal::random<Index>(1,cols) : Index(RankAtCompileTime2);
+  MatrixType2 m2(rank,cols);
+  int guard = 0;
+  do {
+    m2.setRandom();
+  } while(SVD_FOR_MIN_NORM(MatrixType2)(m2).setThreshold(test_precision<Scalar>()).rank()!=rank && (++guard)<10);
+  VERIFY(guard<10);
+
+  RhsType2 rhs2 = RhsType2::Random(rank);
+  // use QR to find a reference minimal norm solution
+  HouseholderQR<MatrixType2T> qr(m2.adjoint());
+  Matrix<Scalar,Dynamic,1> tmp = qr.matrixQR().topLeftCorner(rank,rank).template triangularView<Upper>().adjoint().solve(rhs2);
+  tmp.conservativeResize(cols);
+  tmp.tail(cols-rank).setZero();
+  SolutionType x21 = qr.householderQ() * tmp;
+  // now check with SVD
+  SVD_FOR_MIN_NORM(MatrixType2) svd2(m2, computationOptions);
+  SolutionType x22 = svd2.solve(rhs2);
+  VERIFY_IS_APPROX(m2*x21, rhs2);
+  VERIFY_IS_APPROX(m2*x22, rhs2);
+  VERIFY_IS_APPROX(x21, x22);
+
+  // Now check with a rank deficient matrix
+  typedef Matrix<Scalar, RowsAtCompileTime3, ColsAtCompileTime> MatrixType3;
+  typedef Matrix<Scalar, RowsAtCompileTime3, 1> RhsType3;
+  Index rows3 = RowsAtCompileTime3==Dynamic ? internal::random<Index>(rank+1,2*cols) : Index(RowsAtCompileTime3);
+  Matrix<Scalar,RowsAtCompileTime3,Dynamic> C = Matrix<Scalar,RowsAtCompileTime3,Dynamic>::Random(rows3,rank);
+  MatrixType3 m3 = C * m2;
+  RhsType3 rhs3 = C * rhs2;
+  SVD_FOR_MIN_NORM(MatrixType3) svd3(m3, computationOptions);
+  SolutionType x3 = svd3.solve(rhs3);
+  VERIFY_IS_APPROX(m3*x3, rhs3);
+  VERIFY_IS_APPROX(m3*x21, rhs3);
+  VERIFY_IS_APPROX(m2*x3, rhs2);
+  VERIFY_IS_APPROX(x21, x3);
+}
+
+// Check full, compare_to_full, least_square, and min_norm for all possible compute-options
+template<typename SvdType, typename MatrixType>
+void svd_test_all_computation_options(const MatrixType& m, bool full_only)
+{
+//   if (QRPreconditioner == NoQRPreconditioner && m.rows() != m.cols())
+//     return;
+  SvdType fullSvd(m, ComputeFullU|ComputeFullV);
+  CALL_SUBTEST(( svd_check_full(m, fullSvd) ));
+  CALL_SUBTEST(( svd_least_square<SvdType>(m, ComputeFullU | ComputeFullV) ));
+  CALL_SUBTEST(( svd_min_norm(m, ComputeFullU | ComputeFullV) ));
+  
+  #if defined __INTEL_COMPILER
+  // remark #111: statement is unreachable
+  #pragma warning disable 111
+  #endif
+  if(full_only)
+    return;
+
+  CALL_SUBTEST(( svd_compare_to_full(m, ComputeFullU, fullSvd) ));
+  CALL_SUBTEST(( svd_compare_to_full(m, ComputeFullV, fullSvd) ));
+  CALL_SUBTEST(( svd_compare_to_full(m, 0, fullSvd) ));
+
+  if (MatrixType::ColsAtCompileTime == Dynamic) {
+    // thin U/V are only available with dynamic number of columns
+    CALL_SUBTEST(( svd_compare_to_full(m, ComputeFullU|ComputeThinV, fullSvd) ));
+    CALL_SUBTEST(( svd_compare_to_full(m,              ComputeThinV, fullSvd) ));
+    CALL_SUBTEST(( svd_compare_to_full(m, ComputeThinU|ComputeFullV, fullSvd) ));
+    CALL_SUBTEST(( svd_compare_to_full(m, ComputeThinU             , fullSvd) ));
+    CALL_SUBTEST(( svd_compare_to_full(m, ComputeThinU|ComputeThinV, fullSvd) ));
+    
+    CALL_SUBTEST(( svd_least_square<SvdType>(m, ComputeFullU | ComputeThinV) ));
+    CALL_SUBTEST(( svd_least_square<SvdType>(m, ComputeThinU | ComputeFullV) ));
+    CALL_SUBTEST(( svd_least_square<SvdType>(m, ComputeThinU | ComputeThinV) ));
+
+    CALL_SUBTEST(( svd_min_norm(m, ComputeFullU | ComputeThinV) ));
+    CALL_SUBTEST(( svd_min_norm(m, ComputeThinU | ComputeFullV) ));
+    CALL_SUBTEST(( svd_min_norm(m, ComputeThinU | ComputeThinV) ));
+
+    // test reconstruction
+    typedef typename MatrixType::Index Index;
+    Index diagSize = (std::min)(m.rows(), m.cols());
+    SvdType svd(m, ComputeThinU | ComputeThinV);
+    VERIFY_IS_APPROX(m, svd.matrixU().leftCols(diagSize) * svd.singularValues().asDiagonal() * svd.matrixV().leftCols(diagSize).adjoint());
+  }
+}
+
+
+// work around stupid msvc error when constructing at compile time an expression that involves
+// a division by zero, even if the numeric type has floating point
+template<typename Scalar>
+EIGEN_DONT_INLINE Scalar zero() { return Scalar(0); }
+
+// workaround aggressive optimization in ICC
+template<typename T> EIGEN_DONT_INLINE  T sub(T a, T b) { return a - b; }
+
+// all this function does is verify we don't iterate infinitely on nan/inf values
+template<typename SvdType, typename MatrixType>
+void svd_inf_nan()
+{
+  SvdType svd;
+  typedef typename MatrixType::Scalar Scalar;
+  Scalar some_inf = Scalar(1) / zero<Scalar>();
+  VERIFY(sub(some_inf, some_inf) != sub(some_inf, some_inf));
+  svd.compute(MatrixType::Constant(10,10,some_inf), ComputeFullU | ComputeFullV);
+
+  Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
+  VERIFY(nan != nan);
+  svd.compute(MatrixType::Constant(10,10,nan), ComputeFullU | ComputeFullV);
+
+  MatrixType m = MatrixType::Zero(10,10);
+  m(internal::random<int>(0,9), internal::random<int>(0,9)) = some_inf;
+  svd.compute(m, ComputeFullU | ComputeFullV);
+
+  m = MatrixType::Zero(10,10);
+  m(internal::random<int>(0,9), internal::random<int>(0,9)) = nan;
+  svd.compute(m, ComputeFullU | ComputeFullV);
+  
+  // regression test for bug 791
+  m.resize(3,3);
+  m << 0,    2*NumTraits<Scalar>::epsilon(),  0.5,
+       0,   -0.5,                             0,
+       nan,  0,                               0;
+  svd.compute(m, ComputeFullU | ComputeFullV);
+  
+  m.resize(4,4);
+  m <<  1, 0, 0, 0,
+        0, 3, 1, 2e-308,
+        1, 0, 1, nan,
+        0, nan, nan, 0;
+  svd.compute(m, ComputeFullU | ComputeFullV);
+}
+
+// Regression test for bug 286: JacobiSVD loops indefinitely with some
+// matrices containing denormal numbers.
+template<typename>
+void svd_underoverflow()
+{
+#if defined __INTEL_COMPILER
+// shut up warning #239: floating point underflow
+#pragma warning push
+#pragma warning disable 239
+#endif
+  Matrix2d M;
+  M << -7.90884e-313, -4.94e-324,
+                 0, 5.60844e-313;
+  SVD_DEFAULT(Matrix2d) svd;
+  svd.compute(M,ComputeFullU|ComputeFullV);
+  CALL_SUBTEST( svd_check_full(M,svd) );
+  
+  // Check all 2x2 matrices made with the following coefficients:
+  VectorXd value_set(9);
+  value_set << 0, 1, -1, 5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324, -4.94e-223, 4.94e-223;
+  Array4i id(0,0,0,0);
+  int k = 0;
+  do
+  {
+    M << value_set(id(0)), value_set(id(1)), value_set(id(2)), value_set(id(3));
+    svd.compute(M,ComputeFullU|ComputeFullV);
+    CALL_SUBTEST( svd_check_full(M,svd) );
+
+    id(k)++;
+    if(id(k)>=value_set.size())
+    {
+      while(k<3 && id(k)>=value_set.size()) id(++k)++;
+      id.head(k).setZero();
+      k=0;
+    }
+
+  } while((id<int(value_set.size())).all());
+  
+#if defined __INTEL_COMPILER
+#pragma warning pop
+#endif
+  
+  // Check for overflow:
+  Matrix3d M3;
+  M3 << 4.4331978442502944e+307, -5.8585363752028680e+307,  6.4527017443412964e+307,
+        3.7841695601406358e+307,  2.4331702789740617e+306, -3.5235707140272905e+307,
+       -8.7190887618028355e+307, -7.3453213709232193e+307, -2.4367363684472105e+307;
+
+  SVD_DEFAULT(Matrix3d) svd3;
+  svd3.compute(M3,ComputeFullU|ComputeFullV); // just check we don't loop indefinitely
+  CALL_SUBTEST( svd_check_full(M3,svd3) );
+}
+
+// void jacobisvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
+
+template<typename MatrixType>
+void svd_all_trivial_2x2( void (*cb)(const MatrixType&,bool) )
+{
+  MatrixType M;
+  VectorXd value_set(3);
+  value_set << 0, 1, -1;
+  Array4i id(0,0,0,0);
+  int k = 0;
+  do
+  {
+    M << value_set(id(0)), value_set(id(1)), value_set(id(2)), value_set(id(3));
+    
+    cb(M,false);
+    
+    id(k)++;
+    if(id(k)>=value_set.size())
+    {
+      while(k<3 && id(k)>=value_set.size()) id(++k)++;
+      id.head(k).setZero();
+      k=0;
+    }
+    
+  } while((id<int(value_set.size())).all());
+}
+
+template<typename>
+void svd_preallocate()
+{
+  Vector3f v(3.f, 2.f, 1.f);
+  MatrixXf m = v.asDiagonal();
+
+  internal::set_is_malloc_allowed(false);
+  VERIFY_RAISES_ASSERT(VectorXf tmp(10);)
+  SVD_DEFAULT(MatrixXf) svd;
+  internal::set_is_malloc_allowed(true);
+  svd.compute(m);
+  VERIFY_IS_APPROX(svd.singularValues(), v);
+
+  SVD_DEFAULT(MatrixXf) svd2(3,3);
+  internal::set_is_malloc_allowed(false);
+  svd2.compute(m);
+  internal::set_is_malloc_allowed(true);
+  VERIFY_IS_APPROX(svd2.singularValues(), v);
+  VERIFY_RAISES_ASSERT(svd2.matrixU());
+  VERIFY_RAISES_ASSERT(svd2.matrixV());
+  svd2.compute(m, ComputeFullU | ComputeFullV);
+  VERIFY_IS_APPROX(svd2.matrixU(), Matrix3f::Identity());
+  VERIFY_IS_APPROX(svd2.matrixV(), Matrix3f::Identity());
+  internal::set_is_malloc_allowed(false);
+  svd2.compute(m);
+  internal::set_is_malloc_allowed(true);
+
+  SVD_DEFAULT(MatrixXf) svd3(3,3,ComputeFullU|ComputeFullV);
+  internal::set_is_malloc_allowed(false);
+  svd2.compute(m);
+  internal::set_is_malloc_allowed(true);
+  VERIFY_IS_APPROX(svd2.singularValues(), v);
+  VERIFY_IS_APPROX(svd2.matrixU(), Matrix3f::Identity());
+  VERIFY_IS_APPROX(svd2.matrixV(), Matrix3f::Identity());
+  internal::set_is_malloc_allowed(false);
+  svd2.compute(m, ComputeFullU|ComputeFullV);
+  internal::set_is_malloc_allowed(true);
+}
+
+template<typename SvdType,typename MatrixType> 
+void svd_verify_assert(const MatrixType& m)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  enum {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime
+  };
+
+  typedef Matrix<Scalar, RowsAtCompileTime, 1> RhsType;
+  RhsType rhs(rows);
+  SvdType svd;
+  VERIFY_RAISES_ASSERT(svd.matrixU())
+  VERIFY_RAISES_ASSERT(svd.singularValues())
+  VERIFY_RAISES_ASSERT(svd.matrixV())
+  VERIFY_RAISES_ASSERT(svd.solve(rhs))
+  MatrixType a = MatrixType::Zero(rows, cols);
+  a.setZero();
+  svd.compute(a, 0);
+  VERIFY_RAISES_ASSERT(svd.matrixU())
+  VERIFY_RAISES_ASSERT(svd.matrixV())
+  svd.singularValues();
+  VERIFY_RAISES_ASSERT(svd.solve(rhs))
+    
+  if (ColsAtCompileTime == Dynamic)
+  {
+    svd.compute(a, ComputeThinU);
+    svd.matrixU();
+    VERIFY_RAISES_ASSERT(svd.matrixV())
+    VERIFY_RAISES_ASSERT(svd.solve(rhs))
+    svd.compute(a, ComputeThinV);
+    svd.matrixV();
+    VERIFY_RAISES_ASSERT(svd.matrixU())
+    VERIFY_RAISES_ASSERT(svd.solve(rhs))
+  }
+  else
+  {
+    VERIFY_RAISES_ASSERT(svd.compute(a, ComputeThinU))
+    VERIFY_RAISES_ASSERT(svd.compute(a, ComputeThinV))
+  }
+}
+
+#undef SVD_DEFAULT
+#undef SVD_FOR_MIN_NORM

ADDED   3rd_party/eigen/test/svd_fill.h
Index: 3rd_party/eigen/test/svd_fill.h
==================================================================
--- 3rd_party/eigen/test/svd_fill.h
+++ 3rd_party/eigen/test/svd_fill.h
@@ -0,0 +1,119 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+template<typename T>
+Array<T,4,1> four_denorms();
+
+template<>
+Array4f four_denorms() { return Array4f(5.60844e-39f, -5.60844e-39f, 4.94e-44f, -4.94e-44f); }
+template<>
+Array4d four_denorms() { return Array4d(5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324); }
+template<typename T>
+Array<T,4,1> four_denorms() { return four_denorms<double>().cast<T>(); }
+
+template<typename MatrixType>
+void svd_fill_random(MatrixType &m, int Option = 0)
+{
+  using std::pow;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename MatrixType::Index Index;
+  Index diagSize = (std::min)(m.rows(), m.cols());
+  RealScalar s = std::numeric_limits<RealScalar>::max_exponent10/4;
+  s = internal::random<RealScalar>(1,s);
+  Matrix<RealScalar,Dynamic,1> d =  Matrix<RealScalar,Dynamic,1>::Random(diagSize);
+  for(Index k=0; k<diagSize; ++k)
+    d(k) = d(k)*pow(RealScalar(10),internal::random<RealScalar>(-s,s));
+
+  bool dup     = internal::random<int>(0,10) < 3;
+  bool unit_uv = internal::random<int>(0,10) < (dup?7:3); // if we duplicate some diagonal entries, then increase the chance to preserve them using unitary U and V factors
+  
+  // duplicate some singular values
+  if(dup)
+  {
+    Index n = internal::random<Index>(0,d.size()-1);
+    for(Index i=0; i<n; ++i)
+      d(internal::random<Index>(0,d.size()-1)) = d(internal::random<Index>(0,d.size()-1));
+  }
+  
+  Matrix<Scalar,Dynamic,Dynamic> U(m.rows(),diagSize);
+  Matrix<Scalar,Dynamic,Dynamic> VT(diagSize,m.cols());
+  if(unit_uv)
+  {
+    // in very rare cases let's try with a pure diagonal matrix
+    if(internal::random<int>(0,10) < 1)
+    {
+      U.setIdentity();
+      VT.setIdentity();
+    }
+    else
+    {
+      createRandomPIMatrixOfRank(diagSize,U.rows(), U.cols(), U);
+      createRandomPIMatrixOfRank(diagSize,VT.rows(), VT.cols(), VT);
+    }
+  }
+  else
+  {
+    U.setRandom();
+    VT.setRandom();
+  }
+  
+  Matrix<Scalar,Dynamic,1> samples(9);
+  samples << 0, four_denorms<RealScalar>(),
+            -RealScalar(1)/NumTraits<RealScalar>::highest(), RealScalar(1)/NumTraits<RealScalar>::highest(), (std::numeric_limits<RealScalar>::min)(), pow((std::numeric_limits<RealScalar>::min)(),0.8);
+  
+  if(Option==Symmetric)
+  {
+    m = U * d.asDiagonal() * U.transpose();
+    
+    // randomly nullify some rows/columns
+    {
+      Index count = internal::random<Index>(-diagSize,diagSize);
+      for(Index k=0; k<count; ++k)
+      {
+        Index i = internal::random<Index>(0,diagSize-1);
+        m.row(i).setZero();
+        m.col(i).setZero();
+      }
+      if(count<0)
+      // (partly) cancel some coeffs
+      if(!(dup && unit_uv))
+      {
+        
+        Index n = internal::random<Index>(0,m.size()-1);
+        for(Index k=0; k<n; ++k)
+        {
+          Index i = internal::random<Index>(0,m.rows()-1);
+          Index j = internal::random<Index>(0,m.cols()-1);
+          m(j,i) = m(i,j) = samples(internal::random<Index>(0,samples.size()-1));
+          if(NumTraits<Scalar>::IsComplex)
+            *(&numext::real_ref(m(j,i))+1) = *(&numext::real_ref(m(i,j))+1) = samples.real()(internal::random<Index>(0,samples.size()-1));
+        }
+      }
+    }
+  }
+  else
+  {
+    m = U * d.asDiagonal() * VT;
+    // (partly) cancel some coeffs
+    if(!(dup && unit_uv))
+    {
+      Index n = internal::random<Index>(0,m.size()-1);
+      for(Index k=0; k<n; ++k)
+      {
+        Index i = internal::random<Index>(0,m.rows()-1);
+        Index j = internal::random<Index>(0,m.cols()-1);
+        m(i,j) = samples(internal::random<Index>(0,samples.size()-1));
+        if(NumTraits<Scalar>::IsComplex)
+          *(&numext::real_ref(m(i,j))+1) = samples.real()(internal::random<Index>(0,samples.size()-1));
+      }
+    }
+  }
+}
+

Index: 3rd_party/eigen/test/swap.cpp
==================================================================
--- 3rd_party/eigen/test/swap.cpp
+++ 3rd_party/eigen/test/swap.cpp
@@ -39,13 +39,19 @@
   MatrixType m1_copy = m1;
   MatrixType m2_copy = m2;
   OtherMatrixType m3_copy = m3;
   
   // test swapping 2 matrices of same type
+  Scalar *d1=m1.data(), *d2=m2.data();
   m1.swap(m2);
   VERIFY_IS_APPROX(m1,m2_copy);
   VERIFY_IS_APPROX(m2,m1_copy);
+  if(MatrixType::SizeAtCompileTime==Dynamic)
+  {
+    VERIFY(m1.data()==d2);
+    VERIFY(m2.data()==d1);
+  }
   m1 = m1_copy;
   m2 = m2_copy;
   
   // test swapping 2 matrices of different types
   m1.swap(m3);
@@ -66,18 +72,23 @@
   VERIFY_IS_APPROX(m1,m3_copy);
   VERIFY_IS_APPROX(m3,m1_copy);
   m1 = m1_copy;
   m3 = m3_copy;
   
-  // test assertion on mismatching size -- matrix case
-  VERIFY_RAISES_ASSERT(m1.swap(m1.row(0)));
-  // test assertion on mismatching size -- xpr case
-  VERIFY_RAISES_ASSERT(m1.row(0).swap(m1));
+  if(m1.rows()>1)
+  {
+    // test assertion on mismatching size -- matrix case
+    VERIFY_RAISES_ASSERT(m1.swap(m1.row(0)));
+    // test assertion on mismatching size -- xpr case
+    VERIFY_RAISES_ASSERT(m1.row(0).swap(m1));
+  }
 }
 
 void test_swap()
 {
+  int s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
   CALL_SUBTEST_1( swap(Matrix3f()) ); // fixed size, no vectorization 
   CALL_SUBTEST_2( swap(Matrix4d()) ); // fixed size, possible vectorization 
-  CALL_SUBTEST_3( swap(MatrixXd(3,3)) ); // dyn size, no vectorization 
-  CALL_SUBTEST_4( swap(MatrixXf(30,30)) ); // dyn size, possible vectorization 
+  CALL_SUBTEST_3( swap(MatrixXd(s,s)) ); // dyn size, no vectorization 
+  CALL_SUBTEST_4( swap(MatrixXf(s,s)) ); // dyn size, possible vectorization 
+  TEST_SET_BUT_UNUSED_VARIABLE(s)
 }

DELETED 3rd_party/eigen/test/testsuite.cmake
Index: 3rd_party/eigen/test/testsuite.cmake
==================================================================
--- 3rd_party/eigen/test/testsuite.cmake
+++ 3rd_party/eigen/test/testsuite.cmake
@@ -1,229 +0,0 @@
-
-####################################################################
-#
-# Usage:
-#  - create a new folder, let's call it cdash
-#  - in that folder, do:
-#    ctest -S path/to/eigen/test/testsuite.cmake[,option1=value1[,option2=value2]]
-#
-# Options:
-#  - EIGEN_CXX: compiler, eg.: g++-4.2
-#      default: default c++ compiler
-#  - EIGEN_SITE: eg, INRIA-Bdx_pc-gael, or the name of the contributor, etc.
-#      default: hostname
-#  - EIGEN_BUILD_STRING: a string which identify the system/compiler. It should be formed like that:
-#        <OS_name>-<OS_version>-<arch>-<compiler-version>
-#      with:
-#        <OS_name> = opensuse, debian, osx, windows, cygwin, freebsd, solaris, etc.
-#        <OS_version> = 11.1, XP, vista, leopard, etc.
-#        <arch> = i386, x86_64, ia64, powerpc, etc.
-#        <compiler-version> = gcc-4.3.2, icc-11.0, MSVC-2008, etc.
-#  - EIGEN_EXPLICIT_VECTORIZATION: novec, SSE2, Altivec
-#       default: SSE2 for x86_64 systems, novec otherwise
-#       Its value is automatically appended to EIGEN_BUILD_STRING
-#  - EIGEN_CMAKE_DIR: path to cmake executable
-#  - EIGEN_MODE: dashboard model, can be Experimental, Nightly, or Continuous
-#      default: Nightly
-#  - EIGEN_WORK_DIR: directory used to download the source files and make the builds
-#      default: folder which contains this script
-#  - EIGEN_CMAKE_ARGS: additional arguments passed to cmake
-#  - EIGEN_GENERATOR_TYPE: allows to overwrite the generator type
-#      default: nmake (windows
-#      See http://www.cmake.org/cmake/help/cmake2.6docs.html#section_Generators for a complete
-#      list of supported generators.
-#  - EIGEN_NO_UPDATE: allows to submit dash boards from local repositories
-#      This might be interesting in case you want to submit dashboards
-#      including local changes.
-#  - CTEST_SOURCE_DIRECTORY: path to eigen's src (use a new and empty folder, not the one you are working on)
-#      default: <EIGEN_WORK_DIR>/src
-#  - CTEST_BINARY_DIRECTORY: build directory
-#      default: <EIGEN_WORK_DIR>/nightly-<EIGEN_CXX>
-#
-# Here is an example running several compilers on a linux system:
-# #!/bin/bash
-# ARCH=`uname -m`
-# SITE=`hostname`
-# VERSION=opensuse-11.1
-# WORK_DIR=/home/gael/Coding/eigen/cdash
-# # get the last version of the script
-# wget http://bitbucket.org/eigen/eigen/raw/tip/test/testsuite.cmake -o $WORK_DIR/testsuite.cmake
-# COMMON="ctest -S $WORK_DIR/testsuite.cmake,EIGEN_WORK_DIR=$WORK_DIR,EIGEN_SITE=$SITE,EIGEN_MODE=$1,EIGEN_BUILD_STRING=$OS_VERSION-$ARCH"
-# $COMMON-gcc-3.4.6,EIGEN_CXX=g++-3.4
-# $COMMON-gcc-4.0.1,EIGEN_CXX=g++-4.0.1
-# $COMMON-gcc-4.3.2,EIGEN_CXX=g++-4.3,EIGEN_EXPLICIT_VECTORIZATION=novec
-# $COMMON-gcc-4.3.2,EIGEN_CXX=g++-4.3,EIGEN_EXPLICIT_VECTORIZATION=SSE2
-# $COMMON-icc-11.0,EIGEN_CXX=icpc
-#
-####################################################################
-
-# process the arguments
-
-set(ARGLIST ${CTEST_SCRIPT_ARG})
-while(${ARGLIST} MATCHES  ".+.*")
-
-  # pick first
-  string(REGEX MATCH "([^,]*)(,.*)?" DUMMY ${ARGLIST})
-  SET(TOP ${CMAKE_MATCH_1})
-
-  # remove first
-  string(REGEX MATCHALL "[^,]*,(.*)" DUMMY ${ARGLIST})
-  SET(ARGLIST ${CMAKE_MATCH_1})
-
-  # decompose as a pair key=value
-  string(REGEX MATCH "([^=]*)(=.*)?" DUMMY ${TOP})
-  SET(KEY ${CMAKE_MATCH_1})
-
-  string(REGEX MATCH "[^=]*=(.*)" DUMMY ${TOP})
-  SET(VALUE ${CMAKE_MATCH_1})
-
-  # set the variable to the specified value
-  if(VALUE)
-    SET(${KEY} ${VALUE})
-  else(VALUE)
-    SET(${KEY} ON)
-  endif(VALUE)
-
-endwhile(${ARGLIST} MATCHES ".+.*")
-
-####################################################################
-# Automatically set some user variables if they have not been defined manually
-####################################################################
-cmake_minimum_required(VERSION 2.6 FATAL_ERROR)
-
-if(NOT EIGEN_SITE)
-  site_name(EIGEN_SITE)
-endif(NOT EIGEN_SITE)
-
-if(NOT EIGEN_CMAKE_DIR)
-  SET(EIGEN_CMAKE_DIR "")
-endif(NOT EIGEN_CMAKE_DIR)
-
-if(NOT EIGEN_BUILD_STRING)
-
-  # let's try to find all information we need to make the build string ourself
-
-  # OS
-  build_name(EIGEN_OS_VERSION)
-
-  # arch
-  set(EIGEN_ARCH ${CMAKE_SYSTEM_PROCESSOR})
-  if(WIN32)
-    set(EIGEN_ARCH $ENV{PROCESSOR_ARCHITECTURE})
-  else(WIN32)
-    execute_process(COMMAND uname -m OUTPUT_VARIABLE EIGEN_ARCH OUTPUT_STRIP_TRAILING_WHITESPACE)
-  endif(WIN32)
-
-  set(EIGEN_BUILD_STRING ${EIGEN_OS_VERSION}${EIGEN_ARCH}-${EIGEN_CXX})
-
-endif(NOT EIGEN_BUILD_STRING)
-
-if(DEFINED EIGEN_EXPLICIT_VECTORIZATION)
-  set(EIGEN_BUILD_STRING ${EIGEN_BUILD_STRING}-${EIGEN_EXPLICIT_VECTORIZATION})
-endif(DEFINED EIGEN_EXPLICIT_VECTORIZATION)
-
-if(NOT EIGEN_WORK_DIR)
-  set(EIGEN_WORK_DIR ${CTEST_SCRIPT_DIRECTORY})
-endif(NOT EIGEN_WORK_DIR)
-
-if(NOT CTEST_SOURCE_DIRECTORY)
-  SET (CTEST_SOURCE_DIRECTORY "${EIGEN_WORK_DIR}/src")
-endif(NOT CTEST_SOURCE_DIRECTORY)
-
-if(NOT CTEST_BINARY_DIRECTORY)
-  SET (CTEST_BINARY_DIRECTORY "${EIGEN_WORK_DIR}/nightly_${EIGEN_CXX}")
-endif(NOT CTEST_BINARY_DIRECTORY)
-
-if(NOT EIGEN_MODE)
-  set(EIGEN_MODE Nightly)
-endif(NOT EIGEN_MODE)
-
-## mandatory variables (the default should be ok in most cases):
-
-if(NOT EIGEN_NO_UPDATE)
-  SET (CTEST_CVS_COMMAND "hg")
-  SET (CTEST_CVS_CHECKOUT "${CTEST_CVS_COMMAND} clone http://bitbucket.org/eigen/eigen \"${CTEST_SOURCE_DIRECTORY}\"")
-  SET(CTEST_BACKUP_AND_RESTORE TRUE) # the backup is CVS related ...
-endif(NOT EIGEN_NO_UPDATE)
-
-# which ctest command to use for running the dashboard
-SET (CTEST_COMMAND "${EIGEN_CMAKE_DIR}ctest -D ${EIGEN_MODE} --no-compress-output")
-if($ENV{EIGEN_CTEST_ARGS})
-SET (CTEST_COMMAND "${CTEST_COMMAND} $ENV{EIGEN_CTEST_ARGS}")
-endif($ENV{EIGEN_CTEST_ARGS})
-# what cmake command to use for configuring this dashboard
-SET (CTEST_CMAKE_COMMAND "${EIGEN_CMAKE_DIR}cmake -DEIGEN_LEAVE_TEST_IN_ALL_TARGET=ON")
-
-####################################################################
-# The values in this section are optional you can either
-# have them or leave them commented out
-####################################################################
-
-# this make sure we get consistent outputs
-SET($ENV{LC_MESSAGES} "en_EN")
-
-# should ctest wipe the binary tree before running
-SET(CTEST_START_WITH_EMPTY_BINARY_DIRECTORY TRUE)
-
-# raise the warning/error limit
-set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_WARNINGS "33331")
-set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_ERRORS "33331")
-
-# this is the initial cache to use for the binary tree, be careful to escape
-# any quotes inside of this string if you use it
-if(WIN32 AND NOT UNIX)
-  #message(SEND_ERROR "win32")
-  if(EIGEN_GENERATOR_TYPE)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -G \"${EIGEN_GENERATOR_TYPE}\"")
-    SET (CTEST_INITIAL_CACHE "
-      CMAKE_BUILD_TYPE:STRING=Release
-      BUILDNAME:STRING=${EIGEN_BUILD_STRING}
-      SITE:STRING=${EIGEN_SITE}
-    ")
-  else(EIGEN_GENERATOR_TYPE)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -G \"NMake Makefiles\" -DCMAKE_MAKE_PROGRAM=nmake")
-    SET (CTEST_INITIAL_CACHE "
-      MAKECOMMAND:STRING=nmake /i
-      CMAKE_MAKE_PROGRAM:FILEPATH=nmake
-      CMAKE_GENERATOR:INTERNAL=NMake Makefiles
-      CMAKE_BUILD_TYPE:STRING=Release
-      BUILDNAME:STRING=${EIGEN_BUILD_STRING}
-      SITE:STRING=${EIGEN_SITE}
-    ")
-  endif(EIGEN_GENERATOR_TYPE)
-else(WIN32 AND NOT UNIX)
-  SET (CTEST_INITIAL_CACHE "
-    BUILDNAME:STRING=${EIGEN_BUILD_STRING}
-    SITE:STRING=${EIGEN_SITE}
-  ")
-endif(WIN32 AND NOT UNIX)
-
-# set any extra environment variables to use during the execution of the script here:
-# setting this variable on windows machines causes trouble ...
-
-if(EIGEN_CXX AND NOT WIN32)
-  set(CTEST_ENVIRONMENT "CXX=${EIGEN_CXX}")
-endif(EIGEN_CXX AND NOT WIN32)
-
-if(DEFINED EIGEN_EXPLICIT_VECTORIZATION)
-  if(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE2)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_SSE2=ON")
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE3)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_SSE2=ON -DEIGEN_TEST_SSE3=ON")
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSSE3)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_SSE2=ON -DEIGEN_TEST_SSE3=ON -DEIGEN_TEST_SSSE3=ON")  
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE4_1)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_SSE2=ON -DEIGEN_TEST_SSE3=ON -DEIGEN_TEST_SSSE3=ON -DEIGEN_TEST_SSE4_1=ON")
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE4_2)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_SSE2=ON -DEIGEN_TEST_SSE3=ON -DEIGEN_TEST_SSSE3=ON -DEIGEN_TEST_SSE4_1=ON -DEIGEN_TEST_SSE4_2=ON")
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES Altivec)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_ALTIVEC=ON")
-  elseif(EIGEN_EXPLICIT_VECTORIZATION MATCHES novec)
-    set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} -DEIGEN_TEST_NO_EXPLICIT_VECTORIZATION=ON")
-  else(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE2)
-    message(FATAL_ERROR "Invalid value for EIGEN_EXPLICIT_VECTORIZATION (${EIGEN_EXPLICIT_VECTORIZATION}), must be: novec, SSE2, SSE3, Altivec")
-  endif(EIGEN_EXPLICIT_VECTORIZATION MATCHES SSE2)
-endif(DEFINED EIGEN_EXPLICIT_VECTORIZATION)
-
-if(DEFINED EIGEN_CMAKE_ARGS)
-  set(CTEST_CMAKE_COMMAND "${CTEST_CMAKE_COMMAND} ${EIGEN_CMAKE_ARGS}")
-endif(DEFINED EIGEN_CMAKE_ARGS)

Index: 3rd_party/eigen/test/triangular.cpp
==================================================================
--- 3rd_party/eigen/test/triangular.cpp
+++ 3rd_party/eigen/test/triangular.cpp
@@ -63,11 +63,11 @@
   VERIFY_IS_APPROX(m3.template triangularView<Lower>().conjugate().toDenseMatrix(),
                    m3.conjugate().template triangularView<Lower>().toDenseMatrix());
 
   m1 = MatrixType::Random(rows, cols);
   for (int i=0; i<rows; ++i)
-    while (numext::abs2(m1(i,i))<1e-1) m1(i,i) = internal::random<Scalar>();
+    while (numext::abs2(m1(i,i))<RealScalar(1e-1)) m1(i,i) = internal::random<Scalar>();
 
   Transpose<MatrixType> trm4(m4);
   // test back and forward subsitution with a vector as the rhs
   m3 = m1.template triangularView<Upper>();
   VERIFY(v2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<Lower>().solve(v2)), largerEps));
@@ -76,11 +76,11 @@
   m3 = m1.template triangularView<Upper>();
   VERIFY(v2.isApprox(m3 * (m1.template triangularView<Upper>().solve(v2)), largerEps));
   m3 = m1.template triangularView<Lower>();
   VERIFY(v2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<Lower>().solve(v2)), largerEps));
 
-  // test back and forward subsitution with a matrix as the rhs
+  // test back and forward substitution with a matrix as the rhs
   m3 = m1.template triangularView<Upper>();
   VERIFY(m2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<Lower>().solve(m2)), largerEps));
   m3 = m1.template triangularView<Lower>();
   VERIFY(m2.isApprox(m3.transpose() * (m1.transpose().template triangularView<Upper>().solve(m2)), largerEps));
   m3 = m1.template triangularView<Upper>();
@@ -111,10 +111,25 @@
   m2.setZero();
   m2.template triangularView<Upper>().swap(m1);
   m3.setZero();
   m3.template triangularView<Upper>().setOnes();
   VERIFY_IS_APPROX(m2,m3);
+  
+  m1.setRandom();
+  m3 = m1.template triangularView<Upper>();
+  Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> m5(cols, internal::random<int>(1,20));  m5.setRandom();
+  Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> m6(internal::random<int>(1,20), rows);  m6.setRandom();
+  VERIFY_IS_APPROX(m1.template triangularView<Upper>() * m5, m3*m5);
+  VERIFY_IS_APPROX(m6*m1.template triangularView<Upper>(), m6*m3);
+
+  m1up = m1.template triangularView<Upper>();
+  VERIFY_IS_APPROX(m1.template selfadjointView<Upper>().template triangularView<Upper>().toDenseMatrix(), m1up);
+  VERIFY_IS_APPROX(m1up.template selfadjointView<Upper>().template triangularView<Upper>().toDenseMatrix(), m1up);
+  VERIFY_IS_APPROX(m1.template selfadjointView<Upper>().template triangularView<Lower>().toDenseMatrix(), m1up.adjoint());
+  VERIFY_IS_APPROX(m1up.template selfadjointView<Upper>().template triangularView<Lower>().toDenseMatrix(), m1up.adjoint());
+
+  VERIFY_IS_APPROX(m1.template selfadjointView<Upper>().diagonal(), m1.diagonal());
 
 }
 
 
 template<typename MatrixType> void triangular_rect(const MatrixType& m)

Index: 3rd_party/eigen/test/umfpack_support.cpp
==================================================================
--- 3rd_party/eigen/test/umfpack_support.cpp
+++ 3rd_party/eigen/test/umfpack_support.cpp
@@ -5,10 +5,11 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#define EIGEN_NO_DEBUG_SMALL_PRODUCT_BLOCKS
 #include "sparse_solver.h"
 
 #include <Eigen/UmfPackSupport>
 
 template<typename T> void test_umfpack_support_T()

Index: 3rd_party/eigen/test/unalignedassert.cpp
==================================================================
--- 3rd_party/eigen/test/unalignedassert.cpp
+++ 3rd_party/eigen/test/unalignedassert.cpp
@@ -1,16 +1,42 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#if defined(EIGEN_TEST_PART_1)
+  // default
+#elif defined(EIGEN_TEST_PART_2)
+  #define EIGEN_MAX_STATIC_ALIGN_BYTES 16
+  #define EIGEN_MAX_ALIGN_BYTES 16
+#elif defined(EIGEN_TEST_PART_3)
+  #define EIGEN_MAX_STATIC_ALIGN_BYTES 32
+  #define EIGEN_MAX_ALIGN_BYTES 32
+#elif defined(EIGEN_TEST_PART_4)
+  #define EIGEN_MAX_STATIC_ALIGN_BYTES 64
+  #define EIGEN_MAX_ALIGN_BYTES 64
+#endif
 
 #include "main.h"
 
+typedef Matrix<float,  6,1> Vector6f;
+typedef Matrix<float,  8,1> Vector8f;
+typedef Matrix<float, 12,1> Vector12f;
+
+typedef Matrix<double, 5,1> Vector5d;
+typedef Matrix<double, 6,1> Vector6d;
+typedef Matrix<double, 7,1> Vector7d;
+typedef Matrix<double, 8,1> Vector8d;
+typedef Matrix<double, 9,1> Vector9d;
+typedef Matrix<double,10,1> Vector10d;
+typedef Matrix<double,12,1> Vector12d;
+
 struct TestNew1
 {
   MatrixXd m; // good: m will allocate its own array, taking care of alignment.
   TestNew1() : m(20,20) {}
 };
@@ -34,11 +60,11 @@
 };
 
 struct TestNew5
 {
   EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  float f; // try the f at first -- the EIGEN_ALIGN16 attribute of m should make that still work
+  float f; // try the f at first -- the EIGEN_ALIGN_MAX attribute of m should make that still work
   Matrix4f m;
 };
 
 struct TestNew6
 {
@@ -61,46 +87,56 @@
   delete x;
   y = new T[2];
   delete[] y;
 }
 
-#if EIGEN_ALIGN_STATICALLY
+#if EIGEN_MAX_STATIC_ALIGN_BYTES>0
 template<typename T>
 void construct_at_boundary(int boundary)
 {
   char buf[sizeof(T)+256];
-  size_t _buf = reinterpret_cast<size_t>(buf);
-  _buf += (16 - (_buf % 16)); // make 16-byte aligned
+  size_t _buf = reinterpret_cast<internal::UIntPtr>(buf);
+  _buf += (EIGEN_MAX_ALIGN_BYTES - (_buf % EIGEN_MAX_ALIGN_BYTES)); // make 16/32/...-byte aligned
   _buf += boundary; // make exact boundary-aligned
   T *x = ::new(reinterpret_cast<void*>(_buf)) T;
   x[0].setZero(); // just in order to silence warnings
   x->~T();
 }
 #endif
 
 void unalignedassert()
 {
-  #if EIGEN_ALIGN_STATICALLY
+#if EIGEN_MAX_STATIC_ALIGN_BYTES>0
   construct_at_boundary<Vector2f>(4);
   construct_at_boundary<Vector3f>(4);
   construct_at_boundary<Vector4f>(16);
+  construct_at_boundary<Vector6f>(4);
+  construct_at_boundary<Vector8f>(EIGEN_MAX_ALIGN_BYTES);
+  construct_at_boundary<Vector12f>(16);
   construct_at_boundary<Matrix2f>(16);
   construct_at_boundary<Matrix3f>(4);
-  construct_at_boundary<Matrix4f>(16);
+  construct_at_boundary<Matrix4f>(EIGEN_MAX_ALIGN_BYTES);
 
   construct_at_boundary<Vector2d>(16);
   construct_at_boundary<Vector3d>(4);
-  construct_at_boundary<Vector4d>(16);
-  construct_at_boundary<Matrix2d>(16);
+  construct_at_boundary<Vector4d>(EIGEN_MAX_ALIGN_BYTES);
+  construct_at_boundary<Vector5d>(4);
+  construct_at_boundary<Vector6d>(16);
+  construct_at_boundary<Vector7d>(4);
+  construct_at_boundary<Vector8d>(EIGEN_MAX_ALIGN_BYTES);
+  construct_at_boundary<Vector9d>(4);
+  construct_at_boundary<Vector10d>(16);
+  construct_at_boundary<Vector12d>(EIGEN_MAX_ALIGN_BYTES);
+  construct_at_boundary<Matrix2d>(EIGEN_MAX_ALIGN_BYTES);
   construct_at_boundary<Matrix3d>(4);
-  construct_at_boundary<Matrix4d>(16);
+  construct_at_boundary<Matrix4d>(EIGEN_MAX_ALIGN_BYTES);
 
   construct_at_boundary<Vector2cf>(16);
   construct_at_boundary<Vector3cf>(4);
-  construct_at_boundary<Vector2cd>(16);
+  construct_at_boundary<Vector2cd>(EIGEN_MAX_ALIGN_BYTES);
   construct_at_boundary<Vector3cd>(16);
-  #endif
+#endif
 
   check_unalignedassert_good<TestNew1>();
   check_unalignedassert_good<TestNew2>();
   check_unalignedassert_good<TestNew3>();
 
@@ -107,21 +143,38 @@
   check_unalignedassert_good<TestNew4>();
   check_unalignedassert_good<TestNew5>();
   check_unalignedassert_good<TestNew6>();
   check_unalignedassert_good<Depends<true> >();
 
-#if EIGEN_ALIGN_STATICALLY
-  VERIFY_RAISES_ASSERT(construct_at_boundary<Vector4f>(8));
-  VERIFY_RAISES_ASSERT(construct_at_boundary<Matrix4f>(8));
-  VERIFY_RAISES_ASSERT(construct_at_boundary<Vector2d>(8));
-  VERIFY_RAISES_ASSERT(construct_at_boundary<Vector4d>(8));
-  VERIFY_RAISES_ASSERT(construct_at_boundary<Matrix2d>(8));
-  VERIFY_RAISES_ASSERT(construct_at_boundary<Matrix4d>(8));
-  VERIFY_RAISES_ASSERT(construct_at_boundary<Vector2cf>(8));
-  VERIFY_RAISES_ASSERT(construct_at_boundary<Vector2cd>(8));
+#if EIGEN_MAX_STATIC_ALIGN_BYTES>0
+  if(EIGEN_MAX_ALIGN_BYTES>=16)
+  {
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector4f>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector8f>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector12f>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector2d>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector4d>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector6d>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector8d>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector10d>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector12d>(8));
+    // Complexes are disabled because the compiler might aggressively vectorize
+    // the initialization of complex coeffs to 0 before we can check for alignedness
+    //VERIFY_RAISES_ASSERT(construct_at_boundary<Vector2cf>(8));
+    VERIFY_RAISES_ASSERT(construct_at_boundary<Vector4i>(8));
+  }
+  for(int b=8; b<EIGEN_MAX_ALIGN_BYTES; b+=8)
+  {
+    if(b<32)  VERIFY_RAISES_ASSERT(construct_at_boundary<Vector8f>(b));
+    if(b<64)  VERIFY_RAISES_ASSERT(construct_at_boundary<Matrix4f>(b));
+    if(b<32)  VERIFY_RAISES_ASSERT(construct_at_boundary<Vector4d>(b));
+    if(b<32)  VERIFY_RAISES_ASSERT(construct_at_boundary<Matrix2d>(b));
+    if(b<128) VERIFY_RAISES_ASSERT(construct_at_boundary<Matrix4d>(b));
+    //if(b<32)  VERIFY_RAISES_ASSERT(construct_at_boundary<Vector2cd>(b));
+  }
 #endif
 }
 
 void test_unalignedassert()
 {
   CALL_SUBTEST(unalignedassert());
 }

Index: 3rd_party/eigen/test/unalignedcount.cpp
==================================================================
--- 3rd_party/eigen/test/unalignedcount.cpp
+++ 3rd_party/eigen/test/unalignedcount.cpp
@@ -28,11 +28,18 @@
 
 #include "main.h"
 
 void test_unalignedcount()
 {
-  #ifdef EIGEN_VECTORIZE_SSE
+  #if defined(EIGEN_VECTORIZE_AVX)
+  VectorXf a(40), b(40);
+  VERIFY_ALIGNED_UNALIGNED_COUNT(a += b, 10, 0, 5, 0);
+  VERIFY_ALIGNED_UNALIGNED_COUNT(a.segment(0,40) += b.segment(0,40), 5, 5, 5, 0);
+  VERIFY_ALIGNED_UNALIGNED_COUNT(a.segment(0,40) -= b.segment(0,40), 5, 5, 5, 0);
+  VERIFY_ALIGNED_UNALIGNED_COUNT(a.segment(0,40) *= 3.5, 5, 0, 5, 0);
+  VERIFY_ALIGNED_UNALIGNED_COUNT(a.segment(0,40) /= 3.5, 5, 0, 5, 0);
+  #elif defined(EIGEN_VECTORIZE_SSE)
   VectorXf a(40), b(40);
   VERIFY_ALIGNED_UNALIGNED_COUNT(a += b, 20, 0, 10, 0);
   VERIFY_ALIGNED_UNALIGNED_COUNT(a.segment(0,40) += b.segment(0,40), 10, 10, 10, 0);
   VERIFY_ALIGNED_UNALIGNED_COUNT(a.segment(0,40) -= b.segment(0,40), 10, 10, 10, 0);
   VERIFY_ALIGNED_UNALIGNED_COUNT(a.segment(0,40) *= 3.5, 10, 0, 10, 0);

Index: 3rd_party/eigen/test/upperbidiagonalization.cpp
==================================================================
--- 3rd_party/eigen/test/upperbidiagonalization.cpp
+++ 3rd_party/eigen/test/upperbidiagonalization.cpp
@@ -33,11 +33,11 @@
 {
   for(int i = 0; i < g_repeat; i++) {
    CALL_SUBTEST_1( upperbidiag(MatrixXf(3,3)) );
    CALL_SUBTEST_2( upperbidiag(MatrixXd(17,12)) );
    CALL_SUBTEST_3( upperbidiag(MatrixXcf(20,20)) );
-   CALL_SUBTEST_4( upperbidiag(MatrixXcd(16,15)) );
+   CALL_SUBTEST_4( upperbidiag(Matrix<std::complex<double>,Dynamic,Dynamic,RowMajor>(16,15)) );
    CALL_SUBTEST_5( upperbidiag(Matrix<float,6,4>()) );
    CALL_SUBTEST_6( upperbidiag(Matrix<float,5,5>()) );
    CALL_SUBTEST_7( upperbidiag(Matrix<double,4,3>()) );
   }
 }

Index: 3rd_party/eigen/test/vectorization_logic.cpp
==================================================================
--- 3rd_party/eigen/test/vectorization_logic.cpp
+++ 3rd_party/eigen/test/vectorization_logic.cpp
@@ -1,86 +1,108 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#ifdef EIGEN_TEST_PART_1
+#define EIGEN_UNALIGNED_VECTORIZE 1
+#endif
+
+#ifdef EIGEN_TEST_PART_2
+#define EIGEN_UNALIGNED_VECTORIZE 0
+#endif
+
+#ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
+#undef EIGEN_DEFAULT_TO_ROW_MAJOR
+#endif
 #define EIGEN_DEBUG_ASSIGN
 #include "main.h"
 #include <typeinfo>
 
-std::string demangle_traversal(int t)
-{
-  if(t==DefaultTraversal) return "DefaultTraversal";
-  if(t==LinearTraversal) return "LinearTraversal";
-  if(t==InnerVectorizedTraversal) return "InnerVectorizedTraversal";
-  if(t==LinearVectorizedTraversal) return "LinearVectorizedTraversal";
-  if(t==SliceVectorizedTraversal) return "SliceVectorizedTraversal";
-  return "?";
-}
-std::string demangle_unrolling(int t)
-{
-  if(t==NoUnrolling) return "NoUnrolling";
-  if(t==InnerUnrolling) return "InnerUnrolling";
-  if(t==CompleteUnrolling) return "CompleteUnrolling";
-  return "?";
-}
+using internal::demangle_flags;
+using internal::demangle_traversal;
+using internal::demangle_unrolling;
 
 template<typename Dst, typename Src>
 bool test_assign(const Dst&, const Src&, int traversal, int unrolling)
 {
-  internal::assign_traits<Dst,Src>::debug();
-  bool res = internal::assign_traits<Dst,Src>::Traversal==traversal
-          && internal::assign_traits<Dst,Src>::Unrolling==unrolling;
+  typedef internal::copy_using_evaluator_traits<internal::evaluator<Dst>,internal::evaluator<Src>, internal::assign_op<typename Dst::Scalar,typename Src::Scalar> > traits;
+  bool res = traits::Traversal==traversal;
+  if(unrolling==InnerUnrolling+CompleteUnrolling)
+    res = res && (int(traits::Unrolling)==InnerUnrolling || int(traits::Unrolling)==CompleteUnrolling);
+  else
+    res = res && int(traits::Unrolling)==unrolling;
   if(!res)
   {
+    std::cerr << "Src: " << demangle_flags(Src::Flags) << std::endl;
+    std::cerr << "     " << demangle_flags(internal::evaluator<Src>::Flags) << std::endl;
+    std::cerr << "Dst: " << demangle_flags(Dst::Flags) << std::endl;
+    std::cerr << "     " << demangle_flags(internal::evaluator<Dst>::Flags) << std::endl;
+    traits::debug();
     std::cerr << " Expected Traversal == " << demangle_traversal(traversal)
-              << " got " << demangle_traversal(internal::assign_traits<Dst,Src>::Traversal) << "\n";
+              << " got " << demangle_traversal(traits::Traversal) << "\n";
     std::cerr << " Expected Unrolling == " << demangle_unrolling(unrolling)
-              << " got " << demangle_unrolling(internal::assign_traits<Dst,Src>::Unrolling) << "\n";
+              << " got " << demangle_unrolling(traits::Unrolling) << "\n";
   }
   return res;
 }
 
 template<typename Dst, typename Src>
 bool test_assign(int traversal, int unrolling)
 {
-  internal::assign_traits<Dst,Src>::debug();
-  bool res = internal::assign_traits<Dst,Src>::Traversal==traversal
-          && internal::assign_traits<Dst,Src>::Unrolling==unrolling;
+  typedef internal::copy_using_evaluator_traits<internal::evaluator<Dst>,internal::evaluator<Src>, internal::assign_op<typename Dst::Scalar,typename Src::Scalar> > traits;
+  bool res = traits::Traversal==traversal && traits::Unrolling==unrolling;
   if(!res)
   {
+    std::cerr << "Src: " << demangle_flags(Src::Flags) << std::endl;
+    std::cerr << "     " << demangle_flags(internal::evaluator<Src>::Flags) << std::endl;
+    std::cerr << "Dst: " << demangle_flags(Dst::Flags) << std::endl;
+    std::cerr << "     " << demangle_flags(internal::evaluator<Dst>::Flags) << std::endl;
+    traits::debug();
     std::cerr << " Expected Traversal == " << demangle_traversal(traversal)
-              << " got " << demangle_traversal(internal::assign_traits<Dst,Src>::Traversal) << "\n";
+              << " got " << demangle_traversal(traits::Traversal) << "\n";
     std::cerr << " Expected Unrolling == " << demangle_unrolling(unrolling)
-              << " got " << demangle_unrolling(internal::assign_traits<Dst,Src>::Unrolling) << "\n";
+              << " got " << demangle_unrolling(traits::Unrolling) << "\n";
   }
   return res;
 }
 
 template<typename Xpr>
 bool test_redux(const Xpr&, int traversal, int unrolling)
 {
-  typedef internal::redux_traits<internal::scalar_sum_op<typename Xpr::Scalar>,Xpr> traits;
+  typedef typename Xpr::Scalar Scalar;
+  typedef internal::redux_traits<internal::scalar_sum_op<Scalar,Scalar>,internal::redux_evaluator<Xpr> > traits;
+  
   bool res = traits::Traversal==traversal && traits::Unrolling==unrolling;
   if(!res)
   {
+    std::cerr << demangle_flags(Xpr::Flags) << std::endl;
+    std::cerr << demangle_flags(internal::evaluator<Xpr>::Flags) << std::endl;
+    traits::debug();
+    
     std::cerr << " Expected Traversal == " << demangle_traversal(traversal)
               << " got " << demangle_traversal(traits::Traversal) << "\n";
     std::cerr << " Expected Unrolling == " << demangle_unrolling(unrolling)
               << " got " << demangle_unrolling(traits::Unrolling) << "\n";
   }
   return res;
 }
 
-template<typename Scalar, bool Enable = internal::packet_traits<Scalar>::Vectorizable> struct vectorization_logic
+template<typename Scalar, bool Enable = internal::packet_traits<Scalar>::Vectorizable>
+struct vectorization_logic
 {
+  typedef internal::packet_traits<Scalar> PacketTraits;
+  
+  typedef typename internal::packet_traits<Scalar>::type PacketType;
+  typedef typename internal::unpacket_traits<PacketType>::half HalfPacketType;
   enum {
-    PacketSize = internal::packet_traits<Scalar>::size
+    PacketSize = internal::unpacket_traits<PacketType>::size,
+    HalfPacketSize = internal::unpacket_traits<HalfPacketType>::size
   };
   static void run()
   {
     
     typedef Matrix<Scalar,PacketSize,1> Vector1;
@@ -88,12 +110,12 @@
     typedef Matrix<Scalar,Dynamic,Dynamic> MatrixXX;
     typedef Matrix<Scalar,PacketSize,PacketSize> Matrix11;
     typedef Matrix<Scalar,2*PacketSize,2*PacketSize> Matrix22;
     typedef Matrix<Scalar,(Matrix11::Flags&RowMajorBit)?16:4*PacketSize,(Matrix11::Flags&RowMajorBit)?4*PacketSize:16> Matrix44;
     typedef Matrix<Scalar,(Matrix11::Flags&RowMajorBit)?16:4*PacketSize,(Matrix11::Flags&RowMajorBit)?4*PacketSize:16,DontAlign|EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION> Matrix44u;
-    typedef Matrix<Scalar,4*PacketSize,16,ColMajor> Matrix44c;
-    typedef Matrix<Scalar,4*PacketSize,16,RowMajor> Matrix44r;
+    typedef Matrix<Scalar,4*PacketSize,4*PacketSize,ColMajor> Matrix44c;
+    typedef Matrix<Scalar,4*PacketSize,4*PacketSize,RowMajor> Matrix44r;
 
     typedef Matrix<Scalar,
         (PacketSize==8 ? 4 : PacketSize==4 ? 2 : PacketSize==2 ? 1 : /*PacketSize==1 ?*/ 1),
         (PacketSize==8 ? 2 : PacketSize==4 ? 2 : PacketSize==2 ? 2 : /*PacketSize==1 ?*/ 1)
       > Matrix1;
@@ -129,39 +151,67 @@
 
     VERIFY(test_assign(Matrix44(),Matrix44()+Matrix44(),
       InnerVectorizedTraversal,InnerUnrolling));
 
     VERIFY(test_assign(Matrix44u(),Matrix44()+Matrix44(),
-      LinearTraversal,NoUnrolling));
+      EIGEN_UNALIGNED_VECTORIZE ? InnerVectorizedTraversal : LinearTraversal,
+      EIGEN_UNALIGNED_VECTORIZE ? InnerUnrolling : NoUnrolling));
+
+    VERIFY(test_assign(Matrix1(),Matrix1()+Matrix1(),
+      (Matrix1::InnerSizeAtCompileTime % PacketSize)==0 ? InnerVectorizedTraversal : LinearVectorizedTraversal,
+      CompleteUnrolling));
 
     VERIFY(test_assign(Matrix1u(),Matrix1()+Matrix1(),
-      LinearTraversal,CompleteUnrolling));
+      EIGEN_UNALIGNED_VECTORIZE ? ((Matrix1::InnerSizeAtCompileTime % PacketSize)==0 ? InnerVectorizedTraversal : LinearVectorizedTraversal)
+                                : LinearTraversal, CompleteUnrolling));
 
     VERIFY(test_assign(Matrix44c().col(1),Matrix44c().col(2)+Matrix44c().col(3),
       InnerVectorizedTraversal,CompleteUnrolling));
-    
+
     VERIFY(test_assign(Matrix44r().row(2),Matrix44r().row(1)+Matrix44r().row(1),
       InnerVectorizedTraversal,CompleteUnrolling));
-        
+
     if(PacketSize>1)
     {
       typedef Matrix<Scalar,3,3,ColMajor> Matrix33c;
+      typedef Matrix<Scalar,3,1,ColMajor> Vector3;
       VERIFY(test_assign(Matrix33c().row(2),Matrix33c().row(1)+Matrix33c().row(1),
         LinearTraversal,CompleteUnrolling));
+      VERIFY(test_assign(Vector3(),Vector3()+Vector3(),
+        EIGEN_UNALIGNED_VECTORIZE ? (HalfPacketSize==1 ? InnerVectorizedTraversal : LinearVectorizedTraversal) : (HalfPacketSize==1 ? InnerVectorizedTraversal : LinearTraversal), CompleteUnrolling));
       VERIFY(test_assign(Matrix33c().col(0),Matrix33c().col(1)+Matrix33c().col(1),
-        LinearTraversal,CompleteUnrolling));
-      
-      VERIFY(test_assign(Matrix3(),Matrix3().cwiseQuotient(Matrix3()),
+        EIGEN_UNALIGNED_VECTORIZE ? (HalfPacketSize==1 ? InnerVectorizedTraversal : LinearVectorizedTraversal) : (HalfPacketSize==1 ? SliceVectorizedTraversal : LinearTraversal),
+        ((!EIGEN_UNALIGNED_VECTORIZE) && HalfPacketSize==1) ? NoUnrolling : CompleteUnrolling));
+
+      VERIFY(test_assign(Matrix3(),Matrix3().cwiseProduct(Matrix3()),
         LinearVectorizedTraversal,CompleteUnrolling));
 
       VERIFY(test_assign(Matrix<Scalar,17,17>(),Matrix<Scalar,17,17>()+Matrix<Scalar,17,17>(),
-        LinearTraversal,NoUnrolling));
+        HalfPacketSize==1             ? InnerVectorizedTraversal  :
+        EIGEN_UNALIGNED_VECTORIZE ? LinearVectorizedTraversal :
+                                        LinearTraversal,
+        NoUnrolling));
+
+      VERIFY(test_assign(Matrix11(), Matrix11()+Matrix11(),InnerVectorizedTraversal,CompleteUnrolling));
+
+
+      VERIFY(test_assign(Matrix11(),Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(2,3)+Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(8,4),
+        (EIGEN_UNALIGNED_VECTORIZE) ? InnerVectorizedTraversal : DefaultTraversal, CompleteUnrolling|InnerUnrolling));
+
+      VERIFY(test_assign(Vector1(),Matrix11()*Vector1(),
+                         InnerVectorizedTraversal,CompleteUnrolling));
 
-      VERIFY(test_assign(Matrix11(),Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(2,3)+Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(10,4),
-      DefaultTraversal,CompleteUnrolling));
+      VERIFY(test_assign(Matrix11(),Matrix11().lazyProduct(Matrix11()),
+                         InnerVectorizedTraversal,InnerUnrolling+CompleteUnrolling));
     }
-    
+
+    VERIFY(test_redux(Vector1(),
+      LinearVectorizedTraversal,CompleteUnrolling));
+
+    VERIFY(test_redux(Matrix<Scalar,PacketSize,3>(),
+      LinearVectorizedTraversal,CompleteUnrolling));
+
     VERIFY(test_redux(Matrix3(),
       LinearVectorizedTraversal,CompleteUnrolling));
 
     VERIFY(test_redux(Matrix44(),
       LinearVectorizedTraversal,NoUnrolling));
@@ -172,64 +222,198 @@
     VERIFY(test_redux(Matrix44c().template block<2*PacketSize,1>(1,2),
       LinearVectorizedTraversal,CompleteUnrolling));
 
     VERIFY(test_redux(Matrix44r().template block<1,2*PacketSize>(2,1),
       LinearVectorizedTraversal,CompleteUnrolling));
-    
+
     VERIFY((test_assign<
-            Map<Matrix22, Aligned, OuterStride<3*PacketSize> >,
+            Map<Matrix22, AlignedMax, OuterStride<3*PacketSize> >,
             Matrix22
             >(InnerVectorizedTraversal,CompleteUnrolling)));
 
     VERIFY((test_assign<
-            Map<Matrix22, Aligned, InnerStride<3*PacketSize> >,
-            Matrix22
-            >(DefaultTraversal,CompleteUnrolling)));
+            Map<Matrix<Scalar,EIGEN_PLAIN_ENUM_MAX(2,PacketSize),EIGEN_PLAIN_ENUM_MAX(2,PacketSize)>, AlignedMax, InnerStride<3*PacketSize> >,
+            Matrix<Scalar,EIGEN_PLAIN_ENUM_MAX(2,PacketSize),EIGEN_PLAIN_ENUM_MAX(2,PacketSize)>
+            >(DefaultTraversal,PacketSize>=8?InnerUnrolling:CompleteUnrolling)));
 
-    VERIFY((test_assign(Matrix11(), Matrix11()*Matrix11(), InnerVectorizedTraversal, CompleteUnrolling)));
+    VERIFY((test_assign(Matrix11(), Matrix<Scalar,PacketSize,EIGEN_PLAIN_ENUM_MIN(2,PacketSize)>()*Matrix<Scalar,EIGEN_PLAIN_ENUM_MIN(2,PacketSize),PacketSize>(),
+                        InnerVectorizedTraversal, CompleteUnrolling)));
     #endif
 
     VERIFY(test_assign(MatrixXX(10,10),MatrixXX(20,20).block(10,10,2,3),
       SliceVectorizedTraversal,NoUnrolling));
 
     VERIFY(test_redux(VectorX(10),
       LinearVectorizedTraversal,NoUnrolling));
-
-    
   }
 };
 
 template<typename Scalar> struct vectorization_logic<Scalar,false>
 {
+  static void run() {}
+};
+
+template<typename Scalar, bool Enable = !internal::is_same<typename internal::unpacket_traits<typename internal::packet_traits<Scalar>::type>::half,
+                                                           typename internal::packet_traits<Scalar>::type>::value >
+struct vectorization_logic_half
+{
+  typedef internal::packet_traits<Scalar> PacketTraits;
+  typedef typename internal::unpacket_traits<typename internal::packet_traits<Scalar>::type>::half PacketType;
+  enum {
+    PacketSize = internal::unpacket_traits<PacketType>::size
+  };
+  static void run()
+  {
+    
+    typedef Matrix<Scalar,PacketSize,1> Vector1;
+    typedef Matrix<Scalar,PacketSize,PacketSize> Matrix11;
+    typedef Matrix<Scalar,5*PacketSize,7,ColMajor> Matrix57;
+    typedef Matrix<Scalar,3*PacketSize,5,ColMajor> Matrix35;
+    typedef Matrix<Scalar,5*PacketSize,7,DontAlign|ColMajor> Matrix57u;
+//     typedef Matrix<Scalar,(Matrix11::Flags&RowMajorBit)?16:4*PacketSize,(Matrix11::Flags&RowMajorBit)?4*PacketSize:16> Matrix44;
+//     typedef Matrix<Scalar,(Matrix11::Flags&RowMajorBit)?16:4*PacketSize,(Matrix11::Flags&RowMajorBit)?4*PacketSize:16,DontAlign|EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION> Matrix44u;
+//     typedef Matrix<Scalar,4*PacketSize,4*PacketSize,ColMajor> Matrix44c;
+//     typedef Matrix<Scalar,4*PacketSize,4*PacketSize,RowMajor> Matrix44r;
+
+    typedef Matrix<Scalar,
+        (PacketSize==8 ? 4 : PacketSize==4 ? 2 : PacketSize==2 ? 1 : /*PacketSize==1 ?*/ 1),
+        (PacketSize==8 ? 2 : PacketSize==4 ? 2 : PacketSize==2 ? 2 : /*PacketSize==1 ?*/ 1)
+      > Matrix1;
+
+    typedef Matrix<Scalar,
+        (PacketSize==8 ? 4 : PacketSize==4 ? 2 : PacketSize==2 ? 1 : /*PacketSize==1 ?*/ 1),
+        (PacketSize==8 ? 2 : PacketSize==4 ? 2 : PacketSize==2 ? 2 : /*PacketSize==1 ?*/ 1),
+      DontAlign|((Matrix1::Flags&RowMajorBit)?RowMajor:ColMajor)> Matrix1u;
+
+    // this type is made such that it can only be vectorized when viewed as a linear 1D vector
+    typedef Matrix<Scalar,
+        (PacketSize==8 ? 4 : PacketSize==4 ? 6 : PacketSize==2 ? ((Matrix11::Flags&RowMajorBit)?2:3) : /*PacketSize==1 ?*/ 1),
+        (PacketSize==8 ? 6 : PacketSize==4 ? 2 : PacketSize==2 ? ((Matrix11::Flags&RowMajorBit)?3:2) : /*PacketSize==1 ?*/ 3)
+      > Matrix3;
+    
+    #if !EIGEN_GCC_AND_ARCH_DOESNT_WANT_STACK_ALIGNMENT
+    VERIFY(test_assign(Vector1(),Vector1(),
+      InnerVectorizedTraversal,CompleteUnrolling));
+    VERIFY(test_assign(Vector1(),Vector1()+Vector1(),
+      InnerVectorizedTraversal,CompleteUnrolling));
+    VERIFY(test_assign(Vector1(),Vector1().template segment<PacketSize>(0).derived(),
+      EIGEN_UNALIGNED_VECTORIZE ? InnerVectorizedTraversal : LinearVectorizedTraversal,CompleteUnrolling));
+    VERIFY(test_assign(Vector1(),Scalar(2.1)*Vector1()-Vector1(),
+      InnerVectorizedTraversal,CompleteUnrolling));
+    VERIFY(test_assign(Vector1(),(Scalar(2.1)*Vector1().template segment<PacketSize>(0)-Vector1().template segment<PacketSize>(0)).derived(),
+      EIGEN_UNALIGNED_VECTORIZE ? InnerVectorizedTraversal : LinearVectorizedTraversal,CompleteUnrolling));
+    VERIFY(test_assign(Vector1(),Vector1().cwiseProduct(Vector1()),
+      InnerVectorizedTraversal,CompleteUnrolling));
+    VERIFY(test_assign(Vector1(),Vector1().template cast<Scalar>(),
+      InnerVectorizedTraversal,CompleteUnrolling));
+
+
+    VERIFY(test_assign(Vector1(),Vector1(),
+      InnerVectorizedTraversal,CompleteUnrolling));
+    VERIFY(test_assign(Vector1(),Vector1()+Vector1(),
+      InnerVectorizedTraversal,CompleteUnrolling));
+    VERIFY(test_assign(Vector1(),Vector1().cwiseProduct(Vector1()),
+      InnerVectorizedTraversal,CompleteUnrolling));
+
+    VERIFY(test_assign(Matrix57(),Matrix57()+Matrix57(),
+      InnerVectorizedTraversal,InnerUnrolling));
+
+    VERIFY(test_assign(Matrix57u(),Matrix57()+Matrix57(),
+      EIGEN_UNALIGNED_VECTORIZE ? InnerVectorizedTraversal : LinearTraversal,
+      EIGEN_UNALIGNED_VECTORIZE ? InnerUnrolling : NoUnrolling));
+
+    VERIFY(test_assign(Matrix1u(),Matrix1()+Matrix1(),
+      EIGEN_UNALIGNED_VECTORIZE ? ((Matrix1::InnerSizeAtCompileTime % PacketSize)==0 ? InnerVectorizedTraversal : LinearVectorizedTraversal) : LinearTraversal,CompleteUnrolling));
+        
+    if(PacketSize>1)
+    {
+      typedef Matrix<Scalar,3,3,ColMajor> Matrix33c;
+      VERIFY(test_assign(Matrix33c().row(2),Matrix33c().row(1)+Matrix33c().row(1),
+        LinearTraversal,CompleteUnrolling));
+      VERIFY(test_assign(Matrix33c().col(0),Matrix33c().col(1)+Matrix33c().col(1),
+        EIGEN_UNALIGNED_VECTORIZE ? (PacketSize==1 ? InnerVectorizedTraversal : LinearVectorizedTraversal) : LinearTraversal,CompleteUnrolling));
+              
+      VERIFY(test_assign(Matrix3(),Matrix3().cwiseQuotient(Matrix3()),
+        PacketTraits::HasDiv ? LinearVectorizedTraversal : LinearTraversal,CompleteUnrolling));
+        
+      VERIFY(test_assign(Matrix<Scalar,17,17>(),Matrix<Scalar,17,17>()+Matrix<Scalar,17,17>(),
+        EIGEN_UNALIGNED_VECTORIZE ? (PacketSize==1 ? InnerVectorizedTraversal : LinearVectorizedTraversal) : LinearTraversal,
+        NoUnrolling));
+        
+      VERIFY(test_assign(Matrix11(),Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(2,3)+Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(8,4),
+        EIGEN_UNALIGNED_VECTORIZE ? InnerVectorizedTraversal : DefaultTraversal,PacketSize>4?InnerUnrolling:CompleteUnrolling));
+
+      VERIFY(test_assign(Vector1(),Matrix11()*Vector1(),
+                         InnerVectorizedTraversal,CompleteUnrolling));
+
+      VERIFY(test_assign(Matrix11(),Matrix11().lazyProduct(Matrix11()),
+                         InnerVectorizedTraversal,InnerUnrolling+CompleteUnrolling));
+    }
+    
+    VERIFY(test_redux(Vector1(),
+      LinearVectorizedTraversal,CompleteUnrolling));
+
+    VERIFY(test_redux(Matrix<Scalar,PacketSize,3>(),
+      LinearVectorizedTraversal,CompleteUnrolling));
+
+    VERIFY(test_redux(Matrix3(),
+      LinearVectorizedTraversal,CompleteUnrolling));
+
+    VERIFY(test_redux(Matrix35(),
+      LinearVectorizedTraversal,CompleteUnrolling));
+
+    VERIFY(test_redux(Matrix57().template block<PacketSize,3>(1,0),
+      DefaultTraversal,CompleteUnrolling));
+
+    VERIFY((test_assign<
+            Map<Matrix<Scalar,EIGEN_PLAIN_ENUM_MAX(2,PacketSize),EIGEN_PLAIN_ENUM_MAX(2,PacketSize)>, AlignedMax, InnerStride<3*PacketSize> >,
+            Matrix<Scalar,EIGEN_PLAIN_ENUM_MAX(2,PacketSize),EIGEN_PLAIN_ENUM_MAX(2,PacketSize)>
+            >(DefaultTraversal,CompleteUnrolling)));
+
+    VERIFY((test_assign(Matrix57(), Matrix<Scalar,5*PacketSize,3>()*Matrix<Scalar,3,7>(),
+                        InnerVectorizedTraversal, InnerUnrolling|CompleteUnrolling)));
+    #endif
+  }
+};
+
+template<typename Scalar> struct vectorization_logic_half<Scalar,false>
+{
   static void run() {}
 };
 
 void test_vectorization_logic()
 {
 
 #ifdef EIGEN_VECTORIZE
 
+  CALL_SUBTEST( vectorization_logic<int>::run() );
   CALL_SUBTEST( vectorization_logic<float>::run() );
   CALL_SUBTEST( vectorization_logic<double>::run() );
   CALL_SUBTEST( vectorization_logic<std::complex<float> >::run() );
   CALL_SUBTEST( vectorization_logic<std::complex<double> >::run() );
   
+  CALL_SUBTEST( vectorization_logic_half<int>::run() );
+  CALL_SUBTEST( vectorization_logic_half<float>::run() );
+  CALL_SUBTEST( vectorization_logic_half<double>::run() );
+  CALL_SUBTEST( vectorization_logic_half<std::complex<float> >::run() );
+  CALL_SUBTEST( vectorization_logic_half<std::complex<double> >::run() );
+  
   if(internal::packet_traits<float>::Vectorizable)
   {
     VERIFY(test_assign(Matrix<float,3,3>(),Matrix<float,3,3>()+Matrix<float,3,3>(),
-      LinearTraversal,CompleteUnrolling));
+      EIGEN_UNALIGNED_VECTORIZE ? LinearVectorizedTraversal : LinearTraversal,CompleteUnrolling));
       
     VERIFY(test_redux(Matrix<float,5,2>(),
-      DefaultTraversal,CompleteUnrolling));
+      EIGEN_UNALIGNED_VECTORIZE ? LinearVectorizedTraversal : DefaultTraversal,CompleteUnrolling));
   }
   
   if(internal::packet_traits<double>::Vectorizable)
   {
     VERIFY(test_assign(Matrix<double,3,3>(),Matrix<double,3,3>()+Matrix<double,3,3>(),
-      LinearTraversal,CompleteUnrolling));
+      EIGEN_UNALIGNED_VECTORIZE ? LinearVectorizedTraversal : LinearTraversal,CompleteUnrolling));
     
     VERIFY(test_redux(Matrix<double,7,3>(),
-      DefaultTraversal,CompleteUnrolling));
+      EIGEN_UNALIGNED_VECTORIZE ? LinearVectorizedTraversal : DefaultTraversal,CompleteUnrolling));
   }
 #endif // EIGEN_VECTORIZE
 
 }

Index: 3rd_party/eigen/test/vectorwiseop.cpp
==================================================================
--- 3rd_party/eigen/test/vectorwiseop.cpp
+++ 3rd_party/eigen/test/vectorwiseop.cpp
@@ -1,14 +1,16 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#define TEST_ENABLE_TEMPORARY_TRACKING
 #define EIGEN_NO_STATIC_ASSERT
 
 #include "main.h"
 
 template<typename ArrayType> void vectorwiseop_array(const ArrayType& m)
@@ -99,20 +101,32 @@
   VERIFY_IS_APPROX(m2, m1.rowwise() / rowvec);
   VERIFY_IS_APPROX(m2.row(r), m1.row(r) / rowvec);
 
   VERIFY_RAISES_ASSERT(m2.rowwise() /= rowvec.transpose());
   VERIFY_RAISES_ASSERT(m1.rowwise() / rowvec.transpose());
-  
+
   m2 = m1;
   // yes, there might be an aliasing issue there but ".rowwise() /="
-  // is suppposed to evaluate " m2.colwise().sum()" into to temporary to avoid
-  // evaluating the reducions multiple times
+  // is supposed to evaluate " m2.colwise().sum()" into a temporary to avoid
+  // evaluating the reduction multiple times
   if(ArrayType::RowsAtCompileTime>2 || ArrayType::RowsAtCompileTime==Dynamic)
   {
     m2.rowwise() /= m2.colwise().sum();
     VERIFY_IS_APPROX(m2, m1.rowwise() / m1.colwise().sum());
   }
+
+  // all/any
+  Array<bool,Dynamic,Dynamic> mb(rows,cols);
+  mb = (m1.real()<=0.7).colwise().all();
+  VERIFY( (mb.col(c) == (m1.real().col(c)<=0.7).all()).all() );
+  mb = (m1.real()<=0.7).rowwise().all();
+  VERIFY( (mb.row(r) == (m1.real().row(r)<=0.7).all()).all() );
+
+  mb = (m1.real()>=0.7).colwise().any();
+  VERIFY( (mb.col(c) == (m1.real().col(c)>=0.7).any()).all() );
+  mb = (m1.real()>=0.7).rowwise().any();
+  VERIFY( (mb.row(r) == (m1.real().row(r)>=0.7).any()).all() );
 }
 
 template<typename MatrixType> void vectorwiseop_matrix(const MatrixType& m)
 {
   typedef typename MatrixType::Index Index;
@@ -142,64 +156,97 @@
   m2 = m1;
   m2.colwise() += colvec;
   VERIFY_IS_APPROX(m2, m1.colwise() + colvec);
   VERIFY_IS_APPROX(m2.col(c), m1.col(c) + colvec);
 
-  VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose());
-  VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose());
+  if(rows>1)
+  {
+    VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose());
+    VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose());
+  }
 
   m2 = m1;
   m2.rowwise() += rowvec;
   VERIFY_IS_APPROX(m2, m1.rowwise() + rowvec);
   VERIFY_IS_APPROX(m2.row(r), m1.row(r) + rowvec);
 
-  VERIFY_RAISES_ASSERT(m2.rowwise() += rowvec.transpose());
-  VERIFY_RAISES_ASSERT(m1.rowwise() + rowvec.transpose());
+  if(cols>1)
+  {
+    VERIFY_RAISES_ASSERT(m2.rowwise() += rowvec.transpose());
+    VERIFY_RAISES_ASSERT(m1.rowwise() + rowvec.transpose());
+  }
 
   // test substraction
 
   m2 = m1;
   m2.colwise() -= colvec;
   VERIFY_IS_APPROX(m2, m1.colwise() - colvec);
   VERIFY_IS_APPROX(m2.col(c), m1.col(c) - colvec);
 
-  VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose());
-  VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose());
+  if(rows>1)
+  {
+    VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose());
+    VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose());
+  }
 
   m2 = m1;
   m2.rowwise() -= rowvec;
   VERIFY_IS_APPROX(m2, m1.rowwise() - rowvec);
   VERIFY_IS_APPROX(m2.row(r), m1.row(r) - rowvec);
 
-  VERIFY_RAISES_ASSERT(m2.rowwise() -= rowvec.transpose());
-  VERIFY_RAISES_ASSERT(m1.rowwise() - rowvec.transpose());
-  
+  if(cols>1)
+  {
+    VERIFY_RAISES_ASSERT(m2.rowwise() -= rowvec.transpose());
+    VERIFY_RAISES_ASSERT(m1.rowwise() - rowvec.transpose());
+  }
+
   // test norm
   rrres = m1.colwise().norm();
   VERIFY_IS_APPROX(rrres(c), m1.col(c).norm());
   rcres = m1.rowwise().norm();
   VERIFY_IS_APPROX(rcres(r), m1.row(r).norm());
-  
+
+  VERIFY_IS_APPROX(m1.cwiseAbs().colwise().sum(), m1.colwise().template lpNorm<1>());
+  VERIFY_IS_APPROX(m1.cwiseAbs().rowwise().sum(), m1.rowwise().template lpNorm<1>());
+  VERIFY_IS_APPROX(m1.cwiseAbs().colwise().maxCoeff(), m1.colwise().template lpNorm<Infinity>());
+  VERIFY_IS_APPROX(m1.cwiseAbs().rowwise().maxCoeff(), m1.rowwise().template lpNorm<Infinity>());
+
+  // regression for bug 1158
+  VERIFY_IS_APPROX(m1.cwiseAbs().colwise().sum().x(), m1.col(0).cwiseAbs().sum());
+
   // test normalized
   m2 = m1.colwise().normalized();
   VERIFY_IS_APPROX(m2.col(c), m1.col(c).normalized());
   m2 = m1.rowwise().normalized();
   VERIFY_IS_APPROX(m2.row(r), m1.row(r).normalized());
-  
+
   // test normalize
   m2 = m1;
   m2.colwise().normalize();
   VERIFY_IS_APPROX(m2.col(c), m1.col(c).normalized());
   m2 = m1;
   m2.rowwise().normalize();
   VERIFY_IS_APPROX(m2.row(r), m1.row(r).normalized());
+
+  // test with partial reduction of products
+  Matrix<Scalar,MatrixType::RowsAtCompileTime,MatrixType::RowsAtCompileTime> m1m1 = m1 * m1.transpose();
+  VERIFY_IS_APPROX( (m1 * m1.transpose()).colwise().sum(), m1m1.colwise().sum());
+  Matrix<Scalar,1,MatrixType::RowsAtCompileTime> tmp(rows);
+  VERIFY_EVALUATION_COUNT( tmp = (m1 * m1.transpose()).colwise().sum(), 1);
+
+  m2 = m1.rowwise() - (m1.colwise().sum()/RealScalar(m1.rows())).eval();
+  m1 = m1.rowwise() - (m1.colwise().sum()/RealScalar(m1.rows()));
+  VERIFY_IS_APPROX( m1, m2 );
+  VERIFY_EVALUATION_COUNT( m2 = (m1.rowwise() - m1.colwise().sum()/RealScalar(m1.rows())), (MatrixType::RowsAtCompileTime!=1 ? 1 : 0) );
 }
 
 void test_vectorwiseop()
 {
-  CALL_SUBTEST_1(vectorwiseop_array(Array22cd()));
-  CALL_SUBTEST_2(vectorwiseop_array(Array<double, 3, 2>()));
-  CALL_SUBTEST_3(vectorwiseop_array(ArrayXXf(3, 4)));
-  CALL_SUBTEST_4(vectorwiseop_matrix(Matrix4cf()));
-  CALL_SUBTEST_5(vectorwiseop_matrix(Matrix<float,4,5>()));
-  CALL_SUBTEST_6(vectorwiseop_matrix(MatrixXd(7,2)));
+  CALL_SUBTEST_1( vectorwiseop_array(Array22cd()) );
+  CALL_SUBTEST_2( vectorwiseop_array(Array<double, 3, 2>()) );
+  CALL_SUBTEST_3( vectorwiseop_array(ArrayXXf(3, 4)) );
+  CALL_SUBTEST_4( vectorwiseop_matrix(Matrix4cf()) );
+  CALL_SUBTEST_5( vectorwiseop_matrix(Matrix<float,4,5>()) );
+  CALL_SUBTEST_6( vectorwiseop_matrix(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+  CALL_SUBTEST_7( vectorwiseop_matrix(VectorXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+  CALL_SUBTEST_7( vectorwiseop_matrix(RowVectorXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
 }

Index: 3rd_party/eigen/test/visitor.cpp
==================================================================
--- 3rd_party/eigen/test/visitor.cpp
+++ 3rd_party/eigen/test/visitor.cpp
@@ -53,10 +53,15 @@
   VERIFY(maxcol == eigen_maxcol);
   VERIFY_IS_APPROX(minc, eigen_minc);
   VERIFY_IS_APPROX(maxc, eigen_maxc);
   VERIFY_IS_APPROX(minc, m.minCoeff());
   VERIFY_IS_APPROX(maxc, m.maxCoeff());
+
+  eigen_maxc = (m.adjoint()*m).maxCoeff(&eigen_maxrow,&eigen_maxcol);
+  eigen_maxc = (m.adjoint()*m).eval().maxCoeff(&maxrow,&maxcol);
+  VERIFY(maxrow == eigen_maxrow);
+  VERIFY(maxcol == eigen_maxcol);
 }
 
 template<typename VectorType> void vectorVisitor(const VectorType& w)
 {
   typedef typename VectorType::Scalar Scalar;

Index: 3rd_party/eigen/test/zerosized.cpp
==================================================================
--- 3rd_party/eigen/test/zerosized.cpp
+++ 3rd_party/eigen/test/zerosized.cpp
@@ -23,10 +23,11 @@
 
 
 template<typename MatrixType> void zeroSizedMatrix()
 {
   MatrixType t1;
+  typedef typename MatrixType::Scalar Scalar;
 
   if (MatrixType::SizeAtCompileTime == Dynamic || MatrixType::SizeAtCompileTime == 0)
   {
     zeroReduction(t1);
     if (MatrixType::RowsAtCompileTime == Dynamic)
@@ -35,18 +36,35 @@
       VERIFY(t1.cols() == 0);
 
     if (MatrixType::RowsAtCompileTime == Dynamic && MatrixType::ColsAtCompileTime == Dynamic)
     {
 
-      MatrixType t2(0, 0);
+      MatrixType t2(0, 0), t3(t1);
       VERIFY(t2.rows() == 0);
       VERIFY(t2.cols() == 0);
 
       zeroReduction(t2);
       VERIFY(t1==t2);
     }
   }
+
+  if(MatrixType::MaxColsAtCompileTime!=0 && MatrixType::MaxRowsAtCompileTime!=0)
+  {
+    Index rows = MatrixType::RowsAtCompileTime==Dynamic ? internal::random<Index>(1,10) : Index(MatrixType::RowsAtCompileTime);
+    Index cols = MatrixType::ColsAtCompileTime==Dynamic ? internal::random<Index>(1,10) : Index(MatrixType::ColsAtCompileTime);
+    MatrixType m(rows,cols);
+    zeroReduction(m.template block<0,MatrixType::ColsAtCompileTime>(0,0,0,cols));
+    zeroReduction(m.template block<MatrixType::RowsAtCompileTime,0>(0,0,rows,0));
+    zeroReduction(m.template block<0,1>(0,0));
+    zeroReduction(m.template block<1,0>(0,0));
+    Matrix<Scalar,Dynamic,Dynamic> prod = m.template block<MatrixType::RowsAtCompileTime,0>(0,0,rows,0) * m.template block<0,MatrixType::ColsAtCompileTime>(0,0,0,cols);
+    VERIFY(prod.rows()==rows && prod.cols()==cols);
+    VERIFY(prod.isZero());
+    prod = m.template block<1,0>(0,0) * m.template block<0,1>(0,0);
+    VERIFY(prod.size()==1);
+    VERIFY(prod.isZero());
+  }
 }
 
 template<typename VectorType> void zeroSizedVector()
 {
   VectorType t1;

Index: 3rd_party/eigen/unsupported/Eigen/AdolcForward
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/AdolcForward
+++ 3rd_party/eigen/unsupported/Eigen/AdolcForward
@@ -23,11 +23,11 @@
 
 #define ADOLC_TAPELESS
 #ifndef NUMBER_DIRECTIONS
 # define NUMBER_DIRECTIONS 2
 #endif
-#include <adolc/adouble.h>
+#include <adolc/adtl.h>
 
 // adolc defines some very stupid macros:
 #if defined(malloc)
 # undef malloc
 #endif

Index: 3rd_party/eigen/unsupported/Eigen/AlignedVector3
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/AlignedVector3
+++ 3rd_party/eigen/unsupported/Eigen/AlignedVector3
@@ -55,10 +55,15 @@
     EIGEN_DENSE_PUBLIC_INTERFACE(AlignedVector3)
     using Base::operator*;
 
     inline Index rows() const { return 3; }
     inline Index cols() const { return 1; }
+    
+    Scalar* data() { return m_coeffs.data(); }
+    const Scalar* data() const { return m_coeffs.data(); }
+    Index innerStride() const { return 1; }
+    Index outerStride() const { return 3; }
 
     inline const Scalar& coeff(Index row, Index col) const
     { return m_coeffs.coeff(row, col); }
 
     inline Scalar& coeffRef(Index row, Index col)
@@ -98,18 +103,24 @@
         dest.m_coeffs.w() = Scalar(0);
       }
     };
 
     template<typename Derived>
-    inline explicit AlignedVector3(const MatrixBase<Derived>& other)
+    inline AlignedVector3(const MatrixBase<Derived>& other)
     {
       generic_assign_selector<Derived>::run(*this,other.derived());
     }
 
     inline AlignedVector3& operator=(const AlignedVector3& other)
     { m_coeffs = other.m_coeffs; return *this; }
 
+    template <typename Derived>
+    inline AlignedVector3& operator=(const MatrixBase<Derived>& other)
+    {
+      generic_assign_selector<Derived>::run(*this,other.derived());
+      return *this;
+    }
 
     inline AlignedVector3 operator+(const AlignedVector3& other) const
     { return AlignedVector3(m_coeffs + other.m_coeffs); }
 
     inline AlignedVector3& operator+=(const AlignedVector3& other)
@@ -146,11 +157,11 @@
     inline void normalize()
     {
       m_coeffs /= norm();
     }
 
-    inline AlignedVector3 normalized()
+    inline AlignedVector3 normalized() const
     {
       return AlignedVector3(m_coeffs / norm());
     }
 
     inline Scalar sum() const
@@ -175,16 +186,39 @@
     {
       return AlignedVector3(m_coeffs.cross3(other.m_coeffs));
     }
 
     template<typename Derived>
-    inline bool isApprox(const MatrixBase<Derived>& other, RealScalar eps=NumTraits<Scalar>::dummy_precision()) const
+    inline bool isApprox(const MatrixBase<Derived>& other, const RealScalar& eps=NumTraits<Scalar>::dummy_precision()) const
     {
       return m_coeffs.template head<3>().isApprox(other,eps);
     }
+    
+    CoeffType& coeffs() { return m_coeffs; }
+    const CoeffType& coeffs() const { return m_coeffs; }
+};
+
+namespace internal {
+
+template<typename _Scalar>
+struct eval<AlignedVector3<_Scalar>, Dense>
+{
+ typedef const AlignedVector3<_Scalar>& type;
+};
+
+template<typename Scalar>
+struct evaluator<AlignedVector3<Scalar> >
+  : evaluator<Matrix<Scalar,4,1> >
+{
+  typedef AlignedVector3<Scalar> XprType;
+  typedef evaluator<Matrix<Scalar,4,1> > Base;
+  
+  evaluator(const XprType &m) : Base(m.coeffs()) {}  
 };
+
+}
 
 //@}
 
 }
 
 #endif // EIGEN_ALIGNED_VECTOR3

Index: 3rd_party/eigen/unsupported/Eigen/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/CMakeLists.txt
@@ -1,11 +1,32 @@
-set(Eigen_HEADERS AdolcForward BVH IterativeSolvers MatrixFunctions MoreVectorization AutoDiff AlignedVector3 Polynomials
-                  FFT NonLinearOptimization SparseExtra IterativeSolvers
-                  NumericalDiff Skyline MPRealSupport OpenGLSupport KroneckerProduct Splines LevenbergMarquardt
-   )
+set(Eigen_HEADERS 
+  AdolcForward
+  AlignedVector3
+  ArpackSupport
+  AutoDiff
+  BVH
+  EulerAngles
+  FFT
+  IterativeSolvers 
+  KroneckerProduct
+  LevenbergMarquardt
+  MatrixFunctions 
+  MoreVectorization
+  MPRealSupport
+  NonLinearOptimization
+  NumericalDiff
+  OpenGLSupport
+  Polynomials
+  Skyline 
+  SparseExtra
+  SpecialFunctions
+  Splines
+  )
 
 install(FILES
   ${Eigen_HEADERS}
   DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen COMPONENT Devel
   )
 
-add_subdirectory(src)
+install(DIRECTORY src DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen COMPONENT Devel FILES_MATCHING PATTERN "*.h")
+
+add_subdirectory(CXX11)

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/CMakeLists.txt
@@ -0,0 +1,8 @@
+set(Eigen_CXX11_HEADERS Tensor TensorSymmetry ThreadPool)
+
+install(FILES
+  ${Eigen_CXX11_HEADERS}
+  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/CXX11 COMPONENT Devel
+  )
+
+install(DIRECTORY src DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/CXX11 COMPONENT Devel FILES_MATCHING PATTERN "*.h")

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/Tensor
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/Tensor
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/Tensor
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/Tensor
@@ -0,0 +1,152 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+//#ifndef EIGEN_CXX11_TENSOR_MODULE
+//#define EIGEN_CXX11_TENSOR_MODULE
+
+#include "../../../Eigen/Core"
+
+#ifdef EIGEN_USE_SYCL
+#undef min
+#undef max
+#undef isnan
+#undef isinf
+#undef isfinite
+#include <SYCL/sycl.hpp>
+#include <map>
+#include <memory>
+#include <utility>
+#endif
+
+#include <Eigen/src/Core/util/DisableStupidWarnings.h>
+
+#include "../SpecialFunctions"
+#include "src/util/CXX11Meta.h"
+#include "src/util/MaxSizeVector.h"
+
+/** \defgroup CXX11_Tensor_Module Tensor Module
+  *
+  * This module provides a Tensor class for storing arbitrarily indexed
+  * objects.
+  *
+  * \code
+  * #include <Eigen/CXX11/Tensor>
+  * \endcode
+  */
+
+#include <cmath>
+#include <cstddef>
+#include <cstring>
+
+#ifdef _WIN32
+typedef __int16 int16_t;
+typedef unsigned __int16 uint16_t;
+typedef __int32 int32_t;
+typedef unsigned __int32 uint32_t;
+typedef __int64 int64_t;
+typedef unsigned __int64 uint64_t;
+#else
+#include <stdint.h>
+#endif
+
+#if __cplusplus > 199711 || EIGEN_COMP_MSVC >= 1900
+#include <random>
+#endif
+
+#ifdef _WIN32
+#include <windows.h>
+#elif defined(__APPLE__)
+#include <mach/mach_time.h>
+#else
+#include <time.h>
+#endif
+
+#ifdef EIGEN_USE_THREADS
+#include "ThreadPool"
+#endif
+
+#ifdef EIGEN_USE_GPU
+#include <iostream>
+#include <cuda_runtime.h>
+#if __cplusplus >= 201103L
+#include <atomic>
+#include <unistd.h>
+#endif
+#endif
+
+#include "src/Tensor/TensorMacros.h"
+#include "src/Tensor/TensorForwardDeclarations.h"
+#include "src/Tensor/TensorMeta.h"
+#include "src/Tensor/TensorFunctors.h"
+#include "src/Tensor/TensorCostModel.h"
+#include "src/Tensor/TensorDeviceDefault.h"
+#include "src/Tensor/TensorDeviceThreadPool.h"
+#include "src/Tensor/TensorDeviceCuda.h"
+#include "src/Tensor/TensorDeviceSycl.h"
+#include "src/Tensor/TensorIndexList.h"
+#include "src/Tensor/TensorDimensionList.h"
+#include "src/Tensor/TensorDimensions.h"
+#include "src/Tensor/TensorInitializer.h"
+#include "src/Tensor/TensorTraits.h"
+#include "src/Tensor/TensorRandom.h"
+#include "src/Tensor/TensorUInt128.h"
+#include "src/Tensor/TensorIntDiv.h"
+#include "src/Tensor/TensorGlobalFunctions.h"
+
+#include "src/Tensor/TensorBase.h"
+
+#include "src/Tensor/TensorEvaluator.h"
+#include "src/Tensor/TensorExpr.h"
+#include "src/Tensor/TensorReduction.h"
+#include "src/Tensor/TensorReductionCuda.h"
+#include "src/Tensor/TensorArgMax.h"
+#include "src/Tensor/TensorConcatenation.h"
+#include "src/Tensor/TensorContractionMapper.h"
+#include "src/Tensor/TensorContractionBlocking.h"
+#include "src/Tensor/TensorContraction.h"
+#include "src/Tensor/TensorContractionThreadPool.h"
+#include "src/Tensor/TensorContractionCuda.h"
+#include "src/Tensor/TensorConversion.h"
+#include "src/Tensor/TensorConvolution.h"
+#include "src/Tensor/TensorFFT.h"
+#include "src/Tensor/TensorPatch.h"
+#include "src/Tensor/TensorImagePatch.h"
+#include "src/Tensor/TensorVolumePatch.h"
+#include "src/Tensor/TensorBroadcasting.h"
+#include "src/Tensor/TensorChipping.h"
+#include "src/Tensor/TensorInflation.h"
+#include "src/Tensor/TensorLayoutSwap.h"
+#include "src/Tensor/TensorMorphing.h"
+#include "src/Tensor/TensorPadding.h"
+#include "src/Tensor/TensorReverse.h"
+#include "src/Tensor/TensorShuffling.h"
+#include "src/Tensor/TensorStriding.h"
+#include "src/Tensor/TensorCustomOp.h"
+#include "src/Tensor/TensorEvalTo.h"
+#include "src/Tensor/TensorForcedEval.h"
+#include "src/Tensor/TensorGenerator.h"
+#include "src/Tensor/TensorAssign.h"
+#include "src/Tensor/TensorScan.h"
+
+#include "src/Tensor/TensorSycl.h"
+#include "src/Tensor/TensorExecutor.h"
+#include "src/Tensor/TensorDevice.h"
+
+#include "src/Tensor/TensorStorage.h"
+#include "src/Tensor/Tensor.h"
+#include "src/Tensor/TensorFixedSize.h"
+#include "src/Tensor/TensorMap.h"
+#include "src/Tensor/TensorRef.h"
+
+#include "src/Tensor/TensorIO.h"
+
+#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
+
+//#endif // EIGEN_CXX11_TENSOR_MODULE

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/TensorSymmetry
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/TensorSymmetry
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/TensorSymmetry
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/TensorSymmetry
@@ -0,0 +1,42 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSORSYMMETRY_MODULE
+#define EIGEN_CXX11_TENSORSYMMETRY_MODULE
+
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include <Eigen/src/Core/util/DisableStupidWarnings.h>
+
+#include "src/util/CXX11Meta.h"
+
+/** \defgroup CXX11_TensorSymmetry_Module Tensor Symmetry Module
+  *
+  * This module provides a classes that allow for the definition of
+  * symmetries w.r.t. tensor indices.
+  *
+  * Including this module will implicitly include the Tensor module.
+  *
+  * \code
+  * #include <Eigen/TensorSymmetry>
+  * \endcode
+  */
+
+#include "src/TensorSymmetry/util/TemplateGroupTheory.h"
+#include "src/TensorSymmetry/Symmetry.h"
+#include "src/TensorSymmetry/StaticSymmetry.h"
+#include "src/TensorSymmetry/DynamicSymmetry.h"
+
+#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
+
+#endif // EIGEN_CXX11_TENSORSYMMETRY_MODULE
+
+/*
+ * kate: space-indent on; indent-width 2; mixedindent off; indent-mode cstyle;
+ */

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/ThreadPool
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/ThreadPool
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/ThreadPool
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/ThreadPool
@@ -0,0 +1,65 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_MODULE
+#define EIGEN_CXX11_THREADPOOL_MODULE
+
+#include "../../../Eigen/Core"
+
+#include <Eigen/src/Core/util/DisableStupidWarnings.h>
+
+/** \defgroup CXX11_ThreadPool_Module C++11 ThreadPool Module
+  *
+  * This module provides 2 threadpool implementations
+  *  - a simple reference implementation
+  *  - a faster non blocking implementation
+  *
+  * This module requires C++11.
+  *
+  * \code
+  * #include <Eigen/CXX11/ThreadPool>
+  * \endcode
+  */
+
+
+// The code depends on CXX11, so only include the module if the
+// compiler supports it.
+#if __cplusplus > 199711L || EIGEN_COMP_MSVC >= 1900
+#include <cstddef>
+#include <cstring>
+#include <stdint.h>
+#include <time.h>
+
+#include <vector>
+#include <atomic>
+#include <condition_variable>
+#include <deque>
+#include <mutex>
+#include <thread>
+#include <functional>
+#include <memory>
+
+#include "src/util/CXX11Meta.h"
+#include "src/util/MaxSizeVector.h"
+
+#include "src/ThreadPool/ThreadLocal.h"
+#include "src/ThreadPool/ThreadYield.h"
+#include "src/ThreadPool/EventCount.h"
+#include "src/ThreadPool/RunQueue.h"
+#include "src/ThreadPool/ThreadPoolInterface.h"
+#include "src/ThreadPool/ThreadEnvironment.h"
+#include "src/ThreadPool/SimpleThreadPool.h"
+#include "src/ThreadPool/NonBlockingThreadPool.h"
+
+#endif
+
+#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
+
+#endif // EIGEN_CXX11_THREADPOOL_MODULE
+

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/README.md
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/README.md
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/README.md
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/README.md
@@ -0,0 +1,1757 @@
+# Eigen Tensors
+
+Tensors are multidimensional arrays of elements. Elements are typically scalars,
+but more complex types such as strings are also supported.
+
+[TOC]
+
+## Tensor Classes
+
+You can manipulate a tensor with one of the following classes.  They all are in
+the namespace ```::Eigen.```
+
+
+### Class Tensor<data_type, rank>
+
+This is the class to use to create a tensor and allocate memory for it.  The
+class is templatized with the tensor datatype, such as float or int, and the
+tensor rank.  The rank is the number of dimensions, for example rank 2 is a
+matrix.
+
+Tensors of this class are resizable.  For example, if you assign a tensor of a
+different size to a Tensor, that tensor is resized to match its new value.
+
+#### Constructor Tensor<data_type, rank>(size0, size1, ...)
+
+Constructor for a Tensor.  The constructor must be passed ```rank``` integers
+indicating the sizes of the instance along each of the the ```rank```
+dimensions.
+
+    // Create a tensor of rank 3 of sizes 2, 3, 4.  This tensor owns
+    // memory to hold 24 floating point values (24 = 2 x 3 x 4).
+    Tensor<float, 3> t_3d(2, 3, 4);
+
+    // Resize t_3d by assigning a tensor of different sizes, but same rank.
+    t_3d = Tensor<float, 3>(3, 4, 3);
+
+#### Constructor Tensor<data_type, rank>(size_array)
+
+Constructor where the sizes for the constructor are specified as an array of
+values instead of an explicitly list of parameters.  The array type to use is
+```Eigen::array<Eigen::Index>```.  The array can be constructed automatically
+from an initializer list.
+
+    // Create a tensor of strings of rank 2 with sizes 5, 7.
+    Tensor<string, 2> t_2d({5, 7});
+
+
+### Class TensorFixedSize<data_type, Sizes<size0, size1, ...>>
+
+Class to use for tensors of fixed size, where the size is known at compile
+time.  Fixed sized tensors can provide very fast computations because all their
+dimensions are known by the compiler.  FixedSize tensors are not resizable.
+
+If the total number of elements in a fixed size tensor is small enough the
+tensor data is held onto the stack and does not cause heap allocation and free.
+
+    // Create a 4 x 3 tensor of floats.
+    TensorFixedSize<float, Sizes<4, 3>> t_4x3;
+
+### Class TensorMap<Tensor<data_type, rank>>
+
+This is the class to use to create a tensor on top of memory allocated and
+owned by another part of your code.  It allows to view any piece of allocated
+memory as a Tensor.  Instances of this class do not own the memory where the
+data are stored.
+
+A TensorMap is not resizable because it does not own the memory where its data
+are stored.
+
+#### Constructor TensorMap<Tensor<data_type, rank>>(data, size0, size1, ...)
+
+Constructor for a Tensor.  The constructor must be passed a pointer to the
+storage for the data, and "rank" size attributes.  The storage has to be
+large enough to hold all the data.
+
+    // Map a tensor of ints on top of stack-allocated storage.
+    int storage[128];  // 2 x 4 x 2 x 8 = 128
+    TensorMap<Tensor<int, 4>> t_4d(storage, 2, 4, 2, 8);
+
+    // The same storage can be viewed as a different tensor.
+    // You can also pass the sizes as an array.
+    TensorMap<Tensor<int, 2>> t_2d(storage, 16, 8);
+
+    // You can also map fixed-size tensors.  Here we get a 1d view of
+    // the 2d fixed-size tensor.
+    Tensor<float, Sizes<4, 5>> t_4x3;
+    TensorMap<Tensor<float, 1>> t_12(t_4x3, 12);
+
+
+#### Class TensorRef
+
+See Assigning to a TensorRef below.
+
+## Accessing Tensor Elements
+
+#### <data_type> tensor(index0, index1...)
+
+Return the element at position ```(index0, index1...)``` in tensor
+```tensor```.  You must pass as many parameters as the rank of ```tensor```.
+The expression can be used as an l-value to set the value of the element at the
+specified position.  The value returned is of the datatype of the tensor.
+
+    // Set the value of the element at position (0, 1, 0);
+    Tensor<float, 3> t_3d(2, 3, 4);
+    t_3d(0, 1, 0) = 12.0f;
+
+    // Initialize all elements to random values.
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 4; ++k) {
+          t_3d(i, j, k) = ...some random value...;
+        }
+      }
+    }
+
+    // Print elements of a tensor.
+    for (int i = 0; i < 2; ++i) {
+      LOG(INFO) << t_3d(i, 0, 0);
+    }
+
+
+## TensorLayout
+
+The tensor library supports 2 layouts: ```ColMajor``` (the default) and
+```RowMajor```.  Only the default column major layout is currently fully
+supported, and it is therefore not recommended to attempt to use the row major
+layout at the moment.
+
+The layout of a tensor is optionally specified as part of its type. If not
+specified explicitly column major is assumed.
+
+    Tensor<float, 3, ColMajor> col_major;  // equivalent to Tensor<float, 3>
+    TensorMap<Tensor<float, 3, RowMajor> > row_major(data, ...);
+
+All the arguments to an expression must use the same layout. Attempting to mix
+different layouts will result in a compilation error.
+
+It is possible to change the layout of a tensor or an expression using the
+```swap_layout()``` method.  Note that this will also reverse the order of the
+dimensions.
+
+    Tensor<float, 2, ColMajor> col_major(2, 4);
+    Tensor<float, 2, RowMajor> row_major(2, 4);
+
+    Tensor<float, 2> col_major_result = col_major;  // ok, layouts match
+    Tensor<float, 2> col_major_result = row_major;  // will not compile
+
+    // Simple layout swap
+    col_major_result = row_major.swap_layout();
+    eigen_assert(col_major_result.dimension(0) == 4);
+    eigen_assert(col_major_result.dimension(1) == 2);
+
+    // Swap the layout and preserve the order of the dimensions
+    array<int, 2> shuffle(1, 0);
+    col_major_result = row_major.swap_layout().shuffle(shuffle);
+    eigen_assert(col_major_result.dimension(0) == 2);
+    eigen_assert(col_major_result.dimension(1) == 4);
+
+
+## Tensor Operations
+
+The Eigen Tensor library provides a vast library of operations on Tensors:
+numerical operations such as addition and multiplication, geometry operations
+such as slicing and shuffling, etc.  These operations are available as methods
+of the Tensor classes, and in some cases as operator overloads.  For example
+the following code computes the elementwise addition of two tensors:
+
+    Tensor<float, 3> t1(2, 3, 4);
+    ...set some values in t1...
+    Tensor<float, 3> t2(2, 3, 4);
+    ...set some values in t2...
+    // Set t3 to the element wise sum of t1 and t2
+    Tensor<float, 3> t3 = t1 + t2;
+
+While the code above looks easy enough, it is important to understand that the
+expression ```t1 + t2``` is not actually adding the values of the tensors.  The
+expression instead constructs a "tensor operator" object of the class
+TensorCwiseBinaryOp<scalar_sum>, which has references to the tensors
+```t1``` and ```t2```.  This is a small C++ object that knows how to add
+```t1``` and ```t2```.  It is only when the value of the expression is assigned
+to the tensor ```t3``` that the addition is actually performed.  Technically,
+this happens through the overloading of ```operator=()``` in the Tensor class.
+
+This mechanism for computing tensor expressions allows for lazy evaluation and
+optimizations which are what make the tensor library very fast.
+
+Of course, the tensor operators do nest, and the expression ```t1 + t2 *
+0.3f``` is actually represented with the (approximate) tree of operators:
+
+    TensorCwiseBinaryOp<scalar_sum>(t1, TensorCwiseUnaryOp<scalar_mul>(t2, 0.3f))
+
+
+### Tensor Operations and C++ "auto"
+
+Because Tensor operations create tensor operators, the C++ ```auto``` keyword
+does not have its intuitive meaning.  Consider these 2 lines of code:
+
+    Tensor<float, 3> t3 = t1 + t2;
+    auto t4 = t1 + t2;
+
+In the first line we allocate the tensor ```t3``` and it will contain the
+result of the addition of ```t1``` and ```t2```.  In the second line, ```t4```
+is actually the tree of tensor operators that will compute the addition of
+```t1``` and ```t2```.  In fact, ```t4``` is *not* a tensor and you cannot get
+the values of its elements:
+
+    Tensor<float, 3> t3 = t1 + t2;
+    cout << t3(0, 0, 0);  // OK prints the value of t1(0, 0, 0) + t2(0, 0, 0)
+
+    auto t4 = t1 + t2;
+    cout << t4(0, 0, 0);  // Compilation error!
+
+When you use ```auto``` you do not get a Tensor as a result but instead a
+non-evaluated expression.  So only use ```auto``` to delay evaluation.
+
+Unfortunately, there is no single underlying concrete type for holding
+non-evaluated expressions, hence you have to use auto in the case when you do
+want to hold non-evaluated expressions.
+
+When you need the results of set of tensor computations you have to assign the
+result to a Tensor that will be capable of holding onto them.  This can be
+either a normal Tensor, a fixed size Tensor, or a TensorMap on an existing
+piece of memory.  All the following will work:
+
+    auto t4 = t1 + t2;
+
+    Tensor<float, 3> result = t4;  // Could also be: result(t4);
+    cout << result(0, 0, 0);
+
+    TensorMap<float, 4> result(<a float* with enough space>, <size0>, ...) = t4;
+    cout << result(0, 0, 0);
+
+    TensorFixedSize<float, Sizes<size0, ...>> result = t4;
+    cout << result(0, 0, 0);
+
+Until you need the results, you can keep the operation around, and even reuse
+it for additional operations.  As long as you keep the expression as an
+operation, no computation is performed.
+
+    // One way to compute exp((t1 + t2) * 0.2f);
+    auto t3 = t1 + t2;
+    auto t4 = t3 * 0.2f;
+    auto t5 = t4.exp();
+    Tensor<float, 3> result = t5;
+
+    // Another way, exactly as efficient as the previous one:
+    Tensor<float, 3> result = ((t1 + t2) * 0.2f).exp();
+
+### Controlling When Expression are Evaluated
+
+There are several ways to control when expressions are evaluated:
+
+*   Assignment to a Tensor, TensorFixedSize, or TensorMap.
+*   Use of the eval() method.
+*   Assignment to a TensorRef.
+
+#### Assigning to a Tensor, TensorFixedSize, or TensorMap.
+
+The most common way to evaluate an expression is to assign it to a Tensor.  In
+the example below, the ```auto``` declarations make the intermediate values
+"Operations", not Tensors, and do not cause the expressions to be evaluated.
+The assignment to the Tensor ```result``` causes the evaluation of all the
+operations.
+
+    auto t3 = t1 + t2;             // t3 is an Operation.
+    auto t4 = t3 * 0.2f;           // t4 is an Operation.
+    auto t5 = t4.exp();            // t5 is an Operation.
+    Tensor<float, 3> result = t5;  // The operations are evaluated.
+
+If you know the ranks and sizes of the Operation value you can assign the
+Operation to a TensorFixedSize instead of a Tensor, which is a bit more
+efficient.
+
+    // We know that the result is a 4x4x2 tensor!
+    TensorFixedSize<float, 4, 4, 2> result = t5;
+
+Simiarly, assigning an expression to a TensorMap causes its evaluation.  Like
+tensors of type TensorFixedSize, TensorMaps cannot be resized so they have to
+have the rank and sizes of the expression that are assigned to them.
+
+#### Calling eval().
+
+When you compute large composite expressions, you sometimes want to tell Eigen
+that an intermediate value in the expression tree is worth evaluating ahead of
+time.  This is done by inserting a call to the ```eval()``` method of the
+expression Operation.
+
+    // The previous example could have been written:
+    Tensor<float, 3> result = ((t1 + t2) * 0.2f).exp();
+
+    // If you want to compute (t1 + t2) once ahead of time you can write:
+    Tensor<float, 3> result = ((t1 + t2).eval() * 0.2f).exp();
+
+Semantically, calling ```eval()``` is equivalent to materializing the value of
+the expression in a temporary Tensor of the right size.  The code above in
+effect does:
+
+    // .eval() knows the size!
+    TensorFixedSize<float, 4, 4, 2> tmp = t1 + t2;
+    Tensor<float, 3> result = (tmp * 0.2f).exp();
+
+Note that the return value of ```eval()``` is itself an Operation, so the
+following code does not do what you may think:
+
+    // Here t3 is an evaluation Operation.  t3 has not been evaluated yet.
+    auto t3 = (t1 + t2).eval();
+
+    // You can use t3 in another expression.  Still no evaluation.
+    auto t4 = (t3 * 0.2f).exp();
+
+    // The value is evaluated when you assign the Operation to a Tensor, using
+    // an intermediate tensor to represent t3.x
+    Tensor<float, 3> result = t4;
+
+While in the examples above calling ```eval()``` does not make a difference in
+performance, in other cases it can make a huge difference.  In the expression
+below the ```broadcast()``` expression causes the ```X.maximum()``` expression
+to be evaluated many times:
+
+    Tensor<...> X ...;
+    Tensor<...> Y = ((X - X.maximum(depth_dim).reshape(dims2d).broadcast(bcast))
+                     * beta).exp();
+
+Inserting a call to ```eval()``` between the ```maximum()``` and
+```reshape()``` calls guarantees that maximum() is only computed once and
+greatly speeds-up execution:
+
+    Tensor<...> Y =
+      ((X - X.maximum(depth_dim).eval().reshape(dims2d).broadcast(bcast))
+        * beta).exp();
+
+In the other example below, the tensor ```Y``` is both used in the expression
+and its assignment.  This is an aliasing problem and if the evaluation is not
+done in the right order Y will be updated incrementally during the evaluation
+resulting in bogus results:
+
+     Tensor<...> Y ...;
+     Y = Y / (Y.sum(depth_dim).reshape(dims2d).broadcast(bcast));
+
+Inserting a call to ```eval()``` between the ```sum()``` and ```reshape()```
+expressions ensures that the sum is computed before any updates to ```Y``` are
+done.
+
+     Y = Y / (Y.sum(depth_dim).eval().reshape(dims2d).broadcast(bcast));
+
+Note that an eval around the full right hand side expression is not needed
+because the generated has to compute the i-th value of the right hand side
+before assigning it to the left hand side.
+
+However, if you were assigning the expression value to a shuffle of ```Y```
+then you would need to force an eval for correctness by adding an ```eval()```
+call for the right hand side:
+
+     Y.shuffle(...) =
+        (Y / (Y.sum(depth_dim).eval().reshape(dims2d).broadcast(bcast))).eval();
+
+
+#### Assigning to a TensorRef.
+
+If you need to access only a few elements from the value of an expression you
+can avoid materializing the value in a full tensor by using a TensorRef.
+
+A TensorRef is a small wrapper class for any Eigen Operation.  It provides
+overloads for the ```()``` operator that let you access individual values in
+the expression.  TensorRef is convenient, because the Operation themselves do
+not provide a way to access individual elements.
+
+    // Create a TensorRef for the expression.  The expression is not
+    // evaluated yet.
+    TensorRef<Tensor<float, 3> > ref = ((t1 + t2) * 0.2f).exp();
+
+    // Use "ref" to access individual elements.  The expression is evaluated
+    // on the fly.
+    float at_0 = ref(0, 0, 0);
+    cout << ref(0, 1, 0);
+
+Only use TensorRef when you need a subset of the values of the expression.
+TensorRef only computes the values you access.  However note that if you are
+going to access all the values it will be much faster to materialize the
+results in a Tensor first.
+
+In some cases, if the full Tensor result would be very large, you may save
+memory by accessing it as a TensorRef.  But not always.  So don't count on it.
+
+
+### Controlling How Expressions Are Evaluated
+
+The tensor library provides several implementations of the various operations
+such as contractions and convolutions.  The implementations are optimized for
+different environments: single threaded on CPU, multi threaded on CPU, or on a
+GPU using cuda.  Additional implementations may be added later.
+
+You can choose which implementation to use with the ```device()``` call.  If
+you do not choose an implementation explicitly the default implementation that
+uses a single thread on the CPU is used.
+
+The default implementation has been optimized for recent Intel CPUs, taking
+advantage of SSE, AVX, and FMA instructions.  Work is ongoing to tune the
+library on ARM CPUs.  Note that you need to pass compiler-dependent flags
+to enable the use of SSE, AVX, and other instructions.
+
+For example, the following code adds two tensors using the default
+single-threaded CPU implementation:
+
+    Tensor<float, 2> a(30, 40);
+    Tensor<float, 2> b(30, 40);
+    Tensor<float, 2> c = a + b;
+
+To choose a different implementation you have to insert a ```device()``` call
+before the assignment of the result.  For technical C++ reasons this requires
+that the Tensor for the result be declared on its own.  This means that you
+have to know the size of the result.
+
+    Eigen::Tensor<float, 2> c(30, 40);
+    c.device(...) = a + b;
+
+The call to ```device()``` must be the last call on the left of the operator=.
+
+You must pass to the ```device()``` call an Eigen device object.  There are
+presently three devices you can use: DefaultDevice, ThreadPoolDevice and
+GpuDevice.
+
+
+#### Evaluating With the DefaultDevice
+
+This is exactly the same as not inserting a ```device()``` call.
+
+    DefaultDevice my_device;
+    c.device(my_device) = a + b;
+
+#### Evaluating with a Thread Pool
+
+    // Create the Eigen ThreadPoolDevice.
+    Eigen::ThreadPoolDevice my_device(4 /* number of threads to use */);
+
+    // Now just use the device when evaluating expressions.
+    Eigen::Tensor<float, 2> c(30, 50);
+    c.device(my_device) = a.contract(b, dot_product_dims);
+
+
+#### Evaluating On GPU
+
+This is presently a bit more complicated than just using a thread pool device.
+You need to create a GPU device but you also need to explicitly allocate the
+memory for tensors with cuda.
+
+
+## API Reference
+
+### Datatypes
+
+In the documentation of the tensor methods and Operation we mention datatypes
+that are tensor-type specific:
+
+#### <Tensor-Type>::Dimensions
+
+Acts like an array of ints.  Has an ```int size``` attribute, and can be
+indexed like an array to access individual values.  Used to represent the
+dimensions of a tensor.  See ```dimensions()```.
+
+#### <Tensor-Type>::Index
+
+Acts like an ```int```.  Used for indexing tensors along their dimensions.  See
+```operator()```, ```dimension()```, and ```size()```.
+
+#### <Tensor-Type>::Scalar
+
+Represents the datatype of individual tensor elements.  For example, for a
+```Tensor<float>```, ```Scalar``` is the type ```float```.  See
+```setConstant()```.
+
+#### <Operation>
+
+We use this pseudo type to indicate that a tensor Operation is returned by a
+method.  We indicate in the text the type and dimensions of the tensor that the
+Operation returns after evaluation.
+
+The Operation will have to be evaluated, for example by assigning it to a
+tensor, before you can access the values of the resulting tensor.  You can also
+access the values through a TensorRef.
+
+
+## Built-in Tensor Methods
+
+These are usual C++ methods that act on tensors immediately.  They are not
+Operations which provide delayed evaluation of their results.  Unless specified
+otherwise, all the methods listed below are available on all tensor classes:
+Tensor, TensorFixedSize, and TensorMap.
+
+## Metadata
+
+### int NumDimensions
+
+Constant value indicating the number of dimensions of a Tensor.  This is also
+known as the tensor "rank".
+
+      Eigen::Tensor<float, 2> a(3, 4);
+      cout << "Dims " << a.NumDimensions;
+      => Dims 2
+
+### Dimensions dimensions()
+
+Returns an array-like object representing the dimensions of the tensor.
+The actual type of the dimensions() result is <Tensor-Type>::Dimensions.
+
+    Eigen::Tensor<float, 2> a(3, 4);
+    const Eigen::Tensor<float, 2>::Dimensions& d = a.dimensions();
+    cout << "Dim size: " << d.size << ", dim 0: " << d[0]
+         << ", dim 1: " << d[1];
+    => Dim size: 2, dim 0: 3, dim 1: 4
+
+If you use a C++11 compiler, you can use ```auto``` to simplify the code:
+
+    const auto& d = a.dimensions();
+    cout << "Dim size: " << d.size << ", dim 0: " << d[0]
+         << ", dim 1: " << d[1];
+    => Dim size: 2, dim 0: 3, dim 1: 4
+
+### Index dimension(Index n)
+
+Returns the n-th dimension of the tensor.  The actual type of the
+```dimension()``` result is ```<Tensor-Type>::Index```, but you can
+always use it like an int.
+
+      Eigen::Tensor<float, 2> a(3, 4);
+      int dim1 = a.dimension(1);
+      cout << "Dim 1: " << dim1;
+      => Dim 1: 4
+
+### Index size()
+
+Returns the total number of elements in the tensor.  This is the product of all
+the tensor dimensions.  The actual type of the ```size()``` result is
+```<Tensor-Type>::Index```, but you can always use it like an int.
+
+    Eigen::Tensor<float, 2> a(3, 4);
+    cout << "Size: " << a.size();
+    => Size: 12
+
+
+### Getting Dimensions From An Operation
+
+A few operations provide ```dimensions()``` directly,
+e.g. ```TensorReslicingOp```.  Most operations defer calculating dimensions
+until the operation is being evaluated.  If you need access to the dimensions
+of a deferred operation, you can wrap it in a TensorRef (see Assigning to a
+TensorRef above), which provides ```dimensions()``` and ```dimension()``` as
+above.
+
+TensorRef can also wrap the plain Tensor types, so this is a useful idiom in
+templated contexts where the underlying object could be either a raw Tensor
+or some deferred operation (e.g. a slice of a Tensor).  In this case, the
+template code can wrap the object in a TensorRef and reason about its
+dimensionality while remaining agnostic to the underlying type.
+
+
+## Constructors
+
+### Tensor
+
+Creates a tensor of the specified size. The number of arguments must be equal
+to the rank of the tensor. The content of the tensor is not initialized.
+
+    Eigen::Tensor<float, 2> a(3, 4);
+    cout << "NumRows: " << a.dimension(0) << " NumCols: " << a.dimension(1) << endl;
+    => NumRows: 3 NumCols: 4
+
+### TensorFixedSize
+
+Creates a tensor of the specified size. The number of arguments in the Size<>
+template parameter determines the rank of the tensor. The content of the tensor
+is not initialized.
+
+    Eigen::TensorFixedSize<float, Size<3, 4>> a;
+    cout << "Rank: " << a.rank() << endl;
+    => Rank: 2
+    cout << "NumRows: " << a.dimension(0) << " NumCols: " << a.dimension(1) << endl;
+    => NumRows: 3 NumCols: 4
+
+### TensorMap
+
+Creates a tensor mapping an existing array of data. The data must not be freed
+until the TensorMap is discarded, and the size of the data must be large enough
+to accomodate of the coefficients of the tensor.
+
+    float data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11};
+    Eigen::TensorMap<float, 2> a(data, 3, 4);
+    cout << "NumRows: " << a.dimension(0) << " NumCols: " << a.dimension(1) << endl;
+    => NumRows: 3 NumCols: 4
+    cout << "a(1, 2): " << a(1, 2) << endl;
+    => a(1, 2): 9
+
+
+## Contents Initialization
+
+When a new Tensor or a new TensorFixedSize are created, memory is allocated to
+hold all the tensor elements, but the memory is not initialized.  Similarly,
+when a new TensorMap is created on top of non-initialized memory the memory its
+contents are not initialized.
+
+You can use one of the methods below to initialize the tensor memory.  These
+have an immediate effect on the tensor and return the tensor itself as a
+result.  These are not tensor Operations which delay evaluation.
+
+### <Tensor-Type> setConstant(const Scalar& val)
+
+Sets all elements of the tensor to the constant value ```val```.  ```Scalar```
+is the type of data stored in the tensor.  You can pass any value that is
+convertible to that type.
+
+Returns the tensor itself in case you want to chain another call.
+
+    a.setConstant(12.3f);
+    cout << "Constant: " << endl << a << endl << endl;
+    =>
+    Constant:
+    12.3 12.3 12.3 12.3
+    12.3 12.3 12.3 12.3
+    12.3 12.3 12.3 12.3
+
+Note that ```setConstant()``` can be used on any tensor where the element type
+has a copy constructor and an ```operator=()```:
+
+    Eigen::Tensor<string, 2> a(2, 3);
+    a.setConstant("yolo");
+    cout << "String tensor: " << endl << a << endl << endl;
+    =>
+    String tensor:
+    yolo yolo yolo
+    yolo yolo yolo
+
+
+### <Tensor-Type> setZero()
+
+Fills the tensor with zeros.  Equivalent to ```setConstant(Scalar(0))```.
+Returns the tensor itself in case you want to chain another call.
+
+    a.setZero();
+    cout << "Zeros: " << endl << a << endl << endl;
+    =>
+    Zeros:
+    0 0 0 0
+    0 0 0 0
+    0 0 0 0
+
+
+### <Tensor-Type> setValues({..initializer_list})
+
+Fills the tensor with explicit values specified in a std::initializer_list.
+The type of the initializer list depends on the type and rank of the tensor.
+
+If the tensor has rank N, the initializer list must be nested N times.  The
+most deeply nested lists must contains P scalars of the Tensor type where P is
+the size of the last dimension of the Tensor.
+
+For example, for a ```TensorFixedSize<float, 2, 3>``` the initializer list must
+contains 2 lists of 3 floats each.
+
+```setValues()``` returns the tensor itself in case you want to chain another
+call.
+
+    Eigen::Tensor<float, 2> a(2, 3);
+    a.setValues({{0.0f, 1.0f, 2.0f}, {3.0f, 4.0f, 5.0f}});
+    cout << "a" << endl << a << endl << endl;
+    =>
+    a
+    0 1 2
+    3 4 5
+
+If a list is too short, the corresponding elements of the tensor will not be
+changed.  This is valid at each level of nesting.  For example the following
+code only sets the values of the first row of the tensor.
+
+    Eigen::Tensor<int, 2> a(2, 3);
+    a.setConstant(1000);
+    a.setValues({{10, 20, 30}});
+    cout << "a" << endl << a << endl << endl;
+    =>
+    a
+    10   20   30
+    1000 1000 1000
+
+### <Tensor-Type> setRandom()
+
+Fills the tensor with random values.  Returns the tensor itself in case you
+want to chain another call.
+
+    a.setRandom();
+    cout << "Random: " << endl << a << endl << endl;
+    =>
+    Random:
+      0.680375    0.59688  -0.329554    0.10794
+     -0.211234   0.823295   0.536459 -0.0452059
+      0.566198  -0.604897  -0.444451   0.257742
+
+You can customize ```setRandom()``` by providing your own random number
+generator as a template argument:
+
+    a.setRandom<MyRandomGenerator>();
+
+Here, ```MyRandomGenerator``` must be a struct with the following member
+functions, where Scalar and Index are the same as ```<Tensor-Type>::Scalar```
+and ```<Tensor-Type>::Index```.
+
+See ```struct UniformRandomGenerator``` in TensorFunctors.h for an example.
+
+    // Custom number generator for use with setRandom().
+    struct MyRandomGenerator {
+      // Default and copy constructors. Both are needed
+      MyRandomGenerator() { }
+      MyRandomGenerator(const MyRandomGenerator& ) { }
+
+      // Return a random value to be used.  "element_location" is the
+      // location of the entry to set in the tensor, it can typically
+      // be ignored.
+      Scalar operator()(Eigen::DenseIndex element_location,
+                        Eigen::DenseIndex /*unused*/ = 0) const {
+        return <randomly generated value of type T>;
+      }
+
+      // Same as above but generates several numbers at a time.
+      typename internal::packet_traits<Scalar>::type packetOp(
+          Eigen::DenseIndex packet_location, Eigen::DenseIndex /*unused*/ = 0) const {
+        return <a packet of randomly generated values>;
+      }
+    };
+
+You can also use one of the 2 random number generators that are part of the
+tensor library:
+*   UniformRandomGenerator
+*   NormalRandomGenerator
+
+
+## Data Access
+
+The Tensor, TensorFixedSize, and TensorRef classes provide the following
+accessors to access the tensor coefficients:
+
+    const Scalar& operator()(const array<Index, NumIndices>& indices)
+    const Scalar& operator()(Index firstIndex, IndexTypes... otherIndices)
+    Scalar& operator()(const array<Index, NumIndices>& indices)
+    Scalar& operator()(Index firstIndex, IndexTypes... otherIndices)
+
+The number of indices must be equal to the rank of the tensor. Moreover, these
+accessors are not available on tensor expressions. In order to access the
+values of a tensor expression, the expression must either be evaluated or
+wrapped in a TensorRef.
+
+
+### Scalar* data() and const Scalar* data() const
+
+Returns a pointer to the storage for the tensor.  The pointer is const if the
+tensor was const.  This allows direct access to the data.  The layout of the
+data depends on the tensor layout: RowMajor or ColMajor.
+
+This access is usually only needed for special cases, for example when mixing
+Eigen Tensor code with other libraries.
+
+Scalar is the type of data stored in the tensor.
+
+    Eigen::Tensor<float, 2> a(3, 4);
+    float* a_data = a.data();
+    a_data[0] = 123.45f;
+    cout << "a(0, 0): " << a(0, 0);
+    => a(0, 0): 123.45
+
+
+## Tensor Operations
+
+All the methods documented below return non evaluated tensor ```Operations```.
+These can be chained: you can apply another Tensor Operation to the value
+returned by the method.
+
+The chain of Operation is evaluated lazily, typically when it is assigned to a
+tensor.  See "Controlling when Expression are Evaluated" for more details about
+their evaluation.
+
+### <Operation> constant(const Scalar& val)
+
+Returns a tensor of the same type and dimensions as the original tensor but
+where all elements have the value ```val```.
+
+This is useful, for example, when you want to add or subtract a constant from a
+tensor, or multiply every element of a tensor by a scalar.
+
+    Eigen::Tensor<float, 2> a(2, 3);
+    a.setConstant(1.0f);
+    Eigen::Tensor<float, 2> b = a + a.constant(2.0f);
+    Eigen::Tensor<float, 2> c = b * b.constant(0.2f);
+    cout << "a" << endl << a << endl << endl;
+    cout << "b" << endl << b << endl << endl;
+    cout << "c" << endl << c << endl << endl;
+    =>
+    a
+    1 1 1
+    1 1 1
+
+    b
+    3 3 3
+    3 3 3
+
+    c
+    0.6 0.6 0.6
+    0.6 0.6 0.6
+
+### <Operation> random()
+
+Returns a tensor of the same type and dimensions as the current tensor
+but where all elements have random values.
+
+This is for example useful to add random values to an existing tensor.
+The generation of random values can be customized in the same manner
+as for ```setRandom()```.
+
+    Eigen::Tensor<float, 2> a(2, 3);
+    a.setConstant(1.0f);
+    Eigen::Tensor<float, 2> b = a + a.random();
+    cout << "a" << endl << a << endl << endl;
+    cout << "b" << endl << b << endl << endl;
+    =>
+    a
+    1 1 1
+    1 1 1
+
+    b
+    1.68038   1.5662  1.82329
+    0.788766  1.59688 0.395103
+
+
+## Unary Element Wise Operations
+
+All these operations take a single input tensor as argument and return a tensor
+of the same type and dimensions as the tensor to which they are applied.  The
+requested operations are applied to each element independently.
+
+### <Operation> operator-()
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the opposite values of the original tensor.
+
+    Eigen::Tensor<float, 2> a(2, 3);
+    a.setConstant(1.0f);
+    Eigen::Tensor<float, 2> b = -a;
+    cout << "a" << endl << a << endl << endl;
+    cout << "b" << endl << b << endl << endl;
+    =>
+    a
+    1 1 1
+    1 1 1
+
+    b
+    -1 -1 -1
+    -1 -1 -1
+
+### <Operation> sqrt()
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the square roots of the original tensor.
+
+### <Operation> rsqrt()
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the inverse square roots of the original tensor.
+
+### <Operation> square()
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the squares of the original tensor values.
+
+### <Operation> inverse()
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the inverse of the original tensor values.
+
+### <Operation> exp()
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the exponential of the original tensor.
+
+### <Operation> log()
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the natural logarithms of the original tensor.
+
+### <Operation> abs()
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the absolute values of the original tensor.
+
+### <Operation> pow(Scalar exponent)
+
+Returns a tensor of the same type and dimensions as the original tensor
+containing the coefficients of the original tensor to the power of the
+exponent.
+
+The type of the exponent, Scalar, is always the same as the type of the
+tensor coefficients.  For example, only integer exponents can be used in
+conjuntion with tensors of integer values.
+
+You can use cast() to lift this restriction.  For example this computes
+cubic roots of an int Tensor:
+
+    Eigen::Tensor<int, 2> a(2, 3);
+    a.setValues({{0, 1, 8}, {27, 64, 125}});
+    Eigen::Tensor<double, 2> b = a.cast<double>().pow(1.0 / 3.0);
+    cout << "a" << endl << a << endl << endl;
+    cout << "b" << endl << b << endl << endl;
+    =>
+    a
+    0   1   8
+    27  64 125
+
+    b
+    0 1 2
+    3 4 5
+
+### <Operation>  operator * (Scalar scale)
+
+Multiplies all the coefficients of the input tensor by the provided scale.
+
+### <Operation>  cwiseMax(Scalar threshold)
+TODO
+
+### <Operation>  cwiseMin(Scalar threshold)
+TODO
+
+### <Operation>  unaryExpr(const CustomUnaryOp& func)
+TODO
+
+
+## Binary Element Wise Operations
+
+These operations take two input tensors as arguments. The 2 input tensors should
+be of the same type and dimensions. The result is a tensor of the same
+dimensions as the tensors to which they are applied, and unless otherwise
+specified it is also of the same type. The requested operations are applied to
+each pair of elements independently.
+
+### <Operation> operator+(const OtherDerived& other)
+
+Returns a tensor of the same type and dimensions as the input tensors
+containing the coefficient wise sums of the inputs.
+
+### <Operation> operator-(const OtherDerived& other)
+
+Returns a tensor of the same type and dimensions as the input tensors
+containing the coefficient wise differences of the inputs.
+
+### <Operation> operator*(const OtherDerived& other)
+
+Returns a tensor of the same type and dimensions as the input tensors
+containing the coefficient wise products of the inputs.
+
+### <Operation> operator/(const OtherDerived& other)
+
+Returns a tensor of the same type and dimensions as the input tensors
+containing the coefficient wise quotients of the inputs.
+
+This operator is not supported for integer types.
+
+### <Operation> cwiseMax(const OtherDerived& other)
+
+Returns a tensor of the same type and dimensions as the input tensors
+containing the coefficient wise maximums of the inputs.
+
+### <Operation> cwiseMin(const OtherDerived& other)
+
+Returns a tensor of the same type and dimensions as the input tensors
+containing the coefficient wise mimimums of the inputs.
+
+### <Operation> Logical operators
+
+The following logical operators are supported as well:
+
+*   operator&&(const OtherDerived& other)
+*   operator||(const OtherDerived& other)
+*   operator<(const OtherDerived& other)
+*   operator<=(const OtherDerived& other)
+*   operator>(const OtherDerived& other)
+*   operator>=(const OtherDerived& other)
+*   operator==(const OtherDerived& other)
+*   operator!=(const OtherDerived& other)
+
+They all return a tensor of boolean values.
+
+
+## Selection (select(const ThenDerived& thenTensor, const ElseDerived& elseTensor)
+
+Selection is a coefficient-wise ternary operator that is the tensor equivalent
+to the if-then-else operation.
+
+    Tensor<bool, 3> if = ...;
+    Tensor<float, 3> then = ...;
+    Tensor<float, 3> else = ...;
+    Tensor<float, 3> result = if.select(then, else);
+
+The 3 arguments must be of the same dimensions, which will also be the dimension
+of the result.  The 'if' tensor must be of type boolean, the 'then' and the
+'else' tensor must be of the same type, which will also be the type of the
+result.
+
+Each coefficient in the result is equal to the corresponding coefficient in the
+'then' tensor if the corresponding value in the 'if' tensor is true. If not, the
+resulting coefficient will come from the 'else' tensor.
+
+
+## Contraction
+
+Tensor *contractions* are a generalization of the matrix product to the
+multidimensional case.
+
+    // Create 2 matrices using tensors of rank 2
+    Eigen::Tensor<int, 2> a(2, 3);
+    a.setValues({{1, 2, 3}, {6, 5, 4}});
+    Eigen::Tensor<int, 2> b(3, 2);
+    a.setValues({{1, 2}, {4, 5}, {5, 6}});
+
+    // Compute the traditional matrix product
+    array<IndexPair<int>, 1> product_dims = { IndexPair(1, 0) };
+    Eigen::Tensor<int, 2> AB = a.contract(b, product_dims);
+
+    // Compute the product of the transpose of the matrices
+    array<IndexPair<int>, 1> transpose_product_dims = { IndexPair(0, 1) };
+    Eigen::Tensor<int, 2> AtBt = a.contract(b, transposed_product_dims);
+
+
+## Reduction Operations
+
+A *Reduction* operation returns a tensor with fewer dimensions than the
+original tensor.  The values in the returned tensor are computed by applying a
+*reduction operator* to slices of values from the original tensor.  You specify
+the dimensions along which the slices are made.
+
+The Eigen Tensor library provides a set of predefined reduction operators such
+as ```maximum()``` and ```sum()``` and lets you define additional operators by
+implementing a few methods from a reductor template.
+
+### Reduction Dimensions
+
+All reduction operations take a single parameter of type
+```<TensorType>::Dimensions``` which can always be specified as an array of
+ints.  These are called the "reduction dimensions."  The values are the indices
+of the dimensions of the input tensor over which the reduction is done.  The
+parameter can have at most as many element as the rank of the input tensor;
+each element must be less than the tensor rank, as it indicates one of the
+dimensions to reduce.
+
+Each dimension of the input tensor should occur at most once in the reduction
+dimensions as the implementation does not remove duplicates.
+
+The order of the values in the reduction dimensions does not affect the
+results, but the code may execute faster if you list the dimensions in
+increasing order.
+
+Example: Reduction along one dimension.
+
+    // Create a tensor of 2 dimensions
+    Eigen::Tensor<int, 2> a(2, 3);
+    a.setValues({{1, 2, 3}, {6, 5, 4}});
+    // Reduce it along the second dimension (1)...
+    Eigen::array<int, 1> dims({1 /* dimension to reduce */});
+    // ...using the "maximum" operator.
+    // The result is a tensor with one dimension.  The size of
+    // that dimension is the same as the first (non-reduced) dimension of a.
+    Eigen::Tensor<int, 1> b = a.maximum(dims);
+    cout << "a" << endl << a << endl << endl;
+    cout << "b" << endl << b << endl << endl;
+    =>
+    a
+    1 2 3
+    6 5 4
+
+    b
+    3
+    6
+
+Example: Reduction along two dimensions.
+
+    Eigen::Tensor<float, 3, Eigen::ColMajor> a(2, 3, 4);
+    a.setValues({{{0.0f, 1.0f, 2.0f, 3.0f},
+                  {7.0f, 6.0f, 5.0f, 4.0f},
+                  {8.0f, 9.0f, 10.0f, 11.0f}},
+                 {{12.0f, 13.0f, 14.0f, 15.0f},
+                  {19.0f, 18.0f, 17.0f, 16.0f},
+                  {20.0f, 21.0f, 22.0f, 23.0f}}});
+    // The tensor a has 3 dimensions.  We reduce along the
+    // first 2, resulting in a tensor with a single dimension
+    // of size 4 (the last dimension of a.)
+    // Note that we pass the array of reduction dimensions
+    // directly to the maximum() call.
+    Eigen::Tensor<float, 1, Eigen::ColMajor> b =
+        a.maximum(Eigen::array<int, 2>({0, 1}));
+    cout << "b" << endl << b << endl << endl;
+    =>
+    b
+    20
+    21
+    22
+    23
+
+#### Reduction along all dimensions
+
+As a special case, if you pass no parameter to a reduction operation the
+original tensor is reduced along *all* its dimensions.  The result is a
+scalar, represented as a zero-dimension tensor.
+
+    Eigen::Tensor<float, 3> a(2, 3, 4);
+    a.setValues({{{0.0f, 1.0f, 2.0f, 3.0f},
+                  {7.0f, 6.0f, 5.0f, 4.0f},
+                  {8.0f, 9.0f, 10.0f, 11.0f}},
+                 {{12.0f, 13.0f, 14.0f, 15.0f},
+                  {19.0f, 18.0f, 17.0f, 16.0f},
+                  {20.0f, 21.0f, 22.0f, 23.0f}}});
+    // Reduce along all dimensions using the sum() operator.
+    Eigen::Tensor<float, 0> b = a.sum();
+    cout << "b" << endl << b << endl << endl;
+    =>
+    b
+    276
+
+
+### <Operation> sum(const Dimensions& new_dims)
+### <Operation> sum()
+
+Reduce a tensor using the sum() operator.  The resulting values
+are the sum of the reduced values.
+
+### <Operation> mean(const Dimensions& new_dims)
+### <Operation> mean()
+
+Reduce a tensor using the mean() operator.  The resulting values
+are the mean of the reduced values.
+
+### <Operation> maximum(const Dimensions& new_dims)
+### <Operation> maximum()
+
+Reduce a tensor using the maximum() operator.  The resulting values are the
+largest of the reduced values.
+
+### <Operation> minimum(const Dimensions& new_dims)
+### <Operation> minimum()
+
+Reduce a tensor using the minimum() operator.  The resulting values
+are the smallest of the reduced values.
+
+### <Operation> prod(const Dimensions& new_dims)
+### <Operation> prod()
+
+Reduce a tensor using the prod() operator.  The resulting values
+are the product of the reduced values.
+
+### <Operation> all(const Dimensions& new_dims)
+### <Operation> all()
+Reduce a tensor using the all() operator.  Casts tensor to bool and then checks
+whether all elements are true.  Runs through all elements rather than
+short-circuiting, so may be significantly inefficient.
+
+### <Operation> any(const Dimensions& new_dims)
+### <Operation> any()
+Reduce a tensor using the any() operator.  Casts tensor to bool and then checks
+whether any element is true.  Runs through all elements rather than
+short-circuiting, so may be significantly inefficient.
+
+
+### <Operation> reduce(const Dimensions& new_dims, const Reducer& reducer)
+
+Reduce a tensor using a user-defined reduction operator.  See ```SumReducer```
+in TensorFunctors.h for information on how to implement a reduction operator.
+
+
+## Scan Operations
+
+A *Scan* operation returns a tensor with the same dimensions as the original
+tensor. The operation performs an inclusive scan along the specified
+axis, which means it computes a running total along the axis for a given
+reduction operation.
+If the reduction operation corresponds to summation, then this computes the
+prefix sum of the tensor along the given axis.
+
+Example:
+dd a comment to this line
+
+    // Create a tensor of 2 dimensions
+    Eigen::Tensor<int, 2> a(2, 3);
+    a.setValues({{1, 2, 3}, {4, 5, 6}});
+    // Scan it along the second dimension (1) using summation
+    Eigen::Tensor<int, 2> b = a.cumsum(1);
+    // The result is a tensor with the same size as the input
+    cout << "a" << endl << a << endl << endl;
+    cout << "b" << endl << b << endl << endl;
+    =>
+    a
+    1 2 3
+    6 5 4
+
+    b
+    1  3  6
+    4  9 15
+
+### <Operation> cumsum(const Index& axis)
+
+Perform a scan by summing consecutive entries.
+
+### <Operation> cumprod(const Index& axis)
+
+Perform a scan by multiplying consecutive entries.
+
+
+## Convolutions
+
+### <Operation> convolve(const Kernel& kernel, const Dimensions& dims)
+
+Returns a tensor that is the output of the convolution of the input tensor with the kernel,
+along the specified dimensions of the input tensor. The dimension size for dimensions of the output tensor
+which were part of the convolution will be reduced by the formula:
+output_dim_size = input_dim_size - kernel_dim_size + 1 (requires: input_dim_size >= kernel_dim_size).
+The dimension sizes for dimensions that were not part of the convolution will remain the same.
+Performance of the convolution can depend on the length of the stride(s) of the input tensor dimension(s) along which the
+convolution is computed (the first dimension has the shortest stride for ColMajor, whereas RowMajor's shortest stride is
+for the last dimension).
+
+    // Compute convolution along the second and third dimension.
+    Tensor<float, 4, DataLayout> input(3, 3, 7, 11);
+    Tensor<float, 2, DataLayout> kernel(2, 2);
+    Tensor<float, 4, DataLayout> output(3, 2, 6, 11);
+    input.setRandom();
+    kernel.setRandom();
+
+    Eigen::array<ptrdiff_t, 2> dims({1, 2});  // Specify second and third dimension for convolution.
+    output = input.convolve(kernel, dims);
+
+    for (int i = 0; i < 3; ++i) {
+      for (int j = 0; j < 2; ++j) {
+        for (int k = 0; k < 6; ++k) {
+          for (int l = 0; l < 11; ++l) {
+            const float result = output(i,j,k,l);
+            const float expected = input(i,j+0,k+0,l) * kernel(0,0) +
+                                   input(i,j+1,k+0,l) * kernel(1,0) +
+                                   input(i,j+0,k+1,l) * kernel(0,1) +
+                                   input(i,j+1,k+1,l) * kernel(1,1);
+            VERIFY_IS_APPROX(result, expected);
+          }
+        }
+      }
+    }
+
+
+## Geometrical Operations
+
+These operations return a Tensor with different dimensions than the original
+Tensor.  They can be used to access slices of tensors, see them with different
+dimensions, or pad tensors with additional data.
+
+### <Operation> reshape(const Dimensions& new_dims)
+
+Returns a view of the input tensor that has been reshaped to the specified
+new dimensions.  The argument new_dims is an array of Index values.  The
+rank of the resulting tensor is equal to the number of elements in new_dims.
+
+The product of all the sizes in the new dimension array must be equal to
+the number of elements in the input tensor.
+
+    // Increase the rank of the input tensor by introducing a new dimension
+    // of size 1.
+    Tensor<float, 2> input(7, 11);
+    array<int, 3> three_dims{{7, 11, 1}};
+    Tensor<float, 3> result = input.reshape(three_dims);
+
+    // Decrease the rank of the input tensor by merging 2 dimensions;
+    array<int, 1> one_dim{{7 * 11}};
+    Tensor<float, 1> result = input.reshape(one_dim);
+
+This operation does not move any data in the input tensor, so the resulting
+contents of a reshaped Tensor depend on the data layout of the original Tensor.
+
+For example this is what happens when you ```reshape()``` a 2D ColMajor tensor
+to one dimension:
+
+    Eigen::Tensor<float, 2, Eigen::ColMajor> a(2, 3);
+    a.setValues({{0.0f, 100.0f, 200.0f}, {300.0f, 400.0f, 500.0f}});
+    Eigen::array<Eigen::DenseIndex, 1> one_dim({3 * 2});
+    Eigen::Tensor<float, 1, Eigen::ColMajor> b = a.reshape(one_dim);
+    cout << "b" << endl << b << endl;
+    =>
+    b
+      0
+    300
+    100
+    400
+    200
+    500
+
+This is what happens when the 2D Tensor is RowMajor:
+
+    Eigen::Tensor<float, 2, Eigen::RowMajor> a(2, 3);
+    a.setValues({{0.0f, 100.0f, 200.0f}, {300.0f, 400.0f, 500.0f}});
+    Eigen::array<Eigen::DenseIndex, 1> one_dim({3 * 2});
+    Eigen::Tensor<float, 1, Eigen::RowMajor> b = a.reshape(one_dim);
+    cout << "b" << endl << b << endl;
+    =>
+    b
+      0
+    100
+    200
+    300
+    400
+    500
+
+The reshape operation is a lvalue. In other words, it can be used on the left
+side of the assignment operator.
+
+The previous example can be rewritten as follow:
+
+    Eigen::Tensor<float, 2, Eigen::ColMajor> a(2, 3);
+    a.setValues({{0.0f, 100.0f, 200.0f}, {300.0f, 400.0f, 500.0f}});
+    Eigen::array<Eigen::DenseIndex, 2> two_dim({2, 3});
+    Eigen::Tensor<float, 1, Eigen::ColMajor> b;
+    b.reshape(two_dim) = a;
+    cout << "b" << endl << b << endl;
+    =>
+    b
+      0
+    300
+    100
+    400
+    200
+    500
+
+Note that "b" itself was not reshaped but that instead the assignment is done to
+the reshape view of b.
+
+
+### <Operation> shuffle(const Shuffle& shuffle)
+
+Returns a copy of the input tensor whose dimensions have been
+reordered according to the specified permutation. The argument shuffle
+is an array of Index values. Its size is the rank of the input
+tensor. It must contain a permutation of 0, 1, ..., rank - 1. The i-th
+dimension of the output tensor equals to the size of the shuffle[i]-th
+dimension of the input tensor. For example:
+
+    // Shuffle all dimensions to the left by 1.
+    Tensor<float, 3> input(20, 30, 50);
+    // ... set some values in input.
+    Tensor<float, 3> output = input.shuffle({1, 2, 0})
+
+    eigen_assert(output.dimension(0) == 30);
+    eigen_assert(output.dimension(1) == 50);
+    eigen_assert(output.dimension(2) == 20);
+
+Indices into the output tensor are shuffled accordingly to formulate
+indices into the input tensor. For example, one can assert in the above
+code snippet that:
+
+    eigen_assert(output(3, 7, 11) == input(11, 3, 7));
+
+In general, one can assert that
+
+    eigen_assert(output(..., indices[shuffle[i]], ...) ==
+                 input(..., indices[i], ...))
+
+The shuffle operation results in a lvalue, which means that it can be assigned
+to. In other words, it can be used on the left side of the assignment operator.
+
+Let's rewrite the previous example to take advantage of this feature:
+
+    // Shuffle all dimensions to the left by 1.
+    Tensor<float, 3> input(20, 30, 50);
+    // ... set some values in input.
+    Tensor<float, 3> output(30, 50, 20);
+    output.shuffle({2, 0, 1}) = input;
+
+
+### <Operation> stride(const Strides& strides)
+
+Returns a view of the input tensor that strides (skips stride-1
+elements) along each of the dimensions.  The argument strides is an
+array of Index values.  The dimensions of the resulting tensor are
+ceil(input_dimensions[i] / strides[i]).
+
+For example this is what happens when you ```stride()``` a 2D tensor:
+
+    Eigen::Tensor<int, 2> a(4, 3);
+    a.setValues({{0, 100, 200}, {300, 400, 500}, {600, 700, 800}, {900, 1000, 1100}});
+    Eigen::array<Eigen::DenseIndex, 2> strides({3, 2});
+    Eigen::Tensor<int, 2> b = a.stride(strides);
+    cout << "b" << endl << b << endl;
+    =>
+    b
+       0   200
+     900  1100
+
+It is possible to assign a tensor to a stride:
+    Tensor<float, 3> input(20, 30, 50);
+    // ... set some values in input.
+    Tensor<float, 3> output(40, 90, 200);
+    output.stride({2, 3, 4}) = input;
+
+
+### <Operation> slice(const StartIndices& offsets, const Sizes& extents)
+
+Returns a sub-tensor of the given tensor. For each dimension i, the slice is
+made of the coefficients stored between offset[i] and offset[i] + extents[i] in
+the input tensor.
+
+    Eigen::Tensor<int, 2> a(4, 3);
+    a.setValues({{0, 100, 200}, {300, 400, 500},
+                 {600, 700, 800}, {900, 1000, 1100}});
+    Eigen::array<int, 2> offsets = {1, 0};
+    Eigen::array<int, 2> extents = {2, 2};
+    Eigen::Tensor<int, 1> slice = a.slice(offsets, extents);
+    cout << "a" << endl << a << endl;
+    =>
+    a
+       0   100   200
+     300   400   500
+     600   700   800
+     900  1000  1100
+    cout << "slice" << endl << slice << endl;
+    =>
+    slice
+     300   400
+     600   700
+
+
+### <Operation> chip(const Index offset, const Index dim)
+
+A chip is a special kind of slice. It is the subtensor at the given offset in
+the dimension dim. The returned tensor has one fewer dimension than the input
+tensor: the dimension dim is removed.
+
+For example, a matrix chip would be either a row or a column of the input
+matrix.
+
+    Eigen::Tensor<int, 2> a(4, 3);
+    a.setValues({{0, 100, 200}, {300, 400, 500},
+                 {600, 700, 800}, {900, 1000, 1100}});
+    Eigen::Tensor<int, 1> row_3 = a.chip(2, 0);
+    Eigen::Tensor<int, 1> col_2 = a.chip(1, 1);
+    cout << "a" << endl << a << endl;
+    =>
+    a
+       0   100   200
+     300   400   500
+     600   700   800
+     900  1000  1100
+    cout << "row_3" << endl << row_3 << endl;
+    =>
+    row_3
+       600   700   800
+    cout << "col_2" << endl << col_2 << endl;
+    =>
+    col_2
+       100   400   700    1000
+
+It is possible to assign values to a tensor chip since the chip operation is a
+lvalue. For example:
+
+    Eigen::Tensor<int, 1> a(3);
+    a.setValues({{100, 200, 300}});
+    Eigen::Tensor<int, 2> b(2, 3);
+    b.setZero();
+    b.chip(0, 0) = a;
+    cout << "a" << endl << a << endl;
+    =>
+    a
+     100
+     200
+     300
+    cout << "b" << endl << b << endl;
+    =>
+    b
+       100   200   300
+         0     0     0
+
+
+### <Operation> reverse(const ReverseDimensions& reverse)
+
+Returns a view of the input tensor that reverses the order of the coefficients
+along a subset of the dimensions.  The argument reverse is an array of boolean
+values that indicates whether or not the order of the coefficients should be
+reversed along each of the dimensions.  This operation preserves the dimensions
+of the input tensor.
+
+For example this is what happens when you ```reverse()``` the first dimension
+of a 2D tensor:
+
+    Eigen::Tensor<int, 2> a(4, 3);
+    a.setValues({{0, 100, 200}, {300, 400, 500},
+                {600, 700, 800}, {900, 1000, 1100}});
+    Eigen::array<bool, 2> reverse({true, false});
+    Eigen::Tensor<int, 2> b = a.reverse(reverse);
+    cout << "a" << endl << a << endl << "b" << endl << b << endl;
+    =>
+    a
+       0   100   200
+     300   400   500
+     600   700   800
+     900  1000  1100
+    b
+     900  1000  1100
+     600   700   800
+     300   400   500
+       0   100   200
+
+
+### <Operation> broadcast(const Broadcast& broadcast)
+
+Returns a view of the input tensor in which the input is replicated one to many
+times.
+The broadcast argument specifies how many copies of the input tensor need to be
+made in each of the dimensions.
+
+    Eigen::Tensor<int, 2> a(2, 3);
+    a.setValues({{0, 100, 200}, {300, 400, 500}});
+    Eigen::array<int, 2> bcast({3, 2});
+    Eigen::Tensor<int, 2> b = a.broadcast(bcast);
+    cout << "a" << endl << a << endl << "b" << endl << b << endl;
+    =>
+    a
+       0   100   200
+     300   400   500
+    b
+       0   100   200    0   100   200
+     300   400   500  300   400   500
+       0   100   200    0   100   200
+     300   400   500  300   400   500
+       0   100   200    0   100   200
+     300   400   500  300   400   500
+
+### <Operation> concatenate(const OtherDerived& other, Axis axis)
+
+TODO
+
+### <Operation>  pad(const PaddingDimensions& padding)
+
+Returns a view of the input tensor in which the input is padded with zeros.
+
+    Eigen::Tensor<int, 2> a(2, 3);
+    a.setValues({{0, 100, 200}, {300, 400, 500}});
+    Eigen::array<pair<int, int>, 2> paddings;
+    paddings[0] = make_pair(0, 1);
+    paddings[1] = make_pair(2, 3);
+    Eigen::Tensor<int, 2> b = a.pad(paddings);
+    cout << "a" << endl << a << endl << "b" << endl << b << endl;
+    =>
+    a
+       0   100   200
+     300   400   500
+    b
+       0     0     0    0
+       0     0     0    0
+       0   100   200    0
+     300   400   500    0
+       0     0     0    0
+       0     0     0    0
+       0     0     0    0
+
+
+### <Operation>  extract_patches(const PatchDims& patch_dims)
+
+Returns a tensor of coefficient patches extracted from the input tensor, where
+each patch is of dimension specified by 'patch_dims'. The returned tensor has
+one greater dimension than the input tensor, which is used to index each patch.
+The patch index in the output tensor depends on the data layout of the input
+tensor: the patch index is the last dimension ColMajor layout, and the first
+dimension in RowMajor layout.
+
+For example, given the following input tensor:
+
+  Eigen::Tensor<float, 2, DataLayout> tensor(3,4);
+  tensor.setValues({{0.0f, 1.0f, 2.0f, 3.0f},
+                    {4.0f, 5.0f, 6.0f, 7.0f},
+                    {8.0f, 9.0f, 10.0f, 11.0f}});
+
+  cout << "tensor: " << endl << tensor << endl;
+=>
+tensor:
+ 0   1   2   3
+ 4   5   6   7
+ 8   9  10  11
+
+Six 2x2 patches can be extracted and indexed using the following code:
+
+  Eigen::Tensor<float, 3, DataLayout> patch;
+  Eigen::array<ptrdiff_t, 2> patch_dims;
+  patch_dims[0] = 2;
+  patch_dims[1] = 2;
+  patch = tensor.extract_patches(patch_dims);
+  for (int k = 0; k < 6; ++k) {
+    cout << "patch index: " << k << endl;
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 2; ++j) {
+        if (DataLayout == ColMajor) {
+          cout << patch(i, j, k) << " ";
+        } else {
+          cout << patch(k, i, j) << " ";
+        }
+      }
+      cout << endl;
+    }
+  }
+
+This code results in the following output when the data layout is ColMajor:
+
+patch index: 0
+0 1
+4 5
+patch index: 1
+4 5
+8 9
+patch index: 2
+1 2
+5 6
+patch index: 3
+5 6
+9 10
+patch index: 4
+2 3
+6 7
+patch index: 5
+6 7
+10 11
+
+This code results in the following output when the data layout is RowMajor:
+(NOTE: the set of patches is the same as in ColMajor, but are indexed differently).
+
+patch index: 0
+0 1
+4 5
+patch index: 1
+1 2
+5 6
+patch index: 2
+2 3
+6 7
+patch index: 3
+4 5
+8 9
+patch index: 4
+5 6
+9 10
+patch index: 5
+6 7
+10 11
+
+### <Operation>  extract_image_patches(const Index patch_rows, const Index patch_cols,
+                          const Index row_stride, const Index col_stride,
+                          const PaddingType padding_type)
+
+Returns a tensor of coefficient image patches extracted from the input tensor,
+which is expected to have dimensions ordered as follows (depending on the data
+layout of the input tensor, and the number of additional dimensions 'N'):
+
+*) ColMajor
+1st dimension: channels (of size d)
+2nd dimension: rows (of size r)
+3rd dimension: columns (of size c)
+4th-Nth dimension: time (for video) or batch (for bulk processing).
+
+*) RowMajor (reverse order of ColMajor)
+1st-Nth dimension: time (for video) or batch (for bulk processing).
+N+1'th dimension: columns (of size c)
+N+2'th dimension: rows (of size r)
+N+3'th dimension: channels (of size d)
+
+The returned tensor has one greater dimension than the input tensor, which is
+used to index each patch. The patch index in the output tensor depends on the
+data layout of the input tensor: the patch index is the 4'th dimension in
+ColMajor layout, and the 4'th from the last dimension in RowMajor layout.
+
+For example, given the following input tensor with the following dimension
+sizes:
+ *) depth:   2
+ *) rows:    3
+ *) columns: 5
+ *) batch:   7
+
+  Tensor<float, 4> tensor(2,3,5,7);
+  Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
+
+2x2 image patches can be extracted and indexed using the following code:
+
+*) 2D patch: ColMajor (patch indexed by second-to-last dimension)
+  Tensor<float, 5> twod_patch;
+  twod_patch = tensor.extract_image_patches<2, 2>();
+  // twod_patch.dimension(0) == 2
+  // twod_patch.dimension(1) == 2
+  // twod_patch.dimension(2) == 2
+  // twod_patch.dimension(3) == 3*5
+  // twod_patch.dimension(4) == 7
+
+*) 2D patch: RowMajor (patch indexed by the second dimension)
+  Tensor<float, 5, RowMajor> twod_patch_row_major;
+  twod_patch_row_major = tensor_row_major.extract_image_patches<2, 2>();
+  // twod_patch_row_major.dimension(0) == 7
+  // twod_patch_row_major.dimension(1) == 3*5
+  // twod_patch_row_major.dimension(2) == 2
+  // twod_patch_row_major.dimension(3) == 2
+  // twod_patch_row_major.dimension(4) == 2
+
+## Special Operations
+
+### <Operation> cast<T>()
+
+Returns a tensor of type T with the same dimensions as the original tensor.
+The returned tensor contains the values of the original tensor converted to
+type T.
+
+    Eigen::Tensor<float, 2> a(2, 3);
+    Eigen::Tensor<int, 2> b = a.cast<int>();
+
+This can be useful for example if you need to do element-wise division of
+Tensors of integers.  This is not currently supported by the Tensor library
+but you can easily cast the tensors to floats to do the division:
+
+    Eigen::Tensor<int, 2> a(2, 3);
+    a.setValues({{0, 1, 2}, {3, 4, 5}});
+    Eigen::Tensor<int, 2> b =
+        (a.cast<float>() / a.constant(2).cast<float>()).cast<int>();
+    cout << "a" << endl << a << endl << endl;
+    cout << "b" << endl << b << endl << endl;
+    =>
+    a
+    0 1 2
+    3 4 5
+
+    b
+    0 0 1
+    1 2 2
+
+
+### <Operation>     eval()
+
+TODO
+
+
+## Representation of scalar values
+
+Scalar values are often represented by tensors of size 1 and rank 1. It would be
+more logical and user friendly to use tensors of rank 0 instead. For example
+Tensor<T, N>::maximum() currently returns a Tensor<T, 1>. Similarly, the inner
+product of 2 1d tensors (through contractions) returns a 1d tensor. In the
+future these operations might be updated to return 0d tensors instead.
+
+## Limitations
+
+*   The number of tensor dimensions is currently limited to 250 when using a
+    compiler that supports cxx11. It is limited to only 5 for older compilers.
+*   The IndexList class requires a cxx11 compliant compiler. You can use an
+    array of indices instead if you don't have access to a modern compiler.
+*   On GPUs only floating point values are properly tested and optimized for.
+*   Complex and integer values are known to be broken on GPUs. If you try to use
+    them you'll most likely end up triggering a static assertion failure such as
+    EIGEN_STATIC_ASSERT(packetSize > 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
+
+

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/Tensor.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/Tensor.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/Tensor.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/Tensor.h
@@ -0,0 +1,527 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_H
+#define EIGEN_CXX11_TENSOR_TENSOR_H
+
+namespace Eigen {
+
+/** \class Tensor
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief The tensor class.
+  *
+  * The %Tensor class is the work-horse for all \em dense tensors within Eigen.
+  *
+  * The %Tensor class encompasses only dynamic-size objects so far.
+  *
+  * The first two template parameters are required:
+  * \tparam Scalar_ \anchor tensor_tparam_scalar Numeric type, e.g. float, double, int or std::complex<float>.
+  *                 User defined scalar types are supported as well (see \ref user_defined_scalars "here").
+  * \tparam NumIndices_ Number of indices (i.e. rank of the tensor)
+  *
+  * The remaining template parameters are optional -- in most cases you don't have to worry about them.
+  * \tparam Options_ \anchor tensor_tparam_options A combination of either \b #RowMajor or \b #ColMajor, and of either
+  *                 \b #AutoAlign or \b #DontAlign.
+  *                 The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required
+  *                 for vectorization. It defaults to aligning tensors. Note that tensors currently do not support any operations that profit from vectorization.
+  *                 Support for such operations (i.e. adding two tensors etc.) is planned.
+  *
+  * You can access elements of tensors using normal subscripting:
+  *
+  * \code
+  * Eigen::Tensor<double, 4> t(10, 10, 10, 10);
+  * t(0, 1, 2, 3) = 42.0;
+  * \endcode
+  *
+  * This class can be extended with the help of the plugin mechanism described on the page
+  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_TENSOR_PLUGIN.
+  *
+  * <i><b>Some notes:</b></i>
+  *
+  * <dl>
+  * <dt><b>Relation to other parts of Eigen:</b></dt>
+  * <dd>The midterm developement goal for this class is to have a similar hierarchy as Eigen uses for matrices, so that
+  * taking blocks or using tensors in expressions is easily possible, including an interface with the vector/matrix code
+  * by providing .asMatrix() and .asVector() (or similar) methods for rank 2 and 1 tensors. However, currently, the %Tensor
+  * class does not provide any of these features and is only available as a stand-alone class that just allows for
+  * coefficient access. Also, when fixed-size tensors are implemented, the number of template arguments is likely to
+  * change dramatically.</dd>
+  * </dl>
+  *
+  * \ref TopicStorageOrders
+  */
+
+template<typename Scalar_, int NumIndices_, int Options_, typename IndexType_>
+class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexType_> >
+{
+  public:
+    typedef Tensor<Scalar_, NumIndices_, Options_, IndexType_> Self;
+    typedef TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexType_> > Base;
+    typedef typename Eigen::internal::nested<Self>::type Nested;
+    typedef typename internal::traits<Self>::StorageKind StorageKind;
+    typedef typename internal::traits<Self>::Index Index;
+    typedef Scalar_ Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename Base::CoeffReturnType CoeffReturnType;
+
+    enum {
+      IsAligned = bool(EIGEN_MAX_ALIGN_BYTES>0) & !(Options_&DontAlign),
+      Layout = Options_ & RowMajor ? RowMajor : ColMajor,
+      CoordAccess = true,
+      RawAccess = true
+    };
+
+    static const int Options = Options_;
+    static const int NumIndices = NumIndices_;
+    typedef DSizes<Index, NumIndices_> Dimensions;
+
+  protected:
+    TensorStorage<Scalar, Dimensions, Options> m_storage;
+
+#ifdef EIGEN_HAS_SFINAE
+    template<typename CustomIndices>
+    struct isOfNormalIndex{
+      static const bool is_array = internal::is_base_of<array<Index, NumIndices>, CustomIndices>::value;
+      static const bool is_int = NumTraits<CustomIndices>::IsInteger;
+      static const bool value = is_array | is_int;
+    };
+#endif
+
+  public:
+    // Metadata
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index                         rank()                   const { return NumIndices; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index                         dimension(std::size_t n) const { return m_storage.dimensions()[n]; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions&             dimensions()             const { return m_storage.dimensions(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index                         size()                   const { return m_storage.size(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar                        *data()                        { return m_storage.data(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar                  *data()                  const { return m_storage.data(); }
+
+    // This makes EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    // work, because that uses base().coeffRef() - and we don't yet
+    // implement a similar class hierarchy
+    inline Self& base()             { return *this; }
+    inline const Self& base() const { return *this; }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    EIGEN_DEVICE_FUNC inline const Scalar& coeff(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
+    {
+      // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return coeff(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
+    }
+#endif
+
+    // normal indices
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(const array<Index, NumIndices>& indices) const
+    {
+      eigen_internal_assert(checkIndexRange(indices));
+      return m_storage.data()[linearizedIndex(indices)];
+    }
+
+    // custom indices
+#ifdef EIGEN_HAS_SFINAE
+    template<typename CustomIndices,
+             EIGEN_SFINAE_ENABLE_IF( !(isOfNormalIndex<CustomIndices>::value) )
+    >
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(CustomIndices& indices) const
+    {
+        return coeff(internal::customIndices2Array<Index,NumIndices>(indices));
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff() const
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return m_storage.data()[0];
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return m_storage.data()[index];
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    inline Scalar& coeffRef(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
+    {
+      // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return coeffRef(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
+    }
+#endif
+
+    // normal indices
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(const array<Index, NumIndices>& indices)
+    {
+      eigen_internal_assert(checkIndexRange(indices));
+      return m_storage.data()[linearizedIndex(indices)];
+    }
+
+    // custom indices
+#ifdef EIGEN_HAS_SFINAE
+    template<typename CustomIndices,
+             EIGEN_SFINAE_ENABLE_IF( !(isOfNormalIndex<CustomIndices>::value) )
+             >
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(CustomIndices& indices)
+    {
+        return coeffRef(internal::customIndices2Array<Index,NumIndices>(indices));
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef()
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return m_storage.data()[0];
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return m_storage.data()[index];
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    inline const Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
+    {
+      // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return this->operator()(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
+    }
+#else
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1) const
+    {
+      return coeff(array<Index, 2>(i0, i1));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2) const
+    {
+      return coeff(array<Index, 3>(i0, i1, i2));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3) const
+    {
+      return coeff(array<Index, 4>(i0, i1, i2, i3));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
+    {
+      return coeff(array<Index, 5>(i0, i1, i2, i3, i4));
+    }
+#endif
+
+    // custom indices
+#ifdef EIGEN_HAS_SFINAE
+    template<typename CustomIndices,
+             EIGEN_SFINAE_ENABLE_IF( !(isOfNormalIndex<CustomIndices>::value) )
+    >
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()(CustomIndices& indices) const
+    {
+        return coeff(internal::customIndices2Array<Index,NumIndices>(indices));
+    }
+#endif
+
+    // normal indices
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const
+    {
+      return coeff(indices);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()(Index index) const
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return coeff(index);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()() const
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return coeff();
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator[](Index index) const
+    {
+      // The bracket operator is only for vectors, use the parenthesis operator instead.
+      EIGEN_STATIC_ASSERT(NumIndices == 1, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return coeff(index);
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    inline Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
+    {
+      // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return operator()(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
+    }
+#else
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1)
+    {
+      return coeffRef(array<Index, 2>(i0, i1));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2)
+    {
+      return coeffRef(array<Index, 3>(i0, i1, i2));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
+    {
+      return coeffRef(array<Index, 4>(i0, i1, i2, i3));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
+    {
+      return coeffRef(array<Index, 5>(i0, i1, i2, i3, i4));
+    }
+#endif
+
+    // normal indices
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices)
+    {
+      return coeffRef(indices);
+    }
+
+    // custom indices
+#ifdef EIGEN_HAS_SFINAE
+    template<typename CustomIndices,
+             EIGEN_SFINAE_ENABLE_IF( !(isOfNormalIndex<CustomIndices>::value) )
+    >
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(CustomIndices& indices)
+    {
+      return coeffRef(internal::customIndices2Array<Index,NumIndices>(indices));
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(Index index)
+    {
+      eigen_assert(index >= 0 && index < size());
+      return coeffRef(index);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()()
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return coeffRef();
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator[](Index index)
+    {
+      // The bracket operator is only for vectors, use the parenthesis operator instead
+      EIGEN_STATIC_ASSERT(NumIndices == 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return coeffRef(index);
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Tensor()
+      : m_storage()
+    {
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Tensor(const Self& other)
+      : m_storage(other.m_storage)
+    {
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index firstDimension, IndexTypes... otherDimensions)
+        : m_storage(firstDimension, otherDimensions...)
+    {
+      // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+#else
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(Index dim1)
+      : m_storage(dim1, array<Index, 1>(dim1))
+    {
+      EIGEN_STATIC_ASSERT(1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index dim1, Index dim2)
+      : m_storage(dim1*dim2, array<Index, 2>(dim1, dim2))
+    {
+      EIGEN_STATIC_ASSERT(2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index dim1, Index dim2, Index dim3)
+      : m_storage(dim1*dim2*dim3, array<Index, 3>(dim1, dim2, dim3))
+    {
+      EIGEN_STATIC_ASSERT(3 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index dim1, Index dim2, Index dim3, Index dim4)
+      : m_storage(dim1*dim2*dim3*dim4, array<Index, 4>(dim1, dim2, dim3, dim4))
+    {
+      EIGEN_STATIC_ASSERT(4 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index dim1, Index dim2, Index dim3, Index dim4, Index dim5)
+      : m_storage(dim1*dim2*dim3*dim4*dim5, array<Index, 5>(dim1, dim2, dim3, dim4, dim5))
+    {
+      EIGEN_STATIC_ASSERT(5 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+#endif
+
+    /** Normal Dimension */
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(const array<Index, NumIndices>& dimensions)
+        : m_storage(internal::array_prod(dimensions), dimensions)
+    {
+      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Tensor(const TensorBase<OtherDerived, ReadOnlyAccessors>& other)
+    {
+      typedef TensorAssignOp<Tensor, const OtherDerived> Assign;
+      Assign assign(*this, other.derived());
+      resize(TensorEvaluator<const Assign, DefaultDevice>(assign, DefaultDevice()).dimensions());
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+    }
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Tensor(const TensorBase<OtherDerived, WriteAccessors>& other)
+    {
+      typedef TensorAssignOp<Tensor, const OtherDerived> Assign;
+      Assign assign(*this, other.derived());
+      resize(TensorEvaluator<const Assign, DefaultDevice>(assign, DefaultDevice()).dimensions());
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Tensor& operator=(const Tensor& other)
+    {
+      typedef TensorAssignOp<Tensor, const Tensor> Assign;
+      Assign assign(*this, other);
+      resize(TensorEvaluator<const Assign, DefaultDevice>(assign, DefaultDevice()).dimensions());
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Tensor& operator=(const OtherDerived& other)
+    {
+      typedef TensorAssignOp<Tensor, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      resize(TensorEvaluator<const Assign, DefaultDevice>(assign, DefaultDevice()).dimensions());
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
+    void resize(Index firstDimension, IndexTypes... otherDimensions)
+    {
+      // The number of dimensions used to resize a tensor must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      resize(array<Index, NumIndices>{{firstDimension, otherDimensions...}});
+    }
+#endif
+
+    /** Normal Dimension */
+    EIGEN_DEVICE_FUNC void resize(const array<Index, NumIndices>& dimensions)
+    {
+      int i;
+      Index size = Index(1);
+      for (i = 0; i < NumIndices; i++) {
+        internal::check_rows_cols_for_overflow<Dynamic>::run(size, dimensions[i]);
+        size *= dimensions[i];
+      }
+      #ifdef EIGEN_INITIALIZE_COEFFS
+        bool size_changed = size != this->size();
+        m_storage.resize(size, dimensions);
+        if(size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+      #else
+        m_storage.resize(size, dimensions);
+      #endif
+    }
+
+    // Why this overload, DSizes is derived from array ??? //
+    EIGEN_DEVICE_FUNC void resize(const DSizes<Index, NumIndices>& dimensions) {
+      array<Index, NumIndices> dims;
+      for (int i = 0; i < NumIndices; ++i) {
+        dims[i] = dimensions[i];
+      }
+      resize(dims);
+    }
+
+    EIGEN_DEVICE_FUNC
+    void resize()
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      // Nothing to do: rank 0 tensors have fixed size
+    }
+
+    /** Custom Dimension */
+#ifdef EIGEN_HAS_SFINAE
+    template<typename CustomDimension,
+             EIGEN_SFINAE_ENABLE_IF( !(isOfNormalIndex<CustomDimension>::value) )
+    >
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(CustomDimension& dimensions)
+    {
+      resize(internal::customIndices2Array<Index,NumIndices>(dimensions));
+    }
+#endif
+
+#ifndef EIGEN_EMULATE_CXX11_META_H
+    template <typename std::ptrdiff_t... Indices>
+    EIGEN_DEVICE_FUNC
+    void resize(const Sizes<Indices...>& dimensions) {
+      array<Index, NumIndices> dims;
+      for (int i = 0; i < NumIndices; ++i) {
+        dims[i] = static_cast<Index>(dimensions[i]);
+      }
+      resize(dims);
+    }
+#else
+    template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5>
+    EIGEN_DEVICE_FUNC
+    void resize(const Sizes<V1, V2, V3, V4, V5>& dimensions) {
+      array<Index, NumIndices> dims;
+      for (int i = 0; i < NumIndices; ++i) {
+        dims[i] = static_cast<Index>(dimensions[i]);
+      }
+      resize(dims);
+    }
+#endif
+
+  protected:
+
+    bool checkIndexRange(const array<Index, NumIndices>& indices) const
+    {
+      using internal::array_apply_and_reduce;
+      using internal::array_zip_and_reduce;
+      using internal::greater_equal_zero_op;
+      using internal::logical_and_op;
+      using internal::lesser_op;
+
+      return
+        // check whether the indices are all >= 0
+        array_apply_and_reduce<logical_and_op, greater_equal_zero_op>(indices) &&
+        // check whether the indices fit in the dimensions
+        array_zip_and_reduce<logical_and_op, lesser_op>(indices, m_storage.dimensions());
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index linearizedIndex(const array<Index, NumIndices>& indices) const
+    {
+      if (Options&RowMajor) {
+        return m_storage.dimensions().IndexOfRowMajor(indices);
+      } else {
+        return m_storage.dimensions().IndexOfColMajor(indices);
+      }
+    }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorArgMax.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorArgMax.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorArgMax.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorArgMax.h
@@ -0,0 +1,299 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Eugene Brevdo <ebrevdo@gmail.com>
+//                    Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_ARG_MAX_H
+#define EIGEN_CXX11_TENSOR_TENSOR_ARG_MAX_H
+
+namespace Eigen {
+namespace internal {
+
+/** \class TensorIndexTuple
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor + Index Tuple class.
+  *
+  *
+  */
+template<typename XprType>
+struct traits<TensorIndexTupleOp<XprType> > : public traits<XprType>
+{
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef Tuple<Index, typename XprTraits::Scalar> Scalar;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename XprType>
+struct eval<TensorIndexTupleOp<XprType>, Eigen::Dense>
+{
+  typedef const TensorIndexTupleOp<XprType>& type;
+};
+
+template<typename XprType>
+struct nested<TensorIndexTupleOp<XprType>, 1,
+              typename eval<TensorIndexTupleOp<XprType> >::type>
+{
+  typedef TensorIndexTupleOp<XprType> type;
+};
+
+}  // end namespace internal
+
+template<typename XprType>
+class TensorIndexTupleOp : public TensorBase<TensorIndexTupleOp<XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorIndexTupleOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename Eigen::internal::nested<TensorIndexTupleOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorIndexTupleOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorIndexTupleOp>::Index Index;
+  typedef Tuple<Index, typename XprType::CoeffReturnType> CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorIndexTupleOp(const XprType& expr)
+      : m_xpr(expr) {}
+
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename XprType::Nested>::type&
+  expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+};
+
+// Eval as rvalue
+template<typename ArgType, typename Device>
+struct TensorEvaluator<const TensorIndexTupleOp<ArgType>, Device>
+{
+  typedef TensorIndexTupleOp<ArgType> XprType;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
+  static const int NumDims = internal::array_size<Dimensions>::value;
+
+  enum {
+    IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/ false,
+    PacketAccess = /*TensorEvaluator<ArgType, Device>::PacketAccess*/ false,
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device) { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {
+    return m_impl.dimensions();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return CoeffReturnType(index, m_impl.coeff(index));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    return m_impl.costPerCoeff(vectorized) + TensorOpCost(0, 0, 1);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ protected:
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+namespace internal {
+
+/** \class TensorTupleIndex
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Converts to Tensor<Tuple<Index, Scalar> > and reduces to Tensor<Index>.
+  *
+  */
+template<typename ReduceOp, typename Dims, typename XprType>
+struct traits<TensorTupleReducerOp<ReduceOp, Dims, XprType> > : public traits<XprType>
+{
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef Index Scalar;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions - array_size<Dims>::value;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename ReduceOp, typename Dims, typename XprType>
+struct eval<TensorTupleReducerOp<ReduceOp, Dims, XprType>, Eigen::Dense>
+{
+  typedef const TensorTupleReducerOp<ReduceOp, Dims, XprType>& type;
+};
+
+template<typename ReduceOp, typename Dims, typename XprType>
+struct nested<TensorTupleReducerOp<ReduceOp, Dims, XprType>, 1,
+              typename eval<TensorTupleReducerOp<ReduceOp, Dims, XprType> >::type>
+{
+  typedef TensorTupleReducerOp<ReduceOp, Dims, XprType> type;
+};
+
+}  // end namespace internal
+
+template<typename ReduceOp, typename Dims, typename XprType>
+class TensorTupleReducerOp : public TensorBase<TensorTupleReducerOp<ReduceOp, Dims, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorTupleReducerOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename Eigen::internal::nested<TensorTupleReducerOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorTupleReducerOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorTupleReducerOp>::Index Index;
+  typedef Index CoeffReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorTupleReducerOp(const XprType& expr,
+                                                          const ReduceOp& reduce_op,
+                                                          const int return_dim,
+                                                          const Dims& reduce_dims)
+      : m_xpr(expr), m_reduce_op(reduce_op), m_return_dim(return_dim), m_reduce_dims(reduce_dims) {}
+
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename XprType::Nested>::type&
+  expression() const { return m_xpr; }
+
+  EIGEN_DEVICE_FUNC
+  const ReduceOp& reduce_op() const { return m_reduce_op; }
+
+  EIGEN_DEVICE_FUNC
+  const Dims& reduce_dims() const { return m_reduce_dims; }
+
+  EIGEN_DEVICE_FUNC
+  int return_dim() const { return m_return_dim; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const ReduceOp m_reduce_op;
+    const int m_return_dim;
+    const Dims m_reduce_dims;
+};
+
+// Eval as rvalue
+template<typename ReduceOp, typename Dims, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Device>
+{
+  typedef TensorTupleReducerOp<ReduceOp, Dims, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename TensorIndexTupleOp<ArgType>::CoeffReturnType TupleType;
+  typedef typename TensorEvaluator<const TensorReductionOp<ReduceOp, Dims, const TensorIndexTupleOp<ArgType> >, Device>::Dimensions Dimensions;
+  typedef typename TensorEvaluator<const TensorIndexTupleOp<ArgType> , Device>::Dimensions InputDimensions;
+  static const int NumDims = internal::array_size<InputDimensions>::value;
+  typedef array<Index, NumDims> StrideDims;
+
+  enum {
+    IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/ false,
+    PacketAccess = /*TensorEvaluator<ArgType, Device>::PacketAccess*/ false,
+    BlockAccess = false,
+    Layout = TensorEvaluator<const TensorReductionOp<ReduceOp, Dims, const TensorIndexTupleOp<ArgType> >, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_orig_impl(op.expression(), device),
+        m_impl(op.expression().index_tuples().reduce(op.reduce_dims(), op.reduce_op()), device),
+        m_return_dim(op.return_dim()) {
+
+    gen_strides(m_orig_impl.dimensions(), m_strides);
+    if (Layout == static_cast<int>(ColMajor)) {
+      const Index total_size = internal::array_prod(m_orig_impl.dimensions());
+      m_stride_mod = (m_return_dim < NumDims - 1) ? m_strides[m_return_dim + 1] : total_size;
+    } else {
+      const Index total_size = internal::array_prod(m_orig_impl.dimensions());
+      m_stride_mod = (m_return_dim > 0) ? m_strides[m_return_dim - 1] : total_size;
+    }
+    m_stride_div = m_strides[m_return_dim];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {
+    return m_impl.dimensions();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+    const TupleType v = m_impl.coeff(index);
+    return (m_return_dim < 0) ? v.first : (v.first % m_stride_mod) / m_stride_div;
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    const double compute_cost = 1.0 +
+        (m_return_dim < 0 ? 0.0 : (TensorOpCost::ModCost<Index>() + TensorOpCost::DivCost<Index>()));
+    return m_orig_impl.costPerCoeff(vectorized) +
+           m_impl.costPerCoeff(vectorized) + TensorOpCost(0, 0, compute_cost);
+  }
+
+ private:
+  EIGEN_DEVICE_FUNC void gen_strides(const InputDimensions& dims, StrideDims& strides) {
+    if (m_return_dim < 0) {
+      return;  // Won't be using the strides.
+    }
+    eigen_assert(m_return_dim < NumDims &&
+                 "Asking to convert index to a dimension outside of the rank");
+
+    // Calculate m_stride_div and m_stride_mod, which are used to
+    // calculate the value of an index w.r.t. the m_return_dim.
+    if (Layout == static_cast<int>(ColMajor)) {
+      strides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        strides[i] = strides[i-1] * dims[i-1];
+      }
+    } else {
+      strides[NumDims-1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        strides[i] = strides[i+1] * dims[i+1];
+      }
+    }
+  }
+
+ protected:
+  TensorEvaluator<const TensorIndexTupleOp<ArgType>, Device> m_orig_impl;
+  TensorEvaluator<const TensorReductionOp<ReduceOp, Dims, const TensorIndexTupleOp<ArgType> >, Device> m_impl;
+  const int m_return_dim;
+  StrideDims m_strides;
+  Index m_stride_mod;
+  Index m_stride_div;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_ARG_MAX_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorAssign.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorAssign.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorAssign.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorAssign.h
@@ -0,0 +1,181 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_ASSIGN_H
+#define EIGEN_CXX11_TENSOR_TENSOR_ASSIGN_H
+
+namespace Eigen {
+
+/** \class TensorAssign
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief The tensor assignment class.
+  *
+  * This class is represents the assignment of the values resulting from the evaluation of
+  * the rhs expression to the memory locations denoted by the lhs expression.
+  */
+namespace internal {
+template<typename LhsXprType, typename RhsXprType>
+struct traits<TensorAssignOp<LhsXprType, RhsXprType> >
+{
+  typedef typename LhsXprType::Scalar Scalar;
+  typedef typename traits<LhsXprType>::StorageKind StorageKind;
+  typedef typename promote_index_type<typename traits<LhsXprType>::Index,
+                                      typename traits<RhsXprType>::Index>::type Index;
+  typedef typename LhsXprType::Nested LhsNested;
+  typedef typename RhsXprType::Nested RhsNested;
+  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef typename remove_reference<RhsNested>::type _RhsNested;
+  static const std::size_t NumDimensions = internal::traits<LhsXprType>::NumDimensions;
+  static const int Layout = internal::traits<LhsXprType>::Layout;
+
+  enum {
+    Flags = 0
+  };
+};
+
+template<typename LhsXprType, typename RhsXprType>
+struct eval<TensorAssignOp<LhsXprType, RhsXprType>, Eigen::Dense>
+{
+  typedef const TensorAssignOp<LhsXprType, RhsXprType>& type;
+};
+
+template<typename LhsXprType, typename RhsXprType>
+struct nested<TensorAssignOp<LhsXprType, RhsXprType>, 1, typename eval<TensorAssignOp<LhsXprType, RhsXprType> >::type>
+{
+  typedef TensorAssignOp<LhsXprType, RhsXprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename LhsXprType, typename RhsXprType>
+class TensorAssignOp : public TensorBase<TensorAssignOp<LhsXprType, RhsXprType> >
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorAssignOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename LhsXprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorAssignOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorAssignOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorAssignOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorAssignOp(LhsXprType& lhs, const RhsXprType& rhs)
+      : m_lhs_xpr(lhs), m_rhs_xpr(rhs) {}
+
+    /** \returns the nested expressions */
+    EIGEN_DEVICE_FUNC
+    typename internal::remove_all<typename LhsXprType::Nested>::type&
+    lhsExpression() const { return *((typename internal::remove_all<typename LhsXprType::Nested>::type*)&m_lhs_xpr); }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename RhsXprType::Nested>::type&
+    rhsExpression() const { return m_rhs_xpr; }
+
+  protected:
+    typename internal::remove_all<typename LhsXprType::Nested>::type& m_lhs_xpr;
+    const typename internal::remove_all<typename RhsXprType::Nested>::type& m_rhs_xpr;
+};
+
+
+template<typename LeftArgType, typename RightArgType, typename Device>
+struct TensorEvaluator<const TensorAssignOp<LeftArgType, RightArgType>, Device>
+{
+  typedef TensorAssignOp<LeftArgType, RightArgType> XprType;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef typename TensorEvaluator<RightArgType, Device>::Dimensions Dimensions;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = TensorEvaluator<LeftArgType, Device>::IsAligned & TensorEvaluator<RightArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<LeftArgType, Device>::PacketAccess & TensorEvaluator<RightArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<LeftArgType, Device>::Layout,
+    RawAccess = TensorEvaluator<LeftArgType, Device>::RawAccess
+  };
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device) :
+      m_leftImpl(op.lhsExpression(), device),
+      m_rightImpl(op.rhsExpression(), device)
+  {
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout)), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  }
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const
+  {
+    // The dimensions of the lhs and the rhs tensors should be equal to prevent
+    // overflows and ensure the result is fully initialized.
+    // TODO: use left impl instead if right impl dimensions are known at compile time.
+    return m_rightImpl.dimensions();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+    eigen_assert(dimensions_match(m_leftImpl.dimensions(), m_rightImpl.dimensions()));
+    m_leftImpl.evalSubExprsIfNeeded(NULL);
+    // If the lhs provides raw access to its storage area (i.e. if m_leftImpl.data() returns a non
+    // null value), attempt to evaluate the rhs expression in place. Returns true iff in place
+    // evaluation isn't supported and the caller still needs to manually assign the values generated
+    // by the rhs to the lhs.
+    return m_rightImpl.evalSubExprsIfNeeded(m_leftImpl.data());
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_leftImpl.cleanup();
+    m_rightImpl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalScalar(Index i) {
+    m_leftImpl.coeffRef(i) = m_rightImpl.coeff(i);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalPacket(Index i) {
+    const int LhsStoreMode = TensorEvaluator<LeftArgType, Device>::IsAligned ? Aligned : Unaligned;
+    const int RhsLoadMode = TensorEvaluator<RightArgType, Device>::IsAligned ? Aligned : Unaligned;
+    m_leftImpl.template writePacket<LhsStoreMode>(i, m_rightImpl.template packet<RhsLoadMode>(i));
+  }
+  EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const
+  {
+    return m_leftImpl.coeff(index);
+  }
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const
+  {
+    return m_leftImpl.template packet<LoadMode>(index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    // We assume that evalPacket or evalScalar is called to perform the
+    // assignment and account for the cost of the write here, but reduce left
+    // cost by one load because we are using m_leftImpl.coeffRef.
+    TensorOpCost left = m_leftImpl.costPerCoeff(vectorized);
+    return m_rightImpl.costPerCoeff(vectorized) +
+           TensorOpCost(
+               numext::maxi(0.0, left.bytes_loaded() - sizeof(CoeffReturnType)),
+               left.bytes_stored(), left.compute_cycles()) +
+           TensorOpCost(0, sizeof(CoeffReturnType), 0, vectorized, PacketSize);
+  }
+
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<LeftArgType, Device>& left_impl() const { return m_leftImpl; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<RightArgType, Device>& right_impl() const { return m_rightImpl; }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return m_leftImpl.data(); }
+
+ private:
+  TensorEvaluator<LeftArgType, Device> m_leftImpl;
+  TensorEvaluator<RightArgType, Device> m_rightImpl;
+};
+
+}
+
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_ASSIGN_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
@@ -0,0 +1,1010 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_BASE_H
+#define EIGEN_CXX11_TENSOR_TENSOR_BASE_H
+
+// clang-format off
+
+namespace Eigen {
+
+/** \class TensorBase
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief The tensor base class.
+  *
+  * This class is the common parent of the Tensor and TensorMap class, thus
+  * making it possible to use either class interchangably in expressions.
+  */
+
+template<typename Derived>
+class TensorBase<Derived, ReadOnlyAccessors>
+{
+  public:
+    typedef internal::traits<Derived> DerivedTraits;
+    typedef typename DerivedTraits::Scalar Scalar;
+    typedef typename DerivedTraits::Index Index;
+    typedef typename internal::remove_const<Scalar>::type CoeffReturnType;
+    static const int NumDimensions = DerivedTraits::NumDimensions;
+
+    // Generic nullary operation support.
+    template <typename CustomNullaryOp> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<CustomNullaryOp, const Derived>
+    nullaryExpr(const CustomNullaryOp& func) const {
+      return TensorCwiseNullaryOp<CustomNullaryOp, const Derived>(derived(), func);
+    }
+
+    // Coefficient-wise nullary operators
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived>
+    constant(const Scalar& value) const {
+      return nullaryExpr(internal::scalar_constant_op<Scalar>(value));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<internal::UniformRandomGenerator<Scalar>, const Derived>
+    random() const {
+      return nullaryExpr(internal::UniformRandomGenerator<Scalar>());
+    }
+    template <typename RandomGenerator> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseNullaryOp<RandomGenerator, const Derived>
+    random(const RandomGenerator& gen = RandomGenerator()) const {
+      return nullaryExpr(gen);
+    }
+
+    // Tensor generation
+    template <typename Generator> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorGeneratorOp<Generator, const Derived>
+    generate(const Generator& generator) const {
+      return TensorGeneratorOp<Generator, const Derived>(derived(), generator);
+    }
+
+    // Generic unary operation support.
+    template <typename CustomUnaryOp> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<CustomUnaryOp, const Derived>
+    unaryExpr(const CustomUnaryOp& func) const {
+      return TensorCwiseUnaryOp<CustomUnaryOp, const Derived>(derived(), func);
+    }
+
+    // Coefficient-wise unary operators
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const Derived>
+    operator-() const {
+      return unaryExpr(internal::scalar_opposite_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sqrt_op<Scalar>, const Derived>
+    sqrt() const {
+      return unaryExpr(internal::scalar_sqrt_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sign_op<Scalar>, const Derived>
+    sign() const {
+      return unaryExpr(internal::scalar_sign_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_rsqrt_op<Scalar>, const Derived>
+    rsqrt() const {
+      return unaryExpr(internal::scalar_rsqrt_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_square_op<Scalar>, const Derived>
+    square() const {
+      return unaryExpr(internal::scalar_square_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_cube_op<Scalar>, const Derived>
+    cube() const {
+      return unaryExpr(internal::scalar_cube_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived>
+    inverse() const {
+      return unaryExpr(internal::scalar_inverse_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_tanh_op<Scalar>, const Derived>
+    tanh() const {
+      return unaryExpr(internal::scalar_tanh_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_lgamma_op<Scalar>, const Derived>
+    lgamma() const {
+      return unaryExpr(internal::scalar_lgamma_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_digamma_op<Scalar>, const Derived>
+    digamma() const {
+      return unaryExpr(internal::scalar_digamma_op<Scalar>());
+    }
+
+    // igamma(a = this, x = other)
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_igamma_op<Scalar>, const Derived, const OtherDerived>
+    igamma(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_igamma_op<Scalar>());
+    }
+
+    // igammac(a = this, x = other)
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_igammac_op<Scalar>, const Derived, const OtherDerived>
+    igammac(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_igammac_op<Scalar>());
+    }
+
+    // zeta(x = this, q = other)
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_zeta_op<Scalar>, const Derived, const OtherDerived>
+    zeta(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_zeta_op<Scalar>());
+    }
+
+    // polygamma(n = this, x = other)
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_polygamma_op<Scalar>, const Derived, const OtherDerived>
+    polygamma(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_polygamma_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_erf_op<Scalar>, const Derived>
+    erf() const {
+      return unaryExpr(internal::scalar_erf_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_erfc_op<Scalar>, const Derived>
+    erfc() const {
+      return unaryExpr(internal::scalar_erfc_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sigmoid_op<Scalar>, const Derived>
+    sigmoid() const {
+      return unaryExpr(internal::scalar_sigmoid_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_exp_op<Scalar>, const Derived>
+    exp() const {
+      return unaryExpr(internal::scalar_exp_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_log_op<Scalar>, const Derived>
+    log() const {
+      return unaryExpr(internal::scalar_log_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_log1p_op<Scalar>, const Derived>
+    log1p() const {
+      return unaryExpr(internal::scalar_log1p_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_abs_op<Scalar>, const Derived>
+    abs() const {
+      return unaryExpr(internal::scalar_abs_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, const Derived>
+    conjugate() const {
+      return unaryExpr(internal::scalar_conjugate_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_pow_op<Scalar,Scalar> >, const Derived>
+    pow(Scalar exponent) const {
+      return unaryExpr(internal::bind2nd_op<internal::scalar_pow_op<Scalar,Scalar> >(exponent));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_real_op<Scalar>, const Derived>
+    real() const {
+      return unaryExpr(internal::scalar_real_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_imag_op<Scalar>, const Derived>
+    imag() const {
+      return unaryExpr(internal::scalar_imag_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_sum_op<Scalar,Scalar> >, const Derived>
+    operator+ (Scalar rhs) const {
+      return unaryExpr(internal::bind2nd_op<internal::scalar_sum_op<Scalar,Scalar> >(rhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE friend
+    const TensorCwiseUnaryOp<internal::bind1st_op<internal::scalar_sum_op<Scalar> >, const Derived>
+    operator+ (Scalar lhs, const Derived& rhs) {
+      return rhs.unaryExpr(internal::bind1st_op<internal::scalar_sum_op<Scalar> >(lhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_difference_op<Scalar,Scalar> >, const Derived>
+    operator- (Scalar rhs) const {
+      EIGEN_STATIC_ASSERT((NumTraits<Scalar>::IsSigned || internal::is_same<Scalar, const std::complex<float> >::value), YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return unaryExpr(internal::bind2nd_op<internal::scalar_difference_op<Scalar,Scalar> >(rhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE friend
+    const TensorCwiseUnaryOp<internal::bind1st_op<internal::scalar_difference_op<Scalar> >, const Derived>
+    operator- (Scalar lhs, const Derived& rhs) {
+      return rhs.unaryExpr(internal::bind1st_op<internal::scalar_difference_op<Scalar> >(lhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_product_op<Scalar,Scalar> >, const Derived>
+    operator* (Scalar rhs) const {
+      return unaryExpr(internal::bind2nd_op<internal::scalar_product_op<Scalar,Scalar> >(rhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE friend
+    const TensorCwiseUnaryOp<internal::bind1st_op<internal::scalar_product_op<Scalar> >, const Derived>
+    operator* (Scalar lhs, const Derived& rhs) {
+      return rhs.unaryExpr(internal::bind1st_op<internal::scalar_product_op<Scalar> >(lhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::bind2nd_op<internal::scalar_quotient_op<Scalar,Scalar> >, const Derived>
+    operator/ (Scalar rhs) const {
+      return unaryExpr(internal::bind2nd_op<internal::scalar_quotient_op<Scalar,Scalar> >(rhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE friend
+    const TensorCwiseUnaryOp<internal::bind1st_op<internal::scalar_quotient_op<Scalar> >, const Derived>
+    operator/ (Scalar lhs, const Derived& rhs) {
+      return rhs.unaryExpr(internal::bind1st_op<internal::scalar_quotient_op<Scalar> >(lhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_mod_op<Scalar>, const Derived>
+    operator% (Scalar rhs) const {
+      EIGEN_STATIC_ASSERT(NumTraits<Scalar>::IsInteger, YOU_MADE_A_PROGRAMMING_MISTAKE_TRY_MOD);
+      return unaryExpr(internal::scalar_mod_op<Scalar>(rhs));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
+    cwiseMax(Scalar threshold) const {
+      return cwiseMax(constant(threshold));
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
+    cwiseMin(Scalar threshold) const {
+      return cwiseMin(constant(threshold));
+    }
+
+    template <typename NewType> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorConversionOp<NewType, const Derived>
+    cast() const {
+      return TensorConversionOp<NewType, const Derived>(derived());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_round_op<Scalar>, const Derived>
+    round() const {
+      return unaryExpr(internal::scalar_round_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_ceil_op<Scalar>, const Derived>
+    ceil() const {
+      return unaryExpr(internal::scalar_ceil_op<Scalar>());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_floor_op<Scalar>, const Derived>
+    floor() const {
+      return unaryExpr(internal::scalar_floor_op<Scalar>());
+    }
+
+    // Generic binary operation support.
+    template <typename CustomBinaryOp, typename OtherDerived> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived>
+    binaryExpr(const OtherDerived& other, const CustomBinaryOp& func) const {
+      return TensorCwiseBinaryOp<CustomBinaryOp, const Derived, const OtherDerived>(derived(), other, func);
+    }
+
+    // Coefficient-wise binary operators.
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_sum_op<Scalar>, const Derived, const OtherDerived>
+    operator+(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_sum_op<Scalar>());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const Derived, const OtherDerived>
+    operator-(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_difference_op<Scalar>());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_product_op<Scalar>, const Derived, const OtherDerived>
+    operator*(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_product_op<Scalar>());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, const Derived, const OtherDerived>
+    operator/(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_quotient_op<Scalar>());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const OtherDerived>
+    cwiseMax(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_max_op<Scalar>());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const OtherDerived>
+    cwiseMin(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_min_op<Scalar>());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived>
+    operator&&(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_boolean_and_op());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>
+    operator||(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_boolean_or_op());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_boolean_xor_op, const Derived, const OtherDerived>
+    operator^(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_boolean_xor_op());
+    }
+
+    // Comparisons and tests.
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LT>, const Derived, const OtherDerived>
+    operator<(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LT>());
+    }
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LE>, const Derived, const OtherDerived>
+    operator<=(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LE>());
+    }
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GT>, const Derived, const OtherDerived>
+    operator>(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GT>());
+    }
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GE>, const Derived, const OtherDerived>
+    operator>=(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GE>());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_EQ>, const Derived, const OtherDerived>
+    operator==(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_EQ>());
+    }
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_NEQ>, const Derived, const OtherDerived>
+    operator!=(const OtherDerived& other) const {
+      return binaryExpr(other.derived(), internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_NEQ>());
+    }
+
+    // comparisons and tests for Scalars
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LT>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
+    operator<(Scalar threshold) const {
+      return operator<(constant(threshold));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LE>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
+    operator<=(Scalar threshold) const {
+      return operator<=(constant(threshold));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GT>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
+    operator>(Scalar threshold) const {
+      return operator>(constant(threshold));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GE>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
+    operator>=(Scalar threshold) const {
+      return operator>=(constant(threshold));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_EQ>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
+    operator==(Scalar threshold) const {
+      return operator==(constant(threshold));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseBinaryOp<internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_NEQ>, const Derived, const TensorCwiseNullaryOp<internal::scalar_constant_op<Scalar>, const Derived> >
+    operator!=(Scalar threshold) const {
+      return operator!=(constant(threshold));
+    }
+
+    // Checks
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_isnan_op<Scalar>, const Derived>
+    (isnan)() const {
+      return unaryExpr(internal::scalar_isnan_op<Scalar>());
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_isinf_op<Scalar>, const Derived>
+    (isinf)() const {
+      return unaryExpr(internal::scalar_isinf_op<Scalar>());
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_isfinite_op<Scalar>, const Derived>
+    (isfinite)() const {
+      return unaryExpr(internal::scalar_isfinite_op<Scalar>());
+    }
+
+    // Coefficient-wise ternary operators.
+    template<typename ThenDerived, typename ElseDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorSelectOp<const Derived, const ThenDerived, const ElseDerived>
+    select(const ThenDerived& thenTensor, const ElseDerived& elseTensor) const {
+      return TensorSelectOp<const Derived, const ThenDerived, const ElseDerived>(derived(), thenTensor.derived(), elseTensor.derived());
+    }
+
+    // Contractions.
+    typedef Eigen::IndexPair<Index> DimensionPair;
+
+    template<typename OtherDerived, typename Dimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorContractionOp<const Dimensions, const Derived, const OtherDerived>
+    contract(const OtherDerived& other, const Dimensions& dims) const {
+      return TensorContractionOp<const Dimensions, const Derived, const OtherDerived>(derived(), other.derived(), dims);
+    }
+
+    // Convolutions.
+    template<typename KernelDerived, typename Dimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorConvolutionOp<const Dimensions, const Derived, const KernelDerived>
+    convolve(const KernelDerived& kernel, const Dimensions& dims) const {
+      return TensorConvolutionOp<const Dimensions, const Derived, const KernelDerived>(derived(), kernel.derived(), dims);
+    }
+
+    // Fourier transforms
+    template <int FFTDataType, int FFTDirection, typename FFT> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection>
+    fft(const FFT& fft) const {
+      return TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection>(derived(), fft);
+    }
+
+    // Scan.
+    typedef TensorScanOp<internal::SumReducer<CoeffReturnType>, const Derived> TensorScanSumOp;
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorScanSumOp
+    cumsum(const Index& axis, bool exclusive = false) const {
+      return TensorScanSumOp(derived(), axis, exclusive);
+    }
+
+    typedef TensorScanOp<internal::ProdReducer<CoeffReturnType>, const Derived> TensorScanProdOp;
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorScanProdOp
+    cumprod(const Index& axis, bool exclusive = false) const {
+      return TensorScanProdOp(derived(), axis, exclusive);
+    }
+
+    template <typename Reducer>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorScanOp<Reducer, const Derived>
+    scan(const Index& axis, const Reducer& reducer, bool exclusive = false) const {
+      return TensorScanOp<Reducer, const Derived>(derived(), axis, exclusive, reducer);
+    }
+
+    // Reductions.
+    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::SumReducer<CoeffReturnType>, const Dims, const Derived>
+    sum(const Dims& dims) const {
+      return TensorReductionOp<internal::SumReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::SumReducer<CoeffReturnType>());
+    }
+
+    const TensorReductionOp<internal::SumReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>
+    sum() const {
+      DimensionList<Index, NumDimensions> in_dims;
+      return TensorReductionOp<internal::SumReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::SumReducer<CoeffReturnType>());
+    }
+
+    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const Dims, const Derived>
+    mean(const Dims& dims) const {
+      return TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MeanReducer<CoeffReturnType>());
+    }
+
+    const TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>
+    mean() const {
+      DimensionList<Index, NumDimensions> in_dims;
+      return TensorReductionOp<internal::MeanReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MeanReducer<CoeffReturnType>());
+    }
+
+    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const Dims, const Derived>
+    prod(const Dims& dims) const {
+      return TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::ProdReducer<CoeffReturnType>());
+    }
+
+    const TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>
+    prod() const {
+      DimensionList<Index, NumDimensions> in_dims;
+      return TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::ProdReducer<CoeffReturnType>());
+    }
+
+    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const Dims, const Derived>
+    maximum(const Dims& dims) const {
+      return TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MaxReducer<CoeffReturnType>());
+    }
+
+    const TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>
+    maximum() const {
+      DimensionList<Index, NumDimensions> in_dims;
+      return TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MaxReducer<CoeffReturnType>());
+    }
+
+    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::MinReducer<CoeffReturnType>, const Dims, const Derived>
+    minimum(const Dims& dims) const {
+      return TensorReductionOp<internal::MinReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MinReducer<CoeffReturnType>());
+    }
+
+    const TensorReductionOp<internal::MinReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>
+    minimum() const {
+      DimensionList<Index, NumDimensions> in_dims;
+      return TensorReductionOp<internal::MinReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MinReducer<CoeffReturnType>());
+    }
+
+    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::AndReducer, const Dims, const TensorConversionOp<bool, const Derived> >
+    all(const Dims& dims) const {
+      return cast<bool>().reduce(dims, internal::AndReducer());
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::AndReducer, const DimensionList<Index, NumDimensions>, const TensorConversionOp<bool, const Derived> >
+    all() const {
+      DimensionList<Index, NumDimensions> in_dims;
+      return cast<bool>().reduce(in_dims, internal::AndReducer());
+    }
+
+    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::OrReducer, const Dims, const TensorConversionOp<bool, const Derived> >
+    any(const Dims& dims) const {
+      return cast<bool>().reduce(dims, internal::OrReducer());
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::OrReducer, const DimensionList<Index, NumDimensions>, const TensorConversionOp<bool, const Derived> >
+    any() const {
+      DimensionList<Index, NumDimensions> in_dims;
+      return cast<bool>().reduce(in_dims, internal::OrReducer());
+    }
+
+   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorTupleReducerOp<
+      internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >,
+      const array<Index, NumDimensions>, const Derived>
+    argmax() const {
+      array<Index, NumDimensions> in_dims;
+      for (int d = 0; d < NumDimensions; ++d) in_dims[d] = d;
+      return TensorTupleReducerOp<
+        internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >,
+        const array<Index, NumDimensions>,
+        const Derived>(derived(), internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >(), -1, in_dims);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorTupleReducerOp<
+      internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >,
+      const array<Index, NumDimensions>, const Derived>
+    argmin() const {
+      array<Index, NumDimensions> in_dims;
+      for (int d = 0; d < NumDimensions; ++d) in_dims[d] = d;
+      return TensorTupleReducerOp<
+        internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >,
+        const array<Index, NumDimensions>,
+        const Derived>(derived(), internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >(), -1, in_dims);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorTupleReducerOp<
+      internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >,
+      const array<Index, 1>, const Derived>
+    argmax(const int return_dim) const {
+      array<Index, 1> in_dims;
+      in_dims[0] = return_dim;
+      return TensorTupleReducerOp<
+        internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >,
+        const array<Index, 1>,
+        const Derived>(derived(), internal::ArgMaxTupleReducer<Tuple<Index, CoeffReturnType> >(), return_dim, in_dims);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorTupleReducerOp<
+      internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >,
+      const array<Index, 1>, const Derived>
+    argmin(const int return_dim) const {
+      array<Index, 1> in_dims;
+      in_dims[0] = return_dim;
+      return TensorTupleReducerOp<
+        internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >,
+        const array<Index, 1>,
+        const Derived>(derived(), internal::ArgMinTupleReducer<Tuple<Index, CoeffReturnType> >(), return_dim, in_dims);
+    }
+
+    template <typename Reducer, typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<Reducer, const Dims, const Derived>
+    reduce(const Dims& dims, const Reducer& reducer) const {
+      return TensorReductionOp<Reducer, const Dims, const Derived>(derived(), dims, reducer);
+    }
+
+    template <typename Broadcast> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorBroadcastingOp<const Broadcast, const Derived>
+    broadcast(const Broadcast& broadcast) const {
+      return TensorBroadcastingOp<const Broadcast, const Derived>(derived(), broadcast);
+    }
+
+    template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorConcatenationOp<Axis, const Derived, const OtherDerived>
+    concatenate(const OtherDerived& other, Axis axis) const {
+      return TensorConcatenationOp<Axis, const Derived, const OtherDerived>(derived(), other.derived(), axis);
+    }
+
+    template <typename PatchDims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorPatchOp<const PatchDims, const Derived>
+    extract_patches(const PatchDims& patch_dims) const {
+      return TensorPatchOp<const PatchDims, const Derived>(derived(), patch_dims);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorImagePatchOp<Dynamic, Dynamic, const Derived>
+    extract_image_patches(const Index patch_rows = 1, const Index patch_cols = 1,
+                          const Index row_stride = 1, const Index col_stride = 1,
+                          const Index in_row_stride = 1, const Index in_col_stride = 1,
+                          const PaddingType padding_type = PADDING_SAME, const Scalar padding_value = Scalar(0)) const {
+      return TensorImagePatchOp<Dynamic, Dynamic, const Derived>(derived(), patch_rows, patch_cols, row_stride, col_stride,
+                                                                 in_row_stride, in_col_stride, 1, 1, padding_type, padding_value);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorImagePatchOp<Dynamic, Dynamic, const Derived>
+    extract_image_patches(const Index patch_rows, const Index patch_cols,
+                          const Index row_stride, const Index col_stride,
+                          const Index in_row_stride, const Index in_col_stride,
+                          const Index row_inflate_stride, const Index col_inflate_stride,
+                          const Index padding_top, const Index padding_bottom,
+                          const Index padding_left,const Index padding_right,
+                          const Scalar padding_value) const {
+      return TensorImagePatchOp<Dynamic, Dynamic, const Derived>(derived(), patch_rows, patch_cols, row_stride, col_stride,
+                                                                 in_row_stride, in_col_stride, row_inflate_stride, col_inflate_stride,
+                                                                 padding_top, padding_bottom, padding_left, padding_right, padding_value);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorVolumePatchOp<Dynamic, Dynamic, Dynamic, const Derived>
+    extract_volume_patches(const Index patch_planes, const Index patch_rows, const Index patch_cols,
+                           const Index plane_stride = 1, const Index row_stride = 1, const Index col_stride = 1,
+                           const PaddingType padding_type = PADDING_SAME, const Scalar padding_value = Scalar(0)) const {
+      return TensorVolumePatchOp<Dynamic, Dynamic, Dynamic, const Derived>(derived(), patch_planes, patch_rows, patch_cols, plane_stride, row_stride, col_stride, 1, 1, 1, 1, 1, 1, padding_type, padding_value);
+    }
+
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorVolumePatchOp<Dynamic, Dynamic, Dynamic, const Derived>
+    extract_volume_patches(const Index patch_planes, const Index patch_rows, const Index patch_cols,
+                           const Index plane_stride, const Index row_stride, const Index col_stride,
+                           const Index plane_inflate_stride, const Index row_inflate_stride, const Index col_inflate_stride,
+                           const Index padding_top_z, const Index padding_bottom_z,
+                           const Index padding_top, const Index padding_bottom,
+                           const Index padding_left, const Index padding_right, const Scalar padding_value = Scalar(0)) const {
+      return TensorVolumePatchOp<Dynamic, Dynamic, Dynamic, const Derived>(derived(), patch_planes, patch_rows, patch_cols, plane_stride, row_stride, col_stride, 1, 1, 1, plane_inflate_stride, row_inflate_stride, col_inflate_stride, padding_top_z, padding_bottom_z, padding_top, padding_bottom, padding_left, padding_right, padding_value);
+    }
+
+    // Morphing operators.
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorLayoutSwapOp<const Derived>
+    swap_layout() const {
+      return TensorLayoutSwapOp<const Derived>(derived());
+    }
+    template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReshapingOp<const NewDimensions, const Derived>
+    reshape(const NewDimensions& newDimensions) const {
+      return TensorReshapingOp<const NewDimensions, const Derived>(derived(), newDimensions);
+    }
+    template <typename StartIndices, typename Sizes> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorSlicingOp<const StartIndices, const Sizes, const Derived>
+    slice(const StartIndices& startIndices, const Sizes& sizes) const {
+      return TensorSlicingOp<const StartIndices, const Sizes, const Derived>(derived(), startIndices, sizes);
+    }
+    template <typename StartIndices, typename StopIndices, typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, const Derived>
+    stridedSlice(const StartIndices& startIndices, const StopIndices& stopIndices, const Strides& strides) const {
+      return TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides,
+                                const Derived>(derived(), startIndices, stopIndices, strides);
+    }
+    template <Index DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorChippingOp<DimId, const Derived>
+    chip(const Index offset) const {
+      return TensorChippingOp<DimId, const Derived>(derived(), offset, DimId);
+    }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorChippingOp<Dynamic, const Derived>
+    chip(const Index offset, const Index dim) const {
+      return TensorChippingOp<Dynamic, const Derived>(derived(), offset, dim);
+    }
+    template <typename ReverseDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReverseOp<const ReverseDimensions, const Derived>
+    reverse(const ReverseDimensions& rev) const {
+      return TensorReverseOp<const ReverseDimensions, const Derived>(derived(), rev);
+    }
+    template <typename PaddingDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorPaddingOp<const PaddingDimensions, const Derived>
+    pad(const PaddingDimensions& padding) const {
+      return TensorPaddingOp<const PaddingDimensions, const Derived>(derived(), padding, internal::scalar_cast_op<int, Scalar>()(0));
+    }
+    template <typename PaddingDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorPaddingOp<const PaddingDimensions, const Derived>
+    pad(const PaddingDimensions& padding, const Scalar padding_value) const {
+      return TensorPaddingOp<const PaddingDimensions, const Derived>(derived(), padding, padding_value);
+    }
+    template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorShufflingOp<const Shuffle, const Derived>
+    shuffle(const Shuffle& shuffle) const {
+      return TensorShufflingOp<const Shuffle, const Derived>(derived(), shuffle);
+    }
+    template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorStridingOp<const Strides, const Derived>
+    stride(const Strides& strides) const {
+      return TensorStridingOp<const Strides, const Derived>(derived(), strides);
+    }
+    template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorInflationOp<const Strides, const Derived>
+    inflate(const Strides& strides) const {
+      return TensorInflationOp<const Strides, const Derived>(derived(), strides);
+    }
+
+    // Returns a tensor containing index/value tuples
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorIndexTupleOp<const Derived>
+    index_tuples() const {
+      return TensorIndexTupleOp<const Derived>(derived());
+    }
+
+    // Support for custom unary and binary operations
+    template <typename CustomUnaryFunc>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCustomUnaryOp<const CustomUnaryFunc, const Derived> customOp(const CustomUnaryFunc& op) const {
+      return TensorCustomUnaryOp<const CustomUnaryFunc, const Derived>(derived(), op);
+    }
+    template <typename OtherDerived, typename CustomBinaryFunc>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorCustomBinaryOp<const CustomBinaryFunc, const Derived, const OtherDerived> customOp(const OtherDerived& other, const CustomBinaryFunc& op) const {
+      return TensorCustomBinaryOp<const CustomBinaryFunc, const Derived, const OtherDerived>(derived(), other, op);
+    }
+
+    // Force the evaluation of the expression.
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorForcedEvalOp<const Derived> eval() const {
+      return TensorForcedEvalOp<const Derived>(derived());
+    }
+
+  protected:
+    template <typename Scalar, int NumIndices, int Options, typename IndexType> friend class Tensor;
+    template <typename Scalar, typename Dimensions, int Option, typename IndexTypes> friend class TensorFixedSize;
+    template <typename OtherDerived, int AccessLevel> friend class TensorBase;
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); }
+};
+
+template<typename Derived, int AccessLevel = internal::accessors_level<Derived>::value>
+class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> {
+ public:
+    typedef internal::traits<Derived> DerivedTraits;
+    typedef typename DerivedTraits::Scalar Scalar;
+    typedef typename DerivedTraits::Index Index;
+    typedef Scalar CoeffReturnType;
+    static const int NumDimensions = DerivedTraits::NumDimensions;
+
+    template <typename Scalar, int NumIndices, int Options, typename IndexType> friend class Tensor;
+    template <typename Scalar, typename Dimensions, int Option, typename IndexTypes> friend class TensorFixedSize;
+    template <typename OtherDerived, int OtherAccessLevel> friend class TensorBase;
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Derived& setZero() {
+      return setConstant(Scalar(0));
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Derived& setConstant(const Scalar& val) {
+      return derived() = this->constant(val);
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Derived& setRandom() {
+      return derived() = this->random();
+    }
+    template <typename RandomGenerator> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Derived& setRandom() {
+      return derived() = this->template random<RandomGenerator>();
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Derived& setValues(
+        const typename internal::Initializer<Derived, NumDimensions>::InitList& vals) {
+      TensorEvaluator<Derived, DefaultDevice> eval(derived(), DefaultDevice());
+      internal::initialize_tensor<Derived, NumDimensions>(eval, vals);
+      return derived();
+    }
+#endif  // EIGEN_HAS_VARIADIC_TEMPLATES
+
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator+=(const OtherDerived& other) {
+      return derived() = derived() + other.derived();
+    }
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator-=(const OtherDerived& other) {
+      return derived() = derived() - other.derived();
+    }
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator*=(const OtherDerived& other) {
+      return derived() = derived() * other.derived();
+    }
+    template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Derived& operator/=(const OtherDerived& other) {
+      return derived() = derived() / other.derived();
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorLayoutSwapOp<const Derived>
+    swap_layout() const {
+      return TensorLayoutSwapOp<const Derived>(derived());
+    }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorLayoutSwapOp<Derived>
+    swap_layout() {
+      return TensorLayoutSwapOp<Derived>(derived());
+    }
+
+    template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorConcatenationOp<const Axis, const Derived, const OtherDerived>
+    concatenate(const OtherDerived& other, const Axis& axis) const {
+      return TensorConcatenationOp<const Axis, const Derived, const OtherDerived>(derived(), other, axis);
+    }
+    template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorConcatenationOp<const Axis, Derived, OtherDerived>
+    concatenate(const OtherDerived& other, const Axis& axis) {
+      return TensorConcatenationOp<const Axis, Derived, OtherDerived>(derived(), other, axis);
+    }
+
+    template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReshapingOp<const NewDimensions, const Derived>
+    reshape(const NewDimensions& newDimensions) const {
+      return TensorReshapingOp<const NewDimensions, const Derived>(derived(), newDimensions);
+    }
+    template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorReshapingOp<const NewDimensions, Derived>
+    reshape(const NewDimensions& newDimensions) {
+      return TensorReshapingOp<const NewDimensions, Derived>(derived(), newDimensions);
+    }
+
+    template <typename StartIndices, typename Sizes> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorSlicingOp<const StartIndices, const Sizes, const Derived>
+    slice(const StartIndices& startIndices, const Sizes& sizes) const {
+      return TensorSlicingOp<const StartIndices, const Sizes, const Derived>(derived(), startIndices, sizes);
+    }
+    template <typename StartIndices, typename Sizes> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorSlicingOp<const StartIndices, const Sizes, Derived>
+    slice(const StartIndices& startIndices, const Sizes& sizes) {
+      return TensorSlicingOp<const StartIndices, const Sizes, Derived>(derived(), startIndices, sizes);
+    }
+
+    template <typename StartIndices, typename StopIndices, typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, const Derived>
+    stridedSlice(const StartIndices& startIndices, const StopIndices& stopIndices, const Strides& strides) const {
+      return TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides,
+                                const Derived>(derived(), startIndices, stopIndices, strides);
+    }
+    template <typename StartIndices, typename StopIndices, typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides, Derived>
+    stridedSlice(const StartIndices& startIndices, const StopIndices& stopIndices, const Strides& strides) {
+      return TensorStridingSlicingOp<const StartIndices, const StopIndices, const Strides,
+                                Derived>(derived(), startIndices, stopIndices, strides);
+    }
+
+    template <DenseIndex DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorChippingOp<DimId, const Derived>
+    chip(const Index offset) const {
+      return TensorChippingOp<DimId, const Derived>(derived(), offset, DimId);
+    }
+    template <Index DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorChippingOp<DimId, Derived>
+    chip(const Index offset) {
+      return TensorChippingOp<DimId, Derived>(derived(), offset, DimId);
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorChippingOp<Dynamic, const Derived>
+    chip(const Index offset, const Index dim) const {
+      return TensorChippingOp<Dynamic, const Derived>(derived(), offset, dim);
+    }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorChippingOp<Dynamic, Derived>
+    chip(const Index offset, const Index dim) {
+      return TensorChippingOp<Dynamic, Derived>(derived(), offset, dim);
+    }
+
+    template <typename ReverseDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReverseOp<const ReverseDimensions, const Derived>
+    reverse(const ReverseDimensions& rev) const {
+      return TensorReverseOp<const ReverseDimensions, const Derived>(derived(), rev);
+    }
+    template <typename ReverseDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorReverseOp<const ReverseDimensions, Derived>
+    reverse(const ReverseDimensions& rev) {
+      return TensorReverseOp<const ReverseDimensions, Derived>(derived(), rev);
+    }
+
+    template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorShufflingOp<const Shuffle, const Derived>
+    shuffle(const Shuffle& shuffle) const {
+      return TensorShufflingOp<const Shuffle, const Derived>(derived(), shuffle);
+    }
+    template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorShufflingOp<const Shuffle, Derived>
+    shuffle(const Shuffle& shuffle) {
+      return TensorShufflingOp<const Shuffle, Derived>(derived(), shuffle);
+    }
+
+    template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorStridingOp<const Strides, const Derived>
+    stride(const Strides& strides) const {
+      return TensorStridingOp<const Strides, const Derived>(derived(), strides);
+    }
+    template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorStridingOp<const Strides, Derived>
+    stride(const Strides& strides) {
+      return TensorStridingOp<const Strides, Derived>(derived(), strides);
+    }
+
+    // Select the device on which to evaluate the expression.
+    template <typename DeviceType>
+    TensorDevice<Derived, DeviceType> device(const DeviceType& device) {
+      return TensorDevice<Derived, DeviceType>(device, derived());
+    }
+
+ protected:
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Derived& derived() { return *static_cast<Derived*>(this); }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_BASE_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
@@ -0,0 +1,392 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_BROADCASTING_H
+#define EIGEN_CXX11_TENSOR_TENSOR_BROADCASTING_H
+
+namespace Eigen {
+
+/** \class TensorBroadcasting
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor broadcasting class.
+  *
+  *
+  */
+namespace internal {
+template<typename Broadcast, typename XprType>
+struct traits<TensorBroadcastingOp<Broadcast, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename Broadcast, typename XprType>
+struct eval<TensorBroadcastingOp<Broadcast, XprType>, Eigen::Dense>
+{
+  typedef const TensorBroadcastingOp<Broadcast, XprType>& type;
+};
+
+template<typename Broadcast, typename XprType>
+struct nested<TensorBroadcastingOp<Broadcast, XprType>, 1, typename eval<TensorBroadcastingOp<Broadcast, XprType> >::type>
+{
+  typedef TensorBroadcastingOp<Broadcast, XprType> type;
+};
+
+template <typename Dims>
+struct is_input_scalar {
+  static const bool value = false;
+};
+template <>
+struct is_input_scalar<Sizes<> > {
+  static const bool value = true;
+};
+#ifndef EIGEN_EMULATE_CXX11_META_H
+template <typename std::size_t... Indices>
+struct is_input_scalar<Sizes<Indices...> > {
+  static const bool value = (Sizes<Indices...>::total_size == 1);
+};
+#endif
+
+}  // end namespace internal
+
+
+
+template<typename Broadcast, typename XprType>
+class TensorBroadcastingOp : public TensorBase<TensorBroadcastingOp<Broadcast, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorBroadcastingOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorBroadcastingOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorBroadcastingOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorBroadcastingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBroadcastingOp(const XprType& expr, const Broadcast& broadcast)
+      : m_xpr(expr), m_broadcast(broadcast) {}
+
+    EIGEN_DEVICE_FUNC
+    const Broadcast& broadcast() const { return m_broadcast; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const Broadcast m_broadcast;
+};
+
+
+// Eval as rvalue
+template<typename Broadcast, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
+{
+  typedef TensorBroadcastingOp<Broadcast, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions InputDimensions;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = true,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+    : m_broadcast(op.broadcast()),m_impl(op.expression(), device)
+  {
+    // The broadcasting op doesn't change the rank of the tensor. One can't broadcast a scalar
+    // and store the result in a scalar. Instead one should reshape the scalar into a a N-D
+    // tensor with N >= 1 of 1 element first and then broadcast.
+    EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    const InputDimensions& input_dims = m_impl.dimensions();
+    const Broadcast& broadcast = op.broadcast();
+    for (int i = 0; i < NumDims; ++i) {
+      eigen_assert(input_dims[i] > 0);
+      m_dimensions[i] = input_dims[i] * broadcast[i];
+    }
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_inputStrides[0] = 1;
+      m_outputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
+        m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
+      }
+    } else {
+      m_inputStrides[NumDims-1] = 1;
+      m_outputStrides[NumDims-1] = 1;
+      for (int i = NumDims-2; i >= 0; --i) {
+        m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
+        m_outputStrides[i] = m_outputStrides[i+1] * m_dimensions[i+1];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE CoeffReturnType coeff(Index index) const
+  {
+    if (internal::is_input_scalar<typename internal::remove_all<InputDimensions>::type>::value) {
+      return m_impl.coeff(0);
+    }
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      return coeffColMajor(index);
+    } else {
+      return coeffRowMajor(index);
+    }
+  }
+
+  // TODO: attempt to speed this up. The integer divisions and modulo are slow
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeffColMajor(Index index) const
+  {
+    Index inputIndex = 0;
+    for (int i = NumDims - 1; i > 0; --i) {
+      const Index idx = index / m_outputStrides[i];
+      if (internal::index_statically_eq<Broadcast>(i, 1)) {
+        eigen_assert(idx < m_impl.dimensions()[i]);
+        inputIndex += idx * m_inputStrides[i];
+      } else {
+        if (internal::index_statically_eq<InputDimensions>(i, 1)) {
+          eigen_assert(idx % m_impl.dimensions()[i] == 0);
+        } else {
+          inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i];
+        }
+      }
+      index -= idx * m_outputStrides[i];
+    }
+    if (internal::index_statically_eq<Broadcast>(0, 1)) {
+      eigen_assert(index < m_impl.dimensions()[0]);
+      inputIndex += index;
+    } else {
+      if (internal::index_statically_eq<InputDimensions>(0, 1)) {
+        eigen_assert(index % m_impl.dimensions()[0] == 0);
+      } else {
+        inputIndex += (index % m_impl.dimensions()[0]);
+      }
+    }
+    return m_impl.coeff(inputIndex);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeffRowMajor(Index index) const
+  {
+    Index inputIndex = 0;
+    for (int i = 0; i < NumDims - 1; ++i) {
+      const Index idx = index / m_outputStrides[i];
+      if (internal::index_statically_eq<Broadcast>(i, 1)) {
+        eigen_assert(idx < m_impl.dimensions()[i]);
+        inputIndex += idx * m_inputStrides[i];
+      } else {
+        if (internal::index_statically_eq<InputDimensions>(i, 1)) {
+          eigen_assert(idx % m_impl.dimensions()[i] == 0);
+        } else {
+          inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i];
+        }
+      }
+      index -= idx * m_outputStrides[i];
+    }
+    if (internal::index_statically_eq<Broadcast>(NumDims-1, 1)) {
+      eigen_assert(index < m_impl.dimensions()[NumDims-1]);
+      inputIndex += index;
+    } else {
+      if (internal::index_statically_eq<InputDimensions>(NumDims-1, 1)) {
+        eigen_assert(index % m_impl.dimensions()[NumDims-1] == 0);
+      } else {
+        inputIndex += (index % m_impl.dimensions()[NumDims-1]);
+      }
+    }
+    return m_impl.coeff(inputIndex);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketReturnType packet(Index index) const
+  {
+    if (internal::is_input_scalar<typename internal::remove_all<InputDimensions>::type>::value) {
+      return internal::pset1<PacketReturnType>(m_impl.coeff(0));
+    }
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      return packetColMajor<LoadMode>(index);
+    } else {
+      return packetRowMajor<LoadMode>(index);
+    }
+  }
+
+  // Ignore the LoadMode and always use unaligned loads since we can't guarantee
+  // the alignment at compile time.
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetColMajor(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    const Index originalIndex = index;
+
+    Index inputIndex = 0;
+    for (int i = NumDims - 1; i > 0; --i) {
+      const Index idx = index / m_outputStrides[i];
+      if (internal::index_statically_eq<Broadcast>(i, 1)) {
+        eigen_assert(idx < m_impl.dimensions()[i]);
+        inputIndex += idx * m_inputStrides[i];
+      } else {
+        if (internal::index_statically_eq<InputDimensions>(i, 1)) {
+          eigen_assert(idx % m_impl.dimensions()[i] == 0);
+        } else {
+          inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i];
+        }
+      }
+      index -= idx * m_outputStrides[i];
+    }
+    Index innermostLoc;
+    if (internal::index_statically_eq<Broadcast>(0, 1)) {
+      eigen_assert(index < m_impl.dimensions()[0]);
+      innermostLoc = index;
+    } else {
+      if (internal::index_statically_eq<InputDimensions>(0, 1)) {
+        eigen_assert(index % m_impl.dimensions()[0] == 0);
+        innermostLoc = 0;
+      } else {
+        innermostLoc = index % m_impl.dimensions()[0];
+      }
+    }
+    inputIndex += innermostLoc;
+
+    // Todo: this could be extended to the second dimension if we're not
+    // broadcasting alongside the first dimension, and so on.
+    if (innermostLoc + PacketSize <= m_impl.dimensions()[0]) {
+      return m_impl.template packet<Unaligned>(inputIndex);
+    } else {
+      EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+      values[0] = m_impl.coeff(inputIndex);
+      for (int i = 1; i < PacketSize; ++i) {
+        values[i] = coeffColMajor(originalIndex+i);
+      }
+      PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+      return rslt;
+    }
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetRowMajor(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    const Index originalIndex = index;
+
+    Index inputIndex = 0;
+    for (int i = 0; i < NumDims - 1; ++i) {
+      const Index idx = index / m_outputStrides[i];
+      if (internal::index_statically_eq<Broadcast>(i, 1)) {
+        eigen_assert(idx < m_impl.dimensions()[i]);
+        inputIndex += idx * m_inputStrides[i];
+      } else {
+        if (internal::index_statically_eq<InputDimensions>(i, 1)) {
+          eigen_assert(idx % m_impl.dimensions()[i] == 0);
+        } else {
+          inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i];
+        }
+      }
+      index -= idx * m_outputStrides[i];
+    }
+    Index innermostLoc;
+    if (internal::index_statically_eq<Broadcast>(NumDims-1, 1)) {
+      eigen_assert(index < m_impl.dimensions()[NumDims-1]);
+      innermostLoc = index;
+    } else {
+      if (internal::index_statically_eq<InputDimensions>(NumDims-1, 1)) {
+        eigen_assert(index % m_impl.dimensions()[NumDims-1] == 0);
+        innermostLoc = 0;
+      } else {
+        innermostLoc = index % m_impl.dimensions()[NumDims-1];
+      }
+    }
+    inputIndex += innermostLoc;
+
+    // Todo: this could be extended to the second dimension if we're not
+    // broadcasting alongside the first dimension, and so on.
+    if (innermostLoc + PacketSize <= m_impl.dimensions()[NumDims-1]) {
+      return m_impl.template packet<Unaligned>(inputIndex);
+    } else {
+      EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+      values[0] = m_impl.coeff(inputIndex);
+      for (int i = 1; i < PacketSize; ++i) {
+        values[i] = coeffRowMajor(originalIndex+i);
+      }
+      PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+      return rslt;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    double compute_cost = TensorOpCost::AddCost<Index>();
+    if (NumDims > 0) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        compute_cost += TensorOpCost::DivCost<Index>();
+        if (internal::index_statically_eq<Broadcast>(i, 1)) {
+          compute_cost +=
+              TensorOpCost::MulCost<Index>() + TensorOpCost::AddCost<Index>();
+        } else {
+          if (!internal::index_statically_eq<InputDimensions>(i, 1)) {
+            compute_cost += TensorOpCost::MulCost<Index>() +
+                            TensorOpCost::ModCost<Index>() +
+                            TensorOpCost::AddCost<Index>();
+          }
+        }
+        compute_cost +=
+            TensorOpCost::MulCost<Index>() + TensorOpCost::AddCost<Index>();
+      }
+    }
+    return m_impl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+  const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+
+  Broadcast functor() const { return m_broadcast; }
+
+ protected:
+  const Broadcast m_broadcast;
+  Dimensions m_dimensions;
+  array<Index, NumDims> m_outputStrides;
+  array<Index, NumDims> m_inputStrides;
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_BROADCASTING_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
@@ -0,0 +1,384 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CHIPPING_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CHIPPING_H
+
+namespace Eigen {
+
+/** \class TensorKChippingReshaping
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief A chip is a thin slice, corresponding to a column or a row in a 2-d tensor.
+  *
+  *
+  */
+
+namespace internal {
+template<DenseIndex DimId, typename XprType>
+struct traits<TensorChippingOp<DimId, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions - 1;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<DenseIndex DimId, typename XprType>
+struct eval<TensorChippingOp<DimId, XprType>, Eigen::Dense>
+{
+  typedef const TensorChippingOp<DimId, XprType>& type;
+};
+
+template<DenseIndex DimId, typename XprType>
+struct nested<TensorChippingOp<DimId, XprType>, 1, typename eval<TensorChippingOp<DimId, XprType> >::type>
+{
+  typedef TensorChippingOp<DimId, XprType> type;
+};
+
+template <DenseIndex DimId>
+struct DimensionId
+{
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DimensionId(DenseIndex dim) {
+    eigen_assert(dim == DimId);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex actualDim() const {
+    return DimId;
+  }
+};
+template <>
+struct DimensionId<Dynamic>
+{
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DimensionId(DenseIndex dim) : actual_dim(dim) {
+    eigen_assert(dim >= 0);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex actualDim() const {
+    return actual_dim;
+  }
+ private:
+  const DenseIndex actual_dim;
+};
+
+
+}  // end namespace internal
+
+
+
+template<DenseIndex DimId, typename XprType>
+class TensorChippingOp : public TensorBase<TensorChippingOp<DimId, XprType> >
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorChippingOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorChippingOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorChippingOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorChippingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorChippingOp(const XprType& expr, const Index offset, const Index dim)
+      : m_xpr(expr), m_offset(offset), m_dim(dim) {
+  }
+
+  EIGEN_DEVICE_FUNC
+  const Index offset() const { return m_offset; }
+  EIGEN_DEVICE_FUNC
+  const Index dim() const { return m_dim.actualDim(); }
+
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename XprType::Nested>::type&
+  expression() const { return m_xpr; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE TensorChippingOp& operator = (const TensorChippingOp& other)
+  {
+    typedef TensorAssignOp<TensorChippingOp, const TensorChippingOp> Assign;
+    Assign assign(*this, other);
+    internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+    return *this;
+  }
+
+  template<typename OtherDerived>
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE TensorChippingOp& operator = (const OtherDerived& other)
+  {
+    typedef TensorAssignOp<TensorChippingOp, const OtherDerived> Assign;
+    Assign assign(*this, other);
+    internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+    return *this;
+  }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const Index m_offset;
+    const internal::DimensionId<DimId> m_dim;
+};
+
+
+// Eval as rvalue
+template<DenseIndex DimId, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
+{
+  typedef TensorChippingOp<DimId, ArgType> XprType;
+  static const int NumInputDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  static const int NumDims = NumInputDims-1;
+  typedef typename XprType::Index Index;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+
+  enum {
+    // Alignment can't be guaranteed at compile time since it depends on the
+    // slice offsets.
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_dim(op.dim()), m_device(device)
+  {
+    EIGEN_STATIC_ASSERT((NumInputDims >= 1), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    eigen_assert(NumInputDims > m_dim.actualDim());
+
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    eigen_assert(op.offset() < input_dims[m_dim.actualDim()]);
+
+    int j = 0;
+    for (int i = 0; i < NumInputDims; ++i) {
+      if (i != m_dim.actualDim()) {
+        m_dimensions[j] = input_dims[i];
+        ++j;
+      }
+    }
+
+    m_stride = 1;
+    m_inputStride = 1;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = 0; i < m_dim.actualDim(); ++i) {
+        m_stride *= input_dims[i];
+        m_inputStride *= input_dims[i];
+      }
+    } else {
+      for (int i = NumInputDims-1; i > m_dim.actualDim(); --i) {
+        m_stride *= input_dims[i];
+        m_inputStride *= input_dims[i];
+      }
+    }
+    m_inputStride *= input_dims[m_dim.actualDim()];
+    m_inputOffset = m_stride * op.offset();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_impl.coeff(srcCoeff(index));
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == 0) ||
+	(static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == NumInputDims-1)) {
+      // m_stride is equal to 1, so let's avoid the integer division.
+      eigen_assert(m_stride == 1);
+      Index inputIndex = index * m_inputStride + m_inputOffset;
+      EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+      for (int i = 0; i < PacketSize; ++i) {
+        values[i] = m_impl.coeff(inputIndex);
+        inputIndex += m_inputStride;
+      }
+      PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+      return rslt;
+    } else if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == NumInputDims - 1) ||
+	       (static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == 0)) {
+      // m_stride is aways greater than index, so let's avoid the integer division.
+      eigen_assert(m_stride > index);
+      return m_impl.template packet<LoadMode>(index + m_inputOffset);
+    } else {
+      const Index idx = index / m_stride;
+      const Index rem = index - idx * m_stride;
+      if (rem + PacketSize <= m_stride) {
+        Index inputIndex = idx * m_inputStride + m_inputOffset + rem;
+        return m_impl.template packet<LoadMode>(inputIndex);
+      } else {
+        // Cross the stride boundary. Fallback to slow path.
+        EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+        for (int i = 0; i < PacketSize; ++i) {
+          values[i] = coeff(index);
+          ++index;
+        }
+        PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+        return rslt;
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    double cost = 0;
+    if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) &&
+         m_dim.actualDim() == 0) ||
+        (static_cast<int>(Layout) == static_cast<int>(RowMajor) &&
+         m_dim.actualDim() == NumInputDims - 1)) {
+      cost += TensorOpCost::MulCost<Index>() + TensorOpCost::AddCost<Index>();
+    } else if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) &&
+                m_dim.actualDim() == NumInputDims - 1) ||
+               (static_cast<int>(Layout) == static_cast<int>(RowMajor) &&
+                m_dim.actualDim() == 0)) {
+      cost += TensorOpCost::AddCost<Index>();
+    } else {
+      cost += 3 * TensorOpCost::MulCost<Index>() + TensorOpCost::DivCost<Index>() +
+              3 * TensorOpCost::AddCost<Index>();
+    }
+
+    return m_impl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType* data() const {
+    CoeffReturnType* result = const_cast<CoeffReturnType*>(m_impl.data());
+    if (((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == NumDims) ||
+         (static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == 0)) &&
+        result) {
+      return result + m_inputOffset;
+    } else {
+      return NULL;
+    }
+  }
+
+ protected:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index srcCoeff(Index index) const
+  {
+    Index inputIndex;
+    if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == 0) ||
+	(static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == NumInputDims-1)) {
+      // m_stride is equal to 1, so let's avoid the integer division.
+      eigen_assert(m_stride == 1);
+      inputIndex = index * m_inputStride + m_inputOffset;
+    } else if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == NumInputDims-1) ||
+	       (static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == 0)) {
+      // m_stride is aways greater than index, so let's avoid the integer division.
+      eigen_assert(m_stride > index);
+      inputIndex = index + m_inputOffset;
+    } else {
+      const Index idx = index / m_stride;
+      inputIndex = idx * m_inputStride + m_inputOffset;
+      index -= idx * m_stride;
+      inputIndex += index;
+    }
+    return inputIndex;
+  }
+
+  Dimensions m_dimensions;
+  Index m_stride;
+  Index m_inputOffset;
+  Index m_inputStride;
+  TensorEvaluator<ArgType, Device> m_impl;
+  const internal::DimensionId<DimId> m_dim;
+  const Device& m_device;
+};
+
+
+// Eval as lvalue
+template<DenseIndex DimId, typename ArgType, typename Device>
+struct TensorEvaluator<TensorChippingOp<DimId, ArgType>, Device>
+  : public TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
+{
+  typedef TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device> Base;
+  typedef TensorChippingOp<DimId, ArgType> XprType;
+  static const int NumInputDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  static const int NumDims = NumInputDims-1;
+  typedef typename XprType::Index Index;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+    : Base(op, device)
+    { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index)
+  {
+    return this->m_impl.coeffRef(this->srcCoeff(index));
+  }
+
+  template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x)
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+
+    if ((static_cast<int>(this->Layout) == static_cast<int>(ColMajor) && this->m_dim.actualDim() == 0) ||
+	(static_cast<int>(this->Layout) == static_cast<int>(RowMajor) && this->m_dim.actualDim() == NumInputDims-1)) {
+      // m_stride is equal to 1, so let's avoid the integer division.
+      eigen_assert(this->m_stride == 1);
+      EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+      internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
+      Index inputIndex = index * this->m_inputStride + this->m_inputOffset;
+      for (int i = 0; i < PacketSize; ++i) {
+        this->m_impl.coeffRef(inputIndex) = values[i];
+        inputIndex += this->m_inputStride;
+      }
+    } else if ((static_cast<int>(this->Layout) == static_cast<int>(ColMajor) && this->m_dim.actualDim() == NumInputDims-1) ||
+	       (static_cast<int>(this->Layout) == static_cast<int>(RowMajor) && this->m_dim.actualDim() == 0)) {
+      // m_stride is aways greater than index, so let's avoid the integer division.
+      eigen_assert(this->m_stride > index);
+      this->m_impl.template writePacket<StoreMode>(index + this->m_inputOffset, x);
+    } else {
+      const Index idx = index / this->m_stride;
+      const Index rem = index - idx * this->m_stride;
+      if (rem + PacketSize <= this->m_stride) {
+        const Index inputIndex = idx * this->m_inputStride + this->m_inputOffset + rem;
+        this->m_impl.template writePacket<StoreMode>(inputIndex, x);
+      } else {
+        // Cross stride boundary. Fallback to slow path.
+        EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+        internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
+        for (int i = 0; i < PacketSize; ++i) {
+          this->coeffRef(index) = values[i];
+          ++index;
+        }
+      }
+    }
+  }
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CHIPPING_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConcatenation.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConcatenation.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConcatenation.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConcatenation.h
@@ -0,0 +1,361 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONCATENATION_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CONCATENATION_H
+
+namespace Eigen {
+
+/** \class TensorConcatenationOp
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor concatenation class.
+  *
+  *
+  */
+namespace internal {
+template<typename Axis, typename LhsXprType, typename RhsXprType>
+struct traits<TensorConcatenationOp<Axis, LhsXprType, RhsXprType> >
+{
+  // Type promotion to handle the case where the types of the lhs and the rhs are different.
+  typedef typename promote_storage_type<typename LhsXprType::Scalar,
+                                        typename RhsXprType::Scalar>::ret Scalar;
+  typedef typename promote_storage_type<typename traits<LhsXprType>::StorageKind,
+                                        typename traits<RhsXprType>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<LhsXprType>::Index,
+                                      typename traits<RhsXprType>::Index>::type Index;
+  typedef typename LhsXprType::Nested LhsNested;
+  typedef typename RhsXprType::Nested RhsNested;
+  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef typename remove_reference<RhsNested>::type _RhsNested;
+  static const int NumDimensions = traits<LhsXprType>::NumDimensions;
+  static const int Layout = traits<LhsXprType>::Layout;
+  enum { Flags = 0 };
+};
+
+template<typename Axis, typename LhsXprType, typename RhsXprType>
+struct eval<TensorConcatenationOp<Axis, LhsXprType, RhsXprType>, Eigen::Dense>
+{
+  typedef const TensorConcatenationOp<Axis, LhsXprType, RhsXprType>& type;
+};
+
+template<typename Axis, typename LhsXprType, typename RhsXprType>
+struct nested<TensorConcatenationOp<Axis, LhsXprType, RhsXprType>, 1, typename eval<TensorConcatenationOp<Axis, LhsXprType, RhsXprType> >::type>
+{
+  typedef TensorConcatenationOp<Axis, LhsXprType, RhsXprType> type;
+};
+
+}  // end namespace internal
+
+
+template<typename Axis, typename LhsXprType, typename RhsXprType>
+class TensorConcatenationOp : public TensorBase<TensorConcatenationOp<Axis, LhsXprType, RhsXprType>, WriteAccessors>
+{
+  public:
+    typedef typename internal::traits<TensorConcatenationOp>::Scalar Scalar;
+    typedef typename internal::traits<TensorConcatenationOp>::StorageKind StorageKind;
+    typedef typename internal::traits<TensorConcatenationOp>::Index Index;
+    typedef typename internal::nested<TensorConcatenationOp>::type Nested;
+    typedef typename internal::promote_storage_type<typename LhsXprType::CoeffReturnType,
+                                                    typename RhsXprType::CoeffReturnType>::ret CoeffReturnType;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorConcatenationOp(const LhsXprType& lhs, const RhsXprType& rhs, Axis axis)
+        : m_lhs_xpr(lhs), m_rhs_xpr(rhs), m_axis(axis) {}
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename LhsXprType::Nested>::type&
+    lhsExpression() const { return m_lhs_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename RhsXprType::Nested>::type&
+    rhsExpression() const { return m_rhs_xpr; }
+
+    EIGEN_DEVICE_FUNC const Axis& axis() const { return m_axis; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorConcatenationOp& operator = (const TensorConcatenationOp& other)
+    {
+      typedef TensorAssignOp<TensorConcatenationOp, const TensorConcatenationOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorConcatenationOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorConcatenationOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename LhsXprType::Nested m_lhs_xpr;
+    typename RhsXprType::Nested m_rhs_xpr;
+    const Axis m_axis;
+};
+
+
+// Eval as rvalue
+template<typename Axis, typename LeftArgType, typename RightArgType, typename Device>
+struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgType>, Device>
+{
+  typedef TensorConcatenationOp<Axis, LeftArgType, RightArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<LeftArgType, Device>::Dimensions>::value;
+  static const int RightNumDims = internal::array_size<typename TensorEvaluator<RightArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  enum {
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<LeftArgType, Device>::PacketAccess & TensorEvaluator<RightArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<LeftArgType, Device>::Layout,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+    : m_leftImpl(op.lhsExpression(), device), m_rightImpl(op.rhsExpression(), device), m_axis(op.axis())
+  {
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout) || NumDims == 1), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    EIGEN_STATIC_ASSERT((NumDims == RightNumDims), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    eigen_assert(0 <= m_axis && m_axis < NumDims);
+    const Dimensions& lhs_dims = m_leftImpl.dimensions();
+    const Dimensions& rhs_dims = m_rightImpl.dimensions();
+    {
+      int i = 0;
+      for (; i < m_axis; ++i) {
+        eigen_assert(lhs_dims[i] > 0);
+        eigen_assert(lhs_dims[i] == rhs_dims[i]);
+        m_dimensions[i] = lhs_dims[i];
+      }
+      eigen_assert(lhs_dims[i] > 0);  // Now i == m_axis.
+      eigen_assert(rhs_dims[i] > 0);
+      m_dimensions[i] = lhs_dims[i] + rhs_dims[i];
+      for (++i; i < NumDims; ++i) {
+        eigen_assert(lhs_dims[i] > 0);
+        eigen_assert(lhs_dims[i] == rhs_dims[i]);
+        m_dimensions[i] = lhs_dims[i];
+      }
+    }
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_leftStrides[0] = 1;
+      m_rightStrides[0] = 1;
+      m_outputStrides[0] = 1;
+
+      for (int j = 1; j < NumDims; ++j) {
+        m_leftStrides[j] = m_leftStrides[j-1] * lhs_dims[j-1];
+        m_rightStrides[j] = m_rightStrides[j-1] * rhs_dims[j-1];
+        m_outputStrides[j] = m_outputStrides[j-1] * m_dimensions[j-1];
+      }
+    } else {
+      m_leftStrides[NumDims - 1] = 1;
+      m_rightStrides[NumDims - 1] = 1;
+      m_outputStrides[NumDims - 1] = 1;
+
+      for (int j = NumDims - 2; j >= 0; --j) {
+        m_leftStrides[j] = m_leftStrides[j+1] * lhs_dims[j+1];
+        m_rightStrides[j] = m_rightStrides[j+1] * rhs_dims[j+1];
+        m_outputStrides[j] = m_outputStrides[j+1] * m_dimensions[j+1];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  // TODO(phli): Add short-circuit memcpy evaluation if underlying data are linear?
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/)
+  {
+    m_leftImpl.evalSubExprsIfNeeded(NULL);
+    m_rightImpl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup()
+  {
+    m_leftImpl.cleanup();
+    m_rightImpl.cleanup();
+  }
+
+  // TODO(phli): attempt to speed this up. The integer divisions and modulo are slow.
+  // See CL/76180724 comments for more ideas.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    // Collect dimension-wise indices (subs).
+    array<Index, NumDims> subs;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        subs[i] = index / m_outputStrides[i];
+        index -= subs[i] * m_outputStrides[i];
+      }
+      subs[0] = index;
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        subs[i] = index / m_outputStrides[i];
+        index -= subs[i] * m_outputStrides[i];
+      }
+      subs[NumDims - 1] = index;
+    }
+
+    const Dimensions& left_dims = m_leftImpl.dimensions();
+    if (subs[m_axis] < left_dims[m_axis]) {
+      Index left_index;
+      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+        left_index = subs[0];
+        for (int i = 1; i < NumDims; ++i) {
+          left_index += (subs[i] % left_dims[i]) * m_leftStrides[i];
+        }
+      } else {
+        left_index = subs[NumDims - 1];
+        for (int i = NumDims - 2; i >= 0; --i) {
+          left_index += (subs[i] % left_dims[i]) * m_leftStrides[i];
+        }
+      }
+      return m_leftImpl.coeff(left_index);
+    } else {
+      subs[m_axis] -= left_dims[m_axis];
+      const Dimensions& right_dims = m_rightImpl.dimensions();
+      Index right_index;
+      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+        right_index = subs[0];
+        for (int i = 1; i < NumDims; ++i) {
+          right_index += (subs[i] % right_dims[i]) * m_rightStrides[i];
+        }
+      } else {
+        right_index = subs[NumDims - 1];
+        for (int i = NumDims - 2; i >= 0; --i) {
+          right_index += (subs[i] % right_dims[i]) * m_rightStrides[i];
+        }
+      }
+      return m_rightImpl.coeff(right_index);
+    }
+  }
+
+  // TODO(phli): Add a real vectorization.
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
+    EIGEN_STATIC_ASSERT((packetSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index + packetSize - 1 < dimensions().TotalSize());
+
+    EIGEN_ALIGN_MAX CoeffReturnType values[packetSize];
+    for (int i = 0; i < packetSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    const double compute_cost = NumDims * (2 * TensorOpCost::AddCost<Index>() +
+                                           2 * TensorOpCost::MulCost<Index>() +
+                                           TensorOpCost::DivCost<Index>() +
+                                           TensorOpCost::ModCost<Index>());
+    const double lhs_size = m_leftImpl.dimensions().TotalSize();
+    const double rhs_size = m_rightImpl.dimensions().TotalSize();
+    return (lhs_size / (lhs_size + rhs_size)) *
+               m_leftImpl.costPerCoeff(vectorized) +
+           (rhs_size / (lhs_size + rhs_size)) *
+               m_rightImpl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, compute_cost);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+  protected:
+    Dimensions m_dimensions;
+    array<Index, NumDims> m_outputStrides;
+    array<Index, NumDims> m_leftStrides;
+    array<Index, NumDims> m_rightStrides;
+    TensorEvaluator<LeftArgType, Device> m_leftImpl;
+    TensorEvaluator<RightArgType, Device> m_rightImpl;
+    const Axis m_axis;
+};
+
+// Eval as lvalue
+template<typename Axis, typename LeftArgType, typename RightArgType, typename Device>
+  struct TensorEvaluator<TensorConcatenationOp<Axis, LeftArgType, RightArgType>, Device>
+  : public TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgType>, Device>
+{
+  typedef TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgType>, Device> Base;
+  typedef TensorConcatenationOp<Axis, LeftArgType, RightArgType> XprType;
+  typedef typename Base::Dimensions Dimensions;
+  enum {
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<LeftArgType, Device>::PacketAccess & TensorEvaluator<RightArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<LeftArgType, Device>::Layout,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(XprType& op, const Device& device)
+    : Base(op, device)
+  {
+    EIGEN_STATIC_ASSERT((static_cast<int>(Layout) == static_cast<int>(ColMajor)), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index)
+  {
+    // Collect dimension-wise indices (subs).
+    array<Index, Base::NumDims> subs;
+    for (int i = Base::NumDims - 1; i > 0; --i) {
+      subs[i] = index / this->m_outputStrides[i];
+      index -= subs[i] * this->m_outputStrides[i];
+    }
+    subs[0] = index;
+
+    const Dimensions& left_dims = this->m_leftImpl.dimensions();
+    if (subs[this->m_axis] < left_dims[this->m_axis]) {
+      Index left_index = subs[0];
+      for (int i = 1; i < Base::NumDims; ++i) {
+        left_index += (subs[i] % left_dims[i]) * this->m_leftStrides[i];
+      }
+      return this->m_leftImpl.coeffRef(left_index);
+    } else {
+      subs[this->m_axis] -= left_dims[this->m_axis];
+      const Dimensions& right_dims = this->m_rightImpl.dimensions();
+      Index right_index = subs[0];
+      for (int i = 1; i < Base::NumDims; ++i) {
+        right_index += (subs[i] % right_dims[i]) * this->m_rightStrides[i];
+      }
+      return this->m_rightImpl.coeffRef(right_index);
+    }
+  }
+
+  template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x)
+  {
+    const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
+    EIGEN_STATIC_ASSERT((packetSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index + packetSize - 1 < this->dimensions().TotalSize());
+
+    EIGEN_ALIGN_MAX CoeffReturnType values[packetSize];
+    internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
+    for (int i = 0; i < packetSize; ++i) {
+      coeffRef(index+i) = values[i];
+    }
+  }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CONCATENATION_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
@@ -0,0 +1,628 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_H
+
+namespace Eigen {
+
+/** \class TensorContraction
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor contraction class.
+  *
+  *
+  */
+namespace internal {
+
+template<typename Dimensions, typename LhsXprType, typename RhsXprType>
+struct traits<TensorContractionOp<Dimensions, LhsXprType, RhsXprType> >
+{
+  // Type promotion to handle the case where the types of the lhs and the rhs are different.
+  typedef typename gebp_traits<typename remove_const<typename LhsXprType::Scalar>::type,
+                               typename remove_const<typename RhsXprType::Scalar>::type>::ResScalar Scalar;
+
+  typedef typename promote_storage_type<typename traits<LhsXprType>::StorageKind,
+                                        typename traits<RhsXprType>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<LhsXprType>::Index,
+                                      typename traits<RhsXprType>::Index>::type Index;
+  typedef typename LhsXprType::Nested LhsNested;
+  typedef typename RhsXprType::Nested RhsNested;
+  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef typename remove_reference<RhsNested>::type _RhsNested;
+
+  // From NumDims below.
+  static const int NumDimensions = traits<RhsXprType>::NumDimensions + traits<RhsXprType>::NumDimensions - 2 * array_size<Dimensions>::value;
+  static const int Layout = traits<LhsXprType>::Layout;
+
+  enum {
+    Flags = 0
+  };
+};
+
+template<typename Dimensions, typename LhsXprType, typename RhsXprType>
+struct eval<TensorContractionOp<Dimensions, LhsXprType, RhsXprType>, Eigen::Dense>
+{
+  typedef const TensorContractionOp<Dimensions, LhsXprType, RhsXprType>& type;
+};
+
+template<typename Dimensions, typename LhsXprType, typename RhsXprType>
+struct nested<TensorContractionOp<Dimensions, LhsXprType, RhsXprType>, 1, typename eval<TensorContractionOp<Dimensions, LhsXprType, RhsXprType> >::type>
+{
+  typedef TensorContractionOp<Dimensions, LhsXprType, RhsXprType> type;
+};
+
+template<typename Indices_, typename LeftArgType_, typename RightArgType_, typename Device_>
+struct traits<TensorEvaluator<const TensorContractionOp<Indices_, LeftArgType_, RightArgType_>, Device_> > {
+  typedef Indices_ Indices;
+  typedef LeftArgType_ LeftArgType;
+  typedef RightArgType_ RightArgType;
+  typedef Device_ Device;
+
+  // From NumDims below.
+  static const int NumDimensions = traits<LeftArgType_>::NumDimensions + traits<RightArgType_>::NumDimensions - 2 * array_size<Indices_>::value;
+};
+
+}  // end namespace internal
+
+template<typename Indices, typename LhsXprType, typename RhsXprType>
+class TensorContractionOp : public TensorBase<TensorContractionOp<Indices, LhsXprType, RhsXprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorContractionOp>::Scalar Scalar;
+  typedef typename internal::gebp_traits<typename LhsXprType::CoeffReturnType,
+                                                   typename RhsXprType::CoeffReturnType>::ResScalar CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorContractionOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorContractionOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorContractionOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorContractionOp(
+      const LhsXprType& lhs, const RhsXprType& rhs, const Indices& dims)
+      : m_lhs_xpr(lhs), m_rhs_xpr(rhs), m_indices(dims) {}
+
+  EIGEN_DEVICE_FUNC
+  const Indices& indices() const { return m_indices; }
+
+  /** \returns the nested expressions */
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename LhsXprType::Nested>::type&
+  lhsExpression() const { return m_lhs_xpr; }
+
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename RhsXprType::Nested>::type&
+  rhsExpression() const { return m_rhs_xpr; }
+
+  protected:
+    typename LhsXprType::Nested m_lhs_xpr;
+    typename RhsXprType::Nested m_rhs_xpr;
+    const Indices m_indices;
+};
+
+
+template<typename Derived>
+struct TensorContractionEvaluatorBase
+{
+  typedef typename internal::traits<Derived>::Indices Indices;
+  typedef typename internal::traits<Derived>::LeftArgType LeftArgType;
+  typedef typename internal::traits<Derived>::RightArgType RightArgType;
+  typedef typename internal::traits<Derived>::Device Device;
+
+  typedef TensorContractionOp<Indices, LeftArgType, RightArgType> XprType;
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+
+  enum {
+    IsAligned = true,
+    PacketAccess = (internal::unpacket_traits<PacketReturnType>::size > 1),
+    Layout = TensorEvaluator<LeftArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = true
+  };
+
+  // Most of the code is assuming that both input tensors are ColMajor. If the
+  // inputs are RowMajor, we will "cheat" by swapping the LHS and RHS:
+  // If we want to compute A * B = C, where A is LHS and B is RHS, the code
+  // will pretend B is LHS and A is RHS.
+  typedef typename internal::conditional<
+    static_cast<int>(Layout) == static_cast<int>(ColMajor), LeftArgType, RightArgType>::type EvalLeftArgType;
+  typedef typename internal::conditional<
+    static_cast<int>(Layout) == static_cast<int>(ColMajor), RightArgType, LeftArgType>::type EvalRightArgType;
+
+  static const int LDims =
+      internal::array_size<typename TensorEvaluator<EvalLeftArgType, Device>::Dimensions>::value;
+  static const int RDims =
+      internal::array_size<typename TensorEvaluator<EvalRightArgType, Device>::Dimensions>::value;
+  static const int ContractDims = internal::array_size<Indices>::value;
+  static const int NumDims = LDims + RDims - 2 * ContractDims;
+
+  typedef array<Index, ContractDims> contract_t;
+  typedef array<Index, LDims - ContractDims> left_nocontract_t;
+  typedef array<Index, RDims - ContractDims> right_nocontract_t;
+
+  typedef DSizes<Index, NumDims> Dimensions;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  TensorContractionEvaluatorBase(const XprType& op, const Device& device)
+    : m_leftImpl(choose(Cond<static_cast<int>(Layout) == static_cast<int>(ColMajor)>(),
+                          op.lhsExpression(), op.rhsExpression()), device),
+    m_rightImpl(choose(Cond<static_cast<int>(Layout) == static_cast<int>(ColMajor)>(),
+                          op.rhsExpression(), op.lhsExpression()), device),
+        m_device(device),
+        m_result(NULL) {
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) ==
+			   static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout)),
+                        YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+
+    DSizes<Index, LDims> eval_left_dims;
+    DSizes<Index, RDims> eval_right_dims;
+    array<IndexPair<Index>, ContractDims> eval_op_indices;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      // For ColMajor, we keep using the existing dimensions
+      for (int i = 0; i < LDims; i++) {
+        eval_left_dims[i] = m_leftImpl.dimensions()[i];
+      }
+      for (int i = 0; i < RDims; i++) {
+        eval_right_dims[i] = m_rightImpl.dimensions()[i];
+      }
+      // We keep the pairs of contracting indices.
+      for (int i = 0; i < ContractDims; i++) {
+        eval_op_indices[i].first = op.indices()[i].first;
+        eval_op_indices[i].second = op.indices()[i].second;
+      }
+    } else {
+      // For RowMajor, we need to reverse the existing dimensions
+      for (int i = 0; i < LDims; i++) {
+        eval_left_dims[i] = m_leftImpl.dimensions()[LDims - i - 1];
+      }
+      for (int i = 0; i < RDims; i++) {
+        eval_right_dims[i] = m_rightImpl.dimensions()[RDims - i - 1];
+      }
+      // We need to flip all the pairs of contracting indices as well as
+      // reversing the dimensions.
+      for (int i = 0; i < ContractDims; i++) {
+        eval_op_indices[i].first = LDims - 1 - op.indices()[ContractDims - 1 - i].second;
+        eval_op_indices[i].second = RDims - 1 - op.indices()[ContractDims - 1 - i].first;
+      }
+    }
+
+    // Check for duplicate axes and make sure the first index in eval_op_indices
+    // is increasing. Using O(n^2) sorting is OK since ContractDims is small
+    for (int i = 0; i < ContractDims; i++) {
+      for (int j = i + 1; j < ContractDims; j++) {
+        eigen_assert(eval_op_indices[j].first != eval_op_indices[i].first &&
+                     eval_op_indices[j].second != eval_op_indices[i].second &&
+                     "contraction axes should be unique");
+        if (eval_op_indices[j].first < eval_op_indices[i].first) {
+          numext::swap(eval_op_indices[j], eval_op_indices[i]);
+        }
+      }
+    }
+
+    array<Index, LDims> lhs_strides;
+    lhs_strides[0] = 1;
+    for (int i = 0; i < LDims-1; ++i) {
+      lhs_strides[i+1] = lhs_strides[i] * eval_left_dims[i];
+    }
+
+    array<Index, RDims> rhs_strides;
+    rhs_strides[0] = 1;
+    for (int i = 0; i < RDims-1; ++i) {
+      rhs_strides[i+1] = rhs_strides[i] * eval_right_dims[i];
+    }
+
+    if (m_i_strides.size() > 0) m_i_strides[0] = 1;
+    if (m_j_strides.size() > 0) m_j_strides[0] = 1;
+    if (m_k_strides.size() > 0) m_k_strides[0] = 1;
+
+    m_i_size = 1;
+    m_j_size = 1;
+    m_k_size = 1;
+
+    // To compute the dimension, we simply concatenate the non-contracting
+    // dimensions of the left and then the right tensor. Additionally, we also
+    // compute the strides corresponding to the left non-contracting
+    // dimensions and right non-contracting dimensions.
+    m_lhs_inner_dim_contiguous = true;
+    int dim_idx = 0;
+    unsigned int nocontract_idx = 0;
+
+    for (int i = 0; i < LDims; i++) {
+      // find if we are contracting on index i of left tensor
+      bool contracting = false;
+      for (int j = 0; j < ContractDims; j++) {
+        if (eval_op_indices[j].first == i) {
+          contracting = true;
+          break;
+        }
+      }
+      if (!contracting) {
+        // add dimension size to output dimensions
+        m_dimensions[dim_idx] = eval_left_dims[i];
+        m_left_nocontract_strides[nocontract_idx] = lhs_strides[i];
+        if (dim_idx != i) {
+          m_lhs_inner_dim_contiguous = false;
+        }
+        if (nocontract_idx+1 < internal::array_size<left_nocontract_t>::value) {
+          m_i_strides[nocontract_idx+1] =
+              m_i_strides[nocontract_idx] * eval_left_dims[i];
+        } else {
+          m_i_size = m_i_strides[nocontract_idx] * eval_left_dims[i];
+        }
+        dim_idx++;
+        nocontract_idx++;
+      }
+    }
+
+    nocontract_idx = 0;
+    for (int i = 0; i < RDims; i++) {
+      bool contracting = false;
+      // find if we are contracting on index i of right tensor
+      for (int j = 0; j < ContractDims; j++) {
+        if (eval_op_indices[j].second == i) {
+          contracting = true;
+          break;
+        }
+      }
+      if (!contracting) {
+        m_dimensions[dim_idx] = eval_right_dims[i];
+        if (nocontract_idx+1 < internal::array_size<right_nocontract_t>::value) {
+          m_j_strides[nocontract_idx+1] =
+              m_j_strides[nocontract_idx] * eval_right_dims[i];
+        } else {
+          m_j_size = m_j_strides[nocontract_idx] * eval_right_dims[i];
+        }
+        m_right_nocontract_strides[nocontract_idx] = rhs_strides[i];
+        dim_idx++;
+        nocontract_idx++;
+      }
+    }
+
+    // Now compute the strides corresponding to the contracting dimensions. We
+    // assumed above that non-contracting axes are represented in the same order
+    // in the matrix as they are in the tensor. This is not the case for
+    // contracting axes. As the contracting axes must be of the same size in
+    // each tensor, we'll only look at the first tensor here.
+    m_rhs_inner_dim_contiguous = true;
+    m_rhs_inner_dim_reordered = false;
+    for (int i = 0; i < ContractDims; i++) {
+      Index left = eval_op_indices[i].first;
+      Index right = eval_op_indices[i].second;
+
+      Index size = eval_left_dims[left];
+      eigen_assert(size == eval_right_dims[right] &&
+                   "Contraction axes must be same size");
+
+      if (i+1 < static_cast<int>(internal::array_size<contract_t>::value)) {
+        m_k_strides[i+1] = m_k_strides[i] * size;
+      } else {
+        m_k_size = m_k_strides[i] * size;
+      }
+      m_left_contracting_strides[i] = lhs_strides[left];
+      m_right_contracting_strides[i] = rhs_strides[right];
+
+      if (i > 0 && right < eval_op_indices[i-1].second) {
+        m_rhs_inner_dim_reordered = true;
+      }
+      if (right != i) {
+        m_rhs_inner_dim_contiguous = false;
+      }
+    }
+
+    // If the layout is RowMajor, we need to reverse the m_dimensions
+    if (static_cast<int>(Layout) == static_cast<int>(RowMajor)) {
+      for (int i = 0, j = NumDims - 1; i < j; i++, j--) {
+        numext::swap(m_dimensions[i], m_dimensions[j]);
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) {
+    m_leftImpl.evalSubExprsIfNeeded(NULL);
+    m_rightImpl.evalSubExprsIfNeeded(NULL);
+    if (data) {
+      evalTo(data);
+      return false;
+    } else {
+      m_result = static_cast<Scalar *>(m_device.allocate(dimensions().TotalSize() * sizeof(Scalar)));
+      evalTo(m_result);
+      return true;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC void evalTo(Scalar* buffer) const {
+    if (this->m_lhs_inner_dim_contiguous) {
+      if (this->m_rhs_inner_dim_contiguous) {
+        if (this->m_rhs_inner_dim_reordered) {
+          static_cast<const Derived*>(this)->template evalProduct<true, true, true, Unaligned>(buffer);
+        }
+        else {
+          static_cast<const Derived*>(this)->template evalProduct<true, true, false, Unaligned>(buffer);
+        }
+      }
+      else {
+       if (this->m_rhs_inner_dim_reordered) {
+          static_cast<const Derived*>(this)->template evalProduct<true, false, true, Unaligned>(buffer);
+        }
+        else {
+          static_cast<const Derived*>(this)->template evalProduct<true, false, false, Unaligned>(buffer);
+        }
+      }
+    }
+    else {
+      if (this->m_rhs_inner_dim_contiguous) {
+        if (this->m_rhs_inner_dim_reordered) {
+          static_cast<const Derived*>(this)->template evalProduct<false, true, true, Unaligned>(buffer);
+        }
+        else {
+          static_cast<const Derived*>(this)->template evalProduct<false, true, false, Unaligned>(buffer);
+        }
+      }
+      else {
+       if (this->m_rhs_inner_dim_reordered) {
+          static_cast<const Derived*>(this)->template evalProduct<false, false, true, Unaligned>(buffer);
+        }
+        else {
+          static_cast<const Derived*>(this)->template evalProduct<false, false, false, Unaligned>(buffer);
+        }
+      }
+    }
+  }
+
+  template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous, bool rhs_inner_dim_reordered, int Alignment>
+  EIGEN_DEVICE_FUNC void evalGemv(Scalar* buffer) const {
+    const Index rows = m_i_size;
+    const Index cols = m_k_size;
+
+    typedef typename internal::remove_const<typename EvalLeftArgType::Scalar>::type LhsScalar;
+    typedef typename internal::remove_const<typename EvalRightArgType::Scalar>::type RhsScalar;
+    typedef TensorEvaluator<EvalLeftArgType, Device> LeftEvaluator;
+    typedef TensorEvaluator<EvalRightArgType, Device> RightEvaluator;
+    const Index lhs_packet_size = internal::unpacket_traits<typename LeftEvaluator::PacketReturnType>::size;
+    const Index rhs_packet_size = internal::unpacket_traits<typename RightEvaluator::PacketReturnType>::size;
+    const int lhs_alignment = LeftEvaluator::IsAligned ? Aligned : Unaligned;
+    const int rhs_alignment = RightEvaluator::IsAligned ? Aligned : Unaligned;
+    typedef internal::TensorContractionInputMapper<LhsScalar, Index, internal::Lhs,
+                                                   LeftEvaluator, left_nocontract_t,
+                                                   contract_t, lhs_packet_size,
+                                                   lhs_inner_dim_contiguous,
+                                                   false, lhs_alignment> LhsMapper;
+
+    typedef internal::TensorContractionInputMapper<RhsScalar, Index, internal::Rhs,
+                                                   RightEvaluator, right_nocontract_t,
+                                                   contract_t, rhs_packet_size,
+                                                   rhs_inner_dim_contiguous,
+                                                   rhs_inner_dim_reordered, rhs_alignment> RhsMapper;
+
+    LhsMapper lhs(m_leftImpl, m_left_nocontract_strides, m_i_strides,
+                  m_left_contracting_strides, m_k_strides);
+    RhsMapper rhs(m_rightImpl, m_right_nocontract_strides, m_j_strides,
+                  m_right_contracting_strides, m_k_strides);
+
+    const Scalar alpha(1);
+    const Index resIncr(1);
+
+    // zero out the result buffer (which must be of size at least rows * sizeof(Scalar)
+    m_device.memset(buffer, 0, rows * sizeof(Scalar));
+
+    internal::general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,false,RhsScalar,RhsMapper,false>::run(
+        rows, cols, lhs, rhs,
+        buffer, resIncr, alpha);
+  }
+
+  template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous, bool rhs_inner_dim_reordered, int Alignment>
+  EIGEN_DEVICE_FUNC void evalGemm(Scalar* buffer) const {
+    // columns in left side, rows in right side
+    const Index k = this->m_k_size;
+
+    // rows in left side
+    const Index m = this->m_i_size;
+
+    // columns in right side
+    const Index n = this->m_j_size;
+
+    // zero out the result buffer (which must be of size at least m * n * sizeof(Scalar)
+    this->m_device.memset(buffer, 0, m * n * sizeof(Scalar));
+
+    // define mr, nr, and all of my data mapper types
+    typedef typename internal::remove_const<typename EvalLeftArgType::Scalar>::type LhsScalar;
+    typedef typename internal::remove_const<typename EvalRightArgType::Scalar>::type RhsScalar;
+    typedef typename internal::gebp_traits<LhsScalar, RhsScalar> Traits;
+
+    const Index nr = Traits::nr;
+    const Index mr = Traits::mr;
+
+    typedef TensorEvaluator<EvalLeftArgType, Device> LeftEvaluator;
+    typedef TensorEvaluator<EvalRightArgType, Device> RightEvaluator;
+
+    const Index lhs_packet_size = internal::unpacket_traits<typename LeftEvaluator::PacketReturnType>::size;
+    const Index rhs_packet_size = internal::unpacket_traits<typename RightEvaluator::PacketReturnType>::size;
+
+    typedef internal::TensorContractionInputMapper<LhsScalar, Index, internal::Lhs,
+                                                   LeftEvaluator, left_nocontract_t,
+                                                   contract_t, lhs_packet_size,
+                                                   lhs_inner_dim_contiguous,
+                                                   false, Unaligned> LhsMapper;
+
+    typedef internal::TensorContractionInputMapper<RhsScalar, Index, internal::Rhs,
+                                                   RightEvaluator, right_nocontract_t,
+                                                   contract_t, rhs_packet_size,
+                                                   rhs_inner_dim_contiguous,
+                                                   rhs_inner_dim_reordered, Unaligned> RhsMapper;
+
+    typedef internal::blas_data_mapper<Scalar, Index, ColMajor> OutputMapper;
+
+    // Declare GEBP packing and kernel structs
+    internal::gemm_pack_lhs<LhsScalar, Index, typename LhsMapper::SubMapper, mr, Traits::LhsProgress, ColMajor> pack_lhs;
+    internal::gemm_pack_rhs<RhsScalar, Index, typename RhsMapper::SubMapper, nr, ColMajor> pack_rhs;
+
+    internal::gebp_kernel<LhsScalar, RhsScalar, Index, OutputMapper, mr, nr, false, false> gebp;
+
+    // initialize data mappers
+    LhsMapper lhs(this->m_leftImpl, this->m_left_nocontract_strides, this->m_i_strides,
+                  this->m_left_contracting_strides, this->m_k_strides);
+
+    RhsMapper rhs(this->m_rightImpl, this->m_right_nocontract_strides, this->m_j_strides,
+                  this->m_right_contracting_strides, this->m_k_strides);
+
+    OutputMapper output(buffer, m);
+
+    // Sizes of the blocks to load in cache. See the Goto paper for details.
+    internal::TensorContractionBlocking<LhsMapper, RhsMapper, Index, internal::ShardByCol> blocking(k, m, n, 1);
+    const Index kc = blocking.kc();
+    const Index mc = numext::mini(m, blocking.mc());
+    const Index nc = numext::mini(n, blocking.nc());
+    const Index sizeA = mc * kc;
+    const Index sizeB = kc * nc;
+
+    LhsScalar* blockA = static_cast<LhsScalar *>(this->m_device.allocate(sizeA * sizeof(LhsScalar)));
+    RhsScalar* blockB = static_cast<RhsScalar *>(this->m_device.allocate(sizeB * sizeof(RhsScalar)));
+
+    for(Index i2=0; i2<m; i2+=mc)
+    {
+      const Index actual_mc = numext::mini(i2+mc,m)-i2;
+      for (Index k2 = 0; k2 < k; k2 += kc) {
+        // make sure we don't overshoot right edge of left matrix, then pack vertical panel
+        const Index actual_kc = numext::mini(k2 + kc, k) - k2;
+        pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc, 0, 0);
+
+        // series of horizontal blocks
+        for (Index j2 = 0; j2 < n; j2 += nc) {
+          // make sure we don't overshoot right edge of right matrix, then pack block
+          const Index actual_nc = numext::mini(j2 + nc, n) - j2;
+          pack_rhs(blockB, rhs.getSubMapper(k2, j2), actual_kc, actual_nc, 0, 0);
+
+          // call gebp (matrix kernel)
+          // The parameters here are copied from Eigen's GEMM implementation
+          gebp(output.getSubMapper(i2, j2), blockA, blockB, actual_mc, actual_kc, actual_nc, Scalar(1), -1, -1, 0, 0);
+        }
+      }
+    }
+
+    this->m_device.deallocate(blockA);
+    this->m_device.deallocate(blockB);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_leftImpl.cleanup();
+    m_rightImpl.cleanup();
+
+    if (m_result != NULL) {
+      m_device.deallocate(m_result);
+      m_result = NULL;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+    return m_result[index];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool) const {
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_result + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar* data() const { return m_result; }
+
+  protected:
+  // Prevent assignment
+  TensorContractionEvaluatorBase& operator = (const TensorContractionEvaluatorBase&);
+  Dimensions m_dimensions;
+
+  contract_t m_k_strides;
+  contract_t m_left_contracting_strides;
+  contract_t m_right_contracting_strides;
+
+  bool m_lhs_inner_dim_contiguous;
+  bool m_rhs_inner_dim_contiguous;
+  bool m_rhs_inner_dim_reordered;
+
+  left_nocontract_t m_i_strides;
+  right_nocontract_t m_j_strides;
+  left_nocontract_t m_left_nocontract_strides;
+  right_nocontract_t m_right_nocontract_strides;
+
+  Index m_i_size;
+  Index m_j_size;
+  Index m_k_size;
+
+  TensorEvaluator<EvalLeftArgType, Device> m_leftImpl;
+  TensorEvaluator<EvalRightArgType, Device> m_rightImpl;
+  const Device& m_device;
+  Scalar* m_result;
+};
+
+
+// evaluator for default device
+template<typename Indices, typename LeftArgType, typename RightArgType, typename Device>
+struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, Device> :
+    public TensorContractionEvaluatorBase<
+      TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, Device> > {
+  typedef TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, Device> Self;
+  typedef TensorContractionEvaluatorBase<Self> Base;
+
+  typedef TensorContractionOp<Indices, LeftArgType, RightArgType> XprType;
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+
+  enum {
+    Layout = TensorEvaluator<LeftArgType, Device>::Layout
+  };
+
+  // Most of the code is assuming that both input tensors are ColMajor. If the
+  // inputs are RowMajor, we will "cheat" by swapping the LHS and RHS:
+  // If we want to compute A * B = C, where A is LHS and B is RHS, the code
+  // will pretend B is LHS and A is RHS.
+  typedef typename internal::conditional<
+    static_cast<int>(Layout) == static_cast<int>(ColMajor), LeftArgType, RightArgType>::type EvalLeftArgType;
+  typedef typename internal::conditional<
+    static_cast<int>(Layout) == static_cast<int>(ColMajor), RightArgType, LeftArgType>::type EvalRightArgType;
+
+  static const int LDims =
+      internal::array_size<typename TensorEvaluator<EvalLeftArgType, Device>::Dimensions>::value;
+  static const int RDims =
+      internal::array_size<typename TensorEvaluator<EvalRightArgType, Device>::Dimensions>::value;
+  static const int ContractDims = internal::array_size<Indices>::value;
+
+  typedef array<Index, ContractDims> contract_t;
+  typedef array<Index, LDims - ContractDims> left_nocontract_t;
+  typedef array<Index, RDims - ContractDims> right_nocontract_t;
+
+  static const int NumDims = LDims + RDims - 2 * ContractDims;
+
+  // Could we use NumDimensions here?
+  typedef DSizes<Index, NumDims> Dimensions;
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device) :
+      Base(op, device) { }
+
+  template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous, bool rhs_inner_dim_reordered, int Alignment>
+  EIGEN_DEVICE_FUNC void evalProduct(Scalar* buffer) const {
+    if (this->m_j_size == 1) {
+      this->template evalGemv<lhs_inner_dim_contiguous, rhs_inner_dim_contiguous, rhs_inner_dim_reordered, Alignment>(buffer);
+      return;
+    }
+
+    this->template evalGemm<lhs_inner_dim_contiguous, rhs_inner_dim_contiguous, rhs_inner_dim_reordered, Alignment>(buffer);
+  }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionBlocking.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionBlocking.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionBlocking.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionBlocking.h
@@ -0,0 +1,56 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_BLOCKING_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_BLOCKING_H
+
+
+namespace Eigen {
+namespace internal {
+
+enum {
+  ShardByRow = 0,
+  ShardByCol = 1
+};
+
+
+// Default Blocking Strategy
+template <typename LhsMapper, typename RhsMapper, typename Index, int ShardingType=ShardByCol>
+class TensorContractionBlocking {
+ public:
+
+  typedef typename LhsMapper::Scalar LhsScalar;
+  typedef typename RhsMapper::Scalar RhsScalar;
+
+  EIGEN_DEVICE_FUNC TensorContractionBlocking(Index k, Index m, Index n, Index num_threads = 1) :
+      kc_(k), mc_(m), nc_(n)
+  {
+    if (ShardingType == ShardByCol) {
+      computeProductBlockingSizes<LhsScalar, RhsScalar, 1>(kc_, mc_, nc_, num_threads);
+    }
+    else {
+      computeProductBlockingSizes<LhsScalar, RhsScalar, 1>(kc_, nc_, mc_, num_threads);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Index kc() const { return kc_; }
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Index mc() const { return mc_; }
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Index nc() const { return nc_; }
+
+ private:
+  Index kc_;
+  Index mc_;
+  Index nc_;
+};
+
+
+} // end namespace internal
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_BLOCKING_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionCuda.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionCuda.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionCuda.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionCuda.h
@@ -0,0 +1,1391 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014-2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+// Copyright (C) 2015 Navdeep Jaitly <ndjaitly@google.com>
+// Copyright (C) 2014 Eric Martin <eric@ericmart.in>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_CUDA_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_CUDA_H
+
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+
+namespace Eigen {
+
+template<typename Scalar, typename Index, typename LhsMapper,
+         typename RhsMapper, typename OutputMapper, bool needs_edge_check>
+__device__ EIGEN_STRONG_INLINE void
+EigenContractionKernelInternal(const LhsMapper lhs, const RhsMapper rhs,
+                               const OutputMapper output, Scalar* lhs_shmem, Scalar* rhs_shmem,
+                       const Index m_size, const Index n_size, const Index k_size) {
+
+  const Index m_block_idx = blockIdx.x;
+  const Index n_block_idx = blockIdx.y;
+
+  const Index base_m = 64 * m_block_idx;
+  const Index base_n = 64 * n_block_idx;
+
+  // declare and initialize 64 registers for output 8x8 block
+
+  // prefetch registers
+  Scalar lhs_pf0;
+  Scalar lhs_pf1;
+  Scalar lhs_pf2;
+  Scalar lhs_pf3;
+  Scalar lhs_pf4;
+  Scalar lhs_pf5;
+  Scalar lhs_pf6;
+  Scalar lhs_pf7;
+
+  Scalar rhs_pf0;
+  Scalar rhs_pf1;
+  Scalar rhs_pf2;
+  Scalar rhs_pf3;
+  Scalar rhs_pf4;
+  Scalar rhs_pf5;
+  Scalar rhs_pf6;
+  Scalar rhs_pf7;
+
+  // shared memory is formatted
+  // (contract idx in block, nocontract idx in block, block idx)
+  // where block idx is column major. This transposition limits the number of
+  // bank conflicts when reading the LHS. The core idea is that since the contracting
+  // index is shared by both sides, then the contracting index should be in threadIdx.x.
+
+  // On the LHS, we pad each row inside of each block with an extra element. This makes
+  // each block 8 rows of 9 elements, which is 72 elements. This gives no bank conflicts
+  // on writes and very few 2-way conflicts on reads. There is an 8x8 grid of these blocks.
+
+  // On the RHS we just add 8 padding elements to the end of each block. This gives no bank
+  // conflicts on writes and also none on reads.
+
+  // storage indices
+  const Index lhs_store_idx_base = threadIdx.y * 72 + threadIdx.x * 9 + threadIdx.z;
+  const Index rhs_store_idx_base = threadIdx.y * 72 + threadIdx.z * 8 + threadIdx.x;
+
+  const Index lhs_store_idx_0 = lhs_store_idx_base + 576 * 0;
+  const Index lhs_store_idx_1 = lhs_store_idx_base + 576 * 1;
+  const Index lhs_store_idx_2 = lhs_store_idx_base + 576 * 2;
+  const Index lhs_store_idx_3 = lhs_store_idx_base + 576 * 3;
+  const Index lhs_store_idx_4 = lhs_store_idx_base + 576 * 4;
+  const Index lhs_store_idx_5 = lhs_store_idx_base + 576 * 5;
+  const Index lhs_store_idx_6 = lhs_store_idx_base + 576 * 6;
+  const Index lhs_store_idx_7 = lhs_store_idx_base + 576 * 7;
+
+  const Index rhs_store_idx_0 = rhs_store_idx_base + 576 * 0;
+  const Index rhs_store_idx_1 = rhs_store_idx_base + 576 * 1;
+  const Index rhs_store_idx_2 = rhs_store_idx_base + 576 * 2;
+  const Index rhs_store_idx_3 = rhs_store_idx_base + 576 * 3;
+  const Index rhs_store_idx_4 = rhs_store_idx_base + 576 * 4;
+  const Index rhs_store_idx_5 = rhs_store_idx_base + 576 * 5;
+  const Index rhs_store_idx_6 = rhs_store_idx_base + 576 * 6;
+  const Index rhs_store_idx_7 = rhs_store_idx_base + 576 * 7;
+
+  // in the loading code, the following variables are important:
+  // threadIdx.x: the vertical position in an 8x8 block
+  // threadIdx.y: the vertical index of the 8x8 block in the grid
+  // threadIdx.z: the horizontal position in an 8x8 block
+  // k: the horizontal index of the 8x8 block in the grid
+  //
+  // The k parameter is implicit (it was the loop counter for a loop that went
+  // from 0 to <8, but now that loop is unrolled in the below code.
+
+  const Index load_idx_vert = threadIdx.x + 8 * threadIdx.y;
+  const Index lhs_vert = base_m + load_idx_vert;
+
+#define prefetchIntoRegisters(base_k)                           \
+  {                                                             \
+    lhs_pf0 = conv(0);                                          \
+    lhs_pf1 = conv(0);                                          \
+    lhs_pf2 = conv(0);                                          \
+    lhs_pf3 = conv(0);                                          \
+    lhs_pf4 = conv(0);                                          \
+    lhs_pf5 = conv(0);                                          \
+    lhs_pf6 = conv(0);                                          \
+    lhs_pf7 = conv(0);                                          \
+                                                                \
+    rhs_pf0 = conv(0);                                          \
+    rhs_pf1 = conv(0);                                          \
+    rhs_pf2 = conv(0);                                          \
+    rhs_pf3 = conv(0);                                          \
+    rhs_pf4 = conv(0);                                          \
+    rhs_pf5 = conv(0);                                          \
+    rhs_pf6 = conv(0);                                          \
+    rhs_pf7 = conv(0);                                          \
+                                                                \
+    if (!needs_edge_check || lhs_vert < m_size) {               \
+      const Index lhs_horiz_0 = base_k + threadIdx.z + 0 * 8;   \
+      const Index lhs_horiz_1 = base_k + threadIdx.z + 1 * 8;   \
+      const Index lhs_horiz_2 = base_k + threadIdx.z + 2 * 8;   \
+      const Index lhs_horiz_3 = base_k + threadIdx.z + 3 * 8;   \
+      const Index lhs_horiz_4 = base_k + threadIdx.z + 4 * 8;   \
+      const Index lhs_horiz_5 = base_k + threadIdx.z + 5 * 8;   \
+      const Index lhs_horiz_6 = base_k + threadIdx.z + 6 * 8;   \
+      const Index lhs_horiz_7 = base_k + threadIdx.z + 7 * 8;   \
+                                                                \
+      if (!needs_edge_check || lhs_horiz_7 < k_size) {          \
+        lhs_pf0 = lhs(lhs_vert, lhs_horiz_0);                   \
+        lhs_pf1 = lhs(lhs_vert, lhs_horiz_1);                   \
+        lhs_pf2 = lhs(lhs_vert, lhs_horiz_2);                   \
+        lhs_pf3 = lhs(lhs_vert, lhs_horiz_3);                   \
+        lhs_pf4 = lhs(lhs_vert, lhs_horiz_4);                   \
+        lhs_pf5 = lhs(lhs_vert, lhs_horiz_5);                   \
+        lhs_pf6 = lhs(lhs_vert, lhs_horiz_6);                   \
+        lhs_pf7 = lhs(lhs_vert, lhs_horiz_7);                   \
+      } else if (lhs_horiz_6 < k_size) {                        \
+        lhs_pf0 = lhs(lhs_vert, lhs_horiz_0);                   \
+        lhs_pf1 = lhs(lhs_vert, lhs_horiz_1);                   \
+        lhs_pf2 = lhs(lhs_vert, lhs_horiz_2);                   \
+        lhs_pf3 = lhs(lhs_vert, lhs_horiz_3);                   \
+        lhs_pf4 = lhs(lhs_vert, lhs_horiz_4);                   \
+        lhs_pf5 = lhs(lhs_vert, lhs_horiz_5);                   \
+        lhs_pf6 = lhs(lhs_vert, lhs_horiz_6);                   \
+      } else if (lhs_horiz_5 < k_size) {                        \
+        lhs_pf0 = lhs(lhs_vert, lhs_horiz_0);                   \
+        lhs_pf1 = lhs(lhs_vert, lhs_horiz_1);                   \
+        lhs_pf2 = lhs(lhs_vert, lhs_horiz_2);                   \
+        lhs_pf3 = lhs(lhs_vert, lhs_horiz_3);                   \
+        lhs_pf4 = lhs(lhs_vert, lhs_horiz_4);                   \
+        lhs_pf5 = lhs(lhs_vert, lhs_horiz_5);                   \
+      } else if (lhs_horiz_4 < k_size) {                        \
+        lhs_pf0 = lhs(lhs_vert, lhs_horiz_0);                   \
+        lhs_pf1 = lhs(lhs_vert, lhs_horiz_1);                   \
+        lhs_pf2 = lhs(lhs_vert, lhs_horiz_2);                   \
+        lhs_pf3 = lhs(lhs_vert, lhs_horiz_3);                   \
+        lhs_pf4 = lhs(lhs_vert, lhs_horiz_4);                   \
+      } else if (lhs_horiz_3 < k_size) {                        \
+        lhs_pf0 = lhs(lhs_vert, lhs_horiz_0);                   \
+        lhs_pf1 = lhs(lhs_vert, lhs_horiz_1);                   \
+        lhs_pf2 = lhs(lhs_vert, lhs_horiz_2);                   \
+        lhs_pf3 = lhs(lhs_vert, lhs_horiz_3);                   \
+      } else if (lhs_horiz_2 < k_size) {                        \
+        lhs_pf0 = lhs(lhs_vert, lhs_horiz_0);                   \
+        lhs_pf1 = lhs(lhs_vert, lhs_horiz_1);                   \
+        lhs_pf2 = lhs(lhs_vert, lhs_horiz_2);                   \
+      } else if (lhs_horiz_1 < k_size) {                        \
+        lhs_pf0 = lhs(lhs_vert, lhs_horiz_0);                   \
+        lhs_pf1 = lhs(lhs_vert, lhs_horiz_1);                   \
+      } else if (lhs_horiz_0 < k_size) {                        \
+        lhs_pf0 = lhs(lhs_vert, lhs_horiz_0);                   \
+      }                                                         \
+    }                                                           \
+                                                                \
+    const Index rhs_vert = base_k + load_idx_vert;              \
+    if (!needs_edge_check || rhs_vert < k_size) {               \
+      const Index rhs_horiz_0 = base_n + threadIdx.z + 0 * 8;   \
+      const Index rhs_horiz_1 = base_n + threadIdx.z + 1 * 8;   \
+      const Index rhs_horiz_2 = base_n + threadIdx.z + 2 * 8;   \
+      const Index rhs_horiz_3 = base_n + threadIdx.z + 3 * 8;   \
+      const Index rhs_horiz_4 = base_n + threadIdx.z + 4 * 8;   \
+      const Index rhs_horiz_5 = base_n + threadIdx.z + 5 * 8;   \
+      const Index rhs_horiz_6 = base_n + threadIdx.z + 6 * 8;   \
+      const Index rhs_horiz_7 = base_n + threadIdx.z + 7 * 8;   \
+                                                                \
+      if (rhs_horiz_7 < n_size) {                               \
+        rhs_pf0 = rhs(rhs_vert, rhs_horiz_0);                   \
+        rhs_pf1 = rhs(rhs_vert, rhs_horiz_1);                   \
+        rhs_pf2 = rhs(rhs_vert, rhs_horiz_2);                   \
+        rhs_pf3 = rhs(rhs_vert, rhs_horiz_3);                   \
+        rhs_pf4 = rhs(rhs_vert, rhs_horiz_4);                   \
+        rhs_pf5 = rhs(rhs_vert, rhs_horiz_5);                   \
+        rhs_pf6 = rhs(rhs_vert, rhs_horiz_6);                   \
+        rhs_pf7 = rhs(rhs_vert, rhs_horiz_7);                   \
+      } else if (rhs_horiz_6 < n_size) {                        \
+        rhs_pf0 = rhs(rhs_vert, rhs_horiz_0);                   \
+        rhs_pf1 = rhs(rhs_vert, rhs_horiz_1);                   \
+        rhs_pf2 = rhs(rhs_vert, rhs_horiz_2);                   \
+        rhs_pf3 = rhs(rhs_vert, rhs_horiz_3);                   \
+        rhs_pf4 = rhs(rhs_vert, rhs_horiz_4);                   \
+        rhs_pf5 = rhs(rhs_vert, rhs_horiz_5);                   \
+        rhs_pf6 = rhs(rhs_vert, rhs_horiz_6);                   \
+      } else if (rhs_horiz_5 < n_size) {                        \
+        rhs_pf0 = rhs(rhs_vert, rhs_horiz_0);                   \
+        rhs_pf1 = rhs(rhs_vert, rhs_horiz_1);                   \
+        rhs_pf2 = rhs(rhs_vert, rhs_horiz_2);                   \
+        rhs_pf3 = rhs(rhs_vert, rhs_horiz_3);                   \
+        rhs_pf4 = rhs(rhs_vert, rhs_horiz_4);                   \
+        rhs_pf5 = rhs(rhs_vert, rhs_horiz_5);                   \
+      } else if (rhs_horiz_4 < n_size) {                        \
+        rhs_pf0 = rhs(rhs_vert, rhs_horiz_0);                   \
+        rhs_pf1 = rhs(rhs_vert, rhs_horiz_1);                   \
+        rhs_pf2 = rhs(rhs_vert, rhs_horiz_2);                   \
+        rhs_pf3 = rhs(rhs_vert, rhs_horiz_3);                   \
+        rhs_pf4 = rhs(rhs_vert, rhs_horiz_4);                   \
+      } else if (rhs_horiz_3 < n_size) {                        \
+        rhs_pf0 = rhs(rhs_vert, rhs_horiz_0);                   \
+        rhs_pf1 = rhs(rhs_vert, rhs_horiz_1);                   \
+        rhs_pf2 = rhs(rhs_vert, rhs_horiz_2);                   \
+        rhs_pf3 = rhs(rhs_vert, rhs_horiz_3);                   \
+      } else if (rhs_horiz_2 < n_size) {                        \
+        rhs_pf0 = rhs(rhs_vert, rhs_horiz_0);                   \
+        rhs_pf1 = rhs(rhs_vert, rhs_horiz_1);                   \
+        rhs_pf2 = rhs(rhs_vert, rhs_horiz_2);                   \
+      } else if (rhs_horiz_1 < n_size) {                        \
+        rhs_pf0 = rhs(rhs_vert, rhs_horiz_0);                   \
+        rhs_pf1 = rhs(rhs_vert, rhs_horiz_1);                   \
+      } else if (rhs_horiz_0 < n_size) {                        \
+        rhs_pf0 = rhs(rhs_vert, rhs_horiz_0);                   \
+      }                                                         \
+    }                                                           \
+  }                                                             \
+
+#define writeRegToShmem(_)                      \
+  lhs_shmem[lhs_store_idx_0] = lhs_pf0;         \
+  rhs_shmem[rhs_store_idx_0] = rhs_pf0;         \
+                                                \
+  lhs_shmem[lhs_store_idx_1] = lhs_pf1;         \
+  rhs_shmem[rhs_store_idx_1] = rhs_pf1;         \
+                                                \
+  lhs_shmem[lhs_store_idx_2] = lhs_pf2;         \
+  rhs_shmem[rhs_store_idx_2] = rhs_pf2;         \
+                                                \
+  lhs_shmem[lhs_store_idx_3] = lhs_pf3;         \
+  rhs_shmem[rhs_store_idx_3] = rhs_pf3;         \
+                                                \
+  lhs_shmem[lhs_store_idx_4] = lhs_pf4;         \
+  rhs_shmem[rhs_store_idx_4] = rhs_pf4;         \
+                                                \
+  lhs_shmem[lhs_store_idx_5] = lhs_pf5;         \
+  rhs_shmem[rhs_store_idx_5] = rhs_pf5;         \
+                                                \
+  lhs_shmem[lhs_store_idx_6] = lhs_pf6;         \
+  rhs_shmem[rhs_store_idx_6] = rhs_pf6;         \
+                                                \
+  lhs_shmem[lhs_store_idx_7] = lhs_pf7;         \
+  rhs_shmem[rhs_store_idx_7] = rhs_pf7;         \
+
+  // declare and initialize result array
+#define res(i, j) _res_##i##j
+#define initResultRow(i)                        \
+  Scalar res(i, 0) = conv(0);                   \
+  Scalar res(i, 1) = conv(0);                   \
+  Scalar res(i, 2) = conv(0);                   \
+  Scalar res(i, 3) = conv(0);                   \
+  Scalar res(i, 4) = conv(0);                   \
+  Scalar res(i, 5) = conv(0);                   \
+  Scalar res(i, 6) = conv(0);                   \
+  Scalar res(i, 7) = conv(0);                   \
+
+  internal::scalar_cast_op<int, Scalar> conv;
+  initResultRow(0);
+  initResultRow(1);
+  initResultRow(2);
+  initResultRow(3);
+  initResultRow(4);
+  initResultRow(5);
+  initResultRow(6);
+  initResultRow(7);
+#undef initResultRow
+
+  for (Index base_k = 0; base_k < k_size; base_k += 64) {
+    // wait for previous iteration to finish with shmem. Despite common sense,
+    // the code is a bit faster with this here then at bottom of loop
+    __syncthreads();
+
+    prefetchIntoRegisters(base_k);
+    writeRegToShmem();
+
+    #undef prefetchIntoRegisters
+    #undef writeRegToShmem
+
+    // wait for shared mem packing to be done before starting computation
+    __syncthreads();
+
+    // compute 8x8 matrix product by outer product. This involves packing one column
+    // of LHS and one row of RHS into registers (takes 16 registers).
+
+#define lcol(i) _lcol##i
+    Scalar lcol(0);
+    Scalar lcol(1);
+    Scalar lcol(2);
+    Scalar lcol(3);
+    Scalar lcol(4);
+    Scalar lcol(5);
+    Scalar lcol(6);
+    Scalar lcol(7);
+
+#define rrow(j) _rrow##j
+    Scalar rrow(0);
+    Scalar rrow(1);
+    Scalar rrow(2);
+    Scalar rrow(3);
+    Scalar rrow(4);
+    Scalar rrow(5);
+    Scalar rrow(6);
+    Scalar rrow(7);
+
+    // Now x corresponds to k, y to m, and z to n
+    const Scalar* lhs_block = &lhs_shmem[threadIdx.x + 9 * threadIdx.y];
+    const Scalar* rhs_block = &rhs_shmem[threadIdx.x + 8 * threadIdx.z];
+
+#define lhs_element(i, j) lhs_block[72 * ((i) + 8 * (j))]
+#define rhs_element(i, j) rhs_block[72 * ((i) + 8 * (j))]
+
+#define loadData(i, j)                          \
+    lcol(0) = lhs_element(0, j);               \
+    rrow(0) = rhs_element(i, 0);               \
+    lcol(1) = lhs_element(1, j);               \
+    rrow(1) = rhs_element(i, 1);               \
+    lcol(2) = lhs_element(2, j);               \
+    rrow(2) = rhs_element(i, 2);               \
+    lcol(3) = lhs_element(3, j);               \
+    rrow(3) = rhs_element(i, 3);               \
+    lcol(4) = lhs_element(4, j);               \
+    rrow(4) = rhs_element(i, 4);               \
+    lcol(5) = lhs_element(5, j);               \
+    rrow(5) = rhs_element(i, 5);               \
+    lcol(6) = lhs_element(6, j);               \
+    rrow(6) = rhs_element(i, 6);               \
+    lcol(7) = lhs_element(7, j);               \
+    rrow(7) = rhs_element(i, 7);               \
+
+#define computeCol(j)                           \
+    res(0, j) += lcol(0) * rrow(j);             \
+    res(1, j) += lcol(1) * rrow(j);             \
+    res(2, j) += lcol(2) * rrow(j);             \
+    res(3, j) += lcol(3) * rrow(j);             \
+    res(4, j) += lcol(4) * rrow(j);             \
+    res(5, j) += lcol(5) * rrow(j);             \
+    res(6, j) += lcol(6) * rrow(j);             \
+    res(7, j) += lcol(7) * rrow(j);             \
+
+#define computePass(i)                          \
+    loadData(i, i);                             \
+                                                \
+    computeCol(0);                              \
+    computeCol(1);                              \
+    computeCol(2);                              \
+    computeCol(3);                              \
+    computeCol(4);                              \
+    computeCol(5);                              \
+    computeCol(6);                              \
+    computeCol(7);                              \
+
+    computePass(0);
+    computePass(1);
+    computePass(2);
+    computePass(3);
+    computePass(4);
+    computePass(5);
+    computePass(6);
+    computePass(7);
+
+#undef lcol
+#undef rrow
+#undef lhs_element
+#undef rhs_element
+#undef loadData
+#undef computeCol
+#undef computePass
+  } // end loop over k
+
+  // we've now iterated over all of the large (ie width 64) k blocks and
+  // accumulated results in registers. At this point thread (x, y, z) contains
+  // the sum across all big k blocks of the product of little k block of index (x, y)
+  // with block of index (y, z). To compute the final output, we need to reduce
+  // the 8 threads over y by summation.
+#define shuffleInc(i, j, mask) res(i, j) += __shfl_xor(res(i, j), mask)
+
+#define reduceRow(i, mask)                      \
+  shuffleInc(i, 0, mask);                       \
+  shuffleInc(i, 1, mask);                       \
+  shuffleInc(i, 2, mask);                       \
+  shuffleInc(i, 3, mask);                       \
+  shuffleInc(i, 4, mask);                       \
+  shuffleInc(i, 5, mask);                       \
+  shuffleInc(i, 6, mask);                       \
+  shuffleInc(i, 7, mask);                       \
+
+#define reduceMatrix(mask)                      \
+  reduceRow(0, mask);                           \
+  reduceRow(1, mask);                           \
+  reduceRow(2, mask);                           \
+  reduceRow(3, mask);                           \
+  reduceRow(4, mask);                           \
+  reduceRow(5, mask);                           \
+  reduceRow(6, mask);                           \
+  reduceRow(7, mask);                           \
+
+  // actually perform the reduction, now each thread of index (_, y, z)
+  // contains the correct values in its registers that belong in the output
+  // block
+  reduceMatrix(1);
+  reduceMatrix(2);
+  reduceMatrix(4);
+
+#undef shuffleInc
+#undef reduceRow
+#undef reduceMatrix
+
+  // now we need to copy the 64 values into main memory. We can't split work
+  // among threads because all variables are in registers. There's 2 ways
+  // to do this:
+  // (1) have 1 thread do 64 writes from registers into global memory
+  // (2) have 1 thread do 64 writes into shared memory, and then 8 threads
+  //     each do 8 writes into global memory. We can just overwrite the shared
+  //     memory from the problem we just solved.
+  // (2) is slightly faster than (1) due to less branching and more ILP
+
+  // TODO: won't yield much gain, but could just use currently unused shared mem
+  //       and then we won't have to sync
+  // wait for shared mem to be out of use
+  __syncthreads();
+
+#define writeResultShmem(i, j)                                          \
+  lhs_shmem[i + 8 * threadIdx.y + 64 * threadIdx.z + 512 * j] = res(i, j); \
+
+#define writeRow(i)                             \
+  writeResultShmem(i, 0);                       \
+  writeResultShmem(i, 1);                       \
+  writeResultShmem(i, 2);                       \
+  writeResultShmem(i, 3);                       \
+  writeResultShmem(i, 4);                       \
+  writeResultShmem(i, 5);                       \
+  writeResultShmem(i, 6);                       \
+  writeResultShmem(i, 7);                       \
+
+  if (threadIdx.x == 0) {
+    writeRow(0);
+    writeRow(1);
+    writeRow(2);
+    writeRow(3);
+    writeRow(4);
+    writeRow(5);
+    writeRow(6);
+    writeRow(7);
+  }
+#undef writeResultShmem
+#undef writeRow
+
+  const int max_i_write = numext::mini((int)((m_size - base_m - threadIdx.y + 7) / 8), 8);
+  const int max_j_write = numext::mini((int)((n_size - base_n - threadIdx.z + 7) / 8), 8);
+
+  if (threadIdx.x < max_i_write) {
+    if (max_j_write == 8) {
+      // TODO: can i trade bank conflicts for coalesced writes?
+      Scalar val0 = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * 0];
+      Scalar val1 = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * 1];
+      Scalar val2 = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * 2];
+      Scalar val3 = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * 3];
+      Scalar val4 = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * 4];
+      Scalar val5 = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * 5];
+      Scalar val6 = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * 6];
+      Scalar val7 = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * 7];
+
+      output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * 0) = val0;
+      output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * 1) = val1;
+      output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * 2) = val2;
+      output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * 3) = val3;
+      output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * 4) = val4;
+      output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * 5) = val5;
+      output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * 6) = val6;
+      output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * 7) = val7;
+    } else {
+#pragma unroll 7
+      for (int j = 0; j < max_j_write; j++) {
+        Scalar val = lhs_shmem[threadIdx.x + 8 * threadIdx.y + 64 * threadIdx.z + 512 * j];
+        output(base_m + threadIdx.y + 8 * threadIdx.x, base_n + threadIdx.z + 8 * j) = val;
+      }
+    }
+  }
+#undef res
+}
+
+
+template<typename Scalar, typename Index, typename LhsMapper,
+         typename RhsMapper, typename OutputMapper>
+__global__ void
+__launch_bounds__(512)
+EigenContractionKernel(const LhsMapper lhs, const RhsMapper rhs,
+                       const OutputMapper output,
+                       const Index m_size, const Index n_size, const Index k_size) {
+  __shared__ Scalar lhs_shmem[72 * 64];
+  __shared__ Scalar rhs_shmem[72 * 64];
+
+  const Index m_block_idx = blockIdx.x;
+  const Index n_block_idx = blockIdx.y;
+
+  const Index base_m = 64 * m_block_idx;
+  const Index base_n = 64 * n_block_idx;
+
+  if (base_m + 63 < m_size && base_n + 63 < n_size) {
+    EigenContractionKernelInternal<Scalar, Index, LhsMapper, RhsMapper, OutputMapper, false>(lhs, rhs, output, lhs_shmem, rhs_shmem, m_size, n_size, k_size);
+  } else {
+    EigenContractionKernelInternal<Scalar, Index, LhsMapper, RhsMapper, OutputMapper, true>(lhs, rhs, output, lhs_shmem, rhs_shmem, m_size, n_size, k_size);
+  }
+}
+
+
+template<typename Index, typename LhsMapper,
+         typename RhsMapper, typename OutputMapper, bool CHECK_LHS_BOUNDARY,
+         bool CHECK_RHS_BOUNDARY>
+__device__ EIGEN_STRONG_INLINE void
+EigenFloatContractionKernelInternal16x16(const LhsMapper lhs, const RhsMapper rhs,
+                       const OutputMapper output, float2 lhs_shmem2[][16],
+                       float2 rhs_shmem2[][8], const Index m_size,
+                       const Index n_size, const Index k_size,
+                       const Index base_m, const Index base_n) {
+  typedef float Scalar;
+
+  // prefetch registers
+  float4 lhs_pf0, rhs_pf0;
+
+  float4 results[4];
+  for (int i=0; i < 4; i++) {
+    results[i].x = results[i].y = results[i].z = results[i].w = 0;
+  }
+
+
+#define prefetch_lhs(reg, row, col)                   \
+    if (!CHECK_LHS_BOUNDARY) {                        \
+      if (col < k_size) {                             \
+        reg =lhs.loadPacket<Unaligned>(row, col);     \
+      }                                               \
+    } else {                                          \
+      if (col < k_size) {                             \
+        if (row + 3 < m_size) {                       \
+          reg =lhs.loadPacket<Unaligned>(row, col);   \
+        } else if (row + 2 < m_size) {                \
+          reg.x =lhs(row + 0, col);                   \
+          reg.y =lhs(row + 1, col);                   \
+          reg.z =lhs(row + 2, col);                   \
+        } else if (row + 1 < m_size) {                \
+          reg.x =lhs(row + 0, col);                   \
+          reg.y =lhs(row + 1, col);                   \
+        } else if (row  < m_size) {                   \
+          reg.x =lhs(row + 0, col);                   \
+        }                                             \
+      }                                               \
+    }                                                 \
+
+
+  Index lhs_vert = base_m+threadIdx.x*4;
+
+  for (Index k = 0; k < k_size; k += 16) {
+    lhs_pf0 = internal::pset1<float4>(0);
+    rhs_pf0 = internal::pset1<float4>(0);
+
+    Index lhs_horiz = threadIdx.y+k;
+    prefetch_lhs(lhs_pf0, lhs_vert, lhs_horiz)
+
+    Index rhs_vert = k+(threadIdx.x%4)*4;
+    Index rhs_horiz0 = (threadIdx.x>>2)+threadIdx.y*4+base_n;
+
+    if (!CHECK_RHS_BOUNDARY) {
+      if ((rhs_vert + 3) < k_size) {
+        // just CHECK_RHS_BOUNDARY
+        rhs_pf0 = rhs.loadPacket<Unaligned>(rhs_vert, rhs_horiz0);
+      } else if (rhs_vert + 2 < k_size) {
+        // just CHECK_RHS_BOUNDARY
+        rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+        rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+        rhs_pf0.z = rhs(rhs_vert + 2, rhs_horiz0);
+      } else if (rhs_vert + 1 < k_size) {
+        rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+        rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+      } else if (rhs_vert  < k_size) {
+        rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+      }
+    } else {
+      if (rhs_horiz0 < n_size) {
+        if ((rhs_vert + 3) < k_size) {
+          rhs_pf0 = rhs.loadPacket<Unaligned>(rhs_vert, rhs_horiz0);
+        } else if ((rhs_vert + 2) < k_size) {
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+          rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+          rhs_pf0.z = rhs(rhs_vert + 2, rhs_horiz0);
+        } else if ((rhs_vert + 1) < k_size) {
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+          rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+        } else if (rhs_vert  < k_size) {
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+        }
+      }
+    }
+    float x1, x2 ;
+    // the following can be a bitwise operation..... some day.
+    if((threadIdx.x%8) < 4) {
+      x1 = rhs_pf0.y;
+      x2 = rhs_pf0.w;
+    } else {
+      x1 = rhs_pf0.x;
+      x2 = rhs_pf0.z;
+    }
+    x1 = __shfl_xor(x1, 4);
+    x2 = __shfl_xor(x2, 4);
+    if((threadIdx.x%8) < 4) {
+      rhs_pf0.y = x1;
+      rhs_pf0.w = x2;
+    } else {
+      rhs_pf0.x = x1;
+      rhs_pf0.z = x2;
+    }
+
+    // We have 64 features.
+    // Row 0 -> times (0, 4, 8, 12, 1, 5, 9, 13) for features 0, 1.
+    // Row 1 -> times (0, 4, 8, 12, 1, 5, 9, 13) for features 2, 3.
+    // ...
+    // Row 31 -> times (0, 4, 8, 12, 1, 5, 9, 13) for features 62, 63
+    // Row 32 -> times (2, 6, 10, 14, 3, 7, 11, 15) for features 0, 1
+    // ...
+    rhs_shmem2[(threadIdx.x>>3)+ threadIdx.y*2][threadIdx.x%8] = make_float2(rhs_pf0.x, rhs_pf0.y);
+    rhs_shmem2[(threadIdx.x>>3)+ threadIdx.y*2+32][threadIdx.x%8] = make_float2(rhs_pf0.z, rhs_pf0.w);
+
+    // Row 0 (time 0) -> features (0, 1), (4, 5), .. (28, 29), (32, 33), ..  (60, 61)
+    // Row 1 (time 1) -> features (0, 1), (4, 5), .. (28, 29), (32, 33), ..  (60, 61)
+    // ...
+    // Row 15 (time 15) -> features (0, 1), (4, 5), .. (28, 29), (32, 33), ..  (60, 61)
+    // Row 16 (time 0) -> features (2, 3), (6, 7), .. (30, 31), (34, 35), ..  (62, 63)
+    // ...
+
+    lhs_shmem2[threadIdx.y][threadIdx.x] = make_float2(lhs_pf0.x, lhs_pf0.y);
+    lhs_shmem2[threadIdx.y+16][threadIdx.x] = make_float2(lhs_pf0.z, lhs_pf0.w);
+
+
+#define add_vals(fl1, fl2, fr1, fr2)\
+    results[0].x += fl1.x * fr1.x;\
+    results[0].y += fl1.y * fr1.x;\
+    results[0].z += fl2.x * fr1.x;\
+    results[0].w += fl2.y * fr1.x;\
+\
+    results[1].x += fl1.x * fr1.y;\
+    results[1].y += fl1.y * fr1.y;\
+    results[1].z += fl2.x * fr1.y;\
+    results[1].w += fl2.y * fr1.y;\
+\
+    results[2].x += fl1.x * fr2.x;\
+    results[2].y += fl1.y * fr2.x;\
+    results[2].z += fl2.x * fr2.x;\
+    results[2].w += fl2.y * fr2.x;\
+\
+    results[3].x += fl1.x * fr2.y;\
+    results[3].y += fl1.y * fr2.y;\
+    results[3].z += fl2.x * fr2.y;\
+    results[3].w += fl2.y * fr2.y;\
+
+    __syncthreads();
+
+    // Do the multiplies.
+    #pragma unroll
+    for (int koff = 0; koff < 16; koff ++) {
+      // 32 x threads.
+      float2 fl1 = lhs_shmem2[koff][threadIdx.x];
+      float2 fl2 = lhs_shmem2[koff + 16][threadIdx.x];
+
+      int start_feature = threadIdx.y * 4;
+      float2 fr1 = rhs_shmem2[(start_feature>>1) + 32*((koff%4)/2)][koff/4 + (koff%2)*4];
+      float2 fr2 = rhs_shmem2[(start_feature>>1) + 1 + 32*((koff%4)/2)][koff/4 + (koff%2)*4];
+
+      add_vals(fl1, fl2, fr1, fr2)
+    }
+    __syncthreads();
+  }
+
+#undef prefetch_lhs
+#undef add_vals
+
+  Index horiz_base = threadIdx.y*4+base_n;
+  if (!CHECK_LHS_BOUNDARY && !CHECK_RHS_BOUNDARY) {
+    for (int i = 0; i < 4; i++) {
+      output(lhs_vert, horiz_base + i) = results[i].x;
+      output(lhs_vert + 1, horiz_base + i) = results[i].y;
+      output(lhs_vert + 2, horiz_base + i) = results[i].z;
+      output(lhs_vert + 3, horiz_base + i) = results[i].w;
+    }
+  } else if (!CHECK_RHS_BOUNDARY) {
+    // CHECK LHS
+    if (lhs_vert + 3 < m_size) {
+      for (int i = 0; i < 4; i++) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+        output(lhs_vert + 1, horiz_base + i) = results[i].y;
+        output(lhs_vert + 2, horiz_base + i) = results[i].z;
+        output(lhs_vert + 3, horiz_base + i) = results[i].w;
+      }
+    } else if (lhs_vert + 2 < m_size) {
+      for (int i = 0; i < 4; i++) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+        output(lhs_vert + 1, horiz_base + i) = results[i].y;
+        output(lhs_vert + 2, horiz_base + i) = results[i].z;
+      }
+    } else if (lhs_vert + 1 < m_size) {
+      for (int i = 0; i < 4; i++) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+        output(lhs_vert + 1, horiz_base + i) = results[i].y;
+      }
+    } else if (lhs_vert  < m_size) {
+      for (int i = 0; i < 4; i++) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+      }
+    }
+  } else if (!CHECK_LHS_BOUNDARY) {
+    // CHECK RHS
+    /*
+    int ncols_rem = fminf(n_size- horiz_base, 4);
+    for (int i = 0; i < ncols_rem; i++) {
+      output(lhs_vert, horiz_base + i) = results[i].x;
+      output(lhs_vert + 1, horiz_base + i) = results[i].y;
+      output(lhs_vert + 2, horiz_base + i) = results[i].z;
+      output(lhs_vert + 3, horiz_base + i) = results[i].w;
+    }*/
+    for (int i = 0; i < 4; i++) {
+      if (horiz_base+i < n_size) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+        output(lhs_vert + 1, horiz_base + i) = results[i].y;
+        output(lhs_vert + 2, horiz_base + i) = results[i].z;
+        output(lhs_vert + 3, horiz_base + i) = results[i].w;
+       }
+    }
+  } else {
+    // CHECK both boundaries.
+    for (int i = 0; i < 4; i++) {
+      if (horiz_base+i < n_size) {
+        if (lhs_vert < m_size)
+          output(lhs_vert, horiz_base + i) = results[i].x;
+        if (lhs_vert + 1 < m_size)
+          output(lhs_vert + 1, horiz_base + i) = results[i].y;
+        if (lhs_vert + 2 < m_size)
+          output(lhs_vert + 2, horiz_base + i) = results[i].z;
+        if (lhs_vert + 3 < m_size)
+          output(lhs_vert + 3, horiz_base + i) = results[i].w;
+      }
+    }
+  }
+}
+
+
+template<typename Index, typename LhsMapper,
+         typename RhsMapper, typename OutputMapper, bool CHECK_LHS_BOUNDARY,
+         bool CHECK_RHS_BOUNDARY>
+__device__ EIGEN_STRONG_INLINE void
+EigenFloatContractionKernelInternal(const LhsMapper lhs, const RhsMapper rhs,
+                       const OutputMapper output, float2 lhs_shmem2[][32],
+                       float2 rhs_shmem2[][8], const Index m_size,
+                       const Index n_size, const Index k_size,
+                       const Index base_m, const Index base_n) {
+  typedef float Scalar;
+
+  // prefetch registers
+  float4 lhs_pf0, lhs_pf1, lhs_pf2, lhs_pf3;
+  float4 rhs_pf0, rhs_pf1;
+
+  float4 results[8];
+  for (int i=0; i < 8; i++) {
+    results[i].x = results[i].y = results[i].z = results[i].w = 0;
+  }
+
+
+  Index lhs_vert = base_m+threadIdx.x*4+(threadIdx.y%4)*32;
+  for (Index k = 0; k < k_size; k += 32) {
+    lhs_pf0 = internal::pset1<float4>(0);
+    lhs_pf1 = internal::pset1<float4>(0);
+    lhs_pf2 = internal::pset1<float4>(0);
+    lhs_pf3 = internal::pset1<float4>(0);
+
+    rhs_pf0 = internal::pset1<float4>(0);
+    rhs_pf1 = internal::pset1<float4>(0);
+
+     if (!CHECK_LHS_BOUNDARY) {
+      if ((threadIdx.y/4+k+24) < k_size) {
+        lhs_pf0 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k));
+        lhs_pf1 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+8));
+        lhs_pf2 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+16));
+        lhs_pf3 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+24));
+      } else if ((threadIdx.y/4+k+16) < k_size) {
+        lhs_pf0 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k));
+        lhs_pf1 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+8));
+        lhs_pf2 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+16));
+      } else if ((threadIdx.y/4+k+8) < k_size) {
+        lhs_pf0 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k));
+        lhs_pf1 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+8));
+      } else if ((threadIdx.y/4+k) < k_size) {
+        lhs_pf0 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k));
+      }
+    } else {
+      // just CHECK_LHS_BOUNDARY
+      if (lhs_vert + 3 < m_size) {
+        if ((threadIdx.y/4+k+24) < k_size) {
+          lhs_pf0 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k));
+          lhs_pf1 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+8));
+          lhs_pf2 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+16));
+          lhs_pf3 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+24));
+        } else if ((threadIdx.y/4+k+16) < k_size) {
+          lhs_pf0 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k));
+          lhs_pf1 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+8));
+          lhs_pf2 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+16));
+        } else if ((threadIdx.y/4+k+8) < k_size) {
+          lhs_pf0 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k));
+          lhs_pf1 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k+8));
+        } else if ((threadIdx.y/4+k) < k_size) {
+          lhs_pf0 =lhs.loadPacket<Unaligned>(lhs_vert, (threadIdx.y/4+k));
+        }
+      } else if (lhs_vert + 2 < m_size) {
+        if ((threadIdx.y/4+k+24) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf0.y =lhs(lhs_vert + 1, (threadIdx.y/4+k));
+          lhs_pf0.z =lhs(lhs_vert + 2, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+          lhs_pf1.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+8));
+          lhs_pf1.z =lhs(lhs_vert + 2, (threadIdx.y/4+k+8));
+          lhs_pf2.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+16));
+          lhs_pf2.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+16));
+          lhs_pf2.z =lhs(lhs_vert + 2, (threadIdx.y/4+k+16));
+          lhs_pf3.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+24));
+          lhs_pf3.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+24));
+          lhs_pf3.z =lhs(lhs_vert + 2, (threadIdx.y/4+k+24));
+        } else if ((threadIdx.y/4+k+16) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf0.y =lhs(lhs_vert + 1, (threadIdx.y/4+k));
+          lhs_pf0.z =lhs(lhs_vert + 2, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+          lhs_pf1.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+8));
+          lhs_pf1.z =lhs(lhs_vert + 2, (threadIdx.y/4+k+8));
+          lhs_pf2.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+16));
+          lhs_pf2.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+16));
+          lhs_pf2.z =lhs(lhs_vert + 2, (threadIdx.y/4+k+16));
+        } else if ((threadIdx.y/4+k+8) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf0.y =lhs(lhs_vert + 1, (threadIdx.y/4+k));
+          lhs_pf0.z =lhs(lhs_vert + 2, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+          lhs_pf1.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+8));
+          lhs_pf1.z =lhs(lhs_vert + 2, (threadIdx.y/4+k+8));
+        } else if ((threadIdx.y/4+k) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf0.y =lhs(lhs_vert + 1, (threadIdx.y/4+k));
+          lhs_pf0.z =lhs(lhs_vert + 2, (threadIdx.y/4+k));
+        }
+      } else if (lhs_vert + 1 < m_size) {
+        if ((threadIdx.y/4+k+24) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf0.y =lhs(lhs_vert + 1, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+          lhs_pf1.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+8));
+          lhs_pf2.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+16));
+          lhs_pf2.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+16));
+          lhs_pf3.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+24));
+          lhs_pf3.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+24));
+        } else if ((threadIdx.y/4+k+16) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf0.y =lhs(lhs_vert + 1, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+          lhs_pf1.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+8));
+          lhs_pf2.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+16));
+          lhs_pf2.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+16));
+        } else if ((threadIdx.y/4+k+8) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf0.y =lhs(lhs_vert + 1, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+          lhs_pf1.y =lhs(lhs_vert + 1, (threadIdx.y/4+k+8));
+        } else if ((threadIdx.y/4+k) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf0.y =lhs(lhs_vert + 1, (threadIdx.y/4+k));
+        }
+      } else if (lhs_vert < m_size) {
+        if ((threadIdx.y/4+k+24) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+          lhs_pf2.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+16));
+          lhs_pf3.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+24));
+        } else if ((threadIdx.y/4+k+16) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+          lhs_pf2.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+16));
+        } else if ((threadIdx.y/4+k+8) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+          lhs_pf1.x =lhs(lhs_vert + 0, (threadIdx.y/4+k+8));
+        } else if ((threadIdx.y/4+k) < k_size) {
+          lhs_pf0.x =lhs(lhs_vert + 0, (threadIdx.y/4+k));
+        }
+      }
+    }
+    __syncthreads();
+    Index rhs_vert = k+threadIdx.x*4;
+    Index rhs_horiz0 = threadIdx.y*2+base_n;
+    Index rhs_horiz1 = threadIdx.y*2+1+base_n;
+    if (!CHECK_RHS_BOUNDARY) {
+      if ((rhs_vert + 3) < k_size) {
+        // just CHECK_RHS_BOUNDARY
+        rhs_pf0 = rhs.loadPacket<Unaligned>(rhs_vert, rhs_horiz0);
+        rhs_pf1 = rhs.loadPacket<Unaligned>(rhs_vert, rhs_horiz1);
+      } else if (rhs_vert + 2 < k_size) {
+        // just CHECK_RHS_BOUNDARY
+        rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+        rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+        rhs_pf0.z = rhs(rhs_vert + 2, rhs_horiz0);
+        rhs_pf1.x = rhs(rhs_vert, rhs_horiz1);
+        rhs_pf1.y = rhs(rhs_vert + 1, rhs_horiz1);
+        rhs_pf1.z = rhs(rhs_vert + 2, rhs_horiz1);
+      } else if (rhs_vert + 1 < k_size) {
+        rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+        rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+        rhs_pf1.x = rhs(rhs_vert, rhs_horiz1);
+        rhs_pf1.y = rhs(rhs_vert + 1, rhs_horiz1);
+      } else if (rhs_vert  < k_size) {
+        rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+        rhs_pf1.x = rhs(rhs_vert, rhs_horiz1);
+      }
+    } else {
+      if (rhs_horiz1 < n_size) {
+        if ((rhs_vert + 3) < k_size) {
+          // just CHECK_RHS_BOUNDARY
+          rhs_pf0 = rhs.loadPacket<Unaligned>(rhs_vert, rhs_horiz0);
+          rhs_pf1 = rhs.loadPacket<Unaligned>(rhs_vert, rhs_horiz1);
+        } else if (rhs_vert + 2 < k_size) {
+          // just CHECK_RHS_BOUNDARY
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+          rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+          rhs_pf0.z = rhs(rhs_vert + 2, rhs_horiz0);
+          rhs_pf1.x = rhs(rhs_vert, rhs_horiz1);
+          rhs_pf1.y = rhs(rhs_vert + 1, rhs_horiz1);
+          rhs_pf1.z = rhs(rhs_vert + 2, rhs_horiz1);
+        } else if (k+threadIdx.x*4 + 1 < k_size) {
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+          rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+          rhs_pf1.x = rhs(rhs_vert, rhs_horiz1);
+          rhs_pf1.y = rhs(rhs_vert + 1, rhs_horiz1);
+        } else if (k+threadIdx.x*4  < k_size) {
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+          rhs_pf1.x = rhs(rhs_vert, rhs_horiz1);
+        }
+      } else if (rhs_horiz0 < n_size) {
+        if ((rhs_vert + 3) < k_size) {
+          // just CHECK_RHS_BOUNDARY
+          rhs_pf0 = rhs.loadPacket<Unaligned>(rhs_vert, rhs_horiz0);
+        } else if ((rhs_vert + 2) < k_size) {
+          // just CHECK_RHS_BOUNDARY
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+          rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+          rhs_pf0.z = rhs(rhs_vert + 2, rhs_horiz0);
+        } else if ((rhs_vert + 1) < k_size) {
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+          rhs_pf0.y = rhs(rhs_vert + 1, rhs_horiz0);
+        } else if (rhs_vert  < k_size) {
+          rhs_pf0.x = rhs(rhs_vert, rhs_horiz0);
+        }
+      }
+    }
+    __syncthreads();
+    // Loaded. Do computation
+    // Row 0 -> times (0, 4, 8, .. 28) for features 0, 1.
+    // Row 1 -> times (0, 4, 8, .. 28) for features 2, 3.
+    // ..
+    // Row 31 -> times (0, 4, 8, .. 28) for features 62, 63
+    rhs_shmem2[threadIdx.y][threadIdx.x] = make_float2(rhs_pf0.x, rhs_pf1.x);
+    // Row 32 -> times (1, 5, 9, .. 29) for features 0, 1.
+    // Row 33 -> times (1, 5, 9, .. 29) for features 2, 3.
+    // ..
+    rhs_shmem2[threadIdx.y+32][threadIdx.x] = make_float2(rhs_pf0.y, rhs_pf1.y);
+    // Row 64 -> times (2, 6, 10, .. 30) for features 0, 1.
+    // Row 65 -> times (2, 6, 10, .. 30) for features 2, 3.
+    rhs_shmem2[threadIdx.y+64][threadIdx.x] = make_float2(rhs_pf0.z, rhs_pf1.z);
+    // Row 96 -> times (3, 7, 11, .. 31) for features 0, 1.
+    // Row 97 -> times (3, 7, 11, .. 31) for features 2, 3.
+    rhs_shmem2[threadIdx.y+96][threadIdx.x] = make_float2(rhs_pf0.w, rhs_pf1.w);
+
+    // LHS.
+    // Row 0 (time 0) -> features (0, 1), (4, 5), .. (28, 29), (32, 33), ..  (60, 61) .. (124, 125)
+    // Row 1 (time 1) -> features (0, 1), (4, 5), .. (28, 29), (32, 33), ..  (60, 61) .. (124, 125)
+    // ...
+    // Row 8 (time 0) -> features (2, 3), (6, 7), .. (30, 31), (34, 35), ..  (62, 63) .. (126, 127)
+    // Row 15 (time 7) -> features (2, 3), (6, 7), .. (30, 31), (34, 35), ..  (62, 63) .. (126, 127)
+
+
+#define add_vals(a_feat1, a_feat2, f1, f2, f3, f4)\
+      results[0].x += a_feat1.x * f1.x;\
+      results[1].x += a_feat1.x * f1.y;\
+      results[2].x += a_feat1.x * f2.x;\
+      results[3].x += a_feat1.x * f2.y;\
+      results[4].x += a_feat1.x * f3.x;\
+      results[5].x += a_feat1.x * f3.y;\
+      results[6].x += a_feat1.x * f4.x;\
+      results[7].x += a_feat1.x * f4.y;\
+\
+      results[0].y += a_feat1.y * f1.x;\
+      results[1].y += a_feat1.y * f1.y;\
+      results[2].y += a_feat1.y * f2.x;\
+      results[3].y += a_feat1.y * f2.y;\
+      results[4].y += a_feat1.y * f3.x;\
+      results[5].y += a_feat1.y * f3.y;\
+      results[6].y += a_feat1.y * f4.x;\
+      results[7].y += a_feat1.y * f4.y;\
+\
+      results[0].z += a_feat2.x * f1.x;\
+      results[1].z += a_feat2.x * f1.y;\
+      results[2].z += a_feat2.x * f2.x;\
+      results[3].z += a_feat2.x * f2.y;\
+      results[4].z += a_feat2.x * f3.x;\
+      results[5].z += a_feat2.x * f3.y;\
+      results[6].z += a_feat2.x * f4.x;\
+      results[7].z += a_feat2.x * f4.y;\
+\
+      results[0].w += a_feat2.y * f1.x;\
+      results[1].w += a_feat2.y * f1.y;\
+      results[2].w += a_feat2.y * f2.x;\
+      results[3].w += a_feat2.y * f2.y;\
+      results[4].w += a_feat2.y * f3.x;\
+      results[5].w += a_feat2.y * f3.y;\
+      results[6].w += a_feat2.y * f4.x;\
+      results[7].w += a_feat2.y * f4.y;\
+
+    lhs_shmem2[threadIdx.y/4][threadIdx.x+(threadIdx.y%4)*8] = make_float2(lhs_pf0.x, lhs_pf0.y);
+    lhs_shmem2[threadIdx.y/4+8][threadIdx.x+(threadIdx.y%4)*8] = make_float2(lhs_pf1.x, lhs_pf1.y);
+    lhs_shmem2[threadIdx.y/4+16][threadIdx.x+(threadIdx.y%4)*8] = make_float2(lhs_pf2.x, lhs_pf2.y);
+    lhs_shmem2[threadIdx.y/4+24][threadIdx.x+(threadIdx.y%4)*8] = make_float2(lhs_pf3.x, lhs_pf3.y);
+
+    lhs_shmem2[threadIdx.y/4 + 32][threadIdx.x+(threadIdx.y%4)*8] = make_float2(lhs_pf0.z, lhs_pf0.w);
+    lhs_shmem2[threadIdx.y/4 + 40][threadIdx.x+(threadIdx.y%4)*8] = make_float2(lhs_pf1.z, lhs_pf1.w);
+    lhs_shmem2[threadIdx.y/4 + 48][threadIdx.x+(threadIdx.y%4)*8] = make_float2(lhs_pf2.z, lhs_pf2.w);
+    lhs_shmem2[threadIdx.y/4 + 56][threadIdx.x+(threadIdx.y%4)*8] = make_float2(lhs_pf3.z, lhs_pf3.w);
+
+    __syncthreads();
+
+    // Do the multiplies.
+    #pragma unroll
+    for (int koff = 0; koff < 32; koff ++) {
+      float2 a3 = lhs_shmem2[koff][threadIdx.x + (threadIdx.y % 4) * 8];
+      float2 a4 = lhs_shmem2[koff + 32][threadIdx.x + (threadIdx.y % 4) * 8];
+
+      // first feature is at (threadIdx.y/4) * 8 last is at start + 8.
+      int start_feature = (threadIdx.y / 4) * 8;
+
+      float2 br1 = rhs_shmem2[start_feature/2 +     (koff % 4) * 32][koff/4];
+      float2 br2 = rhs_shmem2[start_feature/2 + 1 + (koff % 4) * 32][koff/4];
+      float2 br3 = rhs_shmem2[start_feature/2 + 2 + (koff % 4) * 32][koff/4];
+      float2 br4 = rhs_shmem2[start_feature/2 + 3 + (koff % 4) * 32][koff/4];
+
+      add_vals(a3, a4, br1, br2, br3, br4)
+    }
+    __syncthreads();
+  } // end loop over k
+
+
+  __syncthreads();
+  Index horiz_base = (threadIdx.y/4)*8+base_n;
+  if (!CHECK_LHS_BOUNDARY && !CHECK_RHS_BOUNDARY) {
+    for (int i = 0; i < 8; i++) {
+      output(lhs_vert, horiz_base + i) = results[i].x;
+      output(lhs_vert + 1, horiz_base + i) = results[i].y;
+      output(lhs_vert + 2, horiz_base + i) = results[i].z;
+      output(lhs_vert + 3, horiz_base + i) = results[i].w;
+    }
+  } else if (!CHECK_RHS_BOUNDARY) {
+    if (lhs_vert + 3 < m_size) {
+      for (int i = 0; i < 8; i++) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+        output(lhs_vert + 1, horiz_base + i) = results[i].y;
+        output(lhs_vert + 2, horiz_base + i) = results[i].z;
+        output(lhs_vert + 3, horiz_base + i) = results[i].w;
+      }
+    } else if (lhs_vert + 2 < m_size) {
+      for (int i = 0; i < 8; i++) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+        output(lhs_vert + 1, horiz_base + i) = results[i].y;
+        output(lhs_vert + 2, horiz_base + i) = results[i].z;
+      }
+    } else if (lhs_vert + 1 < m_size) {
+      for (int i = 0; i < 8; i++) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+        output(lhs_vert + 1, horiz_base + i) = results[i].y;
+      }
+    } else if (lhs_vert  < m_size) {
+      for (int i = 0; i < 8; i++) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+      }
+    }
+  } else if (!CHECK_LHS_BOUNDARY) {
+    // CHECK BOUNDARY_B
+    for (int i = 0; i < 8; i++) {
+      if (horiz_base + i < n_size) {
+        output(lhs_vert, horiz_base + i) = results[i].x;
+        output(lhs_vert + 1, horiz_base + i) = results[i].y;
+        output(lhs_vert + 2, horiz_base + i) = results[i].z;
+        output(lhs_vert + 3, horiz_base + i) = results[i].w;
+      }
+    }
+  } else {
+    // CHECK both boundaries.
+    for (int i = 0; i < 8; i++) {
+      if (horiz_base + i < n_size) {
+        if (lhs_vert < m_size)
+          output(lhs_vert, horiz_base + i) = results[i].x;
+        if (lhs_vert + 1 < m_size)
+          output(lhs_vert + 1, horiz_base + i) = results[i].y;
+        if (lhs_vert + 2 < m_size)
+          output(lhs_vert + 2, horiz_base + i) = results[i].z;
+        if (lhs_vert + 3 < m_size)
+          output(lhs_vert + 3, horiz_base + i) = results[i].w;
+      }
+    }
+  }
+}
+
+
+template<typename Index, typename LhsMapper,
+         typename RhsMapper, typename OutputMapper>
+__global__ void
+__launch_bounds__(256)
+EigenFloatContractionKernel(const LhsMapper lhs, const RhsMapper rhs,
+                       const OutputMapper output,
+                       const Index m_size, const Index n_size, const Index k_size) {
+  __shared__ float2 lhs_shmem[64*32];
+  __shared__ float2 rhs_shmem[128*8];
+
+  typedef float2 LHS_MEM[64][32];
+  typedef float2 RHS_MEM[128][8];
+
+  typedef float2 LHS_MEM16x16[32][16];
+  typedef float2 RHS_MEM16x16[64][8];
+
+  const Index m_block_idx = blockIdx.x;
+  const Index n_block_idx = blockIdx.y;
+
+  const Index base_m = 128 * m_block_idx;
+  const Index base_n = 64 * n_block_idx;
+
+  bool check_rhs = (base_n + 63) >= n_size;
+  bool check_lhs128 = (base_m + 127) >= m_size;
+
+  if (!check_rhs) {
+    if (!check_lhs128) {
+      // >= 128 rows left
+      EigenFloatContractionKernelInternal<Index, LhsMapper, RhsMapper, OutputMapper, false, false>(
+                     lhs, rhs, output, *((LHS_MEM *) lhs_shmem), *((RHS_MEM *) rhs_shmem), m_size, n_size, k_size, base_m, base_n);
+    } else {
+      EigenFloatContractionKernelInternal<Index, LhsMapper, RhsMapper, OutputMapper, true, false>(
+                     lhs, rhs, output, *((LHS_MEM *) lhs_shmem), *((RHS_MEM *) rhs_shmem), m_size, n_size, k_size, base_m, base_n);
+    }
+  } else {
+    if (!check_lhs128) {
+      // >= 128 rows left
+      EigenFloatContractionKernelInternal<Index, LhsMapper, RhsMapper, OutputMapper, false, true>(
+                     lhs, rhs, output, *((LHS_MEM *) lhs_shmem), *((RHS_MEM *) rhs_shmem), m_size, n_size, k_size, base_m, base_n);
+    } else {
+      EigenFloatContractionKernelInternal<Index, LhsMapper, RhsMapper, OutputMapper, true, true>(
+                     lhs, rhs, output, *((LHS_MEM *) lhs_shmem), *((RHS_MEM *) rhs_shmem), m_size, n_size, k_size, base_m, base_n);
+    }
+  }
+}
+
+template<typename Index, typename LhsMapper,
+         typename RhsMapper, typename OutputMapper>
+__global__ void
+__launch_bounds__(256)
+EigenFloatContractionKernel16x16(const LhsMapper lhs, const RhsMapper rhs,
+                       const OutputMapper output,
+                       const Index m_size, const Index n_size, const Index k_size) {
+  __shared__ float2 lhs_shmem[32][16];
+  __shared__ float2 rhs_shmem[64][8];
+
+  const Index m_block_idx = blockIdx.x;
+  const Index n_block_idx = blockIdx.y;
+
+  const Index base_m = 64 * m_block_idx;
+  const Index base_n = 64 * n_block_idx;
+
+  if (base_m + 63 < m_size) {
+    if (base_n + 63 < n_size) {
+      EigenFloatContractionKernelInternal16x16<Index, LhsMapper, RhsMapper, OutputMapper, false, false>(lhs, rhs, output, lhs_shmem, rhs_shmem, m_size, n_size, k_size, base_m, base_n);
+    } else {
+      EigenFloatContractionKernelInternal16x16<Index, LhsMapper, RhsMapper, OutputMapper, false, true>(lhs, rhs, output, lhs_shmem, rhs_shmem, m_size, n_size, k_size, base_m, base_n);
+    }
+  } else {
+    if (base_n + 63 < n_size) {
+      EigenFloatContractionKernelInternal16x16<Index, LhsMapper, RhsMapper, OutputMapper, true, false>(lhs, rhs, output, lhs_shmem, rhs_shmem, m_size, n_size, k_size, base_m, base_n);
+    } else {
+      EigenFloatContractionKernelInternal16x16<Index, LhsMapper, RhsMapper, OutputMapper, true, true>(lhs, rhs, output, lhs_shmem, rhs_shmem, m_size, n_size, k_size, base_m, base_n);
+    }
+  }
+}
+
+
+template<typename Indices, typename LeftArgType, typename RightArgType>
+struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, GpuDevice> :
+    public TensorContractionEvaluatorBase<TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, GpuDevice> > {
+
+  typedef GpuDevice Device;
+
+  typedef TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, Device> Self;
+  typedef TensorContractionEvaluatorBase<Self> Base;
+
+  typedef TensorContractionOp<Indices, LeftArgType, RightArgType> XprType;
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, GpuDevice>::type PacketReturnType;
+
+  enum {
+    Layout = TensorEvaluator<LeftArgType, Device>::Layout,
+  };
+
+  // Most of the code is assuming that both input tensors are ColMajor. If the
+  // inputs are RowMajor, we will "cheat" by swapping the LHS and RHS:
+  // If we want to compute A * B = C, where A is LHS and B is RHS, the code
+  // will pretend B is LHS and A is RHS.
+  typedef typename internal::conditional<
+    static_cast<int>(Layout) == static_cast<int>(ColMajor), LeftArgType, RightArgType>::type EvalLeftArgType;
+  typedef typename internal::conditional<
+    static_cast<int>(Layout) == static_cast<int>(ColMajor), RightArgType, LeftArgType>::type EvalRightArgType;
+
+  static const int LDims =
+      internal::array_size<typename TensorEvaluator<EvalLeftArgType, Device>::Dimensions>::value;
+  static const int RDims =
+      internal::array_size<typename TensorEvaluator<EvalRightArgType, Device>::Dimensions>::value;
+  static const int ContractDims = internal::array_size<Indices>::value;
+
+  typedef array<Index, LDims> left_dim_mapper_t;
+  typedef array<Index, RDims> right_dim_mapper_t;
+
+  typedef array<Index, ContractDims> contract_t;
+  typedef array<Index, LDims - ContractDims> left_nocontract_t;
+  typedef array<Index, RDims - ContractDims> right_nocontract_t;
+
+  static const int NumDims = LDims + RDims - 2 * ContractDims;
+
+  typedef DSizes<Index, NumDims> Dimensions;
+
+  // typedefs needed in evalTo
+  typedef typename internal::remove_const<typename EvalLeftArgType::Scalar>::type LhsScalar;
+  typedef typename internal::remove_const<typename EvalRightArgType::Scalar>::type RhsScalar;
+
+  typedef TensorEvaluator<EvalLeftArgType, Device> LeftEvaluator;
+  typedef TensorEvaluator<EvalRightArgType, Device> RightEvaluator;
+
+  typedef typename LeftEvaluator::Dimensions LeftDimensions;
+  typedef typename RightEvaluator::Dimensions RightDimensions;
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device) :
+      Base(op, device) {}
+
+  // We need to redefine this method to make nvcc happy
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) {
+    this->m_leftImpl.evalSubExprsIfNeeded(NULL);
+    this->m_rightImpl.evalSubExprsIfNeeded(NULL);
+    if (data) {
+      evalTo(data);
+      return false;
+    } else {
+      this->m_result = static_cast<Scalar *>(this->m_device.allocate(this->dimensions().TotalSize() * sizeof(Scalar)));
+      evalTo(this->m_result);
+      return true;
+    }
+  }
+
+  void evalTo(Scalar* buffer) const {
+    if (this->m_lhs_inner_dim_contiguous) {
+      if (this->m_rhs_inner_dim_contiguous) {
+        if (this->m_rhs_inner_dim_reordered) {
+          evalTyped<true, true, true, Unaligned>(buffer);
+        }
+        else {
+          evalTyped<true, true, false, Unaligned>(buffer);
+        }
+      }
+      else {
+       if (this->m_rhs_inner_dim_reordered) {
+          evalTyped<true, false, true, Unaligned>(buffer);
+        }
+        else {
+          evalTyped<true, false, false, Unaligned>(buffer);
+        }
+      }
+    }
+    else {
+      if (this->m_rhs_inner_dim_contiguous) {
+        if (this->m_rhs_inner_dim_reordered) {
+          evalTyped<false, true, true, Unaligned>(buffer);
+        }
+        else {
+          evalTyped<false, true, false, Unaligned>(buffer);
+        }
+      }
+      else {
+       if (this->m_rhs_inner_dim_reordered) {
+          evalTyped<false, false, true, Unaligned>(buffer);
+        }
+        else {
+          evalTyped<false, false, false, Unaligned>(buffer);
+        }
+      }
+    }
+  }
+
+  template <typename LhsScalar, typename RhsScalar, typename Index, typename LhsMapper, typename RhsMapper, typename OutputMapper> struct LaunchKernels {
+    static void Run(const LhsMapper& lhs, const RhsMapper& rhs, const OutputMapper& output, Index m, Index n, Index k, const GpuDevice& device) {
+    const Index m_blocks = (m + 63) / 64;
+    const Index n_blocks = (n + 63) / 64;
+    const dim3 num_blocks(m_blocks, n_blocks, 1);
+    const dim3 block_size(8, 8, 8);
+    LAUNCH_CUDA_KERNEL((EigenContractionKernel<Scalar, Index, LhsMapper, RhsMapper, OutputMapper>), num_blocks, block_size, 0, device, lhs, rhs, output, m, n, k);
+    }
+  };
+
+  template <typename Index, typename LhsMapper, typename RhsMapper, typename OutputMapper> struct LaunchKernels<float, float, Index, LhsMapper, RhsMapper, OutputMapper> {
+    static void Run(const LhsMapper& lhs, const RhsMapper& rhs, const OutputMapper& output, Index m, Index n, Index k, const GpuDevice& device) {
+      if (m < 768 || n < 768) {
+        const Index m_blocks = (m + 63) / 64;
+        const Index n_blocks = (n + 63) / 64;
+        const dim3 num_blocks(m_blocks, n_blocks, 1);
+        const dim3 block_size(16, 16, 1);
+        LAUNCH_CUDA_KERNEL((EigenFloatContractionKernel16x16<Index, LhsMapper, RhsMapper, OutputMapper>), num_blocks, block_size, 0, device, lhs, rhs, output, m, n, k);
+      } else {
+        const Index m_blocks = (m + 127) / 128;
+        const Index n_blocks = (n + 63) / 64;
+        const dim3 num_blocks(m_blocks, n_blocks, 1);
+        const dim3 block_size(8, 32, 1);
+        LAUNCH_CUDA_KERNEL((EigenFloatContractionKernel<Index, LhsMapper, RhsMapper, OutputMapper>), num_blocks, block_size, 0, device, lhs, rhs, output, m, n, k);
+      }
+    }
+  };
+
+  template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous, bool rhs_inner_dim_reordered, int Alignment>
+  void evalTyped(Scalar* buffer) const {
+    // columns in left side, rows in right side
+    const Index k = this->m_k_size;
+    EIGEN_UNUSED_VARIABLE(k)
+
+    // rows in left side
+    const Index m = this->m_i_size;
+
+    // columns in right side
+    const Index n = this->m_j_size;
+
+    // zero out the result buffer (which must be of size at least m * n * sizeof(Scalar)
+    this->m_device.memset(buffer, 0, m * n * sizeof(Scalar));
+
+    typedef internal::TensorContractionInputMapper<LhsScalar, Index, internal::Lhs,
+                                                   LeftEvaluator, left_nocontract_t,
+                                                   contract_t, 4,
+                                                   lhs_inner_dim_contiguous,
+                                                   false, Unaligned> LhsMapper;
+
+    typedef internal::TensorContractionInputMapper<RhsScalar, Index, internal::Rhs,
+                                                   RightEvaluator, right_nocontract_t,
+                                                   contract_t, 4,
+                                                   rhs_inner_dim_contiguous,
+                                                   rhs_inner_dim_reordered, Unaligned> RhsMapper;
+
+    typedef internal::blas_data_mapper<Scalar, Index, ColMajor> OutputMapper;
+
+
+    // initialize data mappers
+    LhsMapper lhs(this->m_leftImpl, this->m_left_nocontract_strides, this->m_i_strides,
+                  this->m_left_contracting_strides, this->m_k_strides);
+
+    RhsMapper rhs(this->m_rightImpl, this->m_right_nocontract_strides, this->m_j_strides,
+                  this->m_right_contracting_strides, this->m_k_strides);
+
+    OutputMapper output(buffer, m);
+
+    setCudaSharedMemConfig(cudaSharedMemBankSizeEightByte);
+    LaunchKernels<LhsScalar, RhsScalar, Index, LhsMapper, RhsMapper, OutputMapper>::Run(lhs, rhs, output,  m, n, k, this->m_device);
+  }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_USE_GPU and __CUDACC__
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_CUDA_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionMapper.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionMapper.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionMapper.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionMapper.h
@@ -0,0 +1,467 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_MAPPER_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_MAPPER_H
+
+namespace Eigen {
+
+namespace internal {
+
+enum {
+  Rhs = 0,
+  Lhs = 1
+};
+
+/*
+ * Implementation of the Eigen blas_data_mapper class for tensors.
+ */
+
+template <typename Tensor, bool HasRawAccess> struct CoeffLoader {
+  enum {
+    DirectOffsets = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE CoeffLoader(const Tensor& tensor) : m_tensor(tensor) { }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void offsetBuffer(typename Tensor::Index) {
+    eigen_assert(false && "unsupported");
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE typename Tensor::Scalar coeff(typename Tensor::Index index) const { return m_tensor.coeff(index); }
+
+ template<int LoadMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+ typename Tensor::PacketReturnType packet(typename Tensor::Index index) const
+  {
+    return m_tensor.template packet<LoadMode>(index);
+  }
+
+
+ private:
+  const Tensor m_tensor;
+};
+
+template <typename Tensor> struct CoeffLoader<Tensor, true> {
+  enum {
+    DirectOffsets = true
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE CoeffLoader(const Tensor& tensor) : m_data(tensor.data()) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void offsetBuffer(typename Tensor::Index offset) {
+    m_data += offset;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE typename Tensor::Scalar coeff(typename Tensor::Index index) const { return loadConstant(m_data+index); }
+
+ template<int LoadMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+ typename Tensor::PacketReturnType packet(typename Tensor::Index index) const
+  {
+    return internal::ploadt_ro<typename Tensor::PacketReturnType, LoadMode>(m_data + index);
+  }
+ private:
+  typedef typename Tensor::Scalar Scalar;
+  const Scalar* m_data;
+};
+
+template<typename Scalar, typename Index, int side,
+         typename Tensor,
+         typename nocontract_t, typename contract_t,
+         int packet_size, bool inner_dim_contiguous, int Alignment>
+class SimpleTensorContractionMapper {
+  public:
+  EIGEN_DEVICE_FUNC
+  SimpleTensorContractionMapper(const Tensor& tensor,
+                                const nocontract_t& nocontract_strides,
+                                const nocontract_t& ij_strides,
+                                const contract_t& contract_strides,
+                                const contract_t& k_strides) :
+      m_tensor(tensor),
+      m_nocontract_strides(nocontract_strides),
+      m_ij_strides(ij_strides),
+      m_contract_strides(contract_strides),
+      m_k_strides(k_strides) { }
+
+  enum {
+    DirectOffsets = CoeffLoader<Tensor, Tensor::RawAccess>::DirectOffsets
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void offsetBuffer(typename Tensor::Index offset) {
+    m_tensor.offsetBuffer(offset);
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE void prefetch(Index /*i*/) { }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE Scalar operator()(Index row) const {
+    // column major assumption
+    return operator()(row, 0);
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE Scalar operator()(Index row, Index col) const {
+    return m_tensor.coeff(computeIndex(row, col));
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE Index computeIndex(Index row, Index col) const {
+    const bool left = (side == Lhs);
+    Index nocontract_val = left ? row : col;
+    Index linidx = 0;
+    for (int i = static_cast<int>(array_size<nocontract_t>::value) - 1; i > 0; i--) {
+      const Index idx = nocontract_val / m_ij_strides[i];
+      linidx += idx * m_nocontract_strides[i];
+      nocontract_val -= idx * m_ij_strides[i];
+    }
+    if (array_size<typename Tensor::Dimensions>::value > array_size<contract_t>::value) {
+      if (side == Lhs && inner_dim_contiguous) {
+        eigen_assert(m_nocontract_strides[0] == 1);
+        linidx += nocontract_val;
+      } else {
+        linidx += nocontract_val * m_nocontract_strides[0];
+      }
+    }
+
+    Index contract_val = left ? col : row;
+    if(array_size<contract_t>::value > 0) {
+      for (int i = static_cast<int>(array_size<contract_t>::value) - 1; i > 0; i--) {
+        const Index idx = contract_val / m_k_strides[i];
+        linidx += idx * m_contract_strides[i];
+        contract_val -= idx * m_k_strides[i];
+      }
+
+      if (side == Rhs && inner_dim_contiguous) {
+        eigen_assert(m_contract_strides[0] == 1);
+        linidx += contract_val;
+      } else {
+        linidx += contract_val * m_contract_strides[0];
+      }
+    }
+
+    return linidx;
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE IndexPair<Index> computeIndexPair(Index row, Index col, const Index distance) const {
+    const bool left = (side == Lhs);
+    Index nocontract_val[2] = {left ? row : col, left ? row + distance : col};
+    Index linidx[2] = {0, 0};
+    if (array_size<typename Tensor::Dimensions>::value > array_size<contract_t>::value) {
+      for (int i = static_cast<int>(array_size<nocontract_t>::value) - 1; i > 0; i--) {
+        const Index idx0 = nocontract_val[0] / m_ij_strides[i];
+        const Index idx1 = nocontract_val[1] / m_ij_strides[i];
+        linidx[0] += idx0 * m_nocontract_strides[i];
+        linidx[1] += idx1 * m_nocontract_strides[i];
+        nocontract_val[0] -= idx0 * m_ij_strides[i];
+        nocontract_val[1] -= idx1 * m_ij_strides[i];
+      }
+      if (side == Lhs && inner_dim_contiguous) {
+        eigen_assert(m_nocontract_strides[0] == 1);
+        linidx[0] += nocontract_val[0];
+        linidx[1] += nocontract_val[1];
+      } else {
+        linidx[0] += nocontract_val[0] * m_nocontract_strides[0];
+        linidx[1] += nocontract_val[1] * m_nocontract_strides[0];
+      }
+    }
+
+    Index contract_val[2] = {left ? col : row, left ? col : row + distance};
+    if (array_size<contract_t>::value> 0) {
+      for (int i = static_cast<int>(array_size<contract_t>::value) - 1; i > 0; i--) {
+        const Index idx0 = contract_val[0] / m_k_strides[i];
+        const Index idx1 = contract_val[1] / m_k_strides[i];
+        linidx[0] += idx0 * m_contract_strides[i];
+        linidx[1] += idx1 * m_contract_strides[i];
+        contract_val[0] -= idx0 * m_k_strides[i];
+        contract_val[1] -= idx1 * m_k_strides[i];
+      }
+
+      if (side == Rhs && inner_dim_contiguous) {
+        eigen_assert(m_contract_strides[0] == 1);
+        linidx[0] += contract_val[0];
+        linidx[1] += contract_val[1];
+      } else {
+        linidx[0] += contract_val[0] * m_contract_strides[0];
+        linidx[1] += contract_val[1] * m_contract_strides[0];
+      }
+    }
+    return IndexPair<Index>(linidx[0], linidx[1]);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Index firstAligned(Index size) const {
+    // Only claim alignment when we can compute the actual stride (ie when we're
+    // dealing with the lhs with inner_dim_contiguous. This is because the
+    // matrix-vector product relies on the stride when dealing with aligned inputs.
+    return (Alignment == Aligned) && (side == Lhs) && inner_dim_contiguous ? 0 : size;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Index stride() const {
+    return ((side == Lhs) && inner_dim_contiguous && array_size<contract_t>::value > 0) ? m_contract_strides[0] : 1;
+  }
+
+ protected:
+  CoeffLoader<Tensor, Tensor::RawAccess> m_tensor;
+  const nocontract_t m_nocontract_strides;
+  const nocontract_t m_ij_strides;
+  const contract_t m_contract_strides;
+  const contract_t m_k_strides;
+};
+
+
+template<typename Scalar, typename Index, int side,
+         typename Tensor,
+         typename nocontract_t, typename contract_t,
+         int packet_size, bool inner_dim_contiguous,
+         bool inner_dim_reordered, int Alignment>
+class BaseTensorContractionMapper : public SimpleTensorContractionMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, packet_size, inner_dim_contiguous, Alignment>
+{
+ public:
+  typedef SimpleTensorContractionMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, packet_size, inner_dim_contiguous, Alignment> ParentMapper;
+
+  EIGEN_DEVICE_FUNC
+  BaseTensorContractionMapper(const Tensor& tensor,
+                              const nocontract_t& nocontract_strides,
+                              const nocontract_t& ij_strides,
+                              const contract_t& contract_strides,
+                              const contract_t& k_strides) :
+  ParentMapper(tensor, nocontract_strides, ij_strides, contract_strides, k_strides) { }
+
+  typedef typename Tensor::PacketReturnType Packet;
+  typedef typename unpacket_traits<Packet>::half HalfPacket;
+
+  template <int AlignmentType>
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE Packet loadPacket(Index i, Index j) const {
+    // whole method makes column major assumption
+
+    // don't need to add offsets for now (because operator handles that)
+    // current code assumes packet size must be a multiple of 2
+    EIGEN_STATIC_ASSERT(packet_size % 2 == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    if (Tensor::PacketAccess && inner_dim_contiguous && !inner_dim_reordered) {
+      const Index index = this->computeIndex(i, j);
+      eigen_assert(this->computeIndex(i+packet_size-1, j) == index + packet_size-1);
+      return this->m_tensor.template packet<AlignmentType>(index);
+    }
+
+    const IndexPair<Index> indexPair = this->computeIndexPair(i, j, packet_size - 1);
+    const Index first = indexPair.first;
+    const Index last = indexPair.second;
+
+    // We can always do optimized packet reads from left hand side right now, because
+    // the vertical matrix dimension on the left hand side is never contracting.
+    // On the right hand side we need to check if the contracting dimensions may have
+    // been shuffled first.
+    if (Tensor::PacketAccess &&
+        (side == Lhs || internal::array_size<contract_t>::value <= 1 || !inner_dim_reordered) &&
+        (last - first) == (packet_size - 1)) {
+
+      return this->m_tensor.template packet<AlignmentType>(first);
+    }
+
+    EIGEN_ALIGN_MAX Scalar data[packet_size];
+
+    data[0] = this->m_tensor.coeff(first);
+    for (Index k = 1; k < packet_size - 1; k += 2) {
+      const IndexPair<Index> internal_pair = this->computeIndexPair(i + k, j, 1);
+      data[k] = this->m_tensor.coeff(internal_pair.first);
+      data[k + 1] = this->m_tensor.coeff(internal_pair.second);
+    }
+    data[packet_size - 1] = this->m_tensor.coeff(last);
+
+    return pload<Packet>(data);
+  }
+
+  template <int AlignmentType>
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE HalfPacket loadHalfPacket(Index i, Index j) const {
+    // whole method makes column major assumption
+
+    // don't need to add offsets for now (because operator handles that)
+    const Index half_packet_size = unpacket_traits<HalfPacket>::size;
+    if (half_packet_size == packet_size) {
+      return loadPacket<AlignmentType>(i, j);
+    }
+    EIGEN_ALIGN_MAX Scalar data[half_packet_size];
+    for (Index k = 0; k < half_packet_size; k++) {
+      data[k] = operator()(i + k, j);
+    }
+    return pload<HalfPacket>(data);
+  }
+};
+
+
+template<typename Scalar, typename Index, int side,
+         typename Tensor,
+         typename nocontract_t, typename contract_t,
+         bool inner_dim_contiguous,
+         bool inner_dim_reordered, int Alignment>
+class BaseTensorContractionMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, 1, inner_dim_contiguous, inner_dim_reordered, Alignment> : public SimpleTensorContractionMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, 1, inner_dim_contiguous, Alignment>
+{
+ public:
+  typedef SimpleTensorContractionMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, 1, inner_dim_contiguous, Alignment> ParentMapper;
+
+  EIGEN_DEVICE_FUNC
+  BaseTensorContractionMapper(const Tensor& tensor,
+                              const nocontract_t& nocontract_strides,
+                              const nocontract_t& ij_strides,
+                              const contract_t& contract_strides,
+                              const contract_t& k_strides) :
+  ParentMapper(tensor, nocontract_strides, ij_strides, contract_strides, k_strides) { }
+
+  typedef typename Tensor::PacketReturnType Packet;
+  template <int> EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE Packet loadPacket(Index i, Index j) const {
+    EIGEN_ALIGN_MAX Scalar data[1];
+    data[0] = this->m_tensor.coeff(this->computeIndex(i, j));
+    return pload<typename Tensor::PacketReturnType>(data);
+  }
+  template <int> EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE Packet loadHalfPacket(Index i, Index j) const {
+    return loadPacket(i, j);
+  }
+};
+
+
+template<typename Scalar, typename Index, int side,
+         typename Tensor,
+         typename nocontract_t, typename contract_t,
+         int packet_size,
+         bool inner_dim_contiguous, bool inner_dim_reordered, int Alignment>
+class TensorContractionSubMapper {
+ public:
+  typedef typename Tensor::PacketReturnType Packet;
+  typedef typename unpacket_traits<Packet>::half HalfPacket;
+
+  typedef BaseTensorContractionMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, packet_size, inner_dim_contiguous, inner_dim_reordered, Alignment> ParentMapper;
+  typedef TensorContractionSubMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, packet_size, inner_dim_contiguous, inner_dim_reordered, Alignment> Self;
+  typedef Self LinearMapper;
+
+  enum {
+    // We can use direct offsets iff the parent mapper supports then and we can compute the strides.
+    // TODO: we should also enable direct offsets for the Rhs case.
+    UseDirectOffsets = ParentMapper::DirectOffsets && (side == Lhs) && inner_dim_contiguous && (array_size<contract_t>::value > 0)
+  };
+
+  EIGEN_DEVICE_FUNC TensorContractionSubMapper(const ParentMapper& base_mapper, Index vert_offset, Index horiz_offset)
+      : m_base_mapper(base_mapper), m_vert_offset(vert_offset), m_horiz_offset(horiz_offset) {
+    // Bake the offsets into the buffer used by the base mapper whenever possible. This avoids the need to recompute
+    // this offset every time we attempt to access a coefficient.
+    if (UseDirectOffsets) {
+      Index stride = m_base_mapper.stride();
+      m_base_mapper.offsetBuffer(vert_offset + horiz_offset * stride);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar operator()(Index i) const {
+    if (UseDirectOffsets) {
+      return m_base_mapper(i, 0);
+    }
+    return m_base_mapper(i + m_vert_offset, m_horiz_offset);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar operator()(Index i, Index j) const {
+    if (UseDirectOffsets) {
+      return m_base_mapper(i, j);
+    }
+    return m_base_mapper(i + m_vert_offset, j + m_horiz_offset);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet loadPacket(Index i) const {
+    if (UseDirectOffsets) {
+      return m_base_mapper.template loadPacket<Alignment>(i, 0);
+    }
+    return m_base_mapper.template loadPacket<Alignment>(i + m_vert_offset, m_horiz_offset);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet loadPacket(Index i, Index j) const {
+    if (UseDirectOffsets) {
+      return m_base_mapper.template loadPacket<Alignment>(i, j);
+    }
+    return m_base_mapper.template loadPacket<Alignment>(i + m_vert_offset, j + m_horiz_offset);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE HalfPacket loadHalfPacket(Index i) const {
+    if (UseDirectOffsets) {
+      return m_base_mapper.template loadHalfPacket<Alignment>(i, 0);
+    }
+    return m_base_mapper.template loadHalfPacket<Alignment>(i + m_vert_offset, m_horiz_offset);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacket(Index i, Packet p) const {
+    if (UseDirectOffsets) {
+      m_base_mapper.storePacket(i, 0, p);
+    }
+    m_base_mapper.storePacket(i + m_vert_offset, m_horiz_offset, p);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE LinearMapper getLinearMapper(Index i, Index j) const {
+    if (UseDirectOffsets) {
+      return LinearMapper(m_base_mapper, i, j);
+    }
+    return LinearMapper(m_base_mapper, i + m_vert_offset, j + m_horiz_offset);
+  }
+
+  template <typename PacketT, int AlignmentType>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketT load(Index i) const {
+    EIGEN_STATIC_ASSERT((internal::is_same<PacketT, Packet>::value), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    const int ActualAlignment = (AlignmentType == Aligned) && (Alignment == Aligned) ? Aligned : Unaligned;
+    if (UseDirectOffsets) {
+     return m_base_mapper.template loadPacket<ActualAlignment>(i, 0);
+    }
+    return m_base_mapper.template loadPacket<ActualAlignment>(i + m_vert_offset, m_horiz_offset);
+  }
+
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool aligned(Index) const {
+    return false;
+  }
+
+ private:
+  ParentMapper m_base_mapper;
+  const Index m_vert_offset;
+  const Index m_horiz_offset;
+};
+
+
+template<typename Scalar_, typename Index, int side,
+         typename Tensor,
+         typename nocontract_t, typename contract_t,
+         int packet_size,
+         bool inner_dim_contiguous, bool inner_dim_reordered, int Alignment>
+class TensorContractionInputMapper
+  : public BaseTensorContractionMapper<Scalar_, Index, side, Tensor, nocontract_t, contract_t, packet_size, inner_dim_contiguous, inner_dim_reordered, Alignment> {
+
+ public:
+  typedef Scalar_ Scalar;
+  typedef BaseTensorContractionMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, packet_size, inner_dim_contiguous, inner_dim_reordered, Alignment> Base;
+  typedef TensorContractionSubMapper<Scalar, Index, side, Tensor, nocontract_t, contract_t, packet_size, inner_dim_contiguous, inner_dim_reordered, Alignment> SubMapper;
+  typedef SubMapper VectorMapper;
+
+  EIGEN_DEVICE_FUNC TensorContractionInputMapper(const Tensor& tensor,
+                               const nocontract_t& nocontract_strides,
+                               const nocontract_t& ij_strides,
+                               const contract_t& contract_strides,
+                               const contract_t& k_strides)
+      : Base(tensor, nocontract_strides, ij_strides, contract_strides, k_strides) { }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE SubMapper getSubMapper(Index i, Index j) const {
+    return SubMapper(*this, i, j);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE VectorMapper getVectorMapper(Index i, Index j) const {
+    return VectorMapper(*this, i, j);
+  }
+};
+
+
+
+}  // end namespace internal
+}  // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_MAPPER_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionThreadPool.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionThreadPool.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionThreadPool.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorContractionThreadPool.h
@@ -0,0 +1,1052 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_THREAD_POOL_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_THREAD_POOL_H
+
+// evaluator for thread pool device
+#ifdef EIGEN_USE_THREADS
+
+namespace Eigen {
+
+#ifdef EIGEN_USE_SIMPLE_THREAD_POOL
+namespace internal {
+
+template<typename LhsScalar, typename LhsMapper, typename Index>
+struct packLhsArg {
+  LhsScalar* blockA;
+  const LhsMapper& lhs;
+  const Index m_start;
+  const Index k_start;
+  const Index mc;
+  const Index kc;
+};
+
+template<typename LhsScalar, typename RhsScalar, typename RhsMapper, typename OutputMapper, typename Index>
+struct packRhsAndKernelArg {
+  const MaxSizeVector<LhsScalar*>* blockAs;
+  RhsScalar* blockB;
+  const RhsMapper& rhs;
+  OutputMapper& output;
+  const Index m;
+  const Index k;
+  const Index n;
+  const Index mc;
+  const Index kc;
+  const Index nc;
+  const Index num_threads;
+  const Index num_blockAs;
+  const Index max_m;
+  const Index k_block_idx;
+  const Index m_block_idx;
+  const Index n_block_idx;
+  const Index m_blocks;
+  const Index n_blocks;
+  MaxSizeVector<Notification*>* kernel_notifications;
+  const MaxSizeVector<Notification*>* lhs_notifications;
+  const bool need_to_pack;
+};
+
+}  // end namespace internal
+#endif  // EIGEN_USE_SIMPLE_THREAD_POOL
+
+template<typename Indices, typename LeftArgType, typename RightArgType>
+struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, ThreadPoolDevice> :
+    public TensorContractionEvaluatorBase<TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, ThreadPoolDevice> > {
+
+  typedef ThreadPoolDevice Device;
+
+  typedef TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgType>, Device> Self;
+  typedef TensorContractionEvaluatorBase<Self> Base;
+
+  typedef TensorContractionOp<Indices, LeftArgType, RightArgType> XprType;
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+
+  enum {
+    Layout = TensorEvaluator<LeftArgType, Device>::Layout,
+  };
+
+  // Most of the code is assuming that both input tensors are ColMajor. If the
+  // inputs are RowMajor, we will "cheat" by swapping the LHS and RHS:
+  // If we want to compute A * B = C, where A is LHS and B is RHS, the code
+  // will pretend B is LHS and A is RHS.
+  typedef typename internal::conditional<
+    static_cast<int>(Layout) == static_cast<int>(ColMajor), LeftArgType, RightArgType>::type EvalLeftArgType;
+  typedef typename internal::conditional<
+    static_cast<int>(Layout) == static_cast<int>(ColMajor), RightArgType, LeftArgType>::type EvalRightArgType;
+
+  static const int LDims =
+      internal::array_size<typename TensorEvaluator<EvalLeftArgType, Device>::Dimensions>::value;
+  static const int RDims =
+      internal::array_size<typename TensorEvaluator<EvalRightArgType, Device>::Dimensions>::value;
+  static const int ContractDims = internal::array_size<Indices>::value;
+
+  typedef array<Index, LDims> left_dim_mapper_t;
+  typedef array<Index, RDims> right_dim_mapper_t;
+
+  typedef array<Index, ContractDims> contract_t;
+  typedef array<Index, LDims - ContractDims> left_nocontract_t;
+  typedef array<Index, RDims - ContractDims> right_nocontract_t;
+
+  static const int NumDims = LDims + RDims - 2 * ContractDims;
+
+  typedef DSizes<Index, NumDims> Dimensions;
+
+  // typedefs needed in evalTo
+  typedef typename internal::remove_const<typename EvalLeftArgType::Scalar>::type LhsScalar;
+  typedef typename internal::remove_const<typename EvalRightArgType::Scalar>::type RhsScalar;
+  typedef typename internal::gebp_traits<LhsScalar, RhsScalar> Traits;
+
+  typedef TensorEvaluator<EvalLeftArgType, Device> LeftEvaluator;
+  typedef TensorEvaluator<EvalRightArgType, Device> RightEvaluator;
+
+  TensorEvaluator(const XprType& op, const Device& device) :
+      Base(op, device) {}
+
+#ifndef EIGEN_USE_SIMPLE_THREAD_POOL
+  template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous,
+            bool rhs_inner_dim_reordered, int Alignment>
+  void evalProduct(Scalar* buffer) const {
+    typedef
+        typename internal::remove_const<typename EvalLeftArgType::Scalar>::type
+            LhsScalar;
+    typedef
+        typename internal::remove_const<typename EvalRightArgType::Scalar>::type
+            RhsScalar;
+    typedef typename internal::gebp_traits<LhsScalar, RhsScalar> Traits;
+    typedef TensorEvaluator<EvalLeftArgType, Device> LeftEvaluator;
+    typedef TensorEvaluator<EvalRightArgType, Device> RightEvaluator;
+    typedef internal::TensorContractionInputMapper<
+        LhsScalar, Index, internal::Lhs, LeftEvaluator, left_nocontract_t,
+        contract_t, internal::packet_traits<LhsScalar>::size,
+        lhs_inner_dim_contiguous, false, Unaligned>
+        LhsMapper;
+    typedef internal::TensorContractionInputMapper<
+        RhsScalar, Index, internal::Rhs, RightEvaluator, right_nocontract_t,
+        contract_t, internal::packet_traits<RhsScalar>::size,
+        rhs_inner_dim_contiguous, rhs_inner_dim_reordered, Unaligned>
+        RhsMapper;
+    typedef internal::blas_data_mapper<Scalar, Index, ColMajor> OutputMapper;
+    typedef internal::gemm_pack_lhs<LhsScalar, Index,
+                                    typename LhsMapper::SubMapper, Traits::mr,
+                                    Traits::LhsProgress, ColMajor>
+        LhsPacker;
+    typedef internal::gemm_pack_rhs<
+        RhsScalar, Index, typename RhsMapper::SubMapper, Traits::nr, ColMajor>
+        RhsPacker;
+    typedef internal::gebp_kernel<LhsScalar, RhsScalar, Index, OutputMapper,
+                                  Traits::mr, Traits::nr, false, false>
+        GebpKernel;
+
+    const Index m = this->m_i_size;
+    const Index n = this->m_j_size;
+    const Index k = this->m_k_size;
+    if (m == 0 || n == 0 || k == 0) return;
+
+    // Compute a set of algorithm parameters:
+    // - kernel block sizes (bm, bn, bk)
+    // - task grain sizes (number of kernels executed per task: gm, gn)
+    // - number of threads
+    // - sharding by row/column
+    // - parallel packing or first lhs then rhs
+    // and some derived parameters:
+    // - number of tasks (nm, nn, nk)
+    // - number of kernels (nm0, nn0)
+    // Unfortunately, all these parameters are tightly interdependent.
+    // So in some cases we first compute approximate values, then compute other
+    // values based on these approximations and then refine the approximations.
+
+    // There are lots of heuristics here. There is some reasoning behind them,
+    // but ultimately they are just tuned on contraction benchmarks for
+    // different input configurations, thread counts and instruction sets.
+    // So feel free to question any of them.
+
+    // Compute whether we want to shard by row or by column.
+    // This is a first approximation, it will be refined later. Since we don't
+    // know number of threads yet we use 2, because what's we are most
+    // interested in at this point is whether it makes sense to use
+    // parallelization at all or not.
+    bool shard_by_col = shardByCol(m, n, 2);
+
+    // First approximation of kernel blocking sizes.
+    // Again, we don't know number of threads yet, so we use 2.
+    Index bm, bn, bk;
+    if (shard_by_col) {
+      internal::TensorContractionBlocking<LhsMapper, RhsMapper, Index,
+                                          internal::ShardByCol>
+          blocking(k, m, n, 2);
+      bm = blocking.mc();
+      bn = blocking.nc();
+      bk = blocking.kc();
+    } else {
+      internal::TensorContractionBlocking<LhsMapper, RhsMapper, Index,
+                                          internal::ShardByRow>
+          blocking(k, m, n, 2);
+      bm = blocking.mc();
+      bn = blocking.nc();
+      bk = blocking.kc();
+    }
+
+    // Compute optimal number of threads.
+    // Note: we use bk instead of k here because we are interested in amount of
+    // _parallelizable_ computations, and computations are not parallelizable
+    // across k dimension.
+    const TensorOpCost cost =
+        contractionCost(m, n, bm, bn, bk, shard_by_col, false);
+    int num_threads = TensorCostModel<ThreadPoolDevice>::numThreads(
+        static_cast<double>(n) * m, cost, this->m_device.numThreads());
+
+    // TODO(dvyukov): this is a stop-gap to prevent regressions while the cost
+    // model is not tuned. Remove this when the cost model is tuned.
+    if (n == 1) num_threads = 1;
+
+    if (num_threads == 1) {
+      // The single-threaded algorithm should be faster in this case.
+      if (n == 1)
+        this->template evalGemv<lhs_inner_dim_contiguous,
+                                rhs_inner_dim_contiguous,
+                                rhs_inner_dim_reordered, Alignment>(buffer);
+      else
+        this->template evalGemm<lhs_inner_dim_contiguous,
+                                rhs_inner_dim_contiguous,
+                                rhs_inner_dim_reordered, Alignment>(buffer);
+      return;
+    }
+
+    // Now that we know number of threads, recalculate sharding and blocking.
+    shard_by_col = shardByCol(m, n, num_threads);
+    if (shard_by_col) {
+      internal::TensorContractionBlocking<LhsMapper, RhsMapper, Index,
+                                          internal::ShardByCol>
+          blocking(k, m, n, num_threads);
+      bm = blocking.mc();
+      bn = blocking.nc();
+      bk = blocking.kc();
+    } else {
+      internal::TensorContractionBlocking<LhsMapper, RhsMapper, Index,
+                                          internal::ShardByRow>
+          blocking(k, m, n, num_threads);
+      bm = blocking.mc();
+      bn = blocking.nc();
+      bk = blocking.kc();
+    }
+
+    // Number of kernels for each dimension.
+    Index nm0 = divup(m, bm);
+    Index nn0 = divup(n, bn);
+    Index nk = divup(k, bk);
+
+    // Calculate task grain size (number of kernels executed per task).
+    // This task size coarsening serves two purposes:
+    // 1. It reduces per-task overheads including synchronization overheads.
+    // 2. It allows to use caches better (reuse the same packed rhs in several
+    // consecutive kernels).
+    Index gm = 1;
+    Index gn = 1;
+    // If we are sharding by column, then we prefer to reduce rows first.
+    if (shard_by_col) {
+      gm = coarsenM(m, n, bm, bn, bk, gn, num_threads, shard_by_col);
+      gn = coarsenN(m, n, bm, bn, bk, gm, num_threads, shard_by_col);
+    } else {
+      gn = coarsenN(m, n, bm, bn, bk, gm, num_threads, shard_by_col);
+      gm = coarsenM(m, n, bm, bn, bk, gn, num_threads, shard_by_col);
+    }
+    // Number of tasks in each dimension.
+    Index nm = divup(nm0, gm);
+    Index nn = divup(nn0, gn);
+
+    // Last by not least, decide whether we want to issue both lhs and rhs
+    // packing in parallel; or issue lhs packing first, and then issue rhs
+    // packing when lhs packing completes (for !shard_by_col lhs and rhs are
+    // swapped). Parallel packing allows more parallelism (for both packing and
+    // kernels), while sequential packing provides better locality (once
+    // a thread finishes rhs packing it proceed to kernels with that rhs).
+    // First, we are interested in parallel packing if there are few tasks.
+    bool parallel_pack = num_threads >= nm * nn;
+    // Also do parallel packing if all data fits into L2$.
+    if (m * bk * Index(sizeof(LhsScalar)) + n * bk * Index(sizeof(RhsScalar)) <=
+        l2CacheSize() * num_threads)
+      parallel_pack = true;
+    // But don't do it if we will use each rhs only once. Locality seems to be
+    // more important in this case.
+    if ((shard_by_col ? nm : nn) == 1) parallel_pack = false;
+
+    LhsMapper lhs(this->m_leftImpl, this->m_left_nocontract_strides,
+                  this->m_i_strides, this->m_left_contracting_strides,
+                  this->m_k_strides);
+
+    RhsMapper rhs(this->m_rightImpl, this->m_right_nocontract_strides,
+                  this->m_j_strides, this->m_right_contracting_strides,
+                  this->m_k_strides);
+
+    Context<LhsPacker, RhsPacker, GebpKernel, LhsMapper, RhsMapper,
+            OutputMapper>(this->m_device, num_threads, lhs, rhs, buffer, m, n,
+                          k, bm, bn, bk, nm, nn, nk, gm, gn, nm0, nn0,
+                          shard_by_col, parallel_pack)
+        .run();
+  }
+
+  // Context coordinates a single parallel gemm operation.
+  template <typename LhsPacker, typename RhsPacker, typename GebpKernel,
+            typename LhsMapper, typename RhsMapper, typename OutputMapper>
+  class Context {
+   public:
+    Context(const Device& device, int num_threads, LhsMapper& lhs,
+            RhsMapper& rhs, Scalar* buffer, Index tm, Index tn, Index tk, Index bm,
+            Index bn, Index bk, Index nm, Index nn, Index nk, Index gm,
+            Index gn, Index nm0, Index nn0, bool shard_by_col,
+            bool parallel_pack)
+        : device_(device),
+          lhs_(lhs),
+          rhs_(rhs),
+          buffer_(buffer),
+          output_(buffer, tm),
+          num_threads_(num_threads),
+          shard_by_col_(shard_by_col),
+          parallel_pack_(parallel_pack),
+          m_(tm),
+          n_(tn),
+          k_(tk),
+          bm_(bm),
+          bn_(bn),
+          bk_(bk),
+          nm_(nm),
+          nn_(nn),
+          nk_(nk),
+          gm_(gm),
+          gn_(gn),
+          nm0_(nm0),
+          nn0_(nn0)
+  {
+      for (Index x = 0; x < P; x++) {
+        // Normal number of notifications for k slice switch is
+        // nm_ + nn_ + nm_ * nn_. However, first P - 1 slices will receive only
+        // nm_ + nn_ notifications, because they will not receive notifications
+        // from preceeding kernels.
+        state_switch_[x] =
+            x == 0
+                ? 1
+                : (parallel_pack_ ? nn_ + nm_ : (shard_by_col_ ? nn_ : nm_)) +
+                      (x == P - 1 ? nm_ * nn_ : 0);
+        state_packing_ready_[x] =
+            parallel_pack_ ? 0 : (shard_by_col_ ? nm_ : nn_);
+        state_kernel_[x] = new std::atomic<uint8_t>*[nm_];
+        for (Index m = 0; m < nm_; m++) {
+          state_kernel_[x][m] = new std::atomic<uint8_t>[nn_];
+          // Kernels generally receive 3 notifications (previous kernel + 2
+          // packing), but the first slice won't get notifications from previous
+          // kernels.
+          for (Index n = 0; n < nn_; n++)
+            state_kernel_[x][m][n].store(
+                (x == 0 ? 0 : 1) + (parallel_pack_ ? 2 : 1),
+                std::memory_order_relaxed);
+        }
+      }
+
+      // Allocate memory for packed rhs/lhs matrices.
+      size_t align = numext::maxi(EIGEN_MAX_ALIGN_BYTES, 1);
+      size_t lhs_size =
+          divup<size_t>(bm_ * bk_ * sizeof(LhsScalar), align) * align;
+      size_t rhs_size =
+          divup<size_t>(bn_ * bk_ * sizeof(RhsScalar), align) * align;
+      packed_mem_ = static_cast<char*>(internal::aligned_malloc(
+          (nm0_ * lhs_size + nn0_ * rhs_size) * std::min<size_t>(nk_, P - 1)));
+      char* mem = static_cast<char*>(packed_mem_);
+      for (Index x = 0; x < numext::mini<Index>(nk_, P - 1); x++) {
+        packed_lhs_[x].resize(nm0_);
+        for (Index m = 0; m < nm0_; m++) {
+          packed_lhs_[x][m] = reinterpret_cast<LhsScalar*>(mem);
+          mem += lhs_size;
+        }
+        packed_rhs_[x].resize(nn0_);
+        for (Index n = 0; n < nn0_; n++) {
+          packed_rhs_[x][n] = reinterpret_cast<RhsScalar*>(mem);
+          mem += rhs_size;
+        }
+      }
+    }
+
+    ~Context() {
+      for (Index x = 0; x < P; x++) {
+        for (Index m = 0; m < nm_; m++) delete[] state_kernel_[x][m];
+        delete[] state_kernel_[x];
+      }
+      internal::aligned_free(packed_mem_);
+    }
+
+    void run() {
+      // Kick off packing of the first slice.
+      signal_switch(0, 1);
+      // Wait for overall completion.
+      // TODO(dvyukov): this wait can lead to deadlock.
+      // If nthreads contractions are concurrently submitted from worker
+      // threads, this wait will block all worker threads and the system will
+      // deadlock.
+      done_.Wait();
+    }
+
+   private:
+    Notification done_;
+    const Device& device_;
+    LhsMapper& lhs_;
+    RhsMapper& rhs_;
+    Scalar* const buffer_;
+    OutputMapper output_;
+    const int num_threads_;
+    const bool shard_by_col_;
+    const bool parallel_pack_;
+    // Matrix sizes.
+    const Index m_;
+    const Index n_;
+    const Index k_;
+    // Block sizes.
+    const Index bm_;
+    const Index bn_;
+    const Index bk_;
+    // Number of tasks.
+    const Index nm_;
+    const Index nn_;
+    const Index nk_;
+    // Task grain sizes (number of kernels executed per task).
+    const Index gm_;
+    const Index gn_;
+    // Number of blocks (this is different from ni_/nn_ because of task size
+    // coarsening).
+    const Index nm0_;
+    const Index nn0_;
+
+    // Parallelization strategy.
+    //
+    // Blocks related to the same k block can run in parallel because they write
+    // to different output blocks. So we parallelize within k slices, this
+    // gives us parallelism level of m x n. Before we can start any kernels
+    // related to k-th slice, we need to issue m lhs packing tasks and n rhs
+    // packing tasks.
+    //
+    // However, there is a bottleneck when we are finishing kernels for k-th
+    // slice (at the very end there is only 1 runnable kernel). To mitigate this
+    // bottleneck we allow kernels from k-th and k+1-th slices to run in
+    // parallel. Note that (m, n, k) and (m, n, k+1) kernels write to the same
+    // output block, so they must not run in parallel.
+    //
+    // This gives us the following dependency graph.
+    // On each k slice we have m x n kernel tasks, m lhs paking tasks and n rhs
+    // packing tasks.
+    // Kernel (m, n, k) can start when:
+    //  - kernel (m, n, k-1) has finished
+    //  - lhs packing (m, k) has finished
+    //  - rhs packing (n, k) has finished
+    // Lhs/rhs packing can start when:
+    //  - all k-1 packing has finished (artificially imposed to limit amount of
+    //  parallel packing)
+    //
+    // On top of that we limit runnable tasks to two consecutive k slices.
+    // This is done to limit amount of memory we need for packed lhs/rhs
+    // (for each k slice we need m*bk + n*bk memory in packed_lhs_/packed_rhs_).
+    //
+    // state_switch_ tracks when we are ready to switch to the next k slice.
+    // state_kernel_[m][n] tracks when we are ready to kick off kernel (m, n).
+    // These variable are rolling over 3 consecutive k slices: first two we are
+    // actively executing + one to track completion of kernels in the second
+    // slice.
+    static const Index P = 3;
+    void* packed_mem_;
+    std::vector<LhsScalar*> packed_lhs_[P - 1];
+    std::vector<RhsScalar*> packed_rhs_[P - 1];
+    std::atomic<uint8_t>** state_kernel_[P];
+    // state_switch_ is frequently modified by worker threads, while other
+    // fields are read-only after constructor. Let's move it to a separate cache
+    // line to reduce cache-coherency traffic.
+    char pad_[128];
+    std::atomic<Index> state_packing_ready_[P];
+    std::atomic<Index> state_switch_[P];
+
+    void pack_lhs(Index m, Index k) {
+      const Index mend = m * gm_ + gm(m);
+      for (Index m1 = m * gm_; m1 < mend; m1++)
+        LhsPacker()(packed_lhs_[k % (P - 1)][m1],
+                    lhs_.getSubMapper(m1 * bm_, k * bk_), bk(k), bm(m1));
+
+      if (!parallel_pack_ && shard_by_col_) {
+        signal_packing(k);
+      } else {
+        signal_switch(k + 1);
+        for (Index n = nn_ - 1; n >= 0; n--) signal_kernel(m, n, k, n == 0);
+      }
+    }
+
+    void pack_rhs(Index n, Index k) {
+      const Index nend = n * gn_ + gn(n);
+      for (Index n1 = n * gn_; n1 < nend; n1++) {
+        if (k == 0) {
+          // Zero the output memory in parallel.
+          // On 10000x2x10000 mm zeroing can easily take half of time.
+          // Zero (bn x m) row. Safe to do here because all kernels that will
+          // write to this memory depend on completion of this task.
+          // Note: don't call device_.memset() here. device_.memset() blocks on
+          // thread pool worker thread, which can lead to underutilization and
+          // deadlocks.
+          memset(buffer_ + n1 * bn_ * m_, 0, bn(n1) * m_ * sizeof(Scalar));
+        }
+        RhsPacker()(packed_rhs_[k % (P - 1)][n1],
+                    rhs_.getSubMapper(k * bk_, n1 * bn_), bk(k), bn(n1));
+      }
+
+      if (parallel_pack_ || shard_by_col_) {
+        signal_switch(k + 1);
+        for (Index m = nm_ - 1; m >= 0; m--) signal_kernel(m, n, k, m == 0);
+      } else {
+        signal_packing(k);
+      }
+    }
+
+    void kernel(Index m, Index n, Index k) {
+      // Note: order of iteration matters here. Iteration over m is innermost
+      // because we want to reuse the same packed rhs in consequetive tasks
+      // (rhs fits into L2$ while lhs only into L3$).
+      const Index nend = n * gn_ + gn(n);
+      const Index mend = m * gm_ + gm(m);
+      if (shard_by_col_) {
+        for (Index n1 = n * gn_; n1 < nend; n1++) {
+          for (Index m1 = m * gm_; m1 < mend; m1++)
+            GebpKernel()(output_.getSubMapper(m1 * bm_, n1 * bn_),
+                         packed_lhs_[k % (P - 1)][m1],
+                         packed_rhs_[k % (P - 1)][n1], bm(m1), bk(k), bn(n1),
+                         Scalar(1), -1, -1, 0, 0);
+        }
+      } else {
+        for (Index m1 = m * gm_; m1 < mend; m1++)
+          for (Index n1 = n * gn_; n1 < nend; n1++) {
+            GebpKernel()(output_.getSubMapper(m1 * bm_, n1 * bn_),
+                         packed_lhs_[k % (P - 1)][m1],
+                         packed_rhs_[k % (P - 1)][n1], bm(m1), bk(k), bn(n1),
+                         Scalar(1), -1, -1, 0, 0);
+          }
+      }
+      signal_kernel(m, n, k + 1, false);
+      signal_switch(k + 2);
+    }
+
+    void signal_packing(Index k) {
+      eigen_assert(!parallel_pack_);
+      Index s = state_packing_ready_[k % P].fetch_sub(1);
+      eigen_assert(s > 0);
+      if (s != 1) return;
+      state_packing_ready_[k % P] = shard_by_col_ ? nm_ : nn_;
+      enqueue_packing(k, shard_by_col_);
+    }
+
+    void signal_kernel(Index m, Index n, Index k, bool sync) {
+      std::atomic<uint8_t>* state = &state_kernel_[k % P][m][n];
+      Index s = state->load();
+      eigen_assert(s > 0);
+      if (s != 1 && state->fetch_sub(1) != 1) return;
+      state->store(parallel_pack_ ? 3 : 2, std::memory_order_relaxed);
+      if (sync)
+        kernel(m, n, k);
+      else
+        device_.enqueueNoNotification([=]() { kernel(m, n, k); });
+    }
+
+    void signal_switch(Index k, Index v = 1) {
+      Index s = state_switch_[k % P].fetch_sub(v);
+      eigen_assert(s >= v);
+      if (s != v) return;
+
+      // Ready to switch to the next k slice.
+      // Reset counter for the next iteration.
+      state_switch_[k % P] =
+          (parallel_pack_ ? nm_ + nn_ : (shard_by_col_ ? nn_ : nm_)) +
+          nm_ * nn_;
+      if (k < nk_) {
+        // Issue lhs/rhs packing. Their completion will in turn kick off
+        // kernels.
+        if (parallel_pack_) {
+          enqueue_packing(k, !shard_by_col_);
+          enqueue_packing(k, shard_by_col_);
+        } else if (shard_by_col_) {
+          enqueue_packing(k, false);
+        } else {
+          enqueue_packing(k, true);
+        }
+
+        // Termination handling.
+        // Because kernel completion signals k + 2 switch, we need to finish nk
+        // + 2 slices without issuing any tasks on nk + 1 slice. So here we
+        // pretend that all nk + 1 packing tasks just finish instantly; so that
+        // nk + 2 switch only waits for completion of nk kernels.
+      } else if (k == nk_) {
+        signal_switch(k + 1,
+                      parallel_pack_ ? nm_ + nn_ : (shard_by_col_ ? nn_ : nm_));
+      } else {
+        done_.Notify();
+      }
+    }
+
+    // Enqueue all rhs/lhs packing for k-th slice.
+    void enqueue_packing(Index k, bool rhs) {
+      enqueue_packing_helper(0, rhs ? nn_ : nm_, k, rhs);
+    }
+
+    void enqueue_packing_helper(Index start, Index end, Index k, bool rhs) {
+      if (end - start == 1) {
+        if (rhs)
+          pack_rhs(start, k);
+        else
+          pack_lhs(start, k);
+      } else {
+        Index mid = (start + end) / 2;
+        device_.enqueueNoNotification(
+            [=]() { enqueue_packing_helper(mid, end, k, rhs); });
+        device_.enqueueNoNotification(
+            [=]() { enqueue_packing_helper(start, mid, k, rhs); });
+      }
+    }
+
+    // Block sizes with accounting for potentially incomplete last block.
+    Index bm(Index m) const { return m + 1 < nm0_ ? bm_ : m_ + bm_ - bm_ * nm0_; }
+    Index bn(Index n) const { return n + 1 < nn0_ ? bn_ : n_ + bn_ - bn_ * nn0_; }
+    Index bk(Index k) const { return k + 1 < nk_ ? bk_ : k_ + bk_ - bk_ * nk_; }
+    // Task grain sizes accounting for potentially incomplete last task.
+    Index gm(Index m) const { return m + 1 < nm_ ? gm_ : nm0_ + gm_ - gm_ * nm_; }
+    Index gn(Index n) const { return n + 1 < nn_ ? gn_ : nn0_ + gn_ - gn_ * nn_; }
+
+    Context(const Context&) = delete;
+    void operator=(const Context&) = delete;
+  };
+
+  // Decide whether we want to shard m x n contraction by columns or by rows.
+  static bool shardByCol(Index m, Index n, Index num_threads) {
+    // Note: we are comparing both n and m against Traits::nr, it is not
+    // a mistake. We are trying to figure out how both n and m will fit into
+    // the main sharding dimension.
+
+    // Sharding by column is the default
+    // ... unless there is enough data for vectorization over rows
+    if (m / num_threads >= Traits::nr &&
+        // and not enough data for vectorization over columns
+        (n / num_threads < Traits::nr ||
+         // ... or barely enough data for vectorization over columns,
+         // but it is not evenly dividable across threads
+         (n / num_threads < 4 * Traits::nr &&
+          (n % (num_threads * Traits::nr)) != 0 &&
+          // ... and it is evenly dividable across threads for rows
+          ((m % (num_threads * Traits::nr)) == 0 ||
+           // .. or it is not evenly dividable for both dimensions but
+           // there is much more data over rows so that corner effects are
+           // mitigated.
+           (m / n >= 6)))))
+      return false;
+    // Wait, or if matrices are just substantially prolonged over the other
+    // dimension.
+    if (n / num_threads < 16 * Traits::nr && m > n * 32) return false;
+    return true;
+  }
+
+  Index coarsenM(Index m, Index n, Index bm, Index bn, Index bk, Index gn,
+                 int num_threads, bool shard_by_col) const {
+    Index gm = 1;
+    Index gm1 = 1;
+    Index nm0 = divup(m, bm);
+    Index nm1 = nm0;
+    for (;;) {
+      // Find the next candidate for m grain size. It needs to result in
+      // different number of blocks. E.g. if we have 10 kernels, we want to try
+      // 5 and 10, but not 6, 7, 8 and 9.
+      while (gm1 <= nm0 && nm1 == divup(nm0, gm1)) gm1++;
+      if (gm1 > nm0) break;
+      // Check the candidate.
+      int res = checkGrain(m, n, bm, bn, bk, gm1, gn, gm, gn, num_threads,
+                           shard_by_col);
+      if (res < 0) break;
+      nm1 = divup(nm0, gm1);
+      if (res == 0) continue;
+      // Commit new grain size.
+      gm = gm1;
+    }
+    return gm;
+  }
+
+  Index coarsenN(Index m, Index n, Index bm, Index bn, Index bk, Index gm,
+                 int num_threads, bool shard_by_col) const {
+    Index gn = 1;
+    Index gn1 = 1;
+    Index nn0 = divup(n, bn);
+    Index nn1 = nn0;
+    for (;;) {
+      while (gn1 <= nn0 && nn1 == divup(nn0, gn1)) gn1++;
+      if (gn1 > nn0) break;
+      int res = checkGrain(m, n, bm, bn, bk, gm, gn1, gm, gn, num_threads,
+                           shard_by_col);
+      if (res < 0) break;
+      nn1 = divup(nn0, gn1);
+      if (res == 0) continue;
+      gn = gn1;
+    }
+    return gn;
+  }
+
+  // checkGrain checks whether grain (gm, gn) is suitable and is better than
+  // (oldgm, oldgn).
+  int checkGrain(Index m, Index n, Index bm, Index bn, Index bk, Index gm,
+                 Index gn, Index oldgm, Index oldgn, int num_threads,
+                 bool shard_by_col) const {
+    const TensorOpCost cost =
+        contractionCost(bm * gm, bn * gn, bm, bn, bk, shard_by_col, true);
+    double taskSize = TensorCostModel<ThreadPoolDevice>::taskSize(
+        static_cast<double>(bm) * gm * bn * gn, cost);
+    // If the task is too small, then we agree on it regardless of anything
+    // else. Otherwise synchronization overheads will dominate.
+    if (taskSize < 1) return 1;
+    // If it is too large, then we reject it and all larger tasks.
+    if (taskSize > 2) return -1;
+    // Now we are in presumably good task size range.
+    // The main deciding factor here is parallelism. Consider that we have 12
+    // kernels and 4 threads. Grains of 2, 3 and 4 all yield good task sizes.
+    // But 2/4 yield 6/3 tasks, which gives us parallelism of 0.75 (at most 3/4
+    // of cores will be busy). While grain size 3 gives us 4 tasks, which gives
+    // us parallelism of 1 (we can load all cores).
+    Index nm0 = divup(m, bm);
+    Index nn0 = divup(n, bn);
+    Index new_tasks = divup(nm0, gm) * divup(nn0, gn);
+    double new_parallelism = static_cast<double>(new_tasks) /
+                             (divup<int>(new_tasks, num_threads) * num_threads);
+    Index old_tasks = divup(nm0, oldgm) * divup(nn0, oldgn);
+    double old_parallelism = static_cast<double>(old_tasks) /
+                             (divup<int>(old_tasks, num_threads) * num_threads);
+    if (new_parallelism > old_parallelism || new_parallelism == 1) return 1;
+    return 0;
+  }
+
+#else  // EIGEN_USE_SIMPLE_THREAD_POOL
+
+  template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous, bool rhs_inner_dim_reordered, int Alignment>
+  void evalProduct(Scalar* buffer) const {
+    if (this->m_j_size == 1) {
+      this->template evalGemv<lhs_inner_dim_contiguous, rhs_inner_dim_contiguous, rhs_inner_dim_reordered, Alignment>(buffer);
+      return;
+    }
+
+    evalGemm<lhs_inner_dim_contiguous, rhs_inner_dim_contiguous, rhs_inner_dim_reordered, Alignment>(buffer);
+  }
+
+  template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous, bool rhs_inner_dim_reordered, int Alignment>
+  void evalGemm(Scalar* buffer) const {
+    // columns in left side, rows in right side
+    const Index k = this->m_k_size;
+
+    // rows in left side
+    const Index m = this->m_i_size;
+
+    // columns in right side
+    const Index n = this->m_j_size;
+
+    // zero out the result buffer (which must be of size at least m * n * sizeof(Scalar)
+    this->m_device.memset(buffer, 0, m * n * sizeof(Scalar));
+
+
+    const int lhs_packet_size = internal::unpacket_traits<typename LeftEvaluator::PacketReturnType>::size;
+    const int rhs_packet_size = internal::unpacket_traits<typename RightEvaluator::PacketReturnType>::size;
+
+    typedef internal::TensorContractionInputMapper<LhsScalar, Index, internal::Lhs,
+                                                   LeftEvaluator, left_nocontract_t,
+                                                   contract_t, lhs_packet_size,
+                                                   lhs_inner_dim_contiguous,
+                                                   false, Unaligned> LhsMapper;
+
+    typedef internal::TensorContractionInputMapper<RhsScalar, Index, internal::Rhs,
+                                                   RightEvaluator, right_nocontract_t,
+                                                   contract_t, rhs_packet_size,
+                                                   rhs_inner_dim_contiguous,
+                                                   rhs_inner_dim_reordered, Unaligned> RhsMapper;
+
+    typedef internal::blas_data_mapper<Scalar, Index, ColMajor> OutputMapper;
+
+    // TODO: packing could be faster sometimes if we supported row major tensor mappers
+    typedef internal::gemm_pack_lhs<LhsScalar, Index, typename LhsMapper::SubMapper, Traits::mr,
+                                    Traits::LhsProgress, ColMajor> LhsPacker;
+    typedef internal::gemm_pack_rhs<RhsScalar, Index, typename RhsMapper::SubMapper, Traits::nr, ColMajor> RhsPacker;
+
+    // TODO: replace false, false with conjugate values?
+    typedef internal::gebp_kernel<LhsScalar, RhsScalar, Index, OutputMapper,
+                                  Traits::mr, Traits::nr, false, false> GebpKernel;
+
+    typedef internal::packLhsArg<LhsScalar, LhsMapper, Index> packLArg;
+    typedef internal::packRhsAndKernelArg<LhsScalar, RhsScalar, RhsMapper, OutputMapper, Index> packRKArg;
+
+    // initialize data mappers
+    LhsMapper lhs(this->m_leftImpl, this->m_left_nocontract_strides, this->m_i_strides,
+                  this->m_left_contracting_strides, this->m_k_strides);
+
+    RhsMapper rhs(this->m_rightImpl, this->m_right_nocontract_strides, this->m_j_strides,
+                  this->m_right_contracting_strides, this->m_k_strides);
+
+    OutputMapper output(buffer, m);
+
+    // compute block sizes (which depend on number of threads)
+    const Index num_threads = this->m_device.numThreads();
+    internal::TensorContractionBlocking<LhsMapper, RhsMapper, Index, internal::ShardByCol> blocking(k, m, n, num_threads);
+    Index mc = blocking.mc();
+    Index nc = blocking.nc();
+    Index kc = blocking.kc();
+    eigen_assert(mc <= m);
+    eigen_assert(nc <= n);
+    eigen_assert(kc <= k);
+
+#define CEIL_DIV(a, b) (((a) + (b) - 1) / (b))
+    const Index k_blocks = CEIL_DIV(k, kc);
+    const Index n_blocks = CEIL_DIV(n, nc);
+    const Index m_blocks = CEIL_DIV(m, mc);
+    const Index sizeA = mc * kc;
+    const Index sizeB = kc * nc;
+
+    /*    cout << "m: " << m << " n: " << n << " k: " << k << endl;
+    cout << "mc: " << mc << " nc: " << nc << " kc: " << kc << endl;
+    cout << "m_blocks: " << m_blocks << " n_blocks: " << n_blocks << " k_blocks: " << k_blocks << endl;
+    cout << "num threads: " << num_threads << endl;
+    */
+
+    // note: m_device.allocate should return 16 byte aligned pointers, but if blockA and blockB
+    //       aren't 16 byte aligned segfaults will happen due to SIMD instructions
+    // note: You can get away with allocating just a single blockA and offsets and meet the
+    //       the alignment requirements with the assumption that
+    //       (Traits::mr * sizeof(ResScalar)) % 16 == 0
+    const Index numBlockAs = numext::mini(num_threads, m_blocks);
+    MaxSizeVector<LhsScalar *> blockAs(num_threads);
+    for (int i = 0; i < num_threads; i++) {
+      blockAs.push_back(static_cast<LhsScalar *>(this->m_device.allocate(sizeA * sizeof(LhsScalar))));
+    }
+
+    // To circumvent alignment issues, I'm just going to separately allocate the memory for each thread
+    // TODO: is this too much memory to allocate? This simplifies coding a lot, but is wasteful.
+    //       Other options: (1) reuse memory when a thread finishes. con: tricky
+    //                      (2) allocate block B memory in each thread. con: overhead
+    MaxSizeVector<RhsScalar *> blockBs(n_blocks);
+    for (int i = 0; i < n_blocks; i++) {
+      blockBs.push_back(static_cast<RhsScalar *>(this->m_device.allocate(sizeB * sizeof(RhsScalar))));
+    }
+
+    // lhs_notifications starts with all null Notifications
+    MaxSizeVector<Notification*> lhs_notifications(num_threads, nullptr);
+
+    // this should really be numBlockAs * n_blocks;
+    const Index num_kernel_notifications = num_threads * n_blocks;
+    MaxSizeVector<Notification*> kernel_notifications(num_kernel_notifications,
+                                                    nullptr);
+
+    for (Index k_block_idx = 0; k_block_idx < k_blocks; k_block_idx++) {
+      const Index k_start = k_block_idx * kc;
+      // make sure we don't overshoot right edge of left matrix
+      const Index actual_kc = numext::mini(k_start + kc, k) - k_start;
+
+      for (Index m_block_idx = 0; m_block_idx < m_blocks; m_block_idx += numBlockAs) {
+        const Index num_blocks = numext::mini(m_blocks-m_block_idx, numBlockAs);
+
+        for (Index mt_block_idx = m_block_idx; mt_block_idx < m_block_idx+num_blocks; mt_block_idx++) {
+          const Index m_start = mt_block_idx * mc;
+          const Index actual_mc = numext::mini(m_start + mc, m) - m_start;
+          eigen_assert(actual_mc > 0);
+
+          Index blockAId = (k_block_idx * m_blocks + mt_block_idx) % num_threads;
+
+          for (int i = 0; i < n_blocks; ++i) {
+            Index notification_id = (blockAId * n_blocks + i);
+            // Wait for any current kernels using this slot to complete
+            // before using it.
+            if (kernel_notifications[notification_id]) {
+              wait_until_ready(kernel_notifications[notification_id]);
+              delete kernel_notifications[notification_id];
+            }
+            kernel_notifications[notification_id] = new Notification();
+          }
+          const packLArg arg = {
+            blockAs[blockAId], // blockA
+            lhs,        // lhs
+            m_start,    // m
+            k_start,    // k
+            actual_mc,  // mc
+            actual_kc,  // kc
+          };
+
+          // Delete any existing notification since we may be
+          // replacing it.  The algorithm should ensure that there are
+          // no existing waiters on this notification.
+          delete lhs_notifications[blockAId];
+          lhs_notifications[blockAId] =
+          this->m_device.enqueue(&Self::packLhs<packLArg, LhsPacker>, arg);
+        }
+
+        // now start kernels.
+        const Index m_base_start = m_block_idx * mc;
+        const bool need_to_pack = m_block_idx == 0;
+
+        for (Index n_block_idx = 0; n_block_idx < n_blocks; n_block_idx++) {
+          const Index n_start = n_block_idx * nc;
+          const Index actual_nc = numext::mini(n_start + nc, n) - n_start;
+
+          // first make sure the previous kernels are all done before overwriting rhs. Also wait if
+          // we're going to start new k. In both cases need_to_pack is true.
+          if (need_to_pack) {
+            for (Index i = num_blocks; i < num_threads; ++i) {
+              Index blockAId = (k_block_idx * m_blocks + i + m_block_idx) % num_threads;
+              Index future_id = (blockAId * n_blocks + n_block_idx);
+              wait_until_ready(kernel_notifications[future_id]);
+            }
+          }
+
+          packRKArg arg = {
+            &blockAs, // blockA
+            blockBs[n_block_idx], // blockB
+            rhs,          // rhs
+            output,       // output
+            m_base_start, // m
+            k_start,      // k
+            n_start,      // n
+            mc,           // mc
+            actual_kc,    // kc
+            actual_nc,    // nc
+            num_threads,
+            numBlockAs,
+            m,
+            k_block_idx,
+            m_block_idx,
+            n_block_idx, // n_block_idx
+            m_blocks, // m_blocks
+            n_blocks, // n_blocks
+            &kernel_notifications, // kernel notifications
+            &lhs_notifications,    // lhs notifications
+            need_to_pack, // need_to_pack
+          };
+
+          // We asynchronously kick off this function, which ends up
+          // notifying the appropriate kernel_notifications objects,
+          // which this thread waits on before exiting.
+          this->m_device.enqueueNoNotification(&Self::packRhsAndKernel<packRKArg, RhsPacker, GebpKernel>, arg);
+        }
+      }
+    }
+
+    // Make sure all the kernels are done.
+    for (size_t i = 0; i < kernel_notifications.size(); ++i) {
+      wait_until_ready(kernel_notifications[i]);
+      delete kernel_notifications[i];
+    }
+
+    // No need to wait for lhs notifications since they should have
+    // already been waited on.  Just clean them up.
+    for (size_t i = 0; i < lhs_notifications.size(); ++i) {
+      delete lhs_notifications[i];
+    }
+
+    // deallocate all of the memory for both A and B's
+    for (size_t i = 0; i < blockAs.size(); i++) {
+      this->m_device.deallocate(blockAs[i]);
+    }
+    for (size_t i = 0; i < blockBs.size(); i++) {
+      this->m_device.deallocate(blockBs[i]);
+    }
+
+#undef CEIL_DIV
+  }
+
+  /*
+   * Packs a LHS block of size (mt, kc) starting at lhs(m, k). Before packing
+   * the LHS block, check that all of the kernels that worked on the same
+   * mt_block_idx in the previous m_block are done.
+   */
+  template <typename packLArg, typename LhsPacker>
+  static void packLhs(const packLArg arg) {
+    // perform actual packing
+    LhsPacker pack_lhs;
+    pack_lhs(arg.blockA, arg.lhs.getSubMapper(arg.m_start, arg.k_start), arg.kc, arg.mc);
+  }
+
+  /*
+   * Packs a RHS block of size (kc, nc) starting at (k, n) after checking that
+   * all kernels in the previous block are done.
+   * Then for each LHS future, we wait on the future and then call GEBP
+   * on the area packed by the future (which starts at
+   * blockA + future_idx * mt * kc) on the LHS and with the full packed
+   * RHS block.
+   * The output of this GEBP is written to output(m + i * mt, n).
+   */
+  template <typename packRKArg, typename RhsPacker, typename GebpKernel>
+  static void packRhsAndKernel(packRKArg arg) {
+    if (arg.need_to_pack) {
+      RhsPacker pack_rhs;
+      pack_rhs(arg.blockB, arg.rhs.getSubMapper(arg.k, arg.n), arg.kc, arg.nc);
+    }
+
+    GebpKernel gebp;
+    for (Index mt_block_idx = 0; mt_block_idx < arg.num_blockAs; mt_block_idx++) {
+      const Index m_base_start = arg.m + arg.mc*mt_block_idx;
+      if (m_base_start < arg.max_m) {
+        Index blockAId = (arg.k_block_idx * arg.m_blocks + mt_block_idx + arg.m_block_idx) % arg.num_threads;
+        wait_until_ready((*arg.lhs_notifications)[blockAId]);
+        const Index actual_mc = numext::mini(m_base_start + arg.mc, arg.max_m) - m_base_start;
+        gebp(arg.output.getSubMapper(m_base_start, arg.n),
+             (*arg.blockAs)[blockAId], arg.blockB,
+             actual_mc, arg.kc, arg.nc, Scalar(1), -1, -1, 0, 0);
+
+        // Notify that the kernel is done.
+        const Index set_idx = blockAId * arg.n_blocks + arg.n_block_idx;
+        (*arg.kernel_notifications)[set_idx]->Notify();
+      }
+    }
+  }
+#endif  // EIGEN_USE_SIMPLE_THREAD_POOL
+
+  TensorOpCost contractionCost(Index m, Index n, Index bm, Index bn, Index bk,
+                               bool shard_by_col, bool prepacked) const {
+    const int packed_size = std::min<int>(PacketType<LhsScalar, Device>::size,
+                                          PacketType<RhsScalar, Device>::size);
+    const int output_packet_size = internal::unpacket_traits<PacketReturnType>::size;
+    const double kd = static_cast<double>(bk);
+    // Peak VFMA bandwidth is 0.5. However if we have not enough data for
+    // vectorization bandwidth drops. The 4.0 and 2.0 bandwidth is determined
+    // experimentally.
+    double computeBandwidth = bk == 1 ? 4.0 :
+          (shard_by_col ? bn : bm) < Traits::nr ||
+          (shard_by_col ? bm : bn) < Traits::mr ? 2.0 : 0.5;
+#ifndef EIGEN_VECTORIZE_FMA
+    // Bandwidth of all of VFMA/MULPS/ADDPS is 0.5 on latest Intel processors.
+    // However for MULPS/ADDPS we have dependent sequence of 2 such instructions,
+    // so overall bandwidth is 1.0.
+    if (computeBandwidth == 0.5) computeBandwidth = 1.0;
+#endif
+    // Computations.
+    TensorOpCost cost = TensorOpCost(0, 0, kd * computeBandwidth, true, packed_size);
+    // Output stores.
+    cost += TensorOpCost(0, sizeof(CoeffReturnType), 0, true, output_packet_size);
+    if (prepacked) {
+      // Packing and kernels are executed in different tasks. When we calculate
+      // task grain size we look only at kernel cost assuming that kernel
+      // is more expensive than packing.
+      return cost;
+    }
+    // Lhs/rhs loads + computations.
+    TensorOpCost lhsCost = this->m_leftImpl.costPerCoeff(true) * (kd / n);
+    TensorOpCost rhsCost = this->m_rightImpl.costPerCoeff(true) * (kd / m);
+    // Lhs packing memory cost does not contribute considerably to overall
+    // execution time because lhs is prefetched early and accessed sequentially.
+    if (shard_by_col)
+      lhsCost.dropMemoryCost();
+    else
+      rhsCost.dropMemoryCost();
+    return cost + lhsCost + rhsCost;
+  }
+};
+
+} // end namespace Eigen
+
+#endif  // EIGEN_USE_THREADS
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_THREAD_POOL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConversion.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConversion.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConversion.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConversion.h
@@ -0,0 +1,279 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONVERSION_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CONVERSION_H
+
+namespace Eigen {
+
+/** \class TensorConversionOp
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor conversion class. This class makes it possible to vectorize
+  * type casting operations when the number of scalars per packet in the source
+  * and the destination type differ
+  */
+namespace internal {
+template<typename TargetType, typename XprType>
+struct traits<TensorConversionOp<TargetType, XprType> >
+{
+  // Type promotion to handle the case where the types of the lhs and the rhs are different.
+  typedef TargetType Scalar;
+  typedef typename traits<XprType>::StorageKind StorageKind;
+  typedef typename traits<XprType>::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = traits<XprType>::NumDimensions;
+  static const int Layout = traits<XprType>::Layout;
+  enum { Flags = 0 };
+};
+
+template<typename TargetType, typename XprType>
+struct eval<TensorConversionOp<TargetType, XprType>, Eigen::Dense>
+{
+  typedef const TensorConversionOp<TargetType, XprType>& type;
+};
+
+template<typename TargetType, typename XprType>
+struct nested<TensorConversionOp<TargetType, XprType>, 1, typename eval<TensorConversionOp<TargetType, XprType> >::type>
+{
+  typedef TensorConversionOp<TargetType, XprType> type;
+};
+
+}  // end namespace internal
+
+
+template <typename TensorEvaluator, typename SrcPacket, typename TgtPacket, int SrcCoeffRatio, int TgtCoeffRatio>
+struct PacketConverter {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  PacketConverter(const TensorEvaluator& impl)
+      : m_impl(impl) {}
+
+  template<int LoadMode, typename Index>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TgtPacket packet(Index index) const {
+    return internal::pcast<SrcPacket, TgtPacket>(m_impl.template packet<LoadMode>(index));
+  }
+
+ private:
+  const TensorEvaluator& m_impl;
+};
+
+
+template <typename TensorEvaluator, typename SrcPacket, typename TgtPacket>
+struct PacketConverter<TensorEvaluator, SrcPacket, TgtPacket, 2, 1> {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  PacketConverter(const TensorEvaluator& impl)
+      : m_impl(impl) {}
+
+  template<int LoadMode, typename Index>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TgtPacket packet(Index index) const {
+    const int SrcPacketSize = internal::unpacket_traits<SrcPacket>::size;
+
+    SrcPacket src1 = m_impl.template packet<LoadMode>(index);
+    SrcPacket src2 = m_impl.template packet<LoadMode>(index + SrcPacketSize);
+    TgtPacket result = internal::pcast<SrcPacket, TgtPacket>(src1, src2);
+    return result;
+  }
+
+ private:
+  const TensorEvaluator& m_impl;
+};
+
+template <typename TensorEvaluator, typename SrcPacket, typename TgtPacket>
+struct PacketConverter<TensorEvaluator, SrcPacket, TgtPacket, 4, 1> {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  PacketConverter(const TensorEvaluator& impl)
+      : m_impl(impl) {}
+
+  template<int LoadMode, typename Index>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TgtPacket packet(Index index) const {
+    const int SrcPacketSize = internal::unpacket_traits<SrcPacket>::size;
+
+    SrcPacket src1 = m_impl.template packet<LoadMode>(index);
+    SrcPacket src2 = m_impl.template packet<LoadMode>(index + SrcPacketSize);
+    SrcPacket src3 = m_impl.template packet<LoadMode>(index + 2 * SrcPacketSize);
+    SrcPacket src4 = m_impl.template packet<LoadMode>(index + 3 * SrcPacketSize);
+    TgtPacket result = internal::pcast<SrcPacket, TgtPacket>(src1, src2, src3, src4);
+    return result;
+  }
+
+ private:
+  const TensorEvaluator& m_impl;
+};
+
+template <typename TensorEvaluator, typename SrcPacket, typename TgtPacket>
+struct PacketConverter<TensorEvaluator, SrcPacket, TgtPacket, 1, 2> {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  PacketConverter(const TensorEvaluator& impl)
+      : m_impl(impl), m_maxIndex(impl.dimensions().TotalSize()) {}
+
+  template<int LoadMode, typename Index>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TgtPacket packet(Index index) const {
+    const int SrcPacketSize = internal::unpacket_traits<SrcPacket>::size;
+    // Only call m_impl.packet() when we have direct access to the underlying data. This
+    // ensures that we don't compute the subexpression twice. We may however load some
+    // coefficients twice, but in practice this doesn't negatively impact performance.
+    if (m_impl.data() && (index + SrcPacketSize < m_maxIndex)) {
+      // Force unaligned memory loads since we can't ensure alignment anymore
+      return internal::pcast<SrcPacket, TgtPacket>(m_impl.template packet<Unaligned>(index));
+    } else {
+      const int TgtPacketSize = internal::unpacket_traits<TgtPacket>::size;
+      typedef typename internal::unpacket_traits<SrcPacket>::type SrcType;
+      typedef typename internal::unpacket_traits<TgtPacket>::type TgtType;
+      internal::scalar_cast_op<SrcType, TgtType> converter;
+      EIGEN_ALIGN_MAX typename internal::unpacket_traits<TgtPacket>::type values[TgtPacketSize];
+      for (int i = 0; i < TgtPacketSize; ++i) {
+        values[i] = converter(m_impl.coeff(index+i));
+      }
+      TgtPacket rslt = internal::pload<TgtPacket>(values);
+      return rslt;
+    }
+  }
+
+ private:
+  const TensorEvaluator& m_impl;
+  const typename TensorEvaluator::Index m_maxIndex;
+};
+
+template<typename TargetType, typename XprType>
+class TensorConversionOp : public TensorBase<TensorConversionOp<TargetType, XprType>, ReadOnlyAccessors>
+{
+  public:
+    typedef typename internal::traits<TensorConversionOp>::Scalar Scalar;
+    typedef typename internal::traits<TensorConversionOp>::StorageKind StorageKind;
+    typedef typename internal::traits<TensorConversionOp>::Index Index;
+    typedef typename internal::nested<TensorConversionOp>::type Nested;
+    typedef Scalar CoeffReturnType;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorConversionOp(const XprType& xpr)
+        : m_xpr(xpr) {}
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+};
+
+template <bool SameType, typename Eval, typename Scalar> struct ConversionSubExprEval {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool run(Eval& impl, Scalar*) {
+    impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+};
+
+template <typename Eval, typename Scalar> struct ConversionSubExprEval<true, Eval, Scalar> {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool run(Eval& impl, Scalar* data) {
+    return impl.evalSubExprsIfNeeded(data);
+  }
+};
+
+
+// Eval as rvalue
+template<typename TargetType, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorConversionOp<TargetType, ArgType>, Device>
+{
+  typedef TensorConversionOp<TargetType, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
+  typedef TargetType Scalar;
+  typedef TargetType CoeffReturnType;
+  typedef typename internal::remove_all<typename internal::traits<ArgType>::Scalar>::type SrcType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef typename PacketType<SrcType, Device>::type PacketSourceType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = true,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+    : m_impl(op.expression(), device)
+  {
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_impl.dimensions(); }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data)
+  {
+    return ConversionSubExprEval<internal::is_same<TargetType, SrcType>::value, TensorEvaluator<ArgType, Device>, Scalar>::run(m_impl, data);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup()
+  {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    internal::scalar_cast_op<SrcType, TargetType> converter;
+    return converter(m_impl.coeff(index));
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    const bool Vectorizable = TensorEvaluator<ArgType, Device>::PacketAccess &
+        internal::type_casting_traits<SrcType, TargetType>::VectorizedCast;
+    return PacketConv<LoadMode, Vectorizable>::run(m_impl, index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    const double cast_cost = TensorOpCost::CastCost<SrcType, TargetType>();
+    if (vectorized) {
+      const double SrcCoeffRatio =
+          internal::type_casting_traits<SrcType, TargetType>::SrcCoeffRatio;
+      const double TgtCoeffRatio =
+          internal::type_casting_traits<SrcType, TargetType>::TgtCoeffRatio;
+      return m_impl.costPerCoeff(vectorized) * (SrcCoeffRatio / PacketSize) +
+          TensorOpCost(0, 0, TgtCoeffRatio * (cast_cost / PacketSize));
+    } else {
+      return m_impl.costPerCoeff(vectorized) + TensorOpCost(0, 0, cast_cost);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+  protected:
+  template <int LoadMode, bool ActuallyVectorize>
+  struct PacketConv {
+    static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType run(const TensorEvaluator<ArgType, Device>& impl, Index index) {
+      internal::scalar_cast_op<SrcType, TargetType> converter;
+      EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+      for (int i = 0; i < PacketSize; ++i) {
+        values[i] = converter(impl.coeff(index+i));
+      }
+      PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+      return rslt;
+    }
+  };
+
+  template <int LoadMode>
+  struct PacketConv<LoadMode, true> {
+    static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType run(const TensorEvaluator<ArgType, Device>& impl, Index index) {
+      const int SrcCoeffRatio = internal::type_casting_traits<SrcType, TargetType>::SrcCoeffRatio;
+      const int TgtCoeffRatio = internal::type_casting_traits<SrcType, TargetType>::TgtCoeffRatio;
+      PacketConverter<TensorEvaluator<ArgType, Device>, PacketSourceType, PacketReturnType,
+                      SrcCoeffRatio, TgtCoeffRatio> converter(impl);
+      return converter.template packet<LoadMode>(index);
+    }
+  };
+
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CONVERSION_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
@@ -0,0 +1,1104 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONVOLUTION_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CONVOLUTION_H
+
+namespace Eigen {
+
+/** \class TensorConvolution
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor convolution class.
+  *
+  *
+  */
+namespace internal {
+
+template <typename Index, typename InputDims, int NumKernelDims, int Layout>
+class IndexMapper {
+ public:
+  IndexMapper(const InputDims& input_dims, const array<Index, NumKernelDims>& kernel_dims,
+              const array<Index, NumKernelDims>& indices) {
+
+    array<Index, NumDims> dimensions = input_dims;
+    for (int i = 0; i < NumKernelDims; ++i) {
+      const Index index = indices[i];
+      const Index input_dim = input_dims[index];
+      const Index kernel_dim = kernel_dims[i];
+      const Index result_dim = input_dim - kernel_dim + 1;
+      dimensions[index] = result_dim;
+    }
+
+    array<Index, NumDims> inputStrides;
+    array<Index, NumDims> outputStrides;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      inputStrides[0] = 1;
+      outputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        inputStrides[i] = inputStrides[i-1] * input_dims[i-1];
+        outputStrides[i] = outputStrides[i-1] * dimensions[i-1];
+      }
+    } else {
+      inputStrides[NumDims - 1] = 1;
+      outputStrides[NumDims - 1] = 1;
+      for (int i = static_cast<int>(NumDims) - 2; i >= 0; --i) {
+        inputStrides[i] = inputStrides[i + 1] * input_dims[i + 1];
+        outputStrides[i] = outputStrides[i + 1] * dimensions[i + 1];
+      }
+    }
+
+    array<Index, NumDims> cudaInputDimensions;
+    array<Index, NumDims> cudaOutputDimensions;
+    array<Index, NumDims> tmp = dimensions;
+    array<Index, NumDims> ordering;
+    const size_t offset = static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                              ? 0
+                              : NumDims - NumKernelDims;
+    for (int i = 0; i < NumKernelDims; ++i) {
+      const Index index = i + offset;
+      ordering[index] = indices[i];
+      tmp[indices[i]] = -1;
+      cudaInputDimensions[index] = input_dims[indices[i]];
+      cudaOutputDimensions[index] = dimensions[indices[i]];
+    }
+
+    int written = static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                      ? NumKernelDims
+                      : 0;
+    for (int i = 0; i < NumDims; ++i) {
+      if (tmp[i] >= 0) {
+        ordering[written] = i;
+        cudaInputDimensions[written] = input_dims[i];
+        cudaOutputDimensions[written] = dimensions[i];
+        ++written;
+      }
+    }
+
+    for (int i = 0; i < NumDims; ++i) {
+      m_inputStrides[i] = inputStrides[ordering[i]];
+      m_outputStrides[i] = outputStrides[ordering[i]];
+    }
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = 0; i < NumDims; ++i) {
+        if (i > NumKernelDims) {
+          m_cudaInputStrides[i] =
+              m_cudaInputStrides[i - 1] * cudaInputDimensions[i - 1];
+          m_cudaOutputStrides[i] =
+              m_cudaOutputStrides[i - 1] * cudaOutputDimensions[i - 1];
+        } else {
+          m_cudaInputStrides[i] = 1;
+          m_cudaOutputStrides[i] = 1;
+        }
+      }
+    } else {
+      for (int i = NumDims - 1; i >= 0; --i) {
+        if (i + 1 < offset) {
+          m_cudaInputStrides[i] =
+              m_cudaInputStrides[i + 1] * cudaInputDimensions[i + 1];
+          m_cudaOutputStrides[i] =
+              m_cudaOutputStrides[i + 1] * cudaOutputDimensions[i + 1];
+        } else {
+          m_cudaInputStrides[i] = 1;
+          m_cudaOutputStrides[i] = 1;
+        }
+      }
+    }
+  }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Index mapCudaInputPlaneToTensorInputOffset(Index p) const {
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int d = NumDims - 1; d > NumKernelDims; --d) {
+        const Index idx = p / m_cudaInputStrides[d];
+        inputIndex += idx * m_inputStrides[d];
+        p -= idx * m_cudaInputStrides[d];
+      }
+      inputIndex += p * m_inputStrides[NumKernelDims];
+    } else {
+      std::ptrdiff_t limit = 0;
+      if (NumKernelDims < NumDims) {
+        limit = NumDims - NumKernelDims - 1;
+      }
+      for (int d = 0; d < limit; ++d) {
+        const Index idx = p / m_cudaInputStrides[d];
+        inputIndex += idx * m_inputStrides[d];
+        p -= idx * m_cudaInputStrides[d];
+      }
+      inputIndex += p * m_inputStrides[limit];
+    }
+    return inputIndex;
+  }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Index mapCudaOutputPlaneToTensorOutputOffset(Index p) const {
+    Index outputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int d = NumDims - 1; d > NumKernelDims; --d) {
+        const Index idx = p / m_cudaOutputStrides[d];
+        outputIndex += idx * m_outputStrides[d];
+        p -= idx * m_cudaOutputStrides[d];
+      }
+      outputIndex += p * m_outputStrides[NumKernelDims];
+    } else {
+      std::ptrdiff_t limit = 0;
+      if (NumKernelDims < NumDims) {
+        limit = NumDims - NumKernelDims - 1;
+      }
+      for (int d = 0; d < limit; ++d) {
+        const Index idx = p / m_cudaOutputStrides[d];
+        outputIndex += idx * m_outputStrides[d];
+        p -= idx * m_cudaOutputStrides[d];
+      }
+      outputIndex += p * m_outputStrides[limit];
+    }
+    return outputIndex;
+  }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Index mapCudaInputKernelToTensorInputOffset(Index i) const {
+    const size_t offset = static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                              ? 0
+                              : NumDims - NumKernelDims;
+    return i * m_inputStrides[offset];
+  }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Index mapCudaOutputKernelToTensorOutputOffset(Index i) const {
+    const size_t offset = static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                              ? 0
+                              : NumDims - NumKernelDims;
+    return i * m_outputStrides[offset];
+  }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Index mapCudaInputKernelToTensorInputOffset(Index i, Index j) const {
+    const size_t offset = static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                              ? 0
+                              : NumDims - NumKernelDims;
+    return i * m_inputStrides[offset] + j * m_inputStrides[offset + 1];
+  }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Index mapCudaOutputKernelToTensorOutputOffset(Index i, Index j) const {
+    const size_t offset = static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                              ? 0
+                              : NumDims - NumKernelDims;
+    return i * m_outputStrides[offset] + j * m_outputStrides[offset + 1];
+  }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Index mapCudaInputKernelToTensorInputOffset(Index i, Index j, Index k) const {
+    const size_t offset = static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                              ? 0
+                              : NumDims - NumKernelDims;
+    return i * m_inputStrides[offset] + j * m_inputStrides[offset + 1] +
+           k * m_inputStrides[offset + 2];
+  }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Index mapCudaOutputKernelToTensorOutputOffset(Index i, Index j, Index k) const {
+    const size_t offset = static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                              ? 0
+                              : NumDims - NumKernelDims;
+    return i * m_outputStrides[offset] + j * m_outputStrides[offset + 1] +
+           k * m_outputStrides[offset + 2];
+  }
+
+ private:
+  static const int NumDims = internal::array_size<InputDims>::value;
+  array<Index, NumDims> m_inputStrides;
+  array<Index, NumDims> m_outputStrides;
+  array<Index, NumDims> m_cudaInputStrides;
+  array<Index, NumDims> m_cudaOutputStrides;
+};
+
+
+
+template<typename Dimensions, typename InputXprType, typename KernelXprType>
+struct traits<TensorConvolutionOp<Dimensions, InputXprType, KernelXprType> >
+{
+  // Type promotion to handle the case where the types of the lhs and the rhs are different.
+  typedef typename promote_storage_type<typename InputXprType::Scalar,
+                                        typename KernelXprType::Scalar>::ret Scalar;
+  typedef typename promote_storage_type<typename traits<InputXprType>::StorageKind,
+                                        typename traits<KernelXprType>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<InputXprType>::Index,
+                                      typename traits<KernelXprType>::Index>::type Index;
+  typedef typename InputXprType::Nested LhsNested;
+  typedef typename KernelXprType::Nested RhsNested;
+  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef typename remove_reference<RhsNested>::type _RhsNested;
+  static const int NumDimensions = traits<InputXprType>::NumDimensions;
+  static const int Layout = traits<InputXprType>::Layout;
+
+  enum {
+    Flags = 0
+  };
+};
+
+template<typename Dimensions, typename InputXprType, typename KernelXprType>
+struct eval<TensorConvolutionOp<Dimensions, InputXprType, KernelXprType>, Eigen::Dense>
+{
+  typedef const TensorConvolutionOp<Dimensions, InputXprType, KernelXprType>& type;
+};
+
+template<typename Dimensions, typename InputXprType, typename KernelXprType>
+struct nested<TensorConvolutionOp<Dimensions, InputXprType, KernelXprType>, 1, typename eval<TensorConvolutionOp<Dimensions, InputXprType, KernelXprType> >::type>
+{
+  typedef TensorConvolutionOp<Dimensions, InputXprType, KernelXprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename Indices, typename InputXprType, typename KernelXprType>
+class TensorConvolutionOp : public TensorBase<TensorConvolutionOp<Indices, InputXprType, KernelXprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorConvolutionOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename internal::promote_storage_type<typename InputXprType::CoeffReturnType,
+                                                  typename KernelXprType::CoeffReturnType>::ret CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorConvolutionOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorConvolutionOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorConvolutionOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorConvolutionOp(const InputXprType& input, const KernelXprType& kernel, const Indices& dims)
+      : m_input_xpr(input), m_kernel_xpr(kernel), m_indices(dims) {}
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const Indices& indices() const { return m_indices; }
+
+    /** \returns the nested expressions */
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const typename internal::remove_all<typename InputXprType::Nested>::type&
+    inputExpression() const { return m_input_xpr; }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const typename internal::remove_all<typename KernelXprType::Nested>::type&
+    kernelExpression() const { return m_kernel_xpr; }
+
+  protected:
+    typename InputXprType::Nested m_input_xpr;
+    typename KernelXprType::Nested m_kernel_xpr;
+    const Indices m_indices;
+};
+
+
+template<typename Indices, typename InputArgType, typename KernelArgType, typename Device>
+struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelArgType>, Device>
+{
+  typedef TensorConvolutionOp<Indices, InputArgType, KernelArgType> XprType;
+
+  static const int NumDims = internal::array_size<typename TensorEvaluator<InputArgType, Device>::Dimensions>::value;
+  static const int NumKernelDims = internal::array_size<Indices>::value;
+  typedef typename XprType::Index Index;
+  typedef DSizes<Index, NumDims> Dimensions;
+
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = TensorEvaluator<InputArgType, Device>::IsAligned & TensorEvaluator<KernelArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<InputArgType, Device>::PacketAccess & TensorEvaluator<KernelArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<InputArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_inputImpl(op.inputExpression(), device), m_kernelImpl(op.kernelExpression(), device), m_kernelArg(op.kernelExpression()), m_kernel(NULL), m_local_kernel(false), m_device(device)
+  {
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<InputArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<KernelArgType, Device>::Layout)), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    const typename TensorEvaluator<InputArgType, Device>::Dimensions& input_dims = m_inputImpl.dimensions();
+    const typename TensorEvaluator<KernelArgType, Device>::Dimensions& kernel_dims = m_kernelImpl.dimensions();
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_inputStride[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_inputStride[i] = m_inputStride[i - 1] * input_dims[i - 1];
+      }
+    } else {
+      m_inputStride[NumDims - 1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_inputStride[i] = m_inputStride[i + 1] * input_dims[i + 1];
+      }
+    }
+
+    m_dimensions = m_inputImpl.dimensions();
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = 0; i < NumKernelDims; ++i) {
+        const Index index = op.indices()[i];
+        const Index input_dim = input_dims[index];
+        const Index kernel_dim = kernel_dims[i];
+        const Index result_dim = input_dim - kernel_dim + 1;
+        m_dimensions[index] = result_dim;
+        if (i > 0) {
+          m_kernelStride[i] = m_kernelStride[i - 1] * kernel_dims[i - 1];
+        } else {
+          m_kernelStride[0] = 1;
+        }
+        m_indexStride[i] = m_inputStride[index];
+      }
+
+      m_outputStride[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_outputStride[i] = m_outputStride[i - 1] * m_dimensions[i - 1];
+      }
+    } else {
+      for (int i = NumKernelDims - 1; i >= 0; --i) {
+        const Index index = op.indices()[i];
+        const Index input_dim = input_dims[index];
+        const Index kernel_dim = kernel_dims[i];
+        const Index result_dim = input_dim - kernel_dim + 1;
+        m_dimensions[index] = result_dim;
+        if (i < NumKernelDims - 1) {
+          m_kernelStride[i] = m_kernelStride[i + 1] * kernel_dims[i + 1];
+        } else {
+          m_kernelStride[NumKernelDims - 1] = 1;
+        }
+        m_indexStride[i] = m_inputStride[index];
+      }
+
+      m_outputStride[NumDims - 1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_outputStride[i] = m_outputStride[i + 1] * m_dimensions[i + 1];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+    m_inputImpl.evalSubExprsIfNeeded(NULL);
+    preloadKernel();
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_inputImpl.cleanup();
+    if (m_local_kernel) {
+      m_device.deallocate((void*)m_kernel);
+      m_local_kernel = false;
+    }
+    m_kernel = NULL;
+  }
+
+  void evalTo(typename XprType::Scalar* buffer) {
+    evalSubExprsIfNeeded(NULL);
+    for (int i = 0; i < dimensions().TotalSize(); ++i) {
+      buffer[i] += coeff(i);
+    }
+    cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    CoeffReturnType result = CoeffReturnType(0);
+    convolve(firstInput(index), 0, NumKernelDims-1, result);
+    return result;
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC PacketReturnType packet(const Index index) const
+  {
+    Index indices[2] = {index, index+PacketSize-1};
+    Index startInputs[2] = {0, 0};
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx0 = indices[0] / m_outputStride[i];
+        const Index idx1 = indices[1] / m_outputStride[i];
+        startInputs[0] += idx0 * m_inputStride[i];
+        startInputs[1] += idx1 * m_inputStride[i];
+        indices[0] -= idx0 * m_outputStride[i];
+        indices[1] -= idx1 * m_outputStride[i];
+      }
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx0 = indices[0] / m_outputStride[i];
+        const Index idx1 = indices[1] / m_outputStride[i];
+        startInputs[0] += idx0 * m_inputStride[i];
+        startInputs[1] += idx1 * m_inputStride[i];
+        indices[0] -= idx0 * m_outputStride[i];
+        indices[1] -= idx1 * m_outputStride[i];
+      }
+    }
+    startInputs[0] += indices[0];
+    startInputs[1] += indices[1];
+
+    if (startInputs[1]-startInputs[0] == PacketSize-1) {
+      PacketReturnType result = internal::pset1<PacketReturnType>(0);
+      convolvePacket(startInputs[0], 0, NumKernelDims-1, result);
+      return result;
+    } else {
+      EIGEN_ALIGN_MAX Scalar data[PacketSize];
+      data[0] = Scalar(0);
+      convolve(startInputs[0], 0, NumKernelDims-1, data[0]);
+      for (int i = 1; i < PacketSize-1; ++i) {
+        data[i] = Scalar(0);
+        convolve(firstInput(index+i), 0, NumKernelDims-1, data[i]);
+      }
+      data[PacketSize-1] = Scalar(0);
+      convolve(startInputs[1], 0, NumKernelDims-1, data[PacketSize-1]);
+      return internal::pload<PacketReturnType>(data);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    const double kernel_size = m_kernelImpl.dimensions().TotalSize();
+    // We ignore the use of fused multiply-add.
+    const double convolve_compute_cost =
+        TensorOpCost::AddCost<Scalar>() + TensorOpCost::MulCost<Scalar>();
+    const double firstIndex_compute_cost =
+        NumDims *
+        (2 * TensorOpCost::AddCost<Index>() + 2 * TensorOpCost::MulCost<Index>() +
+         TensorOpCost::DivCost<Index>());
+    return TensorOpCost(0, 0, firstIndex_compute_cost, vectorized, PacketSize) +
+           kernel_size * (m_inputImpl.costPerCoeff(vectorized) +
+                          m_kernelImpl.costPerCoeff(vectorized) +
+                          TensorOpCost(0, 0, convolve_compute_cost, vectorized,
+                                       PacketSize));
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ private:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index firstInput(Index index) const {
+    Index startInput = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx = index / m_outputStride[i];
+        startInput += idx * m_inputStride[i];
+        index -= idx * m_outputStride[i];
+      }
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx = index / m_outputStride[i];
+        startInput += idx * m_inputStride[i];
+        index -= idx * m_outputStride[i];
+      }
+    }
+    startInput += index;
+    return startInput;
+  }
+
+  EIGEN_DEVICE_FUNC void convolve(Index firstIndex, Index firstKernel, int DimIndex, CoeffReturnType& accum) const {
+    for (int j = 0; j < m_kernelImpl.dimensions()[DimIndex]; ++j) {
+      const Index input = firstIndex + j * m_indexStride[DimIndex];
+      const Index kernel = firstKernel + j * m_kernelStride[DimIndex];
+      if (DimIndex > 0) {
+        convolve(input, kernel, DimIndex-1, accum);
+      } else {
+        accum += m_inputImpl.coeff(input) * m_kernel[kernel];
+      }
+    }
+  }
+
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC void convolvePacket(Index firstIndex, Index firstKernel, int DimIndex, Packet& accum) const {
+    for (int j = 0; j < m_kernelImpl.dimensions()[DimIndex]; ++j) {
+      const Index input = firstIndex + j * m_indexStride[DimIndex];
+      const Index kernel = firstKernel + j * m_kernelStride[DimIndex];
+      if (DimIndex > 0) {
+        convolvePacket(input, kernel, DimIndex-1, accum);
+      } else {
+        accum = internal::pmadd<Packet>(m_inputImpl.template packet<Unaligned>(input), internal::pset1<Packet>(m_kernel[kernel]), accum);
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void preloadKernel() {
+    // Don't make a local copy of the kernel unless we have to (i.e. it's an
+    // expression that needs to be evaluated)
+    const Scalar* in_place = m_kernelImpl.data();
+    if (in_place) {
+      m_kernel = in_place;
+      m_local_kernel = false;
+    } else {
+      size_t kernel_sz = m_kernelImpl.dimensions().TotalSize() * sizeof(Scalar);
+      Scalar* local = (Scalar*)m_device.allocate(kernel_sz);
+      typedef TensorEvalToOp<const KernelArgType> EvalTo;
+      EvalTo evalToTmp(local, m_kernelArg);
+      const bool PacketAccess = internal::IsVectorizable<Device, KernelArgType>::value;
+      internal::TensorExecutor<const EvalTo, Device, PacketAccess>::run(evalToTmp, m_device);
+
+      m_kernel = local;
+      m_local_kernel = true;
+    }
+  }
+
+  array<Index, NumDims> m_inputStride;
+  array<Index, NumDims> m_outputStride;
+
+  array<Index, NumKernelDims> m_indexStride;
+  array<Index, NumKernelDims> m_kernelStride;
+  TensorEvaluator<InputArgType, Device> m_inputImpl;
+  TensorEvaluator<KernelArgType, Device> m_kernelImpl;
+  Dimensions m_dimensions;
+
+  KernelArgType m_kernelArg;
+  const Scalar* m_kernel;
+  bool m_local_kernel;
+  const Device& m_device;
+};
+
+
+
+
+// Use an optimized implementation of the evaluation code for GPUs whenever possible.
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+
+template <int StaticKernelSize>
+struct GetKernelSize {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int operator() (const int /*kernelSize*/) const {
+    return StaticKernelSize;
+  }
+};
+template <>
+struct GetKernelSize<Dynamic> {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int operator() (const int kernelSize) const {
+    return kernelSize;
+  }
+};
+
+template <typename InputEvaluator, typename Index, typename InputDims,
+          int StaticKernelSize>
+__global__ void EigenConvolutionKernel1D(
+    InputEvaluator eval,
+    const internal::IndexMapper<Index, InputDims, 1, InputEvaluator::Layout>
+        indexMapper,
+    const float* __restrict kernel, const int numPlanes, const int numX,
+    const int maxX, const int kernelSize, float* buffer) {
+  extern __shared__ float s[];
+
+  const int first_x = blockIdx.x * maxX;
+  const int last_x = (first_x + maxX < numX ? first_x + maxX : numX) - 1;
+  const int num_x_input = last_x - first_x + GetKernelSize<StaticKernelSize>()(kernelSize);
+  const int num_x_output = last_x - first_x + 1;
+
+  const int first_plane = blockIdx.y * blockDim.y;
+  const int plane_stride = blockDim.y * gridDim.y;
+
+  for (int p = first_plane + threadIdx.y; p < numPlanes; p += plane_stride) {
+    // Load inputs to shared memory
+    const int plane_input_offset = indexMapper.mapCudaInputPlaneToTensorInputOffset(p);
+    const int plane_kernel_offset = threadIdx.y * num_x_input;
+    #pragma unroll
+    for (int i = threadIdx.x; i < num_x_input; i += blockDim.x) {
+      const int tensor_index = plane_input_offset + indexMapper.mapCudaInputKernelToTensorInputOffset(i+first_x);
+      s[i + plane_kernel_offset] = eval.coeff(tensor_index);
+    }
+
+    __syncthreads();
+
+    // Compute the convolution
+    const int plane_output_offset = indexMapper.mapCudaOutputPlaneToTensorOutputOffset(p);
+
+    #pragma unroll
+    for (int i = threadIdx.x; i < num_x_output; i += blockDim.x) {
+      const int kernel_offset = plane_kernel_offset + i;
+      float result = 0.0f;
+      #pragma unroll
+      for (int k = 0; k < GetKernelSize<StaticKernelSize>()(kernelSize); ++k) {
+        result += s[k + kernel_offset] * kernel[k];
+      }
+      const int tensor_index = plane_output_offset + indexMapper.mapCudaOutputKernelToTensorOutputOffset(i+first_x);
+      buffer[tensor_index] = result;
+    }
+    __syncthreads();
+  }
+};
+
+template <typename InputEvaluator, typename Index, typename InputDims,
+          int StaticKernelSizeX, int StaticKernelSizeY>
+__global__ void EigenConvolutionKernel2D(
+    InputEvaluator eval,
+    const internal::IndexMapper<Index, InputDims, 2, InputEvaluator::Layout>
+        indexMapper,
+    const float* __restrict kernel, const int numPlanes, const int numX,
+    const int maxX, const int numY, const int maxY, const int kernelSizeX,
+    const int kernelSizeY, float* buffer) {
+  extern __shared__ float s[];
+
+  const int first_x = blockIdx.x * maxX;
+  const int last_x = (first_x + maxX < numX ? first_x + maxX : numX) - 1;
+  const int num_x_input = last_x - first_x + GetKernelSize<StaticKernelSizeX>()(kernelSizeX);
+  const int num_x_output = last_x - first_x + 1;
+
+  const int first_y = blockIdx.y * maxY;
+  const int last_y = (first_y + maxY < numY ? first_y + maxY : numY) - 1;
+  const int num_y_input = last_y - first_y + GetKernelSize<StaticKernelSizeY>()(kernelSizeY);
+  const int num_y_output = last_y - first_y + 1;
+
+  const int first_plane = blockIdx.z * blockDim.z;
+  const int plane_stride = blockDim.z * gridDim.z;
+
+  for (int p = first_plane + threadIdx.z; p < numPlanes; p += plane_stride) {
+
+    const int plane_input_offset = indexMapper.mapCudaInputPlaneToTensorInputOffset(p);
+    const int plane_kernel_offset = threadIdx.z * num_y_input;
+
+    // Load inputs to shared memory
+    #pragma unroll
+    for (int j = threadIdx.y; j < num_y_input; j += blockDim.y) {
+      const int input_offset = num_x_input * (j + plane_kernel_offset);
+      #pragma unroll
+      for (int i = threadIdx.x; i < num_x_input; i += blockDim.x) {
+        const int tensor_index = plane_input_offset + indexMapper.mapCudaInputKernelToTensorInputOffset(i+first_x, j+first_y);
+        s[i + input_offset] = eval.coeff(tensor_index);
+      }
+    }
+
+    __syncthreads();
+
+    // Convolution
+    const int plane_output_offset = indexMapper.mapCudaOutputPlaneToTensorOutputOffset(p);
+
+    #pragma unroll
+    for (int j = threadIdx.y; j < num_y_output; j += blockDim.y) {
+      #pragma unroll
+      for (int i = threadIdx.x; i < num_x_output; i += blockDim.x) {
+        float result = 0.0f;
+        #pragma unroll
+        for (int l = 0; l < GetKernelSize<StaticKernelSizeY>()(kernelSizeY); ++l) {
+          const int kernel_offset = kernelSizeX * l;
+          const int input_offset = i + num_x_input * (j + l + plane_kernel_offset);
+          #pragma unroll
+          for (int k = 0; k < GetKernelSize<StaticKernelSizeX>()(kernelSizeX); ++k) {
+            result += s[k + input_offset] * kernel[k + kernel_offset];
+          }
+        }
+        const int tensor_index = plane_output_offset + indexMapper.mapCudaOutputKernelToTensorOutputOffset(i+first_x, j+first_y);
+        buffer[tensor_index] = result;
+      }
+    }
+
+    __syncthreads();
+  }
+};
+
+template <typename InputEvaluator, typename Index, typename InputDims>
+__global__ void EigenConvolutionKernel3D(
+    InputEvaluator eval,
+    const internal::IndexMapper<Index, InputDims, 3, InputEvaluator::Layout>
+        indexMapper,
+    const float* __restrict kernel, const size_t numPlanes, const size_t numX,
+    const size_t maxX, const size_t numY, const size_t maxY, const size_t numZ,
+    const size_t maxZ, const size_t kernelSizeX, const size_t kernelSizeY,
+    const size_t kernelSizeZ, float* buffer) {
+  extern __shared__ float s[];
+
+  // Load inputs to shared memory
+  const int first_x = blockIdx.x * maxX;
+  const int last_x = (first_x + maxX < numX ? first_x + maxX : numX) - 1;
+  const int num_x_input = last_x - first_x + kernelSizeX;
+
+  const int first_y = blockIdx.y * maxY;
+  const int last_y = (first_y + maxY < numY ? first_y + maxY : numY) - 1;
+  const int num_y_input = last_y - first_y + kernelSizeY;
+
+  const int first_z = blockIdx.z * maxZ;
+  const int last_z = (first_z + maxZ < numZ ? first_z + maxZ : numZ) - 1;
+  const int num_z_input = last_z - first_z + kernelSizeZ;
+
+  for (int p = 0; p < numPlanes; ++p) {
+
+    const int plane_input_offset = indexMapper.mapCudaInputPlaneToTensorInputOffset(p);
+    const int plane_kernel_offset = 0;
+
+    for (int k = threadIdx.z; k < num_z_input; k += blockDim.z) {
+      for (int j = threadIdx.y; j < num_y_input; j += blockDim.y) {
+        for (int i = threadIdx.x; i < num_x_input; i += blockDim.x) {
+          const int tensor_index = plane_input_offset + indexMapper.mapCudaInputKernelToTensorInputOffset(i+first_x, j+first_y, k+first_z);
+          s[i + num_x_input * (j + num_y_input * (k + plane_kernel_offset))] = eval.coeff(tensor_index);
+        }
+      }
+    }
+
+    __syncthreads();
+
+    // Convolution
+    const int num_z_output = last_z - first_z + 1;
+    const int num_y_output = last_y - first_y + 1;
+    const int num_x_output = last_x - first_x + 1;
+    const int plane_output_offset = indexMapper.mapCudaOutputPlaneToTensorOutputOffset(p);
+
+    for (int k = threadIdx.z; k < num_z_output; k += blockDim.z) {
+      for (int j = threadIdx.y; j < num_y_output; j += blockDim.y) {
+        for (int i = threadIdx.x; i < num_x_output; i += blockDim.x) {
+          float result = 0.0f;
+          for (int n = 0; n < kernelSizeZ; ++n) {
+            for (int m = 0; m < kernelSizeY; ++m) {
+              for (int l = 0; l < kernelSizeX; ++l) {
+                result += s[i + l + num_x_input * (j + m + num_y_input * (k + n + plane_kernel_offset))] * kernel[l + kernelSizeX * (m + kernelSizeY * n)];
+              }
+            }
+          }
+          const int tensor_index = plane_output_offset + indexMapper.mapCudaOutputKernelToTensorOutputOffset(i+first_x, j+first_y, k+first_z);
+          buffer[tensor_index] = result;
+        }
+      }
+    }
+    __syncthreads();
+  }
+};
+
+
+
+template<typename Indices, typename InputArgType, typename KernelArgType>
+struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelArgType>, GpuDevice>
+{
+  typedef TensorConvolutionOp<Indices, InputArgType, KernelArgType> XprType;
+
+  static const int NumDims =  internal::array_size<typename TensorEvaluator<InputArgType, GpuDevice>::Dimensions>::value;
+  static const int NumKernelDims = internal::array_size<Indices>::value;
+  typedef typename XprType::Index Index;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename TensorEvaluator<KernelArgType, GpuDevice>::Dimensions KernelDimensions;
+
+  enum {
+    IsAligned = TensorEvaluator<InputArgType, GpuDevice>::IsAligned & TensorEvaluator<KernelArgType, GpuDevice>::IsAligned,
+    PacketAccess = false,
+    Layout = TensorEvaluator<InputArgType, GpuDevice>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const GpuDevice& device)
+      : m_inputImpl(op.inputExpression(), device), m_kernelArg(op.kernelExpression()), m_kernelImpl(op.kernelExpression(), device), m_indices(op.indices()), m_buf(NULL), m_kernel(NULL), m_local_kernel(false), m_device(device)
+  {
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<InputArgType, GpuDevice>::Layout) == static_cast<int>(TensorEvaluator<KernelArgType, GpuDevice>::Layout)), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    const typename TensorEvaluator<InputArgType, GpuDevice>::Dimensions& input_dims = m_inputImpl.dimensions();
+    const typename TensorEvaluator<KernelArgType, GpuDevice>::Dimensions& kernel_dims = m_kernelImpl.dimensions();
+
+    m_dimensions = m_inputImpl.dimensions();
+    for (int i = 0; i < NumKernelDims; ++i) {
+      const Index index = op.indices()[i];
+      const Index input_dim = input_dims[index];
+      const Index kernel_dim = kernel_dims[i];
+      const Index result_dim = input_dim - kernel_dim + 1;
+      m_dimensions[index] = result_dim;
+    }
+  }
+
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, GpuDevice>::type PacketReturnType;
+  typedef typename InputArgType::Scalar Scalar;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) {
+    preloadKernel();
+    m_inputImpl.evalSubExprsIfNeeded(NULL);
+    if (data) {
+      executeEval(data);
+      return false;
+    } else {
+      m_buf = (Scalar*)m_device.allocate(dimensions().TotalSize() * sizeof(Scalar));
+      executeEval(m_buf);
+      return true;
+    }
+  }
+
+  EIGEN_STRONG_INLINE void cleanup() {
+    m_inputImpl.cleanup();
+    if (m_buf) {
+      m_device.deallocate(m_buf);
+      m_buf = NULL;
+    }
+    if (m_local_kernel) {
+      m_device.deallocate((void*)m_kernel);
+      m_local_kernel = false;
+    }
+    m_kernel = NULL;
+  }
+
+  EIGEN_STRONG_INLINE void preloadKernel() {
+    // Don't make a local copy of the kernel unless we have to (i.e. it's an
+    // expression that needs to be evaluated)
+    const Scalar* in_place = m_kernelImpl.data();
+    if (in_place) {
+      m_kernel = in_place;
+      m_local_kernel = false;
+    } else {
+      size_t kernel_sz = m_kernelImpl.dimensions().TotalSize() * sizeof(Scalar);
+      Scalar* local = (Scalar*)m_device.allocate(kernel_sz);
+      typedef TensorEvalToOp<const KernelArgType> EvalTo;
+      EvalTo evalToTmp(local, m_kernelArg);
+      const bool PacketAccess = internal::IsVectorizable<GpuDevice, KernelArgType>::value;
+      internal::TensorExecutor<const EvalTo, GpuDevice, PacketAccess>::run(evalToTmp, m_device);
+
+      m_kernel = local;
+      m_local_kernel = true;
+    }
+  }
+
+  static unsigned int ceil(unsigned int num, unsigned int denom) {
+    const unsigned int rounded_toward_zero = num / denom;
+    if (num > rounded_toward_zero * denom) {
+      return rounded_toward_zero + 1;
+    }
+    return rounded_toward_zero;
+  }
+
+  void executeEval(Scalar* data) const {
+    typedef typename TensorEvaluator<InputArgType, GpuDevice>::Dimensions InputDims;
+
+    const int maxSharedMem = m_device.sharedMemPerBlock();
+    const int maxThreadsPerBlock = m_device.maxCudaThreadsPerBlock();
+    const int maxBlocksPerProcessor = m_device.maxCudaThreadsPerMultiProcessor() / maxThreadsPerBlock;
+    const int numMultiProcessors = m_device.getNumCudaMultiProcessors();
+    const int warpSize = 32;
+
+    switch (NumKernelDims) {
+      case 1: {
+        const int kernel_size = m_kernelImpl.dimensions().TotalSize();
+
+        const int numX = dimensions()[m_indices[0]];
+        const int numP = dimensions().TotalSize() / numX;
+        int maxX;
+        dim3 block_size;
+
+        const int single_stride_dim =
+            static_cast<int>(Layout) == static_cast<int>(ColMajor)
+                ? 0
+                : m_inputImpl.dimensions().rank() - 1;
+        if (m_indices[0] == single_stride_dim) {
+          // Maximum the reuse
+          const int inner_dim = ((maxSharedMem / (sizeof(Scalar)) - kernel_size + 1 + 31) / 32) * 32;
+          maxX = numext::mini<int>(inner_dim, numX);
+          const int maxP = numext::mini<int>(maxSharedMem / ((kernel_size - 1 + maxX) * sizeof(Scalar)), numP);
+          block_size.x = numext::mini(maxThreadsPerBlock, maxX);
+          block_size.y = numext::mini<int>(maxThreadsPerBlock / block_size.x, maxP);
+        }
+        else {
+          // Read as much as possible alongside the inner most dimension, that is the plane
+          const int inner_dim = maxSharedMem / ((warpSize + kernel_size) * sizeof(Scalar));
+          const int maxP = numext::mini<int>(inner_dim, numP);
+          maxX = numext::mini<int>(maxSharedMem / (inner_dim * sizeof(Scalar)) - kernel_size + 1, numX);
+
+          block_size.x = numext::mini(warpSize, maxX);
+          block_size.y = numext::mini<int>(maxThreadsPerBlock/block_size.x, maxP);
+        }
+
+        const int shared_mem = block_size.y * (maxX + kernel_size - 1) * sizeof(Scalar);
+        assert(shared_mem <= maxSharedMem);
+
+        const int num_x_blocks = ceil(numX, maxX);
+        const int blocksPerProcessor = numext::mini(maxBlocksPerProcessor, maxSharedMem / shared_mem);
+        const int num_y_blocks = ceil(numMultiProcessors * blocksPerProcessor, num_x_blocks);
+
+        dim3 num_blocks(num_x_blocks, numext::mini<int>(num_y_blocks, ceil(numP, block_size.y)));
+
+
+        //cout << "launching 1D kernel with block_size.x: " << block_size.x << " block_size.y: " << block_size.y << " num_blocks.x: " << num_blocks.x << " num_blocks.y: " << num_blocks.y << " maxX: " << maxX << " shared_mem: " << shared_mem << " in stream " << m_device.stream() << endl;
+
+        const array<Index, 1> indices(m_indices[0]);
+        const array<Index, 1> kernel_dims(m_kernelImpl.dimensions()[0]);
+        internal::IndexMapper<Index, InputDims, 1, Layout> indexMapper(
+            m_inputImpl.dimensions(), kernel_dims, indices);
+        switch(kernel_size) {
+          case 4: {
+            LAUNCH_CUDA_KERNEL((EigenConvolutionKernel1D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims, 4>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, 4, data);
+            break;
+          }
+          case 7: {
+            LAUNCH_CUDA_KERNEL((EigenConvolutionKernel1D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims, 7>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, 7, data);
+            break;
+          }
+          default: {
+            LAUNCH_CUDA_KERNEL((EigenConvolutionKernel1D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims, Dynamic>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, kernel_size, data);
+          }
+        }
+        break;
+      }
+
+      case 2: {
+        const int idxX =
+            static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : 1;
+        const int idxY =
+            static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 1 : 0;
+        const int kernel_size_x = m_kernelImpl.dimensions()[idxX];
+        const int kernel_size_y = m_kernelImpl.dimensions()[idxY];
+
+        const int numX = dimensions()[m_indices[idxX]];
+        const int numY = dimensions()[m_indices[idxY]];
+        const int numP = dimensions().TotalSize() / (numX*numY);
+
+        const float scaling_factor = sqrtf(static_cast<float>(maxSharedMem) / (sizeof(Scalar) * kernel_size_y * kernel_size_x));
+
+        // Snap maxX to warp size
+        int inner_dim = ((static_cast<int>(scaling_factor * kernel_size_x) - kernel_size_x + 1 + 32) / 32) * 32;
+        const int maxX = numext::mini<int>(inner_dim, numX);
+        const int maxY = numext::mini<int>(maxSharedMem / (sizeof(Scalar) * (maxX + kernel_size_x - 1)) - kernel_size_y + 1, numY);
+        const int maxP = numext::mini<int>(maxSharedMem / ((kernel_size_x - 1 + maxX) * (kernel_size_y - 1 + maxY) * sizeof(Scalar)), numP);
+
+        dim3 block_size;
+        block_size.x = numext::mini(1024, maxX);
+        block_size.y = numext::mini<int>(1024/block_size.x, maxY);
+        block_size.z = numext::mini<int>(1024/(block_size.x*block_size.y), maxP);
+
+        const int shared_mem = block_size.z * (maxX + kernel_size_x - 1) * (maxY + kernel_size_y - 1) * sizeof(Scalar);
+        assert(shared_mem <= maxSharedMem);
+
+        const int num_x_blocks = ceil(numX, maxX);
+        const int num_y_blocks = ceil(numY, maxY);
+        const int blocksPerProcessor = numext::mini(maxBlocksPerProcessor, maxSharedMem / shared_mem);
+        const int num_z_blocks = ceil(numMultiProcessors * blocksPerProcessor, num_x_blocks * num_y_blocks);
+
+        dim3 num_blocks(num_x_blocks, num_y_blocks, numext::mini<int>(num_z_blocks, ceil(numP, block_size.z)));
+
+
+        //cout << "launching 2D kernel with block_size.x: " << block_size.x << " block_size.y: " << block_size.y  << " block_size.z: " << block_size.z << " num_blocks.x: " << num_blocks.x << " num_blocks.y: " << num_blocks.y << " num_blocks.z: " << num_blocks.z << " maxX: " << maxX << " maxY: " << maxY << " maxP: " << maxP << " shared_mem: " << shared_mem << " in stream " << m_device.stream() << endl;
+
+        const array<Index, 2> indices(m_indices[idxX], m_indices[idxY]);
+        const array<Index, 2> kernel_dims(m_kernelImpl.dimensions()[idxX],
+                                          m_kernelImpl.dimensions()[idxY]);
+        internal::IndexMapper<Index, InputDims, 2, Layout> indexMapper(
+            m_inputImpl.dimensions(), kernel_dims, indices);
+        switch (kernel_size_x) {
+          case 4: {
+            switch (kernel_size_y) {
+              case 7: {
+                LAUNCH_CUDA_KERNEL((EigenConvolutionKernel2D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims, 4, 7>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, numY, maxY, 4, 7, data);
+                break;
+              }
+              default: {
+                LAUNCH_CUDA_KERNEL((EigenConvolutionKernel2D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims, 4, Dynamic>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, numY, maxY, 4, kernel_size_y, data);
+                break;
+              }
+            }
+            break;
+          }
+          case 7: {
+            switch (kernel_size_y) {
+              case 4: {
+                LAUNCH_CUDA_KERNEL((EigenConvolutionKernel2D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims, 7, 4>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, numY, maxY, 7, 4, data);
+                break;
+              }
+              default: {
+                LAUNCH_CUDA_KERNEL((EigenConvolutionKernel2D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims, 7, Dynamic>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, numY, maxY, 7, kernel_size_y, data);
+                break;
+              }
+            }
+            break;
+          }
+          default: {
+            LAUNCH_CUDA_KERNEL((EigenConvolutionKernel2D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims, Dynamic, Dynamic>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, numY, maxY, kernel_size_x, kernel_size_y, data);
+            break;
+          }
+        }
+        break;
+      }
+
+      case 3: {
+        const int idxX =
+            static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : 2;
+        const int idxY =
+            static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 1 : 1;
+        const int idxZ =
+            static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 2 : 0;
+
+        const int kernel_size_x = m_kernelImpl.dimensions()[idxX];
+        const int kernel_size_y = m_kernelImpl.dimensions()[idxY];
+        const int kernel_size_z = m_kernelImpl.dimensions()[idxZ];
+
+        const int numX = dimensions()[m_indices[idxX]];
+        const int numY = dimensions()[m_indices[idxY]];
+        const int numZ = dimensions()[m_indices[idxZ]];
+        const int numP = dimensions().TotalSize() / (numX*numY*numZ);
+
+        const int maxX = numext::mini<int>(128, numext::mini<int>(maxSharedMem / (sizeof(Scalar) * kernel_size_y * kernel_size_z) - kernel_size_x + 1, numX));
+        const int maxY = numext::mini<int>(128, numext::mini<int>(maxSharedMem / (sizeof(Scalar) * (maxX + kernel_size_x - 1) * kernel_size_z) - kernel_size_y + 1, numY));
+        const int maxZ = numext::mini<int>(128, numext::mini<int>(maxSharedMem / (sizeof(Scalar) * (maxX + kernel_size_x - 1) * (maxY + kernel_size_y - 1)) - kernel_size_z + 1, numZ));
+
+        dim3 block_size;
+        block_size.x = numext::mini(32, maxX);
+        block_size.y = numext::mini(32, maxY);
+        block_size.z = numext::mini<int>(1024/(block_size.x*block_size.y), maxZ);
+        dim3 num_blocks(ceil(numX, maxX), ceil(numY, maxY), ceil(numZ, maxZ));
+
+        const int shared_mem = (maxX + kernel_size_x - 1) * (maxY + kernel_size_y - 1) * (maxZ + kernel_size_z - 1) * sizeof(Scalar);
+        assert(shared_mem <= maxSharedMem);
+
+        //cout << "launching 3D kernel with block_size.x: " << block_size.x << " block_size.y: " << block_size.y  << " block_size.z: " << block_size.z << " num_blocks.x: " << num_blocks.x << " num_blocks.y: " << num_blocks.y << " num_blocks.z: " << num_blocks.z  << " shared_mem: " << shared_mem << " in stream " << m_device.stream() << endl;
+        const array<Index, 3> indices(m_indices[idxX], m_indices[idxY],
+                                      m_indices[idxZ]);
+        const array<Index, 3> kernel_dims(m_kernelImpl.dimensions()[idxX],
+                                          m_kernelImpl.dimensions()[idxY],
+                                          m_kernelImpl.dimensions()[idxZ]);
+        internal::IndexMapper<Index, InputDims, 3, Layout> indexMapper(
+            m_inputImpl.dimensions(), kernel_dims, indices);
+
+        LAUNCH_CUDA_KERNEL((EigenConvolutionKernel3D<TensorEvaluator<InputArgType, GpuDevice>, Index, InputDims>), num_blocks, block_size, shared_mem, m_device, m_inputImpl, indexMapper, m_kernel, numP, numX, maxX, numY, maxY, numZ, maxZ, kernel_size_x, kernel_size_y, kernel_size_z, data);
+        break;
+      }
+
+      default: {
+        EIGEN_STATIC_ASSERT((NumKernelDims >= 1 && NumKernelDims <= 3), THIS_METHOD_IS_ONLY_FOR_OBJECTS_OF_A_SPECIFIC_SIZE);
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    eigen_assert(m_buf);
+    eigen_assert(index < m_dimensions.TotalSize());
+    return m_buf[index];
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(const Index index) const
+  {
+    eigen_assert(m_buf);
+    eigen_assert(index < m_dimensions.TotalSize());
+    return internal::ploadt<PacketReturnType, LoadMode>(m_buf+index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    // TODO(rmlarsen): FIXME: For now, this is just a copy of the CPU cost
+    // model.
+    const double kernel_size = m_kernelImpl.dimensions().TotalSize();
+    // We ignore the use of fused multiply-add.
+    const double convolve_compute_cost =
+        TensorOpCost::AddCost<Scalar>() + TensorOpCost::MulCost<Scalar>();
+    const double firstIndex_compute_cost =
+        NumDims *
+        (2 * TensorOpCost::AddCost<Index>() + 2 * TensorOpCost::MulCost<Index>() +
+         TensorOpCost::DivCost<Index>());
+    return TensorOpCost(0, 0, firstIndex_compute_cost, vectorized, PacketSize) +
+           kernel_size * (m_inputImpl.costPerCoeff(vectorized) +
+                          m_kernelImpl.costPerCoeff(vectorized) +
+                          TensorOpCost(0, 0, convolve_compute_cost, vectorized,
+                                       PacketSize));
+  }
+
+ private:
+  // No assignment (copies are needed by the kernels)
+  TensorEvaluator& operator = (const TensorEvaluator&);
+
+  TensorEvaluator<InputArgType, GpuDevice> m_inputImpl;
+  TensorEvaluator<KernelArgType, GpuDevice> m_kernelImpl;
+  KernelArgType m_kernelArg;
+  Indices m_indices;
+  Dimensions m_dimensions;
+  Scalar* m_buf;
+  const Scalar* m_kernel;
+  bool m_local_kernel;
+
+  const GpuDevice& m_device;
+};
+#endif
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CONVOLUTION_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorCostModel.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorCostModel.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorCostModel.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorCostModel.h
@@ -0,0 +1,212 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Rasmus Munk Larsen <rmlarsen@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_COST_MODEL_H
+#define EIGEN_CXX11_TENSOR_TENSOR_COST_MODEL_H
+
+namespace Eigen {
+
+/** \class TensorEvaluator
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief A cost model used to limit the number of threads used for evaluating
+  * tensor expression.
+  *
+  */
+
+// Class storing the cost of evaluating a tensor expression in terms of the
+// estimated number of operand bytes loads, bytes stored, and compute cycles.
+class TensorOpCost {
+ public:
+  // TODO(rmlarsen): Fix the scalar op costs in Eigen proper. Even a simple
+  // model based on minimal reciprocal throughput numbers from Intel or
+  // Agner Fog's tables would be better than what is there now.
+  template <typename ArgType>
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int MulCost() {
+    return internal::functor_traits<
+        internal::scalar_product_op<ArgType, ArgType> >::Cost;
+  }
+  template <typename ArgType>
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int AddCost() {
+    return internal::functor_traits<internal::scalar_sum_op<ArgType> >::Cost;
+  }
+  template <typename ArgType>
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int DivCost() {
+    return internal::functor_traits<
+        internal::scalar_quotient_op<ArgType, ArgType> >::Cost;
+  }
+  template <typename ArgType>
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int ModCost() {
+    return internal::functor_traits<internal::scalar_mod_op<ArgType> >::Cost;
+  }
+  template <typename SrcType, typename TargetType>
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int CastCost() {
+    return internal::functor_traits<
+        internal::scalar_cast_op<SrcType, TargetType> >::Cost;
+  }
+
+  EIGEN_DEVICE_FUNC
+  TensorOpCost() : bytes_loaded_(0), bytes_stored_(0), compute_cycles_(0) {}
+  EIGEN_DEVICE_FUNC
+  TensorOpCost(double bytes_loaded, double bytes_stored, double compute_cycles)
+      : bytes_loaded_(bytes_loaded),
+        bytes_stored_(bytes_stored),
+        compute_cycles_(compute_cycles) {}
+
+  EIGEN_DEVICE_FUNC
+  TensorOpCost(double bytes_loaded, double bytes_stored, double compute_cycles,
+               bool vectorized, double packet_size)
+      : bytes_loaded_(bytes_loaded),
+        bytes_stored_(bytes_stored),
+        compute_cycles_(vectorized ? compute_cycles / packet_size
+                                   : compute_cycles) {
+    eigen_assert(bytes_loaded >= 0 && (numext::isfinite)(bytes_loaded));
+    eigen_assert(bytes_stored >= 0 && (numext::isfinite)(bytes_stored));
+    eigen_assert(compute_cycles >= 0 && (numext::isfinite)(compute_cycles));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double bytes_loaded() const {
+    return bytes_loaded_;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double bytes_stored() const {
+    return bytes_stored_;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double compute_cycles() const {
+    return compute_cycles_;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double total_cost(
+      double load_cost, double store_cost, double compute_cost) const {
+    return load_cost * bytes_loaded_ + store_cost * bytes_stored_ +
+           compute_cost * compute_cycles_;
+  }
+
+  // Drop memory access component. Intended for cases when memory accesses are
+  // sequential or are completely masked by computations.
+  EIGEN_DEVICE_FUNC void dropMemoryCost() {
+    bytes_loaded_ = 0;
+    bytes_stored_ = 0;
+  }
+
+  // TODO(rmlarsen): Define min in terms of total cost, not elementwise.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost cwiseMin(
+      const TensorOpCost& rhs) const {
+    double bytes_loaded = numext::mini(bytes_loaded_, rhs.bytes_loaded());
+    double bytes_stored = numext::mini(bytes_stored_, rhs.bytes_stored());
+    double compute_cycles = numext::mini(compute_cycles_, rhs.compute_cycles());
+    return TensorOpCost(bytes_loaded, bytes_stored, compute_cycles);
+  }
+
+  // TODO(rmlarsen): Define max in terms of total cost, not elementwise.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost cwiseMax(
+      const TensorOpCost& rhs) const {
+    double bytes_loaded = numext::maxi(bytes_loaded_, rhs.bytes_loaded());
+    double bytes_stored = numext::maxi(bytes_stored_, rhs.bytes_stored());
+    double compute_cycles = numext::maxi(compute_cycles_, rhs.compute_cycles());
+    return TensorOpCost(bytes_loaded, bytes_stored, compute_cycles);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost& operator+=(
+      const TensorOpCost& rhs) {
+    bytes_loaded_ += rhs.bytes_loaded();
+    bytes_stored_ += rhs.bytes_stored();
+    compute_cycles_ += rhs.compute_cycles();
+    return *this;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost& operator*=(double rhs) {
+    bytes_loaded_ *= rhs;
+    bytes_stored_ *= rhs;
+    compute_cycles_ *= rhs;
+    return *this;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE friend TensorOpCost operator+(
+      TensorOpCost lhs, const TensorOpCost& rhs) {
+    lhs += rhs;
+    return lhs;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE friend TensorOpCost operator*(
+      TensorOpCost lhs, double rhs) {
+    lhs *= rhs;
+    return lhs;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE friend TensorOpCost operator*(
+      double lhs, TensorOpCost rhs) {
+    rhs *= lhs;
+    return rhs;
+  }
+
+  friend std::ostream& operator<<(std::ostream& os, const TensorOpCost& tc) {
+    return os << "[bytes_loaded = " << tc.bytes_loaded()
+              << ", bytes_stored = " << tc.bytes_stored()
+              << ", compute_cycles = " << tc.compute_cycles() << "]";
+  }
+
+ private:
+  double bytes_loaded_;
+  double bytes_stored_;
+  double compute_cycles_;
+};
+
+// TODO(rmlarsen): Implement a policy that chooses an "optimal" number of theads
+// in [1:max_threads] instead of just switching multi-threading off for small
+// work units.
+template <typename Device>
+class TensorCostModel {
+ public:
+  // Scaling from Eigen compute cost to device cycles.
+  static const int kDeviceCyclesPerComputeCycle = 1;
+
+ // Costs in device cycles.
+  static const int kStartupCycles = 100000;
+  static const int kPerThreadCycles = 100000;
+  static const int kTaskSize = 40000;
+
+  // Returns the number of threads in [1:max_threads] to use for
+  // evaluating an expression with the given output size and cost per
+  // coefficient.
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int numThreads(
+      double output_size, const TensorOpCost& cost_per_coeff, int max_threads) {
+    double cost = totalCost(output_size, cost_per_coeff);
+    int threads = (cost - kStartupCycles) / kPerThreadCycles + 0.9;
+    return numext::mini(max_threads, numext::maxi(1, threads));
+  }
+
+  // taskSize assesses parallel task size.
+  // Value of 1.0 means ideal parallel task size. Values < 1.0 mean that task
+  // granularity needs to be increased to mitigate parallelization overheads.
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double taskSize(
+      double output_size, const TensorOpCost& cost_per_coeff) {
+    return totalCost(output_size, cost_per_coeff) / kTaskSize;
+  }
+
+ private:
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double totalCost(
+      double output_size, const TensorOpCost& cost_per_coeff) {
+    // Cost of memory fetches from L2 cache. 64 is typical cache line size.
+    // 11 is L2 cache latency on Haswell.
+    // We don't know whether data is in L1, L2 or L3. But we are most interested
+    // in single-threaded computational time around 100us-10ms (smaller time
+    // is too small for parallelization, larger time is not intersting
+    // either because we are probably using all available threads already).
+    // And for the target time range, L2 seems to be what matters. Data set
+    // fitting into L1 is too small to take noticeable time. Data set fitting
+    // only into L3 presumably will take more than 10ms to load and process.
+    const double kLoadCycles = 1.0 / 64 * 11;
+    const double kStoreCycles = 1.0 / 64 * 11;
+    // Scaling from Eigen compute cost to device cycles.
+    return output_size *
+        cost_per_coeff.total_cost(kLoadCycles, kStoreCycles,
+                                  kDeviceCyclesPerComputeCycle);
+  }
+};
+
+}  // namespace Eigen
+
+#endif  // EIGEN_CXX11_TENSOR_TENSOR_COST_MODEL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h
@@ -0,0 +1,313 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_CUSTOM_OP_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CUSTOM_OP_H
+
+namespace Eigen {
+
+/** \class TensorCustomUnaryOp
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor custom class.
+  *
+  *
+  */
+namespace internal {
+template<typename CustomUnaryFunc, typename XprType>
+struct traits<TensorCustomUnaryOp<CustomUnaryFunc, XprType> >
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::StorageKind StorageKind;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = traits<XprType>::NumDimensions;
+  static const int Layout = traits<XprType>::Layout;
+};
+
+template<typename CustomUnaryFunc, typename XprType>
+struct eval<TensorCustomUnaryOp<CustomUnaryFunc, XprType>, Eigen::Dense>
+{
+  typedef const TensorCustomUnaryOp<CustomUnaryFunc, XprType>& type;
+};
+
+template<typename CustomUnaryFunc, typename XprType>
+struct nested<TensorCustomUnaryOp<CustomUnaryFunc, XprType> >
+{
+  typedef TensorCustomUnaryOp<CustomUnaryFunc, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename CustomUnaryFunc, typename XprType>
+class TensorCustomUnaryOp : public TensorBase<TensorCustomUnaryOp<CustomUnaryFunc, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename internal::traits<TensorCustomUnaryOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename internal::nested<TensorCustomUnaryOp>::type Nested;
+  typedef typename internal::traits<TensorCustomUnaryOp>::StorageKind StorageKind;
+  typedef typename internal::traits<TensorCustomUnaryOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCustomUnaryOp(const XprType& expr, const CustomUnaryFunc& func)
+      : m_expr(expr), m_func(func) {}
+
+  EIGEN_DEVICE_FUNC
+  const CustomUnaryFunc& func() const { return m_func; }
+
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename XprType::Nested>::type&
+  expression() const { return m_expr; }
+
+  protected:
+    typename XprType::Nested m_expr;
+    const CustomUnaryFunc m_func;
+};
+
+
+// Eval as rvalue
+template<typename CustomUnaryFunc, typename XprType, typename Device>
+struct TensorEvaluator<const TensorCustomUnaryOp<CustomUnaryFunc, XprType>, Device>
+{
+  typedef TensorCustomUnaryOp<CustomUnaryFunc, XprType> ArgType;
+  typedef typename internal::traits<ArgType>::Index Index;
+  static const int NumDims = internal::traits<ArgType>::NumDimensions;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename internal::remove_const<typename ArgType::Scalar>::type Scalar;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = (internal::packet_traits<Scalar>::size > 1),
+    BlockAccess = false,
+    Layout = TensorEvaluator<XprType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const ArgType& op, const Device& device)
+      : m_op(op), m_device(device), m_result(NULL)
+  {
+    m_dimensions = op.func().dimensions(op.expression());
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
+    if (data) {
+      evalTo(data);
+      return false;
+    } else {
+      m_result = static_cast<CoeffReturnType*>(
+          m_device.allocate(dimensions().TotalSize() * sizeof(Scalar)));
+      evalTo(m_result);
+      return true;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    if (m_result != NULL) {
+      m_device.deallocate(m_result);
+      m_result = NULL;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+    return m_result[index];
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_result + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    // TODO(rmlarsen): Extend CustomOp API to return its cost estimate.
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return m_result; }
+
+ protected:
+  EIGEN_DEVICE_FUNC void evalTo(Scalar* data) {
+    TensorMap<Tensor<CoeffReturnType, NumDims, Layout, Index> > result(
+        data, m_dimensions);
+    m_op.func().eval(m_op.expression(), result, m_device);
+  }
+
+  Dimensions m_dimensions;
+  const ArgType m_op;
+  const Device& m_device;
+  CoeffReturnType* m_result;
+};
+
+
+
+/** \class TensorCustomBinaryOp
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor custom class.
+  *
+  *
+  */
+namespace internal {
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType>
+struct traits<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> >
+{
+  typedef typename internal::promote_storage_type<typename LhsXprType::Scalar,
+                                                  typename RhsXprType::Scalar>::ret Scalar;
+  typedef typename internal::promote_storage_type<typename LhsXprType::CoeffReturnType,
+                                                  typename RhsXprType::CoeffReturnType>::ret CoeffReturnType;
+  typedef typename promote_storage_type<typename traits<LhsXprType>::StorageKind,
+                                        typename traits<RhsXprType>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<LhsXprType>::Index,
+                                      typename traits<RhsXprType>::Index>::type Index;
+  typedef typename LhsXprType::Nested LhsNested;
+  typedef typename RhsXprType::Nested RhsNested;
+  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef typename remove_reference<RhsNested>::type _RhsNested;
+  static const int NumDimensions = traits<LhsXprType>::NumDimensions;
+  static const int Layout = traits<LhsXprType>::Layout;
+};
+
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType>
+struct eval<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, Eigen::Dense>
+{
+  typedef const TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>& type;
+};
+
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType>
+struct nested<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> >
+{
+  typedef TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType>
+class TensorCustomBinaryOp : public TensorBase<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename internal::traits<TensorCustomBinaryOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename internal::traits<TensorCustomBinaryOp>::CoeffReturnType CoeffReturnType;
+  typedef typename internal::nested<TensorCustomBinaryOp>::type Nested;
+  typedef typename internal::traits<TensorCustomBinaryOp>::StorageKind StorageKind;
+  typedef typename internal::traits<TensorCustomBinaryOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCustomBinaryOp(const LhsXprType& lhs, const RhsXprType& rhs, const CustomBinaryFunc& func)
+
+      : m_lhs_xpr(lhs), m_rhs_xpr(rhs), m_func(func) {}
+
+  EIGEN_DEVICE_FUNC
+  const CustomBinaryFunc& func() const { return m_func; }
+
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename LhsXprType::Nested>::type&
+  lhsExpression() const { return m_lhs_xpr; }
+
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename RhsXprType::Nested>::type&
+  rhsExpression() const { return m_rhs_xpr; }
+
+  protected:
+    typename LhsXprType::Nested m_lhs_xpr;
+    typename RhsXprType::Nested m_rhs_xpr;
+    const CustomBinaryFunc m_func;
+};
+
+
+// Eval as rvalue
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType, typename Device>
+struct TensorEvaluator<const TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, Device>
+{
+  typedef TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> XprType;
+  typedef typename internal::traits<XprType>::Index Index;
+  static const int NumDims = internal::traits<XprType>::NumDimensions;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = (internal::packet_traits<Scalar>::size > 1),
+    BlockAccess = false,
+    Layout = TensorEvaluator<LhsXprType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_op(op), m_device(device), m_result(NULL)
+  {
+    m_dimensions = op.func().dimensions(op.lhsExpression(), op.rhsExpression());
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
+    if (data) {
+      evalTo(data);
+      return false;
+    } else {
+      m_result = static_cast<Scalar *>(m_device.allocate(dimensions().TotalSize() * sizeof(Scalar)));
+      evalTo(m_result);
+      return true;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    if (m_result != NULL) {
+      m_device.deallocate(m_result);
+      m_result = NULL;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+    return m_result[index];
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_result + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    // TODO(rmlarsen): Extend CustomOp API to return its cost estimate.
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return m_result; }
+
+ protected:
+  EIGEN_DEVICE_FUNC void evalTo(Scalar* data) {
+    TensorMap<Tensor<Scalar, NumDims, Layout> > result(data, m_dimensions);
+    m_op.func().eval(m_op.lhsExpression(), m_op.rhsExpression(), result, m_device);
+  }
+
+  Dimensions m_dimensions;
+  const XprType m_op;
+  const Device& m_device;
+  CoeffReturnType* m_result;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CUSTOM_OP_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDevice.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDevice.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDevice.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDevice.h
@@ -0,0 +1,68 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H
+#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H
+
+namespace Eigen {
+
+/** \class TensorDevice
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Pseudo expression providing an operator = that will evaluate its argument
+  * on the specified computing 'device' (GPU, thread pool, ...)
+  *
+  * Example:
+  *    C.device(EIGEN_GPU) = A + B;
+  *
+  * Todo: operator *= and /=.
+  */
+
+template <typename ExpressionType, typename DeviceType> class TensorDevice {
+  public:
+    TensorDevice(const DeviceType& device, ExpressionType& expression) : m_device(device), m_expression(expression) {}
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE TensorDevice& operator=(const OtherDerived& other) {
+      typedef TensorAssignOp<ExpressionType, const OtherDerived> Assign;
+      Assign assign(m_expression, other);
+      internal::TensorExecutor<const Assign, DeviceType>::run(assign, m_device);
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE TensorDevice& operator+=(const OtherDerived& other) {
+      typedef typename OtherDerived::Scalar Scalar;
+      typedef TensorCwiseBinaryOp<internal::scalar_sum_op<Scalar>, const ExpressionType, const OtherDerived> Sum;
+      Sum sum(m_expression, other);
+      typedef TensorAssignOp<ExpressionType, const Sum> Assign;
+      Assign assign(m_expression, sum);
+      internal::TensorExecutor<const Assign, DeviceType>::run(assign, m_device);
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE TensorDevice& operator-=(const OtherDerived& other) {
+      typedef typename OtherDerived::Scalar Scalar;
+      typedef TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const ExpressionType, const OtherDerived> Difference;
+      Difference difference(m_expression, other);
+      typedef TensorAssignOp<ExpressionType, const Difference> Assign;
+      Assign assign(m_expression, difference);
+      internal::TensorExecutor<const Assign, DeviceType>::run(assign, m_device);
+      return *this;
+    }
+
+  protected:
+    const DeviceType& m_device;
+    ExpressionType& m_expression;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceCuda.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceCuda.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceCuda.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceCuda.h
@@ -0,0 +1,337 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#if defined(EIGEN_USE_GPU) && !defined(EIGEN_CXX11_TENSOR_TENSOR_DEVICE_CUDA_H)
+#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_CUDA_H
+
+namespace Eigen {
+
+static const int kCudaScratchSize = 1024;
+
+// This defines an interface that GPUDevice can take to use
+// CUDA streams underneath.
+class StreamInterface {
+ public:
+  virtual ~StreamInterface() {}
+
+  virtual const cudaStream_t& stream() const = 0;
+  virtual const cudaDeviceProp& deviceProperties() const = 0;
+
+  // Allocate memory on the actual device where the computation will run
+  virtual void* allocate(size_t num_bytes) const = 0;
+  virtual void deallocate(void* buffer) const = 0;
+
+  // Return a scratchpad buffer of size 1k
+  virtual void* scratchpad() const = 0;
+
+  // Return a semaphore. The semaphore is initially initialized to 0, and
+  // each kernel using it is responsible for resetting to 0 upon completion
+  // to maintain the invariant that the semaphore is always equal to 0 upon
+  // each kernel start.
+  virtual unsigned int* semaphore() const = 0;
+};
+
+static cudaDeviceProp* m_deviceProperties;
+static bool m_devicePropInitialized = false;
+
+static void initializeDeviceProp() {
+  if (!m_devicePropInitialized) {
+    // Attempts to ensure proper behavior in the case of multiple threads
+    // calling this function simultaneously. This would be trivial to
+    // implement if we could use std::mutex, but unfortunately mutex don't
+    // compile with nvcc, so we resort to atomics and thread fences instead.
+    // Note that if the caller uses a compiler that doesn't support c++11 we
+    // can't ensure that the initialization is thread safe.
+#if __cplusplus >= 201103L
+    static std::atomic<bool> first(true);
+    if (first.exchange(false)) {
+#else
+    static bool first = true;
+    if (first) {
+      first = false;
+#endif
+      // We're the first thread to reach this point.
+      int num_devices;
+      cudaError_t status = cudaGetDeviceCount(&num_devices);
+      if (status != cudaSuccess) {
+        std::cerr << "Failed to get the number of CUDA devices: "
+                  << cudaGetErrorString(status)
+                  << std::endl;
+        assert(status == cudaSuccess);
+      }
+      m_deviceProperties = new cudaDeviceProp[num_devices];
+      for (int i = 0; i < num_devices; ++i) {
+        status = cudaGetDeviceProperties(&m_deviceProperties[i], i);
+        if (status != cudaSuccess) {
+          std::cerr << "Failed to initialize CUDA device #"
+                    << i
+                    << ": "
+                    << cudaGetErrorString(status)
+                    << std::endl;
+          assert(status == cudaSuccess);
+        }
+      }
+
+#if __cplusplus >= 201103L
+      std::atomic_thread_fence(std::memory_order_release);
+#endif
+      m_devicePropInitialized = true;
+    } else {
+      // Wait for the other thread to inititialize the properties.
+      while (!m_devicePropInitialized) {
+#if __cplusplus >= 201103L
+        std::atomic_thread_fence(std::memory_order_acquire);
+#endif
+        sleep(1);
+      }
+    }
+  }
+}
+
+static const cudaStream_t default_stream = cudaStreamDefault;
+
+class CudaStreamDevice : public StreamInterface {
+ public:
+  // Use the default stream on the current device
+  CudaStreamDevice() : stream_(&default_stream), scratch_(NULL), semaphore_(NULL) {
+    cudaGetDevice(&device_);
+    initializeDeviceProp();
+  }
+  // Use the default stream on the specified device
+  CudaStreamDevice(int device) : stream_(&default_stream), device_(device), scratch_(NULL), semaphore_(NULL) {
+    initializeDeviceProp();
+  }
+  // Use the specified stream. Note that it's the
+  // caller responsibility to ensure that the stream can run on
+  // the specified device. If no device is specified the code
+  // assumes that the stream is associated to the current gpu device.
+  CudaStreamDevice(const cudaStream_t* stream, int device = -1)
+      : stream_(stream), device_(device), scratch_(NULL), semaphore_(NULL) {
+    if (device < 0) {
+      cudaGetDevice(&device_);
+    } else {
+      int num_devices;
+      cudaError_t err = cudaGetDeviceCount(&num_devices);
+      EIGEN_UNUSED_VARIABLE(err)
+      assert(err == cudaSuccess);
+      assert(device < num_devices);
+      device_ = device;
+    }
+    initializeDeviceProp();
+  }
+
+  virtual ~CudaStreamDevice() {
+    if (scratch_) {
+      deallocate(scratch_);
+    }
+  }
+
+  const cudaStream_t& stream() const { return *stream_; }
+  const cudaDeviceProp& deviceProperties() const {
+    return m_deviceProperties[device_];
+  }
+  virtual void* allocate(size_t num_bytes) const {
+    cudaError_t err = cudaSetDevice(device_);
+    EIGEN_UNUSED_VARIABLE(err)
+    assert(err == cudaSuccess);
+    void* result;
+    err = cudaMalloc(&result, num_bytes);
+    assert(err == cudaSuccess);
+    assert(result != NULL);
+    return result;
+  }
+  virtual void deallocate(void* buffer) const {
+    cudaError_t err = cudaSetDevice(device_);
+    EIGEN_UNUSED_VARIABLE(err)
+    assert(err == cudaSuccess);
+    assert(buffer != NULL);
+    err = cudaFree(buffer);
+    assert(err == cudaSuccess);
+  }
+
+  virtual void* scratchpad() const {
+    if (scratch_ == NULL) {
+      scratch_ = allocate(kCudaScratchSize + sizeof(unsigned int));
+    }
+    return scratch_;
+  }
+
+  virtual unsigned int* semaphore() const {
+    if (semaphore_ == NULL) {
+      char* scratch = static_cast<char*>(scratchpad()) + kCudaScratchSize;
+      semaphore_ = reinterpret_cast<unsigned int*>(scratch);
+      cudaError_t err = cudaMemsetAsync(semaphore_, 0, sizeof(unsigned int), *stream_);
+      EIGEN_UNUSED_VARIABLE(err)
+      assert(err == cudaSuccess);
+    }
+    return semaphore_;
+  }
+
+ private:
+  const cudaStream_t* stream_;
+  int device_;
+  mutable void* scratch_;
+  mutable unsigned int* semaphore_;
+};
+
+struct GpuDevice {
+  // The StreamInterface is not owned: the caller is
+  // responsible for its initialization and eventual destruction.
+  explicit GpuDevice(const StreamInterface* stream) : stream_(stream), max_blocks_(INT_MAX) {
+    eigen_assert(stream);
+  }
+  explicit GpuDevice(const StreamInterface* stream, int num_blocks) : stream_(stream), max_blocks_(num_blocks) {
+    eigen_assert(stream);
+  }
+  // TODO(bsteiner): This is an internal API, we should not expose it.
+  EIGEN_STRONG_INLINE const cudaStream_t& stream() const {
+    return stream_->stream();
+  }
+
+  EIGEN_STRONG_INLINE void* allocate(size_t num_bytes) const {
+    return stream_->allocate(num_bytes);
+  }
+
+  EIGEN_STRONG_INLINE void deallocate(void* buffer) const {
+    stream_->deallocate(buffer);
+  }
+
+  EIGEN_STRONG_INLINE void* scratchpad() const {
+    return stream_->scratchpad();
+  }
+
+  EIGEN_STRONG_INLINE unsigned int* semaphore() const {
+    return stream_->semaphore();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpy(void* dst, const void* src, size_t n) const {
+#ifndef __CUDA_ARCH__
+    cudaError_t err = cudaMemcpyAsync(dst, src, n, cudaMemcpyDeviceToDevice,
+                                      stream_->stream());
+    EIGEN_UNUSED_VARIABLE(err)
+    assert(err == cudaSuccess);
+#else
+  eigen_assert(false && "The default device should be used instead to generate kernel code");
+#endif
+  }
+
+  EIGEN_STRONG_INLINE void memcpyHostToDevice(void* dst, const void* src, size_t n) const {
+    cudaError_t err =
+        cudaMemcpyAsync(dst, src, n, cudaMemcpyHostToDevice, stream_->stream());
+    EIGEN_UNUSED_VARIABLE(err)
+    assert(err == cudaSuccess);
+  }
+
+  EIGEN_STRONG_INLINE void memcpyDeviceToHost(void* dst, const void* src, size_t n) const {
+    cudaError_t err =
+        cudaMemcpyAsync(dst, src, n, cudaMemcpyDeviceToHost, stream_->stream());
+    EIGEN_UNUSED_VARIABLE(err)
+    assert(err == cudaSuccess);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memset(void* buffer, int c, size_t n) const {
+#ifndef __CUDA_ARCH__
+    cudaError_t err = cudaMemsetAsync(buffer, c, n, stream_->stream());
+    EIGEN_UNUSED_VARIABLE(err)
+    assert(err == cudaSuccess);
+#else
+  eigen_assert(false && "The default device should be used instead to generate kernel code");
+#endif
+  }
+
+  EIGEN_STRONG_INLINE size_t numThreads() const {
+    // FIXME
+    return 32;
+  }
+
+  EIGEN_STRONG_INLINE size_t firstLevelCacheSize() const {
+    // FIXME
+    return 48*1024;
+  }
+
+  EIGEN_STRONG_INLINE size_t lastLevelCacheSize() const {
+    // We won't try to take advantage of the l2 cache for the time being, and
+    // there is no l3 cache on cuda devices.
+    return firstLevelCacheSize();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void synchronize() const {
+#if defined(__CUDACC__) && !defined(__CUDA_ARCH__)
+    cudaError_t err = cudaStreamSynchronize(stream_->stream());
+    if (err != cudaSuccess) {
+      std::cerr << "Error detected in CUDA stream: "
+                << cudaGetErrorString(err)
+                << std::endl;
+      assert(err == cudaSuccess);
+    }
+#else
+    assert(false && "The default device should be used instead to generate kernel code");
+#endif
+  }
+
+  EIGEN_STRONG_INLINE int getNumCudaMultiProcessors() const {
+    return stream_->deviceProperties().multiProcessorCount;
+  }
+  EIGEN_STRONG_INLINE int maxCudaThreadsPerBlock() const {
+    return stream_->deviceProperties().maxThreadsPerBlock;
+  }
+  EIGEN_STRONG_INLINE int maxCudaThreadsPerMultiProcessor() const {
+    return stream_->deviceProperties().maxThreadsPerMultiProcessor;
+  }
+  EIGEN_STRONG_INLINE int sharedMemPerBlock() const {
+    return stream_->deviceProperties().sharedMemPerBlock;
+  }
+  EIGEN_STRONG_INLINE int majorDeviceVersion() const {
+    return stream_->deviceProperties().major;
+  }
+  EIGEN_STRONG_INLINE int minorDeviceVersion() const {
+    return stream_->deviceProperties().minor;
+  }
+
+  EIGEN_STRONG_INLINE int maxBlocks() const {
+    return max_blocks_;
+  }
+
+  // This function checks if the CUDA runtime recorded an error for the
+  // underlying stream device.
+  inline bool ok() const {
+#ifdef __CUDACC__
+    cudaError_t error = cudaStreamQuery(stream_->stream());
+    return (error == cudaSuccess) || (error == cudaErrorNotReady);
+#else
+    return false;
+#endif
+  }
+
+ private:
+  const StreamInterface* stream_;
+  int max_blocks_;
+};
+
+#define LAUNCH_CUDA_KERNEL(kernel, gridsize, blocksize, sharedmem, device, ...)             \
+  (kernel) <<< (gridsize), (blocksize), (sharedmem), (device).stream() >>> (__VA_ARGS__);   \
+  assert(cudaGetLastError() == cudaSuccess);
+
+
+// FIXME: Should be device and kernel specific.
+#ifdef __CUDACC__
+static EIGEN_DEVICE_FUNC inline void setCudaSharedMemConfig(cudaSharedMemConfig config) {
+#ifndef __CUDA_ARCH__
+  cudaError_t status = cudaDeviceSetSharedMemConfig(config);
+  EIGEN_UNUSED_VARIABLE(status)
+  assert(status == cudaSuccess);
+#else
+  EIGEN_UNUSED_VARIABLE(config)
+#endif
+}
+#endif
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_CUDA_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceDefault.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceDefault.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceDefault.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceDefault.h
@@ -0,0 +1,81 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_DEVICE_DEFAULT_H
+#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_DEFAULT_H
+
+
+namespace Eigen {
+
+// Default device for the machine (typically a single cpu core)
+struct DefaultDevice {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void* allocate(size_t num_bytes) const {
+    return internal::aligned_malloc(num_bytes);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void deallocate(void* buffer) const {
+    internal::aligned_free(buffer);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpy(void* dst, const void* src, size_t n) const {
+    ::memcpy(dst, src, n);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyHostToDevice(void* dst, const void* src, size_t n) const {
+    memcpy(dst, src, n);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyDeviceToHost(void* dst, const void* src, size_t n) const {
+    memcpy(dst, src, n);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memset(void* buffer, int c, size_t n) const {
+    ::memset(buffer, c, n);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t numThreads() const {
+#ifndef __CUDA_ARCH__
+    // Running on the host CPU
+    return 1;
+#else
+    // Running on a CUDA device
+    return 32;
+#endif
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t firstLevelCacheSize() const {
+#ifndef __CUDA_ARCH__
+    // Running on the host CPU
+    return l1CacheSize();
+#else
+    // Running on a CUDA device, return the amount of shared memory available.
+    return 48*1024;
+#endif
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t lastLevelCacheSize() const {
+#ifndef __CUDA_ARCH__
+    // Running single threaded on the host CPU
+    return l3CacheSize();
+#else
+    // Running on a CUDA device
+    return firstLevelCacheSize();
+#endif
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int majorDeviceVersion() const {
+#ifndef __CUDA_ARCH__
+    // Running single threaded on the host CPU
+    // Should return an enum that encodes the ISA supported by the CPU
+    return 1;
+#else
+    // Running on a CUDA device
+    return __CUDA_ARCH__ / 100;
+#endif
+  }
+};
+
+}  // namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_DEFAULT_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
@@ -0,0 +1,122 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#if defined(EIGEN_USE_SYCL) && !defined(EIGEN_CXX11_TENSOR_TENSOR_DEVICE_SYCL_H)
+#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_SYCL_H
+
+namespace Eigen {
+struct SyclDevice {
+  /// class members
+  /// sycl queue
+  mutable cl::sycl::queue m_queue;
+  /// std::map is the container used to make sure that we create only one buffer
+  /// per pointer. The lifespan of the buffer now depends on the lifespan of SyclDevice.
+  /// If a non-read-only pointer is needed to be accessed on the host we should manually deallocate it.
+  mutable std::map<const void *, std::shared_ptr<void>> buffer_map;
+  /// creating device by using selector
+  template<typename dev_Selector> SyclDevice(dev_Selector s)
+  :
+#ifdef EIGEN_EXCEPTIONS
+  m_queue(cl::sycl::queue(s, [=](cl::sycl::exception_list l) {
+    for (const auto& e : l) {
+      try {
+        std::rethrow_exception(e);
+      } catch (cl::sycl::exception e) {
+          std::cout << e.what() << std::endl;
+        }
+    }
+  }))
+#else
+  m_queue(cl::sycl::queue(s))
+#endif
+  {}
+  // destructor
+  ~SyclDevice() { deallocate_all(); }
+
+  template <typename T> void deallocate(T *p) const {
+    auto it = buffer_map.find(p);
+    if (it != buffer_map.end()) {
+      buffer_map.erase(it);
+      internal::aligned_free(p);
+    }
+  }
+  void deallocate_all() const {
+    std::map<const void *, std::shared_ptr<void>>::iterator it=buffer_map.begin();
+    while (it!=buffer_map.end()) {
+      auto p=it->first;
+      buffer_map.erase(it);
+      internal::aligned_free(const_cast<void*>(p));
+      it=buffer_map.begin();
+    }
+    buffer_map.clear();
+  }
+
+  /// creation of sycl accessor for a buffer. This function first tries to find
+  /// the buffer in the buffer_map. If found it gets the accessor from it, if not,
+  ///the function then adds an entry by creating a sycl buffer for that particular pointer.
+  template <cl::sycl::access::mode AcMd, typename T> inline cl::sycl::accessor<T, 1, AcMd, cl::sycl::access::target::global_buffer>
+  get_sycl_accessor(size_t num_bytes, cl::sycl::handler &cgh, const T * ptr) const {
+    return (get_sycl_buffer<T>(num_bytes, ptr)->template get_access<AcMd, cl::sycl::access::target::global_buffer>(cgh));
+  }
+
+  template<typename T> inline  std::pair<std::map<const void *, std::shared_ptr<void>>::iterator,bool> add_sycl_buffer(const T *ptr, size_t num_bytes) const {
+    using Type = cl::sycl::buffer<T, 1>;
+    std::pair<std::map<const void *, std::shared_ptr<void>>::iterator,bool> ret = buffer_map.insert(std::pair<const void *, std::shared_ptr<void>>(ptr, std::shared_ptr<void>(new Type(cl::sycl::range<1>(num_bytes)),
+      [](void *dataMem) { delete static_cast<Type*>(dataMem); })));
+    (static_cast<Type*>(buffer_map.at(ptr).get()))->set_final_data(nullptr);
+    return ret;
+  }
+
+  template <typename T> inline cl::sycl::buffer<T, 1>* get_sycl_buffer(size_t num_bytes,const T * ptr) const {
+    return static_cast<cl::sycl::buffer<T, 1>*>(add_sycl_buffer(ptr, num_bytes).first->second.get());
+  }
+
+  /// allocating memory on the cpu
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void *allocate(size_t) const {
+    return internal::aligned_malloc(8);
+  }
+
+  // some runtime conditions that can be applied here
+  bool isDeviceSuitable() const { return true; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpy(void *dst, const void *src, size_t n) const {
+    ::memcpy(dst, src, n);
+  }
+
+  template<typename T> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyHostToDevice(T *dst, const T *src, size_t n) const {
+    auto host_acc= (static_cast<cl::sycl::buffer<T, 1>*>(add_sycl_buffer(dst, n).first->second.get()))-> template get_access<cl::sycl::access::mode::discard_write, cl::sycl::access::target::host_buffer>();
+    memcpy(host_acc.get_pointer(), src, n);
+  }
+ /// whith the current implementation of sycl, the data is copied twice from device to host. This will be fixed soon.
+  template<typename T> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyDeviceToHost(T *dst, const T *src, size_t n) const {
+    auto it = buffer_map.find(src);
+    if (it != buffer_map.end()) {
+      auto host_acc= (static_cast<cl::sycl::buffer<T, 1>*>(it->second.get()))-> template get_access<cl::sycl::access::mode::read, cl::sycl::access::target::host_buffer>();
+      memcpy(dst,host_acc.get_pointer(),  n);
+    } else{
+      eigen_assert("no device memory found. The memory might be destroyed before creation");
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memset(void *buffer, int c, size_t n) const {
+    ::memset(buffer, c, n);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int majorDeviceVersion() const {
+  return 1;
+  }
+};
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_SYCL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
@@ -0,0 +1,279 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#if defined(EIGEN_USE_THREADS) && !defined(EIGEN_CXX11_TENSOR_TENSOR_DEVICE_THREAD_POOL_H)
+#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_THREAD_POOL_H
+
+namespace Eigen {
+
+// Use the SimpleThreadPool by default. We'll switch to the new non blocking
+// thread pool later.
+#ifndef EIGEN_USE_SIMPLE_THREAD_POOL
+template <typename Env> using ThreadPoolTempl = NonBlockingThreadPoolTempl<Env>;
+typedef NonBlockingThreadPool ThreadPool;
+#else
+template <typename Env> using ThreadPoolTempl = SimpleThreadPoolTempl<Env>;
+typedef SimpleThreadPool ThreadPool;
+#endif
+
+
+// Barrier is an object that allows one or more threads to wait until
+// Notify has been called a specified number of times.
+class Barrier {
+ public:
+  Barrier(unsigned int count) : state_(count << 1), notified_(false) {
+    eigen_assert(((count << 1) >> 1) == count);
+  }
+  ~Barrier() {
+    eigen_assert((state_>>1) == 0);
+  }
+
+  void Notify() {
+    unsigned int v = state_.fetch_sub(2, std::memory_order_acq_rel) - 2;
+    if (v != 1) {
+      eigen_assert(((v + 2) & ~1) != 0);
+      return;  // either count has not dropped to 0, or waiter is not waiting
+    }
+    std::unique_lock<std::mutex> l(mu_);
+    eigen_assert(!notified_);
+    notified_ = true;
+    cv_.notify_all();
+  }
+
+  void Wait() {
+    unsigned int v = state_.fetch_or(1, std::memory_order_acq_rel);
+    if ((v >> 1) == 0) return;
+    std::unique_lock<std::mutex> l(mu_);
+    while (!notified_) {
+      cv_.wait(l);
+    }
+  }
+
+ private:
+  std::mutex mu_;
+  std::condition_variable cv_;
+  std::atomic<unsigned int> state_;  // low bit is waiter flag
+  bool notified_;
+};
+
+
+// Notification is an object that allows a user to to wait for another
+// thread to signal a notification that an event has occurred.
+//
+// Multiple threads can wait on the same Notification object,
+// but only one caller must call Notify() on the object.
+struct Notification : Barrier {
+  Notification() : Barrier(1) {};
+};
+
+
+// Runs an arbitrary function and then calls Notify() on the passed in
+// Notification.
+template <typename Function, typename... Args> struct FunctionWrapperWithNotification
+{
+  static void run(Notification* n, Function f, Args... args) {
+    f(args...);
+    if (n) {
+      n->Notify();
+    }
+  }
+};
+
+template <typename Function, typename... Args> struct FunctionWrapperWithBarrier
+{
+  static void run(Barrier* b, Function f, Args... args) {
+    f(args...);
+    if (b) {
+      b->Notify();
+    }
+  }
+};
+
+template <typename SyncType>
+static EIGEN_STRONG_INLINE void wait_until_ready(SyncType* n) {
+  if (n) {
+    n->Wait();
+  }
+}
+
+
+// Build a thread pool device on top the an existing pool of threads.
+struct ThreadPoolDevice {
+  // The ownership of the thread pool remains with the caller.
+  ThreadPoolDevice(ThreadPoolInterface* pool, int num_cores) : pool_(pool), num_threads_(num_cores) { }
+
+  EIGEN_STRONG_INLINE void* allocate(size_t num_bytes) const {
+    return internal::aligned_malloc(num_bytes);
+  }
+
+  EIGEN_STRONG_INLINE void deallocate(void* buffer) const {
+    internal::aligned_free(buffer);
+  }
+
+  EIGEN_STRONG_INLINE void memcpy(void* dst, const void* src, size_t n) const {
+    ::memcpy(dst, src, n);
+  }
+  EIGEN_STRONG_INLINE void memcpyHostToDevice(void* dst, const void* src, size_t n) const {
+    memcpy(dst, src, n);
+  }
+  EIGEN_STRONG_INLINE void memcpyDeviceToHost(void* dst, const void* src, size_t n) const {
+    memcpy(dst, src, n);
+  }
+
+  EIGEN_STRONG_INLINE void memset(void* buffer, int c, size_t n) const {
+    ::memset(buffer, c, n);
+  }
+
+  EIGEN_STRONG_INLINE int numThreads() const {
+    return num_threads_;
+  }
+
+  EIGEN_STRONG_INLINE size_t firstLevelCacheSize() const {
+    return l1CacheSize();
+  }
+
+  EIGEN_STRONG_INLINE size_t lastLevelCacheSize() const {
+    // The l3 cache size is shared between all the cores.
+    return l3CacheSize() / num_threads_;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int majorDeviceVersion() const {
+    // Should return an enum that encodes the ISA supported by the CPU
+    return 1;
+  }
+
+  template <class Function, class... Args>
+  EIGEN_STRONG_INLINE Notification* enqueue(Function&& f, Args&&... args) const {
+    Notification* n = new Notification();
+    pool_->Schedule(std::bind(&FunctionWrapperWithNotification<Function, Args...>::run, n, f, args...));
+    return n;
+  }
+
+  template <class Function, class... Args>
+  EIGEN_STRONG_INLINE void enqueue_with_barrier(Barrier* b,
+                                                Function&& f,
+                                                Args&&... args) const {
+    pool_->Schedule(std::bind(
+        &FunctionWrapperWithBarrier<Function, Args...>::run, b, f, args...));
+  }
+
+  template <class Function, class... Args>
+  EIGEN_STRONG_INLINE void enqueueNoNotification(Function&& f, Args&&... args) const {
+    pool_->Schedule(std::bind(f, args...));
+  }
+
+  // Returns a logical thread index between 0 and pool_->NumThreads() - 1 if
+  // called from one of the threads in pool_. Returns -1 otherwise.
+  EIGEN_STRONG_INLINE int currentThreadId() const {
+    return pool_->CurrentThreadId();
+  }
+
+  // parallelFor executes f with [0, n) arguments in parallel and waits for
+  // completion. F accepts a half-open interval [first, last).
+  // Block size is choosen based on the iteration cost and resulting parallel
+  // efficiency. If block_align is not nullptr, it is called to round up the
+  // block size.
+  void parallelFor(Index n, const TensorOpCost& cost,
+                   std::function<Index(Index)> block_align,
+                   std::function<void(Index, Index)> f) const {
+    typedef TensorCostModel<ThreadPoolDevice> CostModel;
+    if (n <= 1 || numThreads() == 1 ||
+        CostModel::numThreads(n, cost, static_cast<int>(numThreads())) == 1) {
+      f(0, n);
+      return;
+    }
+
+    // Calculate block size based on (1) the iteration cost and (2) parallel
+    // efficiency. We want blocks to be not too small to mitigate
+    // parallelization overheads; not too large to mitigate tail
+    // effect and potential load imbalance and we also want number
+    // of blocks to be evenly dividable across threads.
+
+    double block_size_f = 1.0 / CostModel::taskSize(1, cost);
+    Index block_size = numext::mini(n, numext::maxi<Index>(1, block_size_f));
+    const Index max_block_size =
+        numext::mini(n, numext::maxi<Index>(1, 2 * block_size_f));
+    if (block_align) {
+      Index new_block_size = block_align(block_size);
+      eigen_assert(new_block_size >= block_size);
+      block_size = numext::mini(n, new_block_size);
+    }
+    Index block_count = divup(n, block_size);
+    // Calculate parallel efficiency as fraction of total CPU time used for
+    // computations:
+    double max_efficiency =
+        static_cast<double>(block_count) /
+        (divup<int>(block_count, numThreads()) * numThreads());
+    // Now try to increase block size up to max_block_size as long as it
+    // doesn't decrease parallel efficiency.
+    for (Index prev_block_count = block_count; prev_block_count > 1;) {
+      // This is the next block size that divides size into a smaller number
+      // of blocks than the current block_size.
+      Index coarser_block_size = divup(n, prev_block_count - 1);
+      if (block_align) {
+        Index new_block_size = block_align(coarser_block_size);
+        eigen_assert(new_block_size >= coarser_block_size);
+        coarser_block_size = numext::mini(n, new_block_size);
+      }
+      if (coarser_block_size > max_block_size) {
+        break;  // Reached max block size. Stop.
+      }
+      // Recalculate parallel efficiency.
+      const Index coarser_block_count = divup(n, coarser_block_size);
+      eigen_assert(coarser_block_count < prev_block_count);
+      prev_block_count = coarser_block_count;
+      const double coarser_efficiency =
+          static_cast<double>(coarser_block_count) /
+          (divup<int>(coarser_block_count, numThreads()) * numThreads());
+      if (coarser_efficiency + 0.01 >= max_efficiency) {
+        // Taking it.
+        block_size = coarser_block_size;
+        block_count = coarser_block_count;
+        if (max_efficiency < coarser_efficiency) {
+          max_efficiency = coarser_efficiency;
+        }
+      }
+    }
+
+    // Recursively divide size into halves until we reach block_size.
+    // Division code rounds mid to block_size, so we are guaranteed to get
+    // block_count leaves that do actual computations.
+    Barrier barrier(static_cast<unsigned int>(block_count));
+    std::function<void(Index, Index)> handleRange;
+    handleRange = [=, &handleRange, &barrier, &f](Index first, Index last) {
+      if (last - first <= block_size) {
+        // Single block or less, execute directly.
+        f(first, last);
+        barrier.Notify();
+        return;
+      }
+      // Split into halves and submit to the pool.
+      Index mid = first + divup((last - first) / 2, block_size) * block_size;
+      pool_->Schedule([=, &handleRange]() { handleRange(mid, last); });
+      pool_->Schedule([=, &handleRange]() { handleRange(first, mid); });
+    };
+    handleRange(0, n);
+    barrier.Wait();
+  }
+
+  // Convenience wrapper for parallelFor that does not align blocks.
+  void parallelFor(Index n, const TensorOpCost& cost,
+                   std::function<void(Index, Index)> f) const {
+    parallelFor(n, cost, nullptr, std::move(f));
+  }
+
+ private:
+  ThreadPoolInterface* pool_;
+  int num_threads_;
+};
+
+
+}  // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_THREAD_POOL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDimensionList.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDimensionList.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDimensionList.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDimensionList.h
@@ -0,0 +1,236 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_DIMENSION_LIST_H
+#define EIGEN_CXX11_TENSOR_TENSOR_DIMENSION_LIST_H
+
+namespace Eigen {
+
+/** \internal
+  *
+  * \class TensorDimensionList
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Special case of tensor index list used to list all the dimensions of a tensor of rank n.
+  *
+  * \sa Tensor
+  */
+
+template <typename Index, std::size_t Rank> struct DimensionList {
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+  const Index operator[] (const Index i) const { return i; }
+};
+
+namespace internal {
+
+template<typename Index, std::size_t Rank> struct array_size<DimensionList<Index, Rank> > {
+  static const size_t value = Rank;
+};
+template<typename Index, std::size_t Rank> struct array_size<const DimensionList<Index, Rank> > {
+  static const size_t value = Rank;
+};
+
+template<DenseIndex n, typename Index, std::size_t Rank> const Index array_get(DimensionList<Index, Rank>&) {
+  return n;
+}
+template<DenseIndex n, typename Index, std::size_t Rank> const Index array_get(const DimensionList<Index, Rank>&) {
+  return n;
+}
+
+
+#if EIGEN_HAS_CONSTEXPR
+template <typename Index, std::size_t Rank>
+struct index_known_statically_impl<DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex) {
+    return true;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_known_statically_impl<const DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex) {
+    return true;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct all_indices_known_statically_impl<DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return true;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct all_indices_known_statically_impl<const DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return true;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct indices_statically_known_to_increase_impl<DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return true;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct indices_statically_known_to_increase_impl<const DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return true;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct index_statically_eq_impl<DimensionList<Index, Rank> > {
+  static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return i == value;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_statically_eq_impl<const DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return i == value;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct index_statically_ne_impl<DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return i != value;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_statically_ne_impl<const DimensionList<Index, Rank> > {
+  static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return i != value;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct index_statically_gt_impl<DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return i > value;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_statically_gt_impl<const DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return i > value;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct index_statically_lt_impl<DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return i < value;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_statically_lt_impl<const DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return i < value;
+  }
+};
+
+#else
+template <typename Index, std::size_t Rank>
+struct index_known_statically_impl<DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE bool run(const DenseIndex) {
+    return true;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_known_statically_impl<const DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE bool run(const DenseIndex) {
+    return true;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct all_indices_known_statically_impl<DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE bool run() {
+    return true;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct all_indices_known_statically_impl<const DimensionList<Index, Rank> > {
+  EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE bool run() {
+    return true;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct indices_statically_known_to_increase_impl<DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run() {
+    return true;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct indices_statically_known_to_increase_impl<const DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run() {
+    return true;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct index_statically_eq_impl<DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex, const DenseIndex) {
+    return false;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_statically_eq_impl<const DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex, const DenseIndex) {
+    return false;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct index_statically_ne_impl<DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex, const DenseIndex){
+    return false;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_statically_ne_impl<const DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex, const DenseIndex) {
+    return false;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct index_statically_gt_impl<DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex, const DenseIndex) {
+    return false;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_statically_gt_impl<const DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex, const DenseIndex) {
+    return false;
+  }
+};
+
+template <typename Index, std::size_t Rank>
+struct index_statically_lt_impl<DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex, const DenseIndex) {
+    return false;
+  }
+};
+template <typename Index, std::size_t Rank>
+struct index_statically_lt_impl<const DimensionList<Index, Rank> > {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex, const DenseIndex) {
+    return false;
+  }
+};
+#endif
+
+}  // end namespace internal
+}  // end namespace Eigen
+
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_DIMENSION_LIST_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
@@ -0,0 +1,428 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_DIMENSIONS_H
+#define EIGEN_CXX11_TENSOR_TENSOR_DIMENSIONS_H
+
+
+namespace Eigen {
+
+/** \internal
+  *
+  * \class TensorDimensions
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Set of classes used to encode and store the dimensions of a Tensor.
+  *
+  * The Sizes class encodes as part of the type the number of dimensions and the
+  * sizes corresponding to each dimension. It uses no storage space since it is
+  * entirely known at compile time.
+  * The DSizes class is its dynamic sibling: the number of dimensions is known
+  * at compile time but the sizes are set during execution.
+  *
+  * \sa Tensor
+  */
+
+// Boilerplate code
+namespace internal {
+
+template<std::size_t n, typename Dimension> struct dget {
+  static const std::size_t value = get<n, Dimension>::value;
+};
+
+
+template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor>
+struct fixed_size_tensor_index_linearization_helper
+{
+  template <typename Dimensions> EIGEN_DEVICE_FUNC
+  static inline Index run(array<Index, NumIndices> const& indices,
+                          const Dimensions& dimensions)
+  {
+    return array_get<RowMajor ? n - 1 : (NumIndices - n)>(indices) +
+        dget<RowMajor ? n - 1 : (NumIndices - n), Dimensions>::value *
+        fixed_size_tensor_index_linearization_helper<Index, NumIndices, n - 1, RowMajor>::run(indices, dimensions);
+  }
+};
+
+template<typename Index, std::size_t NumIndices, bool RowMajor>
+struct fixed_size_tensor_index_linearization_helper<Index, NumIndices, 0, RowMajor>
+{
+  template <typename Dimensions> EIGEN_DEVICE_FUNC
+  static inline Index run(array<Index, NumIndices> const&, const Dimensions&)
+  {
+    return 0;
+  }
+};
+
+template<typename Index, std::size_t n>
+struct fixed_size_tensor_index_extraction_helper
+{
+  template <typename Dimensions> EIGEN_DEVICE_FUNC
+  static inline Index run(const Index index,
+                          const Dimensions& dimensions)
+  {
+    const Index mult = (index == n-1) ? 1 : 0;
+    return array_get<n-1>(dimensions) * mult +
+        fixed_size_tensor_index_extraction_helper<Index, n - 1>::run(index, dimensions);
+  }
+};
+
+template<typename Index>
+struct fixed_size_tensor_index_extraction_helper<Index, 0>
+{
+  template <typename Dimensions> EIGEN_DEVICE_FUNC
+  static inline Index run(const Index,
+                          const Dimensions&)
+  {
+    return 0;
+  }
+  };
+
+}  // end namespace internal
+
+
+// Fixed size
+#ifndef EIGEN_EMULATE_CXX11_META_H
+template <typename std::ptrdiff_t... Indices>
+struct Sizes : internal::numeric_list<std::ptrdiff_t, Indices...> {
+  typedef internal::numeric_list<std::ptrdiff_t, Indices...> Base;
+  static const std::ptrdiff_t total_size = internal::arg_prod(Indices...);
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t rank() const {
+    return Base::count;
+  }
+
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t TotalSize() {
+    return internal::arg_prod(Indices...);
+  }
+
+  EIGEN_DEVICE_FUNC Sizes() { }
+  template <typename DenseIndex>
+  explicit EIGEN_DEVICE_FUNC Sizes(const array<DenseIndex, Base::count>& /*indices*/) {
+    // todo: add assertion
+  }
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  template <typename... DenseIndex> EIGEN_DEVICE_FUNC Sizes(DenseIndex...) { }
+  explicit EIGEN_DEVICE_FUNC Sizes(std::initializer_list<std::ptrdiff_t> /*l*/) {
+    // todo: add assertion
+  }
+#endif
+
+  template <typename T> Sizes& operator = (const T& /*other*/) {
+    // add assertion failure if the size of other is different
+    return *this;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t operator[] (const std::size_t index) const {
+    return internal::fixed_size_tensor_index_extraction_helper<std::ptrdiff_t, Base::count>::run(index, *this);
+  }
+
+  template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
+    return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, false>::run(indices, *static_cast<const Base*>(this));
+  }
+  template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
+    return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, *static_cast<const Base*>(this));
+  }
+};
+
+namespace internal {
+template <typename std::ptrdiff_t... Indices>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_prod(const Sizes<Indices...>&) {
+  return Sizes<Indices...>::total_size;
+}
+}
+
+#else
+
+template <std::size_t n>
+struct non_zero_size {
+  typedef internal::type2val<std::size_t, n> type;
+};
+template <>
+struct non_zero_size<0> {
+  typedef internal::null_type type;
+};
+
+template <std::size_t V1=0, std::size_t V2=0, std::size_t V3=0, std::size_t V4=0, std::size_t V5=0> struct Sizes {
+  typedef typename internal::make_type_list<typename non_zero_size<V1>::type, typename non_zero_size<V2>::type, typename non_zero_size<V3>::type, typename non_zero_size<V4>::type, typename non_zero_size<V5>::type >::type Base;
+  static const size_t count = Base::count;
+  static const std::size_t total_size = internal::arg_prod<Base>::value;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t rank() const {
+    return count;
+  }
+
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t TotalSize() {
+    return internal::arg_prod<Base>::value;
+  }
+
+  Sizes() { }
+  template <typename DenseIndex>
+  explicit Sizes(const array<DenseIndex, Base::count>& /*indices*/) {
+    // todo: add assertion
+  }
+  template <typename T> Sizes& operator = (const T& /*other*/) {
+    // add assertion failure if the size of other is different
+    return *this;
+  }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  template <typename... DenseIndex> Sizes(DenseIndex... /*indices*/) { }
+  explicit Sizes(std::initializer_list<std::size_t>) {
+    // todo: add assertion
+  }
+#else
+  EIGEN_DEVICE_FUNC explicit Sizes(const DenseIndex) {
+  }
+  EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex) {
+  }
+  EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex, const DenseIndex) {
+  }
+  EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex, const DenseIndex, const DenseIndex) {
+  }
+  EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex, const DenseIndex, const DenseIndex, const DenseIndex) {
+  }
+#endif
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex operator[] (const int index) const {
+    switch (index) {
+      case 0:
+        return internal::get<0, Base>::value;
+      case 1:
+        return internal::get<1, Base>::value;
+      case 2:
+        return internal::get<2, Base>::value;
+      case 3:
+        return internal::get<3, Base>::value;
+      case 4:
+        return internal::get<4, Base>::value;
+      default:
+        eigen_assert(false && "index overflow");
+        return static_cast<DenseIndex>(-1);
+    }
+  }
+
+  template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
+    return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, false>::run(indices, *reinterpret_cast<const Base*>(this));
+  }
+  template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
+    return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, *reinterpret_cast<const Base*>(this));
+  }
+};
+
+namespace internal {
+template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t array_prod(const Sizes<V1, V2, V3, V4, V5>&) {
+  return Sizes<V1, V2, V3, V4, V5>::total_size;
+}
+}
+
+#endif
+
+// Boilerplate
+namespace internal {
+template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor>
+struct tensor_index_linearization_helper
+{
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Index run(array<Index, NumIndices> const& indices, array<Index, NumIndices> const& dimensions)
+  {
+    return array_get<RowMajor ? n : (NumIndices - n - 1)>(indices) +
+      array_get<RowMajor ? n : (NumIndices - n - 1)>(dimensions) *
+        tensor_index_linearization_helper<Index, NumIndices, n - 1, RowMajor>::run(indices, dimensions);
+  }
+};
+
+template<typename Index, std::size_t NumIndices, bool RowMajor>
+struct tensor_index_linearization_helper<Index, NumIndices, 0, RowMajor>
+{
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Index run(array<Index, NumIndices> const& indices, array<Index, NumIndices> const&)
+  {
+    return array_get<RowMajor ? 0 : NumIndices - 1>(indices);
+  }
+};
+}  // end namespace internal
+
+
+
+// Dynamic size
+template <typename DenseIndex, int NumDims>
+struct DSizes : array<DenseIndex, NumDims> {
+  typedef array<DenseIndex, NumDims> Base;
+  static const int count = NumDims;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t rank() const {
+    return NumDims;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex TotalSize() const {
+    return (NumDims == 0) ? 1 : internal::array_prod(*static_cast<const Base*>(this));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DSizes() {
+    for (int i = 0 ; i < NumDims; ++i) {
+      (*this)[i] = 0;
+    }
+  }
+  EIGEN_DEVICE_FUNC explicit DSizes(const array<DenseIndex, NumDims>& a) : Base(a) { }
+
+  EIGEN_DEVICE_FUNC explicit DSizes(const DenseIndex i0) {
+    eigen_assert(NumDims == 1);
+    (*this)[0] = i0;
+  }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  template<typename... IndexTypes> EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE explicit DSizes(DenseIndex firstDimension, DenseIndex secondDimension, IndexTypes... otherDimensions) : Base({{firstDimension, secondDimension, otherDimensions...}}) {
+    EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 2 == NumDims, YOU_MADE_A_PROGRAMMING_MISTAKE)
+  }
+#else
+  EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1) {
+    eigen_assert(NumDims == 2);
+    (*this)[0] = i0;
+    (*this)[1] = i1;
+  }
+  EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2) {
+    eigen_assert(NumDims == 3);
+    (*this)[0] = i0;
+    (*this)[1] = i1;
+    (*this)[2] = i2;
+  }
+  EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2, const DenseIndex i3) {
+    eigen_assert(NumDims == 4);
+    (*this)[0] = i0;
+    (*this)[1] = i1;
+    (*this)[2] = i2;
+    (*this)[3] = i3;
+  }
+  EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2, const DenseIndex i3, const DenseIndex i4) {
+    eigen_assert(NumDims == 5);
+    (*this)[0] = i0;
+    (*this)[1] = i1;
+    (*this)[2] = i2;
+    (*this)[3] = i3;
+    (*this)[4] = i4;
+  }
+#endif
+
+  EIGEN_DEVICE_FUNC DSizes& operator = (const array<DenseIndex, NumDims>& other) {
+    *static_cast<Base*>(this) = other;
+    return *this;
+  }
+
+  // A constexpr would be so much better here
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex IndexOfColMajor(const array<DenseIndex, NumDims>& indices) const {
+    return internal::tensor_index_linearization_helper<DenseIndex, NumDims, NumDims - 1, false>::run(indices, *static_cast<const Base*>(this));
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex IndexOfRowMajor(const array<DenseIndex, NumDims>& indices) const {
+    return internal::tensor_index_linearization_helper<DenseIndex, NumDims, NumDims - 1, true>::run(indices, *static_cast<const Base*>(this));
+  }
+};
+
+
+
+
+// Boilerplate
+namespace internal {
+template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor>
+struct tensor_vsize_index_linearization_helper
+{
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Index run(array<Index, NumIndices> const& indices, std::vector<DenseIndex> const& dimensions)
+  {
+    return array_get<RowMajor ? n : (NumIndices - n - 1)>(indices) +
+      array_get<RowMajor ? n : (NumIndices - n - 1)>(dimensions) *
+        tensor_vsize_index_linearization_helper<Index, NumIndices, n - 1, RowMajor>::run(indices, dimensions);
+  }
+};
+
+template<typename Index, std::size_t NumIndices, bool RowMajor>
+struct tensor_vsize_index_linearization_helper<Index, NumIndices, 0, RowMajor>
+{
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Index run(array<Index, NumIndices> const& indices, std::vector<DenseIndex> const&)
+  {
+    return array_get<RowMajor ? 0 : NumIndices - 1>(indices);
+  }
+};
+}  // end namespace internal
+
+
+namespace internal {
+
+template <typename DenseIndex, int NumDims> struct array_size<const DSizes<DenseIndex, NumDims> > {
+  static const size_t value = NumDims;
+};
+template <typename DenseIndex, int NumDims> struct array_size<DSizes<DenseIndex, NumDims> > {
+  static const size_t value = NumDims;
+};
+#ifndef EIGEN_EMULATE_CXX11_META_H
+template <typename std::ptrdiff_t... Indices> struct array_size<const Sizes<Indices...> > {
+static const std::ptrdiff_t value = Sizes<Indices...>::count;
+};
+template <typename std::ptrdiff_t... Indices> struct array_size<Sizes<Indices...> > {
+static const std::ptrdiff_t value = Sizes<Indices...>::count;
+};
+template <std::ptrdiff_t n, typename std::ptrdiff_t... Indices> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_get(const Sizes<Indices...>&) {
+  return get<n, internal::numeric_list<std::size_t, Indices...> >::value;
+}
+template <std::ptrdiff_t n> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_get(const Sizes<>&) {
+  eigen_assert(false && "should never be called");
+  return -1;
+}
+#else
+template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> struct array_size<const Sizes<V1,V2,V3,V4,V5> > {
+  static const size_t value = Sizes<V1,V2,V3,V4,V5>::count;
+};
+template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> struct array_size<Sizes<V1,V2,V3,V4,V5> > {
+  static const size_t value = Sizes<V1,V2,V3,V4,V5>::count;
+};
+template <std::size_t n, std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t array_get(const Sizes<V1,V2,V3,V4,V5>&) {
+  return get<n, typename Sizes<V1,V2,V3,V4,V5>::Base>::value;
+}
+
+#endif
+
+
+template <typename Dims1, typename Dims2, size_t n, size_t m>
+struct sizes_match_below_dim {
+  static EIGEN_DEVICE_FUNC  inline bool run(Dims1&, Dims2&) {
+    return false;
+  }
+};
+template <typename Dims1, typename Dims2, size_t n>
+struct sizes_match_below_dim<Dims1, Dims2, n, n> {
+  static EIGEN_DEVICE_FUNC  inline bool run(Dims1& dims1, Dims2& dims2) {
+    return (array_get<n-1>(dims1) == array_get<n-1>(dims2)) &
+        sizes_match_below_dim<Dims1, Dims2, n-1, n-1>::run(dims1, dims2);
+  }
+};
+template <typename Dims1, typename Dims2>
+struct sizes_match_below_dim<Dims1, Dims2, 0, 0> {
+  static EIGEN_DEVICE_FUNC  inline bool run(Dims1&, Dims2&) {
+    return true;
+  }
+};
+
+} // end namespace internal
+
+
+template <typename Dims1, typename Dims2>
+EIGEN_DEVICE_FUNC bool dimensions_match(Dims1& dims1, Dims2& dims2) {
+  return internal::sizes_match_below_dim<Dims1, Dims2, internal::array_size<Dims1>::value, internal::array_size<Dims2>::value>::run(dims1, dims2);
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_DIMENSIONS_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorEvalTo.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorEvalTo.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorEvalTo.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorEvalTo.h
@@ -0,0 +1,181 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_EVAL_TO_H
+#define EIGEN_CXX11_TENSOR_TENSOR_EVAL_TO_H
+
+namespace Eigen {
+
+/** \class TensorForcedEval
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor reshaping class.
+  *
+  *
+  */
+namespace internal {
+template<typename XprType, template <class> class MakePointer_>
+struct traits<TensorEvalToOp<XprType, MakePointer_> >
+{
+  // Type promotion to handle the case where the types of the lhs and the rhs are different.
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+
+  enum {
+    Flags = 0
+  };
+  template <class T>
+  struct MakePointer {
+    // Intermediate typedef to workaround MSVC issue.
+    typedef MakePointer_<T> MakePointerT;
+    typedef typename MakePointerT::Type Type;
+  };
+};
+
+template<typename XprType, template <class> class MakePointer_>
+struct eval<TensorEvalToOp<XprType, MakePointer_>, Eigen::Dense>
+{
+  typedef const TensorEvalToOp<XprType, MakePointer_>& type;
+};
+
+template<typename XprType, template <class> class MakePointer_>
+struct nested<TensorEvalToOp<XprType, MakePointer_>, 1, typename eval<TensorEvalToOp<XprType, MakePointer_> >::type>
+{
+  typedef TensorEvalToOp<XprType, MakePointer_> type;
+};
+
+}  // end namespace internal
+
+
+
+
+template<typename XprType, template <class> class MakePointer_>
+class TensorEvalToOp : public TensorBase<TensorEvalToOp<XprType, MakePointer_>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorEvalToOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename MakePointer_<CoeffReturnType>::Type PointerType;
+  typedef typename Eigen::internal::nested<TensorEvalToOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorEvalToOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorEvalToOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvalToOp(PointerType buffer, const XprType& expr)
+      : m_xpr(expr), m_buffer(buffer) {}
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC PointerType buffer() const { return m_buffer; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    PointerType m_buffer;
+};
+
+
+
+template<typename ArgType, typename Device, template <class> class MakePointer_>
+struct TensorEvaluator<const TensorEvalToOp<ArgType, MakePointer_>, Device>
+{
+  typedef TensorEvalToOp<ArgType, MakePointer_> XprType;
+  typedef typename ArgType::Scalar Scalar;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
+  typedef typename XprType::Index Index;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = TensorEvaluator<ArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = true
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_device(device),
+          m_buffer(op.buffer()), m_op(op), m_expression(op.expression())
+  { }
+
+  // Used for accessor extraction in SYCL Managed TensorMap:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const XprType& op() const {
+    return m_op;
+  }
+  
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ~TensorEvaluator() {
+  }
+
+  typedef typename internal::traits<const TensorEvalToOp<ArgType, MakePointer_> >::template MakePointer<CoeffReturnType>::Type DevicePointer;
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_impl.dimensions(); }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(DevicePointer scalar) {
+    EIGEN_UNUSED_VARIABLE(scalar);
+    eigen_assert(scalar == NULL);
+    return m_impl.evalSubExprsIfNeeded(m_buffer);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalScalar(Index i) {
+    m_buffer[i] = m_impl.coeff(i);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalPacket(Index i) {
+    internal::pstoret<CoeffReturnType, PacketReturnType, Aligned>(m_buffer + i, m_impl.template packet<TensorEvaluator<ArgType, Device>::IsAligned ? Aligned : Unaligned>(i));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_buffer[index];
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_buffer + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    // We assume that evalPacket or evalScalar is called to perform the
+    // assignment and account for the cost of the write here.
+    return m_impl.costPerCoeff(vectorized) +
+        TensorOpCost(0, sizeof(CoeffReturnType), 0, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC DevicePointer data() const { return m_buffer; }
+  ArgType expression() const { return m_expression; }
+
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+  /// added for sycl in order to construct the buffer from the sycl device
+  const Device& device() const{return m_device;}
+
+ private:
+  TensorEvaluator<ArgType, Device> m_impl;
+  const Device& m_device;
+  DevicePointer m_buffer;
+  const XprType& m_op;
+  const ArgType m_expression;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_EVAL_TO_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h
@@ -0,0 +1,633 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_EVALUATOR_H
+#define EIGEN_CXX11_TENSOR_TENSOR_EVALUATOR_H
+
+namespace Eigen {
+
+/** \class TensorEvaluator
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief The tensor evaluator classes.
+  *
+  * These classes are responsible for the evaluation of the tensor expression.
+  *
+  * TODO: add support for more types of expressions, in particular expressions
+  * leading to lvalues (slicing, reshaping, etc...)
+  */
+
+// Generic evaluator
+template<typename Derived, typename Device>
+struct TensorEvaluator
+{
+  typedef typename Derived::Index Index;
+  typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef typename Derived::Dimensions Dimensions;
+
+  // NumDimensions is -1 for variable dim tensors
+  static const int NumCoords = internal::traits<Derived>::NumDimensions > 0 ?
+                               internal::traits<Derived>::NumDimensions : 0;
+
+  enum {
+    IsAligned = Derived::IsAligned,
+    PacketAccess = (internal::unpacket_traits<PacketReturnType>::size > 1),
+    Layout = Derived::Layout,
+    CoordAccess = NumCoords > 0,
+    RawAccess = true
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const Derived& m, const Device& device)
+      : m_data(const_cast<typename internal::traits<Derived>::template MakePointer<Scalar>::Type>(m.data())), m_dims(m.dimensions()), m_device(device), m_impl(m)
+  { }
+
+  // Used for accessor extraction in SYCL Managed TensorMap:
+  const Derived& derived() const { return m_impl; }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dims; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* dest) {
+    if (dest) {
+      m_device.memcpy((void*)dest, m_data, sizeof(Scalar) * m_dims.TotalSize());
+      return false;
+    }
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+    eigen_assert(m_data);
+    return m_data[index];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
+    eigen_assert(m_data);
+    return m_data[index];
+  }
+
+  template<int LoadMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  PacketReturnType packet(Index index) const
+  {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_data + index);
+  }
+
+  template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x)
+  {
+    return internal::pstoret<Scalar, PacketReturnType, StoreMode>(m_data + index, x);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(const array<DenseIndex, NumCoords>& coords) const {
+    eigen_assert(m_data);
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      return m_data[m_dims.IndexOfColMajor(coords)];
+    } else {
+      return m_data[m_dims.IndexOfRowMajor(coords)];
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(const array<DenseIndex, NumCoords>& coords) {
+    eigen_assert(m_data);
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      return m_data[m_dims.IndexOfColMajor(coords)];
+    } else {
+      return m_data[m_dims.IndexOfRowMajor(coords)];
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized,
+                        internal::unpacket_traits<PacketReturnType>::size);
+  }
+
+  EIGEN_DEVICE_FUNC typename internal::traits<Derived>::template MakePointer<Scalar>::Type data() const { return m_data; }
+
+  /// required by sycl in order to construct sycl buffer from raw pointer
+  const Device& device() const{return m_device;}
+
+ protected:
+  typename internal::traits<Derived>::template MakePointer<Scalar>::Type m_data;
+  Dimensions m_dims;
+  const Device& m_device;
+  const Derived& m_impl;
+};
+
+namespace {
+template <typename T> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T loadConstant(const T* address) {
+  return *address;
+}
+// Use the texture cache on CUDA devices whenever possible
+#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 350
+template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+float loadConstant(const float* address) {
+  return __ldg(address);
+}
+template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+double loadConstant(const double* address) {
+  return __ldg(address);
+}
+template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+Eigen::half loadConstant(const Eigen::half* address) {
+  return Eigen::half(half_impl::raw_uint16_to_half(__ldg(&address->x)));
+}
+#endif
+}
+
+
+// Default evaluator for rvalues
+template<typename Derived, typename Device>
+struct TensorEvaluator<const Derived, Device>
+{
+  typedef typename Derived::Index Index;
+  typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef typename Derived::Dimensions Dimensions;
+
+  // NumDimensions is -1 for variable dim tensors
+  static const int NumCoords = internal::traits<Derived>::NumDimensions > 0 ?
+                               internal::traits<Derived>::NumDimensions : 0;
+
+  enum {
+    IsAligned = Derived::IsAligned,
+    PacketAccess = (internal::unpacket_traits<PacketReturnType>::size > 1),
+    Layout = Derived::Layout,
+    CoordAccess = NumCoords > 0,
+    RawAccess = true
+  };
+
+  // Used for accessor extraction in SYCL Managed TensorMap:
+  const Derived& derived() const { return m_impl; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const Derived& m, const Device& device)
+      : m_data(m.data()), m_dims(m.dimensions()), m_device(device), m_impl(m)
+  { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dims; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
+    if (!NumTraits<typename internal::remove_const<Scalar>::type>::RequireInitialization && data) {
+      m_device.memcpy((void*)data, m_data, m_dims.TotalSize() * sizeof(Scalar));
+      return false;
+    }
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+    eigen_assert(m_data);
+    return loadConstant(m_data+index);
+  }
+
+  template<int LoadMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  PacketReturnType packet(Index index) const
+  {
+    return internal::ploadt_ro<PacketReturnType, LoadMode>(m_data + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(const array<DenseIndex, NumCoords>& coords) const {
+    eigen_assert(m_data);
+    const Index index = (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? m_dims.IndexOfColMajor(coords)
+                        : m_dims.IndexOfRowMajor(coords);
+    return loadConstant(m_data+index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized,
+                        internal::unpacket_traits<PacketReturnType>::size);
+  }
+
+  EIGEN_DEVICE_FUNC typename internal::traits<Derived>::template MakePointer<const Scalar>::Type data() const { return m_data; }
+
+  /// added for sycl in order to construct the buffer from the sycl device
+  const Device& device() const{return m_device;}
+
+ protected:
+  typename internal::traits<Derived>::template MakePointer<const Scalar>::Type m_data;
+  Dimensions m_dims;
+  const Device& m_device;
+  const Derived& m_impl;
+};
+
+
+
+
+// -------------------- CwiseNullaryOp --------------------
+
+template<typename NullaryOp, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorCwiseNullaryOp<NullaryOp, ArgType>, Device>
+{
+  typedef TensorCwiseNullaryOp<NullaryOp, ArgType> XprType;
+
+  enum {
+    IsAligned = true,
+    PacketAccess = internal::functor_traits<NullaryOp>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC
+  TensorEvaluator(const XprType& op, const Device& device)
+      : m_functor(op.functor()), m_argImpl(op.nestedExpression(), device), m_wrapper()
+  { }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename internal::traits<XprType>::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_argImpl.dimensions(); }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) { return true; }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const
+  {
+    return m_wrapper(m_functor, index);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return m_wrapper.template packetOp<PacketReturnType, Index>(m_functor, index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized,
+                        internal::unpacket_traits<PacketReturnType>::size);
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return NULL; }
+
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<ArgType, Device>& impl() const { return m_argImpl; }
+  /// required by sycl in order to extract the accessor
+  NullaryOp functor() const { return m_functor; }
+
+
+ private:
+  const NullaryOp m_functor;
+  TensorEvaluator<ArgType, Device> m_argImpl;
+  const internal::nullary_wrapper<CoeffReturnType,NullaryOp> m_wrapper;
+};
+
+
+
+// -------------------- CwiseUnaryOp --------------------
+
+template<typename UnaryOp, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorCwiseUnaryOp<UnaryOp, ArgType>, Device>
+{
+  typedef TensorCwiseUnaryOp<UnaryOp, ArgType> XprType;
+
+  enum {
+    IsAligned = TensorEvaluator<ArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess & internal::functor_traits<UnaryOp>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device)
+    : m_functor(op.functor()),
+      m_argImpl(op.nestedExpression(), device)
+  { }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename internal::traits<XprType>::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_argImpl.dimensions(); }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+    m_argImpl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_argImpl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const
+  {
+    return m_functor(m_argImpl.coeff(index));
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return m_functor.packetOp(m_argImpl.template packet<LoadMode>(index));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    const double functor_cost = internal::functor_traits<UnaryOp>::Cost;
+    return m_argImpl.costPerCoeff(vectorized) +
+        TensorOpCost(0, 0, functor_cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return NULL; }
+
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<ArgType, Device> & impl() const { return m_argImpl; }
+  /// added for sycl in order to construct the buffer from sycl device
+  UnaryOp functor() const { return m_functor; }
+
+
+ private:
+  const UnaryOp m_functor;
+  TensorEvaluator<ArgType, Device> m_argImpl;
+};
+
+
+// -------------------- CwiseBinaryOp --------------------
+
+template<typename BinaryOp, typename LeftArgType, typename RightArgType, typename Device>
+struct TensorEvaluator<const TensorCwiseBinaryOp<BinaryOp, LeftArgType, RightArgType>, Device>
+{
+  typedef TensorCwiseBinaryOp<BinaryOp, LeftArgType, RightArgType> XprType;
+
+  enum {
+    IsAligned = TensorEvaluator<LeftArgType, Device>::IsAligned & TensorEvaluator<RightArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<LeftArgType, Device>::PacketAccess & TensorEvaluator<RightArgType, Device>::PacketAccess &
+                   internal::functor_traits<BinaryOp>::PacketAccess,
+    Layout = TensorEvaluator<LeftArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device)
+    : m_functor(op.functor()),
+      m_leftImpl(op.lhsExpression(), device),
+      m_rightImpl(op.rhsExpression(), device)
+  {
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout) || internal::traits<XprType>::NumDimensions <= 1), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    eigen_assert(dimensions_match(m_leftImpl.dimensions(), m_rightImpl.dimensions()));
+  }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename internal::traits<XprType>::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+  typedef typename TensorEvaluator<LeftArgType, Device>::Dimensions Dimensions;
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const
+  {
+    // TODO: use right impl instead if right impl dimensions are known at compile time.
+    return m_leftImpl.dimensions();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) {
+    m_leftImpl.evalSubExprsIfNeeded(NULL);
+    m_rightImpl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_leftImpl.cleanup();
+    m_rightImpl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const
+  {
+    return m_functor(m_leftImpl.coeff(index), m_rightImpl.coeff(index));
+  }
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return m_functor.packetOp(m_leftImpl.template packet<LoadMode>(index), m_rightImpl.template packet<LoadMode>(index));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    const double functor_cost = internal::functor_traits<BinaryOp>::Cost;
+    return m_leftImpl.costPerCoeff(vectorized) +
+           m_rightImpl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, functor_cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return NULL; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<LeftArgType, Device>& left_impl() const { return m_leftImpl; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<RightArgType, Device>& right_impl() const { return m_rightImpl; }
+  /// required by sycl in order to extract the accessor
+  BinaryOp functor() const { return m_functor; }
+
+ private:
+  const BinaryOp m_functor;
+  TensorEvaluator<LeftArgType, Device> m_leftImpl;
+  TensorEvaluator<RightArgType, Device> m_rightImpl;
+};
+
+// -------------------- CwiseTernaryOp --------------------
+
+template<typename TernaryOp, typename Arg1Type, typename Arg2Type, typename Arg3Type, typename Device>
+struct TensorEvaluator<const TensorCwiseTernaryOp<TernaryOp, Arg1Type, Arg2Type, Arg3Type>, Device>
+{
+  typedef TensorCwiseTernaryOp<TernaryOp, Arg1Type, Arg2Type, Arg3Type> XprType;
+
+  enum {
+    IsAligned = TensorEvaluator<Arg1Type, Device>::IsAligned & TensorEvaluator<Arg2Type, Device>::IsAligned & TensorEvaluator<Arg3Type, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<Arg1Type, Device>::PacketAccess & TensorEvaluator<Arg2Type, Device>::PacketAccess & TensorEvaluator<Arg3Type, Device>::PacketAccess &
+                   internal::functor_traits<TernaryOp>::PacketAccess,
+    Layout = TensorEvaluator<Arg1Type, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device)
+    : m_functor(op.functor()),
+      m_arg1Impl(op.arg1Expression(), device),
+      m_arg2Impl(op.arg2Expression(), device),
+      m_arg3Impl(op.arg3Expression(), device)
+  {
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<Arg1Type, Device>::Layout) == static_cast<int>(TensorEvaluator<Arg3Type, Device>::Layout) || internal::traits<XprType>::NumDimensions <= 1), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::StorageKind,
+                         typename internal::traits<Arg2Type>::StorageKind>::value),
+                        STORAGE_KIND_MUST_MATCH)
+    EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::StorageKind,
+                         typename internal::traits<Arg3Type>::StorageKind>::value),
+                        STORAGE_KIND_MUST_MATCH)
+    EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::Index,
+                         typename internal::traits<Arg2Type>::Index>::value),
+                        STORAGE_INDEX_MUST_MATCH)
+    EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::Index,
+                         typename internal::traits<Arg3Type>::Index>::value),
+                        STORAGE_INDEX_MUST_MATCH)
+
+    eigen_assert(dimensions_match(m_arg1Impl.dimensions(), m_arg2Impl.dimensions()) && dimensions_match(m_arg1Impl.dimensions(), m_arg3Impl.dimensions()));
+  }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename internal::traits<XprType>::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+  typedef typename TensorEvaluator<Arg1Type, Device>::Dimensions Dimensions;
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const
+  {
+    // TODO: use arg2 or arg3 dimensions if they are known at compile time.
+    return m_arg1Impl.dimensions();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) {
+    m_arg1Impl.evalSubExprsIfNeeded(NULL);
+    m_arg2Impl.evalSubExprsIfNeeded(NULL);
+    m_arg3Impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_arg1Impl.cleanup();
+    m_arg2Impl.cleanup();
+    m_arg3Impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const
+  {
+    return m_functor(m_arg1Impl.coeff(index), m_arg2Impl.coeff(index), m_arg3Impl.coeff(index));
+  }
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return m_functor.packetOp(m_arg1Impl.template packet<LoadMode>(index),
+                              m_arg2Impl.template packet<LoadMode>(index),
+                              m_arg3Impl.template packet<LoadMode>(index));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    const double functor_cost = internal::functor_traits<TernaryOp>::Cost;
+    return m_arg1Impl.costPerCoeff(vectorized) +
+           m_arg2Impl.costPerCoeff(vectorized) +
+           m_arg3Impl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, functor_cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return NULL; }
+
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<Arg1Type, Device> & arg1Impl() const { return m_arg1Impl; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<Arg2Type, Device>& arg2Impl() const { return m_arg2Impl; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<Arg3Type, Device>& arg3Impl() const { return m_arg3Impl; }
+
+ private:
+  const TernaryOp m_functor;
+  TensorEvaluator<Arg1Type, Device> m_arg1Impl;
+  TensorEvaluator<Arg2Type, Device> m_arg2Impl;
+  TensorEvaluator<Arg3Type, Device> m_arg3Impl;
+};
+
+
+// -------------------- SelectOp --------------------
+
+template<typename IfArgType, typename ThenArgType, typename ElseArgType, typename Device>
+struct TensorEvaluator<const TensorSelectOp<IfArgType, ThenArgType, ElseArgType>, Device>
+{
+  typedef TensorSelectOp<IfArgType, ThenArgType, ElseArgType> XprType;
+  typedef typename XprType::Scalar Scalar;
+
+  enum {
+    IsAligned = TensorEvaluator<ThenArgType, Device>::IsAligned & TensorEvaluator<ElseArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<ThenArgType, Device>::PacketAccess & TensorEvaluator<ElseArgType, Device>::PacketAccess &
+                   internal::packet_traits<Scalar>::HasBlend,
+    Layout = TensorEvaluator<IfArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device)
+    : m_condImpl(op.ifExpression(), device),
+      m_thenImpl(op.thenExpression(), device),
+      m_elseImpl(op.elseExpression(), device)
+  {
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<IfArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<ThenArgType, Device>::Layout)), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<IfArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<ElseArgType, Device>::Layout)), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    eigen_assert(dimensions_match(m_condImpl.dimensions(), m_thenImpl.dimensions()));
+    eigen_assert(dimensions_match(m_thenImpl.dimensions(), m_elseImpl.dimensions()));
+  }
+
+  typedef typename XprType::Index Index;
+  typedef typename internal::traits<XprType>::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+  typedef typename TensorEvaluator<IfArgType, Device>::Dimensions Dimensions;
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const
+  {
+    // TODO: use then or else impl instead if they happen to be known at compile time.
+    return m_condImpl.dimensions();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) {
+    m_condImpl.evalSubExprsIfNeeded(NULL);
+    m_thenImpl.evalSubExprsIfNeeded(NULL);
+    m_elseImpl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_condImpl.cleanup();
+    m_thenImpl.cleanup();
+    m_elseImpl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const
+  {
+    return m_condImpl.coeff(index) ? m_thenImpl.coeff(index) : m_elseImpl.coeff(index);
+  }
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const
+  {
+    internal::Selector<PacketSize> select;
+    for (Index i = 0; i < PacketSize; ++i) {
+      select.select[i] = m_condImpl.coeff(index+i);
+    }
+    return internal::pblend(select,
+                            m_thenImpl.template packet<LoadMode>(index),
+                            m_elseImpl.template packet<LoadMode>(index));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    return m_condImpl.costPerCoeff(vectorized) +
+           m_thenImpl.costPerCoeff(vectorized)
+        .cwiseMax(m_elseImpl.costPerCoeff(vectorized));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType* data() const { return NULL; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<IfArgType, Device> & cond_impl() const { return m_condImpl; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<ThenArgType, Device>& then_impl() const { return m_thenImpl; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<ElseArgType, Device>& else_impl() const { return m_elseImpl; }
+
+ private:
+  TensorEvaluator<IfArgType, Device> m_condImpl;
+  TensorEvaluator<ThenArgType, Device> m_thenImpl;
+  TensorEvaluator<ElseArgType, Device> m_elseImpl;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_EVALUATOR_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h
@@ -0,0 +1,288 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_EXECUTOR_H
+#define EIGEN_CXX11_TENSOR_TENSOR_EXECUTOR_H
+
+namespace Eigen {
+
+/** \class TensorExecutor
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief The tensor executor class.
+  *
+  * This class is responsible for launch the evaluation of the expression on
+  * the specified computing device.
+  */
+namespace internal {
+
+// Default strategy: the expression is evaluated with a single cpu thread.
+template<typename Expression, typename Device, bool Vectorizable>
+class TensorExecutor
+{
+ public:
+  typedef typename Expression::Index Index;
+  EIGEN_DEVICE_FUNC
+  static inline void run(const Expression& expr, const Device& device = Device())
+  {
+    TensorEvaluator<Expression, Device> evaluator(expr, device);
+    const bool needs_assign = evaluator.evalSubExprsIfNeeded(NULL);
+    if (needs_assign)
+    {
+      const Index size = array_prod(evaluator.dimensions());
+      for (Index i = 0; i < size; ++i) {
+        evaluator.evalScalar(i);
+      }
+    }
+    evaluator.cleanup();
+  }
+};
+
+
+template<typename Expression>
+class TensorExecutor<Expression, DefaultDevice, true>
+{
+ public:
+  typedef typename Expression::Index Index;
+  EIGEN_DEVICE_FUNC
+  static inline void run(const Expression& expr, const DefaultDevice& device = DefaultDevice())
+  {
+    TensorEvaluator<Expression, DefaultDevice> evaluator(expr, device);
+    const bool needs_assign = evaluator.evalSubExprsIfNeeded(NULL);
+    if (needs_assign)
+    {
+      const Index size = array_prod(evaluator.dimensions());
+      const int PacketSize = unpacket_traits<typename TensorEvaluator<Expression, DefaultDevice>::PacketReturnType>::size;
+      // Give the compiler a strong hint to unroll the loop. But don't insist
+      // on unrolling, because if the function is expensive the compiler should not
+      // unroll the loop at the expense of inlining.
+      const Index UnrolledSize = (size / (4 * PacketSize)) * 4 * PacketSize;
+      for (Index i = 0; i < UnrolledSize; i += 4*PacketSize) {
+        for (Index j = 0; j < 4; j++) {
+          evaluator.evalPacket(i + j * PacketSize);
+        }
+      }
+      const Index VectorizedSize = (size / PacketSize) * PacketSize;
+      for (Index i = UnrolledSize; i < VectorizedSize; i += PacketSize) {
+        evaluator.evalPacket(i);
+      }
+      for (Index i = VectorizedSize; i < size; ++i) {
+        evaluator.evalScalar(i);
+      }
+    }
+    evaluator.cleanup();
+  }
+};
+
+
+
+// Multicore strategy: the index space is partitioned and each partition is executed on a single core
+#ifdef EIGEN_USE_THREADS
+template <typename Evaluator, typename Index, bool Vectorizable>
+struct EvalRange {
+  static void run(Evaluator* evaluator_in, const Index first, const Index last) {
+    Evaluator evaluator = *evaluator_in;
+    eigen_assert(last >= first);
+    for (Index i = first; i < last; ++i) {
+      evaluator.evalScalar(i);
+    }
+  }
+
+  static Index alignBlockSize(Index size) {
+    return size;
+  }
+};
+
+template <typename Evaluator, typename Index>
+struct EvalRange<Evaluator, Index, true> {
+  static const int PacketSize = unpacket_traits<typename Evaluator::PacketReturnType>::size;
+
+  static void run(Evaluator* evaluator_in, const Index first, const Index last) {
+    Evaluator evaluator = *evaluator_in;
+    eigen_assert(last >= first);
+    Index i = first;
+    if (last - first >= PacketSize) {
+      eigen_assert(first % PacketSize == 0);
+      Index last_chunk_offset = last - 4 * PacketSize;
+      // Give the compiler a strong hint to unroll the loop. But don't insist
+      // on unrolling, because if the function is expensive the compiler should not
+      // unroll the loop at the expense of inlining.
+      for (; i <= last_chunk_offset; i += 4*PacketSize) {
+        for (Index j = 0; j < 4; j++) {
+          evaluator.evalPacket(i + j * PacketSize);
+        }
+      }
+      last_chunk_offset = last - PacketSize;
+      for (; i <= last_chunk_offset; i += PacketSize) {
+        evaluator.evalPacket(i);
+      }
+    }
+    for (; i < last; ++i) {
+      evaluator.evalScalar(i);
+    }
+  }
+
+  static Index alignBlockSize(Index size) {
+    // Align block size to packet size and account for unrolling in run above.
+    if (size >= 16 * PacketSize) {
+      return (size + 4 * PacketSize - 1) & ~(4 * PacketSize - 1);
+    }
+    // Aligning to 4 * PacketSize would increase block size by more than 25%.
+    return (size + PacketSize - 1) & ~(PacketSize - 1);
+  }
+};
+
+template <typename Expression, bool Vectorizable>
+class TensorExecutor<Expression, ThreadPoolDevice, Vectorizable> {
+ public:
+  typedef typename Expression::Index Index;
+  static inline void run(const Expression& expr, const ThreadPoolDevice& device)
+  {
+    typedef TensorEvaluator<Expression, ThreadPoolDevice> Evaluator;
+    Evaluator evaluator(expr, device);
+    const bool needs_assign = evaluator.evalSubExprsIfNeeded(NULL);
+    if (needs_assign)
+    {
+      const Index size = array_prod(evaluator.dimensions());
+#if !defined(EIGEN_USE_SIMPLE_THREAD_POOL)
+      device.parallelFor(size, evaluator.costPerCoeff(Vectorizable),
+                         EvalRange<Evaluator, Index, Vectorizable>::alignBlockSize,
+                         [&evaluator](Index first, Index last) {
+                           EvalRange<Evaluator, Index, Vectorizable>::run(&evaluator, first, last);
+                         });
+#else
+      size_t num_threads = device.numThreads();
+      if (num_threads > 1) {
+        num_threads = TensorCostModel<ThreadPoolDevice>::numThreads(
+            size, evaluator.costPerCoeff(Vectorizable), num_threads);
+      }
+      if (num_threads == 1) {
+        EvalRange<Evaluator, Index, Vectorizable>::run(&evaluator, 0, size);
+      } else {
+        const Index PacketSize = Vectorizable ? unpacket_traits<typename Evaluator::PacketReturnType>::size : 1;
+        Index blocksz = std::ceil<Index>(static_cast<float>(size)/num_threads) + PacketSize - 1;
+        const Index blocksize = numext::maxi<Index>(PacketSize, (blocksz - (blocksz % PacketSize)));
+        const Index numblocks = size / blocksize;
+
+        Barrier barrier(numblocks);
+        for (int i = 0; i < numblocks; ++i) {
+          device.enqueue_with_barrier(
+              &barrier, &EvalRange<Evaluator, Index, Vectorizable>::run,
+              &evaluator, i * blocksize, (i + 1) * blocksize);
+        }
+        if (numblocks * blocksize < size) {
+          EvalRange<Evaluator, Index, Vectorizable>::run(
+              &evaluator, numblocks * blocksize, size);
+        }
+        barrier.Wait();
+      }
+#endif  // defined(!EIGEN_USE_SIMPLE_THREAD_POOL)
+    }
+    evaluator.cleanup();
+  }
+};
+#endif  // EIGEN_USE_THREADS
+
+
+// GPU: the evaluation of the expression is offloaded to a GPU.
+#if defined(EIGEN_USE_GPU)
+
+template <typename Expression, bool Vectorizable>
+class TensorExecutor<Expression, GpuDevice, Vectorizable> {
+ public:
+  typedef typename Expression::Index Index;
+  static void run(const Expression& expr, const GpuDevice& device);
+};
+
+
+#if defined(__CUDACC__)
+template <typename Evaluator, typename Index, bool Vectorizable>
+struct EigenMetaKernelEval {
+  static __device__ EIGEN_ALWAYS_INLINE
+  void run(Evaluator& eval, Index first, Index last, Index step_size) {
+    for (Index i = first; i < last; i += step_size) {
+      eval.evalScalar(i);
+    }
+  }
+};
+
+template <typename Evaluator, typename Index>
+struct EigenMetaKernelEval<Evaluator, Index, true> {
+  static __device__ EIGEN_ALWAYS_INLINE
+  void run(Evaluator& eval, Index first, Index last, Index step_size) {
+    const Index PacketSize = unpacket_traits<typename Evaluator::PacketReturnType>::size;
+    const Index vectorized_size = (last / PacketSize) * PacketSize;
+    const Index vectorized_step_size = step_size * PacketSize;
+
+    // Use the vector path
+    for (Index i = first * PacketSize; i < vectorized_size;
+         i += vectorized_step_size) {
+      eval.evalPacket(i);
+    }
+    for (Index i = vectorized_size + first; i < last; i += step_size) {
+      eval.evalScalar(i);
+    }
+  }
+};
+
+template <typename Evaluator, typename Index>
+__global__ void
+__launch_bounds__(1024)
+EigenMetaKernel(Evaluator eval, Index size) {
+
+  const Index first_index = blockIdx.x * blockDim.x + threadIdx.x;
+  const Index step_size = blockDim.x * gridDim.x;
+
+  const bool vectorizable = Evaluator::PacketAccess & Evaluator::IsAligned;
+  EigenMetaKernelEval<Evaluator, Index, vectorizable>::run(eval, first_index, size, step_size);
+}
+
+/*static*/
+template <typename Expression, bool Vectorizable>
+inline void TensorExecutor<Expression, GpuDevice, Vectorizable>::run(
+    const Expression& expr, const GpuDevice& device) {
+  TensorEvaluator<Expression, GpuDevice> evaluator(expr, device);
+  const bool needs_assign = evaluator.evalSubExprsIfNeeded(NULL);
+  if (needs_assign) {
+    const int block_size = device.maxCudaThreadsPerBlock();
+    const int max_blocks = device.getNumCudaMultiProcessors() *
+                           device.maxCudaThreadsPerMultiProcessor() / block_size;
+    const Index size = array_prod(evaluator.dimensions());
+    // Create a least one block to ensure we won't crash when tensorflow calls with tensors of size 0.
+    const int num_blocks = numext::maxi<int>(numext::mini<int>(max_blocks, divup<int>(size, block_size)), 1);
+
+    LAUNCH_CUDA_KERNEL(
+        (EigenMetaKernel<TensorEvaluator<Expression, GpuDevice>, Index>),
+        num_blocks, block_size, 0, device, evaluator, size);
+  }
+  evaluator.cleanup();
+}
+
+#endif  // __CUDACC__
+#endif  // EIGEN_USE_GPU
+
+// SYCL Executor policy
+#ifdef EIGEN_USE_SYCL
+
+template <typename Expression, bool Vectorizable>
+class TensorExecutor<Expression, SyclDevice, Vectorizable> {
+public:
+  static inline void run(const Expression &expr, const SyclDevice &device) {
+    // call TensorSYCL module
+    TensorSycl::run(expr, device);
+  }
+};
+
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_EXECUTOR_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorExpr.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorExpr.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorExpr.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorExpr.h
@@ -0,0 +1,371 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_EXPR_H
+#define EIGEN_CXX11_TENSOR_TENSOR_EXPR_H
+
+namespace Eigen {
+
+/** \class TensorExpr
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor expression classes.
+  *
+  * The TensorCwiseNullaryOp class applies a nullary operators to an expression.
+  * This is typically used to generate constants.
+  *
+  * The TensorCwiseUnaryOp class represents an expression where a unary operator
+  * (e.g. cwiseSqrt) is applied to an expression.
+  *
+  * The TensorCwiseBinaryOp class represents an expression where a binary
+  * operator (e.g. addition) is applied to a lhs and a rhs expression.
+  *
+  */
+namespace internal {
+template<typename NullaryOp, typename XprType>
+struct traits<TensorCwiseNullaryOp<NullaryOp, XprType> >
+    : traits<XprType>
+{
+  typedef traits<XprType> XprTraits;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::Nested XprTypeNested;
+  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+
+  enum {
+    Flags = 0
+  };
+};
+
+}  // end namespace internal
+
+
+
+template<typename NullaryOp, typename XprType>
+class TensorCwiseNullaryOp : public TensorBase<TensorCwiseNullaryOp<NullaryOp, XprType>, ReadOnlyAccessors>
+{
+  public:
+    typedef typename Eigen::internal::traits<TensorCwiseNullaryOp>::Scalar Scalar;
+    typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+    typedef typename XprType::CoeffReturnType CoeffReturnType;
+    typedef TensorCwiseNullaryOp<NullaryOp, XprType> Nested;
+    typedef typename Eigen::internal::traits<TensorCwiseNullaryOp>::StorageKind StorageKind;
+    typedef typename Eigen::internal::traits<TensorCwiseNullaryOp>::Index Index;
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCwiseNullaryOp(const XprType& xpr, const NullaryOp& func = NullaryOp())
+        : m_xpr(xpr), m_functor(func) {}
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    nestedExpression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    const NullaryOp& functor() const { return m_functor; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const NullaryOp m_functor;
+};
+
+
+
+namespace internal {
+template<typename UnaryOp, typename XprType>
+struct traits<TensorCwiseUnaryOp<UnaryOp, XprType> >
+    : traits<XprType>
+{
+  // TODO(phli): Add InputScalar, InputPacket.  Check references to
+  // current Scalar/Packet to see if the intent is Input or Output.
+  typedef typename result_of<UnaryOp(typename XprType::Scalar)>::type Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprType::Nested XprTypeNested;
+  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename UnaryOp, typename XprType>
+struct eval<TensorCwiseUnaryOp<UnaryOp, XprType>, Eigen::Dense>
+{
+  typedef const TensorCwiseUnaryOp<UnaryOp, XprType>& type;
+};
+
+template<typename UnaryOp, typename XprType>
+struct nested<TensorCwiseUnaryOp<UnaryOp, XprType>, 1, typename eval<TensorCwiseUnaryOp<UnaryOp, XprType> >::type>
+{
+  typedef TensorCwiseUnaryOp<UnaryOp, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename UnaryOp, typename XprType>
+class TensorCwiseUnaryOp : public TensorBase<TensorCwiseUnaryOp<UnaryOp, XprType>, ReadOnlyAccessors>
+{
+  public:
+    // TODO(phli): Add InputScalar, InputPacket.  Check references to
+    // current Scalar/Packet to see if the intent is Input or Output.
+    typedef typename Eigen::internal::traits<TensorCwiseUnaryOp>::Scalar Scalar;
+    typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+    typedef Scalar CoeffReturnType;
+    typedef typename Eigen::internal::nested<TensorCwiseUnaryOp>::type Nested;
+    typedef typename Eigen::internal::traits<TensorCwiseUnaryOp>::StorageKind StorageKind;
+    typedef typename Eigen::internal::traits<TensorCwiseUnaryOp>::Index Index;
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
+      : m_xpr(xpr), m_functor(func) {}
+
+    EIGEN_DEVICE_FUNC
+    const UnaryOp& functor() const { return m_functor; }
+
+    /** \returns the nested expression */
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    nestedExpression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const UnaryOp m_functor;
+};
+
+
+namespace internal {
+template<typename BinaryOp, typename LhsXprType, typename RhsXprType>
+struct traits<TensorCwiseBinaryOp<BinaryOp, LhsXprType, RhsXprType> >
+{
+  // Type promotion to handle the case where the types of the lhs and the rhs
+  // are different.
+  // TODO(phli): Add Lhs/RhsScalar, Lhs/RhsPacket.  Check references to
+  // current Scalar/Packet to see if the intent is Inputs or Output.
+  typedef typename result_of<
+      BinaryOp(typename LhsXprType::Scalar,
+               typename RhsXprType::Scalar)>::type Scalar;
+  typedef traits<LhsXprType> XprTraits;
+  typedef typename promote_storage_type<
+      typename traits<LhsXprType>::StorageKind,
+      typename traits<RhsXprType>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<
+      typename traits<LhsXprType>::Index,
+      typename traits<RhsXprType>::Index>::type Index;
+  typedef typename LhsXprType::Nested LhsNested;
+  typedef typename RhsXprType::Nested RhsNested;
+  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef typename remove_reference<RhsNested>::type _RhsNested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+
+  enum {
+    Flags = 0
+  };
+};
+
+template<typename BinaryOp, typename LhsXprType, typename RhsXprType>
+struct eval<TensorCwiseBinaryOp<BinaryOp, LhsXprType, RhsXprType>, Eigen::Dense>
+{
+  typedef const TensorCwiseBinaryOp<BinaryOp, LhsXprType, RhsXprType>& type;
+};
+
+template<typename BinaryOp, typename LhsXprType, typename RhsXprType>
+struct nested<TensorCwiseBinaryOp<BinaryOp, LhsXprType, RhsXprType>, 1, typename eval<TensorCwiseBinaryOp<BinaryOp, LhsXprType, RhsXprType> >::type>
+{
+  typedef TensorCwiseBinaryOp<BinaryOp, LhsXprType, RhsXprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename BinaryOp, typename LhsXprType, typename RhsXprType>
+class TensorCwiseBinaryOp : public TensorBase<TensorCwiseBinaryOp<BinaryOp, LhsXprType, RhsXprType>, ReadOnlyAccessors>
+{
+  public:
+    // TODO(phli): Add Lhs/RhsScalar, Lhs/RhsPacket.  Check references to
+    // current Scalar/Packet to see if the intent is Inputs or Output.
+    typedef typename Eigen::internal::traits<TensorCwiseBinaryOp>::Scalar Scalar;
+    typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+    typedef Scalar CoeffReturnType;
+    typedef typename Eigen::internal::nested<TensorCwiseBinaryOp>::type Nested;
+    typedef typename Eigen::internal::traits<TensorCwiseBinaryOp>::StorageKind StorageKind;
+    typedef typename Eigen::internal::traits<TensorCwiseBinaryOp>::Index Index;
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCwiseBinaryOp(const LhsXprType& lhs, const RhsXprType& rhs, const BinaryOp& func = BinaryOp())
+        : m_lhs_xpr(lhs), m_rhs_xpr(rhs), m_functor(func) {}
+
+    EIGEN_DEVICE_FUNC
+    const BinaryOp& functor() const { return m_functor; }
+
+    /** \returns the nested expressions */
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename LhsXprType::Nested>::type&
+    lhsExpression() const { return m_lhs_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename RhsXprType::Nested>::type&
+    rhsExpression() const { return m_rhs_xpr; }
+
+  protected:
+    typename LhsXprType::Nested m_lhs_xpr;
+    typename RhsXprType::Nested m_rhs_xpr;
+    const BinaryOp m_functor;
+};
+
+
+namespace internal {
+template<typename TernaryOp, typename Arg1XprType, typename Arg2XprType, typename Arg3XprType>
+struct traits<TensorCwiseTernaryOp<TernaryOp, Arg1XprType, Arg2XprType, Arg3XprType> >
+{
+  // Type promotion to handle the case where the types of the args are different.
+  typedef typename result_of<
+      TernaryOp(typename Arg1XprType::Scalar,
+                typename Arg2XprType::Scalar,
+                typename Arg3XprType::Scalar)>::type Scalar;
+  typedef traits<Arg1XprType> XprTraits;
+  typedef typename traits<Arg1XprType>::StorageKind StorageKind;
+  typedef typename traits<Arg1XprType>::Index Index;
+  typedef typename Arg1XprType::Nested Arg1Nested;
+  typedef typename Arg2XprType::Nested Arg2Nested;
+  typedef typename Arg3XprType::Nested Arg3Nested;
+  typedef typename remove_reference<Arg1Nested>::type _Arg1Nested;
+  typedef typename remove_reference<Arg2Nested>::type _Arg2Nested;
+  typedef typename remove_reference<Arg3Nested>::type _Arg3Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+
+  enum {
+    Flags = 0
+  };
+};
+
+template<typename TernaryOp, typename Arg1XprType, typename Arg2XprType, typename Arg3XprType>
+struct eval<TensorCwiseTernaryOp<TernaryOp, Arg1XprType, Arg2XprType, Arg3XprType>, Eigen::Dense>
+{
+  typedef const TensorCwiseTernaryOp<TernaryOp, Arg1XprType, Arg2XprType, Arg3XprType>& type;
+};
+
+template<typename TernaryOp, typename Arg1XprType, typename Arg2XprType, typename Arg3XprType>
+struct nested<TensorCwiseTernaryOp<TernaryOp, Arg1XprType, Arg2XprType, Arg3XprType>, 1, typename eval<TensorCwiseTernaryOp<TernaryOp, Arg1XprType, Arg2XprType, Arg3XprType> >::type>
+{
+  typedef TensorCwiseTernaryOp<TernaryOp, Arg1XprType, Arg2XprType, Arg3XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename TernaryOp, typename Arg1XprType, typename Arg2XprType, typename Arg3XprType>
+class TensorCwiseTernaryOp : public TensorBase<TensorCwiseTernaryOp<TernaryOp, Arg1XprType, Arg2XprType, Arg3XprType>, ReadOnlyAccessors>
+{
+  public:
+    typedef typename Eigen::internal::traits<TensorCwiseTernaryOp>::Scalar Scalar;
+    typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+    typedef Scalar CoeffReturnType;
+    typedef typename Eigen::internal::nested<TensorCwiseTernaryOp>::type Nested;
+    typedef typename Eigen::internal::traits<TensorCwiseTernaryOp>::StorageKind StorageKind;
+    typedef typename Eigen::internal::traits<TensorCwiseTernaryOp>::Index Index;
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCwiseTernaryOp(const Arg1XprType& arg1, const Arg2XprType& arg2, const Arg3XprType& arg3, const TernaryOp& func = TernaryOp())
+        : m_arg1_xpr(arg1), m_arg2_xpr(arg2), m_arg3_xpr(arg3), m_functor(func) {}
+
+    EIGEN_DEVICE_FUNC
+    const TernaryOp& functor() const { return m_functor; }
+
+    /** \returns the nested expressions */
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename Arg1XprType::Nested>::type&
+    arg1Expression() const { return m_arg1_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename Arg2XprType::Nested>::type&
+    arg2Expression() const { return m_arg2_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename Arg3XprType::Nested>::type&
+    arg3Expression() const { return m_arg3_xpr; }
+
+  protected:
+    typename Arg1XprType::Nested m_arg1_xpr;
+    typename Arg2XprType::Nested m_arg2_xpr;
+    typename Arg3XprType::Nested m_arg3_xpr;
+    const TernaryOp m_functor;
+};
+
+
+namespace internal {
+template<typename IfXprType, typename ThenXprType, typename ElseXprType>
+struct traits<TensorSelectOp<IfXprType, ThenXprType, ElseXprType> >
+    : traits<ThenXprType>
+{
+  typedef typename traits<ThenXprType>::Scalar Scalar;
+  typedef traits<ThenXprType> XprTraits;
+  typedef typename promote_storage_type<typename traits<ThenXprType>::StorageKind,
+                                        typename traits<ElseXprType>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<ElseXprType>::Index,
+                                      typename traits<ThenXprType>::Index>::type Index;
+  typedef typename IfXprType::Nested IfNested;
+  typedef typename ThenXprType::Nested ThenNested;
+  typedef typename ElseXprType::Nested ElseNested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename IfXprType, typename ThenXprType, typename ElseXprType>
+struct eval<TensorSelectOp<IfXprType, ThenXprType, ElseXprType>, Eigen::Dense>
+{
+  typedef const TensorSelectOp<IfXprType, ThenXprType, ElseXprType>& type;
+};
+
+template<typename IfXprType, typename ThenXprType, typename ElseXprType>
+struct nested<TensorSelectOp<IfXprType, ThenXprType, ElseXprType>, 1, typename eval<TensorSelectOp<IfXprType, ThenXprType, ElseXprType> >::type>
+{
+  typedef TensorSelectOp<IfXprType, ThenXprType, ElseXprType> type;
+};
+
+}  // end namespace internal
+
+
+template<typename IfXprType, typename ThenXprType, typename ElseXprType>
+class TensorSelectOp : public TensorBase<TensorSelectOp<IfXprType, ThenXprType, ElseXprType>, ReadOnlyAccessors>
+{
+  public:
+    typedef typename Eigen::internal::traits<TensorSelectOp>::Scalar Scalar;
+    typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+    typedef typename internal::promote_storage_type<typename ThenXprType::CoeffReturnType,
+                                                    typename ElseXprType::CoeffReturnType>::ret CoeffReturnType;
+    typedef typename Eigen::internal::nested<TensorSelectOp>::type Nested;
+    typedef typename Eigen::internal::traits<TensorSelectOp>::StorageKind StorageKind;
+    typedef typename Eigen::internal::traits<TensorSelectOp>::Index Index;
+
+    EIGEN_DEVICE_FUNC
+    TensorSelectOp(const IfXprType& a_condition,
+                   const ThenXprType& a_then,
+                   const ElseXprType& a_else)
+      : m_condition(a_condition), m_then(a_then), m_else(a_else)
+    { }
+
+    EIGEN_DEVICE_FUNC
+    const IfXprType& ifExpression() const { return m_condition; }
+
+    EIGEN_DEVICE_FUNC
+    const ThenXprType& thenExpression() const { return m_then; }
+
+    EIGEN_DEVICE_FUNC
+    const ElseXprType& elseExpression() const { return m_else; }
+
+  protected:
+    typename IfXprType::Nested m_condition;
+    typename ThenXprType::Nested m_then;
+    typename ElseXprType::Nested m_else;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_EXPR_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFFT.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFFT.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFFT.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFFT.h
@@ -0,0 +1,651 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Jianwei Cui <thucjw@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_FFT_H
+#define EIGEN_CXX11_TENSOR_TENSOR_FFT_H
+
+// This code requires the ability to initialize arrays of constant
+// values directly inside a class.
+#if __cplusplus >= 201103L || EIGEN_COMP_MSVC >= 1900
+
+namespace Eigen {
+
+/** \class TensorFFT
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor FFT class.
+  *
+  * TODO:
+  * Vectorize the Cooley Tukey and the Bluestein algorithm
+  * Add support for multithreaded evaluation
+  * Improve the performance on GPU
+  */
+
+template <bool NeedUprade> struct MakeComplex {
+  template <typename T>
+  EIGEN_DEVICE_FUNC
+  T operator() (const T& val) const { return val; }
+};
+
+template <> struct MakeComplex<true> {
+  template <typename T>
+  EIGEN_DEVICE_FUNC
+  std::complex<T> operator() (const T& val) const { return std::complex<T>(val, 0); }
+};
+
+template <> struct MakeComplex<false> {
+  template <typename T>
+  EIGEN_DEVICE_FUNC
+  std::complex<T> operator() (const std::complex<T>& val) const { return val; }
+};
+
+template <int ResultType> struct PartOf {
+  template <typename T> T operator() (const T& val) const { return val; }
+};
+
+template <> struct PartOf<RealPart> {
+  template <typename T> T operator() (const std::complex<T>& val) const { return val.real(); }
+};
+
+template <> struct PartOf<ImagPart> {
+  template <typename T> T operator() (const std::complex<T>& val) const { return val.imag(); }
+};
+
+namespace internal {
+template <typename FFT, typename XprType, int FFTResultType, int FFTDir>
+struct traits<TensorFFTOp<FFT, XprType, FFTResultType, FFTDir> > : public traits<XprType> {
+  typedef traits<XprType> XprTraits;
+  typedef typename NumTraits<typename XprTraits::Scalar>::Real RealScalar;
+  typedef typename std::complex<RealScalar> ComplexScalar;
+  typedef typename XprTraits::Scalar InputScalar;
+  typedef typename conditional<FFTResultType == RealPart || FFTResultType == ImagPart, RealScalar, ComplexScalar>::type OutputScalar;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template <typename FFT, typename XprType, int FFTResultType, int FFTDirection>
+struct eval<TensorFFTOp<FFT, XprType, FFTResultType, FFTDirection>, Eigen::Dense> {
+  typedef const TensorFFTOp<FFT, XprType, FFTResultType, FFTDirection>& type;
+};
+
+template <typename FFT, typename XprType, int FFTResultType, int FFTDirection>
+struct nested<TensorFFTOp<FFT, XprType, FFTResultType, FFTDirection>, 1, typename eval<TensorFFTOp<FFT, XprType, FFTResultType, FFTDirection> >::type> {
+  typedef TensorFFTOp<FFT, XprType, FFTResultType, FFTDirection> type;
+};
+
+}  // end namespace internal
+
+template <typename FFT, typename XprType, int FFTResultType, int FFTDir>
+class TensorFFTOp : public TensorBase<TensorFFTOp<FFT, XprType, FFTResultType, FFTDir>, ReadOnlyAccessors> {
+ public:
+  typedef typename Eigen::internal::traits<TensorFFTOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename std::complex<RealScalar> ComplexScalar;
+  typedef typename internal::conditional<FFTResultType == RealPart || FFTResultType == ImagPart, RealScalar, ComplexScalar>::type OutputScalar;
+  typedef OutputScalar CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorFFTOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorFFTOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorFFTOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorFFTOp(const XprType& expr, const FFT& fft)
+      : m_xpr(expr), m_fft(fft) {}
+
+  EIGEN_DEVICE_FUNC
+  const FFT& fft() const { return m_fft; }
+
+  EIGEN_DEVICE_FUNC
+  const typename internal::remove_all<typename XprType::Nested>::type& expression() const {
+    return m_xpr;
+  }
+
+ protected:
+  typename XprType::Nested m_xpr;
+  const FFT m_fft;
+};
+
+// Eval as rvalue
+template <typename FFT, typename ArgType, typename Device, int FFTResultType, int FFTDir>
+struct TensorEvaluator<const TensorFFTOp<FFT, ArgType, FFTResultType, FFTDir>, Device> {
+  typedef TensorFFTOp<FFT, ArgType, FFTResultType, FFTDir> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename std::complex<RealScalar> ComplexScalar;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions InputDimensions;
+  typedef internal::traits<XprType> XprTraits;
+  typedef typename XprTraits::Scalar InputScalar;
+  typedef typename internal::conditional<FFTResultType == RealPart || FFTResultType == ImagPart, RealScalar, ComplexScalar>::type OutputScalar;
+  typedef OutputScalar CoeffReturnType;
+  typedef typename PacketType<OutputScalar, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = true,
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) : m_fft(op.fft()), m_impl(op.expression(), device), m_data(NULL), m_device(device) {
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    for (int i = 0; i < NumDims; ++i) {
+      eigen_assert(input_dims[i] > 0);
+      m_dimensions[i] = input_dims[i];
+    }
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_strides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_strides[i] = m_strides[i - 1] * m_dimensions[i - 1];
+      }
+    } else {
+      m_strides[NumDims - 1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_strides[i] = m_strides[i + 1] * m_dimensions[i + 1];
+      }
+    }
+    m_size = m_dimensions.TotalSize();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {
+    return m_dimensions;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(OutputScalar* data) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    if (data) {
+      evalToBuf(data);
+      return false;
+    } else {
+      m_data = (CoeffReturnType*)m_device.allocate(sizeof(CoeffReturnType) * m_size);
+      evalToBuf(m_data);
+      return true;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    if (m_data) {
+      m_device.deallocate(m_data);
+      m_data = NULL;
+    }
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE CoeffReturnType coeff(Index index) const {
+    return m_data[index];
+  }
+
+  template <int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketReturnType
+  packet(Index index) const {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_data + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return m_data; }
+
+
+ private:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalToBuf(OutputScalar* data) {
+    const bool write_to_out = internal::is_same<OutputScalar, ComplexScalar>::value;
+    ComplexScalar* buf = write_to_out ? (ComplexScalar*)data : (ComplexScalar*)m_device.allocate(sizeof(ComplexScalar) * m_size);
+
+    for (Index i = 0; i < m_size; ++i) {
+      buf[i] = MakeComplex<internal::is_same<InputScalar, RealScalar>::value>()(m_impl.coeff(i));
+    }
+
+    for (size_t i = 0; i < m_fft.size(); ++i) {
+      Index dim = m_fft[i];
+      eigen_assert(dim >= 0 && dim < NumDims);
+      Index line_len = m_dimensions[dim];
+      eigen_assert(line_len >= 1);
+      ComplexScalar* line_buf = (ComplexScalar*)m_device.allocate(sizeof(ComplexScalar) * line_len);
+      const bool is_power_of_two = isPowerOfTwo(line_len);
+      const Index good_composite = is_power_of_two ? 0 : findGoodComposite(line_len);
+      const Index log_len = is_power_of_two ? getLog2(line_len) : getLog2(good_composite);
+
+      ComplexScalar* a = is_power_of_two ? NULL : (ComplexScalar*)m_device.allocate(sizeof(ComplexScalar) * good_composite);
+      ComplexScalar* b = is_power_of_two ? NULL : (ComplexScalar*)m_device.allocate(sizeof(ComplexScalar) * good_composite);
+      ComplexScalar* pos_j_base_powered = is_power_of_two ? NULL : (ComplexScalar*)m_device.allocate(sizeof(ComplexScalar) * (line_len + 1));
+      if (!is_power_of_two) {
+        // Compute twiddle factors
+        //   t_n = exp(sqrt(-1) * pi * n^2 / line_len)
+        // for n = 0, 1,..., line_len-1.
+        // For n > 2 we use the recurrence t_n = t_{n-1}^2 / t_{n-2} * t_1^2
+        pos_j_base_powered[0] = ComplexScalar(1, 0);
+        if (line_len > 1) {
+          const RealScalar pi_over_len(EIGEN_PI / line_len);
+          const ComplexScalar pos_j_base = ComplexScalar(
+	       std::cos(pi_over_len), std::sin(pi_over_len));
+          pos_j_base_powered[1] = pos_j_base;
+          if (line_len > 2) {
+            const ComplexScalar pos_j_base_sq = pos_j_base * pos_j_base;
+            for (int j = 2; j < line_len + 1; ++j) {
+              pos_j_base_powered[j] = pos_j_base_powered[j - 1] *
+                                      pos_j_base_powered[j - 1] /
+                                      pos_j_base_powered[j - 2] * pos_j_base_sq;
+            }
+          }
+        }
+      }
+
+      for (Index partial_index = 0; partial_index < m_size / line_len; ++partial_index) {
+        const Index base_offset = getBaseOffsetFromIndex(partial_index, dim);
+
+        // get data into line_buf
+        const Index stride = m_strides[dim];
+        if (stride == 1) {
+          memcpy(line_buf, &buf[base_offset], line_len*sizeof(ComplexScalar));
+        } else {
+          Index offset = base_offset;
+          for (int j = 0; j < line_len; ++j, offset += stride) {
+            line_buf[j] = buf[offset];
+          }
+        }
+
+        // processs the line
+        if (is_power_of_two) {
+          processDataLineCooleyTukey(line_buf, line_len, log_len);
+        }
+        else {
+          processDataLineBluestein(line_buf, line_len, good_composite, log_len, a, b, pos_j_base_powered);
+        }
+
+        // write back
+        if (FFTDir == FFT_FORWARD && stride == 1) {
+          memcpy(&buf[base_offset], line_buf, line_len*sizeof(ComplexScalar));
+        } else {
+          Index offset = base_offset;
+          const ComplexScalar div_factor =  ComplexScalar(1.0 / line_len, 0);
+          for (int j = 0; j < line_len; ++j, offset += stride) {
+             buf[offset] = (FFTDir == FFT_FORWARD) ? line_buf[j] : line_buf[j] * div_factor;
+          }
+        }
+      }
+      m_device.deallocate(line_buf);
+      if (!is_power_of_two) {
+        m_device.deallocate(a);
+        m_device.deallocate(b);
+        m_device.deallocate(pos_j_base_powered);
+      }
+    }
+
+    if(!write_to_out) {
+      for (Index i = 0; i < m_size; ++i) {
+        data[i] = PartOf<FFTResultType>()(buf[i]);
+      }
+      m_device.deallocate(buf);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static bool isPowerOfTwo(Index x) {
+    eigen_assert(x > 0);
+    return !(x & (x - 1));
+  }
+
+  // The composite number for padding, used in Bluestein's FFT algorithm
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static Index findGoodComposite(Index n) {
+    Index i = 2;
+    while (i < 2 * n - 1) i *= 2;
+    return i;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static Index getLog2(Index m) {
+    Index log2m = 0;
+    while (m >>= 1) log2m++;
+    return log2m;
+  }
+
+  // Call Cooley Tukey algorithm directly, data length must be power of 2
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void processDataLineCooleyTukey(ComplexScalar* line_buf, Index line_len, Index log_len) {
+    eigen_assert(isPowerOfTwo(line_len));
+    scramble_FFT(line_buf, line_len);
+    compute_1D_Butterfly<FFTDir>(line_buf, line_len, log_len);
+  }
+
+  // Call Bluestein's FFT algorithm, m is a good composite number greater than (2 * n - 1), used as the padding length
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void processDataLineBluestein(ComplexScalar* line_buf, Index line_len, Index good_composite, Index log_len, ComplexScalar* a, ComplexScalar* b, const ComplexScalar* pos_j_base_powered) {
+    Index n = line_len;
+    Index m = good_composite;
+    ComplexScalar* data = line_buf;
+
+    for (Index i = 0; i < n; ++i) {
+      if(FFTDir == FFT_FORWARD) {
+        a[i] = data[i] * numext::conj(pos_j_base_powered[i]);
+      }
+      else {
+        a[i] = data[i] * pos_j_base_powered[i];
+      }
+    }
+    for (Index i = n; i < m; ++i) {
+      a[i] = ComplexScalar(0, 0);
+    }
+
+    for (Index i = 0; i < n; ++i) {
+      if(FFTDir == FFT_FORWARD) {
+        b[i] = pos_j_base_powered[i];
+      }
+      else {
+        b[i] = numext::conj(pos_j_base_powered[i]);
+      }
+    }
+    for (Index i = n; i < m - n; ++i) {
+      b[i] = ComplexScalar(0, 0);
+    }
+    for (Index i = m - n; i < m; ++i) {
+      if(FFTDir == FFT_FORWARD) {
+        b[i] = pos_j_base_powered[m-i];
+      }
+      else {
+        b[i] = numext::conj(pos_j_base_powered[m-i]);
+      }
+    }
+
+    scramble_FFT(a, m);
+    compute_1D_Butterfly<FFT_FORWARD>(a, m, log_len);
+
+    scramble_FFT(b, m);
+    compute_1D_Butterfly<FFT_FORWARD>(b, m, log_len);
+
+    for (Index i = 0; i < m; ++i) {
+      a[i] *= b[i];
+    }
+
+    scramble_FFT(a, m);
+    compute_1D_Butterfly<FFT_REVERSE>(a, m, log_len);
+
+    //Do the scaling after ifft
+    for (Index i = 0; i < m; ++i) {
+      a[i] /= m;
+    }
+
+    for (Index i = 0; i < n; ++i) {
+      if(FFTDir == FFT_FORWARD) {
+        data[i] = a[i] * numext::conj(pos_j_base_powered[i]);
+      }
+      else {
+        data[i] = a[i] * pos_j_base_powered[i];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE static void scramble_FFT(ComplexScalar* data, Index n) {
+    eigen_assert(isPowerOfTwo(n));
+    Index j = 1;
+    for (Index i = 1; i < n; ++i){
+      if (j > i) {
+        std::swap(data[j-1], data[i-1]);
+      }
+      Index m = n >> 1;
+      while (m >= 2 && j > m) {
+        j -= m;
+        m >>= 1;
+      }
+      j += m;
+    }
+  }
+
+  template <int Dir>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void butterfly_2(ComplexScalar* data) {
+    ComplexScalar tmp = data[1];
+    data[1] = data[0] - data[1];
+    data[0] += tmp;
+  }
+
+  template <int Dir>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void butterfly_4(ComplexScalar* data) {
+    ComplexScalar tmp[4];
+    tmp[0] = data[0] + data[1];
+    tmp[1] = data[0] - data[1];
+    tmp[2] = data[2] + data[3];
+    if (Dir == FFT_FORWARD) {
+      tmp[3] = ComplexScalar(0.0, -1.0) * (data[2] - data[3]);
+    } else {
+      tmp[3] = ComplexScalar(0.0, 1.0) * (data[2] - data[3]);
+    }
+    data[0] = tmp[0] + tmp[2];
+    data[1] = tmp[1] + tmp[3];
+    data[2] = tmp[0] - tmp[2];
+    data[3] = tmp[1] - tmp[3];
+  }
+
+  template <int Dir>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void butterfly_8(ComplexScalar* data) {
+    ComplexScalar tmp_1[8];
+    ComplexScalar tmp_2[8];
+
+    tmp_1[0] = data[0] + data[1];
+    tmp_1[1] = data[0] - data[1];
+    tmp_1[2] = data[2] + data[3];
+    if (Dir == FFT_FORWARD) {
+      tmp_1[3] = (data[2] - data[3]) * ComplexScalar(0, -1);
+    } else {
+      tmp_1[3] = (data[2] - data[3]) * ComplexScalar(0, 1);
+    }
+    tmp_1[4] = data[4] + data[5];
+    tmp_1[5] = data[4] - data[5];
+    tmp_1[6] = data[6] + data[7];
+    if (Dir == FFT_FORWARD) {
+      tmp_1[7] = (data[6] - data[7]) * ComplexScalar(0, -1);
+    } else {
+      tmp_1[7] = (data[6] - data[7]) * ComplexScalar(0, 1);
+    }
+    tmp_2[0] = tmp_1[0] + tmp_1[2];
+    tmp_2[1] = tmp_1[1] + tmp_1[3];
+    tmp_2[2] = tmp_1[0] - tmp_1[2];
+    tmp_2[3] = tmp_1[1] - tmp_1[3];
+    tmp_2[4] = tmp_1[4] + tmp_1[6];
+// SQRT2DIV2 = sqrt(2)/2
+#define SQRT2DIV2 0.7071067811865476
+    if (Dir == FFT_FORWARD) {
+      tmp_2[5] = (tmp_1[5] + tmp_1[7]) * ComplexScalar(SQRT2DIV2, -SQRT2DIV2);
+      tmp_2[6] = (tmp_1[4] - tmp_1[6]) * ComplexScalar(0, -1);
+      tmp_2[7] = (tmp_1[5] - tmp_1[7]) * ComplexScalar(-SQRT2DIV2, -SQRT2DIV2);
+    } else {
+      tmp_2[5] = (tmp_1[5] + tmp_1[7]) * ComplexScalar(SQRT2DIV2, SQRT2DIV2);
+      tmp_2[6] = (tmp_1[4] - tmp_1[6]) * ComplexScalar(0, 1);
+      tmp_2[7] = (tmp_1[5] - tmp_1[7]) * ComplexScalar(-SQRT2DIV2, SQRT2DIV2);
+    }
+    data[0] = tmp_2[0] + tmp_2[4];
+    data[1] = tmp_2[1] + tmp_2[5];
+    data[2] = tmp_2[2] + tmp_2[6];
+    data[3] = tmp_2[3] + tmp_2[7];
+    data[4] = tmp_2[0] - tmp_2[4];
+    data[5] = tmp_2[1] - tmp_2[5];
+    data[6] = tmp_2[2] - tmp_2[6];
+    data[7] = tmp_2[3] - tmp_2[7];
+  }
+
+  template <int Dir>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void butterfly_1D_merge(
+      ComplexScalar* data, Index n, Index n_power_of_2) {
+    // Original code:
+    // RealScalar wtemp = std::sin(M_PI/n);
+    // RealScalar wpi =  -std::sin(2 * M_PI/n);
+    const RealScalar wtemp = m_sin_PI_div_n_LUT[n_power_of_2];
+    const RealScalar wpi = (Dir == FFT_FORWARD)
+                               ? m_minus_sin_2_PI_div_n_LUT[n_power_of_2]
+                               : -m_minus_sin_2_PI_div_n_LUT[n_power_of_2];
+
+    const ComplexScalar wp(wtemp, wpi);
+    const ComplexScalar wp_one = wp + ComplexScalar(1, 0);
+    const ComplexScalar wp_one_2 = wp_one * wp_one;
+    const ComplexScalar wp_one_3 = wp_one_2 * wp_one;
+    const ComplexScalar wp_one_4 = wp_one_3 * wp_one;
+    const Index n2 = n / 2;
+    ComplexScalar w(1.0, 0.0);
+    for (Index i = 0; i < n2; i += 4) {
+       ComplexScalar temp0(data[i + n2] * w);
+       ComplexScalar temp1(data[i + 1 + n2] * w * wp_one);
+       ComplexScalar temp2(data[i + 2 + n2] * w * wp_one_2);
+       ComplexScalar temp3(data[i + 3 + n2] * w * wp_one_3);
+       w = w * wp_one_4;
+
+       data[i + n2] = data[i] - temp0;
+       data[i] += temp0;
+
+       data[i + 1 + n2] = data[i + 1] - temp1;
+       data[i + 1] += temp1;
+
+       data[i + 2 + n2] = data[i + 2] - temp2;
+       data[i + 2] += temp2;
+
+       data[i + 3 + n2] = data[i + 3] - temp3;
+       data[i + 3] += temp3;
+    }
+  }
+
+ template <int Dir>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void compute_1D_Butterfly(
+      ComplexScalar* data, Index n, Index n_power_of_2) {
+    eigen_assert(isPowerOfTwo(n));
+    if (n > 8) {
+      compute_1D_Butterfly<Dir>(data, n / 2, n_power_of_2 - 1);
+      compute_1D_Butterfly<Dir>(data + n / 2, n / 2, n_power_of_2 - 1);
+      butterfly_1D_merge<Dir>(data, n, n_power_of_2);
+    } else if (n == 8) {
+      butterfly_8<Dir>(data);
+    } else if (n == 4) {
+      butterfly_4<Dir>(data);
+    } else if (n == 2) {
+      butterfly_2<Dir>(data);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index getBaseOffsetFromIndex(Index index, Index omitted_dim) const {
+    Index result = 0;
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > omitted_dim; --i) {
+        const Index partial_m_stride = m_strides[i] / m_dimensions[omitted_dim];
+        const Index idx = index / partial_m_stride;
+        index -= idx * partial_m_stride;
+        result += idx * m_strides[i];
+      }
+      result += index;
+    }
+    else {
+      for (Index i = 0; i < omitted_dim; ++i) {
+        const Index partial_m_stride = m_strides[i] / m_dimensions[omitted_dim];
+        const Index idx = index / partial_m_stride;
+        index -= idx * partial_m_stride;
+        result += idx * m_strides[i];
+      }
+      result += index;
+    }
+    // Value of index_coords[omitted_dim] is not determined to this step
+    return result;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index getIndexFromOffset(Index base, Index omitted_dim, Index offset) const {
+    Index result = base + offset * m_strides[omitted_dim] ;
+    return result;
+  }
+
+ protected:
+  Index m_size;
+  const FFT& m_fft;
+  Dimensions m_dimensions;
+  array<Index, NumDims> m_strides;
+  TensorEvaluator<ArgType, Device> m_impl;
+  CoeffReturnType* m_data;
+  const Device& m_device;
+
+  // This will support a maximum FFT size of 2^32 for each dimension
+  // m_sin_PI_div_n_LUT[i] = (-2) * std::sin(M_PI / std::pow(2,i)) ^ 2;
+  const RealScalar m_sin_PI_div_n_LUT[32] = {
+    RealScalar(0.0),
+    RealScalar(-2),
+    RealScalar(-0.999999999999999),
+    RealScalar(-0.292893218813453),
+    RealScalar(-0.0761204674887130),
+    RealScalar(-0.0192147195967696),
+    RealScalar(-0.00481527332780311),
+    RealScalar(-0.00120454379482761),
+    RealScalar(-3.01181303795779e-04),
+    RealScalar(-7.52981608554592e-05),
+    RealScalar(-1.88247173988574e-05),
+    RealScalar(-4.70619042382852e-06),
+    RealScalar(-1.17654829809007e-06),
+    RealScalar(-2.94137117780840e-07),
+    RealScalar(-7.35342821488550e-08),
+    RealScalar(-1.83835707061916e-08),
+    RealScalar(-4.59589268710903e-09),
+    RealScalar(-1.14897317243732e-09),
+    RealScalar(-2.87243293150586e-10),
+    RealScalar( -7.18108232902250e-11),
+    RealScalar(-1.79527058227174e-11),
+    RealScalar(-4.48817645568941e-12),
+    RealScalar(-1.12204411392298e-12),
+    RealScalar(-2.80511028480785e-13),
+    RealScalar(-7.01277571201985e-14),
+    RealScalar(-1.75319392800498e-14),
+    RealScalar(-4.38298482001247e-15),
+    RealScalar(-1.09574620500312e-15),
+    RealScalar(-2.73936551250781e-16),
+    RealScalar(-6.84841378126949e-17),
+    RealScalar(-1.71210344531737e-17),
+    RealScalar(-4.28025861329343e-18)
+  };
+
+  // m_minus_sin_2_PI_div_n_LUT[i] = -std::sin(2 * M_PI / std::pow(2,i));
+  const RealScalar m_minus_sin_2_PI_div_n_LUT[32] = {
+    RealScalar(0.0),
+    RealScalar(0.0),
+    RealScalar(-1.00000000000000e+00),
+    RealScalar(-7.07106781186547e-01),
+    RealScalar(-3.82683432365090e-01),
+    RealScalar(-1.95090322016128e-01),
+    RealScalar(-9.80171403295606e-02),
+    RealScalar(-4.90676743274180e-02),
+    RealScalar(-2.45412285229123e-02),
+    RealScalar(-1.22715382857199e-02),
+    RealScalar(-6.13588464915448e-03),
+    RealScalar(-3.06795676296598e-03),
+    RealScalar(-1.53398018628477e-03),
+    RealScalar(-7.66990318742704e-04),
+    RealScalar(-3.83495187571396e-04),
+    RealScalar(-1.91747597310703e-04),
+    RealScalar(-9.58737990959773e-05),
+    RealScalar(-4.79368996030669e-05),
+    RealScalar(-2.39684498084182e-05),
+    RealScalar(-1.19842249050697e-05),
+    RealScalar(-5.99211245264243e-06),
+    RealScalar(-2.99605622633466e-06),
+    RealScalar(-1.49802811316901e-06),
+    RealScalar(-7.49014056584716e-07),
+    RealScalar(-3.74507028292384e-07),
+    RealScalar(-1.87253514146195e-07),
+    RealScalar(-9.36267570730981e-08),
+    RealScalar(-4.68133785365491e-08),
+    RealScalar(-2.34066892682746e-08),
+    RealScalar(-1.17033446341373e-08),
+    RealScalar(-5.85167231706864e-09),
+    RealScalar(-2.92583615853432e-09)
+  };
+};
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_HAS_CONSTEXPR
+
+
+#endif  // EIGEN_CXX11_TENSOR_TENSOR_FFT_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFixedSize.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFixedSize.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFixedSize.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFixedSize.h
@@ -0,0 +1,389 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_FIXED_SIZE_H
+#define EIGEN_CXX11_TENSOR_TENSOR_FIXED_SIZE_H
+
+namespace Eigen {
+
+/** \class TensorFixedSize
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief The fixed sized version of the tensor class.
+  *
+  * The fixed sized equivalent of
+  * Eigen::Tensor<float, 3> t(3, 5, 7);
+  * is
+  * Eigen::TensorFixedSize<float, Size<3,5,7>> t;
+  */
+
+template<typename Scalar_, typename Dimensions_, int Options_, typename IndexType>
+class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_, Options_, IndexType> >
+{
+  public:
+    typedef TensorFixedSize<Scalar_, Dimensions_, Options_, IndexType> Self;
+    typedef TensorBase<TensorFixedSize<Scalar_, Dimensions_, Options_, IndexType> > Base;
+    typedef typename Eigen::internal::nested<Self>::type Nested;
+    typedef typename internal::traits<Self>::StorageKind StorageKind;
+    typedef typename internal::traits<Self>::Index Index;
+    typedef Scalar_ Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename Base::CoeffReturnType CoeffReturnType;
+
+    static const int Options = Options_;
+
+    enum {
+      IsAligned = bool(EIGEN_MAX_ALIGN_BYTES>0),
+      Layout = Options_ & RowMajor ? RowMajor : ColMajor,
+      CoordAccess = true,
+      RawAccess = true
+    };
+
+  typedef Dimensions_ Dimensions;
+  static const std::size_t NumIndices = Dimensions::count;
+
+  protected:
+  TensorStorage<Scalar, Dimensions, Options> m_storage;
+
+  public:
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index                    rank()                   const { return NumIndices; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index                    dimension(std::size_t n) const { return m_storage.dimensions()[n]; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions&        dimensions()             const { return m_storage.dimensions(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index                    size()                   const { return m_storage.size(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar                   *data()                        { return m_storage.data(); }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar             *data()                  const { return m_storage.data(); }
+
+    // This makes EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    // work, because that uses base().coeffRef() - and we don't yet
+    // implement a similar class hierarchy
+    inline Self& base()             { return *this; }
+    inline const Self& base() const { return *this; }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index firstIndex, IndexTypes... otherIndices) const
+    {
+      // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return coeff(array<Index, NumIndices>{{firstIndex, otherIndices...}});
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& coeff(const array<Index, NumIndices>& indices) const
+    {
+      eigen_internal_assert(checkIndexRange(indices));
+      return m_storage.data()[linearizedIndex(indices)];
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return m_storage.data()[index];
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& coeff() const
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return m_storage.data()[0];
+    }
+
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index firstIndex, IndexTypes... otherIndices)
+    {
+      // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return coeffRef(array<Index, NumIndices>{{firstIndex, otherIndices...}});
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef(const array<Index, NumIndices>& indices)
+    {
+      eigen_internal_assert(checkIndexRange(indices));
+      return m_storage.data()[linearizedIndex(indices)];
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return m_storage.data()[index];
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef()
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return m_storage.data()[0];
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()(Index firstIndex, IndexTypes... otherIndices) const
+    {
+      // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return this->operator()(array<Index, NumIndices>{{firstIndex, otherIndices...}});
+    }
+#else
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1) const
+    {
+      if (Options&RowMajor) {
+        const Index index = i1 + i0 * m_storage.dimensions()[1];
+        return m_storage.data()[index];
+      } else {
+        const Index index = i0 + i1 * m_storage.dimensions()[0];
+        return m_storage.data()[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2) const
+    {
+      if (Options&RowMajor) {
+         const Index index = i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0);
+         return m_storage.data()[index];
+      } else {
+         const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * i2);
+        return m_storage.data()[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3) const
+    {
+      if (Options&RowMajor) {
+        const Index index = i3 + m_storage.dimensions()[3] * (i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0));
+        return m_storage.data()[index];
+      } else {
+        const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * (i2 + m_storage.dimensions()[2] * i3));
+        return m_storage.data()[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
+    {
+      if (Options&RowMajor) {
+        const Index index = i4 + m_storage.dimensions()[4] * (i3 + m_storage.dimensions()[3] * (i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0)));
+        return m_storage.data()[index];
+      } else {
+        const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * (i2 + m_storage.dimensions()[2] * (i3 + m_storage.dimensions()[3] * i4)));
+        return m_storage.data()[index];
+      }
+    }
+#endif
+
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const
+    {
+      eigen_assert(checkIndexRange(indices));
+      return coeff(indices);
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index index) const
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return coeff(index);
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()() const
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return coeff();
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator[](Index index) const
+    {
+      // The bracket operator is only for vectors, use the parenthesis operator instead.
+      EIGEN_STATIC_ASSERT(NumIndices == 1, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return coeff(index);
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, IndexTypes... otherIndices)
+    {
+      // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return operator()(array<Index, NumIndices>{{firstIndex, otherIndices...}});
+    }
+#else
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1)
+    {
+       if (Options&RowMajor) {
+         const Index index = i1 + i0 * m_storage.dimensions()[1];
+        return m_storage.data()[index];
+      } else {
+        const Index index = i0 + i1 * m_storage.dimensions()[0];
+        return m_storage.data()[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2)
+    {
+       if (Options&RowMajor) {
+         const Index index = i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0);
+        return m_storage.data()[index];
+      } else {
+         const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * i2);
+        return m_storage.data()[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
+    {
+      if (Options&RowMajor) {
+        const Index index = i3 + m_storage.dimensions()[3] * (i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0));
+        return m_storage.data()[index];
+      } else {
+        const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * (i2 + m_storage.dimensions()[2] * i3));
+        return m_storage.data()[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
+    {
+      if (Options&RowMajor) {
+        const Index index = i4 + m_storage.dimensions()[4] * (i3 + m_storage.dimensions()[3] * (i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0)));
+        return m_storage.data()[index];
+      } else {
+        const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * (i2 + m_storage.dimensions()[2] * (i3 + m_storage.dimensions()[3] * i4)));
+        return m_storage.data()[index];
+      }
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices)
+    {
+      eigen_assert(checkIndexRange(indices));
+      return coeffRef(indices);
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index index)
+    {
+      eigen_assert(index >= 0 && index < size());
+      return coeffRef(index);
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()()
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return coeffRef();
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator[](Index index)
+    {
+      // The bracket operator is only for vectors, use the parenthesis operator instead
+      EIGEN_STATIC_ASSERT(NumIndices == 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return coeffRef(index);
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorFixedSize()
+      : m_storage()
+    {
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorFixedSize(const Self& other)
+      : m_storage(other.m_storage)
+    {
+    }
+
+#if EIGEN_HAS_RVALUE_REFERENCES
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorFixedSize(Self&& other)
+      : m_storage(other.m_storage)
+    {
+    }
+#endif
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorFixedSize(const TensorBase<OtherDerived, ReadOnlyAccessors>& other)
+    {
+      typedef TensorAssignOp<TensorFixedSize, const OtherDerived> Assign;
+      Assign assign(*this, other.derived());
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+    }
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorFixedSize(const TensorBase<OtherDerived, WriteAccessors>& other)
+    {
+      typedef TensorAssignOp<TensorFixedSize, const OtherDerived> Assign;
+      Assign assign(*this, other.derived());
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorFixedSize& operator=(const TensorFixedSize& other)
+    {
+      // FIXME: check that the dimensions of other match the dimensions of *this.
+      // Unfortunately this isn't possible yet when the rhs is an expression.
+      typedef TensorAssignOp<Self, const TensorFixedSize> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorFixedSize& operator=(const OtherDerived& other)
+    {
+      // FIXME: check that the dimensions of other match the dimensions of *this.
+      // Unfortunately this isn't possible yet when the rhs is an expression.
+      typedef TensorAssignOp<Self, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE bool checkIndexRange(const array<Index, NumIndices>& /*indices*/) const
+    {
+      using internal::array_apply_and_reduce;
+      using internal::array_zip_and_reduce;
+      using internal::greater_equal_zero_op;
+      using internal::logical_and_op;
+      using internal::lesser_op;
+
+      return true;
+        // check whether the indices are all >= 0
+          /*       array_apply_and_reduce<logical_and_op, greater_equal_zero_op>(indices) &&
+        // check whether the indices fit in the dimensions
+        array_zip_and_reduce<logical_and_op, lesser_op>(indices, m_storage.dimensions());*/
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index linearizedIndex(const array<Index, NumIndices>& indices) const
+    {
+      if (Options&RowMajor) {
+        return m_storage.dimensions().IndexOfRowMajor(indices);
+      } else {
+        return m_storage.dimensions().IndexOfColMajor(indices);
+      }
+    }
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_FIXED_SIZE_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
@@ -0,0 +1,167 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_FORCED_EVAL_H
+#define EIGEN_CXX11_TENSOR_TENSOR_FORCED_EVAL_H
+
+namespace Eigen {
+
+/** \class TensorForcedEval
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor reshaping class.
+  *
+  *
+  */
+/// template <class> class MakePointer_ is added to convert the host pointer to the device pointer.
+/// It is added due to the fact that for our device compiler T* is not allowed.
+/// If we wanted to use the same Evaluator functions we have to convert that type to our pointer T.
+/// This is done through our MakePointer_ class. By default the Type in the MakePointer_<T> is T* .
+/// Therefore, by adding the default value, we managed to convert the type and it does not break any
+/// existing code as its default value is T*.
+namespace internal {
+template<typename XprType, template <class> class MakePointer_>
+struct traits<TensorForcedEvalOp<XprType, MakePointer_> >
+{
+  // Type promotion to handle the case where the types of the lhs and the rhs are different.
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename traits<XprType>::StorageKind StorageKind;
+  typedef typename traits<XprType>::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+
+  enum {
+    Flags = 0
+  };
+  template <class T> struct MakePointer {
+    // Intermediate typedef to workaround MSVC issue.
+    typedef MakePointer_<T> MakePointerT;
+    typedef typename MakePointerT::Type Type;
+  };
+};
+
+template<typename XprType, template <class> class MakePointer_>
+struct eval<TensorForcedEvalOp<XprType, MakePointer_>, Eigen::Dense>
+{
+  typedef const TensorForcedEvalOp<XprType, MakePointer_>& type;
+};
+
+template<typename XprType, template <class> class MakePointer_>
+struct nested<TensorForcedEvalOp<XprType, MakePointer_>, 1, typename eval<TensorForcedEvalOp<XprType, MakePointer_> >::type>
+{
+  typedef TensorForcedEvalOp<XprType, MakePointer_> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename XprType, template <class> class MakePointer_>
+class TensorForcedEvalOp : public TensorBase<TensorForcedEvalOp<XprType, MakePointer_>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorForcedEvalOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorForcedEvalOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorForcedEvalOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorForcedEvalOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorForcedEvalOp(const XprType& expr)
+      : m_xpr(expr) {}
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+};
+
+
+template<typename ArgType, typename Device, template <class> class MakePointer_>
+struct TensorEvaluator<const TensorForcedEvalOp<ArgType, MakePointer_>, Device>
+{
+  typedef TensorForcedEvalOp<ArgType, MakePointer_> XprType;
+  typedef typename ArgType::Scalar Scalar;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = true,
+    PacketAccess = (PacketSize > 1),
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    RawAccess = true
+  };
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device)
+	/// op_ is used for sycl
+      : m_impl(op.expression(), device), m_op(op.expression()), m_device(device), m_buffer(NULL)
+  { }
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_impl.dimensions(); }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) {
+    const Index numValues =  internal::array_prod(m_impl.dimensions());
+    m_buffer = (CoeffReturnType*)m_device.allocate(numValues * sizeof(CoeffReturnType));
+    // Should initialize the memory in case we're dealing with non POD types.
+    if (NumTraits<CoeffReturnType>::RequireInitialization) {
+      for (Index i = 0; i < numValues; ++i) {
+        new(m_buffer+i) CoeffReturnType();
+      }
+    }
+    typedef TensorEvalToOp< const typename internal::remove_const<ArgType>::type > EvalTo;
+    EvalTo evalToTmp(m_buffer, m_op);
+    const bool PacketAccess = internal::IsVectorizable<Device, const ArgType>::value;
+    internal::TensorExecutor<const EvalTo, typename internal::remove_const<Device>::type, PacketAccess>::run(evalToTmp, m_device);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_device.deallocate(m_buffer);
+    m_buffer = NULL;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_buffer[index];
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_buffer + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC typename MakePointer<Scalar>::Type data() const { return m_buffer; }
+
+  /// required by sycl in order to extract the sycl accessor
+  const TensorEvaluator<ArgType, Device>& impl() { return m_impl; }
+  /// used by sycl in order to build the sycl buffer
+  const Device& device() const{return m_device;}
+ private:
+  TensorEvaluator<ArgType, Device> m_impl;
+  const ArgType m_op;
+  const Device& m_device;
+  typename MakePointer<CoeffReturnType>::Type m_buffer;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_FORCED_EVAL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
@@ -0,0 +1,109 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_FORWARD_DECLARATIONS_H
+#define EIGEN_CXX11_TENSOR_TENSOR_FORWARD_DECLARATIONS_H
+
+namespace Eigen {
+
+// MakePointer class is used as a container of the adress space of the pointer
+// on the host and on the device. From the host side it generates the T* pointer
+// and when EIGEN_USE_SYCL is used it construct a buffer with a map_allocator to
+// T* m_data on the host. It is always called on the device.
+// Specialisation of MakePointer class for creating the sycl buffer with
+// map_allocator.
+template<typename T> struct MakePointer {
+  typedef T* Type;
+};
+
+template<typename PlainObjectType, int Options_ = Unaligned, template <class> class MakePointer_ = MakePointer> class TensorMap;
+template<typename Scalar_, int NumIndices_, int Options_ = 0, typename IndexType = DenseIndex> class Tensor;
+template<typename Scalar_, typename Dimensions, int Options_ = 0, typename IndexType = DenseIndex> class TensorFixedSize;
+template<typename PlainObjectType> class TensorRef;
+template<typename Derived, int AccessLevel> class TensorBase;
+
+template<typename NullaryOp, typename PlainObjectType> class TensorCwiseNullaryOp;
+template<typename UnaryOp, typename XprType> class TensorCwiseUnaryOp;
+template<typename BinaryOp, typename LeftXprType, typename RightXprType> class TensorCwiseBinaryOp;
+template<typename TernaryOp, typename Arg1XprType, typename Arg2XprType, typename Arg3XprType> class TensorCwiseTernaryOp;
+template<typename IfXprType, typename ThenXprType, typename ElseXprType> class TensorSelectOp;
+template<typename Op, typename Dims, typename XprType, template <class> class MakePointer_ = MakePointer > class TensorReductionOp;
+template<typename XprType> class TensorIndexTupleOp;
+template<typename ReduceOp, typename Dims, typename XprType> class TensorTupleReducerOp;
+template<typename Axis, typename LeftXprType, typename RightXprType> class TensorConcatenationOp;
+template<typename Dimensions, typename LeftXprType, typename RightXprType> class TensorContractionOp;
+template<typename TargetType, typename XprType> class TensorConversionOp;
+template<typename Dimensions, typename InputXprType, typename KernelXprType> class TensorConvolutionOp;
+template<typename FFT, typename XprType, int FFTDataType, int FFTDirection> class TensorFFTOp;
+template<typename PatchDim, typename XprType> class TensorPatchOp;
+template<DenseIndex Rows, DenseIndex Cols, typename XprType> class TensorImagePatchOp;
+template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType> class TensorVolumePatchOp;
+template<typename Broadcast, typename XprType> class TensorBroadcastingOp;
+template<DenseIndex DimId, typename XprType> class TensorChippingOp;
+template<typename NewDimensions, typename XprType> class TensorReshapingOp;
+template<typename XprType> class TensorLayoutSwapOp;
+template<typename StartIndices, typename Sizes, typename XprType> class TensorSlicingOp;
+template<typename ReverseDimensions, typename XprType> class TensorReverseOp;
+template<typename PaddingDimensions, typename XprType> class TensorPaddingOp;
+template<typename Shuffle, typename XprType> class TensorShufflingOp;
+template<typename Strides, typename XprType> class TensorStridingOp;
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType> class TensorStridingSlicingOp;
+template<typename Strides, typename XprType> class TensorInflationOp;
+template<typename Generator, typename XprType> class TensorGeneratorOp;
+template<typename LeftXprType, typename RightXprType> class TensorAssignOp;
+template<typename Op, typename XprType> class TensorScanOp;
+
+template<typename CustomUnaryFunc, typename XprType> class TensorCustomUnaryOp;
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType> class TensorCustomBinaryOp;
+
+template<typename XprType, template <class> class MakePointer_ = MakePointer> class TensorEvalToOp;
+template<typename XprType, template <class> class MakePointer_ = MakePointer> class TensorForcedEvalOp;
+
+template<typename ExpressionType, typename DeviceType> class TensorDevice;
+template<typename Derived, typename Device> struct TensorEvaluator;
+
+struct DefaultDevice;
+struct ThreadPoolDevice;
+struct GpuDevice;
+struct SyclDevice;
+
+enum FFTResultType {
+  RealPart = 0,
+  ImagPart = 1,
+  BothParts = 2
+};
+
+enum FFTDirection {
+    FFT_FORWARD = 0,
+    FFT_REVERSE = 1
+};
+
+
+namespace internal {
+
+template <typename Device, typename Expression>
+struct IsVectorizable {
+  static const bool value = TensorEvaluator<Expression, Device>::PacketAccess;
+};
+
+template <typename Expression>
+struct IsVectorizable<GpuDevice, Expression> {
+  static const bool value = TensorEvaluator<Expression, GpuDevice>::PacketAccess &&
+                            TensorEvaluator<Expression, GpuDevice>::IsAligned;
+};
+
+template <typename Expression, typename Device,
+          bool Vectorizable = IsVectorizable<Device, Expression>::value>
+class TensorExecutor;
+
+}  // end namespace internal
+
+}  // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_FORWARD_DECLARATIONS_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
@@ -0,0 +1,489 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_FUNCTORS_H
+#define EIGEN_CXX11_TENSOR_TENSOR_FUNCTORS_H
+
+namespace Eigen {
+namespace internal {
+
+
+/** \internal
+ * \brief Template functor to compute the modulo between an array and a scalar.
+ */
+template <typename Scalar>
+struct scalar_mod_op {
+  EIGEN_DEVICE_FUNC scalar_mod_op(const Scalar& divisor) : m_divisor(divisor) {}
+  EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a % m_divisor; }
+  const Scalar m_divisor;
+};
+template <typename Scalar>
+struct functor_traits<scalar_mod_op<Scalar> >
+{ enum { Cost = scalar_div_cost<Scalar,false>::value, PacketAccess = false }; };
+
+
+/** \internal
+ * \brief Template functor to compute the modulo between 2 arrays.
+ */
+template <typename Scalar>
+struct scalar_mod2_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_mod2_op);
+  EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a, const Scalar& b) const { return a % b; }
+};
+template <typename Scalar>
+struct functor_traits<scalar_mod2_op<Scalar> >
+{ enum { Cost = scalar_div_cost<Scalar,false>::value, PacketAccess = false }; };
+
+template <typename Scalar>
+struct scalar_fmod_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_fmod_op);
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar
+  operator()(const Scalar& a, const Scalar& b) const {
+    return numext::fmod(a, b);
+  }
+};
+template <typename Scalar>
+struct functor_traits<scalar_fmod_op<Scalar> > {
+  enum { Cost = 13,  // Reciprocal throughput of FPREM on Haswell.
+         PacketAccess = false };
+};
+
+
+/** \internal
+  * \brief Template functor to compute the sigmoid of a scalar
+  * \sa class CwiseUnaryOp, ArrayBase::sigmoid()
+  */
+template <typename T>
+struct scalar_sigmoid_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_sigmoid_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T operator()(const T& x) const {
+    const T one = T(1);
+    return one / (one + numext::exp(-x));
+  }
+
+  template <typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Packet packetOp(const Packet& x) const {
+    const Packet one = pset1<Packet>(T(1));
+    return pdiv(one, padd(one, pexp(pnegate(x))));
+  }
+};
+
+template <typename T>
+struct functor_traits<scalar_sigmoid_op<T> > {
+  enum {
+    Cost = NumTraits<T>::AddCost * 2 + NumTraits<T>::MulCost * 6,
+    PacketAccess = packet_traits<T>::HasAdd && packet_traits<T>::HasDiv &&
+                   packet_traits<T>::HasNegate && packet_traits<T>::HasExp
+  };
+};
+
+
+template<typename Reducer, typename Device>
+struct reducer_traits {
+  enum {
+    Cost = 1,
+    PacketAccess = false
+  };
+};
+
+// Standard reduction functors
+template <typename T> struct SumReducer
+{
+  static const bool PacketAccess = packet_traits<T>::HasAdd;
+  static const bool IsStateful = false;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const {
+    internal::scalar_sum_op<T> sum_op;
+    *accum = sum_op(*accum, t);
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const {
+    (*accum) = padd<Packet>(*accum, p);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
+    internal::scalar_cast_op<int, T> conv;
+    return conv(0);
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet initializePacket() const {
+    return pset1<Packet>(initialize());
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalize(const T accum) const {
+    return accum;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet finalizePacket(const Packet& vaccum) const {
+    return vaccum;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalizeBoth(const T saccum, const Packet& vaccum) const {
+    internal::scalar_sum_op<T> sum_op;
+    return sum_op(saccum, predux(vaccum));
+  }
+};
+
+template <typename T, typename Device>
+struct reducer_traits<SumReducer<T>, Device> {
+  enum {
+    Cost = NumTraits<T>::AddCost,
+    PacketAccess = PacketType<T, Device>::HasAdd
+  };
+};
+
+
+template <typename T> struct MeanReducer
+{
+  static const bool PacketAccess = packet_traits<T>::HasAdd && !NumTraits<T>::IsInteger;
+  static const bool IsStateful = true;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  MeanReducer() : scalarCount_(0), packetCount_(0) { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) {
+    internal::scalar_sum_op<T> sum_op;
+    *accum = sum_op(*accum, t);
+    scalarCount_++;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) {
+    (*accum) = padd<Packet>(*accum, p);
+    packetCount_++;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
+    internal::scalar_cast_op<int, T> conv;
+    return conv(0);
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet initializePacket() const {
+    return pset1<Packet>(initialize());
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalize(const T accum) const {
+    return accum / scalarCount_;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet finalizePacket(const Packet& vaccum) const {
+    return pdiv(vaccum, pset1<Packet>(packetCount_));
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalizeBoth(const T saccum, const Packet& vaccum) const {
+    internal::scalar_sum_op<T> sum_op;
+    return sum_op(saccum, predux(vaccum)) / (scalarCount_ + packetCount_ * unpacket_traits<Packet>::size);
+  }
+
+  protected:
+    DenseIndex scalarCount_;
+    DenseIndex packetCount_;
+};
+
+template <typename T, typename Device>
+struct reducer_traits<MeanReducer<T>, Device> {
+  enum {
+    Cost = NumTraits<T>::AddCost,
+    PacketAccess = PacketType<T, Device>::HasAdd
+  };
+};
+
+
+template <typename T, bool IsMax = true, bool IsInteger = true>
+struct MinMaxBottomValue {
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE T bottom_value() {
+    return Eigen::NumTraits<T>::lowest();
+  }
+};
+template <typename T>
+struct MinMaxBottomValue<T, true, false> {
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE T bottom_value() {
+    return -Eigen::NumTraits<T>::infinity();
+  }
+};
+template <typename T>
+struct MinMaxBottomValue<T, false, true> {
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE T bottom_value() {
+    return Eigen::NumTraits<T>::highest();
+  }
+};
+template <typename T>
+struct MinMaxBottomValue<T, false, false> {
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE T bottom_value() {
+    return Eigen::NumTraits<T>::infinity();
+  }
+};
+
+
+template <typename T> struct MaxReducer
+{
+  static const bool PacketAccess = packet_traits<T>::HasMax;
+  static const bool IsStateful = false;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const {
+    if (t > *accum) { *accum = t; }
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const {
+    (*accum) = pmax<Packet>(*accum, p);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
+    return MinMaxBottomValue<T, true, Eigen::NumTraits<T>::IsInteger>::bottom_value();
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet initializePacket() const {
+    return pset1<Packet>(initialize());
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalize(const T accum) const {
+    return accum;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet finalizePacket(const Packet& vaccum) const {
+    return vaccum;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalizeBoth(const T saccum, const Packet& vaccum) const {
+    return numext::maxi(saccum, predux_max(vaccum));
+  }
+};
+
+template <typename T, typename Device>
+struct reducer_traits<MaxReducer<T>, Device> {
+  enum {
+    Cost = NumTraits<T>::AddCost,
+    PacketAccess = PacketType<T, Device>::HasMax
+  };
+};
+
+
+template <typename T> struct MinReducer
+{
+  static const bool PacketAccess = packet_traits<T>::HasMin;
+  static const bool IsStateful = false;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const {
+    if (t < *accum) { *accum = t; }
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const {
+    (*accum) = pmin<Packet>(*accum, p);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
+    return MinMaxBottomValue<T, false, Eigen::NumTraits<T>::IsInteger>::bottom_value();
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet initializePacket() const {
+    return pset1<Packet>(initialize());
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalize(const T accum) const {
+    return accum;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet finalizePacket(const Packet& vaccum) const {
+    return vaccum;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalizeBoth(const T saccum, const Packet& vaccum) const {
+    return numext::mini(saccum, predux_min(vaccum));
+  }
+};
+
+template <typename T, typename Device>
+struct reducer_traits<MinReducer<T>, Device> {
+  enum {
+    Cost = NumTraits<T>::AddCost,
+    PacketAccess = PacketType<T, Device>::HasMin
+  };
+};
+
+
+template <typename T> struct ProdReducer
+{
+  static const bool PacketAccess = packet_traits<T>::HasMul;
+  static const bool IsStateful = false;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const {
+    internal::scalar_product_op<T> prod_op;
+    (*accum) = prod_op(*accum, t);
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const {
+    (*accum) = pmul<Packet>(*accum, p);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
+    internal::scalar_cast_op<int, T> conv;
+    return conv(1);
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet initializePacket() const {
+    return pset1<Packet>(initialize());
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalize(const T accum) const {
+    return accum;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet finalizePacket(const Packet& vaccum) const {
+    return vaccum;
+  }
+  template <typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalizeBoth(const T saccum, const Packet& vaccum) const {
+    internal::scalar_product_op<T> prod_op;
+    return prod_op(saccum, predux_mul(vaccum));
+  }
+};
+
+template <typename T, typename Device>
+struct reducer_traits<ProdReducer<T>, Device> {
+  enum {
+    Cost = NumTraits<T>::MulCost,
+    PacketAccess = PacketType<T, Device>::HasMul
+  };
+};
+
+
+struct AndReducer
+{
+  static const bool PacketAccess = false;
+  static const bool IsStateful = false;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(bool t, bool* accum) const {
+    *accum = *accum && t;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool initialize() const {
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool finalize(bool accum) const {
+    return accum;
+  }
+};
+
+template <typename Device>
+struct reducer_traits<AndReducer, Device> {
+  enum {
+    Cost = 1,
+    PacketAccess = false
+  };
+};
+
+
+struct OrReducer {
+  static const bool PacketAccess = false;
+  static const bool IsStateful = false;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(bool t, bool* accum) const {
+    *accum = *accum || t;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool initialize() const {
+    return false;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool finalize(bool accum) const {
+    return accum;
+  }
+};
+
+template <typename Device>
+struct reducer_traits<OrReducer, Device> {
+  enum {
+    Cost = 1,
+    PacketAccess = false
+  };
+};
+
+
+// Argmin/Argmax reducers
+template <typename T> struct ArgMaxTupleReducer
+{
+  static const bool PacketAccess = false;
+  static const bool IsStateful = false;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const {
+    if (t.second > accum->second) { *accum = t; }
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
+    return T(0, NumTraits<typename T::second_type>::lowest());
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalize(const T& accum) const {
+    return accum;
+  }
+};
+
+template <typename T, typename Device>
+struct reducer_traits<ArgMaxTupleReducer<T>, Device> {
+  enum {
+    Cost = NumTraits<T>::AddCost,
+    PacketAccess = false
+  };
+};
+
+
+template <typename T> struct ArgMinTupleReducer
+{
+  static const bool PacketAccess = false;
+  static const bool IsStateful = false;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T& t, T* accum) const {
+    if (t.second < accum->second) { *accum = t; }
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
+    return T(0, NumTraits<typename T::second_type>::highest());
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalize(const T& accum) const {
+    return accum;
+  }
+};
+
+template <typename T, typename Device>
+struct reducer_traits<ArgMinTupleReducer<T>, Device> {
+  enum {
+    Cost = NumTraits<T>::AddCost,
+    PacketAccess = false
+  };
+};
+
+
+template <typename T, typename Index, size_t NumDims>
+class GaussianGenerator {
+ public:
+  static const bool PacketAccess = false;
+
+  EIGEN_DEVICE_FUNC GaussianGenerator(const array<T, NumDims>& means,
+                                      const array<T, NumDims>& std_devs)
+      : m_means(means)
+  {
+    for (size_t i = 0; i < NumDims; ++i) {
+      m_two_sigmas[i] = std_devs[i] * std_devs[i] * 2;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC T operator()(const array<Index, NumDims>& coordinates) const {
+    T tmp = T(0);
+    for (size_t i = 0; i < NumDims; ++i) {
+      T offset = coordinates[i] - m_means[i];
+      tmp += offset * offset / m_two_sigmas[i];
+    }
+    return numext::exp(-tmp);
+  }
+
+ private:
+  array<T, NumDims> m_means;
+  array<T, NumDims> m_two_sigmas;
+};
+
+template <typename T, typename Index, size_t NumDims>
+struct functor_traits<GaussianGenerator<T, Index, NumDims> > {
+  enum {
+    Cost = NumDims * (2 * NumTraits<T>::AddCost + NumTraits<T>::MulCost +
+                      functor_traits<scalar_quotient_op<T, T> >::Cost) +
+           functor_traits<scalar_exp_op<T> >::Cost,
+    PacketAccess = GaussianGenerator<T, Index, NumDims>::PacketAccess
+  };
+};
+
+} // end namespace internal
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_FUNCTORS_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h
@@ -0,0 +1,185 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_GENERATOR_H
+#define EIGEN_CXX11_TENSOR_TENSOR_GENERATOR_H
+
+namespace Eigen {
+
+/** \class TensorGenerator
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor generator class.
+  *
+  *
+  */
+namespace internal {
+template<typename Generator, typename XprType>
+struct traits<TensorGeneratorOp<Generator, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename Generator, typename XprType>
+struct eval<TensorGeneratorOp<Generator, XprType>, Eigen::Dense>
+{
+  typedef const TensorGeneratorOp<Generator, XprType>& type;
+};
+
+template<typename Generator, typename XprType>
+struct nested<TensorGeneratorOp<Generator, XprType>, 1, typename eval<TensorGeneratorOp<Generator, XprType> >::type>
+{
+  typedef TensorGeneratorOp<Generator, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename Generator, typename XprType>
+class TensorGeneratorOp : public TensorBase<TensorGeneratorOp<Generator, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorGeneratorOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorGeneratorOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorGeneratorOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorGeneratorOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorGeneratorOp(const XprType& expr, const Generator& generator)
+      : m_xpr(expr), m_generator(generator) {}
+
+    EIGEN_DEVICE_FUNC
+    const Generator& generator() const { return m_generator; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const Generator m_generator;
+};
+
+
+// Eval as rvalue
+template<typename Generator, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorGeneratorOp<Generator, ArgType>, Device>
+{
+  typedef TensorGeneratorOp<Generator, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
+  static const int NumDims = internal::array_size<Dimensions>::value;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  enum {
+    IsAligned = false,
+    PacketAccess = (internal::unpacket_traits<PacketReturnType>::size > 1),
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_generator(op.generator())
+  {
+    TensorEvaluator<ArgType, Device> impl(op.expression(), device);
+    m_dimensions = impl.dimensions();
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_strides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_strides[i] = m_strides[i - 1] * m_dimensions[i - 1];
+      }
+    } else {
+      m_strides[NumDims - 1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_strides[i] = m_strides[i + 1] * m_dimensions[i + 1];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    array<Index, NumDims> coords;
+    extract_coordinates(index, coords);
+    return m_generator(coords);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
+    EIGEN_STATIC_ASSERT((packetSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+packetSize-1 < dimensions().TotalSize());
+
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[packetSize];
+    for (int i = 0; i < packetSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool) const {
+    // TODO(rmlarsen): This is just a placeholder. Define interface to make
+    // generators return their cost.
+    return TensorOpCost(0, 0, TensorOpCost::AddCost<Scalar>() +
+                                  TensorOpCost::MulCost<Scalar>());
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ protected:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void extract_coordinates(Index index, array<Index, NumDims>& coords) const {
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx = index / m_strides[i];
+        index -= idx * m_strides[i];
+        coords[i] = idx;
+      }
+      coords[0] = index;
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx = index / m_strides[i];
+        index -= idx * m_strides[i];
+        coords[i] = idx;
+      }
+      coords[NumDims-1] = index;
+    }
+  }
+
+  Dimensions m_dimensions;
+  array<Index, NumDims> m_strides;
+  Generator m_generator;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_GENERATOR_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorGlobalFunctions.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorGlobalFunctions.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorGlobalFunctions.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorGlobalFunctions.h
@@ -0,0 +1,33 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Eugene Brevdo <ebrevdo@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_GLOBAL_FUNCTIONS_H
+#define EIGEN_CXX11_TENSOR_TENSOR_GLOBAL_FUNCTIONS_H
+
+namespace Eigen {
+
+/** \cpp11 \returns an expression of the coefficient-wise betainc(\a x, \a a, \a b) to the given tensors.
+ *
+ * This function computes the regularized incomplete beta function (integral).
+ *
+ */
+template <typename ADerived, typename BDerived, typename XDerived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const
+    TensorCwiseTernaryOp<internal::scalar_betainc_op<typename XDerived::Scalar>,
+                         const ADerived, const BDerived, const XDerived>
+    betainc(const ADerived& a, const BDerived& b, const XDerived& x) {
+  return TensorCwiseTernaryOp<
+      internal::scalar_betainc_op<typename XDerived::Scalar>, const ADerived,
+      const BDerived, const XDerived>(
+      a, b, x, internal::scalar_betainc_op<typename XDerived::Scalar>());
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_GLOBAL_FUNCTIONS_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIO.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIO.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIO.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIO.h
@@ -0,0 +1,79 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_IO_H
+#define EIGEN_CXX11_TENSOR_TENSOR_IO_H
+
+namespace Eigen {
+
+namespace internal {
+
+// Print the tensor as a 2d matrix
+template <typename Tensor, int Rank>
+struct TensorPrinter {
+  static void run (std::ostream& os, const Tensor& tensor) {
+    typedef typename internal::remove_const<typename Tensor::Scalar>::type Scalar;
+    typedef typename Tensor::Index Index;
+    const Index total_size = internal::array_prod(tensor.dimensions());
+    if (total_size > 0) {
+      const Index first_dim = Eigen::internal::array_get<0>(tensor.dimensions());
+      static const int layout = Tensor::Layout;
+      Map<const Array<Scalar, Dynamic, Dynamic, layout> > matrix(const_cast<Scalar*>(tensor.data()), first_dim, total_size/first_dim);
+      os << matrix;
+    }
+  }
+};
+
+
+// Print the tensor as a vector
+template <typename Tensor>
+struct TensorPrinter<Tensor, 1> {
+  static void run (std::ostream& os, const Tensor& tensor) {
+    typedef typename internal::remove_const<typename Tensor::Scalar>::type Scalar;
+    typedef typename Tensor::Index Index;
+    const Index total_size = internal::array_prod(tensor.dimensions());
+    if (total_size > 0) {
+      Map<const Array<Scalar, Dynamic, 1> > array(const_cast<Scalar*>(tensor.data()), total_size);
+      os << array;
+    }
+  }
+};
+
+
+// Print the tensor as a scalar
+template <typename Tensor>
+struct TensorPrinter<Tensor, 0> {
+  static void run (std::ostream& os, const Tensor& tensor) {
+    os << tensor.coeff(0);
+  }
+};
+}
+
+template <typename T>
+std::ostream& operator << (std::ostream& os, const TensorBase<T, ReadOnlyAccessors>& expr) {
+  typedef TensorEvaluator<const TensorForcedEvalOp<const T>, DefaultDevice> Evaluator;
+  typedef typename Evaluator::Dimensions Dimensions;
+
+  // Evaluate the expression if needed
+  TensorForcedEvalOp<const T> eval = expr.eval();
+  Evaluator tensor(eval, DefaultDevice());
+  tensor.evalSubExprsIfNeeded(NULL);
+
+  // Print the result
+  static const int rank = internal::array_size<Dimensions>::value;
+  internal::TensorPrinter<Evaluator, rank>::run(os, tensor);
+
+  // Cleanup.
+  tensor.cleanup();
+  return os;
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_IO_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h
@@ -0,0 +1,509 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_IMAGE_PATCH_H
+#define EIGEN_CXX11_TENSOR_TENSOR_IMAGE_PATCH_H
+
+namespace Eigen {
+
+/** \class TensorImagePatch
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Patch extraction specialized for image processing.
+  * This assumes that the input has a least 3 dimensions ordered as follow:
+  *  1st dimension: channels (of size d)
+  *  2nd dimension: rows (of size r)
+  *  3rd dimension: columns (of size c)
+  *  There can be additional dimensions such as time (for video) or batch (for
+  * bulk processing after the first 3.
+  * Calling the image patch code with patch_rows and patch_cols is equivalent
+  * to calling the regular patch extraction code with parameters d, patch_rows,
+  * patch_cols, and 1 for all the additional dimensions.
+  */
+namespace internal {
+template<DenseIndex Rows, DenseIndex Cols, typename XprType>
+struct traits<TensorImagePatchOp<Rows, Cols, XprType> > : public traits<XprType>
+{
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions + 1;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<DenseIndex Rows, DenseIndex Cols, typename XprType>
+struct eval<TensorImagePatchOp<Rows, Cols, XprType>, Eigen::Dense>
+{
+  typedef const TensorImagePatchOp<Rows, Cols, XprType>& type;
+};
+
+template<DenseIndex Rows, DenseIndex Cols, typename XprType>
+struct nested<TensorImagePatchOp<Rows, Cols, XprType>, 1, typename eval<TensorImagePatchOp<Rows, Cols, XprType> >::type>
+{
+  typedef TensorImagePatchOp<Rows, Cols, XprType> type;
+};
+
+}  // end namespace internal
+
+template<DenseIndex Rows, DenseIndex Cols, typename XprType>
+class TensorImagePatchOp : public TensorBase<TensorImagePatchOp<Rows, Cols, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorImagePatchOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorImagePatchOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorImagePatchOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorImagePatchOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorImagePatchOp(const XprType& expr, DenseIndex patch_rows, DenseIndex patch_cols,
+                                                           DenseIndex row_strides, DenseIndex col_strides,
+                                                           DenseIndex in_row_strides, DenseIndex in_col_strides,
+                                                           DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
+                                                           PaddingType padding_type, Scalar padding_value)
+      : m_xpr(expr), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
+        m_row_strides(row_strides), m_col_strides(col_strides),
+        m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
+        m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
+        m_padding_explicit(false), m_padding_top(0), m_padding_bottom(0), m_padding_left(0), m_padding_right(0),
+        m_padding_type(padding_type), m_padding_value(padding_value) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorImagePatchOp(const XprType& expr, DenseIndex patch_rows, DenseIndex patch_cols,
+                                                           DenseIndex row_strides, DenseIndex col_strides,
+                                                           DenseIndex in_row_strides, DenseIndex in_col_strides,
+                                                           DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
+                                                           DenseIndex padding_top, DenseIndex padding_bottom,
+                                                           DenseIndex padding_left, DenseIndex padding_right,
+                                                           Scalar padding_value)
+      : m_xpr(expr), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
+        m_row_strides(row_strides), m_col_strides(col_strides),
+        m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
+        m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
+        m_padding_explicit(true), m_padding_top(padding_top), m_padding_bottom(padding_bottom),
+        m_padding_left(padding_left), m_padding_right(padding_right),
+        m_padding_type(PADDING_VALID), m_padding_value(padding_value) {}
+
+    EIGEN_DEVICE_FUNC
+    DenseIndex patch_rows() const { return m_patch_rows; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex patch_cols() const { return m_patch_cols; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex row_strides() const { return m_row_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex col_strides() const { return m_col_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex in_row_strides() const { return m_in_row_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex in_col_strides() const { return m_in_col_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex row_inflate_strides() const { return m_row_inflate_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex col_inflate_strides() const { return m_col_inflate_strides; }
+    EIGEN_DEVICE_FUNC
+    bool padding_explicit() const { return m_padding_explicit; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_top() const { return m_padding_top; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_bottom() const { return m_padding_bottom; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_left() const { return m_padding_left; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_right() const { return m_padding_right; }
+    EIGEN_DEVICE_FUNC
+    PaddingType padding_type() const { return m_padding_type; }
+    EIGEN_DEVICE_FUNC
+    Scalar padding_value() const { return m_padding_value; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const DenseIndex m_patch_rows;
+    const DenseIndex m_patch_cols;
+    const DenseIndex m_row_strides;
+    const DenseIndex m_col_strides;
+    const DenseIndex m_in_row_strides;
+    const DenseIndex m_in_col_strides;
+    const DenseIndex m_row_inflate_strides;
+    const DenseIndex m_col_inflate_strides;
+    const bool m_padding_explicit;
+    const DenseIndex m_padding_top;
+    const DenseIndex m_padding_bottom;
+    const DenseIndex m_padding_left;
+    const DenseIndex m_padding_right;
+    const PaddingType m_padding_type;
+    const Scalar m_padding_value;
+};
+
+// Eval as rvalue
+template<DenseIndex Rows, DenseIndex Cols, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
+{
+  typedef TensorImagePatchOp<Rows, Cols, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumInputDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  static const int NumDims = NumInputDims + 1;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>,
+                          Device> Self;
+  typedef TensorEvaluator<ArgType, Device> Impl;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device)
+  {
+    EIGEN_STATIC_ASSERT((NumDims >= 4), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    m_paddingValue = op.padding_value();
+
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+
+    // Caches a few variables.
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_inputDepth = input_dims[0];
+      m_inputRows = input_dims[1];
+      m_inputCols = input_dims[2];
+    } else {
+      m_inputDepth = input_dims[NumInputDims-1];
+      m_inputRows = input_dims[NumInputDims-2];
+      m_inputCols = input_dims[NumInputDims-3];
+    }
+
+    m_row_strides = op.row_strides();
+    m_col_strides = op.col_strides();
+
+    // Input strides and effective input/patch size
+    m_in_row_strides = op.in_row_strides();
+    m_in_col_strides = op.in_col_strides();
+    m_row_inflate_strides = op.row_inflate_strides();
+    m_col_inflate_strides = op.col_inflate_strides();
+    // The "effective" input rows and input cols are the input rows and cols
+    // after inflating them with zeros.
+    // For examples, a 2x3 matrix with row_inflate_strides and
+    // col_inflate_strides of 2 comes from:
+    //   A B C
+    //   D E F
+    //
+    // to a matrix is 3 x 5:
+    //
+    //   A . B . C
+    //   . . . . .
+    //   D . E . F
+
+    m_input_rows_eff = (m_inputRows - 1) * m_row_inflate_strides + 1;
+    m_input_cols_eff = (m_inputCols - 1) * m_col_inflate_strides + 1;
+    m_patch_rows_eff = op.patch_rows() + (op.patch_rows() - 1) * (m_in_row_strides - 1);
+    m_patch_cols_eff = op.patch_cols() + (op.patch_cols() - 1) * (m_in_col_strides - 1);
+
+    if (op.padding_explicit()) {
+      m_outputRows = numext::ceil((m_input_rows_eff + op.padding_top() + op.padding_bottom() - m_patch_rows_eff + 1.f) / static_cast<float>(m_row_strides));
+      m_outputCols = numext::ceil((m_input_cols_eff + op.padding_left() + op.padding_right() - m_patch_cols_eff + 1.f) / static_cast<float>(m_col_strides));
+      m_rowPaddingTop = op.padding_top();
+      m_colPaddingLeft = op.padding_left();
+    } else {
+      // Computing padding from the type
+      switch (op.padding_type()) {
+        case PADDING_VALID:
+          m_outputRows = numext::ceil((m_input_rows_eff - m_patch_rows_eff + 1.f) / static_cast<float>(m_row_strides));
+          m_outputCols = numext::ceil((m_input_cols_eff - m_patch_cols_eff + 1.f) / static_cast<float>(m_col_strides));
+          // Calculate the padding
+          m_rowPaddingTop = numext::maxi<Index>(0, ((m_outputRows - 1) * m_row_strides + m_patch_rows_eff - m_input_rows_eff) / 2);
+          m_colPaddingLeft = numext::maxi<Index>(0, ((m_outputCols - 1) * m_col_strides + m_patch_cols_eff - m_input_cols_eff) / 2);
+          break;
+        case PADDING_SAME:
+          m_outputRows = numext::ceil(m_input_rows_eff / static_cast<float>(m_row_strides));
+          m_outputCols = numext::ceil(m_input_cols_eff / static_cast<float>(m_col_strides));
+          // Calculate the padding
+          m_rowPaddingTop = ((m_outputRows - 1) * m_row_strides + m_patch_rows_eff - m_input_rows_eff) / 2;
+          m_colPaddingLeft = ((m_outputCols - 1) * m_col_strides + m_patch_cols_eff - m_input_cols_eff) / 2;
+          break;
+        default:
+          eigen_assert(false && "unexpected padding");
+      }
+    }
+    eigen_assert(m_outputRows > 0);
+    eigen_assert(m_outputCols > 0);
+
+    // Dimensions for result of extraction.
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      // ColMajor
+      // 0: depth
+      // 1: patch_rows
+      // 2: patch_cols
+      // 3: number of patches
+      // 4 and beyond: anything else (such as batch).
+      m_dimensions[0] = input_dims[0];
+      m_dimensions[1] = op.patch_rows();
+      m_dimensions[2] = op.patch_cols();
+      m_dimensions[3] = m_outputRows * m_outputCols;
+      for (int i = 4; i < NumDims; ++i) {
+        m_dimensions[i] = input_dims[i-1];
+      }
+    } else {
+      // RowMajor
+      // NumDims-1: depth
+      // NumDims-2: patch_rows
+      // NumDims-3: patch_cols
+      // NumDims-4: number of patches
+      // NumDims-5 and beyond: anything else (such as batch).
+      m_dimensions[NumDims-1] = input_dims[NumInputDims-1];
+      m_dimensions[NumDims-2] = op.patch_rows();
+      m_dimensions[NumDims-3] = op.patch_cols();
+      m_dimensions[NumDims-4] = m_outputRows * m_outputCols;
+      for (int i = NumDims-5; i >= 0; --i) {
+        m_dimensions[i] = input_dims[i];
+      }
+    }
+
+    // Strides for moving the patch in various dimensions.
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_colStride = m_dimensions[1];
+      m_patchStride = m_colStride * m_dimensions[2] * m_dimensions[0];
+      m_otherStride = m_patchStride * m_dimensions[3];
+    } else {
+      m_colStride = m_dimensions[NumDims-2];
+      m_patchStride = m_colStride * m_dimensions[NumDims-3] * m_dimensions[NumDims-1];
+      m_otherStride = m_patchStride * m_dimensions[NumDims-4];
+    }
+
+    // Strides for navigating through the input tensor.
+    m_rowInputStride = m_inputDepth;
+    m_colInputStride = m_inputDepth * m_inputRows;
+    m_patchInputStride = m_inputDepth * m_inputRows * m_inputCols;
+
+    // Fast representations of different variables.
+    m_fastOtherStride = internal::TensorIntDivisor<Index>(m_otherStride);
+    m_fastPatchStride = internal::TensorIntDivisor<Index>(m_patchStride);
+    m_fastColStride = internal::TensorIntDivisor<Index>(m_colStride);
+    m_fastInflateRowStride = internal::TensorIntDivisor<Index>(m_row_inflate_strides);
+    m_fastInflateColStride = internal::TensorIntDivisor<Index>(m_col_inflate_strides);
+    m_fastInputColsEff = internal::TensorIntDivisor<Index>(m_input_cols_eff);
+
+    // Number of patches in the width dimension.
+    m_fastOutputRows = internal::TensorIntDivisor<Index>(m_outputRows);
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[0]);
+    } else {
+      m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[NumDims-1]);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    // Patch index corresponding to the passed in index.
+    const Index patchIndex = index / m_fastPatchStride;
+    // Find the offset of the element wrt the location of the first element.
+    const Index patchOffset = (index - patchIndex * m_patchStride) / m_fastOutputDepth;
+
+    // Other ways to index this element.
+    const Index otherIndex = (NumDims == 4) ? 0 : index / m_fastOtherStride;
+    const Index patch2DIndex = (NumDims == 4) ? patchIndex : (index - otherIndex * m_otherStride) / m_fastPatchStride;
+
+    // Calculate col index in the input original tensor.
+    const Index colIndex = patch2DIndex / m_fastOutputRows;
+    const Index colOffset = patchOffset / m_fastColStride;
+    const Index inputCol = colIndex * m_col_strides + colOffset * m_in_col_strides - m_colPaddingLeft;
+    const Index origInputCol = (m_col_inflate_strides == 1) ? inputCol : ((inputCol >= 0) ? (inputCol / m_fastInflateColStride) : 0);
+    if (inputCol < 0 || inputCol >= m_input_cols_eff ||
+        ((m_col_inflate_strides != 1) && (inputCol != origInputCol * m_col_inflate_strides))) {
+      return Scalar(m_paddingValue);
+    }
+
+    // Calculate row index in the original input tensor.
+    const Index rowIndex = patch2DIndex - colIndex * m_outputRows;
+    const Index rowOffset = patchOffset - colOffset * m_colStride;
+    const Index inputRow = rowIndex * m_row_strides + rowOffset * m_in_row_strides - m_rowPaddingTop;
+    const Index origInputRow = (m_row_inflate_strides == 1) ? inputRow : ((inputRow >= 0) ? (inputRow / m_fastInflateRowStride) : 0);
+    if (inputRow < 0 || inputRow >= m_input_rows_eff ||
+        ((m_row_inflate_strides != 1) && (inputRow != origInputRow * m_row_inflate_strides))) {
+      return Scalar(m_paddingValue);
+    }
+
+    const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
+    const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index];
+
+    const Index inputIndex = depth + origInputRow * m_rowInputStride + origInputCol * m_colInputStride + otherIndex * m_patchInputStride;
+    return m_impl.coeff(inputIndex);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    if (m_in_row_strides != 1 || m_in_col_strides != 1 || m_row_inflate_strides != 1 || m_col_inflate_strides != 1) {
+      return packetWithPossibleZero(index);
+    }
+
+    const Index indices[2] = {index, index + PacketSize - 1};
+    const Index patchIndex = indices[0] / m_fastPatchStride;
+    if (patchIndex != indices[1] / m_fastPatchStride) {
+      return packetWithPossibleZero(index);
+    }
+    const Index otherIndex = (NumDims == 4) ? 0 : indices[0] / m_fastOtherStride;
+    eigen_assert(otherIndex == indices[1] / m_fastOtherStride);
+
+    // Find the offset of the element wrt the location of the first element.
+    const Index patchOffsets[2] = {(indices[0] - patchIndex * m_patchStride) / m_fastOutputDepth,
+                                   (indices[1] - patchIndex * m_patchStride) / m_fastOutputDepth};
+
+    const Index patch2DIndex = (NumDims == 4) ? patchIndex : (indices[0] - otherIndex * m_otherStride) / m_fastPatchStride;
+    eigen_assert(patch2DIndex == (indices[1] - otherIndex * m_otherStride) / m_fastPatchStride);
+
+    const Index colIndex = patch2DIndex / m_fastOutputRows;
+    const Index colOffsets[2] = {patchOffsets[0] / m_fastColStride, patchOffsets[1] / m_fastColStride};
+
+    // Calculate col indices in the original input tensor.
+    const Index inputCols[2] = {colIndex * m_col_strides + colOffsets[0] -
+      m_colPaddingLeft, colIndex * m_col_strides + colOffsets[1] - m_colPaddingLeft};
+    if (inputCols[1] < 0 || inputCols[0] >= m_inputCols) {
+      return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
+    }
+
+    if (inputCols[0] == inputCols[1]) {
+      const Index rowIndex = patch2DIndex - colIndex * m_outputRows;
+      const Index rowOffsets[2] = {patchOffsets[0] - colOffsets[0]*m_colStride, patchOffsets[1] - colOffsets[1]*m_colStride};
+      eigen_assert(rowOffsets[0] <= rowOffsets[1]);
+      // Calculate col indices in the original input tensor.
+      const Index inputRows[2] = {rowIndex * m_row_strides + rowOffsets[0] -
+        m_rowPaddingTop, rowIndex * m_row_strides + rowOffsets[1] - m_rowPaddingTop};
+
+      if (inputRows[1] < 0 || inputRows[0] >= m_inputRows) {
+        return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
+      }
+
+      if (inputRows[0] >= 0 && inputRows[1] < m_inputRows) {
+        // no padding
+        const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
+        const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index];
+        const Index inputIndex = depth + inputRows[0] * m_rowInputStride + inputCols[0] * m_colInputStride + otherIndex * m_patchInputStride;
+        return m_impl.template packet<Unaligned>(inputIndex);
+      }
+    }
+
+    return packetWithPossibleZero(index);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+  const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+
+  Index rowPaddingTop() const { return m_rowPaddingTop; }
+  Index colPaddingLeft() const { return m_colPaddingLeft; }
+  Index outputRows() const { return m_outputRows; }
+  Index outputCols() const { return m_outputCols; }
+  Index userRowStride() const { return m_row_strides; }
+  Index userColStride() const { return m_col_strides; }
+  Index userInRowStride() const { return m_in_row_strides; }
+  Index userInColStride() const { return m_in_col_strides; }
+  Index rowInflateStride() const { return m_row_inflate_strides; }
+  Index colInflateStride() const { return m_col_inflate_strides; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    // We conservatively estimate the cost for the code path where the computed
+    // index is inside the original image and
+    // TensorEvaluator<ArgType, Device>::CoordAccess is false.
+    const double compute_cost = 3 * TensorOpCost::DivCost<Index>() +
+                                6 * TensorOpCost::MulCost<Index>() +
+                                8 * TensorOpCost::MulCost<Index>();
+    return m_impl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
+  }
+
+ protected:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
+  {
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+    for (int i = 0; i < PacketSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  Dimensions m_dimensions;
+
+  Index m_otherStride;
+  Index m_patchStride;
+  Index m_colStride;
+  Index m_row_strides;
+  Index m_col_strides;
+
+  Index m_in_row_strides;
+  Index m_in_col_strides;
+  Index m_row_inflate_strides;
+  Index m_col_inflate_strides;
+
+  Index m_input_rows_eff;
+  Index m_input_cols_eff;
+  Index m_patch_rows_eff;
+  Index m_patch_cols_eff;
+
+  internal::TensorIntDivisor<Index> m_fastOtherStride;
+  internal::TensorIntDivisor<Index> m_fastPatchStride;
+  internal::TensorIntDivisor<Index> m_fastColStride;
+  internal::TensorIntDivisor<Index> m_fastInflateRowStride;
+  internal::TensorIntDivisor<Index> m_fastInflateColStride;
+  internal::TensorIntDivisor<Index> m_fastInputColsEff;
+
+  Index m_rowInputStride;
+  Index m_colInputStride;
+  Index m_patchInputStride;
+
+  Index m_inputDepth;
+  Index m_inputRows;
+  Index m_inputCols;
+
+  Index m_outputRows;
+  Index m_outputCols;
+
+  Index m_rowPaddingTop;
+  Index m_colPaddingLeft;
+
+  internal::TensorIntDivisor<Index> m_fastOutputRows;
+  internal::TensorIntDivisor<Index> m_fastOutputDepth;
+
+  Scalar m_paddingValue;
+
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_IMAGE_PATCH_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h
@@ -0,0 +1,725 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_INDEX_LIST_H
+#define EIGEN_CXX11_TENSOR_TENSOR_INDEX_LIST_H
+
+
+#if EIGEN_HAS_CONSTEXPR && EIGEN_HAS_VARIADIC_TEMPLATES
+
+#define EIGEN_HAS_INDEX_LIST
+
+namespace Eigen {
+
+/** \internal
+  *
+  * \class TensorIndexList
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Set of classes used to encode a set of Tensor dimensions/indices.
+  *
+  * The indices in the list can be known at compile time or at runtime. A mix
+  * of static and dynamic indices can also be provided if needed. The tensor
+  * code will attempt to take advantage of the indices that are known at
+  * compile time to optimize the code it generates.
+  *
+  * This functionality requires a c++11 compliant compiler. If your compiler
+  * is older you need to use arrays of indices instead.
+  *
+  * Several examples are provided in the cxx11_tensor_index_list.cpp file.
+  *
+  * \sa Tensor
+  */
+
+template <DenseIndex n>
+struct type2index {
+  static const DenseIndex value = n;
+  EIGEN_DEVICE_FUNC constexpr operator DenseIndex() const { return n; }
+  EIGEN_DEVICE_FUNC void set(DenseIndex val) {
+    eigen_assert(val == n);
+  }
+};
+
+// This can be used with IndexPairList to get compile-time constant pairs,
+// such as IndexPairList<type2indexpair<1,2>, type2indexpair<3,4>>().
+template <DenseIndex f, DenseIndex s>
+struct type2indexpair {
+  static const DenseIndex first = f;
+  static const DenseIndex second = s;
+
+  constexpr EIGEN_DEVICE_FUNC operator IndexPair<DenseIndex>() const {
+    return IndexPair<DenseIndex>(f, s);
+  }
+
+  EIGEN_DEVICE_FUNC void set(const IndexPair<DenseIndex>& val) {
+    eigen_assert(val.first == f);
+    eigen_assert(val.second == s);
+  }
+};
+
+
+template<DenseIndex n> struct NumTraits<type2index<n> >
+{
+  typedef DenseIndex Real;
+  enum {
+    IsComplex = 0,
+    RequireInitialization = false,
+    ReadCost = 1,
+    AddCost = 1,
+    MulCost = 1
+  };
+
+  EIGEN_DEVICE_FUNC static inline Real epsilon() { return 0; }
+  EIGEN_DEVICE_FUNC static inline Real dummy_precision() { return 0; }
+  EIGEN_DEVICE_FUNC static inline Real highest() { return n; }
+  EIGEN_DEVICE_FUNC static inline Real lowest() { return n; }
+};
+
+namespace internal {
+template <typename T>
+EIGEN_DEVICE_FUNC void update_value(T& val, DenseIndex new_val) {
+  val = new_val;
+}
+template <DenseIndex n>
+EIGEN_DEVICE_FUNC void update_value(type2index<n>& val, DenseIndex new_val) {
+  val.set(new_val);
+}
+
+template <typename T>
+EIGEN_DEVICE_FUNC void update_value(T& val, IndexPair<DenseIndex> new_val) {
+  val = new_val;
+}
+template <DenseIndex f, DenseIndex s>
+EIGEN_DEVICE_FUNC void update_value(type2indexpair<f, s>& val, IndexPair<DenseIndex> new_val) {
+  val.set(new_val);
+}
+
+
+template <typename T>
+struct is_compile_time_constant {
+  static constexpr bool value = false;
+};
+
+template <DenseIndex idx>
+struct is_compile_time_constant<type2index<idx> > {
+  static constexpr bool value = true;
+};
+template <DenseIndex idx>
+struct is_compile_time_constant<const type2index<idx> > {
+  static constexpr bool value = true;
+};
+template <DenseIndex idx>
+struct is_compile_time_constant<type2index<idx>& > {
+  static constexpr bool value = true;
+};
+template <DenseIndex idx>
+struct is_compile_time_constant<const type2index<idx>& > {
+  static constexpr bool value = true;
+};
+
+template <DenseIndex f, DenseIndex s>
+struct is_compile_time_constant<type2indexpair<f, s> > {
+  static constexpr bool value = true;
+};
+template <DenseIndex f, DenseIndex s>
+struct is_compile_time_constant<const type2indexpair<f, s> > {
+  static constexpr bool value = true;
+};
+template <DenseIndex f, DenseIndex s>
+struct is_compile_time_constant<type2indexpair<f, s>& > {
+  static constexpr bool value = true;
+};
+template <DenseIndex f, DenseIndex s>
+struct is_compile_time_constant<const type2indexpair<f, s>& > {
+  static constexpr bool value = true;
+};
+
+
+template<typename... T>
+struct IndexTuple;
+
+template<typename T, typename... O>
+struct IndexTuple<T, O...> {
+  EIGEN_DEVICE_FUNC constexpr IndexTuple() : head(), others() { }
+  EIGEN_DEVICE_FUNC constexpr IndexTuple(const T& v, const O... o) : head(v), others(o...) { }
+
+  constexpr static int count = 1 + sizeof...(O);
+  T head;
+  IndexTuple<O...> others;
+  typedef T Head;
+  typedef IndexTuple<O...> Other;
+};
+
+template<typename T>
+  struct IndexTuple<T> {
+  EIGEN_DEVICE_FUNC constexpr IndexTuple() : head() { }
+  EIGEN_DEVICE_FUNC constexpr IndexTuple(const T& v) : head(v) { }
+
+  constexpr static int count = 1;
+  T head;
+  typedef T Head;
+};
+
+
+template<int N, typename... T>
+struct IndexTupleExtractor;
+
+template<int N, typename T, typename... O>
+struct IndexTupleExtractor<N, T, O...> {
+
+  typedef typename IndexTupleExtractor<N-1, O...>::ValType ValType;
+
+  EIGEN_DEVICE_FUNC static constexpr ValType& get_val(IndexTuple<T, O...>& val) {
+    return IndexTupleExtractor<N-1, O...>::get_val(val.others);
+  }
+
+  EIGEN_DEVICE_FUNC static constexpr const ValType& get_val(const IndexTuple<T, O...>& val) {
+    return IndexTupleExtractor<N-1, O...>::get_val(val.others);
+  }
+  template <typename V>
+  EIGEN_DEVICE_FUNC static void set_val(IndexTuple<T, O...>& val, V& new_val) {
+    IndexTupleExtractor<N-1, O...>::set_val(val.others, new_val);
+  }
+
+};
+
+template<typename T, typename... O>
+  struct IndexTupleExtractor<0, T, O...> {
+
+  typedef T ValType;
+
+  EIGEN_DEVICE_FUNC static constexpr ValType& get_val(IndexTuple<T, O...>& val) {
+    return val.head;
+  }
+  EIGEN_DEVICE_FUNC static constexpr const ValType& get_val(const IndexTuple<T, O...>& val) {
+    return val.head;
+  }
+  template <typename V>
+  EIGEN_DEVICE_FUNC static void set_val(IndexTuple<T, O...>& val, V& new_val) {
+    val.head = new_val;
+  }
+};
+
+
+
+template <int N, typename T, typename... O>
+EIGEN_DEVICE_FUNC constexpr typename IndexTupleExtractor<N, T, O...>::ValType& array_get(IndexTuple<T, O...>& tuple) {
+  return IndexTupleExtractor<N, T, O...>::get_val(tuple);
+}
+template <int N, typename T, typename... O>
+EIGEN_DEVICE_FUNC constexpr const typename IndexTupleExtractor<N, T, O...>::ValType& array_get(const IndexTuple<T, O...>& tuple) {
+  return IndexTupleExtractor<N, T, O...>::get_val(tuple);
+}
+template <typename T, typename... O>
+  struct array_size<IndexTuple<T, O...> > {
+  static const size_t value = IndexTuple<T, O...>::count;
+};
+template <typename T, typename... O>
+  struct array_size<const IndexTuple<T, O...> > {
+  static const size_t value = IndexTuple<T, O...>::count;
+};
+
+
+
+
+template <DenseIndex Idx, typename ValueT>
+struct tuple_coeff {
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static constexpr ValueT get(const DenseIndex i, const IndexTuple<T...>& t) {
+    //    return array_get<Idx>(t) * (i == Idx) + tuple_coeff<Idx-1>::get(i, t) * (i != Idx);
+    return (i == Idx ? array_get<Idx>(t) : tuple_coeff<Idx-1, ValueT>::get(i, t));
+  }
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static void set(const DenseIndex i, IndexTuple<T...>& t, const ValueT& value) {
+    if (i == Idx) {
+      update_value(array_get<Idx>(t), value);
+    } else {
+      tuple_coeff<Idx-1, ValueT>::set(i, t, value);
+    }
+  }
+
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static constexpr bool value_known_statically(const DenseIndex i, const IndexTuple<T...>& t) {
+    return ((i == Idx) & is_compile_time_constant<typename IndexTupleExtractor<Idx, T...>::ValType>::value) ||
+        tuple_coeff<Idx-1, ValueT>::value_known_statically(i, t);
+  }
+
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static constexpr bool values_up_to_known_statically(const IndexTuple<T...>& t) {
+    return is_compile_time_constant<typename IndexTupleExtractor<Idx, T...>::ValType>::value &&
+        tuple_coeff<Idx-1, ValueT>::values_up_to_known_statically(t);
+  }
+
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static constexpr bool values_up_to_statically_known_to_increase(const IndexTuple<T...>& t) {
+    return is_compile_time_constant<typename IndexTupleExtractor<Idx, T...>::ValType>::value &&
+           is_compile_time_constant<typename IndexTupleExtractor<Idx, T...>::ValType>::value &&
+           array_get<Idx>(t) > array_get<Idx-1>(t) &&
+           tuple_coeff<Idx-1, ValueT>::values_up_to_statically_known_to_increase(t);
+  }
+};
+
+template <typename ValueT>
+struct tuple_coeff<0, ValueT> {
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static constexpr ValueT get(const DenseIndex /*i*/, const IndexTuple<T...>& t) {
+    //  eigen_assert (i == 0);  // gcc fails to compile assertions in constexpr
+    return array_get<0>(t)/* * (i == 0)*/;
+  }
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static void set(const DenseIndex i, IndexTuple<T...>& t, const ValueT value) {
+    eigen_assert (i == 0);
+    update_value(array_get<0>(t), value);
+  }
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static constexpr bool value_known_statically(const DenseIndex i, const IndexTuple<T...>&) {
+    return is_compile_time_constant<typename IndexTupleExtractor<0, T...>::ValType>::value & (i == 0);
+  }
+
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static constexpr bool values_up_to_known_statically(const IndexTuple<T...>&) {
+    return is_compile_time_constant<typename IndexTupleExtractor<0, T...>::ValType>::value;
+  }
+
+  template <typename... T>
+  EIGEN_DEVICE_FUNC static constexpr bool values_up_to_statically_known_to_increase(const IndexTuple<T...>&) {
+    return true;
+  }
+};
+}  // namespace internal
+
+
+
+template<typename FirstType, typename... OtherTypes>
+struct IndexList : internal::IndexTuple<FirstType, OtherTypes...> {
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC constexpr DenseIndex operator[] (const DenseIndex i) const {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...> >::value-1, DenseIndex>::get(i, *this);
+  }
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC constexpr DenseIndex get(const DenseIndex i) const {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...> >::value-1, DenseIndex>::get(i, *this);
+  }
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC void set(const DenseIndex i, const DenseIndex value) {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...> >::value-1, DenseIndex>::set(i, *this, value);
+  }
+
+  EIGEN_DEVICE_FUNC constexpr IndexList(const internal::IndexTuple<FirstType, OtherTypes...>& other) : internal::IndexTuple<FirstType, OtherTypes...>(other) { }
+  EIGEN_DEVICE_FUNC constexpr IndexList(FirstType& first, OtherTypes... other) : internal::IndexTuple<FirstType, OtherTypes...>(first, other...) { }
+  EIGEN_DEVICE_FUNC constexpr IndexList() : internal::IndexTuple<FirstType, OtherTypes...>() { }
+
+  EIGEN_DEVICE_FUNC constexpr bool value_known_statically(const DenseIndex i) const {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...> >::value-1, DenseIndex>::value_known_statically(i, *this);
+  }
+  EIGEN_DEVICE_FUNC constexpr bool all_values_known_statically() const {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...> >::value-1, DenseIndex>::values_up_to_known_statically(*this);
+  }
+
+  EIGEN_DEVICE_FUNC constexpr bool values_statically_known_to_increase() const {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...> >::value-1, DenseIndex>::values_up_to_statically_known_to_increase(*this);
+  }
+};
+
+
+template<typename FirstType, typename... OtherTypes>
+constexpr IndexList<FirstType, OtherTypes...> make_index_list(FirstType val1, OtherTypes... other_vals) {
+  return IndexList<FirstType, OtherTypes...>(val1, other_vals...);
+}
+
+
+template<typename FirstType, typename... OtherTypes>
+struct IndexPairList : internal::IndexTuple<FirstType, OtherTypes...> {
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC constexpr IndexPair<DenseIndex> operator[] (const DenseIndex i) const {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...> >::value-1, IndexPair<DenseIndex>>::get(i, *this);
+  }
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC void set(const DenseIndex i, const IndexPair<DenseIndex> value) {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...>>::value-1, IndexPair<DenseIndex> >::set(i, *this, value);
+  }
+
+  EIGEN_DEVICE_FUNC  constexpr IndexPairList(const internal::IndexTuple<FirstType, OtherTypes...>& other) : internal::IndexTuple<FirstType, OtherTypes...>(other) { }
+  EIGEN_DEVICE_FUNC  constexpr IndexPairList() : internal::IndexTuple<FirstType, OtherTypes...>() { }
+
+  EIGEN_DEVICE_FUNC constexpr bool value_known_statically(const DenseIndex i) const {
+    return internal::tuple_coeff<internal::array_size<internal::IndexTuple<FirstType, OtherTypes...> >::value-1, DenseIndex>::value_known_statically(i, *this);
+  }
+};
+
+namespace internal {
+
+template<typename FirstType, typename... OtherTypes> size_t array_prod(const IndexList<FirstType, OtherTypes...>& sizes) {
+  size_t result = 1;
+  for (int i = 0; i < array_size<IndexList<FirstType, OtherTypes...> >::value; ++i) {
+    result *= sizes[i];
+  }
+  return result;
+}
+
+template<typename FirstType, typename... OtherTypes> struct array_size<IndexList<FirstType, OtherTypes...> > {
+  static const size_t value = array_size<IndexTuple<FirstType, OtherTypes...> >::value;
+};
+template<typename FirstType, typename... OtherTypes> struct array_size<const IndexList<FirstType, OtherTypes...> > {
+  static const size_t value = array_size<IndexTuple<FirstType, OtherTypes...> >::value;
+};
+
+template<typename FirstType, typename... OtherTypes> struct array_size<IndexPairList<FirstType, OtherTypes...> > {
+  static const size_t value = std::tuple_size<std::tuple<FirstType, OtherTypes...> >::value;
+};
+template<typename FirstType, typename... OtherTypes> struct array_size<const IndexPairList<FirstType, OtherTypes...> > {
+  static const size_t value = std::tuple_size<std::tuple<FirstType, OtherTypes...> >::value;
+};
+
+template<DenseIndex N, typename FirstType, typename... OtherTypes> EIGEN_DEVICE_FUNC constexpr DenseIndex array_get(IndexList<FirstType, OtherTypes...>& a) {
+  return IndexTupleExtractor<N, FirstType, OtherTypes...>::get_val(a);
+}
+template<DenseIndex N, typename FirstType, typename... OtherTypes> EIGEN_DEVICE_FUNC constexpr DenseIndex array_get(const IndexList<FirstType, OtherTypes...>& a) {
+  return IndexTupleExtractor<N, FirstType, OtherTypes...>::get_val(a);
+}
+
+template <typename T>
+struct index_known_statically_impl {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex) {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_known_statically_impl<IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i);
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_known_statically_impl<const IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i);
+  }
+};
+
+
+template <typename T>
+struct all_indices_known_statically_impl {
+  static constexpr bool run() {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct all_indices_known_statically_impl<IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return IndexList<FirstType, OtherTypes...>().all_values_known_statically();
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct all_indices_known_statically_impl<const IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return IndexList<FirstType, OtherTypes...>().all_values_known_statically();
+  }
+};
+
+
+template <typename T>
+struct indices_statically_known_to_increase_impl {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+  struct indices_statically_known_to_increase_impl<IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return Eigen::IndexList<FirstType, OtherTypes...>().values_statically_known_to_increase();
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+  struct indices_statically_known_to_increase_impl<const IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run() {
+    return Eigen::IndexList<FirstType, OtherTypes...>().values_statically_known_to_increase();
+  }
+};
+
+
+template <typename Tx>
+struct index_statically_eq_impl {
+  EIGEN_DEVICE_FUNC static constexpr bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_statically_eq_impl<IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexList<FirstType, OtherTypes...>().get(i) == value);
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_statically_eq_impl<const IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexList<FirstType, OtherTypes...>().get(i) == value);
+  }
+};
+
+
+template <typename T>
+struct index_statically_ne_impl {
+  EIGEN_DEVICE_FUNC static constexpr bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_statically_ne_impl<IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexList<FirstType, OtherTypes...>().get(i) != value);
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_statically_ne_impl<const IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexList<FirstType, OtherTypes...>().get(i) != value);
+  }
+};
+
+
+template <typename T>
+struct index_statically_gt_impl {
+  EIGEN_DEVICE_FUNC static constexpr bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_statically_gt_impl<IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexList<FirstType, OtherTypes...>().get(i) > value);
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_statically_gt_impl<const IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexList<FirstType, OtherTypes...>().get(i) > value);
+  }
+};
+
+
+
+template <typename T>
+struct index_statically_lt_impl {
+  EIGEN_DEVICE_FUNC static constexpr bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_statically_lt_impl<IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexList<FirstType, OtherTypes...>().get(i) < value);
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_statically_lt_impl<const IndexList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexList<FirstType, OtherTypes...>().get(i) < value);
+  }
+};
+
+
+
+template <typename Tx>
+struct index_pair_first_statically_eq_impl {
+  EIGEN_DEVICE_FUNC static constexpr bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_pair_first_statically_eq_impl<IndexPairList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexPairList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexPairList<FirstType, OtherTypes...>().operator[](i).first == value);
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_pair_first_statically_eq_impl<const IndexPairList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexPairList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexPairList<FirstType, OtherTypes...>().operator[](i).first == value);
+  }
+};
+
+
+
+template <typename Tx>
+struct index_pair_second_statically_eq_impl {
+  EIGEN_DEVICE_FUNC static constexpr bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_pair_second_statically_eq_impl<IndexPairList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexPairList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexPairList<FirstType, OtherTypes...>().operator[](i).second == value);
+  }
+};
+
+template <typename FirstType, typename... OtherTypes>
+struct index_pair_second_statically_eq_impl<const IndexPairList<FirstType, OtherTypes...> > {
+  EIGEN_DEVICE_FUNC static constexpr bool run(const DenseIndex i, const DenseIndex value) {
+    return IndexPairList<FirstType, OtherTypes...>().value_known_statically(i) &
+        (IndexPairList<FirstType, OtherTypes...>().operator[](i).second == value);
+  }
+};
+
+
+}  // end namespace internal
+}  // end namespace Eigen
+
+#else
+
+namespace Eigen {
+namespace internal {
+
+template <typename T>
+struct index_known_statically_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(const DenseIndex) {
+    return false;
+  }
+};
+
+template <typename T>
+struct all_indices_known_statically_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run() {
+    return false;
+  }
+};
+
+template <typename T>
+struct indices_statically_known_to_increase_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run() {
+    return false;
+  }
+};
+
+template <typename T>
+struct index_statically_eq_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename T>
+struct index_statically_ne_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename T>
+struct index_statically_gt_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename T>
+struct index_statically_lt_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename Tx>
+struct index_pair_first_statically_eq_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+template <typename Tx>
+struct index_pair_second_statically_eq_impl {
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool run(DenseIndex, DenseIndex) {
+    return false;
+  }
+};
+
+
+
+}  // end namespace internal
+}  // end namespace Eigen
+
+#endif
+
+
+namespace Eigen {
+namespace internal {
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool index_known_statically(DenseIndex i) {
+  return index_known_statically_impl<T>::run(i);
+}
+
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool all_indices_known_statically() {
+  return all_indices_known_statically_impl<T>::run();
+}
+
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool indices_statically_known_to_increase() {
+  return indices_statically_known_to_increase_impl<T>::run();
+}
+
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool index_statically_eq(DenseIndex i, DenseIndex value) {
+  return index_statically_eq_impl<T>::run(i, value);
+}
+
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool index_statically_ne(DenseIndex i, DenseIndex value) {
+  return index_statically_ne_impl<T>::run(i, value);
+}
+
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool index_statically_gt(DenseIndex i, DenseIndex value) {
+  return index_statically_gt_impl<T>::run(i, value);
+}
+
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool index_statically_lt(DenseIndex i, DenseIndex value) {
+  return index_statically_lt_impl<T>::run(i, value);
+}
+
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool index_pair_first_statically_eq(DenseIndex i, DenseIndex value) {
+  return index_pair_first_statically_eq_impl<T>::run(i, value);
+}
+
+template <typename T>
+static EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR bool index_pair_second_statically_eq(DenseIndex i, DenseIndex value) {
+  return index_pair_second_statically_eq_impl<T>::run(i, value);
+}
+
+}  // end namespace internal
+}  // end namespace Eigen
+
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_INDEX_LIST_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorInflation.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorInflation.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorInflation.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorInflation.h
@@ -0,0 +1,229 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Ke Yang <yangke@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_INFLATION_H
+#define EIGEN_CXX11_TENSOR_TENSOR_INFLATION_H
+
+namespace Eigen {
+
+/** \class TensorInflation
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor inflation class.
+  *
+  *
+  */
+namespace internal {
+template<typename Strides, typename XprType>
+struct traits<TensorInflationOp<Strides, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename Strides, typename XprType>
+struct eval<TensorInflationOp<Strides, XprType>, Eigen::Dense>
+{
+  typedef const TensorInflationOp<Strides, XprType>& type;
+};
+
+template<typename Strides, typename XprType>
+struct nested<TensorInflationOp<Strides, XprType>, 1, typename eval<TensorInflationOp<Strides, XprType> >::type>
+{
+  typedef TensorInflationOp<Strides, XprType> type;
+};
+
+}  // end namespace internal
+
+template<typename Strides, typename XprType>
+class TensorInflationOp : public TensorBase<TensorInflationOp<Strides, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorInflationOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorInflationOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorInflationOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorInflationOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorInflationOp(const XprType& expr, const Strides& strides)
+      : m_xpr(expr), m_strides(strides) {}
+
+    EIGEN_DEVICE_FUNC
+    const Strides& strides() const { return m_strides; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const Strides m_strides;
+};
+
+// Eval as rvalue
+template<typename Strides, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorInflationOp<Strides, ArgType>, Device>
+{
+  typedef TensorInflationOp<Strides, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/ false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_strides(op.strides())
+  {
+    m_dimensions = m_impl.dimensions();
+    // Expand each dimension to the inflated dimension.
+    for (int i = 0; i < NumDims; ++i) {
+      m_dimensions[i] = (m_dimensions[i] - 1) * op.strides()[i] + 1;
+    }
+
+    // Remember the strides for fast division.
+    for (int i = 0; i < NumDims; ++i) {
+      m_fastStrides[i] = internal::TensorIntDivisor<Index>(m_strides[i]);
+    }
+
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_outputStrides[0] = 1;
+      m_inputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
+        m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
+      }
+    } else {  // RowMajor
+      m_outputStrides[NumDims-1] = 1;
+      m_inputStrides[NumDims-1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_outputStrides[i] = m_outputStrides[i+1] * m_dimensions[i+1];
+        m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  // Computes the input index given the output index. Returns true if the output
+  // index doesn't fall into a hole.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool getInputIndex(Index index, Index* inputIndex) const
+  {
+    eigen_assert(index < dimensions().TotalSize());
+    *inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx = index / m_outputStrides[i];
+        if (idx != idx / m_fastStrides[i] * m_strides[i]) {
+          return false;
+        }
+        *inputIndex += idx / m_strides[i] * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      if (index != index / m_fastStrides[0] * m_strides[0]) {
+        return false;
+      }
+      *inputIndex += index / m_strides[0];
+      return true;
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx = index / m_outputStrides[i];
+        if (idx != idx / m_fastStrides[i] * m_strides[i]) {
+          return false;
+        }
+        *inputIndex += idx / m_strides[i] * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      if (index != index / m_fastStrides[NumDims-1] * m_strides[NumDims-1]) {
+        return false;
+      }
+      *inputIndex += index / m_strides[NumDims - 1];
+    }
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    Index inputIndex = 0;
+    if (getInputIndex(index, &inputIndex)) {
+     return m_impl.coeff(inputIndex);
+    } else {
+     return Scalar(0);
+    }
+  }
+
+  // TODO(yangke): optimize this function so that we can detect and produce
+  // all-zero packets
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+    for (int i = 0; i < PacketSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    const double compute_cost = NumDims * (3 * TensorOpCost::DivCost<Index>() +
+                                           3 * TensorOpCost::MulCost<Index>() +
+                                           2 * TensorOpCost::AddCost<Index>());
+    const double input_size = m_impl.dimensions().TotalSize();
+    const double output_size = m_dimensions.TotalSize();
+    if (output_size == 0)
+      return TensorOpCost();
+    return m_impl.costPerCoeff(vectorized) +
+           TensorOpCost(sizeof(CoeffReturnType) * input_size / output_size, 0,
+                        compute_cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ protected:
+  Dimensions m_dimensions;
+  array<Index, NumDims> m_outputStrides;
+  array<Index, NumDims> m_inputStrides;
+  TensorEvaluator<ArgType, Device> m_impl;
+  const Strides m_strides;
+  array<internal::TensorIntDivisor<Index>, NumDims> m_fastStrides;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_INFLATION_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorInitializer.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorInitializer.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorInitializer.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorInitializer.h
@@ -0,0 +1,82 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_INITIALIZER_H
+#define EIGEN_CXX11_TENSOR_TENSOR_INITIALIZER_H
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+
+#include <initializer_list>
+
+namespace Eigen {
+
+/** \class TensorInitializer
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Helper template to initialize Tensors from std::initializer_lists.
+  */
+namespace internal {
+
+template <typename Derived, int N>
+struct Initializer {
+  typedef std::initializer_list<
+    typename Initializer<Derived, N - 1>::InitList> InitList;
+
+  static void run(TensorEvaluator<Derived, DefaultDevice>& tensor,
+                  Eigen::array<typename traits<Derived>::Index, traits<Derived>::NumDimensions>* indices,
+                  const InitList& vals) {
+    int i = 0;
+    for (auto v : vals) {
+      (*indices)[traits<Derived>::NumDimensions - N] = i++;
+      Initializer<Derived, N - 1>::run(tensor, indices, v);
+    }
+  }
+};
+
+template <typename Derived>
+struct Initializer<Derived, 1> {
+  typedef std::initializer_list<typename traits<Derived>::Scalar> InitList;
+
+  static void run(TensorEvaluator<Derived, DefaultDevice>& tensor,
+                  Eigen::array<typename traits<Derived>::Index, traits<Derived>::NumDimensions>* indices,
+                  const InitList& vals) {
+    int i = 0;
+    // There is likely a faster way to do that than iterating.
+    for (auto v : vals) {
+      (*indices)[traits<Derived>::NumDimensions - 1] = i++;
+      tensor.coeffRef(*indices) = v;
+    }
+  }
+};
+
+template <typename Derived>
+struct Initializer<Derived, 0> {
+  typedef typename traits<Derived>::Scalar InitList;
+
+  static void run(TensorEvaluator<Derived, DefaultDevice>& tensor,
+                  Eigen::array<typename traits<Derived>::Index, traits<Derived>::NumDimensions>*,
+                  const InitList& v) {
+    tensor.coeffRef(0) = v;
+  }
+};
+
+
+template <typename Derived, int N>
+void initialize_tensor(TensorEvaluator<Derived, DefaultDevice>& tensor,
+                       const typename Initializer<Derived, traits<Derived>::NumDimensions>::InitList& vals) {
+  Eigen::array<typename traits<Derived>::Index, traits<Derived>::NumDimensions> indices;
+  Initializer<Derived, traits<Derived>::NumDimensions>::run(tensor, &indices, vals);
+}
+
+}  // namespace internal
+}  // namespace Eigen
+
+#endif  // EIGEN_HAS_VARIADIC_TEMPLATES
+
+#endif  // EIGEN_CXX11_TENSOR_TENSOR_INITIALIZER_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIntDiv.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIntDiv.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIntDiv.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorIntDiv.h
@@ -0,0 +1,253 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_INTDIV_H
+#define EIGEN_CXX11_TENSOR_TENSOR_INTDIV_H
+
+
+namespace Eigen {
+
+/** \internal
+  *
+  * \class TensorIntDiv
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Fast integer division by a constant.
+  *
+  * See the paper from Granlund and Montgomery for explanation.
+  *   (at http://dx.doi.org/10.1145/773473.178249)
+  *
+  * \sa Tensor
+  */
+
+namespace internal {
+
+namespace {
+
+  // Note: result is undefined if val == 0
+  template <typename T>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+  typename internal::enable_if<sizeof(T)==4,int>::type count_leading_zeros(const T val)
+  {
+#ifdef __CUDA_ARCH__
+    return __clz(val);
+#elif EIGEN_COMP_MSVC
+    unsigned long index;
+    _BitScanReverse(&index, val);
+    return 31 - index;
+#else
+    EIGEN_STATIC_ASSERT(sizeof(unsigned long long) == 8, YOU_MADE_A_PROGRAMMING_MISTAKE);
+    return __builtin_clz(static_cast<uint32_t>(val));
+#endif
+  }
+
+  template <typename T>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+  typename internal::enable_if<sizeof(T)==8,int>::type count_leading_zeros(const T val)
+  {
+#ifdef __CUDA_ARCH__
+    return __clzll(val);
+#elif EIGEN_COMP_MSVC && EIGEN_ARCH_x86_64
+    unsigned long index;
+    _BitScanReverse64(&index, val);
+    return 63 - index;
+#elif EIGEN_COMP_MSVC
+    // MSVC's _BitScanReverse64 is not available for 32bits builds.
+    unsigned int lo = (unsigned int)(val&0xffffffff);
+    unsigned int hi = (unsigned int)((val>>32)&0xffffffff);
+    int n;
+    if(hi==0)
+      n = 32 + count_leading_zeros<unsigned int>(lo);
+    else
+      n = count_leading_zeros<unsigned int>(hi);
+    return n;
+#else
+    EIGEN_STATIC_ASSERT(sizeof(unsigned long long) == 8, YOU_MADE_A_PROGRAMMING_MISTAKE);
+    return __builtin_clzll(static_cast<uint64_t>(val));
+#endif
+  }
+
+  template <typename T>
+  struct UnsignedTraits {
+    typedef typename conditional<sizeof(T) == 8, uint64_t, uint32_t>::type type;
+  };
+
+  template <typename T>
+  struct DividerTraits {
+    typedef typename UnsignedTraits<T>::type type;
+    static const int N = sizeof(T) * 8;
+  };
+
+  template <typename T>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE uint32_t muluh(const uint32_t a, const T b) {
+#if defined(__CUDA_ARCH__)
+    return __umulhi(a, b);
+#else
+    return (static_cast<uint64_t>(a) * b) >> 32;
+#endif
+  }
+
+  template <typename T>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE uint64_t muluh(const uint64_t a, const T b) {
+#if defined(__CUDA_ARCH__)
+    return __umul64hi(a, b);
+#elif defined(__SIZEOF_INT128__)
+    __uint128_t v = static_cast<__uint128_t>(a) * static_cast<__uint128_t>(b);
+    return static_cast<uint64_t>(v >> 64);
+#else
+    return (TensorUInt128<static_val<0>, uint64_t>(a) * TensorUInt128<static_val<0>, uint64_t>(b)).upper();
+#endif
+  }
+
+  template <int N, typename T>
+  struct DividerHelper {
+    static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE uint32_t computeMultiplier(const int log_div, const T divider) {
+      EIGEN_STATIC_ASSERT(N == 32, YOU_MADE_A_PROGRAMMING_MISTAKE);
+      return static_cast<uint32_t>((static_cast<uint64_t>(1) << (N+log_div)) / divider - (static_cast<uint64_t>(1) << N) + 1);
+    }
+  };
+
+  template <typename T>
+  struct DividerHelper<64, T> {
+    static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE uint64_t computeMultiplier(const int log_div, const T divider) {
+#if defined(__SIZEOF_INT128__) && !defined(__CUDA_ARCH__)
+      return static_cast<uint64_t>((static_cast<__uint128_t>(1) << (64+log_div)) / static_cast<__uint128_t>(divider) - (static_cast<__uint128_t>(1) << 64) + 1);
+#else
+      const uint64_t shift = 1ULL << log_div;
+      TensorUInt128<uint64_t, uint64_t> result = TensorUInt128<uint64_t, static_val<0> >(shift, 0) / TensorUInt128<static_val<0>, uint64_t>(divider)
+                                               - TensorUInt128<static_val<1>, static_val<0> >(1, 0)
+                                               + TensorUInt128<static_val<0>, static_val<1> >(1);
+      return static_cast<uint64_t>(result);
+#endif
+    }
+  };
+}
+
+
+template <typename T, bool div_gt_one = false>
+struct TensorIntDivisor {
+ public:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorIntDivisor() {
+    multiplier = 0;
+    shift1 = 0;
+    shift2 = 0;
+  }
+
+  // Must have 0 < divider < 2^31. This is relaxed to
+  // 0 < divider < 2^63 when using 64-bit indices on platforms that support
+  // the __uint128_t type.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorIntDivisor(const T divider) {
+    const int N = DividerTraits<T>::N;
+    eigen_assert(static_cast<typename UnsignedTraits<T>::type>(divider) < NumTraits<UnsignedType>::highest()/2);
+    eigen_assert(divider > 0);
+
+    // fast ln2
+    const int leading_zeros = count_leading_zeros(static_cast<UnsignedType>(divider));
+    int log_div = N - leading_zeros;
+    // if divider is a power of two then log_div is 1 more than it should be.
+    if ((static_cast<typename UnsignedTraits<T>::type>(1) << (log_div-1)) == static_cast<typename UnsignedTraits<T>::type>(divider))
+      log_div--;
+
+    multiplier = DividerHelper<N, T>::computeMultiplier(log_div, divider);
+    shift1 = log_div > 1 ? 1 : log_div;
+    shift2 = log_div > 1 ? log_div-1 : 0;
+  }
+
+  // Must have 0 <= numerator. On platforms that dont support the __uint128_t
+  // type numerator should also be less than 2^32-1.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T divide(const T numerator) const {
+    eigen_assert(static_cast<typename UnsignedTraits<T>::type>(numerator) < NumTraits<UnsignedType>::highest()/2);
+    //eigen_assert(numerator >= 0); // this is implicitly asserted by the line above
+
+    UnsignedType t1 = muluh(multiplier, numerator);
+    UnsignedType t = (static_cast<UnsignedType>(numerator) - t1) >> shift1;
+    return (t1 + t) >> shift2;
+  }
+
+ private:
+  typedef typename DividerTraits<T>::type UnsignedType;
+  UnsignedType multiplier;
+  int32_t shift1;
+  int32_t shift2;
+};
+
+
+// Optimized version for signed 32 bit integers.
+// Derived from Hacker's Delight.
+// Only works for divisors strictly greater than one
+template <>
+class TensorIntDivisor<int32_t, true> {
+ public:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorIntDivisor() {
+    magic = 0;
+    shift = 0;
+  }
+  // Must have 2 <= divider
+  EIGEN_DEVICE_FUNC TensorIntDivisor(int32_t divider)  {
+    eigen_assert(divider >= 2);
+    calcMagic(divider);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE int divide(const int32_t n) const {
+#ifdef __CUDA_ARCH__
+    return (__umulhi(magic, n) >> shift);
+#else
+    uint64_t v = static_cast<uint64_t>(magic) * static_cast<uint64_t>(n);
+    return (static_cast<uint32_t>(v >> 32) >> shift);
+#endif
+  }
+
+private:
+  // Compute the magic numbers. See Hacker's Delight section 10 for an in
+  // depth explanation.
+  EIGEN_DEVICE_FUNC void calcMagic(int32_t d) {
+   const unsigned two31 = 0x80000000;     // 2**31.
+   unsigned ad = d;
+   unsigned t = two31 + (ad >> 31);
+   unsigned anc = t - 1 - t%ad;     // Absolute value of nc.
+   int p = 31;                      // Init. p.
+   unsigned q1 = two31/anc;         // Init. q1 = 2**p/|nc|.
+   unsigned r1 = two31 - q1*anc;    // Init. r1 = rem(2**p, |nc|).
+   unsigned q2 = two31/ad;          // Init. q2 = 2**p/|d|.
+   unsigned r2 = two31 - q2*ad;     // Init. r2 = rem(2**p, |d|).
+   unsigned delta = 0;
+   do {
+      p = p + 1;
+      q1 = 2*q1;           // Update q1 = 2**p/|nc|.
+      r1 = 2*r1;           // Update r1 = rem(2**p, |nc|).
+      if (r1 >= anc) {     // (Must be an unsigned
+         q1 = q1 + 1;      // comparison here).
+         r1 = r1 - anc;}
+      q2 = 2*q2;           // Update q2 = 2**p/|d|.
+      r2 = 2*r2;           // Update r2 = rem(2**p, |d|).
+      if (r2 >= ad) {      // (Must be an unsigned
+         q2 = q2 + 1;      // comparison here).
+         r2 = r2 - ad;}
+      delta = ad - r2;
+   } while (q1 < delta || (q1 == delta && r1 == 0));
+
+   magic = (unsigned)(q2 + 1);
+   shift = p - 32;
+  }
+
+  uint32_t magic;
+  int32_t shift;
+};
+
+
+template <typename T, bool div_gt_one>
+static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T operator / (const T& numerator, const TensorIntDivisor<T, div_gt_one>& divisor) {
+  return divisor.divide(numerator);
+}
+
+
+} // end namespace internal
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_INTDIV_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorLayoutSwap.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorLayoutSwap.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorLayoutSwap.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorLayoutSwap.h
@@ -0,0 +1,209 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_LAYOUT_SWAP_H
+#define EIGEN_CXX11_TENSOR_TENSOR_LAYOUT_SWAP_H
+
+namespace Eigen {
+
+/** \class TensorLayoutSwap
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Swap the layout from col-major to row-major, or row-major
+  * to col-major, and invert the order of the dimensions.
+  *
+  * Beware: the dimensions are reversed by this operation. If you want to
+  * preserve the ordering of the dimensions, you need to combine this
+  * operation with a shuffle.
+  *
+  * \example:
+  * Tensor<float, 2, ColMajor> input(2, 4);
+  * Tensor<float, 2, RowMajor> output = input.swap_layout();
+  * eigen_assert(output.dimension(0) == 4);
+  * eigen_assert(output.dimension(1) == 2);
+  *
+  * array<int, 2> shuffle(1, 0);
+  * output = input.swap_layout().shuffle(shuffle);
+  * eigen_assert(output.dimension(0) == 2);
+  * eigen_assert(output.dimension(1) == 4);
+  *
+  */
+namespace internal {
+template<typename XprType>
+struct traits<TensorLayoutSwapOp<XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = traits<XprType>::NumDimensions;
+  static const int Layout = (traits<XprType>::Layout == ColMajor) ? RowMajor : ColMajor;
+};
+
+template<typename XprType>
+struct eval<TensorLayoutSwapOp<XprType>, Eigen::Dense>
+{
+  typedef const TensorLayoutSwapOp<XprType>& type;
+};
+
+template<typename XprType>
+struct nested<TensorLayoutSwapOp<XprType>, 1, typename eval<TensorLayoutSwapOp<XprType> >::type>
+{
+  typedef TensorLayoutSwapOp<XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename XprType>
+class TensorLayoutSwapOp : public TensorBase<TensorLayoutSwapOp<XprType>, WriteAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorLayoutSwapOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorLayoutSwapOp(const XprType& expr)
+      : m_xpr(expr) {}
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorLayoutSwapOp& operator = (const TensorLayoutSwapOp& other)
+    {
+      typedef TensorAssignOp<TensorLayoutSwapOp, const TensorLayoutSwapOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorLayoutSwapOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorLayoutSwapOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename XprType::Nested m_xpr;
+};
+
+
+// Eval as rvalue
+template<typename ArgType, typename Device>
+struct TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device>
+{
+  typedef TensorLayoutSwapOp<ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+
+  enum {
+    IsAligned = TensorEvaluator<ArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = (static_cast<int>(TensorEvaluator<ArgType, Device>::Layout) == static_cast<int>(ColMajor)) ? RowMajor : ColMajor,
+    CoordAccess = false,  // to be implemented
+    RawAccess = TensorEvaluator<ArgType, Device>::RawAccess
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device)
+  {
+    for(int i = 0; i < NumDims; ++i) {
+      m_dimensions[i] = m_impl.dimensions()[NumDims-1-i];
+    }
+  }
+
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
+    return m_impl.evalSubExprsIfNeeded(data);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_impl.coeff(index);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return m_impl.template packet<LoadMode>(index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    return m_impl.costPerCoeff(vectorized);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return m_impl.data(); }
+
+  const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+
+ protected:
+  TensorEvaluator<ArgType, Device> m_impl;
+  Dimensions m_dimensions;
+};
+
+
+// Eval as lvalue
+template<typename ArgType, typename Device>
+  struct TensorEvaluator<TensorLayoutSwapOp<ArgType>, Device>
+  : public TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device>
+{
+  typedef TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device> Base;
+  typedef TensorLayoutSwapOp<ArgType> XprType;
+
+  enum {
+    IsAligned = TensorEvaluator<ArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = (static_cast<int>(TensorEvaluator<ArgType, Device>::Layout) == static_cast<int>(ColMajor)) ? RowMajor : ColMajor,
+    CoordAccess = false  // to be implemented
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+    : Base(op, device)
+  { }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index)
+  {
+    return this->m_impl.coeffRef(index);
+  }
+  template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x)
+  {
+    this->m_impl.template writePacket<StoreMode>(index, x);
+  }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_LAYOUT_SWAP_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMacros.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMacros.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMacros.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMacros.h
@@ -0,0 +1,54 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_META_MACROS_H
+#define EIGEN_CXX11_TENSOR_TENSOR_META_MACROS_H
+
+
+/** use this macro in sfinae selection in templated functions
+ *
+ *   template<typename T,
+ *            typename std::enable_if< isBanana<T>::value , int >::type = 0
+ *   >
+ *   void foo(){}
+ *
+ *   becomes =>
+ *
+ *   template<typename TopoType,
+ *           SFINAE_ENABLE_IF( isBanana<T>::value )
+ *   >
+ *   void foo(){}
+ */
+
+// SFINAE requires variadic templates
+#ifndef __CUDACC__
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  // SFINAE doesn't work for gcc <= 4.7
+  #ifdef EIGEN_COMP_GNUC
+    #if EIGEN_GNUC_AT_LEAST(4,8)
+      #define EIGEN_HAS_SFINAE
+    #endif
+  #else
+    #define EIGEN_HAS_SFINAE
+  #endif
+#endif
+#endif
+
+#define EIGEN_SFINAE_ENABLE_IF( __condition__ ) \
+    typename internal::enable_if< ( __condition__ ) , int >::type = 0
+
+
+#if EIGEN_HAS_CONSTEXPR
+#define EIGEN_CONSTEXPR constexpr
+#else
+#define EIGEN_CONSTEXPR
+#endif
+
+
+#endif

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
@@ -0,0 +1,321 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_MAP_H
+#define EIGEN_CXX11_TENSOR_TENSOR_MAP_H
+
+namespace Eigen {
+
+/** \class TensorMap
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief A tensor expression mapping an existing array of data.
+  *
+  */
+/// template <class> class MakePointer_ is added to convert the host pointer to the device pointer.
+/// It is added due to the fact that for our device compiler T* is not allowed.
+/// If we wanted to use the same Evaluator functions we have to convert that type to our pointer T.
+/// This is done through our MakePointer_ class. By default the Type in the MakePointer_<T> is T* .
+/// Therefore, by adding the default value, we managed to convert the type and it does not break any
+/// existing code as its default value is T*.
+template<typename PlainObjectType, int Options_, template <class> class MakePointer_> class TensorMap : public TensorBase<TensorMap<PlainObjectType, Options_, MakePointer_> >
+{
+  public:
+    typedef TensorMap<PlainObjectType, Options_, MakePointer_> Self;
+    typedef typename PlainObjectType::Base Base;
+    typedef typename Eigen::internal::nested<Self>::type Nested;
+    typedef typename internal::traits<PlainObjectType>::StorageKind StorageKind;
+    typedef typename internal::traits<PlainObjectType>::Index Index;
+    typedef typename internal::traits<PlainObjectType>::Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename Base::CoeffReturnType CoeffReturnType;
+
+  /*    typedef typename internal::conditional<
+                         bool(internal::is_lvalue<PlainObjectType>::value),
+                         Scalar *,
+                         const Scalar *>::type
+                     PointerType;*/
+    typedef typename MakePointer_<Scalar>::Type PointerType;
+    typedef PointerType PointerArgType;
+
+    static const int Options = Options_;
+
+    static const Index NumIndices = PlainObjectType::NumIndices;
+    typedef typename PlainObjectType::Dimensions Dimensions;
+
+    enum {
+      IsAligned = ((int(Options_)&Aligned)==Aligned),
+      Layout = PlainObjectType::Layout,
+      CoordAccess = true,
+      RawAccess = true
+    };
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr) : m_data(dataPtr), m_dimensions() {
+      // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT((0 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions(firstDimension, otherDimensions...) {
+      // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT((sizeof...(otherDimensions) + 1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+#else
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(firstDimension) {
+      // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT((1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2) : m_data(dataPtr), m_dimensions(dim1, dim2) {
+      EIGEN_STATIC_ASSERT(2 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3) {
+      EIGEN_STATIC_ASSERT(3 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4) {
+      EIGEN_STATIC_ASSERT(4 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4, Index dim5) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4, dim5) {
+      EIGEN_STATIC_ASSERT(5 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
+#endif
+
+   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const array<Index, NumIndices>& dimensions)
+      : m_data(dataPtr), m_dimensions(dimensions)
+    { }
+
+    template <typename Dimensions>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const Dimensions& dimensions)
+      : m_data(dataPtr), m_dimensions(dimensions)
+    { }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PlainObjectType& tensor)
+      : m_data(tensor.data()), m_dimensions(tensor.dimensions())
+    { }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index rank() const { return m_dimensions.rank(); }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index dimension(Index n) const { return m_dimensions[n]; }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE PointerType data() { return m_data; }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const PointerType data() const { return m_data; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const
+    {
+      //      eigen_assert(checkIndexRange(indices));
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = m_dimensions.IndexOfRowMajor(indices);
+        return m_data[index];
+      } else {
+        const Index index = m_dimensions.IndexOfColMajor(indices);
+        return m_data[index];
+      }
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()() const
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return m_data[0];
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index index) const
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return m_data[index];
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
+    {
+      EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = m_dimensions.IndexOfRowMajor(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
+        return m_data[index];
+      } else {
+        const Index index = m_dimensions.IndexOfColMajor(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
+        return m_data[index];
+      }
+    }
+#else
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1) const
+    {
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = i1 + i0 * m_dimensions[1];
+        return m_data[index];
+      } else {
+        const Index index = i0 + i1 * m_dimensions[0];
+        return m_data[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2) const
+    {
+      if (PlainObjectType::Options&RowMajor) {
+         const Index index = i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0);
+         return m_data[index];
+      } else {
+         const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2);
+        return m_data[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3) const
+    {
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0));
+        return m_data[index];
+      } else {
+        const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3));
+        return m_data[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
+    {
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)));
+        return m_data[index];
+      } else {
+        const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4)));
+        return m_data[index];
+      }
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices)
+    {
+      //      eigen_assert(checkIndexRange(indices));
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = m_dimensions.IndexOfRowMajor(indices);
+        return m_data[index];
+      } else {
+        const Index index = m_dimensions.IndexOfColMajor(indices);
+        return m_data[index];
+      }
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()()
+    {
+      EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE)
+      return m_data[0];
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index index)
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return m_data[index];
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
+    {
+      static_assert(sizeof...(otherIndices) + 2 == NumIndices || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
+      const std::size_t NumDims = sizeof...(otherIndices) + 2;
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = m_dimensions.IndexOfRowMajor(array<Index, NumDims>{{firstIndex, secondIndex, otherIndices...}});
+        return m_data[index];
+      } else {
+        const Index index = m_dimensions.IndexOfColMajor(array<Index, NumDims>{{firstIndex, secondIndex, otherIndices...}});
+        return m_data[index];
+      }
+    }
+#else
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1)
+    {
+       if (PlainObjectType::Options&RowMajor) {
+         const Index index = i1 + i0 * m_dimensions[1];
+        return m_data[index];
+      } else {
+        const Index index = i0 + i1 * m_dimensions[0];
+        return m_data[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2)
+    {
+       if (PlainObjectType::Options&RowMajor) {
+         const Index index = i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0);
+        return m_data[index];
+      } else {
+         const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2);
+        return m_data[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
+    {
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0));
+        return m_data[index];
+      } else {
+        const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3));
+        return m_data[index];
+      }
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
+    {
+      if (PlainObjectType::Options&RowMajor) {
+        const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)));
+        return m_data[index];
+      } else {
+        const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4)));
+        return m_data[index];
+      }
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Self& operator=(const Self& other)
+    {
+      typedef TensorAssignOp<Self, const Self> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    Self& operator=(const OtherDerived& other)
+    {
+      typedef TensorAssignOp<Self, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  private:
+    typename MakePointer_<Scalar>::Type m_data;
+    Dimensions m_dimensions;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_MAP_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMeta.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMeta.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMeta.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMeta.h
@@ -0,0 +1,218 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_META_H
+#define EIGEN_CXX11_TENSOR_TENSOR_META_H
+
+namespace Eigen {
+
+template<bool cond> struct Cond {};
+
+template<typename T1, typename T2> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+const T1& choose(Cond<true>, const T1& first, const T2&) {
+  return first;
+}
+
+template<typename T1, typename T2> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+const T2& choose(Cond<false>, const T1&, const T2& second) {
+  return second;
+}
+
+
+template <typename T, typename X, typename Y>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T divup(const X x, const Y y) {
+  return static_cast<T>((x + y - 1) / y);
+}
+
+template <typename T>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+T divup(const T x, const T y) {
+  return static_cast<T>((x + y - 1) / y);
+}
+
+template <size_t n> struct max_n_1 {
+  static const size_t size = n;
+};
+template <> struct max_n_1<0> {
+  static const size_t size = 1;
+};
+
+
+// Default packet types
+template <typename Scalar, typename Device>
+struct PacketType : internal::packet_traits<Scalar> {
+  typedef typename internal::packet_traits<Scalar>::type type;
+};
+
+// For CUDA packet types when using a GpuDevice
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__) && defined(EIGEN_HAS_CUDA_FP16)
+template <>
+struct PacketType<half, GpuDevice> {
+  typedef half2 type;
+  static const int size = 2;
+  enum {
+    HasAdd    = 1,
+    HasSub    = 1,
+    HasMul    = 1,
+    HasNegate = 1,
+    HasAbs    = 1,
+    HasArg    = 0,
+    HasAbs2   = 0,
+    HasMin    = 1,
+    HasMax    = 1,
+    HasConj   = 0,
+    HasSetLinear = 0,
+    HasBlend  = 0,
+
+    HasDiv    = 1,
+    HasSqrt   = 1,
+    HasRsqrt  = 1,
+    HasExp    = 1,
+    HasLog    = 1,
+    HasLog1p  = 0,
+    HasLog10  = 0,
+    HasPow    = 1,
+  };
+};
+#endif
+
+#if defined(EIGEN_USE_SYCL)
+template <typename T>
+  struct PacketType<T, SyclDevice> {
+  typedef T type;
+  static const int size = 1;
+  enum {
+    HasAdd    = 0,
+    HasSub    = 0,
+    HasMul    = 0,
+    HasNegate = 0,
+    HasAbs    = 0,
+    HasArg    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasConj   = 0,
+    HasSetLinear = 0,
+    HasBlend  = 0
+  };
+};
+#endif
+
+
+// Tuple mimics std::pair but works on e.g. nvcc.
+template <typename U, typename V> struct Tuple {
+ public:
+  U first;
+  V second;
+
+  typedef U first_type;
+  typedef V second_type;
+
+  EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Tuple() : first(), second() {}
+
+  EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Tuple(const U& f, const V& s) : first(f), second(s) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Tuple& operator= (const Tuple& rhs) {
+    if (&rhs == this) return *this;
+    first = rhs.first;
+    second = rhs.second;
+    return *this;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void swap(Tuple& rhs) {
+    using numext::swap;
+    swap(first, rhs.first);
+    swap(second, rhs.second);
+  }
+};
+
+template <typename U, typename V>
+EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+bool operator==(const Tuple<U, V>& x, const Tuple<U, V>& y) {
+  return (x.first == y.first && x.second == y.second);
+}
+
+template <typename U, typename V>
+EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+bool operator!=(const Tuple<U, V>& x, const Tuple<U, V>& y) {
+  return !(x == y);
+}
+
+
+// Can't use std::pairs on cuda devices
+template <typename Idx> struct IndexPair {
+  EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE IndexPair() : first(0), second(0) {}
+  EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE IndexPair(Idx f, Idx s) : first(f), second(s) {}
+
+  EIGEN_DEVICE_FUNC void set(IndexPair<Idx> val) {
+    first = val.first;
+    second = val.second;
+  }
+
+  Idx first;
+  Idx second;
+};
+
+
+#ifdef EIGEN_HAS_SFINAE
+namespace internal {
+
+  template<typename IndexType, Index... Is>
+  EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  array<Index, sizeof...(Is)> customIndices2Array(IndexType& idx, numeric_list<Index, Is...>) {
+    return { idx[Is]... };
+  }
+  template<typename IndexType>
+  EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  array<Index, 0> customIndices2Array(IndexType&, numeric_list<Index>) {
+    return array<Index, 0>();
+  }
+
+  /** Make an array (for index/dimensions) out of a custom index */
+  template<typename Index, std::size_t NumIndices, typename IndexType>
+  EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  array<Index, NumIndices> customIndices2Array(IndexType& idx) {
+    return customIndices2Array(idx, typename gen_numeric_list<Index, NumIndices>::type{});
+  }
+
+
+  template <typename B, typename D>
+  struct is_base_of
+  {
+
+    typedef char (&yes)[1];
+    typedef char (&no)[2];
+
+    template <typename BB, typename DD>
+    struct Host
+    {
+      operator BB*() const;
+      operator DD*();
+    };
+
+    template<typename T>
+    static yes check(D*, T);
+    static no check(B*, int);
+
+    static const bool value = sizeof(check(Host<B,D>(), int())) == sizeof(yes);
+  };
+
+}
+#endif
+
+
+
+}  // namespace Eigen
+
+#endif  // EIGEN_CXX11_TENSOR_TENSOR_META_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
@@ -0,0 +1,888 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_MORPHING_H
+#define EIGEN_CXX11_TENSOR_TENSOR_MORPHING_H
+
+namespace Eigen {
+
+/** \class TensorReshaping
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor reshaping class.
+  *
+  *
+  */
+namespace internal {
+template<typename NewDimensions, typename XprType>
+struct traits<TensorReshapingOp<NewDimensions, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = array_size<NewDimensions>::value;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename NewDimensions, typename XprType>
+struct eval<TensorReshapingOp<NewDimensions, XprType>, Eigen::Dense>
+{
+  typedef const TensorReshapingOp<NewDimensions, XprType>& type;
+};
+
+template<typename NewDimensions, typename XprType>
+struct nested<TensorReshapingOp<NewDimensions, XprType>, 1, typename eval<TensorReshapingOp<NewDimensions, XprType> >::type>
+{
+  typedef TensorReshapingOp<NewDimensions, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename NewDimensions, typename XprType>
+class TensorReshapingOp : public TensorBase<TensorReshapingOp<NewDimensions, XprType>, WriteAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorReshapingOp>::Scalar Scalar;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorReshapingOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorReshapingOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorReshapingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReshapingOp(const XprType& expr, const NewDimensions& dims)
+      : m_xpr(expr), m_dims(dims) {}
+
+    EIGEN_DEVICE_FUNC
+    const NewDimensions& dimensions() const { return m_dims; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorReshapingOp& operator = (const TensorReshapingOp& other)
+    {
+      typedef TensorAssignOp<TensorReshapingOp, const TensorReshapingOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorReshapingOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorReshapingOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const NewDimensions m_dims;
+};
+
+
+// Eval as rvalue
+template<typename NewDimensions, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorReshapingOp<NewDimensions, ArgType>, Device>
+{
+  typedef TensorReshapingOp<NewDimensions, ArgType> XprType;
+  typedef NewDimensions Dimensions;
+
+  enum {
+    IsAligned = TensorEvaluator<ArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = TensorEvaluator<ArgType, Device>::RawAccess
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_dimensions(op.dimensions())
+  {
+    // The total size of the reshaped tensor must be equal to the total size
+    // of the input tensor.
+    eigen_assert(internal::array_prod(m_impl.dimensions()) == internal::array_prod(op.dimensions()));
+  }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
+    return m_impl.evalSubExprsIfNeeded(data);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_impl.coeff(index);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return m_impl.template packet<LoadMode>(index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    return m_impl.costPerCoeff(vectorized);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return const_cast<Scalar*>(m_impl.data()); }
+
+  EIGEN_DEVICE_FUNC const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+
+ protected:
+  TensorEvaluator<ArgType, Device> m_impl;
+  NewDimensions m_dimensions;
+};
+
+
+// Eval as lvalue
+template<typename NewDimensions, typename ArgType, typename Device>
+  struct TensorEvaluator<TensorReshapingOp<NewDimensions, ArgType>, Device>
+  : public TensorEvaluator<const TensorReshapingOp<NewDimensions, ArgType>, Device>
+
+{
+  typedef TensorEvaluator<const TensorReshapingOp<NewDimensions, ArgType>, Device> Base;
+  typedef TensorReshapingOp<NewDimensions, ArgType> XprType;
+  typedef NewDimensions Dimensions;
+
+  enum {
+    IsAligned = TensorEvaluator<ArgType, Device>::IsAligned,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = TensorEvaluator<ArgType, Device>::RawAccess
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+    : Base(op, device)
+  { }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index)
+  {
+    return this->m_impl.coeffRef(index);
+  }
+  template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x)
+  {
+    this->m_impl.template writePacket<StoreMode>(index, x);
+  }
+};
+
+
+/** \class TensorSlicing
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor slicing class.
+  *
+  *
+  */
+namespace internal {
+template<typename StartIndices, typename Sizes, typename XprType>
+struct traits<TensorSlicingOp<StartIndices, Sizes, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = array_size<StartIndices>::value;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename StartIndices, typename Sizes, typename XprType>
+struct eval<TensorSlicingOp<StartIndices, Sizes, XprType>, Eigen::Dense>
+{
+  typedef const TensorSlicingOp<StartIndices, Sizes, XprType>& type;
+};
+
+template<typename StartIndices, typename Sizes, typename XprType>
+struct nested<TensorSlicingOp<StartIndices, Sizes, XprType>, 1, typename eval<TensorSlicingOp<StartIndices, Sizes, XprType> >::type>
+{
+  typedef TensorSlicingOp<StartIndices, Sizes, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename StartIndices, typename Sizes, typename XprType>
+class TensorSlicingOp : public TensorBase<TensorSlicingOp<StartIndices, Sizes, XprType> >
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorSlicingOp>::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorSlicingOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorSlicingOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorSlicingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorSlicingOp(const XprType& expr, const StartIndices& indices, const Sizes& sizes)
+      : m_xpr(expr), m_indices(indices), m_sizes(sizes) {}
+
+    EIGEN_DEVICE_FUNC
+    const StartIndices& startIndices() const { return m_indices; }
+    EIGEN_DEVICE_FUNC
+    const Sizes& sizes() const { return m_sizes; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorSlicingOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorSlicingOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorSlicingOp& operator = (const TensorSlicingOp& other)
+    {
+      typedef TensorAssignOp<TensorSlicingOp, const TensorSlicingOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const StartIndices m_indices;
+    const Sizes m_sizes;
+};
+
+
+// Fixme: figure out the exact threshold
+namespace {
+template <typename Index, typename Device> struct MemcpyTriggerForSlicing {
+  EIGEN_DEVICE_FUNC MemcpyTriggerForSlicing(const Device& device) : threshold_(2 * device.numThreads()) { }
+  EIGEN_DEVICE_FUNC bool operator ()(Index val) const { return val > threshold_; }
+
+ private:
+  Index threshold_;
+};
+
+// It is very expensive to start the memcpy kernel on GPU: we therefore only
+// use it for large copies.
+#ifdef EIGEN_USE_GPU
+template <typename Index> struct MemcpyTriggerForSlicing<Index, GpuDevice>  {
+  EIGEN_DEVICE_FUNC MemcpyTriggerForSlicing(const GpuDevice&) { }
+  EIGEN_DEVICE_FUNC bool operator ()(Index val) const { return val > 4*1024*1024; }
+};
+#endif
+}
+
+// Eval as rvalue
+template<typename StartIndices, typename Sizes, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorSlicingOp<StartIndices, Sizes, ArgType>, Device>
+{
+  typedef TensorSlicingOp<StartIndices, Sizes, ArgType> XprType;
+  static const int NumDims = internal::array_size<Sizes>::value;
+
+  enum {
+    // Alignment can't be guaranteed at compile time since it depends on the
+    // slice offsets and sizes.
+    IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_device(device), m_dimensions(op.sizes()), m_offsets(op.startIndices())
+  {
+    for (std::size_t i = 0; i < internal::array_size<Dimensions>::value; ++i) {
+      eigen_assert(m_impl.dimensions()[i] >= op.sizes()[i] + op.startIndices()[i]);
+    }
+
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    const Sizes& output_dims = op.sizes();
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_inputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
+      }
+
+     // Don't initialize m_fastOutputStrides[0] since it won't ever be accessed.
+      m_outputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_outputStrides[i] = m_outputStrides[i-1] * output_dims[i-1];
+        m_fastOutputStrides[i] = internal::TensorIntDivisor<Index>(m_outputStrides[i]);
+      }
+    } else {
+      m_inputStrides[NumDims-1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
+      }
+
+     // Don't initialize m_fastOutputStrides[NumDims-1] since it won't ever be accessed.
+      m_outputStrides[NumDims-1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_outputStrides[i] = m_outputStrides[i+1] * output_dims[i+1];
+        m_fastOutputStrides[i] = internal::TensorIntDivisor<Index>(m_outputStrides[i]);
+      }
+    }
+  }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef Sizes Dimensions;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    if (!NumTraits<typename internal::remove_const<Scalar>::type>::RequireInitialization && data && m_impl.data()) {
+      Index contiguous_values = 1;
+      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+        for (int i = 0; i < NumDims; ++i) {
+          contiguous_values *= dimensions()[i];
+          if (dimensions()[i] != m_impl.dimensions()[i]) {
+            break;
+          }
+        }
+      } else {
+        for (int i = NumDims-1; i >= 0; --i) {
+          contiguous_values *= dimensions()[i];
+          if (dimensions()[i] != m_impl.dimensions()[i]) {
+            break;
+          }
+        }
+      }
+      // Use memcpy if it's going to be faster than using the regular evaluation.
+      const MemcpyTriggerForSlicing<Index, Device> trigger(m_device);
+      if (trigger(contiguous_values)) {
+        Scalar* src = (Scalar*)m_impl.data();
+        for (int i = 0; i < internal::array_prod(dimensions()); i += contiguous_values) {
+          Index offset = srcCoeff(i);
+          m_device.memcpy((void*)(data+i), src+offset, contiguous_values * sizeof(Scalar));
+        }
+        return false;
+      }
+    }
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_impl.coeff(srcCoeff(index));
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
+    EIGEN_STATIC_ASSERT((packetSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+packetSize-1 < internal::array_prod(dimensions()));
+
+    Index inputIndices[] = {0, 0};
+    Index indices[] = {index, index + packetSize - 1};
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx0 = indices[0] / m_fastOutputStrides[i];
+        const Index idx1 = indices[1] / m_fastOutputStrides[i];
+        inputIndices[0] += (idx0 + m_offsets[i]) * m_inputStrides[i];
+        inputIndices[1] += (idx1 + m_offsets[i]) * m_inputStrides[i];
+        indices[0] -= idx0 * m_outputStrides[i];
+        indices[1] -= idx1 * m_outputStrides[i];
+      }
+      inputIndices[0] += (indices[0] + m_offsets[0]);
+      inputIndices[1] += (indices[1] + m_offsets[0]);
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx0 = indices[0] / m_fastOutputStrides[i];
+        const Index idx1 = indices[1] / m_fastOutputStrides[i];
+        inputIndices[0] += (idx0 + m_offsets[i]) * m_inputStrides[i];
+        inputIndices[1] += (idx1 + m_offsets[i]) * m_inputStrides[i];
+        indices[0] -= idx0 * m_outputStrides[i];
+        indices[1] -= idx1 * m_outputStrides[i];
+      }
+      inputIndices[0] += (indices[0] + m_offsets[NumDims-1]);
+      inputIndices[1] += (indices[1] + m_offsets[NumDims-1]);
+    }
+    if (inputIndices[1] - inputIndices[0] == packetSize - 1) {
+      PacketReturnType rslt = m_impl.template packet<Unaligned>(inputIndices[0]);
+      return rslt;
+    }
+    else {
+      EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[packetSize];
+      values[0] = m_impl.coeff(inputIndices[0]);
+      values[packetSize-1] = m_impl.coeff(inputIndices[1]);
+      for (int i = 1; i < packetSize-1; ++i) {
+        values[i] = coeff(index+i);
+      }
+      PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+      return rslt;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    return m_impl.costPerCoeff(vectorized) + TensorOpCost(0, 0, NumDims);
+  }
+
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar* data() const {
+    Scalar* result = m_impl.data();
+    if (result) {
+      Index offset = 0;
+      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+        for (int i = 0; i < NumDims; ++i) {
+          if (m_dimensions[i] != m_impl.dimensions()[i]) {
+            offset += m_offsets[i] * m_inputStrides[i];
+            for (int j = i+1; j < NumDims; ++j) {
+              if (m_dimensions[j] > 1) {
+                return NULL;
+              }
+              offset += m_offsets[j] * m_inputStrides[j];
+            }
+            break;
+          }
+        }
+      } else {
+        for (int i = NumDims - 1; i >= 0; --i) {
+          if (m_dimensions[i] != m_impl.dimensions()[i]) {
+            offset += m_offsets[i] * m_inputStrides[i];
+            for (int j = i-1; j >= 0; --j) {
+              if (m_dimensions[j] > 1) {
+                return NULL;
+              }
+              offset += m_offsets[j] * m_inputStrides[j];
+            }
+            break;
+          }
+        }
+      }
+      return result + offset;
+    }
+    return NULL;
+  }
+
+ protected:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index srcCoeff(Index index) const
+  {
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx = index / m_fastOutputStrides[i];
+        inputIndex += (idx + m_offsets[i]) * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      inputIndex += (index + m_offsets[0]);
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx = index / m_fastOutputStrides[i];
+        inputIndex += (idx + m_offsets[i]) * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      inputIndex += (index + m_offsets[NumDims-1]);
+    }
+    return inputIndex;
+  }
+
+  array<Index, NumDims> m_outputStrides;
+  array<internal::TensorIntDivisor<Index>, NumDims> m_fastOutputStrides;
+  array<Index, NumDims> m_inputStrides;
+  TensorEvaluator<ArgType, Device> m_impl;
+  const Device& m_device;
+  Dimensions m_dimensions;
+  const StartIndices m_offsets;
+};
+
+
+// Eval as lvalue
+template<typename StartIndices, typename Sizes, typename ArgType, typename Device>
+struct TensorEvaluator<TensorSlicingOp<StartIndices, Sizes, ArgType>, Device>
+  : public TensorEvaluator<const TensorSlicingOp<StartIndices, Sizes, ArgType>, Device>
+{
+  typedef TensorEvaluator<const TensorSlicingOp<StartIndices, Sizes, ArgType>, Device> Base;
+  typedef TensorSlicingOp<StartIndices, Sizes, ArgType> XprType;
+  static const int NumDims = internal::array_size<Sizes>::value;
+
+  enum {
+    IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+    : Base(op, device)
+    { }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef Sizes Dimensions;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index)
+  {
+    return this->m_impl.coeffRef(this->srcCoeff(index));
+  }
+
+  template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x)
+  {
+    const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
+    Index inputIndices[] = {0, 0};
+    Index indices[] = {index, index + packetSize - 1};
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx0 = indices[0] / this->m_fastOutputStrides[i];
+        const Index idx1 = indices[1] / this->m_fastOutputStrides[i];
+        inputIndices[0] += (idx0 + this->m_offsets[i]) * this->m_inputStrides[i];
+        inputIndices[1] += (idx1 + this->m_offsets[i]) * this->m_inputStrides[i];
+        indices[0] -= idx0 * this->m_outputStrides[i];
+        indices[1] -= idx1 * this->m_outputStrides[i];
+      }
+      inputIndices[0] += (indices[0] + this->m_offsets[0]);
+      inputIndices[1] += (indices[1] + this->m_offsets[0]);
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx0 = indices[0] / this->m_fastOutputStrides[i];
+        const Index idx1 = indices[1] / this->m_fastOutputStrides[i];
+        inputIndices[0] += (idx0 + this->m_offsets[i]) * this->m_inputStrides[i];
+        inputIndices[1] += (idx1 + this->m_offsets[i]) * this->m_inputStrides[i];
+        indices[0] -= idx0 * this->m_outputStrides[i];
+        indices[1] -= idx1 * this->m_outputStrides[i];
+      }
+      inputIndices[0] += (indices[0] + this->m_offsets[NumDims-1]);
+      inputIndices[1] += (indices[1] + this->m_offsets[NumDims-1]);
+    }
+    if (inputIndices[1] - inputIndices[0] == packetSize - 1) {
+      this->m_impl.template writePacket<StoreMode>(inputIndices[0], x);
+    }
+    else {
+      EIGEN_ALIGN_MAX CoeffReturnType values[packetSize];
+      internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
+      this->m_impl.coeffRef(inputIndices[0]) = values[0];
+      this->m_impl.coeffRef(inputIndices[1]) = values[packetSize-1];
+      for (int i = 1; i < packetSize-1; ++i) {
+        this->coeffRef(index+i) = values[i];
+      }
+    }
+  }
+};
+
+
+
+namespace internal {
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType>
+struct traits<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = array_size<StartIndices>::value;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType>
+struct eval<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType>, Eigen::Dense>
+{
+  typedef const TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType>& type;
+};
+
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType>
+struct nested<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType>, 1, typename eval<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType> >::type>
+{
+  typedef TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType> type;
+};
+
+}  // end namespace internal
+
+
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType>
+class TensorStridingSlicingOp : public TensorBase<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType> >
+{
+  public:
+  typedef typename internal::traits<TensorStridingSlicingOp>::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename internal::nested<TensorStridingSlicingOp>::type Nested;
+  typedef typename internal::traits<TensorStridingSlicingOp>::StorageKind StorageKind;
+  typedef typename internal::traits<TensorStridingSlicingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorStridingSlicingOp(
+    const XprType& expr, const StartIndices& startIndices,
+    const StopIndices& stopIndices, const Strides& strides)
+      : m_xpr(expr), m_startIndices(startIndices), m_stopIndices(stopIndices),
+        m_strides(strides) {}
+
+    EIGEN_DEVICE_FUNC
+    const StartIndices& startIndices() const { return m_startIndices; }
+    EIGEN_DEVICE_FUNC
+    const StartIndices& stopIndices() const { return m_stopIndices; }
+    EIGEN_DEVICE_FUNC
+    const StartIndices& strides() const { return m_strides; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorStridingSlicingOp& operator = (const TensorStridingSlicingOp& other)
+    {
+      typedef TensorAssignOp<TensorStridingSlicingOp, const TensorStridingSlicingOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(
+          assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorStridingSlicingOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorStridingSlicingOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(
+          assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const StartIndices m_startIndices;
+    const StopIndices m_stopIndices;
+    const Strides m_strides;
+};
+
+// Eval as rvalue
+template<typename StartIndices, typename StopIndices, typename Strides, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType>, Device>
+{
+  typedef TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType> XprType;
+  static const int NumDims = internal::array_size<Strides>::value;
+
+  enum {
+    // Alignment can't be guaranteed at compile time since it depends on the
+    // slice offsets and sizes.
+    IsAligned = false,
+    PacketAccess = false,
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_device(device), m_strides(op.strides())
+  {
+    // Handle degenerate intervals by gracefully clamping and allowing m_dimensions to be zero
+    DSizes<Index,NumDims> startIndicesClamped, stopIndicesClamped;
+    for (size_t i = 0; i < internal::array_size<Dimensions>::value; ++i) {
+      eigen_assert(m_strides[i] != 0 && "0 stride is invalid");
+      if(m_strides[i]>0){
+        startIndicesClamped[i] = clamp(op.startIndices()[i], 0, m_impl.dimensions()[i]);
+        stopIndicesClamped[i] = clamp(op.stopIndices()[i], 0, m_impl.dimensions()[i]);
+      }else{
+        /* implies m_strides[i]<0 by assert */
+        startIndicesClamped[i] = clamp(op.startIndices()[i], -1, m_impl.dimensions()[i] - 1);
+        stopIndicesClamped[i] = clamp(op.stopIndices()[i], -1, m_impl.dimensions()[i] - 1);
+      }
+      m_startIndices[i] = startIndicesClamped[i];
+    }
+
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+
+    // check for degenerate intervals and compute output tensor shape
+    bool degenerate = false;;
+    for(int i = 0; i < NumDims; i++){
+      Index interval = stopIndicesClamped[i] - startIndicesClamped[i];
+      if(interval == 0 || ((interval<0) != (m_strides[i]<0))){
+        m_dimensions[i] = 0;
+        degenerate = true;
+      }else{
+        m_dimensions[i] = interval / m_strides[i]
+                          + (interval % m_strides[i] != 0 ? 1 : 0);
+        eigen_assert(m_dimensions[i] >= 0);
+      }
+    }
+    Strides output_dims = m_dimensions;
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_inputStrides[0] = m_strides[0];
+      m_offsets[0] = startIndicesClamped[0];
+      Index previousDimProduct = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        previousDimProduct *= input_dims[i-1];
+        m_inputStrides[i] = previousDimProduct * m_strides[i];
+        m_offsets[i] = startIndicesClamped[i] * previousDimProduct;
+      }
+
+      // Don't initialize m_fastOutputStrides[0] since it won't ever be accessed.
+      m_outputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_outputStrides[i] = m_outputStrides[i-1] * output_dims[i-1];
+        // NOTE: if tensor is degenerate, we send 1 to prevent TensorIntDivisor constructor crash
+        m_fastOutputStrides[i] = internal::TensorIntDivisor<Index>(degenerate ? 1 : m_outputStrides[i]);
+      }
+    } else {
+      m_inputStrides[NumDims-1] = m_strides[NumDims-1];
+      m_offsets[NumDims-1] = startIndicesClamped[NumDims-1];
+      Index previousDimProduct = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        previousDimProduct *= input_dims[i+1];
+        m_inputStrides[i] = previousDimProduct * m_strides[i];
+        m_offsets[i] = startIndicesClamped[i] * previousDimProduct;
+      }
+
+      m_outputStrides[NumDims-1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_outputStrides[i] = m_outputStrides[i+1] * output_dims[i+1];
+        // NOTE: if tensor is degenerate, we send 1 to prevent TensorIntDivisor constructor crash
+        m_fastOutputStrides[i] = internal::TensorIntDivisor<Index>(degenerate ? 1 : m_outputStrides[i]);
+      }
+    }
+    m_block_total_size_max = numext::maxi(static_cast<std::size_t>(1),
+                                          device.lastLevelCacheSize() /
+                                          sizeof(Scalar));
+  }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename internal::remove_const<Scalar>::type ScalarNonConst;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef Strides Dimensions;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_impl.coeff(srcCoeff(index));
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    return m_impl.costPerCoeff(vectorized) + TensorOpCost(0, 0, NumDims);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar* data() const {
+    return NULL;
+  }
+
+ protected:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index srcCoeff(Index index) const
+  {
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i >= 0; --i) {
+        const Index idx = index / m_fastOutputStrides[i];
+        inputIndex += idx * m_inputStrides[i] + m_offsets[i];
+        index -= idx * m_outputStrides[i];
+      }
+    } else {
+      for (int i = 0; i < NumDims; ++i) {
+        const Index idx = index / m_fastOutputStrides[i];
+        inputIndex += idx * m_inputStrides[i] + m_offsets[i];
+        index -= idx * m_outputStrides[i];
+      }
+    }
+    return inputIndex;
+  }
+
+  static EIGEN_STRONG_INLINE Index clamp(Index value, Index min, Index max) {
+    return numext::maxi(min, numext::mini(max,value));
+  }
+
+  array<Index, NumDims> m_outputStrides;
+  array<internal::TensorIntDivisor<Index>, NumDims> m_fastOutputStrides;
+  array<Index, NumDims> m_inputStrides;
+  TensorEvaluator<ArgType, Device> m_impl;
+  const Device& m_device;
+  DSizes<Index, NumDims> m_startIndices; // clamped startIndices
+  DSizes<Index, NumDims> m_dimensions;
+  DSizes<Index, NumDims> m_offsets; // offset in a flattened shape
+  const Strides m_strides;
+  std::size_t m_block_total_size_max;
+};
+
+// Eval as lvalue
+template<typename StartIndices, typename StopIndices, typename Strides, typename ArgType, typename Device>
+struct TensorEvaluator<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType>, Device>
+  : public TensorEvaluator<const TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType>, Device>
+{
+  typedef TensorEvaluator<const TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType>, Device> Base;
+  typedef TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType> XprType;
+  static const int NumDims = internal::array_size<Strides>::value;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = false,
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = TensorEvaluator<ArgType, Device>::CoordAccess,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+    : Base(op, device)
+    { }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename internal::remove_const<Scalar>::type ScalarNonConst;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef Strides Dimensions;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index)
+  {
+    return this->m_impl.coeffRef(this->srcCoeff(index));
+  }
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_MORPHING_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
@@ -0,0 +1,397 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_PADDING_H
+#define EIGEN_CXX11_TENSOR_TENSOR_PADDING_H
+
+namespace Eigen {
+
+/** \class TensorPadding
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor padding class.
+  * At the moment only padding with a constant value is supported.
+  *
+  */
+namespace internal {
+template<typename PaddingDimensions, typename XprType>
+struct traits<TensorPaddingOp<PaddingDimensions, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename PaddingDimensions, typename XprType>
+struct eval<TensorPaddingOp<PaddingDimensions, XprType>, Eigen::Dense>
+{
+  typedef const TensorPaddingOp<PaddingDimensions, XprType>& type;
+};
+
+template<typename PaddingDimensions, typename XprType>
+struct nested<TensorPaddingOp<PaddingDimensions, XprType>, 1, typename eval<TensorPaddingOp<PaddingDimensions, XprType> >::type>
+{
+  typedef TensorPaddingOp<PaddingDimensions, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename PaddingDimensions, typename XprType>
+class TensorPaddingOp : public TensorBase<TensorPaddingOp<PaddingDimensions, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorPaddingOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorPaddingOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorPaddingOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorPaddingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPaddingOp(const XprType& expr, const PaddingDimensions& padding_dims, const Scalar padding_value)
+      : m_xpr(expr), m_padding_dims(padding_dims), m_padding_value(padding_value) {}
+
+    EIGEN_DEVICE_FUNC
+    const PaddingDimensions& padding() const { return m_padding_dims; }
+    EIGEN_DEVICE_FUNC
+    Scalar padding_value() const { return m_padding_value; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const PaddingDimensions m_padding_dims;
+    const Scalar m_padding_value;
+};
+
+
+// Eval as rvalue
+template<typename PaddingDimensions, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device>
+{
+  typedef TensorPaddingOp<PaddingDimensions, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<PaddingDimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = true,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = true,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_padding(op.padding()), m_paddingValue(op.padding_value())
+  {
+    // The padding op doesn't change the rank of the tensor. Directly padding a scalar would lead
+    // to a vector, which doesn't make sense. Instead one should reshape the scalar into a vector
+    // of 1 element first and then pad.
+    EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    // Compute dimensions
+    m_dimensions = m_impl.dimensions();
+    for (int i = 0; i < NumDims; ++i) {
+      m_dimensions[i] += m_padding[i].first + m_padding[i].second;
+    }
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_inputStrides[0] = 1;
+      m_outputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
+        m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
+      }
+      m_outputStrides[NumDims] = m_outputStrides[NumDims-1] * m_dimensions[NumDims-1];
+    } else {
+      m_inputStrides[NumDims - 1] = 1;
+      m_outputStrides[NumDims] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
+        m_outputStrides[i+1] = m_outputStrides[i+2] * m_dimensions[i+1];
+      }
+      m_outputStrides[0] = m_outputStrides[1] * m_dimensions[0];
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    eigen_assert(index < dimensions().TotalSize());
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx = index / m_outputStrides[i];
+        if (isPaddingAtIndexForDim(idx, i)) {
+          return m_paddingValue;
+        }
+        inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      if (isPaddingAtIndexForDim(index, 0)) {
+        return m_paddingValue;
+      }
+      inputIndex += (index - m_padding[0].first);
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx = index / m_outputStrides[i+1];
+        if (isPaddingAtIndexForDim(idx, i)) {
+          return m_paddingValue;
+        }
+        inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
+        index -= idx * m_outputStrides[i+1];
+      }
+      if (isPaddingAtIndexForDim(index, NumDims-1)) {
+        return m_paddingValue;
+      }
+      inputIndex += (index - m_padding[NumDims-1].first);
+    }
+    return m_impl.coeff(inputIndex);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      return packetColMajor(index);
+    }
+    return packetRowMajor(index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    TensorOpCost cost = m_impl.costPerCoeff(vectorized);
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = 0; i < NumDims; ++i)
+        updateCostPerDimension(cost, i, i == 0);
+    } else {
+      for (int i = NumDims - 1; i >= 0; --i)
+        updateCostPerDimension(cost, i, i == NumDims - 1);
+    }
+    return cost;
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ private:
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isPaddingAtIndexForDim(
+      Index index, int dim_index) const {
+#if defined(EIGEN_HAS_INDEX_LIST)
+    return (!internal::index_pair_first_statically_eq<PaddingDimensions>(dim_index, 0) &&
+            index < m_padding[dim_index].first) ||
+        (!internal::index_pair_second_statically_eq<PaddingDimensions>(dim_index, 0) &&
+         index >= m_dimensions[dim_index] - m_padding[dim_index].second);
+#else
+    return (index < m_padding[dim_index].first) ||
+           (index >= m_dimensions[dim_index] - m_padding[dim_index].second);
+#endif
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isLeftPaddingCompileTimeZero(
+      int dim_index) const {
+#if defined(EIGEN_HAS_INDEX_LIST)
+    return internal::index_pair_first_statically_eq<PaddingDimensions>(dim_index, 0);
+#else
+    EIGEN_UNUSED_VARIABLE(dim_index);
+    return false;
+#endif
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isRightPaddingCompileTimeZero(
+      int dim_index) const {
+#if defined(EIGEN_HAS_INDEX_LIST)
+    return internal::index_pair_second_statically_eq<PaddingDimensions>(dim_index, 0);
+#else
+    EIGEN_UNUSED_VARIABLE(dim_index);
+    return false;
+#endif
+  }
+
+
+  void updateCostPerDimension(TensorOpCost& cost, int i, bool first) const {
+    const double in = static_cast<double>(m_impl.dimensions()[i]);
+    const double out = in + m_padding[i].first + m_padding[i].second;
+    if (out == 0)
+      return;
+    const double reduction = in / out;
+    cost *= reduction;
+    if (first) {
+      cost += TensorOpCost(0, 0, 2 * TensorOpCost::AddCost<Index>() +
+                    reduction * (1 * TensorOpCost::AddCost<Index>()));
+    } else {
+      cost += TensorOpCost(0, 0, 2 * TensorOpCost::AddCost<Index>() +
+                                 2 * TensorOpCost::MulCost<Index>() +
+                    reduction * (2 * TensorOpCost::MulCost<Index>() +
+                                 1 * TensorOpCost::DivCost<Index>()));
+    }
+  }
+
+ protected:
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetColMajor(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    const Index initialIndex = index;
+    Index inputIndex = 0;
+    for (int i = NumDims - 1; i > 0; --i) {
+      const Index first = index;
+      const Index last = index + PacketSize - 1;
+      const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i];
+      const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i];
+      const Index lastPaddedRight = m_outputStrides[i+1];
+
+      if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) {
+        // all the coefficient are in the padding zone.
+        return internal::pset1<PacketReturnType>(m_paddingValue);
+      }
+      else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) {
+        // all the coefficient are in the padding zone.
+        return internal::pset1<PacketReturnType>(m_paddingValue);
+      }
+      else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
+        // all the coefficient are between the 2 padding zones.
+        const Index idx = index / m_outputStrides[i];
+        inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      else {
+        // Every other case
+        return packetWithPossibleZero(initialIndex);
+      }
+    }
+
+    const Index last = index + PacketSize - 1;
+    const Index first = index;
+    const Index lastPaddedLeft = m_padding[0].first;
+    const Index firstPaddedRight = (m_dimensions[0] - m_padding[0].second);
+    const Index lastPaddedRight = m_outputStrides[1];
+
+    if (!isLeftPaddingCompileTimeZero(0) && last < lastPaddedLeft) {
+      // all the coefficient are in the padding zone.
+      return internal::pset1<PacketReturnType>(m_paddingValue);
+    }
+    else if (!isRightPaddingCompileTimeZero(0) && first >= firstPaddedRight && last < lastPaddedRight) {
+      // all the coefficient are in the padding zone.
+      return internal::pset1<PacketReturnType>(m_paddingValue);
+    }
+    else if ((isLeftPaddingCompileTimeZero(0) && isRightPaddingCompileTimeZero(0)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
+      // all the coefficient are between the 2 padding zones.
+      inputIndex += (index - m_padding[0].first);
+      return m_impl.template packet<Unaligned>(inputIndex);
+    }
+    // Every other case
+    return packetWithPossibleZero(initialIndex);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetRowMajor(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    const Index initialIndex = index;
+    Index inputIndex = 0;
+
+    for (int i = 0; i < NumDims - 1; ++i) {
+      const Index first = index;
+      const Index last = index + PacketSize - 1;
+      const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i+1];
+      const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i+1];
+      const Index lastPaddedRight = m_outputStrides[i];
+
+      if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) {
+        // all the coefficient are in the padding zone.
+        return internal::pset1<PacketReturnType>(m_paddingValue);
+      }
+      else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) {
+        // all the coefficient are in the padding zone.
+        return internal::pset1<PacketReturnType>(m_paddingValue);
+      }
+      else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
+        // all the coefficient are between the 2 padding zones.
+        const Index idx = index / m_outputStrides[i+1];
+        inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
+        index -= idx * m_outputStrides[i+1];
+      }
+      else {
+        // Every other case
+        return packetWithPossibleZero(initialIndex);
+      }
+    }
+
+    const Index last = index + PacketSize - 1;
+    const Index first = index;
+    const Index lastPaddedLeft = m_padding[NumDims-1].first;
+    const Index firstPaddedRight = (m_dimensions[NumDims-1] - m_padding[NumDims-1].second);
+    const Index lastPaddedRight = m_outputStrides[NumDims-1];
+
+    if (!isLeftPaddingCompileTimeZero(NumDims-1) && last < lastPaddedLeft) {
+      // all the coefficient are in the padding zone.
+      return internal::pset1<PacketReturnType>(m_paddingValue);
+    }
+    else if (!isRightPaddingCompileTimeZero(NumDims-1) && first >= firstPaddedRight && last < lastPaddedRight) {
+      // all the coefficient are in the padding zone.
+      return internal::pset1<PacketReturnType>(m_paddingValue);
+    }
+    else if ((isLeftPaddingCompileTimeZero(NumDims-1) && isRightPaddingCompileTimeZero(NumDims-1)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
+      // all the coefficient are between the 2 padding zones.
+      inputIndex += (index - m_padding[NumDims-1].first);
+      return m_impl.template packet<Unaligned>(inputIndex);
+    }
+    // Every other case
+    return packetWithPossibleZero(initialIndex);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
+  {
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+    for (int i = 0; i < PacketSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  Dimensions m_dimensions;
+  array<Index, NumDims+1> m_outputStrides;
+  array<Index, NumDims> m_inputStrides;
+  TensorEvaluator<ArgType, Device> m_impl;
+  PaddingDimensions m_padding;
+
+  Scalar m_paddingValue;
+};
+
+
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_PADDING_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorPatch.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorPatch.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorPatch.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorPatch.h
@@ -0,0 +1,269 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_PATCH_H
+#define EIGEN_CXX11_TENSOR_TENSOR_PATCH_H
+
+namespace Eigen {
+
+/** \class TensorPatch
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor patch class.
+  *
+  *
+  */
+namespace internal {
+template<typename PatchDim, typename XprType>
+struct traits<TensorPatchOp<PatchDim, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions + 1;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename PatchDim, typename XprType>
+struct eval<TensorPatchOp<PatchDim, XprType>, Eigen::Dense>
+{
+  typedef const TensorPatchOp<PatchDim, XprType>& type;
+};
+
+template<typename PatchDim, typename XprType>
+struct nested<TensorPatchOp<PatchDim, XprType>, 1, typename eval<TensorPatchOp<PatchDim, XprType> >::type>
+{
+  typedef TensorPatchOp<PatchDim, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename PatchDim, typename XprType>
+class TensorPatchOp : public TensorBase<TensorPatchOp<PatchDim, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorPatchOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorPatchOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorPatchOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorPatchOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPatchOp(const XprType& expr, const PatchDim& patch_dims)
+      : m_xpr(expr), m_patch_dims(patch_dims) {}
+
+    EIGEN_DEVICE_FUNC
+    const PatchDim& patch_dims() const { return m_patch_dims; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const PatchDim m_patch_dims;
+};
+
+
+// Eval as rvalue
+template<typename PatchDim, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorPatchOp<PatchDim, ArgType>, Device>
+{
+  typedef TensorPatchOp<PatchDim, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value + 1;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+
+  enum {
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,
+    RawAccess = false
+ };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device)
+  {
+    Index num_patches = 1;
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    const PatchDim& patch_dims = op.patch_dims();
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = 0; i < NumDims-1; ++i) {
+        m_dimensions[i] = patch_dims[i];
+        num_patches *= (input_dims[i] - patch_dims[i] + 1);
+      }
+      m_dimensions[NumDims-1] = num_patches;
+
+      m_inputStrides[0] = 1;
+      m_patchStrides[0] = 1;
+      for (int i = 1; i < NumDims-1; ++i) {
+        m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
+        m_patchStrides[i] = m_patchStrides[i-1] * (input_dims[i-1] - patch_dims[i-1] + 1);
+      }
+      m_outputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
+      }
+    } else {
+      for (int i = 0; i < NumDims-1; ++i) {
+        m_dimensions[i+1] = patch_dims[i];
+        num_patches *= (input_dims[i] - patch_dims[i] + 1);
+      }
+      m_dimensions[0] = num_patches;
+
+      m_inputStrides[NumDims-2] = 1;
+      m_patchStrides[NumDims-2] = 1;
+      for (int i = NumDims-3; i >= 0; --i) {
+        m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
+        m_patchStrides[i] = m_patchStrides[i+1] * (input_dims[i+1] - patch_dims[i+1] + 1);
+      }
+      m_outputStrides[NumDims-1] = 1;
+      for (int i = NumDims-2; i >= 0; --i) {
+        m_outputStrides[i] = m_outputStrides[i+1] * m_dimensions[i+1];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    Index output_stride_index = (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? NumDims - 1 : 0;
+    // Find the location of the first element of the patch.
+    Index patchIndex = index / m_outputStrides[output_stride_index];
+    // Find the offset of the element wrt the location of the first element.
+    Index patchOffset = index - patchIndex * m_outputStrides[output_stride_index];
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 2; i > 0; --i) {
+        const Index patchIdx = patchIndex / m_patchStrides[i];
+        patchIndex -= patchIdx * m_patchStrides[i];
+        const Index offsetIdx = patchOffset / m_outputStrides[i];
+        patchOffset -= offsetIdx * m_outputStrides[i];
+        inputIndex += (patchIdx + offsetIdx) * m_inputStrides[i];
+      }
+    } else {
+      for (int i = 0; i < NumDims - 2; ++i) {
+        const Index patchIdx = patchIndex / m_patchStrides[i];
+        patchIndex -= patchIdx * m_patchStrides[i];
+        const Index offsetIdx = patchOffset / m_outputStrides[i+1];
+        patchOffset -= offsetIdx * m_outputStrides[i+1];
+        inputIndex += (patchIdx + offsetIdx) * m_inputStrides[i];
+      }
+    }
+    inputIndex += (patchIndex + patchOffset);
+    return m_impl.coeff(inputIndex);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    Index output_stride_index = (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? NumDims - 1 : 0;
+    Index indices[2] = {index, index + PacketSize - 1};
+    Index patchIndices[2] = {indices[0] / m_outputStrides[output_stride_index],
+                             indices[1] / m_outputStrides[output_stride_index]};
+    Index patchOffsets[2] = {indices[0] - patchIndices[0] * m_outputStrides[output_stride_index],
+                             indices[1] - patchIndices[1] * m_outputStrides[output_stride_index]};
+
+    Index inputIndices[2] = {0, 0};
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 2; i > 0; --i) {
+        const Index patchIdx[2] = {patchIndices[0] / m_patchStrides[i],
+                                   patchIndices[1] / m_patchStrides[i]};
+        patchIndices[0] -= patchIdx[0] * m_patchStrides[i];
+        patchIndices[1] -= patchIdx[1] * m_patchStrides[i];
+
+        const Index offsetIdx[2] = {patchOffsets[0] / m_outputStrides[i],
+                                    patchOffsets[1] / m_outputStrides[i]};
+        patchOffsets[0] -= offsetIdx[0] * m_outputStrides[i];
+        patchOffsets[1] -= offsetIdx[1] * m_outputStrides[i];
+
+        inputIndices[0] += (patchIdx[0] + offsetIdx[0]) * m_inputStrides[i];
+        inputIndices[1] += (patchIdx[1] + offsetIdx[1]) * m_inputStrides[i];
+      }
+    } else {
+      for (int i = 0; i < NumDims - 2; ++i) {
+        const Index patchIdx[2] = {patchIndices[0] / m_patchStrides[i],
+                                   patchIndices[1] / m_patchStrides[i]};
+        patchIndices[0] -= patchIdx[0] * m_patchStrides[i];
+        patchIndices[1] -= patchIdx[1] * m_patchStrides[i];
+
+        const Index offsetIdx[2] = {patchOffsets[0] / m_outputStrides[i+1],
+                                    patchOffsets[1] / m_outputStrides[i+1]};
+        patchOffsets[0] -= offsetIdx[0] * m_outputStrides[i+1];
+        patchOffsets[1] -= offsetIdx[1] * m_outputStrides[i+1];
+
+        inputIndices[0] += (patchIdx[0] + offsetIdx[0]) * m_inputStrides[i];
+        inputIndices[1] += (patchIdx[1] + offsetIdx[1]) * m_inputStrides[i];
+      }
+    }
+    inputIndices[0] += (patchIndices[0] + patchOffsets[0]);
+    inputIndices[1] += (patchIndices[1] + patchOffsets[1]);
+
+    if (inputIndices[1] - inputIndices[0] == PacketSize - 1) {
+      PacketReturnType rslt = m_impl.template packet<Unaligned>(inputIndices[0]);
+      return rslt;
+    }
+    else {
+      EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize];
+      values[0] = m_impl.coeff(inputIndices[0]);
+      values[PacketSize-1] = m_impl.coeff(inputIndices[1]);
+      for (int i = 1; i < PacketSize-1; ++i) {
+        values[i] = coeff(index+i);
+      }
+      PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+      return rslt;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    const double compute_cost = NumDims * (TensorOpCost::DivCost<Index>() +
+                                           TensorOpCost::MulCost<Index>() +
+                                           2 * TensorOpCost::AddCost<Index>());
+    return m_impl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ protected:
+  Dimensions m_dimensions;
+  array<Index, NumDims> m_outputStrides;
+  array<Index, NumDims-1> m_inputStrides;
+  array<Index, NumDims-1> m_patchStrides;
+
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_PATCH_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h
@@ -0,0 +1,276 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_RANDOM_H
+#define EIGEN_CXX11_TENSOR_TENSOR_RANDOM_H
+
+namespace Eigen {
+namespace internal {
+
+namespace {
+
+EIGEN_DEVICE_FUNC uint64_t get_random_seed() {
+#ifdef __CUDA_ARCH__
+  // We don't support 3d kernels since we currently only use 1 and
+  // 2d kernels.
+  assert(threadIdx.z == 0);
+  return clock64() +
+      blockIdx.x * blockDim.x + threadIdx.x +
+      gridDim.x * blockDim.x * (blockIdx.y * blockDim.y + threadIdx.y);
+
+#elif defined _WIN32
+  // Use the current time as a baseline.
+  SYSTEMTIME st;
+  GetSystemTime(&st);
+  int time = st.wSecond + 1000 * st.wMilliseconds;
+  // Mix in a random number to make sure that we get different seeds if
+  // we try to generate seeds faster than the clock resolution.
+  // We need 2 random values since the generator only generate 16 bits at
+  // a time (https://msdn.microsoft.com/en-us/library/398ax69y.aspx)
+  int rnd1 = ::rand();
+  int rnd2 = ::rand();
+  uint64_t rnd = (rnd1 | rnd2 << 16) ^ time;
+  return rnd;
+
+#elif defined __APPLE__
+  // Same approach as for win32, except that the random number generator
+  // is better (// https://developer.apple.com/legacy/library/documentation/Darwin/Reference/ManPages/man3/random.3.html#//apple_ref/doc/man/3/random).
+  uint64_t rnd = ::random() ^ mach_absolute_time();
+  return rnd;
+
+#else
+  // Augment the current time with pseudo random number generation
+  // to ensure that we get different seeds if we try to generate seeds
+  // faster than the clock resolution.
+  timespec ts;
+  clock_gettime(CLOCK_REALTIME, &ts);
+  uint64_t rnd = ::random() ^ ts.tv_nsec;
+  return rnd;
+#endif
+}
+
+static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE unsigned PCG_XSH_RS_generator(uint64_t* state) {
+  // TODO: Unify with the implementation in the non blocking thread pool.
+  uint64_t current = *state;
+  // Update the internal state
+  *state = current * 6364136223846793005ULL + 0xda3e39cb94b95bdbULL;
+  // Generate the random output (using the PCG-XSH-RS scheme)
+  return static_cast<unsigned>((current ^ (current >> 22)) >> (22 + (current >> 61)));
+}
+
+static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE uint64_t PCG_XSH_RS_state(uint64_t seed) {
+  seed = seed ? seed : get_random_seed();
+  return seed * 6364136223846793005ULL + 0xda3e39cb94b95bdbULL;
+}
+
+}  // namespace
+
+
+template <typename T> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+T RandomToTypeUniform(uint64_t* state) {
+  unsigned rnd = PCG_XSH_RS_generator(state);
+  return static_cast<T>(rnd);
+}
+
+
+template <> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+Eigen::half RandomToTypeUniform<Eigen::half>(uint64_t* state) {
+  Eigen::half result;
+  // Generate 10 random bits for the mantissa
+  unsigned rnd = PCG_XSH_RS_generator(state);
+  result.x = static_cast<uint16_t>(rnd & 0x3ffu);
+  // Set the exponent
+  result.x |= (static_cast<uint16_t>(15) << 10);
+  // Return the final result
+  return result - Eigen::half(1.0f);
+}
+
+
+template <> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float RandomToTypeUniform<float>(uint64_t* state) {
+  typedef union {
+    uint32_t raw;
+    float fp;
+  } internal;
+  internal result;
+  // Generate 23 random bits for the mantissa mantissa
+  const unsigned rnd = PCG_XSH_RS_generator(state);
+  result.raw = rnd & 0x7fffffu;
+  // Set the exponent
+  result.raw |= (static_cast<uint32_t>(127) << 23);
+  // Return the final result
+  return result.fp - 1.0f;
+}
+
+template <> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double RandomToTypeUniform<double>(uint64_t* state) {
+  typedef union {
+    uint64_t raw;
+    double dp;
+  } internal;
+  internal result;
+  result.raw = 0;
+  // Generate 52 random bits for the mantissa
+  // First generate the upper 20 bits
+  unsigned rnd1 = PCG_XSH_RS_generator(state) & 0xfffffu;
+  // The generate the lower 32 bits
+  unsigned rnd2 = PCG_XSH_RS_generator(state);
+  result.raw = (static_cast<uint64_t>(rnd1) << 32) | rnd2;
+  // Set the exponent
+  result.raw |= (static_cast<uint64_t>(1023) << 52);
+  // Return the final result
+  return result.dp - 1.0;
+}
+
+template <> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+std::complex<float> RandomToTypeUniform<std::complex<float> >(uint64_t* state) {
+  return std::complex<float>(RandomToTypeUniform<float>(state),
+                             RandomToTypeUniform<float>(state));
+}
+template <> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+std::complex<double> RandomToTypeUniform<std::complex<double> >(uint64_t* state) {
+  return std::complex<double>(RandomToTypeUniform<double>(state),
+                              RandomToTypeUniform<double>(state));
+}
+
+template <typename T> class UniformRandomGenerator {
+ public:
+  static const bool PacketAccess = true;
+
+  // Uses the given "seed" if non-zero, otherwise uses a random seed.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE UniformRandomGenerator(
+      uint64_t seed = 0) {
+    m_state = PCG_XSH_RS_state(seed);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE UniformRandomGenerator(
+      const UniformRandomGenerator& other) {
+    m_state = other.m_state;
+  }
+
+  template<typename Index> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  T operator()(Index i) const {
+    uint64_t local_state = m_state + i;
+    T result = RandomToTypeUniform<T>(&local_state);
+    m_state = local_state;
+    return result;
+  }
+
+  template<typename Packet, typename Index> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Packet packetOp(Index i) const {
+    const int packetSize = internal::unpacket_traits<Packet>::size;
+    EIGEN_ALIGN_MAX T values[packetSize];
+    uint64_t local_state = m_state + i;
+    for (int j = 0; j < packetSize; ++j) {
+      values[j] = RandomToTypeUniform<T>(&local_state);
+    }
+    m_state = local_state;
+    return internal::pload<Packet>(values);
+  }
+
+ private:
+  mutable uint64_t m_state;
+};
+
+template <typename Scalar>
+struct functor_traits<UniformRandomGenerator<Scalar> > {
+  enum {
+    // Rough estimate for floating point, multiplied by ceil(sizeof(T) / sizeof(float)).
+    Cost = 12 * NumTraits<Scalar>::AddCost *
+           ((sizeof(Scalar) + sizeof(float) - 1) / sizeof(float)),
+    PacketAccess = UniformRandomGenerator<Scalar>::PacketAccess
+  };
+};
+
+
+
+template <typename T> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+T RandomToTypeNormal(uint64_t* state) {
+  // Use the ratio of uniform method to generate numbers following a normal
+  // distribution. See for example Numerical Recipes chapter 7.3.9 for the
+  // details.
+  T u, v, q;
+  do {
+    u = RandomToTypeUniform<T>(state);
+    v = T(1.7156) * (RandomToTypeUniform<T>(state) - T(0.5));
+    const T x = u - T(0.449871);
+    const T y = numext::abs(v) + T(0.386595);
+    q = x*x + y * (T(0.196)*y - T(0.25472)*x);
+  } while (q > T(0.27597) &&
+           (q > T(0.27846) || v*v > T(-4) * numext::log(u) * u*u));
+
+  return v/u;
+}
+
+template <> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+std::complex<float> RandomToTypeNormal<std::complex<float> >(uint64_t* state) {
+  return std::complex<float>(RandomToTypeNormal<float>(state),
+                             RandomToTypeNormal<float>(state));
+}
+template <> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+std::complex<double> RandomToTypeNormal<std::complex<double> >(uint64_t* state) {
+  return std::complex<double>(RandomToTypeNormal<double>(state),
+                              RandomToTypeNormal<double>(state));
+}
+
+
+template <typename T> class NormalRandomGenerator {
+ public:
+  static const bool PacketAccess = true;
+
+  // Uses the given "seed" if non-zero, otherwise uses a random seed.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE NormalRandomGenerator(uint64_t seed = 0) {
+    m_state = PCG_XSH_RS_state(seed);
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE NormalRandomGenerator(
+      const NormalRandomGenerator& other) {
+    m_state = other.m_state;
+  }
+
+ template<typename Index> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  T operator()(Index i) const {
+    uint64_t local_state = m_state + i;
+    T result = RandomToTypeNormal<T>(&local_state);
+    m_state = local_state;
+    return result;
+  }
+
+  template<typename Packet, typename Index> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  Packet packetOp(Index i) const {
+    const int packetSize = internal::unpacket_traits<Packet>::size;
+    EIGEN_ALIGN_MAX T values[packetSize];
+    uint64_t local_state = m_state + i;
+    for (int j = 0; j < packetSize; ++j) {
+      values[j] = RandomToTypeNormal<T>(&local_state);
+    }
+    m_state = local_state;
+    return internal::pload<Packet>(values);
+  }
+
+ private:
+  mutable uint64_t m_state;
+};
+
+
+template <typename Scalar>
+struct functor_traits<NormalRandomGenerator<Scalar> > {
+  enum {
+    // On average, we need to generate about 3 random numbers
+    // 15 mul, 8 add, 1.5 logs
+    Cost = 3 * functor_traits<UniformRandomGenerator<Scalar> >::Cost +
+           15 * NumTraits<Scalar>::AddCost + 8 * NumTraits<Scalar>::AddCost +
+           3 * functor_traits<scalar_log_op<Scalar> >::Cost / 2,
+    PacketAccess = NormalRandomGenerator<Scalar>::PacketAccess
+  };
+};
+
+
+} // end namespace internal
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_RANDOM_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
@@ -0,0 +1,781 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+// Copyright (C) 2016 Mehdi Goli, Codeplay Software Ltd <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_REDUCTION_H
+#define EIGEN_CXX11_TENSOR_TENSOR_REDUCTION_H
+
+namespace Eigen {
+
+/** \class TensorReduction
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor reduction class.
+  *
+  */
+
+namespace internal {
+  template<typename Op, typename Dims, typename XprType,template <class> class MakePointer_ >
+  struct traits<TensorReductionOp<Op, Dims, XprType, MakePointer_> >
+ : traits<XprType>
+{
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::Scalar Scalar;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  static const int NumDimensions = XprTraits::NumDimensions - array_size<Dims>::value;
+  static const int Layout = XprTraits::Layout;
+
+  template <class T> struct MakePointer {
+    // Intermediate typedef to workaround MSVC issue.
+    typedef MakePointer_<T> MakePointerT;
+    typedef typename MakePointerT::Type Type;
+  };
+};
+
+template<typename Op, typename Dims, typename XprType, template <class> class MakePointer_>
+struct eval<TensorReductionOp<Op, Dims, XprType, MakePointer_>, Eigen::Dense>
+{
+  typedef const TensorReductionOp<Op, Dims, XprType, MakePointer_>& type;
+};
+
+template<typename Op, typename Dims, typename XprType, template <class> class MakePointer_>
+struct nested<TensorReductionOp<Op, Dims, XprType, MakePointer_>, 1, typename eval<TensorReductionOp<Op, Dims, XprType, MakePointer_> >::type>
+{
+  typedef TensorReductionOp<Op, Dims, XprType, MakePointer_> type;
+};
+
+
+template <typename OutputDims> struct DimInitializer {
+  template <typename InputDims, typename ReducedDims> EIGEN_DEVICE_FUNC
+  static void run(const InputDims& input_dims,
+                  const array<bool, internal::array_size<InputDims>::value>& reduced,
+                  OutputDims* output_dims, ReducedDims* reduced_dims) {
+    const int NumInputDims = internal::array_size<InputDims>::value;
+    int outputIndex = 0;
+    int reduceIndex = 0;
+    for (int i = 0; i < NumInputDims; ++i) {
+      if (reduced[i]) {
+        (*reduced_dims)[reduceIndex] = input_dims[i];
+        ++reduceIndex;
+      } else {
+        (*output_dims)[outputIndex] = input_dims[i];
+        ++outputIndex;
+      }
+    }
+  }
+};
+
+template <> struct DimInitializer<Sizes<> > {
+  template <typename InputDims, typename Index, size_t Rank> EIGEN_DEVICE_FUNC
+  static void run(const InputDims& input_dims, const array<bool, Rank>&,
+                  Sizes<>*, array<Index, Rank>* reduced_dims) {
+    const int NumInputDims = internal::array_size<InputDims>::value;
+    for (int i = 0; i < NumInputDims; ++i) {
+      (*reduced_dims)[i] = input_dims[i];
+    }
+  }
+};
+
+
+template <typename ReducedDims, int NumTensorDims, int Layout>
+struct are_inner_most_dims {
+  static const bool value = false;
+};
+template <typename ReducedDims, int NumTensorDims, int Layout>
+struct preserve_inner_most_dims {
+  static const bool value = false;
+};
+
+#if EIGEN_HAS_CONSTEXPR && EIGEN_HAS_VARIADIC_TEMPLATES
+template <typename ReducedDims, int NumTensorDims>
+struct are_inner_most_dims<ReducedDims, NumTensorDims, ColMajor>{
+  static const bool tmp1 = indices_statically_known_to_increase<ReducedDims>();
+  static const bool tmp2 = index_statically_eq<ReducedDims>(0, 0);
+  static const bool tmp3 = index_statically_eq<ReducedDims>(array_size<ReducedDims>::value-1, array_size<ReducedDims>::value-1);
+  static const bool value = tmp1 & tmp2 & tmp3;
+};
+template <typename ReducedDims, int NumTensorDims>
+struct are_inner_most_dims<ReducedDims, NumTensorDims, RowMajor>{
+  static const bool tmp1 = indices_statically_known_to_increase<ReducedDims>();
+  static const bool tmp2 = index_statically_eq<ReducedDims>(0, NumTensorDims - array_size<ReducedDims>::value);
+  static const bool tmp3 = index_statically_eq<ReducedDims>(array_size<ReducedDims>::value - 1, NumTensorDims - 1);
+  static const bool value = tmp1 & tmp2 & tmp3;
+
+};
+template <typename ReducedDims, int NumTensorDims>
+struct preserve_inner_most_dims<ReducedDims, NumTensorDims, ColMajor>{
+  static const bool tmp1 = indices_statically_known_to_increase<ReducedDims>();
+  static const bool tmp2 = index_statically_gt<ReducedDims>(0, 0);
+  static const bool value = tmp1 & tmp2;
+
+};
+template <typename ReducedDims, int NumTensorDims>
+struct preserve_inner_most_dims<ReducedDims, NumTensorDims, RowMajor>{
+  static const bool tmp1 = indices_statically_known_to_increase<ReducedDims>();
+  static const bool tmp2 = index_statically_lt<ReducedDims>(array_size<ReducedDims>::value - 1, NumTensorDims - 1);
+  static const bool value = tmp1 & tmp2;
+};
+#endif
+
+
+template <int DimIndex, typename Self, typename Op>
+struct GenericDimReducer {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const Self& self, typename Self::Index firstIndex, Op& reducer, typename Self::CoeffReturnType* accum) {
+    EIGEN_STATIC_ASSERT((DimIndex > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    for (int j = 0; j < self.m_reducedDims[DimIndex]; ++j) {
+      const typename Self::Index input = firstIndex + j * self.m_reducedStrides[DimIndex];
+      GenericDimReducer<DimIndex-1, Self, Op>::reduce(self, input, reducer, accum);
+    }
+  }
+};
+template <typename Self, typename Op>
+struct GenericDimReducer<0, Self, Op> {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const Self& self, typename Self::Index firstIndex, Op& reducer, typename Self::CoeffReturnType* accum) {
+    for (int j = 0; j < self.m_reducedDims[0]; ++j) {
+      const typename Self::Index input = firstIndex + j * self.m_reducedStrides[0];
+      reducer.reduce(self.m_impl.coeff(input), accum);
+    }
+  }
+};
+template <typename Self, typename Op>
+struct GenericDimReducer<-1, Self, Op> {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const Self& self, typename Self::Index index, Op& reducer, typename Self::CoeffReturnType* accum) {
+    reducer.reduce(self.m_impl.coeff(index), accum);
+  }
+};
+
+template <typename Self, typename Op, bool Vectorizable = (Self::InputPacketAccess & Op::PacketAccess)>
+struct InnerMostDimReducer {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename Self::CoeffReturnType reduce(const Self& self, typename Self::Index firstIndex, typename Self::Index numValuesToReduce, Op& reducer) {
+    typename Self::CoeffReturnType accum = reducer.initialize();
+    for (typename Self::Index j = 0; j < numValuesToReduce; ++j) {
+      reducer.reduce(self.m_impl.coeff(firstIndex + j), &accum);
+    }
+    return reducer.finalize(accum);
+  }
+};
+
+template <typename Self, typename Op>
+struct InnerMostDimReducer<Self, Op, true> {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename Self::CoeffReturnType reduce(const Self& self, typename Self::Index firstIndex, typename Self::Index numValuesToReduce, Op& reducer) {
+    const int packetSize = internal::unpacket_traits<typename Self::PacketReturnType>::size;
+    const typename Self::Index VectorizedSize = (numValuesToReduce / packetSize) * packetSize;
+    typename Self::PacketReturnType p = reducer.template initializePacket<typename Self::PacketReturnType>();
+    for (typename Self::Index j = 0; j < VectorizedSize; j += packetSize) {
+      reducer.reducePacket(self.m_impl.template packet<Unaligned>(firstIndex + j), &p);
+    }
+    typename Self::CoeffReturnType accum = reducer.initialize();
+    for (typename Self::Index j = VectorizedSize; j < numValuesToReduce; ++j) {
+      reducer.reduce(self.m_impl.coeff(firstIndex + j), &accum);
+    }
+    return reducer.finalizeBoth(accum, p);
+  }
+};
+
+template <int DimIndex, typename Self, typename Op, bool vectorizable = (Self::InputPacketAccess & Op::PacketAccess)>
+struct InnerMostDimPreserver {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const Self&, typename Self::Index, Op&, typename Self::PacketReturnType*) {
+    eigen_assert(false && "should never be called");
+  }
+};
+
+template <int DimIndex, typename Self, typename Op>
+struct InnerMostDimPreserver<DimIndex, Self, Op, true> {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const Self& self, typename Self::Index firstIndex, Op& reducer, typename Self::PacketReturnType* accum) {
+    EIGEN_STATIC_ASSERT((DimIndex > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    for (typename Self::Index j = 0; j < self.m_reducedDims[DimIndex]; ++j) {
+      const typename Self::Index input = firstIndex + j * self.m_reducedStrides[DimIndex];
+      InnerMostDimPreserver<DimIndex-1, Self, Op>::reduce(self, input, reducer, accum);
+    }
+  }
+};
+
+template <typename Self, typename Op>
+struct InnerMostDimPreserver<0, Self, Op, true> {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const Self& self, typename Self::Index firstIndex, Op& reducer, typename Self::PacketReturnType* accum) {
+    for (typename Self::Index j = 0; j < self.m_reducedDims[0]; ++j) {
+      const typename Self::Index input = firstIndex + j * self.m_reducedStrides[0];
+      reducer.reducePacket(self.m_impl.template packet<Unaligned>(input), accum);
+    }
+  }
+};
+template <typename Self, typename Op>
+struct InnerMostDimPreserver<-1, Self, Op, true> {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const Self&, typename Self::Index, Op&, typename Self::PacketReturnType*) {
+    eigen_assert(false && "should never be called");
+  }
+};
+
+// Default full reducer
+template <typename Self, typename Op, typename Device, bool Vectorizable = (Self::InputPacketAccess & Op::PacketAccess)>
+struct FullReducer {
+  static const bool HasOptimizedImplementation = false;
+
+  static EIGEN_DEVICE_FUNC void run(const Self& self, Op& reducer, const Device&, typename Self::CoeffReturnType* output) {
+    const typename Self::Index num_coeffs = array_prod(self.m_impl.dimensions());
+    *output = InnerMostDimReducer<Self, Op, Vectorizable>::reduce(self, 0, num_coeffs, reducer);
+  }
+};
+
+
+#ifdef EIGEN_USE_THREADS
+// Multithreaded full reducers
+template <typename Self, typename Op,
+          bool Vectorizable = (Self::InputPacketAccess & Op::PacketAccess)>
+struct FullReducerShard {
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Self& self, typename Self::Index firstIndex,
+                  typename Self::Index numValuesToReduce, Op& reducer,
+                  typename Self::CoeffReturnType* output) {
+    *output = InnerMostDimReducer<Self, Op, Vectorizable>::reduce(
+        self, firstIndex, numValuesToReduce, reducer);
+  }
+};
+
+// Multithreaded full reducer
+template <typename Self, typename Op, bool Vectorizable>
+struct FullReducer<Self, Op, ThreadPoolDevice, Vectorizable> {
+  static const bool HasOptimizedImplementation = !Op::IsStateful;
+  static const int PacketSize =
+      unpacket_traits<typename Self::PacketReturnType>::size;
+
+  // launch one reducer per thread and accumulate the result.
+  static void run(const Self& self, Op& reducer, const ThreadPoolDevice& device,
+                  typename Self::CoeffReturnType* output) {
+    typedef typename Self::Index Index;
+    const Index num_coeffs = array_prod(self.m_impl.dimensions());
+    if (num_coeffs == 0) {
+      *output = reducer.finalize(reducer.initialize());
+      return;
+    }
+    const TensorOpCost cost =
+        self.m_impl.costPerCoeff(Vectorizable) +
+        TensorOpCost(0, 0, internal::functor_traits<Op>::Cost, Vectorizable,
+                     PacketSize);
+    const int num_threads = TensorCostModel<ThreadPoolDevice>::numThreads(
+        num_coeffs, cost, device.numThreads());
+    if (num_threads == 1) {
+      *output =
+          InnerMostDimReducer<Self, Op, Vectorizable>::reduce(self, 0, num_coeffs, reducer);
+      return;
+    }
+    const Index blocksize =
+        std::floor<Index>(static_cast<float>(num_coeffs) / num_threads);
+    const Index numblocks = blocksize > 0 ? num_coeffs / blocksize : 0;
+    eigen_assert(num_coeffs >= numblocks * blocksize);
+
+    Barrier barrier(internal::convert_index<unsigned int>(numblocks));
+    MaxSizeVector<typename Self::CoeffReturnType> shards(numblocks, reducer.initialize());
+    for (Index i = 0; i < numblocks; ++i) {
+      device.enqueue_with_barrier(&barrier, &FullReducerShard<Self, Op, Vectorizable>::run,
+                                  self, i * blocksize, blocksize, reducer,
+                                  &shards[i]);
+    }
+    typename Self::CoeffReturnType finalShard;
+    if (numblocks * blocksize < num_coeffs) {
+      finalShard = InnerMostDimReducer<Self, Op, Vectorizable>::reduce(
+          self, numblocks * blocksize, num_coeffs - numblocks * blocksize,
+          reducer);
+    } else {
+      finalShard = reducer.initialize();
+    }
+    barrier.Wait();
+
+    for (Index i = 0; i < numblocks; ++i) {
+      reducer.reduce(shards[i], &finalShard);
+    }
+    *output = reducer.finalize(finalShard);
+  }
+};
+
+#endif
+
+
+// Default inner reducer
+template <typename Self, typename Op, typename Device>
+struct InnerReducer {
+  static const bool HasOptimizedImplementation = false;
+
+  EIGEN_DEVICE_FUNC static bool run(const Self&, Op&, const Device&, typename Self::CoeffReturnType*, typename Self::Index, typename Self::Index) {
+    eigen_assert(false && "Not implemented");
+    return true;
+  }
+};
+
+// Default outer reducer
+template <typename Self, typename Op, typename Device>
+struct OuterReducer {
+  static const bool HasOptimizedImplementation = false;
+
+  EIGEN_DEVICE_FUNC static bool run(const Self&, Op&, const Device&, typename Self::CoeffReturnType*, typename Self::Index, typename Self::Index) {
+    eigen_assert(false && "Not implemented");
+    return true;
+  }
+};
+
+
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+template <int B, int N, typename S, typename R, typename I>
+__global__ void FullReductionKernel(R, const S, I, typename S::CoeffReturnType*, unsigned int*);
+
+
+#ifdef EIGEN_HAS_CUDA_FP16
+template <typename S, typename R, typename I>
+__global__ void ReductionInitFullReduxKernelHalfFloat(R, const S, I, half2*);
+template <int B, int N, typename S, typename R, typename I>
+__global__ void FullReductionKernelHalfFloat(R, const S, I, half*, half2*);
+template <int NPT, typename S, typename R, typename I>
+__global__ void InnerReductionKernelHalfFloat(R, const S, I, I, half*);
+
+#endif
+
+template <int NPT, typename S, typename R, typename I>
+__global__ void InnerReductionKernel(R, const S, I, I, typename S::CoeffReturnType*);
+
+template <int NPT, typename S, typename R, typename I>
+__global__ void OuterReductionKernel(R, const S, I, I, typename S::CoeffReturnType*);
+#endif
+
+}  // end namespace internal
+
+
+template <typename Op, typename Dims, typename XprType,  template <class> class MakePointer_>
+class TensorReductionOp : public TensorBase<TensorReductionOp<Op, Dims, XprType, MakePointer_>, ReadOnlyAccessors> {
+  public:
+    typedef typename Eigen::internal::traits<TensorReductionOp>::Scalar Scalar;
+    typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+    typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+    typedef typename Eigen::internal::nested<TensorReductionOp>::type Nested;
+    typedef typename Eigen::internal::traits<TensorReductionOp>::StorageKind StorageKind;
+    typedef typename Eigen::internal::traits<TensorReductionOp>::Index Index;
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorReductionOp(const XprType& expr, const Dims& dims) : m_expr(expr), m_dims(dims)
+    { }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorReductionOp(const XprType& expr, const Dims& dims, const Op& reducer) : m_expr(expr), m_dims(dims), m_reducer(reducer)
+    { }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const XprType& expression() const { return m_expr; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const Dims& dims() const { return m_dims; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const Op& reducer() const { return m_reducer; }
+
+  protected:
+    typename XprType::Nested m_expr;
+    const Dims m_dims;
+    const Op m_reducer;
+};
+
+
+// Eval as rvalue
+template<typename Op, typename Dims, typename ArgType, template <class> class MakePointer_, typename Device>
+struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType, MakePointer_>, Device>
+{
+  typedef TensorReductionOp<Op, Dims, ArgType, MakePointer_> XprType;
+  typedef typename XprType::Index Index;
+  typedef ArgType ChildType;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions InputDimensions;
+  static const int NumInputDims = internal::array_size<InputDimensions>::value;
+  static const int NumReducedDims = internal::array_size<Dims>::value;
+  static const int NumOutputDims = NumInputDims - NumReducedDims;
+  typedef typename internal::conditional<NumOutputDims==0, Sizes<>, DSizes<Index, NumOutputDims> >::type Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType, MakePointer_>, Device> Self;
+  static const bool InputPacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = Self::InputPacketAccess && Op::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  static const bool ReducingInnerMostDims = internal::are_inner_most_dims<Dims, NumInputDims, Layout>::value;
+  static const bool PreservingInnerMostDims = internal::preserve_inner_most_dims<Dims, NumInputDims, Layout>::value;
+  static const bool RunningFullReduction = (NumOutputDims==0);
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_reducer(op.reducer()), m_result(NULL), m_device(device), m_xpr_dims(op.dims())
+  {
+    EIGEN_STATIC_ASSERT((NumInputDims >= NumReducedDims), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    EIGEN_STATIC_ASSERT((!ReducingInnerMostDims | !PreservingInnerMostDims | (NumReducedDims == NumInputDims)),
+                        YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    // Build the bitmap indicating if an input dimension is reduced or not.
+    for (int i = 0; i < NumInputDims; ++i) {
+      m_reduced[i] = false;
+    }
+    for (int i = 0; i < NumReducedDims; ++i) {
+      eigen_assert(op.dims()[i] >= 0);
+      eigen_assert(op.dims()[i] < NumInputDims);
+      m_reduced[op.dims()[i]] = true;
+    }
+
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    internal::DimInitializer<Dimensions>::run(input_dims, m_reduced, &m_dimensions, &m_reducedDims);
+
+    // Precompute output strides.
+    if (NumOutputDims > 0) {
+      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+        m_outputStrides[0] = 1;
+        for (int i = 1; i < NumOutputDims; ++i) {
+          m_outputStrides[i] = m_outputStrides[i - 1] * m_dimensions[i - 1];
+        }
+      } else {
+        m_outputStrides.back() = 1;
+        for (int i = NumOutputDims - 2; i >= 0; --i) {
+          m_outputStrides[i] = m_outputStrides[i + 1] * m_dimensions[i + 1];
+        }
+      }
+    }
+
+    // Precompute input strides.
+    if (NumInputDims > 0) {
+      array<Index, NumInputDims> input_strides;
+      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+        input_strides[0] = 1;
+        for (int i = 1; i < NumInputDims; ++i) {
+          input_strides[i] = input_strides[i-1] * input_dims[i-1];
+        }
+      } else {
+        input_strides.back() = 1;
+        for (int i = NumInputDims - 2; i >= 0; --i) {
+          input_strides[i] = input_strides[i + 1] * input_dims[i + 1];
+        }
+      }
+
+      int outputIndex = 0;
+      int reduceIndex = 0;
+      for (int i = 0; i < NumInputDims; ++i) {
+        if (m_reduced[i]) {
+          m_reducedStrides[reduceIndex] = input_strides[i];
+          ++reduceIndex;
+        } else {
+          m_preservedStrides[outputIndex] = input_strides[i];
+          ++outputIndex;
+        }
+      }
+    }
+
+    // Special case for full reductions
+    if (NumOutputDims == 0) {
+      m_preservedStrides[0] = internal::array_prod(input_dims);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool evalSubExprsIfNeeded(typename MakePointer_<CoeffReturnType>::Type data) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+
+    // Use the FullReducer if possible.
+    if ((RunningFullReduction && RunningOnSycl) ||(RunningFullReduction &&
+        internal::FullReducer<Self, Op, Device>::HasOptimizedImplementation &&
+        ((RunningOnGPU && (m_device.majorDeviceVersion() >= 3)) ||
+         !RunningOnGPU))) {
+      bool need_assign = false;
+      if (!data) {
+        m_result = static_cast<CoeffReturnType*>(m_device.allocate(sizeof(CoeffReturnType)));
+        data = m_result;
+        need_assign = true;
+      }
+      Op reducer(m_reducer);
+      internal::FullReducer<Self, Op, Device>::run(*this, reducer, m_device, data);
+      return need_assign;
+    }
+    else if(RunningOnSycl){
+      const Index num_values_to_reduce = internal::array_prod(m_reducedDims);
+      const Index num_coeffs_to_preserve = internal::array_prod(m_dimensions);
+      if (!data) {
+        data = static_cast<CoeffReturnType*>(m_device.allocate(sizeof(CoeffReturnType) * num_coeffs_to_preserve));
+        m_result = data;
+      }
+      Op reducer(m_reducer);
+      internal::InnerReducer<Self, Op, Device>::run(*this, reducer, m_device, data, num_values_to_reduce, num_coeffs_to_preserve);
+      return (m_result != NULL);
+    }
+
+    // Attempt to use an optimized reduction.
+    else if (RunningOnGPU && (m_device.majorDeviceVersion() >= 3)) {
+      bool reducing_inner_dims = true;
+      for (int i = 0; i < NumReducedDims; ++i) {
+        if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+          reducing_inner_dims &= m_reduced[i];
+        } else {
+          reducing_inner_dims &= m_reduced[NumInputDims - 1 - i];
+        }
+      }
+      if (internal::InnerReducer<Self, Op, Device>::HasOptimizedImplementation &&
+          (reducing_inner_dims || ReducingInnerMostDims)) {
+        const Index num_values_to_reduce = internal::array_prod(m_reducedDims);
+        const Index num_coeffs_to_preserve = internal::array_prod(m_dimensions);
+        if (!data) {
+          if (num_coeffs_to_preserve < 1024 && num_values_to_reduce > num_coeffs_to_preserve && num_values_to_reduce > 128) {
+            data = static_cast<CoeffReturnType*>(m_device.allocate(sizeof(CoeffReturnType) * num_coeffs_to_preserve));
+            m_result = data;
+          }
+          else {
+            return true;
+          }
+        }
+        Op reducer(m_reducer);
+        if (internal::InnerReducer<Self, Op, Device>::run(*this, reducer, m_device, data, num_values_to_reduce, num_coeffs_to_preserve)) {
+          if (m_result) {
+            m_device.deallocate(m_result);
+            m_result = NULL;
+          }
+          return true;
+        } else {
+          return (m_result != NULL);
+        }
+      }
+
+      bool preserving_inner_dims = true;
+      for (int i = 0; i < NumReducedDims; ++i) {
+        if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+          preserving_inner_dims &= m_reduced[NumInputDims - 1 - i];
+        } else {
+          preserving_inner_dims &= m_reduced[i];
+        }
+      }
+      if (internal::OuterReducer<Self, Op, Device>::HasOptimizedImplementation &&
+          preserving_inner_dims) {
+        const Index num_values_to_reduce = internal::array_prod(m_reducedDims);
+        const Index num_coeffs_to_preserve = internal::array_prod(m_dimensions);
+        if (!data) {
+          if (num_coeffs_to_preserve < 1024 && num_values_to_reduce > num_coeffs_to_preserve && num_values_to_reduce > 32) {
+            data = static_cast<CoeffReturnType*>(m_device.allocate(sizeof(CoeffReturnType) * num_coeffs_to_preserve));
+            m_result = data;
+          }
+          else {
+            return true;
+          }
+        }
+        Op reducer(m_reducer);
+        if (internal::OuterReducer<Self, Op, Device>::run(*this, reducer, m_device, data, num_values_to_reduce, num_coeffs_to_preserve)) {
+          if (m_result) {
+            m_device.deallocate(m_result);
+            m_result = NULL;
+          }
+          return true;
+        } else {
+          return (m_result != NULL);
+        }
+      }
+    }
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+    if (m_result) {
+      m_device.deallocate(m_result);
+      m_result = NULL;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    if ((RunningOnSycl || RunningFullReduction || RunningOnGPU) && m_result) {
+      return *(m_result + index);
+    }
+    Op reducer(m_reducer);
+    if (ReducingInnerMostDims || RunningFullReduction) {
+      const Index num_values_to_reduce =
+        (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? m_preservedStrides[0] : m_preservedStrides[NumPreservedStrides - 1];
+      return internal::InnerMostDimReducer<Self, Op>::reduce(*this, firstInput(index),
+                                                             num_values_to_reduce, reducer);
+    } else {
+      typename Self::CoeffReturnType accum = reducer.initialize();
+      internal::GenericDimReducer<NumReducedDims-1, Self, Op>::reduce(*this, firstInput(index), reducer, &accum);
+      return reducer.finalize(accum);
+    }
+  }
+
+  // TODO(bsteiner): provide a more efficient implementation.
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index + PacketSize - 1 < Index(internal::array_prod(dimensions())));
+
+    if (RunningOnGPU && m_result) {
+      return internal::pload<PacketReturnType>(m_result + index);
+    }
+
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+    if (ReducingInnerMostDims) {
+      const Index num_values_to_reduce =
+        (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? m_preservedStrides[0] : m_preservedStrides[NumPreservedStrides - 1];
+      const Index firstIndex = firstInput(index);
+      for (Index i = 0; i < PacketSize; ++i) {
+        Op reducer(m_reducer);
+        values[i] = internal::InnerMostDimReducer<Self, Op>::reduce(*this, firstIndex + i * num_values_to_reduce,
+                                                                    num_values_to_reduce, reducer);
+      }
+    } else if (PreservingInnerMostDims) {
+      const Index firstIndex = firstInput(index);
+      const int innermost_dim = (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? 0 : NumOutputDims - 1;
+      // TBD: extend this the the n innermost dimensions that we preserve.
+      if (((firstIndex % m_dimensions[innermost_dim]) + PacketSize - 1) < m_dimensions[innermost_dim]) {
+        Op reducer(m_reducer);
+        typename Self::PacketReturnType accum = reducer.template initializePacket<typename Self::PacketReturnType>();
+        internal::InnerMostDimPreserver<NumReducedDims-1, Self, Op>::reduce(*this, firstIndex, reducer, &accum);
+        return reducer.finalizePacket(accum);
+      } else {
+        for (int i = 0; i < PacketSize; ++i) {
+          values[i] = coeff(index + i);
+        }
+      }
+    } else {
+      for (int i = 0; i < PacketSize; ++i) {
+        values[i] = coeff(index + i);
+      }
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  // Must be called after evalSubExprsIfNeeded().
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    if (RunningFullReduction && m_result) {
+      return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized, PacketSize);
+    } else {
+      const Index num_values_to_reduce = internal::array_prod(m_reducedDims);
+      const double compute_cost = num_values_to_reduce * internal::functor_traits<Op>::Cost;
+      return m_impl.costPerCoeff(vectorized) * num_values_to_reduce +
+          TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC typename MakePointer_<Scalar>::Type data() const { return m_result; }
+  /// required by sycl in order to extract the accessor
+  const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+  /// added for sycl in order to construct the buffer from the sycl device
+  const Device& device() const{return m_device;}
+  /// added for sycl in order to re-construct the reduction eval on the device for the sub-kernel
+  const Dims& xprDims() const {return m_xpr_dims;}
+
+
+  private:
+  template <int, typename, typename> friend struct internal::GenericDimReducer;
+  template <typename, typename, bool> friend struct internal::InnerMostDimReducer;
+  template <int, typename, typename, bool> friend struct internal::InnerMostDimPreserver;
+  template <typename S, typename O, typename D, bool V> friend struct internal::FullReducer;
+#ifdef EIGEN_USE_THREADS
+  template <typename S, typename O, bool V> friend struct internal::FullReducerShard;
+#endif
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+  template <int B, int N, typename S, typename R, typename I> friend void internal::FullReductionKernel(R, const S, I, typename S::CoeffReturnType*, unsigned int*);
+#ifdef EIGEN_HAS_CUDA_FP16
+  template <typename S, typename R, typename I> friend void internal::ReductionInitFullReduxKernelHalfFloat(R, const S, I, half2*);
+  template <int B, int N, typename S, typename R, typename I> friend void internal::FullReductionKernelHalfFloat(R, const S, I, half*, half2*);
+  template <int NPT, typename S, typename R, typename I> friend void internal::InnerReductionKernelHalfFloat(R, const S, I, I, half*);
+#endif
+  template <int NPT, typename S, typename R, typename I> friend void internal::InnerReductionKernel(R, const S, I, I, typename S::CoeffReturnType*);
+
+  template <int NPT, typename S, typename R, typename I> friend void internal::OuterReductionKernel(R, const S, I, I, typename S::CoeffReturnType*);
+#endif
+
+  template <typename S, typename O, typename D> friend struct internal::InnerReducer;
+
+  // Returns the Index in the input tensor of the first value that needs to be
+  // used to compute the reduction at output index "index".
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index firstInput(Index index) const {
+    if (ReducingInnerMostDims) {
+      if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+        return index * m_preservedStrides[0];
+      } else {
+        return index * m_preservedStrides[NumPreservedStrides - 1];
+      }
+    }
+    // TBD: optimize the case where we preserve the innermost dimensions.
+    Index startInput = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumOutputDims - 1; i > 0; --i) {
+        // This is index_i in the output tensor.
+        const Index idx = index / m_outputStrides[i];
+        startInput += idx * m_preservedStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      if (PreservingInnerMostDims) {
+        eigen_assert(m_preservedStrides[0] == 1);
+        startInput += index;
+      } else {
+        startInput += index * m_preservedStrides[0];
+      }
+    } else {
+      for (int i = 0; i < NumOutputDims - 1; ++i) {
+        // This is index_i in the output tensor.
+        const Index idx = index / m_outputStrides[i];
+        startInput += idx * m_preservedStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      if (PreservingInnerMostDims) {
+        eigen_assert(m_preservedStrides[NumPreservedStrides - 1] == 1);
+        startInput += index;
+      } else {
+        startInput += index * m_preservedStrides[NumPreservedStrides - 1];
+      }
+    }
+    return startInput;
+  }
+
+  // Bitmap indicating if an input dimension is reduced or not.
+  array<bool, NumInputDims> m_reduced;
+  // Dimensions of the output of the operation.
+  Dimensions m_dimensions;
+  // Precomputed strides for the output tensor.
+  array<Index, NumOutputDims> m_outputStrides;
+  // Subset of strides of the input tensor for the non-reduced dimensions.
+  // Indexed by output dimensions.
+  static const int NumPreservedStrides = max_n_1<NumOutputDims>::size;
+  array<Index, NumPreservedStrides> m_preservedStrides;
+
+  // Subset of strides of the input tensor for the reduced dimensions.
+  // Indexed by reduced dimensions.
+  array<Index, NumReducedDims> m_reducedStrides;
+  // Size of the input dimensions that are reduced.
+  // Indexed by reduced dimensions.
+  array<Index, NumReducedDims> m_reducedDims;
+
+  // Evaluator for the input expression.
+  TensorEvaluator<ArgType, Device> m_impl;
+
+  // Operation to apply for computing the reduction.
+  Op m_reducer;
+
+  // For full reductions
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+  static const bool RunningOnGPU = internal::is_same<Device, Eigen::GpuDevice>::value;
+  static const bool RunningOnSycl = false;
+#elif defined(EIGEN_USE_SYCL)
+static const bool RunningOnSycl = internal::is_same<typename internal::remove_all<Device>::type, Eigen::SyclDevice>::value;
+static const bool RunningOnGPU = false;
+#else
+  static const bool RunningOnGPU = false;
+  static const bool RunningOnSycl = false;
+#endif
+  typename MakePointer_<CoeffReturnType>::Type m_result;
+
+  const Device& m_device;
+  const Dims& m_xpr_dims;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_REDUCTION_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
@@ -0,0 +1,750 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_REDUCTION_CUDA_H
+#define EIGEN_CXX11_TENSOR_TENSOR_REDUCTION_CUDA_H
+
+namespace Eigen {
+namespace internal {
+
+
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+// Full reducers for GPU, don't vectorize for now
+
+// Reducer function that enables multiple cuda thread to safely accumulate at the same
+// output address. It basically reads the current value of the output variable, and
+// attempts to update it with the new value. If in the meantime another cuda thread
+// updated the content of the output address it will try again.
+template <typename T, typename R>
+__device__ EIGEN_ALWAYS_INLINE void atomicReduce(T* output, T accum, R& reducer) {
+#if __CUDA_ARCH__ >= 300
+  if (sizeof(T) == 4)
+  {
+    unsigned int oldval = *reinterpret_cast<unsigned int*>(output);
+    unsigned int newval = oldval;
+    reducer.reduce(accum, reinterpret_cast<T*>(&newval));
+    if (newval == oldval) {
+      return;
+    }
+    unsigned int readback;
+    while ((readback = atomicCAS((unsigned int*)output, oldval, newval)) != oldval) {
+      oldval = readback;
+      newval = oldval;
+      reducer.reduce(accum, reinterpret_cast<T*>(&newval));
+      if (newval == oldval) {
+        return;
+      }
+    }
+  }
+  else if (sizeof(T) == 8) {
+    unsigned long long oldval = *reinterpret_cast<unsigned long long*>(output);
+    unsigned long long newval = oldval;
+    reducer.reduce(accum, reinterpret_cast<T*>(&newval));
+    if (newval == oldval) {
+      return;
+    }
+    unsigned long long readback;
+    while ((readback = atomicCAS((unsigned long long*)output, oldval, newval)) != oldval) {
+      oldval = readback;
+      newval = oldval;
+      reducer.reduce(accum, reinterpret_cast<T*>(&newval));
+      if (newval == oldval) {
+        return;
+      }
+    }
+  }
+  else {
+    assert(0 && "Wordsize not supported");
+  }
+#else
+  assert(0 && "Shouldn't be called on unsupported device");
+#endif
+}
+
+// We extend atomicExch to support extra data types
+template <typename Type>
+__device__ inline Type atomicExchCustom(Type* address, Type val) {
+  return atomicExch(address, val);
+}
+
+template <>
+__device__ inline double atomicExchCustom(double* address, double val) {
+  unsigned long long int* address_as_ull = reinterpret_cast<unsigned long long int*>(address);
+  return __longlong_as_double(atomicExch(address_as_ull, __double_as_longlong(val)));
+}
+
+#ifdef EIGEN_HAS_CUDA_FP16
+template <template <typename T> class R>
+__device__ inline void atomicReduce(half2* output, half2 accum, R<half>& reducer) {
+  unsigned int oldval = *reinterpret_cast<unsigned int*>(output);
+  unsigned int newval = oldval;
+  reducer.reducePacket(accum, reinterpret_cast<half2*>(&newval));
+  if (newval == oldval) {
+    return;
+  }
+  unsigned int readback;
+  while ((readback = atomicCAS((unsigned int*)output, oldval, newval)) != oldval) {
+    oldval = readback;
+    newval = oldval;
+    reducer.reducePacket(accum, reinterpret_cast<half2*>(&newval));
+    if (newval == oldval) {
+      return;
+    }
+  }
+}
+#endif
+
+template <>
+__device__ inline void atomicReduce(float* output, float accum, SumReducer<float>&) {
+#if __CUDA_ARCH__ >= 300
+  atomicAdd(output, accum);
+#else
+  assert(0 && "Shouldn't be called on unsupported device");
+#endif
+}
+
+
+template <typename CoeffType, typename Index>
+__global__ void ReductionInitKernel(const CoeffType val, Index num_preserved_coeffs, CoeffType* output) {
+  const Index thread_id = blockIdx.x * blockDim.x + threadIdx.x;
+  const Index num_threads = blockDim.x * gridDim.x;
+  for (Index i = thread_id; i < num_preserved_coeffs; i += num_threads) {
+    output[i] = val;
+  }
+}
+
+
+template <int BlockSize, int NumPerThread, typename Self,
+          typename Reducer, typename Index>
+__global__ void FullReductionKernel(Reducer reducer, const Self input, Index num_coeffs,
+                                    typename Self::CoeffReturnType* output, unsigned int* semaphore) {
+#if __CUDA_ARCH__ >= 300
+  // Initialize the output value
+  const Index first_index = blockIdx.x * BlockSize * NumPerThread + threadIdx.x;
+  if (gridDim.x == 1) {
+    if (first_index == 0) {
+      *output = reducer.initialize();
+    }
+  }
+  else {
+    if (threadIdx.x == 0) {
+      unsigned int block = atomicCAS(semaphore, 0u, 1u);
+      if (block == 0) {
+        // We're the first block to run, initialize the output value
+        atomicExchCustom(output, reducer.initialize());
+        __threadfence();
+        atomicExch(semaphore, 2u);
+      }
+      else {
+        // Wait for the first block to initialize the output value.
+        // Use atomicCAS here to ensure that the reads aren't cached
+        unsigned int val;
+        do {
+          val = atomicCAS(semaphore, 2u, 2u);
+        }
+        while (val < 2u);
+      }
+    }
+  }
+
+  __syncthreads();
+
+  eigen_assert(gridDim.x == 1 || *semaphore >= 2u);
+
+  typename Self::CoeffReturnType accum = reducer.initialize();
+  Index max_iter = numext::mini<Index>(num_coeffs - first_index, NumPerThread*BlockSize);
+  for (Index i = 0; i < max_iter; i+=BlockSize) {
+    const Index index = first_index + i;
+    eigen_assert(index < num_coeffs);
+    typename Self::CoeffReturnType val = input.m_impl.coeff(index);
+    reducer.reduce(val, &accum);
+  }
+
+#pragma unroll
+  for (int offset = warpSize/2; offset > 0; offset /= 2) {
+    reducer.reduce(__shfl_down(accum, offset, warpSize), &accum);
+  }
+
+  if ((threadIdx.x & (warpSize - 1)) == 0) {
+    atomicReduce(output, accum, reducer);
+  }
+
+  if (gridDim.x > 1 && threadIdx.x == 0) {
+    // Let the last block reset the semaphore
+    atomicInc(semaphore, gridDim.x + 1);
+  }
+#else
+  assert(0 && "Shouldn't be called on unsupported device");
+#endif
+}
+
+
+#ifdef EIGEN_HAS_CUDA_FP16
+template <typename Self,
+          typename Reducer, typename Index>
+__global__ void ReductionInitFullReduxKernelHalfFloat(Reducer reducer, const Self input, Index num_coeffs, half2* scratch) {
+  eigen_assert(blockDim.x == 1);
+  eigen_assert(gridDim.x == 1);
+  if (num_coeffs % 2 != 0) {
+    half last = input.m_impl.coeff(num_coeffs-1);
+    *scratch = __halves2half2(last, reducer.initialize());
+  } else {
+    *scratch = reducer.template initializePacket<half2>();
+  }
+}
+
+template <typename Self,
+          typename Reducer, typename Index>
+__global__ void ReductionInitKernelHalfFloat(Reducer reducer, const Self input, Index num_coeffs, half* output) {
+  const Index thread_id = blockIdx.x * blockDim.x + threadIdx.x;
+  const Index num_threads = blockDim.x * gridDim.x;
+  const Index num_packets = num_coeffs / 2;
+  for (Index i = thread_id; i < num_packets; i += num_threads) {
+    ((half2*)output)[i] = reducer.template initializePacket<half2>();
+  }
+
+  if (thread_id == 0 && num_coeffs % 2 != 0) {
+    output[num_coeffs-1] = reducer.initialize();
+  }
+}
+
+template <int BlockSize, int NumPerThread, typename Self,
+          typename Reducer, typename Index>
+__global__ void FullReductionKernelHalfFloat(Reducer reducer, const Self input, Index num_coeffs,
+                                    half* output, half2* scratch) {
+  eigen_assert(NumPerThread % 2 == 0);
+
+  const Index first_index = blockIdx.x * BlockSize * NumPerThread + 2*threadIdx.x;
+
+  // Initialize the output value if it wasn't initialized by the ReductionInitKernel
+  if (gridDim.x == 1 && first_index == 0) {
+    if (num_coeffs % 2 != 0) {
+      half last = input.m_impl.coeff(num_coeffs-1);
+      *scratch = __halves2half2(last, reducer.initialize());
+    } else {
+      *scratch = reducer.template initializePacket<half2>();
+    }
+    __syncthreads();
+  }
+
+  half2 accum = reducer.template initializePacket<half2>();
+  const Index max_iter = numext::mini<Index>((num_coeffs - first_index) / 2, NumPerThread*BlockSize / 2);
+  for (Index i = 0; i < max_iter; i += BlockSize) {
+    const Index index = first_index + 2*i;
+    eigen_assert(index + 1 < num_coeffs);
+    half2 val = input.m_impl.template packet<Unaligned>(index);
+    reducer.reducePacket(val, &accum);
+  }
+
+#pragma unroll
+  for (int offset = warpSize/2; offset > 0; offset /= 2) {
+    reducer.reducePacket(__shfl_down(accum, offset, warpSize), &accum);
+  }
+
+  if ((threadIdx.x & (warpSize - 1)) == 0) {
+    atomicReduce(scratch, accum, reducer);
+  }
+
+  __syncthreads();
+
+  if (gridDim.x == 1 && first_index == 0) {
+    half tmp = __low2half(*scratch);
+    reducer.reduce(__high2half(*scratch), &tmp);
+    *output = tmp;
+  }
+}
+
+template <typename Op>
+__global__ void ReductionCleanupKernelHalfFloat(Op& reducer, half* output, half2* scratch) {
+  eigen_assert(threadIdx.x == 1);
+  half tmp = __low2half(*scratch);
+  reducer.reduce(__high2half(*scratch), &tmp);
+  *output = tmp;
+}
+
+#endif
+
+template <typename Self, typename Op, typename OutputType, bool PacketAccess, typename Enabled = void>
+struct FullReductionLauncher {
+  static void run(const Self&, Op&, const GpuDevice&, OutputType*, typename Self::Index) {
+    assert(false && "Should only be called on doubles, floats and half floats");
+  }
+};
+
+// Specialization for float and double
+template <typename Self, typename Op, typename OutputType, bool PacketAccess>
+struct FullReductionLauncher<
+    Self, Op, OutputType, PacketAccess,
+    typename internal::enable_if<
+      internal::is_same<float, OutputType>::value ||
+      internal::is_same<double, OutputType>::value,
+    void>::type> {
+  static void run(const Self& self, Op& reducer, const GpuDevice& device, OutputType* output, typename Self::Index num_coeffs) {
+    typedef typename Self::Index Index;
+    typedef typename Self::CoeffReturnType Scalar;
+    const int block_size = 256;
+    const int num_per_thread = 128;
+    const int num_blocks = divup<int>(num_coeffs, block_size * num_per_thread);
+
+    unsigned int* semaphore = NULL;
+    if (num_blocks > 1) {
+      semaphore = device.semaphore();
+    }
+
+    LAUNCH_CUDA_KERNEL((FullReductionKernel<block_size, num_per_thread, Self, Op, Index>),
+                       num_blocks, block_size, 0, device, reducer, self, num_coeffs, output, semaphore);
+  }
+};
+
+#ifdef EIGEN_HAS_CUDA_FP16
+template <typename Self, typename Op>
+struct FullReductionLauncher<Self, Op, Eigen::half, false> {
+  static void run(const Self&, Op&, const GpuDevice&, half*, typename Self::Index) {
+    assert(false && "Should not be called since there is no packet accessor");
+  }
+};
+
+template <typename Self, typename Op>
+struct FullReductionLauncher<Self, Op, Eigen::half, true> {
+  static void run(const Self& self, Op& reducer, const GpuDevice& device, half* output, typename Self::Index num_coeffs) {
+    typedef typename Self::Index Index;
+
+    const int block_size = 256;
+    const int num_per_thread = 128;
+    const int num_blocks = divup<int>(num_coeffs, block_size * num_per_thread);
+    half2* scratch = static_cast<half2*>(device.scratchpad());
+
+    if (num_blocks > 1) {
+      // We initialize the output and the scrathpad outside the reduction kernel when we can't be sure that there
+      // won't be a race conditions between multiple thread blocks.
+      LAUNCH_CUDA_KERNEL((ReductionInitFullReduxKernelHalfFloat<Self, Op, Index>),
+                         1, 1, 0, device, reducer, self, num_coeffs, scratch);
+    }
+
+    LAUNCH_CUDA_KERNEL((FullReductionKernelHalfFloat<block_size, num_per_thread, Self, Op, Index>),
+                       num_blocks, block_size, 0, device, reducer, self, num_coeffs, output, scratch);
+
+    if (num_blocks > 1) {
+      LAUNCH_CUDA_KERNEL((ReductionCleanupKernelHalfFloat<Op>),
+                         1, 1, 0, device, reducer, output, scratch);
+    }
+  }
+};
+#endif
+
+
+template <typename Self, typename Op, bool Vectorizable>
+struct FullReducer<Self, Op, GpuDevice, Vectorizable> {
+  // Unfortunately nvidia doesn't support well exotic types such as complex,
+  // so reduce the scope of the optimized version of the code to the simple cases
+  // of doubles, floats and half floats
+#ifdef EIGEN_HAS_CUDA_FP16
+  static const bool HasOptimizedImplementation = !Op::IsStateful &&
+      (internal::is_same<typename Self::CoeffReturnType, float>::value ||
+       internal::is_same<typename Self::CoeffReturnType, double>::value ||
+       (internal::is_same<typename Self::CoeffReturnType, Eigen::half>::value && reducer_traits<Op, GpuDevice>::PacketAccess));
+#else
+  static const bool HasOptimizedImplementation = !Op::IsStateful &&
+                                                (internal::is_same<typename Self::CoeffReturnType, float>::value ||
+                                                 internal::is_same<typename Self::CoeffReturnType, double>::value);
+#endif
+
+  template <typename OutputType>
+  static void run(const Self& self, Op& reducer, const GpuDevice& device, OutputType* output) {
+    assert(HasOptimizedImplementation && "Should only be called on doubles, floats or half floats");
+    const Index num_coeffs = array_prod(self.m_impl.dimensions());
+    // Don't crash when we're called with an input tensor of size 0.
+    if (num_coeffs == 0) {
+      return;
+    }
+
+    FullReductionLauncher<Self, Op, OutputType, reducer_traits<Op, GpuDevice>::PacketAccess>::run(self, reducer, device, output, num_coeffs);
+  }
+};
+
+
+template <int NumPerThread, typename Self,
+          typename Reducer, typename Index>
+__global__ void InnerReductionKernel(Reducer reducer, const Self input, Index num_coeffs_to_reduce, Index num_preserved_coeffs,
+                                         typename Self::CoeffReturnType* output) {
+#if __CUDA_ARCH__ >= 300
+  typedef typename Self::CoeffReturnType Type;
+  eigen_assert(blockDim.y == 1);
+  eigen_assert(blockDim.z == 1);
+  eigen_assert(gridDim.y == 1);
+  eigen_assert(gridDim.z == 1);
+
+  const int unroll_times = 16;
+  eigen_assert(NumPerThread % unroll_times == 0);
+
+  const Index input_col_blocks = divup<Index>(num_coeffs_to_reduce, blockDim.x * NumPerThread);
+  const Index num_input_blocks = input_col_blocks * num_preserved_coeffs;
+
+  const Index num_threads = blockDim.x * gridDim.x;
+  const Index thread_id = blockIdx.x * blockDim.x + threadIdx.x;
+
+  // Initialize the output values if they weren't initialized by the ReductionInitKernel
+  if (gridDim.x == 1) {
+    for (Index i = thread_id; i < num_preserved_coeffs; i += num_threads) {
+      output[i] = reducer.initialize();
+    }
+    __syncthreads();
+  }
+
+  for (Index i = blockIdx.x; i < num_input_blocks; i += gridDim.x) {
+    const Index row = i / input_col_blocks;
+
+    if (row < num_preserved_coeffs) {
+      const Index col_block = i % input_col_blocks;
+      const Index col_begin = col_block * blockDim.x * NumPerThread + threadIdx.x;
+
+      Type reduced_val = reducer.initialize();
+
+      for (Index j = 0; j < NumPerThread; j += unroll_times) {
+        const Index last_col = col_begin + blockDim.x * (j + unroll_times - 1);
+        if (last_col >= num_coeffs_to_reduce) {
+          for (Index col = col_begin + blockDim.x * j; col < num_coeffs_to_reduce; col += blockDim.x) {
+            const Type val = input.m_impl.coeff(row * num_coeffs_to_reduce + col);
+            reducer.reduce(val, &reduced_val);
+          }
+          break;
+        } else {
+          // Faster version of the loop with no branches after unrolling.
+#pragma unroll
+          for (int k = 0; k < unroll_times; ++k) {
+            const Index col = col_begin + blockDim.x * (j + k);
+            reducer.reduce(input.m_impl.coeff(row * num_coeffs_to_reduce + col), &reduced_val);
+          }
+        }
+      }
+
+#pragma unroll
+      for (int offset = warpSize/2; offset > 0; offset /= 2) {
+        reducer.reduce(__shfl_down(reduced_val, offset), &reduced_val);
+      }
+
+      if ((threadIdx.x & (warpSize - 1)) == 0) {
+        atomicReduce(&(output[row]), reduced_val, reducer);
+      }
+    }
+  }
+#else
+  assert(0 && "Shouldn't be called on unsupported device");
+#endif
+}
+
+#ifdef EIGEN_HAS_CUDA_FP16
+
+template <int NumPerThread, typename Self,
+          typename Reducer, typename Index>
+__global__ void InnerReductionKernelHalfFloat(Reducer reducer, const Self input, Index num_coeffs_to_reduce, Index num_preserved_coeffs,
+                                              half* output) {
+  eigen_assert(blockDim.y == 1);
+  eigen_assert(blockDim.z == 1);
+  eigen_assert(gridDim.y == 1);
+  eigen_assert(gridDim.z == 1);
+
+  const int unroll_times = 16;
+  eigen_assert(NumPerThread % unroll_times == 0);
+  eigen_assert(unroll_times % 2 == 0);
+
+  const Index input_col_blocks = divup<Index>(num_coeffs_to_reduce, blockDim.x * NumPerThread * 2);
+  const Index num_input_blocks = divup<Index>(input_col_blocks * num_preserved_coeffs, 2);
+
+  const Index num_threads = blockDim.x * gridDim.x;
+  const Index thread_id = blockIdx.x * blockDim.x + threadIdx.x;
+
+  // Initialize the output values if they weren't initialized by the ReductionInitKernel
+  if (gridDim.x == 1) {
+    Index i = 2*thread_id;
+    for (; i + 1 < num_preserved_coeffs; i += 2*num_threads) {
+      half* loc = output + i;
+      *((half2*)loc) = reducer.template initializePacket<half2>();
+    }
+    if (i < num_preserved_coeffs) {
+      output[i] = reducer.initialize();
+    }
+    __syncthreads();
+  }
+
+  for (Index i = blockIdx.x; i < num_input_blocks; i += gridDim.x) {
+    const Index row = 2 * (i / input_col_blocks);
+
+    if (row + 1 < num_preserved_coeffs) {
+      const Index col_block = i % input_col_blocks;
+      const Index col_begin = 2 * (col_block * blockDim.x * NumPerThread + threadIdx.x);
+
+      half2 reduced_val1 = reducer.template initializePacket<half2>();
+      half2 reduced_val2 = reducer.template initializePacket<half2>();
+
+      for (Index j = 0; j < NumPerThread; j += unroll_times) {
+        const Index last_col = col_begin + blockDim.x * (j + unroll_times - 1) * 2;
+        if (last_col >= num_coeffs_to_reduce) {
+          Index col = col_begin + blockDim.x * j;
+          for (; col + 1 < num_coeffs_to_reduce; col += blockDim.x) {
+            const half2 val1 = input.m_impl.template packet<Unaligned>(row * num_coeffs_to_reduce + col);
+            reducer.reducePacket(val1, &reduced_val1);
+            const half2 val2 = input.m_impl.template packet<Unaligned>((row+1) * num_coeffs_to_reduce + col);
+            reducer.reducePacket(val2, &reduced_val2);
+          }
+          if (col < num_coeffs_to_reduce) {
+            // Peel;
+            const half last1 = input.m_impl.coeff(row * num_coeffs_to_reduce + col);
+            const half2 val1 = __halves2half2(last1, reducer.initialize());
+            reducer.reducePacket(val1, &reduced_val1);
+            const half last2 = input.m_impl.coeff((row+1) * num_coeffs_to_reduce + col);
+            const half2 val2 = __halves2half2(last2, reducer.initialize());
+            reducer.reducePacket(val2, &reduced_val2);
+          }
+          break;
+        } else {
+          // Faster version of the loop with no branches after unrolling.
+#pragma unroll
+          for (int k = 0; k < unroll_times; ++k) {
+            const Index col = col_begin + blockDim.x * (j + k) * 2;
+            reducer.reducePacket(input.m_impl.template packet<Unaligned>(row * num_coeffs_to_reduce + col), &reduced_val1);
+            reducer.reducePacket(input.m_impl.template packet<Unaligned>((row + 1)* num_coeffs_to_reduce + col), &reduced_val2);
+          }
+        }
+      }
+
+#pragma unroll
+      for (int offset = warpSize/2; offset > 0; offset /= 2) {
+        reducer.reducePacket(__shfl_down(reduced_val1, offset, warpSize), &reduced_val1);
+        reducer.reducePacket(__shfl_down(reduced_val2, offset, warpSize), &reduced_val2);
+      }
+
+      half val1 =  __low2half(reduced_val1);
+      reducer.reduce(__high2half(reduced_val1), &val1);
+      half val2 =  __low2half(reduced_val2);
+      reducer.reduce(__high2half(reduced_val2), &val2);
+      half2 val = __halves2half2(val1, val2);
+
+      if ((threadIdx.x & (warpSize - 1)) == 0) {
+        half* loc = output + row;
+        atomicReduce((half2*)loc, val, reducer);
+      }
+    }
+  }
+}
+
+#endif
+
+template <typename Self, typename Op, typename OutputType, bool PacketAccess, typename Enabled = void>
+struct InnerReductionLauncher {
+  static EIGEN_DEVICE_FUNC bool run(const Self&, Op&, const GpuDevice&, OutputType*, typename Self::Index, typename Self::Index) {
+    assert(false && "Should only be called to reduce doubles, floats and half floats on a gpu device");
+    return true;
+  }
+};
+
+// Specialization for float and double
+template <typename Self, typename Op, typename OutputType, bool PacketAccess>
+struct InnerReductionLauncher<
+  Self, Op, OutputType, PacketAccess,
+  typename internal::enable_if<
+    internal::is_same<float, OutputType>::value ||
+    internal::is_same<double, OutputType>::value,
+  void>::type> {
+  static bool run(const Self& self, Op& reducer, const GpuDevice& device, OutputType* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
+    typedef typename Self::Index Index;
+
+    const Index num_coeffs = num_coeffs_to_reduce * num_preserved_vals;
+    const int block_size = 256;
+    const int num_per_thread = 128;
+    const int dyn_blocks = divup<int>(num_coeffs, block_size * num_per_thread);
+    const int max_blocks = device.getNumCudaMultiProcessors() *
+                           device.maxCudaThreadsPerMultiProcessor() / block_size;
+    const int num_blocks = numext::mini<int>(max_blocks, dyn_blocks);
+
+    if (num_blocks > 1) {
+      // We initialize the outputs outside the reduction kernel when we can't be sure that there
+      // won't be a race conditions between multiple thread blocks.
+      const int dyn_blocks = divup<int>(num_preserved_vals, 1024);
+      const int max_blocks = device.getNumCudaMultiProcessors() *
+                           device.maxCudaThreadsPerMultiProcessor() / 1024;
+      const int num_blocks = numext::mini<int>(max_blocks, dyn_blocks);
+      LAUNCH_CUDA_KERNEL((ReductionInitKernel<OutputType, Index>),
+                         num_blocks, 1024, 0, device, reducer.initialize(),
+                         num_preserved_vals, output);
+    }
+
+    LAUNCH_CUDA_KERNEL((InnerReductionKernel<num_per_thread, Self, Op, Index>),
+                       num_blocks, block_size, 0, device, reducer, self, num_coeffs_to_reduce, num_preserved_vals, output);
+
+    return false;
+  }
+};
+
+#ifdef EIGEN_HAS_CUDA_FP16
+template <typename Self, typename Op>
+struct InnerReductionLauncher<Self, Op, Eigen::half, false> {
+  static bool run(const Self&, Op&, const GpuDevice&, half*, typename Self::Index, typename Self::Index) {
+    assert(false && "Should not be called since there is no packet accessor");
+    return true;
+  }
+};
+
+template <typename Self, typename Op>
+struct InnerReductionLauncher<Self, Op, Eigen::half, true> {
+  static bool run(const Self& self, Op& reducer, const GpuDevice& device, half* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
+    typedef typename Self::Index Index;
+
+    if (num_preserved_vals % 2 != 0) {
+      // Not supported yet, revert to the slower code path
+      return true;
+    }
+
+    const Index num_coeffs = num_coeffs_to_reduce * num_preserved_vals;
+    const int block_size = /*256*/128;
+    const int num_per_thread = /*128*/64;
+    const int dyn_blocks = divup<int>(num_coeffs, block_size * num_per_thread);
+    const int max_blocks = device.getNumCudaMultiProcessors() *
+                           device.maxCudaThreadsPerMultiProcessor() / block_size;
+    const int num_blocks = numext::mini<int>(max_blocks, dyn_blocks);
+
+    if (num_blocks > 1) {
+      // We initialize the outputs outside the reduction kernel when we can't be sure that there
+      // won't be a race conditions between multiple thread blocks.
+      const int dyn_blocks = divup<int>(num_preserved_vals, 1024);
+      const int max_blocks = device.getNumCudaMultiProcessors() *
+                           device.maxCudaThreadsPerMultiProcessor() / 1024;
+      const int num_blocks = numext::mini<int>(max_blocks, dyn_blocks);
+      LAUNCH_CUDA_KERNEL((ReductionInitKernelHalfFloat<Self, Op, Index>),
+                         1, 1, 0, device, reducer, self, num_preserved_vals, output);
+    }
+
+    LAUNCH_CUDA_KERNEL((InnerReductionKernelHalfFloat<num_per_thread, Self, Op, Index>),
+                       num_blocks, block_size, 0, device, reducer, self, num_coeffs_to_reduce, num_preserved_vals, output);
+
+    return false;
+  }
+};
+#endif
+
+
+template <typename Self, typename Op>
+struct InnerReducer<Self, Op, GpuDevice> {
+  // Unfortunately nvidia doesn't support well exotic types such as complex,
+  // so reduce the scope of the optimized version of the code to the simple case
+  // of floats and half floats.
+#ifdef EIGEN_HAS_CUDA_FP16
+  static const bool HasOptimizedImplementation = !Op::IsStateful &&
+      (internal::is_same<typename Self::CoeffReturnType, float>::value ||
+       internal::is_same<typename Self::CoeffReturnType, double>::value ||
+       (internal::is_same<typename Self::CoeffReturnType, Eigen::half>::value && reducer_traits<Op, GpuDevice>::PacketAccess));
+#else
+  static const bool HasOptimizedImplementation = !Op::IsStateful &&
+                                                 (internal::is_same<typename Self::CoeffReturnType, float>::value ||
+                                                  internal::is_same<typename Self::CoeffReturnType, double>::value);
+#endif
+
+  template <typename OutputType>
+  static bool run(const Self& self, Op& reducer, const GpuDevice& device, OutputType* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
+    assert(HasOptimizedImplementation && "Should only be called on doubles, floats or half floats");
+    const Index num_coeffs = array_prod(self.m_impl.dimensions());
+    // Don't crash when we're called with an input tensor of size 0.
+    if (num_coeffs == 0) {
+      return true;
+    }
+    // It's faster to use the usual code.
+    if (num_coeffs_to_reduce <= 128) {
+      return true;
+    }
+
+    return InnerReductionLauncher<Self, Op, OutputType, reducer_traits<Op, GpuDevice>::PacketAccess>::run(self, reducer, device, output, num_coeffs_to_reduce, num_preserved_vals);
+  }
+};
+
+template <int NumPerThread, typename Self,
+          typename Reducer, typename Index>
+__global__ void OuterReductionKernel(Reducer reducer, const Self input, Index num_coeffs_to_reduce, Index num_preserved_coeffs,
+                                     typename Self::CoeffReturnType* output) {
+  const Index num_threads = blockDim.x * gridDim.x;
+  const Index thread_id = blockIdx.x * blockDim.x + threadIdx.x;
+  // Initialize the output values if they weren't initialized by the ReductionInitKernel
+  if (gridDim.x == 1) {
+    for (Index i = thread_id; i < num_preserved_coeffs; i += num_threads) {
+      output[i] = reducer.initialize();
+    }
+    __syncthreads();
+  }
+
+  // Do the reduction.
+  const Index max_iter = num_preserved_coeffs * divup<Index>(num_coeffs_to_reduce, NumPerThread);
+  for (Index i = thread_id; i < max_iter; i += num_threads) {
+    const Index input_col = i % num_preserved_coeffs;
+    const Index input_row = (i / num_preserved_coeffs) * NumPerThread;
+    typename Self::CoeffReturnType reduced_val = reducer.initialize();
+    const Index max_row = numext::mini(input_row + NumPerThread, num_coeffs_to_reduce);
+    for (Index j = input_row; j < max_row; j++) {
+      typename Self::CoeffReturnType val = input.m_impl.coeff(j * num_preserved_coeffs + input_col);
+      reducer.reduce(val, &reduced_val);
+    }
+    atomicReduce(&(output[input_col]), reduced_val, reducer);
+  }
+}
+
+
+template <typename Self, typename Op>
+struct OuterReducer<Self, Op, GpuDevice> {
+  // Unfortunately nvidia doesn't support well exotic types such as complex,
+  // so reduce the scope of the optimized version of the code to the simple case
+  // of floats.
+  static const bool HasOptimizedImplementation = !Op::IsStateful &&
+                                                 (internal::is_same<typename Self::CoeffReturnType, float>::value ||
+                                                  internal::is_same<typename Self::CoeffReturnType, double>::value);
+  template <typename Device, typename OutputType>
+  static EIGEN_DEVICE_FUNC bool run(const Self&, Op&, const Device&, OutputType*, typename Self::Index, typename Self::Index) {
+    assert(false && "Should only be called to reduce doubles or floats on a gpu device");
+    return true;
+  }
+
+  static bool run(const Self& self, Op& reducer, const GpuDevice& device, float* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
+    typedef typename Self::Index Index;
+
+    // It's faster to use the usual code.
+    if (num_coeffs_to_reduce <= 32) {
+      return true;
+    }
+
+    const Index num_coeffs = num_coeffs_to_reduce * num_preserved_vals;
+    const int block_size = 256;
+    const int num_per_thread = 16;
+    const int dyn_blocks = divup<int>(num_coeffs, block_size * num_per_thread);
+    const int max_blocks = device.getNumCudaMultiProcessors() *
+                           device.maxCudaThreadsPerMultiProcessor() / block_size;
+    const int num_blocks = numext::mini<int>(max_blocks, dyn_blocks);
+
+    if (num_blocks > 1) {
+      // We initialize the outputs in the reduction kernel itself when we don't have to worry
+      // about race conditions between multiple thread blocks.
+      const int dyn_blocks = divup<int>(num_preserved_vals, 1024);
+      const int max_blocks = device.getNumCudaMultiProcessors() *
+                             device.maxCudaThreadsPerMultiProcessor() / 1024;
+      const int num_blocks = numext::mini<int>(max_blocks, dyn_blocks);
+      LAUNCH_CUDA_KERNEL((ReductionInitKernel<float, Index>),
+                         num_blocks, 1024, 0, device, reducer.initialize(),
+                         num_preserved_vals, output);
+    }
+
+    LAUNCH_CUDA_KERNEL((OuterReductionKernel<num_per_thread, Self, Op, Index>),
+                       num_blocks, block_size, 0, device, reducer, self, num_coeffs_to_reduce, num_preserved_vals, output);
+
+    return false;
+  }
+};
+
+#endif
+
+
+} // end namespace internal
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_REDUCTION_CUDA_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReductionSycl.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReductionSycl.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReductionSycl.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReductionSycl.h
@@ -0,0 +1,242 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensorSyclPlaceHolderExpr.h
+ *
+ * \brief:
+ *  This is the specialisation of the placeholder expression based on the
+ * operation type
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSOR_REDUCTION_SYCL_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSOR_REDUCTION_SYCL_HPP
+
+namespace Eigen {
+namespace internal {
+
+template<typename CoeffReturnType, typename KernelName> struct syclGenericBufferReducer{
+template<typename BufferTOut, typename BufferTIn>
+static void run(BufferTOut* bufOut, BufferTIn& bufI, const Eigen::SyclDevice& dev, size_t length, size_t local){
+  do {
+          auto f = [length, local, bufOut, &bufI](cl::sycl::handler& h) mutable {
+            cl::sycl::nd_range<1> r{cl::sycl::range<1>{std::max(length, local)},
+                                    cl::sycl::range<1>{std::min(length, local)}};
+            /* Two accessors are used: one to the buffer that is being reduced,
+             * and a second to local memory, used to store intermediate data. */
+            auto aI =
+                bufI.template get_access<cl::sycl::access::mode::read_write>(h);
+            auto aOut =
+                bufOut->template get_access<cl::sycl::access::mode::discard_write>(h);
+            cl::sycl::accessor<CoeffReturnType, 1, cl::sycl::access::mode::read_write,
+                               cl::sycl::access::target::local>
+                scratch(cl::sycl::range<1>(local), h);
+
+            /* The parallel_for invocation chosen is the variant with an nd_item
+             * parameter, since the code requires barriers for correctness. */
+            h.parallel_for<KernelName>(
+                r, [aOut, aI, scratch, local, length](cl::sycl::nd_item<1> id) {
+                  size_t globalid = id.get_global(0);
+                  size_t localid = id.get_local(0);
+                  /* All threads collectively read from global memory into local.
+                   * The barrier ensures all threads' IO is resolved before
+                   * execution continues (strictly speaking, all threads within
+                   * a single work-group - there is no co-ordination between
+                   * work-groups, only work-items). */
+                  if (globalid < length) {
+                    scratch[localid] = aI[globalid];
+                  }
+                  id.barrier(cl::sycl::access::fence_space::local_space);
+
+                  /* Apply the reduction operation between the current local
+                   * id and the one on the other half of the vector. */
+                  if (globalid < length) {
+                    int min = (length < local) ? length : local;
+                    for (size_t offset = min / 2; offset > 0; offset /= 2) {
+                      if (localid < offset) {
+                        scratch[localid] += scratch[localid + offset];
+                      }
+                      id.barrier(cl::sycl::access::fence_space::local_space);
+                    }
+                    /* The final result will be stored in local id 0. */
+                    if (localid == 0) {
+                      aI[id.get_group(0)] = scratch[localid];
+                      if((length<=local) && globalid ==0){
+                        aOut[globalid]=scratch[localid];
+                      }
+                    }
+                  }
+                });
+          };
+            dev.m_queue.submit(f);
+            dev.m_queue.throw_asynchronous();
+
+          /* At this point, you could queue::wait_and_throw() to ensure that
+           * errors are caught quickly. However, this would likely impact
+           * performance negatively. */
+          length = length / local;
+
+        } while (length > 1);
+
+
+
+}
+
+};
+
+/// For now let's start with a full reducer
+/// Self is useless here because in expression construction we are going to treat reduction as a leafnode.
+/// we want to take reduction child and then build a construction and apply the full reducer function on it. Fullreducre applies the
+/// reduction operation on the child of the reduction. once it is done the reduction is an empty shell and can be thrown away and treated as
+// a leafNode.
+template <typename Self, typename Op, bool Vectorizable>
+struct FullReducer<Self, Op, const Eigen::SyclDevice, Vectorizable> {
+
+  typedef typename Self::CoeffReturnType CoeffReturnType;
+  static const bool HasOptimizedImplementation = false;
+
+  static void run(const Self& self, Op& reducer, const Eigen::SyclDevice& dev, CoeffReturnType* output) {
+    typedef const typename Self::ChildType HostExpr; /// this is the child of reduction
+    typedef  typename TensorSycl::internal::createPlaceHolderExpression<HostExpr>::Type PlaceHolderExpr;
+    auto functors = TensorSycl::internal::extractFunctors(self.impl());
+    int red_factor =256; /// initial reduction. If the size is less than red_factor we only creates one thread.
+    size_t inputSize =self.impl().dimensions().TotalSize();
+    size_t rng = inputSize/red_factor; // the total number of thread initially is half the size of the input
+    size_t remaining = inputSize% red_factor;
+    if(rng ==0) {
+      red_factor=1;
+    };
+    size_t tileSize =dev.m_queue.get_device(). template get_info<cl::sycl::info::device::max_work_group_size>()/2;
+    size_t GRange=std::max((size_t )1, rng);
+
+    // convert global range to power of 2 for redecution
+    GRange--;
+    GRange |= GRange >> 1;
+    GRange |= GRange >> 2;
+    GRange |= GRange >> 4;
+    GRange |= GRange >> 8;
+    GRange |= GRange >> 16;
+#if __x86_64__ || __ppc64__ || _WIN64
+    GRange |= GRange >> 32;
+#endif
+    GRange++;
+    size_t  outTileSize = tileSize;
+    /// if the shared memory is less than the GRange, we set shared_mem size to the TotalSize and in this case one kernel would be created for recursion to reduce all to one.
+    if (GRange < outTileSize) outTileSize=GRange;
+    // getting final out buffer at the moment the created buffer is true because there is no need for assign
+    auto out_buffer =dev.template get_sycl_buffer<typename Eigen::internal::remove_all<CoeffReturnType>::type>(self.dimensions().TotalSize(), output);
+    /// creating the shared memory for calculating reduction.
+    /// This one is used to collect all the reduced value of shared memory as we dont have global barrier on GPU. Once it is saved we can
+    /// recursively apply reduction on it in order to reduce the whole.
+    auto temp_global_buffer =cl::sycl::buffer<CoeffReturnType, 1>(cl::sycl::range<1>(GRange));
+    typedef typename Eigen::internal::remove_all<decltype(self.xprDims())>::type Dims;
+    Dims dims= self.xprDims();
+    Op functor = reducer;
+    dev.m_queue.submit([&](cl::sycl::handler &cgh) {
+      // create a tuple of accessors from Evaluator
+      auto tuple_of_accessors =  TensorSycl::internal::createTupleOfAccessors(cgh, self.impl());
+      auto tmp_global_accessor = temp_global_buffer. template get_access<cl::sycl::access::mode::read_write, cl::sycl::access::target::global_buffer>(cgh);
+
+      cgh.parallel_for<PlaceHolderExpr>( cl::sycl::nd_range<1>(cl::sycl::range<1>(GRange), cl::sycl::range<1>(outTileSize)), [=](cl::sycl::nd_item<1> itemID) {
+        typedef typename TensorSycl::internal::ConvertToDeviceExpression<const HostExpr>::Type DevExpr;
+        auto device_expr = TensorSycl::internal::createDeviceExpression<DevExpr, PlaceHolderExpr>(functors, tuple_of_accessors);
+        /// reduction cannot be captured automatically through our device conversion recursion. The reason is that reduction has two behaviour
+        /// the first behaviour is when it is used as a root to lauch the sub-kernel. The second one is when it is treated as a leafnode to pass the
+        /// calculated result to its parent kernel. While the latter is automatically detected through our device expression generator. The former is created here.
+        const auto device_self_expr= TensorReductionOp<Op, Dims, decltype(device_expr.expr) ,MakeGlobalPointer>(device_expr.expr, dims, functor);
+        /// This is the evaluator for device_self_expr. This is exactly similar to the self which has been passed to run function. The difference is
+        /// the device_evaluator is detectable and recognisable on the device.
+        auto device_self_evaluator = Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::DefaultDevice>(device_self_expr, Eigen::DefaultDevice());
+        /// const cast added as a naive solution to solve the qualifier drop error
+        auto globalid=itemID.get_global_linear_id();
+
+        if(globalid<rng)
+          tmp_global_accessor.get_pointer()[globalid]=InnerMostDimReducer<decltype(device_self_evaluator), Op, false>::reduce(device_self_evaluator, red_factor*globalid, red_factor, const_cast<Op&>(functor));
+        else
+          tmp_global_accessor.get_pointer()[globalid]=static_cast<CoeffReturnType>(0);
+
+        if(remaining!=0 && globalid==0 )
+          // this will add the rest of input buffer when the input size is not devidable to red_factor.
+          tmp_global_accessor.get_pointer()[globalid]+=InnerMostDimReducer<decltype(device_self_evaluator), Op, false>::reduce(device_self_evaluator, red_factor*(rng), remaining, const_cast<Op&>(functor));
+      });
+    });
+  dev.m_queue.throw_asynchronous();
+
+/// This is used to recursively reduce the tmp value to an element of 1;
+  syclGenericBufferReducer<CoeffReturnType,HostExpr>::run(out_buffer, temp_global_buffer,dev, GRange,  outTileSize);
+  }
+
+};
+
+template <typename Self, typename Op>
+struct InnerReducer<Self, Op, const Eigen::SyclDevice> {
+
+  typedef typename Self::CoeffReturnType CoeffReturnType;
+  static const bool HasOptimizedImplementation = false;
+
+  static bool run(const Self& self, Op& reducer, const Eigen::SyclDevice& dev, CoeffReturnType* output, typename Self::Index , typename Self::Index num_coeffs_to_preserve) {
+    typedef const typename Self::ChildType HostExpr; /// this is the child of reduction
+    typedef  typename TensorSycl::internal::createPlaceHolderExpression<HostExpr>::Type PlaceHolderExpr;
+    auto functors = TensorSycl::internal::extractFunctors(self.impl());
+
+    size_t tileSize =dev.m_queue.get_device(). template get_info<cl::sycl::info::device::max_work_group_size>()/2;
+
+    size_t GRange=num_coeffs_to_preserve;
+    if (tileSize>GRange) tileSize=GRange;
+    else if(GRange>tileSize){
+      size_t xMode = GRange % tileSize;
+      if (xMode != 0) GRange += (tileSize - xMode);
+    }
+    // getting final out buffer at the moment the created buffer is true because there is no need for assign
+    /// creating the shared memory for calculating reduction.
+    /// This one is used to collect all the reduced value of shared memory as we dont have global barrier on GPU. Once it is saved we can
+    /// recursively apply reduction on it in order to reduce the whole.
+    typedef typename Eigen::internal::remove_all<decltype(self.xprDims())>::type Dims;
+    Dims dims= self.xprDims();
+    Op functor = reducer;
+
+    dev.m_queue.submit([&](cl::sycl::handler &cgh) {
+      // create a tuple of accessors from Evaluator
+      auto tuple_of_accessors =  TensorSycl::internal::createTupleOfAccessors(cgh, self.impl());
+      auto output_accessor = dev.template get_sycl_accessor<cl::sycl::access::mode::discard_write>(num_coeffs_to_preserve,cgh, output);
+
+      cgh.parallel_for<Self>( cl::sycl::nd_range<1>(cl::sycl::range<1>(GRange), cl::sycl::range<1>(tileSize)), [=](cl::sycl::nd_item<1> itemID) {
+        typedef typename TensorSycl::internal::ConvertToDeviceExpression<const HostExpr>::Type DevExpr;
+        auto device_expr = TensorSycl::internal::createDeviceExpression<DevExpr, PlaceHolderExpr>(functors, tuple_of_accessors);
+        /// reduction cannot be captured automatically through our device conversion recursion. The reason is that reduction has two behaviour
+        /// the first behaviour is when it is used as a root to lauch the sub-kernel. The second one is when it is treated as a leafnode to pass the
+        /// calculated result to its parent kernel. While the latter is automatically detected through our device expression generator. The former is created here.
+        const auto device_self_expr= TensorReductionOp<Op, Dims, decltype(device_expr.expr) ,MakeGlobalPointer>(device_expr.expr, dims, functor);
+        /// This is the evaluator for device_self_expr. This is exactly similar to the self which has been passed to run function. The difference is
+        /// the device_evaluator is detectable and recognisable on the device.
+        typedef Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::DefaultDevice> DeiceSelf;
+        auto device_self_evaluator = Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::DefaultDevice>(device_self_expr, Eigen::DefaultDevice());
+        /// const cast added as a naive solution to solve the qualifier drop error
+        auto globalid=itemID.get_global_linear_id();
+        if (globalid< static_cast<size_t>(num_coeffs_to_preserve)) {
+          typename DeiceSelf::CoeffReturnType accum = functor.initialize();
+          GenericDimReducer<DeiceSelf::NumReducedDims-1, DeiceSelf, Op>::reduce(device_self_evaluator, device_self_evaluator.firstInput(globalid),const_cast<Op&>(functor), &accum);
+          functor.finalize(accum);
+          output_accessor.get_pointer()[globalid]= accum;
+        }
+      });
+    });
+  dev.m_queue.throw_asynchronous();
+    return false;
+  }
+};
+
+}  // end namespace internal
+}  // namespace Eigen
+
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSOR_REDUCTION_SYCL_HPP

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorRef.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorRef.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorRef.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorRef.h
@@ -0,0 +1,429 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_REF_H
+#define EIGEN_CXX11_TENSOR_TENSOR_REF_H
+
+namespace Eigen {
+
+namespace internal {
+
+template <typename Dimensions, typename Scalar>
+class TensorLazyBaseEvaluator {
+ public:
+  TensorLazyBaseEvaluator() : m_refcount(0) { }
+  virtual ~TensorLazyBaseEvaluator() { }
+
+  EIGEN_DEVICE_FUNC virtual const Dimensions& dimensions() const = 0;
+  EIGEN_DEVICE_FUNC virtual const Scalar* data() const = 0;
+
+  EIGEN_DEVICE_FUNC virtual const Scalar coeff(DenseIndex index) const = 0;
+  EIGEN_DEVICE_FUNC virtual Scalar& coeffRef(DenseIndex index) = 0;
+
+  void incrRefCount() { ++m_refcount; }
+  void decrRefCount() { --m_refcount; }
+  int refCount() const { return m_refcount; }
+
+ private:
+  // No copy, no assigment;
+  TensorLazyBaseEvaluator(const TensorLazyBaseEvaluator& other);
+  TensorLazyBaseEvaluator& operator = (const TensorLazyBaseEvaluator& other);
+
+  int m_refcount;
+};
+
+
+template <typename Dimensions, typename Expr, typename Device>
+class TensorLazyEvaluatorReadOnly : public TensorLazyBaseEvaluator<Dimensions, typename TensorEvaluator<Expr, Device>::Scalar> {
+ public:
+  //  typedef typename TensorEvaluator<Expr, Device>::Dimensions Dimensions;
+  typedef typename TensorEvaluator<Expr, Device>::Scalar Scalar;
+
+  TensorLazyEvaluatorReadOnly(const Expr& expr, const Device& device) : m_impl(expr, device), m_dummy(Scalar(0)) {
+    m_dims = m_impl.dimensions();
+    m_impl.evalSubExprsIfNeeded(NULL);
+  }
+  virtual ~TensorLazyEvaluatorReadOnly() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC virtual const Dimensions& dimensions() const {
+    return m_dims;
+  }
+  EIGEN_DEVICE_FUNC virtual const Scalar* data() const {
+    return m_impl.data();
+  }
+
+  EIGEN_DEVICE_FUNC virtual const Scalar coeff(DenseIndex index) const {
+    return m_impl.coeff(index);
+  }
+  EIGEN_DEVICE_FUNC virtual Scalar& coeffRef(DenseIndex /*index*/) {
+    eigen_assert(false && "can't reference the coefficient of a rvalue");
+    return m_dummy;
+  };
+
+ protected:
+  TensorEvaluator<Expr, Device> m_impl;
+  Dimensions m_dims;
+  Scalar m_dummy;
+};
+
+template <typename Dimensions, typename Expr, typename Device>
+class TensorLazyEvaluatorWritable : public TensorLazyEvaluatorReadOnly<Dimensions, Expr, Device> {
+ public:
+  typedef TensorLazyEvaluatorReadOnly<Dimensions, Expr, Device> Base;
+  typedef typename Base::Scalar Scalar;
+
+  TensorLazyEvaluatorWritable(const Expr& expr, const Device& device) : Base(expr, device) {
+  }
+  virtual ~TensorLazyEvaluatorWritable() {
+  }
+
+  EIGEN_DEVICE_FUNC virtual Scalar& coeffRef(DenseIndex index) {
+    return this->m_impl.coeffRef(index);
+  }
+};
+
+template <typename Dimensions, typename Expr, typename Device>
+class TensorLazyEvaluator : public internal::conditional<bool(internal::is_lvalue<Expr>::value),
+                            TensorLazyEvaluatorWritable<Dimensions, Expr, Device>,
+                            TensorLazyEvaluatorReadOnly<Dimensions, const Expr, Device> >::type {
+ public:
+  typedef typename internal::conditional<bool(internal::is_lvalue<Expr>::value),
+                                         TensorLazyEvaluatorWritable<Dimensions, Expr, Device>,
+                                         TensorLazyEvaluatorReadOnly<Dimensions, const Expr, Device> >::type Base;
+  typedef typename Base::Scalar Scalar;
+
+  TensorLazyEvaluator(const Expr& expr, const Device& device) : Base(expr, device) {
+  }
+  virtual ~TensorLazyEvaluator() {
+  }
+};
+
+}  // namespace internal
+
+
+/** \class TensorRef
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief A reference to a tensor expression
+  * The expression will be evaluated lazily (as much as possible).
+  *
+  */
+template<typename PlainObjectType> class TensorRef : public TensorBase<TensorRef<PlainObjectType> >
+{
+  public:
+    typedef TensorRef<PlainObjectType> Self;
+    typedef typename PlainObjectType::Base Base;
+    typedef typename Eigen::internal::nested<Self>::type Nested;
+    typedef typename internal::traits<PlainObjectType>::StorageKind StorageKind;
+    typedef typename internal::traits<PlainObjectType>::Index Index;
+    typedef typename internal::traits<PlainObjectType>::Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename Base::CoeffReturnType CoeffReturnType;
+    typedef Scalar* PointerType;
+    typedef PointerType PointerArgType;
+
+    static const Index NumIndices = PlainObjectType::NumIndices;
+    typedef typename PlainObjectType::Dimensions Dimensions;
+
+    enum {
+      IsAligned = false,
+      PacketAccess = false,
+      Layout = PlainObjectType::Layout,
+      CoordAccess = false,  // to be implemented
+      RawAccess = false
+    };
+
+    EIGEN_STRONG_INLINE TensorRef() : m_evaluator(NULL) {
+    }
+
+    template <typename Expression>
+    EIGEN_STRONG_INLINE TensorRef(const Expression& expr) : m_evaluator(new internal::TensorLazyEvaluator<Dimensions, Expression, DefaultDevice>(expr, DefaultDevice())) {
+      m_evaluator->incrRefCount();
+    }
+
+    template <typename Expression>
+    EIGEN_STRONG_INLINE TensorRef& operator = (const Expression& expr) {
+      unrefEvaluator();
+      m_evaluator = new internal::TensorLazyEvaluator<Dimensions, Expression, DefaultDevice>(expr, DefaultDevice());
+      m_evaluator->incrRefCount();
+      return *this;
+    }
+
+    ~TensorRef() {
+      unrefEvaluator();
+    }
+
+    TensorRef(const TensorRef& other) : m_evaluator(other.m_evaluator) {
+      eigen_assert(m_evaluator->refCount() > 0);
+      m_evaluator->incrRefCount();
+    }
+
+    TensorRef& operator = (const TensorRef& other) {
+      if (this != &other) {
+        unrefEvaluator();
+        m_evaluator = other.m_evaluator;
+        eigen_assert(m_evaluator->refCount() > 0);
+        m_evaluator->incrRefCount();
+      }
+      return *this;
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index rank() const { return m_evaluator->dimensions().size(); }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index dimension(Index n) const { return m_evaluator->dimensions()[n]; }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_evaluator->dimensions(); }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Index size() const { return m_evaluator->dimensions().TotalSize(); }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar* data() const { return m_evaluator->data(); }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar operator()(Index index) const
+    {
+      return m_evaluator->coeff(index);
+    }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar operator()(Index firstIndex, IndexTypes... otherIndices) const
+    {
+      const std::size_t num_indices = (sizeof...(otherIndices) + 1);
+      const array<Index, num_indices> indices{{firstIndex, otherIndices...}};
+      return coeff(indices);
+    }
+    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index firstIndex, IndexTypes... otherIndices)
+    {
+      const std::size_t num_indices = (sizeof...(otherIndices) + 1);
+      const array<Index, num_indices> indices{{firstIndex, otherIndices...}};
+      return coeffRef(indices);
+    }
+#else
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar operator()(Index i0, Index i1) const
+    {
+      array<Index, 2> indices;
+      indices[0] = i0;
+      indices[1] = i1;
+      return coeff(indices);
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar operator()(Index i0, Index i1, Index i2) const
+    {
+      array<Index, 3> indices;
+      indices[0] = i0;
+      indices[1] = i1;
+      indices[2] = i2;
+      return coeff(indices);
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar operator()(Index i0, Index i1, Index i2, Index i3) const
+    {
+      array<Index, 4> indices;
+      indices[0] = i0;
+      indices[1] = i1;
+      indices[2] = i2;
+      indices[3] = i3;
+      return coeff(indices);
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
+    {
+      array<Index, 5> indices;
+      indices[0] = i0;
+      indices[1] = i1;
+      indices[2] = i2;
+      indices[3] = i3;
+      indices[4] = i4;
+      return coeff(indices);
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index i0, Index i1)
+    {
+      array<Index, 2> indices;
+      indices[0] = i0;
+      indices[1] = i1;
+      return coeffRef(indices);
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index i0, Index i1, Index i2)
+    {
+      array<Index, 3> indices;
+      indices[0] = i0;
+      indices[1] = i1;
+      indices[2] = i2;
+      return coeffRef(indices);
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
+    {
+      array<Index, 4> indices;
+      indices[0] = i0;
+      indices[1] = i1;
+      indices[2] = i2;
+      indices[3] = i3;
+      return coeffRef(indices);
+    }
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index i0, Index i1, Index i2, Index i3, Index i4)
+    {
+      array<Index, 5> indices;
+      indices[0] = i0;
+      indices[1] = i1;
+      indices[2] = i2;
+      indices[3] = i3;
+      indices[4] = i4;
+      return coeffRef(indices);
+    }
+#endif
+
+    template <std::size_t NumIndices> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar coeff(const array<Index, NumIndices>& indices) const
+    {
+      const Dimensions& dims = this->dimensions();
+      Index index = 0;
+      if (PlainObjectType::Options & RowMajor) {
+        index += indices[0];
+        for (size_t i = 1; i < NumIndices; ++i) {
+          index = index * dims[i] + indices[i];
+        }
+      } else {
+        index += indices[NumIndices-1];
+        for (int i = NumIndices-2; i >= 0; --i) {
+          index = index * dims[i] + indices[i];
+        }
+      }
+      return m_evaluator->coeff(index);
+    }
+    template <std::size_t NumIndices> EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef(const array<Index, NumIndices>& indices)
+    {
+      const Dimensions& dims = this->dimensions();
+      Index index = 0;
+      if (PlainObjectType::Options & RowMajor) {
+        index += indices[0];
+        for (size_t i = 1; i < NumIndices; ++i) {
+          index = index * dims[i] + indices[i];
+        }
+      } else {
+        index += indices[NumIndices-1];
+        for (int i = NumIndices-2; i >= 0; --i) {
+          index = index * dims[i] + indices[i];
+        }
+      }
+      return m_evaluator->coeffRef(index);
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
+    {
+      return m_evaluator->coeff(index);
+    }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
+    {
+      return m_evaluator->coeffRef(index);
+    }
+
+  private:
+    EIGEN_STRONG_INLINE void unrefEvaluator() {
+      if (m_evaluator) {
+        m_evaluator->decrRefCount();
+        if (m_evaluator->refCount() == 0) {
+          delete m_evaluator;
+        }
+      }
+    }
+
+  internal::TensorLazyBaseEvaluator<Dimensions, Scalar>* m_evaluator;
+};
+
+
+// evaluator for rvalues
+template<typename Derived, typename Device>
+struct TensorEvaluator<const TensorRef<Derived>, Device>
+{
+  typedef typename Derived::Index Index;
+  typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef typename Derived::Dimensions Dimensions;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = false,
+    Layout = TensorRef<Derived>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const TensorRef<Derived>& m, const Device&)
+      : m_ref(m)
+  { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_ref.dimensions(); }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+    return m_ref.coeff(index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
+    return m_ref.coeffRef(index);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return m_ref.data(); }
+
+ protected:
+  TensorRef<Derived> m_ref;
+};
+
+
+// evaluator for lvalues
+template<typename Derived, typename Device>
+struct TensorEvaluator<TensorRef<Derived>, Device> : public TensorEvaluator<const TensorRef<Derived>, Device>
+{
+  typedef typename Derived::Index Index;
+  typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::Scalar CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef typename Derived::Dimensions Dimensions;
+
+  typedef TensorEvaluator<const TensorRef<Derived>, Device> Base;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = false,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(TensorRef<Derived>& m, const Device& d) : Base(m, d)
+  { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
+    return this->m_ref.coeffRef(index);
+  }
+};
+
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_REF_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
@@ -0,0 +1,288 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Navdeep Jaitly <ndjaitly@google.com>
+//                    Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H
+#define EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H
+namespace Eigen {
+
+/** \class TensorReverse
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor reverse elements class.
+  *
+  */
+namespace internal {
+template<typename ReverseDimensions, typename XprType>
+struct traits<TensorReverseOp<ReverseDimensions,
+                              XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename ReverseDimensions, typename XprType>
+struct eval<TensorReverseOp<ReverseDimensions, XprType>, Eigen::Dense>
+{
+  typedef const TensorReverseOp<ReverseDimensions, XprType>& type;
+};
+
+template<typename ReverseDimensions, typename XprType>
+struct nested<TensorReverseOp<ReverseDimensions, XprType>, 1,
+            typename eval<TensorReverseOp<ReverseDimensions, XprType> >::type>
+{
+  typedef TensorReverseOp<ReverseDimensions, XprType> type;
+};
+
+}  // end namespace internal
+
+template<typename ReverseDimensions, typename XprType>
+class TensorReverseOp : public TensorBase<TensorReverseOp<ReverseDimensions,
+                                          XprType>, WriteAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorReverseOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorReverseOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorReverseOp>::StorageKind
+                                                                    StorageKind;
+  typedef typename Eigen::internal::traits<TensorReverseOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReverseOp(
+      const XprType& expr, const ReverseDimensions& reverse_dims)
+      : m_xpr(expr), m_reverse_dims(reverse_dims) { }
+
+    EIGEN_DEVICE_FUNC
+    const ReverseDimensions& reverse() const { return m_reverse_dims; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorReverseOp& operator = (const TensorReverseOp& other)
+    {
+      typedef TensorAssignOp<TensorReverseOp, const TensorReverseOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorReverseOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorReverseOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const ReverseDimensions m_reverse_dims;
+};
+
+// Eval as rvalue
+template<typename ReverseDimensions, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device>
+{
+  typedef TensorReverseOp<ReverseDimensions, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<ReverseDimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
+                                                        const Device& device)
+      : m_impl(op.expression(), device), m_reverse(op.reverse())
+  {
+    // Reversing a scalar isn't supported yet. It would be a no-op anyway.
+    EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    // Compute strides
+    m_dimensions = m_impl.dimensions();
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_strides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_strides[i] = m_strides[i-1] * m_dimensions[i-1];
+      }
+    } else {
+      m_strides[NumDims-1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_strides[i] = m_strides[i+1] * m_dimensions[i+1];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index reverseIndex(
+      Index index) const {
+    eigen_assert(index < dimensions().TotalSize());
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        Index idx = index / m_strides[i];
+        index -= idx * m_strides[i];
+        if (m_reverse[i]) {
+          idx = m_dimensions[i] - idx - 1;
+        }
+        inputIndex += idx * m_strides[i] ;
+      }
+      if (m_reverse[0]) {
+        inputIndex += (m_dimensions[0] - index - 1);
+      } else {
+        inputIndex += index;
+      }
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        Index idx = index / m_strides[i];
+        index -= idx * m_strides[i];
+        if (m_reverse[i]) {
+          idx = m_dimensions[i] - idx - 1;
+        }
+        inputIndex += idx * m_strides[i] ;
+      }
+      if (m_reverse[NumDims-1]) {
+        inputIndex += (m_dimensions[NumDims-1] - index - 1);
+      } else {
+        inputIndex += index;
+      }
+    }
+    return inputIndex;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(
+      Index index) const  {
+    return m_impl.coeff(reverseIndex(index));
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    // TODO(ndjaitly): write a better packing routine that uses
+    // local structure.
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type
+                                                            values[PacketSize];
+    for (int i = 0; i < PacketSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    double compute_cost = NumDims * (2 * TensorOpCost::AddCost<Index>() +
+                                     2 * TensorOpCost::MulCost<Index>() +
+                                     TensorOpCost::DivCost<Index>());
+    for (int i = 0; i < NumDims; ++i) {
+      if (m_reverse[i]) {
+        compute_cost += 2 * TensorOpCost::AddCost<Index>();
+      }
+    }
+    return m_impl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, compute_cost, false /* vectorized */, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ protected:
+  Dimensions m_dimensions;
+  array<Index, NumDims> m_strides;
+  TensorEvaluator<ArgType, Device> m_impl;
+  ReverseDimensions m_reverse;
+};
+
+// Eval as lvalue
+
+template <typename ReverseDimensions, typename ArgType, typename Device>
+struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
+    : public TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>,
+                             Device> {
+  typedef TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>,
+                          Device> Base;
+  typedef TensorReverseOp<ReverseDimensions, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<ReverseDimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
+                                                        const Device& device)
+      : Base(op, device) {}
+
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const Dimensions& dimensions() const { return this->m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
+    return this->m_impl.coeffRef(this->reverseIndex(index));
+  }
+
+  template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x) {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    // This code is pilfered from TensorMorphing.h
+    EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize];
+    internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
+    for (int i = 0; i < PacketSize; ++i) {
+      this->coeffRef(index+i) = values[i];
+    }
+  }
+
+};
+
+
+}  // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorScan.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorScan.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorScan.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorScan.h
@@ -0,0 +1,287 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Igor Babuschkin <igor@babuschk.in>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_SCAN_H
+#define EIGEN_CXX11_TENSOR_TENSOR_SCAN_H
+
+namespace Eigen {
+
+namespace internal {
+
+template <typename Op, typename XprType>
+struct traits<TensorScanOp<Op, XprType> >
+    : public traits<XprType> {
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename Op, typename XprType>
+struct eval<TensorScanOp<Op, XprType>, Eigen::Dense>
+{
+  typedef const TensorScanOp<Op, XprType>& type;
+};
+
+template<typename Op, typename XprType>
+struct nested<TensorScanOp<Op, XprType>, 1,
+            typename eval<TensorScanOp<Op, XprType> >::type>
+{
+  typedef TensorScanOp<Op, XprType> type;
+};
+} // end namespace internal
+
+/** \class TensorScan
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor scan class.
+  */
+template <typename Op, typename XprType>
+class TensorScanOp
+    : public TensorBase<TensorScanOp<Op, XprType>, ReadOnlyAccessors> {
+public:
+  typedef typename Eigen::internal::traits<TensorScanOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorScanOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorScanOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorScanOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorScanOp(
+      const XprType& expr, const Index& axis, bool exclusive = false, const Op& op = Op())
+      : m_expr(expr), m_axis(axis), m_accumulator(op), m_exclusive(exclusive) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const Index axis() const { return m_axis; }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const XprType& expression() const { return m_expr; }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const Op accumulator() const { return m_accumulator; }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  bool exclusive() const { return m_exclusive; }
+
+protected:
+  typename XprType::Nested m_expr;
+  const Index m_axis;
+  const Op m_accumulator;
+  const bool m_exclusive;
+};
+
+template <typename Self, typename Reducer, typename Device>
+struct ScanLauncher;
+
+// Eval as rvalue
+template <typename Op, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorScanOp<Op, ArgType>, Device> {
+
+  typedef TensorScanOp<Op, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  typedef TensorEvaluator<const TensorScanOp<Op, ArgType>, Device> Self;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = (internal::unpacket_traits<PacketReturnType>::size > 1),
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,
+    RawAccess = true
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
+                                                        const Device& device)
+      : m_impl(op.expression(), device),
+        m_device(device),
+        m_exclusive(op.exclusive()),
+        m_accumulator(op.accumulator()),
+        m_size(m_impl.dimensions()[op.axis()]),
+        m_stride(1),
+        m_output(NULL) {
+
+    // Accumulating a scalar isn't supported.
+    EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    eigen_assert(op.axis() >= 0 && op.axis() < NumDims);
+
+    // Compute stride of scan axis
+    const Dimensions& dims = m_impl.dimensions();
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = 0; i < op.axis(); ++i) {
+        m_stride = m_stride * dims[i];
+      }
+    } else {
+      for (int i = NumDims - 1; i > op.axis(); --i) {
+        m_stride = m_stride * dims[i];
+      }
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {
+    return m_impl.dimensions();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Index& stride() const {
+    return m_stride;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Index& size() const {
+    return m_size;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Op& accumulator() const {
+    return m_accumulator;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool exclusive() const {
+    return m_exclusive;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorEvaluator<ArgType, Device>& inner() const {
+    return m_impl;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Device& device() const {
+    return m_device;
+  }
+
+  EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    ScanLauncher<Self, Op, Device> launcher;
+    if (data) {
+      launcher(*this, data);
+      return false;
+    }
+
+    const Index total_size = internal::array_prod(dimensions());
+    m_output = static_cast<CoeffReturnType*>(m_device.allocate(total_size * sizeof(Scalar)));
+    launcher(*this, m_output);
+    return true;
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_output + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType* data() const
+  {
+    return m_output;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_output[index];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool) const {
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    if (m_output != NULL) {
+      m_device.deallocate(m_output);
+      m_output = NULL;
+    }
+    m_impl.cleanup();
+  }
+
+protected:
+  TensorEvaluator<ArgType, Device> m_impl;
+  const Device& m_device;
+  const bool m_exclusive;
+  Op m_accumulator;
+  const Index m_size;
+  Index m_stride;
+  CoeffReturnType* m_output;
+};
+
+// CPU implementation of scan
+// TODO(ibab) This single-threaded implementation should be parallelized,
+// at least by running multiple scans at the same time.
+template <typename Self, typename Reducer, typename Device>
+struct ScanLauncher {
+  void operator()(Self& self, typename Self::CoeffReturnType *data) {
+    Index total_size = internal::array_prod(self.dimensions());
+
+    // We fix the index along the scan axis to 0 and perform a
+    // scan per remaining entry. The iteration is split into two nested
+    // loops to avoid an integer division by keeping track of each idx1 and idx2.
+    for (Index idx1 = 0; idx1 < total_size; idx1 += self.stride() * self.size()) {
+      for (Index idx2 = 0; idx2 < self.stride(); idx2++) {
+        // Calculate the starting offset for the scan
+        Index offset = idx1 + idx2;
+
+        // Compute the scan along the axis, starting at the calculated offset
+        typename Self::CoeffReturnType accum = self.accumulator().initialize();
+        for (Index idx3 = 0; idx3 < self.size(); idx3++) {
+          Index curr = offset + idx3 * self.stride();
+
+          if (self.exclusive()) {
+            data[curr] = self.accumulator().finalize(accum);
+            self.accumulator().reduce(self.inner().coeff(curr), &accum);
+          } else {
+            self.accumulator().reduce(self.inner().coeff(curr), &accum);
+            data[curr] = self.accumulator().finalize(accum);
+          }
+        }
+      }
+    }
+  }
+};
+
+#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+
+// GPU implementation of scan
+// TODO(ibab) This placeholder implementation performs multiple scans in
+// parallel, but it would be better to use a parallel scan algorithm and
+// optimize memory access.
+template <typename Self, typename Reducer>
+__global__ void ScanKernel(Self self, Index total_size, typename Self::CoeffReturnType* data) {
+  // Compute offset as in the CPU version
+  Index val = threadIdx.x + blockIdx.x * blockDim.x;
+  Index offset = (val / self.stride()) * self.stride() * self.size() + val % self.stride();
+
+  if (offset + (self.size() - 1) * self.stride() < total_size) {
+    // Compute the scan along the axis, starting at the calculated offset
+    typename Self::CoeffReturnType accum = self.accumulator().initialize();
+    for (Index idx = 0; idx < self.size(); idx++) {
+      Index curr = offset + idx * self.stride();
+      if (self.exclusive()) {
+        data[curr] = self.accumulator().finalize(accum);
+        self.accumulator().reduce(self.inner().coeff(curr), &accum);
+      } else {
+        self.accumulator().reduce(self.inner().coeff(curr), &accum);
+        data[curr] = self.accumulator().finalize(accum);
+      }
+    }
+  }
+  __syncthreads();
+
+}
+
+template <typename Self, typename Reducer>
+struct ScanLauncher<Self, Reducer, GpuDevice> {
+  void operator()(const Self& self, typename Self::CoeffReturnType* data) {
+     Index total_size = internal::array_prod(self.dimensions());
+     Index num_blocks = (total_size / self.size() + 63) / 64;
+     Index block_size = 64;
+     LAUNCH_CUDA_KERNEL((ScanKernel<Self, Reducer>), num_blocks, block_size, 0, self.device(), self, total_size, data);
+  }
+};
+#endif  // EIGEN_USE_GPU && __CUDACC__
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_CXX11_TENSOR_TENSOR_SCAN_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
@@ -0,0 +1,264 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_SHUFFLING_H
+#define EIGEN_CXX11_TENSOR_TENSOR_SHUFFLING_H
+
+namespace Eigen {
+
+/** \class TensorShuffling
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor shuffling class.
+  *
+  *
+  */
+namespace internal {
+template<typename Shuffle, typename XprType>
+struct traits<TensorShufflingOp<Shuffle, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename Shuffle, typename XprType>
+struct eval<TensorShufflingOp<Shuffle, XprType>, Eigen::Dense>
+{
+  typedef const TensorShufflingOp<Shuffle, XprType>& type;
+};
+
+template<typename Shuffle, typename XprType>
+struct nested<TensorShufflingOp<Shuffle, XprType>, 1, typename eval<TensorShufflingOp<Shuffle, XprType> >::type>
+{
+  typedef TensorShufflingOp<Shuffle, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename Shuffle, typename XprType>
+class TensorShufflingOp : public TensorBase<TensorShufflingOp<Shuffle, XprType> >
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorShufflingOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorShufflingOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorShufflingOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorShufflingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorShufflingOp(const XprType& expr, const Shuffle& shuffle)
+      : m_xpr(expr), m_shuffle(shuffle) {}
+
+    EIGEN_DEVICE_FUNC
+    const Shuffle& shufflePermutation() const { return m_shuffle; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorShufflingOp& operator = (const TensorShufflingOp& other)
+    {
+      typedef TensorAssignOp<TensorShufflingOp, const TensorShufflingOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorShufflingOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorShufflingOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const Shuffle m_shuffle;
+};
+
+
+// Eval as rvalue
+template<typename Shuffle, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorShufflingOp<Shuffle, ArgType>, Device>
+{
+  typedef TensorShufflingOp<Shuffle, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = (internal::packet_traits<Scalar>::size > 1),
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device)
+  {
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    const Shuffle& shuffle = op.shufflePermutation();
+    for (int i = 0; i < NumDims; ++i) {
+      m_dimensions[i] = input_dims[shuffle[i]];
+    }
+
+    array<Index, NumDims> inputStrides;
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      inputStrides[0] = 1;
+      m_outputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        inputStrides[i] = inputStrides[i - 1] * input_dims[i - 1];
+        m_outputStrides[i] = m_outputStrides[i - 1] * m_dimensions[i - 1];
+      }
+    } else {
+      inputStrides[NumDims - 1] = 1;
+      m_outputStrides[NumDims - 1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        inputStrides[i] = inputStrides[i + 1] * input_dims[i + 1];
+        m_outputStrides[i] = m_outputStrides[i + 1] * m_dimensions[i + 1];
+      }
+    }
+
+    for (int i = 0; i < NumDims; ++i) {
+      m_inputStrides[i] = inputStrides[shuffle[i]];
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_impl.coeff(srcCoeff(index));
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+    for (int i = 0; i < PacketSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    const double compute_cost = NumDims * (2 * TensorOpCost::AddCost<Index>() +
+                                           2 * TensorOpCost::MulCost<Index>() +
+                                           TensorOpCost::DivCost<Index>());
+    return m_impl.costPerCoeff(vectorized) +
+           TensorOpCost(0, 0, compute_cost, false /* vectorized */, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ protected:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index srcCoeff(Index index) const {
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx = index / m_outputStrides[i];
+        inputIndex += idx * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      return inputIndex + index * m_inputStrides[0];
+    } else {
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx = index / m_outputStrides[i];
+        inputIndex += idx * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      return inputIndex + index * m_inputStrides[NumDims - 1];
+    }
+  }
+
+  Dimensions m_dimensions;
+  array<Index, NumDims> m_outputStrides;
+  array<Index, NumDims> m_inputStrides;
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+
+// Eval as lvalue
+template<typename Shuffle, typename ArgType, typename Device>
+struct TensorEvaluator<TensorShufflingOp<Shuffle, ArgType>, Device>
+    : public TensorEvaluator<const TensorShufflingOp<Shuffle, ArgType>, Device>
+{
+  typedef TensorEvaluator<const TensorShufflingOp<Shuffle, ArgType>, Device> Base;
+
+  typedef TensorShufflingOp<Shuffle, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = (internal::packet_traits<Scalar>::size > 1),
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : Base(op, device)
+  { }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index)
+  {
+    return this->m_impl.coeffRef(this->srcCoeff(index));
+  }
+
+  template <int StoreMode> EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x)
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+    internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
+    for (int i = 0; i < PacketSize; ++i) {
+      this->coeffRef(index+i) = values[i];
+    }
+  }
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_SHUFFLING_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorStorage.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorStorage.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorStorage.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorStorage.h
@@ -0,0 +1,146 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+// Copyright (C) 2014-2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSORSTORAGE_H
+#define EIGEN_CXX11_TENSOR_TENSORSTORAGE_H
+
+#ifdef EIGEN_TENSOR_STORAGE_CTOR_PLUGIN
+  #define EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN EIGEN_TENSOR_STORAGE_CTOR_PLUGIN;
+#else
+  #define EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN
+#endif
+
+namespace Eigen {
+
+/** \internal
+  *
+  * \class TensorStorage
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Stores the data of a tensor
+  *
+  * This class stores the data of fixed-size, dynamic-size or mixed tensors
+  * in a way as compact as possible.
+  *
+  * \sa Tensor
+  */
+template<typename T, typename Dimensions, int Options_> class TensorStorage;
+
+
+// Pure fixed-size storage
+template<typename T, int Options_, typename FixedDimensions>
+class TensorStorage<T, FixedDimensions, Options_>
+{
+ private:
+  static const std::size_t Size = FixedDimensions::total_size;
+
+  // Allocate an array of size at least one to prevent compiler warnings.
+  static const std::size_t MinSize = max_n_1<Size>::size;
+  EIGEN_ALIGN_MAX T m_data[MinSize];
+
+  FixedDimensions m_dimensions;
+
+ public:
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE TensorStorage() {
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T *data() { return m_data; }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T *data() const { return m_data; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const FixedDimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE DenseIndex size() const { return m_dimensions.TotalSize(); }
+};
+
+
+// pure dynamic
+template<typename T, int Options_, typename IndexType, int NumIndices_>
+class TensorStorage<T, DSizes<IndexType, NumIndices_>, Options_>
+{
+  public:
+    typedef IndexType Index;
+    typedef DSizes<IndexType, NumIndices_> Dimensions;
+    typedef TensorStorage<T, DSizes<IndexType, NumIndices_>, Options_> Self;
+
+    EIGEN_DEVICE_FUNC TensorStorage() : m_data(0), m_dimensions() {
+      if (NumIndices_ == 0) {
+	m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(1);
+      }
+    }
+    EIGEN_DEVICE_FUNC TensorStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(0), m_dimensions(internal::template repeat<NumIndices_, Index>(0)) {}
+    EIGEN_DEVICE_FUNC TensorStorage(Index size, const array<Index, NumIndices_>& dimensions)
+        : m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(size)), m_dimensions(dimensions)
+      { EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    template <typename... DenseIndex>
+    EIGEN_DEVICE_FUNC TensorStorage(DenseIndex... indices) : m_dimensions(indices...) {
+      m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(internal::array_prod(m_dimensions));
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC TensorStorage(const Self& other)
+      : m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(internal::array_prod(other.m_dimensions)))
+      , m_dimensions(other.m_dimensions)
+    {
+      internal::smart_copy(other.m_data, other.m_data+internal::array_prod(other.m_dimensions), m_data);
+    }
+    EIGEN_DEVICE_FUNC Self& operator=(const Self& other)
+    {
+      if (this != &other) {
+        Self tmp(other);
+        this->swap(tmp);
+      }
+      return *this;
+    }
+
+    EIGEN_DEVICE_FUNC  ~TensorStorage() { internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, internal::array_prod(m_dimensions)); }
+    EIGEN_DEVICE_FUNC  void swap(Self& other)
+    { numext::swap(m_data,other.m_data); numext::swap(m_dimensions,other.m_dimensions); }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {return m_dimensions;}
+
+    EIGEN_DEVICE_FUNC void resize(Index size, const array<Index, NumIndices_>& nbDimensions)
+    {
+      const Index currentSz = internal::array_prod(m_dimensions);
+      if(size != currentSz)
+      {
+        internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, currentSz);
+        if (size)
+          m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(size);
+        else if (NumIndices_ == 0) {
+	  m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(1);
+	}
+	else 
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
+      }
+      m_dimensions = nbDimensions;
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T *data() { return m_data; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T *data() const { return m_data; }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); }
+
+ private:
+  T *m_data;
+  Dimensions m_dimensions;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSORSTORAGE_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorStriding.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorStriding.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorStriding.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorStriding.h
@@ -0,0 +1,338 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_STRIDING_H
+#define EIGEN_CXX11_TENSOR_TENSOR_STRIDING_H
+
+namespace Eigen {
+
+/** \class TensorStriding
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor striding class.
+  *
+  *
+  */
+namespace internal {
+template<typename Strides, typename XprType>
+struct traits<TensorStridingOp<Strides, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename Strides, typename XprType>
+struct eval<TensorStridingOp<Strides, XprType>, Eigen::Dense>
+{
+  typedef const TensorStridingOp<Strides, XprType>& type;
+};
+
+template<typename Strides, typename XprType>
+struct nested<TensorStridingOp<Strides, XprType>, 1, typename eval<TensorStridingOp<Strides, XprType> >::type>
+{
+  typedef TensorStridingOp<Strides, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename Strides, typename XprType>
+class TensorStridingOp : public TensorBase<TensorStridingOp<Strides, XprType> >
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorStridingOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorStridingOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorStridingOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorStridingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorStridingOp(const XprType& expr, const Strides& dims)
+      : m_xpr(expr), m_dims(dims) {}
+
+    EIGEN_DEVICE_FUNC
+    const Strides& strides() const { return m_dims; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorStridingOp& operator = (const TensorStridingOp& other)
+    {
+      typedef TensorAssignOp<TensorStridingOp, const TensorStridingOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorStridingOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorStridingOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const Strides m_dims;
+};
+
+
+// Eval as rvalue
+template<typename Strides, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
+{
+  typedef TensorStridingOp<Strides, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device)
+  {
+    m_dimensions = m_impl.dimensions();
+    for (int i = 0; i < NumDims; ++i) {
+      m_dimensions[i] = ceilf(static_cast<float>(m_dimensions[i]) / op.strides()[i]);
+    }
+
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_outputStrides[0] = 1;
+      m_inputStrides[0] = 1;
+      for (int i = 1; i < NumDims; ++i) {
+        m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
+        m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
+        m_inputStrides[i-1] *= op.strides()[i-1];
+      }
+      m_inputStrides[NumDims-1] *= op.strides()[NumDims-1];
+    } else {  // RowMajor
+      m_outputStrides[NumDims-1] = 1;
+      m_inputStrides[NumDims-1] = 1;
+      for (int i = NumDims - 2; i >= 0; --i) {
+        m_outputStrides[i] = m_outputStrides[i+1] * m_dimensions[i+1];
+        m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
+        m_inputStrides[i+1] *= op.strides()[i+1];
+      }
+      m_inputStrides[0] *= op.strides()[0];
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_impl.coeff(srcCoeff(index));
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    Index inputIndices[] = {0, 0};
+    Index indices[] = {index, index + PacketSize - 1};
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx0 = indices[0] / m_outputStrides[i];
+        const Index idx1 = indices[1] / m_outputStrides[i];
+        inputIndices[0] += idx0 * m_inputStrides[i];
+        inputIndices[1] += idx1 * m_inputStrides[i];
+        indices[0] -= idx0 * m_outputStrides[i];
+        indices[1] -= idx1 * m_outputStrides[i];
+      }
+      inputIndices[0] += indices[0] * m_inputStrides[0];
+      inputIndices[1] += indices[1] * m_inputStrides[0];
+    } else {  // RowMajor
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx0 = indices[0] / m_outputStrides[i];
+        const Index idx1 = indices[1] / m_outputStrides[i];
+        inputIndices[0] += idx0 * m_inputStrides[i];
+        inputIndices[1] += idx1 * m_inputStrides[i];
+        indices[0] -= idx0 * m_outputStrides[i];
+        indices[1] -= idx1 * m_outputStrides[i];
+      }
+      inputIndices[0] += indices[0] * m_inputStrides[NumDims-1];
+      inputIndices[1] += indices[1] * m_inputStrides[NumDims-1];
+    }
+    if (inputIndices[1] - inputIndices[0] == PacketSize - 1) {
+      PacketReturnType rslt = m_impl.template packet<Unaligned>(inputIndices[0]);
+      return rslt;
+    }
+    else {
+      EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+      values[0] = m_impl.coeff(inputIndices[0]);
+      values[PacketSize-1] = m_impl.coeff(inputIndices[1]);
+      for (int i = 1; i < PacketSize-1; ++i) {
+        values[i] = coeff(index+i);
+      }
+      PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+      return rslt;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    double compute_cost = (NumDims - 1) * (TensorOpCost::AddCost<Index>() +
+                                           TensorOpCost::MulCost<Index>() +
+                                           TensorOpCost::DivCost<Index>()) +
+        TensorOpCost::MulCost<Index>();
+    if (vectorized) {
+      compute_cost *= 2;  // packet() computes two indices
+    }
+    const int innerDim = (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? 0 : (NumDims - 1);
+    return m_impl.costPerCoeff(vectorized && m_inputStrides[innerDim] == 1) +
+        // Computation is not vectorized per se, but it is done once per packet.
+        TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ protected:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index srcCoeff(Index index) const
+  {
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx = index / m_outputStrides[i];
+        inputIndex += idx * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      inputIndex += index * m_inputStrides[0];
+    } else {  // RowMajor
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx = index / m_outputStrides[i];
+        inputIndex += idx * m_inputStrides[i];
+        index -= idx * m_outputStrides[i];
+      }
+      inputIndex += index * m_inputStrides[NumDims-1];
+    }
+    return inputIndex;
+  }
+
+  Dimensions m_dimensions;
+  array<Index, NumDims> m_outputStrides;
+  array<Index, NumDims> m_inputStrides;
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+
+// Eval as lvalue
+template<typename Strides, typename ArgType, typename Device>
+struct TensorEvaluator<TensorStridingOp<Strides, ArgType>, Device>
+    : public TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
+{
+  typedef TensorStridingOp<Strides, ArgType> XprType;
+  typedef TensorEvaluator<const XprType, Device> Base;
+  //  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  //  typedef DSizes<Index, NumDims> Dimensions;
+
+  enum {
+    IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : Base(op, device) { }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
+  {
+    return this->m_impl.coeffRef(this->srcCoeff(index));
+  }
+
+  template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void writePacket(Index index, const PacketReturnType& x)
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < this->dimensions().TotalSize());
+
+    Index inputIndices[] = {0, 0};
+    Index indices[] = {index, index + PacketSize - 1};
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumDims - 1; i > 0; --i) {
+        const Index idx0 = indices[0] / this->m_outputStrides[i];
+        const Index idx1 = indices[1] / this->m_outputStrides[i];
+        inputIndices[0] += idx0 * this->m_inputStrides[i];
+        inputIndices[1] += idx1 * this->m_inputStrides[i];
+        indices[0] -= idx0 * this->m_outputStrides[i];
+        indices[1] -= idx1 * this->m_outputStrides[i];
+      }
+      inputIndices[0] += indices[0] * this->m_inputStrides[0];
+      inputIndices[1] += indices[1] * this->m_inputStrides[0];
+    } else {  // RowMajor
+      for (int i = 0; i < NumDims - 1; ++i) {
+        const Index idx0 = indices[0] / this->m_outputStrides[i];
+        const Index idx1 = indices[1] / this->m_outputStrides[i];
+        inputIndices[0] += idx0 * this->m_inputStrides[i];
+        inputIndices[1] += idx1 * this->m_inputStrides[i];
+        indices[0] -= idx0 * this->m_outputStrides[i];
+        indices[1] -= idx1 * this->m_outputStrides[i];
+      }
+      inputIndices[0] += indices[0] * this->m_inputStrides[NumDims-1];
+      inputIndices[1] += indices[1] * this->m_inputStrides[NumDims-1];
+    }
+    if (inputIndices[1] - inputIndices[0] == PacketSize - 1) {
+      this->m_impl.template writePacket<Unaligned>(inputIndices[0], x);
+    }
+    else {
+      EIGEN_ALIGN_MAX Scalar values[PacketSize];
+      internal::pstore<Scalar, PacketReturnType>(values, x);
+      this->m_impl.coeffRef(inputIndices[0]) = values[0];
+      this->m_impl.coeffRef(inputIndices[1]) = values[PacketSize-1];
+      for (int i = 1; i < PacketSize-1; ++i) {
+        this->coeffRef(index+i) = values[i];
+      }
+    }
+  }
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_STRIDING_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSycl.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSycl.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSycl.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSycl.h
@@ -0,0 +1,82 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: eigen@codeplay.com
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+// General include header of SYCL target for Tensor Module
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_H
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_H
+
+#ifdef EIGEN_USE_SYCL
+
+// global pointer to set different attribute state for a class
+template <class T>
+struct MakeGlobalPointer {
+  typedef typename cl::sycl::global_ptr<T>::pointer_t Type;
+};
+
+// global pointer to set different attribute state for a class
+template <class T>
+struct MakeLocalPointer {
+  typedef typename cl::sycl::local_ptr<T>::pointer_t Type;
+};
+
+
+namespace Eigen {
+namespace TensorSycl {
+namespace internal {
+
+/// This struct is used for special expression nodes with no operations (for example assign and selectOP).
+  struct NoOP;
+
+template<bool IsConst, typename T> struct GetType{
+  typedef const T Type;
+};
+template<typename T> struct GetType<false, T>{
+  typedef T Type;
+};
+
+}
+}
+}
+
+// tuple construction
+#include "TensorSyclTuple.h"
+
+// counting number of leaf at compile time
+#include "TensorSyclLeafCount.h"
+
+// The index PlaceHolder takes the actual expression and replaces the actual
+// data on it with the place holder. It uses the same pre-order expression tree
+// traverse as the leaf count in order to give the right access number to each
+// node in the expression
+#include "TensorSyclPlaceHolderExpr.h"
+
+// creation of an accessor tuple from a tuple of SYCL buffers
+#include "TensorSyclExtractAccessor.h"
+
+// this is used to change the address space type in tensor map for GPU
+#include "TensorSyclConvertToDeviceExpression.h"
+
+// this is used to extract the functors
+#include "TensorSyclExtractFunctors.h"
+
+// this is used to create tensormap on the device
+// this is used to construct the expression on the device
+#include "TensorSyclExprConstructor.h"
+
+/// this is used for extracting tensor reduction
+#include "TensorReductionSycl.h"
+
+// kernel execution using fusion
+#include "TensorSyclRun.h"
+
+#endif  // end of EIGEN_USE_SYCL
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclConvertToDeviceExpression.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclConvertToDeviceExpression.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclConvertToDeviceExpression.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclConvertToDeviceExpression.h
@@ -0,0 +1,121 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensorSyclConvertToDeviceExpression.h
+ *
+ * \brief:
+ *  Conversion from host pointer to device pointer
+ *  inside leaf nodes of the expression.
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_CONVERT_TO_DEVICE_EXPRESSION_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_CONVERT_TO_DEVICE_EXPRESSION_HPP
+
+namespace Eigen {
+namespace TensorSycl {
+namespace internal {
+
+/// \struct ConvertToDeviceExpression
+/// \brief This struct is used to convert the MakePointer in the host expression
+/// to the MakeGlobalPointer for the device expression. For the leafNodes
+/// containing the pointer. This is due to the fact that the address space of
+/// the pointer T* is different on the host and the device.
+template <typename Expr>
+struct ConvertToDeviceExpression;
+
+template<template<class...> class NonOpCategory, bool IsConst, typename... Args>
+struct NonOpConversion{
+  typedef typename GetType<IsConst, NonOpCategory<typename ConvertToDeviceExpression<Args>::Type...> >::Type Type;
+};
+
+
+template<template<class, template <class> class > class NonOpCategory, bool IsConst, typename Args>
+struct DeviceConvertor{
+  typedef typename GetType<IsConst, NonOpCategory<typename ConvertToDeviceExpression<Args>::Type, MakeGlobalPointer> >::Type Type;
+};
+
+/// specialisation of the \ref ConvertToDeviceExpression struct when the node
+/// type is TensorMap
+#define TENSORMAPCONVERT(CVQual)\
+template <typename Scalar_, int Options_, int Options2_, int NumIndices_, typename IndexType_, template <class> class MakePointer_>\
+struct ConvertToDeviceExpression<CVQual TensorMap<Tensor<Scalar_, NumIndices_, Options_, IndexType_>, Options2_, MakePointer_> > {\
+  typedef CVQual TensorMap<Tensor<Scalar_, NumIndices_, Options_, IndexType_>, Options2_, MakeGlobalPointer> Type;\
+};
+
+TENSORMAPCONVERT(const)
+TENSORMAPCONVERT()
+#undef TENSORMAPCONVERT
+
+/// specialisation of the \ref ConvertToDeviceExpression struct when the node
+/// type is TensorCwiseNullaryOp, TensorCwiseUnaryOp, TensorCwiseBinaryOp, TensorCwiseTernaryOp, TensorBroadcastingOp
+#define CATEGORYCONVERT(CVQual)\
+template <template<class, class...> class Category, typename OP, typename... subExprs>\
+struct ConvertToDeviceExpression<CVQual Category<OP, subExprs...> > {\
+  typedef CVQual Category<OP, typename ConvertToDeviceExpression<subExprs>::Type... > Type;\
+};
+CATEGORYCONVERT(const)
+CATEGORYCONVERT()
+#undef CATEGORYCONVERT
+
+
+/// specialisation of the \ref ConvertToDeviceExpression struct when the node
+/// type is  TensorCwiseSelectOp
+#define SELECTOPCONVERT(CVQual, Res)\
+template <typename IfExpr, typename ThenExpr, typename ElseExpr>\
+struct ConvertToDeviceExpression<CVQual TensorSelectOp<IfExpr, ThenExpr, ElseExpr> >\
+: NonOpConversion<TensorSelectOp, Res, IfExpr, ThenExpr, ElseExpr> {};
+SELECTOPCONVERT(const, true)
+SELECTOPCONVERT(, false)
+#undef SELECTOPCONVERT
+
+/// specialisation of the \ref ConvertToDeviceExpression struct when the node
+/// type is const AssingOP
+#define ASSIGNCONVERT(CVQual, Res)\
+template <typename LHSExpr, typename RHSExpr>\
+struct ConvertToDeviceExpression<CVQual TensorAssignOp<LHSExpr, RHSExpr> >\
+: NonOpConversion<TensorAssignOp, Res, LHSExpr, RHSExpr>{};
+
+ASSIGNCONVERT(const, true)
+ASSIGNCONVERT(, false)
+#undef ASSIGNCONVERT
+
+/// specialisation of the \ref ConvertToDeviceExpression struct when the node
+/// type is either TensorForcedEvalOp or TensorEvalToOp
+#define KERNELBROKERCONVERT(CVQual, Res, ExprNode)\
+template <typename Expr>\
+struct ConvertToDeviceExpression<CVQual ExprNode<Expr> > \
+: DeviceConvertor<ExprNode, Res, Expr>{};
+
+KERNELBROKERCONVERT(const, true, TensorForcedEvalOp)
+KERNELBROKERCONVERT(, false, TensorForcedEvalOp)
+KERNELBROKERCONVERT(const, true, TensorEvalToOp)
+KERNELBROKERCONVERT(, false, TensorEvalToOp)
+#undef KERNELBROKERCONVERT
+
+/// specialisation of the \ref ConvertToDeviceExpression struct when the node type is TensorReductionOp
+#define KERNELBROKERCONVERTREDUCTION(CVQual)\
+template <typename OP, typename Dim, typename subExpr, template <class> class MakePointer_>\
+struct ConvertToDeviceExpression<CVQual TensorReductionOp<OP, Dim, subExpr, MakePointer_> > {\
+  typedef CVQual TensorReductionOp<OP, Dim, typename ConvertToDeviceExpression<subExpr>::Type, MakeGlobalPointer> Type;\
+};
+
+KERNELBROKERCONVERTREDUCTION(const)
+KERNELBROKERCONVERTREDUCTION()
+#undef KERNELBROKERCONVERTREDUCTION
+
+}  // namespace internal
+}  // namespace TensorSycl
+}  // namespace Eigen
+
+#endif  // UNSUPPORTED_EIGEN_CXX1

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExprConstructor.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExprConstructor.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExprConstructor.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExprConstructor.h
@@ -0,0 +1,239 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensorSyclExprConstructor.h
+ *
+ * \brief:
+ *  This file re-create an expression on the SYCL device in order
+ *  to use the original tensor evaluator.
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXPR_CONSTRUCTOR_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXPR_CONSTRUCTOR_HPP
+
+namespace Eigen {
+namespace TensorSycl {
+namespace internal {
+/// this class is used by EvalToOp in order to create an lhs expression which is
+/// a pointer from an accessor on device-only buffer
+template <typename PtrType, size_t N, typename... Params>
+struct EvalToLHSConstructor {
+  PtrType expr;
+  EvalToLHSConstructor(const utility::tuple::Tuple<Params...> &t): expr((&(*(utility::tuple::get<N>(t).get_pointer())))) {}
+};
+
+/// \struct ExprConstructor is used to reconstruct the expression on the device and
+/// recreate the expression with MakeGlobalPointer containing the device address
+/// space for the TensorMap pointers used in eval function.
+/// It receives the original expression type, the functor of the node, the tuple
+/// of accessors, and the device expression type to re-instantiate the
+/// expression tree for the device
+template <typename OrigExpr, typename IndexExpr, typename... Params>
+struct ExprConstructor;
+
+/// specialisation of the \ref ExprConstructor struct when the node type is
+/// TensorMap
+#define TENSORMAP(CVQual)\
+template <typename Scalar_, int Options_, int Options2_, int Options3_, int NumIndices_, typename IndexType_,\
+template <class> class MakePointer_, size_t N, typename... Params>\
+struct ExprConstructor< CVQual TensorMap<Tensor<Scalar_, NumIndices_, Options_, IndexType_>, Options2_, MakeGlobalPointer>,\
+CVQual PlaceHolder<CVQual TensorMap<Tensor<Scalar_, NumIndices_, Options_, IndexType_>, Options3_, MakePointer_>, N>, Params...>{\
+  typedef  CVQual TensorMap<Tensor<Scalar_, NumIndices_, Options_, IndexType_>, Options2_, MakeGlobalPointer>  Type;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &fd, const utility::tuple::Tuple<Params...> &t)\
+  : expr(Type((&(*(utility::tuple::get<N>(t).get_pointer()))), fd.dimensions())) {}\
+};
+
+TENSORMAP(const)
+TENSORMAP()
+#undef TENSORMAP
+
+#define UNARYCATEGORY(CVQual)\
+template <template<class, class> class UnaryCategory, typename OP, typename OrigRHSExpr, typename RHSExpr, typename... Params>\
+struct ExprConstructor<CVQual UnaryCategory<OP, OrigRHSExpr>, CVQual UnaryCategory<OP, RHSExpr>, Params...> {\
+  typedef  ExprConstructor<OrigRHSExpr, RHSExpr, Params...> my_type;\
+  my_type rhsExpr;\
+  typedef CVQual UnaryCategory<OP, typename my_type::Type> Type;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &funcD, const utility::tuple::Tuple<Params...> &t)\
+  : rhsExpr(funcD.rhsExpr, t), expr(rhsExpr.expr, funcD.func) {}\
+};
+
+UNARYCATEGORY(const)
+UNARYCATEGORY()
+#undef UNARYCATEGORY
+
+/// specialisation of the \ref ExprConstructor struct when the node type is
+/// TensorBinaryOp
+#define BINARYCATEGORY(CVQual)\
+template <template<class, class, class> class BinaryCategory, typename OP, typename OrigLHSExpr, typename OrigRHSExpr, typename LHSExpr,\
+typename RHSExpr, typename... Params>\
+struct ExprConstructor<CVQual BinaryCategory<OP, OrigLHSExpr, OrigRHSExpr>,  CVQual BinaryCategory<OP, LHSExpr, RHSExpr>, Params...> {\
+  typedef  ExprConstructor<OrigLHSExpr, LHSExpr, Params...> my_left_type;\
+  typedef  ExprConstructor<OrigRHSExpr, RHSExpr, Params...> my_right_type;\
+  typedef  CVQual BinaryCategory<OP, typename my_left_type::Type, typename my_right_type::Type> Type;\
+  my_left_type lhsExpr;\
+  my_right_type rhsExpr;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &funcD, const utility::tuple::Tuple<Params...> &t)\
+  : lhsExpr(funcD.lhsExpr, t),rhsExpr(funcD.rhsExpr, t), expr(lhsExpr.expr, rhsExpr.expr, funcD.func) {}\
+};
+
+BINARYCATEGORY(const)
+BINARYCATEGORY()
+#undef BINARYCATEGORY
+
+/// specialisation of the \ref ExprConstructor struct when the node type is
+/// TensorCwiseTernaryOp
+#define TERNARYCATEGORY(CVQual)\
+template <template <class, class, class, class> class TernaryCategory, typename OP, typename OrigArg1Expr, typename OrigArg2Expr,typename OrigArg3Expr,\
+typename Arg1Expr, typename Arg2Expr, typename Arg3Expr, typename... Params>\
+struct ExprConstructor<CVQual TernaryCategory<OP, OrigArg1Expr, OrigArg2Expr, OrigArg3Expr>, CVQual TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Params...> {\
+  typedef ExprConstructor<OrigArg1Expr, Arg1Expr, Params...> my_arg1_type;\
+  typedef ExprConstructor<OrigArg2Expr, Arg2Expr, Params...> my_arg2_type;\
+  typedef ExprConstructor<OrigArg3Expr, Arg3Expr, Params...> my_arg3_type;\
+  typedef  CVQual TernaryCategory<OP, typename my_arg1_type::Type, typename my_arg2_type::Type, typename my_arg3_type::Type> Type;\
+  my_arg1_type arg1Expr;\
+  my_arg2_type arg2Expr;\
+  my_arg3_type arg3Expr;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &funcD,const utility::tuple::Tuple<Params...> &t)\
+  : arg1Expr(funcD.arg1Expr, t), arg2Expr(funcD.arg2Expr, t), arg3Expr(funcD.arg3Expr, t), expr(arg1Expr.expr, arg2Expr.expr, arg3Expr.expr, funcD.func) {}\
+};
+
+TERNARYCATEGORY(const)
+TERNARYCATEGORY()
+#undef TERNARYCATEGORY
+
+/// specialisation of the \ref ExprConstructor struct when the node type is
+/// TensorCwiseSelectOp
+#define SELECTOP(CVQual)\
+template <typename OrigIfExpr, typename OrigThenExpr, typename OrigElseExpr, typename IfExpr, typename ThenExpr, typename ElseExpr, typename... Params>\
+struct ExprConstructor< CVQual TensorSelectOp<OrigIfExpr, OrigThenExpr, OrigElseExpr>, CVQual TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Params...> {\
+  typedef  ExprConstructor<OrigIfExpr, IfExpr, Params...> my_if_type;\
+  typedef  ExprConstructor<OrigThenExpr, ThenExpr, Params...> my_then_type;\
+  typedef  ExprConstructor<OrigElseExpr, ElseExpr, Params...> my_else_type;\
+  typedef CVQual TensorSelectOp<typename my_if_type::Type, typename my_then_type::Type, typename my_else_type::Type> Type;\
+  my_if_type ifExpr;\
+  my_then_type thenExpr;\
+  my_else_type elseExpr;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &funcD, const utility::tuple::Tuple<Params...> &t)\
+  : ifExpr(funcD.ifExpr, t), thenExpr(funcD.thenExpr, t), elseExpr(funcD.elseExpr, t), expr(ifExpr.expr, thenExpr.expr, elseExpr.expr) {}\
+};
+
+SELECTOP(const)
+SELECTOP()
+#undef SELECTOP
+
+/// specialisation of the \ref ExprConstructor struct when the node type is
+/// const TensorAssignOp
+#define ASSIGN(CVQual)\
+template <typename OrigLHSExpr, typename OrigRHSExpr, typename LHSExpr, typename RHSExpr, typename... Params>\
+struct ExprConstructor<CVQual TensorAssignOp<OrigLHSExpr, OrigRHSExpr>,  CVQual TensorAssignOp<LHSExpr, RHSExpr>, Params...> {\
+  typedef ExprConstructor<OrigLHSExpr, LHSExpr, Params...> my_left_type;\
+  typedef ExprConstructor<OrigRHSExpr, RHSExpr, Params...> my_right_type;\
+  typedef CVQual TensorAssignOp<typename my_left_type::Type, typename my_right_type::Type>  Type;\
+  my_left_type lhsExpr;\
+  my_right_type rhsExpr;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &funcD, const utility::tuple::Tuple<Params...> &t)\
+  : lhsExpr(funcD.lhsExpr, t), rhsExpr(funcD.rhsExpr, t), expr(lhsExpr.expr, rhsExpr.expr) {}\
+ };
+
+ ASSIGN(const)
+ ASSIGN()
+ #undef ASSIGN
+/// specialisation of the \ref ExprConstructor struct when the node type is
+///  TensorEvalToOp
+#define EVALTO(CVQual)\
+template <typename OrigExpr, typename Expr, typename... Params>\
+struct ExprConstructor<CVQual TensorEvalToOp<OrigExpr, MakeGlobalPointer>, CVQual TensorEvalToOp<Expr>, Params...> {\
+  typedef ExprConstructor<OrigExpr, Expr, Params...> my_expr_type;\
+  typedef typename TensorEvalToOp<OrigExpr, MakeGlobalPointer>::PointerType my_buffer_type;\
+  typedef CVQual TensorEvalToOp<typename my_expr_type::Type, MakeGlobalPointer> Type;\
+  my_expr_type nestedExpression;\
+  EvalToLHSConstructor<my_buffer_type, 0, Params...> buffer;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &funcD, const utility::tuple::Tuple<Params...> &t)\
+  : nestedExpression(funcD.rhsExpr, t), buffer(t), expr(buffer.expr, nestedExpression.expr) {}\
+};
+
+EVALTO(const)
+EVALTO()
+#undef EVALTO
+
+/// specialisation of the \ref ExprConstructor struct when the node type is
+/// TensorForcedEvalOp
+#define FORCEDEVAL(CVQual)\
+template <typename OrigExpr, typename DevExpr, size_t N, typename... Params>\
+struct ExprConstructor<CVQual TensorForcedEvalOp<OrigExpr, MakeGlobalPointer>,\
+CVQual PlaceHolder<CVQual TensorForcedEvalOp<DevExpr>, N>, Params...> {\
+  typedef CVQual TensorMap<Tensor<typename TensorForcedEvalOp<DevExpr, MakeGlobalPointer>::Scalar,\
+  TensorForcedEvalOp<DevExpr, MakeGlobalPointer>::NumDimensions, 0, typename TensorForcedEvalOp<DevExpr>::Index>, 0, MakeGlobalPointer> Type;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &fd, const utility::tuple::Tuple<Params...> &t)\
+  : expr(Type((&(*(utility::tuple::get<N>(t).get_pointer()))), fd.dimensions())) {}\
+};
+
+FORCEDEVAL(const)
+FORCEDEVAL()
+#undef FORCEDEVAL
+
+template <bool Conds,  size_t X , size_t Y > struct ValueCondition {
+  static const size_t Res =X;
+};
+template<size_t X, size_t Y> struct ValueCondition<false, X , Y> {
+  static const size_t Res =Y;
+};
+
+/// specialisation of the \ref ExprConstructor struct when the node type is TensorReductionOp
+#define SYCLREDUCTIONEXPR(CVQual)\
+template <typename OP, typename Dim, typename OrigExpr, typename DevExpr, size_t N, typename... Params>\
+struct ExprConstructor<CVQual TensorReductionOp<OP, Dim, OrigExpr, MakeGlobalPointer>,\
+CVQual PlaceHolder<CVQual TensorReductionOp<OP, Dim, DevExpr>, N>, Params...> {\
+  static const size_t NumIndices= ValueCondition< TensorReductionOp<OP, Dim, DevExpr, MakeGlobalPointer>::NumDimensions==0,  1, TensorReductionOp<OP, Dim, DevExpr, MakeGlobalPointer>::NumDimensions >::Res;\
+  typedef CVQual TensorMap<Tensor<typename TensorReductionOp<OP, Dim, DevExpr, MakeGlobalPointer>::Scalar,\
+  NumIndices, 0, typename TensorReductionOp<OP, Dim, DevExpr>::Index>, 0, MakeGlobalPointer> Type;\
+  Type expr;\
+  template <typename FuncDetector>\
+  ExprConstructor(FuncDetector &fd, const utility::tuple::Tuple<Params...> &t)\
+  : expr(Type((&(*(utility::tuple::get<N>(t).get_pointer()))), fd.dimensions())) {}\
+};
+
+SYCLREDUCTIONEXPR(const)
+SYCLREDUCTIONEXPR()
+#undef SYCLREDUCTIONEXPR
+
+/// template deduction for \ref ExprConstructor struct
+template <typename OrigExpr, typename IndexExpr, typename FuncD, typename... Params>
+auto createDeviceExpression(FuncD &funcD, const utility::tuple::Tuple<Params...> &t)
+    -> decltype(ExprConstructor<OrigExpr, IndexExpr, Params...>(funcD, t)) {
+  return ExprConstructor<OrigExpr, IndexExpr, Params...>(funcD, t);
+}
+
+} /// namespace TensorSycl
+} /// namespace internal
+} /// namespace Eigen
+
+
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXPR_CONSTRUCTOR_HPP

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractAccessor.h
@@ -0,0 +1,204 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensorSyclExtractAccessor.h
+ *
+ * \brief:
+ * ExtractAccessor takes Expression placeHolder expression and the tuple of sycl
+ * buffers as an input. Using pre-order tree traversal, ExtractAccessor
+ * recursively calls itself for its children in the expression tree. The
+ * leaf node in the PlaceHolder expression is nothing but a container preserving
+ * the order of the actual data in the tuple of sycl buffer. By invoking the
+ * extract accessor for the PlaceHolder<N>, an accessor is created for the Nth
+ * buffer in the tuple of buffers. This accessor is then added as an Nth
+ * element in the tuple of accessors. In this case we preserve the order of data
+ * in the expression tree.
+ *
+ * This is the specialisation of extract accessor method for different operation
+ * type in the PlaceHolder expression.
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXTRACT_ACCESSOR_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXTRACT_ACCESSOR_HPP
+
+namespace Eigen {
+namespace TensorSycl {
+namespace internal {
+/// \struct ExtractAccessor: Extract Accessor Class is used to extract the
+/// accessor from a buffer.
+/// Depending on the type of the leaf node we can get a read accessor or a
+/// read_write accessor
+template <typename Evaluator>
+struct ExtractAccessor;
+
+struct AccessorConstructor{
+  template<typename Arg> static inline auto getTuple(cl::sycl::handler& cgh, Arg eval)
+  -> decltype(ExtractAccessor<Arg>::getTuple(cgh, eval)) {
+  return ExtractAccessor<Arg>::getTuple(cgh, eval);
+  }
+
+  template<typename Arg1, typename Arg2> static inline auto getTuple(cl::sycl::handler& cgh, Arg1 eval1, Arg2 eval2)
+  -> decltype(utility::tuple::append(ExtractAccessor<Arg1>::getTuple(cgh, eval1), ExtractAccessor<Arg2>::getTuple(cgh, eval2))) {
+    return utility::tuple::append(ExtractAccessor<Arg1>::getTuple(cgh, eval1), ExtractAccessor<Arg2>::getTuple(cgh, eval2));
+  }
+  template<typename Arg1, typename Arg2, typename Arg3>	static inline auto getTuple(cl::sycl::handler& cgh, Arg1 eval1 , Arg2 eval2 , Arg3 eval3)
+  -> decltype(utility::tuple::append(ExtractAccessor<Arg1>::getTuple(cgh, eval1),utility::tuple::append(ExtractAccessor<Arg2>::getTuple(cgh, eval2), ExtractAccessor<Arg3>::getTuple(cgh, eval3)))) {
+    return utility::tuple::append(ExtractAccessor<Arg1>::getTuple(cgh, eval1),utility::tuple::append(ExtractAccessor<Arg2>::getTuple(cgh, eval2), ExtractAccessor<Arg3>::getTuple(cgh, eval3)));
+  }
+  template< cl::sycl::access::mode AcM, typename Arg> static inline auto getAccessor(cl::sycl::handler& cgh, Arg eval)
+  -> decltype(utility::tuple::make_tuple( eval.device().template get_sycl_accessor<AcM,
+  typename Eigen::internal::remove_all<typename Arg::CoeffReturnType>::type>(eval.dimensions().TotalSize(), cgh,eval.data()))){
+    return utility::tuple::make_tuple(eval.device().template get_sycl_accessor<AcM, typename Eigen::internal::remove_all<typename Arg::CoeffReturnType>::type>(eval.dimensions().TotalSize(), cgh,eval.data()));
+  }
+};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is
+/// const TensorCwiseNullaryOp, const TensorCwiseUnaryOp and const TensorBroadcastingOp
+template <template<class, class> class UnaryCategory, typename OP, typename RHSExpr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<const UnaryCategory<OP, RHSExpr>, Dev> > {
+  static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const UnaryCategory<OP, RHSExpr>, Dev> eval)
+  -> decltype(AccessorConstructor::getTuple(cgh, eval.impl())){
+    return AccessorConstructor::getTuple(cgh, eval.impl());
+  }
+};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is TensorCwiseNullaryOp,  TensorCwiseUnaryOp and  TensorBroadcastingOp
+template <template<class, class> class UnaryCategory, typename OP, typename RHSExpr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<UnaryCategory<OP, RHSExpr>, Dev> >
+: ExtractAccessor<TensorEvaluator<const UnaryCategory<OP, RHSExpr>, Dev> > {};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is const TensorCwiseBinaryOp
+template <template<class, class, class> class BinaryCategory, typename OP,  typename LHSExpr, typename RHSExpr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<const BinaryCategory<OP, LHSExpr, RHSExpr>, Dev> > {
+  static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const BinaryCategory<OP, LHSExpr, RHSExpr>, Dev> eval)
+  -> decltype(AccessorConstructor::getTuple(cgh, eval.left_impl(), eval.right_impl())){
+    return AccessorConstructor::getTuple(cgh, eval.left_impl(), eval.right_impl());
+  }
+};
+/// specialisation of the \ref ExtractAccessor struct when the node type is TensorCwiseBinaryOp
+template <template<class, class, class> class BinaryCategory, typename OP,  typename LHSExpr, typename RHSExpr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<BinaryCategory<OP, LHSExpr, RHSExpr>, Dev> >
+: ExtractAccessor<TensorEvaluator<const BinaryCategory<OP, LHSExpr, RHSExpr>, Dev> >{};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is
+/// const TensorCwiseTernaryOp
+template <template<class, class, class, class> class TernaryCategory, typename OP, typename Arg1Expr, typename Arg2Expr, typename Arg3Expr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<const TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Dev> > {
+  static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Dev> eval)
+  -> decltype(AccessorConstructor::getTuple(cgh, eval.arg1Impl(), eval.arg2Impl(), eval.arg3Impl())){
+    return AccessorConstructor::getTuple(cgh, eval.arg1Impl(), eval.arg2Impl(), eval.arg3Impl());
+  }
+};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is TensorCwiseTernaryOp
+template <template<class, class, class, class> class TernaryCategory, typename OP, typename Arg1Expr, typename Arg2Expr, typename Arg3Expr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Dev> >
+: ExtractAccessor<TensorEvaluator<const TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Dev> >{};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is
+/// const TensorCwiseSelectOp. This is a special case where there is no OP
+template <typename IfExpr, typename ThenExpr, typename ElseExpr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<const TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Dev> > {
+  static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Dev> eval)
+  -> decltype(AccessorConstructor::getTuple(cgh, eval.cond_impl(), eval.then_impl(), eval.else_impl())){
+    return AccessorConstructor::getTuple(cgh, eval.cond_impl(), eval.then_impl(), eval.else_impl());
+  }
+};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is
+/// TensorCwiseSelectOp. This is a special case where there is no OP
+template <typename IfExpr, typename ThenExpr, typename ElseExpr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Dev> >
+: ExtractAccessor<TensorEvaluator<const TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Dev> >{};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is const TensorAssignOp
+template <typename LHSExpr, typename RHSExpr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<const TensorAssignOp<LHSExpr, RHSExpr>, Dev> > {
+  static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const TensorAssignOp<LHSExpr, RHSExpr>, Dev> eval)
+  -> decltype(AccessorConstructor::getTuple(cgh, eval.left_impl(), eval.right_impl())){
+    return AccessorConstructor::getTuple(cgh, eval.left_impl(), eval.right_impl());
+ }
+};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is TensorAssignOp
+template <typename LHSExpr, typename RHSExpr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<TensorAssignOp<LHSExpr, RHSExpr>, Dev> >
+: ExtractAccessor<TensorEvaluator<const TensorAssignOp<LHSExpr, RHSExpr>, Dev> >{};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is const TensorMap
+#define TENSORMAPEXPR(CVQual, ACCType)\
+template <typename PlainObjectType, int Options_, typename Dev>\
+struct ExtractAccessor<TensorEvaluator<CVQual TensorMap<PlainObjectType, Options_>, Dev> > {\
+  static inline auto getTuple(cl::sycl::handler& cgh,const TensorEvaluator<CVQual TensorMap<PlainObjectType, Options_>, Dev> eval)\
+  -> decltype(AccessorConstructor::template getAccessor<ACCType>(cgh, eval)){\
+    return AccessorConstructor::template getAccessor<ACCType>(cgh, eval);\
+  }\
+};
+TENSORMAPEXPR(const, cl::sycl::access::mode::read)
+TENSORMAPEXPR(, cl::sycl::access::mode::read_write)
+#undef TENSORMAPEXPR
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is const TensorForcedEvalOp
+template <typename Expr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<const TensorForcedEvalOp<Expr>, Dev> > {
+  static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const TensorForcedEvalOp<Expr>, Dev> eval)
+  -> decltype(AccessorConstructor::template getAccessor<cl::sycl::access::mode::read>(cgh, eval)){
+    return AccessorConstructor::template getAccessor<cl::sycl::access::mode::read>(cgh, eval);
+  }
+};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is TensorForcedEvalOp
+template <typename Expr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<TensorForcedEvalOp<Expr>, Dev> >
+: ExtractAccessor<TensorEvaluator<const TensorForcedEvalOp<Expr>, Dev> >{};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is const TensorEvalToOp
+template <typename Expr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<const TensorEvalToOp<Expr>, Dev> > {
+  static inline auto getTuple(cl::sycl::handler& cgh,const TensorEvaluator<const TensorEvalToOp<Expr>, Dev> eval)
+  -> decltype(utility::tuple::append(AccessorConstructor::template getAccessor<cl::sycl::access::mode::write>(cgh, eval), AccessorConstructor::getTuple(cgh, eval.impl()))){
+    return utility::tuple::append(AccessorConstructor::template getAccessor<cl::sycl::access::mode::write>(cgh, eval), AccessorConstructor::getTuple(cgh, eval.impl()));
+  }
+};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is TensorEvalToOp
+template <typename Expr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<TensorEvalToOp<Expr>, Dev> >
+: ExtractAccessor<TensorEvaluator<const TensorEvalToOp<Expr>, Dev> >{};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is const TensorReductionOp
+template <typename OP, typename Dim, typename Expr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<const TensorReductionOp<OP, Dim, Expr>, Dev> > {
+  static inline auto getTuple(cl::sycl::handler& cgh, const TensorEvaluator<const TensorReductionOp<OP, Dim, Expr>, Dev> eval)
+  -> decltype(AccessorConstructor::template getAccessor<cl::sycl::access::mode::read>(cgh, eval)){
+    return AccessorConstructor::template getAccessor<cl::sycl::access::mode::read>(cgh, eval);
+  }
+};
+
+/// specialisation of the \ref ExtractAccessor struct when the node type is TensorReductionOp
+template <typename OP, typename Dim, typename Expr, typename Dev>
+struct ExtractAccessor<TensorEvaluator<TensorReductionOp<OP, Dim, Expr>, Dev> >
+: ExtractAccessor<TensorEvaluator<const TensorReductionOp<OP, Dim, Expr>, Dev> >{};
+
+/// template deduction for \ref ExtractAccessor
+template <typename Evaluator>
+auto createTupleOfAccessors(cl::sycl::handler& cgh, const Evaluator& expr)
+-> decltype(ExtractAccessor<Evaluator>::getTuple(cgh, expr)) {
+  return ExtractAccessor<Evaluator>::getTuple(cgh, expr);
+}
+
+} /// namespace TensorSycl
+} /// namespace internal
+} /// namespace Eigen
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXTRACT_ACCESSOR_HPP

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractFunctors.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractFunctors.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractFunctors.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclExtractFunctors.h
@@ -0,0 +1,177 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensorSyclextractFunctors.h
+ *
+ * \brief:
+ *  Used to extract all the functors allocated to each node of the expression
+*tree.
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXTRACT_FUNCTORS_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXTRACT_FUNCTORS_HPP
+
+namespace Eigen {
+namespace TensorSycl {
+namespace internal {
+/// \struct FunctorExtractor:  This struct is used to extract the functors
+/// constructed on
+/// the host-side, to pack them and reuse them in reconstruction of the
+/// expression on the device.
+/// We have to do that as in Eigen the functors are not stateless so we cannot
+/// re-instantiate them on the device.
+/// We have to pass instantiated functors to the device.
+// This struct is used for leafNode (TensorMap) and nodes behaving like leafNode (TensorForcedEval).
+template <typename Evaluator> struct FunctorExtractor{
+  typedef typename Evaluator::Dimensions Dimensions;
+  const Dimensions m_dimensions;
+  const Dimensions& dimensions() const { return m_dimensions; }
+  FunctorExtractor(const Evaluator& expr)
+  : m_dimensions(expr.dimensions()) {}
+
+};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// const TensorCwiseNullaryOp, const TensorCwiseUnaryOp, and const TensorBroadcastingOp
+template <template <class, class> class UnaryCategory, typename OP, typename RHSExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<const UnaryCategory<OP, RHSExpr>, Dev> > {
+  FunctorExtractor<TensorEvaluator<RHSExpr, Dev> > rhsExpr;
+  OP func;
+  FunctorExtractor(const TensorEvaluator<const UnaryCategory<OP, RHSExpr>, Dev>& expr)
+  : rhsExpr(expr.impl()), func(expr.functor()) {}
+};
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// TensorCwiseNullaryOp, TensorCwiseUnaryOp, and TensorBroadcastingOp
+template <template <class, class> class UnaryCategory, typename OP, typename RHSExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<UnaryCategory<OP, RHSExpr>, Dev> >
+: FunctorExtractor<TensorEvaluator<const UnaryCategory<OP, RHSExpr>, Dev> >{};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// const TensorCwiseBinaryOp
+template <template<class, class, class> class BinaryCategory, typename OP, typename LHSExpr, typename RHSExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<const BinaryCategory<OP, LHSExpr, RHSExpr>, Dev> > {
+  FunctorExtractor<TensorEvaluator<LHSExpr, Dev> > lhsExpr;
+  FunctorExtractor<TensorEvaluator<RHSExpr, Dev> > rhsExpr;
+  OP func;
+  FunctorExtractor(const TensorEvaluator<const BinaryCategory<OP, LHSExpr, RHSExpr>, Dev>& expr)
+  : lhsExpr(expr.left_impl()),rhsExpr(expr.right_impl()),func(expr.functor()) {}
+};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// const TensorCwiseBinaryOp
+template <template <class, class, class> class BinaryCategory, typename OP, typename LHSExpr, typename RHSExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<BinaryCategory<OP,  LHSExpr, RHSExpr>, Dev> >
+: FunctorExtractor<TensorEvaluator<const BinaryCategory<OP,  LHSExpr, RHSExpr>, Dev> >{};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// const TensorCwiseTernaryOp
+template <template <class, class, class, class> class TernaryCategory, typename OP, typename Arg1Expr, typename Arg2Expr, typename Arg3Expr,typename Dev>
+struct FunctorExtractor<TensorEvaluator<const TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Dev> > {
+  FunctorExtractor<TensorEvaluator<Arg1Expr, Dev> > arg1Expr;
+  FunctorExtractor<TensorEvaluator<Arg2Expr, Dev> > arg2Expr;
+  FunctorExtractor<TensorEvaluator<Arg3Expr, Dev> > arg3Expr;
+  OP func;
+  FunctorExtractor(const TensorEvaluator<const TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Dev>& expr)
+  : arg1Expr(expr.arg1Impl()), arg2Expr(expr.arg2Impl()), arg3Expr(expr.arg3Impl()), func(expr.functor()) {}
+};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// TensorCwiseTernaryOp
+template <template <class, class, class, class> class TernaryCategory, typename OP, typename Arg1Expr, typename Arg2Expr, typename Arg3Expr, typename Dev>
+struct FunctorExtractor<TensorEvaluator< TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Dev> >
+:FunctorExtractor<TensorEvaluator<const TernaryCategory<OP, Arg1Expr, Arg2Expr, Arg3Expr>, Dev> >{};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// const TensorCwiseSelectOp. This is an specialisation without OP so it has to be separated.
+template <typename IfExpr, typename ThenExpr, typename ElseExpr, typename Dev>
+struct FunctorExtractor< TensorEvaluator<const TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Dev> > {
+  FunctorExtractor<TensorEvaluator<IfExpr, Dev> > ifExpr;
+  FunctorExtractor<TensorEvaluator<ThenExpr, Dev> > thenExpr;
+  FunctorExtractor<TensorEvaluator<ElseExpr, Dev> > elseExpr;
+  FunctorExtractor(const TensorEvaluator<const TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Dev>& expr)
+  : ifExpr(expr.cond_impl()), thenExpr(expr.then_impl()), elseExpr(expr.else_impl()) {}
+};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// TensorCwiseSelectOp. This is an specialisation without OP so it has to be separated
+template <typename IfExpr, typename ThenExpr, typename ElseExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Dev> >
+:FunctorExtractor< TensorEvaluator<const TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, Dev> > {};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// const TensorAssignOp. This is an specialisation without OP so it has to be separated.
+template <typename LHSExpr, typename RHSExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<const TensorAssignOp<LHSExpr, RHSExpr>, Dev> > {
+  FunctorExtractor<TensorEvaluator<LHSExpr, Dev> > lhsExpr;
+  FunctorExtractor<TensorEvaluator<RHSExpr, Dev> > rhsExpr;
+  FunctorExtractor(const TensorEvaluator<const TensorAssignOp<LHSExpr, RHSExpr>, Dev>& expr)
+  : lhsExpr(expr.left_impl()), rhsExpr(expr.right_impl()) {}
+};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// TensorAssignOp. This is an specialisation without OP so it has to be separated.
+template <typename LHSExpr, typename RHSExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<TensorAssignOp<LHSExpr, RHSExpr>, Dev> >
+:FunctorExtractor<TensorEvaluator<const TensorAssignOp<LHSExpr, RHSExpr>, Dev> >{};
+
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// const TensorEvalToOp, This is an specialisation without OP so it has to be separated.
+template <typename RHSExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<const TensorEvalToOp<RHSExpr>, Dev> > {
+  FunctorExtractor<TensorEvaluator<RHSExpr, Dev> > rhsExpr;
+  FunctorExtractor(const TensorEvaluator<const TensorEvalToOp<RHSExpr>, Dev>& expr)
+  : rhsExpr(expr.impl()) {}
+};
+
+/// specialisation of the \ref FunctorExtractor struct when the node type is
+/// TensorEvalToOp. This is a specialisation without OP so it has to be separated.
+template <typename RHSExpr, typename Dev>
+struct FunctorExtractor<TensorEvaluator<TensorEvalToOp<RHSExpr>, Dev> >
+: FunctorExtractor<TensorEvaluator<const TensorEvalToOp<RHSExpr>, Dev> > {};
+
+template<typename Dim, size_t NumOutputDim> struct DimConstr {
+template<typename InDim>
+  static inline Dim getDim(InDim dims ) {return dims;}
+};
+
+template<typename Dim> struct DimConstr<Dim, 0> {
+  template<typename InDim>
+    static inline Dim getDim(InDim dims ) {return Dim(dims.TotalSize());}
+};
+
+template<typename Op, typename Dims, typename ArgType, template <class> class MakePointer_, typename Device>
+struct FunctorExtractor<TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType, MakePointer_>, Device>>{
+  typedef TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType, MakePointer_>, Device> Evaluator;
+  typedef typename Eigen::internal::conditional<Evaluator::NumOutputDims==0, DSizes<typename Evaluator::Index, 1>, typename Evaluator::Dimensions >::type Dimensions;
+  const Dimensions m_dimensions;
+  const Dimensions& dimensions() const { return m_dimensions; }
+  FunctorExtractor(const TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType, MakePointer_>, Device>& expr)
+  : m_dimensions(DimConstr<Dimensions, Evaluator::NumOutputDims>::getDim(expr.dimensions())) {}
+};
+
+
+template<typename Op, typename Dims, typename ArgType, template <class> class MakePointer_, typename Device>
+struct FunctorExtractor<TensorEvaluator<TensorReductionOp<Op, Dims, ArgType, MakePointer_>, Device>>
+: FunctorExtractor<TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType, MakePointer_>, Device>>{};
+/// template deduction function for FunctorExtractor
+template <typename Evaluator>
+auto inline extractFunctors(const Evaluator& evaluator)-> FunctorExtractor<Evaluator> {
+  return FunctorExtractor<Evaluator>(evaluator);
+}
+}  // namespace internal
+}  // namespace TensorSycl
+}  // namespace Eigen
+
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_EXTRACT_FUNCTORS_HPP

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclLeafCount.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclLeafCount.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclLeafCount.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclLeafCount.h
@@ -0,0 +1,114 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensorSyclLeafCount.h
+ *
+ * \brief:
+ *  The leaf count used the pre-order expression tree traverse in order to name
+ *  count the number of leaf nodes in the expression
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_LEAF_COUNT_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_LEAF_COUNT_HPP
+
+namespace Eigen {
+namespace TensorSycl {
+namespace internal {
+/// \brief LeafCount used to counting terminal nodes. The total number of
+/// leaf nodes is used by MakePlaceHolderExprHelper to find the order
+/// of the leaf node in a expression tree at compile time.
+template <typename Expr>
+struct LeafCount;
+
+template<typename... Args> struct CategoryCount;
+
+template<> struct CategoryCount<>
+{
+  static const size_t Count =0;
+};
+
+template<typename Arg, typename... Args>
+struct CategoryCount<Arg,Args...>{
+  static const size_t Count = LeafCount<Arg>::Count + CategoryCount<Args...>::Count;
+};
+
+/// specialisation of the \ref LeafCount struct when the node type is const TensorMap
+template <typename PlainObjectType, int Options_, template <class> class MakePointer_>
+struct LeafCount<const TensorMap<PlainObjectType, Options_, MakePointer_> > {
+  static const size_t Count =1;
+};
+
+/// specialisation of the \ref LeafCount struct when the node type is TensorMap
+template <typename PlainObjectType, int Options_, template <class> class MakePointer_>
+struct LeafCount<TensorMap<PlainObjectType, Options_, MakePointer_> > :LeafCount<const TensorMap<PlainObjectType, Options_, MakePointer_> >{};
+
+// const TensorCwiseUnaryOp, const TensorCwiseNullaryOp, const TensorCwiseBinaryOp, const TensorCwiseTernaryOp, and Const TensorBroadcastingOp
+template <template <class, class...> class CategoryExpr, typename OP, typename... RHSExpr>
+struct LeafCount<const CategoryExpr<OP, RHSExpr...> >: CategoryCount<RHSExpr...> {};
+// TensorCwiseUnaryOp,  TensorCwiseNullaryOp,  TensorCwiseBinaryOp,  TensorCwiseTernaryOp, and  TensorBroadcastingOp
+template <template <class, class...> class CategoryExpr, typename OP, typename... RHSExpr>
+struct LeafCount<CategoryExpr<OP, RHSExpr...> > :LeafCount<const CategoryExpr<OP, RHSExpr...> >{};
+
+/// specialisation of the \ref LeafCount struct when the node type is const TensorSelectOp is an exception
+template <typename IfExpr, typename ThenExpr, typename ElseExpr>
+struct LeafCount<const TensorSelectOp<IfExpr, ThenExpr, ElseExpr> > : CategoryCount<IfExpr, ThenExpr, ElseExpr> {};
+/// specialisation of the \ref LeafCount struct when the node type is TensorSelectOp
+template <typename IfExpr, typename ThenExpr, typename ElseExpr>
+struct LeafCount<TensorSelectOp<IfExpr, ThenExpr, ElseExpr> >: LeafCount<const TensorSelectOp<IfExpr, ThenExpr, ElseExpr> > {};
+
+
+/// specialisation of the \ref LeafCount struct when the node type is const TensorAssignOp
+template <typename LHSExpr, typename RHSExpr>
+struct LeafCount<const TensorAssignOp<LHSExpr, RHSExpr> >: CategoryCount<LHSExpr,RHSExpr> {};
+
+/// specialisation of the \ref LeafCount struct when the node type is
+/// TensorAssignOp is an exception. It is not the same as Unary
+template <typename LHSExpr, typename RHSExpr>
+struct LeafCount<TensorAssignOp<LHSExpr, RHSExpr> > :LeafCount<const TensorAssignOp<LHSExpr, RHSExpr> >{};
+
+/// specialisation of the \ref LeafCount struct when the node type is const TensorForcedEvalOp
+template <typename Expr>
+struct LeafCount<const TensorForcedEvalOp<Expr> > {
+    static const size_t Count =1;
+};
+
+/// specialisation of the \ref LeafCount struct when the node type is TensorForcedEvalOp
+template <typename Expr>
+struct LeafCount<TensorForcedEvalOp<Expr> >: LeafCount<const TensorForcedEvalOp<Expr> > {};
+
+/// specialisation of the \ref LeafCount struct when the node type is const TensorEvalToOp
+template <typename Expr>
+struct LeafCount<const TensorEvalToOp<Expr> > {
+  static const size_t Count = 1 + CategoryCount<Expr>::Count;
+};
+
+/// specialisation of the \ref LeafCount struct when the node type is const TensorReductionOp
+template <typename OP, typename Dim, typename Expr>
+struct LeafCount<const TensorReductionOp<OP, Dim, Expr> > {
+    static const size_t Count =1;
+};
+
+/// specialisation of the \ref LeafCount struct when the node type is TensorReductionOp
+template <typename OP, typename Dim, typename Expr>
+struct LeafCount<TensorReductionOp<OP, Dim, Expr> >: LeafCount<const TensorReductionOp<OP, Dim, Expr> >{};
+
+/// specialisation of the \ref LeafCount struct when the node type is TensorEvalToOp
+template <typename Expr>
+struct LeafCount<TensorEvalToOp<Expr> >: LeafCount<const TensorEvalToOp<Expr> >{};
+
+} /// namespace TensorSycl
+} /// namespace internal
+} /// namespace Eigen
+
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_LEAF_COUNT_HPP

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclPlaceHolderExpr.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclPlaceHolderExpr.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclPlaceHolderExpr.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclPlaceHolderExpr.h
@@ -0,0 +1,181 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensorSyclPlaceHolderExpr.h
+ *
+ * \brief:
+ *  This is the specialisation of the placeholder expression based on the
+ * operation type
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_PLACEHOLDER_EXPR_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_PLACEHOLDER_EXPR_HPP
+
+namespace Eigen {
+namespace TensorSycl {
+namespace internal {
+
+/// \struct PlaceHolder
+/// \brief PlaceHolder is used to replace the \ref TensorMap in the expression
+/// tree.
+/// PlaceHolder contains the order of the leaf node in the expression tree.
+template <typename Scalar, size_t N>
+struct PlaceHolder {
+  static constexpr size_t I = N;
+  typedef Scalar Type;
+};
+
+/// \sttruct PlaceHolderExpression
+/// \brief it is used to create the PlaceHolder expression. The PlaceHolder
+/// expression is a copy of expression type in which the TensorMap of the has
+/// been replaced with PlaceHolder.
+template <typename Expr, size_t N>
+struct PlaceHolderExpression;
+
+template<size_t N, typename... Args>
+struct CalculateIndex;
+
+template<size_t N, typename Arg>
+struct CalculateIndex<N, Arg>{
+  typedef typename PlaceHolderExpression<Arg, N>::Type ArgType;
+  typedef utility::tuple::Tuple<ArgType> ArgsTuple;
+};
+
+template<size_t N, typename Arg1, typename Arg2>
+struct CalculateIndex<N, Arg1, Arg2>{
+  static const size_t Arg2LeafCount = LeafCount<Arg2>::Count;
+  typedef typename PlaceHolderExpression<Arg1, N - Arg2LeafCount>::Type Arg1Type;
+  typedef typename PlaceHolderExpression<Arg2, N>::Type Arg2Type;
+  typedef utility::tuple::Tuple<Arg1Type, Arg2Type> ArgsTuple;
+};
+
+template<size_t N, typename Arg1, typename Arg2, typename Arg3>
+struct CalculateIndex<N, Arg1, Arg2, Arg3> {
+  static const size_t Arg3LeafCount = LeafCount<Arg3>::Count;
+  static const size_t Arg2LeafCount = LeafCount<Arg2>::Count;
+  typedef typename PlaceHolderExpression<Arg1, N - Arg3LeafCount - Arg2LeafCount>::Type Arg1Type;
+  typedef typename PlaceHolderExpression<Arg2, N - Arg3LeafCount>::Type Arg2Type;
+  typedef typename PlaceHolderExpression<Arg3, N>::Type Arg3Type;
+  typedef utility::tuple::Tuple<Arg1Type, Arg2Type, Arg3Type> ArgsTuple;
+};
+
+template<template<class...> class Category , class OP, class TPL>
+struct CategoryHelper;
+
+template<template<class...> class Category , class OP, class ...T >
+struct CategoryHelper<Category, OP, utility::tuple::Tuple<T...> > {
+  typedef Category<OP, T... > Type;
+};
+
+template<template<class...> class Category , class ...T >
+struct CategoryHelper<Category, NoOP, utility::tuple::Tuple<T...> > {
+  typedef Category<T... > Type;
+};
+
+/// specialisation of the \ref PlaceHolderExpression when the node is
+/// TensorCwiseNullaryOp, TensorCwiseUnaryOp, TensorBroadcastingOp, TensorCwiseBinaryOp,  TensorCwiseTernaryOp
+#define OPEXPRCATEGORY(CVQual)\
+template <template <class, class... > class Category, typename OP, typename... SubExpr, size_t N>\
+struct PlaceHolderExpression<CVQual Category<OP, SubExpr...>, N>{\
+  typedef CVQual typename CategoryHelper<Category, OP, typename CalculateIndex<N, SubExpr...>::ArgsTuple>::Type Type;\
+};
+
+OPEXPRCATEGORY(const)
+OPEXPRCATEGORY()
+#undef OPEXPRCATEGORY
+
+/// specialisation of the \ref PlaceHolderExpression when the node is
+/// TensorCwiseSelectOp
+#define SELECTEXPR(CVQual)\
+template <typename IfExpr, typename ThenExpr, typename ElseExpr, size_t N>\
+struct PlaceHolderExpression<CVQual TensorSelectOp<IfExpr, ThenExpr, ElseExpr>, N> {\
+  typedef CVQual typename CategoryHelper<TensorSelectOp, NoOP, typename CalculateIndex<N, IfExpr, ThenExpr, ElseExpr>::ArgsTuple>::Type Type;\
+};
+
+SELECTEXPR(const)
+SELECTEXPR()
+#undef SELECTEXPR
+
+/// specialisation of the \ref PlaceHolderExpression when the node is
+/// TensorAssignOp
+#define ASSIGNEXPR(CVQual)\
+template <typename LHSExpr, typename RHSExpr, size_t N>\
+struct PlaceHolderExpression<CVQual TensorAssignOp<LHSExpr, RHSExpr>, N> {\
+  typedef CVQual typename CategoryHelper<TensorAssignOp, NoOP, typename CalculateIndex<N, LHSExpr, RHSExpr>::ArgsTuple>::Type Type;\
+};
+
+ASSIGNEXPR(const)
+ASSIGNEXPR()
+#undef ASSIGNEXPR
+
+/// specialisation of the \ref PlaceHolderExpression when the node is
+/// TensorMap
+#define TENSORMAPEXPR(CVQual)\
+template <typename Scalar_, int Options_, int Options2_, int NumIndices_, typename IndexType_, template <class> class MakePointer_, size_t N>\
+struct PlaceHolderExpression< CVQual TensorMap< Tensor<Scalar_, NumIndices_, Options_, IndexType_>, Options2_, MakePointer_>, N> {\
+  typedef CVQual PlaceHolder<CVQual TensorMap<Tensor<Scalar_, NumIndices_, Options_, IndexType_>, Options2_, MakePointer_>, N> Type;\
+};
+
+TENSORMAPEXPR(const)
+TENSORMAPEXPR()
+#undef TENSORMAPEXPR
+
+/// specialisation of the \ref PlaceHolderExpression when the node is
+/// TensorForcedEvalOp
+#define FORCEDEVAL(CVQual)\
+template <typename Expr, size_t N>\
+struct PlaceHolderExpression<CVQual TensorForcedEvalOp<Expr>, N> {\
+  typedef CVQual PlaceHolder<CVQual TensorForcedEvalOp<Expr>, N> Type;\
+};
+
+FORCEDEVAL(const)
+FORCEDEVAL()
+#undef FORCEDEVAL
+
+/// specialisation of the \ref PlaceHolderExpression when the node is
+/// TensorEvalToOp
+#define EVALTO(CVQual)\
+template <typename Expr, size_t N>\
+struct PlaceHolderExpression<CVQual TensorEvalToOp<Expr>, N> {\
+  typedef CVQual TensorEvalToOp<typename CalculateIndex <N, Expr>::ArgType> Type;\
+};
+
+EVALTO(const)
+EVALTO()
+#undef EVALTO
+
+
+/// specialisation of the \ref PlaceHolderExpression when the node is
+/// TensorReductionOp
+#define SYCLREDUCTION(CVQual)\
+template <typename OP, typename Dims, typename Expr, size_t N>\
+struct PlaceHolderExpression<CVQual TensorReductionOp<OP, Dims, Expr>, N>{\
+  typedef CVQual PlaceHolder<CVQual TensorReductionOp<OP, Dims,Expr>, N> Type;\
+};
+SYCLREDUCTION(const)
+SYCLREDUCTION()
+#undef SYCLREDUCTION
+
+/// template deduction for \ref PlaceHolderExpression struct
+template <typename Expr>
+struct createPlaceHolderExpression {
+  static const size_t TotalLeaves = LeafCount<Expr>::Count;
+  typedef typename PlaceHolderExpression<Expr, TotalLeaves - 1>::Type Type;
+};
+
+}  // internal
+}  // TensorSycl
+}  // namespace Eigen
+
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_PLACEHOLDER_EXPR_HPP

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclRun.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclRun.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclRun.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclRun.h
@@ -0,0 +1,70 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Cummins Chris PhD student at The University of Edinburgh.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensorSyclRun.h
+ *
+ * \brief:
+ * Schedule_kernel invoke an specialised version of kernel struct. The
+ * specialisation is based on the data dimension in sycl buffer
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_SYCLRUN_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_SYCLRUN_HPP
+
+namespace Eigen {
+namespace TensorSycl {
+/// The run function in tensor sycl convert the expression tree to a buffer
+/// based expression tree;
+/// creates the expression tree for the device with accessor to buffers;
+/// construct the kernel and submit it to the sycl queue.
+template <typename Expr, typename Dev>
+void run(Expr &expr, Dev &dev) {
+  Eigen::TensorEvaluator<Expr, Dev> evaluator(expr, dev);
+  const bool needs_assign = evaluator.evalSubExprsIfNeeded(NULL);
+  if (needs_assign) {
+    typedef  typename internal::createPlaceHolderExpression<Expr>::Type PlaceHolderExpr;
+    auto functors = internal::extractFunctors(evaluator);
+
+    size_t tileSize =dev.m_queue.get_device(). template get_info<cl::sycl::info::device::max_work_group_size>()/2;
+    dev.m_queue.submit([&](cl::sycl::handler &cgh) {
+
+      // create a tuple of accessors from Evaluator
+      auto tuple_of_accessors = internal::createTupleOfAccessors<decltype(evaluator)>(cgh, evaluator);
+      const auto range = utility::tuple::get<0>(tuple_of_accessors).get_range()[0];
+      size_t GRange=range;
+      if (tileSize>GRange) tileSize=GRange;
+      else if(GRange>tileSize){
+        size_t xMode = GRange % tileSize;
+        if (xMode != 0) GRange += (tileSize - xMode);
+      }
+      // run the kernel
+      cgh.parallel_for<PlaceHolderExpr>( cl::sycl::nd_range<1>(cl::sycl::range<1>(GRange), cl::sycl::range<1>(tileSize)), [=](cl::sycl::nd_item<1> itemID) {
+        typedef  typename internal::ConvertToDeviceExpression<Expr>::Type DevExpr;
+        auto device_expr =internal::createDeviceExpression<DevExpr, PlaceHolderExpr>(functors, tuple_of_accessors);
+        auto device_evaluator = Eigen::TensorEvaluator<decltype(device_expr.expr), Eigen::DefaultDevice>(device_expr.expr, Eigen::DefaultDevice());
+        if (itemID.get_global_linear_id() < range) {
+          device_evaluator.evalScalar(static_cast<int>(itemID.get_global_linear_id()));
+        }
+      });
+    });
+    dev.m_queue.throw_asynchronous();
+  }
+
+  evaluator.cleanup();
+}
+}  // namespace TensorSycl
+}  // namespace Eigen
+
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_SYCLRUN_HPP

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclTuple.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclTuple.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclTuple.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorSyclTuple.h
@@ -0,0 +1,234 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*****************************************************************
+ * TensroSyclTuple.h
+ *
+ * \brief:
+ *  Minimal implementation of std::tuple that can be used inside a SYCL kernel.
+ *
+*****************************************************************/
+
+#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_TUPLE_HPP
+#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_TUPLE_HPP
+namespace utility {
+namespace tuple {
+/// \struct StaticIf
+/// \brief The StaticIf struct is used to statically choose the type based on the
+/// condition.
+template <bool, typename T = void> struct StaticIf;
+/// \brief specialisation of the \ref StaticIf when the condition is true
+template <typename T>
+struct StaticIf<true, T> {
+  typedef T type;
+};
+
+/// \struct Tuple
+/// \brief is a fixed-size collection of heterogeneous values
+/// \ztparam Ts...	-	the types of the elements that the tuple stores.
+/// Empty list is supported.
+template <class... Ts>
+struct Tuple {};
+
+/// \brief specialisation of the \ref Tuple class when the tuple has at least
+/// one element.
+/// \tparam T : the type of the first element in the tuple.
+/// \tparam Ts... the rest of the elements in the tuple. Ts... can be empty.
+template <class T, class... Ts>
+struct Tuple<T, Ts...> {
+  Tuple(T t, Ts... ts) : head(t), tail(ts...) {}
+  T head;
+  Tuple<Ts...> tail;
+};
+
+///\ struct ElemTypeHolder
+/// \brief ElemTypeHolder class is used to specify the types of the
+/// elements inside the tuple
+/// \tparam size_t the number of elements inside the tuple
+/// \tparam class the tuple class
+template <size_t, class>
+struct ElemTypeHolder;
+
+/// \brief specialisation of the \ref ElemTypeHolder class when the number of
+/// elements inside the tuple is 1
+template <class T, class... Ts>
+struct ElemTypeHolder<0, Tuple<T, Ts...> > {
+  typedef T type;
+};
+
+/// \brief specialisation of the \ref ElemTypeHolder class when the number of
+/// elements inside the tuple is bigger than 1. It recursively calls itself to
+/// detect the type of each element in the tuple
+/// \tparam T : the type of the first element in the tuple.
+/// \tparam Ts... the rest of the elements in the tuple. Ts... can be empty.
+/// \tparam K is the Kth element in the tuple
+template <size_t k, class T, class... Ts>
+struct ElemTypeHolder<k, Tuple<T, Ts...> > {
+  typedef typename ElemTypeHolder<k - 1, Tuple<Ts...> >::type type;
+};
+
+/// get
+/// \brief Extracts the first element from the tuple.
+/// K=0 represents the first element of the tuple. The tuple cannot be empty.
+/// \tparam Ts... are the type of the elements in the tuple.
+/// \param t is the tuple whose contents to extract
+/// \return  typename ElemTypeHolder<0, Tuple<Ts...> >::type &>::type
+
+#define TERMINATE_CONDS_TUPLE_GET(CVQual) \
+template <size_t k, class... Ts> \
+typename StaticIf<k == 0, CVQual typename ElemTypeHolder<0, Tuple<Ts...> >::type &>::type \
+get(CVQual Tuple<Ts...> &t) { \
+  static_assert(sizeof...(Ts)!=0, "The requseted value is bigger than the size of the tuple"); \
+  return t.head; \
+}
+
+TERMINATE_CONDS_TUPLE_GET(const)
+TERMINATE_CONDS_TUPLE_GET()
+#undef TERMINATE_CONDS_TUPLE_GET
+/// get
+/// \brief Extracts the Kth element from the tuple.
+///\tparam K is an integer value in [0,sizeof...(Types)).
+/// \tparam T is the (sizeof...(Types) -(K+1)) element in the tuple
+/// \tparam Ts... are the type of the elements  in the tuple.
+/// \param t is the tuple whose contents to extract
+/// \return  typename ElemTypeHolder<K, Tuple<Ts...> >::type &>::type
+#define RECURSIVE_TUPLE_GET(CVQual) \
+template <size_t k, class T, class... Ts> \
+typename StaticIf<k != 0, CVQual typename ElemTypeHolder<k, Tuple<T, Ts...> >::type &>::type \
+get(CVQual Tuple<T, Ts...> &t) { \
+  return utility::tuple::get<k - 1>(t.tail); \
+}
+RECURSIVE_TUPLE_GET(const)
+RECURSIVE_TUPLE_GET()
+#undef RECURSIVE_TUPLE_GET
+
+/// make_tuple
+/// \brief Creates a tuple object, deducing the target type from the types of
+/// arguments.
+/// \tparam Args the type of the arguments to construct the tuple from
+/// \param args zero or more arguments to construct the tuple from
+/// \return Tuple<Args...>
+template <typename... Args>
+Tuple<Args...> make_tuple(Args... args) {
+  return Tuple<Args...>(args...);
+}
+
+/// size
+/// \brief Provides access to the number of elements in a tuple as a
+/// compile-time constant expression.
+/// \tparam Args the type of the arguments to construct the tuple from
+/// \return size_t
+template <typename... Args>
+static constexpr size_t size(Tuple<Args...> &) {
+  return sizeof...(Args);
+}
+
+/// \struct IndexList
+/// \brief Creates a list of index from the elements in the tuple
+/// \tparam Is... a list of index from [0 to sizeof...(tuple elements))
+template <size_t... Is>
+struct IndexList {};
+
+/// \struct RangeBuilder
+/// \brief Collects internal details for generating index ranges [MIN, MAX)
+/// Declare primary template for index range builder
+/// \tparam MIN is the starting index in the tuple
+/// \tparam N represents sizeof..(elemens)- sizeof...(Is)
+/// \tparam Is... are the list of generated index so far
+template <size_t MIN, size_t N, size_t... Is>
+struct RangeBuilder;
+
+/// \brief base Step: Specialisation of the \ref RangeBuilder when the
+/// MIN==MAX. In this case the Is... is [0 to sizeof...(tuple elements))
+/// \tparam MIN is the starting index of the tuple
+/// \tparam Is is [0 to sizeof...(tuple elements))
+template <size_t MIN, size_t... Is>
+struct RangeBuilder<MIN, MIN, Is...> {
+  typedef IndexList<Is...> type;
+};
+
+/// Induction step: Specialisation of the RangeBuilder class when N!=MIN
+/// in this case we are recursively subtracting N by one and adding one
+/// index to Is... list until MIN==N
+/// \tparam MIN is the starting index in the tuple
+/// \tparam N represents sizeof..(elemens)- sizeof...(Is)
+/// \tparam Is... are the list of generated index so far
+template <size_t MIN, size_t N, size_t... Is>
+struct RangeBuilder : public RangeBuilder<MIN, N - 1, N - 1, Is...> {};
+
+/// \brief IndexRange that returns a [MIN, MAX) index range
+/// \tparam MIN is the starting index in the tuple
+/// \tparam MAX is the size of the tuple
+template <size_t MIN, size_t MAX>
+struct IndexRange: RangeBuilder<MIN, MAX>::type {};
+
+/// append_base
+/// \brief unpacking the elements of the input tuple t and creating a new tuple
+/// by adding element a at the end of it.
+///\tparam Args... the type of the elements inside the tuple t
+/// \tparam T the type of the new element going to be added at the end of tuple
+/// \tparam I... is the list of index from [0 to sizeof...(t))
+/// \param t the tuple on which we want to append a.
+/// \param a the new elements going to be added to the tuple
+/// \return Tuple<Args..., T>
+template <typename... Args, typename T, size_t... I>
+Tuple<Args..., T> append_base(Tuple<Args...> t, T a,IndexList<I...>) {
+  return utility::tuple::make_tuple(get<I>(t)..., a);
+}
+
+/// append
+/// \brief the deduction function for \ref append_base that automatically
+/// generate the \ref IndexRange
+///\tparam Args... the type of the elements inside the tuple t
+/// \tparam T the type of the new element going to be added at the end of tuple
+/// \param t the tuple on which we want to append a.
+/// \param a the new elements going to be added to the tuple
+/// \return Tuple<Args..., T>
+template <typename... Args, typename T>
+Tuple<Args..., T> append(Tuple<Args...> t, T a) {
+  return utility::tuple::append_base(t, a,  IndexRange<0, sizeof...(Args)>());
+}
+
+/// append_base
+/// \brief This is a specialisation of \ref append_base when we want to
+/// concatenate
+/// tuple t2 at the end of the tuple t1. Here we unpack both tuples, generate the
+/// IndexRange for each of them and create an output tuple T that contains both
+/// elements of t1 and t2.
+///\tparam Args1... the type of the elements inside the tuple t1
+///\tparam Args2... the type of the elements inside the tuple t2
+/// \tparam I1... is the list of index from [0 to sizeof...(t1))
+/// \tparam I2... is the list of index from [0 to sizeof...(t2))
+/// \param t1 is the tuple on which we want to append t2.
+/// \param t2 is the tuple that is going to be added on t1.
+/// \return Tuple<Args1..., Args2...>
+template <typename... Args1, typename... Args2, size_t... I1, size_t... I2>
+Tuple<Args1..., Args2...> append_base(Tuple<Args1...> t1, Tuple<Args2...> t2, IndexList<I1...>, IndexList<I2...>) {
+  return utility::tuple::make_tuple(get<I1>(t1)...,get<I2>(t2)...);
+}
+
+/// append
+/// \brief deduction function for \ref append_base when we are appending tuple
+/// t1 by tuple t2. In this case the \ref IndexRange for both tuple are
+/// automatically generated.
+///\tparam Args1... the type of the elements inside the tuple t1
+///\tparam Args2... the type of the elements inside the tuple t2
+/// \param t1 is the tuple on which we want to append t2.
+/// \param t2 is the tuple that is going to be added on t1.
+/// \return Tuple<Args1..., Args2...>
+template <typename... Args1, typename... Args2>
+Tuple<Args1..., Args2...> append(Tuple<Args1...> t1,Tuple<Args2...> t2) {
+  return utility::tuple::append_base(t1, t2, IndexRange<0, sizeof...(Args1)>(), IndexRange<0, sizeof...(Args2)>());
+}
+}  // tuple
+}  // utility
+#endif  // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCL_TUPLE_HPP

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
@@ -0,0 +1,272 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_TRAITS_H
+#define EIGEN_CXX11_TENSOR_TENSOR_TRAITS_H
+
+namespace Eigen {
+namespace internal {
+
+
+template<typename Scalar, int Options>
+class compute_tensor_flags
+{
+  enum {
+    is_dynamic_size_storage = 1,
+
+    is_aligned =
+    (
+        ((Options&DontAlign)==0) && (
+#if EIGEN_MAX_STATIC_ALIGN_BYTES>0
+            (!is_dynamic_size_storage)
+#else
+            0
+#endif
+            |
+#if EIGEN_MAX_ALIGN_BYTES>0
+            is_dynamic_size_storage
+#else
+            0
+#endif
+      )
+     ),
+    packet_access_bit = packet_traits<Scalar>::Vectorizable && is_aligned ? PacketAccessBit : 0
+  };
+
+  public:
+    enum { ret = packet_access_bit };
+};
+
+
+template<typename Scalar_, int NumIndices_, int Options_, typename IndexType_>
+struct traits<Tensor<Scalar_, NumIndices_, Options_, IndexType_> >
+{
+  typedef Scalar_ Scalar;
+  typedef Dense StorageKind;
+  typedef IndexType_ Index;
+  static const int NumDimensions = NumIndices_;
+  static const int Layout = Options_ & RowMajor ? RowMajor : ColMajor;
+  enum {
+    Options = Options_,
+    Flags = compute_tensor_flags<Scalar_, Options_>::ret | (is_const<Scalar_>::value ? 0 : LvalueBit)
+  };
+  template <typename T> struct MakePointer {
+    typedef T* Type;
+  };
+};
+
+
+template<typename Scalar_, typename Dimensions, int Options_, typename IndexType_>
+struct traits<TensorFixedSize<Scalar_, Dimensions, Options_, IndexType_> >
+{
+  typedef Scalar_ Scalar;
+  typedef Dense StorageKind;
+  typedef IndexType_ Index;
+  static const int NumDimensions = array_size<Dimensions>::value;
+  static const int Layout = Options_ & RowMajor ? RowMajor : ColMajor;
+  enum {
+    Options = Options_,
+    Flags = compute_tensor_flags<Scalar_, Options_>::ret | (is_const<Scalar_>::value ? 0: LvalueBit)
+  };
+  template <typename T> struct MakePointer {
+    typedef T* Type;
+  };
+};
+
+
+template<typename PlainObjectType, int Options_, template <class> class MakePointer_>
+struct traits<TensorMap<PlainObjectType, Options_, MakePointer_> >
+  : public traits<PlainObjectType>
+{
+  typedef traits<PlainObjectType> BaseTraits;
+  typedef typename BaseTraits::Scalar Scalar;
+  typedef typename BaseTraits::StorageKind StorageKind;
+  typedef typename BaseTraits::Index Index;
+  static const int NumDimensions = BaseTraits::NumDimensions;
+  static const int Layout = BaseTraits::Layout;
+  enum {
+    Options = Options_,
+    Flags = BaseTraits::Flags
+  };
+  template <class T> struct MakePointer {
+    // Intermediate typedef to workaround MSVC issue.
+    typedef MakePointer_<T> MakePointerT;
+    typedef typename MakePointerT::Type Type;
+  };
+};
+
+template<typename PlainObjectType>
+struct traits<TensorRef<PlainObjectType> >
+  : public traits<PlainObjectType>
+{
+  typedef traits<PlainObjectType> BaseTraits;
+  typedef typename BaseTraits::Scalar Scalar;
+  typedef typename BaseTraits::StorageKind StorageKind;
+  typedef typename BaseTraits::Index Index;
+  static const int NumDimensions = BaseTraits::NumDimensions;
+  static const int Layout = BaseTraits::Layout;
+  enum {
+    Options = BaseTraits::Options,
+    Flags = BaseTraits::Flags
+  };
+};
+
+
+template<typename _Scalar, int NumIndices_, int Options, typename IndexType_>
+struct eval<Tensor<_Scalar, NumIndices_, Options, IndexType_>, Eigen::Dense>
+{
+  typedef const Tensor<_Scalar, NumIndices_, Options, IndexType_>& type;
+};
+
+template<typename _Scalar, int NumIndices_, int Options, typename IndexType_>
+struct eval<const Tensor<_Scalar, NumIndices_, Options, IndexType_>, Eigen::Dense>
+{
+  typedef const Tensor<_Scalar, NumIndices_, Options, IndexType_>& type;
+};
+
+template<typename Scalar_, typename Dimensions, int Options, typename IndexType_>
+struct eval<TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>, Eigen::Dense>
+{
+  typedef const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>& type;
+};
+
+template<typename Scalar_, typename Dimensions, int Options, typename IndexType_>
+struct eval<const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>, Eigen::Dense>
+{
+  typedef const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>& type;
+};
+
+template<typename PlainObjectType, int Options, template <class> class MakePointer>
+struct eval<TensorMap<PlainObjectType, Options, MakePointer>, Eigen::Dense>
+{
+  typedef const TensorMap<PlainObjectType, Options, MakePointer>& type;
+};
+
+template<typename PlainObjectType, int Options, template <class> class MakePointer>
+struct eval<const TensorMap<PlainObjectType, Options, MakePointer>, Eigen::Dense>
+{
+  typedef const TensorMap<PlainObjectType, Options, MakePointer>& type;
+};
+
+template<typename PlainObjectType>
+struct eval<TensorRef<PlainObjectType>, Eigen::Dense>
+{
+  typedef const TensorRef<PlainObjectType>& type;
+};
+
+template<typename PlainObjectType>
+struct eval<const TensorRef<PlainObjectType>, Eigen::Dense>
+{
+  typedef const TensorRef<PlainObjectType>& type;
+};
+
+// TODO nested<> does not exist anymore in Eigen/Core, and it thus has to be removed in favor of ref_selector.
+template<typename T, int n=1, typename PlainObject = void> struct nested
+{
+  typedef typename ref_selector<T>::type type;
+};
+
+template <typename Scalar_, int NumIndices_, int Options_, typename IndexType_>
+struct nested<Tensor<Scalar_, NumIndices_, Options_, IndexType_> >
+{
+  typedef const Tensor<Scalar_, NumIndices_, Options_, IndexType_>& type;
+};
+
+template <typename Scalar_, int NumIndices_, int Options_, typename IndexType_>
+struct nested<const Tensor<Scalar_, NumIndices_, Options_, IndexType_> >
+{
+  typedef const Tensor<Scalar_, NumIndices_, Options_, IndexType_>& type;
+};
+
+template <typename Scalar_, typename Dimensions, int Options, typename IndexType_>
+struct nested<TensorFixedSize<Scalar_, Dimensions, Options, IndexType_> >
+{
+  typedef const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>& type;
+};
+
+template <typename Scalar_, typename Dimensions, int Options, typename IndexType_>
+struct nested<const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_> >
+{
+  typedef const TensorFixedSize<Scalar_, Dimensions, Options, IndexType_>& type;
+};
+
+
+template <typename PlainObjectType, int Options, template <class> class MakePointer>
+struct nested<TensorMap<PlainObjectType, Options, MakePointer> >
+{
+  typedef const TensorMap<PlainObjectType, Options, MakePointer>& type;
+};
+
+template <typename PlainObjectType, int Options, template <class> class MakePointer>
+struct nested<const TensorMap<PlainObjectType, Options, MakePointer> >
+{
+  typedef const TensorMap<PlainObjectType, Options, MakePointer>& type;
+};
+
+template <typename PlainObjectType>
+struct nested<TensorRef<PlainObjectType> >
+{
+  typedef const TensorRef<PlainObjectType>& type;
+};
+
+template <typename PlainObjectType>
+struct nested<const TensorRef<PlainObjectType> >
+{
+  typedef const TensorRef<PlainObjectType>& type;
+};
+
+}  // end namespace internal
+
+// Convolutional layers take in an input tensor of shape (D, R, C, B), or (D, C,
+// R, B), and convolve it with a set of filters, which can also be presented as
+// a tensor (D, K, K, M), where M is the number of filters, K is the filter
+// size, and each 3-dimensional tensor of size (D, K, K) is a filter. For
+// simplicity we assume that we always use square filters (which is usually the
+// case in images), hence the two Ks in the tensor dimension.  It also takes in
+// a few additional parameters:
+// Stride (S): The convolution stride is the offset between locations where we
+//             apply the filters.  A larger stride means that the output will be
+//             spatially smaller.
+// Padding (P): The padding we apply to the input tensor along the R and C
+//              dimensions.  This is usually used to make sure that the spatial
+//              dimensions of the output matches our intention.
+//
+// Two types of padding are often used:
+//   SAME: The pad value is computed so that the output will have size
+//         R/S and C/S.
+//   VALID: no padding is carried out.
+// When we do padding, the padded values at the padded locations are usually
+// zero.
+//
+// The output dimensions for convolution, when given all the parameters above,
+// are as follows:
+// When Padding = SAME: the output size is (B, R', C', M), where
+//   R' = ceil(float(R) / float(S))
+//   C' = ceil(float(C) / float(S))
+// where ceil is the ceiling function.  The input tensor is padded with 0 as
+// needed.  The number of padded rows and columns are computed as:
+//   Pr = ((R' - 1) * S + K - R) / 2
+//   Pc = ((C' - 1) * S + K - C) / 2
+// when the stride is 1, we have the simplified case R'=R, C'=C, Pr=Pc=(K-1)/2.
+// This is where SAME comes from - the output has the same size as the input has.
+// When Padding = VALID: the output size is computed as
+//   R' = ceil(float(R - K + 1) / float(S))
+//   C' = ceil(float(C - K + 1) / float(S))
+// and the number of padded rows and columns are computed in the same way as in
+// the SAME case.
+// When the stride is 1, we have the simplified case R'=R-K+1, C'=C-K+1, Pr=0,
+// Pc=0.
+typedef enum {
+  PADDING_VALID = 1,
+  PADDING_SAME = 2
+} PaddingType;
+
+}  // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_TRAITS_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorUInt128.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorUInt128.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorUInt128.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorUInt128.h
@@ -0,0 +1,248 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_UINT128_H
+#define EIGEN_CXX11_TENSOR_TENSOR_UINT128_H
+
+namespace Eigen {
+namespace internal {
+
+
+template <uint64_t n>
+struct static_val {
+  static const uint64_t value = n;
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE operator uint64_t() const { return n; }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static_val() { }
+
+  template <typename T>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static_val(const T& v) {
+    eigen_assert(v == n);
+  }
+};
+
+
+template <typename HIGH = uint64_t, typename LOW = uint64_t>
+struct TensorUInt128
+{
+  HIGH high;
+  LOW low;
+
+  template<typename OTHER_HIGH, typename OTHER_LOW>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+  TensorUInt128(const TensorUInt128<OTHER_HIGH, OTHER_LOW>& other) : high(other.high), low(other.low) {
+    EIGEN_STATIC_ASSERT(sizeof(OTHER_HIGH) <= sizeof(HIGH), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    EIGEN_STATIC_ASSERT(sizeof(OTHER_LOW) <= sizeof(LOW), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  }
+
+  template<typename OTHER_HIGH, typename OTHER_LOW>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+  TensorUInt128& operator = (const TensorUInt128<OTHER_HIGH, OTHER_LOW>& other) {
+    EIGEN_STATIC_ASSERT(sizeof(OTHER_HIGH) <= sizeof(HIGH), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    EIGEN_STATIC_ASSERT(sizeof(OTHER_LOW) <= sizeof(LOW), YOU_MADE_A_PROGRAMMING_MISTAKE);
+    high = other.high;
+    low = other.low;
+    return *this;
+  }
+
+  template<typename T>
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+  explicit TensorUInt128(const T& x) : high(0), low(x) {
+    eigen_assert((static_cast<typename conditional<sizeof(T) == 8, uint64_t, uint32_t>::type>(x) <= NumTraits<uint64_t>::highest()));
+    eigen_assert(x >= 0);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+  TensorUInt128(HIGH y, LOW x) : high(y), low(x) { }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE operator LOW() const {
+    return low;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE LOW lower() const {
+    return low;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE HIGH upper() const {
+    return high;
+  }
+};
+
+
+template <typename HL, typename LL, typename HR, typename LR>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+bool operator == (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs)
+{
+  return (lhs.high == rhs.high) & (lhs.low == rhs.low);
+}
+
+template <typename HL, typename LL, typename HR, typename LR>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+bool operator != (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs)
+{
+  return (lhs.high != rhs.high) | (lhs.low != rhs.low);
+}
+
+template <typename HL, typename LL, typename HR, typename LR>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+bool operator >= (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs)
+{
+  if (lhs.high != rhs.high) {
+    return lhs.high > rhs.high;
+  }
+  return lhs.low >= rhs.low;
+}
+
+template <typename HL, typename LL, typename HR, typename LR>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+bool operator < (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs)
+{
+  if (lhs.high != rhs.high) {
+    return lhs.high < rhs.high;
+  }
+  return lhs.low < rhs.low;
+}
+
+template <typename HL, typename LL, typename HR, typename LR>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+TensorUInt128<uint64_t, uint64_t> operator + (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs)
+{
+  TensorUInt128<uint64_t, uint64_t> result(lhs.high + rhs.high, lhs.low + rhs.low);
+  if (result.low < rhs.low) {
+    result.high += 1;
+  }
+  return result;
+}
+
+template <typename HL, typename LL, typename HR, typename LR>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+TensorUInt128<uint64_t, uint64_t> operator - (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs)
+{
+  TensorUInt128<uint64_t, uint64_t> result(lhs.high - rhs.high, lhs.low - rhs.low);
+  if (result.low > lhs.low) {
+    result.high -= 1;
+  }
+  return result;
+}
+
+
+template <typename HL, typename LL, typename HR, typename LR>
+static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+TensorUInt128<uint64_t, uint64_t> operator * (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs)
+{
+  // Split each 128-bit integer into 4 32-bit integers, and then do the
+  // multiplications by hand as follow:
+  //   lhs      a  b  c  d
+  //   rhs      e  f  g  h
+  //           -----------
+  //           ah bh ch dh
+  //           bg cg dg
+  //           cf df
+  //           de
+  // The result is stored in 2 64bit integers, high and low.
+
+  const uint64_t LOW = 0x00000000FFFFFFFFLL;
+  const uint64_t HIGH = 0xFFFFFFFF00000000LL;
+
+  uint64_t d = lhs.low & LOW;
+  uint64_t c = (lhs.low & HIGH) >> 32LL;
+  uint64_t b = lhs.high & LOW;
+  uint64_t a = (lhs.high & HIGH) >> 32LL;
+
+  uint64_t h = rhs.low & LOW;
+  uint64_t g = (rhs.low & HIGH) >> 32LL;
+  uint64_t f = rhs.high & LOW;
+  uint64_t e = (rhs.high & HIGH) >> 32LL;
+
+  // Compute the low 32 bits of low
+  uint64_t acc = d * h;
+  uint64_t low = acc & LOW;
+  //  Compute the high 32 bits of low. Add a carry every time we wrap around
+  acc >>= 32LL;
+  uint64_t carry = 0;
+  uint64_t acc2 = acc + c * h;
+  if (acc2 < acc) {
+    carry++;
+  }
+  acc = acc2 + d * g;
+  if (acc < acc2) {
+    carry++;
+  }
+  low |= (acc << 32LL);
+
+  // Carry forward the high bits of acc to initiate the computation of the
+  // low 32 bits of high
+  acc2 = (acc >> 32LL) | (carry << 32LL);
+  carry = 0;
+
+  acc = acc2 + b * h;
+  if (acc < acc2) {
+    carry++;
+  }
+  acc2 = acc + c * g;
+  if (acc2 < acc) {
+    carry++;
+  }
+  acc = acc2 + d * f;
+  if (acc < acc2) {
+    carry++;
+  }
+  uint64_t high = acc & LOW;
+
+  // Start to compute the high 32 bits of high.
+  acc2 = (acc >> 32LL) | (carry << 32LL);
+
+  acc = acc2 + a * h;
+  acc2 = acc + b * g;
+  acc = acc2 + c * f;
+  acc2 = acc + d * e;
+  high |= (acc2 << 32LL);
+
+  return TensorUInt128<uint64_t, uint64_t>(high, low);
+}
+
+template <typename HL, typename LL, typename HR, typename LR>
+static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+TensorUInt128<uint64_t, uint64_t> operator / (const TensorUInt128<HL, LL>& lhs, const TensorUInt128<HR, LR>& rhs)
+{
+  if (rhs == TensorUInt128<static_val<0>, static_val<1> >(1)) {
+    return TensorUInt128<uint64_t, uint64_t>(lhs.high, lhs.low);
+  } else if (lhs < rhs) {
+    return TensorUInt128<uint64_t, uint64_t>(0);
+  } else {
+    // calculate the biggest power of 2 times rhs that's less than or equal to lhs
+    TensorUInt128<uint64_t, uint64_t> power2(1);
+    TensorUInt128<uint64_t, uint64_t> d(rhs);
+    TensorUInt128<uint64_t, uint64_t> tmp(lhs - d);
+    while (lhs >= d) {
+      tmp = tmp - d;
+      d = d + d;
+      power2 = power2 + power2;
+    }
+
+    tmp = TensorUInt128<uint64_t, uint64_t>(lhs.high, lhs.low);
+    TensorUInt128<uint64_t, uint64_t> result(0);
+    while (power2 != TensorUInt128<static_val<0>, static_val<0> >(0)) {
+      if (tmp >= d) {
+        tmp = tmp - d;
+        result = result + power2;
+      }
+      // Shift right
+      power2 = TensorUInt128<uint64_t, uint64_t>(power2.high >> 1, (power2.low >> 1) | (power2.high << 63));
+      d = TensorUInt128<uint64_t, uint64_t>(d.high >> 1, (d.low >> 1) | (d.high << 63));
+    }
+
+    return result;
+  }
+}
+
+
+}  // namespace internal
+}  // namespace Eigen
+
+
+#endif  // EIGEN_CXX11_TENSOR_TENSOR_UINT128_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -0,0 +1,608 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_VOLUME_PATCH_H
+#define EIGEN_CXX11_TENSOR_TENSOR_VOLUME_PATCH_H
+
+namespace Eigen {
+
+/** \class TensorVolumePatch
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Patch extraction specialized for processing of volumetric data.
+  * This assumes that the input has a least 4 dimensions ordered as follows:
+  *  - channels
+  *  - planes
+  *  - rows
+  *  - columns
+  *  - (optional) additional dimensions such as time or batch size.
+  * Calling the volume patch code with patch_planes, patch_rows, and patch_cols
+  * is equivalent to calling the regular patch extraction code with parameters
+  * d, patch_planes, patch_rows, patch_cols, and 1 for all the additional
+  * dimensions.
+  */
+namespace internal {
+template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
+struct traits<TensorVolumePatchOp<Planes, Rows, Cols, XprType> > : public traits<XprType>
+{
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef traits<XprType> XprTraits;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = XprTraits::NumDimensions + 1;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
+struct eval<TensorVolumePatchOp<Planes, Rows, Cols, XprType>, Eigen::Dense>
+{
+  typedef const TensorVolumePatchOp<Planes, Rows, Cols, XprType>& type;
+};
+
+template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
+struct nested<TensorVolumePatchOp<Planes, Rows, Cols, XprType>, 1, typename eval<TensorVolumePatchOp<Planes, Rows, Cols, XprType> >::type>
+{
+  typedef TensorVolumePatchOp<Planes, Rows, Cols, XprType> type;
+};
+
+}  // end namespace internal
+
+template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
+class TensorVolumePatchOp : public TensorBase<TensorVolumePatchOp<Planes, Rows, Cols, XprType>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorVolumePatchOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorVolumePatchOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorVolumePatchOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorVolumePatchOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorVolumePatchOp(const XprType& expr, DenseIndex patch_planes, DenseIndex patch_rows, DenseIndex patch_cols,
+                                                            DenseIndex plane_strides, DenseIndex row_strides, DenseIndex col_strides,
+                                                            DenseIndex in_plane_strides, DenseIndex in_row_strides, DenseIndex in_col_strides,
+                                                            DenseIndex plane_inflate_strides, DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
+                                                            PaddingType padding_type, Scalar padding_value)
+      : m_xpr(expr), m_patch_planes(patch_planes), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
+        m_plane_strides(plane_strides), m_row_strides(row_strides), m_col_strides(col_strides),
+        m_in_plane_strides(in_plane_strides), m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
+        m_plane_inflate_strides(plane_inflate_strides), m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
+        m_padding_explicit(false), m_padding_top_z(0), m_padding_bottom_z(0), m_padding_top(0), m_padding_bottom(0), m_padding_left(0), m_padding_right(0),
+        m_padding_type(padding_type), m_padding_value(padding_value) {}
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorVolumePatchOp(const XprType& expr, DenseIndex patch_planes, DenseIndex patch_rows, DenseIndex patch_cols,
+                                                           DenseIndex plane_strides, DenseIndex row_strides, DenseIndex col_strides,
+                                                           DenseIndex in_plane_strides, DenseIndex in_row_strides, DenseIndex in_col_strides,
+                                                           DenseIndex plane_inflate_strides, DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
+                                                           DenseIndex padding_top_z, DenseIndex padding_bottom_z,
+                                                           DenseIndex padding_top, DenseIndex padding_bottom,
+                                                           DenseIndex padding_left, DenseIndex padding_right,
+                                                           Scalar padding_value)
+      : m_xpr(expr), m_patch_planes(patch_planes), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
+        m_plane_strides(plane_strides), m_row_strides(row_strides), m_col_strides(col_strides),
+        m_in_plane_strides(in_plane_strides), m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
+        m_plane_inflate_strides(plane_inflate_strides), m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
+        m_padding_explicit(true), m_padding_top_z(padding_top_z), m_padding_bottom_z(padding_bottom_z), m_padding_top(padding_top), m_padding_bottom(padding_bottom),
+        m_padding_left(padding_left), m_padding_right(padding_right),
+        m_padding_type(PADDING_VALID), m_padding_value(padding_value) {}
+
+    EIGEN_DEVICE_FUNC
+    DenseIndex patch_planes() const { return m_patch_planes; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex patch_rows() const { return m_patch_rows; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex patch_cols() const { return m_patch_cols; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex plane_strides() const { return m_plane_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex row_strides() const { return m_row_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex col_strides() const { return m_col_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex in_plane_strides() const { return m_in_plane_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex in_row_strides() const { return m_in_row_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex in_col_strides() const { return m_in_col_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex plane_inflate_strides() const { return m_plane_inflate_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex row_inflate_strides() const { return m_row_inflate_strides; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex col_inflate_strides() const { return m_col_inflate_strides; }
+    EIGEN_DEVICE_FUNC
+    bool padding_explicit() const { return m_padding_explicit; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_top_z() const { return m_padding_top_z; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_bottom_z() const { return m_padding_bottom_z; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_top() const { return m_padding_top; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_bottom() const { return m_padding_bottom; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_left() const { return m_padding_left; }
+    EIGEN_DEVICE_FUNC
+    DenseIndex padding_right() const { return m_padding_right; }
+    EIGEN_DEVICE_FUNC
+    PaddingType padding_type() const { return m_padding_type; }
+    EIGEN_DEVICE_FUNC
+    Scalar padding_value() const { return m_padding_value; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const DenseIndex m_patch_planes;
+    const DenseIndex m_patch_rows;
+    const DenseIndex m_patch_cols;
+    const DenseIndex m_plane_strides;
+    const DenseIndex m_row_strides;
+    const DenseIndex m_col_strides;
+    const DenseIndex m_in_plane_strides;
+    const DenseIndex m_in_row_strides;
+    const DenseIndex m_in_col_strides;
+    const DenseIndex m_plane_inflate_strides;
+    const DenseIndex m_row_inflate_strides;
+    const DenseIndex m_col_inflate_strides;
+    const bool m_padding_explicit;
+    const DenseIndex m_padding_top_z;
+    const DenseIndex m_padding_bottom_z;
+    const DenseIndex m_padding_top;
+    const DenseIndex m_padding_bottom;
+    const DenseIndex m_padding_left;
+    const DenseIndex m_padding_right;
+    const PaddingType m_padding_type;
+    const Scalar m_padding_value;
+};
+
+
+// Eval as rvalue
+template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, Device>
+{
+  typedef TensorVolumePatchOp<Planes, Rows, Cols, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumInputDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  static const int NumDims = NumInputDims + 1;
+  typedef DSizes<Index, NumDims> Dimensions;
+  typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = false,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,
+    RawAccess = false
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device)
+  {
+    EIGEN_STATIC_ASSERT((NumDims >= 5), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    m_paddingValue = op.padding_value();
+
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+
+    // Cache a few variables.
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_inputDepth = input_dims[0];
+      m_inputPlanes = input_dims[1];
+      m_inputRows = input_dims[2];
+      m_inputCols = input_dims[3];
+    } else {
+      m_inputDepth = input_dims[NumInputDims-1];
+      m_inputPlanes = input_dims[NumInputDims-2];
+      m_inputRows = input_dims[NumInputDims-3];
+      m_inputCols = input_dims[NumInputDims-4];
+    }
+
+    m_plane_strides = op.plane_strides();
+    m_row_strides = op.row_strides();
+    m_col_strides = op.col_strides();
+
+    // Input strides and effective input/patch size
+    m_in_plane_strides = op.in_plane_strides();
+    m_in_row_strides = op.in_row_strides();
+    m_in_col_strides = op.in_col_strides();
+    m_plane_inflate_strides = op.plane_inflate_strides();
+    m_row_inflate_strides = op.row_inflate_strides();
+    m_col_inflate_strides = op.col_inflate_strides();
+
+    // The "effective" spatial size after inflating data with zeros.
+    m_input_planes_eff = (m_inputPlanes - 1) * m_plane_inflate_strides + 1;
+    m_input_rows_eff = (m_inputRows - 1) * m_row_inflate_strides + 1;
+    m_input_cols_eff = (m_inputCols - 1) * m_col_inflate_strides + 1;
+    m_patch_planes_eff = op.patch_planes() + (op.patch_planes() - 1) * (m_in_plane_strides - 1);
+    m_patch_rows_eff = op.patch_rows() + (op.patch_rows() - 1) * (m_in_row_strides - 1);
+    m_patch_cols_eff = op.patch_cols() + (op.patch_cols() - 1) * (m_in_col_strides - 1);
+
+    if (op.padding_explicit()) {
+      m_outputPlanes = numext::ceil((m_input_planes_eff + op.padding_top_z() + op.padding_bottom_z() - m_patch_planes_eff + 1.f) / static_cast<float>(m_plane_strides));
+      m_outputRows = numext::ceil((m_input_rows_eff + op.padding_top() + op.padding_bottom() - m_patch_rows_eff + 1.f) / static_cast<float>(m_row_strides));
+      m_outputCols = numext::ceil((m_input_cols_eff + op.padding_left() + op.padding_right() - m_patch_cols_eff + 1.f) / static_cast<float>(m_col_strides));
+      m_planePaddingTop = op.padding_top_z();
+      m_rowPaddingTop = op.padding_top();
+      m_colPaddingLeft = op.padding_left();
+    } else {
+      // Computing padding from the type
+      switch (op.padding_type()) {
+        case PADDING_VALID:
+          m_outputPlanes = numext::ceil((m_input_planes_eff - m_patch_planes_eff + 1.f) / static_cast<float>(m_plane_strides));
+          m_outputRows = numext::ceil((m_input_rows_eff - m_patch_rows_eff + 1.f) / static_cast<float>(m_row_strides));
+          m_outputCols = numext::ceil((m_input_cols_eff - m_patch_cols_eff + 1.f) / static_cast<float>(m_col_strides));
+          m_planePaddingTop = 0;
+          m_rowPaddingTop = 0;
+          m_colPaddingLeft = 0;
+          break;
+        case PADDING_SAME: {
+          m_outputPlanes = numext::ceil(m_input_planes_eff / static_cast<float>(m_plane_strides));
+          m_outputRows = numext::ceil(m_input_rows_eff / static_cast<float>(m_row_strides));
+          m_outputCols = numext::ceil(m_input_cols_eff / static_cast<float>(m_col_strides));
+          const Index dz = m_outputPlanes * m_plane_strides + m_patch_planes_eff - 1 - m_input_planes_eff;
+          const Index dy = m_outputRows * m_row_strides + m_patch_rows_eff - 1 - m_input_rows_eff;
+          const Index dx = m_outputCols * m_col_strides + m_patch_cols_eff - 1 - m_input_cols_eff;
+          m_planePaddingTop = dz - dz / 2;
+          m_rowPaddingTop = dy - dy / 2;
+          m_colPaddingLeft = dx - dx / 2;
+          break;
+        }
+        default:
+          eigen_assert(false && "unexpected padding");
+      }
+    }
+    eigen_assert(m_outputRows > 0);
+    eigen_assert(m_outputCols > 0);
+    eigen_assert(m_outputPlanes > 0);
+
+    // Dimensions for result of extraction.
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      // ColMajor
+      // 0: depth
+      // 1: patch_planes
+      // 2: patch_rows
+      // 3: patch_cols
+      // 4: number of patches
+      // 5 and beyond: anything else (such as batch).
+      m_dimensions[0] = input_dims[0];
+      m_dimensions[1] = op.patch_planes();
+      m_dimensions[2] = op.patch_rows();
+      m_dimensions[3] = op.patch_cols();
+      m_dimensions[4] = m_outputPlanes * m_outputRows * m_outputCols;
+      for (int i = 5; i < NumDims; ++i) {
+        m_dimensions[i] = input_dims[i-1];
+      }
+    } else {
+      // RowMajor
+      // NumDims-1: depth
+      // NumDims-2: patch_planes
+      // NumDims-3: patch_rows
+      // NumDims-4: patch_cols
+      // NumDims-5: number of patches
+      // NumDims-6 and beyond: anything else (such as batch).
+      m_dimensions[NumDims-1] = input_dims[NumInputDims-1];
+      m_dimensions[NumDims-2] = op.patch_planes();
+      m_dimensions[NumDims-3] = op.patch_rows();
+      m_dimensions[NumDims-4] = op.patch_cols();
+      m_dimensions[NumDims-5] = m_outputPlanes * m_outputRows * m_outputCols;
+      for (int i = NumDims-6; i >= 0; --i) {
+        m_dimensions[i] = input_dims[i];
+      }
+    }
+
+    // Strides for the output tensor.
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_rowStride = m_dimensions[1];
+      m_colStride = m_dimensions[2] * m_rowStride;
+      m_patchStride = m_colStride * m_dimensions[3] * m_dimensions[0];
+      m_otherStride = m_patchStride * m_dimensions[4];
+    } else {
+      m_rowStride = m_dimensions[NumDims-2];
+      m_colStride = m_dimensions[NumDims-3] * m_rowStride;
+      m_patchStride = m_colStride * m_dimensions[NumDims-4] * m_dimensions[NumDims-1];
+      m_otherStride = m_patchStride * m_dimensions[NumDims-5];
+    }
+
+    // Strides for navigating through the input tensor.
+    m_planeInputStride = m_inputDepth;
+    m_rowInputStride = m_inputDepth * m_inputPlanes;
+    m_colInputStride = m_inputDepth * m_inputRows * m_inputPlanes;
+    m_otherInputStride = m_inputDepth * m_inputRows * m_inputCols * m_inputPlanes;
+
+    m_outputPlanesRows = m_outputPlanes * m_outputRows;
+
+    // Fast representations of different variables.
+    m_fastOtherStride = internal::TensorIntDivisor<Index>(m_otherStride);
+    m_fastPatchStride = internal::TensorIntDivisor<Index>(m_patchStride);
+    m_fastColStride = internal::TensorIntDivisor<Index>(m_colStride);
+    m_fastRowStride = internal::TensorIntDivisor<Index>(m_rowStride);
+    m_fastInputRowStride = internal::TensorIntDivisor<Index>(m_row_inflate_strides);
+    m_fastInputColStride = internal::TensorIntDivisor<Index>(m_col_inflate_strides);
+    m_fastInputPlaneStride = internal::TensorIntDivisor<Index>(m_plane_inflate_strides);
+    m_fastInputColsEff = internal::TensorIntDivisor<Index>(m_input_cols_eff);
+    m_fastOutputPlanes = internal::TensorIntDivisor<Index>(m_outputPlanes);
+    m_fastOutputPlanesRows = internal::TensorIntDivisor<Index>(m_outputPlanesRows);
+
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[0]);
+    } else {
+      m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[NumDims-1]);
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    // Patch index corresponding to the passed in index.
+    const Index patchIndex = index / m_fastPatchStride;
+
+    // Spatial offset within the patch. This has to be translated into 3D
+    // coordinates within the patch.
+    const Index patchOffset = (index - patchIndex * m_patchStride) / m_fastOutputDepth;
+
+    // Batch, etc.
+    const Index otherIndex = (NumDims == 5) ? 0 : index / m_fastOtherStride;
+    const Index patch3DIndex = (NumDims == 5) ? patchIndex : (index - otherIndex * m_otherStride) / m_fastPatchStride;
+
+    // Calculate column index in the input original tensor.
+    const Index colIndex = patch3DIndex / m_fastOutputPlanesRows;
+    const Index colOffset = patchOffset / m_fastColStride;
+    const Index inputCol = colIndex * m_col_strides + colOffset * m_in_col_strides - m_colPaddingLeft;
+    const Index origInputCol = (m_col_inflate_strides == 1) ? inputCol : ((inputCol >= 0) ? (inputCol / m_fastInputColStride) : 0);
+    if (inputCol < 0 || inputCol >= m_input_cols_eff ||
+        ((m_col_inflate_strides != 1) && (inputCol != origInputCol * m_col_inflate_strides))) {
+      return Scalar(m_paddingValue);
+    }
+
+    // Calculate row index in the original input tensor.
+    const Index rowIndex = (patch3DIndex - colIndex * m_outputPlanesRows) / m_fastOutputPlanes;
+    const Index rowOffset = (patchOffset - colOffset * m_colStride) / m_fastRowStride;
+    const Index inputRow = rowIndex * m_row_strides + rowOffset * m_in_row_strides - m_rowPaddingTop;
+    const Index origInputRow = (m_row_inflate_strides == 1) ? inputRow : ((inputRow >= 0) ? (inputRow / m_fastInputRowStride) : 0);
+    if (inputRow < 0 || inputRow >= m_input_rows_eff ||
+        ((m_row_inflate_strides != 1) && (inputRow != origInputRow * m_row_inflate_strides))) {
+      return Scalar(m_paddingValue);
+    }
+
+    // Calculate plane index in the original input tensor.
+    const Index planeIndex = (patch3DIndex - m_outputPlanes * (colIndex * m_outputRows + rowIndex));
+    const Index planeOffset = patchOffset - colOffset * m_colStride - rowOffset * m_rowStride;
+    const Index inputPlane = planeIndex * m_plane_strides + planeOffset * m_in_plane_strides - m_planePaddingTop;
+    const Index origInputPlane = (m_plane_inflate_strides == 1) ? inputPlane : ((inputPlane >= 0) ? (inputPlane / m_fastInputPlaneStride) : 0);
+    if (inputPlane < 0 || inputPlane >= m_input_planes_eff ||
+        ((m_plane_inflate_strides != 1) && (inputPlane != origInputPlane * m_plane_inflate_strides))) {
+      return Scalar(m_paddingValue);
+    }
+
+    const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
+    const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index];
+
+    const Index inputIndex = depth +
+        origInputRow * m_rowInputStride +
+        origInputCol * m_colInputStride +
+        origInputPlane * m_planeInputStride +
+        otherIndex * m_otherInputStride;
+
+    return m_impl.coeff(inputIndex);
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
+
+    if (m_in_row_strides != 1 || m_in_col_strides != 1 || m_row_inflate_strides != 1 || m_col_inflate_strides != 1 ||
+        m_in_plane_strides != 1 || m_plane_inflate_strides != 1) {
+      return packetWithPossibleZero(index);
+    }
+
+    const Index indices[2] = {index, index + PacketSize - 1};
+    const Index patchIndex = indices[0] / m_fastPatchStride;
+    if (patchIndex != indices[1] / m_fastPatchStride) {
+      return packetWithPossibleZero(index);
+    }
+    const Index otherIndex = (NumDims == 5) ? 0 : indices[0] / m_fastOtherStride;
+    eigen_assert(otherIndex == indices[1] / m_fastOtherStride);
+
+    // Find the offset of the element wrt the location of the first element.
+    const Index patchOffsets[2] = {(indices[0] - patchIndex * m_patchStride) / m_fastOutputDepth,
+                                   (indices[1] - patchIndex * m_patchStride) / m_fastOutputDepth};
+
+    const Index patch3DIndex = (NumDims == 5) ? patchIndex : (indices[0] - otherIndex * m_otherStride) / m_fastPatchStride;
+    eigen_assert(patch3DIndex == (indices[1] - otherIndex * m_otherStride) / m_fastPatchStride);
+
+    const Index colIndex = patch3DIndex / m_fastOutputPlanesRows;
+    const Index colOffsets[2] = {
+      patchOffsets[0] / m_fastColStride,
+      patchOffsets[1] / m_fastColStride};
+
+    // Calculate col indices in the original input tensor.
+    const Index inputCols[2] = {
+      colIndex * m_col_strides + colOffsets[0] - m_colPaddingLeft,
+      colIndex * m_col_strides + colOffsets[1] - m_colPaddingLeft};
+    if (inputCols[1] < 0 || inputCols[0] >= m_inputCols) {
+      return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
+    }
+
+    if (inputCols[0] != inputCols[1]) {
+      return packetWithPossibleZero(index);
+    }
+
+    const Index rowIndex = (patch3DIndex - colIndex * m_outputPlanesRows) / m_fastOutputPlanes;
+    const Index rowOffsets[2] = {
+      (patchOffsets[0] - colOffsets[0] * m_colStride) / m_fastRowStride,
+      (patchOffsets[1] - colOffsets[1] * m_colStride) / m_fastRowStride};
+    eigen_assert(rowOffsets[0] <= rowOffsets[1]);
+    // Calculate col indices in the original input tensor.
+    const Index inputRows[2] = {
+      rowIndex * m_row_strides + rowOffsets[0] - m_rowPaddingTop,
+      rowIndex * m_row_strides + rowOffsets[1] - m_rowPaddingTop};
+
+    if (inputRows[1] < 0 || inputRows[0] >= m_inputRows) {
+      return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
+    }
+
+    if (inputRows[0] != inputRows[1]) {
+      return packetWithPossibleZero(index);
+    }
+
+    const Index planeIndex = (patch3DIndex - m_outputPlanes * (colIndex * m_outputRows + rowIndex));
+    const Index planeOffsets[2] = {
+      patchOffsets[0] - colOffsets[0] * m_colStride - rowOffsets[0] * m_rowStride,
+      patchOffsets[1] - colOffsets[1] * m_colStride - rowOffsets[1] * m_rowStride};
+    eigen_assert(planeOffsets[0] <= planeOffsets[1]);
+    const Index inputPlanes[2] = {
+      planeIndex * m_plane_strides + planeOffsets[0] - m_planePaddingTop,
+      planeIndex * m_plane_strides + planeOffsets[1] - m_planePaddingTop};
+
+    if (inputPlanes[1] < 0 || inputPlanes[0] >= m_inputPlanes) {
+      return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
+    }
+
+    if (inputPlanes[0] >= 0 && inputPlanes[1] < m_inputPlanes) {
+      // no padding
+      const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
+      const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index];
+      const Index inputIndex = depth +
+          inputRows[0] * m_rowInputStride +
+          inputCols[0] * m_colInputStride +
+          m_planeInputStride * inputPlanes[0] +
+          otherIndex * m_otherInputStride;
+      return m_impl.template packet<Unaligned>(inputIndex);
+    }
+
+    return packetWithPossibleZero(index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
+  costPerCoeff(bool vectorized) const {
+    const double compute_cost =
+        10 * TensorOpCost::DivCost<Index>() + 21 * TensorOpCost::MulCost<Index>() +
+        8 * TensorOpCost::AddCost<Index>();
+    return TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+  const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
+
+  Index planePaddingTop() const { return m_planePaddingTop; }
+  Index rowPaddingTop() const { return m_rowPaddingTop; }
+  Index colPaddingLeft() const { return m_colPaddingLeft; }
+  Index outputPlanes() const { return m_outputPlanes; }
+  Index outputRows() const { return m_outputRows; }
+  Index outputCols() const { return m_outputCols; }
+  Index userPlaneStride() const { return m_plane_strides; }
+  Index userRowStride() const { return m_row_strides; }
+  Index userColStride() const { return m_col_strides; }
+  Index userInPlaneStride() const { return m_in_plane_strides; }
+  Index userInRowStride() const { return m_in_row_strides; }
+  Index userInColStride() const { return m_in_col_strides; }
+  Index planeInflateStride() const { return m_plane_inflate_strides; }
+  Index rowInflateStride() const { return m_row_inflate_strides; }
+  Index colInflateStride() const { return m_col_inflate_strides; }
+
+ protected:
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
+  {
+    EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+    for (int i = 0; i < PacketSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  Dimensions m_dimensions;
+
+  // Parameters passed to the costructor.
+  Index m_plane_strides;
+  Index m_row_strides;
+  Index m_col_strides;
+
+  Index m_outputPlanes;
+  Index m_outputRows;
+  Index m_outputCols;
+
+  Index m_planePaddingTop;
+  Index m_rowPaddingTop;
+  Index m_colPaddingLeft;
+
+  Index m_in_plane_strides;
+  Index m_in_row_strides;
+  Index m_in_col_strides;
+
+  Index m_plane_inflate_strides;
+  Index m_row_inflate_strides;
+  Index m_col_inflate_strides;
+
+  // Cached input size.
+  Index m_inputDepth;
+  Index m_inputPlanes;
+  Index m_inputRows;
+  Index m_inputCols;
+
+  // Other cached variables.
+  Index m_outputPlanesRows;
+
+  // Effective input/patch post-inflation size.
+  Index m_input_planes_eff;
+  Index m_input_rows_eff;
+  Index m_input_cols_eff;
+  Index m_patch_planes_eff;
+  Index m_patch_rows_eff;
+  Index m_patch_cols_eff;
+
+  // Strides for the output tensor.
+  Index m_otherStride;
+  Index m_patchStride;
+  Index m_rowStride;
+  Index m_colStride;
+
+  // Strides for the input tensor.
+  Index m_planeInputStride;
+  Index m_rowInputStride;
+  Index m_colInputStride;
+  Index m_otherInputStride;
+
+  internal::TensorIntDivisor<Index> m_fastOtherStride;
+  internal::TensorIntDivisor<Index> m_fastPatchStride;
+  internal::TensorIntDivisor<Index> m_fastColStride;
+  internal::TensorIntDivisor<Index> m_fastRowStride;
+  internal::TensorIntDivisor<Index> m_fastInputPlaneStride;
+  internal::TensorIntDivisor<Index> m_fastInputRowStride;
+  internal::TensorIntDivisor<Index> m_fastInputColStride;
+  internal::TensorIntDivisor<Index> m_fastInputColsEff;
+  internal::TensorIntDivisor<Index> m_fastOutputPlanesRows;
+  internal::TensorIntDivisor<Index> m_fastOutputPlanes;
+  internal::TensorIntDivisor<Index> m_fastOutputDepth;
+
+  Scalar m_paddingValue;
+
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_VOLUME_PATCH_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/DynamicSymmetry.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/DynamicSymmetry.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/DynamicSymmetry.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/DynamicSymmetry.h
@@ -0,0 +1,293 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSORSYMMETRY_DYNAMICSYMMETRY_H
+#define EIGEN_CXX11_TENSORSYMMETRY_DYNAMICSYMMETRY_H
+
+namespace Eigen {
+
+class DynamicSGroup
+{
+  public:
+    inline explicit DynamicSGroup() : m_numIndices(1), m_elements(), m_generators(), m_globalFlags(0) { m_elements.push_back(ge(Generator(0, 0, 0))); }
+    inline DynamicSGroup(const DynamicSGroup& o) : m_numIndices(o.m_numIndices), m_elements(o.m_elements), m_generators(o.m_generators), m_globalFlags(o.m_globalFlags) { }
+    inline DynamicSGroup(DynamicSGroup&& o) : m_numIndices(o.m_numIndices), m_elements(), m_generators(o.m_generators), m_globalFlags(o.m_globalFlags) { std::swap(m_elements, o.m_elements); }
+    inline DynamicSGroup& operator=(const DynamicSGroup& o) { m_numIndices = o.m_numIndices; m_elements = o.m_elements; m_generators = o.m_generators; m_globalFlags = o.m_globalFlags; return *this; }
+    inline DynamicSGroup& operator=(DynamicSGroup&& o) { m_numIndices = o.m_numIndices; std::swap(m_elements, o.m_elements); m_generators = o.m_generators; m_globalFlags = o.m_globalFlags; return *this; }
+
+    void add(int one, int two, int flags = 0);
+
+    template<typename Gen_>
+    inline void add(Gen_) { add(Gen_::One, Gen_::Two, Gen_::Flags); }
+    inline void addSymmetry(int one, int two) { add(one, two, 0); }
+    inline void addAntiSymmetry(int one, int two) { add(one, two, NegationFlag); }
+    inline void addHermiticity(int one, int two) { add(one, two, ConjugationFlag); }
+    inline void addAntiHermiticity(int one, int two) { add(one, two, NegationFlag | ConjugationFlag); }
+
+    template<typename Op, typename RV, typename Index, std::size_t N, typename... Args>
+    inline RV apply(const std::array<Index, N>& idx, RV initial, Args&&... args) const
+    {
+      eigen_assert(N >= m_numIndices && "Can only apply symmetry group to objects that have at least the required amount of indices.");
+      for (std::size_t i = 0; i < size(); i++)
+        initial = Op::run(h_permute(i, idx, typename internal::gen_numeric_list<int, N>::type()), m_elements[i].flags, initial, std::forward<Args>(args)...);
+      return initial;
+    }
+
+    template<typename Op, typename RV, typename Index, typename... Args>
+    inline RV apply(const std::vector<Index>& idx, RV initial, Args&&... args) const
+    {
+      eigen_assert(idx.size() >= m_numIndices && "Can only apply symmetry group to objects that have at least the required amount of indices.");
+      for (std::size_t i = 0; i < size(); i++)
+        initial = Op::run(h_permute(i, idx), m_elements[i].flags, initial, std::forward<Args>(args)...);
+      return initial;
+    }
+
+    inline int globalFlags() const { return m_globalFlags; }
+    inline std::size_t size() const { return m_elements.size(); }
+
+    template<typename Tensor_, typename... IndexTypes>
+    inline internal::tensor_symmetry_value_setter<Tensor_, DynamicSGroup> operator()(Tensor_& tensor, typename Tensor_::Index firstIndex, IndexTypes... otherIndices) const
+    {
+      static_assert(sizeof...(otherIndices) + 1 == Tensor_::NumIndices, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
+      return operator()(tensor, std::array<typename Tensor_::Index, Tensor_::NumIndices>{{firstIndex, otherIndices...}});
+    }
+
+    template<typename Tensor_>
+    inline internal::tensor_symmetry_value_setter<Tensor_, DynamicSGroup> operator()(Tensor_& tensor, std::array<typename Tensor_::Index, Tensor_::NumIndices> const& indices) const
+    {
+      return internal::tensor_symmetry_value_setter<Tensor_, DynamicSGroup>(tensor, *this, indices);
+    }
+  private:
+    struct GroupElement {
+      std::vector<int> representation;
+      int flags;
+      bool isId() const
+      {
+        for (std::size_t i = 0; i < representation.size(); i++)
+          if (i != (size_t)representation[i])
+            return false;
+        return true;
+      }
+    };
+    struct Generator {
+      int one;
+      int two;
+      int flags;
+      constexpr inline Generator(int one_, int two_, int flags_) : one(one_), two(two_), flags(flags_) {}
+    };
+
+    std::size_t m_numIndices;
+    std::vector<GroupElement> m_elements;
+    std::vector<Generator> m_generators;
+    int m_globalFlags;
+
+    template<typename Index, std::size_t N, int... n>
+    inline std::array<Index, N> h_permute(std::size_t which, const std::array<Index, N>& idx, internal::numeric_list<int, n...>) const
+    {
+      return std::array<Index, N>{{ idx[n >= m_numIndices ? n : m_elements[which].representation[n]]... }};
+    }
+
+    template<typename Index>
+    inline std::vector<Index> h_permute(std::size_t which, std::vector<Index> idx) const
+    {
+      std::vector<Index> result;
+      result.reserve(idx.size());
+      for (auto k : m_elements[which].representation)
+        result.push_back(idx[k]);
+      for (std::size_t i = m_numIndices; i < idx.size(); i++)
+        result.push_back(idx[i]);
+      return result;
+    }
+
+    inline GroupElement ge(Generator const& g) const
+    {
+      GroupElement result;
+      result.representation.reserve(m_numIndices);
+      result.flags = g.flags;
+      for (std::size_t k = 0; k < m_numIndices; k++) {
+        if (k == (std::size_t)g.one)
+          result.representation.push_back(g.two);
+        else if (k == (std::size_t)g.two)
+          result.representation.push_back(g.one);
+        else
+          result.representation.push_back(int(k));
+      }
+      return result;
+    }
+
+    GroupElement mul(GroupElement, GroupElement) const;
+    inline GroupElement mul(Generator g1, GroupElement g2) const
+    {
+      return mul(ge(g1), g2);
+    }
+
+    inline GroupElement mul(GroupElement g1, Generator g2) const
+    {
+      return mul(g1, ge(g2));
+    }
+
+    inline GroupElement mul(Generator g1, Generator g2) const
+    {
+      return mul(ge(g1), ge(g2));
+    }
+
+    inline int findElement(GroupElement e) const
+    {
+      for (auto ee : m_elements) {
+        if (ee.representation == e.representation)
+          return ee.flags ^ e.flags;
+      }
+      return -1;
+    }
+
+    void updateGlobalFlags(int flagDiffOfSameGenerator);
+};
+
+// dynamic symmetry group that auto-adds the template parameters in the constructor
+template<typename... Gen>
+class DynamicSGroupFromTemplateArgs : public DynamicSGroup
+{
+  public:
+    inline DynamicSGroupFromTemplateArgs() : DynamicSGroup()
+    {
+      add_all(internal::type_list<Gen...>());
+    }
+    inline DynamicSGroupFromTemplateArgs(DynamicSGroupFromTemplateArgs const& other) : DynamicSGroup(other) { }
+    inline DynamicSGroupFromTemplateArgs(DynamicSGroupFromTemplateArgs&& other) : DynamicSGroup(other) { }
+    inline DynamicSGroupFromTemplateArgs<Gen...>& operator=(const DynamicSGroupFromTemplateArgs<Gen...>& o) { DynamicSGroup::operator=(o); return *this; }
+    inline DynamicSGroupFromTemplateArgs<Gen...>& operator=(DynamicSGroupFromTemplateArgs<Gen...>&& o) { DynamicSGroup::operator=(o); return *this; }
+  
+  private:
+    template<typename Gen1, typename... GenNext>
+    inline void add_all(internal::type_list<Gen1, GenNext...>)
+    {
+      add(Gen1());
+      add_all(internal::type_list<GenNext...>());
+    }
+
+    inline void add_all(internal::type_list<>)
+    {
+    }
+};
+
+inline DynamicSGroup::GroupElement DynamicSGroup::mul(GroupElement g1, GroupElement g2) const
+{
+  eigen_internal_assert(g1.representation.size() == m_numIndices);
+  eigen_internal_assert(g2.representation.size() == m_numIndices);
+
+  GroupElement result;
+  result.representation.reserve(m_numIndices);
+  for (std::size_t i = 0; i < m_numIndices; i++) {
+    int v = g2.representation[g1.representation[i]];
+    eigen_assert(v >= 0);
+    result.representation.push_back(v);
+  }
+  result.flags = g1.flags ^ g2.flags;
+  return result;
+}
+
+inline void DynamicSGroup::add(int one, int two, int flags)
+{
+  eigen_assert(one >= 0);
+  eigen_assert(two >= 0);
+  eigen_assert(one != two);
+
+  if ((std::size_t)one >= m_numIndices || (std::size_t)two >= m_numIndices) {
+    std::size_t newNumIndices = (one > two) ? one : two + 1;
+    for (auto& gelem : m_elements) {
+      gelem.representation.reserve(newNumIndices);
+      for (std::size_t i = m_numIndices; i < newNumIndices; i++)
+        gelem.representation.push_back(i);
+    }
+    m_numIndices = newNumIndices;
+  }
+
+  Generator g{one, two, flags};
+  GroupElement e = ge(g);
+
+  /* special case for first generator */
+  if (m_elements.size() == 1) {
+    while (!e.isId()) {
+      m_elements.push_back(e);
+      e = mul(e, g);
+    }
+
+    if (e.flags > 0)
+      updateGlobalFlags(e.flags);
+
+    // only add in case we didn't have identity
+    if (m_elements.size() > 1)
+      m_generators.push_back(g);
+    return;
+  }
+
+  int p = findElement(e);
+  if (p >= 0) {
+    updateGlobalFlags(p);
+    return;
+  }
+
+  std::size_t coset_order = m_elements.size();
+  m_elements.push_back(e);
+  for (std::size_t i = 1; i < coset_order; i++)
+    m_elements.push_back(mul(m_elements[i], e));
+  m_generators.push_back(g);
+
+  std::size_t coset_rep = coset_order;
+  do {
+    for (auto g : m_generators) {
+      e = mul(m_elements[coset_rep], g);
+      p = findElement(e);
+      if (p < 0) {
+        // element not yet in group
+        m_elements.push_back(e);
+        for (std::size_t i = 1; i < coset_order; i++)
+          m_elements.push_back(mul(m_elements[i], e));
+      } else if (p > 0) {
+        updateGlobalFlags(p);
+      }
+    }
+    coset_rep += coset_order;
+  } while (coset_rep < m_elements.size());
+}
+
+inline void DynamicSGroup::updateGlobalFlags(int flagDiffOfSameGenerator)
+{
+    switch (flagDiffOfSameGenerator) {
+      case 0:
+      default:
+        // nothing happened
+        break;
+      case NegationFlag:
+        // every element is it's own negative => whole tensor is zero
+        m_globalFlags |= GlobalZeroFlag;
+        break;
+      case ConjugationFlag:
+        // every element is it's own conjugate => whole tensor is real
+        m_globalFlags |= GlobalRealFlag;
+        break;
+      case (NegationFlag | ConjugationFlag):
+        // every element is it's own negative conjugate => whole tensor is imaginary
+        m_globalFlags |= GlobalImagFlag;
+        break;
+      /* NOTE:
+       *   since GlobalZeroFlag == GlobalRealFlag | GlobalImagFlag, if one generator
+       *   causes the tensor to be real and the next one to be imaginary, this will
+       *   trivially give the correct result
+       */
+    }
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSORSYMMETRY_DYNAMICSYMMETRY_H
+
+/*
+ * kate: space-indent on; indent-width 2; mixedindent off; indent-mode cstyle;
+ */

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/StaticSymmetry.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/StaticSymmetry.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/StaticSymmetry.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/StaticSymmetry.h
@@ -0,0 +1,236 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSORSYMMETRY_STATICSYMMETRY_H
+#define EIGEN_CXX11_TENSORSYMMETRY_STATICSYMMETRY_H
+
+namespace Eigen {
+
+namespace internal {
+
+template<typename list> struct tensor_static_symgroup_permutate;
+
+template<int... nn>
+struct tensor_static_symgroup_permutate<numeric_list<int, nn...>>
+{
+  constexpr static std::size_t N = sizeof...(nn);
+
+  template<typename T>
+  constexpr static inline std::array<T, N> run(const std::array<T, N>& indices)
+  {
+    return {{indices[nn]...}};
+  }
+};
+
+template<typename indices_, int flags_>
+struct tensor_static_symgroup_element
+{
+  typedef indices_ indices;
+  constexpr static int flags = flags_;
+};
+
+template<typename Gen, int N>
+struct tensor_static_symgroup_element_ctor
+{
+  typedef tensor_static_symgroup_element<
+    typename gen_numeric_list_swapped_pair<int, N, Gen::One, Gen::Two>::type,
+    Gen::Flags
+  > type;
+};
+
+template<int N>
+struct tensor_static_symgroup_identity_ctor
+{
+  typedef tensor_static_symgroup_element<
+    typename gen_numeric_list<int, N>::type,
+    0
+  > type;
+};
+
+template<typename iib>
+struct tensor_static_symgroup_multiply_helper
+{
+  template<int... iia>
+  constexpr static inline numeric_list<int, get<iia, iib>::value...> helper(numeric_list<int, iia...>) {
+    return numeric_list<int, get<iia, iib>::value...>();
+  }
+};
+
+template<typename A, typename B>
+struct tensor_static_symgroup_multiply
+{
+  private:
+    typedef typename A::indices iia;
+    typedef typename B::indices iib;
+    constexpr static int ffa = A::flags;
+    constexpr static int ffb = B::flags;
+  
+  public:
+    static_assert(iia::count == iib::count, "Cannot multiply symmetry elements with different number of indices.");
+
+    typedef tensor_static_symgroup_element<
+      decltype(tensor_static_symgroup_multiply_helper<iib>::helper(iia())),
+      ffa ^ ffb
+    > type;
+};
+
+template<typename A, typename B>
+struct tensor_static_symgroup_equality
+{
+    typedef typename A::indices iia;
+    typedef typename B::indices iib;
+    constexpr static int ffa = A::flags;
+    constexpr static int ffb = B::flags;
+    static_assert(iia::count == iib::count, "Cannot compare symmetry elements with different number of indices.");
+
+    constexpr static bool value = is_same<iia, iib>::value;
+
+  private:
+    /* this should be zero if they are identical, or else the tensor
+     * will be forced to be pure real, pure imaginary or even pure zero
+     */
+    constexpr static int flags_cmp_ = ffa ^ ffb;
+
+    /* either they are not equal, then we don't care whether the flags
+     * match, or they are equal, and then we have to check
+     */
+    constexpr static bool is_zero      = value && flags_cmp_ == NegationFlag;
+    constexpr static bool is_real      = value && flags_cmp_ == ConjugationFlag;
+    constexpr static bool is_imag      = value && flags_cmp_ == (NegationFlag | ConjugationFlag);
+
+  public:
+    constexpr static int global_flags = 
+      (is_real ? GlobalRealFlag : 0) |
+      (is_imag ? GlobalImagFlag : 0) |
+      (is_zero ? GlobalZeroFlag : 0);
+};
+
+template<std::size_t NumIndices, typename... Gen>
+struct tensor_static_symgroup
+{
+  typedef StaticSGroup<Gen...> type;
+  constexpr static std::size_t size = type::static_size;
+};
+
+template<typename Index, std::size_t N, int... ii, int... jj>
+constexpr static inline std::array<Index, N> tensor_static_symgroup_index_permute(std::array<Index, N> idx, internal::numeric_list<int, ii...>, internal::numeric_list<int, jj...>)
+{
+  return {{ idx[ii]..., idx[jj]... }};
+}
+
+template<typename Index, int... ii>
+static inline std::vector<Index> tensor_static_symgroup_index_permute(std::vector<Index> idx, internal::numeric_list<int, ii...>)
+{
+  std::vector<Index> result{{ idx[ii]... }};
+  std::size_t target_size = idx.size();
+  for (std::size_t i = result.size(); i < target_size; i++)
+    result.push_back(idx[i]);
+  return result;
+}
+
+template<typename T> struct tensor_static_symgroup_do_apply;
+
+template<typename first, typename... next>
+struct tensor_static_symgroup_do_apply<internal::type_list<first, next...>>
+{
+  template<typename Op, typename RV, std::size_t SGNumIndices, typename Index, std::size_t NumIndices, typename... Args>
+  static inline RV run(const std::array<Index, NumIndices>& idx, RV initial, Args&&... args)
+  {
+    static_assert(NumIndices >= SGNumIndices, "Can only apply symmetry group to objects that have at least the required amount of indices.");
+    typedef typename internal::gen_numeric_list<int, NumIndices - SGNumIndices, SGNumIndices>::type remaining_indices;
+    initial = Op::run(tensor_static_symgroup_index_permute(idx, typename first::indices(), remaining_indices()), first::flags, initial, std::forward<Args>(args)...);
+    return tensor_static_symgroup_do_apply<internal::type_list<next...>>::template run<Op, RV, SGNumIndices>(idx, initial, args...);
+  }
+
+  template<typename Op, typename RV, std::size_t SGNumIndices, typename Index, typename... Args>
+  static inline RV run(const std::vector<Index>& idx, RV initial, Args&&... args)
+  {
+    eigen_assert(idx.size() >= SGNumIndices && "Can only apply symmetry group to objects that have at least the required amount of indices.");
+    initial = Op::run(tensor_static_symgroup_index_permute(idx, typename first::indices()), first::flags, initial, std::forward<Args>(args)...);
+    return tensor_static_symgroup_do_apply<internal::type_list<next...>>::template run<Op, RV, SGNumIndices>(idx, initial, args...);
+  }
+};
+
+template<EIGEN_TPL_PP_SPEC_HACK_DEF(typename, empty)>
+struct tensor_static_symgroup_do_apply<internal::type_list<EIGEN_TPL_PP_SPEC_HACK_USE(empty)>>
+{
+  template<typename Op, typename RV, std::size_t SGNumIndices, typename Index, std::size_t NumIndices, typename... Args>
+  static inline RV run(const std::array<Index, NumIndices>&, RV initial, Args&&...)
+  {
+    // do nothing
+    return initial;
+  }
+
+  template<typename Op, typename RV, std::size_t SGNumIndices, typename Index, typename... Args>
+  static inline RV run(const std::vector<Index>&, RV initial, Args&&...)
+  {
+    // do nothing
+    return initial;
+  }
+};
+
+} // end namespace internal
+
+template<typename... Gen>
+class StaticSGroup
+{
+    constexpr static std::size_t NumIndices = internal::tensor_symmetry_num_indices<Gen...>::value;
+    typedef internal::group_theory::enumerate_group_elements<
+      internal::tensor_static_symgroup_multiply,
+      internal::tensor_static_symgroup_equality,
+      typename internal::tensor_static_symgroup_identity_ctor<NumIndices>::type,
+      internal::type_list<typename internal::tensor_static_symgroup_element_ctor<Gen, NumIndices>::type...>
+    > group_elements;
+    typedef typename group_elements::type ge;
+  public:
+    constexpr inline StaticSGroup() {}
+    constexpr inline StaticSGroup(const StaticSGroup<Gen...>&) {}
+    constexpr inline StaticSGroup(StaticSGroup<Gen...>&&) {}
+
+    template<typename Op, typename RV, typename Index, std::size_t N, typename... Args>
+    static inline RV apply(const std::array<Index, N>& idx, RV initial, Args&&... args)
+    {
+      return internal::tensor_static_symgroup_do_apply<ge>::template run<Op, RV, NumIndices>(idx, initial, args...);
+    }
+
+    template<typename Op, typename RV, typename Index, typename... Args>
+    static inline RV apply(const std::vector<Index>& idx, RV initial, Args&&... args)
+    {
+      eigen_assert(idx.size() == NumIndices);
+      return internal::tensor_static_symgroup_do_apply<ge>::template run<Op, RV, NumIndices>(idx, initial, args...);
+    }
+
+    constexpr static std::size_t static_size = ge::count;
+
+    constexpr static inline std::size_t size() {
+      return ge::count;
+    }
+    constexpr static inline int globalFlags() { return group_elements::global_flags; }
+
+    template<typename Tensor_, typename... IndexTypes>
+    inline internal::tensor_symmetry_value_setter<Tensor_, StaticSGroup<Gen...>> operator()(Tensor_& tensor, typename Tensor_::Index firstIndex, IndexTypes... otherIndices) const
+    {
+      static_assert(sizeof...(otherIndices) + 1 == Tensor_::NumIndices, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
+      return operator()(tensor, std::array<typename Tensor_::Index, Tensor_::NumIndices>{{firstIndex, otherIndices...}});
+    }
+
+    template<typename Tensor_>
+    inline internal::tensor_symmetry_value_setter<Tensor_, StaticSGroup<Gen...>> operator()(Tensor_& tensor, std::array<typename Tensor_::Index, Tensor_::NumIndices> const& indices) const
+    {
+      return internal::tensor_symmetry_value_setter<Tensor_, StaticSGroup<Gen...>>(tensor, *this, indices);
+    }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSORSYMMETRY_STATICSYMMETRY_H
+
+/*
+ * kate: space-indent on; indent-width 2; mixedindent off; indent-mode cstyle;
+ */

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/Symmetry.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/Symmetry.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/Symmetry.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/Symmetry.h
@@ -0,0 +1,338 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSORSYMMETRY_SYMMETRY_H
+#define EIGEN_CXX11_TENSORSYMMETRY_SYMMETRY_H
+
+namespace Eigen {
+
+enum {
+  NegationFlag           = 0x01,
+  ConjugationFlag        = 0x02
+};
+
+enum {
+  GlobalRealFlag         = 0x01,
+  GlobalImagFlag         = 0x02,
+  GlobalZeroFlag         = 0x03
+};
+
+namespace internal {
+
+template<std::size_t NumIndices, typename... Sym>                   struct tensor_symmetry_pre_analysis;
+template<std::size_t NumIndices, typename... Sym>                   struct tensor_static_symgroup;
+template<bool instantiate, std::size_t NumIndices, typename... Sym> struct tensor_static_symgroup_if;
+template<typename Tensor_> struct tensor_symmetry_calculate_flags;
+template<typename Tensor_> struct tensor_symmetry_assign_value;
+template<typename... Sym> struct tensor_symmetry_num_indices;
+
+} // end namespace internal
+
+template<int One_, int Two_>
+struct Symmetry
+{
+  static_assert(One_ != Two_, "Symmetries must cover distinct indices.");
+  constexpr static int One = One_;
+  constexpr static int Two = Two_;
+  constexpr static int Flags = 0;
+};
+
+template<int One_, int Two_>
+struct AntiSymmetry
+{
+  static_assert(One_ != Two_, "Symmetries must cover distinct indices.");
+  constexpr static int One = One_;
+  constexpr static int Two = Two_;
+  constexpr static int Flags = NegationFlag;
+};
+
+template<int One_, int Two_>
+struct Hermiticity
+{
+  static_assert(One_ != Two_, "Symmetries must cover distinct indices.");
+  constexpr static int One = One_;
+  constexpr static int Two = Two_;
+  constexpr static int Flags = ConjugationFlag;
+};
+
+template<int One_, int Two_>
+struct AntiHermiticity
+{
+  static_assert(One_ != Two_, "Symmetries must cover distinct indices.");
+  constexpr static int One = One_;
+  constexpr static int Two = Two_;
+  constexpr static int Flags = ConjugationFlag | NegationFlag;
+};
+
+/** \class DynamicSGroup
+  * \ingroup TensorSymmetry_Module
+  *
+  * \brief Dynamic symmetry group
+  *
+  * The %DynamicSGroup class represents a symmetry group that need not be known at
+  * compile time. It is useful if one wants to support arbitrary run-time defineable
+  * symmetries for tensors, but it is also instantiated if a symmetry group is defined
+  * at compile time that would be either too large for the compiler to reasonably
+  * generate (using templates to calculate this at compile time is very inefficient)
+  * or that the compiler could generate the group but that it wouldn't make sense to
+  * unroll the loop for setting coefficients anymore.
+  */
+class DynamicSGroup;
+
+/** \internal
+  *
+  * \class DynamicSGroupFromTemplateArgs
+  * \ingroup TensorSymmetry_Module
+  *
+  * \brief Dynamic symmetry group, initialized from template arguments
+  *
+  * This class is a child class of DynamicSGroup. It uses the template arguments
+  * specified to initialize itself.
+  */
+template<typename... Gen>
+class DynamicSGroupFromTemplateArgs;
+
+/** \class StaticSGroup
+  * \ingroup TensorSymmetry_Module
+  *
+  * \brief Static symmetry group
+  *
+  * This class represents a symmetry group that is known and resolved completely
+  * at compile time. Ideally, no run-time penalty is incurred compared to the
+  * manual unrolling of the symmetry.
+  *
+  * <b><i>CAUTION:</i></b>
+  *
+  * Do not use this class directly for large symmetry groups. The compiler
+  * may run into a limit, or segfault or in the very least will take a very,
+  * very, very long time to compile the code. Use the SGroup class instead
+  * if you want a static group. That class contains logic that will
+  * automatically select the DynamicSGroup class instead if the symmetry
+  * group becomes too large. (In that case, unrolling may not even be
+  * beneficial.)
+  */
+template<typename... Gen>
+class StaticSGroup;
+
+/** \class SGroup
+  * \ingroup TensorSymmetry_Module
+  *
+  * \brief Symmetry group, initialized from template arguments
+  *
+  * This class represents a symmetry group whose generators are already
+  * known at compile time. It may or may not be resolved at compile time,
+  * depending on the estimated size of the group.
+  *
+  * \sa StaticSGroup
+  * \sa DynamicSGroup
+  */
+template<typename... Gen>
+class SGroup : public internal::tensor_symmetry_pre_analysis<internal::tensor_symmetry_num_indices<Gen...>::value, Gen...>::root_type
+{
+  public:
+    constexpr static std::size_t NumIndices = internal::tensor_symmetry_num_indices<Gen...>::value;
+    typedef typename internal::tensor_symmetry_pre_analysis<NumIndices, Gen...>::root_type Base;
+
+    // make standard constructors + assignment operators public
+    inline SGroup() : Base() { }
+    inline SGroup(const SGroup<Gen...>& other) : Base(other) { }
+    inline SGroup(SGroup<Gen...>&& other) : Base(other) { }
+    inline SGroup<Gen...>& operator=(const SGroup<Gen...>& other) { Base::operator=(other); return *this; }
+    inline SGroup<Gen...>& operator=(SGroup<Gen...>&& other) { Base::operator=(other); return *this; }
+
+    // all else is defined in the base class
+};
+
+namespace internal {
+
+template<typename... Sym> struct tensor_symmetry_num_indices
+{
+  constexpr static std::size_t value = 1;
+};
+
+template<int One_, int Two_, typename... Sym> struct tensor_symmetry_num_indices<Symmetry<One_, Two_>, Sym...>
+{
+private:
+  constexpr static std::size_t One = static_cast<std::size_t>(One_);
+  constexpr static std::size_t Two = static_cast<std::size_t>(Two_);
+  constexpr static std::size_t Three = tensor_symmetry_num_indices<Sym...>::value;
+
+  // don't use std::max, since it's not constexpr until C++14...
+  constexpr static std::size_t maxOneTwoPlusOne = ((One > Two) ? One : Two) + 1;
+public:
+  constexpr static std::size_t value = (maxOneTwoPlusOne > Three) ? maxOneTwoPlusOne : Three;
+};
+
+template<int One_, int Two_, typename... Sym> struct tensor_symmetry_num_indices<AntiSymmetry<One_, Two_>, Sym...>
+  : public tensor_symmetry_num_indices<Symmetry<One_, Two_>, Sym...> {};
+template<int One_, int Two_, typename... Sym> struct tensor_symmetry_num_indices<Hermiticity<One_, Two_>, Sym...>
+  : public tensor_symmetry_num_indices<Symmetry<One_, Two_>, Sym...> {};
+template<int One_, int Two_, typename... Sym> struct tensor_symmetry_num_indices<AntiHermiticity<One_, Two_>, Sym...>
+  : public tensor_symmetry_num_indices<Symmetry<One_, Two_>, Sym...> {};
+
+/** \internal
+  *
+  * \class tensor_symmetry_pre_analysis
+  * \ingroup TensorSymmetry_Module
+  *
+  * \brief Pre-select whether to use a static or dynamic symmetry group
+  *
+  * When a symmetry group could in principle be determined at compile time,
+  * this template implements the logic whether to actually do that or whether
+  * to rather defer that to runtime.
+  *
+  * The logic is as follows:
+  * <dl>
+  * <dt><b>No generators (trivial symmetry):</b></dt>
+  * <dd>Use a trivial static group. Ideally, this has no performance impact
+  *     compared to not using symmetry at all. In practice, this might not
+  *     be the case.</dd>
+  * <dt><b>More than 4 generators:</b></dt>
+  * <dd>Calculate the group at run time, it is likely far too large for the
+  *     compiler to be able to properly generate it in a realistic time.</dd>
+  * <dt><b>Up to and including 4 generators:</b></dt>
+  * <dd>Actually enumerate all group elements, but then check how many there
+  *     are. If there are more than 16, it is unlikely that unrolling the
+  *     loop (as is done in the static compile-time case) is sensible, so
+  *     use a dynamic group instead. If there are at most 16 elements, actually
+  *     use that static group. Note that the largest group with 4 generators
+  *     still compiles with reasonable resources.</dd>
+  * </dl>
+  *
+  * Note: Example compile time performance with g++-4.6 on an Intenl Core i5-3470
+  *       with 16 GiB RAM (all generators non-redundant and the subgroups don't
+  *       factorize):
+  *
+  *          # Generators          -O0 -ggdb               -O2
+  *          -------------------------------------------------------------------
+  *          1                 0.5 s  /   250 MiB     0.45s /   230 MiB
+  *          2                 0.5 s  /   260 MiB     0.5 s /   250 MiB
+  *          3                 0.65s  /   310 MiB     0.62s /   310 MiB
+  *          4                 2.2 s  /   860 MiB     1.7 s /   770 MiB
+  *          5               130   s  / 13000 MiB   120   s / 11000 MiB
+  *
+  * It is clear that everything is still very efficient up to 4 generators, then
+  * the memory and CPU requirements become unreasonable. Thus we only instantiate
+  * the template group theory logic if the number of generators supplied is 4 or
+  * lower, otherwise this will be forced to be done during runtime, where the
+  * algorithm is reasonably fast.
+  */
+template<std::size_t NumIndices>
+struct tensor_symmetry_pre_analysis<NumIndices>
+{
+  typedef StaticSGroup<> root_type;
+};
+
+template<std::size_t NumIndices, typename Gen_, typename... Gens_>
+struct tensor_symmetry_pre_analysis<NumIndices, Gen_, Gens_...>
+{
+  constexpr static std::size_t max_static_generators = 4;
+  constexpr static std::size_t max_static_elements = 16;
+  typedef tensor_static_symgroup_if<(sizeof...(Gens_) + 1 <= max_static_generators), NumIndices, Gen_, Gens_...> helper;
+  constexpr static std::size_t possible_size = helper::size;
+
+  typedef typename conditional<
+    possible_size == 0 || possible_size >= max_static_elements,
+    DynamicSGroupFromTemplateArgs<Gen_, Gens_...>,
+    typename helper::type
+  >::type root_type;
+};
+
+template<bool instantiate, std::size_t NumIndices, typename... Gens>
+struct tensor_static_symgroup_if
+{
+  constexpr static std::size_t size = 0;
+  typedef void type;
+};
+
+template<std::size_t NumIndices, typename... Gens>
+struct tensor_static_symgroup_if<true, NumIndices, Gens...> : tensor_static_symgroup<NumIndices, Gens...> {};
+
+template<typename Tensor_>
+struct tensor_symmetry_assign_value
+{
+  typedef typename Tensor_::Index Index;
+  typedef typename Tensor_::Scalar Scalar;
+  constexpr static std::size_t NumIndices = Tensor_::NumIndices;
+
+  static inline int run(const std::array<Index, NumIndices>& transformed_indices, int transformation_flags, int dummy, Tensor_& tensor, const Scalar& value_)
+  {
+    Scalar value(value_);
+    if (transformation_flags & ConjugationFlag)
+      value = numext::conj(value);
+    if (transformation_flags & NegationFlag)
+      value = -value;
+    tensor.coeffRef(transformed_indices) = value;
+    return dummy;
+  }
+};
+
+template<typename Tensor_>
+struct tensor_symmetry_calculate_flags
+{
+  typedef typename Tensor_::Index Index;
+  constexpr static std::size_t NumIndices = Tensor_::NumIndices;
+
+  static inline int run(const std::array<Index, NumIndices>& transformed_indices, int transform_flags, int current_flags, const std::array<Index, NumIndices>& orig_indices)
+  {
+    if (transformed_indices == orig_indices) {
+      if (transform_flags & (ConjugationFlag | NegationFlag))
+        return current_flags | GlobalImagFlag; // anti-hermitian diagonal
+      else if (transform_flags & ConjugationFlag)
+        return current_flags | GlobalRealFlag; // hermitian diagonal
+      else if (transform_flags & NegationFlag)
+        return current_flags | GlobalZeroFlag; // anti-symmetric diagonal
+    }
+    return current_flags;
+  }
+};
+
+template<typename Tensor_, typename Symmetry_, int Flags = 0>
+class tensor_symmetry_value_setter
+{
+  public:
+    typedef typename Tensor_::Index Index;
+    typedef typename Tensor_::Scalar Scalar;
+    constexpr static std::size_t NumIndices = Tensor_::NumIndices;
+
+    inline tensor_symmetry_value_setter(Tensor_& tensor, Symmetry_ const& symmetry, std::array<Index, NumIndices> const& indices)
+      : m_tensor(tensor), m_symmetry(symmetry), m_indices(indices) { }
+
+    inline tensor_symmetry_value_setter<Tensor_, Symmetry_, Flags>& operator=(Scalar const& value)
+    {
+      doAssign(value);
+      return *this;
+    }
+  private:
+    Tensor_& m_tensor;
+    Symmetry_ m_symmetry;
+    std::array<Index, NumIndices> m_indices;
+
+    inline void doAssign(Scalar const& value)
+    {
+      #ifdef EIGEN_TENSOR_SYMMETRY_CHECK_VALUES
+        int value_flags = m_symmetry.template apply<internal::tensor_symmetry_calculate_flags<Tensor_>, int>(m_indices, m_symmetry.globalFlags(), m_indices);
+        if (value_flags & GlobalRealFlag)
+          eigen_assert(numext::imag(value) == 0);
+        if (value_flags & GlobalImagFlag)
+          eigen_assert(numext::real(value) == 0);
+      #endif
+      m_symmetry.template apply<internal::tensor_symmetry_assign_value<Tensor_>, int>(m_indices, 0, m_tensor, value);
+    }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSORSYMMETRY_SYMMETRY_H
+
+/*
+ * kate: space-indent on; indent-width 2; mixedindent off; indent-mode cstyle;
+ */

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/util/TemplateGroupTheory.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/util/TemplateGroupTheory.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/util/TemplateGroupTheory.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/TensorSymmetry/util/TemplateGroupTheory.h
@@ -0,0 +1,666 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSORSYMMETRY_TEMPLATEGROUPTHEORY_H
+#define EIGEN_CXX11_TENSORSYMMETRY_TEMPLATEGROUPTHEORY_H
+
+namespace Eigen {
+
+namespace internal {
+
+namespace group_theory {
+
+/** \internal
+  * \file CXX11/Tensor/util/TemplateGroupTheory.h
+  * This file contains C++ templates that implement group theory algorithms.
+  *
+  * The algorithms allow for a compile-time analysis of finite groups.
+  *
+  * Currently only Dimino's algorithm is implemented, which returns a list
+  * of all elements in a group given a set of (possibly redundant) generators.
+  * (One could also do that with the so-called orbital algorithm, but that
+  * is much more expensive and usually has no advantages.)
+  */
+
+/**********************************************************************
+ *                "Ok kid, here is where it gets complicated."
+ *                         - Amelia Pond in the "Doctor Who" episode
+ *                           "The Big Bang"
+ *
+ * Dimino's algorithm
+ * ==================
+ *
+ * The following is Dimino's algorithm in sequential form:
+ *
+ * Input: identity element, list of generators, equality check,
+ *        multiplication operation
+ * Output: list of group elements
+ *
+ * 1. add identity element
+ * 2. remove identities from list of generators
+ * 3. add all powers of first generator that aren't the
+ *    identity element
+ * 4. go through all remaining generators:
+ *        a. if generator is already in the list of elements
+ *                -> do nothing
+ *        b. otherwise
+ *                i.   remember current # of elements
+ *                     (i.e. the size of the current subgroup)
+ *                ii.  add all current elements (which includes
+ *                     the identity) each multiplied from right
+ *                     with the current generator to the group
+ *                iii. add all remaining cosets that are generated
+ *                     by products of the new generator with itself
+ *                     and all other generators seen so far
+ *
+ * In functional form, this is implemented as a long set of recursive
+ * templates that have a complicated relationship.
+ *
+ * The main interface for Dimino's algorithm is the template
+ * enumerate_group_elements. All lists are implemented as variadic
+ * type_list<typename...> and numeric_list<typename = int, int...>
+ * templates.
+ *
+ * 'Calling' templates is usually done via typedefs.
+ *
+ * This algorithm is an extended version of the basic version. The
+ * extension consists in the fact that each group element has a set
+ * of flags associated with it. Multiplication of two group elements
+ * with each other results in a group element whose flags are the
+ * XOR of the flags of the previous elements. Each time the algorithm
+ * notices that a group element it just calculated is already in the
+ * list of current elements, the flags of both will be compared and
+ * added to the so-called 'global flags' of the group.
+ *
+ * The rationale behind this extension is that this allows not only
+ * for the description of symmetries between tensor indices, but
+ * also allows for the description of hermiticity, antisymmetry and
+ * antihermiticity. Negation and conjugation each are specific bit
+ * in the flags value and if two different ways to reach a group
+ * element lead to two different flags, this poses a constraint on
+ * the allowed values of the resulting tensor. For example, if a
+ * group element is reach both with and without the conjugation
+ * flags, it is clear that the resulting tensor has to be real.
+ *
+ * Note that this flag mechanism is quite generic and may have other
+ * uses beyond tensor properties.
+ *
+ * IMPORTANT: 
+ *     This algorithm assumes the group to be finite. If you try to
+ *     run it with a group that's infinite, the algorithm will only
+ *     terminate once you hit a compiler limit (max template depth).
+ *     Also note that trying to use this implementation to create a
+ *     very large group will probably either make you hit the same
+ *     limit, cause the compiler to segfault or at the very least
+ *     take a *really* long time (hours, days, weeks - sic!) to
+ *     compile. It is not recommended to plug in more than 4
+ *     generators, unless they are independent of each other.
+ */
+
+/** \internal
+  *
+  * \class strip_identities
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Cleanse a list of group elements of the identity element
+  *
+  * This template is used to make a first pass through all initial
+  * generators of Dimino's algorithm and remove the identity
+  * elements.
+  *
+  * \sa enumerate_group_elements
+  */
+template<template<typename, typename> class Equality, typename id, typename L> struct strip_identities;
+
+template<
+  template<typename, typename> class Equality,
+  typename id,
+  typename t,
+  typename... ts
+>
+struct strip_identities<Equality, id, type_list<t, ts...>>
+{
+  typedef typename conditional<
+    Equality<id, t>::value,
+    typename strip_identities<Equality, id, type_list<ts...>>::type,
+    typename concat<type_list<t>, typename strip_identities<Equality, id, type_list<ts...>>::type>::type
+  >::type type;
+  constexpr static int global_flags = Equality<id, t>::global_flags | strip_identities<Equality, id, type_list<ts...>>::global_flags;
+};
+
+template<
+  template<typename, typename> class Equality,
+  typename id
+  EIGEN_TPL_PP_SPEC_HACK_DEFC(typename, ts)
+>
+struct strip_identities<Equality, id, type_list<EIGEN_TPL_PP_SPEC_HACK_USE(ts)>>
+{
+  typedef type_list<> type;
+  constexpr static int global_flags = 0;
+};
+
+/** \internal
+  *
+  * \class dimino_first_step_elements_helper 
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Recursive template that adds powers of the first generator to the list of group elements
+  *
+  * This template calls itself recursively to add powers of the first
+  * generator to the list of group elements. It stops if it reaches
+  * the identity element again.
+  *
+  * \sa enumerate_group_elements, dimino_first_step_elements
+  */
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename g,
+  typename current_element,
+  typename elements,
+  bool dont_add_current_element   // = false
+>
+struct dimino_first_step_elements_helper :
+  public dimino_first_step_elements_helper<
+    Multiply,
+    Equality,
+    id,
+    g,
+    typename Multiply<current_element, g>::type,
+    typename concat<elements, type_list<current_element>>::type,
+    Equality<typename Multiply<current_element, g>::type, id>::value
+  > {};
+
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename g,
+  typename current_element,
+  typename elements
+>
+struct dimino_first_step_elements_helper<Multiply, Equality, id, g, current_element, elements, true>
+{
+  typedef elements type;
+  constexpr static int global_flags = Equality<current_element, id>::global_flags;
+};
+
+/** \internal
+  *
+  * \class dimino_first_step_elements
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Add all powers of the first generator to the list of group elements
+  *
+  * This template takes the first non-identity generator and generates the initial
+  * list of elements which consists of all powers of that generator. For a group
+  * with just one generated, it would be enumerated after this.
+  *
+  * \sa enumerate_group_elements
+  */
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename generators
+>
+struct dimino_first_step_elements
+{
+  typedef typename get<0, generators>::type first_generator;
+  typedef typename skip<1, generators>::type next_generators;
+  typedef type_list<first_generator> generators_done;
+
+  typedef dimino_first_step_elements_helper<
+    Multiply,
+    Equality,
+    id,
+    first_generator,
+    first_generator,
+    type_list<id>,
+    false
+  > helper;
+  typedef typename helper::type type;
+  constexpr static int global_flags = helper::global_flags;
+};
+
+/** \internal
+  *
+  * \class dimino_get_coset_elements
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Generate all elements of a specific coset
+  *
+  * This template generates all the elements of a specific coset by
+  * multiplying all elements in the given subgroup with the new
+  * coset representative. Note that the first element of the
+  * subgroup is always the identity element, so the first element of
+  * ther result of this template is going to be the coset
+  * representative itself.
+  *
+  * Note that this template accepts an additional boolean parameter
+  * that specifies whether to actually generate the coset (true) or
+  * just return an empty list (false).
+  *
+  * \sa enumerate_group_elements, dimino_add_cosets_for_rep
+  */
+template<
+  template<typename, typename> class Multiply,
+  typename sub_group_elements,
+  typename new_coset_rep,
+  bool generate_coset      // = true
+>
+struct dimino_get_coset_elements
+{
+  typedef typename apply_op_from_right<Multiply, new_coset_rep, sub_group_elements>::type type;
+};
+
+template<
+  template<typename, typename> class Multiply,
+  typename sub_group_elements,
+  typename new_coset_rep
+>
+struct dimino_get_coset_elements<Multiply, sub_group_elements, new_coset_rep, false>
+{
+  typedef type_list<> type;
+};
+
+/** \internal
+  *
+  * \class dimino_add_cosets_for_rep
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Recursive template for adding coset spaces
+  *
+  * This template multiplies the coset representative with a generator
+  * from the list of previous generators. If the new element is not in
+  * the group already, it adds the corresponding coset. Finally it
+  * proceeds to call itself with the next generator from the list.
+  *
+  * \sa enumerate_group_elements, dimino_add_all_coset_spaces
+  */
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename sub_group_elements,
+  typename elements,
+  typename generators,
+  typename rep_element,
+  int sub_group_size
+>
+struct dimino_add_cosets_for_rep;
+
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename sub_group_elements,
+  typename elements,
+  typename g,
+  typename... gs,
+  typename rep_element,
+  int sub_group_size
+>
+struct dimino_add_cosets_for_rep<Multiply, Equality, id, sub_group_elements, elements, type_list<g, gs...>, rep_element, sub_group_size>
+{
+  typedef typename Multiply<rep_element, g>::type new_coset_rep;
+  typedef contained_in_list_gf<Equality, new_coset_rep, elements> _cil;
+  constexpr static bool add_coset = !_cil::value;
+
+  typedef typename dimino_get_coset_elements<
+    Multiply,
+    sub_group_elements,
+    new_coset_rep,
+    add_coset
+  >::type coset_elements;
+
+  typedef dimino_add_cosets_for_rep<
+    Multiply,
+    Equality,
+    id,
+    sub_group_elements,
+    typename concat<elements, coset_elements>::type,
+    type_list<gs...>,
+    rep_element,
+    sub_group_size
+  > _helper;
+
+  typedef typename _helper::type type;
+  constexpr static int global_flags = _cil::global_flags | _helper::global_flags;
+
+  /* Note that we don't have to update global flags here, since
+   * we will only add these elements if they are not part of
+   * the group already. But that only happens if the coset rep
+   * is not already in the group, so the check for the coset rep
+   * will catch this.
+   */
+};
+
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename sub_group_elements,
+  typename elements
+  EIGEN_TPL_PP_SPEC_HACK_DEFC(typename, empty),
+  typename rep_element,
+  int sub_group_size
+>
+struct dimino_add_cosets_for_rep<Multiply, Equality, id, sub_group_elements, elements, type_list<EIGEN_TPL_PP_SPEC_HACK_USE(empty)>, rep_element, sub_group_size>
+{
+  typedef elements type;
+  constexpr static int global_flags = 0;
+};
+
+/** \internal
+  *
+  * \class dimino_add_all_coset_spaces
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Recursive template for adding all coset spaces for a new generator
+  *
+  * This template tries to go through the list of generators (with
+  * the help of the dimino_add_cosets_for_rep template) as long as
+  * it still finds elements that are not part of the group and add
+  * the corresponding cosets.
+  *
+  * \sa enumerate_group_elements, dimino_add_cosets_for_rep
+  */
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename sub_group_elements,
+  typename elements,
+  typename generators,
+  int sub_group_size,
+  int rep_pos,
+  bool stop_condition        // = false
+>
+struct dimino_add_all_coset_spaces
+{
+  typedef typename get<rep_pos, elements>::type rep_element;
+  typedef dimino_add_cosets_for_rep<
+    Multiply,
+    Equality,
+    id,
+    sub_group_elements,
+    elements,
+    generators,
+    rep_element,
+    sub_group_elements::count
+  > _ac4r;
+  typedef typename _ac4r::type new_elements;
+  
+  constexpr static int new_rep_pos = rep_pos + sub_group_elements::count;
+  constexpr static bool new_stop_condition = new_rep_pos >= new_elements::count;
+
+  typedef dimino_add_all_coset_spaces<
+    Multiply,
+    Equality,
+    id,
+    sub_group_elements,
+    new_elements,
+    generators,
+    sub_group_size,
+    new_rep_pos,
+    new_stop_condition
+  > _helper;
+
+  typedef typename _helper::type type;
+  constexpr static int global_flags = _helper::global_flags | _ac4r::global_flags;
+};
+
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename sub_group_elements,
+  typename elements,
+  typename generators,
+  int sub_group_size,
+  int rep_pos
+>
+struct dimino_add_all_coset_spaces<Multiply, Equality, id, sub_group_elements, elements, generators, sub_group_size, rep_pos, true>
+{
+  typedef elements type;
+  constexpr static int global_flags = 0;
+};
+
+/** \internal
+  *
+  * \class dimino_add_generator
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Enlarge the group by adding a new generator.
+  *
+  * It accepts a boolean parameter that determines if the generator is redundant,
+  * i.e. was already seen in the group. In that case, it reduces to a no-op.
+  *
+  * \sa enumerate_group_elements, dimino_add_all_coset_spaces
+  */
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename elements,
+  typename generators_done,
+  typename current_generator,
+  bool redundant          // = false
+>
+struct dimino_add_generator
+{
+  /* this template is only called if the generator is not redundant
+   * => all elements of the group multiplied with the new generator
+   *    are going to be new elements of the most trivial coset space
+   */
+  typedef typename apply_op_from_right<Multiply, current_generator, elements>::type multiplied_elements;
+  typedef typename concat<elements, multiplied_elements>::type new_elements;
+
+  constexpr static int rep_pos = elements::count;
+
+  typedef dimino_add_all_coset_spaces<
+    Multiply,
+    Equality,
+    id,
+    elements, // elements of previous subgroup
+    new_elements,
+    typename concat<generators_done, type_list<current_generator>>::type,
+    elements::count, // size of previous subgroup
+    rep_pos,
+    false // don't stop (because rep_pos >= new_elements::count is always false at this point)
+  > _helper;
+  typedef typename _helper::type type;
+  constexpr static int global_flags = _helper::global_flags;
+};
+
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename elements,
+  typename generators_done,
+  typename current_generator
+>
+struct dimino_add_generator<Multiply, Equality, id, elements, generators_done, current_generator, true>
+{
+  // redundant case
+  typedef elements type;
+  constexpr static int global_flags = 0;
+};
+
+/** \internal
+  *
+  * \class dimino_add_remaining_generators
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Recursive template that adds all remaining generators to a group
+  *
+  * Loop through the list of generators that remain and successively
+  * add them to the group.
+  *
+  * \sa enumerate_group_elements, dimino_add_generator
+  */
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename generators_done,
+  typename remaining_generators,
+  typename elements
+>
+struct dimino_add_remaining_generators
+{
+  typedef typename get<0, remaining_generators>::type first_generator;
+  typedef typename skip<1, remaining_generators>::type next_generators;
+
+  typedef contained_in_list_gf<Equality, first_generator, elements> _cil;
+
+  typedef dimino_add_generator<
+    Multiply,
+    Equality,
+    id,
+    elements,
+    generators_done,
+    first_generator,
+    _cil::value
+  > _helper;
+
+  typedef typename _helper::type new_elements;
+
+  typedef dimino_add_remaining_generators<
+    Multiply,
+    Equality,
+    id,
+    typename concat<generators_done, type_list<first_generator>>::type,
+    next_generators,
+    new_elements
+  > _next_iter;
+
+  typedef typename _next_iter::type type;
+  constexpr static int global_flags =
+    _cil::global_flags |
+    _helper::global_flags |
+    _next_iter::global_flags;
+};
+
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename generators_done,
+  typename elements
+>
+struct dimino_add_remaining_generators<Multiply, Equality, id, generators_done, type_list<>, elements>
+{
+  typedef elements type;
+  constexpr static int global_flags = 0;
+};
+
+/** \internal
+  *
+  * \class enumerate_group_elements_noid
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Helper template that implements group element enumeration
+  *
+  * This is a helper template that implements the actual enumeration
+  * of group elements. This has been split so that the list of
+  * generators can be cleansed of the identity element before
+  * performing the actual operation.
+  *
+  * \sa enumerate_group_elements
+  */
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename generators,
+  int initial_global_flags = 0
+>
+struct enumerate_group_elements_noid
+{
+  typedef dimino_first_step_elements<Multiply, Equality, id, generators> first_step;
+  typedef typename first_step::type first_step_elements;
+
+  typedef dimino_add_remaining_generators<
+    Multiply,
+    Equality,
+    id,
+    typename first_step::generators_done,
+    typename first_step::next_generators, // remaining_generators
+    typename first_step::type // first_step elements
+  > _helper;
+
+  typedef typename _helper::type type;
+  constexpr static int global_flags =
+    initial_global_flags |
+    first_step::global_flags |
+    _helper::global_flags;
+};
+
+// in case when no generators are specified
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  int initial_global_flags
+>
+struct enumerate_group_elements_noid<Multiply, Equality, id, type_list<>, initial_global_flags>
+{
+  typedef type_list<id> type;
+  constexpr static int global_flags = initial_global_flags;
+};
+
+/** \internal
+  *
+  * \class enumerate_group_elements
+  * \ingroup CXX11_TensorSymmetry_Module
+  *
+  * \brief Enumerate all elements in a finite group
+  *
+  * This template enumerates all elements in a finite group. It accepts
+  * the following template parameters:
+  *
+  * \tparam Multiply      The multiplication operation that multiplies two group elements
+  *                       with each other.
+  * \tparam Equality      The equality check operation that checks if two group elements
+  *                       are equal to another.
+  * \tparam id            The identity element
+  * \tparam _generators   A list of (possibly redundant) generators of the group
+  */
+template<
+  template<typename, typename> class Multiply,
+  template<typename, typename> class Equality,
+  typename id,
+  typename _generators
+>
+struct enumerate_group_elements
+  : public enumerate_group_elements_noid<
+      Multiply,
+      Equality,
+      id,
+      typename strip_identities<Equality, id, _generators>::type,
+      strip_identities<Equality, id, _generators>::global_flags
+    >
+{
+};
+
+} // end namespace group_theory
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSORSYMMETRY_TEMPLATEGROUPTHEORY_H
+
+/*
+ * kate: space-indent on; indent-width 2; mixedindent off; indent-mode cstyle;
+ */

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/EventCount.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/EventCount.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/EventCount.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/EventCount.h
@@ -0,0 +1,233 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Dmitry Vyukov <dvyukov@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_EVENTCOUNT_H_
+#define EIGEN_CXX11_THREADPOOL_EVENTCOUNT_H_
+
+namespace Eigen {
+
+// EventCount allows to wait for arbitrary predicates in non-blocking
+// algorithms. Think of condition variable, but wait predicate does not need to
+// be protected by a mutex. Usage:
+// Waiting thread does:
+//
+//   if (predicate)
+//     return act();
+//   EventCount::Waiter& w = waiters[my_index];
+//   ec.Prewait(&w);
+//   if (predicate) {
+//     ec.CancelWait(&w);
+//     return act();
+//   }
+//   ec.CommitWait(&w);
+//
+// Notifying thread does:
+//
+//   predicate = true;
+//   ec.Notify(true);
+//
+// Notify is cheap if there are no waiting threads. Prewait/CommitWait are not
+// cheap, but they are executed only if the preceeding predicate check has
+// failed.
+//
+// Algorihtm outline:
+// There are two main variables: predicate (managed by user) and state_.
+// Operation closely resembles Dekker mutual algorithm:
+// https://en.wikipedia.org/wiki/Dekker%27s_algorithm
+// Waiting thread sets state_ then checks predicate, Notifying thread sets
+// predicate then checks state_. Due to seq_cst fences in between these
+// operations it is guaranteed than either waiter will see predicate change
+// and won't block, or notifying thread will see state_ change and will unblock
+// the waiter, or both. But it can't happen that both threads don't see each
+// other changes, which would lead to deadlock.
+class EventCount {
+ public:
+  class Waiter;
+
+  EventCount(MaxSizeVector<Waiter>& waiters) : waiters_(waiters) {
+    eigen_assert(waiters.size() < (1 << kWaiterBits) - 1);
+    // Initialize epoch to something close to overflow to test overflow.
+    state_ = kStackMask | (kEpochMask - kEpochInc * waiters.size() * 2);
+  }
+
+  ~EventCount() {
+    // Ensure there are no waiters.
+    eigen_assert((state_.load() & (kStackMask | kWaiterMask)) == kStackMask);
+  }
+
+  // Prewait prepares for waiting.
+  // After calling this function the thread must re-check the wait predicate
+  // and call either CancelWait or CommitWait passing the same Waiter object.
+  void Prewait(Waiter* w) {
+    w->epoch = state_.fetch_add(kWaiterInc, std::memory_order_relaxed);
+    std::atomic_thread_fence(std::memory_order_seq_cst);
+  }
+
+  // CommitWait commits waiting.
+  void CommitWait(Waiter* w) {
+    w->state = Waiter::kNotSignaled;
+    // Modification epoch of this waiter.
+    uint64_t epoch =
+        (w->epoch & kEpochMask) +
+        (((w->epoch & kWaiterMask) >> kWaiterShift) << kEpochShift);
+    uint64_t state = state_.load(std::memory_order_seq_cst);
+    for (;;) {
+      if (int64_t((state & kEpochMask) - epoch) < 0) {
+        // The preceeding waiter has not decided on its fate. Wait until it
+        // calls either CancelWait or CommitWait, or is notified.
+        EIGEN_THREAD_YIELD();
+        state = state_.load(std::memory_order_seq_cst);
+        continue;
+      }
+      // We've already been notified.
+      if (int64_t((state & kEpochMask) - epoch) > 0) return;
+      // Remove this thread from prewait counter and add it to the waiter list.
+      eigen_assert((state & kWaiterMask) != 0);
+      uint64_t newstate = state - kWaiterInc + kEpochInc;
+      newstate = (newstate & ~kStackMask) | (w - &waiters_[0]);
+      if ((state & kStackMask) == kStackMask)
+        w->next.store(nullptr, std::memory_order_relaxed);
+      else
+        w->next.store(&waiters_[state & kStackMask], std::memory_order_relaxed);
+      if (state_.compare_exchange_weak(state, newstate,
+                                       std::memory_order_release))
+        break;
+    }
+    Park(w);
+  }
+
+  // CancelWait cancels effects of the previous Prewait call.
+  void CancelWait(Waiter* w) {
+    uint64_t epoch =
+        (w->epoch & kEpochMask) +
+        (((w->epoch & kWaiterMask) >> kWaiterShift) << kEpochShift);
+    uint64_t state = state_.load(std::memory_order_relaxed);
+    for (;;) {
+      if (int64_t((state & kEpochMask) - epoch) < 0) {
+        // The preceeding waiter has not decided on its fate. Wait until it
+        // calls either CancelWait or CommitWait, or is notified.
+        EIGEN_THREAD_YIELD();
+        state = state_.load(std::memory_order_relaxed);
+        continue;
+      }
+      // We've already been notified.
+      if (int64_t((state & kEpochMask) - epoch) > 0) return;
+      // Remove this thread from prewait counter.
+      eigen_assert((state & kWaiterMask) != 0);
+      if (state_.compare_exchange_weak(state, state - kWaiterInc + kEpochInc,
+                                       std::memory_order_relaxed))
+        return;
+    }
+  }
+
+  // Notify wakes one or all waiting threads.
+  // Must be called after changing the associated wait predicate.
+  void Notify(bool all) {
+    std::atomic_thread_fence(std::memory_order_seq_cst);
+    uint64_t state = state_.load(std::memory_order_acquire);
+    for (;;) {
+      // Easy case: no waiters.
+      if ((state & kStackMask) == kStackMask && (state & kWaiterMask) == 0)
+        return;
+      uint64_t waiters = (state & kWaiterMask) >> kWaiterShift;
+      uint64_t newstate;
+      if (all) {
+        // Reset prewait counter and empty wait list.
+        newstate = (state & kEpochMask) + (kEpochInc * waiters) + kStackMask;
+      } else if (waiters) {
+        // There is a thread in pre-wait state, unblock it.
+        newstate = state + kEpochInc - kWaiterInc;
+      } else {
+        // Pop a waiter from list and unpark it.
+        Waiter* w = &waiters_[state & kStackMask];
+        Waiter* wnext = w->next.load(std::memory_order_relaxed);
+        uint64_t next = kStackMask;
+        if (wnext != nullptr) next = wnext - &waiters_[0];
+        // Note: we don't add kEpochInc here. ABA problem on the lock-free stack
+        // can't happen because a waiter is re-pushed onto the stack only after
+        // it was in the pre-wait state which inevitably leads to epoch
+        // increment.
+        newstate = (state & kEpochMask) + next;
+      }
+      if (state_.compare_exchange_weak(state, newstate,
+                                       std::memory_order_acquire)) {
+        if (!all && waiters) return;  // unblocked pre-wait thread
+        if ((state & kStackMask) == kStackMask) return;
+        Waiter* w = &waiters_[state & kStackMask];
+        if (!all) w->next.store(nullptr, std::memory_order_relaxed);
+        Unpark(w);
+        return;
+      }
+    }
+  }
+
+  class Waiter {
+    friend class EventCount;
+    // Align to 128 byte boundary to prevent false sharing with other Waiter objects in the same vector.
+    EIGEN_ALIGN_TO_BOUNDARY(128) std::atomic<Waiter*> next;
+    std::mutex mu;
+    std::condition_variable cv;
+    uint64_t epoch;
+    unsigned state;
+    enum {
+      kNotSignaled,
+      kWaiting,
+      kSignaled,
+    };
+  };
+
+ private:
+  // State_ layout:
+  // - low kStackBits is a stack of waiters committed wait.
+  // - next kWaiterBits is count of waiters in prewait state.
+  // - next kEpochBits is modification counter.
+  static const uint64_t kStackBits = 16;
+  static const uint64_t kStackMask = (1ull << kStackBits) - 1;
+  static const uint64_t kWaiterBits = 16;
+  static const uint64_t kWaiterShift = 16;
+  static const uint64_t kWaiterMask = ((1ull << kWaiterBits) - 1)
+                                      << kWaiterShift;
+  static const uint64_t kWaiterInc = 1ull << kWaiterBits;
+  static const uint64_t kEpochBits = 32;
+  static const uint64_t kEpochShift = 32;
+  static const uint64_t kEpochMask = ((1ull << kEpochBits) - 1) << kEpochShift;
+  static const uint64_t kEpochInc = 1ull << kEpochShift;
+  std::atomic<uint64_t> state_;
+  MaxSizeVector<Waiter>& waiters_;
+
+  void Park(Waiter* w) {
+    std::unique_lock<std::mutex> lock(w->mu);
+    while (w->state != Waiter::kSignaled) {
+      w->state = Waiter::kWaiting;
+      w->cv.wait(lock);
+    }
+  }
+
+  void Unpark(Waiter* waiters) {
+    Waiter* next = nullptr;
+    for (Waiter* w = waiters; w; w = next) {
+      next = w->next.load(std::memory_order_relaxed);
+      unsigned state;
+      {
+        std::unique_lock<std::mutex> lock(w->mu);
+        state = w->state;
+        w->state = Waiter::kSignaled;
+      }
+      // Avoid notifying if it wasn't waiting.
+      if (state == Waiter::kWaiting) w->cv.notify_one();
+    }
+  }
+
+  EventCount(const EventCount&) = delete;
+  void operator=(const EventCount&) = delete;
+};
+
+}  // namespace Eigen
+
+#endif  // EIGEN_CXX11_THREADPOOL_EVENTCOUNT_H_

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/NonBlockingThreadPool.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/NonBlockingThreadPool.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/NonBlockingThreadPool.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/NonBlockingThreadPool.h
@@ -0,0 +1,274 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Dmitry Vyukov <dvyukov@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_NONBLOCKING_THREAD_POOL_H
+#define EIGEN_CXX11_THREADPOOL_NONBLOCKING_THREAD_POOL_H
+
+
+namespace Eigen {
+
+template <typename Environment>
+class NonBlockingThreadPoolTempl : public Eigen::ThreadPoolInterface {
+ public:
+  typedef typename Environment::Task Task;
+  typedef RunQueue<Task, 1024> Queue;
+
+  NonBlockingThreadPoolTempl(int num_threads, Environment env = Environment())
+      : env_(env),
+        threads_(num_threads),
+        queues_(num_threads),
+        coprimes_(num_threads),
+        waiters_(num_threads),
+        blocked_(0),
+        spinning_(0),
+        done_(false),
+        ec_(waiters_) {
+    waiters_.resize(num_threads);
+
+    // Calculate coprimes of num_threads.
+    // Coprimes are used for a random walk over all threads in Steal
+    // and NonEmptyQueueIndex. Iteration is based on the fact that if we take
+    // a walk starting thread index t and calculate num_threads - 1 subsequent
+    // indices as (t + coprime) % num_threads, we will cover all threads without
+    // repetitions (effectively getting a presudo-random permutation of thread
+    // indices).
+    for (int i = 1; i <= num_threads; i++) {
+      unsigned a = i;
+      unsigned b = num_threads;
+      // If GCD(a, b) == 1, then a and b are coprimes.
+      while (b != 0) {
+        unsigned tmp = a;
+        a = b;
+        b = tmp % b;
+      }
+      if (a == 1) {
+        coprimes_.push_back(i);
+      }
+    }
+    for (int i = 0; i < num_threads; i++) {
+      queues_.push_back(new Queue());
+    }
+    for (int i = 0; i < num_threads; i++) {
+      threads_.push_back(env_.CreateThread([this, i]() { WorkerLoop(i); }));
+    }
+  }
+
+  ~NonBlockingThreadPoolTempl() {
+    done_ = true;
+    // Now if all threads block without work, they will start exiting.
+    // But note that threads can continue to work arbitrary long,
+    // block, submit new work, unblock and otherwise live full life.
+    ec_.Notify(true);
+
+    // Join threads explicitly to avoid destruction order issues.
+    for (size_t i = 0; i < threads_.size(); i++) delete threads_[i];
+    for (size_t i = 0; i < threads_.size(); i++) delete queues_[i];
+  }
+
+  void Schedule(std::function<void()> fn) {
+    Task t = env_.CreateTask(std::move(fn));
+    PerThread* pt = GetPerThread();
+    if (pt->pool == this) {
+      // Worker thread of this pool, push onto the thread's queue.
+      Queue* q = queues_[pt->thread_id];
+      t = q->PushFront(std::move(t));
+    } else {
+      // A free-standing thread (or worker of another pool), push onto a random
+      // queue.
+      Queue* q = queues_[Rand(&pt->rand) % queues_.size()];
+      t = q->PushBack(std::move(t));
+    }
+    // Note: below we touch this after making w available to worker threads.
+    // Strictly speaking, this can lead to a racy-use-after-free. Consider that
+    // Schedule is called from a thread that is neither main thread nor a worker
+    // thread of this pool. Then, execution of w directly or indirectly
+    // completes overall computations, which in turn leads to destruction of
+    // this. We expect that such scenario is prevented by program, that is,
+    // this is kept alive while any threads can potentially be in Schedule.
+    if (!t.f)
+      ec_.Notify(false);
+    else
+      env_.ExecuteTask(t);  // Push failed, execute directly.
+  }
+
+  int NumThreads() const final {
+    return static_cast<int>(threads_.size());
+  }
+
+  int CurrentThreadId() const final {
+    const PerThread* pt =
+        const_cast<NonBlockingThreadPoolTempl*>(this)->GetPerThread();
+    if (pt->pool == this) {
+      return pt->thread_id;
+    } else {
+      return -1;
+    }
+  }
+
+ private:
+  typedef typename Environment::EnvThread Thread;
+
+  struct PerThread {
+    constexpr PerThread() : pool(NULL), rand(0), thread_id(-1) { }
+    NonBlockingThreadPoolTempl* pool;  // Parent pool, or null for normal threads.
+    uint64_t rand;  // Random generator state.
+    int thread_id;  // Worker thread index in pool.
+  };
+
+  Environment env_;
+  MaxSizeVector<Thread*> threads_;
+  MaxSizeVector<Queue*> queues_;
+  MaxSizeVector<unsigned> coprimes_;
+  MaxSizeVector<EventCount::Waiter> waiters_;
+  std::atomic<unsigned> blocked_;
+  std::atomic<bool> spinning_;
+  std::atomic<bool> done_;
+  EventCount ec_;
+
+  // Main worker thread loop.
+  void WorkerLoop(int thread_id) {
+    PerThread* pt = GetPerThread();
+    pt->pool = this;
+    pt->rand = std::hash<std::thread::id>()(std::this_thread::get_id());
+    pt->thread_id = thread_id;
+    Queue* q = queues_[thread_id];
+    EventCount::Waiter* waiter = &waiters_[thread_id];
+    for (;;) {
+      Task t = q->PopFront();
+      if (!t.f) {
+        t = Steal();
+        if (!t.f) {
+          // Leave one thread spinning. This reduces latency.
+          // TODO(dvyukov): 1000 iterations is based on fair dice roll, tune it.
+          // Also, the time it takes to attempt to steal work 1000 times depends
+          // on the size of the thread pool. However the speed at which the user
+          // of the thread pool submit tasks is independent of the size of the
+          // pool. Consider a time based limit instead.
+          if (!spinning_ && !spinning_.exchange(true)) {
+            for (int i = 0; i < 1000 && !t.f; i++) {
+              t = Steal();
+            }
+            spinning_ = false;
+          }
+          if (!t.f) {
+            if (!WaitForWork(waiter, &t)) {
+              return;
+            }
+          }
+        }
+      }
+      if (t.f) {
+        env_.ExecuteTask(t);
+      }
+    }
+  }
+
+  // Steal tries to steal work from other worker threads in best-effort manner.
+  Task Steal() {
+    PerThread* pt = GetPerThread();
+    const size_t size = queues_.size();
+    unsigned r = Rand(&pt->rand);
+    unsigned inc = coprimes_[r % coprimes_.size()];
+    unsigned victim = r % size;
+    for (unsigned i = 0; i < size; i++) {
+      Task t = queues_[victim]->PopBack();
+      if (t.f) {
+        return t;
+      }
+      victim += inc;
+      if (victim >= size) {
+        victim -= size;
+      }
+    }
+    return Task();
+  }
+
+  // WaitForWork blocks until new work is available (returns true), or if it is
+  // time to exit (returns false). Can optionally return a task to execute in t
+  // (in such case t.f != nullptr on return).
+  bool WaitForWork(EventCount::Waiter* waiter, Task* t) {
+    eigen_assert(!t->f);
+    // We already did best-effort emptiness check in Steal, so prepare for
+    // blocking.
+    ec_.Prewait(waiter);
+    // Now do a reliable emptiness check.
+    int victim = NonEmptyQueueIndex();
+    if (victim != -1) {
+      ec_.CancelWait(waiter);
+      *t = queues_[victim]->PopBack();
+      return true;
+    }
+    // Number of blocked threads is used as termination condition.
+    // If we are shutting down and all worker threads blocked without work,
+    // that's we are done.
+    blocked_++;
+    if (done_ && blocked_ == threads_.size()) {
+      ec_.CancelWait(waiter);
+      // Almost done, but need to re-check queues.
+      // Consider that all queues are empty and all worker threads are preempted
+      // right after incrementing blocked_ above. Now a free-standing thread
+      // submits work and calls destructor (which sets done_). If we don't
+      // re-check queues, we will exit leaving the work unexecuted.
+      if (NonEmptyQueueIndex() != -1) {
+        // Note: we must not pop from queues before we decrement blocked_,
+        // otherwise the following scenario is possible. Consider that instead
+        // of checking for emptiness we popped the only element from queues.
+        // Now other worker threads can start exiting, which is bad if the
+        // work item submits other work. So we just check emptiness here,
+        // which ensures that all worker threads exit at the same time.
+        blocked_--;
+        return true;
+      }
+      // Reached stable termination state.
+      ec_.Notify(true);
+      return false;
+    }
+    ec_.CommitWait(waiter);
+    blocked_--;
+    return true;
+  }
+
+  int NonEmptyQueueIndex() {
+    PerThread* pt = GetPerThread();
+    const size_t size = queues_.size();
+    unsigned r = Rand(&pt->rand);
+    unsigned inc = coprimes_[r % coprimes_.size()];
+    unsigned victim = r % size;
+    for (unsigned i = 0; i < size; i++) {
+      if (!queues_[victim]->Empty()) {
+        return victim;
+      }
+      victim += inc;
+      if (victim >= size) {
+        victim -= size;
+      }
+    }
+    return -1;
+  }
+
+  static EIGEN_STRONG_INLINE PerThread* GetPerThread() {
+    EIGEN_THREAD_LOCAL PerThread per_thread_;
+    PerThread* pt = &per_thread_;
+    return pt;
+  }
+
+  static EIGEN_STRONG_INLINE unsigned Rand(uint64_t* state) {
+    uint64_t current = *state;
+    // Update the internal state
+    *state = current * 6364136223846793005ULL + 0xda3e39cb94b95bdbULL;
+    // Generate the random output (using the PCG-XSH-RS scheme)
+    return static_cast<unsigned>((current ^ (current >> 22)) >> (22 + (current >> 61)));
+  }
+};
+
+typedef NonBlockingThreadPoolTempl<StlThreadEnvironment> NonBlockingThreadPool;
+
+}  // namespace Eigen
+
+#endif  // EIGEN_CXX11_THREADPOOL_NONBLOCKING_THREAD_POOL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/RunQueue.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/RunQueue.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/RunQueue.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/RunQueue.h
@@ -0,0 +1,210 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Dmitry Vyukov <dvyukov@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_RUNQUEUE_H_
+#define EIGEN_CXX11_THREADPOOL_RUNQUEUE_H_
+
+
+namespace Eigen {
+
+// RunQueue is a fixed-size, partially non-blocking deque or Work items.
+// Operations on front of the queue must be done by a single thread (owner),
+// operations on back of the queue can be done by multiple threads concurrently.
+//
+// Algorithm outline:
+// All remote threads operating on the queue back are serialized by a mutex.
+// This ensures that at most two threads access state: owner and one remote
+// thread (Size aside). The algorithm ensures that the occupied region of the
+// underlying array is logically continuous (can wraparound, but no stray
+// occupied elements). Owner operates on one end of this region, remote thread
+// operates on the other end. Synchronization between these threads
+// (potential consumption of the last element and take up of the last empty
+// element) happens by means of state variable in each element. States are:
+// empty, busy (in process of insertion of removal) and ready. Threads claim
+// elements (empty->busy and ready->busy transitions) by means of a CAS
+// operation. The finishing transition (busy->empty and busy->ready) are done
+// with plain store as the element is exclusively owned by the current thread.
+//
+// Note: we could permit only pointers as elements, then we would not need
+// separate state variable as null/non-null pointer value would serve as state,
+// but that would require malloc/free per operation for large, complex values
+// (and this is designed to store std::function<()>).
+template <typename Work, unsigned kSize>
+class RunQueue {
+ public:
+  RunQueue() : front_(0), back_(0) {
+    // require power-of-two for fast masking
+    eigen_assert((kSize & (kSize - 1)) == 0);
+    eigen_assert(kSize > 2);            // why would you do this?
+    eigen_assert(kSize <= (64 << 10));  // leave enough space for counter
+    for (unsigned i = 0; i < kSize; i++)
+      array_[i].state.store(kEmpty, std::memory_order_relaxed);
+  }
+
+  ~RunQueue() { eigen_assert(Size() == 0); }
+
+  // PushFront inserts w at the beginning of the queue.
+  // If queue is full returns w, otherwise returns default-constructed Work.
+  Work PushFront(Work w) {
+    unsigned front = front_.load(std::memory_order_relaxed);
+    Elem* e = &array_[front & kMask];
+    uint8_t s = e->state.load(std::memory_order_relaxed);
+    if (s != kEmpty ||
+        !e->state.compare_exchange_strong(s, kBusy, std::memory_order_acquire))
+      return w;
+    front_.store(front + 1 + (kSize << 1), std::memory_order_relaxed);
+    e->w = std::move(w);
+    e->state.store(kReady, std::memory_order_release);
+    return Work();
+  }
+
+  // PopFront removes and returns the first element in the queue.
+  // If the queue was empty returns default-constructed Work.
+  Work PopFront() {
+    unsigned front = front_.load(std::memory_order_relaxed);
+    Elem* e = &array_[(front - 1) & kMask];
+    uint8_t s = e->state.load(std::memory_order_relaxed);
+    if (s != kReady ||
+        !e->state.compare_exchange_strong(s, kBusy, std::memory_order_acquire))
+      return Work();
+    Work w = std::move(e->w);
+    e->state.store(kEmpty, std::memory_order_release);
+    front = ((front - 1) & kMask2) | (front & ~kMask2);
+    front_.store(front, std::memory_order_relaxed);
+    return w;
+  }
+
+  // PushBack adds w at the end of the queue.
+  // If queue is full returns w, otherwise returns default-constructed Work.
+  Work PushBack(Work w) {
+    std::unique_lock<std::mutex> lock(mutex_);
+    unsigned back = back_.load(std::memory_order_relaxed);
+    Elem* e = &array_[(back - 1) & kMask];
+    uint8_t s = e->state.load(std::memory_order_relaxed);
+    if (s != kEmpty ||
+        !e->state.compare_exchange_strong(s, kBusy, std::memory_order_acquire))
+      return w;
+    back = ((back - 1) & kMask2) | (back & ~kMask2);
+    back_.store(back, std::memory_order_relaxed);
+    e->w = std::move(w);
+    e->state.store(kReady, std::memory_order_release);
+    return Work();
+  }
+
+  // PopBack removes and returns the last elements in the queue.
+  // Can fail spuriously.
+  Work PopBack() {
+    if (Empty()) return Work();
+    std::unique_lock<std::mutex> lock(mutex_, std::try_to_lock);
+    if (!lock) return Work();
+    unsigned back = back_.load(std::memory_order_relaxed);
+    Elem* e = &array_[back & kMask];
+    uint8_t s = e->state.load(std::memory_order_relaxed);
+    if (s != kReady ||
+        !e->state.compare_exchange_strong(s, kBusy, std::memory_order_acquire))
+      return Work();
+    Work w = std::move(e->w);
+    e->state.store(kEmpty, std::memory_order_release);
+    back_.store(back + 1 + (kSize << 1), std::memory_order_relaxed);
+    return w;
+  }
+
+  // PopBackHalf removes and returns half last elements in the queue.
+  // Returns number of elements removed. But can also fail spuriously.
+  unsigned PopBackHalf(std::vector<Work>* result) {
+    if (Empty()) return 0;
+    std::unique_lock<std::mutex> lock(mutex_, std::try_to_lock);
+    if (!lock) return 0;
+    unsigned back = back_.load(std::memory_order_relaxed);
+    unsigned size = Size();
+    unsigned mid = back;
+    if (size > 1) mid = back + (size - 1) / 2;
+    unsigned n = 0;
+    unsigned start = 0;
+    for (; static_cast<int>(mid - back) >= 0; mid--) {
+      Elem* e = &array_[mid & kMask];
+      uint8_t s = e->state.load(std::memory_order_relaxed);
+      if (n == 0) {
+        if (s != kReady ||
+            !e->state.compare_exchange_strong(s, kBusy,
+                                              std::memory_order_acquire))
+          continue;
+        start = mid;
+      } else {
+        // Note: no need to store temporal kBusy, we exclusively own these
+        // elements.
+        eigen_assert(s == kReady);
+      }
+      result->push_back(std::move(e->w));
+      e->state.store(kEmpty, std::memory_order_release);
+      n++;
+    }
+    if (n != 0)
+      back_.store(start + 1 + (kSize << 1), std::memory_order_relaxed);
+    return n;
+  }
+
+  // Size returns current queue size.
+  // Can be called by any thread at any time.
+  unsigned Size() const {
+    // Emptiness plays critical role in thread pool blocking. So we go to great
+    // effort to not produce false positives (claim non-empty queue as empty).
+    for (;;) {
+      // Capture a consistent snapshot of front/tail.
+      unsigned front = front_.load(std::memory_order_acquire);
+      unsigned back = back_.load(std::memory_order_acquire);
+      unsigned front1 = front_.load(std::memory_order_relaxed);
+      if (front != front1) continue;
+      int size = (front & kMask2) - (back & kMask2);
+      // Fix overflow.
+      if (size < 0) size += 2 * kSize;
+      // Order of modification in push/pop is crafted to make the queue look
+      // larger than it is during concurrent modifications. E.g. pop can
+      // decrement size before the corresponding push has incremented it.
+      // So the computed size can be up to kSize + 1, fix it.
+      if (size > static_cast<int>(kSize)) size = kSize;
+      return size;
+    }
+  }
+
+  // Empty tests whether container is empty.
+  // Can be called by any thread at any time.
+  bool Empty() const { return Size() == 0; }
+
+ private:
+  static const unsigned kMask = kSize - 1;
+  static const unsigned kMask2 = (kSize << 1) - 1;
+  struct Elem {
+    std::atomic<uint8_t> state;
+    Work w;
+  };
+  enum {
+    kEmpty,
+    kBusy,
+    kReady,
+  };
+  std::mutex mutex_;
+  // Low log(kSize) + 1 bits in front_ and back_ contain rolling index of
+  // front/back, repsectively. The remaining bits contain modification counters
+  // that are incremented on Push operations. This allows us to (1) distinguish
+  // between empty and full conditions (if we would use log(kSize) bits for
+  // position, these conditions would be indistinguishable); (2) obtain
+  // consistent snapshot of front_/back_ for Size operation using the
+  // modification counters.
+  std::atomic<unsigned> front_;
+  std::atomic<unsigned> back_;
+  Elem array_[kSize];
+
+  RunQueue(const RunQueue&) = delete;
+  void operator=(const RunQueue&) = delete;
+};
+
+}  // namespace Eigen
+
+#endif  // EIGEN_CXX11_THREADPOOL_RUNQUEUE_H_

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/SimpleThreadPool.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/SimpleThreadPool.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/SimpleThreadPool.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/SimpleThreadPool.h
@@ -0,0 +1,154 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_SIMPLE_THREAD_POOL_H
+#define EIGEN_CXX11_THREADPOOL_SIMPLE_THREAD_POOL_H
+
+namespace Eigen {
+
+// The implementation of the ThreadPool type ensures that the Schedule method
+// runs the functions it is provided in FIFO order when the scheduling is done
+// by a single thread.
+// Environment provides a way to create threads and also allows to intercept
+// task submission and execution.
+template <typename Environment>
+class SimpleThreadPoolTempl : public ThreadPoolInterface {
+ public:
+  // Construct a pool that contains "num_threads" threads.
+  explicit SimpleThreadPoolTempl(int num_threads, Environment env = Environment())
+      : env_(env), threads_(num_threads), waiters_(num_threads) {
+    for (int i = 0; i < num_threads; i++) {
+      threads_.push_back(env.CreateThread([this, i]() { WorkerLoop(i); }));
+    }
+  }
+
+  // Wait until all scheduled work has finished and then destroy the
+  // set of threads.
+  ~SimpleThreadPoolTempl() {
+    {
+      // Wait for all work to get done.
+      std::unique_lock<std::mutex> l(mu_);
+      while (!pending_.empty()) {
+        empty_.wait(l);
+      }
+      exiting_ = true;
+
+      // Wakeup all waiters.
+      for (auto w : waiters_) {
+        w->ready = true;
+        w->task.f = nullptr;
+        w->cv.notify_one();
+      }
+    }
+
+    // Wait for threads to finish.
+    for (auto t : threads_) {
+      delete t;
+    }
+  }
+
+  // Schedule fn() for execution in the pool of threads. The functions are
+  // executed in the order in which they are scheduled.
+  void Schedule(std::function<void()> fn) final {
+    Task t = env_.CreateTask(std::move(fn));
+    std::unique_lock<std::mutex> l(mu_);
+    if (waiters_.empty()) {
+      pending_.push_back(std::move(t));
+    } else {
+      Waiter* w = waiters_.back();
+      waiters_.pop_back();
+      w->ready = true;
+      w->task = std::move(t);
+      w->cv.notify_one();
+    }
+  }
+
+  int NumThreads() const final {
+    return static_cast<int>(threads_.size());
+  }
+
+  int CurrentThreadId() const final {
+    const PerThread* pt = this->GetPerThread();
+    if (pt->pool == this) {
+      return pt->thread_id;
+    } else {
+      return -1;
+    }
+  }
+
+ protected:
+  void WorkerLoop(int thread_id) {
+    std::unique_lock<std::mutex> l(mu_);
+    PerThread* pt = GetPerThread();
+    pt->pool = this;
+    pt->thread_id = thread_id;
+    Waiter w;
+    Task t;
+    while (!exiting_) {
+      if (pending_.empty()) {
+        // Wait for work to be assigned to me
+        w.ready = false;
+        waiters_.push_back(&w);
+        while (!w.ready) {
+          w.cv.wait(l);
+        }
+        t = w.task;
+        w.task.f = nullptr;
+      } else {
+        // Pick up pending work
+        t = std::move(pending_.front());
+        pending_.pop_front();
+        if (pending_.empty()) {
+          empty_.notify_all();
+        }
+      }
+      if (t.f) {
+        mu_.unlock();
+        env_.ExecuteTask(t);
+        t.f = nullptr;
+        mu_.lock();
+      }
+    }
+  }
+
+ private:
+  typedef typename Environment::Task Task;
+  typedef typename Environment::EnvThread Thread;
+
+  struct Waiter {
+    std::condition_variable cv;
+    Task task;
+    bool ready;
+  };
+
+  struct PerThread {
+    constexpr PerThread() : pool(NULL), thread_id(-1) { }
+    SimpleThreadPoolTempl* pool;  // Parent pool, or null for normal threads.
+    int thread_id;                // Worker thread index in pool.
+  };
+
+  Environment env_;
+  std::mutex mu_;
+  MaxSizeVector<Thread*> threads_;  // All threads
+  MaxSizeVector<Waiter*> waiters_;  // Stack of waiting threads.
+  std::deque<Task> pending_;        // Queue of pending work
+  std::condition_variable empty_;   // Signaled on pending_.empty()
+  bool exiting_ = false;
+
+  PerThread* GetPerThread() const {
+    EIGEN_THREAD_LOCAL PerThread per_thread;
+    return &per_thread;
+  }
+};
+
+typedef SimpleThreadPoolTempl<StlThreadEnvironment> SimpleThreadPool;
+
+}  // namespace Eigen
+
+#endif  // EIGEN_CXX11_THREADPOOL_SIMPLE_THREAD_POOL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadEnvironment.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadEnvironment.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadEnvironment.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadEnvironment.h
@@ -0,0 +1,38 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_THREAD_ENVIRONMENT_H
+#define EIGEN_CXX11_THREADPOOL_THREAD_ENVIRONMENT_H
+
+namespace Eigen {
+
+struct StlThreadEnvironment {
+  struct Task {
+    std::function<void()> f;
+  };
+
+  // EnvThread constructor must start the thread,
+  // destructor must join the thread.
+  class EnvThread {
+   public:
+    EnvThread(std::function<void()> f) : thr_(std::move(f)) {}
+    ~EnvThread() { thr_.join(); }
+
+   private:
+    std::thread thr_;
+  };
+
+  EnvThread* CreateThread(std::function<void()> f) { return new EnvThread(std::move(f)); }
+  Task CreateTask(std::function<void()> f) { return Task{std::move(f)}; }
+  void ExecuteTask(const Task& t) { t.f(); }
+};
+
+}  // namespace Eigen
+
+#endif  // EIGEN_CXX11_THREADPOOL_THREAD_ENVIRONMENT_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadLocal.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadLocal.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadLocal.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadLocal.h
@@ -0,0 +1,22 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_THREAD_LOCAL_H
+#define EIGEN_CXX11_THREADPOOL_THREAD_LOCAL_H
+
+// Try to come up with a portable implementation of thread local variables
+#if EIGEN_COMP_GNUC && EIGEN_GNUC_AT_MOST(4, 7)
+#define EIGEN_THREAD_LOCAL static __thread
+#elif EIGEN_COMP_CLANG
+#define EIGEN_THREAD_LOCAL static __thread
+#else
+#define EIGEN_THREAD_LOCAL static thread_local
+#endif
+
+#endif  // EIGEN_CXX11_THREADPOOL_THREAD_LOCAL_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadPoolInterface.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadPoolInterface.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadPoolInterface.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadPoolInterface.h
@@ -0,0 +1,33 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_THREAD_POOL_INTERFACE_H
+#define EIGEN_CXX11_THREADPOOL_THREAD_POOL_INTERFACE_H
+
+namespace Eigen {
+
+// This defines an interface that ThreadPoolDevice can take to use
+// custom thread pools underneath.
+class ThreadPoolInterface {
+ public:
+  virtual void Schedule(std::function<void()> fn) = 0;
+
+  // Returns the number of threads in the pool.
+  virtual int NumThreads() const = 0;
+
+  // Returns a logical thread index between 0 and NumThreads() - 1 if called
+  // from one of the threads in the pool. Returns -1 otherwise.
+  virtual int CurrentThreadId() const = 0;
+
+  virtual ~ThreadPoolInterface() {}
+};
+
+}  // namespace Eigen
+
+#endif  // EIGEN_CXX11_THREADPOOL_THREAD_POOL_INTERFACE_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadYield.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadYield.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadYield.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/ThreadPool/ThreadYield.h
@@ -0,0 +1,20 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_THREADPOOL_THREAD_YIELD_H
+#define EIGEN_CXX11_THREADPOOL_THREAD_YIELD_H
+
+// Try to come up with a portable way to yield
+#if EIGEN_COMP_GNUC && EIGEN_GNUC_AT_MOST(4, 7)
+#define EIGEN_THREAD_YIELD() sched_yield()
+#else
+#define EIGEN_THREAD_YIELD() std::this_thread::yield()
+#endif
+
+#endif  // EIGEN_CXX11_THREADPOOL_THREAD_YIELD_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/util/CXX11Meta.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/CXX11Meta.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/CXX11Meta.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/CXX11Meta.h
@@ -0,0 +1,542 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11META_H
+#define EIGEN_CXX11META_H
+
+#include <vector>
+#include "EmulateArray.h"
+
+// Emulate the cxx11 functionality that we need if the compiler doesn't support it.
+// Visual studio 2015 doesn't advertise itself as cxx11 compliant, although it
+// supports enough of the standard for our needs
+#if __cplusplus > 199711L || EIGEN_COMP_MSVC >= 1900
+
+#include "CXX11Workarounds.h"
+
+namespace Eigen {
+
+namespace internal {
+
+/** \internal
+  * \file CXX11/util/CXX11Meta.h
+  * This file contains generic metaprogramming classes which are not specifically related to Eigen.
+  * This file expands upon Core/util/Meta.h and adds support for C++11 specific features.
+  */
+
+template<typename... tt>
+struct type_list { constexpr static int count = sizeof...(tt); };
+
+template<typename t, typename... tt>
+struct type_list<t, tt...> { constexpr static int count = sizeof...(tt) + 1; typedef t first_type; };
+
+template<typename T, T... nn>
+struct numeric_list { constexpr static std::size_t count = sizeof...(nn); };
+
+template<typename T, T n, T... nn>
+struct numeric_list<T, n, nn...> { constexpr static std::size_t count = sizeof...(nn) + 1; constexpr static T first_value = n; };
+
+/* numeric list constructors
+ *
+ * equivalencies:
+ *     constructor                                              result
+ *     typename gen_numeric_list<int, 5>::type                  numeric_list<int, 0,1,2,3,4>
+ *     typename gen_numeric_list_reversed<int, 5>::type         numeric_list<int, 4,3,2,1,0>
+ *     typename gen_numeric_list_swapped_pair<int, 5,1,2>::type numeric_list<int, 0,2,1,3,4>
+ *     typename gen_numeric_list_repeated<int, 0, 5>::type      numeric_list<int, 0,0,0,0,0>
+ */
+
+template<typename T, std::size_t n, T start = 0, T... ii> struct gen_numeric_list                     : gen_numeric_list<T, n-1, start, start + n-1, ii...> {};
+template<typename T, T start, T... ii>                    struct gen_numeric_list<T, 0, start, ii...> { typedef numeric_list<T, ii...> type; };
+
+template<typename T, std::size_t n, T start = 0, T... ii> struct gen_numeric_list_reversed                     : gen_numeric_list_reversed<T, n-1, start, ii..., start + n-1> {};
+template<typename T, T start, T... ii>                    struct gen_numeric_list_reversed<T, 0, start, ii...> { typedef numeric_list<T, ii...> type; };
+
+template<typename T, std::size_t n, T a, T b, T start = 0, T... ii> struct gen_numeric_list_swapped_pair                           : gen_numeric_list_swapped_pair<T, n-1, a, b, start, (start + n-1) == a ? b : ((start + n-1) == b ? a : (start + n-1)), ii...> {};
+template<typename T, T a, T b, T start, T... ii>                    struct gen_numeric_list_swapped_pair<T, 0, a, b, start, ii...> { typedef numeric_list<T, ii...> type; };
+
+template<typename T, std::size_t n, T V, T... nn> struct gen_numeric_list_repeated                 : gen_numeric_list_repeated<T, n-1, V, V, nn...> {};
+template<typename T, T V, T... nn>                struct gen_numeric_list_repeated<T, 0, V, nn...> { typedef numeric_list<T, nn...> type; };
+
+/* list manipulation: concatenate */
+
+template<class a, class b> struct concat;
+
+template<typename... as, typename... bs> struct concat<type_list<as...>,       type_list<bs...>>        { typedef type_list<as..., bs...> type; };
+template<typename T, T... as, T... bs>   struct concat<numeric_list<T, as...>, numeric_list<T, bs...> > { typedef numeric_list<T, as..., bs...> type; };
+
+template<typename... p> struct mconcat;
+template<typename a>                             struct mconcat<a>           { typedef a type; };
+template<typename a, typename b>                 struct mconcat<a, b>        : concat<a, b> {};
+template<typename a, typename b, typename... cs> struct mconcat<a, b, cs...> : concat<a, typename mconcat<b, cs...>::type> {};
+
+/* list manipulation: extract slices */
+
+template<int n, typename x> struct take;
+template<int n, typename a, typename... as> struct take<n, type_list<a, as...>> : concat<type_list<a>, typename take<n-1, type_list<as...>>::type> {};
+template<int n>                             struct take<n, type_list<>>         { typedef type_list<> type; };
+template<typename a, typename... as>        struct take<0, type_list<a, as...>> { typedef type_list<> type; };
+template<>                                  struct take<0, type_list<>>         { typedef type_list<> type; };
+
+template<typename T, int n, T a, T... as> struct take<n, numeric_list<T, a, as...>> : concat<numeric_list<T, a>, typename take<n-1, numeric_list<T, as...>>::type> {};
+template<typename T, int n>               struct take<n, numeric_list<T>>           { typedef numeric_list<T> type; };
+template<typename T, T a, T... as>        struct take<0, numeric_list<T, a, as...>> { typedef numeric_list<T> type; };
+template<typename T>                      struct take<0, numeric_list<T>>           { typedef numeric_list<T> type; };
+
+template<typename T, int n, T... ii>      struct h_skip_helper_numeric;
+template<typename T, int n, T i, T... ii> struct h_skip_helper_numeric<T, n, i, ii...> : h_skip_helper_numeric<T, n-1, ii...> {};
+template<typename T, T i, T... ii>        struct h_skip_helper_numeric<T, 0, i, ii...> { typedef numeric_list<T, i, ii...> type; };
+template<typename T, int n>               struct h_skip_helper_numeric<T, n>           { typedef numeric_list<T> type; };
+template<typename T>                      struct h_skip_helper_numeric<T, 0>           { typedef numeric_list<T> type; };
+
+template<int n, typename... tt>             struct h_skip_helper_type;
+template<int n, typename t, typename... tt> struct h_skip_helper_type<n, t, tt...> : h_skip_helper_type<n-1, tt...> {};
+template<typename t, typename... tt>        struct h_skip_helper_type<0, t, tt...> { typedef type_list<t, tt...> type; };
+template<int n>                             struct h_skip_helper_type<n>           { typedef type_list<> type; };
+template<>                                  struct h_skip_helper_type<0>           { typedef type_list<> type; };
+
+template<int n>
+struct h_skip {
+  template<typename T, T... ii>
+  constexpr static inline typename h_skip_helper_numeric<T, n, ii...>::type helper(numeric_list<T, ii...>) { return typename h_skip_helper_numeric<T, n, ii...>::type(); }
+  template<typename... tt>
+  constexpr static inline typename h_skip_helper_type<n, tt...>::type helper(type_list<tt...>) { return typename h_skip_helper_type<n, tt...>::type(); }
+};
+
+template<int n, typename a> struct skip { typedef decltype(h_skip<n>::helper(a())) type; };
+
+template<int start, int count, typename a> struct slice : take<count, typename skip<start, a>::type> {};
+
+/* list manipulation: retrieve single element from list */
+
+template<int n, typename x> struct get;
+
+template<int n, typename a, typename... as>               struct get<n, type_list<a, as...>>   : get<n-1, type_list<as...>> {};
+template<typename a, typename... as>                      struct get<0, type_list<a, as...>>   { typedef a type; };
+
+template<typename T, int n, T a, T... as>                        struct get<n, numeric_list<T, a, as...>>   : get<n-1, numeric_list<T, as...>> {};
+template<typename T, T a, T... as>                               struct get<0, numeric_list<T, a, as...>>   { constexpr static T value = a; };
+
+/* always get type, regardless of dummy; good for parameter pack expansion */
+
+template<typename T, T dummy, typename t> struct id_numeric  { typedef t type; };
+template<typename dummy, typename t>      struct id_type     { typedef t type; };
+
+/* equality checking, flagged version */
+
+template<typename a, typename b> struct is_same_gf : is_same<a, b> { constexpr static int global_flags = 0; };
+
+/* apply_op to list */
+
+template<
+  bool from_left, // false
+  template<typename, typename> class op,
+  typename additional_param,
+  typename... values
+>
+struct h_apply_op_helper                                        { typedef type_list<typename op<values, additional_param>::type...> type; };
+template<
+  template<typename, typename> class op,
+  typename additional_param,
+  typename... values
+>
+struct h_apply_op_helper<true, op, additional_param, values...> { typedef type_list<typename op<additional_param, values>::type...> type; };
+
+template<
+  bool from_left,
+  template<typename, typename> class op,
+  typename additional_param
+>
+struct h_apply_op
+{
+  template<typename... values>
+  constexpr static typename h_apply_op_helper<from_left, op, additional_param, values...>::type helper(type_list<values...>)
+  { return typename h_apply_op_helper<from_left, op, additional_param, values...>::type(); }
+};
+
+template<
+  template<typename, typename> class op,
+  typename additional_param,
+  typename a
+>
+struct apply_op_from_left { typedef decltype(h_apply_op<true, op, additional_param>::helper(a())) type; };
+
+template<
+  template<typename, typename> class op,
+  typename additional_param,
+  typename a
+>
+struct apply_op_from_right { typedef decltype(h_apply_op<false, op, additional_param>::helper(a())) type; };
+
+/* see if an element is in a list */
+
+template<
+  template<typename, typename> class test,
+  typename check_against,
+  typename h_list,
+  bool last_check_positive = false
+>
+struct contained_in_list;
+
+template<
+  template<typename, typename> class test,
+  typename check_against,
+  typename h_list
+>
+struct contained_in_list<test, check_against, h_list, true>
+{
+  constexpr static bool value = true;
+};
+
+template<
+  template<typename, typename> class test,
+  typename check_against,
+  typename a,
+  typename... as
+>
+struct contained_in_list<test, check_against, type_list<a, as...>, false> : contained_in_list<test, check_against, type_list<as...>, test<check_against, a>::value> {};
+
+template<
+  template<typename, typename> class test,
+  typename check_against
+  EIGEN_TPL_PP_SPEC_HACK_DEFC(typename, empty)
+>
+struct contained_in_list<test, check_against, type_list<EIGEN_TPL_PP_SPEC_HACK_USE(empty)>, false> { constexpr static bool value = false; };
+
+/* see if an element is in a list and check for global flags */
+
+template<
+  template<typename, typename> class test,
+  typename check_against,
+  typename h_list,
+  int default_flags = 0,
+  bool last_check_positive = false,
+  int last_check_flags = default_flags
+>
+struct contained_in_list_gf;
+
+template<
+  template<typename, typename> class test,
+  typename check_against,
+  typename h_list,
+  int default_flags,
+  int last_check_flags
+>
+struct contained_in_list_gf<test, check_against, h_list, default_flags, true, last_check_flags>
+{
+  constexpr static bool value = true;
+  constexpr static int global_flags = last_check_flags;
+};
+
+template<
+  template<typename, typename> class test,
+  typename check_against,
+  typename a,
+  typename... as,
+  int default_flags,
+  int last_check_flags
+>
+struct contained_in_list_gf<test, check_against, type_list<a, as...>, default_flags, false, last_check_flags> : contained_in_list_gf<test, check_against, type_list<as...>, default_flags, test<check_against, a>::value, test<check_against, a>::global_flags> {};
+
+template<
+  template<typename, typename> class test,
+  typename check_against
+  EIGEN_TPL_PP_SPEC_HACK_DEFC(typename, empty),
+  int default_flags,
+  int last_check_flags
+>
+struct contained_in_list_gf<test, check_against, type_list<EIGEN_TPL_PP_SPEC_HACK_USE(empty)>, default_flags, false, last_check_flags> { constexpr static bool value = false; constexpr static int global_flags = default_flags; };
+
+/* generic reductions */
+
+template<
+  typename Reducer,
+  typename... Ts
+> struct reduce;
+
+template<
+  typename Reducer
+> struct reduce<Reducer>
+{
+  constexpr static inline int run() { return Reducer::Identity; }
+};
+
+template<
+  typename Reducer,
+  typename A
+> struct reduce<Reducer, A>
+{
+  constexpr static inline A run(A a) { return a; }
+};
+
+template<
+  typename Reducer,
+  typename A,
+  typename... Ts
+> struct reduce<Reducer, A, Ts...>
+{
+  constexpr static inline auto run(A a, Ts... ts) -> decltype(Reducer::run(a, reduce<Reducer, Ts...>::run(ts...))) {
+    return Reducer::run(a, reduce<Reducer, Ts...>::run(ts...));
+  }
+};
+
+/* generic binary operations */
+
+struct sum_op           {
+  template<typename A, typename B> EIGEN_DEVICE_FUNC constexpr static inline auto run(A a, B b) -> decltype(a + b)   { return a + b;   }
+  static constexpr int Identity = 0;
+};
+struct product_op       {
+  template<typename A, typename B> EIGEN_DEVICE_FUNC constexpr static inline auto run(A a, B b) -> decltype(a * b)   { return a * b;   }
+  static constexpr int Identity = 1;
+};
+
+struct logical_and_op   { template<typename A, typename B> constexpr static inline auto run(A a, B b) -> decltype(a && b)  { return a && b;  } };
+struct logical_or_op    { template<typename A, typename B> constexpr static inline auto run(A a, B b) -> decltype(a || b)  { return a || b;  } };
+
+struct equal_op         { template<typename A, typename B> constexpr static inline auto run(A a, B b) -> decltype(a == b)  { return a == b;  } };
+struct not_equal_op     { template<typename A, typename B> constexpr static inline auto run(A a, B b) -> decltype(a != b)  { return a != b;  } };
+struct lesser_op        { template<typename A, typename B> constexpr static inline auto run(A a, B b) -> decltype(a < b)   { return a < b;   } };
+struct lesser_equal_op  { template<typename A, typename B> constexpr static inline auto run(A a, B b) -> decltype(a <= b)  { return a <= b;  } };
+struct greater_op       { template<typename A, typename B> constexpr static inline auto run(A a, B b) -> decltype(a > b)   { return a > b;   } };
+struct greater_equal_op { template<typename A, typename B> constexpr static inline auto run(A a, B b) -> decltype(a >= b)  { return a >= b;  } };
+
+/* generic unary operations */
+
+struct not_op                { template<typename A> constexpr static inline auto run(A a) -> decltype(!a)      { return !a;      } };
+struct negation_op           { template<typename A> constexpr static inline auto run(A a) -> decltype(-a)      { return -a;      } };
+struct greater_equal_zero_op { template<typename A> constexpr static inline auto run(A a) -> decltype(a >= 0)  { return a >= 0;  } };
+
+
+/* reductions for lists */
+
+// using auto -> return value spec makes ICC 13.0 and 13.1 crash here, so we have to hack it
+// together in front... (13.0 doesn't work with array_prod/array_reduce/... anyway, but 13.1
+// does...
+template<typename... Ts>
+constexpr inline decltype(reduce<product_op, Ts...>::run((*((Ts*)0))...)) arg_prod(Ts... ts)
+{
+  return reduce<product_op, Ts...>::run(ts...);
+}
+
+template<typename... Ts>
+constexpr inline decltype(reduce<sum_op, Ts...>::run((*((Ts*)0))...)) arg_sum(Ts... ts)
+{
+  return reduce<sum_op, Ts...>::run(ts...);
+}
+
+/* reverse arrays */
+
+template<typename Array, int... n>
+constexpr inline Array h_array_reverse(Array arr, numeric_list<int, n...>)
+{
+  return {{array_get<sizeof...(n) - n - 1>(arr)...}};
+}
+
+template<typename T, std::size_t N>
+constexpr inline array<T, N> array_reverse(array<T, N> arr)
+{
+  return h_array_reverse(arr, typename gen_numeric_list<int, N>::type());
+}
+
+
+/* generic array reductions */
+
+// can't reuse standard reduce() interface above because Intel's Compiler
+// *really* doesn't like it, so we just reimplement the stuff
+// (start from N - 1 and work down to 0 because specialization for
+// n == N - 1 also doesn't work in Intel's compiler, so it goes into
+// an infinite loop)
+template<typename Reducer, typename T, std::size_t N, std::size_t n = N - 1>
+struct h_array_reduce {
+  EIGEN_DEVICE_FUNC constexpr static inline auto run(array<T, N> arr, T identity) -> decltype(Reducer::run(h_array_reduce<Reducer, T, N, n - 1>::run(arr, identity), array_get<n>(arr)))
+  {
+    return Reducer::run(h_array_reduce<Reducer, T, N, n - 1>::run(arr, identity), array_get<n>(arr));
+  }
+};
+
+template<typename Reducer, typename T, std::size_t N>
+struct h_array_reduce<Reducer, T, N, 0>
+{
+  EIGEN_DEVICE_FUNC constexpr static inline T run(const array<T, N>& arr, T)
+  {
+    return array_get<0>(arr);
+  }
+};
+
+template<typename Reducer, typename T>
+struct h_array_reduce<Reducer, T, 0>
+{
+  EIGEN_DEVICE_FUNC constexpr static inline T run(const array<T, 0>&, T identity)
+  {
+    return identity;
+  }
+};
+
+template<typename Reducer, typename T, std::size_t N>
+EIGEN_DEVICE_FUNC constexpr inline auto array_reduce(const array<T, N>& arr, T identity) -> decltype(h_array_reduce<Reducer, T, N>::run(arr, identity))
+{
+  return h_array_reduce<Reducer, T, N>::run(arr, identity);
+}
+
+/* standard array reductions */
+
+template<typename T, std::size_t N>
+EIGEN_DEVICE_FUNC constexpr inline auto array_sum(const array<T, N>& arr) -> decltype(array_reduce<sum_op, T, N>(arr, static_cast<T>(0)))
+{
+  return array_reduce<sum_op, T, N>(arr, static_cast<T>(0));
+}
+
+template<typename T, std::size_t N>
+EIGEN_DEVICE_FUNC constexpr inline auto array_prod(const array<T, N>& arr) -> decltype(array_reduce<product_op, T, N>(arr, static_cast<T>(1)))
+{
+  return array_reduce<product_op, T, N>(arr, static_cast<T>(1));
+}
+
+template<typename t>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE t array_prod(const std::vector<t>& a) {
+  eigen_assert(a.size() > 0);
+  t prod = 1;
+  for (size_t i = 0; i < a.size(); ++i) { prod *= a[i]; }
+  return prod;
+}
+
+/* zip an array */
+
+template<typename Op, typename A, typename B, std::size_t N, int... n>
+constexpr inline array<decltype(Op::run(A(), B())),N> h_array_zip(array<A, N> a, array<B, N> b, numeric_list<int, n...>)
+{
+  return array<decltype(Op::run(A(), B())),N>{{ Op::run(array_get<n>(a), array_get<n>(b))... }};
+}
+
+template<typename Op, typename A, typename B, std::size_t N>
+constexpr inline array<decltype(Op::run(A(), B())),N> array_zip(array<A, N> a, array<B, N> b)
+{
+  return h_array_zip<Op>(a, b, typename gen_numeric_list<int, N>::type());
+}
+
+/* zip an array and reduce the result */
+
+template<typename Reducer, typename Op, typename A, typename B, std::size_t N, int... n>
+constexpr inline auto h_array_zip_and_reduce(array<A, N> a, array<B, N> b, numeric_list<int, n...>) -> decltype(reduce<Reducer, typename id_numeric<int,n,decltype(Op::run(A(), B()))>::type...>::run(Op::run(array_get<n>(a), array_get<n>(b))...))
+{
+  return reduce<Reducer, typename id_numeric<int,n,decltype(Op::run(A(), B()))>::type...>::run(Op::run(array_get<n>(a), array_get<n>(b))...);
+}
+
+template<typename Reducer, typename Op, typename A, typename B, std::size_t N>
+constexpr inline auto array_zip_and_reduce(array<A, N> a, array<B, N> b) -> decltype(h_array_zip_and_reduce<Reducer, Op, A, B, N>(a, b, typename gen_numeric_list<int, N>::type()))
+{
+  return h_array_zip_and_reduce<Reducer, Op, A, B, N>(a, b, typename gen_numeric_list<int, N>::type());
+}
+
+/* apply stuff to an array */
+
+template<typename Op, typename A, std::size_t N, int... n>
+constexpr inline array<decltype(Op::run(A())),N> h_array_apply(array<A, N> a, numeric_list<int, n...>)
+{
+  return array<decltype(Op::run(A())),N>{{ Op::run(array_get<n>(a))... }};
+}
+
+template<typename Op, typename A, std::size_t N>
+constexpr inline array<decltype(Op::run(A())),N> array_apply(array<A, N> a)
+{
+  return h_array_apply<Op>(a, typename gen_numeric_list<int, N>::type());
+}
+
+/* apply stuff to an array and reduce */
+
+template<typename Reducer, typename Op, typename A, std::size_t N, int... n>
+constexpr inline auto h_array_apply_and_reduce(array<A, N> arr, numeric_list<int, n...>) -> decltype(reduce<Reducer, typename id_numeric<int,n,decltype(Op::run(A()))>::type...>::run(Op::run(array_get<n>(arr))...))
+{
+  return reduce<Reducer, typename id_numeric<int,n,decltype(Op::run(A()))>::type...>::run(Op::run(array_get<n>(arr))...);
+}
+
+template<typename Reducer, typename Op, typename A, std::size_t N>
+constexpr inline auto array_apply_and_reduce(array<A, N> a) -> decltype(h_array_apply_and_reduce<Reducer, Op, A, N>(a, typename gen_numeric_list<int, N>::type()))
+{
+  return h_array_apply_and_reduce<Reducer, Op, A, N>(a, typename gen_numeric_list<int, N>::type());
+}
+
+/* repeat a value n times (and make an array out of it
+ * usage:
+ *   array<int, 16> = repeat<16>(42);
+ */
+
+template<int n>
+struct h_repeat
+{
+  template<typename t, int... ii>
+  constexpr static inline array<t, n> run(t v, numeric_list<int, ii...>)
+  {
+    return {{ typename id_numeric<int, ii, t>::type(v)... }};
+  }
+};
+
+template<int n, typename t>
+constexpr array<t, n> repeat(t v) { return h_repeat<n>::run(v, typename gen_numeric_list<int, n>::type()); }
+
+/* instantiate a class by a C-style array */
+template<class InstType, typename ArrType, std::size_t N, bool Reverse, typename... Ps>
+struct h_instantiate_by_c_array;
+
+template<class InstType, typename ArrType, std::size_t N, typename... Ps>
+struct h_instantiate_by_c_array<InstType, ArrType, N, false, Ps...>
+{
+  static InstType run(ArrType* arr, Ps... args)
+  {
+    return h_instantiate_by_c_array<InstType, ArrType, N - 1, false, Ps..., ArrType>::run(arr + 1, args..., arr[0]);
+  }
+};
+
+template<class InstType, typename ArrType, std::size_t N, typename... Ps>
+struct h_instantiate_by_c_array<InstType, ArrType, N, true, Ps...>
+{
+  static InstType run(ArrType* arr, Ps... args)
+  {
+    return h_instantiate_by_c_array<InstType, ArrType, N - 1, false, ArrType, Ps...>::run(arr + 1, arr[0], args...);
+  }
+};
+
+template<class InstType, typename ArrType, typename... Ps>
+struct h_instantiate_by_c_array<InstType, ArrType, 0, false, Ps...>
+{
+  static InstType run(ArrType* arr, Ps... args)
+  {
+    (void)arr;
+    return InstType(args...);
+  }
+};
+
+template<class InstType, typename ArrType, typename... Ps>
+struct h_instantiate_by_c_array<InstType, ArrType, 0, true, Ps...>
+{
+  static InstType run(ArrType* arr, Ps... args)
+  {
+    (void)arr;
+    return InstType(args...);
+  }
+};
+
+template<class InstType, typename ArrType, std::size_t N, bool Reverse = false>
+InstType instantiate_by_c_array(ArrType* arr)
+{
+  return h_instantiate_by_c_array<InstType, ArrType, N, Reverse>::run(arr);
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#else // Non C++11, fallback to emulation mode
+
+#include "EmulateCXX11Meta.h"
+
+#endif
+
+#endif // EIGEN_CXX11META_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/util/CXX11Workarounds.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/CXX11Workarounds.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/CXX11Workarounds.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/CXX11Workarounds.h
@@ -0,0 +1,88 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11WORKAROUNDS_H
+#define EIGEN_CXX11WORKAROUNDS_H
+
+/* COMPATIBILITY CHECKS
+ * (so users of compilers that are too old get some realistic error messages)
+ */
+#if defined(__INTEL_COMPILER) && (__INTEL_COMPILER < 1310)
+#error Intel Compiler only supports required C++ features since version 13.1.
+// note that most stuff in principle works with 13.0 but when combining
+// some features, at some point 13.0 will just fail with an internal assertion
+#elif defined(__GNUC__) && !defined(__clang__) && !defined(__INTEL_COMPILER) && (__GNUC__ < 4 || (__GNUC__ == 4 && __GNUC_MINOR__ < 6))
+// G++ < 4.6 by default will continue processing the source files - even if we use #error to make
+// it error out. For this reason, we use the pragma to make sure G++ aborts at the first error
+// it sees. Unfortunately, that is still not our #error directive, but at least the output is
+// short enough the user has a chance to see that the compiler version is not sufficient for
+// the funky template mojo we use.
+#pragma GCC diagnostic error "-Wfatal-errors"
+#error GNU C++ Compiler (g++) only supports required C++ features since version 4.6.
+#endif
+
+/* Check that the compiler at least claims to support C++11. It might not be sufficient
+ * because the compiler may not implement it correctly, but at least we'll know.
+ * On the other hand, visual studio still doesn't claim to support C++11 although it's
+ * compliant enugh for our purpose.
+ */
+#if (__cplusplus <= 199711L) && (EIGEN_COMP_MSVC < 1900)
+#if defined(__GNUC__) && !defined(__clang__) && !defined(__INTEL_COMPILER)
+#pragma GCC diagnostic error "-Wfatal-errors"
+#endif
+#error This library needs at least a C++11 compliant compiler. If you use g++/clang, please enable the -std=c++11 compiler flag. (-std=c++0x on older versions.)
+#endif
+
+namespace Eigen {
+
+namespace internal {
+
+/* std::get is only constexpr in C++14, not yet in C++11
+ */
+
+
+template<std::size_t I, class T> constexpr inline T&       array_get(std::vector<T>&       a) { return a[I]; }
+template<std::size_t I, class T> constexpr inline T&&      array_get(std::vector<T>&&      a) { return a[I]; }
+template<std::size_t I, class T> constexpr inline T const& array_get(std::vector<T> const& a) { return a[I]; }
+
+/* Suppose you have a template of the form
+ * template<typename T> struct X;
+ * And you want to specialize it in such a way:
+ *    template<typename S1, typename... SN> struct X<Foo<S1, SN...>> { ::: };
+ *    template<>                            struct X<Foo<>>          { ::: };
+ * This will work in Intel's compiler 13.0, but only to some extent in g++ 4.6, since
+ * g++ can only match templates called with parameter packs if the number of template
+ * arguments is not a fixed size (so inside the first specialization, referencing
+ * X<Foo<Sn...>> will fail in g++). On the other hand, g++ will accept the following:
+ *    template<typename S...> struct X<Foo<S...>> { ::: }:
+ * as an additional (!) specialization, which will then only match the empty case.
+ * But Intel's compiler 13.0 won't accept that, it will only accept the empty syntax,
+ * so we have to create a workaround for this.
+ */
+#if defined(__GNUC__) && !defined(__INTEL_COMPILER)
+#define EIGEN_TPL_PP_SPEC_HACK_DEF(mt, n)    mt... n
+#define EIGEN_TPL_PP_SPEC_HACK_DEFC(mt, n)   , EIGEN_TPL_PP_SPEC_HACK_DEF(mt, n)
+#define EIGEN_TPL_PP_SPEC_HACK_USE(n)        n...
+#define EIGEN_TPL_PP_SPEC_HACK_USEC(n)       , n...
+#else
+#define EIGEN_TPL_PP_SPEC_HACK_DEF(mt, n)
+#define EIGEN_TPL_PP_SPEC_HACK_DEFC(mt, n)
+#define EIGEN_TPL_PP_SPEC_HACK_USE(n)
+#define EIGEN_TPL_PP_SPEC_HACK_USEC(n)
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11WORKAROUNDS_H
+
+/*
+ * kate: space-indent on; indent-width 2; mixedindent off; indent-mode cstyle;
+ */

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/util/EmulateArray.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/EmulateArray.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/EmulateArray.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/EmulateArray.h
@@ -0,0 +1,267 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_EMULATE_ARRAY_H
+#define EIGEN_EMULATE_ARRAY_H
+
+
+
+// The array class is only available starting with cxx11. Emulate our own here
+// if needed. Beware, msvc still doesn't advertise itself as a c++11 compiler!
+// Moreover, CUDA doesn't support the STL containers, so we use our own instead.
+#if (__cplusplus <= 199711L && EIGEN_COMP_MSVC < 1900) || defined(__CUDACC__) || defined(EIGEN_AVOID_STL_ARRAY)
+
+namespace Eigen {
+template <typename T, size_t n> class array {
+ public:
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& operator[] (size_t index) { return values[index]; }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& operator[] (size_t index) const { return values[index]; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& front() { return values[0]; }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& front() const { return values[0]; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& back() { return values[n-1]; }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& back() const { return values[n-1]; }
+
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+  static std::size_t size() { return n; }
+
+  T values[n];
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array() { }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(const T& v) {
+    EIGEN_STATIC_ASSERT(n==1, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    values[0] = v;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(const T& v1, const T& v2) {
+    EIGEN_STATIC_ASSERT(n==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    values[0] = v1;
+    values[1] = v2;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3) {
+    EIGEN_STATIC_ASSERT(n==3, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    values[0] = v1;
+    values[1] = v2;
+    values[2] = v3;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3,
+                            const T& v4) {
+    EIGEN_STATIC_ASSERT(n==4, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    values[0] = v1;
+    values[1] = v2;
+    values[2] = v3;
+    values[3] = v4;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3, const T& v4,
+                            const T& v5) {
+    EIGEN_STATIC_ASSERT(n==5, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    values[0] = v1;
+    values[1] = v2;
+    values[2] = v3;
+    values[3] = v4;
+    values[4] = v5;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3, const T& v4,
+                            const T& v5, const T& v6) {
+    EIGEN_STATIC_ASSERT(n==6, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    values[0] = v1;
+    values[1] = v2;
+    values[2] = v3;
+    values[3] = v4;
+    values[4] = v5;
+    values[5] = v6;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3, const T& v4,
+                            const T& v5, const T& v6, const T& v7) {
+    EIGEN_STATIC_ASSERT(n==7, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    values[0] = v1;
+    values[1] = v2;
+    values[2] = v3;
+    values[3] = v4;
+    values[4] = v5;
+    values[5] = v6;
+    values[6] = v7;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(
+      const T& v1, const T& v2, const T& v3, const T& v4,
+      const T& v5, const T& v6, const T& v7, const T& v8) {
+    EIGEN_STATIC_ASSERT(n==8, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    values[0] = v1;
+    values[1] = v2;
+    values[2] = v3;
+    values[3] = v4;
+    values[4] = v5;
+    values[5] = v6;
+    values[6] = v7;
+    values[7] = v8;
+  }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array(std::initializer_list<T> l) {
+    eigen_assert(l.size() == n);
+    internal::smart_copy(l.begin(), l.end(), values);
+  }
+#endif
+};
+
+
+// Specialize array for zero size
+template <typename T> class array<T, 0> {
+ public:
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& operator[] (size_t) {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& operator[] (size_t) const {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& front() {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& front() const {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T& back() {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T& back() const {
+    eigen_assert(false && "Can't index a zero size array");
+    return dummy;
+  }
+
+  static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::size_t size() { return 0; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE array() : dummy() { }
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  EIGEN_DEVICE_FUNC array(std::initializer_list<T> l) : dummy() {
+    eigen_assert(l.size() == 0);
+  }
+#endif
+
+ private:
+  T dummy;
+};
+
+// Comparison operator
+// Todo: implement !=, <, <=, >,  and >=
+template<class T, std::size_t N>
+EIGEN_DEVICE_FUNC bool operator==(const array<T,N>& lhs, const array<T,N>& rhs) {
+  for (std::size_t i = 0; i < N; ++i) {
+    if (lhs[i] != rhs[i]) {
+      return false;
+    }
+  }
+  return true;
+}
+
+
+namespace internal {
+template<std::size_t I, class T, std::size_t N>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T& array_get(array<T,N>& a) {
+  return a[I];
+}
+template<std::size_t I, class T, std::size_t N>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T& array_get(const array<T,N>& a) {
+  return a[I];
+}
+
+template <typename T> struct array_size;
+template<class T, std::size_t N> struct array_size<array<T,N> > {
+  static const size_t value = N;
+};
+template <typename T> struct array_size;
+template<class T, std::size_t N> struct array_size<array<T,N>& > {
+  static const size_t value = N;
+};
+template <typename T> struct array_size;
+template<class T, std::size_t N> struct array_size<const array<T,N> > {
+  static const size_t value = N;
+};
+template <typename T> struct array_size;
+template<class T, std::size_t N> struct array_size<const array<T,N>& > {
+  static const size_t value = N;
+};
+
+}  // end namespace internal
+}  // end namespace Eigen
+
+#else
+
+// The compiler supports c++11, and we're not targetting cuda: use std::array as Eigen::array
+#include <array>
+namespace Eigen {
+
+template <typename T, std::size_t N> using array = std::array<T, N>;
+
+namespace internal {
+/* std::get is only constexpr in C++14, not yet in C++11
+ *     - libstdc++ from version 4.7 onwards has it nevertheless,
+ *                                          so use that
+ *     - libstdc++ older versions: use _M_instance directly
+ *     - libc++ all versions so far: use __elems_ directly
+ *     - all other libs: use std::get to be portable, but
+ *                       this may not be constexpr
+ */
+#if defined(__GLIBCXX__) && __GLIBCXX__ < 20120322
+#define STD_GET_ARR_HACK             a._M_instance[I]
+#elif defined(_LIBCPP_VERSION)
+#define STD_GET_ARR_HACK             a.__elems_[I]
+#else
+#define STD_GET_ARR_HACK             std::template get<I, T, N>(a)
+#endif
+
+template<std::size_t I, class T, std::size_t N> constexpr inline T&       array_get(std::array<T,N>&       a) { return (T&)       STD_GET_ARR_HACK; }
+template<std::size_t I, class T, std::size_t N> constexpr inline T&&      array_get(std::array<T,N>&&      a) { return (T&&)      STD_GET_ARR_HACK; }
+template<std::size_t I, class T, std::size_t N> constexpr inline T const& array_get(std::array<T,N> const& a) { return (T const&) STD_GET_ARR_HACK; }
+
+#undef STD_GET_ARR_HACK
+
+template <typename T> struct array_size;
+template<class T, std::size_t N> struct array_size<const std::array<T,N> > {
+  static const size_t value = N;
+};
+template <typename T> struct array_size;
+template<class T, std::size_t N> struct array_size<std::array<T,N> > {
+  static const size_t value = N;
+};
+}  // end namespace internal
+}  // end namespace Eigen
+
+#endif
+
+#endif  // EIGEN_EMULATE_ARRAY_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/util/EmulateCXX11Meta.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/EmulateCXX11Meta.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/EmulateCXX11Meta.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/EmulateCXX11Meta.h
@@ -0,0 +1,311 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_EMULATE_CXX11_META_H
+#define EIGEN_EMULATE_CXX11_META_H
+
+
+
+namespace Eigen {
+
+namespace internal {
+
+/** \internal
+  * \file CXX11/util/EmulateCXX11Meta.h
+  * This file emulates a subset of the functionality provided by CXXMeta.h for
+  * compilers that don't yet support cxx11 such as nvcc.
+  */
+
+struct empty_list { static const std::size_t count = 0; };
+
+template<typename T, typename Tail=empty_list> struct type_list {
+  typedef T HeadType;
+  typedef Tail TailType;
+  static const T head;
+  static const Tail tail;
+  static const std::size_t count = 1 + Tail::count;
+};
+
+struct null_type { };
+
+template<typename T1 = null_type, typename T2 = null_type, typename T3 = null_type,
+         typename T4 = null_type, typename T5 = null_type, typename T6 = null_type,
+         typename T7 = null_type, typename T8 = null_type>
+struct make_type_list {
+  typedef typename make_type_list<T2, T3, T4, T5, T6, T7, T8>::type tailresult;
+
+  typedef type_list<T1, tailresult> type;
+};
+
+template<> struct make_type_list<> {
+  typedef empty_list type;
+};
+
+
+template <std::size_t index, class TList> struct get_type;
+
+template <class Head, class Tail>
+struct get_type<0, type_list<Head, Tail> >
+{
+  typedef Head type;
+};
+
+template <std::size_t i, class Head, class Tail>
+struct get_type<i, type_list<Head, Tail> >
+{
+  typedef typename get_type<i-1, Tail>::type type;
+};
+
+
+/* numeric list */
+template <typename T, T n>
+struct type2val {
+  typedef T type;
+  static const T value = n;
+};
+
+
+template<typename T, size_t n, T V> struct gen_numeric_list_repeated;
+
+template<typename T, T V> struct gen_numeric_list_repeated<T, 1, V> {
+  typedef typename make_type_list<type2val<T, V> >::type type;
+};
+
+template<typename T, T V> struct gen_numeric_list_repeated<T, 2, V> {
+  typedef typename make_type_list<type2val<T, V>, type2val<T, V> >::type type;
+};
+
+template<typename T, T V> struct gen_numeric_list_repeated<T, 3, V> {
+  typedef typename make_type_list<type2val<T, V>, type2val<T, V>, type2val<T, V> >::type type;
+};
+
+template<typename T, T V> struct gen_numeric_list_repeated<T, 4, V> {
+  typedef typename make_type_list<type2val<T, V>, type2val<T, V>, type2val<T, V>, type2val<T, V> >::type type;
+};
+
+template<typename T, T V> struct gen_numeric_list_repeated<T, 5, V> {
+  typedef typename make_type_list<type2val<T, V>, type2val<T, V>, type2val<T, V>, type2val<T, V>, type2val<T, V> >::type type;
+};
+
+template<typename T, T V> struct gen_numeric_list_repeated<T, 6, V> {
+  typedef typename make_type_list<type2val<T, V>, type2val<T, V>, type2val<T, V>,
+                                  type2val<T, V>, type2val<T, V>, type2val<T, V> >::type type;
+};
+
+template<typename T, T V> struct gen_numeric_list_repeated<T, 7, V> {
+  typedef typename make_type_list<type2val<T, V>, type2val<T, V>, type2val<T, V>,
+                                  type2val<T, V>, type2val<T, V>, type2val<T, V>,
+                                  type2val<T, V> >::type type;
+};
+
+template<typename T, T V> struct gen_numeric_list_repeated<T, 8, V> {
+  typedef typename make_type_list<type2val<T, V>, type2val<T, V>, type2val<T, V>,
+                                  type2val<T, V>, type2val<T, V>, type2val<T, V>,
+                                  type2val<T, V>, type2val<T, V> >::type type;
+};
+
+
+template <std::size_t index, class NList> struct get;
+
+template <std::size_t i>
+struct get<i, empty_list>
+{
+  get() { eigen_assert(false && "index overflow"); }
+  typedef void type;
+  static const char value = '\0';
+};
+
+template <std::size_t i, class Head>
+struct get<i, type_list<Head, empty_list> >
+{
+  get() { eigen_assert(false && "index overflow"); }
+  typedef void type;
+  static const char value = '\0';
+};
+
+template <class Head>
+struct get<0, type_list<Head, empty_list> >
+{
+  typedef typename Head::type type;
+  static const type value = Head::value;
+};
+
+template <class Head, class Tail>
+struct get<0, type_list<Head, Tail> >
+{
+  typedef typename Head::type type;
+  static const type value = Head::value;
+};
+
+template <std::size_t i, class Head, class Tail>
+struct get<i, type_list<Head, Tail> >
+{
+  typedef typename Tail::HeadType::type type;
+  static const type value = get<i-1, Tail>::value;
+};
+
+
+template <class NList> struct arg_prod {
+  static const typename NList::HeadType::type value = get<0, NList>::value * arg_prod<typename NList::TailType>::value;
+};
+template <> struct arg_prod<empty_list> {
+  static const int value = 1;
+};
+
+
+template<int n, typename t>
+array<t, n> repeat(t v) {
+  array<t, n> array;
+  array.fill(v);
+  return array;
+}
+
+template<std::size_t I, class Head, class Tail>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename Head::type array_get(type_list<Head, Tail>&) {
+  return get<I, type_list<Head, Tail> >::value;
+}
+template<std::size_t I, class Head, class Tail>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename Head::type array_get(const type_list<Head, Tail>&) {
+  return get<I, type_list<Head, Tail> >::value;
+}
+
+template <class NList>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename NList::HeadType::type array_prod(const NList&) {
+  return arg_prod<NList>::value;
+}
+
+template<typename t, std::size_t n>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE t array_prod(const array<t, n>& a) {
+  t prod = 1;
+  for (size_t i = 0; i < n; ++i) { prod *= a[i]; }
+  return prod;
+}
+template<typename t>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE t array_prod(const array<t, 0>& /*a*/) {
+  return 0;
+}
+
+template<typename t>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE t array_prod(const std::vector<t>& a) {
+  eigen_assert(a.size() > 0);
+  t prod = 1;
+  for (size_t i = 0; i < a.size(); ++i) { prod *= a[i]; }
+  return prod;
+}
+
+
+template<std::size_t I, class T>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T& array_get(std::vector<T>& a) {
+  return a[I];
+}
+template<std::size_t I, class T>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T& array_get(const std::vector<T>& a) {
+  return a[I];
+}
+
+struct sum_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a + b; }
+};
+struct product_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a * b; }
+};
+
+struct logical_and_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a && b; }
+};
+struct logical_or_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a || b; }
+};
+
+struct equal_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a == b; }
+};
+struct not_equal_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a != b; }
+};
+struct lesser_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a < b; }
+};
+struct lesser_equal_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a <= b; }
+};
+
+struct greater_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a > b; }
+};
+struct greater_equal_op {
+  template<typename A, typename B> static inline bool run(A a, B b) { return a >= b; }
+};
+
+struct not_op {
+  template<typename A> static inline bool run(A a) { return !a; }
+};
+struct negation_op {
+  template<typename A> static inline bool run(A a) { return -a; }
+};
+struct greater_equal_zero_op {
+  template<typename A> static inline bool run(A a) { return a >= 0; }
+};
+
+
+template<typename Reducer, typename Op, typename A, std::size_t N>
+struct ArrayApplyAndReduce {
+  static inline bool run(const array<A, N>& a) {
+    EIGEN_STATIC_ASSERT(N >= 2, YOU_MADE_A_PROGRAMMING_MISTAKE);
+    bool result = Reducer::run(Op::run(a[0]), Op::run(a[1]));
+    for (size_t i = 2; i < N; ++i) {
+      result = Reducer::run(result, Op::run(a[i]));
+    }
+    return result;
+  }
+};
+
+template<typename Reducer, typename Op, typename A>
+struct ArrayApplyAndReduce<Reducer, Op, A, 1>  {
+  static inline bool run(const array<A, 1>& a) {
+    return Op::run(a[0]);
+  }
+};
+
+template<typename Reducer, typename Op, typename A, std::size_t N>
+inline bool array_apply_and_reduce(const array<A, N>& a) {
+  return ArrayApplyAndReduce<Reducer, Op, A, N>::run(a);
+}
+
+template<typename Reducer, typename Op, typename A, typename B, std::size_t N>
+struct ArrayZipAndReduce {
+  static inline bool run(const array<A, N>& a, const array<B, N>& b) {
+    EIGEN_STATIC_ASSERT(N >= 2, YOU_MADE_A_PROGRAMMING_MISTAKE);
+    bool result = Reducer::run(Op::run(a[0], b[0]), Op::run(a[1], b[1]));
+    for (size_t i = 2; i < N; ++i) {
+      result = Reducer::run(result, Op::run(a[i], b[i]));
+    }
+    return result;
+  }
+};
+
+template<typename Reducer, typename Op, typename A, typename B>
+struct ArrayZipAndReduce<Reducer, Op, A, B, 1> {
+  static inline bool run(const array<A, 1>& a, const array<B, 1>& b) {
+    return Op::run(a[0], b[0]);
+  }
+};
+
+template<typename Reducer, typename Op, typename A, typename B, std::size_t N>
+inline bool array_zip_and_reduce(const array<A, N>& a, const array<B, N>& b) {
+  return ArrayZipAndReduce<Reducer, Op, A, B, N>::run(a, b);
+}
+
+}  // end namespace internal
+
+}  // end namespace Eigen
+
+
+
+#endif  // EIGEN_EMULATE_CXX11_META_H

ADDED   3rd_party/eigen/unsupported/Eigen/CXX11/src/util/MaxSizeVector.h
Index: 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/MaxSizeVector.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/MaxSizeVector.h
+++ 3rd_party/eigen/unsupported/Eigen/CXX11/src/util/MaxSizeVector.h
@@ -0,0 +1,141 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_FIXEDSIZEVECTOR_H
+#define EIGEN_FIXEDSIZEVECTOR_H
+
+namespace Eigen {
+
+/** \class MaxSizeVector
+  * \ingroup Core
+  *
+  * \brief The MaxSizeVector class.
+  *
+  * The %MaxSizeVector provides a subset of std::vector functionality.
+  *
+  * The goal is to provide basic std::vector operations when using
+  * std::vector is not an option (e.g. on GPU or when compiling using
+  * FMA/AVX, as this can cause either compilation failures or illegal
+  * instruction failures).
+  *
+  * Beware: The constructors are not API compatible with these of
+  * std::vector.
+  */
+template <typename T>
+class MaxSizeVector {
+ public:
+  // Construct a new MaxSizeVector, reserve n elements.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  explicit MaxSizeVector(size_t n)
+      : reserve_(n), size_(0),
+        data_(static_cast<T*>(internal::aligned_malloc(n * sizeof(T)))) {
+    for (size_t i = 0; i < n; ++i) { new (&data_[i]) T; }
+  }
+
+  // Construct a new MaxSizeVector, reserve and resize to n.
+  // Copy the init value to all elements.
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  MaxSizeVector(size_t n, const T& init)
+      : reserve_(n), size_(n),
+        data_(static_cast<T*>(internal::aligned_malloc(n * sizeof(T)))) {
+    for (size_t i = 0; i < n; ++i) { new (&data_[i]) T(init); }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  ~MaxSizeVector() {
+    for (size_t i = 0; i < size_; ++i) {
+      data_[i].~T();
+    }
+    internal::aligned_free(data_);
+  }
+
+  void resize(size_t n) {
+    eigen_assert(n <= reserve_);
+    for (size_t i = size_; i < n; ++i) {
+      new (&data_[i]) T;
+    }
+    for (size_t i = n; i < size_; ++i) {
+      data_[i].~T();
+    }
+    size_ = n;
+  }
+
+  // Append new elements (up to reserved size).
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void push_back(const T& t) {
+    eigen_assert(size_ < reserve_);
+    data_[size_++] = t;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const T& operator[] (size_t i) const {
+    eigen_assert(i < size_);
+    return data_[i];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  T& operator[] (size_t i) {
+    eigen_assert(i < size_);
+    return data_[i];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  T& back() {
+    eigen_assert(size_ > 0);
+    return data_[size_ - 1];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const T& back() const {
+    eigen_assert(size_ > 0);
+    return data_[size_ - 1];
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  void pop_back() {
+    // NOTE: This does not destroy the value at the end the way
+    // std::vector's version of pop_back() does.  That happens when
+    // the Vector is destroyed.
+    eigen_assert(size_ > 0);
+    size_--;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  size_t size() const { return size_; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  bool empty() const { return size_ == 0; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  T* data() { return data_; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const T* data() const { return data_; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  T* begin() { return data_; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  T* end() { return data_ + size_; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const T* begin() const { return data_; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const T* end() const { return data_ + size_; }
+
+ private:
+  size_t reserve_;
+  size_t size_;
+  T* data_;
+};
+
+}  // namespace Eigen
+
+#endif  // EIGEN_FIXEDSIZEVECTOR_H

ADDED   3rd_party/eigen/unsupported/Eigen/EulerAngles
Index: 3rd_party/eigen/unsupported/Eigen/EulerAngles
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/EulerAngles
+++ 3rd_party/eigen/unsupported/Eigen/EulerAngles
@@ -0,0 +1,43 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Tal Hadad <tal_hd@hotmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_EULERANGLES_MODULE_H
+#define EIGEN_EULERANGLES_MODULE_H
+
+
+#include "Eigen/Core"
+#include "Eigen/Geometry"
+
+#include "Eigen/src/Core/util/DisableStupidWarnings.h"
+
+namespace Eigen {
+
+/**
+  * \defgroup EulerAngles_Module EulerAngles module
+  * \brief This module provides generic euler angles rotation.
+  *
+  * Euler angles are a way to represent 3D rotation.
+  *
+  * In order to use this module in your code, include this header:
+  * \code
+  * #include <unsupported/Eigen/EulerAngles>
+  * \endcode
+  *
+  * See \ref EulerAngles for more information.
+  *
+  */
+
+}
+
+#include "src/EulerAngles/EulerSystem.h"
+#include "src/EulerAngles/EulerAngles.h"
+
+#include "Eigen/src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_EULERANGLES_MODULE_H

Index: 3rd_party/eigen/unsupported/Eigen/IterativeSolvers
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/IterativeSolvers
+++ 3rd_party/eigen/unsupported/Eigen/IterativeSolvers
@@ -22,24 +22,21 @@
   * #include <unsupported/Eigen/IterativeSolvers>
   * \endcode
   */
 //@{
 
-#include "../../Eigen/src/misc/Solve.h"
-#include "../../Eigen/src/misc/SparseSolve.h"
-
 #ifndef EIGEN_MPL2_ONLY
 #include "src/IterativeSolvers/IterationController.h"
 #include "src/IterativeSolvers/ConstrainedConjGrad.h"
 #endif
 
 #include "src/IterativeSolvers/IncompleteLU.h"
 #include "../../Eigen/Jacobi"
 #include "../../Eigen/Householder"
 #include "src/IterativeSolvers/GMRES.h"
-#include "src/IterativeSolvers/IncompleteCholesky.h"
+#include "src/IterativeSolvers/DGMRES.h"
 //#include "src/IterativeSolvers/SSORPreconditioner.h"
 #include "src/IterativeSolvers/MINRES.h"
 
 //@}
 
 #endif // EIGEN_ITERATIVE_SOLVERS_MODULE_H

Index: 3rd_party/eigen/unsupported/Eigen/KroneckerProduct
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/KroneckerProduct
+++ 3rd_party/eigen/unsupported/Eigen/KroneckerProduct
@@ -10,10 +10,12 @@
 #define EIGEN_KRONECKER_PRODUCT_MODULE_H
 
 #include "../../Eigen/Core"
 
 #include "../../Eigen/src/Core/util/DisableStupidWarnings.h"
+
+#include "../../Eigen/src/SparseCore/SparseUtil.h"
 
 namespace Eigen {
 
 /**
   * \defgroup KroneckerProduct_Module KroneckerProduct module

Index: 3rd_party/eigen/unsupported/Eigen/MPRealSupport
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/MPRealSupport
+++ 3rd_party/eigen/unsupported/Eigen/MPRealSupport
@@ -24,10 +24,12 @@
   * \endcode
   *
   * This module provides support for multi precision floating point numbers
   * via the <a href="http://www.holoborodko.com/pavel/mpfr">MPFR C++</a>
   * library which itself is built upon <a href="http://www.mpfr.org/">MPFR</a>/<a href="http://gmplib.org/">GMP</a>.
+  *
+  * \warning MPFR C++ is licensed under the GPL.
   *
   * You can find a copy of MPFR C++ that is known to be compatible in the unsupported/test/mpreal folder.
   *
   * Here is an example:
   *
@@ -63,34 +65,39 @@
     enum {
       IsInteger = 0,
       IsSigned = 1,
       IsComplex = 0,
       RequireInitialization = 1,
-      ReadCost = 10,
-      AddCost = 10,
-      MulCost = 40
+      ReadCost = HugeCost,
+      AddCost  = HugeCost,
+      MulCost  = HugeCost
     };
 
     typedef mpfr::mpreal Real;
     typedef mpfr::mpreal NonInteger;
     
-    inline static Real highest   (long Precision = mpfr::mpreal::get_default_prec())  { return  mpfr::maxval(Precision); }
-    inline static Real lowest    (long Precision = mpfr::mpreal::get_default_prec())  { return -mpfr::maxval(Precision); }
+    static inline Real highest  (long Precision = mpfr::mpreal::get_default_prec()) { return  mpfr::maxval(Precision); }
+    static inline Real lowest   (long Precision = mpfr::mpreal::get_default_prec()) { return -mpfr::maxval(Precision); }
 
     // Constants
-    inline static Real Pi       (long Precision = mpfr::mpreal::get_default_prec())     {    return mpfr::const_pi(Precision);        }
-    inline static Real Euler    (long Precision = mpfr::mpreal::get_default_prec())     {    return mpfr::const_euler(Precision);     }
-    inline static Real Log2     (long Precision = mpfr::mpreal::get_default_prec())     {    return mpfr::const_log2(Precision);      }
-    inline static Real Catalan  (long Precision = mpfr::mpreal::get_default_prec())     {    return mpfr::const_catalan(Precision);   }
-
-    inline static Real epsilon  (long Precision = mpfr::mpreal::get_default_prec())     {    return mpfr::machine_epsilon(Precision); }
-    inline static Real epsilon  (const Real& x)                                         {    return mpfr::machine_epsilon(x); }
-
-    inline static Real dummy_precision()   
-    { 
-        unsigned int weak_prec = ((mpfr::mpreal::get_default_prec()-1) * 90) / 100;
-        return mpfr::machine_epsilon(weak_prec);
+    static inline Real Pi      (long Precision = mpfr::mpreal::get_default_prec())  { return mpfr::const_pi(Precision);        }
+    static inline Real Euler   (long Precision = mpfr::mpreal::get_default_prec())  { return mpfr::const_euler(Precision);     }
+    static inline Real Log2    (long Precision = mpfr::mpreal::get_default_prec())  { return mpfr::const_log2(Precision);      }
+    static inline Real Catalan (long Precision = mpfr::mpreal::get_default_prec())  { return mpfr::const_catalan(Precision);   }
+
+    static inline Real epsilon (long Precision = mpfr::mpreal::get_default_prec())  { return mpfr::machine_epsilon(Precision); }
+    static inline Real epsilon (const Real& x)                                      { return mpfr::machine_epsilon(x); }
+
+#ifdef MPREAL_HAVE_DYNAMIC_STD_NUMERIC_LIMITS
+    static inline int digits10 (long Precision = mpfr::mpreal::get_default_prec())  { return std::numeric_limits<Real>::digits10(Precision); }
+    static inline int digits10 (const Real& x)                                      { return std::numeric_limits<Real>::digits10(x); }
+#endif
+
+    static inline Real dummy_precision()
+    {
+      mpfr_prec_t weak_prec = ((mpfr::mpreal::get_default_prec()-1) * 90) / 100;
+      return mpfr::machine_epsilon(weak_prec);
     }
   };
 
   namespace internal {
 
@@ -137,67 +144,66 @@
     class gebp_traits<mpfr::mpreal, mpfr::mpreal, false, false>
     {
     public:
       typedef mpfr::mpreal ResScalar;
       enum {
-        nr = 2, // must be 2 for proper packing...
-        mr = 1,
-        WorkSpaceFactor = nr,
-        LhsProgress = 1,
-        RhsProgress = 1
-      };
-    };
-
-    template<typename Index, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs>
-    struct gebp_kernel<mpfr::mpreal,mpfr::mpreal,Index,mr,nr,ConjugateLhs,ConjugateRhs>
-    {
-      typedef mpfr::mpreal mpreal;
-
-      EIGEN_DONT_INLINE
-      void operator()(mpreal* res, Index resStride, const mpreal* blockA, const mpreal* blockB, Index rows, Index depth, Index cols, mpreal alpha,
-                      Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, mpreal* /*unpackedB*/ = 0)
-      {
-        mpreal acc1, acc2, tmp;
-        
-        if(strideA==-1) strideA = depth;
-        if(strideB==-1) strideB = depth;
-
-        for(Index j=0; j<cols; j+=nr)
-        {
-          Index actual_nr = (std::min<Index>)(nr,cols-j);
-          mpreal *C1 = res + j*resStride;
-          mpreal *C2 = res + (j+1)*resStride;
-          for(Index i=0; i<rows; i++)
-          {
-            mpreal *B = const_cast<mpreal*>(blockB) + j*strideB + offsetB*actual_nr;
-            mpreal *A = const_cast<mpreal*>(blockA) + i*strideA + offsetA;
-            acc1 = 0;
-            acc2 = 0;
-            for(Index k=0; k<depth; k++)
-            {
-              mpfr_mul(tmp.mpfr_ptr(), A[k].mpfr_ptr(), B[0].mpfr_ptr(), mpreal::get_default_rnd());
-              mpfr_add(acc1.mpfr_ptr(), acc1.mpfr_ptr(), tmp.mpfr_ptr(),  mpreal::get_default_rnd());
-              
-              if(actual_nr==2) {
-                mpfr_mul(tmp.mpfr_ptr(), A[k].mpfr_ptr(), B[1].mpfr_ptr(), mpreal::get_default_rnd());
-                mpfr_add(acc2.mpfr_ptr(), acc2.mpfr_ptr(), tmp.mpfr_ptr(),  mpreal::get_default_rnd());
-              }
-              
-              B+=actual_nr;
-            }
-            
-            mpfr_mul(acc1.mpfr_ptr(), acc1.mpfr_ptr(), alpha.mpfr_ptr(), mpreal::get_default_rnd());
-            mpfr_add(C1[i].mpfr_ptr(), C1[i].mpfr_ptr(), acc1.mpfr_ptr(),  mpreal::get_default_rnd());
-            
-            if(actual_nr==2) {
-              mpfr_mul(acc2.mpfr_ptr(), acc2.mpfr_ptr(), alpha.mpfr_ptr(), mpreal::get_default_rnd());
-              mpfr_add(C2[i].mpfr_ptr(), C2[i].mpfr_ptr(), acc2.mpfr_ptr(),  mpreal::get_default_rnd());
-            }
-          }
-        }
-      }
-    };
-
+        Vectorizable = false,
+        LhsPacketSize = 1,
+        RhsPacketSize = 1,
+        ResPacketSize = 1,
+        NumberOfRegisters = 1,
+        nr = 1,
+        mr = 1,
+        LhsProgress = 1,
+        RhsProgress = 1
+      };
+      typedef ResScalar LhsPacket;
+      typedef ResScalar RhsPacket;
+      typedef ResScalar ResPacket;
+      
+    };
+
+
+
+    template<typename Index, typename DataMapper, bool ConjugateLhs, bool ConjugateRhs>
+    struct gebp_kernel<mpfr::mpreal,mpfr::mpreal,Index,DataMapper,1,1,ConjugateLhs,ConjugateRhs>
+    {
+      typedef mpfr::mpreal mpreal;
+
+      EIGEN_DONT_INLINE
+      void operator()(const DataMapper& res, const mpreal* blockA, const mpreal* blockB, 
+                      Index rows, Index depth, Index cols, const mpreal& alpha,
+                      Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0)
+      {
+        if(rows==0 || cols==0 || depth==0)
+          return;
+
+        mpreal  acc1(0,mpfr_get_prec(blockA[0].mpfr_srcptr())),
+                tmp (0,mpfr_get_prec(blockA[0].mpfr_srcptr()));
+
+        if(strideA==-1) strideA = depth;
+        if(strideB==-1) strideB = depth;
+
+        for(Index i=0; i<rows; ++i)
+        {
+          for(Index j=0; j<cols; ++j)
+          {
+            const mpreal *A = blockA + i*strideA + offsetA;
+            const mpreal *B = blockB + j*strideB + offsetB;
+            
+            acc1 = 0;
+            for(Index k=0; k<depth; k++)
+            {
+              mpfr_mul(tmp.mpfr_ptr(), A[k].mpfr_srcptr(), B[k].mpfr_srcptr(), mpreal::get_default_rnd());
+              mpfr_add(acc1.mpfr_ptr(), acc1.mpfr_ptr(), tmp.mpfr_ptr(),  mpreal::get_default_rnd());
+            }
+            
+            mpfr_mul(acc1.mpfr_ptr(), acc1.mpfr_srcptr(), alpha.mpfr_srcptr(), mpreal::get_default_rnd());
+            mpfr_add(res(i,j).mpfr_ptr(), res(i,j).mpfr_srcptr(), acc1.mpfr_srcptr(),  mpreal::get_default_rnd());
+          }
+        }
+      }
+    };
   } // end namespace internal
 }
 
 #endif // EIGEN_MPREALSUPPORT_MODULE_H

Index: 3rd_party/eigen/unsupported/Eigen/MatrixFunctions
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/MatrixFunctions
+++ 3rd_party/eigen/unsupported/Eigen/MatrixFunctions
@@ -11,12 +11,10 @@
 #ifndef EIGEN_MATRIX_FUNCTIONS
 #define EIGEN_MATRIX_FUNCTIONS
 
 #include <cfloat>
 #include <list>
-#include <functional>
-#include <iterator>
 
 #include <Eigen/Core>
 #include <Eigen/LU>
 #include <Eigen/Eigenvalues>
 
@@ -82,11 +80,13 @@
 \endcode
 
 \param[in]  M  a square matrix.
 \returns  expression representing \f$ \cos(M) \f$.
 
-This function calls \ref matrixbase_matrixfunction "matrixFunction()" with StdStemFunctions::cos().
+This function computes the matrix cosine. Use ArrayBase::cos() for computing the entry-wise cosine.
+
+The implementation calls \ref matrixbase_matrixfunction "matrixFunction()" with StdStemFunctions::cos().
 
 \sa \ref matrixbase_sin "sin()" for an example.
 
 
 
@@ -122,10 +122,13 @@
 \f[ \exp(M) = \sum_{k=0}^\infty \frac{M^k}{k!}. \f]
 The matrix exponential can be used to solve linear ordinary
 differential equations: the solution of \f$ y' = My \f$ with the
 initial condition \f$ y(0) = y_0 \f$ is given by
 \f$ y(t) = \exp(M) y_0 \f$.
+
+The matrix exponential is different from applying the exp function to all the entries in the matrix.
+Use ArrayBase::exp() if you want to do the latter.
 
 The cost of the computation is approximately \f$ 20 n^3 \f$ for
 matrices of size \f$ n \f$. The number 20 depends weakly on the
 norm of the matrix.
 
@@ -176,10 +179,13 @@
 The matrix logarithm of \f$ M \f$ is a matrix \f$ X \f$ such that 
 \f$ \exp(X) = M \f$ where exp denotes the matrix exponential. As for
 the scalar logarithm, the equation \f$ \exp(X) = M \f$ may have
 multiple solutions; this function returns a matrix whose eigenvalues
 have imaginary part in the interval \f$ (-\pi,\pi] \f$.
+
+The matrix logarithm is different from applying the log function to all the entries in the matrix.
+Use ArrayBase::log() if you want to do the latter.
 
 In the real case, the matrix \f$ M \f$ should be invertible and
 it should have no eigenvalues which are real and negative (pairs of
 complex conjugate eigenvalues are allowed). In the complex case, it
 only needs to be invertible.
@@ -228,25 +234,69 @@
 \code
 const MatrixPowerReturnValue<Derived> MatrixBase<Derived>::pow(RealScalar p) const
 \endcode
 
 \param[in]  M  base of the matrix power, should be a square matrix.
-\param[in]  p  exponent of the matrix power, should be real.
+\param[in]  p  exponent of the matrix power.
 
 The matrix power \f$ M^p \f$ is defined as \f$ \exp(p \log(M)) \f$,
 where exp denotes the matrix exponential, and log denotes the matrix
-logarithm.
+logarithm. This is different from raising all the entries in the matrix
+to the p-th power. Use ArrayBase::pow() if you want to do the latter.
 
-The matrix \f$ M \f$ should meet the conditions to be an argument of
-matrix logarithm. If \p p is not of the real scalar type of \p M, it
-is casted into the real scalar type of \p M.
+If \p p is complex, the scalar type of \p M should be the type of \p
+p . \f$ M^p \f$ simply evaluates into \f$ \exp(p \log(M)) \f$.
+Therefore, the matrix \f$ M \f$ should meet the conditions to be an
+argument of matrix logarithm.
 
-This function computes the matrix power using the Schur-Pad&eacute;
+If \p p is real, it is casted into the real scalar type of \p M. Then
+this function computes the matrix power using the Schur-Pad&eacute;
 algorithm as implemented by class MatrixPower. The exponent is split
 into integral part and fractional part, where the fractional part is
 in the interval \f$ (-1, 1) \f$. The main diagonal and the first
 super-diagonal is directly computed.
+
+If \p M is singular with a semisimple zero eigenvalue and \p p is
+positive, the Schur factor \f$ T \f$ is reordered with Givens
+rotations, i.e.
+
+\f[ T = \left[ \begin{array}{cc}
+      T_1 & T_2 \\
+      0   & 0
+    \end{array} \right] \f]
+
+where \f$ T_1 \f$ is invertible. Then \f$ T^p \f$ is given by
+
+\f[ T^p = \left[ \begin{array}{cc}
+      T_1^p & T_1^{-1} T_1^p T_2 \\
+      0     & 0
+    \end{array}. \right] \f]
+
+\warning Fractional power of a matrix with a non-semisimple zero
+eigenvalue is not well-defined. We introduce an assertion failure
+against inaccurate result, e.g. \code
+#include <unsupported/Eigen/MatrixFunctions>
+#include <iostream>
+
+int main()
+{
+  Eigen::Matrix4d A;
+  A << 0, 0, 2, 3,
+       0, 0, 4, 5,
+       0, 0, 6, 7,
+       0, 0, 8, 9;
+  std::cout << A.pow(0.37) << std::endl;
+  
+  // The 1 makes eigenvalue 0 non-semisimple.
+  A.coeffRef(0, 1) = 1;
+
+  // This fails if EIGEN_NO_DEBUG is undefined.
+  std::cout << A.pow(0.37) << std::endl;
+
+  return 0;
+}
+\endcode
 
 Details of the algorithm can be found in: Nicholas J. Higham and
 Lijing Lin, "A Schur-Pad&eacute; algorithm for fractional powers of a
 matrix," <em>SIAM J. %Matrix Anal. Applic.</em>,
 <b>32(3)</b>:1056&ndash;1078, 2011.
@@ -348,11 +398,13 @@
 \endcode
 
 \param[in]  M  a square matrix.
 \returns  expression representing \f$ \sin(M) \f$.
 
-This function calls \ref matrixbase_matrixfunction "matrixFunction()" with StdStemFunctions::sin().
+This function computes the matrix sine. Use ArrayBase::sin() for computing the entry-wise sine.
+
+The implementation calls \ref matrixbase_matrixfunction "matrixFunction()" with StdStemFunctions::sin().
 
 Example: \include MatrixSine.cpp
 Output: \verbinclude MatrixSine.out
 
 
@@ -385,11 +437,13 @@
 \param[in]  M  invertible matrix whose square root is to be computed.
 \returns    expression representing the matrix square root of \p M.
 
 The matrix square root of \f$ M \f$ is the matrix \f$ M^{1/2} \f$
 whose square is the original matrix; so if \f$ S = M^{1/2} \f$ then
-\f$ S^2 = M \f$. 
+\f$ S^2 = M \f$. This is different from taking the square root of all
+the entries in the matrix; use ArrayBase::sqrt() if you want to do the
+latter.
 
 In the <b>real case</b>, the matrix \f$ M \f$ should be invertible and
 it should have no eigenvalues which are real and negative (pairs of
 complex conjugate eigenvalues are allowed). In that case, the matrix
 has a square root which is also real, and this is the square root

Index: 3rd_party/eigen/unsupported/Eigen/OpenGLSupport
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/OpenGLSupport
+++ 3rd_party/eigen/unsupported/Eigen/OpenGLSupport
@@ -49,11 +49,11 @@
 namespace internal {                                                                                                \
   template< typename XprType,                                                                                       \
             typename Scalar = typename XprType::Scalar,                                                             \
             int Rows = XprType::RowsAtCompileTime,                                                                  \
             int Cols = XprType::ColsAtCompileTime,                                                                  \
-            bool IsGLCompatible = bool(XprType::Flags&LinearAccessBit)                                              \
+            bool IsGLCompatible = bool(internal::evaluator<XprType>::Flags&LinearAccessBit)                         \
                               && bool(XprType::Flags&DirectAccessBit)                                               \
                               && (XprType::IsVectorAtCompileTime || (XprType::Flags&RowMajorBit)==0)>               \
   struct EIGEN_CAT(EIGEN_CAT(gl_,FUNC),_impl);                                                                      \
                                                                                                                     \
   template<typename XprType, typename Scalar, int Rows, int Cols>                                                   \
@@ -178,15 +178,15 @@
 template<typename Scalar> void glLoadMatrix(const Transform<Scalar,3,Projective>& t)    { glLoadMatrix(t.matrix()); }
 template<typename Scalar> void glLoadMatrix(const Transform<Scalar,3,AffineCompact>& t) { glLoadMatrix(Transform<Scalar,3,Affine>(t).matrix()); }
 
 inline void glRotate(const Rotation2D<float>& rot)
 {
-  glRotatef(rot.angle()*180.f/float(M_PI), 0.f, 0.f, 1.f);
+  glRotatef(rot.angle()*180.f/float(EIGEN_PI), 0.f, 0.f, 1.f);
 }
 inline void glRotate(const Rotation2D<double>& rot)
 {
-  glRotated(rot.angle()*180.0/M_PI, 0.0, 0.0, 1.0);
+  glRotated(rot.angle()*180.0/EIGEN_PI, 0.0, 0.0, 1.0);
 }
 
 template<typename Derived> void glRotate(const RotationBase<Derived,3>& rot)
 {  
   Transform<typename Derived::Scalar,3,Projective> tr(rot);
@@ -201,11 +201,11 @@
 namespace internal {                                                                                                            \
   template< typename XprType,                                                                                                   \
             typename Scalar = typename XprType::Scalar,                                                                         \
             int Rows = XprType::RowsAtCompileTime,                                                                              \
             int Cols = XprType::ColsAtCompileTime,                                                                              \
-            bool IsGLCompatible = bool(XprType::Flags&LinearAccessBit)                                                          \
+            bool IsGLCompatible = bool(internal::evaluator<XprType>::Flags&LinearAccessBit)                                     \
                               && bool(XprType::Flags&DirectAccessBit)                                                           \
                               && (XprType::IsVectorAtCompileTime || (XprType::Flags&RowMajorBit)==0)>                           \
   struct EIGEN_CAT(EIGEN_CAT(gl_,FUNC),_impl);                                                                                  \
                                                                                                                                 \
   template<typename XprType, typename Scalar, int Rows, int Cols>                                                               \
@@ -274,16 +274,16 @@
 
 #endif
 
 #ifdef GL_VERSION_2_1
 
-static void glUniformMatrix2x3fv_ei(GLint loc, const float* v)         { glUniformMatrix2x3fv(loc,1,false,v); }
-static void glUniformMatrix3x2fv_ei(GLint loc, const float* v)         { glUniformMatrix3x2fv(loc,1,false,v); }
-static void glUniformMatrix2x4fv_ei(GLint loc, const float* v)         { glUniformMatrix2x4fv(loc,1,false,v); }
-static void glUniformMatrix4x2fv_ei(GLint loc, const float* v)         { glUniformMatrix4x2fv(loc,1,false,v); }
-static void glUniformMatrix3x4fv_ei(GLint loc, const float* v)         { glUniformMatrix3x4fv(loc,1,false,v); }
-static void glUniformMatrix4x3fv_ei(GLint loc, const float* v)         { glUniformMatrix4x3fv(loc,1,false,v); }
+inline void glUniformMatrix2x3fv_ei(GLint loc, const float* v)         { glUniformMatrix2x3fv(loc,1,false,v); }
+inline void glUniformMatrix3x2fv_ei(GLint loc, const float* v)         { glUniformMatrix3x2fv(loc,1,false,v); }
+inline void glUniformMatrix2x4fv_ei(GLint loc, const float* v)         { glUniformMatrix2x4fv(loc,1,false,v); }
+inline void glUniformMatrix4x2fv_ei(GLint loc, const float* v)         { glUniformMatrix4x2fv(loc,1,false,v); }
+inline void glUniformMatrix3x4fv_ei(GLint loc, const float* v)         { glUniformMatrix3x4fv(loc,1,false,v); }
+inline void glUniformMatrix4x3fv_ei(GLint loc, const float* v)         { glUniformMatrix4x3fv(loc,1,false,v); }
 
 EIGEN_GL_FUNC1_SPECIALIZATION_MAT(glUniform,GLint,const,float,        2,3,Matrix2x3fv_ei)
 EIGEN_GL_FUNC1_SPECIALIZATION_MAT(glUniform,GLint,const,float,        3,2,Matrix3x2fv_ei)
 EIGEN_GL_FUNC1_SPECIALIZATION_MAT(glUniform,GLint,const,float,        2,4,Matrix2x4fv_ei)
 EIGEN_GL_FUNC1_SPECIALIZATION_MAT(glUniform,GLint,const,float,        4,2,Matrix4x2fv_ei)

DELETED 3rd_party/eigen/unsupported/Eigen/SVD
Index: 3rd_party/eigen/unsupported/Eigen/SVD
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/SVD
+++ 3rd_party/eigen/unsupported/Eigen/SVD
@@ -1,39 +0,0 @@
-#ifndef EIGEN_SVD_MODULE_H
-#define EIGEN_SVD_MODULE_H
-
-#include <Eigen/QR>
-#include <Eigen/Householder>
-#include <Eigen/Jacobi>
-
-#include "../../Eigen/src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup SVD_Module SVD module
-  *
-  *
-  *
-  * This module provides SVD decomposition for matrices (both real and complex).
-  * This decomposition is accessible via the following MatrixBase method:
-  *  - MatrixBase::jacobiSvd()
-  *
-  * \code
-  * #include <Eigen/SVD>
-  * \endcode
-  */
-
-#include "../../Eigen/src/misc/Solve.h"
-#include "../../Eigen/src/SVD/UpperBidiagonalization.h"
-#include "src/SVD/SVDBase.h"
-#include "src/SVD/JacobiSVD.h"
-#include "src/SVD/BDCSVD.h"
-#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
-#include "../../Eigen/src/SVD/JacobiSVD_MKL.h"
-#endif
-
-#ifdef EIGEN2_SUPPORT
-#include "../../Eigen/src/Eigen2Support/SVD.h"
-#endif
-
-#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_SVD_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Index: 3rd_party/eigen/unsupported/Eigen/SparseExtra
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/SparseExtra
+++ 3rd_party/eigen/unsupported/Eigen/SparseExtra
@@ -35,13 +35,10 @@
   * #include <Eigen/SparseExtra>
   * \endcode
   */
 
 
-#include "../../Eigen/src/misc/Solve.h"
-#include "../../Eigen/src/misc/SparseSolve.h"
-
 #include "src/SparseExtra/DynamicSparseMatrix.h"
 #include "src/SparseExtra/BlockOfDynamicSparseMatrix.h"
 #include "src/SparseExtra/RandomSetter.h"
 
 #include "src/SparseExtra/MarketIO.h"

ADDED   3rd_party/eigen/unsupported/Eigen/SpecialFunctions
Index: 3rd_party/eigen/unsupported/Eigen/SpecialFunctions
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/SpecialFunctions
+++ 3rd_party/eigen/unsupported/Eigen/SpecialFunctions
@@ -0,0 +1,63 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Gael Guennebaud <g.gael@free.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPECIALFUNCTIONS_MODULE
+#define EIGEN_SPECIALFUNCTIONS_MODULE
+
+#include <math.h>
+
+#include "../../Eigen/Core"
+
+#include "../../Eigen/src/Core/util/DisableStupidWarnings.h"
+
+namespace Eigen {
+
+/**
+  * \defgroup SpecialFunctions_Module Special math functions module
+  *
+  * This module features additional coefficient-wise math functions available
+  * within the numext:: namespace for the scalar version, and as method and/or free
+  * functions of Array. Those include:
+  *
+  * - erf
+  * - erfc
+  * - lgamma
+  * - igamma
+  * - igammac
+  * - digamma
+  * - polygamma
+  * - zeta
+  * - betainc
+  *
+  * \code
+  * #include <unsupported/Eigen/SpecialFunctions>
+  * \endcode
+  */
+//@{
+
+}
+
+#include "src/SpecialFunctions/SpecialFunctionsImpl.h"
+#include "src/SpecialFunctions/SpecialFunctionsPacketMath.h"
+#include "src/SpecialFunctions/SpecialFunctionsHalf.h"
+#include "src/SpecialFunctions/SpecialFunctionsFunctors.h"
+#include "src/SpecialFunctions/SpecialFunctionsArrayAPI.h"
+
+#if defined EIGEN_VECTORIZE_CUDA
+  #include "src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h"
+#endif
+
+namespace Eigen {
+//@}
+}
+
+
+#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_SPECIALFUNCTIONS_MODULE

Index: 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
+++ 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
@@ -18,41 +18,64 @@
 public:
   AutoDiffJacobian() : Functor() {}
   AutoDiffJacobian(const Functor& f) : Functor(f) {}
 
   // forward constructors
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  template<typename... T>
+  AutoDiffJacobian(const T& ...Values) : Functor(Values...) {}
+#else
   template<typename T0>
   AutoDiffJacobian(const T0& a0) : Functor(a0) {}
   template<typename T0, typename T1>
   AutoDiffJacobian(const T0& a0, const T1& a1) : Functor(a0, a1) {}
   template<typename T0, typename T1, typename T2>
   AutoDiffJacobian(const T0& a0, const T1& a1, const T2& a2) : Functor(a0, a1, a2) {}
-
-  enum {
-    InputsAtCompileTime = Functor::InputsAtCompileTime,
-    ValuesAtCompileTime = Functor::ValuesAtCompileTime
-  };
+#endif
 
   typedef typename Functor::InputType InputType;
   typedef typename Functor::ValueType ValueType;
-  typedef typename Functor::JacobianType JacobianType;
-  typedef typename JacobianType::Scalar Scalar;
+  typedef typename ValueType::Scalar Scalar;
+
+  enum {
+    InputsAtCompileTime = InputType::RowsAtCompileTime,
+    ValuesAtCompileTime = ValueType::RowsAtCompileTime
+  };
+
+  typedef Matrix<Scalar, ValuesAtCompileTime, InputsAtCompileTime> JacobianType;
   typedef typename JacobianType::Index Index;
 
-  typedef Matrix<Scalar,InputsAtCompileTime,1> DerivativeType;
+  typedef Matrix<Scalar, InputsAtCompileTime, 1> DerivativeType;
   typedef AutoDiffScalar<DerivativeType> ActiveScalar;
-
 
   typedef Matrix<ActiveScalar, InputsAtCompileTime, 1> ActiveInput;
   typedef Matrix<ActiveScalar, ValuesAtCompileTime, 1> ActiveValue;
 
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  // Some compilers don't accept variadic parameters after a default parameter,
+  // i.e., we can't just write _jac=0 but we need to overload operator():
+  EIGEN_STRONG_INLINE
+  void operator() (const InputType& x, ValueType* v) const
+  {
+      this->operator()(x, v, 0);
+  }
+  template<typename... ParamsType>
+  void operator() (const InputType& x, ValueType* v, JacobianType* _jac,
+                   const ParamsType&... Params) const
+#else
   void operator() (const InputType& x, ValueType* v, JacobianType* _jac=0) const
+#endif
   {
     eigen_assert(v!=0);
+
     if (!_jac)
     {
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+      Functor::operator()(x, v, Params...);
+#else
       Functor::operator()(x, v);
+#endif
       return;
     }
 
     JacobianType& jac = *_jac;
 
@@ -59,25 +82,27 @@
     ActiveInput ax = x.template cast<ActiveScalar>();
     ActiveValue av(jac.rows());
 
     if(InputsAtCompileTime==Dynamic)
       for (Index j=0; j<jac.rows(); j++)
-        av[j].derivatives().resize(this->inputs());
+        av[j].derivatives().resize(x.rows());
 
     for (Index i=0; i<jac.cols(); i++)
-      ax[i].derivatives() = DerivativeType::Unit(this->inputs(),i);
+      ax[i].derivatives() = DerivativeType::Unit(x.rows(),i);
 
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+    Functor::operator()(ax, &av, Params...);
+#else
     Functor::operator()(ax, &av);
+#endif
 
     for (Index i=0; i<jac.rows(); i++)
     {
       (*v)[i] = av[i].value();
       jac.row(i) = av[i].derivatives();
     }
   }
-protected:
-
 };
 
 }
 
 #endif // EIGEN_AUTODIFF_JACOBIAN_H

Index: 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
+++ 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h
@@ -27,10 +27,17 @@
 }
 
 template<typename _DerType, bool Enable> struct auto_diff_special_op;
 
 } // end namespace internal
+
+template<typename _DerType> class AutoDiffScalar;
+
+template<typename NewDerType>
+inline AutoDiffScalar<NewDerType> MakeAutoDiffScalar(const typename NewDerType::Scalar& value, const NewDerType &der) {
+  return AutoDiffScalar<NewDerType>(value,der);
+}
 
 /** \class AutoDiffScalar
   * \brief A scalar type replacement with automatic differentation capability
   *
   * \param _DerType the vector type used to store/represent the derivatives. The base scalar type
@@ -58,11 +65,11 @@
 
 template<typename _DerType>
 class AutoDiffScalar
   : public internal::auto_diff_special_op
             <_DerType, !internal::is_same<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar,
-                                        typename NumTraits<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar>::Real>::value>
+                                          typename NumTraits<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar>::Real>::value>
 {
   public:
     typedef internal::auto_diff_special_op
             <_DerType, !internal::is_same<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar,
                        typename NumTraits<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar>::Real>::value> Base;
@@ -97,11 +104,17 @@
     AutoDiffScalar(const Scalar& value, const DerType& der)
       : m_value(value), m_derivatives(der)
     {}
 
     template<typename OtherDerType>
-    AutoDiffScalar(const AutoDiffScalar<OtherDerType>& other)
+    AutoDiffScalar(const AutoDiffScalar<OtherDerType>& other
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    , typename internal::enable_if<
+            internal::is_same<Scalar, typename internal::traits<typename internal::remove_all<OtherDerType>::type>::Scalar>::value
+        &&  internal::is_convertible<OtherDerType,DerType>::value , void*>::type = 0
+#endif
+    )
       : m_value(other.value()), m_derivatives(other.derivatives())
     {}
 
     friend  std::ostream & operator << (std::ostream & s, const AutoDiffScalar& a)
     {
@@ -124,10 +137,18 @@
     {
       m_value = other.value();
       m_derivatives = other.derivatives();
       return *this;
     }
+
+    inline AutoDiffScalar& operator=(const Scalar& other)
+    {
+      m_value = other;
+      if(m_derivatives.size()>0)
+        m_derivatives.setZero();
+      return *this;
+    }
 
 //     inline operator const Scalar& () const { return m_value; }
 //     inline operator Scalar& () { return m_value; }
 
     inline const Scalar& value() const { return m_value; }
@@ -243,24 +264,20 @@
       return AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >(
         -m_value,
         -m_derivatives);
     }
 
-    inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >
+    inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) >
     operator*(const Scalar& other) const
     {
-      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >(
-        m_value * other,
-        (m_derivatives * other));
+      return MakeAutoDiffScalar(m_value * other, m_derivatives * other);
     }
 
-    friend inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >
+    friend inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) >
     operator*(const Scalar& other, const AutoDiffScalar& a)
     {
-      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >(
-        a.value() * other,
-        a.derivatives() * other);
+      return MakeAutoDiffScalar(a.value() * other, a.derivatives() * other);
     }
 
 //     inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
 //     operator*(const Real& other) const
 //     {
@@ -275,24 +292,20 @@
 //       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
 //         a.value() * other,
 //         a.derivatives() * other);
 //     }
 
-    inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >
+    inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) >
     operator/(const Scalar& other) const
     {
-      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >(
-        m_value / other,
-        (m_derivatives * (Scalar(1)/other)));
+      return MakeAutoDiffScalar(m_value / other, (m_derivatives * (Scalar(1)/other)));
     }
 
-    friend inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >
+    friend inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) >
     operator/(const Scalar& other, const AutoDiffScalar& a)
     {
-      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >(
-        other / a.value(),
-        a.derivatives() * (Scalar(-other) / (a.value()*a.value())));
+      return MakeAutoDiffScalar(other / a.value(), a.derivatives() * (Scalar(-other) / (a.value()*a.value())));
     }
 
 //     inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
 //     operator/(const Real& other) const
 //     {
@@ -308,38 +321,33 @@
 //         other / a.value(),
 //         a.derivatives() * (-Real(1)/other));
 //     }
 
     template<typename OtherDerType>
-    inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>,
-        const CwiseBinaryOp<internal::scalar_difference_op<Scalar>,
-          const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType>,
-          const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const typename internal::remove_all<OtherDerType>::type > > > >
+    inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(
+        CwiseBinaryOp<internal::scalar_difference_op<Scalar> EIGEN_COMMA
+          const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) EIGEN_COMMA
+          const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<OtherDerType>::type,Scalar,product) >,Scalar,product) >
     operator/(const AutoDiffScalar<OtherDerType>& other) const
     {
       internal::make_coherent(m_derivatives, other.derivatives());
-      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>,
-        const CwiseBinaryOp<internal::scalar_difference_op<Scalar>,
-          const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType>,
-          const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const typename internal::remove_all<OtherDerType>::type > > > >(
+      return MakeAutoDiffScalar(
         m_value / other.value(),
-          ((m_derivatives * other.value()) - (m_value * other.derivatives()))
+          ((m_derivatives * other.value()) - (other.derivatives() * m_value))
         * (Scalar(1)/(other.value()*other.value())));
     }
 
     template<typename OtherDerType>
     inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
-        const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType>,
-        const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const typename internal::remove_all<OtherDerType>::type> > >
+        const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product),
+        const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<OtherDerType>::type,Scalar,product) > >
     operator*(const AutoDiffScalar<OtherDerType>& other) const
     {
       internal::make_coherent(m_derivatives, other.derivatives());
-      return AutoDiffScalar<const CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
-        const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType>,
-        const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const typename internal::remove_all<OtherDerType>::type > > >(
+      return MakeAutoDiffScalar(
         m_value * other.value(),
-        (m_derivatives * other.value()) + (m_value * other.derivatives()));
+        (m_derivatives * other.value()) + (other.derivatives() * m_value));
     }
 
     inline AutoDiffScalar& operator*=(const Scalar& other)
     {
       *this = *this * other;
@@ -412,22 +420,22 @@
     derived().value() += other;
     return derived();
   }
 
 
-  inline const AutoDiffScalar<typename CwiseUnaryOp<scalar_multiple2_op<Scalar,Real>, DerType>::Type >
+  inline const AutoDiffScalar<typename CwiseUnaryOp<bind2nd_op<scalar_product_op<Scalar,Real> >, DerType>::Type >
   operator*(const Real& other) const
   {
-    return AutoDiffScalar<typename CwiseUnaryOp<scalar_multiple2_op<Scalar,Real>, DerType>::Type >(
+    return AutoDiffScalar<typename CwiseUnaryOp<bind2nd_op<scalar_product_op<Scalar,Real> >, DerType>::Type >(
       derived().value() * other,
       derived().derivatives() * other);
   }
 
-  friend inline const AutoDiffScalar<typename CwiseUnaryOp<scalar_multiple2_op<Scalar,Real>, DerType>::Type >
+  friend inline const AutoDiffScalar<typename CwiseUnaryOp<bind1st_op<scalar_product_op<Real,Scalar> >, DerType>::Type >
   operator*(const Real& other, const AutoDiffScalar<_DerType>& a)
   {
-    return AutoDiffScalar<typename CwiseUnaryOp<scalar_multiple2_op<Scalar,Real>, DerType>::Type >(
+    return AutoDiffScalar<typename CwiseUnaryOp<bind1st_op<scalar_product_op<Real,Scalar> >, DerType>::Type >(
       a.value() * other,
       a.derivatives() * other);
   }
 
   inline AutoDiffScalar<_DerType>& operator*=(const Scalar& other)
@@ -487,47 +495,48 @@
       b.setZero();
     }
   }
 };
 
-template<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols>
-struct scalar_product_traits<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>,A_Scalar>
-{
-  enum { Defined = 1 };
-  typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> ReturnType;
-};
-
-template<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols>
-struct scalar_product_traits<A_Scalar, Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> >
-{
-  enum { Defined = 1 };
-  typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> ReturnType;
-};
-
-template<typename DerType>
-struct scalar_product_traits<AutoDiffScalar<DerType>,typename DerType::Scalar>
-{
-  enum { Defined = 1 };
-  typedef AutoDiffScalar<DerType> ReturnType;
-};
-
-template<typename DerType>
-struct scalar_product_traits<typename DerType::Scalar,AutoDiffScalar<DerType> >
-{
-  enum { Defined = 1 };
-  typedef AutoDiffScalar<DerType> ReturnType;
-};
-
-} // end namespace internal
-
-#define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \
-  template<typename DerType> \
-  inline const Eigen::AutoDiffScalar<Eigen::CwiseUnaryOp<Eigen::internal::scalar_multiple_op<typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar>, const typename Eigen::internal::remove_all<DerType>::type> > \
-  FUNC(const Eigen::AutoDiffScalar<DerType>& x) { \
-    using namespace Eigen; \
-    typedef typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar Scalar; \
-    typedef AutoDiffScalar<CwiseUnaryOp<Eigen::internal::scalar_multiple_op<Scalar>, const typename Eigen::internal::remove_all<DerType>::type> > ReturnType; \
+} // end namespace internal
+
+template<typename DerType, typename BinOp>
+struct ScalarBinaryOpTraits<AutoDiffScalar<DerType>,typename DerType::Scalar,BinOp>
+{
+  typedef AutoDiffScalar<DerType> ReturnType;
+};
+
+template<typename DerType, typename BinOp>
+struct ScalarBinaryOpTraits<typename DerType::Scalar,AutoDiffScalar<DerType>, BinOp>
+{
+  typedef AutoDiffScalar<DerType> ReturnType;
+};
+
+
+// The following is an attempt to let Eigen's known about expression template, but that's more tricky!
+
+// template<typename DerType, typename BinOp>
+// struct ScalarBinaryOpTraits<AutoDiffScalar<DerType>,AutoDiffScalar<DerType>, BinOp>
+// {
+//   enum { Defined = 1 };
+//   typedef AutoDiffScalar<typename DerType::PlainObject> ReturnType;
+// };
+//
+// template<typename DerType1,typename DerType2, typename BinOp>
+// struct ScalarBinaryOpTraits<AutoDiffScalar<DerType1>,AutoDiffScalar<DerType2>, BinOp>
+// {
+//   enum { Defined = 1 };//internal::is_same<typename DerType1::Scalar,typename DerType2::Scalar>::value };
+//   typedef AutoDiffScalar<typename DerType1::PlainObject> ReturnType;
+// };
+
+#define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \
+  template<typename DerType> \
+  inline const Eigen::AutoDiffScalar< \
+  EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename Eigen::internal::remove_all<DerType>::type, typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar, product) > \
+  FUNC(const Eigen::AutoDiffScalar<DerType>& x) { \
+    using namespace Eigen; \
+    EIGEN_UNUSED typedef typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar Scalar; \
     CODE; \
   }
 
 template<typename DerType>
 inline const AutoDiffScalar<DerType>& conj(const AutoDiffScalar<DerType>& x)  { return x; }
@@ -534,109 +543,151 @@
 template<typename DerType>
 inline const AutoDiffScalar<DerType>& real(const AutoDiffScalar<DerType>& x)  { return x; }
 template<typename DerType>
 inline typename DerType::Scalar imag(const AutoDiffScalar<DerType>&)    { return 0.; }
 template<typename DerType, typename T>
-inline AutoDiffScalar<DerType> (min)(const AutoDiffScalar<DerType>& x, const T& y)    { return (x <= y ? x : y); }
+inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (min)(const AutoDiffScalar<DerType>& x, const T& y) {
+  typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> ADS;
+  return (x <= y ? ADS(x) : ADS(y));
+}
+template<typename DerType, typename T>
+inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (max)(const AutoDiffScalar<DerType>& x, const T& y) {
+  typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> ADS;
+  return (x >= y ? ADS(x) : ADS(y));
+}
 template<typename DerType, typename T>
-inline AutoDiffScalar<DerType> (max)(const AutoDiffScalar<DerType>& x, const T& y)    { return (x >= y ? x : y); }
+inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (min)(const T& x, const AutoDiffScalar<DerType>& y) {
+  typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> ADS;
+  return (x < y ? ADS(x) : ADS(y));
+}
 template<typename DerType, typename T>
-inline AutoDiffScalar<DerType> (min)(const T& x, const AutoDiffScalar<DerType>& y)    { return (x < y ? x : y); }
-template<typename DerType, typename T>
-inline AutoDiffScalar<DerType> (max)(const T& x, const AutoDiffScalar<DerType>& y)    { return (x > y ? x : y); }
+inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (max)(const T& x, const AutoDiffScalar<DerType>& y) {
+  typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> ADS;
+  return (x > y ? ADS(x) : ADS(y));
+}
+template<typename DerType>
+inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (min)(const AutoDiffScalar<DerType>& x, const AutoDiffScalar<DerType>& y) {
+  return (x.value() < y.value() ? x : y);
+}
+template<typename DerType>
+inline AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> (max)(const AutoDiffScalar<DerType>& x, const AutoDiffScalar<DerType>& y) {
+  return (x.value() >= y.value() ? x : y);
+}
+
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs,
   using std::abs;
-  return ReturnType(abs(x.value()), x.derivatives() * (x.value()<0 ? -1 : 1) );)
+  return Eigen::MakeAutoDiffScalar(abs(x.value()), x.derivatives() * (x.value()<0 ? -1 : 1) );)
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs2,
   using numext::abs2;
-  return ReturnType(abs2(x.value()), x.derivatives() * (Scalar(2)*x.value()));)
+  return Eigen::MakeAutoDiffScalar(abs2(x.value()), x.derivatives() * (Scalar(2)*x.value()));)
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sqrt,
   using std::sqrt;
   Scalar sqrtx = sqrt(x.value());
-  return ReturnType(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));)
+  return Eigen::MakeAutoDiffScalar(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));)
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cos,
   using std::cos;
   using std::sin;
-  return ReturnType(cos(x.value()), x.derivatives() * (-sin(x.value())));)
+  return Eigen::MakeAutoDiffScalar(cos(x.value()), x.derivatives() * (-sin(x.value())));)
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sin,
   using std::sin;
   using std::cos;
-  return ReturnType(sin(x.value()),x.derivatives() * cos(x.value()));)
+  return Eigen::MakeAutoDiffScalar(sin(x.value()),x.derivatives() * cos(x.value()));)
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(exp,
   using std::exp;
   Scalar expx = exp(x.value());
-  return ReturnType(expx,x.derivatives() * expx);)
+  return Eigen::MakeAutoDiffScalar(expx,x.derivatives() * expx);)
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(log,
   using std::log;
-  return ReturnType(log(x.value()),x.derivatives() * (Scalar(1)/x.value()));)
+  return Eigen::MakeAutoDiffScalar(log(x.value()),x.derivatives() * (Scalar(1)/x.value()));)
 
 template<typename DerType>
-inline const Eigen::AutoDiffScalar<Eigen::CwiseUnaryOp<Eigen::internal::scalar_multiple_op<typename Eigen::internal::traits<DerType>::Scalar>, const DerType> >
-pow(const Eigen::AutoDiffScalar<DerType>& x, typename Eigen::internal::traits<DerType>::Scalar y)
+inline const Eigen::AutoDiffScalar<
+EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<DerType>::type,typename internal::traits<typename internal::remove_all<DerType>::type>::Scalar,product) >
+pow(const Eigen::AutoDiffScalar<DerType> &x, const typename internal::traits<typename internal::remove_all<DerType>::type>::Scalar &y)
 {
   using namespace Eigen;
-  typedef typename Eigen::internal::traits<DerType>::Scalar Scalar;
-  return AutoDiffScalar<CwiseUnaryOp<Eigen::internal::scalar_multiple_op<Scalar>, const DerType> >(
-    std::pow(x.value(),y),
-    x.derivatives() * (y * std::pow(x.value(),y-1)));
+  using std::pow;
+  return Eigen::MakeAutoDiffScalar(pow(x.value(),y), x.derivatives() * (y * pow(x.value(),y-1)));
 }
 
 
 template<typename DerTypeA,typename DerTypeB>
-inline const AutoDiffScalar<Matrix<typename internal::traits<DerTypeA>::Scalar,Dynamic,1> >
+inline const AutoDiffScalar<Matrix<typename internal::traits<typename internal::remove_all<DerTypeA>::type>::Scalar,Dynamic,1> >
 atan2(const AutoDiffScalar<DerTypeA>& a, const AutoDiffScalar<DerTypeB>& b)
 {
   using std::atan2;
-  using std::max;
-  typedef typename internal::traits<DerTypeA>::Scalar Scalar;
+  typedef typename internal::traits<typename internal::remove_all<DerTypeA>::type>::Scalar Scalar;
   typedef AutoDiffScalar<Matrix<Scalar,Dynamic,1> > PlainADS;
   PlainADS ret;
   ret.value() = atan2(a.value(), b.value());
   
-  Scalar tmp2 = a.value() * a.value();
-  Scalar tmp3 = b.value() * b.value();
-  Scalar tmp4 = tmp3/(tmp2+tmp3);
+  Scalar squared_hypot = a.value() * a.value() + b.value() * b.value();
   
-  if (tmp4!=0)
-    ret.derivatives() = (a.derivatives() * b.value() - a.value() * b.derivatives()) * (tmp2+tmp3);
+  // if (squared_hypot==0) the derivation is undefined and the following results in a NaN:
+  ret.derivatives() = (a.derivatives() * b.value() - a.value() * b.derivatives()) / squared_hypot;
 
   return ret;
 }
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(tan,
   using std::tan;
   using std::cos;
-  return ReturnType(tan(x.value()),x.derivatives() * (Scalar(1)/numext::abs2(cos(x.value()))));)
+  return Eigen::MakeAutoDiffScalar(tan(x.value()),x.derivatives() * (Scalar(1)/numext::abs2(cos(x.value()))));)
 
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(asin,
   using std::sqrt;
   using std::asin;
-  return ReturnType(asin(x.value()),x.derivatives() * (Scalar(1)/sqrt(1-numext::abs2(x.value()))));)
+  return Eigen::MakeAutoDiffScalar(asin(x.value()),x.derivatives() * (Scalar(1)/sqrt(1-numext::abs2(x.value()))));)
   
 EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(acos,
   using std::sqrt;
   using std::acos;
-  return ReturnType(acos(x.value()),x.derivatives() * (Scalar(-1)/sqrt(1-numext::abs2(x.value()))));)
+  return Eigen::MakeAutoDiffScalar(acos(x.value()),x.derivatives() * (Scalar(-1)/sqrt(1-numext::abs2(x.value()))));)
+
+EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(tanh,
+  using std::cosh;
+  using std::tanh;
+  return Eigen::MakeAutoDiffScalar(tanh(x.value()),x.derivatives() * (Scalar(1)/numext::abs2(cosh(x.value()))));)
+
+EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sinh,
+  using std::sinh;
+  using std::cosh;
+  return Eigen::MakeAutoDiffScalar(sinh(x.value()),x.derivatives() * cosh(x.value()));)
+
+EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cosh,
+  using std::sinh;
+  using std::cosh;
+  return Eigen::MakeAutoDiffScalar(cosh(x.value()),x.derivatives() * sinh(x.value()));)
 
 #undef EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY
 
 template<typename DerType> struct NumTraits<AutoDiffScalar<DerType> >
-  : NumTraits< typename NumTraits<typename DerType::Scalar>::Real >
+  : NumTraits< typename NumTraits<typename internal::remove_all<DerType>::type::Scalar>::Real >
 {
-  typedef AutoDiffScalar<Matrix<typename NumTraits<typename DerType::Scalar>::Real,DerType::RowsAtCompileTime,DerType::ColsAtCompileTime> > Real;
+  typedef typename internal::remove_all<DerType>::type DerTypeCleaned;
+  typedef AutoDiffScalar<Matrix<typename NumTraits<typename DerTypeCleaned::Scalar>::Real,DerTypeCleaned::RowsAtCompileTime,DerTypeCleaned::ColsAtCompileTime,
+                                0, DerTypeCleaned::MaxRowsAtCompileTime, DerTypeCleaned::MaxColsAtCompileTime> > Real;
   typedef AutoDiffScalar<DerType> NonInteger;
-  typedef AutoDiffScalar<DerType>& Nested;
+  typedef AutoDiffScalar<DerType> Nested;
+  typedef typename NumTraits<typename DerTypeCleaned::Scalar>::Literal Literal;
   enum{
     RequireInitialization = 1
   };
 };
 
 }
 
+namespace std {
+template <typename T>
+class numeric_limits<Eigen::AutoDiffScalar<T> >
+  : public numeric_limits<typename T::Scalar> {};
+
+}  // namespace std
+
 #endif // EIGEN_AUTODIFF_SCALAR_H

DELETED 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/AutoDiff/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_AutoDiff_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_AutoDiff_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/AutoDiff COMPONENT Devel
-  )

DELETED 3rd_party/eigen/unsupported/Eigen/src/BVH/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/BVH/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/BVH/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/BVH/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_BVH_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_BVH_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/BVH COMPONENT Devel
-  )

DELETED 3rd_party/eigen/unsupported/Eigen/src/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/CMakeLists.txt
@@ -1,13 +0,0 @@
-ADD_SUBDIRECTORY(AutoDiff)
-ADD_SUBDIRECTORY(BVH)
-ADD_SUBDIRECTORY(FFT)
-ADD_SUBDIRECTORY(IterativeSolvers)
-ADD_SUBDIRECTORY(MatrixFunctions)
-ADD_SUBDIRECTORY(MoreVectorization)
-ADD_SUBDIRECTORY(NonLinearOptimization)
-ADD_SUBDIRECTORY(NumericalDiff)
-ADD_SUBDIRECTORY(Polynomials)
-ADD_SUBDIRECTORY(Skyline)
-ADD_SUBDIRECTORY(SparseExtra)
-ADD_SUBDIRECTORY(KroneckerProduct)
-ADD_SUBDIRECTORY(Splines)

Index: 3rd_party/eigen/unsupported/Eigen/src/Eigenvalues/ArpackSelfAdjointEigenSolver.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Eigenvalues/ArpackSelfAdjointEigenSolver.h
+++ 3rd_party/eigen/unsupported/Eigen/src/Eigenvalues/ArpackSelfAdjointEigenSolver.h
@@ -626,19 +626,19 @@
       m_nbrConverged  = iparam[4];
 
       m_info = Success;
     }
 
-    delete select;
+    delete[] select;
   }
 
-  delete v;
-  delete iparam;
-  delete ipntr;
-  delete workd;
-  delete workl;
-  delete resid;
+  delete[] v;
+  delete[] iparam;
+  delete[] ipntr;
+  delete[] workd;
+  delete[] workl;
+  delete[] resid;
 
   m_isInitialized = true;
 
   return *this;
 }

ADDED   3rd_party/eigen/unsupported/Eigen/src/EulerAngles/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/CMakeLists.txt
@@ -0,0 +1,6 @@
+FILE(GLOB Eigen_EulerAngles_SRCS "*.h")
+
+INSTALL(FILES
+  ${Eigen_EulerAngles_SRCS}
+  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/EulerAngles COMPONENT Devel
+  )

ADDED   3rd_party/eigen/unsupported/Eigen/src/EulerAngles/EulerAngles.h
Index: 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/EulerAngles.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/EulerAngles.h
+++ 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/EulerAngles.h
@@ -0,0 +1,386 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Tal Hadad <tal_hd@hotmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_EULERANGLESCLASS_H// TODO: Fix previous "EIGEN_EULERANGLES_H" definition?
+#define EIGEN_EULERANGLESCLASS_H
+
+namespace Eigen
+{
+  /*template<typename Other,
+         int OtherRows=Other::RowsAtCompileTime,
+         int OtherCols=Other::ColsAtCompileTime>
+  struct ei_eulerangles_assign_impl;*/
+
+  /** \class EulerAngles
+    *
+    * \ingroup EulerAngles_Module
+    *
+    * \brief Represents a rotation in a 3 dimensional space as three Euler angles.
+    *
+    * Euler rotation is a set of three rotation of three angles over three fixed axes, defined by the EulerSystem given as a template parameter.
+    * 
+    * Here is how intrinsic Euler angles works:
+    *  - first, rotate the axes system over the alpha axis in angle alpha
+    *  - then, rotate the axes system over the beta axis(which was rotated in the first stage) in angle beta
+    *  - then, rotate the axes system over the gamma axis(which was rotated in the two stages above) in angle gamma
+    *
+    * \note This class support only intrinsic Euler angles for simplicity,
+    *  see EulerSystem how to easily overcome this for extrinsic systems.
+    *
+    * ### Rotation representation and conversions ###
+    *
+    * It has been proved(see Wikipedia link below) that every rotation can be represented
+    *  by Euler angles, but there is no singular representation (e.g. unlike rotation matrices).
+    * Therefore, you can convert from Eigen rotation and to them
+    *  (including rotation matrices, which is not called "rotations" by Eigen design).
+    *
+    * Euler angles usually used for:
+    *  - convenient human representation of rotation, especially in interactive GUI.
+    *  - gimbal systems and robotics
+    *  - efficient encoding(i.e. 3 floats only) of rotation for network protocols.
+    *
+    * However, Euler angles are slow comparing to quaternion or matrices,
+    *  because their unnatural math definition, although it's simple for human.
+    * To overcome this, this class provide easy movement from the math friendly representation
+    *  to the human friendly representation, and vise-versa.
+    *
+    * All the user need to do is a safe simple C++ type conversion,
+    *  and this class take care for the math.
+    * Additionally, some axes related computation is done in compile time.
+    *
+    * #### Euler angles ranges in conversions ####
+    *
+    * When converting some rotation to Euler angles, there are some ways you can guarantee
+    *  the Euler angles ranges.
+    *
+    * #### implicit ranges ####
+    * When using implicit ranges, all angles are guarantee to be in the range [-PI, +PI],
+    *  unless you convert from some other Euler angles.
+    * In this case, the range is __undefined__ (might be even less than -PI or greater than +2*PI).
+    * \sa EulerAngles(const MatrixBase<Derived>&)
+    * \sa EulerAngles(const RotationBase<Derived, 3>&)
+    *
+    * #### explicit ranges ####
+    * When using explicit ranges, all angles are guarantee to be in the range you choose.
+    * In the range Boolean parameter, you're been ask whether you prefer the positive range or not:
+    * - _true_ - force the range between [0, +2*PI]
+    * - _false_ - force the range between [-PI, +PI]
+    *
+    * ##### compile time ranges #####
+    * This is when you have compile time ranges and you prefer to
+    *  use template parameter. (e.g. for performance)
+    * \sa FromRotation()
+    *
+    * ##### run-time time ranges #####
+    * Run-time ranges are also supported.
+    * \sa EulerAngles(const MatrixBase<Derived>&, bool, bool, bool)
+    * \sa EulerAngles(const RotationBase<Derived, 3>&, bool, bool, bool)
+    *
+    * ### Convenient user typedefs ###
+    *
+    * Convenient typedefs for EulerAngles exist for float and double scalar,
+    *  in a form of EulerAngles{A}{B}{C}{scalar},
+    *  e.g. \ref EulerAnglesXYZd, \ref EulerAnglesZYZf.
+    *
+    * Only for positive axes{+x,+y,+z} Euler systems are have convenient typedef.
+    * If you need negative axes{-x,-y,-z}, it is recommended to create you own typedef with
+    *  a word that represent what you need.
+    *
+    * ### Example ###
+    *
+    * \include EulerAngles.cpp
+    * Output: \verbinclude EulerAngles.out
+    *
+    * ### Additional reading ###
+    *
+    * If you're want to get more idea about how Euler system work in Eigen see EulerSystem.
+    *
+    * More information about Euler angles: https://en.wikipedia.org/wiki/Euler_angles
+    *
+    * \tparam _Scalar the scalar type, i.e., the type of the angles.
+    *
+    * \tparam _System the EulerSystem to use, which represents the axes of rotation.
+    */
+  template <typename _Scalar, class _System>
+  class EulerAngles : public RotationBase<EulerAngles<_Scalar, _System>, 3>
+  {
+    public:
+      /** the scalar type of the angles */
+      typedef _Scalar Scalar;
+      
+      /** the EulerSystem to use, which represents the axes of rotation. */
+      typedef _System System;
+    
+      typedef Matrix<Scalar,3,3> Matrix3; /*!< the equivalent rotation matrix type */
+      typedef Matrix<Scalar,3,1> Vector3; /*!< the equivalent 3 dimension vector type */
+      typedef Quaternion<Scalar> QuaternionType; /*!< the equivalent quaternion type */
+      typedef AngleAxis<Scalar> AngleAxisType; /*!< the equivalent angle-axis type */
+      
+      /** \returns the axis vector of the first (alpha) rotation */
+      static Vector3 AlphaAxisVector() {
+        const Vector3& u = Vector3::Unit(System::AlphaAxisAbs - 1);
+        return System::IsAlphaOpposite ? -u : u;
+      }
+      
+      /** \returns the axis vector of the second (beta) rotation */
+      static Vector3 BetaAxisVector() {
+        const Vector3& u = Vector3::Unit(System::BetaAxisAbs - 1);
+        return System::IsBetaOpposite ? -u : u;
+      }
+      
+      /** \returns the axis vector of the third (gamma) rotation */
+      static Vector3 GammaAxisVector() {
+        const Vector3& u = Vector3::Unit(System::GammaAxisAbs - 1);
+        return System::IsGammaOpposite ? -u : u;
+      }
+
+    private:
+      Vector3 m_angles;
+
+    public:
+      /** Default constructor without initialization. */
+      EulerAngles() {}
+      /** Constructs and initialize Euler angles(\p alpha, \p beta, \p gamma). */
+      EulerAngles(const Scalar& alpha, const Scalar& beta, const Scalar& gamma) :
+        m_angles(alpha, beta, gamma) {}
+      
+      /** Constructs and initialize Euler angles from a 3x3 rotation matrix \p m.
+        *
+        * \note All angles will be in the range [-PI, PI].
+      */
+      template<typename Derived>
+      EulerAngles(const MatrixBase<Derived>& m) { *this = m; }
+      
+      /** Constructs and initialize Euler angles from a 3x3 rotation matrix \p m,
+        *  with options to choose for each angle the requested range.
+        *
+        * If positive range is true, then the specified angle will be in the range [0, +2*PI].
+        * Otherwise, the specified angle will be in the range [-PI, +PI].
+        *
+        * \param m The 3x3 rotation matrix to convert
+        * \param positiveRangeAlpha If true, alpha will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        * \param positiveRangeBeta If true, beta will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        * \param positiveRangeGamma If true, gamma will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+      */
+      template<typename Derived>
+      EulerAngles(
+        const MatrixBase<Derived>& m,
+        bool positiveRangeAlpha,
+        bool positiveRangeBeta,
+        bool positiveRangeGamma) {
+        
+        System::CalcEulerAngles(*this, m, positiveRangeAlpha, positiveRangeBeta, positiveRangeGamma);
+      }
+      
+      /** Constructs and initialize Euler angles from a rotation \p rot.
+        *
+        * \note All angles will be in the range [-PI, PI], unless \p rot is an EulerAngles.
+        *  If rot is an EulerAngles, expected EulerAngles range is __undefined__.
+        *  (Use other functions here for enforcing range if this effect is desired)
+      */
+      template<typename Derived>
+      EulerAngles(const RotationBase<Derived, 3>& rot) { *this = rot; }
+      
+      /** Constructs and initialize Euler angles from a rotation \p rot,
+        *  with options to choose for each angle the requested range.
+        *
+        * If positive range is true, then the specified angle will be in the range [0, +2*PI].
+        * Otherwise, the specified angle will be in the range [-PI, +PI].
+        *
+        * \param rot The 3x3 rotation matrix to convert
+        * \param positiveRangeAlpha If true, alpha will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        * \param positiveRangeBeta If true, beta will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        * \param positiveRangeGamma If true, gamma will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+      */
+      template<typename Derived>
+      EulerAngles(
+        const RotationBase<Derived, 3>& rot,
+        bool positiveRangeAlpha,
+        bool positiveRangeBeta,
+        bool positiveRangeGamma) {
+        
+        System::CalcEulerAngles(*this, rot.toRotationMatrix(), positiveRangeAlpha, positiveRangeBeta, positiveRangeGamma);
+      }
+
+      /** \returns The angle values stored in a vector (alpha, beta, gamma). */
+      const Vector3& angles() const { return m_angles; }
+      /** \returns A read-write reference to the angle values stored in a vector (alpha, beta, gamma). */
+      Vector3& angles() { return m_angles; }
+
+      /** \returns The value of the first angle. */
+      Scalar alpha() const { return m_angles[0]; }
+      /** \returns A read-write reference to the angle of the first angle. */
+      Scalar& alpha() { return m_angles[0]; }
+
+      /** \returns The value of the second angle. */
+      Scalar beta() const { return m_angles[1]; }
+      /** \returns A read-write reference to the angle of the second angle. */
+      Scalar& beta() { return m_angles[1]; }
+
+      /** \returns The value of the third angle. */
+      Scalar gamma() const { return m_angles[2]; }
+      /** \returns A read-write reference to the angle of the third angle. */
+      Scalar& gamma() { return m_angles[2]; }
+
+      /** \returns The Euler angles rotation inverse (which is as same as the negative),
+        *  (-alpha, -beta, -gamma).
+      */
+      EulerAngles inverse() const
+      {
+        EulerAngles res;
+        res.m_angles = -m_angles;
+        return res;
+      }
+
+      /** \returns The Euler angles rotation negative (which is as same as the inverse),
+        *  (-alpha, -beta, -gamma).
+      */
+      EulerAngles operator -() const
+      {
+        return inverse();
+      }
+      
+      /** Constructs and initialize Euler angles from a 3x3 rotation matrix \p m,
+        *  with options to choose for each angle the requested range (__only in compile time__).
+        *
+        * If positive range is true, then the specified angle will be in the range [0, +2*PI].
+        * Otherwise, the specified angle will be in the range [-PI, +PI].
+        *
+        * \param m The 3x3 rotation matrix to convert
+        * \tparam positiveRangeAlpha If true, alpha will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        * \tparam positiveRangeBeta If true, beta will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        * \tparam positiveRangeGamma If true, gamma will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        */
+      template<
+        bool PositiveRangeAlpha,
+        bool PositiveRangeBeta,
+        bool PositiveRangeGamma,
+        typename Derived>
+      static EulerAngles FromRotation(const MatrixBase<Derived>& m)
+      {
+        EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(Derived, 3, 3)
+        
+        EulerAngles e;
+        System::template CalcEulerAngles<
+          PositiveRangeAlpha, PositiveRangeBeta, PositiveRangeGamma, _Scalar>(e, m);
+        return e;
+      }
+      
+      /** Constructs and initialize Euler angles from a rotation \p rot,
+        *  with options to choose for each angle the requested range (__only in compile time__).
+        *
+        * If positive range is true, then the specified angle will be in the range [0, +2*PI].
+        * Otherwise, the specified angle will be in the range [-PI, +PI].
+        *
+        * \param rot The 3x3 rotation matrix to convert
+        * \tparam positiveRangeAlpha If true, alpha will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        * \tparam positiveRangeBeta If true, beta will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+        * \tparam positiveRangeGamma If true, gamma will be in [0, 2*PI]. Otherwise, in [-PI, +PI].
+      */
+      template<
+        bool PositiveRangeAlpha,
+        bool PositiveRangeBeta,
+        bool PositiveRangeGamma,
+        typename Derived>
+      static EulerAngles FromRotation(const RotationBase<Derived, 3>& rot)
+      {
+        return FromRotation<PositiveRangeAlpha, PositiveRangeBeta, PositiveRangeGamma>(rot.toRotationMatrix());
+      }
+      
+      /*EulerAngles& fromQuaternion(const QuaternionType& q)
+      {
+        // TODO: Implement it in a faster way for quaternions
+        // According to http://www.euclideanspace.com/maths/geometry/rotations/conversions/quaternionToEuler/
+        //  we can compute only the needed matrix cells and then convert to euler angles. (see ZYX example below)
+        // Currently we compute all matrix cells from quaternion.
+
+        // Special case only for ZYX
+        //Scalar y2 = q.y() * q.y();
+        //m_angles[0] = std::atan2(2*(q.w()*q.z() + q.x()*q.y()), (1 - 2*(y2 + q.z()*q.z())));
+        //m_angles[1] = std::asin( 2*(q.w()*q.y() - q.z()*q.x()));
+        //m_angles[2] = std::atan2(2*(q.w()*q.x() + q.y()*q.z()), (1 - 2*(q.x()*q.x() + y2)));
+      }*/
+      
+      /** Set \c *this from a rotation matrix(i.e. pure orthogonal matrix with determinant of +1). */
+      template<typename Derived>
+      EulerAngles& operator=(const MatrixBase<Derived>& m) {
+        EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(Derived, 3, 3)
+        
+        System::CalcEulerAngles(*this, m);
+        return *this;
+      }
+
+      // TODO: Assign and construct from another EulerAngles (with different system)
+      
+      /** Set \c *this from a rotation. */
+      template<typename Derived>
+      EulerAngles& operator=(const RotationBase<Derived, 3>& rot) {
+        System::CalcEulerAngles(*this, rot.toRotationMatrix());
+        return *this;
+      }
+      
+      // TODO: Support isApprox function
+
+      /** \returns an equivalent 3x3 rotation matrix. */
+      Matrix3 toRotationMatrix() const
+      {
+        return static_cast<QuaternionType>(*this).toRotationMatrix();
+      }
+
+      /** Convert the Euler angles to quaternion. */
+      operator QuaternionType() const
+      {
+        return
+          AngleAxisType(alpha(), AlphaAxisVector()) *
+          AngleAxisType(beta(), BetaAxisVector())   *
+          AngleAxisType(gamma(), GammaAxisVector());
+      }
+      
+      friend std::ostream& operator<<(std::ostream& s, const EulerAngles<Scalar, System>& eulerAngles)
+      {
+        s << eulerAngles.angles().transpose();
+        return s;
+      }
+  };
+
+#define EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(AXES, SCALAR_TYPE, SCALAR_POSTFIX) \
+  /** \ingroup EulerAngles_Module */ \
+  typedef EulerAngles<SCALAR_TYPE, EulerSystem##AXES> EulerAngles##AXES##SCALAR_POSTFIX;
+
+#define EIGEN_EULER_ANGLES_TYPEDEFS(SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(XYZ, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(XYX, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(XZY, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(XZX, SCALAR_TYPE, SCALAR_POSTFIX) \
+ \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(YZX, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(YZY, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(YXZ, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(YXY, SCALAR_TYPE, SCALAR_POSTFIX) \
+ \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(ZXY, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(ZXZ, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(ZYX, SCALAR_TYPE, SCALAR_POSTFIX) \
+  EIGEN_EULER_ANGLES_SINGLE_TYPEDEF(ZYZ, SCALAR_TYPE, SCALAR_POSTFIX)
+
+EIGEN_EULER_ANGLES_TYPEDEFS(float, f)
+EIGEN_EULER_ANGLES_TYPEDEFS(double, d)
+
+  namespace internal
+  {
+    template<typename _Scalar, class _System>
+    struct traits<EulerAngles<_Scalar, _System> >
+    {
+      typedef _Scalar Scalar;
+    };
+  }
+  
+}
+
+#endif // EIGEN_EULERANGLESCLASS_H

ADDED   3rd_party/eigen/unsupported/Eigen/src/EulerAngles/EulerSystem.h
Index: 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/EulerSystem.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/EulerSystem.h
+++ 3rd_party/eigen/unsupported/Eigen/src/EulerAngles/EulerSystem.h
@@ -0,0 +1,326 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Tal Hadad <tal_hd@hotmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_EULERSYSTEM_H
+#define EIGEN_EULERSYSTEM_H
+
+namespace Eigen
+{
+  // Forward declerations
+  template <typename _Scalar, class _System>
+  class EulerAngles;
+  
+  namespace internal
+  {
+    // TODO: Check if already exists on the rest API
+    template <int Num, bool IsPositive = (Num > 0)>
+    struct Abs
+    {
+      enum { value = Num };
+    };
+  
+    template <int Num>
+    struct Abs<Num, false>
+    {
+      enum { value = -Num };
+    };
+
+    template <int Axis>
+    struct IsValidAxis
+    {
+      enum { value = Axis != 0 && Abs<Axis>::value <= 3 };
+    };
+  }
+  
+  #define EIGEN_EULER_ANGLES_CLASS_STATIC_ASSERT(COND,MSG) typedef char static_assertion_##MSG[(COND)?1:-1]
+  
+  /** \brief Representation of a fixed signed rotation axis for EulerSystem.
+    *
+    * \ingroup EulerAngles_Module
+    *
+    * Values here represent:
+    *  - The axis of the rotation: X, Y or Z.
+    *  - The sign (i.e. direction of the rotation along the axis): positive(+) or negative(-)
+    *
+    * Therefore, this could express all the axes {+X,+Y,+Z,-X,-Y,-Z}
+    *
+    * For positive axis, use +EULER_{axis}, and for negative axis use -EULER_{axis}.
+    */
+  enum EulerAxis
+  {
+    EULER_X = 1, /*!< the X axis */
+    EULER_Y = 2, /*!< the Y axis */
+    EULER_Z = 3  /*!< the Z axis */
+  };
+  
+  /** \class EulerSystem
+    *
+    * \ingroup EulerAngles_Module
+    *
+    * \brief Represents a fixed Euler rotation system.
+    *
+    * This meta-class goal is to represent the Euler system in compilation time, for EulerAngles.
+    *
+    * You can use this class to get two things:
+    *  - Build an Euler system, and then pass it as a template parameter to EulerAngles.
+    *  - Query some compile time data about an Euler system. (e.g. Whether it's tait bryan)
+    *
+    * Euler rotation is a set of three rotation on fixed axes. (see \ref EulerAngles)
+    * This meta-class store constantly those signed axes. (see \ref EulerAxis)
+    *
+    * ### Types of Euler systems ###
+    *
+    * All and only valid 3 dimension Euler rotation over standard
+    *  signed axes{+X,+Y,+Z,-X,-Y,-Z} are supported:
+    *  - all axes X, Y, Z in each valid order (see below what order is valid)
+    *  - rotation over the axis is supported both over the positive and negative directions.
+    *  - both tait bryan and proper/classic Euler angles (i.e. the opposite).
+    *
+    * Since EulerSystem support both positive and negative directions,
+    *  you may call this rotation distinction in other names:
+    *  - _right handed_ or _left handed_
+    *  - _counterclockwise_ or _clockwise_
+    *
+    * Notice all axed combination are valid, and would trigger a static assertion.
+    * Same unsigned axes can't be neighbors, e.g. {X,X,Y} is invalid.
+    * This yield two and only two classes:
+    *  - _tait bryan_ - all unsigned axes are distinct, e.g. {X,Y,Z}
+    *  - _proper/classic Euler angles_ - The first and the third unsigned axes is equal,
+    *     and the second is different, e.g. {X,Y,X}
+    *
+    * ### Intrinsic vs extrinsic Euler systems ###
+    *
+    * Only intrinsic Euler systems are supported for simplicity.
+    *  If you want to use extrinsic Euler systems,
+    *   just use the equal intrinsic opposite order for axes and angles.
+    *  I.e axes (A,B,C) becomes (C,B,A), and angles (a,b,c) becomes (c,b,a).
+    *
+    * ### Convenient user typedefs ###
+    *
+    * Convenient typedefs for EulerSystem exist (only for positive axes Euler systems),
+    *  in a form of EulerSystem{A}{B}{C}, e.g. \ref EulerSystemXYZ.
+    *
+    * ### Additional reading ###
+    *
+    * More information about Euler angles: https://en.wikipedia.org/wiki/Euler_angles
+    *
+    * \tparam _AlphaAxis the first fixed EulerAxis
+    *
+    * \tparam _AlphaAxis the second fixed EulerAxis
+    *
+    * \tparam _AlphaAxis the third fixed EulerAxis
+    */
+  template <int _AlphaAxis, int _BetaAxis, int _GammaAxis>
+  class EulerSystem
+  {
+    public:
+    // It's defined this way and not as enum, because I think
+    //  that enum is not guerantee to support negative numbers
+    
+    /** The first rotation axis */
+    static const int AlphaAxis = _AlphaAxis;
+    
+    /** The second rotation axis */
+    static const int BetaAxis = _BetaAxis;
+    
+    /** The third rotation axis */
+    static const int GammaAxis = _GammaAxis;
+
+    enum
+    {
+      AlphaAxisAbs = internal::Abs<AlphaAxis>::value, /*!< the first rotation axis unsigned */
+      BetaAxisAbs = internal::Abs<BetaAxis>::value, /*!< the second rotation axis unsigned */
+      GammaAxisAbs = internal::Abs<GammaAxis>::value, /*!< the third rotation axis unsigned */
+      
+      IsAlphaOpposite = (AlphaAxis < 0) ? 1 : 0, /*!< weather alpha axis is negative */
+      IsBetaOpposite = (BetaAxis < 0) ? 1 : 0, /*!< weather beta axis is negative */
+      IsGammaOpposite = (GammaAxis < 0) ? 1 : 0, /*!< weather gamma axis is negative */
+      
+      IsOdd = ((AlphaAxisAbs)%3 == (BetaAxisAbs - 1)%3) ? 0 : 1, /*!< weather the Euler system is odd */
+      IsEven = IsOdd ? 0 : 1, /*!< weather the Euler system is even */
+
+      IsTaitBryan = ((unsigned)AlphaAxisAbs != (unsigned)GammaAxisAbs) ? 1 : 0 /*!< weather the Euler system is tait bryan */
+    };
+    
+    private:
+    
+    EIGEN_EULER_ANGLES_CLASS_STATIC_ASSERT(internal::IsValidAxis<AlphaAxis>::value,
+      ALPHA_AXIS_IS_INVALID);
+      
+    EIGEN_EULER_ANGLES_CLASS_STATIC_ASSERT(internal::IsValidAxis<BetaAxis>::value,
+      BETA_AXIS_IS_INVALID);
+      
+    EIGEN_EULER_ANGLES_CLASS_STATIC_ASSERT(internal::IsValidAxis<GammaAxis>::value,
+      GAMMA_AXIS_IS_INVALID);
+      
+    EIGEN_EULER_ANGLES_CLASS_STATIC_ASSERT((unsigned)AlphaAxisAbs != (unsigned)BetaAxisAbs,
+      ALPHA_AXIS_CANT_BE_EQUAL_TO_BETA_AXIS);
+      
+    EIGEN_EULER_ANGLES_CLASS_STATIC_ASSERT((unsigned)BetaAxisAbs != (unsigned)GammaAxisAbs,
+      BETA_AXIS_CANT_BE_EQUAL_TO_GAMMA_AXIS);
+
+    enum
+    {
+      // I, J, K are the pivot indexes permutation for the rotation matrix, that match this Euler system. 
+      // They are used in this class converters.
+      // They are always different from each other, and their possible values are: 0, 1, or 2.
+      I = AlphaAxisAbs - 1,
+      J = (AlphaAxisAbs - 1 + 1 + IsOdd)%3,
+      K = (AlphaAxisAbs - 1 + 2 - IsOdd)%3
+    };
+    
+    // TODO: Get @mat parameter in form that avoids double evaluation.
+    template <typename Derived>
+    static void CalcEulerAngles_imp(Matrix<typename MatrixBase<Derived>::Scalar, 3, 1>& res, const MatrixBase<Derived>& mat, internal::true_type /*isTaitBryan*/)
+    {
+      using std::atan2;
+      using std::sin;
+      using std::cos;
+      
+      typedef typename Derived::Scalar Scalar;
+      typedef Matrix<Scalar,2,1> Vector2;
+      
+      res[0] = atan2(mat(J,K), mat(K,K));
+      Scalar c2 = Vector2(mat(I,I), mat(I,J)).norm();
+      if((IsOdd && res[0]<Scalar(0)) || ((!IsOdd) && res[0]>Scalar(0))) {
+        if(res[0] > Scalar(0)) {
+          res[0] -= Scalar(EIGEN_PI);
+        }
+        else {
+          res[0] += Scalar(EIGEN_PI);
+        }
+        res[1] = atan2(-mat(I,K), -c2);
+      }
+      else
+        res[1] = atan2(-mat(I,K), c2);
+      Scalar s1 = sin(res[0]);
+      Scalar c1 = cos(res[0]);
+      res[2] = atan2(s1*mat(K,I)-c1*mat(J,I), c1*mat(J,J) - s1 * mat(K,J));
+    }
+
+    template <typename Derived>
+    static void CalcEulerAngles_imp(Matrix<typename MatrixBase<Derived>::Scalar,3,1>& res, const MatrixBase<Derived>& mat, internal::false_type /*isTaitBryan*/)
+    {
+      using std::atan2;
+      using std::sin;
+      using std::cos;
+
+      typedef typename Derived::Scalar Scalar;
+      typedef Matrix<Scalar,2,1> Vector2;
+      
+      res[0] = atan2(mat(J,I), mat(K,I));
+      if((IsOdd && res[0]<Scalar(0)) || ((!IsOdd) && res[0]>Scalar(0)))
+      {
+        if(res[0] > Scalar(0)) {
+          res[0] -= Scalar(EIGEN_PI);
+        }
+        else {
+          res[0] += Scalar(EIGEN_PI);
+        }
+        Scalar s2 = Vector2(mat(J,I), mat(K,I)).norm();
+        res[1] = -atan2(s2, mat(I,I));
+      }
+      else
+      {
+        Scalar s2 = Vector2(mat(J,I), mat(K,I)).norm();
+        res[1] = atan2(s2, mat(I,I));
+      }
+
+      // With a=(0,1,0), we have i=0; j=1; k=2, and after computing the first two angles,
+      // we can compute their respective rotation, and apply its inverse to M. Since the result must
+      // be a rotation around x, we have:
+      //
+      //  c2  s1.s2 c1.s2                   1  0   0 
+      //  0   c1    -s1       *    M    =   0  c3  s3
+      //  -s2 s1.c2 c1.c2                   0 -s3  c3
+      //
+      //  Thus:  m11.c1 - m21.s1 = c3  &   m12.c1 - m22.s1 = s3
+
+      Scalar s1 = sin(res[0]);
+      Scalar c1 = cos(res[0]);
+      res[2] = atan2(c1*mat(J,K)-s1*mat(K,K), c1*mat(J,J) - s1 * mat(K,J));
+    }
+    
+    template<typename Scalar>
+    static void CalcEulerAngles(
+      EulerAngles<Scalar, EulerSystem>& res,
+      const typename EulerAngles<Scalar, EulerSystem>::Matrix3& mat)
+    {
+      CalcEulerAngles(res, mat, false, false, false);
+    }
+    
+    template<
+      bool PositiveRangeAlpha,
+      bool PositiveRangeBeta,
+      bool PositiveRangeGamma,
+      typename Scalar>
+    static void CalcEulerAngles(
+      EulerAngles<Scalar, EulerSystem>& res,
+      const typename EulerAngles<Scalar, EulerSystem>::Matrix3& mat)
+    {
+      CalcEulerAngles(res, mat, PositiveRangeAlpha, PositiveRangeBeta, PositiveRangeGamma);
+    }
+    
+    template<typename Scalar>
+    static void CalcEulerAngles(
+      EulerAngles<Scalar, EulerSystem>& res,
+      const typename EulerAngles<Scalar, EulerSystem>::Matrix3& mat,
+      bool PositiveRangeAlpha,
+      bool PositiveRangeBeta,
+      bool PositiveRangeGamma)
+    {
+      CalcEulerAngles_imp(
+        res.angles(), mat,
+        typename internal::conditional<IsTaitBryan, internal::true_type, internal::false_type>::type());
+
+      if (IsAlphaOpposite == IsOdd)
+        res.alpha() = -res.alpha();
+        
+      if (IsBetaOpposite == IsOdd)
+        res.beta() = -res.beta();
+        
+      if (IsGammaOpposite == IsOdd)
+        res.gamma() = -res.gamma();
+      
+      // Saturate results to the requested range
+      if (PositiveRangeAlpha && (res.alpha() < 0))
+        res.alpha() += Scalar(2 * EIGEN_PI);
+      
+      if (PositiveRangeBeta && (res.beta() < 0))
+        res.beta() += Scalar(2 * EIGEN_PI);
+      
+      if (PositiveRangeGamma && (res.gamma() < 0))
+        res.gamma() += Scalar(2 * EIGEN_PI);
+    }
+    
+    template <typename _Scalar, class _System>
+    friend class Eigen::EulerAngles;
+  };
+
+#define EIGEN_EULER_SYSTEM_TYPEDEF(A, B, C) \
+  /** \ingroup EulerAngles_Module */ \
+  typedef EulerSystem<EULER_##A, EULER_##B, EULER_##C> EulerSystem##A##B##C;
+  
+  EIGEN_EULER_SYSTEM_TYPEDEF(X,Y,Z)
+  EIGEN_EULER_SYSTEM_TYPEDEF(X,Y,X)
+  EIGEN_EULER_SYSTEM_TYPEDEF(X,Z,Y)
+  EIGEN_EULER_SYSTEM_TYPEDEF(X,Z,X)
+  
+  EIGEN_EULER_SYSTEM_TYPEDEF(Y,Z,X)
+  EIGEN_EULER_SYSTEM_TYPEDEF(Y,Z,Y)
+  EIGEN_EULER_SYSTEM_TYPEDEF(Y,X,Z)
+  EIGEN_EULER_SYSTEM_TYPEDEF(Y,X,Y)
+  
+  EIGEN_EULER_SYSTEM_TYPEDEF(Z,X,Y)
+  EIGEN_EULER_SYSTEM_TYPEDEF(Z,X,Z)
+  EIGEN_EULER_SYSTEM_TYPEDEF(Z,Y,X)
+  EIGEN_EULER_SYSTEM_TYPEDEF(Z,Y,Z)
+}
+
+#endif // EIGEN_EULERSYSTEM_H

DELETED 3rd_party/eigen/unsupported/Eigen/src/FFT/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/FFT/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/FFT/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/FFT/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_FFT_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_FFT_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/FFT COMPONENT Devel
-  )

DELETED 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_IterativeSolvers_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_IterativeSolvers_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/IterativeSolvers COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/DGMRES.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/DGMRES.h
+++ 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/DGMRES.h
@@ -38,11 +38,10 @@
 template <typename VectorType, typename IndexType>
 void sortWithPermutation (VectorType& vec, IndexType& perm, typename IndexType::Scalar& ncut)
 {
   eigen_assert(vec.size() == perm.size());
   typedef typename IndexType::Scalar Index; 
-  typedef typename VectorType::Scalar Scalar; 
   bool flag; 
   for (Index k  = 0; k < ncut; k++)
   {
     flag = false;
     for (Index j = 0; j < vec.size()-1; j++)
@@ -82,10 +81,12 @@
  * solver.setEigenv(1); // Set the number of eigenvalues to deflate
  * solver.compute(A);
  * x = solver.solve(b);
  * \endcode
  * 
+ * DGMRES can also be used in a matrix-free context, see the following \link MatrixfreeSolverExample example \endlink.
+ *
  * References :
  * [1] D. NUENTSA WAKAM and F. PACULL, Memory Efficient Hybrid
  *  Algebraic Solvers for Linear Systems Arising from Compressible
  *  Flows, Computers and Fluids, In Press,
  *  http://dx.doi.org/10.1016/j.compfluid.2012.03.023   
@@ -99,20 +100,22 @@
  */
 template< typename _MatrixType, typename _Preconditioner>
 class DGMRES : public IterativeSolverBase<DGMRES<_MatrixType,_Preconditioner> >
 {
     typedef IterativeSolverBase<DGMRES> Base;
-    using Base::mp_matrix;
+    using Base::matrix;
     using Base::m_error;
     using Base::m_iterations;
     using Base::m_info;
     using Base::m_isInitialized;
     using Base::m_tolerance; 
   public:
+    using Base::_solve_impl;
     typedef _MatrixType MatrixType;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::StorageIndex StorageIndex;
     typedef typename MatrixType::RealScalar RealScalar;
     typedef _Preconditioner Preconditioner;
     typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; 
     typedef Matrix<RealScalar,Dynamic,Dynamic> DenseRealMatrix; 
     typedef Matrix<Scalar,Dynamic,1> DenseVector;
@@ -131,56 +134,40 @@
     * \warning this class stores a reference to the matrix A as well as some
     * precomputed values that depend on it. Therefore, if \a A is changed
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  DGMRES(const MatrixType& A) : Base(A),m_restart(30),m_neig(0),m_r(0),m_maxNeig(5),m_isDeflAllocated(false),m_isDeflInitialized(false)
-  {}
+  template<typename MatrixDerived>
+  explicit DGMRES(const EigenBase<MatrixDerived>& A) : Base(A.derived()), m_restart(30),m_neig(0),m_r(0),m_maxNeig(5),m_isDeflAllocated(false),m_isDeflInitialized(false) {}
 
   ~DGMRES() {}
   
-  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A
-    * \a x0 as an initial solution.
-    *
-    * \sa compute()
-    */
-  template<typename Rhs,typename Guess>
-  inline const internal::solve_retval_with_guess<DGMRES, Rhs, Guess>
-  solveWithGuess(const MatrixBase<Rhs>& b, const Guess& x0) const
-  {
-    eigen_assert(m_isInitialized && "DGMRES is not initialized.");
-    eigen_assert(Base::rows()==b.rows()
-              && "DGMRES::solve(): invalid number of rows of the right hand side matrix b");
-    return internal::solve_retval_with_guess
-            <DGMRES, Rhs, Guess>(*this, b.derived(), x0);
-  }
-  
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solveWithGuess(const Rhs& b, Dest& x) const
+  void _solve_with_guess_impl(const Rhs& b, Dest& x) const
   {    
     bool failed = false;
     for(int j=0; j<b.cols(); ++j)
     {
       m_iterations = Base::maxIterations();
       m_error = Base::m_tolerance;
       
       typename Dest::ColXpr xj(x,j);
-      dgmres(*mp_matrix, b.col(j), xj, Base::m_preconditioner);
+      dgmres(matrix(), b.col(j), xj, Base::m_preconditioner);
     }
     m_info = failed ? NumericalIssue
            : m_error <= Base::m_tolerance ? Success
            : NoConvergence;
     m_isInitialized = true;
   }
 
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solve(const Rhs& b, Dest& x) const
+  void _solve_impl(const Rhs& b, MatrixBase<Dest>& x) const
   {
     x = b;
-    _solveWithGuess(b,x);
+    _solve_with_guess_impl(b,x.derived());
   }
   /** 
    * Get the restart value
     */
   int restart() { return m_restart; }
@@ -215,11 +202,11 @@
     void dgmres(const MatrixType& mat,const Rhs& rhs, Dest& x, const Preconditioner& precond) const;
     // Perform one cycle of GMRES
     template<typename Dest>
     int dgmresCycle(const MatrixType& mat, const Preconditioner& precond, Dest& x, DenseVector& r0, RealScalar& beta, const RealScalar& normRhs, int& nbIts) const; 
     // Compute data to use for deflation 
-    int dgmresComputeDeflationData(const MatrixType& mat, const Preconditioner& precond, const Index& it, Index& neig) const;
+    int dgmresComputeDeflationData(const MatrixType& mat, const Preconditioner& precond, const Index& it, StorageIndex& neig) const;
     // Apply deflation to a vector
     template<typename RhsType, typename DestType>
     int dgmresApplyDeflation(const RhsType& In, DestType& Out) const; 
     ComplexVector schurValues(const ComplexSchur<DenseMatrix>& schurofH) const;
     ComplexVector schurValues(const RealSchur<DenseMatrix>& schurofH) const;
@@ -231,11 +218,11 @@
     mutable Index m_restart; // Maximum size of the Krylov subspace
     mutable DenseMatrix m_U; // Vectors that form the basis of the invariant subspace 
     mutable DenseMatrix m_MU; // matrix operator applied to m_U (for next cycles)
     mutable DenseMatrix m_T; /* T=U^T*M^{-1}*A*U */
     mutable PartialPivLU<DenseMatrix> m_luT; // LU factorization of m_T
-    mutable int m_neig; //Number of eigenvalues to extract at each restart
+    mutable StorageIndex m_neig; //Number of eigenvalues to extract at each restart
     mutable int m_r; // Current number of deflated eigenvalues, size of m_U
     mutable int m_maxNeig; // Maximum number of eigenvalues to deflate
     mutable RealScalar m_lambdaN; //Modulus of the largest eigenvalue of A
     mutable bool m_isDeflAllocated;
     mutable bool m_isDeflInitialized;
@@ -351,11 +338,11 @@
     m_H.col(it).applyOnTheLeft(it,it+1,gr[it].adjoint());
     g.applyOnTheLeft(it,it+1, gr[it].adjoint()); 
     
     beta = std::abs(g(it+1));
     m_error = beta/normRhs; 
-    std::cerr << nbIts << " Relative Residual Norm " << m_error << std::endl;
+    // std::cerr << nbIts << " Relative Residual Norm " << m_error << std::endl;
     it++; nbIts++; 
     
     if (m_error < m_tolerance)
     {
       // The method has converged
@@ -429,21 +416,21 @@
   if (j < it-1) eig(j) = std::complex<RealScalar>(T(j,j),RealScalar(0));
   return eig;
 }
 
 template< typename _MatrixType, typename _Preconditioner>
-int DGMRES<_MatrixType, _Preconditioner>::dgmresComputeDeflationData(const MatrixType& mat, const Preconditioner& precond, const Index& it, Index& neig) const
+int DGMRES<_MatrixType, _Preconditioner>::dgmresComputeDeflationData(const MatrixType& mat, const Preconditioner& precond, const Index& it, StorageIndex& neig) const
 {
   // First, find the Schur form of the Hessenberg matrix H
   typename internal::conditional<NumTraits<Scalar>::IsComplex, ComplexSchur<DenseMatrix>, RealSchur<DenseMatrix> >::type schurofH; 
   bool computeU = true;
   DenseMatrix matrixQ(it,it); 
   matrixQ.setIdentity();
   schurofH.computeFromHessenberg(m_Hes.topLeftCorner(it,it), matrixQ, computeU); 
   
   ComplexVector eig(it);
-  Matrix<Index,Dynamic,1>perm(it); 
+  Matrix<StorageIndex,Dynamic,1>perm(it);
   eig = this->schurValues(schurofH);
   
   // Reorder the absolute values of Schur values
   DenseRealVector modulEig(it); 
   for (int j=0; j<it; ++j) modulEig(j) = std::abs(eig(j)); 
@@ -520,23 +507,7 @@
   DenseVector x1 = m_U.leftCols(m_r).transpose() * x; 
   y = x + m_U.leftCols(m_r) * ( m_lambdaN * m_luT.solve(x1) - x1);
   return 0; 
 }
 
-namespace internal {
-
-  template<typename _MatrixType, typename _Preconditioner, typename Rhs>
-struct solve_retval<DGMRES<_MatrixType, _Preconditioner>, Rhs>
-  : solve_retval_base<DGMRES<_MatrixType, _Preconditioner>, Rhs>
-{
-  typedef DGMRES<_MatrixType, _Preconditioner> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-} // end namespace internal
-
 } // end namespace Eigen
 #endif 

Index: 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/GMRES.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/GMRES.h
+++ 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/GMRES.h
@@ -9,197 +9,201 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GMRES_H
 #define EIGEN_GMRES_H
 
-namespace Eigen { 
+namespace Eigen {
 
 namespace internal {
 
 /**
- * Generalized Minimal Residual Algorithm based on the
- * Arnoldi algorithm implemented with Householder reflections.
- *
- * Parameters:
- *  \param mat       matrix of linear system of equations
- *  \param Rhs       right hand side vector of linear system of equations
- *  \param x         on input: initial guess, on output: solution
- *  \param precond   preconditioner used
- *  \param iters     on input: maximum number of iterations to perform
- *                   on output: number of iterations performed
- *  \param restart   number of iterations for a restart
- *  \param tol_error on input: residual tolerance
- *                   on output: residuum achieved
- *
- * \sa IterativeMethods::bicgstab() 
- *  
- *
- * For references, please see:
- *
- * Saad, Y. and Schultz, M. H.
- * GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems.
- * SIAM J.Sci.Stat.Comp. 7, 1986, pp. 856 - 869.
- *
- * Saad, Y.
- * Iterative Methods for Sparse Linear Systems.
- * Society for Industrial and Applied Mathematics, Philadelphia, 2003.
- *
- * Walker, H. F.
- * Implementations of the GMRES method.
- * Comput.Phys.Comm. 53, 1989, pp. 311 - 320.
- *
- * Walker, H. F.
- * Implementation of the GMRES Method using Householder Transformations.
- * SIAM J.Sci.Stat.Comp. 9, 1988, pp. 152 - 163.
- *
- */
+* Generalized Minimal Residual Algorithm based on the
+* Arnoldi algorithm implemented with Householder reflections.
+*
+* Parameters:
+*  \param mat       matrix of linear system of equations
+*  \param Rhs       right hand side vector of linear system of equations
+*  \param x         on input: initial guess, on output: solution
+*  \param precond   preconditioner used
+*  \param iters     on input: maximum number of iterations to perform
+*                   on output: number of iterations performed
+*  \param restart   number of iterations for a restart
+*  \param tol_error on input: relative residual tolerance
+*                   on output: residuum achieved
+*
+* \sa IterativeMethods::bicgstab()
+*
+*
+* For references, please see:
+*
+* Saad, Y. and Schultz, M. H.
+* GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems.
+* SIAM J.Sci.Stat.Comp. 7, 1986, pp. 856 - 869.
+*
+* Saad, Y.
+* Iterative Methods for Sparse Linear Systems.
+* Society for Industrial and Applied Mathematics, Philadelphia, 2003.
+*
+* Walker, H. F.
+* Implementations of the GMRES method.
+* Comput.Phys.Comm. 53, 1989, pp. 311 - 320.
+*
+* Walker, H. F.
+* Implementation of the GMRES Method using Householder Transformations.
+* SIAM J.Sci.Stat.Comp. 9, 1988, pp. 152 - 163.
+*
+*/
 template<typename MatrixType, typename Rhs, typename Dest, typename Preconditioner>
 bool gmres(const MatrixType & mat, const Rhs & rhs, Dest & x, const Preconditioner & precond,
-		int &iters, const int &restart, typename Dest::RealScalar & tol_error) {
-
-	using std::sqrt;
-	using std::abs;
-
-	typedef typename Dest::RealScalar RealScalar;
-	typedef typename Dest::Scalar Scalar;
-	typedef Matrix < Scalar, Dynamic, 1 > VectorType;
-	typedef Matrix < Scalar, Dynamic, Dynamic > FMatrixType;
-
-	RealScalar tol = tol_error;
-	const int maxIters = iters;
-	iters = 0;
-
-	const int m = mat.rows();
-
-	VectorType p0 = rhs - mat*x;
-	VectorType r0 = precond.solve(p0);
- 
-	// is initial guess already good enough?
-	if(abs(r0.norm()) < tol) {
-		return true; 
-	}
-
-	VectorType w = VectorType::Zero(restart + 1);
-
-	FMatrixType H = FMatrixType::Zero(m, restart + 1); // Hessenberg matrix
-	VectorType tau = VectorType::Zero(restart + 1);
-	std::vector < JacobiRotation < Scalar > > G(restart);
-
-	// generate first Householder vector
-	VectorType e(m-1);
-	RealScalar beta;
-	r0.makeHouseholder(e, tau.coeffRef(0), beta);
-	w(0)=(Scalar) beta;
-	H.bottomLeftCorner(m - 1, 1) = e;
-
-	for (int k = 1; k <= restart; ++k) {
-
-		++iters;
-
-		VectorType v = VectorType::Unit(m, k - 1), workspace(m);
-
-		// apply Householder reflections H_{1} ... H_{k-1} to v
-		for (int i = k - 1; i >= 0; --i) {
-			v.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
-		}
-
-		// apply matrix M to v:  v = mat * v;
-		VectorType t=mat*v;
-		v=precond.solve(t);
-
-		// apply Householder reflections H_{k-1} ... H_{1} to v
-		for (int i = 0; i < k; ++i) {
-			v.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
-		}
-
-		if (v.tail(m - k).norm() != 0.0) {
-
-			if (k <= restart) {
-
-				// generate new Householder vector
-                                  VectorType e(m - k - 1);
-				RealScalar beta;
-				v.tail(m - k).makeHouseholder(e, tau.coeffRef(k), beta);
-				H.col(k).tail(m - k - 1) = e;
-
-				// apply Householder reflection H_{k} to v
-				v.tail(m - k).applyHouseholderOnTheLeft(H.col(k).tail(m - k - 1), tau.coeffRef(k), workspace.data());
-
-			}
-                }
-
-                if (k > 1) {
-                        for (int i = 0; i < k - 1; ++i) {
-                                // apply old Givens rotations to v
-                                v.applyOnTheLeft(i, i + 1, G[i].adjoint());
-                        }
-                }
-
-                if (k<m && v(k) != (Scalar) 0) {
-                        // determine next Givens rotation
-                        G[k - 1].makeGivens(v(k - 1), v(k));
-
-                        // apply Givens rotation to v and w
-                        v.applyOnTheLeft(k - 1, k, G[k - 1].adjoint());
-                        w.applyOnTheLeft(k - 1, k, G[k - 1].adjoint());
-
-                }
-
-                // insert coefficients into upper matrix triangle
-                H.col(k - 1).head(k) = v.head(k);
-
-                bool stop=(k==m || abs(w(k)) < tol || iters == maxIters);
-
-                if (stop || k == restart) {
-
-                        // solve upper triangular system
-                        VectorType y = w.head(k);
-                        H.topLeftCorner(k, k).template triangularView < Eigen::Upper > ().solveInPlace(y);
-
-                        // use Horner-like scheme to calculate solution vector
-                        VectorType x_new = y(k - 1) * VectorType::Unit(m, k - 1);
-
-                        // apply Householder reflection H_{k} to x_new
-                        x_new.tail(m - k + 1).applyHouseholderOnTheLeft(H.col(k - 1).tail(m - k), tau.coeffRef(k - 1), workspace.data());
-
-                        for (int i = k - 2; i >= 0; --i) {
-                                x_new += y(i) * VectorType::Unit(m, i);
-                                // apply Householder reflection H_{i} to x_new
-                                x_new.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
-                        }
-
-                        x += x_new;
-
-                        if (stop) {
-                                return true;
-                        } else {
-                                k=0;
-
-                                // reset data for a restart  r0 = rhs - mat * x;
-                                VectorType p0=mat*x;
-                                VectorType p1=precond.solve(p0);
-                                r0 = rhs - p1;
-//                                 r0_sqnorm = r0.squaredNorm();
-                                w = VectorType::Zero(restart + 1);
-                                H = FMatrixType::Zero(m, restart + 1);
-                                tau = VectorType::Zero(restart + 1);
-
-                                // generate first Householder vector
-                                RealScalar beta;
-                                r0.makeHouseholder(e, tau.coeffRef(0), beta);
-                                w(0)=(Scalar) beta;
-                                H.bottomLeftCorner(m - 1, 1) = e;
-
-                        }
-
-                }
-
-
-
-	}
-	
-	return false;
+    Index &iters, const Index &restart, typename Dest::RealScalar & tol_error) {
+
+  using std::sqrt;
+  using std::abs;
+
+  typedef typename Dest::RealScalar RealScalar;
+  typedef typename Dest::Scalar Scalar;
+  typedef Matrix < Scalar, Dynamic, 1 > VectorType;
+  typedef Matrix < Scalar, Dynamic, Dynamic, ColMajor> FMatrixType;
+
+  RealScalar tol = tol_error;
+  const Index maxIters = iters;
+  iters = 0;
+
+  const Index m = mat.rows();
+
+  // residual and preconditioned residual
+  VectorType p0 = rhs - mat*x;
+  VectorType r0 = precond.solve(p0);
+
+  const RealScalar r0Norm = r0.norm();
+
+  // is initial guess already good enough?
+  if(r0Norm == 0)
+  {
+    tol_error = 0;
+    return true;
+  }
+
+  // storage for Hessenberg matrix and Householder data
+  FMatrixType H   = FMatrixType::Zero(m, restart + 1);
+  VectorType w    = VectorType::Zero(restart + 1);
+  VectorType tau  = VectorType::Zero(restart + 1);
+
+  // storage for Jacobi rotations
+  std::vector < JacobiRotation < Scalar > > G(restart);
+  
+  // storage for temporaries
+  VectorType t(m), v(m), workspace(m), x_new(m);
+
+  // generate first Householder vector
+  Ref<VectorType> H0_tail = H.col(0).tail(m - 1);
+  RealScalar beta;
+  r0.makeHouseholder(H0_tail, tau.coeffRef(0), beta);
+  w(0) = Scalar(beta);
+  
+  for (Index k = 1; k <= restart; ++k)
+  {
+    ++iters;
+
+    v = VectorType::Unit(m, k - 1);
+
+    // apply Householder reflections H_{1} ... H_{k-1} to v
+    // TODO: use a HouseholderSequence
+    for (Index i = k - 1; i >= 0; --i) {
+      v.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
+    }
+
+    // apply matrix M to v:  v = mat * v;
+    t.noalias() = mat * v;
+    v = precond.solve(t);
+
+    // apply Householder reflections H_{k-1} ... H_{1} to v
+    // TODO: use a HouseholderSequence
+    for (Index i = 0; i < k; ++i) {
+      v.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
+    }
+
+    if (v.tail(m - k).norm() != 0.0)
+    {
+      if (k <= restart)
+      {
+        // generate new Householder vector
+        Ref<VectorType> Hk_tail = H.col(k).tail(m - k - 1);
+        v.tail(m - k).makeHouseholder(Hk_tail, tau.coeffRef(k), beta);
+
+        // apply Householder reflection H_{k} to v
+        v.tail(m - k).applyHouseholderOnTheLeft(Hk_tail, tau.coeffRef(k), workspace.data());
+      }
+    }
+
+    if (k > 1)
+    {
+      for (Index i = 0; i < k - 1; ++i)
+      {
+        // apply old Givens rotations to v
+        v.applyOnTheLeft(i, i + 1, G[i].adjoint());
+      }
+    }
+
+    if (k<m && v(k) != (Scalar) 0)
+    {
+      // determine next Givens rotation
+      G[k - 1].makeGivens(v(k - 1), v(k));
+
+      // apply Givens rotation to v and w
+      v.applyOnTheLeft(k - 1, k, G[k - 1].adjoint());
+      w.applyOnTheLeft(k - 1, k, G[k - 1].adjoint());
+    }
+
+    // insert coefficients into upper matrix triangle
+    H.col(k-1).head(k) = v.head(k);
+
+    tol_error = abs(w(k)) / r0Norm;
+    bool stop = (k==m || tol_error < tol || iters == maxIters);
+
+    if (stop || k == restart)
+    {
+      // solve upper triangular system
+      Ref<VectorType> y = w.head(k);
+      H.topLeftCorner(k, k).template triangularView <Upper>().solveInPlace(y);
+
+      // use Horner-like scheme to calculate solution vector
+      x_new.setZero();
+      for (Index i = k - 1; i >= 0; --i)
+      {
+        x_new(i) += y(i);
+        // apply Householder reflection H_{i} to x_new
+        x_new.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data());
+      }
+
+      x += x_new;
+
+      if(stop)
+      {
+        return true;
+      }
+      else
+      {
+        k=0;
+
+        // reset data for restart
+        p0.noalias() = rhs - mat*x;
+        r0 = precond.solve(p0);
+
+        // clear Hessenberg matrix and Householder data
+        H.setZero();
+        w.setZero();
+        tau.setZero();
+
+        // generate first Householder vector
+        r0.makeHouseholder(H0_tail, tau.coeffRef(0), beta);
+        w(0) = Scalar(beta);
+      }
+    }
+  }
+
+  return false;
 
 }
 
 }
 
@@ -228,11 +232,11 @@
   * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
   *
   * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
   * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
   * and NumTraits<Scalar>::epsilon() for the tolerance.
-  * 
+  *
   * This class can be used as the direct solver classes. Here is a typical usage example:
   * \code
   * int n = 10000;
   * VectorXd x(n), b(n);
   * SparseMatrix<double> A(n,n);
@@ -242,142 +246,98 @@
   * std::cout << "#iterations:     " << solver.iterations() << std::endl;
   * std::cout << "estimated error: " << solver.error()      << std::endl;
   * // update b, and solve again
   * x = solver.solve(b);
   * \endcode
-  * 
+  *
   * By default the iterations start with x=0 as an initial guess of the solution.
-  * One can control the start using the solveWithGuess() method. Here is a step by
-  * step execution example starting with a random guess and printing the evolution
-  * of the estimated error:
-  * * \code
-  * x = VectorXd::Random(n);
-  * solver.setMaxIterations(1);
-  * int i = 0;
-  * do {
-  *   x = solver.solveWithGuess(b,x);
-  *   std::cout << i << " : " << solver.error() << std::endl;
-  *   ++i;
-  * } while (solver.info()!=Success && i<100);
-  * \endcode
-  * Note that such a step by step excution is slightly slower.
-  * 
+  * One can control the start using the solveWithGuess() method.
+  * 
+  * GMRES can also be used in a matrix-free context, see the following \link MatrixfreeSolverExample example \endlink.
+  *
   * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
   */
 template< typename _MatrixType, typename _Preconditioner>
 class GMRES : public IterativeSolverBase<GMRES<_MatrixType,_Preconditioner> >
 {
   typedef IterativeSolverBase<GMRES> Base;
-  using Base::mp_matrix;
+  using Base::matrix;
   using Base::m_error;
   using Base::m_iterations;
   using Base::m_info;
   using Base::m_isInitialized;
- 
+
 private:
-  int m_restart;
-  
+  Index m_restart;
+
 public:
+  using Base::_solve_impl;
   typedef _MatrixType MatrixType;
   typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::RealScalar RealScalar;
   typedef _Preconditioner Preconditioner;
 
 public:
 
   /** Default constructor. */
   GMRES() : Base(), m_restart(30) {}
 
   /** Initialize the solver with matrix \a A for further \c Ax=b solving.
-    * 
+    *
     * This constructor is a shortcut for the default constructor followed
     * by a call to compute().
-    * 
+    *
     * \warning this class stores a reference to the matrix A as well as some
     * precomputed values that depend on it. Therefore, if \a A is changed
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  GMRES(const MatrixType& A) : Base(A), m_restart(30) {}
+  template<typename MatrixDerived>
+  explicit GMRES(const EigenBase<MatrixDerived>& A) : Base(A.derived()), m_restart(30) {}
 
   ~GMRES() {}
-  
+
   /** Get the number of iterations after that a restart is performed.
     */
-  int get_restart() { return m_restart; }
-  
+  Index get_restart() { return m_restart; }
+
   /** Set the number of iterations after that a restart is performed.
     *  \param restart   number of iterations for a restarti, default is 30.
     */
-  void set_restart(const int restart) { m_restart=restart; }
-  
-  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A
-    * \a x0 as an initial solution.
-    *
-    * \sa compute()
-    */
-  template<typename Rhs,typename Guess>
-  inline const internal::solve_retval_with_guess<GMRES, Rhs, Guess>
-  solveWithGuess(const MatrixBase<Rhs>& b, const Guess& x0) const
-  {
-    eigen_assert(m_isInitialized && "GMRES is not initialized.");
-    eigen_assert(Base::rows()==b.rows()
-              && "GMRES::solve(): invalid number of rows of the right hand side matrix b");
-    return internal::solve_retval_with_guess
-            <GMRES, Rhs, Guess>(*this, b.derived(), x0);
-  }
-  
+  void set_restart(const Index restart) { m_restart=restart; }
+
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solveWithGuess(const Rhs& b, Dest& x) const
-  {    
+  void _solve_with_guess_impl(const Rhs& b, Dest& x) const
+  {
     bool failed = false;
-    for(int j=0; j<b.cols(); ++j)
+    for(Index j=0; j<b.cols(); ++j)
     {
       m_iterations = Base::maxIterations();
       m_error = Base::m_tolerance;
-      
+
       typename Dest::ColXpr xj(x,j);
-      if(!internal::gmres(*mp_matrix, b.col(j), xj, Base::m_preconditioner, m_iterations, m_restart, m_error))
+      if(!internal::gmres(matrix(), b.col(j), xj, Base::m_preconditioner, m_iterations, m_restart, m_error))
         failed = true;
     }
     m_info = failed ? NumericalIssue
-           : m_error <= Base::m_tolerance ? Success
-           : NoConvergence;
+          : m_error <= Base::m_tolerance ? Success
+          : NoConvergence;
     m_isInitialized = true;
   }
 
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solve(const Rhs& b, Dest& x) const
+  void _solve_impl(const Rhs& b, MatrixBase<Dest> &x) const
   {
     x = b;
     if(x.squaredNorm() == 0) return; // Check Zero right hand side
-    _solveWithGuess(b,x);
+    _solve_with_guess_impl(b,x.derived());
   }
 
 protected:
 
 };
 
-
-namespace internal {
-
-  template<typename _MatrixType, typename _Preconditioner, typename Rhs>
-struct solve_retval<GMRES<_MatrixType, _Preconditioner>, Rhs>
-  : solve_retval_base<GMRES<_MatrixType, _Preconditioner>, Rhs>
-{
-  typedef GMRES<_MatrixType, _Preconditioner> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-} // end namespace internal
-
 } // end namespace Eigen
 
 #endif // EIGEN_GMRES_H

DELETED 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h
Index: 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h
+++ 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h
@@ -1,278 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_INCOMPLETE_CHOlESKY_H
-#define EIGEN_INCOMPLETE_CHOlESKY_H
-#include "Eigen/src/IterativeLinearSolvers/IncompleteLUT.h" 
-#include <Eigen/OrderingMethods>
-#include <list>
-
-namespace Eigen {  
-/** 
- * \brief Modified Incomplete Cholesky with dual threshold
- * 
- * References : C-J. Lin and J. J. Moré, Incomplete Cholesky Factorizations with
- *              Limited memory, SIAM J. Sci. Comput.  21(1), pp. 24-45, 1999
- * 
- * \tparam _MatrixType The type of the sparse matrix. It should be a symmetric 
- *                     matrix. It is advised to give  a row-oriented sparse matrix 
- * \tparam _UpLo The triangular part of the matrix to reference. 
- * \tparam _OrderingType 
- */
-
-template <typename Scalar, int _UpLo = Lower, typename _OrderingType = NaturalOrdering<int> >
-class IncompleteCholesky : internal::noncopyable
-{
-  public:
-    typedef SparseMatrix<Scalar,ColMajor> MatrixType;
-    typedef _OrderingType OrderingType;
-    typedef typename MatrixType::RealScalar RealScalar; 
-    typedef typename MatrixType::Index Index; 
-    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
-    typedef Matrix<Scalar,Dynamic,1> ScalarType; 
-    typedef Matrix<Index,Dynamic, 1> IndexType;
-    typedef std::vector<std::list<Index> > VectorList; 
-    enum { UpLo = _UpLo };
-  public:
-    IncompleteCholesky() : m_shift(1),m_factorizationIsOk(false) {}
-    IncompleteCholesky(const MatrixType& matrix) : m_shift(1),m_factorizationIsOk(false)
-    {
-      compute(matrix);
-    }
-    
-    Index rows() const { return m_L.rows(); }
-    
-    Index cols() const { return m_L.cols(); }
-    
-
-    /** \brief Reports whether previous computation was successful.
-      *
-      * \returns \c Success if computation was succesful,
-      *          \c NumericalIssue if the matrix appears to be negative.
-      */
-    ComputationInfo info() const
-    {
-      eigen_assert(m_isInitialized && "IncompleteLLT is not initialized.");
-      return m_info;
-    }
-    
-    /** 
-     * \brief Set the initial shift parameter
-     */
-    void setShift( Scalar shift) { m_shift = shift; }
-    
-    /**
-    * \brief Computes the fill reducing permutation vector. 
-    */
-    template<typename MatrixType>
-    void analyzePattern(const MatrixType& mat)
-    {
-      OrderingType ord; 
-      ord(mat.template selfadjointView<UpLo>(), m_perm); 
-      m_analysisIsOk = true; 
-    }
-    
-    template<typename MatrixType>
-    void factorize(const MatrixType& amat);
-    
-    template<typename MatrixType>
-    void compute (const MatrixType& matrix)
-    {
-      analyzePattern(matrix); 
-      factorize(matrix);
-    }
-    
-    template<typename Rhs, typename Dest>
-    void _solve(const Rhs& b, Dest& x) const
-    {
-      eigen_assert(m_factorizationIsOk && "factorize() should be called first");
-      if (m_perm.rows() == b.rows())
-        x = m_perm.inverse() * b; 
-      else 
-        x = b; 
-      x = m_scal.asDiagonal() * x;
-      x = m_L.template triangularView<UnitLower>().solve(x); 
-      x = m_L.adjoint().template triangularView<Upper>().solve(x); 
-      if (m_perm.rows() == b.rows())
-        x = m_perm * x;
-      x = m_scal.asDiagonal() * x;
-    }
-    template<typename Rhs> inline const internal::solve_retval<IncompleteCholesky, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_factorizationIsOk && "IncompleteLLT did not succeed");
-      eigen_assert(m_isInitialized && "IncompleteLLT is not initialized.");
-      eigen_assert(cols()==b.rows()
-                && "IncompleteLLT::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<IncompleteCholesky, Rhs>(*this, b.derived());
-    }
-  protected:
-    SparseMatrix<Scalar,ColMajor> m_L;  // The lower part stored in CSC
-    ScalarType m_scal; // The vector for scaling the matrix 
-    Scalar m_shift; //The initial shift parameter
-    bool m_analysisIsOk; 
-    bool m_factorizationIsOk; 
-    bool m_isInitialized;
-    ComputationInfo m_info;
-    PermutationType m_perm; 
-    
-  private:
-    template <typename IdxType, typename SclType>
-    inline void updateList(const IdxType& colPtr, IdxType& rowIdx, SclType& vals, const Index& col, const Index& jk, IndexType& firstElt, VectorList& listCol); 
-}; 
-
-template<typename Scalar, int _UpLo, typename OrderingType>
-template<typename _MatrixType>
-void IncompleteCholesky<Scalar,_UpLo, OrderingType>::factorize(const _MatrixType& mat)
-{
-  using std::sqrt;
-  using std::min;
-  eigen_assert(m_analysisIsOk && "analyzePattern() should be called first"); 
-    
-  // Dropping strategies : Keep only the p largest elements per column, where p is the number of elements in the column of the original matrix. Other strategies will be added
-  
-  // Apply the fill-reducing permutation computed in analyzePattern()
-  if (m_perm.rows() == mat.rows() ) // To detect the null permutation
-    m_L.template selfadjointView<Lower>() = mat.template selfadjointView<_UpLo>().twistedBy(m_perm);
-  else
-    m_L.template selfadjointView<Lower>() = mat.template selfadjointView<_UpLo>();
-  
-  Index n = m_L.cols(); 
-  Index nnz = m_L.nonZeros();
-  Map<ScalarType> vals(m_L.valuePtr(), nnz); //values
-  Map<IndexType> rowIdx(m_L.innerIndexPtr(), nnz);  //Row indices
-  Map<IndexType> colPtr( m_L.outerIndexPtr(), n+1); // Pointer to the beginning of each row
-  IndexType firstElt(n-1); // for each j, points to the next entry in vals that will be used in the factorization
-  VectorList listCol(n); // listCol(j) is a linked list of columns to update column j
-  ScalarType curCol(n); // Store a  nonzero values in each column
-  IndexType irow(n); // Row indices of nonzero elements in each column
-  
-  
-  // Computes the scaling factors 
-  m_scal.resize(n);
-  for (int j = 0; j < n; j++)
-  {
-    m_scal(j) = m_L.col(j).norm();
-    m_scal(j) = sqrt(m_scal(j));
-  }
-  // Scale and compute the shift for the matrix 
-  Scalar mindiag = vals[0];
-  for (int j = 0; j < n; j++){
-    for (int k = colPtr[j]; k < colPtr[j+1]; k++)
-     vals[k] /= (m_scal(j) * m_scal(rowIdx[k]));
-    mindiag = (min)(vals[colPtr[j]], mindiag);
-  }
-  
-  if(mindiag < Scalar(0.)) m_shift = m_shift - mindiag;
-  // Apply the shift to the diagonal elements of the matrix
-  for (int j = 0; j < n; j++)
-    vals[colPtr[j]] += m_shift;
-  // jki version of the Cholesky factorization 
-  for (int j=0; j < n; ++j)
-  {  
-    //Left-looking factorize the column j 
-    // First, load the jth column into curCol 
-    Scalar diag = vals[colPtr[j]];  // It is assumed that only the lower part is stored
-    curCol.setZero();
-    irow.setLinSpaced(n,0,n-1); 
-    for (int i = colPtr[j] + 1; i < colPtr[j+1]; i++)
-    {
-      curCol(rowIdx[i]) = vals[i]; 
-      irow(rowIdx[i]) = rowIdx[i]; 
-    }
-    std::list<int>::iterator k; 
-    // Browse all previous columns that will update column j
-    for(k = listCol[j].begin(); k != listCol[j].end(); k++) 
-    {
-      int jk = firstElt(*k); // First element to use in the column 
-      jk += 1; 
-      for (int i = jk; i < colPtr[*k+1]; i++)
-      {
-        curCol(rowIdx[i]) -= vals[i] * vals[jk] ;
-      }
-      updateList(colPtr,rowIdx,vals, *k, jk, firstElt, listCol);
-    }
-    
-    // Scale the current column
-    if(RealScalar(diag) <= 0) 
-    {
-      std::cerr << "\nNegative diagonal during Incomplete factorization... "<< j << "\n";
-      m_info = NumericalIssue; 
-      return; 
-    }
-    RealScalar rdiag = sqrt(RealScalar(diag));
-    vals[colPtr[j]] = rdiag;
-    for (int i = j+1; i < n; i++)
-    {
-      //Scale 
-      curCol(i) /= rdiag;
-      //Update the remaining diagonals with curCol
-      vals[colPtr[i]] -= curCol(i) * curCol(i);
-    }
-    // Select the largest p elements
-    //  p is the original number of elements in the column (without the diagonal)
-    int p = colPtr[j+1] - colPtr[j] - 1 ; 
-    internal::QuickSplit(curCol, irow, p); 
-    // Insert the largest p elements in the matrix
-    int cpt = 0; 
-    for (int i = colPtr[j]+1; i < colPtr[j+1]; i++)
-    {
-      vals[i] = curCol(cpt); 
-      rowIdx[i] = irow(cpt); 
-      cpt ++; 
-    }
-    // Get the first smallest row index and put it after the diagonal element
-    Index jk = colPtr(j)+1;
-    updateList(colPtr,rowIdx,vals,j,jk,firstElt,listCol); 
-  }
-  m_factorizationIsOk = true; 
-  m_isInitialized = true;
-  m_info = Success; 
-}
-
-template<typename Scalar, int _UpLo, typename OrderingType>
-template <typename IdxType, typename SclType>
-inline void IncompleteCholesky<Scalar,_UpLo, OrderingType>::updateList(const IdxType& colPtr, IdxType& rowIdx, SclType& vals, const Index& col, const Index& jk, IndexType& firstElt, VectorList& listCol)
-{
-  if (jk < colPtr(col+1) )
-  {
-    Index p = colPtr(col+1) - jk;
-    Index minpos; 
-    rowIdx.segment(jk,p).minCoeff(&minpos);
-    minpos += jk;
-    if (rowIdx(minpos) != rowIdx(jk))
-    {
-      //Swap
-      std::swap(rowIdx(jk),rowIdx(minpos));
-      std::swap(vals(jk),vals(minpos));
-    }
-    firstElt(col) = jk;
-    listCol[rowIdx(jk)].push_back(col);
-  }
-}
-namespace internal {
-
-template<typename _Scalar, int _UpLo, typename OrderingType, typename Rhs>
-struct solve_retval<IncompleteCholesky<_Scalar,  _UpLo, OrderingType>, Rhs>
-  : solve_retval_base<IncompleteCholesky<_Scalar, _UpLo, OrderingType>, Rhs>
-{
-  typedef IncompleteCholesky<_Scalar, _UpLo, OrderingType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-} // end namespace internal
-
-} // end namespace Eigen 
-
-#endif

Index: 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteLU.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteLU.h
+++ 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteLU.h
@@ -11,24 +11,28 @@
 #define EIGEN_INCOMPLETE_LU_H
 
 namespace Eigen { 
 
 template <typename _Scalar>
-class IncompleteLU
+class IncompleteLU : public SparseSolverBase<IncompleteLU<_Scalar> >
 {
+  protected:
+    typedef SparseSolverBase<IncompleteLU<_Scalar> > Base;
+    using Base::m_isInitialized;
+    
     typedef _Scalar Scalar;
     typedef Matrix<Scalar,Dynamic,1> Vector;
     typedef typename Vector::Index Index;
     typedef SparseMatrix<Scalar,RowMajor> FactorType;
 
   public:
     typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
 
-    IncompleteLU() : m_isInitialized(false) {}
+    IncompleteLU() {}
 
     template<typename MatrixType>
-    IncompleteLU(const MatrixType& mat) : m_isInitialized(false)
+    IncompleteLU(const MatrixType& mat)
     {
       compute(mat);
     }
 
     Index rows() const { return m_lu.rows(); }
@@ -69,45 +73,18 @@
       m_isInitialized = true;
       return *this;
     }
 
     template<typename Rhs, typename Dest>
-    void _solve(const Rhs& b, Dest& x) const
+    void _solve_impl(const Rhs& b, Dest& x) const
     {
       x = m_lu.template triangularView<UnitLower>().solve(b);
       x = m_lu.template triangularView<Upper>().solve(x);
     }
 
-    template<typename Rhs> inline const internal::solve_retval<IncompleteLU, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "IncompleteLU is not initialized.");
-      eigen_assert(cols()==b.rows()
-                && "IncompleteLU::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<IncompleteLU, Rhs>(*this, b.derived());
-    }
-
   protected:
     FactorType m_lu;
-    bool m_isInitialized;
-};
-
-namespace internal {
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<IncompleteLU<_MatrixType>, Rhs>
-  : solve_retval_base<IncompleteLU<_MatrixType>, Rhs>
-{
-  typedef IncompleteLU<_MatrixType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-} // end namespace internal
+};
 
 } // end namespace Eigen
 
 #endif // EIGEN_INCOMPLETE_LU_H

Index: 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/MINRES.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/MINRES.h
+++ 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/MINRES.h
@@ -1,10 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2012 Giacomo Po <gpo@ucla.edu>
-// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -27,51 +27,60 @@
          * \param tol_error On input the tolerance error, on output an estimation of the relative error.
          */
         template<typename MatrixType, typename Rhs, typename Dest, typename Preconditioner>
         EIGEN_DONT_INLINE
         void minres(const MatrixType& mat, const Rhs& rhs, Dest& x,
-                    const Preconditioner& precond, int& iters,
+                    const Preconditioner& precond, Index& iters,
                     typename Dest::RealScalar& tol_error)
         {
             using std::sqrt;
             typedef typename Dest::RealScalar RealScalar;
             typedef typename Dest::Scalar Scalar;
             typedef Matrix<Scalar,Dynamic,1> VectorType;
 
-            // initialize
-            const int maxIters(iters);  // initialize maxIters to iters
-            const int N(mat.cols());    // the size of the matrix
+            // Check for zero rhs
             const RealScalar rhsNorm2(rhs.squaredNorm());
+            if(rhsNorm2 == 0)
+            {
+                x.setZero();
+                iters = 0;
+                tol_error = 0;
+                return;
+            }
+            
+            // initialize
+            const Index maxIters(iters);  // initialize maxIters to iters
+            const Index N(mat.cols());    // the size of the matrix
             const RealScalar threshold2(tol_error*tol_error*rhsNorm2); // convergence threshold (compared to residualNorm2)
             
             // Initialize preconditioned Lanczos
-//            VectorType v_old(N); // will be initialized inside loop
+            VectorType v_old(N); // will be initialized inside loop
             VectorType v( VectorType::Zero(N) ); //initialize v
             VectorType v_new(rhs-mat*x); //initialize v_new
             RealScalar residualNorm2(v_new.squaredNorm());
-//            VectorType w(N); // will be initialized inside loop
+            VectorType w(N); // will be initialized inside loop
             VectorType w_new(precond.solve(v_new)); // initialize w_new
 //            RealScalar beta; // will be initialized inside loop
             RealScalar beta_new2(v_new.dot(w_new));
-            eigen_assert(beta_new2 >= 0 && "PRECONDITIONER IS NOT POSITIVE DEFINITE");
+            eigen_assert(beta_new2 >= 0.0 && "PRECONDITIONER IS NOT POSITIVE DEFINITE");
             RealScalar beta_new(sqrt(beta_new2));
             const RealScalar beta_one(beta_new);
             v_new /= beta_new;
             w_new /= beta_new;
             // Initialize other variables
             RealScalar c(1.0); // the cosine of the Givens rotation
             RealScalar c_old(1.0);
             RealScalar s(0.0); // the sine of the Givens rotation
             RealScalar s_old(0.0); // the sine of the Givens rotation
-//            VectorType p_oold(N); // will be initialized in loop
+            VectorType p_oold(N); // will be initialized in loop
             VectorType p_old(VectorType::Zero(N)); // initialize p_old=0
             VectorType p(p_old); // initialize p=0
             RealScalar eta(1.0);
                         
             iters = 0; // reset iters
-            while ( iters < maxIters ){
-                
+            while ( iters < maxIters )
+            {
                 // Preconditioned Lanczos
                 /* Note that there are 4 variants on the Lanczos algorithm. These are
                  * described in Paige, C. C. (1972). Computational variants of
                  * the Lanczos method for the eigenproblem. IMA Journal of Applied
                  * Mathematics, 10(3), 373–381. The current implementation corresponds 
@@ -79,21 +88,21 @@
                  * algorithm 6.14 in Y. Saad, Iterative Methods for Sparse Linear
                  * Systems, 2003 p.173. For the preconditioned version see 
                  * A. Greenbaum, Iterative Methods for Solving Linear Systems, SIAM (1987).
                  */
                 const RealScalar beta(beta_new);
-//                v_old = v; // update: at first time step, this makes v_old = 0 so value of beta doesn't matter
-                const VectorType v_old(v); // NOT SURE IF CREATING v_old EVERY ITERATION IS EFFICIENT
+                v_old = v; // update: at first time step, this makes v_old = 0 so value of beta doesn't matter
+//                const VectorType v_old(v); // NOT SURE IF CREATING v_old EVERY ITERATION IS EFFICIENT
                 v = v_new; // update
-//                w = w_new; // update
-                const VectorType w(w_new); // NOT SURE IF CREATING w EVERY ITERATION IS EFFICIENT
+                w = w_new; // update
+//                const VectorType w(w_new); // NOT SURE IF CREATING w EVERY ITERATION IS EFFICIENT
                 v_new.noalias() = mat*w - beta*v_old; // compute v_new
                 const RealScalar alpha = v_new.dot(w);
                 v_new -= alpha*v; // overwrite v_new
                 w_new = precond.solve(v_new); // overwrite w_new
                 beta_new2 = v_new.dot(w_new); // compute beta_new
-                eigen_assert(beta_new2 >= 0 && "PRECONDITIONER IS NOT POSITIVE DEFINITE");
+                eigen_assert(beta_new2 >= 0.0 && "PRECONDITIONER IS NOT POSITIVE DEFINITE");
                 beta_new = sqrt(beta_new2); // compute beta_new
                 v_new /= beta_new; // overwrite v_new for next iteration
                 w_new /= beta_new; // overwrite w_new for next iteration
                 
                 // Givens rotation
@@ -105,32 +114,38 @@
                 s_old = s; // store for next iteration
                 c=r1_hat/r1; // new cosine
                 s=beta_new/r1; // new sine
                 
                 // Update solution
-//                p_oold = p_old;
-                const VectorType p_oold(p_old); // NOT SURE IF CREATING p_oold EVERY ITERATION IS EFFICIENT
+                p_oold = p_old;
+//                const VectorType p_oold(p_old); // NOT SURE IF CREATING p_oold EVERY ITERATION IS EFFICIENT
                 p_old = p;
                 p.noalias()=(w-r2*p_old-r3*p_oold) /r1; // IS NOALIAS REQUIRED?
                 x += beta_one*c*eta*p;
+                
+                /* Update the squared residual. Note that this is the estimated residual.
+                The real residual |Ax-b|^2 may be slightly larger */
                 residualNorm2 *= s*s;
                 
-                if ( residualNorm2 < threshold2){
+                if ( residualNorm2 < threshold2)
+                {
                     break;
                 }
                 
                 eta=-s*eta; // update eta
                 iters++; // increment iteration number (for output purposes)
             }
-            tol_error = std::sqrt(residualNorm2 / rhsNorm2); // return error. Note that this is the estimated error. The real error |Ax-b|/|b| may be slightly larger 
+            
+            /* Compute error. Note that this is the estimated error. The real 
+             error |Ax-b|/|b| may be slightly larger */
+            tol_error = std::sqrt(residualNorm2 / rhsNorm2);
         }
         
     }
     
     template< typename _MatrixType, int _UpLo=Lower,
     typename _Preconditioner = IdentityPreconditioner>
-//    typename _Preconditioner = IdentityPreconditioner<typename _MatrixType::Scalar> > // preconditioner must be positive definite
     class MINRES;
     
     namespace internal {
         
         template< typename _MatrixType, int _UpLo, typename _Preconditioner>
@@ -148,12 +163,12 @@
      * This class allows to solve for A.x = b sparse linear problems using the MINRES algorithm
      * of Paige and Saunders (1975). The sparse matrix A must be symmetric (possibly indefinite).
      * The vectors x and b can be either dense or sparse.
      *
      * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix.
-     * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
-     *               or Upper. Default is Lower.
+     * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower,
+     *               Upper, or Lower|Upper in which the full matrix entries will be considered. Default is Lower.
      * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
      *
      * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
      * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
      * and NumTraits<Scalar>::epsilon() for the tolerance.
@@ -172,41 +187,30 @@
      * // update b, and solve again
      * x = mr.solve(b);
      * \endcode
      *
      * By default the iterations start with x=0 as an initial guess of the solution.
-     * One can control the start using the solveWithGuess() method. Here is a step by
-     * step execution example starting with a random guess and printing the evolution
-     * of the estimated error:
-     * * \code
-     * x = VectorXd::Random(n);
-     * mr.setMaxIterations(1);
-     * int i = 0;
-     * do {
-     *   x = mr.solveWithGuess(b,x);
-     *   std::cout << i << " : " << mr.error() << std::endl;
-     *   ++i;
-     * } while (mr.info()!=Success && i<100);
-     * \endcode
-     * Note that such a step by step excution is slightly slower.
+     * One can control the start using the solveWithGuess() method.
+     *
+     * MINRES can also be used in a matrix-free context, see the following \link MatrixfreeSolverExample example \endlink.
      *
      * \sa class ConjugateGradient, BiCGSTAB, SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
      */
     template< typename _MatrixType, int _UpLo, typename _Preconditioner>
     class MINRES : public IterativeSolverBase<MINRES<_MatrixType,_UpLo,_Preconditioner> >
     {
         
         typedef IterativeSolverBase<MINRES> Base;
-        using Base::mp_matrix;
+        using Base::matrix;
         using Base::m_error;
         using Base::m_iterations;
         using Base::m_info;
         using Base::m_isInitialized;
     public:
+        using Base::_solve_impl;
         typedef _MatrixType MatrixType;
         typedef typename MatrixType::Scalar Scalar;
-        typedef typename MatrixType::Index Index;
         typedef typename MatrixType::RealScalar RealScalar;
         typedef _Preconditioner Preconditioner;
         
         enum {UpLo = _UpLo};
         
@@ -223,80 +227,63 @@
          * \warning this class stores a reference to the matrix A as well as some
          * precomputed values that depend on it. Therefore, if \a A is changed
          * this class becomes invalid. Call compute() to update it with the new
          * matrix A, or modify a copy of A.
          */
-        MINRES(const MatrixType& A) : Base(A) {}
+        template<typename MatrixDerived>
+        explicit MINRES(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
         
         /** Destructor. */
         ~MINRES(){}
-		
-        /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A
-         * \a x0 as an initial solution.
-         *
-         * \sa compute()
-         */
-        template<typename Rhs,typename Guess>
-        inline const internal::solve_retval_with_guess<MINRES, Rhs, Guess>
-        solveWithGuess(const MatrixBase<Rhs>& b, const Guess& x0) const
-        {
-            eigen_assert(m_isInitialized && "MINRES is not initialized.");
-            eigen_assert(Base::rows()==b.rows()
-                         && "MINRES::solve(): invalid number of rows of the right hand side matrix b");
-            return internal::solve_retval_with_guess
-            <MINRES, Rhs, Guess>(*this, b.derived(), x0);
-        }
-        
+
         /** \internal */
         template<typename Rhs,typename Dest>
-        void _solveWithGuess(const Rhs& b, Dest& x) const
+        void _solve_with_guess_impl(const Rhs& b, Dest& x) const
         {
+            typedef typename Base::MatrixWrapper MatrixWrapper;
+            typedef typename Base::ActualMatrixType ActualMatrixType;
+            enum {
+              TransposeInput  =   (!MatrixWrapper::MatrixFree)
+                              &&  (UpLo==(Lower|Upper))
+                              &&  (!MatrixType::IsRowMajor)
+                              &&  (!NumTraits<Scalar>::IsComplex)
+            };
+            typedef typename internal::conditional<TransposeInput,Transpose<const ActualMatrixType>, ActualMatrixType const&>::type RowMajorWrapper;
+            EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(MatrixWrapper::MatrixFree,UpLo==(Lower|Upper)),MATRIX_FREE_CONJUGATE_GRADIENT_IS_COMPATIBLE_WITH_UPPER_UNION_LOWER_MODE_ONLY);
+            typedef typename internal::conditional<UpLo==(Lower|Upper),
+                                                  RowMajorWrapper,
+                                                  typename MatrixWrapper::template ConstSelfAdjointViewReturnType<UpLo>::Type
+                                            >::type SelfAdjointWrapper;
+
             m_iterations = Base::maxIterations();
             m_error = Base::m_tolerance;
-            
+            RowMajorWrapper row_mat(matrix());
             for(int j=0; j<b.cols(); ++j)
             {
                 m_iterations = Base::maxIterations();
                 m_error = Base::m_tolerance;
                 
                 typename Dest::ColXpr xj(x,j);
-                internal::minres(mp_matrix->template selfadjointView<UpLo>(), b.col(j), xj,
+                internal::minres(SelfAdjointWrapper(row_mat), b.col(j), xj,
                                  Base::m_preconditioner, m_iterations, m_error);
             }
             
             m_isInitialized = true;
             m_info = m_error <= Base::m_tolerance ? Success : NoConvergence;
         }
         
         /** \internal */
         template<typename Rhs,typename Dest>
-        void _solve(const Rhs& b, Dest& x) const
+        void _solve_impl(const Rhs& b, MatrixBase<Dest> &x) const
         {
             x.setZero();
-            _solveWithGuess(b,x);
+            _solve_with_guess_impl(b,x.derived());
         }
         
     protected:
         
     };
-    
-    namespace internal {
-        
-        template<typename _MatrixType, int _UpLo, typename _Preconditioner, typename Rhs>
-        struct solve_retval<MINRES<_MatrixType,_UpLo,_Preconditioner>, Rhs>
-        : solve_retval_base<MINRES<_MatrixType,_UpLo,_Preconditioner>, Rhs>
-        {
-            typedef MINRES<_MatrixType,_UpLo,_Preconditioner> Dec;
-            EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-            
-            template<typename Dest> void evalTo(Dest& dst) const
-            {
-                dec()._solve(rhs(),dst);
-            }
-        };
-        
-    } // end namespace internal
-    
+
 } // end namespace Eigen
 
 #endif // EIGEN_MINRES_H
 

Index: 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/Scaling.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/Scaling.h
+++ 3rd_party/eigen/unsupported/Eigen/src/IterativeSolvers/Scaling.h
@@ -7,10 +7,13 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ITERSCALING_H
 #define EIGEN_ITERSCALING_H
+
+namespace Eigen {
+
 /**
   * \ingroup IterativeSolvers_Module
   * \brief iterative scaling algorithm to equilibrate rows and column norms in matrices
   * 
   * This class can be used as a preprocessing tool to accelerate the convergence of iterative methods 
@@ -39,12 +42,10 @@
   * 
   * References : D. Ruiz and B. Ucar, A Symmetry Preserving Algorithm for Matrix Scaling, INRIA Research report RR-7552
   * 
   * \sa \ref IncompleteLUT 
   */
-namespace Eigen {
-using std::abs; 
 template<typename _MatrixType>
 class IterScaling
 {
   public:
     typedef _MatrixType MatrixType; 
@@ -69,10 +70,11 @@
      * 
      * \sa LeftScaling() RightScaling()
      */
     void compute (const MatrixType& mat)
     {
+      using std::abs;
       int m = mat.rows(); 
       int n = mat.cols();
       eigen_assert((m>0 && m == n) && "Please give a non - empty matrix");
       m_left.resize(m); 
       m_right.resize(n);

DELETED 3rd_party/eigen/unsupported/Eigen/src/KroneckerProduct/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/KroneckerProduct/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/KroneckerProduct/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/KroneckerProduct/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_KroneckerProduct_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_KroneckerProduct_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/KroneckerProduct COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h
+++ 3rd_party/eigen/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h
@@ -10,15 +10,67 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef KRONECKER_TENSOR_PRODUCT_H
 #define KRONECKER_TENSOR_PRODUCT_H
 
-namespace Eigen { 
+namespace Eigen {
+
+/*!
+ * \ingroup KroneckerProduct_Module
+ *
+ * \brief The base class of dense and sparse Kronecker product.
+ *
+ * \tparam Derived is the derived type.
+ */
+template<typename Derived>
+class KroneckerProductBase : public ReturnByValue<Derived>
+{
+  private:
+    typedef typename internal::traits<Derived> Traits;
+    typedef typename Traits::Scalar Scalar;
+
+  protected:
+    typedef typename Traits::Lhs Lhs;
+    typedef typename Traits::Rhs Rhs;
+
+  public:
+    /*! \brief Constructor. */
+    KroneckerProductBase(const Lhs& A, const Rhs& B)
+      : m_A(A), m_B(B)
+    {}
+
+    inline Index rows() const { return m_A.rows() * m_B.rows(); }
+    inline Index cols() const { return m_A.cols() * m_B.cols(); }
+
+    /*!
+     * This overrides ReturnByValue::coeff because this function is
+     * efficient enough.
+     */
+    Scalar coeff(Index row, Index col) const
+    {
+      return m_A.coeff(row / m_B.rows(), col / m_B.cols()) *
+             m_B.coeff(row % m_B.rows(), col % m_B.cols());
+    }
+
+    /*!
+     * This overrides ReturnByValue::coeff because this function is
+     * efficient enough.
+     */
+    Scalar coeff(Index i) const
+    {
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
+      return m_A.coeff(i / m_A.size()) * m_B.coeff(i % m_A.size());
+    }
 
-template<typename Scalar, int Options, typename Index> class SparseMatrix;
+  protected:
+    typename Lhs::Nested m_A;
+    typename Rhs::Nested m_B;
+};
 
 /*!
+ * \ingroup KroneckerProduct_Module
+ *
  * \brief Kronecker tensor product helper class for dense matrices
  *
  * This class is the return value of kroneckerProduct(MatrixBase,
  * MatrixBase). Use the function rather than construct this class
  * directly to avoid specifying template prarameters.
@@ -25,47 +77,30 @@
  *
  * \tparam Lhs  Type of the left-hand side, a matrix expression.
  * \tparam Rhs  Type of the rignt-hand side, a matrix expression.
  */
 template<typename Lhs, typename Rhs>
-class KroneckerProduct : public ReturnByValue<KroneckerProduct<Lhs,Rhs> >
+class KroneckerProduct : public KroneckerProductBase<KroneckerProduct<Lhs,Rhs> >
 {
   private:
-    typedef ReturnByValue<KroneckerProduct> Base;
-    typedef typename Base::Scalar Scalar;
-    typedef typename Base::Index Index;
+    typedef KroneckerProductBase<KroneckerProduct> Base;
+    using Base::m_A;
+    using Base::m_B;
 
   public:
     /*! \brief Constructor. */
     KroneckerProduct(const Lhs& A, const Rhs& B)
-      : m_A(A), m_B(B)
+      : Base(A, B)
     {}
 
     /*! \brief Evaluate the Kronecker tensor product. */
     template<typename Dest> void evalTo(Dest& dst) const;
-    
-    inline Index rows() const { return m_A.rows() * m_B.rows(); }
-    inline Index cols() const { return m_A.cols() * m_B.cols(); }
-
-    Scalar coeff(Index row, Index col) const
-    {
-      return m_A.coeff(row / m_B.rows(), col / m_B.cols()) *
-             m_B.coeff(row % m_B.rows(), col % m_B.cols());
-    }
-
-    Scalar coeff(Index i) const
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(KroneckerProduct);
-      return m_A.coeff(i / m_A.size()) * m_B.coeff(i % m_A.size());
-    }
-
-  private:
-    typename Lhs::Nested m_A;
-    typename Rhs::Nested m_B;
 };
 
 /*!
+ * \ingroup KroneckerProduct_Module
+ *
  * \brief Kronecker tensor product helper class for sparse matrices
  *
  * If at least one of the operands is a sparse matrix expression,
  * then this class is returned and evaluates into a sparse matrix.
  *
@@ -75,38 +110,25 @@
  *
  * \tparam Lhs  Type of the left-hand side, a matrix expression.
  * \tparam Rhs  Type of the rignt-hand side, a matrix expression.
  */
 template<typename Lhs, typename Rhs>
-class KroneckerProductSparse : public EigenBase<KroneckerProductSparse<Lhs,Rhs> >
+class KroneckerProductSparse : public KroneckerProductBase<KroneckerProductSparse<Lhs,Rhs> >
 {
   private:
-    typedef typename internal::traits<KroneckerProductSparse>::Index Index;
+    typedef KroneckerProductBase<KroneckerProductSparse> Base;
+    using Base::m_A;
+    using Base::m_B;
 
   public:
     /*! \brief Constructor. */
     KroneckerProductSparse(const Lhs& A, const Rhs& B)
-      : m_A(A), m_B(B)
+      : Base(A, B)
     {}
 
     /*! \brief Evaluate the Kronecker tensor product. */
     template<typename Dest> void evalTo(Dest& dst) const;
-    
-    inline Index rows() const { return m_A.rows() * m_B.rows(); }
-    inline Index cols() const { return m_A.cols() * m_B.cols(); }
-
-    template<typename Scalar, int Options, typename Index>
-    operator SparseMatrix<Scalar, Options, Index>()
-    {
-      SparseMatrix<Scalar, Options, Index> result;
-      evalTo(result.derived());
-      return result;
-    }
-
-  private:
-    typename Lhs::Nested m_A;
-    typename Rhs::Nested m_B;
 };
 
 template<typename Lhs, typename Rhs>
 template<typename Dest>
 void KroneckerProduct<Lhs,Rhs>::evalTo(Dest& dst) const
@@ -122,26 +144,53 @@
 
 template<typename Lhs, typename Rhs>
 template<typename Dest>
 void KroneckerProductSparse<Lhs,Rhs>::evalTo(Dest& dst) const
 {
-  const Index Br = m_B.rows(),
-              Bc = m_B.cols();
-  dst.resize(rows(),cols());
+  Index Br = m_B.rows(), Bc = m_B.cols();
+  dst.resize(this->rows(), this->cols());
   dst.resizeNonZeros(0);
-  dst.reserve(m_A.nonZeros() * m_B.nonZeros());
+  
+  // 1 - evaluate the operands if needed:
+  typedef typename internal::nested_eval<Lhs,Dynamic>::type Lhs1;
+  typedef typename internal::remove_all<Lhs1>::type Lhs1Cleaned;
+  const Lhs1 lhs1(m_A);
+  typedef typename internal::nested_eval<Rhs,Dynamic>::type Rhs1;
+  typedef typename internal::remove_all<Rhs1>::type Rhs1Cleaned;
+  const Rhs1 rhs1(m_B);
+    
+  // 2 - construct respective iterators
+  typedef Eigen::InnerIterator<Lhs1Cleaned> LhsInnerIterator;
+  typedef Eigen::InnerIterator<Rhs1Cleaned> RhsInnerIterator;
+  
+  // compute number of non-zeros per innervectors of dst
+  {
+    // TODO VectorXi is not necessarily big enough!
+    VectorXi nnzA = VectorXi::Zero(Dest::IsRowMajor ? m_A.rows() : m_A.cols());
+    for (Index kA=0; kA < m_A.outerSize(); ++kA)
+      for (LhsInnerIterator itA(lhs1,kA); itA; ++itA)
+        nnzA(Dest::IsRowMajor ? itA.row() : itA.col())++;
+      
+    VectorXi nnzB = VectorXi::Zero(Dest::IsRowMajor ? m_B.rows() : m_B.cols());
+    for (Index kB=0; kB < m_B.outerSize(); ++kB)
+      for (RhsInnerIterator itB(rhs1,kB); itB; ++itB)
+        nnzB(Dest::IsRowMajor ? itB.row() : itB.col())++;
+    
+    Matrix<int,Dynamic,Dynamic,ColMajor> nnzAB = nnzB * nnzA.transpose();
+    dst.reserve(VectorXi::Map(nnzAB.data(), nnzAB.size()));
+  }
 
   for (Index kA=0; kA < m_A.outerSize(); ++kA)
   {
     for (Index kB=0; kB < m_B.outerSize(); ++kB)
     {
-      for (typename Lhs::InnerIterator itA(m_A,kA); itA; ++itA)
+      for (LhsInnerIterator itA(lhs1,kA); itA; ++itA)
       {
-        for (typename Rhs::InnerIterator itB(m_B,kB); itB; ++itB)
+        for (RhsInnerIterator itB(rhs1,kB); itB; ++itB)
         {
-          const Index i = itA.row() * Br + itB.row(),
-                      j = itA.col() * Bc + itB.col();
+          Index i = itA.row() * Br + itB.row(),
+                j = itA.col() * Bc + itB.col();
           dst.insert(i,j) = itA.value() * itB.value();
         }
       }
     }
   }
@@ -152,18 +201,18 @@
 template<typename _Lhs, typename _Rhs>
 struct traits<KroneckerProduct<_Lhs,_Rhs> >
 {
   typedef typename remove_all<_Lhs>::type Lhs;
   typedef typename remove_all<_Rhs>::type Rhs;
-  typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
+  typedef typename ScalarBinaryOpTraits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
+  typedef typename promote_index_type<typename Lhs::StorageIndex, typename Rhs::StorageIndex>::type StorageIndex;
 
   enum {
     Rows = size_at_compile_time<traits<Lhs>::RowsAtCompileTime, traits<Rhs>::RowsAtCompileTime>::ret,
     Cols = size_at_compile_time<traits<Lhs>::ColsAtCompileTime, traits<Rhs>::ColsAtCompileTime>::ret,
     MaxRows = size_at_compile_time<traits<Lhs>::MaxRowsAtCompileTime, traits<Rhs>::MaxRowsAtCompileTime>::ret,
-    MaxCols = size_at_compile_time<traits<Lhs>::MaxColsAtCompileTime, traits<Rhs>::MaxColsAtCompileTime>::ret,
-    CoeffReadCost = Lhs::CoeffReadCost + Rhs::CoeffReadCost + NumTraits<Scalar>::MulCost
+    MaxCols = size_at_compile_time<traits<Lhs>::MaxColsAtCompileTime, traits<Rhs>::MaxColsAtCompileTime>::ret
   };
 
   typedef Matrix<Scalar,Rows,Cols> ReturnType;
 };
 
@@ -171,13 +220,13 @@
 struct traits<KroneckerProductSparse<_Lhs,_Rhs> >
 {
   typedef MatrixXpr XprKind;
   typedef typename remove_all<_Lhs>::type Lhs;
   typedef typename remove_all<_Rhs>::type Rhs;
-  typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
-  typedef typename promote_storage_type<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind>::ret StorageKind;
-  typedef typename promote_index_type<typename Lhs::Index, typename Rhs::Index>::type Index;
+  typedef typename ScalarBinaryOpTraits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
+  typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind, scalar_product_op<typename Lhs::Scalar, typename Rhs::Scalar> >::ret StorageKind;
+  typedef typename promote_index_type<typename Lhs::StorageIndex, typename Rhs::StorageIndex>::type StorageIndex;
 
   enum {
     LhsFlags = Lhs::Flags,
     RhsFlags = Rhs::Flags,
 
@@ -188,13 +237,15 @@
 
     EvalToRowMajor = (LhsFlags & RhsFlags & RowMajorBit),
     RemovedBits = ~(EvalToRowMajor ? 0 : RowMajorBit),
 
     Flags = ((LhsFlags | RhsFlags) & HereditaryBits & RemovedBits)
-          | EvalBeforeNestingBit | EvalBeforeAssigningBit,
-    CoeffReadCost = Dynamic
+          | EvalBeforeNestingBit,
+    CoeffReadCost = HugeCost
   };
+
+  typedef SparseMatrix<Scalar, 0, StorageIndex> ReturnType;
 };
 
 } // end namespace internal
 
 /*!
@@ -225,10 +276,20 @@
 /*!
  * \ingroup KroneckerProduct_Module
  *
  * Computes Kronecker tensor product of two matrices, at least one of
  * which is sparse
+ *
+ * \warning If you want to replace a matrix by its Kronecker product
+ *          with some matrix, do \b NOT do this:
+ * \code
+ * A = kroneckerProduct(A,B); // bug!!! caused by aliasing effect
+ * \endcode
+ * instead, use eval() to work around this:
+ * \code
+ * A = kroneckerProduct(A,B).eval();
+ * \endcode
  *
  * \param a  Dense/sparse matrix a
  * \param b  Dense/sparse matrix b
  * \return   Kronecker tensor product of a and b, stored in a sparse
  *           matrix

DELETED 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_LevenbergMarquardt_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_LevenbergMarquardt_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/LevenbergMarquardt COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMcovar.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMcovar.h
+++ 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMcovar.h
@@ -21,11 +21,10 @@
         Matrix< Scalar, Dynamic, Dynamic > &r,
         const VectorXi& ipvt,
         Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon()) )
 {
     using std::abs;
-    typedef DenseIndex Index;
     /* Local variables */
     Index i, j, k, l, ii, jj;
     bool sing;
     Scalar temp;
 

Index: 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMpar.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMpar.h
+++ 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMpar.h
@@ -28,11 +28,11 @@
   {
     using std::sqrt;
     using std::abs;
     typedef typename QRSolver::MatrixType MatrixType;
     typedef typename QRSolver::Scalar Scalar;
-    typedef typename QRSolver::Index Index;
+//    typedef typename QRSolver::StorageIndex StorageIndex;
 
     /* Local variables */
     Index j;
     Scalar fp;
     Scalar parc, parl;

Index: 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMqrsolv.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMqrsolv.h
+++ 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LMqrsolv.h
@@ -17,22 +17,21 @@
 
 namespace Eigen { 
 
 namespace internal {
 
-template <typename Scalar,int Rows, int Cols, typename Index>
+template <typename Scalar,int Rows, int Cols, typename PermIndex>
 void lmqrsolv(
   Matrix<Scalar,Rows,Cols> &s,
-  const PermutationMatrix<Dynamic,Dynamic,Index> &iPerm,
+  const PermutationMatrix<Dynamic,Dynamic,PermIndex> &iPerm,
   const Matrix<Scalar,Dynamic,1> &diag,
   const Matrix<Scalar,Dynamic,1> &qtb,
   Matrix<Scalar,Dynamic,1> &x,
   Matrix<Scalar,Dynamic,1> &sdiag)
 {
-
     /* Local variables */
-    Index i, j, k, l;
+    Index i, j, k;
     Scalar temp;
     Index n = s.cols();
     Matrix<Scalar,Dynamic,1>  wa(n);
     JacobiRotation<Scalar> givens;
 
@@ -50,11 +49,11 @@
     /*     eliminate the diagonal matrix d using a givens rotation. */
     for (j = 0; j < n; ++j) {
 
         /*        prepare the row of d to be eliminated, locating the */
         /*        diagonal element using p from the qr factorization. */
-        l = iPerm.indices()(j);
+        const PermIndex l = iPerm.indices()(j);
         if (diag[l] == 0.)
             break;
         sdiag.tail(n-j).setZero();
         sdiag[j] = diag[l];
 

Index: 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h
+++ 3rd_party/eigen/unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h
@@ -113,12 +113,11 @@
     typedef _FunctorType FunctorType;
     typedef typename FunctorType::QRSolver QRSolver;
     typedef typename FunctorType::JacobianType JacobianType;
     typedef typename JacobianType::Scalar Scalar;
     typedef typename JacobianType::RealScalar RealScalar; 
-    typedef typename JacobianType::Index Index;
-    typedef typename QRSolver::Index PermIndex;
+    typedef typename QRSolver::StorageIndex PermIndex;
     typedef Matrix<Scalar,Dynamic,1> FVectorType;
     typedef PermutationMatrix<Dynamic,Dynamic> PermutationType;
   public:
     LevenbergMarquardt(FunctorType& functor) 
     : m_functor(functor),m_nfev(0),m_njev(0),m_fnorm(0.0),m_gnorm(0),
@@ -142,15 +141,17 @@
             const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon())
             );
     
     /** Sets the default parameters */
     void resetParameters() 
-    { 
+    {
+      using std::sqrt;        
+
       m_factor = 100.; 
       m_maxfev = 400; 
-      m_ftol = std::sqrt(NumTraits<RealScalar>::epsilon());
-      m_xtol = std::sqrt(NumTraits<RealScalar>::epsilon());
+      m_ftol = sqrt(NumTraits<RealScalar>::epsilon());
+      m_xtol = sqrt(NumTraits<RealScalar>::epsilon());
       m_gtol = 0. ; 
       m_epsfcn = 0. ;
     }
     
     /** Sets the tolerance for the norm of the solution vector*/
@@ -171,10 +172,28 @@
     /** Sets the maximum number of function evaluation */
     void setMaxfev(Index maxfev) {m_maxfev = maxfev; }
     
     /** Use an external Scaling. If set to true, pass a nonzero diagonal to diag() */
     void setExternalScaling(bool value) {m_useExternalScaling  = value; }
+    
+    /** \returns the tolerance for the norm of the solution vector */
+    RealScalar xtol() const {return m_xtol; }
+    
+    /** \returns the tolerance for the norm of the vector function */
+    RealScalar ftol() const {return m_ftol; }
+    
+    /** \returns the tolerance for the norm of the gradient of the error vector */
+    RealScalar gtol() const {return m_gtol; }
+    
+    /** \returns the step bound for the diagonal shift */
+    RealScalar factor() const {return m_factor; }
+    
+    /** \returns the error precision */
+    RealScalar epsilon() const {return m_epsfcn; }
+    
+    /** \returns the maximum number of function evaluation */
+    Index maxfev() const {return m_maxfev; }
     
     /** \returns a reference to the diagonal of the jacobian */
     FVectorType& diag() {return m_diag; }
     
     /** \returns the number of iterations performed */
@@ -283,11 +302,11 @@
     //FIXME Sparse Case : Allocate space for the jacobian
     m_fjac.resize(m, n);
 //     m_fjac.reserve(VectorXi::Constant(n,5)); // FIXME Find a better alternative
     if (!m_useExternalScaling)
         m_diag.resize(n);
-    eigen_assert( (!m_useExternalScaling || m_diag.size()==n) || "When m_useExternalScaling is set, the caller must provide a valid 'm_diag'");
+    eigen_assert( (!m_useExternalScaling || m_diag.size()==n) && "When m_useExternalScaling is set, the caller must provide a valid 'm_diag'");
     m_qtf.resize(n);
 
     /* Function Body */
     m_nfev = 0;
     m_njev = 0;

DELETED 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_MatrixFunctions_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_MatrixFunctions_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/MatrixFunctions COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
+++ 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
@@ -1,10 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009, 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
-// Copyright (C) 2011 Chen-Pang He <jdh8@ms63.hinet.net>
+// Copyright (C) 2009, 2010, 2013 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2011, 2013 Chen-Pang He <jdh8@ms63.hinet.net>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -12,425 +12,406 @@
 #define EIGEN_MATRIX_EXPONENTIAL
 
 #include "StemFunction.h"
 
 namespace Eigen {
-
-/** \ingroup MatrixFunctions_Module
-  * \brief Class for computing the matrix exponential.
-  * \tparam MatrixType type of the argument of the exponential,
-  * expected to be an instantiation of the Matrix class template.
-  */
-template <typename MatrixType>
-class MatrixExponential {
-
-  public:
-
-    /** \brief Constructor.
-      * 
-      * The class stores a reference to \p M, so it should not be
-      * changed (or destroyed) before compute() is called.
-      *
-      * \param[in] M  matrix whose exponential is to be computed.
-      */
-    MatrixExponential(const MatrixType &M);
-
-    /** \brief Computes the matrix exponential.
-      *
-      * \param[out] result  the matrix exponential of \p M in the constructor.
-      */
-    template <typename ResultType> 
-    void compute(ResultType &result);
+namespace internal {
+
+/** \brief Scaling operator.
+ *
+ * This struct is used by CwiseUnaryOp to scale a matrix by \f$ 2^{-s} \f$.
+ */
+template <typename RealScalar>
+struct MatrixExponentialScalingOp
+{
+  /** \brief Constructor.
+   *
+   * \param[in] squarings  The integer \f$ s \f$ in this document.
+   */
+  MatrixExponentialScalingOp(int squarings) : m_squarings(squarings) { }
+
+
+  /** \brief Scale a matrix coefficient.
+   *
+   * \param[in,out] x  The scalar to be scaled, becoming \f$ 2^{-s} x \f$.
+   */
+  inline const RealScalar operator() (const RealScalar& x) const
+  {
+    using std::ldexp;
+    return ldexp(x, -m_squarings);
+  }
+
+  typedef std::complex<RealScalar> ComplexScalar;
+
+  /** \brief Scale a matrix coefficient.
+   *
+   * \param[in,out] x  The scalar to be scaled, becoming \f$ 2^{-s} x \f$.
+   */
+  inline const ComplexScalar operator() (const ComplexScalar& x) const
+  {
+    using std::ldexp;
+    return ComplexScalar(ldexp(x.real(), -m_squarings), ldexp(x.imag(), -m_squarings));
+  }
 
   private:
-
-    // Prevent copying
-    MatrixExponential(const MatrixExponential&);
-    MatrixExponential& operator=(const MatrixExponential&);
-
-    /** \brief Compute the (3,3)-Pad&eacute; approximant to the exponential.
-     *
-     *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
-     *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
-     *
-     *  \param[in] A   Argument of matrix exponential
-     */
-    void pade3(const MatrixType &A);
-
-    /** \brief Compute the (5,5)-Pad&eacute; approximant to the exponential.
-     *
-     *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
-     *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
-     *
-     *  \param[in] A   Argument of matrix exponential
-     */
-    void pade5(const MatrixType &A);
-
-    /** \brief Compute the (7,7)-Pad&eacute; approximant to the exponential.
-     *
-     *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
-     *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
-     *
-     *  \param[in] A   Argument of matrix exponential
-     */
-    void pade7(const MatrixType &A);
-
-    /** \brief Compute the (9,9)-Pad&eacute; approximant to the exponential.
-     *
-     *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
-     *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
-     *
-     *  \param[in] A   Argument of matrix exponential
-     */
-    void pade9(const MatrixType &A);
-
-    /** \brief Compute the (13,13)-Pad&eacute; approximant to the exponential.
-     *
-     *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
-     *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
-     *
-     *  \param[in] A   Argument of matrix exponential
-     */
-    void pade13(const MatrixType &A);
-
-    /** \brief Compute the (17,17)-Pad&eacute; approximant to the exponential.
-     *
-     *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
-     *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
-     *
-     *  This function activates only if your long double is double-double or quadruple.
-     *
-     *  \param[in] A   Argument of matrix exponential
-     */
-    void pade17(const MatrixType &A);
-
-    /** \brief Compute Pad&eacute; approximant to the exponential.
-     *
-     * Computes \c m_U, \c m_V and \c m_squarings such that
-     * \f$ (V+U)(V-U)^{-1} \f$ is a Pad&eacute; of
-     * \f$ \exp(2^{-\mbox{squarings}}M) \f$ around \f$ M = 0 \f$. The
-     * degree of the Pad&eacute; approximant and the value of
-     * squarings are chosen such that the approximation error is no
-     * more than the round-off error.
-     *
-     * The argument of this function should correspond with the (real
-     * part of) the entries of \c m_M.  It is used to select the
-     * correct implementation using overloading.
-     */
-    void computeUV(double);
-
-    /** \brief Compute Pad&eacute; approximant to the exponential.
-     *
-     *  \sa computeUV(double);
-     */
-    void computeUV(float);
-    
-    /** \brief Compute Pad&eacute; approximant to the exponential.
-     *
-     *  \sa computeUV(double);
-     */
-    void computeUV(long double);
-
-    typedef typename internal::traits<MatrixType>::Scalar Scalar;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename std::complex<RealScalar> ComplexScalar;
-
-    /** \brief Reference to matrix whose exponential is to be computed. */
-    typename internal::nested<MatrixType>::type m_M;
-
-    /** \brief Odd-degree terms in numerator of Pad&eacute; approximant. */
-    MatrixType m_U;
-
-    /** \brief Even-degree terms in numerator of Pad&eacute; approximant. */
-    MatrixType m_V;
-
-    /** \brief Used for temporary storage. */
-    MatrixType m_tmp1;
-
-    /** \brief Used for temporary storage. */
-    MatrixType m_tmp2;
-
-    /** \brief Identity matrix of the same size as \c m_M. */
-    MatrixType m_Id;
-
-    /** \brief Number of squarings required in the last step. */
     int m_squarings;
+};
+
+/** \brief Compute the (3,3)-Pad&eacute; approximant to the exponential.
+ *
+ *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
+ *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
+ */
+template <typename MatA, typename MatU, typename MatV>
+void matrix_exp_pade3(const MatA& A, MatU& U, MatV& V)
+{
+  typedef typename MatA::PlainObject MatrixType;
+  typedef typename NumTraits<typename traits<MatA>::Scalar>::Real RealScalar;
+  const RealScalar b[] = {120.L, 60.L, 12.L, 1.L};
+  const MatrixType A2 = A * A;
+  const MatrixType tmp = b[3] * A2 + b[1] * MatrixType::Identity(A.rows(), A.cols());
+  U.noalias() = A * tmp;
+  V = b[2] * A2 + b[0] * MatrixType::Identity(A.rows(), A.cols());
+}
+
+/** \brief Compute the (5,5)-Pad&eacute; approximant to the exponential.
+ *
+ *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
+ *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
+ */
+template <typename MatA, typename MatU, typename MatV>
+void matrix_exp_pade5(const MatA& A, MatU& U, MatV& V)
+{
+  typedef typename MatA::PlainObject MatrixType;
+  typedef typename NumTraits<typename traits<MatrixType>::Scalar>::Real RealScalar;
+  const RealScalar b[] = {30240.L, 15120.L, 3360.L, 420.L, 30.L, 1.L};
+  const MatrixType A2 = A * A;
+  const MatrixType A4 = A2 * A2;
+  const MatrixType tmp = b[5] * A4 + b[3] * A2 + b[1] * MatrixType::Identity(A.rows(), A.cols());
+  U.noalias() = A * tmp;
+  V = b[4] * A4 + b[2] * A2 + b[0] * MatrixType::Identity(A.rows(), A.cols());
+}
+
+/** \brief Compute the (7,7)-Pad&eacute; approximant to the exponential.
+ *
+ *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
+ *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
+ */
+template <typename MatA, typename MatU, typename MatV>
+void matrix_exp_pade7(const MatA& A, MatU& U, MatV& V)
+{
+  typedef typename MatA::PlainObject MatrixType;
+  typedef typename NumTraits<typename traits<MatrixType>::Scalar>::Real RealScalar;
+  const RealScalar b[] = {17297280.L, 8648640.L, 1995840.L, 277200.L, 25200.L, 1512.L, 56.L, 1.L};
+  const MatrixType A2 = A * A;
+  const MatrixType A4 = A2 * A2;
+  const MatrixType A6 = A4 * A2;
+  const MatrixType tmp = b[7] * A6 + b[5] * A4 + b[3] * A2 
+    + b[1] * MatrixType::Identity(A.rows(), A.cols());
+  U.noalias() = A * tmp;
+  V = b[6] * A6 + b[4] * A4 + b[2] * A2 + b[0] * MatrixType::Identity(A.rows(), A.cols());
+
+}
+
+/** \brief Compute the (9,9)-Pad&eacute; approximant to the exponential.
+ *
+ *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
+ *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
+ */
+template <typename MatA, typename MatU, typename MatV>
+void matrix_exp_pade9(const MatA& A, MatU& U, MatV& V)
+{
+  typedef typename MatA::PlainObject MatrixType;
+  typedef typename NumTraits<typename traits<MatrixType>::Scalar>::Real RealScalar;
+  const RealScalar b[] = {17643225600.L, 8821612800.L, 2075673600.L, 302702400.L, 30270240.L,
+                          2162160.L, 110880.L, 3960.L, 90.L, 1.L};
+  const MatrixType A2 = A * A;
+  const MatrixType A4 = A2 * A2;
+  const MatrixType A6 = A4 * A2;
+  const MatrixType A8 = A6 * A2;
+  const MatrixType tmp = b[9] * A8 + b[7] * A6 + b[5] * A4 + b[3] * A2 
+    + b[1] * MatrixType::Identity(A.rows(), A.cols());
+  U.noalias() = A * tmp;
+  V = b[8] * A8 + b[6] * A6 + b[4] * A4 + b[2] * A2 + b[0] * MatrixType::Identity(A.rows(), A.cols());
+}
+
+/** \brief Compute the (13,13)-Pad&eacute; approximant to the exponential.
+ *
+ *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
+ *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
+ */
+template <typename MatA, typename MatU, typename MatV>
+void matrix_exp_pade13(const MatA& A, MatU& U, MatV& V)
+{
+  typedef typename MatA::PlainObject MatrixType;
+  typedef typename NumTraits<typename traits<MatrixType>::Scalar>::Real RealScalar;
+  const RealScalar b[] = {64764752532480000.L, 32382376266240000.L, 7771770303897600.L,
+                          1187353796428800.L, 129060195264000.L, 10559470521600.L, 670442572800.L,
+                          33522128640.L, 1323241920.L, 40840800.L, 960960.L, 16380.L, 182.L, 1.L};
+  const MatrixType A2 = A * A;
+  const MatrixType A4 = A2 * A2;
+  const MatrixType A6 = A4 * A2;
+  V = b[13] * A6 + b[11] * A4 + b[9] * A2; // used for temporary storage
+  MatrixType tmp = A6 * V;
+  tmp += b[7] * A6 + b[5] * A4 + b[3] * A2 + b[1] * MatrixType::Identity(A.rows(), A.cols());
+  U.noalias() = A * tmp;
+  tmp = b[12] * A6 + b[10] * A4 + b[8] * A2;
+  V.noalias() = A6 * tmp;
+  V += b[6] * A6 + b[4] * A4 + b[2] * A2 + b[0] * MatrixType::Identity(A.rows(), A.cols());
+}
+
+/** \brief Compute the (17,17)-Pad&eacute; approximant to the exponential.
+ *
+ *  After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Pad&eacute;
+ *  approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$.
+ *
+ *  This function activates only if your long double is double-double or quadruple.
+ */
+#if LDBL_MANT_DIG > 64
+template <typename MatA, typename MatU, typename MatV>
+void matrix_exp_pade17(const MatA& A, MatU& U, MatV& V)
+{
+  typedef typename MatA::PlainObject MatrixType;
+  typedef typename NumTraits<typename traits<MatrixType>::Scalar>::Real RealScalar;
+  const RealScalar b[] = {830034394580628357120000.L, 415017197290314178560000.L,
+                          100610229646136770560000.L, 15720348382208870400000.L,
+                          1774878043152614400000.L, 153822763739893248000.L, 10608466464820224000.L,
+                          595373117923584000.L, 27563570274240000.L, 1060137318240000.L,
+                          33924394183680.L, 899510451840.L, 19554575040.L, 341863200.L, 4651200.L,
+                          46512.L, 306.L, 1.L};
+  const MatrixType A2 = A * A;
+  const MatrixType A4 = A2 * A2;
+  const MatrixType A6 = A4 * A2;
+  const MatrixType A8 = A4 * A4;
+  V = b[17] * A8 + b[15] * A6 + b[13] * A4 + b[11] * A2; // used for temporary storage
+  MatrixType tmp = A8 * V;
+  tmp += b[9] * A8 + b[7] * A6 + b[5] * A4 + b[3] * A2 
+    + b[1] * MatrixType::Identity(A.rows(), A.cols());
+  U.noalias() = A * tmp;
+  tmp = b[16] * A8 + b[14] * A6 + b[12] * A4 + b[10] * A2;
+  V.noalias() = tmp * A8;
+  V += b[8] * A8 + b[6] * A6 + b[4] * A4 + b[2] * A2 
+    + b[0] * MatrixType::Identity(A.rows(), A.cols());
+}
+#endif
+
+template <typename MatrixType, typename RealScalar = typename NumTraits<typename traits<MatrixType>::Scalar>::Real>
+struct matrix_exp_computeUV
+{
+  /** \brief Compute Pad&eacute; approximant to the exponential.
+    *
+    * Computes \c U, \c V and \c squarings such that \f$ (V+U)(V-U)^{-1} \f$ is a Pad&eacute;
+    * approximant of \f$ \exp(2^{-\mbox{squarings}}M) \f$ around \f$ M = 0 \f$, where \f$ M \f$
+    * denotes the matrix \c arg. The degree of the Pad&eacute; approximant and the value of squarings
+    * are chosen such that the approximation error is no more than the round-off error.
+    */
+  static void run(const MatrixType& arg, MatrixType& U, MatrixType& V, int& squarings);
+};
+
+template <typename MatrixType>
+struct matrix_exp_computeUV<MatrixType, float>
+{
+  template <typename ArgType>
+  static void run(const ArgType& arg, MatrixType& U, MatrixType& V, int& squarings)
+  {
+    using std::frexp;
+    using std::pow;
+    const float l1norm = arg.cwiseAbs().colwise().sum().maxCoeff();
+    squarings = 0;
+    if (l1norm < 4.258730016922831e-001f) {
+      matrix_exp_pade3(arg, U, V);
+    } else if (l1norm < 1.880152677804762e+000f) {
+      matrix_exp_pade5(arg, U, V);
+    } else {
+      const float maxnorm = 3.925724783138660f;
+      frexp(l1norm / maxnorm, &squarings);
+      if (squarings < 0) squarings = 0;
+      MatrixType A = arg.unaryExpr(MatrixExponentialScalingOp<float>(squarings));
+      matrix_exp_pade7(A, U, V);
+    }
+  }
+};
 
-    /** \brief L1 norm of m_M. */
-    RealScalar m_l1norm;
+template <typename MatrixType>
+struct matrix_exp_computeUV<MatrixType, double>
+{
+  template <typename ArgType>
+  static void run(const ArgType& arg, MatrixType& U, MatrixType& V, int& squarings)
+  {
+    using std::frexp;
+    using std::pow;
+    const double l1norm = arg.cwiseAbs().colwise().sum().maxCoeff();
+    squarings = 0;
+    if (l1norm < 1.495585217958292e-002) {
+      matrix_exp_pade3(arg, U, V);
+    } else if (l1norm < 2.539398330063230e-001) {
+      matrix_exp_pade5(arg, U, V);
+    } else if (l1norm < 9.504178996162932e-001) {
+      matrix_exp_pade7(arg, U, V);
+    } else if (l1norm < 2.097847961257068e+000) {
+      matrix_exp_pade9(arg, U, V);
+    } else {
+      const double maxnorm = 5.371920351148152;
+      frexp(l1norm / maxnorm, &squarings);
+      if (squarings < 0) squarings = 0;
+      MatrixType A = arg.unaryExpr(MatrixExponentialScalingOp<double>(squarings));
+      matrix_exp_pade13(A, U, V);
+    }
+  }
+};
+  
+template <typename MatrixType>
+struct matrix_exp_computeUV<MatrixType, long double>
+{
+  template <typename ArgType>
+  static void run(const ArgType& arg, MatrixType& U, MatrixType& V, int& squarings)
+  {
+#if   LDBL_MANT_DIG == 53   // double precision
+    matrix_exp_computeUV<MatrixType, double>::run(arg, U, V, squarings);
+  
+#else
+  
+    using std::frexp;
+    using std::pow;
+    const long double l1norm = arg.cwiseAbs().colwise().sum().maxCoeff();
+    squarings = 0;
+  
+#if LDBL_MANT_DIG <= 64   // extended precision
+  
+    if (l1norm < 4.1968497232266989671e-003L) {
+      matrix_exp_pade3(arg, U, V);
+    } else if (l1norm < 1.1848116734693823091e-001L) {
+      matrix_exp_pade5(arg, U, V);
+    } else if (l1norm < 5.5170388480686700274e-001L) {
+      matrix_exp_pade7(arg, U, V);
+    } else if (l1norm < 1.3759868875587845383e+000L) {
+      matrix_exp_pade9(arg, U, V);
+    } else {
+      const long double maxnorm = 4.0246098906697353063L;
+      frexp(l1norm / maxnorm, &squarings);
+      if (squarings < 0) squarings = 0;
+      MatrixType A = arg.unaryExpr(MatrixExponentialScalingOp<long double>(squarings));
+      matrix_exp_pade13(A, U, V);
+    }
+  
+#elif LDBL_MANT_DIG <= 106  // double-double
+  
+    if (l1norm < 3.2787892205607026992947488108213e-005L) {
+      matrix_exp_pade3(arg, U, V);
+    } else if (l1norm < 6.4467025060072760084130906076332e-003L) {
+      matrix_exp_pade5(arg, U, V);
+    } else if (l1norm < 6.8988028496595374751374122881143e-002L) {
+      matrix_exp_pade7(arg, U, V);
+    } else if (l1norm < 2.7339737518502231741495857201670e-001L) {
+      matrix_exp_pade9(arg, U, V);
+    } else if (l1norm < 1.3203382096514474905666448850278e+000L) {
+      matrix_exp_pade13(arg, U, V);
+    } else {
+      const long double maxnorm = 3.2579440895405400856599663723517L;
+      frexp(l1norm / maxnorm, &squarings);
+      if (squarings < 0) squarings = 0;
+      MatrixType A = arg.unaryExpr(MatrixExponentialScalingOp<long double>(squarings));
+      matrix_exp_pade17(A, U, V);
+    }
+  
+#elif LDBL_MANT_DIG <= 112  // quadruple precison
+  
+    if (l1norm < 1.639394610288918690547467954466970e-005L) {
+      matrix_exp_pade3(arg, U, V);
+    } else if (l1norm < 4.253237712165275566025884344433009e-003L) {
+      matrix_exp_pade5(arg, U, V);
+    } else if (l1norm < 5.125804063165764409885122032933142e-002L) {
+      matrix_exp_pade7(arg, U, V);
+    } else if (l1norm < 2.170000765161155195453205651889853e-001L) {
+      matrix_exp_pade9(arg, U, V);
+    } else if (l1norm < 1.125358383453143065081397882891878e+000L) {
+      matrix_exp_pade13(arg, U, V);
+    } else {
+      frexp(l1norm / maxnorm, &squarings);
+      if (squarings < 0) squarings = 0;
+      MatrixType A = arg.unaryExpr(MatrixExponentialScalingOp<long double>(squarings));
+      matrix_exp_pade17(A, U, V);
+    }
+  
+#else
+  
+    // this case should be handled in compute()
+    eigen_assert(false && "Bug in MatrixExponential"); 
+  
+#endif
+#endif  // LDBL_MANT_DIG
+  }
 };
 
-template <typename MatrixType>
-MatrixExponential<MatrixType>::MatrixExponential(const MatrixType &M) :
-  m_M(M),
-  m_U(M.rows(),M.cols()),
-  m_V(M.rows(),M.cols()),
-  m_tmp1(M.rows(),M.cols()),
-  m_tmp2(M.rows(),M.cols()),
-  m_Id(MatrixType::Identity(M.rows(), M.cols())),
-  m_squarings(0),
-  m_l1norm(M.cwiseAbs().colwise().sum().maxCoeff())
-{
-  /* empty body */
-}
-
-template <typename MatrixType>
-template <typename ResultType> 
-void MatrixExponential<MatrixType>::compute(ResultType &result)
-{
-#if LDBL_MANT_DIG > 112 // rarely happens
-  if(sizeof(RealScalar) > 14) {
-    result = m_M.matrixFunction(StdStemFunctions<ComplexScalar>::exp);
+
+/* Computes the matrix exponential
+ *
+ * \param arg    argument of matrix exponential (should be plain object)
+ * \param result variable in which result will be stored
+ */
+template <typename ArgType, typename ResultType>
+void matrix_exp_compute(const ArgType& arg, ResultType &result)
+{
+  typedef typename ArgType::PlainObject MatrixType;
+#if LDBL_MANT_DIG > 112 // rarely happens
+  typedef typename traits<MatrixType>::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef typename std::complex<RealScalar> ComplexScalar;
+  if (sizeof(RealScalar) > 14) {
+    result = arg.matrixFunction(internal::stem_function_exp<ComplexScalar>);
     return;
   }
 #endif
-  computeUV(RealScalar());
-  m_tmp1 = m_U + m_V;   // numerator of Pade approximant
-  m_tmp2 = -m_U + m_V;  // denominator of Pade approximant
-  result = m_tmp2.partialPivLu().solve(m_tmp1);
-  for (int i=0; i<m_squarings; i++)
+  MatrixType U, V;
+  int squarings; 
+  matrix_exp_computeUV<MatrixType>::run(arg, U, V, squarings); // Pade approximant is (U+V) / (-U+V)
+  MatrixType numer = U + V;
+  MatrixType denom = -U + V;
+  result = denom.partialPivLu().solve(numer);
+  for (int i=0; i<squarings; i++)
     result *= result;   // undo scaling by repeated squaring
 }
 
-template <typename MatrixType>
-EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade3(const MatrixType &A)
-{
-  const RealScalar b[] = {120., 60., 12., 1.};
-  m_tmp1.noalias() = A * A;
-  m_tmp2 = b[3]*m_tmp1 + b[1]*m_Id;
-  m_U.noalias() = A * m_tmp2;
-  m_V = b[2]*m_tmp1 + b[0]*m_Id;
-}
-
-template <typename MatrixType>
-EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade5(const MatrixType &A)
-{
-  const RealScalar b[] = {30240., 15120., 3360., 420., 30., 1.};
-  MatrixType A2 = A * A;
-  m_tmp1.noalias() = A2 * A2;
-  m_tmp2 = b[5]*m_tmp1 + b[3]*A2 + b[1]*m_Id;
-  m_U.noalias() = A * m_tmp2;
-  m_V = b[4]*m_tmp1 + b[2]*A2 + b[0]*m_Id;
-}
-
-template <typename MatrixType>
-EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade7(const MatrixType &A)
-{
-  const RealScalar b[] = {17297280., 8648640., 1995840., 277200., 25200., 1512., 56., 1.};
-  MatrixType A2 = A * A;
-  MatrixType A4 = A2 * A2;
-  m_tmp1.noalias() = A4 * A2;
-  m_tmp2 = b[7]*m_tmp1 + b[5]*A4 + b[3]*A2 + b[1]*m_Id;
-  m_U.noalias() = A * m_tmp2;
-  m_V = b[6]*m_tmp1 + b[4]*A4 + b[2]*A2 + b[0]*m_Id;
-}
-
-template <typename MatrixType>
-EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade9(const MatrixType &A)
-{
-  const RealScalar b[] = {17643225600., 8821612800., 2075673600., 302702400., 30270240.,
-		      2162160., 110880., 3960., 90., 1.};
-  MatrixType A2 = A * A;
-  MatrixType A4 = A2 * A2;
-  MatrixType A6 = A4 * A2;
-  m_tmp1.noalias() = A6 * A2;
-  m_tmp2 = b[9]*m_tmp1 + b[7]*A6 + b[5]*A4 + b[3]*A2 + b[1]*m_Id;
-  m_U.noalias() = A * m_tmp2;
-  m_V = b[8]*m_tmp1 + b[6]*A6 + b[4]*A4 + b[2]*A2 + b[0]*m_Id;
-}
-
-template <typename MatrixType>
-EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade13(const MatrixType &A)
-{
-  const RealScalar b[] = {64764752532480000., 32382376266240000., 7771770303897600.,
-		      1187353796428800., 129060195264000., 10559470521600., 670442572800.,
-		      33522128640., 1323241920., 40840800., 960960., 16380., 182., 1.};
-  MatrixType A2 = A * A;
-  MatrixType A4 = A2 * A2;
-  m_tmp1.noalias() = A4 * A2;
-  m_V = b[13]*m_tmp1 + b[11]*A4 + b[9]*A2; // used for temporary storage
-  m_tmp2.noalias() = m_tmp1 * m_V;
-  m_tmp2 += b[7]*m_tmp1 + b[5]*A4 + b[3]*A2 + b[1]*m_Id;
-  m_U.noalias() = A * m_tmp2;
-  m_tmp2 = b[12]*m_tmp1 + b[10]*A4 + b[8]*A2;
-  m_V.noalias() = m_tmp1 * m_tmp2;
-  m_V += b[6]*m_tmp1 + b[4]*A4 + b[2]*A2 + b[0]*m_Id;
-}
-
-#if LDBL_MANT_DIG > 64
-template <typename MatrixType>
-EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade17(const MatrixType &A)
-{
-  const RealScalar b[] = {830034394580628357120000.L, 415017197290314178560000.L,
-		      100610229646136770560000.L, 15720348382208870400000.L,
-		      1774878043152614400000.L, 153822763739893248000.L, 10608466464820224000.L,
-		      595373117923584000.L, 27563570274240000.L, 1060137318240000.L,
-		      33924394183680.L, 899510451840.L, 19554575040.L, 341863200.L, 4651200.L,
-		      46512.L, 306.L, 1.L};
-  MatrixType A2 = A * A;
-  MatrixType A4 = A2 * A2;
-  MatrixType A6 = A4 * A2;
-  m_tmp1.noalias() = A4 * A4;
-  m_V = b[17]*m_tmp1 + b[15]*A6 + b[13]*A4 + b[11]*A2; // used for temporary storage
-  m_tmp2.noalias() = m_tmp1 * m_V;
-  m_tmp2 += b[9]*m_tmp1 + b[7]*A6 + b[5]*A4 + b[3]*A2 + b[1]*m_Id;
-  m_U.noalias() = A * m_tmp2;
-  m_tmp2 = b[16]*m_tmp1 + b[14]*A6 + b[12]*A4 + b[10]*A2;
-  m_V.noalias() = m_tmp1 * m_tmp2;
-  m_V += b[8]*m_tmp1 + b[6]*A6 + b[4]*A4 + b[2]*A2 + b[0]*m_Id;
-}
-#endif
-
-template <typename MatrixType>
-void MatrixExponential<MatrixType>::computeUV(float)
-{
-  using std::frexp;
-  using std::pow;
-  if (m_l1norm < 4.258730016922831e-001) {
-    pade3(m_M);
-  } else if (m_l1norm < 1.880152677804762e+000) {
-    pade5(m_M);
-  } else {
-    const float maxnorm = 3.925724783138660f;
-    frexp(m_l1norm / maxnorm, &m_squarings);
-    if (m_squarings < 0) m_squarings = 0;
-    MatrixType A = m_M / pow(Scalar(2), m_squarings);
-    pade7(A);
-  }
-}
-
-template <typename MatrixType>
-void MatrixExponential<MatrixType>::computeUV(double)
-{
-  using std::frexp;
-  using std::pow;
-  if (m_l1norm < 1.495585217958292e-002) {
-    pade3(m_M);
-  } else if (m_l1norm < 2.539398330063230e-001) {
-    pade5(m_M);
-  } else if (m_l1norm < 9.504178996162932e-001) {
-    pade7(m_M);
-  } else if (m_l1norm < 2.097847961257068e+000) {
-    pade9(m_M);
-  } else {
-    const double maxnorm = 5.371920351148152;
-    frexp(m_l1norm / maxnorm, &m_squarings);
-    if (m_squarings < 0) m_squarings = 0;
-    MatrixType A = m_M / pow(Scalar(2), m_squarings);
-    pade13(A);
-  }
-}
-
-template <typename MatrixType>
-void MatrixExponential<MatrixType>::computeUV(long double)
-{
-  using std::frexp;
-  using std::pow;
-#if   LDBL_MANT_DIG == 53   // double precision
-  computeUV(double());
-#elif LDBL_MANT_DIG <= 64   // extended precision
-  if (m_l1norm < 4.1968497232266989671e-003L) {
-    pade3(m_M);
-  } else if (m_l1norm < 1.1848116734693823091e-001L) {
-    pade5(m_M);
-  } else if (m_l1norm < 5.5170388480686700274e-001L) {
-    pade7(m_M);
-  } else if (m_l1norm < 1.3759868875587845383e+000L) {
-    pade9(m_M);
-  } else {
-    const long double maxnorm = 4.0246098906697353063L;
-    frexp(m_l1norm / maxnorm, &m_squarings);
-    if (m_squarings < 0) m_squarings = 0;
-    MatrixType A = m_M / pow(Scalar(2), m_squarings);
-    pade13(A);
-  }
-#elif LDBL_MANT_DIG <= 106  // double-double
-  if (m_l1norm < 3.2787892205607026992947488108213e-005L) {
-    pade3(m_M);
-  } else if (m_l1norm < 6.4467025060072760084130906076332e-003L) {
-    pade5(m_M);
-  } else if (m_l1norm < 6.8988028496595374751374122881143e-002L) {
-    pade7(m_M);
-  } else if (m_l1norm < 2.7339737518502231741495857201670e-001L) {
-    pade9(m_M);
-  } else if (m_l1norm < 1.3203382096514474905666448850278e+000L) {
-    pade13(m_M);
-  } else {
-    const long double maxnorm = 3.2579440895405400856599663723517L;
-    frexp(m_l1norm / maxnorm, &m_squarings);
-    if (m_squarings < 0) m_squarings = 0;
-    MatrixType A = m_M / pow(Scalar(2), m_squarings);
-    pade17(A);
-  }
-#elif LDBL_MANT_DIG <= 112  // quadruple precison
-  if (m_l1norm < 1.639394610288918690547467954466970e-005L) {
-    pade3(m_M);
-  } else if (m_l1norm < 4.253237712165275566025884344433009e-003L) {
-    pade5(m_M);
-  } else if (m_l1norm < 5.125804063165764409885122032933142e-002L) {
-    pade7(m_M);
-  } else if (m_l1norm < 2.170000765161155195453205651889853e-001L) {
-    pade9(m_M);
-  } else if (m_l1norm < 1.125358383453143065081397882891878e+000L) {
-    pade13(m_M);
-  } else {
-    const long double maxnorm = 2.884233277829519311757165057717815L;
-    frexp(m_l1norm / maxnorm, &m_squarings);
-    if (m_squarings < 0) m_squarings = 0;
-    MatrixType A = m_M / pow(Scalar(2), m_squarings);
-    pade17(A);
-  }
-#else
-  // this case should be handled in compute()
-  eigen_assert(false && "Bug in MatrixExponential"); 
-#endif  // LDBL_MANT_DIG
-}
+} // end namespace Eigen::internal
 
 /** \ingroup MatrixFunctions_Module
   *
   * \brief Proxy for the matrix exponential of some matrix (expression).
   *
   * \tparam Derived  Type of the argument to the matrix exponential.
   *
-  * This class holds the argument to the matrix exponential until it
-  * is assigned or evaluated for some other reason (so the argument
-  * should not be changed in the meantime). It is the return type of
-  * MatrixBase::exp() and most of the time this is the only way it is
-  * used.
+  * This class holds the argument to the matrix exponential until it is assigned or evaluated for
+  * some other reason (so the argument should not be changed in the meantime). It is the return type
+  * of MatrixBase::exp() and most of the time this is the only way it is used.
   */
 template<typename Derived> struct MatrixExponentialReturnValue
 : public ReturnByValue<MatrixExponentialReturnValue<Derived> >
 {
     typedef typename Derived::Index Index;
   public:
     /** \brief Constructor.
       *
-      * \param[in] src %Matrix (expression) forming the argument of the
-      * matrix exponential.
+      * \param src %Matrix (expression) forming the argument of the matrix exponential.
       */
     MatrixExponentialReturnValue(const Derived& src) : m_src(src) { }
 
     /** \brief Compute the matrix exponential.
       *
-      * \param[out] result the matrix exponential of \p src in the
-      * constructor.
+      * \param result the matrix exponential of \p src in the constructor.
       */
     template <typename ResultType>
     inline void evalTo(ResultType& result) const
     {
-      const typename Derived::PlainObject srcEvaluated = m_src.eval();
-      MatrixExponential<typename Derived::PlainObject> me(srcEvaluated);
-      me.compute(result);
+      const typename internal::nested_eval<Derived, 10>::type tmp(m_src);
+      internal::matrix_exp_compute(tmp, result);
     }
 
     Index rows() const { return m_src.rows(); }
     Index cols() const { return m_src.cols(); }
 
   protected:
-    const Derived& m_src;
-  private:
-    MatrixExponentialReturnValue& operator=(const MatrixExponentialReturnValue&);
+    const typename internal::ref_selector<Derived>::type m_src;
 };
 
 namespace internal {
 template<typename Derived>
 struct traits<MatrixExponentialReturnValue<Derived> >

Index: 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
+++ 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
@@ -1,410 +1,257 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009-2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2009-2011, 2013 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATRIX_FUNCTION
 #define EIGEN_MATRIX_FUNCTION
 
 #include "StemFunction.h"
-#include "MatrixFunctionAtomic.h"
 
 
 namespace Eigen { 
 
-/** \ingroup MatrixFunctions_Module
-  * \brief Class for computing matrix functions.
-  * \tparam  MatrixType  type of the argument of the matrix function,
-  *                      expected to be an instantiation of the Matrix class template.
-  * \tparam  AtomicType  type for computing matrix function of atomic blocks.
-  * \tparam  IsComplex   used internally to select correct specialization.
-  *
-  * This class implements the Schur-Parlett algorithm for computing matrix functions. The spectrum of the
-  * matrix is divided in clustered of eigenvalues that lies close together. This class delegates the
-  * computation of the matrix function on every block corresponding to these clusters to an object of type
-  * \p AtomicType and uses these results to compute the matrix function of the whole matrix. The class
-  * \p AtomicType should have a \p compute() member function for computing the matrix function of a block.
-  *
-  * \sa class MatrixFunctionAtomic, class MatrixLogarithmAtomic
-  */
-template <typename MatrixType, 
-	  typename AtomicType,  
-          int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
-class MatrixFunction
-{  
-  public:
-
-    /** \brief Constructor. 
-      *
-      * \param[in]  A       argument of matrix function, should be a square matrix.
-      * \param[in]  atomic  class for computing matrix function of atomic blocks.
-      *
-      * The class stores references to \p A and \p atomic, so they should not be
-      * changed (or destroyed) before compute() is called.
-      */
-    MatrixFunction(const MatrixType& A, AtomicType& atomic);
-
-    /** \brief Compute the matrix function.
-      *
-      * \param[out] result  the function \p f applied to \p A, as
-      * specified in the constructor.
-      *
-      * See MatrixBase::matrixFunction() for details on how this computation
-      * is implemented.
-      */
-    template <typename ResultType> 
-    void compute(ResultType &result);    
-};
-
-
-/** \internal \ingroup MatrixFunctions_Module 
-  * \brief Partial specialization of MatrixFunction for real matrices
-  */
-template <typename MatrixType, typename AtomicType>
-class MatrixFunction<MatrixType, AtomicType, 0>
-{  
-  private:
-
-    typedef internal::traits<MatrixType> Traits;
-    typedef typename Traits::Scalar Scalar;
-    static const int Rows = Traits::RowsAtCompileTime;
-    static const int Cols = Traits::ColsAtCompileTime;
-    static const int Options = MatrixType::Options;
-    static const int MaxRows = Traits::MaxRowsAtCompileTime;
-    static const int MaxCols = Traits::MaxColsAtCompileTime;
-
-    typedef std::complex<Scalar> ComplexScalar;
-    typedef Matrix<ComplexScalar, Rows, Cols, Options, MaxRows, MaxCols> ComplexMatrix;
-
-  public:
-
-    /** \brief Constructor. 
-      *
-      * \param[in]  A       argument of matrix function, should be a square matrix.
-      * \param[in]  atomic  class for computing matrix function of atomic blocks.
-      */
-    MatrixFunction(const MatrixType& A, AtomicType& atomic) : m_A(A), m_atomic(atomic) { }
-
-    /** \brief Compute the matrix function.
-      *
-      * \param[out] result  the function \p f applied to \p A, as
-      * specified in the constructor.
-      *
-      * This function converts the real matrix \c A to a complex matrix,
-      * uses MatrixFunction<MatrixType,1> and then converts the result back to
-      * a real matrix.
-      */
-    template <typename ResultType>
-    void compute(ResultType& result) 
-    {
-      ComplexMatrix CA = m_A.template cast<ComplexScalar>();
-      ComplexMatrix Cresult;
-      MatrixFunction<ComplexMatrix, AtomicType> mf(CA, m_atomic);
-      mf.compute(Cresult);
-      result = Cresult.real();
-    }
-
-  private:
-    typename internal::nested<MatrixType>::type m_A; /**< \brief Reference to argument of matrix function. */
-    AtomicType& m_atomic; /**< \brief Class for computing matrix function of atomic blocks. */
-
-    MatrixFunction& operator=(const MatrixFunction&);
-};
-
-      
-/** \internal \ingroup MatrixFunctions_Module 
-  * \brief Partial specialization of MatrixFunction for complex matrices
-  */
-template <typename MatrixType, typename AtomicType>
-class MatrixFunction<MatrixType, AtomicType, 1>
-{
-  private:
-
-    typedef internal::traits<MatrixType> Traits;
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
-    static const int RowsAtCompileTime = Traits::RowsAtCompileTime;
-    static const int ColsAtCompileTime = Traits::ColsAtCompileTime;
-    static const int Options = MatrixType::Options;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef Matrix<Scalar, Traits::RowsAtCompileTime, 1> VectorType;
-    typedef Matrix<Index, Traits::RowsAtCompileTime, 1> IntVectorType;
-    typedef Matrix<Index, Dynamic, 1> DynamicIntVectorType;
-    typedef std::list<Scalar> Cluster;
-    typedef std::list<Cluster> ListOfClusters;
-    typedef Matrix<Scalar, Dynamic, Dynamic, Options, RowsAtCompileTime, ColsAtCompileTime> DynMatrixType;
-
-  public:
-
-    MatrixFunction(const MatrixType& A, AtomicType& atomic);
-    template <typename ResultType> void compute(ResultType& result);
-
-  private:
-
-    void computeSchurDecomposition();
-    void partitionEigenvalues();
-    typename ListOfClusters::iterator findCluster(Scalar key);
-    void computeClusterSize();
-    void computeBlockStart();
-    void constructPermutation();
-    void permuteSchur();
-    void swapEntriesInSchur(Index index);
-    void computeBlockAtomic();
-    Block<MatrixType> block(MatrixType& A, Index i, Index j);
-    void computeOffDiagonal();
-    DynMatrixType solveTriangularSylvester(const DynMatrixType& A, const DynMatrixType& B, const DynMatrixType& C);
-
-    typename internal::nested<MatrixType>::type m_A; /**< \brief Reference to argument of matrix function. */
-    AtomicType& m_atomic; /**< \brief Class for computing matrix function of atomic blocks. */
-    MatrixType m_T; /**< \brief Triangular part of Schur decomposition */
-    MatrixType m_U; /**< \brief Unitary part of Schur decomposition */
-    MatrixType m_fT; /**< \brief %Matrix function applied to #m_T */
-    ListOfClusters m_clusters; /**< \brief Partition of eigenvalues into clusters of ei'vals "close" to each other */
-    DynamicIntVectorType m_eivalToCluster; /**< \brief m_eivalToCluster[i] = j means i-th ei'val is in j-th cluster */
-    DynamicIntVectorType m_clusterSize; /**< \brief Number of eigenvalues in each clusters  */
-    DynamicIntVectorType m_blockStart; /**< \brief Row index at which block corresponding to i-th cluster starts */
-    IntVectorType m_permutation; /**< \brief Permutation which groups ei'vals in the same cluster together */
-
-    /** \brief Maximum distance allowed between eigenvalues to be considered "close".
-      *
-      * This is morally a \c static \c const \c Scalar, but only
-      * integers can be static constant class members in C++. The
-      * separation constant is set to 0.1, a value taken from the
-      * paper by Davies and Higham. */
-    static const RealScalar separation() { return static_cast<RealScalar>(0.1); }
-
-    MatrixFunction& operator=(const MatrixFunction&);
-};
-
-/** \brief Constructor. 
- *
- * \param[in]  A       argument of matrix function, should be a square matrix.
- * \param[in]  atomic  class for computing matrix function of atomic blocks.
- */
-template <typename MatrixType, typename AtomicType>
-MatrixFunction<MatrixType,AtomicType,1>::MatrixFunction(const MatrixType& A, AtomicType& atomic)
-  : m_A(A), m_atomic(atomic)
-{
-  /* empty body */
-}
-
-/** \brief Compute the matrix function.
-  *
-  * \param[out] result  the function \p f applied to \p A, as
-  * specified in the constructor.
-  */
-template <typename MatrixType, typename AtomicType>
-template <typename ResultType>
-void MatrixFunction<MatrixType,AtomicType,1>::compute(ResultType& result) 
-{
-  computeSchurDecomposition();
-  partitionEigenvalues();
-  computeClusterSize();
-  computeBlockStart();
-  constructPermutation();
-  permuteSchur();
-  computeBlockAtomic();
-  computeOffDiagonal();
-  result = m_U * (m_fT.template triangularView<Upper>() * m_U.adjoint());
-}
-
-/** \brief Store the Schur decomposition of #m_A in #m_T and #m_U */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::computeSchurDecomposition()
-{
-  const ComplexSchur<MatrixType> schurOfA(m_A);  
-  m_T = schurOfA.matrixT();
-  m_U = schurOfA.matrixU();
+namespace internal {
+
+/** \brief Maximum distance allowed between eigenvalues to be considered "close". */
+static const float matrix_function_separation = 0.1f;
+
+/** \ingroup MatrixFunctions_Module
+  * \class MatrixFunctionAtomic
+  * \brief Helper class for computing matrix functions of atomic matrices.
+  *
+  * Here, an atomic matrix is a triangular matrix whose diagonal entries are close to each other.
+  */
+template <typename MatrixType>
+class MatrixFunctionAtomic 
+{
+  public:
+
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename stem_function<Scalar>::type StemFunction;
+
+    /** \brief Constructor
+      * \param[in]  f  matrix function to compute.
+      */
+    MatrixFunctionAtomic(StemFunction f) : m_f(f) { }
+
+    /** \brief Compute matrix function of atomic matrix
+      * \param[in]  A  argument of matrix function, should be upper triangular and atomic
+      * \returns  f(A), the matrix function evaluated at the given matrix
+      */
+    MatrixType compute(const MatrixType& A);
+
+  private:
+    StemFunction* m_f;
+};
+
+template <typename MatrixType>
+typename NumTraits<typename MatrixType::Scalar>::Real matrix_function_compute_mu(const MatrixType& A)
+{
+  typedef typename plain_col_type<MatrixType>::type VectorType;
+  typename MatrixType::Index rows = A.rows();
+  const MatrixType N = MatrixType::Identity(rows, rows) - A;
+  VectorType e = VectorType::Ones(rows);
+  N.template triangularView<Upper>().solveInPlace(e);
+  return e.cwiseAbs().maxCoeff();
+}
+
+template <typename MatrixType>
+MatrixType MatrixFunctionAtomic<MatrixType>::compute(const MatrixType& A)
+{
+  // TODO: Use that A is upper triangular
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef typename MatrixType::Index Index;
+  Index rows = A.rows();
+  Scalar avgEival = A.trace() / Scalar(RealScalar(rows));
+  MatrixType Ashifted = A - avgEival * MatrixType::Identity(rows, rows);
+  RealScalar mu = matrix_function_compute_mu(Ashifted);
+  MatrixType F = m_f(avgEival, 0) * MatrixType::Identity(rows, rows);
+  MatrixType P = Ashifted;
+  MatrixType Fincr;
+  for (Index s = 1; s < 1.1 * rows + 10; s++) { // upper limit is fairly arbitrary
+    Fincr = m_f(avgEival, static_cast<int>(s)) * P;
+    F += Fincr;
+    P = Scalar(RealScalar(1.0/(s + 1))) * P * Ashifted;
+
+    // test whether Taylor series converged
+    const RealScalar F_norm = F.cwiseAbs().rowwise().sum().maxCoeff();
+    const RealScalar Fincr_norm = Fincr.cwiseAbs().rowwise().sum().maxCoeff();
+    if (Fincr_norm < NumTraits<Scalar>::epsilon() * F_norm) {
+      RealScalar delta = 0;
+      RealScalar rfactorial = 1;
+      for (Index r = 0; r < rows; r++) {
+        RealScalar mx = 0;
+        for (Index i = 0; i < rows; i++)
+          mx = (std::max)(mx, std::abs(m_f(Ashifted(i, i) + avgEival, static_cast<int>(s+r))));
+        if (r != 0)
+          rfactorial *= RealScalar(r);
+        delta = (std::max)(delta, mx / rfactorial);
+      }
+      const RealScalar P_norm = P.cwiseAbs().rowwise().sum().maxCoeff();
+      if (mu * delta * P_norm < NumTraits<Scalar>::epsilon() * F_norm) // series converged
+        break;
+    }
+  }
+  return F;
+}
+
+/** \brief Find cluster in \p clusters containing some value 
+  * \param[in] key Value to find
+  * \returns Iterator to cluster containing \p key, or \c clusters.end() if no cluster in \p m_clusters
+  * contains \p key.
+  */
+template <typename Index, typename ListOfClusters>
+typename ListOfClusters::iterator matrix_function_find_cluster(Index key, ListOfClusters& clusters)
+{
+  typename std::list<Index>::iterator j;
+  for (typename ListOfClusters::iterator i = clusters.begin(); i != clusters.end(); ++i) {
+    j = std::find(i->begin(), i->end(), key);
+    if (j != i->end())
+      return i;
+  }
+  return clusters.end();
 }
 
 /** \brief Partition eigenvalues in clusters of ei'vals close to each other
   * 
-  * This function computes #m_clusters. This is a partition of the
-  * eigenvalues of #m_T in clusters, such that
-  * # Any eigenvalue in a certain cluster is at most separation() away
-  *   from another eigenvalue in the same cluster.
-  * # The distance between two eigenvalues in different clusters is
-  *   more than separation().
-  * The implementation follows Algorithm 4.1 in the paper of Davies
-  * and Higham. 
-  */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::partitionEigenvalues()
-{
-  using std::abs;
-  const Index rows = m_T.rows();
-  VectorType diag = m_T.diagonal(); // contains eigenvalues of A
-
-  for (Index i=0; i<rows; ++i) {
-    // Find set containing diag(i), adding a new set if necessary
-    typename ListOfClusters::iterator qi = findCluster(diag(i));
-    if (qi == m_clusters.end()) {
+  * \param[in]  eivals    Eigenvalues
+  * \param[out] clusters  Resulting partition of eigenvalues
+  *
+  * The partition satisfies the following two properties:
+  * # Any eigenvalue in a certain cluster is at most matrix_function_separation() away from another eigenvalue
+  *   in the same cluster.
+  * # The distance between two eigenvalues in different clusters is more than matrix_function_separation().  
+  * The implementation follows Algorithm 4.1 in the paper of Davies and Higham.
+  */
+template <typename EivalsType, typename Cluster>
+void matrix_function_partition_eigenvalues(const EivalsType& eivals, std::list<Cluster>& clusters)
+{
+  typedef typename EivalsType::Index Index;
+  typedef typename EivalsType::RealScalar RealScalar;
+  for (Index i=0; i<eivals.rows(); ++i) {
+    // Find cluster containing i-th ei'val, adding a new cluster if necessary
+    typename std::list<Cluster>::iterator qi = matrix_function_find_cluster(i, clusters);
+    if (qi == clusters.end()) {
       Cluster l;
-      l.push_back(diag(i));
-      m_clusters.push_back(l);
-      qi = m_clusters.end();
+      l.push_back(i);
+      clusters.push_back(l);
+      qi = clusters.end();
       --qi;
     }
 
     // Look for other element to add to the set
-    for (Index j=i+1; j<rows; ++j) {
-      if (abs(diag(j) - diag(i)) <= separation() && std::find(qi->begin(), qi->end(), diag(j)) == qi->end()) {
-        typename ListOfClusters::iterator qj = findCluster(diag(j));
-        if (qj == m_clusters.end()) {
-          qi->push_back(diag(j));
+    for (Index j=i+1; j<eivals.rows(); ++j) {
+      if (abs(eivals(j) - eivals(i)) <= RealScalar(matrix_function_separation)
+          && std::find(qi->begin(), qi->end(), j) == qi->end()) {
+        typename std::list<Cluster>::iterator qj = matrix_function_find_cluster(j, clusters);
+        if (qj == clusters.end()) {
+          qi->push_back(j);
         } else {
           qi->insert(qi->end(), qj->begin(), qj->end());
-          m_clusters.erase(qj);
+          clusters.erase(qj);
         }
       }
     }
   }
 }
 
-/** \brief Find cluster in #m_clusters containing some value 
-  * \param[in] key Value to find
-  * \returns Iterator to cluster containing \c key, or
-  * \c m_clusters.end() if no cluster in m_clusters contains \c key.
-  */
-template <typename MatrixType, typename AtomicType>
-typename MatrixFunction<MatrixType,AtomicType,1>::ListOfClusters::iterator MatrixFunction<MatrixType,AtomicType,1>::findCluster(Scalar key)
-{
-  typename Cluster::iterator j;
-  for (typename ListOfClusters::iterator i = m_clusters.begin(); i != m_clusters.end(); ++i) {
-    j = std::find(i->begin(), i->end(), key);
-    if (j != i->end())
-      return i;
-  }
-  return m_clusters.end();
-}
-
-/** \brief Compute #m_clusterSize and #m_eivalToCluster using #m_clusters */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::computeClusterSize()
-{
-  const Index rows = m_T.rows();
-  VectorType diag = m_T.diagonal(); 
-  const Index numClusters = static_cast<Index>(m_clusters.size());
-
-  m_clusterSize.setZero(numClusters);
-  m_eivalToCluster.resize(rows);
+/** \brief Compute size of each cluster given a partitioning */
+template <typename ListOfClusters, typename Index>
+void matrix_function_compute_cluster_size(const ListOfClusters& clusters, Matrix<Index, Dynamic, 1>& clusterSize)
+{
+  const Index numClusters = static_cast<Index>(clusters.size());
+  clusterSize.setZero(numClusters);
+  Index clusterIndex = 0;
+  for (typename ListOfClusters::const_iterator cluster = clusters.begin(); cluster != clusters.end(); ++cluster) {
+    clusterSize[clusterIndex] = cluster->size();
+    ++clusterIndex;
+  }
+}
+
+/** \brief Compute start of each block using clusterSize */
+template <typename VectorType>
+void matrix_function_compute_block_start(const VectorType& clusterSize, VectorType& blockStart)
+{
+  blockStart.resize(clusterSize.rows());
+  blockStart(0) = 0;
+  for (typename VectorType::Index i = 1; i < clusterSize.rows(); i++) {
+    blockStart(i) = blockStart(i-1) + clusterSize(i-1);
+  }
+}
+
+/** \brief Compute mapping of eigenvalue indices to cluster indices */
+template <typename EivalsType, typename ListOfClusters, typename VectorType>
+void matrix_function_compute_map(const EivalsType& eivals, const ListOfClusters& clusters, VectorType& eivalToCluster)
+{
+  typedef typename EivalsType::Index Index;
+  eivalToCluster.resize(eivals.rows());
   Index clusterIndex = 0;
-  for (typename ListOfClusters::const_iterator cluster = m_clusters.begin(); cluster != m_clusters.end(); ++cluster) {
-    for (Index i = 0; i < diag.rows(); ++i) {
-      if (std::find(cluster->begin(), cluster->end(), diag(i)) != cluster->end()) {
-        ++m_clusterSize[clusterIndex];
-        m_eivalToCluster[i] = clusterIndex;
+  for (typename ListOfClusters::const_iterator cluster = clusters.begin(); cluster != clusters.end(); ++cluster) {
+    for (Index i = 0; i < eivals.rows(); ++i) {
+      if (std::find(cluster->begin(), cluster->end(), i) != cluster->end()) {
+        eivalToCluster[i] = clusterIndex;
       }
     }
     ++clusterIndex;
   }
 }
 
-/** \brief Compute #m_blockStart using #m_clusterSize */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::computeBlockStart()
-{
-  m_blockStart.resize(m_clusterSize.rows());
-  m_blockStart(0) = 0;
-  for (Index i = 1; i < m_clusterSize.rows(); i++) {
-    m_blockStart(i) = m_blockStart(i-1) + m_clusterSize(i-1);
-  }
-}
-
-/** \brief Compute #m_permutation using #m_eivalToCluster and #m_blockStart */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::constructPermutation()
-{
-  DynamicIntVectorType indexNextEntry = m_blockStart;
-  m_permutation.resize(m_T.rows());
-  for (Index i = 0; i < m_T.rows(); i++) {
-    Index cluster = m_eivalToCluster[i];
-    m_permutation[i] = indexNextEntry[cluster];
-    ++indexNextEntry[cluster];
-  }
-}  
-
-/** \brief Permute Schur decomposition in #m_U and #m_T according to #m_permutation */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::permuteSchur()
-{
-  IntVectorType p = m_permutation;
-  for (Index i = 0; i < p.rows() - 1; i++) {
-    Index j;
-    for (j = i; j < p.rows(); j++) {
-      if (p(j) == i) break;
-    }
-    eigen_assert(p(j) == i);
-    for (Index k = j-1; k >= i; k--) {
-      swapEntriesInSchur(k);
-      std::swap(p.coeffRef(k), p.coeffRef(k+1));
-    }
-  }
-}
-
-/** \brief Swap rows \a index and \a index+1 in Schur decomposition in #m_U and #m_T */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::swapEntriesInSchur(Index index)
-{
-  JacobiRotation<Scalar> rotation;
-  rotation.makeGivens(m_T(index, index+1), m_T(index+1, index+1) - m_T(index, index));
-  m_T.applyOnTheLeft(index, index+1, rotation.adjoint());
-  m_T.applyOnTheRight(index, index+1, rotation);
-  m_U.applyOnTheRight(index, index+1, rotation);
-}  
-
-/** \brief Compute block diagonal part of #m_fT.
-  *
-  * This routine computes the matrix function applied to the block diagonal part of #m_T, with the blocking
-  * given by #m_blockStart. The matrix function of each diagonal block is computed by #m_atomic. The
-  * off-diagonal parts of #m_fT are set to zero.
-  */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::computeBlockAtomic()
-{ 
-  m_fT.resize(m_T.rows(), m_T.cols());
-  m_fT.setZero();
-  for (Index i = 0; i < m_clusterSize.rows(); ++i) {
-    block(m_fT, i, i) = m_atomic.compute(block(m_T, i, i));
-  }
-}
-
-/** \brief Return block of matrix according to blocking given by #m_blockStart */
-template <typename MatrixType, typename AtomicType>
-Block<MatrixType> MatrixFunction<MatrixType,AtomicType,1>::block(MatrixType& A, Index i, Index j)
-{
-  return A.block(m_blockStart(i), m_blockStart(j), m_clusterSize(i), m_clusterSize(j));
-}
-
-/** \brief Compute part of #m_fT above block diagonal.
-  *
-  * This routine assumes that the block diagonal part of #m_fT (which
-  * equals the matrix function applied to #m_T) has already been computed and computes
-  * the part above the block diagonal. The part below the diagonal is
-  * zero, because #m_T is upper triangular.
-  */
-template <typename MatrixType, typename AtomicType>
-void MatrixFunction<MatrixType,AtomicType,1>::computeOffDiagonal()
-{ 
-  for (Index diagIndex = 1; diagIndex < m_clusterSize.rows(); diagIndex++) {
-    for (Index blockIndex = 0; blockIndex < m_clusterSize.rows() - diagIndex; blockIndex++) {
-      // compute (blockIndex, blockIndex+diagIndex) block
-      DynMatrixType A = block(m_T, blockIndex, blockIndex);
-      DynMatrixType B = -block(m_T, blockIndex+diagIndex, blockIndex+diagIndex);
-      DynMatrixType C = block(m_fT, blockIndex, blockIndex) * block(m_T, blockIndex, blockIndex+diagIndex);
-      C -= block(m_T, blockIndex, blockIndex+diagIndex) * block(m_fT, blockIndex+diagIndex, blockIndex+diagIndex);
-      for (Index k = blockIndex + 1; k < blockIndex + diagIndex; k++) {
-	C += block(m_fT, blockIndex, k) * block(m_T, k, blockIndex+diagIndex);
-	C -= block(m_T, blockIndex, k) * block(m_fT, k, blockIndex+diagIndex);
-      }
-      block(m_fT, blockIndex, blockIndex+diagIndex) = solveTriangularSylvester(A, B, C);
-    }
+/** \brief Compute permutation which groups ei'vals in same cluster together */
+template <typename DynVectorType, typename VectorType>
+void matrix_function_compute_permutation(const DynVectorType& blockStart, const DynVectorType& eivalToCluster, VectorType& permutation)
+{
+  typedef typename VectorType::Index Index;
+  DynVectorType indexNextEntry = blockStart;
+  permutation.resize(eivalToCluster.rows());
+  for (Index i = 0; i < eivalToCluster.rows(); i++) {
+    Index cluster = eivalToCluster[i];
+    permutation[i] = indexNextEntry[cluster];
+    ++indexNextEntry[cluster];
+  }
+}  
+
+/** \brief Permute Schur decomposition in U and T according to permutation */
+template <typename VectorType, typename MatrixType>
+void matrix_function_permute_schur(VectorType& permutation, MatrixType& U, MatrixType& T)
+{
+  typedef typename VectorType::Index Index;
+  for (Index i = 0; i < permutation.rows() - 1; i++) {
+    Index j;
+    for (j = i; j < permutation.rows(); j++) {
+      if (permutation(j) == i) break;
+    }
+    eigen_assert(permutation(j) == i);
+    for (Index k = j-1; k >= i; k--) {
+      JacobiRotation<typename MatrixType::Scalar> rotation;
+      rotation.makeGivens(T(k, k+1), T(k+1, k+1) - T(k, k));
+      T.applyOnTheLeft(k, k+1, rotation.adjoint());
+      T.applyOnTheRight(k, k+1, rotation);
+      U.applyOnTheRight(k, k+1, rotation);
+      std::swap(permutation.coeffRef(k), permutation.coeffRef(k+1));
+    }
+  }
+}
+
+/** \brief Compute block diagonal part of matrix function.
+  *
+  * This routine computes the matrix function applied to the block diagonal part of \p T (which should be
+  * upper triangular), with the blocking given by \p blockStart and \p clusterSize. The matrix function of
+  * each diagonal block is computed by \p atomic. The off-diagonal parts of \p fT are set to zero.
+  */
+template <typename MatrixType, typename AtomicType, typename VectorType>
+void matrix_function_compute_block_atomic(const MatrixType& T, AtomicType& atomic, const VectorType& blockStart, const VectorType& clusterSize, MatrixType& fT)
+{ 
+  fT.setZero(T.rows(), T.cols());
+  for (typename VectorType::Index i = 0; i < clusterSize.rows(); ++i) {
+    fT.block(blockStart(i), blockStart(i), clusterSize(i), clusterSize(i))
+      = atomic.compute(T.block(blockStart(i), blockStart(i), clusterSize(i), clusterSize(i)));
   }
 }
 
 /** \brief Solve a triangular Sylvester equation AX + XB = C 
   *
@@ -412,41 +259,40 @@
   * \param[in]  B  the matrix B; should be square and upper triangular
   * \param[in]  C  the matrix C; should have correct size.
   *
   * \returns the solution X.
   *
-  * If A is m-by-m and B is n-by-n, then both C and X are m-by-n. 
-  * The (i,j)-th component of the Sylvester equation is
+  * If A is m-by-m and B is n-by-n, then both C and X are m-by-n.  The (i,j)-th component of the Sylvester
+  * equation is
   * \f[ 
   *     \sum_{k=i}^m A_{ik} X_{kj} + \sum_{k=1}^j X_{ik} B_{kj} = C_{ij}. 
   * \f]
   * This can be re-arranged to yield:
   * \f[ 
   *     X_{ij} = \frac{1}{A_{ii} + B_{jj}} \Bigl( C_{ij}
   *     - \sum_{k=i+1}^m A_{ik} X_{kj} - \sum_{k=1}^{j-1} X_{ik} B_{kj} \Bigr).
   * \f]
-  * It is assumed that A and B are such that the numerator is never
-  * zero (otherwise the Sylvester equation does not have a unique
-  * solution). In that case, these equations can be evaluated in the
-  * order \f$ i=m,\ldots,1 \f$ and \f$ j=1,\ldots,n \f$.
+  * It is assumed that A and B are such that the numerator is never zero (otherwise the Sylvester equation
+  * does not have a unique solution). In that case, these equations can be evaluated in the order 
+  * \f$ i=m,\ldots,1 \f$ and \f$ j=1,\ldots,n \f$.
   */
-template <typename MatrixType, typename AtomicType>
-typename MatrixFunction<MatrixType,AtomicType,1>::DynMatrixType MatrixFunction<MatrixType,AtomicType,1>::solveTriangularSylvester(
-  const DynMatrixType& A, 
-  const DynMatrixType& B, 
-  const DynMatrixType& C)
+template <typename MatrixType>
+MatrixType matrix_function_solve_triangular_sylvester(const MatrixType& A, const MatrixType& B, const MatrixType& C)
 {
   eigen_assert(A.rows() == A.cols());
   eigen_assert(A.isUpperTriangular());
   eigen_assert(B.rows() == B.cols());
   eigen_assert(B.isUpperTriangular());
   eigen_assert(C.rows() == A.rows());
   eigen_assert(C.cols() == B.rows());
 
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::Scalar Scalar;
+
   Index m = A.rows();
   Index n = B.rows();
-  DynMatrixType X(m, n);
+  MatrixType X(m, n);
 
   for (Index i = m - 1; i >= 0; --i) {
     for (Index j = 0; j < n; ++j) {
 
       // Compute AX = \sum_{k=i+1}^m A_{ik} X_{kj}
@@ -470,71 +316,214 @@
       X(i,j) = (C(i,j) - AX - XB) / (A(i,i) + B(j,j));
     }
   }
   return X;
 }
+
+/** \brief Compute part of matrix function above block diagonal.
+  *
+  * This routine completes the computation of \p fT, denoting a matrix function applied to the triangular
+  * matrix \p T. It assumes that the block diagonal part of \p fT has already been computed. The part below
+  * the diagonal is zero, because \p T is upper triangular.
+  */
+template <typename MatrixType, typename VectorType>
+void matrix_function_compute_above_diagonal(const MatrixType& T, const VectorType& blockStart, const VectorType& clusterSize, MatrixType& fT)
+{ 
+  typedef internal::traits<MatrixType> Traits;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
+  static const int RowsAtCompileTime = Traits::RowsAtCompileTime;
+  static const int ColsAtCompileTime = Traits::ColsAtCompileTime;
+  static const int Options = MatrixType::Options;
+  typedef Matrix<Scalar, Dynamic, Dynamic, Options, RowsAtCompileTime, ColsAtCompileTime> DynMatrixType;
+
+  for (Index k = 1; k < clusterSize.rows(); k++) {
+    for (Index i = 0; i < clusterSize.rows() - k; i++) {
+      // compute (i, i+k) block
+      DynMatrixType A = T.block(blockStart(i), blockStart(i), clusterSize(i), clusterSize(i));
+      DynMatrixType B = -T.block(blockStart(i+k), blockStart(i+k), clusterSize(i+k), clusterSize(i+k));
+      DynMatrixType C = fT.block(blockStart(i), blockStart(i), clusterSize(i), clusterSize(i))
+        * T.block(blockStart(i), blockStart(i+k), clusterSize(i), clusterSize(i+k));
+      C -= T.block(blockStart(i), blockStart(i+k), clusterSize(i), clusterSize(i+k))
+        * fT.block(blockStart(i+k), blockStart(i+k), clusterSize(i+k), clusterSize(i+k));
+      for (Index m = i + 1; m < i + k; m++) {
+        C += fT.block(blockStart(i), blockStart(m), clusterSize(i), clusterSize(m))
+          * T.block(blockStart(m), blockStart(i+k), clusterSize(m), clusterSize(i+k));
+        C -= T.block(blockStart(i), blockStart(m), clusterSize(i), clusterSize(m))
+          * fT.block(blockStart(m), blockStart(i+k), clusterSize(m), clusterSize(i+k));
+      }
+      fT.block(blockStart(i), blockStart(i+k), clusterSize(i), clusterSize(i+k))
+        = matrix_function_solve_triangular_sylvester(A, B, C);
+    }
+  }
+}
+
+/** \ingroup MatrixFunctions_Module
+  * \brief Class for computing matrix functions.
+  * \tparam  MatrixType  type of the argument of the matrix function,
+  *                      expected to be an instantiation of the Matrix class template.
+  * \tparam  AtomicType  type for computing matrix function of atomic blocks.
+  * \tparam  IsComplex   used internally to select correct specialization.
+  *
+  * This class implements the Schur-Parlett algorithm for computing matrix functions. The spectrum of the
+  * matrix is divided in clustered of eigenvalues that lies close together. This class delegates the
+  * computation of the matrix function on every block corresponding to these clusters to an object of type
+  * \p AtomicType and uses these results to compute the matrix function of the whole matrix. The class
+  * \p AtomicType should have a \p compute() member function for computing the matrix function of a block.
+  *
+  * \sa class MatrixFunctionAtomic, class MatrixLogarithmAtomic
+  */
+template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
+struct matrix_function_compute
+{  
+    /** \brief Compute the matrix function.
+      *
+      * \param[in]  A       argument of matrix function, should be a square matrix.
+      * \param[in]  atomic  class for computing matrix function of atomic blocks.
+      * \param[out] result  the function \p f applied to \p A, as
+      * specified in the constructor.
+      *
+      * See MatrixBase::matrixFunction() for details on how this computation
+      * is implemented.
+      */
+    template <typename AtomicType, typename ResultType> 
+    static void run(const MatrixType& A, AtomicType& atomic, ResultType &result);    
+};
+
+/** \internal \ingroup MatrixFunctions_Module 
+  * \brief Partial specialization of MatrixFunction for real matrices
+  *
+  * This converts the real matrix to a complex matrix, compute the matrix function of that matrix, and then
+  * converts the result back to a real matrix.
+  */
+template <typename MatrixType>
+struct matrix_function_compute<MatrixType, 0>
+{  
+  template <typename MatA, typename AtomicType, typename ResultType>
+  static void run(const MatA& A, AtomicType& atomic, ResultType &result)
+  {
+    typedef internal::traits<MatrixType> Traits;
+    typedef typename Traits::Scalar Scalar;
+    static const int Rows = Traits::RowsAtCompileTime, Cols = Traits::ColsAtCompileTime;
+    static const int MaxRows = Traits::MaxRowsAtCompileTime, MaxCols = Traits::MaxColsAtCompileTime;
+
+    typedef std::complex<Scalar> ComplexScalar;
+    typedef Matrix<ComplexScalar, Rows, Cols, 0, MaxRows, MaxCols> ComplexMatrix;
+
+    ComplexMatrix CA = A.template cast<ComplexScalar>();
+    ComplexMatrix Cresult;
+    matrix_function_compute<ComplexMatrix>::run(CA, atomic, Cresult);
+    result = Cresult.real();
+  }
+};
+
+/** \internal \ingroup MatrixFunctions_Module 
+  * \brief Partial specialization of MatrixFunction for complex matrices
+  */
+template <typename MatrixType>
+struct matrix_function_compute<MatrixType, 1>
+{
+  template <typename MatA, typename AtomicType, typename ResultType>
+  static void run(const MatA& A, AtomicType& atomic, ResultType &result)
+  {
+    typedef internal::traits<MatrixType> Traits;
+    
+    // compute Schur decomposition of A
+    const ComplexSchur<MatrixType> schurOfA(A);  
+    MatrixType T = schurOfA.matrixT();
+    MatrixType U = schurOfA.matrixU();
+
+    // partition eigenvalues into clusters of ei'vals "close" to each other
+    std::list<std::list<Index> > clusters; 
+    matrix_function_partition_eigenvalues(T.diagonal(), clusters);
+
+    // compute size of each cluster
+    Matrix<Index, Dynamic, 1> clusterSize;
+    matrix_function_compute_cluster_size(clusters, clusterSize);
+
+    // blockStart[i] is row index at which block corresponding to i-th cluster starts 
+    Matrix<Index, Dynamic, 1> blockStart; 
+    matrix_function_compute_block_start(clusterSize, blockStart);
+
+    // compute map so that eivalToCluster[i] = j means that i-th ei'val is in j-th cluster 
+    Matrix<Index, Dynamic, 1> eivalToCluster;
+    matrix_function_compute_map(T.diagonal(), clusters, eivalToCluster);
+
+    // compute permutation which groups ei'vals in same cluster together 
+    Matrix<Index, Traits::RowsAtCompileTime, 1> permutation;
+    matrix_function_compute_permutation(blockStart, eivalToCluster, permutation);
+
+    // permute Schur decomposition
+    matrix_function_permute_schur(permutation, U, T);
+
+    // compute result
+    MatrixType fT; // matrix function applied to T
+    matrix_function_compute_block_atomic(T, atomic, blockStart, clusterSize, fT);
+    matrix_function_compute_above_diagonal(T, blockStart, clusterSize, fT);
+    result = U * (fT.template triangularView<Upper>() * U.adjoint());
+  }
+};
+
+} // end of namespace internal
 
 /** \ingroup MatrixFunctions_Module
   *
   * \brief Proxy for the matrix function of some matrix (expression).
   *
   * \tparam Derived  Type of the argument to the matrix function.
   *
-  * This class holds the argument to the matrix function until it is
-  * assigned or evaluated for some other reason (so the argument
-  * should not be changed in the meantime). It is the return type of
-  * matrixBase::matrixFunction() and related functions and most of the
-  * time this is the only way it is used.
+  * This class holds the argument to the matrix function until it is assigned or evaluated for some other
+  * reason (so the argument should not be changed in the meantime). It is the return type of
+  * matrixBase::matrixFunction() and related functions and most of the time this is the only way it is used.
   */
 template<typename Derived> class MatrixFunctionReturnValue
 : public ReturnByValue<MatrixFunctionReturnValue<Derived> >
 {
   public:
-
     typedef typename Derived::Scalar Scalar;
     typedef typename Derived::Index Index;
     typedef typename internal::stem_function<Scalar>::type StemFunction;
 
-   /** \brief Constructor.
+  protected:
+    typedef typename internal::ref_selector<Derived>::type DerivedNested;
+
+  public:
+
+    /** \brief Constructor.
       *
-      * \param[in] A  %Matrix (expression) forming the argument of the
-      * matrix function.
+      * \param[in] A  %Matrix (expression) forming the argument of the matrix function.
       * \param[in] f  Stem function for matrix function under consideration.
       */
     MatrixFunctionReturnValue(const Derived& A, StemFunction f) : m_A(A), m_f(f) { }
 
     /** \brief Compute the matrix function.
       *
-      * \param[out] result \p f applied to \p A, where \p f and \p A
-      * are as in the constructor.
+      * \param[out] result \p f applied to \p A, where \p f and \p A are as in the constructor.
       */
     template <typename ResultType>
     inline void evalTo(ResultType& result) const
     {
-      typedef typename Derived::PlainObject PlainObject;
-      typedef internal::traits<PlainObject> Traits;
+      typedef typename internal::nested_eval<Derived, 10>::type NestedEvalType;
+      typedef typename internal::remove_all<NestedEvalType>::type NestedEvalTypeClean;
+      typedef internal::traits<NestedEvalTypeClean> Traits;
       static const int RowsAtCompileTime = Traits::RowsAtCompileTime;
       static const int ColsAtCompileTime = Traits::ColsAtCompileTime;
-      static const int Options = PlainObject::Options;
       typedef std::complex<typename NumTraits<Scalar>::Real> ComplexScalar;
-      typedef Matrix<ComplexScalar, Dynamic, Dynamic, Options, RowsAtCompileTime, ColsAtCompileTime> DynMatrixType;
-      typedef MatrixFunctionAtomic<DynMatrixType> AtomicType;
+      typedef Matrix<ComplexScalar, Dynamic, Dynamic, 0, RowsAtCompileTime, ColsAtCompileTime> DynMatrixType;
+
+      typedef internal::MatrixFunctionAtomic<DynMatrixType> AtomicType;
       AtomicType atomic(m_f);
 
-      const PlainObject Aevaluated = m_A.eval();
-      MatrixFunction<PlainObject, AtomicType> mf(Aevaluated, atomic);
-      mf.compute(result);
+      internal::matrix_function_compute<typename NestedEvalTypeClean::PlainObject>::run(m_A, atomic, result);
     }
 
     Index rows() const { return m_A.rows(); }
     Index cols() const { return m_A.cols(); }
 
   private:
-    typename internal::nested<Derived>::type m_A;
+    const DerivedNested m_A;
     StemFunction *m_f;
-
-    MatrixFunctionReturnValue& operator=(const MatrixFunctionReturnValue&);
 };
 
 namespace internal {
 template<typename Derived>
 struct traits<MatrixFunctionReturnValue<Derived> >
@@ -557,35 +546,35 @@
 template <typename Derived>
 const MatrixFunctionReturnValue<Derived> MatrixBase<Derived>::sin() const
 {
   eigen_assert(rows() == cols());
   typedef typename internal::stem_function<Scalar>::ComplexScalar ComplexScalar;
-  return MatrixFunctionReturnValue<Derived>(derived(), StdStemFunctions<ComplexScalar>::sin);
+  return MatrixFunctionReturnValue<Derived>(derived(), internal::stem_function_sin<ComplexScalar>);
 }
 
 template <typename Derived>
 const MatrixFunctionReturnValue<Derived> MatrixBase<Derived>::cos() const
 {
   eigen_assert(rows() == cols());
   typedef typename internal::stem_function<Scalar>::ComplexScalar ComplexScalar;
-  return MatrixFunctionReturnValue<Derived>(derived(), StdStemFunctions<ComplexScalar>::cos);
+  return MatrixFunctionReturnValue<Derived>(derived(), internal::stem_function_cos<ComplexScalar>);
 }
 
 template <typename Derived>
 const MatrixFunctionReturnValue<Derived> MatrixBase<Derived>::sinh() const
 {
   eigen_assert(rows() == cols());
   typedef typename internal::stem_function<Scalar>::ComplexScalar ComplexScalar;
-  return MatrixFunctionReturnValue<Derived>(derived(), StdStemFunctions<ComplexScalar>::sinh);
+  return MatrixFunctionReturnValue<Derived>(derived(), internal::stem_function_sinh<ComplexScalar>);
 }
 
 template <typename Derived>
 const MatrixFunctionReturnValue<Derived> MatrixBase<Derived>::cosh() const
 {
   eigen_assert(rows() == cols());
   typedef typename internal::stem_function<Scalar>::ComplexScalar ComplexScalar;
-  return MatrixFunctionReturnValue<Derived>(derived(), StdStemFunctions<ComplexScalar>::cosh);
+  return MatrixFunctionReturnValue<Derived>(derived(), internal::stem_function_cosh<ComplexScalar>);
 }
 
 } // end namespace Eigen
 
 #endif // EIGEN_MATRIX_FUNCTION

DELETED 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h
Index: 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h
+++ 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h
@@ -1,131 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Jitse Niesen <jitse@maths.leeds.ac.uk>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_MATRIX_FUNCTION_ATOMIC
-#define EIGEN_MATRIX_FUNCTION_ATOMIC
-
-namespace Eigen { 
-
-/** \ingroup MatrixFunctions_Module
-  * \class MatrixFunctionAtomic
-  * \brief Helper class for computing matrix functions of atomic matrices.
-  *
-  * \internal
-  * Here, an atomic matrix is a triangular matrix whose diagonal
-  * entries are close to each other.
-  */
-template <typename MatrixType>
-class MatrixFunctionAtomic
-{
-  public:
-
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename internal::stem_function<Scalar>::type StemFunction;
-    typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-    /** \brief Constructor
-      * \param[in]  f  matrix function to compute.
-      */
-    MatrixFunctionAtomic(StemFunction f) : m_f(f) { }
-
-    /** \brief Compute matrix function of atomic matrix
-      * \param[in]  A  argument of matrix function, should be upper triangular and atomic
-      * \returns  f(A), the matrix function evaluated at the given matrix
-      */
-    MatrixType compute(const MatrixType& A);
-
-  private:
-
-    // Prevent copying
-    MatrixFunctionAtomic(const MatrixFunctionAtomic&);
-    MatrixFunctionAtomic& operator=(const MatrixFunctionAtomic&);
-
-    void computeMu();
-    bool taylorConverged(Index s, const MatrixType& F, const MatrixType& Fincr, const MatrixType& P);
-
-    /** \brief Pointer to scalar function */
-    StemFunction* m_f;
-
-    /** \brief Size of matrix function */
-    Index m_Arows;
-
-    /** \brief Mean of eigenvalues */
-    Scalar m_avgEival;
-
-    /** \brief Argument shifted by mean of eigenvalues */
-    MatrixType m_Ashifted;
-
-    /** \brief Constant used to determine whether Taylor series has converged */
-    RealScalar m_mu;
-};
-
-template <typename MatrixType>
-MatrixType MatrixFunctionAtomic<MatrixType>::compute(const MatrixType& A)
-{
-  // TODO: Use that A is upper triangular
-  m_Arows = A.rows();
-  m_avgEival = A.trace() / Scalar(RealScalar(m_Arows));
-  m_Ashifted = A - m_avgEival * MatrixType::Identity(m_Arows, m_Arows);
-  computeMu();
-  MatrixType F = m_f(m_avgEival, 0) * MatrixType::Identity(m_Arows, m_Arows);
-  MatrixType P = m_Ashifted;
-  MatrixType Fincr;
-  for (Index s = 1; s < 1.1 * m_Arows + 10; s++) { // upper limit is fairly arbitrary
-    Fincr = m_f(m_avgEival, static_cast<int>(s)) * P;
-    F += Fincr;
-    P = Scalar(RealScalar(1.0/(s + 1))) * P * m_Ashifted;
-    if (taylorConverged(s, F, Fincr, P)) {
-      return F;
-    }
-  }
-  eigen_assert("Taylor series does not converge" && 0);
-  return F;
-}
-
-/** \brief Compute \c m_mu. */
-template <typename MatrixType>
-void MatrixFunctionAtomic<MatrixType>::computeMu()
-{
-  const MatrixType N = MatrixType::Identity(m_Arows, m_Arows) - m_Ashifted;
-  VectorType e = VectorType::Ones(m_Arows);
-  N.template triangularView<Upper>().solveInPlace(e);
-  m_mu = e.cwiseAbs().maxCoeff();
-}
-
-/** \brief Determine whether Taylor series has converged */
-template <typename MatrixType>
-bool MatrixFunctionAtomic<MatrixType>::taylorConverged(Index s, const MatrixType& F,
-						       const MatrixType& Fincr, const MatrixType& P)
-{
-  const Index n = F.rows();
-  const RealScalar F_norm = F.cwiseAbs().rowwise().sum().maxCoeff();
-  const RealScalar Fincr_norm = Fincr.cwiseAbs().rowwise().sum().maxCoeff();
-  if (Fincr_norm < NumTraits<Scalar>::epsilon() * F_norm) {
-    RealScalar delta = 0;
-    RealScalar rfactorial = 1;
-    for (Index r = 0; r < n; r++) {
-      RealScalar mx = 0;
-      for (Index i = 0; i < n; i++)
-        mx = (std::max)(mx, std::abs(m_f(m_Ashifted(i, i) + m_avgEival, static_cast<int>(s+r))));
-      if (r != 0)
-        rfactorial *= RealScalar(r);
-      delta = (std::max)(delta, mx / rfactorial);
-    }
-    const RealScalar P_norm = P.cwiseAbs().rowwise().sum().maxCoeff();
-    if (m_mu * delta * P_norm < NumTraits<Scalar>::epsilon() * F_norm)
-      return true;
-  }
-  return false;
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_MATRIX_FUNCTION_ATOMIC

Index: 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
+++ 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
@@ -1,103 +1,45 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2011, 2013 Jitse Niesen <jitse@maths.leeds.ac.uk>
 // Copyright (C) 2011 Chen-Pang He <jdh8@ms63.hinet.net>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATRIX_LOGARITHM
 #define EIGEN_MATRIX_LOGARITHM
 
-#ifndef M_PI
-#define M_PI 3.141592653589793238462643383279503L
-#endif
-
 namespace Eigen { 
 
-/** \ingroup MatrixFunctions_Module
-  * \class MatrixLogarithmAtomic
-  * \brief Helper class for computing matrix logarithm of atomic matrices.
-  *
-  * \internal
-  * Here, an atomic matrix is a triangular matrix whose diagonal
-  * entries are close to each other.
-  *
-  * \sa class MatrixFunctionAtomic, MatrixBase::log()
-  */
-template <typename MatrixType>
-class MatrixLogarithmAtomic
-{
-public:
-
-  typedef typename MatrixType::Scalar Scalar;
-  // typedef typename MatrixType::Index Index;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  // typedef typename internal::stem_function<Scalar>::type StemFunction;
-  // typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  /** \brief Constructor. */
-  MatrixLogarithmAtomic() { }
-
-  /** \brief Compute matrix logarithm of atomic matrix
-    * \param[in]  A  argument of matrix logarithm, should be upper triangular and atomic
-    * \returns  The logarithm of \p A.
-    */
-  MatrixType compute(const MatrixType& A);
-
-private:
-
-  void compute2x2(const MatrixType& A, MatrixType& result);
-  void computeBig(const MatrixType& A, MatrixType& result);
-  int getPadeDegree(float normTminusI);
-  int getPadeDegree(double normTminusI);
-  int getPadeDegree(long double normTminusI);
-  void computePade(MatrixType& result, const MatrixType& T, int degree);
-  void computePade3(MatrixType& result, const MatrixType& T);
-  void computePade4(MatrixType& result, const MatrixType& T);
-  void computePade5(MatrixType& result, const MatrixType& T);
-  void computePade6(MatrixType& result, const MatrixType& T);
-  void computePade7(MatrixType& result, const MatrixType& T);
-  void computePade8(MatrixType& result, const MatrixType& T);
-  void computePade9(MatrixType& result, const MatrixType& T);
-  void computePade10(MatrixType& result, const MatrixType& T);
-  void computePade11(MatrixType& result, const MatrixType& T);
-
-  static const int minPadeDegree = 3;
-  static const int maxPadeDegree = std::numeric_limits<RealScalar>::digits<= 24?  5:  // single precision
-                                   std::numeric_limits<RealScalar>::digits<= 53?  7:  // double precision
-                                   std::numeric_limits<RealScalar>::digits<= 64?  8:  // extended precision
-                                   std::numeric_limits<RealScalar>::digits<=106? 10:  // double-double
-                                                                                 11;  // quadruple precision
-
-  // Prevent copying
-  MatrixLogarithmAtomic(const MatrixLogarithmAtomic&);
-  MatrixLogarithmAtomic& operator=(const MatrixLogarithmAtomic&);
+namespace internal { 
+
+template <typename Scalar>
+struct matrix_log_min_pade_degree 
+{
+  static const int value = 3;
 };
 
-/** \brief Compute logarithm of triangular matrix with clustered eigenvalues. */
-template <typename MatrixType>
-MatrixType MatrixLogarithmAtomic<MatrixType>::compute(const MatrixType& A)
-{
-  using std::log;
-  MatrixType result(A.rows(), A.rows());
-  if (A.rows() == 1)
-    result(0,0) = log(A(0,0));
-  else if (A.rows() == 2)
-    compute2x2(A, result);
-  else
-    computeBig(A, result);
-  return result;
-}
+template <typename Scalar>
+struct matrix_log_max_pade_degree 
+{
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  static const int value = std::numeric_limits<RealScalar>::digits<= 24?  5:  // single precision
+                           std::numeric_limits<RealScalar>::digits<= 53?  7:  // double precision
+                           std::numeric_limits<RealScalar>::digits<= 64?  8:  // extended precision
+                           std::numeric_limits<RealScalar>::digits<=106? 10:  // double-double
+                                                                         11;  // quadruple precision
+};
 
 /** \brief Compute logarithm of 2x2 triangular matrix. */
 template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::compute2x2(const MatrixType& A, MatrixType& result)
+void matrix_log_compute_2x2(const MatrixType& A, MatrixType& result)
 {
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
   using std::abs;
   using std::ceil;
   using std::imag;
   using std::log;
 
@@ -106,85 +48,57 @@
 
   result(0,0) = logA00;
   result(1,0) = Scalar(0);
   result(1,1) = logA11;
 
-  if (A(0,0) == A(1,1)) {
-    result(0,1) = A(0,1) / A(0,0);
-  } else if ((abs(A(0,0)) < 0.5*abs(A(1,1))) || (abs(A(0,0)) > 2*abs(A(1,1)))) {
-    result(0,1) = A(0,1) * (logA11 - logA00) / (A(1,1) - A(0,0));
-  } else {
-    // computation in previous branch is inaccurate if A(1,1) \approx A(0,0)
-    int unwindingNumber = static_cast<int>(ceil((imag(logA11 - logA00) - M_PI) / (2*M_PI)));
-    Scalar y = A(1,1) - A(0,0), x = A(1,1) + A(0,0);
-    result(0,1) = A(0,1) * (Scalar(2) * numext::atanh2(y,x) + Scalar(0,2*M_PI*unwindingNumber)) / y;
-  }
-}
-
-/** \brief Compute logarithm of triangular matrices with size > 2. 
-  * \details This uses a inverse scale-and-square algorithm. */
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computeBig(const MatrixType& A, MatrixType& result)
-{
-  using std::pow;
-  int numberOfSquareRoots = 0;
-  int numberOfExtraSquareRoots = 0;
-  int degree;
-  MatrixType T = A, sqrtT;
-  const RealScalar maxNormForPade = maxPadeDegree<= 5? 5.3149729967117310e-1:                     // single precision
-                                    maxPadeDegree<= 7? 2.6429608311114350e-1:                     // double precision
-                                    maxPadeDegree<= 8? 2.32777776523703892094e-1L:                // extended precision
-                                    maxPadeDegree<=10? 1.05026503471351080481093652651105e-1L:    // double-double
-                                                       1.1880960220216759245467951592883642e-1L;  // quadruple precision
-
-  while (true) {
-    RealScalar normTminusI = (T - MatrixType::Identity(T.rows(), T.rows())).cwiseAbs().colwise().sum().maxCoeff();
-    if (normTminusI < maxNormForPade) {
-      degree = getPadeDegree(normTminusI);
-      int degree2 = getPadeDegree(normTminusI / RealScalar(2));
-      if ((degree - degree2 <= 1) || (numberOfExtraSquareRoots == 1)) 
-        break;
-      ++numberOfExtraSquareRoots;
-    }
-    MatrixSquareRootTriangular<MatrixType>(T).compute(sqrtT);
-    T = sqrtT.template triangularView<Upper>();
-    ++numberOfSquareRoots;
-  }
-
-  computePade(result, T, degree);
-  result *= pow(RealScalar(2), numberOfSquareRoots);
-}
-
-/* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = float) */
-template <typename MatrixType>
-int MatrixLogarithmAtomic<MatrixType>::getPadeDegree(float normTminusI)
-{
-  const float maxNormForPade[] = { 2.5111573934555054e-1 /* degree = 3 */ , 4.0535837411880493e-1,
-            5.3149729967117310e-1 };
-  int degree = 3;
+  Scalar y = A(1,1) - A(0,0);
+  if (y==Scalar(0))
+  {
+    result(0,1) = A(0,1) / A(0,0);
+  }
+  else if ((abs(A(0,0)) < RealScalar(0.5)*abs(A(1,1))) || (abs(A(0,0)) > 2*abs(A(1,1))))
+  {
+    result(0,1) = A(0,1) * (logA11 - logA00) / y;
+  }
+  else
+  {
+    // computation in previous branch is inaccurate if A(1,1) \approx A(0,0)
+    int unwindingNumber = static_cast<int>(ceil((imag(logA11 - logA00) - RealScalar(EIGEN_PI)) / RealScalar(2*EIGEN_PI)));
+    result(0,1) = A(0,1) * (numext::log1p(y/A(0,0)) + Scalar(0,2*EIGEN_PI*unwindingNumber)) / y;
+  }
+}
+
+/* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = float) */
+inline int matrix_log_get_pade_degree(float normTminusI)
+{
+  const float maxNormForPade[] = { 2.5111573934555054e-1 /* degree = 3 */ , 4.0535837411880493e-1,
+            5.3149729967117310e-1 };
+  const int minPadeDegree = matrix_log_min_pade_degree<float>::value;
+  const int maxPadeDegree = matrix_log_max_pade_degree<float>::value;
+  int degree = minPadeDegree;
   for (; degree <= maxPadeDegree; ++degree) 
     if (normTminusI <= maxNormForPade[degree - minPadeDegree])
       break;
   return degree;
 }
 
 /* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = double) */
-template <typename MatrixType>
-int MatrixLogarithmAtomic<MatrixType>::getPadeDegree(double normTminusI)
+inline int matrix_log_get_pade_degree(double normTminusI)
 {
   const double maxNormForPade[] = { 1.6206284795015624e-2 /* degree = 3 */ , 5.3873532631381171e-2,
             1.1352802267628681e-1, 1.8662860613541288e-1, 2.642960831111435e-1 };
-  int degree = 3;
+  const int minPadeDegree = matrix_log_min_pade_degree<double>::value;
+  const int maxPadeDegree = matrix_log_max_pade_degree<double>::value;
+  int degree = minPadeDegree;
   for (; degree <= maxPadeDegree; ++degree)
     if (normTminusI <= maxNormForPade[degree - minPadeDegree])
       break;
   return degree;
 }
 
 /* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = long double) */
-template <typename MatrixType>
-int MatrixLogarithmAtomic<MatrixType>::getPadeDegree(long double normTminusI)
+inline int matrix_log_get_pade_degree(long double normTminusI)
 {
 #if   LDBL_MANT_DIG == 53         // double precision
   const long double maxNormForPade[] = { 1.6206284795015624e-2L /* degree = 3 */ , 5.3873532631381171e-2L,
             1.1352802267628681e-1L, 1.8662860613541288e-1L, 2.642960831111435e-1L };
 #elif LDBL_MANT_DIG <= 64         // extended precision
@@ -202,210 +116,183 @@
             5.8853168473544560470387769480192666e-4L, 2.9216120366601315391789493628113520e-3L,
             8.8415758124319434347116734705174308e-3L, 1.9850836029449446668518049562565291e-2L,
             3.6688019729653446926585242192447447e-2L, 5.9290962294020186998954055264528393e-2L,
             8.6998436081634343903250580992127677e-2L, 1.1880960220216759245467951592883642e-1L };
 #endif
-  int degree = 3;
+  const int minPadeDegree = matrix_log_min_pade_degree<long double>::value;
+  const int maxPadeDegree = matrix_log_max_pade_degree<long double>::value;
+  int degree = minPadeDegree;
   for (; degree <= maxPadeDegree; ++degree)
     if (normTminusI <= maxNormForPade[degree - minPadeDegree])
       break;
   return degree;
 }
 
 /* \brief Compute Pade approximation to matrix logarithm */
 template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade(MatrixType& result, const MatrixType& T, int degree)
-{
-  switch (degree) {
-    case 3:  computePade3(result, T);  break;
-    case 4:  computePade4(result, T);  break;
-    case 5:  computePade5(result, T);  break;
-    case 6:  computePade6(result, T);  break;
-    case 7:  computePade7(result, T);  break;
-    case 8:  computePade8(result, T);  break;
-    case 9:  computePade9(result, T);  break;
-    case 10: computePade10(result, T); break;
-    case 11: computePade11(result, T); break;
-    default: assert(false); // should never happen
-  }
-} 
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade3(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 3;
-  const RealScalar nodes[]   = { 0.1127016653792583114820734600217600L, 0.5000000000000000000000000000000000L,
-            0.8872983346207416885179265399782400L };
-  const RealScalar weights[] = { 0.2777777777777777777777777777777778L, 0.4444444444444444444444444444444444L,
-            0.2777777777777777777777777777777778L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade4(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 4;
-  const RealScalar nodes[]   = { 0.0694318442029737123880267555535953L, 0.3300094782075718675986671204483777L,
-            0.6699905217924281324013328795516223L, 0.9305681557970262876119732444464048L };
-  const RealScalar weights[] = { 0.1739274225687269286865319746109997L, 0.3260725774312730713134680253890003L,
-            0.3260725774312730713134680253890003L, 0.1739274225687269286865319746109997L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade5(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 5;
-  const RealScalar nodes[]   = { 0.0469100770306680036011865608503035L, 0.2307653449471584544818427896498956L,
-            0.5000000000000000000000000000000000L, 0.7692346550528415455181572103501044L,
-            0.9530899229693319963988134391496965L };
-  const RealScalar weights[] = { 0.1184634425280945437571320203599587L, 0.2393143352496832340206457574178191L,
-            0.2844444444444444444444444444444444L, 0.2393143352496832340206457574178191L,
-            0.1184634425280945437571320203599587L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade6(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 6;
-  const RealScalar nodes[]   = { 0.0337652428984239860938492227530027L, 0.1693953067668677431693002024900473L,
-            0.3806904069584015456847491391596440L, 0.6193095930415984543152508608403560L,
-            0.8306046932331322568306997975099527L, 0.9662347571015760139061507772469973L };
-  const RealScalar weights[] = { 0.0856622461895851725201480710863665L, 0.1803807865240693037849167569188581L,
-            0.2339569672863455236949351719947755L, 0.2339569672863455236949351719947755L,
-            0.1803807865240693037849167569188581L, 0.0856622461895851725201480710863665L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade7(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 7;
-  const RealScalar nodes[]   = { 0.0254460438286207377369051579760744L, 0.1292344072003027800680676133596058L,
-            0.2970774243113014165466967939615193L, 0.5000000000000000000000000000000000L,
-            0.7029225756886985834533032060384807L, 0.8707655927996972199319323866403942L,
-            0.9745539561713792622630948420239256L };
-  const RealScalar weights[] = { 0.0647424830844348466353057163395410L, 0.1398526957446383339507338857118898L,
-            0.1909150252525594724751848877444876L, 0.2089795918367346938775510204081633L,
-            0.1909150252525594724751848877444876L, 0.1398526957446383339507338857118898L,
-            0.0647424830844348466353057163395410L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade8(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 8;
-  const RealScalar nodes[]   = { 0.0198550717512318841582195657152635L, 0.1016667612931866302042230317620848L,
-            0.2372337950418355070911304754053768L, 0.4082826787521750975302619288199080L,
-            0.5917173212478249024697380711800920L, 0.7627662049581644929088695245946232L,
-            0.8983332387068133697957769682379152L, 0.9801449282487681158417804342847365L };
-  const RealScalar weights[] = { 0.0506142681451881295762656771549811L, 0.1111905172266872352721779972131204L,
-            0.1568533229389436436689811009933007L, 0.1813418916891809914825752246385978L,
-            0.1813418916891809914825752246385978L, 0.1568533229389436436689811009933007L,
-            0.1111905172266872352721779972131204L, 0.0506142681451881295762656771549811L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade9(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 9;
-  const RealScalar nodes[]   = { 0.0159198802461869550822118985481636L, 0.0819844463366821028502851059651326L,
-            0.1933142836497048013456489803292629L, 0.3378732882980955354807309926783317L,
-            0.5000000000000000000000000000000000L, 0.6621267117019044645192690073216683L,
-            0.8066857163502951986543510196707371L, 0.9180155536633178971497148940348674L,
-            0.9840801197538130449177881014518364L };
-  const RealScalar weights[] = { 0.0406371941807872059859460790552618L, 0.0903240803474287020292360156214564L,
-            0.1303053482014677311593714347093164L, 0.1561735385200014200343152032922218L,
-            0.1651196775006298815822625346434870L, 0.1561735385200014200343152032922218L,
-            0.1303053482014677311593714347093164L, 0.0903240803474287020292360156214564L,
-            0.0406371941807872059859460790552618L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade10(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 10;
-  const RealScalar nodes[]   = { 0.0130467357414141399610179939577740L, 0.0674683166555077446339516557882535L,
-            0.1602952158504877968828363174425632L, 0.2833023029353764046003670284171079L,
-            0.4255628305091843945575869994351400L, 0.5744371694908156054424130005648600L,
-            0.7166976970646235953996329715828921L, 0.8397047841495122031171636825574368L,
-            0.9325316833444922553660483442117465L, 0.9869532642585858600389820060422260L };
-  const RealScalar weights[] = { 0.0333356721543440687967844049466659L, 0.0747256745752902965728881698288487L,
-            0.1095431812579910219977674671140816L, 0.1346333596549981775456134607847347L,
-            0.1477621123573764350869464973256692L, 0.1477621123573764350869464973256692L,
-            0.1346333596549981775456134607847347L, 0.1095431812579910219977674671140816L,
-            0.0747256745752902965728881698288487L, 0.0333356721543440687967844049466659L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
-
-template <typename MatrixType>
-void MatrixLogarithmAtomic<MatrixType>::computePade11(MatrixType& result, const MatrixType& T)
-{
-  const int degree = 11;
-  const RealScalar nodes[]   = { 0.0108856709269715035980309994385713L, 0.0564687001159523504624211153480364L,
-            0.1349239972129753379532918739844233L, 0.2404519353965940920371371652706952L,
-            0.3652284220238275138342340072995692L, 0.5000000000000000000000000000000000L,
-            0.6347715779761724861657659927004308L, 0.7595480646034059079628628347293048L,
-            0.8650760027870246620467081260155767L, 0.9435312998840476495375788846519636L,
-            0.9891143290730284964019690005614287L };
-  const RealScalar weights[] = { 0.0278342835580868332413768602212743L, 0.0627901847324523123173471496119701L,
-            0.0931451054638671257130488207158280L, 0.1165968822959952399592618524215876L,
-            0.1314022722551233310903444349452546L, 0.1364625433889503153572417641681711L,
-            0.1314022722551233310903444349452546L, 0.1165968822959952399592618524215876L,
-            0.0931451054638671257130488207158280L, 0.0627901847324523123173471496119701L,
-            0.0278342835580868332413768602212743L };
-  eigen_assert(degree <= maxPadeDegree);
-  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
-  result.setZero(T.rows(), T.rows());
-  for (int k = 0; k < degree; ++k)
-    result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI)
-                           .template triangularView<Upper>().solve(TminusI);
-}
+void matrix_log_compute_pade(MatrixType& result, const MatrixType& T, int degree)
+{
+  typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+  const int minPadeDegree = 3;
+  const int maxPadeDegree = 11;
+  assert(degree >= minPadeDegree && degree <= maxPadeDegree);
+
+  const RealScalar nodes[][maxPadeDegree] = { 
+    { 0.1127016653792583114820734600217600L, 0.5000000000000000000000000000000000L,  // degree 3
+      0.8872983346207416885179265399782400L }, 
+    { 0.0694318442029737123880267555535953L, 0.3300094782075718675986671204483777L,  // degree 4
+      0.6699905217924281324013328795516223L, 0.9305681557970262876119732444464048L },
+    { 0.0469100770306680036011865608503035L, 0.2307653449471584544818427896498956L,  // degree 5
+      0.5000000000000000000000000000000000L, 0.7692346550528415455181572103501044L,
+      0.9530899229693319963988134391496965L },
+    { 0.0337652428984239860938492227530027L, 0.1693953067668677431693002024900473L,  // degree 6
+      0.3806904069584015456847491391596440L, 0.6193095930415984543152508608403560L,
+      0.8306046932331322568306997975099527L, 0.9662347571015760139061507772469973L },
+    { 0.0254460438286207377369051579760744L, 0.1292344072003027800680676133596058L,  // degree 7
+      0.2970774243113014165466967939615193L, 0.5000000000000000000000000000000000L,
+      0.7029225756886985834533032060384807L, 0.8707655927996972199319323866403942L,
+      0.9745539561713792622630948420239256L },
+    { 0.0198550717512318841582195657152635L, 0.1016667612931866302042230317620848L,  // degree 8
+      0.2372337950418355070911304754053768L, 0.4082826787521750975302619288199080L,
+      0.5917173212478249024697380711800920L, 0.7627662049581644929088695245946232L,
+      0.8983332387068133697957769682379152L, 0.9801449282487681158417804342847365L },
+    { 0.0159198802461869550822118985481636L, 0.0819844463366821028502851059651326L,  // degree 9
+      0.1933142836497048013456489803292629L, 0.3378732882980955354807309926783317L,
+      0.5000000000000000000000000000000000L, 0.6621267117019044645192690073216683L,
+      0.8066857163502951986543510196707371L, 0.9180155536633178971497148940348674L,
+      0.9840801197538130449177881014518364L },
+    { 0.0130467357414141399610179939577740L, 0.0674683166555077446339516557882535L,  // degree 10
+      0.1602952158504877968828363174425632L, 0.2833023029353764046003670284171079L,
+      0.4255628305091843945575869994351400L, 0.5744371694908156054424130005648600L,
+      0.7166976970646235953996329715828921L, 0.8397047841495122031171636825574368L,
+      0.9325316833444922553660483442117465L, 0.9869532642585858600389820060422260L },
+    { 0.0108856709269715035980309994385713L, 0.0564687001159523504624211153480364L,  // degree 11
+      0.1349239972129753379532918739844233L, 0.2404519353965940920371371652706952L,
+      0.3652284220238275138342340072995692L, 0.5000000000000000000000000000000000L,
+      0.6347715779761724861657659927004308L, 0.7595480646034059079628628347293048L,
+      0.8650760027870246620467081260155767L, 0.9435312998840476495375788846519636L,
+      0.9891143290730284964019690005614287L } };
+
+  const RealScalar weights[][maxPadeDegree] = { 
+    { 0.2777777777777777777777777777777778L, 0.4444444444444444444444444444444444L,  // degree 3
+      0.2777777777777777777777777777777778L },
+    { 0.1739274225687269286865319746109997L, 0.3260725774312730713134680253890003L,  // degree 4
+      0.3260725774312730713134680253890003L, 0.1739274225687269286865319746109997L },
+    { 0.1184634425280945437571320203599587L, 0.2393143352496832340206457574178191L,  // degree 5
+      0.2844444444444444444444444444444444L, 0.2393143352496832340206457574178191L,
+      0.1184634425280945437571320203599587L },
+    { 0.0856622461895851725201480710863665L, 0.1803807865240693037849167569188581L,  // degree 6
+      0.2339569672863455236949351719947755L, 0.2339569672863455236949351719947755L,
+      0.1803807865240693037849167569188581L, 0.0856622461895851725201480710863665L },
+    { 0.0647424830844348466353057163395410L, 0.1398526957446383339507338857118898L,  // degree 7
+      0.1909150252525594724751848877444876L, 0.2089795918367346938775510204081633L,
+      0.1909150252525594724751848877444876L, 0.1398526957446383339507338857118898L,
+      0.0647424830844348466353057163395410L },
+    { 0.0506142681451881295762656771549811L, 0.1111905172266872352721779972131204L,  // degree 8
+      0.1568533229389436436689811009933007L, 0.1813418916891809914825752246385978L,
+      0.1813418916891809914825752246385978L, 0.1568533229389436436689811009933007L,
+      0.1111905172266872352721779972131204L, 0.0506142681451881295762656771549811L },
+    { 0.0406371941807872059859460790552618L, 0.0903240803474287020292360156214564L,  // degree 9
+      0.1303053482014677311593714347093164L, 0.1561735385200014200343152032922218L,
+      0.1651196775006298815822625346434870L, 0.1561735385200014200343152032922218L,
+      0.1303053482014677311593714347093164L, 0.0903240803474287020292360156214564L,
+      0.0406371941807872059859460790552618L },
+    { 0.0333356721543440687967844049466659L, 0.0747256745752902965728881698288487L,  // degree 10
+      0.1095431812579910219977674671140816L, 0.1346333596549981775456134607847347L,
+      0.1477621123573764350869464973256692L, 0.1477621123573764350869464973256692L,
+      0.1346333596549981775456134607847347L, 0.1095431812579910219977674671140816L,
+      0.0747256745752902965728881698288487L, 0.0333356721543440687967844049466659L },
+    { 0.0278342835580868332413768602212743L, 0.0627901847324523123173471496119701L,  // degree 11
+      0.0931451054638671257130488207158280L, 0.1165968822959952399592618524215876L,
+      0.1314022722551233310903444349452546L, 0.1364625433889503153572417641681711L,
+      0.1314022722551233310903444349452546L, 0.1165968822959952399592618524215876L,
+      0.0931451054638671257130488207158280L, 0.0627901847324523123173471496119701L,
+      0.0278342835580868332413768602212743L } };
+
+  MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
+  result.setZero(T.rows(), T.rows());
+  for (int k = 0; k < degree; ++k) {
+    RealScalar weight = weights[degree-minPadeDegree][k];
+    RealScalar node = nodes[degree-minPadeDegree][k];
+    result += weight * (MatrixType::Identity(T.rows(), T.rows()) + node * TminusI)
+                       .template triangularView<Upper>().solve(TminusI);
+  }
+} 
+
+/** \brief Compute logarithm of triangular matrices with size > 2. 
+  * \details This uses a inverse scale-and-square algorithm. */
+template <typename MatrixType>
+void matrix_log_compute_big(const MatrixType& A, MatrixType& result)
+{
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  using std::pow;
+
+  int numberOfSquareRoots = 0;
+  int numberOfExtraSquareRoots = 0;
+  int degree;
+  MatrixType T = A, sqrtT;
+
+  int maxPadeDegree = matrix_log_max_pade_degree<Scalar>::value;
+  const RealScalar maxNormForPade = maxPadeDegree<= 5? 5.3149729967117310e-1L:                    // single precision
+                                    maxPadeDegree<= 7? 2.6429608311114350e-1L:                    // double precision
+                                    maxPadeDegree<= 8? 2.32777776523703892094e-1L:                // extended precision
+                                    maxPadeDegree<=10? 1.05026503471351080481093652651105e-1L:    // double-double
+                                                       1.1880960220216759245467951592883642e-1L;  // quadruple precision
+
+  while (true) {
+    RealScalar normTminusI = (T - MatrixType::Identity(T.rows(), T.rows())).cwiseAbs().colwise().sum().maxCoeff();
+    if (normTminusI < maxNormForPade) {
+      degree = matrix_log_get_pade_degree(normTminusI);
+      int degree2 = matrix_log_get_pade_degree(normTminusI / RealScalar(2));
+      if ((degree - degree2 <= 1) || (numberOfExtraSquareRoots == 1)) 
+        break;
+      ++numberOfExtraSquareRoots;
+    }
+    matrix_sqrt_triangular(T, sqrtT);
+    T = sqrtT.template triangularView<Upper>();
+    ++numberOfSquareRoots;
+  }
+
+  matrix_log_compute_pade(result, T, degree);
+  result *= pow(RealScalar(2), numberOfSquareRoots);
+}
+
+/** \ingroup MatrixFunctions_Module
+  * \class MatrixLogarithmAtomic
+  * \brief Helper class for computing matrix logarithm of atomic matrices.
+  *
+  * Here, an atomic matrix is a triangular matrix whose diagonal entries are close to each other.
+  *
+  * \sa class MatrixFunctionAtomic, MatrixBase::log()
+  */
+template <typename MatrixType>
+class MatrixLogarithmAtomic
+{
+public:
+  /** \brief Compute matrix logarithm of atomic matrix
+    * \param[in]  A  argument of matrix logarithm, should be upper triangular and atomic
+    * \returns  The logarithm of \p A.
+    */
+  MatrixType compute(const MatrixType& A);
+};
+
+template <typename MatrixType>
+MatrixType MatrixLogarithmAtomic<MatrixType>::compute(const MatrixType& A)
+{
+  using std::log;
+  MatrixType result(A.rows(), A.rows());
+  if (A.rows() == 1)
+    result(0,0) = log(A(0,0));
+  else if (A.rows() == 2)
+    matrix_log_compute_2x2(A, result);
+  else
+    matrix_log_compute_big(A, result);
+  return result;
+}
+
+} // end of namespace internal
 
 /** \ingroup MatrixFunctions_Module
   *
   * \brief Proxy for the matrix logarithm of some matrix (expression).
   *
@@ -419,49 +306,49 @@
   */
 template<typename Derived> class MatrixLogarithmReturnValue
 : public ReturnByValue<MatrixLogarithmReturnValue<Derived> >
 {
 public:
-
   typedef typename Derived::Scalar Scalar;
   typedef typename Derived::Index Index;
+
+protected:
+  typedef typename internal::ref_selector<Derived>::type DerivedNested;
+
+public:
 
   /** \brief Constructor.
     *
     * \param[in]  A  %Matrix (expression) forming the argument of the matrix logarithm.
     */
-  MatrixLogarithmReturnValue(const Derived& A) : m_A(A) { }
+  explicit MatrixLogarithmReturnValue(const Derived& A) : m_A(A) { }
   
   /** \brief Compute the matrix logarithm.
     *
     * \param[out]  result  Logarithm of \p A, where \A is as specified in the constructor.
     */
   template <typename ResultType>
   inline void evalTo(ResultType& result) const
   {
-    typedef typename Derived::PlainObject PlainObject;
-    typedef internal::traits<PlainObject> Traits;
+    typedef typename internal::nested_eval<Derived, 10>::type DerivedEvalType;
+    typedef typename internal::remove_all<DerivedEvalType>::type DerivedEvalTypeClean;
+    typedef internal::traits<DerivedEvalTypeClean> Traits;
     static const int RowsAtCompileTime = Traits::RowsAtCompileTime;
     static const int ColsAtCompileTime = Traits::ColsAtCompileTime;
-    static const int Options = PlainObject::Options;
     typedef std::complex<typename NumTraits<Scalar>::Real> ComplexScalar;
-    typedef Matrix<ComplexScalar, Dynamic, Dynamic, Options, RowsAtCompileTime, ColsAtCompileTime> DynMatrixType;
-    typedef MatrixLogarithmAtomic<DynMatrixType> AtomicType;
+    typedef Matrix<ComplexScalar, Dynamic, Dynamic, 0, RowsAtCompileTime, ColsAtCompileTime> DynMatrixType;
+    typedef internal::MatrixLogarithmAtomic<DynMatrixType> AtomicType;
     AtomicType atomic;
     
-    const PlainObject Aevaluated = m_A.eval();
-    MatrixFunction<PlainObject, AtomicType> mf(Aevaluated, atomic);
-    mf.compute(result);
+    internal::matrix_function_compute<typename DerivedEvalTypeClean::PlainObject>::run(m_A, atomic, result);
   }
 
   Index rows() const { return m_A.rows(); }
   Index cols() const { return m_A.cols(); }
   
 private:
-  typename internal::nested<Derived>::type m_A;
-  
-  MatrixLogarithmReturnValue& operator=(const MatrixLogarithmReturnValue&);
+  const DerivedNested m_A;
 };
 
 namespace internal {
   template<typename Derived>
   struct traits<MatrixLogarithmReturnValue<Derived> >

Index: 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h
+++ 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h
@@ -12,20 +12,52 @@
 
 namespace Eigen {
 
 template<typename MatrixType> class MatrixPower;
 
+/**
+ * \ingroup MatrixFunctions_Module
+ *
+ * \brief Proxy for the matrix power of some matrix.
+ *
+ * \tparam MatrixType  type of the base, a matrix.
+ *
+ * This class holds the arguments to the matrix power until it is
+ * assigned or evaluated for some other reason (so the argument
+ * should not be changed in the meantime). It is the return type of
+ * MatrixPower::operator() and related functions and most of the
+ * time this is the only way it is used.
+ */
+/* TODO This class is only used by MatrixPower, so it should be nested
+ * into MatrixPower, like MatrixPower::ReturnValue. However, my
+ * compiler complained about unused template parameter in the
+ * following declaration in namespace internal.
+ *
+ * template<typename MatrixType>
+ * struct traits<MatrixPower<MatrixType>::ReturnValue>;
+ */
 template<typename MatrixType>
-class MatrixPowerRetval : public ReturnByValue< MatrixPowerRetval<MatrixType> >
+class MatrixPowerParenthesesReturnValue : public ReturnByValue< MatrixPowerParenthesesReturnValue<MatrixType> >
 {
   public:
     typedef typename MatrixType::RealScalar RealScalar;
     typedef typename MatrixType::Index Index;
 
-    MatrixPowerRetval(MatrixPower<MatrixType>& pow, RealScalar p) : m_pow(pow), m_p(p)
+    /**
+     * \brief Constructor.
+     *
+     * \param[in] pow  %MatrixPower storing the base.
+     * \param[in] p    scalar, the exponent of the matrix power.
+     */
+    MatrixPowerParenthesesReturnValue(MatrixPower<MatrixType>& pow, RealScalar p) : m_pow(pow), m_p(p)
     { }
 
+    /**
+     * \brief Compute the matrix power.
+     *
+     * \param[out] result
+     */
     template<typename ResultType>
     inline void evalTo(ResultType& res) const
     { m_pow.compute(res, m_p); }
 
     Index rows() const { return m_pow.rows(); }
@@ -32,15 +64,29 @@
     Index cols() const { return m_pow.cols(); }
 
   private:
     MatrixPower<MatrixType>& m_pow;
     const RealScalar m_p;
-    MatrixPowerRetval& operator=(const MatrixPowerRetval&);
 };
 
+/**
+ * \ingroup MatrixFunctions_Module
+ *
+ * \brief Class for computing matrix powers.
+ *
+ * \tparam MatrixType  type of the base, expected to be an instantiation
+ * of the Matrix class template.
+ *
+ * This class is capable of computing triangular real/complex matrices
+ * raised to a power in the interval \f$ (-1, 1) \f$.
+ *
+ * \note Currently this class is only used by MatrixPower. One may
+ * insist that this be nested into MatrixPower. This class is here to
+ * faciliate future development of triangular matrix functions.
+ */
 template<typename MatrixType>
-class MatrixPowerAtomic
+class MatrixPowerAtomic : internal::noncopyable
 {
   private:
     enum {
       RowsAtCompileTime = MatrixType::RowsAtCompileTime,
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime
@@ -47,43 +93,64 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
     typedef std::complex<RealScalar> ComplexScalar;
     typedef typename MatrixType::Index Index;
-    typedef Array<Scalar, RowsAtCompileTime, 1, ColMajor, MaxRowsAtCompileTime> ArrayType;
+    typedef Block<MatrixType,Dynamic,Dynamic> ResultType;
 
     const MatrixType& m_A;
     RealScalar m_p;
 
-    void computePade(int degree, const MatrixType& IminusT, MatrixType& res) const;
-    void compute2x2(MatrixType& res, RealScalar p) const;
-    void computeBig(MatrixType& res) const;
+    void computePade(int degree, const MatrixType& IminusT, ResultType& res) const;
+    void compute2x2(ResultType& res, RealScalar p) const;
+    void computeBig(ResultType& res) const;
     static int getPadeDegree(float normIminusT);
     static int getPadeDegree(double normIminusT);
     static int getPadeDegree(long double normIminusT);
     static ComplexScalar computeSuperDiag(const ComplexScalar&, const ComplexScalar&, RealScalar p);
     static RealScalar computeSuperDiag(RealScalar, RealScalar, RealScalar p);
 
   public:
+    /**
+     * \brief Constructor.
+     *
+     * \param[in] T  the base of the matrix power.
+     * \param[in] p  the exponent of the matrix power, should be in
+     * \f$ (-1, 1) \f$.
+     *
+     * The class stores a reference to T, so it should not be changed
+     * (or destroyed) before evaluation. Only the upper triangular
+     * part of T is read.
+     */
     MatrixPowerAtomic(const MatrixType& T, RealScalar p);
-    void compute(MatrixType& res) const;
+    
+    /**
+     * \brief Compute the matrix power.
+     *
+     * \param[out] res  \f$ A^p \f$ where A and p are specified in the
+     * constructor.
+     */
+    void compute(ResultType& res) const;
 };
 
 template<typename MatrixType>
 MatrixPowerAtomic<MatrixType>::MatrixPowerAtomic(const MatrixType& T, RealScalar p) :
   m_A(T), m_p(p)
-{ eigen_assert(T.rows() == T.cols()); }
+{
+  eigen_assert(T.rows() == T.cols());
+  eigen_assert(p > -1 && p < 1);
+}
 
 template<typename MatrixType>
-void MatrixPowerAtomic<MatrixType>::compute(MatrixType& res) const
+void MatrixPowerAtomic<MatrixType>::compute(ResultType& res) const
 {
-  res.resizeLike(m_A);
+  using std::pow;
   switch (m_A.rows()) {
     case 0:
       break;
     case 1:
-      res(0,0) = std::pow(m_A(0,0), m_p);
+      res(0,0) = pow(m_A(0,0), m_p);
       break;
     case 2:
       compute2x2(res, m_p);
       break;
     default:
@@ -90,28 +157,28 @@
       computeBig(res);
   }
 }
 
 template<typename MatrixType>
-void MatrixPowerAtomic<MatrixType>::computePade(int degree, const MatrixType& IminusT, MatrixType& res) const
+void MatrixPowerAtomic<MatrixType>::computePade(int degree, const MatrixType& IminusT, ResultType& res) const
 {
-  int i = degree<<1;
-  res = (m_p-degree) / ((i-1)<<1) * IminusT;
+  int i = 2*degree;
+  res = (m_p-degree) / (2*i-2) * IminusT;
+
   for (--i; i; --i) {
     res = (MatrixType::Identity(IminusT.rows(), IminusT.cols()) + res).template triangularView<Upper>()
-	.solve((i==1 ? -m_p : i&1 ? (-m_p-(i>>1))/(i<<1) : (m_p-(i>>1))/((i-1)<<1)) * IminusT).eval();
+	.solve((i==1 ? -m_p : i&1 ? (-m_p-i/2)/(2*i) : (m_p-i/2)/(2*i-2)) * IminusT).eval();
   }
   res += MatrixType::Identity(IminusT.rows(), IminusT.cols());
 }
 
 // This function assumes that res has the correct size (see bug 614)
 template<typename MatrixType>
-void MatrixPowerAtomic<MatrixType>::compute2x2(MatrixType& res, RealScalar p) const
+void MatrixPowerAtomic<MatrixType>::compute2x2(ResultType& res, RealScalar p) const
 {
   using std::abs;
   using std::pow;
-  
   res.coeffRef(0,0) = pow(m_A.coeff(0,0), p);
 
   for (Index i=1; i < m_A.cols(); ++i) {
     res.coeffRef(i,i) = pow(m_A.coeff(i,i), p);
     if (m_A.coeff(i-1,i-1) == m_A.coeff(i,i))
@@ -123,36 +190,24 @@
     res.coeffRef(i-1,i) *= m_A.coeff(i-1,i);
   }
 }
 
 template<typename MatrixType>
-void MatrixPowerAtomic<MatrixType>::computeBig(MatrixType& res) const
+void MatrixPowerAtomic<MatrixType>::computeBig(ResultType& res) const
 {
+  using std::ldexp;
   const int digits = std::numeric_limits<RealScalar>::digits;
-  const RealScalar maxNormForPade = digits <=  24? 4.3386528e-1f:                           // sigle precision
-				    digits <=  53? 2.789358995219730e-1:                    // double precision
-				    digits <=  64? 2.4471944416607995472e-1L:               // extended precision
-				    digits <= 106? 1.1016843812851143391275867258512e-1L:   // double-double
-						   9.134603732914548552537150753385375e-2L; // quadruple precision
+  const RealScalar maxNormForPade = digits <=  24? 4.3386528e-1L                            // single precision
+                                  : digits <=  53? 2.789358995219730e-1L                    // double precision
+                                  : digits <=  64? 2.4471944416607995472e-1L                // extended precision
+                                  : digits <= 106? 1.1016843812851143391275867258512e-1L    // double-double
+                                  :                9.134603732914548552537150753385375e-2L; // quadruple precision
   MatrixType IminusT, sqrtT, T = m_A.template triangularView<Upper>();
   RealScalar normIminusT;
   int degree, degree2, numberOfSquareRoots = 0;
   bool hasExtraSquareRoot = false;
 
-  /* FIXME
-   * For singular T, norm(I - T) >= 1 but maxNormForPade < 1, leads to infinite
-   * loop.  We should move 0 eigenvalues to bottom right corner.  We need not
-   * worry about tiny values (e.g. 1e-300) because they will reach 1 if
-   * repetitively sqrt'ed.
-   *
-   * If the 0 eigenvalues are semisimple, they can form a 0 matrix at the
-   * bottom right corner.
-   *
-   * [ T  A ]^p   [ T^p  (T^-1 T^p A) ]
-   * [      ]   = [                   ]
-   * [ 0  0 ]     [  0         0      ]
-   */
   for (Index i=0; i < m_A.cols(); ++i)
     eigen_assert(m_A(i,i) != RealScalar(0));
 
   while (true) {
     IminusT = MatrixType::Identity(m_A.rows(), m_A.cols()) - T;
@@ -162,18 +217,18 @@
       degree2 = getPadeDegree(normIminusT/2);
       if (degree - degree2 <= 1 || hasExtraSquareRoot)
 	break;
       hasExtraSquareRoot = true;
     }
-    MatrixSquareRootTriangular<MatrixType>(T).compute(sqrtT);
+    matrix_sqrt_triangular(T, sqrtT);
     T = sqrtT.template triangularView<Upper>();
     ++numberOfSquareRoots;
   }
   computePade(degree, IminusT, res);
 
   for (; numberOfSquareRoots; --numberOfSquareRoots) {
-    compute2x2(res, std::ldexp(m_p, -numberOfSquareRoots));
+    compute2x2(res, ldexp(m_p, -numberOfSquareRoots));
     res = res.template triangularView<Upper>() * res;
   }
   compute2x2(res, m_p);
 }
   
@@ -207,11 +262,11 @@
   const int maxPadeDegree = 7;
   const double maxNormForPade[] = { 1.884160592658218e-2L /* degree = 3 */ , 6.038881904059573e-2L, 1.239917516308172e-1L,
       1.999045567181744e-1L, 2.789358995219730e-1L };
 #elif LDBL_MANT_DIG <= 64
   const int maxPadeDegree = 8;
-  const double maxNormForPade[] = { 6.3854693117491799460e-3L /* degree = 3 */ , 2.6394893435456973676e-2L,
+  const long double maxNormForPade[] = { 6.3854693117491799460e-3L /* degree = 3 */ , 2.6394893435456973676e-2L,
       6.4216043030404063729e-2L, 1.1701165502926694307e-1L, 1.7904284231268670284e-1L, 2.4471944416607995472e-1L };
 #elif LDBL_MANT_DIG <= 106
   const int maxPadeDegree = 10;
   const double maxNormForPade[] = { 1.0007161601787493236741409687186e-4L /* degree = 3 */ ,
       1.0007161601787493236741409687186e-3L, 4.7069769360887572939882574746264e-3L, 1.3220386624169159689406653101695e-2L,
@@ -234,23 +289,32 @@
 
 template<typename MatrixType>
 inline typename MatrixPowerAtomic<MatrixType>::ComplexScalar
 MatrixPowerAtomic<MatrixType>::computeSuperDiag(const ComplexScalar& curr, const ComplexScalar& prev, RealScalar p)
 {
-  ComplexScalar logCurr = std::log(curr);
-  ComplexScalar logPrev = std::log(prev);
-  int unwindingNumber = std::ceil((numext::imag(logCurr - logPrev) - M_PI) / (2*M_PI));
-  ComplexScalar w = numext::atanh2(curr - prev, curr + prev) + ComplexScalar(0, M_PI*unwindingNumber);
-  return RealScalar(2) * std::exp(RealScalar(0.5) * p * (logCurr + logPrev)) * std::sinh(p * w) / (curr - prev);
+  using std::ceil;
+  using std::exp;
+  using std::log;
+  using std::sinh;
+
+  ComplexScalar logCurr = log(curr);
+  ComplexScalar logPrev = log(prev);
+  int unwindingNumber = ceil((numext::imag(logCurr - logPrev) - RealScalar(EIGEN_PI)) / RealScalar(2*EIGEN_PI));
+  ComplexScalar w = numext::log1p((curr-prev)/prev)/RealScalar(2) + ComplexScalar(0, EIGEN_PI*unwindingNumber);
+  return RealScalar(2) * exp(RealScalar(0.5) * p * (logCurr + logPrev)) * sinh(p * w) / (curr - prev);
 }
 
 template<typename MatrixType>
 inline typename MatrixPowerAtomic<MatrixType>::RealScalar
 MatrixPowerAtomic<MatrixType>::computeSuperDiag(RealScalar curr, RealScalar prev, RealScalar p)
 {
-  RealScalar w = numext::atanh2(curr - prev, curr + prev);
-  return 2 * std::exp(p * (std::log(curr) + std::log(prev)) / 2) * std::sinh(p * w) / (curr - prev);
+  using std::exp;
+  using std::log;
+  using std::sinh;
+
+  RealScalar w = numext::log1p((curr-prev)/prev)/RealScalar(2);
+  return 2 * exp(p * (log(curr) + log(prev)) / 2) * sinh(p * w) / (curr - prev);
 }
 
 /**
  * \ingroup MatrixFunctions_Module
  *
@@ -269,19 +333,13 @@
  * Example:
  * \include MatrixPower_optimal.cpp
  * Output: \verbinclude MatrixPower_optimal.out
  */
 template<typename MatrixType>
-class MatrixPower
+class MatrixPower : internal::noncopyable
 {
   private:
-    enum {
-      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
-    };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
     typedef typename MatrixType::Index Index;
 
   public:
@@ -291,22 +349,26 @@
      * \param[in] A  the base of the matrix power.
      *
      * The class stores a reference to A, so it should not be changed
      * (or destroyed) before evaluation.
      */
-    explicit MatrixPower(const MatrixType& A) : m_A(A), m_conditionNumber(0)
+    explicit MatrixPower(const MatrixType& A) :
+      m_A(A),
+      m_conditionNumber(0),
+      m_rank(A.cols()),
+      m_nulls(0)
     { eigen_assert(A.rows() == A.cols()); }
 
     /**
      * \brief Returns the matrix power.
      *
      * \param[in] p  exponent, a real scalar.
      * \return The expression \f$ A^p \f$, where A is specified in the
      * constructor.
      */
-    const MatrixPowerRetval<MatrixType> operator()(RealScalar p)
-    { return MatrixPowerRetval<MatrixType>(*this, p); }
+    const MatrixPowerParenthesesReturnValue<MatrixType> operator()(RealScalar p)
+    { return MatrixPowerParenthesesReturnValue<MatrixType>(*this, p); }
 
     /**
      * \brief Compute the matrix power.
      *
      * \param[in]  p    exponent, a real scalar.
@@ -319,25 +381,58 @@
     Index rows() const { return m_A.rows(); }
     Index cols() const { return m_A.cols(); }
 
   private:
     typedef std::complex<RealScalar> ComplexScalar;
-    typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, MatrixType::Options,
-              MaxRowsAtCompileTime, MaxColsAtCompileTime> ComplexMatrix;
+    typedef Matrix<ComplexScalar, Dynamic, Dynamic, 0,
+              MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> ComplexMatrix;
 
+    /** \brief Reference to the base of matrix power. */
     typename MatrixType::Nested m_A;
+
+    /** \brief Temporary storage. */
     MatrixType m_tmp;
-    ComplexMatrix m_T, m_U, m_fT;
+
+    /** \brief Store the result of Schur decomposition. */
+    ComplexMatrix m_T, m_U;
+    
+    /** \brief Store fractional power of m_T. */
+    ComplexMatrix m_fT;
+
+    /**
+     * \brief Condition number of m_A.
+     *
+     * It is initialized as 0 to avoid performing unnecessary Schur
+     * decomposition, which is the bottleneck.
+     */
     RealScalar m_conditionNumber;
 
-    RealScalar modfAndInit(RealScalar, RealScalar*);
+    /** \brief Rank of m_A. */
+    Index m_rank;
+    
+    /** \brief Rank deficiency of m_A. */
+    Index m_nulls;
+
+    /**
+     * \brief Split p into integral part and fractional part.
+     *
+     * \param[in]  p        The exponent.
+     * \param[out] p        The fractional part ranging in \f$ (-1, 1) \f$.
+     * \param[out] intpart  The integral part.
+     *
+     * Only if the fractional part is nonzero, it calls initialize().
+     */
+    void split(RealScalar& p, RealScalar& intpart);
+
+    /** \brief Perform Schur decomposition for fractional power. */
+    void initialize();
 
     template<typename ResultType>
-    void computeIntPower(ResultType&, RealScalar);
+    void computeIntPower(ResultType& res, RealScalar p);
 
     template<typename ResultType>
-    void computeFracPower(ResultType&, RealScalar);
+    void computeFracPower(ResultType& res, RealScalar p);
 
     template<int Rows, int Cols, int Options, int MaxRows, int MaxCols>
     static void revertSchur(
         Matrix<ComplexScalar, Rows, Cols, Options, MaxRows, MaxCols>& res,
         const ComplexMatrix& T,
@@ -352,76 +447,124 @@
 
 template<typename MatrixType>
 template<typename ResultType>
 void MatrixPower<MatrixType>::compute(ResultType& res, RealScalar p)
 {
+  using std::pow;
   switch (cols()) {
     case 0:
       break;
     case 1:
-      res(0,0) = std::pow(m_A.coeff(0,0), p);
+      res(0,0) = pow(m_A.coeff(0,0), p);
       break;
     default:
-      RealScalar intpart, x = modfAndInit(p, &intpart);
+      RealScalar intpart;
+      split(p, intpart);
+
+      res = MatrixType::Identity(rows(), cols());
       computeIntPower(res, intpart);
-      computeFracPower(res, x);
+      if (p) computeFracPower(res, p);
+  }
+}
+
+template<typename MatrixType>
+void MatrixPower<MatrixType>::split(RealScalar& p, RealScalar& intpart)
+{
+  using std::floor;
+  using std::pow;
+
+  intpart = floor(p);
+  p -= intpart;
+
+  // Perform Schur decomposition if it is not yet performed and the power is
+  // not an integer.
+  if (!m_conditionNumber && p)
+    initialize();
+
+  // Choose the more stable of intpart = floor(p) and intpart = ceil(p).
+  if (p > RealScalar(0.5) && p > (1-p) * pow(m_conditionNumber, p)) {
+    --p;
+    ++intpart;
   }
 }
 
 template<typename MatrixType>
-typename MatrixPower<MatrixType>::RealScalar
-MatrixPower<MatrixType>::modfAndInit(RealScalar x, RealScalar* intpart)
-{
-  typedef Array<RealScalar, RowsAtCompileTime, 1, ColMajor, MaxRowsAtCompileTime> RealArray;
-
-  *intpart = std::floor(x);
-  RealScalar res = x - *intpart;
-
-  if (!m_conditionNumber && res) {
-    const ComplexSchur<MatrixType> schurOfA(m_A);
-    m_T = schurOfA.matrixT();
-    m_U = schurOfA.matrixU();
-    
-    const RealArray absTdiag = m_T.diagonal().array().abs();
-    m_conditionNumber = absTdiag.maxCoeff() / absTdiag.minCoeff();
-  }
-
-  if (res>RealScalar(0.5) && res>(1-res)*std::pow(m_conditionNumber, res)) {
-    --res;
-    ++*intpart;
-  }
-  return res;
+void MatrixPower<MatrixType>::initialize()
+{
+  const ComplexSchur<MatrixType> schurOfA(m_A);
+  JacobiRotation<ComplexScalar> rot;
+  ComplexScalar eigenvalue;
+
+  m_fT.resizeLike(m_A);
+  m_T = schurOfA.matrixT();
+  m_U = schurOfA.matrixU();
+  m_conditionNumber = m_T.diagonal().array().abs().maxCoeff() / m_T.diagonal().array().abs().minCoeff();
+
+  // Move zero eigenvalues to the bottom right corner.
+  for (Index i = cols()-1; i>=0; --i) {
+    if (m_rank <= 2)
+      return;
+    if (m_T.coeff(i,i) == RealScalar(0)) {
+      for (Index j=i+1; j < m_rank; ++j) {
+        eigenvalue = m_T.coeff(j,j);
+        rot.makeGivens(m_T.coeff(j-1,j), eigenvalue);
+        m_T.applyOnTheRight(j-1, j, rot);
+        m_T.applyOnTheLeft(j-1, j, rot.adjoint());
+        m_T.coeffRef(j-1,j-1) = eigenvalue;
+        m_T.coeffRef(j,j) = RealScalar(0);
+        m_U.applyOnTheRight(j-1, j, rot);
+      }
+      --m_rank;
+    }
+  }
+
+  m_nulls = rows() - m_rank;
+  if (m_nulls) {
+    eigen_assert(m_T.bottomRightCorner(m_nulls, m_nulls).isZero()
+        && "Base of matrix power should be invertible or with a semisimple zero eigenvalue.");
+    m_fT.bottomRows(m_nulls).fill(RealScalar(0));
+  }
 }
 
 template<typename MatrixType>
 template<typename ResultType>
 void MatrixPower<MatrixType>::computeIntPower(ResultType& res, RealScalar p)
 {
-  RealScalar pp = std::abs(p);
-
-  if (p<0)  m_tmp = m_A.inverse();
-  else      m_tmp = m_A;
-
-  res = MatrixType::Identity(rows(), cols());
-  while (pp >= 1) {
-    if (std::fmod(pp, 2) >= 1)
+  using std::abs;
+  using std::fmod;
+  RealScalar pp = abs(p);
+
+  if (p<0) 
+    m_tmp = m_A.inverse();
+  else     
+    m_tmp = m_A;
+
+  while (true) {
+    if (fmod(pp, 2) >= 1)
       res = m_tmp * res;
-    m_tmp *= m_tmp;
     pp /= 2;
+    if (pp < 1)
+      break;
+    m_tmp *= m_tmp;
   }
 }
 
 template<typename MatrixType>
 template<typename ResultType>
 void MatrixPower<MatrixType>::computeFracPower(ResultType& res, RealScalar p)
 {
-  if (p) {
-    eigen_assert(m_conditionNumber);
-    MatrixPowerAtomic<ComplexMatrix>(m_T, p).compute(m_fT);
-    revertSchur(m_tmp, m_fT, m_U);
-    res = m_tmp * res;
+  Block<ComplexMatrix,Dynamic,Dynamic> blockTp(m_fT, 0, 0, m_rank, m_rank);
+  eigen_assert(m_conditionNumber);
+  eigen_assert(m_rank + m_nulls == rows());
+
+  MatrixPowerAtomic<ComplexMatrix>(m_T.topLeftCorner(m_rank, m_rank), p).compute(blockTp);
+  if (m_nulls) {
+    m_fT.topRightCorner(m_rank, m_nulls) = m_T.topLeftCorner(m_rank, m_rank).template triangularView<Upper>()
+        .solve(blockTp * m_T.topRightCorner(m_rank, m_nulls));
   }
+  revertSchur(m_tmp, m_fT, m_U);
+  res = m_tmp * res;
 }
 
 template<typename MatrixType>
 template<int Rows, int Cols, int Options, int MaxRows, int MaxCols>
 inline void MatrixPower<MatrixType>::revertSchur(
@@ -461,11 +604,11 @@
 
     /**
      * \brief Constructor.
      *
      * \param[in] A  %Matrix (expression), the base of the matrix power.
-     * \param[in] p  scalar, the exponent of the matrix power.
+     * \param[in] p  real scalar, the exponent of the matrix power.
      */
     MatrixPowerReturnValue(const Derived& A, RealScalar p) : m_A(A), m_p(p)
     { }
 
     /**
@@ -482,27 +625,85 @@
     Index cols() const { return m_A.cols(); }
 
   private:
     const Derived& m_A;
     const RealScalar m_p;
-    MatrixPowerReturnValue& operator=(const MatrixPowerReturnValue&);
+};
+
+/**
+ * \ingroup MatrixFunctions_Module
+ *
+ * \brief Proxy for the matrix power of some matrix (expression).
+ *
+ * \tparam Derived  type of the base, a matrix (expression).
+ *
+ * This class holds the arguments to the matrix power until it is
+ * assigned or evaluated for some other reason (so the argument
+ * should not be changed in the meantime). It is the return type of
+ * MatrixBase::pow() and related functions and most of the
+ * time this is the only way it is used.
+ */
+template<typename Derived>
+class MatrixComplexPowerReturnValue : public ReturnByValue< MatrixComplexPowerReturnValue<Derived> >
+{
+  public:
+    typedef typename Derived::PlainObject PlainObject;
+    typedef typename std::complex<typename Derived::RealScalar> ComplexScalar;
+    typedef typename Derived::Index Index;
+
+    /**
+     * \brief Constructor.
+     *
+     * \param[in] A  %Matrix (expression), the base of the matrix power.
+     * \param[in] p  complex scalar, the exponent of the matrix power.
+     */
+    MatrixComplexPowerReturnValue(const Derived& A, const ComplexScalar& p) : m_A(A), m_p(p)
+    { }
+
+    /**
+     * \brief Compute the matrix power.
+     *
+     * Because \p p is complex, \f$ A^p \f$ is simply evaluated as \f$
+     * \exp(p \log(A)) \f$.
+     *
+     * \param[out] result  \f$ A^p \f$ where \p A and \p p are as in the
+     * constructor.
+     */
+    template<typename ResultType>
+    inline void evalTo(ResultType& res) const
+    { res = (m_p * m_A.log()).exp(); }
+
+    Index rows() const { return m_A.rows(); }
+    Index cols() const { return m_A.cols(); }
+
+  private:
+    const Derived& m_A;
+    const ComplexScalar m_p;
 };
 
 namespace internal {
 
 template<typename MatrixPowerType>
-struct traits< MatrixPowerRetval<MatrixPowerType> >
+struct traits< MatrixPowerParenthesesReturnValue<MatrixPowerType> >
 { typedef typename MatrixPowerType::PlainObject ReturnType; };
 
 template<typename Derived>
 struct traits< MatrixPowerReturnValue<Derived> >
 { typedef typename Derived::PlainObject ReturnType; };
 
+template<typename Derived>
+struct traits< MatrixComplexPowerReturnValue<Derived> >
+{ typedef typename Derived::PlainObject ReturnType; };
+
 }
 
 template<typename Derived>
 const MatrixPowerReturnValue<Derived> MatrixBase<Derived>::pow(const RealScalar& p) const
 { return MatrixPowerReturnValue<Derived>(derived(), p); }
 
+template<typename Derived>
+const MatrixComplexPowerReturnValue<Derived> MatrixBase<Derived>::pow(const std::complex<RealScalar>& p) const
+{ return MatrixComplexPowerReturnValue<Derived>(derived(), p); }
+
 } // namespace Eigen
 
 #endif // EIGEN_MATRIX_POWER

Index: 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h
+++ 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2011, 2013 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -10,209 +10,68 @@
 #ifndef EIGEN_MATRIX_SQUARE_ROOT
 #define EIGEN_MATRIX_SQUARE_ROOT
 
 namespace Eigen { 
 
-/** \ingroup MatrixFunctions_Module
-  * \brief Class for computing matrix square roots of upper quasi-triangular matrices.
-  * \tparam  MatrixType  type of the argument of the matrix square root,
-  *                      expected to be an instantiation of the Matrix class template.
-  *
-  * This class computes the square root of the upper quasi-triangular
-  * matrix stored in the upper Hessenberg part of the matrix passed to
-  * the constructor.
-  *
-  * \sa MatrixSquareRoot, MatrixSquareRootTriangular
-  */
-template <typename MatrixType>
-class MatrixSquareRootQuasiTriangular
-{
-  public:
-
-    /** \brief Constructor. 
-      *
-      * \param[in]  A  upper quasi-triangular matrix whose square root 
-      *                is to be computed.
-      *
-      * The class stores a reference to \p A, so it should not be
-      * changed (or destroyed) before compute() is called.
-      */
-    MatrixSquareRootQuasiTriangular(const MatrixType& A) 
-      : m_A(A) 
-    {
-      eigen_assert(A.rows() == A.cols());
-    }
-    
-    /** \brief Compute the matrix square root
-      *
-      * \param[out] result  square root of \p A, as specified in the constructor.
-      *
-      * Only the upper Hessenberg part of \p result is updated, the
-      * rest is not touched.  See MatrixBase::sqrt() for details on
-      * how this computation is implemented.
-      */
-    template <typename ResultType> void compute(ResultType &result);    
-    
-  private:
-    typedef typename MatrixType::Index Index;
-    typedef typename MatrixType::Scalar Scalar;
-    
-    void computeDiagonalPartOfSqrt(MatrixType& sqrtT, const MatrixType& T);
-    void computeOffDiagonalPartOfSqrt(MatrixType& sqrtT, const MatrixType& T);
-    void compute2x2diagonalBlock(MatrixType& sqrtT, const MatrixType& T, typename MatrixType::Index i);
-    void compute1x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, 
-				  typename MatrixType::Index i, typename MatrixType::Index j);
-    void compute1x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, 
-				  typename MatrixType::Index i, typename MatrixType::Index j);
-    void compute2x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, 
-				  typename MatrixType::Index i, typename MatrixType::Index j);
-    void compute2x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, 
-				  typename MatrixType::Index i, typename MatrixType::Index j);
-  
-    template <typename SmallMatrixType>
-    static void solveAuxiliaryEquation(SmallMatrixType& X, const SmallMatrixType& A, 
-				     const SmallMatrixType& B, const SmallMatrixType& C);
-  
-    const MatrixType& m_A;
-};
-
-template <typename MatrixType>
-template <typename ResultType> 
-void MatrixSquareRootQuasiTriangular<MatrixType>::compute(ResultType &result)
-{
-  result.resize(m_A.rows(), m_A.cols());
-  computeDiagonalPartOfSqrt(result, m_A);
-  computeOffDiagonalPartOfSqrt(result, m_A);
-}
-
-// pre:  T is quasi-upper-triangular and sqrtT is a zero matrix of the same size
-// post: the diagonal blocks of sqrtT are the square roots of the diagonal blocks of T
-template <typename MatrixType>
-void MatrixSquareRootQuasiTriangular<MatrixType>::computeDiagonalPartOfSqrt(MatrixType& sqrtT, 
-									  const MatrixType& T)
-{
-  using std::sqrt;
-  const Index size = m_A.rows();
-  for (Index i = 0; i < size; i++) {
-    if (i == size - 1 || T.coeff(i+1, i) == 0) {
-      eigen_assert(T(i,i) >= 0);
-      sqrtT.coeffRef(i,i) = sqrt(T.coeff(i,i));
-    }
-    else {
-      compute2x2diagonalBlock(sqrtT, T, i);
-      ++i;
-    }
-  }
-}
-
-// pre:  T is quasi-upper-triangular and diagonal blocks of sqrtT are square root of diagonal blocks of T.
-// post: sqrtT is the square root of T.
-template <typename MatrixType>
-void MatrixSquareRootQuasiTriangular<MatrixType>::computeOffDiagonalPartOfSqrt(MatrixType& sqrtT, 
-									     const MatrixType& T)
-{
-  const Index size = m_A.rows();
-  for (Index j = 1; j < size; j++) {
-      if (T.coeff(j, j-1) != 0)  // if T(j-1:j, j-1:j) is a 2-by-2 block
-	continue;
-    for (Index i = j-1; i >= 0; i--) {
-      if (i > 0 && T.coeff(i, i-1) != 0)  // if T(i-1:i, i-1:i) is a 2-by-2 block
-	continue;
-      bool iBlockIs2x2 = (i < size - 1) && (T.coeff(i+1, i) != 0);
-      bool jBlockIs2x2 = (j < size - 1) && (T.coeff(j+1, j) != 0);
-      if (iBlockIs2x2 && jBlockIs2x2) 
-	compute2x2offDiagonalBlock(sqrtT, T, i, j);
-      else if (iBlockIs2x2 && !jBlockIs2x2) 
-	compute2x1offDiagonalBlock(sqrtT, T, i, j);
-      else if (!iBlockIs2x2 && jBlockIs2x2) 
-	compute1x2offDiagonalBlock(sqrtT, T, i, j);
-      else if (!iBlockIs2x2 && !jBlockIs2x2) 
-	compute1x1offDiagonalBlock(sqrtT, T, i, j);
-    }
-  }
-}
+namespace internal {
 
 // pre:  T.block(i,i,2,2) has complex conjugate eigenvalues
 // post: sqrtT.block(i,i,2,2) is square root of T.block(i,i,2,2)
-template <typename MatrixType>
-void MatrixSquareRootQuasiTriangular<MatrixType>
-     ::compute2x2diagonalBlock(MatrixType& sqrtT, const MatrixType& T, typename MatrixType::Index i)
+template <typename MatrixType, typename ResultType>
+void matrix_sqrt_quasi_triangular_2x2_diagonal_block(const MatrixType& T, typename MatrixType::Index i, ResultType& sqrtT)
 {
   // TODO: This case (2-by-2 blocks with complex conjugate eigenvalues) is probably hidden somewhere
   //       in EigenSolver. If we expose it, we could call it directly from here.
+  typedef typename traits<MatrixType>::Scalar Scalar;
   Matrix<Scalar,2,2> block = T.template block<2,2>(i,i);
   EigenSolver<Matrix<Scalar,2,2> > es(block);
   sqrtT.template block<2,2>(i,i)
     = (es.eigenvectors() * es.eigenvalues().cwiseSqrt().asDiagonal() * es.eigenvectors().inverse()).real();
 }
 
 // pre:  block structure of T is such that (i,j) is a 1x1 block,
 //       all blocks of sqrtT to left of and below (i,j) are correct
 // post: sqrtT(i,j) has the correct value
-template <typename MatrixType>
-void MatrixSquareRootQuasiTriangular<MatrixType>
-     ::compute1x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, 
-				  typename MatrixType::Index i, typename MatrixType::Index j)
+template <typename MatrixType, typename ResultType>
+void matrix_sqrt_quasi_triangular_1x1_off_diagonal_block(const MatrixType& T, typename MatrixType::Index i, typename MatrixType::Index j, ResultType& sqrtT)
 {
+  typedef typename traits<MatrixType>::Scalar Scalar;
   Scalar tmp = (sqrtT.row(i).segment(i+1,j-i-1) * sqrtT.col(j).segment(i+1,j-i-1)).value();
   sqrtT.coeffRef(i,j) = (T.coeff(i,j) - tmp) / (sqrtT.coeff(i,i) + sqrtT.coeff(j,j));
 }
 
 // similar to compute1x1offDiagonalBlock()
-template <typename MatrixType>
-void MatrixSquareRootQuasiTriangular<MatrixType>
-     ::compute1x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, 
-				  typename MatrixType::Index i, typename MatrixType::Index j)
+template <typename MatrixType, typename ResultType>
+void matrix_sqrt_quasi_triangular_1x2_off_diagonal_block(const MatrixType& T, typename MatrixType::Index i, typename MatrixType::Index j, ResultType& sqrtT)
 {
+  typedef typename traits<MatrixType>::Scalar Scalar;
   Matrix<Scalar,1,2> rhs = T.template block<1,2>(i,j);
   if (j-i > 1)
     rhs -= sqrtT.block(i, i+1, 1, j-i-1) * sqrtT.block(i+1, j, j-i-1, 2);
   Matrix<Scalar,2,2> A = sqrtT.coeff(i,i) * Matrix<Scalar,2,2>::Identity();
   A += sqrtT.template block<2,2>(j,j).transpose();
   sqrtT.template block<1,2>(i,j).transpose() = A.fullPivLu().solve(rhs.transpose());
 }
 
 // similar to compute1x1offDiagonalBlock()
-template <typename MatrixType>
-void MatrixSquareRootQuasiTriangular<MatrixType>
-     ::compute2x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, 
-				  typename MatrixType::Index i, typename MatrixType::Index j)
+template <typename MatrixType, typename ResultType>
+void matrix_sqrt_quasi_triangular_2x1_off_diagonal_block(const MatrixType& T, typename MatrixType::Index i, typename MatrixType::Index j, ResultType& sqrtT)
 {
+  typedef typename traits<MatrixType>::Scalar Scalar;
   Matrix<Scalar,2,1> rhs = T.template block<2,1>(i,j);
   if (j-i > 2)
     rhs -= sqrtT.block(i, i+2, 2, j-i-2) * sqrtT.block(i+2, j, j-i-2, 1);
   Matrix<Scalar,2,2> A = sqrtT.coeff(j,j) * Matrix<Scalar,2,2>::Identity();
   A += sqrtT.template block<2,2>(i,i);
   sqrtT.template block<2,1>(i,j) = A.fullPivLu().solve(rhs);
 }
 
-// similar to compute1x1offDiagonalBlock()
-template <typename MatrixType>
-void MatrixSquareRootQuasiTriangular<MatrixType>
-     ::compute2x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, 
-				  typename MatrixType::Index i, typename MatrixType::Index j)
-{
-  Matrix<Scalar,2,2> A = sqrtT.template block<2,2>(i,i);
-  Matrix<Scalar,2,2> B = sqrtT.template block<2,2>(j,j);
-  Matrix<Scalar,2,2> C = T.template block<2,2>(i,j);
-  if (j-i > 2)
-    C -= sqrtT.block(i, i+2, 2, j-i-2) * sqrtT.block(i+2, j, j-i-2, 2);
-  Matrix<Scalar,2,2> X;
-  solveAuxiliaryEquation(X, A, B, C);
-  sqrtT.template block<2,2>(i,j) = X;
-}
-
 // solves the equation A X + X B = C where all matrices are 2-by-2
 template <typename MatrixType>
-template <typename SmallMatrixType>
-void MatrixSquareRootQuasiTriangular<MatrixType>
-     ::solveAuxiliaryEquation(SmallMatrixType& X, const SmallMatrixType& A,
-			      const SmallMatrixType& B, const SmallMatrixType& C)
-{
-  EIGEN_STATIC_ASSERT((internal::is_same<SmallMatrixType, Matrix<Scalar,2,2> >::value),
-		      EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT);
-
+void matrix_sqrt_quasi_triangular_solve_auxiliary_equation(MatrixType& X, const MatrixType& A, const MatrixType& B, const MatrixType& C)
+{
+  typedef typename traits<MatrixType>::Scalar Scalar;
   Matrix<Scalar,4,4> coeffMatrix = Matrix<Scalar,4,4>::Zero();
   coeffMatrix.coeffRef(0,0) = A.coeff(0,0) + B.coeff(0,0);
   coeffMatrix.coeffRef(1,1) = A.coeff(0,0) + B.coeff(1,1);
   coeffMatrix.coeffRef(2,2) = A.coeff(1,1) + B.coeff(0,0);
   coeffMatrix.coeffRef(3,3) = A.coeff(1,1) + B.coeff(1,1);
@@ -222,185 +81,228 @@
   coeffMatrix.coeffRef(1,3) = A.coeff(0,1);
   coeffMatrix.coeffRef(2,0) = A.coeff(1,0);
   coeffMatrix.coeffRef(2,3) = B.coeff(1,0);
   coeffMatrix.coeffRef(3,1) = A.coeff(1,0);
   coeffMatrix.coeffRef(3,2) = B.coeff(0,1);
-  
+
   Matrix<Scalar,4,1> rhs;
   rhs.coeffRef(0) = C.coeff(0,0);
   rhs.coeffRef(1) = C.coeff(0,1);
   rhs.coeffRef(2) = C.coeff(1,0);
   rhs.coeffRef(3) = C.coeff(1,1);
-  
+
   Matrix<Scalar,4,1> result;
   result = coeffMatrix.fullPivLu().solve(rhs);
 
   X.coeffRef(0,0) = result.coeff(0);
   X.coeffRef(0,1) = result.coeff(1);
   X.coeffRef(1,0) = result.coeff(2);
   X.coeffRef(1,1) = result.coeff(3);
 }
 
-
-/** \ingroup MatrixFunctions_Module
-  * \brief Class for computing matrix square roots of upper triangular matrices.
-  * \tparam  MatrixType  type of the argument of the matrix square root,
-  *                      expected to be an instantiation of the Matrix class template.
-  *
-  * This class computes the square root of the upper triangular matrix
-  * stored in the upper triangular part (including the diagonal) of
-  * the matrix passed to the constructor.
-  *
-  * \sa MatrixSquareRoot, MatrixSquareRootQuasiTriangular
-  */
-template <typename MatrixType>
-class MatrixSquareRootTriangular
-{
-  public:
-    MatrixSquareRootTriangular(const MatrixType& A) 
-      : m_A(A) 
-    {
-      eigen_assert(A.rows() == A.cols());
-    }
-
-    /** \brief Compute the matrix square root
-      *
-      * \param[out] result  square root of \p A, as specified in the constructor.
-      *
-      * Only the upper triangular part (including the diagonal) of 
-      * \p result is updated, the rest is not touched.  See
-      * MatrixBase::sqrt() for details on how this computation is
-      * implemented.
-      */
-    template <typename ResultType> void compute(ResultType &result);    
-
- private:
-    const MatrixType& m_A;
-};
-
-template <typename MatrixType>
-template <typename ResultType> 
-void MatrixSquareRootTriangular<MatrixType>::compute(ResultType &result)
-{
-  using std::sqrt;
-
-  // Compute square root of m_A and store it in upper triangular part of result
-  // This uses that the square root of triangular matrices can be computed directly.
-  result.resize(m_A.rows(), m_A.cols());
-  typedef typename MatrixType::Index Index;
-  for (Index i = 0; i < m_A.rows(); i++) {
-    result.coeffRef(i,i) = sqrt(m_A.coeff(i,i));
-  }
-  for (Index j = 1; j < m_A.cols(); j++) {
-    for (Index i = j-1; i >= 0; i--) {
-      typedef typename MatrixType::Scalar Scalar;
-      // if i = j-1, then segment has length 0 so tmp = 0
-      Scalar tmp = (result.row(i).segment(i+1,j-i-1) * result.col(j).segment(i+1,j-i-1)).value();
-      // denominator may be zero if original matrix is singular
-      result.coeffRef(i,j) = (m_A.coeff(i,j) - tmp) / (result.coeff(i,i) + result.coeff(j,j));
-    }
-  }
-}
-
-
-/** \ingroup MatrixFunctions_Module
-  * \brief Class for computing matrix square roots of general matrices.
+// similar to compute1x1offDiagonalBlock()
+template <typename MatrixType, typename ResultType>
+void matrix_sqrt_quasi_triangular_2x2_off_diagonal_block(const MatrixType& T, typename MatrixType::Index i, typename MatrixType::Index j, ResultType& sqrtT)
+{
+  typedef typename traits<MatrixType>::Scalar Scalar;
+  Matrix<Scalar,2,2> A = sqrtT.template block<2,2>(i,i);
+  Matrix<Scalar,2,2> B = sqrtT.template block<2,2>(j,j);
+  Matrix<Scalar,2,2> C = T.template block<2,2>(i,j);
+  if (j-i > 2)
+    C -= sqrtT.block(i, i+2, 2, j-i-2) * sqrtT.block(i+2, j, j-i-2, 2);
+  Matrix<Scalar,2,2> X;
+  matrix_sqrt_quasi_triangular_solve_auxiliary_equation(X, A, B, C);
+  sqrtT.template block<2,2>(i,j) = X;
+}
+
+// pre:  T is quasi-upper-triangular and sqrtT is a zero matrix of the same size
+// post: the diagonal blocks of sqrtT are the square roots of the diagonal blocks of T
+template <typename MatrixType, typename ResultType>
+void matrix_sqrt_quasi_triangular_diagonal(const MatrixType& T, ResultType& sqrtT)
+{
+  using std::sqrt;
+  typedef typename MatrixType::Index Index;
+  const Index size = T.rows();
+  for (Index i = 0; i < size; i++) {
+    if (i == size - 1 || T.coeff(i+1, i) == 0) {
+      eigen_assert(T(i,i) >= 0);
+      sqrtT.coeffRef(i,i) = sqrt(T.coeff(i,i));
+    }
+    else {
+      matrix_sqrt_quasi_triangular_2x2_diagonal_block(T, i, sqrtT);
+      ++i;
+    }
+  }
+}
+
+// pre:  T is quasi-upper-triangular and diagonal blocks of sqrtT are square root of diagonal blocks of T.
+// post: sqrtT is the square root of T.
+template <typename MatrixType, typename ResultType>
+void matrix_sqrt_quasi_triangular_off_diagonal(const MatrixType& T, ResultType& sqrtT)
+{
+  typedef typename MatrixType::Index Index;
+  const Index size = T.rows();
+  for (Index j = 1; j < size; j++) {
+      if (T.coeff(j, j-1) != 0)  // if T(j-1:j, j-1:j) is a 2-by-2 block
+	continue;
+    for (Index i = j-1; i >= 0; i--) {
+      if (i > 0 && T.coeff(i, i-1) != 0)  // if T(i-1:i, i-1:i) is a 2-by-2 block
+	continue;
+      bool iBlockIs2x2 = (i < size - 1) && (T.coeff(i+1, i) != 0);
+      bool jBlockIs2x2 = (j < size - 1) && (T.coeff(j+1, j) != 0);
+      if (iBlockIs2x2 && jBlockIs2x2) 
+        matrix_sqrt_quasi_triangular_2x2_off_diagonal_block(T, i, j, sqrtT);
+      else if (iBlockIs2x2 && !jBlockIs2x2) 
+        matrix_sqrt_quasi_triangular_2x1_off_diagonal_block(T, i, j, sqrtT);
+      else if (!iBlockIs2x2 && jBlockIs2x2) 
+        matrix_sqrt_quasi_triangular_1x2_off_diagonal_block(T, i, j, sqrtT);
+      else if (!iBlockIs2x2 && !jBlockIs2x2) 
+        matrix_sqrt_quasi_triangular_1x1_off_diagonal_block(T, i, j, sqrtT);
+    }
+  }
+}
+
+} // end of namespace internal
+
+/** \ingroup MatrixFunctions_Module
+  * \brief Compute matrix square root of quasi-triangular matrix.
+  *
+  * \tparam  MatrixType  type of \p arg, the argument of matrix square root,
+  *                      expected to be an instantiation of the Matrix class template.
+  * \tparam  ResultType  type of \p result, where result is to be stored.
+  * \param[in]  arg      argument of matrix square root.
+  * \param[out] result   matrix square root of upper Hessenberg part of \p arg.
+  *
+  * This function computes the square root of the upper quasi-triangular matrix stored in the upper
+  * Hessenberg part of \p arg.  Only the upper Hessenberg part of \p result is updated, the rest is
+  * not touched.  See MatrixBase::sqrt() for details on how this computation is implemented.
+  *
+  * \sa MatrixSquareRoot, MatrixSquareRootQuasiTriangular
+  */
+template <typename MatrixType, typename ResultType> 
+void matrix_sqrt_quasi_triangular(const MatrixType &arg, ResultType &result)
+{
+  eigen_assert(arg.rows() == arg.cols());
+  result.resize(arg.rows(), arg.cols());
+  internal::matrix_sqrt_quasi_triangular_diagonal(arg, result);
+  internal::matrix_sqrt_quasi_triangular_off_diagonal(arg, result);
+}
+
+
+/** \ingroup MatrixFunctions_Module
+  * \brief Compute matrix square root of triangular matrix.
+  *
+  * \tparam  MatrixType  type of \p arg, the argument of matrix square root,
+  *                      expected to be an instantiation of the Matrix class template.
+  * \tparam  ResultType  type of \p result, where result is to be stored.
+  * \param[in]  arg      argument of matrix square root.
+  * \param[out] result   matrix square root of upper triangular part of \p arg.
+  *
+  * Only the upper triangular part (including the diagonal) of \p result is updated, the rest is not
+  * touched.  See MatrixBase::sqrt() for details on how this computation is implemented.
+  *
+  * \sa MatrixSquareRoot, MatrixSquareRootQuasiTriangular
+  */
+template <typename MatrixType, typename ResultType> 
+void matrix_sqrt_triangular(const MatrixType &arg, ResultType &result)
+{
+  using std::sqrt;
+  typedef typename MatrixType::Index Index;
+      typedef typename MatrixType::Scalar Scalar;
+
+  eigen_assert(arg.rows() == arg.cols());
+
+  // Compute square root of arg and store it in upper triangular part of result
+  // This uses that the square root of triangular matrices can be computed directly.
+  result.resize(arg.rows(), arg.cols());
+  for (Index i = 0; i < arg.rows(); i++) {
+    result.coeffRef(i,i) = sqrt(arg.coeff(i,i));
+  }
+  for (Index j = 1; j < arg.cols(); j++) {
+    for (Index i = j-1; i >= 0; i--) {
+      // if i = j-1, then segment has length 0 so tmp = 0
+      Scalar tmp = (result.row(i).segment(i+1,j-i-1) * result.col(j).segment(i+1,j-i-1)).value();
+      // denominator may be zero if original matrix is singular
+      result.coeffRef(i,j) = (arg.coeff(i,j) - tmp) / (result.coeff(i,i) + result.coeff(j,j));
+    }
+  }
+}
+
+
+namespace internal {
+
+/** \ingroup MatrixFunctions_Module
+  * \brief Helper struct for computing matrix square roots of general matrices.
   * \tparam  MatrixType  type of the argument of the matrix square root,
   *                      expected to be an instantiation of the Matrix class template.
   *
   * \sa MatrixSquareRootTriangular, MatrixSquareRootQuasiTriangular, MatrixBase::sqrt()
   */
 template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
-class MatrixSquareRoot
-{
-  public:
-
-    /** \brief Constructor. 
-      *
-      * \param[in]  A  matrix whose square root is to be computed.
-      *
-      * The class stores a reference to \p A, so it should not be
-      * changed (or destroyed) before compute() is called.
-      */
-    MatrixSquareRoot(const MatrixType& A); 
-    
-    /** \brief Compute the matrix square root
-      *
-      * \param[out] result  square root of \p A, as specified in the constructor.
-      *
-      * See MatrixBase::sqrt() for details on how this computation is
-      * implemented.
-      */
-    template <typename ResultType> void compute(ResultType &result);    
+struct matrix_sqrt_compute
+{
+  /** \brief Compute the matrix square root
+    *
+    * \param[in]  arg     matrix whose square root is to be computed.
+    * \param[out] result  square root of \p arg.
+    *
+    * See MatrixBase::sqrt() for details on how this computation is implemented.
+    */
+  template <typename ResultType> static void run(const MatrixType &arg, ResultType &result);    
 };
 
 
 // ********** Partial specialization for real matrices **********
 
 template <typename MatrixType>
-class MatrixSquareRoot<MatrixType, 0>
-{
-  public:
-
-    MatrixSquareRoot(const MatrixType& A) 
-      : m_A(A) 
-    {  
-      eigen_assert(A.rows() == A.cols());
-    }
-  
-    template <typename ResultType> void compute(ResultType &result)
-    {
-      // Compute Schur decomposition of m_A
-      const RealSchur<MatrixType> schurOfA(m_A);  
-      const MatrixType& T = schurOfA.matrixT();
-      const MatrixType& U = schurOfA.matrixU();
-    
-      // Compute square root of T
-      MatrixType sqrtT = MatrixType::Zero(m_A.rows(), m_A.cols());
-      MatrixSquareRootQuasiTriangular<MatrixType>(T).compute(sqrtT);
-    
-      // Compute square root of m_A
-      result = U * sqrtT * U.adjoint();
-    }
-    
-  private:
-    const MatrixType& m_A;
+struct matrix_sqrt_compute<MatrixType, 0>
+{
+  template <typename ResultType>
+  static void run(const MatrixType &arg, ResultType &result)
+  {
+    eigen_assert(arg.rows() == arg.cols());
+
+    // Compute Schur decomposition of arg
+    const RealSchur<MatrixType> schurOfA(arg);  
+    const MatrixType& T = schurOfA.matrixT();
+    const MatrixType& U = schurOfA.matrixU();
+    
+    // Compute square root of T
+    MatrixType sqrtT = MatrixType::Zero(arg.rows(), arg.cols());
+    matrix_sqrt_quasi_triangular(T, sqrtT);
+    
+    // Compute square root of arg
+    result = U * sqrtT * U.adjoint();
+  }
 };
 
 
 // ********** Partial specialization for complex matrices **********
 
 template <typename MatrixType>
-class MatrixSquareRoot<MatrixType, 1>
-{
-  public:
-
-    MatrixSquareRoot(const MatrixType& A) 
-      : m_A(A) 
-    {  
-      eigen_assert(A.rows() == A.cols());
-    }
-  
-    template <typename ResultType> void compute(ResultType &result)
-    {
-      // Compute Schur decomposition of m_A
-      const ComplexSchur<MatrixType> schurOfA(m_A);  
-      const MatrixType& T = schurOfA.matrixT();
-      const MatrixType& U = schurOfA.matrixU();
-    
-      // Compute square root of T
-      MatrixType sqrtT;
-      MatrixSquareRootTriangular<MatrixType>(T).compute(sqrtT);
-    
-      // Compute square root of m_A
-      result = U * (sqrtT.template triangularView<Upper>() * U.adjoint());
-    }
-    
-  private:
-    const MatrixType& m_A;
+struct matrix_sqrt_compute<MatrixType, 1>
+{
+  template <typename ResultType>
+  static void run(const MatrixType &arg, ResultType &result)
+  {
+    eigen_assert(arg.rows() == arg.cols());
+
+    // Compute Schur decomposition of arg
+    const ComplexSchur<MatrixType> schurOfA(arg);  
+    const MatrixType& T = schurOfA.matrixT();
+    const MatrixType& U = schurOfA.matrixU();
+    
+    // Compute square root of T
+    MatrixType sqrtT;
+    matrix_sqrt_triangular(T, sqrtT);
+    
+    // Compute square root of arg
+    result = U * (sqrtT.template triangularView<Upper>() * U.adjoint());
+  }
 };
 
+} // end namespace internal
 
 /** \ingroup MatrixFunctions_Module
   *
   * \brief Proxy for the matrix square root of some matrix (expression).
   *
@@ -413,39 +315,41 @@
   * used.
   */
 template<typename Derived> class MatrixSquareRootReturnValue
 : public ReturnByValue<MatrixSquareRootReturnValue<Derived> >
 {
+  protected:
     typedef typename Derived::Index Index;
+    typedef typename internal::ref_selector<Derived>::type DerivedNested;
+
   public:
     /** \brief Constructor.
       *
       * \param[in]  src  %Matrix (expression) forming the argument of the
       * matrix square root.
       */
-    MatrixSquareRootReturnValue(const Derived& src) : m_src(src) { }
+    explicit MatrixSquareRootReturnValue(const Derived& src) : m_src(src) { }
 
     /** \brief Compute the matrix square root.
       *
       * \param[out]  result  the matrix square root of \p src in the
       * constructor.
       */
     template <typename ResultType>
     inline void evalTo(ResultType& result) const
     {
-      const typename Derived::PlainObject srcEvaluated = m_src.eval();
-      MatrixSquareRoot<typename Derived::PlainObject> me(srcEvaluated);
-      me.compute(result);
+      typedef typename internal::nested_eval<Derived, 10>::type DerivedEvalType;
+      typedef typename internal::remove_all<DerivedEvalType>::type DerivedEvalTypeClean;
+      DerivedEvalType tmp(m_src);
+      internal::matrix_sqrt_compute<DerivedEvalTypeClean>::run(tmp, result);
     }
 
     Index rows() const { return m_src.rows(); }
     Index cols() const { return m_src.cols(); }
 
   protected:
-    const Derived& m_src;
-  private:
-    MatrixSquareRootReturnValue& operator=(const MatrixSquareRootReturnValue&);
+    const DerivedNested m_src;
 };
 
 namespace internal {
 template<typename Derived>
 struct traits<MatrixSquareRootReturnValue<Derived> >

Index: 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/StemFunction.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/StemFunction.h
+++ 3rd_party/eigen/unsupported/Eigen/src/MatrixFunctions/StemFunction.h
@@ -1,9 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010, 2013 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
@@ -10,96 +10,108 @@
 #ifndef EIGEN_STEM_FUNCTION
 #define EIGEN_STEM_FUNCTION
 
 namespace Eigen { 
 
-/** \ingroup MatrixFunctions_Module 
-  * \brief Stem functions corresponding to standard mathematical functions.
-  */
-template <typename Scalar>
-class StdStemFunctions
-{
-  public:
-
-    /** \brief The exponential function (and its derivatives). */
-    static Scalar exp(Scalar x, int)
-    {
-      return std::exp(x);
-    }
-
-    /** \brief Cosine (and its derivatives). */
-    static Scalar cos(Scalar x, int n)
-    {
-      Scalar res;
-      switch (n % 4) {
-      case 0: 
-	res = std::cos(x);
-	break;
-      case 1:
-	res = -std::sin(x);
-	break;
-      case 2:
-	res = -std::cos(x);
-	break;
-      case 3:
-	res = std::sin(x);
-	break;
-      }
-      return res;
-    }
-
-    /** \brief Sine (and its derivatives). */
-    static Scalar sin(Scalar x, int n)
-    {
-      Scalar res;
-      switch (n % 4) {
-      case 0:
-	res = std::sin(x);
-	break;
-      case 1:
-	res = std::cos(x);
-	break;
-      case 2:
-	res = -std::sin(x);
-	break;
-      case 3:
-	res = -std::cos(x);
-	break;
-      }
-      return res;
-    }
-
-    /** \brief Hyperbolic cosine (and its derivatives). */
-    static Scalar cosh(Scalar x, int n)
-    {
-      Scalar res;
-      switch (n % 2) {
-      case 0:
-	res = std::cosh(x);
-	break;
-      case 1:
-	res = std::sinh(x);
-	break;
-      }
-      return res;
-    }
-	
-    /** \brief Hyperbolic sine (and its derivatives). */
-    static Scalar sinh(Scalar x, int n)
-    {
-      Scalar res;
-      switch (n % 2) {
-      case 0:
-	res = std::sinh(x);
-	break;
-      case 1:
-	res = std::cosh(x);
-	break;
-      }
-      return res;
-    }
-
-}; // end of class StdStemFunctions
+namespace internal {
+
+/** \brief The exponential function (and its derivatives). */
+template <typename Scalar>
+Scalar stem_function_exp(Scalar x, int)
+{
+  using std::exp;
+  return exp(x);
+}
+
+/** \brief Cosine (and its derivatives). */
+template <typename Scalar>
+Scalar stem_function_cos(Scalar x, int n)
+{
+  using std::cos;
+  using std::sin;
+  Scalar res;
+
+  switch (n % 4) {
+  case 0: 
+    res = std::cos(x);
+    break;
+  case 1:
+    res = -std::sin(x);
+    break;
+  case 2:
+    res = -std::cos(x);
+    break;
+  case 3:
+    res = std::sin(x);
+    break;
+  }
+  return res;
+}
+
+/** \brief Sine (and its derivatives). */
+template <typename Scalar>
+Scalar stem_function_sin(Scalar x, int n)
+{
+  using std::cos;
+  using std::sin;
+  Scalar res;
+
+  switch (n % 4) {
+  case 0:
+    res = std::sin(x);
+    break;
+  case 1:
+    res = std::cos(x);
+    break;
+  case 2:
+    res = -std::sin(x);
+    break;
+  case 3:
+    res = -std::cos(x);
+    break;
+  }
+  return res;
+}
+
+/** \brief Hyperbolic cosine (and its derivatives). */
+template <typename Scalar>
+Scalar stem_function_cosh(Scalar x, int n)
+{
+  using std::cosh;
+  using std::sinh;
+  Scalar res;
+  
+  switch (n % 2) {
+  case 0:
+    res = std::cosh(x);
+    break;
+  case 1:
+    res = std::sinh(x);
+    break;
+  }
+  return res;
+}
+	
+/** \brief Hyperbolic sine (and its derivatives). */
+template <typename Scalar>
+Scalar stem_function_sinh(Scalar x, int n)
+{
+  using std::cosh;
+  using std::sinh;
+  Scalar res;
+  
+  switch (n % 2) {
+  case 0:
+    res = std::sinh(x);
+    break;
+  case 1:
+    res = std::cosh(x);
+    break;
+  }
+  return res;
+}
+
+} // end namespace internal
 
 } // end namespace Eigen
 
 #endif // EIGEN_STEM_FUNCTION

DELETED 3rd_party/eigen/unsupported/Eigen/src/MoreVectorization/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/MoreVectorization/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/MoreVectorization/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/MoreVectorization/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_MoreVectorization_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_MoreVectorization_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/MoreVectorization COMPONENT Devel
-  )

DELETED 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_NonLinearOptimization_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_NonLinearOptimization_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/NonLinearOptimization COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
+++ 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
@@ -148,11 +148,11 @@
     fvec.resize(n);
     qtf.resize(n);
     fjac.resize(n, n);
     if (!useExternalScaling)
         diag.resize(n);
-    eigen_assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
+    eigen_assert( (!useExternalScaling || diag.size()==n) && "When useExternalScaling is set, the caller must provide a valid 'diag'");
 
     /* Function Body */
     nfev = 0;
     njev = 0;
 
@@ -388,11 +388,11 @@
     qtf.resize(n);
     fjac.resize(n, n);
     fvec.resize(n);
     if (!useExternalScaling)
         diag.resize(n);
-    eigen_assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
+    eigen_assert( (!useExternalScaling || diag.size()==n) && "When useExternalScaling is set, the caller must provide a valid 'diag'");
 
     /* Function Body */
     nfev = 0;
     njev = 0;
 

Index: 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
+++ 3rd_party/eigen/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
@@ -43,22 +43,28 @@
   * http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm
   */
 template<typename FunctorType, typename Scalar=double>
 class LevenbergMarquardt
 {
+    static Scalar sqrt_epsilon()
+    {
+      using std::sqrt;
+      return sqrt(NumTraits<Scalar>::epsilon());
+    }
+    
 public:
     LevenbergMarquardt(FunctorType &_functor)
         : functor(_functor) { nfev = njev = iter = 0;  fnorm = gnorm = 0.; useExternalScaling=false; }
 
     typedef DenseIndex Index;
-
+    
     struct Parameters {
         Parameters()
             : factor(Scalar(100.))
             , maxfev(400)
-            , ftol(std::sqrt(NumTraits<Scalar>::epsilon()))
-            , xtol(std::sqrt(NumTraits<Scalar>::epsilon()))
+            , ftol(sqrt_epsilon())
+            , xtol(sqrt_epsilon())
             , gtol(Scalar(0.))
             , epsfcn(Scalar(0.)) {}
         Scalar factor;
         Index maxfev;   // maximum number of function evaluation
         Scalar ftol;
@@ -70,11 +76,11 @@
     typedef Matrix< Scalar, Dynamic, 1 > FVectorType;
     typedef Matrix< Scalar, Dynamic, Dynamic > JacobianType;
 
     LevenbergMarquardtSpace::Status lmder1(
             FVectorType &x,
-            const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon())
+            const Scalar tol = sqrt_epsilon()
             );
 
     LevenbergMarquardtSpace::Status minimize(FVectorType &x);
     LevenbergMarquardtSpace::Status minimizeInit(FVectorType &x);
     LevenbergMarquardtSpace::Status minimizeOneStep(FVectorType &x);
@@ -81,16 +87,16 @@
 
     static LevenbergMarquardtSpace::Status lmdif1(
             FunctorType &functor,
             FVectorType &x,
             Index *nfev,
-            const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon())
+            const Scalar tol = sqrt_epsilon()
             );
 
     LevenbergMarquardtSpace::Status lmstr1(
             FVectorType  &x,
-            const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon())
+            const Scalar tol = sqrt_epsilon()
             );
 
     LevenbergMarquardtSpace::Status minimizeOptimumStorage(FVectorType  &x);
     LevenbergMarquardtSpace::Status minimizeOptimumStorageInit(FVectorType  &x);
     LevenbergMarquardtSpace::Status minimizeOptimumStorageOneStep(FVectorType  &x);
@@ -107,10 +113,11 @@
     Scalar fnorm, gnorm;
     bool useExternalScaling; 
 
     Scalar lm_param(void) { return par; }
 private:
+    
     FunctorType &functor;
     Index n;
     Index m;
     FVectorType wa1, wa2, wa3, wa4;
 
@@ -170,11 +177,11 @@
     wa4.resize(m);
     fvec.resize(m);
     fjac.resize(m, n);
     if (!useExternalScaling)
         diag.resize(n);
-    eigen_assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
+    eigen_assert( (!useExternalScaling || diag.size()==n) && "When useExternalScaling is set, the caller must provide a valid 'diag'");
     qtf.resize(n);
 
     /* Function Body */
     nfev = 0;
     njev = 0;
@@ -206,11 +213,11 @@
 LevenbergMarquardtSpace::Status
 LevenbergMarquardt<FunctorType,Scalar>::minimizeOneStep(FVectorType  &x)
 {
     using std::abs;
     using std::sqrt;
-    
+
     eigen_assert(x.size()==n); // check the caller is not cheating us
 
     /* calculate the jacobian matrix. */
     Index df_ret = functor.df(x, fjac);
     if (df_ret<0)
@@ -389,11 +396,11 @@
     // The purpose it to only use a nxn matrix, instead of mxn here, so
     // that we can handle cases where m>>n :
     fjac.resize(n, n);
     if (!useExternalScaling)
         diag.resize(n);
-    eigen_assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
+    eigen_assert( (!useExternalScaling || diag.size()==n) && "When useExternalScaling is set, the caller must provide a valid 'diag'");
     qtf.resize(n);
 
     /* Function Body */
     nfev = 0;
     njev = 0;

DELETED 3rd_party/eigen/unsupported/Eigen/src/NumericalDiff/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/NumericalDiff/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/NumericalDiff/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/NumericalDiff/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_NumericalDiff_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_NumericalDiff_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/NumericalDiff COMPONENT Devel
-  )

DELETED 3rd_party/eigen/unsupported/Eigen/src/Polynomials/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/Polynomials/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Polynomials/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/Polynomials/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Polynomials_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Polynomials_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/Polynomials COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
+++ 3rd_party/eigen/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
@@ -39,11 +39,11 @@
     typedef DenseIndex Index;
 
   protected:
     template< typename OtherPolynomial >
     inline void setPolynomial( const OtherPolynomial& poly ){
-      m_roots.resize(poly.size()); }
+      m_roots.resize(poly.size()-1); }
 
   public:
     template< typename OtherPolynomial >
     inline PolynomialSolverBase( const OtherPolynomial& poly ){
       setPolynomial( poly() ); }
@@ -314,11 +314,11 @@
   * - real roots,
   * - greatest, smallest complex roots,
   * - real roots with greatest, smallest absolute real value.
   * - greatest, smallest real roots.
   *
-  * WARNING: this polynomial solver is experimental, part of the unsuported Eigen modules.
+  * WARNING: this polynomial solver is experimental, part of the unsupported Eigen modules.
   *
   *
   * Currently a QR algorithm is used to compute the eigenvalues of the companion matrix of
   * the polynomial to compute its roots.
   * This supposes that the complex moduli of the roots are all distinct: e.g. there should
@@ -343,14 +343,23 @@
     /** Computes the complex roots of a new polynomial. */
     template< typename OtherPolynomial >
     void compute( const OtherPolynomial& poly )
     {
       eigen_assert( Scalar(0) != poly[poly.size()-1] );
-      internal::companion<Scalar,_Deg> companion( poly );
-      companion.balance();
-      m_eigenSolver.compute( companion.denseMatrix() );
-      m_roots = m_eigenSolver.eigenvalues();
+      eigen_assert( poly.size() > 1 );
+      if(poly.size() >  2 )
+      {
+        internal::companion<Scalar,_Deg> companion( poly );
+        companion.balance();
+        m_eigenSolver.compute( companion.denseMatrix() );
+        m_roots = m_eigenSolver.eigenvalues();
+      }
+      else if(poly.size () == 2)
+      {
+        m_roots.resize(1);
+        m_roots[0] = -poly[0]/poly[1];
+      }
     }
 
   public:
     template< typename OtherPolynomial >
     inline PolynomialSolver( const OtherPolynomial& poly ){
@@ -374,16 +383,24 @@
   public:
     /** Computes the complex roots of a new polynomial. */
     template< typename OtherPolynomial >
     void compute( const OtherPolynomial& poly )
     {
-      eigen_assert( Scalar(0) != poly[poly.size()-1] );
-      m_roots[0] = -poly[0]/poly[poly.size()-1];
+      eigen_assert( poly.size() == 2 );
+      eigen_assert( Scalar(0) != poly[1] );
+      m_roots[0] = -poly[0]/poly[1];
     }
 
+  public:
+    template< typename OtherPolynomial >
+    inline PolynomialSolver( const OtherPolynomial& poly ){
+      compute( poly ); }
+
+    inline PolynomialSolver(){}
+
   protected:
     using                   PS_Base::m_roots;
 };
 
 } // end namespace Eigen
 
 #endif // EIGEN_POLYNOMIAL_SOLVER_H

Index: 3rd_party/eigen/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
+++ 3rd_party/eigen/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
@@ -54,11 +54,11 @@
     T val=poly[0];
     T inv_x = T(1)/x;
     for( DenseIndex i=1; i<poly.size(); ++i ){
       val = val*inv_x + poly[i]; }
 
-    return std::pow(x,(T)(poly.size()-1)) * val;
+    return numext::pow(x,(T)(poly.size()-1)) * val;
   }
 }
 
 /** \ingroup Polynomials_Module
  * \returns a maximum bound for the absolute value of any root of the polynomial.

DELETED 3rd_party/eigen/unsupported/Eigen/src/SVD/BDCSVD.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SVD/BDCSVD.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SVD/BDCSVD.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SVD/BDCSVD.h
@@ -1,748 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-// 
-// We used the "A Divide-And-Conquer Algorithm for the Bidiagonal SVD"
-// research report written by Ming Gu and Stanley C.Eisenstat
-// The code variable names correspond to the names they used in their 
-// report
-//
-// Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com>
-// Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr>
-// Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr>
-// Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr>
-//
-// Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_BDCSVD_H
-#define EIGEN_BDCSVD_H
-
-#define EPSILON 0.0000000000000001
-
-#define ALGOSWAP 32
-
-namespace Eigen {
-/** \ingroup SVD_Module
- *
- *
- * \class BDCSVD
- *
- * \brief class Bidiagonal Divide and Conquer SVD
- *
- * \param MatrixType the type of the matrix of which we are computing the SVD decomposition
- * We plan to have a very similar interface to JacobiSVD on this class.
- * It should be used to speed up the calcul of SVD for big matrices. 
- */
-template<typename _MatrixType> 
-class BDCSVD : public SVDBase<_MatrixType>
-{
-  typedef SVDBase<_MatrixType> Base;
-    
-public:
-  using Base::rows;
-  using Base::cols;
-  
-  typedef _MatrixType MatrixType;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-  typedef typename MatrixType::Index Index;
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime, 
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime, 
-    DiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime), 
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, 
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, 
-    MaxDiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(MaxRowsAtCompileTime, MaxColsAtCompileTime), 
-    MatrixOptions = MatrixType::Options
-  };
-
-  typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, 
-		 MatrixOptions, MaxRowsAtCompileTime, MaxRowsAtCompileTime>
-  MatrixUType;
-  typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime, 
-		 MatrixOptions, MaxColsAtCompileTime, MaxColsAtCompileTime>
-  MatrixVType;
-  typedef typename internal::plain_diag_type<MatrixType, RealScalar>::type SingularValuesType;
-  typedef typename internal::plain_row_type<MatrixType>::type RowType;
-  typedef typename internal::plain_col_type<MatrixType>::type ColType;
-  typedef Matrix<Scalar, Dynamic, Dynamic> MatrixX;
-  typedef Matrix<RealScalar, Dynamic, Dynamic> MatrixXr;
-  typedef Matrix<RealScalar, Dynamic, 1> VectorType;
-
-  /** \brief Default Constructor.
-   *
-   * The default constructor is useful in cases in which the user intends to
-   * perform decompositions via BDCSVD::compute(const MatrixType&).
-   */
-  BDCSVD()
-    : SVDBase<_MatrixType>::SVDBase(), 
-      algoswap(ALGOSWAP)
-  {}
-
-
-  /** \brief Default Constructor with memory preallocation
-   *
-   * Like the default constructor but with preallocation of the internal data
-   * according to the specified problem size.
-   * \sa BDCSVD()
-   */
-  BDCSVD(Index rows, Index cols, unsigned int computationOptions = 0)
-    : SVDBase<_MatrixType>::SVDBase(), 
-      algoswap(ALGOSWAP)
-  {
-    allocate(rows, cols, computationOptions);
-  }
-
-  /** \brief Constructor performing the decomposition of given matrix.
-   *
-   * \param matrix the matrix to decompose
-   * \param computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed.
-   *                           By default, none is computed. This is a bit - field, the possible bits are #ComputeFullU, #ComputeThinU, 
-   *                           #ComputeFullV, #ComputeThinV.
-   *
-   * Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not
-   * available with the (non - default) FullPivHouseholderQR preconditioner.
-   */
-  BDCSVD(const MatrixType& matrix, unsigned int computationOptions = 0)
-    : SVDBase<_MatrixType>::SVDBase(), 
-      algoswap(ALGOSWAP)
-  {
-    compute(matrix, computationOptions);
-  }
-
-  ~BDCSVD() 
-  {
-  }
-  /** \brief Method performing the decomposition of given matrix using custom options.
-   *
-   * \param matrix the matrix to decompose
-   * \param computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed.
-   *                           By default, none is computed. This is a bit - field, the possible bits are #ComputeFullU, #ComputeThinU, 
-   *                           #ComputeFullV, #ComputeThinV.
-   *
-   * Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not
-   * available with the (non - default) FullPivHouseholderQR preconditioner.
-   */
-  SVDBase<MatrixType>& compute(const MatrixType& matrix, unsigned int computationOptions);
-
-  /** \brief Method performing the decomposition of given matrix using current options.
-   *
-   * \param matrix the matrix to decompose
-   *
-   * This method uses the current \a computationOptions, as already passed to the constructor or to compute(const MatrixType&, unsigned int).
-   */
-  SVDBase<MatrixType>& compute(const MatrixType& matrix)
-  {
-    return compute(matrix, this->m_computationOptions);
-  }
-
-  void setSwitchSize(int s) 
-  {
-    eigen_assert(s>3 && "BDCSVD the size of the algo switch has to be greater than 4");
-    algoswap = s;
-  }
-
-
-  /** \returns a (least squares) solution of \f$ A x = b \f$ using the current SVD decomposition of A.
-   *
-   * \param b the right - hand - side of the equation to solve.
-   *
-   * \note Solving requires both U and V to be computed. Thin U and V are enough, there is no need for full U or V.
-   *
-   * \note SVD solving is implicitly least - squares. Thus, this method serves both purposes of exact solving and least - squares solving.
-   * In other words, the returned solution is guaranteed to minimize the Euclidean norm \f$ \Vert A x - b \Vert \f$.
-   */
-  template<typename Rhs>
-  inline const internal::solve_retval<BDCSVD, Rhs>
-  solve(const MatrixBase<Rhs>& b) const
-  {
-    eigen_assert(this->m_isInitialized && "BDCSVD is not initialized.");
-    eigen_assert(SVDBase<_MatrixType>::computeU() && SVDBase<_MatrixType>::computeV() && 
-		 "BDCSVD::solve() requires both unitaries U and V to be computed (thin unitaries suffice).");
-    return internal::solve_retval<BDCSVD, Rhs>(*this, b.derived());
-  }
-
- 
-  const MatrixUType& matrixU() const
-  {
-    eigen_assert(this->m_isInitialized && "SVD is not initialized.");
-    if (isTranspose){
-      eigen_assert(this->computeV() && "This SVD decomposition didn't compute U. Did you ask for it?");
-      return this->m_matrixV;
-    }
-    else 
-    {
-      eigen_assert(this->computeU() && "This SVD decomposition didn't compute U. Did you ask for it?");
-      return this->m_matrixU;
-    }
-     
-  }
-
-
-  const MatrixVType& matrixV() const
-  {
-    eigen_assert(this->m_isInitialized && "SVD is not initialized.");
-    if (isTranspose){
-      eigen_assert(this->computeU() && "This SVD decomposition didn't compute V. Did you ask for it?");
-      return this->m_matrixU;
-    }
-    else
-    {
-      eigen_assert(this->computeV() && "This SVD decomposition didn't compute V. Did you ask for it?");
-      return this->m_matrixV;
-    }
-  }
- 
-private:
-  void allocate(Index rows, Index cols, unsigned int computationOptions);
-  void divide (Index firstCol, Index lastCol, Index firstRowW, 
-	       Index firstColW, Index shift);
-  void deflation43(Index firstCol, Index shift, Index i, Index size);
-  void deflation44(Index firstColu , Index firstColm, Index firstRowW, Index firstColW, Index i, Index j, Index size);
-  void deflation(Index firstCol, Index lastCol, Index k, Index firstRowW, Index firstColW, Index shift);
-  void copyUV(MatrixXr naiveU, MatrixXr naiveV, MatrixX householderU, MatrixX houseHolderV);
-
-protected:
-  MatrixXr m_naiveU, m_naiveV;
-  MatrixXr m_computed;
-  Index nRec;
-  int algoswap;
-  bool isTranspose, compU, compV;
-  
-}; //end class BDCSVD
-
-
-// Methode to allocate ans initialize matrix and attributs
-template<typename MatrixType>
-void BDCSVD<MatrixType>::allocate(Index rows, Index cols, unsigned int computationOptions)
-{
-  isTranspose = (cols > rows);
-  if (SVDBase<MatrixType>::allocate(rows, cols, computationOptions)) return;
-  m_computed = MatrixXr::Zero(this->m_diagSize + 1, this->m_diagSize );
-  if (isTranspose){
-    compU = this->computeU();
-    compV = this->computeV();    
-  } 
-  else
-  {
-    compV = this->computeU();
-    compU = this->computeV();   
-  }
-  if (compU) m_naiveU = MatrixXr::Zero(this->m_diagSize + 1, this->m_diagSize + 1 );
-  else m_naiveU = MatrixXr::Zero(2, this->m_diagSize + 1 );
-  
-  if (compV) m_naiveV = MatrixXr::Zero(this->m_diagSize, this->m_diagSize);
-  
-
-  //should be changed for a cleaner implementation
-  if (isTranspose){
-    bool aux;
-    if (this->computeU()||this->computeV()){
-      aux = this->m_computeFullU;
-      this->m_computeFullU = this->m_computeFullV;
-      this->m_computeFullV = aux;
-      aux = this->m_computeThinU;
-      this->m_computeThinU = this->m_computeThinV;
-      this->m_computeThinV = aux;
-    } 
-  }
-}// end allocate
-
-// Methode which compute the BDCSVD for the int
-template<>
-SVDBase<Matrix<int, Dynamic, Dynamic> >&
-BDCSVD<Matrix<int, Dynamic, Dynamic> >::compute(const MatrixType& matrix, unsigned int computationOptions) {
-  allocate(matrix.rows(), matrix.cols(), computationOptions);
-  this->m_nonzeroSingularValues = 0;
-  m_computed = Matrix<int, Dynamic, Dynamic>::Zero(rows(), cols());
-  for (int i=0; i<this->m_diagSize; i++)   {
-    this->m_singularValues.coeffRef(i) = 0;
-  }
-  if (this->m_computeFullU) this->m_matrixU = Matrix<int, Dynamic, Dynamic>::Zero(rows(), rows());
-  if (this->m_computeFullV) this->m_matrixV = Matrix<int, Dynamic, Dynamic>::Zero(cols(), cols()); 
-  this->m_isInitialized = true;
-  return *this;
-}
-
-
-// Methode which compute the BDCSVD
-template<typename MatrixType>
-SVDBase<MatrixType>&
-BDCSVD<MatrixType>::compute(const MatrixType& matrix, unsigned int computationOptions) 
-{
-  allocate(matrix.rows(), matrix.cols(), computationOptions);
-  using std::abs;
-
-  //**** step 1 Bidiagonalization  isTranspose = (matrix.cols()>matrix.rows()) ;
-  MatrixType copy;
-  if (isTranspose) copy = matrix.adjoint();
-  else copy = matrix;
-  
-  internal::UpperBidiagonalization<MatrixX > bid(copy);
-
-  //**** step 2 Divide
-  // this is ugly and has to be redone (care of complex cast)
-  MatrixXr temp;
-  temp = bid.bidiagonal().toDenseMatrix().transpose();
-  m_computed.setZero();
-  for (int i=0; i<this->m_diagSize - 1; i++)   {
-    m_computed(i, i) = temp(i, i);
-    m_computed(i + 1, i) = temp(i + 1, i);
-  }
-  m_computed(this->m_diagSize - 1, this->m_diagSize - 1) = temp(this->m_diagSize - 1, this->m_diagSize - 1);
-  divide(0, this->m_diagSize - 1, 0, 0, 0);
-
-  //**** step 3 copy
-  for (int i=0; i<this->m_diagSize; i++)   {
-    RealScalar a = abs(m_computed.coeff(i, i));
-    this->m_singularValues.coeffRef(i) = a;
-    if (a == 0){
-      this->m_nonzeroSingularValues = i;
-      break;
-    }
-    else  if (i == this->m_diagSize - 1)
-    {
-      this->m_nonzeroSingularValues = i + 1;
-      break;
-    }
-  }
-  copyUV(m_naiveV, m_naiveU, bid.householderU(), bid.householderV());
-  this->m_isInitialized = true;
-  return *this;
-}// end compute
-
-
-template<typename MatrixType>
-void BDCSVD<MatrixType>::copyUV(MatrixXr naiveU, MatrixXr naiveV, MatrixX householderU, MatrixX householderV){
-  if (this->computeU()){
-    MatrixX temp = MatrixX::Zero(naiveU.rows(), naiveU.cols());
-    temp.real() = naiveU;
-    if (this->m_computeThinU){
-      this->m_matrixU = MatrixX::Identity(householderU.cols(), this->m_nonzeroSingularValues );
-      this->m_matrixU.block(0, 0, this->m_diagSize, this->m_nonzeroSingularValues) = 
-	temp.block(0, 0, this->m_diagSize, this->m_nonzeroSingularValues);
-      this->m_matrixU = householderU * this->m_matrixU ;
-    }
-    else
-    {
-      this->m_matrixU = MatrixX::Identity(householderU.cols(), householderU.cols());
-      this->m_matrixU.block(0, 0, this->m_diagSize, this->m_diagSize) = temp.block(0, 0, this->m_diagSize, this->m_diagSize);
-      this->m_matrixU = householderU * this->m_matrixU ;
-    }
-  }
-  if (this->computeV()){
-    MatrixX temp = MatrixX::Zero(naiveV.rows(), naiveV.cols());
-    temp.real() = naiveV;
-    if (this->m_computeThinV){
-      this->m_matrixV = MatrixX::Identity(householderV.cols(),this->m_nonzeroSingularValues );
-      this->m_matrixV.block(0, 0, this->m_nonzeroSingularValues, this->m_nonzeroSingularValues) = 
-	temp.block(0, 0, this->m_nonzeroSingularValues, this->m_nonzeroSingularValues);
-      this->m_matrixV = householderV * this->m_matrixV ;
-    }
-    else  
-    {
-      this->m_matrixV = MatrixX::Identity(householderV.cols(), householderV.cols());
-      this->m_matrixV.block(0, 0, this->m_diagSize, this->m_diagSize) = temp.block(0, 0, this->m_diagSize, this->m_diagSize);
-      this->m_matrixV = householderV * this->m_matrixV;
-    }
-  }
-}
-
-// The divide algorithm is done "in place", we are always working on subsets of the same matrix. The divide methods takes as argument the 
-// place of the submatrix we are currently working on.
-
-//@param firstCol : The Index of the first column of the submatrix of m_computed and for m_naiveU;
-//@param lastCol : The Index of the last column of the submatrix of m_computed and for m_naiveU; 
-// lastCol + 1 - firstCol is the size of the submatrix.
-//@param firstRowW : The Index of the first row of the matrix W that we are to change. (see the reference paper section 1 for more information on W)
-//@param firstRowW : Same as firstRowW with the column.
-//@param shift : Each time one takes the left submatrix, one must add 1 to the shift. Why? Because! We actually want the last column of the U submatrix 
-// to become the first column (*coeff) and to shift all the other columns to the right. There are more details on the reference paper.
-template<typename MatrixType>
-void BDCSVD<MatrixType>::divide (Index firstCol, Index lastCol, Index firstRowW, 
-				 Index firstColW, Index shift)
-{
-  // requires nbRows = nbCols + 1;
-  using std::pow;
-  using std::sqrt;
-  using std::abs;
-  const Index n = lastCol - firstCol + 1;
-  const Index k = n/2;
-  RealScalar alphaK;
-  RealScalar betaK; 
-  RealScalar r0; 
-  RealScalar lambda, phi, c0, s0;
-  MatrixXr l, f;
-  // We use the other algorithm which is more efficient for small 
-  // matrices.
-  if (n < algoswap){
-    JacobiSVD<MatrixXr> b(m_computed.block(firstCol, firstCol, n + 1, n), 
-			  ComputeFullU | (ComputeFullV * compV)) ;
-    if (compU) m_naiveU.block(firstCol, firstCol, n + 1, n + 1).real() << b.matrixU();
-    else 
-    {
-      m_naiveU.row(0).segment(firstCol, n + 1).real() << b.matrixU().row(0);
-      m_naiveU.row(1).segment(firstCol, n + 1).real() << b.matrixU().row(n);
-    }
-    if (compV) m_naiveV.block(firstRowW, firstColW, n, n).real() << b.matrixV();
-    m_computed.block(firstCol + shift, firstCol + shift, n + 1, n).setZero();
-    for (int i=0; i<n; i++)
-    {
-      m_computed(firstCol + shift + i, firstCol + shift +i) = b.singularValues().coeffRef(i);
-    }
-    return;
-  }
-  // We use the divide and conquer algorithm
-  alphaK =  m_computed(firstCol + k, firstCol + k);
-  betaK = m_computed(firstCol + k + 1, firstCol + k);
-  // The divide must be done in that order in order to have good results. Divide change the data inside the submatrices
-  // and the divide of the right submatrice reads one column of the left submatrice. That's why we need to treat the 
-  // right submatrix before the left one. 
-  divide(k + 1 + firstCol, lastCol, k + 1 + firstRowW, k + 1 + firstColW, shift);
-  divide(firstCol, k - 1 + firstCol, firstRowW, firstColW + 1, shift + 1);
-  if (compU)
-  {
-    lambda = m_naiveU(firstCol + k, firstCol + k);
-    phi = m_naiveU(firstCol + k + 1, lastCol + 1);
-  } 
-  else 
-  {
-    lambda = m_naiveU(1, firstCol + k);
-    phi = m_naiveU(0, lastCol + 1);
-  }
-  r0 = sqrt((abs(alphaK * lambda) * abs(alphaK * lambda))
-	    + abs(betaK * phi) * abs(betaK * phi));
-  if (compU)
-  {
-    l = m_naiveU.row(firstCol + k).segment(firstCol, k);
-    f = m_naiveU.row(firstCol + k + 1).segment(firstCol + k + 1, n - k - 1);
-  } 
-  else 
-  {
-    l = m_naiveU.row(1).segment(firstCol, k);
-    f = m_naiveU.row(0).segment(firstCol + k + 1, n - k - 1);
-  }
-  if (compV) m_naiveV(firstRowW+k, firstColW) = 1;
-  if (r0 == 0)
-  {
-    c0 = 1;
-    s0 = 0;
-  }
-  else
-  {
-    c0 = alphaK * lambda / r0;
-    s0 = betaK * phi / r0;
-  }
-  if (compU)
-  {
-    MatrixXr q1 (m_naiveU.col(firstCol + k).segment(firstCol, k + 1));     
-    // we shiftW Q1 to the right
-    for (Index i = firstCol + k - 1; i >= firstCol; i--) 
-    {
-      m_naiveU.col(i + 1).segment(firstCol, k + 1) << m_naiveU.col(i).segment(firstCol, k + 1);
-    }
-    // we shift q1 at the left with a factor c0
-    m_naiveU.col(firstCol).segment( firstCol, k + 1) << (q1 * c0);
-    // last column = q1 * - s0
-    m_naiveU.col(lastCol + 1).segment(firstCol, k + 1) << (q1 * ( - s0));
-    // first column = q2 * s0
-    m_naiveU.col(firstCol).segment(firstCol + k + 1, n - k) << 
-      m_naiveU.col(lastCol + 1).segment(firstCol + k + 1, n - k) *s0; 
-    // q2 *= c0
-    m_naiveU.col(lastCol + 1).segment(firstCol + k + 1, n - k) *= c0; 
-  } 
-  else 
-  {
-    RealScalar q1 = (m_naiveU(0, firstCol + k));
-    // we shift Q1 to the right
-    for (Index i = firstCol + k - 1; i >= firstCol; i--) 
-    {
-      m_naiveU(0, i + 1) = m_naiveU(0, i);
-    }
-    // we shift q1 at the left with a factor c0
-    m_naiveU(0, firstCol) = (q1 * c0);
-    // last column = q1 * - s0
-    m_naiveU(0, lastCol + 1) = (q1 * ( - s0));
-    // first column = q2 * s0
-    m_naiveU(1, firstCol) = m_naiveU(1, lastCol + 1) *s0; 
-    // q2 *= c0
-    m_naiveU(1, lastCol + 1) *= c0;
-    m_naiveU.row(1).segment(firstCol + 1, k).setZero();
-    m_naiveU.row(0).segment(firstCol + k + 1, n - k - 1).setZero();
-  }
-  m_computed(firstCol + shift, firstCol + shift) = r0;
-  m_computed.col(firstCol + shift).segment(firstCol + shift + 1, k) << alphaK * l.transpose().real();
-  m_computed.col(firstCol + shift).segment(firstCol + shift + k + 1, n - k - 1) << betaK * f.transpose().real();
-
-
-  // the line below do the deflation of the matrix for the third part of the algorithm
-  // Here the deflation is commented because the third part of the algorithm is not implemented
-  // the third part of the algorithm is a fast SVD on the matrix m_computed which works thanks to the deflation
-
-  deflation(firstCol, lastCol, k, firstRowW, firstColW, shift);
-
-  // Third part of the algorithm, since the real third part of the algorithm is not implemeted we use a JacobiSVD
-  JacobiSVD<MatrixXr> res= JacobiSVD<MatrixXr>(m_computed.block(firstCol + shift, firstCol +shift, n + 1, n), 
-					       ComputeFullU | (ComputeFullV * compV)) ;
-  if (compU) m_naiveU.block(firstCol, firstCol, n + 1, n + 1) *= res.matrixU();
-  else m_naiveU.block(0, firstCol, 2, n + 1) *= res.matrixU();
-  
-  if (compV) m_naiveV.block(firstRowW, firstColW, n, n) *= res.matrixV();
-  m_computed.block(firstCol + shift, firstCol + shift, n, n) << MatrixXr::Zero(n, n);
-  for (int i=0; i<n; i++)
-    m_computed(firstCol + shift + i, firstCol + shift +i) = res.singularValues().coeffRef(i);
-  // end of the third part
-
-
-}// end divide
-
-
-// page 12_13
-// i >= 1, di almost null and zi non null.
-// We use a rotation to zero out zi applied to the left of M
-template <typename MatrixType>
-void BDCSVD<MatrixType>::deflation43(Index firstCol, Index shift, Index i, Index size){
-  using std::abs;
-  using std::sqrt;
-  using std::pow;
-  RealScalar c = m_computed(firstCol + shift, firstCol + shift);
-  RealScalar s = m_computed(i, firstCol + shift);
-  RealScalar r = sqrt(pow(abs(c), 2) + pow(abs(s), 2));
-  if (r == 0){
-    m_computed(i, i)=0;
-    return;
-  }
-  c/=r;
-  s/=r;
-  m_computed(firstCol + shift, firstCol + shift) = r;  
-  m_computed(i, firstCol + shift) = 0;
-  m_computed(i, i) = 0;
-  if (compU){
-    m_naiveU.col(firstCol).segment(firstCol,size) = 
-      c * m_naiveU.col(firstCol).segment(firstCol, size) - 
-      s * m_naiveU.col(i).segment(firstCol, size) ;
-
-    m_naiveU.col(i).segment(firstCol, size) = 
-      (c + s*s/c) * m_naiveU.col(i).segment(firstCol, size) + 
-      (s/c) * m_naiveU.col(firstCol).segment(firstCol,size);
-  }
-}// end deflation 43
-
-
-// page 13
-// i,j >= 1, i != j and |di - dj| < epsilon * norm2(M)
-// We apply two rotations to have zj = 0;
-template <typename MatrixType>
-void BDCSVD<MatrixType>::deflation44(Index firstColu , Index firstColm, Index firstRowW, Index firstColW, Index i, Index j, Index size){
-  using std::abs;
-  using std::sqrt;
-  using std::conj;
-  using std::pow;
-  RealScalar c = m_computed(firstColm, firstColm + j - 1);
-  RealScalar s = m_computed(firstColm, firstColm + i - 1);
-  RealScalar r = sqrt(pow(abs(c), 2) + pow(abs(s), 2));
-  if (r==0){
-    m_computed(firstColm + i, firstColm + i) = m_computed(firstColm + j, firstColm + j);
-    return;
-  }
-  c/=r;
-  s/=r;
-  m_computed(firstColm + i, firstColm) = r;  
-  m_computed(firstColm + i, firstColm + i) = m_computed(firstColm + j, firstColm + j);
-  m_computed(firstColm + j, firstColm) = 0;
-  if (compU){
-    m_naiveU.col(firstColu + i).segment(firstColu, size) = 
-      c * m_naiveU.col(firstColu + i).segment(firstColu, size) - 
-      s * m_naiveU.col(firstColu + j).segment(firstColu, size) ;
-
-    m_naiveU.col(firstColu + j).segment(firstColu, size) = 
-      (c + s*s/c) *  m_naiveU.col(firstColu + j).segment(firstColu, size) + 
-      (s/c) * m_naiveU.col(firstColu + i).segment(firstColu, size);
-  } 
-  if (compV){
-    m_naiveV.col(firstColW + i).segment(firstRowW, size - 1) = 
-      c * m_naiveV.col(firstColW + i).segment(firstRowW, size - 1) + 
-      s * m_naiveV.col(firstColW + j).segment(firstRowW, size - 1) ;
-
-    m_naiveV.col(firstColW + j).segment(firstRowW, size - 1)  = 
-      (c + s*s/c) * m_naiveV.col(firstColW + j).segment(firstRowW, size - 1) - 
-      (s/c) * m_naiveV.col(firstColW + i).segment(firstRowW, size - 1);
-  }
-}// end deflation 44
-
-
-
-template <typename MatrixType>
-void BDCSVD<MatrixType>::deflation(Index firstCol, Index lastCol, Index k, Index firstRowW, Index firstColW, Index shift){
-  //condition 4.1
-  RealScalar EPS = EPSILON * (std::max<RealScalar>(m_computed(firstCol + shift + 1, firstCol + shift + 1), m_computed(firstCol + k, firstCol + k)));
-  const Index length = lastCol + 1 - firstCol;
-  if (m_computed(firstCol + shift, firstCol + shift) < EPS){
-    m_computed(firstCol + shift, firstCol + shift) = EPS;
-  }
-  //condition 4.2
-  for (Index i=firstCol + shift + 1;i<=lastCol + shift;i++){
-    if (std::abs(m_computed(i, firstCol + shift)) < EPS){
-      m_computed(i, firstCol + shift) = 0;
-    }
-  }
-
-  //condition 4.3
-  for (Index i=firstCol + shift + 1;i<=lastCol + shift; i++){
-    if (m_computed(i, i) < EPS){
-      deflation43(firstCol, shift, i, length);
-    }
-  }
-
-  //condition 4.4
- 
-  Index i=firstCol + shift + 1, j=firstCol + shift + k + 1;
-  //we stock the final place of each line
-  Index *permutation = new Index[length];
-
-  for (Index p =1; p < length; p++) {
-    if (i> firstCol + shift + k){
-      permutation[p] = j;
-      j++;
-    } else if (j> lastCol + shift) 
-    {
-      permutation[p] = i;
-      i++;
-    }
-    else 
-    {
-      if (m_computed(i, i) < m_computed(j, j)){
-        permutation[p] = j;
-        j++;
-      } 
-      else
-      {
-        permutation[p] = i;
-        i++;
-      }
-    }
-  }
-  //we do the permutation
-  RealScalar aux;
-  //we stock the current index of each col
-  //and the column of each index
-  Index *realInd = new Index[length];
-  Index *realCol = new Index[length];
-  for (int pos = 0; pos< length; pos++){
-    realCol[pos] = pos + firstCol + shift;
-    realInd[pos] = pos;
-  }
-  const Index Zero = firstCol + shift;
-  VectorType temp;
-  for (int i = 1; i < length - 1; i++){
-    const Index I = i + Zero;
-    const Index realI = realInd[i];
-    const Index j  = permutation[length - i] - Zero;
-    const Index J = realCol[j];
-    
-    //diag displace
-    aux = m_computed(I, I); 
-    m_computed(I, I) = m_computed(J, J);
-    m_computed(J, J) = aux;
-    
-    //firstrow displace
-    aux = m_computed(I, Zero); 
-    m_computed(I, Zero) = m_computed(J, Zero);
-    m_computed(J, Zero) = aux;
-
-    // change columns
-    if (compU) {
-      temp = m_naiveU.col(I - shift).segment(firstCol, length + 1);
-      m_naiveU.col(I - shift).segment(firstCol, length + 1) << 
-        m_naiveU.col(J - shift).segment(firstCol, length + 1);
-      m_naiveU.col(J - shift).segment(firstCol, length + 1) << temp;
-    } 
-    else
-    {
-      temp = m_naiveU.col(I - shift).segment(0, 2);
-      m_naiveU.col(I - shift).segment(0, 2) << 
-        m_naiveU.col(J - shift).segment(0, 2);
-      m_naiveU.col(J - shift).segment(0, 2) << temp;      
-    }
-    if (compV) {
-      const Index CWI = I + firstColW - Zero;
-      const Index CWJ = J + firstColW - Zero;
-      temp = m_naiveV.col(CWI).segment(firstRowW, length);
-      m_naiveV.col(CWI).segment(firstRowW, length) << m_naiveV.col(CWJ).segment(firstRowW, length);
-      m_naiveV.col(CWJ).segment(firstRowW, length) << temp;
-    }
-
-    //update real pos
-    realCol[realI] = J;
-    realCol[j] = I;
-    realInd[J - Zero] = realI;
-    realInd[I - Zero] = j;
-  }
-  for (Index i = firstCol + shift + 1; i<lastCol + shift;i++){
-    if ((m_computed(i + 1, i + 1) - m_computed(i, i)) < EPS){
-      deflation44(firstCol , 
-		  firstCol + shift, 
-		  firstRowW, 
-		  firstColW, 
-		  i - Zero, 
-		  i + 1 - Zero, 
-		  length);
-    }
-  }
-  delete [] permutation;
-  delete [] realInd;
-  delete [] realCol;
-
-}//end deflation
-
-
-namespace internal{
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<BDCSVD<_MatrixType>, Rhs>
-  : solve_retval_base<BDCSVD<_MatrixType>, Rhs>
-{
-  typedef BDCSVD<_MatrixType> BDCSVDType;
-  EIGEN_MAKE_SOLVE_HELPERS(BDCSVDType, Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    eigen_assert(rhs().rows() == dec().rows());
-    // A = U S V^*
-    // So A^{ - 1} = V S^{ - 1} U^*    
-    Index diagSize = (std::min)(dec().rows(), dec().cols());
-    typename BDCSVDType::SingularValuesType invertedSingVals(diagSize);
-    Index nonzeroSingVals = dec().nonzeroSingularValues();
-    invertedSingVals.head(nonzeroSingVals) = dec().singularValues().head(nonzeroSingVals).array().inverse();
-    invertedSingVals.tail(diagSize - nonzeroSingVals).setZero();
-    
-    dst = dec().matrixV().leftCols(diagSize)
-      * invertedSingVals.asDiagonal()
-      * dec().matrixU().leftCols(diagSize).adjoint()
-      * rhs();	
-    return;
-  }
-};
-
-} //end namespace internal
-
-  /** \svd_module
-   *
-   * \return the singular value decomposition of \c *this computed by 
-   *  BDC Algorithm
-   *
-   * \sa class BDCSVD
-   */
-/*
-template<typename Derived>
-BDCSVD<typename MatrixBase<Derived>::PlainObject>
-MatrixBase<Derived>::bdcSvd(unsigned int computationOptions) const
-{
-  return BDCSVD<PlainObject>(*this, computationOptions);
-}
-*/
-
-} // end namespace Eigen
-
-#endif

DELETED 3rd_party/eigen/unsupported/Eigen/src/SVD/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/SVD/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SVD/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/SVD/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SVD_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_SVD_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}unsupported/Eigen/src/SVD COMPONENT Devel
-  )

DELETED 3rd_party/eigen/unsupported/Eigen/src/SVD/JacobiSVD.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SVD/JacobiSVD.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SVD/JacobiSVD.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SVD/JacobiSVD.h
@@ -1,782 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_JACOBISVD_H
-#define EIGEN_JACOBISVD_H
-
-namespace Eigen { 
-
-namespace internal {
-// forward declaration (needed by ICC)
-// the empty body is required by MSVC
-template<typename MatrixType, int QRPreconditioner,
-         bool IsComplex = NumTraits<typename MatrixType::Scalar>::IsComplex>
-struct svd_precondition_2x2_block_to_be_real {};
-
-/*** QR preconditioners (R-SVD)
- ***
- *** Their role is to reduce the problem of computing the SVD to the case of a square matrix.
- *** This approach, known as R-SVD, is an optimization for rectangular-enough matrices, and is a requirement for
- *** JacobiSVD which by itself is only able to work on square matrices.
- ***/
-
-enum { PreconditionIfMoreColsThanRows, PreconditionIfMoreRowsThanCols };
-
-template<typename MatrixType, int QRPreconditioner, int Case>
-struct qr_preconditioner_should_do_anything
-{
-  enum { a = MatrixType::RowsAtCompileTime != Dynamic &&
-             MatrixType::ColsAtCompileTime != Dynamic &&
-             MatrixType::ColsAtCompileTime <= MatrixType::RowsAtCompileTime,
-         b = MatrixType::RowsAtCompileTime != Dynamic &&
-             MatrixType::ColsAtCompileTime != Dynamic &&
-             MatrixType::RowsAtCompileTime <= MatrixType::ColsAtCompileTime,
-         ret = !( (QRPreconditioner == NoQRPreconditioner) ||
-                  (Case == PreconditionIfMoreColsThanRows && bool(a)) ||
-                  (Case == PreconditionIfMoreRowsThanCols && bool(b)) )
-  };
-};
-
-template<typename MatrixType, int QRPreconditioner, int Case,
-         bool DoAnything = qr_preconditioner_should_do_anything<MatrixType, QRPreconditioner, Case>::ret
-> struct qr_preconditioner_impl {};
-
-template<typename MatrixType, int QRPreconditioner, int Case>
-class qr_preconditioner_impl<MatrixType, QRPreconditioner, Case, false>
-{
-public:
-  typedef typename MatrixType::Index Index;
-  void allocate(const JacobiSVD<MatrixType, QRPreconditioner>&) {}
-  bool run(JacobiSVD<MatrixType, QRPreconditioner>&, const MatrixType&)
-  {
-    return false;
-  }
-};
-
-/*** preconditioner using FullPivHouseholderQR ***/
-
-template<typename MatrixType>
-class qr_preconditioner_impl<MatrixType, FullPivHouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
-{
-public:
-  typedef typename MatrixType::Index Index;
-  typedef typename MatrixType::Scalar Scalar;
-  enum
-  {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime
-  };
-  typedef Matrix<Scalar, 1, RowsAtCompileTime, RowMajor, 1, MaxRowsAtCompileTime> WorkspaceType;
-
-  void allocate(const JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd)
-  {
-    if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
-    {
-      m_qr.~QRType();
-      ::new (&m_qr) QRType(svd.rows(), svd.cols());
-    }
-    if (svd.m_computeFullU) m_workspace.resize(svd.rows());
-  }
-
-  bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
-  {
-    if(matrix.rows() > matrix.cols())
-    {
-      m_qr.compute(matrix);
-      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
-      if(svd.m_computeFullU) m_qr.matrixQ().evalTo(svd.m_matrixU, m_workspace);
-      if(svd.computeV()) svd.m_matrixV = m_qr.colsPermutation();
-      return true;
-    }
-    return false;
-  }
-private:
-  typedef FullPivHouseholderQR<MatrixType> QRType;
-  QRType m_qr;
-  WorkspaceType m_workspace;
-};
-
-template<typename MatrixType>
-class qr_preconditioner_impl<MatrixType, FullPivHouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
-{
-public:
-  typedef typename MatrixType::Index Index;
-  typedef typename MatrixType::Scalar Scalar;
-  enum
-  {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    Options = MatrixType::Options
-  };
-  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, Options, MaxColsAtCompileTime, MaxRowsAtCompileTime>
-          TransposeTypeWithSameStorageOrder;
-
-  void allocate(const JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd)
-  {
-    if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
-    {
-      m_qr.~QRType();
-      ::new (&m_qr) QRType(svd.cols(), svd.rows());
-    }
-    m_adjoint.resize(svd.cols(), svd.rows());
-    if (svd.m_computeFullV) m_workspace.resize(svd.cols());
-  }
-
-  bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
-  {
-    if(matrix.cols() > matrix.rows())
-    {
-      m_adjoint = matrix.adjoint();
-      m_qr.compute(m_adjoint);
-      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
-      if(svd.m_computeFullV) m_qr.matrixQ().evalTo(svd.m_matrixV, m_workspace);
-      if(svd.computeU()) svd.m_matrixU = m_qr.colsPermutation();
-      return true;
-    }
-    else return false;
-  }
-private:
-  typedef FullPivHouseholderQR<TransposeTypeWithSameStorageOrder> QRType;
-  QRType m_qr;
-  TransposeTypeWithSameStorageOrder m_adjoint;
-  typename internal::plain_row_type<MatrixType>::type m_workspace;
-};
-
-/*** preconditioner using ColPivHouseholderQR ***/
-
-template<typename MatrixType>
-class qr_preconditioner_impl<MatrixType, ColPivHouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
-{
-public:
-  typedef typename MatrixType::Index Index;
-
-  void allocate(const JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd)
-  {
-    if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
-    {
-      m_qr.~QRType();
-      ::new (&m_qr) QRType(svd.rows(), svd.cols());
-    }
-    if (svd.m_computeFullU) m_workspace.resize(svd.rows());
-    else if (svd.m_computeThinU) m_workspace.resize(svd.cols());
-  }
-
-  bool run(JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
-  {
-    if(matrix.rows() > matrix.cols())
-    {
-      m_qr.compute(matrix);
-      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
-      if(svd.m_computeFullU) m_qr.householderQ().evalTo(svd.m_matrixU, m_workspace);
-      else if(svd.m_computeThinU)
-      {
-        svd.m_matrixU.setIdentity(matrix.rows(), matrix.cols());
-        m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixU, m_workspace);
-      }
-      if(svd.computeV()) svd.m_matrixV = m_qr.colsPermutation();
-      return true;
-    }
-    return false;
-  }
-
-private:
-  typedef ColPivHouseholderQR<MatrixType> QRType;
-  QRType m_qr;
-  typename internal::plain_col_type<MatrixType>::type m_workspace;
-};
-
-template<typename MatrixType>
-class qr_preconditioner_impl<MatrixType, ColPivHouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
-{
-public:
-  typedef typename MatrixType::Index Index;
-  typedef typename MatrixType::Scalar Scalar;
-  enum
-  {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    Options = MatrixType::Options
-  };
-
-  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, Options, MaxColsAtCompileTime, MaxRowsAtCompileTime>
-          TransposeTypeWithSameStorageOrder;
-
-  void allocate(const JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd)
-  {
-    if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
-    {
-      m_qr.~QRType();
-      ::new (&m_qr) QRType(svd.cols(), svd.rows());
-    }
-    if (svd.m_computeFullV) m_workspace.resize(svd.cols());
-    else if (svd.m_computeThinV) m_workspace.resize(svd.rows());
-    m_adjoint.resize(svd.cols(), svd.rows());
-  }
-
-  bool run(JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
-  {
-    if(matrix.cols() > matrix.rows())
-    {
-      m_adjoint = matrix.adjoint();
-      m_qr.compute(m_adjoint);
-
-      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
-      if(svd.m_computeFullV) m_qr.householderQ().evalTo(svd.m_matrixV, m_workspace);
-      else if(svd.m_computeThinV)
-      {
-        svd.m_matrixV.setIdentity(matrix.cols(), matrix.rows());
-        m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixV, m_workspace);
-      }
-      if(svd.computeU()) svd.m_matrixU = m_qr.colsPermutation();
-      return true;
-    }
-    else return false;
-  }
-
-private:
-  typedef ColPivHouseholderQR<TransposeTypeWithSameStorageOrder> QRType;
-  QRType m_qr;
-  TransposeTypeWithSameStorageOrder m_adjoint;
-  typename internal::plain_row_type<MatrixType>::type m_workspace;
-};
-
-/*** preconditioner using HouseholderQR ***/
-
-template<typename MatrixType>
-class qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
-{
-public:
-  typedef typename MatrixType::Index Index;
-
-  void allocate(const JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd)
-  {
-    if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
-    {
-      m_qr.~QRType();
-      ::new (&m_qr) QRType(svd.rows(), svd.cols());
-    }
-    if (svd.m_computeFullU) m_workspace.resize(svd.rows());
-    else if (svd.m_computeThinU) m_workspace.resize(svd.cols());
-  }
-
-  bool run(JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd, const MatrixType& matrix)
-  {
-    if(matrix.rows() > matrix.cols())
-    {
-      m_qr.compute(matrix);
-      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
-      if(svd.m_computeFullU) m_qr.householderQ().evalTo(svd.m_matrixU, m_workspace);
-      else if(svd.m_computeThinU)
-      {
-        svd.m_matrixU.setIdentity(matrix.rows(), matrix.cols());
-        m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixU, m_workspace);
-      }
-      if(svd.computeV()) svd.m_matrixV.setIdentity(matrix.cols(), matrix.cols());
-      return true;
-    }
-    return false;
-  }
-private:
-  typedef HouseholderQR<MatrixType> QRType;
-  QRType m_qr;
-  typename internal::plain_col_type<MatrixType>::type m_workspace;
-};
-
-template<typename MatrixType>
-class qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
-{
-public:
-  typedef typename MatrixType::Index Index;
-  typedef typename MatrixType::Scalar Scalar;
-  enum
-  {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    Options = MatrixType::Options
-  };
-
-  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, Options, MaxColsAtCompileTime, MaxRowsAtCompileTime>
-          TransposeTypeWithSameStorageOrder;
-
-  void allocate(const JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd)
-  {
-    if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
-    {
-      m_qr.~QRType();
-      ::new (&m_qr) QRType(svd.cols(), svd.rows());
-    }
-    if (svd.m_computeFullV) m_workspace.resize(svd.cols());
-    else if (svd.m_computeThinV) m_workspace.resize(svd.rows());
-    m_adjoint.resize(svd.cols(), svd.rows());
-  }
-
-  bool run(JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd, const MatrixType& matrix)
-  {
-    if(matrix.cols() > matrix.rows())
-    {
-      m_adjoint = matrix.adjoint();
-      m_qr.compute(m_adjoint);
-
-      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
-      if(svd.m_computeFullV) m_qr.householderQ().evalTo(svd.m_matrixV, m_workspace);
-      else if(svd.m_computeThinV)
-      {
-        svd.m_matrixV.setIdentity(matrix.cols(), matrix.rows());
-        m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixV, m_workspace);
-      }
-      if(svd.computeU()) svd.m_matrixU.setIdentity(matrix.rows(), matrix.rows());
-      return true;
-    }
-    else return false;
-  }
-
-private:
-  typedef HouseholderQR<TransposeTypeWithSameStorageOrder> QRType;
-  QRType m_qr;
-  TransposeTypeWithSameStorageOrder m_adjoint;
-  typename internal::plain_row_type<MatrixType>::type m_workspace;
-};
-
-/*** 2x2 SVD implementation
- ***
- *** JacobiSVD consists in performing a series of 2x2 SVD subproblems
- ***/
-
-template<typename MatrixType, int QRPreconditioner>
-struct svd_precondition_2x2_block_to_be_real<MatrixType, QRPreconditioner, false>
-{
-  typedef JacobiSVD<MatrixType, QRPreconditioner> SVD;
-  typedef typename SVD::Index Index;
-  static void run(typename SVD::WorkMatrixType&, SVD&, Index, Index) {}
-};
-
-template<typename MatrixType, int QRPreconditioner>
-struct svd_precondition_2x2_block_to_be_real<MatrixType, QRPreconditioner, true>
-{
-  typedef JacobiSVD<MatrixType, QRPreconditioner> SVD;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename SVD::Index Index;
-  static void run(typename SVD::WorkMatrixType& work_matrix, SVD& svd, Index p, Index q)
-  {
-    using std::sqrt;
-    Scalar z;
-    JacobiRotation<Scalar> rot;
-    RealScalar n = sqrt(numext::abs2(work_matrix.coeff(p,p)) + numext::abs2(work_matrix.coeff(q,p)));
-    if(n==0)
-    {
-      z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q);
-      work_matrix.row(p) *= z;
-      if(svd.computeU()) svd.m_matrixU.col(p) *= conj(z);
-      z = abs(work_matrix.coeff(q,q)) / work_matrix.coeff(q,q);
-      work_matrix.row(q) *= z;
-      if(svd.computeU()) svd.m_matrixU.col(q) *= conj(z);
-    }
-    else
-    {
-      rot.c() = conj(work_matrix.coeff(p,p)) / n;
-      rot.s() = work_matrix.coeff(q,p) / n;
-      work_matrix.applyOnTheLeft(p,q,rot);
-      if(svd.computeU()) svd.m_matrixU.applyOnTheRight(p,q,rot.adjoint());
-      if(work_matrix.coeff(p,q) != Scalar(0))
-      {
-        Scalar z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q);
-        work_matrix.col(q) *= z;
-        if(svd.computeV()) svd.m_matrixV.col(q) *= z;
-      }
-      if(work_matrix.coeff(q,q) != Scalar(0))
-      {
-        z = abs(work_matrix.coeff(q,q)) / work_matrix.coeff(q,q);
-        work_matrix.row(q) *= z;
-        if(svd.computeU()) svd.m_matrixU.col(q) *= conj(z);
-      }
-    }
-  }
-};
-
-template<typename MatrixType, typename RealScalar, typename Index>
-void real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q,
-                            JacobiRotation<RealScalar> *j_left,
-                            JacobiRotation<RealScalar> *j_right)
-{
-  using std::sqrt;
-  Matrix<RealScalar,2,2> m;
-  m << numext::real(matrix.coeff(p,p)), numext::real(matrix.coeff(p,q)),
-       numext::real(matrix.coeff(q,p)), numext::real(matrix.coeff(q,q));
-  JacobiRotation<RealScalar> rot1;
-  RealScalar t = m.coeff(0,0) + m.coeff(1,1);
-  RealScalar d = m.coeff(1,0) - m.coeff(0,1);
-  if(t == RealScalar(0))
-  {
-    rot1.c() = RealScalar(0);
-    rot1.s() = d > RealScalar(0) ? RealScalar(1) : RealScalar(-1);
-  }
-  else
-  {
-    RealScalar u = d / t;
-    rot1.c() = RealScalar(1) / sqrt(RealScalar(1) + numext::abs2(u));
-    rot1.s() = rot1.c() * u;
-  }
-  m.applyOnTheLeft(0,1,rot1);
-  j_right->makeJacobi(m,0,1);
-  *j_left  = rot1 * j_right->transpose();
-}
-
-} // end namespace internal
-
-/** \ingroup SVD_Module
-  *
-  *
-  * \class JacobiSVD
-  *
-  * \brief Two-sided Jacobi SVD decomposition of a rectangular matrix
-  *
-  * \param MatrixType the type of the matrix of which we are computing the SVD decomposition
-  * \param QRPreconditioner this optional parameter allows to specify the type of QR decomposition that will be used internally
-  *                        for the R-SVD step for non-square matrices. See discussion of possible values below.
-  *
-  * SVD decomposition consists in decomposing any n-by-p matrix \a A as a product
-  *   \f[ A = U S V^* \f]
-  * where \a U is a n-by-n unitary, \a V is a p-by-p unitary, and \a S is a n-by-p real positive matrix which is zero outside of its main diagonal;
-  * the diagonal entries of S are known as the \em singular \em values of \a A and the columns of \a U and \a V are known as the left
-  * and right \em singular \em vectors of \a A respectively.
-  *
-  * Singular values are always sorted in decreasing order.
-  *
-  * This JacobiSVD decomposition computes only the singular values by default. If you want \a U or \a V, you need to ask for them explicitly.
-  *
-  * You can ask for only \em thin \a U or \a V to be computed, meaning the following. In case of a rectangular n-by-p matrix, letting \a m be the
-  * smaller value among \a n and \a p, there are only \a m singular vectors; the remaining columns of \a U and \a V do not correspond to actual
-  * singular vectors. Asking for \em thin \a U or \a V means asking for only their \a m first columns to be formed. So \a U is then a n-by-m matrix,
-  * and \a V is then a p-by-m matrix. Notice that thin \a U and \a V are all you need for (least squares) solving.
-  *
-  * Here's an example demonstrating basic usage:
-  * \include JacobiSVD_basic.cpp
-  * Output: \verbinclude JacobiSVD_basic.out
-  *
-  * This JacobiSVD class is a two-sided Jacobi R-SVD decomposition, ensuring optimal reliability and accuracy. The downside is that it's slower than
-  * bidiagonalizing SVD algorithms for large square matrices; however its complexity is still \f$ O(n^2p) \f$ where \a n is the smaller dimension and
-  * \a p is the greater dimension, meaning that it is still of the same order of complexity as the faster bidiagonalizing R-SVD algorithms.
-  * In particular, like any R-SVD, it takes advantage of non-squareness in that its complexity is only linear in the greater dimension.
-  *
-  * If the input matrix has inf or nan coefficients, the result of the computation is undefined, but the computation is guaranteed to
-  * terminate in finite (and reasonable) time.
-  *
-  * The possible values for QRPreconditioner are:
-  * \li ColPivHouseholderQRPreconditioner is the default. In practice it's very safe. It uses column-pivoting QR.
-  * \li FullPivHouseholderQRPreconditioner, is the safest and slowest. It uses full-pivoting QR.
-  *     Contrary to other QRs, it doesn't allow computing thin unitaries.
-  * \li HouseholderQRPreconditioner is the fastest, and less safe and accurate than the pivoting variants. It uses non-pivoting QR.
-  *     This is very similar in safety and accuracy to the bidiagonalization process used by bidiagonalizing SVD algorithms (since bidiagonalization
-  *     is inherently non-pivoting). However the resulting SVD is still more reliable than bidiagonalizing SVDs because the Jacobi-based iterarive
-  *     process is more reliable than the optimized bidiagonal SVD iterations.
-  * \li NoQRPreconditioner allows not to use a QR preconditioner at all. This is useful if you know that you will only be computing
-  *     JacobiSVD decompositions of square matrices. Non-square matrices require a QR preconditioner. Using this option will result in
-  *     faster compilation and smaller executable code. It won't significantly speed up computation, since JacobiSVD is always checking
-  *     if QR preconditioning is needed before applying it anyway.
-  *
-  * \sa MatrixBase::jacobiSvd()
-  */
-template<typename _MatrixType, int QRPreconditioner> 
-class JacobiSVD : public SVDBase<_MatrixType>
-{
-  public:
-
-    typedef _MatrixType MatrixType;
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
-    enum {
-      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      DiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime),
-      MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-      MaxDiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(MaxRowsAtCompileTime,MaxColsAtCompileTime),
-      MatrixOptions = MatrixType::Options
-    };
-
-    typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime,
-                   MatrixOptions, MaxRowsAtCompileTime, MaxRowsAtCompileTime>
-            MatrixUType;
-    typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime,
-                   MatrixOptions, MaxColsAtCompileTime, MaxColsAtCompileTime>
-            MatrixVType;
-    typedef typename internal::plain_diag_type<MatrixType, RealScalar>::type SingularValuesType;
-    typedef typename internal::plain_row_type<MatrixType>::type RowType;
-    typedef typename internal::plain_col_type<MatrixType>::type ColType;
-    typedef Matrix<Scalar, DiagSizeAtCompileTime, DiagSizeAtCompileTime,
-                   MatrixOptions, MaxDiagSizeAtCompileTime, MaxDiagSizeAtCompileTime>
-            WorkMatrixType;
-
-    /** \brief Default Constructor.
-      *
-      * The default constructor is useful in cases in which the user intends to
-      * perform decompositions via JacobiSVD::compute(const MatrixType&).
-      */
-    JacobiSVD()
-      : SVDBase<_MatrixType>::SVDBase()
-    {}
-
-
-    /** \brief Default Constructor with memory preallocation
-      *
-      * Like the default constructor but with preallocation of the internal data
-      * according to the specified problem size.
-      * \sa JacobiSVD()
-      */
-    JacobiSVD(Index rows, Index cols, unsigned int computationOptions = 0)
-      : SVDBase<_MatrixType>::SVDBase() 
-    {
-      allocate(rows, cols, computationOptions);
-    }
-
-    /** \brief Constructor performing the decomposition of given matrix.
-     *
-     * \param matrix the matrix to decompose
-     * \param computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed.
-     *                           By default, none is computed. This is a bit-field, the possible bits are #ComputeFullU, #ComputeThinU,
-     *                           #ComputeFullV, #ComputeThinV.
-     *
-     * Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not
-     * available with the (non-default) FullPivHouseholderQR preconditioner.
-     */
-    JacobiSVD(const MatrixType& matrix, unsigned int computationOptions = 0)
-      : SVDBase<_MatrixType>::SVDBase()
-    {
-      compute(matrix, computationOptions);
-    }
-
-    /** \brief Method performing the decomposition of given matrix using custom options.
-     *
-     * \param matrix the matrix to decompose
-     * \param computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed.
-     *                           By default, none is computed. This is a bit-field, the possible bits are #ComputeFullU, #ComputeThinU,
-     *                           #ComputeFullV, #ComputeThinV.
-     *
-     * Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not
-     * available with the (non-default) FullPivHouseholderQR preconditioner.
-     */
-    SVDBase<MatrixType>& compute(const MatrixType& matrix, unsigned int computationOptions);
-
-    /** \brief Method performing the decomposition of given matrix using current options.
-     *
-     * \param matrix the matrix to decompose
-     *
-     * This method uses the current \a computationOptions, as already passed to the constructor or to compute(const MatrixType&, unsigned int).
-     */
-    SVDBase<MatrixType>& compute(const MatrixType& matrix)
-    {
-      return compute(matrix, this->m_computationOptions);
-    }
-    
-    /** \returns a (least squares) solution of \f$ A x = b \f$ using the current SVD decomposition of A.
-      *
-      * \param b the right-hand-side of the equation to solve.
-      *
-      * \note Solving requires both U and V to be computed. Thin U and V are enough, there is no need for full U or V.
-      *
-      * \note SVD solving is implicitly least-squares. Thus, this method serves both purposes of exact solving and least-squares solving.
-      * In other words, the returned solution is guaranteed to minimize the Euclidean norm \f$ \Vert A x - b \Vert \f$.
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<JacobiSVD, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(this->m_isInitialized && "JacobiSVD is not initialized.");
-      eigen_assert(SVDBase<MatrixType>::computeU() && SVDBase<MatrixType>::computeV() && "JacobiSVD::solve() requires both unitaries U and V to be computed (thin unitaries suffice).");
-      return internal::solve_retval<JacobiSVD, Rhs>(*this, b.derived());
-    }
-
-    
-
-  private:
-    void allocate(Index rows, Index cols, unsigned int computationOptions);
-
-  protected:
-    WorkMatrixType m_workMatrix;
-   
-    template<typename __MatrixType, int _QRPreconditioner, bool _IsComplex>
-    friend struct internal::svd_precondition_2x2_block_to_be_real;
-    template<typename __MatrixType, int _QRPreconditioner, int _Case, bool _DoAnything>
-    friend struct internal::qr_preconditioner_impl;
-
-    internal::qr_preconditioner_impl<MatrixType, QRPreconditioner, internal::PreconditionIfMoreColsThanRows> m_qr_precond_morecols;
-    internal::qr_preconditioner_impl<MatrixType, QRPreconditioner, internal::PreconditionIfMoreRowsThanCols> m_qr_precond_morerows;
-};
-
-template<typename MatrixType, int QRPreconditioner>
-void JacobiSVD<MatrixType, QRPreconditioner>::allocate(Index rows, Index cols, unsigned int computationOptions)
-{
-  if (SVDBase<MatrixType>::allocate(rows, cols, computationOptions)) return;
-
-  if (QRPreconditioner == FullPivHouseholderQRPreconditioner)
-  {
-      eigen_assert(!(this->m_computeThinU || this->m_computeThinV) &&
-              "JacobiSVD: can't compute thin U or thin V with the FullPivHouseholderQR preconditioner. "
-              "Use the ColPivHouseholderQR preconditioner instead.");
-  }
-
-  m_workMatrix.resize(this->m_diagSize, this->m_diagSize);
-  
-  if(this->m_cols>this->m_rows) m_qr_precond_morecols.allocate(*this);
-  if(this->m_rows>this->m_cols) m_qr_precond_morerows.allocate(*this);
-}
-
-template<typename MatrixType, int QRPreconditioner>
-SVDBase<MatrixType>&
-JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsigned int computationOptions)
-{
-  using std::abs;
-  allocate(matrix.rows(), matrix.cols(), computationOptions);
-
-  // currently we stop when we reach precision 2*epsilon as the last bit of precision can require an unreasonable number of iterations,
-  // only worsening the precision of U and V as we accumulate more rotations
-  const RealScalar precision = RealScalar(2) * NumTraits<Scalar>::epsilon();
-
-  // limit for very small denormal numbers to be considered zero in order to avoid infinite loops (see bug 286)
-  const RealScalar considerAsZero = RealScalar(2) * std::numeric_limits<RealScalar>::denorm_min();
-
-  /*** step 1. The R-SVD step: we use a QR decomposition to reduce to the case of a square matrix */
-
-  if(!m_qr_precond_morecols.run(*this, matrix) && !m_qr_precond_morerows.run(*this, matrix))
-  {
-    m_workMatrix = matrix.block(0,0,this->m_diagSize,this->m_diagSize);
-    if(this->m_computeFullU) this->m_matrixU.setIdentity(this->m_rows,this->m_rows);
-    if(this->m_computeThinU) this->m_matrixU.setIdentity(this->m_rows,this->m_diagSize);
-    if(this->m_computeFullV) this->m_matrixV.setIdentity(this->m_cols,this->m_cols);
-    if(this->m_computeThinV) this->m_matrixV.setIdentity(this->m_cols, this->m_diagSize);
-  }
-
-  /*** step 2. The main Jacobi SVD iteration. ***/
-
-  bool finished = false;
-  while(!finished)
-  {
-    finished = true;
-
-    // do a sweep: for all index pairs (p,q), perform SVD of the corresponding 2x2 sub-matrix
-
-    for(Index p = 1; p < this->m_diagSize; ++p)
-    {
-      for(Index q = 0; q < p; ++q)
-      {
-        // if this 2x2 sub-matrix is not diagonal already...
-        // notice that this comparison will evaluate to false if any NaN is involved, ensuring that NaN's don't
-        // keep us iterating forever. Similarly, small denormal numbers are considered zero.
-        using std::max;
-        RealScalar threshold = (max)(considerAsZero, precision * (max)(abs(m_workMatrix.coeff(p,p)),
-                                                                       abs(m_workMatrix.coeff(q,q))));
-        if((max)(abs(m_workMatrix.coeff(p,q)),abs(m_workMatrix.coeff(q,p))) > threshold)
-        {
-          finished = false;
-
-          // perform SVD decomposition of 2x2 sub-matrix corresponding to indices p,q to make it diagonal
-          internal::svd_precondition_2x2_block_to_be_real<MatrixType, QRPreconditioner>::run(m_workMatrix, *this, p, q);
-          JacobiRotation<RealScalar> j_left, j_right;
-          internal::real_2x2_jacobi_svd(m_workMatrix, p, q, &j_left, &j_right);
-
-          // accumulate resulting Jacobi rotations
-          m_workMatrix.applyOnTheLeft(p,q,j_left);
-          if(SVDBase<MatrixType>::computeU()) this->m_matrixU.applyOnTheRight(p,q,j_left.transpose());
-
-          m_workMatrix.applyOnTheRight(p,q,j_right);
-          if(SVDBase<MatrixType>::computeV()) this->m_matrixV.applyOnTheRight(p,q,j_right);
-        }
-      }
-    }
-  }
-
-  /*** step 3. The work matrix is now diagonal, so ensure it's positive so its diagonal entries are the singular values ***/
-
-  for(Index i = 0; i < this->m_diagSize; ++i)
-  {
-    RealScalar a = abs(m_workMatrix.coeff(i,i));
-    this->m_singularValues.coeffRef(i) = a;
-    if(SVDBase<MatrixType>::computeU() && (a!=RealScalar(0))) this->m_matrixU.col(i) *= this->m_workMatrix.coeff(i,i)/a;
-  }
-
-  /*** step 4. Sort singular values in descending order and compute the number of nonzero singular values ***/
-
-  this->m_nonzeroSingularValues = this->m_diagSize;
-  for(Index i = 0; i < this->m_diagSize; i++)
-  {
-    Index pos;
-    RealScalar maxRemainingSingularValue = this->m_singularValues.tail(this->m_diagSize-i).maxCoeff(&pos);
-    if(maxRemainingSingularValue == RealScalar(0))
-    {
-      this->m_nonzeroSingularValues = i;
-      break;
-    }
-    if(pos)
-    {
-      pos += i;
-      std::swap(this->m_singularValues.coeffRef(i), this->m_singularValues.coeffRef(pos));
-      if(SVDBase<MatrixType>::computeU()) this->m_matrixU.col(pos).swap(this->m_matrixU.col(i));
-      if(SVDBase<MatrixType>::computeV()) this->m_matrixV.col(pos).swap(this->m_matrixV.col(i));
-    }
-  }
-
-  this->m_isInitialized = true;
-  return *this;
-}
-
-namespace internal {
-template<typename _MatrixType, int QRPreconditioner, typename Rhs>
-struct solve_retval<JacobiSVD<_MatrixType, QRPreconditioner>, Rhs>
-  : solve_retval_base<JacobiSVD<_MatrixType, QRPreconditioner>, Rhs>
-{
-  typedef JacobiSVD<_MatrixType, QRPreconditioner> JacobiSVDType;
-  EIGEN_MAKE_SOLVE_HELPERS(JacobiSVDType,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    eigen_assert(rhs().rows() == dec().rows());
-
-    // A = U S V^*
-    // So A^{-1} = V S^{-1} U^*
-
-    Index diagSize = (std::min)(dec().rows(), dec().cols());
-    typename JacobiSVDType::SingularValuesType invertedSingVals(diagSize);
-
-    Index nonzeroSingVals = dec().nonzeroSingularValues();
-    invertedSingVals.head(nonzeroSingVals) = dec().singularValues().head(nonzeroSingVals).array().inverse();
-    invertedSingVals.tail(diagSize - nonzeroSingVals).setZero();
-
-    dst = dec().matrixV().leftCols(diagSize)
-        * invertedSingVals.asDiagonal()
-        * dec().matrixU().leftCols(diagSize).adjoint()
-        * rhs();
-  }
-};
-} // end namespace internal
-
-/** \svd_module
-  *
-  * \return the singular value decomposition of \c *this computed by two-sided
-  * Jacobi transformations.
-  *
-  * \sa class JacobiSVD
-  */
-template<typename Derived>
-JacobiSVD<typename MatrixBase<Derived>::PlainObject>
-MatrixBase<Derived>::jacobiSvd(unsigned int computationOptions) const
-{
-  return JacobiSVD<PlainObject>(*this, computationOptions);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_JACOBISVD_H

DELETED 3rd_party/eigen/unsupported/Eigen/src/SVD/SVDBase.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SVD/SVDBase.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SVD/SVDBase.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SVD/SVDBase.h
@@ -1,236 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com>
-// Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr>
-// Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr>
-// Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SVD_H
-#define EIGEN_SVD_H
-
-namespace Eigen {
-/** \ingroup SVD_Module
- *
- *
- * \class SVDBase
- *
- * \brief Mother class of SVD classes algorithms
- *
- * \param MatrixType the type of the matrix of which we are computing the SVD decomposition
- * SVD decomposition consists in decomposing any n-by-p matrix \a A as a product
- *   \f[ A = U S V^* \f]
- * where \a U is a n-by-n unitary, \a V is a p-by-p unitary, and \a S is a n-by-p real positive matrix which is zero outside of its main diagonal;
- * the diagonal entries of S are known as the \em singular \em values of \a A and the columns of \a U and \a V are known as the left
- * and right \em singular \em vectors of \a A respectively.
- *
- * Singular values are always sorted in decreasing order.
- *
- * 
- * You can ask for only \em thin \a U or \a V to be computed, meaning the following. In case of a rectangular n-by-p matrix, letting \a m be the
- * smaller value among \a n and \a p, there are only \a m singular vectors; the remaining columns of \a U and \a V do not correspond to actual
- * singular vectors. Asking for \em thin \a U or \a V means asking for only their \a m first columns to be formed. So \a U is then a n-by-m matrix,
- * and \a V is then a p-by-m matrix. Notice that thin \a U and \a V are all you need for (least squares) solving.
- *  
- * If the input matrix has inf or nan coefficients, the result of the computation is undefined, but the computation is guaranteed to
- * terminate in finite (and reasonable) time.
- * \sa MatrixBase::genericSvd()
- */
-template<typename _MatrixType> 
-class SVDBase
-{
-
-public:
-  typedef _MatrixType MatrixType;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-  typedef typename MatrixType::Index Index;
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-    DiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime),
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    MaxDiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(MaxRowsAtCompileTime,MaxColsAtCompileTime),
-    MatrixOptions = MatrixType::Options
-  };
-
-  typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime,
-		 MatrixOptions, MaxRowsAtCompileTime, MaxRowsAtCompileTime>
-  MatrixUType;
-  typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime,
-		 MatrixOptions, MaxColsAtCompileTime, MaxColsAtCompileTime>
-  MatrixVType;
-  typedef typename internal::plain_diag_type<MatrixType, RealScalar>::type SingularValuesType;
-  typedef typename internal::plain_row_type<MatrixType>::type RowType;
-  typedef typename internal::plain_col_type<MatrixType>::type ColType;
-  typedef Matrix<Scalar, DiagSizeAtCompileTime, DiagSizeAtCompileTime,
-		 MatrixOptions, MaxDiagSizeAtCompileTime, MaxDiagSizeAtCompileTime>
-  WorkMatrixType;
-	
-
-
-
-  /** \brief Method performing the decomposition of given matrix using custom options.
-   *
-   * \param matrix the matrix to decompose
-   * \param computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed.
-   *                           By default, none is computed. This is a bit-field, the possible bits are #ComputeFullU, #ComputeThinU,
-   *                           #ComputeFullV, #ComputeThinV.
-   *
-   * Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not
-   * available with the (non-default) FullPivHouseholderQR preconditioner.
-   */
-  SVDBase& compute(const MatrixType& matrix, unsigned int computationOptions);
-
-  /** \brief Method performing the decomposition of given matrix using current options.
-   *
-   * \param matrix the matrix to decompose
-   *
-   * This method uses the current \a computationOptions, as already passed to the constructor or to compute(const MatrixType&, unsigned int).
-   */
-  //virtual SVDBase& compute(const MatrixType& matrix) = 0;
-  SVDBase& compute(const MatrixType& matrix);
-
-  /** \returns the \a U matrix.
-   *
-   * For the SVDBase decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p,
-   * the U matrix is n-by-n if you asked for #ComputeFullU, and is n-by-m if you asked for #ComputeThinU.
-   *
-   * The \a m first columns of \a U are the left singular vectors of the matrix being decomposed.
-   *
-   * This method asserts that you asked for \a U to be computed.
-   */
-  const MatrixUType& matrixU() const
-  {
-    eigen_assert(m_isInitialized && "SVD is not initialized.");
-    eigen_assert(computeU() && "This SVD decomposition didn't compute U. Did you ask for it?");
-    return m_matrixU;
-  }
-
-  /** \returns the \a V matrix.
-   *
-   * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p,
-   * the V matrix is p-by-p if you asked for #ComputeFullV, and is p-by-m if you asked for ComputeThinV.
-   *
-   * The \a m first columns of \a V are the right singular vectors of the matrix being decomposed.
-   *
-   * This method asserts that you asked for \a V to be computed.
-   */
-  const MatrixVType& matrixV() const
-  {
-    eigen_assert(m_isInitialized && "SVD is not initialized.");
-    eigen_assert(computeV() && "This SVD decomposition didn't compute V. Did you ask for it?");
-    return m_matrixV;
-  }
-
-  /** \returns the vector of singular values.
-   *
-   * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p, the
-   * returned vector has size \a m.  Singular values are always sorted in decreasing order.
-   */
-  const SingularValuesType& singularValues() const
-  {
-    eigen_assert(m_isInitialized && "SVD is not initialized.");
-    return m_singularValues;
-  }
-
-  
-
-  /** \returns the number of singular values that are not exactly 0 */
-  Index nonzeroSingularValues() const
-  {
-    eigen_assert(m_isInitialized && "SVD is not initialized.");
-    return m_nonzeroSingularValues;
-  }
-
-
-  /** \returns true if \a U (full or thin) is asked for in this SVD decomposition */
-  inline bool computeU() const { return m_computeFullU || m_computeThinU; }
-  /** \returns true if \a V (full or thin) is asked for in this SVD decomposition */
-  inline bool computeV() const { return m_computeFullV || m_computeThinV; }
-
-
-  inline Index rows() const { return m_rows; }
-  inline Index cols() const { return m_cols; }
-
-
-protected:
-  // return true if already allocated
-  bool allocate(Index rows, Index cols, unsigned int computationOptions) ;
-
-  MatrixUType m_matrixU;
-  MatrixVType m_matrixV;
-  SingularValuesType m_singularValues;
-  bool m_isInitialized, m_isAllocated;
-  bool m_computeFullU, m_computeThinU;
-  bool m_computeFullV, m_computeThinV;
-  unsigned int m_computationOptions;
-  Index m_nonzeroSingularValues, m_rows, m_cols, m_diagSize;
-
-
-  /** \brief Default Constructor.
-   *
-   * Default constructor of SVDBase
-   */
-  SVDBase()
-    : m_isInitialized(false),
-      m_isAllocated(false),
-      m_computationOptions(0),
-      m_rows(-1), m_cols(-1)
-  {}
-
-
-};
-
-
-template<typename MatrixType>
-bool SVDBase<MatrixType>::allocate(Index rows, Index cols, unsigned int computationOptions)
-{
-  eigen_assert(rows >= 0 && cols >= 0);
-
-  if (m_isAllocated &&
-      rows == m_rows &&
-      cols == m_cols &&
-      computationOptions == m_computationOptions)
-  {
-    return true;
-  }
-
-  m_rows = rows;
-  m_cols = cols;
-  m_isInitialized = false;
-  m_isAllocated = true;
-  m_computationOptions = computationOptions;
-  m_computeFullU = (computationOptions & ComputeFullU) != 0;
-  m_computeThinU = (computationOptions & ComputeThinU) != 0;
-  m_computeFullV = (computationOptions & ComputeFullV) != 0;
-  m_computeThinV = (computationOptions & ComputeThinV) != 0;
-  eigen_assert(!(m_computeFullU && m_computeThinU) && "SVDBase: you can't ask for both full and thin U");
-  eigen_assert(!(m_computeFullV && m_computeThinV) && "SVDBase: you can't ask for both full and thin V");
-  eigen_assert(EIGEN_IMPLIES(m_computeThinU || m_computeThinV, MatrixType::ColsAtCompileTime==Dynamic) &&
-	       "SVDBase: thin U and V are only available when your matrix has a dynamic number of columns.");
-
-  m_diagSize = (std::min)(m_rows, m_cols);
-  m_singularValues.resize(m_diagSize);
-  if(RowsAtCompileTime==Dynamic)
-    m_matrixU.resize(m_rows, m_computeFullU ? m_rows
-		     : m_computeThinU ? m_diagSize
-		     : 0);
-  if(ColsAtCompileTime==Dynamic)
-    m_matrixV.resize(m_cols, m_computeFullV ? m_cols
-		     : m_computeThinV ? m_diagSize
-		     : 0);
-
-  return false;
-}
-
-}// end namespace
-
-#endif // EIGEN_SVD_H

DELETED 3rd_party/eigen/unsupported/Eigen/src/SVD/TODOBdcsvd.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/SVD/TODOBdcsvd.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SVD/TODOBdcsvd.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/SVD/TODOBdcsvd.txt
@@ -1,29 +0,0 @@
-TO DO LIST
-
-
-
-(optional optimization) - do all the allocations in the allocate part 
-                        - support static matrices
-                        - return a error at compilation time when using integer matrices (int, long, std::complex<int>, ...)
-
-to finish the algorithm :
-			-implement the last part of the algorithm as described on the reference paper. 
-			    You may find more information on that part on this paper
-
-			-to replace the call to JacobiSVD at the end of the divide algorithm, just after the call to 
-			    deflation.
-
-(suggested step by step resolution)
-                       0) comment the call to Jacobi in the last part of the divide method and everything right after
-                               until the end of the method. What is commented can be a guideline to steps 3) 4) and 6)
-                       1) solve the secular equation (Characteristic equation) on the values that are not null (zi!=0 and di!=0), after the deflation
-                               wich should be uncommented in the divide method
-                       2) remember the values of the singular values that are already computed (zi=0)
-                       3) assign the singular values found in m_computed at the right places (with the ones found in step 2) )
-                               in decreasing order
-                       4) set the firstcol to zero (except the first element) in m_computed
-                       5) compute all the singular vectors when CompV is set to true and only the left vectors when
-                               CompV is set to false
-                       6) multiply naiveU and naiveV to the right by the matrices found, only naiveU when CompV is set to
-                               false, /!\ if CompU is false NaiveU has only 2 rows
-                       7) delete everything commented in step 0)

DELETED 3rd_party/eigen/unsupported/Eigen/src/SVD/doneInBDCSVD.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/SVD/doneInBDCSVD.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SVD/doneInBDCSVD.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/SVD/doneInBDCSVD.txt
@@ -1,21 +0,0 @@
-This unsupported package is about a divide and conquer algorithm to compute SVD.
-
-The implementation follows as closely as possible the following reference paper : 
-http://www.cs.yale.edu/publications/techreports/tr933.pdf
-
-The code documentation uses the same names for variables as the reference paper. The code, deflation included, is
-working  but there are a few things that could be optimised as explained in the TODOBdsvd. 
-
-In the code comments were put at the line where would be the third step of the algorithm so one could simply add the call 
-of a function doing the last part of the algorithm and that would not require any knowledge of the part we implemented.
-
-In the TODOBdcsvd we explain what is the main difficulty of the last part and suggest a reference paper to help solve it.
-
-The implemented has trouble with fixed size matrices. 
-
-In the actual implementation, it returns matrices of zero when ask to do a svd on an int matrix. 
-
-
-Paper for the third part:
-http://www.stat.uchicago.edu/~lekheng/courses/302/classics/greengard-rokhlin.pdf
-

DELETED 3rd_party/eigen/unsupported/Eigen/src/Skyline/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/Skyline/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Skyline/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/Skyline/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Skyline_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Skyline_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/Skyline COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/Skyline/SkylineProduct.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Skyline/SkylineProduct.h
+++ 3rd_party/eigen/unsupported/Eigen/src/Skyline/SkylineProduct.h
@@ -12,12 +12,12 @@
 
 namespace Eigen { 
 
 template<typename Lhs, typename Rhs, int ProductMode>
 struct SkylineProductReturnType {
-    typedef const typename internal::nested<Lhs, Rhs::RowsAtCompileTime>::type LhsNested;
-    typedef const typename internal::nested<Rhs, Lhs::RowsAtCompileTime>::type RhsNested;
+    typedef const typename internal::nested_eval<Lhs, Rhs::RowsAtCompileTime>::type LhsNested;
+    typedef const typename internal::nested_eval<Rhs, Lhs::RowsAtCompileTime>::type RhsNested;
 
     typedef SkylineProduct<LhsNested, RhsNested, ProductMode> Type;
 };
 
 template<typename LhsNested, typename RhsNested, int ProductMode>
@@ -47,11 +47,11 @@
 
         Flags = (int(LhsFlags | RhsFlags) & HereditaryBits & RemovedBits)
         | EvalBeforeAssigningBit
         | EvalBeforeNestingBit,
 
-        CoeffReadCost = Dynamic
+        CoeffReadCost = HugeCost
     };
 
     typedef typename internal::conditional<ResultIsSkyline,
             SkylineMatrixBase<SkylineProduct<LhsNested, RhsNested, ProductMode> >,
             MatrixBase<SkylineProduct<LhsNested, RhsNested, ProductMode> > >::type Base;

ADDED   3rd_party/eigen/unsupported/Eigen/src/SparseExtra/BlockSparseMatrix.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/BlockSparseMatrix.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/BlockSparseMatrix.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/BlockSparseMatrix.h
@@ -0,0 +1,1079 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Desire Nuentsa <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 2013 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSEBLOCKMATRIX_H
+#define EIGEN_SPARSEBLOCKMATRIX_H
+
+namespace Eigen { 
+/** \ingroup SparseCore_Module
+  *
+  * \class BlockSparseMatrix
+  *
+  * \brief A versatile sparse matrix representation where each element is a block
+  *
+  * This class provides routines to manipulate block sparse matrices stored in a
+  * BSR-like representation. There are two main types :
+  *
+  * 1. All blocks have the same number of rows and columns, called block size
+  * in the following. In this case, if this block size is known at compile time,
+  * it can be given as a template parameter like
+  * \code
+  * BlockSparseMatrix<Scalar, 3, ColMajor> bmat(b_rows, b_cols);
+  * \endcode
+  * Here, bmat is a b_rows x b_cols block sparse matrix
+  * where each coefficient is a 3x3 dense matrix.
+  * If the block size is fixed but will be given at runtime,
+  * \code
+  * BlockSparseMatrix<Scalar, Dynamic, ColMajor> bmat(b_rows, b_cols);
+  * bmat.setBlockSize(block_size);
+  * \endcode
+  *
+  * 2. The second case is for variable-block sparse matrices.
+  * Here each block has its own dimensions. The only restriction is that all the blocks
+  * in a row (resp. a column) should have the same number of rows (resp. of columns).
+  * It is thus required in this case to describe the layout of the matrix by calling
+  * setBlockLayout(rowBlocks, colBlocks).
+  *
+  * In any of the previous case, the matrix can be filled by calling setFromTriplets().
+  * A regular sparse matrix can be converted to a block sparse matrix and vice versa.
+  * It is obviously required to describe the block layout beforehand by calling either
+  * setBlockSize() for fixed-size blocks or setBlockLayout for variable-size blocks.
+  *
+  * \tparam _Scalar The Scalar type
+  * \tparam _BlockAtCompileTime The block layout option. It takes the following values
+  * Dynamic : block size known at runtime
+  * a numeric number : fixed-size block known at compile time
+  */
+template<typename _Scalar, int _BlockAtCompileTime=Dynamic, int _Options=ColMajor, typename _StorageIndex=int> class BlockSparseMatrix;
+
+template<typename BlockSparseMatrixT> class BlockSparseMatrixView;
+
+namespace internal {
+template<typename _Scalar, int _BlockAtCompileTime, int _Options, typename _Index>
+struct traits<BlockSparseMatrix<_Scalar,_BlockAtCompileTime,_Options, _Index> >
+{
+  typedef _Scalar Scalar;
+  typedef _Index Index;
+  typedef Sparse StorageKind; // FIXME Where is it used ??
+  typedef MatrixXpr XprKind;
+  enum {
+    RowsAtCompileTime = Dynamic,
+    ColsAtCompileTime = Dynamic,
+    MaxRowsAtCompileTime = Dynamic,
+    MaxColsAtCompileTime = Dynamic,
+    BlockSize = _BlockAtCompileTime,
+    Flags = _Options | NestByRefBit | LvalueBit,
+    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    SupportedAccessPatterns = InnerRandomAccessPattern
+  };
+};
+template<typename BlockSparseMatrixT>
+struct traits<BlockSparseMatrixView<BlockSparseMatrixT> >
+{
+  typedef Ref<Matrix<typename BlockSparseMatrixT::Scalar, BlockSparseMatrixT::BlockSize, BlockSparseMatrixT::BlockSize> > Scalar;
+  typedef Ref<Matrix<typename BlockSparseMatrixT::RealScalar, BlockSparseMatrixT::BlockSize, BlockSparseMatrixT::BlockSize> > RealScalar;
+
+};
+
+// Function object to sort a triplet list
+template<typename Iterator, bool IsColMajor>
+struct TripletComp
+{
+  typedef typename Iterator::value_type Triplet;
+  bool operator()(const Triplet& a, const Triplet& b)
+  { if(IsColMajor)
+      return ((a.col() == b.col() && a.row() < b.row()) || (a.col() < b.col()));
+    else
+      return ((a.row() == b.row() && a.col() < b.col()) || (a.row() < b.row()));
+  }
+};
+} // end namespace internal
+
+
+/* Proxy to view the block sparse matrix as a regular sparse matrix */
+template<typename BlockSparseMatrixT>
+class BlockSparseMatrixView : public SparseMatrixBase<BlockSparseMatrixT>
+{
+  public:
+    typedef Ref<typename BlockSparseMatrixT::BlockScalar> Scalar;
+    typedef Ref<typename BlockSparseMatrixT::BlockRealScalar> RealScalar;
+    typedef typename BlockSparseMatrixT::Index Index;
+    typedef  BlockSparseMatrixT Nested;
+    enum {
+      Flags = BlockSparseMatrixT::Options,
+      Options = BlockSparseMatrixT::Options,
+      RowsAtCompileTime = BlockSparseMatrixT::RowsAtCompileTime,
+      ColsAtCompileTime = BlockSparseMatrixT::ColsAtCompileTime,
+      MaxColsAtCompileTime = BlockSparseMatrixT::MaxColsAtCompileTime,
+      MaxRowsAtCompileTime = BlockSparseMatrixT::MaxRowsAtCompileTime
+    };
+  public:
+    BlockSparseMatrixView(const BlockSparseMatrixT& spblockmat)
+     : m_spblockmat(spblockmat)
+    {}
+
+    Index outerSize() const
+    {
+      return (Flags&RowMajorBit) == 1 ? this->rows() : this->cols();
+    }
+    Index cols() const
+    {
+      return m_spblockmat.blockCols();
+    }
+    Index rows() const
+    {
+      return m_spblockmat.blockRows();
+    }
+    Scalar coeff(Index row, Index col)
+    {
+      return m_spblockmat.coeff(row, col);
+    }
+    Scalar coeffRef(Index row, Index col)
+    {
+      return m_spblockmat.coeffRef(row, col);
+    }
+    // Wrapper to iterate over all blocks
+    class InnerIterator : public BlockSparseMatrixT::BlockInnerIterator
+    {
+      public:
+      InnerIterator(const BlockSparseMatrixView& mat, Index outer)
+          : BlockSparseMatrixT::BlockInnerIterator(mat.m_spblockmat, outer)
+      {}
+
+    };
+
+  protected:
+    const BlockSparseMatrixT& m_spblockmat;
+};
+
+// Proxy to view a regular vector as a block vector
+template<typename BlockSparseMatrixT, typename VectorType>
+class BlockVectorView
+{
+  public:
+    enum {
+      BlockSize = BlockSparseMatrixT::BlockSize,
+      ColsAtCompileTime = VectorType::ColsAtCompileTime,
+      RowsAtCompileTime = VectorType::RowsAtCompileTime,
+      Flags = VectorType::Flags
+    };
+    typedef Ref<const Matrix<typename BlockSparseMatrixT::Scalar, (RowsAtCompileTime==1)? 1 : BlockSize, (ColsAtCompileTime==1)? 1 : BlockSize> >Scalar;
+    typedef typename BlockSparseMatrixT::Index Index;
+  public:
+    BlockVectorView(const BlockSparseMatrixT& spblockmat, const VectorType& vec)
+    : m_spblockmat(spblockmat),m_vec(vec)
+    { }
+    inline Index cols() const
+    {
+      return m_vec.cols();
+    }
+    inline Index size() const
+    {
+      return m_spblockmat.blockRows();
+    }
+    inline Scalar coeff(Index bi) const
+    {
+      Index startRow = m_spblockmat.blockRowsIndex(bi);
+      Index rowSize = m_spblockmat.blockRowsIndex(bi+1) - startRow;
+      return m_vec.middleRows(startRow, rowSize);
+    }
+    inline Scalar coeff(Index bi, Index j) const
+    {
+      Index startRow = m_spblockmat.blockRowsIndex(bi);
+      Index rowSize = m_spblockmat.blockRowsIndex(bi+1) - startRow;
+      return m_vec.block(startRow, j, rowSize, 1);
+    }
+  protected:
+    const BlockSparseMatrixT& m_spblockmat;
+    const VectorType& m_vec;
+};
+
+template<typename VectorType, typename Index> class BlockVectorReturn;
+
+
+// Proxy to view a regular vector as a block vector
+template<typename BlockSparseMatrixT, typename VectorType>
+class BlockVectorReturn
+{
+  public:
+    enum {
+      ColsAtCompileTime = VectorType::ColsAtCompileTime,
+      RowsAtCompileTime = VectorType::RowsAtCompileTime,
+      Flags = VectorType::Flags
+    };
+    typedef Ref<Matrix<typename VectorType::Scalar, RowsAtCompileTime, ColsAtCompileTime> > Scalar;
+    typedef typename BlockSparseMatrixT::Index Index;
+  public:
+    BlockVectorReturn(const BlockSparseMatrixT& spblockmat, VectorType& vec)
+    : m_spblockmat(spblockmat),m_vec(vec)
+    { }
+    inline Index size() const
+    {
+      return m_spblockmat.blockRows();
+    }
+    inline Scalar coeffRef(Index bi)
+    {
+      Index startRow = m_spblockmat.blockRowsIndex(bi);
+      Index rowSize = m_spblockmat.blockRowsIndex(bi+1) - startRow;
+      return m_vec.middleRows(startRow, rowSize);
+    }
+    inline Scalar coeffRef(Index bi, Index j)
+    {
+      Index startRow = m_spblockmat.blockRowsIndex(bi);
+      Index rowSize = m_spblockmat.blockRowsIndex(bi+1) - startRow;
+      return m_vec.block(startRow, j, rowSize, 1);
+    }
+
+  protected:
+    const BlockSparseMatrixT& m_spblockmat;
+    VectorType& m_vec;
+};
+
+// Block version of the sparse dense product
+template<typename Lhs, typename Rhs>
+class BlockSparseTimeDenseProduct;
+
+namespace internal {
+
+template<typename BlockSparseMatrixT, typename VecType>
+struct traits<BlockSparseTimeDenseProduct<BlockSparseMatrixT, VecType> >
+{
+  typedef Dense StorageKind;
+  typedef MatrixXpr XprKind;
+  typedef typename BlockSparseMatrixT::Scalar Scalar;
+  typedef typename BlockSparseMatrixT::Index Index;
+  enum {
+    RowsAtCompileTime = Dynamic,
+    ColsAtCompileTime = Dynamic,
+    MaxRowsAtCompileTime = Dynamic,
+    MaxColsAtCompileTime = Dynamic,
+    Flags = 0,
+    CoeffReadCost = internal::traits<BlockSparseMatrixT>::CoeffReadCost
+  };
+};
+} // end namespace internal
+
+template<typename Lhs, typename Rhs>
+class BlockSparseTimeDenseProduct
+  : public ProductBase<BlockSparseTimeDenseProduct<Lhs,Rhs>, Lhs, Rhs>
+{
+  public:
+    EIGEN_PRODUCT_PUBLIC_INTERFACE(BlockSparseTimeDenseProduct)
+
+    BlockSparseTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+    {}
+
+    template<typename Dest> void scaleAndAddTo(Dest& dest, const typename Rhs::Scalar& alpha) const
+    {
+      BlockVectorReturn<Lhs,Dest> tmpDest(m_lhs, dest);
+      internal::sparse_time_dense_product( BlockSparseMatrixView<Lhs>(m_lhs),  BlockVectorView<Lhs, Rhs>(m_lhs, m_rhs), tmpDest, alpha);
+    }
+
+  private:
+    BlockSparseTimeDenseProduct& operator=(const BlockSparseTimeDenseProduct&);
+};
+
+template<typename _Scalar, int _BlockAtCompileTime, int _Options, typename _StorageIndex>
+class BlockSparseMatrix : public SparseMatrixBase<BlockSparseMatrix<_Scalar,_BlockAtCompileTime, _Options,_StorageIndex> >
+{
+  public:
+    typedef _Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef _StorageIndex StorageIndex;
+    typedef typename internal::ref_selector<BlockSparseMatrix<_Scalar, _BlockAtCompileTime, _Options, _StorageIndex> >::type Nested;
+
+    enum {
+      Options = _Options,
+      Flags = Options,
+      BlockSize=_BlockAtCompileTime,
+      RowsAtCompileTime = Dynamic,
+      ColsAtCompileTime = Dynamic,
+      MaxRowsAtCompileTime = Dynamic,
+      MaxColsAtCompileTime = Dynamic,
+      IsVectorAtCompileTime = 0,
+      IsColMajor = Flags&RowMajorBit ? 0 : 1
+    };
+    typedef Matrix<Scalar, _BlockAtCompileTime, _BlockAtCompileTime,IsColMajor ? ColMajor : RowMajor> BlockScalar;
+    typedef Matrix<RealScalar, _BlockAtCompileTime, _BlockAtCompileTime,IsColMajor ? ColMajor : RowMajor> BlockRealScalar;
+    typedef typename internal::conditional<_BlockAtCompileTime==Dynamic, Scalar, BlockScalar>::type BlockScalarReturnType;
+    typedef BlockSparseMatrix<Scalar, BlockSize, IsColMajor ? ColMajor : RowMajor, StorageIndex> PlainObject;
+  public:
+    // Default constructor
+    BlockSparseMatrix()
+    : m_innerBSize(0),m_outerBSize(0),m_innerOffset(0),m_outerOffset(0),
+      m_nonzerosblocks(0),m_values(0),m_blockPtr(0),m_indices(0),
+      m_outerIndex(0),m_blockSize(BlockSize)
+    { }
+
+
+    /**
+     * \brief Construct and resize
+     *
+     */
+    BlockSparseMatrix(Index brow, Index bcol)
+      : m_innerBSize(IsColMajor ? brow : bcol),
+        m_outerBSize(IsColMajor ? bcol : brow),
+        m_innerOffset(0),m_outerOffset(0),m_nonzerosblocks(0),
+        m_values(0),m_blockPtr(0),m_indices(0),
+        m_outerIndex(0),m_blockSize(BlockSize)
+    { }
+
+    /**
+     * \brief Copy-constructor
+     */
+    BlockSparseMatrix(const BlockSparseMatrix& other)
+      : m_innerBSize(other.m_innerBSize),m_outerBSize(other.m_outerBSize),
+        m_nonzerosblocks(other.m_nonzerosblocks),m_nonzeros(other.m_nonzeros),
+        m_blockPtr(0),m_blockSize(other.m_blockSize)
+    {
+      // should we allow copying between variable-size blocks and fixed-size blocks ??
+      eigen_assert(m_blockSize == BlockSize && " CAN NOT COPY BETWEEN FIXED-SIZE AND VARIABLE-SIZE BLOCKS");
+
+      std::copy(other.m_innerOffset, other.m_innerOffset+m_innerBSize+1, m_innerOffset);
+      std::copy(other.m_outerOffset, other.m_outerOffset+m_outerBSize+1, m_outerOffset);
+      std::copy(other.m_values, other.m_values+m_nonzeros, m_values);
+
+      if(m_blockSize != Dynamic)
+        std::copy(other.m_blockPtr, other.m_blockPtr+m_nonzerosblocks, m_blockPtr);
+
+      std::copy(other.m_indices, other.m_indices+m_nonzerosblocks, m_indices);
+      std::copy(other.m_outerIndex, other.m_outerIndex+m_outerBSize, m_outerIndex);
+    }
+
+    friend void swap(BlockSparseMatrix& first, BlockSparseMatrix& second)
+    {
+      std::swap(first.m_innerBSize, second.m_innerBSize);
+      std::swap(first.m_outerBSize, second.m_outerBSize);
+      std::swap(first.m_innerOffset, second.m_innerOffset);
+      std::swap(first.m_outerOffset, second.m_outerOffset);
+      std::swap(first.m_nonzerosblocks, second.m_nonzerosblocks);
+      std::swap(first.m_nonzeros, second.m_nonzeros);
+      std::swap(first.m_values, second.m_values);
+      std::swap(first.m_blockPtr, second.m_blockPtr);
+      std::swap(first.m_indices, second.m_indices);
+      std::swap(first.m_outerIndex, second.m_outerIndex);
+      std::swap(first.m_BlockSize, second.m_blockSize);
+    }
+
+    BlockSparseMatrix& operator=(BlockSparseMatrix other)
+    {
+      //Copy-and-swap paradigm ... avoid leaked data if thrown
+      swap(*this, other);
+      return *this;
+    }
+
+    // Destructor
+    ~BlockSparseMatrix()
+    {
+      delete[] m_outerIndex;
+      delete[] m_innerOffset;
+      delete[] m_outerOffset;
+      delete[] m_indices;
+      delete[] m_blockPtr;
+      delete[] m_values;
+    }
+
+
+    /**
+      * \brief Constructor from a sparse matrix
+      *
+      */
+    template<typename MatrixType>
+    inline BlockSparseMatrix(const MatrixType& spmat) : m_blockSize(BlockSize)
+    {
+      EIGEN_STATIC_ASSERT((m_blockSize != Dynamic), THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE);
+
+      *this = spmat;
+    }
+
+    /**
+      * \brief Assignment from a sparse matrix with the same storage order
+      *
+      * Convert from a sparse matrix to block sparse matrix.
+      * \warning Before calling this function, tt is necessary to call
+      * either setBlockLayout() (matrices with variable-size blocks)
+      * or setBlockSize() (for fixed-size blocks).
+      */
+    template<typename MatrixType>
+    inline BlockSparseMatrix& operator=(const MatrixType& spmat)
+    {
+      eigen_assert((m_innerBSize != 0 && m_outerBSize != 0)
+                   && "Trying to assign to a zero-size matrix, call resize() first");
+      eigen_assert(((MatrixType::Options&RowMajorBit) != IsColMajor) && "Wrong storage order");
+      typedef SparseMatrix<bool,MatrixType::Options,typename MatrixType::Index> MatrixPatternType;
+      MatrixPatternType  blockPattern(blockRows(), blockCols());
+      m_nonzeros = 0;
+
+      // First, compute the number of nonzero blocks and their locations
+      for(StorageIndex bj = 0; bj < m_outerBSize; ++bj)
+      {
+        // Browse each outer block and compute the structure
+        std::vector<bool> nzblocksFlag(m_innerBSize,false);  // Record the existing blocks
+        blockPattern.startVec(bj);
+        for(StorageIndex j = blockOuterIndex(bj); j < blockOuterIndex(bj+1); ++j)
+        {
+          typename MatrixType::InnerIterator it_spmat(spmat, j);
+          for(; it_spmat; ++it_spmat)
+          {
+            StorageIndex bi = innerToBlock(it_spmat.index()); // Index of the current nonzero block
+            if(!nzblocksFlag[bi])
+            {
+              // Save the index of this nonzero block
+              nzblocksFlag[bi] = true;
+              blockPattern.insertBackByOuterInnerUnordered(bj, bi) = true;
+              // Compute the total number of nonzeros (including explicit zeros in blocks)
+              m_nonzeros += blockOuterSize(bj) * blockInnerSize(bi);
+            }
+          }
+        } // end current outer block
+      }
+      blockPattern.finalize();
+
+      // Allocate the internal arrays
+      setBlockStructure(blockPattern);
+
+      for(StorageIndex nz = 0; nz < m_nonzeros; ++nz) m_values[nz] = Scalar(0);
+      for(StorageIndex bj = 0; bj < m_outerBSize; ++bj)
+      {
+        // Now copy the values
+        for(StorageIndex j = blockOuterIndex(bj); j < blockOuterIndex(bj+1); ++j)
+        {
+          // Browse the outer block column by column (for column-major matrices)
+          typename MatrixType::InnerIterator it_spmat(spmat, j);
+          for(; it_spmat; ++it_spmat)
+          {
+            StorageIndex idx = 0; // Position of this block in the column block
+            StorageIndex bi = innerToBlock(it_spmat.index()); // Index of the current nonzero block
+            // Go to the inner block where this element belongs to
+            while(bi > m_indices[m_outerIndex[bj]+idx]) ++idx; // Not expensive for ordered blocks
+            StorageIndex idxVal;// Get the right position in the array of values for this element
+            if(m_blockSize == Dynamic)
+            {
+              // Offset from all blocks before ...
+              idxVal =  m_blockPtr[m_outerIndex[bj]+idx];
+              // ... and offset inside the block
+              idxVal += (j - blockOuterIndex(bj)) * blockOuterSize(bj) + it_spmat.index() - m_innerOffset[bi];
+            }
+            else
+            {
+              // All blocks before
+              idxVal = (m_outerIndex[bj] + idx) * m_blockSize * m_blockSize;
+              // inside the block
+              idxVal += (j - blockOuterIndex(bj)) * m_blockSize + (it_spmat.index()%m_blockSize);
+            }
+            // Insert the value
+            m_values[idxVal] = it_spmat.value();
+          } // end of this column
+        } // end of this block
+      } // end of this outer block
+
+      return *this;
+    }
+
+    /**
+      * \brief Set the nonzero block pattern of the matrix
+      *
+      * Given a sparse matrix describing the nonzero block pattern,
+      * this function prepares the internal pointers for values.
+      * After calling this function, any *nonzero* block (bi, bj) can be set
+      * with a simple call to coeffRef(bi,bj).
+      *
+      *
+      * \warning Before calling this function, tt is necessary to call
+      * either setBlockLayout() (matrices with variable-size blocks)
+      * or setBlockSize() (for fixed-size blocks).
+      *
+      * \param blockPattern Sparse matrix of boolean elements describing the block structure
+      *
+      * \sa setBlockLayout() \sa setBlockSize()
+      */
+    template<typename MatrixType>
+    void setBlockStructure(const MatrixType& blockPattern)
+    {
+      resize(blockPattern.rows(), blockPattern.cols());
+      reserve(blockPattern.nonZeros());
+
+      // Browse the block pattern and set up the various pointers
+      m_outerIndex[0] = 0;
+      if(m_blockSize == Dynamic) m_blockPtr[0] = 0;
+      for(StorageIndex nz = 0; nz < m_nonzeros; ++nz) m_values[nz] = Scalar(0);
+      for(StorageIndex bj = 0; bj < m_outerBSize; ++bj)
+      {
+        //Browse each outer block
+
+        //First, copy and save the indices of nonzero blocks
+        //FIXME : find a way to avoid this ...
+        std::vector<int> nzBlockIdx;
+        typename MatrixType::InnerIterator it(blockPattern, bj);
+        for(; it; ++it)
+        {
+          nzBlockIdx.push_back(it.index());
+        }
+        std::sort(nzBlockIdx.begin(), nzBlockIdx.end());
+
+        // Now, fill block indices and (eventually) pointers to blocks
+        for(StorageIndex idx = 0; idx < nzBlockIdx.size(); ++idx)
+        {
+          StorageIndex offset = m_outerIndex[bj]+idx; // offset in m_indices
+          m_indices[offset] = nzBlockIdx[idx];
+          if(m_blockSize == Dynamic)
+            m_blockPtr[offset] = m_blockPtr[offset-1] + blockInnerSize(nzBlockIdx[idx]) * blockOuterSize(bj);
+          // There is no blockPtr for fixed-size blocks... not needed !???
+        }
+        // Save the pointer to the next outer block
+        m_outerIndex[bj+1] = m_outerIndex[bj] + nzBlockIdx.size();
+      }
+    }
+
+    /**
+      * \brief Set the number of rows and columns blocks
+      */
+    inline void resize(Index brow, Index bcol)
+    {
+      m_innerBSize = IsColMajor ? brow : bcol;
+      m_outerBSize = IsColMajor ? bcol : brow;
+    }
+
+    /**
+      * \brief set the block size at runtime for fixed-size block layout
+      *
+      * Call this only for fixed-size blocks
+      */
+    inline void setBlockSize(Index blockSize)
+    {
+      m_blockSize = blockSize;
+    }
+
+    /**
+      * \brief Set the row and column block layouts,
+      *
+      * This function set the size of each row and column block.
+      * So this function should be used only for blocks with variable size.
+      * \param rowBlocks : Number of rows per row block
+      * \param colBlocks : Number of columns per column block
+      * \sa resize(), setBlockSize()
+      */
+    inline void setBlockLayout(const VectorXi& rowBlocks, const VectorXi& colBlocks)
+    {
+      const VectorXi& innerBlocks = IsColMajor ? rowBlocks : colBlocks;
+      const VectorXi& outerBlocks = IsColMajor ? colBlocks : rowBlocks;
+      eigen_assert(m_innerBSize == innerBlocks.size() && "CHECK THE NUMBER OF ROW OR COLUMN BLOCKS");
+      eigen_assert(m_outerBSize == outerBlocks.size() && "CHECK THE NUMBER OF ROW OR COLUMN BLOCKS");
+      m_outerBSize = outerBlocks.size();
+      //  starting index of blocks... cumulative sums
+      m_innerOffset = new StorageIndex[m_innerBSize+1];
+      m_outerOffset = new StorageIndex[m_outerBSize+1];
+      m_innerOffset[0] = 0;
+      m_outerOffset[0] = 0;
+      std::partial_sum(&innerBlocks[0], &innerBlocks[m_innerBSize-1]+1, &m_innerOffset[1]);
+      std::partial_sum(&outerBlocks[0], &outerBlocks[m_outerBSize-1]+1, &m_outerOffset[1]);
+
+      // Compute the total number of nonzeros
+      m_nonzeros = 0;
+      for(StorageIndex bj = 0; bj < m_outerBSize; ++bj)
+        for(StorageIndex bi = 0; bi < m_innerBSize; ++bi)
+          m_nonzeros += outerBlocks[bj] * innerBlocks[bi];
+
+    }
+
+    /**
+      * \brief Allocate the internal array of pointers to blocks and their inner indices
+      *
+      * \note For fixed-size blocks, call setBlockSize() to set the block.
+      * And For variable-size blocks, call setBlockLayout() before using this function
+      *
+      * \param nonzerosblocks Number of nonzero blocks. The total number of nonzeros is
+      * is computed in setBlockLayout() for variable-size blocks
+      * \sa setBlockSize()
+      */
+    inline void reserve(const Index nonzerosblocks)
+    {
+      eigen_assert((m_innerBSize != 0 && m_outerBSize != 0) &&
+          "TRYING TO RESERVE ZERO-SIZE MATRICES, CALL resize() first");
+
+      //FIXME Should free if already allocated
+      m_outerIndex = new StorageIndex[m_outerBSize+1];
+
+      m_nonzerosblocks = nonzerosblocks;
+      if(m_blockSize != Dynamic)
+      {
+        m_nonzeros = nonzerosblocks * (m_blockSize * m_blockSize);
+        m_blockPtr = 0;
+      }
+      else
+      {
+        // m_nonzeros  is already computed in setBlockLayout()
+        m_blockPtr = new StorageIndex[m_nonzerosblocks+1];
+      }
+      m_indices = new StorageIndex[m_nonzerosblocks+1];
+      m_values = new Scalar[m_nonzeros];
+    }
+
+
+    /**
+      * \brief Fill values in a matrix  from a triplet list.
+      *
+      * Each triplet item has a block stored in an Eigen dense matrix.
+      * The InputIterator class should provide the functions row(), col() and value()
+      *
+      * \note For fixed-size blocks, call setBlockSize() before this function.
+      *
+      * FIXME Do not accept duplicates
+      */
+    template<typename InputIterator>
+    void setFromTriplets(const InputIterator& begin, const InputIterator& end)
+    {
+      eigen_assert((m_innerBSize!=0 && m_outerBSize !=0) && "ZERO BLOCKS, PLEASE CALL resize() before");
+
+      /* First, sort the triplet list
+        * FIXME This can be unnecessarily expensive since only the inner indices have to be sorted
+        * The best approach is like in SparseMatrix::setFromTriplets()
+        */
+      internal::TripletComp<InputIterator, IsColMajor> tripletcomp;
+      std::sort(begin, end, tripletcomp);
+
+      /* Count the number of rows and column blocks,
+       * and the number of nonzero blocks per outer dimension
+       */
+      VectorXi rowBlocks(m_innerBSize); // Size of each block row
+      VectorXi colBlocks(m_outerBSize); // Size of each block column
+      rowBlocks.setZero(); colBlocks.setZero();
+      VectorXi nzblock_outer(m_outerBSize); // Number of nz blocks per outer vector
+      VectorXi nz_outer(m_outerBSize); // Number of nz per outer vector...for variable-size blocks
+      nzblock_outer.setZero();
+      nz_outer.setZero();
+      for(InputIterator it(begin); it !=end; ++it)
+      {
+        eigen_assert(it->row() >= 0 && it->row() < this->blockRows() && it->col() >= 0 && it->col() < this->blockCols());
+        eigen_assert((it->value().rows() == it->value().cols() && (it->value().rows() == m_blockSize))
+                     || (m_blockSize == Dynamic));
+
+        if(m_blockSize == Dynamic)
+        {
+          eigen_assert((rowBlocks[it->row()] == 0 || rowBlocks[it->row()] == it->value().rows()) &&
+              "NON CORRESPONDING SIZES FOR ROW BLOCKS");
+          eigen_assert((colBlocks[it->col()] == 0 || colBlocks[it->col()] == it->value().cols()) &&
+              "NON CORRESPONDING SIZES FOR COLUMN BLOCKS");
+          rowBlocks[it->row()] =it->value().rows();
+          colBlocks[it->col()] = it->value().cols();
+        }
+        nz_outer(IsColMajor ? it->col() : it->row()) += it->value().rows() * it->value().cols();
+        nzblock_outer(IsColMajor ? it->col() : it->row())++;
+      }
+      // Allocate member arrays
+      if(m_blockSize == Dynamic) setBlockLayout(rowBlocks, colBlocks);
+      StorageIndex nzblocks = nzblock_outer.sum();
+      reserve(nzblocks);
+
+       // Temporary markers
+      VectorXi block_id(m_outerBSize); // To be used as a block marker during insertion
+
+      // Setup outer index pointers and markers
+      m_outerIndex[0] = 0;
+      if (m_blockSize == Dynamic)  m_blockPtr[0] =  0;
+      for(StorageIndex bj = 0; bj < m_outerBSize; ++bj)
+      {
+        m_outerIndex[bj+1] = m_outerIndex[bj] + nzblock_outer(bj);
+        block_id(bj) = m_outerIndex[bj];
+        if(m_blockSize==Dynamic)
+        {
+          m_blockPtr[m_outerIndex[bj+1]] = m_blockPtr[m_outerIndex[bj]] + nz_outer(bj);
+        }
+      }
+
+      // Fill the matrix
+      for(InputIterator it(begin); it!=end; ++it)
+      {
+        StorageIndex outer = IsColMajor ? it->col() : it->row();
+        StorageIndex inner = IsColMajor ? it->row() : it->col();
+        m_indices[block_id(outer)] = inner;
+        StorageIndex block_size = it->value().rows()*it->value().cols();
+        StorageIndex nz_marker = blockPtr(block_id[outer]);
+        memcpy(&(m_values[nz_marker]), it->value().data(), block_size * sizeof(Scalar));
+        if(m_blockSize == Dynamic)
+        {
+          m_blockPtr[block_id(outer)+1] = m_blockPtr[block_id(outer)] + block_size;
+        }
+        block_id(outer)++;
+      }
+
+      // An alternative when the outer indices are sorted...no need to use an array of markers
+//      for(Index bcol = 0; bcol < m_outerBSize; ++bcol)
+//      {
+//      Index id = 0, id_nz = 0, id_nzblock = 0;
+//      for(InputIterator it(begin); it!=end; ++it)
+//      {
+//        while (id<bcol) // one pass should do the job unless there are empty columns
+//        {
+//          id++;
+//          m_outerIndex[id+1]=m_outerIndex[id];
+//        }
+//        m_outerIndex[id+1] += 1;
+//        m_indices[id_nzblock]=brow;
+//        Index block_size = it->value().rows()*it->value().cols();
+//        m_blockPtr[id_nzblock+1] = m_blockPtr[id_nzblock] + block_size;
+//        id_nzblock++;
+//        memcpy(&(m_values[id_nz]),it->value().data(), block_size*sizeof(Scalar));
+//        id_nz += block_size;
+//      }
+//      while(id < m_outerBSize-1) // Empty columns at the end
+//      {
+//        id++;
+//        m_outerIndex[id+1]=m_outerIndex[id];
+//      }
+//      }
+    }
+
+
+    /**
+      * \returns the number of rows
+      */
+    inline Index rows() const
+    {
+//      return blockRows();
+      return (IsColMajor ? innerSize() : outerSize());
+    }
+
+    /**
+      * \returns the number of cols
+      */
+    inline Index cols() const
+    {
+//      return blockCols();
+      return (IsColMajor ? outerSize() : innerSize());
+    }
+
+    inline Index innerSize() const
+    {
+      if(m_blockSize == Dynamic) return m_innerOffset[m_innerBSize];
+      else return  (m_innerBSize * m_blockSize) ;
+    }
+
+    inline Index outerSize() const
+    {
+      if(m_blockSize == Dynamic) return m_outerOffset[m_outerBSize];
+      else return  (m_outerBSize * m_blockSize) ;
+    }
+    /** \returns the number of rows grouped by blocks */
+    inline Index blockRows() const
+    {
+      return (IsColMajor ? m_innerBSize : m_outerBSize);
+    }
+    /** \returns the number of columns grouped by blocks */
+    inline Index blockCols() const
+    {
+      return (IsColMajor ? m_outerBSize : m_innerBSize);
+    }
+
+    inline Index outerBlocks() const { return m_outerBSize; }
+    inline Index innerBlocks() const { return m_innerBSize; }
+
+    /** \returns the block index where outer belongs to */
+    inline Index outerToBlock(Index outer) const
+    {
+      eigen_assert(outer < outerSize() && "OUTER INDEX OUT OF BOUNDS");
+
+      if(m_blockSize != Dynamic)
+        return (outer / m_blockSize); // Integer division
+
+      StorageIndex b_outer = 0;
+      while(m_outerOffset[b_outer] <= outer) ++b_outer;
+      return b_outer - 1;
+    }
+    /** \returns  the block index where inner belongs to */
+    inline Index innerToBlock(Index inner) const
+    {
+      eigen_assert(inner < innerSize() && "OUTER INDEX OUT OF BOUNDS");
+
+      if(m_blockSize != Dynamic)
+        return (inner / m_blockSize); // Integer division
+
+      StorageIndex b_inner = 0;
+      while(m_innerOffset[b_inner] <= inner) ++b_inner;
+      return b_inner - 1;
+    }
+
+    /**
+      *\returns a reference to the (i,j) block as an Eigen Dense Matrix
+      */
+    Ref<BlockScalar> coeffRef(Index brow, Index bcol)
+    {
+      eigen_assert(brow < blockRows() && "BLOCK ROW INDEX OUT OF BOUNDS");
+      eigen_assert(bcol < blockCols() && "BLOCK nzblocksFlagCOLUMN OUT OF BOUNDS");
+
+      StorageIndex rsize = IsColMajor ? blockInnerSize(brow): blockOuterSize(bcol);
+      StorageIndex csize = IsColMajor ? blockOuterSize(bcol) : blockInnerSize(brow);
+      StorageIndex inner = IsColMajor ? brow : bcol;
+      StorageIndex outer = IsColMajor ? bcol : brow;
+      StorageIndex offset = m_outerIndex[outer];
+      while(offset < m_outerIndex[outer+1] && m_indices[offset] != inner)
+        offset++;
+      if(m_indices[offset] == inner)
+      {
+        return Map<BlockScalar>(&(m_values[blockPtr(offset)]), rsize, csize);
+      }
+      else
+      {
+        //FIXME the block does not exist, Insert it !!!!!!!!!
+        eigen_assert("DYNAMIC INSERTION IS NOT YET SUPPORTED");
+      }
+    }
+
+    /**
+      * \returns the value of the (i,j) block as an Eigen Dense Matrix
+      */
+    Map<const BlockScalar> coeff(Index brow, Index bcol) const
+    {
+      eigen_assert(brow < blockRows() && "BLOCK ROW INDEX OUT OF BOUNDS");
+      eigen_assert(bcol < blockCols() && "BLOCK COLUMN OUT OF BOUNDS");
+
+      StorageIndex rsize = IsColMajor ? blockInnerSize(brow): blockOuterSize(bcol);
+      StorageIndex csize = IsColMajor ? blockOuterSize(bcol) : blockInnerSize(brow);
+      StorageIndex inner = IsColMajor ? brow : bcol;
+      StorageIndex outer = IsColMajor ? bcol : brow;
+      StorageIndex offset = m_outerIndex[outer];
+      while(offset < m_outerIndex[outer+1] && m_indices[offset] != inner) offset++;
+      if(m_indices[offset] == inner)
+      {
+        return Map<const BlockScalar> (&(m_values[blockPtr(offset)]), rsize, csize);
+      }
+      else
+//        return BlockScalar::Zero(rsize, csize);
+        eigen_assert("NOT YET SUPPORTED");
+    }
+
+    // Block Matrix times vector product
+    template<typename VecType>
+    BlockSparseTimeDenseProduct<BlockSparseMatrix, VecType> operator*(const VecType& lhs) const
+    {
+      return BlockSparseTimeDenseProduct<BlockSparseMatrix, VecType>(*this, lhs);
+    }
+
+    /** \returns the number of nonzero blocks */
+    inline Index nonZerosBlocks() const { return m_nonzerosblocks; }
+    /** \returns the total number of nonzero elements, including eventual explicit zeros in blocks */
+    inline Index nonZeros() const { return m_nonzeros; }
+
+    inline BlockScalarReturnType *valuePtr() {return static_cast<BlockScalarReturnType *>(m_values);}
+//    inline Scalar *valuePtr(){ return m_values; }
+    inline StorageIndex *innerIndexPtr() {return m_indices; }
+    inline const StorageIndex *innerIndexPtr() const {return m_indices; }
+    inline StorageIndex *outerIndexPtr() {return m_outerIndex; }
+    inline const StorageIndex* outerIndexPtr() const {return m_outerIndex; }
+
+    /** \brief for compatibility purposes with the SparseMatrix class */
+    inline bool isCompressed() const {return true;}
+    /**
+      * \returns the starting index of the bi row block
+      */
+    inline Index blockRowsIndex(Index bi) const
+    {
+      return IsColMajor ? blockInnerIndex(bi) : blockOuterIndex(bi);
+    }
+
+    /**
+      * \returns the starting index of the bj col block
+      */
+    inline Index blockColsIndex(Index bj) const
+    {
+      return IsColMajor ? blockOuterIndex(bj) : blockInnerIndex(bj);
+    }
+
+    inline Index blockOuterIndex(Index bj) const
+    {
+      return (m_blockSize == Dynamic) ? m_outerOffset[bj] : (bj * m_blockSize);
+    }
+    inline Index blockInnerIndex(Index bi) const
+    {
+      return (m_blockSize == Dynamic) ? m_innerOffset[bi] : (bi * m_blockSize);
+    }
+
+    // Not needed ???
+    inline Index blockInnerSize(Index bi) const
+    {
+      return (m_blockSize == Dynamic) ? (m_innerOffset[bi+1] - m_innerOffset[bi]) : m_blockSize;
+    }
+    inline Index blockOuterSize(Index bj) const
+    {
+      return (m_blockSize == Dynamic) ? (m_outerOffset[bj+1]- m_outerOffset[bj]) : m_blockSize;
+    }
+
+    /**
+      * \brief Browse the matrix by outer index
+      */
+    class InnerIterator; // Browse column by column
+
+    /**
+      * \brief Browse the matrix by block outer index
+      */
+    class BlockInnerIterator; // Browse block by block
+
+    friend std::ostream & operator << (std::ostream & s, const BlockSparseMatrix& m)
+    {
+      for (StorageIndex j = 0; j < m.outerBlocks(); ++j)
+      {
+        BlockInnerIterator itb(m, j);
+        for(; itb; ++itb)
+        {
+          s << "("<<itb.row() << ", " << itb.col() << ")\n";
+          s << itb.value() <<"\n";
+        }
+      }
+      s << std::endl;
+      return s;
+    }
+
+    /**
+      * \returns the starting position of the block <id> in the array of values
+      */
+    Index blockPtr(Index id) const
+    {
+      if(m_blockSize == Dynamic) return m_blockPtr[id];
+      else return id * m_blockSize * m_blockSize;
+      //return blockDynIdx(id, typename internal::conditional<(BlockSize==Dynamic), internal::true_type, internal::false_type>::type());
+    }
+
+
+  protected:
+//    inline Index blockDynIdx(Index id, internal::true_type) const
+//    {
+//      return m_blockPtr[id];
+//    }
+//    inline Index blockDynIdx(Index id, internal::false_type) const
+//    {
+//      return id * BlockSize * BlockSize;
+//    }
+
+    // To be implemented
+    // Insert a block at a particular location... need to make a room for that
+    Map<BlockScalar> insert(Index brow, Index bcol);
+
+    Index m_innerBSize; // Number of block rows
+    Index m_outerBSize; // Number of block columns
+    StorageIndex *m_innerOffset; // Starting index of each inner block (size m_innerBSize+1)
+    StorageIndex *m_outerOffset; // Starting index of each outer block (size m_outerBSize+1)
+    Index m_nonzerosblocks; // Total nonzeros blocks (lower than  m_innerBSize x m_outerBSize)
+    Index m_nonzeros; // Total nonzeros elements
+    Scalar *m_values; //Values stored block column after block column (size m_nonzeros)
+    StorageIndex *m_blockPtr; // Pointer to the beginning of each block in m_values, size m_nonzeroblocks ... null for fixed-size blocks
+    StorageIndex *m_indices; //Inner block indices, size m_nonzerosblocks ... OK
+    StorageIndex *m_outerIndex; // Starting pointer of each block column in m_indices (size m_outerBSize)... OK
+    Index m_blockSize; // Size of a block for fixed-size blocks, otherwise -1
+};
+
+template<typename _Scalar, int _BlockAtCompileTime, int _Options, typename _StorageIndex>
+class BlockSparseMatrix<_Scalar, _BlockAtCompileTime, _Options, _StorageIndex>::BlockInnerIterator
+{
+  public:
+
+    enum{
+      Flags = _Options
+    };
+
+    BlockInnerIterator(const BlockSparseMatrix& mat, const Index outer)
+    : m_mat(mat),m_outer(outer),
+      m_id(mat.m_outerIndex[outer]),
+      m_end(mat.m_outerIndex[outer+1])
+    {
+    }
+
+    inline BlockInnerIterator& operator++() {m_id++; return *this; }
+
+    inline const Map<const BlockScalar> value() const
+    {
+      return Map<const BlockScalar>(&(m_mat.m_values[m_mat.blockPtr(m_id)]),
+          rows(),cols());
+    }
+    inline Map<BlockScalar> valueRef()
+    {
+      return Map<BlockScalar>(&(m_mat.m_values[m_mat.blockPtr(m_id)]),
+          rows(),cols());
+    }
+    // Block inner index
+    inline Index index() const {return m_mat.m_indices[m_id]; }
+    inline Index outer() const { return m_outer; }
+    // block row index
+    inline Index row() const  {return index(); }
+    // block column index
+    inline Index col() const {return outer(); }
+    // FIXME Number of rows in the current block
+    inline Index rows() const { return (m_mat.m_blockSize==Dynamic) ? (m_mat.m_innerOffset[index()+1] - m_mat.m_innerOffset[index()]) : m_mat.m_blockSize; }
+    // Number of columns in the current block ...
+    inline Index cols() const { return (m_mat.m_blockSize==Dynamic) ? (m_mat.m_outerOffset[m_outer+1]-m_mat.m_outerOffset[m_outer]) : m_mat.m_blockSize;}
+    inline operator bool() const { return (m_id < m_end); }
+
+  protected:
+    const BlockSparseMatrix<_Scalar, _BlockAtCompileTime, _Options, StorageIndex>& m_mat;
+    const Index m_outer;
+    Index m_id;
+    Index m_end;
+};
+
+template<typename _Scalar, int _BlockAtCompileTime, int _Options, typename _StorageIndex>
+class BlockSparseMatrix<_Scalar, _BlockAtCompileTime, _Options, _StorageIndex>::InnerIterator
+{
+  public:
+    InnerIterator(const BlockSparseMatrix& mat, Index outer)
+    : m_mat(mat),m_outerB(mat.outerToBlock(outer)),m_outer(outer),
+      itb(mat, mat.outerToBlock(outer)),
+      m_offset(outer - mat.blockOuterIndex(m_outerB))
+     {
+        if (itb)
+        {
+          m_id = m_mat.blockInnerIndex(itb.index());
+          m_start = m_id;
+          m_end = m_mat.blockInnerIndex(itb.index()+1);
+        }
+     }
+    inline InnerIterator& operator++()
+    {
+      m_id++;
+      if (m_id >= m_end)
+      {
+        ++itb;
+        if (itb)
+        {
+          m_id = m_mat.blockInnerIndex(itb.index());
+          m_start = m_id;
+          m_end = m_mat.blockInnerIndex(itb.index()+1);
+        }
+      }
+      return *this;
+    }
+    inline const Scalar& value() const
+    {
+      return itb.value().coeff(m_id - m_start, m_offset);
+    }
+    inline Scalar& valueRef()
+    {
+      return itb.valueRef().coeff(m_id - m_start, m_offset);
+    }
+    inline Index index() const { return m_id; }
+    inline Index outer() const {return m_outer; }
+    inline Index col() const {return outer(); }
+    inline Index row() const { return index();}
+    inline operator bool() const
+    {
+      return itb;
+    }
+  protected:
+    const BlockSparseMatrix& m_mat;
+    const Index m_outer;
+    const Index m_outerB;
+    BlockInnerIterator itb; // Iterator through the blocks
+    const Index m_offset; // Position of this column in the block
+    Index m_start; // starting inner index of this block
+    Index m_id; // current inner index in the block
+    Index m_end; // starting inner index of the next block
+
+};
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSEBLOCKMATRIX_H

DELETED 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_SparseExtra_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_SparseExtra_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/SparseExtra COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
@@ -31,15 +31,15 @@
   *
   * \see SparseMatrix
   */
 
 namespace internal {
-template<typename _Scalar, int _Options, typename _Index>
-struct traits<DynamicSparseMatrix<_Scalar, _Options, _Index> >
+template<typename _Scalar, int _Options, typename _StorageIndex>
+struct traits<DynamicSparseMatrix<_Scalar, _Options, _StorageIndex> >
 {
   typedef _Scalar Scalar;
-  typedef _Index Index;
+  typedef _StorageIndex StorageIndex;
   typedef Sparse StorageKind;
   typedef MatrixXpr XprKind;
   enum {
     RowsAtCompileTime = Dynamic,
     ColsAtCompileTime = Dynamic,
@@ -50,14 +50,16 @@
     SupportedAccessPatterns = OuterRandomAccessPattern
   };
 };
 }
 
-template<typename _Scalar, int _Options, typename _Index>
+template<typename _Scalar, int _Options, typename _StorageIndex>
  class  DynamicSparseMatrix
-  : public SparseMatrixBase<DynamicSparseMatrix<_Scalar, _Options, _Index> >
+  : public SparseMatrixBase<DynamicSparseMatrix<_Scalar, _Options, _StorageIndex> >
 {
+    typedef SparseMatrixBase<DynamicSparseMatrix> Base;
+    using Base::convert_index;
   public:
     EIGEN_SPARSE_PUBLIC_INTERFACE(DynamicSparseMatrix)
     // FIXME: why are these operator already alvailable ???
     // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, +=)
     // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, -=)
@@ -68,25 +70,25 @@
       Options = _Options
     };
 
   protected:
 
-    typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
+    typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0), StorageIndex> TransposedSparseMatrix;
 
     Index m_innerSize;
-    std::vector<internal::CompressedStorage<Scalar,Index> > m_data;
+    std::vector<internal::CompressedStorage<Scalar,StorageIndex> > m_data;
 
   public:
 
     inline Index rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
     inline Index cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
     inline Index innerSize() const { return m_innerSize; }
-    inline Index outerSize() const { return static_cast<Index>(m_data.size()); }
+    inline Index outerSize() const { return convert_index(m_data.size()); }
     inline Index innerNonZeros(Index j) const { return m_data[j].size(); }
 
-    std::vector<internal::CompressedStorage<Scalar,Index> >& _data() { return m_data; }
-    const std::vector<internal::CompressedStorage<Scalar,Index> >& _data() const { return m_data; }
+    std::vector<internal::CompressedStorage<Scalar,StorageIndex> >& _data() { return m_data; }
+    const std::vector<internal::CompressedStorage<Scalar,StorageIndex> >& _data() const { return m_data; }
 
     /** \returns the coefficient value at given position \a row, \a col
       * This operation involes a log(rho*outer_size) binary search.
       */
     inline Scalar coeff(Index row, Index col) const
@@ -119,11 +121,11 @@
     /** \returns the number of non zero coefficients */
     Index nonZeros() const
     {
       Index res = 0;
       for (Index j=0; j<outerSize(); ++j)
-        res += static_cast<Index>(m_data[j].size());
+        res += m_data[j].size();
       return res;
     }
 
 
 
@@ -195,11 +197,11 @@
     /** Resize the matrix without preserving the data (the matrix is set to zero)
       */
     void resize(Index rows, Index cols)
     {
       const Index outerSize = IsRowMajor ? rows : cols;
-      m_innerSize = IsRowMajor ? cols : rows;
+      m_innerSize = convert_index(IsRowMajor ? cols : rows);
       setZero();
       if (Index(m_data.size()) != outerSize)
       {
         m_data.resize(outerSize);
       }
@@ -318,40 +320,73 @@
 #   ifdef EIGEN_DYNAMICSPARSEMATRIX_PLUGIN
 #     include EIGEN_DYNAMICSPARSEMATRIX_PLUGIN
 #   endif
  };
 
-template<typename Scalar, int _Options, typename _Index>
-class DynamicSparseMatrix<Scalar,_Options,_Index>::InnerIterator : public SparseVector<Scalar,_Options,_Index>::InnerIterator
+template<typename Scalar, int _Options, typename _StorageIndex>
+class DynamicSparseMatrix<Scalar,_Options,_StorageIndex>::InnerIterator : public SparseVector<Scalar,_Options,_StorageIndex>::InnerIterator
 {
-    typedef typename SparseVector<Scalar,_Options,_Index>::InnerIterator Base;
+    typedef typename SparseVector<Scalar,_Options,_StorageIndex>::InnerIterator Base;
   public:
     InnerIterator(const DynamicSparseMatrix& mat, Index outer)
       : Base(mat.m_data[outer]), m_outer(outer)
     {}
 
     inline Index row() const { return IsRowMajor ? m_outer : Base::index(); }
     inline Index col() const { return IsRowMajor ? Base::index() : m_outer; }
+    inline Index outer() const { return m_outer; }
 
   protected:
     const Index m_outer;
 };
 
-template<typename Scalar, int _Options, typename _Index>
-class DynamicSparseMatrix<Scalar,_Options,_Index>::ReverseInnerIterator : public SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator
+template<typename Scalar, int _Options, typename _StorageIndex>
+class DynamicSparseMatrix<Scalar,_Options,_StorageIndex>::ReverseInnerIterator : public SparseVector<Scalar,_Options,_StorageIndex>::ReverseInnerIterator
 {
-    typedef typename SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator Base;
+    typedef typename SparseVector<Scalar,_Options,_StorageIndex>::ReverseInnerIterator Base;
   public:
     ReverseInnerIterator(const DynamicSparseMatrix& mat, Index outer)
       : Base(mat.m_data[outer]), m_outer(outer)
     {}
 
     inline Index row() const { return IsRowMajor ? m_outer : Base::index(); }
     inline Index col() const { return IsRowMajor ? Base::index() : m_outer; }
+    inline Index outer() const { return m_outer; }
 
   protected:
     const Index m_outer;
 };
+
+namespace internal {
+
+template<typename _Scalar, int _Options, typename _StorageIndex>
+struct evaluator<DynamicSparseMatrix<_Scalar,_Options,_StorageIndex> >
+  : evaluator_base<DynamicSparseMatrix<_Scalar,_Options,_StorageIndex> >
+{
+  typedef _Scalar Scalar;
+  typedef DynamicSparseMatrix<_Scalar,_Options,_StorageIndex> SparseMatrixType;
+  typedef typename SparseMatrixType::InnerIterator InnerIterator;
+  typedef typename SparseMatrixType::ReverseInnerIterator ReverseInnerIterator;
+  
+  enum {
+    CoeffReadCost = NumTraits<_Scalar>::ReadCost,
+    Flags = SparseMatrixType::Flags
+  };
+  
+  evaluator() : m_matrix(0) {}
+  evaluator(const SparseMatrixType &mat) : m_matrix(&mat) {}
+  
+  operator SparseMatrixType&() { return m_matrix->const_cast_derived(); }
+  operator const SparseMatrixType&() const { return *m_matrix; }
+  
+  Scalar coeff(Index row, Index col) const { return m_matrix->coeff(row,col); }
+  
+  Index nonZerosEstimate() const { return m_matrix->nonZeros(); }
+
+  const SparseMatrixType *m_matrix;
+};
+
+}
 
 } // end namespace Eigen
 
 #endif // EIGEN_DYNAMIC_SPARSEMATRIX_H

Index: 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/MarketIO.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/MarketIO.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/MarketIO.h
@@ -16,11 +16,11 @@
 namespace Eigen { 
 
 namespace internal 
 {
   template <typename Scalar>
-  inline bool GetMarketLine (std::stringstream& line, int& M, int& N, int& i, int& j, Scalar& value)
+  inline bool GetMarketLine (std::stringstream& line, Index& M, Index& N, Index& i, Index& j, Scalar& value)
   {
     line >> i >> j >> value;
     i--;
     j--;
     if(i>=0 && j>=0 && i<M && j<N)
@@ -29,11 +29,11 @@
     }
     else
       return false;
   }
   template <typename Scalar>
-  inline bool GetMarketLine (std::stringstream& line, int& M, int& N, int& i, int& j, std::complex<Scalar>& value)
+  inline bool GetMarketLine (std::stringstream& line, Index& M, Index& N, Index& i, Index& j, std::complex<Scalar>& value)
   {
     Scalar valR, valI;
     line >> i >> j >> valR >> valI;
     i--;
     j--;
@@ -131,24 +131,25 @@
   
 template<typename SparseMatrixType>
 bool loadMarket(SparseMatrixType& mat, const std::string& filename)
 {
   typedef typename SparseMatrixType::Scalar Scalar;
+  typedef typename SparseMatrixType::Index Index;
   std::ifstream input(filename.c_str(),std::ios::in);
   if(!input)
     return false;
   
   const int maxBuffersize = 2048;
   char buffer[maxBuffersize];
   
   bool readsizes = false;
 
-  typedef Triplet<Scalar,int> T;
+  typedef Triplet<Scalar,Index> T;
   std::vector<T> elements;
   
-  int M(-1), N(-1), NNZ(-1);
-  int count = 0;
+  Index M(-1), N(-1), NNZ(-1);
+  Index count = 0;
   while(input.getline(buffer, maxBuffersize))
   {
     // skip comments   
     //NOTE An appropriate test should be done on the header to get the  symmetry
     if(buffer[0]=='%')
@@ -160,18 +161,18 @@
     {
       line >> M >> N >> NNZ;
       if(M > 0 && N > 0 && NNZ > 0) 
       {
         readsizes = true;
-        std::cout << "sizes: " << M << "," << N << "," << NNZ << "\n";
+        //std::cout << "sizes: " << M << "," << N << "," << NNZ << "\n";
         mat.resize(M,N);
         mat.reserve(NNZ);
       }
     }
     else
     { 
-      int i(-1), j(-1);
+      Index i(-1), j(-1);
       Scalar value; 
       if( internal::GetMarketLine(line, M, N, i, j, value) ) 
       {
         ++ count;
         elements.push_back(T(i,j,value));
@@ -236,13 +237,13 @@
   out << mat.rows() << " " << mat.cols() << " " << mat.nonZeros() << "\n";
   int count = 0;
   for(int j=0; j<mat.outerSize(); ++j)
     for(typename SparseMatrixType::InnerIterator it(mat,j); it; ++it)
     {
-	++ count;
-	internal::PutMatrixElt(it.value(), it.row()+1, it.col()+1, out);
-	// out << it.row()+1 << " " << it.col()+1 << " " << it.value() << "\n";
+      ++ count;
+      internal::PutMatrixElt(it.value(), it.row()+1, it.col()+1, out);
+      // out << it.row()+1 << " " << it.col()+1 << " " << it.value() << "\n";
     }
   out.close();
   return true;
 }
 

Index: 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h
@@ -39,24 +39,22 @@
  * \tparam Scalar The scalar type 
  */
 template <typename Scalar>
 class MatrixMarketIterator 
 {
+    typedef typename NumTraits<Scalar>::Real RealScalar;
   public:
     typedef Matrix<Scalar,Dynamic,1> VectorType; 
     typedef SparseMatrix<Scalar,ColMajor> MatrixType; 
   
   public:
-    MatrixMarketIterator(const std::string folder):m_sym(0),m_isvalid(false),m_matIsLoaded(false),m_hasRhs(false),m_hasrefX(false),m_folder(folder)
+    MatrixMarketIterator(const std::string &folder)
+      : m_sym(0), m_isvalid(false), m_matIsLoaded(false), m_hasRhs(false), m_hasrefX(false), m_folder(folder)
     {
       m_folder_id = opendir(folder.c_str());
-      if (!m_folder_id){
-        m_isvalid = false;
-        std::cerr << "The provided Matrix folder could not be opened \n\n";
-        abort();
-      }
-      Getnextvalidmatrix();
+      if(m_folder_id)
+        Getnextvalidmatrix();
     }
     
     ~MatrixMarketIterator()
     {
       if (m_folder_id) closedir(m_folder_id); 
@@ -79,20 +77,34 @@
       if (m_matIsLoaded) return m_mat;
       
       std::string matrix_file = m_folder + "/" + m_matname + ".mtx";
       if ( !loadMarket(m_mat, matrix_file)) 
       {
+        std::cerr << "Warning loadMarket failed when loading \"" << matrix_file << "\"" << std::endl;
         m_matIsLoaded = false;
         return m_mat;
       }
       m_matIsLoaded = true; 
-      
+
       if (m_sym != NonSymmetric) 
-      { // Store the upper part of the matrix. It is needed by the solvers dealing with nonsymmetric matrices ??
-        MatrixType B; 
-        B = m_mat;
-        m_mat = B.template selfadjointView<Lower>();
+      {
+        // Check whether we need to restore a full matrix:
+        RealScalar diag_norm  = m_mat.diagonal().norm();
+        RealScalar lower_norm = m_mat.template triangularView<Lower>().norm();
+        RealScalar upper_norm = m_mat.template triangularView<Upper>().norm();
+        if(lower_norm>diag_norm && upper_norm==diag_norm)
+        {
+          // only the lower part is stored
+          MatrixType tmp(m_mat);
+          m_mat = tmp.template selfadjointView<Lower>();
+        }
+        else if(upper_norm>diag_norm && lower_norm==diag_norm)
+        {
+          // only the upper part is stored
+          MatrixType tmp(m_mat);
+          m_mat = tmp.template selfadjointView<Upper>();
+        }
       }
       return m_mat; 
     }
     
     /** Return the right hand side corresponding to the current matrix. 
@@ -141,19 +153,22 @@
       if (m_hasrefX)
       {
         m_refX.resize(m_mat.cols());
         m_hasrefX = loadMarketVector(m_refX, lhs_file);
       }
+      else
+        m_refX.resize(0);
       return m_refX; 
     }
     
     inline std::string& matname() { return m_matname; }
     
     inline int sym() { return m_sym; }
     
-    inline bool hasRhs() {return m_hasRhs; }
-    inline bool hasrefX() {return m_hasrefX; }
+    bool hasRhs() {return m_hasRhs; }
+    bool hasrefX() {return m_hasrefX; }
+    bool isFolderValid() { return bool(m_folder_id); }
     
   protected:
     
     inline bool Fileexists(std::string file)
     {

Index: 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h
@@ -93,14 +93,14 @@
 
 /** \class RandomSetter
   *
   * \brief The RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access
   *
-  * \param SparseMatrixType the type of the sparse matrix we are updating
-  * \param MapTraits a traits class representing the map implementation used for the temporary sparse storage.
+  * \tparam SparseMatrixType the type of the sparse matrix we are updating
+  * \tparam MapTraits a traits class representing the map implementation used for the temporary sparse storage.
   *                  Its default value depends on the system.
-  * \param OuterPacketBits defines the number of rows (or columns) manage by a single map object
+  * \tparam OuterPacketBits defines the number of rows (or columns) manage by a single map object
   *                        as a power of two exponent.
   *
   * This class temporarily represents a sparse matrix object using a generic map implementation allowing for
   * efficient random access. The conversion from the compressed representation to a hash_map object is performed
   * in the RandomSetter constructor, while the sparse matrix is updated back at destruction time. This strategy
@@ -152,11 +152,11 @@
 #endif
          ,int OuterPacketBits = 6>
 class RandomSetter
 {
     typedef typename SparseMatrixType::Scalar Scalar;
-    typedef typename SparseMatrixType::Index Index;
+    typedef typename SparseMatrixType::StorageIndex StorageIndex;
 
     struct ScalarWrapper
     {
       ScalarWrapper() : value(0) {}
       Scalar value;
@@ -294,11 +294,11 @@
     {
       const Index outer = SetterRowMajor ? row : col;
       const Index inner = SetterRowMajor ? col : row;
       const Index outerMajor = outer >> OuterPacketBits; // index of the packet/map
       const Index outerMinor = outer & OuterPacketMask;  // index of the inner vector in the packet
-      const KeyType key = (KeyType(outerMinor)<<m_keyBitsOffset) | inner;
+      const KeyType key = internal::convert_index<KeyType>((outerMinor<<m_keyBitsOffset) | inner);
       return m_hashmaps[outerMajor][key].value;
     }
 
     /** \returns the number of non zero coefficients
       *

ADDED   3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsArrayAPI.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsArrayAPI.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsArrayAPI.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsArrayAPI.h
@@ -0,0 +1,124 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+
+#ifndef EIGEN_SPECIALFUNCTIONS_ARRAYAPI_H
+#define EIGEN_SPECIALFUNCTIONS_ARRAYAPI_H
+
+namespace Eigen {
+
+/** \cpp11 \returns an expression of the coefficient-wise igamma(\a a, \a x) to the given arrays.
+  *
+  * This function computes the coefficient-wise incomplete gamma function.
+  *
+  * \note This function supports only float and double scalar types in c++11 mode. To support other scalar types,
+  * or float/double in non c++11 mode, the user has to provide implementations of igammac(T,T) for any scalar
+  * type T to be supported.
+  *
+  * \sa Eigen::igammac(), Eigen::lgamma()
+  */
+template<typename Derived,typename ExponentDerived>
+inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_igamma_op<typename Derived::Scalar>, const Derived, const ExponentDerived>
+igamma(const Eigen::ArrayBase<Derived>& a, const Eigen::ArrayBase<ExponentDerived>& x)
+{
+  return Eigen::CwiseBinaryOp<Eigen::internal::scalar_igamma_op<typename Derived::Scalar>, const Derived, const ExponentDerived>(
+    a.derived(),
+    x.derived()
+  );
+}
+
+/** \cpp11 \returns an expression of the coefficient-wise igammac(\a a, \a x) to the given arrays.
+  *
+  * This function computes the coefficient-wise complementary incomplete gamma function.
+  *
+  * \note This function supports only float and double scalar types in c++11 mode. To support other scalar types,
+  * or float/double in non c++11 mode, the user has to provide implementations of igammac(T,T) for any scalar
+  * type T to be supported.
+  *
+  * \sa Eigen::igamma(), Eigen::lgamma()
+  */
+template<typename Derived,typename ExponentDerived>
+inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_igammac_op<typename Derived::Scalar>, const Derived, const ExponentDerived>
+igammac(const Eigen::ArrayBase<Derived>& a, const Eigen::ArrayBase<ExponentDerived>& x)
+{
+  return Eigen::CwiseBinaryOp<Eigen::internal::scalar_igammac_op<typename Derived::Scalar>, const Derived, const ExponentDerived>(
+    a.derived(),
+    x.derived()
+  );
+}
+
+/** \cpp11 \returns an expression of the coefficient-wise polygamma(\a n, \a x) to the given arrays.
+  *
+  * It returns the \a n -th derivative of the digamma(psi) evaluated at \c x.
+  *
+  * \note This function supports only float and double scalar types in c++11 mode. To support other scalar types,
+  * or float/double in non c++11 mode, the user has to provide implementations of polygamma(T,T) for any scalar
+  * type T to be supported.
+  *
+  * \sa Eigen::digamma()
+  */
+// * \warning Be careful with the order of the parameters: x.polygamma(n) is equivalent to polygamma(n,x)
+// * \sa ArrayBase::polygamma()
+template<typename DerivedN,typename DerivedX>
+inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_polygamma_op<typename DerivedX::Scalar>, const DerivedN, const DerivedX>
+polygamma(const Eigen::ArrayBase<DerivedN>& n, const Eigen::ArrayBase<DerivedX>& x)
+{
+  return Eigen::CwiseBinaryOp<Eigen::internal::scalar_polygamma_op<typename DerivedX::Scalar>, const DerivedN, const DerivedX>(
+    n.derived(),
+    x.derived()
+  );
+}
+
+/** \cpp11 \returns an expression of the coefficient-wise betainc(\a x, \a a, \a b) to the given arrays.
+  *
+  * This function computes the regularized incomplete beta function (integral).
+  *
+  * \note This function supports only float and double scalar types in c++11 mode. To support other scalar types,
+  * or float/double in non c++11 mode, the user has to provide implementations of betainc(T,T,T) for any scalar
+  * type T to be supported.
+  *
+  * \sa Eigen::betainc(), Eigen::lgamma()
+  */
+template<typename ArgADerived, typename ArgBDerived, typename ArgXDerived>
+inline const Eigen::CwiseTernaryOp<Eigen::internal::scalar_betainc_op<typename ArgXDerived::Scalar>, const ArgADerived, const ArgBDerived, const ArgXDerived>
+betainc(const Eigen::ArrayBase<ArgADerived>& a, const Eigen::ArrayBase<ArgBDerived>& b, const Eigen::ArrayBase<ArgXDerived>& x)
+{
+  return Eigen::CwiseTernaryOp<Eigen::internal::scalar_betainc_op<typename ArgXDerived::Scalar>, const ArgADerived, const ArgBDerived, const ArgXDerived>(
+    a.derived(),
+    b.derived(),
+    x.derived()
+  );
+}
+
+
+/** \returns an expression of the coefficient-wise zeta(\a x, \a q) to the given arrays.
+  *
+  * It returns the Riemann zeta function of two arguments \a x and \a q:
+  *
+  * \param x is the exposent, it must be > 1
+  * \param q is the shift, it must be > 0
+  *
+  * \note This function supports only float and double scalar types. To support other scalar types, the user has
+  * to provide implementations of zeta(T,T) for any scalar type T to be supported.
+  *
+  * \sa ArrayBase::zeta()
+  */
+template<typename DerivedX,typename DerivedQ>
+inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_zeta_op<typename DerivedX::Scalar>, const DerivedX, const DerivedQ>
+zeta(const Eigen::ArrayBase<DerivedX>& x, const Eigen::ArrayBase<DerivedQ>& q)
+{
+  return Eigen::CwiseBinaryOp<Eigen::internal::scalar_zeta_op<typename DerivedX::Scalar>, const DerivedX, const DerivedQ>(
+    x.derived(),
+    q.derived()
+  );
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPECIALFUNCTIONS_ARRAYAPI_H

ADDED   3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsFunctors.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsFunctors.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsFunctors.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsFunctors.h
@@ -0,0 +1,236 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Eugene Brevdo <ebrevdo@gmail.com>
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPECIALFUNCTIONS_FUNCTORS_H
+#define EIGEN_SPECIALFUNCTIONS_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+
+/** \internal
+  * \brief Template functor to compute the incomplete gamma function igamma(a, x)
+  *
+  * \sa class CwiseBinaryOp, Cwise::igamma
+  */
+template<typename Scalar> struct scalar_igamma_op : binary_op_base<Scalar,Scalar>
+{
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_igamma_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& x) const {
+    using numext::igamma; return igamma(a, x);
+  }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& x) const {
+    return internal::pigamma(a, x);
+  }
+};
+template<typename Scalar>
+struct functor_traits<scalar_igamma_op<Scalar> > {
+  enum {
+    // Guesstimate
+    Cost = 20 * NumTraits<Scalar>::MulCost + 10 * NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasIGamma
+  };
+};
+
+
+/** \internal
+  * \brief Template functor to compute the complementary incomplete gamma function igammac(a, x)
+  *
+  * \sa class CwiseBinaryOp, Cwise::igammac
+  */
+template<typename Scalar> struct scalar_igammac_op : binary_op_base<Scalar,Scalar>
+{
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_igammac_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& x) const {
+    using numext::igammac; return igammac(a, x);
+  }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& x) const
+  {
+    return internal::pigammac(a, x);
+  }
+};
+template<typename Scalar>
+struct functor_traits<scalar_igammac_op<Scalar> > {
+  enum {
+    // Guesstimate
+    Cost = 20 * NumTraits<Scalar>::MulCost + 10 * NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasIGammac
+  };
+};
+
+
+/** \internal
+  * \brief Template functor to compute the incomplete beta integral betainc(a, b, x)
+  *
+  */
+template<typename Scalar> struct scalar_betainc_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_betainc_op)
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& x, const Scalar& a, const Scalar& b) const {
+    using numext::betainc; return betainc(x, a, b);
+  }
+  template<typename Packet>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& x, const Packet& a, const Packet& b) const
+  {
+    return internal::pbetainc(x, a, b);
+  }
+};
+template<typename Scalar>
+struct functor_traits<scalar_betainc_op<Scalar> > {
+  enum {
+    // Guesstimate
+    Cost = 400 * NumTraits<Scalar>::MulCost + 400 * NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasBetaInc
+  };
+};
+
+
+/** \internal
+ * \brief Template functor to compute the natural log of the absolute
+ * value of Gamma of a scalar
+ * \sa class CwiseUnaryOp, Cwise::lgamma()
+ */
+template<typename Scalar> struct scalar_lgamma_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_lgamma_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const {
+    using numext::lgamma; return lgamma(a);
+  }
+  typedef typename packet_traits<Scalar>::type Packet;
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plgamma(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_lgamma_op<Scalar> >
+{
+  enum {
+    // Guesstimate
+    Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasLGamma
+  };
+};
+
+/** \internal
+ * \brief Template functor to compute psi, the derivative of lgamma of a scalar.
+ * \sa class CwiseUnaryOp, Cwise::digamma()
+ */
+template<typename Scalar> struct scalar_digamma_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_digamma_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const {
+    using numext::digamma; return digamma(a);
+  }
+  typedef typename packet_traits<Scalar>::type Packet;
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pdigamma(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_digamma_op<Scalar> >
+{
+  enum {
+    // Guesstimate
+    Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasDiGamma
+  };
+};
+
+/** \internal
+ * \brief Template functor to compute the Riemann Zeta function of two arguments.
+ * \sa class CwiseUnaryOp, Cwise::zeta()
+ */
+template<typename Scalar> struct scalar_zeta_op {
+    EIGEN_EMPTY_STRUCT_CTOR(scalar_zeta_op)
+    EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& x, const Scalar& q) const {
+        using numext::zeta; return zeta(x, q);
+    }
+    typedef typename packet_traits<Scalar>::type Packet;
+    EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& x, const Packet& q) const { return internal::pzeta(x, q); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_zeta_op<Scalar> >
+{
+    enum {
+        // Guesstimate
+        Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
+        PacketAccess = packet_traits<Scalar>::HasZeta
+    };
+};
+
+/** \internal
+ * \brief Template functor to compute the polygamma function.
+ * \sa class CwiseUnaryOp, Cwise::polygamma()
+ */
+template<typename Scalar> struct scalar_polygamma_op {
+    EIGEN_EMPTY_STRUCT_CTOR(scalar_polygamma_op)
+    EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& n, const Scalar& x) const {
+        using numext::polygamma; return polygamma(n, x);
+    }
+    typedef typename packet_traits<Scalar>::type Packet;
+    EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& n, const Packet& x) const { return internal::ppolygamma(n, x); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_polygamma_op<Scalar> >
+{
+    enum {
+        // Guesstimate
+        Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
+        PacketAccess = packet_traits<Scalar>::HasPolygamma
+    };
+};
+
+/** \internal
+ * \brief Template functor to compute the Gauss error function of a
+ * scalar
+ * \sa class CwiseUnaryOp, Cwise::erf()
+ */
+template<typename Scalar> struct scalar_erf_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_erf_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const {
+    using numext::erf; return erf(a);
+  }
+  typedef typename packet_traits<Scalar>::type Packet;
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::perf(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_erf_op<Scalar> >
+{
+  enum {
+    // Guesstimate
+    Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasErf
+  };
+};
+
+/** \internal
+ * \brief Template functor to compute the Complementary Error Function
+ * of a scalar
+ * \sa class CwiseUnaryOp, Cwise::erfc()
+ */
+template<typename Scalar> struct scalar_erfc_op {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_erfc_op)
+  EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const {
+    using numext::erfc; return erfc(a);
+  }
+  typedef typename packet_traits<Scalar>::type Packet;
+  EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::perfc(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_erfc_op<Scalar> >
+{
+  enum {
+    // Guesstimate
+    Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
+    PacketAccess = packet_traits<Scalar>::HasErfc
+  };
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPECIALFUNCTIONS_FUNCTORS_H

ADDED   3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsHalf.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsHalf.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsHalf.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsHalf.h
@@ -0,0 +1,47 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPECIALFUNCTIONS_HALF_H
+#define EIGEN_SPECIALFUNCTIONS_HALF_H
+
+namespace Eigen {
+namespace numext {
+
+#if EIGEN_HAS_C99_MATH
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half lgamma(const Eigen::half& a) {
+  return Eigen::half(Eigen::numext::lgamma(static_cast<float>(a)));
+}
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half digamma(const Eigen::half& a) {
+  return Eigen::half(Eigen::numext::digamma(static_cast<float>(a)));
+}
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half zeta(const Eigen::half& x, const Eigen::half& q) {
+  return Eigen::half(Eigen::numext::zeta(static_cast<float>(x), static_cast<float>(q)));
+}
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half polygamma(const Eigen::half& n, const Eigen::half& x) {
+  return Eigen::half(Eigen::numext::polygamma(static_cast<float>(n), static_cast<float>(x)));
+}
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half erf(const Eigen::half& a) {
+  return Eigen::half(Eigen::numext::erf(static_cast<float>(a)));
+}
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half erfc(const Eigen::half& a) {
+  return Eigen::half(Eigen::numext::erfc(static_cast<float>(a)));
+}
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half igamma(const Eigen::half& a, const Eigen::half& x) {
+  return Eigen::half(Eigen::numext::igamma(static_cast<float>(a), static_cast<float>(x)));
+}
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half igammac(const Eigen::half& a, const Eigen::half& x) {
+  return Eigen::half(Eigen::numext::igammac(static_cast<float>(a), static_cast<float>(x)));
+}
+template<> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half betainc(const Eigen::half& a, const Eigen::half& b, const Eigen::half& x) {
+  return Eigen::half(Eigen::numext::betainc(static_cast<float>(a), static_cast<float>(b), static_cast<float>(x)));
+}
+#endif
+
+}  // end namespace numext
+}  // end namespace Eigen
+
+#endif  // EIGEN_SPECIALFUNCTIONS_HALF_H

ADDED   3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h
@@ -0,0 +1,1565 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Eugene Brevdo <ebrevdo@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPECIAL_FUNCTIONS_H
+#define EIGEN_SPECIAL_FUNCTIONS_H
+
+namespace Eigen {
+namespace internal {
+
+//  Parts of this code are based on the Cephes Math Library.
+//
+//  Cephes Math Library Release 2.8:  June, 2000
+//  Copyright 1984, 1987, 1992, 2000 by Stephen L. Moshier
+//
+//  Permission has been kindly provided by the original author
+//  to incorporate the Cephes software into the Eigen codebase:
+//
+//    From: Stephen Moshier
+//    To: Eugene Brevdo
+//    Subject: Re: Permission to wrap several cephes functions in Eigen
+//
+//    Hello Eugene,
+//
+//    Thank you for writing.
+//
+//    If your licensing is similar to BSD, the formal way that has been
+//    handled is simply to add a statement to the effect that you are incorporating
+//    the Cephes software by permission of the author.
+//
+//    Good luck with your project,
+//    Steve
+
+namespace cephes {
+
+/* polevl (modified for Eigen)
+ *
+ *      Evaluate polynomial
+ *
+ *
+ *
+ * SYNOPSIS:
+ *
+ * int N;
+ * Scalar x, y, coef[N+1];
+ *
+ * y = polevl<decltype(x), N>( x, coef);
+ *
+ *
+ *
+ * DESCRIPTION:
+ *
+ * Evaluates polynomial of degree N:
+ *
+ *                     2          N
+ * y  =  C  + C x + C x  +...+ C x
+ *        0    1     2          N
+ *
+ * Coefficients are stored in reverse order:
+ *
+ * coef[0] = C  , ..., coef[N] = C  .
+ *            N                   0
+ *
+ *  The function p1evl() assumes that coef[N] = 1.0 and is
+ * omitted from the array.  Its calling arguments are
+ * otherwise the same as polevl().
+ *
+ *
+ * The Eigen implementation is templatized.  For best speed, store
+ * coef as a const array (constexpr), e.g.
+ *
+ * const double coef[] = {1.0, 2.0, 3.0, ...};
+ *
+ */
+template <typename Scalar, int N>
+struct polevl {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(const Scalar x, const Scalar coef[]) {
+    EIGEN_STATIC_ASSERT((N > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+    return polevl<Scalar, N - 1>::run(x, coef) * x + coef[N];
+  }
+};
+
+template <typename Scalar>
+struct polevl<Scalar, 0> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(const Scalar, const Scalar coef[]) {
+    return coef[0];
+  }
+};
+
+}  // end namespace cephes
+
+/****************************************************************************
+ * Implementation of lgamma, requires C++11/C99                             *
+ ****************************************************************************/
+
+template <typename Scalar>
+struct lgamma_impl {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(const Scalar) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+template <typename Scalar>
+struct lgamma_retval {
+  typedef Scalar type;
+};
+
+#if EIGEN_HAS_C99_MATH
+template <>
+struct lgamma_impl<float> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE float run(float x) {
+#if !defined(__CUDA_ARCH__) && (defined(_BSD_SOURCE) || defined(_SVID_SOURCE)) && !defined(__APPLE__)
+    int signgam;
+    return ::lgammaf_r(x, &signgam);
+#else
+    return ::lgammaf(x);
+#endif
+  }
+};
+
+template <>
+struct lgamma_impl<double> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE double run(double x) {
+#if !defined(__CUDA_ARCH__) && (defined(_BSD_SOURCE) || defined(_SVID_SOURCE)) && !defined(__APPLE__)
+    int signgam;
+    return ::lgamma_r(x, &signgam);
+#else
+    return ::lgamma(x);
+#endif
+  }
+};
+#endif
+
+/****************************************************************************
+ * Implementation of digamma (psi), based on Cephes                         *
+ ****************************************************************************/
+
+template <typename Scalar>
+struct digamma_retval {
+  typedef Scalar type;
+};
+
+/*
+ *
+ * Polynomial evaluation helper for the Psi (digamma) function.
+ *
+ * digamma_impl_maybe_poly::run(s) evaluates the asymptotic Psi expansion for
+ * input Scalar s, assuming s is above 10.0.
+ *
+ * If s is above a certain threshold for the given Scalar type, zero
+ * is returned.  Otherwise the polynomial is evaluated with enough
+ * coefficients for results matching Scalar machine precision.
+ *
+ *
+ */
+template <typename Scalar>
+struct digamma_impl_maybe_poly {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(const Scalar) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+
+template <>
+struct digamma_impl_maybe_poly<float> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE float run(const float s) {
+    const float A[] = {
+      -4.16666666666666666667E-3f,
+      3.96825396825396825397E-3f,
+      -8.33333333333333333333E-3f,
+      8.33333333333333333333E-2f
+    };
+
+    float z;
+    if (s < 1.0e8f) {
+      z = 1.0f / (s * s);
+      return z * cephes::polevl<float, 3>::run(z, A);
+    } else return 0.0f;
+  }
+};
+
+template <>
+struct digamma_impl_maybe_poly<double> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE double run(const double s) {
+    const double A[] = {
+      8.33333333333333333333E-2,
+      -2.10927960927960927961E-2,
+      7.57575757575757575758E-3,
+      -4.16666666666666666667E-3,
+      3.96825396825396825397E-3,
+      -8.33333333333333333333E-3,
+      8.33333333333333333333E-2
+    };
+
+    double z;
+    if (s < 1.0e17) {
+      z = 1.0 / (s * s);
+      return z * cephes::polevl<double, 6>::run(z, A);
+    }
+    else return 0.0;
+  }
+};
+
+template <typename Scalar>
+struct digamma_impl {
+  EIGEN_DEVICE_FUNC
+  static Scalar run(Scalar x) {
+    /*
+     *
+     *     Psi (digamma) function (modified for Eigen)
+     *
+     *
+     * SYNOPSIS:
+     *
+     * double x, y, psi();
+     *
+     * y = psi( x );
+     *
+     *
+     * DESCRIPTION:
+     *
+     *              d      -
+     *   psi(x)  =  -- ln | (x)
+     *              dx
+     *
+     * is the logarithmic derivative of the gamma function.
+     * For integer x,
+     *                   n-1
+     *                    -
+     * psi(n) = -EUL  +   >  1/k.
+     *                    -
+     *                   k=1
+     *
+     * If x is negative, it is transformed to a positive argument by the
+     * reflection formula  psi(1-x) = psi(x) + pi cot(pi x).
+     * For general positive x, the argument is made greater than 10
+     * using the recurrence  psi(x+1) = psi(x) + 1/x.
+     * Then the following asymptotic expansion is applied:
+     *
+     *                           inf.   B
+     *                            -      2k
+     * psi(x) = log(x) - 1/2x -   >   -------
+     *                            -        2k
+     *                           k=1   2k x
+     *
+     * where the B2k are Bernoulli numbers.
+     *
+     * ACCURACY (float):
+     *    Relative error (except absolute when |psi| < 1):
+     * arithmetic   domain     # trials      peak         rms
+     *    IEEE      0,30        30000       1.3e-15     1.4e-16
+     *    IEEE      -30,0       40000       1.5e-15     2.2e-16
+     *
+     * ACCURACY (double):
+     *    Absolute error,  relative when |psi| > 1 :
+     * arithmetic   domain     # trials      peak         rms
+     *    IEEE      -33,0        30000      8.2e-7      1.2e-7
+     *    IEEE      0,33        100000      7.3e-7      7.7e-8
+     *
+     * ERROR MESSAGES:
+     *     message         condition      value returned
+     * psi singularity    x integer <=0      INFINITY
+     */
+
+    Scalar p, q, nz, s, w, y;
+    bool negative = false;
+
+    const Scalar maxnum = NumTraits<Scalar>::infinity();
+    const Scalar m_pi = Scalar(EIGEN_PI);
+
+    const Scalar zero = Scalar(0);
+    const Scalar one = Scalar(1);
+    const Scalar half = Scalar(0.5);
+    nz = zero;
+
+    if (x <= zero) {
+      negative = true;
+      q = x;
+      p = numext::floor(q);
+      if (p == q) {
+        return maxnum;
+      }
+      /* Remove the zeros of tan(m_pi x)
+       * by subtracting the nearest integer from x
+       */
+      nz = q - p;
+      if (nz != half) {
+        if (nz > half) {
+          p += one;
+          nz = q - p;
+        }
+        nz = m_pi / numext::tan(m_pi * nz);
+      }
+      else {
+        nz = zero;
+      }
+      x = one - x;
+    }
+
+    /* use the recurrence psi(x+1) = psi(x) + 1/x. */
+    s = x;
+    w = zero;
+    while (s < Scalar(10)) {
+      w += one / s;
+      s += one;
+    }
+
+    y = digamma_impl_maybe_poly<Scalar>::run(s);
+
+    y = numext::log(s) - (half / s) - y - w;
+
+    return (negative) ? y - nz : y;
+  }
+};
+
+/****************************************************************************
+ * Implementation of erf, requires C++11/C99                                *
+ ****************************************************************************/
+
+template <typename Scalar>
+struct erf_impl {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(const Scalar) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+template <typename Scalar>
+struct erf_retval {
+  typedef Scalar type;
+};
+
+#if EIGEN_HAS_C99_MATH
+template <>
+struct erf_impl<float> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE float run(float x) { return ::erff(x); }
+};
+
+template <>
+struct erf_impl<double> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE double run(double x) { return ::erf(x); }
+};
+#endif  // EIGEN_HAS_C99_MATH
+
+/***************************************************************************
+* Implementation of erfc, requires C++11/C99                               *
+****************************************************************************/
+
+template <typename Scalar>
+struct erfc_impl {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(const Scalar) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+template <typename Scalar>
+struct erfc_retval {
+  typedef Scalar type;
+};
+
+#if EIGEN_HAS_C99_MATH
+template <>
+struct erfc_impl<float> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE float run(const float x) { return ::erfcf(x); }
+};
+
+template <>
+struct erfc_impl<double> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE double run(const double x) { return ::erfc(x); }
+};
+#endif  // EIGEN_HAS_C99_MATH
+
+/**************************************************************************************************************
+ * Implementation of igammac (complemented incomplete gamma integral), based on Cephes but requires C++11/C99 *
+ **************************************************************************************************************/
+
+template <typename Scalar>
+struct igammac_retval {
+  typedef Scalar type;
+};
+
+// NOTE: cephes_helper is also used to implement zeta
+template <typename Scalar>
+struct cephes_helper {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar machep() { assert(false && "machep not supported for this type"); return 0.0; }
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar big() { assert(false && "big not supported for this type"); return 0.0; }
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar biginv() { assert(false && "biginv not supported for this type"); return 0.0; }
+};
+
+template <>
+struct cephes_helper<float> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE float machep() {
+    return NumTraits<float>::epsilon() / 2;  // 1.0 - machep == 1.0
+  }
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE float big() {
+    // use epsneg (1.0 - epsneg == 1.0)
+    return 1.0f / (NumTraits<float>::epsilon() / 2);
+  }
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE float biginv() {
+    // epsneg
+    return machep();
+  }
+};
+
+template <>
+struct cephes_helper<double> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE double machep() {
+    return NumTraits<double>::epsilon() / 2;  // 1.0 - machep == 1.0
+  }
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE double big() {
+    return 1.0 / NumTraits<double>::epsilon();
+  }
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE double biginv() {
+    // inverse of eps
+    return NumTraits<double>::epsilon();
+  }
+};
+
+#if !EIGEN_HAS_C99_MATH
+
+template <typename Scalar>
+struct igammac_impl {
+  EIGEN_DEVICE_FUNC
+  static Scalar run(Scalar a, Scalar x) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+#else
+
+template <typename Scalar> struct igamma_impl;  // predeclare igamma_impl
+
+template <typename Scalar>
+struct igammac_impl {
+  EIGEN_DEVICE_FUNC
+  static Scalar run(Scalar a, Scalar x) {
+    /*  igamc()
+     *
+     *	Incomplete gamma integral (modified for Eigen)
+     *
+     *
+     *
+     * SYNOPSIS:
+     *
+     * double a, x, y, igamc();
+     *
+     * y = igamc( a, x );
+     *
+     * DESCRIPTION:
+     *
+     * The function is defined by
+     *
+     *
+     *  igamc(a,x)   =   1 - igam(a,x)
+     *
+     *                            inf.
+     *                              -
+     *                     1       | |  -t  a-1
+     *               =   -----     |   e   t   dt.
+     *                    -      | |
+     *                   | (a)    -
+     *                             x
+     *
+     *
+     * In this implementation both arguments must be positive.
+     * The integral is evaluated by either a power series or
+     * continued fraction expansion, depending on the relative
+     * values of a and x.
+     *
+     * ACCURACY (float):
+     *
+     *                      Relative error:
+     * arithmetic   domain     # trials      peak         rms
+     *    IEEE      0,30        30000       7.8e-6      5.9e-7
+     *
+     *
+     * ACCURACY (double):
+     *
+     * Tested at random a, x.
+     *                a         x                      Relative error:
+     * arithmetic   domain   domain     # trials      peak         rms
+     *    IEEE     0.5,100   0,100      200000       1.9e-14     1.7e-15
+     *    IEEE     0.01,0.5  0,100      200000       1.4e-13     1.6e-15
+     *
+     */
+    /*
+      Cephes Math Library Release 2.2: June, 1992
+      Copyright 1985, 1987, 1992 by Stephen L. Moshier
+      Direct inquiries to 30 Frost Street, Cambridge, MA 02140
+    */
+    const Scalar zero = 0;
+    const Scalar one = 1;
+    const Scalar nan = NumTraits<Scalar>::quiet_NaN();
+
+    if ((x < zero) || (a <= zero)) {
+      // domain error
+      return nan;
+    }
+
+    if ((x < one) || (x < a)) {
+      /* The checks above ensure that we meet the preconditions for
+       * igamma_impl::Impl(), so call it, rather than igamma_impl::Run().
+       * Calling Run() would also work, but in that case the compiler may not be
+       * able to prove that igammac_impl::Run and igamma_impl::Run are not
+       * mutually recursive.  This leads to worse code, particularly on
+       * platforms like nvptx, where recursion is allowed only begrudgingly.
+       */
+      return (one - igamma_impl<Scalar>::Impl(a, x));
+    }
+
+    return Impl(a, x);
+  }
+
+ private:
+  /* igamma_impl calls igammac_impl::Impl. */
+  friend struct igamma_impl<Scalar>;
+
+  /* Actually computes igamc(a, x).
+   *
+   * Preconditions:
+   *   a > 0
+   *   x >= 1
+   *   x >= a
+   */
+  EIGEN_DEVICE_FUNC static Scalar Impl(Scalar a, Scalar x) {
+    const Scalar zero = 0;
+    const Scalar one = 1;
+    const Scalar two = 2;
+    const Scalar machep = cephes_helper<Scalar>::machep();
+    const Scalar maxlog = numext::log(NumTraits<Scalar>::highest());
+    const Scalar big = cephes_helper<Scalar>::big();
+    const Scalar biginv = cephes_helper<Scalar>::biginv();
+    const Scalar inf = NumTraits<Scalar>::infinity();
+
+    Scalar ans, ax, c, yc, r, t, y, z;
+    Scalar pk, pkm1, pkm2, qk, qkm1, qkm2;
+
+    if (x == inf) return zero;  // std::isinf crashes on CUDA
+
+    /* Compute  x**a * exp(-x) / gamma(a)  */
+    ax = a * numext::log(x) - x - lgamma_impl<Scalar>::run(a);
+    if (ax < -maxlog) {  // underflow
+      return zero;
+    }
+    ax = numext::exp(ax);
+
+    // continued fraction
+    y = one - a;
+    z = x + y + one;
+    c = zero;
+    pkm2 = one;
+    qkm2 = x;
+    pkm1 = x + one;
+    qkm1 = z * x;
+    ans = pkm1 / qkm1;
+
+    while (true) {
+      c += one;
+      y += one;
+      z += two;
+      yc = y * c;
+      pk = pkm1 * z - pkm2 * yc;
+      qk = qkm1 * z - qkm2 * yc;
+      if (qk != zero) {
+        r = pk / qk;
+        t = numext::abs((ans - r) / r);
+        ans = r;
+      } else {
+        t = one;
+      }
+      pkm2 = pkm1;
+      pkm1 = pk;
+      qkm2 = qkm1;
+      qkm1 = qk;
+      if (numext::abs(pk) > big) {
+        pkm2 *= biginv;
+        pkm1 *= biginv;
+        qkm2 *= biginv;
+        qkm1 *= biginv;
+      }
+      if (t <= machep) {
+        break;
+      }
+    }
+
+    return (ans * ax);
+  }
+};
+
+#endif  // EIGEN_HAS_C99_MATH
+
+/************************************************************************************************
+ * Implementation of igamma (incomplete gamma integral), based on Cephes but requires C++11/C99 *
+ ************************************************************************************************/
+
+template <typename Scalar>
+struct igamma_retval {
+  typedef Scalar type;
+};
+
+#if !EIGEN_HAS_C99_MATH
+
+template <typename Scalar>
+struct igamma_impl {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(Scalar a, Scalar x) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+#else
+
+template <typename Scalar>
+struct igamma_impl {
+  EIGEN_DEVICE_FUNC
+  static Scalar run(Scalar a, Scalar x) {
+    /*	igam()
+     *	Incomplete gamma integral
+     *
+     *
+     *
+     * SYNOPSIS:
+     *
+     * double a, x, y, igam();
+     *
+     * y = igam( a, x );
+     *
+     * DESCRIPTION:
+     *
+     * The function is defined by
+     *
+     *                           x
+     *                            -
+     *                   1       | |  -t  a-1
+     *  igam(a,x)  =   -----     |   e   t   dt.
+     *                  -      | |
+     *                 | (a)    -
+     *                           0
+     *
+     *
+     * In this implementation both arguments must be positive.
+     * The integral is evaluated by either a power series or
+     * continued fraction expansion, depending on the relative
+     * values of a and x.
+     *
+     * ACCURACY (double):
+     *
+     *                      Relative error:
+     * arithmetic   domain     # trials      peak         rms
+     *    IEEE      0,30       200000       3.6e-14     2.9e-15
+     *    IEEE      0,100      300000       9.9e-14     1.5e-14
+     *
+     *
+     * ACCURACY (float):
+     *
+     *                      Relative error:
+     * arithmetic   domain     # trials      peak         rms
+     *    IEEE      0,30        20000       7.8e-6      5.9e-7
+     *
+     */
+    /*
+      Cephes Math Library Release 2.2: June, 1992
+      Copyright 1985, 1987, 1992 by Stephen L. Moshier
+      Direct inquiries to 30 Frost Street, Cambridge, MA 02140
+    */
+
+
+    /* left tail of incomplete gamma function:
+     *
+     *          inf.      k
+     *   a  -x   -       x
+     *  x  e     >   ----------
+     *           -     -
+     *          k=0   | (a+k+1)
+     *
+     */
+    const Scalar zero = 0;
+    const Scalar one = 1;
+    const Scalar nan = NumTraits<Scalar>::quiet_NaN();
+
+    if (x == zero) return zero;
+
+    if ((x < zero) || (a <= zero)) {  // domain error
+      return nan;
+    }
+
+    if ((x > one) && (x > a)) {
+      /* The checks above ensure that we meet the preconditions for
+       * igammac_impl::Impl(), so call it, rather than igammac_impl::Run().
+       * Calling Run() would also work, but in that case the compiler may not be
+       * able to prove that igammac_impl::Run and igamma_impl::Run are not
+       * mutually recursive.  This leads to worse code, particularly on
+       * platforms like nvptx, where recursion is allowed only begrudgingly.
+       */
+      return (one - igammac_impl<Scalar>::Impl(a, x));
+    }
+
+    return Impl(a, x);
+  }
+
+ private:
+  /* igammac_impl calls igamma_impl::Impl. */
+  friend struct igammac_impl<Scalar>;
+
+  /* Actually computes igam(a, x).
+   *
+   * Preconditions:
+   *   x > 0
+   *   a > 0
+   *   !(x > 1 && x > a)
+   */
+  EIGEN_DEVICE_FUNC static Scalar Impl(Scalar a, Scalar x) {
+    const Scalar zero = 0;
+    const Scalar one = 1;
+    const Scalar machep = cephes_helper<Scalar>::machep();
+    const Scalar maxlog = numext::log(NumTraits<Scalar>::highest());
+
+    Scalar ans, ax, c, r;
+
+    /* Compute  x**a * exp(-x) / gamma(a)  */
+    ax = a * numext::log(x) - x - lgamma_impl<Scalar>::run(a);
+    if (ax < -maxlog) {
+      // underflow
+      return zero;
+    }
+    ax = numext::exp(ax);
+
+    /* power series */
+    r = a;
+    c = one;
+    ans = one;
+
+    while (true) {
+      r += one;
+      c *= x/r;
+      ans += c;
+      if (c/ans <= machep) {
+        break;
+      }
+    }
+
+    return (ans * ax / a);
+  }
+};
+
+#endif  // EIGEN_HAS_C99_MATH
+
+/*****************************************************************************
+ * Implementation of Riemann zeta function of two arguments, based on Cephes *
+ *****************************************************************************/
+
+template <typename Scalar>
+struct zeta_retval {
+    typedef Scalar type;
+};
+
+template <typename Scalar>
+struct zeta_impl_series {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(const Scalar) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+template <>
+struct zeta_impl_series<float> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE bool run(float& a, float& b, float& s, const float x, const float machep) {
+    int i = 0;
+    while(i < 9)
+    {
+        i += 1;
+        a += 1.0f;
+        b = numext::pow( a, -x );
+        s += b;
+        if( numext::abs(b/s) < machep )
+            return true;
+    }
+
+    //Return whether we are done
+    return false;
+  }
+};
+
+template <>
+struct zeta_impl_series<double> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE bool run(double& a, double& b, double& s, const double x, const double machep) {
+    int i = 0;
+    while( (i < 9) || (a <= 9.0) )
+    {
+        i += 1;
+        a += 1.0;
+        b = numext::pow( a, -x );
+        s += b;
+        if( numext::abs(b/s) < machep )
+            return true;
+    }
+
+    //Return whether we are done
+    return false;
+  }
+};
+
+template <typename Scalar>
+struct zeta_impl {
+    EIGEN_DEVICE_FUNC
+    static Scalar run(Scalar x, Scalar q) {
+        /*							zeta.c
+         *
+         *	Riemann zeta function of two arguments
+         *
+         *
+         *
+         * SYNOPSIS:
+         *
+         * double x, q, y, zeta();
+         *
+         * y = zeta( x, q );
+         *
+         *
+         *
+         * DESCRIPTION:
+         *
+         *
+         *
+         *                 inf.
+         *                  -        -x
+         *   zeta(x,q)  =   >   (k+q)
+         *                  -
+         *                 k=0
+         *
+         * where x > 1 and q is not a negative integer or zero.
+         * The Euler-Maclaurin summation formula is used to obtain
+         * the expansion
+         *
+         *                n
+         *                -       -x
+         * zeta(x,q)  =   >  (k+q)
+         *                -
+         *               k=1
+         *
+         *           1-x                 inf.  B   x(x+1)...(x+2j)
+         *      (n+q)           1         -     2j
+         *  +  ---------  -  -------  +   >    --------------------
+         *        x-1              x      -                   x+2j+1
+         *                   2(n+q)      j=1       (2j)! (n+q)
+         *
+         * where the B2j are Bernoulli numbers.  Note that (see zetac.c)
+         * zeta(x,1) = zetac(x) + 1.
+         *
+         *
+         *
+         * ACCURACY:
+         *
+         * Relative error for single precision:
+         * arithmetic   domain     # trials      peak         rms
+         *    IEEE      0,25        10000       6.9e-7      1.0e-7
+         *
+         * Large arguments may produce underflow in powf(), in which
+         * case the results are inaccurate.
+         *
+         * REFERENCE:
+         *
+         * Gradshteyn, I. S., and I. M. Ryzhik, Tables of Integrals,
+         * Series, and Products, p. 1073; Academic Press, 1980.
+         *
+         */
+
+        int i;
+        Scalar p, r, a, b, k, s, t, w;
+
+        const Scalar A[] = {
+            Scalar(12.0),
+            Scalar(-720.0),
+            Scalar(30240.0),
+            Scalar(-1209600.0),
+            Scalar(47900160.0),
+            Scalar(-1.8924375803183791606e9), /*1.307674368e12/691*/
+            Scalar(7.47242496e10),
+            Scalar(-2.950130727918164224e12), /*1.067062284288e16/3617*/
+            Scalar(1.1646782814350067249e14), /*5.109094217170944e18/43867*/
+            Scalar(-4.5979787224074726105e15), /*8.028576626982912e20/174611*/
+            Scalar(1.8152105401943546773e17), /*1.5511210043330985984e23/854513*/
+            Scalar(-7.1661652561756670113e18) /*1.6938241367317436694528e27/236364091*/
+            };
+
+        const Scalar maxnum = NumTraits<Scalar>::infinity();
+        const Scalar zero = 0.0, half = 0.5, one = 1.0;
+        const Scalar machep = cephes_helper<Scalar>::machep();
+        const Scalar nan = NumTraits<Scalar>::quiet_NaN();
+
+        if( x == one )
+            return maxnum;
+
+        if( x < one )
+        {
+            return nan;
+        }
+
+        if( q <= zero )
+        {
+            if(q == numext::floor(q))
+            {
+                return maxnum;
+            }
+            p = x;
+            r = numext::floor(p);
+            if (p != r)
+                return nan;
+        }
+
+        /* Permit negative q but continue sum until n+q > +9 .
+         * This case should be handled by a reflection formula.
+         * If q<0 and x is an integer, there is a relation to
+         * the polygamma function.
+         */
+        s = numext::pow( q, -x );
+        a = q;
+        b = zero;
+        // Run the summation in a helper function that is specific to the floating precision
+        if (zeta_impl_series<Scalar>::run(a, b, s, x, machep)) {
+            return s;
+        }
+
+        w = a;
+        s += b*w/(x-one);
+        s -= half * b;
+        a = one;
+        k = zero;
+        for( i=0; i<12; i++ )
+        {
+            a *= x + k;
+            b /= w;
+            t = a*b/A[i];
+            s = s + t;
+            t = numext::abs(t/s);
+            if( t < machep ) {
+              break;
+            }
+            k += one;
+            a *= x + k;
+            b /= w;
+            k += one;
+        }
+        return s;
+  }
+};
+
+/****************************************************************************
+ * Implementation of polygamma function, requires C++11/C99                 *
+ ****************************************************************************/
+
+template <typename Scalar>
+struct polygamma_retval {
+    typedef Scalar type;
+};
+
+#if !EIGEN_HAS_C99_MATH
+
+template <typename Scalar>
+struct polygamma_impl {
+    EIGEN_DEVICE_FUNC
+    static EIGEN_STRONG_INLINE Scalar run(Scalar n, Scalar x) {
+        EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                            THIS_TYPE_IS_NOT_SUPPORTED);
+        return Scalar(0);
+    }
+};
+
+#else
+
+template <typename Scalar>
+struct polygamma_impl {
+    EIGEN_DEVICE_FUNC
+    static Scalar run(Scalar n, Scalar x) {
+        Scalar zero = 0.0, one = 1.0;
+        Scalar nplus = n + one;
+        const Scalar nan = NumTraits<Scalar>::quiet_NaN();
+
+        // Check that n is an integer
+        if (numext::floor(n) != n) {
+            return nan;
+        }
+        // Just return the digamma function for n = 1
+        else if (n == zero) {
+            return digamma_impl<Scalar>::run(x);
+        }
+        // Use the same implementation as scipy
+        else {
+            Scalar factorial = numext::exp(lgamma_impl<Scalar>::run(nplus));
+            return numext::pow(-one, nplus) * factorial * zeta_impl<Scalar>::run(nplus, x);
+        }
+  }
+};
+
+#endif  // EIGEN_HAS_C99_MATH
+
+/************************************************************************************************
+ * Implementation of betainc (incomplete beta integral), based on Cephes but requires C++11/C99 *
+ ************************************************************************************************/
+
+template <typename Scalar>
+struct betainc_retval {
+  typedef Scalar type;
+};
+
+#if !EIGEN_HAS_C99_MATH
+
+template <typename Scalar>
+struct betainc_impl {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(Scalar a, Scalar b, Scalar x) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+#else
+
+template <typename Scalar>
+struct betainc_impl {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(Scalar, Scalar, Scalar) {
+    /*	betaincf.c
+     *
+     *	Incomplete beta integral
+     *
+     *
+     * SYNOPSIS:
+     *
+     * float a, b, x, y, betaincf();
+     *
+     * y = betaincf( a, b, x );
+     *
+     *
+     * DESCRIPTION:
+     *
+     * Returns incomplete beta integral of the arguments, evaluated
+     * from zero to x.  The function is defined as
+     *
+     *                  x
+     *     -            -
+     *    | (a+b)      | |  a-1     b-1
+     *  -----------    |   t   (1-t)   dt.
+     *   -     -     | |
+     *  | (a) | (b)   -
+     *                 0
+     *
+     * The domain of definition is 0 <= x <= 1.  In this
+     * implementation a and b are restricted to positive values.
+     * The integral from x to 1 may be obtained by the symmetry
+     * relation
+     *
+     *    1 - betainc( a, b, x )  =  betainc( b, a, 1-x ).
+     *
+     * The integral is evaluated by a continued fraction expansion.
+     * If a < 1, the function calls itself recursively after a
+     * transformation to increase a to a+1.
+     *
+     * ACCURACY (float):
+     *
+     * Tested at random points (a,b,x) with a and b in the indicated
+     * interval and x between 0 and 1.
+     *
+     * arithmetic   domain     # trials      peak         rms
+     * Relative error:
+     *    IEEE       0,30       10000       3.7e-5      5.1e-6
+     *    IEEE       0,100      10000       1.7e-4      2.5e-5
+     * The useful domain for relative error is limited by underflow
+     * of the single precision exponential function.
+     * Absolute error:
+     *    IEEE       0,30      100000       2.2e-5      9.6e-7
+     *    IEEE       0,100      10000       6.5e-5      3.7e-6
+     *
+     * Larger errors may occur for extreme ratios of a and b.
+     *
+     * ACCURACY (double):
+     * arithmetic   domain     # trials      peak         rms
+     *    IEEE      0,5         10000       6.9e-15     4.5e-16
+     *    IEEE      0,85       250000       2.2e-13     1.7e-14
+     *    IEEE      0,1000      30000       5.3e-12     6.3e-13
+     *    IEEE      0,10000    250000       9.3e-11     7.1e-12
+     *    IEEE      0,100000    10000       8.7e-10     4.8e-11
+     * Outputs smaller than the IEEE gradual underflow threshold
+     * were excluded from these statistics.
+     *
+     * ERROR MESSAGES:
+     *   message         condition      value returned
+     * incbet domain      x<0, x>1          nan
+     * incbet underflow                     nan
+     */
+
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, Scalar>::value == false),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    return Scalar(0);
+  }
+};
+
+/* Continued fraction expansion #1 for incomplete beta integral (small_branch = True)
+ * Continued fraction expansion #2 for incomplete beta integral (small_branch = False)
+ */
+template <typename Scalar>
+struct incbeta_cfe {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE Scalar run(Scalar a, Scalar b, Scalar x, bool small_branch) {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar, float>::value ||
+                         internal::is_same<Scalar, double>::value),
+                        THIS_TYPE_IS_NOT_SUPPORTED);
+    const Scalar big = cephes_helper<Scalar>::big();
+    const Scalar machep = cephes_helper<Scalar>::machep();
+    const Scalar biginv = cephes_helper<Scalar>::biginv();
+
+    const Scalar zero = 0;
+    const Scalar one = 1;
+    const Scalar two = 2;
+
+    Scalar xk, pk, pkm1, pkm2, qk, qkm1, qkm2;
+    Scalar k1, k2, k3, k4, k5, k6, k7, k8, k26update;
+    Scalar ans;
+    int n;
+
+    const int num_iters = (internal::is_same<Scalar, float>::value) ? 100 : 300;
+    const Scalar thresh =
+        (internal::is_same<Scalar, float>::value) ? machep : Scalar(3) * machep;
+    Scalar r = (internal::is_same<Scalar, float>::value) ? zero : one;
+
+    if (small_branch) {
+      k1 = a;
+      k2 = a + b;
+      k3 = a;
+      k4 = a + one;
+      k5 = one;
+      k6 = b - one;
+      k7 = k4;
+      k8 = a + two;
+      k26update = one;
+    } else {
+      k1 = a;
+      k2 = b - one;
+      k3 = a;
+      k4 = a + one;
+      k5 = one;
+      k6 = a + b;
+      k7 = a + one;
+      k8 = a + two;
+      k26update = -one;
+      x = x / (one - x);
+    }
+
+    pkm2 = zero;
+    qkm2 = one;
+    pkm1 = one;
+    qkm1 = one;
+    ans = one;
+    n = 0;
+
+    do {
+      xk = -(x * k1 * k2) / (k3 * k4);
+      pk = pkm1 + pkm2 * xk;
+      qk = qkm1 + qkm2 * xk;
+      pkm2 = pkm1;
+      pkm1 = pk;
+      qkm2 = qkm1;
+      qkm1 = qk;
+
+      xk = (x * k5 * k6) / (k7 * k8);
+      pk = pkm1 + pkm2 * xk;
+      qk = qkm1 + qkm2 * xk;
+      pkm2 = pkm1;
+      pkm1 = pk;
+      qkm2 = qkm1;
+      qkm1 = qk;
+
+      if (qk != zero) {
+        r = pk / qk;
+        if (numext::abs(ans - r) < numext::abs(r) * thresh) {
+          return r;
+        }
+        ans = r;
+      }
+
+      k1 += one;
+      k2 += k26update;
+      k3 += two;
+      k4 += two;
+      k5 += one;
+      k6 -= k26update;
+      k7 += two;
+      k8 += two;
+
+      if ((numext::abs(qk) + numext::abs(pk)) > big) {
+        pkm2 *= biginv;
+        pkm1 *= biginv;
+        qkm2 *= biginv;
+        qkm1 *= biginv;
+      }
+      if ((numext::abs(qk) < biginv) || (numext::abs(pk) < biginv)) {
+        pkm2 *= big;
+        pkm1 *= big;
+        qkm2 *= big;
+        qkm1 *= big;
+      }
+    } while (++n < num_iters);
+
+    return ans;
+  }
+};
+
+/* Helper functions depending on the Scalar type */
+template <typename Scalar>
+struct betainc_helper {};
+
+template <>
+struct betainc_helper<float> {
+  /* Core implementation, assumes a large (> 1.0) */
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE float incbsa(float aa, float bb,
+                                                            float xx) {
+    float ans, a, b, t, x, onemx;
+    bool reversed_a_b = false;
+
+    onemx = 1.0f - xx;
+
+    /* see if x is greater than the mean */
+    if (xx > (aa / (aa + bb))) {
+      reversed_a_b = true;
+      a = bb;
+      b = aa;
+      t = xx;
+      x = onemx;
+    } else {
+      a = aa;
+      b = bb;
+      t = onemx;
+      x = xx;
+    }
+
+    /* Choose expansion for optimal convergence */
+    if (b > 10.0f) {
+      if (numext::abs(b * x / a) < 0.3f) {
+        t = betainc_helper<float>::incbps(a, b, x);
+        if (reversed_a_b) t = 1.0f - t;
+        return t;
+      }
+    }
+
+    ans = x * (a + b - 2.0f) / (a - 1.0f);
+    if (ans < 1.0f) {
+      ans = incbeta_cfe<float>::run(a, b, x, true /* small_branch */);
+      t = b * numext::log(t);
+    } else {
+      ans = incbeta_cfe<float>::run(a, b, x, false /* small_branch */);
+      t = (b - 1.0f) * numext::log(t);
+    }
+
+    t += a * numext::log(x) + lgamma_impl<float>::run(a + b) -
+         lgamma_impl<float>::run(a) - lgamma_impl<float>::run(b);
+    t += numext::log(ans / a);
+    t = numext::exp(t);
+
+    if (reversed_a_b) t = 1.0f - t;
+    return t;
+  }
+
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE float incbps(float a, float b, float x) {
+    float t, u, y, s;
+    const float machep = cephes_helper<float>::machep();
+
+    y = a * numext::log(x) + (b - 1.0f) * numext::log1p(-x) - numext::log(a);
+    y -= lgamma_impl<float>::run(a) + lgamma_impl<float>::run(b);
+    y += lgamma_impl<float>::run(a + b);
+
+    t = x / (1.0f - x);
+    s = 0.0f;
+    u = 1.0f;
+    do {
+      b -= 1.0f;
+      if (b == 0.0f) {
+        break;
+      }
+      a += 1.0f;
+      u *= t * b / a;
+      s += u;
+    } while (numext::abs(u) > machep);
+
+    return numext::exp(y) * (1.0f + s);
+  }
+};
+
+template <>
+struct betainc_impl<float> {
+  EIGEN_DEVICE_FUNC
+  static float run(float a, float b, float x) {
+    const float nan = NumTraits<float>::quiet_NaN();
+    float ans, t;
+
+    if (a <= 0.0f) return nan;
+    if (b <= 0.0f) return nan;
+    if ((x <= 0.0f) || (x >= 1.0f)) {
+      if (x == 0.0f) return 0.0f;
+      if (x == 1.0f) return 1.0f;
+      // mtherr("betaincf", DOMAIN);
+      return nan;
+    }
+
+    /* transformation for small aa */
+    if (a <= 1.0f) {
+      ans = betainc_helper<float>::incbsa(a + 1.0f, b, x);
+      t = a * numext::log(x) + b * numext::log1p(-x) +
+          lgamma_impl<float>::run(a + b) - lgamma_impl<float>::run(a + 1.0f) -
+          lgamma_impl<float>::run(b);
+      return (ans + numext::exp(t));
+    } else {
+      return betainc_helper<float>::incbsa(a, b, x);
+    }
+  }
+};
+
+template <>
+struct betainc_helper<double> {
+  EIGEN_DEVICE_FUNC
+  static EIGEN_STRONG_INLINE double incbps(double a, double b, double x) {
+    const double machep = cephes_helper<double>::machep();
+
+    double s, t, u, v, n, t1, z, ai;
+
+    ai = 1.0 / a;
+    u = (1.0 - b) * x;
+    v = u / (a + 1.0);
+    t1 = v;
+    t = u;
+    n = 2.0;
+    s = 0.0;
+    z = machep * ai;
+    while (numext::abs(v) > z) {
+      u = (n - b) * x / n;
+      t *= u;
+      v = t / (a + n);
+      s += v;
+      n += 1.0;
+    }
+    s += t1;
+    s += ai;
+
+    u = a * numext::log(x);
+    // TODO: gamma() is not directly implemented in Eigen.
+    /*
+    if ((a + b) < maxgam && numext::abs(u) < maxlog) {
+      t = gamma(a + b) / (gamma(a) * gamma(b));
+      s = s * t * pow(x, a);
+    } else {
+    */
+    t = lgamma_impl<double>::run(a + b) - lgamma_impl<double>::run(a) -
+        lgamma_impl<double>::run(b) + u + numext::log(s);
+    return s = numext::exp(t);
+  }
+};
+
+template <>
+struct betainc_impl<double> {
+  EIGEN_DEVICE_FUNC
+  static double run(double aa, double bb, double xx) {
+    const double nan = NumTraits<double>::quiet_NaN();
+    const double machep = cephes_helper<double>::machep();
+    // const double maxgam = 171.624376956302725;
+
+    double a, b, t, x, xc, w, y;
+    bool reversed_a_b = false;
+
+    if (aa <= 0.0 || bb <= 0.0) {
+      return nan;  // goto domerr;
+    }
+
+    if ((xx <= 0.0) || (xx >= 1.0)) {
+      if (xx == 0.0) return (0.0);
+      if (xx == 1.0) return (1.0);
+      // mtherr("incbet", DOMAIN);
+      return nan;
+    }
+
+    if ((bb * xx) <= 1.0 && xx <= 0.95) {
+      return betainc_helper<double>::incbps(aa, bb, xx);
+    }
+
+    w = 1.0 - xx;
+
+    /* Reverse a and b if x is greater than the mean. */
+    if (xx > (aa / (aa + bb))) {
+      reversed_a_b = true;
+      a = bb;
+      b = aa;
+      xc = xx;
+      x = w;
+    } else {
+      a = aa;
+      b = bb;
+      xc = w;
+      x = xx;
+    }
+
+    if (reversed_a_b && (b * x) <= 1.0 && x <= 0.95) {
+      t = betainc_helper<double>::incbps(a, b, x);
+      if (t <= machep) {
+        t = 1.0 - machep;
+      } else {
+        t = 1.0 - t;
+      }
+      return t;
+    }
+
+    /* Choose expansion for better convergence. */
+    y = x * (a + b - 2.0) - (a - 1.0);
+    if (y < 0.0) {
+      w = incbeta_cfe<double>::run(a, b, x, true /* small_branch */);
+    } else {
+      w = incbeta_cfe<double>::run(a, b, x, false /* small_branch */) / xc;
+    }
+
+    /* Multiply w by the factor
+         a      b   _             _     _
+        x  (1-x)   | (a+b) / ( a | (a) | (b) ) .   */
+
+    y = a * numext::log(x);
+    t = b * numext::log(xc);
+    // TODO: gamma is not directly implemented in Eigen.
+    /*
+    if ((a + b) < maxgam && numext::abs(y) < maxlog && numext::abs(t) < maxlog)
+    {
+      t = pow(xc, b);
+      t *= pow(x, a);
+      t /= a;
+      t *= w;
+      t *= gamma(a + b) / (gamma(a) * gamma(b));
+    } else {
+    */
+    /* Resort to logarithms.  */
+    y += t + lgamma_impl<double>::run(a + b) - lgamma_impl<double>::run(a) -
+         lgamma_impl<double>::run(b);
+    y += numext::log(w / a);
+    t = numext::exp(y);
+
+    /* } */
+    // done:
+
+    if (reversed_a_b) {
+      if (t <= machep) {
+        t = 1.0 - machep;
+      } else {
+        t = 1.0 - t;
+      }
+    }
+    return t;
+  }
+};
+
+#endif  // EIGEN_HAS_C99_MATH
+
+}  // end namespace internal
+
+namespace numext {
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(lgamma, Scalar)
+    lgamma(const Scalar& x) {
+  return EIGEN_MATHFUNC_IMPL(lgamma, Scalar)::run(x);
+}
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(digamma, Scalar)
+    digamma(const Scalar& x) {
+  return EIGEN_MATHFUNC_IMPL(digamma, Scalar)::run(x);
+}
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(zeta, Scalar)
+zeta(const Scalar& x, const Scalar& q) {
+    return EIGEN_MATHFUNC_IMPL(zeta, Scalar)::run(x, q);
+}
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(polygamma, Scalar)
+polygamma(const Scalar& n, const Scalar& x) {
+    return EIGEN_MATHFUNC_IMPL(polygamma, Scalar)::run(n, x);
+}
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(erf, Scalar)
+    erf(const Scalar& x) {
+  return EIGEN_MATHFUNC_IMPL(erf, Scalar)::run(x);
+}
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(erfc, Scalar)
+    erfc(const Scalar& x) {
+  return EIGEN_MATHFUNC_IMPL(erfc, Scalar)::run(x);
+}
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(igamma, Scalar)
+    igamma(const Scalar& a, const Scalar& x) {
+  return EIGEN_MATHFUNC_IMPL(igamma, Scalar)::run(a, x);
+}
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(igammac, Scalar)
+    igammac(const Scalar& a, const Scalar& x) {
+  return EIGEN_MATHFUNC_IMPL(igammac, Scalar)::run(a, x);
+}
+
+template <typename Scalar>
+EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(betainc, Scalar)
+    betainc(const Scalar& a, const Scalar& b, const Scalar& x) {
+  return EIGEN_MATHFUNC_IMPL(betainc, Scalar)::run(a, b, x);
+}
+
+}  // end namespace numext
+
+
+}  // end namespace Eigen
+
+#endif  // EIGEN_SPECIAL_FUNCTIONS_H

ADDED   3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsPacketMath.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsPacketMath.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsPacketMath.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsPacketMath.h
@@ -0,0 +1,58 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPECIALFUNCTIONS_PACKETMATH_H
+#define EIGEN_SPECIALFUNCTIONS_PACKETMATH_H
+
+namespace Eigen {
+
+namespace internal {
+
+/** \internal \returns the ln(|gamma(\a a)|) (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet plgamma(const Packet& a) { using numext::lgamma; return lgamma(a); }
+
+/** \internal \returns the derivative of lgamma, psi(\a a) (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pdigamma(const Packet& a) { using numext::digamma; return digamma(a); }
+
+/** \internal \returns the zeta function of two arguments (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pzeta(const Packet& x, const Packet& q) { using numext::zeta; return zeta(x, q); }
+
+/** \internal \returns the polygamma function (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet ppolygamma(const Packet& n, const Packet& x) { using numext::polygamma; return polygamma(n, x); }
+
+/** \internal \returns the erf(\a a) (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet perf(const Packet& a) { using numext::erf; return erf(a); }
+
+/** \internal \returns the erfc(\a a) (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet perfc(const Packet& a) { using numext::erfc; return erfc(a); }
+
+/** \internal \returns the incomplete gamma function igamma(\a a, \a x) */
+template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+Packet pigamma(const Packet& a, const Packet& x) { using numext::igamma; return igamma(a, x); }
+
+/** \internal \returns the complementary incomplete gamma function igammac(\a a, \a x) */
+template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+Packet pigammac(const Packet& a, const Packet& x) { using numext::igammac; return igammac(a, x); }
+
+/** \internal \returns the complementary incomplete gamma function betainc(\a a, \a b, \a x) */
+template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+Packet pbetainc(const Packet& a, const Packet& b,const Packet& x) { using numext::betainc; return betainc(a, b, x); }
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPECIALFUNCTIONS_PACKETMATH_H
+

ADDED   3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h
Index: 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h
+++ 3rd_party/eigen/unsupported/Eigen/src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h
@@ -0,0 +1,165 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CUDA_SPECIALFUNCTIONS_H
+#define EIGEN_CUDA_SPECIALFUNCTIONS_H
+
+namespace Eigen {
+
+namespace internal {
+
+// Make sure this is only available when targeting a GPU: we don't want to
+// introduce conflicts between these packet_traits definitions and the ones
+// we'll use on the host side (SSE, AVX, ...)
+#if defined(__CUDACC__) && defined(EIGEN_USE_GPU)
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 plgamma<float4>(const float4& a)
+{
+  return make_float4(lgammaf(a.x), lgammaf(a.y), lgammaf(a.z), lgammaf(a.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 plgamma<double2>(const double2& a)
+{
+  using numext::lgamma;
+  return make_double2(lgamma(a.x), lgamma(a.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 pdigamma<float4>(const float4& a)
+{
+  using numext::digamma;
+  return make_float4(digamma(a.x), digamma(a.y), digamma(a.z), digamma(a.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 pdigamma<double2>(const double2& a)
+{
+  using numext::digamma;
+  return make_double2(digamma(a.x), digamma(a.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 pzeta<float4>(const float4& x, const float4& q)
+{
+    using numext::zeta;
+    return make_float4(zeta(x.x, q.x), zeta(x.y, q.y), zeta(x.z, q.z), zeta(x.w, q.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 pzeta<double2>(const double2& x, const double2& q)
+{
+    using numext::zeta;
+    return make_double2(zeta(x.x, q.x), zeta(x.y, q.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 ppolygamma<float4>(const float4& n, const float4& x)
+{
+    using numext::polygamma;
+    return make_float4(polygamma(n.x, x.x), polygamma(n.y, x.y), polygamma(n.z, x.z), polygamma(n.w, x.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 ppolygamma<double2>(const double2& n, const double2& x)
+{
+    using numext::polygamma;
+    return make_double2(polygamma(n.x, x.x), polygamma(n.y, x.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 perf<float4>(const float4& a)
+{
+  return make_float4(erff(a.x), erff(a.y), erff(a.z), erff(a.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 perf<double2>(const double2& a)
+{
+  using numext::erf;
+  return make_double2(erf(a.x), erf(a.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 perfc<float4>(const float4& a)
+{
+  using numext::erfc;
+  return make_float4(erfc(a.x), erfc(a.y), erfc(a.z), erfc(a.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 perfc<double2>(const double2& a)
+{
+  using numext::erfc;
+  return make_double2(erfc(a.x), erfc(a.y));
+}
+
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 pigamma<float4>(const float4& a, const float4& x)
+{
+  using numext::igamma;
+  return make_float4(
+      igamma(a.x, x.x),
+      igamma(a.y, x.y),
+      igamma(a.z, x.z),
+      igamma(a.w, x.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 pigamma<double2>(const double2& a, const double2& x)
+{
+  using numext::igamma;
+  return make_double2(igamma(a.x, x.x), igamma(a.y, x.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 pigammac<float4>(const float4& a, const float4& x)
+{
+  using numext::igammac;
+  return make_float4(
+      igammac(a.x, x.x),
+      igammac(a.y, x.y),
+      igammac(a.z, x.z),
+      igammac(a.w, x.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 pigammac<double2>(const double2& a, const double2& x)
+{
+  using numext::igammac;
+  return make_double2(igammac(a.x, x.x), igammac(a.y, x.y));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+float4 pbetainc<float4>(const float4& a, const float4& b, const float4& x)
+{
+  using numext::betainc;
+  return make_float4(
+      betainc(a.x, b.x, x.x),
+      betainc(a.y, b.y, x.y),
+      betainc(a.z, b.z, x.z),
+      betainc(a.w, b.w, x.w));
+}
+
+template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+double2 pbetainc<double2>(const double2& a, const double2& b, const double2& x)
+{
+  using numext::betainc;
+  return make_double2(betainc(a.x, b.x, x.x), betainc(a.y, b.y, x.y));
+}
+
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CUDA_SPECIALFUNCTIONS_H

DELETED 3rd_party/eigen/unsupported/Eigen/src/Splines/CMakeLists.txt
Index: 3rd_party/eigen/unsupported/Eigen/src/Splines/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Splines/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/Eigen/src/Splines/CMakeLists.txt
@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Splines_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Splines_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/Splines COMPONENT Devel
-  )

Index: 3rd_party/eigen/unsupported/Eigen/src/Splines/Spline.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Splines/Spline.h
+++ 3rd_party/eigen/unsupported/Eigen/src/Splines/Spline.h
@@ -42,13 +42,19 @@
     /** \brief The point type the spline is representing. */
     typedef typename SplineTraits<Spline>::PointType PointType;
     
     /** \brief The data type used to store knot vectors. */
     typedef typename SplineTraits<Spline>::KnotVectorType KnotVectorType;
+
+    /** \brief The data type used to store parameter vectors. */
+    typedef typename SplineTraits<Spline>::ParameterVectorType ParameterVectorType;
     
     /** \brief The data type used to store non-zero basis functions. */
     typedef typename SplineTraits<Spline>::BasisVectorType BasisVectorType;
+
+    /** \brief The data type used to store the values of the basis function derivatives. */
+    typedef typename SplineTraits<Spline>::BasisDerivativeType BasisDerivativeType;
     
     /** \brief The data type representing the spline's control points. */
     typedef typename SplineTraits<Spline>::ControlPointVectorType ControlPointVectorType;
     
     /**
@@ -55,11 +61,11 @@
     * \brief Creates a (constant) zero spline.
     * For Splines with dynamic degree, the resulting degree will be 0.
     **/
     Spline() 
     : m_knots(1, (Degree==Dynamic ? 2 : 2*Degree+2))
-    , m_ctrls(ControlPointVectorType::Zero(2,(Degree==Dynamic ? 1 : Degree+1))) 
+    , m_ctrls(ControlPointVectorType::Zero(Dimension,(Degree==Dynamic ? 1 : Degree+1))) 
     {
       // in theory this code can go to the initializer list but it will get pretty
       // much unreadable ...
       enum { MinDegree = (Degree==Dynamic ? 0 : Degree) };
       m_knots.template segment<MinDegree+1>(0) = Array<Scalar,1,MinDegree+1>::Zero();
@@ -86,11 +92,11 @@
      * \brief Returns the knots of the underlying spline.
      **/
     const KnotVectorType& knots() const { return m_knots; }
     
     /**
-     * \brief Returns the knots of the underlying spline.
+     * \brief Returns the ctrls of the underlying spline.
      **/    
     const ControlPointVectorType& ctrls() const { return m_ctrls; }
 
     /**
      * \brief Returns the spline value at a given site \f$u\f$.
@@ -201,14 +207,29 @@
      * \param degree The degree of the underlying spline.
      * \param knots The underlying spline's knot vector.
      **/
     static BasisVectorType BasisFunctions(Scalar u, DenseIndex degree, const KnotVectorType& knots);
 
+    /**
+     * \copydoc Spline::basisFunctionDerivatives
+     * \param degree The degree of the underlying spline
+     * \param knots The underlying spline's knot vector.
+     **/    
+    static BasisDerivativeType BasisFunctionDerivatives(
+      const Scalar u, const DenseIndex order, const DenseIndex degree, const KnotVectorType& knots);
 
   private:
     KnotVectorType m_knots; /*!< Knot vector. */
     ControlPointVectorType  m_ctrls; /*!< Control points. */
+
+    template <typename DerivativeType>
+    static void BasisFunctionDerivativesImpl(
+      const typename Spline<_Scalar, _Dim, _Degree>::Scalar u,
+      const DenseIndex order,
+      const DenseIndex p, 
+      const typename Spline<_Scalar, _Dim, _Degree>::KnotVectorType& U,
+      DerivativeType& N_);
   };
 
   template <typename _Scalar, int _Dim, int _Degree>
   DenseIndex Spline<_Scalar, _Dim, _Degree>::Span(
     typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::Scalar u,
@@ -343,24 +364,28 @@
   {
     return Spline::BasisFunctions(u, degree(), knots());
   }
 
   /* --------------------------------------------------------------------------------------------- */
-
-  template <typename SplineType, typename DerivativeType>
-  void basisFunctionDerivativesImpl(const SplineType& spline, typename SplineType::Scalar u, DenseIndex order, DerivativeType& N_)
+  
+  
+  template <typename _Scalar, int _Dim, int _Degree>
+  template <typename DerivativeType>
+  void Spline<_Scalar, _Dim, _Degree>::BasisFunctionDerivativesImpl(
+    const typename Spline<_Scalar, _Dim, _Degree>::Scalar u,
+    const DenseIndex order,
+    const DenseIndex p, 
+    const typename Spline<_Scalar, _Dim, _Degree>::KnotVectorType& U,
+    DerivativeType& N_)
   {
+    typedef Spline<_Scalar, _Dim, _Degree> SplineType;
     enum { Order = SplineTraits<SplineType>::OrderAtCompileTime };
 
     typedef typename SplineTraits<SplineType>::Scalar Scalar;
     typedef typename SplineTraits<SplineType>::BasisVectorType BasisVectorType;
-    typedef typename SplineTraits<SplineType>::KnotVectorType KnotVectorType;
-
-    const KnotVectorType& U = spline.knots();
-
-    const DenseIndex p = spline.degree();
-    const DenseIndex span = spline.span(u);
+  
+    const DenseIndex span = SplineType::Span(u, p, U);
 
     const DenseIndex n = (std::min)(p, order);
 
     N_.resize(n+1, p+1);
 
@@ -367,11 +392,11 @@
     BasisVectorType left = BasisVectorType::Zero(p+1);
     BasisVectorType right = BasisVectorType::Zero(p+1);
 
     Matrix<Scalar,Order,Order> ndu(p+1,p+1);
 
-    double saved, temp;
+    Scalar saved, temp; // FIXME These were double instead of Scalar. Was there a reason for that?
 
     ndu(0,0) = 1.0;
 
     DenseIndex j;
     for (j=1; j<=p; ++j)
@@ -406,11 +431,11 @@
       a(0,0) = 1.0;
 
       // Compute the k-th derivative
       for (DenseIndex k=1; k<=static_cast<DenseIndex>(n); ++k)
       {
-        double d = 0.0;
+        Scalar d = 0.0;
         DenseIndex rk,pk,j1,j2;
         rk = r-k; pk = p-k;
 
         if (r>=k)
         {
@@ -444,31 +469,44 @@
     /* Multiply through by the correct factors */
     /* (Eq. [2.9])                             */
     r = p;
     for (DenseIndex k=1; k<=static_cast<DenseIndex>(n); ++k)
     {
-      for (DenseIndex j=p; j>=0; --j) N_(k,j) *= r;
+      for (j=p; j>=0; --j) N_(k,j) *= r;
       r *= p-k;
     }
   }
 
   template <typename _Scalar, int _Dim, int _Degree>
   typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::BasisDerivativeType
     Spline<_Scalar, _Dim, _Degree>::basisFunctionDerivatives(Scalar u, DenseIndex order) const
   {
-    typename SplineTraits< Spline >::BasisDerivativeType der;
-    basisFunctionDerivativesImpl(*this, u, order, der);
+    typename SplineTraits<Spline<_Scalar, _Dim, _Degree> >::BasisDerivativeType der;
+    BasisFunctionDerivativesImpl(u, order, degree(), knots(), der);
     return der;
   }
 
   template <typename _Scalar, int _Dim, int _Degree>
   template <int DerivativeOrder>
   typename SplineTraits< Spline<_Scalar, _Dim, _Degree>, DerivativeOrder >::BasisDerivativeType
     Spline<_Scalar, _Dim, _Degree>::basisFunctionDerivatives(Scalar u, DenseIndex order) const
   {
-    typename SplineTraits< Spline, DerivativeOrder >::BasisDerivativeType der;
-    basisFunctionDerivativesImpl(*this, u, order, der);
+    typename SplineTraits< Spline<_Scalar, _Dim, _Degree>, DerivativeOrder >::BasisDerivativeType der;
+    BasisFunctionDerivativesImpl(u, order, degree(), knots(), der);
+    return der;
+  }
+
+  template <typename _Scalar, int _Dim, int _Degree>
+  typename SplineTraits<Spline<_Scalar, _Dim, _Degree> >::BasisDerivativeType
+  Spline<_Scalar, _Dim, _Degree>::BasisFunctionDerivatives(
+    const typename Spline<_Scalar, _Dim, _Degree>::Scalar u,
+    const DenseIndex order,
+    const DenseIndex degree,
+    const typename Spline<_Scalar, _Dim, _Degree>::KnotVectorType& knots)
+  {
+    typename SplineTraits<Spline>::BasisDerivativeType der;
+    BasisFunctionDerivativesImpl(u, order, degree, knots, der);
     return der;
   }
 }
 
 #endif // EIGEN_SPLINE_H

Index: 3rd_party/eigen/unsupported/Eigen/src/Splines/SplineFitting.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Splines/SplineFitting.h
+++ 3rd_party/eigen/unsupported/Eigen/src/Splines/SplineFitting.h
@@ -8,14 +8,18 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPLINE_FITTING_H
 #define EIGEN_SPLINE_FITTING_H
 
+#include <algorithm>
+#include <functional>
 #include <numeric>
+#include <vector>
 
 #include "SplineFwd.h"
 
+#include <Eigen/LU>
 #include <Eigen/QR>
 
 namespace Eigen
 {
   /**
@@ -46,10 +50,133 @@
       knots(j+degree) = parameters.segment(j,degree).mean();
 
     knots.segment(0,degree+1) = KnotVectorType::Zero(degree+1);
     knots.segment(knots.size()-degree-1,degree+1) = KnotVectorType::Ones(degree+1);
   }
+
+  /**
+   * \brief Computes knot averages when derivative constraints are present.
+   * Note that this is a technical interpretation of the referenced article
+   * since the algorithm contained therein is incorrect as written.
+   * \ingroup Splines_Module
+   *
+   * \param[in] parameters The parameters at which the interpolation B-Spline
+   *            will intersect the given interpolation points. The parameters
+   *            are assumed to be a non-decreasing sequence.
+   * \param[in] degree The degree of the interpolating B-Spline. This must be
+   *            greater than zero.
+   * \param[in] derivativeIndices The indices corresponding to parameters at
+   *            which there are derivative constraints. The indices are assumed
+   *            to be a non-decreasing sequence.
+   * \param[out] knots The calculated knot vector. These will be returned as a
+   *             non-decreasing sequence
+   *
+   * \sa Les A. Piegl, Khairan Rajab, Volha Smarodzinana. 2008.
+   * Curve interpolation with directional constraints for engineering design. 
+   * Engineering with Computers
+   **/
+  template <typename KnotVectorType, typename ParameterVectorType, typename IndexArray>
+  void KnotAveragingWithDerivatives(const ParameterVectorType& parameters,
+                                    const unsigned int degree,
+                                    const IndexArray& derivativeIndices,
+                                    KnotVectorType& knots)
+  {
+    typedef typename ParameterVectorType::Scalar Scalar;
+
+    DenseIndex numParameters = parameters.size();
+    DenseIndex numDerivatives = derivativeIndices.size();
+
+    if (numDerivatives < 1)
+    {
+      KnotAveraging(parameters, degree, knots);
+      return;
+    }
+
+    DenseIndex startIndex;
+    DenseIndex endIndex;
+  
+    DenseIndex numInternalDerivatives = numDerivatives;
+    
+    if (derivativeIndices[0] == 0)
+    {
+      startIndex = 0;
+      --numInternalDerivatives;
+    }
+    else
+    {
+      startIndex = 1;
+    }
+    if (derivativeIndices[numDerivatives - 1] == numParameters - 1)
+    {
+      endIndex = numParameters - degree;
+      --numInternalDerivatives;
+    }
+    else
+    {
+      endIndex = numParameters - degree - 1;
+    }
+
+    // There are (endIndex - startIndex + 1) knots obtained from the averaging
+    // and 2 for the first and last parameters.
+    DenseIndex numAverageKnots = endIndex - startIndex + 3;
+    KnotVectorType averageKnots(numAverageKnots);
+    averageKnots[0] = parameters[0];
+
+    int newKnotIndex = 0;
+    for (DenseIndex i = startIndex; i <= endIndex; ++i)
+      averageKnots[++newKnotIndex] = parameters.segment(i, degree).mean();
+    averageKnots[++newKnotIndex] = parameters[numParameters - 1];
+
+    newKnotIndex = -1;
+  
+    ParameterVectorType temporaryParameters(numParameters + 1);
+    KnotVectorType derivativeKnots(numInternalDerivatives);
+    for (DenseIndex i = 0; i < numAverageKnots - 1; ++i)
+    {
+      temporaryParameters[0] = averageKnots[i];
+      ParameterVectorType parameterIndices(numParameters);
+      int temporaryParameterIndex = 1;
+      for (DenseIndex j = 0; j < numParameters; ++j)
+      {
+        Scalar parameter = parameters[j];
+        if (parameter >= averageKnots[i] && parameter < averageKnots[i + 1])
+        {
+          parameterIndices[temporaryParameterIndex] = j;
+          temporaryParameters[temporaryParameterIndex++] = parameter;
+        }
+      }
+      temporaryParameters[temporaryParameterIndex] = averageKnots[i + 1];
+
+      for (int j = 0; j <= temporaryParameterIndex - 2; ++j)
+      {
+        for (DenseIndex k = 0; k < derivativeIndices.size(); ++k)
+        {
+          if (parameterIndices[j + 1] == derivativeIndices[k]
+              && parameterIndices[j + 1] != 0
+              && parameterIndices[j + 1] != numParameters - 1)
+          {
+            derivativeKnots[++newKnotIndex] = temporaryParameters.segment(j, 3).mean();
+            break;
+          }
+        }
+      }
+    }
+    
+    KnotVectorType temporaryKnots(averageKnots.size() + derivativeKnots.size());
+
+    std::merge(averageKnots.data(), averageKnots.data() + averageKnots.size(),
+               derivativeKnots.data(), derivativeKnots.data() + derivativeKnots.size(),
+               temporaryKnots.data());
+
+    // Number of knots (one for each point and derivative) plus spline order.
+    DenseIndex numKnots = numParameters + numDerivatives + degree + 1;
+    knots.resize(numKnots);
+
+    knots.head(degree).fill(temporaryKnots[0]);
+    knots.tail(degree).fill(temporaryKnots.template tail<1>()[0]);
+    knots.segment(degree, temporaryKnots.size()) = temporaryKnots;
+  }
 
   /**
    * \brief Computes chord length parameters which are required for spline interpolation.
    * \ingroup Splines_Module
    *
@@ -84,10 +211,11 @@
    **/     
   template <typename SplineType>
   struct SplineFitting
   {
     typedef typename SplineType::KnotVectorType KnotVectorType;
+    typedef typename SplineType::ParameterVectorType ParameterVectorType;
 
     /**
      * \brief Fits an interpolating Spline to the given data points.
      *
      * \param pts The points for which an interpolating spline will be computed.
@@ -107,10 +235,56 @@
      *
      * \returns A spline interpolating the initially provided points.
      **/
     template <typename PointArrayType>
     static SplineType Interpolate(const PointArrayType& pts, DenseIndex degree, const KnotVectorType& knot_parameters);
+
+    /**
+     * \brief Fits an interpolating spline to the given data points and
+     * derivatives.
+     * 
+     * \param points The points for which an interpolating spline will be computed.
+     * \param derivatives The desired derivatives of the interpolating spline at interpolation
+     *                    points.
+     * \param derivativeIndices An array indicating which point each derivative belongs to. This
+     *                          must be the same size as @a derivatives.
+     * \param degree The degree of the interpolating spline.
+     *
+     * \returns A spline interpolating @a points with @a derivatives at those points.
+     *
+     * \sa Les A. Piegl, Khairan Rajab, Volha Smarodzinana. 2008.
+     * Curve interpolation with directional constraints for engineering design. 
+     * Engineering with Computers
+     **/
+    template <typename PointArrayType, typename IndexArray>
+    static SplineType InterpolateWithDerivatives(const PointArrayType& points,
+                                                 const PointArrayType& derivatives,
+                                                 const IndexArray& derivativeIndices,
+                                                 const unsigned int degree);
+
+    /**
+     * \brief Fits an interpolating spline to the given data points and derivatives.
+     * 
+     * \param points The points for which an interpolating spline will be computed.
+     * \param derivatives The desired derivatives of the interpolating spline at interpolation points.
+     * \param derivativeIndices An array indicating which point each derivative belongs to. This
+     *                          must be the same size as @a derivatives.
+     * \param degree The degree of the interpolating spline.
+     * \param parameters The parameters corresponding to the interpolation points.
+     *
+     * \returns A spline interpolating @a points with @a derivatives at those points.
+     *
+     * \sa Les A. Piegl, Khairan Rajab, Volha Smarodzinana. 2008.
+     * Curve interpolation with directional constraints for engineering design. 
+     * Engineering with Computers
+     */
+    template <typename PointArrayType, typename IndexArray>
+    static SplineType InterpolateWithDerivatives(const PointArrayType& points,
+                                                 const PointArrayType& derivatives,
+                                                 const IndexArray& derivativeIndices,
+                                                 const unsigned int degree,
+                                                 const ParameterVectorType& parameters);
   };
 
   template <typename SplineType>
   template <typename PointArrayType>
   SplineType SplineFitting<SplineType>::Interpolate(const PointArrayType& pts, DenseIndex degree, const KnotVectorType& knot_parameters)
@@ -149,8 +323,108 @@
   {
     KnotVectorType chord_lengths; // knot parameters
     ChordLengths(pts, chord_lengths);
     return Interpolate(pts, degree, chord_lengths);
   }
+  
+  template <typename SplineType>
+  template <typename PointArrayType, typename IndexArray>
+  SplineType 
+  SplineFitting<SplineType>::InterpolateWithDerivatives(const PointArrayType& points,
+                                                        const PointArrayType& derivatives,
+                                                        const IndexArray& derivativeIndices,
+                                                        const unsigned int degree,
+                                                        const ParameterVectorType& parameters)
+  {
+    typedef typename SplineType::KnotVectorType::Scalar Scalar;      
+    typedef typename SplineType::ControlPointVectorType ControlPointVectorType;
+
+    typedef Matrix<Scalar, Dynamic, Dynamic> MatrixType;
+
+    const DenseIndex n = points.cols() + derivatives.cols();
+    
+    KnotVectorType knots;
+
+    KnotAveragingWithDerivatives(parameters, degree, derivativeIndices, knots);
+    
+    // fill matrix
+    MatrixType A = MatrixType::Zero(n, n);
+
+    // Use these dimensions for quicker populating, then transpose for solving.
+    MatrixType b(points.rows(), n);
+
+    DenseIndex startRow;
+    DenseIndex derivativeStart;
+
+    // End derivatives.
+    if (derivativeIndices[0] == 0)
+    {
+      A.template block<1, 2>(1, 0) << -1, 1;
+      
+      Scalar y = (knots(degree + 1) - knots(0)) / degree;
+      b.col(1) = y*derivatives.col(0);
+      
+      startRow = 2;
+      derivativeStart = 1;
+    }
+    else
+    {
+      startRow = 1;
+      derivativeStart = 0;
+    }
+    if (derivativeIndices[derivatives.cols() - 1] == points.cols() - 1)
+    {
+      A.template block<1, 2>(n - 2, n - 2) << -1, 1;
+
+      Scalar y = (knots(knots.size() - 1) - knots(knots.size() - (degree + 2))) / degree;
+      b.col(b.cols() - 2) = y*derivatives.col(derivatives.cols() - 1);
+    }
+    
+    DenseIndex row = startRow;
+    DenseIndex derivativeIndex = derivativeStart;
+    for (DenseIndex i = 1; i < parameters.size() - 1; ++i)
+    {
+      const DenseIndex span = SplineType::Span(parameters[i], degree, knots);
+
+      if (derivativeIndices[derivativeIndex] == i)
+      {
+        A.block(row, span - degree, 2, degree + 1)
+          = SplineType::BasisFunctionDerivatives(parameters[i], 1, degree, knots);
+
+        b.col(row++) = points.col(i);
+        b.col(row++) = derivatives.col(derivativeIndex++);
+      }
+      else
+      {
+        A.row(row++).segment(span - degree, degree + 1)
+          = SplineType::BasisFunctions(parameters[i], degree, knots);
+      }
+    }
+    b.col(0) = points.col(0);
+    b.col(b.cols() - 1) = points.col(points.cols() - 1);
+    A(0,0) = 1;
+    A(n - 1, n - 1) = 1;
+    
+    // Solve
+    FullPivLU<MatrixType> lu(A);
+    ControlPointVectorType controlPoints = lu.solve(MatrixType(b.transpose())).transpose();
+
+    SplineType spline(knots, controlPoints);
+    
+    return spline;
+  }
+  
+  template <typename SplineType>
+  template <typename PointArrayType, typename IndexArray>
+  SplineType
+  SplineFitting<SplineType>::InterpolateWithDerivatives(const PointArrayType& points,
+                                                        const PointArrayType& derivatives,
+                                                        const IndexArray& derivativeIndices,
+                                                        const unsigned int degree)
+  {
+    ParameterVectorType parameters;
+    ChordLengths(points, parameters);
+    return InterpolateWithDerivatives(points, derivatives, derivativeIndices, degree, parameters);
+  }
 }
 
 #endif // EIGEN_SPLINE_FITTING_H

Index: 3rd_party/eigen/unsupported/Eigen/src/Splines/SplineFwd.h
==================================================================
--- 3rd_party/eigen/unsupported/Eigen/src/Splines/SplineFwd.h
+++ 3rd_party/eigen/unsupported/Eigen/src/Splines/SplineFwd.h
@@ -29,25 +29,30 @@
       enum { Dimension = _Dim /*!< The spline curve's dimension. */ };
       enum { Degree = _Degree /*!< The spline curve's degree. */ };
 
       enum { OrderAtCompileTime = _Degree==Dynamic ? Dynamic : _Degree+1 /*!< The spline curve's order at compile-time. */ };
       enum { NumOfDerivativesAtCompileTime = OrderAtCompileTime /*!< The number of derivatives defined for the current spline. */ };
+      
+      enum { DerivativeMemoryLayout = Dimension==1 ? RowMajor : ColMajor /*!< The derivative type's memory layout. */ };
 
       /** \brief The data type used to store non-zero basis functions. */
       typedef Array<Scalar,1,OrderAtCompileTime> BasisVectorType;
 
       /** \brief The data type used to store the values of the basis function derivatives. */
       typedef Array<Scalar,Dynamic,Dynamic,RowMajor,NumOfDerivativesAtCompileTime,OrderAtCompileTime> BasisDerivativeType;
       
       /** \brief The data type used to store the spline's derivative values. */
-      typedef Array<Scalar,Dimension,Dynamic,ColMajor,Dimension,NumOfDerivativesAtCompileTime> DerivativeType;
+      typedef Array<Scalar,Dimension,Dynamic,DerivativeMemoryLayout,Dimension,NumOfDerivativesAtCompileTime> DerivativeType;
 
       /** \brief The point type the spline is representing. */
       typedef Array<Scalar,Dimension,1> PointType;
       
       /** \brief The data type used to store knot vectors. */
       typedef Array<Scalar,1,Dynamic> KnotVectorType;
+
+      /** \brief The data type used to store parameter vectors. */
+      typedef Array<Scalar,1,Dynamic> ParameterVectorType;
       
       /** \brief The data type representing the spline's control points. */
       typedef Array<Scalar,Dimension,Dynamic> ControlPointVectorType;
     };
 
@@ -60,16 +65,18 @@
     template < typename _Scalar, int _Dim, int _Degree, int _DerivativeOrder >
     struct SplineTraits< Spline<_Scalar, _Dim, _Degree>, _DerivativeOrder > : public SplineTraits< Spline<_Scalar, _Dim, _Degree> >
     {
       enum { OrderAtCompileTime = _Degree==Dynamic ? Dynamic : _Degree+1 /*!< The spline curve's order at compile-time. */ };
       enum { NumOfDerivativesAtCompileTime = _DerivativeOrder==Dynamic ? Dynamic : _DerivativeOrder+1 /*!< The number of derivatives defined for the current spline. */ };
+      
+      enum { DerivativeMemoryLayout = _Dim==1 ? RowMajor : ColMajor /*!< The derivative type's memory layout. */ };
 
       /** \brief The data type used to store the values of the basis function derivatives. */
       typedef Array<_Scalar,Dynamic,Dynamic,RowMajor,NumOfDerivativesAtCompileTime,OrderAtCompileTime> BasisDerivativeType;
       
       /** \brief The data type used to store the spline's derivative values. */      
-      typedef Array<_Scalar,_Dim,Dynamic,ColMajor,_Dim,NumOfDerivativesAtCompileTime> DerivativeType;
+      typedef Array<_Scalar,_Dim,Dynamic,DerivativeMemoryLayout,_Dim,NumOfDerivativesAtCompileTime> DerivativeType;
     };
 
     /** \brief 2D float B-spline with dynamic degree. */
     typedef Spline<float,2> Spline2f;
     

Index: 3rd_party/eigen/unsupported/doc/Overview.dox
==================================================================
--- 3rd_party/eigen/unsupported/doc/Overview.dox
+++ 3rd_party/eigen/unsupported/doc/Overview.dox
@@ -1,25 +1,28 @@
+/// \brief Namespace containing all symbols from the %Eigen library.
 namespace Eigen {
 
-/** \mainpage Eigen's unsupported modules
+/** \mainpage %Eigen's unsupported modules
 
-This is the API documentation for Eigen's unsupported modules.
+This is the API documentation for %Eigen's unsupported modules.
 
 These modules are contributions from various users. They are provided "as is", without any support.
 
 Click on the \e Modules tab at the top of this page to get a list of all unsupported modules.
 
-Don't miss the <a href="..//index.html">official Eigen documentation</a>.
+Don't miss the <a href="../index.html">official Eigen documentation</a>.
 
 */
 
 /*
 
 \defgroup Unsupported_modules Unsupported modules
 
 The unsupported modules are contributions from various users. They are
 provided "as is", without any support. Nevertheless, some of them are
-subject to be included in Eigen in the future.
+subject to be included in %Eigen in the future.
 
 */
 
+/// \internal \brief Namespace containing low-level routines from the %Eigen library.
+namespace internal {}
 }

Index: 3rd_party/eigen/unsupported/doc/examples/BVH_Example.cpp
==================================================================
--- 3rd_party/eigen/unsupported/doc/examples/BVH_Example.cpp
+++ 3rd_party/eigen/unsupported/doc/examples/BVH_Example.cpp
@@ -4,13 +4,11 @@
 
 using namespace Eigen;
 typedef AlignedBox<double, 2> Box2d;
 
 namespace Eigen {
-    namespace internal {
-        Box2d bounding_box(const Vector2d &v) { return Box2d(v, v); } //compute the bounding box of a single point
-    }
+  Box2d bounding_box(const Vector2d &v) { return Box2d(v, v); } //compute the bounding box of a single point
 }
 
 struct PointPointMinimizer //how to compute squared distances between points and rectangles
 {
   PointPointMinimizer() : calls(0) {}

ADDED   3rd_party/eigen/unsupported/doc/examples/EulerAngles.cpp
Index: 3rd_party/eigen/unsupported/doc/examples/EulerAngles.cpp
==================================================================
--- 3rd_party/eigen/unsupported/doc/examples/EulerAngles.cpp
+++ 3rd_party/eigen/unsupported/doc/examples/EulerAngles.cpp
@@ -0,0 +1,46 @@
+#include <unsupported/Eigen/EulerAngles>
+#include <iostream>
+
+using namespace Eigen;
+
+int main()
+{
+  // A common Euler system by many armies around the world,
+  //  where the first one is the azimuth(the angle from the north -
+  //   the same angle that is show in compass)
+  //  and the second one is elevation(the angle from the horizon)
+  //  and the third one is roll(the angle between the horizontal body
+  //   direction and the plane ground surface)
+  // Keep remembering we're using radian angles here!
+  typedef EulerSystem<-EULER_Z, EULER_Y, EULER_X> MyArmySystem;
+  typedef EulerAngles<double, MyArmySystem> MyArmyAngles;
+  
+  MyArmyAngles vehicleAngles(
+    3.14/*PI*/ / 2, /* heading to east, notice that this angle is counter-clockwise */
+    -0.3, /* going down from a mountain */
+    0.1); /* slightly rolled to the right */
+  
+  // Some Euler angles representation that our plane use.
+  EulerAnglesZYZd planeAngles(0.78474, 0.5271, -0.513794);
+  
+  MyArmyAngles planeAnglesInMyArmyAngles = MyArmyAngles::FromRotation<true, false, false>(planeAngles);
+  
+  std::cout << "vehicle angles(MyArmy):     " << vehicleAngles << std::endl;
+  std::cout << "plane angles(ZYZ):        " << planeAngles << std::endl;
+  std::cout << "plane angles(MyArmy):     " << planeAnglesInMyArmyAngles << std::endl;
+  
+  // Now lets rotate the plane a little bit
+  std::cout << "==========================================================\n";
+  std::cout << "rotating plane now!\n";
+  std::cout << "==========================================================\n";
+  
+  Quaterniond planeRotated = AngleAxisd(-0.342, Vector3d::UnitY()) * planeAngles;
+  
+  planeAngles = planeRotated;
+  planeAnglesInMyArmyAngles = MyArmyAngles::FromRotation<true, false, false>(planeRotated);
+  
+  std::cout << "new plane angles(ZYZ):     " << planeAngles << std::endl;
+  std::cout << "new plane angles(MyArmy): " << planeAnglesInMyArmyAngles << std::endl;
+  
+  return 0;
+}

Index: 3rd_party/eigen/unsupported/test/CMakeLists.txt
==================================================================
--- 3rd_party/eigen/unsupported/test/CMakeLists.txt
+++ 3rd_party/eigen/unsupported/test/CMakeLists.txt
@@ -1,11 +1,27 @@
+# generate split test header file only if it does not yet exist
+# in order to prevent a rebuild everytime cmake is configured
+if(NOT EXISTS ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h)
+  file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h "")
+  foreach(i RANGE 1 999)
+    file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h
+      "#ifdef EIGEN_TEST_PART_${i}\n"
+      "#define CALL_SUBTEST_${i}(FUNC) CALL_SUBTEST(FUNC)\n"
+      "#else\n"
+      "#define CALL_SUBTEST_${i}(FUNC)\n"
+      "#endif\n\n"
+    )
+  endforeach()
+endif()
 
 set_property(GLOBAL PROPERTY EIGEN_CURRENT_SUBPROJECT "Unsupported")
 add_custom_target(BuildUnsupported)
 
-include_directories(../../test ../../unsupported ../../Eigen 
+include_directories(../../test ../../unsupported ../../Eigen
                     ${CMAKE_CURRENT_BINARY_DIR}/../../test)
+
+find_package (Threads)
 
 find_package(GoogleHash)
 if(GOOGLEHASH_FOUND)
   add_definitions("-DEIGEN_GOOGLEHASH_SUPPORT")
   include_directories(${GOOGLEHASH_INCLUDES})
@@ -26,26 +42,34 @@
 # this test seems to never have been successful on x87, so is considered to contain a FP-related bug.
 # see thread: "non-linear optimization test summary"
 ei_add_test(NonLinearOptimization)
 
 ei_add_test(NumericalDiff)
+ei_add_test(autodiff_scalar)
 ei_add_test(autodiff)
+
+if (NOT CMAKE_CXX_COMPILER MATCHES "clang\\+\\+$")
 ei_add_test(BVH)
+endif()
+
 ei_add_test(matrix_exponential)
 ei_add_test(matrix_function)
 ei_add_test(matrix_power)
 ei_add_test(matrix_square_root)
 ei_add_test(alignedvector3)
+
 ei_add_test(FFT)
+
+ei_add_test(EulerAngles)
 
 find_package(MPFR 2.3.0)
 find_package(GMP)
-if(MPFR_FOUND)
+if(MPFR_FOUND AND EIGEN_COMPILER_SUPPORT_CXX11)
   include_directories(${MPFR_INCLUDES} ./mpreal)
   ei_add_property(EIGEN_TESTED_BACKENDS "MPFR C++, ")
   set(EIGEN_MPFR_TEST_LIBRARIES ${MPFR_LIBRARIES} ${GMP_LIBRARIES})
-  ei_add_test(mpreal_support "" "${EIGEN_MPFR_TEST_LIBRARIES}" )
+ ei_add_test(mpreal_support "-std=c++11" "${EIGEN_MPFR_TEST_LIBRARIES}" )
 else()
   ei_add_property(EIGEN_MISSING_BACKENDS "MPFR C++, ")
 endif()
 
 ei_add_test(sparse_extra   "" "")
@@ -80,11 +104,154 @@
     ei_add_property(EIGEN_MISSING_BACKENDS "OpenGL, ")
 endif()
 
 ei_add_test(polynomialsolver)
 ei_add_test(polynomialutils)
-ei_add_test(kronecker_product)
 ei_add_test(splines)
 ei_add_test(gmres)
 ei_add_test(minres)
 ei_add_test(levenberg_marquardt)
-ei_add_test(bdcsvd)
+ei_add_test(kronecker_product)
+ei_add_test(special_functions)
+
+# TODO: The following test names are prefixed with the cxx11 string, since historically
+# the tests depended on c++11. This isn't the case anymore so we ought to rename them.
+# FIXME: Old versions of MSVC fail to compile this code, so we just disable these tests
+# when using visual studio. We should make the check more strict to enable the tests for
+# newer versions of MSVC.
+if (NOT CMAKE_CXX_COMPILER_ID STREQUAL "MSVC")
+ei_add_test(cxx11_tensor_dimension)
+ei_add_test(cxx11_tensor_map)
+ei_add_test(cxx11_tensor_assign)
+ei_add_test(cxx11_tensor_comparisons)
+ei_add_test(cxx11_tensor_forced_eval)
+ei_add_test(cxx11_tensor_math)
+ei_add_test(cxx11_tensor_const)
+ei_add_test(cxx11_tensor_intdiv)
+ei_add_test(cxx11_tensor_casts)
+ei_add_test(cxx11_tensor_empty)
+ei_add_test(cxx11_tensor_sugar)
+ei_add_test(cxx11_tensor_roundings)
+ei_add_test(cxx11_tensor_layout_swap)
+ei_add_test(cxx11_tensor_io)
+if("${CMAKE_SIZEOF_VOID_P}" EQUAL "8")
+  # This test requires __uint128_t which is only available on 64bit systems
+  ei_add_test(cxx11_tensor_uint128)
+endif()
+endif()
+
+if(EIGEN_TEST_CXX11)
+  if(EIGEN_TEST_SYCL)
+    ei_add_test_sycl(cxx11_tensor_sycl "-std=c++11")
+    ei_add_test_sycl(cxx11_tensor_forced_eval_sycl "-std=c++11")
+    ei_add_test_sycl(cxx11_tensor_broadcast_sycl "-std=c++11")
+    ei_add_test_sycl(cxx11_tensor_device_sycl "-std=c++11")
+    ei_add_test_sycl(cxx11_tensor_reduction_sycl "-std=c++11")
+  endif(EIGEN_TEST_SYCL)
+  # It should be safe to always run these tests as there is some fallback code for
+  # older compiler that don't support cxx11.
+  set(CMAKE_CXX_STANDARD 11)
+
+  ei_add_test(cxx11_eventcount "-pthread" "${CMAKE_THREAD_LIBS_INIT}")
+  ei_add_test(cxx11_runqueue "-pthread" "${CMAKE_THREAD_LIBS_INIT}")
+  ei_add_test(cxx11_non_blocking_thread_pool "-pthread" "${CMAKE_THREAD_LIBS_INIT}")
+
+  ei_add_test(cxx11_meta)
+  ei_add_test(cxx11_tensor_simple)
+#  ei_add_test(cxx11_tensor_symmetry)
+  ei_add_test(cxx11_tensor_index_list)
+  ei_add_test(cxx11_tensor_mixed_indices)
+  ei_add_test(cxx11_tensor_contraction)
+  ei_add_test(cxx11_tensor_convolution)
+  ei_add_test(cxx11_tensor_expr)
+  ei_add_test(cxx11_tensor_fixed_size)
+  ei_add_test(cxx11_tensor_of_const_values)
+  ei_add_test(cxx11_tensor_of_complex)
+  ei_add_test(cxx11_tensor_of_strings)
+  ei_add_test(cxx11_tensor_lvalue)
+  ei_add_test(cxx11_tensor_broadcasting)
+  ei_add_test(cxx11_tensor_chipping)
+  ei_add_test(cxx11_tensor_concatenation)
+  ei_add_test(cxx11_tensor_inflation)
+  ei_add_test(cxx11_tensor_morphing)
+  ei_add_test(cxx11_tensor_padding)
+  ei_add_test(cxx11_tensor_patch)
+  ei_add_test(cxx11_tensor_image_patch)
+  ei_add_test(cxx11_tensor_volume_patch)
+  ei_add_test(cxx11_tensor_reduction)
+  ei_add_test(cxx11_tensor_argmax)
+  ei_add_test(cxx11_tensor_shuffling)
+  ei_add_test(cxx11_tensor_striding)
+  ei_add_test(cxx11_tensor_notification "-pthread" "${CMAKE_THREAD_LIBS_INIT}")
+  ei_add_test(cxx11_tensor_thread_pool "-pthread" "${CMAKE_THREAD_LIBS_INIT}")
+  ei_add_test(cxx11_tensor_ref)
+  ei_add_test(cxx11_tensor_random)
+  ei_add_test(cxx11_tensor_generator)
+  ei_add_test(cxx11_tensor_custom_op)
+  ei_add_test(cxx11_tensor_custom_index)
+  ei_add_test(cxx11_tensor_fft)
+  ei_add_test(cxx11_tensor_ifft)
+  ei_add_test(cxx11_tensor_scan)
+
+endif()
+
+# These tests needs nvcc
+find_package(CUDA 7.0)
+if(CUDA_FOUND AND EIGEN_TEST_CUDA)
+  # Make sure to compile without the -pedantic, -Wundef, -Wnon-virtual-dtor
+  # and -fno-check-new flags since they trigger thousands of compilation warnings
+  # in the CUDA runtime
+  # Also remove -ansi that is incompatible with std=c++11.
+  string(REPLACE "-pedantic" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
+  string(REPLACE "-Wundef" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
+  string(REPLACE "-Wnon-virtual-dtor" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
+  string(REPLACE "-fno-check-new" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
+  string(REPLACE "-ansi" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
+
+  message(STATUS "Flags used to compile cuda code: " ${CMAKE_CXX_FLAGS})
+
+  if("${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang")
+    set(CUDA_NVCC_FLAGS "-ccbin ${CMAKE_C_COMPILER}" CACHE STRING "nvcc flags" FORCE)
+  endif()
+  if(EIGEN_TEST_CUDA_CLANG)
+   set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 --cuda-gpu-arch=sm_${EIGEN_CUDA_COMPUTE_ARCH}")
+  endif()
+
+  set(EIGEN_CUDA_RELAXED_CONSTEXPR "--expt-relaxed-constexpr")
+  if (${CUDA_VERSION} STREQUAL "7.0")
+    set(EIGEN_CUDA_RELAXED_CONSTEXPR "--relaxed-constexpr")
+  endif()
+
+  if( (NOT EIGEN_TEST_CXX11) OR (CMAKE_VERSION VERSION_LESS 3.3))
+    set(EIGEN_CUDA_CXX11_FLAG "-std=c++11")
+  else()
+    # otherwise the flag has already been added because of the above set(CMAKE_CXX_STANDARD 11)
+    set(EIGEN_CUDA_CXX11_FLAG "")
+  endif()
+
+  set(CUDA_NVCC_FLAGS  "${EIGEN_CUDA_CXX11_FLAG} ${EIGEN_CUDA_RELAXED_CONSTEXPR} -arch compute_${EIGEN_CUDA_COMPUTE_ARCH} -Xcudafe \"--display_error_number\" ${CUDA_NVCC_FLAGS}")
+  cuda_include_directories("${CMAKE_CURRENT_BINARY_DIR}" "${CUDA_TOOLKIT_ROOT_DIR}/include")
+  set(EIGEN_ADD_TEST_FILENAME_EXTENSION "cu")
+
+  ei_add_test(cxx11_tensor_complex_cuda)
+  ei_add_test(cxx11_tensor_complex_cwise_ops_cuda)
+  ei_add_test(cxx11_tensor_reduction_cuda)
+  ei_add_test(cxx11_tensor_argmax_cuda)
+  ei_add_test(cxx11_tensor_cast_float16_cuda)
+  ei_add_test(cxx11_tensor_scan_cuda)
+
+  # Contractions require arch 3.0 or higher
+  if (${EIGEN_CUDA_COMPUTE_ARCH} GREATER 29)
+    ei_add_test(cxx11_tensor_device)
+    ei_add_test(cxx11_tensor_cuda)
+    ei_add_test(cxx11_tensor_contract_cuda)
+    ei_add_test(cxx11_tensor_of_float16_cuda)
+  endif()
+
+  # The random number generation code requires arch 3.5 or greater.
+  if (${EIGEN_CUDA_COMPUTE_ARCH} GREATER 34)
+    ei_add_test(cxx11_tensor_random_cuda)
+  endif()
+
+
+  unset(EIGEN_ADD_TEST_FILENAME_EXTENSION)
+endif()

ADDED   3rd_party/eigen/unsupported/test/EulerAngles.cpp
Index: 3rd_party/eigen/unsupported/test/EulerAngles.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/EulerAngles.cpp
+++ 3rd_party/eigen/unsupported/test/EulerAngles.cpp
@@ -0,0 +1,208 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Tal Hadad <tal_hd@hotmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <unsupported/Eigen/EulerAngles>
+
+using namespace Eigen;
+
+template<typename EulerSystem, typename Scalar>
+void verify_euler_ranged(const Matrix<Scalar,3,1>& ea,
+  bool positiveRangeAlpha, bool positiveRangeBeta, bool positiveRangeGamma)
+{
+  typedef EulerAngles<Scalar, EulerSystem> EulerAnglesType;
+  typedef Matrix<Scalar,3,3> Matrix3;
+  typedef Matrix<Scalar,3,1> Vector3;
+  typedef Quaternion<Scalar> QuaternionType;
+  typedef AngleAxis<Scalar> AngleAxisType;
+  using std::abs;
+  
+  Scalar alphaRangeStart, alphaRangeEnd;
+  Scalar betaRangeStart, betaRangeEnd;
+  Scalar gammaRangeStart, gammaRangeEnd;
+  
+  if (positiveRangeAlpha)
+  {
+    alphaRangeStart = Scalar(0);
+    alphaRangeEnd = Scalar(2 * EIGEN_PI);
+  }
+  else
+  {
+    alphaRangeStart = -Scalar(EIGEN_PI);
+    alphaRangeEnd = Scalar(EIGEN_PI);
+  }
+  
+  if (positiveRangeBeta)
+  {
+    betaRangeStart = Scalar(0);
+    betaRangeEnd = Scalar(2 * EIGEN_PI);
+  }
+  else
+  {
+    betaRangeStart = -Scalar(EIGEN_PI);
+    betaRangeEnd = Scalar(EIGEN_PI);
+  }
+  
+  if (positiveRangeGamma)
+  {
+    gammaRangeStart = Scalar(0);
+    gammaRangeEnd = Scalar(2 * EIGEN_PI);
+  }
+  else
+  {
+    gammaRangeStart = -Scalar(EIGEN_PI);
+    gammaRangeEnd = Scalar(EIGEN_PI);
+  }
+  
+  const int i = EulerSystem::AlphaAxisAbs - 1;
+  const int j = EulerSystem::BetaAxisAbs - 1;
+  const int k = EulerSystem::GammaAxisAbs - 1;
+  
+  const int iFactor = EulerSystem::IsAlphaOpposite ? -1 : 1;
+  const int jFactor = EulerSystem::IsBetaOpposite ? -1 : 1;
+  const int kFactor = EulerSystem::IsGammaOpposite ? -1 : 1;
+  
+  const Vector3 I = EulerAnglesType::AlphaAxisVector();
+  const Vector3 J = EulerAnglesType::BetaAxisVector();
+  const Vector3 K = EulerAnglesType::GammaAxisVector();
+  
+  EulerAnglesType e(ea[0], ea[1], ea[2]);
+  
+  Matrix3 m(e);
+  Vector3 eabis = EulerAnglesType(m, positiveRangeAlpha, positiveRangeBeta, positiveRangeGamma).angles();
+  
+  // Check that eabis in range
+  VERIFY(alphaRangeStart <= eabis[0] && eabis[0] <= alphaRangeEnd);
+  VERIFY(betaRangeStart <= eabis[1] && eabis[1] <= betaRangeEnd);
+  VERIFY(gammaRangeStart <= eabis[2] && eabis[2] <= gammaRangeEnd);
+  
+  Vector3 eabis2 = m.eulerAngles(i, j, k);
+  
+  // Invert the relevant axes
+  eabis2[0] *= iFactor;
+  eabis2[1] *= jFactor;
+  eabis2[2] *= kFactor;
+  
+  // Saturate the angles to the correct range
+  if (positiveRangeAlpha && (eabis2[0] < 0))
+    eabis2[0] += Scalar(2 * EIGEN_PI);
+  if (positiveRangeBeta && (eabis2[1] < 0))
+    eabis2[1] += Scalar(2 * EIGEN_PI);
+  if (positiveRangeGamma && (eabis2[2] < 0))
+    eabis2[2] += Scalar(2 * EIGEN_PI);
+  
+  VERIFY_IS_APPROX(eabis, eabis2);// Verify that our estimation is the same as m.eulerAngles() is
+  
+  Matrix3 mbis(AngleAxisType(eabis[0], I) * AngleAxisType(eabis[1], J) * AngleAxisType(eabis[2], K));
+  VERIFY_IS_APPROX(m,  mbis);
+  
+  // Tests that are only relevant for no possitive range
+  if (!(positiveRangeAlpha || positiveRangeBeta || positiveRangeGamma))
+  {
+    /* If I==K, and ea[1]==0, then there no unique solution. */ 
+    /* The remark apply in the case where I!=K, and |ea[1]| is close to pi/2. */ 
+    if( (i!=k || ea[1]!=0) && (i==k || !internal::isApprox(abs(ea[1]),Scalar(EIGEN_PI/2),test_precision<Scalar>())) ) 
+      VERIFY((ea-eabis).norm() <= test_precision<Scalar>());
+    
+    // approx_or_less_than does not work for 0
+    VERIFY(0 < eabis[0] || test_isMuchSmallerThan(eabis[0], Scalar(1)));
+  }
+  
+  // Quaternions
+  QuaternionType q(e);
+  eabis = EulerAnglesType(q, positiveRangeAlpha, positiveRangeBeta, positiveRangeGamma).angles();
+  VERIFY_IS_APPROX(eabis, eabis2);// Verify that the euler angles are still the same
+}
+
+template<typename EulerSystem, typename Scalar>
+void verify_euler(const Matrix<Scalar,3,1>& ea)
+{
+  verify_euler_ranged<EulerSystem>(ea, false, false, false);
+  verify_euler_ranged<EulerSystem>(ea, false, false, true);
+  verify_euler_ranged<EulerSystem>(ea, false, true, false);
+  verify_euler_ranged<EulerSystem>(ea, false, true, true);
+  verify_euler_ranged<EulerSystem>(ea, true, false, false);
+  verify_euler_ranged<EulerSystem>(ea, true, false, true);
+  verify_euler_ranged<EulerSystem>(ea, true, true, false);
+  verify_euler_ranged<EulerSystem>(ea, true, true, true);
+}
+
+template<typename Scalar> void check_all_var(const Matrix<Scalar,3,1>& ea)
+{
+  verify_euler<EulerSystemXYZ>(ea);
+  verify_euler<EulerSystemXYX>(ea);
+  verify_euler<EulerSystemXZY>(ea);
+  verify_euler<EulerSystemXZX>(ea);
+  
+  verify_euler<EulerSystemYZX>(ea);
+  verify_euler<EulerSystemYZY>(ea);
+  verify_euler<EulerSystemYXZ>(ea);
+  verify_euler<EulerSystemYXY>(ea);
+  
+  verify_euler<EulerSystemZXY>(ea);
+  verify_euler<EulerSystemZXZ>(ea);
+  verify_euler<EulerSystemZYX>(ea);
+  verify_euler<EulerSystemZYZ>(ea);
+}
+
+template<typename Scalar> void eulerangles()
+{
+  typedef Matrix<Scalar,3,3> Matrix3;
+  typedef Matrix<Scalar,3,1> Vector3;
+  typedef Array<Scalar,3,1> Array3;
+  typedef Quaternion<Scalar> Quaternionx;
+  typedef AngleAxis<Scalar> AngleAxisType;
+
+  Scalar a = internal::random<Scalar>(-Scalar(EIGEN_PI), Scalar(EIGEN_PI));
+  Quaternionx q1;
+  q1 = AngleAxisType(a, Vector3::Random().normalized());
+  Matrix3 m;
+  m = q1;
+  
+  Vector3 ea = m.eulerAngles(0,1,2);
+  check_all_var(ea);
+  ea = m.eulerAngles(0,1,0);
+  check_all_var(ea);
+  
+  // Check with purely random Quaternion:
+  q1.coeffs() = Quaternionx::Coefficients::Random().normalized();
+  m = q1;
+  ea = m.eulerAngles(0,1,2);
+  check_all_var(ea);
+  ea = m.eulerAngles(0,1,0);
+  check_all_var(ea);
+  
+  // Check with random angles in range [0:pi]x[-pi:pi]x[-pi:pi].
+  ea = (Array3::Random() + Array3(1,0,0))*Scalar(EIGEN_PI)*Array3(0.5,1,1);
+  check_all_var(ea);
+  
+  ea[2] = ea[0] = internal::random<Scalar>(0,Scalar(EIGEN_PI));
+  check_all_var(ea);
+  
+  ea[0] = ea[1] = internal::random<Scalar>(0,Scalar(EIGEN_PI));
+  check_all_var(ea);
+  
+  ea[1] = 0;
+  check_all_var(ea);
+  
+  ea.head(2).setZero();
+  check_all_var(ea);
+  
+  ea.setZero();
+  check_all_var(ea);
+}
+
+void test_EulerAngles()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( eulerangles<float>() );
+    CALL_SUBTEST_2( eulerangles<double>() );
+  }
+}

Index: 3rd_party/eigen/unsupported/test/FFTW.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/FFTW.cpp
+++ 3rd_party/eigen/unsupported/test/FFTW.cpp
@@ -16,15 +16,15 @@
 using namespace std;
 using namespace Eigen;
 
 
 template < typename T>
-complex<long double>  promote(complex<T> x) { return complex<long double>(x.real(),x.imag()); }
+complex<long double>  promote(complex<T> x) { return complex<long double>((long double)x.real(),(long double)x.imag()); }
 
-complex<long double>  promote(float x) { return complex<long double>( x); }
-complex<long double>  promote(double x) { return complex<long double>( x); }
-complex<long double>  promote(long double x) { return complex<long double>( x); }
+complex<long double>  promote(float x) { return complex<long double>((long double)x); }
+complex<long double>  promote(double x) { return complex<long double>((long double)x); }
+complex<long double>  promote(long double x) { return complex<long double>((long double)x); }
     
 
     template <typename VT1,typename VT2>
     long double fft_rmse( const VT1 & fftbuf,const VT2 & timebuf)
     {
@@ -31,11 +31,11 @@
         long double totalpower=0;
         long double difpower=0;
         long double pi = acos((long double)-1 );
         for (size_t k0=0;k0<(size_t)fftbuf.size();++k0) {
             complex<long double> acc = 0;
-            long double phinc = -2.*k0* pi / timebuf.size();
+            long double phinc = (long double)(-2.)*k0* pi / timebuf.size();
             for (size_t k1=0;k1<(size_t)timebuf.size();++k1) {
                 acc +=  promote( timebuf[k1] ) * exp( complex<long double>(0,k1*phinc) );
             }
             totalpower += numext::abs2(acc);
             complex<long double> x = promote(fftbuf[k0]); 
@@ -52,12 +52,12 @@
     {
         long double totalpower=0;
         long double difpower=0;
         size_t n = (min)( buf1.size(),buf2.size() );
         for (size_t k=0;k<n;++k) {
-            totalpower += (numext::abs2( buf1[k] ) + numext::abs2(buf2[k]) )/2.;
-            difpower += numext::abs2(buf1[k] - buf2[k]);
+            totalpower += (long double)((numext::abs2( buf1[k] ) + numext::abs2(buf2[k]) )/2);
+            difpower += (long double)(numext::abs2(buf1[k] - buf2[k]));
         }
         return sqrt(difpower/totalpower);
     }
 
 enum { StdVectorContainer, EigenVectorContainer };
@@ -91,23 +91,23 @@
     // make sure it DOESN'T give the right full spectrum answer
     // if we've asked for half-spectrum
     fft.SetFlag(fft.HalfSpectrum );
     fft.fwd( freqBuf,tbuf);
     VERIFY((size_t)freqBuf.size() == (size_t)( (nfft>>1)+1) );
-    VERIFY( fft_rmse(freqBuf,tbuf) < test_precision<T>()  );// gross check
+    VERIFY( T(fft_rmse(freqBuf,tbuf)) < test_precision<T>()  );// gross check
 
     fft.ClearFlag(fft.HalfSpectrum );
     fft.fwd( freqBuf,tbuf);
     VERIFY( (size_t)freqBuf.size() == (size_t)nfft);
-    VERIFY( fft_rmse(freqBuf,tbuf) < test_precision<T>()  );// gross check
+    VERIFY( T(fft_rmse(freqBuf,tbuf)) < test_precision<T>()  );// gross check
 
     if (nfft&1)
         return; // odd FFTs get the wrong size inverse FFT
 
     ScalarVector tbuf2;
     fft.inv( tbuf2 , freqBuf);
-    VERIFY( dif_rmse(tbuf,tbuf2) < test_precision<T>()  );// gross check
+    VERIFY( T(dif_rmse(tbuf,tbuf2)) < test_precision<T>()  );// gross check
 
 
     // verify that the Unscaled flag takes effect
     ScalarVector tbuf3;
     fft.SetFlag(fft.Unscaled);
@@ -119,16 +119,16 @@
 
 
     //for (size_t i=0;i<(size_t) tbuf.size();++i)
     //    cout << "freqBuf=" << freqBuf[i] << " in2=" << tbuf3[i] << " -  in=" << tbuf[i] << " => " << (tbuf3[i] - tbuf[i] ) <<  endl;
 
-    VERIFY( dif_rmse(tbuf,tbuf3) < test_precision<T>()  );// gross check
+    VERIFY( T(dif_rmse(tbuf,tbuf3)) < test_precision<T>()  );// gross check
 
     // verify that ClearFlag works
     fft.ClearFlag(fft.Unscaled);
     fft.inv( tbuf2 , freqBuf);
-    VERIFY( dif_rmse(tbuf,tbuf2) < test_precision<T>()  );// gross check
+    VERIFY( T(dif_rmse(tbuf,tbuf2)) < test_precision<T>()  );// gross check
 }
 
 template <typename T>
 void test_scalar(int nfft)
 {
@@ -150,27 +150,27 @@
     ComplexVector buf3;
     for (int k=0;k<nfft;++k)
         inbuf[k]= Complex( (T)(rand()/(double)RAND_MAX - .5), (T)(rand()/(double)RAND_MAX - .5) );
     fft.fwd( outbuf , inbuf);
 
-    VERIFY( fft_rmse(outbuf,inbuf) < test_precision<T>()  );// gross check
+    VERIFY( T(fft_rmse(outbuf,inbuf)) < test_precision<T>()  );// gross check
     fft.inv( buf3 , outbuf);
 
-    VERIFY( dif_rmse(inbuf,buf3) < test_precision<T>()  );// gross check
+    VERIFY( T(dif_rmse(inbuf,buf3)) < test_precision<T>()  );// gross check
 
     // verify that the Unscaled flag takes effect
     ComplexVector buf4;
     fft.SetFlag(fft.Unscaled);
     fft.inv( buf4 , outbuf);
     for (int k=0;k<nfft;++k)
         buf4[k] *= T(1./nfft);
-    VERIFY( dif_rmse(inbuf,buf4) < test_precision<T>()  );// gross check
+    VERIFY( T(dif_rmse(inbuf,buf4)) < test_precision<T>()  );// gross check
 
     // verify that ClearFlag works
     fft.ClearFlag(fft.Unscaled);
     fft.inv( buf3 , outbuf);
-    VERIFY( dif_rmse(inbuf,buf3) < test_precision<T>()  );// gross check
+    VERIFY( T(dif_rmse(inbuf,buf3)) < test_precision<T>()  );// gross check
 }
 
 template <typename T>
 void test_complex(int nfft)
 {

Index: 3rd_party/eigen/unsupported/test/NonLinearOptimization.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/NonLinearOptimization.cpp
+++ 3rd_party/eigen/unsupported/test/NonLinearOptimization.cpp
@@ -10,11 +10,12 @@
 
 // This disables some useless Warnings on MSVC.
 // It is intended to be done for this test only.
 #include <Eigen/src/Core/util/DisableStupidWarnings.h>
 
-using std::sqrt;
+// tolerance for chekcing number of iterations
+#define LM_EVAL_COUNT_TOL 4/3
 
 int fcn_chkder(const VectorXd &x, VectorXd &fvec, MatrixXd &fjac, int iflag)
 {
     /*      subroutine fcn for chkder example. */
 
@@ -244,13 +245,13 @@
     hybrj_functor(void) : Functor<double>(9,9) {}
 
     int operator()(const VectorXd &x, VectorXd &fvec)
     {
         double temp, temp1, temp2;
-        const int n = x.size();
+        const VectorXd::Index n = x.size();
         assert(fvec.size()==n);
-        for (int k = 0; k < n; k++)
+        for (VectorXd::Index k = 0; k < n; k++)
         {
             temp = (3. - 2.*x[k])*x[k];
             temp1 = 0.;
             if (k) temp1 = x[k-1];
             temp2 = 0.;
@@ -259,16 +260,16 @@
         }
         return 0;
     }
     int df(const VectorXd &x, MatrixXd &fjac)
     {
-        const int n = x.size();
+        const VectorXd::Index n = x.size();
         assert(fjac.rows()==n);
         assert(fjac.cols()==n);
-        for (int k = 0; k < n; k++)
+        for (VectorXd::Index k = 0; k < n; k++)
         {
-            for (int j = 0; j < n; j++)
+            for (VectorXd::Index j = 0; j < n; j++)
                 fjac(k,j) = 0.;
             fjac(k,k) = 3.- 4.*x[k];
             if (k) fjac(k,k-1) = -1.;
             if (k != n-1) fjac(k,k+1) = -2.;
         }
@@ -349,14 +350,14 @@
 {
     hybrd_functor(void) : Functor<double>(9,9) {}
     int operator()(const VectorXd &x, VectorXd &fvec) const
     {
         double temp, temp1, temp2;
-        const int n = x.size();
+        const VectorXd::Index n = x.size();
 
         assert(fvec.size()==n);
-        for (int k=0; k < n; k++)
+        for (VectorXd::Index k=0; k < n; k++)
         {
             temp = (3. - 2.*x[k])*x[k];
             temp1 = 0.;
             if (k) temp1 = x[k-1];
             temp2 = 0.;
@@ -453,11 +454,11 @@
     {
         assert(x.size()==3);
         assert(jac_row.size()==x.size());
         double tmp1, tmp2, tmp3, tmp4;
 
-        int i = rownb-2;
+        VectorXd::Index i = rownb-2;
         tmp1 = i+1;
         tmp2 = 16 - i - 1;
         tmp3 = (i>=8)? tmp2 : tmp1;
         tmp4 = (x[1]*tmp2 + x[2]*tmp3); tmp4 = tmp4*tmp4;
         jac_row[0] = -1;
@@ -1020,11 +1021,13 @@
   // check return value
   VERIFY_IS_EQUAL(info, 2);
   VERIFY_IS_EQUAL(lm.nfev, 79);
   VERIFY_IS_EQUAL(lm.njev, 72);
   // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.430899764097e-25);  // should be 1.4307867721E-25, but nist results are on 128-bit floats
+  std::cout.precision(30);
+  std::cout << lm.fvec.squaredNorm() << "\n";
+  VERIFY(lm.fvec.squaredNorm() <= 1.4307867721E-25);
   // check x
   VERIFY_IS_APPROX(x[0], 9.5100000027E-02);
   VERIFY_IS_APPROX(x[1], 1.0000000001E+00);
   VERIFY_IS_APPROX(x[2], 8.6070000013E-01);
   VERIFY_IS_APPROX(x[3], 3.0000000002E+00);
@@ -1041,11 +1044,11 @@
   // check return value
   VERIFY_IS_EQUAL(info, 2);
   VERIFY_IS_EQUAL(lm.nfev, 9);
   VERIFY_IS_EQUAL(lm.njev, 8);
   // check norm^2
-  VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.428595533845e-25);  // should be 1.4307867721E-25, but nist results are on 128-bit floats
+  VERIFY(lm.fvec.squaredNorm() <= 1.4307867721E-25);
   // check x
   VERIFY_IS_APPROX(x[0], 9.5100000027E-02);
   VERIFY_IS_APPROX(x[1], 1.0000000001E+00);
   VERIFY_IS_APPROX(x[2], 8.6070000013E-01);
   VERIFY_IS_APPROX(x[3], 3.0000000002E+00);
@@ -1260,12 +1263,12 @@
   lm.parameters.factor = 10.;
   info = lm.minimize(x);
 
   // check return value
   VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev, 31);
-  VERIFY_IS_EQUAL(lm.njev, 25);
+  VERIFY(lm.nfev < 31); // 31
+  VERIFY(lm.njev < 25); // 25
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.1680088766E+03);
   // check x
   VERIFY_IS_APPROX(x[0], 2.1380940889E+02);
   VERIFY_IS_APPROX(x[1], 5.4723748542E-01);
@@ -1340,22 +1343,27 @@
   lm.parameters.ftol = NumTraits<double>::epsilon();
   lm.parameters.xtol = NumTraits<double>::epsilon();
   lm.parameters.maxfev = 1000;
   info = lm.minimize(x);
 
-  // check return value
-  VERIFY_IS_EQUAL(info, 2); 
-  VERIFY_IS_EQUAL(lm.nfev, 602 ); 
-  VERIFY_IS_EQUAL(lm.njev, 545 ); 
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.4648946975E-05);
   // check x
   VERIFY_IS_APPROX(x[0], 3.7541005211E-01);
   VERIFY_IS_APPROX(x[1], 1.9358469127E+00);
   VERIFY_IS_APPROX(x[2], -1.4646871366E+00);
   VERIFY_IS_APPROX(x[3], 1.2867534640E-02);
   VERIFY_IS_APPROX(x[4], 2.2122699662E-02);
+  
+  // check return value
+  VERIFY_IS_EQUAL(info, 2); 
+  ++g_test_level;
+  VERIFY_IS_EQUAL(lm.nfev, 602);  // 602
+  VERIFY_IS_EQUAL(lm.njev, 545);  // 545
+  --g_test_level;
+  VERIFY(lm.nfev < 602 * LM_EVAL_COUNT_TOL);
+  VERIFY(lm.njev < 545 * LM_EVAL_COUNT_TOL);
 
   /*
    * Second try
    */
   x<< 0.5  ,1.5  ,-1   ,0.01 ,0.02;
@@ -1830,12 +1838,12 @@
     CALL_SUBTEST/*_4*/(testNistChwirut2());
 
     // NIST tests, level of difficulty = "Average"
     CALL_SUBTEST/*_5*/(testNistHahn1());
     CALL_SUBTEST/*_6*/(testNistMisra1d());
-//     CALL_SUBTEST/*_7*/(testNistMGH17());
-//     CALL_SUBTEST/*_8*/(testNistLanczos1());
+    CALL_SUBTEST/*_7*/(testNistMGH17());
+    CALL_SUBTEST/*_8*/(testNistLanczos1());
 
 //     // NIST tests, level of difficulty = "Higher"
     CALL_SUBTEST/*_9*/(testNistRat42());
 //     CALL_SUBTEST/*_10*/(testNistMGH10());
     CALL_SUBTEST/*_11*/(testNistBoxBOD());

Index: 3rd_party/eigen/unsupported/test/alignedvector3.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/alignedvector3.cpp
+++ 3rd_party/eigen/unsupported/test/alignedvector3.cpp
@@ -7,10 +7,20 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
 #include <unsupported/Eigen/AlignedVector3>
+
+namespace Eigen {
+
+template<typename T,typename Derived>
+T test_relative_error(const AlignedVector3<T> &a, const MatrixBase<Derived> &b)
+{
+  return test_relative_error(a.coeffs().template head<3>(), b);
+}
+
+}
 
 template<typename Scalar>
 void alignedvector3()
 {
   Scalar s1 = internal::random<Scalar>();
@@ -17,12 +27,12 @@
   Scalar s2 = internal::random<Scalar>();
   typedef Matrix<Scalar,3,1> RefType;
   typedef Matrix<Scalar,3,3> Mat33;
   typedef AlignedVector3<Scalar> FastType;
   RefType  r1(RefType::Random()), r2(RefType::Random()), r3(RefType::Random()),
-           r4(RefType::Random()), r5(RefType::Random()), r6(RefType::Random());
-  FastType f1(r1), f2(r2), f3(r3), f4(r4), f5(r5), f6(r6);
+           r4(RefType::Random()), r5(RefType::Random());
+  FastType f1(r1), f2(r2), f3(r3), f4(r4), f5(r5);
   Mat33 m1(Mat33::Random());
   
   VERIFY_IS_APPROX(f1,r1);
   VERIFY_IS_APPROX(f4,r4);
 
@@ -47,13 +57,28 @@
   VERIFY_IS_APPROX((f2+f1).normalized(),(r2+r1).normalized());
   
   f2.normalize();
   r2.normalize();
   VERIFY_IS_APPROX(f2,r2);
+  
+  {
+    FastType f6 = RefType::Zero();
+    FastType f7 = FastType::Zero();
+    VERIFY_IS_APPROX(f6,f7);
+    f6 = r4+r1;
+    VERIFY_IS_APPROX(f6,r4+r1);
+    f6 -= Scalar(2)*r4;
+    VERIFY_IS_APPROX(f6,r1-r4);
+  }
+  
+  std::stringstream ss1, ss2;
+  ss1 << f1;
+  ss2 << r1;
+  VERIFY(ss1.str()==ss2.str());
 }
 
 void test_alignedvector3()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST( alignedvector3<float>() );
   }
 }

Index: 3rd_party/eigen/unsupported/test/autodiff.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/autodiff.cpp
+++ 3rd_party/eigen/unsupported/test/autodiff.cpp
@@ -14,11 +14,12 @@
 EIGEN_DONT_INLINE Scalar foo(const Scalar& x, const Scalar& y)
 {
   using namespace std;
 //   return x+std::sin(y);
   EIGEN_ASM_COMMENT("mybegin");
-  return static_cast<Scalar>(x*2 - pow(x,2) + 2*sqrt(y*y) - 4 * sin(x) + 2 * cos(y) - exp(-0.5*x*x));
+  // pow(float, int) promotes to pow(double, double)
+  return x*2 - 1 + static_cast<Scalar>(pow(1+x,2)) + 2*sqrt(y*y+0) - 4 * sin(0+x) + 2 * cos(y+0) - exp(Scalar(-0.5)*x*x+0);
   //return x+2*y*x;//x*2 -std::pow(x,2);//(2*y/x);// - y*2;
   EIGEN_ASM_COMMENT("myend");
 }
 
 template<typename Vector>
@@ -102,10 +103,93 @@
       }
     }
   }
 };
 
+
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+/* Test functor for the C++11 features. */
+template <typename Scalar>
+struct integratorFunctor
+{
+    typedef Matrix<Scalar, 2, 1> InputType;
+    typedef Matrix<Scalar, 2, 1> ValueType;
+
+    /*
+     * Implementation starts here.
+     */
+    integratorFunctor(const Scalar gain) : _gain(gain) {}
+    integratorFunctor(const integratorFunctor& f) : _gain(f._gain) {}
+    const Scalar _gain;
+
+    template <typename T1, typename T2>
+    void operator() (const T1 &input, T2 *output, const Scalar dt) const
+    {
+        T2 &o = *output;
+
+        /* Integrator to test the AD. */
+        o[0] = input[0] + input[1] * dt * _gain;
+        o[1] = input[1] * _gain;
+    }
+
+    /* Only needed for the test */
+    template <typename T1, typename T2, typename T3>
+    void operator() (const T1 &input, T2 *output, T3 *jacobian, const Scalar dt) const
+    {
+        T2 &o = *output;
+
+        /* Integrator to test the AD. */
+        o[0] = input[0] + input[1] * dt * _gain;
+        o[1] = input[1] * _gain;
+
+        if (jacobian)
+        {
+            T3 &j = *jacobian;
+
+            j(0, 0) = 1;
+            j(0, 1) = dt * _gain;
+            j(1, 0) = 0;
+            j(1, 1) = _gain;
+        }
+    }
+
+};
+
+template<typename Func> void forward_jacobian_cpp11(const Func& f)
+{
+    typedef typename Func::ValueType::Scalar Scalar;
+    typedef typename Func::ValueType ValueType;
+    typedef typename Func::InputType InputType;
+    typedef typename AutoDiffJacobian<Func>::JacobianType JacobianType;
+
+    InputType x = InputType::Random(InputType::RowsAtCompileTime);
+    ValueType y, yref;
+    JacobianType j, jref;
+
+    const Scalar dt = internal::random<double>();
+
+    jref.setZero();
+    yref.setZero();
+    f(x, &yref, &jref, dt);
+
+    //std::cerr << "y, yref, jref: " << "\n";
+    //std::cerr << y.transpose() << "\n\n";
+    //std::cerr << yref << "\n\n";
+    //std::cerr << jref << "\n\n";
+
+    AutoDiffJacobian<Func> autoj(f);
+    autoj(x, &y, &j, dt);
+
+    //std::cerr << "y j (via autodiff): " << "\n";
+    //std::cerr << y.transpose() << "\n\n";
+    //std::cerr << j << "\n\n";
+
+    VERIFY_IS_APPROX(y, yref);
+    VERIFY_IS_APPROX(j, jref);
+}
+#endif
+
 template<typename Func> void forward_jacobian(const Func& f)
 {
     typename Func::InputType x = Func::InputType::Random(f.inputs());
     typename Func::ValueType y(f.values()), yref(f.values());
     typename Func::JacobianType j(f.values(),f.inputs()), jref(f.values(),f.inputs());
@@ -125,49 +209,159 @@
 
     VERIFY_IS_APPROX(y, yref);
     VERIFY_IS_APPROX(j, jref);
 }
 
-
 // TODO also check actual derivatives!
+template <int>
 void test_autodiff_scalar()
 {
   Vector2f p = Vector2f::Random();
   typedef AutoDiffScalar<Vector2f> AD;
   AD ax(p.x(),Vector2f::UnitX());
   AD ay(p.y(),Vector2f::UnitY());
   AD res = foo<AD>(ax,ay);
   VERIFY_IS_APPROX(res.value(), foo(p.x(),p.y()));
 }
+
 
 // TODO also check actual derivatives!
+template <int>
 void test_autodiff_vector()
 {
   Vector2f p = Vector2f::Random();
   typedef AutoDiffScalar<Vector2f> AD;
   typedef Matrix<AD,2,1> VectorAD;
   VectorAD ap = p.cast<AD>();
   ap.x().derivatives() = Vector2f::UnitX();
   ap.y().derivatives() = Vector2f::UnitY();
-  
+
   AD res = foo<VectorAD>(ap);
   VERIFY_IS_APPROX(res.value(), foo(p));
 }
 
+template <int>
 void test_autodiff_jacobian()
 {
   CALL_SUBTEST(( forward_jacobian(TestFunc1<double,2,2>()) ));
   CALL_SUBTEST(( forward_jacobian(TestFunc1<double,2,3>()) ));
   CALL_SUBTEST(( forward_jacobian(TestFunc1<double,3,2>()) ));
   CALL_SUBTEST(( forward_jacobian(TestFunc1<double,3,3>()) ));
   CALL_SUBTEST(( forward_jacobian(TestFunc1<double>(3,3)) ));
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  CALL_SUBTEST(( forward_jacobian_cpp11(integratorFunctor<double>(10)) ));
+#endif
+}
+
+
+template <int>
+void test_autodiff_hessian()
+{
+  typedef AutoDiffScalar<VectorXd> AD;
+  typedef Matrix<AD,Eigen::Dynamic,1> VectorAD;
+  typedef AutoDiffScalar<VectorAD> ADD;
+  typedef Matrix<ADD,Eigen::Dynamic,1> VectorADD;
+  VectorADD x(2);
+  double s1 = internal::random<double>(), s2 = internal::random<double>(), s3 = internal::random<double>(), s4 = internal::random<double>();
+  x(0).value()=s1;
+  x(1).value()=s2;
+
+  //set unit vectors for the derivative directions (partial derivatives of the input vector)
+  x(0).derivatives().resize(2);
+  x(0).derivatives().setZero();
+  x(0).derivatives()(0)= 1;
+  x(1).derivatives().resize(2);
+  x(1).derivatives().setZero();
+  x(1).derivatives()(1)=1;
+
+  //repeat partial derivatives for the inner AutoDiffScalar
+  x(0).value().derivatives() = VectorXd::Unit(2,0);
+  x(1).value().derivatives() = VectorXd::Unit(2,1);
+
+  //set the hessian matrix to zero
+  for(int idx=0; idx<2; idx++) {
+      x(0).derivatives()(idx).derivatives()  = VectorXd::Zero(2);
+      x(1).derivatives()(idx).derivatives()  = VectorXd::Zero(2);
+  }
+
+  ADD y = sin(AD(s3)*x(0) + AD(s4)*x(1));
+
+  VERIFY_IS_APPROX(y.value().derivatives()(0), y.derivatives()(0).value());
+  VERIFY_IS_APPROX(y.value().derivatives()(1), y.derivatives()(1).value());
+  VERIFY_IS_APPROX(y.value().derivatives()(0), s3*std::cos(s1*s3+s2*s4));
+  VERIFY_IS_APPROX(y.value().derivatives()(1), s4*std::cos(s1*s3+s2*s4));
+  VERIFY_IS_APPROX(y.derivatives()(0).derivatives(), -std::sin(s1*s3+s2*s4)*Vector2d(s3*s3,s4*s3));
+  VERIFY_IS_APPROX(y.derivatives()(1).derivatives(),  -std::sin(s1*s3+s2*s4)*Vector2d(s3*s4,s4*s4));
+
+  ADD z = x(0)*x(1);
+  VERIFY_IS_APPROX(z.derivatives()(0).derivatives(), Vector2d(0,1));
+  VERIFY_IS_APPROX(z.derivatives()(1).derivatives(), Vector2d(1,0));
+}
+
+double bug_1222() {
+  typedef Eigen::AutoDiffScalar<Eigen::Vector3d> AD;
+  const double _cv1_3 = 1.0;
+  const AD chi_3 = 1.0;
+  // this line did not work, because operator+ returns ADS<DerType&>, which then cannot be converted to ADS<DerType>
+  const AD denom = chi_3 + _cv1_3;
+  return denom.value();
+}
+
+double bug_1223() {
+  using std::min;
+  typedef Eigen::AutoDiffScalar<Eigen::Vector3d> AD;
+
+  const double _cv1_3 = 1.0;
+  const AD chi_3 = 1.0;
+  const AD denom = 1.0;
+
+  // failed because implementation of min attempts to construct ADS<DerType&> via constructor AutoDiffScalar(const Real& value)
+  // without initializing m_derivatives (which is a reference in this case)
+  #define EIGEN_TEST_SPACE
+  const AD t = min EIGEN_TEST_SPACE (denom / chi_3, 1.0);
+
+  const AD t2 = min EIGEN_TEST_SPACE (denom / (chi_3 * _cv1_3), 1.0);
+
+  return t.value() + t2.value();
+}
+
+// regression test for some compilation issues with specializations of ScalarBinaryOpTraits
+void bug_1260() {
+  Matrix4d A;
+  Vector4d v;
+  A*v;
+}
+
+// check a compilation issue with numext::max
+double bug_1261() {
+  typedef AutoDiffScalar<Matrix2d> AD;
+  typedef Matrix<AD,2,1> VectorAD;
+
+  VectorAD v;
+  const AD maxVal = v.maxCoeff();
+  const AD minVal = v.minCoeff();
+  return maxVal.value() + minVal.value();
+}
+
+double bug_1264() {
+  typedef AutoDiffScalar<Vector2d> AD;
+  const AD s;
+  const Matrix<AD, 3, 1> v1;
+  const Matrix<AD, 3, 1> v2 = (s + 3.0) * v1;
+  return v2(0).value();
 }
 
 void test_autodiff()
 {
   for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( test_autodiff_scalar() );
-    CALL_SUBTEST_2( test_autodiff_vector() );
-    CALL_SUBTEST_3( test_autodiff_jacobian() );
+    CALL_SUBTEST_1( test_autodiff_scalar<1>() );
+    CALL_SUBTEST_2( test_autodiff_vector<1>() );
+    CALL_SUBTEST_3( test_autodiff_jacobian<1>() );
+    CALL_SUBTEST_4( test_autodiff_hessian<1>() );
   }
+
+  bug_1222();
+  bug_1223();
+  bug_1260();
+  bug_1261();
 }
 

ADDED   3rd_party/eigen/unsupported/test/autodiff_scalar.cpp
Index: 3rd_party/eigen/unsupported/test/autodiff_scalar.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/autodiff_scalar.cpp
+++ 3rd_party/eigen/unsupported/test/autodiff_scalar.cpp
@@ -0,0 +1,98 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christoph Hertzberg <chtz@informatik.uni-bremen.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <unsupported/Eigen/AutoDiff>
+
+/*
+ * In this file scalar derivations are tested for correctness.
+ * TODO add more tests!
+ */
+
+template<typename Scalar> void check_atan2()
+{
+  typedef Matrix<Scalar, 1, 1> Deriv1;
+  typedef AutoDiffScalar<Deriv1> AD;
+  
+  AD x(internal::random<Scalar>(-3.0, 3.0), Deriv1::UnitX());
+  
+  using std::exp;
+  Scalar r = exp(internal::random<Scalar>(-10, 10));
+  
+  AD s = sin(x), c = cos(x);
+  AD res = atan2(r*s, r*c);
+  
+  VERIFY_IS_APPROX(res.value(), x.value());
+  VERIFY_IS_APPROX(res.derivatives(), x.derivatives());
+
+  res = atan2(r*s+0, r*c+0);
+  VERIFY_IS_APPROX(res.value(), x.value());
+  VERIFY_IS_APPROX(res.derivatives(), x.derivatives());
+}
+
+template<typename Scalar> void check_hyperbolic_functions()
+{
+  using std::sinh;
+  using std::cosh;
+  using std::tanh;
+  typedef Matrix<Scalar, 1, 1> Deriv1;
+  typedef AutoDiffScalar<Deriv1> AD;
+  Deriv1 p = Deriv1::Random();
+  AD val(p.x(),Deriv1::UnitX());
+
+  Scalar cosh_px = std::cosh(p.x());
+  AD res1 = tanh(val);
+  VERIFY_IS_APPROX(res1.value(), std::tanh(p.x()));
+  VERIFY_IS_APPROX(res1.derivatives().x(), Scalar(1.0) / (cosh_px * cosh_px));
+
+  AD res2 = sinh(val);
+  VERIFY_IS_APPROX(res2.value(), std::sinh(p.x()));
+  VERIFY_IS_APPROX(res2.derivatives().x(), cosh_px);
+
+  AD res3 = cosh(val);
+  VERIFY_IS_APPROX(res3.value(), cosh_px);
+  VERIFY_IS_APPROX(res3.derivatives().x(), std::sinh(p.x()));
+
+  // Check constant values.
+  const Scalar sample_point = Scalar(1) / Scalar(3); 
+  val = AD(sample_point,Deriv1::UnitX());
+  res1 = tanh(val);
+  VERIFY_IS_APPROX(res1.derivatives().x(), Scalar(0.896629559604914));
+
+  res2 = sinh(val);
+  VERIFY_IS_APPROX(res2.derivatives().x(), Scalar(1.056071867829939));
+
+  res3 = cosh(val);
+  VERIFY_IS_APPROX(res3.derivatives().x(), Scalar(0.339540557256150));
+}
+
+template <typename Scalar>
+void check_limits_specialization()
+{
+  typedef Eigen::Matrix<Scalar, 1, 1> Deriv;
+  typedef Eigen::AutoDiffScalar<Deriv> AD;
+
+  typedef std::numeric_limits<AD> A;
+  typedef std::numeric_limits<Scalar> B;
+
+#if EIGEN_HAS_CXX11
+  VERIFY(bool(std::is_base_of<B, A>::value));
+#endif
+}
+
+void test_autodiff_scalar()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( check_atan2<float>() );
+    CALL_SUBTEST_2( check_atan2<double>() );
+    CALL_SUBTEST_3( check_hyperbolic_functions<float>() );
+    CALL_SUBTEST_4( check_hyperbolic_functions<double>() );
+    CALL_SUBTEST_5( check_limits_specialization<double>());
+  }
+}

DELETED 3rd_party/eigen/unsupported/test/bdcsvd.cpp
Index: 3rd_party/eigen/unsupported/test/bdcsvd.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/bdcsvd.cpp
+++ 3rd_party/eigen/unsupported/test/bdcsvd.cpp
@@ -1,213 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com>
-// Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr>
-// Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr>
-// Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/
-
-#include "svd_common.h"
-#include <iostream>
-#include <Eigen/LU>
-
-// check if "svd" is the good image of "m"  
-template<typename MatrixType>
-void bdcsvd_check_full(const MatrixType& m, const BDCSVD<MatrixType>& svd)
-{
-  svd_check_full< MatrixType, BDCSVD< MatrixType > >(m, svd);
-}
-
-// Compare to a reference value
-template<typename MatrixType>
-void bdcsvd_compare_to_full(const MatrixType& m,
-			    unsigned int computationOptions,
-			    const BDCSVD<MatrixType>& referenceSvd)
-{
-  svd_compare_to_full< MatrixType, BDCSVD< MatrixType > >(m, computationOptions, referenceSvd);
-} // end bdcsvd_compare_to_full
-
-
-template<typename MatrixType>
-void bdcsvd_solve(const MatrixType& m, unsigned int computationOptions)
-{
-  svd_solve< MatrixType, BDCSVD< MatrixType > >(m, computationOptions);
-} //  end template bdcsvd_solve
-
-
-// test the computations options
-template<typename MatrixType>
-void bdcsvd_test_all_computation_options(const MatrixType& m)
-{
-  BDCSVD<MatrixType> fullSvd(m, ComputeFullU|ComputeFullV);
-  svd_test_computation_options_1< MatrixType, BDCSVD< MatrixType > >(m, fullSvd); 
-  svd_test_computation_options_2< MatrixType, BDCSVD< MatrixType > >(m, fullSvd); 
-} // end bdcsvd_test_all_computation_options
-
-
-// Call a test with all the computations options
-template<typename MatrixType>
-void bdcsvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
-{
-  MatrixType m = pickrandom ? MatrixType::Random(a.rows(), a.cols()) : a;
-  bdcsvd_test_all_computation_options<MatrixType>(m);
-} // end template bdcsvd
-
-
-// verify assert
-template<typename MatrixType> 
-void bdcsvd_verify_assert(const MatrixType& m)
-{
-  svd_verify_assert< MatrixType, BDCSVD< MatrixType > >(m);
-}// end template bdcsvd_verify_assert
-
-
-// test weird values
-template<typename MatrixType>
-void bdcsvd_inf_nan()
-{
-  svd_inf_nan< MatrixType, BDCSVD< MatrixType > >();
-}// end template bdcsvd_inf_nan
-
-
-
-void bdcsvd_preallocate()
-{
-  svd_preallocate< BDCSVD< MatrixXf > >();
-} // end bdcsvd_preallocate
-
-
-// compare the Singular values returned with Jacobi and Bdc
-template<typename MatrixType> 
-void compare_bdc_jacobi(const MatrixType& a = MatrixType(), unsigned int computationOptions = 0)
-{
-  std::cout << "debut compare" << std::endl;
-  MatrixType m = MatrixType::Random(a.rows(), a.cols());
-  BDCSVD<MatrixType> bdc_svd(m);
-  JacobiSVD<MatrixType> jacobi_svd(m);
-  VERIFY_IS_APPROX(bdc_svd.singularValues(), jacobi_svd.singularValues());
-  if(computationOptions & ComputeFullU)
-    VERIFY_IS_APPROX(bdc_svd.matrixU(), jacobi_svd.matrixU());
-  if(computationOptions & ComputeThinU)
-    VERIFY_IS_APPROX(bdc_svd.matrixU(), jacobi_svd.matrixU());
-  if(computationOptions & ComputeFullV)
-    VERIFY_IS_APPROX(bdc_svd.matrixV(), jacobi_svd.matrixV());
-  if(computationOptions & ComputeThinV)
-    VERIFY_IS_APPROX(bdc_svd.matrixV(), jacobi_svd.matrixV());
-  std::cout << "fin compare" << std::endl;
-} // end template compare_bdc_jacobi
-
-
-// call the tests
-void test_bdcsvd()
-{
-  // test of Dynamic defined Matrix (42, 42) of float 
-  CALL_SUBTEST_11(( bdcsvd_verify_assert<Matrix<float,Dynamic,Dynamic> >
-		    (Matrix<float,Dynamic,Dynamic>(42,42)) ));
-  CALL_SUBTEST_11(( compare_bdc_jacobi<Matrix<float,Dynamic,Dynamic> >
-		    (Matrix<float,Dynamic,Dynamic>(42,42), 0) ));
-  CALL_SUBTEST_11(( bdcsvd<Matrix<float,Dynamic,Dynamic> >
-		    (Matrix<float,Dynamic,Dynamic>(42,42)) ));
-
-  // test of Dynamic defined Matrix (50, 50) of double 
-  CALL_SUBTEST_13(( bdcsvd_verify_assert<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(50,50)) ));
-  CALL_SUBTEST_13(( compare_bdc_jacobi<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(50,50), 0) ));
-  CALL_SUBTEST_13(( bdcsvd<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(50, 50)) )); 
-
-  // test of Dynamic defined Matrix (22, 22) of complex double
-  CALL_SUBTEST_14(( bdcsvd_verify_assert<Matrix<std::complex<double>,Dynamic,Dynamic> >
-  		    (Matrix<std::complex<double>,Dynamic,Dynamic>(22,22)) ));
-  CALL_SUBTEST_14(( compare_bdc_jacobi<Matrix<std::complex<double>,Dynamic,Dynamic> >
-  		    (Matrix<std::complex<double>, Dynamic, Dynamic> (22,22), 0) ));
-  CALL_SUBTEST_14(( bdcsvd<Matrix<std::complex<double>,Dynamic,Dynamic> >
-  		    (Matrix<std::complex<double>,Dynamic,Dynamic>(22, 22)) )); 
-
-  // test of Dynamic defined Matrix (10, 10) of int
-  //CALL_SUBTEST_15(( bdcsvd_verify_assert<Matrix<int,Dynamic,Dynamic> >
-  //		    (Matrix<int,Dynamic,Dynamic>(10,10)) ));		    
-  //CALL_SUBTEST_15(( compare_bdc_jacobi<Matrix<int,Dynamic,Dynamic> >
-  //		    (Matrix<int,Dynamic,Dynamic>(10,10), 0) ));
-  //CALL_SUBTEST_15(( bdcsvd<Matrix<int,Dynamic,Dynamic> >
-  //		    (Matrix<int,Dynamic,Dynamic>(10, 10)) )); 
-  
-
-  // test of Dynamic defined Matrix (8, 6) of double 
- 
-  CALL_SUBTEST_16(( bdcsvd_verify_assert<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(8,6)) ));
-  CALL_SUBTEST_16(( compare_bdc_jacobi<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(8, 6), 0) )); 
-  CALL_SUBTEST_16(( bdcsvd<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(8, 6)) ));
-
-
-  
-  // test of Dynamic defined Matrix (36, 12) of float
-  CALL_SUBTEST_17(( compare_bdc_jacobi<Matrix<float,Dynamic,Dynamic> >
-		    (Matrix<float,Dynamic,Dynamic>(36, 12), 0) )); 
-  CALL_SUBTEST_17(( bdcsvd<Matrix<float,Dynamic,Dynamic> >
-		    (Matrix<float,Dynamic,Dynamic>(36, 12)) )); 
-
-  // test of Dynamic defined Matrix (5, 8) of double 
-  CALL_SUBTEST_18(( compare_bdc_jacobi<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(5, 8), 0) )); 
-  CALL_SUBTEST_18(( bdcsvd<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(5, 8)) )); 
-
-
-  // non regression tests
-  CALL_SUBTEST_3(( bdcsvd_verify_assert(Matrix3f()) ));
-  CALL_SUBTEST_4(( bdcsvd_verify_assert(Matrix4d()) ));
-  CALL_SUBTEST_7(( bdcsvd_verify_assert(MatrixXf(10,12)) ));
-  CALL_SUBTEST_8(( bdcsvd_verify_assert(MatrixXcd(7,5)) ));
-
-  // SUBTESTS 1 and 2 on specifics matrix
-  for(int i = 0; i < g_repeat; i++) {
-    Matrix2cd m;
-    m << 0, 1,
-      0, 1;
-    CALL_SUBTEST_1(( bdcsvd(m, false) ));
-    m << 1, 0,
-      1, 0;
-    CALL_SUBTEST_1(( bdcsvd(m, false) ));
-
-    Matrix2d n;
-    n << 0, 0,
-      0, 0;
-    CALL_SUBTEST_2(( bdcsvd(n, false) ));
-    n << 0, 0,
-      0, 1;
-    CALL_SUBTEST_2(( bdcsvd(n, false) ));
-    
-    // Statics matrix don't work with BDSVD yet
-    // bdc algo on a random 3x3 float matrix
-    // CALL_SUBTEST_3(( bdcsvd<Matrix3f>() ));
-    // bdc algo on a random 4x4 double matrix
-    // CALL_SUBTEST_4(( bdcsvd<Matrix4d>() ));
-    // bdc algo on a random 3x5 float matrix
-    // CALL_SUBTEST_5(( bdcsvd<Matrix<float,3,5> >() ));
-
-    int r = internal::random<int>(1, 30),
-      c = internal::random<int>(1, 30);
-    CALL_SUBTEST_7(( bdcsvd<MatrixXf>(MatrixXf(r,c)) ));
-    CALL_SUBTEST_8(( bdcsvd<MatrixXcd>(MatrixXcd(r,c)) ));
-    (void) r;
-    (void) c;
-
-    // Test on inf/nan matrix
-    CALL_SUBTEST_7( bdcsvd_inf_nan<MatrixXf>() );
-  }
-
-  CALL_SUBTEST_7(( bdcsvd<MatrixXf>(MatrixXf(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) ));
-  CALL_SUBTEST_8(( bdcsvd<MatrixXcd>(MatrixXcd(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3))) ));
-
-  // Test problem size constructors
-  CALL_SUBTEST_7( BDCSVD<MatrixXf>(10,10) );
-
-} // end test_bdcsvd

ADDED   3rd_party/eigen/unsupported/test/cxx11_eventcount.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_eventcount.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_eventcount.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_eventcount.cpp
@@ -0,0 +1,142 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Dmitry Vyukov <dvyukov@google.com>
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_USE_THREADS
+#include "main.h"
+#include <Eigen/CXX11/ThreadPool>
+
+// Visual studio doesn't implement a rand_r() function since its
+// implementation of rand() is already thread safe
+int rand_reentrant(unsigned int* s) {
+#ifdef EIGEN_COMP_MSVC_STRICT
+  EIGEN_UNUSED_VARIABLE(s);
+  return rand();
+#else
+  return rand_r(s);
+#endif
+}
+
+static void test_basic_eventcount()
+{
+  MaxSizeVector<EventCount::Waiter> waiters(1);
+  waiters.resize(1);
+  EventCount ec(waiters);
+  EventCount::Waiter& w = waiters[0];
+  ec.Notify(false);
+  ec.Prewait(&w);
+  ec.Notify(true);
+  ec.CommitWait(&w);
+  ec.Prewait(&w);
+  ec.CancelWait(&w);
+}
+
+// Fake bounded counter-based queue.
+struct TestQueue {
+  std::atomic<int> val_;
+  static const int kQueueSize = 10;
+
+  TestQueue() : val_() {}
+
+  ~TestQueue() { VERIFY_IS_EQUAL(val_.load(), 0); }
+
+  bool Push() {
+    int val = val_.load(std::memory_order_relaxed);
+    for (;;) {
+      VERIFY_GE(val, 0);
+      VERIFY_LE(val, kQueueSize);
+      if (val == kQueueSize) return false;
+      if (val_.compare_exchange_weak(val, val + 1, std::memory_order_relaxed))
+        return true;
+    }
+  }
+
+  bool Pop() {
+    int val = val_.load(std::memory_order_relaxed);
+    for (;;) {
+      VERIFY_GE(val, 0);
+      VERIFY_LE(val, kQueueSize);
+      if (val == 0) return false;
+      if (val_.compare_exchange_weak(val, val - 1, std::memory_order_relaxed))
+        return true;
+    }
+  }
+
+  bool Empty() { return val_.load(std::memory_order_relaxed) == 0; }
+};
+
+const int TestQueue::kQueueSize;
+
+// A number of producers send messages to a set of consumers using a set of
+// fake queues. Ensure that it does not crash, consumers don't deadlock and
+// number of blocked and unblocked threads match.
+static void test_stress_eventcount()
+{
+  const int kThreads = std::thread::hardware_concurrency();
+  static const int kEvents = 1 << 16;
+  static const int kQueues = 10;
+
+  MaxSizeVector<EventCount::Waiter> waiters(kThreads);
+  waiters.resize(kThreads);
+  EventCount ec(waiters);
+  TestQueue queues[kQueues];
+
+  std::vector<std::unique_ptr<std::thread>> producers;
+  for (int i = 0; i < kThreads; i++) {
+    producers.emplace_back(new std::thread([&ec, &queues]() {
+      unsigned int rnd = static_cast<unsigned int>(std::hash<std::thread::id>()(std::this_thread::get_id()));
+      for (int j = 0; j < kEvents; j++) {
+        unsigned idx = rand_reentrant(&rnd) % kQueues;
+        if (queues[idx].Push()) {
+          ec.Notify(false);
+          continue;
+        }
+        EIGEN_THREAD_YIELD();
+        j--;
+      }
+    }));
+  }
+
+  std::vector<std::unique_ptr<std::thread>> consumers;
+  for (int i = 0; i < kThreads; i++) {
+    consumers.emplace_back(new std::thread([&ec, &queues, &waiters, i]() {
+      EventCount::Waiter& w = waiters[i];
+      unsigned int rnd = static_cast<unsigned int>(std::hash<std::thread::id>()(std::this_thread::get_id()));
+      for (int j = 0; j < kEvents; j++) {
+        unsigned idx = rand_reentrant(&rnd) % kQueues;
+        if (queues[idx].Pop()) continue;
+        j--;
+        ec.Prewait(&w);
+        bool empty = true;
+        for (int q = 0; q < kQueues; q++) {
+          if (!queues[q].Empty()) {
+            empty = false;
+            break;
+          }
+        }
+        if (!empty) {
+          ec.CancelWait(&w);
+          continue;
+        }
+        ec.CommitWait(&w);
+      }
+    }));
+  }
+
+  for (int i = 0; i < kThreads; i++) {
+    producers[i]->join();
+    consumers[i]->join();
+  }
+}
+
+void test_cxx11_eventcount()
+{
+  CALL_SUBTEST(test_basic_eventcount());
+  CALL_SUBTEST(test_stress_eventcount());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_meta.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_meta.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_meta.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_meta.cpp
@@ -0,0 +1,357 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <array>
+#include <Eigen/CXX11/src/util/CXX11Meta.h>
+
+using Eigen::internal::is_same;
+using Eigen::internal::type_list;
+using Eigen::internal::numeric_list;
+using Eigen::internal::gen_numeric_list;
+using Eigen::internal::gen_numeric_list_reversed;
+using Eigen::internal::gen_numeric_list_swapped_pair;
+using Eigen::internal::gen_numeric_list_repeated;
+using Eigen::internal::concat;
+using Eigen::internal::mconcat;
+using Eigen::internal::take;
+using Eigen::internal::skip;
+using Eigen::internal::slice;
+using Eigen::internal::get;
+using Eigen::internal::id_numeric;
+using Eigen::internal::id_type;
+using Eigen::internal::is_same_gf;
+using Eigen::internal::apply_op_from_left;
+using Eigen::internal::apply_op_from_right;
+using Eigen::internal::contained_in_list;
+using Eigen::internal::contained_in_list_gf;
+using Eigen::internal::arg_prod;
+using Eigen::internal::arg_sum;
+using Eigen::internal::sum_op;
+using Eigen::internal::product_op;
+using Eigen::internal::array_reverse;
+using Eigen::internal::array_sum;
+using Eigen::internal::array_prod;
+using Eigen::internal::array_reduce;
+using Eigen::internal::array_zip;
+using Eigen::internal::array_zip_and_reduce;
+using Eigen::internal::array_apply;
+using Eigen::internal::array_apply_and_reduce;
+using Eigen::internal::repeat;
+using Eigen::internal::instantiate_by_c_array;
+
+struct dummy_a {};
+struct dummy_b {};
+struct dummy_c {};
+struct dummy_d {};
+struct dummy_e {};
+
+// dummy operation for testing apply
+template<typename A, typename B> struct dummy_op;
+template<> struct dummy_op<dummy_a, dummy_b> { typedef dummy_c type; };
+template<> struct dummy_op<dummy_b, dummy_a> { typedef dummy_d type; };
+template<> struct dummy_op<dummy_b, dummy_c> { typedef dummy_a type; };
+template<> struct dummy_op<dummy_c, dummy_b> { typedef dummy_d type; };
+template<> struct dummy_op<dummy_c, dummy_a> { typedef dummy_b type; };
+template<> struct dummy_op<dummy_a, dummy_c> { typedef dummy_d type; };
+template<> struct dummy_op<dummy_a, dummy_a> { typedef dummy_e type; };
+template<> struct dummy_op<dummy_b, dummy_b> { typedef dummy_e type; };
+template<> struct dummy_op<dummy_c, dummy_c> { typedef dummy_e type; };
+
+template<typename A, typename B> struct dummy_test { constexpr static bool value = false; constexpr static int global_flags = 0; };
+template<> struct dummy_test<dummy_a, dummy_a>     { constexpr static bool value = true;  constexpr static int global_flags = 1; };
+template<> struct dummy_test<dummy_b, dummy_b>     { constexpr static bool value = true;  constexpr static int global_flags = 2; };
+template<> struct dummy_test<dummy_c, dummy_c>     { constexpr static bool value = true;  constexpr static int global_flags = 4; };
+
+struct times2_op { template<typename A> static A run(A v) { return v * 2; } };
+
+struct dummy_inst
+{
+  int c;
+
+  dummy_inst() : c(0) {}
+  explicit dummy_inst(int) : c(1) {}
+  dummy_inst(int, int) : c(2) {}
+  dummy_inst(int, int, int) : c(3) {}
+  dummy_inst(int, int, int, int) : c(4) {}
+  dummy_inst(int, int, int, int, int) : c(5) {}
+};
+
+static void test_gen_numeric_list()
+{
+  VERIFY((is_same<typename gen_numeric_list<int, 0>::type, numeric_list<int>>::value));
+  VERIFY((is_same<typename gen_numeric_list<int, 1>::type, numeric_list<int, 0>>::value));
+  VERIFY((is_same<typename gen_numeric_list<int, 2>::type, numeric_list<int, 0, 1>>::value));
+  VERIFY((is_same<typename gen_numeric_list<int, 5>::type, numeric_list<int, 0, 1, 2, 3, 4>>::value));
+  VERIFY((is_same<typename gen_numeric_list<int, 10>::type, numeric_list<int, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9>>::value));
+
+  VERIFY((is_same<typename gen_numeric_list<int, 0, 42>::type, numeric_list<int>>::value));
+  VERIFY((is_same<typename gen_numeric_list<int, 1, 42>::type, numeric_list<int, 42>>::value));
+  VERIFY((is_same<typename gen_numeric_list<int, 2, 42>::type, numeric_list<int, 42, 43>>::value));
+  VERIFY((is_same<typename gen_numeric_list<int, 5, 42>::type, numeric_list<int, 42, 43, 44, 45, 46>>::value));
+  VERIFY((is_same<typename gen_numeric_list<int, 10, 42>::type, numeric_list<int, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51>>::value));
+
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 0>::type, numeric_list<int>>::value));
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 1>::type, numeric_list<int, 0>>::value));
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 2>::type, numeric_list<int, 1, 0>>::value));
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 5>::type, numeric_list<int, 4, 3, 2, 1, 0>>::value));
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 10>::type, numeric_list<int, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0>>::value));
+
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 0, 42>::type, numeric_list<int>>::value));
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 1, 42>::type, numeric_list<int, 42>>::value));
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 2, 42>::type, numeric_list<int, 43, 42>>::value));
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 5, 42>::type, numeric_list<int, 46, 45, 44, 43, 42>>::value));
+  VERIFY((is_same<typename gen_numeric_list_reversed<int, 10, 42>::type, numeric_list<int, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42>>::value));
+
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 0, 2, 3>::type, numeric_list<int>>::value));
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 1, 2, 3>::type, numeric_list<int, 0>>::value));
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 2, 2, 3>::type, numeric_list<int, 0, 1>>::value));
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 5, 2, 3>::type, numeric_list<int, 0, 1, 3, 2, 4>>::value));
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 10, 2, 3>::type, numeric_list<int, 0, 1, 3, 2, 4, 5, 6, 7, 8, 9>>::value));
+
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 0, 44, 45, 42>::type, numeric_list<int>>::value));
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 1, 44, 45, 42>::type, numeric_list<int, 42>>::value));
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 2, 44, 45, 42>::type, numeric_list<int, 42, 43>>::value));
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 5, 44, 45, 42>::type, numeric_list<int, 42, 43, 45, 44, 46>>::value));
+  VERIFY((is_same<typename gen_numeric_list_swapped_pair<int, 10, 44, 45, 42>::type, numeric_list<int, 42, 43, 45, 44, 46, 47, 48, 49, 50, 51>>::value));
+
+  VERIFY((is_same<typename gen_numeric_list_repeated<int, 0, 0>::type, numeric_list<int>>::value));
+  VERIFY((is_same<typename gen_numeric_list_repeated<int, 1, 0>::type, numeric_list<int, 0>>::value));
+  VERIFY((is_same<typename gen_numeric_list_repeated<int, 2, 0>::type, numeric_list<int, 0, 0>>::value));
+  VERIFY((is_same<typename gen_numeric_list_repeated<int, 5, 0>::type, numeric_list<int, 0, 0, 0, 0, 0>>::value));
+  VERIFY((is_same<typename gen_numeric_list_repeated<int, 10, 0>::type, numeric_list<int, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>>::value));
+}
+
+static void test_concat()
+{
+  VERIFY((is_same<typename concat<type_list<dummy_a, dummy_a>, type_list<>>::type, type_list<dummy_a, dummy_a>>::value));
+  VERIFY((is_same<typename concat<type_list<>, type_list<dummy_a, dummy_a>>::type, type_list<dummy_a, dummy_a>>::value));
+  VERIFY((is_same<typename concat<type_list<dummy_a, dummy_a>, type_list<dummy_a, dummy_a>>::type, type_list<dummy_a, dummy_a, dummy_a, dummy_a>>::value));
+  VERIFY((is_same<typename concat<type_list<dummy_a, dummy_a>, type_list<dummy_b, dummy_c>>::type, type_list<dummy_a, dummy_a, dummy_b, dummy_c>>::value));
+  VERIFY((is_same<typename concat<type_list<dummy_a>, type_list<dummy_b, dummy_c>>::type, type_list<dummy_a, dummy_b, dummy_c>>::value));
+
+  VERIFY((is_same<typename concat<numeric_list<int, 0, 0>, numeric_list<int>>::type, numeric_list<int, 0, 0>>::value));
+  VERIFY((is_same<typename concat<numeric_list<int>, numeric_list<int, 0, 0>>::type, numeric_list<int, 0, 0>>::value));
+  VERIFY((is_same<typename concat<numeric_list<int, 0, 0>, numeric_list<int, 0, 0>>::type, numeric_list<int, 0, 0, 0, 0>>::value));
+  VERIFY((is_same<typename concat<numeric_list<int, 0, 0>, numeric_list<int, 1, 2>>::type, numeric_list<int, 0, 0, 1, 2>>::value));
+  VERIFY((is_same<typename concat<numeric_list<int, 0>, numeric_list<int, 1, 2>>::type, numeric_list<int, 0, 1, 2>>::value));
+
+  VERIFY((is_same<typename mconcat<type_list<dummy_a>>::type, type_list<dummy_a>>::value));
+  VERIFY((is_same<typename mconcat<type_list<dummy_a>, type_list<dummy_b>>::type, type_list<dummy_a, dummy_b>>::value));
+  VERIFY((is_same<typename mconcat<type_list<dummy_a>, type_list<dummy_b>, type_list<dummy_c>>::type, type_list<dummy_a, dummy_b, dummy_c>>::value));
+  VERIFY((is_same<typename mconcat<type_list<dummy_a>, type_list<dummy_b, dummy_c>>::type, type_list<dummy_a, dummy_b, dummy_c>>::value));
+  VERIFY((is_same<typename mconcat<type_list<dummy_a, dummy_b>, type_list<dummy_c>>::type, type_list<dummy_a, dummy_b, dummy_c>>::value));
+
+  VERIFY((is_same<typename mconcat<numeric_list<int, 0>>::type, numeric_list<int, 0>>::value));
+  VERIFY((is_same<typename mconcat<numeric_list<int, 0>, numeric_list<int, 1>>::type, numeric_list<int, 0, 1>>::value));
+  VERIFY((is_same<typename mconcat<numeric_list<int, 0>, numeric_list<int, 1>, numeric_list<int, 2>>::type, numeric_list<int, 0, 1, 2>>::value));
+  VERIFY((is_same<typename mconcat<numeric_list<int, 0>, numeric_list<int, 1, 2>>::type, numeric_list<int, 0, 1, 2>>::value));
+  VERIFY((is_same<typename mconcat<numeric_list<int, 0, 1>, numeric_list<int, 2>>::type, numeric_list<int, 0, 1, 2>>::value));
+}
+
+static void test_slice()
+{
+  typedef type_list<dummy_a, dummy_a, dummy_b, dummy_b, dummy_c, dummy_c> tl;
+  typedef numeric_list<int, 0, 1, 2, 3, 4, 5> il;
+
+  VERIFY((is_same<typename take<0, tl>::type, type_list<>>::value));
+  VERIFY((is_same<typename take<1, tl>::type, type_list<dummy_a>>::value));
+  VERIFY((is_same<typename take<2, tl>::type, type_list<dummy_a, dummy_a>>::value));
+  VERIFY((is_same<typename take<3, tl>::type, type_list<dummy_a, dummy_a, dummy_b>>::value));
+  VERIFY((is_same<typename take<4, tl>::type, type_list<dummy_a, dummy_a, dummy_b, dummy_b>>::value));
+  VERIFY((is_same<typename take<5, tl>::type, type_list<dummy_a, dummy_a, dummy_b, dummy_b, dummy_c>>::value));
+  VERIFY((is_same<typename take<6, tl>::type, type_list<dummy_a, dummy_a, dummy_b, dummy_b, dummy_c, dummy_c>>::value));
+
+  VERIFY((is_same<typename take<0, il>::type, numeric_list<int>>::value));
+  VERIFY((is_same<typename take<1, il>::type, numeric_list<int, 0>>::value));
+  VERIFY((is_same<typename take<2, il>::type, numeric_list<int, 0, 1>>::value));
+  VERIFY((is_same<typename take<3, il>::type, numeric_list<int, 0, 1, 2>>::value));
+  VERIFY((is_same<typename take<4, il>::type, numeric_list<int, 0, 1, 2, 3>>::value));
+  VERIFY((is_same<typename take<5, il>::type, numeric_list<int, 0, 1, 2, 3, 4>>::value));
+  VERIFY((is_same<typename take<6, il>::type, numeric_list<int, 0, 1, 2, 3, 4, 5>>::value));
+  
+  VERIFY((is_same<typename skip<0, tl>::type, type_list<dummy_a, dummy_a, dummy_b, dummy_b, dummy_c, dummy_c>>::value));
+  VERIFY((is_same<typename skip<1, tl>::type, type_list<dummy_a, dummy_b, dummy_b, dummy_c, dummy_c>>::value));
+  VERIFY((is_same<typename skip<2, tl>::type, type_list<dummy_b, dummy_b, dummy_c, dummy_c>>::value));
+  VERIFY((is_same<typename skip<3, tl>::type, type_list<dummy_b, dummy_c, dummy_c>>::value));
+  VERIFY((is_same<typename skip<4, tl>::type, type_list<dummy_c, dummy_c>>::value));
+  VERIFY((is_same<typename skip<5, tl>::type, type_list<dummy_c>>::value));
+  VERIFY((is_same<typename skip<6, tl>::type, type_list<>>::value));
+
+  VERIFY((is_same<typename skip<0, il>::type, numeric_list<int, 0, 1, 2, 3, 4, 5>>::value));
+  VERIFY((is_same<typename skip<1, il>::type, numeric_list<int, 1, 2, 3, 4, 5>>::value));
+  VERIFY((is_same<typename skip<2, il>::type, numeric_list<int, 2, 3, 4, 5>>::value));
+  VERIFY((is_same<typename skip<3, il>::type, numeric_list<int, 3, 4, 5>>::value));
+  VERIFY((is_same<typename skip<4, il>::type, numeric_list<int, 4, 5>>::value));
+  VERIFY((is_same<typename skip<5, il>::type, numeric_list<int, 5>>::value));
+  VERIFY((is_same<typename skip<6, il>::type, numeric_list<int>>::value));
+
+  VERIFY((is_same<typename slice<0, 3, tl>::type, typename take<3, tl>::type>::value));
+  VERIFY((is_same<typename slice<0, 3, il>::type, typename take<3, il>::type>::value));
+  VERIFY((is_same<typename slice<1, 3, tl>::type, type_list<dummy_a, dummy_b, dummy_b>>::value));
+  VERIFY((is_same<typename slice<1, 3, il>::type, numeric_list<int, 1, 2, 3>>::value));
+}
+
+static void test_get()
+{
+  typedef type_list<dummy_a, dummy_a, dummy_b, dummy_b, dummy_c, dummy_c> tl;
+  typedef numeric_list<int, 4, 8, 15, 16, 23, 42> il;
+
+  VERIFY((is_same<typename get<0, tl>::type, dummy_a>::value));
+  VERIFY((is_same<typename get<1, tl>::type, dummy_a>::value));
+  VERIFY((is_same<typename get<2, tl>::type, dummy_b>::value));
+  VERIFY((is_same<typename get<3, tl>::type, dummy_b>::value));
+  VERIFY((is_same<typename get<4, tl>::type, dummy_c>::value));
+  VERIFY((is_same<typename get<5, tl>::type, dummy_c>::value));
+
+  VERIFY_IS_EQUAL(((int)get<0, il>::value), 4);
+  VERIFY_IS_EQUAL(((int)get<1, il>::value), 8);
+  VERIFY_IS_EQUAL(((int)get<2, il>::value), 15);
+  VERIFY_IS_EQUAL(((int)get<3, il>::value), 16);
+  VERIFY_IS_EQUAL(((int)get<4, il>::value), 23);
+  VERIFY_IS_EQUAL(((int)get<5, il>::value), 42);
+}
+
+static void test_id_helper(dummy_a a, dummy_a b, dummy_a c)
+{
+  (void)a;
+  (void)b;
+  (void)c;
+}
+
+template<int... ii>
+static void test_id_numeric()
+{
+  test_id_helper(typename id_numeric<int, ii, dummy_a>::type()...);
+}
+
+template<typename... tt>
+static void test_id_type()
+{
+  test_id_helper(typename id_type<tt, dummy_a>::type()...);
+}
+
+static void test_id()
+{
+  // don't call VERIFY here, just assume it works if it compiles
+  // (otherwise it will complain that it can't find the function)
+  test_id_numeric<1, 4, 6>();
+  test_id_type<dummy_a, dummy_b, dummy_c>();
+}
+
+static void test_is_same_gf()
+{
+  VERIFY((!is_same_gf<dummy_a, dummy_b>::value));
+  VERIFY((!!is_same_gf<dummy_a, dummy_a>::value));
+  VERIFY_IS_EQUAL((!!is_same_gf<dummy_a, dummy_b>::global_flags), false);
+  VERIFY_IS_EQUAL((!!is_same_gf<dummy_a, dummy_a>::global_flags), false);
+}
+
+static void test_apply_op()
+{
+  typedef type_list<dummy_a, dummy_b, dummy_c> tl;
+  VERIFY((!!is_same<typename apply_op_from_left<dummy_op, dummy_a, tl>::type, type_list<dummy_e, dummy_c, dummy_d>>::value));
+  VERIFY((!!is_same<typename apply_op_from_right<dummy_op, dummy_a, tl>::type, type_list<dummy_e, dummy_d, dummy_b>>::value));
+}
+
+static void test_contained_in_list()
+{
+  typedef type_list<dummy_a, dummy_b, dummy_c> tl;
+
+  VERIFY((!!contained_in_list<is_same, dummy_a, tl>::value));
+  VERIFY((!!contained_in_list<is_same, dummy_b, tl>::value));
+  VERIFY((!!contained_in_list<is_same, dummy_c, tl>::value));
+  VERIFY((!contained_in_list<is_same, dummy_d, tl>::value));
+  VERIFY((!contained_in_list<is_same, dummy_e, tl>::value));
+
+  VERIFY((!!contained_in_list_gf<dummy_test, dummy_a, tl>::value));
+  VERIFY((!!contained_in_list_gf<dummy_test, dummy_b, tl>::value));
+  VERIFY((!!contained_in_list_gf<dummy_test, dummy_c, tl>::value));
+  VERIFY((!contained_in_list_gf<dummy_test, dummy_d, tl>::value));
+  VERIFY((!contained_in_list_gf<dummy_test, dummy_e, tl>::value));
+
+  VERIFY_IS_EQUAL(((int)contained_in_list_gf<dummy_test, dummy_a, tl>::global_flags), 1);
+  VERIFY_IS_EQUAL(((int)contained_in_list_gf<dummy_test, dummy_b, tl>::global_flags), 2);
+  VERIFY_IS_EQUAL(((int)contained_in_list_gf<dummy_test, dummy_c, tl>::global_flags), 4);
+  VERIFY_IS_EQUAL(((int)contained_in_list_gf<dummy_test, dummy_d, tl>::global_flags), 0);
+  VERIFY_IS_EQUAL(((int)contained_in_list_gf<dummy_test, dummy_e, tl>::global_flags), 0);
+}
+
+static void test_arg_reductions()
+{
+  VERIFY_IS_EQUAL(arg_sum(1,2,3,4), 10);
+  VERIFY_IS_EQUAL(arg_prod(1,2,3,4), 24);
+  VERIFY_IS_APPROX(arg_sum(0.5, 2, 5), 7.5);
+  VERIFY_IS_APPROX(arg_prod(0.5, 2, 5), 5.0);
+}
+
+static void test_array_reverse_and_reduce()
+{
+  array<int, 6> a{{4, 8, 15, 16, 23, 42}};
+  array<int, 6> b{{42, 23, 16, 15, 8, 4}};
+
+  // there is no operator<< for std::array, so VERIFY_IS_EQUAL will
+  // not compile
+  VERIFY((array_reverse(a) == b));
+  VERIFY((array_reverse(b) == a));
+  VERIFY_IS_EQUAL((array_sum(a)), 108);
+  VERIFY_IS_EQUAL((array_sum(b)), 108);
+  VERIFY_IS_EQUAL((array_prod(a)), 7418880);
+  VERIFY_IS_EQUAL((array_prod(b)), 7418880);
+}
+
+static void test_array_zip_and_apply()
+{
+  array<int, 6> a{{4, 8, 15, 16, 23, 42}};
+  array<int, 6> b{{0, 1, 2, 3, 4, 5}};
+  array<int, 6> c{{4, 9, 17, 19, 27, 47}};
+  array<int, 6> d{{0, 8, 30, 48, 92, 210}};
+  array<int, 6> e{{0, 2, 4, 6, 8, 10}};
+
+  VERIFY((array_zip<sum_op>(a, b) == c));
+  VERIFY((array_zip<product_op>(a, b) == d));
+  VERIFY((array_apply<times2_op>(b) == e));
+  VERIFY_IS_EQUAL((array_apply_and_reduce<sum_op, times2_op>(a)), 216);
+  VERIFY_IS_EQUAL((array_apply_and_reduce<sum_op, times2_op>(b)), 30);
+  VERIFY_IS_EQUAL((array_zip_and_reduce<product_op, sum_op>(a, b)), 14755932);
+  VERIFY_IS_EQUAL((array_zip_and_reduce<sum_op, product_op>(a, b)), 388);
+}
+
+static void test_array_misc()
+{
+  array<int, 3> a3{{1, 1, 1}};
+  array<int, 6> a6{{2, 2, 2, 2, 2, 2}};
+  VERIFY((repeat<3, int>(1) == a3));
+  VERIFY((repeat<6, int>(2) == a6));
+
+  int data[5] = { 0, 1, 2, 3, 4 };
+  VERIFY_IS_EQUAL((instantiate_by_c_array<dummy_inst, int, 0>(data).c), 0);
+  VERIFY_IS_EQUAL((instantiate_by_c_array<dummy_inst, int, 1>(data).c), 1);
+  VERIFY_IS_EQUAL((instantiate_by_c_array<dummy_inst, int, 2>(data).c), 2);
+  VERIFY_IS_EQUAL((instantiate_by_c_array<dummy_inst, int, 3>(data).c), 3);
+  VERIFY_IS_EQUAL((instantiate_by_c_array<dummy_inst, int, 4>(data).c), 4);
+  VERIFY_IS_EQUAL((instantiate_by_c_array<dummy_inst, int, 5>(data).c), 5);
+}
+
+void test_cxx11_meta()
+{
+  CALL_SUBTEST(test_gen_numeric_list());
+  CALL_SUBTEST(test_concat());
+  CALL_SUBTEST(test_slice());
+  CALL_SUBTEST(test_get());
+  CALL_SUBTEST(test_id());
+  CALL_SUBTEST(test_is_same_gf());
+  CALL_SUBTEST(test_apply_op());
+  CALL_SUBTEST(test_contained_in_list());
+  CALL_SUBTEST(test_arg_reductions());
+  CALL_SUBTEST(test_array_reverse_and_reduce());
+  CALL_SUBTEST(test_array_zip_and_apply());
+  CALL_SUBTEST(test_array_misc());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_non_blocking_thread_pool.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_non_blocking_thread_pool.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_non_blocking_thread_pool.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_non_blocking_thread_pool.cpp
@@ -0,0 +1,107 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Dmitry Vyukov <dvyukov@google.com>
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_USE_THREADS
+#include "main.h"
+#include "Eigen/CXX11/ThreadPool"
+
+static void test_create_destroy_empty_pool()
+{
+  // Just create and destroy the pool. This will wind up and tear down worker
+  // threads. Ensure there are no issues in that logic.
+  for (int i = 0; i < 16; ++i) {
+    NonBlockingThreadPool tp(i);
+  }
+}
+
+
+static void test_parallelism()
+{
+  // Test we never-ever fail to match available tasks with idle threads.
+  const int kThreads = 16;  // code below expects that this is a multiple of 4
+  NonBlockingThreadPool tp(kThreads);
+  VERIFY_IS_EQUAL(tp.NumThreads(), kThreads);
+  VERIFY_IS_EQUAL(tp.CurrentThreadId(), -1);
+  for (int iter = 0; iter < 100; ++iter) {
+    std::atomic<int> running(0);
+    std::atomic<int> done(0);
+    std::atomic<int> phase(0);
+    // Schedule kThreads tasks and ensure that they all are running.
+    for (int i = 0; i < kThreads; ++i) {
+      tp.Schedule([&]() {
+        const int thread_id = tp.CurrentThreadId();
+        VERIFY_GE(thread_id, 0);
+        VERIFY_LE(thread_id, kThreads - 1);
+        running++;
+        while (phase < 1) {
+        }
+        done++;
+      });
+    }
+    while (running != kThreads) {
+    }
+    running = 0;
+    phase = 1;
+    // Now, while the previous tasks exit, schedule another kThreads tasks and
+    // ensure that they are running.
+    for (int i = 0; i < kThreads; ++i) {
+      tp.Schedule([&, i]() {
+        running++;
+        while (phase < 2) {
+        }
+        // When all tasks are running, half of tasks exit, quarter of tasks
+        // continue running and quarter of tasks schedule another 2 tasks each.
+        // Concurrently main thread schedules another quarter of tasks.
+        // This gives us another kThreads tasks and we ensure that they all
+        // are running.
+        if (i < kThreads / 2) {
+        } else if (i < 3 * kThreads / 4) {
+          running++;
+          while (phase < 3) {
+          }
+          done++;
+        } else {
+          for (int j = 0; j < 2; ++j) {
+            tp.Schedule([&]() {
+              running++;
+              while (phase < 3) {
+              }
+              done++;
+            });
+          }
+        }
+        done++;
+      });
+    }
+    while (running != kThreads) {
+    }
+    running = 0;
+    phase = 2;
+    for (int i = 0; i < kThreads / 4; ++i) {
+      tp.Schedule([&]() {
+        running++;
+        while (phase < 3) {
+        }
+        done++;
+      });
+    }
+    while (running != kThreads) {
+    }
+    phase = 3;
+    while (done != 3 * kThreads) {
+    }
+  }
+}
+
+void test_cxx11_non_blocking_thread_pool()
+{
+  CALL_SUBTEST(test_create_destroy_empty_pool());
+  CALL_SUBTEST(test_parallelism());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_runqueue.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_runqueue.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_runqueue.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_runqueue.cpp
@@ -0,0 +1,235 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Dmitry Vyukov <dvyukov@google.com>
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_USE_THREADS
+#include <cstdlib>
+#include "main.h"
+#include <Eigen/CXX11/ThreadPool>
+
+
+// Visual studio doesn't implement a rand_r() function since its
+// implementation of rand() is already thread safe
+int rand_reentrant(unsigned int* s) {
+#ifdef EIGEN_COMP_MSVC_STRICT
+  EIGEN_UNUSED_VARIABLE(s);
+  return rand();
+#else
+  return rand_r(s);
+#endif
+}
+
+void test_basic_runqueue()
+{
+  RunQueue<int, 4> q;
+  // Check empty state.
+  VERIFY(q.Empty());
+  VERIFY_IS_EQUAL(0u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PopFront());
+  std::vector<int> stolen;
+  VERIFY_IS_EQUAL(0u, q.PopBackHalf(&stolen));
+  VERIFY_IS_EQUAL(0u, stolen.size());
+  // Push one front, pop one front.
+  VERIFY_IS_EQUAL(0, q.PushFront(1));
+  VERIFY_IS_EQUAL(1u, q.Size());
+  VERIFY_IS_EQUAL(1, q.PopFront());
+  VERIFY_IS_EQUAL(0u, q.Size());
+  // Push front to overflow.
+  VERIFY_IS_EQUAL(0, q.PushFront(2));
+  VERIFY_IS_EQUAL(1u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PushFront(3));
+  VERIFY_IS_EQUAL(2u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PushFront(4));
+  VERIFY_IS_EQUAL(3u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PushFront(5));
+  VERIFY_IS_EQUAL(4u, q.Size());
+  VERIFY_IS_EQUAL(6, q.PushFront(6));
+  VERIFY_IS_EQUAL(4u, q.Size());
+  VERIFY_IS_EQUAL(5, q.PopFront());
+  VERIFY_IS_EQUAL(3u, q.Size());
+  VERIFY_IS_EQUAL(4, q.PopFront());
+  VERIFY_IS_EQUAL(2u, q.Size());
+  VERIFY_IS_EQUAL(3, q.PopFront());
+  VERIFY_IS_EQUAL(1u, q.Size());
+  VERIFY_IS_EQUAL(2, q.PopFront());
+  VERIFY_IS_EQUAL(0u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PopFront());
+  // Push one back, pop one back.
+  VERIFY_IS_EQUAL(0, q.PushBack(7));
+  VERIFY_IS_EQUAL(1u, q.Size());
+  VERIFY_IS_EQUAL(1u, q.PopBackHalf(&stolen));
+  VERIFY_IS_EQUAL(1u, stolen.size());
+  VERIFY_IS_EQUAL(7, stolen[0]);
+  VERIFY_IS_EQUAL(0u, q.Size());
+  stolen.clear();
+  // Push back to overflow.
+  VERIFY_IS_EQUAL(0, q.PushBack(8));
+  VERIFY_IS_EQUAL(1u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PushBack(9));
+  VERIFY_IS_EQUAL(2u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PushBack(10));
+  VERIFY_IS_EQUAL(3u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PushBack(11));
+  VERIFY_IS_EQUAL(4u, q.Size());
+  VERIFY_IS_EQUAL(12, q.PushBack(12));
+  VERIFY_IS_EQUAL(4u, q.Size());
+  // Pop back in halves.
+  VERIFY_IS_EQUAL(2u, q.PopBackHalf(&stolen));
+  VERIFY_IS_EQUAL(2u, stolen.size());
+  VERIFY_IS_EQUAL(10, stolen[0]);
+  VERIFY_IS_EQUAL(11, stolen[1]);
+  VERIFY_IS_EQUAL(2u, q.Size());
+  stolen.clear();
+  VERIFY_IS_EQUAL(1u, q.PopBackHalf(&stolen));
+  VERIFY_IS_EQUAL(1u, stolen.size());
+  VERIFY_IS_EQUAL(9, stolen[0]);
+  VERIFY_IS_EQUAL(1u, q.Size());
+  stolen.clear();
+  VERIFY_IS_EQUAL(1u, q.PopBackHalf(&stolen));
+  VERIFY_IS_EQUAL(1u, stolen.size());
+  VERIFY_IS_EQUAL(8, stolen[0]);
+  stolen.clear();
+  VERIFY_IS_EQUAL(0u, q.PopBackHalf(&stolen));
+  VERIFY_IS_EQUAL(0u, stolen.size());
+  // Empty again.
+  VERIFY(q.Empty());
+  VERIFY_IS_EQUAL(0u, q.Size());
+  VERIFY_IS_EQUAL(0, q.PushFront(1));
+  VERIFY_IS_EQUAL(0, q.PushFront(2));
+  VERIFY_IS_EQUAL(0, q.PushFront(3));
+  VERIFY_IS_EQUAL(1, q.PopBack());
+  VERIFY_IS_EQUAL(2, q.PopBack());
+  VERIFY_IS_EQUAL(3, q.PopBack());
+  VERIFY(q.Empty());
+  VERIFY_IS_EQUAL(0u, q.Size());
+}
+
+// Empty tests that the queue is not claimed to be empty when is is in fact not.
+// Emptiness property is crucial part of thread pool blocking scheme,
+// so we go to great effort to ensure this property. We create a queue with
+// 1 element and then push 1 element (either front or back at random) and pop
+// 1 element (either front or back at random). So queue always contains at least
+// 1 element, but otherwise changes chaotically. Another thread constantly tests
+// that the queue is not claimed to be empty.
+void test_empty_runqueue()
+{
+  RunQueue<int, 4> q;
+  q.PushFront(1);
+  std::atomic<bool> done(false);
+  std::thread mutator([&q, &done]() {
+    unsigned rnd = 0;
+    std::vector<int> stolen;
+    for (int i = 0; i < 1 << 18; i++) {
+      if (rand_reentrant(&rnd) % 2)
+        VERIFY_IS_EQUAL(0, q.PushFront(1));
+      else
+        VERIFY_IS_EQUAL(0, q.PushBack(1));
+      if (rand_reentrant(&rnd) % 2)
+        VERIFY_IS_EQUAL(1, q.PopFront());
+      else {
+        for (;;) {
+          if (q.PopBackHalf(&stolen) == 1) {
+            stolen.clear();
+            break;
+          }
+          VERIFY_IS_EQUAL(0u, stolen.size());
+        }
+      }
+    }
+    done = true;
+  });
+  while (!done) {
+    VERIFY(!q.Empty());
+    int size = q.Size();
+    VERIFY_GE(size, 1);
+    VERIFY_LE(size, 2);
+  }
+  VERIFY_IS_EQUAL(1, q.PopFront());
+  mutator.join();
+}
+
+// Stress is a chaotic random test.
+// One thread (owner) calls PushFront/PopFront, other threads call PushBack/
+// PopBack. Ensure that we don't crash, deadlock, and all sanity checks pass.
+void test_stress_runqueue()
+{
+  static const int kEvents = 1 << 18;
+  RunQueue<int, 8> q;
+  std::atomic<int> total(0);
+  std::vector<std::unique_ptr<std::thread>> threads;
+  threads.emplace_back(new std::thread([&q, &total]() {
+    int sum = 0;
+    int pushed = 1;
+    int popped = 1;
+    while (pushed < kEvents || popped < kEvents) {
+      if (pushed < kEvents) {
+        if (q.PushFront(pushed) == 0) {
+          sum += pushed;
+          pushed++;
+        }
+      }
+      if (popped < kEvents) {
+        int v = q.PopFront();
+        if (v != 0) {
+          sum -= v;
+          popped++;
+        }
+      }
+    }
+    total += sum;
+  }));
+  for (int i = 0; i < 2; i++) {
+    threads.emplace_back(new std::thread([&q, &total]() {
+      int sum = 0;
+      for (int j = 1; j < kEvents; j++) {
+        if (q.PushBack(j) == 0) {
+          sum += j;
+          continue;
+        }
+        EIGEN_THREAD_YIELD();
+        j--;
+      }
+      total += sum;
+    }));
+    threads.emplace_back(new std::thread([&q, &total]() {
+      int sum = 0;
+      std::vector<int> stolen;
+      for (int j = 1; j < kEvents;) {
+        if (q.PopBackHalf(&stolen) == 0) {
+          EIGEN_THREAD_YIELD();
+          continue;
+        }
+        while (stolen.size() && j < kEvents) {
+          int v = stolen.back();
+          stolen.pop_back();
+          VERIFY_IS_NOT_EQUAL(v, 0);
+          sum += v;
+          j++;
+        }
+      }
+      while (stolen.size()) {
+        int v = stolen.back();
+        stolen.pop_back();
+        VERIFY_IS_NOT_EQUAL(v, 0);
+        while ((v = q.PushBack(v)) != 0) EIGEN_THREAD_YIELD();
+      }
+      total -= sum;
+    }));
+  }
+  for (size_t i = 0; i < threads.size(); i++) threads[i]->join();
+  VERIFY(q.Empty());
+  VERIFY(total.load() == 0);
+}
+
+void test_cxx11_runqueue()
+{
+  CALL_SUBTEST_1(test_basic_runqueue());
+  CALL_SUBTEST_2(test_empty_runqueue());
+  CALL_SUBTEST_3(test_stress_runqueue());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_argmax.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_argmax.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_argmax.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_argmax.cpp
@@ -0,0 +1,294 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Eugene Brevdo <ebrevdo@google.com>
+//                    Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::array;
+using Eigen::Tuple;
+
+template <int DataLayout>
+static void test_simple_index_tuples()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  tensor = (tensor + tensor.constant(0.5)).log();
+
+  Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
+  index_tuples = tensor.index_tuples();
+
+  for (DenseIndex n = 0; n < 2*3*5*7; ++n) {
+    const Tuple<DenseIndex, float>& v = index_tuples.coeff(n);
+    VERIFY_IS_EQUAL(v.first, n);
+    VERIFY_IS_EQUAL(v.second, tensor.coeff(n));
+  }
+}
+
+template <int DataLayout>
+static void test_index_tuples_dim()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  tensor = (tensor + tensor.constant(0.5)).log();
+
+  Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
+
+  index_tuples = tensor.index_tuples();
+
+  for (Eigen::DenseIndex n = 0; n < tensor.size(); ++n) {
+    const Tuple<DenseIndex, float>& v = index_tuples(n); //(i, j, k, l);
+    VERIFY_IS_EQUAL(v.first, n);
+    VERIFY_IS_EQUAL(v.second, tensor(n));
+  }
+}
+
+template <int DataLayout>
+static void test_argmax_tuple_reducer()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  tensor = (tensor + tensor.constant(0.5)).log();
+
+  Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
+  index_tuples = tensor.index_tuples();
+
+  Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
+  DimensionList<DenseIndex, 4> dims;
+  reduced = index_tuples.reduce(
+      dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float> >());
+
+  Tensor<float, 0, DataLayout> maxi = tensor.maximum();
+
+  VERIFY_IS_EQUAL(maxi(), reduced(0).second);
+
+  array<DenseIndex, 3> reduce_dims;
+  for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
+  Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7);
+  reduced_by_dims = index_tuples.reduce(
+      reduce_dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float> >());
+
+  Tensor<float, 1, DataLayout> max_by_dims = tensor.maximum(reduce_dims);
+
+  for (int l = 0; l < 7; ++l) {
+    VERIFY_IS_EQUAL(max_by_dims(l), reduced_by_dims(l).second);
+  }
+}
+
+template <int DataLayout>
+static void test_argmin_tuple_reducer()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  tensor = (tensor + tensor.constant(0.5)).log();
+
+  Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
+  index_tuples = tensor.index_tuples();
+
+  Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
+  DimensionList<DenseIndex, 4> dims;
+  reduced = index_tuples.reduce(
+      dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float> >());
+
+  Tensor<float, 0, DataLayout> mini = tensor.minimum();
+
+  VERIFY_IS_EQUAL(mini(), reduced(0).second);
+
+  array<DenseIndex, 3> reduce_dims;
+  for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
+  Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7);
+  reduced_by_dims = index_tuples.reduce(
+      reduce_dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float> >());
+
+  Tensor<float, 1, DataLayout> min_by_dims = tensor.minimum(reduce_dims);
+
+  for (int l = 0; l < 7; ++l) {
+    VERIFY_IS_EQUAL(min_by_dims(l), reduced_by_dims(l).second);
+  }
+}
+
+template <int DataLayout>
+static void test_simple_argmax()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  tensor = (tensor + tensor.constant(0.5)).log();
+  tensor(0,0,0,0) = 10.0;
+
+  Tensor<DenseIndex, 0, DataLayout> tensor_argmax;
+
+  tensor_argmax = tensor.argmax();
+
+  VERIFY_IS_EQUAL(tensor_argmax(0), 0);
+
+  tensor(1,2,4,6) = 20.0;
+
+  tensor_argmax = tensor.argmax();
+
+  VERIFY_IS_EQUAL(tensor_argmax(0), 2*3*5*7 - 1);
+}
+
+template <int DataLayout>
+static void test_simple_argmin()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  tensor = (tensor + tensor.constant(0.5)).log();
+  tensor(0,0,0,0) = -10.0;
+
+  Tensor<DenseIndex, 0, DataLayout> tensor_argmin;
+
+  tensor_argmin = tensor.argmin();
+
+  VERIFY_IS_EQUAL(tensor_argmin(0), 0);
+
+  tensor(1,2,4,6) = -20.0;
+
+  tensor_argmin = tensor.argmin();
+
+  VERIFY_IS_EQUAL(tensor_argmin(0), 2*3*5*7 - 1);
+}
+
+template <int DataLayout>
+static void test_argmax_dim()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  std::vector<int> dims {2, 3, 5, 7};
+
+  for (int dim = 0; dim < 4; ++dim) {
+    tensor.setRandom();
+    tensor = (tensor + tensor.constant(0.5)).log();
+
+    Tensor<DenseIndex, 3, DataLayout> tensor_argmax;
+    array<DenseIndex, 4> ix;
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 5; ++k) {
+          for (int l = 0; l < 7; ++l) {
+            ix[0] = i; ix[1] = j; ix[2] = k; ix[3] = l;
+            if (ix[dim] != 0) continue;
+            // suppose dim == 1, then for all i, k, l, set tensor(i, 0, k, l) = 10.0
+            tensor(ix) = 10.0;
+          }
+        }
+      }
+    }
+
+    tensor_argmax = tensor.argmax(dim);
+
+    VERIFY_IS_EQUAL(tensor_argmax.size(),
+                    ptrdiff_t(2*3*5*7 / tensor.dimension(dim)));
+    for (ptrdiff_t n = 0; n < tensor_argmax.size(); ++n) {
+      // Expect max to be in the first index of the reduced dimension
+      VERIFY_IS_EQUAL(tensor_argmax.data()[n], 0);
+    }
+
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 5; ++k) {
+          for (int l = 0; l < 7; ++l) {
+            ix[0] = i; ix[1] = j; ix[2] = k; ix[3] = l;
+            if (ix[dim] != tensor.dimension(dim) - 1) continue;
+            // suppose dim == 1, then for all i, k, l, set tensor(i, 2, k, l) = 20.0
+            tensor(ix) = 20.0;
+          }
+        }
+      }
+    }
+
+    tensor_argmax = tensor.argmax(dim);
+
+    VERIFY_IS_EQUAL(tensor_argmax.size(),
+                    ptrdiff_t(2*3*5*7 / tensor.dimension(dim)));
+    for (ptrdiff_t n = 0; n < tensor_argmax.size(); ++n) {
+      // Expect max to be in the last index of the reduced dimension
+      VERIFY_IS_EQUAL(tensor_argmax.data()[n], tensor.dimension(dim) - 1);
+    }
+  }
+}
+
+template <int DataLayout>
+static void test_argmin_dim()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  std::vector<int> dims {2, 3, 5, 7};
+
+  for (int dim = 0; dim < 4; ++dim) {
+    tensor.setRandom();
+    tensor = (tensor + tensor.constant(0.5)).log();
+
+    Tensor<DenseIndex, 3, DataLayout> tensor_argmin;
+    array<DenseIndex, 4> ix;
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 5; ++k) {
+          for (int l = 0; l < 7; ++l) {
+            ix[0] = i; ix[1] = j; ix[2] = k; ix[3] = l;
+            if (ix[dim] != 0) continue;
+            // suppose dim == 1, then for all i, k, l, set tensor(i, 0, k, l) = -10.0
+            tensor(ix) = -10.0;
+          }
+        }
+      }
+    }
+
+    tensor_argmin = tensor.argmin(dim);
+
+    VERIFY_IS_EQUAL(tensor_argmin.size(),
+                    ptrdiff_t(2*3*5*7 / tensor.dimension(dim)));
+    for (ptrdiff_t n = 0; n < tensor_argmin.size(); ++n) {
+      // Expect min to be in the first index of the reduced dimension
+      VERIFY_IS_EQUAL(tensor_argmin.data()[n], 0);
+    }
+
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 5; ++k) {
+          for (int l = 0; l < 7; ++l) {
+            ix[0] = i; ix[1] = j; ix[2] = k; ix[3] = l;
+            if (ix[dim] != tensor.dimension(dim) - 1) continue;
+            // suppose dim == 1, then for all i, k, l, set tensor(i, 2, k, l) = -20.0
+            tensor(ix) = -20.0;
+          }
+        }
+      }
+    }
+
+    tensor_argmin = tensor.argmin(dim);
+
+    VERIFY_IS_EQUAL(tensor_argmin.size(),
+                    ptrdiff_t(2*3*5*7 / tensor.dimension(dim)));
+    for (ptrdiff_t n = 0; n < tensor_argmin.size(); ++n) {
+      // Expect min to be in the last index of the reduced dimension
+      VERIFY_IS_EQUAL(tensor_argmin.data()[n], tensor.dimension(dim) - 1);
+    }
+  }
+}
+
+void test_cxx11_tensor_argmax()
+{
+  CALL_SUBTEST(test_simple_index_tuples<RowMajor>());
+  CALL_SUBTEST(test_simple_index_tuples<ColMajor>());
+  CALL_SUBTEST(test_index_tuples_dim<RowMajor>());
+  CALL_SUBTEST(test_index_tuples_dim<ColMajor>());
+  CALL_SUBTEST(test_argmax_tuple_reducer<RowMajor>());
+  CALL_SUBTEST(test_argmax_tuple_reducer<ColMajor>());
+  CALL_SUBTEST(test_argmin_tuple_reducer<RowMajor>());
+  CALL_SUBTEST(test_argmin_tuple_reducer<ColMajor>());
+  CALL_SUBTEST(test_simple_argmax<RowMajor>());
+  CALL_SUBTEST(test_simple_argmax<ColMajor>());
+  CALL_SUBTEST(test_simple_argmin<RowMajor>());
+  CALL_SUBTEST(test_simple_argmin<ColMajor>());
+  CALL_SUBTEST(test_argmax_dim<RowMajor>());
+  CALL_SUBTEST(test_argmax_dim<ColMajor>());
+  CALL_SUBTEST(test_argmin_dim<RowMajor>());
+  CALL_SUBTEST(test_argmin_dim<ColMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_argmax_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_argmax_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_argmax_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_argmax_cuda.cu
@@ -0,0 +1,254 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_FUNC cxx11_tensor_cuda
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template <int Layout>
+void test_cuda_simple_argmax()
+{
+  Tensor<double, 3, Layout> in(Eigen::array<DenseIndex, 3>(72,53,97));
+  Tensor<DenseIndex, 1, Layout> out_max(Eigen::array<DenseIndex, 1>(1));
+  Tensor<DenseIndex, 1, Layout> out_min(Eigen::array<DenseIndex, 1>(1));
+  in.setRandom();
+  in *= in.constant(100.0);
+  in(0, 0, 0) = -1000.0;
+  in(71, 52, 96) = 1000.0;
+
+  std::size_t in_bytes = in.size() * sizeof(double);
+  std::size_t out_bytes = out_max.size() * sizeof(DenseIndex);
+
+  double* d_in;
+  DenseIndex* d_out_max;
+  DenseIndex* d_out_min;
+  cudaMalloc((void**)(&d_in), in_bytes);
+  cudaMalloc((void**)(&d_out_max), out_bytes);
+  cudaMalloc((void**)(&d_out_min), out_bytes);
+
+  cudaMemcpy(d_in, in.data(), in_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<double, 3, Layout>, Aligned > gpu_in(d_in, Eigen::array<DenseIndex, 3>(72,53,97));
+  Eigen::TensorMap<Eigen::Tensor<DenseIndex, 1, Layout>, Aligned > gpu_out_max(d_out_max, Eigen::array<DenseIndex, 1>(1));
+  Eigen::TensorMap<Eigen::Tensor<DenseIndex, 1, Layout>, Aligned > gpu_out_min(d_out_min, Eigen::array<DenseIndex, 1>(1));
+
+  gpu_out_max.device(gpu_device) = gpu_in.argmax();
+  gpu_out_min.device(gpu_device) = gpu_in.argmin();
+
+  assert(cudaMemcpyAsync(out_max.data(), d_out_max, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaMemcpyAsync(out_min.data(), d_out_min, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  VERIFY_IS_EQUAL(out_max(Eigen::array<DenseIndex, 1>(0)), 72*53*97 - 1);
+  VERIFY_IS_EQUAL(out_min(Eigen::array<DenseIndex, 1>(0)), 0);
+
+  cudaFree(d_in);
+  cudaFree(d_out_max);
+  cudaFree(d_out_min);
+}
+
+template <int DataLayout>
+void test_cuda_argmax_dim()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  std::vector<int> dims;
+  dims.push_back(2); dims.push_back(3); dims.push_back(5); dims.push_back(7);
+
+  for (int dim = 0; dim < 4; ++dim) {
+    tensor.setRandom();
+    tensor = (tensor + tensor.constant(0.5)).log();
+
+    array<DenseIndex, 3> out_shape;
+    for (int d = 0; d < 3; ++d) out_shape[d] = (d < dim) ? dims[d] : dims[d+1];
+
+    Tensor<DenseIndex, 3, DataLayout> tensor_arg(out_shape);
+
+    array<DenseIndex, 4> ix;
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 5; ++k) {
+          for (int l = 0; l < 7; ++l) {
+            ix[0] = i; ix[1] = j; ix[2] = k; ix[3] = l;
+            if (ix[dim] != 0) continue;
+            // suppose dim == 1, then for all i, k, l, set tensor(i, 0, k, l) = 10.0
+            tensor(ix) = 10.0;
+          }
+        }
+      }
+    }
+
+    std::size_t in_bytes = tensor.size() * sizeof(float);
+    std::size_t out_bytes = tensor_arg.size() * sizeof(DenseIndex);
+
+    float* d_in;
+    DenseIndex* d_out;
+    cudaMalloc((void**)(&d_in), in_bytes);
+    cudaMalloc((void**)(&d_out), out_bytes);
+
+    cudaMemcpy(d_in, tensor.data(), in_bytes, cudaMemcpyHostToDevice);
+
+    Eigen::CudaStreamDevice stream;
+    Eigen::GpuDevice gpu_device(&stream);
+
+    Eigen::TensorMap<Eigen::Tensor<float, 4, DataLayout>, Aligned > gpu_in(d_in, Eigen::array<DenseIndex, 4>(2, 3, 5, 7));
+    Eigen::TensorMap<Eigen::Tensor<DenseIndex, 3, DataLayout>, Aligned > gpu_out(d_out, out_shape);
+
+    gpu_out.device(gpu_device) = gpu_in.argmax(dim);
+
+    assert(cudaMemcpyAsync(tensor_arg.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+    assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+    VERIFY_IS_EQUAL(tensor_arg.size(),
+                    size_t(2*3*5*7 / tensor.dimension(dim)));
+
+    for (DenseIndex n = 0; n < tensor_arg.size(); ++n) {
+      // Expect max to be in the first index of the reduced dimension
+      VERIFY_IS_EQUAL(tensor_arg.data()[n], 0);
+    }
+
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 5; ++k) {
+          for (int l = 0; l < 7; ++l) {
+            ix[0] = i; ix[1] = j; ix[2] = k; ix[3] = l;
+            if (ix[dim] != tensor.dimension(dim) - 1) continue;
+            // suppose dim == 1, then for all i, k, l, set tensor(i, 2, k, l) = 20.0
+            tensor(ix) = 20.0;
+          }
+        }
+      }
+    }
+
+    cudaMemcpy(d_in, tensor.data(), in_bytes, cudaMemcpyHostToDevice);
+
+    gpu_out.device(gpu_device) = gpu_in.argmax(dim);
+
+    assert(cudaMemcpyAsync(tensor_arg.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+    assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+    for (DenseIndex n = 0; n < tensor_arg.size(); ++n) {
+      // Expect max to be in the last index of the reduced dimension
+      VERIFY_IS_EQUAL(tensor_arg.data()[n], tensor.dimension(dim) - 1);
+    }
+
+    cudaFree(d_in);
+    cudaFree(d_out);
+  }
+}
+
+template <int DataLayout>
+void test_cuda_argmin_dim()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  std::vector<int> dims;
+  dims.push_back(2); dims.push_back(3); dims.push_back(5); dims.push_back(7);
+
+  for (int dim = 0; dim < 4; ++dim) {
+    tensor.setRandom();
+    tensor = (tensor + tensor.constant(0.5)).log();
+
+    array<DenseIndex, 3> out_shape;
+    for (int d = 0; d < 3; ++d) out_shape[d] = (d < dim) ? dims[d] : dims[d+1];
+
+    Tensor<DenseIndex, 3, DataLayout> tensor_arg(out_shape);
+
+    array<DenseIndex, 4> ix;
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 5; ++k) {
+          for (int l = 0; l < 7; ++l) {
+            ix[0] = i; ix[1] = j; ix[2] = k; ix[3] = l;
+            if (ix[dim] != 0) continue;
+            // suppose dim == 1, then for all i, k, l, set tensor(i, 0, k, l) = 10.0
+            tensor(ix) = -10.0;
+          }
+        }
+      }
+    }
+
+    std::size_t in_bytes = tensor.size() * sizeof(float);
+    std::size_t out_bytes = tensor_arg.size() * sizeof(DenseIndex);
+
+    float* d_in;
+    DenseIndex* d_out;
+    cudaMalloc((void**)(&d_in), in_bytes);
+    cudaMalloc((void**)(&d_out), out_bytes);
+
+    cudaMemcpy(d_in, tensor.data(), in_bytes, cudaMemcpyHostToDevice);
+
+    Eigen::CudaStreamDevice stream;
+    Eigen::GpuDevice gpu_device(&stream);
+
+    Eigen::TensorMap<Eigen::Tensor<float, 4, DataLayout>, Aligned > gpu_in(d_in, Eigen::array<DenseIndex, 4>(2, 3, 5, 7));
+    Eigen::TensorMap<Eigen::Tensor<DenseIndex, 3, DataLayout>, Aligned > gpu_out(d_out, out_shape);
+
+    gpu_out.device(gpu_device) = gpu_in.argmin(dim);
+
+    assert(cudaMemcpyAsync(tensor_arg.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+    assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+    VERIFY_IS_EQUAL(tensor_arg.size(),
+                    2*3*5*7 / tensor.dimension(dim));
+
+    for (DenseIndex n = 0; n < tensor_arg.size(); ++n) {
+      // Expect min to be in the first index of the reduced dimension
+      VERIFY_IS_EQUAL(tensor_arg.data()[n], 0);
+    }
+
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        for (int k = 0; k < 5; ++k) {
+          for (int l = 0; l < 7; ++l) {
+            ix[0] = i; ix[1] = j; ix[2] = k; ix[3] = l;
+            if (ix[dim] != tensor.dimension(dim) - 1) continue;
+            // suppose dim == 1, then for all i, k, l, set tensor(i, 2, k, l) = 20.0
+            tensor(ix) = -20.0;
+          }
+        }
+      }
+    }
+
+    cudaMemcpy(d_in, tensor.data(), in_bytes, cudaMemcpyHostToDevice);
+
+    gpu_out.device(gpu_device) = gpu_in.argmin(dim);
+
+    assert(cudaMemcpyAsync(tensor_arg.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+    assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+    for (DenseIndex n = 0; n < tensor_arg.size(); ++n) {
+      // Expect max to be in the last index of the reduced dimension
+      VERIFY_IS_EQUAL(tensor_arg.data()[n], tensor.dimension(dim) - 1);
+    }
+
+    cudaFree(d_in);
+    cudaFree(d_out);
+  }
+}
+
+void test_cxx11_tensor_cuda()
+{
+  CALL_SUBTEST_1(test_cuda_simple_argmax<RowMajor>());
+  CALL_SUBTEST_1(test_cuda_simple_argmax<ColMajor>());
+  CALL_SUBTEST_2(test_cuda_argmax_dim<RowMajor>());
+  CALL_SUBTEST_2(test_cuda_argmax_dim<ColMajor>());
+  CALL_SUBTEST_3(test_cuda_argmin_dim<RowMajor>());
+  CALL_SUBTEST_3(test_cuda_argmin_dim<ColMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_assign.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_assign.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_assign.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_assign.cpp
@@ -0,0 +1,370 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_1d()
+{
+  Tensor<int, 1> vec1(6);
+  Tensor<int, 1, RowMajor> vec2(6);
+  vec1(0) = 4;  vec2(0) = 0;
+  vec1(1) = 8;  vec2(1) = 1;
+  vec1(2) = 15; vec2(2) = 2;
+  vec1(3) = 16; vec2(3) = 3;
+  vec1(4) = 23; vec2(4) = 4;
+  vec1(5) = 42; vec2(5) = 5;
+
+  int col_major[6];
+  int row_major[6];
+  memset(col_major, 0, 6*sizeof(int));
+  memset(row_major, 0, 6*sizeof(int));
+  TensorMap<Tensor<int, 1> > vec3(col_major, 6);
+  TensorMap<Tensor<int, 1, RowMajor> > vec4(row_major, 6);
+
+  vec3 = vec1;
+  vec4 = vec2;
+
+  VERIFY_IS_EQUAL(vec3(0), 4);
+  VERIFY_IS_EQUAL(vec3(1), 8);
+  VERIFY_IS_EQUAL(vec3(2), 15);
+  VERIFY_IS_EQUAL(vec3(3), 16);
+  VERIFY_IS_EQUAL(vec3(4), 23);
+  VERIFY_IS_EQUAL(vec3(5), 42);
+
+  VERIFY_IS_EQUAL(vec4(0), 0);
+  VERIFY_IS_EQUAL(vec4(1), 1);
+  VERIFY_IS_EQUAL(vec4(2), 2);
+  VERIFY_IS_EQUAL(vec4(3), 3);
+  VERIFY_IS_EQUAL(vec4(4), 4);
+  VERIFY_IS_EQUAL(vec4(5), 5);
+
+  vec1.setZero();
+  vec2.setZero();
+  vec1 = vec3;
+  vec2 = vec4;
+
+  VERIFY_IS_EQUAL(vec1(0), 4);
+  VERIFY_IS_EQUAL(vec1(1), 8);
+  VERIFY_IS_EQUAL(vec1(2), 15);
+  VERIFY_IS_EQUAL(vec1(3), 16);
+  VERIFY_IS_EQUAL(vec1(4), 23);
+  VERIFY_IS_EQUAL(vec1(5), 42);
+
+  VERIFY_IS_EQUAL(vec2(0), 0);
+  VERIFY_IS_EQUAL(vec2(1), 1);
+  VERIFY_IS_EQUAL(vec2(2), 2);
+  VERIFY_IS_EQUAL(vec2(3), 3);
+  VERIFY_IS_EQUAL(vec2(4), 4);
+  VERIFY_IS_EQUAL(vec2(5), 5);
+}
+
+static void test_2d()
+{
+  Tensor<int, 2> mat1(2,3);
+  Tensor<int, 2, RowMajor> mat2(2,3);
+
+  mat1(0,0) = 0;
+  mat1(0,1) = 1;
+  mat1(0,2) = 2;
+  mat1(1,0) = 3;
+  mat1(1,1) = 4;
+  mat1(1,2) = 5;
+
+  mat2(0,0) = 0;
+  mat2(0,1) = 1;
+  mat2(0,2) = 2;
+  mat2(1,0) = 3;
+  mat2(1,1) = 4;
+  mat2(1,2) = 5;
+
+  int col_major[6];
+  int row_major[6];
+  memset(col_major, 0, 6*sizeof(int));
+  memset(row_major, 0, 6*sizeof(int));
+  TensorMap<Tensor<int, 2> > mat3(row_major, 2, 3);
+  TensorMap<Tensor<int, 2, RowMajor> > mat4(col_major, 2, 3);
+
+  mat3 = mat1;
+  mat4 = mat2;
+
+  VERIFY_IS_EQUAL(mat3(0,0), 0);
+  VERIFY_IS_EQUAL(mat3(0,1), 1);
+  VERIFY_IS_EQUAL(mat3(0,2), 2);
+  VERIFY_IS_EQUAL(mat3(1,0), 3);
+  VERIFY_IS_EQUAL(mat3(1,1), 4);
+  VERIFY_IS_EQUAL(mat3(1,2), 5);
+
+  VERIFY_IS_EQUAL(mat4(0,0), 0);
+  VERIFY_IS_EQUAL(mat4(0,1), 1);
+  VERIFY_IS_EQUAL(mat4(0,2), 2);
+  VERIFY_IS_EQUAL(mat4(1,0), 3);
+  VERIFY_IS_EQUAL(mat4(1,1), 4);
+  VERIFY_IS_EQUAL(mat4(1,2), 5);
+
+  mat1.setZero();
+  mat2.setZero();
+  mat1 = mat3;
+  mat2 = mat4;
+
+  VERIFY_IS_EQUAL(mat1(0,0), 0);
+  VERIFY_IS_EQUAL(mat1(0,1), 1);
+  VERIFY_IS_EQUAL(mat1(0,2), 2);
+  VERIFY_IS_EQUAL(mat1(1,0), 3);
+  VERIFY_IS_EQUAL(mat1(1,1), 4);
+  VERIFY_IS_EQUAL(mat1(1,2), 5);
+
+  VERIFY_IS_EQUAL(mat2(0,0), 0);
+  VERIFY_IS_EQUAL(mat2(0,1), 1);
+  VERIFY_IS_EQUAL(mat2(0,2), 2);
+  VERIFY_IS_EQUAL(mat2(1,0), 3);
+  VERIFY_IS_EQUAL(mat2(1,1), 4);
+  VERIFY_IS_EQUAL(mat2(1,2), 5);
+}
+
+static void test_3d()
+{
+  Tensor<int, 3> mat1(2,3,7);
+  Tensor<int, 3, RowMajor> mat2(2,3,7);
+
+  int val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        mat2(i,j,k) = val;
+        val++;
+      }
+    }
+  }
+
+  int col_major[2*3*7];
+  int row_major[2*3*7];
+  memset(col_major, 0, 2*3*7*sizeof(int));
+  memset(row_major, 0, 2*3*7*sizeof(int));
+  TensorMap<Tensor<int, 3> > mat3(col_major, 2, 3, 7);
+  TensorMap<Tensor<int, 3, RowMajor> > mat4(row_major, 2, 3, 7);
+
+  mat3 = mat1;
+  mat4 = mat2;
+
+  val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(mat3(i,j,k), val);
+        VERIFY_IS_EQUAL(mat4(i,j,k), val);
+        val++;
+      }
+    }
+  }
+
+  mat1.setZero();
+  mat2.setZero();
+  mat1 = mat3;
+  mat2 = mat4;
+
+  val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(mat1(i,j,k), val);
+        VERIFY_IS_EQUAL(mat2(i,j,k), val);
+        val++;
+      }
+    }
+  }
+}
+
+static void test_same_type()
+{
+  Tensor<int, 1> orig_tensor(5);
+  Tensor<int, 1> dest_tensor(5);
+  orig_tensor.setRandom();
+  dest_tensor.setRandom();
+  int* orig_data = orig_tensor.data();
+  int* dest_data = dest_tensor.data();
+  dest_tensor = orig_tensor;
+  VERIFY_IS_EQUAL(orig_tensor.data(), orig_data);
+  VERIFY_IS_EQUAL(dest_tensor.data(), dest_data);
+  for (int i = 0; i < 5; ++i) {
+    VERIFY_IS_EQUAL(dest_tensor(i), orig_tensor(i));
+  }
+
+  TensorFixedSize<int, Sizes<5> > orig_array;
+  TensorFixedSize<int, Sizes<5> > dest_array;
+  orig_array.setRandom();
+  dest_array.setRandom();
+  orig_data = orig_array.data();
+  dest_data = dest_array.data();
+  dest_array = orig_array;
+  VERIFY_IS_EQUAL(orig_array.data(), orig_data);
+  VERIFY_IS_EQUAL(dest_array.data(), dest_data);
+  for (int i = 0; i < 5; ++i) {
+    VERIFY_IS_EQUAL(dest_array(i), orig_array(i));
+  }
+
+  int orig[5] = {1, 2, 3, 4, 5};
+  int dest[5] = {6, 7, 8, 9, 10};
+  TensorMap<Tensor<int, 1> > orig_map(orig, 5);
+  TensorMap<Tensor<int, 1> > dest_map(dest, 5);
+  orig_data = orig_map.data();
+  dest_data = dest_map.data();
+  dest_map = orig_map;
+  VERIFY_IS_EQUAL(orig_map.data(), orig_data);
+  VERIFY_IS_EQUAL(dest_map.data(), dest_data);
+  for (int i = 0; i < 5; ++i) {
+    VERIFY_IS_EQUAL(dest[i], i+1);
+  }
+}
+
+static void test_auto_resize()
+{
+  Tensor<int, 1> tensor1;
+  Tensor<int, 1> tensor2(3);
+  Tensor<int, 1> tensor3(5);
+  Tensor<int, 1> tensor4(7);
+
+  Tensor<int, 1> new_tensor(5);
+  new_tensor.setRandom();
+
+  tensor1 = tensor2 = tensor3 = tensor4 = new_tensor;
+
+  VERIFY_IS_EQUAL(tensor1.dimension(0), new_tensor.dimension(0));
+  VERIFY_IS_EQUAL(tensor2.dimension(0), new_tensor.dimension(0));
+  VERIFY_IS_EQUAL(tensor3.dimension(0), new_tensor.dimension(0));
+  VERIFY_IS_EQUAL(tensor4.dimension(0), new_tensor.dimension(0));
+  for (int i = 0; i < new_tensor.dimension(0); ++i) {
+    VERIFY_IS_EQUAL(tensor1(i), new_tensor(i));
+    VERIFY_IS_EQUAL(tensor2(i), new_tensor(i));
+    VERIFY_IS_EQUAL(tensor3(i), new_tensor(i));
+    VERIFY_IS_EQUAL(tensor4(i), new_tensor(i));
+  }
+}
+
+
+static void test_compound_assign()
+{
+  Tensor<int, 1> start_tensor(10);
+  Tensor<int, 1> offset_tensor(10);
+  start_tensor.setRandom();
+  offset_tensor.setRandom();
+
+  Tensor<int, 1> tensor = start_tensor;
+  tensor += offset_tensor;
+  for (int i = 0; i < 10; ++i) {
+    VERIFY_IS_EQUAL(tensor(i), start_tensor(i) + offset_tensor(i));
+  }
+
+  tensor = start_tensor;
+  tensor -= offset_tensor;
+  for (int i = 0; i < 10; ++i) {
+    VERIFY_IS_EQUAL(tensor(i), start_tensor(i) - offset_tensor(i));
+  }
+
+  tensor = start_tensor;
+  tensor *= offset_tensor;
+  for (int i = 0; i < 10; ++i) {
+    VERIFY_IS_EQUAL(tensor(i), start_tensor(i) * offset_tensor(i));
+  }
+
+  tensor = start_tensor;
+  tensor /= offset_tensor;
+  for (int i = 0; i < 10; ++i) {
+    VERIFY_IS_EQUAL(tensor(i), start_tensor(i) / offset_tensor(i));
+  }
+}
+
+static void test_std_initializers_tensor() {
+#if EIGEN_HAS_VARIADIC_TEMPLATES
+  Tensor<int, 1> a(3);
+  a.setValues({0, 1, 2});
+  VERIFY_IS_EQUAL(a(0), 0);
+  VERIFY_IS_EQUAL(a(1), 1);
+  VERIFY_IS_EQUAL(a(2), 2);
+
+  // It fills the top-left slice.
+  a.setValues({10, 20});
+  VERIFY_IS_EQUAL(a(0), 10);
+  VERIFY_IS_EQUAL(a(1), 20);
+  VERIFY_IS_EQUAL(a(2), 2);
+
+  // Chaining.
+  Tensor<int, 1> a2(3);
+  a2 = a.setValues({100, 200, 300});
+  VERIFY_IS_EQUAL(a(0), 100);
+  VERIFY_IS_EQUAL(a(1), 200);
+  VERIFY_IS_EQUAL(a(2), 300);
+  VERIFY_IS_EQUAL(a2(0), 100);
+  VERIFY_IS_EQUAL(a2(1), 200);
+  VERIFY_IS_EQUAL(a2(2), 300);
+
+  Tensor<int, 2> b(2, 3);
+  b.setValues({{0, 1, 2}, {3, 4, 5}});
+  VERIFY_IS_EQUAL(b(0, 0), 0);
+  VERIFY_IS_EQUAL(b(0, 1), 1);
+  VERIFY_IS_EQUAL(b(0, 2), 2);
+  VERIFY_IS_EQUAL(b(1, 0), 3);
+  VERIFY_IS_EQUAL(b(1, 1), 4);
+  VERIFY_IS_EQUAL(b(1, 2), 5);
+
+  // It fills the top-left slice.
+  b.setValues({{10, 20}, {30}});
+  VERIFY_IS_EQUAL(b(0, 0), 10);
+  VERIFY_IS_EQUAL(b(0, 1), 20);
+  VERIFY_IS_EQUAL(b(0, 2), 2);
+  VERIFY_IS_EQUAL(b(1, 0), 30);
+  VERIFY_IS_EQUAL(b(1, 1), 4);
+  VERIFY_IS_EQUAL(b(1, 2), 5);
+
+  Eigen::Tensor<int, 3> c(3, 2, 4);
+  c.setValues({{{0, 1, 2, 3}, {4, 5, 6, 7}},
+               {{10, 11, 12, 13}, {14, 15, 16, 17}},
+               {{20, 21, 22, 23}, {24, 25, 26, 27}}});
+  VERIFY_IS_EQUAL(c(0, 0, 0), 0);
+  VERIFY_IS_EQUAL(c(0, 0, 1), 1);
+  VERIFY_IS_EQUAL(c(0, 0, 2), 2);
+  VERIFY_IS_EQUAL(c(0, 0, 3), 3);
+  VERIFY_IS_EQUAL(c(0, 1, 0), 4);
+  VERIFY_IS_EQUAL(c(0, 1, 1), 5);
+  VERIFY_IS_EQUAL(c(0, 1, 2), 6);
+  VERIFY_IS_EQUAL(c(0, 1, 3), 7);
+  VERIFY_IS_EQUAL(c(1, 0, 0), 10);
+  VERIFY_IS_EQUAL(c(1, 0, 1), 11);
+  VERIFY_IS_EQUAL(c(1, 0, 2), 12);
+  VERIFY_IS_EQUAL(c(1, 0, 3), 13);
+  VERIFY_IS_EQUAL(c(1, 1, 0), 14);
+  VERIFY_IS_EQUAL(c(1, 1, 1), 15);
+  VERIFY_IS_EQUAL(c(1, 1, 2), 16);
+  VERIFY_IS_EQUAL(c(1, 1, 3), 17);
+  VERIFY_IS_EQUAL(c(2, 0, 0), 20);
+  VERIFY_IS_EQUAL(c(2, 0, 1), 21);
+  VERIFY_IS_EQUAL(c(2, 0, 2), 22);
+  VERIFY_IS_EQUAL(c(2, 0, 3), 23);
+  VERIFY_IS_EQUAL(c(2, 1, 0), 24);
+  VERIFY_IS_EQUAL(c(2, 1, 1), 25);
+  VERIFY_IS_EQUAL(c(2, 1, 2), 26);
+  VERIFY_IS_EQUAL(c(2, 1, 3), 27);
+#endif  // EIGEN_HAS_VARIADIC_TEMPLATES
+}
+
+void test_cxx11_tensor_assign()
+{
+  CALL_SUBTEST(test_1d());
+  CALL_SUBTEST(test_2d());
+  CALL_SUBTEST(test_3d());
+  CALL_SUBTEST(test_same_type());
+  CALL_SUBTEST(test_auto_resize());
+  CALL_SUBTEST(test_compound_assign());
+  CALL_SUBTEST(test_std_initializers_tensor());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
@@ -0,0 +1,74 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_broadcast_sycl
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_SYCL
+
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::array;
+using Eigen::SyclDevice;
+using Eigen::Tensor;
+using Eigen::TensorMap;
+
+static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
+
+  // BROADCAST test:
+  array<int, 4> in_range   = {{2, 3, 5, 7}};
+  array<int, 4> broadcasts = {{2, 3, 1, 4}};
+  array<int, 4> out_range;  // = in_range * broadcasts
+  for (size_t i = 0; i < out_range.size(); ++i)
+    out_range[i] = in_range[i] * broadcasts[i];
+
+  Tensor<float, 4>  input(in_range);
+  Tensor<float, 4> out(out_range);
+
+  for (size_t i = 0; i < in_range.size(); ++i)
+    VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
+
+
+  for (int i = 0; i < input.size(); ++i)
+    input(i) = static_cast<float>(i);
+
+  float * gpu_in_data  = static_cast<float*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_out_data  = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
+
+  TensorMap<Tensor<float, 4>>  gpu_in(gpu_in_data, in_range);
+  TensorMap<Tensor<float, 4>> gpu_out(gpu_out_data, out_range);
+  sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(float));
+  gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+
+  for (int i = 0; i < 4; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 28; ++l) {
+          VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), out(i,j,k,l));
+        }
+      }
+    }
+  }
+  printf("Broadcast Test Passed\n");
+  sycl_device.deallocate(gpu_in_data);
+  sycl_device.deallocate(gpu_out_data);
+}
+
+void test_cxx11_tensor_broadcast_sycl() {
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_broadcast_sycl(sycl_device));
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_broadcasting.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_broadcasting.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_broadcasting.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_broadcasting.cpp
@@ -0,0 +1,194 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template <int DataLayout>
+static void test_simple_broadcasting()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  array<ptrdiff_t, 4> broadcasts;
+  broadcasts[0] = 1;
+  broadcasts[1] = 1;
+  broadcasts[2] = 1;
+  broadcasts[3] = 1;
+
+  Tensor<float, 4, DataLayout> no_broadcast;
+  no_broadcast = tensor.broadcast(broadcasts);
+
+  VERIFY_IS_EQUAL(no_broadcast.dimension(0), 2);
+  VERIFY_IS_EQUAL(no_broadcast.dimension(1), 3);
+  VERIFY_IS_EQUAL(no_broadcast.dimension(2), 5);
+  VERIFY_IS_EQUAL(no_broadcast.dimension(3), 7);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), no_broadcast(i,j,k,l));
+        }
+      }
+    }
+  }
+
+  broadcasts[0] = 2;
+  broadcasts[1] = 3;
+  broadcasts[2] = 1;
+  broadcasts[3] = 4;
+  Tensor<float, 4, DataLayout> broadcast;
+  broadcast = tensor.broadcast(broadcasts);
+
+  VERIFY_IS_EQUAL(broadcast.dimension(0), 4);
+  VERIFY_IS_EQUAL(broadcast.dimension(1), 9);
+  VERIFY_IS_EQUAL(broadcast.dimension(2), 5);
+  VERIFY_IS_EQUAL(broadcast.dimension(3), 28);
+
+  for (int i = 0; i < 4; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 28; ++l) {
+          VERIFY_IS_EQUAL(tensor(i%2,j%3,k%5,l%7), broadcast(i,j,k,l));
+        }
+      }
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_vectorized_broadcasting()
+{
+  Tensor<float, 3, DataLayout> tensor(8,3,5);
+  tensor.setRandom();
+  array<ptrdiff_t, 3> broadcasts;
+  broadcasts[0] = 2;
+  broadcasts[1] = 3;
+  broadcasts[2] = 4;
+
+  Tensor<float, 3, DataLayout> broadcast;
+  broadcast = tensor.broadcast(broadcasts);
+
+  VERIFY_IS_EQUAL(broadcast.dimension(0), 16);
+  VERIFY_IS_EQUAL(broadcast.dimension(1), 9);
+  VERIFY_IS_EQUAL(broadcast.dimension(2), 20);
+
+  for (int i = 0; i < 16; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 20; ++k) {
+        VERIFY_IS_EQUAL(tensor(i%8,j%3,k%5), broadcast(i,j,k));
+      }
+    }
+  }
+
+  tensor.resize(11,3,5);
+  tensor.setRandom();
+  broadcast = tensor.broadcast(broadcasts);
+
+  VERIFY_IS_EQUAL(broadcast.dimension(0), 22);
+  VERIFY_IS_EQUAL(broadcast.dimension(1), 9);
+  VERIFY_IS_EQUAL(broadcast.dimension(2), 20);
+
+  for (int i = 0; i < 22; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 20; ++k) {
+        VERIFY_IS_EQUAL(tensor(i%11,j%3,k%5), broadcast(i,j,k));
+      }
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_static_broadcasting()
+{
+  Tensor<float, 3, DataLayout> tensor(8,3,5);
+  tensor.setRandom();
+
+#if EIGEN_HAS_CONSTEXPR
+  Eigen::IndexList<Eigen::type2index<2>, Eigen::type2index<3>, Eigen::type2index<4>> broadcasts;
+#else
+  Eigen::array<int, 3> broadcasts;
+  broadcasts[0] = 2;
+  broadcasts[1] = 3;
+  broadcasts[2] = 4;
+#endif
+
+  Tensor<float, 3, DataLayout> broadcast;
+  broadcast = tensor.broadcast(broadcasts);
+
+  VERIFY_IS_EQUAL(broadcast.dimension(0), 16);
+  VERIFY_IS_EQUAL(broadcast.dimension(1), 9);
+  VERIFY_IS_EQUAL(broadcast.dimension(2), 20);
+
+  for (int i = 0; i < 16; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 20; ++k) {
+        VERIFY_IS_EQUAL(tensor(i%8,j%3,k%5), broadcast(i,j,k));
+      }
+    }
+  }
+
+  tensor.resize(11,3,5);
+  tensor.setRandom();
+  broadcast = tensor.broadcast(broadcasts);
+
+  VERIFY_IS_EQUAL(broadcast.dimension(0), 22);
+  VERIFY_IS_EQUAL(broadcast.dimension(1), 9);
+  VERIFY_IS_EQUAL(broadcast.dimension(2), 20);
+
+  for (int i = 0; i < 22; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 20; ++k) {
+        VERIFY_IS_EQUAL(tensor(i%11,j%3,k%5), broadcast(i,j,k));
+      }
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_fixed_size_broadcasting()
+{
+  // Need to add a [] operator to the Size class for this to work
+#if 0
+  Tensor<float, 1, DataLayout> t1(10);
+  t1.setRandom();
+  TensorFixedSize<float, Sizes<1>, DataLayout> t2;
+  t2 = t2.constant(20.0f);
+
+  Tensor<float, 1, DataLayout> t3 = t1 + t2.broadcast(Eigen::array<int, 1>{{10}});
+  for (int i = 0; i < 10; ++i) {
+    VERIFY_IS_APPROX(t3(i), t1(i) + t2(0));
+  }
+
+  TensorMap<TensorFixedSize<float, Sizes<1>, DataLayout> > t4(t2.data(), {{1}});
+  Tensor<float, 1, DataLayout> t5 = t1 + t4.broadcast(Eigen::array<int, 1>{{10}});
+  for (int i = 0; i < 10; ++i) {
+    VERIFY_IS_APPROX(t5(i), t1(i) + t2(0));
+  }
+#endif
+}
+
+
+void test_cxx11_tensor_broadcasting()
+{
+  CALL_SUBTEST(test_simple_broadcasting<ColMajor>());
+  CALL_SUBTEST(test_simple_broadcasting<RowMajor>());
+  CALL_SUBTEST(test_vectorized_broadcasting<ColMajor>());
+  CALL_SUBTEST(test_vectorized_broadcasting<RowMajor>());
+  CALL_SUBTEST(test_static_broadcasting<ColMajor>());
+  CALL_SUBTEST(test_static_broadcasting<RowMajor>());
+  CALL_SUBTEST(test_fixed_size_broadcasting<ColMajor>());
+  CALL_SUBTEST(test_fixed_size_broadcasting<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_cast_float16_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_cast_float16_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_cast_float16_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_cast_float16_cuda.cu
@@ -0,0 +1,82 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_cast_float16_cuda
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+void test_cuda_conversion() {
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int num_elem = 101;
+
+  Tensor<float, 1> floats(num_elem);
+  floats.setRandom();
+
+  float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  Eigen::half* d_half = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+  float* d_conv = (float*)gpu_device.allocate(num_elem * sizeof(float));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float(
+      d_float, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_half(
+      d_half, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_conv(
+      d_conv, num_elem);
+
+  gpu_device.memcpyHostToDevice(d_float, floats.data(), num_elem*sizeof(float));
+
+  gpu_half.device(gpu_device) = gpu_float.cast<Eigen::half>();
+  gpu_conv.device(gpu_device) = gpu_half.cast<float>();
+
+  Tensor<float, 1> initial(num_elem);
+  Tensor<float, 1> final(num_elem);
+  gpu_device.memcpyDeviceToHost(initial.data(), d_float, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(final.data(), d_conv, num_elem*sizeof(float));
+  gpu_device.synchronize();
+
+  for (int i = 0; i < num_elem; ++i) {
+    VERIFY_IS_APPROX(initial(i), final(i));
+  }
+
+  gpu_device.deallocate(d_float);
+  gpu_device.deallocate(d_half);
+  gpu_device.deallocate(d_conv);
+}
+
+
+void test_fallback_conversion() {
+  int num_elem = 101;
+  Tensor<float, 1> floats(num_elem);
+  floats.setRandom();
+
+  Eigen::Tensor<Eigen::half, 1> halfs = floats.cast<Eigen::half>();
+  Eigen::Tensor<float, 1> conv = halfs.cast<float>();
+
+  for (int i = 0; i < num_elem; ++i) {
+    VERIFY_IS_APPROX(floats(i), conv(i));
+  }
+}
+
+
+void test_cxx11_tensor_cast_float16_cuda()
+{
+  CALL_SUBTEST(test_cuda_conversion());
+  CALL_SUBTEST(test_fallback_conversion());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_casts.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_casts.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_casts.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_casts.cpp
@@ -0,0 +1,115 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::array;
+
+static void test_simple_cast()
+{
+  Tensor<float, 2> ftensor(20,30);
+  ftensor = ftensor.random() * 100.f;
+  Tensor<char, 2> chartensor(20,30);
+  chartensor.setRandom();
+  Tensor<std::complex<float>, 2> cplextensor(20,30);
+  cplextensor.setRandom();
+
+  chartensor = ftensor.cast<char>();
+  cplextensor = ftensor.cast<std::complex<float> >();
+
+  for (int i = 0; i < 20; ++i) {
+    for (int j = 0; j < 30; ++j) {
+      VERIFY_IS_EQUAL(chartensor(i,j), static_cast<char>(ftensor(i,j)));
+      VERIFY_IS_EQUAL(cplextensor(i,j), static_cast<std::complex<float> >(ftensor(i,j)));
+    }
+  }
+}
+
+
+static void test_vectorized_cast()
+{
+  Tensor<int, 2> itensor(20,30);
+  itensor = itensor.random() / 1000;
+  Tensor<float, 2> ftensor(20,30);
+  ftensor.setRandom();
+  Tensor<double, 2> dtensor(20,30);
+  dtensor.setRandom();
+
+  ftensor = itensor.cast<float>();
+  dtensor = itensor.cast<double>();
+
+  for (int i = 0; i < 20; ++i) {
+    for (int j = 0; j < 30; ++j) {
+      VERIFY_IS_EQUAL(itensor(i,j), static_cast<int>(ftensor(i,j)));
+      VERIFY_IS_EQUAL(dtensor(i,j), static_cast<double>(ftensor(i,j)));
+    }
+  }
+}
+
+
+static void test_float_to_int_cast()
+{
+  Tensor<float, 2> ftensor(20,30);
+  ftensor = ftensor.random() * 1000.0f;
+  Tensor<double, 2> dtensor(20,30);
+  dtensor = dtensor.random() * 1000.0;
+
+  Tensor<int, 2> i1tensor = ftensor.cast<int>();
+  Tensor<int, 2> i2tensor = dtensor.cast<int>();
+
+  for (int i = 0; i < 20; ++i) {
+    for (int j = 0; j < 30; ++j) {
+      VERIFY_IS_EQUAL(i1tensor(i,j), static_cast<int>(ftensor(i,j)));
+      VERIFY_IS_EQUAL(i2tensor(i,j), static_cast<int>(dtensor(i,j)));
+    }
+  }
+}
+
+
+static void test_big_to_small_type_cast()
+{
+  Tensor<double, 2> dtensor(20, 30);
+  dtensor.setRandom();
+  Tensor<float, 2> ftensor(20, 30);
+  ftensor = dtensor.cast<float>();
+
+  for (int i = 0; i < 20; ++i) {
+    for (int j = 0; j < 30; ++j) {
+      VERIFY_IS_APPROX(dtensor(i,j), static_cast<double>(ftensor(i,j)));
+    }
+  }
+}
+
+
+static void test_small_to_big_type_cast()
+{
+  Tensor<float, 2> ftensor(20, 30);
+  ftensor.setRandom();
+  Tensor<double, 2> dtensor(20, 30);
+  dtensor = ftensor.cast<double>();
+
+  for (int i = 0; i < 20; ++i) {
+    for (int j = 0; j < 30; ++j) {
+      VERIFY_IS_APPROX(dtensor(i,j), static_cast<double>(ftensor(i,j)));
+    }
+  }
+}
+
+
+void test_cxx11_tensor_casts()
+{
+   CALL_SUBTEST(test_simple_cast());
+   CALL_SUBTEST(test_vectorized_cast());
+   CALL_SUBTEST(test_float_to_int_cast());
+   CALL_SUBTEST(test_big_to_small_type_cast());
+   CALL_SUBTEST(test_small_to_big_type_cast());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_chipping.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_chipping.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_chipping.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_chipping.cpp
@@ -0,0 +1,425 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<int DataLayout>
+static void test_simple_chip()
+{
+  Tensor<float, 5, DataLayout> tensor(2,3,5,7,11);
+  tensor.setRandom();
+
+  Tensor<float, 4, DataLayout> chip1;
+  chip1 = tensor.template chip<0>(1);
+
+  VERIFY_IS_EQUAL(chip1.dimension(0), 3);
+  VERIFY_IS_EQUAL(chip1.dimension(1), 5);
+  VERIFY_IS_EQUAL(chip1.dimension(2), 7);
+  VERIFY_IS_EQUAL(chip1.dimension(3), 11);
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        for (int l = 0; l < 11; ++l) {
+          VERIFY_IS_EQUAL(chip1(i,j,k,l), tensor(1,i,j,k,l));
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> chip2 = tensor.template chip<1>(1);
+  VERIFY_IS_EQUAL(chip2.dimension(0), 2);
+  VERIFY_IS_EQUAL(chip2.dimension(1), 5);
+  VERIFY_IS_EQUAL(chip2.dimension(2), 7);
+  VERIFY_IS_EQUAL(chip2.dimension(3), 11);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        for (int l = 0; l < 11; ++l) {
+          VERIFY_IS_EQUAL(chip2(i,j,k,l), tensor(i,1,j,k,l));
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> chip3 = tensor.template chip<2>(2);
+  VERIFY_IS_EQUAL(chip3.dimension(0), 2);
+  VERIFY_IS_EQUAL(chip3.dimension(1), 3);
+  VERIFY_IS_EQUAL(chip3.dimension(2), 7);
+  VERIFY_IS_EQUAL(chip3.dimension(3), 11);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        for (int l = 0; l < 11; ++l) {
+          VERIFY_IS_EQUAL(chip3(i,j,k,l), tensor(i,j,2,k,l));
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> chip4(tensor.template chip<3>(5));
+  VERIFY_IS_EQUAL(chip4.dimension(0), 2);
+  VERIFY_IS_EQUAL(chip4.dimension(1), 3);
+  VERIFY_IS_EQUAL(chip4.dimension(2), 5);
+  VERIFY_IS_EQUAL(chip4.dimension(3), 11);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(chip4(i,j,k,l), tensor(i,j,k,5,l));
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> chip5(tensor.template chip<4>(7));
+  VERIFY_IS_EQUAL(chip5.dimension(0), 2);
+  VERIFY_IS_EQUAL(chip5.dimension(1), 3);
+  VERIFY_IS_EQUAL(chip5.dimension(2), 5);
+  VERIFY_IS_EQUAL(chip5.dimension(3), 7);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(chip5(i,j,k,l), tensor(i,j,k,l,7));
+        }
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+static void test_dynamic_chip()
+{
+  Tensor<float, 5, DataLayout> tensor(2,3,5,7,11);
+  tensor.setRandom();
+
+  Tensor<float, 4, DataLayout> chip1;
+  chip1 = tensor.chip(1, 0);
+  VERIFY_IS_EQUAL(chip1.dimension(0), 3);
+  VERIFY_IS_EQUAL(chip1.dimension(1), 5);
+  VERIFY_IS_EQUAL(chip1.dimension(2), 7);
+  VERIFY_IS_EQUAL(chip1.dimension(3), 11);
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        for (int l = 0; l < 11; ++l) {
+          VERIFY_IS_EQUAL(chip1(i,j,k,l), tensor(1,i,j,k,l));
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> chip2 = tensor.chip(1, 1);
+  VERIFY_IS_EQUAL(chip2.dimension(0), 2);
+  VERIFY_IS_EQUAL(chip2.dimension(1), 5);
+  VERIFY_IS_EQUAL(chip2.dimension(2), 7);
+  VERIFY_IS_EQUAL(chip2.dimension(3), 11);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        for (int l = 0; l < 11; ++l) {
+          VERIFY_IS_EQUAL(chip2(i,j,k,l), tensor(i,1,j,k,l));
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> chip3 = tensor.chip(2, 2);
+  VERIFY_IS_EQUAL(chip3.dimension(0), 2);
+  VERIFY_IS_EQUAL(chip3.dimension(1), 3);
+  VERIFY_IS_EQUAL(chip3.dimension(2), 7);
+  VERIFY_IS_EQUAL(chip3.dimension(3), 11);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        for (int l = 0; l < 11; ++l) {
+          VERIFY_IS_EQUAL(chip3(i,j,k,l), tensor(i,j,2,k,l));
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> chip4(tensor.chip(5, 3));
+  VERIFY_IS_EQUAL(chip4.dimension(0), 2);
+  VERIFY_IS_EQUAL(chip4.dimension(1), 3);
+  VERIFY_IS_EQUAL(chip4.dimension(2), 5);
+  VERIFY_IS_EQUAL(chip4.dimension(3), 11);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(chip4(i,j,k,l), tensor(i,j,k,5,l));
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> chip5(tensor.chip(7, 4));
+  VERIFY_IS_EQUAL(chip5.dimension(0), 2);
+  VERIFY_IS_EQUAL(chip5.dimension(1), 3);
+  VERIFY_IS_EQUAL(chip5.dimension(2), 5);
+  VERIFY_IS_EQUAL(chip5.dimension(3), 7);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(chip5(i,j,k,l), tensor(i,j,k,l,7));
+        }
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+static void test_chip_in_expr() {
+  Tensor<float, 5, DataLayout> input1(2,3,5,7,11);
+  input1.setRandom();
+  Tensor<float, 4, DataLayout> input2(3,5,7,11);
+  input2.setRandom();
+
+  Tensor<float, 4, DataLayout> result = input1.template chip<0>(0) + input2;
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        for (int l = 0; l < 11; ++l) {
+          float expected = input1(0,i,j,k,l) + input2(i,j,k,l);
+          VERIFY_IS_EQUAL(result(i,j,k,l), expected);
+        }
+      }
+    }
+  }
+
+  Tensor<float, 3, DataLayout> input3(3,7,11);
+  input3.setRandom();
+  Tensor<float, 3, DataLayout> result2 = input1.template chip<0>(0).template chip<1>(2) + input3;
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 7; ++j) {
+      for (int k = 0; k < 11; ++k) {
+        float expected = input1(0,i,2,j,k) + input3(i,j,k);
+        VERIFY_IS_EQUAL(result2(i,j,k), expected);
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+static void test_chip_as_lvalue()
+{
+  Tensor<float, 5, DataLayout> input1(2,3,5,7,11);
+  input1.setRandom();
+
+  Tensor<float, 4, DataLayout> input2(3,5,7,11);
+  input2.setRandom();
+  Tensor<float, 5, DataLayout> tensor = input1;
+  tensor.template chip<0>(1) = input2;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          for (int m = 0; m < 11; ++m) {
+            if (i != 1) {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m));
+            } else {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input2(j,k,l,m));
+            }
+          }
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> input3(2,5,7,11);
+  input3.setRandom();
+  tensor = input1;
+  tensor.template chip<1>(1) = input3;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          for (int m = 0; m < 11; ++m) {
+            if (j != 1) {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m));
+            } else {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input3(i,k,l,m));
+            }
+          }
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> input4(2,3,7,11);
+  input4.setRandom();
+  tensor = input1;
+  tensor.template chip<2>(3) = input4;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          for (int m = 0; m < 11; ++m) {
+            if (k != 3) {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m));
+            } else {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input4(i,j,l,m));
+            }
+          }
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> input5(2,3,5,11);
+  input5.setRandom();
+  tensor = input1;
+  tensor.template chip<3>(4) = input5;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          for (int m = 0; m < 11; ++m) {
+            if (l != 4) {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m));
+            } else {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input5(i,j,k,m));
+            }
+          }
+        }
+      }
+    }
+  }
+
+  Tensor<float, 4, DataLayout> input6(2,3,5,7);
+  input6.setRandom();
+  tensor = input1;
+  tensor.template chip<4>(5) = input6;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          for (int m = 0; m < 11; ++m) {
+            if (m != 5) {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m));
+            } else {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input6(i,j,k,l));
+            }
+          }
+        }
+      }
+    }
+  }
+
+  Tensor<float, 5, DataLayout> input7(2,3,5,7,11);
+  input7.setRandom();
+  tensor = input1;
+  tensor.chip(0, 0) = input7.chip(0, 0);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          for (int m = 0; m < 11; ++m) {
+            if (i != 0) {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m));
+            } else {
+              VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input7(i,j,k,l,m));
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+static void test_chip_raw_data_col_major()
+{
+  Tensor<float, 5, ColMajor> tensor(2,3,5,7,11);
+  tensor.setRandom();
+
+  typedef TensorEvaluator<decltype(tensor.chip<4>(3)), DefaultDevice> Evaluator4;
+  auto chip = Evaluator4(tensor.chip<4>(3), DefaultDevice());
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          int chip_index = i + 2 * (j + 3 * (k + 5 * l));
+          VERIFY_IS_EQUAL(chip.data()[chip_index], tensor(i,j,k,l,3));
+        }
+      }
+    }
+  }
+
+  typedef TensorEvaluator<decltype(tensor.chip<0>(0)), DefaultDevice> Evaluator0;
+  auto chip0 = Evaluator0(tensor.chip<0>(0), DefaultDevice());
+  VERIFY_IS_EQUAL(chip0.data(), static_cast<float*>(0));
+
+  typedef TensorEvaluator<decltype(tensor.chip<1>(0)), DefaultDevice> Evaluator1;
+  auto chip1 = Evaluator1(tensor.chip<1>(0), DefaultDevice());
+  VERIFY_IS_EQUAL(chip1.data(), static_cast<float*>(0));
+
+  typedef TensorEvaluator<decltype(tensor.chip<2>(0)), DefaultDevice> Evaluator2;
+  auto chip2 = Evaluator2(tensor.chip<2>(0), DefaultDevice());
+  VERIFY_IS_EQUAL(chip2.data(), static_cast<float*>(0));
+
+  typedef TensorEvaluator<decltype(tensor.chip<3>(0)), DefaultDevice> Evaluator3;
+  auto chip3 = Evaluator3(tensor.chip<3>(0), DefaultDevice());
+  VERIFY_IS_EQUAL(chip3.data(), static_cast<float*>(0));
+}
+
+static void test_chip_raw_data_row_major()
+{
+  Tensor<float, 5, RowMajor> tensor(11,7,5,3,2);
+  tensor.setRandom();
+
+  typedef TensorEvaluator<decltype(tensor.chip<0>(3)), DefaultDevice> Evaluator0;
+  auto chip = Evaluator0(tensor.chip<0>(3), DefaultDevice());
+  for (int i = 0; i < 7; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 2; ++l) {
+          int chip_index = l + 2 * (k + 3 * (j + 5 * i));
+          VERIFY_IS_EQUAL(chip.data()[chip_index], tensor(3,i,j,k,l));
+        }
+      }
+    }
+  }
+
+  typedef TensorEvaluator<decltype(tensor.chip<1>(0)), DefaultDevice> Evaluator1;
+  auto chip1 = Evaluator1(tensor.chip<1>(0), DefaultDevice());
+  VERIFY_IS_EQUAL(chip1.data(), static_cast<float*>(0));
+
+  typedef TensorEvaluator<decltype(tensor.chip<2>(0)), DefaultDevice> Evaluator2;
+  auto chip2 = Evaluator2(tensor.chip<2>(0), DefaultDevice());
+  VERIFY_IS_EQUAL(chip2.data(), static_cast<float*>(0));
+
+  typedef TensorEvaluator<decltype(tensor.chip<3>(0)), DefaultDevice> Evaluator3;
+  auto chip3 = Evaluator3(tensor.chip<3>(0), DefaultDevice());
+  VERIFY_IS_EQUAL(chip3.data(), static_cast<float*>(0));
+
+  typedef TensorEvaluator<decltype(tensor.chip<4>(0)), DefaultDevice> Evaluator4;
+  auto chip4 = Evaluator4(tensor.chip<4>(0), DefaultDevice());
+  VERIFY_IS_EQUAL(chip4.data(), static_cast<float*>(0));
+}
+
+void test_cxx11_tensor_chipping()
+{
+  CALL_SUBTEST(test_simple_chip<ColMajor>());
+  CALL_SUBTEST(test_simple_chip<RowMajor>());
+  CALL_SUBTEST(test_dynamic_chip<ColMajor>());
+  CALL_SUBTEST(test_dynamic_chip<RowMajor>());
+  CALL_SUBTEST(test_chip_in_expr<ColMajor>());
+  CALL_SUBTEST(test_chip_in_expr<RowMajor>());
+  CALL_SUBTEST(test_chip_as_lvalue<ColMajor>());
+  CALL_SUBTEST(test_chip_as_lvalue<RowMajor>());
+  CALL_SUBTEST(test_chip_raw_data_col_major());
+  CALL_SUBTEST(test_chip_raw_data_row_major());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_comparisons.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_comparisons.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_comparisons.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_comparisons.cpp
@@ -0,0 +1,84 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_orderings()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<bool, 3> lt(2,3,7);
+  Tensor<bool, 3> le(2,3,7);
+  Tensor<bool, 3> gt(2,3,7);
+  Tensor<bool, 3> ge(2,3,7);
+
+  mat1.setRandom();
+  mat2.setRandom();
+
+  lt = mat1 < mat2;
+  le = mat1 <= mat2;
+  gt = mat1 > mat2;
+  ge = mat1 >= mat2;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(lt(i,j,k), mat1(i,j,k) < mat2(i,j,k));
+        VERIFY_IS_EQUAL(le(i,j,k), mat1(i,j,k) <= mat2(i,j,k));
+        VERIFY_IS_EQUAL(gt(i,j,k), mat1(i,j,k) > mat2(i,j,k));
+        VERIFY_IS_EQUAL(ge(i,j,k), mat1(i,j,k) >= mat2(i,j,k));
+      }
+    }
+  }
+}
+
+
+static void test_equality()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+
+  mat1.setRandom();
+  mat2.setRandom();
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        if (internal::random<bool>()) {
+          mat2(i,j,k) = mat1(i,j,k);
+        }
+      }
+    }
+  }
+
+  Tensor<bool, 3> eq(2,3,7);
+  Tensor<bool, 3> ne(2,3,7);
+  eq = (mat1 == mat2);
+  ne = (mat1 != mat2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(eq(i,j,k), mat1(i,j,k) == mat2(i,j,k));
+        VERIFY_IS_EQUAL(ne(i,j,k), mat1(i,j,k) != mat2(i,j,k));
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_comparisons()
+{
+  CALL_SUBTEST(test_orderings());
+  CALL_SUBTEST(test_equality());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_complex_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_complex_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_complex_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_complex_cuda.cu
@@ -0,0 +1,153 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_FUNC cxx11_tensor_complex
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+void test_cuda_nullary() {
+  Tensor<std::complex<float>, 1, 0, int> in1(2);
+  Tensor<std::complex<float>, 1, 0, int> in2(2);
+  in1.setRandom();
+  in2.setRandom();
+
+  std::size_t float_bytes = in1.size() * sizeof(float);
+  std::size_t complex_bytes = in1.size() * sizeof(std::complex<float>);
+
+  std::complex<float>* d_in1;
+  std::complex<float>* d_in2;
+  float* d_out2;
+  cudaMalloc((void**)(&d_in1), complex_bytes);
+  cudaMalloc((void**)(&d_in2), complex_bytes);
+  cudaMalloc((void**)(&d_out2), float_bytes);
+  cudaMemcpy(d_in1, in1.data(), complex_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in2, in2.data(), complex_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in1(
+      d_in1, 2);
+  Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in2(
+      d_in2, 2);
+  Eigen::TensorMap<Eigen::Tensor<float, 1, 0, int>, Eigen::Aligned> gpu_out2(
+      d_out2, 2);
+
+  gpu_in1.device(gpu_device) = gpu_in1.constant(std::complex<float>(3.14f, 2.7f));
+  gpu_out2.device(gpu_device) = gpu_in2.abs();
+
+  Tensor<std::complex<float>, 1, 0, int> new1(2);
+  Tensor<float, 1, 0, int> new2(2);
+
+  assert(cudaMemcpyAsync(new1.data(), d_in1, complex_bytes, cudaMemcpyDeviceToHost,
+                         gpu_device.stream()) == cudaSuccess);
+  assert(cudaMemcpyAsync(new2.data(), d_out2, float_bytes, cudaMemcpyDeviceToHost,
+                         gpu_device.stream()) == cudaSuccess);
+
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 2; ++i) {
+    VERIFY_IS_APPROX(new1(i), std::complex<float>(3.14f, 2.7f));
+    VERIFY_IS_APPROX(new2(i), std::abs(in2(i)));
+  }
+
+  cudaFree(d_in1);
+  cudaFree(d_in2);
+  cudaFree(d_out2);
+}
+
+
+static void test_cuda_sum_reductions() {
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  const int num_rows = internal::random<int>(1024, 5*1024);
+  const int num_cols = internal::random<int>(1024, 5*1024);
+
+  Tensor<std::complex<float>, 2> in(num_rows, num_cols);
+  in.setRandom();
+
+  Tensor<std::complex<float>, 0> full_redux;
+  full_redux = in.sum();
+
+  std::size_t in_bytes = in.size() * sizeof(std::complex<float>);
+  std::size_t out_bytes = full_redux.size() * sizeof(std::complex<float>);
+  std::complex<float>* gpu_in_ptr = static_cast<std::complex<float>*>(gpu_device.allocate(in_bytes));
+  std::complex<float>* gpu_out_ptr = static_cast<std::complex<float>*>(gpu_device.allocate(out_bytes));
+  gpu_device.memcpyHostToDevice(gpu_in_ptr, in.data(), in_bytes);
+
+  TensorMap<Tensor<std::complex<float>, 2> > in_gpu(gpu_in_ptr, num_rows, num_cols);
+  TensorMap<Tensor<std::complex<float>, 0> > out_gpu(gpu_out_ptr);
+
+  out_gpu.device(gpu_device) = in_gpu.sum();
+
+  Tensor<std::complex<float>, 0> full_redux_gpu;
+  gpu_device.memcpyDeviceToHost(full_redux_gpu.data(), gpu_out_ptr, out_bytes);
+  gpu_device.synchronize();
+
+  // Check that the CPU and GPU reductions return the same result.
+  VERIFY_IS_APPROX(full_redux(), full_redux_gpu());
+
+  gpu_device.deallocate(gpu_in_ptr);
+  gpu_device.deallocate(gpu_out_ptr);
+}
+
+
+static void test_cuda_product_reductions() {
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  const int num_rows = internal::random<int>(1024, 5*1024);
+  const int num_cols = internal::random<int>(1024, 5*1024);
+
+  Tensor<std::complex<float>, 2> in(num_rows, num_cols);
+  in.setRandom();
+
+  Tensor<std::complex<float>, 0> full_redux;
+  full_redux = in.prod();
+
+  std::size_t in_bytes = in.size() * sizeof(std::complex<float>);
+  std::size_t out_bytes = full_redux.size() * sizeof(std::complex<float>);
+  std::complex<float>* gpu_in_ptr = static_cast<std::complex<float>*>(gpu_device.allocate(in_bytes));
+  std::complex<float>* gpu_out_ptr = static_cast<std::complex<float>*>(gpu_device.allocate(out_bytes));
+  gpu_device.memcpyHostToDevice(gpu_in_ptr, in.data(), in_bytes);
+
+  TensorMap<Tensor<std::complex<float>, 2> > in_gpu(gpu_in_ptr, num_rows, num_cols);
+  TensorMap<Tensor<std::complex<float>, 0> > out_gpu(gpu_out_ptr);
+
+  out_gpu.device(gpu_device) = in_gpu.prod();
+
+  Tensor<std::complex<float>, 0> full_redux_gpu;
+  gpu_device.memcpyDeviceToHost(full_redux_gpu.data(), gpu_out_ptr, out_bytes);
+  gpu_device.synchronize();
+
+  // Check that the CPU and GPU reductions return the same result.
+  VERIFY_IS_APPROX(full_redux(), full_redux_gpu());
+
+  gpu_device.deallocate(gpu_in_ptr);
+  gpu_device.deallocate(gpu_out_ptr);
+}
+
+
+void test_cxx11_tensor_complex()
+{
+  CALL_SUBTEST(test_cuda_nullary());
+  CALL_SUBTEST(test_cuda_sum_reductions());
+  CALL_SUBTEST(test_cuda_product_reductions());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_complex_cwise_ops_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_complex_cwise_ops_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_complex_cwise_ops_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_complex_cwise_ops_cuda.cu
@@ -0,0 +1,97 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_FUNC cxx11_tensor_complex_cwise_ops
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<typename T>
+void test_cuda_complex_cwise_ops() {
+  const int kNumItems = 2;
+  std::size_t complex_bytes = kNumItems * sizeof(std::complex<T>);
+
+  std::complex<T>* d_in1;
+  std::complex<T>* d_in2;
+  std::complex<T>* d_out;
+  cudaMalloc((void**)(&d_in1), complex_bytes);
+  cudaMalloc((void**)(&d_in2), complex_bytes);
+  cudaMalloc((void**)(&d_out), complex_bytes);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<std::complex<T>, 1, 0, int>, Eigen::Aligned> gpu_in1(
+      d_in1, kNumItems);
+  Eigen::TensorMap<Eigen::Tensor<std::complex<T>, 1, 0, int>, Eigen::Aligned> gpu_in2(
+      d_in2, kNumItems);
+  Eigen::TensorMap<Eigen::Tensor<std::complex<T>, 1, 0, int>, Eigen::Aligned> gpu_out(
+      d_out, kNumItems);
+
+  const std::complex<T> a(3.14f, 2.7f);
+  const std::complex<T> b(-10.6f, 1.4f);
+
+  gpu_in1.device(gpu_device) = gpu_in1.constant(a);
+  gpu_in2.device(gpu_device) = gpu_in2.constant(b);
+
+  enum CwiseOp {
+    Add = 0,
+    Sub,
+    Mul,
+    Div
+  };
+
+  Tensor<std::complex<T>, 1, 0, int> actual(kNumItems);
+  for (int op = Add; op <= Div; op++) {
+    std::complex<T> expected;
+    switch (static_cast<CwiseOp>(op)) {
+      case Add:
+        gpu_out.device(gpu_device) = gpu_in1 + gpu_in2;
+        expected = a + b;
+        break;
+      case Sub:
+        gpu_out.device(gpu_device) = gpu_in1 - gpu_in2;
+        expected = a - b;
+        break;
+      case Mul:
+        gpu_out.device(gpu_device) = gpu_in1 * gpu_in2;
+        expected = a * b;
+        break;
+      case Div:
+        gpu_out.device(gpu_device) = gpu_in1 / gpu_in2;
+        expected = a / b;
+        break;
+    }
+    assert(cudaMemcpyAsync(actual.data(), d_out, complex_bytes, cudaMemcpyDeviceToHost,
+                           gpu_device.stream()) == cudaSuccess);
+    assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+    for (int i = 0; i < kNumItems; ++i) {
+      VERIFY_IS_APPROX(actual(i), expected);
+    }
+  }
+
+  cudaFree(d_in1);
+  cudaFree(d_in2);
+  cudaFree(d_out);
+}
+
+
+void test_cxx11_tensor_complex_cwise_ops()
+{
+  CALL_SUBTEST(test_cuda_complex_cwise_ops<float>());
+  CALL_SUBTEST(test_cuda_complex_cwise_ops<double>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_concatenation.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_concatenation.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_concatenation.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_concatenation.cpp
@@ -0,0 +1,137 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<int DataLayout>
+static void test_dimension_failures()
+{
+  Tensor<int, 3, DataLayout> left(2, 3, 1);
+  Tensor<int, 3, DataLayout> right(3, 3, 1);
+  left.setRandom();
+  right.setRandom();
+
+  // Okay; other dimensions are equal.
+  Tensor<int, 3, DataLayout> concatenation = left.concatenate(right, 0);
+
+  // Dimension mismatches.
+  VERIFY_RAISES_ASSERT(concatenation = left.concatenate(right, 1));
+  VERIFY_RAISES_ASSERT(concatenation = left.concatenate(right, 2));
+
+  // Axis > NumDims or < 0.
+  VERIFY_RAISES_ASSERT(concatenation = left.concatenate(right, 3));
+  VERIFY_RAISES_ASSERT(concatenation = left.concatenate(right, -1));
+}
+
+template<int DataLayout>
+static void test_static_dimension_failure()
+{
+  Tensor<int, 2, DataLayout> left(2, 3);
+  Tensor<int, 3, DataLayout> right(2, 3, 1);
+
+#ifdef CXX11_TENSOR_CONCATENATION_STATIC_DIMENSION_FAILURE
+  // Technically compatible, but we static assert that the inputs have same
+  // NumDims.
+  Tensor<int, 3, DataLayout> concatenation = left.concatenate(right, 0);
+#endif
+
+  // This can be worked around in this case.
+  Tensor<int, 3, DataLayout> concatenation = left
+      .reshape(Tensor<int, 3>::Dimensions(2, 3, 1))
+      .concatenate(right, 0);
+  Tensor<int, 2, DataLayout> alternative = left
+      .concatenate(right.reshape(Tensor<int, 2>::Dimensions{{{2, 3}}}), 0);
+}
+
+template<int DataLayout>
+static void test_simple_concatenation()
+{
+  Tensor<int, 3, DataLayout> left(2, 3, 1);
+  Tensor<int, 3, DataLayout> right(2, 3, 1);
+  left.setRandom();
+  right.setRandom();
+
+  Tensor<int, 3, DataLayout> concatenation = left.concatenate(right, 0);
+  VERIFY_IS_EQUAL(concatenation.dimension(0), 4);
+  VERIFY_IS_EQUAL(concatenation.dimension(1), 3);
+  VERIFY_IS_EQUAL(concatenation.dimension(2), 1);
+  for (int j = 0; j < 3; ++j) {
+    for (int i = 0; i < 2; ++i) {
+      VERIFY_IS_EQUAL(concatenation(i, j, 0), left(i, j, 0));
+    }
+    for (int i = 2; i < 4; ++i) {
+      VERIFY_IS_EQUAL(concatenation(i, j, 0), right(i - 2, j, 0));
+    }
+  }
+
+  concatenation = left.concatenate(right, 1);
+  VERIFY_IS_EQUAL(concatenation.dimension(0), 2);
+  VERIFY_IS_EQUAL(concatenation.dimension(1), 6);
+  VERIFY_IS_EQUAL(concatenation.dimension(2), 1);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_EQUAL(concatenation(i, j, 0), left(i, j, 0));
+    }
+    for (int j = 3; j < 6; ++j) {
+      VERIFY_IS_EQUAL(concatenation(i, j, 0), right(i, j - 3, 0));
+    }
+  }
+
+  concatenation = left.concatenate(right, 2);
+  VERIFY_IS_EQUAL(concatenation.dimension(0), 2);
+  VERIFY_IS_EQUAL(concatenation.dimension(1), 3);
+  VERIFY_IS_EQUAL(concatenation.dimension(2), 2);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_EQUAL(concatenation(i, j, 0), left(i, j, 0));
+      VERIFY_IS_EQUAL(concatenation(i, j, 1), right(i, j, 0));
+    }
+  }
+}
+
+
+// TODO(phli): Add test once we have a real vectorized implementation.
+// static void test_vectorized_concatenation() {}
+
+static void test_concatenation_as_lvalue()
+{
+  Tensor<int, 2> t1(2, 3);
+  Tensor<int, 2> t2(2, 3);
+  t1.setRandom();
+  t2.setRandom();
+
+  Tensor<int, 2> result(4, 3);
+  result.setRandom();
+  t1.concatenate(t2, 0) = result;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_EQUAL(t1(i, j), result(i, j));
+      VERIFY_IS_EQUAL(t2(i, j), result(i+2, j));
+    }
+  }
+}
+
+
+void test_cxx11_tensor_concatenation()
+{
+   CALL_SUBTEST(test_dimension_failures<ColMajor>());
+   CALL_SUBTEST(test_dimension_failures<RowMajor>());
+   CALL_SUBTEST(test_static_dimension_failure<ColMajor>());
+   CALL_SUBTEST(test_static_dimension_failure<RowMajor>());
+   CALL_SUBTEST(test_simple_concatenation<ColMajor>());
+   CALL_SUBTEST(test_simple_concatenation<RowMajor>());
+   // CALL_SUBTEST(test_vectorized_concatenation());
+   CALL_SUBTEST(test_concatenation_as_lvalue());
+
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_const.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_const.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_const.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_const.cpp
@@ -0,0 +1,62 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+using Eigen::Tensor;
+
+
+static void test_simple_assign()
+{
+  Tensor<int, 3> random(2,3,7);
+  random.setRandom();
+
+  TensorMap<Tensor<const int, 3> > constant(random.data(), 2, 3, 7);
+  Tensor<int, 3> result(2,3,7);
+  result = constant;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL((result(i,j,k)), random(i,j,k));
+      }
+    }
+  }
+}
+
+
+static void test_assign_of_const_tensor()
+{
+  Tensor<int, 3> random(2,3,7);
+  random.setRandom();
+
+  TensorMap<Tensor<const int, 3> > constant1(random.data(), 2, 3, 7);
+  TensorMap<const Tensor<int, 3> > constant2(random.data(), 2, 3, 7);
+  const TensorMap<Tensor<int, 3> > constant3(random.data(), 2, 3, 7);
+
+  Tensor<int, 2> result1 = constant1.chip(0, 2);
+  Tensor<int, 2> result2 = constant2.chip(0, 2);
+  Tensor<int, 2> result3 = constant3.chip(0, 2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_EQUAL((result1(i,j)), random(i,j,0));
+      VERIFY_IS_EQUAL((result2(i,j)), random(i,j,0));
+      VERIFY_IS_EQUAL((result3(i,j)), random(i,j,0));
+    }
+  }
+}
+
+
+void test_cxx11_tensor_const()
+{
+  CALL_SUBTEST(test_simple_assign());
+  CALL_SUBTEST(test_assign_of_const_tensor());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_contract_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_contract_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_contract_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_contract_cuda.cu
@@ -0,0 +1,216 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+// Copyright (C) 2014 Navdeep Jaitly <ndjaitly@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_cuda
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+typedef Tensor<float, 1>::DimensionPair DimPair;
+
+template<int DataLayout>
+void test_cuda_contraction(int m_size, int k_size, int n_size)
+{
+  std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl;
+  // with these dimensions, the output has 300 * 140 elements, which is
+  // more than 30 * 1024, which is the number of threads in blocks on
+  // a 15 SM GK110 GPU
+  Tensor<float, 2, DataLayout> t_left(m_size, k_size);
+  Tensor<float, 2, DataLayout> t_right(k_size, n_size);
+  Tensor<float, 2, DataLayout> t_result(m_size, n_size);
+  Tensor<float, 2, DataLayout> t_result_gpu(m_size, n_size);
+  Eigen::array<DimPair, 1> dims(DimPair(1, 0));
+
+  t_left.setRandom();
+  t_right.setRandom();
+
+  std::size_t t_left_bytes = t_left.size()  * sizeof(float);
+  std::size_t t_right_bytes = t_right.size() * sizeof(float);
+  std::size_t t_result_bytes = t_result.size() * sizeof(float);
+
+  float* d_t_left;
+  float* d_t_right;
+  float* d_t_result;
+
+  cudaMalloc((void**)(&d_t_left), t_left_bytes);
+  cudaMalloc((void**)(&d_t_right), t_right_bytes);
+  cudaMalloc((void**)(&d_t_result), t_result_bytes);
+
+  cudaMemcpy(d_t_left, t_left.data(), t_left_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_t_right, t_right.data(), t_right_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 2, DataLayout> >
+      gpu_t_left(d_t_left, Eigen::array<int, 2>(m_size, k_size));
+  Eigen::TensorMap<Eigen::Tensor<float, 2, DataLayout> >
+      gpu_t_right(d_t_right, Eigen::array<int, 2>(k_size, n_size));
+  Eigen::TensorMap<Eigen::Tensor<float, 2, DataLayout> >
+      gpu_t_result(d_t_result, Eigen::array<int, 2>(m_size, n_size));
+
+
+  gpu_t_result.device(gpu_device) = gpu_t_left.contract(gpu_t_right, dims);
+  t_result = t_left.contract(t_right, dims);
+
+  cudaMemcpy(t_result_gpu.data(), d_t_result, t_result_bytes, cudaMemcpyDeviceToHost);
+  for (DenseIndex i = 0; i < t_result.size(); i++) {
+    if (fabs(t_result(i) - t_result_gpu(i)) < 1e-4f) {
+      continue;
+    }
+    if (Eigen::internal::isApprox(t_result(i), t_result_gpu(i), 1e-4f)) {
+      continue;
+    }
+    std::cout << "mismatch detected at index " << i << ": " << t_result(i)
+              << " vs " <<  t_result_gpu(i) << std::endl;
+    assert(false);
+  }
+
+  cudaFree((void*)d_t_left);
+  cudaFree((void*)d_t_right);
+  cudaFree((void*)d_t_result);
+}
+
+
+template<int DataLayout>
+void test_scalar(int m_size, int k_size, int n_size)
+{
+  std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl;
+  // with these dimensions, the output has 300 * 140 elements, which is
+  // more than 30 * 1024, which is the number of threads in blocks on
+  // a 15 SM GK110 GPU
+  Tensor<float, 2, DataLayout> t_left(m_size, k_size);
+  Tensor<float, 2, DataLayout> t_right(k_size, n_size);
+  Tensor<float, 0, DataLayout> t_result;
+  Tensor<float, 0, DataLayout> t_result_gpu;
+  Eigen::array<DimPair, 2> dims(DimPair(0, 0), DimPair(1, 1));
+
+  t_left.setRandom();
+  t_right.setRandom();
+
+  std::size_t t_left_bytes = t_left.size()  * sizeof(float);
+  std::size_t t_right_bytes = t_right.size() * sizeof(float);
+  std::size_t t_result_bytes = sizeof(float);
+
+  float* d_t_left;
+  float* d_t_right;
+  float* d_t_result;
+
+  cudaMalloc((void**)(&d_t_left), t_left_bytes);
+  cudaMalloc((void**)(&d_t_right), t_right_bytes);
+  cudaMalloc((void**)(&d_t_result), t_result_bytes);
+
+  cudaMemcpy(d_t_left, t_left.data(), t_left_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_t_right, t_right.data(), t_right_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 2, DataLayout> >
+      gpu_t_left(d_t_left, m_size, k_size);
+  Eigen::TensorMap<Eigen::Tensor<float, 2, DataLayout> >
+      gpu_t_right(d_t_right, k_size, n_size);
+  Eigen::TensorMap<Eigen::Tensor<float, 0, DataLayout> >
+      gpu_t_result(d_t_result);
+
+  gpu_t_result.device(gpu_device) = gpu_t_left.contract(gpu_t_right, dims);
+  t_result = t_left.contract(t_right, dims);
+
+  cudaMemcpy(t_result_gpu.data(), d_t_result, t_result_bytes, cudaMemcpyDeviceToHost);
+  if (fabs(t_result() - t_result_gpu()) > 1e-4f &&
+      !Eigen::internal::isApprox(t_result(), t_result_gpu(), 1e-4f)) {
+    std::cout << "mismatch detected: " << t_result()
+              << " vs " <<  t_result_gpu() << std::endl;
+    assert(false);
+  }
+
+  cudaFree((void*)d_t_left);
+  cudaFree((void*)d_t_right);
+  cudaFree((void*)d_t_result);
+}
+
+
+template<int DataLayout>
+void test_cuda_contraction_m() {
+  for (int k = 32; k < 256; k++) {
+    test_cuda_contraction<ColMajor>(k, 128, 128);
+    test_cuda_contraction<RowMajor>(k, 128, 128);
+  }
+}
+
+template<int DataLayout>
+void test_cuda_contraction_k() {
+  for (int k = 32; k < 256; k++) {
+    test_cuda_contraction<ColMajor>(128, k, 128);
+    test_cuda_contraction<RowMajor>(128, k, 128);
+  }
+}
+
+template<int DataLayout>
+void test_cuda_contraction_n() {
+  for (int k = 32; k < 256; k++) {
+    test_cuda_contraction<ColMajor>(128, 128, k);
+    test_cuda_contraction<RowMajor>(128, 128, k);
+  }
+}
+
+
+template<int DataLayout>
+void test_cuda_contraction_sizes() {
+  int m_sizes[] = { 31,  39,   63,   64,   65,
+                   127, 129,  255,  257 , 511,
+                   512, 513, 1023, 1024, 1025};
+
+  int n_sizes[] = { 31,  39,   63,   64,   65,
+                   127, 129,  255,  257,  511,
+                   512, 513, 1023, 1024, 1025};
+
+  int k_sizes[] = {  31,   39,  63,  64,   65,
+                     95,   96, 127, 129,  255,
+                    257,  511, 512, 513, 1023,
+                   1024, 1025};
+
+  for (int i = 0; i < 15; i++) {
+    for (int j = 0; j < 15; j++) {
+      for (int k = 0; k < 17; k++) {
+        test_cuda_contraction<DataLayout>(m_sizes[i], n_sizes[j], k_sizes[k]);
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_cuda()
+{
+  CALL_SUBTEST_1(test_cuda_contraction<ColMajor>(128, 128, 128));
+  CALL_SUBTEST_1(test_cuda_contraction<RowMajor>(128, 128, 128));
+
+  CALL_SUBTEST_1(test_scalar<ColMajor>(128, 128, 128));
+  CALL_SUBTEST_1(test_scalar<RowMajor>(128, 128, 128));
+
+  CALL_SUBTEST_2(test_cuda_contraction_m<ColMajor>());
+  CALL_SUBTEST_3(test_cuda_contraction_m<RowMajor>());
+
+  CALL_SUBTEST_4(test_cuda_contraction_k<ColMajor>());
+  CALL_SUBTEST_5(test_cuda_contraction_k<RowMajor>());
+
+  CALL_SUBTEST_6(test_cuda_contraction_n<ColMajor>());
+  CALL_SUBTEST_7(test_cuda_contraction_n<RowMajor>());
+
+  CALL_SUBTEST_8(test_cuda_contraction_sizes<ColMajor>());
+  CALL_SUBTEST_9(test_cuda_contraction_sizes<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_contraction.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_contraction.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_contraction.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_contraction.cpp
@@ -0,0 +1,545 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::DefaultDevice;
+using Eigen::Tensor;
+
+typedef Tensor<float, 1>::DimensionPair DimPair;
+
+template<int DataLayout>
+static void test_evals()
+{
+  Tensor<float, 2, DataLayout> mat1(2, 3);
+  Tensor<float, 2, DataLayout> mat2(2, 3);
+  Tensor<float, 2, DataLayout> mat3(3, 2);
+
+  mat1.setRandom();
+  mat2.setRandom();
+  mat3.setRandom();
+
+  Tensor<float, 2, DataLayout> mat4(3,3);
+  mat4.setZero();
+  Eigen::array<DimPair, 1> dims3 = {{DimPair(0, 0)}};
+  typedef TensorEvaluator<decltype(mat1.contract(mat2, dims3)), DefaultDevice> Evaluator;
+  Evaluator eval(mat1.contract(mat2, dims3), DefaultDevice());
+  eval.evalTo(mat4.data());
+  EIGEN_STATIC_ASSERT(Evaluator::NumDims==2ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval.dimensions()[0], 3);
+  VERIFY_IS_EQUAL(eval.dimensions()[1], 3);
+
+  VERIFY_IS_APPROX(mat4(0,0), mat1(0,0)*mat2(0,0) + mat1(1,0)*mat2(1,0));
+  VERIFY_IS_APPROX(mat4(0,1), mat1(0,0)*mat2(0,1) + mat1(1,0)*mat2(1,1));
+  VERIFY_IS_APPROX(mat4(0,2), mat1(0,0)*mat2(0,2) + mat1(1,0)*mat2(1,2));
+  VERIFY_IS_APPROX(mat4(1,0), mat1(0,1)*mat2(0,0) + mat1(1,1)*mat2(1,0));
+  VERIFY_IS_APPROX(mat4(1,1), mat1(0,1)*mat2(0,1) + mat1(1,1)*mat2(1,1));
+  VERIFY_IS_APPROX(mat4(1,2), mat1(0,1)*mat2(0,2) + mat1(1,1)*mat2(1,2));
+  VERIFY_IS_APPROX(mat4(2,0), mat1(0,2)*mat2(0,0) + mat1(1,2)*mat2(1,0));
+  VERIFY_IS_APPROX(mat4(2,1), mat1(0,2)*mat2(0,1) + mat1(1,2)*mat2(1,1));
+  VERIFY_IS_APPROX(mat4(2,2), mat1(0,2)*mat2(0,2) + mat1(1,2)*mat2(1,2));
+
+  Tensor<float, 2, DataLayout> mat5(2,2);
+  mat5.setZero();
+  Eigen::array<DimPair, 1> dims4 = {{DimPair(1, 1)}};
+  typedef TensorEvaluator<decltype(mat1.contract(mat2, dims4)), DefaultDevice> Evaluator2;
+  Evaluator2 eval2(mat1.contract(mat2, dims4), DefaultDevice());
+  eval2.evalTo(mat5.data());
+  EIGEN_STATIC_ASSERT(Evaluator2::NumDims==2ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval2.dimensions()[0], 2);
+  VERIFY_IS_EQUAL(eval2.dimensions()[1], 2);
+
+  VERIFY_IS_APPROX(mat5(0,0), mat1(0,0)*mat2(0,0) + mat1(0,1)*mat2(0,1) + mat1(0,2)*mat2(0,2));
+  VERIFY_IS_APPROX(mat5(0,1), mat1(0,0)*mat2(1,0) + mat1(0,1)*mat2(1,1) + mat1(0,2)*mat2(1,2));
+  VERIFY_IS_APPROX(mat5(1,0), mat1(1,0)*mat2(0,0) + mat1(1,1)*mat2(0,1) + mat1(1,2)*mat2(0,2));
+  VERIFY_IS_APPROX(mat5(1,1), mat1(1,0)*mat2(1,0) + mat1(1,1)*mat2(1,1) + mat1(1,2)*mat2(1,2));
+
+  Tensor<float, 2, DataLayout> mat6(2,2);
+  mat6.setZero();
+  Eigen::array<DimPair, 1> dims6 = {{DimPair(1, 0)}};
+  typedef TensorEvaluator<decltype(mat1.contract(mat3, dims6)), DefaultDevice> Evaluator3;
+  Evaluator3 eval3(mat1.contract(mat3, dims6), DefaultDevice());
+  eval3.evalTo(mat6.data());
+  EIGEN_STATIC_ASSERT(Evaluator3::NumDims==2ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval3.dimensions()[0], 2);
+  VERIFY_IS_EQUAL(eval3.dimensions()[1], 2);
+
+  VERIFY_IS_APPROX(mat6(0,0), mat1(0,0)*mat3(0,0) + mat1(0,1)*mat3(1,0) + mat1(0,2)*mat3(2,0));
+  VERIFY_IS_APPROX(mat6(0,1), mat1(0,0)*mat3(0,1) + mat1(0,1)*mat3(1,1) + mat1(0,2)*mat3(2,1));
+  VERIFY_IS_APPROX(mat6(1,0), mat1(1,0)*mat3(0,0) + mat1(1,1)*mat3(1,0) + mat1(1,2)*mat3(2,0));
+  VERIFY_IS_APPROX(mat6(1,1), mat1(1,0)*mat3(0,1) + mat1(1,1)*mat3(1,1) + mat1(1,2)*mat3(2,1));
+}
+
+template<int DataLayout>
+static void test_scalar()
+{
+  Tensor<float, 1, DataLayout> vec1({6});
+  Tensor<float, 1, DataLayout> vec2({6});
+
+  vec1.setRandom();
+  vec2.setRandom();
+
+  Eigen::array<DimPair, 1> dims = {{DimPair(0, 0)}};
+  Tensor<float, 0, DataLayout> scalar = vec1.contract(vec2, dims);
+
+  float expected = 0.0f;
+  for (int i = 0; i < 6; ++i) {
+    expected += vec1(i) * vec2(i);
+  }
+  VERIFY_IS_APPROX(scalar(), expected);
+}
+
+template<int DataLayout>
+static void test_multidims()
+{
+  Tensor<float, 3, DataLayout> mat1(2, 2, 2);
+  Tensor<float, 4, DataLayout> mat2(2, 2, 2, 2);
+
+  mat1.setRandom();
+  mat2.setRandom();
+
+  Tensor<float, 3, DataLayout> mat3(2, 2, 2);
+  mat3.setZero();
+  Eigen::array<DimPair, 2> dims = {{DimPair(1, 2), DimPair(2, 3)}};
+  typedef TensorEvaluator<decltype(mat1.contract(mat2, dims)), DefaultDevice> Evaluator;
+  Evaluator eval(mat1.contract(mat2, dims), DefaultDevice());
+  eval.evalTo(mat3.data());
+  EIGEN_STATIC_ASSERT(Evaluator::NumDims==3ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval.dimensions()[0], 2);
+  VERIFY_IS_EQUAL(eval.dimensions()[1], 2);
+  VERIFY_IS_EQUAL(eval.dimensions()[2], 2);
+
+  VERIFY_IS_APPROX(mat3(0,0,0), mat1(0,0,0)*mat2(0,0,0,0) + mat1(0,1,0)*mat2(0,0,1,0) +
+                                mat1(0,0,1)*mat2(0,0,0,1) + mat1(0,1,1)*mat2(0,0,1,1));
+  VERIFY_IS_APPROX(mat3(0,0,1), mat1(0,0,0)*mat2(0,1,0,0) + mat1(0,1,0)*mat2(0,1,1,0) +
+                                mat1(0,0,1)*mat2(0,1,0,1) + mat1(0,1,1)*mat2(0,1,1,1));
+  VERIFY_IS_APPROX(mat3(0,1,0), mat1(0,0,0)*mat2(1,0,0,0) + mat1(0,1,0)*mat2(1,0,1,0) +
+                                mat1(0,0,1)*mat2(1,0,0,1) + mat1(0,1,1)*mat2(1,0,1,1));
+  VERIFY_IS_APPROX(mat3(0,1,1), mat1(0,0,0)*mat2(1,1,0,0) + mat1(0,1,0)*mat2(1,1,1,0) +
+                                mat1(0,0,1)*mat2(1,1,0,1) + mat1(0,1,1)*mat2(1,1,1,1));
+  VERIFY_IS_APPROX(mat3(1,0,0), mat1(1,0,0)*mat2(0,0,0,0) + mat1(1,1,0)*mat2(0,0,1,0) +
+                                mat1(1,0,1)*mat2(0,0,0,1) + mat1(1,1,1)*mat2(0,0,1,1));
+  VERIFY_IS_APPROX(mat3(1,0,1), mat1(1,0,0)*mat2(0,1,0,0) + mat1(1,1,0)*mat2(0,1,1,0) +
+                                mat1(1,0,1)*mat2(0,1,0,1) + mat1(1,1,1)*mat2(0,1,1,1));
+  VERIFY_IS_APPROX(mat3(1,1,0), mat1(1,0,0)*mat2(1,0,0,0) + mat1(1,1,0)*mat2(1,0,1,0) +
+                                mat1(1,0,1)*mat2(1,0,0,1) + mat1(1,1,1)*mat2(1,0,1,1));
+  VERIFY_IS_APPROX(mat3(1,1,1), mat1(1,0,0)*mat2(1,1,0,0) + mat1(1,1,0)*mat2(1,1,1,0) +
+                                mat1(1,0,1)*mat2(1,1,0,1) + mat1(1,1,1)*mat2(1,1,1,1));
+
+  Tensor<float, 2, DataLayout> mat4(2, 2);
+  Tensor<float, 3, DataLayout> mat5(2, 2, 2);
+
+  mat4.setRandom();
+  mat5.setRandom();
+
+  Tensor<float, 1, DataLayout> mat6(2);
+  mat6.setZero();
+  Eigen::array<DimPair, 2> dims2({{DimPair(0, 1), DimPair(1, 0)}});
+  typedef TensorEvaluator<decltype(mat4.contract(mat5, dims2)), DefaultDevice> Evaluator2;
+  Evaluator2 eval2(mat4.contract(mat5, dims2), DefaultDevice());
+  eval2.evalTo(mat6.data());
+  EIGEN_STATIC_ASSERT(Evaluator2::NumDims==1ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval2.dimensions()[0], 2);
+
+  VERIFY_IS_APPROX(mat6(0), mat4(0,0)*mat5(0,0,0) + mat4(1,0)*mat5(0,1,0) +
+                   mat4(0,1)*mat5(1,0,0) + mat4(1,1)*mat5(1,1,0));
+  VERIFY_IS_APPROX(mat6(1), mat4(0,0)*mat5(0,0,1) + mat4(1,0)*mat5(0,1,1) +
+                   mat4(0,1)*mat5(1,0,1) + mat4(1,1)*mat5(1,1,1));
+}
+
+template<int DataLayout>
+static void test_holes() {
+  Tensor<float, 4, DataLayout> t1(2, 5, 7, 3);
+  Tensor<float, 5, DataLayout> t2(2, 7, 11, 13, 3);
+  t1.setRandom();
+  t2.setRandom();
+
+  Eigen::array<DimPair, 2> dims = {{DimPair(0, 0), DimPair(3, 4)}};
+  Tensor<float, 5, DataLayout> result = t1.contract(t2, dims);
+  VERIFY_IS_EQUAL(result.dimension(0), 5);
+  VERIFY_IS_EQUAL(result.dimension(1), 7);
+  VERIFY_IS_EQUAL(result.dimension(2), 7);
+  VERIFY_IS_EQUAL(result.dimension(3), 11);
+  VERIFY_IS_EQUAL(result.dimension(4), 13);
+
+  for (int i = 0; i < 5; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 5; ++l) {
+          for (int m = 0; m < 5; ++m) {
+            VERIFY_IS_APPROX(result(i, j, k, l, m),
+                             t1(0, i, j, 0) * t2(0, k, l, m, 0) +
+                             t1(1, i, j, 0) * t2(1, k, l, m, 0) +
+                             t1(0, i, j, 1) * t2(0, k, l, m, 1) +
+                             t1(1, i, j, 1) * t2(1, k, l, m, 1) +
+                             t1(0, i, j, 2) * t2(0, k, l, m, 2) +
+                             t1(1, i, j, 2) * t2(1, k, l, m, 2));
+          }
+        }
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+static void test_full_redux()
+{
+  Tensor<float, 2, DataLayout> t1(2, 2);
+  Tensor<float, 3, DataLayout> t2(2, 2, 2);
+  t1.setRandom();
+  t2.setRandom();
+
+  Eigen::array<DimPair, 2> dims = {{DimPair(0, 0), DimPair(1, 1)}};
+  Tensor<float, 1, DataLayout> result = t1.contract(t2, dims);
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_APPROX(result(0), t1(0, 0) * t2(0, 0, 0) +  t1(1, 0) * t2(1, 0, 0)
+                            + t1(0, 1) * t2(0, 1, 0) +  t1(1, 1) * t2(1, 1, 0));
+  VERIFY_IS_APPROX(result(1), t1(0, 0) * t2(0, 0, 1) +  t1(1, 0) * t2(1, 0, 1)
+                            + t1(0, 1) * t2(0, 1, 1) +  t1(1, 1) * t2(1, 1, 1));
+
+  dims[0] = DimPair(1, 0);
+  dims[1] = DimPair(2, 1);
+  result = t2.contract(t1, dims);
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_APPROX(result(0), t1(0, 0) * t2(0, 0, 0) +  t1(1, 0) * t2(0, 1, 0)
+                            + t1(0, 1) * t2(0, 0, 1) +  t1(1, 1) * t2(0, 1, 1));
+  VERIFY_IS_APPROX(result(1), t1(0, 0) * t2(1, 0, 0) +  t1(1, 0) * t2(1, 1, 0)
+                            + t1(0, 1) * t2(1, 0, 1) +  t1(1, 1) * t2(1, 1, 1));
+}
+
+template<int DataLayout>
+static void test_contraction_of_contraction()
+{
+  Tensor<float, 2, DataLayout> t1(2, 2);
+  Tensor<float, 2, DataLayout> t2(2, 2);
+  Tensor<float, 2, DataLayout> t3(2, 2);
+  Tensor<float, 2, DataLayout> t4(2, 2);
+  t1.setRandom();
+  t2.setRandom();
+  t3.setRandom();
+  t4.setRandom();
+
+  Eigen::array<DimPair, 1> dims = {{DimPair(1, 0)}};
+  auto contract1 = t1.contract(t2, dims);
+  auto diff = t3 - contract1;
+  auto contract2 = t1.contract(t4, dims);
+  Tensor<float, 2, DataLayout> result = contract2.contract(diff, dims);
+
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_EQUAL(result.dimension(1), 2);
+
+  Eigen::Map<Eigen::Matrix<float, Dynamic, Dynamic, DataLayout>>
+      m1(t1.data(), 2, 2), m2(t2.data(), 2, 2), m3(t3.data(), 2, 2),
+      m4(t4.data(), 2, 2);
+  Eigen::Matrix<float, Dynamic, Dynamic, DataLayout>
+      expected = (m1 * m4) * (m3 - m1 * m2);
+
+  VERIFY_IS_APPROX(result(0, 0), expected(0, 0));
+  VERIFY_IS_APPROX(result(0, 1), expected(0, 1));
+  VERIFY_IS_APPROX(result(1, 0), expected(1, 0));
+  VERIFY_IS_APPROX(result(1, 1), expected(1, 1));
+}
+
+template<int DataLayout>
+static void test_expr()
+{
+  Tensor<float, 2, DataLayout> mat1(2, 3);
+  Tensor<float, 2, DataLayout> mat2(3, 2);
+  mat1.setRandom();
+  mat2.setRandom();
+
+  Tensor<float, 2, DataLayout> mat3(2,2);
+
+  Eigen::array<DimPair, 1> dims = {{DimPair(1, 0)}};
+  mat3 = mat1.contract(mat2, dims);
+
+  VERIFY_IS_APPROX(mat3(0,0), mat1(0,0)*mat2(0,0) + mat1(0,1)*mat2(1,0) + mat1(0,2)*mat2(2,0));
+  VERIFY_IS_APPROX(mat3(0,1), mat1(0,0)*mat2(0,1) + mat1(0,1)*mat2(1,1) + mat1(0,2)*mat2(2,1));
+  VERIFY_IS_APPROX(mat3(1,0), mat1(1,0)*mat2(0,0) + mat1(1,1)*mat2(1,0) + mat1(1,2)*mat2(2,0));
+  VERIFY_IS_APPROX(mat3(1,1), mat1(1,0)*mat2(0,1) + mat1(1,1)*mat2(1,1) + mat1(1,2)*mat2(2,1));
+}
+
+template<int DataLayout>
+static void test_out_of_order_contraction()
+{
+  Tensor<float, 3, DataLayout> mat1(2, 2, 2);
+  Tensor<float, 3, DataLayout> mat2(2, 2, 2);
+
+  mat1.setRandom();
+  mat2.setRandom();
+
+  Tensor<float, 2, DataLayout> mat3(2, 2);
+
+  Eigen::array<DimPair, 2> dims = {{DimPair(2, 0), DimPair(0, 2)}};
+  mat3 = mat1.contract(mat2, dims);
+
+  VERIFY_IS_APPROX(mat3(0, 0),
+                   mat1(0,0,0)*mat2(0,0,0) + mat1(1,0,0)*mat2(0,0,1) +
+                   mat1(0,0,1)*mat2(1,0,0) + mat1(1,0,1)*mat2(1,0,1));
+  VERIFY_IS_APPROX(mat3(1, 0),
+                   mat1(0,1,0)*mat2(0,0,0) + mat1(1,1,0)*mat2(0,0,1) +
+                   mat1(0,1,1)*mat2(1,0,0) + mat1(1,1,1)*mat2(1,0,1));
+  VERIFY_IS_APPROX(mat3(0, 1),
+                   mat1(0,0,0)*mat2(0,1,0) + mat1(1,0,0)*mat2(0,1,1) +
+                   mat1(0,0,1)*mat2(1,1,0) + mat1(1,0,1)*mat2(1,1,1));
+  VERIFY_IS_APPROX(mat3(1, 1),
+                   mat1(0,1,0)*mat2(0,1,0) + mat1(1,1,0)*mat2(0,1,1) +
+                   mat1(0,1,1)*mat2(1,1,0) + mat1(1,1,1)*mat2(1,1,1));
+
+  Eigen::array<DimPair, 2> dims2 = {{DimPair(0, 2), DimPair(2, 0)}};
+  mat3 = mat1.contract(mat2, dims2);
+
+  VERIFY_IS_APPROX(mat3(0, 0),
+                   mat1(0,0,0)*mat2(0,0,0) + mat1(1,0,0)*mat2(0,0,1) +
+                   mat1(0,0,1)*mat2(1,0,0) + mat1(1,0,1)*mat2(1,0,1));
+  VERIFY_IS_APPROX(mat3(1, 0),
+                   mat1(0,1,0)*mat2(0,0,0) + mat1(1,1,0)*mat2(0,0,1) +
+                   mat1(0,1,1)*mat2(1,0,0) + mat1(1,1,1)*mat2(1,0,1));
+  VERIFY_IS_APPROX(mat3(0, 1),
+                   mat1(0,0,0)*mat2(0,1,0) + mat1(1,0,0)*mat2(0,1,1) +
+                   mat1(0,0,1)*mat2(1,1,0) + mat1(1,0,1)*mat2(1,1,1));
+  VERIFY_IS_APPROX(mat3(1, 1),
+                   mat1(0,1,0)*mat2(0,1,0) + mat1(1,1,0)*mat2(0,1,1) +
+                   mat1(0,1,1)*mat2(1,1,0) + mat1(1,1,1)*mat2(1,1,1));
+
+}
+
+template<int DataLayout>
+static void test_consistency()
+{
+  // this does something like testing (A*B)^T = (B^T * A^T)
+
+  Tensor<float, 3, DataLayout> mat1(4, 3, 5);
+  Tensor<float, 5, DataLayout> mat2(3, 2, 1, 5, 4);
+  mat1.setRandom();
+  mat2.setRandom();
+
+  Tensor<float, 4, DataLayout> mat3(5, 2, 1, 5);
+  Tensor<float, 4, DataLayout> mat4(2, 1, 5, 5);
+
+  // contract on dimensions of size 4 and 3
+  Eigen::array<DimPair, 2> dims1 = {{DimPair(0, 4), DimPair(1, 0)}};
+  Eigen::array<DimPair, 2> dims2 = {{DimPair(4, 0), DimPair(0, 1)}};
+
+  mat3 = mat1.contract(mat2, dims1);
+  mat4 = mat2.contract(mat1, dims2);
+
+  // check that these are equal except for ordering of dimensions
+  if (DataLayout == ColMajor) {
+    for (size_t i = 0; i < 5; i++) {
+      for (size_t j = 0; j < 10; j++) {
+        VERIFY_IS_APPROX(mat3.data()[i + 5 * j], mat4.data()[j + 10 * i]);
+      }
+    }
+  } else {
+    // Row major
+    for (size_t i = 0; i < 5; i++) {
+      for (size_t j = 0; j < 10; j++) {
+        VERIFY_IS_APPROX(mat3.data()[10 * i + j], mat4.data()[i + 5 * j]);
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+static void test_large_contraction()
+{
+  Tensor<float, 4, DataLayout> t_left(30, 50, 8, 31);
+  Tensor<float, 5, DataLayout> t_right(8, 31, 7, 20, 10);
+  Tensor<float, 5, DataLayout> t_result(30, 50, 7, 20, 10);
+
+  t_left.setRandom();
+  t_right.setRandom();
+
+  // Add a little offset so that the results won't be close to zero.
+  t_left += t_left.constant(1.0f);
+  t_right += t_right.constant(1.0f);
+
+  typedef Map<Eigen::Matrix<float, Dynamic, Dynamic, DataLayout>> MapXf;
+  MapXf m_left(t_left.data(), 1500, 248);
+  MapXf m_right(t_right.data(), 248, 1400);
+  Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> m_result(1500, 1400);
+
+  // this contraction should be equivalent to a single matrix multiplication
+  Eigen::array<DimPair, 2> dims = {{DimPair(2, 0), DimPair(3, 1)}};
+
+  // compute results by separate methods
+  t_result = t_left.contract(t_right, dims);
+  m_result = m_left * m_right;
+
+  for (int i = 0; i < t_result.dimensions().TotalSize(); i++) {
+    VERIFY(&t_result.data()[i] != &m_result.data()[i]);
+    VERIFY_IS_APPROX(t_result.data()[i], m_result.data()[i]);
+  }
+}
+
+template<int DataLayout>
+static void test_matrix_vector()
+{
+  Tensor<float, 2, DataLayout> t_left(30, 50);
+  Tensor<float, 1, DataLayout> t_right(50);
+  Tensor<float, 1, DataLayout> t_result(30);
+
+  t_left.setRandom();
+  t_right.setRandom();
+
+  typedef Map<Eigen::Matrix<float, Dynamic, Dynamic, DataLayout>> MapXf;
+  MapXf m_left(t_left.data(), 30, 50);
+  MapXf m_right(t_right.data(), 50, 1);
+  Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> m_result(30, 1);
+
+  // this contraction should be equivalent to a single matrix multiplication
+  Eigen::array<DimPair, 1> dims{{DimPair(1, 0)}};
+
+  // compute results by separate methods
+  t_result = t_left.contract(t_right, dims);
+  m_result = m_left * m_right;
+
+  for (int i = 0; i < t_result.dimensions().TotalSize(); i++) {
+    VERIFY(internal::isApprox(t_result(i), m_result(i, 0), 1));
+  }
+}
+
+
+template<int DataLayout>
+static void test_tensor_vector()
+{
+  Tensor<float, 3, DataLayout> t_left(7, 13, 17);
+  Tensor<float, 2, DataLayout> t_right(1, 7);
+
+  t_left.setRandom();
+  t_right.setRandom();
+
+  typedef typename Tensor<float, 1, DataLayout>::DimensionPair DimensionPair;
+  Eigen::array<DimensionPair, 1> dim_pair01{{{0, 1}}};
+  Tensor<float, 3, DataLayout> t_result = t_left.contract(t_right, dim_pair01);
+
+  typedef Map<Eigen::Matrix<float, Dynamic, Dynamic, DataLayout>> MapXf;
+  MapXf m_left(t_left.data(), 7, 13*17);
+  MapXf m_right(t_right.data(), 1, 7);
+  Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> m_result = m_left.transpose() * m_right.transpose();
+
+  for (int i = 0; i < t_result.dimensions().TotalSize(); i++) {
+    VERIFY(internal::isApprox(t_result(i), m_result(i, 0), 1));
+  }
+}
+
+
+template<int DataLayout>
+static void test_small_blocking_factors()
+{
+  Tensor<float, 4, DataLayout> t_left(30, 5, 3, 31);
+  Tensor<float, 5, DataLayout> t_right(3, 31, 7, 20, 1);
+  t_left.setRandom();
+  t_right.setRandom();
+
+  // Add a little offset so that the results won't be close to zero.
+  t_left += t_left.constant(1.0f);
+  t_right += t_right.constant(1.0f);
+
+  // Force the cache sizes, which results in smaller blocking factors.
+  Eigen::setCpuCacheSizes(896, 1920, 2944);
+
+  // this contraction should be equivalent to a single matrix multiplication
+  Eigen::array<DimPair, 2> dims = {{DimPair(2, 0), DimPair(3, 1)}};
+  Tensor<float, 5, DataLayout> t_result;
+  t_result = t_left.contract(t_right, dims);
+
+  // compute result using a simple eigen matrix product
+  Map<Eigen::Matrix<float, Dynamic, Dynamic, DataLayout>> m_left(t_left.data(), 150, 93);
+  Map<Eigen::Matrix<float, Dynamic, Dynamic, DataLayout>> m_right(t_right.data(), 93, 140);
+  Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> m_result = m_left * m_right;
+
+  for (int i = 0; i < t_result.dimensions().TotalSize(); i++) {
+    VERIFY_IS_APPROX(t_result.data()[i], m_result.data()[i]);
+  }
+}
+
+template<int DataLayout>
+static void test_tensor_product()
+{
+  Tensor<float, 2, DataLayout> mat1(2, 3);
+  Tensor<float, 2, DataLayout> mat2(4, 1);
+  mat1.setRandom();
+  mat2.setRandom();
+
+  Tensor<float, 4, DataLayout> result = mat1.contract(mat2, Eigen::array<DimPair, 0>{{}});
+
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_EQUAL(result.dimension(1), 3);
+  VERIFY_IS_EQUAL(result.dimension(2), 4);
+  VERIFY_IS_EQUAL(result.dimension(3), 1);
+  for (int i = 0; i < result.dimension(0); ++i) {
+    for (int j = 0; j < result.dimension(1); ++j) {
+      for (int k = 0; k < result.dimension(2); ++k) {
+        for (int l = 0; l < result.dimension(3); ++l) {
+			VERIFY_IS_APPROX(result(i, j, k, l), mat1(i, j) * mat2(k, l) );
+        }
+      }
+    }
+  }
+}
+
+
+template<int DataLayout>
+static void test_const_inputs()
+{
+  Tensor<float, 2, DataLayout> in1(2, 3);
+  Tensor<float, 2, DataLayout> in2(3, 2);
+  in1.setRandom();
+  in2.setRandom();
+
+  TensorMap<Tensor<const float, 2, DataLayout> > mat1(in1.data(), 2, 3);
+  TensorMap<Tensor<const float, 2, DataLayout> > mat2(in2.data(), 3, 2);
+  Tensor<float, 2, DataLayout> mat3(2,2);
+
+  Eigen::array<DimPair, 1> dims = {{DimPair(1, 0)}};
+  mat3 = mat1.contract(mat2, dims);
+
+  VERIFY_IS_APPROX(mat3(0,0), mat1(0,0)*mat2(0,0) + mat1(0,1)*mat2(1,0) + mat1(0,2)*mat2(2,0));
+  VERIFY_IS_APPROX(mat3(0,1), mat1(0,0)*mat2(0,1) + mat1(0,1)*mat2(1,1) + mat1(0,2)*mat2(2,1));
+  VERIFY_IS_APPROX(mat3(1,0), mat1(1,0)*mat2(0,0) + mat1(1,1)*mat2(1,0) + mat1(1,2)*mat2(2,0));
+  VERIFY_IS_APPROX(mat3(1,1), mat1(1,0)*mat2(0,1) + mat1(1,1)*mat2(1,1) + mat1(1,2)*mat2(2,1));
+}
+
+void test_cxx11_tensor_contraction()
+{
+  CALL_SUBTEST(test_evals<ColMajor>());
+  CALL_SUBTEST(test_evals<RowMajor>());
+  CALL_SUBTEST(test_scalar<ColMajor>());
+  CALL_SUBTEST(test_scalar<RowMajor>());
+  CALL_SUBTEST(test_multidims<ColMajor>());
+  CALL_SUBTEST(test_multidims<RowMajor>());
+  CALL_SUBTEST(test_holes<ColMajor>());
+  CALL_SUBTEST(test_holes<RowMajor>());
+  CALL_SUBTEST(test_full_redux<ColMajor>());
+  CALL_SUBTEST(test_full_redux<RowMajor>());
+  CALL_SUBTEST(test_contraction_of_contraction<ColMajor>());
+  CALL_SUBTEST(test_contraction_of_contraction<RowMajor>());
+  CALL_SUBTEST(test_expr<ColMajor>());
+  CALL_SUBTEST(test_expr<RowMajor>());
+  CALL_SUBTEST(test_out_of_order_contraction<ColMajor>());
+  CALL_SUBTEST(test_out_of_order_contraction<RowMajor>());
+  CALL_SUBTEST(test_consistency<ColMajor>());
+  CALL_SUBTEST(test_consistency<RowMajor>());
+  CALL_SUBTEST(test_large_contraction<ColMajor>());
+  CALL_SUBTEST(test_large_contraction<RowMajor>());
+  CALL_SUBTEST(test_matrix_vector<ColMajor>());
+  CALL_SUBTEST(test_matrix_vector<RowMajor>());
+  CALL_SUBTEST(test_tensor_vector<ColMajor>());
+  CALL_SUBTEST(test_tensor_vector<RowMajor>());
+  CALL_SUBTEST(test_small_blocking_factors<ColMajor>());
+  CALL_SUBTEST(test_small_blocking_factors<RowMajor>());
+  CALL_SUBTEST(test_tensor_product<ColMajor>());
+  CALL_SUBTEST(test_tensor_product<RowMajor>());
+  CALL_SUBTEST(test_const_inputs<ColMajor>());
+  CALL_SUBTEST(test_const_inputs<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_convolution.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_convolution.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_convolution.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_convolution.cpp
@@ -0,0 +1,149 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::DefaultDevice;
+
+template <int DataLayout>
+static void test_evals()
+{
+  Tensor<float, 2, DataLayout> input(3, 3);
+  Tensor<float, 1, DataLayout> kernel(2);
+
+  input.setRandom();
+  kernel.setRandom();
+
+  Tensor<float, 2, DataLayout> result(2,3);
+  result.setZero();
+  Eigen::array<Tensor<float, 2>::Index, 1> dims3{{0}};
+
+  typedef TensorEvaluator<decltype(input.convolve(kernel, dims3)), DefaultDevice> Evaluator;
+  Evaluator eval(input.convolve(kernel, dims3), DefaultDevice());
+  eval.evalTo(result.data());
+  EIGEN_STATIC_ASSERT(Evaluator::NumDims==2ul, YOU_MADE_A_PROGRAMMING_MISTAKE);
+  VERIFY_IS_EQUAL(eval.dimensions()[0], 2);
+  VERIFY_IS_EQUAL(eval.dimensions()[1], 3);
+
+  VERIFY_IS_APPROX(result(0,0), input(0,0)*kernel(0) + input(1,0)*kernel(1));  // index 0
+  VERIFY_IS_APPROX(result(0,1), input(0,1)*kernel(0) + input(1,1)*kernel(1));  // index 2
+  VERIFY_IS_APPROX(result(0,2), input(0,2)*kernel(0) + input(1,2)*kernel(1));  // index 4
+  VERIFY_IS_APPROX(result(1,0), input(1,0)*kernel(0) + input(2,0)*kernel(1));  // index 1
+  VERIFY_IS_APPROX(result(1,1), input(1,1)*kernel(0) + input(2,1)*kernel(1));  // index 3
+  VERIFY_IS_APPROX(result(1,2), input(1,2)*kernel(0) + input(2,2)*kernel(1));  // index 5
+}
+
+template <int DataLayout>
+static void test_expr()
+{
+  Tensor<float, 2, DataLayout> input(3, 3);
+  Tensor<float, 2, DataLayout> kernel(2, 2);
+  input.setRandom();
+  kernel.setRandom();
+
+  Tensor<float, 2, DataLayout> result(2,2);
+  Eigen::array<ptrdiff_t, 2> dims;
+  dims[0] = 0;
+  dims[1] = 1;
+  result = input.convolve(kernel, dims);
+
+  VERIFY_IS_APPROX(result(0,0), input(0,0)*kernel(0,0) + input(0,1)*kernel(0,1) +
+                                input(1,0)*kernel(1,0) + input(1,1)*kernel(1,1));
+  VERIFY_IS_APPROX(result(0,1), input(0,1)*kernel(0,0) + input(0,2)*kernel(0,1) +
+                                input(1,1)*kernel(1,0) + input(1,2)*kernel(1,1));
+  VERIFY_IS_APPROX(result(1,0), input(1,0)*kernel(0,0) + input(1,1)*kernel(0,1) +
+                                input(2,0)*kernel(1,0) + input(2,1)*kernel(1,1));
+  VERIFY_IS_APPROX(result(1,1), input(1,1)*kernel(0,0) + input(1,2)*kernel(0,1) +
+                                input(2,1)*kernel(1,0) + input(2,2)*kernel(1,1));
+}
+
+template <int DataLayout>
+static void test_modes() {
+  Tensor<float, 1, DataLayout> input(3);
+  Tensor<float, 1, DataLayout> kernel(3);
+  input(0) = 1.0f;
+  input(1) = 2.0f;
+  input(2) = 3.0f;
+  kernel(0) = 0.5f;
+  kernel(1) = 1.0f;
+  kernel(2) = 0.0f;
+
+  Eigen::array<ptrdiff_t, 1> dims;
+  dims[0] = 0;
+  Eigen::array<std::pair<ptrdiff_t, ptrdiff_t>, 1> padding;
+
+  // Emulate VALID mode (as defined in
+  // http://docs.scipy.org/doc/numpy/reference/generated/numpy.convolve.html).
+  padding[0] = std::make_pair(0, 0);
+  Tensor<float, 1, DataLayout> valid(1);
+  valid = input.pad(padding).convolve(kernel, dims);
+  VERIFY_IS_EQUAL(valid.dimension(0), 1);
+  VERIFY_IS_APPROX(valid(0), 2.5f);
+
+  // Emulate SAME mode (as defined in
+  // http://docs.scipy.org/doc/numpy/reference/generated/numpy.convolve.html).
+  padding[0] = std::make_pair(1, 1);
+  Tensor<float, 1, DataLayout> same(3);
+  same = input.pad(padding).convolve(kernel, dims);
+  VERIFY_IS_EQUAL(same.dimension(0), 3);
+  VERIFY_IS_APPROX(same(0), 1.0f);
+  VERIFY_IS_APPROX(same(1), 2.5f);
+  VERIFY_IS_APPROX(same(2), 4.0f);
+
+  // Emulate FULL mode (as defined in
+  // http://docs.scipy.org/doc/numpy/reference/generated/numpy.convolve.html).
+  padding[0] = std::make_pair(2, 2);
+  Tensor<float, 1, DataLayout> full(5);
+  full = input.pad(padding).convolve(kernel, dims);
+  VERIFY_IS_EQUAL(full.dimension(0), 5);
+  VERIFY_IS_APPROX(full(0), 0.0f);
+  VERIFY_IS_APPROX(full(1), 1.0f);
+  VERIFY_IS_APPROX(full(2), 2.5f);
+  VERIFY_IS_APPROX(full(3), 4.0f);
+  VERIFY_IS_APPROX(full(4), 1.5f);
+}
+
+template <int DataLayout>
+static void test_strides() {
+  Tensor<float, 1, DataLayout> input(13);
+  Tensor<float, 1, DataLayout> kernel(3);
+  input.setRandom();
+  kernel.setRandom();
+
+  Eigen::array<ptrdiff_t, 1> dims;
+  dims[0] = 0;
+  Eigen::array<ptrdiff_t, 1> stride_of_3;
+  stride_of_3[0] = 3;
+  Eigen::array<ptrdiff_t, 1> stride_of_2;
+  stride_of_2[0] = 2;
+
+  Tensor<float, 1, DataLayout> result;
+  result = input.stride(stride_of_3).convolve(kernel, dims).stride(stride_of_2);
+
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_APPROX(result(0), (input(0)*kernel(0) + input(3)*kernel(1) +
+                               input(6)*kernel(2)));
+  VERIFY_IS_APPROX(result(1), (input(6)*kernel(0) + input(9)*kernel(1) +
+                               input(12)*kernel(2)));
+}
+
+void test_cxx11_tensor_convolution()
+{
+  CALL_SUBTEST(test_evals<ColMajor>());
+  CALL_SUBTEST(test_evals<RowMajor>());
+  CALL_SUBTEST(test_expr<ColMajor>());
+  CALL_SUBTEST(test_expr<RowMajor>());
+  CALL_SUBTEST(test_modes<ColMajor>());
+  CALL_SUBTEST(test_modes<RowMajor>());
+  CALL_SUBTEST(test_strides<ColMajor>());
+  CALL_SUBTEST(test_strides<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_cuda.cu
@@ -0,0 +1,1287 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_cuda
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+void test_cuda_nullary() {
+  Tensor<float, 1, 0, int> in1(2);
+  Tensor<float, 1, 0, int> in2(2);
+  in1.setRandom();
+  in2.setRandom();
+
+  std::size_t tensor_bytes = in1.size() * sizeof(float);
+
+  float* d_in1;
+  float* d_in2;
+  cudaMalloc((void**)(&d_in1), tensor_bytes);
+  cudaMalloc((void**)(&d_in2), tensor_bytes);
+  cudaMemcpy(d_in1, in1.data(), tensor_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in2, in2.data(), tensor_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1, 0, int>, Eigen::Aligned> gpu_in1(
+      d_in1, 2);
+  Eigen::TensorMap<Eigen::Tensor<float, 1, 0, int>, Eigen::Aligned> gpu_in2(
+      d_in2, 2);
+
+  gpu_in1.device(gpu_device) = gpu_in1.constant(3.14f);
+  gpu_in2.device(gpu_device) = gpu_in2.random();
+
+  Tensor<float, 1, 0, int> new1(2);
+  Tensor<float, 1, 0, int> new2(2);
+
+  assert(cudaMemcpyAsync(new1.data(), d_in1, tensor_bytes, cudaMemcpyDeviceToHost,
+                         gpu_device.stream()) == cudaSuccess);
+  assert(cudaMemcpyAsync(new2.data(), d_in2, tensor_bytes, cudaMemcpyDeviceToHost,
+                         gpu_device.stream()) == cudaSuccess);
+
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 2; ++i) {
+    VERIFY_IS_APPROX(new1(i), 3.14f);
+    VERIFY_IS_NOT_EQUAL(new2(i), in2(i));
+  }
+
+  cudaFree(d_in1);
+  cudaFree(d_in2);
+}
+
+void test_cuda_elementwise_small() {
+  Tensor<float, 1> in1(Eigen::array<Eigen::DenseIndex, 1>(2));
+  Tensor<float, 1> in2(Eigen::array<Eigen::DenseIndex, 1>(2));
+  Tensor<float, 1> out(Eigen::array<Eigen::DenseIndex, 1>(2));
+  in1.setRandom();
+  in2.setRandom();
+
+  std::size_t in1_bytes = in1.size() * sizeof(float);
+  std::size_t in2_bytes = in2.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_in1;
+  float* d_in2;
+  float* d_out;
+  cudaMalloc((void**)(&d_in1), in1_bytes);
+  cudaMalloc((void**)(&d_in2), in2_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_in1, in1.data(), in1_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in2, in2.data(), in2_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_in1(
+      d_in1, Eigen::array<Eigen::DenseIndex, 1>(2));
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_in2(
+      d_in2, Eigen::array<Eigen::DenseIndex, 1>(2));
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_out(
+      d_out, Eigen::array<Eigen::DenseIndex, 1>(2));
+
+  gpu_out.device(gpu_device) = gpu_in1 + gpu_in2;
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost,
+                         gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 2; ++i) {
+    VERIFY_IS_APPROX(
+        out(Eigen::array<Eigen::DenseIndex, 1>(i)),
+        in1(Eigen::array<Eigen::DenseIndex, 1>(i)) + in2(Eigen::array<Eigen::DenseIndex, 1>(i)));
+  }
+
+  cudaFree(d_in1);
+  cudaFree(d_in2);
+  cudaFree(d_out);
+}
+
+void test_cuda_elementwise()
+{
+  Tensor<float, 3> in1(Eigen::array<Eigen::DenseIndex, 3>(72,53,97));
+  Tensor<float, 3> in2(Eigen::array<Eigen::DenseIndex, 3>(72,53,97));
+  Tensor<float, 3> in3(Eigen::array<Eigen::DenseIndex, 3>(72,53,97));
+  Tensor<float, 3> out(Eigen::array<Eigen::DenseIndex, 3>(72,53,97));
+  in1.setRandom();
+  in2.setRandom();
+  in3.setRandom();
+
+  std::size_t in1_bytes = in1.size() * sizeof(float);
+  std::size_t in2_bytes = in2.size() * sizeof(float);
+  std::size_t in3_bytes = in3.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_in1;
+  float* d_in2;
+  float* d_in3;
+  float* d_out;
+  cudaMalloc((void**)(&d_in1), in1_bytes);
+  cudaMalloc((void**)(&d_in2), in2_bytes);
+  cudaMalloc((void**)(&d_in3), in3_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_in1, in1.data(), in1_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in2, in2.data(), in2_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in3, in3.data(), in3_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 3> > gpu_in1(d_in1, Eigen::array<Eigen::DenseIndex, 3>(72,53,97));
+  Eigen::TensorMap<Eigen::Tensor<float, 3> > gpu_in2(d_in2, Eigen::array<Eigen::DenseIndex, 3>(72,53,97));
+  Eigen::TensorMap<Eigen::Tensor<float, 3> > gpu_in3(d_in3, Eigen::array<Eigen::DenseIndex, 3>(72,53,97));
+  Eigen::TensorMap<Eigen::Tensor<float, 3> > gpu_out(d_out, Eigen::array<Eigen::DenseIndex, 3>(72,53,97));
+
+  gpu_out.device(gpu_device) = gpu_in1 + gpu_in2 * gpu_in3;
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 72; ++i) {
+    for (int j = 0; j < 53; ++j) {
+      for (int k = 0; k < 97; ++k) {
+        VERIFY_IS_APPROX(out(Eigen::array<Eigen::DenseIndex, 3>(i,j,k)), in1(Eigen::array<Eigen::DenseIndex, 3>(i,j,k)) + in2(Eigen::array<Eigen::DenseIndex, 3>(i,j,k)) * in3(Eigen::array<Eigen::DenseIndex, 3>(i,j,k)));
+      }
+    }
+  }
+
+  cudaFree(d_in1);
+  cudaFree(d_in2);
+  cudaFree(d_in3);
+  cudaFree(d_out);
+}
+
+void test_cuda_props() {
+  Tensor<float, 1> in1(200);
+  Tensor<bool, 1> out(200);
+  in1.setRandom();
+
+  std::size_t in1_bytes = in1.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(bool);
+
+  float* d_in1;
+  bool* d_out;
+  cudaMalloc((void**)(&d_in1), in1_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_in1, in1.data(), in1_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_in1(
+      d_in1, 200);
+  Eigen::TensorMap<Eigen::Tensor<bool, 1>, Eigen::Aligned> gpu_out(
+      d_out, 200);
+
+  gpu_out.device(gpu_device) = (gpu_in1.isnan)();
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost,
+                         gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 200; ++i) {
+    VERIFY_IS_EQUAL(out(i), (std::isnan)(in1(i)));
+  }
+
+  cudaFree(d_in1);
+  cudaFree(d_out);
+}
+
+void test_cuda_reduction()
+{
+  Tensor<float, 4> in1(72,53,97,113);
+  Tensor<float, 2> out(72,97);
+  in1.setRandom();
+
+  std::size_t in1_bytes = in1.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_in1;
+  float* d_out;
+  cudaMalloc((void**)(&d_in1), in1_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_in1, in1.data(), in1_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 4> > gpu_in1(d_in1, 72,53,97,113);
+  Eigen::TensorMap<Eigen::Tensor<float, 2> > gpu_out(d_out, 72,97);
+
+  array<Eigen::DenseIndex, 2> reduction_axis;
+  reduction_axis[0] = 1;
+  reduction_axis[1] = 3;
+
+  gpu_out.device(gpu_device) = gpu_in1.maximum(reduction_axis);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 72; ++i) {
+    for (int j = 0; j < 97; ++j) {
+      float expected = 0;
+      for (int k = 0; k < 53; ++k) {
+        for (int l = 0; l < 113; ++l) {
+          expected =
+              std::max<float>(expected, in1(i, k, j, l));
+        }
+      }
+      VERIFY_IS_APPROX(out(i,j), expected);
+    }
+  }
+
+  cudaFree(d_in1);
+  cudaFree(d_out);
+}
+
+template<int DataLayout>
+void test_cuda_contraction()
+{
+  // with these dimensions, the output has 300 * 140 elements, which is
+  // more than 30 * 1024, which is the number of threads in blocks on
+  // a 15 SM GK110 GPU
+  Tensor<float, 4, DataLayout> t_left(6, 50, 3, 31);
+  Tensor<float, 5, DataLayout> t_right(Eigen::array<Eigen::DenseIndex, 5>(3, 31, 7, 20, 1));
+  Tensor<float, 5, DataLayout> t_result(Eigen::array<Eigen::DenseIndex, 5>(6, 50, 7, 20, 1));
+
+  t_left.setRandom();
+  t_right.setRandom();
+
+  std::size_t t_left_bytes = t_left.size()  * sizeof(float);
+  std::size_t t_right_bytes = t_right.size() * sizeof(float);
+  std::size_t t_result_bytes = t_result.size() * sizeof(float);
+
+  float* d_t_left;
+  float* d_t_right;
+  float* d_t_result;
+
+  cudaMalloc((void**)(&d_t_left), t_left_bytes);
+  cudaMalloc((void**)(&d_t_right), t_right_bytes);
+  cudaMalloc((void**)(&d_t_result), t_result_bytes);
+
+  cudaMemcpy(d_t_left, t_left.data(), t_left_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_t_right, t_right.data(), t_right_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 4, DataLayout> > gpu_t_left(d_t_left, 6, 50, 3, 31);
+  Eigen::TensorMap<Eigen::Tensor<float, 5, DataLayout> > gpu_t_right(d_t_right, 3, 31, 7, 20, 1);
+  Eigen::TensorMap<Eigen::Tensor<float, 5, DataLayout> > gpu_t_result(d_t_result, 6, 50, 7, 20, 1);
+
+  typedef Eigen::Map<Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> > MapXf;
+  MapXf m_left(t_left.data(), 300, 93);
+  MapXf m_right(t_right.data(), 93, 140);
+  Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> m_result(300, 140);
+
+  typedef Tensor<float, 1>::DimensionPair DimPair;
+  Eigen::array<DimPair, 2> dims;
+  dims[0] = DimPair(2, 0);
+  dims[1] = DimPair(3, 1);
+
+  m_result = m_left * m_right;
+  gpu_t_result.device(gpu_device) = gpu_t_left.contract(gpu_t_right, dims);
+
+  cudaMemcpy(t_result.data(), d_t_result, t_result_bytes, cudaMemcpyDeviceToHost);
+
+  for (DenseIndex i = 0; i < t_result.size(); i++) {
+    if (fabs(t_result.data()[i] - m_result.data()[i]) >= 1e-4f) {
+      std::cout << "mismatch detected at index " << i << ": " << t_result.data()[i] << " vs " <<  m_result.data()[i] << std::endl;
+      assert(false);
+    }
+  }
+
+  cudaFree(d_t_left);
+  cudaFree(d_t_right);
+  cudaFree(d_t_result);
+}
+
+template<int DataLayout>
+void test_cuda_convolution_1d()
+{
+  Tensor<float, 4, DataLayout> input(74,37,11,137);
+  Tensor<float, 1, DataLayout> kernel(4);
+  Tensor<float, 4, DataLayout> out(74,34,11,137);
+  input = input.constant(10.0f) + input.random();
+  kernel = kernel.constant(7.0f) + kernel.random();
+
+  std::size_t input_bytes = input.size() * sizeof(float);
+  std::size_t kernel_bytes = kernel.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_input;
+  float* d_kernel;
+  float* d_out;
+  cudaMalloc((void**)(&d_input), input_bytes);
+  cudaMalloc((void**)(&d_kernel), kernel_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_input, input.data(), input_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_kernel, kernel.data(), kernel_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 4, DataLayout> > gpu_input(d_input, 74,37,11,137);
+  Eigen::TensorMap<Eigen::Tensor<float, 1, DataLayout> > gpu_kernel(d_kernel, 4);
+  Eigen::TensorMap<Eigen::Tensor<float, 4, DataLayout> > gpu_out(d_out, 74,34,11,137);
+
+  Eigen::array<Eigen::DenseIndex, 1> dims(1);
+  gpu_out.device(gpu_device) = gpu_input.convolve(gpu_kernel, dims);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 74; ++i) {
+    for (int j = 0; j < 34; ++j) {
+      for (int k = 0; k < 11; ++k) {
+        for (int l = 0; l < 137; ++l) {
+          const float result = out(i,j,k,l);
+          const float expected = input(i,j+0,k,l) * kernel(0) + input(i,j+1,k,l) * kernel(1) +
+                                 input(i,j+2,k,l) * kernel(2) + input(i,j+3,k,l) * kernel(3);
+          VERIFY_IS_APPROX(result, expected);
+        }
+      }
+    }
+  }
+
+  cudaFree(d_input);
+  cudaFree(d_kernel);
+  cudaFree(d_out);
+}
+
+void test_cuda_convolution_inner_dim_col_major_1d()
+{
+  Tensor<float, 4, ColMajor> input(74,9,11,7);
+  Tensor<float, 1, ColMajor> kernel(4);
+  Tensor<float, 4, ColMajor> out(71,9,11,7);
+  input = input.constant(10.0f) + input.random();
+  kernel = kernel.constant(7.0f) + kernel.random();
+
+  std::size_t input_bytes = input.size() * sizeof(float);
+  std::size_t kernel_bytes = kernel.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_input;
+  float* d_kernel;
+  float* d_out;
+  cudaMalloc((void**)(&d_input), input_bytes);
+  cudaMalloc((void**)(&d_kernel), kernel_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_input, input.data(), input_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_kernel, kernel.data(), kernel_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 4, ColMajor> > gpu_input(d_input,74,9,11,7);
+  Eigen::TensorMap<Eigen::Tensor<float, 1, ColMajor> > gpu_kernel(d_kernel,4);
+  Eigen::TensorMap<Eigen::Tensor<float, 4, ColMajor> > gpu_out(d_out,71,9,11,7);
+
+  Eigen::array<Eigen::DenseIndex, 1> dims(0);
+  gpu_out.device(gpu_device) = gpu_input.convolve(gpu_kernel, dims);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 71; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 11; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          const float result = out(i,j,k,l);
+          const float expected = input(i+0,j,k,l) * kernel(0) + input(i+1,j,k,l) * kernel(1) +
+                                 input(i+2,j,k,l) * kernel(2) + input(i+3,j,k,l) * kernel(3);
+          VERIFY_IS_APPROX(result, expected);
+        }
+      }
+    }
+  }
+
+  cudaFree(d_input);
+  cudaFree(d_kernel);
+  cudaFree(d_out);
+}
+
+void test_cuda_convolution_inner_dim_row_major_1d()
+{
+  Tensor<float, 4, RowMajor> input(7,9,11,74);
+  Tensor<float, 1, RowMajor> kernel(4);
+  Tensor<float, 4, RowMajor> out(7,9,11,71);
+  input = input.constant(10.0f) + input.random();
+  kernel = kernel.constant(7.0f) + kernel.random();
+
+  std::size_t input_bytes = input.size() * sizeof(float);
+  std::size_t kernel_bytes = kernel.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_input;
+  float* d_kernel;
+  float* d_out;
+  cudaMalloc((void**)(&d_input), input_bytes);
+  cudaMalloc((void**)(&d_kernel), kernel_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_input, input.data(), input_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_kernel, kernel.data(), kernel_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 4, RowMajor> > gpu_input(d_input, 7,9,11,74);
+  Eigen::TensorMap<Eigen::Tensor<float, 1, RowMajor> > gpu_kernel(d_kernel, 4);
+  Eigen::TensorMap<Eigen::Tensor<float, 4, RowMajor> > gpu_out(d_out, 7,9,11,71);
+
+  Eigen::array<Eigen::DenseIndex, 1> dims(3);
+  gpu_out.device(gpu_device) = gpu_input.convolve(gpu_kernel, dims);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 7; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 11; ++k) {
+        for (int l = 0; l < 71; ++l) {
+          const float result = out(i,j,k,l);
+          const float expected = input(i,j,k,l+0) * kernel(0) + input(i,j,k,l+1) * kernel(1) +
+                                 input(i,j,k,l+2) * kernel(2) + input(i,j,k,l+3) * kernel(3);
+          VERIFY_IS_APPROX(result, expected);
+        }
+      }
+    }
+  }
+
+  cudaFree(d_input);
+  cudaFree(d_kernel);
+  cudaFree(d_out);
+}
+
+template<int DataLayout>
+void test_cuda_convolution_2d()
+{
+  Tensor<float, 4, DataLayout> input(74,37,11,137);
+  Tensor<float, 2, DataLayout> kernel(3,4);
+  Tensor<float, 4, DataLayout> out(74,35,8,137);
+  input = input.constant(10.0f) + input.random();
+  kernel = kernel.constant(7.0f) + kernel.random();
+
+  std::size_t input_bytes = input.size() * sizeof(float);
+  std::size_t kernel_bytes = kernel.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_input;
+  float* d_kernel;
+  float* d_out;
+  cudaMalloc((void**)(&d_input), input_bytes);
+  cudaMalloc((void**)(&d_kernel), kernel_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_input, input.data(), input_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_kernel, kernel.data(), kernel_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 4, DataLayout> > gpu_input(d_input,74,37,11,137);
+  Eigen::TensorMap<Eigen::Tensor<float, 2, DataLayout> > gpu_kernel(d_kernel,3,4);
+  Eigen::TensorMap<Eigen::Tensor<float, 4, DataLayout> > gpu_out(d_out,74,35,8,137);
+
+  Eigen::array<Eigen::DenseIndex, 2> dims(1,2);
+  gpu_out.device(gpu_device) = gpu_input.convolve(gpu_kernel, dims);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 74; ++i) {
+    for (int j = 0; j < 35; ++j) {
+      for (int k = 0; k < 8; ++k) {
+        for (int l = 0; l < 137; ++l) {
+          const float result = out(i,j,k,l);
+          const float expected = input(i,j+0,k+0,l) * kernel(0,0) +
+                                 input(i,j+1,k+0,l) * kernel(1,0) +
+                                 input(i,j+2,k+0,l) * kernel(2,0) +
+                                 input(i,j+0,k+1,l) * kernel(0,1) +
+                                 input(i,j+1,k+1,l) * kernel(1,1) +
+                                 input(i,j+2,k+1,l) * kernel(2,1) +
+                                 input(i,j+0,k+2,l) * kernel(0,2) +
+                                 input(i,j+1,k+2,l) * kernel(1,2) +
+                                 input(i,j+2,k+2,l) * kernel(2,2) +
+                                 input(i,j+0,k+3,l) * kernel(0,3) +
+                                 input(i,j+1,k+3,l) * kernel(1,3) +
+                                 input(i,j+2,k+3,l) * kernel(2,3);
+          VERIFY_IS_APPROX(result, expected);
+        }
+      }
+    }
+  }
+
+  cudaFree(d_input);
+  cudaFree(d_kernel);
+  cudaFree(d_out);
+}
+
+template<int DataLayout>
+void test_cuda_convolution_3d()
+{
+  Tensor<float, 5, DataLayout> input(Eigen::array<Eigen::DenseIndex, 5>(74,37,11,137,17));
+  Tensor<float, 3, DataLayout> kernel(3,4,2);
+  Tensor<float, 5, DataLayout> out(Eigen::array<Eigen::DenseIndex, 5>(74,35,8,136,17));
+  input = input.constant(10.0f) + input.random();
+  kernel = kernel.constant(7.0f) + kernel.random();
+
+  std::size_t input_bytes = input.size() * sizeof(float);
+  std::size_t kernel_bytes = kernel.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_input;
+  float* d_kernel;
+  float* d_out;
+  cudaMalloc((void**)(&d_input), input_bytes);
+  cudaMalloc((void**)(&d_kernel), kernel_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_input, input.data(), input_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_kernel, kernel.data(), kernel_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;    
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 5, DataLayout> > gpu_input(d_input,74,37,11,137,17);
+  Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> > gpu_kernel(d_kernel,3,4,2);
+  Eigen::TensorMap<Eigen::Tensor<float, 5, DataLayout> > gpu_out(d_out,74,35,8,136,17);
+
+  Eigen::array<Eigen::DenseIndex, 3> dims(1,2,3);
+  gpu_out.device(gpu_device) = gpu_input.convolve(gpu_kernel, dims);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 74; ++i) {
+    for (int j = 0; j < 35; ++j) {
+      for (int k = 0; k < 8; ++k) {
+        for (int l = 0; l < 136; ++l) {
+          for (int m = 0; m < 17; ++m) {
+            const float result = out(i,j,k,l,m);
+            const float expected = input(i,j+0,k+0,l+0,m) * kernel(0,0,0) +
+                                   input(i,j+1,k+0,l+0,m) * kernel(1,0,0) +
+                                   input(i,j+2,k+0,l+0,m) * kernel(2,0,0) +
+                                   input(i,j+0,k+1,l+0,m) * kernel(0,1,0) +
+                                   input(i,j+1,k+1,l+0,m) * kernel(1,1,0) +
+                                   input(i,j+2,k+1,l+0,m) * kernel(2,1,0) +
+                                   input(i,j+0,k+2,l+0,m) * kernel(0,2,0) +
+                                   input(i,j+1,k+2,l+0,m) * kernel(1,2,0) +
+                                   input(i,j+2,k+2,l+0,m) * kernel(2,2,0) +
+                                   input(i,j+0,k+3,l+0,m) * kernel(0,3,0) +
+                                   input(i,j+1,k+3,l+0,m) * kernel(1,3,0) +
+                                   input(i,j+2,k+3,l+0,m) * kernel(2,3,0) +
+                                   input(i,j+0,k+0,l+1,m) * kernel(0,0,1) +
+                                   input(i,j+1,k+0,l+1,m) * kernel(1,0,1) +
+                                   input(i,j+2,k+0,l+1,m) * kernel(2,0,1) +
+                                   input(i,j+0,k+1,l+1,m) * kernel(0,1,1) +
+                                   input(i,j+1,k+1,l+1,m) * kernel(1,1,1) +
+                                   input(i,j+2,k+1,l+1,m) * kernel(2,1,1) +
+                                   input(i,j+0,k+2,l+1,m) * kernel(0,2,1) +
+                                   input(i,j+1,k+2,l+1,m) * kernel(1,2,1) +
+                                   input(i,j+2,k+2,l+1,m) * kernel(2,2,1) +
+                                   input(i,j+0,k+3,l+1,m) * kernel(0,3,1) +
+                                   input(i,j+1,k+3,l+1,m) * kernel(1,3,1) +
+                                   input(i,j+2,k+3,l+1,m) * kernel(2,3,1);
+            VERIFY_IS_APPROX(result, expected);
+          }
+        }
+      }
+    }
+  }
+
+  cudaFree(d_input);
+  cudaFree(d_kernel);
+  cudaFree(d_out);
+}
+
+
+template <typename Scalar>
+void test_cuda_lgamma(const Scalar stddev)
+{
+  Tensor<Scalar, 2> in(72,97);
+  in.setRandom();
+  in *= in.constant(stddev);
+  Tensor<Scalar, 2> out(72,97);
+  out.setZero();
+
+  std::size_t bytes = in.size() * sizeof(Scalar);
+
+  Scalar* d_in;
+  Scalar* d_out;
+  cudaMalloc((void**)(&d_in), bytes);
+  cudaMalloc((void**)(&d_out), bytes);
+
+  cudaMemcpy(d_in, in.data(), bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_in(d_in, 72, 97);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_out(d_out, 72, 97);
+
+  gpu_out.device(gpu_device) = gpu_in.lgamma();
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 72; ++i) {
+    for (int j = 0; j < 97; ++j) {
+      VERIFY_IS_APPROX(out(i,j), (std::lgamma)(in(i,j)));
+    }
+  }
+
+  cudaFree(d_in);
+  cudaFree(d_out);
+}
+
+template <typename Scalar>
+void test_cuda_digamma()
+{
+  Tensor<Scalar, 1> in(7);
+  Tensor<Scalar, 1> out(7);
+  Tensor<Scalar, 1> expected_out(7);
+  out.setZero();
+
+  in(0) = Scalar(1);
+  in(1) = Scalar(1.5);
+  in(2) = Scalar(4);
+  in(3) = Scalar(-10.5);
+  in(4) = Scalar(10000.5);
+  in(5) = Scalar(0);
+  in(6) = Scalar(-1);
+
+  expected_out(0) = Scalar(-0.5772156649015329);
+  expected_out(1) = Scalar(0.03648997397857645);
+  expected_out(2) = Scalar(1.2561176684318);
+  expected_out(3) = Scalar(2.398239129535781);
+  expected_out(4) = Scalar(9.210340372392849);
+  expected_out(5) = std::numeric_limits<Scalar>::infinity();
+  expected_out(6) = std::numeric_limits<Scalar>::infinity();
+
+  std::size_t bytes = in.size() * sizeof(Scalar);
+
+  Scalar* d_in;
+  Scalar* d_out;
+  cudaMalloc((void**)(&d_in), bytes);
+  cudaMalloc((void**)(&d_out), bytes);
+
+  cudaMemcpy(d_in, in.data(), bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_in(d_in, 7);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_out(d_out, 7);
+
+  gpu_out.device(gpu_device) = gpu_in.digamma();
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 5; ++i) {
+    VERIFY_IS_APPROX(out(i), expected_out(i));
+  }
+  for (int i = 5; i < 7; ++i) {
+    VERIFY_IS_EQUAL(out(i), expected_out(i));
+  }
+
+  cudaFree(d_in);
+  cudaFree(d_out);
+}
+
+template <typename Scalar>
+void test_cuda_zeta()
+{
+  Tensor<Scalar, 1> in_x(6);
+  Tensor<Scalar, 1> in_q(6);
+  Tensor<Scalar, 1> out(6);
+  Tensor<Scalar, 1> expected_out(6);
+  out.setZero();
+
+  in_x(0) = Scalar(1);
+  in_x(1) = Scalar(1.5);
+  in_x(2) = Scalar(4);
+  in_x(3) = Scalar(-10.5);
+  in_x(4) = Scalar(10000.5);
+  in_x(5) = Scalar(3);
+  
+  in_q(0) = Scalar(1.2345);
+  in_q(1) = Scalar(2);
+  in_q(2) = Scalar(1.5);
+  in_q(3) = Scalar(3);
+  in_q(4) = Scalar(1.0001);
+  in_q(5) = Scalar(-2.5);
+
+  expected_out(0) = std::numeric_limits<Scalar>::infinity();
+  expected_out(1) = Scalar(1.61237534869);
+  expected_out(2) = Scalar(0.234848505667);
+  expected_out(3) = Scalar(1.03086757337e-5);
+  expected_out(4) = Scalar(0.367879440865);
+  expected_out(5) = Scalar(0.054102025820864097);
+
+  std::size_t bytes = in_x.size() * sizeof(Scalar);
+
+  Scalar* d_in_x;
+  Scalar* d_in_q;
+  Scalar* d_out;
+  cudaMalloc((void**)(&d_in_x), bytes);
+  cudaMalloc((void**)(&d_in_q), bytes);
+  cudaMalloc((void**)(&d_out), bytes);
+
+  cudaMemcpy(d_in_x, in_x.data(), bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in_q, in_q.data(), bytes, cudaMemcpyHostToDevice);
+  
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_in_x(d_in_x, 6);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_in_q(d_in_q, 6);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_out(d_out, 6);
+
+  gpu_out.device(gpu_device) = gpu_in_x.zeta(gpu_in_q);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  VERIFY_IS_EQUAL(out(0), expected_out(0));
+  VERIFY((std::isnan)(out(3)));
+
+  for (int i = 1; i < 6; ++i) {
+    if (i != 3) {
+      VERIFY_IS_APPROX(out(i), expected_out(i));
+    }
+  }
+
+  cudaFree(d_in_x);
+  cudaFree(d_in_q);
+  cudaFree(d_out);
+}
+
+template <typename Scalar>
+void test_cuda_polygamma()
+{
+  Tensor<Scalar, 1> in_x(7);
+  Tensor<Scalar, 1> in_n(7);
+  Tensor<Scalar, 1> out(7);
+  Tensor<Scalar, 1> expected_out(7);
+  out.setZero();
+
+  in_n(0) = Scalar(1);
+  in_n(1) = Scalar(1);
+  in_n(2) = Scalar(1);
+  in_n(3) = Scalar(17);
+  in_n(4) = Scalar(31);
+  in_n(5) = Scalar(28);
+  in_n(6) = Scalar(8);
+  
+  in_x(0) = Scalar(2);
+  in_x(1) = Scalar(3);
+  in_x(2) = Scalar(25.5);
+  in_x(3) = Scalar(4.7);
+  in_x(4) = Scalar(11.8);
+  in_x(5) = Scalar(17.7);
+  in_x(6) = Scalar(30.2);
+
+  expected_out(0) = Scalar(0.644934066848);
+  expected_out(1) = Scalar(0.394934066848);
+  expected_out(2) = Scalar(0.0399946696496);
+  expected_out(3) = Scalar(293.334565435);
+  expected_out(4) = Scalar(0.445487887616);
+  expected_out(5) = Scalar(-2.47810300902e-07);
+  expected_out(6) = Scalar(-8.29668781082e-09);
+
+  std::size_t bytes = in_x.size() * sizeof(Scalar);
+
+  Scalar* d_in_x;
+  Scalar* d_in_n;
+  Scalar* d_out;
+  cudaMalloc((void**)(&d_in_x), bytes);
+  cudaMalloc((void**)(&d_in_n), bytes);
+  cudaMalloc((void**)(&d_out), bytes);
+
+  cudaMemcpy(d_in_x, in_x.data(), bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in_n, in_n.data(), bytes, cudaMemcpyHostToDevice);
+  
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_in_x(d_in_x, 7);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_in_n(d_in_n, 7);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_out(d_out, 7);
+
+  gpu_out.device(gpu_device) = gpu_in_n.polygamma(gpu_in_x);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 7; ++i) {
+    VERIFY_IS_APPROX(out(i), expected_out(i));
+  }
+
+  cudaFree(d_in_x);
+  cudaFree(d_in_n);
+  cudaFree(d_out);
+}
+
+template <typename Scalar>
+void test_cuda_igamma()
+{
+  Tensor<Scalar, 2> a(6, 6);
+  Tensor<Scalar, 2> x(6, 6);
+  Tensor<Scalar, 2> out(6, 6);
+  out.setZero();
+
+  Scalar a_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
+  Scalar x_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
+
+  for (int i = 0; i < 6; ++i) {
+    for (int j = 0; j < 6; ++j) {
+      a(i, j) = a_s[i];
+      x(i, j) = x_s[j];
+    }
+  }
+
+  Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
+  Scalar igamma_s[][6] = {{0.0, nan, nan, nan, nan, nan},
+                          {0.0, 0.6321205588285578, 0.7768698398515702,
+                           0.9816843611112658, 9.999500016666262e-05, 1.0},
+                          {0.0, 0.4275932955291202, 0.608374823728911,
+                           0.9539882943107686, 7.522076445089201e-07, 1.0},
+                          {0.0, 0.01898815687615381, 0.06564245437845008,
+                           0.5665298796332909, 4.166333347221828e-18, 1.0},
+                          {0.0, 0.9999780593618628, 0.9999899967080838,
+                           0.9999996219837988, 0.9991370418689945, 1.0},
+                          {0.0, 0.0, 0.0, 0.0, 0.0, 0.5042041932513908}};
+
+
+
+  std::size_t bytes = a.size() * sizeof(Scalar);
+
+  Scalar* d_a;
+  Scalar* d_x;
+  Scalar* d_out;
+  assert(cudaMalloc((void**)(&d_a), bytes) == cudaSuccess);
+  assert(cudaMalloc((void**)(&d_x), bytes) == cudaSuccess);
+  assert(cudaMalloc((void**)(&d_out), bytes) == cudaSuccess);
+
+  cudaMemcpy(d_a, a.data(), bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_x, x.data(), bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_a(d_a, 6, 6);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_x(d_x, 6, 6);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_out(d_out, 6, 6);
+
+  gpu_out.device(gpu_device) = gpu_a.igamma(gpu_x);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 6; ++i) {
+    for (int j = 0; j < 6; ++j) {
+      if ((std::isnan)(igamma_s[i][j])) {
+        VERIFY((std::isnan)(out(i, j)));
+      } else {
+        VERIFY_IS_APPROX(out(i, j), igamma_s[i][j]);
+      }
+    }
+  }
+
+  cudaFree(d_a);
+  cudaFree(d_x);
+  cudaFree(d_out);
+}
+
+template <typename Scalar>
+void test_cuda_igammac()
+{
+  Tensor<Scalar, 2> a(6, 6);
+  Tensor<Scalar, 2> x(6, 6);
+  Tensor<Scalar, 2> out(6, 6);
+  out.setZero();
+
+  Scalar a_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
+  Scalar x_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
+
+  for (int i = 0; i < 6; ++i) {
+    for (int j = 0; j < 6; ++j) {
+      a(i, j) = a_s[i];
+      x(i, j) = x_s[j];
+    }
+  }
+
+  Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
+  Scalar igammac_s[][6] = {{nan, nan, nan, nan, nan, nan},
+                           {1.0, 0.36787944117144233, 0.22313016014842982,
+                            0.018315638888734182, 0.9999000049998333, 0.0},
+                           {1.0, 0.5724067044708798, 0.3916251762710878,
+                            0.04601170568923136, 0.9999992477923555, 0.0},
+                           {1.0, 0.9810118431238462, 0.9343575456215499,
+                            0.4334701203667089, 1.0, 0.0},
+                           {1.0, 2.1940638138146658e-05, 1.0003291916285e-05,
+                            3.7801620118431334e-07, 0.0008629581310054535,
+                            0.0},
+                           {1.0, 1.0, 1.0, 1.0, 1.0, 0.49579580674813944}};
+
+  std::size_t bytes = a.size() * sizeof(Scalar);
+
+  Scalar* d_a;
+  Scalar* d_x;
+  Scalar* d_out;
+  cudaMalloc((void**)(&d_a), bytes);
+  cudaMalloc((void**)(&d_x), bytes);
+  cudaMalloc((void**)(&d_out), bytes);
+
+  cudaMemcpy(d_a, a.data(), bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_x, x.data(), bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_a(d_a, 6, 6);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_x(d_x, 6, 6);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_out(d_out, 6, 6);
+
+  gpu_out.device(gpu_device) = gpu_a.igammac(gpu_x);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 6; ++i) {
+    for (int j = 0; j < 6; ++j) {
+      if ((std::isnan)(igammac_s[i][j])) {
+        VERIFY((std::isnan)(out(i, j)));
+      } else {
+        VERIFY_IS_APPROX(out(i, j), igammac_s[i][j]);
+      }
+    }
+  }
+
+  cudaFree(d_a);
+  cudaFree(d_x);
+  cudaFree(d_out);
+}
+
+template <typename Scalar>
+void test_cuda_erf(const Scalar stddev)
+{
+  Tensor<Scalar, 2> in(72,97);
+  in.setRandom();
+  in *= in.constant(stddev);
+  Tensor<Scalar, 2> out(72,97);
+  out.setZero();
+
+  std::size_t bytes = in.size() * sizeof(Scalar);
+
+  Scalar* d_in;
+  Scalar* d_out;
+  assert(cudaMalloc((void**)(&d_in), bytes) == cudaSuccess);
+  assert(cudaMalloc((void**)(&d_out), bytes) == cudaSuccess);
+
+  cudaMemcpy(d_in, in.data(), bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_in(d_in, 72, 97);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_out(d_out, 72, 97);
+
+  gpu_out.device(gpu_device) = gpu_in.erf();
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 72; ++i) {
+    for (int j = 0; j < 97; ++j) {
+      VERIFY_IS_APPROX(out(i,j), (std::erf)(in(i,j)));
+    }
+  }
+
+  cudaFree(d_in);
+  cudaFree(d_out);
+}
+
+template <typename Scalar>
+void test_cuda_erfc(const Scalar stddev)
+{
+  Tensor<Scalar, 2> in(72,97);
+  in.setRandom();
+  in *= in.constant(stddev);
+  Tensor<Scalar, 2> out(72,97);
+  out.setZero();
+
+  std::size_t bytes = in.size() * sizeof(Scalar);
+
+  Scalar* d_in;
+  Scalar* d_out;
+  cudaMalloc((void**)(&d_in), bytes);
+  cudaMalloc((void**)(&d_out), bytes);
+
+  cudaMemcpy(d_in, in.data(), bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_in(d_in, 72, 97);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 2> > gpu_out(d_out, 72, 97);
+
+  gpu_out.device(gpu_device) = gpu_in.erfc();
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 0; i < 72; ++i) {
+    for (int j = 0; j < 97; ++j) {
+      VERIFY_IS_APPROX(out(i,j), (std::erfc)(in(i,j)));
+    }
+  }
+
+  cudaFree(d_in);
+  cudaFree(d_out);
+}
+
+template <typename Scalar>
+void test_cuda_betainc()
+{
+  Tensor<Scalar, 1> in_x(125);
+  Tensor<Scalar, 1> in_a(125);
+  Tensor<Scalar, 1> in_b(125);
+  Tensor<Scalar, 1> out(125);
+  Tensor<Scalar, 1> expected_out(125);
+  out.setZero();
+
+  Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
+
+  Array<Scalar, 1, Dynamic> x(125);
+  Array<Scalar, 1, Dynamic> a(125);
+  Array<Scalar, 1, Dynamic> b(125);
+  Array<Scalar, 1, Dynamic> v(125);
+
+  a << 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+      0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
+      0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
+      0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379, 999.999, 999.999,
+      999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
+      999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
+      999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999;
+
+  b << 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379, 0.999,
+      0.999, 0.999, 0.999, 0.999, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379, 999.999, 999.999,
+      999.999, 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 999.999, 999.999, 999.999, 999.999, 999.999, 0.0, 0.0,
+      0.0, 0.0, 0.0, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379, 0.999,
+      0.999, 0.999, 0.999, 0.999, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379, 999.999, 999.999,
+      999.999, 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 999.999, 999.999, 999.999, 999.999, 999.999, 0.0, 0.0,
+      0.0, 0.0, 0.0, 0.03062277660168379, 0.03062277660168379,
+      0.03062277660168379, 0.03062277660168379, 0.03062277660168379, 0.999,
+      0.999, 0.999, 0.999, 0.999, 31.62177660168379, 31.62177660168379,
+      31.62177660168379, 31.62177660168379, 31.62177660168379, 999.999, 999.999,
+      999.999, 999.999, 999.999;
+
+  x << -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8,
+      1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
+      0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
+      0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
+      0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1,
+      -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8,
+      1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
+      0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
+      0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1;
+
+  v << nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
+      nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
+      nan, nan, 0.47972119876364683, 0.5, 0.5202788012363533, nan, nan,
+      0.9518683957740043, 0.9789663010413743, 0.9931729188073435, nan, nan,
+      0.999995949033062, 0.9999999999993698, 0.9999999999999999, nan, nan,
+      0.9999999999999999, 0.9999999999999999, 0.9999999999999999, nan, nan, nan,
+      nan, nan, nan, nan, 0.006827081192655869, 0.0210336989586256,
+      0.04813160422599567, nan, nan, 0.20014344256217678, 0.5000000000000001,
+      0.7998565574378232, nan, nan, 0.9991401428435834, 0.999999999698403,
+      0.9999999999999999, nan, nan, 0.9999999999999999, 0.9999999999999999,
+      0.9999999999999999, nan, nan, nan, nan, nan, nan, nan,
+      1.0646600232370887e-25, 6.301722877826246e-13, 4.050966937974938e-06, nan,
+      nan, 7.864342668429763e-23, 3.015969667594166e-10, 0.0008598571564165444,
+      nan, nan, 6.031987710123844e-08, 0.5000000000000007, 0.9999999396801229,
+      nan, nan, 0.9999999999999999, 0.9999999999999999, 0.9999999999999999, nan,
+      nan, nan, nan, nan, nan, nan, 0.0, 7.029920380986636e-306,
+      2.2450728208591345e-101, nan, nan, 0.0, 9.275871147869727e-302,
+      1.2232913026152827e-97, nan, nan, 0.0, 3.0891393081932924e-252,
+      2.9303043666183996e-60, nan, nan, 2.248913486879199e-196,
+      0.5000000000004947, 0.9999999999999999, nan;
+
+  for (int i = 0; i < 125; ++i) {
+    in_x(i) = x(i);
+    in_a(i) = a(i);
+    in_b(i) = b(i);
+    expected_out(i) = v(i);
+  }
+
+  std::size_t bytes = in_x.size() * sizeof(Scalar);
+
+  Scalar* d_in_x;
+  Scalar* d_in_a;
+  Scalar* d_in_b;
+  Scalar* d_out;
+  cudaMalloc((void**)(&d_in_x), bytes);
+  cudaMalloc((void**)(&d_in_a), bytes);
+  cudaMalloc((void**)(&d_in_b), bytes);
+  cudaMalloc((void**)(&d_out), bytes);
+
+  cudaMemcpy(d_in_x, in_x.data(), bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in_a, in_a.data(), bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in_b, in_b.data(), bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_in_x(d_in_x, 125);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_in_a(d_in_a, 125);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_in_b(d_in_b, 125);
+  Eigen::TensorMap<Eigen::Tensor<Scalar, 1> > gpu_out(d_out, 125);
+
+  gpu_out.device(gpu_device) = betainc(gpu_in_a, gpu_in_b, gpu_in_x);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  for (int i = 1; i < 125; ++i) {
+    if ((std::isnan)(expected_out(i))) {
+      VERIFY((std::isnan)(out(i)));
+    } else {
+      VERIFY_IS_APPROX(out(i), expected_out(i));
+    }
+  }
+
+  cudaFree(d_in_x);
+  cudaFree(d_in_a);
+  cudaFree(d_in_b);
+  cudaFree(d_out);
+}
+
+
+void test_cxx11_tensor_cuda()
+{
+  CALL_SUBTEST_1(test_cuda_nullary());
+  CALL_SUBTEST_1(test_cuda_elementwise_small());
+  CALL_SUBTEST_1(test_cuda_elementwise());
+  CALL_SUBTEST_1(test_cuda_props());
+  CALL_SUBTEST_1(test_cuda_reduction());
+  CALL_SUBTEST_2(test_cuda_contraction<ColMajor>());
+  CALL_SUBTEST_2(test_cuda_contraction<RowMajor>());
+  CALL_SUBTEST_3(test_cuda_convolution_1d<ColMajor>());
+  CALL_SUBTEST_3(test_cuda_convolution_1d<RowMajor>());
+  CALL_SUBTEST_3(test_cuda_convolution_inner_dim_col_major_1d());
+  CALL_SUBTEST_3(test_cuda_convolution_inner_dim_row_major_1d());
+  CALL_SUBTEST_3(test_cuda_convolution_2d<ColMajor>());
+  CALL_SUBTEST_3(test_cuda_convolution_2d<RowMajor>());
+  CALL_SUBTEST_3(test_cuda_convolution_3d<ColMajor>());
+  CALL_SUBTEST_3(test_cuda_convolution_3d<RowMajor>());
+
+#if __cplusplus > 199711L
+  // std::erf, std::erfc, and so on where only added in c++11. We use them
+  // as a golden reference to validate the results produced by Eigen. Therefore
+  // we can only run these tests if we use a c++11 compiler.
+  CALL_SUBTEST_4(test_cuda_lgamma<float>(1.0f));
+  CALL_SUBTEST_4(test_cuda_lgamma<float>(100.0f));
+  CALL_SUBTEST_4(test_cuda_lgamma<float>(0.01f));
+  CALL_SUBTEST_4(test_cuda_lgamma<float>(0.001f));
+
+  CALL_SUBTEST_4(test_cuda_lgamma<double>(1.0));
+  CALL_SUBTEST_4(test_cuda_lgamma<double>(100.0));
+  CALL_SUBTEST_4(test_cuda_lgamma<double>(0.01));
+  CALL_SUBTEST_4(test_cuda_lgamma<double>(0.001));
+
+  CALL_SUBTEST_4(test_cuda_erf<float>(1.0f));
+  CALL_SUBTEST_4(test_cuda_erf<float>(100.0f));
+  CALL_SUBTEST_4(test_cuda_erf<float>(0.01f));
+  CALL_SUBTEST_4(test_cuda_erf<float>(0.001f));
+
+  CALL_SUBTEST_4(test_cuda_erfc<float>(1.0f));
+  // CALL_SUBTEST(test_cuda_erfc<float>(100.0f));
+  CALL_SUBTEST_4(test_cuda_erfc<float>(5.0f)); // CUDA erfc lacks precision for large inputs
+  CALL_SUBTEST_4(test_cuda_erfc<float>(0.01f));
+  CALL_SUBTEST_4(test_cuda_erfc<float>(0.001f));
+
+  CALL_SUBTEST_4(test_cuda_erf<double>(1.0));
+  CALL_SUBTEST_4(test_cuda_erf<double>(100.0));
+  CALL_SUBTEST_4(test_cuda_erf<double>(0.01));
+  CALL_SUBTEST_4(test_cuda_erf<double>(0.001));
+
+  CALL_SUBTEST_4(test_cuda_erfc<double>(1.0));
+  // CALL_SUBTEST(test_cuda_erfc<double>(100.0));
+  CALL_SUBTEST_4(test_cuda_erfc<double>(5.0)); // CUDA erfc lacks precision for large inputs
+  CALL_SUBTEST_4(test_cuda_erfc<double>(0.01));
+  CALL_SUBTEST_4(test_cuda_erfc<double>(0.001));
+
+  CALL_SUBTEST_5(test_cuda_digamma<float>());
+  CALL_SUBTEST_5(test_cuda_digamma<double>());
+
+  CALL_SUBTEST_5(test_cuda_polygamma<float>());
+  CALL_SUBTEST_5(test_cuda_polygamma<double>());
+
+  CALL_SUBTEST_5(test_cuda_zeta<float>());
+  CALL_SUBTEST_5(test_cuda_zeta<double>());
+
+  CALL_SUBTEST_5(test_cuda_igamma<float>());
+  CALL_SUBTEST_5(test_cuda_igammac<float>());
+
+  CALL_SUBTEST_5(test_cuda_igamma<double>());
+  CALL_SUBTEST_5(test_cuda_igammac<double>());
+
+  CALL_SUBTEST_6(test_cuda_betainc<float>());
+  CALL_SUBTEST_6(test_cuda_betainc<double>());
+#endif
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_custom_index.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_custom_index.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_custom_index.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_custom_index.cpp
@@ -0,0 +1,100 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <limits>
+#include <map>
+
+#include <Eigen/Dense>
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+
+template <int DataLayout>
+static void test_map_as_index()
+{
+#ifdef EIGEN_HAS_SFINAE
+  Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
+  tensor.setRandom();
+
+  using NormalIndex = DSizes<ptrdiff_t, 4>;
+  using CustomIndex = std::map<ptrdiff_t, ptrdiff_t>;
+  CustomIndex coeffC;
+  coeffC[0] = 1;
+  coeffC[1] = 2;
+  coeffC[2] = 4;
+  coeffC[3] = 1;
+  NormalIndex coeff(1,2,4,1);
+
+  VERIFY_IS_EQUAL(tensor.coeff(coeffC), tensor.coeff(coeff));
+  VERIFY_IS_EQUAL(tensor.coeffRef(coeffC), tensor.coeffRef(coeff));
+#endif
+}
+
+
+template <int DataLayout>
+static void test_matrix_as_index()
+{
+#ifdef EIGEN_HAS_SFINAE
+  Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
+  tensor.setRandom();
+
+  using NormalIndex = DSizes<ptrdiff_t, 4>;
+  using CustomIndex = Matrix<unsigned int, 4, 1>;
+  CustomIndex coeffC(1,2,4,1);
+  NormalIndex coeff(1,2,4,1);
+
+  VERIFY_IS_EQUAL(tensor.coeff(coeffC), tensor.coeff(coeff));
+  VERIFY_IS_EQUAL(tensor.coeffRef(coeffC), tensor.coeffRef(coeff));
+#endif
+}
+
+
+template <int DataLayout>
+static void test_varlist_as_index()
+{
+#ifdef EIGEN_HAS_SFINAE
+  Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
+  tensor.setRandom();
+
+  DSizes<ptrdiff_t, 4> coeff(1,2,4,1);
+
+  VERIFY_IS_EQUAL(tensor.coeff({1,2,4,1}), tensor.coeff(coeff));
+  VERIFY_IS_EQUAL(tensor.coeffRef({1,2,4,1}), tensor.coeffRef(coeff));
+#endif
+}
+
+
+template <int DataLayout>
+static void test_sizes_as_index()
+{
+#ifdef EIGEN_HAS_SFINAE
+  Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
+  tensor.setRandom();
+
+  DSizes<ptrdiff_t, 4> coeff(1,2,4,1);
+  Sizes<1,2,4,1> coeffC;
+
+  VERIFY_IS_EQUAL(tensor.coeff(coeffC), tensor.coeff(coeff));
+  VERIFY_IS_EQUAL(tensor.coeffRef(coeffC), tensor.coeffRef(coeff));
+#endif
+}
+
+
+void test_cxx11_tensor_custom_index() {
+  test_map_as_index<ColMajor>();
+  test_map_as_index<RowMajor>();
+  test_matrix_as_index<ColMajor>();
+  test_matrix_as_index<RowMajor>();
+  test_varlist_as_index<ColMajor>();
+  test_varlist_as_index<RowMajor>();
+  test_sizes_as_index<ColMajor>();
+  test_sizes_as_index<RowMajor>();
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_custom_op.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_custom_op.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_custom_op.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_custom_op.cpp
@@ -0,0 +1,111 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+
+struct InsertZeros {
+  DSizes<DenseIndex, 2> dimensions(const Tensor<float, 2>& input) const {
+    DSizes<DenseIndex, 2> result;
+    result[0] = input.dimension(0) * 2;
+    result[1] = input.dimension(1) * 2;
+    return result;
+  }
+
+  template <typename Output, typename Device>
+  void eval(const Tensor<float, 2>& input, Output& output, const Device& device) const
+  {
+    array<DenseIndex, 2> strides;
+    strides[0] = 2;
+    strides[1] = 2;
+    output.stride(strides).device(device) = input;
+
+    Eigen::DSizes<DenseIndex, 2> offsets(1,1);
+    Eigen::DSizes<DenseIndex, 2> extents(output.dimension(0)-1, output.dimension(1)-1);
+    output.slice(offsets, extents).stride(strides).device(device) = input.constant(0.0f);
+  }
+};
+
+static void test_custom_unary_op()
+{
+  Tensor<float, 2> tensor(3,5);
+  tensor.setRandom();
+
+  Tensor<float, 2> result = tensor.customOp(InsertZeros());
+  VERIFY_IS_EQUAL(result.dimension(0), 6);
+  VERIFY_IS_EQUAL(result.dimension(1), 10);
+
+  for (int i = 0; i < 6; i+=2) {
+    for (int j = 0; j < 10; j+=2) {
+      VERIFY_IS_EQUAL(result(i, j), tensor(i/2, j/2));
+    }
+  }
+  for (int i = 1; i < 6; i+=2) {
+    for (int j = 1; j < 10; j+=2) {
+      VERIFY_IS_EQUAL(result(i, j), 0);
+    }
+  }
+}
+
+
+struct BatchMatMul {
+  DSizes<DenseIndex, 3> dimensions(const Tensor<float, 3>& input1, const Tensor<float, 3>& input2) const {
+    DSizes<DenseIndex, 3> result;
+    result[0] = input1.dimension(0);
+    result[1] = input2.dimension(1);
+    result[2] = input2.dimension(2);
+    return result;
+  }
+
+  template <typename Output, typename Device>
+  void eval(const Tensor<float, 3>& input1, const Tensor<float, 3>& input2,
+            Output& output, const Device& device) const
+  {
+    typedef Tensor<float, 3>::DimensionPair DimPair;
+    array<DimPair, 1> dims;
+    dims[0] = DimPair(1, 0);
+    for (int i = 0; i < output.dimension(2); ++i) {
+      output.template chip<2>(i).device(device) = input1.chip<2>(i).contract(input2.chip<2>(i), dims);
+    }
+  }
+};
+
+
+static void test_custom_binary_op()
+{
+  Tensor<float, 3> tensor1(2,3,5);
+  tensor1.setRandom();
+  Tensor<float, 3> tensor2(3,7,5);
+  tensor2.setRandom();
+
+  Tensor<float, 3> result = tensor1.customOp(tensor2, BatchMatMul());
+  for (int i = 0; i < 5; ++i) {
+    typedef Tensor<float, 3>::DimensionPair DimPair;
+    array<DimPair, 1> dims;
+    dims[0] = DimPair(1, 0);
+    Tensor<float, 2> reference = tensor1.chip<2>(i).contract(tensor2.chip<2>(i), dims);
+    TensorRef<Tensor<float, 2> > val = result.chip<2>(i);
+    for (int j = 0; j < 2; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(val(j, k), reference(j, k));
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_custom_op()
+{
+  CALL_SUBTEST(test_custom_unary_op());
+  CALL_SUBTEST(test_custom_binary_op());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_device.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_device.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_device.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_device.cu
@@ -0,0 +1,390 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_device
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+// Context for evaluation on cpu
+struct CPUContext {
+  CPUContext(const Eigen::Tensor<float, 3>& in1, Eigen::Tensor<float, 3>& in2, Eigen::Tensor<float, 3>& out) : in1_(in1), in2_(in2), out_(out), kernel_1d_(2), kernel_2d_(2,2), kernel_3d_(2,2,2) {
+    kernel_1d_(0) = 3.14f;
+    kernel_1d_(1) = 2.7f;
+
+    kernel_2d_(0,0) = 3.14f;
+    kernel_2d_(1,0) = 2.7f;
+    kernel_2d_(0,1) = 0.2f;
+    kernel_2d_(1,1) = 7.0f;
+
+    kernel_3d_(0,0,0) = 3.14f;
+    kernel_3d_(0,1,0) = 2.7f;
+    kernel_3d_(0,0,1) = 0.2f;
+    kernel_3d_(0,1,1) = 7.0f;
+    kernel_3d_(1,0,0) = -1.0f;
+    kernel_3d_(1,1,0) = -0.3f;
+    kernel_3d_(1,0,1) = -0.7f;
+    kernel_3d_(1,1,1) = -0.5f;
+  }
+
+  const Eigen::DefaultDevice& device() const { return cpu_device_; }
+
+  const Eigen::Tensor<float, 3>& in1() const { return in1_; }
+  const Eigen::Tensor<float, 3>& in2() const { return in2_; }
+  Eigen::Tensor<float, 3>& out() { return out_; }
+  const Eigen::Tensor<float, 1>& kernel1d() const { return kernel_1d_; }
+  const Eigen::Tensor<float, 2>& kernel2d() const { return kernel_2d_; }
+  const Eigen::Tensor<float, 3>& kernel3d() const { return kernel_3d_; }
+
+ private:
+  const Eigen::Tensor<float, 3>& in1_;
+  const Eigen::Tensor<float, 3>& in2_;
+  Eigen::Tensor<float, 3>& out_;
+
+  Eigen::Tensor<float, 1> kernel_1d_;
+  Eigen::Tensor<float, 2> kernel_2d_;
+  Eigen::Tensor<float, 3> kernel_3d_;
+
+  Eigen::DefaultDevice cpu_device_;
+};
+
+
+// Context for evaluation on GPU
+struct GPUContext {
+  GPUContext(const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in1, Eigen::TensorMap<Eigen::Tensor<float, 3> >& in2, Eigen::TensorMap<Eigen::Tensor<float, 3> >& out) : in1_(in1), in2_(in2), out_(out), gpu_device_(&stream_) {
+    assert(cudaMalloc((void**)(&kernel_1d_), 2*sizeof(float)) == cudaSuccess);
+    float kernel_1d_val[] = {3.14f, 2.7f};
+    assert(cudaMemcpy(kernel_1d_, kernel_1d_val, 2*sizeof(float), cudaMemcpyHostToDevice) == cudaSuccess);
+
+    assert(cudaMalloc((void**)(&kernel_2d_), 4*sizeof(float)) == cudaSuccess);
+    float kernel_2d_val[] = {3.14f, 2.7f, 0.2f, 7.0f};
+    assert(cudaMemcpy(kernel_2d_, kernel_2d_val, 4*sizeof(float), cudaMemcpyHostToDevice) == cudaSuccess);
+
+    assert(cudaMalloc((void**)(&kernel_3d_), 8*sizeof(float)) == cudaSuccess);
+    float kernel_3d_val[] = {3.14f, -1.0f, 2.7f, -0.3f, 0.2f, -0.7f, 7.0f, -0.5f};
+    assert(cudaMemcpy(kernel_3d_, kernel_3d_val, 8*sizeof(float), cudaMemcpyHostToDevice) == cudaSuccess);
+  }
+  ~GPUContext() {
+    assert(cudaFree(kernel_1d_) == cudaSuccess);
+    assert(cudaFree(kernel_2d_) == cudaSuccess);
+    assert(cudaFree(kernel_3d_) == cudaSuccess);
+  }
+
+  const Eigen::GpuDevice& device() const { return gpu_device_; }
+
+  const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in1() const { return in1_; }
+  const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in2() const { return in2_; }
+  Eigen::TensorMap<Eigen::Tensor<float, 3> >& out() { return out_; }
+  Eigen::TensorMap<Eigen::Tensor<float, 1> > kernel1d() const { return Eigen::TensorMap<Eigen::Tensor<float, 1> >(kernel_1d_, 2); }
+  Eigen::TensorMap<Eigen::Tensor<float, 2> > kernel2d() const { return Eigen::TensorMap<Eigen::Tensor<float, 2> >(kernel_2d_, 2, 2); }
+  Eigen::TensorMap<Eigen::Tensor<float, 3> > kernel3d() const { return Eigen::TensorMap<Eigen::Tensor<float, 3> >(kernel_3d_, 2, 2, 2); }
+
+ private:
+  const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in1_;
+  const Eigen::TensorMap<Eigen::Tensor<float, 3> >& in2_;
+  Eigen::TensorMap<Eigen::Tensor<float, 3> >& out_;
+
+  float* kernel_1d_;
+  float* kernel_2d_;
+  float* kernel_3d_;
+
+  Eigen::CudaStreamDevice stream_;
+  Eigen::GpuDevice gpu_device_;
+};
+
+
+// The actual expression to evaluate
+template <typename Context>
+void test_contextual_eval(Context* context)
+{
+  context->out().device(context->device()) = context->in1() + context->in2() * 3.14f + context->in1().constant(2.718f);
+}
+
+template <typename Context>
+void test_forced_contextual_eval(Context* context)
+{
+  context->out().device(context->device()) = (context->in1() + context->in2()).eval() * 3.14f + context->in1().constant(2.718f);
+}
+
+template <typename Context>
+void test_compound_assignment(Context* context)
+{
+  context->out().device(context->device()) = context->in1().constant(2.718f);
+  context->out().device(context->device()) += context->in1() + context->in2() * 3.14f;
+}
+
+
+template <typename Context>
+void test_contraction(Context* context)
+{
+  Eigen::array<std::pair<int, int>, 2> dims;
+  dims[0] = std::make_pair(1, 1);
+  dims[1] = std::make_pair(2, 2);
+
+  Eigen::array<int, 2> shape(40, 50*70);
+
+  Eigen::DSizes<int, 2> indices(0,0);
+  Eigen::DSizes<int, 2> sizes(40,40);
+
+  context->out().reshape(shape).slice(indices, sizes).device(context->device()) = context->in1().contract(context->in2(), dims);
+}
+
+
+template <typename Context>
+void test_1d_convolution(Context* context)
+{
+  Eigen::DSizes<int, 3> indices(0,0,0);
+  Eigen::DSizes<int, 3> sizes(40,49,70);
+
+  Eigen::array<int, 1> dims(1);
+  context->out().slice(indices, sizes).device(context->device()) = context->in1().convolve(context->kernel1d(), dims);
+}
+
+template <typename Context>
+void test_2d_convolution(Context* context)
+{
+  Eigen::DSizes<int, 3> indices(0,0,0);
+  Eigen::DSizes<int, 3> sizes(40,49,69);
+
+  Eigen::array<int, 2> dims(1,2);
+  context->out().slice(indices, sizes).device(context->device()) = context->in1().convolve(context->kernel2d(), dims);
+}
+
+template <typename Context>
+void test_3d_convolution(Context* context)
+{
+  Eigen::DSizes<int, 3> indices(0,0,0);
+  Eigen::DSizes<int, 3> sizes(39,49,69);
+
+  Eigen::array<int, 3> dims(0,1,2);
+  context->out().slice(indices, sizes).device(context->device()) = context->in1().convolve(context->kernel3d(), dims);
+}
+
+
+void test_cpu() {
+  Eigen::Tensor<float, 3> in1(40,50,70);
+  Eigen::Tensor<float, 3> in2(40,50,70);
+  Eigen::Tensor<float, 3> out(40,50,70);
+
+  in1 = in1.random() + in1.constant(10.0f);
+  in2 = in2.random() + in2.constant(10.0f);
+
+  CPUContext context(in1, in2, out);
+  test_contextual_eval(&context);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 50; ++j) {
+      for (int k = 0; k < 70; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), in1(i,j,k) + in2(i,j,k) * 3.14f + 2.718f);
+      }
+    }
+  }
+
+  test_forced_contextual_eval(&context);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 50; ++j) {
+      for (int k = 0; k < 70; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), (in1(i,j,k) + in2(i,j,k)) * 3.14f + 2.718f);
+      }
+    }
+  }
+
+  test_compound_assignment(&context);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 50; ++j) {
+      for (int k = 0; k < 70; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), in1(i,j,k) + in2(i,j,k) * 3.14f + 2.718f);
+      }
+    }
+  }
+
+  test_contraction(&context);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 40; ++j) {
+      const float result = out(i,j,0);
+      float expected = 0;
+      for (int k = 0; k < 50; ++k) {
+        for (int l = 0; l < 70; ++l) {
+          expected += in1(i, k, l) * in2(j, k, l);
+        }
+      }
+      VERIFY_IS_APPROX(expected, result);
+    }
+  }
+
+  test_1d_convolution(&context);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 49; ++j) {
+      for (int k = 0; k < 70; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), (in1(i,j,k) * 3.14f + in1(i,j+1,k) * 2.7f));
+      }
+    }
+  }
+
+  test_2d_convolution(&context);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 49; ++j) {
+      for (int k = 0; k < 69; ++k) {
+        const float result = out(i,j,k);
+        const float expected = (in1(i,j,k) * 3.14f + in1(i,j+1,k) * 2.7f) +
+                               (in1(i,j,k+1) * 0.2f + in1(i,j+1,k+1) * 7.0f);
+        if (fabs(expected) < 1e-4f && fabs(result) < 1e-4f) {
+          continue;
+        }
+        VERIFY_IS_APPROX(expected, result);
+      }
+    }
+  }
+
+  test_3d_convolution(&context);
+  for (int i = 0; i < 39; ++i) {
+    for (int j = 0; j < 49; ++j) {
+      for (int k = 0; k < 69; ++k) {
+        const float result = out(i,j,k);
+        const float expected = (in1(i,j,k) * 3.14f + in1(i,j+1,k) * 2.7f +
+                                in1(i,j,k+1) * 0.2f + in1(i,j+1,k+1) * 7.0f) +
+                               (in1(i+1,j,k) * -1.0f + in1(i+1,j+1,k) * -0.3f +
+                                in1(i+1,j,k+1) * -0.7f + in1(i+1,j+1,k+1) * -0.5f);
+        if (fabs(expected) < 1e-4f && fabs(result) < 1e-4f) {
+          continue;
+        }
+        VERIFY_IS_APPROX(expected, result);
+      }
+    }
+  }
+}
+
+void test_gpu() {
+  Eigen::Tensor<float, 3> in1(40,50,70);
+  Eigen::Tensor<float, 3> in2(40,50,70);
+  Eigen::Tensor<float, 3> out(40,50,70);
+  in1 = in1.random() + in1.constant(10.0f);
+  in2 = in2.random() + in2.constant(10.0f);
+
+  std::size_t in1_bytes = in1.size() * sizeof(float);
+  std::size_t in2_bytes = in2.size() * sizeof(float);
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_in1;
+  float* d_in2;
+  float* d_out;
+  cudaMalloc((void**)(&d_in1), in1_bytes);
+  cudaMalloc((void**)(&d_in2), in2_bytes);
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  cudaMemcpy(d_in1, in1.data(), in1_bytes, cudaMemcpyHostToDevice);
+  cudaMemcpy(d_in2, in2.data(), in2_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 3> > gpu_in1(d_in1, 40,50,70);
+  Eigen::TensorMap<Eigen::Tensor<float, 3> > gpu_in2(d_in2, 40,50,70);
+  Eigen::TensorMap<Eigen::Tensor<float, 3> > gpu_out(d_out, 40,50,70);
+
+  GPUContext context(gpu_in1, gpu_in2, gpu_out);
+  test_contextual_eval(&context);
+  assert(cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost) == cudaSuccess);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 50; ++j) {
+      for (int k = 0; k < 70; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), in1(i,j,k) + in2(i,j,k) * 3.14f + 2.718f);
+      }
+    }
+  }
+
+  test_forced_contextual_eval(&context);
+  assert(cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost) == cudaSuccess);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 50; ++j) {
+      for (int k = 0; k < 70; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), (in1(i,j,k) + in2(i,j,k)) * 3.14f + 2.718f);
+      }
+    }
+  }
+
+  test_compound_assignment(&context);
+  assert(cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost) == cudaSuccess);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 50; ++j) {
+      for (int k = 0; k < 70; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), in1(i,j,k) + in2(i,j,k) * 3.14f + 2.718f);
+      }
+    }
+  }
+
+  test_contraction(&context);
+  assert(cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost) == cudaSuccess);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 40; ++j) {
+      const float result = out(i,j,0);
+      float expected = 0;
+      for (int k = 0; k < 50; ++k) {
+        for (int l = 0; l < 70; ++l) {
+          expected += in1(i, k, l) * in2(j, k, l);
+        }
+      }
+      VERIFY_IS_APPROX(expected, result);
+    }
+  }
+
+  test_1d_convolution(&context);
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, context.device().stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(context.device().stream()) == cudaSuccess);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 49; ++j) {
+      for (int k = 0; k < 70; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), (in1(i,j,k) * 3.14f + in1(i,j+1,k) * 2.7f));
+      }
+    }
+  }
+
+  test_2d_convolution(&context);
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, context.device().stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(context.device().stream()) == cudaSuccess);
+  for (int i = 0; i < 40; ++i) {
+    for (int j = 0; j < 49; ++j) {
+      for (int k = 0; k < 69; ++k) {
+        const float result = out(i,j,k);
+        const float expected = (in1(i,j,k) * 3.14f + in1(i,j+1,k) * 2.7f +
+                                in1(i,j,k+1) * 0.2f + in1(i,j+1,k+1) * 7.0f);
+        VERIFY_IS_APPROX(expected, result);
+      }
+    }
+  }
+
+  test_3d_convolution(&context);
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, context.device().stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(context.device().stream()) == cudaSuccess);
+  for (int i = 0; i < 39; ++i) {
+    for (int j = 0; j < 49; ++j) {
+      for (int k = 0; k < 69; ++k) {
+       const float result = out(i,j,k);
+        const float expected = (in1(i,j,k) * 3.14f + in1(i,j+1,k) * 2.7f +
+                                in1(i,j,k+1) * 0.2f + in1(i,j+1,k+1) * 7.0f +
+                                in1(i+1,j,k) * -1.0f + in1(i+1,j+1,k) * -0.3f +
+                                in1(i+1,j,k+1) * -0.7f + in1(i+1,j+1,k+1) * -0.5f);
+        VERIFY_IS_APPROX(expected, result);
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_device()
+{
+  CALL_SUBTEST_1(test_cpu());
+  CALL_SUBTEST_2(test_gpu());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_device_sycl.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_device_sycl.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_device_sycl.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_device_sycl.cpp
@@ -0,0 +1,31 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_device_sycl
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_SYCL
+
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+void test_device_sycl(const Eigen::SyclDevice &sycl_device) {
+  std::cout <<"Helo from ComputeCpp: the requested device exists and the device name is : "
+    << sycl_device.m_queue.get_device(). template get_info<cl::sycl::info::device::name>() <<std::endl;;
+}
+void test_cxx11_tensor_device_sycl() {
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_device_sycl(sycl_device));
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_dimension.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_dimension.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_dimension.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_dimension.cpp
@@ -0,0 +1,69 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+
+static void test_dynamic_size()
+{
+  Eigen::DSizes<int, 3> dimensions(2,3,7);
+
+  VERIFY_IS_EQUAL((int)Eigen::internal::array_get<0>(dimensions), 2);
+  VERIFY_IS_EQUAL((int)Eigen::internal::array_get<1>(dimensions), 3);
+  VERIFY_IS_EQUAL((int)Eigen::internal::array_get<2>(dimensions), 7);
+  VERIFY_IS_EQUAL((int)dimensions.TotalSize(), 2*3*7);
+  VERIFY_IS_EQUAL((int)dimensions[0], 2);
+  VERIFY_IS_EQUAL((int)dimensions[1], 3);
+  VERIFY_IS_EQUAL((int)dimensions[2], 7);
+}
+
+static void test_fixed_size()
+{
+  Eigen::Sizes<2,3,7> dimensions;
+
+  VERIFY_IS_EQUAL((int)Eigen::internal::array_get<0>(dimensions), 2);
+  VERIFY_IS_EQUAL((int)Eigen::internal::array_get<1>(dimensions), 3);
+  VERIFY_IS_EQUAL((int)Eigen::internal::array_get<2>(dimensions), 7);
+  VERIFY_IS_EQUAL((int)dimensions.TotalSize(), 2*3*7);
+}
+
+static void test_match()
+{
+  Eigen::DSizes<unsigned int, 3> dyn((unsigned int)2,(unsigned int)3,(unsigned int)7);
+  Eigen::Sizes<2,3,7> stat;
+  VERIFY_IS_EQUAL(Eigen::dimensions_match(dyn, stat), true);
+
+  Eigen::DSizes<int, 3> dyn1(2,3,7);
+  Eigen::DSizes<int, 2> dyn2(2,3);
+  VERIFY_IS_EQUAL(Eigen::dimensions_match(dyn1, dyn2), false);
+}
+
+static void test_rank_zero()
+{
+  Eigen::Sizes<> scalar;
+  VERIFY_IS_EQUAL((int)scalar.TotalSize(), 1);
+  VERIFY_IS_EQUAL((int)scalar.rank(), 0);
+  VERIFY_IS_EQUAL((int)internal::array_prod(scalar), 1);
+
+  Eigen::DSizes<ptrdiff_t, 0> dscalar;
+  VERIFY_IS_EQUAL((int)dscalar.TotalSize(), 1);
+  VERIFY_IS_EQUAL((int)dscalar.rank(), 0);
+}
+
+void test_cxx11_tensor_dimension()
+{
+  CALL_SUBTEST(test_dynamic_size());
+  CALL_SUBTEST(test_fixed_size());
+  CALL_SUBTEST(test_match());
+  CALL_SUBTEST(test_rank_zero());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_empty.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_empty.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_empty.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_empty.cpp
@@ -0,0 +1,40 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+
+static void test_empty_tensor()
+{
+  Tensor<float, 2> source;
+  Tensor<float, 2> tgt1 = source;
+  Tensor<float, 2> tgt2(source);
+  Tensor<float, 2> tgt3;
+  tgt3 = tgt1;
+  tgt3 = tgt2;
+}
+
+static void test_empty_fixed_size_tensor()
+{
+  TensorFixedSize<float, Sizes<0> > source;
+  TensorFixedSize<float, Sizes<0> > tgt1 = source;
+  TensorFixedSize<float, Sizes<0> > tgt2(source);
+  TensorFixedSize<float, Sizes<0> > tgt3;
+  tgt3 = tgt1;
+  tgt3 = tgt2;
+}
+
+
+void test_cxx11_tensor_empty()
+{
+   CALL_SUBTEST(test_empty_tensor());
+   CALL_SUBTEST(test_empty_fixed_size_tensor());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_expr.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_expr.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_expr.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_expr.cpp
@@ -0,0 +1,314 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_1d()
+{
+  Tensor<float, 1> vec1(6);
+  Tensor<float, 1, RowMajor> vec2(6);
+
+  vec1(0) = 4.0;  vec2(0) = 0.0;
+  vec1(1) = 8.0;  vec2(1) = 1.0;
+  vec1(2) = 15.0; vec2(2) = 2.0;
+  vec1(3) = 16.0; vec2(3) = 3.0;
+  vec1(4) = 23.0; vec2(4) = 4.0;
+  vec1(5) = 42.0; vec2(5) = 5.0;
+
+  float data3[6];
+  TensorMap<Tensor<float, 1>> vec3(data3, 6);
+  vec3 = vec1.sqrt();
+  float data4[6];
+  TensorMap<Tensor<float, 1, RowMajor>> vec4(data4, 6);
+  vec4 = vec2.square();
+  float data5[6];
+  TensorMap<Tensor<float, 1, RowMajor>> vec5(data5, 6);
+  vec5 = vec2.cube();
+
+  VERIFY_IS_APPROX(vec3(0), sqrtf(4.0));
+  VERIFY_IS_APPROX(vec3(1), sqrtf(8.0));
+  VERIFY_IS_APPROX(vec3(2), sqrtf(15.0));
+  VERIFY_IS_APPROX(vec3(3), sqrtf(16.0));
+  VERIFY_IS_APPROX(vec3(4), sqrtf(23.0));
+  VERIFY_IS_APPROX(vec3(5), sqrtf(42.0));
+
+  VERIFY_IS_APPROX(vec4(0), 0.0f);
+  VERIFY_IS_APPROX(vec4(1), 1.0f);
+  VERIFY_IS_APPROX(vec4(2), 2.0f * 2.0f);
+  VERIFY_IS_APPROX(vec4(3), 3.0f * 3.0f);
+  VERIFY_IS_APPROX(vec4(4), 4.0f * 4.0f);
+  VERIFY_IS_APPROX(vec4(5), 5.0f * 5.0f);
+
+  VERIFY_IS_APPROX(vec5(0), 0.0f);
+  VERIFY_IS_APPROX(vec5(1), 1.0f);
+  VERIFY_IS_APPROX(vec5(2), 2.0f * 2.0f * 2.0f);
+  VERIFY_IS_APPROX(vec5(3), 3.0f * 3.0f * 3.0f);
+  VERIFY_IS_APPROX(vec5(4), 4.0f * 4.0f * 4.0f);
+  VERIFY_IS_APPROX(vec5(5), 5.0f * 5.0f * 5.0f);
+
+  vec3 = vec1 + vec2;
+  VERIFY_IS_APPROX(vec3(0), 4.0f + 0.0f);
+  VERIFY_IS_APPROX(vec3(1), 8.0f + 1.0f);
+  VERIFY_IS_APPROX(vec3(2), 15.0f + 2.0f);
+  VERIFY_IS_APPROX(vec3(3), 16.0f + 3.0f);
+  VERIFY_IS_APPROX(vec3(4), 23.0f + 4.0f);
+  VERIFY_IS_APPROX(vec3(5), 42.0f + 5.0f);
+}
+
+static void test_2d()
+{
+  float data1[6];
+  TensorMap<Tensor<float, 2>> mat1(data1, 2, 3);
+  float data2[6];
+  TensorMap<Tensor<float, 2, RowMajor>> mat2(data2, 2, 3);
+
+  mat1(0,0) = 0.0;
+  mat1(0,1) = 1.0;
+  mat1(0,2) = 2.0;
+  mat1(1,0) = 3.0;
+  mat1(1,1) = 4.0;
+  mat1(1,2) = 5.0;
+
+  mat2(0,0) = -0.0;
+  mat2(0,1) = -1.0;
+  mat2(0,2) = -2.0;
+  mat2(1,0) = -3.0;
+  mat2(1,1) = -4.0;
+  mat2(1,2) = -5.0;
+
+  Tensor<float, 2> mat3(2,3);
+  Tensor<float, 2, RowMajor> mat4(2,3);
+  mat3 = mat1.abs();
+  mat4 = mat2.abs();
+
+  VERIFY_IS_APPROX(mat3(0,0), 0.0f);
+  VERIFY_IS_APPROX(mat3(0,1), 1.0f);
+  VERIFY_IS_APPROX(mat3(0,2), 2.0f);
+  VERIFY_IS_APPROX(mat3(1,0), 3.0f);
+  VERIFY_IS_APPROX(mat3(1,1), 4.0f);
+  VERIFY_IS_APPROX(mat3(1,2), 5.0f);
+
+  VERIFY_IS_APPROX(mat4(0,0), 0.0f);
+  VERIFY_IS_APPROX(mat4(0,1), 1.0f);
+  VERIFY_IS_APPROX(mat4(0,2), 2.0f);
+  VERIFY_IS_APPROX(mat4(1,0), 3.0f);
+  VERIFY_IS_APPROX(mat4(1,1), 4.0f);
+  VERIFY_IS_APPROX(mat4(1,2), 5.0f);
+}
+
+static void test_3d()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3, RowMajor> mat2(2,3,7);
+
+  float val = 1.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        mat2(i,j,k) = val;
+        val += 1.0f;
+      }
+    }
+  }
+
+  Tensor<float, 3> mat3(2,3,7);
+  mat3 = mat1 + mat1;
+  Tensor<float, 3, RowMajor> mat4(2,3,7);
+  mat4 = mat2 * 3.14f;
+  Tensor<float, 3> mat5(2,3,7);
+  mat5 = mat1.inverse().log();
+  Tensor<float, 3, RowMajor> mat6(2,3,7);
+  mat6 = mat2.pow(0.5f) * 3.14f;
+  Tensor<float, 3> mat7(2,3,7);
+  mat7 = mat1.cwiseMax(mat5 * 2.0f).exp();
+  Tensor<float, 3, RowMajor> mat8(2,3,7);
+  mat8 = (-mat2).exp() * 3.14f;
+  Tensor<float, 3, RowMajor> mat9(2,3,7);
+  mat9 = mat2 + 3.14f;
+  Tensor<float, 3, RowMajor> mat10(2,3,7);
+  mat10 = mat2 - 3.14f;
+  Tensor<float, 3, RowMajor> mat11(2,3,7);
+  mat11 = mat2 / 3.14f;
+
+  val = 1.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat3(i,j,k), val + val);
+        VERIFY_IS_APPROX(mat4(i,j,k), val * 3.14f);
+        VERIFY_IS_APPROX(mat5(i,j,k), logf(1.0f/val));
+        VERIFY_IS_APPROX(mat6(i,j,k), sqrtf(val) * 3.14f);
+        VERIFY_IS_APPROX(mat7(i,j,k), expf((std::max)(val, mat5(i,j,k) * 2.0f)));
+        VERIFY_IS_APPROX(mat8(i,j,k), expf(-val) * 3.14f);
+        VERIFY_IS_APPROX(mat9(i,j,k), val + 3.14f);
+        VERIFY_IS_APPROX(mat10(i,j,k), val - 3.14f);
+        VERIFY_IS_APPROX(mat11(i,j,k), val / 3.14f);
+        val += 1.0f;
+      }
+    }
+  }
+}
+
+static void test_constants()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<float, 3> mat3(2,3,7);
+
+  float val = 1.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        val += 1.0f;
+      }
+    }
+  }
+  mat2 = mat1.constant(3.14f);
+  mat3 = mat1.cwiseMax(7.3f).exp();
+
+  val = 1.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat2(i,j,k), 3.14f);
+        VERIFY_IS_APPROX(mat3(i,j,k), expf((std::max)(val, 7.3f)));
+        val += 1.0f;
+      }
+    }
+  }
+}
+
+static void test_boolean()
+{
+  Tensor<int, 1> vec(6);
+  std::copy_n(std::begin({0, 1, 2, 3, 4, 5}), 6, vec.data());
+
+  // Test ||.
+  Tensor<bool, 1> bool1 = vec < vec.constant(1) || vec > vec.constant(4);
+  VERIFY_IS_EQUAL(bool1[0], true);
+  VERIFY_IS_EQUAL(bool1[1], false);
+  VERIFY_IS_EQUAL(bool1[2], false);
+  VERIFY_IS_EQUAL(bool1[3], false);
+  VERIFY_IS_EQUAL(bool1[4], false);
+  VERIFY_IS_EQUAL(bool1[5], true);
+
+  // Test &&, including cast of operand vec.
+  Tensor<bool, 1> bool2 = vec.cast<bool>() && vec < vec.constant(4);
+  VERIFY_IS_EQUAL(bool2[0], false);
+  VERIFY_IS_EQUAL(bool2[1], true);
+  VERIFY_IS_EQUAL(bool2[2], true);
+  VERIFY_IS_EQUAL(bool2[3], true);
+  VERIFY_IS_EQUAL(bool2[4], false);
+  VERIFY_IS_EQUAL(bool2[5], false);
+
+  // Compilation tests:
+  // Test Tensor<bool> against results of cast or comparison; verifies that
+  // CoeffReturnType is set to match Op return type of bool for Unary and Binary
+  // Ops.
+  Tensor<bool, 1> bool3 = vec.cast<bool>() && bool2;
+  bool3 = vec < vec.constant(4) && bool2;
+}
+
+static void test_functors()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<float, 3> mat3(2,3,7);
+
+  float val = 1.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        val += 1.0f;
+      }
+    }
+  }
+  mat2 = mat1.inverse().unaryExpr(&asinf);
+  mat3 = mat1.unaryExpr(&tanhf);
+
+  val = 1.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat2(i,j,k), asinf(1.0f / mat1(i,j,k)));
+        VERIFY_IS_APPROX(mat3(i,j,k), tanhf(mat1(i,j,k)));
+        val += 1.0f;
+      }
+    }
+  }
+}
+
+static void test_type_casting()
+{
+  Tensor<bool, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<double, 3> mat3(2,3,7);
+  mat1.setRandom();
+  mat2.setRandom();
+
+  mat3 = mat1.cast<double>();
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat3(i,j,k), mat1(i,j,k) ? 1.0 : 0.0);
+      }
+    }
+  }
+
+  mat3 = mat2.cast<double>();
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat3(i,j,k), static_cast<double>(mat2(i,j,k)));
+      }
+    }
+  }
+}
+
+static void test_select()
+{
+  Tensor<float, 3> selector(2,3,7);
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<float, 3> result(2,3,7);
+
+  selector.setRandom();
+  mat1.setRandom();
+  mat2.setRandom();
+  result = (selector > selector.constant(0.5f)).select(mat1, mat2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(result(i,j,k), (selector(i,j,k) > 0.5f) ? mat1(i,j,k) : mat2(i,j,k));
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_expr()
+{
+  CALL_SUBTEST(test_1d());
+  CALL_SUBTEST(test_2d());
+  CALL_SUBTEST(test_3d());
+  CALL_SUBTEST(test_constants());
+  CALL_SUBTEST(test_boolean());
+  CALL_SUBTEST(test_functors());
+  CALL_SUBTEST(test_type_casting());
+  CALL_SUBTEST(test_select());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_fft.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_fft.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_fft.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_fft.cpp
@@ -0,0 +1,273 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Jianwei Cui <thucjw@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template <int DataLayout>
+static void test_fft_2D_golden() {
+  Tensor<float, 2, DataLayout> input(2, 3);
+  input(0, 0) = 1;
+  input(0, 1) = 2;
+  input(0, 2) = 3;
+  input(1, 0) = 4;
+  input(1, 1) = 5;
+  input(1, 2) = 6;
+
+  array<ptrdiff_t, 2> fft;
+  fft[0] = 0;
+  fft[1] = 1;
+
+  Tensor<std::complex<float>, 2, DataLayout> output = input.template fft<Eigen::BothParts, Eigen::FFT_FORWARD>(fft);
+
+  std::complex<float> output_golden[6]; // in ColMajor order
+  output_golden[0] = std::complex<float>(21, 0);
+  output_golden[1] = std::complex<float>(-9, 0);
+  output_golden[2] = std::complex<float>(-3, 1.73205);
+  output_golden[3] = std::complex<float>( 0, 0);
+  output_golden[4] = std::complex<float>(-3, -1.73205);
+  output_golden[5] = std::complex<float>(0 ,0);
+
+  std::complex<float> c_offset = std::complex<float>(1.0, 1.0);
+
+  if (DataLayout == ColMajor) {
+    VERIFY_IS_APPROX(output(0) + c_offset, output_golden[0] + c_offset);
+    VERIFY_IS_APPROX(output(1) + c_offset, output_golden[1] + c_offset);
+    VERIFY_IS_APPROX(output(2) + c_offset, output_golden[2] + c_offset);
+    VERIFY_IS_APPROX(output(3) + c_offset, output_golden[3] + c_offset);
+    VERIFY_IS_APPROX(output(4) + c_offset, output_golden[4] + c_offset);
+    VERIFY_IS_APPROX(output(5) + c_offset, output_golden[5] + c_offset);
+  }
+  else {
+    VERIFY_IS_APPROX(output(0)+ c_offset, output_golden[0]+ c_offset);
+    VERIFY_IS_APPROX(output(1)+ c_offset, output_golden[2]+ c_offset);
+    VERIFY_IS_APPROX(output(2)+ c_offset, output_golden[4]+ c_offset);
+    VERIFY_IS_APPROX(output(3)+ c_offset, output_golden[1]+ c_offset);
+    VERIFY_IS_APPROX(output(4)+ c_offset, output_golden[3]+ c_offset);
+    VERIFY_IS_APPROX(output(5)+ c_offset, output_golden[5]+ c_offset);
+  }
+}
+
+static void test_fft_complex_input_golden() {
+  Tensor<std::complex<float>, 1, ColMajor> input(5);
+  input(0) = std::complex<float>(1, 1);
+  input(1) = std::complex<float>(2, 2);
+  input(2) = std::complex<float>(3, 3);
+  input(3) = std::complex<float>(4, 4);
+  input(4) = std::complex<float>(5, 5);
+
+  array<ptrdiff_t, 1> fft;
+  fft[0] = 0;
+
+  Tensor<std::complex<float>, 1, ColMajor> forward_output_both_parts = input.fft<BothParts, FFT_FORWARD>(fft);
+  Tensor<std::complex<float>, 1, ColMajor> reverse_output_both_parts = input.fft<BothParts, FFT_REVERSE>(fft);
+
+  Tensor<float, 1, ColMajor> forward_output_real_part = input.fft<RealPart, FFT_FORWARD>(fft);
+  Tensor<float, 1, ColMajor> reverse_output_real_part = input.fft<RealPart, FFT_REVERSE>(fft);
+
+  Tensor<float, 1, ColMajor> forward_output_imag_part = input.fft<ImagPart, FFT_FORWARD>(fft);
+  Tensor<float, 1, ColMajor> reverse_output_imag_part = input.fft<ImagPart, FFT_REVERSE>(fft);
+
+  VERIFY_IS_EQUAL(forward_output_both_parts.dimension(0), input.dimension(0));
+  VERIFY_IS_EQUAL(reverse_output_both_parts.dimension(0), input.dimension(0));
+
+  VERIFY_IS_EQUAL(forward_output_real_part.dimension(0), input.dimension(0));
+  VERIFY_IS_EQUAL(reverse_output_real_part.dimension(0), input.dimension(0));
+
+  VERIFY_IS_EQUAL(forward_output_imag_part.dimension(0), input.dimension(0));
+  VERIFY_IS_EQUAL(reverse_output_imag_part.dimension(0), input.dimension(0));
+
+  std::complex<float> forward_golden_result[5];
+  std::complex<float> reverse_golden_result[5];
+
+  forward_golden_result[0] = std::complex<float>(15.000000000000000,+15.000000000000000);
+  forward_golden_result[1] = std::complex<float>(-5.940954801177935, +0.940954801177934);
+  forward_golden_result[2] = std::complex<float>(-3.312299240582266, -1.687700759417735);
+  forward_golden_result[3] = std::complex<float>(-1.687700759417735, -3.312299240582266);
+  forward_golden_result[4] = std::complex<float>( 0.940954801177934, -5.940954801177935);
+
+  reverse_golden_result[0] = std::complex<float>( 3.000000000000000, + 3.000000000000000);
+  reverse_golden_result[1] = std::complex<float>( 0.188190960235587, - 1.188190960235587);
+  reverse_golden_result[2] = std::complex<float>(-0.337540151883547, - 0.662459848116453);
+  reverse_golden_result[3] = std::complex<float>(-0.662459848116453, - 0.337540151883547);
+  reverse_golden_result[4] = std::complex<float>(-1.188190960235587, + 0.188190960235587);
+
+  for(int i = 0; i < 5; ++i) {
+    VERIFY_IS_APPROX(forward_output_both_parts(i), forward_golden_result[i]);
+    VERIFY_IS_APPROX(forward_output_real_part(i), forward_golden_result[i].real());
+    VERIFY_IS_APPROX(forward_output_imag_part(i), forward_golden_result[i].imag());
+  }
+
+  for(int i = 0; i < 5; ++i) {
+    VERIFY_IS_APPROX(reverse_output_both_parts(i), reverse_golden_result[i]);
+    VERIFY_IS_APPROX(reverse_output_real_part(i), reverse_golden_result[i].real());
+    VERIFY_IS_APPROX(reverse_output_imag_part(i), reverse_golden_result[i].imag());
+  }
+}
+
+static void test_fft_real_input_golden() {
+  Tensor<float, 1, ColMajor> input(5);
+  input(0) = 1.0;
+  input(1) = 2.0;
+  input(2) = 3.0;
+  input(3) = 4.0;
+  input(4) = 5.0;
+
+  array<ptrdiff_t, 1> fft;
+  fft[0] = 0;
+
+  Tensor<std::complex<float>, 1, ColMajor> forward_output_both_parts = input.fft<BothParts, FFT_FORWARD>(fft);
+  Tensor<std::complex<float>, 1, ColMajor> reverse_output_both_parts = input.fft<BothParts, FFT_REVERSE>(fft);
+
+  Tensor<float, 1, ColMajor> forward_output_real_part = input.fft<RealPart, FFT_FORWARD>(fft);
+  Tensor<float, 1, ColMajor> reverse_output_real_part = input.fft<RealPart, FFT_REVERSE>(fft);
+
+  Tensor<float, 1, ColMajor> forward_output_imag_part = input.fft<ImagPart, FFT_FORWARD>(fft);
+  Tensor<float, 1, ColMajor> reverse_output_imag_part = input.fft<ImagPart, FFT_REVERSE>(fft);
+
+  VERIFY_IS_EQUAL(forward_output_both_parts.dimension(0), input.dimension(0));
+  VERIFY_IS_EQUAL(reverse_output_both_parts.dimension(0), input.dimension(0));
+
+  VERIFY_IS_EQUAL(forward_output_real_part.dimension(0), input.dimension(0));
+  VERIFY_IS_EQUAL(reverse_output_real_part.dimension(0), input.dimension(0));
+
+  VERIFY_IS_EQUAL(forward_output_imag_part.dimension(0), input.dimension(0));
+  VERIFY_IS_EQUAL(reverse_output_imag_part.dimension(0), input.dimension(0));
+
+  std::complex<float> forward_golden_result[5];
+  std::complex<float> reverse_golden_result[5];
+
+
+  forward_golden_result[0] = std::complex<float>(  15, 0);
+  forward_golden_result[1] = std::complex<float>(-2.5, +3.44095480117793);
+  forward_golden_result[2] = std::complex<float>(-2.5, +0.81229924058227);
+  forward_golden_result[3] = std::complex<float>(-2.5, -0.81229924058227);
+  forward_golden_result[4] = std::complex<float>(-2.5, -3.44095480117793);
+
+  reverse_golden_result[0] = std::complex<float>( 3.0, 0);
+  reverse_golden_result[1] = std::complex<float>(-0.5, -0.688190960235587);
+  reverse_golden_result[2] = std::complex<float>(-0.5, -0.162459848116453);
+  reverse_golden_result[3] = std::complex<float>(-0.5, +0.162459848116453);
+  reverse_golden_result[4] = std::complex<float>(-0.5, +0.688190960235587);
+
+  std::complex<float> c_offset(1.0, 1.0);
+  float r_offset = 1.0;
+
+  for(int i = 0; i < 5; ++i) {
+    VERIFY_IS_APPROX(forward_output_both_parts(i) + c_offset, forward_golden_result[i] + c_offset);
+    VERIFY_IS_APPROX(forward_output_real_part(i)  + r_offset, forward_golden_result[i].real() + r_offset);
+    VERIFY_IS_APPROX(forward_output_imag_part(i)  + r_offset, forward_golden_result[i].imag() + r_offset);
+  }
+
+  for(int i = 0; i < 5; ++i) {
+    VERIFY_IS_APPROX(reverse_output_both_parts(i) + c_offset, reverse_golden_result[i] + c_offset);
+    VERIFY_IS_APPROX(reverse_output_real_part(i)  + r_offset, reverse_golden_result[i].real() + r_offset);
+    VERIFY_IS_APPROX(reverse_output_imag_part(i)  + r_offset, reverse_golden_result[i].imag() + r_offset);
+  }
+}
+
+
+template <int DataLayout, typename RealScalar, bool isComplexInput, int FFTResultType, int FFTDirection, int TensorRank>
+static void test_fft_real_input_energy() {
+
+  Eigen::DSizes<ptrdiff_t, TensorRank> dimensions;
+  ptrdiff_t total_size = 1;
+  for (int i = 0; i < TensorRank; ++i) {
+    dimensions[i] = rand() % 20 + 1;
+    total_size *= dimensions[i];
+  }
+  const DSizes<ptrdiff_t, TensorRank> arr = dimensions;
+
+  typedef typename internal::conditional<isComplexInput == true, std::complex<RealScalar>, RealScalar>::type InputScalar;
+
+  Tensor<InputScalar, TensorRank, DataLayout> input;
+  input.resize(arr);
+  input.setRandom();
+
+  array<ptrdiff_t, TensorRank> fft;
+  for (int i = 0; i < TensorRank; ++i) {
+    fft[i] = i;
+  }
+
+  typedef typename internal::conditional<FFTResultType == Eigen::BothParts, std::complex<RealScalar>, RealScalar>::type OutputScalar;
+  Tensor<OutputScalar, TensorRank, DataLayout> output;
+  output = input.template fft<FFTResultType, FFTDirection>(fft);
+
+  for (int i = 0; i < TensorRank; ++i) {
+    VERIFY_IS_EQUAL(output.dimension(i), input.dimension(i));
+  }
+
+  RealScalar energy_original = 0.0;
+  RealScalar energy_after_fft = 0.0;
+
+  for (int i = 0; i < total_size; ++i) {
+    energy_original += numext::abs2(input(i));
+  }
+
+  for (int i = 0; i < total_size; ++i) {
+    energy_after_fft += numext::abs2(output(i));
+  }
+
+  if(FFTDirection == FFT_FORWARD) {
+    VERIFY_IS_APPROX(energy_original, energy_after_fft / total_size);
+  }
+  else {
+    VERIFY_IS_APPROX(energy_original, energy_after_fft * total_size);
+  }
+}
+
+void test_cxx11_tensor_fft() {
+    test_fft_complex_input_golden();
+    test_fft_real_input_golden();
+
+    test_fft_2D_golden<ColMajor>();
+    test_fft_2D_golden<RowMajor>();
+
+    test_fft_real_input_energy<ColMajor, float,  true,  Eigen::BothParts, FFT_FORWARD, 1>();
+    test_fft_real_input_energy<ColMajor, double, true,  Eigen::BothParts, FFT_FORWARD, 1>();
+    test_fft_real_input_energy<ColMajor, float,  false,  Eigen::BothParts, FFT_FORWARD, 1>();
+    test_fft_real_input_energy<ColMajor, double, false,  Eigen::BothParts, FFT_FORWARD, 1>();
+
+    test_fft_real_input_energy<ColMajor, float,  true,  Eigen::BothParts, FFT_FORWARD, 2>();
+    test_fft_real_input_energy<ColMajor, double, true,  Eigen::BothParts, FFT_FORWARD, 2>();
+    test_fft_real_input_energy<ColMajor, float,  false,  Eigen::BothParts, FFT_FORWARD, 2>();
+    test_fft_real_input_energy<ColMajor, double, false,  Eigen::BothParts, FFT_FORWARD, 2>();
+
+    test_fft_real_input_energy<ColMajor, float,  true,  Eigen::BothParts, FFT_FORWARD, 3>();
+    test_fft_real_input_energy<ColMajor, double, true,  Eigen::BothParts, FFT_FORWARD, 3>();
+    test_fft_real_input_energy<ColMajor, float,  false,  Eigen::BothParts, FFT_FORWARD, 3>();
+    test_fft_real_input_energy<ColMajor, double, false,  Eigen::BothParts, FFT_FORWARD, 3>();
+
+    test_fft_real_input_energy<ColMajor, float,  true,  Eigen::BothParts, FFT_FORWARD, 4>();
+    test_fft_real_input_energy<ColMajor, double, true,  Eigen::BothParts, FFT_FORWARD, 4>();
+    test_fft_real_input_energy<ColMajor, float,  false,  Eigen::BothParts, FFT_FORWARD, 4>();
+    test_fft_real_input_energy<ColMajor, double, false,  Eigen::BothParts, FFT_FORWARD, 4>();
+
+    test_fft_real_input_energy<RowMajor, float,  true,  Eigen::BothParts, FFT_FORWARD, 1>();
+    test_fft_real_input_energy<RowMajor, double, true,  Eigen::BothParts, FFT_FORWARD, 1>();
+    test_fft_real_input_energy<RowMajor, float,  false,  Eigen::BothParts, FFT_FORWARD, 1>();
+    test_fft_real_input_energy<RowMajor, double, false,  Eigen::BothParts, FFT_FORWARD, 1>();
+
+    test_fft_real_input_energy<RowMajor, float,  true,  Eigen::BothParts, FFT_FORWARD, 2>();
+    test_fft_real_input_energy<RowMajor, double, true,  Eigen::BothParts, FFT_FORWARD, 2>();
+    test_fft_real_input_energy<RowMajor, float,  false,  Eigen::BothParts, FFT_FORWARD, 2>();
+    test_fft_real_input_energy<RowMajor, double, false,  Eigen::BothParts, FFT_FORWARD, 2>();
+
+    test_fft_real_input_energy<RowMajor, float,  true,  Eigen::BothParts, FFT_FORWARD, 3>();
+    test_fft_real_input_energy<RowMajor, double, true,  Eigen::BothParts, FFT_FORWARD, 3>();
+    test_fft_real_input_energy<RowMajor, float,  false,  Eigen::BothParts, FFT_FORWARD, 3>();
+    test_fft_real_input_energy<RowMajor, double, false,  Eigen::BothParts, FFT_FORWARD, 3>();
+
+    test_fft_real_input_energy<RowMajor, float,  true,  Eigen::BothParts, FFT_FORWARD, 4>();
+    test_fft_real_input_energy<RowMajor, double, true,  Eigen::BothParts, FFT_FORWARD, 4>();
+    test_fft_real_input_energy<RowMajor, float,  false,  Eigen::BothParts, FFT_FORWARD, 4>();
+    test_fft_real_input_energy<RowMajor, double, false,  Eigen::BothParts, FFT_FORWARD, 4>();
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_fixed_size.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_fixed_size.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_fixed_size.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_fixed_size.cpp
@@ -0,0 +1,261 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+
+static void test_0d()
+{
+  TensorFixedSize<float, Sizes<> > scalar1;
+  TensorFixedSize<float, Sizes<>, RowMajor> scalar2;
+  VERIFY_IS_EQUAL(scalar1.rank(), 0);
+  VERIFY_IS_EQUAL(scalar1.size(), 1);
+  VERIFY_IS_EQUAL(array_prod(scalar1.dimensions()), 1);
+
+  scalar1() = 7.0;
+  scalar2() = 13.0;
+
+  // Test against shallow copy.
+  TensorFixedSize<float, Sizes<> > copy = scalar1;
+  VERIFY_IS_NOT_EQUAL(scalar1.data(), copy.data());
+  VERIFY_IS_APPROX(scalar1(), copy());
+  copy = scalar1;
+  VERIFY_IS_NOT_EQUAL(scalar1.data(), copy.data());
+  VERIFY_IS_APPROX(scalar1(), copy());
+
+  TensorFixedSize<float, Sizes<> > scalar3 = scalar1.sqrt();
+  TensorFixedSize<float, Sizes<>, RowMajor> scalar4 = scalar2.sqrt();
+  VERIFY_IS_EQUAL(scalar3.rank(), 0);
+  VERIFY_IS_APPROX(scalar3(), sqrtf(7.0));
+  VERIFY_IS_APPROX(scalar4(), sqrtf(13.0));
+
+  scalar3 = scalar1 + scalar2;
+  VERIFY_IS_APPROX(scalar3(), 7.0f + 13.0f);
+}
+
+static void test_1d()
+{
+  TensorFixedSize<float, Sizes<6> > vec1;
+  TensorFixedSize<float, Sizes<6>, RowMajor> vec2;
+
+  VERIFY_IS_EQUAL((vec1.size()), 6);
+  //  VERIFY_IS_EQUAL((vec1.dimensions()[0]), 6);
+  //  VERIFY_IS_EQUAL((vec1.dimension(0)), 6);
+
+  vec1(0) = 4.0;  vec2(0) = 0.0;
+  vec1(1) = 8.0;  vec2(1) = 1.0;
+  vec1(2) = 15.0; vec2(2) = 2.0;
+  vec1(3) = 16.0; vec2(3) = 3.0;
+  vec1(4) = 23.0; vec2(4) = 4.0;
+  vec1(5) = 42.0; vec2(5) = 5.0;
+
+  // Test against shallow copy.
+  TensorFixedSize<float, Sizes<6> > copy = vec1;
+  VERIFY_IS_NOT_EQUAL(vec1.data(), copy.data());
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_APPROX(vec1(i), copy(i));
+  }
+  copy = vec1;
+  VERIFY_IS_NOT_EQUAL(vec1.data(), copy.data());
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_APPROX(vec1(i), copy(i));
+  }
+
+  TensorFixedSize<float, Sizes<6> > vec3 = vec1.sqrt();
+  TensorFixedSize<float, Sizes<6>, RowMajor> vec4 = vec2.sqrt();
+
+  VERIFY_IS_EQUAL((vec3.size()), 6);
+  VERIFY_IS_EQUAL(vec3.rank(), 1);
+  //  VERIFY_IS_EQUAL((vec3.dimensions()[0]), 6);
+  //  VERIFY_IS_EQUAL((vec3.dimension(0)), 6);
+
+  VERIFY_IS_APPROX(vec3(0), sqrtf(4.0));
+  VERIFY_IS_APPROX(vec3(1), sqrtf(8.0));
+  VERIFY_IS_APPROX(vec3(2), sqrtf(15.0));
+  VERIFY_IS_APPROX(vec3(3), sqrtf(16.0));
+  VERIFY_IS_APPROX(vec3(4), sqrtf(23.0));
+  VERIFY_IS_APPROX(vec3(5), sqrtf(42.0));
+
+  VERIFY_IS_APPROX(vec4(0), sqrtf(0.0));
+  VERIFY_IS_APPROX(vec4(1), sqrtf(1.0));
+  VERIFY_IS_APPROX(vec4(2), sqrtf(2.0));
+  VERIFY_IS_APPROX(vec4(3), sqrtf(3.0));
+  VERIFY_IS_APPROX(vec4(4), sqrtf(4.0));
+  VERIFY_IS_APPROX(vec4(5), sqrtf(5.0));
+
+  vec3 = vec1 + vec2;
+  VERIFY_IS_APPROX(vec3(0), 4.0f + 0.0f);
+  VERIFY_IS_APPROX(vec3(1), 8.0f + 1.0f);
+  VERIFY_IS_APPROX(vec3(2), 15.0f + 2.0f);
+  VERIFY_IS_APPROX(vec3(3), 16.0f + 3.0f);
+  VERIFY_IS_APPROX(vec3(4), 23.0f + 4.0f);
+  VERIFY_IS_APPROX(vec3(5), 42.0f + 5.0f);
+}
+
+static void test_tensor_map()
+{
+  TensorFixedSize<float, Sizes<6> > vec1;
+  TensorFixedSize<float, Sizes<6>, RowMajor> vec2;
+
+  vec1(0) = 4.0;  vec2(0) = 0.0;
+  vec1(1) = 8.0;  vec2(1) = 1.0;
+  vec1(2) = 15.0; vec2(2) = 2.0;
+  vec1(3) = 16.0; vec2(3) = 3.0;
+  vec1(4) = 23.0; vec2(4) = 4.0;
+  vec1(5) = 42.0; vec2(5) = 5.0;
+
+  float data3[6];
+  TensorMap<TensorFixedSize<float, Sizes<6> > > vec3(data3, 6);
+  vec3 = vec1.sqrt() + vec2;
+
+  VERIFY_IS_APPROX(vec3(0), sqrtf(4.0));
+  VERIFY_IS_APPROX(vec3(1), sqrtf(8.0) + 1.0f);
+  VERIFY_IS_APPROX(vec3(2), sqrtf(15.0) + 2.0f);
+  VERIFY_IS_APPROX(vec3(3), sqrtf(16.0) + 3.0f);
+  VERIFY_IS_APPROX(vec3(4), sqrtf(23.0) + 4.0f);
+  VERIFY_IS_APPROX(vec3(5), sqrtf(42.0) + 5.0f);
+}
+
+static void test_2d()
+{
+  float data1[6];
+  TensorMap<TensorFixedSize<float, Sizes<2, 3> > > mat1(data1,2,3);
+  float data2[6];
+  TensorMap<TensorFixedSize<float, Sizes<2, 3>, RowMajor> > mat2(data2,2,3);
+
+  VERIFY_IS_EQUAL((mat1.size()), 2*3);
+  VERIFY_IS_EQUAL(mat1.rank(), 2);
+  //  VERIFY_IS_EQUAL((mat1.dimension(0)), 2);
+  //  VERIFY_IS_EQUAL((mat1.dimension(1)), 3);
+
+  mat1(0,0) = 0.0;
+  mat1(0,1) = 1.0;
+  mat1(0,2) = 2.0;
+  mat1(1,0) = 3.0;
+  mat1(1,1) = 4.0;
+  mat1(1,2) = 5.0;
+
+  mat2(0,0) = -0.0;
+  mat2(0,1) = -1.0;
+  mat2(0,2) = -2.0;
+  mat2(1,0) = -3.0;
+  mat2(1,1) = -4.0;
+  mat2(1,2) = -5.0;
+
+  TensorFixedSize<float, Sizes<2, 3> > mat3;
+  TensorFixedSize<float, Sizes<2, 3>, RowMajor> mat4;
+  mat3 = mat1.abs();
+  mat4 = mat2.abs();
+
+  VERIFY_IS_EQUAL((mat3.size()), 2*3);
+    //  VERIFY_IS_EQUAL((mat3.dimension(0)), 2);
+    //  VERIFY_IS_EQUAL((mat3.dimension(1)), 3);
+
+  VERIFY_IS_APPROX(mat3(0,0), 0.0f);
+  VERIFY_IS_APPROX(mat3(0,1), 1.0f);
+  VERIFY_IS_APPROX(mat3(0,2), 2.0f);
+  VERIFY_IS_APPROX(mat3(1,0), 3.0f);
+  VERIFY_IS_APPROX(mat3(1,1), 4.0f);
+  VERIFY_IS_APPROX(mat3(1,2), 5.0f);
+
+  VERIFY_IS_APPROX(mat4(0,0), 0.0f);
+  VERIFY_IS_APPROX(mat4(0,1), 1.0f);
+  VERIFY_IS_APPROX(mat4(0,2), 2.0f);
+  VERIFY_IS_APPROX(mat4(1,0), 3.0f);
+  VERIFY_IS_APPROX(mat4(1,1), 4.0f);
+  VERIFY_IS_APPROX(mat4(1,2), 5.0f);
+}
+
+static void test_3d()
+{
+  TensorFixedSize<float, Sizes<2, 3, 7> > mat1;
+  TensorFixedSize<float, Sizes<2, 3, 7>, RowMajor> mat2;
+
+  VERIFY_IS_EQUAL((mat1.size()), 2*3*7);
+  VERIFY_IS_EQUAL(mat1.rank(), 3);
+  //  VERIFY_IS_EQUAL((mat1.dimension(0)), 2);
+  //  VERIFY_IS_EQUAL((mat1.dimension(1)), 3);
+  //  VERIFY_IS_EQUAL((mat1.dimension(2)), 7);
+
+  float val = 0.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        mat2(i,j,k) = val;
+        val += 1.0f;
+      }
+    }
+  }
+
+  TensorFixedSize<float, Sizes<2, 3, 7> > mat3;
+  mat3 = mat1.sqrt();
+  TensorFixedSize<float, Sizes<2, 3, 7>, RowMajor> mat4;
+  mat4 = mat2.sqrt();
+
+  VERIFY_IS_EQUAL((mat3.size()), 2*3*7);
+  //  VERIFY_IS_EQUAL((mat3.dimension(0)), 2);
+  //  VERIFY_IS_EQUAL((mat3.dimension(1)), 3);
+  //  VERIFY_IS_EQUAL((mat3.dimension(2)), 7);
+
+
+  val = 0.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat3(i,j,k), sqrtf(val));
+        VERIFY_IS_APPROX(mat4(i,j,k), sqrtf(val));
+        val += 1.0f;
+      }
+    }
+  }
+}
+
+
+static void test_array()
+{
+  TensorFixedSize<float, Sizes<2, 3, 7> > mat1;
+  float val = 0.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        val += 1.0f;
+      }
+    }
+  }
+
+  TensorFixedSize<float, Sizes<2, 3, 7> > mat3;
+  mat3 = mat1.pow(3.5f);
+
+  val = 0.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat3(i,j,k), powf(val, 3.5f));
+        val += 1.0f;
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_fixed_size()
+{
+  CALL_SUBTEST(test_0d());
+  CALL_SUBTEST(test_1d());
+  CALL_SUBTEST(test_tensor_map());
+  CALL_SUBTEST(test_2d());
+  CALL_SUBTEST(test_3d());
+  CALL_SUBTEST(test_array());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_forced_eval.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_forced_eval.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_forced_eval.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_forced_eval.cpp
@@ -0,0 +1,79 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/Core>
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::MatrixXf;
+using Eigen::Tensor;
+
+static void test_simple()
+{
+  MatrixXf m1(3,3);
+  MatrixXf m2(3,3);
+  m1.setRandom();
+  m2.setRandom();
+
+  TensorMap<Tensor<float, 2> > mat1(m1.data(), 3,3);
+  TensorMap<Tensor<float, 2> > mat2(m2.data(), 3,3);
+
+  Tensor<float, 2> mat3(3,3);
+  mat3 = mat1;
+
+  typedef Tensor<float, 1>::DimensionPair DimPair;
+  Eigen::array<DimPair, 1> dims;
+  dims[0] = DimPair(1, 0);
+
+  mat3 = mat3.contract(mat2, dims).eval();
+
+  VERIFY_IS_APPROX(mat3(0, 0), (m1*m2).eval()(0,0));
+  VERIFY_IS_APPROX(mat3(0, 1), (m1*m2).eval()(0,1));
+  VERIFY_IS_APPROX(mat3(0, 2), (m1*m2).eval()(0,2));
+  VERIFY_IS_APPROX(mat3(1, 0), (m1*m2).eval()(1,0));
+  VERIFY_IS_APPROX(mat3(1, 1), (m1*m2).eval()(1,1));
+  VERIFY_IS_APPROX(mat3(1, 2), (m1*m2).eval()(1,2));
+  VERIFY_IS_APPROX(mat3(2, 0), (m1*m2).eval()(2,0));
+  VERIFY_IS_APPROX(mat3(2, 1), (m1*m2).eval()(2,1));
+  VERIFY_IS_APPROX(mat3(2, 2), (m1*m2).eval()(2,2));
+}
+
+
+static void test_const()
+{
+  MatrixXf input(3,3);
+  input.setRandom();
+  MatrixXf output = input;
+  output.rowwise() -= input.colwise().maxCoeff();
+
+  Eigen::array<int, 1> depth_dim;
+  depth_dim[0] = 0;
+  Tensor<float, 2>::Dimensions dims2d;
+  dims2d[0] = 1;
+  dims2d[1] = 3;
+  Eigen::array<int, 2> bcast;
+  bcast[0] = 3;
+  bcast[1] = 1;
+  const TensorMap<Tensor<const float, 2> > input_tensor(input.data(), 3, 3);
+  Tensor<float, 2> output_tensor= (input_tensor - input_tensor.maximum(depth_dim).eval().reshape(dims2d).broadcast(bcast));
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_APPROX(output(i, j), output_tensor(i, j));
+    }
+  }
+}
+
+
+void test_cxx11_tensor_forced_eval()
+{
+  CALL_SUBTEST(test_simple());
+  CALL_SUBTEST(test_const());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_forced_eval_sycl.cpp
@@ -0,0 +1,70 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_forced_eval_sycl
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_SYCL
+
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+void test_forced_eval_sycl(const Eigen::SyclDevice &sycl_device) {
+
+  int sizeDim1 = 100;
+  int sizeDim2 = 200;
+  int sizeDim3 = 200;
+  Eigen::array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
+  Eigen::Tensor<float, 3> in1(tensorRange);
+  Eigen::Tensor<float, 3> in2(tensorRange);
+  Eigen::Tensor<float, 3> out(tensorRange);
+
+  float * gpu_in1_data  = static_cast<float*>(sycl_device.allocate(in1.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_in2_data  = static_cast<float*>(sycl_device.allocate(in2.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_out_data =  static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
+
+  in1 = in1.random() + in1.constant(10.0f);
+  in2 = in2.random() + in2.constant(10.0f);
+
+  // creating TensorMap from tensor
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_in1(gpu_in1_data, tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_in2(gpu_in2_data, tensorRange);
+  Eigen::TensorMap<Eigen::Tensor<float, 3>> gpu_out(gpu_out_data, tensorRange);
+  sycl_device.memcpyHostToDevice(gpu_in1_data, in1.data(),(in1.dimensions().TotalSize())*sizeof(float));
+  sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in1.dimensions().TotalSize())*sizeof(float));
+  /// c=(a+b)*b
+  gpu_out.device(sycl_device) =(gpu_in1 + gpu_in2).eval() * gpu_in2;
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(out(i, j, k),
+                         (in1(i, j, k) + in2(i, j, k)) * in2(i, j, k));
+      }
+    }
+  }
+  printf("(a+b)*b Test Passed\n");
+  sycl_device.deallocate(gpu_in1_data);
+  sycl_device.deallocate(gpu_in2_data);
+  sycl_device.deallocate(gpu_out_data);
+
+}
+
+void test_cxx11_tensor_forced_eval_sycl() {
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_forced_eval_sycl(sycl_device));
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_generator.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_generator.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_generator.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_generator.cpp
@@ -0,0 +1,91 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+struct Generator1D {
+  Generator1D() { }
+
+  float operator()(const array<Eigen::DenseIndex, 1>& coordinates) const {
+    return coordinates[0];
+  }
+};
+
+template <int DataLayout>
+static void test_1D()
+{
+  Tensor<float, 1> vec(6);
+  Tensor<float, 1> result = vec.generate(Generator1D());
+
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_EQUAL(result(i), i);
+  }
+}
+
+
+struct Generator2D {
+  Generator2D() { }
+
+  float operator()(const array<Eigen::DenseIndex, 2>& coordinates) const {
+    return 3 * coordinates[0] + 11 * coordinates[1];
+  }
+};
+
+template <int DataLayout>
+static void test_2D()
+{
+  Tensor<float, 2> matrix(5, 7);
+  Tensor<float, 2> result = matrix.generate(Generator2D());
+
+  for (int i = 0; i < 5; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      VERIFY_IS_EQUAL(result(i, j), 3*i + 11*j);
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_gaussian()
+{
+  int rows = 32;
+  int cols = 48;
+  array<float, 2> means;
+  means[0] = rows / 2.0f;
+  means[1] = cols / 2.0f;
+  array<float, 2> std_devs;
+  std_devs[0] = 3.14f;
+  std_devs[1] = 2.7f;
+  internal::GaussianGenerator<float, Eigen::DenseIndex, 2> gaussian_gen(means, std_devs);
+
+  Tensor<float, 2> matrix(rows, cols);
+  Tensor<float, 2> result = matrix.generate(gaussian_gen);
+
+  for (int i = 0; i < rows; ++i) {
+    for (int j = 0; j < cols; ++j) {
+      float g_rows = powf(rows/2.0f - i, 2) / (3.14f * 3.14f) * 0.5f;
+      float g_cols = powf(cols/2.0f - j, 2) / (2.7f * 2.7f) * 0.5f;
+      float gaussian = expf(-g_rows - g_cols);
+      VERIFY_IS_EQUAL(result(i, j), gaussian);
+    }
+  }
+}
+
+
+void test_cxx11_tensor_generator()
+{
+  CALL_SUBTEST(test_1D<ColMajor>());
+  CALL_SUBTEST(test_1D<RowMajor>());
+  CALL_SUBTEST(test_2D<ColMajor>());
+  CALL_SUBTEST(test_2D<RowMajor>());
+  CALL_SUBTEST(test_gaussian<ColMajor>());
+  CALL_SUBTEST(test_gaussian<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_ifft.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_ifft.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_ifft.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_ifft.cpp
@@ -0,0 +1,154 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Jianwei Cui <thucjw@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <complex>
+#include <cmath>
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template <int DataLayout>
+static void test_1D_fft_ifft_invariant(int sequence_length) {
+  Tensor<double, 1, DataLayout> tensor(sequence_length);
+  tensor.setRandom();
+
+  array<int, 1> fft;
+  fft[0] = 0;
+
+  Tensor<std::complex<double>, 1, DataLayout> tensor_after_fft;
+  Tensor<std::complex<double>, 1, DataLayout> tensor_after_fft_ifft;
+
+  tensor_after_fft = tensor.template fft<Eigen::BothParts, Eigen::FFT_FORWARD>(fft);
+  tensor_after_fft_ifft = tensor_after_fft.template fft<Eigen::BothParts, Eigen::FFT_REVERSE>(fft);
+
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(0), sequence_length);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(0), sequence_length);
+
+  for (int i = 0; i < sequence_length; ++i) {
+    VERIFY_IS_APPROX(static_cast<float>(tensor(i)), static_cast<float>(std::real(tensor_after_fft_ifft(i))));
+  }
+}
+
+template <int DataLayout>
+static void test_2D_fft_ifft_invariant(int dim0, int dim1) {
+  Tensor<double, 2, DataLayout> tensor(dim0, dim1);
+  tensor.setRandom();
+
+  array<int, 2> fft;
+  fft[0] = 0;
+  fft[1] = 1;
+
+  Tensor<std::complex<double>, 2, DataLayout> tensor_after_fft;
+  Tensor<std::complex<double>, 2, DataLayout> tensor_after_fft_ifft;
+
+  tensor_after_fft = tensor.template fft<Eigen::BothParts, Eigen::FFT_FORWARD>(fft);
+  tensor_after_fft_ifft = tensor_after_fft.template fft<Eigen::BothParts, Eigen::FFT_REVERSE>(fft);
+
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(0), dim0);
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(1), dim1);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(0), dim0);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(1), dim1);
+
+  for (int i = 0; i < dim0; ++i) {
+    for (int j = 0; j < dim1; ++j) {
+      //std::cout << "[" << i << "][" << j << "]" <<  "  Original data: " << tensor(i,j) << " Transformed data:" << tensor_after_fft_ifft(i,j) << std::endl;
+      VERIFY_IS_APPROX(static_cast<float>(tensor(i,j)), static_cast<float>(std::real(tensor_after_fft_ifft(i,j))));
+    }
+  }
+}
+
+template <int DataLayout>
+static void test_3D_fft_ifft_invariant(int dim0, int dim1, int dim2) {
+  Tensor<double, 3, DataLayout> tensor(dim0, dim1, dim2);
+  tensor.setRandom();
+
+  array<int, 3> fft;
+  fft[0] = 0;
+  fft[1] = 1;
+  fft[2] = 2;
+
+  Tensor<std::complex<double>, 3, DataLayout> tensor_after_fft;
+  Tensor<std::complex<double>, 3, DataLayout> tensor_after_fft_ifft;
+
+  tensor_after_fft = tensor.template fft<Eigen::BothParts, Eigen::FFT_FORWARD>(fft);
+  tensor_after_fft_ifft = tensor_after_fft.template fft<Eigen::BothParts, Eigen::FFT_REVERSE>(fft);
+
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(0), dim0);
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(1), dim1);
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(2), dim2);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(0), dim0);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(1), dim1);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(2), dim2);
+
+  for (int i = 0; i < dim0; ++i) {
+    for (int j = 0; j < dim1; ++j) {
+      for (int k = 0; k < dim2; ++k) {
+        VERIFY_IS_APPROX(static_cast<float>(tensor(i,j,k)), static_cast<float>(std::real(tensor_after_fft_ifft(i,j,k))));
+      }
+    }
+  }
+}
+
+template <int DataLayout>
+static void test_sub_fft_ifft_invariant(int dim0, int dim1, int dim2, int dim3) {
+  Tensor<double, 4, DataLayout> tensor(dim0, dim1, dim2, dim3);
+  tensor.setRandom();
+
+  array<int, 2> fft;
+  fft[0] = 2;
+  fft[1] = 0;
+
+  Tensor<std::complex<double>, 4, DataLayout> tensor_after_fft;
+  Tensor<double, 4, DataLayout> tensor_after_fft_ifft;
+
+  tensor_after_fft = tensor.template fft<Eigen::BothParts, Eigen::FFT_FORWARD>(fft);
+  tensor_after_fft_ifft = tensor_after_fft.template fft<Eigen::RealPart, Eigen::FFT_REVERSE>(fft);
+
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(0), dim0);
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(1), dim1);
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(2), dim2);
+  VERIFY_IS_EQUAL(tensor_after_fft.dimension(3), dim3);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(0), dim0);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(1), dim1);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(2), dim2);
+  VERIFY_IS_EQUAL(tensor_after_fft_ifft.dimension(3), dim3);
+
+  for (int i = 0; i < dim0; ++i) {
+    for (int j = 0; j < dim1; ++j) {
+      for (int k = 0; k < dim2; ++k) {
+        for (int l = 0; l < dim3; ++l) {
+          VERIFY_IS_APPROX(static_cast<float>(tensor(i,j,k,l)), static_cast<float>(tensor_after_fft_ifft(i,j,k,l)));
+        }
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_ifft() {
+  CALL_SUBTEST(test_1D_fft_ifft_invariant<ColMajor>(4));
+  CALL_SUBTEST(test_1D_fft_ifft_invariant<ColMajor>(16));
+  CALL_SUBTEST(test_1D_fft_ifft_invariant<ColMajor>(32));
+  CALL_SUBTEST(test_1D_fft_ifft_invariant<ColMajor>(1024*1024));
+
+  CALL_SUBTEST(test_2D_fft_ifft_invariant<ColMajor>(4,4));
+  CALL_SUBTEST(test_2D_fft_ifft_invariant<ColMajor>(8,16));
+  CALL_SUBTEST(test_2D_fft_ifft_invariant<ColMajor>(16,32));
+  CALL_SUBTEST(test_2D_fft_ifft_invariant<ColMajor>(1024,1024));
+
+  CALL_SUBTEST(test_3D_fft_ifft_invariant<ColMajor>(4,4,4));
+  CALL_SUBTEST(test_3D_fft_ifft_invariant<ColMajor>(8,16,32));
+  CALL_SUBTEST(test_3D_fft_ifft_invariant<ColMajor>(16,4,8));
+  CALL_SUBTEST(test_3D_fft_ifft_invariant<ColMajor>(256,256,256));
+
+  CALL_SUBTEST(test_sub_fft_ifft_invariant<ColMajor>(4,4,4,4));
+  CALL_SUBTEST(test_sub_fft_ifft_invariant<ColMajor>(8,16,32,64));
+  CALL_SUBTEST(test_sub_fft_ifft_invariant<ColMajor>(16,4,8,12));
+  CALL_SUBTEST(test_sub_fft_ifft_invariant<ColMajor>(64,64,64,64));
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_image_patch.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_image_patch.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_image_patch.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_image_patch.cpp
@@ -0,0 +1,757 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+void test_simple_patch()
+{
+  Tensor<float, 4> tensor(2,3,5,7);
+  tensor.setRandom();
+  Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
+  VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
+  VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
+  VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
+  VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));
+
+  // Single pixel patch: ColMajor
+  Tensor<float, 5> single_pixel_patch;
+  single_pixel_patch = tensor.extract_image_patches(1, 1);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(0), 2);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(1), 1);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(2), 1);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(3), 3*5);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(4), 7);
+
+  // Single pixel patch: RowMajor
+  Tensor<float, 5, RowMajor> single_pixel_patch_row_major;
+  single_pixel_patch_row_major = tensor_row_major.extract_image_patches(1, 1);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(0), 7);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(1), 3*5);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(2), 1);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(3), 1);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(4), 2);
+
+  for (int i = 0; i < tensor.size(); ++i) {
+    // ColMajor
+    if (tensor.data()[i] != single_pixel_patch.data()[i]) {
+      std::cout << "Mismatch detected at index " << i << " : "
+           << tensor.data()[i] << " vs " << single_pixel_patch.data()[i]
+           << std::endl;
+    }
+    VERIFY_IS_EQUAL(single_pixel_patch.data()[i], tensor.data()[i]);
+    // RowMajor
+    if (tensor_row_major.data()[i] != single_pixel_patch_row_major.data()[i]) {
+      std::cout << "Mismatch detected at index " << i << " : "
+           << tensor.data()[i] << " vs "
+           << single_pixel_patch_row_major.data()[i] << std::endl;
+    }
+    VERIFY_IS_EQUAL(single_pixel_patch_row_major.data()[i],
+                    tensor_row_major.data()[i]);
+    VERIFY_IS_EQUAL(tensor.data()[i], tensor_row_major.data()[i]);
+    VERIFY_IS_EQUAL(single_pixel_patch.data()[i],
+                    single_pixel_patch_row_major.data()[i]);
+  }
+
+  // Entire image patch: ColMajor
+  Tensor<float, 5> entire_image_patch;
+  entire_image_patch = tensor.extract_image_patches(3, 5);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(0), 2);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(1), 3);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(2), 5);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(3), 3*5);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(4), 7);
+
+  // Entire image patch: RowMajor
+  Tensor<float, 5, RowMajor> entire_image_patch_row_major;
+  entire_image_patch_row_major = tensor_row_major.extract_image_patches(3, 5);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(0), 7);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(1), 3*5);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(2), 5);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(3), 3);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(4), 2);
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      int patchId = i+3*j;
+      for (int r = 0; r < 3; ++r) {
+        for (int c = 0; c < 5; ++c) {
+          for (int d = 0; d < 2; ++d) {
+            for (int b = 0; b < 7; ++b) {
+              float expected = 0.0f;
+              float expected_row_major = 0.0f;
+              if (r-1+i >= 0 && c-2+j >= 0 && r-1+i < 3 && c-2+j < 5) {
+                expected = tensor(d, r-1+i, c-2+j, b);
+                expected_row_major = tensor_row_major(b, c-2+j, r-1+i, d);
+              }
+              // ColMajor
+              if (entire_image_patch(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(entire_image_patch(d, r, c, patchId, b), expected);
+              // RowMajor
+              if (entire_image_patch_row_major(b, patchId, c, r, d) !=
+                  expected_row_major) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j
+                     << " r=" << r << " c=" << c << " d=" << d << " b=" << b
+                     << std::endl;
+              }
+              VERIFY_IS_EQUAL(entire_image_patch_row_major(b, patchId, c, r, d),
+                              expected_row_major);
+              // Check that ColMajor and RowMajor agree.
+              VERIFY_IS_EQUAL(expected, expected_row_major);
+            }
+          }
+        }
+      }
+    }
+  }
+
+  // 2D patch: ColMajor
+  Tensor<float, 5> twod_patch;
+  twod_patch = tensor.extract_image_patches(2, 2);
+  VERIFY_IS_EQUAL(twod_patch.dimension(0), 2);
+  VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
+  VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
+  VERIFY_IS_EQUAL(twod_patch.dimension(3), 3*5);
+  VERIFY_IS_EQUAL(twod_patch.dimension(4), 7);
+
+  // 2D patch: RowMajor
+  Tensor<float, 5, RowMajor> twod_patch_row_major;
+  twod_patch_row_major = tensor_row_major.extract_image_patches(2, 2);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(0), 7);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(1), 3*5);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(2), 2);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(3), 2);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(4), 2);
+
+
+  // Based on the calculation described in TensorTraits.h, padding happens to be 0.
+  int row_padding = 0;
+  int col_padding = 0;
+  int stride = 1;
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      int patchId = i+3*j;
+      for (int r = 0; r < 2; ++r) {
+        for (int c = 0; c < 2; ++c) {
+          for (int d = 0; d < 2; ++d) {
+            for (int b = 0; b < 7; ++b) {
+              float expected = 0.0f;
+              float expected_row_major = 0.0f;
+              int row_offset = r*stride + i - row_padding;
+              int col_offset = c*stride + j - col_padding;
+              // ColMajor
+              if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor.dimension(1) && col_offset < tensor.dimension(2)) {
+                expected = tensor(d, row_offset, col_offset, b);
+              }
+              if (twod_patch(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(twod_patch(d, r, c, patchId, b), expected);
+
+              // RowMajor
+              if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor_row_major.dimension(2) && col_offset < tensor_row_major.dimension(1)) {
+                expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
+
+              }
+              if (twod_patch_row_major(b, patchId, c, r, d) != expected_row_major) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(twod_patch_row_major(b, patchId, c, r, d), expected_row_major);
+              // Check that ColMajor and RowMajor agree.
+              VERIFY_IS_EQUAL(expected, expected_row_major);
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+// Verifies VALID padding (no padding) with incrementing values.
+void test_patch_padding_valid()
+{
+  int input_depth = 3;
+  int input_rows = 3;
+  int input_cols = 3;
+  int input_batches = 1;
+  int ksize = 2;  // Corresponds to the Rows and Cols for tensor.extract_image_patches<>.
+  int stride = 2;  // Only same stride is supported.
+  Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
+  // Initializes tensor with incrementing numbers.
+  for (int i = 0; i < tensor.size(); ++i) {
+    tensor.data()[i] = i + 1;
+  }
+  // ColMajor
+  Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);
+
+  VERIFY_IS_EQUAL(result.dimension(0), input_depth);  // depth
+  VERIFY_IS_EQUAL(result.dimension(1), ksize);  // kernel rows
+  VERIFY_IS_EQUAL(result.dimension(2), ksize);  // kernel cols
+  VERIFY_IS_EQUAL(result.dimension(3), 1);  // number of patches
+  VERIFY_IS_EQUAL(result.dimension(4), input_batches);  // number of batches
+
+  // RowMajor
+  Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
+  VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
+  VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
+  VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
+  VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));
+
+  Tensor<float, 5, RowMajor> result_row_major = tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);
+  VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
+  VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
+  VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
+  VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
+  VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));
+
+  // No padding is carried out.
+  int row_padding = 0;
+  int col_padding = 0;
+
+  for (int i = 0; (i+stride+ksize-1) < input_rows; i += stride) {  // input rows
+    for (int j = 0; (j+stride+ksize-1) < input_cols; j += stride) {  // input cols
+      int patchId = i+input_rows*j;
+      for (int r = 0; r < ksize; ++r) {  // patch rows
+        for (int c = 0; c < ksize; ++c) {  // patch cols
+          for (int d = 0; d < input_depth; ++d) {  // depth
+            for (int b = 0; b < input_batches; ++b) {  // batch
+              float expected = 0.0f;
+              float expected_row_major = 0.0f;
+              int row_offset = r + i - row_padding;
+              int col_offset = c + j - col_padding;
+              if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows && col_offset < input_cols) {
+                expected = tensor(d, row_offset, col_offset, b);
+                expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
+              }
+              // ColMajor
+              if (result(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
+              // RowMajor
+              if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
+              // Check that ColMajor and RowMajor agree.
+              VERIFY_IS_EQUAL(expected, expected_row_major);
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+// Verifies VALID padding (no padding) with the same value.
+void test_patch_padding_valid_same_value()
+{
+  int input_depth = 1;
+  int input_rows = 5;
+  int input_cols = 5;
+  int input_batches = 2;
+  int ksize = 3;  // Corresponds to the Rows and Cols for tensor.extract_image_patches<>.
+  int stride = 2;  // Only same stride is supported.
+  // ColMajor
+  Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
+  tensor = tensor.constant(11.0f);
+  Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);
+
+  VERIFY_IS_EQUAL(result.dimension(0), input_depth);  // depth
+  VERIFY_IS_EQUAL(result.dimension(1), ksize);  // kernel rows
+  VERIFY_IS_EQUAL(result.dimension(2), ksize);  // kernel cols
+  VERIFY_IS_EQUAL(result.dimension(3), 4);  // number of patches
+  VERIFY_IS_EQUAL(result.dimension(4), input_batches);  // number of batches
+
+  // RowMajor
+  Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
+  VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
+  VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
+  VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
+  VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));
+
+  Tensor<float, 5, RowMajor> result_row_major = tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);
+  VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
+  VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
+  VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
+  VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
+  VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));
+
+  // No padding is carried out.
+  int row_padding = 0;
+  int col_padding = 0;
+
+  for (int i = 0; (i+stride+ksize-1) <= input_rows; i += stride) {  // input rows
+    for (int j = 0; (j+stride+ksize-1) <= input_cols; j += stride) {  // input cols
+      int patchId = i+input_rows*j;
+      for (int r = 0; r < ksize; ++r) {  // patch rows
+        for (int c = 0; c < ksize; ++c) {  // patch cols
+          for (int d = 0; d < input_depth; ++d) {  // depth
+            for (int b = 0; b < input_batches; ++b) {  // batch
+              float expected = 0.0f;
+              float expected_row_major = 0.0f;
+              int row_offset = r + i - row_padding;
+              int col_offset = c + j - col_padding;
+              if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows && col_offset < input_cols) {
+                expected = tensor(d, row_offset, col_offset, b);
+                expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
+              }
+              // ColMajor
+              if (result(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
+              // RowMajor
+              if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
+              // Check that ColMajor and RowMajor agree.
+              VERIFY_IS_EQUAL(expected, expected_row_major);
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+// Verifies SAME padding.
+void test_patch_padding_same()
+{
+  int input_depth = 3;
+  int input_rows = 4;
+  int input_cols = 2;
+  int input_batches = 1;
+  int ksize = 2;  // Corresponds to the Rows and Cols for tensor.extract_image_patches<>.
+  int stride = 2;  // Only same stride is supported.
+  // ColMajor
+  Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
+  // Initializes tensor with incrementing numbers.
+  for (int i = 0; i < tensor.size(); ++i) {
+    tensor.data()[i] = i + 1;
+  }
+  Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, PADDING_SAME);
+
+  VERIFY_IS_EQUAL(result.dimension(0), input_depth);  // depth
+  VERIFY_IS_EQUAL(result.dimension(1), ksize);  // kernel rows
+  VERIFY_IS_EQUAL(result.dimension(2), ksize);  // kernel cols
+  VERIFY_IS_EQUAL(result.dimension(3), 2);  // number of patches
+  VERIFY_IS_EQUAL(result.dimension(4), input_batches);  // number of batches
+
+  // RowMajor
+  Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
+  VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
+  VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
+  VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
+  VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));
+
+  Tensor<float, 5, RowMajor> result_row_major = tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, PADDING_SAME);
+  VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
+  VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
+  VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
+  VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
+  VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));
+
+  // Based on the calculation described in TensorTraits.h, padding happens to be
+  // 0.
+  int row_padding = 0;
+  int col_padding = 0;
+
+  for (int i = 0; (i+stride+ksize-1) <= input_rows; i += stride) {  // input rows
+    for (int j = 0; (j+stride+ksize-1) <= input_cols; j += stride) {  // input cols
+      int patchId = i+input_rows*j;
+      for (int r = 0; r < ksize; ++r) {  // patch rows
+        for (int c = 0; c < ksize; ++c) {  // patch cols
+          for (int d = 0; d < input_depth; ++d) {  // depth
+            for (int b = 0; b < input_batches; ++b) {  // batch
+              float expected = 0.0f;
+              float expected_row_major = 0.0f;
+              int row_offset = r*stride + i - row_padding;
+              int col_offset = c*stride + j - col_padding;
+              if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows && col_offset < input_cols) {
+                expected = tensor(d, row_offset, col_offset, b);
+                expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
+              }
+              // ColMajor
+              if (result(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
+              // RowMajor
+              if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
+              // Check that ColMajor and RowMajor agree.
+              VERIFY_IS_EQUAL(expected, expected_row_major);
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+void test_patch_no_extra_dim()
+{
+  Tensor<float, 3> tensor(2,3,5);
+  tensor.setRandom();
+  Tensor<float, 3, RowMajor> tensor_row_major = tensor.swap_layout();
+  VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(2));
+  VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(1));
+  VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(0));
+
+  // Single pixel patch: ColMajor
+  Tensor<float, 4> single_pixel_patch;
+  single_pixel_patch = tensor.extract_image_patches(1, 1);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(0), 2);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(1), 1);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(2), 1);
+  VERIFY_IS_EQUAL(single_pixel_patch.dimension(3), 3*5);
+
+  // Single pixel patch: RowMajor
+  Tensor<float, 4, RowMajor> single_pixel_patch_row_major;
+  single_pixel_patch_row_major = tensor_row_major.extract_image_patches(1, 1);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(0), 3*5);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(1), 1);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(2), 1);
+  VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(3), 2);
+
+  for (int i = 0; i < tensor.size(); ++i) {
+    // ColMajor
+    if (tensor.data()[i] != single_pixel_patch.data()[i]) {
+      std::cout << "Mismatch detected at index " << i << " : " << tensor.data()[i] << " vs " << single_pixel_patch.data()[i] << std::endl;
+    }
+    VERIFY_IS_EQUAL(single_pixel_patch.data()[i], tensor.data()[i]);
+    // RowMajor
+    if (tensor_row_major.data()[i] != single_pixel_patch_row_major.data()[i]) {
+      std::cout << "Mismatch detected at index " << i << " : "
+           << tensor.data()[i] << " vs "
+           << single_pixel_patch_row_major.data()[i] << std::endl;
+    }
+    VERIFY_IS_EQUAL(single_pixel_patch_row_major.data()[i],
+                    tensor_row_major.data()[i]);
+    VERIFY_IS_EQUAL(tensor.data()[i], tensor_row_major.data()[i]);
+    VERIFY_IS_EQUAL(single_pixel_patch.data()[i],
+                    single_pixel_patch_row_major.data()[i]);
+  }
+
+  // Entire image patch: ColMajor
+  Tensor<float, 4> entire_image_patch;
+  entire_image_patch = tensor.extract_image_patches(3, 5);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(0), 2);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(1), 3);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(2), 5);
+  VERIFY_IS_EQUAL(entire_image_patch.dimension(3), 3*5);
+
+  // Entire image patch: RowMajor
+  Tensor<float, 4, RowMajor> entire_image_patch_row_major;
+  entire_image_patch_row_major = tensor_row_major.extract_image_patches(3, 5);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(0), 3*5);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(1), 5);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(2), 3);
+  VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(3), 2);
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      int patchId = i+3*j;
+      for (int r = 0; r < 3; ++r) {
+        for (int c = 0; c < 5; ++c) {
+          for (int d = 0; d < 2; ++d) {
+            float expected = 0.0f;
+            float expected_row_major = 0.0f;
+            if (r-1+i >= 0 && c-2+j >= 0 && r-1+i < 3 && c-2+j < 5) {
+              expected = tensor(d, r-1+i, c-2+j);
+              expected_row_major = tensor_row_major(c-2+j, r-1+i, d);
+            }
+            // ColMajor
+            if (entire_image_patch(d, r, c, patchId) != expected) {
+              std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << std::endl;
+            }
+            VERIFY_IS_EQUAL(entire_image_patch(d, r, c, patchId), expected);
+            // RowMajor
+            if (entire_image_patch_row_major(patchId, c, r, d) !=
+                expected_row_major) {
+              std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << std::endl;
+            }
+            VERIFY_IS_EQUAL(entire_image_patch_row_major(patchId, c, r, d),
+                            expected_row_major);
+            // Check that ColMajor and RowMajor agree.
+            VERIFY_IS_EQUAL(expected, expected_row_major);
+          }
+        }
+      }
+    }
+  }
+
+  // 2D patch: ColMajor
+  Tensor<float, 4> twod_patch;
+  twod_patch = tensor.extract_image_patches(2, 2);
+  VERIFY_IS_EQUAL(twod_patch.dimension(0), 2);
+  VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
+  VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
+  VERIFY_IS_EQUAL(twod_patch.dimension(3), 3*5);
+
+  // 2D patch: RowMajor
+  Tensor<float, 4, RowMajor> twod_patch_row_major;
+  twod_patch_row_major = tensor_row_major.extract_image_patches(2, 2);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(0), 3*5);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(1), 2);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(2), 2);
+  VERIFY_IS_EQUAL(twod_patch_row_major.dimension(3), 2);
+
+  // Based on the calculation described in TensorTraits.h, padding happens to be 0.
+  int row_padding = 0;
+  int col_padding = 0;
+  int stride = 1;
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      int patchId = i+3*j;
+      for (int r = 0; r < 2; ++r) {
+        for (int c = 0; c < 2; ++c) {
+          for (int d = 0; d < 2; ++d) {
+            float expected = 0.0f;
+            float expected_row_major = 0.0f;
+            int row_offset = r*stride + i - row_padding;
+            int col_offset = c*stride + j - col_padding;
+            // ColMajor
+            if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor.dimension(1) && col_offset < tensor.dimension(2)) {
+              expected = tensor(d, row_offset, col_offset);
+            }
+            if (twod_patch(d, r, c, patchId) != expected) {
+              std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << std::endl;
+            }
+            VERIFY_IS_EQUAL(twod_patch(d, r, c, patchId), expected);
+            // RowMajor
+            if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor_row_major.dimension(1) && col_offset < tensor_row_major.dimension(0)) {
+              expected_row_major = tensor_row_major(col_offset, row_offset, d);
+            }
+            if (twod_patch_row_major(patchId, c, r, d) != expected_row_major) {
+              std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << std::endl;
+            }
+            VERIFY_IS_EQUAL(twod_patch_row_major(patchId, c, r, d), expected_row_major);
+            // Check that ColMajor and RowMajor agree.
+            VERIFY_IS_EQUAL(expected, expected_row_major);
+          }
+        }
+      }
+    }
+  }
+}
+
+void test_imagenet_patches()
+{
+  // Test the code on typical configurations used by the 'imagenet' benchmarks at
+  // https://github.com/soumith/convnet-benchmarks
+  // ColMajor
+  Tensor<float, 4> l_in(3, 128, 128, 16);
+  l_in.setRandom();
+  Tensor<float, 5> l_out = l_in.extract_image_patches(11, 11);
+  VERIFY_IS_EQUAL(l_out.dimension(0), 3);
+  VERIFY_IS_EQUAL(l_out.dimension(1), 11);
+  VERIFY_IS_EQUAL(l_out.dimension(2), 11);
+  VERIFY_IS_EQUAL(l_out.dimension(3), 128*128);
+  VERIFY_IS_EQUAL(l_out.dimension(4), 16);
+
+  // RowMajor
+  Tensor<float, 5, RowMajor> l_out_row_major = l_in.swap_layout().extract_image_patches(11, 11);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 16);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 128*128);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 11);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 11);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 3);
+
+  for (int b = 0; b < 16; ++b) {
+    for (int i = 0; i < 128; ++i) {
+      for (int j = 0; j < 128; ++j) {
+        int patchId = i+128*j;
+        for (int c = 0; c < 11; ++c) {
+          for (int r = 0; r < 11; ++r) {
+            for (int d = 0; d < 3; ++d) {
+              float expected = 0.0f;
+              if (r-5+i >= 0 && c-5+j >= 0 && r-5+i < 128 && c-5+j < 128) {
+                expected = l_in(d, r-5+i, c-5+j, b);
+              }
+              // ColMajor
+              if (l_out(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
+              // RowMajor
+              if (l_out_row_major(b, patchId, c, r, d) !=
+                  expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j
+                     << " r=" << r << " c=" << c << " d=" << d << " b=" << b
+                     << std::endl;
+              }
+              VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d),
+                              expected);
+            }
+          }
+        }
+      }
+    }
+  }
+
+  // ColMajor
+  l_in.resize(16, 64, 64, 32);
+  l_in.setRandom();
+  l_out = l_in.extract_image_patches(9, 9);
+  VERIFY_IS_EQUAL(l_out.dimension(0), 16);
+  VERIFY_IS_EQUAL(l_out.dimension(1), 9);
+  VERIFY_IS_EQUAL(l_out.dimension(2), 9);
+  VERIFY_IS_EQUAL(l_out.dimension(3), 64*64);
+  VERIFY_IS_EQUAL(l_out.dimension(4), 32);
+
+  // RowMajor
+  l_out_row_major = l_in.swap_layout().extract_image_patches(9, 9);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 64*64);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 9);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 9);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 16);
+
+  for (int b = 0; b < 32; ++b) {
+    for (int i = 0; i < 64; ++i) {
+      for (int j = 0; j < 64; ++j) {
+        int patchId = i+64*j;
+        for (int c = 0; c < 9; ++c) {
+          for (int r = 0; r < 9; ++r) {
+            for (int d = 0; d < 16; ++d) {
+              float expected = 0.0f;
+              if (r-4+i >= 0 && c-4+j >= 0 && r-4+i < 64 && c-4+j < 64) {
+                expected = l_in(d, r-4+i, c-4+j, b);
+              }
+              // ColMajor
+              if (l_out(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
+              // RowMajor
+              if (l_out_row_major(b, patchId, c, r, d) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected);
+            }
+          }
+        }
+      }
+    }
+  }
+
+  // ColMajor
+  l_in.resize(32, 16, 16, 32);
+  l_in.setRandom();
+  l_out = l_in.extract_image_patches(7, 7);
+  VERIFY_IS_EQUAL(l_out.dimension(0), 32);
+  VERIFY_IS_EQUAL(l_out.dimension(1), 7);
+  VERIFY_IS_EQUAL(l_out.dimension(2), 7);
+  VERIFY_IS_EQUAL(l_out.dimension(3), 16*16);
+  VERIFY_IS_EQUAL(l_out.dimension(4), 32);
+
+  // RowMajor
+  l_out_row_major = l_in.swap_layout().extract_image_patches(7, 7);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 16*16);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 7);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 7);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 32);
+
+  for (int b = 0; b < 32; ++b) {
+    for (int i = 0; i < 16; ++i) {
+      for (int j = 0; j < 16; ++j) {
+        int patchId = i+16*j;
+        for (int c = 0; c < 7; ++c) {
+          for (int r = 0; r < 7; ++r) {
+            for (int d = 0; d < 32; ++d) {
+              float expected = 0.0f;
+              if (r-3+i >= 0 && c-3+j >= 0 && r-3+i < 16 && c-3+j < 16) {
+                expected = l_in(d, r-3+i, c-3+j, b);
+              }
+              // ColMajor
+              if (l_out(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
+              // RowMajor
+              if (l_out_row_major(b, patchId, c, r, d) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected);
+            }
+          }
+        }
+      }
+    }
+  }
+
+  // ColMajor
+  l_in.resize(64, 13, 13, 32);
+  l_in.setRandom();
+  l_out = l_in.extract_image_patches(3, 3);
+  VERIFY_IS_EQUAL(l_out.dimension(0), 64);
+  VERIFY_IS_EQUAL(l_out.dimension(1), 3);
+  VERIFY_IS_EQUAL(l_out.dimension(2), 3);
+  VERIFY_IS_EQUAL(l_out.dimension(3), 13*13);
+  VERIFY_IS_EQUAL(l_out.dimension(4), 32);
+
+  // RowMajor
+  l_out_row_major = l_in.swap_layout().extract_image_patches(3, 3);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 13*13);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 3);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 3);
+  VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 64);
+
+  for (int b = 0; b < 32; ++b) {
+    for (int i = 0; i < 13; ++i) {
+      for (int j = 0; j < 13; ++j) {
+        int patchId = i+13*j;
+        for (int c = 0; c < 3; ++c) {
+          for (int r = 0; r < 3; ++r) {
+            for (int d = 0; d < 64; ++d) {
+              float expected = 0.0f;
+              if (r-1+i >= 0 && c-1+j >= 0 && r-1+i < 13 && c-1+j < 13) {
+                expected = l_in(d, r-1+i, c-1+j, b);
+              }
+              // ColMajor
+              if (l_out(d, r, c, patchId, b) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
+              // RowMajor
+              if (l_out_row_major(b, patchId, c, r, d) != expected) {
+                std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
+              }
+              VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected);
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_image_patch()
+{
+  CALL_SUBTEST_1(test_simple_patch());
+  CALL_SUBTEST_2(test_patch_no_extra_dim());
+  CALL_SUBTEST_3(test_patch_padding_valid());
+  CALL_SUBTEST_4(test_patch_padding_valid_same_value());
+  CALL_SUBTEST_5(test_patch_padding_same());
+  CALL_SUBTEST_6(test_imagenet_patches());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_index_list.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_index_list.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_index_list.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_index_list.cpp
@@ -0,0 +1,386 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+#ifdef EIGEN_HAS_INDEX_LIST
+
+static void test_static_index_list()
+{
+  Tensor<float, 4> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  constexpr auto reduction_axis = make_index_list(0, 1, 2);
+  VERIFY_IS_EQUAL(internal::array_get<0>(reduction_axis), 0);
+  VERIFY_IS_EQUAL(internal::array_get<1>(reduction_axis), 1);
+  VERIFY_IS_EQUAL(internal::array_get<2>(reduction_axis), 2);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[0]), 0);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[1]), 1);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[2]), 2);
+
+  EIGEN_STATIC_ASSERT((internal::array_get<0>(reduction_axis) == 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::array_get<1>(reduction_axis) == 1), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::array_get<2>(reduction_axis) == 2), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  Tensor<float, 1> result = tensor.sum(reduction_axis);
+  for (int i = 0; i < result.size(); ++i) {
+    float expected = 0.0f;
+    for (int j = 0; j < 2; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 5; ++l) {
+          expected += tensor(j,k,l,i);
+        }
+      }
+    }
+    VERIFY_IS_APPROX(result(i), expected);
+  }
+}
+
+
+static void test_type2index_list()
+{
+  Tensor<float, 5> tensor(2,3,5,7,11);
+  tensor.setRandom();
+  tensor += tensor.constant(10.0f);
+
+  typedef Eigen::IndexList<Eigen::type2index<0>> Dims0;
+  typedef Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1>> Dims1;
+  typedef Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1>, Eigen::type2index<2>> Dims2;
+  typedef Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1>, Eigen::type2index<2>, Eigen::type2index<3>> Dims3;
+  typedef Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1>, Eigen::type2index<2>, Eigen::type2index<3>, Eigen::type2index<4>> Dims4;
+
+#if 0
+  EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims0>() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims1>() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims2>() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims3>() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims4>() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+#endif
+
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims0, 1, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims1, 2, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims2, 3, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims3, 4, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims4, 5, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims0, 1, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims1, 2, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims2, 3, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims3, 4, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims4, 5, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  const Dims0 reduction_axis0;
+  Tensor<float, 4> result0 = tensor.sum(reduction_axis0);
+  for (int m = 0; m < 11; ++m) {
+    for (int l = 0; l < 7; ++l) {
+      for (int k = 0; k < 5; ++k) {
+        for (int j = 0; j < 3; ++j) {
+          float expected = 0.0f;
+          for (int i = 0; i < 2; ++i) {
+            expected += tensor(i,j,k,l,m);
+          }
+          VERIFY_IS_APPROX(result0(j,k,l,m), expected);
+        }
+      }
+    }
+  }
+
+  const Dims1 reduction_axis1;
+  Tensor<float, 3> result1 = tensor.sum(reduction_axis1);
+  for (int m = 0; m < 11; ++m) {
+    for (int l = 0; l < 7; ++l) {
+      for (int k = 0; k < 5; ++k) {
+        float expected = 0.0f;
+        for (int j = 0; j < 3; ++j) {
+          for (int i = 0; i < 2; ++i) {
+            expected += tensor(i,j,k,l,m);
+          }
+        }
+        VERIFY_IS_APPROX(result1(k,l,m), expected);
+      }
+    }
+  }
+
+  const Dims2 reduction_axis2;
+  Tensor<float, 2> result2 = tensor.sum(reduction_axis2);
+  for (int m = 0; m < 11; ++m) {
+    for (int l = 0; l < 7; ++l) {
+      float expected = 0.0f;
+      for (int k = 0; k < 5; ++k) {
+        for (int j = 0; j < 3; ++j) {
+          for (int i = 0; i < 2; ++i) {
+            expected += tensor(i,j,k,l,m);
+          }
+        }
+      }
+      VERIFY_IS_APPROX(result2(l,m), expected);
+    }
+  }
+
+  const Dims3 reduction_axis3;
+  Tensor<float, 1> result3 = tensor.sum(reduction_axis3);
+  for (int m = 0; m < 11; ++m) {
+    float expected = 0.0f;
+    for (int l = 0; l < 7; ++l) {
+      for (int k = 0; k < 5; ++k) {
+        for (int j = 0; j < 3; ++j) {
+          for (int i = 0; i < 2; ++i) {
+            expected += tensor(i,j,k,l,m);
+          }
+        }
+      }
+    }
+    VERIFY_IS_APPROX(result3(m), expected);
+  }
+
+  const Dims4 reduction_axis4;
+  Tensor<float, 0> result4 = tensor.sum(reduction_axis4);
+  float expected = 0.0f;
+  for (int m = 0; m < 11; ++m) {
+    for (int l = 0; l < 7; ++l) {
+      for (int k = 0; k < 5; ++k) {
+        for (int j = 0; j < 3; ++j) {
+          for (int i = 0; i < 2; ++i) {
+            expected += tensor(i,j,k,l,m);
+          }
+        }
+      }
+    }
+  }
+  VERIFY_IS_APPROX(result4(), expected);
+}
+
+
+static void test_type2indexpair_list()
+{
+  Tensor<float, 5> tensor(2,3,5,7,11);
+  tensor.setRandom();
+  tensor += tensor.constant(10.0f);
+
+  typedef Eigen::IndexPairList<Eigen::type2indexpair<0,10>> Dims0;
+  typedef Eigen::IndexPairList<Eigen::type2indexpair<0,10>, Eigen::type2indexpair<1,11>, Eigen::type2indexpair<2,12>> Dims2_a;
+  typedef Eigen::IndexPairList<Eigen::type2indexpair<0,10>, Eigen::IndexPair<DenseIndex>, Eigen::type2indexpair<2,12>> Dims2_b;
+  typedef Eigen::IndexPairList<Eigen::IndexPair<DenseIndex>, Eigen::type2indexpair<1,11>, Eigen::IndexPair<DenseIndex>> Dims2_c;
+
+  Dims0 d0;
+  Dims2_a d2_a;
+
+  Dims2_b d2_b;
+  d2_b.set(1, Eigen::IndexPair<DenseIndex>(1,11));
+
+  Dims2_c d2_c;
+  d2_c.set(0, Eigen::IndexPair<DenseIndex>(Eigen::IndexPair<DenseIndex>(0,10)));
+  d2_c.set(1, Eigen::IndexPair<DenseIndex>(1,11));  // setting type2indexpair to correct value.
+  d2_c.set(2, Eigen::IndexPair<DenseIndex>(2,12));
+
+  VERIFY_IS_EQUAL(d2_a[0].first, 0);
+  VERIFY_IS_EQUAL(d2_a[0].second, 10);
+  VERIFY_IS_EQUAL(d2_a[1].first, 1);
+  VERIFY_IS_EQUAL(d2_a[1].second, 11);
+  VERIFY_IS_EQUAL(d2_a[2].first, 2);
+  VERIFY_IS_EQUAL(d2_a[2].second, 12);
+
+  VERIFY_IS_EQUAL(d2_b[0].first, 0);
+  VERIFY_IS_EQUAL(d2_b[0].second, 10);
+  VERIFY_IS_EQUAL(d2_b[1].first, 1);
+  VERIFY_IS_EQUAL(d2_b[1].second, 11);
+  VERIFY_IS_EQUAL(d2_b[2].first, 2);
+  VERIFY_IS_EQUAL(d2_b[2].second, 12);
+
+  VERIFY_IS_EQUAL(d2_c[0].first, 0);
+  VERIFY_IS_EQUAL(d2_c[0].second, 10);
+  VERIFY_IS_EQUAL(d2_c[1].first, 1);
+  VERIFY_IS_EQUAL(d2_c[1].second, 11);
+  VERIFY_IS_EQUAL(d2_c[2].first, 2);
+  VERIFY_IS_EQUAL(d2_c[2].second, 12);
+
+  EIGEN_STATIC_ASSERT((d2_a.value_known_statically(0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((d2_a.value_known_statically(1) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((d2_a.value_known_statically(2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((d2_b.value_known_statically(0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((d2_b.value_known_statically(1) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((d2_b.value_known_statically(2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((d2_c.value_known_statically(0) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((d2_c.value_known_statically(1) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((d2_c.value_known_statically(2) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims0>(0, 0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims0>(0, 1) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_a>(0, 0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_a>(0, 1) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_a>(1, 1) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_a>(1, 2) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_a>(2, 2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_a>(2, 3) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_b>(0, 0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_b>(0, 1) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_b>(1, 1) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_b>(1, 2) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_b>(2, 2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_b>(2, 3) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_c>(0, 0) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_c>(0, 1) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_c>(1, 1) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_c>(1, 2) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_c>(2, 2) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_first_statically_eq<Dims2_c>(2, 3) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims0>(0, 10) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims0>(0, 11) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_a>(0, 10) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_a>(0, 11) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_a>(1, 11) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_a>(1, 12) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_a>(2, 12) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_a>(2, 13) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_b>(0, 10) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_b>(0, 11) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_b>(1, 11) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_b>(1, 12) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_b>(2, 12) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_b>(2, 13) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_c>(0, 10) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_c>(0, 11) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_c>(1, 11) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_c>(1, 12) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_c>(2, 12) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((Eigen::internal::index_pair_second_statically_eq<Dims2_c>(2, 13) == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+}
+
+
+static void test_dynamic_index_list()
+{
+  Tensor<float, 4> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  int dim1 = 2;
+  int dim2 = 1;
+  int dim3 = 0;
+
+  auto reduction_axis = make_index_list(dim1, dim2, dim3);
+
+  VERIFY_IS_EQUAL(internal::array_get<0>(reduction_axis), 2);
+  VERIFY_IS_EQUAL(internal::array_get<1>(reduction_axis), 1);
+  VERIFY_IS_EQUAL(internal::array_get<2>(reduction_axis), 0);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[0]), 2);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[1]), 1);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[2]), 0);
+
+  Tensor<float, 1> result = tensor.sum(reduction_axis);
+  for (int i = 0; i < result.size(); ++i) {
+    float expected = 0.0f;
+    for (int j = 0; j < 2; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 5; ++l) {
+          expected += tensor(j,k,l,i);
+        }
+      }
+    }
+    VERIFY_IS_APPROX(result(i), expected);
+  }
+}
+
+static void test_mixed_index_list()
+{
+  Tensor<float, 4> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  int dim2 = 1;
+  int dim4 = 3;
+
+  auto reduction_axis = make_index_list(0, dim2, 2, dim4);
+
+  VERIFY_IS_EQUAL(internal::array_get<0>(reduction_axis), 0);
+  VERIFY_IS_EQUAL(internal::array_get<1>(reduction_axis), 1);
+  VERIFY_IS_EQUAL(internal::array_get<2>(reduction_axis), 2);
+  VERIFY_IS_EQUAL(internal::array_get<3>(reduction_axis), 3);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[0]), 0);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[1]), 1);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[2]), 2);
+  VERIFY_IS_EQUAL(static_cast<DenseIndex>(reduction_axis[3]), 3);
+
+  typedef IndexList<type2index<0>, int, type2index<2>, int> ReductionIndices;
+  ReductionIndices reduction_indices;
+  reduction_indices.set(1, 1);
+  reduction_indices.set(3, 3);
+  EIGEN_STATIC_ASSERT((internal::array_get<0>(reduction_indices) == 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::array_get<2>(reduction_indices) == 2), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::index_known_statically<ReductionIndices>(0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::index_known_statically<ReductionIndices>(2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::index_statically_eq<ReductionIndices>(0, 0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::index_statically_eq<ReductionIndices>(2, 2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+#if 0
+  EIGEN_STATIC_ASSERT((internal::all_indices_known_statically<ReductionIndices>() == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<ReductionIndices>() == false), YOU_MADE_A_PROGRAMMING_MISTAKE);
+#endif
+
+  typedef IndexList<type2index<0>, type2index<1>, type2index<2>, type2index<3>> ReductionList;
+  ReductionList reduction_list;
+  EIGEN_STATIC_ASSERT((internal::index_statically_eq<ReductionList>(0, 0) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::index_statically_eq<ReductionList>(1, 1) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::index_statically_eq<ReductionList>(2, 2) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::index_statically_eq<ReductionList>(3, 3) == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+#if 0
+  EIGEN_STATIC_ASSERT((internal::all_indices_known_statically<ReductionList>() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<ReductionList>() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
+#endif
+
+  Tensor<float, 0> result1 = tensor.sum(reduction_axis);
+  Tensor<float, 0> result2 = tensor.sum(reduction_indices);
+  Tensor<float, 0> result3 = tensor.sum(reduction_list);
+
+  float expected = 0.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          expected += tensor(i,j,k,l);
+        }
+      }
+    }
+  }
+  VERIFY_IS_APPROX(result1(), expected);
+  VERIFY_IS_APPROX(result2(), expected);
+  VERIFY_IS_APPROX(result3(), expected);
+}
+
+
+static void test_dim_check()
+{
+  Eigen::IndexList<Eigen::type2index<1>, int> dim1;
+  dim1.set(1, 2);
+  Eigen::IndexList<Eigen::type2index<1>, int> dim2;
+  dim2.set(1, 2);
+  VERIFY(dimensions_match(dim1, dim2));
+}
+
+
+#endif
+
+void test_cxx11_tensor_index_list()
+{
+#ifdef EIGEN_HAS_INDEX_LIST
+  CALL_SUBTEST(test_static_index_list());
+  CALL_SUBTEST(test_type2index_list());
+  CALL_SUBTEST(test_type2indexpair_list());
+  CALL_SUBTEST(test_dynamic_index_list());
+  CALL_SUBTEST(test_mixed_index_list());
+  CALL_SUBTEST(test_dim_check());
+#endif
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_inflation.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_inflation.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_inflation.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_inflation.cpp
@@ -0,0 +1,81 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Ke Yang <yangke@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<int DataLayout>
+static void test_simple_inflation()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  array<ptrdiff_t, 4> strides;
+
+  strides[0] = 1;
+  strides[1] = 1;
+  strides[2] = 1;
+  strides[3] = 1;
+
+  Tensor<float, 4, DataLayout> no_stride;
+  no_stride = tensor.inflate(strides);
+
+  VERIFY_IS_EQUAL(no_stride.dimension(0), 2);
+  VERIFY_IS_EQUAL(no_stride.dimension(1), 3);
+  VERIFY_IS_EQUAL(no_stride.dimension(2), 5);
+  VERIFY_IS_EQUAL(no_stride.dimension(3), 7);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), no_stride(i,j,k,l));
+        }
+      }
+    }
+  }
+
+  strides[0] = 2;
+  strides[1] = 4;
+  strides[2] = 2;
+  strides[3] = 3;
+  Tensor<float, 4, DataLayout> inflated;
+  inflated = tensor.inflate(strides);
+
+  VERIFY_IS_EQUAL(inflated.dimension(0), 3);
+  VERIFY_IS_EQUAL(inflated.dimension(1), 9);
+  VERIFY_IS_EQUAL(inflated.dimension(2), 9);
+  VERIFY_IS_EQUAL(inflated.dimension(3), 19);
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 9; ++k) {
+        for (int l = 0; l < 19; ++l) {
+          if (i % 2 == 0 &&
+              j % 4 == 0 &&
+              k % 2 == 0 &&
+              l % 3 == 0) {
+            VERIFY_IS_EQUAL(inflated(i,j,k,l),
+                            tensor(i/2, j/4, k/2, l/3));
+          } else {
+            VERIFY_IS_EQUAL(0, inflated(i,j,k,l));
+          }
+        }
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_inflation()
+{
+  CALL_SUBTEST(test_simple_inflation<ColMajor>());
+  CALL_SUBTEST(test_simple_inflation<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_intdiv.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_intdiv.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_intdiv.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_intdiv.cpp
@@ -0,0 +1,147 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014-2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+
+void test_signed_32bit()
+{
+  // Divide by one
+  const Eigen::internal::TensorIntDivisor<int32_t, false> div_by_one(1);
+
+  for (int32_t j = 0; j < 25000; ++j) {
+    const int32_t fast_div = j / div_by_one;
+    const int32_t slow_div = j / 1;
+    VERIFY_IS_EQUAL(fast_div, slow_div);
+  }
+
+  // Standard divide by 2 or more
+  for (int32_t i = 2; i < 25000; ++i) {
+    const Eigen::internal::TensorIntDivisor<int32_t, false> div(i);
+
+    for (int32_t j = 0; j < 25000; ++j) {
+      const int32_t fast_div = j / div;
+      const int32_t slow_div = j / i;
+      VERIFY_IS_EQUAL(fast_div, slow_div);
+    }
+  }
+
+  // Optimized divide by 2 or more
+  for (int32_t i = 2; i < 25000; ++i) {
+    const Eigen::internal::TensorIntDivisor<int32_t, true> div(i);
+
+    for (int32_t j = 0; j < 25000; ++j) {
+      const int32_t fast_div = j / div;
+      const int32_t slow_div = j / i;
+      VERIFY_IS_EQUAL(fast_div, slow_div);
+    }
+  }
+}
+
+
+void test_unsigned_32bit()
+{
+  for (uint32_t i = 1; i < 25000; ++i) {
+    const Eigen::internal::TensorIntDivisor<uint32_t> div(i);
+
+    for (uint32_t j = 0; j < 25000; ++j) {
+      const uint32_t fast_div = j / div;
+      const uint32_t slow_div = j / i;
+      VERIFY_IS_EQUAL(fast_div, slow_div);
+    }
+  }
+}
+
+
+void test_signed_64bit()
+{
+  for (int64_t i = 1; i < 25000; ++i) {
+    const Eigen::internal::TensorIntDivisor<int64_t> div(i);
+
+    for (int64_t j = 0; j < 25000; ++j) {
+      const int64_t fast_div = j / div;
+      const int64_t slow_div = j / i;
+      VERIFY_IS_EQUAL(fast_div, slow_div);
+    }
+  }
+}
+
+
+void test_unsigned_64bit()
+{
+  for (uint64_t i = 1; i < 25000; ++i) {
+    const Eigen::internal::TensorIntDivisor<uint64_t> div(i);
+
+    for (uint64_t j = 0; j < 25000; ++j) {
+      const uint64_t fast_div = j / div;
+      const uint64_t slow_div = j / i;
+      VERIFY_IS_EQUAL(fast_div, slow_div);
+    }
+  }
+}
+
+void test_powers_32bit() {
+  for (int expon = 1; expon < 31; expon++) {
+    int32_t div = (1 << expon);
+    for (int num_expon = 0; num_expon < 32; num_expon++) {
+      int32_t start_num = (1 << num_expon) - 100;
+      int32_t end_num = (1 << num_expon) + 100;
+      if (start_num < 0)
+        start_num = 0;
+      for (int32_t num = start_num; num < end_num; num++) {
+        Eigen::internal::TensorIntDivisor<int32_t> divider =
+          Eigen::internal::TensorIntDivisor<int32_t>(div);
+        int32_t result = num/div;
+        int32_t result_op = divider.divide(num);
+        VERIFY_IS_EQUAL(result_op, result);
+      }
+    }
+  }
+}
+
+void test_powers_64bit() {
+  for (int expon = 0; expon < 63; expon++) {
+    int64_t div = (1ull << expon);
+    for (int num_expon = 0; num_expon < 63; num_expon++) {
+      int64_t start_num = (1ull << num_expon) - 10;
+      int64_t end_num = (1ull << num_expon) + 10;
+      if (start_num < 0)
+        start_num = 0;
+      for (int64_t num = start_num; num < end_num; num++) {
+        Eigen::internal::TensorIntDivisor<int64_t> divider(div);
+        int64_t result = num/div;
+        int64_t result_op = divider.divide(num);
+        VERIFY_IS_EQUAL(result_op, result);
+      }
+    }
+  }
+}
+
+void test_specific() {
+  // A particular combination that was previously failing
+  int64_t div = 209715200;
+  int64_t num = 3238002688ll;
+  Eigen::internal::TensorIntDivisor<int64_t> divider(div);
+  int64_t result = num/div;
+  int64_t result_op = divider.divide(num);
+  VERIFY_IS_EQUAL(result, result_op);
+}
+
+void test_cxx11_tensor_intdiv()
+{
+  CALL_SUBTEST_1(test_signed_32bit());
+  CALL_SUBTEST_2(test_unsigned_32bit());
+  CALL_SUBTEST_3(test_signed_64bit());
+  CALL_SUBTEST_4(test_unsigned_64bit());
+  CALL_SUBTEST_5(test_powers_32bit());
+  CALL_SUBTEST_6(test_powers_64bit());
+  CALL_SUBTEST_7(test_specific());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_io.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_io.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_io.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_io.cpp
@@ -0,0 +1,136 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <sstream>
+#include <string>
+#include <Eigen/CXX11/Tensor>
+
+
+template<int DataLayout>
+static void test_output_0d()
+{
+  Tensor<int, 0, DataLayout> tensor;
+  tensor() = 123;
+
+  std::stringstream os;
+  os << tensor;
+
+  std::string expected("123");
+  VERIFY_IS_EQUAL(std::string(os.str()), expected);
+}
+
+
+template<int DataLayout>
+static void test_output_1d()
+{
+  Tensor<int, 1, DataLayout> tensor(5);
+  for (int i = 0; i < 5; ++i) {
+    tensor(i) = i;
+  }
+
+  std::stringstream os;
+  os << tensor;
+
+  std::string expected("0\n1\n2\n3\n4");
+  VERIFY_IS_EQUAL(std::string(os.str()), expected);
+
+  Eigen::Tensor<double,1,DataLayout> empty_tensor(0);
+  std::stringstream empty_os;
+  empty_os << empty_tensor;
+  std::string empty_string;
+  VERIFY_IS_EQUAL(std::string(empty_os.str()), empty_string);
+}
+
+
+template<int DataLayout>
+static void test_output_2d()
+{
+  Tensor<int, 2, DataLayout> tensor(5, 3);
+  for (int i = 0; i < 5; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      tensor(i, j) = i*j;
+    }
+  }
+
+  std::stringstream os;
+  os << tensor;
+
+  std::string expected("0  0  0\n0  1  2\n0  2  4\n0  3  6\n0  4  8");
+  VERIFY_IS_EQUAL(std::string(os.str()), expected);
+}
+
+
+template<int DataLayout>
+static void test_output_expr()
+{
+  Tensor<int, 1, DataLayout> tensor1(5);
+  Tensor<int, 1, DataLayout> tensor2(5);
+  for (int i = 0; i < 5; ++i) {
+    tensor1(i) = i;
+    tensor2(i) = 7;
+  }
+
+  std::stringstream os;
+  os << tensor1 + tensor2;
+
+  std::string expected(" 7\n 8\n 9\n10\n11");
+  VERIFY_IS_EQUAL(std::string(os.str()), expected);
+}
+
+
+template<int DataLayout>
+static void test_output_string()
+{
+  Tensor<std::string, 2, DataLayout> tensor(5, 3);
+  tensor.setConstant(std::string("foo"));
+
+  std::cout << tensor << std::endl;
+
+  std::stringstream os;
+  os << tensor;
+
+  std::string expected("foo  foo  foo\nfoo  foo  foo\nfoo  foo  foo\nfoo  foo  foo\nfoo  foo  foo");
+  VERIFY_IS_EQUAL(std::string(os.str()), expected);
+}
+
+
+template<int DataLayout>
+static void test_output_const()
+{
+  Tensor<int, 1, DataLayout> tensor(5);
+  for (int i = 0; i < 5; ++i) {
+    tensor(i) = i;
+  }
+
+  TensorMap<Tensor<const int, 1, DataLayout> > tensor_map(tensor.data(), 5);
+
+  std::stringstream os;
+  os << tensor_map;
+
+  std::string expected("0\n1\n2\n3\n4");
+  VERIFY_IS_EQUAL(std::string(os.str()), expected);
+}
+
+
+void test_cxx11_tensor_io()
+{
+  CALL_SUBTEST(test_output_0d<ColMajor>());
+  CALL_SUBTEST(test_output_0d<RowMajor>());
+  CALL_SUBTEST(test_output_1d<ColMajor>());
+  CALL_SUBTEST(test_output_1d<RowMajor>());
+  CALL_SUBTEST(test_output_2d<ColMajor>());
+  CALL_SUBTEST(test_output_2d<RowMajor>());
+  CALL_SUBTEST(test_output_expr<ColMajor>());
+  CALL_SUBTEST(test_output_expr<RowMajor>());
+  CALL_SUBTEST(test_output_string<ColMajor>());
+  CALL_SUBTEST(test_output_string<RowMajor>());
+  CALL_SUBTEST(test_output_const<ColMajor>());
+  CALL_SUBTEST(test_output_const<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_layout_swap.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_layout_swap.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_layout_swap.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_layout_swap.cpp
@@ -0,0 +1,61 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+static void test_simple_swap()
+{
+  Tensor<float, 3, ColMajor> tensor(2,3,7);
+  tensor.setRandom();
+
+  Tensor<float, 3, RowMajor> tensor2 = tensor.swap_layout();
+  VERIFY_IS_EQUAL(tensor.dimension(0), tensor2.dimension(2));
+  VERIFY_IS_EQUAL(tensor.dimension(1), tensor2.dimension(1));
+  VERIFY_IS_EQUAL(tensor.dimension(2), tensor2.dimension(0));
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(tensor(i,j,k), tensor2(k,j,i));
+      }
+    }
+  }
+}
+
+
+static void test_swap_as_lvalue()
+{
+  Tensor<float, 3, ColMajor> tensor(2,3,7);
+  tensor.setRandom();
+
+  Tensor<float, 3, RowMajor> tensor2(7,3,2);
+  tensor2.swap_layout() = tensor;
+  VERIFY_IS_EQUAL(tensor.dimension(0), tensor2.dimension(2));
+  VERIFY_IS_EQUAL(tensor.dimension(1), tensor2.dimension(1));
+  VERIFY_IS_EQUAL(tensor.dimension(2), tensor2.dimension(0));
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(tensor(i,j,k), tensor2(k,j,i));
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_layout_swap()
+{
+  CALL_SUBTEST(test_simple_swap());
+  CALL_SUBTEST(test_swap_as_lvalue());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_lvalue.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_lvalue.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_lvalue.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_lvalue.cpp
@@ -0,0 +1,42 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+
+static void test_compound_assignment()
+{
+  Tensor<float, 3> mat1(2,3,7);
+  Tensor<float, 3> mat2(2,3,7);
+  Tensor<float, 3> mat3(2,3,7);
+
+  mat1.setRandom();
+  mat2.setRandom();
+  mat3 = mat1;
+  mat3 += mat2;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(mat3(i,j,k), mat1(i,j,k) + mat2(i,j,k));
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_lvalue()
+{
+  CALL_SUBTEST(test_compound_assignment());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_map.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_map.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_map.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_map.cpp
@@ -0,0 +1,277 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_0d()
+{
+  Tensor<int, 0> scalar1;
+  Tensor<int, 0, RowMajor> scalar2;
+
+  TensorMap<Tensor<const int, 0> > scalar3(scalar1.data());
+  TensorMap<Tensor<const int, 0, RowMajor> > scalar4(scalar2.data());
+
+  scalar1() = 7;
+  scalar2() = 13;
+
+  VERIFY_IS_EQUAL(scalar1.rank(), 0);
+  VERIFY_IS_EQUAL(scalar1.size(), 1);
+
+  VERIFY_IS_EQUAL(scalar3(), 7);
+  VERIFY_IS_EQUAL(scalar4(), 13);
+}
+
+static void test_1d()
+{
+  Tensor<int, 1> vec1(6);
+  Tensor<int, 1, RowMajor> vec2(6);
+
+  TensorMap<Tensor<const int, 1> > vec3(vec1.data(), 6);
+  TensorMap<Tensor<const int, 1, RowMajor> > vec4(vec2.data(), 6);
+
+  vec1(0) = 4;  vec2(0) = 0;
+  vec1(1) = 8;  vec2(1) = 1;
+  vec1(2) = 15; vec2(2) = 2;
+  vec1(3) = 16; vec2(3) = 3;
+  vec1(4) = 23; vec2(4) = 4;
+  vec1(5) = 42; vec2(5) = 5;
+
+  VERIFY_IS_EQUAL(vec1.rank(), 1);
+  VERIFY_IS_EQUAL(vec1.size(), 6);
+  VERIFY_IS_EQUAL(vec1.dimension(0), 6);
+
+  VERIFY_IS_EQUAL(vec3(0), 4);
+  VERIFY_IS_EQUAL(vec3(1), 8);
+  VERIFY_IS_EQUAL(vec3(2), 15);
+  VERIFY_IS_EQUAL(vec3(3), 16);
+  VERIFY_IS_EQUAL(vec3(4), 23);
+  VERIFY_IS_EQUAL(vec3(5), 42);
+
+  VERIFY_IS_EQUAL(vec4(0), 0);
+  VERIFY_IS_EQUAL(vec4(1), 1);
+  VERIFY_IS_EQUAL(vec4(2), 2);
+  VERIFY_IS_EQUAL(vec4(3), 3);
+  VERIFY_IS_EQUAL(vec4(4), 4);
+  VERIFY_IS_EQUAL(vec4(5), 5);
+}
+
+static void test_2d()
+{
+  Tensor<int, 2> mat1(2,3);
+  Tensor<int, 2, RowMajor> mat2(2,3);
+
+  mat1(0,0) = 0;
+  mat1(0,1) = 1;
+  mat1(0,2) = 2;
+  mat1(1,0) = 3;
+  mat1(1,1) = 4;
+  mat1(1,2) = 5;
+
+  mat2(0,0) = 0;
+  mat2(0,1) = 1;
+  mat2(0,2) = 2;
+  mat2(1,0) = 3;
+  mat2(1,1) = 4;
+  mat2(1,2) = 5;
+
+  TensorMap<Tensor<const int, 2> > mat3(mat1.data(), 2, 3);
+  TensorMap<Tensor<const int, 2, RowMajor> > mat4(mat2.data(), 2, 3);
+
+  VERIFY_IS_EQUAL(mat3.rank(), 2);
+  VERIFY_IS_EQUAL(mat3.size(), 6);
+  VERIFY_IS_EQUAL(mat3.dimension(0), 2);
+  VERIFY_IS_EQUAL(mat3.dimension(1), 3);
+
+  VERIFY_IS_EQUAL(mat4.rank(), 2);
+  VERIFY_IS_EQUAL(mat4.size(), 6);
+  VERIFY_IS_EQUAL(mat4.dimension(0), 2);
+  VERIFY_IS_EQUAL(mat4.dimension(1), 3);
+
+  VERIFY_IS_EQUAL(mat3(0,0), 0);
+  VERIFY_IS_EQUAL(mat3(0,1), 1);
+  VERIFY_IS_EQUAL(mat3(0,2), 2);
+  VERIFY_IS_EQUAL(mat3(1,0), 3);
+  VERIFY_IS_EQUAL(mat3(1,1), 4);
+  VERIFY_IS_EQUAL(mat3(1,2), 5);
+
+  VERIFY_IS_EQUAL(mat4(0,0), 0);
+  VERIFY_IS_EQUAL(mat4(0,1), 1);
+  VERIFY_IS_EQUAL(mat4(0,2), 2);
+  VERIFY_IS_EQUAL(mat4(1,0), 3);
+  VERIFY_IS_EQUAL(mat4(1,1), 4);
+  VERIFY_IS_EQUAL(mat4(1,2), 5);
+}
+
+static void test_3d()
+{
+  Tensor<int, 3> mat1(2,3,7);
+  Tensor<int, 3, RowMajor> mat2(2,3,7);
+
+  int val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        mat2(i,j,k) = val;
+        val++;
+      }
+    }
+  }
+
+  TensorMap<Tensor<const int, 3> > mat3(mat1.data(), 2, 3, 7);
+  TensorMap<Tensor<const int, 3, RowMajor> > mat4(mat2.data(), 2, 3, 7);
+
+  VERIFY_IS_EQUAL(mat3.rank(), 3);
+  VERIFY_IS_EQUAL(mat3.size(), 2*3*7);
+  VERIFY_IS_EQUAL(mat3.dimension(0), 2);
+  VERIFY_IS_EQUAL(mat3.dimension(1), 3);
+  VERIFY_IS_EQUAL(mat3.dimension(2), 7);
+
+  VERIFY_IS_EQUAL(mat4.rank(), 3);
+  VERIFY_IS_EQUAL(mat4.size(), 2*3*7);
+  VERIFY_IS_EQUAL(mat4.dimension(0), 2);
+  VERIFY_IS_EQUAL(mat4.dimension(1), 3);
+  VERIFY_IS_EQUAL(mat4.dimension(2), 7);
+
+  val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(mat3(i,j,k), val);
+        VERIFY_IS_EQUAL(mat4(i,j,k), val);
+        val++;
+      }
+    }
+  }
+}
+
+
+static void test_from_tensor()
+{
+  Tensor<int, 3> mat1(2,3,7);
+  Tensor<int, 3, RowMajor> mat2(2,3,7);
+
+  int val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        mat1(i,j,k) = val;
+        mat2(i,j,k) = val;
+        val++;
+      }
+    }
+  }
+
+  TensorMap<Tensor<int, 3> > mat3(mat1);
+  TensorMap<Tensor<int, 3, RowMajor> > mat4(mat2);
+
+  VERIFY_IS_EQUAL(mat3.rank(), 3);
+  VERIFY_IS_EQUAL(mat3.size(), 2*3*7);
+  VERIFY_IS_EQUAL(mat3.dimension(0), 2);
+  VERIFY_IS_EQUAL(mat3.dimension(1), 3);
+  VERIFY_IS_EQUAL(mat3.dimension(2), 7);
+
+  VERIFY_IS_EQUAL(mat4.rank(), 3);
+  VERIFY_IS_EQUAL(mat4.size(), 2*3*7);
+  VERIFY_IS_EQUAL(mat4.dimension(0), 2);
+  VERIFY_IS_EQUAL(mat4.dimension(1), 3);
+  VERIFY_IS_EQUAL(mat4.dimension(2), 7);
+
+  val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(mat3(i,j,k), val);
+        VERIFY_IS_EQUAL(mat4(i,j,k), val);
+        val++;
+      }
+    }
+  }
+
+  TensorFixedSize<int, Sizes<2,3,7> > mat5;
+
+  val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        array<ptrdiff_t, 3> coords;
+        coords[0] = i;
+        coords[1] = j;
+        coords[2] = k;
+        mat5(coords) = val;
+        val++;
+      }
+    }
+  }
+
+  TensorMap<TensorFixedSize<int, Sizes<2,3,7> > > mat6(mat5);
+
+  VERIFY_IS_EQUAL(mat6.rank(), 3);
+  VERIFY_IS_EQUAL(mat6.size(), 2*3*7);
+  VERIFY_IS_EQUAL(mat6.dimension(0), 2);
+  VERIFY_IS_EQUAL(mat6.dimension(1), 3);
+  VERIFY_IS_EQUAL(mat6.dimension(2), 7);
+
+  val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(mat6(i,j,k), val);
+        val++;
+      }
+    }
+  }
+}
+
+
+static int f(const TensorMap<Tensor<int, 3> >& tensor) {
+  //  Size<0> empty;
+  EIGEN_STATIC_ASSERT((internal::array_size<Sizes<> >::value == 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  EIGEN_STATIC_ASSERT((internal::array_size<DSizes<int, 0> >::value == 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
+  Tensor<int, 0> result = tensor.sum();
+  return result();
+}
+
+static void test_casting()
+{
+  Tensor<int, 3> tensor(2,3,7);
+
+  int val = 0;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        tensor(i,j,k) = val;
+        val++;
+      }
+    }
+  }
+
+  TensorMap<Tensor<int, 3> > map(tensor);
+  int sum1 = f(map);
+  int sum2 = f(tensor);
+
+  VERIFY_IS_EQUAL(sum1, sum2);
+  VERIFY_IS_EQUAL(sum1, 861);
+}
+
+void test_cxx11_tensor_map()
+{
+  CALL_SUBTEST(test_0d());
+  CALL_SUBTEST(test_1d());
+  CALL_SUBTEST(test_2d());
+  CALL_SUBTEST(test_3d());
+
+  CALL_SUBTEST(test_from_tensor());
+  CALL_SUBTEST(test_casting());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_math.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_math.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_math.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_math.cpp
@@ -0,0 +1,46 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_tanh()
+{
+  Tensor<float, 1> vec1(6);
+  vec1.setRandom();
+
+  Tensor<float, 1> vec2 = vec1.tanh();
+
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_APPROX(vec2(i), tanhf(vec1(i)));
+  }
+}
+
+static void test_sigmoid()
+{
+  Tensor<float, 1> vec1(6);
+  vec1.setRandom();
+
+  Tensor<float, 1> vec2 = vec1.sigmoid();
+
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_APPROX(vec2(i), 1.0f / (1.0f + std::exp(-vec1(i))));
+  }
+}
+
+
+void test_cxx11_tensor_math()
+{
+  CALL_SUBTEST(test_tanh());
+  CALL_SUBTEST(test_sigmoid());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_mixed_indices.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_mixed_indices.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_mixed_indices.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_mixed_indices.cpp
@@ -0,0 +1,53 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+
+static void test_simple()
+{
+  Tensor<float, 1, ColMajor> vec1(6);
+  Tensor<float, 1, ColMajor, int> vec2(6);
+
+  vec1(0) = 4.0;  vec2(0) = 0.0;
+  vec1(1) = 8.0;  vec2(1) = 1.0;
+  vec1(2) = 15.0; vec2(2) = 2.0;
+  vec1(3) = 16.0; vec2(3) = 3.0;
+  vec1(4) = 23.0; vec2(4) = 4.0;
+  vec1(5) = 42.0; vec2(5) = 5.0;
+
+  float data3[6];
+  TensorMap<Tensor<float, 1, ColMajor>> vec3(data3, 6);
+  vec3 = vec1.sqrt();
+  float data4[6];
+  TensorMap<Tensor<float, 1, ColMajor, int>> vec4(data4, 6);
+  vec4 = vec2.square();
+
+  VERIFY_IS_APPROX(vec3(0), sqrtf(4.0));
+  VERIFY_IS_APPROX(vec3(1), sqrtf(8.0));
+  VERIFY_IS_APPROX(vec3(2), sqrtf(15.0));
+  VERIFY_IS_APPROX(vec3(3), sqrtf(16.0));
+  VERIFY_IS_APPROX(vec3(4), sqrtf(23.0));
+  VERIFY_IS_APPROX(vec3(5), sqrtf(42.0));
+
+  VERIFY_IS_APPROX(vec4(0), 0.0f);
+  VERIFY_IS_APPROX(vec4(1), 1.0f);
+  VERIFY_IS_APPROX(vec4(2), 2.0f * 2.0f);
+  VERIFY_IS_APPROX(vec4(3), 3.0f * 3.0f);
+  VERIFY_IS_APPROX(vec4(4), 4.0f * 4.0f);
+  VERIFY_IS_APPROX(vec4(5), 5.0f * 5.0f);
+}
+
+
+void test_cxx11_tensor_mixed_indices()
+{
+  CALL_SUBTEST(test_simple());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_morphing.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_morphing.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_morphing.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_morphing.cpp
@@ -0,0 +1,485 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<typename>
+static void test_simple_reshape()
+{
+  Tensor<float, 5> tensor1(2,3,1,7,1);
+  tensor1.setRandom();
+
+  Tensor<float, 3> tensor2(2,3,7);
+  Tensor<float, 2> tensor3(6,7);
+  Tensor<float, 2> tensor4(2,21);
+
+  Tensor<float, 3>::Dimensions dim1(2,3,7);
+  tensor2 = tensor1.reshape(dim1);
+  Tensor<float, 2>::Dimensions dim2(6,7);
+  tensor3 = tensor1.reshape(dim2);
+  Tensor<float, 2>::Dimensions dim3(2,21);
+  tensor4 = tensor1.reshape(dim1).reshape(dim3);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor2(i,j,k));
+        VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor3(i+2*j,k));
+        VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor4(i,j+3*k));
+      }
+    }
+  }
+}
+
+template<typename>
+static void test_reshape_in_expr() {
+  MatrixXf m1(2,3*5*7*11);
+  MatrixXf m2(3*5*7*11,13);
+  m1.setRandom();
+  m2.setRandom();
+  MatrixXf m3 = m1 * m2;
+
+  TensorMap<Tensor<float, 5>> tensor1(m1.data(), 2,3,5,7,11);
+  TensorMap<Tensor<float, 5>> tensor2(m2.data(), 3,5,7,11,13);
+  Tensor<float, 2>::Dimensions newDims1(2,3*5*7*11);
+  Tensor<float, 2>::Dimensions newDims2(3*5*7*11,13);
+  typedef Tensor<float, 1>::DimensionPair DimPair;
+  array<DimPair, 1> contract_along{{DimPair(1, 0)}};
+  Tensor<float, 2> tensor3(2,13);
+  tensor3 = tensor1.reshape(newDims1).contract(tensor2.reshape(newDims2), contract_along);
+
+  Map<MatrixXf> res(tensor3.data(), 2, 13);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 13; ++j) {
+      VERIFY_IS_APPROX(res(i,j), m3(i,j));
+    }
+  }
+}
+
+template<typename>
+static void test_reshape_as_lvalue()
+{
+  Tensor<float, 3> tensor(2,3,7);
+  tensor.setRandom();
+
+  Tensor<float, 2> tensor2d(6,7);
+  Tensor<float, 3>::Dimensions dim(2,3,7);
+  tensor2d.reshape(dim) = tensor;
+
+  float scratch[2*3*1*7*1];
+  TensorMap<Tensor<float, 5>> tensor5d(scratch, 2,3,1,7,1);
+  tensor5d.reshape(dim).device(Eigen::DefaultDevice()) = tensor;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(tensor2d(i+2*j,k), tensor(i,j,k));
+        VERIFY_IS_EQUAL(tensor5d(i,j,0,k,0), tensor(i,j,k));
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+static void test_simple_slice()
+{
+  Tensor<float, 5, DataLayout> tensor(2,3,5,7,11);
+  tensor.setRandom();
+
+  Tensor<float, 5, DataLayout> slice1(1,1,1,1,1);
+  Eigen::DSizes<ptrdiff_t, 5> indices(1,2,3,4,5);
+  Eigen::DSizes<ptrdiff_t, 5> sizes(1,1,1,1,1);
+  slice1 = tensor.slice(indices, sizes);
+  VERIFY_IS_EQUAL(slice1(0,0,0,0,0), tensor(1,2,3,4,5));
+
+  Tensor<float, 5, DataLayout> slice2(1,1,2,2,3);
+  Eigen::DSizes<ptrdiff_t, 5> indices2(1,1,3,4,5);
+  Eigen::DSizes<ptrdiff_t, 5> sizes2(1,1,2,2,3);
+  slice2 = tensor.slice(indices2, sizes2);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 2; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        VERIFY_IS_EQUAL(slice2(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k));
+      }
+    }
+  }
+}
+
+template<typename=void>
+static void test_const_slice()
+{
+  const float b[1] = {42};
+  TensorMap<Tensor<const float, 1> > m(b, 1);
+  DSizes<DenseIndex, 1> offsets;
+  offsets[0] = 0;
+  TensorRef<Tensor<const float, 1> > slice_ref(m.slice(offsets, m.dimensions()));
+  VERIFY_IS_EQUAL(slice_ref(0), 42);
+}
+
+template<int DataLayout>
+static void test_slice_in_expr() {
+  typedef Matrix<float, Dynamic, Dynamic, DataLayout> Mtx;
+  Mtx m1(7,7);
+  Mtx m2(3,3);
+  m1.setRandom();
+  m2.setRandom();
+
+  Mtx m3 = m1.block(1, 2, 3, 3) * m2.block(0, 2, 3, 1);
+
+  TensorMap<Tensor<float, 2, DataLayout>> tensor1(m1.data(), 7, 7);
+  TensorMap<Tensor<float, 2, DataLayout>> tensor2(m2.data(), 3, 3);
+  Tensor<float, 2, DataLayout> tensor3(3,1);
+  typedef Tensor<float, 1>::DimensionPair DimPair;
+  array<DimPair, 1> contract_along{{DimPair(1, 0)}};
+
+  Eigen::DSizes<ptrdiff_t, 2> indices1(1,2);
+  Eigen::DSizes<ptrdiff_t, 2> sizes1(3,3);
+  Eigen::DSizes<ptrdiff_t, 2> indices2(0,2);
+  Eigen::DSizes<ptrdiff_t, 2> sizes2(3,1);
+  tensor3 = tensor1.slice(indices1, sizes1).contract(tensor2.slice(indices2, sizes2), contract_along);
+
+  Map<Mtx> res(tensor3.data(), 3, 1);
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 1; ++j) {
+      VERIFY_IS_APPROX(res(i,j), m3(i,j));
+    }
+  }
+
+  // Take an arbitrary slice of an arbitrarily sized tensor.
+  TensorMap<Tensor<const float, 2, DataLayout>> tensor4(m1.data(), 7, 7);
+  Tensor<float, 1, DataLayout> tensor6 = tensor4.reshape(DSizes<ptrdiff_t, 1>(7*7)).exp().slice(DSizes<ptrdiff_t, 1>(0), DSizes<ptrdiff_t, 1>(35));
+  for (int i = 0; i < 35; ++i) {
+    VERIFY_IS_APPROX(tensor6(i), expf(tensor4.data()[i]));
+  }
+}
+
+template<int DataLayout>
+static void test_slice_as_lvalue()
+{
+  Tensor<float, 3, DataLayout> tensor1(2,2,7);
+  tensor1.setRandom();
+  Tensor<float, 3, DataLayout> tensor2(2,2,7);
+  tensor2.setRandom();
+  Tensor<float, 3, DataLayout> tensor3(4,3,5);
+  tensor3.setRandom();
+  Tensor<float, 3, DataLayout> tensor4(4,3,2);
+  tensor4.setRandom();
+  Tensor<float, 3, DataLayout> tensor5(10,13,12);
+  tensor5.setRandom();
+
+  Tensor<float, 3, DataLayout> result(4,5,7);
+  Eigen::DSizes<ptrdiff_t, 3> sizes12(2,2,7);
+  Eigen::DSizes<ptrdiff_t, 3> first_slice(0,0,0);
+  result.slice(first_slice, sizes12) = tensor1;
+  Eigen::DSizes<ptrdiff_t, 3> second_slice(2,0,0);
+  result.slice(second_slice, sizes12).device(Eigen::DefaultDevice()) = tensor2;
+
+  Eigen::DSizes<ptrdiff_t, 3> sizes3(4,3,5);
+  Eigen::DSizes<ptrdiff_t, 3> third_slice(0,2,0);
+  result.slice(third_slice, sizes3) = tensor3;
+
+  Eigen::DSizes<ptrdiff_t, 3> sizes4(4,3,2);
+  Eigen::DSizes<ptrdiff_t, 3> fourth_slice(0,2,5);
+  result.slice(fourth_slice, sizes4) = tensor4;
+
+  for (int j = 0; j < 2; ++j) {
+    for (int k = 0; k < 7; ++k) {
+      for (int i = 0; i < 2; ++i) {
+        VERIFY_IS_EQUAL(result(i,j,k), tensor1(i,j,k));
+        VERIFY_IS_EQUAL(result(i+2,j,k), tensor2(i,j,k));
+      }
+    }
+  }
+  for (int i = 0; i < 4; ++i) {
+    for (int j = 2; j < 5; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        VERIFY_IS_EQUAL(result(i,j,k), tensor3(i,j-2,k));
+      }
+      for (int k = 5; k < 7; ++k) {
+        VERIFY_IS_EQUAL(result(i,j,k), tensor4(i,j-2,k-5));
+      }
+    }
+  }
+
+  Eigen::DSizes<ptrdiff_t, 3> sizes5(4,5,7);
+  Eigen::DSizes<ptrdiff_t, 3> fifth_slice(0,0,0);
+  result.slice(fifth_slice, sizes5) = tensor5.slice(fifth_slice, sizes5);
+  for (int i = 0; i < 4; ++i) {
+    for (int j = 2; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(result(i,j,k), tensor5(i,j,k));
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+static void test_slice_raw_data()
+{
+  Tensor<float, 4, DataLayout> tensor(3,5,7,11);
+  tensor.setRandom();
+
+  Eigen::DSizes<ptrdiff_t, 4> offsets(1,2,3,4);
+  Eigen::DSizes<ptrdiff_t, 4> extents(1,1,1,1);
+  typedef TensorEvaluator<decltype(tensor.slice(offsets, extents)), DefaultDevice> SliceEvaluator;
+  auto slice1 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+  VERIFY_IS_EQUAL(slice1.dimensions().TotalSize(), 1);
+  VERIFY_IS_EQUAL(slice1.data()[0], tensor(1,2,3,4));
+
+  if (DataLayout == ColMajor) {
+    extents = Eigen::DSizes<ptrdiff_t, 4>(2,1,1,1);
+    auto slice2 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+    VERIFY_IS_EQUAL(slice2.dimensions().TotalSize(), 2);
+    VERIFY_IS_EQUAL(slice2.data()[0], tensor(1,2,3,4));
+    VERIFY_IS_EQUAL(slice2.data()[1], tensor(2,2,3,4));
+  } else {
+    extents = Eigen::DSizes<ptrdiff_t, 4>(1,1,1,2);
+    auto slice2 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+    VERIFY_IS_EQUAL(slice2.dimensions().TotalSize(), 2);
+    VERIFY_IS_EQUAL(slice2.data()[0], tensor(1,2,3,4));
+    VERIFY_IS_EQUAL(slice2.data()[1], tensor(1,2,3,5));
+  }
+
+  extents = Eigen::DSizes<ptrdiff_t, 4>(1,2,1,1);
+  auto slice3 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+  VERIFY_IS_EQUAL(slice3.dimensions().TotalSize(), 2);
+  VERIFY_IS_EQUAL(slice3.data(), static_cast<float*>(0));
+
+  if (DataLayout == ColMajor) {
+    offsets = Eigen::DSizes<ptrdiff_t, 4>(0,2,3,4);
+    extents = Eigen::DSizes<ptrdiff_t, 4>(3,2,1,1);
+    auto slice4 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+    VERIFY_IS_EQUAL(slice4.dimensions().TotalSize(), 6);
+    for (int i = 0; i < 3; ++i) {
+      for (int j = 0; j < 2; ++j) {
+        VERIFY_IS_EQUAL(slice4.data()[i+3*j], tensor(i,2+j,3,4));
+      }
+    }
+  } else {
+    offsets = Eigen::DSizes<ptrdiff_t, 4>(1,2,3,0);
+    extents = Eigen::DSizes<ptrdiff_t, 4>(1,1,2,11);
+    auto slice4 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+    VERIFY_IS_EQUAL(slice4.dimensions().TotalSize(), 22);
+    for (int l = 0; l < 11; ++l) {
+      for (int k = 0; k < 2; ++k) {
+        VERIFY_IS_EQUAL(slice4.data()[l+11*k], tensor(1,2,3+k,l));
+      }
+    }
+  }
+
+  if (DataLayout == ColMajor) {
+    offsets = Eigen::DSizes<ptrdiff_t, 4>(0,0,0,4);
+    extents = Eigen::DSizes<ptrdiff_t, 4>(3,5,7,2);
+    auto slice5 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+    VERIFY_IS_EQUAL(slice5.dimensions().TotalSize(), 210);
+    for (int i = 0; i < 3; ++i) {
+      for (int j = 0; j < 5; ++j) {
+        for (int k = 0; k < 7; ++k) {
+          for (int l = 0; l < 2; ++l) {
+            int slice_index = i + 3 * (j + 5 * (k + 7 * l));
+            VERIFY_IS_EQUAL(slice5.data()[slice_index], tensor(i,j,k,l+4));
+          }
+        }
+      }
+    }
+  } else {
+    offsets = Eigen::DSizes<ptrdiff_t, 4>(1,0,0,0);
+    extents = Eigen::DSizes<ptrdiff_t, 4>(2,5,7,11);
+    auto slice5 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+    VERIFY_IS_EQUAL(slice5.dimensions().TotalSize(), 770);
+    for (int l = 0; l < 11; ++l) {
+      for (int k = 0; k < 7; ++k) {
+        for (int j = 0; j < 5; ++j) {
+          for (int i = 0; i < 2; ++i) {
+            int slice_index = l + 11 * (k + 7 * (j + 5 * i));
+            VERIFY_IS_EQUAL(slice5.data()[slice_index], tensor(i+1,j,k,l));
+          }
+        }
+      }
+    }
+
+  }
+
+  offsets = Eigen::DSizes<ptrdiff_t, 4>(0,0,0,0);
+  extents = Eigen::DSizes<ptrdiff_t, 4>(3,5,7,11);
+  auto slice6 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
+  VERIFY_IS_EQUAL(slice6.dimensions().TotalSize(), 3*5*7*11);
+  VERIFY_IS_EQUAL(slice6.data(), tensor.data());
+}
+
+
+template<int DataLayout>
+static void test_strided_slice()
+{
+  typedef Tensor<float, 5, DataLayout> Tensor5f;
+  typedef Eigen::DSizes<Eigen::DenseIndex, 5> Index5;
+  typedef Tensor<float, 2, DataLayout> Tensor2f;
+  typedef Eigen::DSizes<Eigen::DenseIndex, 2> Index2;
+  Tensor<float, 5, DataLayout> tensor(2,3,5,7,11);
+  Tensor<float, 2, DataLayout> tensor2(7,11);
+  tensor.setRandom();
+  tensor2.setRandom();
+
+  if (true) {
+    Tensor2f slice(2,3);
+    Index2 strides(-2,-1);
+    Index2 indicesStart(5,7);
+    Index2 indicesStop(0,4);
+    slice = tensor2.stridedSlice(indicesStart, indicesStop, strides);
+    for (int j = 0; j < 2; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        VERIFY_IS_EQUAL(slice(j,k), tensor2(5-2*j,7-k));
+      }
+    }
+  }
+
+  if(true) {
+    Tensor2f slice(0,1);
+    Index2 strides(1,1);
+    Index2 indicesStart(5,4);
+    Index2 indicesStop(5,5);
+    slice = tensor2.stridedSlice(indicesStart, indicesStop, strides);
+  }
+
+  if(true) { // test clamped degenerate interavls
+    Tensor2f slice(7,11);
+    Index2 strides(1,-1);
+    Index2 indicesStart(-3,20); // should become 0,10
+    Index2 indicesStop(20,-11); // should become 11, -1
+    slice = tensor2.stridedSlice(indicesStart, indicesStop, strides);
+    for (int j = 0; j < 7; ++j) {
+      for (int k = 0; k < 11; ++k) {
+        VERIFY_IS_EQUAL(slice(j,k), tensor2(j,10-k));
+      }
+    }
+  }
+
+  if(true) {
+    Tensor5f slice1(1,1,1,1,1);
+    Eigen::DSizes<Eigen::DenseIndex, 5> indicesStart(1, 2, 3, 4, 5);
+    Eigen::DSizes<Eigen::DenseIndex, 5> indicesStop(2, 3, 4, 5, 6);
+    Eigen::DSizes<Eigen::DenseIndex, 5> strides(1, 1, 1, 1, 1);
+    slice1 = tensor.stridedSlice(indicesStart, indicesStop, strides);
+    VERIFY_IS_EQUAL(slice1(0,0,0,0,0), tensor(1,2,3,4,5));
+  }
+
+  if(true) {
+    Tensor5f slice(1,1,2,2,3);
+    Index5 start(1, 1, 3, 4, 5);
+    Index5 stop(2, 2, 5, 6, 8);
+    Index5 strides(1, 1, 1, 1, 1);
+    slice = tensor.stridedSlice(start, stop, strides);
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 2; ++j) {
+        for (int k = 0; k < 3; ++k) {
+          VERIFY_IS_EQUAL(slice(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k));
+        }
+      }
+    }
+  }
+
+  if(true) {
+    Tensor5f slice(1,1,2,2,3);
+    Index5 strides3(1, 1, -2, 1, -1);
+    Index5 indices3Start(1, 1, 4, 4, 7);
+    Index5 indices3Stop(2, 2, 0, 6, 4);
+    slice = tensor.stridedSlice(indices3Start, indices3Stop, strides3);
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 2; ++j) {
+        for (int k = 0; k < 3; ++k) {
+          VERIFY_IS_EQUAL(slice(0,0,i,j,k), tensor(1,1,4-2*i,4+j,7-k));
+        }
+      }
+    }
+  }
+
+  if(false) { // tests degenerate interval
+    Tensor5f slice(1,1,2,2,3);
+    Index5 strides3(1, 1, 2, 1, 1);
+    Index5 indices3Start(1, 1, 4, 4, 7);
+    Index5 indices3Stop(2, 2, 0, 6, 4);
+    slice = tensor.stridedSlice(indices3Start, indices3Stop, strides3);
+  }
+}
+
+template<int DataLayout>
+static void test_strided_slice_write()
+{
+  typedef Tensor<float, 2, DataLayout> Tensor2f;
+  typedef Eigen::DSizes<Eigen::DenseIndex, 2> Index2;
+
+  Tensor<float, 2, DataLayout> tensor(7,11),tensor2(7,11);
+  tensor.setRandom();
+  tensor2=tensor;
+  Tensor2f slice(2,3);
+
+  slice.setRandom();
+
+  Index2 strides(1,1);
+  Index2 indicesStart(3,4);
+  Index2 indicesStop(5,7);
+  Index2 lengths(2,3);
+
+  tensor.slice(indicesStart,lengths)=slice;
+  tensor2.stridedSlice(indicesStart,indicesStop,strides)=slice;
+
+  for(int i=0;i<7;i++) for(int j=0;j<11;j++){
+    VERIFY_IS_EQUAL(tensor(i,j), tensor2(i,j));
+  }
+}
+
+
+template<int DataLayout>
+static void test_composition()
+{
+  Eigen::Tensor<float, 2, DataLayout> matrix(7, 11);
+  matrix.setRandom();
+
+  const DSizes<ptrdiff_t, 3> newDims(1, 1, 11);
+  Eigen::Tensor<float, 3, DataLayout> tensor =
+      matrix.slice(DSizes<ptrdiff_t, 2>(2, 0), DSizes<ptrdiff_t, 2>(1, 11)).reshape(newDims);
+
+  VERIFY_IS_EQUAL(tensor.dimensions().TotalSize(), 11);
+  VERIFY_IS_EQUAL(tensor.dimension(0), 1);
+  VERIFY_IS_EQUAL(tensor.dimension(1), 1);
+  VERIFY_IS_EQUAL(tensor.dimension(2), 11);
+  for (int i = 0; i < 11; ++i) {
+    VERIFY_IS_EQUAL(tensor(0,0,i), matrix(2,i));
+  }
+}
+
+
+void test_cxx11_tensor_morphing()
+{
+  CALL_SUBTEST_1(test_simple_reshape<void>());
+  CALL_SUBTEST_1(test_reshape_in_expr<void>());
+  CALL_SUBTEST_1(test_reshape_as_lvalue<void>());
+
+  CALL_SUBTEST_1(test_simple_slice<ColMajor>());
+  CALL_SUBTEST_1(test_simple_slice<RowMajor>());
+  CALL_SUBTEST_1(test_const_slice());
+  CALL_SUBTEST_2(test_slice_in_expr<ColMajor>());
+  CALL_SUBTEST_3(test_slice_in_expr<RowMajor>());
+  CALL_SUBTEST_4(test_slice_as_lvalue<ColMajor>());
+  CALL_SUBTEST_4(test_slice_as_lvalue<RowMajor>());
+  CALL_SUBTEST_5(test_slice_raw_data<ColMajor>());
+  CALL_SUBTEST_5(test_slice_raw_data<RowMajor>());
+
+  CALL_SUBTEST_6(test_strided_slice_write<ColMajor>());
+  CALL_SUBTEST_6(test_strided_slice<ColMajor>());
+  CALL_SUBTEST_6(test_strided_slice_write<RowMajor>());
+  CALL_SUBTEST_6(test_strided_slice<RowMajor>());
+
+  CALL_SUBTEST_7(test_composition<ColMajor>());
+  CALL_SUBTEST_7(test_composition<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_notification.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_notification.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_notification.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_notification.cpp
@@ -0,0 +1,81 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Vijay Vasudevan <vrv@google.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_USE_THREADS
+
+#include <stdlib.h>
+#include "main.h"
+#include <Eigen/CXX11/Tensor>
+
+#if EIGEN_OS_WIN || EIGEN_OS_WIN64
+#include <windows.h>
+void sleep(int seconds) {
+  Sleep(seconds*1000);
+}
+#else
+#include <unistd.h>
+#endif
+
+
+namespace {
+
+void WaitAndAdd(Eigen::Notification* n, int* counter) {
+  n->Wait();
+  *counter = *counter + 1;
+}
+
+}  // namespace
+
+static void test_notification_single()
+{
+  ThreadPool thread_pool(1);
+
+  int counter = 0;
+  Eigen::Notification n;
+  std::function<void()> func = std::bind(&WaitAndAdd, &n, &counter);
+  thread_pool.Schedule(func);
+  sleep(1);
+
+  // The thread should be waiting for the notification.
+  VERIFY_IS_EQUAL(counter, 0);
+
+  // Unblock the thread
+  n.Notify();
+
+  sleep(1);
+
+  // Verify the counter has been incremented
+  VERIFY_IS_EQUAL(counter, 1);
+}
+
+// Like test_notification_single() but enqueues multiple threads to
+// validate that all threads get notified by Notify().
+static void test_notification_multiple()
+{
+  ThreadPool thread_pool(1);
+
+  int counter = 0;
+  Eigen::Notification n;
+  std::function<void()> func = std::bind(&WaitAndAdd, &n, &counter);
+  thread_pool.Schedule(func);
+  thread_pool.Schedule(func);
+  thread_pool.Schedule(func);
+  thread_pool.Schedule(func);
+  sleep(1);
+  VERIFY_IS_EQUAL(counter, 0);
+  n.Notify();
+  sleep(1);
+  VERIFY_IS_EQUAL(counter, 4);
+}
+
+void test_cxx11_tensor_notification()
+{
+  CALL_SUBTEST(test_notification_single());
+  CALL_SUBTEST(test_notification_multiple());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_of_complex.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_of_complex.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_of_complex.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_of_complex.cpp
@@ -0,0 +1,103 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::TensorMap;
+
+
+
+static void test_additions()
+{
+  Tensor<std::complex<float>, 1> data1(3);
+  Tensor<std::complex<float>, 1> data2(3);
+  for (int i = 0; i < 3; ++i) {
+    data1(i) = std::complex<float>(i, -i);
+    data2(i) = std::complex<float>(i, 7 * i);
+  }
+
+  Tensor<std::complex<float>, 1> sum = data1 + data2;
+  for (int i = 0; i < 3; ++i) {
+    VERIFY_IS_EQUAL(sum(i),  std::complex<float>(2*i, 6*i));
+  }
+}
+
+
+static void test_abs()
+{
+  Tensor<std::complex<float>, 1> data1(3);
+  Tensor<std::complex<double>, 1> data2(3);
+  data1.setRandom();
+  data2.setRandom();
+
+  Tensor<float, 1> abs1 = data1.abs();
+  Tensor<double, 1> abs2 = data2.abs();
+  for (int i = 0; i < 3; ++i) {
+    VERIFY_IS_APPROX(abs1(i), std::abs(data1(i)));
+    VERIFY_IS_APPROX(abs2(i), std::abs(data2(i)));
+  }
+}
+
+
+static void test_conjugate()
+{
+  Tensor<std::complex<float>, 1> data1(3);
+  Tensor<std::complex<double>, 1> data2(3);
+  Tensor<int, 1> data3(3);
+  data1.setRandom();
+  data2.setRandom();
+  data3.setRandom();
+
+  Tensor<std::complex<float>, 1> conj1 = data1.conjugate();
+  Tensor<std::complex<double>, 1> conj2 = data2.conjugate();
+  Tensor<int, 1> conj3 = data3.conjugate();
+  for (int i = 0; i < 3; ++i) {
+    VERIFY_IS_APPROX(conj1(i), std::conj(data1(i)));
+    VERIFY_IS_APPROX(conj2(i), std::conj(data2(i)));
+    VERIFY_IS_APPROX(conj3(i), data3(i));
+  }
+}
+
+static void test_contractions()
+{
+  Tensor<std::complex<float>, 4> t_left(30, 50, 8, 31);
+  Tensor<std::complex<float>, 5> t_right(8, 31, 7, 20, 10);
+  Tensor<std::complex<float>, 5> t_result(30, 50, 7, 20, 10);
+
+  t_left.setRandom();
+  t_right.setRandom();
+
+  typedef Map<Matrix<std::complex<float>, Dynamic, Dynamic>> MapXcf;
+  MapXcf m_left(t_left.data(), 1500, 248);
+  MapXcf m_right(t_right.data(), 248, 1400);
+  Matrix<std::complex<float>, Dynamic, Dynamic> m_result(1500, 1400);
+
+  // This contraction should be equivalent to a regular matrix multiplication
+  typedef Tensor<float, 1>::DimensionPair DimPair;
+  Eigen::array<DimPair, 2> dims;
+  dims[0] = DimPair(2, 0);
+  dims[1] = DimPair(3, 1);
+  t_result = t_left.contract(t_right, dims);
+  m_result = m_left * m_right;
+  for (int i = 0; i < t_result.dimensions().TotalSize(); i++) {
+    VERIFY_IS_APPROX(t_result.data()[i], m_result.data()[i]);
+  }
+}
+
+
+void test_cxx11_tensor_of_complex()
+{
+  CALL_SUBTEST(test_additions());
+  CALL_SUBTEST(test_abs());
+  CALL_SUBTEST(test_conjugate());
+  CALL_SUBTEST(test_contractions());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_of_const_values.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_of_const_values.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_of_const_values.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_of_const_values.cpp
@@ -0,0 +1,105 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_assign()
+{
+  float data1[6];
+  TensorMap<Tensor<const float, 2>> mat1(data1, 2, 3);
+  float data2[6];
+  const TensorMap<Tensor<float, 2>> mat2(data2, 2, 3);
+
+  for (int i = 0; i < 6; ++i) {
+    data1[i] = i;
+    data2[i] = -i;
+  }
+
+  Tensor<float, 2> rslt1;
+  rslt1 = mat1;
+  Tensor<float, 2> rslt2;
+  rslt2 = mat2;
+
+  Tensor<float, 2> rslt3 = mat1;
+  Tensor<float, 2> rslt4 = mat2;
+
+  Tensor<float, 2> rslt5(mat1);
+  Tensor<float, 2> rslt6(mat2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_APPROX(rslt1(i,j), static_cast<float>(i + 2*j));
+      VERIFY_IS_APPROX(rslt2(i,j), static_cast<float>(-i - 2*j));
+      VERIFY_IS_APPROX(rslt3(i,j), static_cast<float>(i + 2*j));
+      VERIFY_IS_APPROX(rslt4(i,j), static_cast<float>(-i - 2*j));
+      VERIFY_IS_APPROX(rslt5(i,j), static_cast<float>(i + 2*j));
+      VERIFY_IS_APPROX(rslt6(i,j), static_cast<float>(-i - 2*j));
+    }
+  }
+}
+
+
+static void test_plus()
+{
+  float data1[6];
+  TensorMap<Tensor<const float, 2>> mat1(data1, 2, 3);
+  float data2[6];
+  TensorMap<Tensor<float, 2>> mat2(data2, 2, 3);
+
+  for (int i = 0; i < 6; ++i) {
+    data1[i] = i;
+    data2[i] = -i;
+  }
+
+  Tensor<float, 2> sum1;
+  sum1 = mat1 + mat2;
+  Tensor<float, 2> sum2;
+  sum2 = mat2 + mat1;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_APPROX(sum1(i,j), 0.0f);
+      VERIFY_IS_APPROX(sum2(i,j), 0.0f);
+    }
+  }
+}
+
+
+static void test_plus_equal()
+{
+  float data1[6];
+  TensorMap<Tensor<const float, 2>> mat1(data1, 2, 3);
+  float data2[6];
+  TensorMap<Tensor<float, 2>> mat2(data2, 2, 3);
+
+  for (int i = 0; i < 6; ++i) {
+    data1[i] = i;
+    data2[i] = -i;
+  }
+  mat2 += mat1;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_APPROX(mat2(i,j), 0.0f);
+    }
+  }
+}
+
+
+void test_cxx11_tensor_of_const_values()
+{
+  CALL_SUBTEST(test_assign());
+  CALL_SUBTEST(test_plus());
+  CALL_SUBTEST(test_plus_equal());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_of_float16_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_of_float16_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_of_float16_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_of_float16_cuda.cu
@@ -0,0 +1,494 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_of_float16_cuda
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<typename>
+void test_cuda_numext() {
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int num_elem = 101;
+
+  float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  bool* d_res_half = (bool*)gpu_device.allocate(num_elem * sizeof(bool));
+  bool* d_res_float = (bool*)gpu_device.allocate(num_elem * sizeof(bool));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float(
+      d_float, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<bool, 1>, Eigen::Aligned> gpu_res_half(
+      d_res_half, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<bool, 1>, Eigen::Aligned> gpu_res_float(
+      d_res_float, num_elem);
+
+  gpu_float.device(gpu_device) = gpu_float.random() - gpu_float.constant(0.5f);
+  gpu_res_float.device(gpu_device) = gpu_float.unaryExpr(Eigen::internal::scalar_isnan_op<float>());
+  gpu_res_half.device(gpu_device) = gpu_float.cast<Eigen::half>().unaryExpr(Eigen::internal::scalar_isnan_op<Eigen::half>());
+
+  Tensor<bool, 1> half_prec(num_elem);
+  Tensor<bool, 1> full_prec(num_elem);
+  gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, num_elem*sizeof(bool));
+  gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(bool));
+  gpu_device.synchronize();
+
+  for (int i = 0; i < num_elem; ++i) {
+    std::cout << "Checking numext " << i << std::endl;
+    VERIFY_IS_EQUAL(full_prec(i), half_prec(i));
+  }
+
+  gpu_device.deallocate(d_float);
+  gpu_device.deallocate(d_res_half);
+  gpu_device.deallocate(d_res_float);
+}
+
+
+#ifdef EIGEN_HAS_CUDA_FP16
+
+template<typename>
+void test_cuda_conversion() {
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int num_elem = 101;
+  
+  float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  Eigen::half* d_half = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+  float* d_conv = (float*)gpu_device.allocate(num_elem * sizeof(float));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float(
+      d_float, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_half(
+      d_half, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_conv(
+      d_conv, num_elem);
+
+  gpu_float.device(gpu_device) = gpu_float.random();
+  gpu_half.device(gpu_device) = gpu_float.cast<Eigen::half>();
+  gpu_conv.device(gpu_device) = gpu_half.cast<float>();
+
+  Tensor<float, 1> initial(num_elem);
+  Tensor<float, 1> final(num_elem);
+  gpu_device.memcpyDeviceToHost(initial.data(), d_float, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(final.data(), d_conv, num_elem*sizeof(float));
+
+  for (int i = 0; i < num_elem; ++i) {
+    VERIFY_IS_APPROX(initial(i), final(i));
+  }
+
+  gpu_device.deallocate(d_float);
+  gpu_device.deallocate(d_half);
+  gpu_device.deallocate(d_conv);
+}
+
+template<typename>
+void test_cuda_unary() {
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int num_elem = 101;
+
+  float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_res_half = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_res_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float(
+      d_float, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_half(
+      d_res_half, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_float(
+      d_res_float, num_elem);
+
+  gpu_float.device(gpu_device) = gpu_float.random() - gpu_float.constant(0.5f);
+  gpu_res_float.device(gpu_device) = gpu_float.abs();
+  gpu_res_half.device(gpu_device) = gpu_float.cast<Eigen::half>().abs().cast<float>();
+
+  Tensor<float, 1> half_prec(num_elem);
+  Tensor<float, 1> full_prec(num_elem);
+  gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(float));
+  gpu_device.synchronize();
+
+  for (int i = 0; i < num_elem; ++i) {
+    std::cout << "Checking unary " << i << std::endl;
+    VERIFY_IS_APPROX(full_prec(i), half_prec(i));
+  }
+
+  gpu_device.deallocate(d_float);
+  gpu_device.deallocate(d_res_half);
+  gpu_device.deallocate(d_res_float);
+}
+
+template<typename>
+void test_cuda_elementwise() {
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int num_elem = 101;
+
+  float* d_float1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_float2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_res_half = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_res_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float1(
+      d_float1, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float2(
+      d_float2, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_half(
+      d_res_half, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_float(
+      d_res_float, num_elem);
+
+  gpu_float1.device(gpu_device) = gpu_float1.random();
+  gpu_float2.device(gpu_device) = gpu_float2.random();
+  gpu_res_float.device(gpu_device) = (gpu_float1 + gpu_float2) * gpu_float1;
+  gpu_res_half.device(gpu_device) = ((gpu_float1.cast<Eigen::half>() + gpu_float2.cast<Eigen::half>()) * gpu_float1.cast<Eigen::half>()).cast<float>();
+
+  Tensor<float, 1> half_prec(num_elem);
+  Tensor<float, 1> full_prec(num_elem);
+  gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(float));
+  gpu_device.synchronize();
+
+  for (int i = 0; i < num_elem; ++i) {
+    std::cout << "Checking elemwise " << i << ": full prec = " << full_prec(i) << " vs half prec = " << half_prec(i) << std::endl;
+    VERIFY_IS_APPROX(static_cast<Eigen::half>(full_prec(i)), static_cast<Eigen::half>(half_prec(i)));
+  }
+
+  gpu_device.deallocate(d_float1);
+  gpu_device.deallocate(d_float2);
+  gpu_device.deallocate(d_res_half);
+  gpu_device.deallocate(d_res_float);
+}
+
+template<typename>
+void test_cuda_trancendental() {
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int num_elem = 101;
+
+  float* d_float1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_float2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_float3 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  Eigen::half* d_res1_half = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+  Eigen::half* d_res1_float = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+  Eigen::half* d_res2_half = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+  Eigen::half* d_res2_float = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+  Eigen::half* d_res3_half = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+  Eigen::half* d_res3_float = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float1(d_float1, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float2(d_float2, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float3(d_float3, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res1_half(d_res1_half, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res1_float(d_res1_float, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res2_half(d_res2_half, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res2_float(d_res2_float, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res3_half(d_res3_half, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res3_float(d_res3_float, num_elem);
+
+  gpu_float1.device(gpu_device) = gpu_float1.random() - gpu_float1.constant(0.5f);
+  gpu_float2.device(gpu_device) = gpu_float2.random() + gpu_float1.constant(0.5f);
+  gpu_float3.device(gpu_device) = gpu_float3.random();
+  gpu_res1_float.device(gpu_device) = gpu_float1.exp().cast<Eigen::half>();
+  gpu_res2_float.device(gpu_device) = gpu_float2.log().cast<Eigen::half>();
+  gpu_res3_float.device(gpu_device) = gpu_float3.log1p().cast<Eigen::half>();
+
+  gpu_res1_half.device(gpu_device) = gpu_float1.cast<Eigen::half>();
+  gpu_res1_half.device(gpu_device) = gpu_res1_half.exp();
+
+  gpu_res2_half.device(gpu_device) = gpu_float2.cast<Eigen::half>();
+  gpu_res2_half.device(gpu_device) = gpu_res2_half.log();
+
+  gpu_res3_half.device(gpu_device) = gpu_float3.cast<Eigen::half>();
+  gpu_res3_half.device(gpu_device) = gpu_res3_half.log1p();
+
+  Tensor<float, 1> input1(num_elem);
+  Tensor<Eigen::half, 1> half_prec1(num_elem);
+  Tensor<Eigen::half, 1> full_prec1(num_elem);
+  Tensor<float, 1> input2(num_elem);
+  Tensor<Eigen::half, 1> half_prec2(num_elem);
+  Tensor<Eigen::half, 1> full_prec2(num_elem);
+  Tensor<float, 1> input3(num_elem);
+  Tensor<Eigen::half, 1> half_prec3(num_elem);
+  Tensor<Eigen::half, 1> full_prec3(num_elem);
+  gpu_device.memcpyDeviceToHost(input1.data(), d_float1, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(input2.data(), d_float2, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(input3.data(), d_float3, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(half_prec1.data(), d_res1_half, num_elem*sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(full_prec1.data(), d_res1_float, num_elem*sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(half_prec2.data(), d_res2_half, num_elem*sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(full_prec2.data(), d_res2_float, num_elem*sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(half_prec3.data(), d_res3_half, num_elem*sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(full_prec3.data(), d_res3_float, num_elem*sizeof(Eigen::half));
+  gpu_device.synchronize();
+
+  for (int i = 0; i < num_elem; ++i) {
+    std::cout << "Checking elemwise exp " << i << " input = " << input1(i) << " full = " << full_prec1(i) << " half = " << half_prec1(i) << std::endl;
+    VERIFY_IS_APPROX(full_prec1(i), half_prec1(i));
+  }
+  for (int i = 0; i < num_elem; ++i) {
+    std::cout << "Checking elemwise log " << i << " input = " << input2(i) << " full = " << full_prec2(i) << " half = " << half_prec2(i) << std::endl;
+    if(std::abs(input2(i)-1.f)<0.05f) // log lacks accurary nearby 1
+      VERIFY_IS_APPROX(full_prec2(i)+Eigen::half(0.1f), half_prec2(i)+Eigen::half(0.1f));
+    else
+      VERIFY_IS_APPROX(full_prec2(i), half_prec2(i));
+  }
+  for (int i = 0; i < num_elem; ++i) {
+    std::cout << "Checking elemwise plog1 " << i << " input = " << input3(i) << " full = " << full_prec3(i) << " half = " << half_prec3(i) << std::endl;
+    VERIFY_IS_APPROX(full_prec3(i), half_prec3(i));
+  }
+  gpu_device.deallocate(d_float1);
+  gpu_device.deallocate(d_float2);
+  gpu_device.deallocate(d_float3);
+  gpu_device.deallocate(d_res1_half);
+  gpu_device.deallocate(d_res1_float);
+  gpu_device.deallocate(d_res2_half);
+  gpu_device.deallocate(d_res2_float);
+  gpu_device.deallocate(d_res3_float);
+  gpu_device.deallocate(d_res3_half);
+}
+
+template<typename>
+void test_cuda_contractions() {
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int rows = 23;
+  int cols = 23;
+  int num_elem = rows*cols;
+
+  float* d_float1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_float2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  Eigen::half* d_res_half = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+  Eigen::half* d_res_float = (Eigen::half*)gpu_device.allocate(num_elem * sizeof(Eigen::half));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float1(
+      d_float1, rows, cols);
+  Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float2(
+      d_float2, rows, cols);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 2>, Eigen::Aligned> gpu_res_half(
+      d_res_half, rows, cols);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 2>, Eigen::Aligned> gpu_res_float(
+      d_res_float, rows, cols);
+
+  gpu_float1.device(gpu_device) = gpu_float1.random() - gpu_float1.constant(0.5f);
+  gpu_float2.device(gpu_device) = gpu_float2.random() - gpu_float2.constant(0.5f);
+
+  typedef Tensor<float, 2>::DimensionPair DimPair;
+  Eigen::array<DimPair, 1> dims(DimPair(1, 0));
+  gpu_res_float.device(gpu_device) = gpu_float1.contract(gpu_float2, dims).cast<Eigen::half>();
+  gpu_res_half.device(gpu_device) = gpu_float1.cast<Eigen::half>().contract(gpu_float2.cast<Eigen::half>(), dims);
+
+  Tensor<Eigen::half, 2> half_prec(rows, cols);
+  Tensor<Eigen::half, 2> full_prec(rows, cols);
+  gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, num_elem*sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(Eigen::half));
+  gpu_device.synchronize();
+
+  for (int i = 0; i < rows; ++i) {
+    for (int j = 0; j < cols; ++j) {
+      std::cout << "Checking contract " << i << " " << j << full_prec(i, j) << " " << half_prec(i, j) << std::endl;
+      if (numext::abs(full_prec(i, j) - half_prec(i, j)) > Eigen::half(1e-2f)) {
+        VERIFY_IS_APPROX(full_prec(i, j), half_prec(i, j));
+      }
+    }
+  }
+
+  gpu_device.deallocate(d_float1);
+  gpu_device.deallocate(d_float2);
+  gpu_device.deallocate(d_res_half);
+  gpu_device.deallocate(d_res_float);
+}
+
+template<typename>
+void test_cuda_reductions(int size1, int size2, int redux) {
+
+   std::cout << "Reducing " << size1 << " by " << size2
+             << " tensor along dim " << redux << std::endl; 
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int num_elem = size1*size2;
+  int result_size = (redux == 1 ? size1 : size2);
+
+  float* d_float1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_float2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  Eigen::half* d_res_half = (Eigen::half*)gpu_device.allocate(result_size * sizeof(Eigen::half));
+  Eigen::half* d_res_float = (Eigen::half*)gpu_device.allocate(result_size * sizeof(Eigen::half));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float1(
+      d_float1, size1, size2);
+  Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float2(
+      d_float2, size1, size2);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res_half(
+      d_res_half, result_size);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res_float(
+      d_res_float, result_size);
+
+  gpu_float1.device(gpu_device) = gpu_float1.random() * 2.0f;
+  gpu_float2.device(gpu_device) = gpu_float2.random() * 2.0f;
+
+  Eigen::array<int, 1> redux_dim = {{redux}};
+  gpu_res_float.device(gpu_device) = gpu_float1.sum(redux_dim).cast<Eigen::half>();
+  gpu_res_half.device(gpu_device) = gpu_float1.cast<Eigen::half>().sum(redux_dim);
+
+  Tensor<Eigen::half, 1> half_prec(result_size);
+  Tensor<Eigen::half, 1> full_prec(result_size);
+  gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, result_size*sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, result_size*sizeof(Eigen::half));
+  gpu_device.synchronize();
+
+  for (int i = 0; i < result_size; ++i) {
+    std::cout << "EXPECTED " << full_prec(i) << " GOT " << half_prec(i) << std::endl;
+    VERIFY_IS_APPROX(full_prec(i), half_prec(i));
+  }
+
+  gpu_device.deallocate(d_float1);
+  gpu_device.deallocate(d_float2);
+  gpu_device.deallocate(d_res_half);
+  gpu_device.deallocate(d_res_float);
+}
+
+template<typename>
+void test_cuda_reductions() {
+  test_cuda_reductions<void>(13, 13, 0);
+  test_cuda_reductions<void>(13, 13, 1);
+
+  test_cuda_reductions<void>(35, 36, 0);
+  test_cuda_reductions<void>(35, 36, 1);
+
+  test_cuda_reductions<void>(36, 35, 0);
+  test_cuda_reductions<void>(36, 35, 1);
+}
+
+template<typename>
+void test_cuda_full_reductions() {
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int size = 13;
+  int num_elem = size*size;
+
+  float* d_float1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_float2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  Eigen::half* d_res_half = (Eigen::half*)gpu_device.allocate(1 * sizeof(Eigen::half));
+  Eigen::half* d_res_float = (Eigen::half*)gpu_device.allocate(1 * sizeof(Eigen::half));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float1(
+      d_float1, size, size);
+  Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float2(
+      d_float2, size, size);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 0>, Eigen::Aligned> gpu_res_half(
+      d_res_half);
+  Eigen::TensorMap<Eigen::Tensor<Eigen::half, 0>, Eigen::Aligned> gpu_res_float(
+      d_res_float);
+
+  gpu_float1.device(gpu_device) = gpu_float1.random();
+  gpu_float2.device(gpu_device) = gpu_float2.random();
+
+  gpu_res_float.device(gpu_device) = gpu_float1.sum().cast<Eigen::half>();
+  gpu_res_half.device(gpu_device) = gpu_float1.cast<Eigen::half>().sum();
+
+  Tensor<Eigen::half, 0> half_prec;
+  Tensor<Eigen::half, 0> full_prec;
+  gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, sizeof(Eigen::half));
+  gpu_device.synchronize();
+
+  VERIFY_IS_APPROX(full_prec(), half_prec());
+
+  gpu_res_float.device(gpu_device) = gpu_float1.maximum().cast<Eigen::half>();
+  gpu_res_half.device(gpu_device) = gpu_float1.cast<Eigen::half>().maximum();
+  gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, sizeof(Eigen::half));
+  gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, sizeof(Eigen::half));
+  gpu_device.synchronize();
+
+  VERIFY_IS_APPROX(full_prec(), half_prec());
+
+  gpu_device.deallocate(d_float1);
+  gpu_device.deallocate(d_float2);
+  gpu_device.deallocate(d_res_half);
+  gpu_device.deallocate(d_res_float);
+}
+
+template<typename>
+void test_cuda_forced_evals() {
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+  int num_elem = 101;
+
+  float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_res_half1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_res_half2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
+  float* d_res_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
+
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float(
+      d_float, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_half1(
+      d_res_half1, num_elem);
+ Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Unaligned> gpu_res_half2(
+      d_res_half2, num_elem);
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_float(
+      d_res_float, num_elem);
+
+  Eigen::array<int, 1> no_bcast;
+  no_bcast[0] = 1;
+
+  gpu_float.device(gpu_device) = gpu_float.random() - gpu_float.constant(0.5f);
+  gpu_res_float.device(gpu_device) = gpu_float.abs();
+  gpu_res_half1.device(gpu_device) = gpu_float.cast<Eigen::half>().abs().eval().cast<float>();
+  gpu_res_half2.device(gpu_device) = gpu_float.cast<Eigen::half>().abs().broadcast(no_bcast).eval().cast<float>();
+
+  Tensor<float, 1> half_prec1(num_elem);
+  Tensor<float, 1> half_prec2(num_elem);
+  Tensor<float, 1> full_prec(num_elem);
+  gpu_device.memcpyDeviceToHost(half_prec1.data(), d_res_half1, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(half_prec2.data(), d_res_half1, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(float));
+  gpu_device.synchronize();
+
+  for (int i = 0; i < num_elem; ++i) {
+    std::cout << "Checking forced eval " << i << full_prec(i) << " vs " << half_prec1(i) << " vs " << half_prec2(i) << std::endl;
+    VERIFY_IS_APPROX(full_prec(i), half_prec1(i));
+    VERIFY_IS_APPROX(full_prec(i), half_prec2(i));
+  }
+
+  gpu_device.deallocate(d_float);
+  gpu_device.deallocate(d_res_half1);
+  gpu_device.deallocate(d_res_half2);
+  gpu_device.deallocate(d_res_float);
+}
+#endif
+
+
+void test_cxx11_tensor_of_float16_cuda()
+{
+  CALL_SUBTEST_1(test_cuda_numext<void>());
+
+#ifdef EIGEN_HAS_CUDA_FP16
+  CALL_SUBTEST_1(test_cuda_conversion<void>());
+  CALL_SUBTEST_1(test_cuda_unary<void>());
+  CALL_SUBTEST_1(test_cuda_elementwise<void>());
+  CALL_SUBTEST_1(test_cuda_trancendental<void>());
+  CALL_SUBTEST_2(test_cuda_contractions<void>());
+  CALL_SUBTEST_3(test_cuda_reductions<void>());
+  CALL_SUBTEST_4(test_cuda_full_reductions<void>());
+  CALL_SUBTEST_5(test_cuda_forced_evals<void>());
+#else
+  std::cout << "Half floats are not supported by this version of cuda: skipping the test" << std::endl;
+#endif
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_of_strings.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_of_strings.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_of_strings.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_of_strings.cpp
@@ -0,0 +1,152 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::TensorMap;
+
+static void test_assign()
+{
+  std::string data1[6];
+  TensorMap<Tensor<std::string, 2>> mat1(data1, 2, 3);
+  std::string data2[6];
+  const TensorMap<Tensor<const std::string, 2>> mat2(data2, 2, 3);
+
+  for (int i = 0; i < 6; ++i) {
+    std::ostringstream s1;
+    s1 << "abc" << i*3;
+    data1[i] = s1.str();
+    std::ostringstream s2;
+    s2 << "def" << i*5;
+    data2[i] = s2.str();
+  }
+
+  Tensor<std::string, 2> rslt1;
+  rslt1 = mat1;
+  Tensor<std::string, 2> rslt2;
+  rslt2 = mat2;
+
+  Tensor<std::string, 2> rslt3 = mat1;
+  Tensor<std::string, 2> rslt4 = mat2;
+
+  Tensor<std::string, 2> rslt5(mat1);
+  Tensor<std::string, 2> rslt6(mat2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_EQUAL(rslt1(i,j), data1[i+2*j]);
+      VERIFY_IS_EQUAL(rslt2(i,j), data2[i+2*j]);
+      VERIFY_IS_EQUAL(rslt3(i,j), data1[i+2*j]);
+      VERIFY_IS_EQUAL(rslt4(i,j), data2[i+2*j]);
+      VERIFY_IS_EQUAL(rslt5(i,j), data1[i+2*j]);
+      VERIFY_IS_EQUAL(rslt6(i,j), data2[i+2*j]);
+    }
+  }
+}
+
+
+static void test_concat()
+{
+  Tensor<std::string, 2> t1(2, 3);
+  Tensor<std::string, 2> t2(2, 3);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      std::ostringstream s1;
+      s1 << "abc" << i + j*2;
+      t1(i, j) = s1.str();
+      std::ostringstream s2;
+      s2 << "def" << i*5 + j*32;
+      t2(i, j) = s2.str();
+    }
+  }
+
+  Tensor<std::string, 2> result = t1.concatenate(t2, 1);
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_EQUAL(result.dimension(1), 6);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_EQUAL(result(i, j),   t1(i, j));
+      VERIFY_IS_EQUAL(result(i, j+3), t2(i, j));
+    }
+  }
+}
+
+
+static void test_slices()
+{
+  Tensor<std::string, 2> data(2, 6);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      std::ostringstream s1;
+      s1 << "abc" << i + j*2;
+      data(i, j) = s1.str();
+    }
+  }
+
+  const Eigen::DSizes<ptrdiff_t, 2> half_size(2, 3);
+  const Eigen::DSizes<ptrdiff_t, 2> first_half(0, 0);
+  const Eigen::DSizes<ptrdiff_t, 2> second_half(0, 3);
+
+  Tensor<std::string, 2> t1 = data.slice(first_half, half_size);
+  Tensor<std::string, 2> t2 = data.slice(second_half, half_size);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      VERIFY_IS_EQUAL(data(i, j),   t1(i, j));
+      VERIFY_IS_EQUAL(data(i, j+3), t2(i, j));
+    }
+  }
+}
+
+
+static void test_additions()
+{
+  Tensor<std::string, 1> data1(3);
+  Tensor<std::string, 1> data2(3);
+  for (int i = 0; i < 3; ++i) {
+    data1(i) = "abc";
+    std::ostringstream s1;
+    s1 << i;
+    data2(i) = s1.str();
+  }
+
+  Tensor<std::string, 1> sum = data1 + data2;
+  for (int i = 0; i < 3; ++i) {
+    std::ostringstream concat;
+    concat << "abc" << i;
+    std::string expected = concat.str();
+    VERIFY_IS_EQUAL(sum(i), expected);
+  }
+}
+
+
+static void test_initialization()
+{
+  Tensor<std::string, 2> a(2, 3);
+  a.setConstant(std::string("foo"));
+  for (int i = 0; i < 2*3; ++i) {
+    VERIFY_IS_EQUAL(a(i), std::string("foo"));
+  }
+}
+
+
+void test_cxx11_tensor_of_strings()
+{
+  // Beware: none of this is likely to ever work on a GPU.
+  CALL_SUBTEST(test_assign());
+  CALL_SUBTEST(test_concat());
+  CALL_SUBTEST(test_slices());
+  CALL_SUBTEST(test_additions());
+  CALL_SUBTEST(test_initialization());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_padding.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_padding.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_padding.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_padding.cpp
@@ -0,0 +1,93 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<int DataLayout>
+static void test_simple_padding()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  array<std::pair<ptrdiff_t, ptrdiff_t>, 4> paddings;
+  paddings[0] = std::make_pair(0, 0);
+  paddings[1] = std::make_pair(2, 1);
+  paddings[2] = std::make_pair(3, 4);
+  paddings[3] = std::make_pair(0, 0);
+
+  Tensor<float, 4, DataLayout> padded;
+  padded = tensor.pad(paddings);
+
+  VERIFY_IS_EQUAL(padded.dimension(0), 2+0);
+  VERIFY_IS_EQUAL(padded.dimension(1), 3+3);
+  VERIFY_IS_EQUAL(padded.dimension(2), 5+7);
+  VERIFY_IS_EQUAL(padded.dimension(3), 7+0);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 6; ++j) {
+      for (int k = 0; k < 12; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          if (j >= 2 && j < 5 && k >= 3 && k < 8) {
+            VERIFY_IS_EQUAL(padded(i,j,k,l), tensor(i,j-2,k-3,l));
+          } else {
+            VERIFY_IS_EQUAL(padded(i,j,k,l), 0.0f);
+          }
+        }
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+static void test_padded_expr()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  array<std::pair<ptrdiff_t, ptrdiff_t>, 4> paddings;
+  paddings[0] = std::make_pair(0, 0);
+  paddings[1] = std::make_pair(2, 1);
+  paddings[2] = std::make_pair(3, 4);
+  paddings[3] = std::make_pair(0, 0);
+
+  Eigen::DSizes<ptrdiff_t, 2> reshape_dims;
+  reshape_dims[0] = 12;
+  reshape_dims[1] = 84;
+
+  Tensor<float, 2, DataLayout> result;
+  result = tensor.pad(paddings).reshape(reshape_dims);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 6; ++j) {
+      for (int k = 0; k < 12; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          const float result_value = DataLayout == ColMajor ?
+              result(i+2*j,k+12*l) : result(j+6*i,l+7*k);
+          if (j >= 2 && j < 5 && k >= 3 && k < 8) {
+            VERIFY_IS_EQUAL(result_value, tensor(i,j-2,k-3,l));
+          } else {
+            VERIFY_IS_EQUAL(result_value, 0.0f);
+          }
+        }
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_padding()
+{
+  CALL_SUBTEST(test_simple_padding<ColMajor>());
+  CALL_SUBTEST(test_simple_padding<RowMajor>());
+  CALL_SUBTEST(test_padded_expr<ColMajor>());
+  CALL_SUBTEST(test_padded_expr<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_patch.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_patch.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_patch.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_patch.cpp
@@ -0,0 +1,172 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<int DataLayout>
+static void test_simple_patch()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  array<ptrdiff_t, 4> patch_dims;
+
+  patch_dims[0] = 1;
+  patch_dims[1] = 1;
+  patch_dims[2] = 1;
+  patch_dims[3] = 1;
+
+  Tensor<float, 5, DataLayout> no_patch;
+  no_patch = tensor.extract_patches(patch_dims);
+
+  if (DataLayout == ColMajor) {
+    VERIFY_IS_EQUAL(no_patch.dimension(0), 1);
+    VERIFY_IS_EQUAL(no_patch.dimension(1), 1);
+    VERIFY_IS_EQUAL(no_patch.dimension(2), 1);
+    VERIFY_IS_EQUAL(no_patch.dimension(3), 1);
+    VERIFY_IS_EQUAL(no_patch.dimension(4), tensor.size());
+  } else {
+    VERIFY_IS_EQUAL(no_patch.dimension(0), tensor.size());
+    VERIFY_IS_EQUAL(no_patch.dimension(1), 1);
+    VERIFY_IS_EQUAL(no_patch.dimension(2), 1);
+    VERIFY_IS_EQUAL(no_patch.dimension(3), 1);
+    VERIFY_IS_EQUAL(no_patch.dimension(4), 1);
+  }
+
+  for (int i = 0; i < tensor.size(); ++i) {
+    VERIFY_IS_EQUAL(tensor.data()[i], no_patch.data()[i]);
+  }
+
+  patch_dims[0] = 2;
+  patch_dims[1] = 3;
+  patch_dims[2] = 5;
+  patch_dims[3] = 7;
+  Tensor<float, 5, DataLayout> single_patch;
+  single_patch = tensor.extract_patches(patch_dims);
+
+  if (DataLayout == ColMajor) {
+    VERIFY_IS_EQUAL(single_patch.dimension(0), 2);
+    VERIFY_IS_EQUAL(single_patch.dimension(1), 3);
+    VERIFY_IS_EQUAL(single_patch.dimension(2), 5);
+    VERIFY_IS_EQUAL(single_patch.dimension(3), 7);
+    VERIFY_IS_EQUAL(single_patch.dimension(4), 1);
+  } else {
+    VERIFY_IS_EQUAL(single_patch.dimension(0), 1);
+    VERIFY_IS_EQUAL(single_patch.dimension(1), 2);
+    VERIFY_IS_EQUAL(single_patch.dimension(2), 3);
+    VERIFY_IS_EQUAL(single_patch.dimension(3), 5);
+    VERIFY_IS_EQUAL(single_patch.dimension(4), 7);
+  }
+
+  for (int i = 0; i < tensor.size(); ++i) {
+    VERIFY_IS_EQUAL(tensor.data()[i], single_patch.data()[i]);
+  }
+
+  patch_dims[0] = 1;
+  patch_dims[1] = 2;
+  patch_dims[2] = 2;
+  patch_dims[3] = 1;
+  Tensor<float, 5, DataLayout> twod_patch;
+  twod_patch = tensor.extract_patches(patch_dims);
+
+  if (DataLayout == ColMajor) {
+    VERIFY_IS_EQUAL(twod_patch.dimension(0), 1);
+    VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
+    VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
+    VERIFY_IS_EQUAL(twod_patch.dimension(3), 1);
+    VERIFY_IS_EQUAL(twod_patch.dimension(4), 2*2*4*7);
+  } else {
+    VERIFY_IS_EQUAL(twod_patch.dimension(0), 2*2*4*7);
+    VERIFY_IS_EQUAL(twod_patch.dimension(1), 1);
+    VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
+    VERIFY_IS_EQUAL(twod_patch.dimension(3), 2);
+    VERIFY_IS_EQUAL(twod_patch.dimension(4), 1);
+  }
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 2; ++j) {
+      for (int k = 0; k < 4; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          int patch_loc;
+          if (DataLayout == ColMajor) {
+            patch_loc = i + 2 * (j + 2 * (k + 4 * l));
+          } else {
+            patch_loc = l + 7 * (k + 4 * (j + 2 * i));
+          }
+          for (int x = 0; x < 2; ++x) {
+            for (int y = 0; y < 2; ++y) {
+              if (DataLayout == ColMajor) {
+                VERIFY_IS_EQUAL(tensor(i,j+x,k+y,l), twod_patch(0,x,y,0,patch_loc));
+              } else {
+                VERIFY_IS_EQUAL(tensor(i,j+x,k+y,l), twod_patch(patch_loc,0,x,y,0));
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+
+  patch_dims[0] = 1;
+  patch_dims[1] = 2;
+  patch_dims[2] = 3;
+  patch_dims[3] = 5;
+  Tensor<float, 5, DataLayout> threed_patch;
+  threed_patch = tensor.extract_patches(patch_dims);
+
+  if (DataLayout == ColMajor) {
+    VERIFY_IS_EQUAL(threed_patch.dimension(0), 1);
+    VERIFY_IS_EQUAL(threed_patch.dimension(1), 2);
+    VERIFY_IS_EQUAL(threed_patch.dimension(2), 3);
+    VERIFY_IS_EQUAL(threed_patch.dimension(3), 5);
+    VERIFY_IS_EQUAL(threed_patch.dimension(4), 2*2*3*3);
+  } else {
+    VERIFY_IS_EQUAL(threed_patch.dimension(0), 2*2*3*3);
+    VERIFY_IS_EQUAL(threed_patch.dimension(1), 1);
+    VERIFY_IS_EQUAL(threed_patch.dimension(2), 2);
+    VERIFY_IS_EQUAL(threed_patch.dimension(3), 3);
+    VERIFY_IS_EQUAL(threed_patch.dimension(4), 5);
+  }
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 2; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 3; ++l) {
+          int patch_loc;
+          if (DataLayout == ColMajor) {
+            patch_loc = i + 2 * (j + 2 * (k + 3 * l));
+          } else {
+            patch_loc = l + 3 * (k + 3 * (j + 2 * i));
+          }
+          for (int x = 0; x < 2; ++x) {
+            for (int y = 0; y < 3; ++y) {
+              for (int z = 0; z < 5; ++z) {
+                if (DataLayout == ColMajor) {
+                  VERIFY_IS_EQUAL(tensor(i,j+x,k+y,l+z), threed_patch(0,x,y,z,patch_loc));
+                } else {
+                  VERIFY_IS_EQUAL(tensor(i,j+x,k+y,l+z), threed_patch(patch_loc,0,x,y,z));
+                }
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_patch()
+{
+   CALL_SUBTEST(test_simple_patch<ColMajor>());
+   CALL_SUBTEST(test_simple_patch<RowMajor>());
+   //   CALL_SUBTEST(test_expr_shuffling());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_random.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_random.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_random.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_random.cpp
@@ -0,0 +1,78 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+static void test_default()
+{
+  Tensor<float, 1> vec(6);
+  vec.setRandom();
+
+  // Fixme: we should check that the generated numbers follow a uniform
+  // distribution instead.
+  for (int i = 1; i < 6; ++i) {
+    VERIFY_IS_NOT_EQUAL(vec(i), vec(i-1));
+  }
+}
+
+static void test_normal()
+{
+  Tensor<float, 1> vec(6);
+  vec.setRandom<Eigen::internal::NormalRandomGenerator<float>>();
+
+  // Fixme: we should check that the generated numbers follow a gaussian
+  // distribution instead.
+  for (int i = 1; i < 6; ++i) {
+    VERIFY_IS_NOT_EQUAL(vec(i), vec(i-1));
+  }
+}
+
+
+struct MyGenerator {
+  MyGenerator() { }
+  MyGenerator(const MyGenerator&) { }
+
+  // Return a random value to be used.  "element_location" is the
+  // location of the entry to set in the tensor, it can typically
+  // be ignored.
+  int operator()(Eigen::DenseIndex element_location, Eigen::DenseIndex /*unused*/ = 0) const {
+    return static_cast<int>(3 * element_location);
+  }
+
+  // Same as above but generates several numbers at a time.
+  internal::packet_traits<int>::type packetOp(
+      Eigen::DenseIndex packet_location, Eigen::DenseIndex /*unused*/ = 0) const {
+    const int packetSize = internal::packet_traits<int>::size;
+    EIGEN_ALIGN_MAX int values[packetSize];
+    for (int i = 0; i < packetSize; ++i) {
+      values[i] = static_cast<int>(3 * (packet_location + i));
+    }
+    return internal::pload<typename internal::packet_traits<int>::type>(values);
+  }
+};
+
+
+static void test_custom()
+{
+  Tensor<int, 1> vec(6);
+  vec.setRandom<MyGenerator>();
+
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_EQUAL(vec(i), 3*i);
+  }
+}
+
+void test_cxx11_tensor_random()
+{
+  CALL_SUBTEST(test_default());
+  CALL_SUBTEST(test_normal());
+  CALL_SUBTEST(test_custom());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_random_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_random_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_random_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_random_cuda.cu
@@ -0,0 +1,88 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_random_cuda
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <Eigen/CXX11/Tensor>
+
+
+void test_cuda_random_uniform()
+{
+  Tensor<float, 2> out(72,97);
+  out.setZero();
+
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_out;
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 2> > gpu_out(d_out, 72,97);
+
+  gpu_out.device(gpu_device) = gpu_out.random();
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+
+  // For now we just check thes code doesn't crash.
+  // TODO: come up with a valid test of randomness
+}
+
+
+void test_cuda_random_normal()
+{
+  Tensor<float, 2> out(72,97);
+  out.setZero();
+
+  std::size_t out_bytes = out.size() * sizeof(float);
+
+  float* d_out;
+  cudaMalloc((void**)(&d_out), out_bytes);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 2> > gpu_out(d_out, 72,97);
+
+  Eigen::internal::NormalRandomGenerator<float> gen(true);
+  gpu_out.device(gpu_device) = gpu_out.random(gen);
+
+  assert(cudaMemcpyAsync(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
+  assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
+}
+
+static void test_complex()
+{
+  Tensor<std::complex<float>, 1> vec(6);
+  vec.setRandom();
+
+  // Fixme: we should check that the generated numbers follow a uniform
+  // distribution instead.
+  for (int i = 1; i < 6; ++i) {
+    VERIFY_IS_NOT_EQUAL(vec(i), vec(i-1));
+  }
+}
+
+
+void test_cxx11_tensor_random_cuda()
+{
+  CALL_SUBTEST(test_cuda_random_uniform());
+  CALL_SUBTEST(test_cuda_random_normal());
+  CALL_SUBTEST(test_complex());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_reduction.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction.cpp
@@ -0,0 +1,508 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <limits>
+#include <numeric>
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template <int DataLayout>
+static void test_trivial_reductions() {
+  {
+    Tensor<float, 0, DataLayout> tensor;
+    tensor.setRandom();
+    array<ptrdiff_t, 0> reduction_axis;
+
+    Tensor<float, 0, DataLayout> result = tensor.sum(reduction_axis);
+    VERIFY_IS_EQUAL(result(), tensor());
+  }
+
+  {
+    Tensor<float, 1, DataLayout> tensor(7);
+    tensor.setRandom();
+    array<ptrdiff_t, 0> reduction_axis;
+
+    Tensor<float, 1, DataLayout> result = tensor.sum(reduction_axis);
+    VERIFY_IS_EQUAL(result.dimension(0), 7);
+    for (int i = 0; i < 7; ++i) {
+      VERIFY_IS_EQUAL(result(i), tensor(i));
+    }
+  }
+
+  {
+    Tensor<float, 2, DataLayout> tensor(2, 3);
+    tensor.setRandom();
+    array<ptrdiff_t, 0> reduction_axis;
+
+    Tensor<float, 2, DataLayout> result = tensor.sum(reduction_axis);
+    VERIFY_IS_EQUAL(result.dimension(0), 2);
+    VERIFY_IS_EQUAL(result.dimension(1), 3);
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 3; ++j) {
+        VERIFY_IS_EQUAL(result(i, j), tensor(i, j));
+      }
+    }
+  }
+}
+
+template <int DataLayout>
+static void test_simple_reductions() {
+  Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
+  tensor.setRandom();
+  array<ptrdiff_t, 2> reduction_axis2;
+  reduction_axis2[0] = 1;
+  reduction_axis2[1] = 3;
+
+  Tensor<float, 2, DataLayout> result = tensor.sum(reduction_axis2);
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_EQUAL(result.dimension(1), 5);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      float sum = 0.0f;
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          sum += tensor(i, k, j, l);
+        }
+      }
+      VERIFY_IS_APPROX(result(i, j), sum);
+    }
+  }
+
+  {
+    Tensor<float, 0, DataLayout> sum1 = tensor.sum();
+    VERIFY_IS_EQUAL(sum1.rank(), 0);
+
+    array<ptrdiff_t, 4> reduction_axis4;
+    reduction_axis4[0] = 0;
+    reduction_axis4[1] = 1;
+    reduction_axis4[2] = 2;
+    reduction_axis4[3] = 3;
+    Tensor<float, 0, DataLayout> sum2 = tensor.sum(reduction_axis4);
+    VERIFY_IS_EQUAL(sum2.rank(), 0);
+
+    VERIFY_IS_APPROX(sum1(), sum2());
+  }
+
+  reduction_axis2[0] = 0;
+  reduction_axis2[1] = 2;
+  result = tensor.prod(reduction_axis2);
+  VERIFY_IS_EQUAL(result.dimension(0), 3);
+  VERIFY_IS_EQUAL(result.dimension(1), 7);
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 7; ++j) {
+      float prod = 1.0f;
+      for (int k = 0; k < 2; ++k) {
+        for (int l = 0; l < 5; ++l) {
+          prod *= tensor(k, i, l, j);
+        }
+      }
+      VERIFY_IS_APPROX(result(i, j), prod);
+    }
+  }
+
+  {
+    Tensor<float, 0, DataLayout> prod1 = tensor.prod();
+    VERIFY_IS_EQUAL(prod1.rank(), 0);
+
+    array<ptrdiff_t, 4> reduction_axis4;
+    reduction_axis4[0] = 0;
+    reduction_axis4[1] = 1;
+    reduction_axis4[2] = 2;
+    reduction_axis4[3] = 3;
+    Tensor<float, 0, DataLayout> prod2 = tensor.prod(reduction_axis4);
+    VERIFY_IS_EQUAL(prod2.rank(), 0);
+
+    VERIFY_IS_APPROX(prod1(), prod2());
+  }
+
+  reduction_axis2[0] = 0;
+  reduction_axis2[1] = 2;
+  result = tensor.maximum(reduction_axis2);
+  VERIFY_IS_EQUAL(result.dimension(0), 3);
+  VERIFY_IS_EQUAL(result.dimension(1), 7);
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 7; ++j) {
+      float max_val = std::numeric_limits<float>::lowest();
+      for (int k = 0; k < 2; ++k) {
+        for (int l = 0; l < 5; ++l) {
+          max_val = (std::max)(max_val, tensor(k, i, l, j));
+        }
+      }
+      VERIFY_IS_APPROX(result(i, j), max_val);
+    }
+  }
+
+  {
+    Tensor<float, 0, DataLayout> max1 = tensor.maximum();
+    VERIFY_IS_EQUAL(max1.rank(), 0);
+
+    array<ptrdiff_t, 4> reduction_axis4;
+    reduction_axis4[0] = 0;
+    reduction_axis4[1] = 1;
+    reduction_axis4[2] = 2;
+    reduction_axis4[3] = 3;
+    Tensor<float, 0, DataLayout> max2 = tensor.maximum(reduction_axis4);
+    VERIFY_IS_EQUAL(max2.rank(), 0);
+
+    VERIFY_IS_APPROX(max1(), max2());
+  }
+
+  reduction_axis2[0] = 0;
+  reduction_axis2[1] = 1;
+  result = tensor.minimum(reduction_axis2);
+  VERIFY_IS_EQUAL(result.dimension(0), 5);
+  VERIFY_IS_EQUAL(result.dimension(1), 7);
+  for (int i = 0; i < 5; ++i) {
+    for (int j = 0; j < 7; ++j) {
+      float min_val = (std::numeric_limits<float>::max)();
+      for (int k = 0; k < 2; ++k) {
+        for (int l = 0; l < 3; ++l) {
+          min_val = (std::min)(min_val, tensor(k, l, i, j));
+        }
+      }
+      VERIFY_IS_APPROX(result(i, j), min_val);
+    }
+  }
+
+  {
+    Tensor<float, 0, DataLayout> min1 = tensor.minimum();
+    VERIFY_IS_EQUAL(min1.rank(), 0);
+
+    array<ptrdiff_t, 4> reduction_axis4;
+    reduction_axis4[0] = 0;
+    reduction_axis4[1] = 1;
+    reduction_axis4[2] = 2;
+    reduction_axis4[3] = 3;
+    Tensor<float, 0, DataLayout> min2 = tensor.minimum(reduction_axis4);
+    VERIFY_IS_EQUAL(min2.rank(), 0);
+
+    VERIFY_IS_APPROX(min1(), min2());
+  }
+
+  reduction_axis2[0] = 0;
+  reduction_axis2[1] = 1;
+  result = tensor.mean(reduction_axis2);
+  VERIFY_IS_EQUAL(result.dimension(0), 5);
+  VERIFY_IS_EQUAL(result.dimension(1), 7);
+  for (int i = 0; i < 5; ++i) {
+    for (int j = 0; j < 7; ++j) {
+      float sum = 0.0f;
+      int count = 0;
+      for (int k = 0; k < 2; ++k) {
+        for (int l = 0; l < 3; ++l) {
+          sum += tensor(k, l, i, j);
+          ++count;
+        }
+      }
+      VERIFY_IS_APPROX(result(i, j), sum / count);
+    }
+  }
+
+  {
+    Tensor<float, 0, DataLayout> mean1 = tensor.mean();
+    VERIFY_IS_EQUAL(mean1.rank(), 0);
+
+    array<ptrdiff_t, 4> reduction_axis4;
+    reduction_axis4[0] = 0;
+    reduction_axis4[1] = 1;
+    reduction_axis4[2] = 2;
+    reduction_axis4[3] = 3;
+    Tensor<float, 0, DataLayout> mean2 = tensor.mean(reduction_axis4);
+    VERIFY_IS_EQUAL(mean2.rank(), 0);
+
+    VERIFY_IS_APPROX(mean1(), mean2());
+  }
+
+  {
+    Tensor<int, 1> ints(10);
+    std::iota(ints.data(), ints.data() + ints.dimension(0), 0);
+
+    TensorFixedSize<bool, Sizes<> > all;
+    all = ints.all();
+    VERIFY(!all());
+    all = (ints >= ints.constant(0)).all();
+    VERIFY(all());
+
+    TensorFixedSize<bool, Sizes<> > any;
+    any = (ints > ints.constant(10)).any();
+    VERIFY(!any());
+    any = (ints < ints.constant(1)).any();
+    VERIFY(any());
+  }
+}
+
+
+template <int DataLayout>
+static void test_reductions_in_expr() {
+  Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
+  tensor.setRandom();
+  array<ptrdiff_t, 2> reduction_axis2;
+  reduction_axis2[0] = 1;
+  reduction_axis2[1] = 3;
+
+  Tensor<float, 2, DataLayout> result(2, 5);
+  result = result.constant(1.0f) - tensor.sum(reduction_axis2);
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_EQUAL(result.dimension(1), 5);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      float sum = 0.0f;
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          sum += tensor(i, k, j, l);
+        }
+      }
+      VERIFY_IS_APPROX(result(i, j), 1.0f - sum);
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_full_reductions() {
+  Tensor<float, 2, DataLayout> tensor(2, 3);
+  tensor.setRandom();
+  array<ptrdiff_t, 2> reduction_axis;
+  reduction_axis[0] = 0;
+  reduction_axis[1] = 1;
+
+  Tensor<float, 0, DataLayout> result = tensor.sum(reduction_axis);
+  VERIFY_IS_EQUAL(result.rank(), 0);
+
+  float sum = 0.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      sum += tensor(i, j);
+    }
+  }
+  VERIFY_IS_APPROX(result(0), sum);
+
+  result = tensor.square().sum(reduction_axis).sqrt();
+  VERIFY_IS_EQUAL(result.rank(), 0);
+
+  sum = 0.0f;
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      sum += tensor(i, j) * tensor(i, j);
+    }
+  }
+  VERIFY_IS_APPROX(result(), sqrtf(sum));
+}
+
+struct UserReducer {
+  static const bool PacketAccess = false;
+  UserReducer(float offset) : offset_(offset) {}
+  void reduce(const float val, float* accum) { *accum += val * val; }
+  float initialize() const { return 0; }
+  float finalize(const float accum) const { return 1.0f / (accum + offset_); }
+
+ private:
+  const float offset_;
+};
+
+template <int DataLayout>
+static void test_user_defined_reductions() {
+  Tensor<float, 2, DataLayout> tensor(5, 7);
+  tensor.setRandom();
+  array<ptrdiff_t, 1> reduction_axis;
+  reduction_axis[0] = 1;
+
+  UserReducer reducer(10.0f);
+  Tensor<float, 1, DataLayout> result = tensor.reduce(reduction_axis, reducer);
+  VERIFY_IS_EQUAL(result.dimension(0), 5);
+  for (int i = 0; i < 5; ++i) {
+    float expected = 10.0f;
+    for (int j = 0; j < 7; ++j) {
+      expected += tensor(i, j) * tensor(i, j);
+    }
+    expected = 1.0f / expected;
+    VERIFY_IS_APPROX(result(i), expected);
+  }
+}
+
+template <int DataLayout>
+static void test_tensor_maps() {
+  int inputs[2 * 3 * 5 * 7];
+  TensorMap<Tensor<int, 4, DataLayout> > tensor_map(inputs, 2, 3, 5, 7);
+  TensorMap<Tensor<const int, 4, DataLayout> > tensor_map_const(inputs, 2, 3, 5,
+                                                                7);
+  const TensorMap<Tensor<const int, 4, DataLayout> > tensor_map_const_const(
+      inputs, 2, 3, 5, 7);
+
+  tensor_map.setRandom();
+  array<ptrdiff_t, 2> reduction_axis;
+  reduction_axis[0] = 1;
+  reduction_axis[1] = 3;
+
+  Tensor<int, 2, DataLayout> result = tensor_map.sum(reduction_axis);
+  Tensor<int, 2, DataLayout> result2 = tensor_map_const.sum(reduction_axis);
+  Tensor<int, 2, DataLayout> result3 =
+      tensor_map_const_const.sum(reduction_axis);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      int sum = 0;
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          sum += tensor_map(i, k, j, l);
+        }
+      }
+      VERIFY_IS_EQUAL(result(i, j), sum);
+      VERIFY_IS_EQUAL(result2(i, j), sum);
+      VERIFY_IS_EQUAL(result3(i, j), sum);
+    }
+  }
+}
+
+template <int DataLayout>
+static void test_static_dims() {
+  Tensor<float, 4, DataLayout> in(72, 53, 97, 113);
+  Tensor<float, 2, DataLayout> out(72, 97);
+  in.setRandom();
+
+#if !EIGEN_HAS_CONSTEXPR 
+  array<int, 2> reduction_axis;
+  reduction_axis[0] = 1;
+  reduction_axis[1] = 3;
+#else
+  Eigen::IndexList<Eigen::type2index<1>, Eigen::type2index<3> > reduction_axis;
+#endif
+
+  out = in.maximum(reduction_axis);
+
+  for (int i = 0; i < 72; ++i) {
+    for (int j = 0; j < 97; ++j) {
+      float expected = -1e10f;
+      for (int k = 0; k < 53; ++k) {
+        for (int l = 0; l < 113; ++l) {
+          expected = (std::max)(expected, in(i, k, j, l));
+        }
+      }
+      VERIFY_IS_APPROX(out(i, j), expected);
+    }
+  }
+}
+
+template <int DataLayout>
+static void test_innermost_last_dims() {
+  Tensor<float, 4, DataLayout> in(72, 53, 97, 113);
+  Tensor<float, 2, DataLayout> out(97, 113);
+  in.setRandom();
+
+// Reduce on the innermost dimensions.
+#if !EIGEN_HAS_CONSTEXPR
+  array<int, 2> reduction_axis;
+  reduction_axis[0] = 0;
+  reduction_axis[1] = 1;
+#else
+  // This triggers the use of packets for ColMajor.
+  Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1> > reduction_axis;
+#endif
+
+  out = in.maximum(reduction_axis);
+
+  for (int i = 0; i < 97; ++i) {
+    for (int j = 0; j < 113; ++j) {
+      float expected = -1e10f;
+      for (int k = 0; k < 53; ++k) {
+        for (int l = 0; l < 72; ++l) {
+          expected = (std::max)(expected, in(l, k, i, j));
+        }
+      }
+      VERIFY_IS_APPROX(out(i, j), expected);
+    }
+  }
+}
+
+template <int DataLayout>
+static void test_innermost_first_dims() {
+  Tensor<float, 4, DataLayout> in(72, 53, 97, 113);
+  Tensor<float, 2, DataLayout> out(72, 53);
+  in.setRandom();
+
+// Reduce on the innermost dimensions.
+#if !EIGEN_HAS_CONSTEXPR
+  array<int, 2> reduction_axis;
+  reduction_axis[0] = 2;
+  reduction_axis[1] = 3;
+#else
+  // This triggers the use of packets for RowMajor.
+  Eigen::IndexList<Eigen::type2index<2>, Eigen::type2index<3>> reduction_axis;
+#endif
+
+  out = in.maximum(reduction_axis);
+
+  for (int i = 0; i < 72; ++i) {
+    for (int j = 0; j < 53; ++j) {
+      float expected = -1e10f;
+      for (int k = 0; k < 97; ++k) {
+        for (int l = 0; l < 113; ++l) {
+          expected = (std::max)(expected, in(i, j, k, l));
+        }
+      }
+      VERIFY_IS_APPROX(out(i, j), expected);
+    }
+  }
+}
+
+template <int DataLayout>
+static void test_reduce_middle_dims() {
+  Tensor<float, 4, DataLayout> in(72, 53, 97, 113);
+  Tensor<float, 2, DataLayout> out(72, 53);
+  in.setRandom();
+
+// Reduce on the innermost dimensions.
+#if !EIGEN_HAS_CONSTEXPR
+  array<int, 2> reduction_axis;
+  reduction_axis[0] = 1;
+  reduction_axis[1] = 2;
+#else
+  // This triggers the use of packets for RowMajor.
+  Eigen::IndexList<Eigen::type2index<1>, Eigen::type2index<2>> reduction_axis;
+#endif
+
+  out = in.maximum(reduction_axis);
+
+  for (int i = 0; i < 72; ++i) {
+    for (int j = 0; j < 113; ++j) {
+      float expected = -1e10f;
+      for (int k = 0; k < 53; ++k) {
+        for (int l = 0; l < 97; ++l) {
+          expected = (std::max)(expected, in(i, k, l, j));
+        }
+      }
+      VERIFY_IS_APPROX(out(i, j), expected);
+    }
+  }
+}
+
+void test_cxx11_tensor_reduction() {
+  CALL_SUBTEST(test_trivial_reductions<ColMajor>());
+  CALL_SUBTEST(test_trivial_reductions<RowMajor>());
+  CALL_SUBTEST(test_simple_reductions<ColMajor>());
+  CALL_SUBTEST(test_simple_reductions<RowMajor>());
+  CALL_SUBTEST(test_reductions_in_expr<ColMajor>());
+  CALL_SUBTEST(test_reductions_in_expr<RowMajor>());
+  CALL_SUBTEST(test_full_reductions<ColMajor>());
+  CALL_SUBTEST(test_full_reductions<RowMajor>());
+  CALL_SUBTEST(test_user_defined_reductions<ColMajor>());
+  CALL_SUBTEST(test_user_defined_reductions<RowMajor>());
+  CALL_SUBTEST(test_tensor_maps<ColMajor>());
+  CALL_SUBTEST(test_tensor_maps<RowMajor>());
+  CALL_SUBTEST(test_static_dims<ColMajor>());
+  CALL_SUBTEST(test_static_dims<RowMajor>());
+  CALL_SUBTEST(test_innermost_last_dims<ColMajor>());
+  CALL_SUBTEST(test_innermost_last_dims<RowMajor>());
+  CALL_SUBTEST(test_innermost_first_dims<ColMajor>());
+  CALL_SUBTEST(test_innermost_first_dims<RowMajor>());
+  CALL_SUBTEST(test_reduce_middle_dims<ColMajor>());
+  CALL_SUBTEST(test_reduce_middle_dims<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_reduction_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction_cuda.cu
@@ -0,0 +1,157 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_reduction_cuda
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+
+template<typename Type, int DataLayout>
+static void test_full_reductions() {
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  const int num_rows = internal::random<int>(1024, 5*1024);
+  const int num_cols = internal::random<int>(1024, 5*1024);
+
+  Tensor<Type, 2, DataLayout> in(num_rows, num_cols);
+  in.setRandom();
+
+  Tensor<Type, 0, DataLayout> full_redux;
+  full_redux = in.sum();
+
+  std::size_t in_bytes = in.size() * sizeof(Type);
+  std::size_t out_bytes = full_redux.size() * sizeof(Type);
+  Type* gpu_in_ptr = static_cast<Type*>(gpu_device.allocate(in_bytes));
+  Type* gpu_out_ptr = static_cast<Type*>(gpu_device.allocate(out_bytes));
+  gpu_device.memcpyHostToDevice(gpu_in_ptr, in.data(), in_bytes);
+
+  TensorMap<Tensor<Type, 2, DataLayout> > in_gpu(gpu_in_ptr, num_rows, num_cols);
+  TensorMap<Tensor<Type, 0, DataLayout> > out_gpu(gpu_out_ptr);
+
+  out_gpu.device(gpu_device) = in_gpu.sum();
+
+  Tensor<Type, 0, DataLayout> full_redux_gpu;
+  gpu_device.memcpyDeviceToHost(full_redux_gpu.data(), gpu_out_ptr, out_bytes);
+  gpu_device.synchronize();
+
+  // Check that the CPU and GPU reductions return the same result.
+  VERIFY_IS_APPROX(full_redux(), full_redux_gpu());
+
+  gpu_device.deallocate(gpu_in_ptr);
+  gpu_device.deallocate(gpu_out_ptr);
+}
+
+template<typename Type, int DataLayout>
+static void test_first_dim_reductions() {
+  int dim_x = 33;
+  int dim_y = 1;
+  int dim_z = 128;
+
+  Tensor<Type, 3, DataLayout> in(dim_x, dim_y, dim_z);
+  in.setRandom();
+
+  Eigen::array<int, 1> red_axis;
+  red_axis[0] = 0;
+  Tensor<Type, 2, DataLayout> redux = in.sum(red_axis);
+
+  // Create device
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice dev(&stream);
+  
+  // Create data(T)
+  Type* in_data = (Type*)dev.allocate(dim_x*dim_y*dim_z*sizeof(Type));
+  Type* out_data = (Type*)dev.allocate(dim_z*dim_y*sizeof(Type));
+  Eigen::TensorMap<Eigen::Tensor<Type, 3, DataLayout> > gpu_in(in_data, dim_x, dim_y, dim_z);
+  Eigen::TensorMap<Eigen::Tensor<Type, 2, DataLayout> > gpu_out(out_data, dim_y, dim_z);
+  
+  // Perform operation
+  dev.memcpyHostToDevice(in_data, in.data(), in.size()*sizeof(Type));
+  gpu_out.device(dev) = gpu_in.sum(red_axis);
+  gpu_out.device(dev) += gpu_in.sum(red_axis);
+  Tensor<Type, 2, DataLayout> redux_gpu(dim_y, dim_z);
+  dev.memcpyDeviceToHost(redux_gpu.data(), out_data, gpu_out.size()*sizeof(Type));
+  dev.synchronize();
+
+  // Check that the CPU and GPU reductions return the same result.
+  for (int i = 0; i < gpu_out.size(); ++i) {
+    VERIFY_IS_APPROX(2*redux(i), redux_gpu(i));
+  }
+
+  dev.deallocate(in_data);
+  dev.deallocate(out_data);
+}
+
+template<typename Type, int DataLayout>
+static void test_last_dim_reductions() {
+  int dim_x = 128;
+  int dim_y = 1;
+  int dim_z = 33;
+
+  Tensor<Type, 3, DataLayout> in(dim_x, dim_y, dim_z);
+  in.setRandom();
+
+  Eigen::array<int, 1> red_axis;
+  red_axis[0] = 2;
+  Tensor<Type, 2, DataLayout> redux = in.sum(red_axis);
+
+  // Create device
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice dev(&stream);
+  
+  // Create data
+  Type* in_data = (Type*)dev.allocate(dim_x*dim_y*dim_z*sizeof(Type));
+  Type* out_data = (Type*)dev.allocate(dim_x*dim_y*sizeof(Type));
+  Eigen::TensorMap<Eigen::Tensor<Type, 3, DataLayout> > gpu_in(in_data, dim_x, dim_y, dim_z);
+  Eigen::TensorMap<Eigen::Tensor<Type, 2, DataLayout> > gpu_out(out_data, dim_x, dim_y);
+  
+  // Perform operation
+  dev.memcpyHostToDevice(in_data, in.data(), in.size()*sizeof(Type));
+  gpu_out.device(dev) = gpu_in.sum(red_axis);
+  gpu_out.device(dev) += gpu_in.sum(red_axis);
+  Tensor<Type, 2, DataLayout> redux_gpu(dim_x, dim_y);
+  dev.memcpyDeviceToHost(redux_gpu.data(), out_data, gpu_out.size()*sizeof(Type));
+  dev.synchronize();
+
+  // Check that the CPU and GPU reductions return the same result.
+  for (int i = 0; i < gpu_out.size(); ++i) {
+    VERIFY_IS_APPROX(2*redux(i), redux_gpu(i));
+  }
+
+  dev.deallocate(in_data);
+  dev.deallocate(out_data);
+}
+
+
+void test_cxx11_tensor_reduction_cuda() {
+  CALL_SUBTEST_1((test_full_reductions<float, ColMajor>()));
+  CALL_SUBTEST_1((test_full_reductions<double, ColMajor>()));
+  CALL_SUBTEST_2((test_full_reductions<float, RowMajor>()));
+  CALL_SUBTEST_2((test_full_reductions<double, RowMajor>()));
+  
+  CALL_SUBTEST_3((test_first_dim_reductions<float, ColMajor>()));
+  CALL_SUBTEST_3((test_first_dim_reductions<double, ColMajor>()));
+  CALL_SUBTEST_4((test_first_dim_reductions<float, RowMajor>()));
+// Outer reductions of doubles aren't supported just yet.  					      
+//  CALL_SUBTEST_4((test_first_dim_reductions<double, RowMajor>()))
+
+  CALL_SUBTEST_5((test_last_dim_reductions<float, ColMajor>()));
+// Outer reductions of doubles aren't supported just yet.  					      
+//  CALL_SUBTEST_5((test_last_dim_reductions<double, ColMajor>()));
+  CALL_SUBTEST_6((test_last_dim_reductions<float, RowMajor>()));
+  CALL_SUBTEST_6((test_last_dim_reductions<double, RowMajor>()));
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_reduction_sycl.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction_sycl.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction_sycl.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_reduction_sycl.cpp
@@ -0,0 +1,138 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_reduction_sycl
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_SYCL
+
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+
+
+static void test_full_reductions_sycl(const Eigen::SyclDevice&  sycl_device) {
+
+  const int num_rows = 452;
+  const int num_cols = 765;
+  array<int, 2> tensorRange = {{num_rows, num_cols}};
+
+  Tensor<float, 2> in(tensorRange);
+  Tensor<float, 0> full_redux;
+  Tensor<float, 0> full_redux_gpu;
+
+  in.setRandom();
+
+  full_redux = in.sum();
+
+  float* gpu_in_data = static_cast<float*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(float)));
+  float* gpu_out_data =(float*)sycl_device.allocate(sizeof(float));
+
+  TensorMap<Tensor<float, 2> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<float, 0> >  out_gpu(gpu_out_data);
+
+  sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(float));
+  out_gpu.device(sycl_device) = in_gpu.sum();
+  sycl_device.memcpyDeviceToHost(full_redux_gpu.data(), gpu_out_data, sizeof(float));
+  // Check that the CPU and GPU reductions return the same result.
+  VERIFY_IS_APPROX(full_redux_gpu(), full_redux());
+
+  sycl_device.deallocate(gpu_in_data);
+  sycl_device.deallocate(gpu_out_data);
+}
+
+static void test_first_dim_reductions_sycl(const Eigen::SyclDevice& sycl_device) {
+
+  int dim_x = 145;
+  int dim_y = 1;
+  int dim_z = 67;
+
+  array<int, 3> tensorRange = {{dim_x, dim_y, dim_z}};
+  Eigen::array<int, 1> red_axis;
+  red_axis[0] = 0;
+  array<int, 2> reduced_tensorRange = {{dim_y, dim_z}};
+
+  Tensor<float, 3> in(tensorRange);
+  Tensor<float, 2> redux(reduced_tensorRange);
+  Tensor<float, 2> redux_gpu(reduced_tensorRange);
+
+  in.setRandom();
+
+  redux= in.sum(red_axis);
+
+  float* gpu_in_data = static_cast<float*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(float)));
+  float* gpu_out_data = static_cast<float*>(sycl_device.allocate(redux_gpu.dimensions().TotalSize()*sizeof(float)));
+
+  TensorMap<Tensor<float, 3> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<float, 2> >  out_gpu(gpu_out_data, reduced_tensorRange);
+
+  sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(float));
+  out_gpu.device(sycl_device) = in_gpu.sum(red_axis);
+  sycl_device.memcpyDeviceToHost(redux_gpu.data(), gpu_out_data, redux_gpu.dimensions().TotalSize()*sizeof(float));
+
+  // Check that the CPU and GPU reductions return the same result.
+  for(int j=0; j<reduced_tensorRange[0]; j++ )
+    for(int k=0; k<reduced_tensorRange[1]; k++ )
+      VERIFY_IS_APPROX(redux_gpu(j,k), redux(j,k));
+
+  sycl_device.deallocate(gpu_in_data);
+  sycl_device.deallocate(gpu_out_data);
+}
+
+static void test_last_dim_reductions_sycl(const Eigen::SyclDevice &sycl_device) {
+
+  int dim_x = 567;
+  int dim_y = 1;
+  int dim_z = 47;
+
+  array<int, 3> tensorRange = {{dim_x, dim_y, dim_z}};
+  Eigen::array<int, 1> red_axis;
+  red_axis[0] = 2;
+  array<int, 2> reduced_tensorRange = {{dim_x, dim_y}};
+
+  Tensor<float, 3> in(tensorRange);
+  Tensor<float, 2> redux(reduced_tensorRange);
+  Tensor<float, 2> redux_gpu(reduced_tensorRange);
+
+  in.setRandom();
+
+  redux= in.sum(red_axis);
+
+  float* gpu_in_data = static_cast<float*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(float)));
+  float* gpu_out_data = static_cast<float*>(sycl_device.allocate(redux_gpu.dimensions().TotalSize()*sizeof(float)));
+
+  TensorMap<Tensor<float, 3> >  in_gpu(gpu_in_data, tensorRange);
+  TensorMap<Tensor<float, 2> >  out_gpu(gpu_out_data, reduced_tensorRange);
+
+  sycl_device.memcpyHostToDevice(gpu_in_data, in.data(),(in.dimensions().TotalSize())*sizeof(float));
+  out_gpu.device(sycl_device) = in_gpu.sum(red_axis);
+  sycl_device.memcpyDeviceToHost(redux_gpu.data(), gpu_out_data, redux_gpu.dimensions().TotalSize()*sizeof(float));
+  // Check that the CPU and GPU reductions return the same result.
+  for(int j=0; j<reduced_tensorRange[0]; j++ )
+    for(int k=0; k<reduced_tensorRange[1]; k++ )
+      VERIFY_IS_APPROX(redux_gpu(j,k), redux(j,k));
+
+  sycl_device.deallocate(gpu_in_data);
+  sycl_device.deallocate(gpu_out_data);
+
+}
+
+void test_cxx11_tensor_reduction_sycl() {
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST((test_full_reductions_sycl(sycl_device)));
+  CALL_SUBTEST((test_first_dim_reductions_sycl(sycl_device)));
+  CALL_SUBTEST((test_last_dim_reductions_sycl(sycl_device)));
+
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_ref.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_ref.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_ref.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_ref.cpp
@@ -0,0 +1,248 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_simple_lvalue_ref()
+{
+  Tensor<int, 1> input(6);
+  input.setRandom();
+
+  TensorRef<Tensor<int, 1>> ref3(input);
+  TensorRef<Tensor<int, 1>> ref4 = input;
+
+  VERIFY_IS_EQUAL(ref3.data(), input.data());
+  VERIFY_IS_EQUAL(ref4.data(), input.data());
+
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_EQUAL(ref3(i), input(i));
+    VERIFY_IS_EQUAL(ref4(i), input(i));
+  }
+
+  for (int i = 0; i < 6; ++i) {
+    ref3.coeffRef(i) = i;
+  }
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_EQUAL(input(i), i);
+  }
+  for (int i = 0; i < 6; ++i) {
+    ref4.coeffRef(i) = -i * 2;
+  }
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_EQUAL(input(i), -i*2);
+  }
+}
+
+
+static void test_simple_rvalue_ref()
+{
+  Tensor<int, 1> input1(6);
+  input1.setRandom();
+  Tensor<int, 1> input2(6);
+  input2.setRandom();
+
+  TensorRef<Tensor<int, 1>> ref3(input1 + input2);
+  TensorRef<Tensor<int, 1>> ref4 = input1 + input2;
+
+  VERIFY_IS_NOT_EQUAL(ref3.data(), input1.data());
+  VERIFY_IS_NOT_EQUAL(ref4.data(), input1.data());
+  VERIFY_IS_NOT_EQUAL(ref3.data(), input2.data());
+  VERIFY_IS_NOT_EQUAL(ref4.data(), input2.data());
+
+  for (int i = 0; i < 6; ++i) {
+    VERIFY_IS_EQUAL(ref3(i), input1(i) + input2(i));
+    VERIFY_IS_EQUAL(ref4(i), input1(i) + input2(i));
+  }
+}
+
+
+static void test_multiple_dims()
+{
+  Tensor<float, 3> input(3,5,7);
+  input.setRandom();
+
+  TensorRef<Tensor<float, 3>> ref(input);
+  VERIFY_IS_EQUAL(ref.data(), input.data());
+  VERIFY_IS_EQUAL(ref.dimension(0), 3);
+  VERIFY_IS_EQUAL(ref.dimension(1), 5);
+  VERIFY_IS_EQUAL(ref.dimension(2), 7);
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(ref(i,j,k), input(i,j,k));
+      }
+    }
+  }
+}
+
+
+static void test_slice()
+{
+  Tensor<float, 5> tensor(2,3,5,7,11);
+  tensor.setRandom();
+
+  Eigen::DSizes<ptrdiff_t, 5> indices(1,2,3,4,5);
+  Eigen::DSizes<ptrdiff_t, 5> sizes(1,1,1,1,1);
+  TensorRef<Tensor<float, 5>> slice = tensor.slice(indices, sizes);
+  VERIFY_IS_EQUAL(slice(0,0,0,0,0), tensor(1,2,3,4,5));
+
+  Eigen::DSizes<ptrdiff_t, 5> indices2(1,1,3,4,5);
+  Eigen::DSizes<ptrdiff_t, 5> sizes2(1,1,2,2,3);
+  slice = tensor.slice(indices2, sizes2);
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 2; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        VERIFY_IS_EQUAL(slice(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k));
+      }
+    }
+  }
+
+  Eigen::DSizes<ptrdiff_t, 5> indices3(0,0,0,0,0);
+  Eigen::DSizes<ptrdiff_t, 5> sizes3(2,3,1,1,1);
+  slice = tensor.slice(indices3, sizes3);
+  VERIFY_IS_EQUAL(slice.data(), tensor.data());
+}
+
+
+static void test_ref_of_ref()
+{
+  Tensor<float, 3> input(3,5,7);
+  input.setRandom();
+
+  TensorRef<Tensor<float, 3>> ref(input);
+  TensorRef<Tensor<float, 3>> ref_of_ref(ref);
+  TensorRef<Tensor<float, 3>> ref_of_ref2;
+  ref_of_ref2 = ref;
+
+  VERIFY_IS_EQUAL(ref_of_ref.data(), input.data());
+  VERIFY_IS_EQUAL(ref_of_ref.dimension(0), 3);
+  VERIFY_IS_EQUAL(ref_of_ref.dimension(1), 5);
+  VERIFY_IS_EQUAL(ref_of_ref.dimension(2), 7);
+
+  VERIFY_IS_EQUAL(ref_of_ref2.data(), input.data());
+  VERIFY_IS_EQUAL(ref_of_ref2.dimension(0), 3);
+  VERIFY_IS_EQUAL(ref_of_ref2.dimension(1), 5);
+  VERIFY_IS_EQUAL(ref_of_ref2.dimension(2), 7);
+
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(ref_of_ref(i,j,k), input(i,j,k));
+        VERIFY_IS_EQUAL(ref_of_ref2(i,j,k), input(i,j,k));
+     }
+    }
+  }
+}
+
+
+static void test_ref_in_expr()
+{
+  Tensor<float, 3> input(3,5,7);
+  input.setRandom();
+  TensorRef<Tensor<float, 3>> input_ref(input);
+
+  Tensor<float, 3> result(3,5,7);
+  result.setRandom();
+  TensorRef<Tensor<float, 3>> result_ref(result);
+
+  Tensor<float, 3> bias(3,5,7);
+  bias.setRandom();
+
+  result_ref = input_ref + bias;
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(result_ref(i,j,k), input(i,j,k) + bias(i,j,k));
+        VERIFY_IS_NOT_EQUAL(result(i,j,k), input(i,j,k) + bias(i,j,k));
+      }
+    }
+  }
+
+  result = result_ref;
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_EQUAL(result(i,j,k), input(i,j,k) + bias(i,j,k));
+      }
+    }
+  }
+}
+
+
+static void test_coeff_ref()
+{
+  Tensor<float, 5> tensor(2,3,5,7,11);
+  tensor.setRandom();
+  Tensor<float, 5> original = tensor;
+
+  TensorRef<Tensor<float, 4>> slice = tensor.chip(7, 4);
+  slice.coeffRef(0, 0, 0, 0) = 1.0f;
+  slice.coeffRef(1, 0, 0, 0) += 2.0f;
+
+  VERIFY_IS_EQUAL(tensor(0,0,0,0,7), 1.0f);
+  VERIFY_IS_EQUAL(tensor(1,0,0,0,7), original(1,0,0,0,7) + 2.0f);
+}
+
+
+static void test_nested_ops_with_ref()
+{
+  Tensor<float, 4> t(2, 3, 5, 7);
+  t.setRandom();
+  TensorMap<Tensor<const float, 4> > m(t.data(), 2, 3, 5, 7);
+  array<std::pair<ptrdiff_t, ptrdiff_t>, 4> paddings;
+  paddings[0] = std::make_pair(0, 0);
+  paddings[1] = std::make_pair(2, 1);
+  paddings[2] = std::make_pair(3, 4);
+  paddings[3] = std::make_pair(0, 0);
+  DSizes<Eigen::DenseIndex, 4> shuffle_dims(0, 1, 2, 3);
+  TensorRef<Tensor<const float, 4> > ref(m.pad(paddings));
+  array<std::pair<ptrdiff_t, ptrdiff_t>, 4> trivial;
+  trivial[0] = std::make_pair(0, 0);
+  trivial[1] = std::make_pair(0, 0);
+  trivial[2] = std::make_pair(0, 0);
+  trivial[3] = std::make_pair(0, 0);
+  Tensor<float, 4> padded = ref.shuffle(shuffle_dims).pad(trivial);
+  VERIFY_IS_EQUAL(padded.dimension(0), 2+0);
+  VERIFY_IS_EQUAL(padded.dimension(1), 3+3);
+  VERIFY_IS_EQUAL(padded.dimension(2), 5+7);
+  VERIFY_IS_EQUAL(padded.dimension(3), 7+0);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 6; ++j) {
+      for (int k = 0; k < 12; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          if (j >= 2 && j < 5 && k >= 3 && k < 8) {
+            VERIFY_IS_EQUAL(padded(i,j,k,l), t(i,j-2,k-3,l));
+          } else {
+            VERIFY_IS_EQUAL(padded(i,j,k,l), 0.0f);
+          }
+        }
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_ref()
+{
+  CALL_SUBTEST(test_simple_lvalue_ref());
+  CALL_SUBTEST(test_simple_rvalue_ref());
+  CALL_SUBTEST(test_multiple_dims());
+  CALL_SUBTEST(test_slice());
+  CALL_SUBTEST(test_ref_of_ref());
+  CALL_SUBTEST(test_ref_in_expr());
+  CALL_SUBTEST(test_coeff_ref());
+  CALL_SUBTEST(test_nested_ops_with_ref());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_reverse.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_reverse.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_reverse.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_reverse.cpp
@@ -0,0 +1,190 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Navdeep Jaitly <ndjaitly@google.com and
+//                    Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::array;
+
+template <int DataLayout>
+static void test_simple_reverse()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  array<bool, 4> dim_rev;
+  dim_rev[0] = false;
+  dim_rev[1] = true;
+  dim_rev[2] = true;
+  dim_rev[3] = false;
+
+  Tensor<float, 4, DataLayout> reversed_tensor;
+  reversed_tensor = tensor.reverse(dim_rev);
+
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(0), 2);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(1), 3);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(2), 5);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(3), 7);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), reversed_tensor(i,2-j,4-k,l));
+        }
+      }
+    }
+  }
+
+  dim_rev[0] = true;
+  dim_rev[1] = false;
+  dim_rev[2] = false;
+  dim_rev[3] = false;
+
+  reversed_tensor = tensor.reverse(dim_rev);
+
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(0), 2);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(1), 3);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(2), 5);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(3), 7);
+
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), reversed_tensor(1-i,j,k,l));
+        }
+      }
+    }
+  }
+
+  dim_rev[0] = true;
+  dim_rev[1] = false;
+  dim_rev[2] = false;
+  dim_rev[3] = true;
+
+  reversed_tensor = tensor.reverse(dim_rev);
+
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(0), 2);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(1), 3);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(2), 5);
+  VERIFY_IS_EQUAL(reversed_tensor.dimension(3), 7);
+
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), reversed_tensor(1-i,j,k,6-l));
+        }
+      }
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_expr_reverse(bool LValue)
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  array<bool, 4> dim_rev;
+  dim_rev[0] = false;
+  dim_rev[1] = true;
+  dim_rev[2] = false;
+  dim_rev[3] = true;
+
+  Tensor<float, 4, DataLayout> expected(2, 3, 5, 7);
+  if (LValue) {
+    expected.reverse(dim_rev) = tensor;
+  } else {
+    expected = tensor.reverse(dim_rev);
+  }
+
+  Tensor<float, 4, DataLayout> result(2,3,5,7);
+
+  array<ptrdiff_t, 4> src_slice_dim;
+  src_slice_dim[0] = 2;
+  src_slice_dim[1] = 3;
+  src_slice_dim[2] = 1;
+  src_slice_dim[3] = 7;
+  array<ptrdiff_t, 4> src_slice_start;
+  src_slice_start[0] = 0;
+  src_slice_start[1] = 0;
+  src_slice_start[2] = 0;
+  src_slice_start[3] = 0;
+  array<ptrdiff_t, 4> dst_slice_dim = src_slice_dim;
+  array<ptrdiff_t, 4> dst_slice_start = src_slice_start;
+
+  for (int i = 0; i < 5; ++i) {
+    if (LValue) {
+      result.slice(dst_slice_start, dst_slice_dim).reverse(dim_rev) =
+          tensor.slice(src_slice_start, src_slice_dim);
+    } else {
+      result.slice(dst_slice_start, dst_slice_dim) =
+          tensor.slice(src_slice_start, src_slice_dim).reverse(dim_rev);
+    }
+    src_slice_start[2] += 1;
+    dst_slice_start[2] += 1;
+  }
+
+  VERIFY_IS_EQUAL(result.dimension(0), 2);
+  VERIFY_IS_EQUAL(result.dimension(1), 3);
+  VERIFY_IS_EQUAL(result.dimension(2), 5);
+  VERIFY_IS_EQUAL(result.dimension(3), 7);
+
+  for (int i = 0; i < expected.dimension(0); ++i) {
+    for (int j = 0; j < expected.dimension(1); ++j) {
+      for (int k = 0; k < expected.dimension(2); ++k) {
+        for (int l = 0; l < expected.dimension(3); ++l) {
+          VERIFY_IS_EQUAL(result(i,j,k,l), expected(i,j,k,l));
+        }
+      }
+    }
+  }
+
+  dst_slice_start[2] = 0;
+  result.setRandom();
+  for (int i = 0; i < 5; ++i) {
+     if (LValue) {
+       result.slice(dst_slice_start, dst_slice_dim).reverse(dim_rev) =
+           tensor.slice(dst_slice_start, dst_slice_dim);
+     } else {
+       result.slice(dst_slice_start, dst_slice_dim) =
+           tensor.reverse(dim_rev).slice(dst_slice_start, dst_slice_dim);
+     }
+    dst_slice_start[2] += 1;
+  }
+
+  for (int i = 0; i < expected.dimension(0); ++i) {
+    for (int j = 0; j < expected.dimension(1); ++j) {
+      for (int k = 0; k < expected.dimension(2); ++k) {
+        for (int l = 0; l < expected.dimension(3); ++l) {
+          VERIFY_IS_EQUAL(result(i,j,k,l), expected(i,j,k,l));
+        }
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_reverse()
+{
+  CALL_SUBTEST(test_simple_reverse<ColMajor>());
+  CALL_SUBTEST(test_simple_reverse<RowMajor>());
+  CALL_SUBTEST(test_expr_reverse<ColMajor>(true));
+  CALL_SUBTEST(test_expr_reverse<RowMajor>(true));
+  CALL_SUBTEST(test_expr_reverse<ColMajor>(false));
+  CALL_SUBTEST(test_expr_reverse<RowMajor>(false));
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_roundings.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_roundings.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_roundings.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_roundings.cpp
@@ -0,0 +1,62 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+
+static void test_float_rounding()
+{
+  Tensor<float, 2> ftensor(20,30);
+  ftensor = ftensor.random() * 100.f;
+
+  Tensor<float, 2> result = ftensor.round();
+
+  for (int i = 0; i < 20; ++i) {
+    for (int j = 0; j < 30; ++j) {
+      VERIFY_IS_EQUAL(result(i,j), numext::round(ftensor(i,j)));
+    }
+  }
+}
+
+static void test_float_flooring()
+{
+  Tensor<float, 2> ftensor(20,30);
+  ftensor = ftensor.random() * 100.f;
+
+  Tensor<float, 2> result = ftensor.floor();
+
+  for (int i = 0; i < 20; ++i) {
+    for (int j = 0; j < 30; ++j) {
+      VERIFY_IS_EQUAL(result(i,j), numext::floor(ftensor(i,j)));
+    }
+  }
+}
+
+static void test_float_ceiling()
+{
+  Tensor<float, 2> ftensor(20,30);
+  ftensor = ftensor.random() * 100.f;
+
+  Tensor<float, 2> result = ftensor.ceil();
+
+  for (int i = 0; i < 20; ++i) {
+    for (int j = 0; j < 30; ++j) {
+      VERIFY_IS_EQUAL(result(i,j), numext::ceil(ftensor(i,j)));
+    }
+  }
+}
+
+void test_cxx11_tensor_roundings()
+{
+   CALL_SUBTEST(test_float_rounding());
+   CALL_SUBTEST(test_float_ceiling());
+   CALL_SUBTEST(test_float_flooring());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_scan.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_scan.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_scan.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_scan.cpp
@@ -0,0 +1,110 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Igor Babuschkin <igor@babuschk.in>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <limits>
+#include <numeric>
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template <int DataLayout, typename Type=float, bool Exclusive = false>
+static void test_1d_scan()
+{
+  int size = 50;
+  Tensor<Type, 1, DataLayout> tensor(size);
+  tensor.setRandom();
+  Tensor<Type, 1, DataLayout> result = tensor.cumsum(0, Exclusive);
+
+  VERIFY_IS_EQUAL(tensor.dimension(0), result.dimension(0));
+
+  float accum = 0;
+  for (int i = 0; i < size; i++) {
+    if (Exclusive) {
+      VERIFY_IS_EQUAL(result(i), accum);
+      accum += tensor(i);
+    } else {
+      accum += tensor(i);
+      VERIFY_IS_EQUAL(result(i), accum);
+    }
+  }
+
+  accum = 1;
+  result = tensor.cumprod(0, Exclusive);
+  for (int i = 0; i < size; i++) {
+    if (Exclusive) {
+      VERIFY_IS_EQUAL(result(i), accum);
+      accum *= tensor(i);
+    } else {
+      accum *= tensor(i);
+      VERIFY_IS_EQUAL(result(i), accum);
+    }
+  }
+}
+
+template <int DataLayout, typename Type=float>
+static void test_4d_scan()
+{
+  int size = 5;
+  Tensor<Type, 4, DataLayout> tensor(size, size, size, size);
+  tensor.setRandom();
+
+  Tensor<Type, 4, DataLayout> result(size, size, size, size);
+
+  result = tensor.cumsum(0);
+  float accum = 0;
+  for (int i = 0; i < size; i++) {
+    accum += tensor(i, 1, 2, 3);
+    VERIFY_IS_EQUAL(result(i, 1, 2, 3), accum);
+  }
+  result = tensor.cumsum(1);
+  accum = 0;
+  for (int i = 0; i < size; i++) {
+    accum += tensor(1, i, 2, 3);
+    VERIFY_IS_EQUAL(result(1, i, 2, 3), accum);
+  }
+  result = tensor.cumsum(2);
+  accum = 0;
+  for (int i = 0; i < size; i++) {
+    accum += tensor(1, 2, i, 3);
+    VERIFY_IS_EQUAL(result(1, 2, i, 3), accum);
+  }
+  result = tensor.cumsum(3);
+  accum = 0;
+  for (int i = 0; i < size; i++) {
+    accum += tensor(1, 2, 3, i);
+    VERIFY_IS_EQUAL(result(1, 2, 3, i), accum);
+  }
+}
+
+template <int DataLayout>
+static void test_tensor_maps() {
+  int inputs[20];
+  TensorMap<Tensor<int, 1, DataLayout> > tensor_map(inputs, 20);
+  tensor_map.setRandom();
+
+  Tensor<int, 1, DataLayout> result = tensor_map.cumsum(0);
+
+  int accum = 0;
+  for (int i = 0; i < 20; ++i) {
+    accum += tensor_map(i);
+    VERIFY_IS_EQUAL(result(i), accum);
+  }
+}
+
+void test_cxx11_tensor_scan() {
+  CALL_SUBTEST((test_1d_scan<ColMajor, float, true>()));
+  CALL_SUBTEST((test_1d_scan<ColMajor, float, false>()));
+  CALL_SUBTEST((test_1d_scan<RowMajor, float, true>()));
+  CALL_SUBTEST((test_1d_scan<RowMajor, float, false>()));
+  CALL_SUBTEST(test_4d_scan<ColMajor>());
+  CALL_SUBTEST(test_4d_scan<RowMajor>());
+  CALL_SUBTEST(test_tensor_maps<ColMajor>());
+  CALL_SUBTEST(test_tensor_maps<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_scan_cuda.cu
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_scan_cuda.cu
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_scan_cuda.cu
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_scan_cuda.cu
@@ -0,0 +1,79 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_scan_cuda
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_GPU
+
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+typedef Tensor<float, 1>::DimensionPair DimPair;
+
+template<int DataLayout>
+void test_cuda_cumsum(int m_size, int k_size, int n_size)
+{
+  std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl;
+  Tensor<float, 3, DataLayout> t_input(m_size, k_size, n_size);
+  Tensor<float, 3, DataLayout> t_result(m_size, k_size, n_size);
+  Tensor<float, 3, DataLayout> t_result_gpu(m_size, k_size, n_size);
+
+  t_input.setRandom();
+
+  std::size_t t_input_bytes = t_input.size()  * sizeof(float);
+  std::size_t t_result_bytes = t_result.size() * sizeof(float);
+
+  float* d_t_input;
+  float* d_t_result;
+
+  cudaMalloc((void**)(&d_t_input), t_input_bytes);
+  cudaMalloc((void**)(&d_t_result), t_result_bytes);
+
+  cudaMemcpy(d_t_input, t_input.data(), t_input_bytes, cudaMemcpyHostToDevice);
+
+  Eigen::CudaStreamDevice stream;
+  Eigen::GpuDevice gpu_device(&stream);
+
+  Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> >
+      gpu_t_input(d_t_input, Eigen::array<int, 3>(m_size, k_size, n_size));
+  Eigen::TensorMap<Eigen::Tensor<float, 3, DataLayout> >
+      gpu_t_result(d_t_result, Eigen::array<int, 3>(m_size, k_size, n_size));
+
+  gpu_t_result.device(gpu_device) = gpu_t_input.cumsum(1);
+  t_result = t_input.cumsum(1);
+
+  cudaMemcpy(t_result_gpu.data(), d_t_result, t_result_bytes, cudaMemcpyDeviceToHost);
+  for (DenseIndex i = 0; i < t_result.size(); i++) {
+    if (fabs(t_result(i) - t_result_gpu(i)) < 1e-4f) {
+      continue;
+    }
+    if (Eigen::internal::isApprox(t_result(i), t_result_gpu(i), 1e-4f)) {
+      continue;
+    }
+    std::cout << "mismatch detected at index " << i << ": " << t_result(i)
+              << " vs " <<  t_result_gpu(i) << std::endl;
+    assert(false);
+  }
+
+  cudaFree((void*)d_t_input);
+  cudaFree((void*)d_t_result);
+}
+
+
+void test_cxx11_tensor_scan_cuda()
+{
+  CALL_SUBTEST_1(test_cuda_cumsum<ColMajor>(128, 128, 128));
+  CALL_SUBTEST_2(test_cuda_cumsum<RowMajor>(128, 128, 128));
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_shuffling.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_shuffling.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_shuffling.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_shuffling.cpp
@@ -0,0 +1,228 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::array;
+
+template <int DataLayout>
+static void test_simple_shuffling()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  array<ptrdiff_t, 4> shuffles;
+  shuffles[0] = 0;
+  shuffles[1] = 1;
+  shuffles[2] = 2;
+  shuffles[3] = 3;
+
+  Tensor<float, 4, DataLayout> no_shuffle;
+  no_shuffle = tensor.shuffle(shuffles);
+
+  VERIFY_IS_EQUAL(no_shuffle.dimension(0), 2);
+  VERIFY_IS_EQUAL(no_shuffle.dimension(1), 3);
+  VERIFY_IS_EQUAL(no_shuffle.dimension(2), 5);
+  VERIFY_IS_EQUAL(no_shuffle.dimension(3), 7);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), no_shuffle(i,j,k,l));
+        }
+      }
+    }
+  }
+
+  shuffles[0] = 2;
+  shuffles[1] = 3;
+  shuffles[2] = 1;
+  shuffles[3] = 0;
+  Tensor<float, 4, DataLayout> shuffle;
+  shuffle = tensor.shuffle(shuffles);
+
+  VERIFY_IS_EQUAL(shuffle.dimension(0), 5);
+  VERIFY_IS_EQUAL(shuffle.dimension(1), 7);
+  VERIFY_IS_EQUAL(shuffle.dimension(2), 3);
+  VERIFY_IS_EQUAL(shuffle.dimension(3), 2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), shuffle(k,l,j,i));
+        }
+      }
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_expr_shuffling()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  array<ptrdiff_t, 4> shuffles;
+  shuffles[0] = 2;
+  shuffles[1] = 3;
+  shuffles[2] = 1;
+  shuffles[3] = 0;
+  Tensor<float, 4, DataLayout> expected;
+  expected = tensor.shuffle(shuffles);
+
+  Tensor<float, 4, DataLayout> result(5,7,3,2);
+
+  array<int, 4> src_slice_dim{{2,3,1,7}};
+  array<int, 4> src_slice_start{{0,0,0,0}};
+  array<int, 4> dst_slice_dim{{1,7,3,2}};
+  array<int, 4> dst_slice_start{{0,0,0,0}};
+
+  for (int i = 0; i < 5; ++i) {
+    result.slice(dst_slice_start, dst_slice_dim) =
+        tensor.slice(src_slice_start, src_slice_dim).shuffle(shuffles);
+    src_slice_start[2] += 1;
+    dst_slice_start[0] += 1;
+  }
+
+  VERIFY_IS_EQUAL(result.dimension(0), 5);
+  VERIFY_IS_EQUAL(result.dimension(1), 7);
+  VERIFY_IS_EQUAL(result.dimension(2), 3);
+  VERIFY_IS_EQUAL(result.dimension(3), 2);
+
+  for (int i = 0; i < expected.dimension(0); ++i) {
+    for (int j = 0; j < expected.dimension(1); ++j) {
+      for (int k = 0; k < expected.dimension(2); ++k) {
+        for (int l = 0; l < expected.dimension(3); ++l) {
+          VERIFY_IS_EQUAL(result(i,j,k,l), expected(i,j,k,l));
+        }
+      }
+    }
+  }
+
+  dst_slice_start[0] = 0;
+  result.setRandom();
+  for (int i = 0; i < 5; ++i) {
+    result.slice(dst_slice_start, dst_slice_dim) =
+        tensor.shuffle(shuffles).slice(dst_slice_start, dst_slice_dim);
+    dst_slice_start[0] += 1;
+  }
+
+  for (int i = 0; i < expected.dimension(0); ++i) {
+    for (int j = 0; j < expected.dimension(1); ++j) {
+      for (int k = 0; k < expected.dimension(2); ++k) {
+        for (int l = 0; l < expected.dimension(3); ++l) {
+          VERIFY_IS_EQUAL(result(i,j,k,l), expected(i,j,k,l));
+        }
+      }
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_shuffling_as_value()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  array<ptrdiff_t, 4> shuffles;
+  shuffles[2] = 0;
+  shuffles[3] = 1;
+  shuffles[1] = 2;
+  shuffles[0] = 3;
+  Tensor<float, 4, DataLayout> shuffle(5,7,3,2);
+  shuffle.shuffle(shuffles) = tensor;
+
+  VERIFY_IS_EQUAL(shuffle.dimension(0), 5);
+  VERIFY_IS_EQUAL(shuffle.dimension(1), 7);
+  VERIFY_IS_EQUAL(shuffle.dimension(2), 3);
+  VERIFY_IS_EQUAL(shuffle.dimension(3), 2);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), shuffle(k,l,j,i));
+        }
+      }
+    }
+  }
+
+  array<ptrdiff_t, 4> no_shuffle;
+  no_shuffle[0] = 0;
+  no_shuffle[1] = 1;
+  no_shuffle[2] = 2;
+  no_shuffle[3] = 3;
+  Tensor<float, 4, DataLayout> shuffle2(5,7,3,2);
+  shuffle2.shuffle(shuffles) = tensor.shuffle(no_shuffle);
+  for (int i = 0; i < 5; ++i) {
+    for (int j = 0; j < 7; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 2; ++l) {
+          VERIFY_IS_EQUAL(shuffle2(i,j,k,l), shuffle(i,j,k,l));
+        }
+      }
+    }
+  }
+}
+
+
+template <int DataLayout>
+static void test_shuffle_unshuffle()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+
+  // Choose a random permutation.
+  array<ptrdiff_t, 4> shuffles;
+  for (int i = 0; i < 4; ++i) {
+    shuffles[i] = i;
+  }
+  array<ptrdiff_t, 4> shuffles_inverse;
+  for (int i = 0; i < 4; ++i) {
+    const ptrdiff_t index = internal::random<ptrdiff_t>(i, 3);
+    shuffles_inverse[shuffles[index]] = i;
+    std::swap(shuffles[i], shuffles[index]);
+  }
+
+  Tensor<float, 4, DataLayout> shuffle;
+  shuffle = tensor.shuffle(shuffles).shuffle(shuffles_inverse);
+
+  VERIFY_IS_EQUAL(shuffle.dimension(0), 2);
+  VERIFY_IS_EQUAL(shuffle.dimension(1), 3);
+  VERIFY_IS_EQUAL(shuffle.dimension(2), 5);
+  VERIFY_IS_EQUAL(shuffle.dimension(3), 7);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), shuffle(i,j,k,l));
+        }
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_shuffling()
+{
+  CALL_SUBTEST(test_simple_shuffling<ColMajor>());
+  CALL_SUBTEST(test_simple_shuffling<RowMajor>());
+  CALL_SUBTEST(test_expr_shuffling<ColMajor>());
+  CALL_SUBTEST(test_expr_shuffling<RowMajor>());
+  CALL_SUBTEST(test_shuffling_as_value<ColMajor>());
+  CALL_SUBTEST(test_shuffling_as_value<RowMajor>());
+  CALL_SUBTEST(test_shuffle_unshuffle<ColMajor>());
+  CALL_SUBTEST(test_shuffle_unshuffle<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_simple.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_simple.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_simple.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_simple.cpp
@@ -0,0 +1,327 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_0d()
+{
+  Tensor<int, 0> scalar1;
+  Tensor<int, 0, RowMajor> scalar2;
+  Tensor<int, 0> scalar3;
+  Tensor<int, 0, RowMajor> scalar4;
+
+  scalar3.resize();
+  scalar4.resize();
+
+  scalar1() = 7;
+  scalar2() = 13;
+  scalar3.setValues(17);
+  scalar4.setZero();
+
+  VERIFY_IS_EQUAL(scalar1.rank(), 0);
+  VERIFY_IS_EQUAL(scalar1.size(), 1);
+
+  VERIFY_IS_EQUAL(scalar1(), 7);
+  VERIFY_IS_EQUAL(scalar2(), 13);
+  VERIFY_IS_EQUAL(scalar3(), 17);
+  VERIFY_IS_EQUAL(scalar4(), 0);
+
+  Tensor<int, 0> scalar5(scalar1);
+
+  VERIFY_IS_EQUAL(scalar5(), 7);
+  VERIFY_IS_EQUAL(scalar5.data()[0], 7);
+}
+
+static void test_1d()
+{
+  Tensor<int, 1> vec1(6);
+  Tensor<int, 1, RowMajor> vec2(6);
+  Tensor<int, 1> vec3;
+  Tensor<int, 1, RowMajor> vec4;
+
+  vec3.resize(6);
+  vec4.resize(6);
+
+  vec1(0) = 4;  vec2(0) = 0; vec3(0) = 5;
+  vec1(1) = 8;  vec2(1) = 1; vec3(1) = 4;
+  vec1(2) = 15; vec2(2) = 2; vec3(2) = 3;
+  vec1(3) = 16; vec2(3) = 3; vec3(3) = 2;
+  vec1(4) = 23; vec2(4) = 4; vec3(4) = 1;
+  vec1(5) = 42; vec2(5) = 5; vec3(5) = 0;
+  vec4.setZero();
+
+  VERIFY_IS_EQUAL((vec1.rank()), 1);
+  VERIFY_IS_EQUAL((vec1.size()), 6);
+  VERIFY_IS_EQUAL((vec1.dimensions()[0]), 6);
+
+  VERIFY_IS_EQUAL((vec1[0]), 4);
+  VERIFY_IS_EQUAL((vec1[1]), 8);
+  VERIFY_IS_EQUAL((vec1[2]), 15);
+  VERIFY_IS_EQUAL((vec1[3]), 16);
+  VERIFY_IS_EQUAL((vec1[4]), 23);
+  VERIFY_IS_EQUAL((vec1[5]), 42);
+
+  VERIFY_IS_EQUAL((vec2[0]), 0);
+  VERIFY_IS_EQUAL((vec2[1]), 1);
+  VERIFY_IS_EQUAL((vec2[2]), 2);
+  VERIFY_IS_EQUAL((vec2[3]), 3);
+  VERIFY_IS_EQUAL((vec2[4]), 4);
+  VERIFY_IS_EQUAL((vec2[5]), 5);
+
+  VERIFY_IS_EQUAL((vec3[0]), 5);
+  VERIFY_IS_EQUAL((vec3[1]), 4);
+  VERIFY_IS_EQUAL((vec3[2]), 3);
+  VERIFY_IS_EQUAL((vec3[3]), 2);
+  VERIFY_IS_EQUAL((vec3[4]), 1);
+  VERIFY_IS_EQUAL((vec3[5]), 0);
+
+  VERIFY_IS_EQUAL((vec4[0]), 0);
+  VERIFY_IS_EQUAL((vec4[1]), 0);
+  VERIFY_IS_EQUAL((vec4[2]), 0);
+  VERIFY_IS_EQUAL((vec4[3]), 0);
+  VERIFY_IS_EQUAL((vec4[4]), 0);
+  VERIFY_IS_EQUAL((vec4[5]), 0);
+
+  Tensor<int, 1> vec5(vec1);
+
+  VERIFY_IS_EQUAL((vec5(0)), 4);
+  VERIFY_IS_EQUAL((vec5(1)), 8);
+  VERIFY_IS_EQUAL((vec5(2)), 15);
+  VERIFY_IS_EQUAL((vec5(3)), 16);
+  VERIFY_IS_EQUAL((vec5(4)), 23);
+  VERIFY_IS_EQUAL((vec5(5)), 42);
+
+  VERIFY_IS_EQUAL((vec5.data()[0]), 4);
+  VERIFY_IS_EQUAL((vec5.data()[1]), 8);
+  VERIFY_IS_EQUAL((vec5.data()[2]), 15);
+  VERIFY_IS_EQUAL((vec5.data()[3]), 16);
+  VERIFY_IS_EQUAL((vec5.data()[4]), 23);
+  VERIFY_IS_EQUAL((vec5.data()[5]), 42);
+}
+
+static void test_2d()
+{
+  Tensor<int, 2> mat1(2,3);
+  Tensor<int, 2, RowMajor> mat2(2,3);
+
+  mat1(0,0) = 0;
+  mat1(0,1) = 1;
+  mat1(0,2) = 2;
+  mat1(1,0) = 3;
+  mat1(1,1) = 4;
+  mat1(1,2) = 5;
+
+  mat2(0,0) = 0;
+  mat2(0,1) = 1;
+  mat2(0,2) = 2;
+  mat2(1,0) = 3;
+  mat2(1,1) = 4;
+  mat2(1,2) = 5;
+
+  VERIFY_IS_EQUAL((mat1.rank()), 2);
+  VERIFY_IS_EQUAL((mat1.size()), 6);
+  VERIFY_IS_EQUAL((mat1.dimensions()[0]), 2);
+  VERIFY_IS_EQUAL((mat1.dimensions()[1]), 3);
+
+  VERIFY_IS_EQUAL((mat2.rank()), 2);
+  VERIFY_IS_EQUAL((mat2.size()), 6);
+  VERIFY_IS_EQUAL((mat2.dimensions()[0]), 2);
+  VERIFY_IS_EQUAL((mat2.dimensions()[1]), 3);
+
+  VERIFY_IS_EQUAL((mat1.data()[0]), 0);
+  VERIFY_IS_EQUAL((mat1.data()[1]), 3);
+  VERIFY_IS_EQUAL((mat1.data()[2]), 1);
+  VERIFY_IS_EQUAL((mat1.data()[3]), 4);
+  VERIFY_IS_EQUAL((mat1.data()[4]), 2);
+  VERIFY_IS_EQUAL((mat1.data()[5]), 5);
+
+  VERIFY_IS_EQUAL((mat2.data()[0]), 0);
+  VERIFY_IS_EQUAL((mat2.data()[1]), 1);
+  VERIFY_IS_EQUAL((mat2.data()[2]), 2);
+  VERIFY_IS_EQUAL((mat2.data()[3]), 3);
+  VERIFY_IS_EQUAL((mat2.data()[4]), 4);
+  VERIFY_IS_EQUAL((mat2.data()[5]), 5);
+}
+
+static void test_3d()
+{
+  Tensor<int, 3> epsilon(3,3,3);
+  epsilon.setZero();
+  epsilon(0,1,2) = epsilon(2,0,1) = epsilon(1,2,0) = 1;
+  epsilon(2,1,0) = epsilon(0,2,1) = epsilon(1,0,2) = -1;
+
+  VERIFY_IS_EQUAL((epsilon.size()), 27);
+  VERIFY_IS_EQUAL((epsilon.dimensions()[0]), 3);
+  VERIFY_IS_EQUAL((epsilon.dimensions()[1]), 3);
+  VERIFY_IS_EQUAL((epsilon.dimensions()[2]), 3);
+
+  VERIFY_IS_EQUAL((epsilon(0,0,0)), 0);
+  VERIFY_IS_EQUAL((epsilon(0,0,1)), 0);
+  VERIFY_IS_EQUAL((epsilon(0,0,2)), 0);
+  VERIFY_IS_EQUAL((epsilon(0,1,0)), 0);
+  VERIFY_IS_EQUAL((epsilon(0,1,1)), 0);
+  VERIFY_IS_EQUAL((epsilon(0,2,0)), 0);
+  VERIFY_IS_EQUAL((epsilon(0,2,2)), 0);
+  VERIFY_IS_EQUAL((epsilon(1,0,0)), 0);
+  VERIFY_IS_EQUAL((epsilon(1,0,1)), 0);
+  VERIFY_IS_EQUAL((epsilon(1,1,0)), 0);
+  VERIFY_IS_EQUAL((epsilon(1,1,1)), 0);
+  VERIFY_IS_EQUAL((epsilon(1,1,2)), 0);
+  VERIFY_IS_EQUAL((epsilon(1,2,1)), 0);
+  VERIFY_IS_EQUAL((epsilon(1,2,2)), 0);
+  VERIFY_IS_EQUAL((epsilon(2,0,0)), 0);
+  VERIFY_IS_EQUAL((epsilon(2,0,2)), 0);
+  VERIFY_IS_EQUAL((epsilon(2,1,1)), 0);
+  VERIFY_IS_EQUAL((epsilon(2,1,2)), 0);
+  VERIFY_IS_EQUAL((epsilon(2,2,0)), 0);
+  VERIFY_IS_EQUAL((epsilon(2,2,1)), 0);
+  VERIFY_IS_EQUAL((epsilon(2,2,2)), 0);
+
+  VERIFY_IS_EQUAL((epsilon(0,1,2)), 1);
+  VERIFY_IS_EQUAL((epsilon(2,0,1)), 1);
+  VERIFY_IS_EQUAL((epsilon(1,2,0)), 1);
+  VERIFY_IS_EQUAL((epsilon(2,1,0)), -1);
+  VERIFY_IS_EQUAL((epsilon(0,2,1)), -1);
+  VERIFY_IS_EQUAL((epsilon(1,0,2)), -1);
+
+  array<Eigen::DenseIndex, 3> dims;
+  dims[0] = 2;
+  dims[1] = 3;
+  dims[2] = 4;
+  Tensor<int, 3> t1(dims);
+  Tensor<int, 3, RowMajor> t2(dims);
+
+  VERIFY_IS_EQUAL((t1.size()), 24);
+  VERIFY_IS_EQUAL((t1.dimensions()[0]), 2);
+  VERIFY_IS_EQUAL((t1.dimensions()[1]), 3);
+  VERIFY_IS_EQUAL((t1.dimensions()[2]), 4);
+
+  VERIFY_IS_EQUAL((t2.size()), 24);
+  VERIFY_IS_EQUAL((t2.dimensions()[0]), 2);
+  VERIFY_IS_EQUAL((t2.dimensions()[1]), 3);
+  VERIFY_IS_EQUAL((t2.dimensions()[2]), 4);
+
+  for (int i = 0; i < 2; i++) {
+    for (int j = 0; j < 3; j++) {
+      for (int k = 0; k < 4; k++) {
+        t1(i, j, k) = 100 * i + 10 * j + k;
+        t2(i, j, k) = 100 * i + 10 * j + k;
+      }
+    }
+  }
+
+  VERIFY_IS_EQUAL((t1.data()[0]),    0);
+  VERIFY_IS_EQUAL((t1.data()[1]),  100);
+  VERIFY_IS_EQUAL((t1.data()[2]),   10);
+  VERIFY_IS_EQUAL((t1.data()[3]),  110);
+  VERIFY_IS_EQUAL((t1.data()[4]),   20);
+  VERIFY_IS_EQUAL((t1.data()[5]),  120);
+  VERIFY_IS_EQUAL((t1.data()[6]),    1);
+  VERIFY_IS_EQUAL((t1.data()[7]),  101);
+  VERIFY_IS_EQUAL((t1.data()[8]),   11);
+  VERIFY_IS_EQUAL((t1.data()[9]),  111);
+  VERIFY_IS_EQUAL((t1.data()[10]),  21);
+  VERIFY_IS_EQUAL((t1.data()[11]), 121);
+  VERIFY_IS_EQUAL((t1.data()[12]),   2);
+  VERIFY_IS_EQUAL((t1.data()[13]), 102);
+  VERIFY_IS_EQUAL((t1.data()[14]),  12);
+  VERIFY_IS_EQUAL((t1.data()[15]), 112);
+  VERIFY_IS_EQUAL((t1.data()[16]),  22);
+  VERIFY_IS_EQUAL((t1.data()[17]), 122);
+  VERIFY_IS_EQUAL((t1.data()[18]),   3);
+  VERIFY_IS_EQUAL((t1.data()[19]), 103);
+  VERIFY_IS_EQUAL((t1.data()[20]),  13);
+  VERIFY_IS_EQUAL((t1.data()[21]), 113);
+  VERIFY_IS_EQUAL((t1.data()[22]),  23);
+  VERIFY_IS_EQUAL((t1.data()[23]), 123);
+
+  VERIFY_IS_EQUAL((t2.data()[0]),    0);
+  VERIFY_IS_EQUAL((t2.data()[1]),    1);
+  VERIFY_IS_EQUAL((t2.data()[2]),    2);
+  VERIFY_IS_EQUAL((t2.data()[3]),    3);
+  VERIFY_IS_EQUAL((t2.data()[4]),   10);
+  VERIFY_IS_EQUAL((t2.data()[5]),   11);
+  VERIFY_IS_EQUAL((t2.data()[6]),   12);
+  VERIFY_IS_EQUAL((t2.data()[7]),   13);
+  VERIFY_IS_EQUAL((t2.data()[8]),   20);
+  VERIFY_IS_EQUAL((t2.data()[9]),   21);
+  VERIFY_IS_EQUAL((t2.data()[10]),  22);
+  VERIFY_IS_EQUAL((t2.data()[11]),  23);
+  VERIFY_IS_EQUAL((t2.data()[12]), 100);
+  VERIFY_IS_EQUAL((t2.data()[13]), 101);
+  VERIFY_IS_EQUAL((t2.data()[14]), 102);
+  VERIFY_IS_EQUAL((t2.data()[15]), 103);
+  VERIFY_IS_EQUAL((t2.data()[16]), 110);
+  VERIFY_IS_EQUAL((t2.data()[17]), 111);
+  VERIFY_IS_EQUAL((t2.data()[18]), 112);
+  VERIFY_IS_EQUAL((t2.data()[19]), 113);
+  VERIFY_IS_EQUAL((t2.data()[20]), 120);
+  VERIFY_IS_EQUAL((t2.data()[21]), 121);
+  VERIFY_IS_EQUAL((t2.data()[22]), 122);
+  VERIFY_IS_EQUAL((t2.data()[23]), 123);
+}
+
+static void test_simple_assign()
+{
+  Tensor<int, 3> epsilon(3,3,3);
+  epsilon.setZero();
+  epsilon(0,1,2) = epsilon(2,0,1) = epsilon(1,2,0) = 1;
+  epsilon(2,1,0) = epsilon(0,2,1) = epsilon(1,0,2) = -1;
+
+  Tensor<int, 3> e2(3,3,3);
+  e2.setZero();
+  VERIFY_IS_EQUAL((e2(1,2,0)), 0);
+
+  e2 = epsilon;
+  VERIFY_IS_EQUAL((e2(1,2,0)), 1);
+  VERIFY_IS_EQUAL((e2(0,1,2)), 1);
+  VERIFY_IS_EQUAL((e2(2,0,1)), 1);
+  VERIFY_IS_EQUAL((e2(2,1,0)), -1);
+  VERIFY_IS_EQUAL((e2(0,2,1)), -1);
+  VERIFY_IS_EQUAL((e2(1,0,2)), -1);
+}
+
+static void test_resize()
+{
+  Tensor<int, 3> epsilon;
+  epsilon.resize(2,3,7);
+  VERIFY_IS_EQUAL(epsilon.dimension(0), 2);
+  VERIFY_IS_EQUAL(epsilon.dimension(1), 3);
+  VERIFY_IS_EQUAL(epsilon.dimension(2), 7);
+  VERIFY_IS_EQUAL(epsilon.size(), 2*3*7);
+
+  const int* old_data = epsilon.data();
+  epsilon.resize(3,2,7);
+  VERIFY_IS_EQUAL(epsilon.dimension(0), 3);
+  VERIFY_IS_EQUAL(epsilon.dimension(1), 2);
+  VERIFY_IS_EQUAL(epsilon.dimension(2), 7);
+  VERIFY_IS_EQUAL(epsilon.size(), 2*3*7);
+  VERIFY_IS_EQUAL(epsilon.data(), old_data);
+
+  epsilon.resize(3,5,7);
+  VERIFY_IS_EQUAL(epsilon.dimension(0), 3);
+  VERIFY_IS_EQUAL(epsilon.dimension(1), 5);
+  VERIFY_IS_EQUAL(epsilon.dimension(2), 7);
+  VERIFY_IS_EQUAL(epsilon.size(), 3*5*7);
+}
+
+void test_cxx11_tensor_simple()
+{
+  CALL_SUBTEST(test_0d());
+  CALL_SUBTEST(test_1d());
+  CALL_SUBTEST(test_2d());
+  CALL_SUBTEST(test_3d());
+  CALL_SUBTEST(test_simple_assign());
+  CALL_SUBTEST(test_resize());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_striding.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_striding.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_striding.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_striding.cpp
@@ -0,0 +1,119 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template<int DataLayout>
+static void test_simple_striding()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  array<ptrdiff_t, 4> strides;
+  strides[0] = 1;
+  strides[1] = 1;
+  strides[2] = 1;
+  strides[3] = 1;
+
+  Tensor<float, 4, DataLayout> no_stride;
+  no_stride = tensor.stride(strides);
+
+  VERIFY_IS_EQUAL(no_stride.dimension(0), 2);
+  VERIFY_IS_EQUAL(no_stride.dimension(1), 3);
+  VERIFY_IS_EQUAL(no_stride.dimension(2), 5);
+  VERIFY_IS_EQUAL(no_stride.dimension(3), 7);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), no_stride(i,j,k,l));
+        }
+      }
+    }
+  }
+
+  strides[0] = 2;
+  strides[1] = 4;
+  strides[2] = 2;
+  strides[3] = 3;
+  Tensor<float, 4, DataLayout> stride;
+  stride = tensor.stride(strides);
+
+  VERIFY_IS_EQUAL(stride.dimension(0), 1);
+  VERIFY_IS_EQUAL(stride.dimension(1), 1);
+  VERIFY_IS_EQUAL(stride.dimension(2), 3);
+  VERIFY_IS_EQUAL(stride.dimension(3), 3);
+
+  for (int i = 0; i < 1; ++i) {
+    for (int j = 0; j < 1; ++j) {
+      for (int k = 0; k < 3; ++k) {
+        for (int l = 0; l < 3; ++l) {
+          VERIFY_IS_EQUAL(tensor(2*i,4*j,2*k,3*l), stride(i,j,k,l));
+        }
+      }
+    }
+  }
+}
+
+
+template<int DataLayout>
+static void test_striding_as_lvalue()
+{
+  Tensor<float, 4, DataLayout> tensor(2,3,5,7);
+  tensor.setRandom();
+  array<ptrdiff_t, 4> strides;
+  strides[0] = 2;
+  strides[1] = 4;
+  strides[2] = 2;
+  strides[3] = 3;
+
+  Tensor<float, 4, DataLayout> result(3, 12, 10, 21);
+  result.stride(strides) = tensor;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), result(2*i,4*j,2*k,3*l));
+        }
+      }
+    }
+  }
+
+  array<ptrdiff_t, 4> no_strides;
+  no_strides[0] = 1;
+  no_strides[1] = 1;
+  no_strides[2] = 1;
+  no_strides[3] = 1;
+  Tensor<float, 4, DataLayout> result2(3, 12, 10, 21);
+  result2.stride(strides) = tensor.stride(no_strides);
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 7; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), result2(2*i,4*j,2*k,3*l));
+        }
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_striding()
+{
+  CALL_SUBTEST(test_simple_striding<ColMajor>());
+  CALL_SUBTEST(test_simple_striding<RowMajor>());
+  CALL_SUBTEST(test_striding_as_lvalue<ColMajor>());
+  CALL_SUBTEST(test_striding_as_lvalue<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_sugar.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_sugar.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_sugar.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_sugar.cpp
@@ -0,0 +1,81 @@
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+using Eigen::RowMajor;
+
+static void test_comparison_sugar() {
+  // we already trust comparisons between tensors, we're simply checking that
+  // the sugared versions are doing the same thing
+  Tensor<int, 3> t(6, 7, 5);
+
+  t.setRandom();
+  // make sure we have at least one value == 0
+  t(0,0,0) = 0;
+
+  Tensor<bool,0> b;
+
+#define TEST_TENSOR_EQUAL(e1, e2) \
+  b = ((e1) == (e2)).all();       \
+  VERIFY(b())
+
+#define TEST_OP(op) TEST_TENSOR_EQUAL(t op 0, t op t.constant(0))
+
+  TEST_OP(==);
+  TEST_OP(!=);
+  TEST_OP(<=);
+  TEST_OP(>=);
+  TEST_OP(<);
+  TEST_OP(>);
+#undef TEST_OP
+#undef TEST_TENSOR_EQUAL
+}
+
+
+static void test_scalar_sugar_add_mul() {
+  Tensor<float, 3> A(6, 7, 5);
+  Tensor<float, 3> B(6, 7, 5);
+  A.setRandom();
+  B.setRandom();
+
+  const float alpha = 0.43f;
+  const float beta = 0.21f;
+  const float gamma = 0.14f;
+
+  Tensor<float, 3> R = A.constant(gamma) + A * A.constant(alpha) + B * B.constant(beta);
+  Tensor<float, 3> S = A * alpha + B * beta + gamma;
+  Tensor<float, 3> T = gamma + alpha * A + beta * B;
+
+  for (int i = 0; i < 6*7*5; ++i) {
+    VERIFY_IS_APPROX(R(i), S(i));
+    VERIFY_IS_APPROX(R(i), T(i));
+  }
+}
+
+static void test_scalar_sugar_sub_div() {
+  Tensor<float, 3> A(6, 7, 5);
+  Tensor<float, 3> B(6, 7, 5);
+  A.setRandom();
+  B.setRandom();
+
+  const float alpha = 0.43f;
+  const float beta = 0.21f;
+  const float gamma = 0.14f;
+  const float delta = 0.32f;
+
+  Tensor<float, 3> R = A.constant(gamma) - A / A.constant(alpha)
+      - B.constant(beta) / B - A.constant(delta);
+  Tensor<float, 3> S = gamma - A / alpha - beta / B - delta;
+
+  for (int i = 0; i < 6*7*5; ++i) {
+    VERIFY_IS_APPROX(R(i), S(i));
+  }
+}
+
+void test_cxx11_tensor_sugar()
+{
+  CALL_SUBTEST(test_comparison_sugar());
+  CALL_SUBTEST(test_scalar_sugar_add_mul());
+  CALL_SUBTEST(test_scalar_sugar_sub_div());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_sycl.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_sycl.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_sycl.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_sycl.cpp
@@ -0,0 +1,159 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016
+// Mehdi Goli    Codeplay Software Ltd.
+// Ralph Potter  Codeplay Software Ltd.
+// Luke Iwanski  Codeplay Software Ltd.
+// Contact: <eigen@codeplay.com>
+// Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+
+#define EIGEN_TEST_NO_LONGDOUBLE
+#define EIGEN_TEST_NO_COMPLEX
+#define EIGEN_TEST_FUNC cxx11_tensor_sycl
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_SYCL
+
+#include "main.h"
+#include <unsupported/Eigen/CXX11/Tensor>
+
+using Eigen::array;
+using Eigen::SyclDevice;
+using Eigen::Tensor;
+using Eigen::TensorMap;
+
+void test_sycl_cpu(const Eigen::SyclDevice &sycl_device) {
+
+  int sizeDim1 = 100;
+  int sizeDim2 = 100;
+  int sizeDim3 = 100;
+  array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
+  Tensor<float, 3> in1(tensorRange);
+  Tensor<float, 3> in2(tensorRange);
+  Tensor<float, 3> in3(tensorRange);
+  Tensor<float, 3> out(tensorRange);
+
+  in2 = in2.random();
+  in3 = in3.random();
+
+  float * gpu_in1_data  = static_cast<float*>(sycl_device.allocate(in1.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_in2_data  = static_cast<float*>(sycl_device.allocate(in2.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_in3_data  = static_cast<float*>(sycl_device.allocate(in3.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_out_data =  static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
+
+  TensorMap<Tensor<float, 3>> gpu_in1(gpu_in1_data, tensorRange);
+  TensorMap<Tensor<float, 3>> gpu_in2(gpu_in2_data, tensorRange);
+  TensorMap<Tensor<float, 3>> gpu_in3(gpu_in3_data, tensorRange);
+  TensorMap<Tensor<float, 3>> gpu_out(gpu_out_data, tensorRange);
+
+  /// a=1.2f
+  gpu_in1.device(sycl_device) = gpu_in1.constant(1.2f);
+  sycl_device.memcpyDeviceToHost(in1.data(), gpu_in1_data ,(in1.dimensions().TotalSize())*sizeof(float));
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(in1(i,j,k), 1.2f);
+      }
+    }
+  }
+  printf("a=1.2f Test passed\n");
+
+  /// a=b*1.2f
+  gpu_out.device(sycl_device) = gpu_in1 * 1.2f;
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data ,(out.dimensions().TotalSize())*sizeof(float));
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k),
+                         in1(i,j,k) * 1.2f);
+      }
+    }
+  }
+  printf("a=b*1.2f Test Passed\n");
+
+  /// c=a*b
+  sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in2.dimensions().TotalSize())*sizeof(float));
+  gpu_out.device(sycl_device) = gpu_in1 * gpu_in2;
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k),
+                         in1(i,j,k) *
+                             in2(i,j,k));
+      }
+    }
+  }
+  printf("c=a*b Test Passed\n");
+
+  /// c=a+b
+  gpu_out.device(sycl_device) = gpu_in1 + gpu_in2;
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k),
+                         in1(i,j,k) +
+                             in2(i,j,k));
+      }
+    }
+  }
+  printf("c=a+b Test Passed\n");
+
+  /// c=a*a
+  gpu_out.device(sycl_device) = gpu_in1 * gpu_in1;
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k),
+                         in1(i,j,k) *
+                             in1(i,j,k));
+      }
+    }
+  }
+  printf("c= a*a Test Passed\n");
+
+  //a*3.14f + b*2.7f
+  gpu_out.device(sycl_device) =  gpu_in1 * gpu_in1.constant(3.14f) + gpu_in2 * gpu_in2.constant(2.7f);
+  sycl_device.memcpyDeviceToHost(out.data(),gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k),
+                         in1(i,j,k) * 3.14f
+                       + in2(i,j,k) * 2.7f);
+      }
+    }
+  }
+  printf("a*3.14f + b*2.7f Test Passed\n");
+
+  ///d= (a>0.5? b:c)
+  sycl_device.memcpyHostToDevice(gpu_in3_data, in3.data(),(in3.dimensions().TotalSize())*sizeof(float));
+  gpu_out.device(sycl_device) =(gpu_in1 > gpu_in1.constant(0.5f)).select(gpu_in2, gpu_in3);
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
+  for (int i = 0; i < sizeDim1; ++i) {
+    for (int j = 0; j < sizeDim2; ++j) {
+      for (int k = 0; k < sizeDim3; ++k) {
+        VERIFY_IS_APPROX(out(i, j, k), (in1(i, j, k) > 0.5f)
+                                                ? in2(i, j, k)
+                                                : in3(i, j, k));
+      }
+    }
+  }
+  printf("d= (a>0.5? b:c) Test Passed\n");
+  sycl_device.deallocate(gpu_in1_data);
+  sycl_device.deallocate(gpu_in2_data);
+  sycl_device.deallocate(gpu_in3_data);
+  sycl_device.deallocate(gpu_out_data);
+}
+void test_cxx11_tensor_sycl() {
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_sycl_cpu(sycl_device));
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_symmetry.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_symmetry.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_symmetry.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_symmetry.cpp
@@ -0,0 +1,818 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+#include <Eigen/CXX11/TensorSymmetry>
+
+#include <map>
+#include <set>
+
+using Eigen::Tensor;
+using Eigen::SGroup;
+using Eigen::DynamicSGroup;
+using Eigen::StaticSGroup;
+using Eigen::Symmetry;
+using Eigen::AntiSymmetry;
+using Eigen::Hermiticity;
+using Eigen::AntiHermiticity;
+
+using Eigen::NegationFlag;
+using Eigen::ConjugationFlag;
+using Eigen::GlobalZeroFlag;
+using Eigen::GlobalRealFlag;
+using Eigen::GlobalImagFlag;
+
+// helper function to determine if the compiler intantiated a static
+// or dynamic symmetry group
+template<typename... Sym>
+bool isDynGroup(StaticSGroup<Sym...> const& dummy)
+{
+  (void)dummy;
+  return false;
+}
+
+bool isDynGroup(DynamicSGroup const& dummy)
+{
+  (void)dummy;
+  return true;
+}
+
+// helper class for checking that the symmetry groups are correct
+struct checkIdx {
+  template<typename ArrType>
+  static inline int doCheck_(ArrType e, int flags, int dummy, std::set<uint64_t>& found, std::map<uint64_t, int> const& expected)
+  {
+    // use decimal representation of value
+    uint64_t value = e[0];
+    for (std::size_t i = 1; i < e.size(); i++)
+      value = value * 10 + e[i];
+
+    // we want to make sure that we find each element
+    auto it = expected.find(value);
+    VERIFY((it != expected.end()));
+    VERIFY_IS_EQUAL(it->second, flags);
+
+    // we want to make sure we only have each element once;
+    // set::insert returns true for the second part of the pair
+    // if the element was really inserted and not already there
+    auto p = found.insert(value);
+    VERIFY((p.second));
+
+    return dummy;
+  }
+
+  static inline int run(std::vector<int> e, int flags, int dummy, std::set<uint64_t>& found, std::map<uint64_t, int> const& expected)
+  {
+    return doCheck_(e, flags, dummy, found, expected);
+  }
+
+  template<std::size_t N>
+  static inline int run(std::array<int, N> e, int flags, int dummy, std::set<uint64_t>& found, std::map<uint64_t, int> const& expected)
+  {
+    return doCheck_(e, flags, dummy, found, expected);
+  }
+};
+
+static void test_symgroups_static()
+{
+  std::array<int, 7> identity{{0,1,2,3,4,5,6}};
+
+  // Simple static symmetry group
+  StaticSGroup<
+    AntiSymmetry<0,1>,
+    Hermiticity<0,2>
+  > group;
+
+  std::set<uint64_t> found;
+  std::map<uint64_t, int> expected;
+  expected[ 123456] = 0;
+  expected[1023456] = NegationFlag;
+  expected[2103456] = ConjugationFlag;
+  expected[1203456] = ConjugationFlag | NegationFlag;
+  expected[2013456] = ConjugationFlag | NegationFlag;
+  expected[ 213456] = ConjugationFlag;
+
+  VERIFY_IS_EQUAL(group.size(), 6u);
+  VERIFY_IS_EQUAL(group.globalFlags(), GlobalImagFlag);
+  group.apply<checkIdx, int>(identity, 0, found, expected);
+  VERIFY_IS_EQUAL(found.size(), 6u);
+}
+
+static void test_symgroups_dynamic()
+{
+  std::vector<int> identity;
+  for (int i = 0; i <= 6; i++)
+    identity.push_back(i);
+
+  // Simple dynamic symmetry group
+  DynamicSGroup group;
+  group.add(0,1,NegationFlag);
+  group.add(0,2,ConjugationFlag);
+
+  VERIFY_IS_EQUAL(group.size(), 6u);
+  VERIFY_IS_EQUAL(group.globalFlags(), GlobalImagFlag);
+
+  std::set<uint64_t> found;
+  std::map<uint64_t, int> expected;
+  expected[ 123456] = 0;
+  expected[1023456] = NegationFlag;
+  expected[2103456] = ConjugationFlag;
+  expected[1203456] = ConjugationFlag | NegationFlag;
+  expected[2013456] = ConjugationFlag | NegationFlag;
+  expected[ 213456] = ConjugationFlag;
+
+  VERIFY_IS_EQUAL(group.size(), 6u);
+  VERIFY_IS_EQUAL(group.globalFlags(), GlobalImagFlag);
+  group.apply<checkIdx, int>(identity, 0, found, expected);
+  VERIFY_IS_EQUAL(found.size(), 6u);
+}
+
+static void test_symgroups_selection()
+{
+  std::array<int, 7> identity7{{0,1,2,3,4,5,6}};
+  std::array<int, 10> identity10{{0,1,2,3,4,5,6,7,8,9}};
+
+  {
+    // Do the same test as in test_symgroups_static but
+    // require selection via SGroup
+    SGroup<
+      AntiSymmetry<0,1>,
+      Hermiticity<0,2>
+    > group;
+
+    std::set<uint64_t> found;
+    std::map<uint64_t, int> expected;
+    expected[ 123456] = 0;
+    expected[1023456] = NegationFlag;
+    expected[2103456] = ConjugationFlag;
+    expected[1203456] = ConjugationFlag | NegationFlag;
+    expected[2013456] = ConjugationFlag | NegationFlag;
+    expected[ 213456] = ConjugationFlag;
+
+    VERIFY(!isDynGroup(group));
+    VERIFY_IS_EQUAL(group.size(), 6u);
+    VERIFY_IS_EQUAL(group.globalFlags(), GlobalImagFlag);
+    group.apply<checkIdx, int>(identity7, 0, found, expected);
+    VERIFY_IS_EQUAL(found.size(), 6u);
+  }
+
+  {
+    // simple factorizing group: 5 generators, 2^5 = 32 elements
+    // selection should make this dynamic, although static group
+    // can still be reasonably generated
+    SGroup<
+      Symmetry<0,1>,
+      Symmetry<2,3>,
+      Symmetry<4,5>,
+      Symmetry<6,7>,
+      Symmetry<8,9>
+    > group;
+
+    std::set<uint64_t> found;
+    std::map<uint64_t, int> expected;
+    expected[ 123456789] = 0; expected[ 123456798] = 0; expected[ 123457689] = 0; expected[ 123457698] = 0;
+    expected[ 123546789] = 0; expected[ 123546798] = 0; expected[ 123547689] = 0; expected[ 123547698] = 0;
+    expected[ 132456789] = 0; expected[ 132456798] = 0; expected[ 132457689] = 0; expected[ 132457698] = 0;
+    expected[ 132546789] = 0; expected[ 132546798] = 0; expected[ 132547689] = 0; expected[ 132547698] = 0;
+    expected[1023456789] = 0; expected[1023456798] = 0; expected[1023457689] = 0; expected[1023457698] = 0;
+    expected[1023546789] = 0; expected[1023546798] = 0; expected[1023547689] = 0; expected[1023547698] = 0;
+    expected[1032456789] = 0; expected[1032456798] = 0; expected[1032457689] = 0; expected[1032457698] = 0;
+    expected[1032546789] = 0; expected[1032546798] = 0; expected[1032547689] = 0; expected[1032547698] = 0;
+
+    VERIFY(isDynGroup(group));
+    VERIFY_IS_EQUAL(group.size(), 32u);
+    VERIFY_IS_EQUAL(group.globalFlags(), 0);
+    group.apply<checkIdx, int>(identity10, 0, found, expected);
+    VERIFY_IS_EQUAL(found.size(), 32u);
+
+    // no verify that we could also generate a static group
+    // with these generators
+    found.clear();
+    StaticSGroup<
+      Symmetry<0,1>,
+      Symmetry<2,3>,
+      Symmetry<4,5>,
+      Symmetry<6,7>,
+      Symmetry<8,9>
+    > group_static;
+    VERIFY_IS_EQUAL(group_static.size(), 32u);
+    VERIFY_IS_EQUAL(group_static.globalFlags(), 0);
+    group_static.apply<checkIdx, int>(identity10, 0, found, expected);
+    VERIFY_IS_EQUAL(found.size(), 32u);
+  }
+
+  {
+    // try to create a HUGE group
+    SGroup<
+      Symmetry<0,1>,
+      Symmetry<1,2>,
+      Symmetry<2,3>,
+      Symmetry<3,4>,
+      Symmetry<4,5>,
+      Symmetry<5,6>
+    > group;
+
+    std::set<uint64_t> found;
+    uint64_t pre_expected[5040] = {
+       123456, 1023456,  213456, 2013456, 1203456, 2103456,  132456, 1032456,  312456, 3012456, 1302456, 3102456,
+       231456, 2031456,  321456, 3021456, 2301456, 3201456, 1230456, 2130456, 1320456, 3120456, 2310456, 3210456,
+       124356, 1024356,  214356, 2014356, 1204356, 2104356,  142356, 1042356,  412356, 4012356, 1402356, 4102356,
+       241356, 2041356,  421356, 4021356, 2401356, 4201356, 1240356, 2140356, 1420356, 4120356, 2410356, 4210356,
+       134256, 1034256,  314256, 3014256, 1304256, 3104256,  143256, 1043256,  413256, 4013256, 1403256, 4103256,
+       341256, 3041256,  431256, 4031256, 3401256, 4301256, 1340256, 3140256, 1430256, 4130256, 3410256, 4310256,
+       234156, 2034156,  324156, 3024156, 2304156, 3204156,  243156, 2043156,  423156, 4023156, 2403156, 4203156,
+       342156, 3042156,  432156, 4032156, 3402156, 4302156, 2340156, 3240156, 2430156, 4230156, 3420156, 4320156,
+      1234056, 2134056, 1324056, 3124056, 2314056, 3214056, 1243056, 2143056, 1423056, 4123056, 2413056, 4213056,
+      1342056, 3142056, 1432056, 4132056, 3412056, 4312056, 2341056, 3241056, 2431056, 4231056, 3421056, 4321056,
+       123546, 1023546,  213546, 2013546, 1203546, 2103546,  132546, 1032546,  312546, 3012546, 1302546, 3102546,
+       231546, 2031546,  321546, 3021546, 2301546, 3201546, 1230546, 2130546, 1320546, 3120546, 2310546, 3210546,
+       125346, 1025346,  215346, 2015346, 1205346, 2105346,  152346, 1052346,  512346, 5012346, 1502346, 5102346,
+       251346, 2051346,  521346, 5021346, 2501346, 5201346, 1250346, 2150346, 1520346, 5120346, 2510346, 5210346,
+       135246, 1035246,  315246, 3015246, 1305246, 3105246,  153246, 1053246,  513246, 5013246, 1503246, 5103246,
+       351246, 3051246,  531246, 5031246, 3501246, 5301246, 1350246, 3150246, 1530246, 5130246, 3510246, 5310246,
+       235146, 2035146,  325146, 3025146, 2305146, 3205146,  253146, 2053146,  523146, 5023146, 2503146, 5203146,
+       352146, 3052146,  532146, 5032146, 3502146, 5302146, 2350146, 3250146, 2530146, 5230146, 3520146, 5320146,
+      1235046, 2135046, 1325046, 3125046, 2315046, 3215046, 1253046, 2153046, 1523046, 5123046, 2513046, 5213046,
+      1352046, 3152046, 1532046, 5132046, 3512046, 5312046, 2351046, 3251046, 2531046, 5231046, 3521046, 5321046,
+       124536, 1024536,  214536, 2014536, 1204536, 2104536,  142536, 1042536,  412536, 4012536, 1402536, 4102536,
+       241536, 2041536,  421536, 4021536, 2401536, 4201536, 1240536, 2140536, 1420536, 4120536, 2410536, 4210536,
+       125436, 1025436,  215436, 2015436, 1205436, 2105436,  152436, 1052436,  512436, 5012436, 1502436, 5102436,
+       251436, 2051436,  521436, 5021436, 2501436, 5201436, 1250436, 2150436, 1520436, 5120436, 2510436, 5210436,
+       145236, 1045236,  415236, 4015236, 1405236, 4105236,  154236, 1054236,  514236, 5014236, 1504236, 5104236,
+       451236, 4051236,  541236, 5041236, 4501236, 5401236, 1450236, 4150236, 1540236, 5140236, 4510236, 5410236,
+       245136, 2045136,  425136, 4025136, 2405136, 4205136,  254136, 2054136,  524136, 5024136, 2504136, 5204136,
+       452136, 4052136,  542136, 5042136, 4502136, 5402136, 2450136, 4250136, 2540136, 5240136, 4520136, 5420136,
+      1245036, 2145036, 1425036, 4125036, 2415036, 4215036, 1254036, 2154036, 1524036, 5124036, 2514036, 5214036,
+      1452036, 4152036, 1542036, 5142036, 4512036, 5412036, 2451036, 4251036, 2541036, 5241036, 4521036, 5421036,
+       134526, 1034526,  314526, 3014526, 1304526, 3104526,  143526, 1043526,  413526, 4013526, 1403526, 4103526,
+       341526, 3041526,  431526, 4031526, 3401526, 4301526, 1340526, 3140526, 1430526, 4130526, 3410526, 4310526,
+       135426, 1035426,  315426, 3015426, 1305426, 3105426,  153426, 1053426,  513426, 5013426, 1503426, 5103426,
+       351426, 3051426,  531426, 5031426, 3501426, 5301426, 1350426, 3150426, 1530426, 5130426, 3510426, 5310426,
+       145326, 1045326,  415326, 4015326, 1405326, 4105326,  154326, 1054326,  514326, 5014326, 1504326, 5104326,
+       451326, 4051326,  541326, 5041326, 4501326, 5401326, 1450326, 4150326, 1540326, 5140326, 4510326, 5410326,
+       345126, 3045126,  435126, 4035126, 3405126, 4305126,  354126, 3054126,  534126, 5034126, 3504126, 5304126,
+       453126, 4053126,  543126, 5043126, 4503126, 5403126, 3450126, 4350126, 3540126, 5340126, 4530126, 5430126,
+      1345026, 3145026, 1435026, 4135026, 3415026, 4315026, 1354026, 3154026, 1534026, 5134026, 3514026, 5314026,
+      1453026, 4153026, 1543026, 5143026, 4513026, 5413026, 3451026, 4351026, 3541026, 5341026, 4531026, 5431026,
+       234516, 2034516,  324516, 3024516, 2304516, 3204516,  243516, 2043516,  423516, 4023516, 2403516, 4203516,
+       342516, 3042516,  432516, 4032516, 3402516, 4302516, 2340516, 3240516, 2430516, 4230516, 3420516, 4320516,
+       235416, 2035416,  325416, 3025416, 2305416, 3205416,  253416, 2053416,  523416, 5023416, 2503416, 5203416,
+       352416, 3052416,  532416, 5032416, 3502416, 5302416, 2350416, 3250416, 2530416, 5230416, 3520416, 5320416,
+       245316, 2045316,  425316, 4025316, 2405316, 4205316,  254316, 2054316,  524316, 5024316, 2504316, 5204316,
+       452316, 4052316,  542316, 5042316, 4502316, 5402316, 2450316, 4250316, 2540316, 5240316, 4520316, 5420316,
+       345216, 3045216,  435216, 4035216, 3405216, 4305216,  354216, 3054216,  534216, 5034216, 3504216, 5304216,
+       453216, 4053216,  543216, 5043216, 4503216, 5403216, 3450216, 4350216, 3540216, 5340216, 4530216, 5430216,
+      2345016, 3245016, 2435016, 4235016, 3425016, 4325016, 2354016, 3254016, 2534016, 5234016, 3524016, 5324016,
+      2453016, 4253016, 2543016, 5243016, 4523016, 5423016, 3452016, 4352016, 3542016, 5342016, 4532016, 5432016,
+      1234506, 2134506, 1324506, 3124506, 2314506, 3214506, 1243506, 2143506, 1423506, 4123506, 2413506, 4213506,
+      1342506, 3142506, 1432506, 4132506, 3412506, 4312506, 2341506, 3241506, 2431506, 4231506, 3421506, 4321506,
+      1235406, 2135406, 1325406, 3125406, 2315406, 3215406, 1253406, 2153406, 1523406, 5123406, 2513406, 5213406,
+      1352406, 3152406, 1532406, 5132406, 3512406, 5312406, 2351406, 3251406, 2531406, 5231406, 3521406, 5321406,
+      1245306, 2145306, 1425306, 4125306, 2415306, 4215306, 1254306, 2154306, 1524306, 5124306, 2514306, 5214306,
+      1452306, 4152306, 1542306, 5142306, 4512306, 5412306, 2451306, 4251306, 2541306, 5241306, 4521306, 5421306,
+      1345206, 3145206, 1435206, 4135206, 3415206, 4315206, 1354206, 3154206, 1534206, 5134206, 3514206, 5314206,
+      1453206, 4153206, 1543206, 5143206, 4513206, 5413206, 3451206, 4351206, 3541206, 5341206, 4531206, 5431206,
+      2345106, 3245106, 2435106, 4235106, 3425106, 4325106, 2354106, 3254106, 2534106, 5234106, 3524106, 5324106,
+      2453106, 4253106, 2543106, 5243106, 4523106, 5423106, 3452106, 4352106, 3542106, 5342106, 4532106, 5432106,
+       123465, 1023465,  213465, 2013465, 1203465, 2103465,  132465, 1032465,  312465, 3012465, 1302465, 3102465,
+       231465, 2031465,  321465, 3021465, 2301465, 3201465, 1230465, 2130465, 1320465, 3120465, 2310465, 3210465,
+       124365, 1024365,  214365, 2014365, 1204365, 2104365,  142365, 1042365,  412365, 4012365, 1402365, 4102365,
+       241365, 2041365,  421365, 4021365, 2401365, 4201365, 1240365, 2140365, 1420365, 4120365, 2410365, 4210365,
+       134265, 1034265,  314265, 3014265, 1304265, 3104265,  143265, 1043265,  413265, 4013265, 1403265, 4103265,
+       341265, 3041265,  431265, 4031265, 3401265, 4301265, 1340265, 3140265, 1430265, 4130265, 3410265, 4310265,
+       234165, 2034165,  324165, 3024165, 2304165, 3204165,  243165, 2043165,  423165, 4023165, 2403165, 4203165,
+       342165, 3042165,  432165, 4032165, 3402165, 4302165, 2340165, 3240165, 2430165, 4230165, 3420165, 4320165,
+      1234065, 2134065, 1324065, 3124065, 2314065, 3214065, 1243065, 2143065, 1423065, 4123065, 2413065, 4213065,
+      1342065, 3142065, 1432065, 4132065, 3412065, 4312065, 2341065, 3241065, 2431065, 4231065, 3421065, 4321065,
+       123645, 1023645,  213645, 2013645, 1203645, 2103645,  132645, 1032645,  312645, 3012645, 1302645, 3102645,
+       231645, 2031645,  321645, 3021645, 2301645, 3201645, 1230645, 2130645, 1320645, 3120645, 2310645, 3210645,
+       126345, 1026345,  216345, 2016345, 1206345, 2106345,  162345, 1062345,  612345, 6012345, 1602345, 6102345,
+       261345, 2061345,  621345, 6021345, 2601345, 6201345, 1260345, 2160345, 1620345, 6120345, 2610345, 6210345,
+       136245, 1036245,  316245, 3016245, 1306245, 3106245,  163245, 1063245,  613245, 6013245, 1603245, 6103245,
+       361245, 3061245,  631245, 6031245, 3601245, 6301245, 1360245, 3160245, 1630245, 6130245, 3610245, 6310245,
+       236145, 2036145,  326145, 3026145, 2306145, 3206145,  263145, 2063145,  623145, 6023145, 2603145, 6203145,
+       362145, 3062145,  632145, 6032145, 3602145, 6302145, 2360145, 3260145, 2630145, 6230145, 3620145, 6320145,
+      1236045, 2136045, 1326045, 3126045, 2316045, 3216045, 1263045, 2163045, 1623045, 6123045, 2613045, 6213045,
+      1362045, 3162045, 1632045, 6132045, 3612045, 6312045, 2361045, 3261045, 2631045, 6231045, 3621045, 6321045,
+       124635, 1024635,  214635, 2014635, 1204635, 2104635,  142635, 1042635,  412635, 4012635, 1402635, 4102635,
+       241635, 2041635,  421635, 4021635, 2401635, 4201635, 1240635, 2140635, 1420635, 4120635, 2410635, 4210635,
+       126435, 1026435,  216435, 2016435, 1206435, 2106435,  162435, 1062435,  612435, 6012435, 1602435, 6102435,
+       261435, 2061435,  621435, 6021435, 2601435, 6201435, 1260435, 2160435, 1620435, 6120435, 2610435, 6210435,
+       146235, 1046235,  416235, 4016235, 1406235, 4106235,  164235, 1064235,  614235, 6014235, 1604235, 6104235,
+       461235, 4061235,  641235, 6041235, 4601235, 6401235, 1460235, 4160235, 1640235, 6140235, 4610235, 6410235,
+       246135, 2046135,  426135, 4026135, 2406135, 4206135,  264135, 2064135,  624135, 6024135, 2604135, 6204135,
+       462135, 4062135,  642135, 6042135, 4602135, 6402135, 2460135, 4260135, 2640135, 6240135, 4620135, 6420135,
+      1246035, 2146035, 1426035, 4126035, 2416035, 4216035, 1264035, 2164035, 1624035, 6124035, 2614035, 6214035,
+      1462035, 4162035, 1642035, 6142035, 4612035, 6412035, 2461035, 4261035, 2641035, 6241035, 4621035, 6421035,
+       134625, 1034625,  314625, 3014625, 1304625, 3104625,  143625, 1043625,  413625, 4013625, 1403625, 4103625,
+       341625, 3041625,  431625, 4031625, 3401625, 4301625, 1340625, 3140625, 1430625, 4130625, 3410625, 4310625,
+       136425, 1036425,  316425, 3016425, 1306425, 3106425,  163425, 1063425,  613425, 6013425, 1603425, 6103425,
+       361425, 3061425,  631425, 6031425, 3601425, 6301425, 1360425, 3160425, 1630425, 6130425, 3610425, 6310425,
+       146325, 1046325,  416325, 4016325, 1406325, 4106325,  164325, 1064325,  614325, 6014325, 1604325, 6104325,
+       461325, 4061325,  641325, 6041325, 4601325, 6401325, 1460325, 4160325, 1640325, 6140325, 4610325, 6410325,
+       346125, 3046125,  436125, 4036125, 3406125, 4306125,  364125, 3064125,  634125, 6034125, 3604125, 6304125,
+       463125, 4063125,  643125, 6043125, 4603125, 6403125, 3460125, 4360125, 3640125, 6340125, 4630125, 6430125,
+      1346025, 3146025, 1436025, 4136025, 3416025, 4316025, 1364025, 3164025, 1634025, 6134025, 3614025, 6314025,
+      1463025, 4163025, 1643025, 6143025, 4613025, 6413025, 3461025, 4361025, 3641025, 6341025, 4631025, 6431025,
+       234615, 2034615,  324615, 3024615, 2304615, 3204615,  243615, 2043615,  423615, 4023615, 2403615, 4203615,
+       342615, 3042615,  432615, 4032615, 3402615, 4302615, 2340615, 3240615, 2430615, 4230615, 3420615, 4320615,
+       236415, 2036415,  326415, 3026415, 2306415, 3206415,  263415, 2063415,  623415, 6023415, 2603415, 6203415,
+       362415, 3062415,  632415, 6032415, 3602415, 6302415, 2360415, 3260415, 2630415, 6230415, 3620415, 6320415,
+       246315, 2046315,  426315, 4026315, 2406315, 4206315,  264315, 2064315,  624315, 6024315, 2604315, 6204315,
+       462315, 4062315,  642315, 6042315, 4602315, 6402315, 2460315, 4260315, 2640315, 6240315, 4620315, 6420315,
+       346215, 3046215,  436215, 4036215, 3406215, 4306215,  364215, 3064215,  634215, 6034215, 3604215, 6304215,
+       463215, 4063215,  643215, 6043215, 4603215, 6403215, 3460215, 4360215, 3640215, 6340215, 4630215, 6430215,
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+      2463510, 4263510, 2643510, 6243510, 4623510, 6423510, 3462510, 4362510, 3642510, 6342510, 4632510, 6432510,
+      2356410, 3256410, 2536410, 5236410, 3526410, 5326410, 2365410, 3265410, 2635410, 6235410, 3625410, 6325410,
+      2563410, 5263410, 2653410, 6253410, 5623410, 6523410, 3562410, 5362410, 3652410, 6352410, 5632410, 6532410,
+      2456310, 4256310, 2546310, 5246310, 4526310, 5426310, 2465310, 4265310, 2645310, 6245310, 4625310, 6425310,
+      2564310, 5264310, 2654310, 6254310, 5624310, 6524310, 4562310, 5462310, 4652310, 6452310, 5642310, 6542310,
+      3456210, 4356210, 3546210, 5346210, 4536210, 5436210, 3465210, 4365210, 3645210, 6345210, 4635210, 6435210,
+      3564210, 5364210, 3654210, 6354210, 5634210, 6534210, 4563210, 5463210, 4653210, 6453210, 5643210, 6543210
+    };
+    std::map<uint64_t, int> expected;
+    for (std::size_t i = 0; i < 5040; i++)
+      expected[pre_expected[i]] = 0; // flags are 0, everything is symmetric here
+
+    VERIFY(isDynGroup(group));
+    VERIFY_IS_EQUAL(group.size(), 5040u);
+    VERIFY_IS_EQUAL(group.globalFlags(), 0);
+    group.apply<checkIdx, int>(identity7, 0, found, expected);
+    VERIFY_IS_EQUAL(found.size(), 5040u);
+  }
+}
+
+static void test_tensor_epsilon()
+{
+  SGroup<AntiSymmetry<0,1>, AntiSymmetry<1,2>> sym;
+  Tensor<int, 3> epsilon(3,3,3);
+
+  epsilon.setZero();
+  sym(epsilon, 0, 1, 2) = 1;
+
+  for (int i = 0; i < 3; i++) {
+    for (int j = 0; j < 3; j++) {
+      for (int k = 0; k < 3; k++) {
+        VERIFY_IS_EQUAL((epsilon(i,j,k)), (- (j - i) * (k - j) * (i - k) / 2) );
+      }
+    }
+  }
+}
+
+static void test_tensor_sym()
+{
+  SGroup<Symmetry<0,1>, Symmetry<2,3>> sym;
+  Tensor<int, 4> t(10,10,10,10);
+
+  t.setZero();
+
+  for (int l = 0; l < 10; l++) {
+    for (int k = l; k < 10; k++) {
+      for (int j = 0; j < 10; j++) {
+        for (int i = j; i < 10; i++) {
+          sym(t, i, j, k, l) = (i + j) * (k + l);
+        }
+      }
+    }
+  }
+
+  for (int l = 0; l < 10; l++) {
+    for (int k = 0; k < 10; k++) {
+      for (int j = 0; j < 10; j++) {
+        for (int i = 0; i < 10; i++) {
+          VERIFY_IS_EQUAL((t(i, j, k, l)), ((i + j) * (k + l)));
+        }
+      }
+    }
+  }
+
+}
+
+static void test_tensor_asym()
+{
+  SGroup<AntiSymmetry<0,1>, AntiSymmetry<2,3>> sym;
+  Tensor<int, 4> t(10,10,10,10);
+
+  t.setZero();
+
+  for (int l = 0; l < 10; l++) {
+    for (int k = l + 1; k < 10; k++) {
+      for (int j = 0; j < 10; j++) {
+        for (int i = j + 1; i < 10; i++) {
+          sym(t, i, j, k, l) = ((i * j) + (k * l));
+        }
+      }
+    }
+  }
+
+  for (int l = 0; l < 10; l++) {
+    for (int k = 0; k < 10; k++) {
+      for (int j = 0; j < 10; j++) {
+        for (int i = 0; i < 10; i++) {
+          if (i < j && k < l)
+            VERIFY_IS_EQUAL((t(i, j, k, l)), (((i * j) + (k * l))));
+          else if (i > j && k > l)
+            VERIFY_IS_EQUAL((t(i, j, k, l)), (((i * j) + (k * l))));
+          else if (i < j && k > l)
+            VERIFY_IS_EQUAL((t(i, j, k, l)), (- ((i * j) + (k * l))));
+          else if (i > j && k < l)
+            VERIFY_IS_EQUAL((t(i, j, k, l)), (- ((i * j) + (k * l))));
+          else
+            VERIFY_IS_EQUAL((t(i, j, k, l)), 0);
+        }
+      }
+    }
+  }
+}
+
+static void test_tensor_dynsym()
+{
+  DynamicSGroup sym;
+  sym.addSymmetry(0,1);
+  sym.addSymmetry(2,3);
+  Tensor<int, 4> t(10,10,10,10);
+
+  t.setZero();
+
+  for (int l = 0; l < 10; l++) {
+    for (int k = l; k < 10; k++) {
+      for (int j = 0; j < 10; j++) {
+        for (int i = j; i < 10; i++) {
+          sym(t, i, j, k, l) = (i + j) * (k + l);
+        }
+      }
+    }
+  }
+
+  for (int l = 0; l < 10; l++) {
+    for (int k = 0; k < 10; k++) {
+      for (int j = 0; j < 10; j++) {
+        for (int i = 0; i < 10; i++) {
+          VERIFY_IS_EQUAL((t(i, j, k, l)), ((i + j) * (k + l)));
+        }
+      }
+    }
+  }
+}
+
+static void test_tensor_randacc()
+{
+  SGroup<Symmetry<0,1>, Symmetry<2,3>> sym;
+  Tensor<int, 4> t(10,10,10,10);
+
+  t.setZero();
+
+  // set elements 1 million times, that way we access the
+  // entire matrix
+  for (int n = 0; n < 1000000; n++) {
+    int i = rand() % 10;
+    int j = rand() % 10;
+    int k = rand() % 10;
+    int l = rand() % 10;
+    // only access those indices in a given order
+    if (i < j)
+      std::swap(i, j);
+    if (k < l)
+      std::swap(k, l);
+    sym(t, i, j, k, l) = (i + j) * (k + l);
+  }
+
+  for (int l = 0; l < 10; l++) {
+    for (int k = 0; k < 10; k++) {
+      for (int j = 0; j < 10; j++) {
+        for (int i = 0; i < 10; i++) {
+          VERIFY_IS_EQUAL((t(i, j, k, l)), ((i + j) * (k + l)));
+        }
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_symmetry()
+{
+  CALL_SUBTEST(test_symgroups_static());
+  CALL_SUBTEST(test_symgroups_dynamic());
+  CALL_SUBTEST(test_symgroups_selection());
+  CALL_SUBTEST(test_tensor_epsilon());
+  CALL_SUBTEST(test_tensor_sym());
+  CALL_SUBTEST(test_tensor_asym());
+  CALL_SUBTEST(test_tensor_dynsym());
+  CALL_SUBTEST(test_tensor_randacc());
+}
+
+/*
+ * kate: space-indent on; indent-width 2; mixedindent off; indent-mode cstyle;
+ */

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_thread_pool.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_thread_pool.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_thread_pool.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_thread_pool.cpp
@@ -0,0 +1,373 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#define EIGEN_USE_THREADS
+
+
+#include "main.h"
+#include <iostream>
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+
+void test_multithread_elementwise()
+{
+  Tensor<float, 3> in1(2,3,7);
+  Tensor<float, 3> in2(2,3,7);
+  Tensor<float, 3> out(2,3,7);
+
+  in1.setRandom();
+  in2.setRandom();
+
+  Eigen::ThreadPool tp(internal::random<int>(3, 11));
+  Eigen::ThreadPoolDevice thread_pool_device(&tp, internal::random<int>(3, 11));
+  out.device(thread_pool_device) = in1 + in2 * 3.14f;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), in1(i,j,k) + in2(i,j,k) * 3.14f);
+      }
+    }
+  }
+}
+
+
+void test_multithread_compound_assignment()
+{
+  Tensor<float, 3> in1(2,3,7);
+  Tensor<float, 3> in2(2,3,7);
+  Tensor<float, 3> out(2,3,7);
+
+  in1.setRandom();
+  in2.setRandom();
+
+  Eigen::ThreadPool tp(internal::random<int>(3, 11));
+  Eigen::ThreadPoolDevice thread_pool_device(&tp, internal::random<int>(3, 11));
+  out.device(thread_pool_device) = in1;
+  out.device(thread_pool_device) += in2 * 3.14f;
+
+  for (int i = 0; i < 2; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        VERIFY_IS_APPROX(out(i,j,k), in1(i,j,k) + in2(i,j,k) * 3.14f);
+      }
+    }
+  }
+}
+
+template<int DataLayout>
+void test_multithread_contraction()
+{
+  Tensor<float, 4, DataLayout> t_left(30, 50, 37, 31);
+  Tensor<float, 5, DataLayout> t_right(37, 31, 70, 2, 10);
+  Tensor<float, 5, DataLayout> t_result(30, 50, 70, 2, 10);
+
+  t_left.setRandom();
+  t_right.setRandom();
+
+  // this contraction should be equivalent to a single matrix multiplication
+  typedef Tensor<float, 1>::DimensionPair DimPair;
+  Eigen::array<DimPair, 2> dims({{DimPair(2, 0), DimPair(3, 1)}});
+
+  typedef Map<Matrix<float, Dynamic, Dynamic, DataLayout>> MapXf;
+  MapXf m_left(t_left.data(), 1500, 1147);
+  MapXf m_right(t_right.data(), 1147, 1400);
+  Matrix<float, Dynamic, Dynamic, DataLayout> m_result(1500, 1400);
+
+  Eigen::ThreadPool tp(4);
+  Eigen::ThreadPoolDevice thread_pool_device(&tp, 4);
+
+  // compute results by separate methods
+  t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
+  m_result = m_left * m_right;
+
+ for (ptrdiff_t i = 0; i < t_result.size(); i++) {
+    VERIFY(&t_result.data()[i] != &m_result.data()[i]);
+    if (fabsf(t_result(i) - m_result(i)) < 1e-4f) {
+      continue;
+    }
+    if (Eigen::internal::isApprox(t_result(i), m_result(i), 1e-4f)) {
+      continue;
+    }
+    std::cout << "mismatch detected at index " << i << ": " << t_result(i)
+              << " vs " <<  m_result(i) << std::endl;
+    assert(false);
+  }
+}
+
+template<int DataLayout>
+void test_contraction_corner_cases()
+{
+  Tensor<float, 2, DataLayout> t_left(32, 500);
+  Tensor<float, 2, DataLayout> t_right(32, 28*28);
+  Tensor<float, 2, DataLayout> t_result(500, 28*28);
+
+  t_left = (t_left.constant(-0.5f) + t_left.random()) * 2.0f;
+  t_right = (t_right.constant(-0.6f) + t_right.random()) * 2.0f;
+  t_result = t_result.constant(NAN);
+
+  // this contraction should be equivalent to a single matrix multiplication
+  typedef Tensor<float, 1>::DimensionPair DimPair;
+  Eigen::array<DimPair, 1> dims{{DimPair(0, 0)}};
+
+  typedef Map<Matrix<float, Dynamic, Dynamic, DataLayout>> MapXf;
+  MapXf m_left(t_left.data(), 32, 500);
+  MapXf m_right(t_right.data(), 32, 28*28);
+  Matrix<float, Dynamic, Dynamic, DataLayout> m_result(500, 28*28);
+
+  Eigen::ThreadPool tp(12);
+  Eigen::ThreadPoolDevice thread_pool_device(&tp, 12);
+
+  // compute results by separate methods
+  t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
+  m_result = m_left.transpose() * m_right;
+
+  for (ptrdiff_t i = 0; i < t_result.size(); i++) {
+    assert(!(numext::isnan)(t_result.data()[i]));
+    if (fabsf(t_result.data()[i] - m_result.data()[i]) >= 1e-4f) {
+      std::cout << "mismatch detected at index " << i << " : " << t_result.data()[i] << " vs " <<  m_result.data()[i] << std::endl;
+      assert(false);
+    }
+  }
+
+  t_left.resize(32, 1);
+  t_left = (t_left.constant(-0.5f) + t_left.random()) * 2.0f;
+  t_result.resize (1, 28*28);
+  t_result = t_result.constant(NAN);
+  t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
+  new(&m_left) MapXf(t_left.data(), 32, 1);
+  m_result = m_left.transpose() * m_right;
+  for (ptrdiff_t i = 0; i < t_result.size(); i++) {
+    assert(!(numext::isnan)(t_result.data()[i]));
+    if (fabsf(t_result.data()[i] - m_result.data()[i]) >= 1e-4f) {
+      std::cout << "mismatch detected: " << t_result.data()[i] << " vs " <<  m_result.data()[i] << std::endl;
+      assert(false);
+    }
+  }
+
+  t_left.resize(32, 500);
+  t_right.resize(32, 4);
+  t_left = (t_left.constant(-0.5f) + t_left.random()) * 2.0f;
+  t_right = (t_right.constant(-0.6f) + t_right.random()) * 2.0f;
+  t_result.resize (500, 4);
+  t_result = t_result.constant(NAN);
+  t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
+  new(&m_left) MapXf(t_left.data(), 32, 500);
+  new(&m_right) MapXf(t_right.data(), 32, 4);
+  m_result = m_left.transpose() * m_right;
+  for (ptrdiff_t i = 0; i < t_result.size(); i++) {
+    assert(!(numext::isnan)(t_result.data()[i]));
+    if (fabsf(t_result.data()[i] - m_result.data()[i]) >= 1e-4f) {
+      std::cout << "mismatch detected: " << t_result.data()[i] << " vs " <<  m_result.data()[i] << std::endl;
+      assert(false);
+    }
+  }
+
+  t_left.resize(32, 1);
+  t_right.resize(32, 4);
+  t_left = (t_left.constant(-0.5f) + t_left.random()) * 2.0f;
+  t_right = (t_right.constant(-0.6f) + t_right.random()) * 2.0f;
+  t_result.resize (1, 4);
+  t_result = t_result.constant(NAN);
+  t_result.device(thread_pool_device) = t_left.contract(t_right, dims);
+  new(&m_left) MapXf(t_left.data(), 32, 1);
+  new(&m_right) MapXf(t_right.data(), 32, 4);
+  m_result = m_left.transpose() * m_right;
+  for (ptrdiff_t i = 0; i < t_result.size(); i++) {
+    assert(!(numext::isnan)(t_result.data()[i]));
+    if (fabsf(t_result.data()[i] - m_result.data()[i]) >= 1e-4f) {
+      std::cout << "mismatch detected: " << t_result.data()[i] << " vs " <<  m_result.data()[i] << std::endl;
+      assert(false);
+    }
+  }
+}
+
+template<int DataLayout>
+void test_multithread_contraction_agrees_with_singlethread() {
+  int contract_size = internal::random<int>(1, 5000);
+
+  Tensor<float, 3, DataLayout> left(internal::random<int>(1, 80),
+                                    contract_size,
+                                    internal::random<int>(1, 100));
+
+  Tensor<float, 4, DataLayout> right(internal::random<int>(1, 25),
+                                     internal::random<int>(1, 37),
+                                     contract_size,
+                                     internal::random<int>(1, 51));
+
+  left.setRandom();
+  right.setRandom();
+
+  // add constants to shift values away from 0 for more precision
+  left += left.constant(1.5f);
+  right += right.constant(1.5f);
+
+  typedef Tensor<float, 1>::DimensionPair DimPair;
+  Eigen::array<DimPair, 1> dims({{DimPair(1, 2)}});
+
+  Eigen::ThreadPool tp(internal::random<int>(2, 11));
+  Eigen::ThreadPoolDevice thread_pool_device(&tp, internal::random<int>(2, 11));
+
+  Tensor<float, 5, DataLayout> st_result;
+  st_result = left.contract(right, dims);
+
+  Tensor<float, 5, DataLayout> tp_result(st_result.dimensions());
+  tp_result.device(thread_pool_device) = left.contract(right, dims);
+
+  VERIFY(dimensions_match(st_result.dimensions(), tp_result.dimensions()));
+  for (ptrdiff_t i = 0; i < st_result.size(); i++) {
+    // if both of the values are very small, then do nothing (because the test will fail
+    // due to numerical precision issues when values are small)
+    if (numext::abs(st_result.data()[i] - tp_result.data()[i]) >= 1e-4f) {
+      VERIFY_IS_APPROX(st_result.data()[i], tp_result.data()[i]);
+    }
+  }
+}
+
+
+template<int DataLayout>
+void test_full_contraction() {
+  int contract_size1 = internal::random<int>(1, 500);
+  int contract_size2 = internal::random<int>(1, 500);
+
+  Tensor<float, 2, DataLayout> left(contract_size1,
+                                    contract_size2);
+  Tensor<float, 2, DataLayout> right(contract_size1,
+                                    contract_size2);
+  left.setRandom();
+  right.setRandom();
+
+  // add constants to shift values away from 0 for more precision
+  left += left.constant(1.5f);
+  right += right.constant(1.5f);
+
+  typedef Tensor<float, 2>::DimensionPair DimPair;
+  Eigen::array<DimPair, 2> dims({{DimPair(0, 0), DimPair(1, 1)}});
+
+  Eigen::ThreadPool tp(internal::random<int>(2, 11));
+  Eigen::ThreadPoolDevice thread_pool_device(&tp, internal::random<int>(2, 11));
+
+  Tensor<float, 0, DataLayout> st_result;
+  st_result = left.contract(right, dims);
+
+  Tensor<float, 0, DataLayout> tp_result;
+  tp_result.device(thread_pool_device) = left.contract(right, dims);
+
+  VERIFY(dimensions_match(st_result.dimensions(), tp_result.dimensions()));
+  // if both of the values are very small, then do nothing (because the test will fail
+  // due to numerical precision issues when values are small)
+  if (numext::abs(st_result() - tp_result()) >= 1e-4f) {
+    VERIFY_IS_APPROX(st_result(), tp_result());
+  }
+}
+
+template<int DataLayout>
+void test_multithreaded_reductions() {
+  const int num_threads = internal::random<int>(3, 11);
+  ThreadPool thread_pool(num_threads);
+  Eigen::ThreadPoolDevice thread_pool_device(&thread_pool, num_threads);
+
+  const int num_rows = internal::random<int>(13, 732);
+  const int num_cols = internal::random<int>(13, 732);
+  Tensor<float, 2, DataLayout> t1(num_rows, num_cols);
+  t1.setRandom();
+
+  Tensor<float, 0, DataLayout> full_redux;
+  full_redux = t1.sum();
+
+  Tensor<float, 0, DataLayout> full_redux_tp;
+  full_redux_tp.device(thread_pool_device) = t1.sum();
+
+  // Check that the single threaded and the multi threaded reductions return
+  // the same result.
+  VERIFY_IS_APPROX(full_redux(), full_redux_tp());
+}
+
+
+void test_memcpy() {
+
+  for (int i = 0; i < 5; ++i) {
+    const int num_threads = internal::random<int>(3, 11);
+    Eigen::ThreadPool tp(num_threads);
+    Eigen::ThreadPoolDevice thread_pool_device(&tp, num_threads);
+
+    const int size = internal::random<int>(13, 7632);
+    Tensor<float, 1> t1(size);
+    t1.setRandom();
+    std::vector<float> result(size);
+    thread_pool_device.memcpy(&result[0], t1.data(), size*sizeof(float));
+    for (int j = 0; j < size; j++) {
+      VERIFY_IS_EQUAL(t1(j), result[j]);
+    }
+  }
+}
+
+
+void test_multithread_random()
+{
+  Eigen::ThreadPool tp(2);
+  Eigen::ThreadPoolDevice device(&tp, 2);
+  Tensor<float, 1> t(1 << 20);
+  t.device(device) = t.random<Eigen::internal::NormalRandomGenerator<float>>();
+}
+
+template<int DataLayout>
+void test_multithread_shuffle()
+{
+  Tensor<float, 4, DataLayout> tensor(17,5,7,11);
+  tensor.setRandom();
+
+  const int num_threads = internal::random<int>(2, 11);
+  ThreadPool threads(num_threads);
+  Eigen::ThreadPoolDevice device(&threads, num_threads);
+
+  Tensor<float, 4, DataLayout> shuffle(7,5,11,17);
+  array<ptrdiff_t, 4> shuffles = {{2,1,3,0}};
+  shuffle.device(device) = tensor.shuffle(shuffles);
+
+  for (int i = 0; i < 17; ++i) {
+    for (int j = 0; j < 5; ++j) {
+      for (int k = 0; k < 7; ++k) {
+        for (int l = 0; l < 11; ++l) {
+          VERIFY_IS_EQUAL(tensor(i,j,k,l), shuffle(k,j,l,i));
+        }
+      }
+    }
+  }
+}
+
+
+void test_cxx11_tensor_thread_pool()
+{
+  CALL_SUBTEST_1(test_multithread_elementwise());
+  CALL_SUBTEST_1(test_multithread_compound_assignment());
+
+  CALL_SUBTEST_2(test_multithread_contraction<ColMajor>());
+  CALL_SUBTEST_2(test_multithread_contraction<RowMajor>());
+
+  CALL_SUBTEST_3(test_multithread_contraction_agrees_with_singlethread<ColMajor>());
+  CALL_SUBTEST_3(test_multithread_contraction_agrees_with_singlethread<RowMajor>());
+
+  // Exercise various cases that have been problematic in the past.
+  CALL_SUBTEST_4(test_contraction_corner_cases<ColMajor>());
+  CALL_SUBTEST_4(test_contraction_corner_cases<RowMajor>());
+
+  CALL_SUBTEST_4(test_full_contraction<ColMajor>());
+  CALL_SUBTEST_4(test_full_contraction<RowMajor>());
+
+  CALL_SUBTEST_5(test_multithreaded_reductions<ColMajor>());
+  CALL_SUBTEST_5(test_multithreaded_reductions<RowMajor>());
+
+  CALL_SUBTEST_6(test_memcpy());
+  CALL_SUBTEST_6(test_multithread_random());
+  CALL_SUBTEST_6(test_multithread_shuffle<ColMajor>());
+  CALL_SUBTEST_6(test_multithread_shuffle<RowMajor>());
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_uint128.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_uint128.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_uint128.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_uint128.cpp
@@ -0,0 +1,160 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+
+#if EIGEN_COMP_MSVC
+#define EIGEN_NO_INT128
+#else
+typedef __uint128_t uint128_t;
+#endif
+
+// Only run the test on compilers that support 128bit integers natively
+#ifndef EIGEN_NO_INT128
+
+using Eigen::internal::TensorUInt128;
+using Eigen::internal::static_val;
+
+void VERIFY_EQUAL(TensorUInt128<uint64_t, uint64_t> actual, uint128_t expected) {
+  bool matchl = actual.lower() == static_cast<uint64_t>(expected);
+  bool matchh = actual.upper() == static_cast<uint64_t>(expected >> 64);
+  if (!matchl || !matchh) {
+    const char* testname = g_test_stack.back().c_str();
+    std::cerr << "Test " << testname << " failed in " << __FILE__
+              << " (" << __LINE__ << ")"
+              << std::endl;
+    abort();
+  }
+}
+
+
+void test_add() {
+  uint64_t incr = internal::random<uint64_t>(1, 9999999999);
+  for (uint64_t i1 = 0; i1 < 100; ++i1) {
+    for (uint64_t i2 = 1; i2 < 100 * incr; i2 += incr) {
+      TensorUInt128<uint64_t, uint64_t> i(i1, i2);
+      uint128_t a = (static_cast<uint128_t>(i1) << 64) + static_cast<uint128_t>(i2);
+      for (uint64_t j1 = 0; j1 < 100; ++j1) {
+        for (uint64_t j2 = 1; j2 < 100 * incr; j2 += incr) {
+          TensorUInt128<uint64_t, uint64_t> j(j1, j2);
+          uint128_t b = (static_cast<uint128_t>(j1) << 64) + static_cast<uint128_t>(j2);
+          TensorUInt128<uint64_t, uint64_t> actual = i + j;
+          uint128_t expected = a + b;
+          VERIFY_EQUAL(actual, expected);
+        }
+      }
+    }
+  }
+}
+
+void test_sub() {
+  uint64_t incr = internal::random<uint64_t>(1, 9999999999);
+  for (uint64_t i1 = 0; i1 < 100; ++i1) {
+    for (uint64_t i2 = 1; i2 < 100 * incr; i2 += incr) {
+      TensorUInt128<uint64_t, uint64_t> i(i1, i2);
+      uint128_t a = (static_cast<uint128_t>(i1) << 64) + static_cast<uint128_t>(i2);
+      for (uint64_t j1 = 0; j1 < 100; ++j1) {
+        for (uint64_t j2 = 1; j2 < 100 * incr; j2 += incr) {
+          TensorUInt128<uint64_t, uint64_t> j(j1, j2);
+          uint128_t b = (static_cast<uint128_t>(j1) << 64) + static_cast<uint128_t>(j2);
+          TensorUInt128<uint64_t, uint64_t> actual = i - j;
+          uint128_t expected = a - b;
+          VERIFY_EQUAL(actual, expected);
+        }
+      }
+    }
+  }
+}
+
+void test_mul() {
+  uint64_t incr = internal::random<uint64_t>(1, 9999999999);
+  for (uint64_t i1 = 0; i1 < 100; ++i1) {
+    for (uint64_t i2 = 1; i2 < 100 * incr; i2 += incr) {
+      TensorUInt128<uint64_t, uint64_t> i(i1, i2);
+      uint128_t a = (static_cast<uint128_t>(i1) << 64) + static_cast<uint128_t>(i2);
+      for (uint64_t j1 = 0; j1 < 100; ++j1) {
+        for (uint64_t j2 = 1; j2 < 100 * incr; j2 += incr) {
+          TensorUInt128<uint64_t, uint64_t> j(j1, j2);
+          uint128_t b = (static_cast<uint128_t>(j1) << 64) + static_cast<uint128_t>(j2);
+          TensorUInt128<uint64_t, uint64_t> actual = i * j;
+          uint128_t expected = a * b;
+          VERIFY_EQUAL(actual, expected);
+        }
+      }
+    }
+  }
+}
+
+void test_div() {
+  uint64_t incr = internal::random<uint64_t>(1, 9999999999);
+  for (uint64_t i1 = 0; i1 < 100; ++i1) {
+    for (uint64_t i2 = 1; i2 < 100 * incr; i2 += incr) {
+      TensorUInt128<uint64_t, uint64_t> i(i1, i2);
+      uint128_t a = (static_cast<uint128_t>(i1) << 64) + static_cast<uint128_t>(i2);
+      for (uint64_t j1 = 0; j1 < 100; ++j1) {
+        for (uint64_t j2 = 1; j2 < 100 * incr; j2 += incr) {
+          TensorUInt128<uint64_t, uint64_t> j(j1, j2);
+          uint128_t b = (static_cast<uint128_t>(j1) << 64) + static_cast<uint128_t>(j2);
+          TensorUInt128<uint64_t, uint64_t> actual = i / j;
+          uint128_t expected = a / b;
+          VERIFY_EQUAL(actual, expected);
+        }
+      }
+    }
+  }
+}
+
+void test_misc1() {
+  uint64_t incr = internal::random<uint64_t>(1, 9999999999);
+  for (uint64_t i2 = 1; i2 < 100 * incr; i2 += incr) {
+    TensorUInt128<static_val<0>, uint64_t> i(0, i2);
+    uint128_t a = static_cast<uint128_t>(i2);
+    for (uint64_t j2 = 1; j2 < 100 * incr; j2 += incr) {
+      TensorUInt128<static_val<0>, uint64_t> j(0, j2);
+      uint128_t b = static_cast<uint128_t>(j2);
+      uint64_t actual = (i * j).upper();
+      uint64_t expected = (a * b) >> 64;
+      VERIFY_IS_EQUAL(actual, expected);
+    }
+  }
+}
+
+void test_misc2() {
+  int64_t incr = internal::random<int64_t>(1, 100);
+  for (int64_t log_div = 0; log_div < 63; ++log_div) {
+    for (int64_t divider = 1; divider <= 1000000 * incr; divider += incr) {
+      uint64_t expected = (static_cast<uint128_t>(1) << (64+log_div)) / static_cast<uint128_t>(divider) - (static_cast<uint128_t>(1) << 64) + 1;
+      uint64_t shift = 1ULL << log_div;
+
+      TensorUInt128<uint64_t, uint64_t> result = (TensorUInt128<uint64_t, static_val<0> >(shift, 0) / TensorUInt128<static_val<0>, uint64_t>(divider) - TensorUInt128<static_val<1>, static_val<0> >(1, 0) + TensorUInt128<static_val<0>, static_val<1> >(1));
+      uint64_t actual = static_cast<uint64_t>(result);
+      VERIFY_IS_EQUAL(actual, expected);
+    }
+  }
+}
+#endif
+
+
+void test_cxx11_tensor_uint128()
+{
+#ifdef EIGEN_NO_INT128
+  // Skip the test on compilers that don't support 128bit integers natively
+  return;
+#else
+  CALL_SUBTEST_1(test_add());
+  CALL_SUBTEST_2(test_sub());
+  CALL_SUBTEST_3(test_mul());
+  CALL_SUBTEST_4(test_div());
+  CALL_SUBTEST_5(test_misc1());
+  CALL_SUBTEST_6(test_misc2());
+#endif
+}

ADDED   3rd_party/eigen/unsupported/test/cxx11_tensor_volume_patch.cpp
Index: 3rd_party/eigen/unsupported/test/cxx11_tensor_volume_patch.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/cxx11_tensor_volume_patch.cpp
+++ 3rd_party/eigen/unsupported/test/cxx11_tensor_volume_patch.cpp
@@ -0,0 +1,112 @@
+#include "main.h"
+
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+static void test_single_voxel_patch()
+{
+  Tensor<float, 5> tensor(4,2,3,5,7);
+  tensor.setRandom();
+  Tensor<float, 5, RowMajor> tensor_row_major = tensor.swap_layout();
+
+  Tensor<float, 6> single_voxel_patch;
+  single_voxel_patch = tensor.extract_volume_patches(1, 1, 1);
+  VERIFY_IS_EQUAL(single_voxel_patch.dimension(0), 4);
+  VERIFY_IS_EQUAL(single_voxel_patch.dimension(1), 1);
+  VERIFY_IS_EQUAL(single_voxel_patch.dimension(2), 1);
+  VERIFY_IS_EQUAL(single_voxel_patch.dimension(3), 1);
+  VERIFY_IS_EQUAL(single_voxel_patch.dimension(4), 2 * 3 * 5);
+  VERIFY_IS_EQUAL(single_voxel_patch.dimension(5), 7);
+
+  Tensor<float, 6, RowMajor> single_voxel_patch_row_major;
+  single_voxel_patch_row_major = tensor_row_major.extract_volume_patches(1, 1, 1);
+  VERIFY_IS_EQUAL(single_voxel_patch_row_major.dimension(0), 7);
+  VERIFY_IS_EQUAL(single_voxel_patch_row_major.dimension(1), 2 * 3 * 5);
+  VERIFY_IS_EQUAL(single_voxel_patch_row_major.dimension(2), 1);
+  VERIFY_IS_EQUAL(single_voxel_patch_row_major.dimension(3), 1);
+  VERIFY_IS_EQUAL(single_voxel_patch_row_major.dimension(4), 1);
+  VERIFY_IS_EQUAL(single_voxel_patch_row_major.dimension(5), 4);
+
+  for (int i = 0; i < tensor.size(); ++i) {
+    VERIFY_IS_EQUAL(tensor.data()[i], single_voxel_patch.data()[i]);
+    VERIFY_IS_EQUAL(tensor_row_major.data()[i], single_voxel_patch_row_major.data()[i]);
+    VERIFY_IS_EQUAL(tensor.data()[i], tensor_row_major.data()[i]);
+  }
+}
+
+
+static void test_entire_volume_patch()
+{
+  const int depth = 4;
+  const int patch_z = 2;
+  const int patch_y = 3;
+  const int patch_x = 5;
+  const int batch = 7;
+
+  Tensor<float, 5> tensor(depth, patch_z, patch_y, patch_x, batch);
+  tensor.setRandom();
+  Tensor<float, 5, RowMajor> tensor_row_major = tensor.swap_layout();
+
+  Tensor<float, 6> entire_volume_patch;
+  entire_volume_patch = tensor.extract_volume_patches(patch_z, patch_y, patch_x);
+  VERIFY_IS_EQUAL(entire_volume_patch.dimension(0), depth);
+  VERIFY_IS_EQUAL(entire_volume_patch.dimension(1), patch_z);
+  VERIFY_IS_EQUAL(entire_volume_patch.dimension(2), patch_y);
+  VERIFY_IS_EQUAL(entire_volume_patch.dimension(3), patch_x);
+  VERIFY_IS_EQUAL(entire_volume_patch.dimension(4), patch_z * patch_y * patch_x);
+  VERIFY_IS_EQUAL(entire_volume_patch.dimension(5), batch);
+
+  Tensor<float, 6, RowMajor> entire_volume_patch_row_major;
+  entire_volume_patch_row_major = tensor_row_major.extract_volume_patches(patch_z, patch_y, patch_x);
+  VERIFY_IS_EQUAL(entire_volume_patch_row_major.dimension(0), batch);
+  VERIFY_IS_EQUAL(entire_volume_patch_row_major.dimension(1), patch_z * patch_y * patch_x);
+  VERIFY_IS_EQUAL(entire_volume_patch_row_major.dimension(2), patch_x);
+  VERIFY_IS_EQUAL(entire_volume_patch_row_major.dimension(3), patch_y);
+  VERIFY_IS_EQUAL(entire_volume_patch_row_major.dimension(4), patch_z);
+  VERIFY_IS_EQUAL(entire_volume_patch_row_major.dimension(5), depth);
+
+  const int dz = patch_z - 1;
+  const int dy = patch_y - 1;
+  const int dx = patch_x - 1;
+
+  const int forward_pad_z = dz - dz / 2;
+  const int forward_pad_y = dy - dy / 2;
+  const int forward_pad_x = dx - dx / 2;
+
+  for (int pz = 0; pz < patch_z; pz++) {
+    for (int py = 0; py < patch_y; py++) {
+      for (int px = 0; px < patch_x; px++) {
+        const int patchId = pz + patch_z * (py + px * patch_y);
+        for (int z = 0; z < patch_z; z++) {
+          for (int y = 0; y < patch_y; y++) {
+            for (int x = 0; x < patch_x; x++) {
+              for (int b = 0; b < batch; b++) {
+                for (int d = 0; d < depth; d++) {
+                  float expected = 0.0f;
+                  float expected_row_major = 0.0f;
+                  const int eff_z = z - forward_pad_z + pz;
+                  const int eff_y = y - forward_pad_y + py;
+                  const int eff_x = x - forward_pad_x + px;
+                  if (eff_z >= 0 && eff_y >= 0 && eff_x >= 0 &&
+                      eff_z < patch_z && eff_y < patch_y && eff_x < patch_x) {
+                    expected = tensor(d, eff_z, eff_y, eff_x, b);
+                    expected_row_major = tensor_row_major(b, eff_x, eff_y, eff_z, d);
+                  }
+                  VERIFY_IS_EQUAL(entire_volume_patch(d, z, y, x, patchId, b), expected);
+                  VERIFY_IS_EQUAL(entire_volume_patch_row_major(b, patchId, x, y, z, d), expected_row_major);
+                }
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+void test_cxx11_tensor_volume_patch()
+{
+  CALL_SUBTEST(test_single_voxel_patch());
+  CALL_SUBTEST(test_entire_volume_patch());
+}

Index: 3rd_party/eigen/unsupported/test/forward_adolc.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/forward_adolc.cpp
+++ 3rd_party/eigen/unsupported/test/forward_adolc.cpp
@@ -11,12 +11,10 @@
 #include <Eigen/Dense>
 
 #define NUMBER_DIRECTIONS 16
 #include <unsupported/Eigen/AdolcForward>
 
-int adtl::ADOLC_numDir;
-
 template<typename Vector>
 EIGEN_DONT_INLINE typename Vector::Scalar foo(const Vector& p)
 {
   typedef typename Vector::Scalar Scalar;
   return (p-Vector(Scalar(-1),Scalar(1.))).norm() + (p.array().sqrt().abs() * p.array().sin()).sum() + p.dot(p);
@@ -121,11 +119,11 @@
     VERIFY_IS_APPROX(j, jref);
 }
 
 void test_forward_adolc()
 {
-  adtl::ADOLC_numDir = NUMBER_DIRECTIONS;
+  adtl::setNumDir(NUMBER_DIRECTIONS);
 
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1<double,2,2>()) ));
     CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1<double,2,3>()) ));
     CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1<double,3,2>()) ));

DELETED 3rd_party/eigen/unsupported/test/jacobisvd.cpp
Index: 3rd_party/eigen/unsupported/test/jacobisvd.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/jacobisvd.cpp
+++ 3rd_party/eigen/unsupported/test/jacobisvd.cpp
@@ -1,198 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "svd_common.h"
-
-template<typename MatrixType, int QRPreconditioner>
-void jacobisvd_check_full(const MatrixType& m, const JacobiSVD<MatrixType, QRPreconditioner>& svd)
-{
-  svd_check_full<MatrixType, JacobiSVD<MatrixType, QRPreconditioner > >(m, svd);
-}
-
-template<typename MatrixType, int QRPreconditioner>
-void jacobisvd_compare_to_full(const MatrixType& m,
-                               unsigned int computationOptions,
-                               const JacobiSVD<MatrixType, QRPreconditioner>& referenceSvd)
-{
-  svd_compare_to_full<MatrixType, JacobiSVD<MatrixType, QRPreconditioner> >(m, computationOptions, referenceSvd);
-}
-
-
-template<typename MatrixType, int QRPreconditioner>
-void jacobisvd_solve(const MatrixType& m, unsigned int computationOptions)
-{
-  svd_solve< MatrixType, JacobiSVD< MatrixType, QRPreconditioner > >(m, computationOptions);
-}
-
-
-
-template<typename MatrixType, int QRPreconditioner>
-void jacobisvd_test_all_computation_options(const MatrixType& m)
-{
-  
-  if (QRPreconditioner == NoQRPreconditioner && m.rows() != m.cols())
-    return;
-
-  JacobiSVD< MatrixType, QRPreconditioner > fullSvd(m, ComputeFullU|ComputeFullV);
-  svd_test_computation_options_1< MatrixType, JacobiSVD< MatrixType, QRPreconditioner > >(m, fullSvd);
-
-  if(QRPreconditioner == FullPivHouseholderQRPreconditioner)
-    return;
-  svd_test_computation_options_2< MatrixType, JacobiSVD< MatrixType, QRPreconditioner > >(m, fullSvd);
-
-}
-
-template<typename MatrixType>
-void jacobisvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
-{
-  MatrixType m = pickrandom ? MatrixType::Random(a.rows(), a.cols()) : a;
-
-  jacobisvd_test_all_computation_options<MatrixType, FullPivHouseholderQRPreconditioner>(m);
-  jacobisvd_test_all_computation_options<MatrixType, ColPivHouseholderQRPreconditioner>(m);
-  jacobisvd_test_all_computation_options<MatrixType, HouseholderQRPreconditioner>(m);
-  jacobisvd_test_all_computation_options<MatrixType, NoQRPreconditioner>(m);
-}
-
-
-template<typename MatrixType> 
-void jacobisvd_verify_assert(const MatrixType& m)
-{
-  
-  svd_verify_assert<MatrixType, JacobiSVD< MatrixType > >(m);
-
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime
-  };
-
-  MatrixType a = MatrixType::Zero(rows, cols);
-  a.setZero();
-
-  if (ColsAtCompileTime == Dynamic)
-  {
-    JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner> svd_fullqr;
-    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeFullU|ComputeThinV))
-    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeThinV))
-    VERIFY_RAISES_ASSERT(svd_fullqr.compute(a, ComputeThinU|ComputeFullV))
-  }
-}
-
-template<typename MatrixType>
-void jacobisvd_method()
-{
-  enum { Size = MatrixType::RowsAtCompileTime };
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef Matrix<RealScalar, Size, 1> RealVecType;
-  MatrixType m = MatrixType::Identity();
-  VERIFY_IS_APPROX(m.jacobiSvd().singularValues(), RealVecType::Ones());
-  VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixU());
-  VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixV());
-  VERIFY_IS_APPROX(m.jacobiSvd(ComputeFullU|ComputeFullV).solve(m), m);
-}
-
-
-
-template<typename MatrixType>
-void jacobisvd_inf_nan()
-{
-  svd_inf_nan<MatrixType, JacobiSVD< MatrixType > >();
-}
-
-
-// Regression test for bug 286: JacobiSVD loops indefinitely with some
-// matrices containing denormal numbers.
-void jacobisvd_bug286()
-{
-#if defined __INTEL_COMPILER
-// shut up warning #239: floating point underflow
-#pragma warning push
-#pragma warning disable 239
-#endif
-  Matrix2d M;
-  M << -7.90884e-313, -4.94e-324,
-                 0, 5.60844e-313;
-#if defined __INTEL_COMPILER
-#pragma warning pop
-#endif
-  JacobiSVD<Matrix2d> svd;
-  svd.compute(M); // just check we don't loop indefinitely
-}
-
-
-void jacobisvd_preallocate()
-{
-  svd_preallocate< JacobiSVD <MatrixXf> >();
-}
-
-void test_jacobisvd()
-{
-  CALL_SUBTEST_11(( jacobisvd<Matrix<double,Dynamic,Dynamic> >
-		    (Matrix<double,Dynamic,Dynamic>(16, 6)) ));
-
-  CALL_SUBTEST_3(( jacobisvd_verify_assert(Matrix3f()) ));
-  CALL_SUBTEST_4(( jacobisvd_verify_assert(Matrix4d()) ));
-  CALL_SUBTEST_7(( jacobisvd_verify_assert(MatrixXf(10,12)) ));
-  CALL_SUBTEST_8(( jacobisvd_verify_assert(MatrixXcd(7,5)) ));
-
-  for(int i = 0; i < g_repeat; i++) {
-    Matrix2cd m;
-    m << 0, 1,
-         0, 1;
-    CALL_SUBTEST_1(( jacobisvd(m, false) ));
-    m << 1, 0,
-         1, 0;
-    CALL_SUBTEST_1(( jacobisvd(m, false) ));
-
-    Matrix2d n;
-    n << 0, 0,
-         0, 0;
-    CALL_SUBTEST_2(( jacobisvd(n, false) ));
-    n << 0, 0,
-         0, 1;
-    CALL_SUBTEST_2(( jacobisvd(n, false) ));
-    
-    CALL_SUBTEST_3(( jacobisvd<Matrix3f>() ));
-    CALL_SUBTEST_4(( jacobisvd<Matrix4d>() ));
-    CALL_SUBTEST_5(( jacobisvd<Matrix<float,3,5> >() ));
-    CALL_SUBTEST_6(( jacobisvd<Matrix<double,Dynamic,2> >(Matrix<double,Dynamic,2>(10,2)) ));
-
-    int r = internal::random<int>(1, 30),
-        c = internal::random<int>(1, 30);
-    CALL_SUBTEST_7(( jacobisvd<MatrixXf>(MatrixXf(r,c)) ));
-    CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(r,c)) ));
-    (void) r;
-    (void) c;
-
-    // Test on inf/nan matrix
-    CALL_SUBTEST_7( jacobisvd_inf_nan<MatrixXf>() );
-  }
-
-  CALL_SUBTEST_7(( jacobisvd<MatrixXf>(MatrixXf(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) ));
-  CALL_SUBTEST_8(( jacobisvd<MatrixXcd>(MatrixXcd(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3))) ));
-
-
-  // test matrixbase method
-  CALL_SUBTEST_1(( jacobisvd_method<Matrix2cd>() ));
-  CALL_SUBTEST_3(( jacobisvd_method<Matrix3f>() ));
-
-
-  // Test problem size constructors
-  CALL_SUBTEST_7( JacobiSVD<MatrixXf>(10,10) );
-
-  // Check that preallocation avoids subsequent mallocs
-  CALL_SUBTEST_9( jacobisvd_preallocate() );
-
-  // Regression check for bug 286
-  CALL_SUBTEST_2( jacobisvd_bug286() );
-}

Index: 3rd_party/eigen/unsupported/test/kronecker_product.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/kronecker_product.cpp
+++ 3rd_party/eigen/unsupported/test/kronecker_product.cpp
@@ -7,15 +7,15 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+#ifdef EIGEN_TEST_PART_1
 
 #include "sparse.h"
 #include <Eigen/SparseExtra>
 #include <Eigen/KroneckerProduct>
-
 
 template<typename MatrixType>
 void check_dimension(const MatrixType& ab, const int rows,  const int cols)
 {
   VERIFY_IS_EQUAL(ab.rows(), rows);
@@ -105,55 +105,60 @@
   SM_b.insert(2,0) = DM_b.coeffRef(2,0) = -0.1225112806872035;
   SM_b.insert(2,1) = DM_b.coeffRef(2,1) =  0.5903998022741264;
 
   SparseMatrix<double,RowMajor> SM_row_a(SM_a), SM_row_b(SM_b);
 
-  // test kroneckerProduct(DM_block,DM,DM_fixedSize)
+  // test DM_fixedSize = kroneckerProduct(DM_block,DM)
   Matrix<double, 6, 6> DM_fix_ab = kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b);
 
   CALL_SUBTEST(check_kronecker_product(DM_fix_ab));
+  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b)));
 
   for(int i=0;i<DM_fix_ab.rows();++i)
     for(int j=0;j<DM_fix_ab.cols();++j)
        VERIFY_IS_APPROX(kroneckerProduct(DM_a,DM_b).coeff(i,j), DM_fix_ab(i,j));
 
-  // test kroneckerProduct(DM,DM,DM_block)
+  // test DM_block = kroneckerProduct(DM,DM)
   MatrixXd DM_block_ab(10,15);
   DM_block_ab.block<6,6>(2,5) = kroneckerProduct(DM_a,DM_b);
   CALL_SUBTEST(check_kronecker_product(DM_block_ab.block<6,6>(2,5)));
 
-  // test kroneckerProduct(DM,DM,DM)
+  // test DM = kroneckerProduct(DM,DM)
   MatrixXd DM_ab = kroneckerProduct(DM_a,DM_b);
   CALL_SUBTEST(check_kronecker_product(DM_ab));
+  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a,DM_b)));
 
-  // test kroneckerProduct(SM,DM,SM)
+  // test SM = kroneckerProduct(SM,DM)
   SparseMatrix<double> SM_ab = kroneckerProduct(SM_a,DM_b);
   CALL_SUBTEST(check_kronecker_product(SM_ab));
   SparseMatrix<double,RowMajor> SM_ab2 = kroneckerProduct(SM_a,DM_b);
   CALL_SUBTEST(check_kronecker_product(SM_ab2));
+  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(SM_a,DM_b)));
 
-  // test kroneckerProduct(DM,SM,SM)
+  // test SM = kroneckerProduct(DM,SM)
   SM_ab.setZero();
   SM_ab.insert(0,0)=37.0;
   SM_ab = kroneckerProduct(DM_a,SM_b);
   CALL_SUBTEST(check_kronecker_product(SM_ab));
   SM_ab2.setZero();
   SM_ab2.insert(0,0)=37.0;
   SM_ab2 = kroneckerProduct(DM_a,SM_b);
   CALL_SUBTEST(check_kronecker_product(SM_ab2));
+  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a,SM_b)));
 
-  // test kroneckerProduct(SM,SM,SM)
+  // test SM = kroneckerProduct(SM,SM)
   SM_ab.resize(2,33);
   SM_ab.insert(0,0)=37.0;
   SM_ab = kroneckerProduct(SM_a,SM_b);
   CALL_SUBTEST(check_kronecker_product(SM_ab));
   SM_ab2.resize(5,11);
   SM_ab2.insert(0,0)=37.0;
   SM_ab2 = kroneckerProduct(SM_a,SM_b);
   CALL_SUBTEST(check_kronecker_product(SM_ab2));
+  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(SM_a,SM_b)));
 
-  // test kroneckerProduct(SM,SM,SM) with sparse pattern
+  // test SM = kroneckerProduct(SM,SM) with sparse pattern
   SM_a.resize(4,5);
   SM_b.resize(3,2);
   SM_a.resizeNonZeros(0);
   SM_b.resizeNonZeros(0);
   SM_a.insert(1,0) = -0.1;
@@ -167,15 +172,81 @@
   SM_ab.resize(1,1);
   SM_ab.insert(0,0)=37.0;
   SM_ab = kroneckerProduct(SM_a,SM_b);
   CALL_SUBTEST(check_sparse_kronecker_product(SM_ab));
 
-  // test dimension of result of kroneckerProduct(DM,DM,DM)
+  // test dimension of result of DM = kroneckerProduct(DM,DM)
   MatrixXd DM_a2(2,1);
   MatrixXd DM_b2(5,4);
   MatrixXd DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
   CALL_SUBTEST(check_dimension(DM_ab2,2*5,1*4));
   DM_a2.resize(10,9);
   DM_b2.resize(4,8);
   DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
   CALL_SUBTEST(check_dimension(DM_ab2,10*4,9*8));
+  
+  for(int i = 0; i < g_repeat; i++)
+  {
+    double density = Eigen::internal::random<double>(0.01,0.5);
+    int ra = Eigen::internal::random<int>(1,50);
+    int ca = Eigen::internal::random<int>(1,50);
+    int rb = Eigen::internal::random<int>(1,50);
+    int cb = Eigen::internal::random<int>(1,50);
+    SparseMatrix<float,ColMajor> sA(ra,ca), sB(rb,cb), sC;
+    SparseMatrix<float,RowMajor> sC2;
+    MatrixXf dA(ra,ca), dB(rb,cb), dC;
+    initSparse(density, dA, sA);
+    initSparse(density, dB, sB);
+    
+    sC = kroneckerProduct(sA,sB);
+    dC = kroneckerProduct(dA,dB);
+    VERIFY_IS_APPROX(MatrixXf(sC),dC);
+    
+    sC = kroneckerProduct(sA.transpose(),sB);
+    dC = kroneckerProduct(dA.transpose(),dB);
+    VERIFY_IS_APPROX(MatrixXf(sC),dC);
+    
+    sC = kroneckerProduct(sA.transpose(),sB.transpose());
+    dC = kroneckerProduct(dA.transpose(),dB.transpose());
+    VERIFY_IS_APPROX(MatrixXf(sC),dC);
+    
+    sC = kroneckerProduct(sA,sB.transpose());
+    dC = kroneckerProduct(dA,dB.transpose());
+    VERIFY_IS_APPROX(MatrixXf(sC),dC);
+    
+    sC2 = kroneckerProduct(sA,sB);
+    dC = kroneckerProduct(dA,dB);
+    VERIFY_IS_APPROX(MatrixXf(sC2),dC);
+    
+    sC2 = kroneckerProduct(dA,sB);
+    dC = kroneckerProduct(dA,dB);
+    VERIFY_IS_APPROX(MatrixXf(sC2),dC);
+    
+    sC2 = kroneckerProduct(sA,dB);
+    dC = kroneckerProduct(dA,dB);
+    VERIFY_IS_APPROX(MatrixXf(sC2),dC);
+    
+    sC2 = kroneckerProduct(2*sA,sB);
+    dC = kroneckerProduct(2*dA,dB);
+    VERIFY_IS_APPROX(MatrixXf(sC2),dC);
+  }
+}
+
+#endif
+
+#ifdef EIGEN_TEST_PART_2
+
+// simply check that for a dense kronecker product, sparse module is not needed
+
+#include "main.h"
+#include <Eigen/KroneckerProduct>
+
+void test_kronecker_product()
+{
+  MatrixXd a(2,2), b(3,3), c;
+  a.setRandom();
+  b.setRandom();
+  c = kroneckerProduct(a,b);
+  VERIFY_IS_APPROX(c.block(3,3,3,3), a(1,1)*b);
 }
+
+#endif

Index: 3rd_party/eigen/unsupported/test/levenberg_marquardt.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/levenberg_marquardt.cpp
+++ 3rd_party/eigen/unsupported/test/levenberg_marquardt.cpp
@@ -6,10 +6,13 @@
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
+
+// FIXME: These tests all check for hard-coded values. Ideally, parameters and start estimates should be randomized.
+
 
 #include <stdio.h>
 
 #include "main.h"
 #include <unsupported/Eigen/LevenbergMarquardt>
@@ -17,10 +20,13 @@
 // This disables some useless Warnings on MSVC.
 // It is intended to be done for this test only.
 #include <Eigen/src/Core/util/DisableStupidWarnings.h>
 
 using std::sqrt;
+
+// tolerance for chekcing number of iterations
+#define LM_EVAL_COUNT_TOL 4/3
 
 struct lmder_functor : DenseFunctor<double>
 {
     lmder_functor(void): DenseFunctor<double>(3,15) {}
     int operator()(const VectorXd &x, VectorXd &fvec) const
@@ -273,11 +279,11 @@
 
 // http://www.itl.nist.gov/div898/strd/nls/data/chwirut2.shtml
 void testNistChwirut2(void)
 {
   const int n=3;
-  int info;
+  LevenbergMarquardtSpace::Status info;
 
   VectorXd x(n);
 
   /*
    * First try
@@ -608,11 +614,11 @@
 
 // http://www.itl.nist.gov/div898/strd/nls/data/lanczos1.shtml
 void testNistLanczos1(void)
 {
   const int n=6;
-  int info;
+  LevenbergMarquardtSpace::Status info;
 
   VectorXd x(n);
 
   /*
    * First try
@@ -622,15 +628,15 @@
   lanczos1_functor functor;
   LevenbergMarquardt<lanczos1_functor> lm(functor);
   info = lm.minimize(x);
 
   // check return value
-  VERIFY_IS_EQUAL(info, 2);
+  VERIFY_IS_EQUAL(info, LevenbergMarquardtSpace::RelativeErrorTooSmall);
   VERIFY_IS_EQUAL(lm.nfev(), 79);
   VERIFY_IS_EQUAL(lm.njev(), 72);
   // check norm^2
-//   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 1.430899764097e-25);  // should be 1.4307867721E-25, but nist results are on 128-bit floats
+  VERIFY(lm.fvec().squaredNorm() <= 1.4307867721E-25);
   // check x
   VERIFY_IS_APPROX(x[0], 9.5100000027E-02);
   VERIFY_IS_APPROX(x[1], 1.0000000001E+00);
   VERIFY_IS_APPROX(x[2], 8.6070000013E-01);
   VERIFY_IS_APPROX(x[3], 3.0000000002E+00);
@@ -643,15 +649,15 @@
   x<< 0.5, 0.7, 3.6, 4.2, 4., 6.3;
   // do the computation
   info = lm.minimize(x);
 
   // check return value
-  VERIFY_IS_EQUAL(info, 2);
+  VERIFY_IS_EQUAL(info, LevenbergMarquardtSpace::RelativeErrorTooSmall);
   VERIFY_IS_EQUAL(lm.nfev(), 9);
   VERIFY_IS_EQUAL(lm.njev(), 8);
   // check norm^2
-//   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 1.428595533845e-25);  // should be 1.4307867721E-25, but nist results are on 128-bit floats
+  VERIFY(lm.fvec().squaredNorm() <= 1.4307867721E-25);
   // check x
   VERIFY_IS_APPROX(x[0], 9.5100000027E-02);
   VERIFY_IS_APPROX(x[1], 1.0000000001E+00);
   VERIFY_IS_APPROX(x[2], 8.6070000013E-01);
   VERIFY_IS_APPROX(x[3], 3.0000000002E+00);
@@ -694,11 +700,11 @@
 
 // http://www.itl.nist.gov/div898/strd/nls/data/ratkowsky2.shtml
 void testNistRat42(void)
 {
   const int n=3;
-  int info;
+  LevenbergMarquardtSpace::Status info;
 
   VectorXd x(n);
 
   /*
    * First try
@@ -708,11 +714,11 @@
   rat42_functor functor;
   LevenbergMarquardt<rat42_functor> lm(functor);
   info = lm.minimize(x);
 
   // check return value
-  VERIFY_IS_EQUAL(info, 1);
+  VERIFY_IS_EQUAL(info, LevenbergMarquardtSpace::RelativeReductionTooSmall);
   VERIFY_IS_EQUAL(lm.nfev(), 10);
   VERIFY_IS_EQUAL(lm.njev(), 8);
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 8.0565229338E+00);
   // check x
@@ -726,11 +732,11 @@
   x<< 75., 2.5, 0.07;
   // do the computation
   info = lm.minimize(x);
 
   // check return value
-  VERIFY_IS_EQUAL(info, 1);
+  VERIFY_IS_EQUAL(info, LevenbergMarquardtSpace::RelativeReductionTooSmall);
   VERIFY_IS_EQUAL(lm.nfev(), 6);
   VERIFY_IS_EQUAL(lm.njev(), 5);
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 8.0565229338E+00);
   // check x
@@ -772,11 +778,11 @@
 
 // http://www.itl.nist.gov/div898/strd/nls/data/mgh10.shtml
 void testNistMGH10(void)
 {
   const int n=3;
-  int info;
+  LevenbergMarquardtSpace::Status info;
 
   VectorXd x(n);
 
   /*
    * First try
@@ -784,39 +790,56 @@
   x<< 2., 400000., 25000.;
   // do the computation
   MGH10_functor functor;
   LevenbergMarquardt<MGH10_functor> lm(functor);
   info = lm.minimize(x);
+  ++g_test_level;
+  VERIFY_IS_EQUAL(info, LevenbergMarquardtSpace::RelativeReductionTooSmall);
+  --g_test_level;
+  // was: VERIFY_IS_EQUAL(info, 1);
 
-  // check return value
-  VERIFY_IS_EQUAL(info, 1); 
-  VERIFY_IS_EQUAL(lm.nfev(), 284 ); 
-  VERIFY_IS_EQUAL(lm.njev(), 249 ); 
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 8.7945855171E+01);
   // check x
   VERIFY_IS_APPROX(x[0], 5.6096364710E-03);
   VERIFY_IS_APPROX(x[1], 6.1813463463E+03);
   VERIFY_IS_APPROX(x[2], 3.4522363462E+02);
+  
+  // check return value
+
+  ++g_test_level;
+  VERIFY_IS_EQUAL(lm.nfev(), 284 );
+  VERIFY_IS_EQUAL(lm.njev(), 249 );
+  --g_test_level;
+  VERIFY(lm.nfev() < 284 * LM_EVAL_COUNT_TOL);
+  VERIFY(lm.njev() < 249 * LM_EVAL_COUNT_TOL);
 
   /*
    * Second try
    */
   x<< 0.02, 4000., 250.;
   // do the computation
   info = lm.minimize(x);
+  ++g_test_level;
+  VERIFY_IS_EQUAL(info, LevenbergMarquardtSpace::RelativeReductionTooSmall);
+  // was: VERIFY_IS_EQUAL(info, 1);
+  --g_test_level;
 
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev(), 126);
-  VERIFY_IS_EQUAL(lm.njev(), 116);
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 8.7945855171E+01);
   // check x
   VERIFY_IS_APPROX(x[0], 5.6096364710E-03);
   VERIFY_IS_APPROX(x[1], 6.1813463463E+03);
   VERIFY_IS_APPROX(x[2], 3.4522363462E+02);
+  
+  // check return value
+  ++g_test_level;
+  VERIFY_IS_EQUAL(lm.nfev(), 126);
+  VERIFY_IS_EQUAL(lm.njev(), 116);
+  --g_test_level;
+  VERIFY(lm.nfev() < 126 * LM_EVAL_COUNT_TOL);
+  VERIFY(lm.njev() < 116 * LM_EVAL_COUNT_TOL);
 }
 
 
 struct BoxBOD_functor : DenseFunctor<double>
 {
@@ -864,19 +887,20 @@
   lm.setFtol(1.E6*NumTraits<double>::epsilon());
   lm.setXtol(1.E6*NumTraits<double>::epsilon());
   lm.setFactor(10);
   info = lm.minimize(x);
 
-  // check return value
-  VERIFY_IS_EQUAL(info, 1);
-  VERIFY_IS_EQUAL(lm.nfev(), 31);
-  VERIFY_IS_EQUAL(lm.njev(), 25);
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 1.1680088766E+03);
   // check x
   VERIFY_IS_APPROX(x[0], 2.1380940889E+02);
   VERIFY_IS_APPROX(x[1], 5.4723748542E-01);
+  
+  // check return value
+  VERIFY_IS_EQUAL(info, 1);
+  VERIFY(lm.nfev() < 31); // 31
+  VERIFY(lm.njev() < 25); // 25
 
   /*
    * Second try
    */
   x<< 100., 0.75;
@@ -886,12 +910,16 @@
   lm.setXtol( NumTraits<double>::epsilon());
   info = lm.minimize(x);
 
   // check return value
   VERIFY_IS_EQUAL(info, 1); 
-  VERIFY_IS_EQUAL(lm.nfev(), 15 ); 
-  VERIFY_IS_EQUAL(lm.njev(), 14 ); 
+  ++g_test_level;
+  VERIFY_IS_EQUAL(lm.nfev(), 16 );
+  VERIFY_IS_EQUAL(lm.njev(), 15 );
+  --g_test_level;
+  VERIFY(lm.nfev() < 16 * LM_EVAL_COUNT_TOL);
+  VERIFY(lm.njev() < 15 * LM_EVAL_COUNT_TOL);
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 1.1680088766E+03);
   // check x
   VERIFY_IS_APPROX(x[0], 2.1380940889E+02);
   VERIFY_IS_APPROX(x[1], 5.4723748542E-01);
@@ -946,22 +974,23 @@
   lm.setFtol(NumTraits<double>::epsilon());
   lm.setXtol(NumTraits<double>::epsilon());
   lm.setMaxfev(1000);
   info = lm.minimize(x);
 
-  // check return value
-//   VERIFY_IS_EQUAL(info, 2);  //FIXME Use (lm.info() == Success)
-//   VERIFY_IS_EQUAL(lm.nfev(), 602 ); 
-  VERIFY_IS_EQUAL(lm.njev(), 545 ); 
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 5.4648946975E-05);
   // check x
   VERIFY_IS_APPROX(x[0], 3.7541005211E-01);
   VERIFY_IS_APPROX(x[1], 1.9358469127E+00);
   VERIFY_IS_APPROX(x[2], -1.4646871366E+00);
   VERIFY_IS_APPROX(x[3], 1.2867534640E-02);
   VERIFY_IS_APPROX(x[4], 2.2122699662E-02);
+  
+    // check return value
+//   VERIFY_IS_EQUAL(info, 2);  //FIXME Use (lm.info() == Success)
+  VERIFY(lm.nfev() < 700 ); // 602
+  VERIFY(lm.njev() < 600 ); // 545
 
   /*
    * Second try
    */
   x<< 0.5  ,1.5  ,-1   ,0.01 ,0.02;
@@ -1033,21 +1062,21 @@
   MGH09_functor functor;
   LevenbergMarquardt<MGH09_functor> lm(functor);
   lm.setMaxfev(1000);
   info = lm.minimize(x);
 
-  // check return value
-  VERIFY_IS_EQUAL(info, 1); 
-  VERIFY_IS_EQUAL(lm.nfev(), 490 ); 
-  VERIFY_IS_EQUAL(lm.njev(), 376 ); 
   // check norm^2
   VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 3.0750560385E-04);
   // check x
   VERIFY_IS_APPROX(x[0], 0.1928077089); // should be 1.9280693458E-01
   VERIFY_IS_APPROX(x[1], 0.19126423573); // should be 1.9128232873E-01
   VERIFY_IS_APPROX(x[2], 0.12305309914); // should be 1.2305650693E-01
   VERIFY_IS_APPROX(x[3], 0.13605395375); // should be 1.3606233068E-01
+  // check return value
+  VERIFY_IS_EQUAL(info, 1); 
+  VERIFY(lm.nfev() < 510 ); // 490
+  VERIFY(lm.njev() < 400 ); // 376
 
   /*
    * Second try
    */
   x<< 0.25, 0.39, 0.415, 0.39;

Index: 3rd_party/eigen/unsupported/test/matrix_function.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/matrix_function.cpp
+++ 3rd_party/eigen/unsupported/test/matrix_function.cpp
@@ -100,11 +100,11 @@
 {
   typedef typename internal::traits<MatrixType>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef std::complex<RealScalar> ComplexScalar;
 
-  VERIFY_IS_APPROX(A.exp(), A.matrixFunction(StdStemFunctions<ComplexScalar>::exp));
+  VERIFY_IS_APPROX(A.exp(), A.matrixFunction(internal::stem_function_exp<ComplexScalar>));
 }
 
 template<typename MatrixType>
 void testMatrixLogarithm(const MatrixType& A)
 {
@@ -111,12 +111,12 @@
   typedef typename internal::traits<MatrixType>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
 
   MatrixType scaledA;
   RealScalar maxImagPartOfSpectrum = A.eigenvalues().imag().cwiseAbs().maxCoeff();
-  if (maxImagPartOfSpectrum >= 0.9 * M_PI)
-    scaledA = A * 0.9 * M_PI / maxImagPartOfSpectrum;
+  if (maxImagPartOfSpectrum >= RealScalar(0.9L * EIGEN_PI))
+    scaledA = A * RealScalar(0.9L * EIGEN_PI) / maxImagPartOfSpectrum;
   else
     scaledA = A;
 
   // identity X.exp().log() = X only holds if Im(lambda) < pi for all eigenvalues of X
   MatrixType expA = scaledA.exp();

Index: 3rd_party/eigen/unsupported/test/matrix_functions.h
==================================================================
--- 3rd_party/eigen/unsupported/test/matrix_functions.h
+++ 3rd_party/eigen/unsupported/test/matrix_functions.h
@@ -7,32 +7,52 @@
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "main.h"
 #include <unsupported/Eigen/MatrixFunctions>
+
+// For complex matrices, any matrix is fine.
+template<typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
+struct processTriangularMatrix
+{
+  static void run(MatrixType&, MatrixType&, const MatrixType&)
+  { }
+};
+
+// For real matrices, make sure none of the eigenvalues are negative.
+template<typename MatrixType>
+struct processTriangularMatrix<MatrixType,0>
+{
+  static void run(MatrixType& m, MatrixType& T, const MatrixType& U)
+  {
+    const Index size = m.cols();
+
+    for (Index i=0; i < size; ++i) {
+      if (i == size - 1 || T.coeff(i+1,i) == 0)
+        T.coeffRef(i,i) = std::abs(T.coeff(i,i));
+      else
+        ++i;
+    }
+    m = U * T * U.transpose();
+  }
+};
 
 template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
 struct generateTestMatrix;
 
-// for real matrices, make sure none of the eigenvalues are negative
 template <typename MatrixType>
 struct generateTestMatrix<MatrixType,0>
 {
   static void run(MatrixType& result, typename MatrixType::Index size)
   {
-    MatrixType mat = MatrixType::Random(size, size);
-    EigenSolver<MatrixType> es(mat);
-    typename EigenSolver<MatrixType>::EigenvalueType eivals = es.eigenvalues();
-    for (typename MatrixType::Index i = 0; i < size; ++i) {
-      if (eivals(i).imag() == 0 && eivals(i).real() < 0)
-	eivals(i) = -eivals(i);
-    }
-    result = (es.eigenvectors() * eivals.asDiagonal() * es.eigenvectors().inverse()).real();
+    result = MatrixType::Random(size, size);
+    RealSchur<MatrixType> schur(result);
+    MatrixType T = schur.matrixT();
+    processTriangularMatrix<MatrixType>::run(result, T, schur.matrixU());
   }
 };
 
-// for complex matrices, any matrix is fine
 template <typename MatrixType>
 struct generateTestMatrix<MatrixType,1>
 {
   static void run(MatrixType& result, typename MatrixType::Index size)
   {
@@ -39,9 +59,9 @@
     result = MatrixType::Random(size, size);
   }
 };
 
 template <typename Derived, typename OtherDerived>
-double relerr(const MatrixBase<Derived>& A, const MatrixBase<OtherDerived>& B)
+typename Derived::RealScalar relerr(const MatrixBase<Derived>& A, const MatrixBase<OtherDerived>& B)
 {
   return std::sqrt((A - B).cwiseAbs2().sum() / (std::min)(A.cwiseAbs2().sum(), B.cwiseAbs2().sum()));
 }

Index: 3rd_party/eigen/unsupported/test/matrix_power.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/matrix_power.cpp
+++ 3rd_party/eigen/unsupported/test/matrix_power.cpp
@@ -1,66 +1,39 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+// Copyright (C) 2012, 2013 Chen-Pang He <jdh8@ms63.hinet.net>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #include "matrix_functions.h"
 
-template <typename MatrixType, int IsComplex = NumTraits<typename MatrixType::Scalar>::IsComplex>
-struct generateTriangularMatrix;
-
-// for real matrices, make sure none of the eigenvalues are negative
-template <typename MatrixType>
-struct generateTriangularMatrix<MatrixType,0>
-{
-  static void run(MatrixType& result, typename MatrixType::Index size)
-  {
-    result.resize(size, size);
-    result.template triangularView<Upper>() = MatrixType::Random(size, size);
-    for (typename MatrixType::Index i = 0; i < size; ++i)
-      result.coeffRef(i,i) = std::abs(result.coeff(i,i));
-  }
-};
-
-// for complex matrices, any matrix is fine
-template <typename MatrixType>
-struct generateTriangularMatrix<MatrixType,1>
-{
-  static void run(MatrixType& result, typename MatrixType::Index size)
-  {
-    result.resize(size, size);
-    result.template triangularView<Upper>() = MatrixType::Random(size, size);
-  }
-};
-
 template<typename T>
-void test2dRotation(double tol)
+void test2dRotation(const T& tol)
 {
   Matrix<T,2,2> A, B, C;
   T angle, c, s;
 
   A << 0, 1, -1, 0;
   MatrixPower<Matrix<T,2,2> > Apow(A);
 
   for (int i=0; i<=20; ++i) {
-    angle = pow(10, (i-10) / 5.);
+    angle = std::pow(T(10), (i-10) / T(5.));
     c = std::cos(angle);
     s = std::sin(angle);
     B << c, s, -s, c;
 
-    C = Apow(std::ldexp(angle,1) / M_PI);
+    C = Apow(std::ldexp(angle,1) / T(EIGEN_PI));
     std::cout << "test2dRotation: i = " << i << "   error powerm = " << relerr(C,B) << '\n';
-    VERIFY(C.isApprox(B, static_cast<T>(tol)));
+    VERIFY(C.isApprox(B, tol));
   }
 }
 
 template<typename T>
-void test2dHyperbolicRotation(double tol)
+void test2dHyperbolicRotation(const T& tol)
 {
   Matrix<std::complex<T>,2,2> A, B, C;
   T angle, ch = std::cosh((T)1);
   std::complex<T> ish(0, std::sinh((T)1));
 
@@ -73,16 +46,30 @@
     ish = std::complex<T>(0, std::sinh(angle));
     B << ch, ish, -ish, ch;
 
     C = Apow(angle);
     std::cout << "test2dHyperbolicRotation: i = " << i << "   error powerm = " << relerr(C,B) << '\n';
-    VERIFY(C.isApprox(B, static_cast<T>(tol)));
+    VERIFY(C.isApprox(B, tol));
+  }
+}
+
+template<typename T>
+void test3dRotation(const T& tol)
+{
+  Matrix<T,3,1> v;
+  T angle;
+
+  for (int i=0; i<=20; ++i) {
+    v = Matrix<T,3,1>::Random();
+    v.normalize();
+    angle = std::pow(T(10), (i-10) / T(5.));
+    VERIFY(AngleAxis<T>(angle, v).matrix().isApprox(AngleAxis<T>(1,v).matrix().pow(angle), tol));
   }
 }
 
 template<typename MatrixType>
-void testExponentLaws(const MatrixType& m, double tol)
+void testGeneral(const MatrixType& m, const typename MatrixType::RealScalar& tol)
 {
   typedef typename MatrixType::RealScalar RealScalar;
   MatrixType m1, m2, m3, m4, m5;
   RealScalar x, y;
 
@@ -95,39 +82,123 @@
     m2 = mpow(x);
     m3 = mpow(y);
 
     m4 = mpow(x+y);
     m5.noalias() = m2 * m3;
-    VERIFY(m4.isApprox(m5, static_cast<RealScalar>(tol)));
+    VERIFY(m4.isApprox(m5, tol));
 
     m4 = mpow(x*y);
     m5 = m2.pow(y);
-    VERIFY(m4.isApprox(m5, static_cast<RealScalar>(tol)));
+    VERIFY(m4.isApprox(m5, tol));
 
     m4 = (std::abs(x) * m1).pow(y);
     m5 = std::pow(std::abs(x), y) * m3;
-    VERIFY(m4.isApprox(m5, static_cast<RealScalar>(tol)));
+    VERIFY(m4.isApprox(m5, tol));
+  }
+}
+
+template<typename MatrixType>
+void testSingular(const MatrixType& m_const, const typename MatrixType::RealScalar& tol)
+{
+  // we need to pass by reference in order to prevent errors with
+  // MSVC for aligned data types ...
+  MatrixType& m = const_cast<MatrixType&>(m_const);
+
+  const int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex;
+  typedef typename internal::conditional<IsComplex, TriangularView<MatrixType,Upper>, const MatrixType&>::type TriangularType;
+  typename internal::conditional< IsComplex, ComplexSchur<MatrixType>, RealSchur<MatrixType> >::type schur;
+  MatrixType T;
+
+  for (int i=0; i < g_repeat; ++i) {
+    m.setRandom();
+    m.col(0).fill(0);
+
+    schur.compute(m);
+    T = schur.matrixT();
+    const MatrixType& U = schur.matrixU();
+    processTriangularMatrix<MatrixType>::run(m, T, U);
+    MatrixPower<MatrixType> mpow(m);
+
+    T = T.sqrt();
+    VERIFY(mpow(0.5L).isApprox(U * (TriangularType(T) * U.adjoint()), tol));
+
+    T = T.sqrt();
+    VERIFY(mpow(0.25L).isApprox(U * (TriangularType(T) * U.adjoint()), tol));
+
+    T = T.sqrt();
+    VERIFY(mpow(0.125L).isApprox(U * (TriangularType(T) * U.adjoint()), tol));
+  }
+}
+
+template<typename MatrixType>
+void testLogThenExp(const MatrixType& m_const, const typename MatrixType::RealScalar& tol)
+{
+  // we need to pass by reference in order to prevent errors with
+  // MSVC for aligned data types ...
+  MatrixType& m = const_cast<MatrixType&>(m_const);
+
+  typedef typename MatrixType::Scalar Scalar;
+  Scalar x;
+
+  for (int i=0; i < g_repeat; ++i) {
+    generateTestMatrix<MatrixType>::run(m, m.rows());
+    x = internal::random<Scalar>();
+    VERIFY(m.pow(x).isApprox((x * m.log()).exp(), tol));
   }
 }
 
 typedef Matrix<double,3,3,RowMajor>         Matrix3dRowMajor;
+typedef Matrix<long double,3,3>             Matrix3e;
 typedef Matrix<long double,Dynamic,Dynamic> MatrixXe;
  
 void test_matrix_power()
 {
   CALL_SUBTEST_2(test2dRotation<double>(1e-13));
   CALL_SUBTEST_1(test2dRotation<float>(2e-5));  // was 1e-5, relaxed for clang 2.8 / linux / x86-64
-  CALL_SUBTEST_9(test2dRotation<long double>(1e-13)); 
+  CALL_SUBTEST_9(test2dRotation<long double>(1e-13L));
   CALL_SUBTEST_2(test2dHyperbolicRotation<double>(1e-14));
   CALL_SUBTEST_1(test2dHyperbolicRotation<float>(1e-5));
-  CALL_SUBTEST_9(test2dHyperbolicRotation<long double>(1e-14));
-
-  CALL_SUBTEST_2(testExponentLaws(Matrix2d(),         1e-13));
-  CALL_SUBTEST_7(testExponentLaws(Matrix3dRowMajor(), 1e-13));
-  CALL_SUBTEST_3(testExponentLaws(Matrix4cd(),        1e-13));
-  CALL_SUBTEST_4(testExponentLaws(MatrixXd(8,8),      2e-12));
-  CALL_SUBTEST_1(testExponentLaws(Matrix2f(),         1e-4));
-  CALL_SUBTEST_5(testExponentLaws(Matrix3cf(),        1e-4));
-  CALL_SUBTEST_8(testExponentLaws(Matrix4f(),         1e-4));
-  CALL_SUBTEST_6(testExponentLaws(MatrixXf(2,2),      1e-3)); // see bug 614
-  CALL_SUBTEST_9(testExponentLaws(MatrixXe(7,7),      1e-13));
+  CALL_SUBTEST_9(test2dHyperbolicRotation<long double>(1e-14L));
+
+  CALL_SUBTEST_10(test3dRotation<double>(1e-13));
+  CALL_SUBTEST_11(test3dRotation<float>(1e-5));
+  CALL_SUBTEST_12(test3dRotation<long double>(1e-13L));
+
+  CALL_SUBTEST_2(testGeneral(Matrix2d(),         1e-13));
+  CALL_SUBTEST_7(testGeneral(Matrix3dRowMajor(), 1e-13));
+  CALL_SUBTEST_3(testGeneral(Matrix4cd(),        1e-13));
+  CALL_SUBTEST_4(testGeneral(MatrixXd(8,8),      2e-12));
+  CALL_SUBTEST_1(testGeneral(Matrix2f(),         1e-4));
+  CALL_SUBTEST_5(testGeneral(Matrix3cf(),        1e-4));
+  CALL_SUBTEST_8(testGeneral(Matrix4f(),         1e-4));
+  CALL_SUBTEST_6(testGeneral(MatrixXf(2,2),      1e-3)); // see bug 614
+  CALL_SUBTEST_9(testGeneral(MatrixXe(7,7),      1e-13L));
+  CALL_SUBTEST_10(testGeneral(Matrix3d(),        1e-13));
+  CALL_SUBTEST_11(testGeneral(Matrix3f(),        1e-4));
+  CALL_SUBTEST_12(testGeneral(Matrix3e(),        1e-13L));
+
+  CALL_SUBTEST_2(testSingular(Matrix2d(),         1e-13));
+  CALL_SUBTEST_7(testSingular(Matrix3dRowMajor(), 1e-13));
+  CALL_SUBTEST_3(testSingular(Matrix4cd(),        1e-13));
+  CALL_SUBTEST_4(testSingular(MatrixXd(8,8),      2e-12));
+  CALL_SUBTEST_1(testSingular(Matrix2f(),         1e-4));
+  CALL_SUBTEST_5(testSingular(Matrix3cf(),        1e-4));
+  CALL_SUBTEST_8(testSingular(Matrix4f(),         1e-4));
+  CALL_SUBTEST_6(testSingular(MatrixXf(2,2),      1e-3));
+  CALL_SUBTEST_9(testSingular(MatrixXe(7,7),      1e-13L));
+  CALL_SUBTEST_10(testSingular(Matrix3d(),        1e-13));
+  CALL_SUBTEST_11(testSingular(Matrix3f(),        1e-4));
+  CALL_SUBTEST_12(testSingular(Matrix3e(),        1e-13L));
+
+  CALL_SUBTEST_2(testLogThenExp(Matrix2d(),         1e-13));
+  CALL_SUBTEST_7(testLogThenExp(Matrix3dRowMajor(), 1e-13));
+  CALL_SUBTEST_3(testLogThenExp(Matrix4cd(),        1e-13));
+  CALL_SUBTEST_4(testLogThenExp(MatrixXd(8,8),      2e-12));
+  CALL_SUBTEST_1(testLogThenExp(Matrix2f(),         1e-4));
+  CALL_SUBTEST_5(testLogThenExp(Matrix3cf(),        1e-4));
+  CALL_SUBTEST_8(testLogThenExp(Matrix4f(),         1e-4));
+  CALL_SUBTEST_6(testLogThenExp(MatrixXf(2,2),      1e-3));
+  CALL_SUBTEST_9(testLogThenExp(MatrixXe(7,7),      1e-13L));
+  CALL_SUBTEST_10(testLogThenExp(Matrix3d(),        1e-13));
+  CALL_SUBTEST_11(testLogThenExp(Matrix3f(),        1e-4));
+  CALL_SUBTEST_12(testLogThenExp(Matrix3e(),        1e-13L));
 }

Index: 3rd_party/eigen/unsupported/test/minres.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/minres.cpp
+++ 3rd_party/eigen/unsupported/test/minres.cpp
@@ -1,10 +1,10 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2011 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2012 Giacomo Po <gpo@ucla.edu>
+// Copyright (C) 2011 Gael Guennebaud <g.gael@free.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 #include <cmath>
@@ -12,21 +12,33 @@
 #include "../../test/sparse_solver.h"
 #include <Eigen/IterativeSolvers>
 
 template<typename T> void test_minres_T()
 {
-  MINRES<SparseMatrix<T>, Lower, DiagonalPreconditioner<T> > minres_colmajor_diag;
-  MINRES<SparseMatrix<T>, Lower, IdentityPreconditioner    > minres_colmajor_I;
-//  MINRES<SparseMatrix<T>, Lower, IncompleteLUT<T> >           minres_colmajor_ilut;
-  //minres<SparseMatrix<T>, SSORPreconditioner<T> >     minres_colmajor_ssor;
-
-  CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_diag)  );
-  CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_I) );
- // CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_ilut)     );
-  //CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_ssor)     );
+  // Identity preconditioner
+  MINRES<SparseMatrix<T>, Lower, IdentityPreconditioner    > minres_colmajor_lower_I;
+  MINRES<SparseMatrix<T>, Upper, IdentityPreconditioner    > minres_colmajor_upper_I;
+
+  // Diagonal preconditioner
+  MINRES<SparseMatrix<T>, Lower, DiagonalPreconditioner<T> > minres_colmajor_lower_diag;
+  MINRES<SparseMatrix<T>, Upper, DiagonalPreconditioner<T> > minres_colmajor_upper_diag;
+  MINRES<SparseMatrix<T>, Lower|Upper, DiagonalPreconditioner<T> > minres_colmajor_uplo_diag;
+  
+  // call tests for SPD matrix
+  CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_lower_I) );
+  CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_upper_I) );
+    
+  CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_lower_diag)  );
+  CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_upper_diag)  );
+  CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_uplo_diag)  );
+    
+  // TO DO: symmetric semi-definite matrix
+  // TO DO: symmetric indefinite matrix
+
 }
 
 void test_minres()
 {
   CALL_SUBTEST_1(test_minres_T<double>());
-//  CALL_SUBTEST_2(test_minres_T<std::complex<double> >());
+//  CALL_SUBTEST_2(test_minres_T<std::compex<double> >());
+
 }

Index: 3rd_party/eigen/unsupported/test/mpreal/mpreal.h
==================================================================
--- 3rd_party/eigen/unsupported/test/mpreal/mpreal.h
+++ 3rd_party/eigen/unsupported/test/mpreal/mpreal.h
@@ -1,35 +1,36 @@
 /*
-    MPFR C++: Multi-precision floating point number class for C++. 
+    MPFR C++: Multi-precision floating point number class for C++.
     Based on MPFR library:    http://mpfr.org
 
     Project homepage:    http://www.holoborodko.com/pavel/mpfr
     Contact e-mail:      pavel@holoborodko.com
 
-    Copyright (c) 2008-2014 Pavel Holoborodko
+    Copyright (c) 2008-2015 Pavel Holoborodko
 
     Contributors:
-    Dmitriy Gubanov, Konstantin Holoborodko, Brian Gladman, 
-    Helmut Jarausch, Fokko Beekhof, Ulrich Mutze, Heinz van Saanen, 
-    Pere Constans, Peter van Hoof, Gael Guennebaud, Tsai Chia Cheng, 
+    Dmitriy Gubanov, Konstantin Holoborodko, Brian Gladman,
+    Helmut Jarausch, Fokko Beekhof, Ulrich Mutze, Heinz van Saanen,
+    Pere Constans, Peter van Hoof, Gael Guennebaud, Tsai Chia Cheng,
     Alexei Zubanov, Jauhien Piatlicki, Victor Berger, John Westwood,
-    Petr Aleksandrov, Orion Poplawski, Charles Karney.
+    Petr Aleksandrov, Orion Poplawski, Charles Karney, Arash Partow,
+    Rodney James, Jorge Leitao.
 
     Licensing:
     (A) MPFR C++ is under GNU General Public License ("GPL").
-    
-    (B) Non-free licenses may also be purchased from the author, for users who 
+
+    (B) Non-free licenses may also be purchased from the author, for users who
         do not want their programs protected by the GPL.
 
-        The non-free licenses are for users that wish to use MPFR C++ in 
-        their products but are unwilling to release their software 
-        under the GPL (which would require them to release source code 
+        The non-free licenses are for users that wish to use MPFR C++ in
+        their products but are unwilling to release their software
+        under the GPL (which would require them to release source code
         and allow free redistribution).
 
         Such users can purchase an unlimited-use license from the author.
         Contact us for more details.
-    
+
     GNU General Public License ("GPL") copyright permissions statement:
     **************************************************************************
     This program is free software: you can redistribute it and/or modify
     it under the terms of the GNU General Public License as published by
     the Free Software Foundation, either version 3 of the License, or
@@ -53,33 +54,32 @@
 #include <stdexcept>
 #include <cfloat>
 #include <cmath>
 #include <cstring>
 #include <limits>
+#include <complex>
+#include <algorithm>
 
 // Options
-#define MPREAL_HAVE_INT64_SUPPORT               // Enable int64_t support if possible. Available only for MSVC 2010 & GCC. 
 #define MPREAL_HAVE_MSVC_DEBUGVIEW              // Enable Debugger Visualizer for "Debug" builds in MSVC.
 #define MPREAL_HAVE_DYNAMIC_STD_NUMERIC_LIMITS  // Enable extended std::numeric_limits<mpfr::mpreal> specialization.
                                                 // Meaning that "digits", "round_style" and similar members are defined as functions, not constants.
                                                 // See std::numeric_limits<mpfr::mpreal> at the end of the file for more information.
 
 // Library version
 #define MPREAL_VERSION_MAJOR 3
-#define MPREAL_VERSION_MINOR 5
-#define MPREAL_VERSION_PATCHLEVEL 9
-#define MPREAL_VERSION_STRING "3.5.9"
+#define MPREAL_VERSION_MINOR 6
+#define MPREAL_VERSION_PATCHLEVEL 2
+#define MPREAL_VERSION_STRING "3.6.2"
 
 // Detect compiler using signatures from http://predef.sourceforge.net/
-#if defined(__GNUC__) && defined(__INTEL_COMPILER)
-    #define IsInf(x) isinf(x)                   // Intel ICC compiler on Linux 
-
-#elif defined(_MSC_VER)                         // Microsoft Visual C++ 
-    #define IsInf(x) (!_finite(x))                           
-
+#if defined(__GNUC__)
+    #define IsInf(x) (isinf)(x)                 // GNU C++/Intel ICC compiler on Linux
+#elif defined(_MSC_VER)                         // Microsoft Visual C++
+    #define IsInf(x) (!_finite(x))
 #else
-    #define IsInf(x) std::isinf(x)              // GNU C/C++ (and/or other compilers), just hope for C99 conformance
+    #define IsInf(x) (std::isinf)(x)              // GNU C/C++ (and/or other compilers), just hope for C99 conformance
 #endif
 
 // A Clang feature extension to determine compiler features.
 #ifndef __has_feature
     #define __has_feature(x) 0
@@ -90,70 +90,49 @@
        defined(__GXX_EXPERIMENTAL_CXX0X__) || __cplusplus >= 201103L || \
       (defined(_MSC_VER) && _MSC_VER >= 1600))
 
     #define MPREAL_HAVE_MOVE_SUPPORT
 
-    // Use fields in mpfr_t structure to check if it was initialized / set dummy initialization 
+    // Use fields in mpfr_t structure to check if it was initialized / set dummy initialization
     #define mpfr_is_initialized(x)      (0 != (x)->_mpfr_d)
     #define mpfr_set_uninitialized(x)   ((x)->_mpfr_d = 0 )
 #endif
 
-// Detect support for explicit converters. 
+// Detect support for explicit converters.
 #if (__has_feature(cxx_explicit_conversions) || \
-       defined(__GXX_EXPERIMENTAL_CXX0X__) || __cplusplus >= 201103L || \
-      (defined(_MSC_VER) && _MSC_VER >= 1800))
+       (defined(__GXX_EXPERIMENTAL_CXX0X__) && __GNUC_MINOR__ >= 5) || __cplusplus >= 201103L || \
+       (defined(_MSC_VER) && _MSC_VER >= 1800))
 
     #define MPREAL_HAVE_EXPLICIT_CONVERTERS
 #endif
 
-// Detect available 64-bit capabilities
-#if defined(MPREAL_HAVE_INT64_SUPPORT)
-    
-    #define MPFR_USE_INTMAX_T                   // Should be defined before mpfr.h
-
-    #if defined(_MSC_VER)                       // MSVC + Windows
-        #if (_MSC_VER >= 1600)                    
-            #include <stdint.h>                 // <stdint.h> is available only in msvc2010!
-
-        #else                                   // MPFR relies on intmax_t which is available only in msvc2010
-            #undef MPREAL_HAVE_INT64_SUPPORT    // Besides, MPFR & MPIR have to be compiled with msvc2010
-            #undef MPFR_USE_INTMAX_T            // Since we cannot detect this, disable x64 by default
-                                                // Someone should change this manually if needed.
-        #endif
-
-    #elif defined (__GNUC__) && defined(__linux__)
-        #if defined(__amd64__) || defined(__amd64) || defined(__x86_64__) || defined(__x86_64) || defined(__ia64) || defined(__itanium__) || defined(_M_IA64) || defined (__PPC64__)
-            #undef MPREAL_HAVE_INT64_SUPPORT    // Remove all shaman dances for x64 builds since
-            #undef MPFR_USE_INTMAX_T            // GCC already supports x64 as of "long int" is 64-bit integer, nothing left to do
-        #else
-            #include <stdint.h>                 // use int64_t, uint64_t otherwise
-        #endif
-
-    #else
-        #include <stdint.h>                     // rely on int64_t, uint64_t in all other cases, Mac OSX, etc.
-    #endif
-
-#endif 
+#define MPFR_USE_INTMAX_T   // Enable 64-bit integer types - should be defined before mpfr.h
 
 #if defined(MPREAL_HAVE_MSVC_DEBUGVIEW) && defined(_MSC_VER) && defined(_DEBUG)
     #define MPREAL_MSVC_DEBUGVIEW_CODE     DebugView = toString();
     #define MPREAL_MSVC_DEBUGVIEW_DATA     std::string DebugView;
 #else
-    #define MPREAL_MSVC_DEBUGVIEW_CODE 
-    #define MPREAL_MSVC_DEBUGVIEW_DATA 
+    #define MPREAL_MSVC_DEBUGVIEW_CODE
+    #define MPREAL_MSVC_DEBUGVIEW_DATA
 #endif
 
 #include <mpfr.h>
 
 #if (MPFR_VERSION < MPFR_VERSION_NUM(3,0,0))
     #include <cstdlib>                          // Needed for random()
 #endif
 
 // Less important options
-#define MPREAL_DOUBLE_BITS_OVERFLOW -1          // Triggers overflow exception during conversion to double if mpreal 
+#define MPREAL_DOUBLE_BITS_OVERFLOW -1          // Triggers overflow exception during conversion to double if mpreal
                                                 // cannot fit in MPREAL_DOUBLE_BITS_OVERFLOW bits
                                                 // = -1 disables overflow checks (default)
+
+// Fast replacement for mpfr_set_zero(x, +1):
+// (a) uses low-level data members, might not be compatible with new versions of MPFR
+// (b) sign is not set, add (x)->_mpfr_sign = 1;
+#define mpfr_set_zero_fast(x)  ((x)->_mpfr_exp = __MPFR_EXP_ZERO)
+
 #if defined(__GNUC__)
   #define MPREAL_PERMISSIVE_EXPR __extension__
 #else
   #define MPREAL_PERMISSIVE_EXPR
 #endif
@@ -161,68 +140,68 @@
 namespace mpfr {
 
 class mpreal {
 private:
     mpfr_t mp;
-    
+
 public:
-    
+
     // Get default rounding mode & precision
     inline static mp_rnd_t   get_default_rnd()    {    return (mp_rnd_t)(mpfr_get_default_rounding_mode());       }
     inline static mp_prec_t  get_default_prec()   {    return mpfr_get_default_prec();                            }
 
     // Constructors && type conversions
     mpreal();
     mpreal(const mpreal& u);
-    mpreal(const mpf_t u);    
-    mpreal(const mpz_t u,             mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());    
-    mpreal(const mpq_t u,             mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());    
-    mpreal(const double u,            mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
-    mpreal(const long double u,       mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
-    mpreal(const unsigned long int u, mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
-    mpreal(const unsigned int u,      mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
-    mpreal(const long int u,          mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
-    mpreal(const int u,               mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
-    
+    mpreal(const mpf_t u);
+    mpreal(const mpz_t u,                  mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const mpq_t u,                  mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const double u,                 mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const long double u,            mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const unsigned long long int u, mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const long long int u,          mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const unsigned long int u,      mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const unsigned int u,           mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const long int u,               mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+    mpreal(const int u,                    mp_prec_t prec = mpreal::get_default_prec(), mp_rnd_t mode = mpreal::get_default_rnd());
+
     // Construct mpreal from mpfr_t structure.
-    // shared = true allows to avoid deep copy, so that mpreal and 'u' share the same data & pointers.    
-    mpreal(const mpfr_t  u, bool shared = false);   
-
-#if defined (MPREAL_HAVE_INT64_SUPPORT)
-    mpreal(const uint64_t u,          mp_prec_t prec = mpreal::get_default_prec(),  mp_rnd_t mode = mpreal::get_default_rnd());
-    mpreal(const int64_t u,           mp_prec_t prec = mpreal::get_default_prec(),  mp_rnd_t mode = mpreal::get_default_rnd());
-#endif
+    // shared = true allows to avoid deep copy, so that mpreal and 'u' share the same data & pointers.
+    mpreal(const mpfr_t  u, bool shared = false);
 
     mpreal(const char* s,             mp_prec_t prec = mpreal::get_default_prec(), int base = 10, mp_rnd_t mode = mpreal::get_default_rnd());
     mpreal(const std::string& s,      mp_prec_t prec = mpreal::get_default_prec(), int base = 10, mp_rnd_t mode = mpreal::get_default_rnd());
 
-    ~mpreal();                           
+    ~mpreal();
 
 #ifdef MPREAL_HAVE_MOVE_SUPPORT
     mpreal& operator=(mpreal&& v);
     mpreal(mpreal&& u);
 #endif
 
     // Operations
     // =
-    // +, -, *, /, ++, --, <<, >> 
+    // +, -, *, /, ++, --, <<, >>
     // *=, +=, -=, /=,
     // <, >, ==, <=, >=
 
     // =
     mpreal& operator=(const mpreal& v);
     mpreal& operator=(const mpf_t v);
     mpreal& operator=(const mpz_t v);
     mpreal& operator=(const mpq_t v);
     mpreal& operator=(const long double v);
-    mpreal& operator=(const double v);        
+    mpreal& operator=(const double v);
     mpreal& operator=(const unsigned long int v);
+    mpreal& operator=(const unsigned long long int v);
+    mpreal& operator=(const long long int v);
     mpreal& operator=(const unsigned int v);
     mpreal& operator=(const long int v);
     mpreal& operator=(const int v);
     mpreal& operator=(const char* s);
     mpreal& operator=(const std::string& s);
+    template <typename real_t> mpreal& operator= (const std::complex<real_t>& z);
 
     // +
     mpreal& operator+=(const mpreal& v);
     mpreal& operator+=(const mpf_t v);
     mpreal& operator+=(const mpz_t v);
@@ -232,24 +211,22 @@
     mpreal& operator+=(const unsigned long int u);
     mpreal& operator+=(const unsigned int u);
     mpreal& operator+=(const long int u);
     mpreal& operator+=(const int u);
 
-#if defined (MPREAL_HAVE_INT64_SUPPORT)
-    mpreal& operator+=(const int64_t  u);
-    mpreal& operator+=(const uint64_t u);
-    mpreal& operator-=(const int64_t  u);
-    mpreal& operator-=(const uint64_t u);
-    mpreal& operator*=(const int64_t  u);
-    mpreal& operator*=(const uint64_t u);
-    mpreal& operator/=(const int64_t  u);
-    mpreal& operator/=(const uint64_t u);
-#endif 
+    mpreal& operator+=(const long long int  u);
+    mpreal& operator+=(const unsigned long long int u);
+    mpreal& operator-=(const long long int  u);
+    mpreal& operator-=(const unsigned long long int u);
+    mpreal& operator*=(const long long int  u);
+    mpreal& operator*=(const unsigned long long int u);
+    mpreal& operator/=(const long long int  u);
+    mpreal& operator/=(const unsigned long long int u);
 
     const mpreal operator+() const;
     mpreal& operator++ ();
-    const mpreal  operator++ (int); 
+    const mpreal  operator++ (int);
 
     // -
     mpreal& operator-=(const mpreal& v);
     mpreal& operator-=(const mpz_t v);
     mpreal& operator-=(const mpq_t v);
@@ -263,11 +240,11 @@
     friend const mpreal operator-(const unsigned long int b, const mpreal& a);
     friend const mpreal operator-(const unsigned int b,      const mpreal& a);
     friend const mpreal operator-(const long int b,          const mpreal& a);
     friend const mpreal operator-(const int b,               const mpreal& a);
     friend const mpreal operator-(const double b,            const mpreal& a);
-    mpreal& operator-- ();    
+    mpreal& operator-- ();
     const mpreal  operator-- (int);
 
     // *
     mpreal& operator*=(const mpreal& v);
     mpreal& operator*=(const mpz_t v);
@@ -276,11 +253,11 @@
     mpreal& operator*=(const double v);
     mpreal& operator*=(const unsigned long int v);
     mpreal& operator*=(const unsigned int v);
     mpreal& operator*=(const long int v);
     mpreal& operator*=(const int v);
-    
+
     // /
     mpreal& operator/=(const mpreal& v);
     mpreal& operator/=(const mpz_t v);
     mpreal& operator/=(const mpq_t v);
     mpreal& operator/=(const long double v);
@@ -305,55 +282,31 @@
     mpreal& operator>>=(const unsigned long int u);
     mpreal& operator>>=(const unsigned int u);
     mpreal& operator>>=(const long int u);
     mpreal& operator>>=(const int u);
 
-    // Boolean Operators
-    friend bool operator >  (const mpreal& a, const mpreal& b);
-    friend bool operator >= (const mpreal& a, const mpreal& b);
-    friend bool operator <  (const mpreal& a, const mpreal& b);
-    friend bool operator <= (const mpreal& a, const mpreal& b);
-    friend bool operator == (const mpreal& a, const mpreal& b);
-    friend bool operator != (const mpreal& a, const mpreal& b);
-
-    // Optimized specializations for boolean operators
-    friend bool operator == (const mpreal& a, const unsigned long int b);
-    friend bool operator == (const mpreal& a, const unsigned int b);
-    friend bool operator == (const mpreal& a, const long int b);
-    friend bool operator == (const mpreal& a, const int b);
-    friend bool operator == (const mpreal& a, const long double b);
-    friend bool operator == (const mpreal& a, const double b);
-
-    // Type Conversion operators
-    bool            toBool      (mp_rnd_t mode = GMP_RNDZ)    const;
-    long            toLong      (mp_rnd_t mode = GMP_RNDZ)    const;
-    unsigned long   toULong     (mp_rnd_t mode = GMP_RNDZ)    const;
-    float           toFloat     (mp_rnd_t mode = GMP_RNDN)    const;
-    double          toDouble    (mp_rnd_t mode = GMP_RNDN)    const;
-    long double     toLDouble   (mp_rnd_t mode = GMP_RNDN)    const;
-
-#if defined (MPREAL_HAVE_EXPLICIT_CONVERTERS)
-    explicit operator bool               () const { return toBool();       }
-    explicit operator int                () const { return toLong();       }
-    explicit operator long               () const { return toLong();       }
-    explicit operator long long          () const { return toLong();       }
-    explicit operator unsigned           () const { return toULong();      }
-    explicit operator unsigned long      () const { return toULong();      }
-    explicit operator unsigned long long () const { return toULong();      }
-    explicit operator float              () const { return toFloat();      }
-    explicit operator double             () const { return toDouble();     }
-    explicit operator long double        () const { return toLDouble();    }
-#endif
-
-#if defined (MPREAL_HAVE_INT64_SUPPORT)
-    int64_t         toInt64     (mp_rnd_t mode = GMP_RNDZ)    const;
-    uint64_t        toUInt64    (mp_rnd_t mode = GMP_RNDZ)    const;
-
-    #if defined (MPREAL_HAVE_EXPLICIT_CONVERTERS)
-    explicit operator int64_t   () const { return toInt64();      }
-    explicit operator uint64_t  () const { return toUInt64();     }
-    #endif
+    // Type Conversion operators
+    bool               toBool      (                        )    const;
+    long               toLong      (mp_rnd_t mode = GMP_RNDZ)    const;
+    unsigned long      toULong     (mp_rnd_t mode = GMP_RNDZ)    const;
+    long long          toLLong     (mp_rnd_t mode = GMP_RNDZ)    const;
+    unsigned long long toULLong    (mp_rnd_t mode = GMP_RNDZ)    const;
+    float              toFloat     (mp_rnd_t mode = GMP_RNDN)    const;
+    double             toDouble    (mp_rnd_t mode = GMP_RNDN)    const;
+    long double        toLDouble   (mp_rnd_t mode = GMP_RNDN)    const;
+
+#if defined (MPREAL_HAVE_EXPLICIT_CONVERTERS)
+    explicit operator bool               () const { return toBool();                 }
+    explicit operator int                () const { return int(toLong());            }
+    explicit operator long               () const { return toLong();                 }
+    explicit operator long long          () const { return toLLong();                }
+    explicit operator unsigned           () const { return unsigned(toULong());      }
+    explicit operator unsigned long      () const { return toULong();                }
+    explicit operator unsigned long long () const { return toULLong();               }
+    explicit operator float              () const { return toFloat();                }
+    explicit operator double             () const { return toDouble();               }
+    explicit operator long double        () const { return toLDouble();              }
 #endif
 
     // Get raw pointers so that mpreal can be directly used in raw mpfr_* functions
     ::mpfr_ptr    mpfr_ptr();
     ::mpfr_srcptr mpfr_ptr()    const;
@@ -388,15 +341,16 @@
     friend inline const mpreal mul_2ui(const mpreal& v, unsigned long int k, mp_rnd_t rnd_mode);
     friend inline const mpreal mul_2si(const mpreal& v, long int k, mp_rnd_t rnd_mode);
     friend inline const mpreal div_2ui(const mpreal& v, unsigned long int k, mp_rnd_t rnd_mode);
     friend inline const mpreal div_2si(const mpreal& v, long int k, mp_rnd_t rnd_mode);
     friend int cmpabs(const mpreal& a,const mpreal& b);
-    
+
     friend const mpreal log  (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal log2 (const mpreal& v, mp_rnd_t rnd_mode);
+    friend const mpreal logb (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal log10(const mpreal& v, mp_rnd_t rnd_mode);
-    friend const mpreal exp  (const mpreal& v, mp_rnd_t rnd_mode); 
+    friend const mpreal exp  (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal exp2 (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal exp10(const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal log1p(const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal expm1(const mpreal& v, mp_rnd_t rnd_mode);
 
@@ -433,25 +387,26 @@
 
     friend const mpreal fac_ui (unsigned long int v,  mp_prec_t prec, mp_rnd_t rnd_mode);
     friend const mpreal eint   (const mpreal& v, mp_rnd_t rnd_mode);
 
     friend const mpreal gamma    (const mpreal& v, mp_rnd_t rnd_mode);
+    friend const mpreal tgamma   (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal lngamma  (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal lgamma   (const mpreal& v, int *signp, mp_rnd_t rnd_mode);
     friend const mpreal zeta     (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal erf      (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal erfc     (const mpreal& v, mp_rnd_t rnd_mode);
-    friend const mpreal besselj0 (const mpreal& v, mp_rnd_t rnd_mode); 
-    friend const mpreal besselj1 (const mpreal& v, mp_rnd_t rnd_mode); 
+    friend const mpreal besselj0 (const mpreal& v, mp_rnd_t rnd_mode);
+    friend const mpreal besselj1 (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal besseljn (long n, const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal bessely0 (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal bessely1 (const mpreal& v, mp_rnd_t rnd_mode);
-    friend const mpreal besselyn (long n, const mpreal& v, mp_rnd_t rnd_mode); 
+    friend const mpreal besselyn (long n, const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal fma      (const mpreal& v1, const mpreal& v2, const mpreal& v3, mp_rnd_t rnd_mode);
     friend const mpreal fms      (const mpreal& v1, const mpreal& v2, const mpreal& v3, mp_rnd_t rnd_mode);
     friend const mpreal agm      (const mpreal& v1, const mpreal& v2, mp_rnd_t rnd_mode);
-    friend const mpreal sum      (const mpreal tab[], unsigned long int n, mp_rnd_t rnd_mode);
+    friend const mpreal sum      (const mpreal tab[], const unsigned long int n, int& status, mp_rnd_t rnd_mode);
     friend int sgn(const mpreal& v); // returns -1 or +1
 
 // MPFR 2.4.0 Specifics
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0))
     friend int          sinh_cosh   (mpreal& s, mpreal& c, const mpreal& v, mp_rnd_t rnd_mode);
@@ -462,32 +417,30 @@
     // MATLAB's semantic equivalents
     friend const mpreal rem (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode); // Remainder after division
     friend const mpreal mod (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode); // Modulus after division
 #endif
 
-// MPFR 3.0.0 Specifics
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0))
     friend const mpreal digamma (const mpreal& v,        mp_rnd_t rnd_mode);
     friend const mpreal ai      (const mpreal& v,        mp_rnd_t rnd_mode);
     friend const mpreal urandom (gmp_randstate_t& state, mp_rnd_t rnd_mode);     // use gmp_randinit_default() to init state, gmp_randclear() to clear
+#endif
+
+#if (MPFR_VERSION >= MPFR_VERSION_NUM(3,1,0))
     friend const mpreal grandom (gmp_randstate_t& state, mp_rnd_t rnd_mode);     // use gmp_randinit_default() to init state, gmp_randclear() to clear
     friend const mpreal grandom (unsigned int seed);
 #endif
-    
+
     // Uniformly distributed random number generation in [0,1] using
     // Mersenne-Twister algorithm by default.
     // Use parameter to setup seed, e.g.: random((unsigned)time(NULL))
     // Check urandom() for more precise control.
     friend const mpreal random(unsigned int seed);
 
-    // Exponent and mantissa manipulation
-    friend const mpreal frexp(const mpreal& v, mp_exp_t* exp);    
-    friend const mpreal ldexp(const mpreal& v, mp_exp_t exp);
-
     // Splits mpreal value into fractional and integer parts.
     // Returns fractional part and stores integer part in n.
-    friend const mpreal modf(const mpreal& v, mpreal& n);    
+    friend const mpreal modf(const mpreal& v, mpreal& n);
 
     // Constants
     // don't forget to call mpfr_free_cache() for every thread where you are using const-functions
     friend const mpreal const_log2      (mp_prec_t prec, mp_rnd_t rnd_mode);
     friend const mpreal const_pi        (mp_prec_t prec, mp_rnd_t rnd_mode);
@@ -512,28 +465,28 @@
     friend const mpreal rint_round  (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal rint_trunc  (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal frac        (const mpreal& v, mp_rnd_t rnd_mode);
     friend const mpreal remainder   (         const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode);
     friend const mpreal remquo      (long* q, const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode);
-    
+
     // Miscellaneous Functions
     friend const mpreal nexttoward (const mpreal& x, const mpreal& y);
     friend const mpreal nextabove  (const mpreal& x);
     friend const mpreal nextbelow  (const mpreal& x);
 
     // use gmp_randinit_default() to init state, gmp_randclear() to clear
-    friend const mpreal urandomb (gmp_randstate_t& state); 
+    friend const mpreal urandomb (gmp_randstate_t& state);
 
 // MPFR < 2.4.2 Specifics
 #if (MPFR_VERSION <= MPFR_VERSION_NUM(2,4,2))
     friend const mpreal random2 (mp_size_t size, mp_exp_t exp);
 #endif
 
     // Instance Checkers
-    friend bool isnan    (const mpreal& v);
-    friend bool isinf    (const mpreal& v);
-    friend bool isfinite (const mpreal& v);
+    friend bool (isnan)    (const mpreal& v);
+    friend bool (isinf)    (const mpreal& v);
+    friend bool (isfinite) (const mpreal& v);
 
     friend bool isnum    (const mpreal& v);
     friend bool iszero   (const mpreal& v);
     friend bool isint    (const mpreal& v);
 
@@ -546,22 +499,22 @@
     inline void         set_prec(mp_prec_t prec, mp_rnd_t rnd_mode = get_default_rnd());    // Change precision with rounding mode
 
     // Aliases for get_prec(), set_prec() - needed for compatibility with std::complex<mpreal> interface
     inline mpreal&      setPrecision(int Precision, mp_rnd_t RoundingMode = get_default_rnd());
     inline int          getPrecision() const;
-    
+
     // Set mpreal to +/- inf, NaN, +/-0
-    mpreal&        setInf  (int Sign = +1);    
+    mpreal&        setInf  (int Sign = +1);
     mpreal&        setNan  ();
     mpreal&        setZero (int Sign = +1);
     mpreal&        setSign (int Sign, mp_rnd_t RoundingMode = get_default_rnd());
 
     //Exponent
     mp_exp_t get_exp();
     int set_exp(mp_exp_t e);
     int check_range  (int t, mp_rnd_t rnd_mode = get_default_rnd());
-    int subnormalize (int t,mp_rnd_t rnd_mode = get_default_rnd());
+    int subnormalize (int t, mp_rnd_t rnd_mode = get_default_rnd());
 
     // Inexact conversion from float
     inline bool fits_in_bits(double x, int n);
 
     // Set/Get global properties
@@ -577,21 +530,21 @@
     static int       set_emin (mp_exp_t exp);
     static int       set_emax (mp_exp_t exp);
 
     // Efficient swapping of two mpreal values - needed for std algorithms
     friend void swap(mpreal& x, mpreal& y);
-    
+
     friend const mpreal fmax(const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode);
     friend const mpreal fmin(const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode);
 
 private:
     // Human friendly Debug Preview in Visual Studio.
     // Put one of these lines:
     //
     // mpfr::mpreal=<DebugView>                              ; Show value only
     // mpfr::mpreal=<DebugView>, <mp[0]._mpfr_prec,u>bits    ; Show value & precision
-    // 
+    //
     // at the beginning of
     // [Visual Studio Installation Folder]\Common7\Packages\Debugger\autoexp.dat
     MPREAL_MSVC_DEBUGVIEW_DATA
 
     // "Smart" resources deallocation. Checks if instance initialized before deletion.
@@ -606,19 +559,19 @@
 };
 
 //////////////////////////////////////////////////////////////////////////
 // Constructors & converters
 // Default constructor: creates mp number and initializes it to 0.
-inline mpreal::mpreal() 
-{ 
-    mpfr_init2 (mpfr_ptr(), mpreal::get_default_prec()); 
-    mpfr_set_ui(mpfr_ptr(), 0, mpreal::get_default_rnd());
+inline mpreal::mpreal()
+{
+    mpfr_init2(mpfr_ptr(), mpreal::get_default_prec());
+    mpfr_set_zero_fast(mpfr_ptr());
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
-inline mpreal::mpreal(const mpreal& u) 
+inline mpreal::mpreal(const mpreal& u)
 {
     mpfr_init2(mpfr_ptr(),mpfr_get_prec(u.mpfr_srcptr()));
     mpfr_set  (mpfr_ptr(),u.mpfr_srcptr(),mpreal::get_default_rnd());
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
@@ -625,11 +578,11 @@
 }
 
 #ifdef MPREAL_HAVE_MOVE_SUPPORT
 inline mpreal::mpreal(mpreal&& other)
 {
-    mpfr_set_uninitialized(mpfr_ptr());     // make sure "other" holds no pinter to actual data 
+    mpfr_set_uninitialized(mpfr_ptr());     // make sure "other" holds no pointer to actual data
     mpfr_swap(mpfr_ptr(), other.mpfr_ptr());
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
@@ -697,154 +650,149 @@
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
 inline mpreal::mpreal(const long double u, mp_prec_t prec, mp_rnd_t mode)
-{ 
+{
     mpfr_init2 (mpfr_ptr(), prec);
     mpfr_set_ld(mpfr_ptr(), u, mode);
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
+
+inline mpreal::mpreal(const unsigned long long int u, mp_prec_t prec, mp_rnd_t mode)
+{
+    mpfr_init2 (mpfr_ptr(), prec);
+    mpfr_set_uj(mpfr_ptr(), u, mode);
+
+    MPREAL_MSVC_DEBUGVIEW_CODE;
+}
+
+inline mpreal::mpreal(const long long int u, mp_prec_t prec, mp_rnd_t mode)
+{
+    mpfr_init2 (mpfr_ptr(), prec);
+    mpfr_set_sj(mpfr_ptr(), u, mode);
+
+    MPREAL_MSVC_DEBUGVIEW_CODE;
+}
 
 inline mpreal::mpreal(const unsigned long int u, mp_prec_t prec, mp_rnd_t mode)
-{ 
+{
     mpfr_init2 (mpfr_ptr(), prec);
     mpfr_set_ui(mpfr_ptr(), u, mode);
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
 inline mpreal::mpreal(const unsigned int u, mp_prec_t prec, mp_rnd_t mode)
-{ 
+{
     mpfr_init2 (mpfr_ptr(), prec);
     mpfr_set_ui(mpfr_ptr(), u, mode);
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
 inline mpreal::mpreal(const long int u, mp_prec_t prec, mp_rnd_t mode)
-{ 
+{
     mpfr_init2 (mpfr_ptr(), prec);
     mpfr_set_si(mpfr_ptr(), u, mode);
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
 inline mpreal::mpreal(const int u, mp_prec_t prec, mp_rnd_t mode)
-{ 
+{
     mpfr_init2 (mpfr_ptr(), prec);
     mpfr_set_si(mpfr_ptr(), u, mode);
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
-#if defined (MPREAL_HAVE_INT64_SUPPORT)
-inline mpreal::mpreal(const uint64_t u, mp_prec_t prec, mp_rnd_t mode)
-{
-    mpfr_init2 (mpfr_ptr(), prec);
-    mpfr_set_uj(mpfr_ptr(), u, mode); 
-
-    MPREAL_MSVC_DEBUGVIEW_CODE;
-}
-
-inline mpreal::mpreal(const int64_t u, mp_prec_t prec, mp_rnd_t mode)
-{
-    mpfr_init2 (mpfr_ptr(), prec);
-    mpfr_set_sj(mpfr_ptr(), u, mode); 
-
-    MPREAL_MSVC_DEBUGVIEW_CODE;
-}
-#endif
-
 inline mpreal::mpreal(const char* s, mp_prec_t prec, int base, mp_rnd_t mode)
 {
     mpfr_init2  (mpfr_ptr(), prec);
-    mpfr_set_str(mpfr_ptr(), s, base, mode); 
+    mpfr_set_str(mpfr_ptr(), s, base, mode);
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
 inline mpreal::mpreal(const std::string& s, mp_prec_t prec, int base, mp_rnd_t mode)
 {
     mpfr_init2  (mpfr_ptr(), prec);
-    mpfr_set_str(mpfr_ptr(), s.c_str(), base, mode); 
+    mpfr_set_str(mpfr_ptr(), s.c_str(), base, mode);
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
 }
 
 inline void mpreal::clear(::mpfr_ptr x)
 {
 #ifdef MPREAL_HAVE_MOVE_SUPPORT
-    if(mpfr_is_initialized(x)) 
+    if(mpfr_is_initialized(x))
 #endif
     mpfr_clear(x);
 }
 
-inline mpreal::~mpreal() 
-{ 
+inline mpreal::~mpreal()
+{
     clear(mpfr_ptr());
-}                           
+}
 
 // internal namespace needed for template magic
 namespace internal{
 
     // Use SFINAE to restrict arithmetic operations instantiation only for numeric types
     // This is needed for smooth integration with libraries based on expression templates, like Eigen.
     // TODO: Do the same for boolean operators.
-    template <typename ArgumentType> struct result_type {};    
-    
-    template <> struct result_type<mpreal>              {typedef mpreal type;};    
-    template <> struct result_type<mpz_t>               {typedef mpreal type;};    
-    template <> struct result_type<mpq_t>               {typedef mpreal type;};    
-    template <> struct result_type<long double>         {typedef mpreal type;};    
-    template <> struct result_type<double>              {typedef mpreal type;};    
-    template <> struct result_type<unsigned long int>   {typedef mpreal type;};    
-    template <> struct result_type<unsigned int>        {typedef mpreal type;};    
-    template <> struct result_type<long int>            {typedef mpreal type;};    
-    template <> struct result_type<int>                 {typedef mpreal type;};    
-
-#if defined (MPREAL_HAVE_INT64_SUPPORT)
-    template <> struct result_type<int64_t  >           {typedef mpreal type;};    
-    template <> struct result_type<uint64_t >           {typedef mpreal type;};    
-#endif
+    template <typename ArgumentType> struct result_type {};
+
+    template <> struct result_type<mpreal>              {typedef mpreal type;};
+    template <> struct result_type<mpz_t>               {typedef mpreal type;};
+    template <> struct result_type<mpq_t>               {typedef mpreal type;};
+    template <> struct result_type<long double>         {typedef mpreal type;};
+    template <> struct result_type<double>              {typedef mpreal type;};
+    template <> struct result_type<unsigned long int>   {typedef mpreal type;};
+    template <> struct result_type<unsigned int>        {typedef mpreal type;};
+    template <> struct result_type<long int>            {typedef mpreal type;};
+    template <> struct result_type<int>                 {typedef mpreal type;};
+    template <> struct result_type<long long>           {typedef mpreal type;};
+    template <> struct result_type<unsigned long long>  {typedef mpreal type;};
 }
 
 // + Addition
-template <typename Rhs> 
-inline const typename internal::result_type<Rhs>::type 
+template <typename Rhs>
+inline const typename internal::result_type<Rhs>::type
     operator+(const mpreal& lhs, const Rhs& rhs){ return mpreal(lhs) += rhs;    }
 
-template <typename Lhs> 
-inline const typename internal::result_type<Lhs>::type 
-    operator+(const Lhs& lhs, const mpreal& rhs){ return mpreal(rhs) += lhs;    } 
+template <typename Lhs>
+inline const typename internal::result_type<Lhs>::type
+    operator+(const Lhs& lhs, const mpreal& rhs){ return mpreal(rhs) += lhs;    }
 
 // - Subtraction
-template <typename Rhs> 
-inline const typename internal::result_type<Rhs>::type 
+template <typename Rhs>
+inline const typename internal::result_type<Rhs>::type
     operator-(const mpreal& lhs, const Rhs& rhs){ return mpreal(lhs) -= rhs;    }
 
-template <typename Lhs> 
-inline const typename internal::result_type<Lhs>::type 
+template <typename Lhs>
+inline const typename internal::result_type<Lhs>::type
     operator-(const Lhs& lhs, const mpreal& rhs){ return mpreal(lhs) -= rhs;    }
 
 // * Multiplication
-template <typename Rhs> 
-inline const typename internal::result_type<Rhs>::type 
+template <typename Rhs>
+inline const typename internal::result_type<Rhs>::type
     operator*(const mpreal& lhs, const Rhs& rhs){ return mpreal(lhs) *= rhs;    }
 
-template <typename Lhs> 
-inline const typename internal::result_type<Lhs>::type 
-    operator*(const Lhs& lhs, const mpreal& rhs){ return mpreal(rhs) *= lhs;    } 
+template <typename Lhs>
+inline const typename internal::result_type<Lhs>::type
+    operator*(const Lhs& lhs, const mpreal& rhs){ return mpreal(rhs) *= lhs;    }
 
 // / Division
-template <typename Rhs> 
-inline const typename internal::result_type<Rhs>::type 
+template <typename Rhs>
+inline const typename internal::result_type<Rhs>::type
     operator/(const mpreal& lhs, const Rhs& rhs){ return mpreal(lhs) /= rhs;    }
 
-template <typename Lhs> 
-inline const typename internal::result_type<Lhs>::type 
+template <typename Lhs>
+inline const typename internal::result_type<Lhs>::type
     operator/(const Lhs& lhs, const mpreal& rhs){ return mpreal(lhs) /= rhs;    }
 
 //////////////////////////////////////////////////////////////////////////
 // sqrt
 const mpreal sqrt(const unsigned int v, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
@@ -890,21 +838,21 @@
 const mpreal pow(const long int a, const double b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 
 const mpreal pow(const int a, const unsigned long int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const int a, const unsigned int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const int a, const long int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
-const mpreal pow(const int a, const int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd()); 
+const mpreal pow(const int a, const int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const int a, const long double b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
-const mpreal pow(const int a, const double b, mp_rnd_t rnd_mode = mpreal::get_default_rnd()); 
+const mpreal pow(const int a, const double b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 
-const mpreal pow(const long double a, const long double b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());    
+const mpreal pow(const long double a, const long double b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const long double a, const unsigned long int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const long double a, const unsigned int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const long double a, const long int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const long double a, const int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 
-const mpreal pow(const double a, const double b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());    
+const mpreal pow(const double a, const double b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const double a, const unsigned long int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const double a, const unsigned int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const double a, const long int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 const mpreal pow(const double a, const int b, mp_rnd_t rnd_mode = mpreal::get_default_rnd());
 
@@ -917,13 +865,13 @@
 // Estimate machine epsilon for the given precision
 // Returns smallest eps such that 1.0 + eps != 1.0
 inline mpreal machine_epsilon(mp_prec_t prec = mpreal::get_default_prec());
 
 // Returns smallest eps such that x + eps != x (relative machine epsilon)
-inline mpreal machine_epsilon(const mpreal& x);        
+inline mpreal machine_epsilon(const mpreal& x);
 
-// Gives max & min values for the required precision, 
+// Gives max & min values for the required precision,
 // minval is 'safe' meaning 1 / minval does not overflow
 // maxval is 'safe' meaning 1 / maxval does not underflow
 inline mpreal minval(mp_prec_t prec = mpreal::get_default_prec());
 inline mpreal maxval(mp_prec_t prec = mpreal::get_default_prec());
 
@@ -932,17 +880,17 @@
 
 // 'Dirty' equality check 2: |a-b| < min{|a|,|b|} * eps( min{|a|,|b|} )
 inline bool isEqualFuzzy(const mpreal& a, const mpreal& b);
 
 // 'Bitwise' equality check
-//  maxUlps - a and b can be apart by maxUlps binary numbers. 
+//  maxUlps - a and b can be apart by maxUlps binary numbers.
 inline bool isEqualUlps(const mpreal& a, const mpreal& b, int maxUlps);
 
 //////////////////////////////////////////////////////////////////////////
-//     Convert precision in 'bits' to decimal digits and vice versa.
-//        bits   = ceil(digits*log[2](10))
-//        digits = floor(bits*log[10](2))
+// Convert precision in 'bits' to decimal digits and vice versa.
+//    bits   = ceil(digits*log[2](10))
+//    digits = floor(bits*log[10](2))
 
 inline mp_prec_t digits2bits(int d);
 inline int       bits2digits(mp_prec_t b);
 
 //////////////////////////////////////////////////////////////////////////
@@ -976,19 +924,19 @@
 }
 
 inline mpreal& mpreal::operator=(const mpf_t v)
 {
     mpfr_set_f(mpfr_ptr(), v, mpreal::get_default_rnd());
-    
+
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
 inline mpreal& mpreal::operator=(const mpz_t v)
 {
     mpfr_set_z(mpfr_ptr(), v, mpreal::get_default_rnd());
-    
+
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
 inline mpreal& mpreal::operator=(const mpq_t v)
@@ -997,20 +945,20 @@
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
-inline mpreal& mpreal::operator=(const long double v)        
-{    
+inline mpreal& mpreal::operator=(const long double v)
+{
     mpfr_set_ld(mpfr_ptr(), v, mpreal::get_default_rnd());
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
-inline mpreal& mpreal::operator=(const double v)                
-{   
+inline mpreal& mpreal::operator=(const double v)
+{
 #if (MPREAL_DOUBLE_BITS_OVERFLOW > -1)
   if(fits_in_bits(v, MPREAL_DOUBLE_BITS_OVERFLOW))
   {
     mpfr_set_d(mpfr_ptr(),v,mpreal::get_default_rnd());
   }else
@@ -1021,37 +969,53 @@
 
   MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
-inline mpreal& mpreal::operator=(const unsigned long int v)    
-{    
-    mpfr_set_ui(mpfr_ptr(), v, mpreal::get_default_rnd());    
+inline mpreal& mpreal::operator=(const unsigned long int v)
+{
+    mpfr_set_ui(mpfr_ptr(), v, mpreal::get_default_rnd());
+
+    MPREAL_MSVC_DEBUGVIEW_CODE;
+    return *this;
+}
+
+inline mpreal& mpreal::operator=(const unsigned int v)
+{
+    mpfr_set_ui(mpfr_ptr(), v, mpreal::get_default_rnd());
+
+    MPREAL_MSVC_DEBUGVIEW_CODE;
+    return *this;
+}
+
+inline mpreal& mpreal::operator=(const unsigned long long int v)
+{
+    mpfr_set_uj(mpfr_ptr(), v, mpreal::get_default_rnd());
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
-inline mpreal& mpreal::operator=(const unsigned int v)        
-{    
-    mpfr_set_ui(mpfr_ptr(), v, mpreal::get_default_rnd());    
+inline mpreal& mpreal::operator=(const long long int v)
+{
+    mpfr_set_sj(mpfr_ptr(), v, mpreal::get_default_rnd());
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
-inline mpreal& mpreal::operator=(const long int v)            
-{    
-    mpfr_set_si(mpfr_ptr(), v, mpreal::get_default_rnd());    
+inline mpreal& mpreal::operator=(const long int v)
+{
+    mpfr_set_si(mpfr_ptr(), v, mpreal::get_default_rnd());
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
 inline mpreal& mpreal::operator=(const int v)
-{    
-    mpfr_set_si(mpfr_ptr(), v, mpreal::get_default_rnd());    
+{
+    mpfr_set_si(mpfr_ptr(), v, mpreal::get_default_rnd());
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
@@ -1068,11 +1032,11 @@
 
     mpfr_init2(t, mpfr_get_prec(mpfr_srcptr()));
 
     if(0 == mpfr_set_str(t, s, 10, mpreal::get_default_rnd()))
     {
-        mpfr_set(mpfr_ptr(), t, mpreal::get_default_rnd()); 
+        mpfr_set(mpfr_ptr(), t, mpreal::get_default_rnd());
         MPREAL_MSVC_DEBUGVIEW_CODE;
     }
 
     clear(t);
     return *this;
@@ -1091,18 +1055,23 @@
 
     mpfr_init2(t, mpfr_get_prec(mpfr_srcptr()));
 
     if(0 == mpfr_set_str(t, s.c_str(), 10, mpreal::get_default_rnd()))
     {
-        mpfr_set(mpfr_ptr(), t, mpreal::get_default_rnd()); 
+        mpfr_set(mpfr_ptr(), t, mpreal::get_default_rnd());
         MPREAL_MSVC_DEBUGVIEW_CODE;
     }
 
     clear(t);
     return *this;
 }
 
+template <typename real_t>
+inline mpreal& mpreal::operator= (const std::complex<real_t>& z)
+{
+    return *this = z.real();
+}
 
 //////////////////////////////////////////////////////////////////////////
 // + Addition
 inline mpreal& mpreal::operator+=(const mpreal& v)
 {
@@ -1132,13 +1101,13 @@
     return *this;
 }
 
 inline mpreal& mpreal::operator+= (const long double u)
 {
-    *this += mpreal(u);    
+    *this += mpreal(u);
     MPREAL_MSVC_DEBUGVIEW_CODE;
-    return *this;    
+    return *this;
 }
 
 inline mpreal& mpreal::operator+= (const double u)
 {
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0))
@@ -1177,20 +1146,18 @@
     mpfr_add_si(mpfr_ptr(),mpfr_srcptr(),u,mpreal::get_default_rnd());
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
-#if defined (MPREAL_HAVE_INT64_SUPPORT)
-inline mpreal& mpreal::operator+=(const int64_t  u){    *this += mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
-inline mpreal& mpreal::operator+=(const uint64_t u){    *this += mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
-inline mpreal& mpreal::operator-=(const int64_t  u){    *this -= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
-inline mpreal& mpreal::operator-=(const uint64_t u){    *this -= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
-inline mpreal& mpreal::operator*=(const int64_t  u){    *this *= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
-inline mpreal& mpreal::operator*=(const uint64_t u){    *this *= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
-inline mpreal& mpreal::operator/=(const int64_t  u){    *this /= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
-inline mpreal& mpreal::operator/=(const uint64_t u){    *this /= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
-#endif 
+inline mpreal& mpreal::operator+=(const long long int u)         {    *this += mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
+inline mpreal& mpreal::operator+=(const unsigned long long int u){    *this += mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
+inline mpreal& mpreal::operator-=(const long long int  u)        {    *this -= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
+inline mpreal& mpreal::operator-=(const unsigned long long int u){    *this -= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
+inline mpreal& mpreal::operator*=(const long long int  u)        {    *this *= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
+inline mpreal& mpreal::operator*=(const unsigned long long int u){    *this *= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
+inline mpreal& mpreal::operator/=(const long long int  u)        {    *this /= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
+inline mpreal& mpreal::operator/=(const unsigned long long int u){    *this /= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this;    }
 
 inline const mpreal mpreal::operator+()const    {    return mpreal(*this); }
 
 inline const mpreal operator+(const mpreal& a, const mpreal& b)
 {
@@ -1197,11 +1164,11 @@
   mpreal c(0, (std::max)(mpfr_get_prec(a.mpfr_ptr()), mpfr_get_prec(b.mpfr_ptr())));
   mpfr_add(c.mpfr_ptr(), a.mpfr_srcptr(), b.mpfr_srcptr(), mpreal::get_default_rnd());
   return c;
 }
 
-inline mpreal& mpreal::operator++() 
+inline mpreal& mpreal::operator++()
 {
     return *this += 1;
 }
 
 inline const mpreal mpreal::operator++ (int)
@@ -1209,11 +1176,11 @@
     mpreal x(*this);
     *this += 1;
     return x;
 }
 
-inline mpreal& mpreal::operator--() 
+inline mpreal& mpreal::operator--()
 {
     return *this -= 1;
 }
 
 inline const mpreal mpreal::operator-- (int)
@@ -1246,21 +1213,21 @@
     return *this;
 }
 
 inline mpreal& mpreal::operator-=(const long double v)
 {
-    *this -= mpreal(v);    
+    *this -= mpreal(v);
     MPREAL_MSVC_DEBUGVIEW_CODE;
-    return *this;    
+    return *this;
 }
 
 inline mpreal& mpreal::operator-=(const double v)
 {
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0))
     mpfr_sub_d(mpfr_ptr(),mpfr_srcptr(),v,mpreal::get_default_rnd());
 #else
-    *this -= mpreal(v);    
+    *this -= mpreal(v);
 #endif
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
@@ -1371,21 +1338,21 @@
     return *this;
 }
 
 inline mpreal& mpreal::operator*=(const long double v)
 {
-    *this *= mpreal(v);    
+    *this *= mpreal(v);
     MPREAL_MSVC_DEBUGVIEW_CODE;
-    return *this;    
+    return *this;
 }
 
 inline mpreal& mpreal::operator*=(const double v)
 {
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0))
     mpfr_mul_d(mpfr_ptr(),mpfr_srcptr(),v,mpreal::get_default_rnd());
 #else
-    *this *= mpreal(v);    
+    *this *= mpreal(v);
 #endif
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
@@ -1449,19 +1416,19 @@
 
 inline mpreal& mpreal::operator/=(const long double v)
 {
     *this /= mpreal(v);
     MPREAL_MSVC_DEBUGVIEW_CODE;
-    return *this;    
+    return *this;
 }
 
 inline mpreal& mpreal::operator/=(const double v)
 {
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0))
     mpfr_div_d(mpfr_ptr(),mpfr_srcptr(),v,mpreal::get_default_rnd());
 #else
-    *this /= mpreal(v);    
+    *this /= mpreal(v);
 #endif
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
@@ -1668,49 +1635,90 @@
     mpfr_div_2si(x.mpfr_ptr(),v.mpfr_srcptr(),k,rnd_mode);
     return x;
 }
 
 //////////////////////////////////////////////////////////////////////////
-//Boolean operators
-inline bool operator >  (const mpreal& a, const mpreal& b){    return (mpfr_greater_p       (a.mpfr_srcptr(),b.mpfr_srcptr()) !=0 );    }
-inline bool operator >= (const mpreal& a, const mpreal& b){    return (mpfr_greaterequal_p  (a.mpfr_srcptr(),b.mpfr_srcptr()) !=0 );    }
-inline bool operator <  (const mpreal& a, const mpreal& b){    return (mpfr_less_p          (a.mpfr_srcptr(),b.mpfr_srcptr()) !=0 );    }
-inline bool operator <= (const mpreal& a, const mpreal& b){    return (mpfr_lessequal_p     (a.mpfr_srcptr(),b.mpfr_srcptr()) !=0 );    }
-inline bool operator == (const mpreal& a, const mpreal& b){    return (mpfr_equal_p         (a.mpfr_srcptr(),b.mpfr_srcptr()) !=0 );    }
-inline bool operator != (const mpreal& a, const mpreal& b){    return (mpfr_lessgreater_p   (a.mpfr_srcptr(),b.mpfr_srcptr()) !=0 );    }
-
-inline bool operator == (const mpreal& a, const unsigned long int b ){    return (mpfr_cmp_ui(a.mpfr_srcptr(),b) == 0 );    }
-inline bool operator == (const mpreal& a, const unsigned int b      ){    return (mpfr_cmp_ui(a.mpfr_srcptr(),b) == 0 );    }
-inline bool operator == (const mpreal& a, const long int b          ){    return (mpfr_cmp_si(a.mpfr_srcptr(),b) == 0 );    }
-inline bool operator == (const mpreal& a, const int b               ){    return (mpfr_cmp_si(a.mpfr_srcptr(),b) == 0 );    }
-inline bool operator == (const mpreal& a, const long double b       ){    return (mpfr_cmp_ld(a.mpfr_srcptr(),b) == 0 );    }
-inline bool operator == (const mpreal& a, const double b            ){    return (mpfr_cmp_d (a.mpfr_srcptr(),b) == 0 );    }
-
-
-inline bool isnan    (const mpreal& op){    return (mpfr_nan_p    (op.mpfr_srcptr()) != 0 );    }
-inline bool isinf    (const mpreal& op){    return (mpfr_inf_p    (op.mpfr_srcptr()) != 0 );    }
-inline bool isfinite (const mpreal& op){    return (mpfr_number_p (op.mpfr_srcptr()) != 0 );    }
+//Relational operators
+
+// WARNING:
+//
+// Please note that following checks for double-NaN are guaranteed to work only in IEEE math mode:
+//
+// isnan(b) =  (b != b)
+// isnan(b) = !(b == b)  (we use in code below)
+//
+// Be cautions if you use compiler options which break strict IEEE compliance (e.g. -ffast-math in GCC).
+// Use std::isnan instead (C++11).
+
+inline bool operator >  (const mpreal& a, const mpreal& b           ){  return (mpfr_greater_p(a.mpfr_srcptr(),b.mpfr_srcptr()) != 0 );            }
+inline bool operator >  (const mpreal& a, const unsigned long int b ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) > 0 );                 }
+inline bool operator >  (const mpreal& a, const unsigned int b      ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) > 0 );                 }
+inline bool operator >  (const mpreal& a, const long int b          ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) > 0 );                 }
+inline bool operator >  (const mpreal& a, const int b               ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) > 0 );                 }
+inline bool operator >  (const mpreal& a, const long double b       ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_ld(a.mpfr_srcptr(),b) > 0 );    }
+inline bool operator >  (const mpreal& a, const double b            ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_d (a.mpfr_srcptr(),b) > 0 );    }
+
+inline bool operator >= (const mpreal& a, const mpreal& b           ){  return (mpfr_greaterequal_p(a.mpfr_srcptr(),b.mpfr_srcptr()) != 0 );       }
+inline bool operator >= (const mpreal& a, const unsigned long int b ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) >= 0 );                }
+// inline bool operator >= (const mpreal& a, const unsigned int b      ){  return !isnan EIGEN_NOT_A_MACRO (isnan()a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) >= 0 );                }
+inline bool operator >= (const mpreal& a, const long int b          ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) >= 0 );                }
+inline bool operator >= (const mpreal& a, const int b               ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) >= 0 );                }
+inline bool operator >= (const mpreal& a, const long double b       ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_ld(a.mpfr_srcptr(),b) >= 0 );   }
+inline bool operator >= (const mpreal& a, const double b            ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_d (a.mpfr_srcptr(),b) >= 0 );   }
+
+inline bool operator <  (const mpreal& a, const mpreal& b           ){  return (mpfr_less_p(a.mpfr_srcptr(),b.mpfr_srcptr()) != 0 );               }
+inline bool operator <  (const mpreal& a, const unsigned long int b ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) < 0 );                 }
+inline bool operator <  (const mpreal& a, const unsigned int b      ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) < 0 );                 }
+inline bool operator <  (const mpreal& a, const long int b          ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) < 0 );                 }
+inline bool operator <  (const mpreal& a, const int b               ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) < 0 );                 }
+inline bool operator <  (const mpreal& a, const long double b       ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_ld(a.mpfr_srcptr(),b) < 0 );    }
+inline bool operator <  (const mpreal& a, const double b            ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_d (a.mpfr_srcptr(),b) < 0 );    }
+
+inline bool operator <= (const mpreal& a, const mpreal& b           ){  return (mpfr_lessequal_p(a.mpfr_srcptr(),b.mpfr_srcptr()) != 0 );          }
+inline bool operator <= (const mpreal& a, const unsigned long int b ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) <= 0 );                }
+inline bool operator <= (const mpreal& a, const unsigned int b      ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) <= 0 );                }
+inline bool operator <= (const mpreal& a, const long int b          ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) <= 0 );                }
+inline bool operator <= (const mpreal& a, const int b               ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) <= 0 );                }
+inline bool operator <= (const mpreal& a, const long double b       ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_ld(a.mpfr_srcptr(),b) <= 0 );   }
+inline bool operator <= (const mpreal& a, const double b            ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_d (a.mpfr_srcptr(),b) <= 0 );   }
+
+inline bool operator == (const mpreal& a, const mpreal& b           ){  return (mpfr_equal_p(a.mpfr_srcptr(),b.mpfr_srcptr()) != 0 );              }
+inline bool operator == (const mpreal& a, const unsigned long int b ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) == 0 );                }
+inline bool operator == (const mpreal& a, const unsigned int b      ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_ui(a.mpfr_srcptr(),b) == 0 );                }
+inline bool operator == (const mpreal& a, const long int b          ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) == 0 );                }
+inline bool operator == (const mpreal& a, const int b               ){  return !isnan EIGEN_NOT_A_MACRO (a) && (mpfr_cmp_si(a.mpfr_srcptr(),b) == 0 );                }
+inline bool operator == (const mpreal& a, const long double b       ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_ld(a.mpfr_srcptr(),b) == 0 );   }
+inline bool operator == (const mpreal& a, const double b            ){  return !isnan EIGEN_NOT_A_MACRO (a) && (b == b) && (mpfr_cmp_d (a.mpfr_srcptr(),b) == 0 );   }
+
+inline bool operator != (const mpreal& a, const mpreal& b           ){  return !(a == b);  }
+inline bool operator != (const mpreal& a, const unsigned long int b ){  return !(a == b);  }
+inline bool operator != (const mpreal& a, const unsigned int b      ){  return !(a == b);  }
+inline bool operator != (const mpreal& a, const long int b          ){  return !(a == b);  }
+inline bool operator != (const mpreal& a, const int b               ){  return !(a == b);  }
+inline bool operator != (const mpreal& a, const long double b       ){  return !(a == b);  }
+inline bool operator != (const mpreal& a, const double b            ){  return !(a == b);  }
+
+inline bool (isnan)    (const mpreal& op){    return (mpfr_nan_p    (op.mpfr_srcptr()) != 0 );    }
+inline bool (isinf)    (const mpreal& op){    return (mpfr_inf_p    (op.mpfr_srcptr()) != 0 );    }
+inline bool (isfinite) (const mpreal& op){    return (mpfr_number_p (op.mpfr_srcptr()) != 0 );    }
 inline bool iszero   (const mpreal& op){    return (mpfr_zero_p   (op.mpfr_srcptr()) != 0 );    }
 inline bool isint    (const mpreal& op){    return (mpfr_integer_p(op.mpfr_srcptr()) != 0 );    }
 
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0))
 inline bool isregular(const mpreal& op){    return (mpfr_regular_p(op.mpfr_srcptr()));}
-#endif 
+#endif
 
 //////////////////////////////////////////////////////////////////////////
 // Type Converters
-inline bool             mpreal::toBool (mp_rnd_t /*mode*/) const   {    return  mpfr_zero_p (mpfr_srcptr()) == 0;     }
-inline long             mpreal::toLong   (mp_rnd_t mode)  const    {    return  mpfr_get_si (mpfr_srcptr(), mode);    }
-inline unsigned long    mpreal::toULong  (mp_rnd_t mode)  const    {    return  mpfr_get_ui (mpfr_srcptr(), mode);    }
-inline float            mpreal::toFloat  (mp_rnd_t mode)  const    {    return  mpfr_get_flt(mpfr_srcptr(), mode);    }
-inline double           mpreal::toDouble (mp_rnd_t mode)  const    {    return  mpfr_get_d  (mpfr_srcptr(), mode);    }
-inline long double      mpreal::toLDouble(mp_rnd_t mode)  const    {    return  mpfr_get_ld (mpfr_srcptr(), mode);    }
-
-#if defined (MPREAL_HAVE_INT64_SUPPORT)
-inline int64_t      mpreal::toInt64 (mp_rnd_t mode)    const{    return mpfr_get_sj(mpfr_srcptr(), mode);    }
-inline uint64_t     mpreal::toUInt64(mp_rnd_t mode)    const{    return mpfr_get_uj(mpfr_srcptr(), mode);    }
-#endif
+inline bool               mpreal::toBool   (             )  const    {    return  mpfr_zero_p (mpfr_srcptr()) == 0;     }
+inline long               mpreal::toLong   (mp_rnd_t mode)  const    {    return  mpfr_get_si (mpfr_srcptr(), mode);    }
+inline unsigned long      mpreal::toULong  (mp_rnd_t mode)  const    {    return  mpfr_get_ui (mpfr_srcptr(), mode);    }
+inline float              mpreal::toFloat  (mp_rnd_t mode)  const    {    return  mpfr_get_flt(mpfr_srcptr(), mode);    }
+inline double             mpreal::toDouble (mp_rnd_t mode)  const    {    return  mpfr_get_d  (mpfr_srcptr(), mode);    }
+inline long double        mpreal::toLDouble(mp_rnd_t mode)  const    {    return  mpfr_get_ld (mpfr_srcptr(), mode);    }
+inline long long          mpreal::toLLong  (mp_rnd_t mode)  const    {    return  mpfr_get_sj (mpfr_srcptr(), mode);    }
+inline unsigned long long mpreal::toULLong (mp_rnd_t mode)  const    {    return  mpfr_get_uj (mpfr_srcptr(), mode);    }
 
 inline ::mpfr_ptr     mpreal::mpfr_ptr()             { return mp; }
 inline ::mpfr_srcptr  mpreal::mpfr_ptr()    const    { return mp; }
 inline ::mpfr_srcptr  mpreal::mpfr_srcptr() const    { return mp; }
 
@@ -1752,25 +1760,25 @@
 
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0))
 
     std::ostringstream format;
 
-    int digits = (n >= 0) ? n : bits2digits(mpfr_get_prec(mpfr_srcptr()));
-    
+    int digits = (n >= 0) ? n : 1 + bits2digits(mpfr_get_prec(mpfr_srcptr()));
+
     format << "%." << digits << "RNg";
 
     return toString(format.str());
 
 #else
 
-    char *s, *ns = NULL; 
+    char *s, *ns = NULL;
     size_t slen, nslen;
     mp_exp_t exp;
     std::string out;
 
     if(mpfr_inf_p(mp))
-    { 
+    {
         if(mpfr_sgn(mp)>0) return "+Inf";
         else               return "-Inf";
     }
 
     if(mpfr_zero_p(mp)) return "0";
@@ -1781,11 +1789,11 @@
 
     if(s!=NULL && ns!=NULL)
     {
         slen  = strlen(s);
         nslen = strlen(ns);
-        if(nslen<=slen) 
+        if(nslen<=slen)
         {
             mpfr_free_str(s);
             s = ns;
             slen = nslen;
         }
@@ -1798,11 +1806,11 @@
         {
             if(s[0]=='-')
             {
                 // Remove zeros starting from right end
                 char* ptr = s+slen-1;
-                while (*ptr=='0' && ptr>s+exp) ptr--; 
+                while (*ptr=='0' && ptr>s+exp) ptr--;
 
                 if(ptr==s+exp) out = std::string(s,exp+1);
                 else           out = std::string(s,exp+1)+'.'+std::string(s+exp+1,ptr-(s+exp+1)+1);
 
                 //out = string(s,exp+1)+'.'+string(s+exp+1);
@@ -1809,11 +1817,11 @@
             }
             else
             {
                 // Remove zeros starting from right end
                 char* ptr = s+slen-1;
-                while (*ptr=='0' && ptr>s+exp-1) ptr--; 
+                while (*ptr=='0' && ptr>s+exp-1) ptr--;
 
                 if(ptr==s+exp-1) out = std::string(s,exp);
                 else             out = std::string(s,exp)+'.'+std::string(s+exp,ptr-(s+exp)+1);
 
                 //out = string(s,exp)+'.'+string(s+exp);
@@ -1822,11 +1830,11 @@
         }else{ // exp<0 || exp>slen
             if(s[0]=='-')
             {
                 // Remove zeros starting from right end
                 char* ptr = s+slen-1;
-                while (*ptr=='0' && ptr>s+1) ptr--; 
+                while (*ptr=='0' && ptr>s+1) ptr--;
 
                 if(ptr==s+1) out = std::string(s,2);
                 else         out = std::string(s,2)+'.'+std::string(s+2,ptr-(s+2)+1);
 
                 //out = string(s,2)+'.'+string(s+2);
@@ -1833,11 +1841,11 @@
             }
             else
             {
                 // Remove zeros starting from right end
                 char* ptr = s+slen-1;
-                while (*ptr=='0' && ptr>s) ptr--; 
+                while (*ptr=='0' && ptr>s) ptr--;
 
                 if(ptr==s) out = std::string(s,1);
                 else       out = std::string(s,1)+'.'+std::string(s+1,ptr-(s+1)+1);
 
                 //out = string(s,1)+'.'+string(s+1);
@@ -1860,11 +1868,11 @@
 }
 
 
 //////////////////////////////////////////////////////////////////////////
 // I/O
-inline std::ostream& mpreal::output(std::ostream& os) const 
+inline std::ostream& mpreal::output(std::ostream& os) const
 {
     std::ostringstream format;
     const std::ios::fmtflags flags = os.flags();
 
     format << ((flags & std::ios::showpos) ? "%+" : "%");
@@ -1923,12 +1931,11 @@
 
 //////////////////////////////////////////////////////////////////////////
 // Set/Get number properties
 inline int sgn(const mpreal& op)
 {
-    int r = mpfr_signbit(op.mpfr_srcptr());
-    return (r > 0? -1 : 1);
+    return mpfr_sgn(op.mpfr_srcptr());
 }
 
 inline mpreal& mpreal::setSign(int sign, mp_rnd_t RoundingMode)
 {
     mpfr_setsign(mpfr_ptr(), mpfr_srcptr(), (sign < 0 ? 1 : 0), RoundingMode);
@@ -1946,33 +1953,32 @@
     mpfr_prec_round(mpfr_ptr(), Precision, RoundingMode);
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
-inline mpreal& mpreal::setInf(int sign) 
-{ 
+inline mpreal& mpreal::setInf(int sign)
+{
     mpfr_set_inf(mpfr_ptr(), sign);
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
-}    
+}
 
-inline mpreal& mpreal::setNan() 
+inline mpreal& mpreal::setNan()
 {
     mpfr_set_nan(mpfr_ptr());
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
-inline mpreal&    mpreal::setZero(int sign)
+inline mpreal& mpreal::setZero(int sign)
 {
-
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0))
     mpfr_set_zero(mpfr_ptr(), sign);
 #else
     mpfr_set_si(mpfr_ptr(), 0, (mpfr_get_default_rounding_mode)());
     setSign(sign);
-#endif 
+#endif
 
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return *this;
 }
 
@@ -1997,35 +2003,44 @@
     int x = mpfr_set_exp(mpfr_ptr(), e);
     MPREAL_MSVC_DEBUGVIEW_CODE;
     return x;
 }
 
-inline const mpreal frexp(const mpreal& v, mp_exp_t* exp)
+inline const mpreal frexp(const mpreal& x, mp_exp_t* exp, mp_rnd_t mode = mpreal::get_default_rnd())
 {
-    mpreal x(v);
-    *exp = x.get_exp();
-    x.set_exp(0);
-    return x;
+    mpreal y(x);
+#if (MPFR_VERSION >= MPFR_VERSION_NUM(3,1,0))
+    mpfr_frexp(exp,y.mpfr_ptr(),x.mpfr_srcptr(),mode);
+#else
+    *exp = mpfr_get_exp(y.mpfr_srcptr());
+    mpfr_set_exp(y.mpfr_ptr(),0);
+#endif
+    return y;
 }
 
 inline const mpreal ldexp(const mpreal& v, mp_exp_t exp)
 {
     mpreal x(v);
 
-    // rounding is not important since we just increasing the exponent
-    mpfr_mul_2si(x.mpfr_ptr(), x.mpfr_srcptr(), exp, mpreal::get_default_rnd()); 
+    // rounding is not important since we are just increasing the exponent (= exact operation)
+    mpfr_mul_2si(x.mpfr_ptr(), x.mpfr_srcptr(), exp, mpreal::get_default_rnd());
     return x;
 }
+
+inline const mpreal scalbn(const mpreal& v, mp_exp_t exp)
+{
+    return ldexp(v, exp);
+}
 
 inline mpreal machine_epsilon(mp_prec_t prec)
 {
     /* the smallest eps such that 1 + eps != 1 */
     return machine_epsilon(mpreal(1, prec));
 }
 
 inline mpreal machine_epsilon(const mpreal& x)
-{    
+{
     /* the smallest eps such that x + eps != x */
     if( x < 0)
     {
         return nextabove(-x) + x;
     }else{
@@ -2042,11 +2057,11 @@
 
 // maxval is 'safe' meaning 1 / maxval does not underflow
 inline mpreal maxval(mp_prec_t prec)
 {
     /* max = (1 - eps) * 2^emax, eps is machine epsilon */
-    return (mpreal(1, prec) - machine_epsilon(prec)) << mpreal::get_emax(); 
+    return (mpreal(1, prec) - machine_epsilon(prec)) << mpreal::get_emax();
 }
 
 inline bool isEqualUlps(const mpreal& a, const mpreal& b, int maxUlps)
 {
     return abs(a - b) <= machine_epsilon((max)(abs(a), abs(b))) * maxUlps;
@@ -2059,17 +2074,31 @@
 
 inline bool isEqualFuzzy(const mpreal& a, const mpreal& b)
 {
     return isEqualFuzzy(a, b, machine_epsilon((max)(1, (min)(abs(a), abs(b)))));
 }
+
+//////////////////////////////////////////////////////////////////////////
+// C++11 sign functions.
+inline mpreal copysign(const mpreal& x, const  mpreal& y, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
+{
+    mpreal rop(0, mpfr_get_prec(x.mpfr_ptr()));
+    mpfr_setsign(rop.mpfr_ptr(), x.mpfr_srcptr(), mpfr_signbit(y.mpfr_srcptr()), rnd_mode);
+    return rop;
+}
+
+inline bool signbit(const mpreal& x)
+{
+    return mpfr_signbit(x.mpfr_srcptr());
+}
 
 inline const mpreal modf(const mpreal& v, mpreal& n)
 {
     mpreal f(v);
 
     // rounding is not important since we are using the same number
-    mpfr_frac (f.mpfr_ptr(),f.mpfr_srcptr(),mpreal::get_default_rnd());    
+    mpfr_frac (f.mpfr_ptr(),f.mpfr_srcptr(),mpreal::get_default_rnd());
     mpfr_trunc(n.mpfr_ptr(),v.mpfr_srcptr());
     return f;
 }
 
 inline int mpreal::check_range (int t, mp_rnd_t rnd_mode)
@@ -2128,11 +2157,11 @@
 // Mathematical Functions
 //////////////////////////////////////////////////////////////////////////
 #define MPREAL_UNARY_MATH_FUNCTION_BODY(f)                    \
         mpreal y(0, mpfr_get_prec(x.mpfr_srcptr()));          \
         mpfr_##f(y.mpfr_ptr(), x.mpfr_srcptr(), r);           \
-        return y; 
+        return y;
 
 inline const mpreal sqr  (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd())
 {   MPREAL_UNARY_MATH_FUNCTION_BODY(sqr );    }
 
 inline const mpreal sqrt (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd())
@@ -2151,11 +2180,11 @@
 }
 
 inline const mpreal sqrt(const long int v, mp_rnd_t rnd_mode)
 {
     if (v>=0)   return sqrt(static_cast<unsigned long int>(v),rnd_mode);
-    else        return mpreal().setNan(); // NaN  
+    else        return mpreal().setNan(); // NaN
 }
 
 inline const mpreal sqrt(const int v, mp_rnd_t rnd_mode)
 {
     if (v>=0)   return sqrt(static_cast<unsigned long int>(v),rnd_mode);
@@ -2162,13 +2191,13 @@
     else        return mpreal().setNan(); // NaN
 }
 
 inline const mpreal root(const mpreal& x, unsigned long int k, mp_rnd_t r = mpreal::get_default_rnd())
 {
-    mpreal y(0, mpfr_get_prec(x.mpfr_srcptr())); 
-    mpfr_root(y.mpfr_ptr(), x.mpfr_srcptr(), k, r);  
-    return y; 
+    mpreal y(0, mpfr_get_prec(x.mpfr_srcptr()));
+    mpfr_root(y.mpfr_ptr(), x.mpfr_srcptr(), k, r);
+    return y;
 }
 
 inline const mpreal dim(const mpreal& a, const mpreal& b, mp_rnd_t r = mpreal::get_default_rnd())
 {
     mpreal y(0, mpfr_get_prec(a.mpfr_srcptr()));
@@ -2206,10 +2235,12 @@
 inline const mpreal cot   (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(cot  );    }
 inline const mpreal acos  (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(acos );    }
 inline const mpreal asin  (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(asin );    }
 inline const mpreal atan  (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(atan );    }
 
+inline const mpreal logb  (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   return log2 (abs(x),r);                    }
+
 inline const mpreal acot  (const mpreal& v, mp_rnd_t r = mpreal::get_default_rnd()) {   return atan (1/v, r);                      }
 inline const mpreal asec  (const mpreal& v, mp_rnd_t r = mpreal::get_default_rnd()) {   return acos (1/v, r);                      }
 inline const mpreal acsc  (const mpreal& v, mp_rnd_t r = mpreal::get_default_rnd()) {   return asin (1/v, r);                      }
 inline const mpreal acoth (const mpreal& v, mp_rnd_t r = mpreal::get_default_rnd()) {   return atanh(1/v, r);                      }
 inline const mpreal asech (const mpreal& v, mp_rnd_t r = mpreal::get_default_rnd()) {   return acosh(1/v, r);                      }
@@ -2227,10 +2258,11 @@
 
 inline const mpreal log1p   (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(log1p  );    }
 inline const mpreal expm1   (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(expm1  );    }
 inline const mpreal eint    (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(eint   );    }
 inline const mpreal gamma   (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(gamma  );    }
+inline const mpreal tgamma  (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(gamma  );    }
 inline const mpreal lngamma (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(lngamma);    }
 inline const mpreal zeta    (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(zeta   );    }
 inline const mpreal erf     (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(erf    );    }
 inline const mpreal erfc    (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(erfc   );    }
 inline const mpreal besselj0(const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) {   MPREAL_UNARY_MATH_FUNCTION_BODY(j0     );    }
@@ -2251,11 +2283,11 @@
     mpfr_hypot(a.mpfr_ptr(), x.mpfr_srcptr(), y.mpfr_srcptr(), rnd_mode);
     return a;
 }
 
 inline const mpreal remainder (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
-{    
+{
     mpreal a(0,(std::max)(y.getPrecision(), x.getPrecision()));
     mpfr_remainder(a.mpfr_ptr(), x.mpfr_srcptr(), y.mpfr_srcptr(), rnd_mode);
     return a;
 }
 
@@ -2304,13 +2336,13 @@
 inline const mpreal fma (const mpreal& v1, const mpreal& v2, const mpreal& v3, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
 {
     mpreal a;
     mp_prec_t p1, p2, p3;
 
-    p1 = v1.get_prec(); 
-    p2 = v2.get_prec(); 
-    p3 = v3.get_prec(); 
+    p1 = v1.get_prec();
+    p2 = v2.get_prec();
+    p3 = v3.get_prec();
 
     a.set_prec(p3>p2?(p3>p1?p3:p1):(p2>p1?p2:p1));
 
     mpfr_fma(a.mp,v1.mp,v2.mp,v3.mp,rnd_mode);
     return a;
@@ -2319,13 +2351,13 @@
 inline const mpreal fms (const mpreal& v1, const mpreal& v2, const mpreal& v3, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
 {
     mpreal a;
     mp_prec_t p1, p2, p3;
 
-    p1 = v1.get_prec(); 
-    p2 = v2.get_prec(); 
-    p3 = v3.get_prec(); 
+    p1 = v1.get_prec();
+    p2 = v2.get_prec();
+    p3 = v3.get_prec();
 
     a.set_prec(p3>p2?(p3>p1?p3:p1):(p2>p1?p2:p1));
 
     mpfr_fms(a.mp,v1.mp,v2.mp,v3.mp,rnd_mode);
     return a;
@@ -2334,30 +2366,31 @@
 inline const mpreal agm (const mpreal& v1, const mpreal& v2, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
 {
     mpreal a;
     mp_prec_t p1, p2;
 
-    p1 = v1.get_prec(); 
-    p2 = v2.get_prec(); 
+    p1 = v1.get_prec();
+    p2 = v2.get_prec();
 
     a.set_prec(p1>p2?p1:p2);
 
     mpfr_agm(a.mp, v1.mp, v2.mp, rnd_mode);
 
     return a;
 }
 
-inline const mpreal sum (const mpreal tab[], unsigned long int n, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
+inline const mpreal sum (const mpreal tab[], const unsigned long int n, int& status, mp_rnd_t mode = mpreal::get_default_rnd())
 {
+    mpfr_srcptr *p = new mpfr_srcptr[n];
+
+    for (unsigned long int  i = 0; i < n; i++)
+        p[i] = tab[i].mpfr_srcptr();
+
     mpreal x;
-    mpfr_ptr* t;
-    unsigned long int i;
+    status = mpfr_sum(x.mpfr_ptr(), (mpfr_ptr*)p, n, mode);
 
-    t = new mpfr_ptr[n];
-    for (i=0;i<n;i++) t[i] = (mpfr_ptr)tab[i].mp;
-    mpfr_sum(x.mp,t,n,rnd_mode);
-    delete[] t;
+    delete [] p;
     return x;
 }
 
 //////////////////////////////////////////////////////////////////////////
 // MPFR 2.4.0 Specifics
@@ -2366,13 +2399,13 @@
 inline int sinh_cosh(mpreal& s, mpreal& c, const mpreal& v, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
 {
     return mpfr_sinh_cosh(s.mp,c.mp,v.mp,rnd_mode);
 }
 
-inline const mpreal li2 (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd()) 
-{   
-    MPREAL_UNARY_MATH_FUNCTION_BODY(li2);    
+inline const mpreal li2 (const mpreal& x, mp_rnd_t r = mpreal::get_default_rnd())
+{
+    MPREAL_UNARY_MATH_FUNCTION_BODY(li2);
 }
 
 inline const mpreal rem (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
 {
     /*  R = rem(X,Y) if Y != 0, returns X - n * Y where n = trunc(X/Y). */
@@ -2380,27 +2413,27 @@
 }
 
 inline const mpreal mod (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
 {
     (void)rnd_mode;
-    
-    /*  
+
+    /*
 
     m = mod(x,y) if y != 0, returns x - n*y where n = floor(x/y)
 
     The following are true by convention:
     - mod(x,0) is x
     - mod(x,x) is 0
-    - mod(x,y) for x != y and y != 0 has the same sign as y.    
-    
+    - mod(x,y) for x != y and y != 0 has the same sign as y.
+
     */
 
     if(iszero(y)) return x;
     if(x == y) return 0;
 
     mpreal m = x - floor(x / y) * y;
-    
+
     m.setSign(sgn(y)); // make sure result has the same sign as Y
 
     return m;
 }
 
@@ -2407,12 +2440,12 @@
 inline const mpreal fmod (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
 {
     mpreal a;
     mp_prec_t yp, xp;
 
-    yp = y.get_prec(); 
-    xp = x.get_prec(); 
+    yp = y.get_prec();
+    xp = x.get_prec();
 
     a.set_prec(yp>xp?yp:xp);
 
     mpfr_fmod(a.mp, x.mp, y.mp, rnd_mode);
 
@@ -2550,37 +2583,28 @@
 }
 
 inline const mpreal urandomb (gmp_randstate_t& state)
 {
     mpreal x;
-    mpfr_urandomb(x.mp,state);
+    mpfr_urandomb(x.mpfr_ptr(),state);
     return x;
 }
 
-#if (MPFR_VERSION >= MPFR_VERSION_NUM(3,1,0))
-// use gmp_randinit_default() to init state, gmp_randclear() to clear
+#if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0))
 inline const mpreal urandom (gmp_randstate_t& state, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
 {
     mpreal x;
-    mpfr_urandom(x.mp,state,rnd_mode);
+    mpfr_urandom(x.mpfr_ptr(), state, rnd_mode);
     return x;
 }
-
-inline const mpreal grandom (gmp_randstate_t& state, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
-{
-    mpreal x;
-    mpfr_grandom(x.mp, NULL, state, rnd_mode);
-    return x;
-}
-
-#endif 
+#endif
 
 #if (MPFR_VERSION <= MPFR_VERSION_NUM(2,4,2))
 inline const mpreal random2 (mp_size_t size, mp_exp_t exp)
 {
     mpreal x;
-    mpfr_random2(x.mp,size,exp);
+    mpfr_random2(x.mpfr_ptr(),size,exp);
     return x;
 }
 #endif
 
 // Uniformly distributed random number generation
@@ -2587,20 +2611,19 @@
 // a = random(seed); <- initialization & first random number generation
 // a = random();     <- next random numbers generation
 // seed != 0
 inline const mpreal random(unsigned int seed = 0)
 {
-
 #if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0))
     static gmp_randstate_t state;
-    static bool isFirstTime = true;
+    static bool initialize = true;
 
-    if(isFirstTime)
+    if(initialize)
     {
         gmp_randinit_default(state);
         gmp_randseed_ui(state,0);
-        isFirstTime = false;
+        initialize = false;
     }
 
     if(seed != 0)    gmp_randseed_ui(state,seed);
 
     return mpfr::urandom(state);
@@ -2609,21 +2632,29 @@
     return mpfr::mpreal(std::rand()/(double)RAND_MAX);
 #endif
 
 }
 
-#if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0))
+#if (MPFR_VERSION >= MPFR_VERSION_NUM(3,1,0))
+
+inline const mpreal grandom (gmp_randstate_t& state, mp_rnd_t rnd_mode = mpreal::get_default_rnd())
+{
+    mpreal x;
+    mpfr_grandom(x.mpfr_ptr(), NULL, state, rnd_mode);
+    return x;
+}
+
 inline const mpreal grandom(unsigned int seed = 0)
 {
     static gmp_randstate_t state;
-    static bool isFirstTime = true;
+    static bool initialize = true;
 
-    if(isFirstTime)
+    if(initialize)
     {
         gmp_randinit_default(state);
         gmp_randseed_ui(state,0);
-        isFirstTime = false;
+        initialize = false;
     }
 
     if(seed != 0) gmp_randseed_ui(state,seed);
 
     return mpfr::grandom(state);
@@ -2631,21 +2662,21 @@
 #endif
 
 //////////////////////////////////////////////////////////////////////////
 // Set/Get global properties
 inline void mpreal::set_default_prec(mp_prec_t prec)
-{ 
-    mpfr_set_default_prec(prec); 
+{
+    mpfr_set_default_prec(prec);
 }
 
 inline void mpreal::set_default_rnd(mp_rnd_t rnd_mode)
-{ 
-    mpfr_set_default_rounding_mode(rnd_mode); 
+{
+    mpfr_set_default_rounding_mode(rnd_mode);
 }
 
 inline bool mpreal::fits_in_bits(double x, int n)
-{   
+{
     int i;
     double t;
     return IsInf(x) || (std::modf ( std::ldexp ( std::frexp ( x, &i ), n ), &t ) == 0.0);
 }
 
@@ -2891,11 +2922,11 @@
 {
     if (a>=0)   return pow(static_cast<unsigned long int>(a),mpreal(b),rnd_mode); //mpfr_ui_pow
     else        return pow(mpreal(a),mpreal(b),rnd_mode); //mpfr_pow
 }
 
-// pow long double 
+// pow long double
 inline const mpreal pow(const long double a, const long double b, mp_rnd_t rnd_mode)
 {
     return pow(mpreal(a),mpreal(b),rnd_mode);
 }
 
@@ -2950,13 +2981,13 @@
 // Non-throwing swap C++ idiom: http://en.wikibooks.org/wiki/More_C%2B%2B_Idioms/Non-throwing_swap
 namespace std
 {
   // we are allowed to extend namespace std with specializations only
     template <>
-    inline void swap(mpfr::mpreal& x, mpfr::mpreal& y) 
-    { 
-        return mpfr::swap(x, y); 
+    inline void swap(mpfr::mpreal& x, mpfr::mpreal& y)
+    {
+        return mpfr::swap(x, y);
     }
 
     template<>
     class numeric_limits<mpfr::mpreal>
     {
@@ -2963,11 +2994,11 @@
     public:
         static const bool is_specialized    = true;
         static const bool is_signed         = true;
         static const bool is_integer        = false;
         static const bool is_exact          = false;
-        static const int  radix             = 2;    
+        static const int  radix             = 2;
 
         static const bool has_infinity      = true;
         static const bool has_quiet_NaN     = true;
         static const bool has_signaling_NaN = true;
 
@@ -2983,20 +3014,20 @@
         inline static mpfr::mpreal (max)    (mp_prec_t precision = mpfr::mpreal::get_default_prec()) {  return  mpfr::maxval(precision);  }
         inline static mpfr::mpreal lowest   (mp_prec_t precision = mpfr::mpreal::get_default_prec()) {  return -mpfr::maxval(precision);  }
 
         // Returns smallest eps such that 1 + eps != 1 (classic machine epsilon)
         inline static mpfr::mpreal epsilon(mp_prec_t precision = mpfr::mpreal::get_default_prec()) {  return  mpfr::machine_epsilon(precision); }
-    
+
         // Returns smallest eps such that x + eps != x (relative machine epsilon)
         inline static mpfr::mpreal epsilon(const mpfr::mpreal& x) {  return mpfr::machine_epsilon(x);  }
 
         inline static mpfr::mpreal round_error(mp_prec_t precision = mpfr::mpreal::get_default_prec())
         {
             mp_rnd_t r = mpfr::mpreal::get_default_rnd();
 
-            if(r == GMP_RNDN)  return mpfr::mpreal(0.5, precision); 
-            else               return mpfr::mpreal(1.0, precision);    
+            if(r == GMP_RNDN)  return mpfr::mpreal(0.5, precision);
+            else               return mpfr::mpreal(1.0, precision);
         }
 
         inline static const mpfr::mpreal infinity()         { return mpfr::const_infinity();     }
         inline static const mpfr::mpreal quiet_NaN()        { return mpfr::mpreal().setNan();    }
         inline static const mpfr::mpreal signaling_NaN()    { return mpfr::mpreal().setNan();    }
@@ -3003,31 +3034,31 @@
         inline static const mpfr::mpreal denorm_min()       { return (min)();                    }
 
         // Please note, exponent range is not fixed in MPFR
         static const int min_exponent = MPFR_EMIN_DEFAULT;
         static const int max_exponent = MPFR_EMAX_DEFAULT;
-        MPREAL_PERMISSIVE_EXPR static const int min_exponent10 = (int) (MPFR_EMIN_DEFAULT * 0.3010299956639811); 
-        MPREAL_PERMISSIVE_EXPR static const int max_exponent10 = (int) (MPFR_EMAX_DEFAULT * 0.3010299956639811); 
+        MPREAL_PERMISSIVE_EXPR static const int min_exponent10 = (int) (MPFR_EMIN_DEFAULT * 0.3010299956639811);
+        MPREAL_PERMISSIVE_EXPR static const int max_exponent10 = (int) (MPFR_EMAX_DEFAULT * 0.3010299956639811);
 
 #ifdef MPREAL_HAVE_DYNAMIC_STD_NUMERIC_LIMITS
 
         // Following members should be constant according to standard, but they can be variable in MPFR
-        // So we define them as functions here. 
+        // So we define them as functions here.
         //
         // This is preferable way for std::numeric_limits<mpfr::mpreal> specialization.
-        // But it is incompatible with standard std::numeric_limits and might not work with other libraries, e.g. boost. 
-        // See below for compatible implementation. 
+        // But it is incompatible with standard std::numeric_limits and might not work with other libraries, e.g. boost.
+        // See below for compatible implementation.
         inline static float_round_style round_style()
         {
             mp_rnd_t r = mpfr::mpreal::get_default_rnd();
 
             switch (r)
             {
             case GMP_RNDN: return round_to_nearest;
-            case GMP_RNDZ: return round_toward_zero; 
-            case GMP_RNDU: return round_toward_infinity; 
-            case GMP_RNDD: return round_toward_neg_infinity; 
+            case GMP_RNDZ: return round_toward_zero;
+            case GMP_RNDU: return round_toward_infinity;
+            case GMP_RNDD: return round_toward_neg_infinity;
             default: return round_indeterminate;
             }
         }
 
         inline static int digits()                        {    return int(mpfr::mpreal::get_default_prec());    }
@@ -3050,17 +3081,17 @@
 #else
         // Digits and round_style are NOT constants when it comes to mpreal.
         // If possible, please use functions digits() and round_style() defined above.
         //
         // These (default) values are preserved for compatibility with existing libraries, e.g. boost.
-        // Change them accordingly to your application. 
+        // Change them accordingly to your application.
         //
         // For example, if you use 256 bits of precision uniformly in your program, then:
         // digits       = 256
-        // digits10     = 77 
+        // digits10     = 77
         // max_digits10 = 78
-        // 
+        //
         // Approximate formula for decimal digits is: digits10 = floor(log10(2) * digits). See bits2digits() for more details.
 
         static const std::float_round_style round_style = round_to_nearest;
         static const int digits       = 53;
         static const int digits10     = 15;

Index: 3rd_party/eigen/unsupported/test/mpreal_support.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/mpreal_support.cpp
+++ 3rd_party/eigen/unsupported/test/mpreal_support.cpp
@@ -10,36 +10,44 @@
 void test_mpreal_support()
 {
   // set precision to 256 bits (double has only 53 bits)
   mpreal::set_default_prec(256);
   typedef Matrix<mpreal,Eigen::Dynamic,Eigen::Dynamic> MatrixXmp;
+  typedef Matrix<std::complex<mpreal>,Eigen::Dynamic,Eigen::Dynamic> MatrixXcmp;
 
   std::cerr << "epsilon =         " << NumTraits<mpreal>::epsilon() << "\n";
   std::cerr << "dummy_precision = " << NumTraits<mpreal>::dummy_precision() << "\n";
   std::cerr << "highest =         " << NumTraits<mpreal>::highest() << "\n";
   std::cerr << "lowest =          " << NumTraits<mpreal>::lowest() << "\n";
+  std::cerr << "digits10 =        " << NumTraits<mpreal>::digits10() << "\n";
 
   for(int i = 0; i < g_repeat; i++) {
     int s = Eigen::internal::random<int>(1,100);
     MatrixXmp A = MatrixXmp::Random(s,s);
     MatrixXmp B = MatrixXmp::Random(s,s);
     MatrixXmp S = A.adjoint() * A;
     MatrixXmp X;
+    MatrixXcmp Ac = MatrixXcmp::Random(s,s);
+    MatrixXcmp Bc = MatrixXcmp::Random(s,s);
+    MatrixXcmp Sc = Ac.adjoint() * Ac;
+    MatrixXcmp Xc;
     
     // Basic stuffs
     VERIFY_IS_APPROX(A.real(), A);
     VERIFY(Eigen::internal::isApprox(A.array().abs2().sum(), A.squaredNorm()));
     VERIFY_IS_APPROX(A.array().exp(),         exp(A.array()));
     VERIFY_IS_APPROX(A.array().abs2().sqrt(), A.array().abs());
     VERIFY_IS_APPROX(A.array().sin(),         sin(A.array()));
     VERIFY_IS_APPROX(A.array().cos(),         cos(A.array()));
-    
 
     // Cholesky
     X = S.selfadjointView<Lower>().llt().solve(B);
     VERIFY_IS_APPROX((S.selfadjointView<Lower>()*X).eval(),B);
 
+    Xc = Sc.selfadjointView<Lower>().llt().solve(Bc);
+    VERIFY_IS_APPROX((Sc.selfadjointView<Lower>()*Xc).eval(),Bc);
+    
     // partial LU
     X = A.lu().solve(B);
     VERIFY_IS_APPROX((A*X).eval(),B);
 
     // symmetric eigenvalues

Index: 3rd_party/eigen/unsupported/test/polynomialsolver.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/polynomialsolver.cpp
+++ 3rd_party/eigen/unsupported/test/polynomialsolver.cpp
@@ -36,10 +36,13 @@
   typedef typename SOLVER::RootsType    RootsType;
   typedef Matrix<Scalar,Deg,1>          EvalRootsType;
 
   const Index deg = pols.size()-1;
 
+  // Test template constructor from coefficient vector
+  SOLVER solve_constr (pols);
+
   psolve.compute( pols );
   const RootsType& roots( psolve.roots() );
   EvalRootsType evr( deg );
   for( int i=0; i<roots.size(); ++i ){
     evr[i] = std::abs( poly_eval( pols, roots[i] ) ); }
@@ -102,10 +105,11 @@
   {
     //It is supposed that
     // 1) the roots found are correct
     // 2) the roots have distinct moduli
 
+    typedef typename POLYNOMIAL::Scalar                 Scalar;
     typedef typename REAL_ROOTS::Scalar                 Real;
 
     //Test realRoots
     std::vector< Real > calc_realRoots;
     psolve.realRoots( calc_realRoots );
@@ -116,11 +120,11 @@
     for( size_t i=0; i<calc_realRoots.size(); ++i )
     {
       bool found = false;
       for( size_t j=0; j<calc_realRoots.size()&& !found; ++j )
       {
-        if( internal::isApprox( calc_realRoots[i], real_roots[j] ), psPrec ){
+        if( internal::isApprox( calc_realRoots[i], real_roots[j], psPrec ) ){
           found = true; }
       }
       VERIFY( found );
     }
 
@@ -207,7 +211,8 @@
             internal::random<int>(9,13)
             )) );
     CALL_SUBTEST_10((polynomialsolver<double,Dynamic>(
             internal::random<int>(9,13)
             )) );
+    CALL_SUBTEST_11((polynomialsolver<float,Dynamic>(1)) );
   }
 }

Index: 3rd_party/eigen/unsupported/test/sparse_extra.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/sparse_extra.cpp
+++ 3rd_party/eigen/unsupported/test/sparse_extra.cpp
@@ -47,11 +47,10 @@
   return sm.isApprox(ref);
 }
 
 template<typename SparseMatrixType> void sparse_extra(const SparseMatrixType& ref)
 {
-  typedef typename SparseMatrixType::Index Index;
   const Index rows = ref.rows();
   const Index cols = ref.cols();
   typedef typename SparseMatrixType::Scalar Scalar;
   enum { Flags = SparseMatrixType::Flags };
 

ADDED   3rd_party/eigen/unsupported/test/special_functions.cpp
Index: 3rd_party/eigen/unsupported/test/special_functions.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/special_functions.cpp
+++ 3rd_party/eigen/unsupported/test/special_functions.cpp
@@ -0,0 +1,345 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include "../Eigen/SpecialFunctions"
+
+template<typename X, typename Y>
+void verify_component_wise(const X& x, const Y& y)
+{
+  for(Index i=0; i<x.size(); ++i)
+  {
+    if((numext::isfinite)(y(i)))
+      VERIFY_IS_APPROX( x(i), y(i) );
+    else if((numext::isnan)(y(i)))
+      VERIFY((numext::isnan)(x(i)));
+    else
+      VERIFY_IS_EQUAL( x(i), y(i) );
+  }
+}
+
+template<typename ArrayType> void array_special_functions()
+{
+  using std::abs;
+  using std::sqrt;
+  typedef typename ArrayType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+
+  Scalar plusinf = std::numeric_limits<Scalar>::infinity();
+  Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
+
+  Index rows = internal::random<Index>(1,30);
+  Index cols = 1;
+
+  // API
+  {
+    ArrayType m1 = ArrayType::Random(rows,cols);
+#if EIGEN_HAS_C99_MATH
+    VERIFY_IS_APPROX(m1.lgamma(), lgamma(m1));
+    VERIFY_IS_APPROX(m1.digamma(), digamma(m1));
+    VERIFY_IS_APPROX(m1.erf(), erf(m1));
+    VERIFY_IS_APPROX(m1.erfc(), erfc(m1));
+#endif  // EIGEN_HAS_C99_MATH
+  }
+
+
+#if EIGEN_HAS_C99_MATH
+  // check special functions (comparing against numpy implementation)
+  if (!NumTraits<Scalar>::IsComplex)
+  {
+
+    {
+      ArrayType m1 = ArrayType::Random(rows,cols);
+      ArrayType m2 = ArrayType::Random(rows,cols);
+
+      // Test various propreties of igamma & igammac.  These are normalized
+      // gamma integrals where
+      //   igammac(a, x) = Gamma(a, x) / Gamma(a)
+      //   igamma(a, x) = gamma(a, x) / Gamma(a)
+      // where Gamma and gamma are considered the standard unnormalized
+      // upper and lower incomplete gamma functions, respectively.
+      ArrayType a = m1.abs() + 2;
+      ArrayType x = m2.abs() + 2;
+      ArrayType zero = ArrayType::Zero(rows, cols);
+      ArrayType one = ArrayType::Constant(rows, cols, Scalar(1.0));
+      ArrayType a_m1 = a - one;
+      ArrayType Gamma_a_x = Eigen::igammac(a, x) * a.lgamma().exp();
+      ArrayType Gamma_a_m1_x = Eigen::igammac(a_m1, x) * a_m1.lgamma().exp();
+      ArrayType gamma_a_x = Eigen::igamma(a, x) * a.lgamma().exp();
+      ArrayType gamma_a_m1_x = Eigen::igamma(a_m1, x) * a_m1.lgamma().exp();
+
+      // Gamma(a, 0) == Gamma(a)
+      VERIFY_IS_APPROX(Eigen::igammac(a, zero), one);
+
+      // Gamma(a, x) + gamma(a, x) == Gamma(a)
+      VERIFY_IS_APPROX(Gamma_a_x + gamma_a_x, a.lgamma().exp());
+
+      // Gamma(a, x) == (a - 1) * Gamma(a-1, x) + x^(a-1) * exp(-x)
+      VERIFY_IS_APPROX(Gamma_a_x, (a - 1) * Gamma_a_m1_x + x.pow(a-1) * (-x).exp());
+
+      // gamma(a, x) == (a - 1) * gamma(a-1, x) - x^(a-1) * exp(-x)
+      VERIFY_IS_APPROX(gamma_a_x, (a - 1) * gamma_a_m1_x - x.pow(a-1) * (-x).exp());
+    }
+
+    {
+      // Check exact values of igamma and igammac against a third party calculation.
+      Scalar a_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
+      Scalar x_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
+
+      // location i*6+j corresponds to a_s[i], x_s[j].
+      Scalar igamma_s[][6] = {{0.0, nan, nan, nan, nan, nan},
+                              {0.0, 0.6321205588285578, 0.7768698398515702,
+                              0.9816843611112658, 9.999500016666262e-05, 1.0},
+                              {0.0, 0.4275932955291202, 0.608374823728911,
+                              0.9539882943107686, 7.522076445089201e-07, 1.0},
+                              {0.0, 0.01898815687615381, 0.06564245437845008,
+                              0.5665298796332909, 4.166333347221828e-18, 1.0},
+                              {0.0, 0.9999780593618628, 0.9999899967080838,
+                              0.9999996219837988, 0.9991370418689945, 1.0},
+                              {0.0, 0.0, 0.0, 0.0, 0.0, 0.5042041932513908}};
+      Scalar igammac_s[][6] = {{nan, nan, nan, nan, nan, nan},
+                              {1.0, 0.36787944117144233, 0.22313016014842982,
+                                0.018315638888734182, 0.9999000049998333, 0.0},
+                              {1.0, 0.5724067044708798, 0.3916251762710878,
+                                0.04601170568923136, 0.9999992477923555, 0.0},
+                              {1.0, 0.9810118431238462, 0.9343575456215499,
+                                0.4334701203667089, 1.0, 0.0},
+                              {1.0, 2.1940638138146658e-05, 1.0003291916285e-05,
+                                3.7801620118431334e-07, 0.0008629581310054535,
+                                0.0},
+                              {1.0, 1.0, 1.0, 1.0, 1.0, 0.49579580674813944}};
+      for (int i = 0; i < 6; ++i) {
+        for (int j = 0; j < 6; ++j) {
+          if ((std::isnan)(igamma_s[i][j])) {
+            VERIFY((std::isnan)(numext::igamma(a_s[i], x_s[j])));
+          } else {
+            VERIFY_IS_APPROX(numext::igamma(a_s[i], x_s[j]), igamma_s[i][j]);
+          }
+
+          if ((std::isnan)(igammac_s[i][j])) {
+            VERIFY((std::isnan)(numext::igammac(a_s[i], x_s[j])));
+          } else {
+            VERIFY_IS_APPROX(numext::igammac(a_s[i], x_s[j]), igammac_s[i][j]);
+          }
+        }
+      }
+    }
+  }
+#endif  // EIGEN_HAS_C99_MATH
+
+  // Check the zeta function against scipy.special.zeta
+  {
+    ArrayType x(7), q(7), res(7), ref(7);
+    x << 1.5,   4, 10.5, 10000.5,    3, 1,        0.9;
+    q << 2,   1.5,    3,  1.0001, -2.5, 1.2345, 1.2345;
+    ref << 1.61237534869, 0.234848505667, 1.03086757337e-5, 0.367879440865, 0.054102025820864097, plusinf, nan;
+    CALL_SUBTEST( verify_component_wise(ref, ref); );
+    CALL_SUBTEST( res = x.zeta(q); verify_component_wise(res, ref); );
+    CALL_SUBTEST( res = zeta(x,q); verify_component_wise(res, ref); );
+  }
+
+  // digamma
+  {
+    ArrayType x(7), res(7), ref(7);
+    x << 1, 1.5, 4, -10.5, 10000.5, 0, -1;
+    ref << -0.5772156649015329, 0.03648997397857645, 1.2561176684318, 2.398239129535781, 9.210340372392849, plusinf, plusinf;
+    CALL_SUBTEST( verify_component_wise(ref, ref); );
+
+    CALL_SUBTEST( res = x.digamma(); verify_component_wise(res, ref); );
+    CALL_SUBTEST( res = digamma(x);  verify_component_wise(res, ref); );
+  }
+
+
+#if EIGEN_HAS_C99_MATH
+  {
+    ArrayType n(11), x(11), res(11), ref(11);
+    n << 1, 1,    1, 1.5,   17,   31,   28,    8, 42, 147, 170;
+    x << 2, 3, 25.5, 1.5,  4.7, 11.8, 17.7, 30.2, 15.8, 54.1, 64;
+    ref << 0.644934066848, 0.394934066848, 0.0399946696496, nan, 293.334565435, 0.445487887616, -2.47810300902e-07, -8.29668781082e-09, -0.434562276666, 0.567742190178, -0.0108615497927;
+    CALL_SUBTEST( verify_component_wise(ref, ref); );
+
+    if(sizeof(RealScalar)>=8) {  // double
+      // Reason for commented line: http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1232
+      //       CALL_SUBTEST( res = x.polygamma(n); verify_component_wise(res, ref); );
+      CALL_SUBTEST( res = polygamma(n,x);  verify_component_wise(res, ref); );
+    }
+    else {
+      //       CALL_SUBTEST( res = x.polygamma(n); verify_component_wise(res.head(8), ref.head(8)); );
+      CALL_SUBTEST( res = polygamma(n,x); verify_component_wise(res.head(8), ref.head(8)); );
+    }
+  }
+#endif
+
+#if EIGEN_HAS_C99_MATH
+  {
+    // Inputs and ground truth generated with scipy via:
+    //   a = np.logspace(-3, 3, 5) - 1e-3
+    //   b = np.logspace(-3, 3, 5) - 1e-3
+    //   x = np.linspace(-0.1, 1.1, 5)
+    //   (full_a, full_b, full_x) = np.vectorize(lambda a, b, x: (a, b, x))(*np.ix_(a, b, x))
+    //   full_a = full_a.flatten().tolist()  # same for full_b, full_x
+    //   v = scipy.special.betainc(full_a, full_b, full_x).flatten().tolist()
+    //
+    // Note in Eigen, we call betainc with arguments in the order (x, a, b).
+    ArrayType a(125);
+    ArrayType b(125);
+    ArrayType x(125);
+    ArrayType v(125);
+    ArrayType res(125);
+
+    a << 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
+        0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
+        0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
+        999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
+        999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
+        999.999, 999.999, 999.999;
+
+    b << 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379, 0.999,
+        0.999, 0.999, 0.999, 0.999, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 31.62177660168379, 999.999,
+        999.999, 999.999, 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.999, 0.999, 0.999, 0.999,
+        0.999, 31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
+        999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
+        999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
+        999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
+        0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+        0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
+        31.62177660168379, 31.62177660168379, 31.62177660168379,
+        31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
+        999.999, 999.999;
+
+    x << -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
+        0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
+        0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
+        0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1,
+        -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8,
+        1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
+        0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
+        0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
+        0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
+        0.8, 1.1;
+
+    v << nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
+        nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
+        nan, nan, nan, 0.47972119876364683, 0.5, 0.5202788012363533, nan, nan,
+        0.9518683957740043, 0.9789663010413743, 0.9931729188073435, nan, nan,
+        0.999995949033062, 0.9999999999993698, 0.9999999999999999, nan, nan,
+        0.9999999999999999, 0.9999999999999999, 0.9999999999999999, nan, nan,
+        nan, nan, nan, nan, nan, 0.006827081192655869, 0.0210336989586256,
+        0.04813160422599567, nan, nan, 0.20014344256217678, 0.5000000000000001,
+        0.7998565574378232, nan, nan, 0.9991401428435834, 0.999999999698403,
+        0.9999999999999999, nan, nan, 0.9999999999999999, 0.9999999999999999,
+        0.9999999999999999, nan, nan, nan, nan, nan, nan, nan,
+        1.0646600232370887e-25, 6.301722877826246e-13, 4.050966937974938e-06,
+        nan, nan, 7.864342668429763e-23, 3.015969667594166e-10,
+        0.0008598571564165444, nan, nan, 6.031987710123844e-08,
+        0.5000000000000007, 0.9999999396801229, nan, nan, 0.9999999999999999,
+        0.9999999999999999, 0.9999999999999999, nan, nan, nan, nan, nan, nan,
+        nan, 0.0, 7.029920380986636e-306, 2.2450728208591345e-101, nan, nan,
+        0.0, 9.275871147869727e-302, 1.2232913026152827e-97, nan, nan, 0.0,
+        3.0891393081932924e-252, 2.9303043666183996e-60, nan, nan,
+        2.248913486879199e-196, 0.5000000000004947, 0.9999999999999999, nan;
+
+    CALL_SUBTEST(res = betainc(a, b, x);
+                 verify_component_wise(res, v););
+  }
+
+  // Test various properties of betainc
+  {
+    ArrayType m1 = ArrayType::Random(32);
+    ArrayType m2 = ArrayType::Random(32);
+    ArrayType m3 = ArrayType::Random(32);
+    ArrayType one = ArrayType::Constant(32, Scalar(1.0));
+    const Scalar eps = std::numeric_limits<Scalar>::epsilon();
+    ArrayType a = (m1 * 4.0).exp();
+    ArrayType b = (m2 * 4.0).exp();
+    ArrayType x = m3.abs();
+
+    // betainc(a, 1, x) == x**a
+    CALL_SUBTEST(
+        ArrayType test = betainc(a, one, x);
+        ArrayType expected = x.pow(a);
+        verify_component_wise(test, expected););
+
+    // betainc(1, b, x) == 1 - (1 - x)**b
+    CALL_SUBTEST(
+        ArrayType test = betainc(one, b, x);
+        ArrayType expected = one - (one - x).pow(b);
+        verify_component_wise(test, expected););
+
+    // betainc(a, b, x) == 1 - betainc(b, a, 1-x)
+    CALL_SUBTEST(
+        ArrayType test = betainc(a, b, x) + betainc(b, a, one - x);
+        ArrayType expected = one;
+        verify_component_wise(test, expected););
+
+    // betainc(a+1, b, x) = betainc(a, b, x) - x**a * (1 - x)**b / (a * beta(a, b))
+    CALL_SUBTEST(
+        ArrayType num = x.pow(a) * (one - x).pow(b);
+        ArrayType denom = a * (a.lgamma() + b.lgamma() - (a + b).lgamma()).exp();
+        // Add eps to rhs and lhs so that component-wise test doesn't result in
+        // nans when both outputs are zeros.
+        ArrayType expected = betainc(a, b, x) - num / denom + eps;
+        ArrayType test = betainc(a + one, b, x) + eps;
+        if (sizeof(Scalar) >= 8) { // double
+          verify_component_wise(test, expected);
+        } else {
+          // Reason for limited test: http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1232
+          verify_component_wise(test.head(8), expected.head(8));
+        });
+
+    // betainc(a, b+1, x) = betainc(a, b, x) + x**a * (1 - x)**b / (b * beta(a, b))
+    CALL_SUBTEST(
+        // Add eps to rhs and lhs so that component-wise test doesn't result in
+        // nans when both outputs are zeros.
+        ArrayType num = x.pow(a) * (one - x).pow(b);
+        ArrayType denom = b * (a.lgamma() + b.lgamma() - (a + b).lgamma()).exp();
+        ArrayType expected = betainc(a, b, x) + num / denom + eps;
+        ArrayType test = betainc(a, b + one, x) + eps;
+        verify_component_wise(test, expected););
+  }
+#endif
+}
+
+void test_special_functions()
+{
+  CALL_SUBTEST_1(array_special_functions<ArrayXf>());
+  CALL_SUBTEST_2(array_special_functions<ArrayXd>());
+}

Index: 3rd_party/eigen/unsupported/test/splines.cpp
==================================================================
--- 3rd_party/eigen/unsupported/test/splines.cpp
+++ 3rd_party/eigen/unsupported/test/splines.cpp
@@ -11,27 +11,27 @@
 
 #include <unsupported/Eigen/Splines>
 
 namespace Eigen {
   
-// lets do some explicit instantiations and thus
-// force the compilation of all spline functions...
-template class Spline<double, 2, Dynamic>;
-template class Spline<double, 3, Dynamic>;
-
-template class Spline<double, 2, 2>;
-template class Spline<double, 2, 3>;
-template class Spline<double, 2, 4>;
-template class Spline<double, 2, 5>;
-
-template class Spline<float, 2, Dynamic>;
-template class Spline<float, 3, Dynamic>;
-
-template class Spline<float, 3, 2>;
-template class Spline<float, 3, 3>;
-template class Spline<float, 3, 4>;
-template class Spline<float, 3, 5>;
+  // lets do some explicit instantiations and thus
+  // force the compilation of all spline functions...
+  template class Spline<double, 2, Dynamic>;
+  template class Spline<double, 3, Dynamic>;
+
+  template class Spline<double, 2, 2>;
+  template class Spline<double, 2, 3>;
+  template class Spline<double, 2, 4>;
+  template class Spline<double, 2, 5>;
+
+  template class Spline<float, 2, Dynamic>;
+  template class Spline<float, 3, Dynamic>;
+
+  template class Spline<float, 3, 2>;
+  template class Spline<float, 3, 3>;
+  template class Spline<float, 3, 4>;
+  template class Spline<float, 3, 5>;
 
 }
 
 Spline<double, 2, Dynamic> closed_spline2d()
 {
@@ -232,13 +232,50 @@
       VERIFY( (pt - ref).matrix().norm() < 1e-14 );
     }
   }
 }
 
+void check_global_interpolation_with_derivatives2d()
+{
+  typedef Spline2d::PointType PointType;
+  typedef Spline2d::KnotVectorType KnotVectorType;
+
+  const Eigen::DenseIndex numPoints = 100;
+  const unsigned int dimension = 2;
+  const unsigned int degree = 3;
+
+  ArrayXXd points = ArrayXXd::Random(dimension, numPoints);
+
+  KnotVectorType knots;
+  Eigen::ChordLengths(points, knots);
+
+  ArrayXXd derivatives = ArrayXXd::Random(dimension, numPoints);
+  VectorXd derivativeIndices(numPoints);
+
+  for (Eigen::DenseIndex i = 0; i < numPoints; ++i)
+      derivativeIndices(i) = static_cast<double>(i);
+
+  const Spline2d spline = SplineFitting<Spline2d>::InterpolateWithDerivatives(
+    points, derivatives, derivativeIndices, degree);  
+    
+  for (Eigen::DenseIndex i = 0; i < points.cols(); ++i)
+  {
+    PointType point = spline(knots(i));
+    PointType referencePoint = points.col(i);
+    VERIFY_IS_APPROX(point, referencePoint);
+    PointType derivative = spline.derivatives(knots(i), 1).col(1);
+    PointType referenceDerivative = derivatives.col(i);
+    VERIFY_IS_APPROX(derivative, referenceDerivative);
+  }
+}
 
 void test_splines()
 {
-  CALL_SUBTEST( eval_spline3d() );
-  CALL_SUBTEST( eval_spline3d_onbrks() );
-  CALL_SUBTEST( eval_closed_spline2d() );
-  CALL_SUBTEST( check_global_interpolation2d() );
+  for (int i = 0; i < g_repeat; ++i)
+  {
+    CALL_SUBTEST( eval_spline3d() );
+    CALL_SUBTEST( eval_spline3d_onbrks() );
+    CALL_SUBTEST( eval_closed_spline2d() );
+    CALL_SUBTEST( check_global_interpolation2d() );
+    CALL_SUBTEST( check_global_interpolation_with_derivatives2d() );
+  }
 }

DELETED 3rd_party/eigen/unsupported/test/svd_common.h
Index: 3rd_party/eigen/unsupported/test/svd_common.h
==================================================================
--- 3rd_party/eigen/unsupported/test/svd_common.h
+++ 3rd_party/eigen/unsupported/test/svd_common.h
@@ -1,261 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com>
-// Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr>
-// Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr>
-// Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// discard stack allocation as that too bypasses malloc
-#define EIGEN_STACK_ALLOCATION_LIMIT 0
-#define EIGEN_RUNTIME_NO_MALLOC
-
-#include "main.h"
-#include <unsupported/Eigen/SVD>
-#include <Eigen/LU>
-
-
-// check if "svd" is the good image of "m"  
-template<typename MatrixType, typename SVD>
-void svd_check_full(const MatrixType& m, const SVD& svd)
-{
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime
-  };
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime> MatrixUType;
-  typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime> MatrixVType;
-
-  
-  MatrixType sigma = MatrixType::Zero(rows, cols);
-  sigma.diagonal() = svd.singularValues().template cast<Scalar>();
-  MatrixUType u = svd.matrixU();
-  MatrixVType v = svd.matrixV();
-  VERIFY_IS_APPROX(m, u * sigma * v.adjoint());
-  VERIFY_IS_UNITARY(u);
-  VERIFY_IS_UNITARY(v);
-} // end svd_check_full
-
-
-
-// Compare to a reference value
-template<typename MatrixType, typename SVD>
-void svd_compare_to_full(const MatrixType& m,
-			 unsigned int computationOptions,
-			 const SVD& referenceSvd)
-{
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-  Index diagSize = (std::min)(rows, cols);
-
-  SVD svd(m, computationOptions);
-
-  VERIFY_IS_APPROX(svd.singularValues(), referenceSvd.singularValues());
-  if(computationOptions & ComputeFullU)
-    VERIFY_IS_APPROX(svd.matrixU(), referenceSvd.matrixU());
-  if(computationOptions & ComputeThinU)
-    VERIFY_IS_APPROX(svd.matrixU(), referenceSvd.matrixU().leftCols(diagSize));
-  if(computationOptions & ComputeFullV)
-    VERIFY_IS_APPROX(svd.matrixV(), referenceSvd.matrixV());
-  if(computationOptions & ComputeThinV)
-    VERIFY_IS_APPROX(svd.matrixV(), referenceSvd.matrixV().leftCols(diagSize));
-} // end svd_compare_to_full
-
-
-
-template<typename MatrixType, typename SVD>
-void svd_solve(const MatrixType& m, unsigned int computationOptions)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime
-  };
-
-  typedef Matrix<Scalar, RowsAtCompileTime, Dynamic> RhsType;
-  typedef Matrix<Scalar, ColsAtCompileTime, Dynamic> SolutionType;
-
-  RhsType rhs = RhsType::Random(rows, internal::random<Index>(1, cols));
-  SVD svd(m, computationOptions);
-  SolutionType x = svd.solve(rhs);
-  // evaluate normal equation which works also for least-squares solutions
-  VERIFY_IS_APPROX(m.adjoint()*m*x,m.adjoint()*rhs);
-} // end svd_solve
-
-
-// test computations options
-// 2 functions because Jacobisvd can return before the second function
-template<typename MatrixType, typename SVD>
-void svd_test_computation_options_1(const MatrixType& m, const SVD& fullSvd)
-{
-  svd_check_full< MatrixType, SVD >(m, fullSvd);
-  svd_solve< MatrixType, SVD >(m, ComputeFullU | ComputeFullV);
-}
-
-
-template<typename MatrixType, typename SVD>
-void svd_test_computation_options_2(const MatrixType& m, const SVD& fullSvd)
-{
-  svd_compare_to_full< MatrixType, SVD >(m, ComputeFullU, fullSvd);
-  svd_compare_to_full< MatrixType, SVD >(m, ComputeFullV, fullSvd);
-  svd_compare_to_full< MatrixType, SVD >(m, 0, fullSvd);
-
-  if (MatrixType::ColsAtCompileTime == Dynamic) {
-    // thin U/V are only available with dynamic number of columns
- 
-    svd_compare_to_full< MatrixType, SVD >(m, ComputeFullU|ComputeThinV, fullSvd);
-    svd_compare_to_full< MatrixType, SVD >(m,              ComputeThinV, fullSvd);
-    svd_compare_to_full< MatrixType, SVD >(m, ComputeThinU|ComputeFullV, fullSvd);
-    svd_compare_to_full< MatrixType, SVD >(m, ComputeThinU             , fullSvd);
-    svd_compare_to_full< MatrixType, SVD >(m, ComputeThinU|ComputeThinV, fullSvd);
-    svd_solve<MatrixType, SVD>(m, ComputeFullU | ComputeThinV);
-    svd_solve<MatrixType, SVD>(m, ComputeThinU | ComputeFullV);
-    svd_solve<MatrixType, SVD>(m, ComputeThinU | ComputeThinV);
-    
-    typedef typename MatrixType::Index Index;
-    Index diagSize = (std::min)(m.rows(), m.cols());
-    SVD svd(m, ComputeThinU | ComputeThinV);
-    VERIFY_IS_APPROX(m, svd.matrixU().leftCols(diagSize) * svd.singularValues().asDiagonal() * svd.matrixV().leftCols(diagSize).adjoint());
-  }
-}
-
-template<typename MatrixType, typename SVD> 
-void svd_verify_assert(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::Index Index;
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime
-  };
-
-  typedef Matrix<Scalar, RowsAtCompileTime, 1> RhsType;
-  RhsType rhs(rows);
-  SVD svd;
-  VERIFY_RAISES_ASSERT(svd.matrixU())
-  VERIFY_RAISES_ASSERT(svd.singularValues())
-  VERIFY_RAISES_ASSERT(svd.matrixV())
-  VERIFY_RAISES_ASSERT(svd.solve(rhs))
-  MatrixType a = MatrixType::Zero(rows, cols);
-  a.setZero();
-  svd.compute(a, 0);
-  VERIFY_RAISES_ASSERT(svd.matrixU())
-  VERIFY_RAISES_ASSERT(svd.matrixV())
-  svd.singularValues();
-  VERIFY_RAISES_ASSERT(svd.solve(rhs))
-    
-  if (ColsAtCompileTime == Dynamic)
-  {
-    svd.compute(a, ComputeThinU);
-    svd.matrixU();
-    VERIFY_RAISES_ASSERT(svd.matrixV())
-    VERIFY_RAISES_ASSERT(svd.solve(rhs))
-    svd.compute(a, ComputeThinV);
-    svd.matrixV();
-    VERIFY_RAISES_ASSERT(svd.matrixU())
-    VERIFY_RAISES_ASSERT(svd.solve(rhs))
-  }
-  else
-  {
-    VERIFY_RAISES_ASSERT(svd.compute(a, ComputeThinU))
-    VERIFY_RAISES_ASSERT(svd.compute(a, ComputeThinV))
-  }
-}
-
-// work around stupid msvc error when constructing at compile time an expression that involves
-// a division by zero, even if the numeric type has floating point
-template<typename Scalar>
-EIGEN_DONT_INLINE Scalar zero() { return Scalar(0); }
-
-// workaround aggressive optimization in ICC
-template<typename T> EIGEN_DONT_INLINE  T sub(T a, T b) { return a - b; }
-
-
-template<typename MatrixType, typename SVD>
-void svd_inf_nan()
-{
-  // all this function does is verify we don't iterate infinitely on nan/inf values
-
-  SVD svd;
-  typedef typename MatrixType::Scalar Scalar;
-  Scalar some_inf = Scalar(1) / zero<Scalar>();
-  VERIFY(sub(some_inf, some_inf) != sub(some_inf, some_inf));
-  svd.compute(MatrixType::Constant(10,10,some_inf), ComputeFullU | ComputeFullV);
-
-  Scalar some_nan = zero<Scalar> () / zero<Scalar> ();
-  VERIFY(some_nan != some_nan);
-  svd.compute(MatrixType::Constant(10,10,some_nan), ComputeFullU | ComputeFullV);
-
-  MatrixType m = MatrixType::Zero(10,10);
-  m(internal::random<int>(0,9), internal::random<int>(0,9)) = some_inf;
-  svd.compute(m, ComputeFullU | ComputeFullV);
-
-  m = MatrixType::Zero(10,10);
-  m(internal::random<int>(0,9), internal::random<int>(0,9)) = some_nan;
-  svd.compute(m, ComputeFullU | ComputeFullV);
-}
-
-
-template<typename SVD>
-void svd_preallocate()
-{
-  Vector3f v(3.f, 2.f, 1.f);
-  MatrixXf m = v.asDiagonal();
-
-  internal::set_is_malloc_allowed(false);
-  VERIFY_RAISES_ASSERT(VectorXf v(10);)
-    SVD svd;
-  internal::set_is_malloc_allowed(true);
-  svd.compute(m);
-  VERIFY_IS_APPROX(svd.singularValues(), v);
-
-  SVD svd2(3,3);
-  internal::set_is_malloc_allowed(false);
-  svd2.compute(m);
-  internal::set_is_malloc_allowed(true);
-  VERIFY_IS_APPROX(svd2.singularValues(), v);
-  VERIFY_RAISES_ASSERT(svd2.matrixU());
-  VERIFY_RAISES_ASSERT(svd2.matrixV());
-  svd2.compute(m, ComputeFullU | ComputeFullV);
-  VERIFY_IS_APPROX(svd2.matrixU(), Matrix3f::Identity());
-  VERIFY_IS_APPROX(svd2.matrixV(), Matrix3f::Identity());
-  internal::set_is_malloc_allowed(false);
-  svd2.compute(m);
-  internal::set_is_malloc_allowed(true);
-
-  SVD svd3(3,3,ComputeFullU|ComputeFullV);
-  internal::set_is_malloc_allowed(false);
-  svd2.compute(m);
-  internal::set_is_malloc_allowed(true);
-  VERIFY_IS_APPROX(svd2.singularValues(), v);
-  VERIFY_IS_APPROX(svd2.matrixU(), Matrix3f::Identity());
-  VERIFY_IS_APPROX(svd2.matrixV(), Matrix3f::Identity());
-  internal::set_is_malloc_allowed(false);
-  svd2.compute(m, ComputeFullU|ComputeFullV);
-  internal::set_is_malloc_allowed(true);
-}
-
-
-
-
-

ADDED   3rd_party/eigen/wscript
Index: 3rd_party/eigen/wscript
==================================================================
--- 3rd_party/eigen/wscript
+++ 3rd_party/eigen/wscript
@@ -0,0 +1,7 @@
+def build( bld ):
+        bld(
+                target = 'eigen',
+                includes = './',
+                export_includes = './'
+        )
+

ADDED   3rd_party/libdeflate/COPYING
Index: 3rd_party/libdeflate/COPYING
==================================================================
--- 3rd_party/libdeflate/COPYING
+++ 3rd_party/libdeflate/COPYING
@@ -0,0 +1,21 @@
+Copyright 2016 Eric Biggers
+
+Permission is hereby granted, free of charge, to any person
+obtaining a copy of this software and associated documentation files
+(the "Software"), to deal in the Software without restriction,
+including without limitation the rights to use, copy, modify, merge,
+publish, distribute, sublicense, and/or sell copies of the Software,
+and to permit persons to whom the Software is furnished to do so,
+subject to the following conditions:
+
+The above copyright notice and this permission notice shall be
+included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
+BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
+ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

ADDED   3rd_party/libdeflate/Makefile
Index: 3rd_party/libdeflate/Makefile
==================================================================
--- 3rd_party/libdeflate/Makefile
+++ 3rd_party/libdeflate/Makefile
@@ -0,0 +1,372 @@
+#
+# Use 'make help' to list available targets.
+#
+# Define V=1 to enable "verbose" mode, showing all executed commands.
+#
+# Define USE_SHARED_LIB to link the binaries to the shared library version of
+# libdeflate rather than to the static library version.
+#
+# Define DECOMPRESSION_ONLY to omit all compression code, building a
+# decompression-only library.  If doing this, you must also build a specific
+# library target such as 'libdeflate.a', as the programs will no longer compile.
+#
+# Define DISABLE_GZIP to disable support for the gzip wrapper format.
+#
+# Define DISABLE_ZLIB to disable support for the zlib wrapper format.
+#
+# Define PREFIX to override the installation prefix, like './configure --prefix'
+# in autotools-based projects (default: /usr/local)
+#
+# Define BINDIR to override where to install binaries, like './configure
+# --bindir' in autotools-based projects (default: PREFIX/bin)
+#
+# Define INCDIR to override where to install headers, like './configure
+# --includedir' in autotools-based projects (default: PREFIX/include)
+#
+# Define LIBDIR to override where to install libraries, like './configure
+# --libdir' in autotools-based projects (default: PREFIX/lib)
+#
+# Define DESTDIR to override the installation destination directory
+# (default: empty string)
+#
+# Define FREESTANDING to build a freestanding library, i.e. a library that
+# doesn't link to any libc functions like malloc(), free(), and memcpy().
+# All users will need to call libdeflate_set_memory_allocator().
+#
+# You can also specify a custom CC, CFLAGS, CPPFLAGS, and/or LDFLAGS.
+#
+##############################################################################
+
+#### Common compiler flags.  You can add additional flags by defining CFLAGS
+#### in the environment or on the 'make' command line.
+####
+#### The default optimization flags can be overridden, e.g. via CFLAGS="-O3" or
+#### CFLAGS="-O0 -fno-omit-frame-pointer".  But this usually isn't recommended;
+#### you're unlikely to get significantly better performance even with -O3.
+
+cc-option = $(shell if $(CC) $(1) -c -x c /dev/null -o /dev/null \
+	      1>&2 2>/dev/null; then echo $(1); fi)
+
+override CFLAGS :=							\
+	-O2 -fomit-frame-pointer -std=c99 -I. -Wall -Wundef		\
+	$(call cc-option,-Wpedantic)					\
+	$(call cc-option,-Wdeclaration-after-statement)			\
+	$(call cc-option,-Wmissing-prototypes)				\
+	$(call cc-option,-Wstrict-prototypes)				\
+	$(call cc-option,-Wvla)						\
+	$(call cc-option,-Wimplicit-fallthrough)			\
+	$(CFLAGS)
+
+FREESTANDING :=
+ifdef FREESTANDING
+override CPPFLAGS += -DFREESTANDING
+LIB_CFLAGS += -ffreestanding -nostdlib
+endif
+
+# Don't use this option except for testing; it isn't a stable interface.
+TEST_SUPPORT__DO_NOT_USE :=
+ifdef TEST_SUPPORT__DO_NOT_USE
+override CPPFLAGS += -DTEST_SUPPORT__DO_NOT_USE
+endif
+
+##############################################################################
+
+PREFIX ?= /usr/local
+BINDIR ?= $(PREFIX)/bin
+INCDIR ?= $(PREFIX)/include
+LIBDIR ?= $(PREFIX)/lib
+
+SOVERSION          := 0
+
+STATIC_LIB_SUFFIX  := .a
+PROG_SUFFIX        :=
+PROG_CFLAGS        :=
+HARD_LINKS         := 1
+
+# Compiling for Windows with MinGW?
+ifneq ($(findstring -mingw,$(shell $(CC) -dumpmachine 2>/dev/null)),)
+    STATIC_LIB_SUFFIX  := static.lib
+    SHARED_LIB         := libdeflate.dll
+    SHARED_LIB_SYMLINK :=
+    SHARED_LIB_CFLAGS  :=
+    SHARED_LIB_LDFLAGS := -Wl,--out-implib,libdeflate.lib \
+                          -Wl,--output-def,libdeflate.def \
+                          -Wl,--add-stdcall-alias
+    PROG_SUFFIX        := .exe
+    PROG_CFLAGS        := -static -municode
+    HARD_LINKS         :=
+    override CFLAGS    := $(CFLAGS) $(call cc-option,-Wno-pedantic-ms-format)
+
+    # If AR was not already overridden, then derive it from $(CC).
+    # Note that CC may take different forms, e.g. "cc", "gcc",
+    # "x86_64-w64-mingw32-gcc", or "x86_64-w64-mingw32-gcc-6.3.1".
+    # On Windows it may also have a .exe extension.
+    ifeq ($(AR),ar)
+        AR := $(shell echo $(CC) | \
+                sed -E 's/g?cc(-?[0-9]+(\.[0-9]+)*)?(\.exe)?$$/ar\3/')
+    endif
+
+# macOS?
+else ifeq ($(shell uname),Darwin)
+   SHARED_LIB         := libdeflate.$(SOVERSION).dylib
+   SHARED_LIB_SYMLINK := libdeflate.dylib
+   SHARED_LIB_CFLAGS  := -fPIC
+   SHARED_LIB_LDFLAGS := -install_name $(SHARED_LIB)
+
+# Linux, FreeBSD, etc.
+else
+   SHARED_LIB         := libdeflate.so.$(SOVERSION)
+   SHARED_LIB_SYMLINK := libdeflate.so
+   SHARED_LIB_CFLAGS  := -fPIC
+   SHARED_LIB_LDFLAGS := -Wl,-soname=$(SHARED_LIB)
+endif
+
+##############################################################################
+
+#### Quiet make is enabled by default.  Define V=1 to disable.
+
+ifneq ($(findstring s,$(MAKEFLAGS)),s)
+ifneq ($(V),1)
+        QUIET_CC       = @echo '  CC      ' $@;
+        QUIET_CCLD     = @echo '  CCLD    ' $@;
+        QUIET_AR       = @echo '  AR      ' $@;
+        QUIET_LN       = @echo '  LN      ' $@;
+        QUIET_CP       = @echo '  CP      ' $@;
+        QUIET_GEN      = @echo '  GEN     ' $@;
+endif
+endif
+
+##############################################################################
+
+# Rebuild if a user-specified setting that affects the build changed.
+.build-config: FORCE
+	@flags=$$(							\
+		echo 'USE_SHARED_LIB=$(USE_SHARED_LIB)';		\
+		echo 'DECOMPRESSION_ONLY=$(DECOMPRESSION_ONLY)';	\
+		echo 'DISABLE_GZIP=$(DISABLE_GZIP)';			\
+		echo 'DISABLE_ZLIB=$(DISABLE_ZLIB)';			\
+		echo 'FREESTANDING=$(FREESTANDING)';			\
+		echo 'CC=$(CC)';					\
+		echo 'CFLAGS=$(CFLAGS)';				\
+		echo 'CPPFLAGS=$(CPPFLAGS)';				\
+		echo 'LDFLAGS=$(LDFLAGS)';				\
+	);								\
+	if [ "$$flags" != "`cat $@ 2>/dev/null`" ]; then		\
+		[ -e $@ ] && echo "Rebuilding due to new settings";	\
+		echo "$$flags" > $@;					\
+	fi
+
+##############################################################################
+
+COMMON_HEADERS := $(wildcard common/*.h) libdeflate.h
+DEFAULT_TARGETS :=
+
+#### Library
+
+STATIC_LIB := libdeflate$(STATIC_LIB_SUFFIX)
+
+LIB_CFLAGS += $(CFLAGS) -fvisibility=hidden -D_ANSI_SOURCE
+
+LIB_HEADERS := $(wildcard lib/*.h) $(wildcard lib/*/*.h)
+
+LIB_SRC := lib/deflate_decompress.c lib/utils.c \
+	   $(wildcard lib/*/cpu_features.c)
+
+DECOMPRESSION_ONLY :=
+ifndef DECOMPRESSION_ONLY
+    LIB_SRC += lib/deflate_compress.c
+endif
+
+DISABLE_ZLIB :=
+ifndef DISABLE_ZLIB
+    LIB_SRC += lib/adler32.c lib/zlib_decompress.c
+    ifndef DECOMPRESSION_ONLY
+        LIB_SRC += lib/zlib_compress.c
+    endif
+endif
+
+DISABLE_GZIP :=
+ifndef DISABLE_GZIP
+    LIB_SRC += lib/crc32.c lib/gzip_decompress.c
+    ifndef DECOMPRESSION_ONLY
+        LIB_SRC += lib/gzip_compress.c
+    endif
+endif
+
+STATIC_LIB_OBJ := $(LIB_SRC:.c=.o)
+SHARED_LIB_OBJ := $(LIB_SRC:.c=.shlib.o)
+
+# Compile static library object files
+$(STATIC_LIB_OBJ): %.o: %.c $(LIB_HEADERS) $(COMMON_HEADERS) .build-config
+	$(QUIET_CC) $(CC) -o $@ -c $(CPPFLAGS) $(LIB_CFLAGS) $<
+
+# Compile shared library object files
+$(SHARED_LIB_OBJ): %.shlib.o: %.c $(LIB_HEADERS) $(COMMON_HEADERS) .build-config
+	$(QUIET_CC) $(CC) -o $@ -c $(CPPFLAGS) $(LIB_CFLAGS) \
+		$(SHARED_LIB_CFLAGS) -DLIBDEFLATE_DLL $<
+
+# Create static library
+$(STATIC_LIB):$(STATIC_LIB_OBJ)
+	$(QUIET_AR) $(AR) cr $@ $+
+
+DEFAULT_TARGETS += $(STATIC_LIB)
+
+# Create shared library
+$(SHARED_LIB):$(SHARED_LIB_OBJ)
+	$(QUIET_CCLD) $(CC) -o $@ $(LDFLAGS) $(LIB_CFLAGS) \
+		$(SHARED_LIB_LDFLAGS) -shared $+
+
+DEFAULT_TARGETS += $(SHARED_LIB)
+
+ifdef SHARED_LIB_SYMLINK
+# Create the symlink libdeflate.so => libdeflate.so.$SOVERSION
+$(SHARED_LIB_SYMLINK):$(SHARED_LIB)
+	$(QUIET_LN) ln -sf $+ $@
+DEFAULT_TARGETS += $(SHARED_LIB_SYMLINK)
+endif
+
+##############################################################################
+
+#### Programs
+
+PROG_CFLAGS += $(CFLAGS)		 \
+	       -D_POSIX_C_SOURCE=200809L \
+	       -D_FILE_OFFSET_BITS=64	 \
+	       -DHAVE_CONFIG_H
+
+ALL_PROG_COMMON_HEADERS := programs/config.h \
+			   programs/prog_util.h \
+			   programs/test_util.h
+PROG_COMMON_SRC      := programs/prog_util.c \
+			programs/tgetopt.c
+NONTEST_PROG_SRC     := programs/gzip.c
+TEST_PROG_COMMON_SRC := programs/test_util.c
+TEST_PROG_SRC        := programs/benchmark.c \
+			programs/checksum.c \
+			$(filter-out $(TEST_PROG_COMMON_SRC),$(wildcard programs/test_*.c))
+
+NONTEST_PROGRAMS := $(NONTEST_PROG_SRC:programs/%.c=%$(PROG_SUFFIX))
+DEFAULT_TARGETS  += $(NONTEST_PROGRAMS)
+TEST_PROGRAMS    := $(TEST_PROG_SRC:programs/%.c=%$(PROG_SUFFIX))
+
+PROG_COMMON_OBJ      := $(PROG_COMMON_SRC:%.c=%.o)
+NONTEST_PROG_OBJ     := $(NONTEST_PROG_SRC:%.c=%.o)
+TEST_PROG_COMMON_OBJ := $(TEST_PROG_COMMON_SRC:%.c=%.o)
+TEST_PROG_OBJ        := $(TEST_PROG_SRC:%.c=%.o)
+
+ALL_PROG_OBJ	     := $(PROG_COMMON_OBJ) $(NONTEST_PROG_OBJ) \
+			$(TEST_PROG_COMMON_OBJ) $(TEST_PROG_OBJ)
+
+# Generate autodetected configuration header
+programs/config.h:scripts/detect.sh .build-config
+	$(QUIET_GEN) CC="$(CC)" CFLAGS="$(PROG_CFLAGS)" $< > $@
+
+# Compile program object files
+$(ALL_PROG_OBJ): %.o: %.c $(ALL_PROG_COMMON_HEADERS) $(COMMON_HEADERS) \
+			.build-config
+	$(QUIET_CC) $(CC) -o $@ -c $(CPPFLAGS) $(PROG_CFLAGS) $<
+
+# Link the programs.
+#
+# Note: the test programs are not compiled by default.  One reason is that the
+# test programs must be linked with zlib for doing comparisons.
+
+ifdef USE_SHARED_LIB
+LIB := $(SHARED_LIB)
+else
+LIB := $(STATIC_LIB)
+endif
+
+$(NONTEST_PROGRAMS): %$(PROG_SUFFIX): programs/%.o $(PROG_COMMON_OBJ) $(LIB)
+	$(QUIET_CCLD) $(CC) -o $@ $(LDFLAGS) $(PROG_CFLAGS) $+
+
+$(TEST_PROGRAMS): %$(PROG_SUFFIX): programs/%.o $(PROG_COMMON_OBJ) \
+			$(TEST_PROG_COMMON_OBJ) $(LIB)
+	$(QUIET_CCLD) $(CC) -o $@ $(LDFLAGS) $(PROG_CFLAGS) $+ -lz
+
+ifdef HARD_LINKS
+# Hard link gunzip to gzip
+gunzip$(PROG_SUFFIX):gzip$(PROG_SUFFIX)
+	$(QUIET_LN) ln -f $< $@
+else
+# No hard links; copy gzip to gunzip
+gunzip$(PROG_SUFFIX):gzip$(PROG_SUFFIX)
+	$(QUIET_CP) cp -f $< $@
+endif
+
+DEFAULT_TARGETS += gunzip$(PROG_SUFFIX)
+
+##############################################################################
+
+all:$(DEFAULT_TARGETS)
+
+# Install the files.  Note: not all versions of the 'install' program have the
+# '-D' and '-t' options, so don't use them; use portable commands only.
+install:all
+	install -d $(DESTDIR)$(LIBDIR) $(DESTDIR)$(INCDIR) $(DESTDIR)$(BINDIR)
+	install -m644 $(STATIC_LIB) $(DESTDIR)$(LIBDIR)
+	install -m755 $(SHARED_LIB) $(DESTDIR)$(LIBDIR)
+	install -m644 libdeflate.h $(DESTDIR)$(INCDIR)
+	install -m755 gzip$(PROG_SUFFIX) \
+		$(DESTDIR)$(BINDIR)/libdeflate-gzip$(PROG_SUFFIX)
+	ln -f $(DESTDIR)$(BINDIR)/libdeflate-gzip$(PROG_SUFFIX)		\
+	      $(DESTDIR)$(BINDIR)/libdeflate-gunzip$(PROG_SUFFIX)
+	if [ -n "$(SHARED_LIB_SYMLINK)" ]; then				\
+		ln -sf $(SHARED_LIB)					\
+		       $(DESTDIR)$(LIBDIR)/$(SHARED_LIB_SYMLINK);	\
+	fi
+
+uninstall:
+	rm -f $(DESTDIR)$(LIBDIR)/$(STATIC_LIB)				\
+	      $(DESTDIR)$(LIBDIR)/$(SHARED_LIB)				\
+	      $(DESTDIR)$(INCDIR)/libdeflate.h				\
+	      $(DESTDIR)$(BINDIR)/libdeflate-gzip$(PROG_SUFFIX)		\
+	      $(DESTDIR)$(BINDIR)/libdeflate-gunzip$(PROG_SUFFIX)
+	if [ -n "$(SHARED_LIB_SYMLINK)" ]; then				\
+		rm -f $(DESTDIR)$(LIBDIR)/$(SHARED_LIB_SYMLINK);	\
+	fi
+
+test_programs:$(TEST_PROGRAMS)
+
+# A minimal 'make check' target.  This only runs some quick tests;
+# use scripts/run_tests.sh if you want to run the full tests.
+check:test_programs
+	LD_LIBRARY_PATH=. ./benchmark$(PROG_SUFFIX) < ./benchmark$(PROG_SUFFIX)
+	for prog in test_*; do		\
+		LD_LIBRARY_PATH=. ./$$prog || exit 1;	\
+	done
+
+# Run the clang static analyzer.
+scan-build:
+	scan-build --status-bugs make all test_programs
+
+# Run shellcheck on all shell scripts.
+shellcheck:
+	shellcheck scripts/*.sh
+
+help:
+	@echo "Available targets:"
+	@echo "------------------"
+	@for target in $(DEFAULT_TARGETS) $(TEST_PROGRAMS); do \
+		echo -e "$$target";		\
+	done
+
+clean:
+	rm -f *.a *.dll *.exe *.exp *.dylib *.so \
+		lib/*.o lib/*/*.o \
+		lib/*.obj lib/*/*.obj \
+		lib/*.dllobj lib/*/*.dllobj \
+		programs/*.o programs/*.obj \
+		$(DEFAULT_TARGETS) $(TEST_PROGRAMS) programs/config.h \
+		libdeflate.lib libdeflate.def libdeflatestatic.lib \
+		.build-config
+
+realclean: clean
+	rm -f tags cscope*
+
+FORCE:
+
+.PHONY: all install uninstall test_programs check scan-build shellcheck help \
+	clean realclean
+
+.DEFAULT_GOAL = all

ADDED   3rd_party/libdeflate/Makefile.msc
Index: 3rd_party/libdeflate/Makefile.msc
==================================================================
--- 3rd_party/libdeflate/Makefile.msc
+++ 3rd_party/libdeflate/Makefile.msc
@@ -0,0 +1,65 @@
+#
+# Makefile for the Microsoft toolchain
+#
+# Usage:
+#	nmake /f Makefile.msc
+#
+
+.SUFFIXES: .c .obj .dllobj
+
+CC = cl
+LD = link
+AR = lib
+CFLAGS = /MD /O2 -I.
+LDFLAGS =
+
+STATIC_LIB = libdeflatestatic.lib
+SHARED_LIB = libdeflate.dll
+IMPORT_LIB = libdeflate.lib
+
+STATIC_LIB_OBJ =			\
+	  lib/adler32.obj		\
+	  lib/crc32.obj			\
+	  lib/deflate_compress.obj	\
+	  lib/deflate_decompress.obj	\
+	  lib/gzip_compress.obj		\
+	  lib/gzip_decompress.obj	\
+	  lib/utils.obj			\
+	  lib/x86/cpu_features.obj	\
+	  lib/zlib_compress.obj		\
+	  lib/zlib_decompress.obj
+
+SHARED_LIB_OBJ = $(STATIC_LIB_OBJ:.obj=.dllobj)
+
+PROG_COMMON_OBJ = programs/prog_util.obj \
+		  programs/tgetopt.obj \
+		  $(STATIC_LIB)
+
+PROG_CFLAGS = $(CFLAGS) -Iprograms
+
+all: $(STATIC_LIB) $(SHARED_LIB) $(IMPORT_LIB) gzip.exe gunzip.exe
+
+.c.obj:
+	$(CC) -c /Fo$@ $(CFLAGS) $**
+
+.c.dllobj:
+	$(CC) -c /Fo$@ $(CFLAGS) /DLIBDEFLATE_DLL $**
+
+$(STATIC_LIB): $(STATIC_LIB_OBJ)
+	$(AR) $(ARFLAGS) -out:$@ $(STATIC_LIB_OBJ)
+
+$(SHARED_LIB): $(SHARED_LIB_OBJ)
+	$(LD) $(LDFLAGS) -out:$@ -dll -implib:$(IMPORT_LIB) $(SHARED_LIB_OBJ)
+
+$(IMPORT_LIB): $(SHARED_LIB)
+
+gzip.exe:programs/gzip.obj $(PROG_COMMON_OBJ)
+	$(LD) $(LDFLAGS) -out:$@ $**
+
+gunzip.exe:gzip.exe
+	copy $** $@
+
+clean:
+	-del *.dll *.exe *.exp libdeflate.lib libdeflatestatic.lib gzip.lib \
+		lib\*.obj lib\x86\*.obj lib\*.dllobj lib\x86\*.dllobj \
+		programs\*.obj 2>nul

ADDED   3rd_party/libdeflate/NEWS
Index: 3rd_party/libdeflate/NEWS
==================================================================
--- 3rd_party/libdeflate/NEWS
+++ 3rd_party/libdeflate/NEWS
@@ -0,0 +1,200 @@
+Version 1.7:
+	Added support for compression level 0, "no compression".
+
+	Added an ARM CRC32 instruction accelerated implementation of CRC32.
+
+	Added support for linking the programs to the shared library version of
+	libdeflate rather than to the static library version.
+
+	Made the compression level affect the minimum input size at which
+	compression is attempted.
+
+	Fixed undefined behavior in x86 Adler32 implementation.
+	(No miscompilations were observed in practice.)
+
+	Fixed undefined behavior in x86 CPU feature code.
+	(No miscompilations were observed in practice.)
+
+	Fixed installing shared lib symlink on macOS.
+
+	Documented third-party bindings.
+
+	Made a lot of improvements to the testing scripts and the CI
+	configuration file.
+
+	Lots of other small improvements and cleanups.
+
+Version 1.6:
+	Prevented gcc 10 from miscompiling libdeflate (workaround for
+	https://gcc.gnu.org/bugzilla/show_bug.cgi?id=94994).
+
+	Removed workaround for gcc 5 and earlier producing slow code on
+	ARM32.  If this affects you, please upgrade your compiler.
+
+	New API function: libdeflate_zlib_decompress_ex().  It provides
+	the actual size of the stream that was decompressed, like the
+	gzip and DEFLATE equivalents.
+
+	libdeflate_zlib_decompress() now accepts trailing bytes after
+	the end of the stream, like the gzip and DEFLATE equivalents.
+
+	Added support for custom memory allocators.
+	(New API function: libdeflate_set_memory_allocator())
+
+	Added support for building the library in freestanding mode.
+
+	Building libdeflate no longer requires CPPFLAGS=-Icommon.
+
+Version 1.5:
+	Fixed up stdcall support on 32-bit Windows: the functions are
+	now exported using both suffixed and non-suffixed names, and
+	fixed libdeflate.h to be MSVC-compatible again.
+
+Version 1.4:
+	The 32-bit Windows build of libdeflate now uses the "stdcall"
+	calling convention instead of "cdecl".  If you're calling
+	libdeflate.dll directly from C or C++, you'll need to recompile
+	your code.  If you're calling it from another language, or
+	calling it indirectly using LoadLibrary(), you'll need to update
+	your code to use the stdcall calling convention.
+
+	The Makefile now supports building libdeflate as a shared
+	library (.dylib) on macOS.
+
+	Fixed a bug where support for certain optimizations and optional
+	features (file access hints and more precise timestamps) was
+	incorrectly omitted when libdeflate was compiled with -Werror.
+
+	Added 'make check' target to the Makefile.
+
+	Added CI configuration files.
+
+Version 1.3:
+	`make install` now supports customizing the directories into
+	which binaries, headers, and libraries are installed.
+
+	`make install` now installs into /usr/local by default.
+	To change it, use e.g. `make install PREFIX=/usr`.
+
+	`make install` now works on more platforms.
+
+	The Makefile now supports overriding the optimization flags.
+
+	The compression functions now correctly handle an output data
+	buffer >= 4 GiB in size, and `gzip` and `gunzip` now correctly
+	handle multi-gigabyte files (if enough memory is available).
+
+Version 1.2:
+	Slight improvements to decompression speed.
+
+	Added an AVX-512BW implementation of Adler-32.
+
+	The Makefile now supports a user-specified installation PREFIX.
+
+	Fixed build error with some Visual Studio versions.
+
+Version 1.1:
+	Fixed crash in CRC-32 code when the prebuilt libdeflate for
+	32-bit Windows was called by a program built with Visual Studio.
+
+	Improved the worst-case decompression speed of malicious data.
+
+	Fixed build error when compiling for an ARM processor without
+	hardware floating point support.
+
+	Improved performance on the PowerPC64 architecture.
+
+	Added soname to libdeflate.so, to make packaging easier.
+
+	Added 'make install' target to the Makefile.
+
+	The Makefile now supports user-specified CPPFLAGS.
+
+	The Windows binary releases now include the import library for
+	libdeflate.dll.  libdeflate.lib is now the import library, and
+	libdeflatestatic.lib is the static library.
+
+Version 1.0:
+	Added support for multi-member gzip files.
+
+	Moved architecture-specific code into subdirectories.  If you
+	aren't using the provided Makefile to build libdeflate, you now
+	need to compile lib/*.c and lib/*/*.c instead of just lib/*.c.
+
+	Added an ARM PMULL implementation of CRC-32, which speeds up
+	gzip compression and decompression on 32-bit and 64-bit ARM
+	processors that have the Cryptography Extensions.
+
+	Improved detection of CPU features, resulting in accelerated
+	functions being used in more cases.  This includes:
+
+	   - Detect CPU features on 32-bit x86, not just 64-bit as was
+	     done previously.
+
+	   - Detect CPU features on ARM, both 32 and 64-bit.
+	     (Limited to Linux only currently.)
+
+Version 0.8:
+	Build fixes for certain platforms and compilers.
+
+	libdeflate now produces the same output on all CPU architectures.
+
+	Improved documentation for building libdeflate on Windows.
+
+Version 0.7:
+	Fixed a very rare bug that caused data to be compressed incorrectly.
+	The bug affected compression levels 7 and below since libdeflate v0.2.
+	Although there have been no user reports of the bug, and I believe it
+	would have been highly unlikely to encounter on realistic data, it could
+	occur on data specially crafted to reproduce it.
+
+	Fixed a compilation error when building with clang 3.7.
+
+Version 0.6:
+	Various improvements to the gzip program's behavior.
+
+	Faster CRC-32 on AVX-capable processors.
+
+	Other minor changes.
+
+Version 0.5:
+	The CRC-32 checksum algorithm has been optimized with carryless
+	multiplication instructions for x86_64 (PCLMUL).  This speeds up gzip
+	compression and decompression.
+
+	Build fixes for certain platforms and compilers.
+
+	Added more test programs and scripts.
+
+	libdeflate is now entirely MIT-licensed.
+
+Version 0.4:
+	The Adler-32 checksum algorithm has been optimized with vector
+	instructions for x86_64 (SSE2 and AVX2) and ARM (NEON).  This speeds up
+	zlib compression and decompression.
+
+	To avoid naming collisions, functions and definitions in libdeflate's
+	API have been renamed to be prefixed with "libdeflate_" or
+	"LIBDEFLATE_".  Programs using the old API will need to be updated.
+
+	Various bug fixes and other improvements.
+
+Version 0.3:
+	Some bug fixes and other minor changes.
+
+Version 0.2:
+	Implemented a new block splitting algorithm which typically improves the
+	compression ratio slightly at all compression levels.
+
+	The compressor now outputs each block using the cheapest type (dynamic
+	Huffman, static Huffman, or uncompressed).
+
+	The gzip program has received an overhaul and now behaves more like the
+	standard version.
+
+	Build system updates, including: some build options were changed and
+	some build options were removed, and the default 'make' target now
+	includes the gzip program as well as the library.
+
+Version 0.1:
+	Initial official release.

ADDED   3rd_party/libdeflate/README.md
Index: 3rd_party/libdeflate/README.md
==================================================================
--- 3rd_party/libdeflate/README.md
+++ 3rd_party/libdeflate/README.md
@@ -0,0 +1,283 @@
+# Overview
+
+libdeflate is a library for fast, whole-buffer DEFLATE-based compression and
+decompression.
+
+The supported formats are:
+
+- DEFLATE (raw)
+- zlib (a.k.a. DEFLATE with a zlib wrapper)
+- gzip (a.k.a. DEFLATE with a gzip wrapper)
+
+libdeflate is heavily optimized.  It is significantly faster than the zlib
+library, both for compression and decompression, and especially on x86
+processors.  In addition, libdeflate provides optional high compression modes
+that provide a better compression ratio than the zlib's "level 9".
+
+libdeflate itself is a library, but the following command-line programs which
+use this library are also provided:
+
+* gzip (or gunzip), a program which mostly behaves like the standard equivalent,
+  except that it does not yet have good streaming support and therefore does not
+  yet support very large files
+* benchmark, a program for benchmarking in-memory compression and decompression
+
+## Table of Contents
+
+- [Building](#building)
+  - [For UNIX](#for-unix)
+  - [For macOS](#for-macos)
+  - [For Windows](#for-windows)
+    - [Using Cygwin](#using-cygwin)
+    - [Using MSYS2](#using-msys2)
+- [API](#api)
+- [Bindings for other programming languages](#bindings-for-other-programming-languages)
+- [DEFLATE vs. zlib vs. gzip](#deflate-vs-zlib-vs-gzip)
+- [Compression levels](#compression-levels)
+- [Motivation](#motivation)
+- [License](#license)
+
+
+# Building
+
+## For UNIX
+
+Just run `make`, then (if desired) `make install`.  You need GNU Make and either
+GCC or Clang.  GCC is recommended because it builds slightly faster binaries.
+
+By default, the following targets are built: the static library `libdeflate.a`,
+the shared library `libdeflate.so`, the `gzip` program, and the `gunzip` program
+(which is actually just a hard link to `gzip`).  Benchmarking and test programs
+such as `benchmark` are not built by default.  You can run `make help` to
+display the available build targets.
+
+There are also many options which can be set on the `make` command line, e.g. to
+omit library features or to customize the directories into which `make install`
+installs files.  See the Makefile for details.
+
+## For macOS
+
+Prebuilt macOS binaries can be installed with [Homebrew](https://brew.sh):
+
+    brew install libdeflate
+
+But if you need to build the binaries yourself, see the section for UNIX above.
+
+## For Windows
+
+Prebuilt Windows binaries can be downloaded from
+https://github.com/ebiggers/libdeflate/releases.  But if you need to build the
+binaries yourself, MinGW (gcc) is the recommended compiler to use.  If you're
+performing the build *on* Windows (as opposed to cross-compiling for Windows on
+Linux, for example), you'll need to follow the directions in **one** of the two
+sections below to set up a minimal UNIX-compatible environment using either
+Cygwin or MSYS2, then do the build.  (Other MinGW distributions may not work, as
+they often omit basic UNIX tools such as `sh`.)
+
+Alternatively, libdeflate may be built using the Visual Studio toolchain by
+running `nmake /f Makefile.msc`.  However, while this is supported in the sense
+that it will produce working binaries, it is not recommended because the
+binaries built with MinGW will be significantly faster.
+
+Also note that 64-bit binaries are faster than 32-bit binaries and should be
+preferred whenever possible.
+
+### Using Cygwin
+
+Run the Cygwin installer, available from https://cygwin.com/setup-x86_64.exe.
+When you get to the package selection screen, choose the following additional
+packages from category "Devel":
+
+- git
+- make
+- mingw64-i686-binutils
+- mingw64-i686-gcc-g++
+- mingw64-x86_64-binutils
+- mingw64-x86_64-gcc-g++
+
+(You may skip the mingw64-i686 packages if you don't need to build 32-bit
+binaries.)
+
+After the installation finishes, open a Cygwin terminal.  Then download
+libdeflate's source code (if you haven't already) and `cd` into its directory:
+
+    git clone https://github.com/ebiggers/libdeflate
+    cd libdeflate
+
+(Note that it's not required to use `git`; an alternative is to extract a .zip
+or .tar.gz archive of the source code downloaded from the releases page.
+Also, in case you need to find it in the file browser, note that your home
+directory in Cygwin is usually located at `C:\cygwin64\home\<your username>`.)
+
+Then, to build 64-bit binaries:
+
+    make CC=x86_64-w64-mingw32-gcc
+
+or to build 32-bit binaries:
+
+    make CC=i686-w64-mingw32-gcc
+
+### Using MSYS2
+
+Run the MSYS2 installer, available from http://www.msys2.org/.  After
+installing, open an MSYS2 shell and run:
+
+    pacman -Syu
+
+Say `y`, then when it's finished, close the shell window and open a new one.
+Then run the same command again:
+
+    pacman -Syu
+
+Then, install the packages needed to build libdeflate:
+
+    pacman -S git \
+              make \
+              mingw-w64-i686-binutils \
+              mingw-w64-i686-gcc \
+              mingw-w64-x86_64-binutils \
+              mingw-w64-x86_64-gcc
+
+(You may skip the mingw-w64-i686 packages if you don't need to build 32-bit
+binaries.)
+
+Then download libdeflate's source code (if you haven't already):
+
+    git clone https://github.com/ebiggers/libdeflate
+
+(Note that it's not required to use `git`; an alternative is to extract a .zip
+or .tar.gz archive of the source code downloaded from the releases page.
+Also, in case you need to find it in the file browser, note that your home
+directory in MSYS2 is usually located at `C:\msys64\home\<your username>`.)
+
+Then, to build 64-bit binaries, open "MSYS2 MinGW 64-bit" from the Start menu
+and run the following commands:
+
+    cd libdeflate
+    make clean
+    make
+
+Or to build 32-bit binaries, do the same but use "MSYS2 MinGW 32-bit" instead.
+
+# API
+
+libdeflate has a simple API that is not zlib-compatible.  You can create
+compressors and decompressors and use them to compress or decompress buffers.
+See libdeflate.h for details.
+
+There is currently no support for streaming.  This has been considered, but it
+always significantly increases complexity and slows down fast paths.
+Unfortunately, at this point it remains a future TODO.  So: if your application
+compresses data in "chunks", say, less than 1 MB in size, then libdeflate is a
+great choice for you; that's what it's designed to do.  This is perfect for
+certain use cases such as transparent filesystem compression.  But if your
+application compresses large files as a single compressed stream, similarly to
+the `gzip` program, then libdeflate isn't for you.
+
+Note that with chunk-based compression, you generally should have the
+uncompressed size of each chunk stored outside of the compressed data itself.
+This enables you to allocate an output buffer of the correct size without
+guessing.  However, libdeflate's decompression routines do optionally provide
+the actual number of output bytes in case you need it.
+
+Windows developers: note that the calling convention of libdeflate.dll is
+"stdcall" -- the same as the Win32 API.  If you call into libdeflate.dll using a
+non-C/C++ language, or dynamically using LoadLibrary(), make sure to use the
+stdcall convention.  Using the wrong convention may crash your application.
+(Note: older versions of libdeflate used the "cdecl" convention instead.)
+
+# Bindings for other programming languages
+
+The libdeflate project itself only provides a C library.  If you need to use
+libdeflate from a programming language other than C or C++, consider using the
+following bindings:
+
+* C#: [LibDeflate.NET](https://github.com/jzebedee/LibDeflate.NET)
+* Go: [go-libdeflate](https://github.com/4kills/go-libdeflate)
+* Java: [libdeflate-java](https://github.com/astei/libdeflate-java)
+* Julia: [LibDeflate.jl](https://github.com/jakobnissen/LibDeflate.jl)
+* Python: [deflate](https://github.com/dcwatson/deflate)
+* Ruby: [libdeflate-ruby](https://github.com/kaorimatz/libdeflate-ruby)
+* Rust: [libdeflater](https://github.com/adamkewley/libdeflater)
+
+Note: these are third-party projects which haven't necessarily been vetted by
+the authors of libdeflate.  Please direct all questions, bugs, and improvements
+for these bindings to their authors.
+
+# DEFLATE vs. zlib vs. gzip
+
+The DEFLATE format ([rfc1951](https://www.ietf.org/rfc/rfc1951.txt)), the zlib
+format ([rfc1950](https://www.ietf.org/rfc/rfc1950.txt)), and the gzip format
+([rfc1952](https://www.ietf.org/rfc/rfc1952.txt)) are commonly confused with
+each other as well as with the [zlib software library](http://zlib.net), which
+actually supports all three formats.  libdeflate (this library) also supports
+all three formats.
+
+Briefly, DEFLATE is a raw compressed stream, whereas zlib and gzip are different
+wrappers for this stream.  Both zlib and gzip include checksums, but gzip can
+include extra information such as the original filename.  Generally, you should
+choose a format as follows:
+
+- If you are compressing whole files with no subdivisions, similar to the `gzip`
+  program, you probably should use the gzip format.
+- Otherwise, if you don't need the features of the gzip header and footer but do
+  still want a checksum for corruption detection, you probably should use the
+  zlib format.
+- Otherwise, you probably should use raw DEFLATE.  This is ideal if you don't
+  need checksums, e.g. because they're simply not needed for your use case or
+  because you already compute your own checksums that are stored separately from
+  the compressed stream.
+
+Note that gzip and zlib streams can be distinguished from each other based on
+their starting bytes, but this is not necessarily true of raw DEFLATE streams.
+
+# Compression levels
+
+An often-underappreciated fact of compression formats such as DEFLATE is that
+there are an enormous number of different ways that a given input could be
+compressed.  Different algorithms and different amounts of computation time will
+result in different compression ratios, while remaining equally compatible with
+the decompressor.
+
+For this reason, the commonly used zlib library provides nine compression
+levels.  Level 1 is the fastest but provides the worst compression; level 9
+provides the best compression but is the slowest.  It defaults to level 6.
+libdeflate uses this same design but is designed to improve on both zlib's
+performance *and* compression ratio at every compression level.  In addition,
+libdeflate's levels go [up to 12](https://xkcd.com/670/) to make room for a
+minimum-cost-path based algorithm (sometimes called "optimal parsing") that can
+significantly improve on zlib's compression ratio.
+
+If you are using DEFLATE (or zlib, or gzip) in your application, you should test
+different levels to see which works best for your application.
+
+# Motivation
+
+Despite DEFLATE's widespread use mainly through the zlib library, in the
+compression community this format from the early 1990s is often considered
+obsolete.  And in a few significant ways, it is.
+
+So why implement DEFLATE at all, instead of focusing entirely on
+bzip2/LZMA/xz/LZ4/LZX/ZSTD/Brotli/LZHAM/LZFSE/[insert cool new format here]?
+
+To do something better, you need to understand what came before.  And it turns
+out that most ideas from DEFLATE are still relevant.  Many of the newer formats
+share a similar structure as DEFLATE, with different tweaks.  The effects of
+trivial but very useful tweaks, such as increasing the sliding window size, are
+often confused with the effects of nontrivial but less useful tweaks.  And
+actually, many of these formats are similar enough that common algorithms and
+optimizations (e.g. those dealing with LZ77 matchfinding) can be reused.
+
+In addition, comparing compressors fairly is difficult because the performance
+of a compressor depends heavily on optimizations which are not intrinsic to the
+compression format itself.  In this respect, the zlib library sometimes compares
+poorly to certain newer code because zlib is not well optimized for modern
+processors.  libdeflate addresses this by providing an optimized DEFLATE
+implementation which can be used for benchmarking purposes.  And, of course,
+real applications can use it as well.
+
+# License
+
+libdeflate is [MIT-licensed](COPYING).
+
+I am not aware of any patents or patent applications relevant to libdeflate.

ADDED   3rd_party/libdeflate/common/common_defs.h
Index: 3rd_party/libdeflate/common/common_defs.h
==================================================================
--- 3rd_party/libdeflate/common/common_defs.h
+++ 3rd_party/libdeflate/common/common_defs.h
@@ -0,0 +1,334 @@
+/*
+ * common_defs.h
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#ifndef COMMON_COMMON_DEFS_H
+#define COMMON_COMMON_DEFS_H
+
+#ifdef __GNUC__
+#  include "compiler_gcc.h"
+#elif defined(_MSC_VER)
+#  include "compiler_msc.h"
+#else
+#  pragma message("Unrecognized compiler.  Please add a header file for your compiler.  Compilation will proceed, but performance may suffer!")
+#endif
+
+/* ========================================================================== */
+/*                              Type definitions                              */
+/* ========================================================================== */
+
+#include <stddef.h> /* size_t */
+
+#ifndef __bool_true_false_are_defined
+#  include <stdbool.h> /* bool */
+#endif
+
+/* Fixed-width integer types */
+#include <stdint.h>
+typedef uint8_t u8;
+typedef uint16_t u16;
+typedef uint32_t u32;
+typedef uint64_t u64;
+typedef int8_t s8;
+typedef int16_t s16;
+typedef int32_t s32;
+typedef int64_t s64;
+
+/*
+ * Word type of the target architecture.  Use 'size_t' instead of 'unsigned
+ * long' to account for platforms such as Windows that use 32-bit 'unsigned
+ * long' on 64-bit architectures.
+ */
+typedef size_t machine_word_t;
+
+/* Number of bytes in a word */
+#define WORDBYTES	((int)sizeof(machine_word_t))
+
+/* Number of bits in a word */
+#define WORDBITS	(8 * WORDBYTES)
+
+/* ========================================================================== */
+/*                         Optional compiler features                         */
+/* ========================================================================== */
+
+/* LIBEXPORT - export a function from a shared library */
+#ifndef LIBEXPORT
+#  define LIBEXPORT
+#endif
+
+/* inline - suggest that a function be inlined */
+#ifndef inline
+#  define inline
+#endif
+
+/* forceinline - force a function to be inlined, if possible */
+#ifndef forceinline
+#  define forceinline inline
+#endif
+
+/* restrict - annotate a non-aliased pointer */
+#ifndef restrict
+#  define restrict
+#endif
+
+/* likely(expr) - hint that an expression is usually true */
+#ifndef likely
+#  define likely(expr)		(expr)
+#endif
+
+/* unlikely(expr) - hint that an expression is usually false */
+#ifndef unlikely
+#  define unlikely(expr)	(expr)
+#endif
+
+/* prefetchr(addr) - prefetch into L1 cache for read */
+#ifndef prefetchr
+#  define prefetchr(addr)
+#endif
+
+/* prefetchw(addr) - prefetch into L1 cache for write */
+#ifndef prefetchw
+#  define prefetchw(addr)
+#endif
+
+/* Does the compiler support the 'target' function attribute? */
+#ifndef COMPILER_SUPPORTS_TARGET_FUNCTION_ATTRIBUTE
+#  define COMPILER_SUPPORTS_TARGET_FUNCTION_ATTRIBUTE 0
+#endif
+
+/* Which targets are supported with the 'target' function attribute? */
+#ifndef COMPILER_SUPPORTS_BMI2_TARGET
+#  define COMPILER_SUPPORTS_BMI2_TARGET 0
+#endif
+#ifndef COMPILER_SUPPORTS_AVX_TARGET
+#  define COMPILER_SUPPORTS_AVX_TARGET 0
+#endif
+#ifndef COMPILER_SUPPORTS_AVX512BW_TARGET
+#  define COMPILER_SUPPORTS_AVX512BW_TARGET 0
+#endif
+
+/*
+ * Which targets are supported with the 'target' function attribute and have
+ * intrinsics that work within 'target'-ed functions?
+ */
+#ifndef COMPILER_SUPPORTS_SSE2_TARGET_INTRINSICS
+#  define COMPILER_SUPPORTS_SSE2_TARGET_INTRINSICS 0
+#endif
+#ifndef COMPILER_SUPPORTS_PCLMUL_TARGET_INTRINSICS
+#  define COMPILER_SUPPORTS_PCLMUL_TARGET_INTRINSICS 0
+#endif
+#ifndef COMPILER_SUPPORTS_AVX2_TARGET_INTRINSICS
+#  define COMPILER_SUPPORTS_AVX2_TARGET_INTRINSICS 0
+#endif
+#ifndef COMPILER_SUPPORTS_AVX512BW_TARGET_INTRINSICS
+#  define COMPILER_SUPPORTS_AVX512BW_TARGET_INTRINSICS 0
+#endif
+#ifndef COMPILER_SUPPORTS_NEON_TARGET_INTRINSICS
+#  define COMPILER_SUPPORTS_NEON_TARGET_INTRINSICS 0
+#endif
+#ifndef COMPILER_SUPPORTS_PMULL_TARGET_INTRINSICS
+#  define COMPILER_SUPPORTS_PMULL_TARGET_INTRINSICS 0
+#endif
+#ifndef COMPILER_SUPPORTS_CRC32_TARGET_INTRINSICS
+#  define COMPILER_SUPPORTS_CRC32_TARGET_INTRINSICS 0
+#endif
+
+/* _aligned_attribute(n) - declare that the annotated variable, or variables of
+ * the annotated type, are to be aligned on n-byte boundaries */
+#ifndef _aligned_attribute
+#endif
+
+/* ========================================================================== */
+/*                          Miscellaneous macros                              */
+/* ========================================================================== */
+
+#define ARRAY_LEN(A)		(sizeof(A) / sizeof((A)[0]))
+#define MIN(a, b)		((a) <= (b) ? (a) : (b))
+#define MAX(a, b)		((a) >= (b) ? (a) : (b))
+#define DIV_ROUND_UP(n, d)	(((n) + (d) - 1) / (d))
+#define STATIC_ASSERT(expr)	((void)sizeof(char[1 - 2 * !(expr)]))
+#define ALIGN(n, a)		(((n) + (a) - 1) & ~((a) - 1))
+
+/* ========================================================================== */
+/*                           Endianness handling                              */
+/* ========================================================================== */
+
+/*
+ * CPU_IS_LITTLE_ENDIAN() - a macro which evaluates to 1 if the CPU is little
+ * endian or 0 if it is big endian.  The macro should be defined in a way such
+ * that the compiler can evaluate it at compilation time.  If not defined, a
+ * fallback is used.
+ */
+#ifndef CPU_IS_LITTLE_ENDIAN
+static forceinline int CPU_IS_LITTLE_ENDIAN(void)
+{
+	union {
+		unsigned int v;
+		unsigned char b;
+	} u;
+	u.v = 1;
+	return u.b;
+}
+#endif
+
+/* bswap16(n) - swap the bytes of a 16-bit integer */
+#ifndef bswap16
+static forceinline u16 bswap16(u16 n)
+{
+	return (n << 8) | (n >> 8);
+}
+#endif
+
+/* bswap32(n) - swap the bytes of a 32-bit integer */
+#ifndef bswap32
+static forceinline u32 bswap32(u32 n)
+{
+	return ((n & 0x000000FF) << 24) |
+	       ((n & 0x0000FF00) << 8) |
+	       ((n & 0x00FF0000) >> 8) |
+	       ((n & 0xFF000000) >> 24);
+}
+#endif
+
+/* bswap64(n) - swap the bytes of a 64-bit integer */
+#ifndef bswap64
+static forceinline u64 bswap64(u64 n)
+{
+	return ((n & 0x00000000000000FF) << 56) |
+	       ((n & 0x000000000000FF00) << 40) |
+	       ((n & 0x0000000000FF0000) << 24) |
+	       ((n & 0x00000000FF000000) << 8) |
+	       ((n & 0x000000FF00000000) >> 8) |
+	       ((n & 0x0000FF0000000000) >> 24) |
+	       ((n & 0x00FF000000000000) >> 40) |
+	       ((n & 0xFF00000000000000) >> 56);
+}
+#endif
+
+#define le16_bswap(n) (CPU_IS_LITTLE_ENDIAN() ? (n) : bswap16(n))
+#define le32_bswap(n) (CPU_IS_LITTLE_ENDIAN() ? (n) : bswap32(n))
+#define le64_bswap(n) (CPU_IS_LITTLE_ENDIAN() ? (n) : bswap64(n))
+#define be16_bswap(n) (CPU_IS_LITTLE_ENDIAN() ? bswap16(n) : (n))
+#define be32_bswap(n) (CPU_IS_LITTLE_ENDIAN() ? bswap32(n) : (n))
+#define be64_bswap(n) (CPU_IS_LITTLE_ENDIAN() ? bswap64(n) : (n))
+
+/* ========================================================================== */
+/*                          Unaligned memory accesses                         */
+/* ========================================================================== */
+
+/*
+ * UNALIGNED_ACCESS_IS_FAST should be defined to 1 if unaligned memory accesses
+ * can be performed efficiently on the target platform.
+ */
+#ifndef UNALIGNED_ACCESS_IS_FAST
+#  define UNALIGNED_ACCESS_IS_FAST 0
+#endif
+
+/* ========================================================================== */
+/*                             Bit scan functions                             */
+/* ========================================================================== */
+
+/*
+ * Bit Scan Reverse (BSR) - find the 0-based index (relative to the least
+ * significant end) of the *most* significant 1 bit in the input value.  The
+ * input value must be nonzero!
+ */
+
+#ifndef bsr32
+static forceinline unsigned
+bsr32(u32 n)
+{
+	unsigned i = 0;
+	while ((n >>= 1) != 0)
+		i++;
+	return i;
+}
+#endif
+
+#ifndef bsr64
+static forceinline unsigned
+bsr64(u64 n)
+{
+	unsigned i = 0;
+	while ((n >>= 1) != 0)
+		i++;
+	return i;
+}
+#endif
+
+static forceinline unsigned
+bsrw(machine_word_t n)
+{
+	STATIC_ASSERT(WORDBITS == 32 || WORDBITS == 64);
+	if (WORDBITS == 32)
+		return bsr32(n);
+	else
+		return bsr64(n);
+}
+
+/*
+ * Bit Scan Forward (BSF) - find the 0-based index (relative to the least
+ * significant end) of the *least* significant 1 bit in the input value.  The
+ * input value must be nonzero!
+ */
+
+#ifndef bsf32
+static forceinline unsigned
+bsf32(u32 n)
+{
+	unsigned i = 0;
+	while ((n & 1) == 0) {
+		i++;
+		n >>= 1;
+	}
+	return i;
+}
+#endif
+
+#ifndef bsf64
+static forceinline unsigned
+bsf64(u64 n)
+{
+	unsigned i = 0;
+	while ((n & 1) == 0) {
+		i++;
+		n >>= 1;
+	}
+	return i;
+}
+#endif
+
+static forceinline unsigned
+bsfw(machine_word_t n)
+{
+	STATIC_ASSERT(WORDBITS == 32 || WORDBITS == 64);
+	if (WORDBITS == 32)
+		return bsf32(n);
+	else
+		return bsf64(n);
+}
+
+#endif /* COMMON_COMMON_DEFS_H */

ADDED   3rd_party/libdeflate/common/compiler_gcc.h
Index: 3rd_party/libdeflate/common/compiler_gcc.h
==================================================================
--- 3rd_party/libdeflate/common/compiler_gcc.h
+++ 3rd_party/libdeflate/common/compiler_gcc.h
@@ -0,0 +1,201 @@
+/*
+ * compiler_gcc.h - definitions for the GNU C Compiler.  This also handles clang
+ * and the Intel C Compiler (icc).
+ *
+ * TODO: icc is not well tested, so some things are currently disabled even
+ * though they maybe can be enabled on some icc versions.
+ */
+
+#if !defined(__clang__) && !defined(__INTEL_COMPILER)
+#  define GCC_PREREQ(major, minor)		\
+	(__GNUC__ > (major) ||			\
+	 (__GNUC__ == (major) && __GNUC_MINOR__ >= (minor)))
+#else
+#  define GCC_PREREQ(major, minor)	0
+#endif
+
+/* Note: only check the clang version when absolutely necessary!
+ * "Vendors" such as Apple can use different version numbers. */
+#ifdef __clang__
+#  ifdef __apple_build_version__
+#    define CLANG_PREREQ(major, minor, apple_version)	\
+	(__apple_build_version__ >= (apple_version))
+#  else
+#    define CLANG_PREREQ(major, minor, apple_version)	\
+	(__clang_major__ > (major) ||			\
+	 (__clang_major__ == (major) && __clang_minor__ >= (minor)))
+#  endif
+#else
+#  define CLANG_PREREQ(major, minor, apple_version)	0
+#endif
+
+#ifndef __has_attribute
+#  define __has_attribute(attribute)	0
+#endif
+#ifndef __has_feature
+#  define __has_feature(feature)	0
+#endif
+#ifndef __has_builtin
+#  define __has_builtin(builtin)	0
+#endif
+
+#ifdef _WIN32
+#  define LIBEXPORT __declspec(dllexport)
+#else
+#  define LIBEXPORT __attribute__((visibility("default")))
+#endif
+
+#define inline			inline
+#define forceinline		inline __attribute__((always_inline))
+#define restrict		__restrict__
+#define likely(expr)		__builtin_expect(!!(expr), 1)
+#define unlikely(expr)		__builtin_expect(!!(expr), 0)
+#define prefetchr(addr)		__builtin_prefetch((addr), 0)
+#define prefetchw(addr)		__builtin_prefetch((addr), 1)
+#define _aligned_attribute(n)	__attribute__((aligned(n)))
+
+#define COMPILER_SUPPORTS_TARGET_FUNCTION_ATTRIBUTE	\
+	(GCC_PREREQ(4, 4) || __has_attribute(target))
+
+#if COMPILER_SUPPORTS_TARGET_FUNCTION_ATTRIBUTE
+
+#  if defined(__i386__) || defined(__x86_64__)
+
+#    define COMPILER_SUPPORTS_PCLMUL_TARGET	\
+	(GCC_PREREQ(4, 4) || __has_builtin(__builtin_ia32_pclmulqdq128))
+
+#    define COMPILER_SUPPORTS_AVX_TARGET	\
+	(GCC_PREREQ(4, 6) || __has_builtin(__builtin_ia32_maxps256))
+
+#    define COMPILER_SUPPORTS_BMI2_TARGET	\
+	(GCC_PREREQ(4, 7) || __has_builtin(__builtin_ia32_pdep_di))
+
+#    define COMPILER_SUPPORTS_AVX2_TARGET	\
+	(GCC_PREREQ(4, 7) || __has_builtin(__builtin_ia32_psadbw256))
+
+#    define COMPILER_SUPPORTS_AVX512BW_TARGET	\
+	(GCC_PREREQ(5, 1) || __has_builtin(__builtin_ia32_psadbw512))
+
+	/*
+	 * Prior to gcc 4.9 (r200349) and clang 3.8 (r239883), x86 intrinsics
+	 * not available in the main target could not be used in 'target'
+	 * attribute functions.  Unfortunately clang has no feature test macro
+	 * for this so we have to check its version.
+	 */
+#    if GCC_PREREQ(4, 9) || CLANG_PREREQ(3, 8, 7030000)
+#      define COMPILER_SUPPORTS_SSE2_TARGET_INTRINSICS	1
+#      define COMPILER_SUPPORTS_PCLMUL_TARGET_INTRINSICS	\
+		COMPILER_SUPPORTS_PCLMUL_TARGET
+#      define COMPILER_SUPPORTS_AVX2_TARGET_INTRINSICS	\
+		COMPILER_SUPPORTS_AVX2_TARGET
+#      define COMPILER_SUPPORTS_AVX512BW_TARGET_INTRINSICS	\
+		COMPILER_SUPPORTS_AVX512BW_TARGET
+#    endif
+
+#  elif defined(__arm__) || defined(__aarch64__)
+
+    /*
+     * Determine whether NEON and crypto intrinsics are supported.
+     *
+     * With gcc prior to 6.1, (r230411 for arm32, r226563 for arm64), neither
+     * was available unless enabled in the main target.
+     *
+     * But even after that, to include <arm_neon.h> (which contains both the
+     * basic NEON intrinsics and the crypto intrinsics) the main target still
+     * needs to have:
+     *   - gcc: hardware floating point support
+     *   - clang: NEON support (but not necessarily crypto support)
+     */
+#    if (GCC_PREREQ(6, 1) && defined(__ARM_FP)) || \
+        (defined(__clang__) && defined(__ARM_NEON))
+#      define COMPILER_SUPPORTS_NEON_TARGET_INTRINSICS 1
+       /*
+        * The crypto intrinsics are broken on arm32 with clang, even when using
+        * -mfpu=crypto-neon-fp-armv8, because clang's <arm_neon.h> puts them
+        * behind __aarch64__.  Undefine __ARM_FEATURE_CRYPTO in that case...
+        */
+#      if defined(__clang__) && defined(__arm__)
+#        undef __ARM_FEATURE_CRYPTO
+#      elif __has_builtin(__builtin_neon_vmull_p64) || !defined(__clang__)
+#        define COMPILER_SUPPORTS_PMULL_TARGET_INTRINSICS 1
+#      endif
+#    endif
+
+     /*
+      * Determine whether CRC32 intrinsics are supported.
+      *
+      * With gcc r274827 or later (gcc 10.1+, 9.3+, or 8.4+), or with clang,
+      * they work as expected.  (Well, not quite.  There's still a bug, but we
+      * have to work around it later when including arm_acle.h.)
+      */
+#    if GCC_PREREQ(10, 1) || \
+        (GCC_PREREQ(9, 3) && !GCC_PREREQ(10, 0)) || \
+        (GCC_PREREQ(8, 4) && !GCC_PREREQ(9, 0)) || \
+        (defined(__clang__) && __has_builtin(__builtin_arm_crc32b))
+#      define COMPILER_SUPPORTS_CRC32_TARGET_INTRINSICS 1
+#    endif
+
+#  endif /* __arm__ || __aarch64__ */
+
+#endif /* COMPILER_SUPPORTS_TARGET_FUNCTION_ATTRIBUTE */
+
+/*
+ * Prior to gcc 5.1 and clang 3.9, emmintrin.h only defined vectors of signed
+ * integers (e.g. __v4si), not vectors of unsigned integers (e.g.  __v4su).  But
+ * we need the unsigned ones in order to avoid signed integer overflow, which is
+ * undefined behavior.  Add the missing definitions for the unsigned ones if
+ * needed.
+ */
+#if (GCC_PREREQ(4, 0) && !GCC_PREREQ(5, 1)) || \
+    (defined(__clang__) && !CLANG_PREREQ(3, 9, 8020000)) || \
+    defined(__INTEL_COMPILER)
+typedef unsigned long long  __v2du __attribute__((__vector_size__(16)));
+typedef unsigned int        __v4su __attribute__((__vector_size__(16)));
+typedef unsigned short      __v8hu __attribute__((__vector_size__(16)));
+typedef unsigned char      __v16qu __attribute__((__vector_size__(16)));
+typedef unsigned long long  __v4du __attribute__((__vector_size__(32)));
+typedef unsigned int        __v8su __attribute__((__vector_size__(32)));
+typedef unsigned short     __v16hu __attribute__((__vector_size__(32)));
+typedef unsigned char      __v32qu __attribute__((__vector_size__(32)));
+#endif
+
+#ifdef __INTEL_COMPILER
+typedef int   __v16si __attribute__((__vector_size__(64)));
+typedef short __v32hi __attribute__((__vector_size__(64)));
+typedef char  __v64qi __attribute__((__vector_size__(64)));
+#endif
+
+/* Newer gcc supports __BYTE_ORDER__.  Older gcc doesn't. */
+#ifdef __BYTE_ORDER__
+#  define CPU_IS_LITTLE_ENDIAN() (__BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__)
+#endif
+
+#if GCC_PREREQ(4, 8) || __has_builtin(__builtin_bswap16)
+#  define bswap16	__builtin_bswap16
+#endif
+
+#if GCC_PREREQ(4, 3) || __has_builtin(__builtin_bswap32)
+#  define bswap32	__builtin_bswap32
+#endif
+
+#if GCC_PREREQ(4, 3) || __has_builtin(__builtin_bswap64)
+#  define bswap64	__builtin_bswap64
+#endif
+
+#if defined(__x86_64__) || defined(__i386__) || \
+    defined(__ARM_FEATURE_UNALIGNED) || defined(__powerpc64__) || \
+    /*
+     * For all compilation purposes, WebAssembly behaves like any other CPU
+     * instruction set. Even though WebAssembly engine might be running on top
+     * of different actual CPU architectures, the WebAssembly spec itself
+     * permits unaligned access and it will be fast on most of those platforms,
+     * and simulated at the engine level on others, so it's worth treating it
+     * as a CPU architecture with fast unaligned access.
+    */ defined(__wasm__)
+#  define UNALIGNED_ACCESS_IS_FAST 1
+#endif
+
+#define bsr32(n)	(31 - __builtin_clz(n))
+#define bsr64(n)	(63 - __builtin_clzll(n))
+#define bsf32(n)	__builtin_ctz(n)
+#define bsf64(n)	__builtin_ctzll(n)

ADDED   3rd_party/libdeflate/common/compiler_msc.h
Index: 3rd_party/libdeflate/common/compiler_msc.h
==================================================================
--- 3rd_party/libdeflate/common/compiler_msc.h
+++ 3rd_party/libdeflate/common/compiler_msc.h
@@ -0,0 +1,80 @@
+/*
+ * compiler_msc.h - definitions for the Microsoft C Compiler
+ */
+
+#include <stdint.h>
+#include <stdlib.h> /* for _byteswap_*() */
+
+#define LIBEXPORT	__declspec(dllexport)
+
+/*
+ * Old versions (e.g. VS2010) of MSC don't have the C99 header stdbool.h.
+ * Beware: the below replacement isn't fully standard, since normally any value
+ * != 0 should be implicitly cast to a bool with value 1... but that doesn't
+ * happen if bool is really just an 'int'.
+ */
+typedef int bool;
+#define true 1
+#define false 0
+#define __bool_true_false_are_defined 1
+
+/* Define ssize_t */
+#ifdef _WIN64
+typedef long long ssize_t;
+#else
+typedef int ssize_t;
+#endif
+
+/* Assume a little endian architecture with fast unaligned access */
+#define CPU_IS_LITTLE_ENDIAN()		1
+#define UNALIGNED_ACCESS_IS_FAST	1
+
+/* __restrict has nonstandard behavior; don't use it */
+#define restrict
+
+/* ... but we can use __inline and __forceinline */
+#define inline		__inline
+#define forceinline	__forceinline
+
+/* Byte swap functions */
+#define bswap16	_byteswap_ushort
+#define bswap32	_byteswap_ulong
+#define bswap64	_byteswap_uint64
+
+/* Bit scan functions (32-bit) */
+
+static forceinline unsigned
+bsr32(uint32_t n)
+{
+	_BitScanReverse(&n, n);
+	return n;
+}
+#define bsr32 bsr32
+
+static forceinline unsigned
+bsf32(uint32_t n)
+{
+	_BitScanForward(&n, n);
+	return n;
+}
+#define bsf32 bsf32
+
+#ifdef _M_X64 /* Bit scan functions (64-bit) */
+
+static forceinline unsigned
+bsr64(uint64_t n)
+{
+	_BitScanReverse64(&n, n);
+	return n;
+}
+#define bsr64 bsr64
+
+static forceinline unsigned
+bsf64(uint64_t n)
+{
+	_BitScanForward64(&n, n);
+	return n;
+}
+#define bsf64 bsf64
+
+#endif /* _M_X64 */

ADDED   3rd_party/libdeflate/lib/adler32.c
Index: 3rd_party/libdeflate/lib/adler32.c
==================================================================
--- 3rd_party/libdeflate/lib/adler32.c
+++ 3rd_party/libdeflate/lib/adler32.c
@@ -0,0 +1,130 @@
+/*
+ * adler32.c - Adler-32 checksum algorithm
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include "lib_common.h"
+#include "libdeflate.h"
+
+/* The Adler-32 divisor, or "base", value. */
+#define DIVISOR 65521
+
+/*
+ * MAX_CHUNK_SIZE is the most bytes that can be processed without the
+ * possibility of s2 overflowing when it is represented as an unsigned 32-bit
+ * integer.  This value was computed using the following Python script:
+ *
+ *	divisor = 65521
+ *	count = 0
+ *	s1 = divisor - 1
+ *	s2 = divisor - 1
+ *	while True:
+ *		s1 += 0xFF
+ *		s2 += s1
+ *		if s2 > 0xFFFFFFFF:
+ *			break
+ *		count += 1
+ *	print(count)
+ *
+ * Note that to get the correct worst-case value, we must assume that every byte
+ * has value 0xFF and that s1 and s2 started with the highest possible values
+ * modulo the divisor.
+ */
+#define MAX_CHUNK_SIZE	5552
+
+typedef u32 (*adler32_func_t)(u32, const u8 *, size_t);
+
+/* Include architecture-specific implementations if available */
+#undef DEFAULT_IMPL
+#undef DISPATCH
+#if defined(__arm__) || defined(__aarch64__)
+#  include "arm/adler32_impl.h"
+#elif defined(__i386__) || defined(__x86_64__)
+#  include "x86/adler32_impl.h"
+#endif
+
+/* Define a generic implementation if needed */
+#ifndef DEFAULT_IMPL
+#define DEFAULT_IMPL adler32_generic
+static u32 adler32_generic(u32 adler, const u8 *p, size_t size)
+{
+	u32 s1 = adler & 0xFFFF;
+	u32 s2 = adler >> 16;
+	const u8 * const end = p + size;
+
+	while (p != end) {
+		size_t chunk_size = MIN(end - p, MAX_CHUNK_SIZE);
+		const u8 *chunk_end = p + chunk_size;
+		size_t num_unrolled_iterations = chunk_size / 4;
+
+		while (num_unrolled_iterations--) {
+			s1 += *p++;
+			s2 += s1;
+			s1 += *p++;
+			s2 += s1;
+			s1 += *p++;
+			s2 += s1;
+			s1 += *p++;
+			s2 += s1;
+		}
+		while (p != chunk_end) {
+			s1 += *p++;
+			s2 += s1;
+		}
+		s1 %= DIVISOR;
+		s2 %= DIVISOR;
+	}
+
+	return (s2 << 16) | s1;
+}
+#endif /* !DEFAULT_IMPL */
+
+#ifdef DISPATCH
+static u32 dispatch(u32, const u8 *, size_t);
+
+static volatile adler32_func_t adler32_impl = dispatch;
+
+/* Choose the fastest implementation at runtime */
+static u32 dispatch(u32 adler, const u8 *buffer, size_t size)
+{
+	adler32_func_t f = arch_select_adler32_func();
+
+	if (f == NULL)
+		f = DEFAULT_IMPL;
+
+	adler32_impl = f;
+	return adler32_impl(adler, buffer, size);
+}
+#else
+#  define adler32_impl DEFAULT_IMPL /* only one implementation, use it */
+#endif
+
+LIBDEFLATEEXPORT u32 LIBDEFLATEAPI
+libdeflate_adler32(u32 adler, const void *buffer, size_t size)
+{
+	if (buffer == NULL) /* return initial value */
+		return 1;
+	return adler32_impl(adler, buffer, size);
+}

ADDED   3rd_party/libdeflate/lib/adler32_vec_template.h
Index: 3rd_party/libdeflate/lib/adler32_vec_template.h
==================================================================
--- 3rd_party/libdeflate/lib/adler32_vec_template.h
+++ 3rd_party/libdeflate/lib/adler32_vec_template.h
@@ -0,0 +1,124 @@
+/*
+ * adler32_vec_template.h - template for vectorized Adler-32 implementations
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+/*
+ * This file contains a template for vectorized Adler-32 implementations.
+ *
+ * The inner loop between reductions modulo 65521 of an unvectorized Adler-32
+ * implementation looks something like this:
+ *
+ *	do {
+ *		s1 += *p;
+ *		s2 += s1;
+ *	} while (++p != chunk_end);
+ *
+ * For vectorized calculation of s1, we only need to sum the input bytes.  They
+ * can be accumulated into multiple counters which are eventually summed
+ * together.
+ *
+ * For vectorized calculation of s2, the basic idea is that for each iteration
+ * that processes N bytes, we can perform the following vectorizable
+ * calculation:
+ *
+ *	s2 += N*byte_1 + (N-1)*byte_2 + (N-2)*byte_3 + ... + 1*byte_N
+ *
+ * Or, equivalently, we can sum the byte_1...byte_N for each iteration into N
+ * separate counters, then do the multiplications by N...1 just once at the end
+ * rather than once per iteration.
+ *
+ * Also, we must account for how previous bytes will affect s2 by doing the
+ * following at beginning of each iteration:
+ *
+ *	s2 += s1 * N
+ *
+ * Furthermore, like s1, "s2" can actually be multiple counters which are
+ * eventually summed together.
+ */
+
+static u32 ATTRIBUTES
+FUNCNAME(u32 adler, const u8 *p, size_t size)
+{
+	u32 s1 = adler & 0xFFFF;
+	u32 s2 = adler >> 16;
+	const u8 * const end = p + size;
+	const u8 *vend;
+	const size_t max_chunk_size =
+		MIN(MAX_CHUNK_SIZE, IMPL_MAX_CHUNK_SIZE) -
+		(MIN(MAX_CHUNK_SIZE, IMPL_MAX_CHUNK_SIZE) %
+		 IMPL_SEGMENT_SIZE);
+
+	/* Process a byte at a time until the needed alignment is reached */
+	if (p != end && (uintptr_t)p % IMPL_ALIGNMENT) {
+		do {
+			s1 += *p++;
+			s2 += s1;
+		} while (p != end && (uintptr_t)p % IMPL_ALIGNMENT);
+		s1 %= DIVISOR;
+		s2 %= DIVISOR;
+	}
+
+	/*
+	 * Process "chunks" of bytes using vector instructions.  Chunk sizes are
+	 * limited to MAX_CHUNK_SIZE, which guarantees that s1 and s2 never
+	 * overflow before being reduced modulo DIVISOR.  For vector processing,
+	 * chunk sizes are also made evenly divisible by IMPL_SEGMENT_SIZE and
+	 * may be further limited to IMPL_MAX_CHUNK_SIZE.
+	 */
+	STATIC_ASSERT(IMPL_SEGMENT_SIZE % IMPL_ALIGNMENT == 0);
+	vend = end - ((size_t)(end - p) % IMPL_SEGMENT_SIZE);
+	while (p != vend) {
+		size_t chunk_size = MIN((size_t)(vend - p), max_chunk_size);
+
+		s2 += s1 * chunk_size;
+
+		FUNCNAME_CHUNK((const void *)p, (const void *)(p + chunk_size),
+			       &s1, &s2);
+
+		p += chunk_size;
+		s1 %= DIVISOR;
+		s2 %= DIVISOR;
+	}
+
+	/* Process any remaining bytes */
+	if (p != end) {
+		do {
+			s1 += *p++;
+			s2 += s1;
+		} while (p != end);
+		s1 %= DIVISOR;
+		s2 %= DIVISOR;
+	}
+
+	return (s2 << 16) | s1;
+}
+
+#undef FUNCNAME
+#undef FUNCNAME_CHUNK
+#undef ATTRIBUTES
+#undef IMPL_ALIGNMENT
+#undef IMPL_SEGMENT_SIZE
+#undef IMPL_MAX_CHUNK_SIZE

ADDED   3rd_party/libdeflate/lib/arm/adler32_impl.h
Index: 3rd_party/libdeflate/lib/arm/adler32_impl.h
==================================================================
--- 3rd_party/libdeflate/lib/arm/adler32_impl.h
+++ 3rd_party/libdeflate/lib/arm/adler32_impl.h
@@ -0,0 +1,125 @@
+/*
+ * arm/adler32_impl.h - ARM implementations of Adler-32 checksum algorithm
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#ifndef LIB_ARM_ADLER32_IMPL_H
+#define LIB_ARM_ADLER32_IMPL_H
+
+#include "cpu_features.h"
+
+/* NEON implementation */
+#undef DISPATCH_NEON
+#if !defined(DEFAULT_IMPL) &&	\
+	(defined(__ARM_NEON) || (ARM_CPU_FEATURES_ENABLED &&	\
+				 COMPILER_SUPPORTS_NEON_TARGET_INTRINSICS))
+#  define FUNCNAME		adler32_neon
+#  define FUNCNAME_CHUNK	adler32_neon_chunk
+#  define IMPL_ALIGNMENT	16
+#  define IMPL_SEGMENT_SIZE	32
+/* Prevent unsigned overflow of the 16-bit precision byte counters */
+#  define IMPL_MAX_CHUNK_SIZE	(32 * (0xFFFF / 0xFF))
+#  ifdef __ARM_NEON
+#    define ATTRIBUTES
+#    define DEFAULT_IMPL	adler32_neon
+#  else
+#    ifdef __arm__
+#      define ATTRIBUTES	__attribute__((target("fpu=neon")))
+#    else
+#      define ATTRIBUTES	__attribute__((target("+simd")))
+#    endif
+#    define DISPATCH		1
+#    define DISPATCH_NEON	1
+#  endif
+#  include <arm_neon.h>
+static forceinline ATTRIBUTES void
+adler32_neon_chunk(const uint8x16_t *p, const uint8x16_t * const end,
+		   u32 *s1, u32 *s2)
+{
+	uint32x4_t v_s1 = (uint32x4_t) { 0, 0, 0, 0 };
+	uint32x4_t v_s2 = (uint32x4_t) { 0, 0, 0, 0 };
+	uint16x8_t v_byte_sums_a = (uint16x8_t) { 0, 0, 0, 0, 0, 0, 0, 0 };
+	uint16x8_t v_byte_sums_b = (uint16x8_t) { 0, 0, 0, 0, 0, 0, 0, 0 };
+	uint16x8_t v_byte_sums_c = (uint16x8_t) { 0, 0, 0, 0, 0, 0, 0, 0 };
+	uint16x8_t v_byte_sums_d = (uint16x8_t) { 0, 0, 0, 0, 0, 0, 0, 0 };
+
+	do {
+		const uint8x16_t bytes1 = *p++;
+		const uint8x16_t bytes2 = *p++;
+		uint16x8_t tmp;
+
+		v_s2 += v_s1;
+
+		/* Vector Pairwise Add Long (u8 => u16) */
+		tmp = vpaddlq_u8(bytes1);
+
+		/* Vector Pairwise Add and Accumulate Long (u8 => u16) */
+		tmp = vpadalq_u8(tmp, bytes2);
+
+		/* Vector Pairwise Add and Accumulate Long (u16 => u32) */
+		v_s1 = vpadalq_u16(v_s1, tmp);
+
+		/* Vector Add Wide (u8 => u16) */
+		v_byte_sums_a = vaddw_u8(v_byte_sums_a, vget_low_u8(bytes1));
+		v_byte_sums_b = vaddw_u8(v_byte_sums_b, vget_high_u8(bytes1));
+		v_byte_sums_c = vaddw_u8(v_byte_sums_c, vget_low_u8(bytes2));
+		v_byte_sums_d = vaddw_u8(v_byte_sums_d, vget_high_u8(bytes2));
+
+	} while (p != end);
+
+	/* Vector Shift Left (u32) */
+	v_s2 = vqshlq_n_u32(v_s2, 5);
+
+	/* Vector Multiply Accumulate Long (u16 => u32) */
+	v_s2 = vmlal_u16(v_s2, vget_low_u16(v_byte_sums_a),  (uint16x4_t) { 32, 31, 30, 29 });
+	v_s2 = vmlal_u16(v_s2, vget_high_u16(v_byte_sums_a), (uint16x4_t) { 28, 27, 26, 25 });
+	v_s2 = vmlal_u16(v_s2, vget_low_u16(v_byte_sums_b),  (uint16x4_t) { 24, 23, 22, 21 });
+	v_s2 = vmlal_u16(v_s2, vget_high_u16(v_byte_sums_b), (uint16x4_t) { 20, 19, 18, 17 });
+	v_s2 = vmlal_u16(v_s2, vget_low_u16(v_byte_sums_c),  (uint16x4_t) { 16, 15, 14, 13 });
+	v_s2 = vmlal_u16(v_s2, vget_high_u16(v_byte_sums_c), (uint16x4_t) { 12, 11, 10,  9 });
+	v_s2 = vmlal_u16(v_s2, vget_low_u16 (v_byte_sums_d), (uint16x4_t) {  8,  7,  6,  5 });
+	v_s2 = vmlal_u16(v_s2, vget_high_u16(v_byte_sums_d), (uint16x4_t) {  4,  3,  2,  1 });
+
+	*s1 += v_s1[0] + v_s1[1] + v_s1[2] + v_s1[3];
+	*s2 += v_s2[0] + v_s2[1] + v_s2[2] + v_s2[3];
+}
+#  include "../adler32_vec_template.h"
+#endif /* NEON implementation */
+
+#ifdef DISPATCH
+static inline adler32_func_t
+arch_select_adler32_func(void)
+{
+	u32 features = get_cpu_features();
+
+#ifdef DISPATCH_NEON
+	if (features & ARM_CPU_FEATURE_NEON)
+		return adler32_neon;
+#endif
+	return NULL;
+}
+#endif /* DISPATCH */
+
+#endif /* LIB_ARM_ADLER32_IMPL_H */

ADDED   3rd_party/libdeflate/lib/arm/cpu_features.c
Index: 3rd_party/libdeflate/lib/arm/cpu_features.c
==================================================================
--- 3rd_party/libdeflate/lib/arm/cpu_features.c
+++ 3rd_party/libdeflate/lib/arm/cpu_features.c
@@ -0,0 +1,133 @@
+/*
+ * arm/cpu_features.c - feature detection for ARM processors
+ *
+ * Copyright 2018 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+/*
+ * ARM processors don't have a standard way for unprivileged programs to detect
+ * processor features.  But, on Linux we can read the AT_HWCAP and AT_HWCAP2
+ * values from /proc/self/auxv.
+ *
+ * Ideally we'd use the C library function getauxval(), but it's not guaranteed
+ * to be available: it was only added to glibc in 2.16, and in Android it was
+ * added to API level 18 for ARM and level 21 for AArch64.
+ */
+
+#include "../cpu_features_common.h" /* must be included first */
+#include "cpu_features.h"
+
+#if ARM_CPU_FEATURES_ENABLED
+
+#include <errno.h>
+#include <fcntl.h>
+#include <string.h>
+#include <unistd.h>
+
+#define AT_HWCAP	16
+#define AT_HWCAP2	26
+
+volatile u32 _cpu_features = 0;
+
+static void scan_auxv(unsigned long *hwcap, unsigned long *hwcap2)
+{
+	int fd;
+	unsigned long auxbuf[32];
+	int filled = 0;
+	int i;
+
+	fd = open("/proc/self/auxv", O_RDONLY);
+	if (fd < 0)
+		return;
+
+	for (;;) {
+		do {
+			int ret = read(fd, &((char *)auxbuf)[filled],
+				       sizeof(auxbuf) - filled);
+			if (ret <= 0) {
+				if (ret < 0 && errno == EINTR)
+					continue;
+				goto out;
+			}
+			filled += ret;
+		} while (filled < 2 * sizeof(long));
+
+		i = 0;
+		do {
+			unsigned long type = auxbuf[i];
+			unsigned long value = auxbuf[i + 1];
+
+			if (type == AT_HWCAP)
+				*hwcap = value;
+			else if (type == AT_HWCAP2)
+				*hwcap2 = value;
+			i += 2;
+			filled -= 2 * sizeof(long);
+		} while (filled >= 2 * sizeof(long));
+
+		memmove(auxbuf, &auxbuf[i], filled);
+	}
+out:
+	close(fd);
+}
+
+static const struct cpu_feature arm_cpu_feature_table[] = {
+	{ARM_CPU_FEATURE_NEON,		"neon"},
+	{ARM_CPU_FEATURE_PMULL,		"pmull"},
+	{ARM_CPU_FEATURE_CRC32,		"crc32"},
+};
+
+void setup_cpu_features(void)
+{
+	u32 features = 0;
+	unsigned long hwcap = 0;
+	unsigned long hwcap2 = 0;
+
+	scan_auxv(&hwcap, &hwcap2);
+
+#ifdef __arm__
+	STATIC_ASSERT(sizeof(long) == 4);
+	if (hwcap & (1 << 12))	/* HWCAP_NEON */
+		features |= ARM_CPU_FEATURE_NEON;
+	if (hwcap2 & (1 << 1))	/* HWCAP2_PMULL */
+		features |= ARM_CPU_FEATURE_PMULL;
+	if (hwcap2 & (1 << 4))	/* HWCAP2_CRC32 */
+		features |= ARM_CPU_FEATURE_CRC32;
+#else
+	STATIC_ASSERT(sizeof(long) == 8);
+	if (hwcap & (1 << 1))	/* HWCAP_ASIMD */
+		features |= ARM_CPU_FEATURE_NEON;
+	if (hwcap & (1 << 4))	/* HWCAP_PMULL */
+		features |= ARM_CPU_FEATURE_PMULL;
+	if (hwcap & (1 << 7))	/* HWCAP_CRC32 */
+		features |= ARM_CPU_FEATURE_CRC32;
+#endif
+
+	disable_cpu_features_for_testing(&features, arm_cpu_feature_table,
+					 ARRAY_LEN(arm_cpu_feature_table));
+
+	_cpu_features = features | ARM_CPU_FEATURES_KNOWN;
+}
+
+#endif /* ARM_CPU_FEATURES_ENABLED */

ADDED   3rd_party/libdeflate/lib/arm/cpu_features.h
Index: 3rd_party/libdeflate/lib/arm/cpu_features.h
==================================================================
--- 3rd_party/libdeflate/lib/arm/cpu_features.h
+++ 3rd_party/libdeflate/lib/arm/cpu_features.h
@@ -0,0 +1,40 @@
+/*
+ * arm/cpu_features.h - feature detection for ARM processors
+ */
+
+#ifndef LIB_ARM_CPU_FEATURES_H
+#define LIB_ARM_CPU_FEATURES_H
+
+#include "../lib_common.h"
+
+#if (defined(__arm__) || defined(__aarch64__)) && \
+	defined(__linux__) && \
+	COMPILER_SUPPORTS_TARGET_FUNCTION_ATTRIBUTE && \
+	!defined(FREESTANDING)
+#  define ARM_CPU_FEATURES_ENABLED 1
+#else
+#  define ARM_CPU_FEATURES_ENABLED 0
+#endif
+
+#if ARM_CPU_FEATURES_ENABLED
+
+#define ARM_CPU_FEATURE_NEON		0x00000001
+#define ARM_CPU_FEATURE_PMULL		0x00000002
+#define ARM_CPU_FEATURE_CRC32		0x00000004
+
+#define ARM_CPU_FEATURES_KNOWN		0x80000000
+
+extern volatile u32 _cpu_features;
+
+void setup_cpu_features(void);
+
+static inline u32 get_cpu_features(void)
+{
+	if (_cpu_features == 0)
+		setup_cpu_features();
+	return _cpu_features;
+}
+
+#endif /* ARM_CPU_FEATURES_ENABLED */
+
+#endif /* LIB_ARM_CPU_FEATURES_H */

ADDED   3rd_party/libdeflate/lib/arm/crc32_impl.h
Index: 3rd_party/libdeflate/lib/arm/crc32_impl.h
==================================================================
--- 3rd_party/libdeflate/lib/arm/crc32_impl.h
+++ 3rd_party/libdeflate/lib/arm/crc32_impl.h
@@ -0,0 +1,247 @@
+/*
+ * arm/crc32_impl.h
+ *
+ * Copyright 2017 Jun He <jun.he@linaro.org>
+ * Copyright 2018 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#ifndef LIB_ARM_CRC32_IMPL_H
+#define LIB_ARM_CRC32_IMPL_H
+
+#include "cpu_features.h"
+
+/* Implementation using ARM CRC32 instructions */
+#undef DISPATCH_ARM
+#if !defined(DEFAULT_IMPL) && \
+    (defined(__ARM_FEATURE_CRC32) || \
+     (ARM_CPU_FEATURES_ENABLED && COMPILER_SUPPORTS_CRC32_TARGET_INTRINSICS))
+#  ifdef __ARM_FEATURE_CRC32
+#    define ATTRIBUTES
+#    define DEFAULT_IMPL	crc32_arm
+#  else
+#    ifdef __arm__
+#      ifdef __clang__
+#        define ATTRIBUTES	__attribute__((target("armv8-a,crc")))
+#      else
+#        define ATTRIBUTES	__attribute__((target("arch=armv8-a+crc")))
+#      endif
+#    else
+#      ifdef __clang__
+#        define ATTRIBUTES	__attribute__((target("crc")))
+#      else
+#        define ATTRIBUTES	__attribute__((target("+crc")))
+#      endif
+#    endif
+#    define DISPATCH		1
+#    define DISPATCH_ARM	1
+#  endif
+
+/*
+ * gcc's (as of 10.1) version of arm_acle.h for arm32, and clang's (as of
+ * 10.0.1) version of arm_acle.h for both arm32 and arm64, have a bug where they
+ * only define the CRC32 functions like __crc32b() when __ARM_FEATURE_CRC32 is
+ * defined.  That prevents them from being used via __attribute__((target)) when
+ * the main target doesn't have CRC32 support enabled.  The actual built-ins
+ * like __builtin_arm_crc32b() are available and work, however; it's just the
+ * wrappers in arm_acle.h like __crc32b() that erroneously don't get defined.
+ * Work around this by manually defining __ARM_FEATURE_CRC32.
+ */
+#ifndef __ARM_FEATURE_CRC32
+#  define __ARM_FEATURE_CRC32	1
+#endif
+#include <arm_acle.h>
+
+static u32 ATTRIBUTES
+crc32_arm(u32 remainder, const u8 *p, size_t size)
+{
+	while (size != 0 && (uintptr_t)p & 7) {
+		remainder = __crc32b(remainder, *p++);
+		size--;
+	}
+
+	while (size >= 32) {
+		remainder = __crc32d(remainder, le64_bswap(*((u64 *)p + 0)));
+		remainder = __crc32d(remainder, le64_bswap(*((u64 *)p + 1)));
+		remainder = __crc32d(remainder, le64_bswap(*((u64 *)p + 2)));
+		remainder = __crc32d(remainder, le64_bswap(*((u64 *)p + 3)));
+		p += 32;
+		size -= 32;
+	}
+
+	while (size >= 8) {
+		remainder = __crc32d(remainder, le64_bswap(*(u64 *)p));
+		p += 8;
+		size -= 8;
+	}
+
+	while (size != 0) {
+		remainder = __crc32b(remainder, *p++);
+		size--;
+	}
+
+	return remainder;
+}
+#undef ATTRIBUTES
+#endif /* Implementation using ARM CRC32 instructions */
+
+/*
+ * CRC-32 folding with ARM Crypto extension-PMULL
+ *
+ * This works the same way as the x86 PCLMUL version.
+ * See x86/crc32_pclmul_template.h for an explanation.
+ */
+#undef DISPATCH_PMULL
+#if !defined(DEFAULT_IMPL) && \
+    (defined(__ARM_FEATURE_CRYPTO) ||	\
+     (ARM_CPU_FEATURES_ENABLED &&	\
+      COMPILER_SUPPORTS_PMULL_TARGET_INTRINSICS)) && \
+      /* not yet tested on big endian, probably needs changes to work there */ \
+    (defined(__BYTE_ORDER__) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__)
+#  define FUNCNAME		crc32_pmull
+#  define FUNCNAME_ALIGNED	crc32_pmull_aligned
+#  ifdef __ARM_FEATURE_CRYPTO
+#    define ATTRIBUTES
+#    define DEFAULT_IMPL	crc32_pmull
+#  else
+#    ifdef __arm__
+#      define ATTRIBUTES	__attribute__((target("fpu=crypto-neon-fp-armv8")))
+#    else
+#      ifdef __clang__
+#        define ATTRIBUTES	__attribute__((target("crypto")))
+#      else
+#        define ATTRIBUTES	__attribute__((target("+crypto")))
+#      endif
+#    endif
+#    define DISPATCH		1
+#    define DISPATCH_PMULL	1
+#  endif
+
+#include <arm_neon.h>
+
+static forceinline ATTRIBUTES uint8x16_t
+clmul_00(uint8x16_t a, uint8x16_t b)
+{
+	return (uint8x16_t)vmull_p64((poly64_t)vget_low_u8(a),
+				     (poly64_t)vget_low_u8(b));
+}
+
+static forceinline ATTRIBUTES uint8x16_t
+clmul_10(uint8x16_t a, uint8x16_t b)
+{
+	return (uint8x16_t)vmull_p64((poly64_t)vget_low_u8(a),
+				     (poly64_t)vget_high_u8(b));
+}
+
+static forceinline ATTRIBUTES uint8x16_t
+clmul_11(uint8x16_t a, uint8x16_t b)
+{
+	return (uint8x16_t)vmull_high_p64((poly64x2_t)a, (poly64x2_t)b);
+}
+
+static forceinline ATTRIBUTES uint8x16_t
+fold_128b(uint8x16_t dst, uint8x16_t src, uint8x16_t multipliers)
+{
+	return dst ^ clmul_00(src, multipliers) ^ clmul_11(src, multipliers);
+}
+
+static forceinline ATTRIBUTES u32
+crc32_pmull_aligned(u32 remainder, const uint8x16_t *p, size_t nr_segs)
+{
+	/* Constants precomputed by gen_crc32_multipliers.c.  Do not edit! */
+	const uint8x16_t multipliers_4 =
+		(uint8x16_t)(uint64x2_t){ 0x8F352D95, 0x1D9513D7 };
+	const uint8x16_t multipliers_1 =
+		(uint8x16_t)(uint64x2_t){ 0xAE689191, 0xCCAA009E };
+	const uint8x16_t final_multiplier =
+		(uint8x16_t)(uint64x2_t){ 0xB8BC6765 };
+	const uint8x16_t mask32 = (uint8x16_t)(uint32x4_t){ 0xFFFFFFFF };
+	const uint8x16_t barrett_reduction_constants =
+			(uint8x16_t)(uint64x2_t){ 0x00000001F7011641,
+						  0x00000001DB710641 };
+	const uint8x16_t zeroes = (uint8x16_t){ 0 };
+
+	const uint8x16_t * const end = p + nr_segs;
+	const uint8x16_t * const end512 = p + (nr_segs & ~3);
+	uint8x16_t x0, x1, x2, x3;
+
+	x0 = *p++ ^ (uint8x16_t)(uint32x4_t){ remainder };
+	if (nr_segs >= 4) {
+		x1 = *p++;
+		x2 = *p++;
+		x3 = *p++;
+
+		/* Fold 512 bits at a time */
+		while (p != end512) {
+			x0 = fold_128b(*p++, x0, multipliers_4);
+			x1 = fold_128b(*p++, x1, multipliers_4);
+			x2 = fold_128b(*p++, x2, multipliers_4);
+			x3 = fold_128b(*p++, x3, multipliers_4);
+		}
+
+		/* Fold 512 bits => 128 bits */
+		x1 = fold_128b(x1, x0, multipliers_1);
+		x2 = fold_128b(x2, x1, multipliers_1);
+		x0 = fold_128b(x3, x2, multipliers_1);
+	}
+
+	/* Fold 128 bits at a time */
+	while (p != end)
+		x0 = fold_128b(*p++, x0, multipliers_1);
+
+	/* Fold 128 => 96 bits, implicitly appending 32 zeroes */
+	x0 = vextq_u8(x0, zeroes, 8) ^ clmul_10(x0, multipliers_1);
+
+	/* Fold 96 => 64 bits */
+	x0 = vextq_u8(x0, zeroes, 4) ^ clmul_00(x0 & mask32, final_multiplier);
+
+	/* Reduce 64 => 32 bits using Barrett reduction */
+	x1 = x0;
+	x0 = clmul_00(x0 & mask32, barrett_reduction_constants);
+	x0 = clmul_10(x0 & mask32, barrett_reduction_constants);
+	return vgetq_lane_u32((uint32x4_t)(x0 ^ x1), 1);
+}
+#define IMPL_ALIGNMENT		16
+#define IMPL_SEGMENT_SIZE	16
+#include "../crc32_vec_template.h"
+#endif /* PMULL implementation */
+
+#ifdef DISPATCH
+static inline crc32_func_t
+arch_select_crc32_func(void)
+{
+	u32 features = get_cpu_features();
+
+#ifdef DISPATCH_ARM
+	if (features & ARM_CPU_FEATURE_CRC32)
+		return crc32_arm;
+#endif
+#ifdef DISPATCH_PMULL
+	if (features & ARM_CPU_FEATURE_PMULL)
+		return crc32_pmull;
+#endif
+	return NULL;
+}
+#endif /* DISPATCH */
+
+#endif /* LIB_ARM_CRC32_IMPL_H */

ADDED   3rd_party/libdeflate/lib/arm/matchfinder_impl.h
Index: 3rd_party/libdeflate/lib/arm/matchfinder_impl.h
==================================================================
--- 3rd_party/libdeflate/lib/arm/matchfinder_impl.h
+++ 3rd_party/libdeflate/lib/arm/matchfinder_impl.h
@@ -0,0 +1,86 @@
+/*
+ * arm/matchfinder_impl.h - ARM implementations of matchfinder functions
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#ifndef LIB_ARM_MATCHFINDER_IMPL_H
+#define LIB_ARM_MATCHFINDER_IMPL_H
+
+#ifdef __ARM_NEON
+#  include <arm_neon.h>
+static forceinline void
+matchfinder_init_neon(mf_pos_t *data, size_t size)
+{
+	int16x8_t *p = (int16x8_t *)data;
+	int16x8_t v = (int16x8_t) {
+		MATCHFINDER_INITVAL, MATCHFINDER_INITVAL, MATCHFINDER_INITVAL,
+		MATCHFINDER_INITVAL, MATCHFINDER_INITVAL, MATCHFINDER_INITVAL,
+		MATCHFINDER_INITVAL, MATCHFINDER_INITVAL,
+	};
+
+	STATIC_ASSERT(MATCHFINDER_MEM_ALIGNMENT % sizeof(*p) == 0);
+	STATIC_ASSERT(MATCHFINDER_SIZE_ALIGNMENT % (4 * sizeof(*p)) == 0);
+	STATIC_ASSERT(sizeof(mf_pos_t) == 2);
+
+	do {
+		p[0] = v;
+		p[1] = v;
+		p[2] = v;
+		p[3] = v;
+		p += 4;
+		size -= 4 * sizeof(*p);
+	} while (size != 0);
+}
+#define matchfinder_init matchfinder_init_neon
+
+static forceinline void
+matchfinder_rebase_neon(mf_pos_t *data, size_t size)
+{
+	int16x8_t *p = (int16x8_t *)data;
+	int16x8_t v = (int16x8_t) {
+		(u16)-MATCHFINDER_WINDOW_SIZE, (u16)-MATCHFINDER_WINDOW_SIZE,
+		(u16)-MATCHFINDER_WINDOW_SIZE, (u16)-MATCHFINDER_WINDOW_SIZE,
+		(u16)-MATCHFINDER_WINDOW_SIZE, (u16)-MATCHFINDER_WINDOW_SIZE,
+		(u16)-MATCHFINDER_WINDOW_SIZE, (u16)-MATCHFINDER_WINDOW_SIZE,
+	};
+
+	STATIC_ASSERT(MATCHFINDER_MEM_ALIGNMENT % sizeof(*p) == 0);
+	STATIC_ASSERT(MATCHFINDER_SIZE_ALIGNMENT % (4 * sizeof(*p)) == 0);
+	STATIC_ASSERT(sizeof(mf_pos_t) == 2);
+
+	do {
+		p[0] = vqaddq_s16(p[0], v);
+		p[1] = vqaddq_s16(p[1], v);
+		p[2] = vqaddq_s16(p[2], v);
+		p[3] = vqaddq_s16(p[3], v);
+		p += 4;
+		size -= 4 * sizeof(*p);
+	} while (size != 0);
+}
+#define matchfinder_rebase matchfinder_rebase_neon
+
+#endif /* __ARM_NEON */
+
+#endif /* LIB_ARM_MATCHFINDER_IMPL_H */

ADDED   3rd_party/libdeflate/lib/bt_matchfinder.h
Index: 3rd_party/libdeflate/lib/bt_matchfinder.h
==================================================================
--- 3rd_party/libdeflate/lib/bt_matchfinder.h
+++ 3rd_party/libdeflate/lib/bt_matchfinder.h
@@ -0,0 +1,363 @@
+/*
+ * bt_matchfinder.h - Lempel-Ziv matchfinding with a hash table of binary trees
+ *
+ * Originally public domain; changes after 2016-09-07 are copyrighted.
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ *
+ * ----------------------------------------------------------------------------
+ *
+ * This is a Binary Trees (bt) based matchfinder.
+ *
+ * The main data structure is a hash table where each hash bucket contains a
+ * binary tree of sequences whose first 4 bytes share the same hash code.  Each
+ * sequence is identified by its starting position in the input buffer.  Each
+ * binary tree is always sorted such that each left child represents a sequence
+ * lexicographically lesser than its parent and each right child represents a
+ * sequence lexicographically greater than its parent.
+ *
+ * The algorithm processes the input buffer sequentially.  At each byte
+ * position, the hash code of the first 4 bytes of the sequence beginning at
+ * that position (the sequence being matched against) is computed.  This
+ * identifies the hash bucket to use for that position.  Then, a new binary tree
+ * node is created to represent the current sequence.  Then, in a single tree
+ * traversal, the hash bucket's binary tree is searched for matches and is
+ * re-rooted at the new node.
+ *
+ * Compared to the simpler algorithm that uses linked lists instead of binary
+ * trees (see hc_matchfinder.h), the binary tree version gains more information
+ * at each node visitation.  Ideally, the binary tree version will examine only
+ * 'log(n)' nodes to find the same matches that the linked list version will
+ * find by examining 'n' nodes.  In addition, the binary tree version can
+ * examine fewer bytes at each node by taking advantage of the common prefixes
+ * that result from the sort order, whereas the linked list version may have to
+ * examine up to the full length of the match at each node.
+ *
+ * However, it is not always best to use the binary tree version.  It requires
+ * nearly twice as much memory as the linked list version, and it takes time to
+ * keep the binary trees sorted, even at positions where the compressor does not
+ * need matches.  Generally, when doing fast compression on small buffers,
+ * binary trees are the wrong approach.  They are best suited for thorough
+ * compression and/or large buffers.
+ *
+ * ----------------------------------------------------------------------------
+ */
+
+#ifndef LIB_BT_MATCHFINDER_H
+#define LIB_BT_MATCHFINDER_H
+
+#include "matchfinder_common.h"
+
+#define BT_MATCHFINDER_HASH3_ORDER 16
+#define BT_MATCHFINDER_HASH3_WAYS  2
+#define BT_MATCHFINDER_HASH4_ORDER 16
+
+#define BT_MATCHFINDER_TOTAL_HASH_SIZE		\
+	(((1UL << BT_MATCHFINDER_HASH3_ORDER) * BT_MATCHFINDER_HASH3_WAYS + \
+	  (1UL << BT_MATCHFINDER_HASH4_ORDER)) * sizeof(mf_pos_t))
+
+/* Representation of a match found by the bt_matchfinder  */
+struct lz_match {
+
+	/* The number of bytes matched.  */
+	u16 length;
+
+	/* The offset back from the current position that was matched.  */
+	u16 offset;
+};
+
+struct bt_matchfinder {
+
+	/* The hash table for finding length 3 matches  */
+	mf_pos_t hash3_tab[1UL << BT_MATCHFINDER_HASH3_ORDER][BT_MATCHFINDER_HASH3_WAYS];
+
+	/* The hash table which contains the roots of the binary trees for
+	 * finding length 4+ matches  */
+	mf_pos_t hash4_tab[1UL << BT_MATCHFINDER_HASH4_ORDER];
+
+	/* The child node references for the binary trees.  The left and right
+	 * children of the node for the sequence with position 'pos' are
+	 * 'child_tab[pos * 2]' and 'child_tab[pos * 2 + 1]', respectively.  */
+	mf_pos_t child_tab[2UL * MATCHFINDER_WINDOW_SIZE];
+
+}
+#ifdef _aligned_attribute
+_aligned_attribute(MATCHFINDER_MEM_ALIGNMENT)
+#endif
+;
+
+/* Prepare the matchfinder for a new input buffer.  */
+static forceinline void
+bt_matchfinder_init(struct bt_matchfinder *mf)
+{
+	STATIC_ASSERT(BT_MATCHFINDER_TOTAL_HASH_SIZE %
+		      MATCHFINDER_SIZE_ALIGNMENT == 0);
+
+	matchfinder_init((mf_pos_t *)mf, BT_MATCHFINDER_TOTAL_HASH_SIZE);
+}
+
+static forceinline void
+bt_matchfinder_slide_window(struct bt_matchfinder *mf)
+{
+	STATIC_ASSERT(sizeof(*mf) % MATCHFINDER_SIZE_ALIGNMENT == 0);
+
+	matchfinder_rebase((mf_pos_t *)mf, sizeof(*mf));
+}
+
+static forceinline mf_pos_t *
+bt_left_child(struct bt_matchfinder *mf, s32 node)
+{
+	return &mf->child_tab[2 * (node & (MATCHFINDER_WINDOW_SIZE - 1)) + 0];
+}
+
+static forceinline mf_pos_t *
+bt_right_child(struct bt_matchfinder *mf, s32 node)
+{
+	return &mf->child_tab[2 * (node & (MATCHFINDER_WINDOW_SIZE - 1)) + 1];
+}
+
+/* The minimum permissible value of 'max_len' for bt_matchfinder_get_matches()
+ * and bt_matchfinder_skip_position().  There must be sufficiently many bytes
+ * remaining to load a 32-bit integer from the *next* position.  */
+#define BT_MATCHFINDER_REQUIRED_NBYTES	5
+
+/* Advance the binary tree matchfinder by one byte, optionally recording
+ * matches.  @record_matches should be a compile-time constant.  */
+static forceinline struct lz_match *
+bt_matchfinder_advance_one_byte(struct bt_matchfinder * const restrict mf,
+				const u8 * const restrict in_base,
+				const ptrdiff_t cur_pos,
+				const u32 max_len,
+				const u32 nice_len,
+				const u32 max_search_depth,
+				u32 * const restrict next_hashes,
+				u32 * const restrict best_len_ret,
+				struct lz_match * restrict lz_matchptr,
+				const bool record_matches)
+{
+	const u8 *in_next = in_base + cur_pos;
+	u32 depth_remaining = max_search_depth;
+	const s32 cutoff = cur_pos - MATCHFINDER_WINDOW_SIZE;
+	u32 next_hashseq;
+	u32 hash3;
+	u32 hash4;
+	s32 cur_node;
+#if BT_MATCHFINDER_HASH3_WAYS >= 2
+	s32 cur_node_2;
+#endif
+	const u8 *matchptr;
+	mf_pos_t *pending_lt_ptr, *pending_gt_ptr;
+	u32 best_lt_len, best_gt_len;
+	u32 len;
+	u32 best_len = 3;
+
+	STATIC_ASSERT(BT_MATCHFINDER_HASH3_WAYS >= 1 &&
+		      BT_MATCHFINDER_HASH3_WAYS <= 2);
+
+	next_hashseq = get_unaligned_le32(in_next + 1);
+
+	hash3 = next_hashes[0];
+	hash4 = next_hashes[1];
+
+	next_hashes[0] = lz_hash(next_hashseq & 0xFFFFFF, BT_MATCHFINDER_HASH3_ORDER);
+	next_hashes[1] = lz_hash(next_hashseq, BT_MATCHFINDER_HASH4_ORDER);
+	prefetchw(&mf->hash3_tab[next_hashes[0]]);
+	prefetchw(&mf->hash4_tab[next_hashes[1]]);
+
+	cur_node = mf->hash3_tab[hash3][0];
+	mf->hash3_tab[hash3][0] = cur_pos;
+#if BT_MATCHFINDER_HASH3_WAYS >= 2
+	cur_node_2 = mf->hash3_tab[hash3][1];
+	mf->hash3_tab[hash3][1] = cur_node;
+#endif
+	if (record_matches && cur_node > cutoff) {
+		u32 seq3 = load_u24_unaligned(in_next);
+		if (seq3 == load_u24_unaligned(&in_base[cur_node])) {
+			lz_matchptr->length = 3;
+			lz_matchptr->offset = in_next - &in_base[cur_node];
+			lz_matchptr++;
+		}
+	#if BT_MATCHFINDER_HASH3_WAYS >= 2
+		else if (cur_node_2 > cutoff &&
+			seq3 == load_u24_unaligned(&in_base[cur_node_2]))
+		{
+			lz_matchptr->length = 3;
+			lz_matchptr->offset = in_next - &in_base[cur_node_2];
+			lz_matchptr++;
+		}
+	#endif
+	}
+
+	cur_node = mf->hash4_tab[hash4];
+	mf->hash4_tab[hash4] = cur_pos;
+
+	pending_lt_ptr = bt_left_child(mf, cur_pos);
+	pending_gt_ptr = bt_right_child(mf, cur_pos);
+
+	if (cur_node <= cutoff) {
+		*pending_lt_ptr = MATCHFINDER_INITVAL;
+		*pending_gt_ptr = MATCHFINDER_INITVAL;
+		*best_len_ret = best_len;
+		return lz_matchptr;
+	}
+
+	best_lt_len = 0;
+	best_gt_len = 0;
+	len = 0;
+
+	for (;;) {
+		matchptr = &in_base[cur_node];
+
+		if (matchptr[len] == in_next[len]) {
+			len = lz_extend(in_next, matchptr, len + 1, max_len);
+			if (!record_matches || len > best_len) {
+				if (record_matches) {
+					best_len = len;
+					lz_matchptr->length = len;
+					lz_matchptr->offset = in_next - matchptr;
+					lz_matchptr++;
+				}
+				if (len >= nice_len) {
+					*pending_lt_ptr = *bt_left_child(mf, cur_node);
+					*pending_gt_ptr = *bt_right_child(mf, cur_node);
+					*best_len_ret = best_len;
+					return lz_matchptr;
+				}
+			}
+		}
+
+		if (matchptr[len] < in_next[len]) {
+			*pending_lt_ptr = cur_node;
+			pending_lt_ptr = bt_right_child(mf, cur_node);
+			cur_node = *pending_lt_ptr;
+			best_lt_len = len;
+			if (best_gt_len < len)
+				len = best_gt_len;
+		} else {
+			*pending_gt_ptr = cur_node;
+			pending_gt_ptr = bt_left_child(mf, cur_node);
+			cur_node = *pending_gt_ptr;
+			best_gt_len = len;
+			if (best_lt_len < len)
+				len = best_lt_len;
+		}
+
+		if (cur_node <= cutoff || !--depth_remaining) {
+			*pending_lt_ptr = MATCHFINDER_INITVAL;
+			*pending_gt_ptr = MATCHFINDER_INITVAL;
+			*best_len_ret = best_len;
+			return lz_matchptr;
+		}
+	}
+}
+
+/*
+ * Retrieve a list of matches with the current position.
+ *
+ * @mf
+ *	The matchfinder structure.
+ * @in_base
+ *	Pointer to the next byte in the input buffer to process _at the last
+ *	time bt_matchfinder_init() or bt_matchfinder_slide_window() was called_.
+ * @cur_pos
+ *	The current position in the input buffer relative to @in_base (the
+ *	position of the sequence being matched against).
+ * @max_len
+ *	The maximum permissible match length at this position.  Must be >=
+ *	BT_MATCHFINDER_REQUIRED_NBYTES.
+ * @nice_len
+ *	Stop searching if a match of at least this length is found.
+ *	Must be <= @max_len.
+ * @max_search_depth
+ *	Limit on the number of potential matches to consider.  Must be >= 1.
+ * @next_hashes
+ *	The precomputed hash codes for the sequence beginning at @in_next.
+ *	These will be used and then updated with the precomputed hashcodes for
+ *	the sequence beginning at @in_next + 1.
+ * @best_len_ret
+ *	If a match of length >= 4 was found, then the length of the longest such
+ *	match is written here; otherwise 3 is written here.  (Note: this is
+ *	redundant with the 'struct lz_match' array, but this is easier for the
+ *	compiler to optimize when inlined and the caller immediately does a
+ *	check against 'best_len'.)
+ * @lz_matchptr
+ *	An array in which this function will record the matches.  The recorded
+ *	matches will be sorted by strictly increasing length and (non-strictly)
+ *	increasing offset.  The maximum number of matches that may be found is
+ *	'nice_len - 2'.
+ *
+ * The return value is a pointer to the next available slot in the @lz_matchptr
+ * array.  (If no matches were found, this will be the same as @lz_matchptr.)
+ */
+static forceinline struct lz_match *
+bt_matchfinder_get_matches(struct bt_matchfinder *mf,
+			   const u8 *in_base,
+			   ptrdiff_t cur_pos,
+			   u32 max_len,
+			   u32 nice_len,
+			   u32 max_search_depth,
+			   u32 next_hashes[2],
+			   u32 *best_len_ret,
+			   struct lz_match *lz_matchptr)
+{
+	return bt_matchfinder_advance_one_byte(mf,
+					       in_base,
+					       cur_pos,
+					       max_len,
+					       nice_len,
+					       max_search_depth,
+					       next_hashes,
+					       best_len_ret,
+					       lz_matchptr,
+					       true);
+}
+
+/*
+ * Advance the matchfinder, but don't record any matches.
+ *
+ * This is very similar to bt_matchfinder_get_matches() because both functions
+ * must do hashing and tree re-rooting.
+ */
+static forceinline void
+bt_matchfinder_skip_position(struct bt_matchfinder *mf,
+			     const u8 *in_base,
+			     ptrdiff_t cur_pos,
+			     u32 nice_len,
+			     u32 max_search_depth,
+			     u32 next_hashes[2])
+{
+	u32 best_len;
+	bt_matchfinder_advance_one_byte(mf,
+					in_base,
+					cur_pos,
+					nice_len,
+					nice_len,
+					max_search_depth,
+					next_hashes,
+					&best_len,
+					NULL,
+					false);
+}
+
+#endif /* LIB_BT_MATCHFINDER_H */

ADDED   3rd_party/libdeflate/lib/cpu_features_common.h
Index: 3rd_party/libdeflate/lib/cpu_features_common.h
==================================================================
--- 3rd_party/libdeflate/lib/cpu_features_common.h
+++ 3rd_party/libdeflate/lib/cpu_features_common.h
@@ -0,0 +1,88 @@
+/*
+ * cpu_features_common.h - code shared by all lib/$arch/cpu_features.c
+ *
+ * Copyright 2020 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#ifndef LIB_CPU_FEATURES_COMMON_H
+#define LIB_CPU_FEATURES_COMMON_H
+
+#if defined(TEST_SUPPORT__DO_NOT_USE) && !defined(FREESTANDING)
+#  define _GNU_SOURCE 1 /* for strdup() and strtok_r() */
+#  include <stdio.h>
+#  include <stdlib.h>
+#  include <string.h>
+#endif
+
+#include "lib_common.h"
+
+struct cpu_feature {
+	u32 bit;
+	const char *name;
+};
+
+#if defined(TEST_SUPPORT__DO_NOT_USE) && !defined(FREESTANDING)
+/* Disable any features that are listed in $LIBDEFLATE_DISABLE_CPU_FEATURES. */
+static inline void
+disable_cpu_features_for_testing(u32 *features,
+				 const struct cpu_feature *feature_table,
+				 size_t feature_table_length)
+{
+	char *env_value, *strbuf, *p, *saveptr = NULL;
+	size_t i;
+
+	env_value = getenv("LIBDEFLATE_DISABLE_CPU_FEATURES");
+	if (!env_value)
+		return;
+	strbuf = strdup(env_value);
+	if (!strbuf)
+		abort();
+	p = strtok_r(strbuf, ",", &saveptr);
+	while (p) {
+		for (i = 0; i < feature_table_length; i++) {
+			if (strcmp(p, feature_table[i].name) == 0) {
+				*features &= ~feature_table[i].bit;
+				break;
+			}
+		}
+		if (i == feature_table_length) {
+			fprintf(stderr,
+				"unrecognized feature in LIBDEFLATE_DISABLE_CPU_FEATURES: \"%s\"\n",
+				p);
+			abort();
+		}
+		p = strtok_r(NULL, ",", &saveptr);
+	}
+	free(strbuf);
+}
+#else /* TEST_SUPPORT__DO_NOT_USE */
+static inline void
+disable_cpu_features_for_testing(u32 *features,
+				 const struct cpu_feature *feature_table,
+				 size_t feature_table_length)
+{
+}
+#endif /* !TEST_SUPPORT__DO_NOT_USE */
+
+#endif /* LIB_CPU_FEATURES_COMMON_H */

ADDED   3rd_party/libdeflate/lib/crc32.c
Index: 3rd_party/libdeflate/lib/crc32.c
==================================================================
--- 3rd_party/libdeflate/lib/crc32.c
+++ 3rd_party/libdeflate/lib/crc32.c
@@ -0,0 +1,313 @@
+/*
+ * crc32.c - CRC-32 checksum algorithm for the gzip format
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+/*
+ * High-level description of CRC
+ * =============================
+ *
+ * Consider a bit sequence 'bits[1...len]'.  Interpret 'bits' as the "message"
+ * polynomial M(x) with coefficients in GF(2) (the field of integers modulo 2),
+ * where the coefficient of 'x^i' is 'bits[len - i]'.  Then, compute:
+ *
+ *			R(x) = M(x)*x^n mod G(x)
+ *
+ * where G(x) is a selected "generator" polynomial of degree 'n'.  The remainder
+ * R(x) is a polynomial of max degree 'n - 1'.  The CRC of 'bits' is R(x)
+ * interpreted as a bitstring of length 'n'.
+ *
+ * CRC used in gzip
+ * ================
+ *
+ * In the gzip format (RFC 1952):
+ *
+ *	- The bitstring to checksum is formed from the bytes of the uncompressed
+ *	  data by concatenating the bits from the bytes in order, proceeding
+ *	  from the low-order bit to the high-order bit within each byte.
+ *
+ *	- The generator polynomial G(x) is: x^32 + x^26 + x^23 + x^22 + x^16 +
+ *	  x^12 + x^11 + x^10 + x^8 + x^7 + x^5 + x^4 + x^2 + x + 1.
+ *	  Consequently, the CRC length is 32 bits ("CRC-32").
+ *
+ *	- The highest order 32 coefficients of M(x)*x^n are inverted.
+ *
+ *	- All 32 coefficients of R(x) are inverted.
+ *
+ * The two inversions cause added leading and trailing zero bits to affect the
+ * resulting CRC, whereas with a regular CRC such bits would have no effect on
+ * the CRC.
+ *
+ * Computation and optimizations
+ * =============================
+ *
+ * We can compute R(x) through "long division", maintaining only 32 bits of
+ * state at any given time.  Multiplication by 'x' can be implemented as
+ * right-shifting by 1 (assuming the polynomial<=>bitstring mapping where the
+ * highest order bit represents the coefficient of x^0), and both addition and
+ * subtraction can be implemented as bitwise exclusive OR (since we are working
+ * in GF(2)).  Here is an unoptimized implementation:
+ *
+ *	static u32 crc32_gzip(const u8 *buffer, size_t size)
+ *	{
+ *		u32 remainder = 0;
+ *		const u32 divisor = 0xEDB88320;
+ *
+ *		for (size_t i = 0; i < size * 8 + 32; i++) {
+ *			int bit;
+ *			u32 multiple;
+ *
+ *			if (i < size * 8)
+ *				bit = (buffer[i / 8] >> (i % 8)) & 1;
+ *			else
+ *				bit = 0; // one of the 32 appended 0 bits
+ *
+ *			if (i < 32) // the first 32 bits are inverted
+ *				bit ^= 1;
+ *
+ *			if (remainder & 1)
+ *				multiple = divisor;
+ *			else
+ *				multiple = 0;
+ *
+ *			remainder >>= 1;
+ *			remainder |= (u32)bit << 31;
+ *			remainder ^= multiple;
+ *		}
+ *
+ *		return ~remainder;
+ *	}
+ *
+ * In this implementation, the 32-bit integer 'remainder' maintains the
+ * remainder of the currently processed portion of the message (with 32 zero
+ * bits appended) when divided by the generator polynomial.  'remainder' is the
+ * representation of R(x), and 'divisor' is the representation of G(x) excluding
+ * the x^32 coefficient.  For each bit to process, we multiply R(x) by 'x^1',
+ * then add 'x^0' if the new bit is a 1.  If this causes R(x) to gain a nonzero
+ * x^32 term, then we subtract G(x) from R(x).
+ *
+ * We can speed this up by taking advantage of the fact that XOR is commutative
+ * and associative, so the order in which we combine the inputs into 'remainder'
+ * is unimportant.  And since each message bit we add doesn't affect the choice
+ * of 'multiple' until 32 bits later, we need not actually add each message bit
+ * until that point:
+ *
+ *	static u32 crc32_gzip(const u8 *buffer, size_t size)
+ *	{
+ *		u32 remainder = ~0;
+ *		const u32 divisor = 0xEDB88320;
+ *
+ *		for (size_t i = 0; i < size * 8; i++) {
+ *			int bit;
+ *			u32 multiple;
+ *
+ *			bit = (buffer[i / 8] >> (i % 8)) & 1;
+ *			remainder ^= bit;
+ *			if (remainder & 1)
+ *				multiple = divisor;
+ *			else
+ *				multiple = 0;
+ *			remainder >>= 1;
+ *			remainder ^= multiple;
+ *		}
+ *
+ *		return ~remainder;
+ *	}
+ *
+ * With the above implementation we get the effect of 32 appended 0 bits for
+ * free; they never affect the choice of a divisor, nor would they change the
+ * value of 'remainder' if they were to be actually XOR'ed in.  And by starting
+ * with a remainder of all 1 bits, we get the effect of complementing the first
+ * 32 message bits.
+ *
+ * The next optimization is to process the input in multi-bit units.  Suppose
+ * that we insert the next 'n' message bits into the remainder.  Then we get an
+ * intermediate remainder of length '32 + n' bits, and the CRC of the extra 'n'
+ * bits is the amount by which the low 32 bits of the remainder will change as a
+ * result of cancelling out those 'n' bits.  Taking n=8 (one byte) and
+ * precomputing a table containing the CRC of each possible byte, we get
+ * crc32_slice1() defined below.
+ *
+ * As a further optimization, we could increase the multi-bit unit size to 16.
+ * However, that is inefficient because the table size explodes from 256 entries
+ * (1024 bytes) to 65536 entries (262144 bytes), which wastes memory and won't
+ * fit in L1 cache on typical processors.
+ *
+ * However, we can actually process 4 bytes at a time using 4 different tables
+ * with 256 entries each.  Logically, we form a 64-bit intermediate remainder
+ * and cancel out the high 32 bits in 8-bit chunks.  Bits 32-39 are cancelled
+ * out by the CRC of those bits, whereas bits 40-47 are be cancelled out by the
+ * CRC of those bits with 8 zero bits appended, and so on.  This method is
+ * implemented in crc32_slice4(), defined below.
+ *
+ * In crc32_slice8(), this method is extended to 8 bytes at a time.  The
+ * intermediate remainder (which we never actually store explicitly) is 96 bits.
+ *
+ * On CPUs that support fast carryless multiplication, CRCs can be computed even
+ * more quickly via "folding".  See e.g. the x86 PCLMUL implementation.
+ */
+
+#include "lib_common.h"
+#include "libdeflate.h"
+
+typedef u32 (*crc32_func_t)(u32, const u8 *, size_t);
+
+/* Include architecture-specific implementations if available */
+#undef CRC32_SLICE1
+#undef CRC32_SLICE4
+#undef CRC32_SLICE8
+#undef DEFAULT_IMPL
+#undef DISPATCH
+#if defined(__arm__) || defined(__aarch64__)
+#  include "arm/crc32_impl.h"
+#elif defined(__i386__) || defined(__x86_64__)
+#  include "x86/crc32_impl.h"
+#endif
+
+/*
+ * Define a generic implementation (crc32_slice8()) if needed.  crc32_slice1()
+ * may also be needed as a fallback for architecture-specific implementations.
+ */
+
+#ifndef DEFAULT_IMPL
+#  define CRC32_SLICE8	1
+#  define DEFAULT_IMPL	crc32_slice8
+#endif
+
+#if defined(CRC32_SLICE1) || defined(CRC32_SLICE4) || defined(CRC32_SLICE8)
+#include "crc32_table.h"
+static forceinline u32
+crc32_update_byte(u32 remainder, u8 next_byte)
+{
+	return (remainder >> 8) ^ crc32_table[(u8)remainder ^ next_byte];
+}
+#endif
+
+#ifdef CRC32_SLICE1
+static u32
+crc32_slice1(u32 remainder, const u8 *buffer, size_t size)
+{
+	size_t i;
+
+	STATIC_ASSERT(ARRAY_LEN(crc32_table) >= 0x100);
+
+	for (i = 0; i < size; i++)
+		remainder = crc32_update_byte(remainder, buffer[i]);
+	return remainder;
+}
+#endif /* CRC32_SLICE1 */
+
+#ifdef CRC32_SLICE4
+static u32
+crc32_slice4(u32 remainder, const u8 *buffer, size_t size)
+{
+	const u8 *p = buffer;
+	const u8 *end = buffer + size;
+	const u8 *end32;
+
+	STATIC_ASSERT(ARRAY_LEN(crc32_table) >= 0x400);
+
+	for (; ((uintptr_t)p & 3) && p != end; p++)
+		remainder = crc32_update_byte(remainder, *p);
+
+	end32 = p + ((end - p) & ~3);
+	for (; p != end32; p += 4) {
+		u32 v = le32_bswap(*(const u32 *)p);
+		remainder =
+		    crc32_table[0x300 + (u8)((remainder ^ v) >>  0)] ^
+		    crc32_table[0x200 + (u8)((remainder ^ v) >>  8)] ^
+		    crc32_table[0x100 + (u8)((remainder ^ v) >> 16)] ^
+		    crc32_table[0x000 + (u8)((remainder ^ v) >> 24)];
+	}
+
+	for (; p != end; p++)
+		remainder = crc32_update_byte(remainder, *p);
+
+	return remainder;
+}
+#endif /* CRC32_SLICE4 */
+
+#ifdef CRC32_SLICE8
+static u32
+crc32_slice8(u32 remainder, const u8 *buffer, size_t size)
+{
+	const u8 *p = buffer;
+	const u8 *end = buffer + size;
+	const u8 *end64;
+
+	STATIC_ASSERT(ARRAY_LEN(crc32_table) >= 0x800);
+
+	for (; ((uintptr_t)p & 7) && p != end; p++)
+		remainder = crc32_update_byte(remainder, *p);
+
+	end64 = p + ((end - p) & ~7);
+	for (; p != end64; p += 8) {
+		u32 v1 = le32_bswap(*(const u32 *)(p + 0));
+		u32 v2 = le32_bswap(*(const u32 *)(p + 4));
+		remainder =
+		    crc32_table[0x700 + (u8)((remainder ^ v1) >>  0)] ^
+		    crc32_table[0x600 + (u8)((remainder ^ v1) >>  8)] ^
+		    crc32_table[0x500 + (u8)((remainder ^ v1) >> 16)] ^
+		    crc32_table[0x400 + (u8)((remainder ^ v1) >> 24)] ^
+		    crc32_table[0x300 + (u8)(v2 >>  0)] ^
+		    crc32_table[0x200 + (u8)(v2 >>  8)] ^
+		    crc32_table[0x100 + (u8)(v2 >> 16)] ^
+		    crc32_table[0x000 + (u8)(v2 >> 24)];
+	}
+
+	for (; p != end; p++)
+		remainder = crc32_update_byte(remainder, *p);
+
+	return remainder;
+}
+#endif /* CRC32_SLICE8 */
+
+#ifdef DISPATCH
+static u32 dispatch(u32, const u8 *, size_t);
+
+static volatile crc32_func_t crc32_impl = dispatch;
+
+/* Choose the fastest implementation at runtime */
+static u32 dispatch(u32 remainder, const u8 *buffer, size_t size)
+{
+	crc32_func_t f = arch_select_crc32_func();
+
+	if (f == NULL)
+		f = DEFAULT_IMPL;
+
+	crc32_impl = f;
+	return crc32_impl(remainder, buffer, size);
+}
+#else
+#  define crc32_impl DEFAULT_IMPL /* only one implementation, use it */
+#endif
+
+LIBDEFLATEEXPORT u32 LIBDEFLATEAPI
+libdeflate_crc32(u32 remainder, const void *buffer, size_t size)
+{
+	if (buffer == NULL) /* return initial value */
+		return 0;
+	return ~crc32_impl(~remainder, buffer, size);
+}

ADDED   3rd_party/libdeflate/lib/crc32_table.h
Index: 3rd_party/libdeflate/lib/crc32_table.h
==================================================================
--- 3rd_party/libdeflate/lib/crc32_table.h
+++ 3rd_party/libdeflate/lib/crc32_table.h
@@ -0,0 +1,526 @@
+/*
+ * crc32_table.h - data table to accelerate CRC-32 computation
+ *
+ * THIS FILE WAS AUTOMATICALLY GENERATED BY gen_crc32_table.c.  DO NOT EDIT.
+ */
+
+#include <stdint.h>
+
+static const uint32_t crc32_table[] = {
+	0x00000000, 0x77073096, 0xee0e612c, 0x990951ba,
+	0x076dc419, 0x706af48f, 0xe963a535, 0x9e6495a3,
+	0x0edb8832, 0x79dcb8a4, 0xe0d5e91e, 0x97d2d988,
+	0x09b64c2b, 0x7eb17cbd, 0xe7b82d07, 0x90bf1d91,
+	0x1db71064, 0x6ab020f2, 0xf3b97148, 0x84be41de,
+	0x1adad47d, 0x6ddde4eb, 0xf4d4b551, 0x83d385c7,
+	0x136c9856, 0x646ba8c0, 0xfd62f97a, 0x8a65c9ec,
+	0x14015c4f, 0x63066cd9, 0xfa0f3d63, 0x8d080df5,
+	0x3b6e20c8, 0x4c69105e, 0xd56041e4, 0xa2677172,
+	0x3c03e4d1, 0x4b04d447, 0xd20d85fd, 0xa50ab56b,
+	0x35b5a8fa, 0x42b2986c, 0xdbbbc9d6, 0xacbcf940,
+	0x32d86ce3, 0x45df5c75, 0xdcd60dcf, 0xabd13d59,
+	0x26d930ac, 0x51de003a, 0xc8d75180, 0xbfd06116,
+	0x21b4f4b5, 0x56b3c423, 0xcfba9599, 0xb8bda50f,
+	0x2802b89e, 0x5f058808, 0xc60cd9b2, 0xb10be924,
+	0x2f6f7c87, 0x58684c11, 0xc1611dab, 0xb6662d3d,
+	0x76dc4190, 0x01db7106, 0x98d220bc, 0xefd5102a,
+	0x71b18589, 0x06b6b51f, 0x9fbfe4a5, 0xe8b8d433,
+	0x7807c9a2, 0x0f00f934, 0x9609a88e, 0xe10e9818,
+	0x7f6a0dbb, 0x086d3d2d, 0x91646c97, 0xe6635c01,
+	0x6b6b51f4, 0x1c6c6162, 0x856530d8, 0xf262004e,
+	0x6c0695ed, 0x1b01a57b, 0x8208f4c1, 0xf50fc457,
+	0x65b0d9c6, 0x12b7e950, 0x8bbeb8ea, 0xfcb9887c,
+	0x62dd1ddf, 0x15da2d49, 0x8cd37cf3, 0xfbd44c65,
+	0x4db26158, 0x3ab551ce, 0xa3bc0074, 0xd4bb30e2,
+	0x4adfa541, 0x3dd895d7, 0xa4d1c46d, 0xd3d6f4fb,
+	0x4369e96a, 0x346ed9fc, 0xad678846, 0xda60b8d0,
+	0x44042d73, 0x33031de5, 0xaa0a4c5f, 0xdd0d7cc9,
+	0x5005713c, 0x270241aa, 0xbe0b1010, 0xc90c2086,
+	0x5768b525, 0x206f85b3, 0xb966d409, 0xce61e49f,
+	0x5edef90e, 0x29d9c998, 0xb0d09822, 0xc7d7a8b4,
+	0x59b33d17, 0x2eb40d81, 0xb7bd5c3b, 0xc0ba6cad,
+	0xedb88320, 0x9abfb3b6, 0x03b6e20c, 0x74b1d29a,
+	0xead54739, 0x9dd277af, 0x04db2615, 0x73dc1683,
+	0xe3630b12, 0x94643b84, 0x0d6d6a3e, 0x7a6a5aa8,
+	0xe40ecf0b, 0x9309ff9d, 0x0a00ae27, 0x7d079eb1,
+	0xf00f9344, 0x8708a3d2, 0x1e01f268, 0x6906c2fe,
+	0xf762575d, 0x806567cb, 0x196c3671, 0x6e6b06e7,
+	0xfed41b76, 0x89d32be0, 0x10da7a5a, 0x67dd4acc,
+	0xf9b9df6f, 0x8ebeeff9, 0x17b7be43, 0x60b08ed5,
+	0xd6d6a3e8, 0xa1d1937e, 0x38d8c2c4, 0x4fdff252,
+	0xd1bb67f1, 0xa6bc5767, 0x3fb506dd, 0x48b2364b,
+	0xd80d2bda, 0xaf0a1b4c, 0x36034af6, 0x41047a60,
+	0xdf60efc3, 0xa867df55, 0x316e8eef, 0x4669be79,
+	0xcb61b38c, 0xbc66831a, 0x256fd2a0, 0x5268e236,
+	0xcc0c7795, 0xbb0b4703, 0x220216b9, 0x5505262f,
+	0xc5ba3bbe, 0xb2bd0b28, 0x2bb45a92, 0x5cb36a04,
+	0xc2d7ffa7, 0xb5d0cf31, 0x2cd99e8b, 0x5bdeae1d,
+	0x9b64c2b0, 0xec63f226, 0x756aa39c, 0x026d930a,
+	0x9c0906a9, 0xeb0e363f, 0x72076785, 0x05005713,
+	0x95bf4a82, 0xe2b87a14, 0x7bb12bae, 0x0cb61b38,
+	0x92d28e9b, 0xe5d5be0d, 0x7cdcefb7, 0x0bdbdf21,
+	0x86d3d2d4, 0xf1d4e242, 0x68ddb3f8, 0x1fda836e,
+	0x81be16cd, 0xf6b9265b, 0x6fb077e1, 0x18b74777,
+	0x88085ae6, 0xff0f6a70, 0x66063bca, 0x11010b5c,
+	0x8f659eff, 0xf862ae69, 0x616bffd3, 0x166ccf45,
+	0xa00ae278, 0xd70dd2ee, 0x4e048354, 0x3903b3c2,
+	0xa7672661, 0xd06016f7, 0x4969474d, 0x3e6e77db,
+	0xaed16a4a, 0xd9d65adc, 0x40df0b66, 0x37d83bf0,
+	0xa9bcae53, 0xdebb9ec5, 0x47b2cf7f, 0x30b5ffe9,
+	0xbdbdf21c, 0xcabac28a, 0x53b39330, 0x24b4a3a6,
+	0xbad03605, 0xcdd70693, 0x54de5729, 0x23d967bf,
+	0xb3667a2e, 0xc4614ab8, 0x5d681b02, 0x2a6f2b94,
+	0xb40bbe37, 0xc30c8ea1, 0x5a05df1b, 0x2d02ef8d,
+#if defined(CRC32_SLICE4) || defined(CRC32_SLICE8)
+	0x00000000, 0x191b3141, 0x32366282, 0x2b2d53c3,
+	0x646cc504, 0x7d77f445, 0x565aa786, 0x4f4196c7,
+	0xc8d98a08, 0xd1c2bb49, 0xfaefe88a, 0xe3f4d9cb,
+	0xacb54f0c, 0xb5ae7e4d, 0x9e832d8e, 0x87981ccf,
+	0x4ac21251, 0x53d92310, 0x78f470d3, 0x61ef4192,
+	0x2eaed755, 0x37b5e614, 0x1c98b5d7, 0x05838496,
+	0x821b9859, 0x9b00a918, 0xb02dfadb, 0xa936cb9a,
+	0xe6775d5d, 0xff6c6c1c, 0xd4413fdf, 0xcd5a0e9e,
+	0x958424a2, 0x8c9f15e3, 0xa7b24620, 0xbea97761,
+	0xf1e8e1a6, 0xe8f3d0e7, 0xc3de8324, 0xdac5b265,
+	0x5d5daeaa, 0x44469feb, 0x6f6bcc28, 0x7670fd69,
+	0x39316bae, 0x202a5aef, 0x0b07092c, 0x121c386d,
+	0xdf4636f3, 0xc65d07b2, 0xed705471, 0xf46b6530,
+	0xbb2af3f7, 0xa231c2b6, 0x891c9175, 0x9007a034,
+	0x179fbcfb, 0x0e848dba, 0x25a9de79, 0x3cb2ef38,
+	0x73f379ff, 0x6ae848be, 0x41c51b7d, 0x58de2a3c,
+	0xf0794f05, 0xe9627e44, 0xc24f2d87, 0xdb541cc6,
+	0x94158a01, 0x8d0ebb40, 0xa623e883, 0xbf38d9c2,
+	0x38a0c50d, 0x21bbf44c, 0x0a96a78f, 0x138d96ce,
+	0x5ccc0009, 0x45d73148, 0x6efa628b, 0x77e153ca,
+	0xbabb5d54, 0xa3a06c15, 0x888d3fd6, 0x91960e97,
+	0xded79850, 0xc7cca911, 0xece1fad2, 0xf5facb93,
+	0x7262d75c, 0x6b79e61d, 0x4054b5de, 0x594f849f,
+	0x160e1258, 0x0f152319, 0x243870da, 0x3d23419b,
+	0x65fd6ba7, 0x7ce65ae6, 0x57cb0925, 0x4ed03864,
+	0x0191aea3, 0x188a9fe2, 0x33a7cc21, 0x2abcfd60,
+	0xad24e1af, 0xb43fd0ee, 0x9f12832d, 0x8609b26c,
+	0xc94824ab, 0xd05315ea, 0xfb7e4629, 0xe2657768,
+	0x2f3f79f6, 0x362448b7, 0x1d091b74, 0x04122a35,
+	0x4b53bcf2, 0x52488db3, 0x7965de70, 0x607eef31,
+	0xe7e6f3fe, 0xfefdc2bf, 0xd5d0917c, 0xcccba03d,
+	0x838a36fa, 0x9a9107bb, 0xb1bc5478, 0xa8a76539,
+	0x3b83984b, 0x2298a90a, 0x09b5fac9, 0x10aecb88,
+	0x5fef5d4f, 0x46f46c0e, 0x6dd93fcd, 0x74c20e8c,
+	0xf35a1243, 0xea412302, 0xc16c70c1, 0xd8774180,
+	0x9736d747, 0x8e2de606, 0xa500b5c5, 0xbc1b8484,
+	0x71418a1a, 0x685abb5b, 0x4377e898, 0x5a6cd9d9,
+	0x152d4f1e, 0x0c367e5f, 0x271b2d9c, 0x3e001cdd,
+	0xb9980012, 0xa0833153, 0x8bae6290, 0x92b553d1,
+	0xddf4c516, 0xc4eff457, 0xefc2a794, 0xf6d996d5,
+	0xae07bce9, 0xb71c8da8, 0x9c31de6b, 0x852aef2a,
+	0xca6b79ed, 0xd37048ac, 0xf85d1b6f, 0xe1462a2e,
+	0x66de36e1, 0x7fc507a0, 0x54e85463, 0x4df36522,
+	0x02b2f3e5, 0x1ba9c2a4, 0x30849167, 0x299fa026,
+	0xe4c5aeb8, 0xfdde9ff9, 0xd6f3cc3a, 0xcfe8fd7b,
+	0x80a96bbc, 0x99b25afd, 0xb29f093e, 0xab84387f,
+	0x2c1c24b0, 0x350715f1, 0x1e2a4632, 0x07317773,
+	0x4870e1b4, 0x516bd0f5, 0x7a468336, 0x635db277,
+	0xcbfad74e, 0xd2e1e60f, 0xf9ccb5cc, 0xe0d7848d,
+	0xaf96124a, 0xb68d230b, 0x9da070c8, 0x84bb4189,
+	0x03235d46, 0x1a386c07, 0x31153fc4, 0x280e0e85,
+	0x674f9842, 0x7e54a903, 0x5579fac0, 0x4c62cb81,
+	0x8138c51f, 0x9823f45e, 0xb30ea79d, 0xaa1596dc,
+	0xe554001b, 0xfc4f315a, 0xd7626299, 0xce7953d8,
+	0x49e14f17, 0x50fa7e56, 0x7bd72d95, 0x62cc1cd4,
+	0x2d8d8a13, 0x3496bb52, 0x1fbbe891, 0x06a0d9d0,
+	0x5e7ef3ec, 0x4765c2ad, 0x6c48916e, 0x7553a02f,
+	0x3a1236e8, 0x230907a9, 0x0824546a, 0x113f652b,
+	0x96a779e4, 0x8fbc48a5, 0xa4911b66, 0xbd8a2a27,
+	0xf2cbbce0, 0xebd08da1, 0xc0fdde62, 0xd9e6ef23,
+	0x14bce1bd, 0x0da7d0fc, 0x268a833f, 0x3f91b27e,
+	0x70d024b9, 0x69cb15f8, 0x42e6463b, 0x5bfd777a,
+	0xdc656bb5, 0xc57e5af4, 0xee530937, 0xf7483876,
+	0xb809aeb1, 0xa1129ff0, 0x8a3fcc33, 0x9324fd72,
+	0x00000000, 0x01c26a37, 0x0384d46e, 0x0246be59,
+	0x0709a8dc, 0x06cbc2eb, 0x048d7cb2, 0x054f1685,
+	0x0e1351b8, 0x0fd13b8f, 0x0d9785d6, 0x0c55efe1,
+	0x091af964, 0x08d89353, 0x0a9e2d0a, 0x0b5c473d,
+	0x1c26a370, 0x1de4c947, 0x1fa2771e, 0x1e601d29,
+	0x1b2f0bac, 0x1aed619b, 0x18abdfc2, 0x1969b5f5,
+	0x1235f2c8, 0x13f798ff, 0x11b126a6, 0x10734c91,
+	0x153c5a14, 0x14fe3023, 0x16b88e7a, 0x177ae44d,
+	0x384d46e0, 0x398f2cd7, 0x3bc9928e, 0x3a0bf8b9,
+	0x3f44ee3c, 0x3e86840b, 0x3cc03a52, 0x3d025065,
+	0x365e1758, 0x379c7d6f, 0x35dac336, 0x3418a901,
+	0x3157bf84, 0x3095d5b3, 0x32d36bea, 0x331101dd,
+	0x246be590, 0x25a98fa7, 0x27ef31fe, 0x262d5bc9,
+	0x23624d4c, 0x22a0277b, 0x20e69922, 0x2124f315,
+	0x2a78b428, 0x2bbade1f, 0x29fc6046, 0x283e0a71,
+	0x2d711cf4, 0x2cb376c3, 0x2ef5c89a, 0x2f37a2ad,
+	0x709a8dc0, 0x7158e7f7, 0x731e59ae, 0x72dc3399,
+	0x7793251c, 0x76514f2b, 0x7417f172, 0x75d59b45,
+	0x7e89dc78, 0x7f4bb64f, 0x7d0d0816, 0x7ccf6221,
+	0x798074a4, 0x78421e93, 0x7a04a0ca, 0x7bc6cafd,
+	0x6cbc2eb0, 0x6d7e4487, 0x6f38fade, 0x6efa90e9,
+	0x6bb5866c, 0x6a77ec5b, 0x68315202, 0x69f33835,
+	0x62af7f08, 0x636d153f, 0x612bab66, 0x60e9c151,
+	0x65a6d7d4, 0x6464bde3, 0x662203ba, 0x67e0698d,
+	0x48d7cb20, 0x4915a117, 0x4b531f4e, 0x4a917579,
+	0x4fde63fc, 0x4e1c09cb, 0x4c5ab792, 0x4d98dda5,
+	0x46c49a98, 0x4706f0af, 0x45404ef6, 0x448224c1,
+	0x41cd3244, 0x400f5873, 0x4249e62a, 0x438b8c1d,
+	0x54f16850, 0x55330267, 0x5775bc3e, 0x56b7d609,
+	0x53f8c08c, 0x523aaabb, 0x507c14e2, 0x51be7ed5,
+	0x5ae239e8, 0x5b2053df, 0x5966ed86, 0x58a487b1,
+	0x5deb9134, 0x5c29fb03, 0x5e6f455a, 0x5fad2f6d,
+	0xe1351b80, 0xe0f771b7, 0xe2b1cfee, 0xe373a5d9,
+	0xe63cb35c, 0xe7fed96b, 0xe5b86732, 0xe47a0d05,
+	0xef264a38, 0xeee4200f, 0xeca29e56, 0xed60f461,
+	0xe82fe2e4, 0xe9ed88d3, 0xebab368a, 0xea695cbd,
+	0xfd13b8f0, 0xfcd1d2c7, 0xfe976c9e, 0xff5506a9,
+	0xfa1a102c, 0xfbd87a1b, 0xf99ec442, 0xf85cae75,
+	0xf300e948, 0xf2c2837f, 0xf0843d26, 0xf1465711,
+	0xf4094194, 0xf5cb2ba3, 0xf78d95fa, 0xf64fffcd,
+	0xd9785d60, 0xd8ba3757, 0xdafc890e, 0xdb3ee339,
+	0xde71f5bc, 0xdfb39f8b, 0xddf521d2, 0xdc374be5,
+	0xd76b0cd8, 0xd6a966ef, 0xd4efd8b6, 0xd52db281,
+	0xd062a404, 0xd1a0ce33, 0xd3e6706a, 0xd2241a5d,
+	0xc55efe10, 0xc49c9427, 0xc6da2a7e, 0xc7184049,
+	0xc25756cc, 0xc3953cfb, 0xc1d382a2, 0xc011e895,
+	0xcb4dafa8, 0xca8fc59f, 0xc8c97bc6, 0xc90b11f1,
+	0xcc440774, 0xcd866d43, 0xcfc0d31a, 0xce02b92d,
+	0x91af9640, 0x906dfc77, 0x922b422e, 0x93e92819,
+	0x96a63e9c, 0x976454ab, 0x9522eaf2, 0x94e080c5,
+	0x9fbcc7f8, 0x9e7eadcf, 0x9c381396, 0x9dfa79a1,
+	0x98b56f24, 0x99770513, 0x9b31bb4a, 0x9af3d17d,
+	0x8d893530, 0x8c4b5f07, 0x8e0de15e, 0x8fcf8b69,
+	0x8a809dec, 0x8b42f7db, 0x89044982, 0x88c623b5,
+	0x839a6488, 0x82580ebf, 0x801eb0e6, 0x81dcdad1,
+	0x8493cc54, 0x8551a663, 0x8717183a, 0x86d5720d,
+	0xa9e2d0a0, 0xa820ba97, 0xaa6604ce, 0xaba46ef9,
+	0xaeeb787c, 0xaf29124b, 0xad6fac12, 0xacadc625,
+	0xa7f18118, 0xa633eb2f, 0xa4755576, 0xa5b73f41,
+	0xa0f829c4, 0xa13a43f3, 0xa37cfdaa, 0xa2be979d,
+	0xb5c473d0, 0xb40619e7, 0xb640a7be, 0xb782cd89,
+	0xb2cddb0c, 0xb30fb13b, 0xb1490f62, 0xb08b6555,
+	0xbbd72268, 0xba15485f, 0xb853f606, 0xb9919c31,
+	0xbcde8ab4, 0xbd1ce083, 0xbf5a5eda, 0xbe9834ed,
+	0x00000000, 0xb8bc6765, 0xaa09c88b, 0x12b5afee,
+	0x8f629757, 0x37def032, 0x256b5fdc, 0x9dd738b9,
+	0xc5b428ef, 0x7d084f8a, 0x6fbde064, 0xd7018701,
+	0x4ad6bfb8, 0xf26ad8dd, 0xe0df7733, 0x58631056,
+	0x5019579f, 0xe8a530fa, 0xfa109f14, 0x42acf871,
+	0xdf7bc0c8, 0x67c7a7ad, 0x75720843, 0xcdce6f26,
+	0x95ad7f70, 0x2d111815, 0x3fa4b7fb, 0x8718d09e,
+	0x1acfe827, 0xa2738f42, 0xb0c620ac, 0x087a47c9,
+	0xa032af3e, 0x188ec85b, 0x0a3b67b5, 0xb28700d0,
+	0x2f503869, 0x97ec5f0c, 0x8559f0e2, 0x3de59787,
+	0x658687d1, 0xdd3ae0b4, 0xcf8f4f5a, 0x7733283f,
+	0xeae41086, 0x525877e3, 0x40edd80d, 0xf851bf68,
+	0xf02bf8a1, 0x48979fc4, 0x5a22302a, 0xe29e574f,
+	0x7f496ff6, 0xc7f50893, 0xd540a77d, 0x6dfcc018,
+	0x359fd04e, 0x8d23b72b, 0x9f9618c5, 0x272a7fa0,
+	0xbafd4719, 0x0241207c, 0x10f48f92, 0xa848e8f7,
+	0x9b14583d, 0x23a83f58, 0x311d90b6, 0x89a1f7d3,
+	0x1476cf6a, 0xaccaa80f, 0xbe7f07e1, 0x06c36084,
+	0x5ea070d2, 0xe61c17b7, 0xf4a9b859, 0x4c15df3c,
+	0xd1c2e785, 0x697e80e0, 0x7bcb2f0e, 0xc377486b,
+	0xcb0d0fa2, 0x73b168c7, 0x6104c729, 0xd9b8a04c,
+	0x446f98f5, 0xfcd3ff90, 0xee66507e, 0x56da371b,
+	0x0eb9274d, 0xb6054028, 0xa4b0efc6, 0x1c0c88a3,
+	0x81dbb01a, 0x3967d77f, 0x2bd27891, 0x936e1ff4,
+	0x3b26f703, 0x839a9066, 0x912f3f88, 0x299358ed,
+	0xb4446054, 0x0cf80731, 0x1e4da8df, 0xa6f1cfba,
+	0xfe92dfec, 0x462eb889, 0x549b1767, 0xec277002,
+	0x71f048bb, 0xc94c2fde, 0xdbf98030, 0x6345e755,
+	0x6b3fa09c, 0xd383c7f9, 0xc1366817, 0x798a0f72,
+	0xe45d37cb, 0x5ce150ae, 0x4e54ff40, 0xf6e89825,
+	0xae8b8873, 0x1637ef16, 0x048240f8, 0xbc3e279d,
+	0x21e91f24, 0x99557841, 0x8be0d7af, 0x335cb0ca,
+	0xed59b63b, 0x55e5d15e, 0x47507eb0, 0xffec19d5,
+	0x623b216c, 0xda874609, 0xc832e9e7, 0x708e8e82,
+	0x28ed9ed4, 0x9051f9b1, 0x82e4565f, 0x3a58313a,
+	0xa78f0983, 0x1f336ee6, 0x0d86c108, 0xb53aa66d,
+	0xbd40e1a4, 0x05fc86c1, 0x1749292f, 0xaff54e4a,
+	0x322276f3, 0x8a9e1196, 0x982bbe78, 0x2097d91d,
+	0x78f4c94b, 0xc048ae2e, 0xd2fd01c0, 0x6a4166a5,
+	0xf7965e1c, 0x4f2a3979, 0x5d9f9697, 0xe523f1f2,
+	0x4d6b1905, 0xf5d77e60, 0xe762d18e, 0x5fdeb6eb,
+	0xc2098e52, 0x7ab5e937, 0x680046d9, 0xd0bc21bc,
+	0x88df31ea, 0x3063568f, 0x22d6f961, 0x9a6a9e04,
+	0x07bda6bd, 0xbf01c1d8, 0xadb46e36, 0x15080953,
+	0x1d724e9a, 0xa5ce29ff, 0xb77b8611, 0x0fc7e174,
+	0x9210d9cd, 0x2aacbea8, 0x38191146, 0x80a57623,
+	0xd8c66675, 0x607a0110, 0x72cfaefe, 0xca73c99b,
+	0x57a4f122, 0xef189647, 0xfdad39a9, 0x45115ecc,
+	0x764dee06, 0xcef18963, 0xdc44268d, 0x64f841e8,
+	0xf92f7951, 0x41931e34, 0x5326b1da, 0xeb9ad6bf,
+	0xb3f9c6e9, 0x0b45a18c, 0x19f00e62, 0xa14c6907,
+	0x3c9b51be, 0x842736db, 0x96929935, 0x2e2efe50,
+	0x2654b999, 0x9ee8defc, 0x8c5d7112, 0x34e11677,
+	0xa9362ece, 0x118a49ab, 0x033fe645, 0xbb838120,
+	0xe3e09176, 0x5b5cf613, 0x49e959fd, 0xf1553e98,
+	0x6c820621, 0xd43e6144, 0xc68bceaa, 0x7e37a9cf,
+	0xd67f4138, 0x6ec3265d, 0x7c7689b3, 0xc4caeed6,
+	0x591dd66f, 0xe1a1b10a, 0xf3141ee4, 0x4ba87981,
+	0x13cb69d7, 0xab770eb2, 0xb9c2a15c, 0x017ec639,
+	0x9ca9fe80, 0x241599e5, 0x36a0360b, 0x8e1c516e,
+	0x866616a7, 0x3eda71c2, 0x2c6fde2c, 0x94d3b949,
+	0x090481f0, 0xb1b8e695, 0xa30d497b, 0x1bb12e1e,
+	0x43d23e48, 0xfb6e592d, 0xe9dbf6c3, 0x516791a6,
+	0xccb0a91f, 0x740cce7a, 0x66b96194, 0xde0506f1,
+#endif /* CRC32_SLICE4 || CRC32_SLICE8 */
+#if defined(CRC32_SLICE8)
+	0x00000000, 0x3d6029b0, 0x7ac05360, 0x47a07ad0,
+	0xf580a6c0, 0xc8e08f70, 0x8f40f5a0, 0xb220dc10,
+	0x30704bc1, 0x0d106271, 0x4ab018a1, 0x77d03111,
+	0xc5f0ed01, 0xf890c4b1, 0xbf30be61, 0x825097d1,
+	0x60e09782, 0x5d80be32, 0x1a20c4e2, 0x2740ed52,
+	0x95603142, 0xa80018f2, 0xefa06222, 0xd2c04b92,
+	0x5090dc43, 0x6df0f5f3, 0x2a508f23, 0x1730a693,
+	0xa5107a83, 0x98705333, 0xdfd029e3, 0xe2b00053,
+	0xc1c12f04, 0xfca106b4, 0xbb017c64, 0x866155d4,
+	0x344189c4, 0x0921a074, 0x4e81daa4, 0x73e1f314,
+	0xf1b164c5, 0xccd14d75, 0x8b7137a5, 0xb6111e15,
+	0x0431c205, 0x3951ebb5, 0x7ef19165, 0x4391b8d5,
+	0xa121b886, 0x9c419136, 0xdbe1ebe6, 0xe681c256,
+	0x54a11e46, 0x69c137f6, 0x2e614d26, 0x13016496,
+	0x9151f347, 0xac31daf7, 0xeb91a027, 0xd6f18997,
+	0x64d15587, 0x59b17c37, 0x1e1106e7, 0x23712f57,
+	0x58f35849, 0x659371f9, 0x22330b29, 0x1f532299,
+	0xad73fe89, 0x9013d739, 0xd7b3ade9, 0xead38459,
+	0x68831388, 0x55e33a38, 0x124340e8, 0x2f236958,
+	0x9d03b548, 0xa0639cf8, 0xe7c3e628, 0xdaa3cf98,
+	0x3813cfcb, 0x0573e67b, 0x42d39cab, 0x7fb3b51b,
+	0xcd93690b, 0xf0f340bb, 0xb7533a6b, 0x8a3313db,
+	0x0863840a, 0x3503adba, 0x72a3d76a, 0x4fc3feda,
+	0xfde322ca, 0xc0830b7a, 0x872371aa, 0xba43581a,
+	0x9932774d, 0xa4525efd, 0xe3f2242d, 0xde920d9d,
+	0x6cb2d18d, 0x51d2f83d, 0x167282ed, 0x2b12ab5d,
+	0xa9423c8c, 0x9422153c, 0xd3826fec, 0xeee2465c,
+	0x5cc29a4c, 0x61a2b3fc, 0x2602c92c, 0x1b62e09c,
+	0xf9d2e0cf, 0xc4b2c97f, 0x8312b3af, 0xbe729a1f,
+	0x0c52460f, 0x31326fbf, 0x7692156f, 0x4bf23cdf,
+	0xc9a2ab0e, 0xf4c282be, 0xb362f86e, 0x8e02d1de,
+	0x3c220dce, 0x0142247e, 0x46e25eae, 0x7b82771e,
+	0xb1e6b092, 0x8c869922, 0xcb26e3f2, 0xf646ca42,
+	0x44661652, 0x79063fe2, 0x3ea64532, 0x03c66c82,
+	0x8196fb53, 0xbcf6d2e3, 0xfb56a833, 0xc6368183,
+	0x74165d93, 0x49767423, 0x0ed60ef3, 0x33b62743,
+	0xd1062710, 0xec660ea0, 0xabc67470, 0x96a65dc0,
+	0x248681d0, 0x19e6a860, 0x5e46d2b0, 0x6326fb00,
+	0xe1766cd1, 0xdc164561, 0x9bb63fb1, 0xa6d61601,
+	0x14f6ca11, 0x2996e3a1, 0x6e369971, 0x5356b0c1,
+	0x70279f96, 0x4d47b626, 0x0ae7ccf6, 0x3787e546,
+	0x85a73956, 0xb8c710e6, 0xff676a36, 0xc2074386,
+	0x4057d457, 0x7d37fde7, 0x3a978737, 0x07f7ae87,
+	0xb5d77297, 0x88b75b27, 0xcf1721f7, 0xf2770847,
+	0x10c70814, 0x2da721a4, 0x6a075b74, 0x576772c4,
+	0xe547aed4, 0xd8278764, 0x9f87fdb4, 0xa2e7d404,
+	0x20b743d5, 0x1dd76a65, 0x5a7710b5, 0x67173905,
+	0xd537e515, 0xe857cca5, 0xaff7b675, 0x92979fc5,
+	0xe915e8db, 0xd475c16b, 0x93d5bbbb, 0xaeb5920b,
+	0x1c954e1b, 0x21f567ab, 0x66551d7b, 0x5b3534cb,
+	0xd965a31a, 0xe4058aaa, 0xa3a5f07a, 0x9ec5d9ca,
+	0x2ce505da, 0x11852c6a, 0x562556ba, 0x6b457f0a,
+	0x89f57f59, 0xb49556e9, 0xf3352c39, 0xce550589,
+	0x7c75d999, 0x4115f029, 0x06b58af9, 0x3bd5a349,
+	0xb9853498, 0x84e51d28, 0xc34567f8, 0xfe254e48,
+	0x4c059258, 0x7165bbe8, 0x36c5c138, 0x0ba5e888,
+	0x28d4c7df, 0x15b4ee6f, 0x521494bf, 0x6f74bd0f,
+	0xdd54611f, 0xe03448af, 0xa794327f, 0x9af41bcf,
+	0x18a48c1e, 0x25c4a5ae, 0x6264df7e, 0x5f04f6ce,
+	0xed242ade, 0xd044036e, 0x97e479be, 0xaa84500e,
+	0x4834505d, 0x755479ed, 0x32f4033d, 0x0f942a8d,
+	0xbdb4f69d, 0x80d4df2d, 0xc774a5fd, 0xfa148c4d,
+	0x78441b9c, 0x4524322c, 0x028448fc, 0x3fe4614c,
+	0x8dc4bd5c, 0xb0a494ec, 0xf704ee3c, 0xca64c78c,
+	0x00000000, 0xcb5cd3a5, 0x4dc8a10b, 0x869472ae,
+	0x9b914216, 0x50cd91b3, 0xd659e31d, 0x1d0530b8,
+	0xec53826d, 0x270f51c8, 0xa19b2366, 0x6ac7f0c3,
+	0x77c2c07b, 0xbc9e13de, 0x3a0a6170, 0xf156b2d5,
+	0x03d6029b, 0xc88ad13e, 0x4e1ea390, 0x85427035,
+	0x9847408d, 0x531b9328, 0xd58fe186, 0x1ed33223,
+	0xef8580f6, 0x24d95353, 0xa24d21fd, 0x6911f258,
+	0x7414c2e0, 0xbf481145, 0x39dc63eb, 0xf280b04e,
+	0x07ac0536, 0xccf0d693, 0x4a64a43d, 0x81387798,
+	0x9c3d4720, 0x57619485, 0xd1f5e62b, 0x1aa9358e,
+	0xebff875b, 0x20a354fe, 0xa6372650, 0x6d6bf5f5,
+	0x706ec54d, 0xbb3216e8, 0x3da66446, 0xf6fab7e3,
+	0x047a07ad, 0xcf26d408, 0x49b2a6a6, 0x82ee7503,
+	0x9feb45bb, 0x54b7961e, 0xd223e4b0, 0x197f3715,
+	0xe82985c0, 0x23755665, 0xa5e124cb, 0x6ebdf76e,
+	0x73b8c7d6, 0xb8e41473, 0x3e7066dd, 0xf52cb578,
+	0x0f580a6c, 0xc404d9c9, 0x4290ab67, 0x89cc78c2,
+	0x94c9487a, 0x5f959bdf, 0xd901e971, 0x125d3ad4,
+	0xe30b8801, 0x28575ba4, 0xaec3290a, 0x659ffaaf,
+	0x789aca17, 0xb3c619b2, 0x35526b1c, 0xfe0eb8b9,
+	0x0c8e08f7, 0xc7d2db52, 0x4146a9fc, 0x8a1a7a59,
+	0x971f4ae1, 0x5c439944, 0xdad7ebea, 0x118b384f,
+	0xe0dd8a9a, 0x2b81593f, 0xad152b91, 0x6649f834,
+	0x7b4cc88c, 0xb0101b29, 0x36846987, 0xfdd8ba22,
+	0x08f40f5a, 0xc3a8dcff, 0x453cae51, 0x8e607df4,
+	0x93654d4c, 0x58399ee9, 0xdeadec47, 0x15f13fe2,
+	0xe4a78d37, 0x2ffb5e92, 0xa96f2c3c, 0x6233ff99,
+	0x7f36cf21, 0xb46a1c84, 0x32fe6e2a, 0xf9a2bd8f,
+	0x0b220dc1, 0xc07ede64, 0x46eaacca, 0x8db67f6f,
+	0x90b34fd7, 0x5bef9c72, 0xdd7beedc, 0x16273d79,
+	0xe7718fac, 0x2c2d5c09, 0xaab92ea7, 0x61e5fd02,
+	0x7ce0cdba, 0xb7bc1e1f, 0x31286cb1, 0xfa74bf14,
+	0x1eb014d8, 0xd5ecc77d, 0x5378b5d3, 0x98246676,
+	0x852156ce, 0x4e7d856b, 0xc8e9f7c5, 0x03b52460,
+	0xf2e396b5, 0x39bf4510, 0xbf2b37be, 0x7477e41b,
+	0x6972d4a3, 0xa22e0706, 0x24ba75a8, 0xefe6a60d,
+	0x1d661643, 0xd63ac5e6, 0x50aeb748, 0x9bf264ed,
+	0x86f75455, 0x4dab87f0, 0xcb3ff55e, 0x006326fb,
+	0xf135942e, 0x3a69478b, 0xbcfd3525, 0x77a1e680,
+	0x6aa4d638, 0xa1f8059d, 0x276c7733, 0xec30a496,
+	0x191c11ee, 0xd240c24b, 0x54d4b0e5, 0x9f886340,
+	0x828d53f8, 0x49d1805d, 0xcf45f2f3, 0x04192156,
+	0xf54f9383, 0x3e134026, 0xb8873288, 0x73dbe12d,
+	0x6eded195, 0xa5820230, 0x2316709e, 0xe84aa33b,
+	0x1aca1375, 0xd196c0d0, 0x5702b27e, 0x9c5e61db,
+	0x815b5163, 0x4a0782c6, 0xcc93f068, 0x07cf23cd,
+	0xf6999118, 0x3dc542bd, 0xbb513013, 0x700de3b6,
+	0x6d08d30e, 0xa65400ab, 0x20c07205, 0xeb9ca1a0,
+	0x11e81eb4, 0xdab4cd11, 0x5c20bfbf, 0x977c6c1a,
+	0x8a795ca2, 0x41258f07, 0xc7b1fda9, 0x0ced2e0c,
+	0xfdbb9cd9, 0x36e74f7c, 0xb0733dd2, 0x7b2fee77,
+	0x662adecf, 0xad760d6a, 0x2be27fc4, 0xe0beac61,
+	0x123e1c2f, 0xd962cf8a, 0x5ff6bd24, 0x94aa6e81,
+	0x89af5e39, 0x42f38d9c, 0xc467ff32, 0x0f3b2c97,
+	0xfe6d9e42, 0x35314de7, 0xb3a53f49, 0x78f9ecec,
+	0x65fcdc54, 0xaea00ff1, 0x28347d5f, 0xe368aefa,
+	0x16441b82, 0xdd18c827, 0x5b8cba89, 0x90d0692c,
+	0x8dd55994, 0x46898a31, 0xc01df89f, 0x0b412b3a,
+	0xfa1799ef, 0x314b4a4a, 0xb7df38e4, 0x7c83eb41,
+	0x6186dbf9, 0xaada085c, 0x2c4e7af2, 0xe712a957,
+	0x15921919, 0xdececabc, 0x585ab812, 0x93066bb7,
+	0x8e035b0f, 0x455f88aa, 0xc3cbfa04, 0x089729a1,
+	0xf9c19b74, 0x329d48d1, 0xb4093a7f, 0x7f55e9da,
+	0x6250d962, 0xa90c0ac7, 0x2f987869, 0xe4c4abcc,
+	0x00000000, 0xa6770bb4, 0x979f1129, 0x31e81a9d,
+	0xf44f2413, 0x52382fa7, 0x63d0353a, 0xc5a73e8e,
+	0x33ef4e67, 0x959845d3, 0xa4705f4e, 0x020754fa,
+	0xc7a06a74, 0x61d761c0, 0x503f7b5d, 0xf64870e9,
+	0x67de9cce, 0xc1a9977a, 0xf0418de7, 0x56368653,
+	0x9391b8dd, 0x35e6b369, 0x040ea9f4, 0xa279a240,
+	0x5431d2a9, 0xf246d91d, 0xc3aec380, 0x65d9c834,
+	0xa07ef6ba, 0x0609fd0e, 0x37e1e793, 0x9196ec27,
+	0xcfbd399c, 0x69ca3228, 0x582228b5, 0xfe552301,
+	0x3bf21d8f, 0x9d85163b, 0xac6d0ca6, 0x0a1a0712,
+	0xfc5277fb, 0x5a257c4f, 0x6bcd66d2, 0xcdba6d66,
+	0x081d53e8, 0xae6a585c, 0x9f8242c1, 0x39f54975,
+	0xa863a552, 0x0e14aee6, 0x3ffcb47b, 0x998bbfcf,
+	0x5c2c8141, 0xfa5b8af5, 0xcbb39068, 0x6dc49bdc,
+	0x9b8ceb35, 0x3dfbe081, 0x0c13fa1c, 0xaa64f1a8,
+	0x6fc3cf26, 0xc9b4c492, 0xf85cde0f, 0x5e2bd5bb,
+	0x440b7579, 0xe27c7ecd, 0xd3946450, 0x75e36fe4,
+	0xb044516a, 0x16335ade, 0x27db4043, 0x81ac4bf7,
+	0x77e43b1e, 0xd19330aa, 0xe07b2a37, 0x460c2183,
+	0x83ab1f0d, 0x25dc14b9, 0x14340e24, 0xb2430590,
+	0x23d5e9b7, 0x85a2e203, 0xb44af89e, 0x123df32a,
+	0xd79acda4, 0x71edc610, 0x4005dc8d, 0xe672d739,
+	0x103aa7d0, 0xb64dac64, 0x87a5b6f9, 0x21d2bd4d,
+	0xe47583c3, 0x42028877, 0x73ea92ea, 0xd59d995e,
+	0x8bb64ce5, 0x2dc14751, 0x1c295dcc, 0xba5e5678,
+	0x7ff968f6, 0xd98e6342, 0xe86679df, 0x4e11726b,
+	0xb8590282, 0x1e2e0936, 0x2fc613ab, 0x89b1181f,
+	0x4c162691, 0xea612d25, 0xdb8937b8, 0x7dfe3c0c,
+	0xec68d02b, 0x4a1fdb9f, 0x7bf7c102, 0xdd80cab6,
+	0x1827f438, 0xbe50ff8c, 0x8fb8e511, 0x29cfeea5,
+	0xdf879e4c, 0x79f095f8, 0x48188f65, 0xee6f84d1,
+	0x2bc8ba5f, 0x8dbfb1eb, 0xbc57ab76, 0x1a20a0c2,
+	0x8816eaf2, 0x2e61e146, 0x1f89fbdb, 0xb9fef06f,
+	0x7c59cee1, 0xda2ec555, 0xebc6dfc8, 0x4db1d47c,
+	0xbbf9a495, 0x1d8eaf21, 0x2c66b5bc, 0x8a11be08,
+	0x4fb68086, 0xe9c18b32, 0xd82991af, 0x7e5e9a1b,
+	0xefc8763c, 0x49bf7d88, 0x78576715, 0xde206ca1,
+	0x1b87522f, 0xbdf0599b, 0x8c184306, 0x2a6f48b2,
+	0xdc27385b, 0x7a5033ef, 0x4bb82972, 0xedcf22c6,
+	0x28681c48, 0x8e1f17fc, 0xbff70d61, 0x198006d5,
+	0x47abd36e, 0xe1dcd8da, 0xd034c247, 0x7643c9f3,
+	0xb3e4f77d, 0x1593fcc9, 0x247be654, 0x820cede0,
+	0x74449d09, 0xd23396bd, 0xe3db8c20, 0x45ac8794,
+	0x800bb91a, 0x267cb2ae, 0x1794a833, 0xb1e3a387,
+	0x20754fa0, 0x86024414, 0xb7ea5e89, 0x119d553d,
+	0xd43a6bb3, 0x724d6007, 0x43a57a9a, 0xe5d2712e,
+	0x139a01c7, 0xb5ed0a73, 0x840510ee, 0x22721b5a,
+	0xe7d525d4, 0x41a22e60, 0x704a34fd, 0xd63d3f49,
+	0xcc1d9f8b, 0x6a6a943f, 0x5b828ea2, 0xfdf58516,
+	0x3852bb98, 0x9e25b02c, 0xafcdaab1, 0x09baa105,
+	0xfff2d1ec, 0x5985da58, 0x686dc0c5, 0xce1acb71,
+	0x0bbdf5ff, 0xadcafe4b, 0x9c22e4d6, 0x3a55ef62,
+	0xabc30345, 0x0db408f1, 0x3c5c126c, 0x9a2b19d8,
+	0x5f8c2756, 0xf9fb2ce2, 0xc813367f, 0x6e643dcb,
+	0x982c4d22, 0x3e5b4696, 0x0fb35c0b, 0xa9c457bf,
+	0x6c636931, 0xca146285, 0xfbfc7818, 0x5d8b73ac,
+	0x03a0a617, 0xa5d7ada3, 0x943fb73e, 0x3248bc8a,
+	0xf7ef8204, 0x519889b0, 0x6070932d, 0xc6079899,
+	0x304fe870, 0x9638e3c4, 0xa7d0f959, 0x01a7f2ed,
+	0xc400cc63, 0x6277c7d7, 0x539fdd4a, 0xf5e8d6fe,
+	0x647e3ad9, 0xc209316d, 0xf3e12bf0, 0x55962044,
+	0x90311eca, 0x3646157e, 0x07ae0fe3, 0xa1d90457,
+	0x579174be, 0xf1e67f0a, 0xc00e6597, 0x66796e23,
+	0xa3de50ad, 0x05a95b19, 0x34414184, 0x92364a30,
+	0x00000000, 0xccaa009e, 0x4225077d, 0x8e8f07e3,
+	0x844a0efa, 0x48e00e64, 0xc66f0987, 0x0ac50919,
+	0xd3e51bb5, 0x1f4f1b2b, 0x91c01cc8, 0x5d6a1c56,
+	0x57af154f, 0x9b0515d1, 0x158a1232, 0xd92012ac,
+	0x7cbb312b, 0xb01131b5, 0x3e9e3656, 0xf23436c8,
+	0xf8f13fd1, 0x345b3f4f, 0xbad438ac, 0x767e3832,
+	0xaf5e2a9e, 0x63f42a00, 0xed7b2de3, 0x21d12d7d,
+	0x2b142464, 0xe7be24fa, 0x69312319, 0xa59b2387,
+	0xf9766256, 0x35dc62c8, 0xbb53652b, 0x77f965b5,
+	0x7d3c6cac, 0xb1966c32, 0x3f196bd1, 0xf3b36b4f,
+	0x2a9379e3, 0xe639797d, 0x68b67e9e, 0xa41c7e00,
+	0xaed97719, 0x62737787, 0xecfc7064, 0x205670fa,
+	0x85cd537d, 0x496753e3, 0xc7e85400, 0x0b42549e,
+	0x01875d87, 0xcd2d5d19, 0x43a25afa, 0x8f085a64,
+	0x562848c8, 0x9a824856, 0x140d4fb5, 0xd8a74f2b,
+	0xd2624632, 0x1ec846ac, 0x9047414f, 0x5ced41d1,
+	0x299dc2ed, 0xe537c273, 0x6bb8c590, 0xa712c50e,
+	0xadd7cc17, 0x617dcc89, 0xeff2cb6a, 0x2358cbf4,
+	0xfa78d958, 0x36d2d9c6, 0xb85dde25, 0x74f7debb,
+	0x7e32d7a2, 0xb298d73c, 0x3c17d0df, 0xf0bdd041,
+	0x5526f3c6, 0x998cf358, 0x1703f4bb, 0xdba9f425,
+	0xd16cfd3c, 0x1dc6fda2, 0x9349fa41, 0x5fe3fadf,
+	0x86c3e873, 0x4a69e8ed, 0xc4e6ef0e, 0x084cef90,
+	0x0289e689, 0xce23e617, 0x40ace1f4, 0x8c06e16a,
+	0xd0eba0bb, 0x1c41a025, 0x92cea7c6, 0x5e64a758,
+	0x54a1ae41, 0x980baedf, 0x1684a93c, 0xda2ea9a2,
+	0x030ebb0e, 0xcfa4bb90, 0x412bbc73, 0x8d81bced,
+	0x8744b5f4, 0x4beeb56a, 0xc561b289, 0x09cbb217,
+	0xac509190, 0x60fa910e, 0xee7596ed, 0x22df9673,
+	0x281a9f6a, 0xe4b09ff4, 0x6a3f9817, 0xa6959889,
+	0x7fb58a25, 0xb31f8abb, 0x3d908d58, 0xf13a8dc6,
+	0xfbff84df, 0x37558441, 0xb9da83a2, 0x7570833c,
+	0x533b85da, 0x9f918544, 0x111e82a7, 0xddb48239,
+	0xd7718b20, 0x1bdb8bbe, 0x95548c5d, 0x59fe8cc3,
+	0x80de9e6f, 0x4c749ef1, 0xc2fb9912, 0x0e51998c,
+	0x04949095, 0xc83e900b, 0x46b197e8, 0x8a1b9776,
+	0x2f80b4f1, 0xe32ab46f, 0x6da5b38c, 0xa10fb312,
+	0xabcaba0b, 0x6760ba95, 0xe9efbd76, 0x2545bde8,
+	0xfc65af44, 0x30cfafda, 0xbe40a839, 0x72eaa8a7,
+	0x782fa1be, 0xb485a120, 0x3a0aa6c3, 0xf6a0a65d,
+	0xaa4de78c, 0x66e7e712, 0xe868e0f1, 0x24c2e06f,
+	0x2e07e976, 0xe2ade9e8, 0x6c22ee0b, 0xa088ee95,
+	0x79a8fc39, 0xb502fca7, 0x3b8dfb44, 0xf727fbda,
+	0xfde2f2c3, 0x3148f25d, 0xbfc7f5be, 0x736df520,
+	0xd6f6d6a7, 0x1a5cd639, 0x94d3d1da, 0x5879d144,
+	0x52bcd85d, 0x9e16d8c3, 0x1099df20, 0xdc33dfbe,
+	0x0513cd12, 0xc9b9cd8c, 0x4736ca6f, 0x8b9ccaf1,
+	0x8159c3e8, 0x4df3c376, 0xc37cc495, 0x0fd6c40b,
+	0x7aa64737, 0xb60c47a9, 0x3883404a, 0xf42940d4,
+	0xfeec49cd, 0x32464953, 0xbcc94eb0, 0x70634e2e,
+	0xa9435c82, 0x65e95c1c, 0xeb665bff, 0x27cc5b61,
+	0x2d095278, 0xe1a352e6, 0x6f2c5505, 0xa386559b,
+	0x061d761c, 0xcab77682, 0x44387161, 0x889271ff,
+	0x825778e6, 0x4efd7878, 0xc0727f9b, 0x0cd87f05,
+	0xd5f86da9, 0x19526d37, 0x97dd6ad4, 0x5b776a4a,
+	0x51b26353, 0x9d1863cd, 0x1397642e, 0xdf3d64b0,
+	0x83d02561, 0x4f7a25ff, 0xc1f5221c, 0x0d5f2282,
+	0x079a2b9b, 0xcb302b05, 0x45bf2ce6, 0x89152c78,
+	0x50353ed4, 0x9c9f3e4a, 0x121039a9, 0xdeba3937,
+	0xd47f302e, 0x18d530b0, 0x965a3753, 0x5af037cd,
+	0xff6b144a, 0x33c114d4, 0xbd4e1337, 0x71e413a9,
+	0x7b211ab0, 0xb78b1a2e, 0x39041dcd, 0xf5ae1d53,
+	0x2c8e0fff, 0xe0240f61, 0x6eab0882, 0xa201081c,
+	0xa8c40105, 0x646e019b, 0xeae10678, 0x264b06e6,
+#endif /* CRC32_SLICE8 */
+};

ADDED   3rd_party/libdeflate/lib/crc32_vec_template.h
Index: 3rd_party/libdeflate/lib/crc32_vec_template.h
==================================================================
--- 3rd_party/libdeflate/lib/crc32_vec_template.h
+++ 3rd_party/libdeflate/lib/crc32_vec_template.h
@@ -0,0 +1,61 @@
+/*
+ * crc32_vec_template.h - template for vectorized CRC-32 implementations
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#define CRC32_SLICE1	1
+static u32 crc32_slice1(u32, const u8 *, size_t);
+
+/*
+ * Template for vectorized CRC-32 implementations.
+ *
+ * Note: on unaligned ends of the buffer, we fall back to crc32_slice1() instead
+ * of crc32_slice8() because only a few bytes need to be processed, so a smaller
+ * table is preferable.
+ */
+static u32 ATTRIBUTES
+FUNCNAME(u32 remainder, const u8 *p, size_t size)
+{
+	if ((uintptr_t)p % IMPL_ALIGNMENT) {
+		size_t n = MIN(size, -(uintptr_t)p % IMPL_ALIGNMENT);
+
+		remainder = crc32_slice1(remainder, p, n);
+		p += n;
+		size -= n;
+	}
+	if (size >= IMPL_SEGMENT_SIZE) {
+		remainder = FUNCNAME_ALIGNED(remainder, (const void *)p,
+					     size / IMPL_SEGMENT_SIZE);
+		p += size - (size % IMPL_SEGMENT_SIZE);
+		size %= IMPL_SEGMENT_SIZE;
+	}
+	return crc32_slice1(remainder, p, size);
+}
+
+#undef FUNCNAME
+#undef FUNCNAME_ALIGNED
+#undef ATTRIBUTES
+#undef IMPL_ALIGNMENT
+#undef IMPL_SEGMENT_SIZE

ADDED   3rd_party/libdeflate/lib/decompress_template.h
Index: 3rd_party/libdeflate/lib/decompress_template.h
==================================================================
--- 3rd_party/libdeflate/lib/decompress_template.h
+++ 3rd_party/libdeflate/lib/decompress_template.h
@@ -0,0 +1,421 @@
+/*
+ * decompress_template.h
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+/*
+ * This is the actual DEFLATE decompression routine, lifted out of
+ * deflate_decompress.c so that it can be compiled multiple times with different
+ * target instruction sets.
+ */
+
+static enum libdeflate_result ATTRIBUTES
+FUNCNAME(struct libdeflate_decompressor * restrict d,
+	 const void * restrict in, size_t in_nbytes,
+	 void * restrict out, size_t out_nbytes_avail,
+	 size_t *actual_in_nbytes_ret, size_t *actual_out_nbytes_ret)
+{
+	u8 *out_next = out;
+	u8 * const out_end = out_next + out_nbytes_avail;
+	const u8 *in_next = in;
+	const u8 * const in_end = in_next + in_nbytes;
+	bitbuf_t bitbuf = 0;
+	unsigned bitsleft = 0;
+	size_t overrun_count = 0;
+	unsigned i;
+	unsigned is_final_block;
+	unsigned block_type;
+	u16 len;
+	u16 nlen;
+	unsigned num_litlen_syms;
+	unsigned num_offset_syms;
+	u16 tmp16;
+	u32 tmp32;
+
+next_block:
+	/* Starting to read the next block.  */
+	;
+
+	STATIC_ASSERT(CAN_ENSURE(1 + 2 + 5 + 5 + 4));
+	ENSURE_BITS(1 + 2 + 5 + 5 + 4);
+
+	/* BFINAL: 1 bit  */
+	is_final_block = POP_BITS(1);
+
+	/* BTYPE: 2 bits  */
+	block_type = POP_BITS(2);
+
+	if (block_type == DEFLATE_BLOCKTYPE_DYNAMIC_HUFFMAN) {
+
+		/* Dynamic Huffman block.  */
+
+		/* The order in which precode lengths are stored.  */
+		static const u8 deflate_precode_lens_permutation[DEFLATE_NUM_PRECODE_SYMS] = {
+			16, 17, 18, 0, 8, 7, 9, 6, 10, 5, 11, 4, 12, 3, 13, 2, 14, 1, 15
+		};
+
+		unsigned num_explicit_precode_lens;
+
+		/* Read the codeword length counts.  */
+
+		STATIC_ASSERT(DEFLATE_NUM_LITLEN_SYMS == ((1 << 5) - 1) + 257);
+		num_litlen_syms = POP_BITS(5) + 257;
+
+		STATIC_ASSERT(DEFLATE_NUM_OFFSET_SYMS == ((1 << 5) - 1) + 1);
+		num_offset_syms = POP_BITS(5) + 1;
+
+		STATIC_ASSERT(DEFLATE_NUM_PRECODE_SYMS == ((1 << 4) - 1) + 4);
+		num_explicit_precode_lens = POP_BITS(4) + 4;
+
+		d->static_codes_loaded = false;
+
+		/* Read the precode codeword lengths.  */
+		STATIC_ASSERT(DEFLATE_MAX_PRE_CODEWORD_LEN == (1 << 3) - 1);
+		for (i = 0; i < num_explicit_precode_lens; i++) {
+			ENSURE_BITS(3);
+			d->u.precode_lens[deflate_precode_lens_permutation[i]] = POP_BITS(3);
+		}
+
+		for (; i < DEFLATE_NUM_PRECODE_SYMS; i++)
+			d->u.precode_lens[deflate_precode_lens_permutation[i]] = 0;
+
+		/* Build the decode table for the precode.  */
+		SAFETY_CHECK(build_precode_decode_table(d));
+
+		/* Expand the literal/length and offset codeword lengths.  */
+		for (i = 0; i < num_litlen_syms + num_offset_syms; ) {
+			u32 entry;
+			unsigned presym;
+			u8 rep_val;
+			unsigned rep_count;
+
+			ENSURE_BITS(DEFLATE_MAX_PRE_CODEWORD_LEN + 7);
+
+			/* (The code below assumes that the precode decode table
+			 * does not have any subtables.)  */
+			STATIC_ASSERT(PRECODE_TABLEBITS == DEFLATE_MAX_PRE_CODEWORD_LEN);
+
+			/* Read the next precode symbol.  */
+			entry = d->u.l.precode_decode_table[BITS(DEFLATE_MAX_PRE_CODEWORD_LEN)];
+			REMOVE_BITS(entry & HUFFDEC_LENGTH_MASK);
+			presym = entry >> HUFFDEC_RESULT_SHIFT;
+
+			if (presym < 16) {
+				/* Explicit codeword length  */
+				d->u.l.lens[i++] = presym;
+				continue;
+			}
+
+			/* Run-length encoded codeword lengths  */
+
+			/* Note: we don't need verify that the repeat count
+			 * doesn't overflow the number of elements, since we
+			 * have enough extra spaces to allow for the worst-case
+			 * overflow (138 zeroes when only 1 length was
+			 * remaining).
+			 *
+			 * In the case of the small repeat counts (presyms 16
+			 * and 17), it is fastest to always write the maximum
+			 * number of entries.  That gets rid of branches that
+			 * would otherwise be required.
+			 *
+			 * It is not just because of the numerical order that
+			 * our checks go in the order 'presym < 16', 'presym ==
+			 * 16', and 'presym == 17'.  For typical data this is
+			 * ordered from most frequent to least frequent case.
+			 */
+			STATIC_ASSERT(DEFLATE_MAX_LENS_OVERRUN == 138 - 1);
+
+			if (presym == 16) {
+				/* Repeat the previous length 3 - 6 times  */
+				SAFETY_CHECK(i != 0);
+				rep_val = d->u.l.lens[i - 1];
+				STATIC_ASSERT(3 + ((1 << 2) - 1) == 6);
+				rep_count = 3 + POP_BITS(2);
+				d->u.l.lens[i + 0] = rep_val;
+				d->u.l.lens[i + 1] = rep_val;
+				d->u.l.lens[i + 2] = rep_val;
+				d->u.l.lens[i + 3] = rep_val;
+				d->u.l.lens[i + 4] = rep_val;
+				d->u.l.lens[i + 5] = rep_val;
+				i += rep_count;
+			} else if (presym == 17) {
+				/* Repeat zero 3 - 10 times  */
+				STATIC_ASSERT(3 + ((1 << 3) - 1) == 10);
+				rep_count = 3 + POP_BITS(3);
+				d->u.l.lens[i + 0] = 0;
+				d->u.l.lens[i + 1] = 0;
+				d->u.l.lens[i + 2] = 0;
+				d->u.l.lens[i + 3] = 0;
+				d->u.l.lens[i + 4] = 0;
+				d->u.l.lens[i + 5] = 0;
+				d->u.l.lens[i + 6] = 0;
+				d->u.l.lens[i + 7] = 0;
+				d->u.l.lens[i + 8] = 0;
+				d->u.l.lens[i + 9] = 0;
+				i += rep_count;
+			} else {
+				/* Repeat zero 11 - 138 times  */
+				STATIC_ASSERT(11 + ((1 << 7) - 1) == 138);
+				rep_count = 11 + POP_BITS(7);
+				memset(&d->u.l.lens[i], 0,
+				       rep_count * sizeof(d->u.l.lens[i]));
+				i += rep_count;
+			}
+		}
+	} else if (block_type == DEFLATE_BLOCKTYPE_UNCOMPRESSED) {
+
+		/* Uncompressed block: copy 'len' bytes literally from the input
+		 * buffer to the output buffer.  */
+
+		ALIGN_INPUT();
+
+		SAFETY_CHECK(in_end - in_next >= 4);
+
+		len = READ_U16();
+		nlen = READ_U16();
+
+		SAFETY_CHECK(len == (u16)~nlen);
+		if (unlikely(len > out_end - out_next))
+			return LIBDEFLATE_INSUFFICIENT_SPACE;
+		SAFETY_CHECK(len <= in_end - in_next);
+
+		memcpy(out_next, in_next, len);
+		in_next += len;
+		out_next += len;
+
+		goto block_done;
+
+	} else {
+		SAFETY_CHECK(block_type == DEFLATE_BLOCKTYPE_STATIC_HUFFMAN);
+
+		/*
+		 * Static Huffman block: build the decode tables for the static
+		 * codes.  Skip doing so if the tables are already set up from
+		 * an earlier static block; this speeds up decompression of
+		 * degenerate input of many empty or very short static blocks.
+		 *
+		 * Afterwards, the remainder is the same as decompressing a
+		 * dynamic Huffman block.
+		 */
+
+		if (d->static_codes_loaded)
+			goto have_decode_tables;
+
+		d->static_codes_loaded = true;
+
+		STATIC_ASSERT(DEFLATE_NUM_LITLEN_SYMS == 288);
+		STATIC_ASSERT(DEFLATE_NUM_OFFSET_SYMS == 32);
+
+		for (i = 0; i < 144; i++)
+			d->u.l.lens[i] = 8;
+		for (; i < 256; i++)
+			d->u.l.lens[i] = 9;
+		for (; i < 280; i++)
+			d->u.l.lens[i] = 7;
+		for (; i < 288; i++)
+			d->u.l.lens[i] = 8;
+
+		for (; i < 288 + 32; i++)
+			d->u.l.lens[i] = 5;
+
+		num_litlen_syms = 288;
+		num_offset_syms = 32;
+	}
+
+	/* Decompressing a Huffman block (either dynamic or static)  */
+
+	SAFETY_CHECK(build_offset_decode_table(d, num_litlen_syms, num_offset_syms));
+	SAFETY_CHECK(build_litlen_decode_table(d, num_litlen_syms, num_offset_syms));
+have_decode_tables:
+
+	/* The main DEFLATE decode loop  */
+	for (;;) {
+		u32 entry;
+		u32 length;
+		u32 offset;
+		const u8 *src;
+		u8 *dst;
+
+		/* Decode a litlen symbol.  */
+		ENSURE_BITS(DEFLATE_MAX_LITLEN_CODEWORD_LEN);
+		entry = d->u.litlen_decode_table[BITS(LITLEN_TABLEBITS)];
+		if (entry & HUFFDEC_SUBTABLE_POINTER) {
+			/* Litlen subtable required (uncommon case)  */
+			REMOVE_BITS(LITLEN_TABLEBITS);
+			entry = d->u.litlen_decode_table[
+				((entry >> HUFFDEC_RESULT_SHIFT) & 0xFFFF) +
+				BITS(entry & HUFFDEC_LENGTH_MASK)];
+		}
+		REMOVE_BITS(entry & HUFFDEC_LENGTH_MASK);
+		if (entry & HUFFDEC_LITERAL) {
+			/* Literal  */
+			if (unlikely(out_next == out_end))
+				return LIBDEFLATE_INSUFFICIENT_SPACE;
+			*out_next++ = (u8)(entry >> HUFFDEC_RESULT_SHIFT);
+			continue;
+		}
+
+		/* Match or end-of-block  */
+
+		entry >>= HUFFDEC_RESULT_SHIFT;
+		ENSURE_BITS(MAX_ENSURE);
+
+		/* Pop the extra length bits and add them to the length base to
+		 * produce the full length.  */
+		length = (entry >> HUFFDEC_LENGTH_BASE_SHIFT) +
+			 POP_BITS(entry & HUFFDEC_EXTRA_LENGTH_BITS_MASK);
+
+		/* The match destination must not end after the end of the
+		 * output buffer.  For efficiency, combine this check with the
+		 * end-of-block check.  We're using 0 for the special
+		 * end-of-block length, so subtract 1 and it turn it into
+		 * SIZE_MAX.  */
+		STATIC_ASSERT(HUFFDEC_END_OF_BLOCK_LENGTH == 0);
+		if (unlikely((size_t)length - 1 >= out_end - out_next)) {
+			if (unlikely(length != HUFFDEC_END_OF_BLOCK_LENGTH))
+				return LIBDEFLATE_INSUFFICIENT_SPACE;
+			goto block_done;
+		}
+
+		/* Decode the match offset.  */
+
+		entry = d->offset_decode_table[BITS(OFFSET_TABLEBITS)];
+		if (entry & HUFFDEC_SUBTABLE_POINTER) {
+			/* Offset subtable required (uncommon case)  */
+			REMOVE_BITS(OFFSET_TABLEBITS);
+			entry = d->offset_decode_table[
+				((entry >> HUFFDEC_RESULT_SHIFT) & 0xFFFF) +
+				BITS(entry & HUFFDEC_LENGTH_MASK)];
+		}
+		REMOVE_BITS(entry & HUFFDEC_LENGTH_MASK);
+		entry >>= HUFFDEC_RESULT_SHIFT;
+
+		STATIC_ASSERT(CAN_ENSURE(DEFLATE_MAX_EXTRA_LENGTH_BITS +
+					 DEFLATE_MAX_OFFSET_CODEWORD_LEN) &&
+			      CAN_ENSURE(DEFLATE_MAX_EXTRA_OFFSET_BITS));
+		if (!CAN_ENSURE(DEFLATE_MAX_EXTRA_LENGTH_BITS +
+				DEFLATE_MAX_OFFSET_CODEWORD_LEN +
+				DEFLATE_MAX_EXTRA_OFFSET_BITS))
+			ENSURE_BITS(DEFLATE_MAX_EXTRA_OFFSET_BITS);
+
+		/* Pop the extra offset bits and add them to the offset base to
+		 * produce the full offset.  */
+		offset = (entry & HUFFDEC_OFFSET_BASE_MASK) +
+			 POP_BITS(entry >> HUFFDEC_EXTRA_OFFSET_BITS_SHIFT);
+
+		/* The match source must not begin before the beginning of the
+		 * output buffer.  */
+		SAFETY_CHECK(offset <= out_next - (const u8 *)out);
+
+		/*
+		 * Copy the match: 'length' bytes at 'out_next - offset' to
+		 * 'out_next', possibly overlapping.  If the match doesn't end
+		 * too close to the end of the buffer and offset >= WORDBYTES ||
+		 * offset == 1, take a fast path which copies a word at a time
+		 * -- potentially more than the length of the match, but that's
+		 * fine as long as we check for enough extra space.
+		 *
+		 * The remaining cases are not performance-critical so are
+		 * handled by a simple byte-by-byte copy.
+		 */
+
+		src = out_next - offset;
+		dst = out_next;
+		out_next += length;
+
+		if (UNALIGNED_ACCESS_IS_FAST &&
+		    /* max overrun is writing 3 words for a min length match */
+		    likely(out_end - out_next >=
+			   3 * WORDBYTES - DEFLATE_MIN_MATCH_LEN)) {
+			if (offset >= WORDBYTES) { /* words don't overlap? */
+				copy_word_unaligned(src, dst);
+				src += WORDBYTES;
+				dst += WORDBYTES;
+				copy_word_unaligned(src, dst);
+				src += WORDBYTES;
+				dst += WORDBYTES;
+				do {
+					copy_word_unaligned(src, dst);
+					src += WORDBYTES;
+					dst += WORDBYTES;
+				} while (dst < out_next);
+			} else if (offset == 1) {
+				/* RLE encoding of previous byte, common if the
+				 * data contains many repeated bytes */
+				machine_word_t v = repeat_byte(*src);
+
+				store_word_unaligned(v, dst);
+				dst += WORDBYTES;
+				store_word_unaligned(v, dst);
+				dst += WORDBYTES;
+				do {
+					store_word_unaligned(v, dst);
+					dst += WORDBYTES;
+				} while (dst < out_next);
+			} else {
+				*dst++ = *src++;
+				*dst++ = *src++;
+				do {
+					*dst++ = *src++;
+				} while (dst < out_next);
+			}
+		} else {
+			STATIC_ASSERT(DEFLATE_MIN_MATCH_LEN == 3);
+			*dst++ = *src++;
+			*dst++ = *src++;
+			do {
+				*dst++ = *src++;
+			} while (dst < out_next);
+		}
+	}
+
+block_done:
+	/* Finished decoding a block.  */
+
+	if (!is_final_block)
+		goto next_block;
+
+	/* That was the last block.  */
+
+	/* Discard any readahead bits and check for excessive overread */
+	ALIGN_INPUT();
+
+	/* Optionally return the actual number of bytes read */
+	if (actual_in_nbytes_ret)
+		*actual_in_nbytes_ret = in_next - (u8 *)in;
+
+	/* Optionally return the actual number of bytes written */
+	if (actual_out_nbytes_ret) {
+		*actual_out_nbytes_ret = out_next - (u8 *)out;
+	} else {
+		if (out_next != out_end)
+			return LIBDEFLATE_SHORT_OUTPUT;
+	}
+	return LIBDEFLATE_SUCCESS;
+}
+
+#undef FUNCNAME
+#undef ATTRIBUTES

ADDED   3rd_party/libdeflate/lib/deflate_compress.c
Index: 3rd_party/libdeflate/lib/deflate_compress.c
==================================================================
--- 3rd_party/libdeflate/lib/deflate_compress.c
+++ 3rd_party/libdeflate/lib/deflate_compress.c
@@ -0,0 +1,2854 @@
+/*
+ * deflate_compress.c - a compressor for DEFLATE
+ *
+ * Originally public domain; changes after 2016-09-07 are copyrighted.
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include "deflate_compress.h"
+#include "deflate_constants.h"
+#include "unaligned.h"
+
+#include "libdeflate.h"
+
+/*
+ * By default, the near-optimal parsing algorithm is enabled at compression
+ * level 8 and above.  The near-optimal parsing algorithm produces a compression
+ * ratio significantly better than the greedy and lazy algorithms implemented
+ * here, and also the algorithm used by zlib at level 9.  However, it is slow.
+ */
+#define SUPPORT_NEAR_OPTIMAL_PARSING 1
+
+/*
+ * Define to 1 to maintain the full map from match offsets to offset slots.
+ * This slightly speeds up translations of match offsets to offset slots, but it
+ * uses 32769 bytes of memory rather than the 512 bytes used by the condensed
+ * map.  The speedup provided by the larger map is most helpful when the
+ * near-optimal parsing algorithm is being used.
+ */
+#define USE_FULL_OFFSET_SLOT_FAST	SUPPORT_NEAR_OPTIMAL_PARSING
+
+/*
+ * DEFLATE uses a 32768 byte sliding window; set the matchfinder parameters
+ * appropriately.
+ */
+#define MATCHFINDER_WINDOW_ORDER	15
+
+#include "hc_matchfinder.h"
+#if SUPPORT_NEAR_OPTIMAL_PARSING
+#  include "bt_matchfinder.h"
+#endif
+
+/*
+ * The compressor always chooses a block of at least MIN_BLOCK_LENGTH bytes,
+ * except if the last block has to be shorter.
+ */
+#define MIN_BLOCK_LENGTH	10000
+
+/*
+ * The compressor attempts to end blocks after SOFT_MAX_BLOCK_LENGTH bytes, but
+ * the final length might be slightly longer due to matches extending beyond
+ * this limit.
+ */
+#define SOFT_MAX_BLOCK_LENGTH	300000
+
+/*
+ * The number of observed matches or literals that represents sufficient data to
+ * decide whether the current block should be terminated or not.
+ */
+#define NUM_OBSERVATIONS_PER_BLOCK_CHECK       512
+
+
+#if SUPPORT_NEAR_OPTIMAL_PARSING
+/* Constants specific to the near-optimal parsing algorithm */
+
+/*
+ * The maximum number of matches the matchfinder can find at a single position.
+ * Since the matchfinder never finds more than one match for the same length,
+ * presuming one of each possible length is sufficient for an upper bound.
+ * (This says nothing about whether it is worthwhile to consider so many
+ * matches; this is just defining the worst case.)
+ */
+#  define MAX_MATCHES_PER_POS	(DEFLATE_MAX_MATCH_LEN - DEFLATE_MIN_MATCH_LEN + 1)
+
+/*
+ * The number of lz_match structures in the match cache, excluding the extra
+ * "overflow" entries.  This value should be high enough so that nearly the
+ * time, all matches found in a given block can fit in the match cache.
+ * However, fallback behavior (immediately terminating the block) on cache
+ * overflow is still required.
+ */
+#  define CACHE_LENGTH      (SOFT_MAX_BLOCK_LENGTH * 5)
+
+#endif /* SUPPORT_NEAR_OPTIMAL_PARSING */
+
+/*
+ * These are the compressor-side limits on the codeword lengths for each Huffman
+ * code.  To make outputting bits slightly faster, some of these limits are
+ * lower than the limits defined by the DEFLATE format.  This does not
+ * significantly affect the compression ratio, at least for the block lengths we
+ * use.
+ */
+#define MAX_LITLEN_CODEWORD_LEN		14
+#define MAX_OFFSET_CODEWORD_LEN		DEFLATE_MAX_OFFSET_CODEWORD_LEN
+#define MAX_PRE_CODEWORD_LEN		DEFLATE_MAX_PRE_CODEWORD_LEN
+
+/* Table: length slot => length slot base value  */
+static const unsigned deflate_length_slot_base[] = {
+	3   , 4   , 5   , 6   , 7   , 8   , 9   , 10  ,
+	11  , 13  , 15  , 17  , 19  , 23  , 27  , 31  ,
+	35  , 43  , 51  , 59  , 67  , 83  , 99  , 115 ,
+	131 , 163 , 195 , 227 , 258 ,
+};
+
+/* Table: length slot => number of extra length bits  */
+static const u8 deflate_extra_length_bits[] = {
+	0   , 0   , 0   , 0   , 0   , 0   , 0   , 0 ,
+	1   , 1   , 1   , 1   , 2   , 2   , 2   , 2 ,
+	3   , 3   , 3   , 3   , 4   , 4   , 4   , 4 ,
+	5   , 5   , 5   , 5   , 0   ,
+};
+
+/* Table: offset slot => offset slot base value  */
+static const unsigned deflate_offset_slot_base[] = {
+	1    , 2    , 3    , 4     , 5     , 7     , 9     , 13    ,
+	17   , 25   , 33   , 49    , 65    , 97    , 129   , 193   ,
+	257  , 385  , 513  , 769   , 1025  , 1537  , 2049  , 3073  ,
+	4097 , 6145 , 8193 , 12289 , 16385 , 24577 ,
+};
+
+/* Table: offset slot => number of extra offset bits  */
+static const u8 deflate_extra_offset_bits[] = {
+	0    , 0    , 0    , 0     , 1     , 1     , 2     , 2     ,
+	3    , 3    , 4    , 4     , 5     , 5     , 6     , 6     ,
+	7    , 7    , 8    , 8     , 9     , 9     , 10    , 10    ,
+	11   , 11   , 12   , 12    , 13    , 13    ,
+};
+
+/* Table: length => length slot  */
+static const u8 deflate_length_slot[DEFLATE_MAX_MATCH_LEN + 1] = {
+	0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 12,
+	12, 13, 13, 13, 13, 14, 14, 14, 14, 15, 15, 15, 15, 16, 16, 16, 16, 16,
+	16, 16, 16, 17, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18,
+	18, 19, 19, 19, 19, 19, 19, 19, 19, 20, 20, 20, 20, 20, 20, 20, 20, 20,
+	20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21,
+	21, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22,
+	22, 22, 22, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23,
+	23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
+	24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 25, 25, 25,
+	25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
+	25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 26, 26, 26, 26, 26, 26, 26,
+	26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26,
+	26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
+	27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
+	27, 27, 28,
+};
+
+/* The order in which precode codeword lengths are stored */
+static const u8 deflate_precode_lens_permutation[DEFLATE_NUM_PRECODE_SYMS] = {
+	16, 17, 18, 0, 8, 7, 9, 6, 10, 5, 11, 4, 12, 3, 13, 2, 14, 1, 15
+};
+
+/* Codewords for the DEFLATE Huffman codes.  */
+struct deflate_codewords {
+	u32 litlen[DEFLATE_NUM_LITLEN_SYMS];
+	u32 offset[DEFLATE_NUM_OFFSET_SYMS];
+};
+
+/* Codeword lengths (in bits) for the DEFLATE Huffman codes.
+ * A zero length means the corresponding symbol had zero frequency.  */
+struct deflate_lens {
+	u8 litlen[DEFLATE_NUM_LITLEN_SYMS];
+	u8 offset[DEFLATE_NUM_OFFSET_SYMS];
+};
+
+/* Codewords and lengths for the DEFLATE Huffman codes.  */
+struct deflate_codes {
+	struct deflate_codewords codewords;
+	struct deflate_lens lens;
+};
+
+/* Symbol frequency counters for the DEFLATE Huffman codes.  */
+struct deflate_freqs {
+	u32 litlen[DEFLATE_NUM_LITLEN_SYMS];
+	u32 offset[DEFLATE_NUM_OFFSET_SYMS];
+};
+
+#if SUPPORT_NEAR_OPTIMAL_PARSING
+
+/* Costs for the near-optimal parsing algorithm.  */
+struct deflate_costs {
+
+	/* The cost to output each possible literal.  */
+	u32 literal[DEFLATE_NUM_LITERALS];
+
+	/* The cost to output each possible match length.  */
+	u32 length[DEFLATE_MAX_MATCH_LEN + 1];
+
+	/* The cost to output a match offset of each possible offset slot.  */
+	u32 offset_slot[DEFLATE_NUM_OFFSET_SYMS];
+};
+
+/*
+ * COST_SHIFT is a scaling factor that makes it possible to consider fractional
+ * bit costs.  A token requiring 'n' bits to represent has cost n << COST_SHIFT.
+ *
+ * Note: this is only useful as a statistical trick for when the true costs are
+ * unknown.  In reality, each token in DEFLATE requires a whole number of bits
+ * to output.
+ */
+#define COST_SHIFT	3
+
+/*
+ * The NOSTAT_BITS value for a given alphabet is the number of bits assumed to
+ * be needed to output a symbol that was unused in the previous optimization
+ * pass.  Assigning a default cost allows the symbol to be used in the next
+ * optimization pass.  However, the cost should be relatively high because the
+ * symbol probably won't be used very many times (if at all).
+ */
+#define LITERAL_NOSTAT_BITS	13
+#define LENGTH_NOSTAT_BITS	13
+#define OFFSET_NOSTAT_BITS	10
+
+#endif /* SUPPORT_NEAR_OPTIMAL_PARSING */
+
+/*
+ * Represents a run of literals followed by a match or end-of-block.  This
+ * struct is needed to temporarily store items chosen by the parser, since items
+ * cannot be written until all items for the block have been chosen and the
+ * block's Huffman codes have been computed.
+ */
+struct deflate_sequence {
+
+	/* Bits 0..22: the number of literals in this run.  This may be 0 and
+	 * can be at most about SOFT_MAX_BLOCK_LENGTH.  The literals are not
+	 * stored explicitly in this structure; instead, they are read directly
+	 * from the uncompressed data.
+	 *
+	 * Bits 23..31: the length of the match which follows the literals, or 0
+	 * if this literal run was the last in the block, so there is no match
+	 * which follows it.  */
+	u32 litrunlen_and_length;
+
+	/* If 'length' doesn't indicate end-of-block, then this is the offset of
+	 * the match which follows the literals.  */
+	u16 offset;
+
+	/* If 'length' doesn't indicate end-of-block, then this is the offset
+	 * symbol of the match which follows the literals.  */
+	u8 offset_symbol;
+
+	/* If 'length' doesn't indicate end-of-block, then this is the length
+	 * slot of the match which follows the literals.  */
+	u8 length_slot;
+};
+
+#if SUPPORT_NEAR_OPTIMAL_PARSING
+
+/*
+ * This structure represents a byte position in the input data and a node in the
+ * graph of possible match/literal choices for the current block.
+ *
+ * Logically, each incoming edge to this node is labeled with a literal or a
+ * match that can be taken to reach this position from an earlier position; and
+ * each outgoing edge from this node is labeled with a literal or a match that
+ * can be taken to advance from this position to a later position.
+ *
+ * But these "edges" are actually stored elsewhere (in 'match_cache').  Here we
+ * associate with each node just two pieces of information:
+ *
+ *	'cost_to_end' is the minimum cost to reach the end of the block from
+ *	this position.
+ *
+ *	'item' represents the literal or match that must be chosen from here to
+ *	reach the end of the block with the minimum cost.  Equivalently, this
+ *	can be interpreted as the label of the outgoing edge on the minimum-cost
+ *	path to the "end of block" node from this node.
+ */
+struct deflate_optimum_node {
+
+	u32 cost_to_end;
+
+	/*
+	 * Notes on the match/literal representation used here:
+	 *
+	 *	The low bits of 'item' are the length: 1 if this is a literal,
+	 *	or the match length if this is a match.
+	 *
+	 *	The high bits of 'item' are the actual literal byte if this is a
+	 *	literal, or the match offset if this is a match.
+	 */
+#define OPTIMUM_OFFSET_SHIFT 9
+#define OPTIMUM_LEN_MASK (((u32)1 << OPTIMUM_OFFSET_SHIFT) - 1)
+	u32 item;
+
+};
+
+#endif /* SUPPORT_NEAR_OPTIMAL_PARSING */
+
+/* Block split statistics.  See "Block splitting algorithm" below. */
+#define NUM_LITERAL_OBSERVATION_TYPES 8
+#define NUM_MATCH_OBSERVATION_TYPES 2
+#define NUM_OBSERVATION_TYPES (NUM_LITERAL_OBSERVATION_TYPES + NUM_MATCH_OBSERVATION_TYPES)
+struct block_split_stats {
+	u32 new_observations[NUM_OBSERVATION_TYPES];
+	u32 observations[NUM_OBSERVATION_TYPES];
+	u32 num_new_observations;
+	u32 num_observations;
+};
+
+/* The main DEFLATE compressor structure  */
+struct libdeflate_compressor {
+
+	/* Pointer to the compress() implementation chosen at allocation time */
+	size_t (*impl)(struct libdeflate_compressor *,
+		       const u8 *, size_t, u8 *, size_t);
+
+	/* Frequency counters for the current block  */
+	struct deflate_freqs freqs;
+
+	/* Dynamic Huffman codes for the current block  */
+	struct deflate_codes codes;
+
+	/* Static Huffman codes */
+	struct deflate_codes static_codes;
+
+	/* Block split statistics for the currently pending block */
+	struct block_split_stats split_stats;
+
+	/* A table for fast lookups of offset slot by match offset.
+	 *
+	 * If the full table is being used, it is a direct mapping from offset
+	 * to offset slot.
+	 *
+	 * If the condensed table is being used, the first 256 entries map
+	 * directly to the offset slots of offsets 1 through 256.  The next 256
+	 * entries map to the offset slots for the remaining offsets, stepping
+	 * through the offsets with a stride of 128.  This relies on the fact
+	 * that each of the remaining offset slots contains at least 128 offsets
+	 * and has an offset base that is a multiple of 128.  */
+#if USE_FULL_OFFSET_SLOT_FAST
+	u8 offset_slot_fast[DEFLATE_MAX_MATCH_OFFSET + 1];
+#else
+	u8 offset_slot_fast[512];
+#endif
+
+	/* The "nice" match length: if a match of this length is found, choose
+	 * it immediately without further consideration.  */
+	unsigned nice_match_length;
+
+	/* The maximum search depth: consider at most this many potential
+	 * matches at each position.  */
+	unsigned max_search_depth;
+
+	/* The compression level with which this compressor was created.  */
+	unsigned compression_level;
+
+	/* Anything smaller than this we won't bother trying to compress.  */
+	unsigned min_size_to_compress;
+
+	/* Temporary space for Huffman code output  */
+	u32 precode_freqs[DEFLATE_NUM_PRECODE_SYMS];
+	u8 precode_lens[DEFLATE_NUM_PRECODE_SYMS];
+	u32 precode_codewords[DEFLATE_NUM_PRECODE_SYMS];
+	unsigned precode_items[DEFLATE_NUM_LITLEN_SYMS + DEFLATE_NUM_OFFSET_SYMS];
+	unsigned num_litlen_syms;
+	unsigned num_offset_syms;
+	unsigned num_explicit_lens;
+	unsigned num_precode_items;
+
+	union {
+		/* Data for greedy or lazy parsing  */
+		struct {
+			/* Hash chain matchfinder  */
+			struct hc_matchfinder hc_mf;
+
+			/* The matches and literals that the parser has chosen
+			 * for the current block.  The required length of this
+			 * array is limited by the maximum number of matches
+			 * that can ever be chosen for a single block, plus one
+			 * for the special entry at the end.  */
+			struct deflate_sequence sequences[
+				DIV_ROUND_UP(SOFT_MAX_BLOCK_LENGTH,
+					     DEFLATE_MIN_MATCH_LEN) + 1];
+		} g; /* (g)reedy */
+
+	#if SUPPORT_NEAR_OPTIMAL_PARSING
+		/* Data for near-optimal parsing  */
+		struct {
+
+			/* Binary tree matchfinder  */
+			struct bt_matchfinder bt_mf;
+
+			/*
+			 * Cached matches for the current block.  This array
+			 * contains the matches that were found at each position
+			 * in the block.  Specifically, for each position, there
+			 * is a list of matches found at that position, if any,
+			 * sorted by strictly increasing length.  In addition,
+			 * following the matches for each position, there is a
+			 * special 'struct lz_match' whose 'length' member
+			 * contains the number of matches found at that
+			 * position, and whose 'offset' member contains the
+			 * literal at that position.
+			 *
+			 * Note: in rare cases, there will be a very high number
+			 * of matches in the block and this array will overflow.
+			 * If this happens, we force the end of the current
+			 * block.  CACHE_LENGTH is the length at which we
+			 * actually check for overflow.  The extra slots beyond
+			 * this are enough to absorb the worst case overflow,
+			 * which occurs if starting at &match_cache[CACHE_LENGTH
+			 * - 1], we write MAX_MATCHES_PER_POS matches and a
+			 * match count header, then skip searching for matches
+			 * at 'DEFLATE_MAX_MATCH_LEN - 1' positions and write
+			 * the match count header for each.
+			 */
+			struct lz_match match_cache[CACHE_LENGTH +
+						    MAX_MATCHES_PER_POS +
+						    DEFLATE_MAX_MATCH_LEN - 1];
+
+			/*
+			 * Array of nodes, one per position, for running the
+			 * minimum-cost path algorithm.
+			 *
+			 * This array must be large enough to accommodate the
+			 * worst-case number of nodes, which occurs if we find a
+			 * match of length DEFLATE_MAX_MATCH_LEN at position
+			 * SOFT_MAX_BLOCK_LENGTH - 1, producing a block of
+			 * length SOFT_MAX_BLOCK_LENGTH - 1 +
+			 * DEFLATE_MAX_MATCH_LEN.  Add one for the end-of-block
+			 * node.
+			 */
+			struct deflate_optimum_node optimum_nodes[SOFT_MAX_BLOCK_LENGTH - 1 +
+								  DEFLATE_MAX_MATCH_LEN + 1];
+
+			/* The current cost model being used.  */
+			struct deflate_costs costs;
+
+			unsigned num_optim_passes;
+		} n; /* (n)ear-optimal */
+	#endif /* SUPPORT_NEAR_OPTIMAL_PARSING */
+
+	} p; /* (p)arser */
+};
+
+/*
+ * The type for the bitbuffer variable, which temporarily holds bits that are
+ * being packed into bytes and written to the output buffer.  For best
+ * performance, this should have size equal to a machine word.
+ */
+typedef machine_word_t bitbuf_t;
+#define BITBUF_NBITS	(8 * sizeof(bitbuf_t))
+
+/* Can the specified number of bits always be added to 'bitbuf' after any
+ * pending bytes have been flushed?  */
+#define CAN_BUFFER(n)	((n) <= BITBUF_NBITS - 7)
+
+/*
+ * Structure to keep track of the current state of sending bits to the
+ * compressed output buffer.
+ */
+struct deflate_output_bitstream {
+
+	/* Bits that haven't yet been written to the output buffer.  */
+	bitbuf_t bitbuf;
+
+	/* Number of bits currently held in @bitbuf.  */
+	unsigned bitcount;
+
+	/* Pointer to the beginning of the output buffer.  */
+	u8 *begin;
+
+	/* Pointer to the position in the output buffer at which the next byte
+	 * should be written.  */
+	u8 *next;
+
+	/* Pointer just past the end of the output buffer.  */
+	u8 *end;
+};
+
+/*
+ * OUTPUT_END_PADDING is the size, in bytes, of the extra space that must be
+ * present following os->end, in order to not overrun the buffer when generating
+ * output.  When UNALIGNED_ACCESS_IS_FAST, we need at least sizeof(bitbuf_t)
+ * bytes for put_unaligned_leword().  Otherwise we need only 1 byte.  However,
+ * to make the compression algorithm produce the same result on all CPU
+ * architectures (which is sometimes desirable), we have to unconditionally use
+ * the maximum for any CPU, which is sizeof(bitbuf_t) == 8.
+ */
+#define OUTPUT_END_PADDING	8
+
+/* Initialize the output bitstream.  'size' is assumed to be at least
+ * OUTPUT_END_PADDING.  */
+static void
+deflate_init_output(struct deflate_output_bitstream *os,
+		    void *buffer, size_t size)
+{
+	os->bitbuf = 0;
+	os->bitcount = 0;
+	os->begin = buffer;
+	os->next = os->begin;
+	os->end = os->begin + size - OUTPUT_END_PADDING;
+}
+
+/* Add some bits to the bitbuffer variable of the output bitstream.  The caller
+ * must make sure there is enough room.  */
+static forceinline void
+deflate_add_bits(struct deflate_output_bitstream *os,
+		 const bitbuf_t bits, const unsigned num_bits)
+{
+	os->bitbuf |= bits << os->bitcount;
+	os->bitcount += num_bits;
+}
+
+/* Flush bits from the bitbuffer variable to the output buffer.  */
+static forceinline void
+deflate_flush_bits(struct deflate_output_bitstream *os)
+{
+	if (UNALIGNED_ACCESS_IS_FAST) {
+		/* Flush a whole word (branchlessly).  */
+		put_unaligned_leword(os->bitbuf, os->next);
+		os->bitbuf >>= os->bitcount & ~7;
+		os->next += MIN(os->end - os->next, os->bitcount >> 3);
+		os->bitcount &= 7;
+	} else {
+		/* Flush a byte at a time.  */
+		while (os->bitcount >= 8) {
+			*os->next = os->bitbuf;
+			if (os->next != os->end)
+				os->next++;
+			os->bitcount -= 8;
+			os->bitbuf >>= 8;
+		}
+	}
+}
+
+/* Align the bitstream on a byte boundary. */
+static forceinline void
+deflate_align_bitstream(struct deflate_output_bitstream *os)
+{
+	os->bitcount += -os->bitcount & 7;
+	deflate_flush_bits(os);
+}
+
+/*
+ * Flush any remaining bits to the output buffer if needed.  Return the total
+ * number of bytes written to the output buffer, or 0 if an overflow occurred.
+ */
+static size_t
+deflate_flush_output(struct deflate_output_bitstream *os)
+{
+	if (os->next == os->end) /* overflow?  */
+		return 0;
+
+	while ((int)os->bitcount > 0) {
+		*os->next++ = os->bitbuf;
+		os->bitcount -= 8;
+		os->bitbuf >>= 8;
+	}
+
+	return os->next - os->begin;
+}
+
+/* Given the binary tree node A[subtree_idx] whose children already
+ * satisfy the maxheap property, swap the node with its greater child
+ * until it is greater than both its children, so that the maxheap
+ * property is satisfied in the subtree rooted at A[subtree_idx].  */
+static void
+heapify_subtree(u32 A[], unsigned length, unsigned subtree_idx)
+{
+	unsigned parent_idx;
+	unsigned child_idx;
+	u32 v;
+
+	v = A[subtree_idx];
+	parent_idx = subtree_idx;
+	while ((child_idx = parent_idx * 2) <= length) {
+		if (child_idx < length && A[child_idx + 1] > A[child_idx])
+			child_idx++;
+		if (v >= A[child_idx])
+			break;
+		A[parent_idx] = A[child_idx];
+		parent_idx = child_idx;
+	}
+	A[parent_idx] = v;
+}
+
+/* Rearrange the array 'A' so that it satisfies the maxheap property.
+ * 'A' uses 1-based indices, so the children of A[i] are A[i*2] and A[i*2 + 1].
+ */
+static void
+heapify_array(u32 A[], unsigned length)
+{
+	unsigned subtree_idx;
+
+	for (subtree_idx = length / 2; subtree_idx >= 1; subtree_idx--)
+		heapify_subtree(A, length, subtree_idx);
+}
+
+/*
+ * Sort the array 'A', which contains 'length' unsigned 32-bit integers.
+ *
+ * Note: name this function heap_sort() instead of heapsort() to avoid colliding
+ * with heapsort() from stdlib.h on BSD-derived systems --- though this isn't
+ * necessary when compiling with -D_ANSI_SOURCE, which is the better solution.
+ */
+static void
+heap_sort(u32 A[], unsigned length)
+{
+	A--; /* Use 1-based indices  */
+
+	heapify_array(A, length);
+
+	while (length >= 2) {
+		u32 tmp = A[length];
+		A[length] = A[1];
+		A[1] = tmp;
+		length--;
+		heapify_subtree(A, length, 1);
+	}
+}
+
+#define NUM_SYMBOL_BITS 10
+#define SYMBOL_MASK ((1 << NUM_SYMBOL_BITS) - 1)
+
+#define GET_NUM_COUNTERS(num_syms)	((((num_syms) + 3 / 4) + 3) & ~3)
+/*
+ * Sort the symbols primarily by frequency and secondarily by symbol
+ * value.  Discard symbols with zero frequency and fill in an array with
+ * the remaining symbols, along with their frequencies.  The low
+ * NUM_SYMBOL_BITS bits of each array entry will contain the symbol
+ * value, and the remaining bits will contain the frequency.
+ *
+ * @num_syms
+ *	Number of symbols in the alphabet.
+ *	Can't be greater than (1 << NUM_SYMBOL_BITS).
+ *
+ * @freqs[num_syms]
+ *	The frequency of each symbol.
+ *
+ * @lens[num_syms]
+ *	An array that eventually will hold the length of each codeword.
+ *	This function only fills in the codeword lengths for symbols that
+ *	have zero frequency, which are not well defined per se but will
+ *	be set to 0.
+ *
+ * @symout[num_syms]
+ *	The output array, described above.
+ *
+ * Returns the number of entries in 'symout' that were filled.  This is
+ * the number of symbols that have nonzero frequency.
+ */
+static unsigned
+sort_symbols(unsigned num_syms, const u32 freqs[restrict],
+	     u8 lens[restrict], u32 symout[restrict])
+{
+	unsigned sym;
+	unsigned i;
+	unsigned num_used_syms;
+	unsigned num_counters;
+	unsigned counters[GET_NUM_COUNTERS(DEFLATE_MAX_NUM_SYMS)];
+
+	/* We rely on heapsort, but with an added optimization.  Since
+	 * it's common for most symbol frequencies to be low, we first do
+	 * a count sort using a limited number of counters.  High
+	 * frequencies will be counted in the last counter, and only they
+	 * will be sorted with heapsort.
+	 *
+	 * Note: with more symbols, it is generally beneficial to have more
+	 * counters.  About 1 counter per 4 symbols seems fast.
+	 *
+	 * Note: I also tested radix sort, but even for large symbol
+	 * counts (> 255) and frequencies bounded at 16 bits (enabling
+	 * radix sort by just two base-256 digits), it didn't seem any
+	 * faster than the method implemented here.
+	 *
+	 * Note: I tested the optimized quicksort implementation from
+	 * glibc (with indirection overhead removed), but it was only
+	 * marginally faster than the simple heapsort implemented here.
+	 *
+	 * Tests were done with building the codes for LZX.  Results may
+	 * vary for different compression algorithms...!  */
+
+	num_counters = GET_NUM_COUNTERS(num_syms);
+
+	memset(counters, 0, num_counters * sizeof(counters[0]));
+
+	/* Count the frequencies.  */
+	for (sym = 0; sym < num_syms; sym++)
+		counters[MIN(freqs[sym], num_counters - 1)]++;
+
+	/* Make the counters cumulative, ignoring the zero-th, which
+	 * counted symbols with zero frequency.  As a side effect, this
+	 * calculates the number of symbols with nonzero frequency.  */
+	num_used_syms = 0;
+	for (i = 1; i < num_counters; i++) {
+		unsigned count = counters[i];
+		counters[i] = num_used_syms;
+		num_used_syms += count;
+	}
+
+	/* Sort nonzero-frequency symbols using the counters.  At the
+	 * same time, set the codeword lengths of zero-frequency symbols
+	 * to 0.  */
+	for (sym = 0; sym < num_syms; sym++) {
+		u32 freq = freqs[sym];
+		if (freq != 0) {
+			symout[counters[MIN(freq, num_counters - 1)]++] =
+				sym | (freq << NUM_SYMBOL_BITS);
+		} else {
+			lens[sym] = 0;
+		}
+	}
+
+	/* Sort the symbols counted in the last counter.  */
+	heap_sort(symout + counters[num_counters - 2],
+		  counters[num_counters - 1] - counters[num_counters - 2]);
+
+	return num_used_syms;
+}
+
+/*
+ * Build the Huffman tree.
+ *
+ * This is an optimized implementation that
+ *	(a) takes advantage of the frequencies being already sorted;
+ *	(b) only generates non-leaf nodes, since the non-leaf nodes of a
+ *	    Huffman tree are sufficient to generate a canonical code;
+ *	(c) Only stores parent pointers, not child pointers;
+ *	(d) Produces the nodes in the same memory used for input
+ *	    frequency information.
+ *
+ * Array 'A', which contains 'sym_count' entries, is used for both input
+ * and output.  For this function, 'sym_count' must be at least 2.
+ *
+ * For input, the array must contain the frequencies of the symbols,
+ * sorted in increasing order.  Specifically, each entry must contain a
+ * frequency left shifted by NUM_SYMBOL_BITS bits.  Any data in the low
+ * NUM_SYMBOL_BITS bits of the entries will be ignored by this function.
+ * Although these bits will, in fact, contain the symbols that correspond
+ * to the frequencies, this function is concerned with frequencies only
+ * and keeps the symbols as-is.
+ *
+ * For output, this function will produce the non-leaf nodes of the
+ * Huffman tree.  These nodes will be stored in the first (sym_count - 1)
+ * entries of the array.  Entry A[sym_count - 2] will represent the root
+ * node.  Each other node will contain the zero-based index of its parent
+ * node in 'A', left shifted by NUM_SYMBOL_BITS bits.  The low
+ * NUM_SYMBOL_BITS bits of each entry in A will be kept as-is.  Again,
+ * note that although these low bits will, in fact, contain a symbol
+ * value, this symbol will have *no relationship* with the Huffman tree
+ * node that happens to occupy the same slot.  This is because this
+ * implementation only generates the non-leaf nodes of the tree.
+ */
+static void
+build_tree(u32 A[], unsigned sym_count)
+{
+	/* Index, in 'A', of next lowest frequency symbol that has not
+	 * yet been processed.  */
+	unsigned i = 0;
+
+	/* Index, in 'A', of next lowest frequency parentless non-leaf
+	 * node; or, if equal to 'e', then no such node exists yet.  */
+	unsigned b = 0;
+
+	/* Index, in 'A', of next node to allocate as a non-leaf.  */
+	unsigned e = 0;
+
+	do {
+		unsigned m, n;
+		u32 freq_shifted;
+
+		/* Choose the two next lowest frequency entries.  */
+
+		if (i != sym_count &&
+		    (b == e || (A[i] >> NUM_SYMBOL_BITS) <= (A[b] >> NUM_SYMBOL_BITS)))
+			m = i++;
+		else
+			m = b++;
+
+		if (i != sym_count &&
+		    (b == e || (A[i] >> NUM_SYMBOL_BITS) <= (A[b] >> NUM_SYMBOL_BITS)))
+			n = i++;
+		else
+			n = b++;
+
+		/* Allocate a non-leaf node and link the entries to it.
+		 *
+		 * If we link an entry that we're visiting for the first
+		 * time (via index 'i'), then we're actually linking a
+		 * leaf node and it will have no effect, since the leaf
+		 * will be overwritten with a non-leaf when index 'e'
+		 * catches up to it.  But it's not any slower to
+		 * unconditionally set the parent index.
+		 *
+		 * We also compute the frequency of the non-leaf node as
+		 * the sum of its two children's frequencies.  */
+
+		freq_shifted = (A[m] & ~SYMBOL_MASK) + (A[n] & ~SYMBOL_MASK);
+
+		A[m] = (A[m] & SYMBOL_MASK) | (e << NUM_SYMBOL_BITS);
+		A[n] = (A[n] & SYMBOL_MASK) | (e << NUM_SYMBOL_BITS);
+		A[e] = (A[e] & SYMBOL_MASK) | freq_shifted;
+		e++;
+	} while (sym_count - e > 1);
+		/* When just one entry remains, it is a "leaf" that was
+		 * linked to some other node.  We ignore it, since the
+		 * rest of the array contains the non-leaves which we
+		 * need.  (Note that we're assuming the cases with 0 or 1
+		 * symbols were handled separately.) */
+}
+
+/*
+ * Given the stripped-down Huffman tree constructed by build_tree(),
+ * determine the number of codewords that should be assigned each
+ * possible length, taking into account the length-limited constraint.
+ *
+ * @A
+ *	The array produced by build_tree(), containing parent index
+ *	information for the non-leaf nodes of the Huffman tree.  Each
+ *	entry in this array is a node; a node's parent always has a
+ *	greater index than that node itself.  This function will
+ *	overwrite the parent index information in this array, so
+ *	essentially it will destroy the tree.  However, the data in the
+ *	low NUM_SYMBOL_BITS of each entry will be preserved.
+ *
+ * @root_idx
+ *	The 0-based index of the root node in 'A', and consequently one
+ *	less than the number of tree node entries in 'A'.  (Or, really 2
+ *	less than the actual length of 'A'.)
+ *
+ * @len_counts
+ *	An array of length ('max_codeword_len' + 1) in which the number of
+ *	codewords having each length <= max_codeword_len will be
+ *	returned.
+ *
+ * @max_codeword_len
+ *	The maximum permissible codeword length.
+ */
+static void
+compute_length_counts(u32 A[restrict], unsigned root_idx,
+		      unsigned len_counts[restrict], unsigned max_codeword_len)
+{
+	unsigned len;
+	int node;
+
+	/* The key observations are:
+	 *
+	 * (1) We can traverse the non-leaf nodes of the tree, always
+	 * visiting a parent before its children, by simply iterating
+	 * through the array in reverse order.  Consequently, we can
+	 * compute the depth of each node in one pass, overwriting the
+	 * parent indices with depths.
+	 *
+	 * (2) We can initially assume that in the real Huffman tree,
+	 * both children of the root are leaves.  This corresponds to two
+	 * codewords of length 1.  Then, whenever we visit a (non-leaf)
+	 * node during the traversal, we modify this assumption to
+	 * account for the current node *not* being a leaf, but rather
+	 * its two children being leaves.  This causes the loss of one
+	 * codeword for the current depth and the addition of two
+	 * codewords for the current depth plus one.
+	 *
+	 * (3) We can handle the length-limited constraint fairly easily
+	 * by simply using the largest length available when a depth
+	 * exceeds max_codeword_len.
+	 */
+
+	for (len = 0; len <= max_codeword_len; len++)
+		len_counts[len] = 0;
+	len_counts[1] = 2;
+
+	/* Set the root node's depth to 0.  */
+	A[root_idx] &= SYMBOL_MASK;
+
+	for (node = root_idx - 1; node >= 0; node--) {
+
+		/* Calculate the depth of this node.  */
+
+		unsigned parent = A[node] >> NUM_SYMBOL_BITS;
+		unsigned parent_depth = A[parent] >> NUM_SYMBOL_BITS;
+		unsigned depth = parent_depth + 1;
+		unsigned len = depth;
+
+		/* Set the depth of this node so that it is available
+		 * when its children (if any) are processed.  */
+
+		A[node] = (A[node] & SYMBOL_MASK) | (depth << NUM_SYMBOL_BITS);
+
+		/* If needed, decrease the length to meet the
+		 * length-limited constraint.  This is not the optimal
+		 * method for generating length-limited Huffman codes!
+		 * But it should be good enough.  */
+		if (len >= max_codeword_len) {
+			len = max_codeword_len;
+			do {
+				len--;
+			} while (len_counts[len] == 0);
+		}
+
+		/* Account for the fact that we have a non-leaf node at
+		 * the current depth.  */
+		len_counts[len]--;
+		len_counts[len + 1] += 2;
+	}
+}
+
+/*
+ * Generate the codewords for a canonical Huffman code.
+ *
+ * @A
+ *	The output array for codewords.  In addition, initially this
+ *	array must contain the symbols, sorted primarily by frequency and
+ *	secondarily by symbol value, in the low NUM_SYMBOL_BITS bits of
+ *	each entry.
+ *
+ * @len
+ *	Output array for codeword lengths.
+ *
+ * @len_counts
+ *	An array that provides the number of codewords that will have
+ *	each possible length <= max_codeword_len.
+ *
+ * @max_codeword_len
+ *	Maximum length, in bits, of each codeword.
+ *
+ * @num_syms
+ *	Number of symbols in the alphabet, including symbols with zero
+ *	frequency.  This is the length of the 'A' and 'len' arrays.
+ */
+static void
+gen_codewords(u32 A[restrict], u8 lens[restrict],
+	      const unsigned len_counts[restrict],
+	      unsigned max_codeword_len, unsigned num_syms)
+{
+	u32 next_codewords[DEFLATE_MAX_CODEWORD_LEN + 1];
+	unsigned i;
+	unsigned len;
+	unsigned sym;
+
+	/* Given the number of codewords that will have each length,
+	 * assign codeword lengths to symbols.  We do this by assigning
+	 * the lengths in decreasing order to the symbols sorted
+	 * primarily by increasing frequency and secondarily by
+	 * increasing symbol value.  */
+	for (i = 0, len = max_codeword_len; len >= 1; len--) {
+		unsigned count = len_counts[len];
+		while (count--)
+			lens[A[i++] & SYMBOL_MASK] = len;
+	}
+
+	/* Generate the codewords themselves.  We initialize the
+	 * 'next_codewords' array to provide the lexicographically first
+	 * codeword of each length, then assign codewords in symbol
+	 * order.  This produces a canonical code.  */
+	next_codewords[0] = 0;
+	next_codewords[1] = 0;
+	for (len = 2; len <= max_codeword_len; len++)
+		next_codewords[len] =
+			(next_codewords[len - 1] + len_counts[len - 1]) << 1;
+
+	for (sym = 0; sym < num_syms; sym++)
+		A[sym] = next_codewords[lens[sym]]++;
+}
+
+/*
+ * ---------------------------------------------------------------------
+ *			make_canonical_huffman_code()
+ * ---------------------------------------------------------------------
+ *
+ * Given an alphabet and the frequency of each symbol in it, construct a
+ * length-limited canonical Huffman code.
+ *
+ * @num_syms
+ *	The number of symbols in the alphabet.  The symbols are the
+ *	integers in the range [0, num_syms - 1].  This parameter must be
+ *	at least 2 and can't be greater than (1 << NUM_SYMBOL_BITS).
+ *
+ * @max_codeword_len
+ *	The maximum permissible codeword length.
+ *
+ * @freqs
+ *	An array of @num_syms entries, each of which specifies the
+ *	frequency of the corresponding symbol.  It is valid for some,
+ *	none, or all of the frequencies to be 0.
+ *
+ * @lens
+ *	An array of @num_syms entries in which this function will return
+ *	the length, in bits, of the codeword assigned to each symbol.
+ *	Symbols with 0 frequency will not have codewords per se, but
+ *	their entries in this array will be set to 0.  No lengths greater
+ *	than @max_codeword_len will be assigned.
+ *
+ * @codewords
+ *	An array of @num_syms entries in which this function will return
+ *	the codeword for each symbol, right-justified and padded on the
+ *	left with zeroes.  Codewords for symbols with 0 frequency will be
+ *	undefined.
+ *
+ * ---------------------------------------------------------------------
+ *
+ * This function builds a length-limited canonical Huffman code.
+ *
+ * A length-limited Huffman code contains no codewords longer than some
+ * specified length, and has exactly (with some algorithms) or
+ * approximately (with the algorithm used here) the minimum weighted path
+ * length from the root, given this constraint.
+ *
+ * A canonical Huffman code satisfies the properties that a longer
+ * codeword never lexicographically precedes a shorter codeword, and the
+ * lexicographic ordering of codewords of the same length is the same as
+ * the lexicographic ordering of the corresponding symbols.  A canonical
+ * Huffman code, or more generally a canonical prefix code, can be
+ * reconstructed from only a list containing the codeword length of each
+ * symbol.
+ *
+ * The classic algorithm to generate a Huffman code creates a node for
+ * each symbol, then inserts these nodes into a min-heap keyed by symbol
+ * frequency.  Then, repeatedly, the two lowest-frequency nodes are
+ * removed from the min-heap and added as the children of a new node
+ * having frequency equal to the sum of its two children, which is then
+ * inserted into the min-heap.  When only a single node remains in the
+ * min-heap, it is the root of the Huffman tree.  The codeword for each
+ * symbol is determined by the path needed to reach the corresponding
+ * node from the root.  Descending to the left child appends a 0 bit,
+ * whereas descending to the right child appends a 1 bit.
+ *
+ * The classic algorithm is relatively easy to understand, but it is
+ * subject to a number of inefficiencies.  In practice, it is fastest to
+ * first sort the symbols by frequency.  (This itself can be subject to
+ * an optimization based on the fact that most frequencies tend to be
+ * low.)  At the same time, we sort secondarily by symbol value, which
+ * aids the process of generating a canonical code.  Then, during tree
+ * construction, no heap is necessary because both the leaf nodes and the
+ * unparented non-leaf nodes can be easily maintained in sorted order.
+ * Consequently, there can never be more than two possibilities for the
+ * next-lowest-frequency node.
+ *
+ * In addition, because we're generating a canonical code, we actually
+ * don't need the leaf nodes of the tree at all, only the non-leaf nodes.
+ * This is because for canonical code generation we don't need to know
+ * where the symbols are in the tree.  Rather, we only need to know how
+ * many leaf nodes have each depth (codeword length).  And this
+ * information can, in fact, be quickly generated from the tree of
+ * non-leaves only.
+ *
+ * Furthermore, we can build this stripped-down Huffman tree directly in
+ * the array in which the codewords are to be generated, provided that
+ * these array slots are large enough to hold a symbol and frequency
+ * value.
+ *
+ * Still furthermore, we don't even need to maintain explicit child
+ * pointers.  We only need the parent pointers, and even those can be
+ * overwritten in-place with depth information as part of the process of
+ * extracting codeword lengths from the tree.  So in summary, we do NOT
+ * need a big structure like:
+ *
+ *	struct huffman_tree_node {
+ *		unsigned int symbol;
+ *		unsigned int frequency;
+ *		unsigned int depth;
+ *		struct huffman_tree_node *left_child;
+ *		struct huffman_tree_node *right_child;
+ *	};
+ *
+ *
+ *   ... which often gets used in "naive" implementations of Huffman code
+ *   generation.
+ *
+ * Many of these optimizations are based on the implementation in 7-Zip
+ * (source file: C/HuffEnc.c), which has been placed in the public domain
+ * by Igor Pavlov.
+ */
+static void
+make_canonical_huffman_code(unsigned num_syms, unsigned max_codeword_len,
+			    const u32 freqs[restrict],
+			    u8 lens[restrict], u32 codewords[restrict])
+{
+	u32 *A = codewords;
+	unsigned num_used_syms;
+
+	STATIC_ASSERT(DEFLATE_MAX_NUM_SYMS <= 1 << NUM_SYMBOL_BITS);
+
+	/* We begin by sorting the symbols primarily by frequency and
+	 * secondarily by symbol value.  As an optimization, the array
+	 * used for this purpose ('A') shares storage with the space in
+	 * which we will eventually return the codewords.  */
+
+	num_used_syms = sort_symbols(num_syms, freqs, lens, A);
+
+	/* 'num_used_syms' is the number of symbols with nonzero
+	 * frequency.  This may be less than @num_syms.  'num_used_syms'
+	 * is also the number of entries in 'A' that are valid.  Each
+	 * entry consists of a distinct symbol and a nonzero frequency
+	 * packed into a 32-bit integer.  */
+
+	/* Handle special cases where only 0 or 1 symbols were used (had
+	 * nonzero frequency).  */
+
+	if (unlikely(num_used_syms == 0)) {
+		/* Code is empty.  sort_symbols() already set all lengths
+		 * to 0, so there is nothing more to do.  */
+		return;
+	}
+
+	if (unlikely(num_used_syms == 1)) {
+		/* Only one symbol was used, so we only need one
+		 * codeword.  But two codewords are needed to form the
+		 * smallest complete Huffman code, which uses codewords 0
+		 * and 1.  Therefore, we choose another symbol to which
+		 * to assign a codeword.  We use 0 (if the used symbol is
+		 * not 0) or 1 (if the used symbol is 0).  In either
+		 * case, the lesser-valued symbol must be assigned
+		 * codeword 0 so that the resulting code is canonical.  */
+
+		unsigned sym = A[0] & SYMBOL_MASK;
+		unsigned nonzero_idx = sym ? sym : 1;
+
+		codewords[0] = 0;
+		lens[0] = 1;
+		codewords[nonzero_idx] = 1;
+		lens[nonzero_idx] = 1;
+		return;
+	}
+
+	/* Build a stripped-down version of the Huffman tree, sharing the
+	 * array 'A' with the symbol values.  Then extract length counts
+	 * from the tree and use them to generate the final codewords.  */
+
+	build_tree(A, num_used_syms);
+
+	{
+		unsigned len_counts[DEFLATE_MAX_CODEWORD_LEN + 1];
+
+		compute_length_counts(A, num_used_syms - 2,
+				      len_counts, max_codeword_len);
+
+		gen_codewords(A, lens, len_counts, max_codeword_len, num_syms);
+	}
+}
+
+/*
+ * Clear the Huffman symbol frequency counters.
+ * This must be called when starting a new DEFLATE block.
+ */
+static void
+deflate_reset_symbol_frequencies(struct libdeflate_compressor *c)
+{
+	memset(&c->freqs, 0, sizeof(c->freqs));
+}
+
+/* Reverse the Huffman codeword 'codeword', which is 'len' bits in length.  */
+static u32
+deflate_reverse_codeword(u32 codeword, u8 len)
+{
+	/* The following branchless algorithm is faster than going bit by bit.
+	 * Note: since no codewords are longer than 16 bits, we only need to
+	 * reverse the low 16 bits of the 'u32'.  */
+	STATIC_ASSERT(DEFLATE_MAX_CODEWORD_LEN <= 16);
+
+	/* Flip adjacent 1-bit fields  */
+	codeword = ((codeword & 0x5555) << 1) | ((codeword & 0xAAAA) >> 1);
+
+	/* Flip adjacent 2-bit fields  */
+	codeword = ((codeword & 0x3333) << 2) | ((codeword & 0xCCCC) >> 2);
+
+	/* Flip adjacent 4-bit fields  */
+	codeword = ((codeword & 0x0F0F) << 4) | ((codeword & 0xF0F0) >> 4);
+
+	/* Flip adjacent 8-bit fields  */
+	codeword = ((codeword & 0x00FF) << 8) | ((codeword & 0xFF00) >> 8);
+
+	/* Return the high 'len' bits of the bit-reversed 16 bit value.  */
+	return codeword >> (16 - len);
+}
+
+/* Make a canonical Huffman code with bit-reversed codewords.  */
+static void
+deflate_make_huffman_code(unsigned num_syms, unsigned max_codeword_len,
+			  const u32 freqs[], u8 lens[], u32 codewords[])
+{
+	unsigned sym;
+
+	make_canonical_huffman_code(num_syms, max_codeword_len,
+				    freqs, lens, codewords);
+
+	for (sym = 0; sym < num_syms; sym++)
+		codewords[sym] = deflate_reverse_codeword(codewords[sym], lens[sym]);
+}
+
+/*
+ * Build the literal/length and offset Huffman codes for a DEFLATE block.
+ *
+ * This takes as input the frequency tables for each code and produces as output
+ * a set of tables that map symbols to codewords and codeword lengths.
+ */
+static void
+deflate_make_huffman_codes(const struct deflate_freqs *freqs,
+			   struct deflate_codes *codes)
+{
+	STATIC_ASSERT(MAX_LITLEN_CODEWORD_LEN <= DEFLATE_MAX_LITLEN_CODEWORD_LEN);
+	STATIC_ASSERT(MAX_OFFSET_CODEWORD_LEN <= DEFLATE_MAX_OFFSET_CODEWORD_LEN);
+
+	deflate_make_huffman_code(DEFLATE_NUM_LITLEN_SYMS,
+				  MAX_LITLEN_CODEWORD_LEN,
+				  freqs->litlen,
+				  codes->lens.litlen,
+				  codes->codewords.litlen);
+
+	deflate_make_huffman_code(DEFLATE_NUM_OFFSET_SYMS,
+				  MAX_OFFSET_CODEWORD_LEN,
+				  freqs->offset,
+				  codes->lens.offset,
+				  codes->codewords.offset);
+}
+
+/* Initialize c->static_codes.  */
+static void
+deflate_init_static_codes(struct libdeflate_compressor *c)
+{
+	unsigned i;
+
+	for (i = 0; i < 144; i++)
+		c->freqs.litlen[i] = 1 << (9 - 8);
+	for (; i < 256; i++)
+		c->freqs.litlen[i] = 1 << (9 - 9);
+	for (; i < 280; i++)
+		c->freqs.litlen[i] = 1 << (9 - 7);
+	for (; i < 288; i++)
+		c->freqs.litlen[i] = 1 << (9 - 8);
+
+	for (i = 0; i < 32; i++)
+		c->freqs.offset[i] = 1 << (5 - 5);
+
+	deflate_make_huffman_codes(&c->freqs, &c->static_codes);
+}
+
+/* Return the offset slot for the specified match offset.  */
+static forceinline unsigned
+deflate_get_offset_slot(struct libdeflate_compressor *c, unsigned offset)
+{
+#if USE_FULL_OFFSET_SLOT_FAST
+	return c->offset_slot_fast[offset];
+#else
+	if (offset <= 256)
+		return c->offset_slot_fast[offset - 1];
+	else
+		return c->offset_slot_fast[256 + ((offset - 1) >> 7)];
+#endif
+}
+
+/* Write the header fields common to all DEFLATE block types.  */
+static void
+deflate_write_block_header(struct deflate_output_bitstream *os,
+			   bool is_final_block, unsigned block_type)
+{
+	deflate_add_bits(os, is_final_block, 1);
+	deflate_add_bits(os, block_type, 2);
+	deflate_flush_bits(os);
+}
+
+static unsigned
+deflate_compute_precode_items(const u8 lens[restrict],
+			      const unsigned num_lens,
+			      u32 precode_freqs[restrict],
+			      unsigned precode_items[restrict])
+{
+	unsigned *itemptr;
+	unsigned run_start;
+	unsigned run_end;
+	unsigned extra_bits;
+	u8 len;
+
+	memset(precode_freqs, 0,
+	       DEFLATE_NUM_PRECODE_SYMS * sizeof(precode_freqs[0]));
+
+	itemptr = precode_items;
+	run_start = 0;
+	do {
+		/* Find the next run of codeword lengths.  */
+
+		/* len = the length being repeated  */
+		len = lens[run_start];
+
+		/* Extend the run.  */
+		run_end = run_start;
+		do {
+			run_end++;
+		} while (run_end != num_lens && len == lens[run_end]);
+
+		if (len == 0) {
+			/* Run of zeroes.  */
+
+			/* Symbol 18: RLE 11 to 138 zeroes at a time.  */
+			while ((run_end - run_start) >= 11) {
+				extra_bits = MIN((run_end - run_start) - 11, 0x7F);
+				precode_freqs[18]++;
+				*itemptr++ = 18 | (extra_bits << 5);
+				run_start += 11 + extra_bits;
+			}
+
+			/* Symbol 17: RLE 3 to 10 zeroes at a time.  */
+			if ((run_end - run_start) >= 3) {
+				extra_bits = MIN((run_end - run_start) - 3, 0x7);
+				precode_freqs[17]++;
+				*itemptr++ = 17 | (extra_bits << 5);
+				run_start += 3 + extra_bits;
+			}
+		} else {
+
+			/* A run of nonzero lengths. */
+
+			/* Symbol 16: RLE 3 to 6 of the previous length.  */
+			if ((run_end - run_start) >= 4) {
+				precode_freqs[len]++;
+				*itemptr++ = len;
+				run_start++;
+				do {
+					extra_bits = MIN((run_end - run_start) - 3, 0x3);
+					precode_freqs[16]++;
+					*itemptr++ = 16 | (extra_bits << 5);
+					run_start += 3 + extra_bits;
+				} while ((run_end - run_start) >= 3);
+			}
+		}
+
+		/* Output any remaining lengths without RLE.  */
+		while (run_start != run_end) {
+			precode_freqs[len]++;
+			*itemptr++ = len;
+			run_start++;
+		}
+	} while (run_start != num_lens);
+
+	return itemptr - precode_items;
+}
+
+/*
+ * Huffman codeword lengths for dynamic Huffman blocks are compressed using a
+ * separate Huffman code, the "precode", which contains a symbol for each
+ * possible codeword length in the larger code as well as several special
+ * symbols to represent repeated codeword lengths (a form of run-length
+ * encoding).  The precode is itself constructed in canonical form, and its
+ * codeword lengths are represented literally in 19 3-bit fields that
+ * immediately precede the compressed codeword lengths of the larger code.
+ */
+
+/* Precompute the information needed to output Huffman codes. */
+static void
+deflate_precompute_huffman_header(struct libdeflate_compressor *c)
+{
+	/* Compute how many litlen and offset symbols are needed. */
+
+	for (c->num_litlen_syms = DEFLATE_NUM_LITLEN_SYMS;
+	     c->num_litlen_syms > 257;
+	     c->num_litlen_syms--)
+		if (c->codes.lens.litlen[c->num_litlen_syms - 1] != 0)
+			break;
+
+	for (c->num_offset_syms = DEFLATE_NUM_OFFSET_SYMS;
+	     c->num_offset_syms > 1;
+	     c->num_offset_syms--)
+		if (c->codes.lens.offset[c->num_offset_syms - 1] != 0)
+			break;
+
+	/* If we're not using the full set of literal/length codeword lengths,
+	 * then temporarily move the offset codeword lengths over so that the
+	 * literal/length and offset codeword lengths are contiguous. */
+
+	STATIC_ASSERT(offsetof(struct deflate_lens, offset) ==
+		      DEFLATE_NUM_LITLEN_SYMS);
+
+	if (c->num_litlen_syms != DEFLATE_NUM_LITLEN_SYMS) {
+		memmove((u8 *)&c->codes.lens + c->num_litlen_syms,
+			(u8 *)&c->codes.lens + DEFLATE_NUM_LITLEN_SYMS,
+			c->num_offset_syms);
+	}
+
+	/* Compute the "items" (RLE / literal tokens and extra bits) with which
+	 * the codeword lengths in the larger code will be output. */
+	c->num_precode_items =
+		deflate_compute_precode_items((u8 *)&c->codes.lens,
+					      c->num_litlen_syms +
+							c->num_offset_syms,
+					      c->precode_freqs,
+					      c->precode_items);
+
+	/* Build the precode. */
+	STATIC_ASSERT(MAX_PRE_CODEWORD_LEN <= DEFLATE_MAX_PRE_CODEWORD_LEN);
+	deflate_make_huffman_code(DEFLATE_NUM_PRECODE_SYMS,
+				  MAX_PRE_CODEWORD_LEN,
+				  c->precode_freqs, c->precode_lens,
+				  c->precode_codewords);
+
+	/* Count how many precode lengths we actually need to output. */
+	for (c->num_explicit_lens = DEFLATE_NUM_PRECODE_SYMS;
+	     c->num_explicit_lens > 4;
+	     c->num_explicit_lens--)
+		if (c->precode_lens[deflate_precode_lens_permutation[
+						c->num_explicit_lens - 1]] != 0)
+			break;
+
+	/* Restore the offset codeword lengths if needed. */
+	if (c->num_litlen_syms != DEFLATE_NUM_LITLEN_SYMS) {
+		memmove((u8 *)&c->codes.lens + DEFLATE_NUM_LITLEN_SYMS,
+			(u8 *)&c->codes.lens + c->num_litlen_syms,
+			c->num_offset_syms);
+	}
+}
+
+/* Output the Huffman codes. */
+static void
+deflate_write_huffman_header(struct libdeflate_compressor *c,
+			     struct deflate_output_bitstream *os)
+{
+	unsigned i;
+
+	deflate_add_bits(os, c->num_litlen_syms - 257, 5);
+	deflate_add_bits(os, c->num_offset_syms - 1, 5);
+	deflate_add_bits(os, c->num_explicit_lens - 4, 4);
+	deflate_flush_bits(os);
+
+	/* Output the lengths of the codewords in the precode.  */
+	for (i = 0; i < c->num_explicit_lens; i++) {
+		deflate_add_bits(os, c->precode_lens[
+				       deflate_precode_lens_permutation[i]], 3);
+		deflate_flush_bits(os);
+	}
+
+	/* Output the encoded lengths of the codewords in the larger code.  */
+	for (i = 0; i < c->num_precode_items; i++) {
+		unsigned precode_item = c->precode_items[i];
+		unsigned precode_sym = precode_item & 0x1F;
+		deflate_add_bits(os, c->precode_codewords[precode_sym],
+				 c->precode_lens[precode_sym]);
+		if (precode_sym >= 16) {
+			if (precode_sym == 16)
+				deflate_add_bits(os, precode_item >> 5, 2);
+			else if (precode_sym == 17)
+				deflate_add_bits(os, precode_item >> 5, 3);
+			else
+				deflate_add_bits(os, precode_item >> 5, 7);
+		}
+		STATIC_ASSERT(CAN_BUFFER(DEFLATE_MAX_PRE_CODEWORD_LEN + 7));
+		deflate_flush_bits(os);
+	}
+}
+
+static void
+deflate_write_sequences(struct deflate_output_bitstream * restrict os,
+			const struct deflate_codes * restrict codes,
+			const struct deflate_sequence sequences[restrict],
+			const u8 * restrict in_next)
+{
+	const struct deflate_sequence *seq = sequences;
+
+	for (;;) {
+		u32 litrunlen = seq->litrunlen_and_length & 0x7FFFFF;
+		unsigned length = seq->litrunlen_and_length >> 23;
+		unsigned length_slot;
+		unsigned litlen_symbol;
+		unsigned offset_symbol;
+
+		if (litrunlen) {
+		#if 1
+			while (litrunlen >= 4) {
+				unsigned lit0 = in_next[0];
+				unsigned lit1 = in_next[1];
+				unsigned lit2 = in_next[2];
+				unsigned lit3 = in_next[3];
+
+				deflate_add_bits(os, codes->codewords.litlen[lit0],
+						 codes->lens.litlen[lit0]);
+				if (!CAN_BUFFER(2 * MAX_LITLEN_CODEWORD_LEN))
+					deflate_flush_bits(os);
+
+				deflate_add_bits(os, codes->codewords.litlen[lit1],
+						 codes->lens.litlen[lit1]);
+				if (!CAN_BUFFER(4 * MAX_LITLEN_CODEWORD_LEN))
+					deflate_flush_bits(os);
+
+				deflate_add_bits(os, codes->codewords.litlen[lit2],
+						 codes->lens.litlen[lit2]);
+				if (!CAN_BUFFER(2 * MAX_LITLEN_CODEWORD_LEN))
+					deflate_flush_bits(os);
+
+				deflate_add_bits(os, codes->codewords.litlen[lit3],
+						 codes->lens.litlen[lit3]);
+				deflate_flush_bits(os);
+				in_next += 4;
+				litrunlen -= 4;
+			}
+			if (litrunlen-- != 0) {
+				deflate_add_bits(os, codes->codewords.litlen[*in_next],
+						 codes->lens.litlen[*in_next]);
+				if (!CAN_BUFFER(3 * MAX_LITLEN_CODEWORD_LEN))
+					deflate_flush_bits(os);
+				in_next++;
+				if (litrunlen-- != 0) {
+					deflate_add_bits(os, codes->codewords.litlen[*in_next],
+							 codes->lens.litlen[*in_next]);
+					if (!CAN_BUFFER(3 * MAX_LITLEN_CODEWORD_LEN))
+						deflate_flush_bits(os);
+					in_next++;
+					if (litrunlen-- != 0) {
+						deflate_add_bits(os, codes->codewords.litlen[*in_next],
+								 codes->lens.litlen[*in_next]);
+						if (!CAN_BUFFER(3 * MAX_LITLEN_CODEWORD_LEN))
+							deflate_flush_bits(os);
+						in_next++;
+					}
+				}
+				if (CAN_BUFFER(3 * MAX_LITLEN_CODEWORD_LEN))
+					deflate_flush_bits(os);
+			}
+		#else
+			do {
+				unsigned lit = *in_next++;
+				deflate_add_bits(os, codes->codewords.litlen[lit],
+						 codes->lens.litlen[lit]);
+				deflate_flush_bits(os);
+			} while (--litrunlen);
+		#endif
+		}
+
+		if (length == 0)
+			return;
+
+		in_next += length;
+
+		length_slot = seq->length_slot;
+		litlen_symbol = 257 + length_slot;
+
+		/* Litlen symbol  */
+		deflate_add_bits(os, codes->codewords.litlen[litlen_symbol],
+				 codes->lens.litlen[litlen_symbol]);
+
+		/* Extra length bits  */
+		STATIC_ASSERT(CAN_BUFFER(MAX_LITLEN_CODEWORD_LEN +
+					 DEFLATE_MAX_EXTRA_LENGTH_BITS));
+		deflate_add_bits(os, length - deflate_length_slot_base[length_slot],
+				 deflate_extra_length_bits[length_slot]);
+
+		if (!CAN_BUFFER(MAX_LITLEN_CODEWORD_LEN +
+				DEFLATE_MAX_EXTRA_LENGTH_BITS +
+				MAX_OFFSET_CODEWORD_LEN +
+				DEFLATE_MAX_EXTRA_OFFSET_BITS))
+			deflate_flush_bits(os);
+
+		/* Offset symbol  */
+		offset_symbol = seq->offset_symbol;
+		deflate_add_bits(os, codes->codewords.offset[offset_symbol],
+				 codes->lens.offset[offset_symbol]);
+
+		if (!CAN_BUFFER(MAX_OFFSET_CODEWORD_LEN +
+				DEFLATE_MAX_EXTRA_OFFSET_BITS))
+			deflate_flush_bits(os);
+
+		/* Extra offset bits  */
+		deflate_add_bits(os, seq->offset - deflate_offset_slot_base[offset_symbol],
+				 deflate_extra_offset_bits[offset_symbol]);
+
+		deflate_flush_bits(os);
+
+		seq++;
+	}
+}
+
+#if SUPPORT_NEAR_OPTIMAL_PARSING
+/*
+ * Follow the minimum-cost path in the graph of possible match/literal choices
+ * for the current block and write out the matches/literals using the specified
+ * Huffman codes.
+ *
+ * Note: this is slightly duplicated with deflate_write_sequences(), the reason
+ * being that we don't want to waste time translating between intermediate
+ * match/literal representations.
+ */
+static void
+deflate_write_item_list(struct deflate_output_bitstream *os,
+			const struct deflate_codes *codes,
+			struct libdeflate_compressor *c,
+			u32 block_length)
+{
+	struct deflate_optimum_node *cur_node = &c->p.n.optimum_nodes[0];
+	struct deflate_optimum_node * const end_node = &c->p.n.optimum_nodes[block_length];
+	do {
+		unsigned length = cur_node->item & OPTIMUM_LEN_MASK;
+		unsigned offset = cur_node->item >> OPTIMUM_OFFSET_SHIFT;
+		unsigned litlen_symbol;
+		unsigned length_slot;
+		unsigned offset_slot;
+
+		if (length == 1) {
+			/* Literal  */
+			litlen_symbol = offset;
+			deflate_add_bits(os, codes->codewords.litlen[litlen_symbol],
+					 codes->lens.litlen[litlen_symbol]);
+			deflate_flush_bits(os);
+		} else {
+			/* Match length  */
+			length_slot = deflate_length_slot[length];
+			litlen_symbol = 257 + length_slot;
+			deflate_add_bits(os, codes->codewords.litlen[litlen_symbol],
+					 codes->lens.litlen[litlen_symbol]);
+
+			deflate_add_bits(os, length - deflate_length_slot_base[length_slot],
+					 deflate_extra_length_bits[length_slot]);
+
+			if (!CAN_BUFFER(MAX_LITLEN_CODEWORD_LEN +
+					DEFLATE_MAX_EXTRA_LENGTH_BITS +
+					MAX_OFFSET_CODEWORD_LEN +
+					DEFLATE_MAX_EXTRA_OFFSET_BITS))
+				deflate_flush_bits(os);
+
+
+			/* Match offset  */
+			offset_slot = deflate_get_offset_slot(c, offset);
+			deflate_add_bits(os, codes->codewords.offset[offset_slot],
+					 codes->lens.offset[offset_slot]);
+
+			if (!CAN_BUFFER(MAX_OFFSET_CODEWORD_LEN +
+					DEFLATE_MAX_EXTRA_OFFSET_BITS))
+				deflate_flush_bits(os);
+
+			deflate_add_bits(os, offset - deflate_offset_slot_base[offset_slot],
+					 deflate_extra_offset_bits[offset_slot]);
+
+			deflate_flush_bits(os);
+		}
+		cur_node += length;
+	} while (cur_node != end_node);
+}
+#endif /* SUPPORT_NEAR_OPTIMAL_PARSING */
+
+/* Output the end-of-block symbol.  */
+static void
+deflate_write_end_of_block(struct deflate_output_bitstream *os,
+			   const struct deflate_codes *codes)
+{
+	deflate_add_bits(os, codes->codewords.litlen[DEFLATE_END_OF_BLOCK],
+			 codes->lens.litlen[DEFLATE_END_OF_BLOCK]);
+	deflate_flush_bits(os);
+}
+
+static void
+deflate_write_uncompressed_block(struct deflate_output_bitstream *os,
+				 const u8 *data, u16 len,
+				 bool is_final_block)
+{
+	deflate_write_block_header(os, is_final_block,
+				   DEFLATE_BLOCKTYPE_UNCOMPRESSED);
+	deflate_align_bitstream(os);
+
+	if (4 + (u32)len >= os->end - os->next) {
+		os->next = os->end;
+		return;
+	}
+
+	put_unaligned_le16(len, os->next);
+	os->next += 2;
+	put_unaligned_le16(~len, os->next);
+	os->next += 2;
+	memcpy(os->next, data, len);
+	os->next += len;
+}
+
+static void
+deflate_write_uncompressed_blocks(struct deflate_output_bitstream *os,
+				  const u8 *data, size_t data_length,
+				  bool is_final_block)
+{
+	do {
+		u16 len = MIN(data_length, UINT16_MAX);
+
+		deflate_write_uncompressed_block(os, data, len,
+					is_final_block && len == data_length);
+		data += len;
+		data_length -= len;
+	} while (data_length != 0);
+}
+
+/*
+ * Choose the best type of block to use (dynamic Huffman, static Huffman, or
+ * uncompressed), then output it.
+ */
+static void
+deflate_flush_block(struct libdeflate_compressor * restrict c,
+		    struct deflate_output_bitstream * restrict os,
+		    const u8 * restrict block_begin, u32 block_length,
+		    bool is_final_block, bool use_item_list)
+{
+	static const u8 deflate_extra_precode_bits[DEFLATE_NUM_PRECODE_SYMS] = {
+		0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 7,
+	};
+
+	/* Costs are measured in bits */
+	u32 dynamic_cost = 0;
+	u32 static_cost = 0;
+	u32 uncompressed_cost = 0;
+	struct deflate_codes *codes;
+	int block_type;
+	unsigned sym;
+
+	/* Tally the end-of-block symbol. */
+	c->freqs.litlen[DEFLATE_END_OF_BLOCK]++;
+
+	/* Build dynamic Huffman codes. */
+	deflate_make_huffman_codes(&c->freqs, &c->codes);
+
+	/* Account for the cost of sending dynamic Huffman codes. */
+	deflate_precompute_huffman_header(c);
+	dynamic_cost += 5 + 5 + 4 + (3 * c->num_explicit_lens);
+	for (sym = 0; sym < DEFLATE_NUM_PRECODE_SYMS; sym++) {
+		u32 extra = deflate_extra_precode_bits[sym];
+		dynamic_cost += c->precode_freqs[sym] *
+				(extra + c->precode_lens[sym]);
+	}
+
+	/* Account for the cost of encoding literals. */
+	for (sym = 0; sym < 256; sym++) {
+		dynamic_cost += c->freqs.litlen[sym] *
+				c->codes.lens.litlen[sym];
+	}
+	for (sym = 0; sym < 144; sym++)
+		static_cost += c->freqs.litlen[sym] * 8;
+	for (; sym < 256; sym++)
+		static_cost += c->freqs.litlen[sym] * 9;
+
+	/* Account for the cost of encoding the end-of-block symbol. */
+	dynamic_cost += c->codes.lens.litlen[256];
+	static_cost += 7;
+
+	/* Account for the cost of encoding lengths. */
+	for (sym = 257; sym < 257 + ARRAY_LEN(deflate_extra_length_bits); sym++) {
+		u32 extra = deflate_extra_length_bits[sym - 257];
+		dynamic_cost += c->freqs.litlen[sym] *
+				(extra + c->codes.lens.litlen[sym]);
+		static_cost += c->freqs.litlen[sym] *
+				(extra + c->static_codes.lens.litlen[sym]);
+	}
+
+	/* Account for the cost of encoding offsets. */
+	for (sym = 0; sym < ARRAY_LEN(deflate_extra_offset_bits); sym++) {
+		u32 extra = deflate_extra_offset_bits[sym];
+		dynamic_cost += c->freqs.offset[sym] *
+				(extra + c->codes.lens.offset[sym]);
+		static_cost += c->freqs.offset[sym] * (extra + 5);
+	}
+
+	/* Compute the cost of using uncompressed blocks. */
+	uncompressed_cost += (-(os->bitcount + 3) & 7) + 32 +
+			     (40 * (DIV_ROUND_UP(block_length,
+						 UINT16_MAX) - 1)) +
+			     (8 * block_length);
+
+	/* Choose the cheapest block type. */
+	if (dynamic_cost < MIN(static_cost, uncompressed_cost)) {
+		block_type = DEFLATE_BLOCKTYPE_DYNAMIC_HUFFMAN;
+		codes = &c->codes;
+	} else if (static_cost < uncompressed_cost) {
+		block_type = DEFLATE_BLOCKTYPE_STATIC_HUFFMAN;
+		codes = &c->static_codes;
+	} else {
+		block_type = DEFLATE_BLOCKTYPE_UNCOMPRESSED;
+	}
+
+	/* Now actually output the block. */
+
+	if (block_type == DEFLATE_BLOCKTYPE_UNCOMPRESSED) {
+		/* Note: the length being flushed may exceed the maximum length
+		 * of an uncompressed block (65535 bytes).  Therefore, more than
+		 * one uncompressed block might be needed. */
+		deflate_write_uncompressed_blocks(os, block_begin, block_length,
+						  is_final_block);
+	} else {
+		/* Output the block header. */
+		deflate_write_block_header(os, is_final_block, block_type);
+
+		/* Output the Huffman codes (dynamic Huffman blocks only). */
+		if (block_type == DEFLATE_BLOCKTYPE_DYNAMIC_HUFFMAN)
+			deflate_write_huffman_header(c, os);
+
+		/* Output the literals, matches, and end-of-block symbol. */
+	#if SUPPORT_NEAR_OPTIMAL_PARSING
+		if (use_item_list)
+			deflate_write_item_list(os, codes, c, block_length);
+		else
+	#endif
+			deflate_write_sequences(os, codes, c->p.g.sequences,
+						block_begin);
+		deflate_write_end_of_block(os, codes);
+	}
+}
+
+static forceinline void
+deflate_choose_literal(struct libdeflate_compressor *c, unsigned literal,
+		       u32 *litrunlen_p)
+{
+	c->freqs.litlen[literal]++;
+	++*litrunlen_p;
+}
+
+static forceinline void
+deflate_choose_match(struct libdeflate_compressor *c,
+		     unsigned length, unsigned offset,
+		     u32 *litrunlen_p, struct deflate_sequence **next_seq_p)
+{
+	struct deflate_sequence *seq = *next_seq_p;
+	unsigned length_slot = deflate_length_slot[length];
+	unsigned offset_slot = deflate_get_offset_slot(c, offset);
+
+	c->freqs.litlen[257 + length_slot]++;
+	c->freqs.offset[offset_slot]++;
+
+	seq->litrunlen_and_length = ((u32)length << 23) | *litrunlen_p;
+	seq->offset = offset;
+	seq->length_slot = length_slot;
+	seq->offset_symbol = offset_slot;
+
+	*litrunlen_p = 0;
+	*next_seq_p = seq + 1;
+}
+
+static forceinline void
+deflate_finish_sequence(struct deflate_sequence *seq, u32 litrunlen)
+{
+	seq->litrunlen_and_length = litrunlen; /* length = 0 */
+}
+
+/******************************************************************************/
+
+/*
+ * Block splitting algorithm.  The problem is to decide when it is worthwhile to
+ * start a new block with new Huffman codes.  There is a theoretically optimal
+ * solution: recursively consider every possible block split, considering the
+ * exact cost of each block, and choose the minimum cost approach.  But this is
+ * far too slow.  Instead, as an approximation, we can count symbols and after
+ * every N symbols, compare the expected distribution of symbols based on the
+ * previous data with the actual distribution.  If they differ "by enough", then
+ * start a new block.
+ *
+ * As an optimization and heuristic, we don't distinguish between every symbol
+ * but rather we combine many symbols into a single "observation type".  For
+ * literals we only look at the high bits and low bits, and for matches we only
+ * look at whether the match is long or not.  The assumption is that for typical
+ * "real" data, places that are good block boundaries will tend to be noticeable
+ * based only on changes in these aggregate frequencies, without looking for
+ * subtle differences in individual symbols.  For example, a change from ASCII
+ * bytes to non-ASCII bytes, or from few matches (generally less compressible)
+ * to many matches (generally more compressible), would be easily noticed based
+ * on the aggregates.
+ *
+ * For determining whether the frequency distributions are "different enough" to
+ * start a new block, the simply heuristic of splitting when the sum of absolute
+ * differences exceeds a constant seems to be good enough.  We also add a number
+ * proportional to the block length so that the algorithm is more likely to end
+ * long blocks than short blocks.  This reflects the general expectation that it
+ * will become increasingly beneficial to start a new block as the current
+ * block grows longer.
+ *
+ * Finally, for an approximation, it is not strictly necessary that the exact
+ * symbols being used are considered.  With "near-optimal parsing", for example,
+ * the actual symbols that will be used are unknown until after the block
+ * boundary is chosen and the block has been optimized.  Since the final choices
+ * cannot be used, we can use preliminary "greedy" choices instead.
+ */
+
+/* Initialize the block split statistics when starting a new block. */
+static void
+init_block_split_stats(struct block_split_stats *stats)
+{
+	int i;
+
+	for (i = 0; i < NUM_OBSERVATION_TYPES; i++) {
+		stats->new_observations[i] = 0;
+		stats->observations[i] = 0;
+	}
+	stats->num_new_observations = 0;
+	stats->num_observations = 0;
+}
+
+/* Literal observation.  Heuristic: use the top 2 bits and low 1 bits of the
+ * literal, for 8 possible literal observation types.  */
+static forceinline void
+observe_literal(struct block_split_stats *stats, u8 lit)
+{
+	stats->new_observations[((lit >> 5) & 0x6) | (lit & 1)]++;
+	stats->num_new_observations++;
+}
+
+/* Match observation.  Heuristic: use one observation type for "short match" and
+ * one observation type for "long match".  */
+static forceinline void
+observe_match(struct block_split_stats *stats, unsigned length)
+{
+	stats->new_observations[NUM_LITERAL_OBSERVATION_TYPES + (length >= 9)]++;
+	stats->num_new_observations++;
+}
+
+static bool
+do_end_block_check(struct block_split_stats *stats, u32 block_length)
+{
+	int i;
+
+	if (stats->num_observations > 0) {
+
+		/* Note: to avoid slow divisions, we do not divide by
+		 * 'num_observations', but rather do all math with the numbers
+		 * multiplied by 'num_observations'.  */
+		u32 total_delta = 0;
+		for (i = 0; i < NUM_OBSERVATION_TYPES; i++) {
+			u32 expected = stats->observations[i] * stats->num_new_observations;
+			u32 actual = stats->new_observations[i] * stats->num_observations;
+			u32 delta = (actual > expected) ? actual - expected :
+							  expected - actual;
+			total_delta += delta;
+		}
+
+		/* Ready to end the block? */
+		if (total_delta + (block_length / 4096) * stats->num_observations >=
+		    NUM_OBSERVATIONS_PER_BLOCK_CHECK * 200 / 512 * stats->num_observations)
+			return true;
+	}
+
+	for (i = 0; i < NUM_OBSERVATION_TYPES; i++) {
+		stats->num_observations += stats->new_observations[i];
+		stats->observations[i] += stats->new_observations[i];
+		stats->new_observations[i] = 0;
+	}
+	stats->num_new_observations = 0;
+	return false;
+}
+
+static forceinline bool
+should_end_block(struct block_split_stats *stats,
+		 const u8 *in_block_begin, const u8 *in_next, const u8 *in_end)
+{
+	/* Ready to check block split statistics? */
+	if (stats->num_new_observations < NUM_OBSERVATIONS_PER_BLOCK_CHECK ||
+	    in_next - in_block_begin < MIN_BLOCK_LENGTH ||
+	    in_end - in_next < MIN_BLOCK_LENGTH)
+		return false;
+
+	return do_end_block_check(stats, in_next - in_block_begin);
+}
+
+/******************************************************************************/
+
+/*
+ * This is the level 0 "compressor".  It always outputs uncompressed blocks.
+ */
+static size_t
+deflate_compress_none(struct libdeflate_compressor * restrict c,
+		      const u8 * restrict in, size_t in_nbytes,
+		      u8 * restrict out, size_t out_nbytes_avail)
+{
+	struct deflate_output_bitstream os;
+
+	deflate_init_output(&os, out, out_nbytes_avail);
+
+	deflate_write_uncompressed_blocks(&os, in, in_nbytes, true);
+
+	return deflate_flush_output(&os);
+}
+
+/*
+ * This is the "greedy" DEFLATE compressor. It always chooses the longest match.
+ */
+static size_t
+deflate_compress_greedy(struct libdeflate_compressor * restrict c,
+			const u8 * restrict in, size_t in_nbytes,
+			u8 * restrict out, size_t out_nbytes_avail)
+{
+	const u8 *in_next = in;
+	const u8 *in_end = in_next + in_nbytes;
+	struct deflate_output_bitstream os;
+	const u8 *in_cur_base = in_next;
+	unsigned max_len = DEFLATE_MAX_MATCH_LEN;
+	unsigned nice_len = MIN(c->nice_match_length, max_len);
+	u32 next_hashes[2] = {0, 0};
+
+	deflate_init_output(&os, out, out_nbytes_avail);
+	hc_matchfinder_init(&c->p.g.hc_mf);
+
+	do {
+		/* Starting a new DEFLATE block.  */
+
+		const u8 * const in_block_begin = in_next;
+		const u8 * const in_max_block_end =
+			in_next + MIN(in_end - in_next, SOFT_MAX_BLOCK_LENGTH);
+		u32 litrunlen = 0;
+		struct deflate_sequence *next_seq = c->p.g.sequences;
+
+		init_block_split_stats(&c->split_stats);
+		deflate_reset_symbol_frequencies(c);
+
+		do {
+			u32 length;
+			u32 offset;
+
+			/* Decrease the maximum and nice match lengths if we're
+			 * approaching the end of the input buffer.  */
+			if (unlikely(max_len > in_end - in_next)) {
+				max_len = in_end - in_next;
+				nice_len = MIN(nice_len, max_len);
+			}
+
+			length = hc_matchfinder_longest_match(&c->p.g.hc_mf,
+							      &in_cur_base,
+							      in_next,
+							      DEFLATE_MIN_MATCH_LEN - 1,
+							      max_len,
+							      nice_len,
+							      c->max_search_depth,
+							      next_hashes,
+							      &offset);
+
+			if (length >= DEFLATE_MIN_MATCH_LEN) {
+				/* Match found.  */
+				deflate_choose_match(c, length, offset,
+						     &litrunlen, &next_seq);
+				observe_match(&c->split_stats, length);
+				in_next = hc_matchfinder_skip_positions(&c->p.g.hc_mf,
+									&in_cur_base,
+									in_next + 1,
+									in_end,
+									length - 1,
+									next_hashes);
+			} else {
+				/* No match found.  */
+				deflate_choose_literal(c, *in_next, &litrunlen);
+				observe_literal(&c->split_stats, *in_next);
+				in_next++;
+			}
+
+			/* Check if it's time to output another block.  */
+		} while (in_next < in_max_block_end &&
+			 !should_end_block(&c->split_stats, in_block_begin, in_next, in_end));
+
+		deflate_finish_sequence(next_seq, litrunlen);
+		deflate_flush_block(c, &os, in_block_begin,
+				    in_next - in_block_begin,
+				    in_next == in_end, false);
+	} while (in_next != in_end);
+
+	return deflate_flush_output(&os);
+}
+
+/*
+ * This is the "lazy" DEFLATE compressor.  Before choosing a match, it checks to
+ * see if there's a longer match at the next position.  If yes, it outputs a
+ * literal and continues to the next position.  If no, it outputs the match.
+ */
+static size_t
+deflate_compress_lazy(struct libdeflate_compressor * restrict c,
+		      const u8 * restrict in, size_t in_nbytes,
+		      u8 * restrict out, size_t out_nbytes_avail)
+{
+	const u8 *in_next = in;
+	const u8 *in_end = in_next + in_nbytes;
+	struct deflate_output_bitstream os;
+	const u8 *in_cur_base = in_next;
+	unsigned max_len = DEFLATE_MAX_MATCH_LEN;
+	unsigned nice_len = MIN(c->nice_match_length, max_len);
+	u32 next_hashes[2] = {0, 0};
+
+	deflate_init_output(&os, out, out_nbytes_avail);
+	hc_matchfinder_init(&c->p.g.hc_mf);
+
+	do {
+		/* Starting a new DEFLATE block.  */
+
+		const u8 * const in_block_begin = in_next;
+		const u8 * const in_max_block_end =
+			in_next + MIN(in_end - in_next, SOFT_MAX_BLOCK_LENGTH);
+		u32 litrunlen = 0;
+		struct deflate_sequence *next_seq = c->p.g.sequences;
+
+		init_block_split_stats(&c->split_stats);
+		deflate_reset_symbol_frequencies(c);
+
+		do {
+			unsigned cur_len;
+			unsigned cur_offset;
+			unsigned next_len;
+			unsigned next_offset;
+
+			if (unlikely(in_end - in_next < DEFLATE_MAX_MATCH_LEN)) {
+				max_len = in_end - in_next;
+				nice_len = MIN(nice_len, max_len);
+			}
+
+			/* Find the longest match at the current position.  */
+			cur_len = hc_matchfinder_longest_match(&c->p.g.hc_mf,
+							       &in_cur_base,
+							       in_next,
+							       DEFLATE_MIN_MATCH_LEN - 1,
+							       max_len,
+							       nice_len,
+							       c->max_search_depth,
+							       next_hashes,
+							       &cur_offset);
+			in_next += 1;
+
+			if (cur_len < DEFLATE_MIN_MATCH_LEN) {
+				/* No match found.  Choose a literal.  */
+				deflate_choose_literal(c, *(in_next - 1), &litrunlen);
+				observe_literal(&c->split_stats, *(in_next - 1));
+				continue;
+			}
+
+		have_cur_match:
+			observe_match(&c->split_stats, cur_len);
+
+			/* We have a match at the current position.  */
+
+			/* If the current match is very long, choose it
+			 * immediately.  */
+			if (cur_len >= nice_len) {
+				deflate_choose_match(c, cur_len, cur_offset,
+						     &litrunlen, &next_seq);
+				in_next = hc_matchfinder_skip_positions(&c->p.g.hc_mf,
+									&in_cur_base,
+									in_next,
+									in_end,
+									cur_len - 1,
+									next_hashes);
+				continue;
+			}
+
+			/*
+			 * Try to find a match at the next position.
+			 *
+			 * Note: since we already have a match at the *current*
+			 * position, we use only half the 'max_search_depth'
+			 * when checking the *next* position.  This is a useful
+			 * trade-off because it's more worthwhile to use a
+			 * greater search depth on the initial match.
+			 *
+			 * Note: it's possible to structure the code such that
+			 * there's only one call to longest_match(), which
+			 * handles both the "find the initial match" and "try to
+			 * find a longer match" cases.  However, it is faster to
+			 * have two call sites, with longest_match() inlined at
+			 * each.
+			 */
+			if (unlikely(in_end - in_next < DEFLATE_MAX_MATCH_LEN)) {
+				max_len = in_end - in_next;
+				nice_len = MIN(nice_len, max_len);
+			}
+			next_len = hc_matchfinder_longest_match(&c->p.g.hc_mf,
+								&in_cur_base,
+								in_next,
+								cur_len,
+								max_len,
+								nice_len,
+								c->max_search_depth / 2,
+								next_hashes,
+								&next_offset);
+			in_next += 1;
+
+			if (next_len > cur_len) {
+				/* Found a longer match at the next position.
+				 * Output a literal.  Then the next match
+				 * becomes the current match.  */
+				deflate_choose_literal(c, *(in_next - 2), &litrunlen);
+				cur_len = next_len;
+				cur_offset = next_offset;
+				goto have_cur_match;
+			}
+
+			/* No longer match at the next position.
+			 * Output the current match.  */
+			deflate_choose_match(c, cur_len, cur_offset,
+					     &litrunlen, &next_seq);
+			in_next = hc_matchfinder_skip_positions(&c->p.g.hc_mf,
+								&in_cur_base,
+								in_next,
+								in_end,
+								cur_len - 2,
+								next_hashes);
+
+			/* Check if it's time to output another block.  */
+		} while (in_next < in_max_block_end &&
+			 !should_end_block(&c->split_stats, in_block_begin, in_next, in_end));
+
+		deflate_finish_sequence(next_seq, litrunlen);
+		deflate_flush_block(c, &os, in_block_begin,
+				    in_next - in_block_begin,
+				    in_next == in_end, false);
+	} while (in_next != in_end);
+
+	return deflate_flush_output(&os);
+}
+
+#if SUPPORT_NEAR_OPTIMAL_PARSING
+
+/*
+ * Follow the minimum-cost path in the graph of possible match/literal choices
+ * for the current block and compute the frequencies of the Huffman symbols that
+ * would be needed to output those matches and literals.
+ */
+static void
+deflate_tally_item_list(struct libdeflate_compressor *c, u32 block_length)
+{
+	struct deflate_optimum_node *cur_node = &c->p.n.optimum_nodes[0];
+	struct deflate_optimum_node *end_node = &c->p.n.optimum_nodes[block_length];
+	do {
+		unsigned length = cur_node->item & OPTIMUM_LEN_MASK;
+		unsigned offset = cur_node->item >> OPTIMUM_OFFSET_SHIFT;
+
+		if (length == 1) {
+			/* Literal  */
+			c->freqs.litlen[offset]++;
+		} else {
+			/* Match  */
+			c->freqs.litlen[257 + deflate_length_slot[length]]++;
+			c->freqs.offset[deflate_get_offset_slot(c, offset)]++;
+		}
+		cur_node += length;
+	} while (cur_node != end_node);
+}
+
+/* Set the current cost model from the codeword lengths specified in @lens.  */
+static void
+deflate_set_costs_from_codes(struct libdeflate_compressor *c,
+			     const struct deflate_lens *lens)
+{
+	unsigned i;
+
+	/* Literals  */
+	for (i = 0; i < DEFLATE_NUM_LITERALS; i++) {
+		u32 bits = (lens->litlen[i] ? lens->litlen[i] : LITERAL_NOSTAT_BITS);
+		c->p.n.costs.literal[i] = bits << COST_SHIFT;
+	}
+
+	/* Lengths  */
+	for (i = DEFLATE_MIN_MATCH_LEN; i <= DEFLATE_MAX_MATCH_LEN; i++) {
+		unsigned length_slot = deflate_length_slot[i];
+		unsigned litlen_sym = 257 + length_slot;
+		u32 bits = (lens->litlen[litlen_sym] ? lens->litlen[litlen_sym] : LENGTH_NOSTAT_BITS);
+		bits += deflate_extra_length_bits[length_slot];
+		c->p.n.costs.length[i] = bits << COST_SHIFT;
+	}
+
+	/* Offset slots  */
+	for (i = 0; i < ARRAY_LEN(deflate_offset_slot_base); i++) {
+		u32 bits = (lens->offset[i] ? lens->offset[i] : OFFSET_NOSTAT_BITS);
+		bits += deflate_extra_offset_bits[i];
+		c->p.n.costs.offset_slot[i] = bits << COST_SHIFT;
+	}
+}
+
+static forceinline u32
+deflate_default_literal_cost(unsigned literal)
+{
+	STATIC_ASSERT(COST_SHIFT == 3);
+	/* 66 is 8.25 bits/symbol  */
+	return 66;
+}
+
+static forceinline u32
+deflate_default_length_slot_cost(unsigned length_slot)
+{
+	STATIC_ASSERT(COST_SHIFT == 3);
+	/* 60 is 7.5 bits/symbol  */
+	return 60 + ((u32)deflate_extra_length_bits[length_slot] << COST_SHIFT);
+}
+
+static forceinline u32
+deflate_default_offset_slot_cost(unsigned offset_slot)
+{
+	STATIC_ASSERT(COST_SHIFT == 3);
+	/* 39 is 4.875 bits/symbol  */
+	return 39 + ((u32)deflate_extra_offset_bits[offset_slot] << COST_SHIFT);
+}
+
+/*
+ * Set default symbol costs for the first block's first optimization pass.
+ *
+ * It works well to assume that each symbol is equally probable.  This results
+ * in each symbol being assigned a cost of (-log2(1.0/num_syms) * (1 <<
+ * COST_SHIFT)) where 'num_syms' is the number of symbols in the corresponding
+ * alphabet.  However, we intentionally bias the parse towards matches rather
+ * than literals by using a slightly lower default cost for length symbols than
+ * for literals.  This often improves the compression ratio slightly.
+ */
+static void
+deflate_set_default_costs(struct libdeflate_compressor *c)
+{
+	unsigned i;
+
+	/* Literals  */
+	for (i = 0; i < DEFLATE_NUM_LITERALS; i++)
+		c->p.n.costs.literal[i] = deflate_default_literal_cost(i);
+
+	/* Lengths  */
+	for (i = DEFLATE_MIN_MATCH_LEN; i <= DEFLATE_MAX_MATCH_LEN; i++)
+		c->p.n.costs.length[i] = deflate_default_length_slot_cost(
+						deflate_length_slot[i]);
+
+	/* Offset slots  */
+	for (i = 0; i < ARRAY_LEN(deflate_offset_slot_base); i++)
+		c->p.n.costs.offset_slot[i] = deflate_default_offset_slot_cost(i);
+}
+
+static forceinline void
+deflate_adjust_cost(u32 *cost_p, u32 default_cost)
+{
+	*cost_p += ((s32)default_cost - (s32)*cost_p) >> 1;
+}
+
+/*
+ * Adjust the costs when beginning a new block.
+ *
+ * Since the current costs have been optimized for the data, it's undesirable to
+ * throw them away and start over with the default costs.  At the same time, we
+ * don't want to bias the parse by assuming that the next block will be similar
+ * to the current block.  As a compromise, make the costs closer to the
+ * defaults, but don't simply set them to the defaults.
+ */
+static void
+deflate_adjust_costs(struct libdeflate_compressor *c)
+{
+	unsigned i;
+
+	/* Literals  */
+	for (i = 0; i < DEFLATE_NUM_LITERALS; i++)
+		deflate_adjust_cost(&c->p.n.costs.literal[i],
+				    deflate_default_literal_cost(i));
+
+	/* Lengths  */
+	for (i = DEFLATE_MIN_MATCH_LEN; i <= DEFLATE_MAX_MATCH_LEN; i++)
+		deflate_adjust_cost(&c->p.n.costs.length[i],
+				    deflate_default_length_slot_cost(
+						deflate_length_slot[i]));
+
+	/* Offset slots  */
+	for (i = 0; i < ARRAY_LEN(deflate_offset_slot_base); i++)
+		deflate_adjust_cost(&c->p.n.costs.offset_slot[i],
+				    deflate_default_offset_slot_cost(i));
+}
+
+/*
+ * Find the minimum-cost path through the graph of possible match/literal
+ * choices for this block.
+ *
+ * We find the minimum cost path from 'c->p.n.optimum_nodes[0]', which
+ * represents the node at the beginning of the block, to
+ * 'c->p.n.optimum_nodes[block_length]', which represents the node at the end of
+ * the block.  Edge costs are evaluated using the cost model 'c->p.n.costs'.
+ *
+ * The algorithm works backwards, starting at the end node and proceeding
+ * backwards one node at a time.  At each node, the minimum cost to reach the
+ * end node is computed and the match/literal choice that begins that path is
+ * saved.
+ */
+static void
+deflate_find_min_cost_path(struct libdeflate_compressor *c,
+			   const u32 block_length,
+			   const struct lz_match *cache_ptr)
+{
+	struct deflate_optimum_node *end_node = &c->p.n.optimum_nodes[block_length];
+	struct deflate_optimum_node *cur_node = end_node;
+
+	cur_node->cost_to_end = 0;
+	do {
+		unsigned num_matches;
+		unsigned literal;
+		u32 best_cost_to_end;
+
+		cur_node--;
+		cache_ptr--;
+
+		num_matches = cache_ptr->length;
+		literal = cache_ptr->offset;
+
+		/* It's always possible to choose a literal.  */
+		best_cost_to_end = c->p.n.costs.literal[literal] +
+				   (cur_node + 1)->cost_to_end;
+		cur_node->item = ((u32)literal << OPTIMUM_OFFSET_SHIFT) | 1;
+
+		/* Also consider matches if there are any.  */
+		if (num_matches) {
+			const struct lz_match *match;
+			unsigned len;
+			unsigned offset;
+			unsigned offset_slot;
+			u32 offset_cost;
+			u32 cost_to_end;
+
+			/*
+			 * Consider each length from the minimum
+			 * (DEFLATE_MIN_MATCH_LEN) to the length of the longest
+			 * match found at this position.  For each length, we
+			 * consider only the smallest offset for which that
+			 * length is available.  Although this is not guaranteed
+			 * to be optimal due to the possibility of a larger
+			 * offset costing less than a smaller offset to code,
+			 * this is a very useful heuristic.
+			 */
+			match = cache_ptr - num_matches;
+			len = DEFLATE_MIN_MATCH_LEN;
+			do {
+				offset = match->offset;
+				offset_slot = deflate_get_offset_slot(c, offset);
+				offset_cost = c->p.n.costs.offset_slot[offset_slot];
+				do {
+					cost_to_end = offset_cost +
+						      c->p.n.costs.length[len] +
+						      (cur_node + len)->cost_to_end;
+					if (cost_to_end < best_cost_to_end) {
+						best_cost_to_end = cost_to_end;
+						cur_node->item = ((u32)offset << OPTIMUM_OFFSET_SHIFT) | len;
+					}
+				} while (++len <= match->length);
+			} while (++match != cache_ptr);
+			cache_ptr -= num_matches;
+		}
+		cur_node->cost_to_end = best_cost_to_end;
+	} while (cur_node != &c->p.n.optimum_nodes[0]);
+}
+
+/*
+ * Choose the literal/match sequence to use for the current block.  The basic
+ * algorithm finds a minimum-cost path through the block's graph of
+ * literal/match choices, given a cost model.  However, the cost of each symbol
+ * is unknown until the Huffman codes have been built, but at the same time the
+ * Huffman codes depend on the frequencies of chosen symbols.  Consequently,
+ * multiple passes must be used to try to approximate an optimal solution.  The
+ * first pass uses default costs, mixed with the costs from the previous block
+ * if any.  Later passes use the Huffman codeword lengths from the previous pass
+ * as the costs.
+ */
+static void
+deflate_optimize_block(struct libdeflate_compressor *c, u32 block_length,
+		       const struct lz_match *cache_ptr, bool is_first_block)
+{
+	unsigned num_passes_remaining = c->p.n.num_optim_passes;
+	u32 i;
+
+	/* Force the block to really end at the desired length, even if some
+	 * matches extend beyond it. */
+	for (i = block_length; i <= MIN(block_length - 1 + DEFLATE_MAX_MATCH_LEN,
+					ARRAY_LEN(c->p.n.optimum_nodes) - 1); i++)
+		c->p.n.optimum_nodes[i].cost_to_end = 0x80000000;
+
+	/* Set the initial costs. */
+	if (is_first_block)
+		deflate_set_default_costs(c);
+	else
+		deflate_adjust_costs(c);
+
+	for (;;) {
+		/* Find the minimum cost path for this pass. */
+		deflate_find_min_cost_path(c, block_length, cache_ptr);
+
+		/* Compute frequencies of the chosen symbols. */
+		deflate_reset_symbol_frequencies(c);
+		deflate_tally_item_list(c, block_length);
+
+		if (--num_passes_remaining == 0)
+			break;
+
+		/* At least one optimization pass remains; update the costs. */
+		deflate_make_huffman_codes(&c->freqs, &c->codes);
+		deflate_set_costs_from_codes(c, &c->codes.lens);
+	}
+}
+
+/*
+ * This is the "near-optimal" DEFLATE compressor.  It computes the optimal
+ * representation of each DEFLATE block using a minimum-cost path search over
+ * the graph of possible match/literal choices for that block, assuming a
+ * certain cost for each Huffman symbol.
+ *
+ * For several reasons, the end result is not guaranteed to be optimal:
+ *
+ * - Nonoptimal choice of blocks
+ * - Heuristic limitations on which matches are actually considered
+ * - Symbol costs are unknown until the symbols have already been chosen
+ *   (so iterative optimization must be used)
+ */
+static size_t
+deflate_compress_near_optimal(struct libdeflate_compressor * restrict c,
+			      const u8 * restrict in, size_t in_nbytes,
+			      u8 * restrict out, size_t out_nbytes_avail)
+{
+	const u8 *in_next = in;
+	const u8 *in_end = in_next + in_nbytes;
+	struct deflate_output_bitstream os;
+	const u8 *in_cur_base = in_next;
+	const u8 *in_next_slide = in_next + MIN(in_end - in_next, MATCHFINDER_WINDOW_SIZE);
+	unsigned max_len = DEFLATE_MAX_MATCH_LEN;
+	unsigned nice_len = MIN(c->nice_match_length, max_len);
+	u32 next_hashes[2] = {0, 0};
+
+	deflate_init_output(&os, out, out_nbytes_avail);
+	bt_matchfinder_init(&c->p.n.bt_mf);
+
+	do {
+		/* Starting a new DEFLATE block.  */
+
+		struct lz_match *cache_ptr = c->p.n.match_cache;
+		const u8 * const in_block_begin = in_next;
+		const u8 * const in_max_block_end =
+			in_next + MIN(in_end - in_next, SOFT_MAX_BLOCK_LENGTH);
+		const u8 *next_observation = in_next;
+
+		init_block_split_stats(&c->split_stats);
+
+		/*
+		 * Find matches until we decide to end the block.  We end the
+		 * block if any of the following is true:
+		 *
+		 * (1) Maximum block length has been reached
+		 * (2) Match catch may overflow.
+		 * (3) Block split heuristic says to split now.
+		 */
+		do {
+			struct lz_match *matches;
+			unsigned best_len;
+
+			/* Slide the window forward if needed.  */
+			if (in_next == in_next_slide) {
+				bt_matchfinder_slide_window(&c->p.n.bt_mf);
+				in_cur_base = in_next;
+				in_next_slide = in_next + MIN(in_end - in_next,
+							      MATCHFINDER_WINDOW_SIZE);
+			}
+
+			/* Decrease the maximum and nice match lengths if we're
+			 * approaching the end of the input buffer.  */
+			if (unlikely(max_len > in_end - in_next)) {
+				max_len = in_end - in_next;
+				nice_len = MIN(nice_len, max_len);
+			}
+
+			/*
+			 * Find matches with the current position using the
+			 * binary tree matchfinder and save them in
+			 * 'match_cache'.
+			 *
+			 * Note: the binary tree matchfinder is more suited for
+			 * optimal parsing than the hash chain matchfinder.  The
+			 * reasons for this include:
+			 *
+			 * - The binary tree matchfinder can find more matches
+			 *   in the same number of steps.
+			 * - One of the major advantages of hash chains is that
+			 *   skipping positions (not searching for matches at
+			 *   them) is faster; however, with optimal parsing we
+			 *   search for matches at almost all positions, so this
+			 *   advantage of hash chains is negated.
+			 */
+			matches = cache_ptr;
+			best_len = 0;
+			if (likely(max_len >= BT_MATCHFINDER_REQUIRED_NBYTES)) {
+				cache_ptr = bt_matchfinder_get_matches(&c->p.n.bt_mf,
+								       in_cur_base,
+								       in_next - in_cur_base,
+								       max_len,
+								       nice_len,
+								       c->max_search_depth,
+								       next_hashes,
+								       &best_len,
+								       matches);
+			}
+
+			if (in_next >= next_observation) {
+				if (best_len >= 4) {
+					observe_match(&c->split_stats, best_len);
+					next_observation = in_next + best_len;
+				} else {
+					observe_literal(&c->split_stats, *in_next);
+					next_observation = in_next + 1;
+				}
+			}
+
+			cache_ptr->length = cache_ptr - matches;
+			cache_ptr->offset = *in_next;
+			in_next++;
+			cache_ptr++;
+
+			/*
+			 * If there was a very long match found, don't cache any
+			 * matches for the bytes covered by that match.  This
+			 * avoids degenerate behavior when compressing highly
+			 * redundant data, where the number of matches can be
+			 * very large.
+			 *
+			 * This heuristic doesn't actually hurt the compression
+			 * ratio very much.  If there's a long match, then the
+			 * data must be highly compressible, so it doesn't
+			 * matter much what we do.
+			 */
+			if (best_len >= DEFLATE_MIN_MATCH_LEN && best_len >= nice_len) {
+				--best_len;
+				do {
+					if (in_next == in_next_slide) {
+						bt_matchfinder_slide_window(&c->p.n.bt_mf);
+						in_cur_base = in_next;
+						in_next_slide = in_next + MIN(in_end - in_next,
+									      MATCHFINDER_WINDOW_SIZE);
+					}
+					if (unlikely(max_len > in_end - in_next)) {
+						max_len = in_end - in_next;
+						nice_len = MIN(nice_len, max_len);
+					}
+					if (max_len >= BT_MATCHFINDER_REQUIRED_NBYTES) {
+						bt_matchfinder_skip_position(&c->p.n.bt_mf,
+									     in_cur_base,
+									     in_next - in_cur_base,
+									     nice_len,
+									     c->max_search_depth,
+									     next_hashes);
+					}
+					cache_ptr->length = 0;
+					cache_ptr->offset = *in_next;
+					in_next++;
+					cache_ptr++;
+				} while (--best_len);
+			}
+		} while (in_next < in_max_block_end &&
+			 cache_ptr < &c->p.n.match_cache[CACHE_LENGTH] &&
+			 !should_end_block(&c->split_stats, in_block_begin, in_next, in_end));
+
+		/* All the matches for this block have been cached.  Now choose
+		 * the sequence of items to output and flush the block.  */
+		deflate_optimize_block(c, in_next - in_block_begin, cache_ptr,
+				       in_block_begin == in);
+		deflate_flush_block(c, &os, in_block_begin, in_next - in_block_begin,
+				    in_next == in_end, true);
+	} while (in_next != in_end);
+
+	return deflate_flush_output(&os);
+}
+
+#endif /* SUPPORT_NEAR_OPTIMAL_PARSING */
+
+/* Initialize c->offset_slot_fast.  */
+static void
+deflate_init_offset_slot_fast(struct libdeflate_compressor *c)
+{
+	unsigned offset_slot;
+	unsigned offset;
+	unsigned offset_end;
+
+	for (offset_slot = 0;
+	     offset_slot < ARRAY_LEN(deflate_offset_slot_base);
+	     offset_slot++)
+	{
+		offset = deflate_offset_slot_base[offset_slot];
+	#if USE_FULL_OFFSET_SLOT_FAST
+		offset_end = offset + (1 << deflate_extra_offset_bits[offset_slot]);
+		do {
+			c->offset_slot_fast[offset] = offset_slot;
+		} while (++offset != offset_end);
+	#else
+		if (offset <= 256) {
+			offset_end = offset + (1 << deflate_extra_offset_bits[offset_slot]);
+			do {
+				c->offset_slot_fast[offset - 1] = offset_slot;
+			} while (++offset != offset_end);
+		} else {
+			offset_end = offset + (1 << deflate_extra_offset_bits[offset_slot]);
+			do {
+				c->offset_slot_fast[256 + ((offset - 1) >> 7)] = offset_slot;
+			} while ((offset += (1 << 7)) != offset_end);
+		}
+	#endif
+	}
+}
+
+LIBDEFLATEEXPORT struct libdeflate_compressor * LIBDEFLATEAPI
+libdeflate_alloc_compressor(int compression_level)
+{
+	struct libdeflate_compressor *c;
+	size_t size = offsetof(struct libdeflate_compressor, p);
+
+	if (compression_level < 0 || compression_level > 12)
+		return NULL;
+
+#if SUPPORT_NEAR_OPTIMAL_PARSING
+	if (compression_level >= 8)
+		size += sizeof(c->p.n);
+	else if (compression_level >= 1)
+		size += sizeof(c->p.g);
+#else
+	if (compression_level >= 1)
+		size += sizeof(c->p.g);
+#endif
+
+	c = libdeflate_aligned_malloc(MATCHFINDER_MEM_ALIGNMENT, size);
+	if (!c)
+		return NULL;
+
+	c->compression_level = compression_level;
+
+	/*
+	 * The higher the compression level, the more we should bother trying to
+	 * compress very small inputs.
+	 */
+	c->min_size_to_compress = 56 - (compression_level * 4);
+
+	switch (compression_level) {
+	case 0:
+		c->impl = deflate_compress_none;
+		break;
+	case 1:
+		c->impl = deflate_compress_greedy;
+		c->max_search_depth = 2;
+		c->nice_match_length = 8;
+		break;
+	case 2:
+		c->impl = deflate_compress_greedy;
+		c->max_search_depth = 6;
+		c->nice_match_length = 10;
+		break;
+	case 3:
+		c->impl = deflate_compress_greedy;
+		c->max_search_depth = 12;
+		c->nice_match_length = 14;
+		break;
+	case 4:
+		c->impl = deflate_compress_greedy;
+		c->max_search_depth = 24;
+		c->nice_match_length = 24;
+		break;
+	case 5:
+		c->impl = deflate_compress_lazy;
+		c->max_search_depth = 20;
+		c->nice_match_length = 30;
+		break;
+	case 6:
+		c->impl = deflate_compress_lazy;
+		c->max_search_depth = 40;
+		c->nice_match_length = 65;
+		break;
+	case 7:
+		c->impl = deflate_compress_lazy;
+		c->max_search_depth = 100;
+		c->nice_match_length = 130;
+		break;
+#if SUPPORT_NEAR_OPTIMAL_PARSING
+	case 8:
+		c->impl = deflate_compress_near_optimal;
+		c->max_search_depth = 12;
+		c->nice_match_length = 20;
+		c->p.n.num_optim_passes = 1;
+		break;
+	case 9:
+		c->impl = deflate_compress_near_optimal;
+		c->max_search_depth = 16;
+		c->nice_match_length = 26;
+		c->p.n.num_optim_passes = 2;
+		break;
+	case 10:
+		c->impl = deflate_compress_near_optimal;
+		c->max_search_depth = 30;
+		c->nice_match_length = 50;
+		c->p.n.num_optim_passes = 2;
+		break;
+	case 11:
+		c->impl = deflate_compress_near_optimal;
+		c->max_search_depth = 60;
+		c->nice_match_length = 80;
+		c->p.n.num_optim_passes = 3;
+		break;
+	default:
+		c->impl = deflate_compress_near_optimal;
+		c->max_search_depth = 100;
+		c->nice_match_length = 133;
+		c->p.n.num_optim_passes = 4;
+		break;
+#else
+	case 8:
+		c->impl = deflate_compress_lazy;
+		c->max_search_depth = 150;
+		c->nice_match_length = 200;
+		break;
+	default:
+		c->impl = deflate_compress_lazy;
+		c->max_search_depth = 200;
+		c->nice_match_length = DEFLATE_MAX_MATCH_LEN;
+		break;
+#endif
+	}
+
+	deflate_init_offset_slot_fast(c);
+	deflate_init_static_codes(c);
+
+	return c;
+}
+
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_deflate_compress(struct libdeflate_compressor *c,
+			    const void *in, size_t in_nbytes,
+			    void *out, size_t out_nbytes_avail)
+{
+	if (unlikely(out_nbytes_avail < OUTPUT_END_PADDING))
+		return 0;
+
+	/* For extremely small inputs just use a single uncompressed block. */
+	if (unlikely(in_nbytes < c->min_size_to_compress)) {
+		struct deflate_output_bitstream os;
+		deflate_init_output(&os, out, out_nbytes_avail);
+		if (in_nbytes == 0)
+			in = &os; /* Avoid passing NULL to memcpy() */
+		deflate_write_uncompressed_block(&os, in, in_nbytes, true);
+		return deflate_flush_output(&os);
+	}
+
+	return (*c->impl)(c, in, in_nbytes, out, out_nbytes_avail);
+}
+
+LIBDEFLATEEXPORT void LIBDEFLATEAPI
+libdeflate_free_compressor(struct libdeflate_compressor *c)
+{
+	libdeflate_aligned_free(c);
+}
+
+unsigned int
+deflate_get_compression_level(struct libdeflate_compressor *c)
+{
+	return c->compression_level;
+}
+
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_deflate_compress_bound(struct libdeflate_compressor *c,
+				  size_t in_nbytes)
+{
+	/*
+	 * The worst case is all uncompressed blocks where one block has length
+	 * <= MIN_BLOCK_LENGTH and the others have length MIN_BLOCK_LENGTH.
+	 * Each uncompressed block has 5 bytes of overhead: 1 for BFINAL, BTYPE,
+	 * and alignment to a byte boundary; 2 for LEN; and 2 for NLEN.
+	 */
+	size_t max_num_blocks = MAX(DIV_ROUND_UP(in_nbytes, MIN_BLOCK_LENGTH), 1);
+	return (5 * max_num_blocks) + in_nbytes + 1 + OUTPUT_END_PADDING;
+}

ADDED   3rd_party/libdeflate/lib/deflate_compress.h
Index: 3rd_party/libdeflate/lib/deflate_compress.h
==================================================================
--- 3rd_party/libdeflate/lib/deflate_compress.h
+++ 3rd_party/libdeflate/lib/deflate_compress.h
@@ -0,0 +1,13 @@
+#ifndef LIB_DEFLATE_COMPRESS_H
+#define LIB_DEFLATE_COMPRESS_H
+
+#include "lib_common.h"
+
+/* DEFLATE compression is private to deflate_compress.c, but we do need to be
+ * able to query the compression level for zlib and gzip header generation.  */
+
+struct libdeflate_compressor;
+
+unsigned int deflate_get_compression_level(struct libdeflate_compressor *c);
+
+#endif /* LIB_DEFLATE_COMPRESS_H */

ADDED   3rd_party/libdeflate/lib/deflate_constants.h
Index: 3rd_party/libdeflate/lib/deflate_constants.h
==================================================================
--- 3rd_party/libdeflate/lib/deflate_constants.h
+++ 3rd_party/libdeflate/lib/deflate_constants.h
@@ -0,0 +1,66 @@
+/*
+ * deflate_constants.h - constants for the DEFLATE compression format
+ */
+
+#ifndef LIB_DEFLATE_CONSTANTS_H
+#define LIB_DEFLATE_CONSTANTS_H
+
+/* Valid block types  */
+#define DEFLATE_BLOCKTYPE_UNCOMPRESSED		0
+#define DEFLATE_BLOCKTYPE_STATIC_HUFFMAN	1
+#define DEFLATE_BLOCKTYPE_DYNAMIC_HUFFMAN	2
+
+/* Minimum and maximum supported match lengths (in bytes)  */
+#define DEFLATE_MIN_MATCH_LEN			3
+#define DEFLATE_MAX_MATCH_LEN			258
+
+/* Minimum and maximum supported match offsets (in bytes)  */
+#define DEFLATE_MIN_MATCH_OFFSET		1
+#define DEFLATE_MAX_MATCH_OFFSET		32768
+
+#define DEFLATE_MAX_WINDOW_SIZE			32768
+
+/* Number of symbols in each Huffman code.  Note: for the literal/length
+ * and offset codes, these are actually the maximum values; a given block
+ * might use fewer symbols.  */
+#define DEFLATE_NUM_PRECODE_SYMS		19
+#define DEFLATE_NUM_LITLEN_SYMS			288
+#define DEFLATE_NUM_OFFSET_SYMS			32
+
+/* The maximum number of symbols across all codes  */
+#define DEFLATE_MAX_NUM_SYMS			288
+
+/* Division of symbols in the literal/length code  */
+#define DEFLATE_NUM_LITERALS			256
+#define DEFLATE_END_OF_BLOCK			256
+#define DEFLATE_NUM_LEN_SYMS			31
+
+/* Maximum codeword length, in bits, within each Huffman code  */
+#define DEFLATE_MAX_PRE_CODEWORD_LEN		7
+#define DEFLATE_MAX_LITLEN_CODEWORD_LEN		15
+#define DEFLATE_MAX_OFFSET_CODEWORD_LEN		15
+
+/* The maximum codeword length across all codes  */
+#define DEFLATE_MAX_CODEWORD_LEN		15
+
+/* Maximum possible overrun when decoding codeword lengths  */
+#define DEFLATE_MAX_LENS_OVERRUN		137
+
+/*
+ * Maximum number of extra bits that may be required to represent a match
+ * length or offset.
+ *
+ * TODO: are we going to have full DEFLATE64 support?  If so, up to 16
+ * length bits must be supported.
+ */
+#define DEFLATE_MAX_EXTRA_LENGTH_BITS		5
+#define DEFLATE_MAX_EXTRA_OFFSET_BITS		14
+
+/* The maximum number of bits in which a match can be represented.  This
+ * is the absolute worst case, which assumes the longest possible Huffman
+ * codewords and the maximum numbers of extra bits.  */
+#define DEFLATE_MAX_MATCH_BITS	\
+	(DEFLATE_MAX_LITLEN_CODEWORD_LEN + DEFLATE_MAX_EXTRA_LENGTH_BITS + \
+	DEFLATE_MAX_OFFSET_CODEWORD_LEN + DEFLATE_MAX_EXTRA_OFFSET_BITS)
+
+#endif /* LIB_DEFLATE_CONSTANTS_H */

ADDED   3rd_party/libdeflate/lib/deflate_decompress.c
Index: 3rd_party/libdeflate/lib/deflate_decompress.c
==================================================================
--- 3rd_party/libdeflate/lib/deflate_decompress.c
+++ 3rd_party/libdeflate/lib/deflate_decompress.c
@@ -0,0 +1,1000 @@
+/*
+ * deflate_decompress.c - a decompressor for DEFLATE
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ *
+ * ---------------------------------------------------------------------------
+ *
+ * This is a highly optimized DEFLATE decompressor.  When compiled with gcc on
+ * x86_64, it decompresses data in about 52% of the time of zlib (48% if BMI2
+ * instructions are available).  On other architectures it should still be
+ * significantly faster than zlib, but the difference may be smaller.
+ *
+ * Why this is faster than zlib's implementation:
+ *
+ * - Word accesses rather than byte accesses when reading input
+ * - Word accesses rather than byte accesses when copying matches
+ * - Faster Huffman decoding combined with various DEFLATE-specific tricks
+ * - Larger bitbuffer variable that doesn't need to be filled as often
+ * - Other optimizations to remove unnecessary branches
+ * - Only full-buffer decompression is supported, so the code doesn't need to
+ *   support stopping and resuming decompression.
+ * - On x86_64, compile a version of the decompression routine using BMI2
+ *   instructions and use it automatically at runtime when supported.
+ */
+
+#include <limits.h>
+
+#include "deflate_constants.h"
+#include "unaligned.h"
+
+#include "libdeflate.h"
+
+/*
+ * If the expression passed to SAFETY_CHECK() evaluates to false, then the
+ * decompression routine immediately returns LIBDEFLATE_BAD_DATA, indicating the
+ * compressed data is invalid.
+ *
+ * Theoretically, these checks could be disabled for specialized applications
+ * where all input to the decompressor will be trusted.
+ */
+#if 0
+#  pragma message("UNSAFE DECOMPRESSION IS ENABLED. THIS MUST ONLY BE USED IF THE DECOMPRESSOR INPUT WILL ALWAYS BE TRUSTED!")
+#  define SAFETY_CHECK(expr)	(void)(expr)
+#else
+#  define SAFETY_CHECK(expr)	if (unlikely(!(expr))) return LIBDEFLATE_BAD_DATA
+#endif
+
+/*
+ * Each TABLEBITS number is the base-2 logarithm of the number of entries in the
+ * main portion of the corresponding decode table.  Each number should be large
+ * enough to ensure that for typical data, the vast majority of symbols can be
+ * decoded by a direct lookup of the next TABLEBITS bits of compressed data.
+ * However, this must be balanced against the fact that a larger table requires
+ * more memory and requires more time to fill.
+ *
+ * Note: you cannot change a TABLEBITS number without also changing the
+ * corresponding ENOUGH number!
+ */
+#define PRECODE_TABLEBITS	7
+#define LITLEN_TABLEBITS	10
+#define OFFSET_TABLEBITS	8
+
+/*
+ * Each ENOUGH number is the maximum number of decode table entries that may be
+ * required for the corresponding Huffman code, including the main table and all
+ * subtables.  Each number depends on three parameters:
+ *
+ *	(1) the maximum number of symbols in the code (DEFLATE_NUM_*_SYMS)
+ *	(2) the number of main table bits (the TABLEBITS numbers defined above)
+ *	(3) the maximum allowed codeword length (DEFLATE_MAX_*_CODEWORD_LEN)
+ *
+ * The ENOUGH numbers were computed using the utility program 'enough' from
+ * zlib.  This program enumerates all possible relevant Huffman codes to find
+ * the worst-case usage of decode table entries.
+ */
+#define PRECODE_ENOUGH		128	/* enough 19 7 7	*/
+#define LITLEN_ENOUGH		1334	/* enough 288 10 15	*/
+#define OFFSET_ENOUGH		402	/* enough 32 8 15	*/
+
+/*
+ * Type for codeword lengths.
+ */
+typedef u8 len_t;
+
+/*
+ * The main DEFLATE decompressor structure.  Since this implementation only
+ * supports full buffer decompression, this structure does not store the entire
+ * decompression state, but rather only some arrays that are too large to
+ * comfortably allocate on the stack.
+ */
+struct libdeflate_decompressor {
+
+	/*
+	 * The arrays aren't all needed at the same time.  'precode_lens' and
+	 * 'precode_decode_table' are unneeded after 'lens' has been filled.
+	 * Furthermore, 'lens' need not be retained after building the litlen
+	 * and offset decode tables.  In fact, 'lens' can be in union with
+	 * 'litlen_decode_table' provided that 'offset_decode_table' is separate
+	 * and is built first.
+	 */
+
+	union {
+		len_t precode_lens[DEFLATE_NUM_PRECODE_SYMS];
+
+		struct {
+			len_t lens[DEFLATE_NUM_LITLEN_SYMS +
+				   DEFLATE_NUM_OFFSET_SYMS +
+				   DEFLATE_MAX_LENS_OVERRUN];
+
+			u32 precode_decode_table[PRECODE_ENOUGH];
+		} l;
+
+		u32 litlen_decode_table[LITLEN_ENOUGH];
+	} u;
+
+	u32 offset_decode_table[OFFSET_ENOUGH];
+
+	/* used only during build_decode_table() */
+	u16 sorted_syms[DEFLATE_MAX_NUM_SYMS];
+
+	bool static_codes_loaded;
+};
+
+/*****************************************************************************
+ *				Input bitstream                              *
+ *****************************************************************************/
+
+/*
+ * The state of the "input bitstream" consists of the following variables:
+ *
+ *	- in_next: pointer to the next unread byte in the input buffer
+ *
+ *	- in_end: pointer just past the end of the input buffer
+ *
+ *	- bitbuf: a word-sized variable containing bits that have been read from
+ *		  the input buffer.  The buffered bits are right-aligned
+ *		  (they're the low-order bits).
+ *
+ *	- bitsleft: number of bits in 'bitbuf' that are valid.
+ *
+ * To make it easier for the compiler to optimize the code by keeping variables
+ * in registers, these are declared as normal variables and manipulated using
+ * macros.
+ */
+
+/*
+ * The type for the bitbuffer variable ('bitbuf' described above).  For best
+ * performance, this should have size equal to a machine word.
+ *
+ * 64-bit platforms have a significant advantage: they get a bigger bitbuffer
+ * which they have to fill less often.
+ */
+typedef machine_word_t bitbuf_t;
+
+/*
+ * Number of bits the bitbuffer variable can hold.
+ *
+ * This is one less than the obvious value because of the optimized arithmetic
+ * in FILL_BITS_WORDWISE() that leaves 'bitsleft' in the range
+ * [WORDBITS - 8, WORDBITS - 1] rather than [WORDBITS - 7, WORDBITS].
+ */
+#define BITBUF_NBITS	(8 * sizeof(bitbuf_t) - 1)
+
+/*
+ * The maximum number of bits that can be ensured in the bitbuffer variable,
+ * i.e. the maximum value of 'n' that can be passed ENSURE_BITS(n).  The decoder
+ * only reads whole bytes from memory, so this is the lowest value of 'bitsleft'
+ * at which another byte cannot be read without first consuming some bits.
+ */
+#define MAX_ENSURE	(BITBUF_NBITS - 7)
+
+/*
+ * Evaluates to true if 'n' is a valid argument to ENSURE_BITS(n), or false if
+ * 'n' is too large to be passed to ENSURE_BITS(n).  Note: if 'n' is a compile
+ * time constant, then this expression will be a compile-type constant.
+ * Therefore, CAN_ENSURE() can be used choose between alternative
+ * implementations at compile time.
+ */
+#define CAN_ENSURE(n)	((n) <= MAX_ENSURE)
+
+/*
+ * Fill the bitbuffer variable, reading one byte at a time.
+ *
+ * If we would overread the input buffer, we just don't read anything, leaving
+ * the bits zeroed but marking them filled.  This simplifies the decompressor
+ * because it removes the need to distinguish between real overreads and
+ * overreads that occur only because of the decompressor's own lookahead.
+ *
+ * The disadvantage is that real overreads are not detected immediately.
+ * However, this is safe because the decompressor is still guaranteed to make
+ * forward progress when presented never-ending 0 bits.  In an existing block
+ * output will be getting generated, whereas new blocks can only be uncompressed
+ * (since the type code for uncompressed blocks is 0), for which we check for
+ * previous overread.  But even if we didn't check, uncompressed blocks would
+ * fail to validate because LEN would not equal ~NLEN.  So the decompressor will
+ * eventually either detect that the output buffer is full, or detect invalid
+ * input, or finish the final block.
+ */
+#define FILL_BITS_BYTEWISE()					\
+do {								\
+	if (likely(in_next != in_end))				\
+		bitbuf |= (bitbuf_t)*in_next++ << bitsleft;	\
+	else							\
+		overrun_count++;				\
+	bitsleft += 8;						\
+} while (bitsleft <= BITBUF_NBITS - 8)
+
+/*
+ * Fill the bitbuffer variable by reading the next word from the input buffer
+ * and branchlessly updating 'in_next' and 'bitsleft' based on how many bits
+ * were filled.  This can be significantly faster than FILL_BITS_BYTEWISE().
+ * However, for this to work correctly, the word must be interpreted in
+ * little-endian format.  In addition, the memory access may be unaligned.
+ * Therefore, this method is most efficient on little-endian architectures that
+ * support fast unaligned access, such as x86 and x86_64.
+ *
+ * For faster updating of 'bitsleft', we consider the bitbuffer size in bits to
+ * be 1 less than the word size and therefore be all 1 bits.  Then the number of
+ * bits filled is the value of the 0 bits in position >= 3 when changed to 1.
+ * E.g. if words are 64 bits and bitsleft = 16 = b010000 then we refill b101000
+ * = 40 bits = 5 bytes.  This uses only 4 operations to update 'in_next' and
+ * 'bitsleft': one each of +, ^, >>, and |.  (Not counting operations the
+ * compiler optimizes out.)  In contrast, the alternative of:
+ *
+ *	in_next += (BITBUF_NBITS - bitsleft) >> 3;
+ *	bitsleft += (BITBUF_NBITS - bitsleft) & ~7;
+ *
+ * (where BITBUF_NBITS would be WORDBITS rather than WORDBITS - 1) would on
+ * average refill an extra bit, but uses 5 operations: two +, and one each of
+ * -, >>, and &.  Also the - and & must be completed before 'bitsleft' can be
+ * updated, while the current solution updates 'bitsleft' with no dependencies.
+ */
+#define FILL_BITS_WORDWISE()					\
+do {								\
+	/* BITBUF_NBITS must be all 1's in binary, see above */	\
+	STATIC_ASSERT((BITBUF_NBITS & (BITBUF_NBITS + 1)) == 0);\
+								\
+	bitbuf |= get_unaligned_leword(in_next) << bitsleft;	\
+	in_next += (bitsleft ^ BITBUF_NBITS) >> 3;		\
+	bitsleft |= BITBUF_NBITS & ~7;				\
+} while (0)
+
+/*
+ * Does the bitbuffer variable currently contain at least 'n' bits?
+ */
+#define HAVE_BITS(n) (bitsleft >= (n))
+
+/*
+ * Load more bits from the input buffer until the specified number of bits is
+ * present in the bitbuffer variable.  'n' cannot be too large; see MAX_ENSURE
+ * and CAN_ENSURE().
+ */
+#define ENSURE_BITS(n)						\
+if (!HAVE_BITS(n)) {						\
+	if (CPU_IS_LITTLE_ENDIAN() &&				\
+	    UNALIGNED_ACCESS_IS_FAST &&				\
+	    likely(in_end - in_next >= sizeof(bitbuf_t)))	\
+		FILL_BITS_WORDWISE();				\
+	else							\
+		FILL_BITS_BYTEWISE();				\
+}
+
+/*
+ * Return the next 'n' bits from the bitbuffer variable without removing them.
+ */
+#define BITS(n) ((u32)bitbuf & (((u32)1 << (n)) - 1))
+
+/*
+ * Remove the next 'n' bits from the bitbuffer variable.
+ */
+#define REMOVE_BITS(n) (bitbuf >>= (n), bitsleft -= (n))
+
+/*
+ * Remove and return the next 'n' bits from the bitbuffer variable.
+ */
+#define POP_BITS(n) (tmp32 = BITS(n), REMOVE_BITS(n), tmp32)
+
+/*
+ * Verify that the input buffer hasn't been overread, then align the input to
+ * the next byte boundary, discarding any remaining bits in the current byte.
+ *
+ * Note that if the bitbuffer variable currently contains more than 7 bits, then
+ * we must rewind 'in_next', effectively putting those bits back.  Only the bits
+ * in what would be the "current" byte if we were reading one byte at a time can
+ * be actually discarded.
+ */
+#define ALIGN_INPUT()							\
+do {									\
+	SAFETY_CHECK(overrun_count <= (bitsleft >> 3));			\
+	in_next -= (bitsleft >> 3) - overrun_count;			\
+	overrun_count = 0;						\
+	bitbuf = 0;							\
+	bitsleft = 0;							\
+} while(0)
+
+/*
+ * Read a 16-bit value from the input.  This must have been preceded by a call
+ * to ALIGN_INPUT(), and the caller must have already checked for overrun.
+ */
+#define READ_U16() (tmp16 = get_unaligned_le16(in_next), in_next += 2, tmp16)
+
+/*****************************************************************************
+ *                              Huffman decoding                             *
+ *****************************************************************************/
+
+/*
+ * A decode table for order TABLEBITS consists of a main table of (1 <<
+ * TABLEBITS) entries followed by a variable number of subtables.
+ *
+ * The decoding algorithm takes the next TABLEBITS bits of compressed data and
+ * uses them as an index into the decode table.  The resulting entry is either a
+ * "direct entry", meaning that it contains the value desired, or a "subtable
+ * pointer", meaning that the entry references a subtable that must be indexed
+ * using more bits of the compressed data to decode the symbol.
+ *
+ * Each decode table (a main table along with its subtables, if any) is
+ * associated with a Huffman code.  Logically, the result of a decode table
+ * lookup is a symbol from the alphabet from which the corresponding Huffman
+ * code was constructed.  A symbol with codeword length n <= TABLEBITS is
+ * associated with 2**(TABLEBITS - n) direct entries in the table, whereas a
+ * symbol with codeword length n > TABLEBITS is associated with one or more
+ * subtable entries.
+ *
+ * On top of this basic design, we implement several optimizations:
+ *
+ * - We store the length of each codeword directly in each of its decode table
+ *   entries.  This allows the codeword length to be produced without indexing
+ *   an additional table.
+ *
+ * - When beneficial, we don't store the Huffman symbol itself, but instead data
+ *   generated from it.  For example, when decoding an offset symbol in DEFLATE,
+ *   it's more efficient if we can decode the offset base and number of extra
+ *   offset bits directly rather than decoding the offset symbol and then
+ *   looking up both of those values in an additional table or tables.
+ *
+ * The size of each decode table entry is 32 bits, which provides slightly
+ * better performance than 16-bit entries on 32 and 64 bit processers, provided
+ * that the table doesn't get so large that it takes up too much memory and
+ * starts generating cache misses.  The bits of each decode table entry are
+ * defined as follows:
+ *
+ * - Bits 30 -- 31: flags (see below)
+ * - Bits 8 -- 29: decode result: a Huffman symbol or related data
+ * - Bits 0 -- 7: codeword length
+ */
+
+/*
+ * This flag is set in all main decode table entries that represent subtable
+ * pointers.
+ */
+#define HUFFDEC_SUBTABLE_POINTER	0x80000000
+
+/*
+ * This flag is set in all entries in the litlen decode table that represent
+ * literals.
+ */
+#define HUFFDEC_LITERAL			0x40000000
+
+/* Mask for extracting the codeword length from a decode table entry.  */
+#define HUFFDEC_LENGTH_MASK		0xFF
+
+/* Shift to extract the decode result from a decode table entry.  */
+#define HUFFDEC_RESULT_SHIFT		8
+
+/* Shift a decode result into its position in the decode table entry.  */
+#define HUFFDEC_RESULT_ENTRY(result)	((u32)(result) << HUFFDEC_RESULT_SHIFT)
+
+/* The decode result for each precode symbol.  There is no special optimization
+ * for the precode; the decode result is simply the symbol value.  */
+static const u32 precode_decode_results[DEFLATE_NUM_PRECODE_SYMS] = {
+#define ENTRY(presym)	HUFFDEC_RESULT_ENTRY(presym)
+	ENTRY(0)   , ENTRY(1)   , ENTRY(2)   , ENTRY(3)   ,
+	ENTRY(4)   , ENTRY(5)   , ENTRY(6)   , ENTRY(7)   ,
+	ENTRY(8)   , ENTRY(9)   , ENTRY(10)  , ENTRY(11)  ,
+	ENTRY(12)  , ENTRY(13)  , ENTRY(14)  , ENTRY(15)  ,
+	ENTRY(16)  , ENTRY(17)  , ENTRY(18)  ,
+#undef ENTRY
+};
+
+/* The decode result for each litlen symbol.  For literals, this is the literal
+ * value itself and the HUFFDEC_LITERAL flag.  For lengths, this is the length
+ * base and the number of extra length bits.  */
+static const u32 litlen_decode_results[DEFLATE_NUM_LITLEN_SYMS] = {
+
+	/* Literals  */
+#define ENTRY(literal)	(HUFFDEC_LITERAL | HUFFDEC_RESULT_ENTRY(literal))
+	ENTRY(0)   , ENTRY(1)   , ENTRY(2)   , ENTRY(3)   ,
+	ENTRY(4)   , ENTRY(5)   , ENTRY(6)   , ENTRY(7)   ,
+	ENTRY(8)   , ENTRY(9)   , ENTRY(10)  , ENTRY(11)  ,
+	ENTRY(12)  , ENTRY(13)  , ENTRY(14)  , ENTRY(15)  ,
+	ENTRY(16)  , ENTRY(17)  , ENTRY(18)  , ENTRY(19)  ,
+	ENTRY(20)  , ENTRY(21)  , ENTRY(22)  , ENTRY(23)  ,
+	ENTRY(24)  , ENTRY(25)  , ENTRY(26)  , ENTRY(27)  ,
+	ENTRY(28)  , ENTRY(29)  , ENTRY(30)  , ENTRY(31)  ,
+	ENTRY(32)  , ENTRY(33)  , ENTRY(34)  , ENTRY(35)  ,
+	ENTRY(36)  , ENTRY(37)  , ENTRY(38)  , ENTRY(39)  ,
+	ENTRY(40)  , ENTRY(41)  , ENTRY(42)  , ENTRY(43)  ,
+	ENTRY(44)  , ENTRY(45)  , ENTRY(46)  , ENTRY(47)  ,
+	ENTRY(48)  , ENTRY(49)  , ENTRY(50)  , ENTRY(51)  ,
+	ENTRY(52)  , ENTRY(53)  , ENTRY(54)  , ENTRY(55)  ,
+	ENTRY(56)  , ENTRY(57)  , ENTRY(58)  , ENTRY(59)  ,
+	ENTRY(60)  , ENTRY(61)  , ENTRY(62)  , ENTRY(63)  ,
+	ENTRY(64)  , ENTRY(65)  , ENTRY(66)  , ENTRY(67)  ,
+	ENTRY(68)  , ENTRY(69)  , ENTRY(70)  , ENTRY(71)  ,
+	ENTRY(72)  , ENTRY(73)  , ENTRY(74)  , ENTRY(75)  ,
+	ENTRY(76)  , ENTRY(77)  , ENTRY(78)  , ENTRY(79)  ,
+	ENTRY(80)  , ENTRY(81)  , ENTRY(82)  , ENTRY(83)  ,
+	ENTRY(84)  , ENTRY(85)  , ENTRY(86)  , ENTRY(87)  ,
+	ENTRY(88)  , ENTRY(89)  , ENTRY(90)  , ENTRY(91)  ,
+	ENTRY(92)  , ENTRY(93)  , ENTRY(94)  , ENTRY(95)  ,
+	ENTRY(96)  , ENTRY(97)  , ENTRY(98)  , ENTRY(99)  ,
+	ENTRY(100) , ENTRY(101) , ENTRY(102) , ENTRY(103) ,
+	ENTRY(104) , ENTRY(105) , ENTRY(106) , ENTRY(107) ,
+	ENTRY(108) , ENTRY(109) , ENTRY(110) , ENTRY(111) ,
+	ENTRY(112) , ENTRY(113) , ENTRY(114) , ENTRY(115) ,
+	ENTRY(116) , ENTRY(117) , ENTRY(118) , ENTRY(119) ,
+	ENTRY(120) , ENTRY(121) , ENTRY(122) , ENTRY(123) ,
+	ENTRY(124) , ENTRY(125) , ENTRY(126) , ENTRY(127) ,
+	ENTRY(128) , ENTRY(129) , ENTRY(130) , ENTRY(131) ,
+	ENTRY(132) , ENTRY(133) , ENTRY(134) , ENTRY(135) ,
+	ENTRY(136) , ENTRY(137) , ENTRY(138) , ENTRY(139) ,
+	ENTRY(140) , ENTRY(141) , ENTRY(142) , ENTRY(143) ,
+	ENTRY(144) , ENTRY(145) , ENTRY(146) , ENTRY(147) ,
+	ENTRY(148) , ENTRY(149) , ENTRY(150) , ENTRY(151) ,
+	ENTRY(152) , ENTRY(153) , ENTRY(154) , ENTRY(155) ,
+	ENTRY(156) , ENTRY(157) , ENTRY(158) , ENTRY(159) ,
+	ENTRY(160) , ENTRY(161) , ENTRY(162) , ENTRY(163) ,
+	ENTRY(164) , ENTRY(165) , ENTRY(166) , ENTRY(167) ,
+	ENTRY(168) , ENTRY(169) , ENTRY(170) , ENTRY(171) ,
+	ENTRY(172) , ENTRY(173) , ENTRY(174) , ENTRY(175) ,
+	ENTRY(176) , ENTRY(177) , ENTRY(178) , ENTRY(179) ,
+	ENTRY(180) , ENTRY(181) , ENTRY(182) , ENTRY(183) ,
+	ENTRY(184) , ENTRY(185) , ENTRY(186) , ENTRY(187) ,
+	ENTRY(188) , ENTRY(189) , ENTRY(190) , ENTRY(191) ,
+	ENTRY(192) , ENTRY(193) , ENTRY(194) , ENTRY(195) ,
+	ENTRY(196) , ENTRY(197) , ENTRY(198) , ENTRY(199) ,
+	ENTRY(200) , ENTRY(201) , ENTRY(202) , ENTRY(203) ,
+	ENTRY(204) , ENTRY(205) , ENTRY(206) , ENTRY(207) ,
+	ENTRY(208) , ENTRY(209) , ENTRY(210) , ENTRY(211) ,
+	ENTRY(212) , ENTRY(213) , ENTRY(214) , ENTRY(215) ,
+	ENTRY(216) , ENTRY(217) , ENTRY(218) , ENTRY(219) ,
+	ENTRY(220) , ENTRY(221) , ENTRY(222) , ENTRY(223) ,
+	ENTRY(224) , ENTRY(225) , ENTRY(226) , ENTRY(227) ,
+	ENTRY(228) , ENTRY(229) , ENTRY(230) , ENTRY(231) ,
+	ENTRY(232) , ENTRY(233) , ENTRY(234) , ENTRY(235) ,
+	ENTRY(236) , ENTRY(237) , ENTRY(238) , ENTRY(239) ,
+	ENTRY(240) , ENTRY(241) , ENTRY(242) , ENTRY(243) ,
+	ENTRY(244) , ENTRY(245) , ENTRY(246) , ENTRY(247) ,
+	ENTRY(248) , ENTRY(249) , ENTRY(250) , ENTRY(251) ,
+	ENTRY(252) , ENTRY(253) , ENTRY(254) , ENTRY(255) ,
+#undef ENTRY
+
+#define HUFFDEC_EXTRA_LENGTH_BITS_MASK	0xFF
+#define HUFFDEC_LENGTH_BASE_SHIFT	8
+#define HUFFDEC_END_OF_BLOCK_LENGTH	0
+
+#define ENTRY(length_base, num_extra_bits)	HUFFDEC_RESULT_ENTRY(	\
+	((u32)(length_base) << HUFFDEC_LENGTH_BASE_SHIFT) | (num_extra_bits))
+
+	/* End of block  */
+	ENTRY(HUFFDEC_END_OF_BLOCK_LENGTH, 0),
+
+	/* Lengths  */
+	ENTRY(3  , 0) , ENTRY(4  , 0) , ENTRY(5  , 0) , ENTRY(6  , 0),
+	ENTRY(7  , 0) , ENTRY(8  , 0) , ENTRY(9  , 0) , ENTRY(10 , 0),
+	ENTRY(11 , 1) , ENTRY(13 , 1) , ENTRY(15 , 1) , ENTRY(17 , 1),
+	ENTRY(19 , 2) , ENTRY(23 , 2) , ENTRY(27 , 2) , ENTRY(31 , 2),
+	ENTRY(35 , 3) , ENTRY(43 , 3) , ENTRY(51 , 3) , ENTRY(59 , 3),
+	ENTRY(67 , 4) , ENTRY(83 , 4) , ENTRY(99 , 4) , ENTRY(115, 4),
+	ENTRY(131, 5) , ENTRY(163, 5) , ENTRY(195, 5) , ENTRY(227, 5),
+	ENTRY(258, 0) , ENTRY(258, 0) , ENTRY(258, 0) ,
+#undef ENTRY
+};
+
+/* The decode result for each offset symbol.  This is the offset base and the
+ * number of extra offset bits.  */
+static const u32 offset_decode_results[DEFLATE_NUM_OFFSET_SYMS] = {
+
+#define HUFFDEC_EXTRA_OFFSET_BITS_SHIFT 16
+#define HUFFDEC_OFFSET_BASE_MASK (((u32)1 << HUFFDEC_EXTRA_OFFSET_BITS_SHIFT) - 1)
+
+#define ENTRY(offset_base, num_extra_bits)	HUFFDEC_RESULT_ENTRY(	\
+		((u32)(num_extra_bits) << HUFFDEC_EXTRA_OFFSET_BITS_SHIFT) | \
+		(offset_base))
+	ENTRY(1     , 0)  , ENTRY(2     , 0)  , ENTRY(3     , 0)  , ENTRY(4     , 0)  ,
+	ENTRY(5     , 1)  , ENTRY(7     , 1)  , ENTRY(9     , 2)  , ENTRY(13    , 2) ,
+	ENTRY(17    , 3)  , ENTRY(25    , 3)  , ENTRY(33    , 4)  , ENTRY(49    , 4)  ,
+	ENTRY(65    , 5)  , ENTRY(97    , 5)  , ENTRY(129   , 6)  , ENTRY(193   , 6)  ,
+	ENTRY(257   , 7)  , ENTRY(385   , 7)  , ENTRY(513   , 8)  , ENTRY(769   , 8)  ,
+	ENTRY(1025  , 9)  , ENTRY(1537  , 9)  , ENTRY(2049  , 10) , ENTRY(3073  , 10) ,
+	ENTRY(4097  , 11) , ENTRY(6145  , 11) , ENTRY(8193  , 12) , ENTRY(12289 , 12) ,
+	ENTRY(16385 , 13) , ENTRY(24577 , 13) , ENTRY(32769 , 14) , ENTRY(49153 , 14) ,
+#undef ENTRY
+};
+
+/*
+ * Build a table for fast decoding of symbols from a Huffman code.  As input,
+ * this function takes the codeword length of each symbol which may be used in
+ * the code.  As output, it produces a decode table for the canonical Huffman
+ * code described by the codeword lengths.  The decode table is built with the
+ * assumption that it will be indexed with "bit-reversed" codewords, where the
+ * low-order bit is the first bit of the codeword.  This format is used for all
+ * Huffman codes in DEFLATE.
+ *
+ * @decode_table
+ *	The array in which the decode table will be generated.  This array must
+ *	have sufficient length; see the definition of the ENOUGH numbers.
+ * @lens
+ *	An array which provides, for each symbol, the length of the
+ *	corresponding codeword in bits, or 0 if the symbol is unused.  This may
+ *	alias @decode_table, since nothing is written to @decode_table until all
+ *	@lens have been consumed.  All codeword lengths are assumed to be <=
+ *	@max_codeword_len but are otherwise considered untrusted.  If they do
+ *	not form a valid Huffman code, then the decode table is not built and
+ *	%false is returned.
+ * @num_syms
+ *	The number of symbols in the code, including all unused symbols.
+ * @decode_results
+ *	An array which provides, for each symbol, the actual value to store into
+ *	the decode table.  This value will be directly produced as the result of
+ *	decoding that symbol, thereby moving the indirection out of the decode
+ *	loop and into the table initialization.
+ * @table_bits
+ *	The log base-2 of the number of main table entries to use.
+ * @max_codeword_len
+ *	The maximum allowed codeword length for this Huffman code.
+ *	Must be <= DEFLATE_MAX_CODEWORD_LEN.
+ * @sorted_syms
+ *	A temporary array of length @num_syms.
+ *
+ * Returns %true if successful; %false if the codeword lengths do not form a
+ * valid Huffman code.
+ */
+static bool
+build_decode_table(u32 decode_table[],
+		   const len_t lens[],
+		   const unsigned num_syms,
+		   const u32 decode_results[],
+		   const unsigned table_bits,
+		   const unsigned max_codeword_len,
+		   u16 *sorted_syms)
+{
+	unsigned len_counts[DEFLATE_MAX_CODEWORD_LEN + 1];
+	unsigned offsets[DEFLATE_MAX_CODEWORD_LEN + 1];
+	unsigned sym;		/* current symbol */
+	unsigned codeword;	/* current codeword, bit-reversed */
+	unsigned len;		/* current codeword length in bits */
+	unsigned count;		/* num codewords remaining with this length */
+	u32 codespace_used;	/* codespace used out of '2^max_codeword_len' */
+	unsigned cur_table_end; /* end index of current table */
+	unsigned subtable_prefix; /* codeword prefix of current subtable */
+	unsigned subtable_start;  /* start index of current subtable */
+	unsigned subtable_bits;   /* log2 of current subtable length */
+
+	/* Count how many codewords have each length, including 0. */
+	for (len = 0; len <= max_codeword_len; len++)
+		len_counts[len] = 0;
+	for (sym = 0; sym < num_syms; sym++)
+		len_counts[lens[sym]]++;
+
+	/*
+	 * Sort the symbols primarily by increasing codeword length and
+	 * secondarily by increasing symbol value; or equivalently by their
+	 * codewords in lexicographic order, since a canonical code is assumed.
+	 *
+	 * For efficiency, also compute 'codespace_used' in the same pass over
+	 * 'len_counts[]' used to build 'offsets[]' for sorting.
+	 */
+
+	/* Ensure that 'codespace_used' cannot overflow. */
+	STATIC_ASSERT(sizeof(codespace_used) == 4);
+	STATIC_ASSERT(UINT32_MAX / (1U << (DEFLATE_MAX_CODEWORD_LEN - 1)) >=
+		      DEFLATE_MAX_NUM_SYMS);
+
+	offsets[0] = 0;
+	offsets[1] = len_counts[0];
+	codespace_used = 0;
+	for (len = 1; len < max_codeword_len; len++) {
+		offsets[len + 1] = offsets[len] + len_counts[len];
+		codespace_used = (codespace_used << 1) + len_counts[len];
+	}
+	codespace_used = (codespace_used << 1) + len_counts[len];
+
+	for (sym = 0; sym < num_syms; sym++)
+		sorted_syms[offsets[lens[sym]]++] = sym;
+
+	sorted_syms += offsets[0]; /* Skip unused symbols */
+
+	/* lens[] is done being used, so we can write to decode_table[] now. */
+
+	/*
+	 * Check whether the lengths form a complete code (exactly fills the
+	 * codespace), an incomplete code (doesn't fill the codespace), or an
+	 * overfull code (overflows the codespace).  A codeword of length 'n'
+	 * uses proportion '1/(2^n)' of the codespace.  An overfull code is
+	 * nonsensical, so is considered invalid.  An incomplete code is
+	 * considered valid only in two specific cases; see below.
+	 */
+
+	/* overfull code? */
+	if (unlikely(codespace_used > (1U << max_codeword_len)))
+		return false;
+
+	/* incomplete code? */
+	if (unlikely(codespace_used < (1U << max_codeword_len))) {
+		u32 entry;
+		unsigned i;
+
+		if (codespace_used == 0) {
+			/*
+			 * An empty code is allowed.  This can happen for the
+			 * offset code in DEFLATE, since a dynamic Huffman block
+			 * need not contain any matches.
+			 */
+
+			/* sym=0, len=1 (arbitrary) */
+			entry = decode_results[0] | 1;
+		} else {
+			/*
+			 * Allow codes with a single used symbol, with codeword
+			 * length 1.  The DEFLATE RFC is unclear regarding this
+			 * case.  What zlib's decompressor does is permit this
+			 * for the litlen and offset codes and assume the
+			 * codeword is '0' rather than '1'.  We do the same
+			 * except we allow this for precodes too, since there's
+			 * no convincing reason to treat the codes differently.
+			 * We also assign both codewords '0' and '1' to the
+			 * symbol to avoid having to handle '1' specially.
+			 */
+			if (codespace_used != (1U << (max_codeword_len - 1)) ||
+			    len_counts[1] != 1)
+				return false;
+			entry = decode_results[*sorted_syms] | 1;
+		}
+		/*
+		 * Note: the decode table still must be fully initialized, in
+		 * case the stream is malformed and contains bits from the part
+		 * of the codespace the incomplete code doesn't use.
+		 */
+		for (i = 0; i < (1U << table_bits); i++)
+			decode_table[i] = entry;
+		return true;
+	}
+
+	/*
+	 * The lengths form a complete code.  Now, enumerate the codewords in
+	 * lexicographic order and fill the decode table entries for each one.
+	 *
+	 * First, process all codewords with len <= table_bits.  Each one gets
+	 * '2^(table_bits-len)' direct entries in the table.
+	 *
+	 * Since DEFLATE uses bit-reversed codewords, these entries aren't
+	 * consecutive but rather are spaced '2^len' entries apart.  This makes
+	 * filling them naively somewhat awkward and inefficient, since strided
+	 * stores are less cache-friendly and preclude the use of word or
+	 * vector-at-a-time stores to fill multiple entries per instruction.
+	 *
+	 * To optimize this, we incrementally double the table size.  When
+	 * processing codewords with length 'len', the table is treated as
+	 * having only '2^len' entries, so each codeword uses just one entry.
+	 * Then, each time 'len' is incremented, the table size is doubled and
+	 * the first half is copied to the second half.  This significantly
+	 * improves performance over naively doing strided stores.
+	 *
+	 * Note that some entries copied for each table doubling may not have
+	 * been initialized yet, but it doesn't matter since they're guaranteed
+	 * to be initialized later (because the Huffman code is complete).
+	 */
+	codeword = 0;
+	len = 1;
+	while ((count = len_counts[len]) == 0)
+		len++;
+	cur_table_end = 1U << len;
+	while (len <= table_bits) {
+		/* Process all 'count' codewords with length 'len' bits. */
+		do {
+			unsigned bit;
+
+			/* Fill the first entry for the current codeword. */
+			decode_table[codeword] =
+				decode_results[*sorted_syms++] | len;
+
+			if (codeword == cur_table_end - 1) {
+				/* Last codeword (all 1's) */
+				for (; len < table_bits; len++) {
+					memcpy(&decode_table[cur_table_end],
+					       decode_table,
+					       cur_table_end *
+						sizeof(decode_table[0]));
+					cur_table_end <<= 1;
+				}
+				return true;
+			}
+			/*
+			 * To advance to the lexicographically next codeword in
+			 * the canonical code, the codeword must be incremented,
+			 * then 0's must be appended to the codeword as needed
+			 * to match the next codeword's length.
+			 *
+			 * Since the codeword is bit-reversed, appending 0's is
+			 * a no-op.  However, incrementing it is nontrivial.  To
+			 * do so efficiently, use the 'bsr' instruction to find
+			 * the last (highest order) 0 bit in the codeword, set
+			 * it, and clear any later (higher order) 1 bits.  But
+			 * 'bsr' actually finds the highest order 1 bit, so to
+			 * use it first flip all bits in the codeword by XOR'ing
+			 * it with (1U << len) - 1 == cur_table_end - 1.
+			 */
+			bit = 1U << bsr32(codeword ^ (cur_table_end - 1));
+			codeword &= bit - 1;
+			codeword |= bit;
+		} while (--count);
+
+		/* Advance to the next codeword length. */
+		do {
+			if (++len <= table_bits) {
+				memcpy(&decode_table[cur_table_end],
+				       decode_table,
+				       cur_table_end * sizeof(decode_table[0]));
+				cur_table_end <<= 1;
+			}
+		} while ((count = len_counts[len]) == 0);
+	}
+
+	/* Process codewords with len > table_bits.  These require subtables. */
+	cur_table_end = 1U << table_bits;
+	subtable_prefix = -1;
+	subtable_start = 0;
+	for (;;) {
+		u32 entry;
+		unsigned i;
+		unsigned stride;
+		unsigned bit;
+
+		/*
+		 * Start a new subtable if the first 'table_bits' bits of the
+		 * codeword don't match the prefix of the current subtable.
+		 */
+		if ((codeword & ((1U << table_bits) - 1)) != subtable_prefix) {
+			subtable_prefix = (codeword & ((1U << table_bits) - 1));
+			subtable_start = cur_table_end;
+			/*
+			 * Calculate the subtable length.  If the codeword has
+			 * length 'table_bits + n', then the subtable needs
+			 * '2^n' entries.  But it may need more; if fewer than
+			 * '2^n' codewords of length 'table_bits + n' remain,
+			 * then the length will need to be incremented to bring
+			 * in longer codewords until the subtable can be
+			 * completely filled.  Note that because the Huffman
+			 * code is complete, it will always be possible to fill
+			 * the subtable eventually.
+			 */
+			subtable_bits = len - table_bits;
+			codespace_used = count;
+			while (codespace_used < (1U << subtable_bits)) {
+				subtable_bits++;
+				codespace_used = (codespace_used << 1) +
+					len_counts[table_bits + subtable_bits];
+			}
+			cur_table_end = subtable_start + (1U << subtable_bits);
+
+			/*
+			 * Create the entry that points from the main table to
+			 * the subtable.  This entry contains the index of the
+			 * start of the subtable and the number of bits with
+			 * which the subtable is indexed (the log base 2 of the
+			 * number of entries it contains).
+			 */
+			decode_table[subtable_prefix] =
+				HUFFDEC_SUBTABLE_POINTER |
+				HUFFDEC_RESULT_ENTRY(subtable_start) |
+				subtable_bits;
+		}
+
+		/* Fill the subtable entries for the current codeword. */
+		entry = decode_results[*sorted_syms++] | (len - table_bits);
+		i = subtable_start + (codeword >> table_bits);
+		stride = 1U << (len - table_bits);
+		do {
+			decode_table[i] = entry;
+			i += stride;
+		} while (i < cur_table_end);
+
+		/* Advance to the next codeword. */
+		if (codeword == (1U << len) - 1) /* last codeword (all 1's)? */
+			return true;
+		bit = 1U << bsr32(codeword ^ ((1U << len) - 1));
+		codeword &= bit - 1;
+		codeword |= bit;
+		count--;
+		while (count == 0)
+			count = len_counts[++len];
+	}
+}
+
+/* Build the decode table for the precode.  */
+static bool
+build_precode_decode_table(struct libdeflate_decompressor *d)
+{
+	/* When you change TABLEBITS, you must change ENOUGH, and vice versa! */
+	STATIC_ASSERT(PRECODE_TABLEBITS == 7 && PRECODE_ENOUGH == 128);
+
+	return build_decode_table(d->u.l.precode_decode_table,
+				  d->u.precode_lens,
+				  DEFLATE_NUM_PRECODE_SYMS,
+				  precode_decode_results,
+				  PRECODE_TABLEBITS,
+				  DEFLATE_MAX_PRE_CODEWORD_LEN,
+				  d->sorted_syms);
+}
+
+/* Build the decode table for the literal/length code.  */
+static bool
+build_litlen_decode_table(struct libdeflate_decompressor *d,
+			  unsigned num_litlen_syms, unsigned num_offset_syms)
+{
+	/* When you change TABLEBITS, you must change ENOUGH, and vice versa! */
+	STATIC_ASSERT(LITLEN_TABLEBITS == 10 && LITLEN_ENOUGH == 1334);
+
+	return build_decode_table(d->u.litlen_decode_table,
+				  d->u.l.lens,
+				  num_litlen_syms,
+				  litlen_decode_results,
+				  LITLEN_TABLEBITS,
+				  DEFLATE_MAX_LITLEN_CODEWORD_LEN,
+				  d->sorted_syms);
+}
+
+/* Build the decode table for the offset code.  */
+static bool
+build_offset_decode_table(struct libdeflate_decompressor *d,
+			  unsigned num_litlen_syms, unsigned num_offset_syms)
+{
+	/* When you change TABLEBITS, you must change ENOUGH, and vice versa! */
+	STATIC_ASSERT(OFFSET_TABLEBITS == 8 && OFFSET_ENOUGH == 402);
+
+	return build_decode_table(d->offset_decode_table,
+				  d->u.l.lens + num_litlen_syms,
+				  num_offset_syms,
+				  offset_decode_results,
+				  OFFSET_TABLEBITS,
+				  DEFLATE_MAX_OFFSET_CODEWORD_LEN,
+				  d->sorted_syms);
+}
+
+static forceinline machine_word_t
+repeat_byte(u8 b)
+{
+	machine_word_t v;
+
+	STATIC_ASSERT(WORDBITS == 32 || WORDBITS == 64);
+
+	v = b;
+	v |= v << 8;
+	v |= v << 16;
+	v |= v << ((WORDBITS == 64) ? 32 : 0);
+	return v;
+}
+
+static forceinline void
+copy_word_unaligned(const void *src, void *dst)
+{
+	store_word_unaligned(load_word_unaligned(src), dst);
+}
+
+/*****************************************************************************
+ *                         Main decompression routine
+ *****************************************************************************/
+
+typedef enum libdeflate_result (*decompress_func_t)
+	(struct libdeflate_decompressor * restrict d,
+	 const void * restrict in, size_t in_nbytes,
+	 void * restrict out, size_t out_nbytes_avail,
+	 size_t *actual_in_nbytes_ret, size_t *actual_out_nbytes_ret);
+
+#undef DEFAULT_IMPL
+#undef DISPATCH
+#if defined(__i386__) || defined(__x86_64__)
+#  include "x86/decompress_impl.h"
+#endif
+
+#ifndef DEFAULT_IMPL
+#  define FUNCNAME deflate_decompress_default
+#  define ATTRIBUTES
+#  include "decompress_template.h"
+#  define DEFAULT_IMPL deflate_decompress_default
+#endif
+
+#ifdef DISPATCH
+static enum libdeflate_result
+dispatch(struct libdeflate_decompressor * restrict d,
+	 const void * restrict in, size_t in_nbytes,
+	 void * restrict out, size_t out_nbytes_avail,
+	 size_t *actual_in_nbytes_ret, size_t *actual_out_nbytes_ret);
+
+static volatile decompress_func_t decompress_impl = dispatch;
+
+/* Choose the fastest implementation at runtime */
+static enum libdeflate_result
+dispatch(struct libdeflate_decompressor * restrict d,
+	 const void * restrict in, size_t in_nbytes,
+	 void * restrict out, size_t out_nbytes_avail,
+	 size_t *actual_in_nbytes_ret, size_t *actual_out_nbytes_ret)
+{
+	decompress_func_t f = arch_select_decompress_func();
+
+	if (f == NULL)
+		f = DEFAULT_IMPL;
+
+	decompress_impl = f;
+	return (*f)(d, in, in_nbytes, out, out_nbytes_avail,
+		    actual_in_nbytes_ret, actual_out_nbytes_ret);
+}
+#else
+#  define decompress_impl DEFAULT_IMPL /* only one implementation, use it */
+#endif
+
+
+/*
+ * This is the main DEFLATE decompression routine.  See libdeflate.h for the
+ * documentation.
+ *
+ * Note that the real code is in decompress_template.h.  The part here just
+ * handles calling the appropriate implementation depending on the CPU features
+ * at runtime.
+ */
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_deflate_decompress_ex(struct libdeflate_decompressor * restrict d,
+				 const void * restrict in, size_t in_nbytes,
+				 void * restrict out, size_t out_nbytes_avail,
+				 size_t *actual_in_nbytes_ret,
+				 size_t *actual_out_nbytes_ret)
+{
+	return decompress_impl(d, in, in_nbytes, out, out_nbytes_avail,
+			       actual_in_nbytes_ret, actual_out_nbytes_ret);
+}
+
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_deflate_decompress(struct libdeflate_decompressor * restrict d,
+			      const void * restrict in, size_t in_nbytes,
+			      void * restrict out, size_t out_nbytes_avail,
+			      size_t *actual_out_nbytes_ret)
+{
+	return libdeflate_deflate_decompress_ex(d, in, in_nbytes,
+						out, out_nbytes_avail,
+						NULL, actual_out_nbytes_ret);
+}
+
+LIBDEFLATEEXPORT struct libdeflate_decompressor * LIBDEFLATEAPI
+libdeflate_alloc_decompressor(void)
+{
+	/*
+	 * Note that only certain parts of the decompressor actually must be
+	 * initialized here:
+	 *
+	 * - 'static_codes_loaded' must be initialized to false.
+	 *
+	 * - The first half of the main portion of each decode table must be
+	 *   initialized to any value, to avoid reading from uninitialized
+	 *   memory during table expansion in build_decode_table().  (Although,
+	 *   this is really just to avoid warnings with dynamic tools like
+	 *   valgrind, since build_decode_table() is guaranteed to initialize
+	 *   all entries eventually anyway.)
+	 *
+	 * But for simplicity, we currently just zero the whole decompressor.
+	 */
+	struct libdeflate_decompressor *d = libdeflate_malloc(sizeof(*d));
+
+	if (d == NULL)
+		return NULL;
+	memset(d, 0, sizeof(*d));
+	return d;
+}
+
+LIBDEFLATEEXPORT void LIBDEFLATEAPI
+libdeflate_free_decompressor(struct libdeflate_decompressor *d)
+{
+	libdeflate_free(d);
+}

ADDED   3rd_party/libdeflate/lib/gzip_compress.c
Index: 3rd_party/libdeflate/lib/gzip_compress.c
==================================================================
--- 3rd_party/libdeflate/lib/gzip_compress.c
+++ 3rd_party/libdeflate/lib/gzip_compress.c
@@ -0,0 +1,95 @@
+/*
+ * gzip_compress.c - compress with a gzip wrapper
+ *
+ * Originally public domain; changes after 2016-09-07 are copyrighted.
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include "deflate_compress.h"
+#include "gzip_constants.h"
+#include "unaligned.h"
+
+#include "libdeflate.h"
+
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_gzip_compress(struct libdeflate_compressor *c,
+			 const void *in, size_t in_nbytes,
+			 void *out, size_t out_nbytes_avail)
+{
+	u8 *out_next = out;
+	unsigned compression_level;
+	u8 xfl;
+	size_t deflate_size;
+
+	if (out_nbytes_avail <= GZIP_MIN_OVERHEAD)
+		return 0;
+
+	/* ID1 */
+	*out_next++ = GZIP_ID1;
+	/* ID2 */
+	*out_next++ = GZIP_ID2;
+	/* CM */
+	*out_next++ = GZIP_CM_DEFLATE;
+	/* FLG */
+	*out_next++ = 0;
+	/* MTIME */
+	put_unaligned_le32(GZIP_MTIME_UNAVAILABLE, out_next);
+	out_next += 4;
+	/* XFL */
+	xfl = 0;
+	compression_level = deflate_get_compression_level(c);
+	if (compression_level < 2)
+		xfl |= GZIP_XFL_FASTEST_COMPRESSION;
+	else if (compression_level >= 8)
+		xfl |= GZIP_XFL_SLOWEST_COMPRESSION;
+	*out_next++ = xfl;
+	/* OS */
+	*out_next++ = GZIP_OS_UNKNOWN;	/* OS  */
+
+	/* Compressed data  */
+	deflate_size = libdeflate_deflate_compress(c, in, in_nbytes, out_next,
+					out_nbytes_avail - GZIP_MIN_OVERHEAD);
+	if (deflate_size == 0)
+		return 0;
+	out_next += deflate_size;
+
+	/* CRC32 */
+	put_unaligned_le32(libdeflate_crc32(0, in, in_nbytes), out_next);
+	out_next += 4;
+
+	/* ISIZE */
+	put_unaligned_le32((u32)in_nbytes, out_next);
+	out_next += 4;
+
+	return out_next - (u8 *)out;
+}
+
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_gzip_compress_bound(struct libdeflate_compressor *c,
+			       size_t in_nbytes)
+{
+	return GZIP_MIN_OVERHEAD +
+	       libdeflate_deflate_compress_bound(c, in_nbytes);
+}

ADDED   3rd_party/libdeflate/lib/gzip_constants.h
Index: 3rd_party/libdeflate/lib/gzip_constants.h
==================================================================
--- 3rd_party/libdeflate/lib/gzip_constants.h
+++ 3rd_party/libdeflate/lib/gzip_constants.h
@@ -0,0 +1,45 @@
+/*
+ * gzip_constants.h - constants for the gzip wrapper format
+ */
+
+#ifndef LIB_GZIP_CONSTANTS_H
+#define LIB_GZIP_CONSTANTS_H
+
+#define GZIP_MIN_HEADER_SIZE	10
+#define GZIP_FOOTER_SIZE	8
+#define GZIP_MIN_OVERHEAD	(GZIP_MIN_HEADER_SIZE + GZIP_FOOTER_SIZE)
+
+#define GZIP_ID1		0x1F
+#define GZIP_ID2		0x8B
+
+#define GZIP_CM_DEFLATE		8
+
+#define GZIP_FTEXT		0x01
+#define GZIP_FHCRC		0x02
+#define GZIP_FEXTRA		0x04
+#define GZIP_FNAME		0x08
+#define GZIP_FCOMMENT		0x10
+#define GZIP_FRESERVED		0xE0
+
+#define GZIP_MTIME_UNAVAILABLE	0
+
+#define GZIP_XFL_SLOWEST_COMPRESSION	0x02
+#define GZIP_XFL_FASTEST_COMPRESSION	0x04
+
+#define GZIP_OS_FAT		0
+#define GZIP_OS_AMIGA		1
+#define GZIP_OS_VMS		2
+#define GZIP_OS_UNIX		3
+#define GZIP_OS_VM_CMS		4
+#define GZIP_OS_ATARI_TOS	5
+#define GZIP_OS_HPFS		6
+#define GZIP_OS_MACINTOSH	7
+#define GZIP_OS_Z_SYSTEM	8
+#define GZIP_OS_CP_M		9
+#define GZIP_OS_TOPS_20		10
+#define GZIP_OS_NTFS		11
+#define GZIP_OS_QDOS		12
+#define GZIP_OS_RISCOS		13
+#define GZIP_OS_UNKNOWN		255
+
+#endif /* LIB_GZIP_CONSTANTS_H */

ADDED   3rd_party/libdeflate/lib/gzip_decompress.c
Index: 3rd_party/libdeflate/lib/gzip_decompress.c
==================================================================
--- 3rd_party/libdeflate/lib/gzip_decompress.c
+++ 3rd_party/libdeflate/lib/gzip_decompress.c
@@ -0,0 +1,148 @@
+/*
+ * gzip_decompress.c - decompress with a gzip wrapper
+ *
+ * Originally public domain; changes after 2016-09-07 are copyrighted.
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include "gzip_constants.h"
+#include "unaligned.h"
+
+#include "libdeflate.h"
+
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_gzip_decompress_ex(struct libdeflate_decompressor *d,
+			      const void *in, size_t in_nbytes,
+			      void *out, size_t out_nbytes_avail,
+			      size_t *actual_in_nbytes_ret,
+			      size_t *actual_out_nbytes_ret)
+{
+	const u8 *in_next = in;
+	const u8 * const in_end = in_next + in_nbytes;
+	u8 flg;
+	size_t actual_in_nbytes;
+	size_t actual_out_nbytes;
+	enum libdeflate_result result;
+
+	if (in_nbytes < GZIP_MIN_OVERHEAD)
+		return LIBDEFLATE_BAD_DATA;
+
+	/* ID1 */
+	if (*in_next++ != GZIP_ID1)
+		return LIBDEFLATE_BAD_DATA;
+	/* ID2 */
+	if (*in_next++ != GZIP_ID2)
+		return LIBDEFLATE_BAD_DATA;
+	/* CM */
+	if (*in_next++ != GZIP_CM_DEFLATE)
+		return LIBDEFLATE_BAD_DATA;
+	flg = *in_next++;
+	/* MTIME */
+	in_next += 4;
+	/* XFL */
+	in_next += 1;
+	/* OS */
+	in_next += 1;
+
+	if (flg & GZIP_FRESERVED)
+		return LIBDEFLATE_BAD_DATA;
+
+	/* Extra field */
+	if (flg & GZIP_FEXTRA) {
+		u16 xlen = get_unaligned_le16(in_next);
+		in_next += 2;
+
+		if (in_end - in_next < (u32)xlen + GZIP_FOOTER_SIZE)
+			return LIBDEFLATE_BAD_DATA;
+
+		in_next += xlen;
+	}
+
+	/* Original file name (zero terminated) */
+	if (flg & GZIP_FNAME) {
+		while (*in_next++ != 0 && in_next != in_end)
+			;
+		if (in_end - in_next < GZIP_FOOTER_SIZE)
+			return LIBDEFLATE_BAD_DATA;
+	}
+
+	/* File comment (zero terminated) */
+	if (flg & GZIP_FCOMMENT) {
+		while (*in_next++ != 0 && in_next != in_end)
+			;
+		if (in_end - in_next < GZIP_FOOTER_SIZE)
+			return LIBDEFLATE_BAD_DATA;
+	}
+
+	/* CRC16 for gzip header */
+	if (flg & GZIP_FHCRC) {
+		in_next += 2;
+		if (in_end - in_next < GZIP_FOOTER_SIZE)
+			return LIBDEFLATE_BAD_DATA;
+	}
+
+	/* Compressed data  */
+	result = libdeflate_deflate_decompress_ex(d, in_next,
+					in_end - GZIP_FOOTER_SIZE - in_next,
+					out, out_nbytes_avail,
+					&actual_in_nbytes,
+					actual_out_nbytes_ret);
+	if (result != LIBDEFLATE_SUCCESS)
+		return result;
+
+	if (actual_out_nbytes_ret)
+		actual_out_nbytes = *actual_out_nbytes_ret;
+	else
+		actual_out_nbytes = out_nbytes_avail;
+
+	in_next += actual_in_nbytes;
+
+	/* CRC32 */
+	if (libdeflate_crc32(0, out, actual_out_nbytes) !=
+	    get_unaligned_le32(in_next))
+		return LIBDEFLATE_BAD_DATA;
+	in_next += 4;
+
+	/* ISIZE */
+	if ((u32)actual_out_nbytes != get_unaligned_le32(in_next))
+		return LIBDEFLATE_BAD_DATA;
+	in_next += 4;
+
+	if (actual_in_nbytes_ret)
+		*actual_in_nbytes_ret = in_next - (u8 *)in;
+
+	return LIBDEFLATE_SUCCESS;
+}
+
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_gzip_decompress(struct libdeflate_decompressor *d,
+			   const void *in, size_t in_nbytes,
+			   void *out, size_t out_nbytes_avail,
+			   size_t *actual_out_nbytes_ret)
+{
+	return libdeflate_gzip_decompress_ex(d, in, in_nbytes,
+					     out, out_nbytes_avail,
+					     NULL, actual_out_nbytes_ret);
+}

ADDED   3rd_party/libdeflate/lib/hc_matchfinder.h
Index: 3rd_party/libdeflate/lib/hc_matchfinder.h
==================================================================
--- 3rd_party/libdeflate/lib/hc_matchfinder.h
+++ 3rd_party/libdeflate/lib/hc_matchfinder.h
@@ -0,0 +1,412 @@
+/*
+ * hc_matchfinder.h - Lempel-Ziv matchfinding with a hash table of linked lists
+ *
+ * Originally public domain; changes after 2016-09-07 are copyrighted.
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ *
+ * ---------------------------------------------------------------------------
+ *
+ *				   Algorithm
+ *
+ * This is a Hash Chains (hc) based matchfinder.
+ *
+ * The main data structure is a hash table where each hash bucket contains a
+ * linked list (or "chain") of sequences whose first 4 bytes share the same hash
+ * code.  Each sequence is identified by its starting position in the input
+ * buffer.
+ *
+ * The algorithm processes the input buffer sequentially.  At each byte
+ * position, the hash code of the first 4 bytes of the sequence beginning at
+ * that position (the sequence being matched against) is computed.  This
+ * identifies the hash bucket to use for that position.  Then, this hash
+ * bucket's linked list is searched for matches.  Then, a new linked list node
+ * is created to represent the current sequence and is prepended to the list.
+ *
+ * This algorithm has several useful properties:
+ *
+ * - It only finds true Lempel-Ziv matches; i.e., those where the matching
+ *   sequence occurs prior to the sequence being matched against.
+ *
+ * - The sequences in each linked list are always sorted by decreasing starting
+ *   position.  Therefore, the closest (smallest offset) matches are found
+ *   first, which in many compression formats tend to be the cheapest to encode.
+ *
+ * - Although fast running time is not guaranteed due to the possibility of the
+ *   lists getting very long, the worst degenerate behavior can be easily
+ *   prevented by capping the number of nodes searched at each position.
+ *
+ * - If the compressor decides not to search for matches at a certain position,
+ *   then that position can be quickly inserted without searching the list.
+ *
+ * - The algorithm is adaptable to sliding windows: just store the positions
+ *   relative to a "base" value that is updated from time to time, and stop
+ *   searching each list when the sequences get too far away.
+ *
+ * ----------------------------------------------------------------------------
+ *
+ *				 Optimizations
+ *
+ * The main hash table and chains handle length 4+ matches.  Length 3 matches
+ * are handled by a separate hash table with no chains.  This works well for
+ * typical "greedy" or "lazy"-style compressors, where length 3 matches are
+ * often only helpful if they have small offsets.  Instead of searching a full
+ * chain for length 3+ matches, the algorithm just checks for one close length 3
+ * match, then focuses on finding length 4+ matches.
+ *
+ * The longest_match() and skip_positions() functions are inlined into the
+ * compressors that use them.  This isn't just about saving the overhead of a
+ * function call.  These functions are intended to be called from the inner
+ * loops of compressors, where giving the compiler more control over register
+ * allocation is very helpful.  There is also significant benefit to be gained
+ * from allowing the CPU to predict branches independently at each call site.
+ * For example, "lazy"-style compressors can be written with two calls to
+ * longest_match(), each of which starts with a different 'best_len' and
+ * therefore has significantly different performance characteristics.
+ *
+ * Although any hash function can be used, a multiplicative hash is fast and
+ * works well.
+ *
+ * On some processors, it is significantly faster to extend matches by whole
+ * words (32 or 64 bits) instead of by individual bytes.  For this to be the
+ * case, the processor must implement unaligned memory accesses efficiently and
+ * must have either a fast "find first set bit" instruction or a fast "find last
+ * set bit" instruction, depending on the processor's endianness.
+ *
+ * The code uses one loop for finding the first match and one loop for finding a
+ * longer match.  Each of these loops is tuned for its respective task and in
+ * combination are faster than a single generalized loop that handles both
+ * tasks.
+ *
+ * The code also uses a tight inner loop that only compares the last and first
+ * bytes of a potential match.  It is only when these bytes match that a full
+ * match extension is attempted.
+ *
+ * ----------------------------------------------------------------------------
+ */
+
+#ifndef LIB_HC_MATCHFINDER_H
+#define LIB_HC_MATCHFINDER_H
+
+#include "matchfinder_common.h"
+
+#define HC_MATCHFINDER_HASH3_ORDER	15
+#define HC_MATCHFINDER_HASH4_ORDER	16
+
+#define HC_MATCHFINDER_TOTAL_HASH_SIZE			\
+	(((1UL << HC_MATCHFINDER_HASH3_ORDER) +		\
+	  (1UL << HC_MATCHFINDER_HASH4_ORDER)) * sizeof(mf_pos_t))
+
+struct hc_matchfinder {
+
+	/* The hash table for finding length 3 matches  */
+	mf_pos_t hash3_tab[1UL << HC_MATCHFINDER_HASH3_ORDER];
+
+	/* The hash table which contains the first nodes of the linked lists for
+	 * finding length 4+ matches  */
+	mf_pos_t hash4_tab[1UL << HC_MATCHFINDER_HASH4_ORDER];
+
+	/* The "next node" references for the linked lists.  The "next node" of
+	 * the node for the sequence with position 'pos' is 'next_tab[pos]'.  */
+	mf_pos_t next_tab[MATCHFINDER_WINDOW_SIZE];
+
+}
+#ifdef _aligned_attribute
+  _aligned_attribute(MATCHFINDER_MEM_ALIGNMENT)
+#endif
+;
+
+/* Prepare the matchfinder for a new input buffer.  */
+static forceinline void
+hc_matchfinder_init(struct hc_matchfinder *mf)
+{
+	STATIC_ASSERT(HC_MATCHFINDER_TOTAL_HASH_SIZE %
+		      MATCHFINDER_SIZE_ALIGNMENT == 0);
+
+	matchfinder_init((mf_pos_t *)mf, HC_MATCHFINDER_TOTAL_HASH_SIZE);
+}
+
+static forceinline void
+hc_matchfinder_slide_window(struct hc_matchfinder *mf)
+{
+	STATIC_ASSERT(sizeof(*mf) % MATCHFINDER_SIZE_ALIGNMENT == 0);
+
+	matchfinder_rebase((mf_pos_t *)mf, sizeof(*mf));
+}
+
+/*
+ * Find the longest match longer than 'best_len' bytes.
+ *
+ * @mf
+ *	The matchfinder structure.
+ * @in_base_p
+ *	Location of a pointer which points to the place in the input data the
+ *	matchfinder currently stores positions relative to.  This may be updated
+ *	by this function.
+ * @cur_pos
+ *	The current position in the input buffer relative to @in_base (the
+ *	position of the sequence being matched against).
+ * @best_len
+ *	Require a match longer than this length.
+ * @max_len
+ *	The maximum permissible match length at this position.
+ * @nice_len
+ *	Stop searching if a match of at least this length is found.
+ *	Must be <= @max_len.
+ * @max_search_depth
+ *	Limit on the number of potential matches to consider.  Must be >= 1.
+ * @next_hashes
+ *	The precomputed hash codes for the sequence beginning at @in_next.
+ *	These will be used and then updated with the precomputed hashcodes for
+ *	the sequence beginning at @in_next + 1.
+ * @offset_ret
+ *	If a match is found, its offset is returned in this location.
+ *
+ * Return the length of the match found, or 'best_len' if no match longer than
+ * 'best_len' was found.
+ */
+static forceinline u32
+hc_matchfinder_longest_match(struct hc_matchfinder * const restrict mf,
+			     const u8 ** const restrict in_base_p,
+			     const u8 * const restrict in_next,
+			     u32 best_len,
+			     const u32 max_len,
+			     const u32 nice_len,
+			     const u32 max_search_depth,
+			     u32 * const restrict next_hashes,
+			     u32 * const restrict offset_ret)
+{
+	u32 depth_remaining = max_search_depth;
+	const u8 *best_matchptr = in_next;
+	mf_pos_t cur_node3, cur_node4;
+	u32 hash3, hash4;
+	u32 next_hashseq;
+	u32 seq4;
+	const u8 *matchptr;
+	u32 len;
+	u32 cur_pos = in_next - *in_base_p;
+	const u8 *in_base;
+	mf_pos_t cutoff;
+
+	if (cur_pos == MATCHFINDER_WINDOW_SIZE) {
+		hc_matchfinder_slide_window(mf);
+		*in_base_p += MATCHFINDER_WINDOW_SIZE;
+		cur_pos = 0;
+	}
+
+	in_base = *in_base_p;
+	cutoff = cur_pos - MATCHFINDER_WINDOW_SIZE;
+
+	if (unlikely(max_len < 5)) /* can we read 4 bytes from 'in_next + 1'? */
+		goto out;
+
+	/* Get the precomputed hash codes.  */
+	hash3 = next_hashes[0];
+	hash4 = next_hashes[1];
+
+	/* From the hash buckets, get the first node of each linked list.  */
+	cur_node3 = mf->hash3_tab[hash3];
+	cur_node4 = mf->hash4_tab[hash4];
+
+	/* Update for length 3 matches.  This replaces the singleton node in the
+	 * 'hash3' bucket with the node for the current sequence.  */
+	mf->hash3_tab[hash3] = cur_pos;
+
+	/* Update for length 4 matches.  This prepends the node for the current
+	 * sequence to the linked list in the 'hash4' bucket.  */
+	mf->hash4_tab[hash4] = cur_pos;
+	mf->next_tab[cur_pos] = cur_node4;
+
+	/* Compute the next hash codes.  */
+	next_hashseq = get_unaligned_le32(in_next + 1);
+	next_hashes[0] = lz_hash(next_hashseq & 0xFFFFFF, HC_MATCHFINDER_HASH3_ORDER);
+	next_hashes[1] = lz_hash(next_hashseq, HC_MATCHFINDER_HASH4_ORDER);
+	prefetchw(&mf->hash3_tab[next_hashes[0]]);
+	prefetchw(&mf->hash4_tab[next_hashes[1]]);
+
+	if (best_len < 4) {  /* No match of length >= 4 found yet?  */
+
+		/* Check for a length 3 match if needed.  */
+
+		if (cur_node3 <= cutoff)
+			goto out;
+
+		seq4 = load_u32_unaligned(in_next);
+
+		if (best_len < 3) {
+			matchptr = &in_base[cur_node3];
+			if (load_u24_unaligned(matchptr) == loaded_u32_to_u24(seq4)) {
+				best_len = 3;
+				best_matchptr = matchptr;
+			}
+		}
+
+		/* Check for a length 4 match.  */
+
+		if (cur_node4 <= cutoff)
+			goto out;
+
+		for (;;) {
+			/* No length 4 match found yet.  Check the first 4 bytes.  */
+			matchptr = &in_base[cur_node4];
+
+			if (load_u32_unaligned(matchptr) == seq4)
+				break;
+
+			/* The first 4 bytes did not match.  Keep trying.  */
+			cur_node4 = mf->next_tab[cur_node4 & (MATCHFINDER_WINDOW_SIZE - 1)];
+			if (cur_node4 <= cutoff || !--depth_remaining)
+				goto out;
+		}
+
+		/* Found a match of length >= 4.  Extend it to its full length.  */
+		best_matchptr = matchptr;
+		best_len = lz_extend(in_next, best_matchptr, 4, max_len);
+		if (best_len >= nice_len)
+			goto out;
+		cur_node4 = mf->next_tab[cur_node4 & (MATCHFINDER_WINDOW_SIZE - 1)];
+		if (cur_node4 <= cutoff || !--depth_remaining)
+			goto out;
+	} else {
+		if (cur_node4 <= cutoff || best_len >= nice_len)
+			goto out;
+	}
+
+	/* Check for matches of length >= 5.  */
+
+	for (;;) {
+		for (;;) {
+			matchptr = &in_base[cur_node4];
+
+			/* Already found a length 4 match.  Try for a longer
+			 * match; start by checking either the last 4 bytes and
+			 * the first 4 bytes, or the last byte.  (The last byte,
+			 * the one which would extend the match length by 1, is
+			 * the most important.)  */
+		#if UNALIGNED_ACCESS_IS_FAST
+			if ((load_u32_unaligned(matchptr + best_len - 3) ==
+			     load_u32_unaligned(in_next + best_len - 3)) &&
+			    (load_u32_unaligned(matchptr) ==
+			     load_u32_unaligned(in_next)))
+		#else
+			if (matchptr[best_len] == in_next[best_len])
+		#endif
+				break;
+
+			/* Continue to the next node in the list.  */
+			cur_node4 = mf->next_tab[cur_node4 & (MATCHFINDER_WINDOW_SIZE - 1)];
+			if (cur_node4 <= cutoff || !--depth_remaining)
+				goto out;
+		}
+
+	#if UNALIGNED_ACCESS_IS_FAST
+		len = 4;
+	#else
+		len = 0;
+	#endif
+		len = lz_extend(in_next, matchptr, len, max_len);
+		if (len > best_len) {
+			/* This is the new longest match.  */
+			best_len = len;
+			best_matchptr = matchptr;
+			if (best_len >= nice_len)
+				goto out;
+		}
+
+		/* Continue to the next node in the list.  */
+		cur_node4 = mf->next_tab[cur_node4 & (MATCHFINDER_WINDOW_SIZE - 1)];
+		if (cur_node4 <= cutoff || !--depth_remaining)
+			goto out;
+	}
+out:
+	*offset_ret = in_next - best_matchptr;
+	return best_len;
+}
+
+/*
+ * Advance the matchfinder, but don't search for matches.
+ *
+ * @mf
+ *	The matchfinder structure.
+ * @in_base_p
+ *	Location of a pointer which points to the place in the input data the
+ *	matchfinder currently stores positions relative to.  This may be updated
+ *	by this function.
+ * @cur_pos
+ *	The current position in the input buffer relative to @in_base.
+ * @end_pos
+ *	The end position of the input buffer, relative to @in_base.
+ * @next_hashes
+ *	The precomputed hash codes for the sequence beginning at @in_next.
+ *	These will be used and then updated with the precomputed hashcodes for
+ *	the sequence beginning at @in_next + @count.
+ * @count
+ *	The number of bytes to advance.  Must be > 0.
+ *
+ * Returns @in_next + @count.
+ */
+static forceinline const u8 *
+hc_matchfinder_skip_positions(struct hc_matchfinder * const restrict mf,
+			      const u8 ** const restrict in_base_p,
+			      const u8 *in_next,
+			      const u8 * const in_end,
+			      const u32 count,
+			      u32 * const restrict next_hashes)
+{
+	u32 cur_pos;
+	u32 hash3, hash4;
+	u32 next_hashseq;
+	u32 remaining = count;
+
+	if (unlikely(count + 5 > in_end - in_next))
+		return &in_next[count];
+
+	cur_pos = in_next - *in_base_p;
+	hash3 = next_hashes[0];
+	hash4 = next_hashes[1];
+	do {
+		if (cur_pos == MATCHFINDER_WINDOW_SIZE) {
+			hc_matchfinder_slide_window(mf);
+			*in_base_p += MATCHFINDER_WINDOW_SIZE;
+			cur_pos = 0;
+		}
+		mf->hash3_tab[hash3] = cur_pos;
+		mf->next_tab[cur_pos] = mf->hash4_tab[hash4];
+		mf->hash4_tab[hash4] = cur_pos;
+
+		next_hashseq = get_unaligned_le32(++in_next);
+		hash3 = lz_hash(next_hashseq & 0xFFFFFF, HC_MATCHFINDER_HASH3_ORDER);
+		hash4 = lz_hash(next_hashseq, HC_MATCHFINDER_HASH4_ORDER);
+		cur_pos++;
+	} while (--remaining);
+
+	prefetchw(&mf->hash3_tab[hash3]);
+	prefetchw(&mf->hash4_tab[hash4]);
+	next_hashes[0] = hash3;
+	next_hashes[1] = hash4;
+
+	return in_next;
+}
+
+#endif /* LIB_HC_MATCHFINDER_H */

ADDED   3rd_party/libdeflate/lib/lib_common.h
Index: 3rd_party/libdeflate/lib/lib_common.h
==================================================================
--- 3rd_party/libdeflate/lib/lib_common.h
+++ 3rd_party/libdeflate/lib/lib_common.h
@@ -0,0 +1,67 @@
+/*
+ * lib_common.h - internal header included by all library code
+ */
+
+#ifndef LIB_LIB_COMMON_H
+#define LIB_LIB_COMMON_H
+
+#ifdef LIBDEFLATE_H
+#  error "lib_common.h must always be included before libdeflate.h"
+   /* because BUILDING_LIBDEFLATE must be set first */
+#endif
+
+#define BUILDING_LIBDEFLATE
+
+#include "../common/common_defs.h"
+
+/*
+ * Prefix with "_libdeflate_" all global symbols which are not part of the API
+ * and don't already have a "libdeflate" prefix.  This avoids exposing overly
+ * generic names when libdeflate is built as a static library.
+ *
+ * Note that the chosen prefix is not really important and can be changed
+ * without breaking library users.  It was just chosen so that the resulting
+ * symbol names are unlikely to conflict with those from any other software.
+ * Also note that this fixup has no useful effect when libdeflate is built as a
+ * shared library, since these symbols are not exported.
+ */
+#define SYM_FIXUP(sym)			_libdeflate_##sym
+#define deflate_get_compression_level	SYM_FIXUP(deflate_get_compression_level)
+#define _cpu_features			SYM_FIXUP(_cpu_features)
+#define setup_cpu_features		SYM_FIXUP(setup_cpu_features)
+
+void *libdeflate_malloc(size_t size);
+void libdeflate_free(void *ptr);
+
+void *libdeflate_aligned_malloc(size_t alignment, size_t size);
+void libdeflate_aligned_free(void *ptr);
+
+#ifdef FREESTANDING
+/*
+ * With -ffreestanding, <string.h> may be missing, and we must provide
+ * implementations of memset(), memcpy(), memmove(), and memcmp().
+ * See https://gcc.gnu.org/onlinedocs/gcc/Standards.html
+ *
+ * Also, -ffreestanding disables interpreting calls to these functions as
+ * built-ins.  E.g., calling memcpy(&v, p, WORDBYTES) will make a function call,
+ * not be optimized to a single load instruction.  For performance reasons we
+ * don't want that.  So, declare these functions as macros that expand to the
+ * corresponding built-ins.  This approach is recommended in the gcc man page.
+ * We still need the actual function definitions in case gcc calls them.
+ */
+void *memset(void *s, int c, size_t n);
+#define memset(s, c, n)		__builtin_memset((s), (c), (n))
+
+void *memcpy(void *dest, const void *src, size_t n);
+#define memcpy(dest, src, n)	__builtin_memcpy((dest), (src), (n))
+
+void *memmove(void *dest, const void *src, size_t n);
+#define memmove(dest, src, n)	__builtin_memmove((dest), (src), (n))
+
+int memcmp(const void *s1, const void *s2, size_t n);
+#define memcmp(s1, s2, n)	__builtin_memcmp((s1), (s2), (n))
+#else
+#include <string.h>
+#endif
+
+#endif /* LIB_LIB_COMMON_H */

ADDED   3rd_party/libdeflate/lib/matchfinder_common.h
Index: 3rd_party/libdeflate/lib/matchfinder_common.h
==================================================================
--- 3rd_party/libdeflate/lib/matchfinder_common.h
+++ 3rd_party/libdeflate/lib/matchfinder_common.h
@@ -0,0 +1,176 @@
+/*
+ * matchfinder_common.h - common code for Lempel-Ziv matchfinding
+ */
+
+#ifndef LIB_MATCHFINDER_COMMON_H
+#define LIB_MATCHFINDER_COMMON_H
+
+#include "lib_common.h"
+#include "unaligned.h"
+
+#ifndef MATCHFINDER_WINDOW_ORDER
+#  error "MATCHFINDER_WINDOW_ORDER must be defined!"
+#endif
+
+#define MATCHFINDER_WINDOW_SIZE (1UL << MATCHFINDER_WINDOW_ORDER)
+
+typedef s16 mf_pos_t;
+
+#define MATCHFINDER_INITVAL ((mf_pos_t)-MATCHFINDER_WINDOW_SIZE)
+
+/*
+ * Required alignment of the matchfinder buffer pointer and size.  The values
+ * here come from the AVX-2 implementation, which is the worst case.
+ */
+#define MATCHFINDER_MEM_ALIGNMENT	32
+#define MATCHFINDER_SIZE_ALIGNMENT	128
+
+#undef matchfinder_init
+#undef matchfinder_rebase
+#ifdef _aligned_attribute
+#  if defined(__arm__) || defined(__aarch64__)
+#    include "arm/matchfinder_impl.h"
+#  elif defined(__i386__) || defined(__x86_64__)
+#    include "x86/matchfinder_impl.h"
+#  endif
+#endif
+
+/*
+ * Initialize the hash table portion of the matchfinder.
+ *
+ * Essentially, this is an optimized memset().
+ *
+ * 'data' must be aligned to a MATCHFINDER_MEM_ALIGNMENT boundary, and
+ * 'size' must be a multiple of MATCHFINDER_SIZE_ALIGNMENT.
+ */
+#ifndef matchfinder_init
+static forceinline void
+matchfinder_init(mf_pos_t *data, size_t size)
+{
+	size_t num_entries = size / sizeof(*data);
+	size_t i;
+
+	for (i = 0; i < num_entries; i++)
+		data[i] = MATCHFINDER_INITVAL;
+}
+#endif
+
+/*
+ * Slide the matchfinder by WINDOW_SIZE bytes.
+ *
+ * This must be called just after each WINDOW_SIZE bytes have been run through
+ * the matchfinder.
+ *
+ * This will subtract WINDOW_SIZE bytes from each entry in the array specified.
+ * The effect is that all entries are updated to be relative to the current
+ * position, rather than the position WINDOW_SIZE bytes prior.
+ *
+ * Underflow is detected and replaced with signed saturation.  This ensures that
+ * once the sliding window has passed over a position, that position forever
+ * remains out of bounds.
+ *
+ * The array passed in must contain all matchfinder data that is
+ * position-relative.  Concretely, this will include the hash table as well as
+ * the table of positions that is used to link together the sequences in each
+ * hash bucket.  Note that in the latter table, the links are 1-ary in the case
+ * of "hash chains", and 2-ary in the case of "binary trees".  In either case,
+ * the links need to be rebased in the same way.
+ *
+ * 'data' must be aligned to a MATCHFINDER_MEM_ALIGNMENT boundary, and
+ * 'size' must be a multiple of MATCHFINDER_SIZE_ALIGNMENT.
+ */
+#ifndef matchfinder_rebase
+static forceinline void
+matchfinder_rebase(mf_pos_t *data, size_t size)
+{
+	size_t num_entries = size / sizeof(*data);
+	size_t i;
+
+	if (MATCHFINDER_WINDOW_SIZE == 32768) {
+		/* Branchless version for 32768 byte windows.  If the value was
+		 * already negative, clear all bits except the sign bit; this
+		 * changes the value to -32768.  Otherwise, set the sign bit;
+		 * this is equivalent to subtracting 32768.  */
+		for (i = 0; i < num_entries; i++) {
+			u16 v = data[i];
+			u16 sign_bit = v & 0x8000;
+			v &= sign_bit - ((sign_bit >> 15) ^ 1);
+			v |= 0x8000;
+			data[i] = v;
+		}
+		return;
+	}
+
+	for (i = 0; i < num_entries; i++) {
+		if (data[i] >= 0)
+			data[i] -= (mf_pos_t)-MATCHFINDER_WINDOW_SIZE;
+		else
+			data[i] = (mf_pos_t)-MATCHFINDER_WINDOW_SIZE;
+	}
+}
+#endif
+
+/*
+ * The hash function: given a sequence prefix held in the low-order bits of a
+ * 32-bit value, multiply by a carefully-chosen large constant.  Discard any
+ * bits of the product that don't fit in a 32-bit value, but take the
+ * next-highest @num_bits bits of the product as the hash value, as those have
+ * the most randomness.
+ */
+static forceinline u32
+lz_hash(u32 seq, unsigned num_bits)
+{
+	return (u32)(seq * 0x1E35A7BD) >> (32 - num_bits);
+}
+
+/*
+ * Return the number of bytes at @matchptr that match the bytes at @strptr, up
+ * to a maximum of @max_len.  Initially, @start_len bytes are matched.
+ */
+static forceinline unsigned
+lz_extend(const u8 * const strptr, const u8 * const matchptr,
+	  const unsigned start_len, const unsigned max_len)
+{
+	unsigned len = start_len;
+	machine_word_t v_word;
+
+	if (UNALIGNED_ACCESS_IS_FAST) {
+
+		if (likely(max_len - len >= 4 * WORDBYTES)) {
+
+		#define COMPARE_WORD_STEP				\
+			v_word = load_word_unaligned(&matchptr[len]) ^	\
+				 load_word_unaligned(&strptr[len]);	\
+			if (v_word != 0)				\
+				goto word_differs;			\
+			len += WORDBYTES;				\
+
+			COMPARE_WORD_STEP
+			COMPARE_WORD_STEP
+			COMPARE_WORD_STEP
+			COMPARE_WORD_STEP
+		#undef COMPARE_WORD_STEP
+		}
+
+		while (len + WORDBYTES <= max_len) {
+			v_word = load_word_unaligned(&matchptr[len]) ^
+				 load_word_unaligned(&strptr[len]);
+			if (v_word != 0)
+				goto word_differs;
+			len += WORDBYTES;
+		}
+	}
+
+	while (len < max_len && matchptr[len] == strptr[len])
+		len++;
+	return len;
+
+word_differs:
+	if (CPU_IS_LITTLE_ENDIAN())
+		len += (bsfw(v_word) >> 3);
+	else
+		len += (WORDBITS - 1 - bsrw(v_word)) >> 3;
+	return len;
+}
+
+#endif /* LIB_MATCHFINDER_COMMON_H */

ADDED   3rd_party/libdeflate/lib/unaligned.h
Index: 3rd_party/libdeflate/lib/unaligned.h
==================================================================
--- 3rd_party/libdeflate/lib/unaligned.h
+++ 3rd_party/libdeflate/lib/unaligned.h
@@ -0,0 +1,228 @@
+/*
+ * unaligned.h - inline functions for unaligned memory accesses
+ */
+
+#ifndef LIB_UNALIGNED_H
+#define LIB_UNALIGNED_H
+
+#include "lib_common.h"
+
+/***** Unaligned loads and stores without endianness conversion *****/
+
+/*
+ * memcpy() is portable, and it usually gets optimized appropriately by modern
+ * compilers.  I.e., each memcpy() of 1, 2, 4, or WORDBYTES bytes gets compiled
+ * to a load or store instruction, not to an actual function call.
+ *
+ * We no longer use the "packed struct" approach, as that is nonstandard, has
+ * unclear semantics, and doesn't receive enough testing
+ * (see https://gcc.gnu.org/bugzilla/show_bug.cgi?id=94994).
+ *
+ * arm32 with __ARM_FEATURE_UNALIGNED in gcc 5 and earlier is a known exception
+ * where memcpy() generates inefficient code
+ * (https://gcc.gnu.org/bugzilla/show_bug.cgi?id=67366).  However, we no longer
+ * consider that one case important enough to maintain different code for.
+ * If you run into it, please just use a newer version of gcc (or use clang).
+ */
+
+#define DEFINE_UNALIGNED_TYPE(type)				\
+static forceinline type						\
+load_##type##_unaligned(const void *p)				\
+{								\
+	type v;							\
+	memcpy(&v, p, sizeof(v));				\
+	return v;						\
+}								\
+								\
+static forceinline void						\
+store_##type##_unaligned(type v, void *p)			\
+{								\
+	memcpy(p, &v, sizeof(v));				\
+}
+
+DEFINE_UNALIGNED_TYPE(u16)
+DEFINE_UNALIGNED_TYPE(u32)
+DEFINE_UNALIGNED_TYPE(u64)
+DEFINE_UNALIGNED_TYPE(machine_word_t)
+
+#define load_word_unaligned	load_machine_word_t_unaligned
+#define store_word_unaligned	store_machine_word_t_unaligned
+
+/***** Unaligned loads with endianness conversion *****/
+
+static forceinline u16
+get_unaligned_le16(const u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST)
+		return le16_bswap(load_u16_unaligned(p));
+	else
+		return ((u16)p[1] << 8) | p[0];
+}
+
+static forceinline u16
+get_unaligned_be16(const u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST)
+		return be16_bswap(load_u16_unaligned(p));
+	else
+		return ((u16)p[0] << 8) | p[1];
+}
+
+static forceinline u32
+get_unaligned_le32(const u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST)
+		return le32_bswap(load_u32_unaligned(p));
+	else
+		return ((u32)p[3] << 24) | ((u32)p[2] << 16) |
+			((u32)p[1] << 8) | p[0];
+}
+
+static forceinline u32
+get_unaligned_be32(const u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST)
+		return be32_bswap(load_u32_unaligned(p));
+	else
+		return ((u32)p[0] << 24) | ((u32)p[1] << 16) |
+			((u32)p[2] << 8) | p[3];
+}
+
+static forceinline u64
+get_unaligned_le64(const u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST)
+		return le64_bswap(load_u64_unaligned(p));
+	else
+		return ((u64)p[7] << 56) | ((u64)p[6] << 48) |
+			((u64)p[5] << 40) | ((u64)p[4] << 32) |
+			((u64)p[3] << 24) | ((u64)p[2] << 16) |
+			((u64)p[1] << 8) | p[0];
+}
+
+static forceinline machine_word_t
+get_unaligned_leword(const u8 *p)
+{
+	STATIC_ASSERT(WORDBITS == 32 || WORDBITS == 64);
+	if (WORDBITS == 32)
+		return get_unaligned_le32(p);
+	else
+		return get_unaligned_le64(p);
+}
+
+/***** Unaligned stores with endianness conversion *****/
+
+static forceinline void
+put_unaligned_le16(u16 v, u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST) {
+		store_u16_unaligned(le16_bswap(v), p);
+	} else {
+		p[0] = (u8)(v >> 0);
+		p[1] = (u8)(v >> 8);
+	}
+}
+
+static forceinline void
+put_unaligned_be16(u16 v, u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST) {
+		store_u16_unaligned(be16_bswap(v), p);
+	} else {
+		p[0] = (u8)(v >> 8);
+		p[1] = (u8)(v >> 0);
+	}
+}
+
+static forceinline void
+put_unaligned_le32(u32 v, u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST) {
+		store_u32_unaligned(le32_bswap(v), p);
+	} else {
+		p[0] = (u8)(v >> 0);
+		p[1] = (u8)(v >> 8);
+		p[2] = (u8)(v >> 16);
+		p[3] = (u8)(v >> 24);
+	}
+}
+
+static forceinline void
+put_unaligned_be32(u32 v, u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST) {
+		store_u32_unaligned(be32_bswap(v), p);
+	} else {
+		p[0] = (u8)(v >> 24);
+		p[1] = (u8)(v >> 16);
+		p[2] = (u8)(v >> 8);
+		p[3] = (u8)(v >> 0);
+	}
+}
+
+static forceinline void
+put_unaligned_le64(u64 v, u8 *p)
+{
+	if (UNALIGNED_ACCESS_IS_FAST) {
+		store_u64_unaligned(le64_bswap(v), p);
+	} else {
+		p[0] = (u8)(v >> 0);
+		p[1] = (u8)(v >> 8);
+		p[2] = (u8)(v >> 16);
+		p[3] = (u8)(v >> 24);
+		p[4] = (u8)(v >> 32);
+		p[5] = (u8)(v >> 40);
+		p[6] = (u8)(v >> 48);
+		p[7] = (u8)(v >> 56);
+	}
+}
+
+static forceinline void
+put_unaligned_leword(machine_word_t v, u8 *p)
+{
+	STATIC_ASSERT(WORDBITS == 32 || WORDBITS == 64);
+	if (WORDBITS == 32)
+		put_unaligned_le32(v, p);
+	else
+		put_unaligned_le64(v, p);
+}
+
+/***** 24-bit loads *****/
+
+/*
+ * Given a 32-bit value that was loaded with the platform's native endianness,
+ * return a 32-bit value whose high-order 8 bits are 0 and whose low-order 24
+ * bits contain the first 3 bytes, arranged in octets in a platform-dependent
+ * order, at the memory location from which the input 32-bit value was loaded.
+ */
+static forceinline u32
+loaded_u32_to_u24(u32 v)
+{
+	if (CPU_IS_LITTLE_ENDIAN())
+		return v & 0xFFFFFF;
+	else
+		return v >> 8;
+}
+
+/*
+ * Load the next 3 bytes from the memory location @p into the 24 low-order bits
+ * of a 32-bit value.  The order in which the 3 bytes will be arranged as octets
+ * in the 24 bits is platform-dependent.  At least LOAD_U24_REQUIRED_NBYTES
+ * bytes must be available at @p; note that this may be more than 3.
+ */
+static forceinline u32
+load_u24_unaligned(const u8 *p)
+{
+#if UNALIGNED_ACCESS_IS_FAST
+#  define LOAD_U24_REQUIRED_NBYTES 4
+	return loaded_u32_to_u24(load_u32_unaligned(p));
+#else
+#  define LOAD_U24_REQUIRED_NBYTES 3
+	if (CPU_IS_LITTLE_ENDIAN())
+		return ((u32)p[0] << 0) | ((u32)p[1] << 8) | ((u32)p[2] << 16);
+	else
+		return ((u32)p[2] << 0) | ((u32)p[1] << 8) | ((u32)p[0] << 16);
+#endif
+}
+
+#endif /* LIB_UNALIGNED_H */

ADDED   3rd_party/libdeflate/lib/utils.c
Index: 3rd_party/libdeflate/lib/utils.c
==================================================================
--- 3rd_party/libdeflate/lib/utils.c
+++ 3rd_party/libdeflate/lib/utils.c
@@ -0,0 +1,142 @@
+/*
+ * utils.c - utility functions for libdeflate
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include "lib_common.h"
+
+#include "libdeflate.h"
+
+#ifdef FREESTANDING
+#  define malloc NULL
+#  define free NULL
+#else
+#  include <stdlib.h>
+#endif
+
+static void *(*libdeflate_malloc_func)(size_t) = malloc;
+static void (*libdeflate_free_func)(void *) = free;
+
+void *
+libdeflate_malloc(size_t size)
+{
+	return (*libdeflate_malloc_func)(size);
+}
+
+void
+libdeflate_free(void *ptr)
+{
+	(*libdeflate_free_func)(ptr);
+}
+
+void *
+libdeflate_aligned_malloc(size_t alignment, size_t size)
+{
+	void *ptr = libdeflate_malloc(sizeof(void *) + alignment - 1 + size);
+	if (ptr) {
+		void *orig_ptr = ptr;
+		ptr = (void *)ALIGN((uintptr_t)ptr + sizeof(void *), alignment);
+		((void **)ptr)[-1] = orig_ptr;
+	}
+	return ptr;
+}
+
+void
+libdeflate_aligned_free(void *ptr)
+{
+	if (ptr)
+		libdeflate_free(((void **)ptr)[-1]);
+}
+
+LIBDEFLATEEXPORT void LIBDEFLATEAPI
+libdeflate_set_memory_allocator(void *(*malloc_func)(size_t),
+				void (*free_func)(void *))
+{
+	libdeflate_malloc_func = malloc_func;
+	libdeflate_free_func = free_func;
+}
+
+/*
+ * Implementations of libc functions for freestanding library builds.
+ * Normal library builds don't use these.  Not optimized yet; usually the
+ * compiler expands these functions and doesn't actually call them anyway.
+ */
+#ifdef FREESTANDING
+#undef memset
+void * __attribute__((weak))
+memset(void *s, int c, size_t n)
+{
+	u8 *p = s;
+	size_t i;
+
+	for (i = 0; i < n; i++)
+		p[i] = c;
+	return s;
+}
+
+#undef memcpy
+void * __attribute__((weak))
+memcpy(void *dest, const void *src, size_t n)
+{
+	u8 *d = dest;
+	const u8 *s = src;
+	size_t i;
+
+	for (i = 0; i < n; i++)
+		d[i] = s[i];
+	return dest;
+}
+
+#undef memmove
+void * __attribute__((weak))
+memmove(void *dest, const void *src, size_t n)
+{
+	u8 *d = dest;
+	const u8 *s = src;
+	size_t i;
+
+	if (d <= s)
+		return memcpy(d, s, n);
+
+	for (i = n; i > 0; i--)
+		d[i - 1] = s[i - 1];
+	return dest;
+}
+
+#undef memcmp
+int __attribute__((weak))
+memcmp(const void *s1, const void *s2, size_t n)
+{
+	const u8 *p1 = s1;
+	const u8 *p2 = s2;
+	size_t i;
+
+	for (i = 0; i < n; i++) {
+		if (p1[i] != p2[i])
+			return (int)p1[i] - (int)p2[i];
+	}
+	return 0;
+}
+#endif /* FREESTANDING */

ADDED   3rd_party/libdeflate/lib/x86/adler32_impl.h
Index: 3rd_party/libdeflate/lib/x86/adler32_impl.h
==================================================================
--- 3rd_party/libdeflate/lib/x86/adler32_impl.h
+++ 3rd_party/libdeflate/lib/x86/adler32_impl.h
@@ -0,0 +1,337 @@
+/*
+ * x86/adler32_impl.h - x86 implementations of Adler-32 checksum algorithm
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#ifndef LIB_X86_ADLER32_IMPL_H
+#define LIB_X86_ADLER32_IMPL_H
+
+#include "cpu_features.h"
+
+/*
+ * The following macros horizontally sum the s1 counters and add them to the
+ * real s1, and likewise for s2.  They do this via a series of reductions, each
+ * of which halves the vector length, until just one counter remains.
+ *
+ * The s1 reductions don't depend on the s2 reductions and vice versa, so for
+ * efficiency they are interleaved.  Also, every other s1 counter is 0 due to
+ * the 'psadbw' instruction (_mm_sad_epu8) summing groups of 8 bytes rather than
+ * 4; hence, one of the s1 reductions is skipped when going from 128 => 32 bits.
+ */
+
+#define ADLER32_FINISH_VEC_CHUNK_128(s1, s2, v_s1, v_s2)		    \
+{									    \
+	__v4su s1_last = (v_s1), s2_last = (v_s2);			    \
+									    \
+	/* 128 => 32 bits */						    \
+	s2_last += (__v4su)_mm_shuffle_epi32((__m128i)s2_last, 0x31);	    \
+	s1_last += (__v4su)_mm_shuffle_epi32((__m128i)s1_last, 0x02);	    \
+	s2_last += (__v4su)_mm_shuffle_epi32((__m128i)s2_last, 0x02);	    \
+									    \
+	*(s1) += (u32)_mm_cvtsi128_si32((__m128i)s1_last);		    \
+	*(s2) += (u32)_mm_cvtsi128_si32((__m128i)s2_last);		    \
+}
+
+#define ADLER32_FINISH_VEC_CHUNK_256(s1, s2, v_s1, v_s2)		    \
+{									    \
+	__v4su s1_128bit, s2_128bit;					    \
+									    \
+	/* 256 => 128 bits */						    \
+	s1_128bit = (__v4su)_mm256_extracti128_si256((__m256i)(v_s1), 0) +  \
+		    (__v4su)_mm256_extracti128_si256((__m256i)(v_s1), 1);   \
+	s2_128bit = (__v4su)_mm256_extracti128_si256((__m256i)(v_s2), 0) +  \
+		    (__v4su)_mm256_extracti128_si256((__m256i)(v_s2), 1);   \
+									    \
+	ADLER32_FINISH_VEC_CHUNK_128((s1), (s2), s1_128bit, s2_128bit);	    \
+}
+
+#define ADLER32_FINISH_VEC_CHUNK_512(s1, s2, v_s1, v_s2)		    \
+{									    \
+	__v8su s1_256bit, s2_256bit;					    \
+									    \
+	/* 512 => 256 bits */						    \
+	s1_256bit = (__v8su)_mm512_extracti64x4_epi64((__m512i)(v_s1), 0) + \
+		    (__v8su)_mm512_extracti64x4_epi64((__m512i)(v_s1), 1);  \
+	s2_256bit = (__v8su)_mm512_extracti64x4_epi64((__m512i)(v_s2), 0) + \
+		    (__v8su)_mm512_extracti64x4_epi64((__m512i)(v_s2), 1);  \
+									    \
+	ADLER32_FINISH_VEC_CHUNK_256((s1), (s2), s1_256bit, s2_256bit);	    \
+}
+
+/* AVX-512BW implementation: like the AVX2 one, but does 64 bytes at a time */
+#undef DISPATCH_AVX512BW
+#if !defined(DEFAULT_IMPL) &&						\
+    /*
+     * clang before v3.9 is missing some AVX-512BW intrinsics including
+     * _mm512_sad_epu8(), a.k.a. __builtin_ia32_psadbw512.  So just make using
+     * AVX-512BW, even when __AVX512BW__ is defined, conditional on
+     * COMPILER_SUPPORTS_AVX512BW_TARGET where we check for that builtin.
+     */									\
+    COMPILER_SUPPORTS_AVX512BW_TARGET &&				\
+    (defined(__AVX512BW__) || (X86_CPU_FEATURES_ENABLED &&		\
+			       COMPILER_SUPPORTS_AVX512BW_TARGET_INTRINSICS))
+#  define FUNCNAME		adler32_avx512bw
+#  define FUNCNAME_CHUNK	adler32_avx512bw_chunk
+#  define IMPL_ALIGNMENT	64
+#  define IMPL_SEGMENT_SIZE	64
+#  define IMPL_MAX_CHUNK_SIZE	MAX_CHUNK_SIZE
+#  ifdef __AVX512BW__
+#    define ATTRIBUTES
+#    define DEFAULT_IMPL	adler32_avx512bw
+#  else
+#    define ATTRIBUTES		__attribute__((target("avx512bw")))
+#    define DISPATCH		1
+#    define DISPATCH_AVX512BW	1
+#  endif
+#  include <immintrin.h>
+static forceinline ATTRIBUTES void
+adler32_avx512bw_chunk(const __m512i *p, const __m512i *const end,
+		       u32 *s1, u32 *s2)
+{
+	const __m512i zeroes = _mm512_setzero_si512();
+	const __v64qi multipliers = (__v64qi){
+		64, 63, 62, 61, 60, 59, 58, 57, 56, 55, 54, 53, 52, 51, 50, 49,
+		48, 47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33,
+		32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17,
+		16, 15, 14, 13, 12, 11, 10,  9,  8,  7,  6,  5,  4,  3,  2,  1,
+	};
+	const __v32hi ones = (__v32hi)_mm512_set1_epi16(1);
+	__v16si v_s1 = (__v16si)zeroes;
+	__v16si v_s1_sums = (__v16si)zeroes;
+	__v16si v_s2 = (__v16si)zeroes;
+
+	do {
+		/* Load the next 64-byte segment */
+		__m512i bytes = *p++;
+
+		/* Multiply the bytes by 64...1 (the number of times they need
+		 * to be added to s2) and add adjacent products */
+		__v32hi sums = (__v32hi)_mm512_maddubs_epi16(
+						bytes, (__m512i)multipliers);
+
+		/* Keep sum of all previous s1 counters, for adding to s2 later.
+		 * This allows delaying the multiplication by 64 to the end. */
+		v_s1_sums += v_s1;
+
+		/* Add the sum of each group of 8 bytes to the corresponding s1
+		 * counter */
+		v_s1 += (__v16si)_mm512_sad_epu8(bytes, zeroes);
+
+		/* Add the sum of each group of 4 products of the bytes by
+		 * 64...1 to the corresponding s2 counter */
+		v_s2 += (__v16si)_mm512_madd_epi16((__m512i)sums,
+						   (__m512i)ones);
+	} while (p != end);
+
+	/* Finish the s2 counters by adding the sum of the s1 values at the
+	 * beginning of each segment, multiplied by the segment size (64) */
+	v_s2 += (__v16si)_mm512_slli_epi32((__m512i)v_s1_sums, 6);
+
+	/* Add the counters to the real s1 and s2 */
+	ADLER32_FINISH_VEC_CHUNK_512(s1, s2, v_s1, v_s2);
+}
+#  include "../adler32_vec_template.h"
+#endif /* AVX-512BW implementation */
+
+/* AVX2 implementation: like the AVX-512BW one, but does 32 bytes at a time */
+#undef DISPATCH_AVX2
+#if !defined(DEFAULT_IMPL) &&	\
+	(defined(__AVX2__) || (X86_CPU_FEATURES_ENABLED &&	\
+			       COMPILER_SUPPORTS_AVX2_TARGET_INTRINSICS))
+#  define FUNCNAME		adler32_avx2
+#  define FUNCNAME_CHUNK	adler32_avx2_chunk
+#  define IMPL_ALIGNMENT	32
+#  define IMPL_SEGMENT_SIZE	32
+#  define IMPL_MAX_CHUNK_SIZE	MAX_CHUNK_SIZE
+#  ifdef __AVX2__
+#    define ATTRIBUTES
+#    define DEFAULT_IMPL	adler32_avx2
+#  else
+#    define ATTRIBUTES		__attribute__((target("avx2")))
+#    define DISPATCH		1
+#    define DISPATCH_AVX2	1
+#  endif
+#  include <immintrin.h>
+static forceinline ATTRIBUTES void
+adler32_avx2_chunk(const __m256i *p, const __m256i *const end, u32 *s1, u32 *s2)
+{
+	const __m256i zeroes = _mm256_setzero_si256();
+	const __v32qu multipliers = (__v32qu){
+		32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17,
+		16, 15, 14, 13, 12, 11, 10,  9,  8,  7,  6,  5,  4,  3,  2,  1,
+	};
+	const __v16hu ones = (__v16hu)_mm256_set1_epi16(1);
+	__v8su v_s1 = (__v8su)zeroes;
+	__v8su v_s1_sums = (__v8su)zeroes;
+	__v8su v_s2 = (__v8su)zeroes;
+
+	do {
+		/* Load the next 32-byte segment */
+		__m256i bytes = *p++;
+
+		/* Multiply the bytes by 32...1 (the number of times they need
+		 * to be added to s2) and add adjacent products */
+		__v16hu sums = (__v16hu)_mm256_maddubs_epi16(
+						bytes, (__m256i)multipliers);
+
+		/* Keep sum of all previous s1 counters, for adding to s2 later.
+		 * This allows delaying the multiplication by 32 to the end. */
+		v_s1_sums += v_s1;
+
+		/* Add the sum of each group of 8 bytes to the corresponding s1
+		 * counter */
+		v_s1 += (__v8su)_mm256_sad_epu8(bytes, zeroes);
+
+		/* Add the sum of each group of 4 products of the bytes by
+		 * 32...1 to the corresponding s2 counter */
+		v_s2 += (__v8su)_mm256_madd_epi16((__m256i)sums, (__m256i)ones);
+	} while (p != end);
+
+	/* Finish the s2 counters by adding the sum of the s1 values at the
+	 * beginning of each segment, multiplied by the segment size (32) */
+	v_s2 += (__v8su)_mm256_slli_epi32((__m256i)v_s1_sums, 5);
+
+	/* Add the counters to the real s1 and s2 */
+	ADLER32_FINISH_VEC_CHUNK_256(s1, s2, v_s1, v_s2);
+}
+#  include "../adler32_vec_template.h"
+#endif /* AVX2 implementation */
+
+/* SSE2 implementation */
+#undef DISPATCH_SSE2
+#if !defined(DEFAULT_IMPL) &&	\
+	(defined(__SSE2__) || (X86_CPU_FEATURES_ENABLED &&	\
+			       COMPILER_SUPPORTS_SSE2_TARGET_INTRINSICS))
+#  define FUNCNAME		adler32_sse2
+#  define FUNCNAME_CHUNK	adler32_sse2_chunk
+#  define IMPL_ALIGNMENT	16
+#  define IMPL_SEGMENT_SIZE	32
+/*
+ * The 16-bit precision byte counters must not be allowed to undergo *signed*
+ * overflow, otherwise the signed multiplications at the end (_mm_madd_epi16)
+ * would behave incorrectly.
+ */
+#  define IMPL_MAX_CHUNK_SIZE	(32 * (0x7FFF / 0xFF))
+#  ifdef __SSE2__
+#    define ATTRIBUTES
+#    define DEFAULT_IMPL	adler32_sse2
+#  else
+#    define ATTRIBUTES		__attribute__((target("sse2")))
+#    define DISPATCH		1
+#    define DISPATCH_SSE2	1
+#  endif
+#  include <emmintrin.h>
+static forceinline ATTRIBUTES void
+adler32_sse2_chunk(const __m128i *p, const __m128i *const end, u32 *s1, u32 *s2)
+{
+	const __m128i zeroes = _mm_setzero_si128();
+
+	/* s1 counters: 32-bit, sum of bytes */
+	__v4su v_s1 = (__v4su)zeroes;
+
+	/* s2 counters: 32-bit, sum of s1 values */
+	__v4su v_s2 = (__v4su)zeroes;
+
+	/*
+	 * Thirty-two 16-bit counters for byte sums.  Each accumulates the bytes
+	 * that eventually need to be multiplied by a number 32...1 for addition
+	 * into s2.
+	 */
+	__v8hu v_byte_sums_a = (__v8hu)zeroes;
+	__v8hu v_byte_sums_b = (__v8hu)zeroes;
+	__v8hu v_byte_sums_c = (__v8hu)zeroes;
+	__v8hu v_byte_sums_d = (__v8hu)zeroes;
+
+	do {
+		/* Load the next 32 bytes */
+		const __m128i bytes1 = *p++;
+		const __m128i bytes2 = *p++;
+
+		/*
+		 * Accumulate the previous s1 counters into the s2 counters.
+		 * Logically, this really should be v_s2 += v_s1 * 32, but we
+		 * can do the multiplication (or left shift) later.
+		 */
+		v_s2 += v_s1;
+
+		/*
+		 * s1 update: use "Packed Sum of Absolute Differences" to add
+		 * the bytes horizontally with 8 bytes per sum.  Then add the
+		 * sums to the s1 counters.
+		 */
+		v_s1 += (__v4su)_mm_sad_epu8(bytes1, zeroes);
+		v_s1 += (__v4su)_mm_sad_epu8(bytes2, zeroes);
+
+		/*
+		 * Also accumulate the bytes into 32 separate counters that have
+		 * 16-bit precision.
+		 */
+		v_byte_sums_a += (__v8hu)_mm_unpacklo_epi8(bytes1, zeroes);
+		v_byte_sums_b += (__v8hu)_mm_unpackhi_epi8(bytes1, zeroes);
+		v_byte_sums_c += (__v8hu)_mm_unpacklo_epi8(bytes2, zeroes);
+		v_byte_sums_d += (__v8hu)_mm_unpackhi_epi8(bytes2, zeroes);
+
+	} while (p != end);
+
+	/* Finish calculating the s2 counters */
+	v_s2 = (__v4su)_mm_slli_epi32((__m128i)v_s2, 5);
+	v_s2 += (__v4su)_mm_madd_epi16((__m128i)v_byte_sums_a,
+				       (__m128i)(__v8hu){ 32, 31, 30, 29, 28, 27, 26, 25 });
+	v_s2 += (__v4su)_mm_madd_epi16((__m128i)v_byte_sums_b,
+				       (__m128i)(__v8hu){ 24, 23, 22, 21, 20, 19, 18, 17 });
+	v_s2 += (__v4su)_mm_madd_epi16((__m128i)v_byte_sums_c,
+				       (__m128i)(__v8hu){ 16, 15, 14, 13, 12, 11, 10, 9 });
+	v_s2 += (__v4su)_mm_madd_epi16((__m128i)v_byte_sums_d,
+				       (__m128i)(__v8hu){ 8,  7,  6,  5,  4,  3,  2,  1 });
+
+	/* Add the counters to the real s1 and s2 */
+	ADLER32_FINISH_VEC_CHUNK_128(s1, s2, v_s1, v_s2);
+}
+#  include "../adler32_vec_template.h"
+#endif /* SSE2 implementation */
+
+#ifdef DISPATCH
+static inline adler32_func_t
+arch_select_adler32_func(void)
+{
+	u32 features = get_cpu_features();
+
+#ifdef DISPATCH_AVX512BW
+	if (features & X86_CPU_FEATURE_AVX512BW)
+		return adler32_avx512bw;
+#endif
+#ifdef DISPATCH_AVX2
+	if (features & X86_CPU_FEATURE_AVX2)
+		return adler32_avx2;
+#endif
+#ifdef DISPATCH_SSE2
+	if (features & X86_CPU_FEATURE_SSE2)
+		return adler32_sse2;
+#endif
+	return NULL;
+}
+#endif /* DISPATCH */
+
+#endif /* LIB_X86_ADLER32_IMPL_H */

ADDED   3rd_party/libdeflate/lib/x86/cpu_features.c
Index: 3rd_party/libdeflate/lib/x86/cpu_features.c
==================================================================
--- 3rd_party/libdeflate/lib/x86/cpu_features.c
+++ 3rd_party/libdeflate/lib/x86/cpu_features.c
@@ -0,0 +1,152 @@
+/*
+ * x86/cpu_features.c - feature detection for x86 processors
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include "../cpu_features_common.h" /* must be included first */
+#include "cpu_features.h"
+
+#if X86_CPU_FEATURES_ENABLED
+
+volatile u32 _cpu_features = 0;
+
+/* With old GCC versions we have to manually save and restore the x86_32 PIC
+ * register (ebx).  See: https://gcc.gnu.org/bugzilla/show_bug.cgi?id=47602  */
+#if defined(__i386__) && defined(__PIC__)
+#  define EBX_CONSTRAINT "=&r"
+#else
+#  define EBX_CONSTRAINT "=b"
+#endif
+
+/* Execute the CPUID instruction.  */
+static inline void
+cpuid(u32 leaf, u32 subleaf, u32 *a, u32 *b, u32 *c, u32 *d)
+{
+	__asm__(".ifnc %%ebx, %1; mov  %%ebx, %1; .endif\n"
+		"cpuid                                  \n"
+		".ifnc %%ebx, %1; xchg %%ebx, %1; .endif\n"
+		: "=a" (*a), EBX_CONSTRAINT (*b), "=c" (*c), "=d" (*d)
+		: "a" (leaf), "c" (subleaf));
+}
+
+/* Read an extended control register.  */
+static inline u64
+read_xcr(u32 index)
+{
+	u32 edx, eax;
+
+	/* Execute the "xgetbv" instruction.  Old versions of binutils do not
+	 * recognize this instruction, so list the raw bytes instead.  */
+	__asm__ (".byte 0x0f, 0x01, 0xd0" : "=d" (edx), "=a" (eax) : "c" (index));
+
+	return ((u64)edx << 32) | eax;
+}
+
+#undef BIT
+#define BIT(nr)			(1UL << (nr))
+
+#define XCR0_BIT_SSE		BIT(1)
+#define XCR0_BIT_AVX		BIT(2)
+#define XCR0_BIT_OPMASK		BIT(5)
+#define XCR0_BIT_ZMM_HI256	BIT(6)
+#define XCR0_BIT_HI16_ZMM	BIT(7)
+
+#define IS_SET(reg, nr)		((reg) & BIT(nr))
+#define IS_ALL_SET(reg, mask)	(((reg) & (mask)) == (mask))
+
+static const struct cpu_feature x86_cpu_feature_table[] = {
+	{X86_CPU_FEATURE_SSE2,		"sse2"},
+	{X86_CPU_FEATURE_PCLMUL,	"pclmul"},
+	{X86_CPU_FEATURE_AVX,		"avx"},
+	{X86_CPU_FEATURE_AVX2,		"avx2"},
+	{X86_CPU_FEATURE_BMI2,		"bmi2"},
+	{X86_CPU_FEATURE_AVX512BW,	"avx512bw"},
+};
+
+/* Initialize _cpu_features with bits for interesting processor features. */
+void setup_cpu_features(void)
+{
+	u32 features = 0;
+	u32 dummy1, dummy2, dummy3, dummy4;
+	u32 max_function;
+	u32 features_1, features_2, features_3, features_4;
+	bool os_avx_support = false;
+	bool os_avx512_support = false;
+
+	/* Get maximum supported function  */
+	cpuid(0, 0, &max_function, &dummy2, &dummy3, &dummy4);
+	if (max_function < 1)
+		goto out;
+
+	/* Standard feature flags  */
+	cpuid(1, 0, &dummy1, &dummy2, &features_2, &features_1);
+
+	if (IS_SET(features_1, 26))
+		features |= X86_CPU_FEATURE_SSE2;
+
+	if (IS_SET(features_2, 1))
+		features |= X86_CPU_FEATURE_PCLMUL;
+
+	if (IS_SET(features_2, 27)) { /* OSXSAVE set? */
+		u64 xcr0 = read_xcr(0);
+
+		os_avx_support = IS_ALL_SET(xcr0,
+					    XCR0_BIT_SSE |
+					    XCR0_BIT_AVX);
+
+		os_avx512_support = IS_ALL_SET(xcr0,
+					       XCR0_BIT_SSE |
+					       XCR0_BIT_AVX |
+					       XCR0_BIT_OPMASK |
+					       XCR0_BIT_ZMM_HI256 |
+					       XCR0_BIT_HI16_ZMM);
+	}
+
+	if (os_avx_support && IS_SET(features_2, 28))
+		features |= X86_CPU_FEATURE_AVX;
+
+	if (max_function < 7)
+		goto out;
+
+	/* Extended feature flags  */
+	cpuid(7, 0, &dummy1, &features_3, &features_4, &dummy4);
+
+	if (os_avx_support && IS_SET(features_3, 5))
+		features |= X86_CPU_FEATURE_AVX2;
+
+	if (IS_SET(features_3, 8))
+		features |= X86_CPU_FEATURE_BMI2;
+
+	if (os_avx512_support && IS_SET(features_3, 30))
+		features |= X86_CPU_FEATURE_AVX512BW;
+
+out:
+	disable_cpu_features_for_testing(&features, x86_cpu_feature_table,
+					 ARRAY_LEN(x86_cpu_feature_table));
+
+	_cpu_features = features | X86_CPU_FEATURES_KNOWN;
+}
+
+#endif /* X86_CPU_FEATURES_ENABLED */

ADDED   3rd_party/libdeflate/lib/x86/cpu_features.h
Index: 3rd_party/libdeflate/lib/x86/cpu_features.h
==================================================================
--- 3rd_party/libdeflate/lib/x86/cpu_features.h
+++ 3rd_party/libdeflate/lib/x86/cpu_features.h
@@ -0,0 +1,41 @@
+/*
+ * x86/cpu_features.h - feature detection for x86 processors
+ */
+
+#ifndef LIB_X86_CPU_FEATURES_H
+#define LIB_X86_CPU_FEATURES_H
+
+#include "../lib_common.h"
+
+#if (defined(__i386__) || defined(__x86_64__)) && \
+	COMPILER_SUPPORTS_TARGET_FUNCTION_ATTRIBUTE
+#  define X86_CPU_FEATURES_ENABLED 1
+#else
+#  define X86_CPU_FEATURES_ENABLED 0
+#endif
+
+#if X86_CPU_FEATURES_ENABLED
+
+#define X86_CPU_FEATURE_SSE2		0x00000001
+#define X86_CPU_FEATURE_PCLMUL		0x00000002
+#define X86_CPU_FEATURE_AVX		0x00000004
+#define X86_CPU_FEATURE_AVX2		0x00000008
+#define X86_CPU_FEATURE_BMI2		0x00000010
+#define X86_CPU_FEATURE_AVX512BW	0x00000020
+
+#define X86_CPU_FEATURES_KNOWN		0x80000000
+
+extern volatile u32 _cpu_features;
+
+void setup_cpu_features(void);
+
+static inline u32 get_cpu_features(void)
+{
+	if (_cpu_features == 0)
+		setup_cpu_features();
+	return _cpu_features;
+}
+
+#endif /* X86_CPU_FEATURES_ENABLED */
+
+#endif /* LIB_X86_CPU_FEATURES_H */

ADDED   3rd_party/libdeflate/lib/x86/crc32_impl.h
Index: 3rd_party/libdeflate/lib/x86/crc32_impl.h
==================================================================
--- 3rd_party/libdeflate/lib/x86/crc32_impl.h
+++ 3rd_party/libdeflate/lib/x86/crc32_impl.h
@@ -0,0 +1,92 @@
+/*
+ * x86/crc32_impl.h - x86 implementations of CRC-32 checksum algorithm
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#ifndef LIB_X86_CRC32_IMPL_H
+#define LIB_X86_CRC32_IMPL_H
+
+#include "cpu_features.h"
+
+/*
+ * Include the PCLMUL/AVX implementation?  Although our PCLMUL-optimized CRC-32
+ * function doesn't use any AVX intrinsics specifically, it can benefit a lot
+ * from being compiled for an AVX target: on Skylake, ~16700 MB/s vs. ~10100
+ * MB/s.  I expect this is related to the PCLMULQDQ instructions being assembled
+ * in the newer three-operand form rather than the older two-operand form.
+ *
+ * Note: this is only needed if __AVX__ is *not* defined, since otherwise the
+ * "regular" PCLMUL implementation would already be AVX enabled.
+ */
+#undef DISPATCH_PCLMUL_AVX
+#if !defined(DEFAULT_IMPL) && !defined(__AVX__) &&	\
+	X86_CPU_FEATURES_ENABLED && COMPILER_SUPPORTS_AVX_TARGET &&	\
+	(defined(__PCLMUL__) || COMPILER_SUPPORTS_PCLMUL_TARGET_INTRINSICS)
+#  define FUNCNAME		crc32_pclmul_avx
+#  define FUNCNAME_ALIGNED	crc32_pclmul_avx_aligned
+#  define ATTRIBUTES		__attribute__((target("pclmul,avx")))
+#  define DISPATCH		1
+#  define DISPATCH_PCLMUL_AVX	1
+#  include "crc32_pclmul_template.h"
+#endif
+
+/* PCLMUL implementation */
+#undef DISPATCH_PCLMUL
+#if !defined(DEFAULT_IMPL) &&	\
+	(defined(__PCLMUL__) || (X86_CPU_FEATURES_ENABLED &&	\
+				 COMPILER_SUPPORTS_PCLMUL_TARGET_INTRINSICS))
+#  define FUNCNAME		crc32_pclmul
+#  define FUNCNAME_ALIGNED	crc32_pclmul_aligned
+#  ifdef __PCLMUL__
+#    define ATTRIBUTES
+#    define DEFAULT_IMPL	crc32_pclmul
+#  else
+#    define ATTRIBUTES		__attribute__((target("pclmul")))
+#    define DISPATCH		1
+#    define DISPATCH_PCLMUL	1
+#  endif
+#  include "crc32_pclmul_template.h"
+#endif
+
+#ifdef DISPATCH
+static inline crc32_func_t
+arch_select_crc32_func(void)
+{
+	u32 features = get_cpu_features();
+
+#ifdef DISPATCH_PCLMUL_AVX
+	if ((features & X86_CPU_FEATURE_PCLMUL) &&
+	    (features & X86_CPU_FEATURE_AVX))
+		return crc32_pclmul_avx;
+#endif
+#ifdef DISPATCH_PCLMUL
+	if (features & X86_CPU_FEATURE_PCLMUL)
+		return crc32_pclmul;
+#endif
+	return NULL;
+}
+#endif /* DISPATCH */
+
+#endif /* LIB_X86_CRC32_IMPL_H */

ADDED   3rd_party/libdeflate/lib/x86/crc32_pclmul_template.h
Index: 3rd_party/libdeflate/lib/x86/crc32_pclmul_template.h
==================================================================
--- 3rd_party/libdeflate/lib/x86/crc32_pclmul_template.h
+++ 3rd_party/libdeflate/lib/x86/crc32_pclmul_template.h
@@ -0,0 +1,262 @@
+/*
+ * x86/crc32_pclmul_template.h
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include <immintrin.h>
+
+/*
+ * CRC-32 folding with PCLMULQDQ.
+ *
+ * The basic idea is to repeatedly "fold" each 512 bits into the next 512 bits,
+ * producing an abbreviated message which is congruent the original message
+ * modulo the generator polynomial G(x).
+ *
+ * Folding each 512 bits is implemented as eight 64-bit folds, each of which
+ * uses one carryless multiplication instruction.  It's expected that CPUs may
+ * be able to execute some of these multiplications in parallel.
+ *
+ * Explanation of "folding": let A(x) be 64 bits from the message, and let B(x)
+ * be 95 bits from a constant distance D later in the message.  The relevant
+ * portion of the message can be written as:
+ *
+ *	M(x) = A(x)*x^D + B(x)
+ *
+ * ... where + and * represent addition and multiplication, respectively, of
+ * polynomials over GF(2).  Note that when implemented on a computer, these
+ * operations are equivalent to XOR and carryless multiplication, respectively.
+ *
+ * For the purpose of CRC calculation, only the remainder modulo the generator
+ * polynomial G(x) matters:
+ *
+ *	M(x) mod G(x) = (A(x)*x^D + B(x)) mod G(x)
+ *
+ * Since the modulo operation can be applied anywhere in a sequence of additions
+ * and multiplications without affecting the result, this is equivalent to:
+ *
+ *	M(x) mod G(x) = (A(x)*(x^D mod G(x)) + B(x)) mod G(x)
+ *
+ * For any D, 'x^D mod G(x)' will be a polynomial with maximum degree 31, i.e.
+ * a 32-bit quantity.  So 'A(x) * (x^D mod G(x))' is equivalent to a carryless
+ * multiplication of a 64-bit quantity by a 32-bit quantity, producing a 95-bit
+ * product.  Then, adding (XOR-ing) the product to B(x) produces a polynomial
+ * with the same length as B(x) but with the same remainder as 'A(x)*x^D +
+ * B(x)'.  This is the basic fold operation with 64 bits.
+ *
+ * Note that the carryless multiplication instruction PCLMULQDQ actually takes
+ * two 64-bit inputs and produces a 127-bit product in the low-order bits of a
+ * 128-bit XMM register.  This works fine, but care must be taken to account for
+ * "bit endianness".  With the CRC version implemented here, bits are always
+ * ordered such that the lowest-order bit represents the coefficient of highest
+ * power of x and the highest-order bit represents the coefficient of the lowest
+ * power of x.  This is backwards from the more intuitive order.  Still,
+ * carryless multiplication works essentially the same either way.  It just must
+ * be accounted for that when we XOR the 95-bit product in the low-order 95 bits
+ * of a 128-bit XMM register into 128-bits of later data held in another XMM
+ * register, we'll really be XOR-ing the product into the mathematically higher
+ * degree end of those later bits, not the lower degree end as may be expected.
+ *
+ * So given that caveat and the fact that we process 512 bits per iteration, the
+ * 'D' values we need for the two 64-bit halves of each 128 bits of data are:
+ *
+ *	D = (512 + 95) - 64	 for the higher-degree half of each 128 bits,
+ *				 i.e. the lower order bits in the XMM register
+ *
+ *	D = (512 + 95) - 128	 for the lower-degree half of each 128 bits,
+ *				 i.e. the higher order bits in the XMM register
+ *
+ * The required 'x^D mod G(x)' values were precomputed.
+ *
+ * When <= 512 bits remain in the message, we finish up by folding across
+ * smaller distances.  This works similarly; the distance D is just different,
+ * so different constant multipliers must be used.  Finally, once the remaining
+ * message is just 64 bits, it is reduced to the CRC-32 using Barrett reduction
+ * (explained later).
+ *
+ * For more information see the original paper from Intel:
+ *	"Fast CRC Computation for Generic Polynomials Using PCLMULQDQ Instruction"
+ *	December 2009
+ *	http://www.intel.com/content/dam/www/public/us/en/documents/white-papers/fast-crc-computation-generic-polynomials-pclmulqdq-paper.pdf
+ */
+static u32 ATTRIBUTES
+FUNCNAME_ALIGNED(u32 remainder, const __m128i *p, size_t nr_segs)
+{
+	/* Constants precomputed by gen_crc32_multipliers.c.  Do not edit! */
+	const __v2di multipliers_4 = (__v2di){ 0x8F352D95, 0x1D9513D7 };
+	const __v2di multipliers_2 = (__v2di){ 0xF1DA05AA, 0x81256527 };
+	const __v2di multipliers_1 = (__v2di){ 0xAE689191, 0xCCAA009E };
+	const __v2di final_multiplier = (__v2di){ 0xB8BC6765 };
+	const __m128i mask32 = (__m128i)(__v4si){ 0xFFFFFFFF };
+	const __v2di barrett_reduction_constants =
+			(__v2di){ 0x00000001F7011641, 0x00000001DB710641 };
+
+	const __m128i * const end = p + nr_segs;
+	const __m128i * const end512 = p + (nr_segs & ~3);
+	__m128i x0, x1, x2, x3;
+
+	/*
+	 * Account for the current 'remainder', i.e. the CRC of the part of the
+	 * message already processed.  Explanation: rewrite the message
+	 * polynomial M(x) in terms of the first part A(x), the second part
+	 * B(x), and the length of the second part in bits |B(x)| >= 32:
+	 *
+	 *	M(x) = A(x)*x^|B(x)| + B(x)
+	 *
+	 * Then the CRC of M(x) is:
+	 *
+	 *	CRC(M(x)) = CRC(A(x)*x^|B(x)| + B(x))
+	 *	          = CRC(A(x)*x^32*x^(|B(x)| - 32) + B(x))
+	 *	          = CRC(CRC(A(x))*x^(|B(x)| - 32) + B(x))
+	 *
+	 * Note: all arithmetic is modulo G(x), the generator polynomial; that's
+	 * why A(x)*x^32 can be replaced with CRC(A(x)) = A(x)*x^32 mod G(x).
+	 *
+	 * So the CRC of the full message is the CRC of the second part of the
+	 * message where the first 32 bits of the second part of the message
+	 * have been XOR'ed with the CRC of the first part of the message.
+	 */
+	x0 = *p++;
+	x0 ^= (__m128i)(__v4si){ remainder };
+
+	if (p > end512) /* only 128, 256, or 384 bits of input? */
+		goto _128_bits_at_a_time;
+	x1 = *p++;
+	x2 = *p++;
+	x3 = *p++;
+
+	/* Fold 512 bits at a time */
+	for (; p != end512; p += 4) {
+		__m128i y0, y1, y2, y3;
+
+		y0 = p[0];
+		y1 = p[1];
+		y2 = p[2];
+		y3 = p[3];
+
+		/*
+		 * Note: the immediate constant for PCLMULQDQ specifies which
+		 * 64-bit halves of the 128-bit vectors to multiply:
+		 *
+		 * 0x00 means low halves (higher degree polynomial terms for us)
+		 * 0x11 means high halves (lower degree polynomial terms for us)
+		 */
+		y0 ^= _mm_clmulepi64_si128(x0, multipliers_4, 0x00);
+		y1 ^= _mm_clmulepi64_si128(x1, multipliers_4, 0x00);
+		y2 ^= _mm_clmulepi64_si128(x2, multipliers_4, 0x00);
+		y3 ^= _mm_clmulepi64_si128(x3, multipliers_4, 0x00);
+		y0 ^= _mm_clmulepi64_si128(x0, multipliers_4, 0x11);
+		y1 ^= _mm_clmulepi64_si128(x1, multipliers_4, 0x11);
+		y2 ^= _mm_clmulepi64_si128(x2, multipliers_4, 0x11);
+		y3 ^= _mm_clmulepi64_si128(x3, multipliers_4, 0x11);
+
+		x0 = y0;
+		x1 = y1;
+		x2 = y2;
+		x3 = y3;
+	}
+
+	/* Fold 512 bits => 128 bits */
+	x2 ^= _mm_clmulepi64_si128(x0, multipliers_2, 0x00);
+	x3 ^= _mm_clmulepi64_si128(x1, multipliers_2, 0x00);
+	x2 ^= _mm_clmulepi64_si128(x0, multipliers_2, 0x11);
+	x3 ^= _mm_clmulepi64_si128(x1, multipliers_2, 0x11);
+	x3 ^= _mm_clmulepi64_si128(x2, multipliers_1, 0x00);
+	x3 ^= _mm_clmulepi64_si128(x2, multipliers_1, 0x11);
+	x0 = x3;
+
+_128_bits_at_a_time:
+	while (p != end) {
+		/* Fold 128 bits into next 128 bits */
+		x1 = *p++;
+		x1 ^= _mm_clmulepi64_si128(x0, multipliers_1, 0x00);
+		x1 ^= _mm_clmulepi64_si128(x0, multipliers_1, 0x11);
+		x0 = x1;
+	}
+
+	/* Now there are just 128 bits left, stored in 'x0'. */
+
+	/*
+	 * Fold 128 => 96 bits.  This also implicitly appends 32 zero bits,
+	 * which is equivalent to multiplying by x^32.  This is needed because
+	 * the CRC is defined as M(x)*x^32 mod G(x), not just M(x) mod G(x).
+	 */
+	x0 = _mm_srli_si128(x0, 8) ^
+	     _mm_clmulepi64_si128(x0, multipliers_1, 0x10);
+
+	/* Fold 96 => 64 bits */
+	x0 = _mm_srli_si128(x0, 4) ^
+	     _mm_clmulepi64_si128(x0 & mask32, final_multiplier, 0x00);
+
+        /*
+	 * Finally, reduce 64 => 32 bits using Barrett reduction.
+	 *
+	 * Let M(x) = A(x)*x^32 + B(x) be the remaining message.  The goal is to
+	 * compute R(x) = M(x) mod G(x).  Since degree(B(x)) < degree(G(x)):
+	 *
+	 *	R(x) = (A(x)*x^32 + B(x)) mod G(x)
+	 *	     = (A(x)*x^32) mod G(x) + B(x)
+	 *
+	 * Then, by the Division Algorithm there exists a unique q(x) such that:
+	 *
+	 *	A(x)*x^32 mod G(x) = A(x)*x^32 - q(x)*G(x)
+	 *
+	 * Since the left-hand side is of maximum degree 31, the right-hand side
+	 * must be too.  This implies that we can apply 'mod x^32' to the
+	 * right-hand side without changing its value:
+	 *
+	 *	(A(x)*x^32 - q(x)*G(x)) mod x^32 = q(x)*G(x) mod x^32
+	 *
+	 * Note that '+' is equivalent to '-' in polynomials over GF(2).
+	 *
+	 * We also know that:
+	 *
+	 *	              / A(x)*x^32 \
+	 *	q(x) = floor (  ---------  )
+	 *	              \    G(x)   /
+	 *
+	 * To compute this efficiently, we can multiply the top and bottom by
+	 * x^32 and move the division by G(x) to the top:
+	 *
+	 *	              / A(x) * floor(x^64 / G(x)) \
+	 *	q(x) = floor (  -------------------------  )
+	 *	              \           x^32            /
+	 *
+	 * Note that floor(x^64 / G(x)) is a constant.
+	 *
+	 * So finally we have:
+	 *
+	 *	                          / A(x) * floor(x^64 / G(x)) \
+	 *	R(x) = B(x) + G(x)*floor (  -------------------------  )
+	 *	                          \           x^32            /
+	 */
+	x1 = x0;
+	x0 = _mm_clmulepi64_si128(x0 & mask32, barrett_reduction_constants, 0x00);
+	x0 = _mm_clmulepi64_si128(x0 & mask32, barrett_reduction_constants, 0x10);
+	return _mm_cvtsi128_si32(_mm_srli_si128(x0 ^ x1, 4));
+}
+
+#define IMPL_ALIGNMENT		16
+#define IMPL_SEGMENT_SIZE	16
+#include "../crc32_vec_template.h"

ADDED   3rd_party/libdeflate/lib/x86/decompress_impl.h
Index: 3rd_party/libdeflate/lib/x86/decompress_impl.h
==================================================================
--- 3rd_party/libdeflate/lib/x86/decompress_impl.h
+++ 3rd_party/libdeflate/lib/x86/decompress_impl.h
@@ -0,0 +1,31 @@
+#ifndef LIB_X86_DECOMPRESS_IMPL_H
+#define LIB_X86_DECOMPRESS_IMPL_H
+
+#include "cpu_features.h"
+
+/* Include the BMI2-optimized version? */
+#undef DISPATCH_BMI2
+#if !defined(__BMI2__) && X86_CPU_FEATURES_ENABLED && \
+	COMPILER_SUPPORTS_BMI2_TARGET
+#  define FUNCNAME	deflate_decompress_bmi2
+#  define ATTRIBUTES	__attribute__((target("bmi2")))
+#  define DISPATCH	1
+#  define DISPATCH_BMI2	1
+#  include "../decompress_template.h"
+#endif
+
+#ifdef DISPATCH
+static inline decompress_func_t
+arch_select_decompress_func(void)
+{
+	u32 features = get_cpu_features();
+
+#ifdef DISPATCH_BMI2
+	if (features & X86_CPU_FEATURE_BMI2)
+		return deflate_decompress_bmi2;
+#endif
+	return NULL;
+}
+#endif /* DISPATCH */
+
+#endif /* LIB_X86_DECOMPRESS_IMPL_H */

ADDED   3rd_party/libdeflate/lib/x86/matchfinder_impl.h
Index: 3rd_party/libdeflate/lib/x86/matchfinder_impl.h
==================================================================
--- 3rd_party/libdeflate/lib/x86/matchfinder_impl.h
+++ 3rd_party/libdeflate/lib/x86/matchfinder_impl.h
@@ -0,0 +1,122 @@
+/*
+ * x86/matchfinder_impl.h - x86 implementations of matchfinder functions
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#ifndef LIB_X86_MATCHFINDER_IMPL_H
+#define LIB_X86_MATCHFINDER_IMPL_H
+
+#ifdef __AVX2__
+#  include <immintrin.h>
+static forceinline void
+matchfinder_init_avx2(mf_pos_t *data, size_t size)
+{
+	__m256i *p = (__m256i *)data;
+	__m256i v = _mm256_set1_epi16(MATCHFINDER_INITVAL);
+
+	STATIC_ASSERT(MATCHFINDER_MEM_ALIGNMENT % sizeof(*p) == 0);
+	STATIC_ASSERT(MATCHFINDER_SIZE_ALIGNMENT % (4 * sizeof(*p)) == 0);
+	STATIC_ASSERT(sizeof(mf_pos_t) == 2);
+
+	do {
+		p[0] = v;
+		p[1] = v;
+		p[2] = v;
+		p[3] = v;
+		p += 4;
+		size -= 4 * sizeof(*p);
+	} while (size != 0);
+}
+#define matchfinder_init matchfinder_init_avx2
+
+static forceinline void
+matchfinder_rebase_avx2(mf_pos_t *data, size_t size)
+{
+	__m256i *p = (__m256i *)data;
+	__m256i v = _mm256_set1_epi16((u16)-MATCHFINDER_WINDOW_SIZE);
+
+	STATIC_ASSERT(MATCHFINDER_MEM_ALIGNMENT % sizeof(*p) == 0);
+	STATIC_ASSERT(MATCHFINDER_SIZE_ALIGNMENT % (4 * sizeof(*p)) == 0);
+	STATIC_ASSERT(sizeof(mf_pos_t) == 2);
+
+	do {
+		/* PADDSW: Add Packed Signed Integers With Signed Saturation  */
+		p[0] = _mm256_adds_epi16(p[0], v);
+		p[1] = _mm256_adds_epi16(p[1], v);
+		p[2] = _mm256_adds_epi16(p[2], v);
+		p[3] = _mm256_adds_epi16(p[3], v);
+		p += 4;
+		size -= 4 * sizeof(*p);
+	} while (size != 0);
+}
+#define matchfinder_rebase matchfinder_rebase_avx2
+
+#elif defined(__SSE2__)
+#  include <emmintrin.h>
+static forceinline void
+matchfinder_init_sse2(mf_pos_t *data, size_t size)
+{
+	__m128i *p = (__m128i *)data;
+	__m128i v = _mm_set1_epi16(MATCHFINDER_INITVAL);
+
+	STATIC_ASSERT(MATCHFINDER_MEM_ALIGNMENT % sizeof(*p) == 0);
+	STATIC_ASSERT(MATCHFINDER_SIZE_ALIGNMENT % (4 * sizeof(*p)) == 0);
+	STATIC_ASSERT(sizeof(mf_pos_t) == 2);
+
+	do {
+		p[0] = v;
+		p[1] = v;
+		p[2] = v;
+		p[3] = v;
+		p += 4;
+		size -= 4 * sizeof(*p);
+	} while (size != 0);
+}
+#define matchfinder_init matchfinder_init_sse2
+
+static forceinline void
+matchfinder_rebase_sse2(mf_pos_t *data, size_t size)
+{
+	__m128i *p = (__m128i *)data;
+	__m128i v = _mm_set1_epi16((u16)-MATCHFINDER_WINDOW_SIZE);
+
+	STATIC_ASSERT(MATCHFINDER_MEM_ALIGNMENT % sizeof(*p) == 0);
+	STATIC_ASSERT(MATCHFINDER_SIZE_ALIGNMENT % (4 * sizeof(*p)) == 0);
+	STATIC_ASSERT(sizeof(mf_pos_t) == 2);
+
+	do {
+		/* PADDSW: Add Packed Signed Integers With Signed Saturation  */
+		p[0] = _mm_adds_epi16(p[0], v);
+		p[1] = _mm_adds_epi16(p[1], v);
+		p[2] = _mm_adds_epi16(p[2], v);
+		p[3] = _mm_adds_epi16(p[3], v);
+		p += 4;
+		size -= 4 * sizeof(*p);
+	} while (size != 0);
+}
+#define matchfinder_rebase matchfinder_rebase_sse2
+#endif /* __SSE2__ */
+
+#endif /* LIB_X86_MATCHFINDER_IMPL_H */

ADDED   3rd_party/libdeflate/lib/zlib_compress.c
Index: 3rd_party/libdeflate/lib/zlib_compress.c
==================================================================
--- 3rd_party/libdeflate/lib/zlib_compress.c
+++ 3rd_party/libdeflate/lib/zlib_compress.c
@@ -0,0 +1,87 @@
+/*
+ * zlib_compress.c - compress with a zlib wrapper
+ *
+ * Originally public domain; changes after 2016-09-07 are copyrighted.
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include "deflate_compress.h"
+#include "unaligned.h"
+#include "zlib_constants.h"
+
+#include "libdeflate.h"
+
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_zlib_compress(struct libdeflate_compressor *c,
+			 const void *in, size_t in_nbytes,
+			 void *out, size_t out_nbytes_avail)
+{
+	u8 *out_next = out;
+	u16 hdr;
+	unsigned compression_level;
+	unsigned level_hint;
+	size_t deflate_size;
+
+	if (out_nbytes_avail <= ZLIB_MIN_OVERHEAD)
+		return 0;
+
+	/* 2 byte header: CMF and FLG  */
+	hdr = (ZLIB_CM_DEFLATE << 8) | (ZLIB_CINFO_32K_WINDOW << 12);
+	compression_level = deflate_get_compression_level(c);
+	if (compression_level < 2)
+		level_hint = ZLIB_FASTEST_COMPRESSION;
+	else if (compression_level < 6)
+		level_hint = ZLIB_FAST_COMPRESSION;
+	else if (compression_level < 8)
+		level_hint = ZLIB_DEFAULT_COMPRESSION;
+	else
+		level_hint = ZLIB_SLOWEST_COMPRESSION;
+	hdr |= level_hint << 6;
+	hdr |= 31 - (hdr % 31);
+
+	put_unaligned_be16(hdr, out_next);
+	out_next += 2;
+
+	/* Compressed data  */
+	deflate_size = libdeflate_deflate_compress(c, in, in_nbytes, out_next,
+					out_nbytes_avail - ZLIB_MIN_OVERHEAD);
+	if (deflate_size == 0)
+		return 0;
+	out_next += deflate_size;
+
+	/* ADLER32  */
+	put_unaligned_be32(libdeflate_adler32(1, in, in_nbytes), out_next);
+	out_next += 4;
+
+	return out_next - (u8 *)out;
+}
+
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_zlib_compress_bound(struct libdeflate_compressor *c,
+			       size_t in_nbytes)
+{
+	return ZLIB_MIN_OVERHEAD +
+	       libdeflate_deflate_compress_bound(c, in_nbytes);
+}

ADDED   3rd_party/libdeflate/lib/zlib_constants.h
Index: 3rd_party/libdeflate/lib/zlib_constants.h
==================================================================
--- 3rd_party/libdeflate/lib/zlib_constants.h
+++ 3rd_party/libdeflate/lib/zlib_constants.h
@@ -0,0 +1,21 @@
+/*
+ * zlib_constants.h - constants for the zlib wrapper format
+ */
+
+#ifndef LIB_ZLIB_CONSTANTS_H
+#define LIB_ZLIB_CONSTANTS_H
+
+#define ZLIB_MIN_HEADER_SIZE	2
+#define ZLIB_FOOTER_SIZE	4
+#define ZLIB_MIN_OVERHEAD	(ZLIB_MIN_HEADER_SIZE + ZLIB_FOOTER_SIZE)
+
+#define ZLIB_CM_DEFLATE		8
+
+#define ZLIB_CINFO_32K_WINDOW	7
+
+#define ZLIB_FASTEST_COMPRESSION	0
+#define ZLIB_FAST_COMPRESSION		1
+#define ZLIB_DEFAULT_COMPRESSION	2
+#define ZLIB_SLOWEST_COMPRESSION	3
+
+#endif /* LIB_ZLIB_CONSTANTS_H */

ADDED   3rd_party/libdeflate/lib/zlib_decompress.c
Index: 3rd_party/libdeflate/lib/zlib_decompress.c
==================================================================
--- 3rd_party/libdeflate/lib/zlib_decompress.c
+++ 3rd_party/libdeflate/lib/zlib_decompress.c
@@ -0,0 +1,108 @@
+/*
+ * zlib_decompress.c - decompress with a zlib wrapper
+ *
+ * Originally public domain; changes after 2016-09-07 are copyrighted.
+ *
+ * Copyright 2016 Eric Biggers
+ *
+ * Permission is hereby granted, free of charge, to any person
+ * obtaining a copy of this software and associated documentation
+ * files (the "Software"), to deal in the Software without
+ * restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the
+ * Software is furnished to do so, subject to the following
+ * conditions:
+ *
+ * The above copyright notice and this permission notice shall be
+ * included in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+ * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+ * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+ * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+ * OTHER DEALINGS IN THE SOFTWARE.
+ */
+
+#include "unaligned.h"
+#include "zlib_constants.h"
+
+#include "libdeflate.h"
+
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_zlib_decompress_ex(struct libdeflate_decompressor *d,
+			      const void *in, size_t in_nbytes,
+			      void *out, size_t out_nbytes_avail,
+			      size_t *actual_in_nbytes_ret,
+			      size_t *actual_out_nbytes_ret)
+{
+	const u8 *in_next = in;
+	const u8 * const in_end = in_next + in_nbytes;
+	u16 hdr;
+	size_t actual_in_nbytes;
+	size_t actual_out_nbytes;
+	enum libdeflate_result result;
+
+	if (in_nbytes < ZLIB_MIN_OVERHEAD)
+		return LIBDEFLATE_BAD_DATA;
+
+	/* 2 byte header: CMF and FLG  */
+	hdr = get_unaligned_be16(in_next);
+	in_next += 2;
+
+	/* FCHECK */
+	if ((hdr % 31) != 0)
+		return LIBDEFLATE_BAD_DATA;
+
+	/* CM */
+	if (((hdr >> 8) & 0xF) != ZLIB_CM_DEFLATE)
+		return LIBDEFLATE_BAD_DATA;
+
+	/* CINFO */
+	if ((hdr >> 12) > ZLIB_CINFO_32K_WINDOW)
+		return LIBDEFLATE_BAD_DATA;
+
+	/* FDICT */
+	if ((hdr >> 5) & 1)
+		return LIBDEFLATE_BAD_DATA;
+
+	/* Compressed data  */
+	result = libdeflate_deflate_decompress_ex(d, in_next,
+					in_end - ZLIB_FOOTER_SIZE - in_next,
+					out, out_nbytes_avail,
+					&actual_in_nbytes, actual_out_nbytes_ret);
+	if (result != LIBDEFLATE_SUCCESS)
+		return result;
+
+	if (actual_out_nbytes_ret)
+		actual_out_nbytes = *actual_out_nbytes_ret;
+	else
+		actual_out_nbytes = out_nbytes_avail;
+
+	in_next += actual_in_nbytes;
+
+	/* ADLER32  */
+	if (libdeflate_adler32(1, out, actual_out_nbytes) !=
+	    get_unaligned_be32(in_next))
+		return LIBDEFLATE_BAD_DATA;
+	in_next += 4;
+
+	if (actual_in_nbytes_ret)
+		*actual_in_nbytes_ret = in_next - (u8 *)in;
+
+	return LIBDEFLATE_SUCCESS;
+}
+
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_zlib_decompress(struct libdeflate_decompressor *d,
+			   const void *in, size_t in_nbytes,
+			   void *out, size_t out_nbytes_avail,
+			   size_t *actual_out_nbytes_ret)
+{
+	return libdeflate_zlib_decompress_ex(d, in, in_nbytes,
+					     out, out_nbytes_avail,
+					     NULL, actual_out_nbytes_ret);
+}

ADDED   3rd_party/libdeflate/libdeflate.h
Index: 3rd_party/libdeflate/libdeflate.h
==================================================================
--- 3rd_party/libdeflate/libdeflate.h
+++ 3rd_party/libdeflate/libdeflate.h
@@ -0,0 +1,366 @@
+/*
+ * libdeflate.h - public header for libdeflate
+ */
+
+#ifndef LIBDEFLATE_H
+#define LIBDEFLATE_H
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+#define LIBDEFLATE_VERSION_MAJOR	1
+#define LIBDEFLATE_VERSION_MINOR	7
+#define LIBDEFLATE_VERSION_STRING	"1.7"
+
+#include <stddef.h>
+#include <stdint.h>
+
+/*
+ * On Windows, if you want to link to the DLL version of libdeflate, then
+ * #define LIBDEFLATE_DLL.  Note that the calling convention is "stdcall".
+ */
+#ifdef LIBDEFLATE_DLL
+#  ifdef BUILDING_LIBDEFLATE
+#    define LIBDEFLATEEXPORT	LIBEXPORT
+#  elif defined(_WIN32) || defined(__CYGWIN__)
+#    define LIBDEFLATEEXPORT	__declspec(dllimport)
+#  endif
+#endif
+#ifndef LIBDEFLATEEXPORT
+#  define LIBDEFLATEEXPORT
+#endif
+
+#if defined(_WIN32) && !defined(_WIN64)
+#  define LIBDEFLATEAPI_ABI	__stdcall
+#else
+#  define LIBDEFLATEAPI_ABI
+#endif
+
+#if defined(BUILDING_LIBDEFLATE) && defined(__GNUC__) && \
+	defined(_WIN32) && !defined(_WIN64)
+    /*
+     * On 32-bit Windows, gcc assumes 16-byte stack alignment but MSVC only 4.
+     * Realign the stack when entering libdeflate to avoid crashing in SSE/AVX
+     * code when called from an MSVC-compiled application.
+     */
+#  define LIBDEFLATEAPI_STACKALIGN	__attribute__((force_align_arg_pointer))
+#else
+#  define LIBDEFLATEAPI_STACKALIGN
+#endif
+
+#define LIBDEFLATEAPI	LIBDEFLATEAPI_ABI LIBDEFLATEAPI_STACKALIGN
+
+/* ========================================================================== */
+/*                             Compression                                    */
+/* ========================================================================== */
+
+struct libdeflate_compressor;
+
+/*
+ * libdeflate_alloc_compressor() allocates a new compressor that supports
+ * DEFLATE, zlib, and gzip compression.  'compression_level' is the compression
+ * level on a zlib-like scale but with a higher maximum value (1 = fastest, 6 =
+ * medium/default, 9 = slow, 12 = slowest).  Level 0 is also supported and means
+ * "no compression", specifically "create a valid stream, but only emit
+ * uncompressed blocks" (this will expand the data slightly).
+ *
+ * The return value is a pointer to the new compressor, or NULL if out of memory
+ * or if the compression level is invalid (i.e. outside the range [0, 12]).
+ *
+ * Note: for compression, the sliding window size is defined at compilation time
+ * to 32768, the largest size permissible in the DEFLATE format.  It cannot be
+ * changed at runtime.
+ *
+ * A single compressor is not safe to use by multiple threads concurrently.
+ * However, different threads may use different compressors concurrently.
+ */
+LIBDEFLATEEXPORT struct libdeflate_compressor * LIBDEFLATEAPI
+libdeflate_alloc_compressor(int compression_level);
+
+/*
+ * libdeflate_deflate_compress() performs raw DEFLATE compression on a buffer of
+ * data.  The function attempts to compress 'in_nbytes' bytes of data located at
+ * 'in' and write the results to 'out', which has space for 'out_nbytes_avail'
+ * bytes.  The return value is the compressed size in bytes, or 0 if the data
+ * could not be compressed to 'out_nbytes_avail' bytes or fewer.
+ */
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_deflate_compress(struct libdeflate_compressor *compressor,
+			    const void *in, size_t in_nbytes,
+			    void *out, size_t out_nbytes_avail);
+
+/*
+ * libdeflate_deflate_compress_bound() returns a worst-case upper bound on the
+ * number of bytes of compressed data that may be produced by compressing any
+ * buffer of length less than or equal to 'in_nbytes' using
+ * libdeflate_deflate_compress() with the specified compressor.  Mathematically,
+ * this bound will necessarily be a number greater than or equal to 'in_nbytes'.
+ * It may be an overestimate of the true upper bound.  The return value is
+ * guaranteed to be the same for all invocations with the same compressor and
+ * same 'in_nbytes'.
+ *
+ * As a special case, 'compressor' may be NULL.  This causes the bound to be
+ * taken across *any* libdeflate_compressor that could ever be allocated with
+ * this build of the library, with any options.
+ *
+ * Note that this function is not necessary in many applications.  With
+ * block-based compression, it is usually preferable to separately store the
+ * uncompressed size of each block and to store any blocks that did not compress
+ * to less than their original size uncompressed.  In that scenario, there is no
+ * need to know the worst-case compressed size, since the maximum number of
+ * bytes of compressed data that may be used would always be one less than the
+ * input length.  You can just pass a buffer of that size to
+ * libdeflate_deflate_compress() and store the data uncompressed if
+ * libdeflate_deflate_compress() returns 0, indicating that the compressed data
+ * did not fit into the provided output buffer.
+ */
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_deflate_compress_bound(struct libdeflate_compressor *compressor,
+				  size_t in_nbytes);
+
+/*
+ * Like libdeflate_deflate_compress(), but stores the data in the zlib wrapper
+ * format.
+ */
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_zlib_compress(struct libdeflate_compressor *compressor,
+			 const void *in, size_t in_nbytes,
+			 void *out, size_t out_nbytes_avail);
+
+/*
+ * Like libdeflate_deflate_compress_bound(), but assumes the data will be
+ * compressed with libdeflate_zlib_compress() rather than with
+ * libdeflate_deflate_compress().
+ */
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_zlib_compress_bound(struct libdeflate_compressor *compressor,
+			       size_t in_nbytes);
+
+/*
+ * Like libdeflate_deflate_compress(), but stores the data in the gzip wrapper
+ * format.
+ */
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_gzip_compress(struct libdeflate_compressor *compressor,
+			 const void *in, size_t in_nbytes,
+			 void *out, size_t out_nbytes_avail);
+
+/*
+ * Like libdeflate_deflate_compress_bound(), but assumes the data will be
+ * compressed with libdeflate_gzip_compress() rather than with
+ * libdeflate_deflate_compress().
+ */
+LIBDEFLATEEXPORT size_t LIBDEFLATEAPI
+libdeflate_gzip_compress_bound(struct libdeflate_compressor *compressor,
+			       size_t in_nbytes);
+
+/*
+ * libdeflate_free_compressor() frees a compressor that was allocated with
+ * libdeflate_alloc_compressor().  If a NULL pointer is passed in, no action is
+ * taken.
+ */
+LIBDEFLATEEXPORT void LIBDEFLATEAPI
+libdeflate_free_compressor(struct libdeflate_compressor *compressor);
+
+/* ========================================================================== */
+/*                             Decompression                                  */
+/* ========================================================================== */
+
+struct libdeflate_decompressor;
+
+/*
+ * libdeflate_alloc_decompressor() allocates a new decompressor that can be used
+ * for DEFLATE, zlib, and gzip decompression.  The return value is a pointer to
+ * the new decompressor, or NULL if out of memory.
+ *
+ * This function takes no parameters, and the returned decompressor is valid for
+ * decompressing data that was compressed at any compression level and with any
+ * sliding window size.
+ *
+ * A single decompressor is not safe to use by multiple threads concurrently.
+ * However, different threads may use different decompressors concurrently.
+ */
+LIBDEFLATEEXPORT struct libdeflate_decompressor * LIBDEFLATEAPI
+libdeflate_alloc_decompressor(void);
+
+/*
+ * Result of a call to libdeflate_deflate_decompress(),
+ * libdeflate_zlib_decompress(), or libdeflate_gzip_decompress().
+ */
+enum libdeflate_result {
+	/* Decompression was successful.  */
+	LIBDEFLATE_SUCCESS = 0,
+
+	/* Decompressed failed because the compressed data was invalid, corrupt,
+	 * or otherwise unsupported.  */
+	LIBDEFLATE_BAD_DATA = 1,
+
+	/* A NULL 'actual_out_nbytes_ret' was provided, but the data would have
+	 * decompressed to fewer than 'out_nbytes_avail' bytes.  */
+	LIBDEFLATE_SHORT_OUTPUT = 2,
+
+	/* The data would have decompressed to more than 'out_nbytes_avail'
+	 * bytes.  */
+	LIBDEFLATE_INSUFFICIENT_SPACE = 3,
+};
+
+/*
+ * libdeflate_deflate_decompress() decompresses the DEFLATE-compressed stream
+ * from the buffer 'in' with compressed size up to 'in_nbytes' bytes.  The
+ * uncompressed data is written to 'out', a buffer with size 'out_nbytes_avail'
+ * bytes.  If decompression succeeds, then 0 (LIBDEFLATE_SUCCESS) is returned.
+ * Otherwise, a nonzero result code such as LIBDEFLATE_BAD_DATA is returned.  If
+ * a nonzero result code is returned, then the contents of the output buffer are
+ * undefined.
+ *
+ * Decompression stops at the end of the DEFLATE stream (as indicated by the
+ * BFINAL flag), even if it is actually shorter than 'in_nbytes' bytes.
+ *
+ * libdeflate_deflate_decompress() can be used in cases where the actual
+ * uncompressed size is known (recommended) or unknown (not recommended):
+ *
+ *   - If the actual uncompressed size is known, then pass the actual
+ *     uncompressed size as 'out_nbytes_avail' and pass NULL for
+ *     'actual_out_nbytes_ret'.  This makes libdeflate_deflate_decompress() fail
+ *     with LIBDEFLATE_SHORT_OUTPUT if the data decompressed to fewer than the
+ *     specified number of bytes.
+ *
+ *   - If the actual uncompressed size is unknown, then provide a non-NULL
+ *     'actual_out_nbytes_ret' and provide a buffer with some size
+ *     'out_nbytes_avail' that you think is large enough to hold all the
+ *     uncompressed data.  In this case, if the data decompresses to less than
+ *     or equal to 'out_nbytes_avail' bytes, then
+ *     libdeflate_deflate_decompress() will write the actual uncompressed size
+ *     to *actual_out_nbytes_ret and return 0 (LIBDEFLATE_SUCCESS).  Otherwise,
+ *     it will return LIBDEFLATE_INSUFFICIENT_SPACE if the provided buffer was
+ *     not large enough but no other problems were encountered, or another
+ *     nonzero result code if decompression failed for another reason.
+ */
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_deflate_decompress(struct libdeflate_decompressor *decompressor,
+			      const void *in, size_t in_nbytes,
+			      void *out, size_t out_nbytes_avail,
+			      size_t *actual_out_nbytes_ret);
+
+/*
+ * Like libdeflate_deflate_decompress(), but adds the 'actual_in_nbytes_ret'
+ * argument.  If decompression succeeds and 'actual_in_nbytes_ret' is not NULL,
+ * then the actual compressed size of the DEFLATE stream (aligned to the next
+ * byte boundary) is written to *actual_in_nbytes_ret.
+ */
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_deflate_decompress_ex(struct libdeflate_decompressor *decompressor,
+				 const void *in, size_t in_nbytes,
+				 void *out, size_t out_nbytes_avail,
+				 size_t *actual_in_nbytes_ret,
+				 size_t *actual_out_nbytes_ret);
+
+/*
+ * Like libdeflate_deflate_decompress(), but assumes the zlib wrapper format
+ * instead of raw DEFLATE.
+ *
+ * Decompression will stop at the end of the zlib stream, even if it is shorter
+ * than 'in_nbytes'.  If you need to know exactly where the zlib stream ended,
+ * use libdeflate_zlib_decompress_ex().
+ */
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_zlib_decompress(struct libdeflate_decompressor *decompressor,
+			   const void *in, size_t in_nbytes,
+			   void *out, size_t out_nbytes_avail,
+			   size_t *actual_out_nbytes_ret);
+
+/*
+ * Like libdeflate_zlib_decompress(), but adds the 'actual_in_nbytes_ret'
+ * argument.  If 'actual_in_nbytes_ret' is not NULL and the decompression
+ * succeeds (indicating that the first zlib-compressed stream in the input
+ * buffer was decompressed), then the actual number of input bytes consumed is
+ * written to *actual_in_nbytes_ret.
+ */
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_zlib_decompress_ex(struct libdeflate_decompressor *decompressor,
+			      const void *in, size_t in_nbytes,
+			      void *out, size_t out_nbytes_avail,
+			      size_t *actual_in_nbytes_ret,
+			      size_t *actual_out_nbytes_ret);
+
+/*
+ * Like libdeflate_deflate_decompress(), but assumes the gzip wrapper format
+ * instead of raw DEFLATE.
+ *
+ * If multiple gzip-compressed members are concatenated, then only the first
+ * will be decompressed.  Use libdeflate_gzip_decompress_ex() if you need
+ * multi-member support.
+ */
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_gzip_decompress(struct libdeflate_decompressor *decompressor,
+			   const void *in, size_t in_nbytes,
+			   void *out, size_t out_nbytes_avail,
+			   size_t *actual_out_nbytes_ret);
+
+/*
+ * Like libdeflate_gzip_decompress(), but adds the 'actual_in_nbytes_ret'
+ * argument.  If 'actual_in_nbytes_ret' is not NULL and the decompression
+ * succeeds (indicating that the first gzip-compressed member in the input
+ * buffer was decompressed), then the actual number of input bytes consumed is
+ * written to *actual_in_nbytes_ret.
+ */
+LIBDEFLATEEXPORT enum libdeflate_result LIBDEFLATEAPI
+libdeflate_gzip_decompress_ex(struct libdeflate_decompressor *decompressor,
+			      const void *in, size_t in_nbytes,
+			      void *out, size_t out_nbytes_avail,
+			      size_t *actual_in_nbytes_ret,
+			      size_t *actual_out_nbytes_ret);
+
+/*
+ * libdeflate_free_decompressor() frees a decompressor that was allocated with
+ * libdeflate_alloc_decompressor().  If a NULL pointer is passed in, no action
+ * is taken.
+ */
+LIBDEFLATEEXPORT void LIBDEFLATEAPI
+libdeflate_free_decompressor(struct libdeflate_decompressor *decompressor);
+
+/* ========================================================================== */
+/*                                Checksums                                   */
+/* ========================================================================== */
+
+/*
+ * libdeflate_adler32() updates a running Adler-32 checksum with 'len' bytes of
+ * data and returns the updated checksum.  When starting a new checksum, the
+ * required initial value for 'adler' is 1.  This value is also returned when
+ * 'buffer' is specified as NULL.
+ */
+LIBDEFLATEEXPORT uint32_t LIBDEFLATEAPI
+libdeflate_adler32(uint32_t adler, const void *buffer, size_t len);
+
+
+/*
+ * libdeflate_crc32() updates a running CRC-32 checksum with 'len' bytes of data
+ * and returns the updated checksum.  When starting a new checksum, the required
+ * initial value for 'crc' is 0.  This value is also returned when 'buffer' is
+ * specified as NULL.
+ */
+LIBDEFLATEEXPORT uint32_t LIBDEFLATEAPI
+libdeflate_crc32(uint32_t crc, const void *buffer, size_t len);
+
+/* ========================================================================== */
+/*                           Custom memory allocator                          */
+/* ========================================================================== */
+
+/*
+ * Install a custom memory allocator which libdeflate will use for all memory
+ * allocations.  'malloc_func' is a function that must behave like malloc(), and
+ * 'free_func' is a function that must behave like free().
+ *
+ * There must not be any libdeflate_compressor or libdeflate_decompressor
+ * structures in existence when calling this function.
+ */
+LIBDEFLATEEXPORT void LIBDEFLATEAPI
+libdeflate_set_memory_allocator(void *(*malloc_func)(size_t),
+				void (*free_func)(void *));
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif /* LIBDEFLATE_H */

ADDED   3rd_party/libdeflate/wscript
Index: 3rd_party/libdeflate/wscript
==================================================================
--- 3rd_party/libdeflate/wscript
+++ 3rd_party/libdeflate/wscript
@@ -0,0 +1,14 @@
+import os.path
+
+def build( bld ):
+	commonHeaders = bld.path.ant_glob( 'common/*.h' ) + [ 'libdeflate.h' ]
+	libHeaders = bld.path.ant_glob( 'lib/*.h' ) + bld.path.ant_glob( 'lib/*/*.h' )
+	sources = [ 'lib/deflate_decompress.c', 'lib/utils.c' ] + bld.path.ant_glob( 'lib/*/cpu_features.c' )
+	bld.stlib(
+		target = 'deflate',
+		source = sources,
+		features = [ 'c' ],
+		includes = [ './' ],
+		cflags = '-O2 -fomit-frame-pointer -std=c99 -I. -Wall -Wundef',
+		export_includes = '../'
+	)

ADDED   3rd_party/sqlite3/wscript
Index: 3rd_party/sqlite3/wscript
==================================================================
--- 3rd_party/sqlite3/wscript
+++ 3rd_party/sqlite3/wscript
@@ -0,0 +1,15 @@
+import os.path
+
+def build( bld ):
+	sources = [ 'sqlite3/sqlite3.c' ]
+	headers = bld.path.ant_glob( 'sqlite3/*.h' )
+	bld.stlib(
+		target = 'sqlite3',
+		source = sources,
+		features = [ 'c' ],
+		includes = './',
+		cflags = '-fPIC',
+		defines = 'SQLITE_ENABLE_COLUMN_METADATA SQLITE_ENABLE_STAT4 SQLITE_MAX_EXPR_DEPTH=10000 SQLITE_USE_URI=1',
+		use = 'dl',
+		export_includes = './'
+	)

DELETED 3rd_party/threadpool/CHANGE_LOG
Index: 3rd_party/threadpool/CHANGE_LOG
==================================================================
--- 3rd_party/threadpool/CHANGE_LOG
+++ 3rd_party/threadpool/CHANGE_LOG
@@ -1,88 +0,0 @@
-Change Log
-
-0.2.5
-  - Made threadpool compatible to boost::thread 1.37
-  - Fixed hang problem in shutdown method (Thanks to Sohail Somani)
-  - Adapted repository layout to boost (Thanks to Alex Ott)
-    
-0.2.4 (Stable)
-  - Made threadpool compatible to boost::thread 1.35.x code base
-  - Fixed compiler warning in scope_guard.hpp
-
-0.2.3 (Development)
-  - Implemented workaround for Sun C++ Pro compiler bug in pool_core
-  - Removed subtask implementation (there was no demand for this feature)
-  - Improved shutdown policies
-
-0.2.2 (Development)
-  - Refactored SizePolicy and added SizePolicyController
-  - Moved policies into separate files
-  - Fixed some compiler problems (GCC)
-  - Implemented size_controller handling
-  - Implemented two size policies: static_size and fixed_size
-  - Refactored worker_thread handling, moved policies from pool_core to pool
-  - Specialized schedule function for usage with futures
-  - Added compile test project
-  - Improved constness in pool core class
-  - Fixed timed wait
-  - Implemented futures (in progress)
-  - Added result_type to all functors
-
-0.2.1 (Development)
-  - Pool base class (thread_pool) has now reference semantics
-  - Large refactorings: Removed scoped_pool, reimplemented worker (now worker_thread)
-  - Fixed odd resize behaviour. Now resize changes the number of threads immediately
-  - Apply pimpl idiom on pool core class (to make the ugly scoped_pool class needless)
-  - Introduced scheduling policies
-  - Switched to policy-based design (PBD), inspired by Scott Meyers C++ workshop
-  - Cosmetic code change: Replaced keyword 'class' with 'typename' in template definitions
-  - Revised tutorials
-  - New requirements: tasks functions should not and schedulers shall not throw exceptions
-  
-
-0.2.0 (Development)
-  - Moved threadpool into the boost namespace: boost::threadpool
-  - Used keyword volatile to indicate thread-safe member functions
-  - Used volatile on primitve types were appropriate
-  - Moved worker to detail directory
-  - Fixed thread deletion
-  - Extended wait functionality (waiting for idle threads was implemented)
-  - Renamed 'join()' to 'wait()' as 'join' indicates the termination of thread. That was not the case in pool::join.
-  - Changed internal container of lifo and fifo schedulers to improve efficiency.
-  - Improved code reference documentation (source code browser)
-  - Renamed thread_func into task_func
-  - Added += operator to scoped_pool to ease scheduling of tasks
-  - Refactored file structures and class names
-  - Added a new task concept (named subtask) which allows the combination of sequential and parallel execution
-  - Added new task adaptor for looped or timed tasks: looped_task_func
-  - Introduced function clear() which can be used to remove all tasks from the pool and schedulers
-  - New function pool::active() which returns the number of active tasks
-
-0.1.8 (Development)
-  - Fixed some compile errors which were reported by gcc
-  - Wrote tutorial "Prioritized Tasks"
-
-0.1.7 (Development)
-  - Added Visual Studio 2005 project files for tutorial and examples
-
-0.1.6 (Development)
-  - Replaced task adaptor 'task' with boost::bind
-  - Workers are unregistered from thread_group when they are terminated
-  - Working on example boost::iostreams packet_filter
-
-0.1.5 (Development)
-  - Finished threadpool reference
-  - Class pool_adaptor was replaced by smart_pool
-  - Minor pool improvements
-  - First tutorial page online 
-
-0.1.4 (Development)
-  - Created the pool's homepage: http://threadpool.sourceforge.net
-  - Improved documentation
-  - Added build scripts
-
-0.1.3 (Development)
-  - First public release
-  - Added mergesort example
-  - Added tutorial 
-  - Implementation of threadpool core and related classes

DELETED 3rd_party/threadpool/COPYING
Index: 3rd_party/threadpool/COPYING
==================================================================
--- 3rd_party/threadpool/COPYING
+++ 3rd_party/threadpool/COPYING
@@ -1,5 +0,0 @@
-Copyright (c) 2005-2007 Philipp Henkel
-
-Use, modification, and distribution are  subject to the
-Boost Software License, Version 1.0. (See accompanying  file
-LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)

DELETED 3rd_party/threadpool/Jamfile.v2
Index: 3rd_party/threadpool/Jamfile.v2
==================================================================
--- 3rd_party/threadpool/Jamfile.v2
+++ 3rd_party/threadpool/Jamfile.v2
@@ -1,13 +0,0 @@
-use-project /boost
-   : $(BOOST_ROOT)
-   ;
-
-project threadpool
-   : requirements <include>.&&$(BOOST_ROOT)
-     # disable auto-linking for all targets here,
-     # primarily because it caused troubles with V2
-     <define>BOOST_ALL_NO_LIB=1
-   : usage-requirements <include>.&&$(BOOST_ROOT)
-   : build-dir bin.v2
-   ;
-

DELETED 3rd_party/threadpool/Jamrules
Index: 3rd_party/threadpool/Jamrules
==================================================================
--- 3rd_party/threadpool/Jamrules
+++ 3rd_party/threadpool/Jamrules
@@ -1,1 +0,0 @@
-project boost : $(BOOST_ROOT) ;

DELETED 3rd_party/threadpool/LICENSE_1_0.txt
Index: 3rd_party/threadpool/LICENSE_1_0.txt
==================================================================
--- 3rd_party/threadpool/LICENSE_1_0.txt
+++ 3rd_party/threadpool/LICENSE_1_0.txt
@@ -1,23 +0,0 @@
-Boost Software License - Version 1.0 - August 17th, 2003
-
-Permission is hereby granted, free of charge, to any person or organization
-obtaining a copy of the software and accompanying documentation covered by
-this license (the "Software") to use, reproduce, display, distribute,
-execute, and transmit the Software, and to prepare derivative works of the
-Software, and to permit third-parties to whom the Software is furnished to
-do so, all subject to the following:
-
-The copyright notices in the Software and this entire statement, including
-the above license grant, this restriction and the following disclaimer,
-must be included in all copies of the Software, in whole or in part, and
-all derivative works of the Software, unless such copies or derivative
-works are solely in the form of machine-executable object code generated by
-a source language processor.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT
-SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE
-FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
-ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-DEALINGS IN THE SOFTWARE.

DELETED 3rd_party/threadpool/Makefile
Index: 3rd_party/threadpool/Makefile
==================================================================
--- 3rd_party/threadpool/Makefile
+++ 3rd_party/threadpool/Makefile
@@ -1,32 +0,0 @@
-export RELEASE_MANAGER=philipphenkel
-export RELEASE_VERSION=0_2_5
-
-doc: clean
-	make --directory=./libs/threadpool/doc --print-directory doc
-	
-release_doc:
-	make --directory=./libs/threadpool/doc --print-directory release_doc
-
-release_src: clean fetch_clean_src
-	mv clean_src threadpool-$(RELEASE_VERSION)-src
-	zip -r9 threadpool-$(RELEASE_VERSION)-src.zip threadpool-$(RELEASE_VERSION)-src
-	rm -rf threadpool-$(RELEASE_VERSION)-src
-
-deploy_website:
-	make --directory=./libs/threadpool/doc --print-directory deploy_sf 
-	
-clean:
-	rm -rf clean_src
-	rm -rf threadpool-$(RELEASE_VERSION)-src.zip
-	rm -rf threadpool-$(RELEASE_VERSION)-doc.zip
-	make --directory=./libs/threadpool/doc --print-directory clean
-	
-fetch_clean_src:
-	rm -rf clean_src
-	mkdir clean_src	
-#	cvs -d:pserver:anonymous@threadpool.cvs.sourceforge.net:/cvsroot/threadpool login
-	cd clean_src; cvs -z3 -d:pserver:anonymous@threadpool.cvs.sourceforge.net:/cvsroot/threadpool export -r RELEASE_$(RELEASE_VERSION) threadpool
-#	cd clean_src; cvs -z3 -d:ext:$(RELEASE_MANAGER)@cvs.sourceforge.net:/cvsroot/threadpool export -r RELEASE_$(RELEASE_VERSION) threadpool 
-
-
-

DELETED 3rd_party/threadpool/README
Index: 3rd_party/threadpool/README
==================================================================
--- 3rd_party/threadpool/README
+++ 3rd_party/threadpool/README
@@ -1,10 +0,0 @@
-threadpool
-
-Copyright (c) 2005-2007 Philipp Henkel
-
-threadpool is a cross-platform C++ thread pool library and released under the Boost Software License. 
-
-See doc/index.html for information on:
-  - API documentation and a tutorial
-  - External dependencies
-  - Using threadpool

DELETED 3rd_party/threadpool/TODO
Index: 3rd_party/threadpool/TODO
==================================================================
--- 3rd_party/threadpool/TODO
+++ 3rd_party/threadpool/TODO
@@ -1,36 +0,0 @@
-threadpool to-do items
-======================
-
-Documentation
---------------------------------------------
-- Source code documentation
-- Design rationale
-- Tutorial
-- Finish Quickstart Tutorial/Example
-
-Functionality
---------------------------------------------
-- Implement a size policy which dynamically 
-  increase/decrease the pool's size:
-  - init with min/max threads
-  - auto increase
-  - auto decrease (using timed cleanup tasks)
-- Add some kind of deadline scheduler
-- Add futures to pool
-
-
-Examples
---------------------------------------------
-- Buffering Client Requests: Handle 'bursty' client traffic
-  Some applications need more buffering than is provided by OS I/O subsystem
-  
-  Working on 'active' buffer for boost::iostreams
-  buffer_filter which provides a dynamic amount of buffer objects. 
-  buffer_filter uses a threadpool with one thread which provides the buffers to 
-  consumer. (TODO Philipp)
-  
-  2nd implemention step:
-  Flexbile configuration: Buffer capacities can be configured according to
-    - maximum number of requests
-    - maximum number of bytes
-  

DELETED 3rd_party/threadpool/boost/threadpool.hpp
Index: 3rd_party/threadpool/boost/threadpool.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool.hpp
+++ 3rd_party/threadpool/boost/threadpool.hpp
@@ -1,28 +0,0 @@
-/*! \file
-* \brief Main include.
-*
-* This is the only file you have to include in order to use the 
-* complete threadpool library.
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-#ifndef THREADPOOL_HPP_INCLUDED
-#define THREADPOOL_HPP_INCLUDED
-
-#include "./threadpool/future.hpp"
-#include "./threadpool/pool.hpp"
-
-#include "./threadpool/pool_adaptors.hpp"
-#include "./threadpool/task_adaptors.hpp"
-
-
-#endif // THREADPOOL_HPP_INCLUDED
-

DELETED 3rd_party/threadpool/boost/threadpool/detail/future.hpp
Index: 3rd_party/threadpool/boost/threadpool/detail/future.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/detail/future.hpp
+++ 3rd_party/threadpool/boost/threadpool/detail/future.hpp
@@ -1,215 +0,0 @@
-/*! \file
-* \brief TODO.
-*
-* TODO. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_DETAIL_FUTURE_IMPL_HPP_INCLUDED
-#define THREADPOOL_DETAIL_FUTURE_IMPL_HPP_INCLUDED
-
-
-#include "locking_ptr.hpp"
-
-#include <boost/smart_ptr.hpp>
-#include <boost/optional.hpp>
-#include <boost/thread/mutex.hpp>
-#include <boost/thread/condition.hpp>
-#include <boost/thread/xtime.hpp>
-#include <boost/utility/result_of.hpp>
-#include <boost/static_assert.hpp>
-#include <boost/type_traits.hpp>
-
-namespace boost { namespace threadpool { namespace detail 
-{
-
-template<class Result> 
-class future_impl
-{
-public:
-  typedef Result const & result_type; //!< Indicates the functor's result type.
-
-  typedef Result future_result_type; //!< Indicates the future's result type.
-  typedef future_impl<future_result_type> future_type;
-
-private:
-    volatile bool m_ready;
-    volatile future_result_type m_result;
-
-    mutable mutex m_monitor;
-    mutable condition m_condition_ready;	
-
-    volatile bool m_is_cancelled;
-    volatile bool m_executing;
-
-public:
-
-
-public:
-
-  future_impl()
-  : m_ready(false)
-  , m_is_cancelled(false)
-  {
-  }
-
-  bool ready() const volatile
-  {
-    return m_ready; 
-  }
-
-  void wait() const volatile
-  {
-    const future_type* self = const_cast<const future_type*>(this);
-    mutex::scoped_lock lock(self->m_monitor);
-
-    while(!m_ready)
-    {
-      self->m_condition_ready.wait(lock);
-    }
-  }
-
-
-  bool timed_wait(boost::xtime const & timestamp) const
-  {
-    const future_type* self = const_cast<const future_type*>(this);
-    mutex::scoped_lock lock(self->m_monitor);
-
-    while(!m_ready)
-    {
-      if(!self->m_condition_ready.timed_wait(lock, timestamp)) return false;
-    }
-
-    return true;
-  }
-
-
-  result_type operator()() const volatile
-  {
-    wait();
-/*
-    if( throw_exception_ != 0 )
-    {
-      throw_exception_( this );
-    }
-*/
- 
-    return *(const_cast<const future_result_type*>(&m_result));
-  }
-
-
-  void set_value(future_result_type const & r) volatile
-  {
-    locking_ptr<future_type, mutex> lockedThis(*this, m_monitor);
-    if(!m_ready && !m_is_cancelled)
-    {
-      lockedThis->m_result = r;
-      lockedThis->m_ready = true;
-      lockedThis->m_condition_ready.notify_all();
-    }
-  }
-/*
-  template<class E> void set_exception() // throw()
-  {
-    m_impl->template set_exception<E>();
-  }
-
-  template<class E> void set_exception( char const * what ) // throw()
-  {
-    m_impl->template set_exception<E>( what );
-  }
-  */
-
-
-   bool cancel() volatile
-   {
-     if(!m_ready || m_executing)
-     {
-        m_is_cancelled = true;
-        return true;
-     }
-     else
-     {
-       return false;
-     }
-   }
-
-
-   bool is_cancelled() const volatile
-   {
-     return m_is_cancelled;
-   }
-
-
-   void set_execution_status(bool executing) volatile
-   {
-     m_executing = executing;
-   }
-};
-
-
-template<
-  template <typename> class Future,
-  typename Function
->
-class future_impl_task_func
-{
-
-public:
-  typedef void result_type;                         //!< Indicates the functor's result type.
-
-  typedef Function function_type;                   //!< Indicates the function's type.
-  typedef typename result_of<function_type()>::type future_result_type; //!< Indicates the future's result type.
-  typedef Future<future_result_type> future_type;   //!< Indicates the future's type.
-
-  // The task is required to be a nullary function.
-  BOOST_STATIC_ASSERT(function_traits<function_type()>::arity == 0);
-
-  // The task function's result type is required not to be void.
-  BOOST_STATIC_ASSERT(!is_void<future_result_type>::value);
-
-private:
-  function_type             m_function;
-  shared_ptr<future_type>   m_future;
-
-public:
-  future_impl_task_func(function_type const & function, shared_ptr<future_type> const & future)
-  : m_function(function)
-  , m_future(future)
-  {
-  }
-
-  void operator()()
-  {
-    if(m_function)
-    {
-      m_future->set_execution_status(true);
-      if(!m_future->is_cancelled())
-      {
-        // TODO future exeception handling 
-        m_future->set_value(m_function());
-      }
-      m_future->set_execution_status(false); // TODO consider exceptions
-    }
-  }
-
-};
-
-
-
-
-
-} } } // namespace boost::threadpool::detail
-
-#endif // THREADPOOL_DETAIL_FUTURE_IMPL_HPP_INCLUDED
-
-

DELETED 3rd_party/threadpool/boost/threadpool/detail/locking_ptr.hpp
Index: 3rd_party/threadpool/boost/threadpool/detail/locking_ptr.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/detail/locking_ptr.hpp
+++ 3rd_party/threadpool/boost/threadpool/detail/locking_ptr.hpp
@@ -1,85 +0,0 @@
-/*! \file
-* \brief The locking_ptr is smart pointer with a scoped locking mechanism.
-*
-* The class is a wrapper for a volatile pointer. It enables synchronized access to the
-* internal pointer by locking the passed mutex.
-* locking_ptr is based on Andrei Alexandrescu's LockingPtr. For more information
-* see article "volatile - Multithreaded Programmer's Best Friend" by A. Alexandrescu.
-*
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_DETAIL_LOCKING_PTR_HPP_INCLUDED
-#define THREADPOOL_DETAIL_LOCKING_PTR_HPP_INCLUDED
-
-#include <boost/utility.hpp>
-#include <boost/thread/mutex.hpp>
-
-
-namespace boost { namespace threadpool { namespace detail 
-{
-
-/*! \brief  Smart pointer with a scoped locking mechanism.
- *
- * This class is a wrapper for a volatile pointer. It enables synchronized access to the
- * internal pointer by locking the passed mutex.
- */
-  template <typename T, typename Mutex>
-  class locking_ptr 
-  : private noncopyable
-  {
-    T* m_obj;                     //!< The instance pointer. 
-    Mutex & m_mutex;              //!< Mutex is used for scoped locking.
-
-  public:
-    /// Constructor.
-    locking_ptr(volatile T& obj, const volatile Mutex& mtx)
-      : m_obj(const_cast<T*>(&obj))
-      , m_mutex(*const_cast<Mutex*>(&mtx))
-    {   
-      // Lock mutex
-	  m_mutex.lock();
-    }
-
-
-    /// Destructor.
-    ~locking_ptr()
-    { 
-      // Unlock mutex
-      m_mutex.unlock();
-    }
-
-
-    /*! Returns a reference to the stored instance.
-    * \return The instance's reference.
-    */
-    T& operator*() const
-    {    
-      return *m_obj;    
-    }
-
-
-    /*! Returns a pointer to the stored instance.
-    * \return The instance's pointer.
-    */
-    T* operator->() const
-    {   
-      return m_obj;   
-    }
-  };
-
-
-} } } // namespace boost::threadpool::detail
-
-
-#endif // THREADPOOL_DETAIL_LOCKING_PTR_HPP_INCLUDED
-

DELETED 3rd_party/threadpool/boost/threadpool/detail/pool_core.hpp
Index: 3rd_party/threadpool/boost/threadpool/detail/pool_core.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/detail/pool_core.hpp
+++ 3rd_party/threadpool/boost/threadpool/detail/pool_core.hpp
@@ -1,453 +0,0 @@
-/*! \file
-* \brief Thread pool core.
-*
-* This file contains the threadpool's core class: pool<Task, SchedulingPolicy>.
-*
-* Thread pools are a mechanism for asynchronous and parallel processing 
-* within the same process. The pool class provides a convenient way 
-* for dispatching asynchronous tasks as functions objects. The scheduling
-* of these tasks can be easily controlled by using customized schedulers. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_POOL_CORE_HPP_INCLUDED
-#define THREADPOOL_POOL_CORE_HPP_INCLUDED
-
-
-
-
-#include "locking_ptr.hpp"
-#include "worker_thread.hpp"
-
-#include "../task_adaptors.hpp"
-
-#include <boost/thread.hpp>
-#include <boost/thread/exceptions.hpp>
-#include <boost/thread/mutex.hpp>
-#include <boost/thread/condition.hpp>
-#include <boost/smart_ptr.hpp>
-#include <boost/bind.hpp>
-#include <boost/static_assert.hpp>
-#include <boost/type_traits.hpp>
-
-#include <vector>
-
-
-/// The namespace threadpool contains a thread pool and related utility classes.
-namespace boost { namespace threadpool { namespace detail 
-{
-
-  /*! \brief Thread pool. 
-  *
-  * Thread pools are a mechanism for asynchronous and parallel processing 
-  * within the same process. The pool class provides a convenient way 
-  * for dispatching asynchronous tasks as functions objects. The scheduling
-  * of these tasks can be easily controlled by using customized schedulers. 
-  * A task must not throw an exception.
-  *
-  * A pool_impl is DefaultConstructible and NonCopyable.
-  *
-  * \param Task A function object which implements the operator 'void operator() (void) const'. The operator () is called by the pool to execute the task. Exceptions are ignored.
-  * \param Scheduler A task container which determines how tasks are scheduled. It is guaranteed that this container is accessed only by one thread at a time. The scheduler shall not throw exceptions.
-  *
-  * \remarks The pool class is thread-safe.
-  * 
-  * \see Tasks: task_func, prio_task_func
-  * \see Scheduling policies: fifo_scheduler, lifo_scheduler, prio_scheduler
-  */ 
-  template <
-    typename Task, 
-
-    template <typename> class SchedulingPolicy,
-    template <typename> class SizePolicy,
-    template <typename> class SizePolicyController,
-    template <typename> class ShutdownPolicy
-  > 
-  class pool_core
-  : public enable_shared_from_this< pool_core<Task, SchedulingPolicy, SizePolicy, SizePolicyController, ShutdownPolicy > > 
-  , private noncopyable
-  {
-
-  public: // Type definitions
-    typedef Task task_type;                                 //!< Indicates the task's type.
-    typedef SchedulingPolicy<task_type> scheduler_type;     //!< Indicates the scheduler's type.
-    typedef pool_core<Task, 
-                      SchedulingPolicy, 
-                      SizePolicy,
-                      SizePolicyController,
-                      ShutdownPolicy > pool_type;           //!< Indicates the thread pool's type.
-    typedef SizePolicy<pool_type> size_policy_type;         //!< Indicates the sizer's type.
-    //typedef typename size_policy_type::size_controller size_controller_type;
-
-    typedef SizePolicyController<pool_type> size_controller_type;
-
-//    typedef SizePolicy<pool_type>::size_controller size_controller_type;
-    typedef ShutdownPolicy<pool_type> shutdown_policy_type;//!< Indicates the shutdown policy's type.  
-
-    typedef worker_thread<pool_type> worker_type;
-
-    // The task is required to be a nullary function.
-    BOOST_STATIC_ASSERT(function_traits<task_type()>::arity == 0);
-
-    // The task function's result type is required to be void.
-    BOOST_STATIC_ASSERT(is_void<typename result_of<task_type()>::type >::value);
-
-
-  private:  // Friends 
-    friend class worker_thread<pool_type>;
-
-#if defined(__SUNPRO_CC) && (__SUNPRO_CC <= 0x580)  // Tested with CC: Sun C++ 5.8 Patch 121018-08 2006/12/06
-   friend class SizePolicy;
-   friend class ShutdownPolicy;
-#else
-   friend class SizePolicy<pool_type>;
-   friend class ShutdownPolicy<pool_type>;
-#endif
-
-  private: // The following members may be accessed by _multiple_ threads at the same time:
-    volatile size_t m_worker_count;	
-    volatile size_t m_target_worker_count;	
-    volatile size_t m_active_worker_count;
-      
-
-
-  private: // The following members are accessed only by _one_ thread at the same time:
-    scheduler_type  m_scheduler;
-    scoped_ptr<size_policy_type> m_size_policy; // is never null
-    
-    bool  m_terminate_all_workers;								// Indicates if termination of all workers was triggered.
-    std::vector<shared_ptr<worker_type> > m_terminated_workers; // List of workers which are terminated but not fully destructed.
-    
-  private: // The following members are implemented thread-safe:
-    mutable recursive_mutex  m_monitor;
-    mutable condition m_worker_idle_or_terminated_event;	// A worker is idle or was terminated.
-    mutable condition m_task_or_terminate_workers_event;  // Task is available OR total worker count should be reduced.
-
-  public:
-    /// Constructor.
-    pool_core()
-      : m_worker_count(0) 
-      , m_target_worker_count(0)
-      , m_active_worker_count(0)
-      , m_terminate_all_workers(false)
-    {
-      pool_type volatile & self_ref = *this;
-      m_size_policy.reset(new size_policy_type(self_ref));
-
-      m_scheduler.clear();
-    }
-
-
-    /// Destructor.
-    ~pool_core()
-    {
-    }
-
-    /*! Gets the size controller which manages the number of threads in the pool. 
-    * \return The size controller.
-    * \see SizePolicy
-    */
-    size_controller_type size_controller()
-    {
-      return size_controller_type(*m_size_policy, this->shared_from_this());
-    }
-
-    /*! Gets the number of threads in the pool.
-    * \return The number of threads.
-    */
-    size_t size()	const volatile
-    {
-      return m_worker_count;
-    }
-
-// TODO is only called once
-    void shutdown()
-    {
-      ShutdownPolicy<pool_type>::shutdown(*this);
-    }
-
-    /*! Schedules a task for asynchronous execution. The task will be executed once only.
-    * \param task The task function object. It should not throw execeptions.
-    * \return true, if the task could be scheduled and false otherwise. 
-    */  
-    bool schedule(task_type const & task) volatile
-    {	
-      locking_ptr<pool_type, recursive_mutex> lockedThis(*this, m_monitor); 
-      
-      if(lockedThis->m_scheduler.push(task))
-      {
-        lockedThis->m_task_or_terminate_workers_event.notify_one();
-        return true;
-      }
-      else
-      {
-        return false;
-      }
-    }	
-
-
-    /*! Returns the number of tasks which are currently executed.
-    * \return The number of active tasks. 
-    */  
-    size_t active() const volatile
-    {
-      return m_active_worker_count;
-    }
-
-
-    /*! Returns the number of tasks which are ready for execution.    
-    * \return The number of pending tasks. 
-    */  
-    size_t pending() const volatile
-    {
-      locking_ptr<const pool_type, recursive_mutex> lockedThis(*this, m_monitor);
-      return lockedThis->m_scheduler.size();
-    }
-
-
-    /*! Removes all pending tasks from the pool's scheduler.
-    */  
-    void clear() volatile
-    { 
-      locking_ptr<pool_type, recursive_mutex> lockedThis(*this, m_monitor);
-      lockedThis->m_scheduler.clear();
-    }    
-
-
-    /*! Indicates that there are no tasks pending. 
-    * \return true if there are no tasks ready for execution.	
-    * \remarks This function is more efficient that the check 'pending() == 0'.
-    */   
-    bool empty() const volatile
-    {
-      locking_ptr<const pool_type, recursive_mutex> lockedThis(*this, m_monitor);
-      return lockedThis->m_scheduler.empty();
-    }	
-
-
-    /*! The current thread of execution is blocked until the sum of all active
-    *  and pending tasks is equal or less than a given threshold. 
-    * \param task_threshold The maximum number of tasks in pool and scheduler.
-    */     
-    void wait(size_t const task_threshold = 0) const volatile
-    {
-      const pool_type* self = const_cast<const pool_type*>(this);
-      recursive_mutex::scoped_lock lock(self->m_monitor);
-
-      if(0 == task_threshold)
-      {
-        while(0 != self->m_active_worker_count || !self->m_scheduler.empty())
-        { 
-          self->m_worker_idle_or_terminated_event.wait(lock);
-        }
-      }
-      else
-      {
-        while(task_threshold < self->m_active_worker_count + self->m_scheduler.size())
-        { 
-          self->m_worker_idle_or_terminated_event.wait(lock);
-        }
-      }
-    }	
-
-    /*! The current thread of execution is blocked until the timestamp is met
-    * or the sum of all active and pending tasks is equal or less 
-    * than a given threshold.  
-    * \param timestamp The time when function returns at the latest.
-    * \param task_threshold The maximum number of tasks in pool and scheduler.
-    * \return true if the task sum is equal or less than the threshold, false otherwise.
-    */       
-    bool wait(xtime const & timestamp, size_t const task_threshold = 0) const volatile
-    {
-      const pool_type* self = const_cast<const pool_type*>(this);
-      recursive_mutex::scoped_lock lock(self->m_monitor);
-
-      if(0 == task_threshold)
-      {
-        while(0 != self->m_active_worker_count || !self->m_scheduler.empty())
-        { 
-          if(!self->m_worker_idle_or_terminated_event.timed_wait(lock, timestamp)) return false;
-        }
-      }
-      else
-      {
-        while(task_threshold < self->m_active_worker_count + self->m_scheduler.size())
-        { 
-          if(!self->m_worker_idle_or_terminated_event.timed_wait(lock, timestamp)) return false;
-        }
-      }
-
-      return true;
-    }
-
-
-  private:	
-
-
-    void terminate_all_workers(bool const wait) volatile
-    {
-      pool_type* self = const_cast<pool_type*>(this);
-      recursive_mutex::scoped_lock lock(self->m_monitor);
-
-      self->m_terminate_all_workers = true;
-
-      m_target_worker_count = 0;
-      self->m_task_or_terminate_workers_event.notify_all();
-
-      if(wait)
-      {
-        while(m_active_worker_count > 0)
-        {
-          self->m_worker_idle_or_terminated_event.wait(lock);
-        }
-
-        for(typename std::vector<shared_ptr<worker_type> >::iterator it = self->m_terminated_workers.begin();
-          it != self->m_terminated_workers.end();
-          ++it)
-        {
-          (*it)->join();
-        }
-        self->m_terminated_workers.clear();
-      }
-    }
-
-
-    /*! Changes the number of worker threads in the pool. The resizing 
-    *  is handled by the SizePolicy.
-    * \param threads The new number of worker threads.
-    * \return true, if pool will be resized and false if not. 
-    */
-    bool resize(size_t const worker_count) volatile
-    {
-      locking_ptr<pool_type, recursive_mutex> lockedThis(*this, m_monitor); 
-
-      if(!m_terminate_all_workers)
-      {
-        m_target_worker_count = worker_count;
-      }
-      else
-      { 
-        return false;
-      }
-
-
-      if(m_worker_count <= m_target_worker_count)
-      { // increase worker count
-        while(m_worker_count < m_target_worker_count)
-        {
-          try
-          {
-            worker_thread<pool_type>::create_and_attach(lockedThis->shared_from_this());
-            m_worker_count++;
-            m_active_worker_count++;	
-          }
-          catch(thread_resource_error)
-          {
-            return false;
-          }
-        }
-      }
-      else
-      { // decrease worker count
-        lockedThis->m_task_or_terminate_workers_event.notify_all();   // TODO: Optimize number of notified workers
-      }
-
-      return true;
-    }
-
-
-    // worker died with unhandled exception
-    void worker_died_unexpectedly(shared_ptr<worker_type> worker) volatile
-    {
-      locking_ptr<pool_type, recursive_mutex> lockedThis(*this, m_monitor);
-
-      m_worker_count--;
-      m_active_worker_count--;
-      lockedThis->m_worker_idle_or_terminated_event.notify_all();	
-
-      if(m_terminate_all_workers)
-      {
-        lockedThis->m_terminated_workers.push_back(worker);
-      }
-      else
-      {
-        lockedThis->m_size_policy->worker_died_unexpectedly(m_worker_count);
-      }
-    }
-
-    void worker_destructed(shared_ptr<worker_type> worker) volatile
-    {
-      locking_ptr<pool_type, recursive_mutex> lockedThis(*this, m_monitor);
-      m_worker_count--;
-      m_active_worker_count--;
-      lockedThis->m_worker_idle_or_terminated_event.notify_all();	
-
-      if(m_terminate_all_workers)
-      {
-        lockedThis->m_terminated_workers.push_back(worker);
-      }
-    }
-
-
-    bool execute_task() volatile
-    {
-      function0<void> task;
-
-      { // fetch task
-        pool_type* lockedThis = const_cast<pool_type*>(this);
-        recursive_mutex::scoped_lock lock(lockedThis->m_monitor);
-
-        // decrease number of threads if necessary
-        if(m_worker_count > m_target_worker_count)
-        {	
-          return false;	// terminate worker
-        }
-
-
-        // wait for tasks
-        while(lockedThis->m_scheduler.empty())
-        {	
-          // decrease number of workers if necessary
-          if(m_worker_count > m_target_worker_count)
-          {	
-            return false;	// terminate worker
-          }
-          else
-          {
-            m_active_worker_count--;
-            lockedThis->m_worker_idle_or_terminated_event.notify_all();	
-            lockedThis->m_task_or_terminate_workers_event.wait(lock);
-            m_active_worker_count++;
-          }
-        }
-
-        task = lockedThis->m_scheduler.top();
-        lockedThis->m_scheduler.pop();
-      }
-
-      // call task function
-      if(task)
-      {
-        task();
-      }
- 
-      //guard->disable();
-      return true;
-    }
-  };
-
-
-
-
-} } } // namespace boost::threadpool::detail
-
-#endif // THREADPOOL_POOL_CORE_HPP_INCLUDED

DELETED 3rd_party/threadpool/boost/threadpool/detail/scope_guard.hpp
Index: 3rd_party/threadpool/boost/threadpool/detail/scope_guard.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/detail/scope_guard.hpp
+++ 3rd_party/threadpool/boost/threadpool/detail/scope_guard.hpp
@@ -1,65 +0,0 @@
-/*! \file
-* \brief TODO.
-*
-* TODO. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_DETAIL_SCOPE_GUARD_HPP_INCLUDED
-#define THREADPOOL_DETAIL_SCOPE_GUARD_HPP_INCLUDED
-
-
-
-#include <boost/function.hpp>
-
-
-namespace boost { namespace threadpool { namespace detail 
-{
-
-// TODO documentation
-class scope_guard
-: private boost::noncopyable
-{
-	function0<void> const m_function;
-	bool                  m_is_active;
-
-public:
-	scope_guard(function0<void> const & call_on_exit)
-	: m_function(call_on_exit)
-	, m_is_active(true)
-	{
-	}
-
-	~scope_guard()
-	{
-		if(m_is_active && m_function)
-		{
-			m_function();
-		}
-	}
-
-	void disable()
-	{
-		m_is_active = false;
-	}
-};
-
-
-
-
-
-
-} } } // namespace boost::threadpool::detail
-
-#endif // THREADPOOL_DETAIL_SCOPE_GUARD_HPP_INCLUDED
-
-

DELETED 3rd_party/threadpool/boost/threadpool/detail/worker_thread.hpp
Index: 3rd_party/threadpool/boost/threadpool/detail/worker_thread.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/detail/worker_thread.hpp
+++ 3rd_party/threadpool/boost/threadpool/detail/worker_thread.hpp
@@ -1,115 +0,0 @@
-/*! \file
-* \brief Thread pool worker.
-*
-* The worker thread instance is attached to a pool 
-* and executes tasks of this pool. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-#ifndef THREADPOOL_DETAIL_WORKER_THREAD_HPP_INCLUDED
-#define THREADPOOL_DETAIL_WORKER_THREAD_HPP_INCLUDED
-
-
-#include "scope_guard.hpp"
-
-#include <boost/smart_ptr.hpp>
-#include <boost/thread.hpp>
-#include <boost/thread/exceptions.hpp>
-#include <boost/thread/mutex.hpp>
-#include <boost/bind.hpp>
-
-
-namespace boost { namespace threadpool { namespace detail 
-{
-
-  /*! \brief Thread pool worker. 
-  *
-  * A worker_thread represents a thread of execution. The worker is attached to a 
-  * thread pool and processes tasks of that pool. The lifetime of the worker and its 
-  * internal boost::thread is managed automatically.
-  *
-  * This class is a helper class and cannot be constructed or accessed directly.
-  * 
-  * \see pool_core
-  */ 
-  template <typename Pool>
-  class worker_thread
-  : public enable_shared_from_this< worker_thread<Pool> > 
-  , private noncopyable
-  {
-  public:
-    typedef Pool pool_type;         	   //!< Indicates the pool's type.
-
-  private:
-    shared_ptr<pool_type>      m_pool;     //!< Pointer to the pool which created the worker.
-    shared_ptr<boost::thread>  m_thread;   //!< Pointer to the thread which executes the run loop.
-
-    
-    /*! Constructs a new worker. 
-    * \param pool Pointer to it's parent pool.
-    * \see function create_and_attach
-    */
-    worker_thread(shared_ptr<pool_type> const & pool)
-    : m_pool(pool)
-    {
-      assert(pool);
-    }
-
-	
-	/*! Notifies that an exception occurred in the run loop.
-	*/
-	void died_unexpectedly()
-	{
-		m_pool->worker_died_unexpectedly(this->shared_from_this());
-	}
-
-
-  public:
-	  /*! Executes pool's tasks sequentially.
-	  */
-	  void run()
-	  { 
-		  scope_guard notify_exception(bind(&worker_thread::died_unexpectedly, this));
-
-		  while(m_pool->execute_task()) {}
-
-		  notify_exception.disable();
-		  m_pool->worker_destructed(this->shared_from_this());
-	  }
-
-
-	  /*! Joins the worker's thread.
-	  */
-	  void join()
-	  {
-		  m_thread->join();
-	  }
-
-
-	  /*! Constructs a new worker thread and attaches it to the pool.
-	  * \param pool Pointer to the pool.
-	  */
-	  static void create_and_attach(shared_ptr<pool_type> const & pool)
-	  {
-		  shared_ptr<worker_thread> worker(new worker_thread(pool));
-		  if(worker)
-		  {
-			  worker->m_thread.reset(new boost::thread(bind(&worker_thread::run, worker)));
-		  }
-	  }
-
-  };
-
-
-} } } // namespace boost::threadpool::detail
-
-#endif // THREADPOOL_DETAIL_WORKER_THREAD_HPP_INCLUDED
-

DELETED 3rd_party/threadpool/boost/threadpool/future.hpp
Index: 3rd_party/threadpool/boost/threadpool/future.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/future.hpp
+++ 3rd_party/threadpool/boost/threadpool/future.hpp
@@ -1,144 +0,0 @@
-/*! \file
-* \brief TODO.
-*
-* TODO. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-#ifndef THREADPOOL_FUTURE_HPP_INCLUDED
-#define THREADPOOL_FUTURE_HPP_INCLUDED
-
-
-  
-#include "./detail/future.hpp"
-#include <boost/utility/enable_if.hpp>
-
-//#include "pool.hpp"
-//#include <boost/utility.hpp>
-
-//#include <boost/thread/mutex.hpp>
-
-
-namespace boost { namespace threadpool
-{
-
-  /*! \brief Experimental. Do not use in production code. TODO. 
-  *
-  * TODO Future
-  *
-  * \see TODO
-  *
-  */ 
-
-
-template<class Result> 
-class future
-{
-private:
-  shared_ptr<detail::future_impl<Result> > m_impl;
-
-public:
-    typedef Result const & result_type; //!< Indicates the functor's result type.
-    typedef Result future_result_type; //!< Indicates the future's result type.
-
-
-public:
-
-  future()
-  : m_impl(new detail::future_impl<future_result_type>()) // TODO remove this
-  {
-  }
-
-  // only for internal usage
-  future(shared_ptr<detail::future_impl<Result> > const & impl)
-  : m_impl(impl)
-  {
-  }
-
-  bool ready() const
-  {
-    return m_impl->ready();
-  }
-
-  void wait() const
-  {
-    m_impl->wait();
-  }
-
-  bool timed_wait(boost::xtime const & timestamp) const
-  {
-    return m_impl->timed_wait(timestamp);
-  }
-
-   result_type operator()() // throw( thread::cancelation_exception, ... )
-   {
-     return (*m_impl)();
-   }
-
-   result_type get() // throw( thread::cancelation_exception, ... )
-   {
-     return (*m_impl)();
-   }
-
-   bool cancel()
-   {
-     return m_impl->cancel();
-   }
-
-   bool is_cancelled() const
-   {
-     return m_impl->is_cancelled();
-   }
-};
-
-
-
-
-
-template<class Pool, class Function>
-typename disable_if < 
-  is_void< typename result_of< Function() >::type >,
-  future< typename result_of< Function() >::type >
->::type
-schedule(Pool& pool, const Function& task)
-{
-  typedef typename result_of< Function() >::type future_result_type;
-
-  // create future impl and future
-  shared_ptr<detail::future_impl<future_result_type> > impl(new detail::future_impl<future_result_type>);
-  future <future_result_type> res(impl);
-
-  // schedule future impl
-  pool.schedule(detail::future_impl_task_func<detail::future_impl, Function>(task, impl));
-
-  // return future
-  return res;
-
-/*
- TODO
-  if(pool->schedule(bind(&Future::run, future)))
-  {
-    return future;
-  }
-  else
-  {
-    // construct empty future
-    return error_future;
-  }
-  */
-}
-
-
-
-} } // namespace boost::threadpool
-
-#endif // THREADPOOL_FUTURE_HPP_INCLUDED
-

DELETED 3rd_party/threadpool/boost/threadpool/pool.hpp
Index: 3rd_party/threadpool/boost/threadpool/pool.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/pool.hpp
+++ 3rd_party/threadpool/boost/threadpool/pool.hpp
@@ -1,232 +0,0 @@
-/*! \file
-* \brief Thread pool core.
-*
-* This file contains the threadpool's core class: pool<Task, SchedulingPolicy>.
-*
-* Thread pools are a mechanism for asynchronous and parallel processing 
-* within the same process. The pool class provides a convenient way 
-* for dispatching asynchronous tasks as functions objects. The scheduling
-* of these tasks can be easily controlled by using customized schedulers. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_POOL_HPP_INCLUDED
-#define THREADPOOL_POOL_HPP_INCLUDED
-
-#include <boost/ref.hpp>
-
-#include "./detail/pool_core.hpp"
-
-#include "task_adaptors.hpp"
-
-#include "./detail/locking_ptr.hpp"
-
-#include "scheduling_policies.hpp"
-#include "size_policies.hpp"
-#include "shutdown_policies.hpp"
-
-
-
-/// The namespace threadpool contains a thread pool and related utility classes.
-namespace boost { namespace threadpool
-{
-
-
-
-  /*! \brief Thread pool. 
-  *
-  * Thread pools are a mechanism for asynchronous and parallel processing 
-  * within the same process. The pool class provides a convenient way 
-  * for dispatching asynchronous tasks as functions objects. The scheduling
-  * of these tasks can be easily controlled by using customized schedulers. 
-  * A task must not throw an exception.
-  *
-  * A pool is DefaultConstructible, CopyConstructible and Assignable.
-  * It has reference semantics; all copies of the same pool are equivalent and interchangeable. 
-  * All operations on a pool except assignment are strongly thread safe or sequentially consistent; 
-  * that is, the behavior of concurrent calls is as if the calls have been issued sequentially in an unspecified order.
-  *
-  * \param Task A function object which implements the operator 'void operator() (void) const'. The operator () is called by the pool to execute the task. Exceptions are ignored.
-  * \param SchedulingPolicy A task container which determines how tasks are scheduled. It is guaranteed that this container is accessed only by one thread at a time. The scheduler shall not throw exceptions.
-  *
-  * \remarks The pool class is thread-safe.
-  * 
-  * \see Tasks: task_func, prio_task_func
-  * \see Scheduling policies: fifo_scheduler, lifo_scheduler, prio_scheduler
-  */ 
-  template <
-    typename Task                                   = task_func,
-    template <typename> class SchedulingPolicy      = fifo_scheduler,
-    template <typename> class SizePolicy            = static_size,
-    template <typename> class SizePolicyController  = resize_controller,
-    template <typename> class ShutdownPolicy        = wait_for_all_tasks
-  > 
-  class thread_pool 
-  {
-    typedef detail::pool_core<Task, 
-                              SchedulingPolicy,
-                              SizePolicy,
-                              SizePolicyController,
-                              ShutdownPolicy> pool_core_type;
-    shared_ptr<pool_core_type>          m_core; // pimpl idiom
-    shared_ptr<void>                    m_shutdown_controller; // If the last pool holding a pointer to the core is deleted the controller shuts the pool down.
-
-  public: // Type definitions
-    typedef Task task_type;                                   //!< Indicates the task's type.
-    typedef SchedulingPolicy<task_type> scheduler_type;       //!< Indicates the scheduler's type.
- /*   typedef thread_pool<Task, 
-                        SchedulingPolicy,
-                        SizePolicy,
-                        ShutdownPolicy > pool_type;          //!< Indicates the thread pool's type.
- */
-    typedef SizePolicy<pool_core_type> size_policy_type; 
-    typedef SizePolicyController<pool_core_type> size_controller_type;
-
-
-  public:
-    /*! Constructor.
-     * \param initial_threads The pool is immediately resized to set the specified number of threads. The pool's actual number threads depends on the SizePolicy.
-     */
-    thread_pool(size_t initial_threads = 0)
-    : m_core(new pool_core_type)
-    , m_shutdown_controller(static_cast<void*>(0), bind(&pool_core_type::shutdown, m_core))
-    {
-      size_policy_type::init(*m_core, initial_threads);
-    }
-
-
-    /*! Gets the size controller which manages the number of threads in the pool. 
-    * \return The size controller.
-    * \see SizePolicy
-    */
-    size_controller_type size_controller()
-    {
-      return m_core->size_controller();
-    }
-
-
-    /*! Gets the number of threads in the pool.
-    * \return The number of threads.
-    */
-    size_t size()	const
-    {
-      return m_core->size();
-    }
-
-
-     /*! Schedules a task for asynchronous execution. The task will be executed once only.
-     * \param task The task function object. It should not throw execeptions.
-     * \return true, if the task could be scheduled and false otherwise. 
-     */  
-     bool schedule(task_type const & task)
-     {	
-       return m_core->schedule(task);
-     }
-
-
-    /*! Returns the number of tasks which are currently executed.
-    * \return The number of active tasks. 
-    */  
-    size_t active() const
-    {
-      return m_core->active();
-    }
-
-
-    /*! Returns the number of tasks which are ready for execution.    
-    * \return The number of pending tasks. 
-    */  
-    size_t pending() const
-    {
-      return m_core->pending();
-    }
-
-
-    /*! Removes all pending tasks from the pool's scheduler.
-    */  
-    void clear()
-    { 
-      m_core->clear();
-    }    
-
-
-    /*! Indicates that there are no tasks pending. 
-    * \return true if there are no tasks ready for execution.	
-    * \remarks This function is more efficient that the check 'pending() == 0'.
-    */   
-    bool empty() const
-    {
-      return m_core->empty();
-    }	
-
-
-    /*! The current thread of execution is blocked until the sum of all active
-    *  and pending tasks is equal or less than a given threshold. 
-    * \param task_threshold The maximum number of tasks in pool and scheduler.
-    */     
-    void wait(size_t task_threshold = 0) const
-    {
-      m_core->wait(task_threshold);
-    }	
-
-
-    /*! The current thread of execution is blocked until the timestamp is met
-    * or the sum of all active and pending tasks is equal or less 
-    * than a given threshold.  
-    * \param timestamp The time when function returns at the latest.
-    * \param task_threshold The maximum number of tasks in pool and scheduler.
-    * \return true if the task sum is equal or less than the threshold, false otherwise.
-    */       
-    bool wait(xtime const & timestamp, size_t task_threshold = 0) const
-    {
-      return m_core->wait(timestamp, task_threshold);
-    }
-  };
-
-
-
-  /*! \brief Fifo pool.
-  *
-  * The pool's tasks are fifo scheduled task_func functors.
-  *
-  */ 
-  typedef thread_pool<task_func, fifo_scheduler, static_size, resize_controller, wait_for_all_tasks> fifo_pool;
-
-
-  /*! \brief Lifo pool.
-  *
-  * The pool's tasks are lifo scheduled task_func functors.
-  *
-  */ 
-  typedef thread_pool<task_func, lifo_scheduler, static_size, resize_controller, wait_for_all_tasks> lifo_pool;
-
-
-  /*! \brief Pool for prioritized task.
-  *
-  * The pool's tasks are prioritized prio_task_func functors.
-  *
-  */ 
-  typedef thread_pool<prio_task_func, prio_scheduler, static_size, resize_controller, wait_for_all_tasks> prio_pool;
-
-
-  /*! \brief A standard pool.
-  *
-  * The pool's tasks are fifo scheduled task_func functors.
-  *
-  */ 
-  typedef fifo_pool pool;
-
-
-
-} } // namespace boost::threadpool
-
-#endif // THREADPOOL_POOL_HPP_INCLUDED

DELETED 3rd_party/threadpool/boost/threadpool/pool_adaptors.hpp
Index: 3rd_party/threadpool/boost/threadpool/pool_adaptors.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/pool_adaptors.hpp
+++ 3rd_party/threadpool/boost/threadpool/pool_adaptors.hpp
@@ -1,70 +0,0 @@
-/*! \file
-* \brief Pool adaptors.
-*
-* This file contains an easy-to-use adaptor similar to a smart 
-* pointer for the pool class. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_POOL_ADAPTORS_HPP_INCLUDED
-#define THREADPOOL_POOL_ADAPTORS_HPP_INCLUDED
-
-#include <boost/smart_ptr.hpp>
-
-
-namespace boost { namespace threadpool
-{
-
-
-// TODO convenience scheduling function
-    /*! Schedules a Runnable for asynchronous execution. A Runnable is an arbitrary class with a run()
-    * member function. This a convenience shorthand for pool->schedule(bind(&Runnable::run, task_object)).
-    * \param 
-    * \param obj The Runnable object. The member function run() will be exectued and should not throw execeptions.
-    * \return true, if the task could be scheduled and false otherwise. 
-    */  
-    template<typename Pool, typename Runnable>
-    bool schedule(Pool& pool, shared_ptr<Runnable> const & obj)
-    {	
-      return pool->schedule(bind(&Runnable::run, obj));
-    }	
-    
-    /*! Schedules a task for asynchronous execution. The task will be executed once only.
-    * \param task The task function object.
-    */  
-    template<typename Pool>
-    typename enable_if < 
-      is_void< typename result_of< typename Pool::task_type() >::type >,
-      bool
-    >::type
-    schedule(Pool& pool, typename Pool::task_type const & task)
-    {	
-      return pool.schedule(task);
-    }	
-
-
-    template<typename Pool>
-    typename enable_if < 
-      is_void< typename result_of< typename Pool::task_type() >::type >,
-      bool
-    >::type
-    schedule(shared_ptr<Pool> const pool, typename Pool::task_type const & task)
-    {	
-      return pool->schedule(task);
-    }	
-
-
-} } // namespace boost::threadpool
-
-#endif // THREADPOOL_POOL_ADAPTORS_HPP_INCLUDED
-
-

DELETED 3rd_party/threadpool/boost/threadpool/scheduling_policies.hpp
Index: 3rd_party/threadpool/boost/threadpool/scheduling_policies.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/scheduling_policies.hpp
+++ 3rd_party/threadpool/boost/threadpool/scheduling_policies.hpp
@@ -1,262 +0,0 @@
-/*! \file
-* \brief Task scheduling policies.
-*
-* This file contains some fundamental scheduling policies for the pool class. 
-* A scheduling policy is realized by a task container which controls the access to
-* the tasks. 	Fundamentally the container determines the order the tasks are processed
-* by the thread pool. 
-* The task containers need not to be thread-safe because they are used by the pool 
-* in thread-safe way. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_SCHEDULING_POLICIES_HPP_INCLUDED
-#define THREADPOOL_SCHEDULING_POLICIES_HPP_INCLUDED
-
-
-#include <queue>
-#include <deque>
-
-#include "task_adaptors.hpp"
-
-namespace boost { namespace threadpool
-{
-
-  /*! \brief SchedulingPolicy which implements FIFO ordering. 
-  *
-  * This container implements a FIFO scheduling policy.
-  * The first task to be added to the scheduler will be the first to be removed.
-  * The processing proceeds sequentially in the same order. 
-  * FIFO stands for "first in, first out".
-  *
-  * \param Task A function object which implements the operator()(void).
-  *
-  */ 
-  template <typename Task = task_func>  
-  class fifo_scheduler
-  {
-  public:
-    typedef Task task_type; //!< Indicates the scheduler's task type.
-
-  protected:
-    std::deque<task_type> m_container;  //!< Internal task container.	
-
-
-  public:
-    /*! Adds a new task to the scheduler.
-    * \param task The task object.
-    * \return true, if the task could be scheduled and false otherwise. 
-    */
-    bool push(task_type const & task)
-    {
-      m_container.push_back(task);
-      return true;
-    }
-
-    /*! Removes the task which should be executed next.
-    */
-    void pop()
-    {
-      m_container.pop_front();
-    }
-
-    /*! Gets the task which should be executed next.
-    *  \return The task object to be executed.
-    */
-    task_type const & top() const
-    {
-      return m_container.front();
-    }
-
-    /*! Gets the current number of tasks in the scheduler.
-    *  \return The number of tasks.
-    *  \remarks Prefer empty() to size() == 0 to check if the scheduler is empty.
-    */
-    size_t size() const
-    {
-      return m_container.size();
-    }
-
-    /*! Checks if the scheduler is empty.
-    *  \return true if the scheduler contains no tasks, false otherwise.
-    *  \remarks Is more efficient than size() == 0. 
-    */
-    bool empty() const
-    {
-      return m_container.empty();
-    }
-
-    /*! Removes all tasks from the scheduler.
-    */  
-    void clear()
-    {   
-      m_container.clear();
-    } 
-  };
-
-
-
-  /*! \brief SchedulingPolicy which implements LIFO ordering. 
-  *
-  * This container implements a LIFO scheduling policy.
-  * The last task to be added to the scheduler will be the first to be removed.
-  * LIFO stands for "last in, first out".
-  *
-  * \param Task A function object which implements the operator()(void).
-  *
-  */ 
-  template <typename Task = task_func>  
-  class lifo_scheduler
-  {
-  public:
-    typedef Task task_type;  //!< Indicates the scheduler's task type.
-
-  protected:
-    std::deque<task_type> m_container;  //!< Internal task container.	
-
-  public:
-    /*! Adds a new task to the scheduler.
-    * \param task The task object.
-    * \return true, if the task could be scheduled and false otherwise. 
-    */
-    bool push(task_type const & task)
-    {
-      m_container.push_front(task);
-      return true;
-    }
-
-    /*! Removes the task which should be executed next.
-    */
-    void pop()
-    {
-      m_container.pop_front();
-    }
-
-    /*! Gets the task which should be executed next.
-    *  \return The task object to be executed.
-    */
-    task_type const & top() const
-    {
-      return m_container.front();
-    }
-
-    /*! Gets the current number of tasks in the scheduler.
-    *  \return The number of tasks.
-    *  \remarks Prefer empty() to size() == 0 to check if the scheduler is empty.
-    */
-    size_t size() const
-    {
-      return m_container.size();
-    }
-
-    /*! Checks if the scheduler is empty.
-    *  \return true if the scheduler contains no tasks, false otherwise.
-    *  \remarks Is more efficient than size() == 0. 
-    */
-    bool empty() const
-    {
-      return m_container.empty();
-    }
-
-    /*! Removes all tasks from the scheduler.
-    */  
-    void clear()
-    {    
-      m_container.clear();
-    } 
-
-  };
-
-
-
-  /*! \brief SchedulingPolicy which implements prioritized ordering. 
-  *
-  * This container implements a scheduling policy based on task priorities.
-  * The task with highest priority will be the first to be removed.
-  * It must be possible to compare two tasks using operator<. 
-  *
-  * \param Task A function object which implements the operator() and operator<. operator< must be a partial ordering.
-  *
-  * \see prio_thread_func
-  *
-  */ 
-  template <typename Task = prio_task_func>  
-  class prio_scheduler
-  {
-  public:
-    typedef Task task_type; //!< Indicates the scheduler's task type.
-
-  protected:
-    std::priority_queue<task_type> m_container;  //!< Internal task container.
-
-
-  public:
-    /*! Adds a new task to the scheduler.
-    * \param task The task object.
-    * \return true, if the task could be scheduled and false otherwise. 
-    */
-    bool push(task_type const & task)
-    {
-      m_container.push(task);
-      return true;
-    }
-
-    /*! Removes the task which should be executed next.
-    */
-    void pop()
-    {
-      m_container.pop();
-    }
-
-    /*! Gets the task which should be executed next.
-    *  \return The task object to be executed.
-    */
-    task_type const & top() const
-    {
-      return m_container.top();
-    }
-
-    /*! Gets the current number of tasks in the scheduler.
-    *  \return The number of tasks.
-    *  \remarks Prefer empty() to size() == 0 to check if the scheduler is empty.
-    */
-    size_t size() const
-    {
-      return m_container.size();
-    }
-
-    /*! Checks if the scheduler is empty.
-    *  \return true if the scheduler contains no tasks, false otherwise.
-    *  \remarks Is more efficient than size() == 0. 
-    */
-    bool empty() const
-    {
-      return m_container.empty();
-    }
-
-    /*! Removes all tasks from the scheduler.
-    */  
-    void clear()
-    {    
-      while(!m_container.empty())
-      {
-        m_container.pop();
-      }
-    } 
-  };
-
-
-} } // namespace boost::threadpool
-
-
-#endif // THREADPOOL_SCHEDULING_POLICIES_HPP_INCLUDED
-

DELETED 3rd_party/threadpool/boost/threadpool/shutdown_policies.hpp
Index: 3rd_party/threadpool/boost/threadpool/shutdown_policies.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/shutdown_policies.hpp
+++ 3rd_party/threadpool/boost/threadpool/shutdown_policies.hpp
@@ -1,83 +0,0 @@
-/*! \file
-* \brief Shutdown policies.
-*
-* This file contains shutdown policies for thread_pool. 
-* A shutdown policy controls the pool's behavior from the time
-* when the pool is not referenced any longer.
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_SHUTDOWN_POLICIES_HPP_INCLUDED
-#define THREADPOOL_SHUTDOWN_POLICIES_HPP_INCLUDED
-
-
-
-/// The namespace threadpool contains a thread pool and related utility classes.
-namespace boost { namespace threadpool
-{
-
-
-/*! \brief ShutdownPolicy which waits for the completion of all tasks 
-  *          and the worker termination afterwards.
-    *
-  * \param Pool The pool's core type.
-  */ 
-  template<typename Pool>
-  class wait_for_all_tasks
-  {
-  public:
-    static void shutdown(Pool& pool)
-    {
-      pool.wait();
-      pool.terminate_all_workers(true);
-    }
-  };
-
-
-  /*! \brief ShutdownPolicy which waits for the completion of all active tasks 
-  *          and the worker termination afterwards.
-  *
-  * \param Pool The pool's core type.
-  */ 
-  template<typename Pool>
-  class wait_for_active_tasks
-  {
-  public:
-    static void shutdown(Pool& pool)
-    {
-      pool.clear();
-      pool.wait();
-      pool.terminate_all_workers(true);
-    }
-  };
-
-
-  /*! \brief ShutdownPolicy which does not wait for any tasks or worker termination.
-  *
-  * This policy does not wait for any tasks. Nevertheless all active tasks will be processed completely.
-  *
-  * \param Pool The pool's core type.
-  */ 
-  template<typename Pool>
-  class immediately
-  {
-  public:
-    static void shutdown(Pool& pool)
-    {
-      pool.clear();
-      pool.terminate_all_workers(false);
-    }
-  };
-
-} } // namespace boost::threadpool
-
-#endif // THREADPOOL_SHUTDOWN_POLICIES_HPP_INCLUDED

DELETED 3rd_party/threadpool/boost/threadpool/size_policies.hpp
Index: 3rd_party/threadpool/boost/threadpool/size_policies.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/size_policies.hpp
+++ 3rd_party/threadpool/boost/threadpool/size_policies.hpp
@@ -1,99 +0,0 @@
-/*! \file
-* \brief Size policies.
-*
-* This file contains size policies for thread_pool. A size 
-* policy controls the number of worker threads in the pool.
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_SIZE_POLICIES_HPP_INCLUDED
-#define THREADPOOL_SIZE_POLICIES_HPP_INCLUDED
-
-
-
-/// The namespace threadpool contains a thread pool and related utility classes.
-namespace boost { namespace threadpool
-{
-
-  /*! \brief SizePolicyController which provides no functionality.
-  *
-  * \param Pool The pool's core type.
-  */ 
-  template<typename Pool>
-  struct empty_controller
-  {
-    empty_controller(typename Pool::size_policy_type&, shared_ptr<Pool>) {}
-  };
-
-
-  /*! \brief SizePolicyController which allows resizing.
-  *
-  * \param Pool The pool's core type.
-  */ 
-  template< typename Pool >
-  class resize_controller
-  {
-    typedef typename Pool::size_policy_type size_policy_type;
-    reference_wrapper<size_policy_type> m_policy;
-    shared_ptr<Pool> m_pool;                           //!< to make sure that the pool is alive (the policy pointer is valid) as long as the controller exists
-
-  public:
-    resize_controller(size_policy_type& policy, shared_ptr<Pool> pool)
-      : m_policy(policy)
-      , m_pool(pool)
-    {
-    }
-
-    bool resize(size_t worker_count)
-    {
-      return m_policy.get().resize(worker_count);
-    }
-  };
-
-
-  /*! \brief SizePolicy which preserves the thread count.
-  *
-  * \param Pool The pool's core type.
-  */ 
-  template<typename Pool>
-  class static_size
-  {
-    reference_wrapper<Pool volatile> m_pool;
-
-  public:
-    static void init(Pool& pool, size_t const worker_count)
-    {
-      pool.resize(worker_count);
-    }
-
-    static_size(Pool volatile & pool)
-      : m_pool(pool)
-    {}
-
-    bool resize(size_t const worker_count)
-    {
-      return m_pool.get().resize(worker_count);
-    }
-
-    void worker_died_unexpectedly(size_t const new_worker_count)
-    {
-      m_pool.get().resize(new_worker_count + 1);
-    }
-
-    // TODO this functions are not called yet
-    void task_scheduled() {}
-    void task_finished() {}
-  };
-
-} } // namespace boost::threadpool
-
-#endif // THREADPOOL_SIZE_POLICIES_HPP_INCLUDED

DELETED 3rd_party/threadpool/boost/threadpool/task_adaptors.hpp
Index: 3rd_party/threadpool/boost/threadpool/task_adaptors.hpp
==================================================================
--- 3rd_party/threadpool/boost/threadpool/task_adaptors.hpp
+++ 3rd_party/threadpool/boost/threadpool/task_adaptors.hpp
@@ -1,168 +0,0 @@
-/*! \file
-* \brief Task adaptors.
-*
-* This file contains adaptors for task function objects.
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Use, modification, and distribution are  subject to the
-* Boost Software License, Version 1.0. (See accompanying  file
-* LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-#ifndef THREADPOOL_TASK_ADAPTERS_HPP_INCLUDED
-#define THREADPOOL_TASK_ADAPTERS_HPP_INCLUDED
-
-
-#include <boost/smart_ptr.hpp>
-#include <boost/function.hpp>
-#include <boost/thread.hpp>
-
-
-namespace boost { namespace threadpool
-{
-
-  /*! \brief Standard task function object.
-  *
-  * This function object wraps a nullary function which returns void.
-  * The wrapped function is invoked by calling the operator ().
-  *
-  * \see boost function library
-  *
-  */ 
-  typedef function0<void> task_func;
-
-
-
-
-  /*! \brief Prioritized task function object. 
-  *
-  * This function object wraps a task_func object and binds a priority to it.
-  * prio_task_funcs can be compared using the operator < which realises a partial ordering.
-  * The wrapped task function is invoked by calling the operator ().
-  *
-  * \see prio_scheduler
-  *
-  */ 
-  class prio_task_func
-  {
-  private:
-    unsigned int m_priority;  //!< The priority of the task's function.
-    task_func m_function;     //!< The task's function.
-
-  public:
-    typedef void result_type; //!< Indicates the functor's result type.
-
-  public:
-    /*! Constructor.
-    * \param priority The priority of the task.
-    * \param function The task's function object.
-    */
-    prio_task_func(unsigned int const priority, task_func const & function)
-      : m_priority(priority)
-      , m_function(function)
-    {
-    }
-
-    /*! Executes the task function.
-    */
-    void operator() (void) const
-    {
-      if(m_function)
-      {
-        m_function();
-      }
-    }
-
-    /*! Comparison operator which realises a partial ordering based on priorities.
-    * \param rhs The object to compare with.
-    * \return true if the priority of *this is less than right hand side's priority, false otherwise.
-    */
-    bool operator< (const prio_task_func& rhs) const
-    {
-      return m_priority < rhs.m_priority; 
-    }
-
-  };  // prio_task_func
-
-
-
- 
-
-
-
-
-  /*! \brief Looped task function object. 
-  *
-  * This function object wraps a boolean thread function object.
-  * The wrapped task function is invoked by calling the operator () and it is executed in regular 
-  * time intervals until false is returned. The interval length may be zero.
-  * Please note that a pool's thread is engaged as long as the task is looped.
-  *
-  */ 
-  class looped_task_func
-  {
-  private:
-    function0<bool> m_function;   //!< The task's function.
-    unsigned int m_break_s;              //!< Duration of breaks in seconds.
-    unsigned int m_break_ns;             //!< Duration of breaks in nano seconds.
-
-  public:
-    typedef void result_type; //!< Indicates the functor's result type.
-
-  public:
-    /*! Constructor.
-    * \param function The task's function object which is looped until false is returned.
-    * \param interval The minimum break time in milli seconds before the first execution of the task function and between the following ones.
-    */
-    looped_task_func(function0<bool> const & function, unsigned int const interval = 0)
-      : m_function(function)
-    {
-      m_break_s  = interval / 1000;
-      m_break_ns = (interval - m_break_s * 1000) * 1000 * 1000;
-    }
-
-    /*! Executes the task function.
-    */
-    void operator() (void) const
-    {
-      if(m_function)
-      {
-        if(m_break_s > 0 || m_break_ns > 0)
-        { // Sleep some time before first execution
-          xtime xt;
-          xtime_get(&xt, TIME_UTC_);
-          xt.nsec += m_break_ns;
-          xt.sec += m_break_s;
-          thread::sleep(xt); 
-        }
-
-        while(m_function())
-        {
-          if(m_break_s > 0 || m_break_ns > 0)
-          {
-            xtime xt;
-            xtime_get(&xt, TIME_UTC_);
-            xt.nsec += m_break_ns;
-            xt.sec += m_break_s;
-            thread::sleep(xt); 
-          }
-          else
-          {
-            thread::yield(); // Be fair to other threads
-          }
-        }
-      }
-    }
-
-  }; // looped_task_func
-
-
-} } // namespace boost::threadpool
-
-#endif // THREADPOOL_TASK_ADAPTERS_HPP_INCLUDED
-

DELETED 3rd_party/threadpool/libs/threadpool/doc/Makefile
Index: 3rd_party/threadpool/libs/threadpool/doc/Makefile
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/Makefile
+++ 3rd_party/threadpool/libs/threadpool/doc/Makefile
@@ -1,36 +0,0 @@
-DOXYGEN=doxygen
-
-doc: clean copy_footer generate_doc
-
-copy_footer:
-	cp footer/*.htm .
-	
-copy_footer_sf:
-	cp footer_sf/*.htm .	
-	
-generate_doc:
-	$(DOXYGEN) overview.dox
-	$(DOXYGEN) reference.dox
-	$(DOXYGEN) tutorial.dox
-	$(DOXYGEN) examples.dox
-	$(DOXYGEN) design.dox
-
-clean:
-	rm -rf ../../../doc
-	rm -rf ../../../threadpool-$(RELEASE_VERSION)-doc
-	rm -rf ../../../threadpool-$(RELEASE_VERSION)-doc.zip
-
-release_doc: clean doc
-	cd ../../..; mv doc threadpool-$(RELEASE_VERSION)-doc
-	cd ../../..; zip -r9 threadpool-$(RELEASE_VERSION)-doc.zip threadpool-$(RELEASE_VERSION)-doc
-	cd ../../..; mv threadpool-$(RELEASE_VERSION)-doc doc
-
-doc_sf: clean copy_footer_sf generate_doc
-
-deploy_sf: doc_sf
-	scp -vr ../../../doc/*  $(RELEASE_MANAGER)@shell.sourceforge.net:/home/groups/t/th/threadpool/htdocs	
-	
-
-
-
-

DELETED 3rd_party/threadpool/libs/threadpool/doc/design.dox
Index: 3rd_party/threadpool/libs/threadpool/doc/design.dox
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/design.dox
+++ 3rd_party/threadpool/libs/threadpool/doc/design.dox
@@ -1,145 +0,0 @@
-#---------------------------------------------------------------------------
-# Project related configuration options
-#---------------------------------------------------------------------------
-PROJECT_NAME           = "threadpool"
-PROJECT_NUMBER         =
-OUTPUT_DIRECTORY       = ../../../doc/design
-CREATE_SUBDIRS         = NO
-OUTPUT_LANGUAGE        = English
-USE_WINDOWS_ENCODING   = NO
-BRIEF_MEMBER_DESC      = NO
-REPEAT_BRIEF           = NO
-ALWAYS_DETAILED_SEC    = YES
-INLINE_INHERITED_MEMB  = YES
-FULL_PATH_NAMES        = YES
-STRIP_FROM_PATH        = /../../include/
-STRIP_FROM_INC_PATH    = 
-SHORT_NAMES            = YES
-JAVADOC_AUTOBRIEF      = NO
-MULTILINE_CPP_IS_BRIEF = YES
-DETAILS_AT_TOP         = YES
-INHERIT_DOCS           = YES
-DISTRIBUTE_GROUP_DOC   = NO
-SEPARATE_MEMBER_PAGES  = NO
-TAB_SIZE               = 2
-ALIASES                = 
-OPTIMIZE_OUTPUT_FOR_C  = NO
-OPTIMIZE_OUTPUT_JAVA   = NO
-SUBGROUPING            = YES
-
-#---------------------------------------------------------------------------
-# Build related configuration options
-#---------------------------------------------------------------------------
-EXTRACT_ALL            = NO
-EXTRACT_PRIVATE        = NO
-EXTRACT_STATIC         = NO
-EXTRACT_LOCAL_CLASSES  = NO
-EXTRACT_LOCAL_METHODS  = NO
-HIDE_UNDOC_MEMBERS     = YES
-HIDE_UNDOC_CLASSES     = YES
-HIDE_FRIEND_COMPOUNDS  = NO
-HIDE_IN_BODY_DOCS      = NO
-INTERNAL_DOCS          = NO
-CASE_SENSE_NAMES       = YES
-HIDE_SCOPE_NAMES       = NO
-SHOW_INCLUDE_FILES     = NO
-INLINE_INFO            = NO
-SORT_MEMBER_DOCS       = NO
-SORT_BRIEF_DOCS        = NO
-SORT_BY_SCOPE_NAME     = NO
-GENERATE_TODOLIST      = NO
-GENERATE_TESTLIST      = NO
-GENERATE_BUGLIST       = NO
-GENERATE_DEPRECATEDLIST= NO
-ENABLED_SECTIONS       = 
-MAX_INITIALIZER_LINES  = 30
-SHOW_USED_FILES        = NO
-SHOW_DIRECTORIES       = NO
-FILE_VERSION_FILTER    = 
-
-#---------------------------------------------------------------------------
-# configuration options related to warning and progress messages
-#---------------------------------------------------------------------------
-QUIET                  = NO
-WARNINGS               = YES
-WARN_IF_UNDOCUMENTED   = YES
-WARN_IF_DOC_ERROR      = YES
-WARN_NO_PARAMDOC       = NO
-WARN_FORMAT            = "$file:$line: $text"
-WARN_LOGFILE           = 
-
-#---------------------------------------------------------------------------
-# configuration options related to the input files
-#---------------------------------------------------------------------------
-INPUT                  = design.txt
-FILE_PATTERNS          = 
-RECURSIVE              = NO
-EXCLUDE                = 
-EXCLUDE_SYMLINKS       = NO
-EXCLUDE_PATTERNS       = 
-EXAMPLE_PATH           =
-EXAMPLE_PATTERNS       = 
-EXAMPLE_RECURSIVE      = YES
-IMAGE_PATH             = 
-INPUT_FILTER           = 
-FILTER_PATTERNS        = 
-FILTER_SOURCE_FILES    = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to source browsing
-#---------------------------------------------------------------------------
-SOURCE_BROWSER         = NO
-INLINE_SOURCES         = NO
-STRIP_CODE_COMMENTS    = YES
-REFERENCED_BY_RELATION = NO
-REFERENCES_RELATION    = NO
-VERBATIM_HEADERS       = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the alphabetical class index
-#---------------------------------------------------------------------------
-ALPHABETICAL_INDEX     = NO
-COLS_IN_ALPHA_INDEX    = 1
-IGNORE_PREFIX          = 
-
-#---------------------------------------------------------------------------
-# configuration options related to the HTML output
-#---------------------------------------------------------------------------
-GENERATE_HTML          = YES
-HTML_OUTPUT            = .
-HTML_FILE_EXTENSION    = .html
-HTML_HEADER            = design_header.htm
-HTML_FOOTER            = common_footer.htm
-HTML_STYLESHEET        = threadpool.css
-HTML_ALIGN_MEMBERS     = YES
-GENERATE_HTMLHELP      = NO
-CHM_FILE               = 
-HHC_LOCATION           = 
-GENERATE_CHI           = NO
-BINARY_TOC             = NO
-TOC_EXPAND             = NO
-DISABLE_INDEX          = YES
-ENUM_VALUES_PER_LINE   = 1
-GENERATE_TREEVIEW      = NO
-TREEVIEW_WIDTH         = 250
-
-
-#---------------------------------------------------------------------------
-# configuration options related to the LaTeX output
-#---------------------------------------------------------------------------
-GENERATE_LATEX         = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the RTF output
-#---------------------------------------------------------------------------
-GENERATE_RTF           = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the man page output
-#---------------------------------------------------------------------------
-GENERATE_MAN           = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the XML output
-#---------------------------------------------------------------------------
-GENERATE_XML           = NO

DELETED 3rd_party/threadpool/libs/threadpool/doc/design.txt
Index: 3rd_party/threadpool/libs/threadpool/doc/design.txt
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/design.txt
+++ 3rd_party/threadpool/libs/threadpool/doc/design.txt
@@ -1,35 +0,0 @@
-/*! \page intro TODO5
-
-
-A thread pool manages a homogeneous pool of worker threads. In general worker threads are created once and are used to 
-process a sequence of tasks. The re-use of threads reduces the thread creation and teardown overhead. The resource 
-consumption is limited as the number of threads can be restricted. This leads to an improved system stability.
-
-Thread-per-task 
-
-TODO5
-
-light-weight, no administration/management thread, synchronized scheduler, e.g. queue
-
-
- */
-
-
-/*! \page pattern Thread Pool Pattern
-
-
-In the thread pool pattern in programming, a number of N threads are created to perform a number of M tasks, usually organized in a queue. Typically, N << M. As soon as a thread completes its task, it will request the next task from the queue until all tasks have been completed. The thread can then terminate, or sleep until there are new tasks available.
-
-The number of threads used (N) is a parameter that can be tuned to provide the best performance.
-
-The advantage of using a Thread Pool over creating a new thread for each task, is that thread creation and destruction overhead is negated, which may result in better performance and better system stability.
-
-<BR>
-<B>From <A HREF="http://en.wikipedia.org/wiki/Thread_pool_pattern"> Wikipedia </A>, the free encyclopedia.</B>
-
-
-
- */
-
-
-

DELETED 3rd_party/threadpool/libs/threadpool/doc/design_header.htm
Index: 3rd_party/threadpool/libs/threadpool/doc/design_header.htm
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/design_header.htm
+++ 3rd_party/threadpool/libs/threadpool/doc/design_header.htm
@@ -1,38 +0,0 @@
-<HTML>
-  <HEAD>
-    <TITLE>threadpool Documentation</TITLE>
-    <LINK HREF="threadpool.css" REL="stylesheet" TYPE="text/css">
-  </HEAD>
-  <BODY BGCOLOR="#FFFFFF">
-
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-
-          <TD ALIGN="LEFT">
-            <B>$projectname</B>
-          </TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="../index.html">Overview</A> |
-            <A CLASS="qindex" HREF="../reference/annotated.html">Reference</A> |
-            <A CLASS="qindex" HREF="../tutorial/intro.html">Tutorial</A> |
-            <A CLASS="qindex" HREF="../examples/intro.html">Examples</A> |
-            <A CLASS="qindex" HREF="../design/intro.html">Design</A>
-          </TD>
-
-        </TR>
-      </TABLE>
-    </DIV>
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-          <TD ALIGN="LEFT">
-            <B>Design</B>
-          </TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="intro.html">TODO5</A> |
-            <A CLASS="qindex" HREF="pattern.html">Thread Pool Pattern</A>
-          </TD>
-        </TR>
-      </TABLE>
-    </DIV>

DELETED 3rd_party/threadpool/libs/threadpool/doc/examples.dox
Index: 3rd_party/threadpool/libs/threadpool/doc/examples.dox
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/examples.dox
+++ 3rd_party/threadpool/libs/threadpool/doc/examples.dox
@@ -1,145 +0,0 @@
-#---------------------------------------------------------------------------
-# Project related configuration options
-#---------------------------------------------------------------------------
-PROJECT_NAME           = "threadpool"
-PROJECT_NUMBER         = 
-OUTPUT_DIRECTORY       = ../../../doc/examples
-CREATE_SUBDIRS         = NO
-OUTPUT_LANGUAGE        = English
-USE_WINDOWS_ENCODING   = NO
-BRIEF_MEMBER_DESC      = NO
-REPEAT_BRIEF           = NO
-ALWAYS_DETAILED_SEC    = YES
-INLINE_INHERITED_MEMB  = YES
-FULL_PATH_NAMES        = YES
-STRIP_FROM_PATH        = /../../include
-STRIP_FROM_INC_PATH    = 
-SHORT_NAMES            = YES
-JAVADOC_AUTOBRIEF      = NO
-MULTILINE_CPP_IS_BRIEF = YES
-DETAILS_AT_TOP         = YES
-INHERIT_DOCS           = YES
-DISTRIBUTE_GROUP_DOC   = NO
-SEPARATE_MEMBER_PAGES  = NO
-TAB_SIZE               = 2
-ALIASES                = 
-OPTIMIZE_OUTPUT_FOR_C  = NO
-OPTIMIZE_OUTPUT_JAVA   = NO
-SUBGROUPING            = YES
-
-#---------------------------------------------------------------------------
-# Build related configuration options
-#---------------------------------------------------------------------------
-EXTRACT_ALL            = NO
-EXTRACT_PRIVATE        = NO
-EXTRACT_STATIC         = NO
-EXTRACT_LOCAL_CLASSES  = NO
-EXTRACT_LOCAL_METHODS  = NO
-HIDE_UNDOC_MEMBERS     = YES
-HIDE_UNDOC_CLASSES     = YES
-HIDE_FRIEND_COMPOUNDS  = NO
-HIDE_IN_BODY_DOCS      = NO
-INTERNAL_DOCS          = NO
-CASE_SENSE_NAMES       = YES
-HIDE_SCOPE_NAMES       = NO
-SHOW_INCLUDE_FILES     = NO
-INLINE_INFO            = NO
-SORT_MEMBER_DOCS       = NO
-SORT_BRIEF_DOCS        = NO
-SORT_BY_SCOPE_NAME     = NO
-GENERATE_TODOLIST      = NO
-GENERATE_TESTLIST      = NO
-GENERATE_BUGLIST       = NO
-GENERATE_DEPRECATEDLIST= NO
-ENABLED_SECTIONS       = 
-MAX_INITIALIZER_LINES  = 30
-SHOW_USED_FILES        = NO
-SHOW_DIRECTORIES       = NO
-FILE_VERSION_FILTER    = 
-
-#---------------------------------------------------------------------------
-# configuration options related to warning and progress messages
-#---------------------------------------------------------------------------
-QUIET                  = NO
-WARNINGS               = YES
-WARN_IF_UNDOCUMENTED   = YES
-WARN_IF_DOC_ERROR      = YES
-WARN_NO_PARAMDOC       = NO
-WARN_FORMAT            = "$file:$line: $text"
-WARN_LOGFILE           = 
-
-#---------------------------------------------------------------------------
-# configuration options related to the input files
-#---------------------------------------------------------------------------
-INPUT                  = examples.txt
-FILE_PATTERNS          = 
-RECURSIVE              = NO
-EXCLUDE                = 
-EXCLUDE_SYMLINKS       = NO
-EXCLUDE_PATTERNS       = 
-EXAMPLE_PATH           =
-EXAMPLE_PATTERNS       = 
-EXAMPLE_RECURSIVE      = YES
-IMAGE_PATH             = 
-INPUT_FILTER           = 
-FILTER_PATTERNS        = 
-FILTER_SOURCE_FILES    = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to source browsing
-#---------------------------------------------------------------------------
-SOURCE_BROWSER         = NO
-INLINE_SOURCES         = NO
-STRIP_CODE_COMMENTS    = YES
-REFERENCED_BY_RELATION = NO
-REFERENCES_RELATION    = NO
-VERBATIM_HEADERS       = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the alphabetical class index
-#---------------------------------------------------------------------------
-ALPHABETICAL_INDEX     = NO
-COLS_IN_ALPHA_INDEX    = 1
-IGNORE_PREFIX          = 
-
-#---------------------------------------------------------------------------
-# configuration options related to the HTML output
-#---------------------------------------------------------------------------
-GENERATE_HTML          = YES
-HTML_OUTPUT            = .
-HTML_FILE_EXTENSION    = .html
-HTML_HEADER            = examples_header.htm
-HTML_FOOTER            = common_footer.htm
-HTML_STYLESHEET        = threadpool.css
-HTML_ALIGN_MEMBERS     = YES
-GENERATE_HTMLHELP      = NO
-CHM_FILE               = 
-HHC_LOCATION           = 
-GENERATE_CHI           = NO
-BINARY_TOC             = NO
-TOC_EXPAND             = NO
-DISABLE_INDEX          = YES
-ENUM_VALUES_PER_LINE   = 1
-GENERATE_TREEVIEW      = NO
-TREEVIEW_WIDTH         = 250
-
-
-#---------------------------------------------------------------------------
-# configuration options related to the LaTeX output
-#---------------------------------------------------------------------------
-GENERATE_LATEX         = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the RTF output
-#---------------------------------------------------------------------------
-GENERATE_RTF           = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the man page output
-#---------------------------------------------------------------------------
-GENERATE_MAN           = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the XML output
-#---------------------------------------------------------------------------
-GENERATE_XML           = NO

DELETED 3rd_party/threadpool/libs/threadpool/doc/examples.txt
Index: 3rd_party/threadpool/libs/threadpool/doc/examples.txt
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/examples.txt
+++ 3rd_party/threadpool/libs/threadpool/doc/examples.txt
@@ -1,14 +0,0 @@
-
-/*! \page intro TODO3
-
-See src/examples/mergesort/mergesort.cpp
-<BR>
-
- */
-
-
-/*! \page pattern TODO4
-TODO4
-
- */
-

DELETED 3rd_party/threadpool/libs/threadpool/doc/examples_header.htm
Index: 3rd_party/threadpool/libs/threadpool/doc/examples_header.htm
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/examples_header.htm
+++ 3rd_party/threadpool/libs/threadpool/doc/examples_header.htm
@@ -1,38 +0,0 @@
-<HTML>
-  <HEAD>
-    <TITLE>threadpool Documentation</TITLE>
-    <LINK HREF="threadpool.css" REL="stylesheet" TYPE="text/css">
-  </HEAD>
-  <BODY BGCOLOR="#FFFFFF">
-
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-
-          <TD ALIGN="LEFT">
-            <B>$projectname</B>
-          </TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="../index.html">Overview</A> |
-            <A CLASS="qindex" HREF="../reference/annotated.html">Reference</A> |
-            <A CLASS="qindex" HREF="../tutorial/intro.html">Tutorial</A> |
-            <A CLASS="qindex" HREF="../examples/intro.html">Examples</A> |
-            <A CLASS="qindex" HREF="../design/intro.html">Design</A>
-          </TD>
-
-        </TR>
-      </TABLE>
-    </DIV>
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-          <TD ALIGN="LEFT">
-            <B>Examples</B>
-          </TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="intro.html">TODO3</A> |
-            <A CLASS="qindex" HREF="pattern.html">TODO4</A>
-          </TD>
-        </TR>
-      </TABLE>
-    </DIV>

DELETED 3rd_party/threadpool/libs/threadpool/doc/footer/common_footer.htm
Index: 3rd_party/threadpool/libs/threadpool/doc/footer/common_footer.htm
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/footer/common_footer.htm
+++ 3rd_party/threadpool/libs/threadpool/doc/footer/common_footer.htm
@@ -1,17 +0,0 @@
-    <BR>
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-		  <TD CLASS="tiny" ALIGN="LEFT">Copyright &copy 2005-2008 Philipp Henkel</TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="../index.html">Overview</A> |
-            <A CLASS="qindex" HREF="../reference/annotated.html">Reference</A> |
-            <A CLASS="qindex" HREF="../tutorial/intro.html">Tutorial</A> |
-            <A CLASS="qindex" HREF="../examples/intro.html">Examples</A> |
-            <A CLASS="qindex" HREF="../design/intro.html">Design</A>
-          </TD>
-        </TR>       
-      </TABLE>
-    </DIV>  
-  </BODY>
-</HTML>

DELETED 3rd_party/threadpool/libs/threadpool/doc/footer/overview_footer.htm
Index: 3rd_party/threadpool/libs/threadpool/doc/footer/overview_footer.htm
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/footer/overview_footer.htm
+++ 3rd_party/threadpool/libs/threadpool/doc/footer/overview_footer.htm
@@ -1,17 +0,0 @@
-    <BR>
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-          <TD CLASS="tiny" ALIGN="LEFT">Copyright &copy 2005-2008 Philipp Henkel</TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="index.html">Overview</A> |
-            <A CLASS="qindex" HREF="reference/annotated.html">Reference</A> |
-            <A CLASS="qindex" HREF="tutorial/intro.html">Tutorial</A> |
-            <A CLASS="qindex" HREF="examples/intro.html">Examples</A> |
-            <A CLASS="qindex" HREF="design/intro.html">Design</A>
-          </TD>
-        </TR>
-      </TABLE>
-    </DIV>
-  </BODY>
-</HTML>

DELETED 3rd_party/threadpool/libs/threadpool/doc/footer_sf/common_footer.htm
Index: 3rd_party/threadpool/libs/threadpool/doc/footer_sf/common_footer.htm
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/footer_sf/common_footer.htm
+++ 3rd_party/threadpool/libs/threadpool/doc/footer_sf/common_footer.htm
@@ -1,30 +0,0 @@
-    <BR>
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-		  <TD CLASS="tiny" ALIGN="LEFT">Copyright &copy 2005-2008 Philipp Henkel</TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="../index.html">Overview</A> |
-            <A CLASS="qindex" HREF="../reference/annotated.html">Reference</A> |
-            <A CLASS="qindex" HREF="../tutorial/intro.html">Tutorial</A> |
-            <A CLASS="qindex" HREF="../examples/intro.html">Examples</A> |
-            <A CLASS="qindex" HREF="../design/intro.html">Design</A>
-          </TD>
-        </TR>       
-      </TABLE>
-    </DIV>
-    
-    <P align="right" valign="top">
-      Hosted by
-      <A HREF="http://sourceforge.net">
-        <IMG src="http://sflogo.sourceforge.net/sflogo.php?group_id=158064&type=2" 
-             width="125" 
-             height="37" 
-             border="0" 
-             align="top"
-             alt="SourceForge.net Logo"/>
-      </A>
-    </P>    
-    
-  </BODY>
-</HTML>

DELETED 3rd_party/threadpool/libs/threadpool/doc/footer_sf/overview_footer.htm
Index: 3rd_party/threadpool/libs/threadpool/doc/footer_sf/overview_footer.htm
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/footer_sf/overview_footer.htm
+++ 3rd_party/threadpool/libs/threadpool/doc/footer_sf/overview_footer.htm
@@ -1,29 +0,0 @@
-    <BR>
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-          <TD CLASS="tiny" ALIGN="LEFT">Copyright &copy 2005-2008 Philipp Henkel</TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="index.html">Overview</A> |
-            <A CLASS="qindex" HREF="reference/annotated.html">Reference</A> |
-            <A CLASS="qindex" HREF="tutorial/intro.html">Tutorial</A> |
-            <A CLASS="qindex" HREF="examples/intro.html">Examples</A> |
-            <A CLASS="qindex" HREF="design/intro.html">Design</A>
-          </TD>
-        </TR>
-      </TABLE>
-    </DIV>
-  
-    <P align="right" valign="top">
-      Hosted by
-      <A HREF="http://sourceforge.net">
-        <IMG src="http://sflogo.sourceforge.net/sflogo.php?group_id=158064&type=2" 
-             width="125" 
-             height="37" 
-             border="0" 
-             align="top"
-             alt="SourceForge.net Logo"/>
-      </A>
-    </P>
-  </BODY>
-</HTML>

DELETED 3rd_party/threadpool/libs/threadpool/doc/index.html
Index: 3rd_party/threadpool/libs/threadpool/doc/index.html
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/index.html
+++ 3rd_party/threadpool/libs/threadpool/doc/index.html
@@ -1,9 +0,0 @@
-<HTML>
-  <HEAD>
-    <TITLE>threadpool Documentation</TITLE>
-    <meta http-equiv="refresh" content="2;url=overview/index.html">
-  </HEAD>
-  <BODY BGCOLOR="#FFFFFF">
-
-  </BODY>
-</HTML>

DELETED 3rd_party/threadpool/libs/threadpool/doc/overview.dox
Index: 3rd_party/threadpool/libs/threadpool/doc/overview.dox
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/overview.dox
+++ 3rd_party/threadpool/libs/threadpool/doc/overview.dox
@@ -1,145 +0,0 @@
-#---------------------------------------------------------------------------
-# Project related configuration options
-#---------------------------------------------------------------------------
-PROJECT_NAME           = "threadpool"
-PROJECT_NUMBER         = 0.2.5
-OUTPUT_DIRECTORY       = ../../../doc
-CREATE_SUBDIRS         = NO
-OUTPUT_LANGUAGE        = English
-USE_WINDOWS_ENCODING   = NO
-BRIEF_MEMBER_DESC      = NO
-REPEAT_BRIEF           = NO
-ALWAYS_DETAILED_SEC    = YES
-INLINE_INHERITED_MEMB  = YES
-FULL_PATH_NAMES        = YES
-STRIP_FROM_PATH        = /../../../boost/threadpool
-STRIP_FROM_INC_PATH    = 
-SHORT_NAMES            = YES
-JAVADOC_AUTOBRIEF      = NO
-MULTILINE_CPP_IS_BRIEF = YES
-DETAILS_AT_TOP         = YES
-INHERIT_DOCS           = YES
-DISTRIBUTE_GROUP_DOC   = NO
-SEPARATE_MEMBER_PAGES  = NO
-TAB_SIZE               = 2
-ALIASES                = 
-OPTIMIZE_OUTPUT_FOR_C  = NO
-OPTIMIZE_OUTPUT_JAVA   = NO
-SUBGROUPING            = YES
-
-#---------------------------------------------------------------------------
-# Build related configuration options
-#---------------------------------------------------------------------------
-EXTRACT_ALL            = NO
-EXTRACT_PRIVATE        = NO
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DELETED 3rd_party/threadpool/libs/threadpool/doc/overview.txt
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==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/overview.txt
+++ 3rd_party/threadpool/libs/threadpool/doc/overview.txt
@@ -1,205 +0,0 @@
-/*! \mainpage threadpool
-
-
-\section intro_sec threadpool
-threadpool is a cross-platform C++ thread pool library. In general terms thread pools
-are an efficient mechanism for asynchronous task processing within the same process. 
-They realise the <A HREF="design/pattern.html"> thread pool pattern</A>.
-
-A thread pool manages a group of threads in order to process a large number of tasks. 
-Since multiple threads can be executed in parallel this approach may be very efficient regarding the overall program performance on many computer systems. By restricting the number of threads and by reusing them resources are saved 
-and additionally the system stability is increased.
-
-The threadpool library provides a convenient way for dispatching asynchronous tasks. Pools can be customized, managed dynamically and easily integrated into your software.
-
-
-\section dev_status_sec Development Status & Future Work
-The threadpool core classes are completed and the implemenation can be considered ready for production code. The library is used by several commercial server applications and can handle high workload without problems. I'm currently working on helper and service classes which make the 
-usage of the pool more comfortable. A small tutorial introduces the thread pool and 
-more example code will be added in the future. The documentation is far away from being finished.
-<BR>
-<BR><A HREF="http://threadpool.cvs.sourceforge.net/threadpool/threadpool">Browse CVS Repository</A>
-<BR>
-
-<P>
-Features
-- Policy-based thread pool implementation<BR>
-- Scheduling policies: fifo, lifo and priority<BR>
-- Size policies: static_size<BR>
-- Size policy controller: empty_controller, resize_controller<BR>
-- Shutdown policies: wait_for_all_tasks, wait_for_active_tasks, immediately<BR>
-- Smooth integration into STL and boost<BR>
-</P>
-
-<P>
-Future Work
-- More policies: deadline_scheduler, ...<BR>
-- Possibility of limiting the number of pending tasks<BR>
-- Futures (handles to results of scheduled functions)<BR>
-- More examples to illustrate the usage of the library<BR>
-- Provide Unit tests<BR>
-</P>
-
-
-
-
-\section down_sec Download Section
-<P>
-threadpool 0.2.5 (Development Snapshot)
-- <A HREF="http://prdownloads.sourceforge.net/threadpool/threadpool-0_2_5-src.zip?download">threadpool-0_2_5-src.zip</A><BR>
-- <A HREF="http://prdownloads.sourceforge.net/threadpool/threadpool-0_2_5-doc.zip?download">threadpool-0_2_5-doc.zip</A><BR>
-</P>
-
-For more information on the revisions see \ref changelog.
-
-
-\section  platforms_sec Supported Platforms
-threadpool is highly portable. It runs on any platform on which Boost threads are available: Linux, Windows, Mac OS 9/X, Solaris, etc.
-
-
-\section boost_sec Boost Libraries
-Boost is a collection of high-quality C++ libraries and works on almost any
-modern operating system, including UNIX and Windows variants. 
-In fact threadpool is only a small extension to the portable Boost source libraries. 
-It incorporates the thread pool concept by using the thread library from William Kempf.
-For more information on this excellent library visit <A HREF="http://www.boost.org">Boost.org</A>.
-
-
-\section installation_sec Installing & Using threadpool
-threadpool consists only of header files, and so there is no need to build the library itself 
-before using it in your own applications. You simply need to add the 
-following directories to your compiler include path:<BR>
-    - threadpool's include directory<BR>
-    - the boost directory (e.g. the one called boost_1_37_0)<BR>
-
-Furthermore you have to compile boost's thread library and link against it (libboost_thread-*.lib under Windows).
-
-
-
-\section license_sec Software License
-threadpool is released under the \ref license "Boost Software License". 
-This license encourages both commercial and non-commercial use.
-
-
-\section acknowledgments_sec Acknowledgments
-This library was written by Philipp Henkel.
-<P>
-I appreciate your suggestions, and would love to know if you 
-use threadpool. Hopefully you will enjoy it and find it useful. 
-Please post questions, comments, bugs, or contact me at:
-
-</P>
-
-threadpool@googlemail.com<BR>
-or<BR>
-<A HREF="http://www.sourceforge.net/projects/threadpool">www.sourceforge.net/projects/threadpool</A>
-<BR>
-<BR>
-*/
-
-
-
-/*! \page license Software License
-
-\verbinclude LICENSE_1_0.txt 
-
-*/
- 
- 
- 
- /*! \page changelog Change Log
-
- <B>0.2.5 (Stable)</B>
-  - Made threadpool compatible to boost::thread 1.37
-  - Fixed hang problem in shutdown method (Thanks to Sohail Somani)
-  - Adapted repository layout to boost (Thanks to Alex Ott)
- 
-<B>0.2.4 (Stable)</B>
-  - Made threadpool compatible to boost::thread 1.35.x code base
-  - Fixed compiler warning in scope_guard.hpp
- 
-<B>0.2.4 (Stable)</B>
-  - Made threadpool compatible to boost::thread 1.35.x code base
-  - Fixed compiler warning in scope_guard.hpp
-
-<B>0.2.3 (Development)</B>
-  - Implemented workaround for Sun C++ Pro compiler bug in pool_core
-  - Removed subtask implementation (there was no demand for this feature)
-  - Improved shutdown policies
-  
-<B>0.2.2 (Development)</B>
-  - Refactored SizePolicy and added SizePolicyController
-  - Moved policies into separate files
-  - Fixed some compiler problems (GCC)
-  - Implemented size_controller handling
-  - Implemented two size policies: static_size and fixed_size
-  - Refactored worker_thread handling, moved policies from pool_core to pool
-  - Specialized schedule function for usage with futures
-  - Added compile test project
-  - Improved constness in pool core class
-  - Fixed timed wait
-  - Implemented futures (in progress)
-  - Added result_type to all functors
-
-<B>0.2.1 (Development)</B>
-  - Pool base class (thread_pool) has now reference semantics.
-  - Large refactorings: Removed scoped_pool, reimplemented worker (now worker_thread)
-  - Fixed odd resize behaviour. Now resize changes the number of threads immediately.
-  - Apply pimpl idiom on pool core class (to make the ugly scoped_pool class needless)
-  - Introduced scheduling policies
-  - Switched to policy-based design (PBD), inspired by Scott Meyers C++ workshop
-  - Cosmetic code change: Replaced keyword 'class' with 'typename' in template definitions
-  - Revised tutorials
-  - New requirements: tasks functions should not and schedulers shall not throw exceptions
-  
-<B>0.2.0 (Development)</B>
-  - Moved threadpool into the boost namespace: boost::threadpool
-  - Used keyword volatile to indicate thread-safe member functions
-  - Used volatile on primitve types were appropriate
-  - Moved worker to detail directory
-  - Fixed thread deletion
-  - Extended wait functionality (waiting for idle threads was implemented)
-  - Renamed 'join()' to 'wait()' as 'join' indicates the termination of thread. That was not the case in pool::join.
-  - Changed internal container of lifo and fifo schedulers to improve efficiency.
-  - Improved code reference documentation (source code browser)
-  - Renamed thread_func into task_func
-  - Added += operator to scoped_pool to ease scheduling of tasks
-  - Refactored file structures and class names
-  - Added a new task concept (named subtask) which allows the combination of sequential and parallel execution
-  - Added new task adaptor for looped or timed tasks: looped_task_func
-  - Introduced function clear() which can be used to remove all tasks from the pool and schedulers
-  - New function pool::active() which returns the number of active tasks
-
-<B>0.1.8 (Development)</B>
-  - Fixed some compile errors which were reported by gcc
-  - Wrote tutorial "Prioritized Tasks"
-
-<B>0.1.7 (Development)</B>
-  - Added Visual Studio 2005 project files for tutorial and examples
-
-<B>0.1.6 (Development)</B>
-  - Replaced task adaptor 'task' with boost::bind
-  - Workers are unregistered from thread_group when they are terminated
-  - Working on example boost::iostreams packet_filter
-
-<B>0.1.5 (Development)</B>
-  - Finished threadpool reference
-  - Class pool_adaptor was replaced by smart_pool
-  - Minor pool improvements
-  - First tutorial page online 
-
-<B>0.1.4 (Development)</B>
-  - Created the pool's homepage: http://threadpool.sourceforge.net
-  - Improved documentation
-  - Added build scripts
-
-<B>0.1.3 (Development)</B>
-  - First public release
-  - Added mergesort example
-  - Added tutorial 
-  - Implementation of threadpool core and related classes
-
- */
-
-
-

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DELETED 3rd_party/threadpool/libs/threadpool/doc/tutorial.dox
Index: 3rd_party/threadpool/libs/threadpool/doc/tutorial.dox
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/tutorial.dox
+++ 3rd_party/threadpool/libs/threadpool/doc/tutorial.dox
@@ -1,145 +0,0 @@
-#---------------------------------------------------------------------------
-# Project related configuration options
-#---------------------------------------------------------------------------
-PROJECT_NAME           = "threadpool"
-PROJECT_NUMBER         = 
-OUTPUT_DIRECTORY       = ../../../doc/tutorial
-CREATE_SUBDIRS         = NO
-OUTPUT_LANGUAGE        = English
-USE_WINDOWS_ENCODING   = NO
-BRIEF_MEMBER_DESC      = NO
-REPEAT_BRIEF           = NO
-ALWAYS_DETAILED_SEC    = YES
-INLINE_INHERITED_MEMB  = YES
-FULL_PATH_NAMES        = YES
-STRIP_FROM_PATH        = /../../include/
-STRIP_FROM_INC_PATH    = 
-SHORT_NAMES            = YES
-JAVADOC_AUTOBRIEF      = NO
-MULTILINE_CPP_IS_BRIEF = YES
-DETAILS_AT_TOP         = YES
-INHERIT_DOCS           = YES
-DISTRIBUTE_GROUP_DOC   = NO
-SEPARATE_MEMBER_PAGES  = NO
-TAB_SIZE               = 2
-ALIASES                = 
-OPTIMIZE_OUTPUT_FOR_C  = NO
-OPTIMIZE_OUTPUT_JAVA   = NO
-SUBGROUPING            = YES
-
-#---------------------------------------------------------------------------
-# Build related configuration options
-#---------------------------------------------------------------------------
-EXTRACT_ALL            = NO
-EXTRACT_PRIVATE        = NO
-EXTRACT_STATIC         = NO
-EXTRACT_LOCAL_CLASSES  = NO
-EXTRACT_LOCAL_METHODS  = NO
-HIDE_UNDOC_MEMBERS     = YES
-HIDE_UNDOC_CLASSES     = YES
-HIDE_FRIEND_COMPOUNDS  = NO
-HIDE_IN_BODY_DOCS      = NO
-INTERNAL_DOCS          = NO
-CASE_SENSE_NAMES       = YES
-HIDE_SCOPE_NAMES       = NO
-SHOW_INCLUDE_FILES     = NO
-INLINE_INFO            = NO
-SORT_MEMBER_DOCS       = NO
-SORT_BRIEF_DOCS        = NO
-SORT_BY_SCOPE_NAME     = NO
-GENERATE_TODOLIST      = NO
-GENERATE_TESTLIST      = NO
-GENERATE_BUGLIST       = NO
-GENERATE_DEPRECATEDLIST= NO
-ENABLED_SECTIONS       = 
-MAX_INITIALIZER_LINES  = 30
-SHOW_USED_FILES        = NO
-SHOW_DIRECTORIES       = NO
-FILE_VERSION_FILTER    = 
-
-#---------------------------------------------------------------------------
-# configuration options related to warning and progress messages
-#---------------------------------------------------------------------------
-QUIET                  = NO
-WARNINGS               = YES
-WARN_IF_UNDOCUMENTED   = YES
-WARN_IF_DOC_ERROR      = YES
-WARN_NO_PARAMDOC       = NO
-WARN_FORMAT            = "$file:$line: $text"
-WARN_LOGFILE           = 
-
-#---------------------------------------------------------------------------
-# configuration options related to the input files
-#---------------------------------------------------------------------------
-INPUT                  = tutorial.txt
-FILE_PATTERNS          = 
-RECURSIVE              = NO
-EXCLUDE                = 
-EXCLUDE_SYMLINKS       = NO
-EXCLUDE_PATTERNS       = 
-EXAMPLE_PATH           =
-EXAMPLE_PATTERNS       = 
-EXAMPLE_RECURSIVE      = YES
-IMAGE_PATH             = 
-INPUT_FILTER           = 
-FILTER_PATTERNS        = 
-FILTER_SOURCE_FILES    = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to source browsing
-#---------------------------------------------------------------------------
-SOURCE_BROWSER         = NO
-INLINE_SOURCES         = NO
-STRIP_CODE_COMMENTS    = YES
-REFERENCED_BY_RELATION = NO
-REFERENCES_RELATION    = NO
-VERBATIM_HEADERS       = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the alphabetical class index
-#---------------------------------------------------------------------------
-ALPHABETICAL_INDEX     = NO
-COLS_IN_ALPHA_INDEX    = 1
-IGNORE_PREFIX          = 
-
-#---------------------------------------------------------------------------
-# configuration options related to the HTML output
-#---------------------------------------------------------------------------
-GENERATE_HTML          = YES
-HTML_OUTPUT            = .
-HTML_FILE_EXTENSION    = .html
-HTML_HEADER            = tutorial_header.htm
-HTML_FOOTER            = common_footer.htm
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-
-
-#---------------------------------------------------------------------------
-# configuration options related to the LaTeX output
-#---------------------------------------------------------------------------
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-
-#---------------------------------------------------------------------------
-# configuration options related to the RTF output
-#---------------------------------------------------------------------------
-GENERATE_RTF           = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the man page output
-#---------------------------------------------------------------------------
-GENERATE_MAN           = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the XML output
-#---------------------------------------------------------------------------
-GENERATE_XML           = NO

DELETED 3rd_party/threadpool/libs/threadpool/doc/tutorial.txt
Index: 3rd_party/threadpool/libs/threadpool/doc/tutorial.txt
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/tutorial.txt
+++ 3rd_party/threadpool/libs/threadpool/doc/tutorial.txt
@@ -1,207 +0,0 @@
-/*! \page intro Quick Start
-
-This tutorial introduces the threadpool library by discussing an easy to understand source listing:
-
-\code
-01 
-02  #include "threadpool.hpp"
-03
-04  using namespace boost::threadpool;
-05
-06  // Some example tasks
-07  void first_task()
-08  {
-09    ...
-10  }
-11
-13  void second_task()
-14  {
-15    ...
-16  }
-17
-19  void third_task()
-20  {
-21    ...
-22  }
-23  
-24  void execute_with_threadpool()
-25  {
-26    // Create a thread pool.
-27    pool tp(2);
-28    
-29    // Add some tasks to the pool.
-30    tp.schedule(&first_task);
-31    tp.schedule(&second_task);
-32    tp.schedule(&third_task);
-33
-34    // Leave this function and wait until all tasks are finished.
-35  }
-36
-\endcode
-
-We start by including the necessary header files. The complete threadpool functionality can be used by simply including 
-the "threadpool.hpp" header file at line 2. 
-
-The three functions first_task(), second_task and third_task() are placeholders 
-for tasks that should be executed by our pool. 
-
-The thread pool is created at line 27. The argument indicates the number of initial threads.
-The new pool contains two threads that is two tasks can be processed in parallel. The pool's threads 
-are sleeping until tasks are added.
-By default it uses a Fifo scheduling strategy. 
-Fifo is an abbreviation of "first in, first out"
-and means in this case that the first task which is added is the
-first that will be executed. Generally this is the expected default behaviour
-since the tasks are executed in the order they are added to the pool. 
-
-In line 30 to 32 the task functions are scheduled asynchronously using the pool's schedule function.
-A task is registered and it will be executed as soon as one of the pool's threads is idle.   
-It is very important to understand that the task is only scheduled for execution.
-Schedule returns immediately and there are no guarantees about when the tasks are executed and how long 
-the processing will take. As they are added to a fifo pool with two threads the following is true: 
-- the execution of first_task begins first
-- second_task is started after first_task
-- third_task is begun at last
-- a maximum of two tasks may are processed in parallel
-- each scheduled task will be executed once only
-
-
-The pool reference tp is created in the scope of the function execute_with_threadpool(). When this 
-function returns at line 35 tp goes out of scope and the pool will be destructed. As the default ShutdownPolicy 
-is wait_for_all_tasks it is ensured that all tasks are processed before the pool is destroyed.
-
-\code
-101  
-102  ...
-103  execute_with_threadpool();  // execute first_task, second_task and third_task
-104  // When this line is reached all tasks are finished and the pool is destructed.   
-105  
-\endcode
-
-The small code example clarifies the issue. When the function leaves the pool is shut down
-and waits for the tasks. That means the current thread of execution is blocked 
-at the end of the execute_with_threadpool as long as
-the processing of tasks is in progress.
-
-<BR>
-*/
-
-
-/*! \page prioritized Prioritized Tasks
-
-TODO This tutorial is out dated.
-
-It's easy to prioritize asynchronous tasks by using the task adaptor prio_task_func. 
-The following source listing illustrates how to setup the pool and add the tasks:
-
-\code
-01 
-02  #include "threadpool.hpp"
-03
-04  using namespace boost::threadpool;
-05
-06  // Some example tasks
-07  void normal_task()
-08  {
-09    ...
-10  }
-11
-13  void important_task()
-14  {
-15    ...
-16  }
-17  
-18  void execute_prioritized()
-19  {
-20    // Create prioritized thread pool container without any threads.
-21    scoped_pool<prio_pool, 0> tp;
-22
-23    // Add some tasks to the pool.
-24    tp += prio_task_func(5,   &normal_task);
-25    tp += prio_task_func(100, &important_task);
-26    tp += prio_task_func(7,   &normal_task);
-27
-28    // Add the some threads to the pool. This will start the execution of the tasks.
-29    tp->resize(2);
-30
-31    // The tasks are processed according to their priority: important_task(100), nonrelevant_task(7), nonrelevant_task(5).
-32
-33    tp->wait();
-34    
-35    // Now all tasks are finished and the pool will be destroyed safely when tp goes out of scope.
-36  }
-37
-\endcode
-
-Like in the first tutorial we start including the main header file and defining some tasks.
-
-At line 21 a prioritized thread pool is created. That means that the pool's tasks are arranged 
-according to their priority before they get executed. Therefore the tasks themselves have to realize a partial ordering based 
-on operator<. 
-
-The adaptor prio_thread_func satisfies our requirements regarding the order and is just a small wrapper object for 
-the task functions. In line 24 to 26 some prioritized tasks are scheduled. This time the pool's schedule function is used and like smart pool's += operator 
-this function returns immediately.
-
-At line 29 the first thread is added to the pool and the execution of important_task begins. As we have only one thread 
-the tasks are processed sequentially.
-
-Finally wait() is called to ensure that all tasks are finished before our example function returns 
-and the pool is destroyed. This is very important since the behavior is undefined if pool's lifetime ends while tasks are executed.
-
-*/
-
-
-/*! \page task_adaptor Arbitrary Task Functions
-
-TODO This tutorial is out dated.
-
-
-\section member_task Member Task Functions
-
-using namespace boost::threadpool;
-
-TODO <BR>
-boost::bind(member_function, shared_ptr)
-26    tp->schedule(boost::bind(task_with_parameter, 42));
-12  // Second example task
-13  void task_with_parameter(int value)
-14  {
-15    ...
-16  }
-
-\section member_task Functions With Arguments
-
-*/
-
- 
-/*! \page instantiation Advanced Instantiation
-
-TODO This tutorial is out dated.
-
-TODO <BR>
-Pool instantiation
-\code
-
-    boost::shared_ptr<fifo_pool> tp = fifo_pool::create_pool(5);			
-
-    print("  Add tasks ...\n");
-    tp->schedule(&task_1);
-    tp->schedule(&task_2);
-    tp->schedule(&task_3);
-
-    tp->schedule(looped_task_func(&looped_task, 1500));
-
-    print("  Wait until all tasks are finished ...\n");
-    tp->wait();
-    print("  Tasks finished!\n");
-	
-\endcode
-
-
-\code
-    typedef threadpool::pool<boost::function0<void>, threadpool::fifo_scheduler<boost::function0<void> > > pool_type;
-    boost::shared_ptr< pool_type > tp = pool_type::create_pool(5);			
-\endcode
-
-*/

DELETED 3rd_party/threadpool/libs/threadpool/doc/tutorial_header.htm
Index: 3rd_party/threadpool/libs/threadpool/doc/tutorial_header.htm
==================================================================
--- 3rd_party/threadpool/libs/threadpool/doc/tutorial_header.htm
+++ 3rd_party/threadpool/libs/threadpool/doc/tutorial_header.htm
@@ -1,40 +0,0 @@
-<HTML>
-  <HEAD>
-    <TITLE>threadpool Documentation</TITLE>
-    <LINK HREF="threadpool.css" REL="stylesheet" TYPE="text/css">
-  </HEAD>
-  <BODY BGCOLOR="#FFFFFF">
-
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-
-          <TD ALIGN="LEFT">
-            <B>$projectname</B>
-          </TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="../index.html">Overview</A> |
-            <A CLASS="qindex" HREF="../reference/annotated.html">Reference</A> |
-            <A CLASS="qindex" HREF="../tutorial/intro.html">Tutorial</A> |
-            <A CLASS="qindex" HREF="../examples/intro.html">Examples</A> |
-            <A CLASS="qindex" HREF="../design/intro.html">Design</A>
-          </TD>
-
-        </TR>
-      </TABLE>
-    </DIV>
-    <DIV CLASS="qindex">
-      <TABLE BORDER="0" WIDTH="100%">
-        <TR>
-          <TD ALIGN="LEFT">
-            <B>Tutorial</B>
-          </TD>
-          <TD ALIGN="RIGHT">
-            <A CLASS="qindex" HREF="intro.html">Quick Start</A> |
-            <A CLASS="qindex" HREF="prioritized.html">Prioritized Tasks</A> |
-            <A CLASS="qindex" HREF="task_adaptor.html">Arbitrary Task Functions</A> |
-            <A CLASS="qindex" HREF="instantiation.html">Advanced Pool Instantiation</A>            
-          </TD>
-        </TR>
-      </TABLE>
-    </DIV>

DELETED 3rd_party/threadpool/libs/threadpool/example/mergesort/Jamfile.v2
Index: 3rd_party/threadpool/libs/threadpool/example/mergesort/Jamfile.v2
==================================================================
--- 3rd_party/threadpool/libs/threadpool/example/mergesort/Jamfile.v2
+++ 3rd_party/threadpool/libs/threadpool/example/mergesort/Jamfile.v2
@@ -1,11 +0,0 @@
-
-project
-  : requirements
-    <include>../../../..
-    <library>/boost/thread//boost_thread
-    <define>BOOST_ALL_NO_LIB=1
-    <threading>multi
-	<link>static
-  ;
-
-exe mergesort : mergesort.cpp ;

DELETED 3rd_party/threadpool/libs/threadpool/example/mergesort/mergesort.cpp
Index: 3rd_party/threadpool/libs/threadpool/example/mergesort/mergesort.cpp
==================================================================
--- 3rd_party/threadpool/libs/threadpool/example/mergesort/mergesort.cpp
+++ 3rd_party/threadpool/libs/threadpool/example/mergesort/mergesort.cpp
@@ -1,200 +0,0 @@
-/*! \file
- * \brief Mergesort example.
- *
- * This example shows how to use the threadpool library. 
- *
- * Copyright (c) 2005-2006 Philipp Henkel
- *
- * Distributed under the Boost Software License, Version 1.0. (See
- * accompanying file LICENSE_1_0.txt or copy at
- * http://www.boost.org/LICENSE_1_0.txt)
- *
- * http://threadpool.sourceforge.net
- *
- */
-
-
-#include <boost/threadpool.hpp>
-#include <boost/thread/mutex.hpp>
-#include <boost/smart_ptr.hpp>
-#include <iostream>
-#include <sstream>
-#include <algorithm>
-
-
-
-using namespace std;
-using namespace boost::threadpool;
-
-//
-// Helpers
-boost::mutex m_io_monitor;
-
-void print(string text)
-{
-  boost::mutex::scoped_lock lock(m_io_monitor);
-  cout << text;
-}
-
-template<class T>
-string to_string(const T& value)
-{
-  ostringstream ost;
-  ost << value;
-  ost.flush();
-  return ost.str();
-}
-
-unsigned long get_ms_diff(boost::xtime& start, boost::xtime& end)
-{
-  boost::xtime::xtime_sec_t start_ms = start.sec * 1000	+ start.nsec/1000000; 
-  boost::xtime::xtime_sec_t end_ms = end.sec * 1000	+ end.nsec/1000000; 
-  return static_cast<unsigned long>(end_ms - start_ms);
-}
-
-class image
-{
-public:
-  image() : m_content(0)	{}
-  image(int content) : m_content(content)	{}
-
-  image(const image& src)
-  {
-    m_content = src.m_content;
-  }
-
-  bool operator<(const image& l) const
-  {
-    {	// simulate time needed for image comparision
-      boost::xtime xt;
-      boost::xtime_get(&xt, boost::TIME_UTC);
-      int duration = 1+(m_content % 4);
-      xt.nsec += 250 * 1000 * duration;	
-      boost::thread::sleep(xt); 
-	    print(".");
-    }	
-    return m_content < l.m_content;
-  }
-
-protected:
-  int m_content;	// represents image data in this example
-};
-
-
-template<class T>
-class merge_job
-{
-public:
-  merge_job(boost::shared_array<T> data, unsigned int position, unsigned int length) 
-    : m_data(data)
-    , m_position(position)
-    , m_length(length) 
-  {
-    print("merge job created : " + to_string(m_position) +", "+ to_string(m_length) +"\n");
-  }
-
-  void run()
-  {	
-    print("merge job running :   " + to_string(m_position) +", "+ to_string(m_length) +"\n");
-
-    T* begin = m_data.get();
-    std::advance(begin, m_position);
-
-    T* mid = m_data.get();
-    std::advance(mid, m_position + m_length/2);
-
-    T* end = m_data.get();
-    std::advance(end, m_position + m_length);
-
-    std::inplace_merge(begin, mid, end);
-
-    print("\nmerge job finished:     "  + to_string(m_position) +", "+ to_string(m_length) +"\n");
-  }
-
-protected:
-  boost::shared_array<T> m_data;
-  unsigned int m_position;
-  unsigned int m_length;
-};
-
-
-
-
-//
-// A demonstration of the thread_pool class
-int main (int argc, char * const argv[]) 
-{
-  print("MAIN: construct thread pool\n");
-
-		
-
-  boost::xtime start;
-  boost::xtime_get(&start, boost::TIME_UTC);
-
-  int exponent = 7;
-  int data_len = 1 << exponent;  // = pow(2, exponent) 
-
-  print("MAIN: sort array with "+ to_string(data_len) + " elements.\n");
-
-  boost::shared_array<image> data(new image[data_len]);
-
-  // fill array with arbitrary values (not sorted ascendingly)
-  for(int i = 0; i < data_len; i++)
-  {
-    data[i] = image((data_len - i - 1) % 23);
-  }
-
-
-  /***************************/
-  /* Standard implementation */
-  /***************************/
-
-  pool tp;
-  tp.size_controller().resize(5);	
-
-// merge data array
-  for(int step = 1; step <= exponent; step++)
-  {
-    print("\nMAIN: merge step "+ to_string(step)+"\n");
-
-    // divide array into partitions
-    int partition_size = 1 << step;
-    for(int partition = 0; partition < data_len/partition_size; partition++)
-    {
-      // sort partition
-      boost::shared_ptr<merge_job<image> > job(new merge_job<image>(data, partition*partition_size, partition_size));
-      //tp->schedule(prio_task_func(5, boost::bind(&merge_job<image>::run, job)));
-      schedule(tp, boost::bind(&merge_job<image>::run, job));
-     // schedule(tp, job);
-    }
-    tp.wait();	// wait until all partitions are sorted
-  } 
-
-  boost::xtime end;
-  boost::xtime_get(&end, boost::TIME_UTC);				
-
-  print("\nMAIN: duration " + to_string(get_ms_diff(start, end)) + " ms \n");
-
-  print("\nMAIN: check if array is sorted... \n");
-
-  // check if array is sorted ascendingly 
-  bool ascending = true;
-  for(int i = 0; i < data_len-1; i++)
-  {
-    if(data[i+1] < data[i])
-    {
-      ascending = false;
-    }
-  }
-
-  if(ascending)
-  {
-    print("\nMAIN: array is sorted\n");
-  }
-  else
-  {
-    print("\nMAIN: array is NOT sorted!\n");
-  }
-
-  return 0;
-}

DELETED 3rd_party/threadpool/libs/threadpool/quickstart/Jamfile.v2
Index: 3rd_party/threadpool/libs/threadpool/quickstart/Jamfile.v2
==================================================================
--- 3rd_party/threadpool/libs/threadpool/quickstart/Jamfile.v2
+++ 3rd_party/threadpool/libs/threadpool/quickstart/Jamfile.v2
@@ -1,11 +0,0 @@
-
-project
-  : requirements
-    <include>../../..
-    <library>/boost/thread//boost_thread
-    <define>BOOST_ALL_NO_LIB=1
-    <threading>multi
-	<link>static
-  ;
-
-exe quickstart : quickstart.cpp ;

DELETED 3rd_party/threadpool/libs/threadpool/quickstart/README
Index: 3rd_party/threadpool/libs/threadpool/quickstart/README
==================================================================
--- 3rd_party/threadpool/libs/threadpool/quickstart/README
+++ 3rd_party/threadpool/libs/threadpool/quickstart/README
@@ -1,7 +0,0 @@
-Supposing the boost directory is in /usr/local/lib, it is also worth to mention that they need to 
-set LD_LIBRARY_PATH as follows: 
-export LD_LIBRARY_PATH=$(LD_LIBRARY_PATH):/usr/local/lib
-
-Please adapt threadpool.makefile to your system.
-
-Special thanks to Rudy Prabowo who contributed this example to help linux users.

DELETED 3rd_party/threadpool/libs/threadpool/quickstart/quickstart.cpp
Index: 3rd_party/threadpool/libs/threadpool/quickstart/quickstart.cpp
==================================================================
--- 3rd_party/threadpool/libs/threadpool/quickstart/quickstart.cpp
+++ 3rd_party/threadpool/libs/threadpool/quickstart/quickstart.cpp
@@ -1,50 +0,0 @@
-/*! \file
- * \brief Quick start example.
- *
- * This is a very simple example which can be used to configure the threadpool environment on your system. 
- *
- * Copyright (c) 2005-2006 Philipp Henkel
- *
- * Distributed under the Boost Software License, Version 1.0. (See
- * accompanying file LICENSE_1_0.txt or copy at
- * http://www.boost.org/LICENSE_1_0.txt)
- *
- * http://threadpool.sourceforge.net
- *
- */
-
-#include <iostream>
-
-#include <boost/threadpool.hpp>
-
-using namespace std;
-using namespace boost::threadpool;
-
-// Some example tasks
-void first_task()
-{
-   cout << "first task is running\n" ;
-}
-
-void second_task()
-{
-   cout << "second task is running\n" ;
-}
-
-int main(int argc,char *argv[])
-{
-   // Create fifo thread pool container with two threads.
-   pool tp(2);
-   
-   // Add some tasks to the pool.
-   tp.schedule(&first_task);
-   tp.schedule(&second_task);   
-  
-   //  Wait until all tasks are finished.
-   tp.wait();
-   
-   // Now all tasks are finished!	
-   return(0);
-}
-
-

DELETED 3rd_party/threadpool/libs/threadpool/test/compile_all/Jamfile.v2
Index: 3rd_party/threadpool/libs/threadpool/test/compile_all/Jamfile.v2
==================================================================
--- 3rd_party/threadpool/libs/threadpool/test/compile_all/Jamfile.v2
+++ 3rd_party/threadpool/libs/threadpool/test/compile_all/Jamfile.v2
@@ -1,11 +0,0 @@
-
-project
-  : requirements
-    <include>../../../..
-    <library>/boost/thread//boost_thread
-    <define>BOOST_ALL_NO_LIB=1
-    <threading>multi
-	<link>static
-  ;
-
-exe compile_all : compile_all.cpp ;

DELETED 3rd_party/threadpool/libs/threadpool/test/compile_all/compile_all.cpp
Index: 3rd_party/threadpool/libs/threadpool/test/compile_all/compile_all.cpp
==================================================================
--- 3rd_party/threadpool/libs/threadpool/test/compile_all/compile_all.cpp
+++ 3rd_party/threadpool/libs/threadpool/test/compile_all/compile_all.cpp
@@ -1,149 +0,0 @@
-/*! \file
-* \brief threadpool tutorial.
-*
-* This file contains a tutorial for the threadpool library. 
-*
-* Copyright (c) 2005-2006 Philipp Henkel
-*
-* Distributed under the Boost Software License, Version 1.0. (See
-* accompanying file LICENSE_1_0.txt or copy at
-* http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-
-
-
-#include <iostream>
-#include <sstream>
-#include <boost/thread/mutex.hpp>
-#include <boost/bind.hpp>
-
-#include <boost/threadpool.hpp>
-
-using namespace std;
-using namespace boost::threadpool;
-
-
-//
-// Helpers
-boost::mutex m_io_monitor;
-
-void print(string text)
-{
-  boost::mutex::scoped_lock lock(m_io_monitor);
-  cout << text;
-}
-
-template<typename T>
-string to_string(T const & value)
-{
-  ostringstream ost;
-  ost << value;
-  ost.flush();
-  return ost.str();
-}
-
-
-
-//
-// An example task functions
-void task_1()
-{
-  print("  task_1()\n");
-}
-
-void task_2()
-{
-  print("  task_2()\n");
-}
-
-void task_3()
-{
-  print("  task_3()\n");
-}
-
-int task_4()
-{
-  print("  task_4()\n");
-  return 4;
-}
-
-void task_with_parameter(int value)
-{
-  print("  task_with_parameter(" + to_string(value) + ")\n");
-}
-
-int loops = 0;
-bool looped_task()
-{
-  print("  looped_task()\n");
-  return ++loops < 5; 
-}
-
-
-int task_int()
-{
-  print("  task_int()\n");
-  return 23;
-}
-
-
-void fifo_pool_test()
-{
-    pool tp;
-    
-    tp.schedule(&task_1);
-    tp.schedule(boost::bind(task_with_parameter, 4));
-
-    if(!tp.empty())
-    {
-      tp.clear();  // remove all tasks -> no output in this test
-    }
-
-    size_t active_threads   = tp.active();
-    size_t pending_threads  = tp.pending();
-    size_t total_threads    = tp.size();
-    
-    size_t dummy = active_threads + pending_threads + total_threads;
-    dummy++;
-
-    tp.size_controller().resize(5);
-    tp.wait();
-}
-
-void lifo_pool_test()
-{
-    lifo_pool tp;
-    tp.size_controller().resize(0);
-    schedule(tp, &task_1);
-    tp.size_controller().resize(10);
-    tp.wait();
-}
-
-void prio_pool_test()
-{
-    prio_pool tp(2);
-    schedule(tp, prio_task_func(1, &task_1));
-    schedule(tp, prio_task_func(10,&task_2));
-}
-
-
-void future_test()
-{
-    fifo_pool tp(5);
-    future<int> fut = schedule(tp, &task_4);
-    int res = fut();
-}
-
-
-int main (int , char * const []) 
-{
-  fifo_pool_test();
-  lifo_pool_test();
-  prio_pool_test();
-  future_test();
-  return 0;
-}

DELETED 3rd_party/threadpool/libs/threadpool/tutorial/Jamfile.v2
Index: 3rd_party/threadpool/libs/threadpool/tutorial/Jamfile.v2
==================================================================
--- 3rd_party/threadpool/libs/threadpool/tutorial/Jamfile.v2
+++ 3rd_party/threadpool/libs/threadpool/tutorial/Jamfile.v2
@@ -1,11 +0,0 @@
-
-project
-  : requirements
-    <include>../../..
-    <library>/boost/thread//boost_thread
-    <define>BOOST_ALL_NO_LIB=1
-    <threading>multi
-	<link>static
-  ;
-
-exe tutorial : tutorial.cpp ;

DELETED 3rd_party/threadpool/libs/threadpool/tutorial/tutorial.cpp
Index: 3rd_party/threadpool/libs/threadpool/tutorial/tutorial.cpp
==================================================================
--- 3rd_party/threadpool/libs/threadpool/tutorial/tutorial.cpp
+++ 3rd_party/threadpool/libs/threadpool/tutorial/tutorial.cpp
@@ -1,263 +0,0 @@
-/*! \file
-* \brief threadpool tutorial.
-*
-* This file contains a tutorial for the threadpool library. 
-*
-* Copyright (c) 2005-2007 Philipp Henkel
-*
-* Distributed under the Boost Software License, Version 1.0. (See
-* accompanying file LICENSE_1_0.txt or copy at
-* http://www.boost.org/LICENSE_1_0.txt)
-*
-* http://threadpool.sourceforge.net
-*
-*/
-
-//#define _CRTDBG_MAP_ALLOC
-#include <stdlib.h>
-
-#include <iostream>
-#include <sstream>
-#include <boost/thread/mutex.hpp>
-#include <boost/bind.hpp>
-#include <boost/threadpool.hpp>
-
-using namespace std;
-using namespace boost::threadpool;
-
-//
-// Helpers
-boost::mutex m_io_monitor;
-
-void print(string text)
-{
-  boost::mutex::scoped_lock lock(m_io_monitor);
-  cout << text;
-}
-
-template<typename T>
-string to_string(T const & value)
-{
-  ostringstream ost;
-  ost << value;
-  ost.flush();
-  return ost.str();
-}
-
-
-
-//
-// An example task functions
-void task_1()
-{
-  print("  task_1()\n");
-  throw 5;
-}
-
-void task_2()
-{
-  print("  task_2()\n");
-  throw 5;
-}
-
-void task_3()
-{
-  print("  task_3()\n");
-}
-
-void task_with_parameter(int value)
-{
-  print("  task_with_parameter(" + to_string(value) + ")\n");
-}
-
-int loops = 0;
-bool looped_task()
-{
-  print("  looped_task()\n");
-  return ++loops < 5; 
-}
-
-
-int task_int_23()
-{
-  print("  task_int_23()\n");
-  return 23;
-}
-
-int task_int_1()
-{
-  print("  task_int_1()\n");
-  return 1;
-}
-
-
-class CTest
-{
-  pool m_pool;
-public:
-  CTest()
-    : m_pool(pool(1000))
-  {
-  }
-};
-
-
-//
-// A demonstration of the thread_pool class
-int main (int , char * const []) 
-{
-  print("\nWelcome to the threadpool tutorial!\n");
-
-  print("\n**************************************\n");
-  print("Section 1: Quick Start\n");
-  
-  //void func()
-  {	
-    print("  Create a new thread pool\n");
-    pool tp(2); // tp is handle to the pool
-
-    // Add tasks
-    tp.schedule(&task_1);
-    tp.schedule(&task_2);
-    tp.schedule(&task_3);
-    tp.schedule(boost::bind(task_with_parameter, 4));
-
-    // The pool handle tp is allocated on stack and will 
-    // be destructed if it gets out of scope. Before the 
-    // pool is destroyed it waits for its tasks. 
-    // That means the current thread of execution is 
-    // blocked at the end of the function 
-    // (until all tasks are processed).
-    // while (&tp){int i = 3; ++i;}
-  }	 
-
-  { // Section Futures
-    print("\n**************************************\n");
-    print("Section 1: Futures\n");
-    
-  //typedef thread_pool<task_func, fifo_scheduler, static_size, empty_controller, wait_for_all_tasks> test_pool;
-
-    pool tp;
-
-//    tp.resize(0);
-    tp.pending();
-//    tp.clear();
-    boost::xtime t;
-    tp.wait(t);
-    bool test = tp.empty();
-    if(test) 
-    {
-      test = false;
-    }
-
-    tp.size_controller().resize(2);
-
-    //test_pool::size_controller_type controller = tp.size_controller();
-//    controller.resize(5);
-
-    schedule(tp, &task_int_1);
-    future<int> res = schedule(tp, &task_int_23);
-    future<int> res2 = schedule(tp, &task_int_1);
-
-    res.wait();
-    int value = res.get() + res2.get();
-
-    res.cancel();
-    res.is_cancelled();
-value ++;
-
-//thread_pool<boost::function0<int>, fifo_scheduler> test2332;
-
-//TODO runnable comile test
-  }
-
-
-
-  {	// Section 2
-    print("\n**************************************\n");
-    print("Section 2: Controlling scheduling\n");
-
-    // Create a lifo_pool: last task in, first task out
-    lifo_pool tp(0);
-
-    print("  Add tasks (using the pool's schedule function)\n");	
-    schedule(tp, &task_1);
-    schedule(tp, &task_2);
-    schedule(tp, &task_3);
-
-    // tp.wait();  This would be a deadlock as there are no threads which process the tasks.
-
-    print("  Add some threads ...\n");	
-    tp.size_controller().resize(5);
-
-    print("  Wait until all tasks are finished ...\n");
-    tp.wait();
-    print("  Tasks finished!\n");	
-  }	
-
-
-
-  {	// Section 3:
-    print("\n**************************************\n");
-    print("Section 3: Prioritized Tasks\n");
-
-    prio_pool tp(0);
-
-
-    print("  Add prioritized tasks ...\n");	
-    schedule(tp, prio_task_func(1, &task_1));
-    schedule(tp, prio_task_func(10,&task_2));
-    schedule(tp, prio_task_func(5,&task_3));
-
-    // Tasks are ordered according to their priority: task_2, task_4, task_3, task_1
-
-    print("  Thread added\n");	
-    tp.size_controller().resize(10);
-
-    print("  Wait until all tasks are finished ...\n");
-    tp.wait();
-    print("  Tasks finished!\n");	
-  }		
-
-
-/* */
-  {	// Section 5:
-    print("\n**************************************\n");
-    print("Section 5: Advanced thread pool instantiation\n");
-    // Create the pool directly
-/*
-TODO
-boost::shared_ptr<fifo_pool> tp = fifo_pool::create_pool(5);			
-
-    print("  Add tasks ...\n");
-    tp->schedule(&task_1);
-    tp->schedule(&task_2);
-    tp->schedule(&task_3);
-    tp->schedule(looped_task_func(&looped_task, 1500));
-
-    print("  Wait until all tasks are finished ...\n");
-    tp->wait();
-*/
-  
-    print("  Tasks finished!\n");
-  			
-  }			
-
-
-  print("\n**************************************\n");
-  print("Tutorial finished!\n");
-
-
-
-  {	// Section Compile Tests
-    print("\n**************************************\n");
-    print("Section Compile Tests\n");
-
-
-    fifo_pool tp;
-    tp.size_controller().resize(0);
-    tp.empty(); 
-  }
-
-  return 0;
-}

DELETED 3rd_party/threadpool/project-root.jam
Index: 3rd_party/threadpool/project-root.jam
==================================================================
--- 3rd_party/threadpool/project-root.jam
+++ 3rd_party/threadpool/project-root.jam
@@ -1,2 +0,0 @@
-import os ;
-path-constant BOOST_ROOT : [ os.environ BOOST_ROOT ] ;

Index: 3rd_party/wscript
==================================================================
--- 3rd_party/wscript
+++ 3rd_party/wscript
@@ -1,72 +1,2 @@
-import os
-subdirs = [ 'boost_1_55_0' ]
 def build( bld ):
-	bld.add_subdirs( subdirs )
-	bld(
-		name = 'eigen',
-		export_incdirs = 'eigen',
-		uselib = ''
-	)
-	
-	bld(
-		name = 'threadpool',
-		export_incdirs = 'threadpool',
-		uselib = ''
-	)
-
-#	bld(
-#		features = 'cc cshlib',
-#		target = 'sqlite3',
-#		source = [ 'sqlite3/sqlite3/sqlite3.c' ],
-#		includes = 'sqlite3/',
-#		defines = 'SQLITE_ENABLE_COLUMN_METADATA SQLITE_ENABLE_STAT3',
-#		uselib = 'DL',
-#		export_incdirs = 'sqlite3'
-#	)
-
-	import Options
-	if Options.options.all_targets:
-		bld(
-			features = 'cc cprogram',
-			target = 'sqlite3-qctool',
-			source = [ 'sqlite3/sqlite3/shell.c', 'sqlite3/sqlite3/sqlite3.c', 'sqlite3/extensions/extension-functions.c' ],
-			includes = 'sqlite3/',
-			defines = 'SQLITE_ENABLE_COLUMN_METADATA SQLITE_ENABLE_STAT3 HAVE_READLINE',
-			uselib = 'DL READLINE ZLIB M PTHREAD',
-			cflags = '-O3',
-			export_incdirs = 'sqlite3'
-		)
-
-	bld(
-		features = 'cc cstaticlib',
-		name = 'sqlite3',
-		target = 'sqlite3-qctool',
-		source = [ 'sqlite3/sqlite3/sqlite3.c' ],
-		includes = 'sqlite3/',
-		defines = 'SQLITE_ENABLE_COLUMN_METADATA SQLITE_ENABLE_STAT3',
-		cflags = '-O3',
-		uselib = 'DL',
-		export_incdirs = 'sqlite3'
-	)
-
-	bld(
-		features = 'cc cstaticlib',
-		name = 'zstd',
-		target = 'zstd',
-		source = [
-			'zstd-1.1.0/lib/common/zstd_common.c',
-			'zstd-1.1.0/lib/common/entropy_common.c',
-			'zstd-1.1.0/lib/common/fse_decompress.c',
-			'zstd-1.1.0/lib/common/xxhash.c',
-			'zstd-1.1.0/lib/decompress/huf_decompress.c',
-			'zstd-1.1.0/lib/decompress/zbuff_decompress.c',
-			'zstd-1.1.0/lib/decompress/zstd_decompress.c',
-			'zstd-1.1.0/lib/compress/fse_compress.c',
-			'zstd-1.1.0/lib/compress/huf_compress.c',
-			'zstd-1.1.0/lib/compress/zbuff_compress.c',
-			'zstd-1.1.0/lib/compress/zstd_compress.c'
-		],
-		cflags = '-O3',
-		includes = [ 'zstd-1.1.0/lib', 'zstd-1.1.0/lib/common', 'zstd-1.1.0/lib/compress', 'zstd-1.1.0/lib/decompress' ],
-		export_incdirs = 'zstd-1.1.0/lib/'
-	)
+	bld.recurse( [ 'boost_1_55_0', 'sqlite3', 'zstd-1.1.0', 'eigen', 'catch', 'libdeflate' ] )

ADDED   3rd_party/zlib/CMakeLists.txt
Index: 3rd_party/zlib/CMakeLists.txt
==================================================================
--- 3rd_party/zlib/CMakeLists.txt
+++ 3rd_party/zlib/CMakeLists.txt
@@ -0,0 +1,249 @@
+cmake_minimum_required(VERSION 2.4.4)
+set(CMAKE_ALLOW_LOOSE_LOOP_CONSTRUCTS ON)
+
+project(zlib C)
+
+set(VERSION "1.2.11")
+
+option(ASM686 "Enable building i686 assembly implementation")
+option(AMD64 "Enable building amd64 assembly implementation")
+
+set(INSTALL_BIN_DIR "${CMAKE_INSTALL_PREFIX}/bin" CACHE PATH "Installation directory for executables")
+set(INSTALL_LIB_DIR "${CMAKE_INSTALL_PREFIX}/lib" CACHE PATH "Installation directory for libraries")
+set(INSTALL_INC_DIR "${CMAKE_INSTALL_PREFIX}/include" CACHE PATH "Installation directory for headers")
+set(INSTALL_MAN_DIR "${CMAKE_INSTALL_PREFIX}/share/man" CACHE PATH "Installation directory for manual pages")
+set(INSTALL_PKGCONFIG_DIR "${CMAKE_INSTALL_PREFIX}/share/pkgconfig" CACHE PATH "Installation directory for pkgconfig (.pc) files")
+
+include(CheckTypeSize)
+include(CheckFunctionExists)
+include(CheckIncludeFile)
+include(CheckCSourceCompiles)
+enable_testing()
+
+check_include_file(sys/types.h HAVE_SYS_TYPES_H)
+check_include_file(stdint.h    HAVE_STDINT_H)
+check_include_file(stddef.h    HAVE_STDDEF_H)
+
+#
+# Check to see if we have large file support
+#
+set(CMAKE_REQUIRED_DEFINITIONS -D_LARGEFILE64_SOURCE=1)
+# We add these other definitions here because CheckTypeSize.cmake
+# in CMake 2.4.x does not automatically do so and we want
+# compatibility with CMake 2.4.x.
+if(HAVE_SYS_TYPES_H)
+    list(APPEND CMAKE_REQUIRED_DEFINITIONS -DHAVE_SYS_TYPES_H)
+endif()
+if(HAVE_STDINT_H)
+    list(APPEND CMAKE_REQUIRED_DEFINITIONS -DHAVE_STDINT_H)
+endif()
+if(HAVE_STDDEF_H)
+    list(APPEND CMAKE_REQUIRED_DEFINITIONS -DHAVE_STDDEF_H)
+endif()
+check_type_size(off64_t OFF64_T)
+if(HAVE_OFF64_T)
+   add_definitions(-D_LARGEFILE64_SOURCE=1)
+endif()
+set(CMAKE_REQUIRED_DEFINITIONS) # clear variable
+
+#
+# Check for fseeko
+#
+check_function_exists(fseeko HAVE_FSEEKO)
+if(NOT HAVE_FSEEKO)
+    add_definitions(-DNO_FSEEKO)
+endif()
+
+#
+# Check for unistd.h
+#
+check_include_file(unistd.h Z_HAVE_UNISTD_H)
+
+if(MSVC)
+    set(CMAKE_DEBUG_POSTFIX "d")
+    add_definitions(-D_CRT_SECURE_NO_DEPRECATE)
+    add_definitions(-D_CRT_NONSTDC_NO_DEPRECATE)
+    include_directories(${CMAKE_CURRENT_SOURCE_DIR})
+endif()
+
+if(NOT CMAKE_CURRENT_SOURCE_DIR STREQUAL CMAKE_CURRENT_BINARY_DIR)
+    # If we're doing an out of source build and the user has a zconf.h
+    # in their source tree...
+    if(EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/zconf.h)
+        message(STATUS "Renaming")
+        message(STATUS "    ${CMAKE_CURRENT_SOURCE_DIR}/zconf.h")
+        message(STATUS "to 'zconf.h.included' because this file is included with zlib")
+        message(STATUS "but CMake generates it automatically in the build directory.")
+        file(RENAME ${CMAKE_CURRENT_SOURCE_DIR}/zconf.h ${CMAKE_CURRENT_SOURCE_DIR}/zconf.h.included)
+  endif()
+endif()
+
+set(ZLIB_PC ${CMAKE_CURRENT_BINARY_DIR}/zlib.pc)
+configure_file( ${CMAKE_CURRENT_SOURCE_DIR}/zlib.pc.cmakein
+		${ZLIB_PC} @ONLY)
+configure_file(	${CMAKE_CURRENT_SOURCE_DIR}/zconf.h.cmakein
+		${CMAKE_CURRENT_BINARY_DIR}/zconf.h @ONLY)
+include_directories(${CMAKE_CURRENT_BINARY_DIR} ${CMAKE_SOURCE_DIR})
+
+
+#============================================================================
+# zlib
+#============================================================================
+
+set(ZLIB_PUBLIC_HDRS
+    ${CMAKE_CURRENT_BINARY_DIR}/zconf.h
+    zlib.h
+)
+set(ZLIB_PRIVATE_HDRS
+    crc32.h
+    deflate.h
+    gzguts.h
+    inffast.h
+    inffixed.h
+    inflate.h
+    inftrees.h
+    trees.h
+    zutil.h
+)
+set(ZLIB_SRCS
+    adler32.c
+    compress.c
+    crc32.c
+    deflate.c
+    gzclose.c
+    gzlib.c
+    gzread.c
+    gzwrite.c
+    inflate.c
+    infback.c
+    inftrees.c
+    inffast.c
+    trees.c
+    uncompr.c
+    zutil.c
+)
+
+if(NOT MINGW)
+    set(ZLIB_DLL_SRCS
+        win32/zlib1.rc # If present will override custom build rule below.
+    )
+endif()
+
+if(CMAKE_COMPILER_IS_GNUCC)
+    if(ASM686)
+        set(ZLIB_ASMS contrib/asm686/match.S)
+    elseif (AMD64)
+        set(ZLIB_ASMS contrib/amd64/amd64-match.S)
+    endif ()
+
+	if(ZLIB_ASMS)
+		add_definitions(-DASMV)
+		set_source_files_properties(${ZLIB_ASMS} PROPERTIES LANGUAGE C COMPILE_FLAGS -DNO_UNDERLINE)
+	endif()
+endif()
+
+if(MSVC)
+    if(ASM686)
+		ENABLE_LANGUAGE(ASM_MASM)
+        set(ZLIB_ASMS
+			contrib/masmx86/inffas32.asm
+			contrib/masmx86/match686.asm
+		)
+    elseif (AMD64)
+		ENABLE_LANGUAGE(ASM_MASM)
+        set(ZLIB_ASMS
+			contrib/masmx64/gvmat64.asm
+			contrib/masmx64/inffasx64.asm
+		)
+    endif()
+
+	if(ZLIB_ASMS)
+		add_definitions(-DASMV -DASMINF)
+	endif()
+endif()
+
+# parse the full version number from zlib.h and include in ZLIB_FULL_VERSION
+file(READ ${CMAKE_CURRENT_SOURCE_DIR}/zlib.h _zlib_h_contents)
+string(REGEX REPLACE ".*#define[ \t]+ZLIB_VERSION[ \t]+\"([-0-9A-Za-z.]+)\".*"
+    "\\1" ZLIB_FULL_VERSION ${_zlib_h_contents})
+
+if(MINGW)
+    # This gets us DLL resource information when compiling on MinGW.
+    if(NOT CMAKE_RC_COMPILER)
+        set(CMAKE_RC_COMPILER windres.exe)
+    endif()
+
+    add_custom_command(OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/zlib1rc.obj
+                       COMMAND ${CMAKE_RC_COMPILER}
+                            -D GCC_WINDRES
+                            -I ${CMAKE_CURRENT_SOURCE_DIR}
+                            -I ${CMAKE_CURRENT_BINARY_DIR}
+                            -o ${CMAKE_CURRENT_BINARY_DIR}/zlib1rc.obj
+                            -i ${CMAKE_CURRENT_SOURCE_DIR}/win32/zlib1.rc)
+    set(ZLIB_DLL_SRCS ${CMAKE_CURRENT_BINARY_DIR}/zlib1rc.obj)
+endif(MINGW)
+
+add_library(zlib SHARED ${ZLIB_SRCS} ${ZLIB_ASMS} ${ZLIB_DLL_SRCS} ${ZLIB_PUBLIC_HDRS} ${ZLIB_PRIVATE_HDRS})
+add_library(zlibstatic STATIC ${ZLIB_SRCS} ${ZLIB_ASMS} ${ZLIB_PUBLIC_HDRS} ${ZLIB_PRIVATE_HDRS})
+set_target_properties(zlib PROPERTIES DEFINE_SYMBOL ZLIB_DLL)
+set_target_properties(zlib PROPERTIES SOVERSION 1)
+
+if(NOT CYGWIN)
+    # This property causes shared libraries on Linux to have the full version
+    # encoded into their final filename.  We disable this on Cygwin because
+    # it causes cygz-${ZLIB_FULL_VERSION}.dll to be created when cygz.dll
+    # seems to be the default.
+    #
+    # This has no effect with MSVC, on that platform the version info for
+    # the DLL comes from the resource file win32/zlib1.rc
+    set_target_properties(zlib PROPERTIES VERSION ${ZLIB_FULL_VERSION})
+endif()
+
+if(UNIX)
+    # On unix-like platforms the library is almost always called libz
+   set_target_properties(zlib zlibstatic PROPERTIES OUTPUT_NAME z)
+   if(NOT APPLE)
+     set_target_properties(zlib PROPERTIES LINK_FLAGS "-Wl,--version-script,\"${CMAKE_CURRENT_SOURCE_DIR}/zlib.map\"")
+   endif()
+elseif(BUILD_SHARED_LIBS AND WIN32)
+    # Creates zlib1.dll when building shared library version
+    set_target_properties(zlib PROPERTIES SUFFIX "1.dll")
+endif()
+
+if(NOT SKIP_INSTALL_LIBRARIES AND NOT SKIP_INSTALL_ALL )
+    install(TARGETS zlib zlibstatic
+        RUNTIME DESTINATION "${INSTALL_BIN_DIR}"
+        ARCHIVE DESTINATION "${INSTALL_LIB_DIR}"
+        LIBRARY DESTINATION "${INSTALL_LIB_DIR}" )
+endif()
+if(NOT SKIP_INSTALL_HEADERS AND NOT SKIP_INSTALL_ALL )
+    install(FILES ${ZLIB_PUBLIC_HDRS} DESTINATION "${INSTALL_INC_DIR}")
+endif()
+if(NOT SKIP_INSTALL_FILES AND NOT SKIP_INSTALL_ALL )
+    install(FILES zlib.3 DESTINATION "${INSTALL_MAN_DIR}/man3")
+endif()
+if(NOT SKIP_INSTALL_FILES AND NOT SKIP_INSTALL_ALL )
+    install(FILES ${ZLIB_PC} DESTINATION "${INSTALL_PKGCONFIG_DIR}")
+endif()
+
+#============================================================================
+# Example binaries
+#============================================================================
+
+add_executable(example test/example.c)
+target_link_libraries(example zlib)
+add_test(example example)
+
+add_executable(minigzip test/minigzip.c)
+target_link_libraries(minigzip zlib)
+
+if(HAVE_OFF64_T)
+    add_executable(example64 test/example.c)
+    target_link_libraries(example64 zlib)
+    set_target_properties(example64 PROPERTIES COMPILE_FLAGS "-D_FILE_OFFSET_BITS=64")
+    add_test(example64 example64)
+
+    add_executable(minigzip64 test/minigzip.c)
+    target_link_libraries(minigzip64 zlib)
+    set_target_properties(minigzip64 PROPERTIES COMPILE_FLAGS "-D_FILE_OFFSET_BITS=64")
+endif()

ADDED   3rd_party/zlib/ChangeLog
Index: 3rd_party/zlib/ChangeLog
==================================================================
--- 3rd_party/zlib/ChangeLog
+++ 3rd_party/zlib/ChangeLog
@@ -0,0 +1,1515 @@
+
+                ChangeLog file for zlib
+
+Changes in 1.2.11 (15 Jan 2017)
+- Fix deflate stored bug when pulling last block from window
+- Permit immediate deflateParams changes before any deflate input
+
+Changes in 1.2.10 (2 Jan 2017)
+- Avoid warnings on snprintf() return value
+- Fix bug in deflate_stored() for zero-length input
+- Fix bug in gzwrite.c that produced corrupt gzip files
+- Remove files to be installed before copying them in Makefile.in
+- Add warnings when compiling with assembler code
+
+Changes in 1.2.9 (31 Dec 2016)
+- Fix contrib/minizip to permit unzipping with desktop API [Zouzou]
+- Improve contrib/blast to return unused bytes
+- Assure that gzoffset() is correct when appending
+- Improve compress() and uncompress() to support large lengths
+- Fix bug in test/example.c where error code not saved
+- Remedy Coverity warning [Randers-Pehrson]
+- Improve speed of gzprintf() in transparent mode
+- Fix inflateInit2() bug when windowBits is 16 or 32
+- Change DEBUG macro to ZLIB_DEBUG
+- Avoid uninitialized access by gzclose_w()
+- Allow building zlib outside of the source directory
+- Fix bug that accepted invalid zlib header when windowBits is zero
+- Fix gzseek() problem on MinGW due to buggy _lseeki64 there
+- Loop on write() calls in gzwrite.c in case of non-blocking I/O
+- Add --warn (-w) option to ./configure for more compiler warnings
+- Reject a window size of 256 bytes if not using the zlib wrapper
+- Fix bug when level 0 used with Z_HUFFMAN or Z_RLE
+- Add --debug (-d) option to ./configure to define ZLIB_DEBUG
+- Fix bugs in creating a very large gzip header
+- Add uncompress2() function, which returns the input size used
+- Assure that deflateParams() will not switch functions mid-block
+- Dramatically speed up deflation for level 0 (storing)
+- Add gzfread(), duplicating the interface of fread()
+- Add gzfwrite(), duplicating the interface of fwrite()
+- Add deflateGetDictionary() function
+- Use snprintf() for later versions of Microsoft C
+- Fix *Init macros to use z_ prefix when requested
+- Replace as400 with os400 for OS/400 support [Monnerat]
+- Add crc32_z() and adler32_z() functions with size_t lengths
+- Update Visual Studio project files [AraHaan]
+
+Changes in 1.2.8 (28 Apr 2013)
+- Update contrib/minizip/iowin32.c for Windows RT [Vollant]
+- Do not force Z_CONST for C++
+- Clean up contrib/vstudio [Roß]
+- Correct spelling error in zlib.h
+- Fix mixed line endings in contrib/vstudio
+
+Changes in 1.2.7.3 (13 Apr 2013)
+- Fix version numbers and DLL names in contrib/vstudio/*/zlib.rc
+
+Changes in 1.2.7.2 (13 Apr 2013)
+- Change check for a four-byte type back to hexadecimal
+- Fix typo in win32/Makefile.msc
+- Add casts in gzwrite.c for pointer differences
+
+Changes in 1.2.7.1 (24 Mar 2013)
+- Replace use of unsafe string functions with snprintf if available
+- Avoid including stddef.h on Windows for Z_SOLO compile [Niessink]
+- Fix gzgetc undefine when Z_PREFIX set [Turk]
+- Eliminate use of mktemp in Makefile (not always available)
+- Fix bug in 'F' mode for gzopen()
+- Add inflateGetDictionary() function
+- Correct comment in deflate.h
+- Use _snprintf for snprintf in Microsoft C
+- On Darwin, only use /usr/bin/libtool if libtool is not Apple
+- Delete "--version" file if created by "ar --version" [Richard G.]
+- Fix configure check for veracity of compiler error return codes
+- Fix CMake compilation of static lib for MSVC2010 x64
+- Remove unused variable in infback9.c
+- Fix argument checks in gzlog_compress() and gzlog_write()
+- Clean up the usage of z_const and respect const usage within zlib
+- Clean up examples/gzlog.[ch] comparisons of different types
+- Avoid shift equal to bits in type (caused endless loop)
+- Fix uninitialized value bug in gzputc() introduced by const patches
+- Fix memory allocation error in examples/zran.c [Nor]
+- Fix bug where gzopen(), gzclose() would write an empty file
+- Fix bug in gzclose() when gzwrite() runs out of memory
+- Check for input buffer malloc failure in examples/gzappend.c
+- Add note to contrib/blast to use binary mode in stdio
+- Fix comparisons of differently signed integers in contrib/blast
+- Check for invalid code length codes in contrib/puff
+- Fix serious but very rare decompression bug in inftrees.c
+- Update inflateBack() comments, since inflate() can be faster
+- Use underscored I/O function names for WINAPI_FAMILY
+- Add _tr_flush_bits to the external symbols prefixed by --zprefix
+- Add contrib/vstudio/vc10 pre-build step for static only
+- Quote --version-script argument in CMakeLists.txt
+- Don't specify --version-script on Apple platforms in CMakeLists.txt
+- Fix casting error in contrib/testzlib/testzlib.c
+- Fix types in contrib/minizip to match result of get_crc_table()
+- Simplify contrib/vstudio/vc10 with 'd' suffix
+- Add TOP support to win32/Makefile.msc
+- Suport i686 and amd64 assembler builds in CMakeLists.txt
+- Fix typos in the use of _LARGEFILE64_SOURCE in zconf.h
+- Add vc11 and vc12 build files to contrib/vstudio
+- Add gzvprintf() as an undocumented function in zlib
+- Fix configure for Sun shell
+- Remove runtime check in configure for four-byte integer type
+- Add casts and consts to ease user conversion to C++
+- Add man pages for minizip and miniunzip
+- In Makefile uninstall, don't rm if preceding cd fails
+- Do not return Z_BUF_ERROR if deflateParam() has nothing to write
+
+Changes in 1.2.7 (2 May 2012)
+- Replace use of memmove() with a simple copy for portability
+- Test for existence of strerror
+- Restore gzgetc_ for backward compatibility with 1.2.6
+- Fix build with non-GNU make on Solaris
+- Require gcc 4.0 or later on Mac OS X to use the hidden attribute
+- Include unistd.h for Watcom C
+- Use __WATCOMC__ instead of __WATCOM__
+- Do not use the visibility attribute if NO_VIZ defined
+- Improve the detection of no hidden visibility attribute
+- Avoid using __int64 for gcc or solo compilation
+- Cast to char * in gzprintf to avoid warnings [Zinser]
+- Fix make_vms.com for VAX [Zinser]
+- Don't use library or built-in byte swaps
+- Simplify test and use of gcc hidden attribute
+- Fix bug in gzclose_w() when gzwrite() fails to allocate memory
+- Add "x" (O_EXCL) and "e" (O_CLOEXEC) modes support to gzopen()
+- Fix bug in test/minigzip.c for configure --solo
+- Fix contrib/vstudio project link errors [Mohanathas]
+- Add ability to choose the builder in make_vms.com [Schweda]
+- Add DESTDIR support to mingw32 win32/Makefile.gcc
+- Fix comments in win32/Makefile.gcc for proper usage
+- Allow overriding the default install locations for cmake
+- Generate and install the pkg-config file with cmake
+- Build both a static and a shared version of zlib with cmake
+- Include version symbols for cmake builds
+- If using cmake with MSVC, add the source directory to the includes
+- Remove unneeded EXTRA_CFLAGS from win32/Makefile.gcc [Truta]
+- Move obsolete emx makefile to old [Truta]
+- Allow the use of -Wundef when compiling or using zlib
+- Avoid the use of the -u option with mktemp
+- Improve inflate() documentation on the use of Z_FINISH
+- Recognize clang as gcc
+- Add gzopen_w() in Windows for wide character path names
+- Rename zconf.h in CMakeLists.txt to move it out of the way
+- Add source directory in CMakeLists.txt for building examples
+- Look in build directory for zlib.pc in CMakeLists.txt
+- Remove gzflags from zlibvc.def in vc9 and vc10
+- Fix contrib/minizip compilation in the MinGW environment
+- Update ./configure for Solaris, support --64 [Mooney]
+- Remove -R. from Solaris shared build (possible security issue)
+- Avoid race condition for parallel make (-j) running example
+- Fix type mismatch between get_crc_table() and crc_table
+- Fix parsing of version with "-" in CMakeLists.txt [Snider, Ziegler]
+- Fix the path to zlib.map in CMakeLists.txt
+- Force the native libtool in Mac OS X to avoid GNU libtool [Beebe]
+- Add instructions to win32/Makefile.gcc for shared install [Torri]
+
+Changes in 1.2.6.1 (12 Feb 2012)
+- Avoid the use of the Objective-C reserved name "id"
+- Include io.h in gzguts.h for Microsoft compilers
+- Fix problem with ./configure --prefix and gzgetc macro
+- Include gz_header definition when compiling zlib solo
+- Put gzflags() functionality back in zutil.c
+- Avoid library header include in crc32.c for Z_SOLO
+- Use name in GCC_CLASSIC as C compiler for coverage testing, if set
+- Minor cleanup in contrib/minizip/zip.c [Vollant]
+- Update make_vms.com [Zinser]
+- Remove unnecessary gzgetc_ function
+- Use optimized byte swap operations for Microsoft and GNU [Snyder]
+- Fix minor typo in zlib.h comments [Rzesniowiecki]
+
+Changes in 1.2.6 (29 Jan 2012)
+- Update the Pascal interface in contrib/pascal
+- Fix function numbers for gzgetc_ in zlibvc.def files
+- Fix configure.ac for contrib/minizip [Schiffer]
+- Fix large-entry detection in minizip on 64-bit systems [Schiffer]
+- Have ./configure use the compiler return code for error indication
+- Fix CMakeLists.txt for cross compilation [McClure]
+- Fix contrib/minizip/zip.c for 64-bit architectures [Dalsnes]
+- Fix compilation of contrib/minizip on FreeBSD [Marquez]
+- Correct suggested usages in win32/Makefile.msc [Shachar, Horvath]
+- Include io.h for Turbo C / Borland C on all platforms [Truta]
+- Make version explicit in contrib/minizip/configure.ac [Bosmans]
+- Avoid warning for no encryption in contrib/minizip/zip.c [Vollant]
+- Minor cleanup up contrib/minizip/unzip.c [Vollant]
+- Fix bug when compiling minizip with C++ [Vollant]
+- Protect for long name and extra fields in contrib/minizip [Vollant]
+- Avoid some warnings in contrib/minizip [Vollant]
+- Add -I../.. -L../.. to CFLAGS for minizip and miniunzip
+- Add missing libs to minizip linker command
+- Add support for VPATH builds in contrib/minizip
+- Add an --enable-demos option to contrib/minizip/configure
+- Add the generation of configure.log by ./configure
+- Exit when required parameters not provided to win32/Makefile.gcc
+- Have gzputc return the character written instead of the argument
+- Use the -m option on ldconfig for BSD systems [Tobias]
+- Correct in zlib.map when deflateResetKeep was added
+
+Changes in 1.2.5.3 (15 Jan 2012)
+- Restore gzgetc function for binary compatibility
+- Do not use _lseeki64 under Borland C++ [Truta]
+- Update win32/Makefile.msc to build test/*.c [Truta]
+- Remove old/visualc6 given CMakefile and other alternatives
+- Update AS400 build files and documentation [Monnerat]
+- Update win32/Makefile.gcc to build test/*.c [Truta]
+- Permit stronger flushes after Z_BLOCK flushes
+- Avoid extraneous empty blocks when doing empty flushes
+- Permit Z_NULL arguments to deflatePending
+- Allow deflatePrime() to insert bits in the middle of a stream
+- Remove second empty static block for Z_PARTIAL_FLUSH
+- Write out all of the available bits when using Z_BLOCK
+- Insert the first two strings in the hash table after a flush
+
+Changes in 1.2.5.2 (17 Dec 2011)
+- fix ld error: unable to find version dependency 'ZLIB_1.2.5'
+- use relative symlinks for shared libs
+- Avoid searching past window for Z_RLE strategy
+- Assure that high-water mark initialization is always applied in deflate
+- Add assertions to fill_window() in deflate.c to match comments
+- Update python link in README
+- Correct spelling error in gzread.c
+- Fix bug in gzgets() for a concatenated empty gzip stream
+- Correct error in comment for gz_make()
+- Change gzread() and related to ignore junk after gzip streams
+- Allow gzread() and related to continue after gzclearerr()
+- Allow gzrewind() and gzseek() after a premature end-of-file
+- Simplify gzseek() now that raw after gzip is ignored
+- Change gzgetc() to a macro for speed (~40% speedup in testing)
+- Fix gzclose() to return the actual error last encountered
+- Always add large file support for windows
+- Include zconf.h for windows large file support
+- Include zconf.h.cmakein for windows large file support
+- Update zconf.h.cmakein on make distclean
+- Merge vestigial vsnprintf determination from zutil.h to gzguts.h
+- Clarify how gzopen() appends in zlib.h comments
+- Correct documentation of gzdirect() since junk at end now ignored
+- Add a transparent write mode to gzopen() when 'T' is in the mode
+- Update python link in zlib man page
+- Get inffixed.h and MAKEFIXED result to match
+- Add a ./config --solo option to make zlib subset with no library use
+- Add undocumented inflateResetKeep() function for CAB file decoding
+- Add --cover option to ./configure for gcc coverage testing
+- Add #define ZLIB_CONST option to use const in the z_stream interface
+- Add comment to gzdopen() in zlib.h to use dup() when using fileno()
+- Note behavior of uncompress() to provide as much data as it can
+- Add files in contrib/minizip to aid in building libminizip
+- Split off AR options in Makefile.in and configure
+- Change ON macro to Z_ARG to avoid application conflicts
+- Facilitate compilation with Borland C++ for pragmas and vsnprintf
+- Include io.h for Turbo C / Borland C++
+- Move example.c and minigzip.c to test/
+- Simplify incomplete code table filling in inflate_table()
+- Remove code from inflate.c and infback.c that is impossible to execute
+- Test the inflate code with full coverage
+- Allow deflateSetDictionary, inflateSetDictionary at any time (in raw)
+- Add deflateResetKeep and fix inflateResetKeep to retain dictionary
+- Fix gzwrite.c to accommodate reduced memory zlib compilation
+- Have inflate() with Z_FINISH avoid the allocation of a window
+- Do not set strm->adler when doing raw inflate
+- Fix gzeof() to behave just like feof() when read is not past end of file
+- Fix bug in gzread.c when end-of-file is reached
+- Avoid use of Z_BUF_ERROR in gz* functions except for premature EOF
+- Document gzread() capability to read concurrently written files
+- Remove hard-coding of resource compiler in CMakeLists.txt [Blammo]
+
+Changes in 1.2.5.1 (10 Sep 2011)
+- Update FAQ entry on shared builds (#13)
+- Avoid symbolic argument to chmod in Makefile.in
+- Fix bug and add consts in contrib/puff [Oberhumer]
+- Update contrib/puff/zeros.raw test file to have all block types
+- Add full coverage test for puff in contrib/puff/Makefile
+- Fix static-only-build install in Makefile.in
+- Fix bug in unzGetCurrentFileInfo() in contrib/minizip [Kuno]
+- Add libz.a dependency to shared in Makefile.in for parallel builds
+- Spell out "number" (instead of "nb") in zlib.h for total_in, total_out
+- Replace $(...) with `...` in configure for non-bash sh [Bowler]
+- Add darwin* to Darwin* and solaris* to SunOS\ 5* in configure [Groffen]
+- Add solaris* to Linux* in configure to allow gcc use [Groffen]
+- Add *bsd* to Linux* case in configure [Bar-Lev]
+- Add inffast.obj to dependencies in win32/Makefile.msc
+- Correct spelling error in deflate.h [Kohler]
+- Change libzdll.a again to libz.dll.a (!) in win32/Makefile.gcc
+- Add test to configure for GNU C looking for gcc in output of $cc -v
+- Add zlib.pc generation to win32/Makefile.gcc [Weigelt]
+- Fix bug in zlib.h for _FILE_OFFSET_BITS set and _LARGEFILE64_SOURCE not
+- Add comment in zlib.h that adler32_combine with len2 < 0 makes no sense
+- Make NO_DIVIDE option in adler32.c much faster (thanks to John Reiser)
+- Make stronger test in zconf.h to include unistd.h for LFS
+- Apply Darwin patches for 64-bit file offsets to contrib/minizip [Slack]
+- Fix zlib.h LFS support when Z_PREFIX used
+- Add updated as400 support (removed from old) [Monnerat]
+- Avoid deflate sensitivity to volatile input data
+- Avoid division in adler32_combine for NO_DIVIDE
+- Clarify the use of Z_FINISH with deflateBound() amount of space
+- Set binary for output file in puff.c
+- Use u4 type for crc_table to avoid conversion warnings
+- Apply casts in zlib.h to avoid conversion warnings
+- Add OF to prototypes for adler32_combine_ and crc32_combine_ [Miller]
+- Improve inflateSync() documentation to note indeterminancy
+- Add deflatePending() function to return the amount of pending output
+- Correct the spelling of "specification" in FAQ [Randers-Pehrson]
+- Add a check in configure for stdarg.h, use for gzprintf()
+- Check that pointers fit in ints when gzprint() compiled old style
+- Add dummy name before $(SHAREDLIBV) in Makefile [Bar-Lev, Bowler]
+- Delete line in configure that adds -L. libz.a to LDFLAGS [Weigelt]
+- Add debug records in assmebler code [Londer]
+- Update RFC references to use http://tools.ietf.org/html/... [Li]
+- Add --archs option, use of libtool to configure for Mac OS X [Borstel]
+
+Changes in 1.2.5 (19 Apr 2010)
+- Disable visibility attribute in win32/Makefile.gcc [Bar-Lev]
+- Default to libdir as sharedlibdir in configure [Nieder]
+- Update copyright dates on modified source files
+- Update trees.c to be able to generate modified trees.h
+- Exit configure for MinGW, suggesting win32/Makefile.gcc
+- Check for NULL path in gz_open [Homurlu]
+
+Changes in 1.2.4.5 (18 Apr 2010)
+- Set sharedlibdir in configure [Torok]
+- Set LDFLAGS in Makefile.in [Bar-Lev]
+- Avoid mkdir objs race condition in Makefile.in [Bowler]
+- Add ZLIB_INTERNAL in front of internal inter-module functions and arrays
+- Define ZLIB_INTERNAL to hide internal functions and arrays for GNU C
+- Don't use hidden attribute when it is a warning generator (e.g. Solaris)
+
+Changes in 1.2.4.4 (18 Apr 2010)
+- Fix CROSS_PREFIX executable testing, CHOST extract, mingw* [Torok]
+- Undefine _LARGEFILE64_SOURCE in zconf.h if it is zero, but not if empty
+- Try to use bash or ksh regardless of functionality of /bin/sh
+- Fix configure incompatibility with NetBSD sh
+- Remove attempt to run under bash or ksh since have better NetBSD fix
+- Fix win32/Makefile.gcc for MinGW [Bar-Lev]
+- Add diagnostic messages when using CROSS_PREFIX in configure
+- Added --sharedlibdir option to configure [Weigelt]
+- Use hidden visibility attribute when available [Frysinger]
+
+Changes in 1.2.4.3 (10 Apr 2010)
+- Only use CROSS_PREFIX in configure for ar and ranlib if they exist
+- Use CROSS_PREFIX for nm [Bar-Lev]
+- Assume _LARGEFILE64_SOURCE defined is equivalent to true
+- Avoid use of undefined symbols in #if with && and ||
+- Make *64 prototypes in gzguts.h consistent with functions
+- Add -shared load option for MinGW in configure [Bowler]
+- Move z_off64_t to public interface, use instead of off64_t
+- Remove ! from shell test in configure (not portable to Solaris)
+- Change +0 macro tests to -0 for possibly increased portability
+
+Changes in 1.2.4.2 (9 Apr 2010)
+- Add consistent carriage returns to readme.txt's in masmx86 and masmx64
+- Really provide prototypes for *64 functions when building without LFS
+- Only define unlink() in minigzip.c if unistd.h not included
+- Update README to point to contrib/vstudio project files
+- Move projects/vc6 to old/ and remove projects/
+- Include stdlib.h in minigzip.c for setmode() definition under WinCE
+- Clean up assembler builds in win32/Makefile.msc [Rowe]
+- Include sys/types.h for Microsoft for off_t definition
+- Fix memory leak on error in gz_open()
+- Symbolize nm as $NM in configure [Weigelt]
+- Use TEST_LDSHARED instead of LDSHARED to link test programs [Weigelt]
+- Add +0 to _FILE_OFFSET_BITS and _LFS64_LARGEFILE in case not defined
+- Fix bug in gzeof() to take into account unused input data
+- Avoid initialization of structures with variables in puff.c
+- Updated win32/README-WIN32.txt [Rowe]
+
+Changes in 1.2.4.1 (28 Mar 2010)
+- Remove the use of [a-z] constructs for sed in configure [gentoo 310225]
+- Remove $(SHAREDLIB) from LIBS in Makefile.in [Creech]
+- Restore "for debugging" comment on sprintf() in gzlib.c
+- Remove fdopen for MVS from gzguts.h
+- Put new README-WIN32.txt in win32 [Rowe]
+- Add check for shell to configure and invoke another shell if needed
+- Fix big fat stinking bug in gzseek() on uncompressed files
+- Remove vestigial F_OPEN64 define in zutil.h
+- Set and check the value of _LARGEFILE_SOURCE and _LARGEFILE64_SOURCE
+- Avoid errors on non-LFS systems when applications define LFS macros
+- Set EXE to ".exe" in configure for MINGW [Kahle]
+- Match crc32() in crc32.c exactly to the prototype in zlib.h [Sherrill]
+- Add prefix for cross-compilation in win32/makefile.gcc [Bar-Lev]
+- Add DLL install in win32/makefile.gcc [Bar-Lev]
+- Allow Linux* or linux* from uname in configure [Bar-Lev]
+- Allow ldconfig to be redefined in configure and Makefile.in [Bar-Lev]
+- Add cross-compilation prefixes to configure [Bar-Lev]
+- Match type exactly in gz_load() invocation in gzread.c
+- Match type exactly of zcalloc() in zutil.c to zlib.h alloc_func
+- Provide prototypes for *64 functions when building zlib without LFS
+- Don't use -lc when linking shared library on MinGW
+- Remove errno.h check in configure and vestigial errno code in zutil.h
+
+Changes in 1.2.4 (14 Mar 2010)
+- Fix VER3 extraction in configure for no fourth subversion
+- Update zlib.3, add docs to Makefile.in to make .pdf out of it
+- Add zlib.3.pdf to distribution
+- Don't set error code in gzerror() if passed pointer is NULL
+- Apply destination directory fixes to CMakeLists.txt [Lowman]
+- Move #cmakedefine's to a new zconf.in.cmakein
+- Restore zconf.h for builds that don't use configure or cmake
+- Add distclean to dummy Makefile for convenience
+- Update and improve INDEX, README, and FAQ
+- Update CMakeLists.txt for the return of zconf.h [Lowman]
+- Update contrib/vstudio/vc9 and vc10 [Vollant]
+- Change libz.dll.a back to libzdll.a in win32/Makefile.gcc
+- Apply license and readme changes to contrib/asm686 [Raiter]
+- Check file name lengths and add -c option in minigzip.c [Li]
+- Update contrib/amd64 and contrib/masmx86/ [Vollant]
+- Avoid use of "eof" parameter in trees.c to not shadow library variable
+- Update make_vms.com for removal of zlibdefs.h [Zinser]
+- Update assembler code and vstudio projects in contrib [Vollant]
+- Remove outdated assembler code contrib/masm686 and contrib/asm586
+- Remove old vc7 and vc8 from contrib/vstudio
+- Update win32/Makefile.msc, add ZLIB_VER_SUBREVISION [Rowe]
+- Fix memory leaks in gzclose_r() and gzclose_w(), file leak in gz_open()
+- Add contrib/gcc_gvmat64 for longest_match and inflate_fast [Vollant]
+- Remove *64 functions from win32/zlib.def (they're not 64-bit yet)
+- Fix bug in void-returning vsprintf() case in gzwrite.c
+- Fix name change from inflate.h in contrib/inflate86/inffas86.c
+- Check if temporary file exists before removing in make_vms.com [Zinser]
+- Fix make install and uninstall for --static option
+- Fix usage of _MSC_VER in gzguts.h and zutil.h [Truta]
+- Update readme.txt in contrib/masmx64 and masmx86 to assemble
+
+Changes in 1.2.3.9 (21 Feb 2010)
+- Expunge gzio.c
+- Move as400 build information to old
+- Fix updates in contrib/minizip and contrib/vstudio
+- Add const to vsnprintf test in configure to avoid warnings [Weigelt]
+- Delete zconf.h (made by configure) [Weigelt]
+- Change zconf.in.h to zconf.h.in per convention [Weigelt]
+- Check for NULL buf in gzgets()
+- Return empty string for gzgets() with len == 1 (like fgets())
+- Fix description of gzgets() in zlib.h for end-of-file, NULL return
+- Update minizip to 1.1 [Vollant]
+- Avoid MSVC loss of data warnings in gzread.c, gzwrite.c
+- Note in zlib.h that gzerror() should be used to distinguish from EOF
+- Remove use of snprintf() from gzlib.c
+- Fix bug in gzseek()
+- Update contrib/vstudio, adding vc9 and vc10 [Kuno, Vollant]
+- Fix zconf.h generation in CMakeLists.txt [Lowman]
+- Improve comments in zconf.h where modified by configure
+
+Changes in 1.2.3.8 (13 Feb 2010)
+- Clean up text files (tabs, trailing whitespace, etc.) [Oberhumer]
+- Use z_off64_t in gz_zero() and gz_skip() to match state->skip
+- Avoid comparison problem when sizeof(int) == sizeof(z_off64_t)
+- Revert to Makefile.in from 1.2.3.6 (live with the clutter)
+- Fix missing error return in gzflush(), add zlib.h note
+- Add *64 functions to zlib.map [Levin]
+- Fix signed/unsigned comparison in gz_comp()
+- Use SFLAGS when testing shared linking in configure
+- Add --64 option to ./configure to use -m64 with gcc
+- Fix ./configure --help to correctly name options
+- Have make fail if a test fails [Levin]
+- Avoid buffer overrun in contrib/masmx64/gvmat64.asm [Simpson]
+- Remove assembler object files from contrib
+
+Changes in 1.2.3.7 (24 Jan 2010)
+- Always gzopen() with O_LARGEFILE if available
+- Fix gzdirect() to work immediately after gzopen() or gzdopen()
+- Make gzdirect() more precise when the state changes while reading
+- Improve zlib.h documentation in many places
+- Catch memory allocation failure in gz_open()
+- Complete close operation if seek forward in gzclose_w() fails
+- Return Z_ERRNO from gzclose_r() if close() fails
+- Return Z_STREAM_ERROR instead of EOF for gzclose() being passed NULL
+- Return zero for gzwrite() errors to match zlib.h description
+- Return -1 on gzputs() error to match zlib.h description
+- Add zconf.in.h to allow recovery from configure modification [Weigelt]
+- Fix static library permissions in Makefile.in [Weigelt]
+- Avoid warnings in configure tests that hide functionality [Weigelt]
+- Add *BSD and DragonFly to Linux case in configure [gentoo 123571]
+- Change libzdll.a to libz.dll.a in win32/Makefile.gcc [gentoo 288212]
+- Avoid access of uninitialized data for first inflateReset2 call [Gomes]
+- Keep object files in subdirectories to reduce the clutter somewhat
+- Remove default Makefile and zlibdefs.h, add dummy Makefile
+- Add new external functions to Z_PREFIX, remove duplicates, z_z_ -> z_
+- Remove zlibdefs.h completely -- modify zconf.h instead
+
+Changes in 1.2.3.6 (17 Jan 2010)
+- Avoid void * arithmetic in gzread.c and gzwrite.c
+- Make compilers happier with const char * for gz_error message
+- Avoid unused parameter warning in inflate.c
+- Avoid signed-unsigned comparison warning in inflate.c
+- Indent #pragma's for traditional C
+- Fix usage of strwinerror() in glib.c, change to gz_strwinerror()
+- Correct email address in configure for system options
+- Update make_vms.com and add make_vms.com to contrib/minizip [Zinser]
+- Update zlib.map [Brown]
+- Fix Makefile.in for Solaris 10 make of example64 and minizip64 [Torok]
+- Apply various fixes to CMakeLists.txt [Lowman]
+- Add checks on len in gzread() and gzwrite()
+- Add error message for no more room for gzungetc()
+- Remove zlib version check in gzwrite()
+- Defer compression of gzprintf() result until need to
+- Use snprintf() in gzdopen() if available
+- Remove USE_MMAP configuration determination (only used by minigzip)
+- Remove examples/pigz.c (available separately)
+- Update examples/gun.c to 1.6
+
+Changes in 1.2.3.5 (8 Jan 2010)
+- Add space after #if in zutil.h for some compilers
+- Fix relatively harmless bug in deflate_fast() [Exarevsky]
+- Fix same problem in deflate_slow()
+- Add $(SHAREDLIBV) to LIBS in Makefile.in [Brown]
+- Add deflate_rle() for faster Z_RLE strategy run-length encoding
+- Add deflate_huff() for faster Z_HUFFMAN_ONLY encoding
+- Change name of "write" variable in inffast.c to avoid library collisions
+- Fix premature EOF from gzread() in gzio.c [Brown]
+- Use zlib header window size if windowBits is 0 in inflateInit2()
+- Remove compressBound() call in deflate.c to avoid linking compress.o
+- Replace use of errno in gz* with functions, support WinCE [Alves]
+- Provide alternative to perror() in minigzip.c for WinCE [Alves]
+- Don't use _vsnprintf on later versions of MSVC [Lowman]
+- Add CMake build script and input file [Lowman]
+- Update contrib/minizip to 1.1 [Svensson, Vollant]
+- Moved nintendods directory from contrib to .
+- Replace gzio.c with a new set of routines with the same functionality
+- Add gzbuffer(), gzoffset(), gzclose_r(), gzclose_w() as part of above
+- Update contrib/minizip to 1.1b
+- Change gzeof() to return 0 on error instead of -1 to agree with zlib.h
+
+Changes in 1.2.3.4 (21 Dec 2009)
+- Use old school .SUFFIXES in Makefile.in for FreeBSD compatibility
+- Update comments in configure and Makefile.in for default --shared
+- Fix test -z's in configure [Marquess]
+- Build examplesh and minigzipsh when not testing
+- Change NULL's to Z_NULL's in deflate.c and in comments in zlib.h
+- Import LDFLAGS from the environment in configure
+- Fix configure to populate SFLAGS with discovered CFLAGS options
+- Adapt make_vms.com to the new Makefile.in [Zinser]
+- Add zlib2ansi script for C++ compilation [Marquess]
+- Add _FILE_OFFSET_BITS=64 test to make test (when applicable)
+- Add AMD64 assembler code for longest match to contrib [Teterin]
+- Include options from $SFLAGS when doing $LDSHARED
+- Simplify 64-bit file support by introducing z_off64_t type
+- Make shared object files in objs directory to work around old Sun cc
+- Use only three-part version number for Darwin shared compiles
+- Add rc option to ar in Makefile.in for when ./configure not run
+- Add -WI,-rpath,. to LDFLAGS for OSF 1 V4*
+- Set LD_LIBRARYN32_PATH for SGI IRIX shared compile
+- Protect against _FILE_OFFSET_BITS being defined when compiling zlib
+- Rename Makefile.in targets allstatic to static and allshared to shared
+- Fix static and shared Makefile.in targets to be independent
+- Correct error return bug in gz_open() by setting state [Brown]
+- Put spaces before ;;'s in configure for better sh compatibility
+- Add pigz.c (parallel implementation of gzip) to examples/
+- Correct constant in crc32.c to UL [Leventhal]
+- Reject negative lengths in crc32_combine()
+- Add inflateReset2() function to work like inflateEnd()/inflateInit2()
+- Include sys/types.h for _LARGEFILE64_SOURCE [Brown]
+- Correct typo in doc/algorithm.txt [Janik]
+- Fix bug in adler32_combine() [Zhu]
+- Catch missing-end-of-block-code error in all inflates and in puff
+    Assures that random input to inflate eventually results in an error
+- Added enough.c (calculation of ENOUGH for inftrees.h) to examples/
+- Update ENOUGH and its usage to reflect discovered bounds
+- Fix gzerror() error report on empty input file [Brown]
+- Add ush casts in trees.c to avoid pedantic runtime errors
+- Fix typo in zlib.h uncompress() description [Reiss]
+- Correct inflate() comments with regard to automatic header detection
+- Remove deprecation comment on Z_PARTIAL_FLUSH (it stays)
+- Put new version of gzlog (2.0) in examples with interruption recovery
+- Add puff compile option to permit invalid distance-too-far streams
+- Add puff TEST command options, ability to read piped input
+- Prototype the *64 functions in zlib.h when _FILE_OFFSET_BITS == 64, but
+  _LARGEFILE64_SOURCE not defined
+- Fix Z_FULL_FLUSH to truly erase the past by resetting s->strstart
+- Fix deflateSetDictionary() to use all 32K for output consistency
+- Remove extraneous #define MIN_LOOKAHEAD in deflate.c (in deflate.h)
+- Clear bytes after deflate lookahead to avoid use of uninitialized data
+- Change a limit in inftrees.c to be more transparent to Coverity Prevent
+- Update win32/zlib.def with exported symbols from zlib.h
+- Correct spelling errors in zlib.h [Willem, Sobrado]
+- Allow Z_BLOCK for deflate() to force a new block
+- Allow negative bits in inflatePrime() to delete existing bit buffer
+- Add Z_TREES flush option to inflate() to return at end of trees
+- Add inflateMark() to return current state information for random access
+- Add Makefile for NintendoDS to contrib [Costa]
+- Add -w in configure compile tests to avoid spurious warnings [Beucler]
+- Fix typos in zlib.h comments for deflateSetDictionary()
+- Fix EOF detection in transparent gzread() [Maier]
+
+Changes in 1.2.3.3 (2 October 2006)
+- Make --shared the default for configure, add a --static option
+- Add compile option to permit invalid distance-too-far streams
+- Add inflateUndermine() function which is required to enable above
+- Remove use of "this" variable name for C++ compatibility [Marquess]
+- Add testing of shared library in make test, if shared library built
+- Use ftello() and fseeko() if available instead of ftell() and fseek()
+- Provide two versions of all functions that use the z_off_t type for
+  binary compatibility -- a normal version and a 64-bit offset version,
+  per the Large File Support Extension when _LARGEFILE64_SOURCE is
+  defined; use the 64-bit versions by default when _FILE_OFFSET_BITS
+  is defined to be 64
+- Add a --uname= option to configure to perhaps help with cross-compiling
+
+Changes in 1.2.3.2 (3 September 2006)
+- Turn off silly Borland warnings [Hay]
+- Use off64_t and define _LARGEFILE64_SOURCE when present
+- Fix missing dependency on inffixed.h in Makefile.in
+- Rig configure --shared to build both shared and static [Teredesai, Truta]
+- Remove zconf.in.h and instead create a new zlibdefs.h file
+- Fix contrib/minizip/unzip.c non-encrypted after encrypted [Vollant]
+- Add treebuild.xml (see http://treebuild.metux.de/) [Weigelt]
+
+Changes in 1.2.3.1 (16 August 2006)
+- Add watcom directory with OpenWatcom make files [Daniel]
+- Remove #undef of FAR in zconf.in.h for MVS [Fedtke]
+- Update make_vms.com [Zinser]
+- Use -fPIC for shared build in configure [Teredesai, Nicholson]
+- Use only major version number for libz.so on IRIX and OSF1 [Reinholdtsen]
+- Use fdopen() (not _fdopen()) for Interix in zutil.h [Bäck]
+- Add some FAQ entries about the contrib directory
+- Update the MVS question in the FAQ
+- Avoid extraneous reads after EOF in gzio.c [Brown]
+- Correct spelling of "successfully" in gzio.c [Randers-Pehrson]
+- Add comments to zlib.h about gzerror() usage [Brown]
+- Set extra flags in gzip header in gzopen() like deflate() does
+- Make configure options more compatible with double-dash conventions
+  [Weigelt]
+- Clean up compilation under Solaris SunStudio cc [Rowe, Reinholdtsen]
+- Fix uninstall target in Makefile.in [Truta]
+- Add pkgconfig support [Weigelt]
+- Use $(DESTDIR) macro in Makefile.in [Reinholdtsen, Weigelt]
+- Replace set_data_type() with a more accurate detect_data_type() in
+  trees.c, according to the txtvsbin.txt document [Truta]
+- Swap the order of #include <stdio.h> and #include "zlib.h" in
+  gzio.c, example.c and minigzip.c [Truta]
+- Shut up annoying VS2005 warnings about standard C deprecation [Rowe,
+  Truta] (where?)
+- Fix target "clean" from win32/Makefile.bor [Truta]
+- Create .pdb and .manifest files in win32/makefile.msc [Ziegler, Rowe]
+- Update zlib www home address in win32/DLL_FAQ.txt [Truta]
+- Update contrib/masmx86/inffas32.asm for VS2005 [Vollant, Van Wassenhove]
+- Enable browse info in the "Debug" and "ASM Debug" configurations in
+  the Visual C++ 6 project, and set (non-ASM) "Debug" as default [Truta]
+- Add pkgconfig support [Weigelt]
+- Add ZLIB_VER_MAJOR, ZLIB_VER_MINOR and ZLIB_VER_REVISION in zlib.h,
+  for use in win32/zlib1.rc [Polushin, Rowe, Truta]
+- Add a document that explains the new text detection scheme to
+  doc/txtvsbin.txt [Truta]
+- Add rfc1950.txt, rfc1951.txt and rfc1952.txt to doc/ [Truta]
+- Move algorithm.txt into doc/ [Truta]
+- Synchronize FAQ with website
+- Fix compressBound(), was low for some pathological cases [Fearnley]
+- Take into account wrapper variations in deflateBound()
+- Set examples/zpipe.c input and output to binary mode for Windows
+- Update examples/zlib_how.html with new zpipe.c (also web site)
+- Fix some warnings in examples/gzlog.c and examples/zran.c (it seems
+  that gcc became pickier in 4.0)
+- Add zlib.map for Linux: "All symbols from zlib-1.1.4 remain
+  un-versioned, the patch adds versioning only for symbols introduced in
+  zlib-1.2.0 or later.  It also declares as local those symbols which are
+  not designed to be exported." [Levin]
+- Update Z_PREFIX list in zconf.in.h, add --zprefix option to configure
+- Do not initialize global static by default in trees.c, add a response
+  NO_INIT_GLOBAL_POINTERS to initialize them if needed [Marquess]
+- Don't use strerror() in gzio.c under WinCE [Yakimov]
+- Don't use errno.h in zutil.h under WinCE [Yakimov]
+- Move arguments for AR to its usage to allow replacing ar [Marot]
+- Add HAVE_VISIBILITY_PRAGMA in zconf.in.h for Mozilla [Randers-Pehrson]
+- Improve inflateInit() and inflateInit2() documentation
+- Fix structure size comment in inflate.h
+- Change configure help option from --h* to --help [Santos]
+
+Changes in 1.2.3 (18 July 2005)
+- Apply security vulnerability fixes to contrib/infback9 as well
+- Clean up some text files (carriage returns, trailing space)
+- Update testzlib, vstudio, masmx64, and masmx86 in contrib [Vollant]
+
+Changes in 1.2.2.4 (11 July 2005)
+- Add inflatePrime() function for starting inflation at bit boundary
+- Avoid some Visual C warnings in deflate.c
+- Avoid more silly Visual C warnings in inflate.c and inftrees.c for 64-bit
+  compile
+- Fix some spelling errors in comments [Betts]
+- Correct inflateInit2() error return documentation in zlib.h
+- Add zran.c example of compressed data random access to examples
+  directory, shows use of inflatePrime()
+- Fix cast for assignments to strm->state in inflate.c and infback.c
+- Fix zlibCompileFlags() in zutil.c to use 1L for long shifts [Oberhumer]
+- Move declarations of gf2 functions to right place in crc32.c [Oberhumer]
+- Add cast in trees.c t avoid a warning [Oberhumer]
+- Avoid some warnings in fitblk.c, gun.c, gzjoin.c in examples [Oberhumer]
+- Update make_vms.com [Zinser]
+- Initialize state->write in inflateReset() since copied in inflate_fast()
+- Be more strict on incomplete code sets in inflate_table() and increase
+  ENOUGH and MAXD -- this repairs a possible security vulnerability for
+  invalid inflate input.  Thanks to Tavis Ormandy and Markus Oberhumer for
+  discovering the vulnerability and providing test cases.
+- Add ia64 support to configure for HP-UX [Smith]
+- Add error return to gzread() for format or i/o error [Levin]
+- Use malloc.h for OS/2 [Necasek]
+
+Changes in 1.2.2.3 (27 May 2005)
+- Replace 1U constants in inflate.c and inftrees.c for 64-bit compile
+- Typecast fread() return values in gzio.c [Vollant]
+- Remove trailing space in minigzip.c outmode (VC++ can't deal with it)
+- Fix crc check bug in gzread() after gzungetc() [Heiner]
+- Add the deflateTune() function to adjust internal compression parameters
+- Add a fast gzip decompressor, gun.c, to examples (use of inflateBack)
+- Remove an incorrect assertion in examples/zpipe.c
+- Add C++ wrapper in infback9.h [Donais]
+- Fix bug in inflateCopy() when decoding fixed codes
+- Note in zlib.h how much deflateSetDictionary() actually uses
+- Remove USE_DICT_HEAD in deflate.c (would mess up inflate if used)
+- Add _WIN32_WCE to define WIN32 in zconf.in.h [Spencer]
+- Don't include stderr.h or errno.h for _WIN32_WCE in zutil.h [Spencer]
+- Add gzdirect() function to indicate transparent reads
+- Update contrib/minizip [Vollant]
+- Fix compilation of deflate.c when both ASMV and FASTEST [Oberhumer]
+- Add casts in crc32.c to avoid warnings [Oberhumer]
+- Add contrib/masmx64 [Vollant]
+- Update contrib/asm586, asm686, masmx86, testzlib, vstudio [Vollant]
+
+Changes in 1.2.2.2 (30 December 2004)
+- Replace structure assignments in deflate.c and inflate.c with zmemcpy to
+  avoid implicit memcpy calls (portability for no-library compilation)
+- Increase sprintf() buffer size in gzdopen() to allow for large numbers
+- Add INFLATE_STRICT to check distances against zlib header
+- Improve WinCE errno handling and comments [Chang]
+- Remove comment about no gzip header processing in FAQ
+- Add Z_FIXED strategy option to deflateInit2() to force fixed trees
+- Add updated make_vms.com [Coghlan], update README
+- Create a new "examples" directory, move gzappend.c there, add zpipe.c,
+  fitblk.c, gzlog.[ch], gzjoin.c, and zlib_how.html.
+- Add FAQ entry and comments in deflate.c on uninitialized memory access
+- Add Solaris 9 make options in configure [Gilbert]
+- Allow strerror() usage in gzio.c for STDC
+- Fix DecompressBuf in contrib/delphi/ZLib.pas [ManChesTer]
+- Update contrib/masmx86/inffas32.asm and gvmat32.asm [Vollant]
+- Use z_off_t for adler32_combine() and crc32_combine() lengths
+- Make adler32() much faster for small len
+- Use OS_CODE in deflate() default gzip header
+
+Changes in 1.2.2.1 (31 October 2004)
+- Allow inflateSetDictionary() call for raw inflate
+- Fix inflate header crc check bug for file names and comments
+- Add deflateSetHeader() and gz_header structure for custom gzip headers
+- Add inflateGetheader() to retrieve gzip headers
+- Add crc32_combine() and adler32_combine() functions
+- Add alloc_func, free_func, in_func, out_func to Z_PREFIX list
+- Use zstreamp consistently in zlib.h (inflate_back functions)
+- Remove GUNZIP condition from definition of inflate_mode in inflate.h
+  and in contrib/inflate86/inffast.S [Truta, Anderson]
+- Add support for AMD64 in contrib/inflate86/inffas86.c [Anderson]
+- Update projects/README.projects and projects/visualc6 [Truta]
+- Update win32/DLL_FAQ.txt [Truta]
+- Avoid warning under NO_GZCOMPRESS in gzio.c; fix typo [Truta]
+- Deprecate Z_ASCII; use Z_TEXT instead [Truta]
+- Use a new algorithm for setting strm->data_type in trees.c [Truta]
+- Do not define an exit() prototype in zutil.c unless DEBUG defined
+- Remove prototype of exit() from zutil.c, example.c, minigzip.c [Truta]
+- Add comment in zlib.h for Z_NO_FLUSH parameter to deflate()
+- Fix Darwin build version identification [Peterson]
+
+Changes in 1.2.2 (3 October 2004)
+- Update zlib.h comments on gzip in-memory processing
+- Set adler to 1 in inflateReset() to support Java test suite [Walles]
+- Add contrib/dotzlib [Ravn]
+- Update win32/DLL_FAQ.txt [Truta]
+- Update contrib/minizip [Vollant]
+- Move contrib/visual-basic.txt to old/ [Truta]
+- Fix assembler builds in projects/visualc6/ [Truta]
+
+Changes in 1.2.1.2 (9 September 2004)
+- Update INDEX file
+- Fix trees.c to update strm->data_type (no one ever noticed!)
+- Fix bug in error case in inflate.c, infback.c, and infback9.c [Brown]
+- Add "volatile" to crc table flag declaration (for DYNAMIC_CRC_TABLE)
+- Add limited multitasking protection to DYNAMIC_CRC_TABLE
+- Add NO_vsnprintf for VMS in zutil.h [Mozilla]
+- Don't declare strerror() under VMS [Mozilla]
+- Add comment to DYNAMIC_CRC_TABLE to use get_crc_table() to initialize
+- Update contrib/ada [Anisimkov]
+- Update contrib/minizip [Vollant]
+- Fix configure to not hardcode directories for Darwin [Peterson]
+- Fix gzio.c to not return error on empty files [Brown]
+- Fix indentation; update version in contrib/delphi/ZLib.pas and
+  contrib/pascal/zlibpas.pas [Truta]
+- Update mkasm.bat in contrib/masmx86 [Truta]
+- Update contrib/untgz [Truta]
+- Add projects/README.projects [Truta]
+- Add project for MS Visual C++ 6.0 in projects/visualc6 [Cadieux, Truta]
+- Update win32/DLL_FAQ.txt [Truta]
+- Update list of Z_PREFIX symbols in zconf.h [Randers-Pehrson, Truta]
+- Remove an unnecessary assignment to curr in inftrees.c [Truta]
+- Add OS/2 to exe builds in configure [Poltorak]
+- Remove err dummy parameter in zlib.h [Kientzle]
+
+Changes in 1.2.1.1 (9 January 2004)
+- Update email address in README
+- Several FAQ updates
+- Fix a big fat bug in inftrees.c that prevented decoding valid
+  dynamic blocks with only literals and no distance codes --
+  Thanks to "Hot Emu" for the bug report and sample file
+- Add a note to puff.c on no distance codes case.
+
+Changes in 1.2.1 (17 November 2003)
+- Remove a tab in contrib/gzappend/gzappend.c
+- Update some interfaces in contrib for new zlib functions
+- Update zlib version number in some contrib entries
+- Add Windows CE definition for ptrdiff_t in zutil.h [Mai, Truta]
+- Support shared libraries on Hurd and KFreeBSD [Brown]
+- Fix error in NO_DIVIDE option of adler32.c
+
+Changes in 1.2.0.8 (4 November 2003)
+- Update version in contrib/delphi/ZLib.pas and contrib/pascal/zlibpas.pas
+- Add experimental NO_DIVIDE #define in adler32.c
+    - Possibly faster on some processors (let me know if it is)
+- Correct Z_BLOCK to not return on first inflate call if no wrap
+- Fix strm->data_type on inflate() return to correctly indicate EOB
+- Add deflatePrime() function for appending in the middle of a byte
+- Add contrib/gzappend for an example of appending to a stream
+- Update win32/DLL_FAQ.txt [Truta]
+- Delete Turbo C comment in README [Truta]
+- Improve some indentation in zconf.h [Truta]
+- Fix infinite loop on bad input in configure script [Church]
+- Fix gzeof() for concatenated gzip files [Johnson]
+- Add example to contrib/visual-basic.txt [Michael B.]
+- Add -p to mkdir's in Makefile.in [vda]
+- Fix configure to properly detect presence or lack of printf functions
+- Add AS400 support [Monnerat]
+- Add a little Cygwin support [Wilson]
+
+Changes in 1.2.0.7 (21 September 2003)
+- Correct some debug formats in contrib/infback9
+- Cast a type in a debug statement in trees.c
+- Change search and replace delimiter in configure from % to # [Beebe]
+- Update contrib/untgz to 0.2 with various fixes [Truta]
+- Add build support for Amiga [Nikl]
+- Remove some directories in old that have been updated to 1.2
+- Add dylib building for Mac OS X in configure and Makefile.in
+- Remove old distribution stuff from Makefile
+- Update README to point to DLL_FAQ.txt, and add comment on Mac OS X
+- Update links in README
+
+Changes in 1.2.0.6 (13 September 2003)
+- Minor FAQ updates
+- Update contrib/minizip to 1.00 [Vollant]
+- Remove test of gz functions in example.c when GZ_COMPRESS defined [Truta]
+- Update POSTINC comment for 68060 [Nikl]
+- Add contrib/infback9 with deflate64 decoding (unsupported)
+- For MVS define NO_vsnprintf and undefine FAR [van Burik]
+- Add pragma for fdopen on MVS [van Burik]
+
+Changes in 1.2.0.5 (8 September 2003)
+- Add OF to inflateBackEnd() declaration in zlib.h
+- Remember start when using gzdopen in the middle of a file
+- Use internal off_t counters in gz* functions to properly handle seeks
+- Perform more rigorous check for distance-too-far in inffast.c
+- Add Z_BLOCK flush option to return from inflate at block boundary
+- Set strm->data_type on return from inflate
+    - Indicate bits unused, if at block boundary, and if in last block
+- Replace size_t with ptrdiff_t in crc32.c, and check for correct size
+- Add condition so old NO_DEFLATE define still works for compatibility
+- FAQ update regarding the Windows DLL [Truta]
+- INDEX update: add qnx entry, remove aix entry [Truta]
+- Install zlib.3 into mandir [Wilson]
+- Move contrib/zlib_dll_FAQ.txt to win32/DLL_FAQ.txt; update [Truta]
+- Adapt the zlib interface to the new DLL convention guidelines [Truta]
+- Introduce ZLIB_WINAPI macro to allow the export of functions using
+  the WINAPI calling convention, for Visual Basic [Vollant, Truta]
+- Update msdos and win32 scripts and makefiles [Truta]
+- Export symbols by name, not by ordinal, in win32/zlib.def [Truta]
+- Add contrib/ada [Anisimkov]
+- Move asm files from contrib/vstudio/vc70_32 to contrib/asm386 [Truta]
+- Rename contrib/asm386 to contrib/masmx86 [Truta, Vollant]
+- Add contrib/masm686 [Truta]
+- Fix offsets in contrib/inflate86 and contrib/masmx86/inffas32.asm
+  [Truta, Vollant]
+- Update contrib/delphi; rename to contrib/pascal; add example [Truta]
+- Remove contrib/delphi2; add a new contrib/delphi [Truta]
+- Avoid inclusion of the nonstandard <memory.h> in contrib/iostream,
+  and fix some method prototypes [Truta]
+- Fix the ZCR_SEED2 constant to avoid warnings in contrib/minizip
+  [Truta]
+- Avoid the use of backslash (\) in contrib/minizip [Vollant]
+- Fix file time handling in contrib/untgz; update makefiles [Truta]
+- Update contrib/vstudio/vc70_32 to comply with the new DLL guidelines
+  [Vollant]
+- Remove contrib/vstudio/vc15_16 [Vollant]
+- Rename contrib/vstudio/vc70_32 to contrib/vstudio/vc7 [Truta]
+- Update README.contrib [Truta]
+- Invert the assignment order of match_head and s->prev[...] in
+  INSERT_STRING [Truta]
+- Compare TOO_FAR with 32767 instead of 32768, to avoid 16-bit warnings
+  [Truta]
+- Compare function pointers with 0, not with NULL or Z_NULL [Truta]
+- Fix prototype of syncsearch in inflate.c [Truta]
+- Introduce ASMINF macro to be enabled when using an ASM implementation
+  of inflate_fast [Truta]
+- Change NO_DEFLATE to NO_GZCOMPRESS [Truta]
+- Modify test_gzio in example.c to take a single file name as a
+  parameter [Truta]
+- Exit the example.c program if gzopen fails [Truta]
+- Add type casts around strlen in example.c [Truta]
+- Remove casting to sizeof in minigzip.c; give a proper type
+  to the variable compared with SUFFIX_LEN [Truta]
+- Update definitions of STDC and STDC99 in zconf.h [Truta]
+- Synchronize zconf.h with the new Windows DLL interface [Truta]
+- Use SYS16BIT instead of __32BIT__ to distinguish between
+  16- and 32-bit platforms [Truta]
+- Use far memory allocators in small 16-bit memory models for
+  Turbo C [Truta]
+- Add info about the use of ASMV, ASMINF and ZLIB_WINAPI in
+  zlibCompileFlags [Truta]
+- Cygwin has vsnprintf [Wilson]
+- In Windows16, OS_CODE is 0, as in MSDOS [Truta]
+- In Cygwin, OS_CODE is 3 (Unix), not 11 (Windows32) [Wilson]
+
+Changes in 1.2.0.4 (10 August 2003)
+- Minor FAQ updates
+- Be more strict when checking inflateInit2's windowBits parameter
+- Change NO_GUNZIP compile option to NO_GZIP to cover deflate as well
+- Add gzip wrapper option to deflateInit2 using windowBits
+- Add updated QNX rule in configure and qnx directory [Bonnefoy]
+- Make inflate distance-too-far checks more rigorous
+- Clean up FAR usage in inflate
+- Add casting to sizeof() in gzio.c and minigzip.c
+
+Changes in 1.2.0.3 (19 July 2003)
+- Fix silly error in gzungetc() implementation [Vollant]
+- Update contrib/minizip and contrib/vstudio [Vollant]
+- Fix printf format in example.c
+- Correct cdecl support in zconf.in.h [Anisimkov]
+- Minor FAQ updates
+
+Changes in 1.2.0.2 (13 July 2003)
+- Add ZLIB_VERNUM in zlib.h for numerical preprocessor comparisons
+- Attempt to avoid warnings in crc32.c for pointer-int conversion
+- Add AIX to configure, remove aix directory [Bakker]
+- Add some casts to minigzip.c
+- Improve checking after insecure sprintf() or vsprintf() calls
+- Remove #elif's from crc32.c
+- Change leave label to inf_leave in inflate.c and infback.c to avoid
+  library conflicts
+- Remove inflate gzip decoding by default--only enable gzip decoding by
+  special request for stricter backward compatibility
+- Add zlibCompileFlags() function to return compilation information
+- More typecasting in deflate.c to avoid warnings
+- Remove leading underscore from _Capital #defines [Truta]
+- Fix configure to link shared library when testing
+- Add some Windows CE target adjustments [Mai]
+- Remove #define ZLIB_DLL in zconf.h [Vollant]
+- Add zlib.3 [Rodgers]
+- Update RFC URL in deflate.c and algorithm.txt [Mai]
+- Add zlib_dll_FAQ.txt to contrib [Truta]
+- Add UL to some constants [Truta]
+- Update minizip and vstudio [Vollant]
+- Remove vestigial NEED_DUMMY_RETURN from zconf.in.h
+- Expand use of NO_DUMMY_DECL to avoid all dummy structures
+- Added iostream3 to contrib [Schwardt]
+- Replace rewind() with fseek() for WinCE [Truta]
+- Improve setting of zlib format compression level flags
+    - Report 0 for huffman and rle strategies and for level == 0 or 1
+    - Report 2 only for level == 6
+- Only deal with 64K limit when necessary at compile time [Truta]
+- Allow TOO_FAR check to be turned off at compile time [Truta]
+- Add gzclearerr() function [Souza]
+- Add gzungetc() function
+
+Changes in 1.2.0.1 (17 March 2003)
+- Add Z_RLE strategy for run-length encoding [Truta]
+    - When Z_RLE requested, restrict matches to distance one
+    - Update zlib.h, minigzip.c, gzopen(), gzdopen() for Z_RLE
+- Correct FASTEST compilation to allow level == 0
+- Clean up what gets compiled for FASTEST
+- Incorporate changes to zconf.in.h [Vollant]
+    - Refine detection of Turbo C need for dummy returns
+    - Refine ZLIB_DLL compilation
+    - Include additional header file on VMS for off_t typedef
+- Try to use _vsnprintf where it supplants vsprintf [Vollant]
+- Add some casts in inffast.c
+- Enchance comments in zlib.h on what happens if gzprintf() tries to
+  write more than 4095 bytes before compression
+- Remove unused state from inflateBackEnd()
+- Remove exit(0) from minigzip.c, example.c
+- Get rid of all those darn tabs
+- Add "check" target to Makefile.in that does the same thing as "test"
+- Add "mostlyclean" and "maintainer-clean" targets to Makefile.in
+- Update contrib/inflate86 [Anderson]
+- Update contrib/testzlib, contrib/vstudio, contrib/minizip [Vollant]
+- Add msdos and win32 directories with makefiles [Truta]
+- More additions and improvements to the FAQ
+
+Changes in 1.2.0 (9 March 2003)
+- New and improved inflate code
+    - About 20% faster
+    - Does not allocate 32K window unless and until needed
+    - Automatically detects and decompresses gzip streams
+    - Raw inflate no longer needs an extra dummy byte at end
+    - Added inflateBack functions using a callback interface--even faster
+      than inflate, useful for file utilities (gzip, zip)
+    - Added inflateCopy() function to record state for random access on
+      externally generated deflate streams (e.g. in gzip files)
+    - More readable code (I hope)
+- New and improved crc32()
+    - About 50% faster, thanks to suggestions from Rodney Brown
+- Add deflateBound() and compressBound() functions
+- Fix memory leak in deflateInit2()
+- Permit setting dictionary for raw deflate (for parallel deflate)
+- Fix const declaration for gzwrite()
+- Check for some malloc() failures in gzio.c
+- Fix bug in gzopen() on single-byte file 0x1f
+- Fix bug in gzread() on concatenated file with 0x1f at end of buffer
+  and next buffer doesn't start with 0x8b
+- Fix uncompress() to return Z_DATA_ERROR on truncated input
+- Free memory at end of example.c
+- Remove MAX #define in trees.c (conflicted with some libraries)
+- Fix static const's in deflate.c, gzio.c, and zutil.[ch]
+- Declare malloc() and free() in gzio.c if STDC not defined
+- Use malloc() instead of calloc() in zutil.c if int big enough
+- Define STDC for AIX
+- Add aix/ with approach for compiling shared library on AIX
+- Add HP-UX support for shared libraries in configure
+- Add OpenUNIX support for shared libraries in configure
+- Use $cc instead of gcc to build shared library
+- Make prefix directory if needed when installing
+- Correct Macintosh avoidance of typedef Byte in zconf.h
+- Correct Turbo C memory allocation when under Linux
+- Use libz.a instead of -lz in Makefile (assure use of compiled library)
+- Update configure to check for snprintf or vsnprintf functions and their
+  return value, warn during make if using an insecure function
+- Fix configure problem with compile-time knowledge of HAVE_UNISTD_H that
+  is lost when library is used--resolution is to build new zconf.h
+- Documentation improvements (in zlib.h):
+    - Document raw deflate and inflate
+    - Update RFCs URL
+    - Point out that zlib and gzip formats are different
+    - Note that Z_BUF_ERROR is not fatal
+    - Document string limit for gzprintf() and possible buffer overflow
+    - Note requirement on avail_out when flushing
+    - Note permitted values of flush parameter of inflate()
+- Add some FAQs (and even answers) to the FAQ
+- Add contrib/inflate86/ for x86 faster inflate
+- Add contrib/blast/ for PKWare Data Compression Library decompression
+- Add contrib/puff/ simple inflate for deflate format description
+
+Changes in 1.1.4 (11 March 2002)
+- ZFREE was repeated on same allocation on some error conditions.
+  This creates a security problem described in
+  http://www.zlib.org/advisory-2002-03-11.txt
+- Returned incorrect error (Z_MEM_ERROR) on some invalid data
+- Avoid accesses before window for invalid distances with inflate window
+  less than 32K.
+- force windowBits > 8 to avoid a bug in the encoder for a window size
+  of 256 bytes. (A complete fix will be available in 1.1.5).
+
+Changes in 1.1.3 (9 July 1998)
+- fix "an inflate input buffer bug that shows up on rare but persistent
+  occasions" (Mark)
+- fix gzread and gztell for concatenated .gz files (Didier Le Botlan)
+- fix gzseek(..., SEEK_SET) in write mode
+- fix crc check after a gzeek (Frank Faubert)
+- fix miniunzip when the last entry in a zip file is itself a zip file
+  (J Lillge)
+- add contrib/asm586 and contrib/asm686 (Brian Raiter)
+  See http://www.muppetlabs.com/~breadbox/software/assembly.html
+- add support for Delphi 3 in contrib/delphi (Bob Dellaca)
+- add support for C++Builder 3 and Delphi 3 in contrib/delphi2 (Davide Moretti)
+- do not exit prematurely in untgz if 0 at start of block (Magnus Holmgren)
+- use macro EXTERN instead of extern to support DLL for BeOS (Sander Stoks)
+- added a FAQ file
+
+- Support gzdopen on Mac with Metrowerks (Jason Linhart)
+- Do not redefine Byte on Mac (Brad Pettit & Jason Linhart)
+- define SEEK_END too if SEEK_SET is not defined (Albert Chin-A-Young)
+- avoid some warnings with Borland C (Tom Tanner)
+- fix a problem in contrib/minizip/zip.c for 16-bit MSDOS (Gilles Vollant)
+- emulate utime() for WIN32 in contrib/untgz  (Gilles Vollant)
+- allow several arguments to configure (Tim Mooney, Frodo Looijaard)
+- use libdir and includedir in Makefile.in (Tim Mooney)
+- support shared libraries on OSF1 V4 (Tim Mooney)
+- remove so_locations in "make clean"  (Tim Mooney)
+- fix maketree.c compilation error (Glenn, Mark)
+- Python interface to zlib now in Python 1.5 (Jeremy Hylton)
+- new Makefile.riscos (Rich Walker)
+- initialize static descriptors in trees.c for embedded targets (Nick Smith)
+- use "foo-gz" in example.c for RISCOS and VMS (Nick Smith)
+- add the OS/2 files in Makefile.in too (Andrew Zabolotny)
+- fix fdopen and halloc macros for Microsoft C 6.0 (Tom Lane)
+- fix maketree.c to allow clean compilation of inffixed.h (Mark)
+- fix parameter check in deflateCopy (Gunther Nikl)
+- cleanup trees.c, use compressed_len only in debug mode (Christian Spieler)
+- Many portability patches by Christian Spieler:
+  . zutil.c, zutil.h: added "const" for zmem*
+  . Make_vms.com: fixed some typos
+  . Make_vms.com: msdos/Makefile.*: removed zutil.h from some dependency lists
+  . msdos/Makefile.msc: remove "default rtl link library" info from obj files
+  . msdos/Makefile.*: use model-dependent name for the built zlib library
+  . msdos/Makefile.emx, nt/Makefile.emx, nt/Makefile.gcc:
+     new makefiles, for emx (DOS/OS2), emx&rsxnt and mingw32 (Windows 9x / NT)
+- use define instead of typedef for Bytef also for MSC small/medium (Tom Lane)
+- replace __far with _far for better portability (Christian Spieler, Tom Lane)
+- fix test for errno.h in configure (Tim Newsham)
+
+Changes in 1.1.2 (19 March 98)
+- added contrib/minzip, mini zip and unzip based on zlib (Gilles Vollant)
+  See http://www.winimage.com/zLibDll/unzip.html
+- preinitialize the inflate tables for fixed codes, to make the code
+  completely thread safe (Mark)
+- some simplifications and slight speed-up to the inflate code (Mark)
+- fix gzeof on non-compressed files (Allan Schrum)
+- add -std1 option in configure for OSF1 to fix gzprintf (Martin Mokrejs)
+- use default value of 4K for Z_BUFSIZE for 16-bit MSDOS (Tim Wegner + Glenn)
+- added os2/Makefile.def and os2/zlib.def (Andrew Zabolotny)
+- add shared lib support for UNIX_SV4.2MP (MATSUURA Takanori)
+- do not wrap extern "C" around system includes (Tom Lane)
+- mention zlib binding for TCL in README (Andreas Kupries)
+- added amiga/Makefile.pup for Amiga powerUP SAS/C PPC (Andreas Kleinert)
+- allow "make install prefix=..." even after configure (Glenn Randers-Pehrson)
+- allow "configure --prefix $HOME" (Tim Mooney)
+- remove warnings in example.c and gzio.c (Glenn Randers-Pehrson)
+- move Makefile.sas to amiga/Makefile.sas
+
+Changes in 1.1.1 (27 Feb 98)
+- fix macros _tr_tally_* in deflate.h for debug mode  (Glenn Randers-Pehrson)
+- remove block truncation heuristic which had very marginal effect for zlib
+  (smaller lit_bufsize than in gzip 1.2.4) and degraded a little the
+  compression ratio on some files. This also allows inlining _tr_tally for
+  matches in deflate_slow.
+- added msdos/Makefile.w32 for WIN32 Microsoft Visual C++ (Bob Frazier)
+
+Changes in 1.1.0 (24 Feb 98)
+- do not return STREAM_END prematurely in inflate (John Bowler)
+- revert to the zlib 1.0.8 inflate to avoid the gcc 2.8.0 bug (Jeremy Buhler)
+- compile with -DFASTEST to get compression code optimized for speed only
+- in minigzip, try mmap'ing the input file first (Miguel Albrecht)
+- increase size of I/O buffers in minigzip.c and gzio.c (not a big gain
+  on Sun but significant on HP)
+
+- add a pointer to experimental unzip library in README (Gilles Vollant)
+- initialize variable gcc in configure (Chris Herborth)
+
+Changes in 1.0.9 (17 Feb 1998)
+- added gzputs and gzgets functions
+- do not clear eof flag in gzseek (Mark Diekhans)
+- fix gzseek for files in transparent mode (Mark Diekhans)
+- do not assume that vsprintf returns the number of bytes written (Jens Krinke)
+- replace EXPORT with ZEXPORT to avoid conflict with other programs
+- added compress2 in zconf.h, zlib.def, zlib.dnt
+- new asm code from Gilles Vollant in contrib/asm386
+- simplify the inflate code (Mark):
+ . Replace ZALLOC's in huft_build() with single ZALLOC in inflate_blocks_new()
+ . ZALLOC the length list in inflate_trees_fixed() instead of using stack
+ . ZALLOC the value area for huft_build() instead of using stack
+ . Simplify Z_FINISH check in inflate()
+
+- Avoid gcc 2.8.0 comparison bug a little differently than zlib 1.0.8
+- in inftrees.c, avoid cc -O bug on HP (Farshid Elahi)
+- in zconf.h move the ZLIB_DLL stuff earlier to avoid problems with
+  the declaration of FAR (Gilles VOllant)
+- install libz.so* with mode 755 (executable) instead of 644 (Marc Lehmann)
+- read_buf buf parameter of type Bytef* instead of charf*
+- zmemcpy parameters are of type Bytef*, not charf* (Joseph Strout)
+- do not redeclare unlink in minigzip.c for WIN32 (John Bowler)
+- fix check for presence of directories in "make install" (Ian Willis)
+
+Changes in 1.0.8 (27 Jan 1998)
+- fixed offsets in contrib/asm386/gvmat32.asm (Gilles Vollant)
+- fix gzgetc and gzputc for big endian systems (Markus Oberhumer)
+- added compress2() to allow setting the compression level
+- include sys/types.h to get off_t on some systems (Marc Lehmann & QingLong)
+- use constant arrays for the static trees in trees.c instead of computing
+  them at run time (thanks to Ken Raeburn for this suggestion). To create
+  trees.h, compile with GEN_TREES_H and run "make test".
+- check return code of example in "make test" and display result
+- pass minigzip command line options to file_compress
+- simplifying code of inflateSync to avoid gcc 2.8 bug
+
+- support CC="gcc -Wall" in configure -s (QingLong)
+- avoid a flush caused by ftell in gzopen for write mode (Ken Raeburn)
+- fix test for shared library support to avoid compiler warnings
+- zlib.lib -> zlib.dll in msdos/zlib.rc (Gilles Vollant)
+- check for TARGET_OS_MAC in addition to MACOS (Brad Pettit)
+- do not use fdopen for Metrowerks on Mac (Brad Pettit))
+- add checks for gzputc and gzputc in example.c
+- avoid warnings in gzio.c and deflate.c (Andreas Kleinert)
+- use const for the CRC table (Ken Raeburn)
+- fixed "make uninstall" for shared libraries
+- use Tracev instead of Trace in infblock.c
+- in example.c use correct compressed length for test_sync
+- suppress +vnocompatwarnings in configure for HPUX (not always supported)
+
+Changes in 1.0.7 (20 Jan 1998)
+- fix gzseek which was broken in write mode
+- return error for gzseek to negative absolute position
+- fix configure for Linux (Chun-Chung Chen)
+- increase stack space for MSC (Tim Wegner)
+- get_crc_table and inflateSyncPoint are EXPORTed (Gilles Vollant)
+- define EXPORTVA for gzprintf (Gilles Vollant)
+- added man page zlib.3 (Rick Rodgers)
+- for contrib/untgz, fix makedir() and improve Makefile
+
+- check gzseek in write mode in example.c
+- allocate extra buffer for seeks only if gzseek is actually called
+- avoid signed/unsigned comparisons (Tim Wegner, Gilles Vollant)
+- add inflateSyncPoint in zconf.h
+- fix list of exported functions in nt/zlib.dnt and mdsos/zlib.def
+
+Changes in 1.0.6 (19 Jan 1998)
+- add functions gzprintf, gzputc, gzgetc, gztell, gzeof, gzseek, gzrewind and
+  gzsetparams (thanks to Roland Giersig and Kevin Ruland for some of this code)
+- Fix a deflate bug occurring only with compression level 0 (thanks to
+  Andy Buckler for finding this one).
+- In minigzip, pass transparently also the first byte for .Z files.
+- return Z_BUF_ERROR instead of Z_OK if output buffer full in uncompress()
+- check Z_FINISH in inflate (thanks to Marc Schluper)
+- Implement deflateCopy (thanks to Adam Costello)
+- make static libraries by default in configure, add --shared option.
+- move MSDOS or Windows specific files to directory msdos
+- suppress the notion of partial flush to simplify the interface
+  (but the symbol Z_PARTIAL_FLUSH is kept for compatibility with 1.0.4)
+- suppress history buffer provided by application to simplify the interface
+  (this feature was not implemented anyway in 1.0.4)
+- next_in and avail_in must be initialized before calling inflateInit or
+  inflateInit2
+- add EXPORT in all exported functions (for Windows DLL)
+- added Makefile.nt (thanks to Stephen Williams)
+- added the unsupported "contrib" directory:
+   contrib/asm386/ by Gilles Vollant <info@winimage.com>
+        386 asm code replacing longest_match().
+   contrib/iostream/ by Kevin Ruland <kevin@rodin.wustl.edu>
+        A C++ I/O streams interface to the zlib gz* functions
+   contrib/iostream2/  by Tyge Løvset <Tyge.Lovset@cmr.no>
+        Another C++ I/O streams interface
+   contrib/untgz/  by "Pedro A. Aranda Guti\irrez" <paag@tid.es>
+        A very simple tar.gz file extractor using zlib
+   contrib/visual-basic.txt by Carlos Rios <c_rios@sonda.cl>
+        How to use compress(), uncompress() and the gz* functions from VB.
+- pass params -f (filtered data), -h (huffman only), -1 to -9 (compression
+  level) in minigzip (thanks to Tom Lane)
+
+- use const for rommable constants in deflate
+- added test for gzseek and gztell in example.c
+- add undocumented function inflateSyncPoint() (hack for Paul Mackerras)
+- add undocumented function zError to convert error code to string
+  (for Tim Smithers)
+- Allow compilation of gzio with -DNO_DEFLATE to avoid the compression code.
+- Use default memcpy for Symantec MSDOS compiler.
+- Add EXPORT keyword for check_func (needed for Windows DLL)
+- add current directory to LD_LIBRARY_PATH for "make test"
+- create also a link for libz.so.1
+- added support for FUJITSU UXP/DS (thanks to Toshiaki Nomura)
+- use $(SHAREDLIB) instead of libz.so in Makefile.in (for HPUX)
+- added -soname for Linux in configure (Chun-Chung Chen,
+- assign numbers to the exported functions in zlib.def (for Windows DLL)
+- add advice in zlib.h for best usage of deflateSetDictionary
+- work around compiler bug on Atari (cast Z_NULL in call of s->checkfn)
+- allow compilation with ANSI keywords only enabled for TurboC in large model
+- avoid "versionString"[0] (Borland bug)
+- add NEED_DUMMY_RETURN for Borland
+- use variable z_verbose for tracing in debug mode (L. Peter Deutsch).
+- allow compilation with CC
+- defined STDC for OS/2 (David Charlap)
+- limit external names to 8 chars for MVS (Thomas Lund)
+- in minigzip.c, use static buffers only for 16-bit systems
+- fix suffix check for "minigzip -d foo.gz"
+- do not return an error for the 2nd of two consecutive gzflush() (Felix Lee)
+- use _fdopen instead of fdopen for MSC >= 6.0 (Thomas Fanslau)
+- added makelcc.bat for lcc-win32 (Tom St Denis)
+- in Makefile.dj2, use copy and del instead of install and rm (Frank Donahoe)
+- Avoid expanded $Id$. Use "rcs -kb" or "cvs admin -kb" to avoid Id expansion.
+- check for unistd.h in configure (for off_t)
+- remove useless check parameter in inflate_blocks_free
+- avoid useless assignment of s->check to itself in inflate_blocks_new
+- do not flush twice in gzclose (thanks to Ken Raeburn)
+- rename FOPEN as F_OPEN to avoid clash with /usr/include/sys/file.h
+- use NO_ERRNO_H instead of enumeration of operating systems with errno.h
+- work around buggy fclose on pipes for HP/UX
+- support zlib DLL with BORLAND C++ 5.0 (thanks to Glenn Randers-Pehrson)
+- fix configure if CC is already equal to gcc
+
+Changes in 1.0.5 (3 Jan 98)
+- Fix inflate to terminate gracefully when fed corrupted or invalid data
+- Use const for rommable constants in inflate
+- Eliminate memory leaks on error conditions in inflate
+- Removed some vestigial code in inflate
+- Update web address in README
+
+Changes in 1.0.4 (24 Jul 96)
+- In very rare conditions, deflate(s, Z_FINISH) could fail to produce an EOF
+  bit, so the decompressor could decompress all the correct data but went
+  on to attempt decompressing extra garbage data. This affected minigzip too.
+- zlibVersion and gzerror return const char* (needed for DLL)
+- port to RISCOS (no fdopen, no multiple dots, no unlink, no fileno)
+- use z_error only for DEBUG (avoid problem with DLLs)
+
+Changes in 1.0.3 (2 Jul 96)
+- use z_streamp instead of z_stream *, which is now a far pointer in MSDOS
+  small and medium models; this makes the library incompatible with previous
+  versions for these models. (No effect in large model or on other systems.)
+- return OK instead of BUF_ERROR if previous deflate call returned with
+  avail_out as zero but there is nothing to do
+- added memcmp for non STDC compilers
+- define NO_DUMMY_DECL for more Mac compilers (.h files merged incorrectly)
+- define __32BIT__ if __386__ or i386 is defined (pb. with Watcom and SCO)
+- better check for 16-bit mode MSC (avoids problem with Symantec)
+
+Changes in 1.0.2 (23 May 96)
+- added Windows DLL support
+- added a function zlibVersion (for the DLL support)
+- fixed declarations using Bytef in infutil.c (pb with MSDOS medium model)
+- Bytef is define's instead of typedef'd only for Borland C
+- avoid reading uninitialized memory in example.c
+- mention in README that the zlib format is now RFC1950
+- updated Makefile.dj2
+- added algorithm.doc
+
+Changes in 1.0.1 (20 May 96) [1.0 skipped to avoid confusion]
+- fix array overlay in deflate.c which sometimes caused bad compressed data
+- fix inflate bug with empty stored block
+- fix MSDOS medium model which was broken in 0.99
+- fix deflateParams() which could generate bad compressed data.
+- Bytef is define'd instead of typedef'ed (work around Borland bug)
+- added an INDEX file
+- new makefiles for DJGPP (Makefile.dj2), 32-bit Borland (Makefile.b32),
+  Watcom (Makefile.wat), Amiga SAS/C (Makefile.sas)
+- speed up adler32 for modern machines without auto-increment
+- added -ansi for IRIX in configure
+- static_init_done in trees.c is an int
+- define unlink as delete for VMS
+- fix configure for QNX
+- add configure branch for SCO and HPUX
+- avoid many warnings (unused variables, dead assignments, etc...)
+- no fdopen for BeOS
+- fix the Watcom fix for 32 bit mode (define FAR as empty)
+- removed redefinition of Byte for MKWERKS
+- work around an MWKERKS bug (incorrect merge of all .h files)
+
+Changes in 0.99 (27 Jan 96)
+- allow preset dictionary shared between compressor and decompressor
+- allow compression level 0 (no compression)
+- add deflateParams in zlib.h: allow dynamic change of compression level
+  and compression strategy.
+- test large buffers and deflateParams in example.c
+- add optional "configure" to build zlib as a shared library
+- suppress Makefile.qnx, use configure instead
+- fixed deflate for 64-bit systems (detected on Cray)
+- fixed inflate_blocks for 64-bit systems (detected on Alpha)
+- declare Z_DEFLATED in zlib.h (possible parameter for deflateInit2)
+- always return Z_BUF_ERROR when deflate() has nothing to do
+- deflateInit and inflateInit are now macros to allow version checking
+- prefix all global functions and types with z_ with -DZ_PREFIX
+- make falloc completely reentrant (inftrees.c)
+- fixed very unlikely race condition in ct_static_init
+- free in reverse order of allocation to help memory manager
+- use zlib-1.0/* instead of zlib/* inside the tar.gz
+- make zlib warning-free with "gcc -O3 -Wall -Wwrite-strings -Wpointer-arith
+  -Wconversion -Wstrict-prototypes -Wmissing-prototypes"
+- allow gzread on concatenated .gz files
+- deflateEnd now returns Z_DATA_ERROR if it was premature
+- deflate is finally (?) fully deterministic (no matches beyond end of input)
+- Document Z_SYNC_FLUSH
+- add uninstall in Makefile
+- Check for __cpluplus in zlib.h
+- Better test in ct_align for partial flush
+- avoid harmless warnings for Borland C++
+- initialize hash_head in deflate.c
+- avoid warning on fdopen (gzio.c) for HP cc -Aa
+- include stdlib.h for STDC compilers
+- include errno.h for Cray
+- ignore error if ranlib doesn't exist
+- call ranlib twice for NeXTSTEP
+- use exec_prefix instead of prefix for libz.a
+- renamed ct_* as _tr_* to avoid conflict with applications
+- clear z->msg in inflateInit2 before any error return
+- initialize opaque in example.c, gzio.c, deflate.c and inflate.c
+- fixed typo in zconf.h (_GNUC__ => __GNUC__)
+- check for WIN32 in zconf.h and zutil.c (avoid farmalloc in 32-bit mode)
+- fix typo in Make_vms.com (f$trnlnm -> f$getsyi)
+- in fcalloc, normalize pointer if size > 65520 bytes
+- don't use special fcalloc for 32 bit Borland C++
+- use STDC instead of __GO32__ to avoid redeclaring exit, calloc, etc...
+- use Z_BINARY instead of BINARY
+- document that gzclose after gzdopen will close the file
+- allow "a" as mode in gzopen.
+- fix error checking in gzread
+- allow skipping .gz extra-field on pipes
+- added reference to Perl interface in README
+- put the crc table in FAR data (I dislike more and more the medium model :)
+- added get_crc_table
+- added a dimension to all arrays (Borland C can't count).
+- workaround Borland C bug in declaration of inflate_codes_new & inflate_fast
+- guard against multiple inclusion of *.h (for precompiled header on Mac)
+- Watcom C pretends to be Microsoft C small model even in 32 bit mode.
+- don't use unsized arrays to avoid silly warnings by Visual C++:
+     warning C4746: 'inflate_mask' : unsized array treated as  '__far'
+     (what's wrong with far data in far model?).
+- define enum out of inflate_blocks_state to allow compilation with C++
+
+Changes in 0.95 (16 Aug 95)
+- fix MSDOS small and medium model (now easier to adapt to any compiler)
+- inlined send_bits
+- fix the final (:-) bug for deflate with flush (output was correct but
+  not completely flushed in rare occasions).
+- default window size is same for compression and decompression
+  (it's now sufficient to set MAX_WBITS in zconf.h).
+- voidp -> voidpf and voidnp -> voidp (for consistency with other
+  typedefs and because voidnp was not near in large model).
+
+Changes in 0.94 (13 Aug 95)
+- support MSDOS medium model
+- fix deflate with flush (could sometimes generate bad output)
+- fix deflateReset (zlib header was incorrectly suppressed)
+- added support for VMS
+- allow a compression level in gzopen()
+- gzflush now calls fflush
+- For deflate with flush, flush even if no more input is provided.
+- rename libgz.a as libz.a
+- avoid complex expression in infcodes.c triggering Turbo C bug
+- work around a problem with gcc on Alpha (in INSERT_STRING)
+- don't use inline functions (problem with some gcc versions)
+- allow renaming of Byte, uInt, etc... with #define.
+- avoid warning about (unused) pointer before start of array in deflate.c
+- avoid various warnings in gzio.c, example.c, infblock.c, adler32.c, zutil.c
+- avoid reserved word 'new' in trees.c
+
+Changes in 0.93 (25 June 95)
+- temporarily disable inline functions
+- make deflate deterministic
+- give enough lookahead for PARTIAL_FLUSH
+- Set binary mode for stdin/stdout in minigzip.c for OS/2
+- don't even use signed char in inflate (not portable enough)
+- fix inflate memory leak for segmented architectures
+
+Changes in 0.92 (3 May 95)
+- don't assume that char is signed (problem on SGI)
+- Clear bit buffer when starting a stored block
+- no memcpy on Pyramid
+- suppressed inftest.c
+- optimized fill_window, put longest_match inline for gcc
+- optimized inflate on stored blocks.
+- untabify all sources to simplify patches
+
+Changes in 0.91 (2 May 95)
+- Default MEM_LEVEL is 8 (not 9 for Unix) as documented in zlib.h
+- Document the memory requirements in zconf.h
+- added "make install"
+- fix sync search logic in inflateSync
+- deflate(Z_FULL_FLUSH) now works even if output buffer too short
+- after inflateSync, don't scare people with just "lo world"
+- added support for DJGPP
+
+Changes in 0.9 (1 May 95)
+- don't assume that zalloc clears the allocated memory (the TurboC bug
+  was Mark's bug after all :)
+- let again gzread copy uncompressed data unchanged (was working in 0.71)
+- deflate(Z_FULL_FLUSH), inflateReset and inflateSync are now fully implemented
+- added a test of inflateSync in example.c
+- moved MAX_WBITS to zconf.h because users might want to change that.
+- document explicitly that zalloc(64K) on MSDOS must return a normalized
+  pointer (zero offset)
+- added Makefiles for Microsoft C, Turbo C, Borland C++
+- faster crc32()
+
+Changes in 0.8 (29 April 95)
+- added fast inflate (inffast.c)
+- deflate(Z_FINISH) now returns Z_STREAM_END when done. Warning: this
+  is incompatible with previous versions of zlib which returned Z_OK.
+- work around a TurboC compiler bug (bad code for b << 0, see infutil.h)
+  (actually that was not a compiler bug, see 0.81 above)
+- gzread no longer reads one extra byte in certain cases
+- In gzio destroy(), don't reference a freed structure
+- avoid many warnings for MSDOS
+- avoid the ERROR symbol which is used by MS Windows
+
+Changes in 0.71 (14 April 95)
+- Fixed more MSDOS compilation problems :( There is still a bug with
+  TurboC large model.
+
+Changes in 0.7 (14 April 95)
+- Added full inflate support.
+- Simplified the crc32() interface. The pre- and post-conditioning
+  (one's complement) is now done inside crc32(). WARNING: this is
+  incompatible with previous versions; see zlib.h for the new usage.
+
+Changes in 0.61 (12 April 95)
+- workaround for a bug in TurboC. example and minigzip now work on MSDOS.
+
+Changes in 0.6 (11 April 95)
+- added minigzip.c
+- added gzdopen to reopen a file descriptor as gzFile
+- added transparent reading of non-gziped files in gzread.
+- fixed bug in gzread (don't read crc as data)
+- fixed bug in destroy (gzio.c) (don't return Z_STREAM_END for gzclose).
+- don't allocate big arrays in the stack (for MSDOS)
+- fix some MSDOS compilation problems
+
+Changes in 0.5:
+- do real compression in deflate.c. Z_PARTIAL_FLUSH is supported but
+  not yet Z_FULL_FLUSH.
+- support decompression but only in a single step (forced Z_FINISH)
+- added opaque object for zalloc and zfree.
+- added deflateReset and inflateReset
+- added a variable zlib_version for consistency checking.
+- renamed the 'filter' parameter of deflateInit2 as 'strategy'.
+  Added Z_FILTERED and Z_HUFFMAN_ONLY constants.
+
+Changes in 0.4:
+- avoid "zip" everywhere, use zlib instead of ziplib.
+- suppress Z_BLOCK_FLUSH, interpret Z_PARTIAL_FLUSH as block flush
+  if compression method == 8.
+- added adler32 and crc32
+- renamed deflateOptions as deflateInit2, call one or the other but not both
+- added the method parameter for deflateInit2.
+- added inflateInit2
+- simplied considerably deflateInit and inflateInit by not supporting
+  user-provided history buffer. This is supported only in deflateInit2
+  and inflateInit2.
+
+Changes in 0.3:
+- prefix all macro names with Z_
+- use Z_FINISH instead of deflateEnd to finish compression.
+- added Z_HUFFMAN_ONLY
+- added gzerror()

ADDED   3rd_party/zlib/FAQ
Index: 3rd_party/zlib/FAQ
==================================================================
--- 3rd_party/zlib/FAQ
+++ 3rd_party/zlib/FAQ
@@ -0,0 +1,368 @@
+
+                Frequently Asked Questions about zlib
+
+
+If your question is not there, please check the zlib home page
+http://zlib.net/ which may have more recent information.
+The lastest zlib FAQ is at http://zlib.net/zlib_faq.html
+
+
+ 1. Is zlib Y2K-compliant?
+
+    Yes. zlib doesn't handle dates.
+
+ 2. Where can I get a Windows DLL version?
+
+    The zlib sources can be compiled without change to produce a DLL.  See the
+    file win32/DLL_FAQ.txt in the zlib distribution.  Pointers to the
+    precompiled DLL are found in the zlib web site at http://zlib.net/ .
+
+ 3. Where can I get a Visual Basic interface to zlib?
+
+    See
+        * http://marknelson.us/1997/01/01/zlib-engine/
+        * win32/DLL_FAQ.txt in the zlib distribution
+
+ 4. compress() returns Z_BUF_ERROR.
+
+    Make sure that before the call of compress(), the length of the compressed
+    buffer is equal to the available size of the compressed buffer and not
+    zero.  For Visual Basic, check that this parameter is passed by reference
+    ("as any"), not by value ("as long").
+
+ 5. deflate() or inflate() returns Z_BUF_ERROR.
+
+    Before making the call, make sure that avail_in and avail_out are not zero.
+    When setting the parameter flush equal to Z_FINISH, also make sure that
+    avail_out is big enough to allow processing all pending input.  Note that a
+    Z_BUF_ERROR is not fatal--another call to deflate() or inflate() can be
+    made with more input or output space.  A Z_BUF_ERROR may in fact be
+    unavoidable depending on how the functions are used, since it is not
+    possible to tell whether or not there is more output pending when
+    strm.avail_out returns with zero.  See http://zlib.net/zlib_how.html for a
+    heavily annotated example.
+
+ 6. Where's the zlib documentation (man pages, etc.)?
+
+    It's in zlib.h .  Examples of zlib usage are in the files test/example.c
+    and test/minigzip.c, with more in examples/ .
+
+ 7. Why don't you use GNU autoconf or libtool or ...?
+
+    Because we would like to keep zlib as a very small and simple package.
+    zlib is rather portable and doesn't need much configuration.
+
+ 8. I found a bug in zlib.
+
+    Most of the time, such problems are due to an incorrect usage of zlib.
+    Please try to reproduce the problem with a small program and send the
+    corresponding source to us at zlib@gzip.org .  Do not send multi-megabyte
+    data files without prior agreement.
+
+ 9. Why do I get "undefined reference to gzputc"?
+
+    If "make test" produces something like
+
+       example.o(.text+0x154): undefined reference to `gzputc'
+
+    check that you don't have old files libz.* in /usr/lib, /usr/local/lib or
+    /usr/X11R6/lib. Remove any old versions, then do "make install".
+
+10. I need a Delphi interface to zlib.
+
+    See the contrib/delphi directory in the zlib distribution.
+
+11. Can zlib handle .zip archives?
+
+    Not by itself, no.  See the directory contrib/minizip in the zlib
+    distribution.
+
+12. Can zlib handle .Z files?
+
+    No, sorry.  You have to spawn an uncompress or gunzip subprocess, or adapt
+    the code of uncompress on your own.
+
+13. How can I make a Unix shared library?
+
+    By default a shared (and a static) library is built for Unix.  So:
+
+    make distclean
+    ./configure
+    make
+
+14. How do I install a shared zlib library on Unix?
+
+    After the above, then:
+
+    make install
+
+    However, many flavors of Unix come with a shared zlib already installed.
+    Before going to the trouble of compiling a shared version of zlib and
+    trying to install it, you may want to check if it's already there!  If you
+    can #include <zlib.h>, it's there.  The -lz option will probably link to
+    it.  You can check the version at the top of zlib.h or with the
+    ZLIB_VERSION symbol defined in zlib.h .
+
+15. I have a question about OttoPDF.
+
+    We are not the authors of OttoPDF. The real author is on the OttoPDF web
+    site: Joel Hainley, jhainley@myndkryme.com.
+
+16. Can zlib decode Flate data in an Adobe PDF file?
+
+    Yes. See http://www.pdflib.com/ . To modify PDF forms, see
+    http://sourceforge.net/projects/acroformtool/ .
+
+17. Why am I getting this "register_frame_info not found" error on Solaris?
+
+    After installing zlib 1.1.4 on Solaris 2.6, running applications using zlib
+    generates an error such as:
+
+        ld.so.1: rpm: fatal: relocation error: file /usr/local/lib/libz.so:
+        symbol __register_frame_info: referenced symbol not found
+
+    The symbol __register_frame_info is not part of zlib, it is generated by
+    the C compiler (cc or gcc).  You must recompile applications using zlib
+    which have this problem.  This problem is specific to Solaris.  See
+    http://www.sunfreeware.com for Solaris versions of zlib and applications
+    using zlib.
+
+18. Why does gzip give an error on a file I make with compress/deflate?
+
+    The compress and deflate functions produce data in the zlib format, which
+    is different and incompatible with the gzip format.  The gz* functions in
+    zlib on the other hand use the gzip format.  Both the zlib and gzip formats
+    use the same compressed data format internally, but have different headers
+    and trailers around the compressed data.
+
+19. Ok, so why are there two different formats?
+
+    The gzip format was designed to retain the directory information about a
+    single file, such as the name and last modification date.  The zlib format
+    on the other hand was designed for in-memory and communication channel
+    applications, and has a much more compact header and trailer and uses a
+    faster integrity check than gzip.
+
+20. Well that's nice, but how do I make a gzip file in memory?
+
+    You can request that deflate write the gzip format instead of the zlib
+    format using deflateInit2().  You can also request that inflate decode the
+    gzip format using inflateInit2().  Read zlib.h for more details.
+
+21. Is zlib thread-safe?
+
+    Yes.  However any library routines that zlib uses and any application-
+    provided memory allocation routines must also be thread-safe.  zlib's gz*
+    functions use stdio library routines, and most of zlib's functions use the
+    library memory allocation routines by default.  zlib's *Init* functions
+    allow for the application to provide custom memory allocation routines.
+
+    Of course, you should only operate on any given zlib or gzip stream from a
+    single thread at a time.
+
+22. Can I use zlib in my commercial application?
+
+    Yes.  Please read the license in zlib.h.
+
+23. Is zlib under the GNU license?
+
+    No.  Please read the license in zlib.h.
+
+24. The license says that altered source versions must be "plainly marked". So
+    what exactly do I need to do to meet that requirement?
+
+    You need to change the ZLIB_VERSION and ZLIB_VERNUM #defines in zlib.h.  In
+    particular, the final version number needs to be changed to "f", and an
+    identification string should be appended to ZLIB_VERSION.  Version numbers
+    x.x.x.f are reserved for modifications to zlib by others than the zlib
+    maintainers.  For example, if the version of the base zlib you are altering
+    is "1.2.3.4", then in zlib.h you should change ZLIB_VERNUM to 0x123f, and
+    ZLIB_VERSION to something like "1.2.3.f-zachary-mods-v3".  You can also
+    update the version strings in deflate.c and inftrees.c.
+
+    For altered source distributions, you should also note the origin and
+    nature of the changes in zlib.h, as well as in ChangeLog and README, along
+    with the dates of the alterations.  The origin should include at least your
+    name (or your company's name), and an email address to contact for help or
+    issues with the library.
+
+    Note that distributing a compiled zlib library along with zlib.h and
+    zconf.h is also a source distribution, and so you should change
+    ZLIB_VERSION and ZLIB_VERNUM and note the origin and nature of the changes
+    in zlib.h as you would for a full source distribution.
+
+25. Will zlib work on a big-endian or little-endian architecture, and can I
+    exchange compressed data between them?
+
+    Yes and yes.
+
+26. Will zlib work on a 64-bit machine?
+
+    Yes.  It has been tested on 64-bit machines, and has no dependence on any
+    data types being limited to 32-bits in length.  If you have any
+    difficulties, please provide a complete problem report to zlib@gzip.org
+
+27. Will zlib decompress data from the PKWare Data Compression Library?
+
+    No.  The PKWare DCL uses a completely different compressed data format than
+    does PKZIP and zlib.  However, you can look in zlib's contrib/blast
+    directory for a possible solution to your problem.
+
+28. Can I access data randomly in a compressed stream?
+
+    No, not without some preparation.  If when compressing you periodically use
+    Z_FULL_FLUSH, carefully write all the pending data at those points, and
+    keep an index of those locations, then you can start decompression at those
+    points.  You have to be careful to not use Z_FULL_FLUSH too often, since it
+    can significantly degrade compression.  Alternatively, you can scan a
+    deflate stream once to generate an index, and then use that index for
+    random access.  See examples/zran.c .
+
+29. Does zlib work on MVS, OS/390, CICS, etc.?
+
+    It has in the past, but we have not heard of any recent evidence.  There
+    were working ports of zlib 1.1.4 to MVS, but those links no longer work.
+    If you know of recent, successful applications of zlib on these operating
+    systems, please let us know.  Thanks.
+
+30. Is there some simpler, easier to read version of inflate I can look at to
+    understand the deflate format?
+
+    First off, you should read RFC 1951.  Second, yes.  Look in zlib's
+    contrib/puff directory.
+
+31. Does zlib infringe on any patents?
+
+    As far as we know, no.  In fact, that was originally the whole point behind
+    zlib.  Look here for some more information:
+
+    http://www.gzip.org/#faq11
+
+32. Can zlib work with greater than 4 GB of data?
+
+    Yes.  inflate() and deflate() will process any amount of data correctly.
+    Each call of inflate() or deflate() is limited to input and output chunks
+    of the maximum value that can be stored in the compiler's "unsigned int"
+    type, but there is no limit to the number of chunks.  Note however that the
+    strm.total_in and strm_total_out counters may be limited to 4 GB.  These
+    counters are provided as a convenience and are not used internally by
+    inflate() or deflate().  The application can easily set up its own counters
+    updated after each call of inflate() or deflate() to count beyond 4 GB.
+    compress() and uncompress() may be limited to 4 GB, since they operate in a
+    single call.  gzseek() and gztell() may be limited to 4 GB depending on how
+    zlib is compiled.  See the zlibCompileFlags() function in zlib.h.
+
+    The word "may" appears several times above since there is a 4 GB limit only
+    if the compiler's "long" type is 32 bits.  If the compiler's "long" type is
+    64 bits, then the limit is 16 exabytes.
+
+33. Does zlib have any security vulnerabilities?
+
+    The only one that we are aware of is potentially in gzprintf().  If zlib is
+    compiled to use sprintf() or vsprintf(), then there is no protection
+    against a buffer overflow of an 8K string space (or other value as set by
+    gzbuffer()), other than the caller of gzprintf() assuring that the output
+    will not exceed 8K.  On the other hand, if zlib is compiled to use
+    snprintf() or vsnprintf(), which should normally be the case, then there is
+    no vulnerability.  The ./configure script will display warnings if an
+    insecure variation of sprintf() will be used by gzprintf().  Also the
+    zlibCompileFlags() function will return information on what variant of
+    sprintf() is used by gzprintf().
+
+    If you don't have snprintf() or vsnprintf() and would like one, you can
+    find a portable implementation here:
+
+        http://www.ijs.si/software/snprintf/
+
+    Note that you should be using the most recent version of zlib.  Versions
+    1.1.3 and before were subject to a double-free vulnerability, and versions
+    1.2.1 and 1.2.2 were subject to an access exception when decompressing
+    invalid compressed data.
+
+34. Is there a Java version of zlib?
+
+    Probably what you want is to use zlib in Java. zlib is already included
+    as part of the Java SDK in the java.util.zip package. If you really want
+    a version of zlib written in the Java language, look on the zlib home
+    page for links: http://zlib.net/ .
+
+35. I get this or that compiler or source-code scanner warning when I crank it
+    up to maximally-pedantic. Can't you guys write proper code?
+
+    Many years ago, we gave up attempting to avoid warnings on every compiler
+    in the universe.  It just got to be a waste of time, and some compilers
+    were downright silly as well as contradicted each other.  So now, we simply
+    make sure that the code always works.
+
+36. Valgrind (or some similar memory access checker) says that deflate is
+    performing a conditional jump that depends on an uninitialized value.
+    Isn't that a bug?
+
+    No.  That is intentional for performance reasons, and the output of deflate
+    is not affected.  This only started showing up recently since zlib 1.2.x
+    uses malloc() by default for allocations, whereas earlier versions used
+    calloc(), which zeros out the allocated memory.  Even though the code was
+    correct, versions 1.2.4 and later was changed to not stimulate these
+    checkers.
+
+37. Will zlib read the (insert any ancient or arcane format here) compressed
+    data format?
+
+    Probably not. Look in the comp.compression FAQ for pointers to various
+    formats and associated software.
+
+38. How can I encrypt/decrypt zip files with zlib?
+
+    zlib doesn't support encryption.  The original PKZIP encryption is very
+    weak and can be broken with freely available programs.  To get strong
+    encryption, use GnuPG, http://www.gnupg.org/ , which already includes zlib
+    compression.  For PKZIP compatible "encryption", look at
+    http://www.info-zip.org/
+
+39. What's the difference between the "gzip" and "deflate" HTTP 1.1 encodings?
+
+    "gzip" is the gzip format, and "deflate" is the zlib format.  They should
+    probably have called the second one "zlib" instead to avoid confusion with
+    the raw deflate compressed data format.  While the HTTP 1.1 RFC 2616
+    correctly points to the zlib specification in RFC 1950 for the "deflate"
+    transfer encoding, there have been reports of servers and browsers that
+    incorrectly produce or expect raw deflate data per the deflate
+    specification in RFC 1951, most notably Microsoft.  So even though the
+    "deflate" transfer encoding using the zlib format would be the more
+    efficient approach (and in fact exactly what the zlib format was designed
+    for), using the "gzip" transfer encoding is probably more reliable due to
+    an unfortunate choice of name on the part of the HTTP 1.1 authors.
+
+    Bottom line: use the gzip format for HTTP 1.1 encoding.
+
+40. Does zlib support the new "Deflate64" format introduced by PKWare?
+
+    No.  PKWare has apparently decided to keep that format proprietary, since
+    they have not documented it as they have previous compression formats.  In
+    any case, the compression improvements are so modest compared to other more
+    modern approaches, that it's not worth the effort to implement.
+
+41. I'm having a problem with the zip functions in zlib, can you help?
+
+    There are no zip functions in zlib.  You are probably using minizip by
+    Giles Vollant, which is found in the contrib directory of zlib.  It is not
+    part of zlib.  In fact none of the stuff in contrib is part of zlib.  The
+    files in there are not supported by the zlib authors.  You need to contact
+    the authors of the respective contribution for help.
+
+42. The match.asm code in contrib is under the GNU General Public License.
+    Since it's part of zlib, doesn't that mean that all of zlib falls under the
+    GNU GPL?
+
+    No.  The files in contrib are not part of zlib.  They were contributed by
+    other authors and are provided as a convenience to the user within the zlib
+    distribution.  Each item in contrib has its own license.
+
+43. Is zlib subject to export controls?  What is its ECCN?
+
+    zlib is not subject to export controls, and so is classified as EAR99.
+
+44. Can you please sign these lengthy legal documents and fax them back to us
+    so that we can use your software in our product?
+
+    No. Go away. Shoo.

ADDED   3rd_party/zlib/INDEX
Index: 3rd_party/zlib/INDEX
==================================================================
--- 3rd_party/zlib/INDEX
+++ 3rd_party/zlib/INDEX
@@ -0,0 +1,68 @@
+CMakeLists.txt  cmake build file
+ChangeLog       history of changes
+FAQ             Frequently Asked Questions about zlib
+INDEX           this file
+Makefile        dummy Makefile that tells you to ./configure
+Makefile.in     template for Unix Makefile
+README          guess what
+configure       configure script for Unix
+make_vms.com    makefile for VMS
+test/example.c  zlib usages examples for build testing
+test/minigzip.c minimal gzip-like functionality for build testing
+test/infcover.c inf*.c code coverage for build coverage testing
+treebuild.xml   XML description of source file dependencies
+zconf.h.cmakein zconf.h template for cmake
+zconf.h.in      zconf.h template for configure
+zlib.3          Man page for zlib
+zlib.3.pdf      Man page in PDF format
+zlib.map        Linux symbol information
+zlib.pc.in      Template for pkg-config descriptor
+zlib.pc.cmakein zlib.pc template for cmake
+zlib2ansi       perl script to convert source files for C++ compilation
+
+amiga/          makefiles for Amiga SAS C
+as400/          makefiles for AS/400
+doc/            documentation for formats and algorithms
+msdos/          makefiles for MSDOS
+nintendods/     makefile for Nintendo DS
+old/            makefiles for various architectures and zlib documentation
+                files that have not yet been updated for zlib 1.2.x
+qnx/            makefiles for QNX
+watcom/         makefiles for OpenWatcom
+win32/          makefiles for Windows
+
+                zlib public header files (required for library use):
+zconf.h
+zlib.h
+
+                private source files used to build the zlib library:
+adler32.c
+compress.c
+crc32.c
+crc32.h
+deflate.c
+deflate.h
+gzclose.c
+gzguts.h
+gzlib.c
+gzread.c
+gzwrite.c
+infback.c
+inffast.c
+inffast.h
+inffixed.h
+inflate.c
+inflate.h
+inftrees.c
+inftrees.h
+trees.c
+trees.h
+uncompr.c
+zutil.c
+zutil.h
+
+                source files for sample programs
+See examples/README.examples
+
+                unsupported contributions by third parties
+See contrib/README.contrib

ADDED   3rd_party/zlib/Makefile
Index: 3rd_party/zlib/Makefile
==================================================================
--- 3rd_party/zlib/Makefile
+++ 3rd_party/zlib/Makefile
@@ -0,0 +1,5 @@
+all:
+	-@echo "Please use ./configure first.  Thank you."
+
+distclean:
+	make -f Makefile.in distclean

ADDED   3rd_party/zlib/Makefile.in
Index: 3rd_party/zlib/Makefile.in
==================================================================
--- 3rd_party/zlib/Makefile.in
+++ 3rd_party/zlib/Makefile.in
@@ -0,0 +1,410 @@
+# Makefile for zlib
+# Copyright (C) 1995-2017 Jean-loup Gailly, Mark Adler
+# For conditions of distribution and use, see copyright notice in zlib.h
+
+# To compile and test, type:
+#    ./configure; make test
+# Normally configure builds both a static and a shared library.
+# If you want to build just a static library, use: ./configure --static
+
+# To use the asm code, type:
+#    cp contrib/asm?86/match.S ./match.S
+#    make LOC=-DASMV OBJA=match.o
+
+# To install /usr/local/lib/libz.* and /usr/local/include/zlib.h, type:
+#    make install
+# To install in $HOME instead of /usr/local, use:
+#    make install prefix=$HOME
+
+CC=cc
+
+CFLAGS=-O
+#CFLAGS=-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7
+#CFLAGS=-g -DZLIB_DEBUG
+#CFLAGS=-O3 -Wall -Wwrite-strings -Wpointer-arith -Wconversion \
+#           -Wstrict-prototypes -Wmissing-prototypes
+
+SFLAGS=-O
+LDFLAGS=
+TEST_LDFLAGS=-L. libz.a
+LDSHARED=$(CC)
+CPP=$(CC) -E
+
+STATICLIB=libz.a
+SHAREDLIB=libz.so
+SHAREDLIBV=libz.so.1.2.11
+SHAREDLIBM=libz.so.1
+LIBS=$(STATICLIB) $(SHAREDLIBV)
+
+AR=ar
+ARFLAGS=rc
+RANLIB=ranlib
+LDCONFIG=ldconfig
+LDSHAREDLIBC=-lc
+TAR=tar
+SHELL=/bin/sh
+EXE=
+
+prefix = /usr/local
+exec_prefix = ${prefix}
+libdir = ${exec_prefix}/lib
+sharedlibdir = ${libdir}
+includedir = ${prefix}/include
+mandir = ${prefix}/share/man
+man3dir = ${mandir}/man3
+pkgconfigdir = ${libdir}/pkgconfig
+SRCDIR=
+ZINC=
+ZINCOUT=-I.
+
+OBJZ = adler32.o crc32.o deflate.o infback.o inffast.o inflate.o inftrees.o trees.o zutil.o
+OBJG = compress.o uncompr.o gzclose.o gzlib.o gzread.o gzwrite.o
+OBJC = $(OBJZ) $(OBJG)
+
+PIC_OBJZ = adler32.lo crc32.lo deflate.lo infback.lo inffast.lo inflate.lo inftrees.lo trees.lo zutil.lo
+PIC_OBJG = compress.lo uncompr.lo gzclose.lo gzlib.lo gzread.lo gzwrite.lo
+PIC_OBJC = $(PIC_OBJZ) $(PIC_OBJG)
+
+# to use the asm code: make OBJA=match.o, PIC_OBJA=match.lo
+OBJA =
+PIC_OBJA =
+
+OBJS = $(OBJC) $(OBJA)
+
+PIC_OBJS = $(PIC_OBJC) $(PIC_OBJA)
+
+all: static shared
+
+static: example$(EXE) minigzip$(EXE)
+
+shared: examplesh$(EXE) minigzipsh$(EXE)
+
+all64: example64$(EXE) minigzip64$(EXE)
+
+check: test
+
+test: all teststatic testshared
+
+teststatic: static
+	@TMPST=tmpst_$$; \
+	if echo hello world | ./minigzip | ./minigzip -d && ./example $$TMPST ; then \
+	  echo '		*** zlib test OK ***'; \
+	else \
+	  echo '		*** zlib test FAILED ***'; false; \
+	fi; \
+	rm -f $$TMPST
+
+testshared: shared
+	@LD_LIBRARY_PATH=`pwd`:$(LD_LIBRARY_PATH) ; export LD_LIBRARY_PATH; \
+	LD_LIBRARYN32_PATH=`pwd`:$(LD_LIBRARYN32_PATH) ; export LD_LIBRARYN32_PATH; \
+	DYLD_LIBRARY_PATH=`pwd`:$(DYLD_LIBRARY_PATH) ; export DYLD_LIBRARY_PATH; \
+	SHLIB_PATH=`pwd`:$(SHLIB_PATH) ; export SHLIB_PATH; \
+	TMPSH=tmpsh_$$; \
+	if echo hello world | ./minigzipsh | ./minigzipsh -d && ./examplesh $$TMPSH; then \
+	  echo '		*** zlib shared test OK ***'; \
+	else \
+	  echo '		*** zlib shared test FAILED ***'; false; \
+	fi; \
+	rm -f $$TMPSH
+
+test64: all64
+	@TMP64=tmp64_$$; \
+	if echo hello world | ./minigzip64 | ./minigzip64 -d && ./example64 $$TMP64; then \
+	  echo '		*** zlib 64-bit test OK ***'; \
+	else \
+	  echo '		*** zlib 64-bit test FAILED ***'; false; \
+	fi; \
+	rm -f $$TMP64
+
+infcover.o: $(SRCDIR)test/infcover.c $(SRCDIR)zlib.h zconf.h
+	$(CC) $(CFLAGS) $(ZINCOUT) -c -o $@ $(SRCDIR)test/infcover.c
+
+infcover: infcover.o libz.a
+	$(CC) $(CFLAGS) -o $@ infcover.o libz.a
+
+cover: infcover
+	rm -f *.gcda
+	./infcover
+	gcov inf*.c
+
+libz.a: $(OBJS)
+	$(AR) $(ARFLAGS) $@ $(OBJS)
+	-@ ($(RANLIB) $@ || true) >/dev/null 2>&1
+
+match.o: match.S
+	$(CPP) match.S > _match.s
+	$(CC) -c _match.s
+	mv _match.o match.o
+	rm -f _match.s
+
+match.lo: match.S
+	$(CPP) match.S > _match.s
+	$(CC) -c -fPIC _match.s
+	mv _match.o match.lo
+	rm -f _match.s
+
+example.o: $(SRCDIR)test/example.c $(SRCDIR)zlib.h zconf.h
+	$(CC) $(CFLAGS) $(ZINCOUT) -c -o $@ $(SRCDIR)test/example.c
+
+minigzip.o: $(SRCDIR)test/minigzip.c $(SRCDIR)zlib.h zconf.h
+	$(CC) $(CFLAGS) $(ZINCOUT) -c -o $@ $(SRCDIR)test/minigzip.c
+
+example64.o: $(SRCDIR)test/example.c $(SRCDIR)zlib.h zconf.h
+	$(CC) $(CFLAGS) $(ZINCOUT) -D_FILE_OFFSET_BITS=64 -c -o $@ $(SRCDIR)test/example.c
+
+minigzip64.o: $(SRCDIR)test/minigzip.c $(SRCDIR)zlib.h zconf.h
+	$(CC) $(CFLAGS) $(ZINCOUT) -D_FILE_OFFSET_BITS=64 -c -o $@ $(SRCDIR)test/minigzip.c
+
+
+adler32.o: $(SRCDIR)adler32.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)adler32.c
+
+crc32.o: $(SRCDIR)crc32.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)crc32.c
+
+deflate.o: $(SRCDIR)deflate.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)deflate.c
+
+infback.o: $(SRCDIR)infback.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)infback.c
+
+inffast.o: $(SRCDIR)inffast.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)inffast.c
+
+inflate.o: $(SRCDIR)inflate.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)inflate.c
+
+inftrees.o: $(SRCDIR)inftrees.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)inftrees.c
+
+trees.o: $(SRCDIR)trees.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)trees.c
+
+zutil.o: $(SRCDIR)zutil.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)zutil.c
+
+compress.o: $(SRCDIR)compress.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)compress.c
+
+uncompr.o: $(SRCDIR)uncompr.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)uncompr.c
+
+gzclose.o: $(SRCDIR)gzclose.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)gzclose.c
+
+gzlib.o: $(SRCDIR)gzlib.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)gzlib.c
+
+gzread.o: $(SRCDIR)gzread.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)gzread.c
+
+gzwrite.o: $(SRCDIR)gzwrite.c
+	$(CC) $(CFLAGS) $(ZINC) -c -o $@ $(SRCDIR)gzwrite.c
+
+
+adler32.lo: $(SRCDIR)adler32.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/adler32.o $(SRCDIR)adler32.c
+	-@mv objs/adler32.o $@
+
+crc32.lo: $(SRCDIR)crc32.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/crc32.o $(SRCDIR)crc32.c
+	-@mv objs/crc32.o $@
+
+deflate.lo: $(SRCDIR)deflate.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/deflate.o $(SRCDIR)deflate.c
+	-@mv objs/deflate.o $@
+
+infback.lo: $(SRCDIR)infback.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/infback.o $(SRCDIR)infback.c
+	-@mv objs/infback.o $@
+
+inffast.lo: $(SRCDIR)inffast.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/inffast.o $(SRCDIR)inffast.c
+	-@mv objs/inffast.o $@
+
+inflate.lo: $(SRCDIR)inflate.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/inflate.o $(SRCDIR)inflate.c
+	-@mv objs/inflate.o $@
+
+inftrees.lo: $(SRCDIR)inftrees.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/inftrees.o $(SRCDIR)inftrees.c
+	-@mv objs/inftrees.o $@
+
+trees.lo: $(SRCDIR)trees.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/trees.o $(SRCDIR)trees.c
+	-@mv objs/trees.o $@
+
+zutil.lo: $(SRCDIR)zutil.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/zutil.o $(SRCDIR)zutil.c
+	-@mv objs/zutil.o $@
+
+compress.lo: $(SRCDIR)compress.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/compress.o $(SRCDIR)compress.c
+	-@mv objs/compress.o $@
+
+uncompr.lo: $(SRCDIR)uncompr.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/uncompr.o $(SRCDIR)uncompr.c
+	-@mv objs/uncompr.o $@
+
+gzclose.lo: $(SRCDIR)gzclose.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/gzclose.o $(SRCDIR)gzclose.c
+	-@mv objs/gzclose.o $@
+
+gzlib.lo: $(SRCDIR)gzlib.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/gzlib.o $(SRCDIR)gzlib.c
+	-@mv objs/gzlib.o $@
+
+gzread.lo: $(SRCDIR)gzread.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/gzread.o $(SRCDIR)gzread.c
+	-@mv objs/gzread.o $@
+
+gzwrite.lo: $(SRCDIR)gzwrite.c
+	-@mkdir objs 2>/dev/null || test -d objs
+	$(CC) $(SFLAGS) $(ZINC) -DPIC -c -o objs/gzwrite.o $(SRCDIR)gzwrite.c
+	-@mv objs/gzwrite.o $@
+
+
+placebo $(SHAREDLIBV): $(PIC_OBJS) libz.a
+	$(LDSHARED) $(SFLAGS) -o $@ $(PIC_OBJS) $(LDSHAREDLIBC) $(LDFLAGS)
+	rm -f $(SHAREDLIB) $(SHAREDLIBM)
+	ln -s $@ $(SHAREDLIB)
+	ln -s $@ $(SHAREDLIBM)
+	-@rmdir objs
+
+example$(EXE): example.o $(STATICLIB)
+	$(CC) $(CFLAGS) -o $@ example.o $(TEST_LDFLAGS)
+
+minigzip$(EXE): minigzip.o $(STATICLIB)
+	$(CC) $(CFLAGS) -o $@ minigzip.o $(TEST_LDFLAGS)
+
+examplesh$(EXE): example.o $(SHAREDLIBV)
+	$(CC) $(CFLAGS) -o $@ example.o -L. $(SHAREDLIBV)
+
+minigzipsh$(EXE): minigzip.o $(SHAREDLIBV)
+	$(CC) $(CFLAGS) -o $@ minigzip.o -L. $(SHAREDLIBV)
+
+example64$(EXE): example64.o $(STATICLIB)
+	$(CC) $(CFLAGS) -o $@ example64.o $(TEST_LDFLAGS)
+
+minigzip64$(EXE): minigzip64.o $(STATICLIB)
+	$(CC) $(CFLAGS) -o $@ minigzip64.o $(TEST_LDFLAGS)
+
+install-libs: $(LIBS)
+	-@if [ ! -d $(DESTDIR)$(exec_prefix)  ]; then mkdir -p $(DESTDIR)$(exec_prefix); fi
+	-@if [ ! -d $(DESTDIR)$(libdir)       ]; then mkdir -p $(DESTDIR)$(libdir); fi
+	-@if [ ! -d $(DESTDIR)$(sharedlibdir) ]; then mkdir -p $(DESTDIR)$(sharedlibdir); fi
+	-@if [ ! -d $(DESTDIR)$(man3dir)      ]; then mkdir -p $(DESTDIR)$(man3dir); fi
+	-@if [ ! -d $(DESTDIR)$(pkgconfigdir) ]; then mkdir -p $(DESTDIR)$(pkgconfigdir); fi
+	rm -f $(DESTDIR)$(libdir)/$(STATICLIB)
+	cp $(STATICLIB) $(DESTDIR)$(libdir)
+	chmod 644 $(DESTDIR)$(libdir)/$(STATICLIB)
+	-@($(RANLIB) $(DESTDIR)$(libdir)/libz.a || true) >/dev/null 2>&1
+	-@if test -n "$(SHAREDLIBV)"; then \
+	  rm -f $(DESTDIR)$(sharedlibdir)/$(SHAREDLIBV); \
+	  cp $(SHAREDLIBV) $(DESTDIR)$(sharedlibdir); \
+	  echo "cp $(SHAREDLIBV) $(DESTDIR)$(sharedlibdir)"; \
+	  chmod 755 $(DESTDIR)$(sharedlibdir)/$(SHAREDLIBV); \
+	  echo "chmod 755 $(DESTDIR)$(sharedlibdir)/$(SHAREDLIBV)"; \
+	  rm -f $(DESTDIR)$(sharedlibdir)/$(SHAREDLIB) $(DESTDIR)$(sharedlibdir)/$(SHAREDLIBM); \
+	  ln -s $(SHAREDLIBV) $(DESTDIR)$(sharedlibdir)/$(SHAREDLIB); \
+	  ln -s $(SHAREDLIBV) $(DESTDIR)$(sharedlibdir)/$(SHAREDLIBM); \
+	  ($(LDCONFIG) || true)  >/dev/null 2>&1; \
+	fi
+	rm -f $(DESTDIR)$(man3dir)/zlib.3
+	cp $(SRCDIR)zlib.3 $(DESTDIR)$(man3dir)
+	chmod 644 $(DESTDIR)$(man3dir)/zlib.3
+	rm -f $(DESTDIR)$(pkgconfigdir)/zlib.pc
+	cp zlib.pc $(DESTDIR)$(pkgconfigdir)
+	chmod 644 $(DESTDIR)$(pkgconfigdir)/zlib.pc
+# The ranlib in install is needed on NeXTSTEP which checks file times
+# ldconfig is for Linux
+
+install: install-libs
+	-@if [ ! -d $(DESTDIR)$(includedir)   ]; then mkdir -p $(DESTDIR)$(includedir); fi
+	rm -f $(DESTDIR)$(includedir)/zlib.h $(DESTDIR)$(includedir)/zconf.h
+	cp $(SRCDIR)zlib.h zconf.h $(DESTDIR)$(includedir)
+	chmod 644 $(DESTDIR)$(includedir)/zlib.h $(DESTDIR)$(includedir)/zconf.h
+
+uninstall:
+	cd $(DESTDIR)$(includedir) && rm -f zlib.h zconf.h
+	cd $(DESTDIR)$(libdir) && rm -f libz.a; \
+	if test -n "$(SHAREDLIBV)" -a -f $(SHAREDLIBV); then \
+	  rm -f $(SHAREDLIBV) $(SHAREDLIB) $(SHAREDLIBM); \
+	fi
+	cd $(DESTDIR)$(man3dir) && rm -f zlib.3
+	cd $(DESTDIR)$(pkgconfigdir) && rm -f zlib.pc
+
+docs: zlib.3.pdf
+
+zlib.3.pdf: $(SRCDIR)zlib.3
+	groff -mandoc -f H -T ps $(SRCDIR)zlib.3 | ps2pdf - $@
+
+zconf.h.cmakein: $(SRCDIR)zconf.h.in
+	-@ TEMPFILE=zconfh_$$; \
+	echo "/#define ZCONF_H/ a\\\\\n#cmakedefine Z_PREFIX\\\\\n#cmakedefine Z_HAVE_UNISTD_H\n" >> $$TEMPFILE &&\
+	sed -f $$TEMPFILE $(SRCDIR)zconf.h.in > $@ &&\
+	touch -r $(SRCDIR)zconf.h.in $@ &&\
+	rm $$TEMPFILE
+
+zconf: $(SRCDIR)zconf.h.in
+	cp -p $(SRCDIR)zconf.h.in zconf.h
+
+mostlyclean: clean
+clean:
+	rm -f *.o *.lo *~ \
+	   example$(EXE) minigzip$(EXE) examplesh$(EXE) minigzipsh$(EXE) \
+	   example64$(EXE) minigzip64$(EXE) \
+	   infcover \
+	   libz.* foo.gz so_locations \
+	   _match.s maketree contrib/infback9/*.o
+	rm -rf objs
+	rm -f *.gcda *.gcno *.gcov
+	rm -f contrib/infback9/*.gcda contrib/infback9/*.gcno contrib/infback9/*.gcov
+
+maintainer-clean: distclean
+distclean: clean zconf zconf.h.cmakein docs
+	rm -f Makefile zlib.pc configure.log
+	-@rm -f .DS_Store
+	@if [ -f Makefile.in ]; then \
+	printf 'all:\n\t-@echo "Please use ./configure first.  Thank you."\n' > Makefile ; \
+	printf '\ndistclean:\n\tmake -f Makefile.in distclean\n' >> Makefile ; \
+	touch -r $(SRCDIR)Makefile.in Makefile ; fi
+	@if [ ! -f zconf.h.in ]; then rm -f zconf.h zconf.h.cmakein ; fi
+	@if [ ! -f zlib.3 ]; then rm -f zlib.3.pdf ; fi
+
+tags:
+	etags $(SRCDIR)*.[ch]
+
+adler32.o zutil.o: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h
+gzclose.o gzlib.o gzread.o gzwrite.o: $(SRCDIR)zlib.h zconf.h $(SRCDIR)gzguts.h
+compress.o example.o minigzip.o uncompr.o: $(SRCDIR)zlib.h zconf.h
+crc32.o: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)crc32.h
+deflate.o: $(SRCDIR)deflate.h $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h
+infback.o inflate.o: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)inftrees.h $(SRCDIR)inflate.h $(SRCDIR)inffast.h $(SRCDIR)inffixed.h
+inffast.o: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)inftrees.h $(SRCDIR)inflate.h $(SRCDIR)inffast.h
+inftrees.o: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)inftrees.h
+trees.o: $(SRCDIR)deflate.h $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)trees.h
+
+adler32.lo zutil.lo: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h
+gzclose.lo gzlib.lo gzread.lo gzwrite.lo: $(SRCDIR)zlib.h zconf.h $(SRCDIR)gzguts.h
+compress.lo example.lo minigzip.lo uncompr.lo: $(SRCDIR)zlib.h zconf.h
+crc32.lo: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)crc32.h
+deflate.lo: $(SRCDIR)deflate.h $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h
+infback.lo inflate.lo: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)inftrees.h $(SRCDIR)inflate.h $(SRCDIR)inffast.h $(SRCDIR)inffixed.h
+inffast.lo: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)inftrees.h $(SRCDIR)inflate.h $(SRCDIR)inffast.h
+inftrees.lo: $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)inftrees.h
+trees.lo: $(SRCDIR)deflate.h $(SRCDIR)zutil.h $(SRCDIR)zlib.h zconf.h $(SRCDIR)trees.h

ADDED   3rd_party/zlib/README
Index: 3rd_party/zlib/README
==================================================================
--- 3rd_party/zlib/README
+++ 3rd_party/zlib/README
@@ -0,0 +1,115 @@
+ZLIB DATA COMPRESSION LIBRARY
+
+zlib 1.2.11 is a general purpose data compression library.  All the code is
+thread safe.  The data format used by the zlib library is described by RFCs
+(Request for Comments) 1950 to 1952 in the files
+http://tools.ietf.org/html/rfc1950 (zlib format), rfc1951 (deflate format) and
+rfc1952 (gzip format).
+
+All functions of the compression library are documented in the file zlib.h
+(volunteer to write man pages welcome, contact zlib@gzip.org).  A usage example
+of the library is given in the file test/example.c which also tests that
+the library is working correctly.  Another example is given in the file
+test/minigzip.c.  The compression library itself is composed of all source
+files in the root directory.
+
+To compile all files and run the test program, follow the instructions given at
+the top of Makefile.in.  In short "./configure; make test", and if that goes
+well, "make install" should work for most flavors of Unix.  For Windows, use
+one of the special makefiles in win32/ or contrib/vstudio/ .  For VMS, use
+make_vms.com.
+
+Questions about zlib should be sent to <zlib@gzip.org>, or to Gilles Vollant
+<info@winimage.com> for the Windows DLL version.  The zlib home page is
+http://zlib.net/ .  Before reporting a problem, please check this site to
+verify that you have the latest version of zlib; otherwise get the latest
+version and check whether the problem still exists or not.
+
+PLEASE read the zlib FAQ http://zlib.net/zlib_faq.html before asking for help.
+
+Mark Nelson <markn@ieee.org> wrote an article about zlib for the Jan.  1997
+issue of Dr.  Dobb's Journal; a copy of the article is available at
+http://marknelson.us/1997/01/01/zlib-engine/ .
+
+The changes made in version 1.2.11 are documented in the file ChangeLog.
+
+Unsupported third party contributions are provided in directory contrib/ .
+
+zlib is available in Java using the java.util.zip package, documented at
+http://java.sun.com/developer/technicalArticles/Programming/compression/ .
+
+A Perl interface to zlib written by Paul Marquess <pmqs@cpan.org> is available
+at CPAN (Comprehensive Perl Archive Network) sites, including
+http://search.cpan.org/~pmqs/IO-Compress-Zlib/ .
+
+A Python interface to zlib written by A.M. Kuchling <amk@amk.ca> is
+available in Python 1.5 and later versions, see
+http://docs.python.org/library/zlib.html .
+
+zlib is built into tcl: http://wiki.tcl.tk/4610 .
+
+An experimental package to read and write files in .zip format, written on top
+of zlib by Gilles Vollant <info@winimage.com>, is available in the
+contrib/minizip directory of zlib.
+
+
+Notes for some targets:
+
+- For Windows DLL versions, please see win32/DLL_FAQ.txt
+
+- For 64-bit Irix, deflate.c must be compiled without any optimization. With
+  -O, one libpng test fails. The test works in 32 bit mode (with the -n32
+  compiler flag). The compiler bug has been reported to SGI.
+
+- zlib doesn't work with gcc 2.6.3 on a DEC 3000/300LX under OSF/1 2.1 it works
+  when compiled with cc.
+
+- On Digital Unix 4.0D (formely OSF/1) on AlphaServer, the cc option -std1 is
+  necessary to get gzprintf working correctly. This is done by configure.
+
+- zlib doesn't work on HP-UX 9.05 with some versions of /bin/cc. It works with
+  other compilers. Use "make test" to check your compiler.
+
+- gzdopen is not supported on RISCOS or BEOS.
+
+- For PalmOs, see http://palmzlib.sourceforge.net/
+
+
+Acknowledgments:
+
+  The deflate format used by zlib was defined by Phil Katz.  The deflate and
+  zlib specifications were written by L.  Peter Deutsch.  Thanks to all the
+  people who reported problems and suggested various improvements in zlib; they
+  are too numerous to cite here.
+
+Copyright notice:
+
+ (C) 1995-2017 Jean-loup Gailly and Mark Adler
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the authors be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
+
+  Jean-loup Gailly        Mark Adler
+  jloup@gzip.org          madler@alumni.caltech.edu
+
+If you use the zlib library in a product, we would appreciate *not* receiving
+lengthy legal documents to sign.  The sources are provided for free but without
+warranty of any kind.  The library has been entirely written by Jean-loup
+Gailly and Mark Adler; it does not include third-party code.
+
+If you redistribute modified sources, we would appreciate that you include in
+the file ChangeLog history information documenting your changes.  Please read
+the FAQ for more information on the distribution of modified source versions.

ADDED   3rd_party/zlib/adler32.c
Index: 3rd_party/zlib/adler32.c
==================================================================
--- 3rd_party/zlib/adler32.c
+++ 3rd_party/zlib/adler32.c
@@ -0,0 +1,186 @@
+/* adler32.c -- compute the Adler-32 checksum of a data stream
+ * Copyright (C) 1995-2011, 2016 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* @(#) $Id$ */
+
+#include "zutil.h"
+
+local uLong adler32_combine_ OF((uLong adler1, uLong adler2, z_off64_t len2));
+
+#define BASE 65521U     /* largest prime smaller than 65536 */
+#define NMAX 5552
+/* NMAX is the largest n such that 255n(n+1)/2 + (n+1)(BASE-1) <= 2^32-1 */
+
+#define DO1(buf,i)  {adler += (buf)[i]; sum2 += adler;}
+#define DO2(buf,i)  DO1(buf,i); DO1(buf,i+1);
+#define DO4(buf,i)  DO2(buf,i); DO2(buf,i+2);
+#define DO8(buf,i)  DO4(buf,i); DO4(buf,i+4);
+#define DO16(buf)   DO8(buf,0); DO8(buf,8);
+
+/* use NO_DIVIDE if your processor does not do division in hardware --
+   try it both ways to see which is faster */
+#ifdef NO_DIVIDE
+/* note that this assumes BASE is 65521, where 65536 % 65521 == 15
+   (thank you to John Reiser for pointing this out) */
+#  define CHOP(a) \
+    do { \
+        unsigned long tmp = a >> 16; \
+        a &= 0xffffUL; \
+        a += (tmp << 4) - tmp; \
+    } while (0)
+#  define MOD28(a) \
+    do { \
+        CHOP(a); \
+        if (a >= BASE) a -= BASE; \
+    } while (0)
+#  define MOD(a) \
+    do { \
+        CHOP(a); \
+        MOD28(a); \
+    } while (0)
+#  define MOD63(a) \
+    do { /* this assumes a is not negative */ \
+        z_off64_t tmp = a >> 32; \
+        a &= 0xffffffffL; \
+        a += (tmp << 8) - (tmp << 5) + tmp; \
+        tmp = a >> 16; \
+        a &= 0xffffL; \
+        a += (tmp << 4) - tmp; \
+        tmp = a >> 16; \
+        a &= 0xffffL; \
+        a += (tmp << 4) - tmp; \
+        if (a >= BASE) a -= BASE; \
+    } while (0)
+#else
+#  define MOD(a) a %= BASE
+#  define MOD28(a) a %= BASE
+#  define MOD63(a) a %= BASE
+#endif
+
+/* ========================================================================= */
+uLong ZEXPORT adler32_z(adler, buf, len)
+    uLong adler;
+    const Bytef *buf;
+    z_size_t len;
+{
+    unsigned long sum2;
+    unsigned n;
+
+    /* split Adler-32 into component sums */
+    sum2 = (adler >> 16) & 0xffff;
+    adler &= 0xffff;
+
+    /* in case user likes doing a byte at a time, keep it fast */
+    if (len == 1) {
+        adler += buf[0];
+        if (adler >= BASE)
+            adler -= BASE;
+        sum2 += adler;
+        if (sum2 >= BASE)
+            sum2 -= BASE;
+        return adler | (sum2 << 16);
+    }
+
+    /* initial Adler-32 value (deferred check for len == 1 speed) */
+    if (buf == Z_NULL)
+        return 1L;
+
+    /* in case short lengths are provided, keep it somewhat fast */
+    if (len < 16) {
+        while (len--) {
+            adler += *buf++;
+            sum2 += adler;
+        }
+        if (adler >= BASE)
+            adler -= BASE;
+        MOD28(sum2);            /* only added so many BASE's */
+        return adler | (sum2 << 16);
+    }
+
+    /* do length NMAX blocks -- requires just one modulo operation */
+    while (len >= NMAX) {
+        len -= NMAX;
+        n = NMAX / 16;          /* NMAX is divisible by 16 */
+        do {
+            DO16(buf);          /* 16 sums unrolled */
+            buf += 16;
+        } while (--n);
+        MOD(adler);
+        MOD(sum2);
+    }
+
+    /* do remaining bytes (less than NMAX, still just one modulo) */
+    if (len) {                  /* avoid modulos if none remaining */
+        while (len >= 16) {
+            len -= 16;
+            DO16(buf);
+            buf += 16;
+        }
+        while (len--) {
+            adler += *buf++;
+            sum2 += adler;
+        }
+        MOD(adler);
+        MOD(sum2);
+    }
+
+    /* return recombined sums */
+    return adler | (sum2 << 16);
+}
+
+/* ========================================================================= */
+uLong ZEXPORT adler32(adler, buf, len)
+    uLong adler;
+    const Bytef *buf;
+    uInt len;
+{
+    return adler32_z(adler, buf, len);
+}
+
+/* ========================================================================= */
+local uLong adler32_combine_(adler1, adler2, len2)
+    uLong adler1;
+    uLong adler2;
+    z_off64_t len2;
+{
+    unsigned long sum1;
+    unsigned long sum2;
+    unsigned rem;
+
+    /* for negative len, return invalid adler32 as a clue for debugging */
+    if (len2 < 0)
+        return 0xffffffffUL;
+
+    /* the derivation of this formula is left as an exercise for the reader */
+    MOD63(len2);                /* assumes len2 >= 0 */
+    rem = (unsigned)len2;
+    sum1 = adler1 & 0xffff;
+    sum2 = rem * sum1;
+    MOD(sum2);
+    sum1 += (adler2 & 0xffff) + BASE - 1;
+    sum2 += ((adler1 >> 16) & 0xffff) + ((adler2 >> 16) & 0xffff) + BASE - rem;
+    if (sum1 >= BASE) sum1 -= BASE;
+    if (sum1 >= BASE) sum1 -= BASE;
+    if (sum2 >= ((unsigned long)BASE << 1)) sum2 -= ((unsigned long)BASE << 1);
+    if (sum2 >= BASE) sum2 -= BASE;
+    return sum1 | (sum2 << 16);
+}
+
+/* ========================================================================= */
+uLong ZEXPORT adler32_combine(adler1, adler2, len2)
+    uLong adler1;
+    uLong adler2;
+    z_off_t len2;
+{
+    return adler32_combine_(adler1, adler2, len2);
+}
+
+uLong ZEXPORT adler32_combine64(adler1, adler2, len2)
+    uLong adler1;
+    uLong adler2;
+    z_off64_t len2;
+{
+    return adler32_combine_(adler1, adler2, len2);
+}

ADDED   3rd_party/zlib/amiga/Makefile.pup
Index: 3rd_party/zlib/amiga/Makefile.pup
==================================================================
--- 3rd_party/zlib/amiga/Makefile.pup
+++ 3rd_party/zlib/amiga/Makefile.pup
@@ -0,0 +1,69 @@
+# Amiga powerUP (TM) Makefile
+# makefile for libpng and SAS C V6.58/7.00 PPC compiler
+# Copyright (C) 1998 by Andreas R. Kleinert
+
+LIBNAME	= libzip.a
+
+CC	= scppc
+CFLAGS	= NOSTKCHK NOSINT OPTIMIZE OPTGO OPTPEEP OPTINLOCAL OPTINL \
+	  OPTLOOP OPTRDEP=8 OPTDEP=8 OPTCOMP=8 NOVER
+AR	= ppc-amigaos-ar cr
+RANLIB	= ppc-amigaos-ranlib
+LD	= ppc-amigaos-ld -r
+LDFLAGS	= -o
+LDLIBS	= LIB:scppc.a LIB:end.o
+RM	= delete quiet
+
+OBJS = adler32.o compress.o crc32.o gzclose.o gzlib.o gzread.o gzwrite.o \
+       uncompr.o deflate.o trees.o zutil.o inflate.o infback.o inftrees.o inffast.o
+
+TEST_OBJS = example.o minigzip.o
+
+all: example minigzip
+
+check: test
+test: all
+	example
+	echo hello world | minigzip | minigzip -d
+
+$(LIBNAME): $(OBJS)
+	$(AR) $@ $(OBJS)
+	-$(RANLIB) $@
+
+example: example.o $(LIBNAME)
+	$(LD) $(LDFLAGS) $@ LIB:c_ppc.o $@.o $(LIBNAME) $(LDLIBS)
+
+minigzip: minigzip.o $(LIBNAME)
+	$(LD) $(LDFLAGS) $@ LIB:c_ppc.o $@.o $(LIBNAME) $(LDLIBS)
+
+mostlyclean: clean
+clean:
+	$(RM) *.o example minigzip $(LIBNAME) foo.gz
+
+zip:
+	zip -ul9 zlib README ChangeLog Makefile Make????.??? Makefile.?? \
+	  descrip.mms *.[ch]
+
+tgz:
+	cd ..; tar cfz zlib/zlib.tgz zlib/README zlib/ChangeLog zlib/Makefile \
+	  zlib/Make????.??? zlib/Makefile.?? zlib/descrip.mms zlib/*.[ch]
+
+# DO NOT DELETE THIS LINE -- make depend depends on it.
+
+adler32.o: zlib.h zconf.h
+compress.o: zlib.h zconf.h
+crc32.o: crc32.h zlib.h zconf.h
+deflate.o: deflate.h zutil.h zlib.h zconf.h
+example.o: zlib.h zconf.h
+gzclose.o: zlib.h zconf.h gzguts.h
+gzlib.o: zlib.h zconf.h gzguts.h
+gzread.o: zlib.h zconf.h gzguts.h
+gzwrite.o: zlib.h zconf.h gzguts.h
+inffast.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+inflate.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+infback.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+inftrees.o: zutil.h zlib.h zconf.h inftrees.h
+minigzip.o: zlib.h zconf.h
+trees.o: deflate.h zutil.h zlib.h zconf.h trees.h
+uncompr.o: zlib.h zconf.h
+zutil.o: zutil.h zlib.h zconf.h

ADDED   3rd_party/zlib/amiga/Makefile.sas
Index: 3rd_party/zlib/amiga/Makefile.sas
==================================================================
--- 3rd_party/zlib/amiga/Makefile.sas
+++ 3rd_party/zlib/amiga/Makefile.sas
@@ -0,0 +1,68 @@
+# SMakefile for zlib
+# Modified from the standard UNIX Makefile Copyright Jean-loup Gailly
+# Osma Ahvenlampi <Osma.Ahvenlampi@hut.fi>
+# Amiga, SAS/C 6.56 & Smake
+
+CC=sc
+CFLAGS=OPT
+#CFLAGS=OPT CPU=68030
+#CFLAGS=DEBUG=LINE
+LDFLAGS=LIB z.lib
+
+SCOPTIONS=OPTSCHED OPTINLINE OPTALIAS OPTTIME OPTINLOCAL STRMERGE \
+       NOICONS PARMS=BOTH NOSTACKCHECK UTILLIB NOVERSION ERRORREXX \
+       DEF=POSTINC
+
+OBJS = adler32.o compress.o crc32.o gzclose.o gzlib.o gzread.o gzwrite.o \
+       uncompr.o deflate.o trees.o zutil.o inflate.o infback.o inftrees.o inffast.o
+
+TEST_OBJS = example.o minigzip.o
+
+all: SCOPTIONS example minigzip
+
+check: test
+test: all
+	example
+	echo hello world | minigzip | minigzip -d
+
+install: z.lib
+	copy clone zlib.h zconf.h INCLUDE:
+	copy clone z.lib LIB:
+
+z.lib: $(OBJS)
+	oml z.lib r $(OBJS)
+
+example: example.o z.lib
+	$(CC) $(CFLAGS) LINK TO $@ example.o $(LDFLAGS)
+
+minigzip: minigzip.o z.lib
+	$(CC) $(CFLAGS) LINK TO $@ minigzip.o $(LDFLAGS)
+
+mostlyclean: clean
+clean:
+	-delete force quiet example minigzip *.o z.lib foo.gz *.lnk SCOPTIONS
+
+SCOPTIONS: Makefile.sas
+	copy to $@ <from <
+$(SCOPTIONS)
+<
+
+# DO NOT DELETE THIS LINE -- make depend depends on it.
+
+adler32.o: zlib.h zconf.h
+compress.o: zlib.h zconf.h
+crc32.o: crc32.h zlib.h zconf.h
+deflate.o: deflate.h zutil.h zlib.h zconf.h
+example.o: zlib.h zconf.h
+gzclose.o: zlib.h zconf.h gzguts.h
+gzlib.o: zlib.h zconf.h gzguts.h
+gzread.o: zlib.h zconf.h gzguts.h
+gzwrite.o: zlib.h zconf.h gzguts.h
+inffast.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+inflate.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+infback.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+inftrees.o: zutil.h zlib.h zconf.h inftrees.h
+minigzip.o: zlib.h zconf.h
+trees.o: deflate.h zutil.h zlib.h zconf.h trees.h
+uncompr.o: zlib.h zconf.h
+zutil.o: zutil.h zlib.h zconf.h

ADDED   3rd_party/zlib/compress.c
Index: 3rd_party/zlib/compress.c
==================================================================
--- 3rd_party/zlib/compress.c
+++ 3rd_party/zlib/compress.c
@@ -0,0 +1,86 @@
+/* compress.c -- compress a memory buffer
+ * Copyright (C) 1995-2005, 2014, 2016 Jean-loup Gailly, Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* @(#) $Id$ */
+
+#define ZLIB_INTERNAL
+#include "zlib.h"
+
+/* ===========================================================================
+     Compresses the source buffer into the destination buffer. The level
+   parameter has the same meaning as in deflateInit.  sourceLen is the byte
+   length of the source buffer. Upon entry, destLen is the total size of the
+   destination buffer, which must be at least 0.1% larger than sourceLen plus
+   12 bytes. Upon exit, destLen is the actual size of the compressed buffer.
+
+     compress2 returns Z_OK if success, Z_MEM_ERROR if there was not enough
+   memory, Z_BUF_ERROR if there was not enough room in the output buffer,
+   Z_STREAM_ERROR if the level parameter is invalid.
+*/
+int ZEXPORT compress2 (dest, destLen, source, sourceLen, level)
+    Bytef *dest;
+    uLongf *destLen;
+    const Bytef *source;
+    uLong sourceLen;
+    int level;
+{
+    z_stream stream;
+    int err;
+    const uInt max = (uInt)-1;
+    uLong left;
+
+    left = *destLen;
+    *destLen = 0;
+
+    stream.zalloc = (alloc_func)0;
+    stream.zfree = (free_func)0;
+    stream.opaque = (voidpf)0;
+
+    err = deflateInit(&stream, level);
+    if (err != Z_OK) return err;
+
+    stream.next_out = dest;
+    stream.avail_out = 0;
+    stream.next_in = (z_const Bytef *)source;
+    stream.avail_in = 0;
+
+    do {
+        if (stream.avail_out == 0) {
+            stream.avail_out = left > (uLong)max ? max : (uInt)left;
+            left -= stream.avail_out;
+        }
+        if (stream.avail_in == 0) {
+            stream.avail_in = sourceLen > (uLong)max ? max : (uInt)sourceLen;
+            sourceLen -= stream.avail_in;
+        }
+        err = deflate(&stream, sourceLen ? Z_NO_FLUSH : Z_FINISH);
+    } while (err == Z_OK);
+
+    *destLen = stream.total_out;
+    deflateEnd(&stream);
+    return err == Z_STREAM_END ? Z_OK : err;
+}
+
+/* ===========================================================================
+ */
+int ZEXPORT compress (dest, destLen, source, sourceLen)
+    Bytef *dest;
+    uLongf *destLen;
+    const Bytef *source;
+    uLong sourceLen;
+{
+    return compress2(dest, destLen, source, sourceLen, Z_DEFAULT_COMPRESSION);
+}
+
+/* ===========================================================================
+     If the default memLevel or windowBits for deflateInit() is changed, then
+   this function needs to be updated.
+ */
+uLong ZEXPORT compressBound (sourceLen)
+    uLong sourceLen;
+{
+    return sourceLen + (sourceLen >> 12) + (sourceLen >> 14) +
+           (sourceLen >> 25) + 13;
+}

ADDED   3rd_party/zlib/configure
Index: 3rd_party/zlib/configure
==================================================================
--- 3rd_party/zlib/configure
+++ 3rd_party/zlib/configure
@@ -0,0 +1,921 @@
+#!/bin/sh
+# configure script for zlib.
+#
+# Normally configure builds both a static and a shared library.
+# If you want to build just a static library, use: ./configure --static
+#
+# To impose specific compiler or flags or install directory, use for example:
+#    prefix=$HOME CC=cc CFLAGS="-O4" ./configure
+# or for csh/tcsh users:
+#    (setenv prefix $HOME; setenv CC cc; setenv CFLAGS "-O4"; ./configure)
+
+# Incorrect settings of CC or CFLAGS may prevent creating a shared library.
+# If you have problems, try without defining CC and CFLAGS before reporting
+# an error.
+
+# start off configure.log
+echo -------------------- >> configure.log
+echo $0 $* >> configure.log
+date >> configure.log
+
+# get source directory
+SRCDIR=`dirname $0`
+if test $SRCDIR = "."; then
+    ZINC=""
+    ZINCOUT="-I."
+    SRCDIR=""
+else
+    ZINC='-include zconf.h'
+    ZINCOUT='-I. -I$(SRCDIR)'
+    SRCDIR="$SRCDIR/"
+fi
+
+# set command prefix for cross-compilation
+if [ -n "${CHOST}" ]; then
+    uname="`echo "${CHOST}" | sed -e 's/^[^-]*-\([^-]*\)$/\1/' -e 's/^[^-]*-[^-]*-\([^-]*\)$/\1/' -e 's/^[^-]*-[^-]*-\([^-]*\)-.*$/\1/'`"
+    CROSS_PREFIX="${CHOST}-"
+fi
+
+# destination name for static library
+STATICLIB=libz.a
+
+# extract zlib version numbers from zlib.h
+VER=`sed -n -e '/VERSION "/s/.*"\(.*\)".*/\1/p' < ${SRCDIR}zlib.h`
+VER3=`sed -n -e '/VERSION "/s/.*"\([0-9]*\\.[0-9]*\\.[0-9]*\).*/\1/p' < ${SRCDIR}zlib.h`
+VER2=`sed -n -e '/VERSION "/s/.*"\([0-9]*\\.[0-9]*\)\\..*/\1/p' < ${SRCDIR}zlib.h`
+VER1=`sed -n -e '/VERSION "/s/.*"\([0-9]*\)\\..*/\1/p' < ${SRCDIR}zlib.h`
+
+# establish commands for library building
+if "${CROSS_PREFIX}ar" --version >/dev/null 2>/dev/null || test $? -lt 126; then
+    AR=${AR-"${CROSS_PREFIX}ar"}
+    test -n "${CROSS_PREFIX}" && echo Using ${AR} | tee -a configure.log
+else
+    AR=${AR-"ar"}
+    test -n "${CROSS_PREFIX}" && echo Using ${AR} | tee -a configure.log
+fi
+ARFLAGS=${ARFLAGS-"rc"}
+if "${CROSS_PREFIX}ranlib" --version >/dev/null 2>/dev/null || test $? -lt 126; then
+    RANLIB=${RANLIB-"${CROSS_PREFIX}ranlib"}
+    test -n "${CROSS_PREFIX}" && echo Using ${RANLIB} | tee -a configure.log
+else
+    RANLIB=${RANLIB-"ranlib"}
+fi
+if "${CROSS_PREFIX}nm" --version >/dev/null 2>/dev/null || test $? -lt 126; then
+    NM=${NM-"${CROSS_PREFIX}nm"}
+    test -n "${CROSS_PREFIX}" && echo Using ${NM} | tee -a configure.log
+else
+    NM=${NM-"nm"}
+fi
+
+# set defaults before processing command line options
+LDCONFIG=${LDCONFIG-"ldconfig"}
+LDSHAREDLIBC="${LDSHAREDLIBC--lc}"
+ARCHS=
+prefix=${prefix-/usr/local}
+exec_prefix=${exec_prefix-'${prefix}'}
+libdir=${libdir-'${exec_prefix}/lib'}
+sharedlibdir=${sharedlibdir-'${libdir}'}
+includedir=${includedir-'${prefix}/include'}
+mandir=${mandir-'${prefix}/share/man'}
+shared_ext='.so'
+shared=1
+solo=0
+cover=0
+zprefix=0
+zconst=0
+build64=0
+gcc=0
+warn=0
+debug=0
+old_cc="$CC"
+old_cflags="$CFLAGS"
+OBJC='$(OBJZ) $(OBJG)'
+PIC_OBJC='$(PIC_OBJZ) $(PIC_OBJG)'
+
+# leave this script, optionally in a bad way
+leave()
+{
+  if test "$*" != "0"; then
+    echo "** $0 aborting." | tee -a configure.log
+  fi
+  rm -f $test.[co] $test $test$shared_ext $test.gcno ./--version
+  echo -------------------- >> configure.log
+  echo >> configure.log
+  echo >> configure.log
+  exit $1
+}
+
+# process command line options
+while test $# -ge 1
+do
+case "$1" in
+    -h* | --help)
+      echo 'usage:' | tee -a configure.log
+      echo '  configure [--const] [--zprefix] [--prefix=PREFIX]  [--eprefix=EXPREFIX]' | tee -a configure.log
+      echo '    [--static] [--64] [--libdir=LIBDIR] [--sharedlibdir=LIBDIR]' | tee -a configure.log
+      echo '    [--includedir=INCLUDEDIR] [--archs="-arch i386 -arch x86_64"]' | tee -a configure.log
+        exit 0 ;;
+    -p*=* | --prefix=*) prefix=`echo $1 | sed 's/.*=//'`; shift ;;
+    -e*=* | --eprefix=*) exec_prefix=`echo $1 | sed 's/.*=//'`; shift ;;
+    -l*=* | --libdir=*) libdir=`echo $1 | sed 's/.*=//'`; shift ;;
+    --sharedlibdir=*) sharedlibdir=`echo $1 | sed 's/.*=//'`; shift ;;
+    -i*=* | --includedir=*) includedir=`echo $1 | sed 's/.*=//'`;shift ;;
+    -u*=* | --uname=*) uname=`echo $1 | sed 's/.*=//'`;shift ;;
+    -p* | --prefix) prefix="$2"; shift; shift ;;
+    -e* | --eprefix) exec_prefix="$2"; shift; shift ;;
+    -l* | --libdir) libdir="$2"; shift; shift ;;
+    -i* | --includedir) includedir="$2"; shift; shift ;;
+    -s* | --shared | --enable-shared) shared=1; shift ;;
+    -t | --static) shared=0; shift ;;
+    --solo) solo=1; shift ;;
+    --cover) cover=1; shift ;;
+    -z* | --zprefix) zprefix=1; shift ;;
+    -6* | --64) build64=1; shift ;;
+    -a*=* | --archs=*) ARCHS=`echo $1 | sed 's/.*=//'`; shift ;;
+    --sysconfdir=*) echo "ignored option: --sysconfdir" | tee -a configure.log; shift ;;
+    --localstatedir=*) echo "ignored option: --localstatedir" | tee -a configure.log; shift ;;
+    -c* | --const) zconst=1; shift ;;
+    -w* | --warn) warn=1; shift ;;
+    -d* | --debug) debug=1; shift ;;
+    *)
+      echo "unknown option: $1" | tee -a configure.log
+      echo "$0 --help for help" | tee -a configure.log
+      leave 1;;
+    esac
+done
+
+# temporary file name
+test=ztest$$
+
+# put arguments in log, also put test file in log if used in arguments
+show()
+{
+  case "$*" in
+    *$test.c*)
+      echo === $test.c === >> configure.log
+      cat $test.c >> configure.log
+      echo === >> configure.log;;
+  esac
+  echo $* >> configure.log
+}
+
+# check for gcc vs. cc and set compile and link flags based on the system identified by uname
+cat > $test.c <<EOF
+extern int getchar();
+int hello() {return getchar();}
+EOF
+
+test -z "$CC" && echo Checking for ${CROSS_PREFIX}gcc... | tee -a configure.log
+cc=${CC-${CROSS_PREFIX}gcc}
+cflags=${CFLAGS-"-O3"}
+# to force the asm version use: CFLAGS="-O3 -DASMV" ./configure
+case "$cc" in
+  *gcc*) gcc=1 ;;
+  *clang*) gcc=1 ;;
+esac
+case `$cc -v 2>&1` in
+  *gcc*) gcc=1 ;;
+  *clang*) gcc=1 ;;
+esac
+
+show $cc -c $test.c
+if test "$gcc" -eq 1 && ($cc -c $test.c) >> configure.log 2>&1; then
+  echo ... using gcc >> configure.log
+  CC="$cc"
+  CFLAGS="${CFLAGS--O3}"
+  SFLAGS="${CFLAGS--O3} -fPIC"
+  if test "$ARCHS"; then
+    CFLAGS="${CFLAGS} ${ARCHS}"
+    LDFLAGS="${LDFLAGS} ${ARCHS}"
+  fi
+  if test $build64 -eq 1; then
+    CFLAGS="${CFLAGS} -m64"
+    SFLAGS="${SFLAGS} -m64"
+  fi
+  if test "$warn" -eq 1; then
+    if test "$zconst" -eq 1; then
+      CFLAGS="${CFLAGS} -Wall -Wextra -Wcast-qual -pedantic -DZLIB_CONST"
+    else
+      CFLAGS="${CFLAGS} -Wall -Wextra -pedantic"
+    fi
+  fi
+  if test $debug -eq 1; then
+    CFLAGS="${CFLAGS} -DZLIB_DEBUG"
+    SFLAGS="${SFLAGS} -DZLIB_DEBUG"
+  fi
+  if test -z "$uname"; then
+    uname=`(uname -s || echo unknown) 2>/dev/null`
+  fi
+  case "$uname" in
+  Linux* | linux* | GNU | GNU/* | solaris*)
+        LDSHARED=${LDSHARED-"$cc -shared -Wl,-soname,libz.so.1,--version-script,${SRCDIR}zlib.map"} ;;
+  *BSD | *bsd* | DragonFly)
+        LDSHARED=${LDSHARED-"$cc -shared -Wl,-soname,libz.so.1,--version-script,${SRCDIR}zlib.map"}
+        LDCONFIG="ldconfig -m" ;;
+  CYGWIN* | Cygwin* | cygwin* | OS/2*)
+        EXE='.exe' ;;
+  MINGW* | mingw*)
+# temporary bypass
+        rm -f $test.[co] $test $test$shared_ext
+        echo "Please use win32/Makefile.gcc instead." | tee -a configure.log
+        leave 1
+        LDSHARED=${LDSHARED-"$cc -shared"}
+        LDSHAREDLIBC=""
+        EXE='.exe' ;;
+  QNX*)  # This is for QNX6. I suppose that the QNX rule below is for QNX2,QNX4
+         # (alain.bonnefoy@icbt.com)
+                 LDSHARED=${LDSHARED-"$cc -shared -Wl,-hlibz.so.1"} ;;
+  HP-UX*)
+         LDSHARED=${LDSHARED-"$cc -shared $SFLAGS"}
+         case `(uname -m || echo unknown) 2>/dev/null` in
+         ia64)
+                 shared_ext='.so'
+                 SHAREDLIB='libz.so' ;;
+         *)
+                 shared_ext='.sl'
+                 SHAREDLIB='libz.sl' ;;
+         esac ;;
+  Darwin* | darwin*)
+             shared_ext='.dylib'
+             SHAREDLIB=libz$shared_ext
+             SHAREDLIBV=libz.$VER$shared_ext
+             SHAREDLIBM=libz.$VER1$shared_ext
+             LDSHARED=${LDSHARED-"$cc -dynamiclib -install_name $libdir/$SHAREDLIBM -compatibility_version $VER1 -current_version $VER3"}
+             if libtool -V 2>&1 | grep Apple > /dev/null; then
+                 AR="libtool"
+             else
+                 AR="/usr/bin/libtool"
+             fi
+             ARFLAGS="-o" ;;
+  *)             LDSHARED=${LDSHARED-"$cc -shared"} ;;
+  esac
+else
+  # find system name and corresponding cc options
+  CC=${CC-cc}
+  gcc=0
+  echo ... using $CC >> configure.log
+  if test -z "$uname"; then
+    uname=`(uname -sr || echo unknown) 2>/dev/null`
+  fi
+  case "$uname" in
+  HP-UX*)    SFLAGS=${CFLAGS-"-O +z"}
+             CFLAGS=${CFLAGS-"-O"}
+#            LDSHARED=${LDSHARED-"ld -b +vnocompatwarnings"}
+             LDSHARED=${LDSHARED-"ld -b"}
+         case `(uname -m || echo unknown) 2>/dev/null` in
+         ia64)
+             shared_ext='.so'
+             SHAREDLIB='libz.so' ;;
+         *)
+             shared_ext='.sl'
+             SHAREDLIB='libz.sl' ;;
+         esac ;;
+  IRIX*)     SFLAGS=${CFLAGS-"-ansi -O2 -rpath ."}
+             CFLAGS=${CFLAGS-"-ansi -O2"}
+             LDSHARED=${LDSHARED-"cc -shared -Wl,-soname,libz.so.1"} ;;
+  OSF1\ V4*) SFLAGS=${CFLAGS-"-O -std1"}
+             CFLAGS=${CFLAGS-"-O -std1"}
+             LDFLAGS="${LDFLAGS} -Wl,-rpath,."
+             LDSHARED=${LDSHARED-"cc -shared  -Wl,-soname,libz.so -Wl,-msym -Wl,-rpath,$(libdir) -Wl,-set_version,${VER}:1.0"} ;;
+  OSF1*)     SFLAGS=${CFLAGS-"-O -std1"}
+             CFLAGS=${CFLAGS-"-O -std1"}
+             LDSHARED=${LDSHARED-"cc -shared -Wl,-soname,libz.so.1"} ;;
+  QNX*)      SFLAGS=${CFLAGS-"-4 -O"}
+             CFLAGS=${CFLAGS-"-4 -O"}
+             LDSHARED=${LDSHARED-"cc"}
+             RANLIB=${RANLIB-"true"}
+             AR="cc"
+             ARFLAGS="-A" ;;
+  SCO_SV\ 3.2*) SFLAGS=${CFLAGS-"-O3 -dy -KPIC "}
+             CFLAGS=${CFLAGS-"-O3"}
+             LDSHARED=${LDSHARED-"cc -dy -KPIC -G"} ;;
+  SunOS\ 5* | solaris*)
+         LDSHARED=${LDSHARED-"cc -G -h libz$shared_ext.$VER1"}
+         SFLAGS=${CFLAGS-"-fast -KPIC"}
+         CFLAGS=${CFLAGS-"-fast"}
+         if test $build64 -eq 1; then
+             # old versions of SunPRO/Workshop/Studio don't support -m64,
+             # but newer ones do.  Check for it.
+             flag64=`$CC -flags | egrep -- '^-m64'`
+             if test x"$flag64" != x"" ; then
+                 CFLAGS="${CFLAGS} -m64"
+                 SFLAGS="${SFLAGS} -m64"
+             else
+                 case `(uname -m || echo unknown) 2>/dev/null` in
+                   i86*)
+                     SFLAGS="$SFLAGS -xarch=amd64"
+                     CFLAGS="$CFLAGS -xarch=amd64" ;;
+                   *)
+                     SFLAGS="$SFLAGS -xarch=v9"
+                     CFLAGS="$CFLAGS -xarch=v9" ;;
+                 esac
+             fi
+         fi
+         if test -n "$ZINC"; then
+             ZINC='-I- -I. -I$(SRCDIR)'
+         fi
+         ;;
+  SunOS\ 4*) SFLAGS=${CFLAGS-"-O2 -PIC"}
+             CFLAGS=${CFLAGS-"-O2"}
+             LDSHARED=${LDSHARED-"ld"} ;;
+  SunStudio\ 9*) SFLAGS=${CFLAGS-"-fast -xcode=pic32 -xtarget=ultra3 -xarch=v9b"}
+             CFLAGS=${CFLAGS-"-fast -xtarget=ultra3 -xarch=v9b"}
+             LDSHARED=${LDSHARED-"cc -xarch=v9b"} ;;
+  UNIX_System_V\ 4.2.0)
+             SFLAGS=${CFLAGS-"-KPIC -O"}
+             CFLAGS=${CFLAGS-"-O"}
+             LDSHARED=${LDSHARED-"cc -G"} ;;
+  UNIX_SV\ 4.2MP)
+             SFLAGS=${CFLAGS-"-Kconform_pic -O"}
+             CFLAGS=${CFLAGS-"-O"}
+             LDSHARED=${LDSHARED-"cc -G"} ;;
+  OpenUNIX\ 5)
+             SFLAGS=${CFLAGS-"-KPIC -O"}
+             CFLAGS=${CFLAGS-"-O"}
+             LDSHARED=${LDSHARED-"cc -G"} ;;
+  AIX*)  # Courtesy of dbakker@arrayasolutions.com
+             SFLAGS=${CFLAGS-"-O -qmaxmem=8192"}
+             CFLAGS=${CFLAGS-"-O -qmaxmem=8192"}
+             LDSHARED=${LDSHARED-"xlc -G"} ;;
+  # send working options for other systems to zlib@gzip.org
+  *)         SFLAGS=${CFLAGS-"-O"}
+             CFLAGS=${CFLAGS-"-O"}
+             LDSHARED=${LDSHARED-"cc -shared"} ;;
+  esac
+fi
+
+# destination names for shared library if not defined above
+SHAREDLIB=${SHAREDLIB-"libz$shared_ext"}
+SHAREDLIBV=${SHAREDLIBV-"libz$shared_ext.$VER"}
+SHAREDLIBM=${SHAREDLIBM-"libz$shared_ext.$VER1"}
+
+echo >> configure.log
+
+# define functions for testing compiler and library characteristics and logging the results
+
+cat > $test.c <<EOF
+#error error
+EOF
+if ($CC -c $CFLAGS $test.c) 2>/dev/null; then
+  try()
+  {
+    show $*
+    test "`( $* ) 2>&1 | tee -a configure.log`" = ""
+  }
+  echo - using any output from compiler to indicate an error >> configure.log
+else
+  try()
+  {
+    show $*
+    ( $* ) >> configure.log 2>&1
+    ret=$?
+    if test $ret -ne 0; then
+      echo "(exit code "$ret")" >> configure.log
+    fi
+    return $ret
+  }
+fi
+
+tryboth()
+{
+  show $*
+  got=`( $* ) 2>&1`
+  ret=$?
+  printf %s "$got" >> configure.log
+  if test $ret -ne 0; then
+    return $ret
+  fi
+  test "$got" = ""
+}
+
+cat > $test.c << EOF
+int foo() { return 0; }
+EOF
+echo "Checking for obsessive-compulsive compiler options..." >> configure.log
+if try $CC -c $CFLAGS $test.c; then
+  :
+else
+  echo "Compiler error reporting is too harsh for $0 (perhaps remove -Werror)." | tee -a configure.log
+  leave 1
+fi
+
+echo >> configure.log
+
+# see if shared library build supported
+cat > $test.c <<EOF
+extern int getchar();
+int hello() {return getchar();}
+EOF
+if test $shared -eq 1; then
+  echo Checking for shared library support... | tee -a configure.log
+  # we must test in two steps (cc then ld), required at least on SunOS 4.x
+  if try $CC -w -c $SFLAGS $test.c &&
+     try $LDSHARED $SFLAGS -o $test$shared_ext $test.o; then
+    echo Building shared library $SHAREDLIBV with $CC. | tee -a configure.log
+  elif test -z "$old_cc" -a -z "$old_cflags"; then
+    echo No shared library support. | tee -a configure.log
+    shared=0;
+  else
+    echo 'No shared library support; try without defining CC and CFLAGS' | tee -a configure.log
+    shared=0;
+  fi
+fi
+if test $shared -eq 0; then
+  LDSHARED="$CC"
+  ALL="static"
+  TEST="all teststatic"
+  SHAREDLIB=""
+  SHAREDLIBV=""
+  SHAREDLIBM=""
+  echo Building static library $STATICLIB version $VER with $CC. | tee -a configure.log
+else
+  ALL="static shared"
+  TEST="all teststatic testshared"
+fi
+
+# check for underscores in external names for use by assembler code
+CPP=${CPP-"$CC -E"}
+case $CFLAGS in
+  *ASMV*)
+    echo >> configure.log
+    show "$NM $test.o | grep _hello"
+    if test "`$NM $test.o | grep _hello | tee -a configure.log`" = ""; then
+      CPP="$CPP -DNO_UNDERLINE"
+      echo Checking for underline in external names... No. | tee -a configure.log
+    else
+      echo Checking for underline in external names... Yes. | tee -a configure.log
+    fi ;;
+esac
+
+echo >> configure.log
+
+# check for size_t
+cat > $test.c <<EOF
+#include <stdio.h>
+#include <stdlib.h>
+size_t dummy = 0;
+EOF
+if try $CC -c $CFLAGS $test.c; then
+  echo "Checking for size_t... Yes." | tee -a configure.log
+  need_sizet=0
+else
+  echo "Checking for size_t... No." | tee -a configure.log
+  need_sizet=1
+fi
+
+echo >> configure.log
+
+# find the size_t integer type, if needed
+if test $need_sizet -eq 1; then
+  cat > $test.c <<EOF
+long long dummy = 0;
+EOF
+  if try $CC -c $CFLAGS $test.c; then
+    echo "Checking for long long... Yes." | tee -a configure.log
+    cat > $test.c <<EOF
+#include <stdio.h>
+int main(void) {
+    if (sizeof(void *) <= sizeof(int)) puts("int");
+    else if (sizeof(void *) <= sizeof(long)) puts("long");
+    else puts("z_longlong");
+    return 0;
+}
+EOF
+  else
+    echo "Checking for long long... No." | tee -a configure.log
+    cat > $test.c <<EOF
+#include <stdio.h>
+int main(void) {
+    if (sizeof(void *) <= sizeof(int)) puts("int");
+    else puts("long");
+    return 0;
+}
+EOF
+  fi
+  if try $CC $CFLAGS -o $test $test.c; then
+    sizet=`./$test`
+    echo "Checking for a pointer-size integer type..." $sizet"." | tee -a configure.log
+  else
+    echo "Failed to find a pointer-size integer type." | tee -a configure.log
+    leave 1
+  fi
+fi
+
+if test $need_sizet -eq 1; then
+  CFLAGS="${CFLAGS} -DNO_SIZE_T=${sizet}"
+  SFLAGS="${SFLAGS} -DNO_SIZE_T=${sizet}"
+fi
+
+echo >> configure.log
+
+# check for large file support, and if none, check for fseeko()
+cat > $test.c <<EOF
+#include <sys/types.h>
+off64_t dummy = 0;
+EOF
+if try $CC -c $CFLAGS -D_LARGEFILE64_SOURCE=1 $test.c; then
+  CFLAGS="${CFLAGS} -D_LARGEFILE64_SOURCE=1"
+  SFLAGS="${SFLAGS} -D_LARGEFILE64_SOURCE=1"
+  ALL="${ALL} all64"
+  TEST="${TEST} test64"
+  echo "Checking for off64_t... Yes." | tee -a configure.log
+  echo "Checking for fseeko... Yes." | tee -a configure.log
+else
+  echo "Checking for off64_t... No." | tee -a configure.log
+  echo >> configure.log
+  cat > $test.c <<EOF
+#include <stdio.h>
+int main(void) {
+  fseeko(NULL, 0, 0);
+  return 0;
+}
+EOF
+  if try $CC $CFLAGS -o $test $test.c; then
+    echo "Checking for fseeko... Yes." | tee -a configure.log
+  else
+    CFLAGS="${CFLAGS} -DNO_FSEEKO"
+    SFLAGS="${SFLAGS} -DNO_FSEEKO"
+    echo "Checking for fseeko... No." | tee -a configure.log
+  fi
+fi
+
+echo >> configure.log
+
+# check for strerror() for use by gz* functions
+cat > $test.c <<EOF
+#include <string.h>
+#include <errno.h>
+int main() { return strlen(strerror(errno)); }
+EOF
+if try $CC $CFLAGS -o $test $test.c; then
+  echo "Checking for strerror... Yes." | tee -a configure.log
+else
+  CFLAGS="${CFLAGS} -DNO_STRERROR"
+  SFLAGS="${SFLAGS} -DNO_STRERROR"
+  echo "Checking for strerror... No." | tee -a configure.log
+fi
+
+# copy clean zconf.h for subsequent edits
+cp -p ${SRCDIR}zconf.h.in zconf.h
+
+echo >> configure.log
+
+# check for unistd.h and save result in zconf.h
+cat > $test.c <<EOF
+#include <unistd.h>
+int main() { return 0; }
+EOF
+if try $CC -c $CFLAGS $test.c; then
+  sed < zconf.h "/^#ifdef HAVE_UNISTD_H.* may be/s/def HAVE_UNISTD_H\(.*\) may be/ 1\1 was/" > zconf.temp.h
+  mv zconf.temp.h zconf.h
+  echo "Checking for unistd.h... Yes." | tee -a configure.log
+else
+  echo "Checking for unistd.h... No." | tee -a configure.log
+fi
+
+echo >> configure.log
+
+# check for stdarg.h and save result in zconf.h
+cat > $test.c <<EOF
+#include <stdarg.h>
+int main() { return 0; }
+EOF
+if try $CC -c $CFLAGS $test.c; then
+  sed < zconf.h "/^#ifdef HAVE_STDARG_H.* may be/s/def HAVE_STDARG_H\(.*\) may be/ 1\1 was/" > zconf.temp.h
+  mv zconf.temp.h zconf.h
+  echo "Checking for stdarg.h... Yes." | tee -a configure.log
+else
+  echo "Checking for stdarg.h... No." | tee -a configure.log
+fi
+
+# if the z_ prefix was requested, save that in zconf.h
+if test $zprefix -eq 1; then
+  sed < zconf.h "/#ifdef Z_PREFIX.* may be/s/def Z_PREFIX\(.*\) may be/ 1\1 was/" > zconf.temp.h
+  mv zconf.temp.h zconf.h
+  echo >> configure.log
+  echo "Using z_ prefix on all symbols." | tee -a configure.log
+fi
+
+# if --solo compilation was requested, save that in zconf.h and remove gz stuff from object lists
+if test $solo -eq 1; then
+  sed '/#define ZCONF_H/a\
+#define Z_SOLO
+
+' < zconf.h > zconf.temp.h
+  mv zconf.temp.h zconf.h
+OBJC='$(OBJZ)'
+PIC_OBJC='$(PIC_OBJZ)'
+fi
+
+# if code coverage testing was requested, use older gcc if defined, e.g. "gcc-4.2" on Mac OS X
+if test $cover -eq 1; then
+  CFLAGS="${CFLAGS} -fprofile-arcs -ftest-coverage"
+  if test -n "$GCC_CLASSIC"; then
+    CC=$GCC_CLASSIC
+  fi
+fi
+
+echo >> configure.log
+
+# conduct a series of tests to resolve eight possible cases of using "vs" or "s" printf functions
+# (using stdarg or not), with or without "n" (proving size of buffer), and with or without a
+# return value.  The most secure result is vsnprintf() with a return value.  snprintf() with a
+# return value is secure as well, but then gzprintf() will be limited to 20 arguments.
+cat > $test.c <<EOF
+#include <stdio.h>
+#include <stdarg.h>
+#include "zconf.h"
+int main()
+{
+#ifndef STDC
+  choke me
+#endif
+  return 0;
+}
+EOF
+if try $CC -c $CFLAGS $test.c; then
+  echo "Checking whether to use vs[n]printf() or s[n]printf()... using vs[n]printf()." | tee -a configure.log
+
+  echo >> configure.log
+  cat > $test.c <<EOF
+#include <stdio.h>
+#include <stdarg.h>
+int mytest(const char *fmt, ...)
+{
+  char buf[20];
+  va_list ap;
+  va_start(ap, fmt);
+  vsnprintf(buf, sizeof(buf), fmt, ap);
+  va_end(ap);
+  return 0;
+}
+int main()
+{
+  return (mytest("Hello%d\n", 1));
+}
+EOF
+  if try $CC $CFLAGS -o $test $test.c; then
+    echo "Checking for vsnprintf() in stdio.h... Yes." | tee -a configure.log
+
+    echo >> configure.log
+    cat >$test.c <<EOF
+#include <stdio.h>
+#include <stdarg.h>
+int mytest(const char *fmt, ...)
+{
+  int n;
+  char buf[20];
+  va_list ap;
+  va_start(ap, fmt);
+  n = vsnprintf(buf, sizeof(buf), fmt, ap);
+  va_end(ap);
+  return n;
+}
+int main()
+{
+  return (mytest("Hello%d\n", 1));
+}
+EOF
+
+    if try $CC -c $CFLAGS $test.c; then
+      echo "Checking for return value of vsnprintf()... Yes." | tee -a configure.log
+    else
+      CFLAGS="$CFLAGS -DHAS_vsnprintf_void"
+      SFLAGS="$SFLAGS -DHAS_vsnprintf_void"
+      echo "Checking for return value of vsnprintf()... No." | tee -a configure.log
+      echo "  WARNING: apparently vsnprintf() does not return a value. zlib" | tee -a configure.log
+      echo "  can build but will be open to possible string-format security" | tee -a configure.log
+      echo "  vulnerabilities." | tee -a configure.log
+    fi
+  else
+    CFLAGS="$CFLAGS -DNO_vsnprintf"
+    SFLAGS="$SFLAGS -DNO_vsnprintf"
+    echo "Checking for vsnprintf() in stdio.h... No." | tee -a configure.log
+    echo "  WARNING: vsnprintf() not found, falling back to vsprintf(). zlib" | tee -a configure.log
+    echo "  can build but will be open to possible buffer-overflow security" | tee -a configure.log
+    echo "  vulnerabilities." | tee -a configure.log
+
+    echo >> configure.log
+    cat >$test.c <<EOF
+#include <stdio.h>
+#include <stdarg.h>
+int mytest(const char *fmt, ...)
+{
+  int n;
+  char buf[20];
+  va_list ap;
+  va_start(ap, fmt);
+  n = vsprintf(buf, fmt, ap);
+  va_end(ap);
+  return n;
+}
+int main()
+{
+  return (mytest("Hello%d\n", 1));
+}
+EOF
+
+    if try $CC -c $CFLAGS $test.c; then
+      echo "Checking for return value of vsprintf()... Yes." | tee -a configure.log
+    else
+      CFLAGS="$CFLAGS -DHAS_vsprintf_void"
+      SFLAGS="$SFLAGS -DHAS_vsprintf_void"
+      echo "Checking for return value of vsprintf()... No." | tee -a configure.log
+      echo "  WARNING: apparently vsprintf() does not return a value. zlib" | tee -a configure.log
+      echo "  can build but will be open to possible string-format security" | tee -a configure.log
+      echo "  vulnerabilities." | tee -a configure.log
+    fi
+  fi
+else
+  echo "Checking whether to use vs[n]printf() or s[n]printf()... using s[n]printf()." | tee -a configure.log
+
+  echo >> configure.log
+  cat >$test.c <<EOF
+#include <stdio.h>
+int mytest()
+{
+  char buf[20];
+  snprintf(buf, sizeof(buf), "%s", "foo");
+  return 0;
+}
+int main()
+{
+  return (mytest());
+}
+EOF
+
+  if try $CC $CFLAGS -o $test $test.c; then
+    echo "Checking for snprintf() in stdio.h... Yes." | tee -a configure.log
+
+    echo >> configure.log
+    cat >$test.c <<EOF
+#include <stdio.h>
+int mytest()
+{
+  char buf[20];
+  return snprintf(buf, sizeof(buf), "%s", "foo");
+}
+int main()
+{
+  return (mytest());
+}
+EOF
+
+    if try $CC -c $CFLAGS $test.c; then
+      echo "Checking for return value of snprintf()... Yes." | tee -a configure.log
+    else
+      CFLAGS="$CFLAGS -DHAS_snprintf_void"
+      SFLAGS="$SFLAGS -DHAS_snprintf_void"
+      echo "Checking for return value of snprintf()... No." | tee -a configure.log
+      echo "  WARNING: apparently snprintf() does not return a value. zlib" | tee -a configure.log
+      echo "  can build but will be open to possible string-format security" | tee -a configure.log
+      echo "  vulnerabilities." | tee -a configure.log
+    fi
+  else
+    CFLAGS="$CFLAGS -DNO_snprintf"
+    SFLAGS="$SFLAGS -DNO_snprintf"
+    echo "Checking for snprintf() in stdio.h... No." | tee -a configure.log
+    echo "  WARNING: snprintf() not found, falling back to sprintf(). zlib" | tee -a configure.log
+    echo "  can build but will be open to possible buffer-overflow security" | tee -a configure.log
+    echo "  vulnerabilities." | tee -a configure.log
+
+    echo >> configure.log
+    cat >$test.c <<EOF
+#include <stdio.h>
+int mytest()
+{
+  char buf[20];
+  return sprintf(buf, "%s", "foo");
+}
+int main()
+{
+  return (mytest());
+}
+EOF
+
+    if try $CC -c $CFLAGS $test.c; then
+      echo "Checking for return value of sprintf()... Yes." | tee -a configure.log
+    else
+      CFLAGS="$CFLAGS -DHAS_sprintf_void"
+      SFLAGS="$SFLAGS -DHAS_sprintf_void"
+      echo "Checking for return value of sprintf()... No." | tee -a configure.log
+      echo "  WARNING: apparently sprintf() does not return a value. zlib" | tee -a configure.log
+      echo "  can build but will be open to possible string-format security" | tee -a configure.log
+      echo "  vulnerabilities." | tee -a configure.log
+    fi
+  fi
+fi
+
+# see if we can hide zlib internal symbols that are linked between separate source files
+if test "$gcc" -eq 1; then
+  echo >> configure.log
+  cat > $test.c <<EOF
+#define ZLIB_INTERNAL __attribute__((visibility ("hidden")))
+int ZLIB_INTERNAL foo;
+int main()
+{
+  return 0;
+}
+EOF
+  if tryboth $CC -c $CFLAGS $test.c; then
+    CFLAGS="$CFLAGS -DHAVE_HIDDEN"
+    SFLAGS="$SFLAGS -DHAVE_HIDDEN"
+    echo "Checking for attribute(visibility) support... Yes." | tee -a configure.log
+  else
+    echo "Checking for attribute(visibility) support... No." | tee -a configure.log
+  fi
+fi
+
+# show the results in the log
+echo >> configure.log
+echo ALL = $ALL >> configure.log
+echo AR = $AR >> configure.log
+echo ARFLAGS = $ARFLAGS >> configure.log
+echo CC = $CC >> configure.log
+echo CFLAGS = $CFLAGS >> configure.log
+echo CPP = $CPP >> configure.log
+echo EXE = $EXE >> configure.log
+echo LDCONFIG = $LDCONFIG >> configure.log
+echo LDFLAGS = $LDFLAGS >> configure.log
+echo LDSHARED = $LDSHARED >> configure.log
+echo LDSHAREDLIBC = $LDSHAREDLIBC >> configure.log
+echo OBJC = $OBJC >> configure.log
+echo PIC_OBJC = $PIC_OBJC >> configure.log
+echo RANLIB = $RANLIB >> configure.log
+echo SFLAGS = $SFLAGS >> configure.log
+echo SHAREDLIB = $SHAREDLIB >> configure.log
+echo SHAREDLIBM = $SHAREDLIBM >> configure.log
+echo SHAREDLIBV = $SHAREDLIBV >> configure.log
+echo STATICLIB = $STATICLIB >> configure.log
+echo TEST = $TEST >> configure.log
+echo VER = $VER >> configure.log
+echo Z_U4 = $Z_U4 >> configure.log
+echo SRCDIR = $SRCDIR >> configure.log
+echo exec_prefix = $exec_prefix >> configure.log
+echo includedir = $includedir >> configure.log
+echo libdir = $libdir >> configure.log
+echo mandir = $mandir >> configure.log
+echo prefix = $prefix >> configure.log
+echo sharedlibdir = $sharedlibdir >> configure.log
+echo uname = $uname >> configure.log
+
+# udpate Makefile with the configure results
+sed < ${SRCDIR}Makefile.in "
+/^CC *=/s#=.*#=$CC#
+/^CFLAGS *=/s#=.*#=$CFLAGS#
+/^SFLAGS *=/s#=.*#=$SFLAGS#
+/^LDFLAGS *=/s#=.*#=$LDFLAGS#
+/^LDSHARED *=/s#=.*#=$LDSHARED#
+/^CPP *=/s#=.*#=$CPP#
+/^STATICLIB *=/s#=.*#=$STATICLIB#
+/^SHAREDLIB *=/s#=.*#=$SHAREDLIB#
+/^SHAREDLIBV *=/s#=.*#=$SHAREDLIBV#
+/^SHAREDLIBM *=/s#=.*#=$SHAREDLIBM#
+/^AR *=/s#=.*#=$AR#
+/^ARFLAGS *=/s#=.*#=$ARFLAGS#
+/^RANLIB *=/s#=.*#=$RANLIB#
+/^LDCONFIG *=/s#=.*#=$LDCONFIG#
+/^LDSHAREDLIBC *=/s#=.*#=$LDSHAREDLIBC#
+/^EXE *=/s#=.*#=$EXE#
+/^SRCDIR *=/s#=.*#=$SRCDIR#
+/^ZINC *=/s#=.*#=$ZINC#
+/^ZINCOUT *=/s#=.*#=$ZINCOUT#
+/^prefix *=/s#=.*#=$prefix#
+/^exec_prefix *=/s#=.*#=$exec_prefix#
+/^libdir *=/s#=.*#=$libdir#
+/^sharedlibdir *=/s#=.*#=$sharedlibdir#
+/^includedir *=/s#=.*#=$includedir#
+/^mandir *=/s#=.*#=$mandir#
+/^OBJC *=/s#=.*#= $OBJC#
+/^PIC_OBJC *=/s#=.*#= $PIC_OBJC#
+/^all: */s#:.*#: $ALL#
+/^test: */s#:.*#: $TEST#
+" > Makefile
+
+# create zlib.pc with the configure results
+sed < ${SRCDIR}zlib.pc.in "
+/^CC *=/s#=.*#=$CC#
+/^CFLAGS *=/s#=.*#=$CFLAGS#
+/^CPP *=/s#=.*#=$CPP#
+/^LDSHARED *=/s#=.*#=$LDSHARED#
+/^STATICLIB *=/s#=.*#=$STATICLIB#
+/^SHAREDLIB *=/s#=.*#=$SHAREDLIB#
+/^SHAREDLIBV *=/s#=.*#=$SHAREDLIBV#
+/^SHAREDLIBM *=/s#=.*#=$SHAREDLIBM#
+/^AR *=/s#=.*#=$AR#
+/^ARFLAGS *=/s#=.*#=$ARFLAGS#
+/^RANLIB *=/s#=.*#=$RANLIB#
+/^EXE *=/s#=.*#=$EXE#
+/^prefix *=/s#=.*#=$prefix#
+/^exec_prefix *=/s#=.*#=$exec_prefix#
+/^libdir *=/s#=.*#=$libdir#
+/^sharedlibdir *=/s#=.*#=$sharedlibdir#
+/^includedir *=/s#=.*#=$includedir#
+/^mandir *=/s#=.*#=$mandir#
+/^LDFLAGS *=/s#=.*#=$LDFLAGS#
+" | sed -e "
+s/\@VERSION\@/$VER/g;
+" > zlib.pc
+
+# done
+leave 0

ADDED   3rd_party/zlib/crc32.c
Index: 3rd_party/zlib/crc32.c
==================================================================
--- 3rd_party/zlib/crc32.c
+++ 3rd_party/zlib/crc32.c
@@ -0,0 +1,442 @@
+/* crc32.c -- compute the CRC-32 of a data stream
+ * Copyright (C) 1995-2006, 2010, 2011, 2012, 2016 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ *
+ * Thanks to Rodney Brown <rbrown64@csc.com.au> for his contribution of faster
+ * CRC methods: exclusive-oring 32 bits of data at a time, and pre-computing
+ * tables for updating the shift register in one step with three exclusive-ors
+ * instead of four steps with four exclusive-ors.  This results in about a
+ * factor of two increase in speed on a Power PC G4 (PPC7455) using gcc -O3.
+ */
+
+/* @(#) $Id$ */
+
+/*
+  Note on the use of DYNAMIC_CRC_TABLE: there is no mutex or semaphore
+  protection on the static variables used to control the first-use generation
+  of the crc tables.  Therefore, if you #define DYNAMIC_CRC_TABLE, you should
+  first call get_crc_table() to initialize the tables before allowing more than
+  one thread to use crc32().
+
+  DYNAMIC_CRC_TABLE and MAKECRCH can be #defined to write out crc32.h.
+ */
+
+#ifdef MAKECRCH
+#  include <stdio.h>
+#  ifndef DYNAMIC_CRC_TABLE
+#    define DYNAMIC_CRC_TABLE
+#  endif /* !DYNAMIC_CRC_TABLE */
+#endif /* MAKECRCH */
+
+#include "zutil.h"      /* for STDC and FAR definitions */
+
+/* Definitions for doing the crc four data bytes at a time. */
+#if !defined(NOBYFOUR) && defined(Z_U4)
+#  define BYFOUR
+#endif
+#ifdef BYFOUR
+   local unsigned long crc32_little OF((unsigned long,
+                        const unsigned char FAR *, z_size_t));
+   local unsigned long crc32_big OF((unsigned long,
+                        const unsigned char FAR *, z_size_t));
+#  define TBLS 8
+#else
+#  define TBLS 1
+#endif /* BYFOUR */
+
+/* Local functions for crc concatenation */
+local unsigned long gf2_matrix_times OF((unsigned long *mat,
+                                         unsigned long vec));
+local void gf2_matrix_square OF((unsigned long *square, unsigned long *mat));
+local uLong crc32_combine_ OF((uLong crc1, uLong crc2, z_off64_t len2));
+
+
+#ifdef DYNAMIC_CRC_TABLE
+
+local volatile int crc_table_empty = 1;
+local z_crc_t FAR crc_table[TBLS][256];
+local void make_crc_table OF((void));
+#ifdef MAKECRCH
+   local void write_table OF((FILE *, const z_crc_t FAR *));
+#endif /* MAKECRCH */
+/*
+  Generate tables for a byte-wise 32-bit CRC calculation on the polynomial:
+  x^32+x^26+x^23+x^22+x^16+x^12+x^11+x^10+x^8+x^7+x^5+x^4+x^2+x+1.
+
+  Polynomials over GF(2) are represented in binary, one bit per coefficient,
+  with the lowest powers in the most significant bit.  Then adding polynomials
+  is just exclusive-or, and multiplying a polynomial by x is a right shift by
+  one.  If we call the above polynomial p, and represent a byte as the
+  polynomial q, also with the lowest power in the most significant bit (so the
+  byte 0xb1 is the polynomial x^7+x^3+x+1), then the CRC is (q*x^32) mod p,
+  where a mod b means the remainder after dividing a by b.
+
+  This calculation is done using the shift-register method of multiplying and
+  taking the remainder.  The register is initialized to zero, and for each
+  incoming bit, x^32 is added mod p to the register if the bit is a one (where
+  x^32 mod p is p+x^32 = x^26+...+1), and the register is multiplied mod p by
+  x (which is shifting right by one and adding x^32 mod p if the bit shifted
+  out is a one).  We start with the highest power (least significant bit) of
+  q and repeat for all eight bits of q.
+
+  The first table is simply the CRC of all possible eight bit values.  This is
+  all the information needed to generate CRCs on data a byte at a time for all
+  combinations of CRC register values and incoming bytes.  The remaining tables
+  allow for word-at-a-time CRC calculation for both big-endian and little-
+  endian machines, where a word is four bytes.
+*/
+local void make_crc_table()
+{
+    z_crc_t c;
+    int n, k;
+    z_crc_t poly;                       /* polynomial exclusive-or pattern */
+    /* terms of polynomial defining this crc (except x^32): */
+    static volatile int first = 1;      /* flag to limit concurrent making */
+    static const unsigned char p[] = {0,1,2,4,5,7,8,10,11,12,16,22,23,26};
+
+    /* See if another task is already doing this (not thread-safe, but better
+       than nothing -- significantly reduces duration of vulnerability in
+       case the advice about DYNAMIC_CRC_TABLE is ignored) */
+    if (first) {
+        first = 0;
+
+        /* make exclusive-or pattern from polynomial (0xedb88320UL) */
+        poly = 0;
+        for (n = 0; n < (int)(sizeof(p)/sizeof(unsigned char)); n++)
+            poly |= (z_crc_t)1 << (31 - p[n]);
+
+        /* generate a crc for every 8-bit value */
+        for (n = 0; n < 256; n++) {
+            c = (z_crc_t)n;
+            for (k = 0; k < 8; k++)
+                c = c & 1 ? poly ^ (c >> 1) : c >> 1;
+            crc_table[0][n] = c;
+        }
+
+#ifdef BYFOUR
+        /* generate crc for each value followed by one, two, and three zeros,
+           and then the byte reversal of those as well as the first table */
+        for (n = 0; n < 256; n++) {
+            c = crc_table[0][n];
+            crc_table[4][n] = ZSWAP32(c);
+            for (k = 1; k < 4; k++) {
+                c = crc_table[0][c & 0xff] ^ (c >> 8);
+                crc_table[k][n] = c;
+                crc_table[k + 4][n] = ZSWAP32(c);
+            }
+        }
+#endif /* BYFOUR */
+
+        crc_table_empty = 0;
+    }
+    else {      /* not first */
+        /* wait for the other guy to finish (not efficient, but rare) */
+        while (crc_table_empty)
+            ;
+    }
+
+#ifdef MAKECRCH
+    /* write out CRC tables to crc32.h */
+    {
+        FILE *out;
+
+        out = fopen("crc32.h", "w");
+        if (out == NULL) return;
+        fprintf(out, "/* crc32.h -- tables for rapid CRC calculation\n");
+        fprintf(out, " * Generated automatically by crc32.c\n */\n\n");
+        fprintf(out, "local const z_crc_t FAR ");
+        fprintf(out, "crc_table[TBLS][256] =\n{\n  {\n");
+        write_table(out, crc_table[0]);
+#  ifdef BYFOUR
+        fprintf(out, "#ifdef BYFOUR\n");
+        for (k = 1; k < 8; k++) {
+            fprintf(out, "  },\n  {\n");
+            write_table(out, crc_table[k]);
+        }
+        fprintf(out, "#endif\n");
+#  endif /* BYFOUR */
+        fprintf(out, "  }\n};\n");
+        fclose(out);
+    }
+#endif /* MAKECRCH */
+}
+
+#ifdef MAKECRCH
+local void write_table(out, table)
+    FILE *out;
+    const z_crc_t FAR *table;
+{
+    int n;
+
+    for (n = 0; n < 256; n++)
+        fprintf(out, "%s0x%08lxUL%s", n % 5 ? "" : "    ",
+                (unsigned long)(table[n]),
+                n == 255 ? "\n" : (n % 5 == 4 ? ",\n" : ", "));
+}
+#endif /* MAKECRCH */
+
+#else /* !DYNAMIC_CRC_TABLE */
+/* ========================================================================
+ * Tables of CRC-32s of all single-byte values, made by make_crc_table().
+ */
+#include "crc32.h"
+#endif /* DYNAMIC_CRC_TABLE */
+
+/* =========================================================================
+ * This function can be used by asm versions of crc32()
+ */
+const z_crc_t FAR * ZEXPORT get_crc_table()
+{
+#ifdef DYNAMIC_CRC_TABLE
+    if (crc_table_empty)
+        make_crc_table();
+#endif /* DYNAMIC_CRC_TABLE */
+    return (const z_crc_t FAR *)crc_table;
+}
+
+/* ========================================================================= */
+#define DO1 crc = crc_table[0][((int)crc ^ (*buf++)) & 0xff] ^ (crc >> 8)
+#define DO8 DO1; DO1; DO1; DO1; DO1; DO1; DO1; DO1
+
+/* ========================================================================= */
+unsigned long ZEXPORT crc32_z(crc, buf, len)
+    unsigned long crc;
+    const unsigned char FAR *buf;
+    z_size_t len;
+{
+    if (buf == Z_NULL) return 0UL;
+
+#ifdef DYNAMIC_CRC_TABLE
+    if (crc_table_empty)
+        make_crc_table();
+#endif /* DYNAMIC_CRC_TABLE */
+
+#ifdef BYFOUR
+    if (sizeof(void *) == sizeof(ptrdiff_t)) {
+        z_crc_t endian;
+
+        endian = 1;
+        if (*((unsigned char *)(&endian)))
+            return crc32_little(crc, buf, len);
+        else
+            return crc32_big(crc, buf, len);
+    }
+#endif /* BYFOUR */
+    crc = crc ^ 0xffffffffUL;
+    while (len >= 8) {
+        DO8;
+        len -= 8;
+    }
+    if (len) do {
+        DO1;
+    } while (--len);
+    return crc ^ 0xffffffffUL;
+}
+
+/* ========================================================================= */
+unsigned long ZEXPORT crc32(crc, buf, len)
+    unsigned long crc;
+    const unsigned char FAR *buf;
+    uInt len;
+{
+    return crc32_z(crc, buf, len);
+}
+
+#ifdef BYFOUR
+
+/*
+   This BYFOUR code accesses the passed unsigned char * buffer with a 32-bit
+   integer pointer type. This violates the strict aliasing rule, where a
+   compiler can assume, for optimization purposes, that two pointers to
+   fundamentally different types won't ever point to the same memory. This can
+   manifest as a problem only if one of the pointers is written to. This code
+   only reads from those pointers. So long as this code remains isolated in
+   this compilation unit, there won't be a problem. For this reason, this code
+   should not be copied and pasted into a compilation unit in which other code
+   writes to the buffer that is passed to these routines.
+ */
+
+/* ========================================================================= */
+#define DOLIT4 c ^= *buf4++; \
+        c = crc_table[3][c & 0xff] ^ crc_table[2][(c >> 8) & 0xff] ^ \
+            crc_table[1][(c >> 16) & 0xff] ^ crc_table[0][c >> 24]
+#define DOLIT32 DOLIT4; DOLIT4; DOLIT4; DOLIT4; DOLIT4; DOLIT4; DOLIT4; DOLIT4
+
+/* ========================================================================= */
+local unsigned long crc32_little(crc, buf, len)
+    unsigned long crc;
+    const unsigned char FAR *buf;
+    z_size_t len;
+{
+    register z_crc_t c;
+    register const z_crc_t FAR *buf4;
+
+    c = (z_crc_t)crc;
+    c = ~c;
+    while (len && ((ptrdiff_t)buf & 3)) {
+        c = crc_table[0][(c ^ *buf++) & 0xff] ^ (c >> 8);
+        len--;
+    }
+
+    buf4 = (const z_crc_t FAR *)(const void FAR *)buf;
+    while (len >= 32) {
+        DOLIT32;
+        len -= 32;
+    }
+    while (len >= 4) {
+        DOLIT4;
+        len -= 4;
+    }
+    buf = (const unsigned char FAR *)buf4;
+
+    if (len) do {
+        c = crc_table[0][(c ^ *buf++) & 0xff] ^ (c >> 8);
+    } while (--len);
+    c = ~c;
+    return (unsigned long)c;
+}
+
+/* ========================================================================= */
+#define DOBIG4 c ^= *buf4++; \
+        c = crc_table[4][c & 0xff] ^ crc_table[5][(c >> 8) & 0xff] ^ \
+            crc_table[6][(c >> 16) & 0xff] ^ crc_table[7][c >> 24]
+#define DOBIG32 DOBIG4; DOBIG4; DOBIG4; DOBIG4; DOBIG4; DOBIG4; DOBIG4; DOBIG4
+
+/* ========================================================================= */
+local unsigned long crc32_big(crc, buf, len)
+    unsigned long crc;
+    const unsigned char FAR *buf;
+    z_size_t len;
+{
+    register z_crc_t c;
+    register const z_crc_t FAR *buf4;
+
+    c = ZSWAP32((z_crc_t)crc);
+    c = ~c;
+    while (len && ((ptrdiff_t)buf & 3)) {
+        c = crc_table[4][(c >> 24) ^ *buf++] ^ (c << 8);
+        len--;
+    }
+
+    buf4 = (const z_crc_t FAR *)(const void FAR *)buf;
+    while (len >= 32) {
+        DOBIG32;
+        len -= 32;
+    }
+    while (len >= 4) {
+        DOBIG4;
+        len -= 4;
+    }
+    buf = (const unsigned char FAR *)buf4;
+
+    if (len) do {
+        c = crc_table[4][(c >> 24) ^ *buf++] ^ (c << 8);
+    } while (--len);
+    c = ~c;
+    return (unsigned long)(ZSWAP32(c));
+}
+
+#endif /* BYFOUR */
+
+#define GF2_DIM 32      /* dimension of GF(2) vectors (length of CRC) */
+
+/* ========================================================================= */
+local unsigned long gf2_matrix_times(mat, vec)
+    unsigned long *mat;
+    unsigned long vec;
+{
+    unsigned long sum;
+
+    sum = 0;
+    while (vec) {
+        if (vec & 1)
+            sum ^= *mat;
+        vec >>= 1;
+        mat++;
+    }
+    return sum;
+}
+
+/* ========================================================================= */
+local void gf2_matrix_square(square, mat)
+    unsigned long *square;
+    unsigned long *mat;
+{
+    int n;
+
+    for (n = 0; n < GF2_DIM; n++)
+        square[n] = gf2_matrix_times(mat, mat[n]);
+}
+
+/* ========================================================================= */
+local uLong crc32_combine_(crc1, crc2, len2)
+    uLong crc1;
+    uLong crc2;
+    z_off64_t len2;
+{
+    int n;
+    unsigned long row;
+    unsigned long even[GF2_DIM];    /* even-power-of-two zeros operator */
+    unsigned long odd[GF2_DIM];     /* odd-power-of-two zeros operator */
+
+    /* degenerate case (also disallow negative lengths) */
+    if (len2 <= 0)
+        return crc1;
+
+    /* put operator for one zero bit in odd */
+    odd[0] = 0xedb88320UL;          /* CRC-32 polynomial */
+    row = 1;
+    for (n = 1; n < GF2_DIM; n++) {
+        odd[n] = row;
+        row <<= 1;
+    }
+
+    /* put operator for two zero bits in even */
+    gf2_matrix_square(even, odd);
+
+    /* put operator for four zero bits in odd */
+    gf2_matrix_square(odd, even);
+
+    /* apply len2 zeros to crc1 (first square will put the operator for one
+       zero byte, eight zero bits, in even) */
+    do {
+        /* apply zeros operator for this bit of len2 */
+        gf2_matrix_square(even, odd);
+        if (len2 & 1)
+            crc1 = gf2_matrix_times(even, crc1);
+        len2 >>= 1;
+
+        /* if no more bits set, then done */
+        if (len2 == 0)
+            break;
+
+        /* another iteration of the loop with odd and even swapped */
+        gf2_matrix_square(odd, even);
+        if (len2 & 1)
+            crc1 = gf2_matrix_times(odd, crc1);
+        len2 >>= 1;
+
+        /* if no more bits set, then done */
+    } while (len2 != 0);
+
+    /* return combined crc */
+    crc1 ^= crc2;
+    return crc1;
+}
+
+/* ========================================================================= */
+uLong ZEXPORT crc32_combine(crc1, crc2, len2)
+    uLong crc1;
+    uLong crc2;
+    z_off_t len2;
+{
+    return crc32_combine_(crc1, crc2, len2);
+}
+
+uLong ZEXPORT crc32_combine64(crc1, crc2, len2)
+    uLong crc1;
+    uLong crc2;
+    z_off64_t len2;
+{
+    return crc32_combine_(crc1, crc2, len2);
+}

ADDED   3rd_party/zlib/crc32.h
Index: 3rd_party/zlib/crc32.h
==================================================================
--- 3rd_party/zlib/crc32.h
+++ 3rd_party/zlib/crc32.h
@@ -0,0 +1,441 @@
+/* crc32.h -- tables for rapid CRC calculation
+ * Generated automatically by crc32.c
+ */
+
+local const z_crc_t FAR crc_table[TBLS][256] =
+{
+  {
+    0x00000000UL, 0x77073096UL, 0xee0e612cUL, 0x990951baUL, 0x076dc419UL,
+    0x706af48fUL, 0xe963a535UL, 0x9e6495a3UL, 0x0edb8832UL, 0x79dcb8a4UL,
+    0xe0d5e91eUL, 0x97d2d988UL, 0x09b64c2bUL, 0x7eb17cbdUL, 0xe7b82d07UL,
+    0x90bf1d91UL, 0x1db71064UL, 0x6ab020f2UL, 0xf3b97148UL, 0x84be41deUL,
+    0x1adad47dUL, 0x6ddde4ebUL, 0xf4d4b551UL, 0x83d385c7UL, 0x136c9856UL,
+    0x646ba8c0UL, 0xfd62f97aUL, 0x8a65c9ecUL, 0x14015c4fUL, 0x63066cd9UL,
+    0xfa0f3d63UL, 0x8d080df5UL, 0x3b6e20c8UL, 0x4c69105eUL, 0xd56041e4UL,
+    0xa2677172UL, 0x3c03e4d1UL, 0x4b04d447UL, 0xd20d85fdUL, 0xa50ab56bUL,
+    0x35b5a8faUL, 0x42b2986cUL, 0xdbbbc9d6UL, 0xacbcf940UL, 0x32d86ce3UL,
+    0x45df5c75UL, 0xdcd60dcfUL, 0xabd13d59UL, 0x26d930acUL, 0x51de003aUL,
+    0xc8d75180UL, 0xbfd06116UL, 0x21b4f4b5UL, 0x56b3c423UL, 0xcfba9599UL,
+    0xb8bda50fUL, 0x2802b89eUL, 0x5f058808UL, 0xc60cd9b2UL, 0xb10be924UL,
+    0x2f6f7c87UL, 0x58684c11UL, 0xc1611dabUL, 0xb6662d3dUL, 0x76dc4190UL,
+    0x01db7106UL, 0x98d220bcUL, 0xefd5102aUL, 0x71b18589UL, 0x06b6b51fUL,
+    0x9fbfe4a5UL, 0xe8b8d433UL, 0x7807c9a2UL, 0x0f00f934UL, 0x9609a88eUL,
+    0xe10e9818UL, 0x7f6a0dbbUL, 0x086d3d2dUL, 0x91646c97UL, 0xe6635c01UL,
+    0x6b6b51f4UL, 0x1c6c6162UL, 0x856530d8UL, 0xf262004eUL, 0x6c0695edUL,
+    0x1b01a57bUL, 0x8208f4c1UL, 0xf50fc457UL, 0x65b0d9c6UL, 0x12b7e950UL,
+    0x8bbeb8eaUL, 0xfcb9887cUL, 0x62dd1ddfUL, 0x15da2d49UL, 0x8cd37cf3UL,
+    0xfbd44c65UL, 0x4db26158UL, 0x3ab551ceUL, 0xa3bc0074UL, 0xd4bb30e2UL,
+    0x4adfa541UL, 0x3dd895d7UL, 0xa4d1c46dUL, 0xd3d6f4fbUL, 0x4369e96aUL,
+    0x346ed9fcUL, 0xad678846UL, 0xda60b8d0UL, 0x44042d73UL, 0x33031de5UL,
+    0xaa0a4c5fUL, 0xdd0d7cc9UL, 0x5005713cUL, 0x270241aaUL, 0xbe0b1010UL,
+    0xc90c2086UL, 0x5768b525UL, 0x206f85b3UL, 0xb966d409UL, 0xce61e49fUL,
+    0x5edef90eUL, 0x29d9c998UL, 0xb0d09822UL, 0xc7d7a8b4UL, 0x59b33d17UL,
+    0x2eb40d81UL, 0xb7bd5c3bUL, 0xc0ba6cadUL, 0xedb88320UL, 0x9abfb3b6UL,
+    0x03b6e20cUL, 0x74b1d29aUL, 0xead54739UL, 0x9dd277afUL, 0x04db2615UL,
+    0x73dc1683UL, 0xe3630b12UL, 0x94643b84UL, 0x0d6d6a3eUL, 0x7a6a5aa8UL,
+    0xe40ecf0bUL, 0x9309ff9dUL, 0x0a00ae27UL, 0x7d079eb1UL, 0xf00f9344UL,
+    0x8708a3d2UL, 0x1e01f268UL, 0x6906c2feUL, 0xf762575dUL, 0x806567cbUL,
+    0x196c3671UL, 0x6e6b06e7UL, 0xfed41b76UL, 0x89d32be0UL, 0x10da7a5aUL,
+    0x67dd4accUL, 0xf9b9df6fUL, 0x8ebeeff9UL, 0x17b7be43UL, 0x60b08ed5UL,
+    0xd6d6a3e8UL, 0xa1d1937eUL, 0x38d8c2c4UL, 0x4fdff252UL, 0xd1bb67f1UL,
+    0xa6bc5767UL, 0x3fb506ddUL, 0x48b2364bUL, 0xd80d2bdaUL, 0xaf0a1b4cUL,
+    0x36034af6UL, 0x41047a60UL, 0xdf60efc3UL, 0xa867df55UL, 0x316e8eefUL,
+    0x4669be79UL, 0xcb61b38cUL, 0xbc66831aUL, 0x256fd2a0UL, 0x5268e236UL,
+    0xcc0c7795UL, 0xbb0b4703UL, 0x220216b9UL, 0x5505262fUL, 0xc5ba3bbeUL,
+    0xb2bd0b28UL, 0x2bb45a92UL, 0x5cb36a04UL, 0xc2d7ffa7UL, 0xb5d0cf31UL,
+    0x2cd99e8bUL, 0x5bdeae1dUL, 0x9b64c2b0UL, 0xec63f226UL, 0x756aa39cUL,
+    0x026d930aUL, 0x9c0906a9UL, 0xeb0e363fUL, 0x72076785UL, 0x05005713UL,
+    0x95bf4a82UL, 0xe2b87a14UL, 0x7bb12baeUL, 0x0cb61b38UL, 0x92d28e9bUL,
+    0xe5d5be0dUL, 0x7cdcefb7UL, 0x0bdbdf21UL, 0x86d3d2d4UL, 0xf1d4e242UL,
+    0x68ddb3f8UL, 0x1fda836eUL, 0x81be16cdUL, 0xf6b9265bUL, 0x6fb077e1UL,
+    0x18b74777UL, 0x88085ae6UL, 0xff0f6a70UL, 0x66063bcaUL, 0x11010b5cUL,
+    0x8f659effUL, 0xf862ae69UL, 0x616bffd3UL, 0x166ccf45UL, 0xa00ae278UL,
+    0xd70dd2eeUL, 0x4e048354UL, 0x3903b3c2UL, 0xa7672661UL, 0xd06016f7UL,
+    0x4969474dUL, 0x3e6e77dbUL, 0xaed16a4aUL, 0xd9d65adcUL, 0x40df0b66UL,
+    0x37d83bf0UL, 0xa9bcae53UL, 0xdebb9ec5UL, 0x47b2cf7fUL, 0x30b5ffe9UL,
+    0xbdbdf21cUL, 0xcabac28aUL, 0x53b39330UL, 0x24b4a3a6UL, 0xbad03605UL,
+    0xcdd70693UL, 0x54de5729UL, 0x23d967bfUL, 0xb3667a2eUL, 0xc4614ab8UL,
+    0x5d681b02UL, 0x2a6f2b94UL, 0xb40bbe37UL, 0xc30c8ea1UL, 0x5a05df1bUL,
+    0x2d02ef8dUL
+#ifdef BYFOUR
+  },
+  {
+    0x00000000UL, 0x191b3141UL, 0x32366282UL, 0x2b2d53c3UL, 0x646cc504UL,
+    0x7d77f445UL, 0x565aa786UL, 0x4f4196c7UL, 0xc8d98a08UL, 0xd1c2bb49UL,
+    0xfaefe88aUL, 0xe3f4d9cbUL, 0xacb54f0cUL, 0xb5ae7e4dUL, 0x9e832d8eUL,
+    0x87981ccfUL, 0x4ac21251UL, 0x53d92310UL, 0x78f470d3UL, 0x61ef4192UL,
+    0x2eaed755UL, 0x37b5e614UL, 0x1c98b5d7UL, 0x05838496UL, 0x821b9859UL,
+    0x9b00a918UL, 0xb02dfadbUL, 0xa936cb9aUL, 0xe6775d5dUL, 0xff6c6c1cUL,
+    0xd4413fdfUL, 0xcd5a0e9eUL, 0x958424a2UL, 0x8c9f15e3UL, 0xa7b24620UL,
+    0xbea97761UL, 0xf1e8e1a6UL, 0xe8f3d0e7UL, 0xc3de8324UL, 0xdac5b265UL,
+    0x5d5daeaaUL, 0x44469febUL, 0x6f6bcc28UL, 0x7670fd69UL, 0x39316baeUL,
+    0x202a5aefUL, 0x0b07092cUL, 0x121c386dUL, 0xdf4636f3UL, 0xc65d07b2UL,
+    0xed705471UL, 0xf46b6530UL, 0xbb2af3f7UL, 0xa231c2b6UL, 0x891c9175UL,
+    0x9007a034UL, 0x179fbcfbUL, 0x0e848dbaUL, 0x25a9de79UL, 0x3cb2ef38UL,
+    0x73f379ffUL, 0x6ae848beUL, 0x41c51b7dUL, 0x58de2a3cUL, 0xf0794f05UL,
+    0xe9627e44UL, 0xc24f2d87UL, 0xdb541cc6UL, 0x94158a01UL, 0x8d0ebb40UL,
+    0xa623e883UL, 0xbf38d9c2UL, 0x38a0c50dUL, 0x21bbf44cUL, 0x0a96a78fUL,
+    0x138d96ceUL, 0x5ccc0009UL, 0x45d73148UL, 0x6efa628bUL, 0x77e153caUL,
+    0xbabb5d54UL, 0xa3a06c15UL, 0x888d3fd6UL, 0x91960e97UL, 0xded79850UL,
+    0xc7cca911UL, 0xece1fad2UL, 0xf5facb93UL, 0x7262d75cUL, 0x6b79e61dUL,
+    0x4054b5deUL, 0x594f849fUL, 0x160e1258UL, 0x0f152319UL, 0x243870daUL,
+    0x3d23419bUL, 0x65fd6ba7UL, 0x7ce65ae6UL, 0x57cb0925UL, 0x4ed03864UL,
+    0x0191aea3UL, 0x188a9fe2UL, 0x33a7cc21UL, 0x2abcfd60UL, 0xad24e1afUL,
+    0xb43fd0eeUL, 0x9f12832dUL, 0x8609b26cUL, 0xc94824abUL, 0xd05315eaUL,
+    0xfb7e4629UL, 0xe2657768UL, 0x2f3f79f6UL, 0x362448b7UL, 0x1d091b74UL,
+    0x04122a35UL, 0x4b53bcf2UL, 0x52488db3UL, 0x7965de70UL, 0x607eef31UL,
+    0xe7e6f3feUL, 0xfefdc2bfUL, 0xd5d0917cUL, 0xcccba03dUL, 0x838a36faUL,
+    0x9a9107bbUL, 0xb1bc5478UL, 0xa8a76539UL, 0x3b83984bUL, 0x2298a90aUL,
+    0x09b5fac9UL, 0x10aecb88UL, 0x5fef5d4fUL, 0x46f46c0eUL, 0x6dd93fcdUL,
+    0x74c20e8cUL, 0xf35a1243UL, 0xea412302UL, 0xc16c70c1UL, 0xd8774180UL,
+    0x9736d747UL, 0x8e2de606UL, 0xa500b5c5UL, 0xbc1b8484UL, 0x71418a1aUL,
+    0x685abb5bUL, 0x4377e898UL, 0x5a6cd9d9UL, 0x152d4f1eUL, 0x0c367e5fUL,
+    0x271b2d9cUL, 0x3e001cddUL, 0xb9980012UL, 0xa0833153UL, 0x8bae6290UL,
+    0x92b553d1UL, 0xddf4c516UL, 0xc4eff457UL, 0xefc2a794UL, 0xf6d996d5UL,
+    0xae07bce9UL, 0xb71c8da8UL, 0x9c31de6bUL, 0x852aef2aUL, 0xca6b79edUL,
+    0xd37048acUL, 0xf85d1b6fUL, 0xe1462a2eUL, 0x66de36e1UL, 0x7fc507a0UL,
+    0x54e85463UL, 0x4df36522UL, 0x02b2f3e5UL, 0x1ba9c2a4UL, 0x30849167UL,
+    0x299fa026UL, 0xe4c5aeb8UL, 0xfdde9ff9UL, 0xd6f3cc3aUL, 0xcfe8fd7bUL,
+    0x80a96bbcUL, 0x99b25afdUL, 0xb29f093eUL, 0xab84387fUL, 0x2c1c24b0UL,
+    0x350715f1UL, 0x1e2a4632UL, 0x07317773UL, 0x4870e1b4UL, 0x516bd0f5UL,
+    0x7a468336UL, 0x635db277UL, 0xcbfad74eUL, 0xd2e1e60fUL, 0xf9ccb5ccUL,
+    0xe0d7848dUL, 0xaf96124aUL, 0xb68d230bUL, 0x9da070c8UL, 0x84bb4189UL,
+    0x03235d46UL, 0x1a386c07UL, 0x31153fc4UL, 0x280e0e85UL, 0x674f9842UL,
+    0x7e54a903UL, 0x5579fac0UL, 0x4c62cb81UL, 0x8138c51fUL, 0x9823f45eUL,
+    0xb30ea79dUL, 0xaa1596dcUL, 0xe554001bUL, 0xfc4f315aUL, 0xd7626299UL,
+    0xce7953d8UL, 0x49e14f17UL, 0x50fa7e56UL, 0x7bd72d95UL, 0x62cc1cd4UL,
+    0x2d8d8a13UL, 0x3496bb52UL, 0x1fbbe891UL, 0x06a0d9d0UL, 0x5e7ef3ecUL,
+    0x4765c2adUL, 0x6c48916eUL, 0x7553a02fUL, 0x3a1236e8UL, 0x230907a9UL,
+    0x0824546aUL, 0x113f652bUL, 0x96a779e4UL, 0x8fbc48a5UL, 0xa4911b66UL,
+    0xbd8a2a27UL, 0xf2cbbce0UL, 0xebd08da1UL, 0xc0fdde62UL, 0xd9e6ef23UL,
+    0x14bce1bdUL, 0x0da7d0fcUL, 0x268a833fUL, 0x3f91b27eUL, 0x70d024b9UL,
+    0x69cb15f8UL, 0x42e6463bUL, 0x5bfd777aUL, 0xdc656bb5UL, 0xc57e5af4UL,
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+    0x9324fd72UL
+  },
+  {
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+    0xb853f606UL, 0xb9919c31UL, 0xbcde8ab4UL, 0xbd1ce083UL, 0xbf5a5edaUL,
+    0xbe9834edUL
+  },
+  {
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+    0xe9dbf6c3UL, 0x516791a6UL, 0xccb0a91fUL, 0x740cce7aUL, 0x66b96194UL,
+    0xde0506f1UL
+  },
+  {
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+    0x8b9ed92cUL, 0x1daede5bUL, 0xb0c2649bUL, 0x26f263ecUL, 0x9ca36a75UL,
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+    0xf8b3dd68UL, 0x6e83da1fUL, 0xcd16be81UL, 0x5b26b9f6UL, 0xe177b06fUL,
+    0x7747b718UL, 0xe65a0888UL, 0x706a0fffUL, 0xca3b0666UL, 0x5c0b0111UL,
+    0xff9e658fUL, 0x69ae62f8UL, 0xd3ff6b61UL, 0x45cf6c16UL, 0x78e20aa0UL,
+    0xeed20dd7UL, 0x5483044eUL, 0xc2b30339UL, 0x612667a7UL, 0xf71660d0UL,
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+    0x021b685dUL, 0x942b6f2aUL, 0x37be0bb4UL, 0xa18e0cc3UL, 0x1bdf055aUL,
+    0x8def022dUL
+  },
+  {
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+    0xef5a2a20UL, 0x2c09070bUL, 0x6d381c12UL, 0xf33646dfUL, 0xb2075dc6UL,
+    0x715470edUL, 0x30656bf4UL, 0xf7f32abbUL, 0xb6c231a2UL, 0x75911c89UL,
+    0x34a00790UL, 0xfbbc9f17UL, 0xba8d840eUL, 0x79dea925UL, 0x38efb23cUL,
+    0xff79f373UL, 0xbe48e86aUL, 0x7d1bc541UL, 0x3c2ade58UL, 0x054f79f0UL,
+    0x447e62e9UL, 0x872d4fc2UL, 0xc61c54dbUL, 0x018a1594UL, 0x40bb0e8dUL,
+    0x83e823a6UL, 0xc2d938bfUL, 0x0dc5a038UL, 0x4cf4bb21UL, 0x8fa7960aUL,
+    0xce968d13UL, 0x0900cc5cUL, 0x4831d745UL, 0x8b62fa6eUL, 0xca53e177UL,
+    0x545dbbbaUL, 0x156ca0a3UL, 0xd63f8d88UL, 0x970e9691UL, 0x5098d7deUL,
+    0x11a9ccc7UL, 0xd2fae1ecUL, 0x93cbfaf5UL, 0x5cd76272UL, 0x1de6796bUL,
+    0xdeb55440UL, 0x9f844f59UL, 0x58120e16UL, 0x1923150fUL, 0xda703824UL,
+    0x9b41233dUL, 0xa76bfd65UL, 0xe65ae67cUL, 0x2509cb57UL, 0x6438d04eUL,
+    0xa3ae9101UL, 0xe29f8a18UL, 0x21cca733UL, 0x60fdbc2aUL, 0xafe124adUL,
+    0xeed03fb4UL, 0x2d83129fUL, 0x6cb20986UL, 0xab2448c9UL, 0xea1553d0UL,
+    0x29467efbUL, 0x687765e2UL, 0xf6793f2fUL, 0xb7482436UL, 0x741b091dUL,
+    0x352a1204UL, 0xf2bc534bUL, 0xb38d4852UL, 0x70de6579UL, 0x31ef7e60UL,
+    0xfef3e6e7UL, 0xbfc2fdfeUL, 0x7c91d0d5UL, 0x3da0cbccUL, 0xfa368a83UL,
+    0xbb07919aUL, 0x7854bcb1UL, 0x3965a7a8UL, 0x4b98833bUL, 0x0aa99822UL,
+    0xc9fab509UL, 0x88cbae10UL, 0x4f5def5fUL, 0x0e6cf446UL, 0xcd3fd96dUL,
+    0x8c0ec274UL, 0x43125af3UL, 0x022341eaUL, 0xc1706cc1UL, 0x804177d8UL,
+    0x47d73697UL, 0x06e62d8eUL, 0xc5b500a5UL, 0x84841bbcUL, 0x1a8a4171UL,
+    0x5bbb5a68UL, 0x98e87743UL, 0xd9d96c5aUL, 0x1e4f2d15UL, 0x5f7e360cUL,
+    0x9c2d1b27UL, 0xdd1c003eUL, 0x120098b9UL, 0x533183a0UL, 0x9062ae8bUL,
+    0xd153b592UL, 0x16c5f4ddUL, 0x57f4efc4UL, 0x94a7c2efUL, 0xd596d9f6UL,
+    0xe9bc07aeUL, 0xa88d1cb7UL, 0x6bde319cUL, 0x2aef2a85UL, 0xed796bcaUL,
+    0xac4870d3UL, 0x6f1b5df8UL, 0x2e2a46e1UL, 0xe136de66UL, 0xa007c57fUL,
+    0x6354e854UL, 0x2265f34dUL, 0xe5f3b202UL, 0xa4c2a91bUL, 0x67918430UL,
+    0x26a09f29UL, 0xb8aec5e4UL, 0xf99fdefdUL, 0x3accf3d6UL, 0x7bfde8cfUL,
+    0xbc6ba980UL, 0xfd5ab299UL, 0x3e099fb2UL, 0x7f3884abUL, 0xb0241c2cUL,
+    0xf1150735UL, 0x32462a1eUL, 0x73773107UL, 0xb4e17048UL, 0xf5d06b51UL,
+    0x3683467aUL, 0x77b25d63UL, 0x4ed7facbUL, 0x0fe6e1d2UL, 0xccb5ccf9UL,
+    0x8d84d7e0UL, 0x4a1296afUL, 0x0b238db6UL, 0xc870a09dUL, 0x8941bb84UL,
+    0x465d2303UL, 0x076c381aUL, 0xc43f1531UL, 0x850e0e28UL, 0x42984f67UL,
+    0x03a9547eUL, 0xc0fa7955UL, 0x81cb624cUL, 0x1fc53881UL, 0x5ef42398UL,
+    0x9da70eb3UL, 0xdc9615aaUL, 0x1b0054e5UL, 0x5a314ffcUL, 0x996262d7UL,
+    0xd85379ceUL, 0x174fe149UL, 0x567efa50UL, 0x952dd77bUL, 0xd41ccc62UL,
+    0x138a8d2dUL, 0x52bb9634UL, 0x91e8bb1fUL, 0xd0d9a006UL, 0xecf37e5eUL,
+    0xadc26547UL, 0x6e91486cUL, 0x2fa05375UL, 0xe836123aUL, 0xa9070923UL,
+    0x6a542408UL, 0x2b653f11UL, 0xe479a796UL, 0xa548bc8fUL, 0x661b91a4UL,
+    0x272a8abdUL, 0xe0bccbf2UL, 0xa18dd0ebUL, 0x62defdc0UL, 0x23efe6d9UL,
+    0xbde1bc14UL, 0xfcd0a70dUL, 0x3f838a26UL, 0x7eb2913fUL, 0xb924d070UL,
+    0xf815cb69UL, 0x3b46e642UL, 0x7a77fd5bUL, 0xb56b65dcUL, 0xf45a7ec5UL,
+    0x370953eeUL, 0x763848f7UL, 0xb1ae09b8UL, 0xf09f12a1UL, 0x33cc3f8aUL,
+    0x72fd2493UL
+  },
+  {
+    0x00000000UL, 0x376ac201UL, 0x6ed48403UL, 0x59be4602UL, 0xdca80907UL,
+    0xebc2cb06UL, 0xb27c8d04UL, 0x85164f05UL, 0xb851130eUL, 0x8f3bd10fUL,
+    0xd685970dUL, 0xe1ef550cUL, 0x64f91a09UL, 0x5393d808UL, 0x0a2d9e0aUL,
+    0x3d475c0bUL, 0x70a3261cUL, 0x47c9e41dUL, 0x1e77a21fUL, 0x291d601eUL,
+    0xac0b2f1bUL, 0x9b61ed1aUL, 0xc2dfab18UL, 0xf5b56919UL, 0xc8f23512UL,
+    0xff98f713UL, 0xa626b111UL, 0x914c7310UL, 0x145a3c15UL, 0x2330fe14UL,
+    0x7a8eb816UL, 0x4de47a17UL, 0xe0464d38UL, 0xd72c8f39UL, 0x8e92c93bUL,
+    0xb9f80b3aUL, 0x3cee443fUL, 0x0b84863eUL, 0x523ac03cUL, 0x6550023dUL,
+    0x58175e36UL, 0x6f7d9c37UL, 0x36c3da35UL, 0x01a91834UL, 0x84bf5731UL,
+    0xb3d59530UL, 0xea6bd332UL, 0xdd011133UL, 0x90e56b24UL, 0xa78fa925UL,
+    0xfe31ef27UL, 0xc95b2d26UL, 0x4c4d6223UL, 0x7b27a022UL, 0x2299e620UL,
+    0x15f32421UL, 0x28b4782aUL, 0x1fdeba2bUL, 0x4660fc29UL, 0x710a3e28UL,
+    0xf41c712dUL, 0xc376b32cUL, 0x9ac8f52eUL, 0xada2372fUL, 0xc08d9a70UL,
+    0xf7e75871UL, 0xae591e73UL, 0x9933dc72UL, 0x1c259377UL, 0x2b4f5176UL,
+    0x72f11774UL, 0x459bd575UL, 0x78dc897eUL, 0x4fb64b7fUL, 0x16080d7dUL,
+    0x2162cf7cUL, 0xa4748079UL, 0x931e4278UL, 0xcaa0047aUL, 0xfdcac67bUL,
+    0xb02ebc6cUL, 0x87447e6dUL, 0xdefa386fUL, 0xe990fa6eUL, 0x6c86b56bUL,
+    0x5bec776aUL, 0x02523168UL, 0x3538f369UL, 0x087faf62UL, 0x3f156d63UL,
+    0x66ab2b61UL, 0x51c1e960UL, 0xd4d7a665UL, 0xe3bd6464UL, 0xba032266UL,
+    0x8d69e067UL, 0x20cbd748UL, 0x17a11549UL, 0x4e1f534bUL, 0x7975914aUL,
+    0xfc63de4fUL, 0xcb091c4eUL, 0x92b75a4cUL, 0xa5dd984dUL, 0x989ac446UL,
+    0xaff00647UL, 0xf64e4045UL, 0xc1248244UL, 0x4432cd41UL, 0x73580f40UL,
+    0x2ae64942UL, 0x1d8c8b43UL, 0x5068f154UL, 0x67023355UL, 0x3ebc7557UL,
+    0x09d6b756UL, 0x8cc0f853UL, 0xbbaa3a52UL, 0xe2147c50UL, 0xd57ebe51UL,
+    0xe839e25aUL, 0xdf53205bUL, 0x86ed6659UL, 0xb187a458UL, 0x3491eb5dUL,
+    0x03fb295cUL, 0x5a456f5eUL, 0x6d2fad5fUL, 0x801b35e1UL, 0xb771f7e0UL,
+    0xeecfb1e2UL, 0xd9a573e3UL, 0x5cb33ce6UL, 0x6bd9fee7UL, 0x3267b8e5UL,
+    0x050d7ae4UL, 0x384a26efUL, 0x0f20e4eeUL, 0x569ea2ecUL, 0x61f460edUL,
+    0xe4e22fe8UL, 0xd388ede9UL, 0x8a36abebUL, 0xbd5c69eaUL, 0xf0b813fdUL,
+    0xc7d2d1fcUL, 0x9e6c97feUL, 0xa90655ffUL, 0x2c101afaUL, 0x1b7ad8fbUL,
+    0x42c49ef9UL, 0x75ae5cf8UL, 0x48e900f3UL, 0x7f83c2f2UL, 0x263d84f0UL,
+    0x115746f1UL, 0x944109f4UL, 0xa32bcbf5UL, 0xfa958df7UL, 0xcdff4ff6UL,
+    0x605d78d9UL, 0x5737bad8UL, 0x0e89fcdaUL, 0x39e33edbUL, 0xbcf571deUL,
+    0x8b9fb3dfUL, 0xd221f5ddUL, 0xe54b37dcUL, 0xd80c6bd7UL, 0xef66a9d6UL,
+    0xb6d8efd4UL, 0x81b22dd5UL, 0x04a462d0UL, 0x33cea0d1UL, 0x6a70e6d3UL,
+    0x5d1a24d2UL, 0x10fe5ec5UL, 0x27949cc4UL, 0x7e2adac6UL, 0x494018c7UL,
+    0xcc5657c2UL, 0xfb3c95c3UL, 0xa282d3c1UL, 0x95e811c0UL, 0xa8af4dcbUL,
+    0x9fc58fcaUL, 0xc67bc9c8UL, 0xf1110bc9UL, 0x740744ccUL, 0x436d86cdUL,
+    0x1ad3c0cfUL, 0x2db902ceUL, 0x4096af91UL, 0x77fc6d90UL, 0x2e422b92UL,
+    0x1928e993UL, 0x9c3ea696UL, 0xab546497UL, 0xf2ea2295UL, 0xc580e094UL,
+    0xf8c7bc9fUL, 0xcfad7e9eUL, 0x9613389cUL, 0xa179fa9dUL, 0x246fb598UL,
+    0x13057799UL, 0x4abb319bUL, 0x7dd1f39aUL, 0x3035898dUL, 0x075f4b8cUL,
+    0x5ee10d8eUL, 0x698bcf8fUL, 0xec9d808aUL, 0xdbf7428bUL, 0x82490489UL,
+    0xb523c688UL, 0x88649a83UL, 0xbf0e5882UL, 0xe6b01e80UL, 0xd1dadc81UL,
+    0x54cc9384UL, 0x63a65185UL, 0x3a181787UL, 0x0d72d586UL, 0xa0d0e2a9UL,
+    0x97ba20a8UL, 0xce0466aaUL, 0xf96ea4abUL, 0x7c78ebaeUL, 0x4b1229afUL,
+    0x12ac6fadUL, 0x25c6adacUL, 0x1881f1a7UL, 0x2feb33a6UL, 0x765575a4UL,
+    0x413fb7a5UL, 0xc429f8a0UL, 0xf3433aa1UL, 0xaafd7ca3UL, 0x9d97bea2UL,
+    0xd073c4b5UL, 0xe71906b4UL, 0xbea740b6UL, 0x89cd82b7UL, 0x0cdbcdb2UL,
+    0x3bb10fb3UL, 0x620f49b1UL, 0x55658bb0UL, 0x6822d7bbUL, 0x5f4815baUL,
+    0x06f653b8UL, 0x319c91b9UL, 0xb48adebcUL, 0x83e01cbdUL, 0xda5e5abfUL,
+    0xed3498beUL
+  },
+  {
+    0x00000000UL, 0x6567bcb8UL, 0x8bc809aaUL, 0xeeafb512UL, 0x5797628fUL,
+    0x32f0de37UL, 0xdc5f6b25UL, 0xb938d79dUL, 0xef28b4c5UL, 0x8a4f087dUL,
+    0x64e0bd6fUL, 0x018701d7UL, 0xb8bfd64aUL, 0xddd86af2UL, 0x3377dfe0UL,
+    0x56106358UL, 0x9f571950UL, 0xfa30a5e8UL, 0x149f10faUL, 0x71f8ac42UL,
+    0xc8c07bdfUL, 0xada7c767UL, 0x43087275UL, 0x266fcecdUL, 0x707fad95UL,
+    0x1518112dUL, 0xfbb7a43fUL, 0x9ed01887UL, 0x27e8cf1aUL, 0x428f73a2UL,
+    0xac20c6b0UL, 0xc9477a08UL, 0x3eaf32a0UL, 0x5bc88e18UL, 0xb5673b0aUL,
+    0xd00087b2UL, 0x6938502fUL, 0x0c5fec97UL, 0xe2f05985UL, 0x8797e53dUL,
+    0xd1878665UL, 0xb4e03addUL, 0x5a4f8fcfUL, 0x3f283377UL, 0x8610e4eaUL,
+    0xe3775852UL, 0x0dd8ed40UL, 0x68bf51f8UL, 0xa1f82bf0UL, 0xc49f9748UL,
+    0x2a30225aUL, 0x4f579ee2UL, 0xf66f497fUL, 0x9308f5c7UL, 0x7da740d5UL,
+    0x18c0fc6dUL, 0x4ed09f35UL, 0x2bb7238dUL, 0xc518969fUL, 0xa07f2a27UL,
+    0x1947fdbaUL, 0x7c204102UL, 0x928ff410UL, 0xf7e848a8UL, 0x3d58149bUL,
+    0x583fa823UL, 0xb6901d31UL, 0xd3f7a189UL, 0x6acf7614UL, 0x0fa8caacUL,
+    0xe1077fbeUL, 0x8460c306UL, 0xd270a05eUL, 0xb7171ce6UL, 0x59b8a9f4UL,
+    0x3cdf154cUL, 0x85e7c2d1UL, 0xe0807e69UL, 0x0e2fcb7bUL, 0x6b4877c3UL,
+    0xa20f0dcbUL, 0xc768b173UL, 0x29c70461UL, 0x4ca0b8d9UL, 0xf5986f44UL,
+    0x90ffd3fcUL, 0x7e5066eeUL, 0x1b37da56UL, 0x4d27b90eUL, 0x284005b6UL,
+    0xc6efb0a4UL, 0xa3880c1cUL, 0x1ab0db81UL, 0x7fd76739UL, 0x9178d22bUL,
+    0xf41f6e93UL, 0x03f7263bUL, 0x66909a83UL, 0x883f2f91UL, 0xed589329UL,
+    0x546044b4UL, 0x3107f80cUL, 0xdfa84d1eUL, 0xbacff1a6UL, 0xecdf92feUL,
+    0x89b82e46UL, 0x67179b54UL, 0x027027ecUL, 0xbb48f071UL, 0xde2f4cc9UL,
+    0x3080f9dbUL, 0x55e74563UL, 0x9ca03f6bUL, 0xf9c783d3UL, 0x176836c1UL,
+    0x720f8a79UL, 0xcb375de4UL, 0xae50e15cUL, 0x40ff544eUL, 0x2598e8f6UL,
+    0x73888baeUL, 0x16ef3716UL, 0xf8408204UL, 0x9d273ebcUL, 0x241fe921UL,
+    0x41785599UL, 0xafd7e08bUL, 0xcab05c33UL, 0x3bb659edUL, 0x5ed1e555UL,
+    0xb07e5047UL, 0xd519ecffUL, 0x6c213b62UL, 0x094687daUL, 0xe7e932c8UL,
+    0x828e8e70UL, 0xd49eed28UL, 0xb1f95190UL, 0x5f56e482UL, 0x3a31583aUL,
+    0x83098fa7UL, 0xe66e331fUL, 0x08c1860dUL, 0x6da63ab5UL, 0xa4e140bdUL,
+    0xc186fc05UL, 0x2f294917UL, 0x4a4ef5afUL, 0xf3762232UL, 0x96119e8aUL,
+    0x78be2b98UL, 0x1dd99720UL, 0x4bc9f478UL, 0x2eae48c0UL, 0xc001fdd2UL,
+    0xa566416aUL, 0x1c5e96f7UL, 0x79392a4fUL, 0x97969f5dUL, 0xf2f123e5UL,
+    0x05196b4dUL, 0x607ed7f5UL, 0x8ed162e7UL, 0xebb6de5fUL, 0x528e09c2UL,
+    0x37e9b57aUL, 0xd9460068UL, 0xbc21bcd0UL, 0xea31df88UL, 0x8f566330UL,
+    0x61f9d622UL, 0x049e6a9aUL, 0xbda6bd07UL, 0xd8c101bfUL, 0x366eb4adUL,
+    0x53090815UL, 0x9a4e721dUL, 0xff29cea5UL, 0x11867bb7UL, 0x74e1c70fUL,
+    0xcdd91092UL, 0xa8beac2aUL, 0x46111938UL, 0x2376a580UL, 0x7566c6d8UL,
+    0x10017a60UL, 0xfeaecf72UL, 0x9bc973caUL, 0x22f1a457UL, 0x479618efUL,
+    0xa939adfdUL, 0xcc5e1145UL, 0x06ee4d76UL, 0x6389f1ceUL, 0x8d2644dcUL,
+    0xe841f864UL, 0x51792ff9UL, 0x341e9341UL, 0xdab12653UL, 0xbfd69aebUL,
+    0xe9c6f9b3UL, 0x8ca1450bUL, 0x620ef019UL, 0x07694ca1UL, 0xbe519b3cUL,
+    0xdb362784UL, 0x35999296UL, 0x50fe2e2eUL, 0x99b95426UL, 0xfcdee89eUL,
+    0x12715d8cUL, 0x7716e134UL, 0xce2e36a9UL, 0xab498a11UL, 0x45e63f03UL,
+    0x208183bbUL, 0x7691e0e3UL, 0x13f65c5bUL, 0xfd59e949UL, 0x983e55f1UL,
+    0x2106826cUL, 0x44613ed4UL, 0xaace8bc6UL, 0xcfa9377eUL, 0x38417fd6UL,
+    0x5d26c36eUL, 0xb389767cUL, 0xd6eecac4UL, 0x6fd61d59UL, 0x0ab1a1e1UL,
+    0xe41e14f3UL, 0x8179a84bUL, 0xd769cb13UL, 0xb20e77abUL, 0x5ca1c2b9UL,
+    0x39c67e01UL, 0x80fea99cUL, 0xe5991524UL, 0x0b36a036UL, 0x6e511c8eUL,
+    0xa7166686UL, 0xc271da3eUL, 0x2cde6f2cUL, 0x49b9d394UL, 0xf0810409UL,
+    0x95e6b8b1UL, 0x7b490da3UL, 0x1e2eb11bUL, 0x483ed243UL, 0x2d596efbUL,
+    0xc3f6dbe9UL, 0xa6916751UL, 0x1fa9b0ccUL, 0x7ace0c74UL, 0x9461b966UL,
+    0xf10605deUL
+#endif
+  }
+};

ADDED   3rd_party/zlib/deflate.c
Index: 3rd_party/zlib/deflate.c
==================================================================
--- 3rd_party/zlib/deflate.c
+++ 3rd_party/zlib/deflate.c
@@ -0,0 +1,2163 @@
+/* deflate.c -- compress data using the deflation algorithm
+ * Copyright (C) 1995-2017 Jean-loup Gailly and Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/*
+ *  ALGORITHM
+ *
+ *      The "deflation" process depends on being able to identify portions
+ *      of the input text which are identical to earlier input (within a
+ *      sliding window trailing behind the input currently being processed).
+ *
+ *      The most straightforward technique turns out to be the fastest for
+ *      most input files: try all possible matches and select the longest.
+ *      The key feature of this algorithm is that insertions into the string
+ *      dictionary are very simple and thus fast, and deletions are avoided
+ *      completely. Insertions are performed at each input character, whereas
+ *      string matches are performed only when the previous match ends. So it
+ *      is preferable to spend more time in matches to allow very fast string
+ *      insertions and avoid deletions. The matching algorithm for small
+ *      strings is inspired from that of Rabin & Karp. A brute force approach
+ *      is used to find longer strings when a small match has been found.
+ *      A similar algorithm is used in comic (by Jan-Mark Wams) and freeze
+ *      (by Leonid Broukhis).
+ *         A previous version of this file used a more sophisticated algorithm
+ *      (by Fiala and Greene) which is guaranteed to run in linear amortized
+ *      time, but has a larger average cost, uses more memory and is patented.
+ *      However the F&G algorithm may be faster for some highly redundant
+ *      files if the parameter max_chain_length (described below) is too large.
+ *
+ *  ACKNOWLEDGEMENTS
+ *
+ *      The idea of lazy evaluation of matches is due to Jan-Mark Wams, and
+ *      I found it in 'freeze' written by Leonid Broukhis.
+ *      Thanks to many people for bug reports and testing.
+ *
+ *  REFERENCES
+ *
+ *      Deutsch, L.P.,"DEFLATE Compressed Data Format Specification".
+ *      Available in http://tools.ietf.org/html/rfc1951
+ *
+ *      A description of the Rabin and Karp algorithm is given in the book
+ *         "Algorithms" by R. Sedgewick, Addison-Wesley, p252.
+ *
+ *      Fiala,E.R., and Greene,D.H.
+ *         Data Compression with Finite Windows, Comm.ACM, 32,4 (1989) 490-595
+ *
+ */
+
+/* @(#) $Id$ */
+
+#include "deflate.h"
+
+const char deflate_copyright[] =
+   " deflate 1.2.11 Copyright 1995-2017 Jean-loup Gailly and Mark Adler ";
+/*
+  If you use the zlib library in a product, an acknowledgment is welcome
+  in the documentation of your product. If for some reason you cannot
+  include such an acknowledgment, I would appreciate that you keep this
+  copyright string in the executable of your product.
+ */
+
+/* ===========================================================================
+ *  Function prototypes.
+ */
+typedef enum {
+    need_more,      /* block not completed, need more input or more output */
+    block_done,     /* block flush performed */
+    finish_started, /* finish started, need only more output at next deflate */
+    finish_done     /* finish done, accept no more input or output */
+} block_state;
+
+typedef block_state (*compress_func) OF((deflate_state *s, int flush));
+/* Compression function. Returns the block state after the call. */
+
+local int deflateStateCheck      OF((z_streamp strm));
+local void slide_hash     OF((deflate_state *s));
+local void fill_window    OF((deflate_state *s));
+local block_state deflate_stored OF((deflate_state *s, int flush));
+local block_state deflate_fast   OF((deflate_state *s, int flush));
+#ifndef FASTEST
+local block_state deflate_slow   OF((deflate_state *s, int flush));
+#endif
+local block_state deflate_rle    OF((deflate_state *s, int flush));
+local block_state deflate_huff   OF((deflate_state *s, int flush));
+local void lm_init        OF((deflate_state *s));
+local void putShortMSB    OF((deflate_state *s, uInt b));
+local void flush_pending  OF((z_streamp strm));
+local unsigned read_buf   OF((z_streamp strm, Bytef *buf, unsigned size));
+#ifdef ASMV
+#  pragma message("Assembler code may have bugs -- use at your own risk")
+      void match_init OF((void)); /* asm code initialization */
+      uInt longest_match  OF((deflate_state *s, IPos cur_match));
+#else
+local uInt longest_match  OF((deflate_state *s, IPos cur_match));
+#endif
+
+#ifdef ZLIB_DEBUG
+local  void check_match OF((deflate_state *s, IPos start, IPos match,
+                            int length));
+#endif
+
+/* ===========================================================================
+ * Local data
+ */
+
+#define NIL 0
+/* Tail of hash chains */
+
+#ifndef TOO_FAR
+#  define TOO_FAR 4096
+#endif
+/* Matches of length 3 are discarded if their distance exceeds TOO_FAR */
+
+/* Values for max_lazy_match, good_match and max_chain_length, depending on
+ * the desired pack level (0..9). The values given below have been tuned to
+ * exclude worst case performance for pathological files. Better values may be
+ * found for specific files.
+ */
+typedef struct config_s {
+   ush good_length; /* reduce lazy search above this match length */
+   ush max_lazy;    /* do not perform lazy search above this match length */
+   ush nice_length; /* quit search above this match length */
+   ush max_chain;
+   compress_func func;
+} config;
+
+#ifdef FASTEST
+local const config configuration_table[2] = {
+/*      good lazy nice chain */
+/* 0 */ {0,    0,  0,    0, deflate_stored},  /* store only */
+/* 1 */ {4,    4,  8,    4, deflate_fast}}; /* max speed, no lazy matches */
+#else
+local const config configuration_table[10] = {
+/*      good lazy nice chain */
+/* 0 */ {0,    0,  0,    0, deflate_stored},  /* store only */
+/* 1 */ {4,    4,  8,    4, deflate_fast}, /* max speed, no lazy matches */
+/* 2 */ {4,    5, 16,    8, deflate_fast},
+/* 3 */ {4,    6, 32,   32, deflate_fast},
+
+/* 4 */ {4,    4, 16,   16, deflate_slow},  /* lazy matches */
+/* 5 */ {8,   16, 32,   32, deflate_slow},
+/* 6 */ {8,   16, 128, 128, deflate_slow},
+/* 7 */ {8,   32, 128, 256, deflate_slow},
+/* 8 */ {32, 128, 258, 1024, deflate_slow},
+/* 9 */ {32, 258, 258, 4096, deflate_slow}}; /* max compression */
+#endif
+
+/* Note: the deflate() code requires max_lazy >= MIN_MATCH and max_chain >= 4
+ * For deflate_fast() (levels <= 3) good is ignored and lazy has a different
+ * meaning.
+ */
+
+/* rank Z_BLOCK between Z_NO_FLUSH and Z_PARTIAL_FLUSH */
+#define RANK(f) (((f) * 2) - ((f) > 4 ? 9 : 0))
+
+/* ===========================================================================
+ * Update a hash value with the given input byte
+ * IN  assertion: all calls to UPDATE_HASH are made with consecutive input
+ *    characters, so that a running hash key can be computed from the previous
+ *    key instead of complete recalculation each time.
+ */
+#define UPDATE_HASH(s,h,c) (h = (((h)<<s->hash_shift) ^ (c)) & s->hash_mask)
+
+
+/* ===========================================================================
+ * Insert string str in the dictionary and set match_head to the previous head
+ * of the hash chain (the most recent string with same hash key). Return
+ * the previous length of the hash chain.
+ * If this file is compiled with -DFASTEST, the compression level is forced
+ * to 1, and no hash chains are maintained.
+ * IN  assertion: all calls to INSERT_STRING are made with consecutive input
+ *    characters and the first MIN_MATCH bytes of str are valid (except for
+ *    the last MIN_MATCH-1 bytes of the input file).
+ */
+#ifdef FASTEST
+#define INSERT_STRING(s, str, match_head) \
+   (UPDATE_HASH(s, s->ins_h, s->window[(str) + (MIN_MATCH-1)]), \
+    match_head = s->head[s->ins_h], \
+    s->head[s->ins_h] = (Pos)(str))
+#else
+#define INSERT_STRING(s, str, match_head) \
+   (UPDATE_HASH(s, s->ins_h, s->window[(str) + (MIN_MATCH-1)]), \
+    match_head = s->prev[(str) & s->w_mask] = s->head[s->ins_h], \
+    s->head[s->ins_h] = (Pos)(str))
+#endif
+
+/* ===========================================================================
+ * Initialize the hash table (avoiding 64K overflow for 16 bit systems).
+ * prev[] will be initialized on the fly.
+ */
+#define CLEAR_HASH(s) \
+    s->head[s->hash_size-1] = NIL; \
+    zmemzero((Bytef *)s->head, (unsigned)(s->hash_size-1)*sizeof(*s->head));
+
+/* ===========================================================================
+ * Slide the hash table when sliding the window down (could be avoided with 32
+ * bit values at the expense of memory usage). We slide even when level == 0 to
+ * keep the hash table consistent if we switch back to level > 0 later.
+ */
+local void slide_hash(s)
+    deflate_state *s;
+{
+    unsigned n, m;
+    Posf *p;
+    uInt wsize = s->w_size;
+
+    n = s->hash_size;
+    p = &s->head[n];
+    do {
+        m = *--p;
+        *p = (Pos)(m >= wsize ? m - wsize : NIL);
+    } while (--n);
+    n = wsize;
+#ifndef FASTEST
+    p = &s->prev[n];
+    do {
+        m = *--p;
+        *p = (Pos)(m >= wsize ? m - wsize : NIL);
+        /* If n is not on any hash chain, prev[n] is garbage but
+         * its value will never be used.
+         */
+    } while (--n);
+#endif
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateInit_(strm, level, version, stream_size)
+    z_streamp strm;
+    int level;
+    const char *version;
+    int stream_size;
+{
+    return deflateInit2_(strm, level, Z_DEFLATED, MAX_WBITS, DEF_MEM_LEVEL,
+                         Z_DEFAULT_STRATEGY, version, stream_size);
+    /* To do: ignore strm->next_in if we use it as window */
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateInit2_(strm, level, method, windowBits, memLevel, strategy,
+                  version, stream_size)
+    z_streamp strm;
+    int  level;
+    int  method;
+    int  windowBits;
+    int  memLevel;
+    int  strategy;
+    const char *version;
+    int stream_size;
+{
+    deflate_state *s;
+    int wrap = 1;
+    static const char my_version[] = ZLIB_VERSION;
+
+    ushf *overlay;
+    /* We overlay pending_buf and d_buf+l_buf. This works since the average
+     * output size for (length,distance) codes is <= 24 bits.
+     */
+
+    if (version == Z_NULL || version[0] != my_version[0] ||
+        stream_size != sizeof(z_stream)) {
+        return Z_VERSION_ERROR;
+    }
+    if (strm == Z_NULL) return Z_STREAM_ERROR;
+
+    strm->msg = Z_NULL;
+    if (strm->zalloc == (alloc_func)0) {
+#ifdef Z_SOLO
+        return Z_STREAM_ERROR;
+#else
+        strm->zalloc = zcalloc;
+        strm->opaque = (voidpf)0;
+#endif
+    }
+    if (strm->zfree == (free_func)0)
+#ifdef Z_SOLO
+        return Z_STREAM_ERROR;
+#else
+        strm->zfree = zcfree;
+#endif
+
+#ifdef FASTEST
+    if (level != 0) level = 1;
+#else
+    if (level == Z_DEFAULT_COMPRESSION) level = 6;
+#endif
+
+    if (windowBits < 0) { /* suppress zlib wrapper */
+        wrap = 0;
+        windowBits = -windowBits;
+    }
+#ifdef GZIP
+    else if (windowBits > 15) {
+        wrap = 2;       /* write gzip wrapper instead */
+        windowBits -= 16;
+    }
+#endif
+    if (memLevel < 1 || memLevel > MAX_MEM_LEVEL || method != Z_DEFLATED ||
+        windowBits < 8 || windowBits > 15 || level < 0 || level > 9 ||
+        strategy < 0 || strategy > Z_FIXED || (windowBits == 8 && wrap != 1)) {
+        return Z_STREAM_ERROR;
+    }
+    if (windowBits == 8) windowBits = 9;  /* until 256-byte window bug fixed */
+    s = (deflate_state *) ZALLOC(strm, 1, sizeof(deflate_state));
+    if (s == Z_NULL) return Z_MEM_ERROR;
+    strm->state = (struct internal_state FAR *)s;
+    s->strm = strm;
+    s->status = INIT_STATE;     /* to pass state test in deflateReset() */
+
+    s->wrap = wrap;
+    s->gzhead = Z_NULL;
+    s->w_bits = (uInt)windowBits;
+    s->w_size = 1 << s->w_bits;
+    s->w_mask = s->w_size - 1;
+
+    s->hash_bits = (uInt)memLevel + 7;
+    s->hash_size = 1 << s->hash_bits;
+    s->hash_mask = s->hash_size - 1;
+    s->hash_shift =  ((s->hash_bits+MIN_MATCH-1)/MIN_MATCH);
+
+    s->window = (Bytef *) ZALLOC(strm, s->w_size, 2*sizeof(Byte));
+    s->prev   = (Posf *)  ZALLOC(strm, s->w_size, sizeof(Pos));
+    s->head   = (Posf *)  ZALLOC(strm, s->hash_size, sizeof(Pos));
+
+    s->high_water = 0;      /* nothing written to s->window yet */
+
+    s->lit_bufsize = 1 << (memLevel + 6); /* 16K elements by default */
+
+    overlay = (ushf *) ZALLOC(strm, s->lit_bufsize, sizeof(ush)+2);
+    s->pending_buf = (uchf *) overlay;
+    s->pending_buf_size = (ulg)s->lit_bufsize * (sizeof(ush)+2L);
+
+    if (s->window == Z_NULL || s->prev == Z_NULL || s->head == Z_NULL ||
+        s->pending_buf == Z_NULL) {
+        s->status = FINISH_STATE;
+        strm->msg = ERR_MSG(Z_MEM_ERROR);
+        deflateEnd (strm);
+        return Z_MEM_ERROR;
+    }
+    s->d_buf = overlay + s->lit_bufsize/sizeof(ush);
+    s->l_buf = s->pending_buf + (1+sizeof(ush))*s->lit_bufsize;
+
+    s->level = level;
+    s->strategy = strategy;
+    s->method = (Byte)method;
+
+    return deflateReset(strm);
+}
+
+/* =========================================================================
+ * Check for a valid deflate stream state. Return 0 if ok, 1 if not.
+ */
+local int deflateStateCheck (strm)
+    z_streamp strm;
+{
+    deflate_state *s;
+    if (strm == Z_NULL ||
+        strm->zalloc == (alloc_func)0 || strm->zfree == (free_func)0)
+        return 1;
+    s = strm->state;
+    if (s == Z_NULL || s->strm != strm || (s->status != INIT_STATE &&
+#ifdef GZIP
+                                           s->status != GZIP_STATE &&
+#endif
+                                           s->status != EXTRA_STATE &&
+                                           s->status != NAME_STATE &&
+                                           s->status != COMMENT_STATE &&
+                                           s->status != HCRC_STATE &&
+                                           s->status != BUSY_STATE &&
+                                           s->status != FINISH_STATE))
+        return 1;
+    return 0;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateSetDictionary (strm, dictionary, dictLength)
+    z_streamp strm;
+    const Bytef *dictionary;
+    uInt  dictLength;
+{
+    deflate_state *s;
+    uInt str, n;
+    int wrap;
+    unsigned avail;
+    z_const unsigned char *next;
+
+    if (deflateStateCheck(strm) || dictionary == Z_NULL)
+        return Z_STREAM_ERROR;
+    s = strm->state;
+    wrap = s->wrap;
+    if (wrap == 2 || (wrap == 1 && s->status != INIT_STATE) || s->lookahead)
+        return Z_STREAM_ERROR;
+
+    /* when using zlib wrappers, compute Adler-32 for provided dictionary */
+    if (wrap == 1)
+        strm->adler = adler32(strm->adler, dictionary, dictLength);
+    s->wrap = 0;                    /* avoid computing Adler-32 in read_buf */
+
+    /* if dictionary would fill window, just replace the history */
+    if (dictLength >= s->w_size) {
+        if (wrap == 0) {            /* already empty otherwise */
+            CLEAR_HASH(s);
+            s->strstart = 0;
+            s->block_start = 0L;
+            s->insert = 0;
+        }
+        dictionary += dictLength - s->w_size;  /* use the tail */
+        dictLength = s->w_size;
+    }
+
+    /* insert dictionary into window and hash */
+    avail = strm->avail_in;
+    next = strm->next_in;
+    strm->avail_in = dictLength;
+    strm->next_in = (z_const Bytef *)dictionary;
+    fill_window(s);
+    while (s->lookahead >= MIN_MATCH) {
+        str = s->strstart;
+        n = s->lookahead - (MIN_MATCH-1);
+        do {
+            UPDATE_HASH(s, s->ins_h, s->window[str + MIN_MATCH-1]);
+#ifndef FASTEST
+            s->prev[str & s->w_mask] = s->head[s->ins_h];
+#endif
+            s->head[s->ins_h] = (Pos)str;
+            str++;
+        } while (--n);
+        s->strstart = str;
+        s->lookahead = MIN_MATCH-1;
+        fill_window(s);
+    }
+    s->strstart += s->lookahead;
+    s->block_start = (long)s->strstart;
+    s->insert = s->lookahead;
+    s->lookahead = 0;
+    s->match_length = s->prev_length = MIN_MATCH-1;
+    s->match_available = 0;
+    strm->next_in = next;
+    strm->avail_in = avail;
+    s->wrap = wrap;
+    return Z_OK;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateGetDictionary (strm, dictionary, dictLength)
+    z_streamp strm;
+    Bytef *dictionary;
+    uInt  *dictLength;
+{
+    deflate_state *s;
+    uInt len;
+
+    if (deflateStateCheck(strm))
+        return Z_STREAM_ERROR;
+    s = strm->state;
+    len = s->strstart + s->lookahead;
+    if (len > s->w_size)
+        len = s->w_size;
+    if (dictionary != Z_NULL && len)
+        zmemcpy(dictionary, s->window + s->strstart + s->lookahead - len, len);
+    if (dictLength != Z_NULL)
+        *dictLength = len;
+    return Z_OK;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateResetKeep (strm)
+    z_streamp strm;
+{
+    deflate_state *s;
+
+    if (deflateStateCheck(strm)) {
+        return Z_STREAM_ERROR;
+    }
+
+    strm->total_in = strm->total_out = 0;
+    strm->msg = Z_NULL; /* use zfree if we ever allocate msg dynamically */
+    strm->data_type = Z_UNKNOWN;
+
+    s = (deflate_state *)strm->state;
+    s->pending = 0;
+    s->pending_out = s->pending_buf;
+
+    if (s->wrap < 0) {
+        s->wrap = -s->wrap; /* was made negative by deflate(..., Z_FINISH); */
+    }
+    s->status =
+#ifdef GZIP
+        s->wrap == 2 ? GZIP_STATE :
+#endif
+        s->wrap ? INIT_STATE : BUSY_STATE;
+    strm->adler =
+#ifdef GZIP
+        s->wrap == 2 ? crc32(0L, Z_NULL, 0) :
+#endif
+        adler32(0L, Z_NULL, 0);
+    s->last_flush = Z_NO_FLUSH;
+
+    _tr_init(s);
+
+    return Z_OK;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateReset (strm)
+    z_streamp strm;
+{
+    int ret;
+
+    ret = deflateResetKeep(strm);
+    if (ret == Z_OK)
+        lm_init(strm->state);
+    return ret;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateSetHeader (strm, head)
+    z_streamp strm;
+    gz_headerp head;
+{
+    if (deflateStateCheck(strm) || strm->state->wrap != 2)
+        return Z_STREAM_ERROR;
+    strm->state->gzhead = head;
+    return Z_OK;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflatePending (strm, pending, bits)
+    unsigned *pending;
+    int *bits;
+    z_streamp strm;
+{
+    if (deflateStateCheck(strm)) return Z_STREAM_ERROR;
+    if (pending != Z_NULL)
+        *pending = strm->state->pending;
+    if (bits != Z_NULL)
+        *bits = strm->state->bi_valid;
+    return Z_OK;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflatePrime (strm, bits, value)
+    z_streamp strm;
+    int bits;
+    int value;
+{
+    deflate_state *s;
+    int put;
+
+    if (deflateStateCheck(strm)) return Z_STREAM_ERROR;
+    s = strm->state;
+    if ((Bytef *)(s->d_buf) < s->pending_out + ((Buf_size + 7) >> 3))
+        return Z_BUF_ERROR;
+    do {
+        put = Buf_size - s->bi_valid;
+        if (put > bits)
+            put = bits;
+        s->bi_buf |= (ush)((value & ((1 << put) - 1)) << s->bi_valid);
+        s->bi_valid += put;
+        _tr_flush_bits(s);
+        value >>= put;
+        bits -= put;
+    } while (bits);
+    return Z_OK;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateParams(strm, level, strategy)
+    z_streamp strm;
+    int level;
+    int strategy;
+{
+    deflate_state *s;
+    compress_func func;
+
+    if (deflateStateCheck(strm)) return Z_STREAM_ERROR;
+    s = strm->state;
+
+#ifdef FASTEST
+    if (level != 0) level = 1;
+#else
+    if (level == Z_DEFAULT_COMPRESSION) level = 6;
+#endif
+    if (level < 0 || level > 9 || strategy < 0 || strategy > Z_FIXED) {
+        return Z_STREAM_ERROR;
+    }
+    func = configuration_table[s->level].func;
+
+    if ((strategy != s->strategy || func != configuration_table[level].func) &&
+        s->high_water) {
+        /* Flush the last buffer: */
+        int err = deflate(strm, Z_BLOCK);
+        if (err == Z_STREAM_ERROR)
+            return err;
+        if (strm->avail_out == 0)
+            return Z_BUF_ERROR;
+    }
+    if (s->level != level) {
+        if (s->level == 0 && s->matches != 0) {
+            if (s->matches == 1)
+                slide_hash(s);
+            else
+                CLEAR_HASH(s);
+            s->matches = 0;
+        }
+        s->level = level;
+        s->max_lazy_match   = configuration_table[level].max_lazy;
+        s->good_match       = configuration_table[level].good_length;
+        s->nice_match       = configuration_table[level].nice_length;
+        s->max_chain_length = configuration_table[level].max_chain;
+    }
+    s->strategy = strategy;
+    return Z_OK;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateTune(strm, good_length, max_lazy, nice_length, max_chain)
+    z_streamp strm;
+    int good_length;
+    int max_lazy;
+    int nice_length;
+    int max_chain;
+{
+    deflate_state *s;
+
+    if (deflateStateCheck(strm)) return Z_STREAM_ERROR;
+    s = strm->state;
+    s->good_match = (uInt)good_length;
+    s->max_lazy_match = (uInt)max_lazy;
+    s->nice_match = nice_length;
+    s->max_chain_length = (uInt)max_chain;
+    return Z_OK;
+}
+
+/* =========================================================================
+ * For the default windowBits of 15 and memLevel of 8, this function returns
+ * a close to exact, as well as small, upper bound on the compressed size.
+ * They are coded as constants here for a reason--if the #define's are
+ * changed, then this function needs to be changed as well.  The return
+ * value for 15 and 8 only works for those exact settings.
+ *
+ * For any setting other than those defaults for windowBits and memLevel,
+ * the value returned is a conservative worst case for the maximum expansion
+ * resulting from using fixed blocks instead of stored blocks, which deflate
+ * can emit on compressed data for some combinations of the parameters.
+ *
+ * This function could be more sophisticated to provide closer upper bounds for
+ * every combination of windowBits and memLevel.  But even the conservative
+ * upper bound of about 14% expansion does not seem onerous for output buffer
+ * allocation.
+ */
+uLong ZEXPORT deflateBound(strm, sourceLen)
+    z_streamp strm;
+    uLong sourceLen;
+{
+    deflate_state *s;
+    uLong complen, wraplen;
+
+    /* conservative upper bound for compressed data */
+    complen = sourceLen +
+              ((sourceLen + 7) >> 3) + ((sourceLen + 63) >> 6) + 5;
+
+    /* if can't get parameters, return conservative bound plus zlib wrapper */
+    if (deflateStateCheck(strm))
+        return complen + 6;
+
+    /* compute wrapper length */
+    s = strm->state;
+    switch (s->wrap) {
+    case 0:                                 /* raw deflate */
+        wraplen = 0;
+        break;
+    case 1:                                 /* zlib wrapper */
+        wraplen = 6 + (s->strstart ? 4 : 0);
+        break;
+#ifdef GZIP
+    case 2:                                 /* gzip wrapper */
+        wraplen = 18;
+        if (s->gzhead != Z_NULL) {          /* user-supplied gzip header */
+            Bytef *str;
+            if (s->gzhead->extra != Z_NULL)
+                wraplen += 2 + s->gzhead->extra_len;
+            str = s->gzhead->name;
+            if (str != Z_NULL)
+                do {
+                    wraplen++;
+                } while (*str++);
+            str = s->gzhead->comment;
+            if (str != Z_NULL)
+                do {
+                    wraplen++;
+                } while (*str++);
+            if (s->gzhead->hcrc)
+                wraplen += 2;
+        }
+        break;
+#endif
+    default:                                /* for compiler happiness */
+        wraplen = 6;
+    }
+
+    /* if not default parameters, return conservative bound */
+    if (s->w_bits != 15 || s->hash_bits != 8 + 7)
+        return complen + wraplen;
+
+    /* default settings: return tight bound for that case */
+    return sourceLen + (sourceLen >> 12) + (sourceLen >> 14) +
+           (sourceLen >> 25) + 13 - 6 + wraplen;
+}
+
+/* =========================================================================
+ * Put a short in the pending buffer. The 16-bit value is put in MSB order.
+ * IN assertion: the stream state is correct and there is enough room in
+ * pending_buf.
+ */
+local void putShortMSB (s, b)
+    deflate_state *s;
+    uInt b;
+{
+    put_byte(s, (Byte)(b >> 8));
+    put_byte(s, (Byte)(b & 0xff));
+}
+
+/* =========================================================================
+ * Flush as much pending output as possible. All deflate() output, except for
+ * some deflate_stored() output, goes through this function so some
+ * applications may wish to modify it to avoid allocating a large
+ * strm->next_out buffer and copying into it. (See also read_buf()).
+ */
+local void flush_pending(strm)
+    z_streamp strm;
+{
+    unsigned len;
+    deflate_state *s = strm->state;
+
+    _tr_flush_bits(s);
+    len = s->pending;
+    if (len > strm->avail_out) len = strm->avail_out;
+    if (len == 0) return;
+
+    zmemcpy(strm->next_out, s->pending_out, len);
+    strm->next_out  += len;
+    s->pending_out  += len;
+    strm->total_out += len;
+    strm->avail_out -= len;
+    s->pending      -= len;
+    if (s->pending == 0) {
+        s->pending_out = s->pending_buf;
+    }
+}
+
+/* ===========================================================================
+ * Update the header CRC with the bytes s->pending_buf[beg..s->pending - 1].
+ */
+#define HCRC_UPDATE(beg) \
+    do { \
+        if (s->gzhead->hcrc && s->pending > (beg)) \
+            strm->adler = crc32(strm->adler, s->pending_buf + (beg), \
+                                s->pending - (beg)); \
+    } while (0)
+
+/* ========================================================================= */
+int ZEXPORT deflate (strm, flush)
+    z_streamp strm;
+    int flush;
+{
+    int old_flush; /* value of flush param for previous deflate call */
+    deflate_state *s;
+
+    if (deflateStateCheck(strm) || flush > Z_BLOCK || flush < 0) {
+        return Z_STREAM_ERROR;
+    }
+    s = strm->state;
+
+    if (strm->next_out == Z_NULL ||
+        (strm->avail_in != 0 && strm->next_in == Z_NULL) ||
+        (s->status == FINISH_STATE && flush != Z_FINISH)) {
+        ERR_RETURN(strm, Z_STREAM_ERROR);
+    }
+    if (strm->avail_out == 0) ERR_RETURN(strm, Z_BUF_ERROR);
+
+    old_flush = s->last_flush;
+    s->last_flush = flush;
+
+    /* Flush as much pending output as possible */
+    if (s->pending != 0) {
+        flush_pending(strm);
+        if (strm->avail_out == 0) {
+            /* Since avail_out is 0, deflate will be called again with
+             * more output space, but possibly with both pending and
+             * avail_in equal to zero. There won't be anything to do,
+             * but this is not an error situation so make sure we
+             * return OK instead of BUF_ERROR at next call of deflate:
+             */
+            s->last_flush = -1;
+            return Z_OK;
+        }
+
+    /* Make sure there is something to do and avoid duplicate consecutive
+     * flushes. For repeated and useless calls with Z_FINISH, we keep
+     * returning Z_STREAM_END instead of Z_BUF_ERROR.
+     */
+    } else if (strm->avail_in == 0 && RANK(flush) <= RANK(old_flush) &&
+               flush != Z_FINISH) {
+        ERR_RETURN(strm, Z_BUF_ERROR);
+    }
+
+    /* User must not provide more input after the first FINISH: */
+    if (s->status == FINISH_STATE && strm->avail_in != 0) {
+        ERR_RETURN(strm, Z_BUF_ERROR);
+    }
+
+    /* Write the header */
+    if (s->status == INIT_STATE) {
+        /* zlib header */
+        uInt header = (Z_DEFLATED + ((s->w_bits-8)<<4)) << 8;
+        uInt level_flags;
+
+        if (s->strategy >= Z_HUFFMAN_ONLY || s->level < 2)
+            level_flags = 0;
+        else if (s->level < 6)
+            level_flags = 1;
+        else if (s->level == 6)
+            level_flags = 2;
+        else
+            level_flags = 3;
+        header |= (level_flags << 6);
+        if (s->strstart != 0) header |= PRESET_DICT;
+        header += 31 - (header % 31);
+
+        putShortMSB(s, header);
+
+        /* Save the adler32 of the preset dictionary: */
+        if (s->strstart != 0) {
+            putShortMSB(s, (uInt)(strm->adler >> 16));
+            putShortMSB(s, (uInt)(strm->adler & 0xffff));
+        }
+        strm->adler = adler32(0L, Z_NULL, 0);
+        s->status = BUSY_STATE;
+
+        /* Compression must start with an empty pending buffer */
+        flush_pending(strm);
+        if (s->pending != 0) {
+            s->last_flush = -1;
+            return Z_OK;
+        }
+    }
+#ifdef GZIP
+    if (s->status == GZIP_STATE) {
+        /* gzip header */
+        strm->adler = crc32(0L, Z_NULL, 0);
+        put_byte(s, 31);
+        put_byte(s, 139);
+        put_byte(s, 8);
+        if (s->gzhead == Z_NULL) {
+            put_byte(s, 0);
+            put_byte(s, 0);
+            put_byte(s, 0);
+            put_byte(s, 0);
+            put_byte(s, 0);
+            put_byte(s, s->level == 9 ? 2 :
+                     (s->strategy >= Z_HUFFMAN_ONLY || s->level < 2 ?
+                      4 : 0));
+            put_byte(s, OS_CODE);
+            s->status = BUSY_STATE;
+
+            /* Compression must start with an empty pending buffer */
+            flush_pending(strm);
+            if (s->pending != 0) {
+                s->last_flush = -1;
+                return Z_OK;
+            }
+        }
+        else {
+            put_byte(s, (s->gzhead->text ? 1 : 0) +
+                     (s->gzhead->hcrc ? 2 : 0) +
+                     (s->gzhead->extra == Z_NULL ? 0 : 4) +
+                     (s->gzhead->name == Z_NULL ? 0 : 8) +
+                     (s->gzhead->comment == Z_NULL ? 0 : 16)
+                     );
+            put_byte(s, (Byte)(s->gzhead->time & 0xff));
+            put_byte(s, (Byte)((s->gzhead->time >> 8) & 0xff));
+            put_byte(s, (Byte)((s->gzhead->time >> 16) & 0xff));
+            put_byte(s, (Byte)((s->gzhead->time >> 24) & 0xff));
+            put_byte(s, s->level == 9 ? 2 :
+                     (s->strategy >= Z_HUFFMAN_ONLY || s->level < 2 ?
+                      4 : 0));
+            put_byte(s, s->gzhead->os & 0xff);
+            if (s->gzhead->extra != Z_NULL) {
+                put_byte(s, s->gzhead->extra_len & 0xff);
+                put_byte(s, (s->gzhead->extra_len >> 8) & 0xff);
+            }
+            if (s->gzhead->hcrc)
+                strm->adler = crc32(strm->adler, s->pending_buf,
+                                    s->pending);
+            s->gzindex = 0;
+            s->status = EXTRA_STATE;
+        }
+    }
+    if (s->status == EXTRA_STATE) {
+        if (s->gzhead->extra != Z_NULL) {
+            ulg beg = s->pending;   /* start of bytes to update crc */
+            uInt left = (s->gzhead->extra_len & 0xffff) - s->gzindex;
+            while (s->pending + left > s->pending_buf_size) {
+                uInt copy = s->pending_buf_size - s->pending;
+                zmemcpy(s->pending_buf + s->pending,
+                        s->gzhead->extra + s->gzindex, copy);
+                s->pending = s->pending_buf_size;
+                HCRC_UPDATE(beg);
+                s->gzindex += copy;
+                flush_pending(strm);
+                if (s->pending != 0) {
+                    s->last_flush = -1;
+                    return Z_OK;
+                }
+                beg = 0;
+                left -= copy;
+            }
+            zmemcpy(s->pending_buf + s->pending,
+                    s->gzhead->extra + s->gzindex, left);
+            s->pending += left;
+            HCRC_UPDATE(beg);
+            s->gzindex = 0;
+        }
+        s->status = NAME_STATE;
+    }
+    if (s->status == NAME_STATE) {
+        if (s->gzhead->name != Z_NULL) {
+            ulg beg = s->pending;   /* start of bytes to update crc */
+            int val;
+            do {
+                if (s->pending == s->pending_buf_size) {
+                    HCRC_UPDATE(beg);
+                    flush_pending(strm);
+                    if (s->pending != 0) {
+                        s->last_flush = -1;
+                        return Z_OK;
+                    }
+                    beg = 0;
+                }
+                val = s->gzhead->name[s->gzindex++];
+                put_byte(s, val);
+            } while (val != 0);
+            HCRC_UPDATE(beg);
+            s->gzindex = 0;
+        }
+        s->status = COMMENT_STATE;
+    }
+    if (s->status == COMMENT_STATE) {
+        if (s->gzhead->comment != Z_NULL) {
+            ulg beg = s->pending;   /* start of bytes to update crc */
+            int val;
+            do {
+                if (s->pending == s->pending_buf_size) {
+                    HCRC_UPDATE(beg);
+                    flush_pending(strm);
+                    if (s->pending != 0) {
+                        s->last_flush = -1;
+                        return Z_OK;
+                    }
+                    beg = 0;
+                }
+                val = s->gzhead->comment[s->gzindex++];
+                put_byte(s, val);
+            } while (val != 0);
+            HCRC_UPDATE(beg);
+        }
+        s->status = HCRC_STATE;
+    }
+    if (s->status == HCRC_STATE) {
+        if (s->gzhead->hcrc) {
+            if (s->pending + 2 > s->pending_buf_size) {
+                flush_pending(strm);
+                if (s->pending != 0) {
+                    s->last_flush = -1;
+                    return Z_OK;
+                }
+            }
+            put_byte(s, (Byte)(strm->adler & 0xff));
+            put_byte(s, (Byte)((strm->adler >> 8) & 0xff));
+            strm->adler = crc32(0L, Z_NULL, 0);
+        }
+        s->status = BUSY_STATE;
+
+        /* Compression must start with an empty pending buffer */
+        flush_pending(strm);
+        if (s->pending != 0) {
+            s->last_flush = -1;
+            return Z_OK;
+        }
+    }
+#endif
+
+    /* Start a new block or continue the current one.
+     */
+    if (strm->avail_in != 0 || s->lookahead != 0 ||
+        (flush != Z_NO_FLUSH && s->status != FINISH_STATE)) {
+        block_state bstate;
+
+        bstate = s->level == 0 ? deflate_stored(s, flush) :
+                 s->strategy == Z_HUFFMAN_ONLY ? deflate_huff(s, flush) :
+                 s->strategy == Z_RLE ? deflate_rle(s, flush) :
+                 (*(configuration_table[s->level].func))(s, flush);
+
+        if (bstate == finish_started || bstate == finish_done) {
+            s->status = FINISH_STATE;
+        }
+        if (bstate == need_more || bstate == finish_started) {
+            if (strm->avail_out == 0) {
+                s->last_flush = -1; /* avoid BUF_ERROR next call, see above */
+            }
+            return Z_OK;
+            /* If flush != Z_NO_FLUSH && avail_out == 0, the next call
+             * of deflate should use the same flush parameter to make sure
+             * that the flush is complete. So we don't have to output an
+             * empty block here, this will be done at next call. This also
+             * ensures that for a very small output buffer, we emit at most
+             * one empty block.
+             */
+        }
+        if (bstate == block_done) {
+            if (flush == Z_PARTIAL_FLUSH) {
+                _tr_align(s);
+            } else if (flush != Z_BLOCK) { /* FULL_FLUSH or SYNC_FLUSH */
+                _tr_stored_block(s, (char*)0, 0L, 0);
+                /* For a full flush, this empty block will be recognized
+                 * as a special marker by inflate_sync().
+                 */
+                if (flush == Z_FULL_FLUSH) {
+                    CLEAR_HASH(s);             /* forget history */
+                    if (s->lookahead == 0) {
+                        s->strstart = 0;
+                        s->block_start = 0L;
+                        s->insert = 0;
+                    }
+                }
+            }
+            flush_pending(strm);
+            if (strm->avail_out == 0) {
+              s->last_flush = -1; /* avoid BUF_ERROR at next call, see above */
+              return Z_OK;
+            }
+        }
+    }
+
+    if (flush != Z_FINISH) return Z_OK;
+    if (s->wrap <= 0) return Z_STREAM_END;
+
+    /* Write the trailer */
+#ifdef GZIP
+    if (s->wrap == 2) {
+        put_byte(s, (Byte)(strm->adler & 0xff));
+        put_byte(s, (Byte)((strm->adler >> 8) & 0xff));
+        put_byte(s, (Byte)((strm->adler >> 16) & 0xff));
+        put_byte(s, (Byte)((strm->adler >> 24) & 0xff));
+        put_byte(s, (Byte)(strm->total_in & 0xff));
+        put_byte(s, (Byte)((strm->total_in >> 8) & 0xff));
+        put_byte(s, (Byte)((strm->total_in >> 16) & 0xff));
+        put_byte(s, (Byte)((strm->total_in >> 24) & 0xff));
+    }
+    else
+#endif
+    {
+        putShortMSB(s, (uInt)(strm->adler >> 16));
+        putShortMSB(s, (uInt)(strm->adler & 0xffff));
+    }
+    flush_pending(strm);
+    /* If avail_out is zero, the application will call deflate again
+     * to flush the rest.
+     */
+    if (s->wrap > 0) s->wrap = -s->wrap; /* write the trailer only once! */
+    return s->pending != 0 ? Z_OK : Z_STREAM_END;
+}
+
+/* ========================================================================= */
+int ZEXPORT deflateEnd (strm)
+    z_streamp strm;
+{
+    int status;
+
+    if (deflateStateCheck(strm)) return Z_STREAM_ERROR;
+
+    status = strm->state->status;
+
+    /* Deallocate in reverse order of allocations: */
+    TRY_FREE(strm, strm->state->pending_buf);
+    TRY_FREE(strm, strm->state->head);
+    TRY_FREE(strm, strm->state->prev);
+    TRY_FREE(strm, strm->state->window);
+
+    ZFREE(strm, strm->state);
+    strm->state = Z_NULL;
+
+    return status == BUSY_STATE ? Z_DATA_ERROR : Z_OK;
+}
+
+/* =========================================================================
+ * Copy the source state to the destination state.
+ * To simplify the source, this is not supported for 16-bit MSDOS (which
+ * doesn't have enough memory anyway to duplicate compression states).
+ */
+int ZEXPORT deflateCopy (dest, source)
+    z_streamp dest;
+    z_streamp source;
+{
+#ifdef MAXSEG_64K
+    return Z_STREAM_ERROR;
+#else
+    deflate_state *ds;
+    deflate_state *ss;
+    ushf *overlay;
+
+
+    if (deflateStateCheck(source) || dest == Z_NULL) {
+        return Z_STREAM_ERROR;
+    }
+
+    ss = source->state;
+
+    zmemcpy((voidpf)dest, (voidpf)source, sizeof(z_stream));
+
+    ds = (deflate_state *) ZALLOC(dest, 1, sizeof(deflate_state));
+    if (ds == Z_NULL) return Z_MEM_ERROR;
+    dest->state = (struct internal_state FAR *) ds;
+    zmemcpy((voidpf)ds, (voidpf)ss, sizeof(deflate_state));
+    ds->strm = dest;
+
+    ds->window = (Bytef *) ZALLOC(dest, ds->w_size, 2*sizeof(Byte));
+    ds->prev   = (Posf *)  ZALLOC(dest, ds->w_size, sizeof(Pos));
+    ds->head   = (Posf *)  ZALLOC(dest, ds->hash_size, sizeof(Pos));
+    overlay = (ushf *) ZALLOC(dest, ds->lit_bufsize, sizeof(ush)+2);
+    ds->pending_buf = (uchf *) overlay;
+
+    if (ds->window == Z_NULL || ds->prev == Z_NULL || ds->head == Z_NULL ||
+        ds->pending_buf == Z_NULL) {
+        deflateEnd (dest);
+        return Z_MEM_ERROR;
+    }
+    /* following zmemcpy do not work for 16-bit MSDOS */
+    zmemcpy(ds->window, ss->window, ds->w_size * 2 * sizeof(Byte));
+    zmemcpy((voidpf)ds->prev, (voidpf)ss->prev, ds->w_size * sizeof(Pos));
+    zmemcpy((voidpf)ds->head, (voidpf)ss->head, ds->hash_size * sizeof(Pos));
+    zmemcpy(ds->pending_buf, ss->pending_buf, (uInt)ds->pending_buf_size);
+
+    ds->pending_out = ds->pending_buf + (ss->pending_out - ss->pending_buf);
+    ds->d_buf = overlay + ds->lit_bufsize/sizeof(ush);
+    ds->l_buf = ds->pending_buf + (1+sizeof(ush))*ds->lit_bufsize;
+
+    ds->l_desc.dyn_tree = ds->dyn_ltree;
+    ds->d_desc.dyn_tree = ds->dyn_dtree;
+    ds->bl_desc.dyn_tree = ds->bl_tree;
+
+    return Z_OK;
+#endif /* MAXSEG_64K */
+}
+
+/* ===========================================================================
+ * Read a new buffer from the current input stream, update the adler32
+ * and total number of bytes read.  All deflate() input goes through
+ * this function so some applications may wish to modify it to avoid
+ * allocating a large strm->next_in buffer and copying from it.
+ * (See also flush_pending()).
+ */
+local unsigned read_buf(strm, buf, size)
+    z_streamp strm;
+    Bytef *buf;
+    unsigned size;
+{
+    unsigned len = strm->avail_in;
+
+    if (len > size) len = size;
+    if (len == 0) return 0;
+
+    strm->avail_in  -= len;
+
+    zmemcpy(buf, strm->next_in, len);
+    if (strm->state->wrap == 1) {
+        strm->adler = adler32(strm->adler, buf, len);
+    }
+#ifdef GZIP
+    else if (strm->state->wrap == 2) {
+        strm->adler = crc32(strm->adler, buf, len);
+    }
+#endif
+    strm->next_in  += len;
+    strm->total_in += len;
+
+    return len;
+}
+
+/* ===========================================================================
+ * Initialize the "longest match" routines for a new zlib stream
+ */
+local void lm_init (s)
+    deflate_state *s;
+{
+    s->window_size = (ulg)2L*s->w_size;
+
+    CLEAR_HASH(s);
+
+    /* Set the default configuration parameters:
+     */
+    s->max_lazy_match   = configuration_table[s->level].max_lazy;
+    s->good_match       = configuration_table[s->level].good_length;
+    s->nice_match       = configuration_table[s->level].nice_length;
+    s->max_chain_length = configuration_table[s->level].max_chain;
+
+    s->strstart = 0;
+    s->block_start = 0L;
+    s->lookahead = 0;
+    s->insert = 0;
+    s->match_length = s->prev_length = MIN_MATCH-1;
+    s->match_available = 0;
+    s->ins_h = 0;
+#ifndef FASTEST
+#ifdef ASMV
+    match_init(); /* initialize the asm code */
+#endif
+#endif
+}
+
+#ifndef FASTEST
+/* ===========================================================================
+ * Set match_start to the longest match starting at the given string and
+ * return its length. Matches shorter or equal to prev_length are discarded,
+ * in which case the result is equal to prev_length and match_start is
+ * garbage.
+ * IN assertions: cur_match is the head of the hash chain for the current
+ *   string (strstart) and its distance is <= MAX_DIST, and prev_length >= 1
+ * OUT assertion: the match length is not greater than s->lookahead.
+ */
+#ifndef ASMV
+/* For 80x86 and 680x0, an optimized version will be provided in match.asm or
+ * match.S. The code will be functionally equivalent.
+ */
+local uInt longest_match(s, cur_match)
+    deflate_state *s;
+    IPos cur_match;                             /* current match */
+{
+    unsigned chain_length = s->max_chain_length;/* max hash chain length */
+    register Bytef *scan = s->window + s->strstart; /* current string */
+    register Bytef *match;                      /* matched string */
+    register int len;                           /* length of current match */
+    int best_len = (int)s->prev_length;         /* best match length so far */
+    int nice_match = s->nice_match;             /* stop if match long enough */
+    IPos limit = s->strstart > (IPos)MAX_DIST(s) ?
+        s->strstart - (IPos)MAX_DIST(s) : NIL;
+    /* Stop when cur_match becomes <= limit. To simplify the code,
+     * we prevent matches with the string of window index 0.
+     */
+    Posf *prev = s->prev;
+    uInt wmask = s->w_mask;
+
+#ifdef UNALIGNED_OK
+    /* Compare two bytes at a time. Note: this is not always beneficial.
+     * Try with and without -DUNALIGNED_OK to check.
+     */
+    register Bytef *strend = s->window + s->strstart + MAX_MATCH - 1;
+    register ush scan_start = *(ushf*)scan;
+    register ush scan_end   = *(ushf*)(scan+best_len-1);
+#else
+    register Bytef *strend = s->window + s->strstart + MAX_MATCH;
+    register Byte scan_end1  = scan[best_len-1];
+    register Byte scan_end   = scan[best_len];
+#endif
+
+    /* The code is optimized for HASH_BITS >= 8 and MAX_MATCH-2 multiple of 16.
+     * It is easy to get rid of this optimization if necessary.
+     */
+    Assert(s->hash_bits >= 8 && MAX_MATCH == 258, "Code too clever");
+
+    /* Do not waste too much time if we already have a good match: */
+    if (s->prev_length >= s->good_match) {
+        chain_length >>= 2;
+    }
+    /* Do not look for matches beyond the end of the input. This is necessary
+     * to make deflate deterministic.
+     */
+    if ((uInt)nice_match > s->lookahead) nice_match = (int)s->lookahead;
+
+    Assert((ulg)s->strstart <= s->window_size-MIN_LOOKAHEAD, "need lookahead");
+
+    do {
+        Assert(cur_match < s->strstart, "no future");
+        match = s->window + cur_match;
+
+        /* Skip to next match if the match length cannot increase
+         * or if the match length is less than 2.  Note that the checks below
+         * for insufficient lookahead only occur occasionally for performance
+         * reasons.  Therefore uninitialized memory will be accessed, and
+         * conditional jumps will be made that depend on those values.
+         * However the length of the match is limited to the lookahead, so
+         * the output of deflate is not affected by the uninitialized values.
+         */
+#if (defined(UNALIGNED_OK) && MAX_MATCH == 258)
+        /* This code assumes sizeof(unsigned short) == 2. Do not use
+         * UNALIGNED_OK if your compiler uses a different size.
+         */
+        if (*(ushf*)(match+best_len-1) != scan_end ||
+            *(ushf*)match != scan_start) continue;
+
+        /* It is not necessary to compare scan[2] and match[2] since they are
+         * always equal when the other bytes match, given that the hash keys
+         * are equal and that HASH_BITS >= 8. Compare 2 bytes at a time at
+         * strstart+3, +5, ... up to strstart+257. We check for insufficient
+         * lookahead only every 4th comparison; the 128th check will be made
+         * at strstart+257. If MAX_MATCH-2 is not a multiple of 8, it is
+         * necessary to put more guard bytes at the end of the window, or
+         * to check more often for insufficient lookahead.
+         */
+        Assert(scan[2] == match[2], "scan[2]?");
+        scan++, match++;
+        do {
+        } while (*(ushf*)(scan+=2) == *(ushf*)(match+=2) &&
+                 *(ushf*)(scan+=2) == *(ushf*)(match+=2) &&
+                 *(ushf*)(scan+=2) == *(ushf*)(match+=2) &&
+                 *(ushf*)(scan+=2) == *(ushf*)(match+=2) &&
+                 scan < strend);
+        /* The funny "do {}" generates better code on most compilers */
+
+        /* Here, scan <= window+strstart+257 */
+        Assert(scan <= s->window+(unsigned)(s->window_size-1), "wild scan");
+        if (*scan == *match) scan++;
+
+        len = (MAX_MATCH - 1) - (int)(strend-scan);
+        scan = strend - (MAX_MATCH-1);
+
+#else /* UNALIGNED_OK */
+
+        if (match[best_len]   != scan_end  ||
+            match[best_len-1] != scan_end1 ||
+            *match            != *scan     ||
+            *++match          != scan[1])      continue;
+
+        /* The check at best_len-1 can be removed because it will be made
+         * again later. (This heuristic is not always a win.)
+         * It is not necessary to compare scan[2] and match[2] since they
+         * are always equal when the other bytes match, given that
+         * the hash keys are equal and that HASH_BITS >= 8.
+         */
+        scan += 2, match++;
+        Assert(*scan == *match, "match[2]?");
+
+        /* We check for insufficient lookahead only every 8th comparison;
+         * the 256th check will be made at strstart+258.
+         */
+        do {
+        } while (*++scan == *++match && *++scan == *++match &&
+                 *++scan == *++match && *++scan == *++match &&
+                 *++scan == *++match && *++scan == *++match &&
+                 *++scan == *++match && *++scan == *++match &&
+                 scan < strend);
+
+        Assert(scan <= s->window+(unsigned)(s->window_size-1), "wild scan");
+
+        len = MAX_MATCH - (int)(strend - scan);
+        scan = strend - MAX_MATCH;
+
+#endif /* UNALIGNED_OK */
+
+        if (len > best_len) {
+            s->match_start = cur_match;
+            best_len = len;
+            if (len >= nice_match) break;
+#ifdef UNALIGNED_OK
+            scan_end = *(ushf*)(scan+best_len-1);
+#else
+            scan_end1  = scan[best_len-1];
+            scan_end   = scan[best_len];
+#endif
+        }
+    } while ((cur_match = prev[cur_match & wmask]) > limit
+             && --chain_length != 0);
+
+    if ((uInt)best_len <= s->lookahead) return (uInt)best_len;
+    return s->lookahead;
+}
+#endif /* ASMV */
+
+#else /* FASTEST */
+
+/* ---------------------------------------------------------------------------
+ * Optimized version for FASTEST only
+ */
+local uInt longest_match(s, cur_match)
+    deflate_state *s;
+    IPos cur_match;                             /* current match */
+{
+    register Bytef *scan = s->window + s->strstart; /* current string */
+    register Bytef *match;                       /* matched string */
+    register int len;                           /* length of current match */
+    register Bytef *strend = s->window + s->strstart + MAX_MATCH;
+
+    /* The code is optimized for HASH_BITS >= 8 and MAX_MATCH-2 multiple of 16.
+     * It is easy to get rid of this optimization if necessary.
+     */
+    Assert(s->hash_bits >= 8 && MAX_MATCH == 258, "Code too clever");
+
+    Assert((ulg)s->strstart <= s->window_size-MIN_LOOKAHEAD, "need lookahead");
+
+    Assert(cur_match < s->strstart, "no future");
+
+    match = s->window + cur_match;
+
+    /* Return failure if the match length is less than 2:
+     */
+    if (match[0] != scan[0] || match[1] != scan[1]) return MIN_MATCH-1;
+
+    /* The check at best_len-1 can be removed because it will be made
+     * again later. (This heuristic is not always a win.)
+     * It is not necessary to compare scan[2] and match[2] since they
+     * are always equal when the other bytes match, given that
+     * the hash keys are equal and that HASH_BITS >= 8.
+     */
+    scan += 2, match += 2;
+    Assert(*scan == *match, "match[2]?");
+
+    /* We check for insufficient lookahead only every 8th comparison;
+     * the 256th check will be made at strstart+258.
+     */
+    do {
+    } while (*++scan == *++match && *++scan == *++match &&
+             *++scan == *++match && *++scan == *++match &&
+             *++scan == *++match && *++scan == *++match &&
+             *++scan == *++match && *++scan == *++match &&
+             scan < strend);
+
+    Assert(scan <= s->window+(unsigned)(s->window_size-1), "wild scan");
+
+    len = MAX_MATCH - (int)(strend - scan);
+
+    if (len < MIN_MATCH) return MIN_MATCH - 1;
+
+    s->match_start = cur_match;
+    return (uInt)len <= s->lookahead ? (uInt)len : s->lookahead;
+}
+
+#endif /* FASTEST */
+
+#ifdef ZLIB_DEBUG
+
+#define EQUAL 0
+/* result of memcmp for equal strings */
+
+/* ===========================================================================
+ * Check that the match at match_start is indeed a match.
+ */
+local void check_match(s, start, match, length)
+    deflate_state *s;
+    IPos start, match;
+    int length;
+{
+    /* check that the match is indeed a match */
+    if (zmemcmp(s->window + match,
+                s->window + start, length) != EQUAL) {
+        fprintf(stderr, " start %u, match %u, length %d\n",
+                start, match, length);
+        do {
+            fprintf(stderr, "%c%c", s->window[match++], s->window[start++]);
+        } while (--length != 0);
+        z_error("invalid match");
+    }
+    if (z_verbose > 1) {
+        fprintf(stderr,"\\[%d,%d]", start-match, length);
+        do { putc(s->window[start++], stderr); } while (--length != 0);
+    }
+}
+#else
+#  define check_match(s, start, match, length)
+#endif /* ZLIB_DEBUG */
+
+/* ===========================================================================
+ * Fill the window when the lookahead becomes insufficient.
+ * Updates strstart and lookahead.
+ *
+ * IN assertion: lookahead < MIN_LOOKAHEAD
+ * OUT assertions: strstart <= window_size-MIN_LOOKAHEAD
+ *    At least one byte has been read, or avail_in == 0; reads are
+ *    performed for at least two bytes (required for the zip translate_eol
+ *    option -- not supported here).
+ */
+local void fill_window(s)
+    deflate_state *s;
+{
+    unsigned n;
+    unsigned more;    /* Amount of free space at the end of the window. */
+    uInt wsize = s->w_size;
+
+    Assert(s->lookahead < MIN_LOOKAHEAD, "already enough lookahead");
+
+    do {
+        more = (unsigned)(s->window_size -(ulg)s->lookahead -(ulg)s->strstart);
+
+        /* Deal with !@#$% 64K limit: */
+        if (sizeof(int) <= 2) {
+            if (more == 0 && s->strstart == 0 && s->lookahead == 0) {
+                more = wsize;
+
+            } else if (more == (unsigned)(-1)) {
+                /* Very unlikely, but possible on 16 bit machine if
+                 * strstart == 0 && lookahead == 1 (input done a byte at time)
+                 */
+                more--;
+            }
+        }
+
+        /* If the window is almost full and there is insufficient lookahead,
+         * move the upper half to the lower one to make room in the upper half.
+         */
+        if (s->strstart >= wsize+MAX_DIST(s)) {
+
+            zmemcpy(s->window, s->window+wsize, (unsigned)wsize - more);
+            s->match_start -= wsize;
+            s->strstart    -= wsize; /* we now have strstart >= MAX_DIST */
+            s->block_start -= (long) wsize;
+            slide_hash(s);
+            more += wsize;
+        }
+        if (s->strm->avail_in == 0) break;
+
+        /* If there was no sliding:
+         *    strstart <= WSIZE+MAX_DIST-1 && lookahead <= MIN_LOOKAHEAD - 1 &&
+         *    more == window_size - lookahead - strstart
+         * => more >= window_size - (MIN_LOOKAHEAD-1 + WSIZE + MAX_DIST-1)
+         * => more >= window_size - 2*WSIZE + 2
+         * In the BIG_MEM or MMAP case (not yet supported),
+         *   window_size == input_size + MIN_LOOKAHEAD  &&
+         *   strstart + s->lookahead <= input_size => more >= MIN_LOOKAHEAD.
+         * Otherwise, window_size == 2*WSIZE so more >= 2.
+         * If there was sliding, more >= WSIZE. So in all cases, more >= 2.
+         */
+        Assert(more >= 2, "more < 2");
+
+        n = read_buf(s->strm, s->window + s->strstart + s->lookahead, more);
+        s->lookahead += n;
+
+        /* Initialize the hash value now that we have some input: */
+        if (s->lookahead + s->insert >= MIN_MATCH) {
+            uInt str = s->strstart - s->insert;
+            s->ins_h = s->window[str];
+            UPDATE_HASH(s, s->ins_h, s->window[str + 1]);
+#if MIN_MATCH != 3
+            Call UPDATE_HASH() MIN_MATCH-3 more times
+#endif
+            while (s->insert) {
+                UPDATE_HASH(s, s->ins_h, s->window[str + MIN_MATCH-1]);
+#ifndef FASTEST
+                s->prev[str & s->w_mask] = s->head[s->ins_h];
+#endif
+                s->head[s->ins_h] = (Pos)str;
+                str++;
+                s->insert--;
+                if (s->lookahead + s->insert < MIN_MATCH)
+                    break;
+            }
+        }
+        /* If the whole input has less than MIN_MATCH bytes, ins_h is garbage,
+         * but this is not important since only literal bytes will be emitted.
+         */
+
+    } while (s->lookahead < MIN_LOOKAHEAD && s->strm->avail_in != 0);
+
+    /* If the WIN_INIT bytes after the end of the current data have never been
+     * written, then zero those bytes in order to avoid memory check reports of
+     * the use of uninitialized (or uninitialised as Julian writes) bytes by
+     * the longest match routines.  Update the high water mark for the next
+     * time through here.  WIN_INIT is set to MAX_MATCH since the longest match
+     * routines allow scanning to strstart + MAX_MATCH, ignoring lookahead.
+     */
+    if (s->high_water < s->window_size) {
+        ulg curr = s->strstart + (ulg)(s->lookahead);
+        ulg init;
+
+        if (s->high_water < curr) {
+            /* Previous high water mark below current data -- zero WIN_INIT
+             * bytes or up to end of window, whichever is less.
+             */
+            init = s->window_size - curr;
+            if (init > WIN_INIT)
+                init = WIN_INIT;
+            zmemzero(s->window + curr, (unsigned)init);
+            s->high_water = curr + init;
+        }
+        else if (s->high_water < (ulg)curr + WIN_INIT) {
+            /* High water mark at or above current data, but below current data
+             * plus WIN_INIT -- zero out to current data plus WIN_INIT, or up
+             * to end of window, whichever is less.
+             */
+            init = (ulg)curr + WIN_INIT - s->high_water;
+            if (init > s->window_size - s->high_water)
+                init = s->window_size - s->high_water;
+            zmemzero(s->window + s->high_water, (unsigned)init);
+            s->high_water += init;
+        }
+    }
+
+    Assert((ulg)s->strstart <= s->window_size - MIN_LOOKAHEAD,
+           "not enough room for search");
+}
+
+/* ===========================================================================
+ * Flush the current block, with given end-of-file flag.
+ * IN assertion: strstart is set to the end of the current match.
+ */
+#define FLUSH_BLOCK_ONLY(s, last) { \
+   _tr_flush_block(s, (s->block_start >= 0L ? \
+                   (charf *)&s->window[(unsigned)s->block_start] : \
+                   (charf *)Z_NULL), \
+                (ulg)((long)s->strstart - s->block_start), \
+                (last)); \
+   s->block_start = s->strstart; \
+   flush_pending(s->strm); \
+   Tracev((stderr,"[FLUSH]")); \
+}
+
+/* Same but force premature exit if necessary. */
+#define FLUSH_BLOCK(s, last) { \
+   FLUSH_BLOCK_ONLY(s, last); \
+   if (s->strm->avail_out == 0) return (last) ? finish_started : need_more; \
+}
+
+/* Maximum stored block length in deflate format (not including header). */
+#define MAX_STORED 65535
+
+/* Minimum of a and b. */
+#define MIN(a, b) ((a) > (b) ? (b) : (a))
+
+/* ===========================================================================
+ * Copy without compression as much as possible from the input stream, return
+ * the current block state.
+ *
+ * In case deflateParams() is used to later switch to a non-zero compression
+ * level, s->matches (otherwise unused when storing) keeps track of the number
+ * of hash table slides to perform. If s->matches is 1, then one hash table
+ * slide will be done when switching. If s->matches is 2, the maximum value
+ * allowed here, then the hash table will be cleared, since two or more slides
+ * is the same as a clear.
+ *
+ * deflate_stored() is written to minimize the number of times an input byte is
+ * copied. It is most efficient with large input and output buffers, which
+ * maximizes the opportunites to have a single copy from next_in to next_out.
+ */
+local block_state deflate_stored(s, flush)
+    deflate_state *s;
+    int flush;
+{
+    /* Smallest worthy block size when not flushing or finishing. By default
+     * this is 32K. This can be as small as 507 bytes for memLevel == 1. For
+     * large input and output buffers, the stored block size will be larger.
+     */
+    unsigned min_block = MIN(s->pending_buf_size - 5, s->w_size);
+
+    /* Copy as many min_block or larger stored blocks directly to next_out as
+     * possible. If flushing, copy the remaining available input to next_out as
+     * stored blocks, if there is enough space.
+     */
+    unsigned len, left, have, last = 0;
+    unsigned used = s->strm->avail_in;
+    do {
+        /* Set len to the maximum size block that we can copy directly with the
+         * available input data and output space. Set left to how much of that
+         * would be copied from what's left in the window.
+         */
+        len = MAX_STORED;       /* maximum deflate stored block length */
+        have = (s->bi_valid + 42) >> 3;         /* number of header bytes */
+        if (s->strm->avail_out < have)          /* need room for header */
+            break;
+            /* maximum stored block length that will fit in avail_out: */
+        have = s->strm->avail_out - have;
+        left = s->strstart - s->block_start;    /* bytes left in window */
+        if (len > (ulg)left + s->strm->avail_in)
+            len = left + s->strm->avail_in;     /* limit len to the input */
+        if (len > have)
+            len = have;                         /* limit len to the output */
+
+        /* If the stored block would be less than min_block in length, or if
+         * unable to copy all of the available input when flushing, then try
+         * copying to the window and the pending buffer instead. Also don't
+         * write an empty block when flushing -- deflate() does that.
+         */
+        if (len < min_block && ((len == 0 && flush != Z_FINISH) ||
+                                flush == Z_NO_FLUSH ||
+                                len != left + s->strm->avail_in))
+            break;
+
+        /* Make a dummy stored block in pending to get the header bytes,
+         * including any pending bits. This also updates the debugging counts.
+         */
+        last = flush == Z_FINISH && len == left + s->strm->avail_in ? 1 : 0;
+        _tr_stored_block(s, (char *)0, 0L, last);
+
+        /* Replace the lengths in the dummy stored block with len. */
+        s->pending_buf[s->pending - 4] = len;
+        s->pending_buf[s->pending - 3] = len >> 8;
+        s->pending_buf[s->pending - 2] = ~len;
+        s->pending_buf[s->pending - 1] = ~len >> 8;
+
+        /* Write the stored block header bytes. */
+        flush_pending(s->strm);
+
+#ifdef ZLIB_DEBUG
+        /* Update debugging counts for the data about to be copied. */
+        s->compressed_len += len << 3;
+        s->bits_sent += len << 3;
+#endif
+
+        /* Copy uncompressed bytes from the window to next_out. */
+        if (left) {
+            if (left > len)
+                left = len;
+            zmemcpy(s->strm->next_out, s->window + s->block_start, left);
+            s->strm->next_out += left;
+            s->strm->avail_out -= left;
+            s->strm->total_out += left;
+            s->block_start += left;
+            len -= left;
+        }
+
+        /* Copy uncompressed bytes directly from next_in to next_out, updating
+         * the check value.
+         */
+        if (len) {
+            read_buf(s->strm, s->strm->next_out, len);
+            s->strm->next_out += len;
+            s->strm->avail_out -= len;
+            s->strm->total_out += len;
+        }
+    } while (last == 0);
+
+    /* Update the sliding window with the last s->w_size bytes of the copied
+     * data, or append all of the copied data to the existing window if less
+     * than s->w_size bytes were copied. Also update the number of bytes to
+     * insert in the hash tables, in the event that deflateParams() switches to
+     * a non-zero compression level.
+     */
+    used -= s->strm->avail_in;      /* number of input bytes directly copied */
+    if (used) {
+        /* If any input was used, then no unused input remains in the window,
+         * therefore s->block_start == s->strstart.
+         */
+        if (used >= s->w_size) {    /* supplant the previous history */
+            s->matches = 2;         /* clear hash */
+            zmemcpy(s->window, s->strm->next_in - s->w_size, s->w_size);
+            s->strstart = s->w_size;
+        }
+        else {
+            if (s->window_size - s->strstart <= used) {
+                /* Slide the window down. */
+                s->strstart -= s->w_size;
+                zmemcpy(s->window, s->window + s->w_size, s->strstart);
+                if (s->matches < 2)
+                    s->matches++;   /* add a pending slide_hash() */
+            }
+            zmemcpy(s->window + s->strstart, s->strm->next_in - used, used);
+            s->strstart += used;
+        }
+        s->block_start = s->strstart;
+        s->insert += MIN(used, s->w_size - s->insert);
+    }
+    if (s->high_water < s->strstart)
+        s->high_water = s->strstart;
+
+    /* If the last block was written to next_out, then done. */
+    if (last)
+        return finish_done;
+
+    /* If flushing and all input has been consumed, then done. */
+    if (flush != Z_NO_FLUSH && flush != Z_FINISH &&
+        s->strm->avail_in == 0 && (long)s->strstart == s->block_start)
+        return block_done;
+
+    /* Fill the window with any remaining input. */
+    have = s->window_size - s->strstart - 1;
+    if (s->strm->avail_in > have && s->block_start >= (long)s->w_size) {
+        /* Slide the window down. */
+        s->block_start -= s->w_size;
+        s->strstart -= s->w_size;
+        zmemcpy(s->window, s->window + s->w_size, s->strstart);
+        if (s->matches < 2)
+            s->matches++;           /* add a pending slide_hash() */
+        have += s->w_size;          /* more space now */
+    }
+    if (have > s->strm->avail_in)
+        have = s->strm->avail_in;
+    if (have) {
+        read_buf(s->strm, s->window + s->strstart, have);
+        s->strstart += have;
+    }
+    if (s->high_water < s->strstart)
+        s->high_water = s->strstart;
+
+    /* There was not enough avail_out to write a complete worthy or flushed
+     * stored block to next_out. Write a stored block to pending instead, if we
+     * have enough input for a worthy block, or if flushing and there is enough
+     * room for the remaining input as a stored block in the pending buffer.
+     */
+    have = (s->bi_valid + 42) >> 3;         /* number of header bytes */
+        /* maximum stored block length that will fit in pending: */
+    have = MIN(s->pending_buf_size - have, MAX_STORED);
+    min_block = MIN(have, s->w_size);
+    left = s->strstart - s->block_start;
+    if (left >= min_block ||
+        ((left || flush == Z_FINISH) && flush != Z_NO_FLUSH &&
+         s->strm->avail_in == 0 && left <= have)) {
+        len = MIN(left, have);
+        last = flush == Z_FINISH && s->strm->avail_in == 0 &&
+               len == left ? 1 : 0;
+        _tr_stored_block(s, (charf *)s->window + s->block_start, len, last);
+        s->block_start += len;
+        flush_pending(s->strm);
+    }
+
+    /* We've done all we can with the available input and output. */
+    return last ? finish_started : need_more;
+}
+
+/* ===========================================================================
+ * Compress as much as possible from the input stream, return the current
+ * block state.
+ * This function does not perform lazy evaluation of matches and inserts
+ * new strings in the dictionary only for unmatched strings or for short
+ * matches. It is used only for the fast compression options.
+ */
+local block_state deflate_fast(s, flush)
+    deflate_state *s;
+    int flush;
+{
+    IPos hash_head;       /* head of the hash chain */
+    int bflush;           /* set if current block must be flushed */
+
+    for (;;) {
+        /* Make sure that we always have enough lookahead, except
+         * at the end of the input file. We need MAX_MATCH bytes
+         * for the next match, plus MIN_MATCH bytes to insert the
+         * string following the next match.
+         */
+        if (s->lookahead < MIN_LOOKAHEAD) {
+            fill_window(s);
+            if (s->lookahead < MIN_LOOKAHEAD && flush == Z_NO_FLUSH) {
+                return need_more;
+            }
+            if (s->lookahead == 0) break; /* flush the current block */
+        }
+
+        /* Insert the string window[strstart .. strstart+2] in the
+         * dictionary, and set hash_head to the head of the hash chain:
+         */
+        hash_head = NIL;
+        if (s->lookahead >= MIN_MATCH) {
+            INSERT_STRING(s, s->strstart, hash_head);
+        }
+
+        /* Find the longest match, discarding those <= prev_length.
+         * At this point we have always match_length < MIN_MATCH
+         */
+        if (hash_head != NIL && s->strstart - hash_head <= MAX_DIST(s)) {
+            /* To simplify the code, we prevent matches with the string
+             * of window index 0 (in particular we have to avoid a match
+             * of the string with itself at the start of the input file).
+             */
+            s->match_length = longest_match (s, hash_head);
+            /* longest_match() sets match_start */
+        }
+        if (s->match_length >= MIN_MATCH) {
+            check_match(s, s->strstart, s->match_start, s->match_length);
+
+            _tr_tally_dist(s, s->strstart - s->match_start,
+                           s->match_length - MIN_MATCH, bflush);
+
+            s->lookahead -= s->match_length;
+
+            /* Insert new strings in the hash table only if the match length
+             * is not too large. This saves time but degrades compression.
+             */
+#ifndef FASTEST
+            if (s->match_length <= s->max_insert_length &&
+                s->lookahead >= MIN_MATCH) {
+                s->match_length--; /* string at strstart already in table */
+                do {
+                    s->strstart++;
+                    INSERT_STRING(s, s->strstart, hash_head);
+                    /* strstart never exceeds WSIZE-MAX_MATCH, so there are
+                     * always MIN_MATCH bytes ahead.
+                     */
+                } while (--s->match_length != 0);
+                s->strstart++;
+            } else
+#endif
+            {
+                s->strstart += s->match_length;
+                s->match_length = 0;
+                s->ins_h = s->window[s->strstart];
+                UPDATE_HASH(s, s->ins_h, s->window[s->strstart+1]);
+#if MIN_MATCH != 3
+                Call UPDATE_HASH() MIN_MATCH-3 more times
+#endif
+                /* If lookahead < MIN_MATCH, ins_h is garbage, but it does not
+                 * matter since it will be recomputed at next deflate call.
+                 */
+            }
+        } else {
+            /* No match, output a literal byte */
+            Tracevv((stderr,"%c", s->window[s->strstart]));
+            _tr_tally_lit (s, s->window[s->strstart], bflush);
+            s->lookahead--;
+            s->strstart++;
+        }
+        if (bflush) FLUSH_BLOCK(s, 0);
+    }
+    s->insert = s->strstart < MIN_MATCH-1 ? s->strstart : MIN_MATCH-1;
+    if (flush == Z_FINISH) {
+        FLUSH_BLOCK(s, 1);
+        return finish_done;
+    }
+    if (s->last_lit)
+        FLUSH_BLOCK(s, 0);
+    return block_done;
+}
+
+#ifndef FASTEST
+/* ===========================================================================
+ * Same as above, but achieves better compression. We use a lazy
+ * evaluation for matches: a match is finally adopted only if there is
+ * no better match at the next window position.
+ */
+local block_state deflate_slow(s, flush)
+    deflate_state *s;
+    int flush;
+{
+    IPos hash_head;          /* head of hash chain */
+    int bflush;              /* set if current block must be flushed */
+
+    /* Process the input block. */
+    for (;;) {
+        /* Make sure that we always have enough lookahead, except
+         * at the end of the input file. We need MAX_MATCH bytes
+         * for the next match, plus MIN_MATCH bytes to insert the
+         * string following the next match.
+         */
+        if (s->lookahead < MIN_LOOKAHEAD) {
+            fill_window(s);
+            if (s->lookahead < MIN_LOOKAHEAD && flush == Z_NO_FLUSH) {
+                return need_more;
+            }
+            if (s->lookahead == 0) break; /* flush the current block */
+        }
+
+        /* Insert the string window[strstart .. strstart+2] in the
+         * dictionary, and set hash_head to the head of the hash chain:
+         */
+        hash_head = NIL;
+        if (s->lookahead >= MIN_MATCH) {
+            INSERT_STRING(s, s->strstart, hash_head);
+        }
+
+        /* Find the longest match, discarding those <= prev_length.
+         */
+        s->prev_length = s->match_length, s->prev_match = s->match_start;
+        s->match_length = MIN_MATCH-1;
+
+        if (hash_head != NIL && s->prev_length < s->max_lazy_match &&
+            s->strstart - hash_head <= MAX_DIST(s)) {
+            /* To simplify the code, we prevent matches with the string
+             * of window index 0 (in particular we have to avoid a match
+             * of the string with itself at the start of the input file).
+             */
+            s->match_length = longest_match (s, hash_head);
+            /* longest_match() sets match_start */
+
+            if (s->match_length <= 5 && (s->strategy == Z_FILTERED
+#if TOO_FAR <= 32767
+                || (s->match_length == MIN_MATCH &&
+                    s->strstart - s->match_start > TOO_FAR)
+#endif
+                )) {
+
+                /* If prev_match is also MIN_MATCH, match_start is garbage
+                 * but we will ignore the current match anyway.
+                 */
+                s->match_length = MIN_MATCH-1;
+            }
+        }
+        /* If there was a match at the previous step and the current
+         * match is not better, output the previous match:
+         */
+        if (s->prev_length >= MIN_MATCH && s->match_length <= s->prev_length) {
+            uInt max_insert = s->strstart + s->lookahead - MIN_MATCH;
+            /* Do not insert strings in hash table beyond this. */
+
+            check_match(s, s->strstart-1, s->prev_match, s->prev_length);
+
+            _tr_tally_dist(s, s->strstart -1 - s->prev_match,
+                           s->prev_length - MIN_MATCH, bflush);
+
+            /* Insert in hash table all strings up to the end of the match.
+             * strstart-1 and strstart are already inserted. If there is not
+             * enough lookahead, the last two strings are not inserted in
+             * the hash table.
+             */
+            s->lookahead -= s->prev_length-1;
+            s->prev_length -= 2;
+            do {
+                if (++s->strstart <= max_insert) {
+                    INSERT_STRING(s, s->strstart, hash_head);
+                }
+            } while (--s->prev_length != 0);
+            s->match_available = 0;
+            s->match_length = MIN_MATCH-1;
+            s->strstart++;
+
+            if (bflush) FLUSH_BLOCK(s, 0);
+
+        } else if (s->match_available) {
+            /* If there was no match at the previous position, output a
+             * single literal. If there was a match but the current match
+             * is longer, truncate the previous match to a single literal.
+             */
+            Tracevv((stderr,"%c", s->window[s->strstart-1]));
+            _tr_tally_lit(s, s->window[s->strstart-1], bflush);
+            if (bflush) {
+                FLUSH_BLOCK_ONLY(s, 0);
+            }
+            s->strstart++;
+            s->lookahead--;
+            if (s->strm->avail_out == 0) return need_more;
+        } else {
+            /* There is no previous match to compare with, wait for
+             * the next step to decide.
+             */
+            s->match_available = 1;
+            s->strstart++;
+            s->lookahead--;
+        }
+    }
+    Assert (flush != Z_NO_FLUSH, "no flush?");
+    if (s->match_available) {
+        Tracevv((stderr,"%c", s->window[s->strstart-1]));
+        _tr_tally_lit(s, s->window[s->strstart-1], bflush);
+        s->match_available = 0;
+    }
+    s->insert = s->strstart < MIN_MATCH-1 ? s->strstart : MIN_MATCH-1;
+    if (flush == Z_FINISH) {
+        FLUSH_BLOCK(s, 1);
+        return finish_done;
+    }
+    if (s->last_lit)
+        FLUSH_BLOCK(s, 0);
+    return block_done;
+}
+#endif /* FASTEST */
+
+/* ===========================================================================
+ * For Z_RLE, simply look for runs of bytes, generate matches only of distance
+ * one.  Do not maintain a hash table.  (It will be regenerated if this run of
+ * deflate switches away from Z_RLE.)
+ */
+local block_state deflate_rle(s, flush)
+    deflate_state *s;
+    int flush;
+{
+    int bflush;             /* set if current block must be flushed */
+    uInt prev;              /* byte at distance one to match */
+    Bytef *scan, *strend;   /* scan goes up to strend for length of run */
+
+    for (;;) {
+        /* Make sure that we always have enough lookahead, except
+         * at the end of the input file. We need MAX_MATCH bytes
+         * for the longest run, plus one for the unrolled loop.
+         */
+        if (s->lookahead <= MAX_MATCH) {
+            fill_window(s);
+            if (s->lookahead <= MAX_MATCH && flush == Z_NO_FLUSH) {
+                return need_more;
+            }
+            if (s->lookahead == 0) break; /* flush the current block */
+        }
+
+        /* See how many times the previous byte repeats */
+        s->match_length = 0;
+        if (s->lookahead >= MIN_MATCH && s->strstart > 0) {
+            scan = s->window + s->strstart - 1;
+            prev = *scan;
+            if (prev == *++scan && prev == *++scan && prev == *++scan) {
+                strend = s->window + s->strstart + MAX_MATCH;
+                do {
+                } while (prev == *++scan && prev == *++scan &&
+                         prev == *++scan && prev == *++scan &&
+                         prev == *++scan && prev == *++scan &&
+                         prev == *++scan && prev == *++scan &&
+                         scan < strend);
+                s->match_length = MAX_MATCH - (uInt)(strend - scan);
+                if (s->match_length > s->lookahead)
+                    s->match_length = s->lookahead;
+            }
+            Assert(scan <= s->window+(uInt)(s->window_size-1), "wild scan");
+        }
+
+        /* Emit match if have run of MIN_MATCH or longer, else emit literal */
+        if (s->match_length >= MIN_MATCH) {
+            check_match(s, s->strstart, s->strstart - 1, s->match_length);
+
+            _tr_tally_dist(s, 1, s->match_length - MIN_MATCH, bflush);
+
+            s->lookahead -= s->match_length;
+            s->strstart += s->match_length;
+            s->match_length = 0;
+        } else {
+            /* No match, output a literal byte */
+            Tracevv((stderr,"%c", s->window[s->strstart]));
+            _tr_tally_lit (s, s->window[s->strstart], bflush);
+            s->lookahead--;
+            s->strstart++;
+        }
+        if (bflush) FLUSH_BLOCK(s, 0);
+    }
+    s->insert = 0;
+    if (flush == Z_FINISH) {
+        FLUSH_BLOCK(s, 1);
+        return finish_done;
+    }
+    if (s->last_lit)
+        FLUSH_BLOCK(s, 0);
+    return block_done;
+}
+
+/* ===========================================================================
+ * For Z_HUFFMAN_ONLY, do not look for matches.  Do not maintain a hash table.
+ * (It will be regenerated if this run of deflate switches away from Huffman.)
+ */
+local block_state deflate_huff(s, flush)
+    deflate_state *s;
+    int flush;
+{
+    int bflush;             /* set if current block must be flushed */
+
+    for (;;) {
+        /* Make sure that we have a literal to write. */
+        if (s->lookahead == 0) {
+            fill_window(s);
+            if (s->lookahead == 0) {
+                if (flush == Z_NO_FLUSH)
+                    return need_more;
+                break;      /* flush the current block */
+            }
+        }
+
+        /* Output a literal byte */
+        s->match_length = 0;
+        Tracevv((stderr,"%c", s->window[s->strstart]));
+        _tr_tally_lit (s, s->window[s->strstart], bflush);
+        s->lookahead--;
+        s->strstart++;
+        if (bflush) FLUSH_BLOCK(s, 0);
+    }
+    s->insert = 0;
+    if (flush == Z_FINISH) {
+        FLUSH_BLOCK(s, 1);
+        return finish_done;
+    }
+    if (s->last_lit)
+        FLUSH_BLOCK(s, 0);
+    return block_done;
+}

ADDED   3rd_party/zlib/deflate.h
Index: 3rd_party/zlib/deflate.h
==================================================================
--- 3rd_party/zlib/deflate.h
+++ 3rd_party/zlib/deflate.h
@@ -0,0 +1,349 @@
+/* deflate.h -- internal compression state
+ * Copyright (C) 1995-2016 Jean-loup Gailly
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* WARNING: this file should *not* be used by applications. It is
+   part of the implementation of the compression library and is
+   subject to change. Applications should only use zlib.h.
+ */
+
+/* @(#) $Id$ */
+
+#ifndef DEFLATE_H
+#define DEFLATE_H
+
+#include "zutil.h"
+
+/* define NO_GZIP when compiling if you want to disable gzip header and
+   trailer creation by deflate().  NO_GZIP would be used to avoid linking in
+   the crc code when it is not needed.  For shared libraries, gzip encoding
+   should be left enabled. */
+#ifndef NO_GZIP
+#  define GZIP
+#endif
+
+/* ===========================================================================
+ * Internal compression state.
+ */
+
+#define LENGTH_CODES 29
+/* number of length codes, not counting the special END_BLOCK code */
+
+#define LITERALS  256
+/* number of literal bytes 0..255 */
+
+#define L_CODES (LITERALS+1+LENGTH_CODES)
+/* number of Literal or Length codes, including the END_BLOCK code */
+
+#define D_CODES   30
+/* number of distance codes */
+
+#define BL_CODES  19
+/* number of codes used to transfer the bit lengths */
+
+#define HEAP_SIZE (2*L_CODES+1)
+/* maximum heap size */
+
+#define MAX_BITS 15
+/* All codes must not exceed MAX_BITS bits */
+
+#define Buf_size 16
+/* size of bit buffer in bi_buf */
+
+#define INIT_STATE    42    /* zlib header -> BUSY_STATE */
+#ifdef GZIP
+#  define GZIP_STATE  57    /* gzip header -> BUSY_STATE | EXTRA_STATE */
+#endif
+#define EXTRA_STATE   69    /* gzip extra block -> NAME_STATE */
+#define NAME_STATE    73    /* gzip file name -> COMMENT_STATE */
+#define COMMENT_STATE 91    /* gzip comment -> HCRC_STATE */
+#define HCRC_STATE   103    /* gzip header CRC -> BUSY_STATE */
+#define BUSY_STATE   113    /* deflate -> FINISH_STATE */
+#define FINISH_STATE 666    /* stream complete */
+/* Stream status */
+
+
+/* Data structure describing a single value and its code string. */
+typedef struct ct_data_s {
+    union {
+        ush  freq;       /* frequency count */
+        ush  code;       /* bit string */
+    } fc;
+    union {
+        ush  dad;        /* father node in Huffman tree */
+        ush  len;        /* length of bit string */
+    } dl;
+} FAR ct_data;
+
+#define Freq fc.freq
+#define Code fc.code
+#define Dad  dl.dad
+#define Len  dl.len
+
+typedef struct static_tree_desc_s  static_tree_desc;
+
+typedef struct tree_desc_s {
+    ct_data *dyn_tree;           /* the dynamic tree */
+    int     max_code;            /* largest code with non zero frequency */
+    const static_tree_desc *stat_desc;  /* the corresponding static tree */
+} FAR tree_desc;
+
+typedef ush Pos;
+typedef Pos FAR Posf;
+typedef unsigned IPos;
+
+/* A Pos is an index in the character window. We use short instead of int to
+ * save space in the various tables. IPos is used only for parameter passing.
+ */
+
+typedef struct internal_state {
+    z_streamp strm;      /* pointer back to this zlib stream */
+    int   status;        /* as the name implies */
+    Bytef *pending_buf;  /* output still pending */
+    ulg   pending_buf_size; /* size of pending_buf */
+    Bytef *pending_out;  /* next pending byte to output to the stream */
+    ulg   pending;       /* nb of bytes in the pending buffer */
+    int   wrap;          /* bit 0 true for zlib, bit 1 true for gzip */
+    gz_headerp  gzhead;  /* gzip header information to write */
+    ulg   gzindex;       /* where in extra, name, or comment */
+    Byte  method;        /* can only be DEFLATED */
+    int   last_flush;    /* value of flush param for previous deflate call */
+
+                /* used by deflate.c: */
+
+    uInt  w_size;        /* LZ77 window size (32K by default) */
+    uInt  w_bits;        /* log2(w_size)  (8..16) */
+    uInt  w_mask;        /* w_size - 1 */
+
+    Bytef *window;
+    /* Sliding window. Input bytes are read into the second half of the window,
+     * and move to the first half later to keep a dictionary of at least wSize
+     * bytes. With this organization, matches are limited to a distance of
+     * wSize-MAX_MATCH bytes, but this ensures that IO is always
+     * performed with a length multiple of the block size. Also, it limits
+     * the window size to 64K, which is quite useful on MSDOS.
+     * To do: use the user input buffer as sliding window.
+     */
+
+    ulg window_size;
+    /* Actual size of window: 2*wSize, except when the user input buffer
+     * is directly used as sliding window.
+     */
+
+    Posf *prev;
+    /* Link to older string with same hash index. To limit the size of this
+     * array to 64K, this link is maintained only for the last 32K strings.
+     * An index in this array is thus a window index modulo 32K.
+     */
+
+    Posf *head; /* Heads of the hash chains or NIL. */
+
+    uInt  ins_h;          /* hash index of string to be inserted */
+    uInt  hash_size;      /* number of elements in hash table */
+    uInt  hash_bits;      /* log2(hash_size) */
+    uInt  hash_mask;      /* hash_size-1 */
+
+    uInt  hash_shift;
+    /* Number of bits by which ins_h must be shifted at each input
+     * step. It must be such that after MIN_MATCH steps, the oldest
+     * byte no longer takes part in the hash key, that is:
+     *   hash_shift * MIN_MATCH >= hash_bits
+     */
+
+    long block_start;
+    /* Window position at the beginning of the current output block. Gets
+     * negative when the window is moved backwards.
+     */
+
+    uInt match_length;           /* length of best match */
+    IPos prev_match;             /* previous match */
+    int match_available;         /* set if previous match exists */
+    uInt strstart;               /* start of string to insert */
+    uInt match_start;            /* start of matching string */
+    uInt lookahead;              /* number of valid bytes ahead in window */
+
+    uInt prev_length;
+    /* Length of the best match at previous step. Matches not greater than this
+     * are discarded. This is used in the lazy match evaluation.
+     */
+
+    uInt max_chain_length;
+    /* To speed up deflation, hash chains are never searched beyond this
+     * length.  A higher limit improves compression ratio but degrades the
+     * speed.
+     */
+
+    uInt max_lazy_match;
+    /* Attempt to find a better match only when the current match is strictly
+     * smaller than this value. This mechanism is used only for compression
+     * levels >= 4.
+     */
+#   define max_insert_length  max_lazy_match
+    /* Insert new strings in the hash table only if the match length is not
+     * greater than this length. This saves time but degrades compression.
+     * max_insert_length is used only for compression levels <= 3.
+     */
+
+    int level;    /* compression level (1..9) */
+    int strategy; /* favor or force Huffman coding*/
+
+    uInt good_match;
+    /* Use a faster search when the previous match is longer than this */
+
+    int nice_match; /* Stop searching when current match exceeds this */
+
+                /* used by trees.c: */
+    /* Didn't use ct_data typedef below to suppress compiler warning */
+    struct ct_data_s dyn_ltree[HEAP_SIZE];   /* literal and length tree */
+    struct ct_data_s dyn_dtree[2*D_CODES+1]; /* distance tree */
+    struct ct_data_s bl_tree[2*BL_CODES+1];  /* Huffman tree for bit lengths */
+
+    struct tree_desc_s l_desc;               /* desc. for literal tree */
+    struct tree_desc_s d_desc;               /* desc. for distance tree */
+    struct tree_desc_s bl_desc;              /* desc. for bit length tree */
+
+    ush bl_count[MAX_BITS+1];
+    /* number of codes at each bit length for an optimal tree */
+
+    int heap[2*L_CODES+1];      /* heap used to build the Huffman trees */
+    int heap_len;               /* number of elements in the heap */
+    int heap_max;               /* element of largest frequency */
+    /* The sons of heap[n] are heap[2*n] and heap[2*n+1]. heap[0] is not used.
+     * The same heap array is used to build all trees.
+     */
+
+    uch depth[2*L_CODES+1];
+    /* Depth of each subtree used as tie breaker for trees of equal frequency
+     */
+
+    uchf *l_buf;          /* buffer for literals or lengths */
+
+    uInt  lit_bufsize;
+    /* Size of match buffer for literals/lengths.  There are 4 reasons for
+     * limiting lit_bufsize to 64K:
+     *   - frequencies can be kept in 16 bit counters
+     *   - if compression is not successful for the first block, all input
+     *     data is still in the window so we can still emit a stored block even
+     *     when input comes from standard input.  (This can also be done for
+     *     all blocks if lit_bufsize is not greater than 32K.)
+     *   - if compression is not successful for a file smaller than 64K, we can
+     *     even emit a stored file instead of a stored block (saving 5 bytes).
+     *     This is applicable only for zip (not gzip or zlib).
+     *   - creating new Huffman trees less frequently may not provide fast
+     *     adaptation to changes in the input data statistics. (Take for
+     *     example a binary file with poorly compressible code followed by
+     *     a highly compressible string table.) Smaller buffer sizes give
+     *     fast adaptation but have of course the overhead of transmitting
+     *     trees more frequently.
+     *   - I can't count above 4
+     */
+
+    uInt last_lit;      /* running index in l_buf */
+
+    ushf *d_buf;
+    /* Buffer for distances. To simplify the code, d_buf and l_buf have
+     * the same number of elements. To use different lengths, an extra flag
+     * array would be necessary.
+     */
+
+    ulg opt_len;        /* bit length of current block with optimal trees */
+    ulg static_len;     /* bit length of current block with static trees */
+    uInt matches;       /* number of string matches in current block */
+    uInt insert;        /* bytes at end of window left to insert */
+
+#ifdef ZLIB_DEBUG
+    ulg compressed_len; /* total bit length of compressed file mod 2^32 */
+    ulg bits_sent;      /* bit length of compressed data sent mod 2^32 */
+#endif
+
+    ush bi_buf;
+    /* Output buffer. bits are inserted starting at the bottom (least
+     * significant bits).
+     */
+    int bi_valid;
+    /* Number of valid bits in bi_buf.  All bits above the last valid bit
+     * are always zero.
+     */
+
+    ulg high_water;
+    /* High water mark offset in window for initialized bytes -- bytes above
+     * this are set to zero in order to avoid memory check warnings when
+     * longest match routines access bytes past the input.  This is then
+     * updated to the new high water mark.
+     */
+
+} FAR deflate_state;
+
+/* Output a byte on the stream.
+ * IN assertion: there is enough room in pending_buf.
+ */
+#define put_byte(s, c) {s->pending_buf[s->pending++] = (Bytef)(c);}
+
+
+#define MIN_LOOKAHEAD (MAX_MATCH+MIN_MATCH+1)
+/* Minimum amount of lookahead, except at the end of the input file.
+ * See deflate.c for comments about the MIN_MATCH+1.
+ */
+
+#define MAX_DIST(s)  ((s)->w_size-MIN_LOOKAHEAD)
+/* In order to simplify the code, particularly on 16 bit machines, match
+ * distances are limited to MAX_DIST instead of WSIZE.
+ */
+
+#define WIN_INIT MAX_MATCH
+/* Number of bytes after end of data in window to initialize in order to avoid
+   memory checker errors from longest match routines */
+
+        /* in trees.c */
+void ZLIB_INTERNAL _tr_init OF((deflate_state *s));
+int ZLIB_INTERNAL _tr_tally OF((deflate_state *s, unsigned dist, unsigned lc));
+void ZLIB_INTERNAL _tr_flush_block OF((deflate_state *s, charf *buf,
+                        ulg stored_len, int last));
+void ZLIB_INTERNAL _tr_flush_bits OF((deflate_state *s));
+void ZLIB_INTERNAL _tr_align OF((deflate_state *s));
+void ZLIB_INTERNAL _tr_stored_block OF((deflate_state *s, charf *buf,
+                        ulg stored_len, int last));
+
+#define d_code(dist) \
+   ((dist) < 256 ? _dist_code[dist] : _dist_code[256+((dist)>>7)])
+/* Mapping from a distance to a distance code. dist is the distance - 1 and
+ * must not have side effects. _dist_code[256] and _dist_code[257] are never
+ * used.
+ */
+
+#ifndef ZLIB_DEBUG
+/* Inline versions of _tr_tally for speed: */
+
+#if defined(GEN_TREES_H) || !defined(STDC)
+  extern uch ZLIB_INTERNAL _length_code[];
+  extern uch ZLIB_INTERNAL _dist_code[];
+#else
+  extern const uch ZLIB_INTERNAL _length_code[];
+  extern const uch ZLIB_INTERNAL _dist_code[];
+#endif
+
+# define _tr_tally_lit(s, c, flush) \
+  { uch cc = (c); \
+    s->d_buf[s->last_lit] = 0; \
+    s->l_buf[s->last_lit++] = cc; \
+    s->dyn_ltree[cc].Freq++; \
+    flush = (s->last_lit == s->lit_bufsize-1); \
+   }
+# define _tr_tally_dist(s, distance, length, flush) \
+  { uch len = (uch)(length); \
+    ush dist = (ush)(distance); \
+    s->d_buf[s->last_lit] = dist; \
+    s->l_buf[s->last_lit++] = len; \
+    dist--; \
+    s->dyn_ltree[_length_code[len]+LITERALS+1].Freq++; \
+    s->dyn_dtree[d_code(dist)].Freq++; \
+    flush = (s->last_lit == s->lit_bufsize-1); \
+  }
+#else
+# define _tr_tally_lit(s, c, flush) flush = _tr_tally(s, 0, c)
+# define _tr_tally_dist(s, distance, length, flush) \
+              flush = _tr_tally(s, distance, length)
+#endif
+
+#endif /* DEFLATE_H */

ADDED   3rd_party/zlib/doc/algorithm.txt
Index: 3rd_party/zlib/doc/algorithm.txt
==================================================================
--- 3rd_party/zlib/doc/algorithm.txt
+++ 3rd_party/zlib/doc/algorithm.txt
@@ -0,0 +1,209 @@
+1. Compression algorithm (deflate)
+
+The deflation algorithm used by gzip (also zip and zlib) is a variation of
+LZ77 (Lempel-Ziv 1977, see reference below). It finds duplicated strings in
+the input data.  The second occurrence of a string is replaced by a
+pointer to the previous string, in the form of a pair (distance,
+length).  Distances are limited to 32K bytes, and lengths are limited
+to 258 bytes. When a string does not occur anywhere in the previous
+32K bytes, it is emitted as a sequence of literal bytes.  (In this
+description, `string' must be taken as an arbitrary sequence of bytes,
+and is not restricted to printable characters.)
+
+Literals or match lengths are compressed with one Huffman tree, and
+match distances are compressed with another tree. The trees are stored
+in a compact form at the start of each block. The blocks can have any
+size (except that the compressed data for one block must fit in
+available memory). A block is terminated when deflate() determines that
+it would be useful to start another block with fresh trees. (This is
+somewhat similar to the behavior of LZW-based _compress_.)
+
+Duplicated strings are found using a hash table. All input strings of
+length 3 are inserted in the hash table. A hash index is computed for
+the next 3 bytes. If the hash chain for this index is not empty, all
+strings in the chain are compared with the current input string, and
+the longest match is selected.
+
+The hash chains are searched starting with the most recent strings, to
+favor small distances and thus take advantage of the Huffman encoding.
+The hash chains are singly linked. There are no deletions from the
+hash chains, the algorithm simply discards matches that are too old.
+
+To avoid a worst-case situation, very long hash chains are arbitrarily
+truncated at a certain length, determined by a runtime option (level
+parameter of deflateInit). So deflate() does not always find the longest
+possible match but generally finds a match which is long enough.
+
+deflate() also defers the selection of matches with a lazy evaluation
+mechanism. After a match of length N has been found, deflate() searches for
+a longer match at the next input byte. If a longer match is found, the
+previous match is truncated to a length of one (thus producing a single
+literal byte) and the process of lazy evaluation begins again. Otherwise,
+the original match is kept, and the next match search is attempted only N
+steps later.
+
+The lazy match evaluation is also subject to a runtime parameter. If
+the current match is long enough, deflate() reduces the search for a longer
+match, thus speeding up the whole process. If compression ratio is more
+important than speed, deflate() attempts a complete second search even if
+the first match is already long enough.
+
+The lazy match evaluation is not performed for the fastest compression
+modes (level parameter 1 to 3). For these fast modes, new strings
+are inserted in the hash table only when no match was found, or
+when the match is not too long. This degrades the compression ratio
+but saves time since there are both fewer insertions and fewer searches.
+
+
+2. Decompression algorithm (inflate)
+
+2.1 Introduction
+
+The key question is how to represent a Huffman code (or any prefix code) so
+that you can decode fast.  The most important characteristic is that shorter
+codes are much more common than longer codes, so pay attention to decoding the
+short codes fast, and let the long codes take longer to decode.
+
+inflate() sets up a first level table that covers some number of bits of
+input less than the length of longest code.  It gets that many bits from the
+stream, and looks it up in the table.  The table will tell if the next
+code is that many bits or less and how many, and if it is, it will tell
+the value, else it will point to the next level table for which inflate()
+grabs more bits and tries to decode a longer code.
+
+How many bits to make the first lookup is a tradeoff between the time it
+takes to decode and the time it takes to build the table.  If building the
+table took no time (and if you had infinite memory), then there would only
+be a first level table to cover all the way to the longest code.  However,
+building the table ends up taking a lot longer for more bits since short
+codes are replicated many times in such a table.  What inflate() does is
+simply to make the number of bits in the first table a variable, and  then
+to set that variable for the maximum speed.
+
+For inflate, which has 286 possible codes for the literal/length tree, the size
+of the first table is nine bits.  Also the distance trees have 30 possible
+values, and the size of the first table is six bits.  Note that for each of
+those cases, the table ended up one bit longer than the ``average'' code
+length, i.e. the code length of an approximately flat code which would be a
+little more than eight bits for 286 symbols and a little less than five bits
+for 30 symbols.
+
+
+2.2 More details on the inflate table lookup
+
+Ok, you want to know what this cleverly obfuscated inflate tree actually
+looks like.  You are correct that it's not a Huffman tree.  It is simply a
+lookup table for the first, let's say, nine bits of a Huffman symbol.  The
+symbol could be as short as one bit or as long as 15 bits.  If a particular
+symbol is shorter than nine bits, then that symbol's translation is duplicated
+in all those entries that start with that symbol's bits.  For example, if the
+symbol is four bits, then it's duplicated 32 times in a nine-bit table.  If a
+symbol is nine bits long, it appears in the table once.
+
+If the symbol is longer than nine bits, then that entry in the table points
+to another similar table for the remaining bits.  Again, there are duplicated
+entries as needed.  The idea is that most of the time the symbol will be short
+and there will only be one table look up.  (That's whole idea behind data
+compression in the first place.)  For the less frequent long symbols, there
+will be two lookups.  If you had a compression method with really long
+symbols, you could have as many levels of lookups as is efficient.  For
+inflate, two is enough.
+
+So a table entry either points to another table (in which case nine bits in
+the above example are gobbled), or it contains the translation for the symbol
+and the number of bits to gobble.  Then you start again with the next
+ungobbled bit.
+
+You may wonder: why not just have one lookup table for how ever many bits the
+longest symbol is?  The reason is that if you do that, you end up spending
+more time filling in duplicate symbol entries than you do actually decoding.
+At least for deflate's output that generates new trees every several 10's of
+kbytes.  You can imagine that filling in a 2^15 entry table for a 15-bit code
+would take too long if you're only decoding several thousand symbols.  At the
+other extreme, you could make a new table for every bit in the code.  In fact,
+that's essentially a Huffman tree.  But then you spend too much time
+traversing the tree while decoding, even for short symbols.
+
+So the number of bits for the first lookup table is a trade of the time to
+fill out the table vs. the time spent looking at the second level and above of
+the table.
+
+Here is an example, scaled down:
+
+The code being decoded, with 10 symbols, from 1 to 6 bits long:
+
+A: 0
+B: 10
+C: 1100
+D: 11010
+E: 11011
+F: 11100
+G: 11101
+H: 11110
+I: 111110
+J: 111111
+
+Let's make the first table three bits long (eight entries):
+
+000: A,1
+001: A,1
+010: A,1
+011: A,1
+100: B,2
+101: B,2
+110: -> table X (gobble 3 bits)
+111: -> table Y (gobble 3 bits)
+
+Each entry is what the bits decode as and how many bits that is, i.e. how
+many bits to gobble.  Or the entry points to another table, with the number of
+bits to gobble implicit in the size of the table.
+
+Table X is two bits long since the longest code starting with 110 is five bits
+long:
+
+00: C,1
+01: C,1
+10: D,2
+11: E,2
+
+Table Y is three bits long since the longest code starting with 111 is six
+bits long:
+
+000: F,2
+001: F,2
+010: G,2
+011: G,2
+100: H,2
+101: H,2
+110: I,3
+111: J,3
+
+So what we have here are three tables with a total of 20 entries that had to
+be constructed.  That's compared to 64 entries for a single table.  Or
+compared to 16 entries for a Huffman tree (six two entry tables and one four
+entry table).  Assuming that the code ideally represents the probability of
+the symbols, it takes on the average 1.25 lookups per symbol.  That's compared
+to one lookup for the single table, or 1.66 lookups per symbol for the
+Huffman tree.
+
+There, I think that gives you a picture of what's going on.  For inflate, the
+meaning of a particular symbol is often more than just a letter.  It can be a
+byte (a "literal"), or it can be either a length or a distance which
+indicates a base value and a number of bits to fetch after the code that is
+added to the base value.  Or it might be the special end-of-block code.  The
+data structures created in inftrees.c try to encode all that information
+compactly in the tables.
+
+
+Jean-loup Gailly        Mark Adler
+jloup@gzip.org          madler@alumni.caltech.edu
+
+
+References:
+
+[LZ77] Ziv J., Lempel A., ``A Universal Algorithm for Sequential Data
+Compression,'' IEEE Transactions on Information Theory, Vol. 23, No. 3,
+pp. 337-343.
+
+``DEFLATE Compressed Data Format Specification'' available in
+http://tools.ietf.org/html/rfc1951

ADDED   3rd_party/zlib/doc/rfc1950.txt
Index: 3rd_party/zlib/doc/rfc1950.txt
==================================================================
--- 3rd_party/zlib/doc/rfc1950.txt
+++ 3rd_party/zlib/doc/rfc1950.txt
@@ -0,0 +1,619 @@
+
+
+
+
+
+
+Network Working Group                                         P. Deutsch
+Request for Comments: 1950                           Aladdin Enterprises
+Category: Informational                                      J-L. Gailly
+                                                                Info-ZIP
+                                                                May 1996
+
+
+         ZLIB Compressed Data Format Specification version 3.3
+
+Status of This Memo
+
+   This memo provides information for the Internet community.  This memo
+   does not specify an Internet standard of any kind.  Distribution of
+   this memo is unlimited.
+
+IESG Note:
+
+   The IESG takes no position on the validity of any Intellectual
+   Property Rights statements contained in this document.
+
+Notices
+
+   Copyright (c) 1996 L. Peter Deutsch and Jean-Loup Gailly
+
+   Permission is granted to copy and distribute this document for any
+   purpose and without charge, including translations into other
+   languages and incorporation into compilations, provided that the
+   copyright notice and this notice are preserved, and that any
+   substantive changes or deletions from the original are clearly
+   marked.
+
+   A pointer to the latest version of this and related documentation in
+   HTML format can be found at the URL
+   <ftp://ftp.uu.net/graphics/png/documents/zlib/zdoc-index.html>.
+
+Abstract
+
+   This specification defines a lossless compressed data format.  The
+   data can be produced or consumed, even for an arbitrarily long
+   sequentially presented input data stream, using only an a priori
+   bounded amount of intermediate storage.  The format presently uses
+   the DEFLATE compression method but can be easily extended to use
+   other compression methods.  It can be implemented readily in a manner
+   not covered by patents.  This specification also defines the ADLER-32
+   checksum (an extension and improvement of the Fletcher checksum),
+   used for detection of data corruption, and provides an algorithm for
+   computing it.
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 1]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+Table of Contents
+
+   1. Introduction ................................................... 2
+      1.1. Purpose ................................................... 2
+      1.2. Intended audience ......................................... 3
+      1.3. Scope ..................................................... 3
+      1.4. Compliance ................................................ 3
+      1.5.  Definitions of terms and conventions used ................ 3
+      1.6. Changes from previous versions ............................ 3
+   2. Detailed specification ......................................... 3
+      2.1. Overall conventions ....................................... 3
+      2.2. Data format ............................................... 4
+      2.3. Compliance ................................................ 7
+   3. References ..................................................... 7
+   4. Source code .................................................... 8
+   5. Security Considerations ........................................ 8
+   6. Acknowledgements ............................................... 8
+   7. Authors' Addresses ............................................. 8
+   8. Appendix: Rationale ............................................ 9
+   9. Appendix: Sample code ..........................................10
+
+1. Introduction
+
+   1.1. Purpose
+
+      The purpose of this specification is to define a lossless
+      compressed data format that:
+
+          * Is independent of CPU type, operating system, file system,
+            and character set, and hence can be used for interchange;
+
+          * Can be produced or consumed, even for an arbitrarily long
+            sequentially presented input data stream, using only an a
+            priori bounded amount of intermediate storage, and hence can
+            be used in data communications or similar structures such as
+            Unix filters;
+
+          * Can use a number of different compression methods;
+
+          * Can be implemented readily in a manner not covered by
+            patents, and hence can be practiced freely.
+
+      The data format defined by this specification does not attempt to
+      allow random access to compressed data.
+
+
+
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 2]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+   1.2. Intended audience
+
+      This specification is intended for use by implementors of software
+      to compress data into zlib format and/or decompress data from zlib
+      format.
+
+      The text of the specification assumes a basic background in
+      programming at the level of bits and other primitive data
+      representations.
+
+   1.3. Scope
+
+      The specification specifies a compressed data format that can be
+      used for in-memory compression of a sequence of arbitrary bytes.
+
+   1.4. Compliance
+
+      Unless otherwise indicated below, a compliant decompressor must be
+      able to accept and decompress any data set that conforms to all
+      the specifications presented here; a compliant compressor must
+      produce data sets that conform to all the specifications presented
+      here.
+
+   1.5.  Definitions of terms and conventions used
+
+      byte: 8 bits stored or transmitted as a unit (same as an octet).
+      (For this specification, a byte is exactly 8 bits, even on
+      machines which store a character on a number of bits different
+      from 8.) See below, for the numbering of bits within a byte.
+
+   1.6. Changes from previous versions
+
+      Version 3.1 was the first public release of this specification.
+      In version 3.2, some terminology was changed and the Adler-32
+      sample code was rewritten for clarity.  In version 3.3, the
+      support for a preset dictionary was introduced, and the
+      specification was converted to RFC style.
+
+2. Detailed specification
+
+   2.1. Overall conventions
+
+      In the diagrams below, a box like this:
+
+         +---+
+         |   | <-- the vertical bars might be missing
+         +---+
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 3]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+      represents one byte; a box like this:
+
+         +==============+
+         |              |
+         +==============+
+
+      represents a variable number of bytes.
+
+      Bytes stored within a computer do not have a "bit order", since
+      they are always treated as a unit.  However, a byte considered as
+      an integer between 0 and 255 does have a most- and least-
+      significant bit, and since we write numbers with the most-
+      significant digit on the left, we also write bytes with the most-
+      significant bit on the left.  In the diagrams below, we number the
+      bits of a byte so that bit 0 is the least-significant bit, i.e.,
+      the bits are numbered:
+
+         +--------+
+         |76543210|
+         +--------+
+
+      Within a computer, a number may occupy multiple bytes.  All
+      multi-byte numbers in the format described here are stored with
+      the MOST-significant byte first (at the lower memory address).
+      For example, the decimal number 520 is stored as:
+
+             0     1
+         +--------+--------+
+         |00000010|00001000|
+         +--------+--------+
+          ^        ^
+          |        |
+          |        + less significant byte = 8
+          + more significant byte = 2 x 256
+
+   2.2. Data format
+
+      A zlib stream has the following structure:
+
+           0   1
+         +---+---+
+         |CMF|FLG|   (more-->)
+         +---+---+
+
+
+
+
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 4]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+      (if FLG.FDICT set)
+
+           0   1   2   3
+         +---+---+---+---+
+         |     DICTID    |   (more-->)
+         +---+---+---+---+
+
+         +=====================+---+---+---+---+
+         |...compressed data...|    ADLER32    |
+         +=====================+---+---+---+---+
+
+      Any data which may appear after ADLER32 are not part of the zlib
+      stream.
+
+      CMF (Compression Method and flags)
+         This byte is divided into a 4-bit compression method and a 4-
+         bit information field depending on the compression method.
+
+            bits 0 to 3  CM     Compression method
+            bits 4 to 7  CINFO  Compression info
+
+      CM (Compression method)
+         This identifies the compression method used in the file. CM = 8
+         denotes the "deflate" compression method with a window size up
+         to 32K.  This is the method used by gzip and PNG (see
+         references [1] and [2] in Chapter 3, below, for the reference
+         documents).  CM = 15 is reserved.  It might be used in a future
+         version of this specification to indicate the presence of an
+         extra field before the compressed data.
+
+      CINFO (Compression info)
+         For CM = 8, CINFO is the base-2 logarithm of the LZ77 window
+         size, minus eight (CINFO=7 indicates a 32K window size). Values
+         of CINFO above 7 are not allowed in this version of the
+         specification.  CINFO is not defined in this specification for
+         CM not equal to 8.
+
+      FLG (FLaGs)
+         This flag byte is divided as follows:
+
+            bits 0 to 4  FCHECK  (check bits for CMF and FLG)
+            bit  5       FDICT   (preset dictionary)
+            bits 6 to 7  FLEVEL  (compression level)
+
+         The FCHECK value must be such that CMF and FLG, when viewed as
+         a 16-bit unsigned integer stored in MSB order (CMF*256 + FLG),
+         is a multiple of 31.
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 5]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+      FDICT (Preset dictionary)
+         If FDICT is set, a DICT dictionary identifier is present
+         immediately after the FLG byte. The dictionary is a sequence of
+         bytes which are initially fed to the compressor without
+         producing any compressed output. DICT is the Adler-32 checksum
+         of this sequence of bytes (see the definition of ADLER32
+         below).  The decompressor can use this identifier to determine
+         which dictionary has been used by the compressor.
+
+      FLEVEL (Compression level)
+         These flags are available for use by specific compression
+         methods.  The "deflate" method (CM = 8) sets these flags as
+         follows:
+
+            0 - compressor used fastest algorithm
+            1 - compressor used fast algorithm
+            2 - compressor used default algorithm
+            3 - compressor used maximum compression, slowest algorithm
+
+         The information in FLEVEL is not needed for decompression; it
+         is there to indicate if recompression might be worthwhile.
+
+      compressed data
+         For compression method 8, the compressed data is stored in the
+         deflate compressed data format as described in the document
+         "DEFLATE Compressed Data Format Specification" by L. Peter
+         Deutsch. (See reference [3] in Chapter 3, below)
+
+         Other compressed data formats are not specified in this version
+         of the zlib specification.
+
+      ADLER32 (Adler-32 checksum)
+         This contains a checksum value of the uncompressed data
+         (excluding any dictionary data) computed according to Adler-32
+         algorithm. This algorithm is a 32-bit extension and improvement
+         of the Fletcher algorithm, used in the ITU-T X.224 / ISO 8073
+         standard. See references [4] and [5] in Chapter 3, below)
+
+         Adler-32 is composed of two sums accumulated per byte: s1 is
+         the sum of all bytes, s2 is the sum of all s1 values. Both sums
+         are done modulo 65521. s1 is initialized to 1, s2 to zero.  The
+         Adler-32 checksum is stored as s2*65536 + s1 in most-
+         significant-byte first (network) order.
+
+
+
+
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 6]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+   2.3. Compliance
+
+      A compliant compressor must produce streams with correct CMF, FLG
+      and ADLER32, but need not support preset dictionaries.  When the
+      zlib data format is used as part of another standard data format,
+      the compressor may use only preset dictionaries that are specified
+      by this other data format.  If this other format does not use the
+      preset dictionary feature, the compressor must not set the FDICT
+      flag.
+
+      A compliant decompressor must check CMF, FLG, and ADLER32, and
+      provide an error indication if any of these have incorrect values.
+      A compliant decompressor must give an error indication if CM is
+      not one of the values defined in this specification (only the
+      value 8 is permitted in this version), since another value could
+      indicate the presence of new features that would cause subsequent
+      data to be interpreted incorrectly.  A compliant decompressor must
+      give an error indication if FDICT is set and DICTID is not the
+      identifier of a known preset dictionary.  A decompressor may
+      ignore FLEVEL and still be compliant.  When the zlib data format
+      is being used as a part of another standard format, a compliant
+      decompressor must support all the preset dictionaries specified by
+      the other format. When the other format does not use the preset
+      dictionary feature, a compliant decompressor must reject any
+      stream in which the FDICT flag is set.
+
+3. References
+
+   [1] Deutsch, L.P.,"GZIP Compressed Data Format Specification",
+       available in ftp://ftp.uu.net/pub/archiving/zip/doc/
+
+   [2] Thomas Boutell, "PNG (Portable Network Graphics) specification",
+       available in ftp://ftp.uu.net/graphics/png/documents/
+
+   [3] Deutsch, L.P.,"DEFLATE Compressed Data Format Specification",
+       available in ftp://ftp.uu.net/pub/archiving/zip/doc/
+
+   [4] Fletcher, J. G., "An Arithmetic Checksum for Serial
+       Transmissions," IEEE Transactions on Communications, Vol. COM-30,
+       No. 1, January 1982, pp. 247-252.
+
+   [5] ITU-T Recommendation X.224, Annex D, "Checksum Algorithms,"
+       November, 1993, pp. 144, 145. (Available from
+       gopher://info.itu.ch). ITU-T X.244 is also the same as ISO 8073.
+
+
+
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 7]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+4. Source code
+
+   Source code for a C language implementation of a "zlib" compliant
+   library is available at ftp://ftp.uu.net/pub/archiving/zip/zlib/.
+
+5. Security Considerations
+
+   A decoder that fails to check the ADLER32 checksum value may be
+   subject to undetected data corruption.
+
+6. Acknowledgements
+
+   Trademarks cited in this document are the property of their
+   respective owners.
+
+   Jean-Loup Gailly and Mark Adler designed the zlib format and wrote
+   the related software described in this specification.  Glenn
+   Randers-Pehrson converted this document to RFC and HTML format.
+
+7. Authors' Addresses
+
+   L. Peter Deutsch
+   Aladdin Enterprises
+   203 Santa Margarita Ave.
+   Menlo Park, CA 94025
+
+   Phone: (415) 322-0103 (AM only)
+   FAX:   (415) 322-1734
+   EMail: <ghost@aladdin.com>
+
+
+   Jean-Loup Gailly
+
+   EMail: <gzip@prep.ai.mit.edu>
+
+   Questions about the technical content of this specification can be
+   sent by email to
+
+   Jean-Loup Gailly <gzip@prep.ai.mit.edu> and
+   Mark Adler <madler@alumni.caltech.edu>
+
+   Editorial comments on this specification can be sent by email to
+
+   L. Peter Deutsch <ghost@aladdin.com> and
+   Glenn Randers-Pehrson <randeg@alumni.rpi.edu>
+
+
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 8]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+8. Appendix: Rationale
+
+   8.1. Preset dictionaries
+
+      A preset dictionary is specially useful to compress short input
+      sequences. The compressor can take advantage of the dictionary
+      context to encode the input in a more compact manner. The
+      decompressor can be initialized with the appropriate context by
+      virtually decompressing a compressed version of the dictionary
+      without producing any output. However for certain compression
+      algorithms such as the deflate algorithm this operation can be
+      achieved without actually performing any decompression.
+
+      The compressor and the decompressor must use exactly the same
+      dictionary. The dictionary may be fixed or may be chosen among a
+      certain number of predefined dictionaries, according to the kind
+      of input data. The decompressor can determine which dictionary has
+      been chosen by the compressor by checking the dictionary
+      identifier. This document does not specify the contents of
+      predefined dictionaries, since the optimal dictionaries are
+      application specific. Standard data formats using this feature of
+      the zlib specification must precisely define the allowed
+      dictionaries.
+
+   8.2. The Adler-32 algorithm
+
+      The Adler-32 algorithm is much faster than the CRC32 algorithm yet
+      still provides an extremely low probability of undetected errors.
+
+      The modulo on unsigned long accumulators can be delayed for 5552
+      bytes, so the modulo operation time is negligible.  If the bytes
+      are a, b, c, the second sum is 3a + 2b + c + 3, and so is position
+      and order sensitive, unlike the first sum, which is just a
+      checksum.  That 65521 is prime is important to avoid a possible
+      large class of two-byte errors that leave the check unchanged.
+      (The Fletcher checksum uses 255, which is not prime and which also
+      makes the Fletcher check insensitive to single byte changes 0 <->
+      255.)
+
+      The sum s1 is initialized to 1 instead of zero to make the length
+      of the sequence part of s2, so that the length does not have to be
+      checked separately. (Any sequence of zeroes has a Fletcher
+      checksum of zero.)
+
+
+
+
+
+
+
+
+Deutsch & Gailly             Informational                      [Page 9]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+9. Appendix: Sample code
+
+   The following C code computes the Adler-32 checksum of a data buffer.
+   It is written for clarity, not for speed.  The sample code is in the
+   ANSI C programming language. Non C users may find it easier to read
+   with these hints:
+
+      &      Bitwise AND operator.
+      >>     Bitwise right shift operator. When applied to an
+             unsigned quantity, as here, right shift inserts zero bit(s)
+             at the left.
+      <<     Bitwise left shift operator. Left shift inserts zero
+             bit(s) at the right.
+      ++     "n++" increments the variable n.
+      %      modulo operator: a % b is the remainder of a divided by b.
+
+      #define BASE 65521 /* largest prime smaller than 65536 */
+
+      /*
+         Update a running Adler-32 checksum with the bytes buf[0..len-1]
+       and return the updated checksum. The Adler-32 checksum should be
+       initialized to 1.
+
+       Usage example:
+
+         unsigned long adler = 1L;
+
+         while (read_buffer(buffer, length) != EOF) {
+           adler = update_adler32(adler, buffer, length);
+         }
+         if (adler != original_adler) error();
+      */
+      unsigned long update_adler32(unsigned long adler,
+         unsigned char *buf, int len)
+      {
+        unsigned long s1 = adler & 0xffff;
+        unsigned long s2 = (adler >> 16) & 0xffff;
+        int n;
+
+        for (n = 0; n < len; n++) {
+          s1 = (s1 + buf[n]) % BASE;
+          s2 = (s2 + s1)     % BASE;
+        }
+        return (s2 << 16) + s1;
+      }
+
+      /* Return the adler32 of the bytes buf[0..len-1] */
+
+
+
+
+Deutsch & Gailly             Informational                     [Page 10]
+
+RFC 1950       ZLIB Compressed Data Format Specification        May 1996
+
+
+      unsigned long adler32(unsigned char *buf, int len)
+      {
+        return update_adler32(1L, buf, len);
+      }
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
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+
+Deutsch & Gailly             Informational                     [Page 11]
+

ADDED   3rd_party/zlib/doc/rfc1951.txt
Index: 3rd_party/zlib/doc/rfc1951.txt
==================================================================
--- 3rd_party/zlib/doc/rfc1951.txt
+++ 3rd_party/zlib/doc/rfc1951.txt
@@ -0,0 +1,955 @@
+
+
+
+
+
+
+Network Working Group                                         P. Deutsch
+Request for Comments: 1951                           Aladdin Enterprises
+Category: Informational                                         May 1996
+
+
+        DEFLATE Compressed Data Format Specification version 1.3
+
+Status of This Memo
+
+   This memo provides information for the Internet community.  This memo
+   does not specify an Internet standard of any kind.  Distribution of
+   this memo is unlimited.
+
+IESG Note:
+
+   The IESG takes no position on the validity of any Intellectual
+   Property Rights statements contained in this document.
+
+Notices
+
+   Copyright (c) 1996 L. Peter Deutsch
+
+   Permission is granted to copy and distribute this document for any
+   purpose and without charge, including translations into other
+   languages and incorporation into compilations, provided that the
+   copyright notice and this notice are preserved, and that any
+   substantive changes or deletions from the original are clearly
+   marked.
+
+   A pointer to the latest version of this and related documentation in
+   HTML format can be found at the URL
+   <ftp://ftp.uu.net/graphics/png/documents/zlib/zdoc-index.html>.
+
+Abstract
+
+   This specification defines a lossless compressed data format that
+   compresses data using a combination of the LZ77 algorithm and Huffman
+   coding, with efficiency comparable to the best currently available
+   general-purpose compression methods.  The data can be produced or
+   consumed, even for an arbitrarily long sequentially presented input
+   data stream, using only an a priori bounded amount of intermediate
+   storage.  The format can be implemented readily in a manner not
+   covered by patents.
+
+
+
+
+
+
+
+
+Deutsch                      Informational                      [Page 1]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+Table of Contents
+
+   1. Introduction ................................................... 2
+      1.1. Purpose ................................................... 2
+      1.2. Intended audience ......................................... 3
+      1.3. Scope ..................................................... 3
+      1.4. Compliance ................................................ 3
+      1.5.  Definitions of terms and conventions used ................ 3
+      1.6. Changes from previous versions ............................ 4
+   2. Compressed representation overview ............................. 4
+   3. Detailed specification ......................................... 5
+      3.1. Overall conventions ....................................... 5
+          3.1.1. Packing into bytes .................................. 5
+      3.2. Compressed block format ................................... 6
+          3.2.1. Synopsis of prefix and Huffman coding ............... 6
+          3.2.2. Use of Huffman coding in the "deflate" format ....... 7
+          3.2.3. Details of block format ............................. 9
+          3.2.4. Non-compressed blocks (BTYPE=00) ................... 11
+          3.2.5. Compressed blocks (length and distance codes) ...... 11
+          3.2.6. Compression with fixed Huffman codes (BTYPE=01) .... 12
+          3.2.7. Compression with dynamic Huffman codes (BTYPE=10) .. 13
+      3.3. Compliance ............................................... 14
+   4. Compression algorithm details ................................. 14
+   5. References .................................................... 16
+   6. Security Considerations ....................................... 16
+   7. Source code ................................................... 16
+   8. Acknowledgements .............................................. 16
+   9. Author's Address .............................................. 17
+
+1. Introduction
+
+   1.1. Purpose
+
+      The purpose of this specification is to define a lossless
+      compressed data format that:
+          * Is independent of CPU type, operating system, file system,
+            and character set, and hence can be used for interchange;
+          * Can be produced or consumed, even for an arbitrarily long
+            sequentially presented input data stream, using only an a
+            priori bounded amount of intermediate storage, and hence
+            can be used in data communications or similar structures
+            such as Unix filters;
+          * Compresses data with efficiency comparable to the best
+            currently available general-purpose compression methods,
+            and in particular considerably better than the "compress"
+            program;
+          * Can be implemented readily in a manner not covered by
+            patents, and hence can be practiced freely;
+
+
+
+Deutsch                      Informational                      [Page 2]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+          * Is compatible with the file format produced by the current
+            widely used gzip utility, in that conforming decompressors
+            will be able to read data produced by the existing gzip
+            compressor.
+
+      The data format defined by this specification does not attempt to:
+
+          * Allow random access to compressed data;
+          * Compress specialized data (e.g., raster graphics) as well
+            as the best currently available specialized algorithms.
+
+      A simple counting argument shows that no lossless compression
+      algorithm can compress every possible input data set.  For the
+      format defined here, the worst case expansion is 5 bytes per 32K-
+      byte block, i.e., a size increase of 0.015% for large data sets.
+      English text usually compresses by a factor of 2.5 to 3;
+      executable files usually compress somewhat less; graphical data
+      such as raster images may compress much more.
+
+   1.2. Intended audience
+
+      This specification is intended for use by implementors of software
+      to compress data into "deflate" format and/or decompress data from
+      "deflate" format.
+
+      The text of the specification assumes a basic background in
+      programming at the level of bits and other primitive data
+      representations.  Familiarity with the technique of Huffman coding
+      is helpful but not required.
+
+   1.3. Scope
+
+      The specification specifies a method for representing a sequence
+      of bytes as a (usually shorter) sequence of bits, and a method for
+      packing the latter bit sequence into bytes.
+
+   1.4. Compliance
+
+      Unless otherwise indicated below, a compliant decompressor must be
+      able to accept and decompress any data set that conforms to all
+      the specifications presented here; a compliant compressor must
+      produce data sets that conform to all the specifications presented
+      here.
+
+   1.5.  Definitions of terms and conventions used
+
+      Byte: 8 bits stored or transmitted as a unit (same as an octet).
+      For this specification, a byte is exactly 8 bits, even on machines
+
+
+
+Deutsch                      Informational                      [Page 3]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+      which store a character on a number of bits different from eight.
+      See below, for the numbering of bits within a byte.
+
+      String: a sequence of arbitrary bytes.
+
+   1.6. Changes from previous versions
+
+      There have been no technical changes to the deflate format since
+      version 1.1 of this specification.  In version 1.2, some
+      terminology was changed.  Version 1.3 is a conversion of the
+      specification to RFC style.
+
+2. Compressed representation overview
+
+   A compressed data set consists of a series of blocks, corresponding
+   to successive blocks of input data.  The block sizes are arbitrary,
+   except that non-compressible blocks are limited to 65,535 bytes.
+
+   Each block is compressed using a combination of the LZ77 algorithm
+   and Huffman coding. The Huffman trees for each block are independent
+   of those for previous or subsequent blocks; the LZ77 algorithm may
+   use a reference to a duplicated string occurring in a previous block,
+   up to 32K input bytes before.
+
+   Each block consists of two parts: a pair of Huffman code trees that
+   describe the representation of the compressed data part, and a
+   compressed data part.  (The Huffman trees themselves are compressed
+   using Huffman encoding.)  The compressed data consists of a series of
+   elements of two types: literal bytes (of strings that have not been
+   detected as duplicated within the previous 32K input bytes), and
+   pointers to duplicated strings, where a pointer is represented as a
+   pair <length, backward distance>.  The representation used in the
+   "deflate" format limits distances to 32K bytes and lengths to 258
+   bytes, but does not limit the size of a block, except for
+   uncompressible blocks, which are limited as noted above.
+
+   Each type of value (literals, distances, and lengths) in the
+   compressed data is represented using a Huffman code, using one code
+   tree for literals and lengths and a separate code tree for distances.
+   The code trees for each block appear in a compact form just before
+   the compressed data for that block.
+
+
+
+
+
+
+
+
+
+
+Deutsch                      Informational                      [Page 4]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+3. Detailed specification
+
+   3.1. Overall conventions In the diagrams below, a box like this:
+
+         +---+
+         |   | <-- the vertical bars might be missing
+         +---+
+
+      represents one byte; a box like this:
+
+         +==============+
+         |              |
+         +==============+
+
+      represents a variable number of bytes.
+
+      Bytes stored within a computer do not have a "bit order", since
+      they are always treated as a unit.  However, a byte considered as
+      an integer between 0 and 255 does have a most- and least-
+      significant bit, and since we write numbers with the most-
+      significant digit on the left, we also write bytes with the most-
+      significant bit on the left.  In the diagrams below, we number the
+      bits of a byte so that bit 0 is the least-significant bit, i.e.,
+      the bits are numbered:
+
+         +--------+
+         |76543210|
+         +--------+
+
+      Within a computer, a number may occupy multiple bytes.  All
+      multi-byte numbers in the format described here are stored with
+      the least-significant byte first (at the lower memory address).
+      For example, the decimal number 520 is stored as:
+
+             0        1
+         +--------+--------+
+         |00001000|00000010|
+         +--------+--------+
+          ^        ^
+          |        |
+          |        + more significant byte = 2 x 256
+          + less significant byte = 8
+
+      3.1.1. Packing into bytes
+
+         This document does not address the issue of the order in which
+         bits of a byte are transmitted on a bit-sequential medium,
+         since the final data format described here is byte- rather than
+
+
+
+Deutsch                      Informational                      [Page 5]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+         bit-oriented.  However, we describe the compressed block format
+         in below, as a sequence of data elements of various bit
+         lengths, not a sequence of bytes.  We must therefore specify
+         how to pack these data elements into bytes to form the final
+         compressed byte sequence:
+
+             * Data elements are packed into bytes in order of
+               increasing bit number within the byte, i.e., starting
+               with the least-significant bit of the byte.
+             * Data elements other than Huffman codes are packed
+               starting with the least-significant bit of the data
+               element.
+             * Huffman codes are packed starting with the most-
+               significant bit of the code.
+
+         In other words, if one were to print out the compressed data as
+         a sequence of bytes, starting with the first byte at the
+         *right* margin and proceeding to the *left*, with the most-
+         significant bit of each byte on the left as usual, one would be
+         able to parse the result from right to left, with fixed-width
+         elements in the correct MSB-to-LSB order and Huffman codes in
+         bit-reversed order (i.e., with the first bit of the code in the
+         relative LSB position).
+
+   3.2. Compressed block format
+
+      3.2.1. Synopsis of prefix and Huffman coding
+
+         Prefix coding represents symbols from an a priori known
+         alphabet by bit sequences (codes), one code for each symbol, in
+         a manner such that different symbols may be represented by bit
+         sequences of different lengths, but a parser can always parse
+         an encoded string unambiguously symbol-by-symbol.
+
+         We define a prefix code in terms of a binary tree in which the
+         two edges descending from each non-leaf node are labeled 0 and
+         1 and in which the leaf nodes correspond one-for-one with (are
+         labeled with) the symbols of the alphabet; then the code for a
+         symbol is the sequence of 0's and 1's on the edges leading from
+         the root to the leaf labeled with that symbol.  For example:
+
+
+
+
+
+
+
+
+
+
+
+Deutsch                      Informational                      [Page 6]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+                          /\              Symbol    Code
+                         0  1             ------    ----
+                        /    \                A      00
+                       /\     B               B       1
+                      0  1                    C     011
+                     /    \                   D     010
+                    A     /\
+                         0  1
+                        /    \
+                       D      C
+
+         A parser can decode the next symbol from an encoded input
+         stream by walking down the tree from the root, at each step
+         choosing the edge corresponding to the next input bit.
+
+         Given an alphabet with known symbol frequencies, the Huffman
+         algorithm allows the construction of an optimal prefix code
+         (one which represents strings with those symbol frequencies
+         using the fewest bits of any possible prefix codes for that
+         alphabet).  Such a code is called a Huffman code.  (See
+         reference [1] in Chapter 5, references for additional
+         information on Huffman codes.)
+
+         Note that in the "deflate" format, the Huffman codes for the
+         various alphabets must not exceed certain maximum code lengths.
+         This constraint complicates the algorithm for computing code
+         lengths from symbol frequencies.  Again, see Chapter 5,
+         references for details.
+
+      3.2.2. Use of Huffman coding in the "deflate" format
+
+         The Huffman codes used for each alphabet in the "deflate"
+         format have two additional rules:
+
+             * All codes of a given bit length have lexicographically
+               consecutive values, in the same order as the symbols
+               they represent;
+
+             * Shorter codes lexicographically precede longer codes.
+
+
+
+
+
+
+
+
+
+
+
+
+Deutsch                      Informational                      [Page 7]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+         We could recode the example above to follow this rule as
+         follows, assuming that the order of the alphabet is ABCD:
+
+            Symbol  Code
+            ------  ----
+            A       10
+            B       0
+            C       110
+            D       111
+
+         I.e., 0 precedes 10 which precedes 11x, and 110 and 111 are
+         lexicographically consecutive.
+
+         Given this rule, we can define the Huffman code for an alphabet
+         just by giving the bit lengths of the codes for each symbol of
+         the alphabet in order; this is sufficient to determine the
+         actual codes.  In our example, the code is completely defined
+         by the sequence of bit lengths (2, 1, 3, 3).  The following
+         algorithm generates the codes as integers, intended to be read
+         from most- to least-significant bit.  The code lengths are
+         initially in tree[I].Len; the codes are produced in
+         tree[I].Code.
+
+         1)  Count the number of codes for each code length.  Let
+             bl_count[N] be the number of codes of length N, N >= 1.
+
+         2)  Find the numerical value of the smallest code for each
+             code length:
+
+                code = 0;
+                bl_count[0] = 0;
+                for (bits = 1; bits <= MAX_BITS; bits++) {
+                    code = (code + bl_count[bits-1]) << 1;
+                    next_code[bits] = code;
+                }
+
+         3)  Assign numerical values to all codes, using consecutive
+             values for all codes of the same length with the base
+             values determined at step 2. Codes that are never used
+             (which have a bit length of zero) must not be assigned a
+             value.
+
+                for (n = 0;  n <= max_code; n++) {
+                    len = tree[n].Len;
+                    if (len != 0) {
+                        tree[n].Code = next_code[len];
+                        next_code[len]++;
+                    }
+
+
+
+Deutsch                      Informational                      [Page 8]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+                }
+
+         Example:
+
+         Consider the alphabet ABCDEFGH, with bit lengths (3, 3, 3, 3,
+         3, 2, 4, 4).  After step 1, we have:
+
+            N      bl_count[N]
+            -      -----------
+            2      1
+            3      5
+            4      2
+
+         Step 2 computes the following next_code values:
+
+            N      next_code[N]
+            -      ------------
+            1      0
+            2      0
+            3      2
+            4      14
+
+         Step 3 produces the following code values:
+
+            Symbol Length   Code
+            ------ ------   ----
+            A       3        010
+            B       3        011
+            C       3        100
+            D       3        101
+            E       3        110
+            F       2         00
+            G       4       1110
+            H       4       1111
+
+      3.2.3. Details of block format
+
+         Each block of compressed data begins with 3 header bits
+         containing the following data:
+
+            first bit       BFINAL
+            next 2 bits     BTYPE
+
+         Note that the header bits do not necessarily begin on a byte
+         boundary, since a block does not necessarily occupy an integral
+         number of bytes.
+
+
+
+
+
+Deutsch                      Informational                      [Page 9]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+         BFINAL is set if and only if this is the last block of the data
+         set.
+
+         BTYPE specifies how the data are compressed, as follows:
+
+            00 - no compression
+            01 - compressed with fixed Huffman codes
+            10 - compressed with dynamic Huffman codes
+            11 - reserved (error)
+
+         The only difference between the two compressed cases is how the
+         Huffman codes for the literal/length and distance alphabets are
+         defined.
+
+         In all cases, the decoding algorithm for the actual data is as
+         follows:
+
+            do
+               read block header from input stream.
+               if stored with no compression
+                  skip any remaining bits in current partially
+                     processed byte
+                  read LEN and NLEN (see next section)
+                  copy LEN bytes of data to output
+               otherwise
+                  if compressed with dynamic Huffman codes
+                     read representation of code trees (see
+                        subsection below)
+                  loop (until end of block code recognized)
+                     decode literal/length value from input stream
+                     if value < 256
+                        copy value (literal byte) to output stream
+                     otherwise
+                        if value = end of block (256)
+                           break from loop
+                        otherwise (value = 257..285)
+                           decode distance from input stream
+
+                           move backwards distance bytes in the output
+                           stream, and copy length bytes from this
+                           position to the output stream.
+                  end loop
+            while not last block
+
+         Note that a duplicated string reference may refer to a string
+         in a previous block; i.e., the backward distance may cross one
+         or more block boundaries.  However a distance cannot refer past
+         the beginning of the output stream.  (An application using a
+
+
+
+Deutsch                      Informational                     [Page 10]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+         preset dictionary might discard part of the output stream; a
+         distance can refer to that part of the output stream anyway)
+         Note also that the referenced string may overlap the current
+         position; for example, if the last 2 bytes decoded have values
+         X and Y, a string reference with <length = 5, distance = 2>
+         adds X,Y,X,Y,X to the output stream.
+
+         We now specify each compression method in turn.
+
+      3.2.4. Non-compressed blocks (BTYPE=00)
+
+         Any bits of input up to the next byte boundary are ignored.
+         The rest of the block consists of the following information:
+
+              0   1   2   3   4...
+            +---+---+---+---+================================+
+            |  LEN  | NLEN  |... LEN bytes of literal data...|
+            +---+---+---+---+================================+
+
+         LEN is the number of data bytes in the block.  NLEN is the
+         one's complement of LEN.
+
+      3.2.5. Compressed blocks (length and distance codes)
+
+         As noted above, encoded data blocks in the "deflate" format
+         consist of sequences of symbols drawn from three conceptually
+         distinct alphabets: either literal bytes, from the alphabet of
+         byte values (0..255), or <length, backward distance> pairs,
+         where the length is drawn from (3..258) and the distance is
+         drawn from (1..32,768).  In fact, the literal and length
+         alphabets are merged into a single alphabet (0..285), where
+         values 0..255 represent literal bytes, the value 256 indicates
+         end-of-block, and values 257..285 represent length codes
+         (possibly in conjunction with extra bits following the symbol
+         code) as follows:
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+Deutsch                      Informational                     [Page 11]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+                 Extra               Extra               Extra
+            Code Bits Length(s) Code Bits Lengths   Code Bits Length(s)
+            ---- ---- ------     ---- ---- -------   ---- ---- -------
+             257   0     3       267   1   15,16     277   4   67-82
+             258   0     4       268   1   17,18     278   4   83-98
+             259   0     5       269   2   19-22     279   4   99-114
+             260   0     6       270   2   23-26     280   4  115-130
+             261   0     7       271   2   27-30     281   5  131-162
+             262   0     8       272   2   31-34     282   5  163-194
+             263   0     9       273   3   35-42     283   5  195-226
+             264   0    10       274   3   43-50     284   5  227-257
+             265   1  11,12      275   3   51-58     285   0    258
+             266   1  13,14      276   3   59-66
+
+         The extra bits should be interpreted as a machine integer
+         stored with the most-significant bit first, e.g., bits 1110
+         represent the value 14.
+
+                  Extra           Extra               Extra
+             Code Bits Dist  Code Bits   Dist     Code Bits Distance
+             ---- ---- ----  ---- ----  ------    ---- ---- --------
+               0   0    1     10   4     33-48    20    9   1025-1536
+               1   0    2     11   4     49-64    21    9   1537-2048
+               2   0    3     12   5     65-96    22   10   2049-3072
+               3   0    4     13   5     97-128   23   10   3073-4096
+               4   1   5,6    14   6    129-192   24   11   4097-6144
+               5   1   7,8    15   6    193-256   25   11   6145-8192
+               6   2   9-12   16   7    257-384   26   12  8193-12288
+               7   2  13-16   17   7    385-512   27   12 12289-16384
+               8   3  17-24   18   8    513-768   28   13 16385-24576
+               9   3  25-32   19   8   769-1024   29   13 24577-32768
+
+      3.2.6. Compression with fixed Huffman codes (BTYPE=01)
+
+         The Huffman codes for the two alphabets are fixed, and are not
+         represented explicitly in the data.  The Huffman code lengths
+         for the literal/length alphabet are:
+
+                   Lit Value    Bits        Codes
+                   ---------    ----        -----
+                     0 - 143     8          00110000 through
+                                            10111111
+                   144 - 255     9          110010000 through
+                                            111111111
+                   256 - 279     7          0000000 through
+                                            0010111
+                   280 - 287     8          11000000 through
+                                            11000111
+
+
+
+Deutsch                      Informational                     [Page 12]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+         The code lengths are sufficient to generate the actual codes,
+         as described above; we show the codes in the table for added
+         clarity.  Literal/length values 286-287 will never actually
+         occur in the compressed data, but participate in the code
+         construction.
+
+         Distance codes 0-31 are represented by (fixed-length) 5-bit
+         codes, with possible additional bits as shown in the table
+         shown in Paragraph 3.2.5, above.  Note that distance codes 30-
+         31 will never actually occur in the compressed data.
+
+      3.2.7. Compression with dynamic Huffman codes (BTYPE=10)
+
+         The Huffman codes for the two alphabets appear in the block
+         immediately after the header bits and before the actual
+         compressed data, first the literal/length code and then the
+         distance code.  Each code is defined by a sequence of code
+         lengths, as discussed in Paragraph 3.2.2, above.  For even
+         greater compactness, the code length sequences themselves are
+         compressed using a Huffman code.  The alphabet for code lengths
+         is as follows:
+
+               0 - 15: Represent code lengths of 0 - 15
+                   16: Copy the previous code length 3 - 6 times.
+                       The next 2 bits indicate repeat length
+                             (0 = 3, ... , 3 = 6)
+                          Example:  Codes 8, 16 (+2 bits 11),
+                                    16 (+2 bits 10) will expand to
+                                    12 code lengths of 8 (1 + 6 + 5)
+                   17: Repeat a code length of 0 for 3 - 10 times.
+                       (3 bits of length)
+                   18: Repeat a code length of 0 for 11 - 138 times
+                       (7 bits of length)
+
+         A code length of 0 indicates that the corresponding symbol in
+         the literal/length or distance alphabet will not occur in the
+         block, and should not participate in the Huffman code
+         construction algorithm given earlier.  If only one distance
+         code is used, it is encoded using one bit, not zero bits; in
+         this case there is a single code length of one, with one unused
+         code.  One distance code of zero bits means that there are no
+         distance codes used at all (the data is all literals).
+
+         We can now define the format of the block:
+
+               5 Bits: HLIT, # of Literal/Length codes - 257 (257 - 286)
+               5 Bits: HDIST, # of Distance codes - 1        (1 - 32)
+               4 Bits: HCLEN, # of Code Length codes - 4     (4 - 19)
+
+
+
+Deutsch                      Informational                     [Page 13]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+               (HCLEN + 4) x 3 bits: code lengths for the code length
+                  alphabet given just above, in the order: 16, 17, 18,
+                  0, 8, 7, 9, 6, 10, 5, 11, 4, 12, 3, 13, 2, 14, 1, 15
+
+                  These code lengths are interpreted as 3-bit integers
+                  (0-7); as above, a code length of 0 means the
+                  corresponding symbol (literal/length or distance code
+                  length) is not used.
+
+               HLIT + 257 code lengths for the literal/length alphabet,
+                  encoded using the code length Huffman code
+
+               HDIST + 1 code lengths for the distance alphabet,
+                  encoded using the code length Huffman code
+
+               The actual compressed data of the block,
+                  encoded using the literal/length and distance Huffman
+                  codes
+
+               The literal/length symbol 256 (end of data),
+                  encoded using the literal/length Huffman code
+
+         The code length repeat codes can cross from HLIT + 257 to the
+         HDIST + 1 code lengths.  In other words, all code lengths form
+         a single sequence of HLIT + HDIST + 258 values.
+
+   3.3. Compliance
+
+      A compressor may limit further the ranges of values specified in
+      the previous section and still be compliant; for example, it may
+      limit the range of backward pointers to some value smaller than
+      32K.  Similarly, a compressor may limit the size of blocks so that
+      a compressible block fits in memory.
+
+      A compliant decompressor must accept the full range of possible
+      values defined in the previous section, and must accept blocks of
+      arbitrary size.
+
+4. Compression algorithm details
+
+   While it is the intent of this document to define the "deflate"
+   compressed data format without reference to any particular
+   compression algorithm, the format is related to the compressed
+   formats produced by LZ77 (Lempel-Ziv 1977, see reference [2] below);
+   since many variations of LZ77 are patented, it is strongly
+   recommended that the implementor of a compressor follow the general
+   algorithm presented here, which is known not to be patented per se.
+   The material in this section is not part of the definition of the
+
+
+
+Deutsch                      Informational                     [Page 14]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+   specification per se, and a compressor need not follow it in order to
+   be compliant.
+
+   The compressor terminates a block when it determines that starting a
+   new block with fresh trees would be useful, or when the block size
+   fills up the compressor's block buffer.
+
+   The compressor uses a chained hash table to find duplicated strings,
+   using a hash function that operates on 3-byte sequences.  At any
+   given point during compression, let XYZ be the next 3 input bytes to
+   be examined (not necessarily all different, of course).  First, the
+   compressor examines the hash chain for XYZ.  If the chain is empty,
+   the compressor simply writes out X as a literal byte and advances one
+   byte in the input.  If the hash chain is not empty, indicating that
+   the sequence XYZ (or, if we are unlucky, some other 3 bytes with the
+   same hash function value) has occurred recently, the compressor
+   compares all strings on the XYZ hash chain with the actual input data
+   sequence starting at the current point, and selects the longest
+   match.
+
+   The compressor searches the hash chains starting with the most recent
+   strings, to favor small distances and thus take advantage of the
+   Huffman encoding.  The hash chains are singly linked. There are no
+   deletions from the hash chains; the algorithm simply discards matches
+   that are too old.  To avoid a worst-case situation, very long hash
+   chains are arbitrarily truncated at a certain length, determined by a
+   run-time parameter.
+
+   To improve overall compression, the compressor optionally defers the
+   selection of matches ("lazy matching"): after a match of length N has
+   been found, the compressor searches for a longer match starting at
+   the next input byte.  If it finds a longer match, it truncates the
+   previous match to a length of one (thus producing a single literal
+   byte) and then emits the longer match.  Otherwise, it emits the
+   original match, and, as described above, advances N bytes before
+   continuing.
+
+   Run-time parameters also control this "lazy match" procedure.  If
+   compression ratio is most important, the compressor attempts a
+   complete second search regardless of the length of the first match.
+   In the normal case, if the current match is "long enough", the
+   compressor reduces the search for a longer match, thus speeding up
+   the process.  If speed is most important, the compressor inserts new
+   strings in the hash table only when no match was found, or when the
+   match is not "too long".  This degrades the compression ratio but
+   saves time since there are both fewer insertions and fewer searches.
+
+
+
+
+
+Deutsch                      Informational                     [Page 15]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+5. References
+
+   [1] Huffman, D. A., "A Method for the Construction of Minimum
+       Redundancy Codes", Proceedings of the Institute of Radio
+       Engineers, September 1952, Volume 40, Number 9, pp. 1098-1101.
+
+   [2] Ziv J., Lempel A., "A Universal Algorithm for Sequential Data
+       Compression", IEEE Transactions on Information Theory, Vol. 23,
+       No. 3, pp. 337-343.
+
+   [3] Gailly, J.-L., and Adler, M., ZLIB documentation and sources,
+       available in ftp://ftp.uu.net/pub/archiving/zip/doc/
+
+   [4] Gailly, J.-L., and Adler, M., GZIP documentation and sources,
+       available as gzip-*.tar in ftp://prep.ai.mit.edu/pub/gnu/
+
+   [5] Schwartz, E. S., and Kallick, B. "Generating a canonical prefix
+       encoding." Comm. ACM, 7,3 (Mar. 1964), pp. 166-169.
+
+   [6] Hirschberg and Lelewer, "Efficient decoding of prefix codes,"
+       Comm. ACM, 33,4, April 1990, pp. 449-459.
+
+6. Security Considerations
+
+   Any data compression method involves the reduction of redundancy in
+   the data.  Consequently, any corruption of the data is likely to have
+   severe effects and be difficult to correct.  Uncompressed text, on
+   the other hand, will probably still be readable despite the presence
+   of some corrupted bytes.
+
+   It is recommended that systems using this data format provide some
+   means of validating the integrity of the compressed data.  See
+   reference [3], for example.
+
+7. Source code
+
+   Source code for a C language implementation of a "deflate" compliant
+   compressor and decompressor is available within the zlib package at
+   ftp://ftp.uu.net/pub/archiving/zip/zlib/.
+
+8. Acknowledgements
+
+   Trademarks cited in this document are the property of their
+   respective owners.
+
+   Phil Katz designed the deflate format.  Jean-Loup Gailly and Mark
+   Adler wrote the related software described in this specification.
+   Glenn Randers-Pehrson converted this document to RFC and HTML format.
+
+
+
+Deutsch                      Informational                     [Page 16]
+
+RFC 1951      DEFLATE Compressed Data Format Specification      May 1996
+
+
+9. Author's Address
+
+   L. Peter Deutsch
+   Aladdin Enterprises
+   203 Santa Margarita Ave.
+   Menlo Park, CA 94025
+
+   Phone: (415) 322-0103 (AM only)
+   FAX:   (415) 322-1734
+   EMail: <ghost@aladdin.com>
+
+   Questions about the technical content of this specification can be
+   sent by email to:
+
+   Jean-Loup Gailly <gzip@prep.ai.mit.edu> and
+   Mark Adler <madler@alumni.caltech.edu>
+
+   Editorial comments on this specification can be sent by email to:
+
+   L. Peter Deutsch <ghost@aladdin.com> and
+   Glenn Randers-Pehrson <randeg@alumni.rpi.edu>
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+Deutsch                      Informational                     [Page 17]
+

ADDED   3rd_party/zlib/doc/rfc1952.txt
Index: 3rd_party/zlib/doc/rfc1952.txt
==================================================================
--- 3rd_party/zlib/doc/rfc1952.txt
+++ 3rd_party/zlib/doc/rfc1952.txt
@@ -0,0 +1,675 @@
+
+
+
+
+
+
+Network Working Group                                         P. Deutsch
+Request for Comments: 1952                           Aladdin Enterprises
+Category: Informational                                         May 1996
+
+
+               GZIP file format specification version 4.3
+
+Status of This Memo
+
+   This memo provides information for the Internet community.  This memo
+   does not specify an Internet standard of any kind.  Distribution of
+   this memo is unlimited.
+
+IESG Note:
+
+   The IESG takes no position on the validity of any Intellectual
+   Property Rights statements contained in this document.
+
+Notices
+
+   Copyright (c) 1996 L. Peter Deutsch
+
+   Permission is granted to copy and distribute this document for any
+   purpose and without charge, including translations into other
+   languages and incorporation into compilations, provided that the
+   copyright notice and this notice are preserved, and that any
+   substantive changes or deletions from the original are clearly
+   marked.
+
+   A pointer to the latest version of this and related documentation in
+   HTML format can be found at the URL
+   <ftp://ftp.uu.net/graphics/png/documents/zlib/zdoc-index.html>.
+
+Abstract
+
+   This specification defines a lossless compressed data format that is
+   compatible with the widely used GZIP utility.  The format includes a
+   cyclic redundancy check value for detecting data corruption.  The
+   format presently uses the DEFLATE method of compression but can be
+   easily extended to use other compression methods.  The format can be
+   implemented readily in a manner not covered by patents.
+
+
+
+
+
+
+
+
+
+
+Deutsch                      Informational                      [Page 1]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+Table of Contents
+
+   1. Introduction ................................................... 2
+      1.1. Purpose ................................................... 2
+      1.2. Intended audience ......................................... 3
+      1.3. Scope ..................................................... 3
+      1.4. Compliance ................................................ 3
+      1.5. Definitions of terms and conventions used ................. 3
+      1.6. Changes from previous versions ............................ 3
+   2. Detailed specification ......................................... 4
+      2.1. Overall conventions ....................................... 4
+      2.2. File format ............................................... 5
+      2.3. Member format ............................................. 5
+          2.3.1. Member header and trailer ........................... 6
+              2.3.1.1. Extra field ................................... 8
+              2.3.1.2. Compliance .................................... 9
+      3. References .................................................. 9
+      4. Security Considerations .................................... 10
+      5. Acknowledgements ........................................... 10
+      6. Author's Address ........................................... 10
+      7. Appendix: Jean-Loup Gailly's gzip utility .................. 11
+      8. Appendix: Sample CRC Code .................................. 11
+
+1. Introduction
+
+   1.1. Purpose
+
+      The purpose of this specification is to define a lossless
+      compressed data format that:
+
+          * Is independent of CPU type, operating system, file system,
+            and character set, and hence can be used for interchange;
+          * Can compress or decompress a data stream (as opposed to a
+            randomly accessible file) to produce another data stream,
+            using only an a priori bounded amount of intermediate
+            storage, and hence can be used in data communications or
+            similar structures such as Unix filters;
+          * Compresses data with efficiency comparable to the best
+            currently available general-purpose compression methods,
+            and in particular considerably better than the "compress"
+            program;
+          * Can be implemented readily in a manner not covered by
+            patents, and hence can be practiced freely;
+          * Is compatible with the file format produced by the current
+            widely used gzip utility, in that conforming decompressors
+            will be able to read data produced by the existing gzip
+            compressor.
+
+
+
+
+Deutsch                      Informational                      [Page 2]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+      The data format defined by this specification does not attempt to:
+
+          * Provide random access to compressed data;
+          * Compress specialized data (e.g., raster graphics) as well as
+            the best currently available specialized algorithms.
+
+   1.2. Intended audience
+
+      This specification is intended for use by implementors of software
+      to compress data into gzip format and/or decompress data from gzip
+      format.
+
+      The text of the specification assumes a basic background in
+      programming at the level of bits and other primitive data
+      representations.
+
+   1.3. Scope
+
+      The specification specifies a compression method and a file format
+      (the latter assuming only that a file can store a sequence of
+      arbitrary bytes).  It does not specify any particular interface to
+      a file system or anything about character sets or encodings
+      (except for file names and comments, which are optional).
+
+   1.4. Compliance
+
+      Unless otherwise indicated below, a compliant decompressor must be
+      able to accept and decompress any file that conforms to all the
+      specifications presented here; a compliant compressor must produce
+      files that conform to all the specifications presented here.  The
+      material in the appendices is not part of the specification per se
+      and is not relevant to compliance.
+
+   1.5. Definitions of terms and conventions used
+
+      byte: 8 bits stored or transmitted as a unit (same as an octet).
+      (For this specification, a byte is exactly 8 bits, even on
+      machines which store a character on a number of bits different
+      from 8.)  See below for the numbering of bits within a byte.
+
+   1.6. Changes from previous versions
+
+      There have been no technical changes to the gzip format since
+      version 4.1 of this specification.  In version 4.2, some
+      terminology was changed, and the sample CRC code was rewritten for
+      clarity and to eliminate the requirement for the caller to do pre-
+      and post-conditioning.  Version 4.3 is a conversion of the
+      specification to RFC style.
+
+
+
+Deutsch                      Informational                      [Page 3]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+2. Detailed specification
+
+   2.1. Overall conventions
+
+      In the diagrams below, a box like this:
+
+         +---+
+         |   | <-- the vertical bars might be missing
+         +---+
+
+      represents one byte; a box like this:
+
+         +==============+
+         |              |
+         +==============+
+
+      represents a variable number of bytes.
+
+      Bytes stored within a computer do not have a "bit order", since
+      they are always treated as a unit.  However, a byte considered as
+      an integer between 0 and 255 does have a most- and least-
+      significant bit, and since we write numbers with the most-
+      significant digit on the left, we also write bytes with the most-
+      significant bit on the left.  In the diagrams below, we number the
+      bits of a byte so that bit 0 is the least-significant bit, i.e.,
+      the bits are numbered:
+
+         +--------+
+         |76543210|
+         +--------+
+
+      This document does not address the issue of the order in which
+      bits of a byte are transmitted on a bit-sequential medium, since
+      the data format described here is byte- rather than bit-oriented.
+
+      Within a computer, a number may occupy multiple bytes.  All
+      multi-byte numbers in the format described here are stored with
+      the least-significant byte first (at the lower memory address).
+      For example, the decimal number 520 is stored as:
+
+             0        1
+         +--------+--------+
+         |00001000|00000010|
+         +--------+--------+
+          ^        ^
+          |        |
+          |        + more significant byte = 2 x 256
+          + less significant byte = 8
+
+
+
+Deutsch                      Informational                      [Page 4]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+   2.2. File format
+
+      A gzip file consists of a series of "members" (compressed data
+      sets).  The format of each member is specified in the following
+      section.  The members simply appear one after another in the file,
+      with no additional information before, between, or after them.
+
+   2.3. Member format
+
+      Each member has the following structure:
+
+         +---+---+---+---+---+---+---+---+---+---+
+         |ID1|ID2|CM |FLG|     MTIME     |XFL|OS | (more-->)
+         +---+---+---+---+---+---+---+---+---+---+
+
+      (if FLG.FEXTRA set)
+
+         +---+---+=================================+
+         | XLEN  |...XLEN bytes of "extra field"...| (more-->)
+         +---+---+=================================+
+
+      (if FLG.FNAME set)
+
+         +=========================================+
+         |...original file name, zero-terminated...| (more-->)
+         +=========================================+
+
+      (if FLG.FCOMMENT set)
+
+         +===================================+
+         |...file comment, zero-terminated...| (more-->)
+         +===================================+
+
+      (if FLG.FHCRC set)
+
+         +---+---+
+         | CRC16 |
+         +---+---+
+
+         +=======================+
+         |...compressed blocks...| (more-->)
+         +=======================+
+
+           0   1   2   3   4   5   6   7
+         +---+---+---+---+---+---+---+---+
+         |     CRC32     |     ISIZE     |
+         +---+---+---+---+---+---+---+---+
+
+
+
+
+Deutsch                      Informational                      [Page 5]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+      2.3.1. Member header and trailer
+
+         ID1 (IDentification 1)
+         ID2 (IDentification 2)
+            These have the fixed values ID1 = 31 (0x1f, \037), ID2 = 139
+            (0x8b, \213), to identify the file as being in gzip format.
+
+         CM (Compression Method)
+            This identifies the compression method used in the file.  CM
+            = 0-7 are reserved.  CM = 8 denotes the "deflate"
+            compression method, which is the one customarily used by
+            gzip and which is documented elsewhere.
+
+         FLG (FLaGs)
+            This flag byte is divided into individual bits as follows:
+
+               bit 0   FTEXT
+               bit 1   FHCRC
+               bit 2   FEXTRA
+               bit 3   FNAME
+               bit 4   FCOMMENT
+               bit 5   reserved
+               bit 6   reserved
+               bit 7   reserved
+
+            If FTEXT is set, the file is probably ASCII text.  This is
+            an optional indication, which the compressor may set by
+            checking a small amount of the input data to see whether any
+            non-ASCII characters are present.  In case of doubt, FTEXT
+            is cleared, indicating binary data. For systems which have
+            different file formats for ascii text and binary data, the
+            decompressor can use FTEXT to choose the appropriate format.
+            We deliberately do not specify the algorithm used to set
+            this bit, since a compressor always has the option of
+            leaving it cleared and a decompressor always has the option
+            of ignoring it and letting some other program handle issues
+            of data conversion.
+
+            If FHCRC is set, a CRC16 for the gzip header is present,
+            immediately before the compressed data. The CRC16 consists
+            of the two least significant bytes of the CRC32 for all
+            bytes of the gzip header up to and not including the CRC16.
+            [The FHCRC bit was never set by versions of gzip up to
+            1.2.4, even though it was documented with a different
+            meaning in gzip 1.2.4.]
+
+            If FEXTRA is set, optional extra fields are present, as
+            described in a following section.
+
+
+
+Deutsch                      Informational                      [Page 6]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+            If FNAME is set, an original file name is present,
+            terminated by a zero byte.  The name must consist of ISO
+            8859-1 (LATIN-1) characters; on operating systems using
+            EBCDIC or any other character set for file names, the name
+            must be translated to the ISO LATIN-1 character set.  This
+            is the original name of the file being compressed, with any
+            directory components removed, and, if the file being
+            compressed is on a file system with case insensitive names,
+            forced to lower case. There is no original file name if the
+            data was compressed from a source other than a named file;
+            for example, if the source was stdin on a Unix system, there
+            is no file name.
+
+            If FCOMMENT is set, a zero-terminated file comment is
+            present.  This comment is not interpreted; it is only
+            intended for human consumption.  The comment must consist of
+            ISO 8859-1 (LATIN-1) characters.  Line breaks should be
+            denoted by a single line feed character (10 decimal).
+
+            Reserved FLG bits must be zero.
+
+         MTIME (Modification TIME)
+            This gives the most recent modification time of the original
+            file being compressed.  The time is in Unix format, i.e.,
+            seconds since 00:00:00 GMT, Jan.  1, 1970.  (Note that this
+            may cause problems for MS-DOS and other systems that use
+            local rather than Universal time.)  If the compressed data
+            did not come from a file, MTIME is set to the time at which
+            compression started.  MTIME = 0 means no time stamp is
+            available.
+
+         XFL (eXtra FLags)
+            These flags are available for use by specific compression
+            methods.  The "deflate" method (CM = 8) sets these flags as
+            follows:
+
+               XFL = 2 - compressor used maximum compression,
+                         slowest algorithm
+               XFL = 4 - compressor used fastest algorithm
+
+         OS (Operating System)
+            This identifies the type of file system on which compression
+            took place.  This may be useful in determining end-of-line
+            convention for text files.  The currently defined values are
+            as follows:
+
+
+
+
+
+
+Deutsch                      Informational                      [Page 7]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+                 0 - FAT filesystem (MS-DOS, OS/2, NT/Win32)
+                 1 - Amiga
+                 2 - VMS (or OpenVMS)
+                 3 - Unix
+                 4 - VM/CMS
+                 5 - Atari TOS
+                 6 - HPFS filesystem (OS/2, NT)
+                 7 - Macintosh
+                 8 - Z-System
+                 9 - CP/M
+                10 - TOPS-20
+                11 - NTFS filesystem (NT)
+                12 - QDOS
+                13 - Acorn RISCOS
+               255 - unknown
+
+         XLEN (eXtra LENgth)
+            If FLG.FEXTRA is set, this gives the length of the optional
+            extra field.  See below for details.
+
+         CRC32 (CRC-32)
+            This contains a Cyclic Redundancy Check value of the
+            uncompressed data computed according to CRC-32 algorithm
+            used in the ISO 3309 standard and in section 8.1.1.6.2 of
+            ITU-T recommendation V.42.  (See http://www.iso.ch for
+            ordering ISO documents. See gopher://info.itu.ch for an
+            online version of ITU-T V.42.)
+
+         ISIZE (Input SIZE)
+            This contains the size of the original (uncompressed) input
+            data modulo 2^32.
+
+      2.3.1.1. Extra field
+
+         If the FLG.FEXTRA bit is set, an "extra field" is present in
+         the header, with total length XLEN bytes.  It consists of a
+         series of subfields, each of the form:
+
+            +---+---+---+---+==================================+
+            |SI1|SI2|  LEN  |... LEN bytes of subfield data ...|
+            +---+---+---+---+==================================+
+
+         SI1 and SI2 provide a subfield ID, typically two ASCII letters
+         with some mnemonic value.  Jean-Loup Gailly
+         <gzip@prep.ai.mit.edu> is maintaining a registry of subfield
+         IDs; please send him any subfield ID you wish to use.  Subfield
+         IDs with SI2 = 0 are reserved for future use.  The following
+         IDs are currently defined:
+
+
+
+Deutsch                      Informational                      [Page 8]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+            SI1         SI2         Data
+            ----------  ----------  ----
+            0x41 ('A')  0x70 ('P')  Apollo file type information
+
+         LEN gives the length of the subfield data, excluding the 4
+         initial bytes.
+
+      2.3.1.2. Compliance
+
+         A compliant compressor must produce files with correct ID1,
+         ID2, CM, CRC32, and ISIZE, but may set all the other fields in
+         the fixed-length part of the header to default values (255 for
+         OS, 0 for all others).  The compressor must set all reserved
+         bits to zero.
+
+         A compliant decompressor must check ID1, ID2, and CM, and
+         provide an error indication if any of these have incorrect
+         values.  It must examine FEXTRA/XLEN, FNAME, FCOMMENT and FHCRC
+         at least so it can skip over the optional fields if they are
+         present.  It need not examine any other part of the header or
+         trailer; in particular, a decompressor may ignore FTEXT and OS
+         and always produce binary output, and still be compliant.  A
+         compliant decompressor must give an error indication if any
+         reserved bit is non-zero, since such a bit could indicate the
+         presence of a new field that would cause subsequent data to be
+         interpreted incorrectly.
+
+3. References
+
+   [1] "Information Processing - 8-bit single-byte coded graphic
+       character sets - Part 1: Latin alphabet No.1" (ISO 8859-1:1987).
+       The ISO 8859-1 (Latin-1) character set is a superset of 7-bit
+       ASCII. Files defining this character set are available as
+       iso_8859-1.* in ftp://ftp.uu.net/graphics/png/documents/
+
+   [2] ISO 3309
+
+   [3] ITU-T recommendation V.42
+
+   [4] Deutsch, L.P.,"DEFLATE Compressed Data Format Specification",
+       available in ftp://ftp.uu.net/pub/archiving/zip/doc/
+
+   [5] Gailly, J.-L., GZIP documentation, available as gzip-*.tar in
+       ftp://prep.ai.mit.edu/pub/gnu/
+
+   [6] Sarwate, D.V., "Computation of Cyclic Redundancy Checks via Table
+       Look-Up", Communications of the ACM, 31(8), pp.1008-1013.
+
+
+
+
+Deutsch                      Informational                      [Page 9]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+   [7] Schwaderer, W.D., "CRC Calculation", April 85 PC Tech Journal,
+       pp.118-133.
+
+   [8] ftp://ftp.adelaide.edu.au/pub/rocksoft/papers/crc_v3.txt,
+       describing the CRC concept.
+
+4. Security Considerations
+
+   Any data compression method involves the reduction of redundancy in
+   the data.  Consequently, any corruption of the data is likely to have
+   severe effects and be difficult to correct.  Uncompressed text, on
+   the other hand, will probably still be readable despite the presence
+   of some corrupted bytes.
+
+   It is recommended that systems using this data format provide some
+   means of validating the integrity of the compressed data, such as by
+   setting and checking the CRC-32 check value.
+
+5. Acknowledgements
+
+   Trademarks cited in this document are the property of their
+   respective owners.
+
+   Jean-Loup Gailly designed the gzip format and wrote, with Mark Adler,
+   the related software described in this specification.  Glenn
+   Randers-Pehrson converted this document to RFC and HTML format.
+
+6. Author's Address
+
+   L. Peter Deutsch
+   Aladdin Enterprises
+   203 Santa Margarita Ave.
+   Menlo Park, CA 94025
+
+   Phone: (415) 322-0103 (AM only)
+   FAX:   (415) 322-1734
+   EMail: <ghost@aladdin.com>
+
+   Questions about the technical content of this specification can be
+   sent by email to:
+
+   Jean-Loup Gailly <gzip@prep.ai.mit.edu> and
+   Mark Adler <madler@alumni.caltech.edu>
+
+   Editorial comments on this specification can be sent by email to:
+
+   L. Peter Deutsch <ghost@aladdin.com> and
+   Glenn Randers-Pehrson <randeg@alumni.rpi.edu>
+
+
+
+Deutsch                      Informational                     [Page 10]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+7. Appendix: Jean-Loup Gailly's gzip utility
+
+   The most widely used implementation of gzip compression, and the
+   original documentation on which this specification is based, were
+   created by Jean-Loup Gailly <gzip@prep.ai.mit.edu>.  Since this
+   implementation is a de facto standard, we mention some more of its
+   features here.  Again, the material in this section is not part of
+   the specification per se, and implementations need not follow it to
+   be compliant.
+
+   When compressing or decompressing a file, gzip preserves the
+   protection, ownership, and modification time attributes on the local
+   file system, since there is no provision for representing protection
+   attributes in the gzip file format itself.  Since the file format
+   includes a modification time, the gzip decompressor provides a
+   command line switch that assigns the modification time from the file,
+   rather than the local modification time of the compressed input, to
+   the decompressed output.
+
+8. Appendix: Sample CRC Code
+
+   The following sample code represents a practical implementation of
+   the CRC (Cyclic Redundancy Check). (See also ISO 3309 and ITU-T V.42
+   for a formal specification.)
+
+   The sample code is in the ANSI C programming language. Non C users
+   may find it easier to read with these hints:
+
+      &      Bitwise AND operator.
+      ^      Bitwise exclusive-OR operator.
+      >>     Bitwise right shift operator. When applied to an
+             unsigned quantity, as here, right shift inserts zero
+             bit(s) at the left.
+      !      Logical NOT operator.
+      ++     "n++" increments the variable n.
+      0xNNN  0x introduces a hexadecimal (base 16) constant.
+             Suffix L indicates a long value (at least 32 bits).
+
+      /* Table of CRCs of all 8-bit messages. */
+      unsigned long crc_table[256];
+
+      /* Flag: has the table been computed? Initially false. */
+      int crc_table_computed = 0;
+
+      /* Make the table for a fast CRC. */
+      void make_crc_table(void)
+      {
+        unsigned long c;
+
+
+
+Deutsch                      Informational                     [Page 11]
+
+RFC 1952             GZIP File Format Specification             May 1996
+
+
+        int n, k;
+        for (n = 0; n < 256; n++) {
+          c = (unsigned long) n;
+          for (k = 0; k < 8; k++) {
+            if (c & 1) {
+              c = 0xedb88320L ^ (c >> 1);
+            } else {
+              c = c >> 1;
+            }
+          }
+          crc_table[n] = c;
+        }
+        crc_table_computed = 1;
+      }
+
+      /*
+         Update a running crc with the bytes buf[0..len-1] and return
+       the updated crc. The crc should be initialized to zero. Pre- and
+       post-conditioning (one's complement) is performed within this
+       function so it shouldn't be done by the caller. Usage example:
+
+         unsigned long crc = 0L;
+
+         while (read_buffer(buffer, length) != EOF) {
+           crc = update_crc(crc, buffer, length);
+         }
+         if (crc != original_crc) error();
+      */
+      unsigned long update_crc(unsigned long crc,
+                      unsigned char *buf, int len)
+      {
+        unsigned long c = crc ^ 0xffffffffL;
+        int n;
+
+        if (!crc_table_computed)
+          make_crc_table();
+        for (n = 0; n < len; n++) {
+          c = crc_table[(c ^ buf[n]) & 0xff] ^ (c >> 8);
+        }
+        return c ^ 0xffffffffL;
+      }
+
+      /* Return the CRC of the bytes buf[0..len-1]. */
+      unsigned long crc(unsigned char *buf, int len)
+      {
+        return update_crc(0L, buf, len);
+      }
+
+
+
+
+Deutsch                      Informational                     [Page 12]
+

ADDED   3rd_party/zlib/doc/txtvsbin.txt
Index: 3rd_party/zlib/doc/txtvsbin.txt
==================================================================
--- 3rd_party/zlib/doc/txtvsbin.txt
+++ 3rd_party/zlib/doc/txtvsbin.txt
@@ -0,0 +1,107 @@
+A Fast Method for Identifying Plain Text Files
+==============================================
+
+
+Introduction
+------------
+
+Given a file coming from an unknown source, it is sometimes desirable
+to find out whether the format of that file is plain text.  Although
+this may appear like a simple task, a fully accurate detection of the
+file type requires heavy-duty semantic analysis on the file contents.
+It is, however, possible to obtain satisfactory results by employing
+various heuristics.
+
+Previous versions of PKZip and other zip-compatible compression tools
+were using a crude detection scheme: if more than 80% (4/5) of the bytes
+found in a certain buffer are within the range [7..127], the file is
+labeled as plain text, otherwise it is labeled as binary.  A prominent
+limitation of this scheme is the restriction to Latin-based alphabets.
+Other alphabets, like Greek, Cyrillic or Asian, make extensive use of
+the bytes within the range [128..255], and texts using these alphabets
+are most often misidentified by this scheme; in other words, the rate
+of false negatives is sometimes too high, which means that the recall
+is low.  Another weakness of this scheme is a reduced precision, due to
+the false positives that may occur when binary files containing large
+amounts of textual characters are misidentified as plain text.
+
+In this article we propose a new, simple detection scheme that features
+a much increased precision and a near-100% recall.  This scheme is
+designed to work on ASCII, Unicode and other ASCII-derived alphabets,
+and it handles single-byte encodings (ISO-8859, MacRoman, KOI8, etc.)
+and variable-sized encodings (ISO-2022, UTF-8, etc.).  Wider encodings
+(UCS-2/UTF-16 and UCS-4/UTF-32) are not handled, however.
+
+
+The Algorithm
+-------------
+
+The algorithm works by dividing the set of bytecodes [0..255] into three
+categories:
+- The white list of textual bytecodes:
+  9 (TAB), 10 (LF), 13 (CR), 32 (SPACE) to 255.
+- The gray list of tolerated bytecodes:
+  7 (BEL), 8 (BS), 11 (VT), 12 (FF), 26 (SUB), 27 (ESC).
+- The black list of undesired, non-textual bytecodes:
+  0 (NUL) to 6, 14 to 31.
+
+If a file contains at least one byte that belongs to the white list and
+no byte that belongs to the black list, then the file is categorized as
+plain text; otherwise, it is categorized as binary.  (The boundary case,
+when the file is empty, automatically falls into the latter category.)
+
+
+Rationale
+---------
+
+The idea behind this algorithm relies on two observations.
+
+The first observation is that, although the full range of 7-bit codes
+[0..127] is properly specified by the ASCII standard, most control
+characters in the range [0..31] are not used in practice.  The only
+widely-used, almost universally-portable control codes are 9 (TAB),
+10 (LF) and 13 (CR).  There are a few more control codes that are
+recognized on a reduced range of platforms and text viewers/editors:
+7 (BEL), 8 (BS), 11 (VT), 12 (FF), 26 (SUB) and 27 (ESC); but these
+codes are rarely (if ever) used alone, without being accompanied by
+some printable text.  Even the newer, portable text formats such as
+XML avoid using control characters outside the list mentioned here.
+
+The second observation is that most of the binary files tend to contain
+control characters, especially 0 (NUL).  Even though the older text
+detection schemes observe the presence of non-ASCII codes from the range
+[128..255], the precision rarely has to suffer if this upper range is
+labeled as textual, because the files that are genuinely binary tend to
+contain both control characters and codes from the upper range.  On the
+other hand, the upper range needs to be labeled as textual, because it
+is used by virtually all ASCII extensions.  In particular, this range is
+used for encoding non-Latin scripts.
+
+Since there is no counting involved, other than simply observing the
+presence or the absence of some byte values, the algorithm produces
+consistent results, regardless what alphabet encoding is being used.
+(If counting were involved, it could be possible to obtain different
+results on a text encoded, say, using ISO-8859-16 versus UTF-8.)
+
+There is an extra category of plain text files that are "polluted" with
+one or more black-listed codes, either by mistake or by peculiar design
+considerations.  In such cases, a scheme that tolerates a small fraction
+of black-listed codes would provide an increased recall (i.e. more true
+positives).  This, however, incurs a reduced precision overall, since
+false positives are more likely to appear in binary files that contain
+large chunks of textual data.  Furthermore, "polluted" plain text should
+be regarded as binary by general-purpose text detection schemes, because
+general-purpose text processing algorithms might not be applicable.
+Under this premise, it is safe to say that our detection method provides
+a near-100% recall.
+
+Experiments have been run on many files coming from various platforms
+and applications.  We tried plain text files, system logs, source code,
+formatted office documents, compiled object code, etc.  The results
+confirm the optimistic assumptions about the capabilities of this
+algorithm.
+
+
+--
+Cosmin Truta
+Last updated: 2006-May-28

ADDED   3rd_party/zlib/examples/README.examples
Index: 3rd_party/zlib/examples/README.examples
==================================================================
--- 3rd_party/zlib/examples/README.examples
+++ 3rd_party/zlib/examples/README.examples
@@ -0,0 +1,49 @@
+This directory contains examples of the use of zlib and other relevant
+programs and documentation.
+
+enough.c
+    calculation and justification of ENOUGH parameter in inftrees.h
+    - calculates the maximum table space used in inflate tree
+      construction over all possible Huffman codes
+
+fitblk.c
+    compress just enough input to nearly fill a requested output size
+    - zlib isn't designed to do this, but fitblk does it anyway
+
+gun.c
+    uncompress a gzip file
+    - illustrates the use of inflateBack() for high speed file-to-file
+      decompression using call-back functions
+    - is approximately twice as fast as gzip -d
+    - also provides Unix uncompress functionality, again twice as fast
+
+gzappend.c
+    append to a gzip file
+    - illustrates the use of the Z_BLOCK flush parameter for inflate()
+    - illustrates the use of deflatePrime() to start at any bit
+
+gzjoin.c
+    join gzip files without recalculating the crc or recompressing
+    - illustrates the use of the Z_BLOCK flush parameter for inflate()
+    - illustrates the use of crc32_combine()
+
+gzlog.c
+gzlog.h
+    efficiently and robustly maintain a message log file in gzip format
+    - illustrates use of raw deflate, Z_PARTIAL_FLUSH, deflatePrime(),
+      and deflateSetDictionary()
+    - illustrates use of a gzip header extra field
+
+zlib_how.html
+    painfully comprehensive description of zpipe.c (see below)
+    - describes in excruciating detail the use of deflate() and inflate()
+
+zpipe.c
+    reads and writes zlib streams from stdin to stdout
+    - illustrates the proper use of deflate() and inflate()
+    - deeply commented in zlib_how.html (see above)
+
+zran.c
+    index a zlib or gzip stream and randomly access it
+    - illustrates the use of Z_BLOCK, inflatePrime(), and
+      inflateSetDictionary() to provide random access

ADDED   3rd_party/zlib/examples/enough.c
Index: 3rd_party/zlib/examples/enough.c
==================================================================
--- 3rd_party/zlib/examples/enough.c
+++ 3rd_party/zlib/examples/enough.c
@@ -0,0 +1,572 @@
+/* enough.c -- determine the maximum size of inflate's Huffman code tables over
+ * all possible valid and complete Huffman codes, subject to a length limit.
+ * Copyright (C) 2007, 2008, 2012 Mark Adler
+ * Version 1.4  18 August 2012  Mark Adler
+ */
+
+/* Version history:
+   1.0   3 Jan 2007  First version (derived from codecount.c version 1.4)
+   1.1   4 Jan 2007  Use faster incremental table usage computation
+                     Prune examine() search on previously visited states
+   1.2   5 Jan 2007  Comments clean up
+                     As inflate does, decrease root for short codes
+                     Refuse cases where inflate would increase root
+   1.3  17 Feb 2008  Add argument for initial root table size
+                     Fix bug for initial root table size == max - 1
+                     Use a macro to compute the history index
+   1.4  18 Aug 2012  Avoid shifts more than bits in type (caused endless loop!)
+                     Clean up comparisons of different types
+                     Clean up code indentation
+ */
+
+/*
+   Examine all possible Huffman codes for a given number of symbols and a
+   maximum code length in bits to determine the maximum table size for zilb's
+   inflate.  Only complete Huffman codes are counted.
+
+   Two codes are considered distinct if the vectors of the number of codes per
+   length are not identical.  So permutations of the symbol assignments result
+   in the same code for the counting, as do permutations of the assignments of
+   the bit values to the codes (i.e. only canonical codes are counted).
+
+   We build a code from shorter to longer lengths, determining how many symbols
+   are coded at each length.  At each step, we have how many symbols remain to
+   be coded, what the last code length used was, and how many bit patterns of
+   that length remain unused. Then we add one to the code length and double the
+   number of unused patterns to graduate to the next code length.  We then
+   assign all portions of the remaining symbols to that code length that
+   preserve the properties of a correct and eventually complete code.  Those
+   properties are: we cannot use more bit patterns than are available; and when
+   all the symbols are used, there are exactly zero possible bit patterns
+   remaining.
+
+   The inflate Huffman decoding algorithm uses two-level lookup tables for
+   speed.  There is a single first-level table to decode codes up to root bits
+   in length (root == 9 in the current inflate implementation).  The table
+   has 1 << root entries and is indexed by the next root bits of input.  Codes
+   shorter than root bits have replicated table entries, so that the correct
+   entry is pointed to regardless of the bits that follow the short code.  If
+   the code is longer than root bits, then the table entry points to a second-
+   level table.  The size of that table is determined by the longest code with
+   that root-bit prefix.  If that longest code has length len, then the table
+   has size 1 << (len - root), to index the remaining bits in that set of
+   codes.  Each subsequent root-bit prefix then has its own sub-table.  The
+   total number of table entries required by the code is calculated
+   incrementally as the number of codes at each bit length is populated.  When
+   all of the codes are shorter than root bits, then root is reduced to the
+   longest code length, resulting in a single, smaller, one-level table.
+
+   The inflate algorithm also provides for small values of root (relative to
+   the log2 of the number of symbols), where the shortest code has more bits
+   than root.  In that case, root is increased to the length of the shortest
+   code.  This program, by design, does not handle that case, so it is verified
+   that the number of symbols is less than 2^(root + 1).
+
+   In order to speed up the examination (by about ten orders of magnitude for
+   the default arguments), the intermediate states in the build-up of a code
+   are remembered and previously visited branches are pruned.  The memory
+   required for this will increase rapidly with the total number of symbols and
+   the maximum code length in bits.  However this is a very small price to pay
+   for the vast speedup.
+
+   First, all of the possible Huffman codes are counted, and reachable
+   intermediate states are noted by a non-zero count in a saved-results array.
+   Second, the intermediate states that lead to (root + 1) bit or longer codes
+   are used to look at all sub-codes from those junctures for their inflate
+   memory usage.  (The amount of memory used is not affected by the number of
+   codes of root bits or less in length.)  Third, the visited states in the
+   construction of those sub-codes and the associated calculation of the table
+   size is recalled in order to avoid recalculating from the same juncture.
+   Beginning the code examination at (root + 1) bit codes, which is enabled by
+   identifying the reachable nodes, accounts for about six of the orders of
+   magnitude of improvement for the default arguments.  About another four
+   orders of magnitude come from not revisiting previous states.  Out of
+   approximately 2x10^16 possible Huffman codes, only about 2x10^6 sub-codes
+   need to be examined to cover all of the possible table memory usage cases
+   for the default arguments of 286 symbols limited to 15-bit codes.
+
+   Note that an unsigned long long type is used for counting.  It is quite easy
+   to exceed the capacity of an eight-byte integer with a large number of
+   symbols and a large maximum code length, so multiple-precision arithmetic
+   would need to replace the unsigned long long arithmetic in that case.  This
+   program will abort if an overflow occurs.  The big_t type identifies where
+   the counting takes place.
+
+   An unsigned long long type is also used for calculating the number of
+   possible codes remaining at the maximum length.  This limits the maximum
+   code length to the number of bits in a long long minus the number of bits
+   needed to represent the symbols in a flat code.  The code_t type identifies
+   where the bit pattern counting takes place.
+ */
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <assert.h>
+
+#define local static
+
+/* special data types */
+typedef unsigned long long big_t;   /* type for code counting */
+typedef unsigned long long code_t;  /* type for bit pattern counting */
+struct tab {                        /* type for been here check */
+    size_t len;         /* length of bit vector in char's */
+    char *vec;          /* allocated bit vector */
+};
+
+/* The array for saving results, num[], is indexed with this triplet:
+
+      syms: number of symbols remaining to code
+      left: number of available bit patterns at length len
+      len: number of bits in the codes currently being assigned
+
+   Those indices are constrained thusly when saving results:
+
+      syms: 3..totsym (totsym == total symbols to code)
+      left: 2..syms - 1, but only the evens (so syms == 8 -> 2, 4, 6)
+      len: 1..max - 1 (max == maximum code length in bits)
+
+   syms == 2 is not saved since that immediately leads to a single code.  left
+   must be even, since it represents the number of available bit patterns at
+   the current length, which is double the number at the previous length.
+   left ends at syms-1 since left == syms immediately results in a single code.
+   (left > sym is not allowed since that would result in an incomplete code.)
+   len is less than max, since the code completes immediately when len == max.
+
+   The offset into the array is calculated for the three indices with the
+   first one (syms) being outermost, and the last one (len) being innermost.
+   We build the array with length max-1 lists for the len index, with syms-3
+   of those for each symbol.  There are totsym-2 of those, with each one
+   varying in length as a function of sym.  See the calculation of index in
+   count() for the index, and the calculation of size in main() for the size
+   of the array.
+
+   For the deflate example of 286 symbols limited to 15-bit codes, the array
+   has 284,284 entries, taking up 2.17 MB for an 8-byte big_t.  More than
+   half of the space allocated for saved results is actually used -- not all
+   possible triplets are reached in the generation of valid Huffman codes.
+ */
+
+/* The array for tracking visited states, done[], is itself indexed identically
+   to the num[] array as described above for the (syms, left, len) triplet.
+   Each element in the array is further indexed by the (mem, rem) doublet,
+   where mem is the amount of inflate table space used so far, and rem is the
+   remaining unused entries in the current inflate sub-table.  Each indexed
+   element is simply one bit indicating whether the state has been visited or
+   not.  Since the ranges for mem and rem are not known a priori, each bit
+   vector is of a variable size, and grows as needed to accommodate the visited
+   states.  mem and rem are used to calculate a single index in a triangular
+   array.  Since the range of mem is expected in the default case to be about
+   ten times larger than the range of rem, the array is skewed to reduce the
+   memory usage, with eight times the range for mem than for rem.  See the
+   calculations for offset and bit in beenhere() for the details.
+
+   For the deflate example of 286 symbols limited to 15-bit codes, the bit
+   vectors grow to total approximately 21 MB, in addition to the 4.3 MB done[]
+   array itself.
+ */
+
+/* Globals to avoid propagating constants or constant pointers recursively */
+local int max;          /* maximum allowed bit length for the codes */
+local int root;         /* size of base code table in bits */
+local int large;        /* largest code table so far */
+local size_t size;      /* number of elements in num and done */
+local int *code;        /* number of symbols assigned to each bit length */
+local big_t *num;       /* saved results array for code counting */
+local struct tab *done; /* states already evaluated array */
+
+/* Index function for num[] and done[] */
+#define INDEX(i,j,k) (((size_t)((i-1)>>1)*((i-2)>>1)+(j>>1)-1)*(max-1)+k-1)
+
+/* Free allocated space.  Uses globals code, num, and done. */
+local void cleanup(void)
+{
+    size_t n;
+
+    if (done != NULL) {
+        for (n = 0; n < size; n++)
+            if (done[n].len)
+                free(done[n].vec);
+        free(done);
+    }
+    if (num != NULL)
+        free(num);
+    if (code != NULL)
+        free(code);
+}
+
+/* Return the number of possible Huffman codes using bit patterns of lengths
+   len through max inclusive, coding syms symbols, with left bit patterns of
+   length len unused -- return -1 if there is an overflow in the counting.
+   Keep a record of previous results in num to prevent repeating the same
+   calculation.  Uses the globals max and num. */
+local big_t count(int syms, int len, int left)
+{
+    big_t sum;          /* number of possible codes from this juncture */
+    big_t got;          /* value returned from count() */
+    int least;          /* least number of syms to use at this juncture */
+    int most;           /* most number of syms to use at this juncture */
+    int use;            /* number of bit patterns to use in next call */
+    size_t index;       /* index of this case in *num */
+
+    /* see if only one possible code */
+    if (syms == left)
+        return 1;
+
+    /* note and verify the expected state */
+    assert(syms > left && left > 0 && len < max);
+
+    /* see if we've done this one already */
+    index = INDEX(syms, left, len);
+    got = num[index];
+    if (got)
+        return got;         /* we have -- return the saved result */
+
+    /* we need to use at least this many bit patterns so that the code won't be
+       incomplete at the next length (more bit patterns than symbols) */
+    least = (left << 1) - syms;
+    if (least < 0)
+        least = 0;
+
+    /* we can use at most this many bit patterns, lest there not be enough
+       available for the remaining symbols at the maximum length (if there were
+       no limit to the code length, this would become: most = left - 1) */
+    most = (((code_t)left << (max - len)) - syms) /
+            (((code_t)1 << (max - len)) - 1);
+
+    /* count all possible codes from this juncture and add them up */
+    sum = 0;
+    for (use = least; use <= most; use++) {
+        got = count(syms - use, len + 1, (left - use) << 1);
+        sum += got;
+        if (got == (big_t)0 - 1 || sum < got)   /* overflow */
+            return (big_t)0 - 1;
+    }
+
+    /* verify that all recursive calls are productive */
+    assert(sum != 0);
+
+    /* save the result and return it */
+    num[index] = sum;
+    return sum;
+}
+
+/* Return true if we've been here before, set to true if not.  Set a bit in a
+   bit vector to indicate visiting this state.  Each (syms,len,left) state
+   has a variable size bit vector indexed by (mem,rem).  The bit vector is
+   lengthened if needed to allow setting the (mem,rem) bit. */
+local int beenhere(int syms, int len, int left, int mem, int rem)
+{
+    size_t index;       /* index for this state's bit vector */
+    size_t offset;      /* offset in this state's bit vector */
+    int bit;            /* mask for this state's bit */
+    size_t length;      /* length of the bit vector in bytes */
+    char *vector;       /* new or enlarged bit vector */
+
+    /* point to vector for (syms,left,len), bit in vector for (mem,rem) */
+    index = INDEX(syms, left, len);
+    mem -= 1 << root;
+    offset = (mem >> 3) + rem;
+    offset = ((offset * (offset + 1)) >> 1) + rem;
+    bit = 1 << (mem & 7);
+
+    /* see if we've been here */
+    length = done[index].len;
+    if (offset < length && (done[index].vec[offset] & bit) != 0)
+        return 1;       /* done this! */
+
+    /* we haven't been here before -- set the bit to show we have now */
+
+    /* see if we need to lengthen the vector in order to set the bit */
+    if (length <= offset) {
+        /* if we have one already, enlarge it, zero out the appended space */
+        if (length) {
+            do {
+                length <<= 1;
+            } while (length <= offset);
+            vector = realloc(done[index].vec, length);
+            if (vector != NULL)
+                memset(vector + done[index].len, 0, length - done[index].len);
+        }
+
+        /* otherwise we need to make a new vector and zero it out */
+        else {
+            length = 1 << (len - root);
+            while (length <= offset)
+                length <<= 1;
+            vector = calloc(length, sizeof(char));
+        }
+
+        /* in either case, bail if we can't get the memory */
+        if (vector == NULL) {
+            fputs("abort: unable to allocate enough memory\n", stderr);
+            cleanup();
+            exit(1);
+        }
+
+        /* install the new vector */
+        done[index].len = length;
+        done[index].vec = vector;
+    }
+
+    /* set the bit */
+    done[index].vec[offset] |= bit;
+    return 0;
+}
+
+/* Examine all possible codes from the given node (syms, len, left).  Compute
+   the amount of memory required to build inflate's decoding tables, where the
+   number of code structures used so far is mem, and the number remaining in
+   the current sub-table is rem.  Uses the globals max, code, root, large, and
+   done. */
+local void examine(int syms, int len, int left, int mem, int rem)
+{
+    int least;          /* least number of syms to use at this juncture */
+    int most;           /* most number of syms to use at this juncture */
+    int use;            /* number of bit patterns to use in next call */
+
+    /* see if we have a complete code */
+    if (syms == left) {
+        /* set the last code entry */
+        code[len] = left;
+
+        /* complete computation of memory used by this code */
+        while (rem < left) {
+            left -= rem;
+            rem = 1 << (len - root);
+            mem += rem;
+        }
+        assert(rem == left);
+
+        /* if this is a new maximum, show the entries used and the sub-code */
+        if (mem > large) {
+            large = mem;
+            printf("max %d: ", mem);
+            for (use = root + 1; use <= max; use++)
+                if (code[use])
+                    printf("%d[%d] ", code[use], use);
+            putchar('\n');
+            fflush(stdout);
+        }
+
+        /* remove entries as we drop back down in the recursion */
+        code[len] = 0;
+        return;
+    }
+
+    /* prune the tree if we can */
+    if (beenhere(syms, len, left, mem, rem))
+        return;
+
+    /* we need to use at least this many bit patterns so that the code won't be
+       incomplete at the next length (more bit patterns than symbols) */
+    least = (left << 1) - syms;
+    if (least < 0)
+        least = 0;
+
+    /* we can use at most this many bit patterns, lest there not be enough
+       available for the remaining symbols at the maximum length (if there were
+       no limit to the code length, this would become: most = left - 1) */
+    most = (((code_t)left << (max - len)) - syms) /
+            (((code_t)1 << (max - len)) - 1);
+
+    /* occupy least table spaces, creating new sub-tables as needed */
+    use = least;
+    while (rem < use) {
+        use -= rem;
+        rem = 1 << (len - root);
+        mem += rem;
+    }
+    rem -= use;
+
+    /* examine codes from here, updating table space as we go */
+    for (use = least; use <= most; use++) {
+        code[len] = use;
+        examine(syms - use, len + 1, (left - use) << 1,
+                mem + (rem ? 1 << (len - root) : 0), rem << 1);
+        if (rem == 0) {
+            rem = 1 << (len - root);
+            mem += rem;
+        }
+        rem--;
+    }
+
+    /* remove entries as we drop back down in the recursion */
+    code[len] = 0;
+}
+
+/* Look at all sub-codes starting with root + 1 bits.  Look at only the valid
+   intermediate code states (syms, left, len).  For each completed code,
+   calculate the amount of memory required by inflate to build the decoding
+   tables. Find the maximum amount of memory required and show the code that
+   requires that maximum.  Uses the globals max, root, and num. */
+local void enough(int syms)
+{
+    int n;              /* number of remaing symbols for this node */
+    int left;           /* number of unused bit patterns at this length */
+    size_t index;       /* index of this case in *num */
+
+    /* clear code */
+    for (n = 0; n <= max; n++)
+        code[n] = 0;
+
+    /* look at all (root + 1) bit and longer codes */
+    large = 1 << root;              /* base table */
+    if (root < max)                 /* otherwise, there's only a base table */
+        for (n = 3; n <= syms; n++)
+            for (left = 2; left < n; left += 2)
+            {
+                /* look at all reachable (root + 1) bit nodes, and the
+                   resulting codes (complete at root + 2 or more) */
+                index = INDEX(n, left, root + 1);
+                if (root + 1 < max && num[index])       /* reachable node */
+                    examine(n, root + 1, left, 1 << root, 0);
+
+                /* also look at root bit codes with completions at root + 1
+                   bits (not saved in num, since complete), just in case */
+                if (num[index - 1] && n <= left << 1)
+                    examine((n - left) << 1, root + 1, (n - left) << 1,
+                            1 << root, 0);
+            }
+
+    /* done */
+    printf("done: maximum of %d table entries\n", large);
+}
+
+/*
+   Examine and show the total number of possible Huffman codes for a given
+   maximum number of symbols, initial root table size, and maximum code length
+   in bits -- those are the command arguments in that order.  The default
+   values are 286, 9, and 15 respectively, for the deflate literal/length code.
+   The possible codes are counted for each number of coded symbols from two to
+   the maximum.  The counts for each of those and the total number of codes are
+   shown.  The maximum number of inflate table entires is then calculated
+   across all possible codes.  Each new maximum number of table entries and the
+   associated sub-code (starting at root + 1 == 10 bits) is shown.
+
+   To count and examine Huffman codes that are not length-limited, provide a
+   maximum length equal to the number of symbols minus one.
+
+   For the deflate literal/length code, use "enough".  For the deflate distance
+   code, use "enough 30 6".
+
+   This uses the %llu printf format to print big_t numbers, which assumes that
+   big_t is an unsigned long long.  If the big_t type is changed (for example
+   to a multiple precision type), the method of printing will also need to be
+   updated.
+ */
+int main(int argc, char **argv)
+{
+    int syms;           /* total number of symbols to code */
+    int n;              /* number of symbols to code for this run */
+    big_t got;          /* return value of count() */
+    big_t sum;          /* accumulated number of codes over n */
+    code_t word;        /* for counting bits in code_t */
+
+    /* set up globals for cleanup() */
+    code = NULL;
+    num = NULL;
+    done = NULL;
+
+    /* get arguments -- default to the deflate literal/length code */
+    syms = 286;
+    root = 9;
+    max = 15;
+    if (argc > 1) {
+        syms = atoi(argv[1]);
+        if (argc > 2) {
+            root = atoi(argv[2]);
+            if (argc > 3)
+                max = atoi(argv[3]);
+        }
+    }
+    if (argc > 4 || syms < 2 || root < 1 || max < 1) {
+        fputs("invalid arguments, need: [sym >= 2 [root >= 1 [max >= 1]]]\n",
+              stderr);
+        return 1;
+    }
+
+    /* if not restricting the code length, the longest is syms - 1 */
+    if (max > syms - 1)
+        max = syms - 1;
+
+    /* determine the number of bits in a code_t */
+    for (n = 0, word = 1; word; n++, word <<= 1)
+        ;
+
+    /* make sure that the calculation of most will not overflow */
+    if (max > n || (code_t)(syms - 2) >= (((code_t)0 - 1) >> (max - 1))) {
+        fputs("abort: code length too long for internal types\n", stderr);
+        return 1;
+    }
+
+    /* reject impossible code requests */
+    if ((code_t)(syms - 1) > ((code_t)1 << max) - 1) {
+        fprintf(stderr, "%d symbols cannot be coded in %d bits\n",
+                syms, max);
+        return 1;
+    }
+
+    /* allocate code vector */
+    code = calloc(max + 1, sizeof(int));
+    if (code == NULL) {
+        fputs("abort: unable to allocate enough memory\n", stderr);
+        return 1;
+    }
+
+    /* determine size of saved results array, checking for overflows,
+       allocate and clear the array (set all to zero with calloc()) */
+    if (syms == 2)              /* iff max == 1 */
+        num = NULL;             /* won't be saving any results */
+    else {
+        size = syms >> 1;
+        if (size > ((size_t)0 - 1) / (n = (syms - 1) >> 1) ||
+                (size *= n, size > ((size_t)0 - 1) / (n = max - 1)) ||
+                (size *= n, size > ((size_t)0 - 1) / sizeof(big_t)) ||
+                (num = calloc(size, sizeof(big_t))) == NULL) {
+            fputs("abort: unable to allocate enough memory\n", stderr);
+            cleanup();
+            return 1;
+        }
+    }
+
+    /* count possible codes for all numbers of symbols, add up counts */
+    sum = 0;
+    for (n = 2; n <= syms; n++) {
+        got = count(n, 1, 2);
+        sum += got;
+        if (got == (big_t)0 - 1 || sum < got) {     /* overflow */
+            fputs("abort: can't count that high!\n", stderr);
+            cleanup();
+            return 1;
+        }
+        printf("%llu %d-codes\n", got, n);
+    }
+    printf("%llu total codes for 2 to %d symbols", sum, syms);
+    if (max < syms - 1)
+        printf(" (%d-bit length limit)\n", max);
+    else
+        puts(" (no length limit)");
+
+    /* allocate and clear done array for beenhere() */
+    if (syms == 2)
+        done = NULL;
+    else if (size > ((size_t)0 - 1) / sizeof(struct tab) ||
+             (done = calloc(size, sizeof(struct tab))) == NULL) {
+        fputs("abort: unable to allocate enough memory\n", stderr);
+        cleanup();
+        return 1;
+    }
+
+    /* find and show maximum inflate table usage */
+    if (root > max)                 /* reduce root to max length */
+        root = max;
+    if ((code_t)syms < ((code_t)1 << (root + 1)))
+        enough(syms);
+    else
+        puts("cannot handle minimum code lengths > root");
+
+    /* done */
+    cleanup();
+    return 0;
+}

ADDED   3rd_party/zlib/examples/fitblk.c
Index: 3rd_party/zlib/examples/fitblk.c
==================================================================
--- 3rd_party/zlib/examples/fitblk.c
+++ 3rd_party/zlib/examples/fitblk.c
@@ -0,0 +1,233 @@
+/* fitblk.c: example of fitting compressed output to a specified size
+   Not copyrighted -- provided to the public domain
+   Version 1.1  25 November 2004  Mark Adler */
+
+/* Version history:
+   1.0  24 Nov 2004  First version
+   1.1  25 Nov 2004  Change deflateInit2() to deflateInit()
+                     Use fixed-size, stack-allocated raw buffers
+                     Simplify code moving compression to subroutines
+                     Use assert() for internal errors
+                     Add detailed description of approach
+ */
+
+/* Approach to just fitting a requested compressed size:
+
+   fitblk performs three compression passes on a portion of the input
+   data in order to determine how much of that input will compress to
+   nearly the requested output block size.  The first pass generates
+   enough deflate blocks to produce output to fill the requested
+   output size plus a specfied excess amount (see the EXCESS define
+   below).  The last deflate block may go quite a bit past that, but
+   is discarded.  The second pass decompresses and recompresses just
+   the compressed data that fit in the requested plus excess sized
+   buffer.  The deflate process is terminated after that amount of
+   input, which is less than the amount consumed on the first pass.
+   The last deflate block of the result will be of a comparable size
+   to the final product, so that the header for that deflate block and
+   the compression ratio for that block will be about the same as in
+   the final product.  The third compression pass decompresses the
+   result of the second step, but only the compressed data up to the
+   requested size minus an amount to allow the compressed stream to
+   complete (see the MARGIN define below).  That will result in a
+   final compressed stream whose length is less than or equal to the
+   requested size.  Assuming sufficient input and a requested size
+   greater than a few hundred bytes, the shortfall will typically be
+   less than ten bytes.
+
+   If the input is short enough that the first compression completes
+   before filling the requested output size, then that compressed
+   stream is return with no recompression.
+
+   EXCESS is chosen to be just greater than the shortfall seen in a
+   two pass approach similar to the above.  That shortfall is due to
+   the last deflate block compressing more efficiently with a smaller
+   header on the second pass.  EXCESS is set to be large enough so
+   that there is enough uncompressed data for the second pass to fill
+   out the requested size, and small enough so that the final deflate
+   block of the second pass will be close in size to the final deflate
+   block of the third and final pass.  MARGIN is chosen to be just
+   large enough to assure that the final compression has enough room
+   to complete in all cases.
+ */
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <assert.h>
+#include "zlib.h"
+
+#define local static
+
+/* print nastygram and leave */
+local void quit(char *why)
+{
+    fprintf(stderr, "fitblk abort: %s\n", why);
+    exit(1);
+}
+
+#define RAWLEN 4096    /* intermediate uncompressed buffer size */
+
+/* compress from file to def until provided buffer is full or end of
+   input reached; return last deflate() return value, or Z_ERRNO if
+   there was read error on the file */
+local int partcompress(FILE *in, z_streamp def)
+{
+    int ret, flush;
+    unsigned char raw[RAWLEN];
+
+    flush = Z_NO_FLUSH;
+    do {
+        def->avail_in = fread(raw, 1, RAWLEN, in);
+        if (ferror(in))
+            return Z_ERRNO;
+        def->next_in = raw;
+        if (feof(in))
+            flush = Z_FINISH;
+        ret = deflate(def, flush);
+        assert(ret != Z_STREAM_ERROR);
+    } while (def->avail_out != 0 && flush == Z_NO_FLUSH);
+    return ret;
+}
+
+/* recompress from inf's input to def's output; the input for inf and
+   the output for def are set in those structures before calling;
+   return last deflate() return value, or Z_MEM_ERROR if inflate()
+   was not able to allocate enough memory when it needed to */
+local int recompress(z_streamp inf, z_streamp def)
+{
+    int ret, flush;
+    unsigned char raw[RAWLEN];
+
+    flush = Z_NO_FLUSH;
+    do {
+        /* decompress */
+        inf->avail_out = RAWLEN;
+        inf->next_out = raw;
+        ret = inflate(inf, Z_NO_FLUSH);
+        assert(ret != Z_STREAM_ERROR && ret != Z_DATA_ERROR &&
+               ret != Z_NEED_DICT);
+        if (ret == Z_MEM_ERROR)
+            return ret;
+
+        /* compress what was decompresed until done or no room */
+        def->avail_in = RAWLEN - inf->avail_out;
+        def->next_in = raw;
+        if (inf->avail_out != 0)
+            flush = Z_FINISH;
+        ret = deflate(def, flush);
+        assert(ret != Z_STREAM_ERROR);
+    } while (ret != Z_STREAM_END && def->avail_out != 0);
+    return ret;
+}
+
+#define EXCESS 256      /* empirically determined stream overage */
+#define MARGIN 8        /* amount to back off for completion */
+
+/* compress from stdin to fixed-size block on stdout */
+int main(int argc, char **argv)
+{
+    int ret;                /* return code */
+    unsigned size;          /* requested fixed output block size */
+    unsigned have;          /* bytes written by deflate() call */
+    unsigned char *blk;     /* intermediate and final stream */
+    unsigned char *tmp;     /* close to desired size stream */
+    z_stream def, inf;      /* zlib deflate and inflate states */
+
+    /* get requested output size */
+    if (argc != 2)
+        quit("need one argument: size of output block");
+    ret = strtol(argv[1], argv + 1, 10);
+    if (argv[1][0] != 0)
+        quit("argument must be a number");
+    if (ret < 8)            /* 8 is minimum zlib stream size */
+        quit("need positive size of 8 or greater");
+    size = (unsigned)ret;
+
+    /* allocate memory for buffers and compression engine */
+    blk = malloc(size + EXCESS);
+    def.zalloc = Z_NULL;
+    def.zfree = Z_NULL;
+    def.opaque = Z_NULL;
+    ret = deflateInit(&def, Z_DEFAULT_COMPRESSION);
+    if (ret != Z_OK || blk == NULL)
+        quit("out of memory");
+
+    /* compress from stdin until output full, or no more input */
+    def.avail_out = size + EXCESS;
+    def.next_out = blk;
+    ret = partcompress(stdin, &def);
+    if (ret == Z_ERRNO)
+        quit("error reading input");
+
+    /* if it all fit, then size was undersubscribed -- done! */
+    if (ret == Z_STREAM_END && def.avail_out >= EXCESS) {
+        /* write block to stdout */
+        have = size + EXCESS - def.avail_out;
+        if (fwrite(blk, 1, have, stdout) != have || ferror(stdout))
+            quit("error writing output");
+
+        /* clean up and print results to stderr */
+        ret = deflateEnd(&def);
+        assert(ret != Z_STREAM_ERROR);
+        free(blk);
+        fprintf(stderr,
+                "%u bytes unused out of %u requested (all input)\n",
+                size - have, size);
+        return 0;
+    }
+
+    /* it didn't all fit -- set up for recompression */
+    inf.zalloc = Z_NULL;
+    inf.zfree = Z_NULL;
+    inf.opaque = Z_NULL;
+    inf.avail_in = 0;
+    inf.next_in = Z_NULL;
+    ret = inflateInit(&inf);
+    tmp = malloc(size + EXCESS);
+    if (ret != Z_OK || tmp == NULL)
+        quit("out of memory");
+    ret = deflateReset(&def);
+    assert(ret != Z_STREAM_ERROR);
+
+    /* do first recompression close to the right amount */
+    inf.avail_in = size + EXCESS;
+    inf.next_in = blk;
+    def.avail_out = size + EXCESS;
+    def.next_out = tmp;
+    ret = recompress(&inf, &def);
+    if (ret == Z_MEM_ERROR)
+        quit("out of memory");
+
+    /* set up for next reocmpression */
+    ret = inflateReset(&inf);
+    assert(ret != Z_STREAM_ERROR);
+    ret = deflateReset(&def);
+    assert(ret != Z_STREAM_ERROR);
+
+    /* do second and final recompression (third compression) */
+    inf.avail_in = size - MARGIN;   /* assure stream will complete */
+    inf.next_in = tmp;
+    def.avail_out = size;
+    def.next_out = blk;
+    ret = recompress(&inf, &def);
+    if (ret == Z_MEM_ERROR)
+        quit("out of memory");
+    assert(ret == Z_STREAM_END);    /* otherwise MARGIN too small */
+
+    /* done -- write block to stdout */
+    have = size - def.avail_out;
+    if (fwrite(blk, 1, have, stdout) != have || ferror(stdout))
+        quit("error writing output");
+
+    /* clean up and print results to stderr */
+    free(tmp);
+    ret = inflateEnd(&inf);
+    assert(ret != Z_STREAM_ERROR);
+    ret = deflateEnd(&def);
+    assert(ret != Z_STREAM_ERROR);
+    free(blk);
+    fprintf(stderr,
+            "%u bytes unused out of %u requested (%lu input)\n",
+            size - have, size, def.total_in);
+    return 0;
+}

ADDED   3rd_party/zlib/examples/gun.c
Index: 3rd_party/zlib/examples/gun.c
==================================================================
--- 3rd_party/zlib/examples/gun.c
+++ 3rd_party/zlib/examples/gun.c
@@ -0,0 +1,702 @@
+/* gun.c -- simple gunzip to give an example of the use of inflateBack()
+ * Copyright (C) 2003, 2005, 2008, 2010, 2012 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+   Version 1.7  12 August 2012  Mark Adler */
+
+/* Version history:
+   1.0  16 Feb 2003  First version for testing of inflateBack()
+   1.1  21 Feb 2005  Decompress concatenated gzip streams
+                     Remove use of "this" variable (C++ keyword)
+                     Fix return value for in()
+                     Improve allocation failure checking
+                     Add typecasting for void * structures
+                     Add -h option for command version and usage
+                     Add a bunch of comments
+   1.2  20 Mar 2005  Add Unix compress (LZW) decompression
+                     Copy file attributes from input file to output file
+   1.3  12 Jun 2005  Add casts for error messages [Oberhumer]
+   1.4   8 Dec 2006  LZW decompression speed improvements
+   1.5   9 Feb 2008  Avoid warning in latest version of gcc
+   1.6  17 Jan 2010  Avoid signed/unsigned comparison warnings
+   1.7  12 Aug 2012  Update for z_const usage in zlib 1.2.8
+ */
+
+/*
+   gun [ -t ] [ name ... ]
+
+   decompresses the data in the named gzip files.  If no arguments are given,
+   gun will decompress from stdin to stdout.  The names must end in .gz, -gz,
+   .z, -z, _z, or .Z.  The uncompressed data will be written to a file name
+   with the suffix stripped.  On success, the original file is deleted.  On
+   failure, the output file is deleted.  For most failures, the command will
+   continue to process the remaining names on the command line.  A memory
+   allocation failure will abort the command.  If -t is specified, then the
+   listed files or stdin will be tested as gzip files for integrity (without
+   checking for a proper suffix), no output will be written, and no files
+   will be deleted.
+
+   Like gzip, gun allows concatenated gzip streams and will decompress them,
+   writing all of the uncompressed data to the output.  Unlike gzip, gun allows
+   an empty file on input, and will produce no error writing an empty output
+   file.
+
+   gun will also decompress files made by Unix compress, which uses LZW
+   compression.  These files are automatically detected by virtue of their
+   magic header bytes.  Since the end of Unix compress stream is marked by the
+   end-of-file, they cannot be concantenated.  If a Unix compress stream is
+   encountered in an input file, it is the last stream in that file.
+
+   Like gunzip and uncompress, the file attributes of the original compressed
+   file are maintained in the final uncompressed file, to the extent that the
+   user permissions allow it.
+
+   On my Mac OS X PowerPC G4, gun is almost twice as fast as gunzip (version
+   1.2.4) is on the same file, when gun is linked with zlib 1.2.2.  Also the
+   LZW decompression provided by gun is about twice as fast as the standard
+   Unix uncompress command.
+ */
+
+/* external functions and related types and constants */
+#include <stdio.h>          /* fprintf() */
+#include <stdlib.h>         /* malloc(), free() */
+#include <string.h>         /* strerror(), strcmp(), strlen(), memcpy() */
+#include <errno.h>          /* errno */
+#include <fcntl.h>          /* open() */
+#include <unistd.h>         /* read(), write(), close(), chown(), unlink() */
+#include <sys/types.h>
+#include <sys/stat.h>       /* stat(), chmod() */
+#include <utime.h>          /* utime() */
+#include "zlib.h"           /* inflateBackInit(), inflateBack(), */
+                            /* inflateBackEnd(), crc32() */
+
+/* function declaration */
+#define local static
+
+/* buffer constants */
+#define SIZE 32768U         /* input and output buffer sizes */
+#define PIECE 16384         /* limits i/o chunks for 16-bit int case */
+
+/* structure for infback() to pass to input function in() -- it maintains the
+   input file and a buffer of size SIZE */
+struct ind {
+    int infile;
+    unsigned char *inbuf;
+};
+
+/* Load input buffer, assumed to be empty, and return bytes loaded and a
+   pointer to them.  read() is called until the buffer is full, or until it
+   returns end-of-file or error.  Return 0 on error. */
+local unsigned in(void *in_desc, z_const unsigned char **buf)
+{
+    int ret;
+    unsigned len;
+    unsigned char *next;
+    struct ind *me = (struct ind *)in_desc;
+
+    next = me->inbuf;
+    *buf = next;
+    len = 0;
+    do {
+        ret = PIECE;
+        if ((unsigned)ret > SIZE - len)
+            ret = (int)(SIZE - len);
+        ret = (int)read(me->infile, next, ret);
+        if (ret == -1) {
+            len = 0;
+            break;
+        }
+        next += ret;
+        len += ret;
+    } while (ret != 0 && len < SIZE);
+    return len;
+}
+
+/* structure for infback() to pass to output function out() -- it maintains the
+   output file, a running CRC-32 check on the output and the total number of
+   bytes output, both for checking against the gzip trailer.  (The length in
+   the gzip trailer is stored modulo 2^32, so it's ok if a long is 32 bits and
+   the output is greater than 4 GB.) */
+struct outd {
+    int outfile;
+    int check;                  /* true if checking crc and total */
+    unsigned long crc;
+    unsigned long total;
+};
+
+/* Write output buffer and update the CRC-32 and total bytes written.  write()
+   is called until all of the output is written or an error is encountered.
+   On success out() returns 0.  For a write failure, out() returns 1.  If the
+   output file descriptor is -1, then nothing is written.
+ */
+local int out(void *out_desc, unsigned char *buf, unsigned len)
+{
+    int ret;
+    struct outd *me = (struct outd *)out_desc;
+
+    if (me->check) {
+        me->crc = crc32(me->crc, buf, len);
+        me->total += len;
+    }
+    if (me->outfile != -1)
+        do {
+            ret = PIECE;
+            if ((unsigned)ret > len)
+                ret = (int)len;
+            ret = (int)write(me->outfile, buf, ret);
+            if (ret == -1)
+                return 1;
+            buf += ret;
+            len -= ret;
+        } while (len != 0);
+    return 0;
+}
+
+/* next input byte macro for use inside lunpipe() and gunpipe() */
+#define NEXT() (have ? 0 : (have = in(indp, &next)), \
+                last = have ? (have--, (int)(*next++)) : -1)
+
+/* memory for gunpipe() and lunpipe() --
+   the first 256 entries of prefix[] and suffix[] are never used, could
+   have offset the index, but it's faster to waste the memory */
+unsigned char inbuf[SIZE];              /* input buffer */
+unsigned char outbuf[SIZE];             /* output buffer */
+unsigned short prefix[65536];           /* index to LZW prefix string */
+unsigned char suffix[65536];            /* one-character LZW suffix */
+unsigned char match[65280 + 2];         /* buffer for reversed match or gzip
+                                           32K sliding window */
+
+/* throw out what's left in the current bits byte buffer (this is a vestigial
+   aspect of the compressed data format derived from an implementation that
+   made use of a special VAX machine instruction!) */
+#define FLUSHCODE() \
+    do { \
+        left = 0; \
+        rem = 0; \
+        if (chunk > have) { \
+            chunk -= have; \
+            have = 0; \
+            if (NEXT() == -1) \
+                break; \
+            chunk--; \
+            if (chunk > have) { \
+                chunk = have = 0; \
+                break; \
+            } \
+        } \
+        have -= chunk; \
+        next += chunk; \
+        chunk = 0; \
+    } while (0)
+
+/* Decompress a compress (LZW) file from indp to outfile.  The compress magic
+   header (two bytes) has already been read and verified.  There are have bytes
+   of buffered input at next.  strm is used for passing error information back
+   to gunpipe().
+
+   lunpipe() will return Z_OK on success, Z_BUF_ERROR for an unexpected end of
+   file, read error, or write error (a write error indicated by strm->next_in
+   not equal to Z_NULL), or Z_DATA_ERROR for invalid input.
+ */
+local int lunpipe(unsigned have, z_const unsigned char *next, struct ind *indp,
+                  int outfile, z_stream *strm)
+{
+    int last;                   /* last byte read by NEXT(), or -1 if EOF */
+    unsigned chunk;             /* bytes left in current chunk */
+    int left;                   /* bits left in rem */
+    unsigned rem;               /* unused bits from input */
+    int bits;                   /* current bits per code */
+    unsigned code;              /* code, table traversal index */
+    unsigned mask;              /* mask for current bits codes */
+    int max;                    /* maximum bits per code for this stream */
+    unsigned flags;             /* compress flags, then block compress flag */
+    unsigned end;               /* last valid entry in prefix/suffix tables */
+    unsigned temp;              /* current code */
+    unsigned prev;              /* previous code */
+    unsigned final;             /* last character written for previous code */
+    unsigned stack;             /* next position for reversed string */
+    unsigned outcnt;            /* bytes in output buffer */
+    struct outd outd;           /* output structure */
+    unsigned char *p;
+
+    /* set up output */
+    outd.outfile = outfile;
+    outd.check = 0;
+
+    /* process remainder of compress header -- a flags byte */
+    flags = NEXT();
+    if (last == -1)
+        return Z_BUF_ERROR;
+    if (flags & 0x60) {
+        strm->msg = (char *)"unknown lzw flags set";
+        return Z_DATA_ERROR;
+    }
+    max = flags & 0x1f;
+    if (max < 9 || max > 16) {
+        strm->msg = (char *)"lzw bits out of range";
+        return Z_DATA_ERROR;
+    }
+    if (max == 9)                           /* 9 doesn't really mean 9 */
+        max = 10;
+    flags &= 0x80;                          /* true if block compress */
+
+    /* clear table */
+    bits = 9;
+    mask = 0x1ff;
+    end = flags ? 256 : 255;
+
+    /* set up: get first 9-bit code, which is the first decompressed byte, but
+       don't create a table entry until the next code */
+    if (NEXT() == -1)                       /* no compressed data is ok */
+        return Z_OK;
+    final = prev = (unsigned)last;          /* low 8 bits of code */
+    if (NEXT() == -1)                       /* missing a bit */
+        return Z_BUF_ERROR;
+    if (last & 1) {                         /* code must be < 256 */
+        strm->msg = (char *)"invalid lzw code";
+        return Z_DATA_ERROR;
+    }
+    rem = (unsigned)last >> 1;              /* remaining 7 bits */
+    left = 7;
+    chunk = bits - 2;                       /* 7 bytes left in this chunk */
+    outbuf[0] = (unsigned char)final;       /* write first decompressed byte */
+    outcnt = 1;
+
+    /* decode codes */
+    stack = 0;
+    for (;;) {
+        /* if the table will be full after this, increment the code size */
+        if (end >= mask && bits < max) {
+            FLUSHCODE();
+            bits++;
+            mask <<= 1;
+            mask++;
+        }
+
+        /* get a code of length bits */
+        if (chunk == 0)                     /* decrement chunk modulo bits */
+            chunk = bits;
+        code = rem;                         /* low bits of code */
+        if (NEXT() == -1) {                 /* EOF is end of compressed data */
+            /* write remaining buffered output */
+            if (outcnt && out(&outd, outbuf, outcnt)) {
+                strm->next_in = outbuf;     /* signal write error */
+                return Z_BUF_ERROR;
+            }
+            return Z_OK;
+        }
+        code += (unsigned)last << left;     /* middle (or high) bits of code */
+        left += 8;
+        chunk--;
+        if (bits > left) {                  /* need more bits */
+            if (NEXT() == -1)               /* can't end in middle of code */
+                return Z_BUF_ERROR;
+            code += (unsigned)last << left; /* high bits of code */
+            left += 8;
+            chunk--;
+        }
+        code &= mask;                       /* mask to current code length */
+        left -= bits;                       /* number of unused bits */
+        rem = (unsigned)last >> (8 - left); /* unused bits from last byte */
+
+        /* process clear code (256) */
+        if (code == 256 && flags) {
+            FLUSHCODE();
+            bits = 9;                       /* initialize bits and mask */
+            mask = 0x1ff;
+            end = 255;                      /* empty table */
+            continue;                       /* get next code */
+        }
+
+        /* special code to reuse last match */
+        temp = code;                        /* save the current code */
+        if (code > end) {
+            /* Be picky on the allowed code here, and make sure that the code
+               we drop through (prev) will be a valid index so that random
+               input does not cause an exception.  The code != end + 1 check is
+               empirically derived, and not checked in the original uncompress
+               code.  If this ever causes a problem, that check could be safely
+               removed.  Leaving this check in greatly improves gun's ability
+               to detect random or corrupted input after a compress header.
+               In any case, the prev > end check must be retained. */
+            if (code != end + 1 || prev > end) {
+                strm->msg = (char *)"invalid lzw code";
+                return Z_DATA_ERROR;
+            }
+            match[stack++] = (unsigned char)final;
+            code = prev;
+        }
+
+        /* walk through linked list to generate output in reverse order */
+        p = match + stack;
+        while (code >= 256) {
+            *p++ = suffix[code];
+            code = prefix[code];
+        }
+        stack = p - match;
+        match[stack++] = (unsigned char)code;
+        final = code;
+
+        /* link new table entry */
+        if (end < mask) {
+            end++;
+            prefix[end] = (unsigned short)prev;
+            suffix[end] = (unsigned char)final;
+        }
+
+        /* set previous code for next iteration */
+        prev = temp;
+
+        /* write output in forward order */
+        while (stack > SIZE - outcnt) {
+            while (outcnt < SIZE)
+                outbuf[outcnt++] = match[--stack];
+            if (out(&outd, outbuf, outcnt)) {
+                strm->next_in = outbuf; /* signal write error */
+                return Z_BUF_ERROR;
+            }
+            outcnt = 0;
+        }
+        p = match + stack;
+        do {
+            outbuf[outcnt++] = *--p;
+        } while (p > match);
+        stack = 0;
+
+        /* loop for next code with final and prev as the last match, rem and
+           left provide the first 0..7 bits of the next code, end is the last
+           valid table entry */
+    }
+}
+
+/* Decompress a gzip file from infile to outfile.  strm is assumed to have been
+   successfully initialized with inflateBackInit().  The input file may consist
+   of a series of gzip streams, in which case all of them will be decompressed
+   to the output file.  If outfile is -1, then the gzip stream(s) integrity is
+   checked and nothing is written.
+
+   The return value is a zlib error code: Z_MEM_ERROR if out of memory,
+   Z_DATA_ERROR if the header or the compressed data is invalid, or if the
+   trailer CRC-32 check or length doesn't match, Z_BUF_ERROR if the input ends
+   prematurely or a write error occurs, or Z_ERRNO if junk (not a another gzip
+   stream) follows a valid gzip stream.
+ */
+local int gunpipe(z_stream *strm, int infile, int outfile)
+{
+    int ret, first, last;
+    unsigned have, flags, len;
+    z_const unsigned char *next = NULL;
+    struct ind ind, *indp;
+    struct outd outd;
+
+    /* setup input buffer */
+    ind.infile = infile;
+    ind.inbuf = inbuf;
+    indp = &ind;
+
+    /* decompress concatenated gzip streams */
+    have = 0;                               /* no input data read in yet */
+    first = 1;                              /* looking for first gzip header */
+    strm->next_in = Z_NULL;                 /* so Z_BUF_ERROR means EOF */
+    for (;;) {
+        /* look for the two magic header bytes for a gzip stream */
+        if (NEXT() == -1) {
+            ret = Z_OK;
+            break;                          /* empty gzip stream is ok */
+        }
+        if (last != 31 || (NEXT() != 139 && last != 157)) {
+            strm->msg = (char *)"incorrect header check";
+            ret = first ? Z_DATA_ERROR : Z_ERRNO;
+            break;                          /* not a gzip or compress header */
+        }
+        first = 0;                          /* next non-header is junk */
+
+        /* process a compress (LZW) file -- can't be concatenated after this */
+        if (last == 157) {
+            ret = lunpipe(have, next, indp, outfile, strm);
+            break;
+        }
+
+        /* process remainder of gzip header */
+        ret = Z_BUF_ERROR;
+        if (NEXT() != 8) {                  /* only deflate method allowed */
+            if (last == -1) break;
+            strm->msg = (char *)"unknown compression method";
+            ret = Z_DATA_ERROR;
+            break;
+        }
+        flags = NEXT();                     /* header flags */
+        NEXT();                             /* discard mod time, xflgs, os */
+        NEXT();
+        NEXT();
+        NEXT();
+        NEXT();
+        NEXT();
+        if (last == -1) break;
+        if (flags & 0xe0) {
+            strm->msg = (char *)"unknown header flags set";
+            ret = Z_DATA_ERROR;
+            break;
+        }
+        if (flags & 4) {                    /* extra field */
+            len = NEXT();
+            len += (unsigned)(NEXT()) << 8;
+            if (last == -1) break;
+            while (len > have) {
+                len -= have;
+                have = 0;
+                if (NEXT() == -1) break;
+                len--;
+            }
+            if (last == -1) break;
+            have -= len;
+            next += len;
+        }
+        if (flags & 8)                      /* file name */
+            while (NEXT() != 0 && last != -1)
+                ;
+        if (flags & 16)                     /* comment */
+            while (NEXT() != 0 && last != -1)
+                ;
+        if (flags & 2) {                    /* header crc */
+            NEXT();
+            NEXT();
+        }
+        if (last == -1) break;
+
+        /* set up output */
+        outd.outfile = outfile;
+        outd.check = 1;
+        outd.crc = crc32(0L, Z_NULL, 0);
+        outd.total = 0;
+
+        /* decompress data to output */
+        strm->next_in = next;
+        strm->avail_in = have;
+        ret = inflateBack(strm, in, indp, out, &outd);
+        if (ret != Z_STREAM_END) break;
+        next = strm->next_in;
+        have = strm->avail_in;
+        strm->next_in = Z_NULL;             /* so Z_BUF_ERROR means EOF */
+
+        /* check trailer */
+        ret = Z_BUF_ERROR;
+        if (NEXT() != (int)(outd.crc & 0xff) ||
+            NEXT() != (int)((outd.crc >> 8) & 0xff) ||
+            NEXT() != (int)((outd.crc >> 16) & 0xff) ||
+            NEXT() != (int)((outd.crc >> 24) & 0xff)) {
+            /* crc error */
+            if (last != -1) {
+                strm->msg = (char *)"incorrect data check";
+                ret = Z_DATA_ERROR;
+            }
+            break;
+        }
+        if (NEXT() != (int)(outd.total & 0xff) ||
+            NEXT() != (int)((outd.total >> 8) & 0xff) ||
+            NEXT() != (int)((outd.total >> 16) & 0xff) ||
+            NEXT() != (int)((outd.total >> 24) & 0xff)) {
+            /* length error */
+            if (last != -1) {
+                strm->msg = (char *)"incorrect length check";
+                ret = Z_DATA_ERROR;
+            }
+            break;
+        }
+
+        /* go back and look for another gzip stream */
+    }
+
+    /* clean up and return */
+    return ret;
+}
+
+/* Copy file attributes, from -> to, as best we can.  This is best effort, so
+   no errors are reported.  The mode bits, including suid, sgid, and the sticky
+   bit are copied (if allowed), the owner's user id and group id are copied
+   (again if allowed), and the access and modify times are copied. */
+local void copymeta(char *from, char *to)
+{
+    struct stat was;
+    struct utimbuf when;
+
+    /* get all of from's Unix meta data, return if not a regular file */
+    if (stat(from, &was) != 0 || (was.st_mode & S_IFMT) != S_IFREG)
+        return;
+
+    /* set to's mode bits, ignore errors */
+    (void)chmod(to, was.st_mode & 07777);
+
+    /* copy owner's user and group, ignore errors */
+    (void)chown(to, was.st_uid, was.st_gid);
+
+    /* copy access and modify times, ignore errors */
+    when.actime = was.st_atime;
+    when.modtime = was.st_mtime;
+    (void)utime(to, &when);
+}
+
+/* Decompress the file inname to the file outnname, of if test is true, just
+   decompress without writing and check the gzip trailer for integrity.  If
+   inname is NULL or an empty string, read from stdin.  If outname is NULL or
+   an empty string, write to stdout.  strm is a pre-initialized inflateBack
+   structure.  When appropriate, copy the file attributes from inname to
+   outname.
+
+   gunzip() returns 1 if there is an out-of-memory error or an unexpected
+   return code from gunpipe().  Otherwise it returns 0.
+ */
+local int gunzip(z_stream *strm, char *inname, char *outname, int test)
+{
+    int ret;
+    int infile, outfile;
+
+    /* open files */
+    if (inname == NULL || *inname == 0) {
+        inname = "-";
+        infile = 0;     /* stdin */
+    }
+    else {
+        infile = open(inname, O_RDONLY, 0);
+        if (infile == -1) {
+            fprintf(stderr, "gun cannot open %s\n", inname);
+            return 0;
+        }
+    }
+    if (test)
+        outfile = -1;
+    else if (outname == NULL || *outname == 0) {
+        outname = "-";
+        outfile = 1;    /* stdout */
+    }
+    else {
+        outfile = open(outname, O_CREAT | O_TRUNC | O_WRONLY, 0666);
+        if (outfile == -1) {
+            close(infile);
+            fprintf(stderr, "gun cannot create %s\n", outname);
+            return 0;
+        }
+    }
+    errno = 0;
+
+    /* decompress */
+    ret = gunpipe(strm, infile, outfile);
+    if (outfile > 2) close(outfile);
+    if (infile > 2) close(infile);
+
+    /* interpret result */
+    switch (ret) {
+    case Z_OK:
+    case Z_ERRNO:
+        if (infile > 2 && outfile > 2) {
+            copymeta(inname, outname);          /* copy attributes */
+            unlink(inname);
+        }
+        if (ret == Z_ERRNO)
+            fprintf(stderr, "gun warning: trailing garbage ignored in %s\n",
+                    inname);
+        break;
+    case Z_DATA_ERROR:
+        if (outfile > 2) unlink(outname);
+        fprintf(stderr, "gun data error on %s: %s\n", inname, strm->msg);
+        break;
+    case Z_MEM_ERROR:
+        if (outfile > 2) unlink(outname);
+        fprintf(stderr, "gun out of memory error--aborting\n");
+        return 1;
+    case Z_BUF_ERROR:
+        if (outfile > 2) unlink(outname);
+        if (strm->next_in != Z_NULL) {
+            fprintf(stderr, "gun write error on %s: %s\n",
+                    outname, strerror(errno));
+        }
+        else if (errno) {
+            fprintf(stderr, "gun read error on %s: %s\n",
+                    inname, strerror(errno));
+        }
+        else {
+            fprintf(stderr, "gun unexpected end of file on %s\n",
+                    inname);
+        }
+        break;
+    default:
+        if (outfile > 2) unlink(outname);
+        fprintf(stderr, "gun internal error--aborting\n");
+        return 1;
+    }
+    return 0;
+}
+
+/* Process the gun command line arguments.  See the command syntax near the
+   beginning of this source file. */
+int main(int argc, char **argv)
+{
+    int ret, len, test;
+    char *outname;
+    unsigned char *window;
+    z_stream strm;
+
+    /* initialize inflateBack state for repeated use */
+    window = match;                         /* reuse LZW match buffer */
+    strm.zalloc = Z_NULL;
+    strm.zfree = Z_NULL;
+    strm.opaque = Z_NULL;
+    ret = inflateBackInit(&strm, 15, window);
+    if (ret != Z_OK) {
+        fprintf(stderr, "gun out of memory error--aborting\n");
+        return 1;
+    }
+
+    /* decompress each file to the same name with the suffix removed */
+    argc--;
+    argv++;
+    test = 0;
+    if (argc && strcmp(*argv, "-h") == 0) {
+        fprintf(stderr, "gun 1.6 (17 Jan 2010)\n");
+        fprintf(stderr, "Copyright (C) 2003-2010 Mark Adler\n");
+        fprintf(stderr, "usage: gun [-t] [file1.gz [file2.Z ...]]\n");
+        return 0;
+    }
+    if (argc && strcmp(*argv, "-t") == 0) {
+        test = 1;
+        argc--;
+        argv++;
+    }
+    if (argc)
+        do {
+            if (test)
+                outname = NULL;
+            else {
+                len = (int)strlen(*argv);
+                if (strcmp(*argv + len - 3, ".gz") == 0 ||
+                    strcmp(*argv + len - 3, "-gz") == 0)
+                    len -= 3;
+                else if (strcmp(*argv + len - 2, ".z") == 0 ||
+                    strcmp(*argv + len - 2, "-z") == 0 ||
+                    strcmp(*argv + len - 2, "_z") == 0 ||
+                    strcmp(*argv + len - 2, ".Z") == 0)
+                    len -= 2;
+                else {
+                    fprintf(stderr, "gun error: no gz type on %s--skipping\n",
+                            *argv);
+                    continue;
+                }
+                outname = malloc(len + 1);
+                if (outname == NULL) {
+                    fprintf(stderr, "gun out of memory error--aborting\n");
+                    ret = 1;
+                    break;
+                }
+                memcpy(outname, *argv, len);
+                outname[len] = 0;
+            }
+            ret = gunzip(&strm, *argv, outname, test);
+            if (outname != NULL) free(outname);
+            if (ret) break;
+        } while (argv++, --argc);
+    else
+        ret = gunzip(&strm, NULL, NULL, test);
+
+    /* clean up */
+    inflateBackEnd(&strm);
+    return ret;
+}

ADDED   3rd_party/zlib/examples/gzappend.c
Index: 3rd_party/zlib/examples/gzappend.c
==================================================================
--- 3rd_party/zlib/examples/gzappend.c
+++ 3rd_party/zlib/examples/gzappend.c
@@ -0,0 +1,504 @@
+/* gzappend -- command to append to a gzip file
+
+  Copyright (C) 2003, 2012 Mark Adler, all rights reserved
+  version 1.2, 11 Oct 2012
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the author be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
+
+  Mark Adler    madler@alumni.caltech.edu
+ */
+
+/*
+ * Change history:
+ *
+ * 1.0  19 Oct 2003     - First version
+ * 1.1   4 Nov 2003     - Expand and clarify some comments and notes
+ *                      - Add version and copyright to help
+ *                      - Send help to stdout instead of stderr
+ *                      - Add some preemptive typecasts
+ *                      - Add L to constants in lseek() calls
+ *                      - Remove some debugging information in error messages
+ *                      - Use new data_type definition for zlib 1.2.1
+ *                      - Simplfy and unify file operations
+ *                      - Finish off gzip file in gztack()
+ *                      - Use deflatePrime() instead of adding empty blocks
+ *                      - Keep gzip file clean on appended file read errors
+ *                      - Use in-place rotate instead of auxiliary buffer
+ *                        (Why you ask?  Because it was fun to write!)
+ * 1.2  11 Oct 2012     - Fix for proper z_const usage
+ *                      - Check for input buffer malloc failure
+ */
+
+/*
+   gzappend takes a gzip file and appends to it, compressing files from the
+   command line or data from stdin.  The gzip file is written to directly, to
+   avoid copying that file, in case it's large.  Note that this results in the
+   unfriendly behavior that if gzappend fails, the gzip file is corrupted.
+
+   This program was written to illustrate the use of the new Z_BLOCK option of
+   zlib 1.2.x's inflate() function.  This option returns from inflate() at each
+   block boundary to facilitate locating and modifying the last block bit at
+   the start of the final deflate block.  Also whether using Z_BLOCK or not,
+   another required feature of zlib 1.2.x is that inflate() now provides the
+   number of unusued bits in the last input byte used.  gzappend will not work
+   with versions of zlib earlier than 1.2.1.
+
+   gzappend first decompresses the gzip file internally, discarding all but
+   the last 32K of uncompressed data, and noting the location of the last block
+   bit and the number of unused bits in the last byte of the compressed data.
+   The gzip trailer containing the CRC-32 and length of the uncompressed data
+   is verified.  This trailer will be later overwritten.
+
+   Then the last block bit is cleared by seeking back in the file and rewriting
+   the byte that contains it.  Seeking forward, the last byte of the compressed
+   data is saved along with the number of unused bits to initialize deflate.
+
+   A deflate process is initialized, using the last 32K of the uncompressed
+   data from the gzip file to initialize the dictionary.  If the total
+   uncompressed data was less than 32K, then all of it is used to initialize
+   the dictionary.  The deflate output bit buffer is also initialized with the
+   last bits from the original deflate stream.  From here on, the data to
+   append is simply compressed using deflate, and written to the gzip file.
+   When that is complete, the new CRC-32 and uncompressed length are written
+   as the trailer of the gzip file.
+ */
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <fcntl.h>
+#include <unistd.h>
+#include "zlib.h"
+
+#define local static
+#define LGCHUNK 14
+#define CHUNK (1U << LGCHUNK)
+#define DSIZE 32768U
+
+/* print an error message and terminate with extreme prejudice */
+local void bye(char *msg1, char *msg2)
+{
+    fprintf(stderr, "gzappend error: %s%s\n", msg1, msg2);
+    exit(1);
+}
+
+/* return the greatest common divisor of a and b using Euclid's algorithm,
+   modified to be fast when one argument much greater than the other, and
+   coded to avoid unnecessary swapping */
+local unsigned gcd(unsigned a, unsigned b)
+{
+    unsigned c;
+
+    while (a && b)
+        if (a > b) {
+            c = b;
+            while (a - c >= c)
+                c <<= 1;
+            a -= c;
+        }
+        else {
+            c = a;
+            while (b - c >= c)
+                c <<= 1;
+            b -= c;
+        }
+    return a + b;
+}
+
+/* rotate list[0..len-1] left by rot positions, in place */
+local void rotate(unsigned char *list, unsigned len, unsigned rot)
+{
+    unsigned char tmp;
+    unsigned cycles;
+    unsigned char *start, *last, *to, *from;
+
+    /* normalize rot and handle degenerate cases */
+    if (len < 2) return;
+    if (rot >= len) rot %= len;
+    if (rot == 0) return;
+
+    /* pointer to last entry in list */
+    last = list + (len - 1);
+
+    /* do simple left shift by one */
+    if (rot == 1) {
+        tmp = *list;
+        memcpy(list, list + 1, len - 1);
+        *last = tmp;
+        return;
+    }
+
+    /* do simple right shift by one */
+    if (rot == len - 1) {
+        tmp = *last;
+        memmove(list + 1, list, len - 1);
+        *list = tmp;
+        return;
+    }
+
+    /* otherwise do rotate as a set of cycles in place */
+    cycles = gcd(len, rot);             /* number of cycles */
+    do {
+        start = from = list + cycles;   /* start index is arbitrary */
+        tmp = *from;                    /* save entry to be overwritten */
+        for (;;) {
+            to = from;                  /* next step in cycle */
+            from += rot;                /* go right rot positions */
+            if (from > last) from -= len;   /* (pointer better not wrap) */
+            if (from == start) break;   /* all but one shifted */
+            *to = *from;                /* shift left */
+        }
+        *to = tmp;                      /* complete the circle */
+    } while (--cycles);
+}
+
+/* structure for gzip file read operations */
+typedef struct {
+    int fd;                     /* file descriptor */
+    int size;                   /* 1 << size is bytes in buf */
+    unsigned left;              /* bytes available at next */
+    unsigned char *buf;         /* buffer */
+    z_const unsigned char *next;    /* next byte in buffer */
+    char *name;                 /* file name for error messages */
+} file;
+
+/* reload buffer */
+local int readin(file *in)
+{
+    int len;
+
+    len = read(in->fd, in->buf, 1 << in->size);
+    if (len == -1) bye("error reading ", in->name);
+    in->left = (unsigned)len;
+    in->next = in->buf;
+    return len;
+}
+
+/* read from file in, exit if end-of-file */
+local int readmore(file *in)
+{
+    if (readin(in) == 0) bye("unexpected end of ", in->name);
+    return 0;
+}
+
+#define read1(in) (in->left == 0 ? readmore(in) : 0, \
+                   in->left--, *(in->next)++)
+
+/* skip over n bytes of in */
+local void skip(file *in, unsigned n)
+{
+    unsigned bypass;
+
+    if (n > in->left) {
+        n -= in->left;
+        bypass = n & ~((1U << in->size) - 1);
+        if (bypass) {
+            if (lseek(in->fd, (off_t)bypass, SEEK_CUR) == -1)
+                bye("seeking ", in->name);
+            n -= bypass;
+        }
+        readmore(in);
+        if (n > in->left)
+            bye("unexpected end of ", in->name);
+    }
+    in->left -= n;
+    in->next += n;
+}
+
+/* read a four-byte unsigned integer, little-endian, from in */
+unsigned long read4(file *in)
+{
+    unsigned long val;
+
+    val = read1(in);
+    val += (unsigned)read1(in) << 8;
+    val += (unsigned long)read1(in) << 16;
+    val += (unsigned long)read1(in) << 24;
+    return val;
+}
+
+/* skip over gzip header */
+local void gzheader(file *in)
+{
+    int flags;
+    unsigned n;
+
+    if (read1(in) != 31 || read1(in) != 139) bye(in->name, " not a gzip file");
+    if (read1(in) != 8) bye("unknown compression method in", in->name);
+    flags = read1(in);
+    if (flags & 0xe0) bye("unknown header flags set in", in->name);
+    skip(in, 6);
+    if (flags & 4) {
+        n = read1(in);
+        n += (unsigned)(read1(in)) << 8;
+        skip(in, n);
+    }
+    if (flags & 8) while (read1(in) != 0) ;
+    if (flags & 16) while (read1(in) != 0) ;
+    if (flags & 2) skip(in, 2);
+}
+
+/* decompress gzip file "name", return strm with a deflate stream ready to
+   continue compression of the data in the gzip file, and return a file
+   descriptor pointing to where to write the compressed data -- the deflate
+   stream is initialized to compress using level "level" */
+local int gzscan(char *name, z_stream *strm, int level)
+{
+    int ret, lastbit, left, full;
+    unsigned have;
+    unsigned long crc, tot;
+    unsigned char *window;
+    off_t lastoff, end;
+    file gz;
+
+    /* open gzip file */
+    gz.name = name;
+    gz.fd = open(name, O_RDWR, 0);
+    if (gz.fd == -1) bye("cannot open ", name);
+    gz.buf = malloc(CHUNK);
+    if (gz.buf == NULL) bye("out of memory", "");
+    gz.size = LGCHUNK;
+    gz.left = 0;
+
+    /* skip gzip header */
+    gzheader(&gz);
+
+    /* prepare to decompress */
+    window = malloc(DSIZE);
+    if (window == NULL) bye("out of memory", "");
+    strm->zalloc = Z_NULL;
+    strm->zfree = Z_NULL;
+    strm->opaque = Z_NULL;
+    ret = inflateInit2(strm, -15);
+    if (ret != Z_OK) bye("out of memory", " or library mismatch");
+
+    /* decompress the deflate stream, saving append information */
+    lastbit = 0;
+    lastoff = lseek(gz.fd, 0L, SEEK_CUR) - gz.left;
+    left = 0;
+    strm->avail_in = gz.left;
+    strm->next_in = gz.next;
+    crc = crc32(0L, Z_NULL, 0);
+    have = full = 0;
+    do {
+        /* if needed, get more input */
+        if (strm->avail_in == 0) {
+            readmore(&gz);
+            strm->avail_in = gz.left;
+            strm->next_in = gz.next;
+        }
+
+        /* set up output to next available section of sliding window */
+        strm->avail_out = DSIZE - have;
+        strm->next_out = window + have;
+
+        /* inflate and check for errors */
+        ret = inflate(strm, Z_BLOCK);
+        if (ret == Z_STREAM_ERROR) bye("internal stream error!", "");
+        if (ret == Z_MEM_ERROR) bye("out of memory", "");
+        if (ret == Z_DATA_ERROR)
+            bye("invalid compressed data--format violated in", name);
+
+        /* update crc and sliding window pointer */
+        crc = crc32(crc, window + have, DSIZE - have - strm->avail_out);
+        if (strm->avail_out)
+            have = DSIZE - strm->avail_out;
+        else {
+            have = 0;
+            full = 1;
+        }
+
+        /* process end of block */
+        if (strm->data_type & 128) {
+            if (strm->data_type & 64)
+                left = strm->data_type & 0x1f;
+            else {
+                lastbit = strm->data_type & 0x1f;
+                lastoff = lseek(gz.fd, 0L, SEEK_CUR) - strm->avail_in;
+            }
+        }
+    } while (ret != Z_STREAM_END);
+    inflateEnd(strm);
+    gz.left = strm->avail_in;
+    gz.next = strm->next_in;
+
+    /* save the location of the end of the compressed data */
+    end = lseek(gz.fd, 0L, SEEK_CUR) - gz.left;
+
+    /* check gzip trailer and save total for deflate */
+    if (crc != read4(&gz))
+        bye("invalid compressed data--crc mismatch in ", name);
+    tot = strm->total_out;
+    if ((tot & 0xffffffffUL) != read4(&gz))
+        bye("invalid compressed data--length mismatch in", name);
+
+    /* if not at end of file, warn */
+    if (gz.left || readin(&gz))
+        fprintf(stderr,
+            "gzappend warning: junk at end of gzip file overwritten\n");
+
+    /* clear last block bit */
+    lseek(gz.fd, lastoff - (lastbit != 0), SEEK_SET);
+    if (read(gz.fd, gz.buf, 1) != 1) bye("reading after seek on ", name);
+    *gz.buf = (unsigned char)(*gz.buf ^ (1 << ((8 - lastbit) & 7)));
+    lseek(gz.fd, -1L, SEEK_CUR);
+    if (write(gz.fd, gz.buf, 1) != 1) bye("writing after seek to ", name);
+
+    /* if window wrapped, build dictionary from window by rotating */
+    if (full) {
+        rotate(window, DSIZE, have);
+        have = DSIZE;
+    }
+
+    /* set up deflate stream with window, crc, total_in, and leftover bits */
+    ret = deflateInit2(strm, level, Z_DEFLATED, -15, 8, Z_DEFAULT_STRATEGY);
+    if (ret != Z_OK) bye("out of memory", "");
+    deflateSetDictionary(strm, window, have);
+    strm->adler = crc;
+    strm->total_in = tot;
+    if (left) {
+        lseek(gz.fd, --end, SEEK_SET);
+        if (read(gz.fd, gz.buf, 1) != 1) bye("reading after seek on ", name);
+        deflatePrime(strm, 8 - left, *gz.buf);
+    }
+    lseek(gz.fd, end, SEEK_SET);
+
+    /* clean up and return */
+    free(window);
+    free(gz.buf);
+    return gz.fd;
+}
+
+/* append file "name" to gzip file gd using deflate stream strm -- if last
+   is true, then finish off the deflate stream at the end */
+local void gztack(char *name, int gd, z_stream *strm, int last)
+{
+    int fd, len, ret;
+    unsigned left;
+    unsigned char *in, *out;
+
+    /* open file to compress and append */
+    fd = 0;
+    if (name != NULL) {
+        fd = open(name, O_RDONLY, 0);
+        if (fd == -1)
+            fprintf(stderr, "gzappend warning: %s not found, skipping ...\n",
+                    name);
+    }
+
+    /* allocate buffers */
+    in = malloc(CHUNK);
+    out = malloc(CHUNK);
+    if (in == NULL || out == NULL) bye("out of memory", "");
+
+    /* compress input file and append to gzip file */
+    do {
+        /* get more input */
+        len = read(fd, in, CHUNK);
+        if (len == -1) {
+            fprintf(stderr,
+                    "gzappend warning: error reading %s, skipping rest ...\n",
+                    name);
+            len = 0;
+        }
+        strm->avail_in = (unsigned)len;
+        strm->next_in = in;
+        if (len) strm->adler = crc32(strm->adler, in, (unsigned)len);
+
+        /* compress and write all available output */
+        do {
+            strm->avail_out = CHUNK;
+            strm->next_out = out;
+            ret = deflate(strm, last && len == 0 ? Z_FINISH : Z_NO_FLUSH);
+            left = CHUNK - strm->avail_out;
+            while (left) {
+                len = write(gd, out + CHUNK - strm->avail_out - left, left);
+                if (len == -1) bye("writing gzip file", "");
+                left -= (unsigned)len;
+            }
+        } while (strm->avail_out == 0 && ret != Z_STREAM_END);
+    } while (len != 0);
+
+    /* write trailer after last entry */
+    if (last) {
+        deflateEnd(strm);
+        out[0] = (unsigned char)(strm->adler);
+        out[1] = (unsigned char)(strm->adler >> 8);
+        out[2] = (unsigned char)(strm->adler >> 16);
+        out[3] = (unsigned char)(strm->adler >> 24);
+        out[4] = (unsigned char)(strm->total_in);
+        out[5] = (unsigned char)(strm->total_in >> 8);
+        out[6] = (unsigned char)(strm->total_in >> 16);
+        out[7] = (unsigned char)(strm->total_in >> 24);
+        len = 8;
+        do {
+            ret = write(gd, out + 8 - len, len);
+            if (ret == -1) bye("writing gzip file", "");
+            len -= ret;
+        } while (len);
+        close(gd);
+    }
+
+    /* clean up and return */
+    free(out);
+    free(in);
+    if (fd > 0) close(fd);
+}
+
+/* process the compression level option if present, scan the gzip file, and
+   append the specified files, or append the data from stdin if no other file
+   names are provided on the command line -- the gzip file must be writable
+   and seekable */
+int main(int argc, char **argv)
+{
+    int gd, level;
+    z_stream strm;
+
+    /* ignore command name */
+    argc--; argv++;
+
+    /* provide usage if no arguments */
+    if (*argv == NULL) {
+        printf(
+            "gzappend 1.2 (11 Oct 2012) Copyright (C) 2003, 2012 Mark Adler\n"
+               );
+        printf(
+            "usage: gzappend [-level] file.gz [ addthis [ andthis ... ]]\n");
+        return 0;
+    }
+
+    /* set compression level */
+    level = Z_DEFAULT_COMPRESSION;
+    if (argv[0][0] == '-') {
+        if (argv[0][1] < '0' || argv[0][1] > '9' || argv[0][2] != 0)
+            bye("invalid compression level", "");
+        level = argv[0][1] - '0';
+        if (*++argv == NULL) bye("no gzip file name after options", "");
+    }
+
+    /* prepare to append to gzip file */
+    gd = gzscan(*argv++, &strm, level);
+
+    /* append files on command line, or from stdin if none */
+    if (*argv == NULL)
+        gztack(NULL, gd, &strm, 1);
+    else
+        do {
+            gztack(*argv, gd, &strm, argv[1] == NULL);
+        } while (*++argv != NULL);
+    return 0;
+}

ADDED   3rd_party/zlib/examples/gzjoin.c
Index: 3rd_party/zlib/examples/gzjoin.c
==================================================================
--- 3rd_party/zlib/examples/gzjoin.c
+++ 3rd_party/zlib/examples/gzjoin.c
@@ -0,0 +1,449 @@
+/* gzjoin -- command to join gzip files into one gzip file
+
+  Copyright (C) 2004, 2005, 2012 Mark Adler, all rights reserved
+  version 1.2, 14 Aug 2012
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the author be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
+
+  Mark Adler    madler@alumni.caltech.edu
+ */
+
+/*
+ * Change history:
+ *
+ * 1.0  11 Dec 2004     - First version
+ * 1.1  12 Jun 2005     - Changed ssize_t to long for portability
+ * 1.2  14 Aug 2012     - Clean up for z_const usage
+ */
+
+/*
+   gzjoin takes one or more gzip files on the command line and writes out a
+   single gzip file that will uncompress to the concatenation of the
+   uncompressed data from the individual gzip files.  gzjoin does this without
+   having to recompress any of the data and without having to calculate a new
+   crc32 for the concatenated uncompressed data.  gzjoin does however have to
+   decompress all of the input data in order to find the bits in the compressed
+   data that need to be modified to concatenate the streams.
+
+   gzjoin does not do an integrity check on the input gzip files other than
+   checking the gzip header and decompressing the compressed data.  They are
+   otherwise assumed to be complete and correct.
+
+   Each joint between gzip files removes at least 18 bytes of previous trailer
+   and subsequent header, and inserts an average of about three bytes to the
+   compressed data in order to connect the streams.  The output gzip file
+   has a minimal ten-byte gzip header with no file name or modification time.
+
+   This program was written to illustrate the use of the Z_BLOCK option of
+   inflate() and the crc32_combine() function.  gzjoin will not compile with
+   versions of zlib earlier than 1.2.3.
+ */
+
+#include <stdio.h>      /* fputs(), fprintf(), fwrite(), putc() */
+#include <stdlib.h>     /* exit(), malloc(), free() */
+#include <fcntl.h>      /* open() */
+#include <unistd.h>     /* close(), read(), lseek() */
+#include "zlib.h"
+    /* crc32(), crc32_combine(), inflateInit2(), inflate(), inflateEnd() */
+
+#define local static
+
+/* exit with an error (return a value to allow use in an expression) */
+local int bail(char *why1, char *why2)
+{
+    fprintf(stderr, "gzjoin error: %s%s, output incomplete\n", why1, why2);
+    exit(1);
+    return 0;
+}
+
+/* -- simple buffered file input with access to the buffer -- */
+
+#define CHUNK 32768         /* must be a power of two and fit in unsigned */
+
+/* bin buffered input file type */
+typedef struct {
+    char *name;             /* name of file for error messages */
+    int fd;                 /* file descriptor */
+    unsigned left;          /* bytes remaining at next */
+    unsigned char *next;    /* next byte to read */
+    unsigned char *buf;     /* allocated buffer of length CHUNK */
+} bin;
+
+/* close a buffered file and free allocated memory */
+local void bclose(bin *in)
+{
+    if (in != NULL) {
+        if (in->fd != -1)
+            close(in->fd);
+        if (in->buf != NULL)
+            free(in->buf);
+        free(in);
+    }
+}
+
+/* open a buffered file for input, return a pointer to type bin, or NULL on
+   failure */
+local bin *bopen(char *name)
+{
+    bin *in;
+
+    in = malloc(sizeof(bin));
+    if (in == NULL)
+        return NULL;
+    in->buf = malloc(CHUNK);
+    in->fd = open(name, O_RDONLY, 0);
+    if (in->buf == NULL || in->fd == -1) {
+        bclose(in);
+        return NULL;
+    }
+    in->left = 0;
+    in->next = in->buf;
+    in->name = name;
+    return in;
+}
+
+/* load buffer from file, return -1 on read error, 0 or 1 on success, with
+   1 indicating that end-of-file was reached */
+local int bload(bin *in)
+{
+    long len;
+
+    if (in == NULL)
+        return -1;
+    if (in->left != 0)
+        return 0;
+    in->next = in->buf;
+    do {
+        len = (long)read(in->fd, in->buf + in->left, CHUNK - in->left);
+        if (len < 0)
+            return -1;
+        in->left += (unsigned)len;
+    } while (len != 0 && in->left < CHUNK);
+    return len == 0 ? 1 : 0;
+}
+
+/* get a byte from the file, bail if end of file */
+#define bget(in) (in->left ? 0 : bload(in), \
+                  in->left ? (in->left--, *(in->next)++) : \
+                    bail("unexpected end of file on ", in->name))
+
+/* get a four-byte little-endian unsigned integer from file */
+local unsigned long bget4(bin *in)
+{
+    unsigned long val;
+
+    val = bget(in);
+    val += (unsigned long)(bget(in)) << 8;
+    val += (unsigned long)(bget(in)) << 16;
+    val += (unsigned long)(bget(in)) << 24;
+    return val;
+}
+
+/* skip bytes in file */
+local void bskip(bin *in, unsigned skip)
+{
+    /* check pointer */
+    if (in == NULL)
+        return;
+
+    /* easy case -- skip bytes in buffer */
+    if (skip <= in->left) {
+        in->left -= skip;
+        in->next += skip;
+        return;
+    }
+
+    /* skip what's in buffer, discard buffer contents */
+    skip -= in->left;
+    in->left = 0;
+
+    /* seek past multiples of CHUNK bytes */
+    if (skip > CHUNK) {
+        unsigned left;
+
+        left = skip & (CHUNK - 1);
+        if (left == 0) {
+            /* exact number of chunks: seek all the way minus one byte to check
+               for end-of-file with a read */
+            lseek(in->fd, skip - 1, SEEK_CUR);
+            if (read(in->fd, in->buf, 1) != 1)
+                bail("unexpected end of file on ", in->name);
+            return;
+        }
+
+        /* skip the integral chunks, update skip with remainder */
+        lseek(in->fd, skip - left, SEEK_CUR);
+        skip = left;
+    }
+
+    /* read more input and skip remainder */
+    bload(in);
+    if (skip > in->left)
+        bail("unexpected end of file on ", in->name);
+    in->left -= skip;
+    in->next += skip;
+}
+
+/* -- end of buffered input functions -- */
+
+/* skip the gzip header from file in */
+local void gzhead(bin *in)
+{
+    int flags;
+
+    /* verify gzip magic header and compression method */
+    if (bget(in) != 0x1f || bget(in) != 0x8b || bget(in) != 8)
+        bail(in->name, " is not a valid gzip file");
+
+    /* get and verify flags */
+    flags = bget(in);
+    if ((flags & 0xe0) != 0)
+        bail("unknown reserved bits set in ", in->name);
+
+    /* skip modification time, extra flags, and os */
+    bskip(in, 6);
+
+    /* skip extra field if present */
+    if (flags & 4) {
+        unsigned len;
+
+        len = bget(in);
+        len += (unsigned)(bget(in)) << 8;
+        bskip(in, len);
+    }
+
+    /* skip file name if present */
+    if (flags & 8)
+        while (bget(in) != 0)
+            ;
+
+    /* skip comment if present */
+    if (flags & 16)
+        while (bget(in) != 0)
+            ;
+
+    /* skip header crc if present */
+    if (flags & 2)
+        bskip(in, 2);
+}
+
+/* write a four-byte little-endian unsigned integer to out */
+local void put4(unsigned long val, FILE *out)
+{
+    putc(val & 0xff, out);
+    putc((val >> 8) & 0xff, out);
+    putc((val >> 16) & 0xff, out);
+    putc((val >> 24) & 0xff, out);
+}
+
+/* Load up zlib stream from buffered input, bail if end of file */
+local void zpull(z_streamp strm, bin *in)
+{
+    if (in->left == 0)
+        bload(in);
+    if (in->left == 0)
+        bail("unexpected end of file on ", in->name);
+    strm->avail_in = in->left;
+    strm->next_in = in->next;
+}
+
+/* Write header for gzip file to out and initialize trailer. */
+local void gzinit(unsigned long *crc, unsigned long *tot, FILE *out)
+{
+    fwrite("\x1f\x8b\x08\0\0\0\0\0\0\xff", 1, 10, out);
+    *crc = crc32(0L, Z_NULL, 0);
+    *tot = 0;
+}
+
+/* Copy the compressed data from name, zeroing the last block bit of the last
+   block if clr is true, and adding empty blocks as needed to get to a byte
+   boundary.  If clr is false, then the last block becomes the last block of
+   the output, and the gzip trailer is written.  crc and tot maintains the
+   crc and length (modulo 2^32) of the output for the trailer.  The resulting
+   gzip file is written to out.  gzinit() must be called before the first call
+   of gzcopy() to write the gzip header and to initialize crc and tot. */
+local void gzcopy(char *name, int clr, unsigned long *crc, unsigned long *tot,
+                  FILE *out)
+{
+    int ret;                /* return value from zlib functions */
+    int pos;                /* where the "last block" bit is in byte */
+    int last;               /* true if processing the last block */
+    bin *in;                /* buffered input file */
+    unsigned char *start;   /* start of compressed data in buffer */
+    unsigned char *junk;    /* buffer for uncompressed data -- discarded */
+    z_off_t len;            /* length of uncompressed data (support > 4 GB) */
+    z_stream strm;          /* zlib inflate stream */
+
+    /* open gzip file and skip header */
+    in = bopen(name);
+    if (in == NULL)
+        bail("could not open ", name);
+    gzhead(in);
+
+    /* allocate buffer for uncompressed data and initialize raw inflate
+       stream */
+    junk = malloc(CHUNK);
+    strm.zalloc = Z_NULL;
+    strm.zfree = Z_NULL;
+    strm.opaque = Z_NULL;
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit2(&strm, -15);
+    if (junk == NULL || ret != Z_OK)
+        bail("out of memory", "");
+
+    /* inflate and copy compressed data, clear last-block bit if requested */
+    len = 0;
+    zpull(&strm, in);
+    start = in->next;
+    last = start[0] & 1;
+    if (last && clr)
+        start[0] &= ~1;
+    strm.avail_out = 0;
+    for (;;) {
+        /* if input used and output done, write used input and get more */
+        if (strm.avail_in == 0 && strm.avail_out != 0) {
+            fwrite(start, 1, strm.next_in - start, out);
+            start = in->buf;
+            in->left = 0;
+            zpull(&strm, in);
+        }
+
+        /* decompress -- return early when end-of-block reached */
+        strm.avail_out = CHUNK;
+        strm.next_out = junk;
+        ret = inflate(&strm, Z_BLOCK);
+        switch (ret) {
+        case Z_MEM_ERROR:
+            bail("out of memory", "");
+        case Z_DATA_ERROR:
+            bail("invalid compressed data in ", in->name);
+        }
+
+        /* update length of uncompressed data */
+        len += CHUNK - strm.avail_out;
+
+        /* check for block boundary (only get this when block copied out) */
+        if (strm.data_type & 128) {
+            /* if that was the last block, then done */
+            if (last)
+                break;
+
+            /* number of unused bits in last byte */
+            pos = strm.data_type & 7;
+
+            /* find the next last-block bit */
+            if (pos != 0) {
+                /* next last-block bit is in last used byte */
+                pos = 0x100 >> pos;
+                last = strm.next_in[-1] & pos;
+                if (last && clr)
+                    in->buf[strm.next_in - in->buf - 1] &= ~pos;
+            }
+            else {
+                /* next last-block bit is in next unused byte */
+                if (strm.avail_in == 0) {
+                    /* don't have that byte yet -- get it */
+                    fwrite(start, 1, strm.next_in - start, out);
+                    start = in->buf;
+                    in->left = 0;
+                    zpull(&strm, in);
+                }
+                last = strm.next_in[0] & 1;
+                if (last && clr)
+                    in->buf[strm.next_in - in->buf] &= ~1;
+            }
+        }
+    }
+
+    /* update buffer with unused input */
+    in->left = strm.avail_in;
+    in->next = in->buf + (strm.next_in - in->buf);
+
+    /* copy used input, write empty blocks to get to byte boundary */
+    pos = strm.data_type & 7;
+    fwrite(start, 1, in->next - start - 1, out);
+    last = in->next[-1];
+    if (pos == 0 || !clr)
+        /* already at byte boundary, or last file: write last byte */
+        putc(last, out);
+    else {
+        /* append empty blocks to last byte */
+        last &= ((0x100 >> pos) - 1);       /* assure unused bits are zero */
+        if (pos & 1) {
+            /* odd -- append an empty stored block */
+            putc(last, out);
+            if (pos == 1)
+                putc(0, out);               /* two more bits in block header */
+            fwrite("\0\0\xff\xff", 1, 4, out);
+        }
+        else {
+            /* even -- append 1, 2, or 3 empty fixed blocks */
+            switch (pos) {
+            case 6:
+                putc(last | 8, out);
+                last = 0;
+            case 4:
+                putc(last | 0x20, out);
+                last = 0;
+            case 2:
+                putc(last | 0x80, out);
+                putc(0, out);
+            }
+        }
+    }
+
+    /* update crc and tot */
+    *crc = crc32_combine(*crc, bget4(in), len);
+    *tot += (unsigned long)len;
+
+    /* clean up */
+    inflateEnd(&strm);
+    free(junk);
+    bclose(in);
+
+    /* write trailer if this is the last gzip file */
+    if (!clr) {
+        put4(*crc, out);
+        put4(*tot, out);
+    }
+}
+
+/* join the gzip files on the command line, write result to stdout */
+int main(int argc, char **argv)
+{
+    unsigned long crc, tot;     /* running crc and total uncompressed length */
+
+    /* skip command name */
+    argc--;
+    argv++;
+
+    /* show usage if no arguments */
+    if (argc == 0) {
+        fputs("gzjoin usage: gzjoin f1.gz [f2.gz [f3.gz ...]] > fjoin.gz\n",
+              stderr);
+        return 0;
+    }
+
+    /* join gzip files on command line and write to stdout */
+    gzinit(&crc, &tot, stdout);
+    while (argc--)
+        gzcopy(*argv++, argc, &crc, &tot, stdout);
+
+    /* done */
+    return 0;
+}

ADDED   3rd_party/zlib/examples/gzlog.c
Index: 3rd_party/zlib/examples/gzlog.c
==================================================================
--- 3rd_party/zlib/examples/gzlog.c
+++ 3rd_party/zlib/examples/gzlog.c
@@ -0,0 +1,1059 @@
+/*
+ * gzlog.c
+ * Copyright (C) 2004, 2008, 2012, 2016 Mark Adler, all rights reserved
+ * For conditions of distribution and use, see copyright notice in gzlog.h
+ * version 2.2, 14 Aug 2012
+ */
+
+/*
+   gzlog provides a mechanism for frequently appending short strings to a gzip
+   file that is efficient both in execution time and compression ratio.  The
+   strategy is to write the short strings in an uncompressed form to the end of
+   the gzip file, only compressing when the amount of uncompressed data has
+   reached a given threshold.
+
+   gzlog also provides protection against interruptions in the process due to
+   system crashes.  The status of the operation is recorded in an extra field
+   in the gzip file, and is only updated once the gzip file is brought to a
+   valid state.  The last data to be appended or compressed is saved in an
+   auxiliary file, so that if the operation is interrupted, it can be completed
+   the next time an append operation is attempted.
+
+   gzlog maintains another auxiliary file with the last 32K of data from the
+   compressed portion, which is preloaded for the compression of the subsequent
+   data.  This minimizes the impact to the compression ratio of appending.
+ */
+
+/*
+   Operations Concept:
+
+   Files (log name "foo"):
+   foo.gz -- gzip file with the complete log
+   foo.add -- last message to append or last data to compress
+   foo.dict -- dictionary of the last 32K of data for next compression
+   foo.temp -- temporary dictionary file for compression after this one
+   foo.lock -- lock file for reading and writing the other files
+   foo.repairs -- log file for log file recovery operations (not compressed)
+
+   gzip file structure:
+   - fixed-length (no file name) header with extra field (see below)
+   - compressed data ending initially with empty stored block
+   - uncompressed data filling out originally empty stored block and
+     subsequent stored blocks as needed (16K max each)
+   - gzip trailer
+   - no junk at end (no other gzip streams)
+
+   When appending data, the information in the first three items above plus the
+   foo.add file are sufficient to recover an interrupted append operation.  The
+   extra field has the necessary information to restore the start of the last
+   stored block and determine where to append the data in the foo.add file, as
+   well as the crc and length of the gzip data before the append operation.
+
+   The foo.add file is created before the gzip file is marked for append, and
+   deleted after the gzip file is marked as complete.  So if the append
+   operation is interrupted, the data to add will still be there.  If due to
+   some external force, the foo.add file gets deleted between when the append
+   operation was interrupted and when recovery is attempted, the gzip file will
+   still be restored, but without the appended data.
+
+   When compressing data, the information in the first two items above plus the
+   foo.add file are sufficient to recover an interrupted compress operation.
+   The extra field has the necessary information to find the end of the
+   compressed data, and contains both the crc and length of just the compressed
+   data and of the complete set of data including the contents of the foo.add
+   file.
+
+   Again, the foo.add file is maintained during the compress operation in case
+   of an interruption.  If in the unlikely event the foo.add file with the data
+   to be compressed is missing due to some external force, a gzip file with
+   just the previous compressed data will be reconstructed.  In this case, all
+   of the data that was to be compressed is lost (approximately one megabyte).
+   This will not occur if all that happened was an interruption of the compress
+   operation.
+
+   The third state that is marked is the replacement of the old dictionary with
+   the new dictionary after a compress operation.  Once compression is
+   complete, the gzip file is marked as being in the replace state.  This
+   completes the gzip file, so an interrupt after being so marked does not
+   result in recompression.  Then the dictionary file is replaced, and the gzip
+   file is marked as completed.  This state prevents the possibility of
+   restarting compression with the wrong dictionary file.
+
+   All three operations are wrapped by a lock/unlock procedure.  In order to
+   gain exclusive access to the log files, first a foo.lock file must be
+   exclusively created.  When all operations are complete, the lock is
+   released by deleting the foo.lock file.  If when attempting to create the
+   lock file, it already exists and the modify time of the lock file is more
+   than five minutes old (set by the PATIENCE define below), then the old
+   lock file is considered stale and deleted, and the exclusive creation of
+   the lock file is retried.  To assure that there are no false assessments
+   of the staleness of the lock file, the operations periodically touch the
+   lock file to update the modified date.
+
+   Following is the definition of the extra field with all of the information
+   required to enable the above append and compress operations and their
+   recovery if interrupted.  Multi-byte values are stored little endian
+   (consistent with the gzip format).  File pointers are eight bytes long.
+   The crc's and lengths for the gzip trailer are four bytes long.  (Note that
+   the length at the end of a gzip file is used for error checking only, and
+   for large files is actually the length modulo 2^32.)  The stored block
+   length is two bytes long.  The gzip extra field two-byte identification is
+   "ap" for append.  It is assumed that writing the extra field to the file is
+   an "atomic" operation.  That is, either all of the extra field is written
+   to the file, or none of it is, if the operation is interrupted right at the
+   point of updating the extra field.  This is a reasonable assumption, since
+   the extra field is within the first 52 bytes of the file, which is smaller
+   than any expected block size for a mass storage device (usually 512 bytes or
+   larger).
+
+   Extra field (35 bytes):
+   - Pointer to first stored block length -- this points to the two-byte length
+     of the first stored block, which is followed by the two-byte, one's
+     complement of that length.  The stored block length is preceded by the
+     three-bit header of the stored block, which is the actual start of the
+     stored block in the deflate format.  See the bit offset field below.
+   - Pointer to the last stored block length.  This is the same as above, but
+     for the last stored block of the uncompressed data in the gzip file.
+     Initially this is the same as the first stored block length pointer.
+     When the stored block gets to 16K (see the MAX_STORE define), then a new
+     stored block as added, at which point the last stored block length pointer
+     is different from the first stored block length pointer.  When they are
+     different, the first bit of the last stored block header is eight bits, or
+     one byte back from the block length.
+   - Compressed data crc and length.  This is the crc and length of the data
+     that is in the compressed portion of the deflate stream.  These are used
+     only in the event that the foo.add file containing the data to compress is
+     lost after a compress operation is interrupted.
+   - Total data crc and length.  This is the crc and length of all of the data
+     stored in the gzip file, compressed and uncompressed.  It is used to
+     reconstruct the gzip trailer when compressing, as well as when recovering
+     interrupted operations.
+   - Final stored block length.  This is used to quickly find where to append,
+     and allows the restoration of the original final stored block state when
+     an append operation is interrupted.
+   - First stored block start as the number of bits back from the final stored
+     block first length byte.  This value is in the range of 3..10, and is
+     stored as the low three bits of the final byte of the extra field after
+     subtracting three (0..7).  This allows the last-block bit of the stored
+     block header to be updated when a new stored block is added, for the case
+     when the first stored block and the last stored block are the same.  (When
+     they are different, the numbers of bits back is known to be eight.)  This
+     also allows for new compressed data to be appended to the old compressed
+     data in the compress operation, overwriting the previous first stored
+     block, or for the compressed data to be terminated and a valid gzip file
+     reconstructed on the off chance that a compression operation was
+     interrupted and the data to compress in the foo.add file was deleted.
+   - The operation in process.  This is the next two bits in the last byte (the
+     bits under the mask 0x18).  The are interpreted as 0: nothing in process,
+     1: append in process, 2: compress in process, 3: replace in process.
+   - The top three bits of the last byte in the extra field are reserved and
+     are currently set to zero.
+
+   Main procedure:
+   - Exclusively create the foo.lock file using the O_CREAT and O_EXCL modes of
+     the system open() call.  If the modify time of an existing lock file is
+     more than PATIENCE seconds old, then the lock file is deleted and the
+     exclusive create is retried.
+   - Load the extra field from the foo.gz file, and see if an operation was in
+     progress but not completed.  If so, apply the recovery procedure below.
+   - Perform the append procedure with the provided data.
+   - If the uncompressed data in the foo.gz file is 1MB or more, apply the
+     compress procedure.
+   - Delete the foo.lock file.
+
+   Append procedure:
+   - Put what to append in the foo.add file so that the operation can be
+     restarted if this procedure is interrupted.
+   - Mark the foo.gz extra field with the append operation in progress.
+   + Restore the original last-block bit and stored block length of the last
+     stored block from the information in the extra field, in case a previous
+     append operation was interrupted.
+   - Append the provided data to the last stored block, creating new stored
+     blocks as needed and updating the stored blocks last-block bits and
+     lengths.
+   - Update the crc and length with the new data, and write the gzip trailer.
+   - Write over the extra field (with a single write operation) with the new
+     pointers, lengths, and crc's, and mark the gzip file as not in process.
+     Though there is still a foo.add file, it will be ignored since nothing
+     is in process.  If a foo.add file is leftover from a previously
+     completed operation, it is truncated when writing new data to it.
+   - Delete the foo.add file.
+
+   Compress and replace procedures:
+   - Read all of the uncompressed data in the stored blocks in foo.gz and write
+     it to foo.add.  Also write foo.temp with the last 32K of that data to
+     provide a dictionary for the next invocation of this procedure.
+   - Rewrite the extra field marking foo.gz with a compression in process.
+   * If there is no data provided to compress (due to a missing foo.add file
+     when recovering), reconstruct and truncate the foo.gz file to contain
+     only the previous compressed data and proceed to the step after the next
+     one.  Otherwise ...
+   - Compress the data with the dictionary in foo.dict, and write to the
+     foo.gz file starting at the bit immediately following the last previously
+     compressed block.  If there is no foo.dict, proceed anyway with the
+     compression at slightly reduced efficiency.  (For the foo.dict file to be
+     missing requires some external failure beyond simply the interruption of
+     a compress operation.)  During this process, the foo.lock file is
+     periodically touched to assure that that file is not considered stale by
+     another process before we're done.  The deflation is terminated with a
+     non-last empty static block (10 bits long), that is then located and
+     written over by a last-bit-set empty stored block.
+   - Append the crc and length of the data in the gzip file (previously
+     calculated during the append operations).
+   - Write over the extra field with the updated stored block offsets, bits
+     back, crc's, and lengths, and mark foo.gz as in process for a replacement
+     of the dictionary.
+   @ Delete the foo.add file.
+   - Replace foo.dict with foo.temp.
+   - Write over the extra field, marking foo.gz as complete.
+
+   Recovery procedure:
+   - If not a replace recovery, read in the foo.add file, and provide that data
+     to the appropriate recovery below.  If there is no foo.add file, provide
+     a zero data length to the recovery.  In that case, the append recovery
+     restores the foo.gz to the previous compressed + uncompressed data state.
+     For the the compress recovery, a missing foo.add file results in foo.gz
+     being restored to the previous compressed-only data state.
+   - Append recovery:
+     - Pick up append at + step above
+   - Compress recovery:
+     - Pick up compress at * step above
+   - Replace recovery:
+     - Pick up compress at @ step above
+   - Log the repair with a date stamp in foo.repairs
+ */
+
+#include <sys/types.h>
+#include <stdio.h>      /* rename, fopen, fprintf, fclose */
+#include <stdlib.h>     /* malloc, free */
+#include <string.h>     /* strlen, strrchr, strcpy, strncpy, strcmp */
+#include <fcntl.h>      /* open */
+#include <unistd.h>     /* lseek, read, write, close, unlink, sleep, */
+                        /* ftruncate, fsync */
+#include <errno.h>      /* errno */
+#include <time.h>       /* time, ctime */
+#include <sys/stat.h>   /* stat */
+#include <sys/time.h>   /* utimes */
+#include "zlib.h"       /* crc32 */
+
+#include "gzlog.h"      /* header for external access */
+
+#define local static
+typedef unsigned int uint;
+typedef unsigned long ulong;
+
+/* Macro for debugging to deterministically force recovery operations */
+#ifdef GZLOG_DEBUG
+    #include <setjmp.h>         /* longjmp */
+    jmp_buf gzlog_jump;         /* where to go back to */
+    int gzlog_bail = 0;         /* which point to bail at (1..8) */
+    int gzlog_count = -1;       /* number of times through to wait */
+#   define BAIL(n) do { if (n == gzlog_bail && gzlog_count-- == 0) \
+                            longjmp(gzlog_jump, gzlog_bail); } while (0)
+#else
+#   define BAIL(n)
+#endif
+
+/* how old the lock file can be in seconds before considering it stale */
+#define PATIENCE 300
+
+/* maximum stored block size in Kbytes -- must be in 1..63 */
+#define MAX_STORE 16
+
+/* number of stored Kbytes to trigger compression (must be >= 32 to allow
+   dictionary construction, and <= 204 * MAX_STORE, in order for >> 10 to
+   discard the stored block headers contribution of five bytes each) */
+#define TRIGGER 1024
+
+/* size of a deflate dictionary (this cannot be changed) */
+#define DICT 32768U
+
+/* values for the operation (2 bits) */
+#define NO_OP 0
+#define APPEND_OP 1
+#define COMPRESS_OP 2
+#define REPLACE_OP 3
+
+/* macros to extract little-endian integers from an unsigned byte buffer */
+#define PULL2(p) ((p)[0]+((uint)((p)[1])<<8))
+#define PULL4(p) (PULL2(p)+((ulong)PULL2(p+2)<<16))
+#define PULL8(p) (PULL4(p)+((off_t)PULL4(p+4)<<32))
+
+/* macros to store integers into a byte buffer in little-endian order */
+#define PUT2(p,a) do {(p)[0]=a;(p)[1]=(a)>>8;} while(0)
+#define PUT4(p,a) do {PUT2(p,a);PUT2(p+2,a>>16);} while(0)
+#define PUT8(p,a) do {PUT4(p,a);PUT4(p+4,a>>32);} while(0)
+
+/* internal structure for log information */
+#define LOGID "\106\035\172"    /* should be three non-zero characters */
+struct log {
+    char id[4];     /* contains LOGID to detect inadvertent overwrites */
+    int fd;         /* file descriptor for .gz file, opened read/write */
+    char *path;     /* allocated path, e.g. "/var/log/foo" or "foo" */
+    char *end;      /* end of path, for appending suffices such as ".gz" */
+    off_t first;    /* offset of first stored block first length byte */
+    int back;       /* location of first block id in bits back from first */
+    uint stored;    /* bytes currently in last stored block */
+    off_t last;     /* offset of last stored block first length byte */
+    ulong ccrc;     /* crc of compressed data */
+    ulong clen;     /* length (modulo 2^32) of compressed data */
+    ulong tcrc;     /* crc of total data */
+    ulong tlen;     /* length (modulo 2^32) of total data */
+    time_t lock;    /* last modify time of our lock file */
+};
+
+/* gzip header for gzlog */
+local unsigned char log_gzhead[] = {
+    0x1f, 0x8b,                 /* magic gzip id */
+    8,                          /* compression method is deflate */
+    4,                          /* there is an extra field (no file name) */
+    0, 0, 0, 0,                 /* no modification time provided */
+    0, 0xff,                    /* no extra flags, no OS specified */
+    39, 0, 'a', 'p', 35, 0      /* extra field with "ap" subfield */
+                                /* 35 is EXTRA, 39 is EXTRA + 4 */
+};
+
+#define HEAD sizeof(log_gzhead)     /* should be 16 */
+
+/* initial gzip extra field content (52 == HEAD + EXTRA + 1) */
+local unsigned char log_gzext[] = {
+    52, 0, 0, 0, 0, 0, 0, 0,    /* offset of first stored block length */
+    52, 0, 0, 0, 0, 0, 0, 0,    /* offset of last stored block length */
+    0, 0, 0, 0, 0, 0, 0, 0,     /* compressed data crc and length */
+    0, 0, 0, 0, 0, 0, 0, 0,     /* total data crc and length */
+    0, 0,                       /* final stored block data length */
+    5                           /* op is NO_OP, last bit 8 bits back */
+};
+
+#define EXTRA sizeof(log_gzext)     /* should be 35 */
+
+/* initial gzip data and trailer */
+local unsigned char log_gzbody[] = {
+    1, 0, 0, 0xff, 0xff,        /* empty stored block (last) */
+    0, 0, 0, 0,                 /* crc */
+    0, 0, 0, 0                  /* uncompressed length */
+};
+
+#define BODY sizeof(log_gzbody)
+
+/* Exclusively create foo.lock in order to negotiate exclusive access to the
+   foo.* files.  If the modify time of an existing lock file is greater than
+   PATIENCE seconds in the past, then consider the lock file to have been
+   abandoned, delete it, and try the exclusive create again.  Save the lock
+   file modify time for verification of ownership.  Return 0 on success, or -1
+   on failure, usually due to an access restriction or invalid path.  Note that
+   if stat() or unlink() fails, it may be due to another process noticing the
+   abandoned lock file a smidge sooner and deleting it, so those are not
+   flagged as an error. */
+local int log_lock(struct log *log)
+{
+    int fd;
+    struct stat st;
+
+    strcpy(log->end, ".lock");
+    while ((fd = open(log->path, O_CREAT | O_EXCL, 0644)) < 0) {
+        if (errno != EEXIST)
+            return -1;
+        if (stat(log->path, &st) == 0 && time(NULL) - st.st_mtime > PATIENCE) {
+            unlink(log->path);
+            continue;
+        }
+        sleep(2);       /* relinquish the CPU for two seconds while waiting */
+    }
+    close(fd);
+    if (stat(log->path, &st) == 0)
+        log->lock = st.st_mtime;
+    return 0;
+}
+
+/* Update the modify time of the lock file to now, in order to prevent another
+   task from thinking that the lock is stale.  Save the lock file modify time
+   for verification of ownership. */
+local void log_touch(struct log *log)
+{
+    struct stat st;
+
+    strcpy(log->end, ".lock");
+    utimes(log->path, NULL);
+    if (stat(log->path, &st) == 0)
+        log->lock = st.st_mtime;
+}
+
+/* Check the log file modify time against what is expected.  Return true if
+   this is not our lock.  If it is our lock, touch it to keep it. */
+local int log_check(struct log *log)
+{
+    struct stat st;
+
+    strcpy(log->end, ".lock");
+    if (stat(log->path, &st) || st.st_mtime != log->lock)
+        return 1;
+    log_touch(log);
+    return 0;
+}
+
+/* Unlock a previously acquired lock, but only if it's ours. */
+local void log_unlock(struct log *log)
+{
+    if (log_check(log))
+        return;
+    strcpy(log->end, ".lock");
+    unlink(log->path);
+    log->lock = 0;
+}
+
+/* Check the gzip header and read in the extra field, filling in the values in
+   the log structure.  Return op on success or -1 if the gzip header was not as
+   expected.  op is the current operation in progress last written to the extra
+   field.  This assumes that the gzip file has already been opened, with the
+   file descriptor log->fd. */
+local int log_head(struct log *log)
+{
+    int op;
+    unsigned char buf[HEAD + EXTRA];
+
+    if (lseek(log->fd, 0, SEEK_SET) < 0 ||
+        read(log->fd, buf, HEAD + EXTRA) != HEAD + EXTRA ||
+        memcmp(buf, log_gzhead, HEAD)) {
+        return -1;
+    }
+    log->first = PULL8(buf + HEAD);
+    log->last = PULL8(buf + HEAD + 8);
+    log->ccrc = PULL4(buf + HEAD + 16);
+    log->clen = PULL4(buf + HEAD + 20);
+    log->tcrc = PULL4(buf + HEAD + 24);
+    log->tlen = PULL4(buf + HEAD + 28);
+    log->stored = PULL2(buf + HEAD + 32);
+    log->back = 3 + (buf[HEAD + 34] & 7);
+    op = (buf[HEAD + 34] >> 3) & 3;
+    return op;
+}
+
+/* Write over the extra field contents, marking the operation as op.  Use fsync
+   to assure that the device is written to, and in the requested order.  This
+   operation, and only this operation, is assumed to be atomic in order to
+   assure that the log is recoverable in the event of an interruption at any
+   point in the process.  Return -1 if the write to foo.gz failed. */
+local int log_mark(struct log *log, int op)
+{
+    int ret;
+    unsigned char ext[EXTRA];
+
+    PUT8(ext, log->first);
+    PUT8(ext + 8, log->last);
+    PUT4(ext + 16, log->ccrc);
+    PUT4(ext + 20, log->clen);
+    PUT4(ext + 24, log->tcrc);
+    PUT4(ext + 28, log->tlen);
+    PUT2(ext + 32, log->stored);
+    ext[34] = log->back - 3 + (op << 3);
+    fsync(log->fd);
+    ret = lseek(log->fd, HEAD, SEEK_SET) < 0 ||
+          write(log->fd, ext, EXTRA) != EXTRA ? -1 : 0;
+    fsync(log->fd);
+    return ret;
+}
+
+/* Rewrite the last block header bits and subsequent zero bits to get to a byte
+   boundary, setting the last block bit if last is true, and then write the
+   remainder of the stored block header (length and one's complement).  Leave
+   the file pointer after the end of the last stored block data.  Return -1 if
+   there is a read or write failure on the foo.gz file */
+local int log_last(struct log *log, int last)
+{
+    int back, len, mask;
+    unsigned char buf[6];
+
+    /* determine the locations of the bytes and bits to modify */
+    back = log->last == log->first ? log->back : 8;
+    len = back > 8 ? 2 : 1;                 /* bytes back from log->last */
+    mask = 0x80 >> ((back - 1) & 7);        /* mask for block last-bit */
+
+    /* get the byte to modify (one or two back) into buf[0] -- don't need to
+       read the byte if the last-bit is eight bits back, since in that case
+       the entire byte will be modified */
+    buf[0] = 0;
+    if (back != 8 && (lseek(log->fd, log->last - len, SEEK_SET) < 0 ||
+                      read(log->fd, buf, 1) != 1))
+        return -1;
+
+    /* change the last-bit of the last stored block as requested -- note
+       that all bits above the last-bit are set to zero, per the type bits
+       of a stored block being 00 and per the convention that the bits to
+       bring the stream to a byte boundary are also zeros */
+    buf[1] = 0;
+    buf[2 - len] = (*buf & (mask - 1)) + (last ? mask : 0);
+
+    /* write the modified stored block header and lengths, move the file
+       pointer to after the last stored block data */
+    PUT2(buf + 2, log->stored);
+    PUT2(buf + 4, log->stored ^ 0xffff);
+    return lseek(log->fd, log->last - len, SEEK_SET) < 0 ||
+           write(log->fd, buf + 2 - len, len + 4) != len + 4 ||
+           lseek(log->fd, log->stored, SEEK_CUR) < 0 ? -1 : 0;
+}
+
+/* Append len bytes from data to the locked and open log file.  len may be zero
+   if recovering and no .add file was found.  In that case, the previous state
+   of the foo.gz file is restored.  The data is appended uncompressed in
+   deflate stored blocks.  Return -1 if there was an error reading or writing
+   the foo.gz file. */
+local int log_append(struct log *log, unsigned char *data, size_t len)
+{
+    uint put;
+    off_t end;
+    unsigned char buf[8];
+
+    /* set the last block last-bit and length, in case recovering an
+       interrupted append, then position the file pointer to append to the
+       block */
+    if (log_last(log, 1))
+        return -1;
+
+    /* append, adding stored blocks and updating the offset of the last stored
+       block as needed, and update the total crc and length */
+    while (len) {
+        /* append as much as we can to the last block */
+        put = (MAX_STORE << 10) - log->stored;
+        if (put > len)
+            put = (uint)len;
+        if (put) {
+            if (write(log->fd, data, put) != put)
+                return -1;
+            BAIL(1);
+            log->tcrc = crc32(log->tcrc, data, put);
+            log->tlen += put;
+            log->stored += put;
+            data += put;
+            len -= put;
+        }
+
+        /* if we need to, add a new empty stored block */
+        if (len) {
+            /* mark current block as not last */
+            if (log_last(log, 0))
+                return -1;
+
+            /* point to new, empty stored block */
+            log->last += 4 + log->stored + 1;
+            log->stored = 0;
+        }
+
+        /* mark last block as last, update its length */
+        if (log_last(log, 1))
+            return -1;
+        BAIL(2);
+    }
+
+    /* write the new crc and length trailer, and truncate just in case (could
+       be recovering from partial append with a missing foo.add file) */
+    PUT4(buf, log->tcrc);
+    PUT4(buf + 4, log->tlen);
+    if (write(log->fd, buf, 8) != 8 ||
+        (end = lseek(log->fd, 0, SEEK_CUR)) < 0 || ftruncate(log->fd, end))
+        return -1;
+
+    /* write the extra field, marking the log file as done, delete .add file */
+    if (log_mark(log, NO_OP))
+        return -1;
+    strcpy(log->end, ".add");
+    unlink(log->path);          /* ignore error, since may not exist */
+    return 0;
+}
+
+/* Replace the foo.dict file with the foo.temp file.  Also delete the foo.add
+   file, since the compress operation may have been interrupted before that was
+   done.  Returns 1 if memory could not be allocated, or -1 if reading or
+   writing foo.gz fails, or if the rename fails for some reason other than
+   foo.temp not existing.  foo.temp not existing is a permitted error, since
+   the replace operation may have been interrupted after the rename is done,
+   but before foo.gz is marked as complete. */
+local int log_replace(struct log *log)
+{
+    int ret;
+    char *dest;
+
+    /* delete foo.add file */
+    strcpy(log->end, ".add");
+    unlink(log->path);         /* ignore error, since may not exist */
+    BAIL(3);
+
+    /* rename foo.name to foo.dict, replacing foo.dict if it exists */
+    strcpy(log->end, ".dict");
+    dest = malloc(strlen(log->path) + 1);
+    if (dest == NULL)
+        return -2;
+    strcpy(dest, log->path);
+    strcpy(log->end, ".temp");
+    ret = rename(log->path, dest);
+    free(dest);
+    if (ret && errno != ENOENT)
+        return -1;
+    BAIL(4);
+
+    /* mark the foo.gz file as done */
+    return log_mark(log, NO_OP);
+}
+
+/* Compress the len bytes at data and append the compressed data to the
+   foo.gz deflate data immediately after the previous compressed data.  This
+   overwrites the previous uncompressed data, which was stored in foo.add
+   and is the data provided in data[0..len-1].  If this operation is
+   interrupted, it picks up at the start of this routine, with the foo.add
+   file read in again.  If there is no data to compress (len == 0), then we
+   simply terminate the foo.gz file after the previously compressed data,
+   appending a final empty stored block and the gzip trailer.  Return -1 if
+   reading or writing the log.gz file failed, or -2 if there was a memory
+   allocation failure. */
+local int log_compress(struct log *log, unsigned char *data, size_t len)
+{
+    int fd;
+    uint got, max;
+    ssize_t dict;
+    off_t end;
+    z_stream strm;
+    unsigned char buf[DICT];
+
+    /* compress and append compressed data */
+    if (len) {
+        /* set up for deflate, allocating memory */
+        strm.zalloc = Z_NULL;
+        strm.zfree = Z_NULL;
+        strm.opaque = Z_NULL;
+        if (deflateInit2(&strm, Z_DEFAULT_COMPRESSION, Z_DEFLATED, -15, 8,
+                         Z_DEFAULT_STRATEGY) != Z_OK)
+            return -2;
+
+        /* read in dictionary (last 32K of data that was compressed) */
+        strcpy(log->end, ".dict");
+        fd = open(log->path, O_RDONLY, 0);
+        if (fd >= 0) {
+            dict = read(fd, buf, DICT);
+            close(fd);
+            if (dict < 0) {
+                deflateEnd(&strm);
+                return -1;
+            }
+            if (dict)
+                deflateSetDictionary(&strm, buf, (uint)dict);
+        }
+        log_touch(log);
+
+        /* prime deflate with last bits of previous block, position write
+           pointer to write those bits and overwrite what follows */
+        if (lseek(log->fd, log->first - (log->back > 8 ? 2 : 1),
+                SEEK_SET) < 0 ||
+            read(log->fd, buf, 1) != 1 || lseek(log->fd, -1, SEEK_CUR) < 0) {
+            deflateEnd(&strm);
+            return -1;
+        }
+        deflatePrime(&strm, (8 - log->back) & 7, *buf);
+
+        /* compress, finishing with a partial non-last empty static block */
+        strm.next_in = data;
+        max = (((uint)0 - 1) >> 1) + 1; /* in case int smaller than size_t */
+        do {
+            strm.avail_in = len > max ? max : (uint)len;
+            len -= strm.avail_in;
+            do {
+                strm.avail_out = DICT;
+                strm.next_out = buf;
+                deflate(&strm, len ? Z_NO_FLUSH : Z_PARTIAL_FLUSH);
+                got = DICT - strm.avail_out;
+                if (got && write(log->fd, buf, got) != got) {
+                    deflateEnd(&strm);
+                    return -1;
+                }
+                log_touch(log);
+            } while (strm.avail_out == 0);
+        } while (len);
+        deflateEnd(&strm);
+        BAIL(5);
+
+        /* find start of empty static block -- scanning backwards the first one
+           bit is the second bit of the block, if the last byte is zero, then
+           we know the byte before that has a one in the top bit, since an
+           empty static block is ten bits long */
+        if ((log->first = lseek(log->fd, -1, SEEK_CUR)) < 0 ||
+            read(log->fd, buf, 1) != 1)
+            return -1;
+        log->first++;
+        if (*buf) {
+            log->back = 1;
+            while ((*buf & ((uint)1 << (8 - log->back++))) == 0)
+                ;       /* guaranteed to terminate, since *buf != 0 */
+        }
+        else
+            log->back = 10;
+
+        /* update compressed crc and length */
+        log->ccrc = log->tcrc;
+        log->clen = log->tlen;
+    }
+    else {
+        /* no data to compress -- fix up existing gzip stream */
+        log->tcrc = log->ccrc;
+        log->tlen = log->clen;
+    }
+
+    /* complete and truncate gzip stream */
+    log->last = log->first;
+    log->stored = 0;
+    PUT4(buf, log->tcrc);
+    PUT4(buf + 4, log->tlen);
+    if (log_last(log, 1) || write(log->fd, buf, 8) != 8 ||
+        (end = lseek(log->fd, 0, SEEK_CUR)) < 0 || ftruncate(log->fd, end))
+        return -1;
+    BAIL(6);
+
+    /* mark as being in the replace operation */
+    if (log_mark(log, REPLACE_OP))
+        return -1;
+
+    /* execute the replace operation and mark the file as done */
+    return log_replace(log);
+}
+
+/* log a repair record to the .repairs file */
+local void log_log(struct log *log, int op, char *record)
+{
+    time_t now;
+    FILE *rec;
+
+    now = time(NULL);
+    strcpy(log->end, ".repairs");
+    rec = fopen(log->path, "a");
+    if (rec == NULL)
+        return;
+    fprintf(rec, "%.24s %s recovery: %s\n", ctime(&now), op == APPEND_OP ?
+            "append" : (op == COMPRESS_OP ? "compress" : "replace"), record);
+    fclose(rec);
+    return;
+}
+
+/* Recover the interrupted operation op.  First read foo.add for recovering an
+   append or compress operation.  Return -1 if there was an error reading or
+   writing foo.gz or reading an existing foo.add, or -2 if there was a memory
+   allocation failure. */
+local int log_recover(struct log *log, int op)
+{
+    int fd, ret = 0;
+    unsigned char *data = NULL;
+    size_t len = 0;
+    struct stat st;
+
+    /* log recovery */
+    log_log(log, op, "start");
+
+    /* load foo.add file if expected and present */
+    if (op == APPEND_OP || op == COMPRESS_OP) {
+        strcpy(log->end, ".add");
+        if (stat(log->path, &st) == 0 && st.st_size) {
+            len = (size_t)(st.st_size);
+            if ((off_t)len != st.st_size ||
+                    (data = malloc(st.st_size)) == NULL) {
+                log_log(log, op, "allocation failure");
+                return -2;
+            }
+            if ((fd = open(log->path, O_RDONLY, 0)) < 0) {
+                log_log(log, op, ".add file read failure");
+                return -1;
+            }
+            ret = (size_t)read(fd, data, len) != len;
+            close(fd);
+            if (ret) {
+                log_log(log, op, ".add file read failure");
+                return -1;
+            }
+            log_log(log, op, "loaded .add file");
+        }
+        else
+            log_log(log, op, "missing .add file!");
+    }
+
+    /* recover the interrupted operation */
+    switch (op) {
+    case APPEND_OP:
+        ret = log_append(log, data, len);
+        break;
+    case COMPRESS_OP:
+        ret = log_compress(log, data, len);
+        break;
+    case REPLACE_OP:
+        ret = log_replace(log);
+    }
+
+    /* log status */
+    log_log(log, op, ret ? "failure" : "complete");
+
+    /* clean up */
+    if (data != NULL)
+        free(data);
+    return ret;
+}
+
+/* Close the foo.gz file (if open) and release the lock. */
+local void log_close(struct log *log)
+{
+    if (log->fd >= 0)
+        close(log->fd);
+    log->fd = -1;
+    log_unlock(log);
+}
+
+/* Open foo.gz, verify the header, and load the extra field contents, after
+   first creating the foo.lock file to gain exclusive access to the foo.*
+   files.  If foo.gz does not exist or is empty, then write the initial header,
+   extra, and body content of an empty foo.gz log file.  If there is an error
+   creating the lock file due to access restrictions, or an error reading or
+   writing the foo.gz file, or if the foo.gz file is not a proper log file for
+   this object (e.g. not a gzip file or does not contain the expected extra
+   field), then return true.  If there is an error, the lock is released.
+   Otherwise, the lock is left in place. */
+local int log_open(struct log *log)
+{
+    int op;
+
+    /* release open file resource if left over -- can occur if lock lost
+       between gzlog_open() and gzlog_write() */
+    if (log->fd >= 0)
+        close(log->fd);
+    log->fd = -1;
+
+    /* negotiate exclusive access */
+    if (log_lock(log) < 0)
+        return -1;
+
+    /* open the log file, foo.gz */
+    strcpy(log->end, ".gz");
+    log->fd = open(log->path, O_RDWR | O_CREAT, 0644);
+    if (log->fd < 0) {
+        log_close(log);
+        return -1;
+    }
+
+    /* if new, initialize foo.gz with an empty log, delete old dictionary */
+    if (lseek(log->fd, 0, SEEK_END) == 0) {
+        if (write(log->fd, log_gzhead, HEAD) != HEAD ||
+            write(log->fd, log_gzext, EXTRA) != EXTRA ||
+            write(log->fd, log_gzbody, BODY) != BODY) {
+            log_close(log);
+            return -1;
+        }
+        strcpy(log->end, ".dict");
+        unlink(log->path);
+    }
+
+    /* verify log file and load extra field information */
+    if ((op = log_head(log)) < 0) {
+        log_close(log);
+        return -1;
+    }
+
+    /* check for interrupted process and if so, recover */
+    if (op != NO_OP && log_recover(log, op)) {
+        log_close(log);
+        return -1;
+    }
+
+    /* touch the lock file to prevent another process from grabbing it */
+    log_touch(log);
+    return 0;
+}
+
+/* See gzlog.h for the description of the external methods below */
+gzlog *gzlog_open(char *path)
+{
+    size_t n;
+    struct log *log;
+
+    /* check arguments */
+    if (path == NULL || *path == 0)
+        return NULL;
+
+    /* allocate and initialize log structure */
+    log = malloc(sizeof(struct log));
+    if (log == NULL)
+        return NULL;
+    strcpy(log->id, LOGID);
+    log->fd = -1;
+
+    /* save path and end of path for name construction */
+    n = strlen(path);
+    log->path = malloc(n + 9);              /* allow for ".repairs" */
+    if (log->path == NULL) {
+        free(log);
+        return NULL;
+    }
+    strcpy(log->path, path);
+    log->end = log->path + n;
+
+    /* gain exclusive access and verify log file -- may perform a
+       recovery operation if needed */
+    if (log_open(log)) {
+        free(log->path);
+        free(log);
+        return NULL;
+    }
+
+    /* return pointer to log structure */
+    return log;
+}
+
+/* gzlog_compress() return values:
+    0: all good
+   -1: file i/o error (usually access issue)
+   -2: memory allocation failure
+   -3: invalid log pointer argument */
+int gzlog_compress(gzlog *logd)
+{
+    int fd, ret;
+    uint block;
+    size_t len, next;
+    unsigned char *data, buf[5];
+    struct log *log = logd;
+
+    /* check arguments */
+    if (log == NULL || strcmp(log->id, LOGID))
+        return -3;
+
+    /* see if we lost the lock -- if so get it again and reload the extra
+       field information (it probably changed), recover last operation if
+       necessary */
+    if (log_check(log) && log_open(log))
+        return -1;
+
+    /* create space for uncompressed data */
+    len = ((size_t)(log->last - log->first) & ~(((size_t)1 << 10) - 1)) +
+          log->stored;
+    if ((data = malloc(len)) == NULL)
+        return -2;
+
+    /* do statement here is just a cheap trick for error handling */
+    do {
+        /* read in the uncompressed data */
+        if (lseek(log->fd, log->first - 1, SEEK_SET) < 0)
+            break;
+        next = 0;
+        while (next < len) {
+            if (read(log->fd, buf, 5) != 5)
+                break;
+            block = PULL2(buf + 1);
+            if (next + block > len ||
+                read(log->fd, (char *)data + next, block) != block)
+                break;
+            next += block;
+        }
+        if (lseek(log->fd, 0, SEEK_CUR) != log->last + 4 + log->stored)
+            break;
+        log_touch(log);
+
+        /* write the uncompressed data to the .add file */
+        strcpy(log->end, ".add");
+        fd = open(log->path, O_WRONLY | O_CREAT | O_TRUNC, 0644);
+        if (fd < 0)
+            break;
+        ret = (size_t)write(fd, data, len) != len;
+        if (ret | close(fd))
+            break;
+        log_touch(log);
+
+        /* write the dictionary for the next compress to the .temp file */
+        strcpy(log->end, ".temp");
+        fd = open(log->path, O_WRONLY | O_CREAT | O_TRUNC, 0644);
+        if (fd < 0)
+            break;
+        next = DICT > len ? len : DICT;
+        ret = (size_t)write(fd, (char *)data + len - next, next) != next;
+        if (ret | close(fd))
+            break;
+        log_touch(log);
+
+        /* roll back to compressed data, mark the compress in progress */
+        log->last = log->first;
+        log->stored = 0;
+        if (log_mark(log, COMPRESS_OP))
+            break;
+        BAIL(7);
+
+        /* compress and append the data (clears mark) */
+        ret = log_compress(log, data, len);
+        free(data);
+        return ret;
+    } while (0);
+
+    /* broke out of do above on i/o error */
+    free(data);
+    return -1;
+}
+
+/* gzlog_write() return values:
+    0: all good
+   -1: file i/o error (usually access issue)
+   -2: memory allocation failure
+   -3: invalid log pointer argument */
+int gzlog_write(gzlog *logd, void *data, size_t len)
+{
+    int fd, ret;
+    struct log *log = logd;
+
+    /* check arguments */
+    if (log == NULL || strcmp(log->id, LOGID))
+        return -3;
+    if (data == NULL || len <= 0)
+        return 0;
+
+    /* see if we lost the lock -- if so get it again and reload the extra
+       field information (it probably changed), recover last operation if
+       necessary */
+    if (log_check(log) && log_open(log))
+        return -1;
+
+    /* create and write .add file */
+    strcpy(log->end, ".add");
+    fd = open(log->path, O_WRONLY | O_CREAT | O_TRUNC, 0644);
+    if (fd < 0)
+        return -1;
+    ret = (size_t)write(fd, data, len) != len;
+    if (ret | close(fd))
+        return -1;
+    log_touch(log);
+
+    /* mark log file with append in progress */
+    if (log_mark(log, APPEND_OP))
+        return -1;
+    BAIL(8);
+
+    /* append data (clears mark) */
+    if (log_append(log, data, len))
+        return -1;
+
+    /* check to see if it's time to compress -- if not, then done */
+    if (((log->last - log->first) >> 10) + (log->stored >> 10) < TRIGGER)
+        return 0;
+
+    /* time to compress */
+    return gzlog_compress(log);
+}
+
+/* gzlog_close() return values:
+    0: ok
+   -3: invalid log pointer argument */
+int gzlog_close(gzlog *logd)
+{
+    struct log *log = logd;
+
+    /* check arguments */
+    if (log == NULL || strcmp(log->id, LOGID))
+        return -3;
+
+    /* close the log file and release the lock */
+    log_close(log);
+
+    /* free structure and return */
+    if (log->path != NULL)
+        free(log->path);
+    strcpy(log->id, "bad");
+    free(log);
+    return 0;
+}

ADDED   3rd_party/zlib/examples/gzlog.h
Index: 3rd_party/zlib/examples/gzlog.h
==================================================================
--- 3rd_party/zlib/examples/gzlog.h
+++ 3rd_party/zlib/examples/gzlog.h
@@ -0,0 +1,91 @@
+/* gzlog.h
+  Copyright (C) 2004, 2008, 2012 Mark Adler, all rights reserved
+  version 2.2, 14 Aug 2012
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the author be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
+
+  Mark Adler    madler@alumni.caltech.edu
+ */
+
+/* Version History:
+   1.0  26 Nov 2004  First version
+   2.0  25 Apr 2008  Complete redesign for recovery of interrupted operations
+                     Interface changed slightly in that now path is a prefix
+                     Compression now occurs as needed during gzlog_write()
+                     gzlog_write() now always leaves the log file as valid gzip
+   2.1   8 Jul 2012  Fix argument checks in gzlog_compress() and gzlog_write()
+   2.2  14 Aug 2012  Clean up signed comparisons
+ */
+
+/*
+   The gzlog object allows writing short messages to a gzipped log file,
+   opening the log file locked for small bursts, and then closing it.  The log
+   object works by appending stored (uncompressed) data to the gzip file until
+   1 MB has been accumulated.  At that time, the stored data is compressed, and
+   replaces the uncompressed data in the file.  The log file is truncated to
+   its new size at that time.  After each write operation, the log file is a
+   valid gzip file that can decompressed to recover what was written.
+
+   The gzlog operations can be interupted at any point due to an application or
+   system crash, and the log file will be recovered the next time the log is
+   opened with gzlog_open().
+ */
+
+#ifndef GZLOG_H
+#define GZLOG_H
+
+/* gzlog object type */
+typedef void gzlog;
+
+/* Open a gzlog object, creating the log file if it does not exist.  Return
+   NULL on error.  Note that gzlog_open() could take a while to complete if it
+   has to wait to verify that a lock is stale (possibly for five minutes), or
+   if there is significant contention with other instantiations of this object
+   when locking the resource.  path is the prefix of the file names created by
+   this object.  If path is "foo", then the log file will be "foo.gz", and
+   other auxiliary files will be created and destroyed during the process:
+   "foo.dict" for a compression dictionary, "foo.temp" for a temporary (next)
+   dictionary, "foo.add" for data being added or compressed, "foo.lock" for the
+   lock file, and "foo.repairs" to log recovery operations performed due to
+   interrupted gzlog operations.  A gzlog_open() followed by a gzlog_close()
+   will recover a previously interrupted operation, if any. */
+gzlog *gzlog_open(char *path);
+
+/* Write to a gzlog object.  Return zero on success, -1 if there is a file i/o
+   error on any of the gzlog files (this should not happen if gzlog_open()
+   succeeded, unless the device has run out of space or leftover auxiliary
+   files have permissions or ownership that prevent their use), -2 if there is
+   a memory allocation failure, or -3 if the log argument is invalid (e.g. if
+   it was not created by gzlog_open()).  This function will write data to the
+   file uncompressed, until 1 MB has been accumulated, at which time that data
+   will be compressed.  The log file will be a valid gzip file upon successful
+   return. */
+int gzlog_write(gzlog *log, void *data, size_t len);
+
+/* Force compression of any uncompressed data in the log.  This should be used
+   sparingly, if at all.  The main application would be when a log file will
+   not be appended to again.  If this is used to compress frequently while
+   appending, it will both significantly increase the execution time and
+   reduce the compression ratio.  The return codes are the same as for
+   gzlog_write(). */
+int gzlog_compress(gzlog *log);
+
+/* Close a gzlog object.  Return zero on success, -3 if the log argument is
+   invalid.  The log object is freed, and so cannot be referenced again. */
+int gzlog_close(gzlog *log);
+
+#endif

ADDED   3rd_party/zlib/examples/zlib_how.html
Index: 3rd_party/zlib/examples/zlib_how.html
==================================================================
--- 3rd_party/zlib/examples/zlib_how.html
+++ 3rd_party/zlib/examples/zlib_how.html
@@ -0,0 +1,545 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN"
+  "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+<meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">
+<title>zlib Usage Example</title>
+<!--  Copyright (c) 2004, 2005 Mark Adler.  -->
+</head>
+<body bgcolor="#FFFFFF" text="#000000" link="#0000FF" vlink="#00A000">
+<h2 align="center"> zlib Usage Example </h2>
+We often get questions about how the <tt>deflate()</tt> and <tt>inflate()</tt> functions should be used.
+Users wonder when they should provide more input, when they should use more output,
+what to do with a <tt>Z_BUF_ERROR</tt>, how to make sure the process terminates properly, and
+so on.  So for those who have read <tt>zlib.h</tt> (a few times), and
+would like further edification, below is an annotated example in C of simple routines to compress and decompress
+from an input file to an output file using <tt>deflate()</tt> and <tt>inflate()</tt> respectively.  The
+annotations are interspersed between lines of the code.  So please read between the lines.
+We hope this helps explain some of the intricacies of <em>zlib</em>.
+<p>
+Without further adieu, here is the program <a href="zpipe.c"><tt>zpipe.c</tt></a>:
+<pre><b>
+/* zpipe.c: example of proper use of zlib's inflate() and deflate()
+   Not copyrighted -- provided to the public domain
+   Version 1.4  11 December 2005  Mark Adler */
+
+/* Version history:
+   1.0  30 Oct 2004  First version
+   1.1   8 Nov 2004  Add void casting for unused return values
+                     Use switch statement for inflate() return values
+   1.2   9 Nov 2004  Add assertions to document zlib guarantees
+   1.3   6 Apr 2005  Remove incorrect assertion in inf()
+   1.4  11 Dec 2005  Add hack to avoid MSDOS end-of-line conversions
+                     Avoid some compiler warnings for input and output buffers
+ */
+</b></pre><!-- -->
+We now include the header files for the required definitions.  From
+<tt>stdio.h</tt> we use <tt>fopen()</tt>, <tt>fread()</tt>, <tt>fwrite()</tt>,
+<tt>feof()</tt>, <tt>ferror()</tt>, and <tt>fclose()</tt> for file i/o, and
+<tt>fputs()</tt> for error messages.  From <tt>string.h</tt> we use
+<tt>strcmp()</tt> for command line argument processing.
+From <tt>assert.h</tt> we use the <tt>assert()</tt> macro.
+From <tt>zlib.h</tt>
+we use the basic compression functions <tt>deflateInit()</tt>,
+<tt>deflate()</tt>, and <tt>deflateEnd()</tt>, and the basic decompression
+functions <tt>inflateInit()</tt>, <tt>inflate()</tt>, and
+<tt>inflateEnd()</tt>.
+<pre><b>
+#include &lt;stdio.h&gt;
+#include &lt;string.h&gt;
+#include &lt;assert.h&gt;
+#include "zlib.h"
+</b></pre><!-- -->
+This is an ugly hack required to avoid corruption of the input and output data on
+Windows/MS-DOS systems.  Without this, those systems would assume that the input and output
+files are text, and try to convert the end-of-line characters from one standard to
+another.  That would corrupt binary data, and in particular would render the compressed data unusable.
+This sets the input and output to binary which suppresses the end-of-line conversions.
+<tt>SET_BINARY_MODE()</tt> will be used later on <tt>stdin</tt> and <tt>stdout</tt>, at the beginning of <tt>main()</tt>.
+<pre><b>
+#if defined(MSDOS) || defined(OS2) || defined(WIN32) || defined(__CYGWIN__)
+#  include &lt;fcntl.h&gt;
+#  include &lt;io.h&gt;
+#  define SET_BINARY_MODE(file) setmode(fileno(file), O_BINARY)
+#else
+#  define SET_BINARY_MODE(file)
+#endif
+</b></pre><!-- -->
+<tt>CHUNK</tt> is simply the buffer size for feeding data to and pulling data
+from the <em>zlib</em> routines.  Larger buffer sizes would be more efficient,
+especially for <tt>inflate()</tt>.  If the memory is available, buffers sizes
+on the order of 128K or 256K bytes should be used.
+<pre><b>
+#define CHUNK 16384
+</b></pre><!-- -->
+The <tt>def()</tt> routine compresses data from an input file to an output file.  The output data
+will be in the <em>zlib</em> format, which is different from the <em>gzip</em> or <em>zip</em>
+formats.  The <em>zlib</em> format has a very small header of only two bytes to identify it as
+a <em>zlib</em> stream and to provide decoding information, and a four-byte trailer with a fast
+check value to verify the integrity of the uncompressed data after decoding.
+<pre><b>
+/* Compress from file source to file dest until EOF on source.
+   def() returns Z_OK on success, Z_MEM_ERROR if memory could not be
+   allocated for processing, Z_STREAM_ERROR if an invalid compression
+   level is supplied, Z_VERSION_ERROR if the version of zlib.h and the
+   version of the library linked do not match, or Z_ERRNO if there is
+   an error reading or writing the files. */
+int def(FILE *source, FILE *dest, int level)
+{
+</b></pre>
+Here are the local variables for <tt>def()</tt>.  <tt>ret</tt> will be used for <em>zlib</em>
+return codes.  <tt>flush</tt> will keep track of the current flushing state for <tt>deflate()</tt>,
+which is either no flushing, or flush to completion after the end of the input file is reached.
+<tt>have</tt> is the amount of data returned from <tt>deflate()</tt>.  The <tt>strm</tt> structure
+is used to pass information to and from the <em>zlib</em> routines, and to maintain the
+<tt>deflate()</tt> state.  <tt>in</tt> and <tt>out</tt> are the input and output buffers for
+<tt>deflate()</tt>.
+<pre><b>
+    int ret, flush;
+    unsigned have;
+    z_stream strm;
+    unsigned char in[CHUNK];
+    unsigned char out[CHUNK];
+</b></pre><!-- -->
+The first thing we do is to initialize the <em>zlib</em> state for compression using
+<tt>deflateInit()</tt>.  This must be done before the first use of <tt>deflate()</tt>.
+The <tt>zalloc</tt>, <tt>zfree</tt>, and <tt>opaque</tt> fields in the <tt>strm</tt>
+structure must be initialized before calling <tt>deflateInit()</tt>.  Here they are
+set to the <em>zlib</em> constant <tt>Z_NULL</tt> to request that <em>zlib</em> use
+the default memory allocation routines.  An application may also choose to provide
+custom memory allocation routines here.  <tt>deflateInit()</tt> will allocate on the
+order of 256K bytes for the internal state.
+(See <a href="zlib_tech.html"><em>zlib Technical Details</em></a>.)
+<p>
+<tt>deflateInit()</tt> is called with a pointer to the structure to be initialized and
+the compression level, which is an integer in the range of -1 to 9.  Lower compression
+levels result in faster execution, but less compression.  Higher levels result in
+greater compression, but slower execution.  The <em>zlib</em> constant Z_DEFAULT_COMPRESSION,
+equal to -1,
+provides a good compromise between compression and speed and is equivalent to level 6.
+Level 0 actually does no compression at all, and in fact expands the data slightly to produce
+the <em>zlib</em> format (it is not a byte-for-byte copy of the input).
+More advanced applications of <em>zlib</em>
+may use <tt>deflateInit2()</tt> here instead.  Such an application may want to reduce how
+much memory will be used, at some price in compression.  Or it may need to request a
+<em>gzip</em> header and trailer instead of a <em>zlib</em> header and trailer, or raw
+encoding with no header or trailer at all.
+<p>
+We must check the return value of <tt>deflateInit()</tt> against the <em>zlib</em> constant
+<tt>Z_OK</tt> to make sure that it was able to
+allocate memory for the internal state, and that the provided arguments were valid.
+<tt>deflateInit()</tt> will also check that the version of <em>zlib</em> that the <tt>zlib.h</tt>
+file came from matches the version of <em>zlib</em> actually linked with the program.  This
+is especially important for environments in which <em>zlib</em> is a shared library.
+<p>
+Note that an application can initialize multiple, independent <em>zlib</em> streams, which can
+operate in parallel.  The state information maintained in the structure allows the <em>zlib</em>
+routines to be reentrant.
+<pre><b>
+    /* allocate deflate state */
+    strm.zalloc = Z_NULL;
+    strm.zfree = Z_NULL;
+    strm.opaque = Z_NULL;
+    ret = deflateInit(&amp;strm, level);
+    if (ret != Z_OK)
+        return ret;
+</b></pre><!-- -->
+With the pleasantries out of the way, now we can get down to business.  The outer <tt>do</tt>-loop
+reads all of the input file and exits at the bottom of the loop once end-of-file is reached.
+This loop contains the only call of <tt>deflate()</tt>.  So we must make sure that all of the
+input data has been processed and that all of the output data has been generated and consumed
+before we fall out of the loop at the bottom.
+<pre><b>
+    /* compress until end of file */
+    do {
+</b></pre>
+We start off by reading data from the input file.  The number of bytes read is put directly
+into <tt>avail_in</tt>, and a pointer to those bytes is put into <tt>next_in</tt>.  We also
+check to see if end-of-file on the input has been reached.  If we are at the end of file, then <tt>flush</tt> is set to the
+<em>zlib</em> constant <tt>Z_FINISH</tt>, which is later passed to <tt>deflate()</tt> to
+indicate that this is the last chunk of input data to compress.  We need to use <tt>feof()</tt>
+to check for end-of-file as opposed to seeing if fewer than <tt>CHUNK</tt> bytes have been read.  The
+reason is that if the input file length is an exact multiple of <tt>CHUNK</tt>, we will miss
+the fact that we got to the end-of-file, and not know to tell <tt>deflate()</tt> to finish
+up the compressed stream.  If we are not yet at the end of the input, then the <em>zlib</em>
+constant <tt>Z_NO_FLUSH</tt> will be passed to <tt>deflate</tt> to indicate that we are still
+in the middle of the uncompressed data.
+<p>
+If there is an error in reading from the input file, the process is aborted with
+<tt>deflateEnd()</tt> being called to free the allocated <em>zlib</em> state before returning
+the error.  We wouldn't want a memory leak, now would we?  <tt>deflateEnd()</tt> can be called
+at any time after the state has been initialized.  Once that's done, <tt>deflateInit()</tt> (or
+<tt>deflateInit2()</tt>) would have to be called to start a new compression process.  There is
+no point here in checking the <tt>deflateEnd()</tt> return code.  The deallocation can't fail.
+<pre><b>
+        strm.avail_in = fread(in, 1, CHUNK, source);
+        if (ferror(source)) {
+            (void)deflateEnd(&amp;strm);
+            return Z_ERRNO;
+        }
+        flush = feof(source) ? Z_FINISH : Z_NO_FLUSH;
+        strm.next_in = in;
+</b></pre><!-- -->
+The inner <tt>do</tt>-loop passes our chunk of input data to <tt>deflate()</tt>, and then
+keeps calling <tt>deflate()</tt> until it is done producing output.  Once there is no more
+new output, <tt>deflate()</tt> is guaranteed to have consumed all of the input, i.e.,
+<tt>avail_in</tt> will be zero.
+<pre><b>
+        /* run deflate() on input until output buffer not full, finish
+           compression if all of source has been read in */
+        do {
+</b></pre>
+Output space is provided to <tt>deflate()</tt> by setting <tt>avail_out</tt> to the number
+of available output bytes and <tt>next_out</tt> to a pointer to that space.
+<pre><b>
+            strm.avail_out = CHUNK;
+            strm.next_out = out;
+</b></pre>
+Now we call the compression engine itself, <tt>deflate()</tt>.  It takes as many of the
+<tt>avail_in</tt> bytes at <tt>next_in</tt> as it can process, and writes as many as
+<tt>avail_out</tt> bytes to <tt>next_out</tt>.  Those counters and pointers are then
+updated past the input data consumed and the output data written.  It is the amount of
+output space available that may limit how much input is consumed.
+Hence the inner loop to make sure that
+all of the input is consumed by providing more output space each time.  Since <tt>avail_in</tt>
+and <tt>next_in</tt> are updated by <tt>deflate()</tt>, we don't have to mess with those
+between <tt>deflate()</tt> calls until it's all used up.
+<p>
+The parameters to <tt>deflate()</tt> are a pointer to the <tt>strm</tt> structure containing
+the input and output information and the internal compression engine state, and a parameter
+indicating whether and how to flush data to the output.  Normally <tt>deflate</tt> will consume
+several K bytes of input data before producing any output (except for the header), in order
+to accumulate statistics on the data for optimum compression.  It will then put out a burst of
+compressed data, and proceed to consume more input before the next burst.  Eventually,
+<tt>deflate()</tt>
+must be told to terminate the stream, complete the compression with provided input data, and
+write out the trailer check value.  <tt>deflate()</tt> will continue to compress normally as long
+as the flush parameter is <tt>Z_NO_FLUSH</tt>.  Once the <tt>Z_FINISH</tt> parameter is provided,
+<tt>deflate()</tt> will begin to complete the compressed output stream.  However depending on how
+much output space is provided, <tt>deflate()</tt> may have to be called several times until it
+has provided the complete compressed stream, even after it has consumed all of the input.  The flush
+parameter must continue to be <tt>Z_FINISH</tt> for those subsequent calls.
+<p>
+There are other values of the flush parameter that are used in more advanced applications.  You can
+force <tt>deflate()</tt> to produce a burst of output that encodes all of the input data provided
+so far, even if it wouldn't have otherwise, for example to control data latency on a link with
+compressed data.  You can also ask that <tt>deflate()</tt> do that as well as erase any history up to
+that point so that what follows can be decompressed independently, for example for random access
+applications.  Both requests will degrade compression by an amount depending on how often such
+requests are made.
+<p>
+<tt>deflate()</tt> has a return value that can indicate errors, yet we do not check it here.  Why
+not?  Well, it turns out that <tt>deflate()</tt> can do no wrong here.  Let's go through
+<tt>deflate()</tt>'s return values and dispense with them one by one.  The possible values are
+<tt>Z_OK</tt>, <tt>Z_STREAM_END</tt>, <tt>Z_STREAM_ERROR</tt>, or <tt>Z_BUF_ERROR</tt>.  <tt>Z_OK</tt>
+is, well, ok.  <tt>Z_STREAM_END</tt> is also ok and will be returned for the last call of
+<tt>deflate()</tt>.  This is already guaranteed by calling <tt>deflate()</tt> with <tt>Z_FINISH</tt>
+until it has no more output.  <tt>Z_STREAM_ERROR</tt> is only possible if the stream is not
+initialized properly, but we did initialize it properly.  There is no harm in checking for
+<tt>Z_STREAM_ERROR</tt> here, for example to check for the possibility that some
+other part of the application inadvertently clobbered the memory containing the <em>zlib</em> state.
+<tt>Z_BUF_ERROR</tt> will be explained further below, but
+suffice it to say that this is simply an indication that <tt>deflate()</tt> could not consume
+more input or produce more output.  <tt>deflate()</tt> can be called again with more output space
+or more available input, which it will be in this code.
+<pre><b>
+            ret = deflate(&amp;strm, flush);    /* no bad return value */
+            assert(ret != Z_STREAM_ERROR);  /* state not clobbered */
+</b></pre>
+Now we compute how much output <tt>deflate()</tt> provided on the last call, which is the
+difference between how much space was provided before the call, and how much output space
+is still available after the call.  Then that data, if any, is written to the output file.
+We can then reuse the output buffer for the next call of <tt>deflate()</tt>.  Again if there
+is a file i/o error, we call <tt>deflateEnd()</tt> before returning to avoid a memory leak.
+<pre><b>
+            have = CHUNK - strm.avail_out;
+            if (fwrite(out, 1, have, dest) != have || ferror(dest)) {
+                (void)deflateEnd(&amp;strm);
+                return Z_ERRNO;
+            }
+</b></pre>
+The inner <tt>do</tt>-loop is repeated until the last <tt>deflate()</tt> call fails to fill the
+provided output buffer.  Then we know that <tt>deflate()</tt> has done as much as it can with
+the provided input, and that all of that input has been consumed.  We can then fall out of this
+loop and reuse the input buffer.
+<p>
+The way we tell that <tt>deflate()</tt> has no more output is by seeing that it did not fill
+the output buffer, leaving <tt>avail_out</tt> greater than zero.  However suppose that
+<tt>deflate()</tt> has no more output, but just so happened to exactly fill the output buffer!
+<tt>avail_out</tt> is zero, and we can't tell that <tt>deflate()</tt> has done all it can.
+As far as we know, <tt>deflate()</tt>
+has more output for us.  So we call it again.  But now <tt>deflate()</tt> produces no output
+at all, and <tt>avail_out</tt> remains unchanged as <tt>CHUNK</tt>.  That <tt>deflate()</tt> call
+wasn't able to do anything, either consume input or produce output, and so it returns
+<tt>Z_BUF_ERROR</tt>.  (See, I told you I'd cover this later.)  However this is not a problem at
+all.  Now we finally have the desired indication that <tt>deflate()</tt> is really done,
+and so we drop out of the inner loop to provide more input to <tt>deflate()</tt>.
+<p>
+With <tt>flush</tt> set to <tt>Z_FINISH</tt>, this final set of <tt>deflate()</tt> calls will
+complete the output stream.  Once that is done, subsequent calls of <tt>deflate()</tt> would return
+<tt>Z_STREAM_ERROR</tt> if the flush parameter is not <tt>Z_FINISH</tt>, and do no more processing
+until the state is reinitialized.
+<p>
+Some applications of <em>zlib</em> have two loops that call <tt>deflate()</tt>
+instead of the single inner loop we have here.  The first loop would call
+without flushing and feed all of the data to <tt>deflate()</tt>.  The second loop would call
+<tt>deflate()</tt> with no more
+data and the <tt>Z_FINISH</tt> parameter to complete the process.  As you can see from this
+example, that can be avoided by simply keeping track of the current flush state.
+<pre><b>
+        } while (strm.avail_out == 0);
+        assert(strm.avail_in == 0);     /* all input will be used */
+</b></pre><!-- -->
+Now we check to see if we have already processed all of the input file.  That information was
+saved in the <tt>flush</tt> variable, so we see if that was set to <tt>Z_FINISH</tt>.  If so,
+then we're done and we fall out of the outer loop.  We're guaranteed to get <tt>Z_STREAM_END</tt>
+from the last <tt>deflate()</tt> call, since we ran it until the last chunk of input was
+consumed and all of the output was generated.
+<pre><b>
+        /* done when last data in file processed */
+    } while (flush != Z_FINISH);
+    assert(ret == Z_STREAM_END);        /* stream will be complete */
+</b></pre><!-- -->
+The process is complete, but we still need to deallocate the state to avoid a memory leak
+(or rather more like a memory hemorrhage if you didn't do this).  Then
+finally we can return with a happy return value.
+<pre><b>
+    /* clean up and return */
+    (void)deflateEnd(&amp;strm);
+    return Z_OK;
+}
+</b></pre><!-- -->
+Now we do the same thing for decompression in the <tt>inf()</tt> routine. <tt>inf()</tt>
+decompresses what is hopefully a valid <em>zlib</em> stream from the input file and writes the
+uncompressed data to the output file.  Much of the discussion above for <tt>def()</tt>
+applies to <tt>inf()</tt> as well, so the discussion here will focus on the differences between
+the two.
+<pre><b>
+/* Decompress from file source to file dest until stream ends or EOF.
+   inf() returns Z_OK on success, Z_MEM_ERROR if memory could not be
+   allocated for processing, Z_DATA_ERROR if the deflate data is
+   invalid or incomplete, Z_VERSION_ERROR if the version of zlib.h and
+   the version of the library linked do not match, or Z_ERRNO if there
+   is an error reading or writing the files. */
+int inf(FILE *source, FILE *dest)
+{
+</b></pre>
+The local variables have the same functionality as they do for <tt>def()</tt>.  The
+only difference is that there is no <tt>flush</tt> variable, since <tt>inflate()</tt>
+can tell from the <em>zlib</em> stream itself when the stream is complete.
+<pre><b>
+    int ret;
+    unsigned have;
+    z_stream strm;
+    unsigned char in[CHUNK];
+    unsigned char out[CHUNK];
+</b></pre><!-- -->
+The initialization of the state is the same, except that there is no compression level,
+of course, and two more elements of the structure are initialized.  <tt>avail_in</tt>
+and <tt>next_in</tt> must be initialized before calling <tt>inflateInit()</tt>.  This
+is because the application has the option to provide the start of the zlib stream in
+order for <tt>inflateInit()</tt> to have access to information about the compression
+method to aid in memory allocation.  In the current implementation of <em>zlib</em>
+(up through versions 1.2.x), the method-dependent memory allocations are deferred to the first call of
+<tt>inflate()</tt> anyway.  However those fields must be initialized since later versions
+of <em>zlib</em> that provide more compression methods may take advantage of this interface.
+In any case, no decompression is performed by <tt>inflateInit()</tt>, so the
+<tt>avail_out</tt> and <tt>next_out</tt> fields do not need to be initialized before calling.
+<p>
+Here <tt>avail_in</tt> is set to zero and <tt>next_in</tt> is set to <tt>Z_NULL</tt> to
+indicate that no input data is being provided.
+<pre><b>
+    /* allocate inflate state */
+    strm.zalloc = Z_NULL;
+    strm.zfree = Z_NULL;
+    strm.opaque = Z_NULL;
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit(&amp;strm);
+    if (ret != Z_OK)
+        return ret;
+</b></pre><!-- -->
+The outer <tt>do</tt>-loop decompresses input until <tt>inflate()</tt> indicates
+that it has reached the end of the compressed data and has produced all of the uncompressed
+output.  This is in contrast to <tt>def()</tt> which processes all of the input file.
+If end-of-file is reached before the compressed data self-terminates, then the compressed
+data is incomplete and an error is returned.
+<pre><b>
+    /* decompress until deflate stream ends or end of file */
+    do {
+</b></pre>
+We read input data and set the <tt>strm</tt> structure accordingly.  If we've reached the
+end of the input file, then we leave the outer loop and report an error, since the
+compressed data is incomplete.  Note that we may read more data than is eventually consumed
+by <tt>inflate()</tt>, if the input file continues past the <em>zlib</em> stream.
+For applications where <em>zlib</em> streams are embedded in other data, this routine would
+need to be modified to return the unused data, or at least indicate how much of the input
+data was not used, so the application would know where to pick up after the <em>zlib</em> stream.
+<pre><b>
+        strm.avail_in = fread(in, 1, CHUNK, source);
+        if (ferror(source)) {
+            (void)inflateEnd(&amp;strm);
+            return Z_ERRNO;
+        }
+        if (strm.avail_in == 0)
+            break;
+        strm.next_in = in;
+</b></pre><!-- -->
+The inner <tt>do</tt>-loop has the same function it did in <tt>def()</tt>, which is to
+keep calling <tt>inflate()</tt> until has generated all of the output it can with the
+provided input.
+<pre><b>
+        /* run inflate() on input until output buffer not full */
+        do {
+</b></pre>
+Just like in <tt>def()</tt>, the same output space is provided for each call of <tt>inflate()</tt>.
+<pre><b>
+            strm.avail_out = CHUNK;
+            strm.next_out = out;
+</b></pre>
+Now we run the decompression engine itself.  There is no need to adjust the flush parameter, since
+the <em>zlib</em> format is self-terminating. The main difference here is that there are
+return values that we need to pay attention to.  <tt>Z_DATA_ERROR</tt>
+indicates that <tt>inflate()</tt> detected an error in the <em>zlib</em> compressed data format,
+which means that either the data is not a <em>zlib</em> stream to begin with, or that the data was
+corrupted somewhere along the way since it was compressed.  The other error to be processed is
+<tt>Z_MEM_ERROR</tt>, which can occur since memory allocation is deferred until <tt>inflate()</tt>
+needs it, unlike <tt>deflate()</tt>, whose memory is allocated at the start by <tt>deflateInit()</tt>.
+<p>
+Advanced applications may use
+<tt>deflateSetDictionary()</tt> to prime <tt>deflate()</tt> with a set of likely data to improve the
+first 32K or so of compression.  This is noted in the <em>zlib</em> header, so <tt>inflate()</tt>
+requests that that dictionary be provided before it can start to decompress.  Without the dictionary,
+correct decompression is not possible.  For this routine, we have no idea what the dictionary is,
+so the <tt>Z_NEED_DICT</tt> indication is converted to a <tt>Z_DATA_ERROR</tt>.
+<p>
+<tt>inflate()</tt> can also return <tt>Z_STREAM_ERROR</tt>, which should not be possible here,
+but could be checked for as noted above for <tt>def()</tt>.  <tt>Z_BUF_ERROR</tt> does not need to be
+checked for here, for the same reasons noted for <tt>def()</tt>.  <tt>Z_STREAM_END</tt> will be
+checked for later.
+<pre><b>
+            ret = inflate(&amp;strm, Z_NO_FLUSH);
+            assert(ret != Z_STREAM_ERROR);  /* state not clobbered */
+            switch (ret) {
+            case Z_NEED_DICT:
+                ret = Z_DATA_ERROR;     /* and fall through */
+            case Z_DATA_ERROR:
+            case Z_MEM_ERROR:
+                (void)inflateEnd(&amp;strm);
+                return ret;
+            }
+</b></pre>
+The output of <tt>inflate()</tt> is handled identically to that of <tt>deflate()</tt>.
+<pre><b>
+            have = CHUNK - strm.avail_out;
+            if (fwrite(out, 1, have, dest) != have || ferror(dest)) {
+                (void)inflateEnd(&amp;strm);
+                return Z_ERRNO;
+            }
+</b></pre>
+The inner <tt>do</tt>-loop ends when <tt>inflate()</tt> has no more output as indicated
+by not filling the output buffer, just as for <tt>deflate()</tt>.  In this case, we cannot
+assert that <tt>strm.avail_in</tt> will be zero, since the deflate stream may end before the file
+does.
+<pre><b>
+        } while (strm.avail_out == 0);
+</b></pre><!-- -->
+The outer <tt>do</tt>-loop ends when <tt>inflate()</tt> reports that it has reached the
+end of the input <em>zlib</em> stream, has completed the decompression and integrity
+check, and has provided all of the output.  This is indicated by the <tt>inflate()</tt>
+return value <tt>Z_STREAM_END</tt>.  The inner loop is guaranteed to leave <tt>ret</tt>
+equal to <tt>Z_STREAM_END</tt> if the last chunk of the input file read contained the end
+of the <em>zlib</em> stream.  So if the return value is not <tt>Z_STREAM_END</tt>, the
+loop continues to read more input.
+<pre><b>
+        /* done when inflate() says it's done */
+    } while (ret != Z_STREAM_END);
+</b></pre><!-- -->
+At this point, decompression successfully completed, or we broke out of the loop due to no
+more data being available from the input file.  If the last <tt>inflate()</tt> return value
+is not <tt>Z_STREAM_END</tt>, then the <em>zlib</em> stream was incomplete and a data error
+is returned.  Otherwise, we return with a happy return value.  Of course, <tt>inflateEnd()</tt>
+is called first to avoid a memory leak.
+<pre><b>
+    /* clean up and return */
+    (void)inflateEnd(&amp;strm);
+    return ret == Z_STREAM_END ? Z_OK : Z_DATA_ERROR;
+}
+</b></pre><!-- -->
+That ends the routines that directly use <em>zlib</em>.  The following routines make this
+a command-line program by running data through the above routines from <tt>stdin</tt> to
+<tt>stdout</tt>, and handling any errors reported by <tt>def()</tt> or <tt>inf()</tt>.
+<p>
+<tt>zerr()</tt> is used to interpret the possible error codes from <tt>def()</tt>
+and <tt>inf()</tt>, as detailed in their comments above, and print out an error message.
+Note that these are only a subset of the possible return values from <tt>deflate()</tt>
+and <tt>inflate()</tt>.
+<pre><b>
+/* report a zlib or i/o error */
+void zerr(int ret)
+{
+    fputs("zpipe: ", stderr);
+    switch (ret) {
+    case Z_ERRNO:
+        if (ferror(stdin))
+            fputs("error reading stdin\n", stderr);
+        if (ferror(stdout))
+            fputs("error writing stdout\n", stderr);
+        break;
+    case Z_STREAM_ERROR:
+        fputs("invalid compression level\n", stderr);
+        break;
+    case Z_DATA_ERROR:
+        fputs("invalid or incomplete deflate data\n", stderr);
+        break;
+    case Z_MEM_ERROR:
+        fputs("out of memory\n", stderr);
+        break;
+    case Z_VERSION_ERROR:
+        fputs("zlib version mismatch!\n", stderr);
+    }
+}
+</b></pre><!-- -->
+Here is the <tt>main()</tt> routine used to test <tt>def()</tt> and <tt>inf()</tt>.  The
+<tt>zpipe</tt> command is simply a compression pipe from <tt>stdin</tt> to <tt>stdout</tt>, if
+no arguments are given, or it is a decompression pipe if <tt>zpipe -d</tt> is used.  If any other
+arguments are provided, no compression or decompression is performed.  Instead a usage
+message is displayed.  Examples are <tt>zpipe < foo.txt > foo.txt.z</tt> to compress, and
+<tt>zpipe -d < foo.txt.z > foo.txt</tt> to decompress.
+<pre><b>
+/* compress or decompress from stdin to stdout */
+int main(int argc, char **argv)
+{
+    int ret;
+
+    /* avoid end-of-line conversions */
+    SET_BINARY_MODE(stdin);
+    SET_BINARY_MODE(stdout);
+
+    /* do compression if no arguments */
+    if (argc == 1) {
+        ret = def(stdin, stdout, Z_DEFAULT_COMPRESSION);
+        if (ret != Z_OK)
+            zerr(ret);
+        return ret;
+    }
+
+    /* do decompression if -d specified */
+    else if (argc == 2 &amp;&amp; strcmp(argv[1], "-d") == 0) {
+        ret = inf(stdin, stdout);
+        if (ret != Z_OK)
+            zerr(ret);
+        return ret;
+    }
+
+    /* otherwise, report usage */
+    else {
+        fputs("zpipe usage: zpipe [-d] &lt; source &gt; dest\n", stderr);
+        return 1;
+    }
+}
+</b></pre>
+<hr>
+<i>Copyright (c) 2004, 2005 by Mark Adler<br>Last modified 11 December 2005</i>
+</body>
+</html>

ADDED   3rd_party/zlib/examples/zpipe.c
Index: 3rd_party/zlib/examples/zpipe.c
==================================================================
--- 3rd_party/zlib/examples/zpipe.c
+++ 3rd_party/zlib/examples/zpipe.c
@@ -0,0 +1,205 @@
+/* zpipe.c: example of proper use of zlib's inflate() and deflate()
+   Not copyrighted -- provided to the public domain
+   Version 1.4  11 December 2005  Mark Adler */
+
+/* Version history:
+   1.0  30 Oct 2004  First version
+   1.1   8 Nov 2004  Add void casting for unused return values
+                     Use switch statement for inflate() return values
+   1.2   9 Nov 2004  Add assertions to document zlib guarantees
+   1.3   6 Apr 2005  Remove incorrect assertion in inf()
+   1.4  11 Dec 2005  Add hack to avoid MSDOS end-of-line conversions
+                     Avoid some compiler warnings for input and output buffers
+ */
+
+#include <stdio.h>
+#include <string.h>
+#include <assert.h>
+#include "zlib.h"
+
+#if defined(MSDOS) || defined(OS2) || defined(WIN32) || defined(__CYGWIN__)
+#  include <fcntl.h>
+#  include <io.h>
+#  define SET_BINARY_MODE(file) setmode(fileno(file), O_BINARY)
+#else
+#  define SET_BINARY_MODE(file)
+#endif
+
+#define CHUNK 16384
+
+/* Compress from file source to file dest until EOF on source.
+   def() returns Z_OK on success, Z_MEM_ERROR if memory could not be
+   allocated for processing, Z_STREAM_ERROR if an invalid compression
+   level is supplied, Z_VERSION_ERROR if the version of zlib.h and the
+   version of the library linked do not match, or Z_ERRNO if there is
+   an error reading or writing the files. */
+int def(FILE *source, FILE *dest, int level)
+{
+    int ret, flush;
+    unsigned have;
+    z_stream strm;
+    unsigned char in[CHUNK];
+    unsigned char out[CHUNK];
+
+    /* allocate deflate state */
+    strm.zalloc = Z_NULL;
+    strm.zfree = Z_NULL;
+    strm.opaque = Z_NULL;
+    ret = deflateInit(&strm, level);
+    if (ret != Z_OK)
+        return ret;
+
+    /* compress until end of file */
+    do {
+        strm.avail_in = fread(in, 1, CHUNK, source);
+        if (ferror(source)) {
+            (void)deflateEnd(&strm);
+            return Z_ERRNO;
+        }
+        flush = feof(source) ? Z_FINISH : Z_NO_FLUSH;
+        strm.next_in = in;
+
+        /* run deflate() on input until output buffer not full, finish
+           compression if all of source has been read in */
+        do {
+            strm.avail_out = CHUNK;
+            strm.next_out = out;
+            ret = deflate(&strm, flush);    /* no bad return value */
+            assert(ret != Z_STREAM_ERROR);  /* state not clobbered */
+            have = CHUNK - strm.avail_out;
+            if (fwrite(out, 1, have, dest) != have || ferror(dest)) {
+                (void)deflateEnd(&strm);
+                return Z_ERRNO;
+            }
+        } while (strm.avail_out == 0);
+        assert(strm.avail_in == 0);     /* all input will be used */
+
+        /* done when last data in file processed */
+    } while (flush != Z_FINISH);
+    assert(ret == Z_STREAM_END);        /* stream will be complete */
+
+    /* clean up and return */
+    (void)deflateEnd(&strm);
+    return Z_OK;
+}
+
+/* Decompress from file source to file dest until stream ends or EOF.
+   inf() returns Z_OK on success, Z_MEM_ERROR if memory could not be
+   allocated for processing, Z_DATA_ERROR if the deflate data is
+   invalid or incomplete, Z_VERSION_ERROR if the version of zlib.h and
+   the version of the library linked do not match, or Z_ERRNO if there
+   is an error reading or writing the files. */
+int inf(FILE *source, FILE *dest)
+{
+    int ret;
+    unsigned have;
+    z_stream strm;
+    unsigned char in[CHUNK];
+    unsigned char out[CHUNK];
+
+    /* allocate inflate state */
+    strm.zalloc = Z_NULL;
+    strm.zfree = Z_NULL;
+    strm.opaque = Z_NULL;
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit(&strm);
+    if (ret != Z_OK)
+        return ret;
+
+    /* decompress until deflate stream ends or end of file */
+    do {
+        strm.avail_in = fread(in, 1, CHUNK, source);
+        if (ferror(source)) {
+            (void)inflateEnd(&strm);
+            return Z_ERRNO;
+        }
+        if (strm.avail_in == 0)
+            break;
+        strm.next_in = in;
+
+        /* run inflate() on input until output buffer not full */
+        do {
+            strm.avail_out = CHUNK;
+            strm.next_out = out;
+            ret = inflate(&strm, Z_NO_FLUSH);
+            assert(ret != Z_STREAM_ERROR);  /* state not clobbered */
+            switch (ret) {
+            case Z_NEED_DICT:
+                ret = Z_DATA_ERROR;     /* and fall through */
+            case Z_DATA_ERROR:
+            case Z_MEM_ERROR:
+                (void)inflateEnd(&strm);
+                return ret;
+            }
+            have = CHUNK - strm.avail_out;
+            if (fwrite(out, 1, have, dest) != have || ferror(dest)) {
+                (void)inflateEnd(&strm);
+                return Z_ERRNO;
+            }
+        } while (strm.avail_out == 0);
+
+        /* done when inflate() says it's done */
+    } while (ret != Z_STREAM_END);
+
+    /* clean up and return */
+    (void)inflateEnd(&strm);
+    return ret == Z_STREAM_END ? Z_OK : Z_DATA_ERROR;
+}
+
+/* report a zlib or i/o error */
+void zerr(int ret)
+{
+    fputs("zpipe: ", stderr);
+    switch (ret) {
+    case Z_ERRNO:
+        if (ferror(stdin))
+            fputs("error reading stdin\n", stderr);
+        if (ferror(stdout))
+            fputs("error writing stdout\n", stderr);
+        break;
+    case Z_STREAM_ERROR:
+        fputs("invalid compression level\n", stderr);
+        break;
+    case Z_DATA_ERROR:
+        fputs("invalid or incomplete deflate data\n", stderr);
+        break;
+    case Z_MEM_ERROR:
+        fputs("out of memory\n", stderr);
+        break;
+    case Z_VERSION_ERROR:
+        fputs("zlib version mismatch!\n", stderr);
+    }
+}
+
+/* compress or decompress from stdin to stdout */
+int main(int argc, char **argv)
+{
+    int ret;
+
+    /* avoid end-of-line conversions */
+    SET_BINARY_MODE(stdin);
+    SET_BINARY_MODE(stdout);
+
+    /* do compression if no arguments */
+    if (argc == 1) {
+        ret = def(stdin, stdout, Z_DEFAULT_COMPRESSION);
+        if (ret != Z_OK)
+            zerr(ret);
+        return ret;
+    }
+
+    /* do decompression if -d specified */
+    else if (argc == 2 && strcmp(argv[1], "-d") == 0) {
+        ret = inf(stdin, stdout);
+        if (ret != Z_OK)
+            zerr(ret);
+        return ret;
+    }
+
+    /* otherwise, report usage */
+    else {
+        fputs("zpipe usage: zpipe [-d] < source > dest\n", stderr);
+        return 1;
+    }
+}

ADDED   3rd_party/zlib/examples/zran.c
Index: 3rd_party/zlib/examples/zran.c
==================================================================
--- 3rd_party/zlib/examples/zran.c
+++ 3rd_party/zlib/examples/zran.c
@@ -0,0 +1,409 @@
+/* zran.c -- example of zlib/gzip stream indexing and random access
+ * Copyright (C) 2005, 2012 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+   Version 1.1  29 Sep 2012  Mark Adler */
+
+/* Version History:
+ 1.0  29 May 2005  First version
+ 1.1  29 Sep 2012  Fix memory reallocation error
+ */
+
+/* Illustrate the use of Z_BLOCK, inflatePrime(), and inflateSetDictionary()
+   for random access of a compressed file.  A file containing a zlib or gzip
+   stream is provided on the command line.  The compressed stream is decoded in
+   its entirety, and an index built with access points about every SPAN bytes
+   in the uncompressed output.  The compressed file is left open, and can then
+   be read randomly, having to decompress on the average SPAN/2 uncompressed
+   bytes before getting to the desired block of data.
+
+   An access point can be created at the start of any deflate block, by saving
+   the starting file offset and bit of that block, and the 32K bytes of
+   uncompressed data that precede that block.  Also the uncompressed offset of
+   that block is saved to provide a referece for locating a desired starting
+   point in the uncompressed stream.  build_index() works by decompressing the
+   input zlib or gzip stream a block at a time, and at the end of each block
+   deciding if enough uncompressed data has gone by to justify the creation of
+   a new access point.  If so, that point is saved in a data structure that
+   grows as needed to accommodate the points.
+
+   To use the index, an offset in the uncompressed data is provided, for which
+   the latest access point at or preceding that offset is located in the index.
+   The input file is positioned to the specified location in the index, and if
+   necessary the first few bits of the compressed data is read from the file.
+   inflate is initialized with those bits and the 32K of uncompressed data, and
+   the decompression then proceeds until the desired offset in the file is
+   reached.  Then the decompression continues to read the desired uncompressed
+   data from the file.
+
+   Another approach would be to generate the index on demand.  In that case,
+   requests for random access reads from the compressed data would try to use
+   the index, but if a read far enough past the end of the index is required,
+   then further index entries would be generated and added.
+
+   There is some fair bit of overhead to starting inflation for the random
+   access, mainly copying the 32K byte dictionary.  So if small pieces of the
+   file are being accessed, it would make sense to implement a cache to hold
+   some lookahead and avoid many calls to extract() for small lengths.
+
+   Another way to build an index would be to use inflateCopy().  That would
+   not be constrained to have access points at block boundaries, but requires
+   more memory per access point, and also cannot be saved to file due to the
+   use of pointers in the state.  The approach here allows for storage of the
+   index in a file.
+ */
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include "zlib.h"
+
+#define local static
+
+#define SPAN 1048576L       /* desired distance between access points */
+#define WINSIZE 32768U      /* sliding window size */
+#define CHUNK 16384         /* file input buffer size */
+
+/* access point entry */
+struct point {
+    off_t out;          /* corresponding offset in uncompressed data */
+    off_t in;           /* offset in input file of first full byte */
+    int bits;           /* number of bits (1-7) from byte at in - 1, or 0 */
+    unsigned char window[WINSIZE];  /* preceding 32K of uncompressed data */
+};
+
+/* access point list */
+struct access {
+    int have;           /* number of list entries filled in */
+    int size;           /* number of list entries allocated */
+    struct point *list; /* allocated list */
+};
+
+/* Deallocate an index built by build_index() */
+local void free_index(struct access *index)
+{
+    if (index != NULL) {
+        free(index->list);
+        free(index);
+    }
+}
+
+/* Add an entry to the access point list.  If out of memory, deallocate the
+   existing list and return NULL. */
+local struct access *addpoint(struct access *index, int bits,
+    off_t in, off_t out, unsigned left, unsigned char *window)
+{
+    struct point *next;
+
+    /* if list is empty, create it (start with eight points) */
+    if (index == NULL) {
+        index = malloc(sizeof(struct access));
+        if (index == NULL) return NULL;
+        index->list = malloc(sizeof(struct point) << 3);
+        if (index->list == NULL) {
+            free(index);
+            return NULL;
+        }
+        index->size = 8;
+        index->have = 0;
+    }
+
+    /* if list is full, make it bigger */
+    else if (index->have == index->size) {
+        index->size <<= 1;
+        next = realloc(index->list, sizeof(struct point) * index->size);
+        if (next == NULL) {
+            free_index(index);
+            return NULL;
+        }
+        index->list = next;
+    }
+
+    /* fill in entry and increment how many we have */
+    next = index->list + index->have;
+    next->bits = bits;
+    next->in = in;
+    next->out = out;
+    if (left)
+        memcpy(next->window, window + WINSIZE - left, left);
+    if (left < WINSIZE)
+        memcpy(next->window + left, window, WINSIZE - left);
+    index->have++;
+
+    /* return list, possibly reallocated */
+    return index;
+}
+
+/* Make one entire pass through the compressed stream and build an index, with
+   access points about every span bytes of uncompressed output -- span is
+   chosen to balance the speed of random access against the memory requirements
+   of the list, about 32K bytes per access point.  Note that data after the end
+   of the first zlib or gzip stream in the file is ignored.  build_index()
+   returns the number of access points on success (>= 1), Z_MEM_ERROR for out
+   of memory, Z_DATA_ERROR for an error in the input file, or Z_ERRNO for a
+   file read error.  On success, *built points to the resulting index. */
+local int build_index(FILE *in, off_t span, struct access **built)
+{
+    int ret;
+    off_t totin, totout;        /* our own total counters to avoid 4GB limit */
+    off_t last;                 /* totout value of last access point */
+    struct access *index;       /* access points being generated */
+    z_stream strm;
+    unsigned char input[CHUNK];
+    unsigned char window[WINSIZE];
+
+    /* initialize inflate */
+    strm.zalloc = Z_NULL;
+    strm.zfree = Z_NULL;
+    strm.opaque = Z_NULL;
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit2(&strm, 47);      /* automatic zlib or gzip decoding */
+    if (ret != Z_OK)
+        return ret;
+
+    /* inflate the input, maintain a sliding window, and build an index -- this
+       also validates the integrity of the compressed data using the check
+       information at the end of the gzip or zlib stream */
+    totin = totout = last = 0;
+    index = NULL;               /* will be allocated by first addpoint() */
+    strm.avail_out = 0;
+    do {
+        /* get some compressed data from input file */
+        strm.avail_in = fread(input, 1, CHUNK, in);
+        if (ferror(in)) {
+            ret = Z_ERRNO;
+            goto build_index_error;
+        }
+        if (strm.avail_in == 0) {
+            ret = Z_DATA_ERROR;
+            goto build_index_error;
+        }
+        strm.next_in = input;
+
+        /* process all of that, or until end of stream */
+        do {
+            /* reset sliding window if necessary */
+            if (strm.avail_out == 0) {
+                strm.avail_out = WINSIZE;
+                strm.next_out = window;
+            }
+
+            /* inflate until out of input, output, or at end of block --
+               update the total input and output counters */
+            totin += strm.avail_in;
+            totout += strm.avail_out;
+            ret = inflate(&strm, Z_BLOCK);      /* return at end of block */
+            totin -= strm.avail_in;
+            totout -= strm.avail_out;
+            if (ret == Z_NEED_DICT)
+                ret = Z_DATA_ERROR;
+            if (ret == Z_MEM_ERROR || ret == Z_DATA_ERROR)
+                goto build_index_error;
+            if (ret == Z_STREAM_END)
+                break;
+
+            /* if at end of block, consider adding an index entry (note that if
+               data_type indicates an end-of-block, then all of the
+               uncompressed data from that block has been delivered, and none
+               of the compressed data after that block has been consumed,
+               except for up to seven bits) -- the totout == 0 provides an
+               entry point after the zlib or gzip header, and assures that the
+               index always has at least one access point; we avoid creating an
+               access point after the last block by checking bit 6 of data_type
+             */
+            if ((strm.data_type & 128) && !(strm.data_type & 64) &&
+                (totout == 0 || totout - last > span)) {
+                index = addpoint(index, strm.data_type & 7, totin,
+                                 totout, strm.avail_out, window);
+                if (index == NULL) {
+                    ret = Z_MEM_ERROR;
+                    goto build_index_error;
+                }
+                last = totout;
+            }
+        } while (strm.avail_in != 0);
+    } while (ret != Z_STREAM_END);
+
+    /* clean up and return index (release unused entries in list) */
+    (void)inflateEnd(&strm);
+    index->list = realloc(index->list, sizeof(struct point) * index->have);
+    index->size = index->have;
+    *built = index;
+    return index->size;
+
+    /* return error */
+  build_index_error:
+    (void)inflateEnd(&strm);
+    if (index != NULL)
+        free_index(index);
+    return ret;
+}
+
+/* Use the index to read len bytes from offset into buf, return bytes read or
+   negative for error (Z_DATA_ERROR or Z_MEM_ERROR).  If data is requested past
+   the end of the uncompressed data, then extract() will return a value less
+   than len, indicating how much as actually read into buf.  This function
+   should not return a data error unless the file was modified since the index
+   was generated.  extract() may also return Z_ERRNO if there is an error on
+   reading or seeking the input file. */
+local int extract(FILE *in, struct access *index, off_t offset,
+                  unsigned char *buf, int len)
+{
+    int ret, skip;
+    z_stream strm;
+    struct point *here;
+    unsigned char input[CHUNK];
+    unsigned char discard[WINSIZE];
+
+    /* proceed only if something reasonable to do */
+    if (len < 0)
+        return 0;
+
+    /* find where in stream to start */
+    here = index->list;
+    ret = index->have;
+    while (--ret && here[1].out <= offset)
+        here++;
+
+    /* initialize file and inflate state to start there */
+    strm.zalloc = Z_NULL;
+    strm.zfree = Z_NULL;
+    strm.opaque = Z_NULL;
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit2(&strm, -15);         /* raw inflate */
+    if (ret != Z_OK)
+        return ret;
+    ret = fseeko(in, here->in - (here->bits ? 1 : 0), SEEK_SET);
+    if (ret == -1)
+        goto extract_ret;
+    if (here->bits) {
+        ret = getc(in);
+        if (ret == -1) {
+            ret = ferror(in) ? Z_ERRNO : Z_DATA_ERROR;
+            goto extract_ret;
+        }
+        (void)inflatePrime(&strm, here->bits, ret >> (8 - here->bits));
+    }
+    (void)inflateSetDictionary(&strm, here->window, WINSIZE);
+
+    /* skip uncompressed bytes until offset reached, then satisfy request */
+    offset -= here->out;
+    strm.avail_in = 0;
+    skip = 1;                               /* while skipping to offset */
+    do {
+        /* define where to put uncompressed data, and how much */
+        if (offset == 0 && skip) {          /* at offset now */
+            strm.avail_out = len;
+            strm.next_out = buf;
+            skip = 0;                       /* only do this once */
+        }
+        if (offset > WINSIZE) {             /* skip WINSIZE bytes */
+            strm.avail_out = WINSIZE;
+            strm.next_out = discard;
+            offset -= WINSIZE;
+        }
+        else if (offset != 0) {             /* last skip */
+            strm.avail_out = (unsigned)offset;
+            strm.next_out = discard;
+            offset = 0;
+        }
+
+        /* uncompress until avail_out filled, or end of stream */
+        do {
+            if (strm.avail_in == 0) {
+                strm.avail_in = fread(input, 1, CHUNK, in);
+                if (ferror(in)) {
+                    ret = Z_ERRNO;
+                    goto extract_ret;
+                }
+                if (strm.avail_in == 0) {
+                    ret = Z_DATA_ERROR;
+                    goto extract_ret;
+                }
+                strm.next_in = input;
+            }
+            ret = inflate(&strm, Z_NO_FLUSH);       /* normal inflate */
+            if (ret == Z_NEED_DICT)
+                ret = Z_DATA_ERROR;
+            if (ret == Z_MEM_ERROR || ret == Z_DATA_ERROR)
+                goto extract_ret;
+            if (ret == Z_STREAM_END)
+                break;
+        } while (strm.avail_out != 0);
+
+        /* if reach end of stream, then don't keep trying to get more */
+        if (ret == Z_STREAM_END)
+            break;
+
+        /* do until offset reached and requested data read, or stream ends */
+    } while (skip);
+
+    /* compute number of uncompressed bytes read after offset */
+    ret = skip ? 0 : len - strm.avail_out;
+
+    /* clean up and return bytes read or error */
+  extract_ret:
+    (void)inflateEnd(&strm);
+    return ret;
+}
+
+/* Demonstrate the use of build_index() and extract() by processing the file
+   provided on the command line, and the extracting 16K from about 2/3rds of
+   the way through the uncompressed output, and writing that to stdout. */
+int main(int argc, char **argv)
+{
+    int len;
+    off_t offset;
+    FILE *in;
+    struct access *index = NULL;
+    unsigned char buf[CHUNK];
+
+    /* open input file */
+    if (argc != 2) {
+        fprintf(stderr, "usage: zran file.gz\n");
+        return 1;
+    }
+    in = fopen(argv[1], "rb");
+    if (in == NULL) {
+        fprintf(stderr, "zran: could not open %s for reading\n", argv[1]);
+        return 1;
+    }
+
+    /* build index */
+    len = build_index(in, SPAN, &index);
+    if (len < 0) {
+        fclose(in);
+        switch (len) {
+        case Z_MEM_ERROR:
+            fprintf(stderr, "zran: out of memory\n");
+            break;
+        case Z_DATA_ERROR:
+            fprintf(stderr, "zran: compressed data error in %s\n", argv[1]);
+            break;
+        case Z_ERRNO:
+            fprintf(stderr, "zran: read error on %s\n", argv[1]);
+            break;
+        default:
+            fprintf(stderr, "zran: error %d while building index\n", len);
+        }
+        return 1;
+    }
+    fprintf(stderr, "zran: built index with %d access points\n", len);
+
+    /* use index by reading some bytes from an arbitrary offset */
+    offset = (index->list[index->have - 1].out << 1) / 3;
+    len = extract(in, index, offset, buf, CHUNK);
+    if (len < 0)
+        fprintf(stderr, "zran: extraction failed: %s error\n",
+                len == Z_MEM_ERROR ? "out of memory" : "input corrupted");
+    else {
+        fwrite(buf, 1, len, stdout);
+        fprintf(stderr, "zran: extracted %d bytes at %llu\n", len, offset);
+    }
+
+    /* clean up and exit */
+    free_index(index);
+    fclose(in);
+    return 0;
+}

ADDED   3rd_party/zlib/gzclose.c
Index: 3rd_party/zlib/gzclose.c
==================================================================
--- 3rd_party/zlib/gzclose.c
+++ 3rd_party/zlib/gzclose.c
@@ -0,0 +1,25 @@
+/* gzclose.c -- zlib gzclose() function
+ * Copyright (C) 2004, 2010 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+#include "gzguts.h"
+
+/* gzclose() is in a separate file so that it is linked in only if it is used.
+   That way the other gzclose functions can be used instead to avoid linking in
+   unneeded compression or decompression routines. */
+int ZEXPORT gzclose(file)
+    gzFile file;
+{
+#ifndef NO_GZCOMPRESS
+    gz_statep state;
+
+    if (file == NULL)
+        return Z_STREAM_ERROR;
+    state = (gz_statep)file;
+
+    return state->mode == GZ_READ ? gzclose_r(file) : gzclose_w(file);
+#else
+    return gzclose_r(file);
+#endif
+}

ADDED   3rd_party/zlib/gzguts.h
Index: 3rd_party/zlib/gzguts.h
==================================================================
--- 3rd_party/zlib/gzguts.h
+++ 3rd_party/zlib/gzguts.h
@@ -0,0 +1,218 @@
+/* gzguts.h -- zlib internal header definitions for gz* operations
+ * Copyright (C) 2004, 2005, 2010, 2011, 2012, 2013, 2016 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+#ifdef _LARGEFILE64_SOURCE
+#  ifndef _LARGEFILE_SOURCE
+#    define _LARGEFILE_SOURCE 1
+#  endif
+#  ifdef _FILE_OFFSET_BITS
+#    undef _FILE_OFFSET_BITS
+#  endif
+#endif
+
+#ifdef HAVE_HIDDEN
+#  define ZLIB_INTERNAL __attribute__((visibility ("hidden")))
+#else
+#  define ZLIB_INTERNAL
+#endif
+
+#include <stdio.h>
+#include "zlib.h"
+#ifdef STDC
+#  include <string.h>
+#  include <stdlib.h>
+#  include <limits.h>
+#endif
+
+#ifndef _POSIX_SOURCE
+#  define _POSIX_SOURCE
+#endif
+#include <fcntl.h>
+
+#ifdef _WIN32
+#  include <stddef.h>
+#endif
+
+#if defined(__TURBOC__) || defined(_MSC_VER) || defined(_WIN32)
+#  include <io.h>
+#endif
+
+#if defined(_WIN32) || defined(__CYGWIN__)
+#  define WIDECHAR
+#endif
+
+#ifdef WINAPI_FAMILY
+#  define open _open
+#  define read _read
+#  define write _write
+#  define close _close
+#endif
+
+#ifdef NO_DEFLATE       /* for compatibility with old definition */
+#  define NO_GZCOMPRESS
+#endif
+
+#if defined(STDC99) || (defined(__TURBOC__) && __TURBOC__ >= 0x550)
+#  ifndef HAVE_VSNPRINTF
+#    define HAVE_VSNPRINTF
+#  endif
+#endif
+
+#if defined(__CYGWIN__)
+#  ifndef HAVE_VSNPRINTF
+#    define HAVE_VSNPRINTF
+#  endif
+#endif
+
+#if defined(MSDOS) && defined(__BORLANDC__) && (BORLANDC > 0x410)
+#  ifndef HAVE_VSNPRINTF
+#    define HAVE_VSNPRINTF
+#  endif
+#endif
+
+#ifndef HAVE_VSNPRINTF
+#  ifdef MSDOS
+/* vsnprintf may exist on some MS-DOS compilers (DJGPP?),
+   but for now we just assume it doesn't. */
+#    define NO_vsnprintf
+#  endif
+#  ifdef __TURBOC__
+#    define NO_vsnprintf
+#  endif
+#  ifdef WIN32
+/* In Win32, vsnprintf is available as the "non-ANSI" _vsnprintf. */
+#    if !defined(vsnprintf) && !defined(NO_vsnprintf)
+#      if !defined(_MSC_VER) || ( defined(_MSC_VER) && _MSC_VER < 1500 )
+#         define vsnprintf _vsnprintf
+#      endif
+#    endif
+#  endif
+#  ifdef __SASC
+#    define NO_vsnprintf
+#  endif
+#  ifdef VMS
+#    define NO_vsnprintf
+#  endif
+#  ifdef __OS400__
+#    define NO_vsnprintf
+#  endif
+#  ifdef __MVS__
+#    define NO_vsnprintf
+#  endif
+#endif
+
+/* unlike snprintf (which is required in C99), _snprintf does not guarantee
+   null termination of the result -- however this is only used in gzlib.c where
+   the result is assured to fit in the space provided */
+#if defined(_MSC_VER) && _MSC_VER < 1900
+#  define snprintf _snprintf
+#endif
+
+#ifndef local
+#  define local static
+#endif
+/* since "static" is used to mean two completely different things in C, we
+   define "local" for the non-static meaning of "static", for readability
+   (compile with -Dlocal if your debugger can't find static symbols) */
+
+/* gz* functions always use library allocation functions */
+#ifndef STDC
+  extern voidp  malloc OF((uInt size));
+  extern void   free   OF((voidpf ptr));
+#endif
+
+/* get errno and strerror definition */
+#if defined UNDER_CE
+#  include <windows.h>
+#  define zstrerror() gz_strwinerror((DWORD)GetLastError())
+#else
+#  ifndef NO_STRERROR
+#    include <errno.h>
+#    define zstrerror() strerror(errno)
+#  else
+#    define zstrerror() "stdio error (consult errno)"
+#  endif
+#endif
+
+/* provide prototypes for these when building zlib without LFS */
+#if !defined(_LARGEFILE64_SOURCE) || _LFS64_LARGEFILE-0 == 0
+    ZEXTERN gzFile ZEXPORT gzopen64 OF((const char *, const char *));
+    ZEXTERN z_off64_t ZEXPORT gzseek64 OF((gzFile, z_off64_t, int));
+    ZEXTERN z_off64_t ZEXPORT gztell64 OF((gzFile));
+    ZEXTERN z_off64_t ZEXPORT gzoffset64 OF((gzFile));
+#endif
+
+/* default memLevel */
+#if MAX_MEM_LEVEL >= 8
+#  define DEF_MEM_LEVEL 8
+#else
+#  define DEF_MEM_LEVEL  MAX_MEM_LEVEL
+#endif
+
+/* default i/o buffer size -- double this for output when reading (this and
+   twice this must be able to fit in an unsigned type) */
+#define GZBUFSIZE 8192
+
+/* gzip modes, also provide a little integrity check on the passed structure */
+#define GZ_NONE 0
+#define GZ_READ 7247
+#define GZ_WRITE 31153
+#define GZ_APPEND 1     /* mode set to GZ_WRITE after the file is opened */
+
+/* values for gz_state how */
+#define LOOK 0      /* look for a gzip header */
+#define COPY 1      /* copy input directly */
+#define GZIP 2      /* decompress a gzip stream */
+
+/* internal gzip file state data structure */
+typedef struct {
+        /* exposed contents for gzgetc() macro */
+    struct gzFile_s x;      /* "x" for exposed */
+                            /* x.have: number of bytes available at x.next */
+                            /* x.next: next output data to deliver or write */
+                            /* x.pos: current position in uncompressed data */
+        /* used for both reading and writing */
+    int mode;               /* see gzip modes above */
+    int fd;                 /* file descriptor */
+    char *path;             /* path or fd for error messages */
+    unsigned size;          /* buffer size, zero if not allocated yet */
+    unsigned want;          /* requested buffer size, default is GZBUFSIZE */
+    unsigned char *in;      /* input buffer (double-sized when writing) */
+    unsigned char *out;     /* output buffer (double-sized when reading) */
+    int direct;             /* 0 if processing gzip, 1 if transparent */
+        /* just for reading */
+    int how;                /* 0: get header, 1: copy, 2: decompress */
+    z_off64_t start;        /* where the gzip data started, for rewinding */
+    int eof;                /* true if end of input file reached */
+    int past;               /* true if read requested past end */
+        /* just for writing */
+    int level;              /* compression level */
+    int strategy;           /* compression strategy */
+        /* seek request */
+    z_off64_t skip;         /* amount to skip (already rewound if backwards) */
+    int seek;               /* true if seek request pending */
+        /* error information */
+    int err;                /* error code */
+    char *msg;              /* error message */
+        /* zlib inflate or deflate stream */
+    z_stream strm;          /* stream structure in-place (not a pointer) */
+} gz_state;
+typedef gz_state FAR *gz_statep;
+
+/* shared functions */
+void ZLIB_INTERNAL gz_error OF((gz_statep, int, const char *));
+#if defined UNDER_CE
+char ZLIB_INTERNAL *gz_strwinerror OF((DWORD error));
+#endif
+
+/* GT_OFF(x), where x is an unsigned value, is true if x > maximum z_off64_t
+   value -- needed when comparing unsigned to z_off64_t, which is signed
+   (possible z_off64_t types off_t, off64_t, and long are all signed) */
+#ifdef INT_MAX
+#  define GT_OFF(x) (sizeof(int) == sizeof(z_off64_t) && (x) > INT_MAX)
+#else
+unsigned ZLIB_INTERNAL gz_intmax OF((void));
+#  define GT_OFF(x) (sizeof(int) == sizeof(z_off64_t) && (x) > gz_intmax())
+#endif

ADDED   3rd_party/zlib/gzlib.c
Index: 3rd_party/zlib/gzlib.c
==================================================================
--- 3rd_party/zlib/gzlib.c
+++ 3rd_party/zlib/gzlib.c
@@ -0,0 +1,637 @@
+/* gzlib.c -- zlib functions common to reading and writing gzip files
+ * Copyright (C) 2004-2017 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+#include "gzguts.h"
+
+#if defined(_WIN32) && !defined(__BORLANDC__) && !defined(__MINGW32__)
+#  define LSEEK _lseeki64
+#else
+#if defined(_LARGEFILE64_SOURCE) && _LFS64_LARGEFILE-0
+#  define LSEEK lseek64
+#else
+#  define LSEEK lseek
+#endif
+#endif
+
+/* Local functions */
+local void gz_reset OF((gz_statep));
+local gzFile gz_open OF((const void *, int, const char *));
+
+#if defined UNDER_CE
+
+/* Map the Windows error number in ERROR to a locale-dependent error message
+   string and return a pointer to it.  Typically, the values for ERROR come
+   from GetLastError.
+
+   The string pointed to shall not be modified by the application, but may be
+   overwritten by a subsequent call to gz_strwinerror
+
+   The gz_strwinerror function does not change the current setting of
+   GetLastError. */
+char ZLIB_INTERNAL *gz_strwinerror (error)
+     DWORD error;
+{
+    static char buf[1024];
+
+    wchar_t *msgbuf;
+    DWORD lasterr = GetLastError();
+    DWORD chars = FormatMessage(FORMAT_MESSAGE_FROM_SYSTEM
+        | FORMAT_MESSAGE_ALLOCATE_BUFFER,
+        NULL,
+        error,
+        0, /* Default language */
+        (LPVOID)&msgbuf,
+        0,
+        NULL);
+    if (chars != 0) {
+        /* If there is an \r\n appended, zap it.  */
+        if (chars >= 2
+            && msgbuf[chars - 2] == '\r' && msgbuf[chars - 1] == '\n') {
+            chars -= 2;
+            msgbuf[chars] = 0;
+        }
+
+        if (chars > sizeof (buf) - 1) {
+            chars = sizeof (buf) - 1;
+            msgbuf[chars] = 0;
+        }
+
+        wcstombs(buf, msgbuf, chars + 1);
+        LocalFree(msgbuf);
+    }
+    else {
+        sprintf(buf, "unknown win32 error (%ld)", error);
+    }
+
+    SetLastError(lasterr);
+    return buf;
+}
+
+#endif /* UNDER_CE */
+
+/* Reset gzip file state */
+local void gz_reset(state)
+    gz_statep state;
+{
+    state->x.have = 0;              /* no output data available */
+    if (state->mode == GZ_READ) {   /* for reading ... */
+        state->eof = 0;             /* not at end of file */
+        state->past = 0;            /* have not read past end yet */
+        state->how = LOOK;          /* look for gzip header */
+    }
+    state->seek = 0;                /* no seek request pending */
+    gz_error(state, Z_OK, NULL);    /* clear error */
+    state->x.pos = 0;               /* no uncompressed data yet */
+    state->strm.avail_in = 0;       /* no input data yet */
+}
+
+/* Open a gzip file either by name or file descriptor. */
+local gzFile gz_open(path, fd, mode)
+    const void *path;
+    int fd;
+    const char *mode;
+{
+    gz_statep state;
+    z_size_t len;
+    int oflag;
+#ifdef O_CLOEXEC
+    int cloexec = 0;
+#endif
+#ifdef O_EXCL
+    int exclusive = 0;
+#endif
+
+    /* check input */
+    if (path == NULL)
+        return NULL;
+
+    /* allocate gzFile structure to return */
+    state = (gz_statep)malloc(sizeof(gz_state));
+    if (state == NULL)
+        return NULL;
+    state->size = 0;            /* no buffers allocated yet */
+    state->want = GZBUFSIZE;    /* requested buffer size */
+    state->msg = NULL;          /* no error message yet */
+
+    /* interpret mode */
+    state->mode = GZ_NONE;
+    state->level = Z_DEFAULT_COMPRESSION;
+    state->strategy = Z_DEFAULT_STRATEGY;
+    state->direct = 0;
+    while (*mode) {
+        if (*mode >= '0' && *mode <= '9')
+            state->level = *mode - '0';
+        else
+            switch (*mode) {
+            case 'r':
+                state->mode = GZ_READ;
+                break;
+#ifndef NO_GZCOMPRESS
+            case 'w':
+                state->mode = GZ_WRITE;
+                break;
+            case 'a':
+                state->mode = GZ_APPEND;
+                break;
+#endif
+            case '+':       /* can't read and write at the same time */
+                free(state);
+                return NULL;
+            case 'b':       /* ignore -- will request binary anyway */
+                break;
+#ifdef O_CLOEXEC
+            case 'e':
+                cloexec = 1;
+                break;
+#endif
+#ifdef O_EXCL
+            case 'x':
+                exclusive = 1;
+                break;
+#endif
+            case 'f':
+                state->strategy = Z_FILTERED;
+                break;
+            case 'h':
+                state->strategy = Z_HUFFMAN_ONLY;
+                break;
+            case 'R':
+                state->strategy = Z_RLE;
+                break;
+            case 'F':
+                state->strategy = Z_FIXED;
+                break;
+            case 'T':
+                state->direct = 1;
+                break;
+            default:        /* could consider as an error, but just ignore */
+                ;
+            }
+        mode++;
+    }
+
+    /* must provide an "r", "w", or "a" */
+    if (state->mode == GZ_NONE) {
+        free(state);
+        return NULL;
+    }
+
+    /* can't force transparent read */
+    if (state->mode == GZ_READ) {
+        if (state->direct) {
+            free(state);
+            return NULL;
+        }
+        state->direct = 1;      /* for empty file */
+    }
+
+    /* save the path name for error messages */
+#ifdef WIDECHAR
+    if (fd == -2) {
+        len = wcstombs(NULL, path, 0);
+        if (len == (z_size_t)-1)
+            len = 0;
+    }
+    else
+#endif
+        len = strlen((const char *)path);
+    state->path = (char *)malloc(len + 1);
+    if (state->path == NULL) {
+        free(state);
+        return NULL;
+    }
+#ifdef WIDECHAR
+    if (fd == -2)
+        if (len)
+            wcstombs(state->path, path, len + 1);
+        else
+            *(state->path) = 0;
+    else
+#endif
+#if !defined(NO_snprintf) && !defined(NO_vsnprintf)
+        (void)snprintf(state->path, len + 1, "%s", (const char *)path);
+#else
+        strcpy(state->path, path);
+#endif
+
+    /* compute the flags for open() */
+    oflag =
+#ifdef O_LARGEFILE
+        O_LARGEFILE |
+#endif
+#ifdef O_BINARY
+        O_BINARY |
+#endif
+#ifdef O_CLOEXEC
+        (cloexec ? O_CLOEXEC : 0) |
+#endif
+        (state->mode == GZ_READ ?
+         O_RDONLY :
+         (O_WRONLY | O_CREAT |
+#ifdef O_EXCL
+          (exclusive ? O_EXCL : 0) |
+#endif
+          (state->mode == GZ_WRITE ?
+           O_TRUNC :
+           O_APPEND)));
+
+    /* open the file with the appropriate flags (or just use fd) */
+    state->fd = fd > -1 ? fd : (
+#ifdef WIDECHAR
+        fd == -2 ? _wopen(path, oflag, 0666) :
+#endif
+        open((const char *)path, oflag, 0666));
+    if (state->fd == -1) {
+        free(state->path);
+        free(state);
+        return NULL;
+    }
+    if (state->mode == GZ_APPEND) {
+        LSEEK(state->fd, 0, SEEK_END);  /* so gzoffset() is correct */
+        state->mode = GZ_WRITE;         /* simplify later checks */
+    }
+
+    /* save the current position for rewinding (only if reading) */
+    if (state->mode == GZ_READ) {
+        state->start = LSEEK(state->fd, 0, SEEK_CUR);
+        if (state->start == -1) state->start = 0;
+    }
+
+    /* initialize stream */
+    gz_reset(state);
+
+    /* return stream */
+    return (gzFile)state;
+}
+
+/* -- see zlib.h -- */
+gzFile ZEXPORT gzopen(path, mode)
+    const char *path;
+    const char *mode;
+{
+    return gz_open(path, -1, mode);
+}
+
+/* -- see zlib.h -- */
+gzFile ZEXPORT gzopen64(path, mode)
+    const char *path;
+    const char *mode;
+{
+    return gz_open(path, -1, mode);
+}
+
+/* -- see zlib.h -- */
+gzFile ZEXPORT gzdopen(fd, mode)
+    int fd;
+    const char *mode;
+{
+    char *path;         /* identifier for error messages */
+    gzFile gz;
+
+    if (fd == -1 || (path = (char *)malloc(7 + 3 * sizeof(int))) == NULL)
+        return NULL;
+#if !defined(NO_snprintf) && !defined(NO_vsnprintf)
+    (void)snprintf(path, 7 + 3 * sizeof(int), "<fd:%d>", fd);
+#else
+    sprintf(path, "<fd:%d>", fd);   /* for debugging */
+#endif
+    gz = gz_open(path, fd, mode);
+    free(path);
+    return gz;
+}
+
+/* -- see zlib.h -- */
+#ifdef WIDECHAR
+gzFile ZEXPORT gzopen_w(path, mode)
+    const wchar_t *path;
+    const char *mode;
+{
+    return gz_open(path, -2, mode);
+}
+#endif
+
+/* -- see zlib.h -- */
+int ZEXPORT gzbuffer(file, size)
+    gzFile file;
+    unsigned size;
+{
+    gz_statep state;
+
+    /* get internal structure and check integrity */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+    if (state->mode != GZ_READ && state->mode != GZ_WRITE)
+        return -1;
+
+    /* make sure we haven't already allocated memory */
+    if (state->size != 0)
+        return -1;
+
+    /* check and set requested size */
+    if ((size << 1) < size)
+        return -1;              /* need to be able to double it */
+    if (size < 2)
+        size = 2;               /* need two bytes to check magic header */
+    state->want = size;
+    return 0;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzrewind(file)
+    gzFile file;
+{
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+
+    /* check that we're reading and that there's no error */
+    if (state->mode != GZ_READ ||
+            (state->err != Z_OK && state->err != Z_BUF_ERROR))
+        return -1;
+
+    /* back up and start over */
+    if (LSEEK(state->fd, state->start, SEEK_SET) == -1)
+        return -1;
+    gz_reset(state);
+    return 0;
+}
+
+/* -- see zlib.h -- */
+z_off64_t ZEXPORT gzseek64(file, offset, whence)
+    gzFile file;
+    z_off64_t offset;
+    int whence;
+{
+    unsigned n;
+    z_off64_t ret;
+    gz_statep state;
+
+    /* get internal structure and check integrity */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+    if (state->mode != GZ_READ && state->mode != GZ_WRITE)
+        return -1;
+
+    /* check that there's no error */
+    if (state->err != Z_OK && state->err != Z_BUF_ERROR)
+        return -1;
+
+    /* can only seek from start or relative to current position */
+    if (whence != SEEK_SET && whence != SEEK_CUR)
+        return -1;
+
+    /* normalize offset to a SEEK_CUR specification */
+    if (whence == SEEK_SET)
+        offset -= state->x.pos;
+    else if (state->seek)
+        offset += state->skip;
+    state->seek = 0;
+
+    /* if within raw area while reading, just go there */
+    if (state->mode == GZ_READ && state->how == COPY &&
+            state->x.pos + offset >= 0) {
+        ret = LSEEK(state->fd, offset - state->x.have, SEEK_CUR);
+        if (ret == -1)
+            return -1;
+        state->x.have = 0;
+        state->eof = 0;
+        state->past = 0;
+        state->seek = 0;
+        gz_error(state, Z_OK, NULL);
+        state->strm.avail_in = 0;
+        state->x.pos += offset;
+        return state->x.pos;
+    }
+
+    /* calculate skip amount, rewinding if needed for back seek when reading */
+    if (offset < 0) {
+        if (state->mode != GZ_READ)         /* writing -- can't go backwards */
+            return -1;
+        offset += state->x.pos;
+        if (offset < 0)                     /* before start of file! */
+            return -1;
+        if (gzrewind(file) == -1)           /* rewind, then skip to offset */
+            return -1;
+    }
+
+    /* if reading, skip what's in output buffer (one less gzgetc() check) */
+    if (state->mode == GZ_READ) {
+        n = GT_OFF(state->x.have) || (z_off64_t)state->x.have > offset ?
+            (unsigned)offset : state->x.have;
+        state->x.have -= n;
+        state->x.next += n;
+        state->x.pos += n;
+        offset -= n;
+    }
+
+    /* request skip (if not zero) */
+    if (offset) {
+        state->seek = 1;
+        state->skip = offset;
+    }
+    return state->x.pos + offset;
+}
+
+/* -- see zlib.h -- */
+z_off_t ZEXPORT gzseek(file, offset, whence)
+    gzFile file;
+    z_off_t offset;
+    int whence;
+{
+    z_off64_t ret;
+
+    ret = gzseek64(file, (z_off64_t)offset, whence);
+    return ret == (z_off_t)ret ? (z_off_t)ret : -1;
+}
+
+/* -- see zlib.h -- */
+z_off64_t ZEXPORT gztell64(file)
+    gzFile file;
+{
+    gz_statep state;
+
+    /* get internal structure and check integrity */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+    if (state->mode != GZ_READ && state->mode != GZ_WRITE)
+        return -1;
+
+    /* return position */
+    return state->x.pos + (state->seek ? state->skip : 0);
+}
+
+/* -- see zlib.h -- */
+z_off_t ZEXPORT gztell(file)
+    gzFile file;
+{
+    z_off64_t ret;
+
+    ret = gztell64(file);
+    return ret == (z_off_t)ret ? (z_off_t)ret : -1;
+}
+
+/* -- see zlib.h -- */
+z_off64_t ZEXPORT gzoffset64(file)
+    gzFile file;
+{
+    z_off64_t offset;
+    gz_statep state;
+
+    /* get internal structure and check integrity */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+    if (state->mode != GZ_READ && state->mode != GZ_WRITE)
+        return -1;
+
+    /* compute and return effective offset in file */
+    offset = LSEEK(state->fd, 0, SEEK_CUR);
+    if (offset == -1)
+        return -1;
+    if (state->mode == GZ_READ)             /* reading */
+        offset -= state->strm.avail_in;     /* don't count buffered input */
+    return offset;
+}
+
+/* -- see zlib.h -- */
+z_off_t ZEXPORT gzoffset(file)
+    gzFile file;
+{
+    z_off64_t ret;
+
+    ret = gzoffset64(file);
+    return ret == (z_off_t)ret ? (z_off_t)ret : -1;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzeof(file)
+    gzFile file;
+{
+    gz_statep state;
+
+    /* get internal structure and check integrity */
+    if (file == NULL)
+        return 0;
+    state = (gz_statep)file;
+    if (state->mode != GZ_READ && state->mode != GZ_WRITE)
+        return 0;
+
+    /* return end-of-file state */
+    return state->mode == GZ_READ ? state->past : 0;
+}
+
+/* -- see zlib.h -- */
+const char * ZEXPORT gzerror(file, errnum)
+    gzFile file;
+    int *errnum;
+{
+    gz_statep state;
+
+    /* get internal structure and check integrity */
+    if (file == NULL)
+        return NULL;
+    state = (gz_statep)file;
+    if (state->mode != GZ_READ && state->mode != GZ_WRITE)
+        return NULL;
+
+    /* return error information */
+    if (errnum != NULL)
+        *errnum = state->err;
+    return state->err == Z_MEM_ERROR ? "out of memory" :
+                                       (state->msg == NULL ? "" : state->msg);
+}
+
+/* -- see zlib.h -- */
+void ZEXPORT gzclearerr(file)
+    gzFile file;
+{
+    gz_statep state;
+
+    /* get internal structure and check integrity */
+    if (file == NULL)
+        return;
+    state = (gz_statep)file;
+    if (state->mode != GZ_READ && state->mode != GZ_WRITE)
+        return;
+
+    /* clear error and end-of-file */
+    if (state->mode == GZ_READ) {
+        state->eof = 0;
+        state->past = 0;
+    }
+    gz_error(state, Z_OK, NULL);
+}
+
+/* Create an error message in allocated memory and set state->err and
+   state->msg accordingly.  Free any previous error message already there.  Do
+   not try to free or allocate space if the error is Z_MEM_ERROR (out of
+   memory).  Simply save the error message as a static string.  If there is an
+   allocation failure constructing the error message, then convert the error to
+   out of memory. */
+void ZLIB_INTERNAL gz_error(state, err, msg)
+    gz_statep state;
+    int err;
+    const char *msg;
+{
+    /* free previously allocated message and clear */
+    if (state->msg != NULL) {
+        if (state->err != Z_MEM_ERROR)
+            free(state->msg);
+        state->msg = NULL;
+    }
+
+    /* if fatal, set state->x.have to 0 so that the gzgetc() macro fails */
+    if (err != Z_OK && err != Z_BUF_ERROR)
+        state->x.have = 0;
+
+    /* set error code, and if no message, then done */
+    state->err = err;
+    if (msg == NULL)
+        return;
+
+    /* for an out of memory error, return literal string when requested */
+    if (err == Z_MEM_ERROR)
+        return;
+
+    /* construct error message with path */
+    if ((state->msg = (char *)malloc(strlen(state->path) + strlen(msg) + 3)) ==
+            NULL) {
+        state->err = Z_MEM_ERROR;
+        return;
+    }
+#if !defined(NO_snprintf) && !defined(NO_vsnprintf)
+    (void)snprintf(state->msg, strlen(state->path) + strlen(msg) + 3,
+                   "%s%s%s", state->path, ": ", msg);
+#else
+    strcpy(state->msg, state->path);
+    strcat(state->msg, ": ");
+    strcat(state->msg, msg);
+#endif
+}
+
+#ifndef INT_MAX
+/* portably return maximum value for an int (when limits.h presumed not
+   available) -- we need to do this to cover cases where 2's complement not
+   used, since C standard permits 1's complement and sign-bit representations,
+   otherwise we could just use ((unsigned)-1) >> 1 */
+unsigned ZLIB_INTERNAL gz_intmax()
+{
+    unsigned p, q;
+
+    p = 1;
+    do {
+        q = p;
+        p <<= 1;
+        p++;
+    } while (p > q);
+    return q >> 1;
+}
+#endif

ADDED   3rd_party/zlib/gzread.c
Index: 3rd_party/zlib/gzread.c
==================================================================
--- 3rd_party/zlib/gzread.c
+++ 3rd_party/zlib/gzread.c
@@ -0,0 +1,654 @@
+/* gzread.c -- zlib functions for reading gzip files
+ * Copyright (C) 2004, 2005, 2010, 2011, 2012, 2013, 2016 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+#include "gzguts.h"
+
+/* Local functions */
+local int gz_load OF((gz_statep, unsigned char *, unsigned, unsigned *));
+local int gz_avail OF((gz_statep));
+local int gz_look OF((gz_statep));
+local int gz_decomp OF((gz_statep));
+local int gz_fetch OF((gz_statep));
+local int gz_skip OF((gz_statep, z_off64_t));
+local z_size_t gz_read OF((gz_statep, voidp, z_size_t));
+
+/* Use read() to load a buffer -- return -1 on error, otherwise 0.  Read from
+   state->fd, and update state->eof, state->err, and state->msg as appropriate.
+   This function needs to loop on read(), since read() is not guaranteed to
+   read the number of bytes requested, depending on the type of descriptor. */
+local int gz_load(state, buf, len, have)
+    gz_statep state;
+    unsigned char *buf;
+    unsigned len;
+    unsigned *have;
+{
+    int ret;
+    unsigned get, max = ((unsigned)-1 >> 2) + 1;
+
+    *have = 0;
+    do {
+        get = len - *have;
+        if (get > max)
+            get = max;
+        ret = read(state->fd, buf + *have, get);
+        if (ret <= 0)
+            break;
+        *have += (unsigned)ret;
+    } while (*have < len);
+    if (ret < 0) {
+        gz_error(state, Z_ERRNO, zstrerror());
+        return -1;
+    }
+    if (ret == 0)
+        state->eof = 1;
+    return 0;
+}
+
+/* Load up input buffer and set eof flag if last data loaded -- return -1 on
+   error, 0 otherwise.  Note that the eof flag is set when the end of the input
+   file is reached, even though there may be unused data in the buffer.  Once
+   that data has been used, no more attempts will be made to read the file.
+   If strm->avail_in != 0, then the current data is moved to the beginning of
+   the input buffer, and then the remainder of the buffer is loaded with the
+   available data from the input file. */
+local int gz_avail(state)
+    gz_statep state;
+{
+    unsigned got;
+    z_streamp strm = &(state->strm);
+
+    if (state->err != Z_OK && state->err != Z_BUF_ERROR)
+        return -1;
+    if (state->eof == 0) {
+        if (strm->avail_in) {       /* copy what's there to the start */
+            unsigned char *p = state->in;
+            unsigned const char *q = strm->next_in;
+            unsigned n = strm->avail_in;
+            do {
+                *p++ = *q++;
+            } while (--n);
+        }
+        if (gz_load(state, state->in + strm->avail_in,
+                    state->size - strm->avail_in, &got) == -1)
+            return -1;
+        strm->avail_in += got;
+        strm->next_in = state->in;
+    }
+    return 0;
+}
+
+/* Look for gzip header, set up for inflate or copy.  state->x.have must be 0.
+   If this is the first time in, allocate required memory.  state->how will be
+   left unchanged if there is no more input data available, will be set to COPY
+   if there is no gzip header and direct copying will be performed, or it will
+   be set to GZIP for decompression.  If direct copying, then leftover input
+   data from the input buffer will be copied to the output buffer.  In that
+   case, all further file reads will be directly to either the output buffer or
+   a user buffer.  If decompressing, the inflate state will be initialized.
+   gz_look() will return 0 on success or -1 on failure. */
+local int gz_look(state)
+    gz_statep state;
+{
+    z_streamp strm = &(state->strm);
+
+    /* allocate read buffers and inflate memory */
+    if (state->size == 0) {
+        /* allocate buffers */
+        state->in = (unsigned char *)malloc(state->want);
+        state->out = (unsigned char *)malloc(state->want << 1);
+        if (state->in == NULL || state->out == NULL) {
+            free(state->out);
+            free(state->in);
+            gz_error(state, Z_MEM_ERROR, "out of memory");
+            return -1;
+        }
+        state->size = state->want;
+
+        /* allocate inflate memory */
+        state->strm.zalloc = Z_NULL;
+        state->strm.zfree = Z_NULL;
+        state->strm.opaque = Z_NULL;
+        state->strm.avail_in = 0;
+        state->strm.next_in = Z_NULL;
+        if (inflateInit2(&(state->strm), 15 + 16) != Z_OK) {    /* gunzip */
+            free(state->out);
+            free(state->in);
+            state->size = 0;
+            gz_error(state, Z_MEM_ERROR, "out of memory");
+            return -1;
+        }
+    }
+
+    /* get at least the magic bytes in the input buffer */
+    if (strm->avail_in < 2) {
+        if (gz_avail(state) == -1)
+            return -1;
+        if (strm->avail_in == 0)
+            return 0;
+    }
+
+    /* look for gzip magic bytes -- if there, do gzip decoding (note: there is
+       a logical dilemma here when considering the case of a partially written
+       gzip file, to wit, if a single 31 byte is written, then we cannot tell
+       whether this is a single-byte file, or just a partially written gzip
+       file -- for here we assume that if a gzip file is being written, then
+       the header will be written in a single operation, so that reading a
+       single byte is sufficient indication that it is not a gzip file) */
+    if (strm->avail_in > 1 &&
+            strm->next_in[0] == 31 && strm->next_in[1] == 139) {
+        inflateReset(strm);
+        state->how = GZIP;
+        state->direct = 0;
+        return 0;
+    }
+
+    /* no gzip header -- if we were decoding gzip before, then this is trailing
+       garbage.  Ignore the trailing garbage and finish. */
+    if (state->direct == 0) {
+        strm->avail_in = 0;
+        state->eof = 1;
+        state->x.have = 0;
+        return 0;
+    }
+
+    /* doing raw i/o, copy any leftover input to output -- this assumes that
+       the output buffer is larger than the input buffer, which also assures
+       space for gzungetc() */
+    state->x.next = state->out;
+    if (strm->avail_in) {
+        memcpy(state->x.next, strm->next_in, strm->avail_in);
+        state->x.have = strm->avail_in;
+        strm->avail_in = 0;
+    }
+    state->how = COPY;
+    state->direct = 1;
+    return 0;
+}
+
+/* Decompress from input to the provided next_out and avail_out in the state.
+   On return, state->x.have and state->x.next point to the just decompressed
+   data.  If the gzip stream completes, state->how is reset to LOOK to look for
+   the next gzip stream or raw data, once state->x.have is depleted.  Returns 0
+   on success, -1 on failure. */
+local int gz_decomp(state)
+    gz_statep state;
+{
+    int ret = Z_OK;
+    unsigned had;
+    z_streamp strm = &(state->strm);
+
+    /* fill output buffer up to end of deflate stream */
+    had = strm->avail_out;
+    do {
+        /* get more input for inflate() */
+        if (strm->avail_in == 0 && gz_avail(state) == -1)
+            return -1;
+        if (strm->avail_in == 0) {
+            gz_error(state, Z_BUF_ERROR, "unexpected end of file");
+            break;
+        }
+
+        /* decompress and handle errors */
+        ret = inflate(strm, Z_NO_FLUSH);
+        if (ret == Z_STREAM_ERROR || ret == Z_NEED_DICT) {
+            gz_error(state, Z_STREAM_ERROR,
+                     "internal error: inflate stream corrupt");
+            return -1;
+        }
+        if (ret == Z_MEM_ERROR) {
+            gz_error(state, Z_MEM_ERROR, "out of memory");
+            return -1;
+        }
+        if (ret == Z_DATA_ERROR) {              /* deflate stream invalid */
+            gz_error(state, Z_DATA_ERROR,
+                     strm->msg == NULL ? "compressed data error" : strm->msg);
+            return -1;
+        }
+    } while (strm->avail_out && ret != Z_STREAM_END);
+
+    /* update available output */
+    state->x.have = had - strm->avail_out;
+    state->x.next = strm->next_out - state->x.have;
+
+    /* if the gzip stream completed successfully, look for another */
+    if (ret == Z_STREAM_END)
+        state->how = LOOK;
+
+    /* good decompression */
+    return 0;
+}
+
+/* Fetch data and put it in the output buffer.  Assumes state->x.have is 0.
+   Data is either copied from the input file or decompressed from the input
+   file depending on state->how.  If state->how is LOOK, then a gzip header is
+   looked for to determine whether to copy or decompress.  Returns -1 on error,
+   otherwise 0.  gz_fetch() will leave state->how as COPY or GZIP unless the
+   end of the input file has been reached and all data has been processed.  */
+local int gz_fetch(state)
+    gz_statep state;
+{
+    z_streamp strm = &(state->strm);
+
+    do {
+        switch(state->how) {
+        case LOOK:      /* -> LOOK, COPY (only if never GZIP), or GZIP */
+            if (gz_look(state) == -1)
+                return -1;
+            if (state->how == LOOK)
+                return 0;
+            break;
+        case COPY:      /* -> COPY */
+            if (gz_load(state, state->out, state->size << 1, &(state->x.have))
+                    == -1)
+                return -1;
+            state->x.next = state->out;
+            return 0;
+        case GZIP:      /* -> GZIP or LOOK (if end of gzip stream) */
+            strm->avail_out = state->size << 1;
+            strm->next_out = state->out;
+            if (gz_decomp(state) == -1)
+                return -1;
+        }
+    } while (state->x.have == 0 && (!state->eof || strm->avail_in));
+    return 0;
+}
+
+/* Skip len uncompressed bytes of output.  Return -1 on error, 0 on success. */
+local int gz_skip(state, len)
+    gz_statep state;
+    z_off64_t len;
+{
+    unsigned n;
+
+    /* skip over len bytes or reach end-of-file, whichever comes first */
+    while (len)
+        /* skip over whatever is in output buffer */
+        if (state->x.have) {
+            n = GT_OFF(state->x.have) || (z_off64_t)state->x.have > len ?
+                (unsigned)len : state->x.have;
+            state->x.have -= n;
+            state->x.next += n;
+            state->x.pos += n;
+            len -= n;
+        }
+
+        /* output buffer empty -- return if we're at the end of the input */
+        else if (state->eof && state->strm.avail_in == 0)
+            break;
+
+        /* need more data to skip -- load up output buffer */
+        else {
+            /* get more output, looking for header if required */
+            if (gz_fetch(state) == -1)
+                return -1;
+        }
+    return 0;
+}
+
+/* Read len bytes into buf from file, or less than len up to the end of the
+   input.  Return the number of bytes read.  If zero is returned, either the
+   end of file was reached, or there was an error.  state->err must be
+   consulted in that case to determine which. */
+local z_size_t gz_read(state, buf, len)
+    gz_statep state;
+    voidp buf;
+    z_size_t len;
+{
+    z_size_t got;
+    unsigned n;
+
+    /* if len is zero, avoid unnecessary operations */
+    if (len == 0)
+        return 0;
+
+    /* process a skip request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_skip(state, state->skip) == -1)
+            return 0;
+    }
+
+    /* get len bytes to buf, or less than len if at the end */
+    got = 0;
+    do {
+        /* set n to the maximum amount of len that fits in an unsigned int */
+        n = -1;
+        if (n > len)
+            n = len;
+
+        /* first just try copying data from the output buffer */
+        if (state->x.have) {
+            if (state->x.have < n)
+                n = state->x.have;
+            memcpy(buf, state->x.next, n);
+            state->x.next += n;
+            state->x.have -= n;
+        }
+
+        /* output buffer empty -- return if we're at the end of the input */
+        else if (state->eof && state->strm.avail_in == 0) {
+            state->past = 1;        /* tried to read past end */
+            break;
+        }
+
+        /* need output data -- for small len or new stream load up our output
+           buffer */
+        else if (state->how == LOOK || n < (state->size << 1)) {
+            /* get more output, looking for header if required */
+            if (gz_fetch(state) == -1)
+                return 0;
+            continue;       /* no progress yet -- go back to copy above */
+            /* the copy above assures that we will leave with space in the
+               output buffer, allowing at least one gzungetc() to succeed */
+        }
+
+        /* large len -- read directly into user buffer */
+        else if (state->how == COPY) {      /* read directly */
+            if (gz_load(state, (unsigned char *)buf, n, &n) == -1)
+                return 0;
+        }
+
+        /* large len -- decompress directly into user buffer */
+        else {  /* state->how == GZIP */
+            state->strm.avail_out = n;
+            state->strm.next_out = (unsigned char *)buf;
+            if (gz_decomp(state) == -1)
+                return 0;
+            n = state->x.have;
+            state->x.have = 0;
+        }
+
+        /* update progress */
+        len -= n;
+        buf = (char *)buf + n;
+        got += n;
+        state->x.pos += n;
+    } while (len);
+
+    /* return number of bytes read into user buffer */
+    return got;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzread(file, buf, len)
+    gzFile file;
+    voidp buf;
+    unsigned len;
+{
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+
+    /* check that we're reading and that there's no (serious) error */
+    if (state->mode != GZ_READ ||
+            (state->err != Z_OK && state->err != Z_BUF_ERROR))
+        return -1;
+
+    /* since an int is returned, make sure len fits in one, otherwise return
+       with an error (this avoids a flaw in the interface) */
+    if ((int)len < 0) {
+        gz_error(state, Z_STREAM_ERROR, "request does not fit in an int");
+        return -1;
+    }
+
+    /* read len or fewer bytes to buf */
+    len = gz_read(state, buf, len);
+
+    /* check for an error */
+    if (len == 0 && state->err != Z_OK && state->err != Z_BUF_ERROR)
+        return -1;
+
+    /* return the number of bytes read (this is assured to fit in an int) */
+    return (int)len;
+}
+
+/* -- see zlib.h -- */
+z_size_t ZEXPORT gzfread(buf, size, nitems, file)
+    voidp buf;
+    z_size_t size;
+    z_size_t nitems;
+    gzFile file;
+{
+    z_size_t len;
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return 0;
+    state = (gz_statep)file;
+
+    /* check that we're reading and that there's no (serious) error */
+    if (state->mode != GZ_READ ||
+            (state->err != Z_OK && state->err != Z_BUF_ERROR))
+        return 0;
+
+    /* compute bytes to read -- error on overflow */
+    len = nitems * size;
+    if (size && len / size != nitems) {
+        gz_error(state, Z_STREAM_ERROR, "request does not fit in a size_t");
+        return 0;
+    }
+
+    /* read len or fewer bytes to buf, return the number of full items read */
+    return len ? gz_read(state, buf, len) / size : 0;
+}
+
+/* -- see zlib.h -- */
+#ifdef Z_PREFIX_SET
+#  undef z_gzgetc
+#else
+#  undef gzgetc
+#endif
+int ZEXPORT gzgetc(file)
+    gzFile file;
+{
+    int ret;
+    unsigned char buf[1];
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+
+    /* check that we're reading and that there's no (serious) error */
+    if (state->mode != GZ_READ ||
+        (state->err != Z_OK && state->err != Z_BUF_ERROR))
+        return -1;
+
+    /* try output buffer (no need to check for skip request) */
+    if (state->x.have) {
+        state->x.have--;
+        state->x.pos++;
+        return *(state->x.next)++;
+    }
+
+    /* nothing there -- try gz_read() */
+    ret = gz_read(state, buf, 1);
+    return ret < 1 ? -1 : buf[0];
+}
+
+int ZEXPORT gzgetc_(file)
+gzFile file;
+{
+    return gzgetc(file);
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzungetc(c, file)
+    int c;
+    gzFile file;
+{
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+
+    /* check that we're reading and that there's no (serious) error */
+    if (state->mode != GZ_READ ||
+        (state->err != Z_OK && state->err != Z_BUF_ERROR))
+        return -1;
+
+    /* process a skip request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_skip(state, state->skip) == -1)
+            return -1;
+    }
+
+    /* can't push EOF */
+    if (c < 0)
+        return -1;
+
+    /* if output buffer empty, put byte at end (allows more pushing) */
+    if (state->x.have == 0) {
+        state->x.have = 1;
+        state->x.next = state->out + (state->size << 1) - 1;
+        state->x.next[0] = (unsigned char)c;
+        state->x.pos--;
+        state->past = 0;
+        return c;
+    }
+
+    /* if no room, give up (must have already done a gzungetc()) */
+    if (state->x.have == (state->size << 1)) {
+        gz_error(state, Z_DATA_ERROR, "out of room to push characters");
+        return -1;
+    }
+
+    /* slide output data if needed and insert byte before existing data */
+    if (state->x.next == state->out) {
+        unsigned char *src = state->out + state->x.have;
+        unsigned char *dest = state->out + (state->size << 1);
+        while (src > state->out)
+            *--dest = *--src;
+        state->x.next = dest;
+    }
+    state->x.have++;
+    state->x.next--;
+    state->x.next[0] = (unsigned char)c;
+    state->x.pos--;
+    state->past = 0;
+    return c;
+}
+
+/* -- see zlib.h -- */
+char * ZEXPORT gzgets(file, buf, len)
+    gzFile file;
+    char *buf;
+    int len;
+{
+    unsigned left, n;
+    char *str;
+    unsigned char *eol;
+    gz_statep state;
+
+    /* check parameters and get internal structure */
+    if (file == NULL || buf == NULL || len < 1)
+        return NULL;
+    state = (gz_statep)file;
+
+    /* check that we're reading and that there's no (serious) error */
+    if (state->mode != GZ_READ ||
+        (state->err != Z_OK && state->err != Z_BUF_ERROR))
+        return NULL;
+
+    /* process a skip request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_skip(state, state->skip) == -1)
+            return NULL;
+    }
+
+    /* copy output bytes up to new line or len - 1, whichever comes first --
+       append a terminating zero to the string (we don't check for a zero in
+       the contents, let the user worry about that) */
+    str = buf;
+    left = (unsigned)len - 1;
+    if (left) do {
+        /* assure that something is in the output buffer */
+        if (state->x.have == 0 && gz_fetch(state) == -1)
+            return NULL;                /* error */
+        if (state->x.have == 0) {       /* end of file */
+            state->past = 1;            /* read past end */
+            break;                      /* return what we have */
+        }
+
+        /* look for end-of-line in current output buffer */
+        n = state->x.have > left ? left : state->x.have;
+        eol = (unsigned char *)memchr(state->x.next, '\n', n);
+        if (eol != NULL)
+            n = (unsigned)(eol - state->x.next) + 1;
+
+        /* copy through end-of-line, or remainder if not found */
+        memcpy(buf, state->x.next, n);
+        state->x.have -= n;
+        state->x.next += n;
+        state->x.pos += n;
+        left -= n;
+        buf += n;
+    } while (left && eol == NULL);
+
+    /* return terminated string, or if nothing, end of file */
+    if (buf == str)
+        return NULL;
+    buf[0] = 0;
+    return str;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzdirect(file)
+    gzFile file;
+{
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return 0;
+    state = (gz_statep)file;
+
+    /* if the state is not known, but we can find out, then do so (this is
+       mainly for right after a gzopen() or gzdopen()) */
+    if (state->mode == GZ_READ && state->how == LOOK && state->x.have == 0)
+        (void)gz_look(state);
+
+    /* return 1 if transparent, 0 if processing a gzip stream */
+    return state->direct;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzclose_r(file)
+    gzFile file;
+{
+    int ret, err;
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return Z_STREAM_ERROR;
+    state = (gz_statep)file;
+
+    /* check that we're reading */
+    if (state->mode != GZ_READ)
+        return Z_STREAM_ERROR;
+
+    /* free memory and close file */
+    if (state->size) {
+        inflateEnd(&(state->strm));
+        free(state->out);
+        free(state->in);
+    }
+    err = state->err == Z_BUF_ERROR ? Z_BUF_ERROR : Z_OK;
+    gz_error(state, Z_OK, NULL);
+    free(state->path);
+    ret = close(state->fd);
+    free(state);
+    return ret ? Z_ERRNO : err;
+}

ADDED   3rd_party/zlib/gzwrite.c
Index: 3rd_party/zlib/gzwrite.c
==================================================================
--- 3rd_party/zlib/gzwrite.c
+++ 3rd_party/zlib/gzwrite.c
@@ -0,0 +1,665 @@
+/* gzwrite.c -- zlib functions for writing gzip files
+ * Copyright (C) 2004-2017 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+#include "gzguts.h"
+
+/* Local functions */
+local int gz_init OF((gz_statep));
+local int gz_comp OF((gz_statep, int));
+local int gz_zero OF((gz_statep, z_off64_t));
+local z_size_t gz_write OF((gz_statep, voidpc, z_size_t));
+
+/* Initialize state for writing a gzip file.  Mark initialization by setting
+   state->size to non-zero.  Return -1 on a memory allocation failure, or 0 on
+   success. */
+local int gz_init(state)
+    gz_statep state;
+{
+    int ret;
+    z_streamp strm = &(state->strm);
+
+    /* allocate input buffer (double size for gzprintf) */
+    state->in = (unsigned char *)malloc(state->want << 1);
+    if (state->in == NULL) {
+        gz_error(state, Z_MEM_ERROR, "out of memory");
+        return -1;
+    }
+
+    /* only need output buffer and deflate state if compressing */
+    if (!state->direct) {
+        /* allocate output buffer */
+        state->out = (unsigned char *)malloc(state->want);
+        if (state->out == NULL) {
+            free(state->in);
+            gz_error(state, Z_MEM_ERROR, "out of memory");
+            return -1;
+        }
+
+        /* allocate deflate memory, set up for gzip compression */
+        strm->zalloc = Z_NULL;
+        strm->zfree = Z_NULL;
+        strm->opaque = Z_NULL;
+        ret = deflateInit2(strm, state->level, Z_DEFLATED,
+                           MAX_WBITS + 16, DEF_MEM_LEVEL, state->strategy);
+        if (ret != Z_OK) {
+            free(state->out);
+            free(state->in);
+            gz_error(state, Z_MEM_ERROR, "out of memory");
+            return -1;
+        }
+        strm->next_in = NULL;
+    }
+
+    /* mark state as initialized */
+    state->size = state->want;
+
+    /* initialize write buffer if compressing */
+    if (!state->direct) {
+        strm->avail_out = state->size;
+        strm->next_out = state->out;
+        state->x.next = strm->next_out;
+    }
+    return 0;
+}
+
+/* Compress whatever is at avail_in and next_in and write to the output file.
+   Return -1 if there is an error writing to the output file or if gz_init()
+   fails to allocate memory, otherwise 0.  flush is assumed to be a valid
+   deflate() flush value.  If flush is Z_FINISH, then the deflate() state is
+   reset to start a new gzip stream.  If gz->direct is true, then simply write
+   to the output file without compressing, and ignore flush. */
+local int gz_comp(state, flush)
+    gz_statep state;
+    int flush;
+{
+    int ret, writ;
+    unsigned have, put, max = ((unsigned)-1 >> 2) + 1;
+    z_streamp strm = &(state->strm);
+
+    /* allocate memory if this is the first time through */
+    if (state->size == 0 && gz_init(state) == -1)
+        return -1;
+
+    /* write directly if requested */
+    if (state->direct) {
+        while (strm->avail_in) {
+            put = strm->avail_in > max ? max : strm->avail_in;
+            writ = write(state->fd, strm->next_in, put);
+            if (writ < 0) {
+                gz_error(state, Z_ERRNO, zstrerror());
+                return -1;
+            }
+            strm->avail_in -= (unsigned)writ;
+            strm->next_in += writ;
+        }
+        return 0;
+    }
+
+    /* run deflate() on provided input until it produces no more output */
+    ret = Z_OK;
+    do {
+        /* write out current buffer contents if full, or if flushing, but if
+           doing Z_FINISH then don't write until we get to Z_STREAM_END */
+        if (strm->avail_out == 0 || (flush != Z_NO_FLUSH &&
+            (flush != Z_FINISH || ret == Z_STREAM_END))) {
+            while (strm->next_out > state->x.next) {
+                put = strm->next_out - state->x.next > (int)max ? max :
+                      (unsigned)(strm->next_out - state->x.next);
+                writ = write(state->fd, state->x.next, put);
+                if (writ < 0) {
+                    gz_error(state, Z_ERRNO, zstrerror());
+                    return -1;
+                }
+                state->x.next += writ;
+            }
+            if (strm->avail_out == 0) {
+                strm->avail_out = state->size;
+                strm->next_out = state->out;
+                state->x.next = state->out;
+            }
+        }
+
+        /* compress */
+        have = strm->avail_out;
+        ret = deflate(strm, flush);
+        if (ret == Z_STREAM_ERROR) {
+            gz_error(state, Z_STREAM_ERROR,
+                      "internal error: deflate stream corrupt");
+            return -1;
+        }
+        have -= strm->avail_out;
+    } while (have);
+
+    /* if that completed a deflate stream, allow another to start */
+    if (flush == Z_FINISH)
+        deflateReset(strm);
+
+    /* all done, no errors */
+    return 0;
+}
+
+/* Compress len zeros to output.  Return -1 on a write error or memory
+   allocation failure by gz_comp(), or 0 on success. */
+local int gz_zero(state, len)
+    gz_statep state;
+    z_off64_t len;
+{
+    int first;
+    unsigned n;
+    z_streamp strm = &(state->strm);
+
+    /* consume whatever's left in the input buffer */
+    if (strm->avail_in && gz_comp(state, Z_NO_FLUSH) == -1)
+        return -1;
+
+    /* compress len zeros (len guaranteed > 0) */
+    first = 1;
+    while (len) {
+        n = GT_OFF(state->size) || (z_off64_t)state->size > len ?
+            (unsigned)len : state->size;
+        if (first) {
+            memset(state->in, 0, n);
+            first = 0;
+        }
+        strm->avail_in = n;
+        strm->next_in = state->in;
+        state->x.pos += n;
+        if (gz_comp(state, Z_NO_FLUSH) == -1)
+            return -1;
+        len -= n;
+    }
+    return 0;
+}
+
+/* Write len bytes from buf to file.  Return the number of bytes written.  If
+   the returned value is less than len, then there was an error. */
+local z_size_t gz_write(state, buf, len)
+    gz_statep state;
+    voidpc buf;
+    z_size_t len;
+{
+    z_size_t put = len;
+
+    /* if len is zero, avoid unnecessary operations */
+    if (len == 0)
+        return 0;
+
+    /* allocate memory if this is the first time through */
+    if (state->size == 0 && gz_init(state) == -1)
+        return 0;
+
+    /* check for seek request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_zero(state, state->skip) == -1)
+            return 0;
+    }
+
+    /* for small len, copy to input buffer, otherwise compress directly */
+    if (len < state->size) {
+        /* copy to input buffer, compress when full */
+        do {
+            unsigned have, copy;
+
+            if (state->strm.avail_in == 0)
+                state->strm.next_in = state->in;
+            have = (unsigned)((state->strm.next_in + state->strm.avail_in) -
+                              state->in);
+            copy = state->size - have;
+            if (copy > len)
+                copy = len;
+            memcpy(state->in + have, buf, copy);
+            state->strm.avail_in += copy;
+            state->x.pos += copy;
+            buf = (const char *)buf + copy;
+            len -= copy;
+            if (len && gz_comp(state, Z_NO_FLUSH) == -1)
+                return 0;
+        } while (len);
+    }
+    else {
+        /* consume whatever's left in the input buffer */
+        if (state->strm.avail_in && gz_comp(state, Z_NO_FLUSH) == -1)
+            return 0;
+
+        /* directly compress user buffer to file */
+        state->strm.next_in = (z_const Bytef *)buf;
+        do {
+            unsigned n = (unsigned)-1;
+            if (n > len)
+                n = len;
+            state->strm.avail_in = n;
+            state->x.pos += n;
+            if (gz_comp(state, Z_NO_FLUSH) == -1)
+                return 0;
+            len -= n;
+        } while (len);
+    }
+
+    /* input was all buffered or compressed */
+    return put;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzwrite(file, buf, len)
+    gzFile file;
+    voidpc buf;
+    unsigned len;
+{
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return 0;
+    state = (gz_statep)file;
+
+    /* check that we're writing and that there's no error */
+    if (state->mode != GZ_WRITE || state->err != Z_OK)
+        return 0;
+
+    /* since an int is returned, make sure len fits in one, otherwise return
+       with an error (this avoids a flaw in the interface) */
+    if ((int)len < 0) {
+        gz_error(state, Z_DATA_ERROR, "requested length does not fit in int");
+        return 0;
+    }
+
+    /* write len bytes from buf (the return value will fit in an int) */
+    return (int)gz_write(state, buf, len);
+}
+
+/* -- see zlib.h -- */
+z_size_t ZEXPORT gzfwrite(buf, size, nitems, file)
+    voidpc buf;
+    z_size_t size;
+    z_size_t nitems;
+    gzFile file;
+{
+    z_size_t len;
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return 0;
+    state = (gz_statep)file;
+
+    /* check that we're writing and that there's no error */
+    if (state->mode != GZ_WRITE || state->err != Z_OK)
+        return 0;
+
+    /* compute bytes to read -- error on overflow */
+    len = nitems * size;
+    if (size && len / size != nitems) {
+        gz_error(state, Z_STREAM_ERROR, "request does not fit in a size_t");
+        return 0;
+    }
+
+    /* write len bytes to buf, return the number of full items written */
+    return len ? gz_write(state, buf, len) / size : 0;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzputc(file, c)
+    gzFile file;
+    int c;
+{
+    unsigned have;
+    unsigned char buf[1];
+    gz_statep state;
+    z_streamp strm;
+
+    /* get internal structure */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+    strm = &(state->strm);
+
+    /* check that we're writing and that there's no error */
+    if (state->mode != GZ_WRITE || state->err != Z_OK)
+        return -1;
+
+    /* check for seek request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_zero(state, state->skip) == -1)
+            return -1;
+    }
+
+    /* try writing to input buffer for speed (state->size == 0 if buffer not
+       initialized) */
+    if (state->size) {
+        if (strm->avail_in == 0)
+            strm->next_in = state->in;
+        have = (unsigned)((strm->next_in + strm->avail_in) - state->in);
+        if (have < state->size) {
+            state->in[have] = (unsigned char)c;
+            strm->avail_in++;
+            state->x.pos++;
+            return c & 0xff;
+        }
+    }
+
+    /* no room in buffer or not initialized, use gz_write() */
+    buf[0] = (unsigned char)c;
+    if (gz_write(state, buf, 1) != 1)
+        return -1;
+    return c & 0xff;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzputs(file, str)
+    gzFile file;
+    const char *str;
+{
+    int ret;
+    z_size_t len;
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return -1;
+    state = (gz_statep)file;
+
+    /* check that we're writing and that there's no error */
+    if (state->mode != GZ_WRITE || state->err != Z_OK)
+        return -1;
+
+    /* write string */
+    len = strlen(str);
+    ret = gz_write(state, str, len);
+    return ret == 0 && len != 0 ? -1 : ret;
+}
+
+#if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#include <stdarg.h>
+
+/* -- see zlib.h -- */
+int ZEXPORTVA gzvprintf(gzFile file, const char *format, va_list va)
+{
+    int len;
+    unsigned left;
+    char *next;
+    gz_statep state;
+    z_streamp strm;
+
+    /* get internal structure */
+    if (file == NULL)
+        return Z_STREAM_ERROR;
+    state = (gz_statep)file;
+    strm = &(state->strm);
+
+    /* check that we're writing and that there's no error */
+    if (state->mode != GZ_WRITE || state->err != Z_OK)
+        return Z_STREAM_ERROR;
+
+    /* make sure we have some buffer space */
+    if (state->size == 0 && gz_init(state) == -1)
+        return state->err;
+
+    /* check for seek request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_zero(state, state->skip) == -1)
+            return state->err;
+    }
+
+    /* do the printf() into the input buffer, put length in len -- the input
+       buffer is double-sized just for this function, so there is guaranteed to
+       be state->size bytes available after the current contents */
+    if (strm->avail_in == 0)
+        strm->next_in = state->in;
+    next = (char *)(state->in + (strm->next_in - state->in) + strm->avail_in);
+    next[state->size - 1] = 0;
+#ifdef NO_vsnprintf
+#  ifdef HAS_vsprintf_void
+    (void)vsprintf(next, format, va);
+    for (len = 0; len < state->size; len++)
+        if (next[len] == 0) break;
+#  else
+    len = vsprintf(next, format, va);
+#  endif
+#else
+#  ifdef HAS_vsnprintf_void
+    (void)vsnprintf(next, state->size, format, va);
+    len = strlen(next);
+#  else
+    len = vsnprintf(next, state->size, format, va);
+#  endif
+#endif
+
+    /* check that printf() results fit in buffer */
+    if (len == 0 || (unsigned)len >= state->size || next[state->size - 1] != 0)
+        return 0;
+
+    /* update buffer and position, compress first half if past that */
+    strm->avail_in += (unsigned)len;
+    state->x.pos += len;
+    if (strm->avail_in >= state->size) {
+        left = strm->avail_in - state->size;
+        strm->avail_in = state->size;
+        if (gz_comp(state, Z_NO_FLUSH) == -1)
+            return state->err;
+        memcpy(state->in, state->in + state->size, left);
+        strm->next_in = state->in;
+        strm->avail_in = left;
+    }
+    return len;
+}
+
+int ZEXPORTVA gzprintf(gzFile file, const char *format, ...)
+{
+    va_list va;
+    int ret;
+
+    va_start(va, format);
+    ret = gzvprintf(file, format, va);
+    va_end(va);
+    return ret;
+}
+
+#else /* !STDC && !Z_HAVE_STDARG_H */
+
+/* -- see zlib.h -- */
+int ZEXPORTVA gzprintf (file, format, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10,
+                       a11, a12, a13, a14, a15, a16, a17, a18, a19, a20)
+    gzFile file;
+    const char *format;
+    int a1, a2, a3, a4, a5, a6, a7, a8, a9, a10,
+        a11, a12, a13, a14, a15, a16, a17, a18, a19, a20;
+{
+    unsigned len, left;
+    char *next;
+    gz_statep state;
+    z_streamp strm;
+
+    /* get internal structure */
+    if (file == NULL)
+        return Z_STREAM_ERROR;
+    state = (gz_statep)file;
+    strm = &(state->strm);
+
+    /* check that can really pass pointer in ints */
+    if (sizeof(int) != sizeof(void *))
+        return Z_STREAM_ERROR;
+
+    /* check that we're writing and that there's no error */
+    if (state->mode != GZ_WRITE || state->err != Z_OK)
+        return Z_STREAM_ERROR;
+
+    /* make sure we have some buffer space */
+    if (state->size == 0 && gz_init(state) == -1)
+        return state->error;
+
+    /* check for seek request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_zero(state, state->skip) == -1)
+            return state->error;
+    }
+
+    /* do the printf() into the input buffer, put length in len -- the input
+       buffer is double-sized just for this function, so there is guaranteed to
+       be state->size bytes available after the current contents */
+    if (strm->avail_in == 0)
+        strm->next_in = state->in;
+    next = (char *)(strm->next_in + strm->avail_in);
+    next[state->size - 1] = 0;
+#ifdef NO_snprintf
+#  ifdef HAS_sprintf_void
+    sprintf(next, format, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10, a11, a12,
+            a13, a14, a15, a16, a17, a18, a19, a20);
+    for (len = 0; len < size; len++)
+        if (next[len] == 0)
+            break;
+#  else
+    len = sprintf(next, format, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10, a11,
+                  a12, a13, a14, a15, a16, a17, a18, a19, a20);
+#  endif
+#else
+#  ifdef HAS_snprintf_void
+    snprintf(next, state->size, format, a1, a2, a3, a4, a5, a6, a7, a8, a9,
+             a10, a11, a12, a13, a14, a15, a16, a17, a18, a19, a20);
+    len = strlen(next);
+#  else
+    len = snprintf(next, state->size, format, a1, a2, a3, a4, a5, a6, a7, a8,
+                   a9, a10, a11, a12, a13, a14, a15, a16, a17, a18, a19, a20);
+#  endif
+#endif
+
+    /* check that printf() results fit in buffer */
+    if (len == 0 || len >= state->size || next[state->size - 1] != 0)
+        return 0;
+
+    /* update buffer and position, compress first half if past that */
+    strm->avail_in += len;
+    state->x.pos += len;
+    if (strm->avail_in >= state->size) {
+        left = strm->avail_in - state->size;
+        strm->avail_in = state->size;
+        if (gz_comp(state, Z_NO_FLUSH) == -1)
+            return state->err;
+        memcpy(state->in, state->in + state->size, left);
+        strm->next_in = state->in;
+        strm->avail_in = left;
+    }
+    return (int)len;
+}
+
+#endif
+
+/* -- see zlib.h -- */
+int ZEXPORT gzflush(file, flush)
+    gzFile file;
+    int flush;
+{
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return Z_STREAM_ERROR;
+    state = (gz_statep)file;
+
+    /* check that we're writing and that there's no error */
+    if (state->mode != GZ_WRITE || state->err != Z_OK)
+        return Z_STREAM_ERROR;
+
+    /* check flush parameter */
+    if (flush < 0 || flush > Z_FINISH)
+        return Z_STREAM_ERROR;
+
+    /* check for seek request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_zero(state, state->skip) == -1)
+            return state->err;
+    }
+
+    /* compress remaining data with requested flush */
+    (void)gz_comp(state, flush);
+    return state->err;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzsetparams(file, level, strategy)
+    gzFile file;
+    int level;
+    int strategy;
+{
+    gz_statep state;
+    z_streamp strm;
+
+    /* get internal structure */
+    if (file == NULL)
+        return Z_STREAM_ERROR;
+    state = (gz_statep)file;
+    strm = &(state->strm);
+
+    /* check that we're writing and that there's no error */
+    if (state->mode != GZ_WRITE || state->err != Z_OK)
+        return Z_STREAM_ERROR;
+
+    /* if no change is requested, then do nothing */
+    if (level == state->level && strategy == state->strategy)
+        return Z_OK;
+
+    /* check for seek request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_zero(state, state->skip) == -1)
+            return state->err;
+    }
+
+    /* change compression parameters for subsequent input */
+    if (state->size) {
+        /* flush previous input with previous parameters before changing */
+        if (strm->avail_in && gz_comp(state, Z_BLOCK) == -1)
+            return state->err;
+        deflateParams(strm, level, strategy);
+    }
+    state->level = level;
+    state->strategy = strategy;
+    return Z_OK;
+}
+
+/* -- see zlib.h -- */
+int ZEXPORT gzclose_w(file)
+    gzFile file;
+{
+    int ret = Z_OK;
+    gz_statep state;
+
+    /* get internal structure */
+    if (file == NULL)
+        return Z_STREAM_ERROR;
+    state = (gz_statep)file;
+
+    /* check that we're writing */
+    if (state->mode != GZ_WRITE)
+        return Z_STREAM_ERROR;
+
+    /* check for seek request */
+    if (state->seek) {
+        state->seek = 0;
+        if (gz_zero(state, state->skip) == -1)
+            ret = state->err;
+    }
+
+    /* flush, free memory, and close file */
+    if (gz_comp(state, Z_FINISH) == -1)
+        ret = state->err;
+    if (state->size) {
+        if (!state->direct) {
+            (void)deflateEnd(&(state->strm));
+            free(state->out);
+        }
+        free(state->in);
+    }
+    gz_error(state, Z_OK, NULL);
+    free(state->path);
+    if (close(state->fd) == -1)
+        ret = Z_ERRNO;
+    free(state);
+    return ret;
+}

ADDED   3rd_party/zlib/infback.c
Index: 3rd_party/zlib/infback.c
==================================================================
--- 3rd_party/zlib/infback.c
+++ 3rd_party/zlib/infback.c
@@ -0,0 +1,640 @@
+/* infback.c -- inflate using a call-back interface
+ * Copyright (C) 1995-2016 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/*
+   This code is largely copied from inflate.c.  Normally either infback.o or
+   inflate.o would be linked into an application--not both.  The interface
+   with inffast.c is retained so that optimized assembler-coded versions of
+   inflate_fast() can be used with either inflate.c or infback.c.
+ */
+
+#include "zutil.h"
+#include "inftrees.h"
+#include "inflate.h"
+#include "inffast.h"
+
+/* function prototypes */
+local void fixedtables OF((struct inflate_state FAR *state));
+
+/*
+   strm provides memory allocation functions in zalloc and zfree, or
+   Z_NULL to use the library memory allocation functions.
+
+   windowBits is in the range 8..15, and window is a user-supplied
+   window and output buffer that is 2**windowBits bytes.
+ */
+int ZEXPORT inflateBackInit_(strm, windowBits, window, version, stream_size)
+z_streamp strm;
+int windowBits;
+unsigned char FAR *window;
+const char *version;
+int stream_size;
+{
+    struct inflate_state FAR *state;
+
+    if (version == Z_NULL || version[0] != ZLIB_VERSION[0] ||
+        stream_size != (int)(sizeof(z_stream)))
+        return Z_VERSION_ERROR;
+    if (strm == Z_NULL || window == Z_NULL ||
+        windowBits < 8 || windowBits > 15)
+        return Z_STREAM_ERROR;
+    strm->msg = Z_NULL;                 /* in case we return an error */
+    if (strm->zalloc == (alloc_func)0) {
+#ifdef Z_SOLO
+        return Z_STREAM_ERROR;
+#else
+        strm->zalloc = zcalloc;
+        strm->opaque = (voidpf)0;
+#endif
+    }
+    if (strm->zfree == (free_func)0)
+#ifdef Z_SOLO
+        return Z_STREAM_ERROR;
+#else
+    strm->zfree = zcfree;
+#endif
+    state = (struct inflate_state FAR *)ZALLOC(strm, 1,
+                                               sizeof(struct inflate_state));
+    if (state == Z_NULL) return Z_MEM_ERROR;
+    Tracev((stderr, "inflate: allocated\n"));
+    strm->state = (struct internal_state FAR *)state;
+    state->dmax = 32768U;
+    state->wbits = (uInt)windowBits;
+    state->wsize = 1U << windowBits;
+    state->window = window;
+    state->wnext = 0;
+    state->whave = 0;
+    return Z_OK;
+}
+
+/*
+   Return state with length and distance decoding tables and index sizes set to
+   fixed code decoding.  Normally this returns fixed tables from inffixed.h.
+   If BUILDFIXED is defined, then instead this routine builds the tables the
+   first time it's called, and returns those tables the first time and
+   thereafter.  This reduces the size of the code by about 2K bytes, in
+   exchange for a little execution time.  However, BUILDFIXED should not be
+   used for threaded applications, since the rewriting of the tables and virgin
+   may not be thread-safe.
+ */
+local void fixedtables(state)
+struct inflate_state FAR *state;
+{
+#ifdef BUILDFIXED
+    static int virgin = 1;
+    static code *lenfix, *distfix;
+    static code fixed[544];
+
+    /* build fixed huffman tables if first call (may not be thread safe) */
+    if (virgin) {
+        unsigned sym, bits;
+        static code *next;
+
+        /* literal/length table */
+        sym = 0;
+        while (sym < 144) state->lens[sym++] = 8;
+        while (sym < 256) state->lens[sym++] = 9;
+        while (sym < 280) state->lens[sym++] = 7;
+        while (sym < 288) state->lens[sym++] = 8;
+        next = fixed;
+        lenfix = next;
+        bits = 9;
+        inflate_table(LENS, state->lens, 288, &(next), &(bits), state->work);
+
+        /* distance table */
+        sym = 0;
+        while (sym < 32) state->lens[sym++] = 5;
+        distfix = next;
+        bits = 5;
+        inflate_table(DISTS, state->lens, 32, &(next), &(bits), state->work);
+
+        /* do this just once */
+        virgin = 0;
+    }
+#else /* !BUILDFIXED */
+#   include "inffixed.h"
+#endif /* BUILDFIXED */
+    state->lencode = lenfix;
+    state->lenbits = 9;
+    state->distcode = distfix;
+    state->distbits = 5;
+}
+
+/* Macros for inflateBack(): */
+
+/* Load returned state from inflate_fast() */
+#define LOAD() \
+    do { \
+        put = strm->next_out; \
+        left = strm->avail_out; \
+        next = strm->next_in; \
+        have = strm->avail_in; \
+        hold = state->hold; \
+        bits = state->bits; \
+    } while (0)
+
+/* Set state from registers for inflate_fast() */
+#define RESTORE() \
+    do { \
+        strm->next_out = put; \
+        strm->avail_out = left; \
+        strm->next_in = next; \
+        strm->avail_in = have; \
+        state->hold = hold; \
+        state->bits = bits; \
+    } while (0)
+
+/* Clear the input bit accumulator */
+#define INITBITS() \
+    do { \
+        hold = 0; \
+        bits = 0; \
+    } while (0)
+
+/* Assure that some input is available.  If input is requested, but denied,
+   then return a Z_BUF_ERROR from inflateBack(). */
+#define PULL() \
+    do { \
+        if (have == 0) { \
+            have = in(in_desc, &next); \
+            if (have == 0) { \
+                next = Z_NULL; \
+                ret = Z_BUF_ERROR; \
+                goto inf_leave; \
+            } \
+        } \
+    } while (0)
+
+/* Get a byte of input into the bit accumulator, or return from inflateBack()
+   with an error if there is no input available. */
+#define PULLBYTE() \
+    do { \
+        PULL(); \
+        have--; \
+        hold += (unsigned long)(*next++) << bits; \
+        bits += 8; \
+    } while (0)
+
+/* Assure that there are at least n bits in the bit accumulator.  If there is
+   not enough available input to do that, then return from inflateBack() with
+   an error. */
+#define NEEDBITS(n) \
+    do { \
+        while (bits < (unsigned)(n)) \
+            PULLBYTE(); \
+    } while (0)
+
+/* Return the low n bits of the bit accumulator (n < 16) */
+#define BITS(n) \
+    ((unsigned)hold & ((1U << (n)) - 1))
+
+/* Remove n bits from the bit accumulator */
+#define DROPBITS(n) \
+    do { \
+        hold >>= (n); \
+        bits -= (unsigned)(n); \
+    } while (0)
+
+/* Remove zero to seven bits as needed to go to a byte boundary */
+#define BYTEBITS() \
+    do { \
+        hold >>= bits & 7; \
+        bits -= bits & 7; \
+    } while (0)
+
+/* Assure that some output space is available, by writing out the window
+   if it's full.  If the write fails, return from inflateBack() with a
+   Z_BUF_ERROR. */
+#define ROOM() \
+    do { \
+        if (left == 0) { \
+            put = state->window; \
+            left = state->wsize; \
+            state->whave = left; \
+            if (out(out_desc, put, left)) { \
+                ret = Z_BUF_ERROR; \
+                goto inf_leave; \
+            } \
+        } \
+    } while (0)
+
+/*
+   strm provides the memory allocation functions and window buffer on input,
+   and provides information on the unused input on return.  For Z_DATA_ERROR
+   returns, strm will also provide an error message.
+
+   in() and out() are the call-back input and output functions.  When
+   inflateBack() needs more input, it calls in().  When inflateBack() has
+   filled the window with output, or when it completes with data in the
+   window, it calls out() to write out the data.  The application must not
+   change the provided input until in() is called again or inflateBack()
+   returns.  The application must not change the window/output buffer until
+   inflateBack() returns.
+
+   in() and out() are called with a descriptor parameter provided in the
+   inflateBack() call.  This parameter can be a structure that provides the
+   information required to do the read or write, as well as accumulated
+   information on the input and output such as totals and check values.
+
+   in() should return zero on failure.  out() should return non-zero on
+   failure.  If either in() or out() fails, than inflateBack() returns a
+   Z_BUF_ERROR.  strm->next_in can be checked for Z_NULL to see whether it
+   was in() or out() that caused in the error.  Otherwise,  inflateBack()
+   returns Z_STREAM_END on success, Z_DATA_ERROR for an deflate format
+   error, or Z_MEM_ERROR if it could not allocate memory for the state.
+   inflateBack() can also return Z_STREAM_ERROR if the input parameters
+   are not correct, i.e. strm is Z_NULL or the state was not initialized.
+ */
+int ZEXPORT inflateBack(strm, in, in_desc, out, out_desc)
+z_streamp strm;
+in_func in;
+void FAR *in_desc;
+out_func out;
+void FAR *out_desc;
+{
+    struct inflate_state FAR *state;
+    z_const unsigned char FAR *next;    /* next input */
+    unsigned char FAR *put;     /* next output */
+    unsigned have, left;        /* available input and output */
+    unsigned long hold;         /* bit buffer */
+    unsigned bits;              /* bits in bit buffer */
+    unsigned copy;              /* number of stored or match bytes to copy */
+    unsigned char FAR *from;    /* where to copy match bytes from */
+    code here;                  /* current decoding table entry */
+    code last;                  /* parent table entry */
+    unsigned len;               /* length to copy for repeats, bits to drop */
+    int ret;                    /* return code */
+    static const unsigned short order[19] = /* permutation of code lengths */
+        {16, 17, 18, 0, 8, 7, 9, 6, 10, 5, 11, 4, 12, 3, 13, 2, 14, 1, 15};
+
+    /* Check that the strm exists and that the state was initialized */
+    if (strm == Z_NULL || strm->state == Z_NULL)
+        return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+
+    /* Reset the state */
+    strm->msg = Z_NULL;
+    state->mode = TYPE;
+    state->last = 0;
+    state->whave = 0;
+    next = strm->next_in;
+    have = next != Z_NULL ? strm->avail_in : 0;
+    hold = 0;
+    bits = 0;
+    put = state->window;
+    left = state->wsize;
+
+    /* Inflate until end of block marked as last */
+    for (;;)
+        switch (state->mode) {
+        case TYPE:
+            /* determine and dispatch block type */
+            if (state->last) {
+                BYTEBITS();
+                state->mode = DONE;
+                break;
+            }
+            NEEDBITS(3);
+            state->last = BITS(1);
+            DROPBITS(1);
+            switch (BITS(2)) {
+            case 0:                             /* stored block */
+                Tracev((stderr, "inflate:     stored block%s\n",
+                        state->last ? " (last)" : ""));
+                state->mode = STORED;
+                break;
+            case 1:                             /* fixed block */
+                fixedtables(state);
+                Tracev((stderr, "inflate:     fixed codes block%s\n",
+                        state->last ? " (last)" : ""));
+                state->mode = LEN;              /* decode codes */
+                break;
+            case 2:                             /* dynamic block */
+                Tracev((stderr, "inflate:     dynamic codes block%s\n",
+                        state->last ? " (last)" : ""));
+                state->mode = TABLE;
+                break;
+            case 3:
+                strm->msg = (char *)"invalid block type";
+                state->mode = BAD;
+            }
+            DROPBITS(2);
+            break;
+
+        case STORED:
+            /* get and verify stored block length */
+            BYTEBITS();                         /* go to byte boundary */
+            NEEDBITS(32);
+            if ((hold & 0xffff) != ((hold >> 16) ^ 0xffff)) {
+                strm->msg = (char *)"invalid stored block lengths";
+                state->mode = BAD;
+                break;
+            }
+            state->length = (unsigned)hold & 0xffff;
+            Tracev((stderr, "inflate:       stored length %u\n",
+                    state->length));
+            INITBITS();
+
+            /* copy stored block from input to output */
+            while (state->length != 0) {
+                copy = state->length;
+                PULL();
+                ROOM();
+                if (copy > have) copy = have;
+                if (copy > left) copy = left;
+                zmemcpy(put, next, copy);
+                have -= copy;
+                next += copy;
+                left -= copy;
+                put += copy;
+                state->length -= copy;
+            }
+            Tracev((stderr, "inflate:       stored end\n"));
+            state->mode = TYPE;
+            break;
+
+        case TABLE:
+            /* get dynamic table entries descriptor */
+            NEEDBITS(14);
+            state->nlen = BITS(5) + 257;
+            DROPBITS(5);
+            state->ndist = BITS(5) + 1;
+            DROPBITS(5);
+            state->ncode = BITS(4) + 4;
+            DROPBITS(4);
+#ifndef PKZIP_BUG_WORKAROUND
+            if (state->nlen > 286 || state->ndist > 30) {
+                strm->msg = (char *)"too many length or distance symbols";
+                state->mode = BAD;
+                break;
+            }
+#endif
+            Tracev((stderr, "inflate:       table sizes ok\n"));
+
+            /* get code length code lengths (not a typo) */
+            state->have = 0;
+            while (state->have < state->ncode) {
+                NEEDBITS(3);
+                state->lens[order[state->have++]] = (unsigned short)BITS(3);
+                DROPBITS(3);
+            }
+            while (state->have < 19)
+                state->lens[order[state->have++]] = 0;
+            state->next = state->codes;
+            state->lencode = (code const FAR *)(state->next);
+            state->lenbits = 7;
+            ret = inflate_table(CODES, state->lens, 19, &(state->next),
+                                &(state->lenbits), state->work);
+            if (ret) {
+                strm->msg = (char *)"invalid code lengths set";
+                state->mode = BAD;
+                break;
+            }
+            Tracev((stderr, "inflate:       code lengths ok\n"));
+
+            /* get length and distance code code lengths */
+            state->have = 0;
+            while (state->have < state->nlen + state->ndist) {
+                for (;;) {
+                    here = state->lencode[BITS(state->lenbits)];
+                    if ((unsigned)(here.bits) <= bits) break;
+                    PULLBYTE();
+                }
+                if (here.val < 16) {
+                    DROPBITS(here.bits);
+                    state->lens[state->have++] = here.val;
+                }
+                else {
+                    if (here.val == 16) {
+                        NEEDBITS(here.bits + 2);
+                        DROPBITS(here.bits);
+                        if (state->have == 0) {
+                            strm->msg = (char *)"invalid bit length repeat";
+                            state->mode = BAD;
+                            break;
+                        }
+                        len = (unsigned)(state->lens[state->have - 1]);
+                        copy = 3 + BITS(2);
+                        DROPBITS(2);
+                    }
+                    else if (here.val == 17) {
+                        NEEDBITS(here.bits + 3);
+                        DROPBITS(here.bits);
+                        len = 0;
+                        copy = 3 + BITS(3);
+                        DROPBITS(3);
+                    }
+                    else {
+                        NEEDBITS(here.bits + 7);
+                        DROPBITS(here.bits);
+                        len = 0;
+                        copy = 11 + BITS(7);
+                        DROPBITS(7);
+                    }
+                    if (state->have + copy > state->nlen + state->ndist) {
+                        strm->msg = (char *)"invalid bit length repeat";
+                        state->mode = BAD;
+                        break;
+                    }
+                    while (copy--)
+                        state->lens[state->have++] = (unsigned short)len;
+                }
+            }
+
+            /* handle error breaks in while */
+            if (state->mode == BAD) break;
+
+            /* check for end-of-block code (better have one) */
+            if (state->lens[256] == 0) {
+                strm->msg = (char *)"invalid code -- missing end-of-block";
+                state->mode = BAD;
+                break;
+            }
+
+            /* build code tables -- note: do not change the lenbits or distbits
+               values here (9 and 6) without reading the comments in inftrees.h
+               concerning the ENOUGH constants, which depend on those values */
+            state->next = state->codes;
+            state->lencode = (code const FAR *)(state->next);
+            state->lenbits = 9;
+            ret = inflate_table(LENS, state->lens, state->nlen, &(state->next),
+                                &(state->lenbits), state->work);
+            if (ret) {
+                strm->msg = (char *)"invalid literal/lengths set";
+                state->mode = BAD;
+                break;
+            }
+            state->distcode = (code const FAR *)(state->next);
+            state->distbits = 6;
+            ret = inflate_table(DISTS, state->lens + state->nlen, state->ndist,
+                            &(state->next), &(state->distbits), state->work);
+            if (ret) {
+                strm->msg = (char *)"invalid distances set";
+                state->mode = BAD;
+                break;
+            }
+            Tracev((stderr, "inflate:       codes ok\n"));
+            state->mode = LEN;
+
+        case LEN:
+            /* use inflate_fast() if we have enough input and output */
+            if (have >= 6 && left >= 258) {
+                RESTORE();
+                if (state->whave < state->wsize)
+                    state->whave = state->wsize - left;
+                inflate_fast(strm, state->wsize);
+                LOAD();
+                break;
+            }
+
+            /* get a literal, length, or end-of-block code */
+            for (;;) {
+                here = state->lencode[BITS(state->lenbits)];
+                if ((unsigned)(here.bits) <= bits) break;
+                PULLBYTE();
+            }
+            if (here.op && (here.op & 0xf0) == 0) {
+                last = here;
+                for (;;) {
+                    here = state->lencode[last.val +
+                            (BITS(last.bits + last.op) >> last.bits)];
+                    if ((unsigned)(last.bits + here.bits) <= bits) break;
+                    PULLBYTE();
+                }
+                DROPBITS(last.bits);
+            }
+            DROPBITS(here.bits);
+            state->length = (unsigned)here.val;
+
+            /* process literal */
+            if (here.op == 0) {
+                Tracevv((stderr, here.val >= 0x20 && here.val < 0x7f ?
+                        "inflate:         literal '%c'\n" :
+                        "inflate:         literal 0x%02x\n", here.val));
+                ROOM();
+                *put++ = (unsigned char)(state->length);
+                left--;
+                state->mode = LEN;
+                break;
+            }
+
+            /* process end of block */
+            if (here.op & 32) {
+                Tracevv((stderr, "inflate:         end of block\n"));
+                state->mode = TYPE;
+                break;
+            }
+
+            /* invalid code */
+            if (here.op & 64) {
+                strm->msg = (char *)"invalid literal/length code";
+                state->mode = BAD;
+                break;
+            }
+
+            /* length code -- get extra bits, if any */
+            state->extra = (unsigned)(here.op) & 15;
+            if (state->extra != 0) {
+                NEEDBITS(state->extra);
+                state->length += BITS(state->extra);
+                DROPBITS(state->extra);
+            }
+            Tracevv((stderr, "inflate:         length %u\n", state->length));
+
+            /* get distance code */
+            for (;;) {
+                here = state->distcode[BITS(state->distbits)];
+                if ((unsigned)(here.bits) <= bits) break;
+                PULLBYTE();
+            }
+            if ((here.op & 0xf0) == 0) {
+                last = here;
+                for (;;) {
+                    here = state->distcode[last.val +
+                            (BITS(last.bits + last.op) >> last.bits)];
+                    if ((unsigned)(last.bits + here.bits) <= bits) break;
+                    PULLBYTE();
+                }
+                DROPBITS(last.bits);
+            }
+            DROPBITS(here.bits);
+            if (here.op & 64) {
+                strm->msg = (char *)"invalid distance code";
+                state->mode = BAD;
+                break;
+            }
+            state->offset = (unsigned)here.val;
+
+            /* get distance extra bits, if any */
+            state->extra = (unsigned)(here.op) & 15;
+            if (state->extra != 0) {
+                NEEDBITS(state->extra);
+                state->offset += BITS(state->extra);
+                DROPBITS(state->extra);
+            }
+            if (state->offset > state->wsize - (state->whave < state->wsize ?
+                                                left : 0)) {
+                strm->msg = (char *)"invalid distance too far back";
+                state->mode = BAD;
+                break;
+            }
+            Tracevv((stderr, "inflate:         distance %u\n", state->offset));
+
+            /* copy match from window to output */
+            do {
+                ROOM();
+                copy = state->wsize - state->offset;
+                if (copy < left) {
+                    from = put + copy;
+                    copy = left - copy;
+                }
+                else {
+                    from = put - state->offset;
+                    copy = left;
+                }
+                if (copy > state->length) copy = state->length;
+                state->length -= copy;
+                left -= copy;
+                do {
+                    *put++ = *from++;
+                } while (--copy);
+            } while (state->length != 0);
+            break;
+
+        case DONE:
+            /* inflate stream terminated properly -- write leftover output */
+            ret = Z_STREAM_END;
+            if (left < state->wsize) {
+                if (out(out_desc, state->window, state->wsize - left))
+                    ret = Z_BUF_ERROR;
+            }
+            goto inf_leave;
+
+        case BAD:
+            ret = Z_DATA_ERROR;
+            goto inf_leave;
+
+        default:                /* can't happen, but makes compilers happy */
+            ret = Z_STREAM_ERROR;
+            goto inf_leave;
+        }
+
+    /* Return unused input */
+  inf_leave:
+    strm->next_in = next;
+    strm->avail_in = have;
+    return ret;
+}
+
+int ZEXPORT inflateBackEnd(strm)
+z_streamp strm;
+{
+    if (strm == Z_NULL || strm->state == Z_NULL || strm->zfree == (free_func)0)
+        return Z_STREAM_ERROR;
+    ZFREE(strm, strm->state);
+    strm->state = Z_NULL;
+    Tracev((stderr, "inflate: end\n"));
+    return Z_OK;
+}

ADDED   3rd_party/zlib/inffast.c
Index: 3rd_party/zlib/inffast.c
==================================================================
--- 3rd_party/zlib/inffast.c
+++ 3rd_party/zlib/inffast.c
@@ -0,0 +1,323 @@
+/* inffast.c -- fast decoding
+ * Copyright (C) 1995-2017 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+#include "zutil.h"
+#include "inftrees.h"
+#include "inflate.h"
+#include "inffast.h"
+
+#ifdef ASMINF
+#  pragma message("Assembler code may have bugs -- use at your own risk")
+#else
+
+/*
+   Decode literal, length, and distance codes and write out the resulting
+   literal and match bytes until either not enough input or output is
+   available, an end-of-block is encountered, or a data error is encountered.
+   When large enough input and output buffers are supplied to inflate(), for
+   example, a 16K input buffer and a 64K output buffer, more than 95% of the
+   inflate execution time is spent in this routine.
+
+   Entry assumptions:
+
+        state->mode == LEN
+        strm->avail_in >= 6
+        strm->avail_out >= 258
+        start >= strm->avail_out
+        state->bits < 8
+
+   On return, state->mode is one of:
+
+        LEN -- ran out of enough output space or enough available input
+        TYPE -- reached end of block code, inflate() to interpret next block
+        BAD -- error in block data
+
+   Notes:
+
+    - The maximum input bits used by a length/distance pair is 15 bits for the
+      length code, 5 bits for the length extra, 15 bits for the distance code,
+      and 13 bits for the distance extra.  This totals 48 bits, or six bytes.
+      Therefore if strm->avail_in >= 6, then there is enough input to avoid
+      checking for available input while decoding.
+
+    - The maximum bytes that a single length/distance pair can output is 258
+      bytes, which is the maximum length that can be coded.  inflate_fast()
+      requires strm->avail_out >= 258 for each loop to avoid checking for
+      output space.
+ */
+void ZLIB_INTERNAL inflate_fast(strm, start)
+z_streamp strm;
+unsigned start;         /* inflate()'s starting value for strm->avail_out */
+{
+    struct inflate_state FAR *state;
+    z_const unsigned char FAR *in;      /* local strm->next_in */
+    z_const unsigned char FAR *last;    /* have enough input while in < last */
+    unsigned char FAR *out;     /* local strm->next_out */
+    unsigned char FAR *beg;     /* inflate()'s initial strm->next_out */
+    unsigned char FAR *end;     /* while out < end, enough space available */
+#ifdef INFLATE_STRICT
+    unsigned dmax;              /* maximum distance from zlib header */
+#endif
+    unsigned wsize;             /* window size or zero if not using window */
+    unsigned whave;             /* valid bytes in the window */
+    unsigned wnext;             /* window write index */
+    unsigned char FAR *window;  /* allocated sliding window, if wsize != 0 */
+    unsigned long hold;         /* local strm->hold */
+    unsigned bits;              /* local strm->bits */
+    code const FAR *lcode;      /* local strm->lencode */
+    code const FAR *dcode;      /* local strm->distcode */
+    unsigned lmask;             /* mask for first level of length codes */
+    unsigned dmask;             /* mask for first level of distance codes */
+    code here;                  /* retrieved table entry */
+    unsigned op;                /* code bits, operation, extra bits, or */
+                                /*  window position, window bytes to copy */
+    unsigned len;               /* match length, unused bytes */
+    unsigned dist;              /* match distance */
+    unsigned char FAR *from;    /* where to copy match from */
+
+    /* copy state to local variables */
+    state = (struct inflate_state FAR *)strm->state;
+    in = strm->next_in;
+    last = in + (strm->avail_in - 5);
+    out = strm->next_out;
+    beg = out - (start - strm->avail_out);
+    end = out + (strm->avail_out - 257);
+#ifdef INFLATE_STRICT
+    dmax = state->dmax;
+#endif
+    wsize = state->wsize;
+    whave = state->whave;
+    wnext = state->wnext;
+    window = state->window;
+    hold = state->hold;
+    bits = state->bits;
+    lcode = state->lencode;
+    dcode = state->distcode;
+    lmask = (1U << state->lenbits) - 1;
+    dmask = (1U << state->distbits) - 1;
+
+    /* decode literals and length/distances until end-of-block or not enough
+       input data or output space */
+    do {
+        if (bits < 15) {
+            hold += (unsigned long)(*in++) << bits;
+            bits += 8;
+            hold += (unsigned long)(*in++) << bits;
+            bits += 8;
+        }
+        here = lcode[hold & lmask];
+      dolen:
+        op = (unsigned)(here.bits);
+        hold >>= op;
+        bits -= op;
+        op = (unsigned)(here.op);
+        if (op == 0) {                          /* literal */
+            Tracevv((stderr, here.val >= 0x20 && here.val < 0x7f ?
+                    "inflate:         literal '%c'\n" :
+                    "inflate:         literal 0x%02x\n", here.val));
+            *out++ = (unsigned char)(here.val);
+        }
+        else if (op & 16) {                     /* length base */
+            len = (unsigned)(here.val);
+            op &= 15;                           /* number of extra bits */
+            if (op) {
+                if (bits < op) {
+                    hold += (unsigned long)(*in++) << bits;
+                    bits += 8;
+                }
+                len += (unsigned)hold & ((1U << op) - 1);
+                hold >>= op;
+                bits -= op;
+            }
+            Tracevv((stderr, "inflate:         length %u\n", len));
+            if (bits < 15) {
+                hold += (unsigned long)(*in++) << bits;
+                bits += 8;
+                hold += (unsigned long)(*in++) << bits;
+                bits += 8;
+            }
+            here = dcode[hold & dmask];
+          dodist:
+            op = (unsigned)(here.bits);
+            hold >>= op;
+            bits -= op;
+            op = (unsigned)(here.op);
+            if (op & 16) {                      /* distance base */
+                dist = (unsigned)(here.val);
+                op &= 15;                       /* number of extra bits */
+                if (bits < op) {
+                    hold += (unsigned long)(*in++) << bits;
+                    bits += 8;
+                    if (bits < op) {
+                        hold += (unsigned long)(*in++) << bits;
+                        bits += 8;
+                    }
+                }
+                dist += (unsigned)hold & ((1U << op) - 1);
+#ifdef INFLATE_STRICT
+                if (dist > dmax) {
+                    strm->msg = (char *)"invalid distance too far back";
+                    state->mode = BAD;
+                    break;
+                }
+#endif
+                hold >>= op;
+                bits -= op;
+                Tracevv((stderr, "inflate:         distance %u\n", dist));
+                op = (unsigned)(out - beg);     /* max distance in output */
+                if (dist > op) {                /* see if copy from window */
+                    op = dist - op;             /* distance back in window */
+                    if (op > whave) {
+                        if (state->sane) {
+                            strm->msg =
+                                (char *)"invalid distance too far back";
+                            state->mode = BAD;
+                            break;
+                        }
+#ifdef INFLATE_ALLOW_INVALID_DISTANCE_TOOFAR_ARRR
+                        if (len <= op - whave) {
+                            do {
+                                *out++ = 0;
+                            } while (--len);
+                            continue;
+                        }
+                        len -= op - whave;
+                        do {
+                            *out++ = 0;
+                        } while (--op > whave);
+                        if (op == 0) {
+                            from = out - dist;
+                            do {
+                                *out++ = *from++;
+                            } while (--len);
+                            continue;
+                        }
+#endif
+                    }
+                    from = window;
+                    if (wnext == 0) {           /* very common case */
+                        from += wsize - op;
+                        if (op < len) {         /* some from window */
+                            len -= op;
+                            do {
+                                *out++ = *from++;
+                            } while (--op);
+                            from = out - dist;  /* rest from output */
+                        }
+                    }
+                    else if (wnext < op) {      /* wrap around window */
+                        from += wsize + wnext - op;
+                        op -= wnext;
+                        if (op < len) {         /* some from end of window */
+                            len -= op;
+                            do {
+                                *out++ = *from++;
+                            } while (--op);
+                            from = window;
+                            if (wnext < len) {  /* some from start of window */
+                                op = wnext;
+                                len -= op;
+                                do {
+                                    *out++ = *from++;
+                                } while (--op);
+                                from = out - dist;      /* rest from output */
+                            }
+                        }
+                    }
+                    else {                      /* contiguous in window */
+                        from += wnext - op;
+                        if (op < len) {         /* some from window */
+                            len -= op;
+                            do {
+                                *out++ = *from++;
+                            } while (--op);
+                            from = out - dist;  /* rest from output */
+                        }
+                    }
+                    while (len > 2) {
+                        *out++ = *from++;
+                        *out++ = *from++;
+                        *out++ = *from++;
+                        len -= 3;
+                    }
+                    if (len) {
+                        *out++ = *from++;
+                        if (len > 1)
+                            *out++ = *from++;
+                    }
+                }
+                else {
+                    from = out - dist;          /* copy direct from output */
+                    do {                        /* minimum length is three */
+                        *out++ = *from++;
+                        *out++ = *from++;
+                        *out++ = *from++;
+                        len -= 3;
+                    } while (len > 2);
+                    if (len) {
+                        *out++ = *from++;
+                        if (len > 1)
+                            *out++ = *from++;
+                    }
+                }
+            }
+            else if ((op & 64) == 0) {          /* 2nd level distance code */
+                here = dcode[here.val + (hold & ((1U << op) - 1))];
+                goto dodist;
+            }
+            else {
+                strm->msg = (char *)"invalid distance code";
+                state->mode = BAD;
+                break;
+            }
+        }
+        else if ((op & 64) == 0) {              /* 2nd level length code */
+            here = lcode[here.val + (hold & ((1U << op) - 1))];
+            goto dolen;
+        }
+        else if (op & 32) {                     /* end-of-block */
+            Tracevv((stderr, "inflate:         end of block\n"));
+            state->mode = TYPE;
+            break;
+        }
+        else {
+            strm->msg = (char *)"invalid literal/length code";
+            state->mode = BAD;
+            break;
+        }
+    } while (in < last && out < end);
+
+    /* return unused bytes (on entry, bits < 8, so in won't go too far back) */
+    len = bits >> 3;
+    in -= len;
+    bits -= len << 3;
+    hold &= (1U << bits) - 1;
+
+    /* update state and return */
+    strm->next_in = in;
+    strm->next_out = out;
+    strm->avail_in = (unsigned)(in < last ? 5 + (last - in) : 5 - (in - last));
+    strm->avail_out = (unsigned)(out < end ?
+                                 257 + (end - out) : 257 - (out - end));
+    state->hold = hold;
+    state->bits = bits;
+    return;
+}
+
+/*
+   inflate_fast() speedups that turned out slower (on a PowerPC G3 750CXe):
+   - Using bit fields for code structure
+   - Different op definition to avoid & for extra bits (do & for table bits)
+   - Three separate decoding do-loops for direct, window, and wnext == 0
+   - Special case for distance > 1 copies to do overlapped load and store copy
+   - Explicit branch predictions (based on measured branch probabilities)
+   - Deferring match copy and interspersed it with decoding subsequent codes
+   - Swapping literal/length else
+   - Swapping window/direct else
+   - Larger unrolled copy loops (three is about right)
+   - Moving len -= 3 statement into middle of loop
+ */
+
+#endif /* !ASMINF */

ADDED   3rd_party/zlib/inffast.h
Index: 3rd_party/zlib/inffast.h
==================================================================
--- 3rd_party/zlib/inffast.h
+++ 3rd_party/zlib/inffast.h
@@ -0,0 +1,11 @@
+/* inffast.h -- header to use inffast.c
+ * Copyright (C) 1995-2003, 2010 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* WARNING: this file should *not* be used by applications. It is
+   part of the implementation of the compression library and is
+   subject to change. Applications should only use zlib.h.
+ */
+
+void ZLIB_INTERNAL inflate_fast OF((z_streamp strm, unsigned start));

ADDED   3rd_party/zlib/inffixed.h
Index: 3rd_party/zlib/inffixed.h
==================================================================
--- 3rd_party/zlib/inffixed.h
+++ 3rd_party/zlib/inffixed.h
@@ -0,0 +1,94 @@
+    /* inffixed.h -- table for decoding fixed codes
+     * Generated automatically by makefixed().
+     */
+
+    /* WARNING: this file should *not* be used by applications.
+       It is part of the implementation of this library and is
+       subject to change. Applications should only use zlib.h.
+     */
+
+    static const code lenfix[512] = {
+        {96,7,0},{0,8,80},{0,8,16},{20,8,115},{18,7,31},{0,8,112},{0,8,48},
+        {0,9,192},{16,7,10},{0,8,96},{0,8,32},{0,9,160},{0,8,0},{0,8,128},
+        {0,8,64},{0,9,224},{16,7,6},{0,8,88},{0,8,24},{0,9,144},{19,7,59},
+        {0,8,120},{0,8,56},{0,9,208},{17,7,17},{0,8,104},{0,8,40},{0,9,176},
+        {0,8,8},{0,8,136},{0,8,72},{0,9,240},{16,7,4},{0,8,84},{0,8,20},
+        {21,8,227},{19,7,43},{0,8,116},{0,8,52},{0,9,200},{17,7,13},{0,8,100},
+        {0,8,36},{0,9,168},{0,8,4},{0,8,132},{0,8,68},{0,9,232},{16,7,8},
+        {0,8,92},{0,8,28},{0,9,152},{20,7,83},{0,8,124},{0,8,60},{0,9,216},
+        {18,7,23},{0,8,108},{0,8,44},{0,9,184},{0,8,12},{0,8,140},{0,8,76},
+        {0,9,248},{16,7,3},{0,8,82},{0,8,18},{21,8,163},{19,7,35},{0,8,114},
+        {0,8,50},{0,9,196},{17,7,11},{0,8,98},{0,8,34},{0,9,164},{0,8,2},
+        {0,8,130},{0,8,66},{0,9,228},{16,7,7},{0,8,90},{0,8,26},{0,9,148},
+        {20,7,67},{0,8,122},{0,8,58},{0,9,212},{18,7,19},{0,8,106},{0,8,42},
+        {0,9,180},{0,8,10},{0,8,138},{0,8,74},{0,9,244},{16,7,5},{0,8,86},
+        {0,8,22},{64,8,0},{19,7,51},{0,8,118},{0,8,54},{0,9,204},{17,7,15},
+        {0,8,102},{0,8,38},{0,9,172},{0,8,6},{0,8,134},{0,8,70},{0,9,236},
+        {16,7,9},{0,8,94},{0,8,30},{0,9,156},{20,7,99},{0,8,126},{0,8,62},
+        {0,9,220},{18,7,27},{0,8,110},{0,8,46},{0,9,188},{0,8,14},{0,8,142},
+        {0,8,78},{0,9,252},{96,7,0},{0,8,81},{0,8,17},{21,8,131},{18,7,31},
+        {0,8,113},{0,8,49},{0,9,194},{16,7,10},{0,8,97},{0,8,33},{0,9,162},
+        {0,8,1},{0,8,129},{0,8,65},{0,9,226},{16,7,6},{0,8,89},{0,8,25},
+        {0,9,146},{19,7,59},{0,8,121},{0,8,57},{0,9,210},{17,7,17},{0,8,105},
+        {0,8,41},{0,9,178},{0,8,9},{0,8,137},{0,8,73},{0,9,242},{16,7,4},
+        {0,8,85},{0,8,21},{16,8,258},{19,7,43},{0,8,117},{0,8,53},{0,9,202},
+        {17,7,13},{0,8,101},{0,8,37},{0,9,170},{0,8,5},{0,8,133},{0,8,69},
+        {0,9,234},{16,7,8},{0,8,93},{0,8,29},{0,9,154},{20,7,83},{0,8,125},
+        {0,8,61},{0,9,218},{18,7,23},{0,8,109},{0,8,45},{0,9,186},{0,8,13},
+        {0,8,141},{0,8,77},{0,9,250},{16,7,3},{0,8,83},{0,8,19},{21,8,195},
+        {19,7,35},{0,8,115},{0,8,51},{0,9,198},{17,7,11},{0,8,99},{0,8,35},
+        {0,9,166},{0,8,3},{0,8,131},{0,8,67},{0,9,230},{16,7,7},{0,8,91},
+        {0,8,27},{0,9,150},{20,7,67},{0,8,123},{0,8,59},{0,9,214},{18,7,19},
+        {0,8,107},{0,8,43},{0,9,182},{0,8,11},{0,8,139},{0,8,75},{0,9,246},
+        {16,7,5},{0,8,87},{0,8,23},{64,8,0},{19,7,51},{0,8,119},{0,8,55},
+        {0,9,206},{17,7,15},{0,8,103},{0,8,39},{0,9,174},{0,8,7},{0,8,135},
+        {0,8,71},{0,9,238},{16,7,9},{0,8,95},{0,8,31},{0,9,158},{20,7,99},
+        {0,8,127},{0,8,63},{0,9,222},{18,7,27},{0,8,111},{0,8,47},{0,9,190},
+        {0,8,15},{0,8,143},{0,8,79},{0,9,254},{96,7,0},{0,8,80},{0,8,16},
+        {20,8,115},{18,7,31},{0,8,112},{0,8,48},{0,9,193},{16,7,10},{0,8,96},
+        {0,8,32},{0,9,161},{0,8,0},{0,8,128},{0,8,64},{0,9,225},{16,7,6},
+        {0,8,88},{0,8,24},{0,9,145},{19,7,59},{0,8,120},{0,8,56},{0,9,209},
+        {17,7,17},{0,8,104},{0,8,40},{0,9,177},{0,8,8},{0,8,136},{0,8,72},
+        {0,9,241},{16,7,4},{0,8,84},{0,8,20},{21,8,227},{19,7,43},{0,8,116},
+        {0,8,52},{0,9,201},{17,7,13},{0,8,100},{0,8,36},{0,9,169},{0,8,4},
+        {0,8,132},{0,8,68},{0,9,233},{16,7,8},{0,8,92},{0,8,28},{0,9,153},
+        {20,7,83},{0,8,124},{0,8,60},{0,9,217},{18,7,23},{0,8,108},{0,8,44},
+        {0,9,185},{0,8,12},{0,8,140},{0,8,76},{0,9,249},{16,7,3},{0,8,82},
+        {0,8,18},{21,8,163},{19,7,35},{0,8,114},{0,8,50},{0,9,197},{17,7,11},
+        {0,8,98},{0,8,34},{0,9,165},{0,8,2},{0,8,130},{0,8,66},{0,9,229},
+        {16,7,7},{0,8,90},{0,8,26},{0,9,149},{20,7,67},{0,8,122},{0,8,58},
+        {0,9,213},{18,7,19},{0,8,106},{0,8,42},{0,9,181},{0,8,10},{0,8,138},
+        {0,8,74},{0,9,245},{16,7,5},{0,8,86},{0,8,22},{64,8,0},{19,7,51},
+        {0,8,118},{0,8,54},{0,9,205},{17,7,15},{0,8,102},{0,8,38},{0,9,173},
+        {0,8,6},{0,8,134},{0,8,70},{0,9,237},{16,7,9},{0,8,94},{0,8,30},
+        {0,9,157},{20,7,99},{0,8,126},{0,8,62},{0,9,221},{18,7,27},{0,8,110},
+        {0,8,46},{0,9,189},{0,8,14},{0,8,142},{0,8,78},{0,9,253},{96,7,0},
+        {0,8,81},{0,8,17},{21,8,131},{18,7,31},{0,8,113},{0,8,49},{0,9,195},
+        {16,7,10},{0,8,97},{0,8,33},{0,9,163},{0,8,1},{0,8,129},{0,8,65},
+        {0,9,227},{16,7,6},{0,8,89},{0,8,25},{0,9,147},{19,7,59},{0,8,121},
+        {0,8,57},{0,9,211},{17,7,17},{0,8,105},{0,8,41},{0,9,179},{0,8,9},
+        {0,8,137},{0,8,73},{0,9,243},{16,7,4},{0,8,85},{0,8,21},{16,8,258},
+        {19,7,43},{0,8,117},{0,8,53},{0,9,203},{17,7,13},{0,8,101},{0,8,37},
+        {0,9,171},{0,8,5},{0,8,133},{0,8,69},{0,9,235},{16,7,8},{0,8,93},
+        {0,8,29},{0,9,155},{20,7,83},{0,8,125},{0,8,61},{0,9,219},{18,7,23},
+        {0,8,109},{0,8,45},{0,9,187},{0,8,13},{0,8,141},{0,8,77},{0,9,251},
+        {16,7,3},{0,8,83},{0,8,19},{21,8,195},{19,7,35},{0,8,115},{0,8,51},
+        {0,9,199},{17,7,11},{0,8,99},{0,8,35},{0,9,167},{0,8,3},{0,8,131},
+        {0,8,67},{0,9,231},{16,7,7},{0,8,91},{0,8,27},{0,9,151},{20,7,67},
+        {0,8,123},{0,8,59},{0,9,215},{18,7,19},{0,8,107},{0,8,43},{0,9,183},
+        {0,8,11},{0,8,139},{0,8,75},{0,9,247},{16,7,5},{0,8,87},{0,8,23},
+        {64,8,0},{19,7,51},{0,8,119},{0,8,55},{0,9,207},{17,7,15},{0,8,103},
+        {0,8,39},{0,9,175},{0,8,7},{0,8,135},{0,8,71},{0,9,239},{16,7,9},
+        {0,8,95},{0,8,31},{0,9,159},{20,7,99},{0,8,127},{0,8,63},{0,9,223},
+        {18,7,27},{0,8,111},{0,8,47},{0,9,191},{0,8,15},{0,8,143},{0,8,79},
+        {0,9,255}
+    };
+
+    static const code distfix[32] = {
+        {16,5,1},{23,5,257},{19,5,17},{27,5,4097},{17,5,5},{25,5,1025},
+        {21,5,65},{29,5,16385},{16,5,3},{24,5,513},{20,5,33},{28,5,8193},
+        {18,5,9},{26,5,2049},{22,5,129},{64,5,0},{16,5,2},{23,5,385},
+        {19,5,25},{27,5,6145},{17,5,7},{25,5,1537},{21,5,97},{29,5,24577},
+        {16,5,4},{24,5,769},{20,5,49},{28,5,12289},{18,5,13},{26,5,3073},
+        {22,5,193},{64,5,0}
+    };

ADDED   3rd_party/zlib/inflate.c
Index: 3rd_party/zlib/inflate.c
==================================================================
--- 3rd_party/zlib/inflate.c
+++ 3rd_party/zlib/inflate.c
@@ -0,0 +1,1561 @@
+/* inflate.c -- zlib decompression
+ * Copyright (C) 1995-2016 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/*
+ * Change history:
+ *
+ * 1.2.beta0    24 Nov 2002
+ * - First version -- complete rewrite of inflate to simplify code, avoid
+ *   creation of window when not needed, minimize use of window when it is
+ *   needed, make inffast.c even faster, implement gzip decoding, and to
+ *   improve code readability and style over the previous zlib inflate code
+ *
+ * 1.2.beta1    25 Nov 2002
+ * - Use pointers for available input and output checking in inffast.c
+ * - Remove input and output counters in inffast.c
+ * - Change inffast.c entry and loop from avail_in >= 7 to >= 6
+ * - Remove unnecessary second byte pull from length extra in inffast.c
+ * - Unroll direct copy to three copies per loop in inffast.c
+ *
+ * 1.2.beta2    4 Dec 2002
+ * - Change external routine names to reduce potential conflicts
+ * - Correct filename to inffixed.h for fixed tables in inflate.c
+ * - Make hbuf[] unsigned char to match parameter type in inflate.c
+ * - Change strm->next_out[-state->offset] to *(strm->next_out - state->offset)
+ *   to avoid negation problem on Alphas (64 bit) in inflate.c
+ *
+ * 1.2.beta3    22 Dec 2002
+ * - Add comments on state->bits assertion in inffast.c
+ * - Add comments on op field in inftrees.h
+ * - Fix bug in reuse of allocated window after inflateReset()
+ * - Remove bit fields--back to byte structure for speed
+ * - Remove distance extra == 0 check in inflate_fast()--only helps for lengths
+ * - Change post-increments to pre-increments in inflate_fast(), PPC biased?
+ * - Add compile time option, POSTINC, to use post-increments instead (Intel?)
+ * - Make MATCH copy in inflate() much faster for when inflate_fast() not used
+ * - Use local copies of stream next and avail values, as well as local bit
+ *   buffer and bit count in inflate()--for speed when inflate_fast() not used
+ *
+ * 1.2.beta4    1 Jan 2003
+ * - Split ptr - 257 statements in inflate_table() to avoid compiler warnings
+ * - Move a comment on output buffer sizes from inffast.c to inflate.c
+ * - Add comments in inffast.c to introduce the inflate_fast() routine
+ * - Rearrange window copies in inflate_fast() for speed and simplification
+ * - Unroll last copy for window match in inflate_fast()
+ * - Use local copies of window variables in inflate_fast() for speed
+ * - Pull out common wnext == 0 case for speed in inflate_fast()
+ * - Make op and len in inflate_fast() unsigned for consistency
+ * - Add FAR to lcode and dcode declarations in inflate_fast()
+ * - Simplified bad distance check in inflate_fast()
+ * - Added inflateBackInit(), inflateBack(), and inflateBackEnd() in new
+ *   source file infback.c to provide a call-back interface to inflate for
+ *   programs like gzip and unzip -- uses window as output buffer to avoid
+ *   window copying
+ *
+ * 1.2.beta5    1 Jan 2003
+ * - Improved inflateBack() interface to allow the caller to provide initial
+ *   input in strm.
+ * - Fixed stored blocks bug in inflateBack()
+ *
+ * 1.2.beta6    4 Jan 2003
+ * - Added comments in inffast.c on effectiveness of POSTINC
+ * - Typecasting all around to reduce compiler warnings
+ * - Changed loops from while (1) or do {} while (1) to for (;;), again to
+ *   make compilers happy
+ * - Changed type of window in inflateBackInit() to unsigned char *
+ *
+ * 1.2.beta7    27 Jan 2003
+ * - Changed many types to unsigned or unsigned short to avoid warnings
+ * - Added inflateCopy() function
+ *
+ * 1.2.0        9 Mar 2003
+ * - Changed inflateBack() interface to provide separate opaque descriptors
+ *   for the in() and out() functions
+ * - Changed inflateBack() argument and in_func typedef to swap the length
+ *   and buffer address return values for the input function
+ * - Check next_in and next_out for Z_NULL on entry to inflate()
+ *
+ * The history for versions after 1.2.0 are in ChangeLog in zlib distribution.
+ */
+
+#include "zutil.h"
+#include "inftrees.h"
+#include "inflate.h"
+#include "inffast.h"
+
+#ifdef MAKEFIXED
+#  ifndef BUILDFIXED
+#    define BUILDFIXED
+#  endif
+#endif
+
+/* function prototypes */
+local int inflateStateCheck OF((z_streamp strm));
+local void fixedtables OF((struct inflate_state FAR *state));
+local int updatewindow OF((z_streamp strm, const unsigned char FAR *end,
+                           unsigned copy));
+#ifdef BUILDFIXED
+   void makefixed OF((void));
+#endif
+local unsigned syncsearch OF((unsigned FAR *have, const unsigned char FAR *buf,
+                              unsigned len));
+
+local int inflateStateCheck(strm)
+z_streamp strm;
+{
+    struct inflate_state FAR *state;
+    if (strm == Z_NULL ||
+        strm->zalloc == (alloc_func)0 || strm->zfree == (free_func)0)
+        return 1;
+    state = (struct inflate_state FAR *)strm->state;
+    if (state == Z_NULL || state->strm != strm ||
+        state->mode < HEAD || state->mode > SYNC)
+        return 1;
+    return 0;
+}
+
+int ZEXPORT inflateResetKeep(strm)
+z_streamp strm;
+{
+    struct inflate_state FAR *state;
+
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    strm->total_in = strm->total_out = state->total = 0;
+    strm->msg = Z_NULL;
+    if (state->wrap)        /* to support ill-conceived Java test suite */
+        strm->adler = state->wrap & 1;
+    state->mode = HEAD;
+    state->last = 0;
+    state->havedict = 0;
+    state->dmax = 32768U;
+    state->head = Z_NULL;
+    state->hold = 0;
+    state->bits = 0;
+    state->lencode = state->distcode = state->next = state->codes;
+    state->sane = 1;
+    state->back = -1;
+    Tracev((stderr, "inflate: reset\n"));
+    return Z_OK;
+}
+
+int ZEXPORT inflateReset(strm)
+z_streamp strm;
+{
+    struct inflate_state FAR *state;
+
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    state->wsize = 0;
+    state->whave = 0;
+    state->wnext = 0;
+    return inflateResetKeep(strm);
+}
+
+int ZEXPORT inflateReset2(strm, windowBits)
+z_streamp strm;
+int windowBits;
+{
+    int wrap;
+    struct inflate_state FAR *state;
+
+    /* get the state */
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+
+    /* extract wrap request from windowBits parameter */
+    if (windowBits < 0) {
+        wrap = 0;
+        windowBits = -windowBits;
+    }
+    else {
+        wrap = (windowBits >> 4) + 5;
+#ifdef GUNZIP
+        if (windowBits < 48)
+            windowBits &= 15;
+#endif
+    }
+
+    /* set number of window bits, free window if different */
+    if (windowBits && (windowBits < 8 || windowBits > 15))
+        return Z_STREAM_ERROR;
+    if (state->window != Z_NULL && state->wbits != (unsigned)windowBits) {
+        ZFREE(strm, state->window);
+        state->window = Z_NULL;
+    }
+
+    /* update state and reset the rest of it */
+    state->wrap = wrap;
+    state->wbits = (unsigned)windowBits;
+    return inflateReset(strm);
+}
+
+int ZEXPORT inflateInit2_(strm, windowBits, version, stream_size)
+z_streamp strm;
+int windowBits;
+const char *version;
+int stream_size;
+{
+    int ret;
+    struct inflate_state FAR *state;
+
+    if (version == Z_NULL || version[0] != ZLIB_VERSION[0] ||
+        stream_size != (int)(sizeof(z_stream)))
+        return Z_VERSION_ERROR;
+    if (strm == Z_NULL) return Z_STREAM_ERROR;
+    strm->msg = Z_NULL;                 /* in case we return an error */
+    if (strm->zalloc == (alloc_func)0) {
+#ifdef Z_SOLO
+        return Z_STREAM_ERROR;
+#else
+        strm->zalloc = zcalloc;
+        strm->opaque = (voidpf)0;
+#endif
+    }
+    if (strm->zfree == (free_func)0)
+#ifdef Z_SOLO
+        return Z_STREAM_ERROR;
+#else
+        strm->zfree = zcfree;
+#endif
+    state = (struct inflate_state FAR *)
+            ZALLOC(strm, 1, sizeof(struct inflate_state));
+    if (state == Z_NULL) return Z_MEM_ERROR;
+    Tracev((stderr, "inflate: allocated\n"));
+    strm->state = (struct internal_state FAR *)state;
+    state->strm = strm;
+    state->window = Z_NULL;
+    state->mode = HEAD;     /* to pass state test in inflateReset2() */
+    ret = inflateReset2(strm, windowBits);
+    if (ret != Z_OK) {
+        ZFREE(strm, state);
+        strm->state = Z_NULL;
+    }
+    return ret;
+}
+
+int ZEXPORT inflateInit_(strm, version, stream_size)
+z_streamp strm;
+const char *version;
+int stream_size;
+{
+    return inflateInit2_(strm, DEF_WBITS, version, stream_size);
+}
+
+int ZEXPORT inflatePrime(strm, bits, value)
+z_streamp strm;
+int bits;
+int value;
+{
+    struct inflate_state FAR *state;
+
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    if (bits < 0) {
+        state->hold = 0;
+        state->bits = 0;
+        return Z_OK;
+    }
+    if (bits > 16 || state->bits + (uInt)bits > 32) return Z_STREAM_ERROR;
+    value &= (1L << bits) - 1;
+    state->hold += (unsigned)value << state->bits;
+    state->bits += (uInt)bits;
+    return Z_OK;
+}
+
+/*
+   Return state with length and distance decoding tables and index sizes set to
+   fixed code decoding.  Normally this returns fixed tables from inffixed.h.
+   If BUILDFIXED is defined, then instead this routine builds the tables the
+   first time it's called, and returns those tables the first time and
+   thereafter.  This reduces the size of the code by about 2K bytes, in
+   exchange for a little execution time.  However, BUILDFIXED should not be
+   used for threaded applications, since the rewriting of the tables and virgin
+   may not be thread-safe.
+ */
+local void fixedtables(state)
+struct inflate_state FAR *state;
+{
+#ifdef BUILDFIXED
+    static int virgin = 1;
+    static code *lenfix, *distfix;
+    static code fixed[544];
+
+    /* build fixed huffman tables if first call (may not be thread safe) */
+    if (virgin) {
+        unsigned sym, bits;
+        static code *next;
+
+        /* literal/length table */
+        sym = 0;
+        while (sym < 144) state->lens[sym++] = 8;
+        while (sym < 256) state->lens[sym++] = 9;
+        while (sym < 280) state->lens[sym++] = 7;
+        while (sym < 288) state->lens[sym++] = 8;
+        next = fixed;
+        lenfix = next;
+        bits = 9;
+        inflate_table(LENS, state->lens, 288, &(next), &(bits), state->work);
+
+        /* distance table */
+        sym = 0;
+        while (sym < 32) state->lens[sym++] = 5;
+        distfix = next;
+        bits = 5;
+        inflate_table(DISTS, state->lens, 32, &(next), &(bits), state->work);
+
+        /* do this just once */
+        virgin = 0;
+    }
+#else /* !BUILDFIXED */
+#   include "inffixed.h"
+#endif /* BUILDFIXED */
+    state->lencode = lenfix;
+    state->lenbits = 9;
+    state->distcode = distfix;
+    state->distbits = 5;
+}
+
+#ifdef MAKEFIXED
+#include <stdio.h>
+
+/*
+   Write out the inffixed.h that is #include'd above.  Defining MAKEFIXED also
+   defines BUILDFIXED, so the tables are built on the fly.  makefixed() writes
+   those tables to stdout, which would be piped to inffixed.h.  A small program
+   can simply call makefixed to do this:
+
+    void makefixed(void);
+
+    int main(void)
+    {
+        makefixed();
+        return 0;
+    }
+
+   Then that can be linked with zlib built with MAKEFIXED defined and run:
+
+    a.out > inffixed.h
+ */
+void makefixed()
+{
+    unsigned low, size;
+    struct inflate_state state;
+
+    fixedtables(&state);
+    puts("    /* inffixed.h -- table for decoding fixed codes");
+    puts("     * Generated automatically by makefixed().");
+    puts("     */");
+    puts("");
+    puts("    /* WARNING: this file should *not* be used by applications.");
+    puts("       It is part of the implementation of this library and is");
+    puts("       subject to change. Applications should only use zlib.h.");
+    puts("     */");
+    puts("");
+    size = 1U << 9;
+    printf("    static const code lenfix[%u] = {", size);
+    low = 0;
+    for (;;) {
+        if ((low % 7) == 0) printf("\n        ");
+        printf("{%u,%u,%d}", (low & 127) == 99 ? 64 : state.lencode[low].op,
+               state.lencode[low].bits, state.lencode[low].val);
+        if (++low == size) break;
+        putchar(',');
+    }
+    puts("\n    };");
+    size = 1U << 5;
+    printf("\n    static const code distfix[%u] = {", size);
+    low = 0;
+    for (;;) {
+        if ((low % 6) == 0) printf("\n        ");
+        printf("{%u,%u,%d}", state.distcode[low].op, state.distcode[low].bits,
+               state.distcode[low].val);
+        if (++low == size) break;
+        putchar(',');
+    }
+    puts("\n    };");
+}
+#endif /* MAKEFIXED */
+
+/*
+   Update the window with the last wsize (normally 32K) bytes written before
+   returning.  If window does not exist yet, create it.  This is only called
+   when a window is already in use, or when output has been written during this
+   inflate call, but the end of the deflate stream has not been reached yet.
+   It is also called to create a window for dictionary data when a dictionary
+   is loaded.
+
+   Providing output buffers larger than 32K to inflate() should provide a speed
+   advantage, since only the last 32K of output is copied to the sliding window
+   upon return from inflate(), and since all distances after the first 32K of
+   output will fall in the output data, making match copies simpler and faster.
+   The advantage may be dependent on the size of the processor's data caches.
+ */
+local int updatewindow(strm, end, copy)
+z_streamp strm;
+const Bytef *end;
+unsigned copy;
+{
+    struct inflate_state FAR *state;
+    unsigned dist;
+
+    state = (struct inflate_state FAR *)strm->state;
+
+    /* if it hasn't been done already, allocate space for the window */
+    if (state->window == Z_NULL) {
+        state->window = (unsigned char FAR *)
+                        ZALLOC(strm, 1U << state->wbits,
+                               sizeof(unsigned char));
+        if (state->window == Z_NULL) return 1;
+    }
+
+    /* if window not in use yet, initialize */
+    if (state->wsize == 0) {
+        state->wsize = 1U << state->wbits;
+        state->wnext = 0;
+        state->whave = 0;
+    }
+
+    /* copy state->wsize or less output bytes into the circular window */
+    if (copy >= state->wsize) {
+        zmemcpy(state->window, end - state->wsize, state->wsize);
+        state->wnext = 0;
+        state->whave = state->wsize;
+    }
+    else {
+        dist = state->wsize - state->wnext;
+        if (dist > copy) dist = copy;
+        zmemcpy(state->window + state->wnext, end - copy, dist);
+        copy -= dist;
+        if (copy) {
+            zmemcpy(state->window, end - copy, copy);
+            state->wnext = copy;
+            state->whave = state->wsize;
+        }
+        else {
+            state->wnext += dist;
+            if (state->wnext == state->wsize) state->wnext = 0;
+            if (state->whave < state->wsize) state->whave += dist;
+        }
+    }
+    return 0;
+}
+
+/* Macros for inflate(): */
+
+/* check function to use adler32() for zlib or crc32() for gzip */
+#ifdef GUNZIP
+#  define UPDATE(check, buf, len) \
+    (state->flags ? crc32(check, buf, len) : adler32(check, buf, len))
+#else
+#  define UPDATE(check, buf, len) adler32(check, buf, len)
+#endif
+
+/* check macros for header crc */
+#ifdef GUNZIP
+#  define CRC2(check, word) \
+    do { \
+        hbuf[0] = (unsigned char)(word); \
+        hbuf[1] = (unsigned char)((word) >> 8); \
+        check = crc32(check, hbuf, 2); \
+    } while (0)
+
+#  define CRC4(check, word) \
+    do { \
+        hbuf[0] = (unsigned char)(word); \
+        hbuf[1] = (unsigned char)((word) >> 8); \
+        hbuf[2] = (unsigned char)((word) >> 16); \
+        hbuf[3] = (unsigned char)((word) >> 24); \
+        check = crc32(check, hbuf, 4); \
+    } while (0)
+#endif
+
+/* Load registers with state in inflate() for speed */
+#define LOAD() \
+    do { \
+        put = strm->next_out; \
+        left = strm->avail_out; \
+        next = strm->next_in; \
+        have = strm->avail_in; \
+        hold = state->hold; \
+        bits = state->bits; \
+    } while (0)
+
+/* Restore state from registers in inflate() */
+#define RESTORE() \
+    do { \
+        strm->next_out = put; \
+        strm->avail_out = left; \
+        strm->next_in = next; \
+        strm->avail_in = have; \
+        state->hold = hold; \
+        state->bits = bits; \
+    } while (0)
+
+/* Clear the input bit accumulator */
+#define INITBITS() \
+    do { \
+        hold = 0; \
+        bits = 0; \
+    } while (0)
+
+/* Get a byte of input into the bit accumulator, or return from inflate()
+   if there is no input available. */
+#define PULLBYTE() \
+    do { \
+        if (have == 0) goto inf_leave; \
+        have--; \
+        hold += (unsigned long)(*next++) << bits; \
+        bits += 8; \
+    } while (0)
+
+/* Assure that there are at least n bits in the bit accumulator.  If there is
+   not enough available input to do that, then return from inflate(). */
+#define NEEDBITS(n) \
+    do { \
+        while (bits < (unsigned)(n)) \
+            PULLBYTE(); \
+    } while (0)
+
+/* Return the low n bits of the bit accumulator (n < 16) */
+#define BITS(n) \
+    ((unsigned)hold & ((1U << (n)) - 1))
+
+/* Remove n bits from the bit accumulator */
+#define DROPBITS(n) \
+    do { \
+        hold >>= (n); \
+        bits -= (unsigned)(n); \
+    } while (0)
+
+/* Remove zero to seven bits as needed to go to a byte boundary */
+#define BYTEBITS() \
+    do { \
+        hold >>= bits & 7; \
+        bits -= bits & 7; \
+    } while (0)
+
+/*
+   inflate() uses a state machine to process as much input data and generate as
+   much output data as possible before returning.  The state machine is
+   structured roughly as follows:
+
+    for (;;) switch (state) {
+    ...
+    case STATEn:
+        if (not enough input data or output space to make progress)
+            return;
+        ... make progress ...
+        state = STATEm;
+        break;
+    ...
+    }
+
+   so when inflate() is called again, the same case is attempted again, and
+   if the appropriate resources are provided, the machine proceeds to the
+   next state.  The NEEDBITS() macro is usually the way the state evaluates
+   whether it can proceed or should return.  NEEDBITS() does the return if
+   the requested bits are not available.  The typical use of the BITS macros
+   is:
+
+        NEEDBITS(n);
+        ... do something with BITS(n) ...
+        DROPBITS(n);
+
+   where NEEDBITS(n) either returns from inflate() if there isn't enough
+   input left to load n bits into the accumulator, or it continues.  BITS(n)
+   gives the low n bits in the accumulator.  When done, DROPBITS(n) drops
+   the low n bits off the accumulator.  INITBITS() clears the accumulator
+   and sets the number of available bits to zero.  BYTEBITS() discards just
+   enough bits to put the accumulator on a byte boundary.  After BYTEBITS()
+   and a NEEDBITS(8), then BITS(8) would return the next byte in the stream.
+
+   NEEDBITS(n) uses PULLBYTE() to get an available byte of input, or to return
+   if there is no input available.  The decoding of variable length codes uses
+   PULLBYTE() directly in order to pull just enough bytes to decode the next
+   code, and no more.
+
+   Some states loop until they get enough input, making sure that enough
+   state information is maintained to continue the loop where it left off
+   if NEEDBITS() returns in the loop.  For example, want, need, and keep
+   would all have to actually be part of the saved state in case NEEDBITS()
+   returns:
+
+    case STATEw:
+        while (want < need) {
+            NEEDBITS(n);
+            keep[want++] = BITS(n);
+            DROPBITS(n);
+        }
+        state = STATEx;
+    case STATEx:
+
+   As shown above, if the next state is also the next case, then the break
+   is omitted.
+
+   A state may also return if there is not enough output space available to
+   complete that state.  Those states are copying stored data, writing a
+   literal byte, and copying a matching string.
+
+   When returning, a "goto inf_leave" is used to update the total counters,
+   update the check value, and determine whether any progress has been made
+   during that inflate() call in order to return the proper return code.
+   Progress is defined as a change in either strm->avail_in or strm->avail_out.
+   When there is a window, goto inf_leave will update the window with the last
+   output written.  If a goto inf_leave occurs in the middle of decompression
+   and there is no window currently, goto inf_leave will create one and copy
+   output to the window for the next call of inflate().
+
+   In this implementation, the flush parameter of inflate() only affects the
+   return code (per zlib.h).  inflate() always writes as much as possible to
+   strm->next_out, given the space available and the provided input--the effect
+   documented in zlib.h of Z_SYNC_FLUSH.  Furthermore, inflate() always defers
+   the allocation of and copying into a sliding window until necessary, which
+   provides the effect documented in zlib.h for Z_FINISH when the entire input
+   stream available.  So the only thing the flush parameter actually does is:
+   when flush is set to Z_FINISH, inflate() cannot return Z_OK.  Instead it
+   will return Z_BUF_ERROR if it has not reached the end of the stream.
+ */
+
+int ZEXPORT inflate(strm, flush)
+z_streamp strm;
+int flush;
+{
+    struct inflate_state FAR *state;
+    z_const unsigned char FAR *next;    /* next input */
+    unsigned char FAR *put;     /* next output */
+    unsigned have, left;        /* available input and output */
+    unsigned long hold;         /* bit buffer */
+    unsigned bits;              /* bits in bit buffer */
+    unsigned in, out;           /* save starting available input and output */
+    unsigned copy;              /* number of stored or match bytes to copy */
+    unsigned char FAR *from;    /* where to copy match bytes from */
+    code here;                  /* current decoding table entry */
+    code last;                  /* parent table entry */
+    unsigned len;               /* length to copy for repeats, bits to drop */
+    int ret;                    /* return code */
+#ifdef GUNZIP
+    unsigned char hbuf[4];      /* buffer for gzip header crc calculation */
+#endif
+    static const unsigned short order[19] = /* permutation of code lengths */
+        {16, 17, 18, 0, 8, 7, 9, 6, 10, 5, 11, 4, 12, 3, 13, 2, 14, 1, 15};
+
+    if (inflateStateCheck(strm) || strm->next_out == Z_NULL ||
+        (strm->next_in == Z_NULL && strm->avail_in != 0))
+        return Z_STREAM_ERROR;
+
+    state = (struct inflate_state FAR *)strm->state;
+    if (state->mode == TYPE) state->mode = TYPEDO;      /* skip check */
+    LOAD();
+    in = have;
+    out = left;
+    ret = Z_OK;
+    for (;;)
+        switch (state->mode) {
+        case HEAD:
+            if (state->wrap == 0) {
+                state->mode = TYPEDO;
+                break;
+            }
+            NEEDBITS(16);
+#ifdef GUNZIP
+            if ((state->wrap & 2) && hold == 0x8b1f) {  /* gzip header */
+                if (state->wbits == 0)
+                    state->wbits = 15;
+                state->check = crc32(0L, Z_NULL, 0);
+                CRC2(state->check, hold);
+                INITBITS();
+                state->mode = FLAGS;
+                break;
+            }
+            state->flags = 0;           /* expect zlib header */
+            if (state->head != Z_NULL)
+                state->head->done = -1;
+            if (!(state->wrap & 1) ||   /* check if zlib header allowed */
+#else
+            if (
+#endif
+                ((BITS(8) << 8) + (hold >> 8)) % 31) {
+                strm->msg = (char *)"incorrect header check";
+                state->mode = BAD;
+                break;
+            }
+            if (BITS(4) != Z_DEFLATED) {
+                strm->msg = (char *)"unknown compression method";
+                state->mode = BAD;
+                break;
+            }
+            DROPBITS(4);
+            len = BITS(4) + 8;
+            if (state->wbits == 0)
+                state->wbits = len;
+            if (len > 15 || len > state->wbits) {
+                strm->msg = (char *)"invalid window size";
+                state->mode = BAD;
+                break;
+            }
+            state->dmax = 1U << len;
+            Tracev((stderr, "inflate:   zlib header ok\n"));
+            strm->adler = state->check = adler32(0L, Z_NULL, 0);
+            state->mode = hold & 0x200 ? DICTID : TYPE;
+            INITBITS();
+            break;
+#ifdef GUNZIP
+        case FLAGS:
+            NEEDBITS(16);
+            state->flags = (int)(hold);
+            if ((state->flags & 0xff) != Z_DEFLATED) {
+                strm->msg = (char *)"unknown compression method";
+                state->mode = BAD;
+                break;
+            }
+            if (state->flags & 0xe000) {
+                strm->msg = (char *)"unknown header flags set";
+                state->mode = BAD;
+                break;
+            }
+            if (state->head != Z_NULL)
+                state->head->text = (int)((hold >> 8) & 1);
+            if ((state->flags & 0x0200) && (state->wrap & 4))
+                CRC2(state->check, hold);
+            INITBITS();
+            state->mode = TIME;
+        case TIME:
+            NEEDBITS(32);
+            if (state->head != Z_NULL)
+                state->head->time = hold;
+            if ((state->flags & 0x0200) && (state->wrap & 4))
+                CRC4(state->check, hold);
+            INITBITS();
+            state->mode = OS;
+        case OS:
+            NEEDBITS(16);
+            if (state->head != Z_NULL) {
+                state->head->xflags = (int)(hold & 0xff);
+                state->head->os = (int)(hold >> 8);
+            }
+            if ((state->flags & 0x0200) && (state->wrap & 4))
+                CRC2(state->check, hold);
+            INITBITS();
+            state->mode = EXLEN;
+        case EXLEN:
+            if (state->flags & 0x0400) {
+                NEEDBITS(16);
+                state->length = (unsigned)(hold);
+                if (state->head != Z_NULL)
+                    state->head->extra_len = (unsigned)hold;
+                if ((state->flags & 0x0200) && (state->wrap & 4))
+                    CRC2(state->check, hold);
+                INITBITS();
+            }
+            else if (state->head != Z_NULL)
+                state->head->extra = Z_NULL;
+            state->mode = EXTRA;
+        case EXTRA:
+            if (state->flags & 0x0400) {
+                copy = state->length;
+                if (copy > have) copy = have;
+                if (copy) {
+                    if (state->head != Z_NULL &&
+                        state->head->extra != Z_NULL) {
+                        len = state->head->extra_len - state->length;
+                        zmemcpy(state->head->extra + len, next,
+                                len + copy > state->head->extra_max ?
+                                state->head->extra_max - len : copy);
+                    }
+                    if ((state->flags & 0x0200) && (state->wrap & 4))
+                        state->check = crc32(state->check, next, copy);
+                    have -= copy;
+                    next += copy;
+                    state->length -= copy;
+                }
+                if (state->length) goto inf_leave;
+            }
+            state->length = 0;
+            state->mode = NAME;
+        case NAME:
+            if (state->flags & 0x0800) {
+                if (have == 0) goto inf_leave;
+                copy = 0;
+                do {
+                    len = (unsigned)(next[copy++]);
+                    if (state->head != Z_NULL &&
+                            state->head->name != Z_NULL &&
+                            state->length < state->head->name_max)
+                        state->head->name[state->length++] = (Bytef)len;
+                } while (len && copy < have);
+                if ((state->flags & 0x0200) && (state->wrap & 4))
+                    state->check = crc32(state->check, next, copy);
+                have -= copy;
+                next += copy;
+                if (len) goto inf_leave;
+            }
+            else if (state->head != Z_NULL)
+                state->head->name = Z_NULL;
+            state->length = 0;
+            state->mode = COMMENT;
+        case COMMENT:
+            if (state->flags & 0x1000) {
+                if (have == 0) goto inf_leave;
+                copy = 0;
+                do {
+                    len = (unsigned)(next[copy++]);
+                    if (state->head != Z_NULL &&
+                            state->head->comment != Z_NULL &&
+                            state->length < state->head->comm_max)
+                        state->head->comment[state->length++] = (Bytef)len;
+                } while (len && copy < have);
+                if ((state->flags & 0x0200) && (state->wrap & 4))
+                    state->check = crc32(state->check, next, copy);
+                have -= copy;
+                next += copy;
+                if (len) goto inf_leave;
+            }
+            else if (state->head != Z_NULL)
+                state->head->comment = Z_NULL;
+            state->mode = HCRC;
+        case HCRC:
+            if (state->flags & 0x0200) {
+                NEEDBITS(16);
+                if ((state->wrap & 4) && hold != (state->check & 0xffff)) {
+                    strm->msg = (char *)"header crc mismatch";
+                    state->mode = BAD;
+                    break;
+                }
+                INITBITS();
+            }
+            if (state->head != Z_NULL) {
+                state->head->hcrc = (int)((state->flags >> 9) & 1);
+                state->head->done = 1;
+            }
+            strm->adler = state->check = crc32(0L, Z_NULL, 0);
+            state->mode = TYPE;
+            break;
+#endif
+        case DICTID:
+            NEEDBITS(32);
+            strm->adler = state->check = ZSWAP32(hold);
+            INITBITS();
+            state->mode = DICT;
+        case DICT:
+            if (state->havedict == 0) {
+                RESTORE();
+                return Z_NEED_DICT;
+            }
+            strm->adler = state->check = adler32(0L, Z_NULL, 0);
+            state->mode = TYPE;
+        case TYPE:
+            if (flush == Z_BLOCK || flush == Z_TREES) goto inf_leave;
+        case TYPEDO:
+            if (state->last) {
+                BYTEBITS();
+                state->mode = CHECK;
+                break;
+            }
+            NEEDBITS(3);
+            state->last = BITS(1);
+            DROPBITS(1);
+            switch (BITS(2)) {
+            case 0:                             /* stored block */
+                Tracev((stderr, "inflate:     stored block%s\n",
+                        state->last ? " (last)" : ""));
+                state->mode = STORED;
+                break;
+            case 1:                             /* fixed block */
+                fixedtables(state);
+                Tracev((stderr, "inflate:     fixed codes block%s\n",
+                        state->last ? " (last)" : ""));
+                state->mode = LEN_;             /* decode codes */
+                if (flush == Z_TREES) {
+                    DROPBITS(2);
+                    goto inf_leave;
+                }
+                break;
+            case 2:                             /* dynamic block */
+                Tracev((stderr, "inflate:     dynamic codes block%s\n",
+                        state->last ? " (last)" : ""));
+                state->mode = TABLE;
+                break;
+            case 3:
+                strm->msg = (char *)"invalid block type";
+                state->mode = BAD;
+            }
+            DROPBITS(2);
+            break;
+        case STORED:
+            BYTEBITS();                         /* go to byte boundary */
+            NEEDBITS(32);
+            if ((hold & 0xffff) != ((hold >> 16) ^ 0xffff)) {
+                strm->msg = (char *)"invalid stored block lengths";
+                state->mode = BAD;
+                break;
+            }
+            state->length = (unsigned)hold & 0xffff;
+            Tracev((stderr, "inflate:       stored length %u\n",
+                    state->length));
+            INITBITS();
+            state->mode = COPY_;
+            if (flush == Z_TREES) goto inf_leave;
+        case COPY_:
+            state->mode = COPY;
+        case COPY:
+            copy = state->length;
+            if (copy) {
+                if (copy > have) copy = have;
+                if (copy > left) copy = left;
+                if (copy == 0) goto inf_leave;
+                zmemcpy(put, next, copy);
+                have -= copy;
+                next += copy;
+                left -= copy;
+                put += copy;
+                state->length -= copy;
+                break;
+            }
+            Tracev((stderr, "inflate:       stored end\n"));
+            state->mode = TYPE;
+            break;
+        case TABLE:
+            NEEDBITS(14);
+            state->nlen = BITS(5) + 257;
+            DROPBITS(5);
+            state->ndist = BITS(5) + 1;
+            DROPBITS(5);
+            state->ncode = BITS(4) + 4;
+            DROPBITS(4);
+#ifndef PKZIP_BUG_WORKAROUND
+            if (state->nlen > 286 || state->ndist > 30) {
+                strm->msg = (char *)"too many length or distance symbols";
+                state->mode = BAD;
+                break;
+            }
+#endif
+            Tracev((stderr, "inflate:       table sizes ok\n"));
+            state->have = 0;
+            state->mode = LENLENS;
+        case LENLENS:
+            while (state->have < state->ncode) {
+                NEEDBITS(3);
+                state->lens[order[state->have++]] = (unsigned short)BITS(3);
+                DROPBITS(3);
+            }
+            while (state->have < 19)
+                state->lens[order[state->have++]] = 0;
+            state->next = state->codes;
+            state->lencode = (const code FAR *)(state->next);
+            state->lenbits = 7;
+            ret = inflate_table(CODES, state->lens, 19, &(state->next),
+                                &(state->lenbits), state->work);
+            if (ret) {
+                strm->msg = (char *)"invalid code lengths set";
+                state->mode = BAD;
+                break;
+            }
+            Tracev((stderr, "inflate:       code lengths ok\n"));
+            state->have = 0;
+            state->mode = CODELENS;
+        case CODELENS:
+            while (state->have < state->nlen + state->ndist) {
+                for (;;) {
+                    here = state->lencode[BITS(state->lenbits)];
+                    if ((unsigned)(here.bits) <= bits) break;
+                    PULLBYTE();
+                }
+                if (here.val < 16) {
+                    DROPBITS(here.bits);
+                    state->lens[state->have++] = here.val;
+                }
+                else {
+                    if (here.val == 16) {
+                        NEEDBITS(here.bits + 2);
+                        DROPBITS(here.bits);
+                        if (state->have == 0) {
+                            strm->msg = (char *)"invalid bit length repeat";
+                            state->mode = BAD;
+                            break;
+                        }
+                        len = state->lens[state->have - 1];
+                        copy = 3 + BITS(2);
+                        DROPBITS(2);
+                    }
+                    else if (here.val == 17) {
+                        NEEDBITS(here.bits + 3);
+                        DROPBITS(here.bits);
+                        len = 0;
+                        copy = 3 + BITS(3);
+                        DROPBITS(3);
+                    }
+                    else {
+                        NEEDBITS(here.bits + 7);
+                        DROPBITS(here.bits);
+                        len = 0;
+                        copy = 11 + BITS(7);
+                        DROPBITS(7);
+                    }
+                    if (state->have + copy > state->nlen + state->ndist) {
+                        strm->msg = (char *)"invalid bit length repeat";
+                        state->mode = BAD;
+                        break;
+                    }
+                    while (copy--)
+                        state->lens[state->have++] = (unsigned short)len;
+                }
+            }
+
+            /* handle error breaks in while */
+            if (state->mode == BAD) break;
+
+            /* check for end-of-block code (better have one) */
+            if (state->lens[256] == 0) {
+                strm->msg = (char *)"invalid code -- missing end-of-block";
+                state->mode = BAD;
+                break;
+            }
+
+            /* build code tables -- note: do not change the lenbits or distbits
+               values here (9 and 6) without reading the comments in inftrees.h
+               concerning the ENOUGH constants, which depend on those values */
+            state->next = state->codes;
+            state->lencode = (const code FAR *)(state->next);
+            state->lenbits = 9;
+            ret = inflate_table(LENS, state->lens, state->nlen, &(state->next),
+                                &(state->lenbits), state->work);
+            if (ret) {
+                strm->msg = (char *)"invalid literal/lengths set";
+                state->mode = BAD;
+                break;
+            }
+            state->distcode = (const code FAR *)(state->next);
+            state->distbits = 6;
+            ret = inflate_table(DISTS, state->lens + state->nlen, state->ndist,
+                            &(state->next), &(state->distbits), state->work);
+            if (ret) {
+                strm->msg = (char *)"invalid distances set";
+                state->mode = BAD;
+                break;
+            }
+            Tracev((stderr, "inflate:       codes ok\n"));
+            state->mode = LEN_;
+            if (flush == Z_TREES) goto inf_leave;
+        case LEN_:
+            state->mode = LEN;
+        case LEN:
+            if (have >= 6 && left >= 258) {
+                RESTORE();
+                inflate_fast(strm, out);
+                LOAD();
+                if (state->mode == TYPE)
+                    state->back = -1;
+                break;
+            }
+            state->back = 0;
+            for (;;) {
+                here = state->lencode[BITS(state->lenbits)];
+                if ((unsigned)(here.bits) <= bits) break;
+                PULLBYTE();
+            }
+            if (here.op && (here.op & 0xf0) == 0) {
+                last = here;
+                for (;;) {
+                    here = state->lencode[last.val +
+                            (BITS(last.bits + last.op) >> last.bits)];
+                    if ((unsigned)(last.bits + here.bits) <= bits) break;
+                    PULLBYTE();
+                }
+                DROPBITS(last.bits);
+                state->back += last.bits;
+            }
+            DROPBITS(here.bits);
+            state->back += here.bits;
+            state->length = (unsigned)here.val;
+            if ((int)(here.op) == 0) {
+                Tracevv((stderr, here.val >= 0x20 && here.val < 0x7f ?
+                        "inflate:         literal '%c'\n" :
+                        "inflate:         literal 0x%02x\n", here.val));
+                state->mode = LIT;
+                break;
+            }
+            if (here.op & 32) {
+                Tracevv((stderr, "inflate:         end of block\n"));
+                state->back = -1;
+                state->mode = TYPE;
+                break;
+            }
+            if (here.op & 64) {
+                strm->msg = (char *)"invalid literal/length code";
+                state->mode = BAD;
+                break;
+            }
+            state->extra = (unsigned)(here.op) & 15;
+            state->mode = LENEXT;
+        case LENEXT:
+            if (state->extra) {
+                NEEDBITS(state->extra);
+                state->length += BITS(state->extra);
+                DROPBITS(state->extra);
+                state->back += state->extra;
+            }
+            Tracevv((stderr, "inflate:         length %u\n", state->length));
+            state->was = state->length;
+            state->mode = DIST;
+        case DIST:
+            for (;;) {
+                here = state->distcode[BITS(state->distbits)];
+                if ((unsigned)(here.bits) <= bits) break;
+                PULLBYTE();
+            }
+            if ((here.op & 0xf0) == 0) {
+                last = here;
+                for (;;) {
+                    here = state->distcode[last.val +
+                            (BITS(last.bits + last.op) >> last.bits)];
+                    if ((unsigned)(last.bits + here.bits) <= bits) break;
+                    PULLBYTE();
+                }
+                DROPBITS(last.bits);
+                state->back += last.bits;
+            }
+            DROPBITS(here.bits);
+            state->back += here.bits;
+            if (here.op & 64) {
+                strm->msg = (char *)"invalid distance code";
+                state->mode = BAD;
+                break;
+            }
+            state->offset = (unsigned)here.val;
+            state->extra = (unsigned)(here.op) & 15;
+            state->mode = DISTEXT;
+        case DISTEXT:
+            if (state->extra) {
+                NEEDBITS(state->extra);
+                state->offset += BITS(state->extra);
+                DROPBITS(state->extra);
+                state->back += state->extra;
+            }
+#ifdef INFLATE_STRICT
+            if (state->offset > state->dmax) {
+                strm->msg = (char *)"invalid distance too far back";
+                state->mode = BAD;
+                break;
+            }
+#endif
+            Tracevv((stderr, "inflate:         distance %u\n", state->offset));
+            state->mode = MATCH;
+        case MATCH:
+            if (left == 0) goto inf_leave;
+            copy = out - left;
+            if (state->offset > copy) {         /* copy from window */
+                copy = state->offset - copy;
+                if (copy > state->whave) {
+                    if (state->sane) {
+                        strm->msg = (char *)"invalid distance too far back";
+                        state->mode = BAD;
+                        break;
+                    }
+#ifdef INFLATE_ALLOW_INVALID_DISTANCE_TOOFAR_ARRR
+                    Trace((stderr, "inflate.c too far\n"));
+                    copy -= state->whave;
+                    if (copy > state->length) copy = state->length;
+                    if (copy > left) copy = left;
+                    left -= copy;
+                    state->length -= copy;
+                    do {
+                        *put++ = 0;
+                    } while (--copy);
+                    if (state->length == 0) state->mode = LEN;
+                    break;
+#endif
+                }
+                if (copy > state->wnext) {
+                    copy -= state->wnext;
+                    from = state->window + (state->wsize - copy);
+                }
+                else
+                    from = state->window + (state->wnext - copy);
+                if (copy > state->length) copy = state->length;
+            }
+            else {                              /* copy from output */
+                from = put - state->offset;
+                copy = state->length;
+            }
+            if (copy > left) copy = left;
+            left -= copy;
+            state->length -= copy;
+            do {
+                *put++ = *from++;
+            } while (--copy);
+            if (state->length == 0) state->mode = LEN;
+            break;
+        case LIT:
+            if (left == 0) goto inf_leave;
+            *put++ = (unsigned char)(state->length);
+            left--;
+            state->mode = LEN;
+            break;
+        case CHECK:
+            if (state->wrap) {
+                NEEDBITS(32);
+                out -= left;
+                strm->total_out += out;
+                state->total += out;
+                if ((state->wrap & 4) && out)
+                    strm->adler = state->check =
+                        UPDATE(state->check, put - out, out);
+                out = left;
+                if ((state->wrap & 4) && (
+#ifdef GUNZIP
+                     state->flags ? hold :
+#endif
+                     ZSWAP32(hold)) != state->check) {
+                    strm->msg = (char *)"incorrect data check";
+                    state->mode = BAD;
+                    break;
+                }
+                INITBITS();
+                Tracev((stderr, "inflate:   check matches trailer\n"));
+            }
+#ifdef GUNZIP
+            state->mode = LENGTH;
+        case LENGTH:
+            if (state->wrap && state->flags) {
+                NEEDBITS(32);
+                if (hold != (state->total & 0xffffffffUL)) {
+                    strm->msg = (char *)"incorrect length check";
+                    state->mode = BAD;
+                    break;
+                }
+                INITBITS();
+                Tracev((stderr, "inflate:   length matches trailer\n"));
+            }
+#endif
+            state->mode = DONE;
+        case DONE:
+            ret = Z_STREAM_END;
+            goto inf_leave;
+        case BAD:
+            ret = Z_DATA_ERROR;
+            goto inf_leave;
+        case MEM:
+            return Z_MEM_ERROR;
+        case SYNC:
+        default:
+            return Z_STREAM_ERROR;
+        }
+
+    /*
+       Return from inflate(), updating the total counts and the check value.
+       If there was no progress during the inflate() call, return a buffer
+       error.  Call updatewindow() to create and/or update the window state.
+       Note: a memory error from inflate() is non-recoverable.
+     */
+  inf_leave:
+    RESTORE();
+    if (state->wsize || (out != strm->avail_out && state->mode < BAD &&
+            (state->mode < CHECK || flush != Z_FINISH)))
+        if (updatewindow(strm, strm->next_out, out - strm->avail_out)) {
+            state->mode = MEM;
+            return Z_MEM_ERROR;
+        }
+    in -= strm->avail_in;
+    out -= strm->avail_out;
+    strm->total_in += in;
+    strm->total_out += out;
+    state->total += out;
+    if ((state->wrap & 4) && out)
+        strm->adler = state->check =
+            UPDATE(state->check, strm->next_out - out, out);
+    strm->data_type = (int)state->bits + (state->last ? 64 : 0) +
+                      (state->mode == TYPE ? 128 : 0) +
+                      (state->mode == LEN_ || state->mode == COPY_ ? 256 : 0);
+    if (((in == 0 && out == 0) || flush == Z_FINISH) && ret == Z_OK)
+        ret = Z_BUF_ERROR;
+    return ret;
+}
+
+int ZEXPORT inflateEnd(strm)
+z_streamp strm;
+{
+    struct inflate_state FAR *state;
+    if (inflateStateCheck(strm))
+        return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    if (state->window != Z_NULL) ZFREE(strm, state->window);
+    ZFREE(strm, strm->state);
+    strm->state = Z_NULL;
+    Tracev((stderr, "inflate: end\n"));
+    return Z_OK;
+}
+
+int ZEXPORT inflateGetDictionary(strm, dictionary, dictLength)
+z_streamp strm;
+Bytef *dictionary;
+uInt *dictLength;
+{
+    struct inflate_state FAR *state;
+
+    /* check state */
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+
+    /* copy dictionary */
+    if (state->whave && dictionary != Z_NULL) {
+        zmemcpy(dictionary, state->window + state->wnext,
+                state->whave - state->wnext);
+        zmemcpy(dictionary + state->whave - state->wnext,
+                state->window, state->wnext);
+    }
+    if (dictLength != Z_NULL)
+        *dictLength = state->whave;
+    return Z_OK;
+}
+
+int ZEXPORT inflateSetDictionary(strm, dictionary, dictLength)
+z_streamp strm;
+const Bytef *dictionary;
+uInt dictLength;
+{
+    struct inflate_state FAR *state;
+    unsigned long dictid;
+    int ret;
+
+    /* check state */
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    if (state->wrap != 0 && state->mode != DICT)
+        return Z_STREAM_ERROR;
+
+    /* check for correct dictionary identifier */
+    if (state->mode == DICT) {
+        dictid = adler32(0L, Z_NULL, 0);
+        dictid = adler32(dictid, dictionary, dictLength);
+        if (dictid != state->check)
+            return Z_DATA_ERROR;
+    }
+
+    /* copy dictionary to window using updatewindow(), which will amend the
+       existing dictionary if appropriate */
+    ret = updatewindow(strm, dictionary + dictLength, dictLength);
+    if (ret) {
+        state->mode = MEM;
+        return Z_MEM_ERROR;
+    }
+    state->havedict = 1;
+    Tracev((stderr, "inflate:   dictionary set\n"));
+    return Z_OK;
+}
+
+int ZEXPORT inflateGetHeader(strm, head)
+z_streamp strm;
+gz_headerp head;
+{
+    struct inflate_state FAR *state;
+
+    /* check state */
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    if ((state->wrap & 2) == 0) return Z_STREAM_ERROR;
+
+    /* save header structure */
+    state->head = head;
+    head->done = 0;
+    return Z_OK;
+}
+
+/*
+   Search buf[0..len-1] for the pattern: 0, 0, 0xff, 0xff.  Return when found
+   or when out of input.  When called, *have is the number of pattern bytes
+   found in order so far, in 0..3.  On return *have is updated to the new
+   state.  If on return *have equals four, then the pattern was found and the
+   return value is how many bytes were read including the last byte of the
+   pattern.  If *have is less than four, then the pattern has not been found
+   yet and the return value is len.  In the latter case, syncsearch() can be
+   called again with more data and the *have state.  *have is initialized to
+   zero for the first call.
+ */
+local unsigned syncsearch(have, buf, len)
+unsigned FAR *have;
+const unsigned char FAR *buf;
+unsigned len;
+{
+    unsigned got;
+    unsigned next;
+
+    got = *have;
+    next = 0;
+    while (next < len && got < 4) {
+        if ((int)(buf[next]) == (got < 2 ? 0 : 0xff))
+            got++;
+        else if (buf[next])
+            got = 0;
+        else
+            got = 4 - got;
+        next++;
+    }
+    *have = got;
+    return next;
+}
+
+int ZEXPORT inflateSync(strm)
+z_streamp strm;
+{
+    unsigned len;               /* number of bytes to look at or looked at */
+    unsigned long in, out;      /* temporary to save total_in and total_out */
+    unsigned char buf[4];       /* to restore bit buffer to byte string */
+    struct inflate_state FAR *state;
+
+    /* check parameters */
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    if (strm->avail_in == 0 && state->bits < 8) return Z_BUF_ERROR;
+
+    /* if first time, start search in bit buffer */
+    if (state->mode != SYNC) {
+        state->mode = SYNC;
+        state->hold <<= state->bits & 7;
+        state->bits -= state->bits & 7;
+        len = 0;
+        while (state->bits >= 8) {
+            buf[len++] = (unsigned char)(state->hold);
+            state->hold >>= 8;
+            state->bits -= 8;
+        }
+        state->have = 0;
+        syncsearch(&(state->have), buf, len);
+    }
+
+    /* search available input */
+    len = syncsearch(&(state->have), strm->next_in, strm->avail_in);
+    strm->avail_in -= len;
+    strm->next_in += len;
+    strm->total_in += len;
+
+    /* return no joy or set up to restart inflate() on a new block */
+    if (state->have != 4) return Z_DATA_ERROR;
+    in = strm->total_in;  out = strm->total_out;
+    inflateReset(strm);
+    strm->total_in = in;  strm->total_out = out;
+    state->mode = TYPE;
+    return Z_OK;
+}
+
+/*
+   Returns true if inflate is currently at the end of a block generated by
+   Z_SYNC_FLUSH or Z_FULL_FLUSH. This function is used by one PPP
+   implementation to provide an additional safety check. PPP uses
+   Z_SYNC_FLUSH but removes the length bytes of the resulting empty stored
+   block. When decompressing, PPP checks that at the end of input packet,
+   inflate is waiting for these length bytes.
+ */
+int ZEXPORT inflateSyncPoint(strm)
+z_streamp strm;
+{
+    struct inflate_state FAR *state;
+
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    return state->mode == STORED && state->bits == 0;
+}
+
+int ZEXPORT inflateCopy(dest, source)
+z_streamp dest;
+z_streamp source;
+{
+    struct inflate_state FAR *state;
+    struct inflate_state FAR *copy;
+    unsigned char FAR *window;
+    unsigned wsize;
+
+    /* check input */
+    if (inflateStateCheck(source) || dest == Z_NULL)
+        return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)source->state;
+
+    /* allocate space */
+    copy = (struct inflate_state FAR *)
+           ZALLOC(source, 1, sizeof(struct inflate_state));
+    if (copy == Z_NULL) return Z_MEM_ERROR;
+    window = Z_NULL;
+    if (state->window != Z_NULL) {
+        window = (unsigned char FAR *)
+                 ZALLOC(source, 1U << state->wbits, sizeof(unsigned char));
+        if (window == Z_NULL) {
+            ZFREE(source, copy);
+            return Z_MEM_ERROR;
+        }
+    }
+
+    /* copy state */
+    zmemcpy((voidpf)dest, (voidpf)source, sizeof(z_stream));
+    zmemcpy((voidpf)copy, (voidpf)state, sizeof(struct inflate_state));
+    copy->strm = dest;
+    if (state->lencode >= state->codes &&
+        state->lencode <= state->codes + ENOUGH - 1) {
+        copy->lencode = copy->codes + (state->lencode - state->codes);
+        copy->distcode = copy->codes + (state->distcode - state->codes);
+    }
+    copy->next = copy->codes + (state->next - state->codes);
+    if (window != Z_NULL) {
+        wsize = 1U << state->wbits;
+        zmemcpy(window, state->window, wsize);
+    }
+    copy->window = window;
+    dest->state = (struct internal_state FAR *)copy;
+    return Z_OK;
+}
+
+int ZEXPORT inflateUndermine(strm, subvert)
+z_streamp strm;
+int subvert;
+{
+    struct inflate_state FAR *state;
+
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+#ifdef INFLATE_ALLOW_INVALID_DISTANCE_TOOFAR_ARRR
+    state->sane = !subvert;
+    return Z_OK;
+#else
+    (void)subvert;
+    state->sane = 1;
+    return Z_DATA_ERROR;
+#endif
+}
+
+int ZEXPORT inflateValidate(strm, check)
+z_streamp strm;
+int check;
+{
+    struct inflate_state FAR *state;
+
+    if (inflateStateCheck(strm)) return Z_STREAM_ERROR;
+    state = (struct inflate_state FAR *)strm->state;
+    if (check)
+        state->wrap |= 4;
+    else
+        state->wrap &= ~4;
+    return Z_OK;
+}
+
+long ZEXPORT inflateMark(strm)
+z_streamp strm;
+{
+    struct inflate_state FAR *state;
+
+    if (inflateStateCheck(strm))
+        return -(1L << 16);
+    state = (struct inflate_state FAR *)strm->state;
+    return (long)(((unsigned long)((long)state->back)) << 16) +
+        (state->mode == COPY ? state->length :
+            (state->mode == MATCH ? state->was - state->length : 0));
+}
+
+unsigned long ZEXPORT inflateCodesUsed(strm)
+z_streamp strm;
+{
+    struct inflate_state FAR *state;
+    if (inflateStateCheck(strm)) return (unsigned long)-1;
+    state = (struct inflate_state FAR *)strm->state;
+    return (unsigned long)(state->next - state->codes);
+}

ADDED   3rd_party/zlib/inflate.h
Index: 3rd_party/zlib/inflate.h
==================================================================
--- 3rd_party/zlib/inflate.h
+++ 3rd_party/zlib/inflate.h
@@ -0,0 +1,125 @@
+/* inflate.h -- internal inflate state definition
+ * Copyright (C) 1995-2016 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* WARNING: this file should *not* be used by applications. It is
+   part of the implementation of the compression library and is
+   subject to change. Applications should only use zlib.h.
+ */
+
+/* define NO_GZIP when compiling if you want to disable gzip header and
+   trailer decoding by inflate().  NO_GZIP would be used to avoid linking in
+   the crc code when it is not needed.  For shared libraries, gzip decoding
+   should be left enabled. */
+#ifndef NO_GZIP
+#  define GUNZIP
+#endif
+
+/* Possible inflate modes between inflate() calls */
+typedef enum {
+    HEAD = 16180,   /* i: waiting for magic header */
+    FLAGS,      /* i: waiting for method and flags (gzip) */
+    TIME,       /* i: waiting for modification time (gzip) */
+    OS,         /* i: waiting for extra flags and operating system (gzip) */
+    EXLEN,      /* i: waiting for extra length (gzip) */
+    EXTRA,      /* i: waiting for extra bytes (gzip) */
+    NAME,       /* i: waiting for end of file name (gzip) */
+    COMMENT,    /* i: waiting for end of comment (gzip) */
+    HCRC,       /* i: waiting for header crc (gzip) */
+    DICTID,     /* i: waiting for dictionary check value */
+    DICT,       /* waiting for inflateSetDictionary() call */
+        TYPE,       /* i: waiting for type bits, including last-flag bit */
+        TYPEDO,     /* i: same, but skip check to exit inflate on new block */
+        STORED,     /* i: waiting for stored size (length and complement) */
+        COPY_,      /* i/o: same as COPY below, but only first time in */
+        COPY,       /* i/o: waiting for input or output to copy stored block */
+        TABLE,      /* i: waiting for dynamic block table lengths */
+        LENLENS,    /* i: waiting for code length code lengths */
+        CODELENS,   /* i: waiting for length/lit and distance code lengths */
+            LEN_,       /* i: same as LEN below, but only first time in */
+            LEN,        /* i: waiting for length/lit/eob code */
+            LENEXT,     /* i: waiting for length extra bits */
+            DIST,       /* i: waiting for distance code */
+            DISTEXT,    /* i: waiting for distance extra bits */
+            MATCH,      /* o: waiting for output space to copy string */
+            LIT,        /* o: waiting for output space to write literal */
+    CHECK,      /* i: waiting for 32-bit check value */
+    LENGTH,     /* i: waiting for 32-bit length (gzip) */
+    DONE,       /* finished check, done -- remain here until reset */
+    BAD,        /* got a data error -- remain here until reset */
+    MEM,        /* got an inflate() memory error -- remain here until reset */
+    SYNC        /* looking for synchronization bytes to restart inflate() */
+} inflate_mode;
+
+/*
+    State transitions between above modes -
+
+    (most modes can go to BAD or MEM on error -- not shown for clarity)
+
+    Process header:
+        HEAD -> (gzip) or (zlib) or (raw)
+        (gzip) -> FLAGS -> TIME -> OS -> EXLEN -> EXTRA -> NAME -> COMMENT ->
+                  HCRC -> TYPE
+        (zlib) -> DICTID or TYPE
+        DICTID -> DICT -> TYPE
+        (raw) -> TYPEDO
+    Read deflate blocks:
+            TYPE -> TYPEDO -> STORED or TABLE or LEN_ or CHECK
+            STORED -> COPY_ -> COPY -> TYPE
+            TABLE -> LENLENS -> CODELENS -> LEN_
+            LEN_ -> LEN
+    Read deflate codes in fixed or dynamic block:
+                LEN -> LENEXT or LIT or TYPE
+                LENEXT -> DIST -> DISTEXT -> MATCH -> LEN
+                LIT -> LEN
+    Process trailer:
+        CHECK -> LENGTH -> DONE
+ */
+
+/* State maintained between inflate() calls -- approximately 7K bytes, not
+   including the allocated sliding window, which is up to 32K bytes. */
+struct inflate_state {
+    z_streamp strm;             /* pointer back to this zlib stream */
+    inflate_mode mode;          /* current inflate mode */
+    int last;                   /* true if processing last block */
+    int wrap;                   /* bit 0 true for zlib, bit 1 true for gzip,
+                                   bit 2 true to validate check value */
+    int havedict;               /* true if dictionary provided */
+    int flags;                  /* gzip header method and flags (0 if zlib) */
+    unsigned dmax;              /* zlib header max distance (INFLATE_STRICT) */
+    unsigned long check;        /* protected copy of check value */
+    unsigned long total;        /* protected copy of output count */
+    gz_headerp head;            /* where to save gzip header information */
+        /* sliding window */
+    unsigned wbits;             /* log base 2 of requested window size */
+    unsigned wsize;             /* window size or zero if not using window */
+    unsigned whave;             /* valid bytes in the window */
+    unsigned wnext;             /* window write index */
+    unsigned char FAR *window;  /* allocated sliding window, if needed */
+        /* bit accumulator */
+    unsigned long hold;         /* input bit accumulator */
+    unsigned bits;              /* number of bits in "in" */
+        /* for string and stored block copying */
+    unsigned length;            /* literal or length of data to copy */
+    unsigned offset;            /* distance back to copy string from */
+        /* for table and code decoding */
+    unsigned extra;             /* extra bits needed */
+        /* fixed and dynamic code tables */
+    code const FAR *lencode;    /* starting table for length/literal codes */
+    code const FAR *distcode;   /* starting table for distance codes */
+    unsigned lenbits;           /* index bits for lencode */
+    unsigned distbits;          /* index bits for distcode */
+        /* dynamic table building */
+    unsigned ncode;             /* number of code length code lengths */
+    unsigned nlen;              /* number of length code lengths */
+    unsigned ndist;             /* number of distance code lengths */
+    unsigned have;              /* number of code lengths in lens[] */
+    code FAR *next;             /* next available space in codes[] */
+    unsigned short lens[320];   /* temporary storage for code lengths */
+    unsigned short work[288];   /* work area for code table building */
+    code codes[ENOUGH];         /* space for code tables */
+    int sane;                   /* if false, allow invalid distance too far */
+    int back;                   /* bits back of last unprocessed length/lit */
+    unsigned was;               /* initial length of match */
+};

ADDED   3rd_party/zlib/inftrees.c
Index: 3rd_party/zlib/inftrees.c
==================================================================
--- 3rd_party/zlib/inftrees.c
+++ 3rd_party/zlib/inftrees.c
@@ -0,0 +1,304 @@
+/* inftrees.c -- generate Huffman trees for efficient decoding
+ * Copyright (C) 1995-2017 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+#include "zutil.h"
+#include "inftrees.h"
+
+#define MAXBITS 15
+
+const char inflate_copyright[] =
+   " inflate 1.2.11 Copyright 1995-2017 Mark Adler ";
+/*
+  If you use the zlib library in a product, an acknowledgment is welcome
+  in the documentation of your product. If for some reason you cannot
+  include such an acknowledgment, I would appreciate that you keep this
+  copyright string in the executable of your product.
+ */
+
+/*
+   Build a set of tables to decode the provided canonical Huffman code.
+   The code lengths are lens[0..codes-1].  The result starts at *table,
+   whose indices are 0..2^bits-1.  work is a writable array of at least
+   lens shorts, which is used as a work area.  type is the type of code
+   to be generated, CODES, LENS, or DISTS.  On return, zero is success,
+   -1 is an invalid code, and +1 means that ENOUGH isn't enough.  table
+   on return points to the next available entry's address.  bits is the
+   requested root table index bits, and on return it is the actual root
+   table index bits.  It will differ if the request is greater than the
+   longest code or if it is less than the shortest code.
+ */
+int ZLIB_INTERNAL inflate_table(type, lens, codes, table, bits, work)
+codetype type;
+unsigned short FAR *lens;
+unsigned codes;
+code FAR * FAR *table;
+unsigned FAR *bits;
+unsigned short FAR *work;
+{
+    unsigned len;               /* a code's length in bits */
+    unsigned sym;               /* index of code symbols */
+    unsigned min, max;          /* minimum and maximum code lengths */
+    unsigned root;              /* number of index bits for root table */
+    unsigned curr;              /* number of index bits for current table */
+    unsigned drop;              /* code bits to drop for sub-table */
+    int left;                   /* number of prefix codes available */
+    unsigned used;              /* code entries in table used */
+    unsigned huff;              /* Huffman code */
+    unsigned incr;              /* for incrementing code, index */
+    unsigned fill;              /* index for replicating entries */
+    unsigned low;               /* low bits for current root entry */
+    unsigned mask;              /* mask for low root bits */
+    code here;                  /* table entry for duplication */
+    code FAR *next;             /* next available space in table */
+    const unsigned short FAR *base;     /* base value table to use */
+    const unsigned short FAR *extra;    /* extra bits table to use */
+    unsigned match;             /* use base and extra for symbol >= match */
+    unsigned short count[MAXBITS+1];    /* number of codes of each length */
+    unsigned short offs[MAXBITS+1];     /* offsets in table for each length */
+    static const unsigned short lbase[31] = { /* Length codes 257..285 base */
+        3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 17, 19, 23, 27, 31,
+        35, 43, 51, 59, 67, 83, 99, 115, 131, 163, 195, 227, 258, 0, 0};
+    static const unsigned short lext[31] = { /* Length codes 257..285 extra */
+        16, 16, 16, 16, 16, 16, 16, 16, 17, 17, 17, 17, 18, 18, 18, 18,
+        19, 19, 19, 19, 20, 20, 20, 20, 21, 21, 21, 21, 16, 77, 202};
+    static const unsigned short dbase[32] = { /* Distance codes 0..29 base */
+        1, 2, 3, 4, 5, 7, 9, 13, 17, 25, 33, 49, 65, 97, 129, 193,
+        257, 385, 513, 769, 1025, 1537, 2049, 3073, 4097, 6145,
+        8193, 12289, 16385, 24577, 0, 0};
+    static const unsigned short dext[32] = { /* Distance codes 0..29 extra */
+        16, 16, 16, 16, 17, 17, 18, 18, 19, 19, 20, 20, 21, 21, 22, 22,
+        23, 23, 24, 24, 25, 25, 26, 26, 27, 27,
+        28, 28, 29, 29, 64, 64};
+
+    /*
+       Process a set of code lengths to create a canonical Huffman code.  The
+       code lengths are lens[0..codes-1].  Each length corresponds to the
+       symbols 0..codes-1.  The Huffman code is generated by first sorting the
+       symbols by length from short to long, and retaining the symbol order
+       for codes with equal lengths.  Then the code starts with all zero bits
+       for the first code of the shortest length, and the codes are integer
+       increments for the same length, and zeros are appended as the length
+       increases.  For the deflate format, these bits are stored backwards
+       from their more natural integer increment ordering, and so when the
+       decoding tables are built in the large loop below, the integer codes
+       are incremented backwards.
+
+       This routine assumes, but does not check, that all of the entries in
+       lens[] are in the range 0..MAXBITS.  The caller must assure this.
+       1..MAXBITS is interpreted as that code length.  zero means that that
+       symbol does not occur in this code.
+
+       The codes are sorted by computing a count of codes for each length,
+       creating from that a table of starting indices for each length in the
+       sorted table, and then entering the symbols in order in the sorted
+       table.  The sorted table is work[], with that space being provided by
+       the caller.
+
+       The length counts are used for other purposes as well, i.e. finding
+       the minimum and maximum length codes, determining if there are any
+       codes at all, checking for a valid set of lengths, and looking ahead
+       at length counts to determine sub-table sizes when building the
+       decoding tables.
+     */
+
+    /* accumulate lengths for codes (assumes lens[] all in 0..MAXBITS) */
+    for (len = 0; len <= MAXBITS; len++)
+        count[len] = 0;
+    for (sym = 0; sym < codes; sym++)
+        count[lens[sym]]++;
+
+    /* bound code lengths, force root to be within code lengths */
+    root = *bits;
+    for (max = MAXBITS; max >= 1; max--)
+        if (count[max] != 0) break;
+    if (root > max) root = max;
+    if (max == 0) {                     /* no symbols to code at all */
+        here.op = (unsigned char)64;    /* invalid code marker */
+        here.bits = (unsigned char)1;
+        here.val = (unsigned short)0;
+        *(*table)++ = here;             /* make a table to force an error */
+        *(*table)++ = here;
+        *bits = 1;
+        return 0;     /* no symbols, but wait for decoding to report error */
+    }
+    for (min = 1; min < max; min++)
+        if (count[min] != 0) break;
+    if (root < min) root = min;
+
+    /* check for an over-subscribed or incomplete set of lengths */
+    left = 1;
+    for (len = 1; len <= MAXBITS; len++) {
+        left <<= 1;
+        left -= count[len];
+        if (left < 0) return -1;        /* over-subscribed */
+    }
+    if (left > 0 && (type == CODES || max != 1))
+        return -1;                      /* incomplete set */
+
+    /* generate offsets into symbol table for each length for sorting */
+    offs[1] = 0;
+    for (len = 1; len < MAXBITS; len++)
+        offs[len + 1] = offs[len] + count[len];
+
+    /* sort symbols by length, by symbol order within each length */
+    for (sym = 0; sym < codes; sym++)
+        if (lens[sym] != 0) work[offs[lens[sym]]++] = (unsigned short)sym;
+
+    /*
+       Create and fill in decoding tables.  In this loop, the table being
+       filled is at next and has curr index bits.  The code being used is huff
+       with length len.  That code is converted to an index by dropping drop
+       bits off of the bottom.  For codes where len is less than drop + curr,
+       those top drop + curr - len bits are incremented through all values to
+       fill the table with replicated entries.
+
+       root is the number of index bits for the root table.  When len exceeds
+       root, sub-tables are created pointed to by the root entry with an index
+       of the low root bits of huff.  This is saved in low to check for when a
+       new sub-table should be started.  drop is zero when the root table is
+       being filled, and drop is root when sub-tables are being filled.
+
+       When a new sub-table is needed, it is necessary to look ahead in the
+       code lengths to determine what size sub-table is needed.  The length
+       counts are used for this, and so count[] is decremented as codes are
+       entered in the tables.
+
+       used keeps track of how many table entries have been allocated from the
+       provided *table space.  It is checked for LENS and DIST tables against
+       the constants ENOUGH_LENS and ENOUGH_DISTS to guard against changes in
+       the initial root table size constants.  See the comments in inftrees.h
+       for more information.
+
+       sym increments through all symbols, and the loop terminates when
+       all codes of length max, i.e. all codes, have been processed.  This
+       routine permits incomplete codes, so another loop after this one fills
+       in the rest of the decoding tables with invalid code markers.
+     */
+
+    /* set up for code type */
+    switch (type) {
+    case CODES:
+        base = extra = work;    /* dummy value--not used */
+        match = 20;
+        break;
+    case LENS:
+        base = lbase;
+        extra = lext;
+        match = 257;
+        break;
+    default:    /* DISTS */
+        base = dbase;
+        extra = dext;
+        match = 0;
+    }
+
+    /* initialize state for loop */
+    huff = 0;                   /* starting code */
+    sym = 0;                    /* starting code symbol */
+    len = min;                  /* starting code length */
+    next = *table;              /* current table to fill in */
+    curr = root;                /* current table index bits */
+    drop = 0;                   /* current bits to drop from code for index */
+    low = (unsigned)(-1);       /* trigger new sub-table when len > root */
+    used = 1U << root;          /* use root table entries */
+    mask = used - 1;            /* mask for comparing low */
+
+    /* check available table space */
+    if ((type == LENS && used > ENOUGH_LENS) ||
+        (type == DISTS && used > ENOUGH_DISTS))
+        return 1;
+
+    /* process all codes and make table entries */
+    for (;;) {
+        /* create table entry */
+        here.bits = (unsigned char)(len - drop);
+        if (work[sym] + 1U < match) {
+            here.op = (unsigned char)0;
+            here.val = work[sym];
+        }
+        else if (work[sym] >= match) {
+            here.op = (unsigned char)(extra[work[sym] - match]);
+            here.val = base[work[sym] - match];
+        }
+        else {
+            here.op = (unsigned char)(32 + 64);         /* end of block */
+            here.val = 0;
+        }
+
+        /* replicate for those indices with low len bits equal to huff */
+        incr = 1U << (len - drop);
+        fill = 1U << curr;
+        min = fill;                 /* save offset to next table */
+        do {
+            fill -= incr;
+            next[(huff >> drop) + fill] = here;
+        } while (fill != 0);
+
+        /* backwards increment the len-bit code huff */
+        incr = 1U << (len - 1);
+        while (huff & incr)
+            incr >>= 1;
+        if (incr != 0) {
+            huff &= incr - 1;
+            huff += incr;
+        }
+        else
+            huff = 0;
+
+        /* go to next symbol, update count, len */
+        sym++;
+        if (--(count[len]) == 0) {
+            if (len == max) break;
+            len = lens[work[sym]];
+        }
+
+        /* create new sub-table if needed */
+        if (len > root && (huff & mask) != low) {
+            /* if first time, transition to sub-tables */
+            if (drop == 0)
+                drop = root;
+
+            /* increment past last table */
+            next += min;            /* here min is 1 << curr */
+
+            /* determine length of next table */
+            curr = len - drop;
+            left = (int)(1 << curr);
+            while (curr + drop < max) {
+                left -= count[curr + drop];
+                if (left <= 0) break;
+                curr++;
+                left <<= 1;
+            }
+
+            /* check for enough space */
+            used += 1U << curr;
+            if ((type == LENS && used > ENOUGH_LENS) ||
+                (type == DISTS && used > ENOUGH_DISTS))
+                return 1;
+
+            /* point entry in root table to sub-table */
+            low = huff & mask;
+            (*table)[low].op = (unsigned char)curr;
+            (*table)[low].bits = (unsigned char)root;
+            (*table)[low].val = (unsigned short)(next - *table);
+        }
+    }
+
+    /* fill in remaining table entry if code is incomplete (guaranteed to have
+       at most one remaining entry, since if the code is incomplete, the
+       maximum code length that was allowed to get this far is one bit) */
+    if (huff != 0) {
+        here.op = (unsigned char)64;            /* invalid code marker */
+        here.bits = (unsigned char)(len - drop);
+        here.val = (unsigned short)0;
+        next[huff] = here;
+    }
+
+    /* set return parameters */
+    *table += used;
+    *bits = root;
+    return 0;
+}

ADDED   3rd_party/zlib/inftrees.h
Index: 3rd_party/zlib/inftrees.h
==================================================================
--- 3rd_party/zlib/inftrees.h
+++ 3rd_party/zlib/inftrees.h
@@ -0,0 +1,62 @@
+/* inftrees.h -- header to use inftrees.c
+ * Copyright (C) 1995-2005, 2010 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* WARNING: this file should *not* be used by applications. It is
+   part of the implementation of the compression library and is
+   subject to change. Applications should only use zlib.h.
+ */
+
+/* Structure for decoding tables.  Each entry provides either the
+   information needed to do the operation requested by the code that
+   indexed that table entry, or it provides a pointer to another
+   table that indexes more bits of the code.  op indicates whether
+   the entry is a pointer to another table, a literal, a length or
+   distance, an end-of-block, or an invalid code.  For a table
+   pointer, the low four bits of op is the number of index bits of
+   that table.  For a length or distance, the low four bits of op
+   is the number of extra bits to get after the code.  bits is
+   the number of bits in this code or part of the code to drop off
+   of the bit buffer.  val is the actual byte to output in the case
+   of a literal, the base length or distance, or the offset from
+   the current table to the next table.  Each entry is four bytes. */
+typedef struct {
+    unsigned char op;           /* operation, extra bits, table bits */
+    unsigned char bits;         /* bits in this part of the code */
+    unsigned short val;         /* offset in table or code value */
+} code;
+
+/* op values as set by inflate_table():
+    00000000 - literal
+    0000tttt - table link, tttt != 0 is the number of table index bits
+    0001eeee - length or distance, eeee is the number of extra bits
+    01100000 - end of block
+    01000000 - invalid code
+ */
+
+/* Maximum size of the dynamic table.  The maximum number of code structures is
+   1444, which is the sum of 852 for literal/length codes and 592 for distance
+   codes.  These values were found by exhaustive searches using the program
+   examples/enough.c found in the zlib distribtution.  The arguments to that
+   program are the number of symbols, the initial root table size, and the
+   maximum bit length of a code.  "enough 286 9 15" for literal/length codes
+   returns returns 852, and "enough 30 6 15" for distance codes returns 592.
+   The initial root table size (9 or 6) is found in the fifth argument of the
+   inflate_table() calls in inflate.c and infback.c.  If the root table size is
+   changed, then these maximum sizes would be need to be recalculated and
+   updated. */
+#define ENOUGH_LENS 852
+#define ENOUGH_DISTS 592
+#define ENOUGH (ENOUGH_LENS+ENOUGH_DISTS)
+
+/* Type of code to build for inflate_table() */
+typedef enum {
+    CODES,
+    LENS,
+    DISTS
+} codetype;
+
+int ZLIB_INTERNAL inflate_table OF((codetype type, unsigned short FAR *lens,
+                             unsigned codes, code FAR * FAR *table,
+                             unsigned FAR *bits, unsigned short FAR *work));

ADDED   3rd_party/zlib/make_vms.com
Index: 3rd_party/zlib/make_vms.com
==================================================================
--- 3rd_party/zlib/make_vms.com
+++ 3rd_party/zlib/make_vms.com
@@ -0,0 +1,867 @@
+$! make libz under VMS written by
+$! Martin P.J. Zinser
+$!
+$! In case of problems with the install you might contact me at
+$! zinser@zinser.no-ip.info(preferred) or
+$! martin.zinser@eurexchange.com (work)
+$!
+$! Make procedure history for Zlib
+$!
+$!------------------------------------------------------------------------------
+$! Version history
+$! 0.01 20060120 First version to receive a number
+$! 0.02 20061008 Adapt to new Makefile.in
+$! 0.03 20091224 Add support for large file check
+$! 0.04 20100110 Add new gzclose, gzlib, gzread, gzwrite
+$! 0.05 20100221 Exchange zlibdefs.h by zconf.h.in
+$! 0.06 20120111 Fix missing amiss_err, update zconf_h.in, fix new exmples
+$!               subdir path, update module search in makefile.in
+$! 0.07 20120115 Triggered by work done by Alexey Chupahin completly redesigned
+$!               shared image creation
+$! 0.08 20120219 Make it work on VAX again, pre-load missing symbols to shared
+$!               image
+$! 0.09 20120305 SMS.  P1 sets builder ("MMK", "MMS", " " (built-in)).
+$!               "" -> automatic, preference: MMK, MMS, built-in.
+$!
+$ on error then goto err_exit
+$!
+$ true  = 1
+$ false = 0
+$ tmpnam = "temp_" + f$getjpi("","pid")
+$ tt = tmpnam + ".txt"
+$ tc = tmpnam + ".c"
+$ th = tmpnam + ".h"
+$ define/nolog tconfig 'th'
+$ its_decc = false
+$ its_vaxc = false
+$ its_gnuc = false
+$ s_case   = False
+$!
+$! Setup variables holding "config" information
+$!
+$ Make    = "''p1'"
+$ name     = "Zlib"
+$ version  = "?.?.?"
+$ v_string = "ZLIB_VERSION"
+$ v_file   = "zlib.h"
+$ ccopt   = "/include = []"
+$ lopts   = ""
+$ dnsrl   = ""
+$ aconf_in_file = "zconf.h.in#zconf.h_in#zconf_h.in"
+$ conf_check_string = ""
+$ linkonly = false
+$ optfile  = name + ".opt"
+$ mapfile  = name + ".map"
+$ libdefs  = ""
+$ vax      = f$getsyi("HW_MODEL").lt.1024
+$ axp      = f$getsyi("HW_MODEL").ge.1024 .and. f$getsyi("HW_MODEL").lt.4096
+$ ia64     = f$getsyi("HW_MODEL").ge.4096
+$!
+$! 2012-03-05 SMS.
+$! Why is this needed?  And if it is needed, why not simply ".not. vax"?
+$!
+$!!! if axp .or. ia64 then  set proc/parse=extended
+$!
+$ whoami = f$parse(f$environment("Procedure"),,,,"NO_CONCEAL")
+$ mydef  = F$parse(whoami,,,"DEVICE")
+$ mydir  = f$parse(whoami,,,"DIRECTORY") - "]["
+$ myproc = f$parse(whoami,,,"Name") + f$parse(whoami,,,"type")
+$!
+$! Check for MMK/MMS
+$!
+$ if (Make .eqs. "")
+$ then
+$   If F$Search ("Sys$System:MMS.EXE") .nes. "" Then Make = "MMS"
+$   If F$Type (MMK) .eqs. "STRING" Then Make = "MMK"
+$ else
+$   Make = f$edit( Make, "trim")
+$ endif
+$!
+$ gosub find_version
+$!
+$  open/write topt tmp.opt
+$  open/write optf 'optfile'
+$!
+$ gosub check_opts
+$!
+$! Look for the compiler used
+$!
+$ gosub check_compiler
+$ close topt
+$ close optf
+$!
+$ if its_decc
+$ then
+$   ccopt = "/prefix=all" + ccopt
+$   if f$trnlnm("SYS") .eqs. ""
+$   then
+$     if axp
+$     then
+$       define sys sys$library:
+$     else
+$       ccopt = "/decc" + ccopt
+$       define sys decc$library_include:
+$     endif
+$   endif
+$!
+$! 2012-03-05 SMS.
+$! Why /NAMES = AS_IS?  Why not simply ".not. vax"?  And why not on VAX?
+$!
+$   if axp .or. ia64
+$   then
+$       ccopt = ccopt + "/name=as_is/opt=(inline=speed)"
+$       s_case = true
+$   endif
+$ endif
+$ if its_vaxc .or. its_gnuc
+$ then
+$    if f$trnlnm("SYS").eqs."" then define sys sys$library:
+$ endif
+$!
+$! Build a fake configure input header
+$!
+$ open/write conf_hin config.hin
+$ write conf_hin "#undef _LARGEFILE64_SOURCE"
+$ close conf_hin
+$!
+$!
+$ i = 0
+$FIND_ACONF:
+$ fname = f$element(i,"#",aconf_in_file)
+$ if fname .eqs. "#" then goto AMISS_ERR
+$ if f$search(fname) .eqs. ""
+$ then
+$   i = i + 1
+$   goto find_aconf
+$ endif
+$ open/read/err=aconf_err aconf_in 'fname'
+$ open/write aconf zconf.h
+$ACONF_LOOP:
+$ read/end_of_file=aconf_exit aconf_in line
+$ work = f$edit(line, "compress,trim")
+$ if f$extract(0,6,work) .nes. "#undef"
+$ then
+$   if f$extract(0,12,work) .nes. "#cmakedefine"
+$   then
+$       write aconf line
+$   endif
+$ else
+$   cdef = f$element(1," ",work)
+$   gosub check_config
+$ endif
+$ goto aconf_loop
+$ACONF_EXIT:
+$ write aconf ""
+$ write aconf "/* VMS specifics added by make_vms.com: */"
+$ write aconf "#define VMS 1"
+$ write aconf "#include <unistd.h>"
+$ write aconf "#include <unixio.h>"
+$ write aconf "#ifdef _LARGEFILE"
+$ write aconf "# define off64_t __off64_t"
+$ write aconf "# define fopen64 fopen"
+$ write aconf "# define fseeko64 fseeko"
+$ write aconf "# define lseek64 lseek"
+$ write aconf "# define ftello64 ftell"
+$ write aconf "#endif"
+$ write aconf "#if !defined( __VAX) && (__CRTL_VER >= 70312000)"
+$ write aconf "# define HAVE_VSNPRINTF"
+$ write aconf "#endif"
+$ close aconf_in
+$ close aconf
+$ if f$search("''th'") .nes. "" then delete 'th';*
+$! Build the thing plain or with mms
+$!
+$ write sys$output "Compiling Zlib sources ..."
+$ if make.eqs.""
+$ then
+$   if (f$search( "example.obj;*") .nes. "") then delete example.obj;*
+$   if (f$search( "minigzip.obj;*") .nes. "") then delete minigzip.obj;*
+$   CALL MAKE adler32.OBJ "CC ''CCOPT' adler32" -
+                adler32.c zlib.h zconf.h
+$   CALL MAKE compress.OBJ "CC ''CCOPT' compress" -
+                compress.c zlib.h zconf.h
+$   CALL MAKE crc32.OBJ "CC ''CCOPT' crc32" -
+                crc32.c zlib.h zconf.h
+$   CALL MAKE deflate.OBJ "CC ''CCOPT' deflate" -
+                deflate.c deflate.h zutil.h zlib.h zconf.h
+$   CALL MAKE gzclose.OBJ "CC ''CCOPT' gzclose" -
+                gzclose.c zutil.h zlib.h zconf.h
+$   CALL MAKE gzlib.OBJ "CC ''CCOPT' gzlib" -
+                gzlib.c zutil.h zlib.h zconf.h
+$   CALL MAKE gzread.OBJ "CC ''CCOPT' gzread" -
+                gzread.c zutil.h zlib.h zconf.h
+$   CALL MAKE gzwrite.OBJ "CC ''CCOPT' gzwrite" -
+                gzwrite.c zutil.h zlib.h zconf.h
+$   CALL MAKE infback.OBJ "CC ''CCOPT' infback" -
+                infback.c zutil.h inftrees.h inflate.h inffast.h inffixed.h
+$   CALL MAKE inffast.OBJ "CC ''CCOPT' inffast" -
+                inffast.c zutil.h zlib.h zconf.h inffast.h
+$   CALL MAKE inflate.OBJ "CC ''CCOPT' inflate" -
+                inflate.c zutil.h zlib.h zconf.h infblock.h
+$   CALL MAKE inftrees.OBJ "CC ''CCOPT' inftrees" -
+                inftrees.c zutil.h zlib.h zconf.h inftrees.h
+$   CALL MAKE trees.OBJ "CC ''CCOPT' trees" -
+                trees.c deflate.h zutil.h zlib.h zconf.h
+$   CALL MAKE uncompr.OBJ "CC ''CCOPT' uncompr" -
+                uncompr.c zlib.h zconf.h
+$   CALL MAKE zutil.OBJ "CC ''CCOPT' zutil" -
+                zutil.c zutil.h zlib.h zconf.h
+$   write sys$output "Building Zlib ..."
+$   CALL MAKE libz.OLB "lib/crea libz.olb *.obj" *.OBJ
+$   write sys$output "Building example..."
+$   CALL MAKE example.OBJ "CC ''CCOPT' [.test]example" -
+                [.test]example.c zlib.h zconf.h
+$   call make example.exe "LINK example,libz.olb/lib" example.obj libz.olb
+$   write sys$output "Building minigzip..."
+$   CALL MAKE minigzip.OBJ "CC ''CCOPT' [.test]minigzip" -
+              [.test]minigzip.c zlib.h zconf.h
+$   call make minigzip.exe -
+              "LINK minigzip,libz.olb/lib" -
+              minigzip.obj libz.olb
+$ else
+$   gosub crea_mms
+$   write sys$output "Make ''name' ''version' with ''Make' "
+$   'make'
+$ endif
+$!
+$! Create shareable image
+$!
+$ gosub crea_olist
+$ write sys$output "Creating libzshr.exe"
+$ call map_2_shopt 'mapfile' 'optfile'
+$ LINK_'lopts'/SHARE=libzshr.exe modules.opt/opt,'optfile'/opt
+$ write sys$output "Zlib build completed"
+$ delete/nolog tmp.opt;*
+$ exit
+$AMISS_ERR:
+$ write sys$output "No source for config.hin found."
+$ write sys$output "Tried any of ''aconf_in_file'"
+$ goto err_exit
+$CC_ERR:
+$ write sys$output "C compiler required to build ''name'"
+$ goto err_exit
+$ERR_EXIT:
+$ set message/facil/ident/sever/text
+$ close/nolog optf
+$ close/nolog topt
+$ close/nolog aconf_in
+$ close/nolog aconf
+$ close/nolog out
+$ close/nolog min
+$ close/nolog mod
+$ close/nolog h_in
+$ write sys$output "Exiting..."
+$ exit 2
+$!
+$!
+$MAKE: SUBROUTINE   !SUBROUTINE TO CHECK DEPENDENCIES
+$ V = 'F$Verify(0)
+$! P1 = What we are trying to make
+$! P2 = Command to make it
+$! P3 - P8  What it depends on
+$
+$ If F$Search(P1) .Eqs. "" Then Goto Makeit
+$ Time = F$CvTime(F$File(P1,"RDT"))
+$arg=3
+$Loop:
+$       Argument = P'arg
+$       If Argument .Eqs. "" Then Goto Exit
+$       El=0
+$Loop2:
+$       File = F$Element(El," ",Argument)
+$       If File .Eqs. " " Then Goto Endl
+$       AFile = ""
+$Loop3:
+$       OFile = AFile
+$       AFile = F$Search(File)
+$       If AFile .Eqs. "" .Or. AFile .Eqs. OFile Then Goto NextEl
+$       If F$CvTime(F$File(AFile,"RDT")) .Ges. Time Then Goto Makeit
+$       Goto Loop3
+$NextEL:
+$       El = El + 1
+$       Goto Loop2
+$EndL:
+$ arg=arg+1
+$ If arg .Le. 8 Then Goto Loop
+$ Goto Exit
+$
+$Makeit:
+$ VV=F$VERIFY(0)
+$ write sys$output P2
+$ 'P2
+$ VV='F$Verify(VV)
+$Exit:
+$ If V Then Set Verify
+$ENDSUBROUTINE
+$!------------------------------------------------------------------------------
+$!
+$! Check command line options and set symbols accordingly
+$!
+$!------------------------------------------------------------------------------
+$! Version history
+$! 0.01 20041206 First version to receive a number
+$! 0.02 20060126 Add new "HELP" target
+$ CHECK_OPTS:
+$ i = 1
+$ OPT_LOOP:
+$ if i .lt. 9
+$ then
+$   cparm = f$edit(p'i',"upcase")
+$!
+$! Check if parameter actually contains something
+$!
+$   if f$edit(cparm,"trim") .nes. ""
+$   then
+$     if cparm .eqs. "DEBUG"
+$     then
+$       ccopt = ccopt + "/noopt/deb"
+$       lopts = lopts + "/deb"
+$     endif
+$     if f$locate("CCOPT=",cparm) .lt. f$length(cparm)
+$     then
+$       start = f$locate("=",cparm) + 1
+$       len   = f$length(cparm) - start
+$       ccopt = ccopt + f$extract(start,len,cparm)
+$       if f$locate("AS_IS",f$edit(ccopt,"UPCASE")) .lt. f$length(ccopt) -
+          then s_case = true
+$     endif
+$     if cparm .eqs. "LINK" then linkonly = true
+$     if f$locate("LOPTS=",cparm) .lt. f$length(cparm)
+$     then
+$       start = f$locate("=",cparm) + 1
+$       len   = f$length(cparm) - start
+$       lopts = lopts + f$extract(start,len,cparm)
+$     endif
+$     if f$locate("CC=",cparm) .lt. f$length(cparm)
+$     then
+$       start  = f$locate("=",cparm) + 1
+$       len    = f$length(cparm) - start
+$       cc_com = f$extract(start,len,cparm)
+        if (cc_com .nes. "DECC") .and. -
+           (cc_com .nes. "VAXC") .and. -
+           (cc_com .nes. "GNUC")
+$       then
+$         write sys$output "Unsupported compiler choice ''cc_com' ignored"
+$         write sys$output "Use DECC, VAXC, or GNUC instead"
+$       else
+$         if cc_com .eqs. "DECC" then its_decc = true
+$         if cc_com .eqs. "VAXC" then its_vaxc = true
+$         if cc_com .eqs. "GNUC" then its_gnuc = true
+$       endif
+$     endif
+$     if f$locate("MAKE=",cparm) .lt. f$length(cparm)
+$     then
+$       start  = f$locate("=",cparm) + 1
+$       len    = f$length(cparm) - start
+$       mmks = f$extract(start,len,cparm)
+$       if (mmks .eqs. "MMK") .or. (mmks .eqs. "MMS")
+$       then
+$         make = mmks
+$       else
+$         write sys$output "Unsupported make choice ''mmks' ignored"
+$         write sys$output "Use MMK or MMS instead"
+$       endif
+$     endif
+$     if cparm .eqs. "HELP" then gosub bhelp
+$   endif
+$   i = i + 1
+$   goto opt_loop
+$ endif
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! Look for the compiler used
+$!
+$! Version history
+$! 0.01 20040223 First version to receive a number
+$! 0.02 20040229 Save/set value of decc$no_rooted_search_lists
+$! 0.03 20060202 Extend handling of GNU C
+$! 0.04 20090402 Compaq -> hp
+$CHECK_COMPILER:
+$ if (.not. (its_decc .or. its_vaxc .or. its_gnuc))
+$ then
+$   its_decc = (f$search("SYS$SYSTEM:DECC$COMPILER.EXE") .nes. "")
+$   its_vaxc = .not. its_decc .and. (F$Search("SYS$System:VAXC.Exe") .nes. "")
+$   its_gnuc = .not. (its_decc .or. its_vaxc) .and. (f$trnlnm("gnu_cc") .nes. "")
+$ endif
+$!
+$! Exit if no compiler available
+$!
+$ if (.not. (its_decc .or. its_vaxc .or. its_gnuc))
+$ then goto CC_ERR
+$ else
+$   if its_decc
+$   then
+$     write sys$output "CC compiler check ... hp C"
+$     if f$trnlnm("decc$no_rooted_search_lists") .nes. ""
+$     then
+$       dnrsl = f$trnlnm("decc$no_rooted_search_lists")
+$     endif
+$     define/nolog decc$no_rooted_search_lists 1
+$   else
+$     if its_vaxc then write sys$output "CC compiler check ... VAX C"
+$     if its_gnuc
+$     then
+$         write sys$output "CC compiler check ... GNU C"
+$         if f$trnlnm(topt) then write topt "gnu_cc:[000000]gcclib.olb/lib"
+$         if f$trnlnm(optf) then write optf "gnu_cc:[000000]gcclib.olb/lib"
+$         cc = "gcc"
+$     endif
+$     if f$trnlnm(topt) then write topt "sys$share:vaxcrtl.exe/share"
+$     if f$trnlnm(optf) then write optf "sys$share:vaxcrtl.exe/share"
+$   endif
+$ endif
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! If MMS/MMK are available dump out the descrip.mms if required
+$!
+$CREA_MMS:
+$ write sys$output "Creating descrip.mms..."
+$ create descrip.mms
+$ open/append out descrip.mms
+$ copy sys$input: out
+$ deck
+# descrip.mms: MMS description file for building zlib on VMS
+# written by Martin P.J. Zinser
+# <zinser@zinser.no-ip.info or martin.zinser@eurexchange.com>
+
+OBJS = adler32.obj, compress.obj, crc32.obj, gzclose.obj, gzlib.obj\
+       gzread.obj, gzwrite.obj, uncompr.obj, infback.obj\
+       deflate.obj, trees.obj, zutil.obj, inflate.obj, \
+       inftrees.obj, inffast.obj
+
+$ eod
+$ write out "CFLAGS=", ccopt
+$ write out "LOPTS=", lopts
+$ write out "all : example.exe minigzip.exe libz.olb"
+$ copy sys$input: out
+$ deck
+        @ write sys$output " Example applications available"
+
+libz.olb : libz.olb($(OBJS))
+	@ write sys$output " libz available"
+
+example.exe : example.obj libz.olb
+              link $(LOPTS) example,libz.olb/lib
+
+minigzip.exe : minigzip.obj libz.olb
+              link $(LOPTS) minigzip,libz.olb/lib
+
+clean :
+	delete *.obj;*,libz.olb;*,*.opt;*,*.exe;*
+
+
+# Other dependencies.
+adler32.obj  : adler32.c zutil.h zlib.h zconf.h
+compress.obj : compress.c zlib.h zconf.h
+crc32.obj    : crc32.c zutil.h zlib.h zconf.h
+deflate.obj  : deflate.c deflate.h zutil.h zlib.h zconf.h
+example.obj  : [.test]example.c zlib.h zconf.h
+gzclose.obj  : gzclose.c zutil.h zlib.h zconf.h
+gzlib.obj    : gzlib.c zutil.h zlib.h zconf.h
+gzread.obj   : gzread.c zutil.h zlib.h zconf.h
+gzwrite.obj  : gzwrite.c zutil.h zlib.h zconf.h
+inffast.obj  : inffast.c zutil.h zlib.h zconf.h inftrees.h inffast.h
+inflate.obj  : inflate.c zutil.h zlib.h zconf.h
+inftrees.obj : inftrees.c zutil.h zlib.h zconf.h inftrees.h
+minigzip.obj : [.test]minigzip.c zlib.h zconf.h
+trees.obj    : trees.c deflate.h zutil.h zlib.h zconf.h
+uncompr.obj  : uncompr.c zlib.h zconf.h
+zutil.obj    : zutil.c zutil.h zlib.h zconf.h
+infback.obj  : infback.c zutil.h inftrees.h inflate.h inffast.h inffixed.h
+$ eod
+$ close out
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! Read list of core library sources from makefile.in and create options
+$! needed to build shareable image
+$!
+$CREA_OLIST:
+$ open/read min makefile.in
+$ open/write mod modules.opt
+$ src_check_list = "OBJZ =#OBJG ="
+$MRLOOP:
+$ read/end=mrdone min rec
+$ i = 0
+$SRC_CHECK_LOOP:
+$ src_check = f$element(i, "#", src_check_list)
+$ i = i+1
+$ if src_check .eqs. "#" then goto mrloop
+$ if (f$extract(0,6,rec) .nes. src_check) then goto src_check_loop
+$ rec = rec - src_check
+$ gosub extra_filnam
+$ if (f$element(1,"\",rec) .eqs. "\") then goto mrloop
+$MRSLOOP:
+$ read/end=mrdone min rec
+$ gosub extra_filnam
+$ if (f$element(1,"\",rec) .nes. "\") then goto mrsloop
+$MRDONE:
+$ close min
+$ close mod
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! Take record extracted in crea_olist and split it into single filenames
+$!
+$EXTRA_FILNAM:
+$ myrec = f$edit(rec - "\", "trim,compress")
+$ i = 0
+$FELOOP:
+$ srcfil = f$element(i," ", myrec)
+$ if (srcfil .nes. " ")
+$ then
+$   write mod f$parse(srcfil,,,"NAME"), ".obj"
+$   i = i + 1
+$   goto feloop
+$ endif
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! Find current Zlib version number
+$!
+$FIND_VERSION:
+$ open/read h_in 'v_file'
+$hloop:
+$ read/end=hdone h_in rec
+$ rec = f$edit(rec,"TRIM")
+$ if (f$extract(0,1,rec) .nes. "#") then goto hloop
+$ rec = f$edit(rec - "#", "TRIM")
+$ if f$element(0," ",rec) .nes. "define" then goto hloop
+$ if f$element(1," ",rec) .eqs. v_string
+$ then
+$   version = 'f$element(2," ",rec)'
+$   goto hdone
+$ endif
+$ goto hloop
+$hdone:
+$ close h_in
+$ return
+$!------------------------------------------------------------------------------
+$!
+$CHECK_CONFIG:
+$!
+$ in_ldef = f$locate(cdef,libdefs)
+$ if (in_ldef .lt. f$length(libdefs))
+$ then
+$   write aconf "#define ''cdef' 1"
+$   libdefs = f$extract(0,in_ldef,libdefs) + -
+              f$extract(in_ldef + f$length(cdef) + 1, -
+                        f$length(libdefs) - in_ldef - f$length(cdef) - 1, -
+                        libdefs)
+$ else
+$   if (f$type('cdef') .eqs. "INTEGER")
+$   then
+$     write aconf "#define ''cdef' ", 'cdef'
+$   else
+$     if (f$type('cdef') .eqs. "STRING")
+$     then
+$       write aconf "#define ''cdef' ", """", '''cdef'', """"
+$     else
+$       gosub check_cc_def
+$     endif
+$   endif
+$ endif
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! Check if this is a define relating to the properties of the C/C++
+$! compiler
+$!
+$ CHECK_CC_DEF:
+$ if (cdef .eqs. "_LARGEFILE64_SOURCE")
+$ then
+$   copy sys$input: 'tc'
+$   deck
+#include "tconfig"
+#define _LARGEFILE
+#include <stdio.h>
+
+int main(){
+FILE *fp;
+  fp = fopen("temp.txt","r");
+  fseeko(fp,1,SEEK_SET);
+  fclose(fp);
+}
+
+$   eod
+$   test_inv = false
+$   comm_h = false
+$   gosub cc_prop_check
+$   return
+$ endif
+$ write aconf "/* ", line, " */"
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! Check for properties of C/C++ compiler
+$!
+$! Version history
+$! 0.01 20031020 First version to receive a number
+$! 0.02 20031022 Added logic for defines with value
+$! 0.03 20040309 Make sure local config file gets not deleted
+$! 0.04 20041230 Also write include for configure run
+$! 0.05 20050103 Add processing of "comment defines"
+$CC_PROP_CHECK:
+$ cc_prop = true
+$ is_need = false
+$ is_need = (f$extract(0,4,cdef) .eqs. "NEED") .or. (test_inv .eq. true)
+$ if f$search(th) .eqs. "" then create 'th'
+$ set message/nofac/noident/nosever/notext
+$ on error then continue
+$ cc 'tmpnam'
+$ if .not. ($status)  then cc_prop = false
+$ on error then continue
+$! The headers might lie about the capabilities of the RTL
+$ link 'tmpnam',tmp.opt/opt
+$ if .not. ($status)  then cc_prop = false
+$ set message/fac/ident/sever/text
+$ on error then goto err_exit
+$ delete/nolog 'tmpnam'.*;*/exclude='th'
+$ if (cc_prop .and. .not. is_need) .or. -
+     (.not. cc_prop .and. is_need)
+$ then
+$   write sys$output "Checking for ''cdef'... yes"
+$   if f$type('cdef_val'_yes) .nes. ""
+$   then
+$     if f$type('cdef_val'_yes) .eqs. "INTEGER" -
+         then call write_config f$fao("#define !AS !UL",cdef,'cdef_val'_yes)
+$     if f$type('cdef_val'_yes) .eqs. "STRING" -
+         then call write_config f$fao("#define !AS !AS",cdef,'cdef_val'_yes)
+$   else
+$     call write_config f$fao("#define !AS 1",cdef)
+$   endif
+$   if (cdef .eqs. "HAVE_FSEEKO") .or. (cdef .eqs. "_LARGE_FILES") .or. -
+       (cdef .eqs. "_LARGEFILE64_SOURCE") then -
+      call write_config f$string("#define _LARGEFILE 1")
+$ else
+$   write sys$output "Checking for ''cdef'... no"
+$   if (comm_h)
+$   then
+      call write_config f$fao("/* !AS */",line)
+$   else
+$     if f$type('cdef_val'_no) .nes. ""
+$     then
+$       if f$type('cdef_val'_no) .eqs. "INTEGER" -
+           then call write_config f$fao("#define !AS !UL",cdef,'cdef_val'_no)
+$       if f$type('cdef_val'_no) .eqs. "STRING" -
+           then call write_config f$fao("#define !AS !AS",cdef,'cdef_val'_no)
+$     else
+$       call write_config f$fao("#undef !AS",cdef)
+$     endif
+$   endif
+$ endif
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! Check for properties of C/C++ compiler with multiple result values
+$!
+$! Version history
+$! 0.01 20040127 First version
+$! 0.02 20050103 Reconcile changes from cc_prop up to version 0.05
+$CC_MPROP_CHECK:
+$ cc_prop = true
+$ i    = 1
+$ idel = 1
+$ MT_LOOP:
+$ if f$type(result_'i') .eqs. "STRING"
+$ then
+$   set message/nofac/noident/nosever/notext
+$   on error then continue
+$   cc 'tmpnam'_'i'
+$   if .not. ($status)  then cc_prop = false
+$   on error then continue
+$! The headers might lie about the capabilities of the RTL
+$   link 'tmpnam'_'i',tmp.opt/opt
+$   if .not. ($status)  then cc_prop = false
+$   set message/fac/ident/sever/text
+$   on error then goto err_exit
+$   delete/nolog 'tmpnam'_'i'.*;*
+$   if (cc_prop)
+$   then
+$     write sys$output "Checking for ''cdef'... ", mdef_'i'
+$     if f$type(mdef_'i') .eqs. "INTEGER" -
+         then call write_config f$fao("#define !AS !UL",cdef,mdef_'i')
+$     if f$type('cdef_val'_yes) .eqs. "STRING" -
+         then call write_config f$fao("#define !AS !AS",cdef,mdef_'i')
+$     goto msym_clean
+$   else
+$     i = i + 1
+$     goto mt_loop
+$   endif
+$ endif
+$ write sys$output "Checking for ''cdef'... no"
+$ call write_config f$fao("#undef !AS",cdef)
+$ MSYM_CLEAN:
+$ if (idel .le. msym_max)
+$ then
+$   delete/sym mdef_'idel'
+$   idel = idel + 1
+$   goto msym_clean
+$ endif
+$ return
+$!------------------------------------------------------------------------------
+$!
+$! Write configuration to both permanent and temporary config file
+$!
+$! Version history
+$! 0.01 20031029 First version to receive a number
+$!
+$WRITE_CONFIG: SUBROUTINE
+$  write aconf 'p1'
+$  open/append confh 'th'
+$  write confh 'p1'
+$  close confh
+$ENDSUBROUTINE
+$!------------------------------------------------------------------------------
+$!
+$! Analyze the project map file and create the symbol vector for a shareable
+$! image from it
+$!
+$! Version history
+$! 0.01 20120128 First version
+$! 0.02 20120226 Add pre-load logic
+$!
+$ MAP_2_SHOPT: Subroutine
+$!
+$ SAY := "WRITE_ SYS$OUTPUT"
+$!
+$ IF F$SEARCH("''P1'") .EQS. ""
+$ THEN
+$    SAY "MAP_2_SHOPT-E-NOSUCHFILE:  Error, inputfile ''p1' not available"
+$    goto exit_m2s
+$ ENDIF
+$ IF "''P2'" .EQS. ""
+$ THEN
+$    SAY "MAP_2_SHOPT:  Error, no output file provided"
+$    goto exit_m2s
+$ ENDIF
+$!
+$ module1 = "deflate#deflateEnd#deflateInit_#deflateParams#deflateSetDictionary"
+$ module2 = "gzclose#gzerror#gzgetc#gzgets#gzopen#gzprintf#gzputc#gzputs#gzread"
+$ module3 = "gzseek#gztell#inflate#inflateEnd#inflateInit_#inflateSetDictionary"
+$ module4 = "inflateSync#uncompress#zlibVersion#compress"
+$ open/read map 'p1
+$ if axp .or. ia64
+$ then
+$     open/write aopt a.opt
+$     open/write bopt b.opt
+$     write aopt " CASE_SENSITIVE=YES"
+$     write bopt "SYMBOL_VECTOR= (-"
+$     mod_sym_num = 1
+$ MOD_SYM_LOOP:
+$     if f$type(module'mod_sym_num') .nes. ""
+$     then
+$         mod_in = 0
+$ MOD_SYM_IN:
+$         shared_proc = f$element(mod_in, "#", module'mod_sym_num')
+$         if shared_proc .nes. "#"
+$         then
+$             write aopt f$fao(" symbol_vector=(!AS/!AS=PROCEDURE)",-
+        		       f$edit(shared_proc,"upcase"),shared_proc)
+$             write bopt f$fao("!AS=PROCEDURE,-",shared_proc)
+$             mod_in = mod_in + 1
+$             goto mod_sym_in
+$         endif
+$         mod_sym_num = mod_sym_num + 1
+$         goto mod_sym_loop
+$     endif
+$MAP_LOOP:
+$     read/end=map_end map line
+$     if (f$locate("{",line).lt. f$length(line)) .or. -
+         (f$locate("global:", line) .lt. f$length(line))
+$     then
+$         proc = true
+$         goto map_loop
+$     endif
+$     if f$locate("}",line).lt. f$length(line) then proc = false
+$     if f$locate("local:", line) .lt. f$length(line) then proc = false
+$     if proc
+$     then
+$         shared_proc = f$edit(line,"collapse")
+$         chop_semi = f$locate(";", shared_proc)
+$         if chop_semi .lt. f$length(shared_proc) then -
+              shared_proc = f$extract(0, chop_semi, shared_proc)
+$         write aopt f$fao(" symbol_vector=(!AS/!AS=PROCEDURE)",-
+        			 f$edit(shared_proc,"upcase"),shared_proc)
+$         write bopt f$fao("!AS=PROCEDURE,-",shared_proc)
+$     endif
+$     goto map_loop
+$MAP_END:
+$     close/nolog aopt
+$     close/nolog bopt
+$     open/append libopt 'p2'
+$     open/read aopt a.opt
+$     open/read bopt b.opt
+$ALOOP:
+$     read/end=aloop_end aopt line
+$     write libopt line
+$     goto aloop
+$ALOOP_END:
+$     close/nolog aopt
+$     sv = ""
+$BLOOP:
+$     read/end=bloop_end bopt svn
+$     if (svn.nes."")
+$     then
+$        if (sv.nes."") then write libopt sv
+$        sv = svn
+$     endif
+$     goto bloop
+$BLOOP_END:
+$     write libopt f$extract(0,f$length(sv)-2,sv), "-"
+$     write libopt ")"
+$     close/nolog bopt
+$     delete/nolog/noconf a.opt;*,b.opt;*
+$ else
+$     if vax
+$     then
+$     open/append libopt 'p2'
+$     mod_sym_num = 1
+$ VMOD_SYM_LOOP:
+$     if f$type(module'mod_sym_num') .nes. ""
+$     then
+$         mod_in = 0
+$ VMOD_SYM_IN:
+$         shared_proc = f$element(mod_in, "#", module'mod_sym_num')
+$         if shared_proc .nes. "#"
+$         then
+$     	      write libopt f$fao("UNIVERSAL=!AS",-
+      	  			     f$edit(shared_proc,"upcase"))
+$             mod_in = mod_in + 1
+$             goto vmod_sym_in
+$         endif
+$         mod_sym_num = mod_sym_num + 1
+$         goto vmod_sym_loop
+$     endif
+$VMAP_LOOP:
+$     	  read/end=vmap_end map line
+$     	  if (f$locate("{",line).lt. f$length(line)) .or. -
+   	      (f$locate("global:", line) .lt. f$length(line))
+$     	  then
+$     	      proc = true
+$     	      goto vmap_loop
+$     	  endif
+$     	  if f$locate("}",line).lt. f$length(line) then proc = false
+$     	  if f$locate("local:", line) .lt. f$length(line) then proc = false
+$     	  if proc
+$     	  then
+$     	      shared_proc = f$edit(line,"collapse")
+$     	      chop_semi = f$locate(";", shared_proc)
+$     	      if chop_semi .lt. f$length(shared_proc) then -
+      	  	  shared_proc = f$extract(0, chop_semi, shared_proc)
+$     	      write libopt f$fao("UNIVERSAL=!AS",-
+      	  			     f$edit(shared_proc,"upcase"))
+$     	  endif
+$     	  goto vmap_loop
+$VMAP_END:
+$     else
+$         write sys$output "Unknown Architecture (Not VAX, AXP, or IA64)"
+$         write sys$output "No options file created"
+$     endif
+$ endif
+$ EXIT_M2S:
+$ close/nolog map
+$ close/nolog libopt
+$ endsubroutine

ADDED   3rd_party/zlib/msdos/Makefile.bor
Index: 3rd_party/zlib/msdos/Makefile.bor
==================================================================
--- 3rd_party/zlib/msdos/Makefile.bor
+++ 3rd_party/zlib/msdos/Makefile.bor
@@ -0,0 +1,115 @@
+# Makefile for zlib
+# Borland C++
+# Last updated: 15-Mar-2003
+
+# To use, do "make -fmakefile.bor"
+# To compile in small model, set below: MODEL=s
+
+# WARNING: the small model is supported but only for small values of
+# MAX_WBITS and MAX_MEM_LEVEL. For example:
+#    -DMAX_WBITS=11 -DDEF_WBITS=11 -DMAX_MEM_LEVEL=3
+# If you wish to reduce the memory requirements (default 256K for big
+# objects plus a few K), you can add to the LOC macro below:
+#   -DMAX_MEM_LEVEL=7 -DMAX_WBITS=14
+# See zconf.h for details about the memory requirements.
+
+# ------------ Turbo C++, Borland C++ ------------
+
+#    Optional nonstandard preprocessor flags (e.g. -DMAX_MEM_LEVEL=7)
+#    should be added to the environment via "set LOCAL_ZLIB=-DFOO" or added
+#    to the declaration of LOC here:
+LOC = $(LOCAL_ZLIB)
+
+# type for CPU required: 0: 8086, 1: 80186, 2: 80286, 3: 80386, etc.
+CPU_TYP = 0
+
+# memory model: one of s, m, c, l (small, medium, compact, large)
+MODEL=l
+
+# replace bcc with tcc for Turbo C++ 1.0, with bcc32 for the 32 bit version
+CC=bcc
+LD=bcc
+AR=tlib
+
+# compiler flags
+# replace "-O2" by "-O -G -a -d" for Turbo C++ 1.0
+CFLAGS=-O2 -Z -m$(MODEL) $(LOC)
+
+LDFLAGS=-m$(MODEL) -f-
+
+
+# variables
+ZLIB_LIB = zlib_$(MODEL).lib
+
+OBJ1 = adler32.obj compress.obj crc32.obj deflate.obj gzclose.obj gzlib.obj gzread.obj
+OBJ2 = gzwrite.obj infback.obj inffast.obj inflate.obj inftrees.obj trees.obj uncompr.obj zutil.obj
+OBJP1 = +adler32.obj+compress.obj+crc32.obj+deflate.obj+gzclose.obj+gzlib.obj+gzread.obj
+OBJP2 = +gzwrite.obj+infback.obj+inffast.obj+inflate.obj+inftrees.obj+trees.obj+uncompr.obj+zutil.obj
+
+
+# targets
+all: $(ZLIB_LIB) example.exe minigzip.exe
+
+.c.obj:
+	$(CC) -c $(CFLAGS) $*.c
+
+adler32.obj: adler32.c zlib.h zconf.h
+
+compress.obj: compress.c zlib.h zconf.h
+
+crc32.obj: crc32.c zlib.h zconf.h crc32.h
+
+deflate.obj: deflate.c deflate.h zutil.h zlib.h zconf.h
+
+gzclose.obj: gzclose.c zlib.h zconf.h gzguts.h
+
+gzlib.obj: gzlib.c zlib.h zconf.h gzguts.h
+
+gzread.obj: gzread.c zlib.h zconf.h gzguts.h
+
+gzwrite.obj: gzwrite.c zlib.h zconf.h gzguts.h
+
+infback.obj: infback.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h inffixed.h
+
+inffast.obj: inffast.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h
+
+inflate.obj: inflate.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h inffixed.h
+
+inftrees.obj: inftrees.c zutil.h zlib.h zconf.h inftrees.h
+
+trees.obj: trees.c zutil.h zlib.h zconf.h deflate.h trees.h
+
+uncompr.obj: uncompr.c zlib.h zconf.h
+
+zutil.obj: zutil.c zutil.h zlib.h zconf.h
+
+example.obj: test/example.c zlib.h zconf.h
+
+minigzip.obj: test/minigzip.c zlib.h zconf.h
+
+
+# the command line is cut to fit in the MS-DOS 128 byte limit:
+$(ZLIB_LIB): $(OBJ1) $(OBJ2)
+	-del $(ZLIB_LIB)
+	$(AR) $(ZLIB_LIB) $(OBJP1)
+	$(AR) $(ZLIB_LIB) $(OBJP2)
+
+example.exe: example.obj $(ZLIB_LIB)
+	$(LD) $(LDFLAGS) example.obj $(ZLIB_LIB)
+
+minigzip.exe: minigzip.obj $(ZLIB_LIB)
+	$(LD) $(LDFLAGS) minigzip.obj $(ZLIB_LIB)
+
+test: example.exe minigzip.exe
+	example
+	echo hello world | minigzip | minigzip -d
+
+clean:
+	-del *.obj
+	-del *.lib
+	-del *.exe
+	-del zlib_*.bak
+	-del foo.gz

ADDED   3rd_party/zlib/msdos/Makefile.dj2
Index: 3rd_party/zlib/msdos/Makefile.dj2
==================================================================
--- 3rd_party/zlib/msdos/Makefile.dj2
+++ 3rd_party/zlib/msdos/Makefile.dj2
@@ -0,0 +1,104 @@
+# Makefile for zlib.  Modified for djgpp v2.0 by F. J. Donahoe, 3/15/96.
+# Copyright (C) 1995-1998 Jean-loup Gailly.
+# For conditions of distribution and use, see copyright notice in zlib.h
+
+# To compile, or to compile and test, type:
+#
+#   make -fmakefile.dj2;  make test -fmakefile.dj2
+#
+# To install libz.a, zconf.h and zlib.h in the djgpp directories, type:
+#
+#    make install -fmakefile.dj2
+#
+# after first defining LIBRARY_PATH and INCLUDE_PATH in djgpp.env as
+# in the sample below if the pattern of the DJGPP distribution is to
+# be followed.  Remember that, while <sp>'es around <=> are ignored in
+# makefiles, they are *not* in batch files or in djgpp.env.
+# - - - - -
+# [make]
+# INCLUDE_PATH=%\>;INCLUDE_PATH%%\DJDIR%\include
+# LIBRARY_PATH=%\>;LIBRARY_PATH%%\DJDIR%\lib
+# BUTT=-m486
+# - - - - -
+# Alternately, these variables may be defined below, overriding the values
+# in djgpp.env, as
+# INCLUDE_PATH=c:\usr\include
+# LIBRARY_PATH=c:\usr\lib
+
+CC=gcc
+
+#CFLAGS=-MMD -O
+#CFLAGS=-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7
+#CFLAGS=-MMD -g -DZLIB_DEBUG
+CFLAGS=-MMD -O3 $(BUTT) -Wall -Wwrite-strings -Wpointer-arith -Wconversion \
+             -Wstrict-prototypes -Wmissing-prototypes
+
+# If cp.exe is available, replace "copy /Y" with "cp -fp" .
+CP=copy /Y
+# If gnu install.exe is available, replace $(CP) with ginstall.
+INSTALL=$(CP)
+# The default value of RM is "rm -f."  If "rm.exe" is found, comment out:
+RM=del
+LDLIBS=-L. -lz
+LD=$(CC) -s -o
+LDSHARED=$(CC)
+
+INCL=zlib.h zconf.h
+LIBS=libz.a
+
+AR=ar rcs
+
+prefix=/usr/local
+exec_prefix = $(prefix)
+
+OBJS = adler32.o compress.o crc32.o gzclose.o gzlib.o gzread.o gzwrite.o \
+       uncompr.o deflate.o trees.o zutil.o inflate.o infback.o inftrees.o inffast.o
+
+OBJA =
+# to use the asm code: make OBJA=match.o
+
+TEST_OBJS = example.o minigzip.o
+
+all: example.exe minigzip.exe
+
+check: test
+test: all
+	./example
+	echo hello world | .\minigzip | .\minigzip -d
+
+%.o : %.c
+	$(CC) $(CFLAGS) -c $< -o $@
+
+libz.a: $(OBJS) $(OBJA)
+	$(AR) $@ $(OBJS) $(OBJA)
+
+%.exe : %.o $(LIBS)
+	$(LD) $@ $< $(LDLIBS)
+
+# INCLUDE_PATH and LIBRARY_PATH were set for [make] in djgpp.env .
+
+.PHONY : uninstall clean
+
+install: $(INCL) $(LIBS)
+	-@if not exist $(INCLUDE_PATH)\nul mkdir $(INCLUDE_PATH)
+	-@if not exist $(LIBRARY_PATH)\nul mkdir $(LIBRARY_PATH)
+	$(INSTALL) zlib.h $(INCLUDE_PATH)
+	$(INSTALL) zconf.h $(INCLUDE_PATH)
+	$(INSTALL) libz.a $(LIBRARY_PATH)
+
+uninstall:
+	$(RM) $(INCLUDE_PATH)\zlib.h
+	$(RM) $(INCLUDE_PATH)\zconf.h
+	$(RM) $(LIBRARY_PATH)\libz.a
+
+clean:
+	$(RM) *.d
+	$(RM) *.o
+	$(RM) *.exe
+	$(RM) libz.a
+	$(RM) foo.gz
+
+DEPS := $(wildcard *.d)
+ifneq ($(DEPS),)
+include $(DEPS)
+endif

ADDED   3rd_party/zlib/msdos/Makefile.emx
Index: 3rd_party/zlib/msdos/Makefile.emx
==================================================================
--- 3rd_party/zlib/msdos/Makefile.emx
+++ 3rd_party/zlib/msdos/Makefile.emx
@@ -0,0 +1,69 @@
+# Makefile for zlib.  Modified for emx 0.9c by Chr. Spieler, 6/17/98.
+# Copyright (C) 1995-1998 Jean-loup Gailly.
+# For conditions of distribution and use, see copyright notice in zlib.h
+
+# To compile, or to compile and test, type:
+#
+#   make -fmakefile.emx;  make test -fmakefile.emx
+#
+
+CC=gcc
+
+#CFLAGS=-MMD -O
+#CFLAGS=-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7
+#CFLAGS=-MMD -g -DZLIB_DEBUG
+CFLAGS=-MMD -O3 $(BUTT) -Wall -Wwrite-strings -Wpointer-arith -Wconversion \
+             -Wstrict-prototypes -Wmissing-prototypes
+
+# If cp.exe is available, replace "copy /Y" with "cp -fp" .
+CP=copy /Y
+# If gnu install.exe is available, replace $(CP) with ginstall.
+INSTALL=$(CP)
+# The default value of RM is "rm -f."  If "rm.exe" is found, comment out:
+RM=del
+LDLIBS=-L. -lzlib
+LD=$(CC) -s -o
+LDSHARED=$(CC)
+
+INCL=zlib.h zconf.h
+LIBS=zlib.a
+
+AR=ar rcs
+
+prefix=/usr/local
+exec_prefix = $(prefix)
+
+OBJS = adler32.o compress.o crc32.o gzclose.o gzlib.o gzread.o gzwrite.o \
+       uncompr.o deflate.o trees.o zutil.o inflate.o infback.o inftrees.o inffast.o
+
+TEST_OBJS = example.o minigzip.o
+
+all: example.exe minigzip.exe
+
+test: all
+	./example
+	echo hello world | .\minigzip | .\minigzip -d
+
+%.o : %.c
+	$(CC) $(CFLAGS) -c $< -o $@
+
+zlib.a: $(OBJS)
+	$(AR) $@ $(OBJS)
+
+%.exe : %.o $(LIBS)
+	$(LD) $@ $< $(LDLIBS)
+
+
+.PHONY : clean
+
+clean:
+	$(RM) *.d
+	$(RM) *.o
+	$(RM) *.exe
+	$(RM) zlib.a
+	$(RM) foo.gz
+
+DEPS := $(wildcard *.d)
+ifneq ($(DEPS),)
+include $(DEPS)
+endif

ADDED   3rd_party/zlib/msdos/Makefile.msc
Index: 3rd_party/zlib/msdos/Makefile.msc
==================================================================
--- 3rd_party/zlib/msdos/Makefile.msc
+++ 3rd_party/zlib/msdos/Makefile.msc
@@ -0,0 +1,112 @@
+# Makefile for zlib
+# Microsoft C 5.1 or later
+# Last updated: 19-Mar-2003
+
+# To use, do "make makefile.msc"
+# To compile in small model, set below: MODEL=S
+
+# If you wish to reduce the memory requirements (default 256K for big
+# objects plus a few K), you can add to the LOC macro below:
+#   -DMAX_MEM_LEVEL=7 -DMAX_WBITS=14
+# See zconf.h for details about the memory requirements.
+
+# ------------- Microsoft C 5.1 and later -------------
+
+#    Optional nonstandard preprocessor flags (e.g. -DMAX_MEM_LEVEL=7)
+#    should be added to the environment via "set LOCAL_ZLIB=-DFOO" or added
+#    to the declaration of LOC here:
+LOC = $(LOCAL_ZLIB)
+
+# Type for CPU required: 0: 8086, 1: 80186, 2: 80286, 3: 80386, etc.
+CPU_TYP = 0
+
+# Memory model: one of S, M, C, L (small, medium, compact, large)
+MODEL=L
+
+CC=cl
+CFLAGS=-nologo -A$(MODEL) -G$(CPU_TYP) -W3 -Oait -Gs $(LOC)
+#-Ox generates bad code with MSC 5.1
+LIB_CFLAGS=-Zl $(CFLAGS)
+
+LD=link
+LDFLAGS=/noi/e/st:0x1500/noe/farcall/packcode
+# "/farcall/packcode" are only useful for `large code' memory models
+# but should be a "no-op" for small code models.
+
+
+# variables
+ZLIB_LIB = zlib_$(MODEL).lib
+
+OBJ1 = adler32.obj compress.obj crc32.obj deflate.obj gzclose.obj gzlib.obj gzread.obj
+OBJ2 = gzwrite.obj infback.obj inffast.obj inflate.obj inftrees.obj trees.obj uncompr.obj zutil.obj
+
+
+# targets
+all:  $(ZLIB_LIB) example.exe minigzip.exe
+
+.c.obj:
+	$(CC) -c $(LIB_CFLAGS) $*.c
+
+adler32.obj: adler32.c zlib.h zconf.h
+
+compress.obj: compress.c zlib.h zconf.h
+
+crc32.obj: crc32.c zlib.h zconf.h crc32.h
+
+deflate.obj: deflate.c deflate.h zutil.h zlib.h zconf.h
+
+gzclose.obj: gzclose.c zlib.h zconf.h gzguts.h
+
+gzlib.obj: gzlib.c zlib.h zconf.h gzguts.h
+
+gzread.obj: gzread.c zlib.h zconf.h gzguts.h
+
+gzwrite.obj: gzwrite.c zlib.h zconf.h gzguts.h
+
+infback.obj: infback.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h inffixed.h
+
+inffast.obj: inffast.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h
+
+inflate.obj: inflate.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h inffixed.h
+
+inftrees.obj: inftrees.c zutil.h zlib.h zconf.h inftrees.h
+
+trees.obj: trees.c zutil.h zlib.h zconf.h deflate.h trees.h
+
+uncompr.obj: uncompr.c zlib.h zconf.h
+
+zutil.obj: zutil.c zutil.h zlib.h zconf.h
+
+example.obj: test/example.c zlib.h zconf.h
+	$(CC) -c $(CFLAGS) $*.c
+
+minigzip.obj: test/minigzip.c zlib.h zconf.h
+	$(CC) -c $(CFLAGS) $*.c
+
+
+# the command line is cut to fit in the MS-DOS 128 byte limit:
+$(ZLIB_LIB): $(OBJ1) $(OBJ2)
+	if exist $(ZLIB_LIB) del $(ZLIB_LIB)
+	lib $(ZLIB_LIB) $(OBJ1);
+	lib $(ZLIB_LIB) $(OBJ2);
+
+example.exe: example.obj $(ZLIB_LIB)
+	$(LD) $(LDFLAGS) example.obj,,,$(ZLIB_LIB);
+
+minigzip.exe: minigzip.obj $(ZLIB_LIB)
+	$(LD) $(LDFLAGS) minigzip.obj,,,$(ZLIB_LIB);
+
+test: example.exe minigzip.exe
+	example
+	echo hello world | minigzip | minigzip -d
+
+clean:
+	-del *.obj
+	-del *.lib
+	-del *.exe
+	-del *.map
+	-del zlib_*.bak
+	-del foo.gz

ADDED   3rd_party/zlib/msdos/Makefile.tc
Index: 3rd_party/zlib/msdos/Makefile.tc
==================================================================
--- 3rd_party/zlib/msdos/Makefile.tc
+++ 3rd_party/zlib/msdos/Makefile.tc
@@ -0,0 +1,100 @@
+# Makefile for zlib
+# Turbo C 2.01, Turbo C++ 1.01
+# Last updated: 15-Mar-2003
+
+# To use, do "make -fmakefile.tc"
+# To compile in small model, set below: MODEL=s
+
+# WARNING: the small model is supported but only for small values of
+# MAX_WBITS and MAX_MEM_LEVEL. For example:
+#    -DMAX_WBITS=11 -DMAX_MEM_LEVEL=3
+# If you wish to reduce the memory requirements (default 256K for big
+# objects plus a few K), you can add to CFLAGS below:
+#   -DMAX_MEM_LEVEL=7 -DMAX_WBITS=14
+# See zconf.h for details about the memory requirements.
+
+# ------------ Turbo C 2.01, Turbo C++ 1.01 ------------
+MODEL=l
+CC=tcc
+LD=tcc
+AR=tlib
+# CFLAGS=-O2 -G -Z -m$(MODEL) -DMAX_WBITS=11 -DMAX_MEM_LEVEL=3
+CFLAGS=-O2 -G -Z -m$(MODEL)
+LDFLAGS=-m$(MODEL) -f-
+
+
+# variables
+ZLIB_LIB = zlib_$(MODEL).lib
+
+OBJ1 = adler32.obj compress.obj crc32.obj deflate.obj gzclose.obj gzlib.obj gzread.obj
+OBJ2 = gzwrite.obj infback.obj inffast.obj inflate.obj inftrees.obj trees.obj uncompr.obj zutil.obj
+OBJP1 = +adler32.obj+compress.obj+crc32.obj+deflate.obj+gzclose.obj+gzlib.obj+gzread.obj
+OBJP2 = +gzwrite.obj+infback.obj+inffast.obj+inflate.obj+inftrees.obj+trees.obj+uncompr.obj+zutil.obj
+
+
+# targets
+all: $(ZLIB_LIB) example.exe minigzip.exe
+
+.c.obj:
+	$(CC) -c $(CFLAGS) $*.c
+
+adler32.obj: adler32.c zlib.h zconf.h
+
+compress.obj: compress.c zlib.h zconf.h
+
+crc32.obj: crc32.c zlib.h zconf.h crc32.h
+
+deflate.obj: deflate.c deflate.h zutil.h zlib.h zconf.h
+
+gzclose.obj: gzclose.c zlib.h zconf.h gzguts.h
+
+gzlib.obj: gzlib.c zlib.h zconf.h gzguts.h
+
+gzread.obj: gzread.c zlib.h zconf.h gzguts.h
+
+gzwrite.obj: gzwrite.c zlib.h zconf.h gzguts.h
+
+infback.obj: infback.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h inffixed.h
+
+inffast.obj: inffast.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h
+
+inflate.obj: inflate.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h inffixed.h
+
+inftrees.obj: inftrees.c zutil.h zlib.h zconf.h inftrees.h
+
+trees.obj: trees.c zutil.h zlib.h zconf.h deflate.h trees.h
+
+uncompr.obj: uncompr.c zlib.h zconf.h
+
+zutil.obj: zutil.c zutil.h zlib.h zconf.h
+
+example.obj: test/example.c zlib.h zconf.h
+
+minigzip.obj: test/minigzip.c zlib.h zconf.h
+
+
+# the command line is cut to fit in the MS-DOS 128 byte limit:
+$(ZLIB_LIB): $(OBJ1) $(OBJ2)
+	-del $(ZLIB_LIB)
+	$(AR) $(ZLIB_LIB) $(OBJP1)
+	$(AR) $(ZLIB_LIB) $(OBJP2)
+
+example.exe: example.obj $(ZLIB_LIB)
+	$(LD) $(LDFLAGS) example.obj $(ZLIB_LIB)
+
+minigzip.exe: minigzip.obj $(ZLIB_LIB)
+	$(LD) $(LDFLAGS) minigzip.obj $(ZLIB_LIB)
+
+test: example.exe minigzip.exe
+	example
+	echo hello world | minigzip | minigzip -d
+
+clean:
+	-del *.obj
+	-del *.lib
+	-del *.exe
+	-del zlib_*.bak
+	-del foo.gz

ADDED   3rd_party/zlib/nintendods/Makefile
Index: 3rd_party/zlib/nintendods/Makefile
==================================================================
--- 3rd_party/zlib/nintendods/Makefile
+++ 3rd_party/zlib/nintendods/Makefile
@@ -0,0 +1,126 @@
+#---------------------------------------------------------------------------------
+.SUFFIXES:
+#---------------------------------------------------------------------------------
+
+ifeq ($(strip $(DEVKITARM)),)
+$(error "Please set DEVKITARM in your environment. export DEVKITARM=<path to>devkitARM")
+endif
+
+include $(DEVKITARM)/ds_rules
+
+#---------------------------------------------------------------------------------
+# TARGET is the name of the output
+# BUILD is the directory where object files & intermediate files will be placed
+# SOURCES is a list of directories containing source code
+# DATA is a list of directories containing data files
+# INCLUDES is a list of directories containing header files
+#---------------------------------------------------------------------------------
+TARGET		:=	$(shell basename $(CURDIR))
+BUILD		:=	build
+SOURCES		:=	../../
+DATA		:=	data
+INCLUDES	:=	include
+
+#---------------------------------------------------------------------------------
+# options for code generation
+#---------------------------------------------------------------------------------
+ARCH	:=	-mthumb -mthumb-interwork
+
+CFLAGS	:=	-Wall -O2\
+		-march=armv5te -mtune=arm946e-s \
+		-fomit-frame-pointer -ffast-math \
+		$(ARCH)
+
+CFLAGS	+=	$(INCLUDE) -DARM9
+CXXFLAGS	:= $(CFLAGS) -fno-rtti -fno-exceptions
+
+ASFLAGS	:=	$(ARCH) -march=armv5te -mtune=arm946e-s
+LDFLAGS	=	-specs=ds_arm9.specs -g $(ARCH) -Wl,-Map,$(notdir $*.map)
+
+#---------------------------------------------------------------------------------
+# list of directories containing libraries, this must be the top level containing
+# include and lib
+#---------------------------------------------------------------------------------
+LIBDIRS	:=	$(LIBNDS)
+
+#---------------------------------------------------------------------------------
+# no real need to edit anything past this point unless you need to add additional
+# rules for different file extensions
+#---------------------------------------------------------------------------------
+ifneq ($(BUILD),$(notdir $(CURDIR)))
+#---------------------------------------------------------------------------------
+
+export OUTPUT	:=	$(CURDIR)/lib/libz.a
+
+export VPATH	:=	$(foreach dir,$(SOURCES),$(CURDIR)/$(dir)) \
+			$(foreach dir,$(DATA),$(CURDIR)/$(dir))
+
+export DEPSDIR	:=	$(CURDIR)/$(BUILD)
+
+CFILES		:=	$(foreach dir,$(SOURCES),$(notdir $(wildcard $(dir)/*.c)))
+CPPFILES	:=	$(foreach dir,$(SOURCES),$(notdir $(wildcard $(dir)/*.cpp)))
+SFILES		:=	$(foreach dir,$(SOURCES),$(notdir $(wildcard $(dir)/*.s)))
+BINFILES	:=	$(foreach dir,$(DATA),$(notdir $(wildcard $(dir)/*.*)))
+
+#---------------------------------------------------------------------------------
+# use CXX for linking C++ projects, CC for standard C
+#---------------------------------------------------------------------------------
+ifeq ($(strip $(CPPFILES)),)
+#---------------------------------------------------------------------------------
+	export LD	:=	$(CC)
+#---------------------------------------------------------------------------------
+else
+#---------------------------------------------------------------------------------
+	export LD	:=	$(CXX)
+#---------------------------------------------------------------------------------
+endif
+#---------------------------------------------------------------------------------
+
+export OFILES	:=	$(addsuffix .o,$(BINFILES)) \
+			$(CPPFILES:.cpp=.o) $(CFILES:.c=.o) $(SFILES:.s=.o)
+
+export INCLUDE	:=	$(foreach dir,$(INCLUDES),-I$(CURDIR)/$(dir)) \
+			$(foreach dir,$(LIBDIRS),-I$(dir)/include) \
+			-I$(CURDIR)/$(BUILD)
+
+.PHONY: $(BUILD) clean all
+
+#---------------------------------------------------------------------------------
+all: $(BUILD)
+	@[ -d $@ ] || mkdir -p include
+	@cp ../../*.h include
+
+lib:
+	@[ -d $@ ] || mkdir -p $@
+	
+$(BUILD): lib
+	@[ -d $@ ] || mkdir -p $@
+	@$(MAKE) --no-print-directory -C $(BUILD) -f $(CURDIR)/Makefile
+
+#---------------------------------------------------------------------------------
+clean:
+	@echo clean ...
+	@rm -fr $(BUILD) lib
+
+#---------------------------------------------------------------------------------
+else
+
+DEPENDS	:=	$(OFILES:.o=.d)
+
+#---------------------------------------------------------------------------------
+# main targets
+#---------------------------------------------------------------------------------
+$(OUTPUT)	:	$(OFILES)
+
+#---------------------------------------------------------------------------------
+%.bin.o	:	%.bin
+#---------------------------------------------------------------------------------
+	@echo $(notdir $<)
+	@$(bin2o)
+
+
+-include $(DEPENDS)
+
+#---------------------------------------------------------------------------------------
+endif
+#---------------------------------------------------------------------------------------

ADDED   3rd_party/zlib/nintendods/README
Index: 3rd_party/zlib/nintendods/README
==================================================================
--- 3rd_party/zlib/nintendods/README
+++ 3rd_party/zlib/nintendods/README
@@ -0,0 +1,5 @@
+This Makefile requires devkitARM (http://www.devkitpro.org/category/devkitarm/) and works inside "contrib/nds". It is based on a devkitARM template.
+
+Eduardo Costa <eduardo.m.costa@gmail.com>
+January 3, 2009
+

ADDED   3rd_party/zlib/old/Makefile.emx
Index: 3rd_party/zlib/old/Makefile.emx
==================================================================
--- 3rd_party/zlib/old/Makefile.emx
+++ 3rd_party/zlib/old/Makefile.emx
@@ -0,0 +1,69 @@
+# Makefile for zlib.  Modified for emx/rsxnt by Chr. Spieler, 6/16/98.
+# Copyright (C) 1995-1998 Jean-loup Gailly.
+# For conditions of distribution and use, see copyright notice in zlib.h
+
+# To compile, or to compile and test, type:
+#
+#   make -fmakefile.emx;  make test -fmakefile.emx
+#
+
+CC=gcc -Zwin32
+
+#CFLAGS=-MMD -O
+#CFLAGS=-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7
+#CFLAGS=-MMD -g -DZLIB_DEBUG
+CFLAGS=-MMD -O3 $(BUTT) -Wall -Wwrite-strings -Wpointer-arith -Wconversion \
+             -Wstrict-prototypes -Wmissing-prototypes
+
+# If cp.exe is available, replace "copy /Y" with "cp -fp" .
+CP=copy /Y
+# If gnu install.exe is available, replace $(CP) with ginstall.
+INSTALL=$(CP)
+# The default value of RM is "rm -f."  If "rm.exe" is found, comment out:
+RM=del
+LDLIBS=-L. -lzlib
+LD=$(CC) -s -o
+LDSHARED=$(CC)
+
+INCL=zlib.h zconf.h
+LIBS=zlib.a
+
+AR=ar rcs
+
+prefix=/usr/local
+exec_prefix = $(prefix)
+
+OBJS = adler32.o compress.o crc32.o deflate.o gzclose.o gzlib.o gzread.o \
+       gzwrite.o infback.o inffast.o inflate.o inftrees.o trees.o uncompr.o zutil.o
+
+TEST_OBJS = example.o minigzip.o
+
+all: example.exe minigzip.exe
+
+test: all
+	./example
+	echo hello world | .\minigzip | .\minigzip -d
+
+%.o : %.c
+	$(CC) $(CFLAGS) -c $< -o $@
+
+zlib.a: $(OBJS)
+	$(AR) $@ $(OBJS)
+
+%.exe : %.o $(LIBS)
+	$(LD) $@ $< $(LDLIBS)
+
+
+.PHONY : clean
+
+clean:
+	$(RM) *.d
+	$(RM) *.o
+	$(RM) *.exe
+	$(RM) zlib.a
+	$(RM) foo.gz
+
+DEPS := $(wildcard *.d)
+ifneq ($(DEPS),)
+include $(DEPS)
+endif

ADDED   3rd_party/zlib/old/Makefile.riscos
Index: 3rd_party/zlib/old/Makefile.riscos
==================================================================
--- 3rd_party/zlib/old/Makefile.riscos
+++ 3rd_party/zlib/old/Makefile.riscos
@@ -0,0 +1,151 @@
+# Project:   zlib_1_03
+# Patched for zlib 1.1.2 rw@shadow.org.uk 19980430
+# test works out-of-the-box, installs `somewhere' on demand
+
+# Toolflags:
+CCflags = -c -depend !Depend -IC: -g -throwback  -DRISCOS  -fah
+C++flags = -c -depend !Depend -IC: -throwback
+Linkflags = -aif -c++ -o $@
+ObjAsmflags = -throwback -NoCache -depend !Depend
+CMHGflags =
+LibFileflags = -c -l -o $@
+Squeezeflags = -o $@
+
+# change the line below to where _you_ want the library installed.
+libdest = lib:zlib
+
+# Final targets:
+@.lib:   @.o.adler32 @.o.compress @.o.crc32 @.o.deflate @.o.gzio \
+        @.o.infblock @.o.infcodes @.o.inffast @.o.inflate @.o.inftrees @.o.infutil @.o.trees \
+        @.o.uncompr @.o.zutil
+        LibFile $(LibFileflags) @.o.adler32 @.o.compress @.o.crc32 @.o.deflate \
+        @.o.gzio @.o.infblock @.o.infcodes @.o.inffast @.o.inflate @.o.inftrees @.o.infutil \
+        @.o.trees @.o.uncompr @.o.zutil
+test:   @.minigzip @.example @.lib
+	@copy @.lib @.libc  A~C~DF~L~N~P~Q~RS~TV
+	@echo running tests: hang on.
+	@/@.minigzip -f -9 libc
+	@/@.minigzip -d libc-gz
+	@/@.minigzip -f -1 libc
+	@/@.minigzip -d libc-gz
+	@/@.minigzip -h -9 libc
+	@/@.minigzip -d libc-gz
+	@/@.minigzip -h -1 libc
+	@/@.minigzip -d libc-gz
+	@/@.minigzip -9 libc
+	@/@.minigzip -d libc-gz
+	@/@.minigzip -1 libc
+	@/@.minigzip -d libc-gz
+	@diff @.lib @.libc
+	@echo that should have reported '@.lib and @.libc identical' if you have diff.
+	@/@.example @.fred @.fred
+	@echo that will have given lots of hello!'s.
+
+@.minigzip:   @.o.minigzip @.lib C:o.Stubs
+        Link $(Linkflags) @.o.minigzip @.lib C:o.Stubs
+@.example:   @.o.example @.lib C:o.Stubs
+        Link $(Linkflags) @.o.example @.lib C:o.Stubs
+
+install: @.lib
+	cdir $(libdest)
+	cdir $(libdest).h
+	@copy @.h.zlib $(libdest).h.zlib A~C~DF~L~N~P~Q~RS~TV
+	@copy @.h.zconf $(libdest).h.zconf A~C~DF~L~N~P~Q~RS~TV
+	@copy @.lib $(libdest).lib  A~C~DF~L~N~P~Q~RS~TV
+	@echo okay, installed zlib in $(libdest)
+
+clean:; remove @.minigzip
+	remove @.example
+	remove @.libc
+	-wipe @.o.* F~r~cV
+	remove @.fred
+
+# User-editable dependencies:
+.c.o:
+        cc $(ccflags) -o $@ $<
+
+# Static dependencies:
+
+# Dynamic dependencies:
+o.example:	c.example
+o.example:	h.zlib
+o.example:	h.zconf
+o.minigzip:	c.minigzip
+o.minigzip:	h.zlib
+o.minigzip:	h.zconf
+o.adler32:	c.adler32
+o.adler32:	h.zlib
+o.adler32:	h.zconf
+o.compress:	c.compress
+o.compress:	h.zlib
+o.compress:	h.zconf
+o.crc32:	c.crc32
+o.crc32:	h.zlib
+o.crc32:	h.zconf
+o.deflate:	c.deflate
+o.deflate:	h.deflate
+o.deflate:	h.zutil
+o.deflate:	h.zlib
+o.deflate:	h.zconf
+o.gzio:	c.gzio
+o.gzio:	h.zutil
+o.gzio:	h.zlib
+o.gzio:	h.zconf
+o.infblock:	c.infblock
+o.infblock:	h.zutil
+o.infblock:	h.zlib
+o.infblock:	h.zconf
+o.infblock:	h.infblock
+o.infblock:	h.inftrees
+o.infblock:	h.infcodes
+o.infblock:	h.infutil
+o.infcodes:	c.infcodes
+o.infcodes:	h.zutil
+o.infcodes:	h.zlib
+o.infcodes:	h.zconf
+o.infcodes:	h.inftrees
+o.infcodes:	h.infblock
+o.infcodes:	h.infcodes
+o.infcodes:	h.infutil
+o.infcodes:	h.inffast
+o.inffast:	c.inffast
+o.inffast:	h.zutil
+o.inffast:	h.zlib
+o.inffast:	h.zconf
+o.inffast:	h.inftrees
+o.inffast:	h.infblock
+o.inffast:	h.infcodes
+o.inffast:	h.infutil
+o.inffast:	h.inffast
+o.inflate:	c.inflate
+o.inflate:	h.zutil
+o.inflate:	h.zlib
+o.inflate:	h.zconf
+o.inflate:	h.infblock
+o.inftrees:	c.inftrees
+o.inftrees:	h.zutil
+o.inftrees:	h.zlib
+o.inftrees:	h.zconf
+o.inftrees:	h.inftrees
+o.inftrees:	h.inffixed
+o.infutil:	c.infutil
+o.infutil:	h.zutil
+o.infutil:	h.zlib
+o.infutil:	h.zconf
+o.infutil:	h.infblock
+o.infutil:	h.inftrees
+o.infutil:	h.infcodes
+o.infutil:	h.infutil
+o.trees:	c.trees
+o.trees:	h.deflate
+o.trees:	h.zutil
+o.trees:	h.zlib
+o.trees:	h.zconf
+o.trees:	h.trees
+o.uncompr:	c.uncompr
+o.uncompr:	h.zlib
+o.uncompr:	h.zconf
+o.zutil:	c.zutil
+o.zutil:	h.zutil
+o.zutil:	h.zlib
+o.zutil:	h.zconf

ADDED   3rd_party/zlib/old/README
Index: 3rd_party/zlib/old/README
==================================================================
--- 3rd_party/zlib/old/README
+++ 3rd_party/zlib/old/README
@@ -0,0 +1,3 @@
+This directory contains files that have not been updated for zlib 1.2.x
+
+(Volunteers are encouraged to help clean this up.  Thanks.)

ADDED   3rd_party/zlib/old/descrip.mms
Index: 3rd_party/zlib/old/descrip.mms
==================================================================
--- 3rd_party/zlib/old/descrip.mms
+++ 3rd_party/zlib/old/descrip.mms
@@ -0,0 +1,48 @@
+# descrip.mms: MMS description file for building zlib on VMS
+# written by Martin P.J. Zinser <m.zinser@gsi.de>
+
+cc_defs =
+c_deb =
+
+.ifdef __DECC__
+pref = /prefix=all
+.endif
+
+OBJS = adler32.obj, compress.obj, crc32.obj, gzio.obj, uncompr.obj,\
+       deflate.obj, trees.obj, zutil.obj, inflate.obj, infblock.obj,\
+       inftrees.obj, infcodes.obj, infutil.obj, inffast.obj
+
+CFLAGS= $(C_DEB) $(CC_DEFS) $(PREF)
+
+all : example.exe minigzip.exe
+        @ write sys$output " Example applications available"
+libz.olb : libz.olb($(OBJS))
+	@ write sys$output " libz available"
+
+example.exe : example.obj libz.olb
+              link example,libz.olb/lib
+
+minigzip.exe : minigzip.obj libz.olb
+              link minigzip,libz.olb/lib,x11vms:xvmsutils.olb/lib
+
+clean :
+	delete *.obj;*,libz.olb;*
+
+
+# Other dependencies.
+adler32.obj : zutil.h zlib.h zconf.h
+compress.obj : zlib.h zconf.h
+crc32.obj : zutil.h zlib.h zconf.h
+deflate.obj : deflate.h zutil.h zlib.h zconf.h
+example.obj : zlib.h zconf.h
+gzio.obj : zutil.h zlib.h zconf.h
+infblock.obj : zutil.h zlib.h zconf.h infblock.h inftrees.h infcodes.h infutil.h
+infcodes.obj : zutil.h zlib.h zconf.h inftrees.h infutil.h infcodes.h inffast.h
+inffast.obj : zutil.h zlib.h zconf.h inftrees.h infutil.h inffast.h
+inflate.obj : zutil.h zlib.h zconf.h infblock.h
+inftrees.obj : zutil.h zlib.h zconf.h inftrees.h
+infutil.obj : zutil.h zlib.h zconf.h inftrees.h infutil.h
+minigzip.obj : zlib.h zconf.h
+trees.obj : deflate.h zutil.h zlib.h zconf.h
+uncompr.obj : zlib.h zconf.h
+zutil.obj : zutil.h zlib.h zconf.h

ADDED   3rd_party/zlib/old/os2/Makefile.os2
Index: 3rd_party/zlib/old/os2/Makefile.os2
==================================================================
--- 3rd_party/zlib/old/os2/Makefile.os2
+++ 3rd_party/zlib/old/os2/Makefile.os2
@@ -0,0 +1,136 @@
+# Makefile for zlib under OS/2 using GCC (PGCC)
+# For conditions of distribution and use, see copyright notice in zlib.h
+
+# To compile and test, type:
+#   cp Makefile.os2 ..
+#   cd ..
+#   make -f Makefile.os2 test
+
+# This makefile will build a static library z.lib, a shared library
+# z.dll and a import library zdll.lib. You can use either z.lib or
+# zdll.lib by specifying either -lz or -lzdll on gcc's command line
+
+CC=gcc -Zomf -s
+
+CFLAGS=-O6 -Wall
+#CFLAGS=-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7
+#CFLAGS=-g -DZLIB_DEBUG
+#CFLAGS=-O3 -Wall -Wwrite-strings -Wpointer-arith -Wconversion \
+#           -Wstrict-prototypes -Wmissing-prototypes
+
+#################### BUG WARNING: #####################
+## infcodes.c hits a bug in pgcc-1.0, so you have to use either
+## -O# where # <= 4 or one of (-fno-ommit-frame-pointer or -fno-force-mem)
+## This bug is reportedly fixed in pgcc >1.0, but this was not tested
+CFLAGS+=-fno-force-mem
+
+LDFLAGS=-s -L. -lzdll -Zcrtdll
+LDSHARED=$(CC) -s -Zomf -Zdll -Zcrtdll
+
+VER=1.1.0
+ZLIB=z.lib
+SHAREDLIB=z.dll
+SHAREDLIBIMP=zdll.lib
+LIBS=$(ZLIB) $(SHAREDLIB) $(SHAREDLIBIMP)
+
+AR=emxomfar cr
+IMPLIB=emximp
+RANLIB=echo
+TAR=tar
+SHELL=bash
+
+prefix=/usr/local
+exec_prefix = $(prefix)
+
+OBJS = adler32.o compress.o crc32.o gzio.o uncompr.o deflate.o trees.o \
+       zutil.o inflate.o infblock.o inftrees.o infcodes.o infutil.o inffast.o
+
+TEST_OBJS = example.o minigzip.o
+
+DISTFILES = README INDEX ChangeLog configure Make*[a-z0-9] *.[ch] descrip.mms \
+  algorithm.txt zlib.3 msdos/Make*[a-z0-9] msdos/zlib.def msdos/zlib.rc \
+  nt/Makefile.nt nt/zlib.dnt  contrib/README.contrib contrib/*.txt \
+  contrib/asm386/*.asm contrib/asm386/*.c \
+  contrib/asm386/*.bat contrib/asm386/zlibvc.d?? contrib/iostream/*.cpp \
+  contrib/iostream/*.h  contrib/iostream2/*.h contrib/iostream2/*.cpp \
+  contrib/untgz/Makefile contrib/untgz/*.c contrib/untgz/*.w32
+
+all: example.exe minigzip.exe
+
+test: all
+	@LD_LIBRARY_PATH=.:$(LD_LIBRARY_PATH) ; export LD_LIBRARY_PATH; \
+	echo hello world | ./minigzip | ./minigzip -d || \
+	  echo '		*** minigzip test FAILED ***' ; \
+	if ./example; then \
+	  echo '		*** zlib test OK ***'; \
+	else \
+	  echo '		*** zlib test FAILED ***'; \
+	fi
+
+$(ZLIB): $(OBJS)
+	$(AR) $@ $(OBJS)
+	-@ ($(RANLIB) $@ || true) >/dev/null 2>&1
+
+$(SHAREDLIB): $(OBJS) os2/z.def
+	$(LDSHARED) -o $@ $^
+
+$(SHAREDLIBIMP): os2/z.def
+	$(IMPLIB) -o $@ $^
+
+example.exe: example.o $(LIBS)
+	$(CC) $(CFLAGS) -o $@ example.o $(LDFLAGS)
+
+minigzip.exe: minigzip.o $(LIBS)
+	$(CC) $(CFLAGS) -o $@ minigzip.o $(LDFLAGS)
+
+clean:
+	rm -f *.o *~ example minigzip libz.a libz.so* foo.gz
+
+distclean:	clean
+
+zip:
+	mv Makefile Makefile~; cp -p Makefile.in Makefile
+	rm -f test.c ztest*.c
+	v=`sed -n -e 's/\.//g' -e '/VERSION "/s/.*"\(.*\)".*/\1/p' < zlib.h`;\
+	zip -ul9 zlib$$v $(DISTFILES)
+	mv Makefile~ Makefile
+
+dist:
+	mv Makefile Makefile~; cp -p Makefile.in Makefile
+	rm -f test.c ztest*.c
+	d=zlib-`sed -n '/VERSION "/s/.*"\(.*\)".*/\1/p' < zlib.h`;\
+	rm -f $$d.tar.gz; \
+	if test ! -d ../$$d; then rm -f ../$$d; ln -s `pwd` ../$$d; fi; \
+	files=""; \
+	for f in $(DISTFILES); do files="$$files $$d/$$f"; done; \
+	cd ..; \
+	GZIP=-9 $(TAR) chofz $$d/$$d.tar.gz $$files; \
+	if test ! -d $$d; then rm -f $$d; fi
+	mv Makefile~ Makefile
+
+tags:
+	etags *.[ch]
+
+depend:
+	makedepend -- $(CFLAGS) -- *.[ch]
+
+# DO NOT DELETE THIS LINE -- make depend depends on it.
+
+adler32.o: zlib.h zconf.h
+compress.o: zlib.h zconf.h
+crc32.o: zlib.h zconf.h
+deflate.o: deflate.h zutil.h zlib.h zconf.h
+example.o: zlib.h zconf.h
+gzio.o: zutil.h zlib.h zconf.h
+infblock.o: infblock.h inftrees.h infcodes.h infutil.h zutil.h zlib.h zconf.h
+infcodes.o: zutil.h zlib.h zconf.h
+infcodes.o: inftrees.h infblock.h infcodes.h infutil.h inffast.h
+inffast.o: zutil.h zlib.h zconf.h inftrees.h
+inffast.o: infblock.h infcodes.h infutil.h inffast.h
+inflate.o: zutil.h zlib.h zconf.h infblock.h
+inftrees.o: zutil.h zlib.h zconf.h inftrees.h
+infutil.o: zutil.h zlib.h zconf.h infblock.h inftrees.h infcodes.h infutil.h
+minigzip.o: zlib.h zconf.h
+trees.o: deflate.h zutil.h zlib.h zconf.h trees.h
+uncompr.o: zlib.h zconf.h
+zutil.o: zutil.h zlib.h zconf.h

ADDED   3rd_party/zlib/old/os2/zlib.def
Index: 3rd_party/zlib/old/os2/zlib.def
==================================================================
--- 3rd_party/zlib/old/os2/zlib.def
+++ 3rd_party/zlib/old/os2/zlib.def
@@ -0,0 +1,51 @@
+;
+; Slightly modified version of ../nt/zlib.dnt :-)
+;
+
+LIBRARY		Z
+DESCRIPTION	"Zlib compression library for OS/2"
+CODE		PRELOAD MOVEABLE DISCARDABLE
+DATA		PRELOAD MOVEABLE MULTIPLE
+
+EXPORTS
+    adler32
+    compress
+    crc32
+    deflate
+    deflateCopy
+    deflateEnd
+    deflateInit2_
+    deflateInit_
+    deflateParams
+    deflateReset
+    deflateSetDictionary
+    gzclose
+    gzdopen
+    gzerror
+    gzflush
+    gzopen
+    gzread
+    gzwrite
+    inflate
+    inflateEnd
+    inflateInit2_
+    inflateInit_
+    inflateReset
+    inflateSetDictionary
+    inflateSync
+    uncompress
+    zlibVersion
+    gzprintf
+    gzputc
+    gzgetc
+    gzseek
+    gzrewind
+    gztell
+    gzeof
+    gzsetparams
+    zError
+    inflateSyncPoint
+    get_crc_table
+    compress2
+    gzputs
+    gzgets

ADDED   3rd_party/zlib/old/visual-basic.txt
Index: 3rd_party/zlib/old/visual-basic.txt
==================================================================
--- 3rd_party/zlib/old/visual-basic.txt
+++ 3rd_party/zlib/old/visual-basic.txt
@@ -0,0 +1,160 @@
+See below some functions declarations for Visual Basic.
+
+Frequently Asked Question:
+
+Q: Each time I use the compress function I get the -5 error (not enough
+   room in the output buffer).
+
+A: Make sure that the length of the compressed buffer is passed by
+   reference ("as any"), not by value ("as long"). Also check that
+   before the call of compress this length is equal to the total size of
+   the compressed buffer and not zero.
+
+
+From: "Jon Caruana" <jon-net@usa.net>
+Subject: Re: How to port zlib declares to vb?
+Date: Mon, 28 Oct 1996 18:33:03 -0600
+
+Got the answer! (I haven't had time to check this but it's what I got, and
+looks correct):
+
+He has the following routines working:
+        compress
+        uncompress
+        gzopen
+        gzwrite
+        gzread
+        gzclose
+
+Declares follow: (Quoted from Carlos Rios <c_rios@sonda.cl>, in Vb4 form)
+
+#If Win16 Then   'Use Win16 calls.
+Declare Function compress Lib "ZLIB.DLL" (ByVal compr As
+        String, comprLen As Any, ByVal buf As String, ByVal buflen
+        As Long) As Integer
+Declare Function uncompress Lib "ZLIB.DLL" (ByVal uncompr
+        As String, uncomprLen As Any, ByVal compr As String, ByVal
+        lcompr As Long) As Integer
+Declare Function gzopen Lib "ZLIB.DLL" (ByVal filePath As
+        String, ByVal mode As String) As Long
+Declare Function gzread Lib "ZLIB.DLL" (ByVal file As
+        Long, ByVal uncompr As String, ByVal uncomprLen As Integer)
+        As Integer
+Declare Function gzwrite Lib "ZLIB.DLL" (ByVal file As
+        Long, ByVal uncompr As String, ByVal uncomprLen As Integer)
+        As Integer
+Declare Function gzclose Lib "ZLIB.DLL" (ByVal file As
+        Long) As Integer
+#Else
+Declare Function compress Lib "ZLIB32.DLL"
+        (ByVal compr As String, comprLen As Any, ByVal buf As
+        String, ByVal buflen As Long) As Integer
+Declare Function uncompress Lib "ZLIB32.DLL"
+        (ByVal uncompr As String, uncomprLen As Any, ByVal compr As
+        String, ByVal lcompr As Long) As Long
+Declare Function gzopen Lib "ZLIB32.DLL"
+        (ByVal file As String, ByVal mode As String) As Long
+Declare Function gzread Lib "ZLIB32.DLL"
+        (ByVal file As Long, ByVal uncompr As String, ByVal
+        uncomprLen As Long) As Long
+Declare Function gzwrite Lib "ZLIB32.DLL"
+        (ByVal file As Long, ByVal uncompr As String, ByVal
+        uncomprLen As Long) As Long
+Declare Function gzclose Lib "ZLIB32.DLL"
+        (ByVal file As Long) As Long
+#End If
+
+-Jon Caruana
+jon-net@usa.net
+Microsoft Sitebuilder Network Level 1 Member - HTML Writer's Guild Member
+
+
+Here is another example from Michael <michael_borgsys@hotmail.com> that he
+says conforms to the VB guidelines, and that solves the problem of not
+knowing the uncompressed size by storing it at the end of the file:
+
+'Calling the functions:
+'bracket meaning: <parameter> [optional] {Range of possible values}
+'Call subCompressFile(<path with filename to compress> [, <path with
+filename to write to>, [level of compression {1..9}]])
+'Call subUncompressFile(<path with filename to compress>)
+
+Option Explicit
+Private lngpvtPcnSml As Long 'Stores value for 'lngPercentSmaller'
+Private Const SUCCESS As Long = 0
+Private Const strFilExt As String = ".cpr"
+Private Declare Function lngfncCpr Lib "zlib.dll" Alias "compress2" (ByRef
+dest As Any, ByRef destLen As Any, ByRef src As Any, ByVal srcLen As Long,
+ByVal level As Integer) As Long
+Private Declare Function lngfncUcp Lib "zlib.dll" Alias "uncompress" (ByRef
+dest As Any, ByRef destLen As Any, ByRef src As Any, ByVal srcLen As Long)
+As Long
+
+Public Sub subCompressFile(ByVal strargOriFilPth As String, Optional ByVal
+strargCprFilPth As String, Optional ByVal intLvl As Integer = 9)
+    Dim strCprPth As String
+    Dim lngOriSiz As Long
+    Dim lngCprSiz As Long
+    Dim bytaryOri() As Byte
+    Dim bytaryCpr() As Byte
+    lngOriSiz = FileLen(strargOriFilPth)
+    ReDim bytaryOri(lngOriSiz - 1)
+    Open strargOriFilPth For Binary Access Read As #1
+        Get #1, , bytaryOri()
+    Close #1
+    strCprPth = IIf(strargCprFilPth = "", strargOriFilPth, strargCprFilPth)
+'Select file path and name
+    strCprPth = strCprPth & IIf(Right(strCprPth, Len(strFilExt)) =
+strFilExt, "", strFilExt) 'Add file extension if not exists
+    lngCprSiz = (lngOriSiz * 1.01) + 12 'Compression needs temporary a bit
+more space then original file size
+    ReDim bytaryCpr(lngCprSiz - 1)
+    If lngfncCpr(bytaryCpr(0), lngCprSiz, bytaryOri(0), lngOriSiz, intLvl) =
+SUCCESS Then
+        lngpvtPcnSml = (1# - (lngCprSiz / lngOriSiz)) * 100
+        ReDim Preserve bytaryCpr(lngCprSiz - 1)
+        Open strCprPth For Binary Access Write As #1
+            Put #1, , bytaryCpr()
+            Put #1, , lngOriSiz 'Add the the original size value to the end
+(last 4 bytes)
+        Close #1
+    Else
+        MsgBox "Compression error"
+    End If
+    Erase bytaryCpr
+    Erase bytaryOri
+End Sub
+
+Public Sub subUncompressFile(ByVal strargFilPth As String)
+    Dim bytaryCpr() As Byte
+    Dim bytaryOri() As Byte
+    Dim lngOriSiz As Long
+    Dim lngCprSiz As Long
+    Dim strOriPth As String
+    lngCprSiz = FileLen(strargFilPth)
+    ReDim bytaryCpr(lngCprSiz - 1)
+    Open strargFilPth For Binary Access Read As #1
+        Get #1, , bytaryCpr()
+    Close #1
+    'Read the original file size value:
+    lngOriSiz = bytaryCpr(lngCprSiz - 1) * (2 ^ 24) _
+              + bytaryCpr(lngCprSiz - 2) * (2 ^ 16) _
+              + bytaryCpr(lngCprSiz - 3) * (2 ^ 8) _
+              + bytaryCpr(lngCprSiz - 4)
+    ReDim Preserve bytaryCpr(lngCprSiz - 5) 'Cut of the original size value
+    ReDim bytaryOri(lngOriSiz - 1)
+    If lngfncUcp(bytaryOri(0), lngOriSiz, bytaryCpr(0), lngCprSiz) = SUCCESS
+Then
+        strOriPth = Left(strargFilPth, Len(strargFilPth) - Len(strFilExt))
+        Open strOriPth For Binary Access Write As #1
+            Put #1, , bytaryOri()
+        Close #1
+    Else
+        MsgBox "Uncompression error"
+    End If
+    Erase bytaryCpr
+    Erase bytaryOri
+End Sub
+Public Property Get lngPercentSmaller() As Long
+    lngPercentSmaller = lngpvtPcnSml
+End Property

ADDED   3rd_party/zlib/os400/README400
Index: 3rd_party/zlib/os400/README400
==================================================================
--- 3rd_party/zlib/os400/README400
+++ 3rd_party/zlib/os400/README400
@@ -0,0 +1,48 @@
+        ZLIB version 1.2.11 for OS/400 installation instructions
+
+1) Download and unpack the zlib tarball to some IFS directory.
+   (i.e.: /path/to/the/zlib/ifs/source/directory)
+
+   If the installed IFS command suppors gzip format, this is straightforward,
+else you have to unpack first to some directory on a system supporting it,
+then move the whole directory to the IFS via the network (via SMB or FTP).
+
+2) Edit the configuration parameters in the compilation script.
+
+        EDTF STMF('/path/to/the/zlib/ifs/source/directory/os400/make.sh')
+
+Tune the parameters according to your needs if not matching the defaults.
+Save the file and exit after edition.
+
+3) Enter qshell, then work in the zlib OS/400 specific directory.
+
+        QSH
+        cd /path/to/the/zlib/ifs/source/directory/os400
+
+4) Compile and install
+
+        sh make.sh
+
+The script will:
+- create the libraries, objects and IFS directories for the zlib environment,
+- compile all modules,
+- create a service program,
+- create a static and a dynamic binding directory,
+- install header files for C/C++ and for ILE/RPG, both for compilation in
+  DB2 and IFS environments.
+
+That's all. 
+
+
+Notes:  For OS/400 ILE RPG programmers, a /copy member defining the ZLIB
+                API prototypes for ILE RPG can be found in ZLIB/H(ZLIB.INC).
+                In the ILE environment, the same definitions are available from
+                file zlib.inc located in the same IFS include directory as the
+                C/C++ header files.
+                Please read comments in this member for more information.
+
+        Remember that most foreign textual data are ASCII coded: this
+                implementation does not handle conversion from/to ASCII, so
+                text data code conversions must be done explicitely.
+
+        Mainly for the reason above, always open zipped files in binary mode.

ADDED   3rd_party/zlib/os400/bndsrc
Index: 3rd_party/zlib/os400/bndsrc
==================================================================
--- 3rd_party/zlib/os400/bndsrc
+++ 3rd_party/zlib/os400/bndsrc
@@ -0,0 +1,119 @@
+STRPGMEXP PGMLVL(*CURRENT) SIGNATURE('ZLIB')
+
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+/*   Version 1.1.3 entry points.                                    */
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+
+  EXPORT SYMBOL("adler32")
+  EXPORT SYMBOL("compress")
+  EXPORT SYMBOL("compress2")
+  EXPORT SYMBOL("crc32")
+  EXPORT SYMBOL("get_crc_table")
+  EXPORT SYMBOL("deflate")
+  EXPORT SYMBOL("deflateEnd")
+  EXPORT SYMBOL("deflateSetDictionary")
+  EXPORT SYMBOL("deflateCopy")
+  EXPORT SYMBOL("deflateReset")
+  EXPORT SYMBOL("deflateParams")
+  EXPORT SYMBOL("deflatePrime")
+  EXPORT SYMBOL("deflateInit_")
+  EXPORT SYMBOL("deflateInit2_")
+  EXPORT SYMBOL("gzopen")
+  EXPORT SYMBOL("gzdopen")
+  EXPORT SYMBOL("gzsetparams")
+  EXPORT SYMBOL("gzread")
+  EXPORT SYMBOL("gzwrite")
+  EXPORT SYMBOL("gzprintf")
+  EXPORT SYMBOL("gzputs")
+  EXPORT SYMBOL("gzgets")
+  EXPORT SYMBOL("gzputc")
+  EXPORT SYMBOL("gzgetc")
+  EXPORT SYMBOL("gzflush")
+  EXPORT SYMBOL("gzseek")
+  EXPORT SYMBOL("gzrewind")
+  EXPORT SYMBOL("gztell")
+  EXPORT SYMBOL("gzeof")
+  EXPORT SYMBOL("gzclose")
+  EXPORT SYMBOL("gzerror")
+  EXPORT SYMBOL("inflate")
+  EXPORT SYMBOL("inflateEnd")
+  EXPORT SYMBOL("inflateSetDictionary")
+  EXPORT SYMBOL("inflateSync")
+  EXPORT SYMBOL("inflateReset")
+  EXPORT SYMBOL("inflateInit_")
+  EXPORT SYMBOL("inflateInit2_")
+  EXPORT SYMBOL("inflateSyncPoint")
+  EXPORT SYMBOL("uncompress")
+  EXPORT SYMBOL("zlibVersion")
+  EXPORT SYMBOL("zError")
+  EXPORT SYMBOL("z_errmsg")
+
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+/*   Version 1.2.1 additional entry points.                         */
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+
+  EXPORT SYMBOL("compressBound")
+  EXPORT SYMBOL("deflateBound")
+  EXPORT SYMBOL("deflatePending")
+  EXPORT SYMBOL("gzungetc")
+  EXPORT SYMBOL("gzclearerr")
+  EXPORT SYMBOL("inflateBack")
+  EXPORT SYMBOL("inflateBackEnd")
+  EXPORT SYMBOL("inflateBackInit_")
+  EXPORT SYMBOL("inflateCopy")
+  EXPORT SYMBOL("zlibCompileFlags")
+
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+/*   Version 1.2.4 additional entry points.                         */
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+
+  EXPORT SYMBOL("adler32_combine")
+  EXPORT SYMBOL("adler32_combine64")
+  EXPORT SYMBOL("crc32_combine")
+  EXPORT SYMBOL("crc32_combine64")
+  EXPORT SYMBOL("deflateSetHeader")
+  EXPORT SYMBOL("deflateTune")
+  EXPORT SYMBOL("gzbuffer")
+  EXPORT SYMBOL("gzclose_r")
+  EXPORT SYMBOL("gzclose_w")
+  EXPORT SYMBOL("gzdirect")
+  EXPORT SYMBOL("gzoffset")
+  EXPORT SYMBOL("gzoffset64")
+  EXPORT SYMBOL("gzopen64")
+  EXPORT SYMBOL("gzseek64")
+  EXPORT SYMBOL("gztell64")
+  EXPORT SYMBOL("inflateGetHeader")
+  EXPORT SYMBOL("inflateMark")
+  EXPORT SYMBOL("inflatePrime")
+  EXPORT SYMBOL("inflateReset2")
+  EXPORT SYMBOL("inflateUndermine")
+
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+/*   Version 1.2.6 additional entry points.                         */
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+
+  EXPORT SYMBOL("deflateResetKeep")
+  EXPORT SYMBOL("gzgetc_")
+  EXPORT SYMBOL("inflateResetKeep")
+
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+/*   Version 1.2.8 additional entry points.                         */
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+
+  EXPORT SYMBOL("gzvprintf")
+  EXPORT SYMBOL("inflateGetDictionary")
+
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+/*   Version 1.2.9 additional entry points.                         */
+/*@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@*/
+
+  EXPORT SYMBOL("adler32_z")
+  EXPORT SYMBOL("crc32_z")
+  EXPORT SYMBOL("deflateGetDictionary")
+  EXPORT SYMBOL("gzfread")
+  EXPORT SYMBOL("gzfwrite")
+  EXPORT SYMBOL("inflateCodesUsed")
+  EXPORT SYMBOL("inflateValidate")
+  EXPORT SYMBOL("uncompress2")
+
+ENDPGMEXP

ADDED   3rd_party/zlib/os400/make.sh
Index: 3rd_party/zlib/os400/make.sh
==================================================================
--- 3rd_party/zlib/os400/make.sh
+++ 3rd_party/zlib/os400/make.sh
@@ -0,0 +1,366 @@
+#!/bin/sh
+#
+#       ZLIB compilation script for the OS/400.
+#
+#
+#       This is a shell script since make is not a standard component of OS/400.
+
+
+################################################################################
+#
+#                       Tunable configuration parameters.
+#
+################################################################################
+
+TARGETLIB='ZLIB'                # Target OS/400 program library
+STATBNDDIR='ZLIB_A'             # Static binding directory.
+DYNBNDDIR='ZLIB'                # Dynamic binding directory.
+SRVPGM="ZLIB"                   # Service program.
+IFSDIR='/zlib'                  # IFS support base directory.
+TGTCCSID='500'                  # Target CCSID of objects
+DEBUG='*NONE'                   # Debug level
+OPTIMIZE='40'                   # Optimisation level
+OUTPUT='*NONE'                  # Compilation output option.
+TGTRLS='V6R1M0'                 # Target OS release
+
+export TARGETLIB STATBNDDIR DYNBNDDIR SRVPGM IFSDIR
+export TGTCCSID DEBUG OPTIMIZE OUTPUT TGTRLS
+
+
+################################################################################
+#
+#                       OS/400 specific definitions.
+#
+################################################################################
+
+LIBIFSNAME="/QSYS.LIB/${TARGETLIB}.LIB"
+
+
+################################################################################
+#
+#                               Procedures.
+#
+################################################################################
+
+#       action_needed dest [src]
+#
+#       dest is an object to build
+#       if specified, src is an object on which dest depends.
+#
+#       exit 0 (succeeds) if some action has to be taken, else 1.
+
+action_needed()
+
+{
+        [ ! -e "${1}" ] && return 0
+        [ "${2}" ] || return 1
+        [ "${1}" -ot "${2}" ] && return 0
+        return 1
+}
+
+
+#       make_module module_name source_name [additional_definitions]
+#
+#       Compile source name into module if needed.
+#       As side effect, append the module name to variable MODULES.
+#       Set LINK to "YES" if the module has been compiled.
+
+make_module()
+
+{
+    MODULES="${MODULES} ${1}"
+    MODIFSNAME="${LIBIFSNAME}/${1}.MODULE"
+    CSRC="`basename \"${2}\"`"
+
+    if action_needed "${MODIFSNAME}" "${2}"
+    then    :
+    elif [ ! "`sed -e \"/<source name=\\\"${CSRC}\\\">/,/<\\\\/source>/!d\" \
+      -e '/<depend /!d'                                                 \
+      -e 's/.* name=\"\\([^\"]*\\)\".*/\\1/' < \"${TOPDIR}/treebuild.xml\" |
+        while read HDR
+        do      if action_needed \"${MODIFSNAME}\" \"${IFSDIR}/include/${HDR}\"
+                then    echo recompile
+                        break
+                fi
+        done`" ]
+    then    return 0
+    fi
+
+    CMD="CRTCMOD MODULE(${TARGETLIB}/${1}) SRCSTMF('${2}')"
+    CMD="${CMD} SYSIFCOPT(*IFS64IO) OPTION(*INCDIRFIRST)"
+    CMD="${CMD} LOCALETYPE(*LOCALE) FLAG(10)"
+    CMD="${CMD} INCDIR('${IFSDIR}/include' ${INCLUDES})"
+    CMD="${CMD} TGTCCSID(${TGTCCSID}) TGTRLS(${TGTRLS})"
+    CMD="${CMD} OUTPUT(${OUTPUT})"
+    CMD="${CMD} OPTIMIZE(${OPTIMIZE})"
+    CMD="${CMD} DBGVIEW(${DEBUG})"
+    system "${CMD}"
+    LINK=YES
+}
+
+
+#       Determine DB2 object name from IFS name.
+
+db2_name()
+
+{
+        basename "${1}"                                                 |
+        tr 'a-z-' 'A-Z_'                                                |
+        sed -e 's/\..*//'                                               \
+            -e 's/^\(.\).*\(.........\)$/\1\2/'
+}
+
+
+#       Force enumeration types to be the same size as integers.
+
+copy_hfile()
+
+{
+        sed -e '1i\
+#pragma enum(int)\
+' "${@}" -e '$a\
+#pragma enum(pop)\
+'
+}
+
+
+################################################################################
+#
+#                             Script initialization.
+#
+################################################################################
+
+SCRIPTDIR=`dirname "${0}"`
+
+case "${SCRIPTDIR}" in
+/*)     ;;
+*)      SCRIPTDIR="`pwd`/${SCRIPTDIR}"
+esac
+
+while true
+do      case "${SCRIPTDIR}" in
+        */.)    SCRIPTDIR="${SCRIPTDIR%/.}";;
+        *)      break;;
+        esac
+done
+
+#  The script directory is supposed to be in ${TOPDIR}/os400.
+
+TOPDIR=`dirname "${SCRIPTDIR}"`
+export SCRIPTDIR TOPDIR
+cd "${TOPDIR}"
+
+
+#  Extract the version from the master compilation XML file.
+
+VERSION=`sed -e '/^<package /!d'                                        \
+            -e 's/^.* version="\([0-9.]*\)".*$/\1/' -e 'q'              \
+            < treebuild.xml`
+export VERSION
+
+################################################################################
+
+
+#       Create the OS/400 library if it does not exist.
+
+if action_needed "${LIBIFSNAME}"
+then    CMD="CRTLIB LIB(${TARGETLIB}) TEXT('ZLIB: Data compression API')"
+        system "${CMD}"
+fi
+
+
+#       Create the DOCS source file if it does not exist.
+
+if action_needed "${LIBIFSNAME}/DOCS.FILE"
+then    CMD="CRTSRCPF FILE(${TARGETLIB}/DOCS) RCDLEN(112)"
+        CMD="${CMD} CCSID(${TGTCCSID}) TEXT('Documentation texts')"
+        system "${CMD}"
+fi
+
+#       Copy some documentation files if needed.
+
+for TEXT in "${TOPDIR}/ChangeLog" "${TOPDIR}/FAQ"                       \
+    "${TOPDIR}/README" "${SCRIPTDIR}/README400"
+do      MEMBER="${LIBIFSNAME}/DOCS.FILE/`db2_name \"${TEXT}\"`.MBR"
+
+        if action_needed "${MEMBER}" "${TEXT}"
+        then    CMD="CPY OBJ('${TEXT}') TOOBJ('${MEMBER}') TOCCSID(${TGTCCSID})"
+                CMD="${CMD} DTAFMT(*TEXT) REPLACE(*YES)"
+                system "${CMD}"
+        fi
+done
+
+
+#       Create the OS/400 source program file for the C header files.
+
+SRCPF="${LIBIFSNAME}/H.FILE"
+
+if action_needed "${SRCPF}"
+then    CMD="CRTSRCPF FILE(${TARGETLIB}/H) RCDLEN(112)"
+        CMD="${CMD} CCSID(${TGTCCSID}) TEXT('ZLIB: C/C++ header files')"
+        system "${CMD}"
+fi
+
+
+#       Create the IFS directory for the C header files.
+
+if action_needed "${IFSDIR}/include"
+then    mkdir -p "${IFSDIR}/include"
+fi
+
+#       Copy the header files to DB2 library. Link from IFS include directory.
+
+for HFILE in "${TOPDIR}/"*.h
+do      DEST="${SRCPF}/`db2_name \"${HFILE}\"`.MBR"
+
+        if action_needed "${DEST}" "${HFILE}"
+        then    copy_hfile < "${HFILE}" > tmphdrfile
+
+                #       Need to translate to target CCSID.
+
+                CMD="CPY OBJ('`pwd`/tmphdrfile') TOOBJ('${DEST}')"
+                CMD="${CMD} TOCCSID(${TGTCCSID}) DTAFMT(*TEXT) REPLACE(*YES)"
+                system "${CMD}"
+                # touch -r "${HFILE}" "${DEST}"
+                rm -f tmphdrfile
+        fi
+
+        IFSFILE="${IFSDIR}/include/`basename \"${HFILE}\"`"
+
+        if action_needed "${IFSFILE}" "${DEST}"
+        then    rm -f "${IFSFILE}"
+                ln -s "${DEST}" "${IFSFILE}"
+        fi
+done
+
+
+#       Install the ILE/RPG header file.
+
+
+HFILE="${SCRIPTDIR}/zlib.inc"
+DEST="${SRCPF}/ZLIB.INC.MBR"
+
+if action_needed "${DEST}" "${HFILE}"
+then    CMD="CPY OBJ('${HFILE}') TOOBJ('${DEST}')"
+        CMD="${CMD} TOCCSID(${TGTCCSID}) DTAFMT(*TEXT) REPLACE(*YES)"
+        system "${CMD}"
+        # touch -r "${HFILE}" "${DEST}"
+fi
+
+IFSFILE="${IFSDIR}/include/`basename \"${HFILE}\"`"
+
+if action_needed "${IFSFILE}" "${DEST}"
+then    rm -f "${IFSFILE}"
+        ln -s "${DEST}" "${IFSFILE}"
+fi
+
+
+#      Create and compile the identification source file.
+
+echo '#pragma comment(user, "ZLIB version '"${VERSION}"'")' > os400.c
+echo '#pragma comment(user, __DATE__)' >> os400.c
+echo '#pragma comment(user, __TIME__)' >> os400.c
+echo '#pragma comment(copyright, "Copyright (C) 1995-2017 Jean-Loup Gailly, Mark Adler. OS/400 version by P. Monnerat.")' >> os400.c
+make_module     OS400           os400.c
+LINK=                           # No need to rebuild service program yet.
+MODULES=
+
+
+#       Get source list.
+
+CSOURCES=`sed -e '/<source name="/!d'                                   \
+    -e 's/.* name="\([^"]*\)".*/\1/' < treebuild.xml`
+
+#       Compile the sources into modules.
+
+for SRC in ${CSOURCES}
+do      MODULE=`db2_name "${SRC}"`
+        make_module "${MODULE}" "${SRC}"
+done
+
+
+#       If needed, (re)create the static binding directory.
+
+if action_needed "${LIBIFSNAME}/${STATBNDDIR}.BNDDIR"
+then    LINK=YES
+fi
+
+if [ "${LINK}" ]
+then    rm -rf "${LIBIFSNAME}/${STATBNDDIR}.BNDDIR"
+        CMD="CRTBNDDIR BNDDIR(${TARGETLIB}/${STATBNDDIR})"
+        CMD="${CMD} TEXT('ZLIB static binding directory')"
+        system "${CMD}"
+
+        for MODULE in ${MODULES}
+        do      CMD="ADDBNDDIRE BNDDIR(${TARGETLIB}/${STATBNDDIR})"
+                CMD="${CMD} OBJ((${TARGETLIB}/${MODULE} *MODULE))"
+                system "${CMD}"
+        done
+fi
+
+
+#       The exportation file for service program creation must be in a DB2
+#               source file, so make sure it exists.
+
+if action_needed "${LIBIFSNAME}/TOOLS.FILE"
+then    CMD="CRTSRCPF FILE(${TARGETLIB}/TOOLS) RCDLEN(112)"
+        CMD="${CMD} CCSID(${TGTCCSID}) TEXT('ZLIB: build tools')"
+        system "${CMD}"
+fi
+
+
+DEST="${LIBIFSNAME}/TOOLS.FILE/BNDSRC.MBR"
+
+if action_needed "${SCRIPTDIR}/bndsrc" "${DEST}"
+then    CMD="CPY OBJ('${SCRIPTDIR}/bndsrc') TOOBJ('${DEST}')"
+        CMD="${CMD} TOCCSID(${TGTCCSID}) DTAFMT(*TEXT) REPLACE(*YES)"
+        system "${CMD}"
+        # touch -r "${SCRIPTDIR}/bndsrc" "${DEST}"
+        LINK=YES
+fi
+
+
+#       Build the service program if needed.
+
+if action_needed "${LIBIFSNAME}/${SRVPGM}.SRVPGM"
+then    LINK=YES
+fi
+
+if [ "${LINK}" ]
+then    CMD="CRTSRVPGM SRVPGM(${TARGETLIB}/${SRVPGM})"
+        CMD="${CMD} SRCFILE(${TARGETLIB}/TOOLS) SRCMBR(BNDSRC)"
+        CMD="${CMD} MODULE(${TARGETLIB}/OS400)"
+        CMD="${CMD} BNDDIR(${TARGETLIB}/${STATBNDDIR})"
+        CMD="${CMD} TEXT('ZLIB ${VERSION} dynamic library')"
+        CMD="${CMD} TGTRLS(${TGTRLS})"
+        system "${CMD}"
+        LINK=YES
+
+        #       Duplicate the service program for a versioned backup.
+
+        BACKUP=`echo "${SRVPGM}${VERSION}"                              |
+                sed -e 's/.*\(..........\)$/\1/' -e 's/\./_/g'`
+        BACKUP="`db2_name \"${BACKUP}\"`"
+        BKUPIFSNAME="${LIBIFSNAME}/${BACKUP}.SRVPGM"
+        rm -f "${BKUPIFSNAME}"
+        CMD="CRTDUPOBJ OBJ(${SRVPGM}) FROMLIB(${TARGETLIB})"
+        CMD="${CMD} OBJTYPE(*SRVPGM) NEWOBJ(${BACKUP})"
+        system "${CMD}"
+fi
+
+
+#       If needed, (re)create the dynamic binding directory.
+
+if action_needed "${LIBIFSNAME}/${DYNBNDDIR}.BNDDIR"
+then    LINK=YES
+fi
+
+if [ "${LINK}" ]
+then    rm -rf "${LIBIFSNAME}/${DYNBNDDIR}.BNDDIR"
+        CMD="CRTBNDDIR BNDDIR(${TARGETLIB}/${DYNBNDDIR})"
+        CMD="${CMD} TEXT('ZLIB dynamic binding directory')"
+        system "${CMD}"
+        CMD="ADDBNDDIRE BNDDIR(${TARGETLIB}/${DYNBNDDIR})"
+        CMD="${CMD} OBJ((*LIBL/${SRVPGM} *SRVPGM))"
+        system "${CMD}"
+fi

ADDED   3rd_party/zlib/os400/zlib.inc
Index: 3rd_party/zlib/os400/zlib.inc
==================================================================
--- 3rd_party/zlib/os400/zlib.inc
+++ 3rd_party/zlib/os400/zlib.inc
@@ -0,0 +1,527 @@
+      *  ZLIB.INC - Interface to the general purpose compression library
+      *
+      *  ILE RPG400 version by Patrick Monnerat, DATASPHERE.
+      *  Version 1.2.11
+      *
+      *
+      *  WARNING:
+      *     Procedures inflateInit(), inflateInit2(), deflateInit(),
+      *         deflateInit2() and inflateBackInit() need to be called with
+      *         two additional arguments:
+      *         the package version string and the stream control structure.
+      *         size. This is needed because RPG lacks some macro feature.
+      *         Call these procedures as:
+      *             inflateInit(...: ZLIB_VERSION: %size(z_stream))
+      *
+      /if not defined(ZLIB_H_)
+      /define ZLIB_H_
+      *
+      **************************************************************************
+      *                               Constants
+      **************************************************************************
+      *
+      *  Versioning information.
+      *
+     D ZLIB_VERSION    C                   '1.2.11'
+     D ZLIB_VERNUM     C                   X'12a0'
+     D ZLIB_VER_MAJOR  C                   1
+     D ZLIB_VER_MINOR  C                   2
+     D ZLIB_VER_REVISION...
+     D                 C                   11
+     D ZLIB_VER_SUBREVISION...
+     D                 C                   0
+      *
+      *  Other equates.
+      *
+     D Z_NO_FLUSH      C                   0
+     D Z_PARTIAL_FLUSH...
+     D                 C                   1
+     D Z_SYNC_FLUSH    C                   2
+     D Z_FULL_FLUSH    C                   3
+     D Z_FINISH        C                   4
+     D Z_BLOCK         C                   5
+     D Z_TREES         C                   6
+      *
+     D Z_OK            C                   0
+     D Z_STREAM_END    C                   1
+     D Z_NEED_DICT     C                   2
+     D Z_ERRNO         C                   -1
+     D Z_STREAM_ERROR  C                   -2
+     D Z_DATA_ERROR    C                   -3
+     D Z_MEM_ERROR     C                   -4
+     D Z_BUF_ERROR     C                   -5
+     D Z_VERSION_ERROR C                   -6
+      *
+     D Z_NO_COMPRESSION...
+     D                 C                   0
+     D Z_BEST_SPEED    C                   1
+     D Z_BEST_COMPRESSION...
+     D                 C                   9
+     D Z_DEFAULT_COMPRESSION...
+     D                 C                   -1
+      *
+     D Z_FILTERED      C                   1
+     D Z_HUFFMAN_ONLY  C                   2
+     D Z_RLE           C                   3
+     D Z_DEFAULT_STRATEGY...
+     D                 C                   0
+      *
+     D Z_BINARY        C                   0
+     D Z_ASCII         C                   1
+     D Z_UNKNOWN       C                   2
+      *
+     D Z_DEFLATED      C                   8
+      *
+     D Z_NULL          C                   0
+      *
+      **************************************************************************
+      *                                 Types
+      **************************************************************************
+      *
+     D z_streamp       S               *                                        Stream struct ptr
+     D gzFile          S               *                                        File pointer
+     D gz_headerp      S               *
+     D z_off_t         S             10i 0                                      Stream offsets
+     D z_off64_t       S             20i 0                                      Stream offsets
+      *
+      **************************************************************************
+      *                               Structures
+      **************************************************************************
+      *
+      *  The GZIP encode/decode stream support structure.
+      *
+     D z_stream        DS                  align based(z_streamp)
+     D  zs_next_in                     *                                        Next input byte
+     D  zs_avail_in                  10U 0                                      Byte cnt at next_in
+     D  zs_total_in                  10U 0                                      Total bytes read
+     D  zs_next_out                    *                                        Output buffer ptr
+     D  zs_avail_out                 10U 0                                      Room left @ next_out
+     D  zs_total_out                 10U 0                                      Total bytes written
+     D  zs_msg                         *                                        Last errmsg or null
+     D  zs_state                       *                                        Internal state
+     D  zs_zalloc                      *   procptr                              Int. state allocator
+     D  zs_free                        *   procptr                              Int. state dealloc.
+     D  zs_opaque                      *                                        Private alloc. data
+     D  zs_data_type                 10i 0                                      ASC/BIN best guess
+     D  zs_adler                     10u 0                                      Uncompr. adler32 val
+     D                               10U 0                                      Reserved
+     D                               10U 0                                      Ptr. alignment
+      *
+      **************************************************************************
+      *                     Utility function prototypes
+      **************************************************************************
+      *
+     D compress        PR            10I 0 extproc('compress')
+     D  dest                      65535    options(*varsize)                    Destination buffer
+     D  destLen                      10U 0                                      Destination length
+     D  source                    65535    const options(*varsize)              Source buffer
+     D  sourceLen                    10u 0 value                                Source length
+      *
+     D compress2       PR            10I 0 extproc('compress2')
+     D  dest                      65535    options(*varsize)                    Destination buffer
+     D  destLen                      10U 0                                      Destination length
+     D  source                    65535    const options(*varsize)              Source buffer
+     D  sourceLen                    10U 0 value                                Source length
+     D  level                        10I 0 value                                Compression level
+      *
+     D compressBound   PR            10U 0 extproc('compressBound')
+     D  sourceLen                    10U 0 value
+      *
+     D uncompress      PR            10I 0 extproc('uncompress')
+     D  dest                      65535    options(*varsize)                    Destination buffer
+     D  destLen                      10U 0                                      Destination length
+     D  source                    65535    const options(*varsize)              Source buffer
+     D  sourceLen                    10U 0 value                                Source length
+      *
+     D uncompress2     PR            10I 0 extproc('uncompress2')
+     D  dest                      65535    options(*varsize)                    Destination buffer
+     D  destLen                      10U 0                                      Destination length
+     D  source                    65535    const options(*varsize)              Source buffer
+     D  sourceLen                    10U 0                                      Source length
+      *
+      /if not defined(LARGE_FILES)
+     D gzopen          PR                  extproc('gzopen')
+     D                                     like(gzFile)
+     D  path                           *   value options(*string)               File pathname
+     D  mode                           *   value options(*string)               Open mode
+      /else
+     D gzopen          PR                  extproc('gzopen64')
+     D                                     like(gzFile)
+     D  path                           *   value options(*string)               File pathname
+     D  mode                           *   value options(*string)               Open mode
+      *
+     D gzopen64        PR                  extproc('gzopen64')
+     D                                     like(gzFile)
+     D  path                           *   value options(*string)               File pathname
+     D  mode                           *   value options(*string)               Open mode
+      /endif
+      *
+     D gzdopen         PR                  extproc('gzdopen')
+     D                                     like(gzFile)
+     D  fd                           10I 0 value                                File descriptor
+     D  mode                           *   value options(*string)               Open mode
+      *
+     D gzbuffer        PR            10I 0 extproc('gzbuffer')
+     D  file                               value like(gzFile)                   File pointer
+     D  size                         10U 0 value
+      *
+     D gzsetparams     PR            10I 0 extproc('gzsetparams')
+     D  file                               value like(gzFile)                   File pointer
+     D  level                        10I 0 value
+     D  strategy                     10I 0 value
+      *
+     D gzread          PR            10I 0 extproc('gzread')
+     D  file                               value like(gzFile)                   File pointer
+     D  buf                       65535    options(*varsize)                    Buffer
+     D  len                          10u 0 value                                Buffer length
+      *
+     D gzfread          PR           20I 0 extproc('gzfread')
+     D  buf                       65535    options(*varsize)                    Buffer
+     D  size                         20u 0 value                                Buffer length
+     D  nitems                       20u 0 value                                Buffer length
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzwrite         PR            10I 0 extproc('gzwrite')
+     D  file                               value like(gzFile)                   File pointer
+     D  buf                       65535    const options(*varsize)              Buffer
+     D  len                          10u 0 value                                Buffer length
+      *
+     D gzfwrite         PR           20I 0 extproc('gzfwrite')
+     D  buf                       65535    options(*varsize)                    Buffer
+     D  size                         20u 0 value                                Buffer length
+     D  nitems                       20u 0 value                                Buffer length
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzputs          PR            10I 0 extproc('gzputs')
+     D  file                               value like(gzFile)                   File pointer
+     D  s                              *   value options(*string)               String to output
+      *
+     D gzgets          PR              *   extproc('gzgets')
+     D  file                               value like(gzFile)                   File pointer
+     D  buf                       65535    options(*varsize)                    Read buffer
+     D  len                          10i 0 value                                Buffer length
+      *
+     D gzputc          PR            10i 0 extproc('gzputc')
+     D  file                               value like(gzFile)                   File pointer
+     D  c                            10I 0 value                                Character to write
+      *
+     D gzgetc          PR            10i 0 extproc('gzgetc')
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzgetc_         PR            10i 0 extproc('gzgetc_')
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzungetc        PR            10i 0 extproc('gzungetc')
+     D  c                            10I 0 value                                Character to push
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzflush         PR            10i 0 extproc('gzflush')
+     D  file                               value like(gzFile)                   File pointer
+     D  flush                        10I 0 value                                Type of flush
+      *
+      /if not defined(LARGE_FILES)
+     D gzseek          PR                  extproc('gzseek')
+     D                                     like(z_off_t)
+     D  file                               value like(gzFile)                   File pointer
+     D  offset                             value like(z_off_t)                  Offset
+     D  whence                       10i 0 value                                Origin
+      /else
+     D gzseek          PR                  extproc('gzseek64')
+     D                                     like(z_off_t)
+     D  file                               value like(gzFile)                   File pointer
+     D  offset                             value like(z_off_t)                  Offset
+     D  whence                       10i 0 value                                Origin
+      *
+     D gzseek64        PR                  extproc('gzseek64')
+     D                                     like(z_off64_t)
+     D  file                               value like(gzFile)                   File pointer
+     D  offset                             value like(z_off64_t)                Offset
+     D  whence                       10i 0 value                                Origin
+      /endif
+      *
+     D gzrewind        PR            10i 0 extproc('gzrewind')
+     D  file                               value like(gzFile)                   File pointer
+      *
+      /if not defined(LARGE_FILES)
+     D gztell          PR                  extproc('gztell')
+     D                                     like(z_off_t)
+     D  file                               value like(gzFile)                   File pointer
+      /else
+     D gztell          PR                  extproc('gztell64')
+     D                                     like(z_off_t)
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gztell64        PR                  extproc('gztell64')
+     D                                     like(z_off64_t)
+     D  file                               value like(gzFile)                   File pointer
+      /endif
+      *
+      /if not defined(LARGE_FILES)
+     D gzoffset        PR                  extproc('gzoffset')
+     D                                     like(z_off_t)
+     D  file                               value like(gzFile)                   File pointer
+      /else
+     D gzoffset        PR                  extproc('gzoffset64')
+     D                                     like(z_off_t)
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzoffset64      PR                  extproc('gzoffset64')
+     D                                     like(z_off64_t)
+     D  file                               value like(gzFile)                   File pointer
+      /endif
+      *
+     D gzeof           PR            10i 0 extproc('gzeof')
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzdirect        PR            10i 0 extproc('gzdirect')
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzclose_r       PR            10i 0 extproc('gzclose_r')
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzclose_w       PR            10i 0 extproc('gzclose_w')
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzclose         PR            10i 0 extproc('gzclose')
+     D  file                               value like(gzFile)                   File pointer
+      *
+     D gzerror         PR              *   extproc('gzerror')                   Error string
+     D  file                               value like(gzFile)                   File pointer
+     D  errnum                       10I 0                                      Error code
+      *
+     D gzclearerr      PR                  extproc('gzclearerr')
+     D  file                               value like(gzFile)                   File pointer
+      *
+      **************************************************************************
+      *                        Basic function prototypes
+      **************************************************************************
+      *
+     D zlibVersion     PR              *   extproc('zlibVersion')               Version string
+      *
+     D deflateInit     PR            10I 0 extproc('deflateInit_')              Init. compression
+     D  strm                               like(z_stream)                       Compression stream
+     D  level                        10I 0 value                                Compression level
+     D  version                        *   value options(*string)               Version string
+     D  stream_size                  10i 0 value                                Stream struct. size
+      *
+     D deflate         PR            10I 0 extproc('deflate')                   Compress data
+     D  strm                               like(z_stream)                       Compression stream
+     D  flush                        10I 0 value                                Flush type required
+      *
+     D deflateEnd      PR            10I 0 extproc('deflateEnd')                Termin. compression
+     D  strm                               like(z_stream)                       Compression stream
+      *
+     D inflateInit     PR            10I 0 extproc('inflateInit_')              Init. expansion
+     D  strm                               like(z_stream)                       Expansion stream
+     D  version                        *   value options(*string)               Version string
+     D  stream_size                  10i 0 value                                Stream struct. size
+      *
+     D inflate         PR            10I 0 extproc('inflate')                   Expand data
+     D  strm                               like(z_stream)                       Expansion stream
+     D  flush                        10I 0 value                                Flush type required
+      *
+     D inflateEnd      PR            10I 0 extproc('inflateEnd')                Termin. expansion
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+      **************************************************************************
+      *                        Advanced function prototypes
+      **************************************************************************
+      *
+     D deflateInit2    PR            10I 0 extproc('deflateInit2_')             Init. compression
+     D  strm                               like(z_stream)                       Compression stream
+     D  level                        10I 0 value                                Compression level
+     D  method                       10I 0 value                                Compression method
+     D  windowBits                   10I 0 value                                log2(window size)
+     D  memLevel                     10I 0 value                                Mem/cmpress tradeoff
+     D  strategy                     10I 0 value                                Compression strategy
+     D  version                        *   value options(*string)               Version string
+     D  stream_size                  10i 0 value                                Stream struct. size
+      *
+     D deflateSetDictionary...
+     D                 PR            10I 0 extproc('deflateSetDictionary')      Init. dictionary
+     D  strm                               like(z_stream)                       Compression stream
+     D  dictionary                65535    const options(*varsize)              Dictionary bytes
+     D  dictLength                   10U 0 value                                Dictionary length
+      *
+     D deflateCopy     PR            10I 0 extproc('deflateCopy')               Compress strm 2 strm
+     D  dest                               like(z_stream)                       Destination stream
+     D  source                             like(z_stream)                       Source stream
+      *
+     D deflateReset    PR            10I 0 extproc('deflateReset')              End and init. stream
+     D  strm                               like(z_stream)                       Compression stream
+      *
+     D deflateParams   PR            10I 0 extproc('deflateParams')             Change level & strat
+     D  strm                               like(z_stream)                       Compression stream
+     D  level                        10I 0 value                                Compression level
+     D  strategy                     10I 0 value                                Compression strategy
+      *
+     D deflateTune     PR            10I 0 extproc('deflateTune')
+     D  strm                               like(z_stream)                       Compression stream
+     D  good                         10I 0 value
+     D  lazy                         10I 0 value
+     D  nice                         10I 0 value
+     D  chain                        10I 0 value
+      *
+     D deflateBound    PR            10U 0 extproc('deflateBound')              Change level & strat
+     D  strm                               like(z_stream)                       Compression stream
+     D  sourcelen                    10U 0 value                                Compression level
+      *
+     D deflatePending  PR            10I 0 extproc('deflatePending')            Change level & strat
+     D  strm                               like(z_stream)                       Compression stream
+     D  pending                      10U 0                                      Pending bytes
+     D  bits                         10I 0                                      Pending bits
+      *
+     D deflatePrime    PR            10I 0 extproc('deflatePrime')              Change level & strat
+     D  strm                               like(z_stream)                       Compression stream
+     D  bits                         10I 0 value                                # of bits to insert
+     D  value                        10I 0 value                                Bits to insert
+      *
+     D inflateInit2    PR            10I 0 extproc('inflateInit2_')             Init. expansion
+     D  strm                               like(z_stream)                       Expansion stream
+     D  windowBits                   10I 0 value                                log2(window size)
+     D  version                        *   value options(*string)               Version string
+     D  stream_size                  10i 0 value                                Stream struct. size
+      *
+     D inflateSetDictionary...
+     D                 PR            10I 0 extproc('inflateSetDictionary')      Init. dictionary
+     D  strm                               like(z_stream)                       Expansion stream
+     D  dictionary                65535    const options(*varsize)              Dictionary bytes
+     D  dictLength                   10U 0 value                                Dictionary length
+      *
+     D inflateGetDictionary...
+     D                 PR            10I 0 extproc('inflateGetDictionary')      Get dictionary
+     D  strm                               like(z_stream)                       Expansion stream
+     D  dictionary                65535    options(*varsize)                    Dictionary bytes
+     D  dictLength                   10U 0                                      Dictionary length
+      *
+     D deflateGetDictionary...
+     D                 PR            10I 0 extproc('deflateGetDictionary')      Get dictionary
+     D  strm                               like(z_stream)                       Expansion stream
+     D  dictionary                65535    options(*varsize)                    Dictionary bytes
+     D  dictLength                   10U 0                                      Dictionary length
+      *
+     D inflateSync     PR            10I 0 extproc('inflateSync')               Sync. expansion
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+     D inflateCopy     PR            10I 0 extproc('inflateCopy')
+     D  dest                               like(z_stream)                       Destination stream
+     D  source                             like(z_stream)                       Source stream
+      *
+     D inflateReset    PR            10I 0 extproc('inflateReset')              End and init. stream
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+     D inflateReset2   PR            10I 0 extproc('inflateReset2')             End and init. stream
+     D  strm                               like(z_stream)                       Expansion stream
+     D  windowBits                   10I 0 value                                Log2(buffer size)
+      *
+     D inflatePrime    PR            10I 0 extproc('inflatePrime')              Insert bits
+     D  strm                               like(z_stream)                       Expansion stream
+     D  bits                         10I 0 value                                Bit count
+     D  value                        10I 0 value                                Bits to insert
+      *
+     D inflateMark     PR            10I 0 extproc('inflateMark')               Get inflate info
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+     D inflateCodesUsed...
+                       PR            20U 0 extproc('inflateCodesUsed')
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+     D inflateValidate...
+                       PR            20U 0 extproc('inflateValidate')
+     D  strm                               like(z_stream)                       Expansion stream
+     D  check                        10I 0 value
+      *
+     D inflateGetHeader...
+                       PR            10U 0 extproc('inflateGetHeader')
+     D  strm                               like(z_stream)                       Expansion stream
+     D  head                               like(gz_headerp)
+      *
+     D deflateSetHeader...
+                       PR            10U 0 extproc('deflateSetHeader')
+     D  strm                               like(z_stream)                       Expansion stream
+     D  head                               like(gz_headerp)
+      *
+     D inflateBackInit...
+     D                 PR            10I 0 extproc('inflateBackInit_')
+     D  strm                               like(z_stream)                       Expansion stream
+     D  windowBits                   10I 0 value                                Log2(buffer size)
+     D  window                    65535    options(*varsize)                    Buffer
+     D  version                        *   value options(*string)               Version string
+     D  stream_size                  10i 0 value                                Stream struct. size
+      *
+     D inflateBack     PR            10I 0 extproc('inflateBack')
+     D  strm                               like(z_stream)                       Expansion stream
+     D  in                             *   value procptr                        Input function
+     D  in_desc                        *   value                                Input descriptor
+     D  out                            *   value procptr                        Output function
+     D  out_desc                       *   value                                Output descriptor
+      *
+     D inflateBackEnd  PR            10I 0 extproc('inflateBackEnd')
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+     D zlibCompileFlags...
+     D                 PR            10U 0 extproc('zlibCompileFlags')
+      *
+      **************************************************************************
+      *                        Checksum function prototypes
+      **************************************************************************
+      *
+     D adler32         PR            10U 0 extproc('adler32')                   New checksum
+     D  adler                        10U 0 value                                Old checksum
+     D  buf                       65535    const options(*varsize)              Bytes to accumulate
+     D  len                          10U 0 value                                Buffer length
+      *
+     D adler32_combine...
+                       PR            10U 0 extproc('adler32_combine')           New checksum
+     D  adler1                       10U 0 value                                Old checksum
+     D  adler2                       10U 0 value                                Old checksum
+     D  len2                         20U 0 value                                Buffer length
+      *
+     D adler32_z       PR            10U 0 extproc('adler32_z')                 New checksum
+     D  adler                        10U 0 value                                Old checksum
+     D  buf                       65535    const options(*varsize)              Bytes to accumulate
+     D  len                          20U 0 value                                Buffer length
+      *
+     D crc32           PR            10U 0 extproc('crc32')                     New checksum
+     D  crc                          10U 0 value                                Old checksum
+     D  buf                       65535    const options(*varsize)              Bytes to accumulate
+     D  len                          10U 0 value                                Buffer length
+      *
+     D crc32_combine...
+                       PR            10U 0 extproc('crc32_combine')             New checksum
+     D  crc1                         10U 0 value                                Old checksum
+     D  crc2                         10U 0 value                                Old checksum
+     D  len2                         20U 0 value                                Buffer length
+      *
+     D crc32_z         PR            10U 0 extproc('crc32_z')                   New checksum
+     D  crc                          10U 0 value                                Old checksum
+     D  buf                       65535    const options(*varsize)              Bytes to accumulate
+     D  len                          20U 0 value                                Buffer length
+      *
+      **************************************************************************
+      *                     Miscellaneous function prototypes
+      **************************************************************************
+      *
+     D zError          PR              *   extproc('zError')                    Error string
+     D  err                          10I 0 value                                Error code
+      *
+     D inflateSyncPoint...
+     D                 PR            10I 0 extproc('inflateSyncPoint')
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+     D get_crc_table   PR              *   extproc('get_crc_table')             Ptr to ulongs
+      *
+     D inflateUndermine...
+     D                 PR            10I 0 extproc('inflateUndermine')
+     D  strm                               like(z_stream)                       Expansion stream
+     D  arg                          10I 0 value                                Error code
+      *
+     D inflateResetKeep...
+     D                 PR            10I 0 extproc('inflateResetKeep')          End and init. stream
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+     D deflateResetKeep...
+     D                 PR            10I 0 extproc('deflateResetKeep')          End and init. stream
+     D  strm                               like(z_stream)                       Expansion stream
+      *
+      /endif

ADDED   3rd_party/zlib/qnx/package.qpg
Index: 3rd_party/zlib/qnx/package.qpg
==================================================================
--- 3rd_party/zlib/qnx/package.qpg
+++ 3rd_party/zlib/qnx/package.qpg
@@ -0,0 +1,141 @@
+<QPG:Generation>
+   <QPG:Options>
+      <QPG:User unattended="no" verbosity="2" listfiles="yes"/>
+      <QPG:Defaults type="qnx_package"/>
+      <QPG:Source></QPG:Source>
+      <QPG:Release number="+"/>
+      <QPG:Build></QPG:Build>
+      <QPG:FileSorting strip="yes"/>
+      <QPG:Package targets="combine"/>
+      <QPG:Repository generate="yes"/>
+      <QPG:FinalDir></QPG:FinalDir>
+      <QPG:Cleanup></QPG:Cleanup>
+   </QPG:Options>
+
+   <QPG:Responsible>
+      <QPG:Company></QPG:Company>
+      <QPG:Department></QPG:Department>
+      <QPG:Group></QPG:Group>
+      <QPG:Team></QPG:Team>
+      <QPG:Employee></QPG:Employee>
+      <QPG:EmailAddress></QPG:EmailAddress>
+   </QPG:Responsible>
+
+   <QPG:Values>
+      <QPG:Files>
+         <QPG:Add file="../zconf.h" install="/opt/include/" user="root:sys" permission="644"/>
+         <QPG:Add file="../zlib.h" install="/opt/include/" user="root:sys" permission="644"/>
+         <QPG:Add file="../libz.so.1.2.11" install="/opt/lib/" user="root:bin" permission="644"/>
+         <QPG:Add file="libz.so" install="/opt/lib/" component="dev" filetype="symlink" linkto="libz.so.1.2.11"/>
+         <QPG:Add file="libz.so.1" install="/opt/lib/" filetype="symlink" linkto="libz.so.1.2.11"/>
+         <QPG:Add file="../libz.so.1.2.11" install="/opt/lib/" component="slib"/>
+      </QPG:Files>
+
+      <QPG:PackageFilter>
+         <QPM:PackageManifest>
+            <QPM:PackageDescription>
+               <QPM:PackageType>Library</QPM:PackageType>
+               <QPM:PackageReleaseNotes></QPM:PackageReleaseNotes>
+               <QPM:PackageReleaseUrgency>Medium</QPM:PackageReleaseUrgency>
+               <QPM:PackageRepository></QPM:PackageRepository>
+               <QPM:FileVersion>2.0</QPM:FileVersion>
+            </QPM:PackageDescription>
+
+            <QPM:ProductDescription>
+               <QPM:ProductName>zlib</QPM:ProductName>
+               <QPM:ProductIdentifier>zlib</QPM:ProductIdentifier>
+               <QPM:ProductEmail>alain.bonnefoy@icbt.com</QPM:ProductEmail>
+               <QPM:VendorName>Public</QPM:VendorName>
+               <QPM:VendorInstallName>public</QPM:VendorInstallName>
+               <QPM:VendorURL>www.gzip.org/zlib</QPM:VendorURL>
+               <QPM:VendorEmbedURL></QPM:VendorEmbedURL>
+               <QPM:VendorEmail></QPM:VendorEmail>
+               <QPM:AuthorName>Jean-Loup Gailly,Mark Adler</QPM:AuthorName>
+               <QPM:AuthorURL>www.gzip.org/zlib</QPM:AuthorURL>
+               <QPM:AuthorEmbedURL></QPM:AuthorEmbedURL>
+               <QPM:AuthorEmail>zlib@gzip.org</QPM:AuthorEmail>
+               <QPM:ProductIconSmall></QPM:ProductIconSmall>
+               <QPM:ProductIconLarge></QPM:ProductIconLarge>
+               <QPM:ProductDescriptionShort>A massively spiffy yet delicately unobtrusive compression library.</QPM:ProductDescriptionShort>
+               <QPM:ProductDescriptionLong>zlib is designed to be a free, general-purpose, legally unencumbered, lossless data compression library for use on virtually any computer hardware and operating system.</QPM:ProductDescriptionLong>
+               <QPM:ProductDescriptionURL>http://www.gzip.org/zlib</QPM:ProductDescriptionURL>
+               <QPM:ProductDescriptionEmbedURL></QPM:ProductDescriptionEmbedURL>
+            </QPM:ProductDescription>
+
+            <QPM:ReleaseDescription>
+               <QPM:ReleaseVersion>1.2.11</QPM:ReleaseVersion>
+               <QPM:ReleaseUrgency>Medium</QPM:ReleaseUrgency>
+               <QPM:ReleaseStability>Stable</QPM:ReleaseStability>
+               <QPM:ReleaseNoteMinor></QPM:ReleaseNoteMinor>
+               <QPM:ReleaseNoteMajor></QPM:ReleaseNoteMajor>
+               <QPM:ExcludeCountries>
+                  <QPM:Country></QPM:Country>
+               </QPM:ExcludeCountries>
+
+               <QPM:ReleaseCopyright>No License</QPM:ReleaseCopyright>
+            </QPM:ReleaseDescription>
+
+            <QPM:ContentDescription>
+               <QPM:ContentTopic xmlmultiple="true">Software Development/Libraries and Extensions/C Libraries</QPM:ContentTopic>
+               <QPM:ContentKeyword>zlib,compression</QPM:ContentKeyword>
+               <QPM:TargetOS>qnx6</QPM:TargetOS>
+               <QPM:HostOS>qnx6</QPM:HostOS>
+               <QPM:DisplayEnvironment xmlmultiple="true">None</QPM:DisplayEnvironment>
+               <QPM:TargetAudience xmlmultiple="true">Developer</QPM:TargetAudience>
+            </QPM:ContentDescription>
+         </QPM:PackageManifest>
+      </QPG:PackageFilter>
+
+      <QPG:PackageFilter proc="none" target="none">
+         <QPM:PackageManifest>
+            <QPM:ProductInstallationDependencies>
+               <QPM:ProductRequirements></QPM:ProductRequirements>
+            </QPM:ProductInstallationDependencies>
+
+            <QPM:ProductInstallationProcedure>
+               <QPM:Script xmlmultiple="true">
+                  <QPM:ScriptName></QPM:ScriptName>
+                  <QPM:ScriptType>Install</QPM:ScriptType>
+                  <QPM:ScriptTiming>Post</QPM:ScriptTiming>
+                  <QPM:ScriptBlocking>No</QPM:ScriptBlocking>
+                  <QPM:ScriptResult>Ignore</QPM:ScriptResult>
+                  <QPM:ShortDescription></QPM:ShortDescription>
+                  <QPM:UseBinaries>No</QPM:UseBinaries>
+                  <QPM:Priority>Optional</QPM:Priority>
+               </QPM:Script>
+            </QPM:ProductInstallationProcedure>
+         </QPM:PackageManifest>
+
+         <QPM:Launch>
+         </QPM:Launch>
+      </QPG:PackageFilter>
+
+      <QPG:PackageFilter type="core" component="none">
+         <QPM:PackageManifest>
+            <QPM:ProductInstallationProcedure>
+	       <QPM:OrderDependency xmlmultiple="true">
+	          <QPM:Order>InstallOver</QPM:Order>
+	          <QPM:Product>zlib</QPM:Product>
+	       </QPM:OrderDependency>
+            </QPM:ProductInstallationProcedure>
+         </QPM:PackageManifest>
+
+         <QPM:Launch>
+         </QPM:Launch>
+      </QPG:PackageFilter>
+
+      <QPG:PackageFilter type="core" component="dev">
+         <QPM:PackageManifest>
+            <QPM:ProductInstallationProcedure>
+	       <QPM:OrderDependency xmlmultiple="true">
+	          <QPM:Order>InstallOver</QPM:Order>
+	          <QPM:Product>zlib-dev</QPM:Product>
+	       </QPM:OrderDependency>
+            </QPM:ProductInstallationProcedure>
+         </QPM:PackageManifest>
+
+         <QPM:Launch>
+         </QPM:Launch>
+      </QPG:PackageFilter>
+   </QPG:Values>
+</QPG:Generation>

ADDED   3rd_party/zlib/test/example.c
Index: 3rd_party/zlib/test/example.c
==================================================================
--- 3rd_party/zlib/test/example.c
+++ 3rd_party/zlib/test/example.c
@@ -0,0 +1,602 @@
+/* example.c -- usage example of the zlib compression library
+ * Copyright (C) 1995-2006, 2011, 2016 Jean-loup Gailly
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* @(#) $Id$ */
+
+#include "zlib.h"
+#include <stdio.h>
+
+#ifdef STDC
+#  include <string.h>
+#  include <stdlib.h>
+#endif
+
+#if defined(VMS) || defined(RISCOS)
+#  define TESTFILE "foo-gz"
+#else
+#  define TESTFILE "foo.gz"
+#endif
+
+#define CHECK_ERR(err, msg) { \
+    if (err != Z_OK) { \
+        fprintf(stderr, "%s error: %d\n", msg, err); \
+        exit(1); \
+    } \
+}
+
+static z_const char hello[] = "hello, hello!";
+/* "hello world" would be more standard, but the repeated "hello"
+ * stresses the compression code better, sorry...
+ */
+
+static const char dictionary[] = "hello";
+static uLong dictId;    /* Adler32 value of the dictionary */
+
+void test_deflate       OF((Byte *compr, uLong comprLen));
+void test_inflate       OF((Byte *compr, uLong comprLen,
+                            Byte *uncompr, uLong uncomprLen));
+void test_large_deflate OF((Byte *compr, uLong comprLen,
+                            Byte *uncompr, uLong uncomprLen));
+void test_large_inflate OF((Byte *compr, uLong comprLen,
+                            Byte *uncompr, uLong uncomprLen));
+void test_flush         OF((Byte *compr, uLong *comprLen));
+void test_sync          OF((Byte *compr, uLong comprLen,
+                            Byte *uncompr, uLong uncomprLen));
+void test_dict_deflate  OF((Byte *compr, uLong comprLen));
+void test_dict_inflate  OF((Byte *compr, uLong comprLen,
+                            Byte *uncompr, uLong uncomprLen));
+int  main               OF((int argc, char *argv[]));
+
+
+#ifdef Z_SOLO
+
+void *myalloc OF((void *, unsigned, unsigned));
+void myfree OF((void *, void *));
+
+void *myalloc(q, n, m)
+    void *q;
+    unsigned n, m;
+{
+    (void)q;
+    return calloc(n, m);
+}
+
+void myfree(void *q, void *p)
+{
+    (void)q;
+    free(p);
+}
+
+static alloc_func zalloc = myalloc;
+static free_func zfree = myfree;
+
+#else /* !Z_SOLO */
+
+static alloc_func zalloc = (alloc_func)0;
+static free_func zfree = (free_func)0;
+
+void test_compress      OF((Byte *compr, uLong comprLen,
+                            Byte *uncompr, uLong uncomprLen));
+void test_gzio          OF((const char *fname,
+                            Byte *uncompr, uLong uncomprLen));
+
+/* ===========================================================================
+ * Test compress() and uncompress()
+ */
+void test_compress(compr, comprLen, uncompr, uncomprLen)
+    Byte *compr, *uncompr;
+    uLong comprLen, uncomprLen;
+{
+    int err;
+    uLong len = (uLong)strlen(hello)+1;
+
+    err = compress(compr, &comprLen, (const Bytef*)hello, len);
+    CHECK_ERR(err, "compress");
+
+    strcpy((char*)uncompr, "garbage");
+
+    err = uncompress(uncompr, &uncomprLen, compr, comprLen);
+    CHECK_ERR(err, "uncompress");
+
+    if (strcmp((char*)uncompr, hello)) {
+        fprintf(stderr, "bad uncompress\n");
+        exit(1);
+    } else {
+        printf("uncompress(): %s\n", (char *)uncompr);
+    }
+}
+
+/* ===========================================================================
+ * Test read/write of .gz files
+ */
+void test_gzio(fname, uncompr, uncomprLen)
+    const char *fname; /* compressed file name */
+    Byte *uncompr;
+    uLong uncomprLen;
+{
+#ifdef NO_GZCOMPRESS
+    fprintf(stderr, "NO_GZCOMPRESS -- gz* functions cannot compress\n");
+#else
+    int err;
+    int len = (int)strlen(hello)+1;
+    gzFile file;
+    z_off_t pos;
+
+    file = gzopen(fname, "wb");
+    if (file == NULL) {
+        fprintf(stderr, "gzopen error\n");
+        exit(1);
+    }
+    gzputc(file, 'h');
+    if (gzputs(file, "ello") != 4) {
+        fprintf(stderr, "gzputs err: %s\n", gzerror(file, &err));
+        exit(1);
+    }
+    if (gzprintf(file, ", %s!", "hello") != 8) {
+        fprintf(stderr, "gzprintf err: %s\n", gzerror(file, &err));
+        exit(1);
+    }
+    gzseek(file, 1L, SEEK_CUR); /* add one zero byte */
+    gzclose(file);
+
+    file = gzopen(fname, "rb");
+    if (file == NULL) {
+        fprintf(stderr, "gzopen error\n");
+        exit(1);
+    }
+    strcpy((char*)uncompr, "garbage");
+
+    if (gzread(file, uncompr, (unsigned)uncomprLen) != len) {
+        fprintf(stderr, "gzread err: %s\n", gzerror(file, &err));
+        exit(1);
+    }
+    if (strcmp((char*)uncompr, hello)) {
+        fprintf(stderr, "bad gzread: %s\n", (char*)uncompr);
+        exit(1);
+    } else {
+        printf("gzread(): %s\n", (char*)uncompr);
+    }
+
+    pos = gzseek(file, -8L, SEEK_CUR);
+    if (pos != 6 || gztell(file) != pos) {
+        fprintf(stderr, "gzseek error, pos=%ld, gztell=%ld\n",
+                (long)pos, (long)gztell(file));
+        exit(1);
+    }
+
+    if (gzgetc(file) != ' ') {
+        fprintf(stderr, "gzgetc error\n");
+        exit(1);
+    }
+
+    if (gzungetc(' ', file) != ' ') {
+        fprintf(stderr, "gzungetc error\n");
+        exit(1);
+    }
+
+    gzgets(file, (char*)uncompr, (int)uncomprLen);
+    if (strlen((char*)uncompr) != 7) { /* " hello!" */
+        fprintf(stderr, "gzgets err after gzseek: %s\n", gzerror(file, &err));
+        exit(1);
+    }
+    if (strcmp((char*)uncompr, hello + 6)) {
+        fprintf(stderr, "bad gzgets after gzseek\n");
+        exit(1);
+    } else {
+        printf("gzgets() after gzseek: %s\n", (char*)uncompr);
+    }
+
+    gzclose(file);
+#endif
+}
+
+#endif /* Z_SOLO */
+
+/* ===========================================================================
+ * Test deflate() with small buffers
+ */
+void test_deflate(compr, comprLen)
+    Byte *compr;
+    uLong comprLen;
+{
+    z_stream c_stream; /* compression stream */
+    int err;
+    uLong len = (uLong)strlen(hello)+1;
+
+    c_stream.zalloc = zalloc;
+    c_stream.zfree = zfree;
+    c_stream.opaque = (voidpf)0;
+
+    err = deflateInit(&c_stream, Z_DEFAULT_COMPRESSION);
+    CHECK_ERR(err, "deflateInit");
+
+    c_stream.next_in  = (z_const unsigned char *)hello;
+    c_stream.next_out = compr;
+
+    while (c_stream.total_in != len && c_stream.total_out < comprLen) {
+        c_stream.avail_in = c_stream.avail_out = 1; /* force small buffers */
+        err = deflate(&c_stream, Z_NO_FLUSH);
+        CHECK_ERR(err, "deflate");
+    }
+    /* Finish the stream, still forcing small buffers: */
+    for (;;) {
+        c_stream.avail_out = 1;
+        err = deflate(&c_stream, Z_FINISH);
+        if (err == Z_STREAM_END) break;
+        CHECK_ERR(err, "deflate");
+    }
+
+    err = deflateEnd(&c_stream);
+    CHECK_ERR(err, "deflateEnd");
+}
+
+/* ===========================================================================
+ * Test inflate() with small buffers
+ */
+void test_inflate(compr, comprLen, uncompr, uncomprLen)
+    Byte *compr, *uncompr;
+    uLong comprLen, uncomprLen;
+{
+    int err;
+    z_stream d_stream; /* decompression stream */
+
+    strcpy((char*)uncompr, "garbage");
+
+    d_stream.zalloc = zalloc;
+    d_stream.zfree = zfree;
+    d_stream.opaque = (voidpf)0;
+
+    d_stream.next_in  = compr;
+    d_stream.avail_in = 0;
+    d_stream.next_out = uncompr;
+
+    err = inflateInit(&d_stream);
+    CHECK_ERR(err, "inflateInit");
+
+    while (d_stream.total_out < uncomprLen && d_stream.total_in < comprLen) {
+        d_stream.avail_in = d_stream.avail_out = 1; /* force small buffers */
+        err = inflate(&d_stream, Z_NO_FLUSH);
+        if (err == Z_STREAM_END) break;
+        CHECK_ERR(err, "inflate");
+    }
+
+    err = inflateEnd(&d_stream);
+    CHECK_ERR(err, "inflateEnd");
+
+    if (strcmp((char*)uncompr, hello)) {
+        fprintf(stderr, "bad inflate\n");
+        exit(1);
+    } else {
+        printf("inflate(): %s\n", (char *)uncompr);
+    }
+}
+
+/* ===========================================================================
+ * Test deflate() with large buffers and dynamic change of compression level
+ */
+void test_large_deflate(compr, comprLen, uncompr, uncomprLen)
+    Byte *compr, *uncompr;
+    uLong comprLen, uncomprLen;
+{
+    z_stream c_stream; /* compression stream */
+    int err;
+
+    c_stream.zalloc = zalloc;
+    c_stream.zfree = zfree;
+    c_stream.opaque = (voidpf)0;
+
+    err = deflateInit(&c_stream, Z_BEST_SPEED);
+    CHECK_ERR(err, "deflateInit");
+
+    c_stream.next_out = compr;
+    c_stream.avail_out = (uInt)comprLen;
+
+    /* At this point, uncompr is still mostly zeroes, so it should compress
+     * very well:
+     */
+    c_stream.next_in = uncompr;
+    c_stream.avail_in = (uInt)uncomprLen;
+    err = deflate(&c_stream, Z_NO_FLUSH);
+    CHECK_ERR(err, "deflate");
+    if (c_stream.avail_in != 0) {
+        fprintf(stderr, "deflate not greedy\n");
+        exit(1);
+    }
+
+    /* Feed in already compressed data and switch to no compression: */
+    deflateParams(&c_stream, Z_NO_COMPRESSION, Z_DEFAULT_STRATEGY);
+    c_stream.next_in = compr;
+    c_stream.avail_in = (uInt)comprLen/2;
+    err = deflate(&c_stream, Z_NO_FLUSH);
+    CHECK_ERR(err, "deflate");
+
+    /* Switch back to compressing mode: */
+    deflateParams(&c_stream, Z_BEST_COMPRESSION, Z_FILTERED);
+    c_stream.next_in = uncompr;
+    c_stream.avail_in = (uInt)uncomprLen;
+    err = deflate(&c_stream, Z_NO_FLUSH);
+    CHECK_ERR(err, "deflate");
+
+    err = deflate(&c_stream, Z_FINISH);
+    if (err != Z_STREAM_END) {
+        fprintf(stderr, "deflate should report Z_STREAM_END\n");
+        exit(1);
+    }
+    err = deflateEnd(&c_stream);
+    CHECK_ERR(err, "deflateEnd");
+}
+
+/* ===========================================================================
+ * Test inflate() with large buffers
+ */
+void test_large_inflate(compr, comprLen, uncompr, uncomprLen)
+    Byte *compr, *uncompr;
+    uLong comprLen, uncomprLen;
+{
+    int err;
+    z_stream d_stream; /* decompression stream */
+
+    strcpy((char*)uncompr, "garbage");
+
+    d_stream.zalloc = zalloc;
+    d_stream.zfree = zfree;
+    d_stream.opaque = (voidpf)0;
+
+    d_stream.next_in  = compr;
+    d_stream.avail_in = (uInt)comprLen;
+
+    err = inflateInit(&d_stream);
+    CHECK_ERR(err, "inflateInit");
+
+    for (;;) {
+        d_stream.next_out = uncompr;            /* discard the output */
+        d_stream.avail_out = (uInt)uncomprLen;
+        err = inflate(&d_stream, Z_NO_FLUSH);
+        if (err == Z_STREAM_END) break;
+        CHECK_ERR(err, "large inflate");
+    }
+
+    err = inflateEnd(&d_stream);
+    CHECK_ERR(err, "inflateEnd");
+
+    if (d_stream.total_out != 2*uncomprLen + comprLen/2) {
+        fprintf(stderr, "bad large inflate: %ld\n", d_stream.total_out);
+        exit(1);
+    } else {
+        printf("large_inflate(): OK\n");
+    }
+}
+
+/* ===========================================================================
+ * Test deflate() with full flush
+ */
+void test_flush(compr, comprLen)
+    Byte *compr;
+    uLong *comprLen;
+{
+    z_stream c_stream; /* compression stream */
+    int err;
+    uInt len = (uInt)strlen(hello)+1;
+
+    c_stream.zalloc = zalloc;
+    c_stream.zfree = zfree;
+    c_stream.opaque = (voidpf)0;
+
+    err = deflateInit(&c_stream, Z_DEFAULT_COMPRESSION);
+    CHECK_ERR(err, "deflateInit");
+
+    c_stream.next_in  = (z_const unsigned char *)hello;
+    c_stream.next_out = compr;
+    c_stream.avail_in = 3;
+    c_stream.avail_out = (uInt)*comprLen;
+    err = deflate(&c_stream, Z_FULL_FLUSH);
+    CHECK_ERR(err, "deflate");
+
+    compr[3]++; /* force an error in first compressed block */
+    c_stream.avail_in = len - 3;
+
+    err = deflate(&c_stream, Z_FINISH);
+    if (err != Z_STREAM_END) {
+        CHECK_ERR(err, "deflate");
+    }
+    err = deflateEnd(&c_stream);
+    CHECK_ERR(err, "deflateEnd");
+
+    *comprLen = c_stream.total_out;
+}
+
+/* ===========================================================================
+ * Test inflateSync()
+ */
+void test_sync(compr, comprLen, uncompr, uncomprLen)
+    Byte *compr, *uncompr;
+    uLong comprLen, uncomprLen;
+{
+    int err;
+    z_stream d_stream; /* decompression stream */
+
+    strcpy((char*)uncompr, "garbage");
+
+    d_stream.zalloc = zalloc;
+    d_stream.zfree = zfree;
+    d_stream.opaque = (voidpf)0;
+
+    d_stream.next_in  = compr;
+    d_stream.avail_in = 2; /* just read the zlib header */
+
+    err = inflateInit(&d_stream);
+    CHECK_ERR(err, "inflateInit");
+
+    d_stream.next_out = uncompr;
+    d_stream.avail_out = (uInt)uncomprLen;
+
+    err = inflate(&d_stream, Z_NO_FLUSH);
+    CHECK_ERR(err, "inflate");
+
+    d_stream.avail_in = (uInt)comprLen-2;   /* read all compressed data */
+    err = inflateSync(&d_stream);           /* but skip the damaged part */
+    CHECK_ERR(err, "inflateSync");
+
+    err = inflate(&d_stream, Z_FINISH);
+    if (err != Z_DATA_ERROR) {
+        fprintf(stderr, "inflate should report DATA_ERROR\n");
+        /* Because of incorrect adler32 */
+        exit(1);
+    }
+    err = inflateEnd(&d_stream);
+    CHECK_ERR(err, "inflateEnd");
+
+    printf("after inflateSync(): hel%s\n", (char *)uncompr);
+}
+
+/* ===========================================================================
+ * Test deflate() with preset dictionary
+ */
+void test_dict_deflate(compr, comprLen)
+    Byte *compr;
+    uLong comprLen;
+{
+    z_stream c_stream; /* compression stream */
+    int err;
+
+    c_stream.zalloc = zalloc;
+    c_stream.zfree = zfree;
+    c_stream.opaque = (voidpf)0;
+
+    err = deflateInit(&c_stream, Z_BEST_COMPRESSION);
+    CHECK_ERR(err, "deflateInit");
+
+    err = deflateSetDictionary(&c_stream,
+                (const Bytef*)dictionary, (int)sizeof(dictionary));
+    CHECK_ERR(err, "deflateSetDictionary");
+
+    dictId = c_stream.adler;
+    c_stream.next_out = compr;
+    c_stream.avail_out = (uInt)comprLen;
+
+    c_stream.next_in = (z_const unsigned char *)hello;
+    c_stream.avail_in = (uInt)strlen(hello)+1;
+
+    err = deflate(&c_stream, Z_FINISH);
+    if (err != Z_STREAM_END) {
+        fprintf(stderr, "deflate should report Z_STREAM_END\n");
+        exit(1);
+    }
+    err = deflateEnd(&c_stream);
+    CHECK_ERR(err, "deflateEnd");
+}
+
+/* ===========================================================================
+ * Test inflate() with a preset dictionary
+ */
+void test_dict_inflate(compr, comprLen, uncompr, uncomprLen)
+    Byte *compr, *uncompr;
+    uLong comprLen, uncomprLen;
+{
+    int err;
+    z_stream d_stream; /* decompression stream */
+
+    strcpy((char*)uncompr, "garbage");
+
+    d_stream.zalloc = zalloc;
+    d_stream.zfree = zfree;
+    d_stream.opaque = (voidpf)0;
+
+    d_stream.next_in  = compr;
+    d_stream.avail_in = (uInt)comprLen;
+
+    err = inflateInit(&d_stream);
+    CHECK_ERR(err, "inflateInit");
+
+    d_stream.next_out = uncompr;
+    d_stream.avail_out = (uInt)uncomprLen;
+
+    for (;;) {
+        err = inflate(&d_stream, Z_NO_FLUSH);
+        if (err == Z_STREAM_END) break;
+        if (err == Z_NEED_DICT) {
+            if (d_stream.adler != dictId) {
+                fprintf(stderr, "unexpected dictionary");
+                exit(1);
+            }
+            err = inflateSetDictionary(&d_stream, (const Bytef*)dictionary,
+                                       (int)sizeof(dictionary));
+        }
+        CHECK_ERR(err, "inflate with dict");
+    }
+
+    err = inflateEnd(&d_stream);
+    CHECK_ERR(err, "inflateEnd");
+
+    if (strcmp((char*)uncompr, hello)) {
+        fprintf(stderr, "bad inflate with dict\n");
+        exit(1);
+    } else {
+        printf("inflate with dictionary: %s\n", (char *)uncompr);
+    }
+}
+
+/* ===========================================================================
+ * Usage:  example [output.gz  [input.gz]]
+ */
+
+int main(argc, argv)
+    int argc;
+    char *argv[];
+{
+    Byte *compr, *uncompr;
+    uLong comprLen = 10000*sizeof(int); /* don't overflow on MSDOS */
+    uLong uncomprLen = comprLen;
+    static const char* myVersion = ZLIB_VERSION;
+
+    if (zlibVersion()[0] != myVersion[0]) {
+        fprintf(stderr, "incompatible zlib version\n");
+        exit(1);
+
+    } else if (strcmp(zlibVersion(), ZLIB_VERSION) != 0) {
+        fprintf(stderr, "warning: different zlib version\n");
+    }
+
+    printf("zlib version %s = 0x%04x, compile flags = 0x%lx\n",
+            ZLIB_VERSION, ZLIB_VERNUM, zlibCompileFlags());
+
+    compr    = (Byte*)calloc((uInt)comprLen, 1);
+    uncompr  = (Byte*)calloc((uInt)uncomprLen, 1);
+    /* compr and uncompr are cleared to avoid reading uninitialized
+     * data and to ensure that uncompr compresses well.
+     */
+    if (compr == Z_NULL || uncompr == Z_NULL) {
+        printf("out of memory\n");
+        exit(1);
+    }
+
+#ifdef Z_SOLO
+    (void)argc;
+    (void)argv;
+#else
+    test_compress(compr, comprLen, uncompr, uncomprLen);
+
+    test_gzio((argc > 1 ? argv[1] : TESTFILE),
+              uncompr, uncomprLen);
+#endif
+
+    test_deflate(compr, comprLen);
+    test_inflate(compr, comprLen, uncompr, uncomprLen);
+
+    test_large_deflate(compr, comprLen, uncompr, uncomprLen);
+    test_large_inflate(compr, comprLen, uncompr, uncomprLen);
+
+    test_flush(compr, &comprLen);
+    test_sync(compr, comprLen, uncompr, uncomprLen);
+    comprLen = uncomprLen;
+
+    test_dict_deflate(compr, comprLen);
+    test_dict_inflate(compr, comprLen, uncompr, uncomprLen);
+
+    free(compr);
+    free(uncompr);
+
+    return 0;
+}

ADDED   3rd_party/zlib/test/infcover.c
Index: 3rd_party/zlib/test/infcover.c
==================================================================
--- 3rd_party/zlib/test/infcover.c
+++ 3rd_party/zlib/test/infcover.c
@@ -0,0 +1,671 @@
+/* infcover.c -- test zlib's inflate routines with full code coverage
+ * Copyright (C) 2011, 2016 Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* to use, do: ./configure --cover && make cover */
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <assert.h>
+#include "zlib.h"
+
+/* get definition of internal structure so we can mess with it (see pull()),
+   and so we can call inflate_trees() (see cover5()) */
+#define ZLIB_INTERNAL
+#include "inftrees.h"
+#include "inflate.h"
+
+#define local static
+
+/* -- memory tracking routines -- */
+
+/*
+   These memory tracking routines are provided to zlib and track all of zlib's
+   allocations and deallocations, check for LIFO operations, keep a current
+   and high water mark of total bytes requested, optionally set a limit on the
+   total memory that can be allocated, and when done check for memory leaks.
+
+   They are used as follows:
+
+   z_stream strm;
+   mem_setup(&strm)         initializes the memory tracking and sets the
+                            zalloc, zfree, and opaque members of strm to use
+                            memory tracking for all zlib operations on strm
+   mem_limit(&strm, limit)  sets a limit on the total bytes requested -- a
+                            request that exceeds this limit will result in an
+                            allocation failure (returns NULL) -- setting the
+                            limit to zero means no limit, which is the default
+                            after mem_setup()
+   mem_used(&strm, "msg")   prints to stderr "msg" and the total bytes used
+   mem_high(&strm, "msg")   prints to stderr "msg" and the high water mark
+   mem_done(&strm, "msg")   ends memory tracking, releases all allocations
+                            for the tracking as well as leaked zlib blocks, if
+                            any.  If there was anything unusual, such as leaked
+                            blocks, non-FIFO frees, or frees of addresses not
+                            allocated, then "msg" and information about the
+                            problem is printed to stderr.  If everything is
+                            normal, nothing is printed. mem_done resets the
+                            strm members to Z_NULL to use the default memory
+                            allocation routines on the next zlib initialization
+                            using strm.
+ */
+
+/* these items are strung together in a linked list, one for each allocation */
+struct mem_item {
+    void *ptr;                  /* pointer to allocated memory */
+    size_t size;                /* requested size of allocation */
+    struct mem_item *next;      /* pointer to next item in list, or NULL */
+};
+
+/* this structure is at the root of the linked list, and tracks statistics */
+struct mem_zone {
+    struct mem_item *first;     /* pointer to first item in list, or NULL */
+    size_t total, highwater;    /* total allocations, and largest total */
+    size_t limit;               /* memory allocation limit, or 0 if no limit */
+    int notlifo, rogue;         /* counts of non-LIFO frees and rogue frees */
+};
+
+/* memory allocation routine to pass to zlib */
+local void *mem_alloc(void *mem, unsigned count, unsigned size)
+{
+    void *ptr;
+    struct mem_item *item;
+    struct mem_zone *zone = mem;
+    size_t len = count * (size_t)size;
+
+    /* induced allocation failure */
+    if (zone == NULL || (zone->limit && zone->total + len > zone->limit))
+        return NULL;
+
+    /* perform allocation using the standard library, fill memory with a
+       non-zero value to make sure that the code isn't depending on zeros */
+    ptr = malloc(len);
+    if (ptr == NULL)
+        return NULL;
+    memset(ptr, 0xa5, len);
+
+    /* create a new item for the list */
+    item = malloc(sizeof(struct mem_item));
+    if (item == NULL) {
+        free(ptr);
+        return NULL;
+    }
+    item->ptr = ptr;
+    item->size = len;
+
+    /* insert item at the beginning of the list */
+    item->next = zone->first;
+    zone->first = item;
+
+    /* update the statistics */
+    zone->total += item->size;
+    if (zone->total > zone->highwater)
+        zone->highwater = zone->total;
+
+    /* return the allocated memory */
+    return ptr;
+}
+
+/* memory free routine to pass to zlib */
+local void mem_free(void *mem, void *ptr)
+{
+    struct mem_item *item, *next;
+    struct mem_zone *zone = mem;
+
+    /* if no zone, just do a free */
+    if (zone == NULL) {
+        free(ptr);
+        return;
+    }
+
+    /* point next to the item that matches ptr, or NULL if not found -- remove
+       the item from the linked list if found */
+    next = zone->first;
+    if (next) {
+        if (next->ptr == ptr)
+            zone->first = next->next;   /* first one is it, remove from list */
+        else {
+            do {                        /* search the linked list */
+                item = next;
+                next = item->next;
+            } while (next != NULL && next->ptr != ptr);
+            if (next) {                 /* if found, remove from linked list */
+                item->next = next->next;
+                zone->notlifo++;        /* not a LIFO free */
+            }
+
+        }
+    }
+
+    /* if found, update the statistics and free the item */
+    if (next) {
+        zone->total -= next->size;
+        free(next);
+    }
+
+    /* if not found, update the rogue count */
+    else
+        zone->rogue++;
+
+    /* in any case, do the requested free with the standard library function */
+    free(ptr);
+}
+
+/* set up a controlled memory allocation space for monitoring, set the stream
+   parameters to the controlled routines, with opaque pointing to the space */
+local void mem_setup(z_stream *strm)
+{
+    struct mem_zone *zone;
+
+    zone = malloc(sizeof(struct mem_zone));
+    assert(zone != NULL);
+    zone->first = NULL;
+    zone->total = 0;
+    zone->highwater = 0;
+    zone->limit = 0;
+    zone->notlifo = 0;
+    zone->rogue = 0;
+    strm->opaque = zone;
+    strm->zalloc = mem_alloc;
+    strm->zfree = mem_free;
+}
+
+/* set a limit on the total memory allocation, or 0 to remove the limit */
+local void mem_limit(z_stream *strm, size_t limit)
+{
+    struct mem_zone *zone = strm->opaque;
+
+    zone->limit = limit;
+}
+
+/* show the current total requested allocations in bytes */
+local void mem_used(z_stream *strm, char *prefix)
+{
+    struct mem_zone *zone = strm->opaque;
+
+    fprintf(stderr, "%s: %lu allocated\n", prefix, zone->total);
+}
+
+/* show the high water allocation in bytes */
+local void mem_high(z_stream *strm, char *prefix)
+{
+    struct mem_zone *zone = strm->opaque;
+
+    fprintf(stderr, "%s: %lu high water mark\n", prefix, zone->highwater);
+}
+
+/* release the memory allocation zone -- if there are any surprises, notify */
+local void mem_done(z_stream *strm, char *prefix)
+{
+    int count = 0;
+    struct mem_item *item, *next;
+    struct mem_zone *zone = strm->opaque;
+
+    /* show high water mark */
+    mem_high(strm, prefix);
+
+    /* free leftover allocations and item structures, if any */
+    item = zone->first;
+    while (item != NULL) {
+        free(item->ptr);
+        next = item->next;
+        free(item);
+        item = next;
+        count++;
+    }
+
+    /* issue alerts about anything unexpected */
+    if (count || zone->total)
+        fprintf(stderr, "** %s: %lu bytes in %d blocks not freed\n",
+                prefix, zone->total, count);
+    if (zone->notlifo)
+        fprintf(stderr, "** %s: %d frees not LIFO\n", prefix, zone->notlifo);
+    if (zone->rogue)
+        fprintf(stderr, "** %s: %d frees not recognized\n",
+                prefix, zone->rogue);
+
+    /* free the zone and delete from the stream */
+    free(zone);
+    strm->opaque = Z_NULL;
+    strm->zalloc = Z_NULL;
+    strm->zfree = Z_NULL;
+}
+
+/* -- inflate test routines -- */
+
+/* Decode a hexadecimal string, set *len to length, in[] to the bytes.  This
+   decodes liberally, in that hex digits can be adjacent, in which case two in
+   a row writes a byte.  Or they can be delimited by any non-hex character,
+   where the delimiters are ignored except when a single hex digit is followed
+   by a delimiter, where that single digit writes a byte.  The returned data is
+   allocated and must eventually be freed.  NULL is returned if out of memory.
+   If the length is not needed, then len can be NULL. */
+local unsigned char *h2b(const char *hex, unsigned *len)
+{
+    unsigned char *in, *re;
+    unsigned next, val;
+
+    in = malloc((strlen(hex) + 1) >> 1);
+    if (in == NULL)
+        return NULL;
+    next = 0;
+    val = 1;
+    do {
+        if (*hex >= '0' && *hex <= '9')
+            val = (val << 4) + *hex - '0';
+        else if (*hex >= 'A' && *hex <= 'F')
+            val = (val << 4) + *hex - 'A' + 10;
+        else if (*hex >= 'a' && *hex <= 'f')
+            val = (val << 4) + *hex - 'a' + 10;
+        else if (val != 1 && val < 32)  /* one digit followed by delimiter */
+            val += 240;                 /* make it look like two digits */
+        if (val > 255) {                /* have two digits */
+            in[next++] = val & 0xff;    /* save the decoded byte */
+            val = 1;                    /* start over */
+        }
+    } while (*hex++);       /* go through the loop with the terminating null */
+    if (len != NULL)
+        *len = next;
+    re = realloc(in, next);
+    return re == NULL ? in : re;
+}
+
+/* generic inflate() run, where hex is the hexadecimal input data, what is the
+   text to include in an error message, step is how much input data to feed
+   inflate() on each call, or zero to feed it all, win is the window bits
+   parameter to inflateInit2(), len is the size of the output buffer, and err
+   is the error code expected from the first inflate() call (the second
+   inflate() call is expected to return Z_STREAM_END).  If win is 47, then
+   header information is collected with inflateGetHeader().  If a zlib stream
+   is looking for a dictionary, then an empty dictionary is provided.
+   inflate() is run until all of the input data is consumed. */
+local void inf(char *hex, char *what, unsigned step, int win, unsigned len,
+               int err)
+{
+    int ret;
+    unsigned have;
+    unsigned char *in, *out;
+    z_stream strm, copy;
+    gz_header head;
+
+    mem_setup(&strm);
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit2(&strm, win);
+    if (ret != Z_OK) {
+        mem_done(&strm, what);
+        return;
+    }
+    out = malloc(len);                          assert(out != NULL);
+    if (win == 47) {
+        head.extra = out;
+        head.extra_max = len;
+        head.name = out;
+        head.name_max = len;
+        head.comment = out;
+        head.comm_max = len;
+        ret = inflateGetHeader(&strm, &head);   assert(ret == Z_OK);
+    }
+    in = h2b(hex, &have);                       assert(in != NULL);
+    if (step == 0 || step > have)
+        step = have;
+    strm.avail_in = step;
+    have -= step;
+    strm.next_in = in;
+    do {
+        strm.avail_out = len;
+        strm.next_out = out;
+        ret = inflate(&strm, Z_NO_FLUSH);       assert(err == 9 || ret == err);
+        if (ret != Z_OK && ret != Z_BUF_ERROR && ret != Z_NEED_DICT)
+            break;
+        if (ret == Z_NEED_DICT) {
+            ret = inflateSetDictionary(&strm, in, 1);
+                                                assert(ret == Z_DATA_ERROR);
+            mem_limit(&strm, 1);
+            ret = inflateSetDictionary(&strm, out, 0);
+                                                assert(ret == Z_MEM_ERROR);
+            mem_limit(&strm, 0);
+            ((struct inflate_state *)strm.state)->mode = DICT;
+            ret = inflateSetDictionary(&strm, out, 0);
+                                                assert(ret == Z_OK);
+            ret = inflate(&strm, Z_NO_FLUSH);   assert(ret == Z_BUF_ERROR);
+        }
+        ret = inflateCopy(&copy, &strm);        assert(ret == Z_OK);
+        ret = inflateEnd(&copy);                assert(ret == Z_OK);
+        err = 9;                        /* don't care next time around */
+        have += strm.avail_in;
+        strm.avail_in = step > have ? have : step;
+        have -= strm.avail_in;
+    } while (strm.avail_in);
+    free(in);
+    free(out);
+    ret = inflateReset2(&strm, -8);             assert(ret == Z_OK);
+    ret = inflateEnd(&strm);                    assert(ret == Z_OK);
+    mem_done(&strm, what);
+}
+
+/* cover all of the lines in inflate.c up to inflate() */
+local void cover_support(void)
+{
+    int ret;
+    z_stream strm;
+
+    mem_setup(&strm);
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit(&strm);                   assert(ret == Z_OK);
+    mem_used(&strm, "inflate init");
+    ret = inflatePrime(&strm, 5, 31);           assert(ret == Z_OK);
+    ret = inflatePrime(&strm, -1, 0);           assert(ret == Z_OK);
+    ret = inflateSetDictionary(&strm, Z_NULL, 0);
+                                                assert(ret == Z_STREAM_ERROR);
+    ret = inflateEnd(&strm);                    assert(ret == Z_OK);
+    mem_done(&strm, "prime");
+
+    inf("63 0", "force window allocation", 0, -15, 1, Z_OK);
+    inf("63 18 5", "force window replacement", 0, -8, 259, Z_OK);
+    inf("63 18 68 30 d0 0 0", "force split window update", 4, -8, 259, Z_OK);
+    inf("3 0", "use fixed blocks", 0, -15, 1, Z_STREAM_END);
+    inf("", "bad window size", 0, 1, 0, Z_STREAM_ERROR);
+
+    mem_setup(&strm);
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit_(&strm, ZLIB_VERSION - 1, (int)sizeof(z_stream));
+                                                assert(ret == Z_VERSION_ERROR);
+    mem_done(&strm, "wrong version");
+
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit(&strm);                   assert(ret == Z_OK);
+    ret = inflateEnd(&strm);                    assert(ret == Z_OK);
+    fputs("inflate built-in memory routines\n", stderr);
+}
+
+/* cover all inflate() header and trailer cases and code after inflate() */
+local void cover_wrap(void)
+{
+    int ret;
+    z_stream strm, copy;
+    unsigned char dict[257];
+
+    ret = inflate(Z_NULL, 0);                   assert(ret == Z_STREAM_ERROR);
+    ret = inflateEnd(Z_NULL);                   assert(ret == Z_STREAM_ERROR);
+    ret = inflateCopy(Z_NULL, Z_NULL);          assert(ret == Z_STREAM_ERROR);
+    fputs("inflate bad parameters\n", stderr);
+
+    inf("1f 8b 0 0", "bad gzip method", 0, 31, 0, Z_DATA_ERROR);
+    inf("1f 8b 8 80", "bad gzip flags", 0, 31, 0, Z_DATA_ERROR);
+    inf("77 85", "bad zlib method", 0, 15, 0, Z_DATA_ERROR);
+    inf("8 99", "set window size from header", 0, 0, 0, Z_OK);
+    inf("78 9c", "bad zlib window size", 0, 8, 0, Z_DATA_ERROR);
+    inf("78 9c 63 0 0 0 1 0 1", "check adler32", 0, 15, 1, Z_STREAM_END);
+    inf("1f 8b 8 1e 0 0 0 0 0 0 1 0 0 0 0 0 0", "bad header crc", 0, 47, 1,
+        Z_DATA_ERROR);
+    inf("1f 8b 8 2 0 0 0 0 0 0 1d 26 3 0 0 0 0 0 0 0 0 0", "check gzip length",
+        0, 47, 0, Z_STREAM_END);
+    inf("78 90", "bad zlib header check", 0, 47, 0, Z_DATA_ERROR);
+    inf("8 b8 0 0 0 1", "need dictionary", 0, 8, 0, Z_NEED_DICT);
+    inf("78 9c 63 0", "compute adler32", 0, 15, 1, Z_OK);
+
+    mem_setup(&strm);
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit2(&strm, -8);
+    strm.avail_in = 2;
+    strm.next_in = (void *)"\x63";
+    strm.avail_out = 1;
+    strm.next_out = (void *)&ret;
+    mem_limit(&strm, 1);
+    ret = inflate(&strm, Z_NO_FLUSH);           assert(ret == Z_MEM_ERROR);
+    ret = inflate(&strm, Z_NO_FLUSH);           assert(ret == Z_MEM_ERROR);
+    mem_limit(&strm, 0);
+    memset(dict, 0, 257);
+    ret = inflateSetDictionary(&strm, dict, 257);
+                                                assert(ret == Z_OK);
+    mem_limit(&strm, (sizeof(struct inflate_state) << 1) + 256);
+    ret = inflatePrime(&strm, 16, 0);           assert(ret == Z_OK);
+    strm.avail_in = 2;
+    strm.next_in = (void *)"\x80";
+    ret = inflateSync(&strm);                   assert(ret == Z_DATA_ERROR);
+    ret = inflate(&strm, Z_NO_FLUSH);           assert(ret == Z_STREAM_ERROR);
+    strm.avail_in = 4;
+    strm.next_in = (void *)"\0\0\xff\xff";
+    ret = inflateSync(&strm);                   assert(ret == Z_OK);
+    (void)inflateSyncPoint(&strm);
+    ret = inflateCopy(&copy, &strm);            assert(ret == Z_MEM_ERROR);
+    mem_limit(&strm, 0);
+    ret = inflateUndermine(&strm, 1);           assert(ret == Z_DATA_ERROR);
+    (void)inflateMark(&strm);
+    ret = inflateEnd(&strm);                    assert(ret == Z_OK);
+    mem_done(&strm, "miscellaneous, force memory errors");
+}
+
+/* input and output functions for inflateBack() */
+local unsigned pull(void *desc, unsigned char **buf)
+{
+    static unsigned int next = 0;
+    static unsigned char dat[] = {0x63, 0, 2, 0};
+    struct inflate_state *state;
+
+    if (desc == Z_NULL) {
+        next = 0;
+        return 0;   /* no input (already provided at next_in) */
+    }
+    state = (void *)((z_stream *)desc)->state;
+    if (state != Z_NULL)
+        state->mode = SYNC;     /* force an otherwise impossible situation */
+    return next < sizeof(dat) ? (*buf = dat + next++, 1) : 0;
+}
+
+local int push(void *desc, unsigned char *buf, unsigned len)
+{
+    buf += len;
+    return desc != Z_NULL;      /* force error if desc not null */
+}
+
+/* cover inflateBack() up to common deflate data cases and after those */
+local void cover_back(void)
+{
+    int ret;
+    z_stream strm;
+    unsigned char win[32768];
+
+    ret = inflateBackInit_(Z_NULL, 0, win, 0, 0);
+                                                assert(ret == Z_VERSION_ERROR);
+    ret = inflateBackInit(Z_NULL, 0, win);      assert(ret == Z_STREAM_ERROR);
+    ret = inflateBack(Z_NULL, Z_NULL, Z_NULL, Z_NULL, Z_NULL);
+                                                assert(ret == Z_STREAM_ERROR);
+    ret = inflateBackEnd(Z_NULL);               assert(ret == Z_STREAM_ERROR);
+    fputs("inflateBack bad parameters\n", stderr);
+
+    mem_setup(&strm);
+    ret = inflateBackInit(&strm, 15, win);      assert(ret == Z_OK);
+    strm.avail_in = 2;
+    strm.next_in = (void *)"\x03";
+    ret = inflateBack(&strm, pull, Z_NULL, push, Z_NULL);
+                                                assert(ret == Z_STREAM_END);
+        /* force output error */
+    strm.avail_in = 3;
+    strm.next_in = (void *)"\x63\x00";
+    ret = inflateBack(&strm, pull, Z_NULL, push, &strm);
+                                                assert(ret == Z_BUF_ERROR);
+        /* force mode error by mucking with state */
+    ret = inflateBack(&strm, pull, &strm, push, Z_NULL);
+                                                assert(ret == Z_STREAM_ERROR);
+    ret = inflateBackEnd(&strm);                assert(ret == Z_OK);
+    mem_done(&strm, "inflateBack bad state");
+
+    ret = inflateBackInit(&strm, 15, win);      assert(ret == Z_OK);
+    ret = inflateBackEnd(&strm);                assert(ret == Z_OK);
+    fputs("inflateBack built-in memory routines\n", stderr);
+}
+
+/* do a raw inflate of data in hexadecimal with both inflate and inflateBack */
+local int try(char *hex, char *id, int err)
+{
+    int ret;
+    unsigned len, size;
+    unsigned char *in, *out, *win;
+    char *prefix;
+    z_stream strm;
+
+    /* convert to hex */
+    in = h2b(hex, &len);
+    assert(in != NULL);
+
+    /* allocate work areas */
+    size = len << 3;
+    out = malloc(size);
+    assert(out != NULL);
+    win = malloc(32768);
+    assert(win != NULL);
+    prefix = malloc(strlen(id) + 6);
+    assert(prefix != NULL);
+
+    /* first with inflate */
+    strcpy(prefix, id);
+    strcat(prefix, "-late");
+    mem_setup(&strm);
+    strm.avail_in = 0;
+    strm.next_in = Z_NULL;
+    ret = inflateInit2(&strm, err < 0 ? 47 : -15);
+    assert(ret == Z_OK);
+    strm.avail_in = len;
+    strm.next_in = in;
+    do {
+        strm.avail_out = size;
+        strm.next_out = out;
+        ret = inflate(&strm, Z_TREES);
+        assert(ret != Z_STREAM_ERROR && ret != Z_MEM_ERROR);
+        if (ret == Z_DATA_ERROR || ret == Z_NEED_DICT)
+            break;
+    } while (strm.avail_in || strm.avail_out == 0);
+    if (err) {
+        assert(ret == Z_DATA_ERROR);
+        assert(strcmp(id, strm.msg) == 0);
+    }
+    inflateEnd(&strm);
+    mem_done(&strm, prefix);
+
+    /* then with inflateBack */
+    if (err >= 0) {
+        strcpy(prefix, id);
+        strcat(prefix, "-back");
+        mem_setup(&strm);
+        ret = inflateBackInit(&strm, 15, win);
+        assert(ret == Z_OK);
+        strm.avail_in = len;
+        strm.next_in = in;
+        ret = inflateBack(&strm, pull, Z_NULL, push, Z_NULL);
+        assert(ret != Z_STREAM_ERROR);
+        if (err) {
+            assert(ret == Z_DATA_ERROR);
+            assert(strcmp(id, strm.msg) == 0);
+        }
+        inflateBackEnd(&strm);
+        mem_done(&strm, prefix);
+    }
+
+    /* clean up */
+    free(prefix);
+    free(win);
+    free(out);
+    free(in);
+    return ret;
+}
+
+/* cover deflate data cases in both inflate() and inflateBack() */
+local void cover_inflate(void)
+{
+    try("0 0 0 0 0", "invalid stored block lengths", 1);
+    try("3 0", "fixed", 0);
+    try("6", "invalid block type", 1);
+    try("1 1 0 fe ff 0", "stored", 0);
+    try("fc 0 0", "too many length or distance symbols", 1);
+    try("4 0 fe ff", "invalid code lengths set", 1);
+    try("4 0 24 49 0", "invalid bit length repeat", 1);
+    try("4 0 24 e9 ff ff", "invalid bit length repeat", 1);
+    try("4 0 24 e9 ff 6d", "invalid code -- missing end-of-block", 1);
+    try("4 80 49 92 24 49 92 24 71 ff ff 93 11 0",
+        "invalid literal/lengths set", 1);
+    try("4 80 49 92 24 49 92 24 f b4 ff ff c3 84", "invalid distances set", 1);
+    try("4 c0 81 8 0 0 0 0 20 7f eb b 0 0", "invalid literal/length code", 1);
+    try("2 7e ff ff", "invalid distance code", 1);
+    try("c c0 81 0 0 0 0 0 90 ff 6b 4 0", "invalid distance too far back", 1);
+
+    /* also trailer mismatch just in inflate() */
+    try("1f 8b 8 0 0 0 0 0 0 0 3 0 0 0 0 1", "incorrect data check", -1);
+    try("1f 8b 8 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1",
+        "incorrect length check", -1);
+    try("5 c0 21 d 0 0 0 80 b0 fe 6d 2f 91 6c", "pull 17", 0);
+    try("5 e0 81 91 24 cb b2 2c 49 e2 f 2e 8b 9a 47 56 9f fb fe ec d2 ff 1f",
+        "long code", 0);
+    try("ed c0 1 1 0 0 0 40 20 ff 57 1b 42 2c 4f", "length extra", 0);
+    try("ed cf c1 b1 2c 47 10 c4 30 fa 6f 35 1d 1 82 59 3d fb be 2e 2a fc f c",
+        "long distance and extra", 0);
+    try("ed c0 81 0 0 0 0 80 a0 fd a9 17 a9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 "
+        "0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6", "window end", 0);
+    inf("2 8 20 80 0 3 0", "inflate_fast TYPE return", 0, -15, 258,
+        Z_STREAM_END);
+    inf("63 18 5 40 c 0", "window wrap", 3, -8, 300, Z_OK);
+}
+
+/* cover remaining lines in inftrees.c */
+local void cover_trees(void)
+{
+    int ret;
+    unsigned bits;
+    unsigned short lens[16], work[16];
+    code *next, table[ENOUGH_DISTS];
+
+    /* we need to call inflate_table() directly in order to manifest not-
+       enough errors, since zlib insures that enough is always enough */
+    for (bits = 0; bits < 15; bits++)
+        lens[bits] = (unsigned short)(bits + 1);
+    lens[15] = 15;
+    next = table;
+    bits = 15;
+    ret = inflate_table(DISTS, lens, 16, &next, &bits, work);
+                                                assert(ret == 1);
+    next = table;
+    bits = 1;
+    ret = inflate_table(DISTS, lens, 16, &next, &bits, work);
+                                                assert(ret == 1);
+    fputs("inflate_table not enough errors\n", stderr);
+}
+
+/* cover remaining inffast.c decoding and window copying */
+local void cover_fast(void)
+{
+    inf("e5 e0 81 ad 6d cb b2 2c c9 01 1e 59 63 ae 7d ee fb 4d fd b5 35 41 68"
+        " ff 7f 0f 0 0 0", "fast length extra bits", 0, -8, 258, Z_DATA_ERROR);
+    inf("25 fd 81 b5 6d 59 b6 6a 49 ea af 35 6 34 eb 8c b9 f6 b9 1e ef 67 49"
+        " 50 fe ff ff 3f 0 0", "fast distance extra bits", 0, -8, 258,
+        Z_DATA_ERROR);
+    inf("3 7e 0 0 0 0 0", "fast invalid distance code", 0, -8, 258,
+        Z_DATA_ERROR);
+    inf("1b 7 0 0 0 0 0", "fast invalid literal/length code", 0, -8, 258,
+        Z_DATA_ERROR);
+    inf("d c7 1 ae eb 38 c 4 41 a0 87 72 de df fb 1f b8 36 b1 38 5d ff ff 0",
+        "fast 2nd level codes and too far back", 0, -8, 258, Z_DATA_ERROR);
+    inf("63 18 5 8c 10 8 0 0 0 0", "very common case", 0, -8, 259, Z_OK);
+    inf("63 60 60 18 c9 0 8 18 18 18 26 c0 28 0 29 0 0 0",
+        "contiguous and wrap around window", 6, -8, 259, Z_OK);
+    inf("63 0 3 0 0 0 0 0", "copy direct from output", 0, -8, 259,
+        Z_STREAM_END);
+}
+
+int main(void)
+{
+    fprintf(stderr, "%s\n", zlibVersion());
+    cover_support();
+    cover_wrap();
+    cover_back();
+    cover_inflate();
+    cover_trees();
+    cover_fast();
+    return 0;
+}

ADDED   3rd_party/zlib/test/minigzip.c
Index: 3rd_party/zlib/test/minigzip.c
==================================================================
--- 3rd_party/zlib/test/minigzip.c
+++ 3rd_party/zlib/test/minigzip.c
@@ -0,0 +1,651 @@
+/* minigzip.c -- simulate gzip using the zlib compression library
+ * Copyright (C) 1995-2006, 2010, 2011, 2016 Jean-loup Gailly
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/*
+ * minigzip is a minimal implementation of the gzip utility. This is
+ * only an example of using zlib and isn't meant to replace the
+ * full-featured gzip. No attempt is made to deal with file systems
+ * limiting names to 14 or 8+3 characters, etc... Error checking is
+ * very limited. So use minigzip only for testing; use gzip for the
+ * real thing. On MSDOS, use only on file names without extension
+ * or in pipe mode.
+ */
+
+/* @(#) $Id$ */
+
+#include "zlib.h"
+#include <stdio.h>
+
+#ifdef STDC
+#  include <string.h>
+#  include <stdlib.h>
+#endif
+
+#ifdef USE_MMAP
+#  include <sys/types.h>
+#  include <sys/mman.h>
+#  include <sys/stat.h>
+#endif
+
+#if defined(MSDOS) || defined(OS2) || defined(WIN32) || defined(__CYGWIN__)
+#  include <fcntl.h>
+#  include <io.h>
+#  ifdef UNDER_CE
+#    include <stdlib.h>
+#  endif
+#  define SET_BINARY_MODE(file) setmode(fileno(file), O_BINARY)
+#else
+#  define SET_BINARY_MODE(file)
+#endif
+
+#if defined(_MSC_VER) && _MSC_VER < 1900
+#  define snprintf _snprintf
+#endif
+
+#ifdef VMS
+#  define unlink delete
+#  define GZ_SUFFIX "-gz"
+#endif
+#ifdef RISCOS
+#  define unlink remove
+#  define GZ_SUFFIX "-gz"
+#  define fileno(file) file->__file
+#endif
+#if defined(__MWERKS__) && __dest_os != __be_os && __dest_os != __win32_os
+#  include <unix.h> /* for fileno */
+#endif
+
+#if !defined(Z_HAVE_UNISTD_H) && !defined(_LARGEFILE64_SOURCE)
+#ifndef WIN32 /* unlink already in stdio.h for WIN32 */
+  extern int unlink OF((const char *));
+#endif
+#endif
+
+#if defined(UNDER_CE)
+#  include <windows.h>
+#  define perror(s) pwinerror(s)
+
+/* Map the Windows error number in ERROR to a locale-dependent error
+   message string and return a pointer to it.  Typically, the values
+   for ERROR come from GetLastError.
+
+   The string pointed to shall not be modified by the application,
+   but may be overwritten by a subsequent call to strwinerror
+
+   The strwinerror function does not change the current setting
+   of GetLastError.  */
+
+static char *strwinerror (error)
+     DWORD error;
+{
+    static char buf[1024];
+
+    wchar_t *msgbuf;
+    DWORD lasterr = GetLastError();
+    DWORD chars = FormatMessage(FORMAT_MESSAGE_FROM_SYSTEM
+        | FORMAT_MESSAGE_ALLOCATE_BUFFER,
+        NULL,
+        error,
+        0, /* Default language */
+        (LPVOID)&msgbuf,
+        0,
+        NULL);
+    if (chars != 0) {
+        /* If there is an \r\n appended, zap it.  */
+        if (chars >= 2
+            && msgbuf[chars - 2] == '\r' && msgbuf[chars - 1] == '\n') {
+            chars -= 2;
+            msgbuf[chars] = 0;
+        }
+
+        if (chars > sizeof (buf) - 1) {
+            chars = sizeof (buf) - 1;
+            msgbuf[chars] = 0;
+        }
+
+        wcstombs(buf, msgbuf, chars + 1);
+        LocalFree(msgbuf);
+    }
+    else {
+        sprintf(buf, "unknown win32 error (%ld)", error);
+    }
+
+    SetLastError(lasterr);
+    return buf;
+}
+
+static void pwinerror (s)
+    const char *s;
+{
+    if (s && *s)
+        fprintf(stderr, "%s: %s\n", s, strwinerror(GetLastError ()));
+    else
+        fprintf(stderr, "%s\n", strwinerror(GetLastError ()));
+}
+
+#endif /* UNDER_CE */
+
+#ifndef GZ_SUFFIX
+#  define GZ_SUFFIX ".gz"
+#endif
+#define SUFFIX_LEN (sizeof(GZ_SUFFIX)-1)
+
+#define BUFLEN      16384
+#define MAX_NAME_LEN 1024
+
+#ifdef MAXSEG_64K
+#  define local static
+   /* Needed for systems with limitation on stack size. */
+#else
+#  define local
+#endif
+
+#ifdef Z_SOLO
+/* for Z_SOLO, create simplified gz* functions using deflate and inflate */
+
+#if defined(Z_HAVE_UNISTD_H) || defined(Z_LARGE)
+#  include <unistd.h>       /* for unlink() */
+#endif
+
+void *myalloc OF((void *, unsigned, unsigned));
+void myfree OF((void *, void *));
+
+void *myalloc(q, n, m)
+    void *q;
+    unsigned n, m;
+{
+    (void)q;
+    return calloc(n, m);
+}
+
+void myfree(q, p)
+    void *q, *p;
+{
+    (void)q;
+    free(p);
+}
+
+typedef struct gzFile_s {
+    FILE *file;
+    int write;
+    int err;
+    char *msg;
+    z_stream strm;
+} *gzFile;
+
+gzFile gzopen OF((const char *, const char *));
+gzFile gzdopen OF((int, const char *));
+gzFile gz_open OF((const char *, int, const char *));
+
+gzFile gzopen(path, mode)
+const char *path;
+const char *mode;
+{
+    return gz_open(path, -1, mode);
+}
+
+gzFile gzdopen(fd, mode)
+int fd;
+const char *mode;
+{
+    return gz_open(NULL, fd, mode);
+}
+
+gzFile gz_open(path, fd, mode)
+    const char *path;
+    int fd;
+    const char *mode;
+{
+    gzFile gz;
+    int ret;
+
+    gz = malloc(sizeof(struct gzFile_s));
+    if (gz == NULL)
+        return NULL;
+    gz->write = strchr(mode, 'w') != NULL;
+    gz->strm.zalloc = myalloc;
+    gz->strm.zfree = myfree;
+    gz->strm.opaque = Z_NULL;
+    if (gz->write)
+        ret = deflateInit2(&(gz->strm), -1, 8, 15 + 16, 8, 0);
+    else {
+        gz->strm.next_in = 0;
+        gz->strm.avail_in = Z_NULL;
+        ret = inflateInit2(&(gz->strm), 15 + 16);
+    }
+    if (ret != Z_OK) {
+        free(gz);
+        return NULL;
+    }
+    gz->file = path == NULL ? fdopen(fd, gz->write ? "wb" : "rb") :
+                              fopen(path, gz->write ? "wb" : "rb");
+    if (gz->file == NULL) {
+        gz->write ? deflateEnd(&(gz->strm)) : inflateEnd(&(gz->strm));
+        free(gz);
+        return NULL;
+    }
+    gz->err = 0;
+    gz->msg = "";
+    return gz;
+}
+
+int gzwrite OF((gzFile, const void *, unsigned));
+
+int gzwrite(gz, buf, len)
+    gzFile gz;
+    const void *buf;
+    unsigned len;
+{
+    z_stream *strm;
+    unsigned char out[BUFLEN];
+
+    if (gz == NULL || !gz->write)
+        return 0;
+    strm = &(gz->strm);
+    strm->next_in = (void *)buf;
+    strm->avail_in = len;
+    do {
+        strm->next_out = out;
+        strm->avail_out = BUFLEN;
+        (void)deflate(strm, Z_NO_FLUSH);
+        fwrite(out, 1, BUFLEN - strm->avail_out, gz->file);
+    } while (strm->avail_out == 0);
+    return len;
+}
+
+int gzread OF((gzFile, void *, unsigned));
+
+int gzread(gz, buf, len)
+    gzFile gz;
+    void *buf;
+    unsigned len;
+{
+    int ret;
+    unsigned got;
+    unsigned char in[1];
+    z_stream *strm;
+
+    if (gz == NULL || gz->write)
+        return 0;
+    if (gz->err)
+        return 0;
+    strm = &(gz->strm);
+    strm->next_out = (void *)buf;
+    strm->avail_out = len;
+    do {
+        got = fread(in, 1, 1, gz->file);
+        if (got == 0)
+            break;
+        strm->next_in = in;
+        strm->avail_in = 1;
+        ret = inflate(strm, Z_NO_FLUSH);
+        if (ret == Z_DATA_ERROR) {
+            gz->err = Z_DATA_ERROR;
+            gz->msg = strm->msg;
+            return 0;
+        }
+        if (ret == Z_STREAM_END)
+            inflateReset(strm);
+    } while (strm->avail_out);
+    return len - strm->avail_out;
+}
+
+int gzclose OF((gzFile));
+
+int gzclose(gz)
+    gzFile gz;
+{
+    z_stream *strm;
+    unsigned char out[BUFLEN];
+
+    if (gz == NULL)
+        return Z_STREAM_ERROR;
+    strm = &(gz->strm);
+    if (gz->write) {
+        strm->next_in = Z_NULL;
+        strm->avail_in = 0;
+        do {
+            strm->next_out = out;
+            strm->avail_out = BUFLEN;
+            (void)deflate(strm, Z_FINISH);
+            fwrite(out, 1, BUFLEN - strm->avail_out, gz->file);
+        } while (strm->avail_out == 0);
+        deflateEnd(strm);
+    }
+    else
+        inflateEnd(strm);
+    fclose(gz->file);
+    free(gz);
+    return Z_OK;
+}
+
+const char *gzerror OF((gzFile, int *));
+
+const char *gzerror(gz, err)
+    gzFile gz;
+    int *err;
+{
+    *err = gz->err;
+    return gz->msg;
+}
+
+#endif
+
+static char *prog;
+
+void error            OF((const char *msg));
+void gz_compress      OF((FILE   *in, gzFile out));
+#ifdef USE_MMAP
+int  gz_compress_mmap OF((FILE   *in, gzFile out));
+#endif
+void gz_uncompress    OF((gzFile in, FILE   *out));
+void file_compress    OF((char  *file, char *mode));
+void file_uncompress  OF((char  *file));
+int  main             OF((int argc, char *argv[]));
+
+/* ===========================================================================
+ * Display error message and exit
+ */
+void error(msg)
+    const char *msg;
+{
+    fprintf(stderr, "%s: %s\n", prog, msg);
+    exit(1);
+}
+
+/* ===========================================================================
+ * Compress input to output then close both files.
+ */
+
+void gz_compress(in, out)
+    FILE   *in;
+    gzFile out;
+{
+    local char buf[BUFLEN];
+    int len;
+    int err;
+
+#ifdef USE_MMAP
+    /* Try first compressing with mmap. If mmap fails (minigzip used in a
+     * pipe), use the normal fread loop.
+     */
+    if (gz_compress_mmap(in, out) == Z_OK) return;
+#endif
+    for (;;) {
+        len = (int)fread(buf, 1, sizeof(buf), in);
+        if (ferror(in)) {
+            perror("fread");
+            exit(1);
+        }
+        if (len == 0) break;
+
+        if (gzwrite(out, buf, (unsigned)len) != len) error(gzerror(out, &err));
+    }
+    fclose(in);
+    if (gzclose(out) != Z_OK) error("failed gzclose");
+}
+
+#ifdef USE_MMAP /* MMAP version, Miguel Albrecht <malbrech@eso.org> */
+
+/* Try compressing the input file at once using mmap. Return Z_OK if
+ * if success, Z_ERRNO otherwise.
+ */
+int gz_compress_mmap(in, out)
+    FILE   *in;
+    gzFile out;
+{
+    int len;
+    int err;
+    int ifd = fileno(in);
+    caddr_t buf;    /* mmap'ed buffer for the entire input file */
+    off_t buf_len;  /* length of the input file */
+    struct stat sb;
+
+    /* Determine the size of the file, needed for mmap: */
+    if (fstat(ifd, &sb) < 0) return Z_ERRNO;
+    buf_len = sb.st_size;
+    if (buf_len <= 0) return Z_ERRNO;
+
+    /* Now do the actual mmap: */
+    buf = mmap((caddr_t) 0, buf_len, PROT_READ, MAP_SHARED, ifd, (off_t)0);
+    if (buf == (caddr_t)(-1)) return Z_ERRNO;
+
+    /* Compress the whole file at once: */
+    len = gzwrite(out, (char *)buf, (unsigned)buf_len);
+
+    if (len != (int)buf_len) error(gzerror(out, &err));
+
+    munmap(buf, buf_len);
+    fclose(in);
+    if (gzclose(out) != Z_OK) error("failed gzclose");
+    return Z_OK;
+}
+#endif /* USE_MMAP */
+
+/* ===========================================================================
+ * Uncompress input to output then close both files.
+ */
+void gz_uncompress(in, out)
+    gzFile in;
+    FILE   *out;
+{
+    local char buf[BUFLEN];
+    int len;
+    int err;
+
+    for (;;) {
+        len = gzread(in, buf, sizeof(buf));
+        if (len < 0) error (gzerror(in, &err));
+        if (len == 0) break;
+
+        if ((int)fwrite(buf, 1, (unsigned)len, out) != len) {
+            error("failed fwrite");
+        }
+    }
+    if (fclose(out)) error("failed fclose");
+
+    if (gzclose(in) != Z_OK) error("failed gzclose");
+}
+
+
+/* ===========================================================================
+ * Compress the given file: create a corresponding .gz file and remove the
+ * original.
+ */
+void file_compress(file, mode)
+    char  *file;
+    char  *mode;
+{
+    local char outfile[MAX_NAME_LEN];
+    FILE  *in;
+    gzFile out;
+
+    if (strlen(file) + strlen(GZ_SUFFIX) >= sizeof(outfile)) {
+        fprintf(stderr, "%s: filename too long\n", prog);
+        exit(1);
+    }
+
+#if !defined(NO_snprintf) && !defined(NO_vsnprintf)
+    snprintf(outfile, sizeof(outfile), "%s%s", file, GZ_SUFFIX);
+#else
+    strcpy(outfile, file);
+    strcat(outfile, GZ_SUFFIX);
+#endif
+
+    in = fopen(file, "rb");
+    if (in == NULL) {
+        perror(file);
+        exit(1);
+    }
+    out = gzopen(outfile, mode);
+    if (out == NULL) {
+        fprintf(stderr, "%s: can't gzopen %s\n", prog, outfile);
+        exit(1);
+    }
+    gz_compress(in, out);
+
+    unlink(file);
+}
+
+
+/* ===========================================================================
+ * Uncompress the given file and remove the original.
+ */
+void file_uncompress(file)
+    char  *file;
+{
+    local char buf[MAX_NAME_LEN];
+    char *infile, *outfile;
+    FILE  *out;
+    gzFile in;
+    unsigned len = strlen(file);
+
+    if (len + strlen(GZ_SUFFIX) >= sizeof(buf)) {
+        fprintf(stderr, "%s: filename too long\n", prog);
+        exit(1);
+    }
+
+#if !defined(NO_snprintf) && !defined(NO_vsnprintf)
+    snprintf(buf, sizeof(buf), "%s", file);
+#else
+    strcpy(buf, file);
+#endif
+
+    if (len > SUFFIX_LEN && strcmp(file+len-SUFFIX_LEN, GZ_SUFFIX) == 0) {
+        infile = file;
+        outfile = buf;
+        outfile[len-3] = '\0';
+    } else {
+        outfile = file;
+        infile = buf;
+#if !defined(NO_snprintf) && !defined(NO_vsnprintf)
+        snprintf(buf + len, sizeof(buf) - len, "%s", GZ_SUFFIX);
+#else
+        strcat(infile, GZ_SUFFIX);
+#endif
+    }
+    in = gzopen(infile, "rb");
+    if (in == NULL) {
+        fprintf(stderr, "%s: can't gzopen %s\n", prog, infile);
+        exit(1);
+    }
+    out = fopen(outfile, "wb");
+    if (out == NULL) {
+        perror(file);
+        exit(1);
+    }
+
+    gz_uncompress(in, out);
+
+    unlink(infile);
+}
+
+
+/* ===========================================================================
+ * Usage:  minigzip [-c] [-d] [-f] [-h] [-r] [-1 to -9] [files...]
+ *   -c : write to standard output
+ *   -d : decompress
+ *   -f : compress with Z_FILTERED
+ *   -h : compress with Z_HUFFMAN_ONLY
+ *   -r : compress with Z_RLE
+ *   -1 to -9 : compression level
+ */
+
+int main(argc, argv)
+    int argc;
+    char *argv[];
+{
+    int copyout = 0;
+    int uncompr = 0;
+    gzFile file;
+    char *bname, outmode[20];
+
+#if !defined(NO_snprintf) && !defined(NO_vsnprintf)
+    snprintf(outmode, sizeof(outmode), "%s", "wb6 ");
+#else
+    strcpy(outmode, "wb6 ");
+#endif
+
+    prog = argv[0];
+    bname = strrchr(argv[0], '/');
+    if (bname)
+      bname++;
+    else
+      bname = argv[0];
+    argc--, argv++;
+
+    if (!strcmp(bname, "gunzip"))
+      uncompr = 1;
+    else if (!strcmp(bname, "zcat"))
+      copyout = uncompr = 1;
+
+    while (argc > 0) {
+      if (strcmp(*argv, "-c") == 0)
+        copyout = 1;
+      else if (strcmp(*argv, "-d") == 0)
+        uncompr = 1;
+      else if (strcmp(*argv, "-f") == 0)
+        outmode[3] = 'f';
+      else if (strcmp(*argv, "-h") == 0)
+        outmode[3] = 'h';
+      else if (strcmp(*argv, "-r") == 0)
+        outmode[3] = 'R';
+      else if ((*argv)[0] == '-' && (*argv)[1] >= '1' && (*argv)[1] <= '9' &&
+               (*argv)[2] == 0)
+        outmode[2] = (*argv)[1];
+      else
+        break;
+      argc--, argv++;
+    }
+    if (outmode[3] == ' ')
+        outmode[3] = 0;
+    if (argc == 0) {
+        SET_BINARY_MODE(stdin);
+        SET_BINARY_MODE(stdout);
+        if (uncompr) {
+            file = gzdopen(fileno(stdin), "rb");
+            if (file == NULL) error("can't gzdopen stdin");
+            gz_uncompress(file, stdout);
+        } else {
+            file = gzdopen(fileno(stdout), outmode);
+            if (file == NULL) error("can't gzdopen stdout");
+            gz_compress(stdin, file);
+        }
+    } else {
+        if (copyout) {
+            SET_BINARY_MODE(stdout);
+        }
+        do {
+            if (uncompr) {
+                if (copyout) {
+                    file = gzopen(*argv, "rb");
+                    if (file == NULL)
+                        fprintf(stderr, "%s: can't gzopen %s\n", prog, *argv);
+                    else
+                        gz_uncompress(file, stdout);
+                } else {
+                    file_uncompress(*argv);
+                }
+            } else {
+                if (copyout) {
+                    FILE * in = fopen(*argv, "rb");
+
+                    if (in == NULL) {
+                        perror(*argv);
+                    } else {
+                        file = gzdopen(fileno(stdout), outmode);
+                        if (file == NULL) error("can't gzdopen stdout");
+
+                        gz_compress(in, file);
+                    }
+
+                } else {
+                    file_compress(*argv, outmode);
+                }
+            }
+        } while (argv++, --argc);
+    }
+    return 0;
+}

ADDED   3rd_party/zlib/treebuild.xml
Index: 3rd_party/zlib/treebuild.xml
==================================================================
--- 3rd_party/zlib/treebuild.xml
+++ 3rd_party/zlib/treebuild.xml
@@ -0,0 +1,116 @@
+<?xml version="1.0" ?>
+<package name="zlib" version="1.2.11">
+    <library name="zlib" dlversion="1.2.11" dlname="z">
+	<property name="description"> zip compression library </property>
+	<property name="include-target-dir" value="$(@PACKAGE/install-includedir)" />
+
+	<!-- fixme: not implemented yet -->
+	<property name="compiler/c/inline" value="yes" />
+
+	<include-file name="zlib.h" scope="public" mode="644" />
+	<include-file name="zconf.h" scope="public" mode="644" />
+
+	<source name="adler32.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	</source>
+	<source name="compress.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	</source>
+	<source name="crc32.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="crc32.h" />
+	</source>
+	<source name="gzclose.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="gzguts.h" />
+	</source>
+	<source name="gzlib.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="gzguts.h" />
+	</source>
+	<source name="gzread.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="gzguts.h" />
+	</source>
+	<source name="gzwrite.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="gzguts.h" />
+	</source>
+	<source name="uncompr.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	</source>
+	<source name="deflate.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="zutil.h" />
+	    <depend name="deflate.h" />
+	</source>
+	<source name="trees.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="zutil.h" />
+	    <depend name="deflate.h" />
+	    <depend name="trees.h" />
+	</source>
+	<source name="zutil.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="zutil.h" />
+	</source>
+	<source name="inflate.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="zutil.h" />
+	    <depend name="inftrees.h" />
+	    <depend name="inflate.h" />
+	    <depend name="inffast.h" />
+	</source>
+	<source name="infback.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="zutil.h" />
+	    <depend name="inftrees.h" />
+	    <depend name="inflate.h" />
+	    <depend name="inffast.h" />
+	</source>
+	<source name="inftrees.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="zutil.h" />
+	    <depend name="inftrees.h" />
+	</source>
+	<source name="inffast.c">
+	    <depend name="zlib.h" />
+	    <depend name="zconf.h" />
+	    <depend name="zutil.h" />
+	    <depend name="inftrees.h" />
+	    <depend name="inflate.h" />
+	    <depend name="inffast.h" />
+	</source>
+    </library>
+</package>
+
+<!--
+CFLAGS=-O
+#CFLAGS=-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7
+#CFLAGS=-g -DZLIB_DEBUG
+#CFLAGS=-O3 -Wall -Wwrite-strings -Wpointer-arith -Wconversion \
+#           -Wstrict-prototypes -Wmissing-prototypes
+
+# OBJA =
+# to use the asm code: make OBJA=match.o
+#
+match.o: match.S
+	$(CPP) match.S > _match.s
+	$(CC) -c _match.s
+	mv _match.o match.o
+	rm -f _match.s
+-->

ADDED   3rd_party/zlib/trees.c
Index: 3rd_party/zlib/trees.c
==================================================================
--- 3rd_party/zlib/trees.c
+++ 3rd_party/zlib/trees.c
@@ -0,0 +1,1203 @@
+/* trees.c -- output deflated data using Huffman coding
+ * Copyright (C) 1995-2017 Jean-loup Gailly
+ * detect_data_type() function provided freely by Cosmin Truta, 2006
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/*
+ *  ALGORITHM
+ *
+ *      The "deflation" process uses several Huffman trees. The more
+ *      common source values are represented by shorter bit sequences.
+ *
+ *      Each code tree is stored in a compressed form which is itself
+ * a Huffman encoding of the lengths of all the code strings (in
+ * ascending order by source values).  The actual code strings are
+ * reconstructed from the lengths in the inflate process, as described
+ * in the deflate specification.
+ *
+ *  REFERENCES
+ *
+ *      Deutsch, L.P.,"'Deflate' Compressed Data Format Specification".
+ *      Available in ftp.uu.net:/pub/archiving/zip/doc/deflate-1.1.doc
+ *
+ *      Storer, James A.
+ *          Data Compression:  Methods and Theory, pp. 49-50.
+ *          Computer Science Press, 1988.  ISBN 0-7167-8156-5.
+ *
+ *      Sedgewick, R.
+ *          Algorithms, p290.
+ *          Addison-Wesley, 1983. ISBN 0-201-06672-6.
+ */
+
+/* @(#) $Id$ */
+
+/* #define GEN_TREES_H */
+
+#include "deflate.h"
+
+#ifdef ZLIB_DEBUG
+#  include <ctype.h>
+#endif
+
+/* ===========================================================================
+ * Constants
+ */
+
+#define MAX_BL_BITS 7
+/* Bit length codes must not exceed MAX_BL_BITS bits */
+
+#define END_BLOCK 256
+/* end of block literal code */
+
+#define REP_3_6      16
+/* repeat previous bit length 3-6 times (2 bits of repeat count) */
+
+#define REPZ_3_10    17
+/* repeat a zero length 3-10 times  (3 bits of repeat count) */
+
+#define REPZ_11_138  18
+/* repeat a zero length 11-138 times  (7 bits of repeat count) */
+
+local const int extra_lbits[LENGTH_CODES] /* extra bits for each length code */
+   = {0,0,0,0,0,0,0,0,1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,0};
+
+local const int extra_dbits[D_CODES] /* extra bits for each distance code */
+   = {0,0,0,0,1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13};
+
+local const int extra_blbits[BL_CODES]/* extra bits for each bit length code */
+   = {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,3,7};
+
+local const uch bl_order[BL_CODES]
+   = {16,17,18,0,8,7,9,6,10,5,11,4,12,3,13,2,14,1,15};
+/* The lengths of the bit length codes are sent in order of decreasing
+ * probability, to avoid transmitting the lengths for unused bit length codes.
+ */
+
+/* ===========================================================================
+ * Local data. These are initialized only once.
+ */
+
+#define DIST_CODE_LEN  512 /* see definition of array dist_code below */
+
+#if defined(GEN_TREES_H) || !defined(STDC)
+/* non ANSI compilers may not accept trees.h */
+
+local ct_data static_ltree[L_CODES+2];
+/* The static literal tree. Since the bit lengths are imposed, there is no
+ * need for the L_CODES extra codes used during heap construction. However
+ * The codes 286 and 287 are needed to build a canonical tree (see _tr_init
+ * below).
+ */
+
+local ct_data static_dtree[D_CODES];
+/* The static distance tree. (Actually a trivial tree since all codes use
+ * 5 bits.)
+ */
+
+uch _dist_code[DIST_CODE_LEN];
+/* Distance codes. The first 256 values correspond to the distances
+ * 3 .. 258, the last 256 values correspond to the top 8 bits of
+ * the 15 bit distances.
+ */
+
+uch _length_code[MAX_MATCH-MIN_MATCH+1];
+/* length code for each normalized match length (0 == MIN_MATCH) */
+
+local int base_length[LENGTH_CODES];
+/* First normalized length for each code (0 = MIN_MATCH) */
+
+local int base_dist[D_CODES];
+/* First normalized distance for each code (0 = distance of 1) */
+
+#else
+#  include "trees.h"
+#endif /* GEN_TREES_H */
+
+struct static_tree_desc_s {
+    const ct_data *static_tree;  /* static tree or NULL */
+    const intf *extra_bits;      /* extra bits for each code or NULL */
+    int     extra_base;          /* base index for extra_bits */
+    int     elems;               /* max number of elements in the tree */
+    int     max_length;          /* max bit length for the codes */
+};
+
+local const static_tree_desc  static_l_desc =
+{static_ltree, extra_lbits, LITERALS+1, L_CODES, MAX_BITS};
+
+local const static_tree_desc  static_d_desc =
+{static_dtree, extra_dbits, 0,          D_CODES, MAX_BITS};
+
+local const static_tree_desc  static_bl_desc =
+{(const ct_data *)0, extra_blbits, 0,   BL_CODES, MAX_BL_BITS};
+
+/* ===========================================================================
+ * Local (static) routines in this file.
+ */
+
+local void tr_static_init OF((void));
+local void init_block     OF((deflate_state *s));
+local void pqdownheap     OF((deflate_state *s, ct_data *tree, int k));
+local void gen_bitlen     OF((deflate_state *s, tree_desc *desc));
+local void gen_codes      OF((ct_data *tree, int max_code, ushf *bl_count));
+local void build_tree     OF((deflate_state *s, tree_desc *desc));
+local void scan_tree      OF((deflate_state *s, ct_data *tree, int max_code));
+local void send_tree      OF((deflate_state *s, ct_data *tree, int max_code));
+local int  build_bl_tree  OF((deflate_state *s));
+local void send_all_trees OF((deflate_state *s, int lcodes, int dcodes,
+                              int blcodes));
+local void compress_block OF((deflate_state *s, const ct_data *ltree,
+                              const ct_data *dtree));
+local int  detect_data_type OF((deflate_state *s));
+local unsigned bi_reverse OF((unsigned value, int length));
+local void bi_windup      OF((deflate_state *s));
+local void bi_flush       OF((deflate_state *s));
+
+#ifdef GEN_TREES_H
+local void gen_trees_header OF((void));
+#endif
+
+#ifndef ZLIB_DEBUG
+#  define send_code(s, c, tree) send_bits(s, tree[c].Code, tree[c].Len)
+   /* Send a code of the given tree. c and tree must not have side effects */
+
+#else /* !ZLIB_DEBUG */
+#  define send_code(s, c, tree) \
+     { if (z_verbose>2) fprintf(stderr,"\ncd %3d ",(c)); \
+       send_bits(s, tree[c].Code, tree[c].Len); }
+#endif
+
+/* ===========================================================================
+ * Output a short LSB first on the stream.
+ * IN assertion: there is enough room in pendingBuf.
+ */
+#define put_short(s, w) { \
+    put_byte(s, (uch)((w) & 0xff)); \
+    put_byte(s, (uch)((ush)(w) >> 8)); \
+}
+
+/* ===========================================================================
+ * Send a value on a given number of bits.
+ * IN assertion: length <= 16 and value fits in length bits.
+ */
+#ifdef ZLIB_DEBUG
+local void send_bits      OF((deflate_state *s, int value, int length));
+
+local void send_bits(s, value, length)
+    deflate_state *s;
+    int value;  /* value to send */
+    int length; /* number of bits */
+{
+    Tracevv((stderr," l %2d v %4x ", length, value));
+    Assert(length > 0 && length <= 15, "invalid length");
+    s->bits_sent += (ulg)length;
+
+    /* If not enough room in bi_buf, use (valid) bits from bi_buf and
+     * (16 - bi_valid) bits from value, leaving (width - (16-bi_valid))
+     * unused bits in value.
+     */
+    if (s->bi_valid > (int)Buf_size - length) {
+        s->bi_buf |= (ush)value << s->bi_valid;
+        put_short(s, s->bi_buf);
+        s->bi_buf = (ush)value >> (Buf_size - s->bi_valid);
+        s->bi_valid += length - Buf_size;
+    } else {
+        s->bi_buf |= (ush)value << s->bi_valid;
+        s->bi_valid += length;
+    }
+}
+#else /* !ZLIB_DEBUG */
+
+#define send_bits(s, value, length) \
+{ int len = length;\
+  if (s->bi_valid > (int)Buf_size - len) {\
+    int val = (int)value;\
+    s->bi_buf |= (ush)val << s->bi_valid;\
+    put_short(s, s->bi_buf);\
+    s->bi_buf = (ush)val >> (Buf_size - s->bi_valid);\
+    s->bi_valid += len - Buf_size;\
+  } else {\
+    s->bi_buf |= (ush)(value) << s->bi_valid;\
+    s->bi_valid += len;\
+  }\
+}
+#endif /* ZLIB_DEBUG */
+
+
+/* the arguments must not have side effects */
+
+/* ===========================================================================
+ * Initialize the various 'constant' tables.
+ */
+local void tr_static_init()
+{
+#if defined(GEN_TREES_H) || !defined(STDC)
+    static int static_init_done = 0;
+    int n;        /* iterates over tree elements */
+    int bits;     /* bit counter */
+    int length;   /* length value */
+    int code;     /* code value */
+    int dist;     /* distance index */
+    ush bl_count[MAX_BITS+1];
+    /* number of codes at each bit length for an optimal tree */
+
+    if (static_init_done) return;
+
+    /* For some embedded targets, global variables are not initialized: */
+#ifdef NO_INIT_GLOBAL_POINTERS
+    static_l_desc.static_tree = static_ltree;
+    static_l_desc.extra_bits = extra_lbits;
+    static_d_desc.static_tree = static_dtree;
+    static_d_desc.extra_bits = extra_dbits;
+    static_bl_desc.extra_bits = extra_blbits;
+#endif
+
+    /* Initialize the mapping length (0..255) -> length code (0..28) */
+    length = 0;
+    for (code = 0; code < LENGTH_CODES-1; code++) {
+        base_length[code] = length;
+        for (n = 0; n < (1<<extra_lbits[code]); n++) {
+            _length_code[length++] = (uch)code;
+        }
+    }
+    Assert (length == 256, "tr_static_init: length != 256");
+    /* Note that the length 255 (match length 258) can be represented
+     * in two different ways: code 284 + 5 bits or code 285, so we
+     * overwrite length_code[255] to use the best encoding:
+     */
+    _length_code[length-1] = (uch)code;
+
+    /* Initialize the mapping dist (0..32K) -> dist code (0..29) */
+    dist = 0;
+    for (code = 0 ; code < 16; code++) {
+        base_dist[code] = dist;
+        for (n = 0; n < (1<<extra_dbits[code]); n++) {
+            _dist_code[dist++] = (uch)code;
+        }
+    }
+    Assert (dist == 256, "tr_static_init: dist != 256");
+    dist >>= 7; /* from now on, all distances are divided by 128 */
+    for ( ; code < D_CODES; code++) {
+        base_dist[code] = dist << 7;
+        for (n = 0; n < (1<<(extra_dbits[code]-7)); n++) {
+            _dist_code[256 + dist++] = (uch)code;
+        }
+    }
+    Assert (dist == 256, "tr_static_init: 256+dist != 512");
+
+    /* Construct the codes of the static literal tree */
+    for (bits = 0; bits <= MAX_BITS; bits++) bl_count[bits] = 0;
+    n = 0;
+    while (n <= 143) static_ltree[n++].Len = 8, bl_count[8]++;
+    while (n <= 255) static_ltree[n++].Len = 9, bl_count[9]++;
+    while (n <= 279) static_ltree[n++].Len = 7, bl_count[7]++;
+    while (n <= 287) static_ltree[n++].Len = 8, bl_count[8]++;
+    /* Codes 286 and 287 do not exist, but we must include them in the
+     * tree construction to get a canonical Huffman tree (longest code
+     * all ones)
+     */
+    gen_codes((ct_data *)static_ltree, L_CODES+1, bl_count);
+
+    /* The static distance tree is trivial: */
+    for (n = 0; n < D_CODES; n++) {
+        static_dtree[n].Len = 5;
+        static_dtree[n].Code = bi_reverse((unsigned)n, 5);
+    }
+    static_init_done = 1;
+
+#  ifdef GEN_TREES_H
+    gen_trees_header();
+#  endif
+#endif /* defined(GEN_TREES_H) || !defined(STDC) */
+}
+
+/* ===========================================================================
+ * Genererate the file trees.h describing the static trees.
+ */
+#ifdef GEN_TREES_H
+#  ifndef ZLIB_DEBUG
+#    include <stdio.h>
+#  endif
+
+#  define SEPARATOR(i, last, width) \
+      ((i) == (last)? "\n};\n\n" :    \
+       ((i) % (width) == (width)-1 ? ",\n" : ", "))
+
+void gen_trees_header()
+{
+    FILE *header = fopen("trees.h", "w");
+    int i;
+
+    Assert (header != NULL, "Can't open trees.h");
+    fprintf(header,
+            "/* header created automatically with -DGEN_TREES_H */\n\n");
+
+    fprintf(header, "local const ct_data static_ltree[L_CODES+2] = {\n");
+    for (i = 0; i < L_CODES+2; i++) {
+        fprintf(header, "{{%3u},{%3u}}%s", static_ltree[i].Code,
+                static_ltree[i].Len, SEPARATOR(i, L_CODES+1, 5));
+    }
+
+    fprintf(header, "local const ct_data static_dtree[D_CODES] = {\n");
+    for (i = 0; i < D_CODES; i++) {
+        fprintf(header, "{{%2u},{%2u}}%s", static_dtree[i].Code,
+                static_dtree[i].Len, SEPARATOR(i, D_CODES-1, 5));
+    }
+
+    fprintf(header, "const uch ZLIB_INTERNAL _dist_code[DIST_CODE_LEN] = {\n");
+    for (i = 0; i < DIST_CODE_LEN; i++) {
+        fprintf(header, "%2u%s", _dist_code[i],
+                SEPARATOR(i, DIST_CODE_LEN-1, 20));
+    }
+
+    fprintf(header,
+        "const uch ZLIB_INTERNAL _length_code[MAX_MATCH-MIN_MATCH+1]= {\n");
+    for (i = 0; i < MAX_MATCH-MIN_MATCH+1; i++) {
+        fprintf(header, "%2u%s", _length_code[i],
+                SEPARATOR(i, MAX_MATCH-MIN_MATCH, 20));
+    }
+
+    fprintf(header, "local const int base_length[LENGTH_CODES] = {\n");
+    for (i = 0; i < LENGTH_CODES; i++) {
+        fprintf(header, "%1u%s", base_length[i],
+                SEPARATOR(i, LENGTH_CODES-1, 20));
+    }
+
+    fprintf(header, "local const int base_dist[D_CODES] = {\n");
+    for (i = 0; i < D_CODES; i++) {
+        fprintf(header, "%5u%s", base_dist[i],
+                SEPARATOR(i, D_CODES-1, 10));
+    }
+
+    fclose(header);
+}
+#endif /* GEN_TREES_H */
+
+/* ===========================================================================
+ * Initialize the tree data structures for a new zlib stream.
+ */
+void ZLIB_INTERNAL _tr_init(s)
+    deflate_state *s;
+{
+    tr_static_init();
+
+    s->l_desc.dyn_tree = s->dyn_ltree;
+    s->l_desc.stat_desc = &static_l_desc;
+
+    s->d_desc.dyn_tree = s->dyn_dtree;
+    s->d_desc.stat_desc = &static_d_desc;
+
+    s->bl_desc.dyn_tree = s->bl_tree;
+    s->bl_desc.stat_desc = &static_bl_desc;
+
+    s->bi_buf = 0;
+    s->bi_valid = 0;
+#ifdef ZLIB_DEBUG
+    s->compressed_len = 0L;
+    s->bits_sent = 0L;
+#endif
+
+    /* Initialize the first block of the first file: */
+    init_block(s);
+}
+
+/* ===========================================================================
+ * Initialize a new block.
+ */
+local void init_block(s)
+    deflate_state *s;
+{
+    int n; /* iterates over tree elements */
+
+    /* Initialize the trees. */
+    for (n = 0; n < L_CODES;  n++) s->dyn_ltree[n].Freq = 0;
+    for (n = 0; n < D_CODES;  n++) s->dyn_dtree[n].Freq = 0;
+    for (n = 0; n < BL_CODES; n++) s->bl_tree[n].Freq = 0;
+
+    s->dyn_ltree[END_BLOCK].Freq = 1;
+    s->opt_len = s->static_len = 0L;
+    s->last_lit = s->matches = 0;
+}
+
+#define SMALLEST 1
+/* Index within the heap array of least frequent node in the Huffman tree */
+
+
+/* ===========================================================================
+ * Remove the smallest element from the heap and recreate the heap with
+ * one less element. Updates heap and heap_len.
+ */
+#define pqremove(s, tree, top) \
+{\
+    top = s->heap[SMALLEST]; \
+    s->heap[SMALLEST] = s->heap[s->heap_len--]; \
+    pqdownheap(s, tree, SMALLEST); \
+}
+
+/* ===========================================================================
+ * Compares to subtrees, using the tree depth as tie breaker when
+ * the subtrees have equal frequency. This minimizes the worst case length.
+ */
+#define smaller(tree, n, m, depth) \
+   (tree[n].Freq < tree[m].Freq || \
+   (tree[n].Freq == tree[m].Freq && depth[n] <= depth[m]))
+
+/* ===========================================================================
+ * Restore the heap property by moving down the tree starting at node k,
+ * exchanging a node with the smallest of its two sons if necessary, stopping
+ * when the heap property is re-established (each father smaller than its
+ * two sons).
+ */
+local void pqdownheap(s, tree, k)
+    deflate_state *s;
+    ct_data *tree;  /* the tree to restore */
+    int k;               /* node to move down */
+{
+    int v = s->heap[k];
+    int j = k << 1;  /* left son of k */
+    while (j <= s->heap_len) {
+        /* Set j to the smallest of the two sons: */
+        if (j < s->heap_len &&
+            smaller(tree, s->heap[j+1], s->heap[j], s->depth)) {
+            j++;
+        }
+        /* Exit if v is smaller than both sons */
+        if (smaller(tree, v, s->heap[j], s->depth)) break;
+
+        /* Exchange v with the smallest son */
+        s->heap[k] = s->heap[j];  k = j;
+
+        /* And continue down the tree, setting j to the left son of k */
+        j <<= 1;
+    }
+    s->heap[k] = v;
+}
+
+/* ===========================================================================
+ * Compute the optimal bit lengths for a tree and update the total bit length
+ * for the current block.
+ * IN assertion: the fields freq and dad are set, heap[heap_max] and
+ *    above are the tree nodes sorted by increasing frequency.
+ * OUT assertions: the field len is set to the optimal bit length, the
+ *     array bl_count contains the frequencies for each bit length.
+ *     The length opt_len is updated; static_len is also updated if stree is
+ *     not null.
+ */
+local void gen_bitlen(s, desc)
+    deflate_state *s;
+    tree_desc *desc;    /* the tree descriptor */
+{
+    ct_data *tree        = desc->dyn_tree;
+    int max_code         = desc->max_code;
+    const ct_data *stree = desc->stat_desc->static_tree;
+    const intf *extra    = desc->stat_desc->extra_bits;
+    int base             = desc->stat_desc->extra_base;
+    int max_length       = desc->stat_desc->max_length;
+    int h;              /* heap index */
+    int n, m;           /* iterate over the tree elements */
+    int bits;           /* bit length */
+    int xbits;          /* extra bits */
+    ush f;              /* frequency */
+    int overflow = 0;   /* number of elements with bit length too large */
+
+    for (bits = 0; bits <= MAX_BITS; bits++) s->bl_count[bits] = 0;
+
+    /* In a first pass, compute the optimal bit lengths (which may
+     * overflow in the case of the bit length tree).
+     */
+    tree[s->heap[s->heap_max]].Len = 0; /* root of the heap */
+
+    for (h = s->heap_max+1; h < HEAP_SIZE; h++) {
+        n = s->heap[h];
+        bits = tree[tree[n].Dad].Len + 1;
+        if (bits > max_length) bits = max_length, overflow++;
+        tree[n].Len = (ush)bits;
+        /* We overwrite tree[n].Dad which is no longer needed */
+
+        if (n > max_code) continue; /* not a leaf node */
+
+        s->bl_count[bits]++;
+        xbits = 0;
+        if (n >= base) xbits = extra[n-base];
+        f = tree[n].Freq;
+        s->opt_len += (ulg)f * (unsigned)(bits + xbits);
+        if (stree) s->static_len += (ulg)f * (unsigned)(stree[n].Len + xbits);
+    }
+    if (overflow == 0) return;
+
+    Tracev((stderr,"\nbit length overflow\n"));
+    /* This happens for example on obj2 and pic of the Calgary corpus */
+
+    /* Find the first bit length which could increase: */
+    do {
+        bits = max_length-1;
+        while (s->bl_count[bits] == 0) bits--;
+        s->bl_count[bits]--;      /* move one leaf down the tree */
+        s->bl_count[bits+1] += 2; /* move one overflow item as its brother */
+        s->bl_count[max_length]--;
+        /* The brother of the overflow item also moves one step up,
+         * but this does not affect bl_count[max_length]
+         */
+        overflow -= 2;
+    } while (overflow > 0);
+
+    /* Now recompute all bit lengths, scanning in increasing frequency.
+     * h is still equal to HEAP_SIZE. (It is simpler to reconstruct all
+     * lengths instead of fixing only the wrong ones. This idea is taken
+     * from 'ar' written by Haruhiko Okumura.)
+     */
+    for (bits = max_length; bits != 0; bits--) {
+        n = s->bl_count[bits];
+        while (n != 0) {
+            m = s->heap[--h];
+            if (m > max_code) continue;
+            if ((unsigned) tree[m].Len != (unsigned) bits) {
+                Tracev((stderr,"code %d bits %d->%d\n", m, tree[m].Len, bits));
+                s->opt_len += ((ulg)bits - tree[m].Len) * tree[m].Freq;
+                tree[m].Len = (ush)bits;
+            }
+            n--;
+        }
+    }
+}
+
+/* ===========================================================================
+ * Generate the codes for a given tree and bit counts (which need not be
+ * optimal).
+ * IN assertion: the array bl_count contains the bit length statistics for
+ * the given tree and the field len is set for all tree elements.
+ * OUT assertion: the field code is set for all tree elements of non
+ *     zero code length.
+ */
+local void gen_codes (tree, max_code, bl_count)
+    ct_data *tree;             /* the tree to decorate */
+    int max_code;              /* largest code with non zero frequency */
+    ushf *bl_count;            /* number of codes at each bit length */
+{
+    ush next_code[MAX_BITS+1]; /* next code value for each bit length */
+    unsigned code = 0;         /* running code value */
+    int bits;                  /* bit index */
+    int n;                     /* code index */
+
+    /* The distribution counts are first used to generate the code values
+     * without bit reversal.
+     */
+    for (bits = 1; bits <= MAX_BITS; bits++) {
+        code = (code + bl_count[bits-1]) << 1;
+        next_code[bits] = (ush)code;
+    }
+    /* Check that the bit counts in bl_count are consistent. The last code
+     * must be all ones.
+     */
+    Assert (code + bl_count[MAX_BITS]-1 == (1<<MAX_BITS)-1,
+            "inconsistent bit counts");
+    Tracev((stderr,"\ngen_codes: max_code %d ", max_code));
+
+    for (n = 0;  n <= max_code; n++) {
+        int len = tree[n].Len;
+        if (len == 0) continue;
+        /* Now reverse the bits */
+        tree[n].Code = (ush)bi_reverse(next_code[len]++, len);
+
+        Tracecv(tree != static_ltree, (stderr,"\nn %3d %c l %2d c %4x (%x) ",
+             n, (isgraph(n) ? n : ' '), len, tree[n].Code, next_code[len]-1));
+    }
+}
+
+/* ===========================================================================
+ * Construct one Huffman tree and assigns the code bit strings and lengths.
+ * Update the total bit length for the current block.
+ * IN assertion: the field freq is set for all tree elements.
+ * OUT assertions: the fields len and code are set to the optimal bit length
+ *     and corresponding code. The length opt_len is updated; static_len is
+ *     also updated if stree is not null. The field max_code is set.
+ */
+local void build_tree(s, desc)
+    deflate_state *s;
+    tree_desc *desc; /* the tree descriptor */
+{
+    ct_data *tree         = desc->dyn_tree;
+    const ct_data *stree  = desc->stat_desc->static_tree;
+    int elems             = desc->stat_desc->elems;
+    int n, m;          /* iterate over heap elements */
+    int max_code = -1; /* largest code with non zero frequency */
+    int node;          /* new node being created */
+
+    /* Construct the initial heap, with least frequent element in
+     * heap[SMALLEST]. The sons of heap[n] are heap[2*n] and heap[2*n+1].
+     * heap[0] is not used.
+     */
+    s->heap_len = 0, s->heap_max = HEAP_SIZE;
+
+    for (n = 0; n < elems; n++) {
+        if (tree[n].Freq != 0) {
+            s->heap[++(s->heap_len)] = max_code = n;
+            s->depth[n] = 0;
+        } else {
+            tree[n].Len = 0;
+        }
+    }
+
+    /* The pkzip format requires that at least one distance code exists,
+     * and that at least one bit should be sent even if there is only one
+     * possible code. So to avoid special checks later on we force at least
+     * two codes of non zero frequency.
+     */
+    while (s->heap_len < 2) {
+        node = s->heap[++(s->heap_len)] = (max_code < 2 ? ++max_code : 0);
+        tree[node].Freq = 1;
+        s->depth[node] = 0;
+        s->opt_len--; if (stree) s->static_len -= stree[node].Len;
+        /* node is 0 or 1 so it does not have extra bits */
+    }
+    desc->max_code = max_code;
+
+    /* The elements heap[heap_len/2+1 .. heap_len] are leaves of the tree,
+     * establish sub-heaps of increasing lengths:
+     */
+    for (n = s->heap_len/2; n >= 1; n--) pqdownheap(s, tree, n);
+
+    /* Construct the Huffman tree by repeatedly combining the least two
+     * frequent nodes.
+     */
+    node = elems;              /* next internal node of the tree */
+    do {
+        pqremove(s, tree, n);  /* n = node of least frequency */
+        m = s->heap[SMALLEST]; /* m = node of next least frequency */
+
+        s->heap[--(s->heap_max)] = n; /* keep the nodes sorted by frequency */
+        s->heap[--(s->heap_max)] = m;
+
+        /* Create a new node father of n and m */
+        tree[node].Freq = tree[n].Freq + tree[m].Freq;
+        s->depth[node] = (uch)((s->depth[n] >= s->depth[m] ?
+                                s->depth[n] : s->depth[m]) + 1);
+        tree[n].Dad = tree[m].Dad = (ush)node;
+#ifdef DUMP_BL_TREE
+        if (tree == s->bl_tree) {
+            fprintf(stderr,"\nnode %d(%d), sons %d(%d) %d(%d)",
+                    node, tree[node].Freq, n, tree[n].Freq, m, tree[m].Freq);
+        }
+#endif
+        /* and insert the new node in the heap */
+        s->heap[SMALLEST] = node++;
+        pqdownheap(s, tree, SMALLEST);
+
+    } while (s->heap_len >= 2);
+
+    s->heap[--(s->heap_max)] = s->heap[SMALLEST];
+
+    /* At this point, the fields freq and dad are set. We can now
+     * generate the bit lengths.
+     */
+    gen_bitlen(s, (tree_desc *)desc);
+
+    /* The field len is now set, we can generate the bit codes */
+    gen_codes ((ct_data *)tree, max_code, s->bl_count);
+}
+
+/* ===========================================================================
+ * Scan a literal or distance tree to determine the frequencies of the codes
+ * in the bit length tree.
+ */
+local void scan_tree (s, tree, max_code)
+    deflate_state *s;
+    ct_data *tree;   /* the tree to be scanned */
+    int max_code;    /* and its largest code of non zero frequency */
+{
+    int n;                     /* iterates over all tree elements */
+    int prevlen = -1;          /* last emitted length */
+    int curlen;                /* length of current code */
+    int nextlen = tree[0].Len; /* length of next code */
+    int count = 0;             /* repeat count of the current code */
+    int max_count = 7;         /* max repeat count */
+    int min_count = 4;         /* min repeat count */
+
+    if (nextlen == 0) max_count = 138, min_count = 3;
+    tree[max_code+1].Len = (ush)0xffff; /* guard */
+
+    for (n = 0; n <= max_code; n++) {
+        curlen = nextlen; nextlen = tree[n+1].Len;
+        if (++count < max_count && curlen == nextlen) {
+            continue;
+        } else if (count < min_count) {
+            s->bl_tree[curlen].Freq += count;
+        } else if (curlen != 0) {
+            if (curlen != prevlen) s->bl_tree[curlen].Freq++;
+            s->bl_tree[REP_3_6].Freq++;
+        } else if (count <= 10) {
+            s->bl_tree[REPZ_3_10].Freq++;
+        } else {
+            s->bl_tree[REPZ_11_138].Freq++;
+        }
+        count = 0; prevlen = curlen;
+        if (nextlen == 0) {
+            max_count = 138, min_count = 3;
+        } else if (curlen == nextlen) {
+            max_count = 6, min_count = 3;
+        } else {
+            max_count = 7, min_count = 4;
+        }
+    }
+}
+
+/* ===========================================================================
+ * Send a literal or distance tree in compressed form, using the codes in
+ * bl_tree.
+ */
+local void send_tree (s, tree, max_code)
+    deflate_state *s;
+    ct_data *tree; /* the tree to be scanned */
+    int max_code;       /* and its largest code of non zero frequency */
+{
+    int n;                     /* iterates over all tree elements */
+    int prevlen = -1;          /* last emitted length */
+    int curlen;                /* length of current code */
+    int nextlen = tree[0].Len; /* length of next code */
+    int count = 0;             /* repeat count of the current code */
+    int max_count = 7;         /* max repeat count */
+    int min_count = 4;         /* min repeat count */
+
+    /* tree[max_code+1].Len = -1; */  /* guard already set */
+    if (nextlen == 0) max_count = 138, min_count = 3;
+
+    for (n = 0; n <= max_code; n++) {
+        curlen = nextlen; nextlen = tree[n+1].Len;
+        if (++count < max_count && curlen == nextlen) {
+            continue;
+        } else if (count < min_count) {
+            do { send_code(s, curlen, s->bl_tree); } while (--count != 0);
+
+        } else if (curlen != 0) {
+            if (curlen != prevlen) {
+                send_code(s, curlen, s->bl_tree); count--;
+            }
+            Assert(count >= 3 && count <= 6, " 3_6?");
+            send_code(s, REP_3_6, s->bl_tree); send_bits(s, count-3, 2);
+
+        } else if (count <= 10) {
+            send_code(s, REPZ_3_10, s->bl_tree); send_bits(s, count-3, 3);
+
+        } else {
+            send_code(s, REPZ_11_138, s->bl_tree); send_bits(s, count-11, 7);
+        }
+        count = 0; prevlen = curlen;
+        if (nextlen == 0) {
+            max_count = 138, min_count = 3;
+        } else if (curlen == nextlen) {
+            max_count = 6, min_count = 3;
+        } else {
+            max_count = 7, min_count = 4;
+        }
+    }
+}
+
+/* ===========================================================================
+ * Construct the Huffman tree for the bit lengths and return the index in
+ * bl_order of the last bit length code to send.
+ */
+local int build_bl_tree(s)
+    deflate_state *s;
+{
+    int max_blindex;  /* index of last bit length code of non zero freq */
+
+    /* Determine the bit length frequencies for literal and distance trees */
+    scan_tree(s, (ct_data *)s->dyn_ltree, s->l_desc.max_code);
+    scan_tree(s, (ct_data *)s->dyn_dtree, s->d_desc.max_code);
+
+    /* Build the bit length tree: */
+    build_tree(s, (tree_desc *)(&(s->bl_desc)));
+    /* opt_len now includes the length of the tree representations, except
+     * the lengths of the bit lengths codes and the 5+5+4 bits for the counts.
+     */
+
+    /* Determine the number of bit length codes to send. The pkzip format
+     * requires that at least 4 bit length codes be sent. (appnote.txt says
+     * 3 but the actual value used is 4.)
+     */
+    for (max_blindex = BL_CODES-1; max_blindex >= 3; max_blindex--) {
+        if (s->bl_tree[bl_order[max_blindex]].Len != 0) break;
+    }
+    /* Update opt_len to include the bit length tree and counts */
+    s->opt_len += 3*((ulg)max_blindex+1) + 5+5+4;
+    Tracev((stderr, "\ndyn trees: dyn %ld, stat %ld",
+            s->opt_len, s->static_len));
+
+    return max_blindex;
+}
+
+/* ===========================================================================
+ * Send the header for a block using dynamic Huffman trees: the counts, the
+ * lengths of the bit length codes, the literal tree and the distance tree.
+ * IN assertion: lcodes >= 257, dcodes >= 1, blcodes >= 4.
+ */
+local void send_all_trees(s, lcodes, dcodes, blcodes)
+    deflate_state *s;
+    int lcodes, dcodes, blcodes; /* number of codes for each tree */
+{
+    int rank;                    /* index in bl_order */
+
+    Assert (lcodes >= 257 && dcodes >= 1 && blcodes >= 4, "not enough codes");
+    Assert (lcodes <= L_CODES && dcodes <= D_CODES && blcodes <= BL_CODES,
+            "too many codes");
+    Tracev((stderr, "\nbl counts: "));
+    send_bits(s, lcodes-257, 5); /* not +255 as stated in appnote.txt */
+    send_bits(s, dcodes-1,   5);
+    send_bits(s, blcodes-4,  4); /* not -3 as stated in appnote.txt */
+    for (rank = 0; rank < blcodes; rank++) {
+        Tracev((stderr, "\nbl code %2d ", bl_order[rank]));
+        send_bits(s, s->bl_tree[bl_order[rank]].Len, 3);
+    }
+    Tracev((stderr, "\nbl tree: sent %ld", s->bits_sent));
+
+    send_tree(s, (ct_data *)s->dyn_ltree, lcodes-1); /* literal tree */
+    Tracev((stderr, "\nlit tree: sent %ld", s->bits_sent));
+
+    send_tree(s, (ct_data *)s->dyn_dtree, dcodes-1); /* distance tree */
+    Tracev((stderr, "\ndist tree: sent %ld", s->bits_sent));
+}
+
+/* ===========================================================================
+ * Send a stored block
+ */
+void ZLIB_INTERNAL _tr_stored_block(s, buf, stored_len, last)
+    deflate_state *s;
+    charf *buf;       /* input block */
+    ulg stored_len;   /* length of input block */
+    int last;         /* one if this is the last block for a file */
+{
+    send_bits(s, (STORED_BLOCK<<1)+last, 3);    /* send block type */
+    bi_windup(s);        /* align on byte boundary */
+    put_short(s, (ush)stored_len);
+    put_short(s, (ush)~stored_len);
+    zmemcpy(s->pending_buf + s->pending, (Bytef *)buf, stored_len);
+    s->pending += stored_len;
+#ifdef ZLIB_DEBUG
+    s->compressed_len = (s->compressed_len + 3 + 7) & (ulg)~7L;
+    s->compressed_len += (stored_len + 4) << 3;
+    s->bits_sent += 2*16;
+    s->bits_sent += stored_len<<3;
+#endif
+}
+
+/* ===========================================================================
+ * Flush the bits in the bit buffer to pending output (leaves at most 7 bits)
+ */
+void ZLIB_INTERNAL _tr_flush_bits(s)
+    deflate_state *s;
+{
+    bi_flush(s);
+}
+
+/* ===========================================================================
+ * Send one empty static block to give enough lookahead for inflate.
+ * This takes 10 bits, of which 7 may remain in the bit buffer.
+ */
+void ZLIB_INTERNAL _tr_align(s)
+    deflate_state *s;
+{
+    send_bits(s, STATIC_TREES<<1, 3);
+    send_code(s, END_BLOCK, static_ltree);
+#ifdef ZLIB_DEBUG
+    s->compressed_len += 10L; /* 3 for block type, 7 for EOB */
+#endif
+    bi_flush(s);
+}
+
+/* ===========================================================================
+ * Determine the best encoding for the current block: dynamic trees, static
+ * trees or store, and write out the encoded block.
+ */
+void ZLIB_INTERNAL _tr_flush_block(s, buf, stored_len, last)
+    deflate_state *s;
+    charf *buf;       /* input block, or NULL if too old */
+    ulg stored_len;   /* length of input block */
+    int last;         /* one if this is the last block for a file */
+{
+    ulg opt_lenb, static_lenb; /* opt_len and static_len in bytes */
+    int max_blindex = 0;  /* index of last bit length code of non zero freq */
+
+    /* Build the Huffman trees unless a stored block is forced */
+    if (s->level > 0) {
+
+        /* Check if the file is binary or text */
+        if (s->strm->data_type == Z_UNKNOWN)
+            s->strm->data_type = detect_data_type(s);
+
+        /* Construct the literal and distance trees */
+        build_tree(s, (tree_desc *)(&(s->l_desc)));
+        Tracev((stderr, "\nlit data: dyn %ld, stat %ld", s->opt_len,
+                s->static_len));
+
+        build_tree(s, (tree_desc *)(&(s->d_desc)));
+        Tracev((stderr, "\ndist data: dyn %ld, stat %ld", s->opt_len,
+                s->static_len));
+        /* At this point, opt_len and static_len are the total bit lengths of
+         * the compressed block data, excluding the tree representations.
+         */
+
+        /* Build the bit length tree for the above two trees, and get the index
+         * in bl_order of the last bit length code to send.
+         */
+        max_blindex = build_bl_tree(s);
+
+        /* Determine the best encoding. Compute the block lengths in bytes. */
+        opt_lenb = (s->opt_len+3+7)>>3;
+        static_lenb = (s->static_len+3+7)>>3;
+
+        Tracev((stderr, "\nopt %lu(%lu) stat %lu(%lu) stored %lu lit %u ",
+                opt_lenb, s->opt_len, static_lenb, s->static_len, stored_len,
+                s->last_lit));
+
+        if (static_lenb <= opt_lenb) opt_lenb = static_lenb;
+
+    } else {
+        Assert(buf != (char*)0, "lost buf");
+        opt_lenb = static_lenb = stored_len + 5; /* force a stored block */
+    }
+
+#ifdef FORCE_STORED
+    if (buf != (char*)0) { /* force stored block */
+#else
+    if (stored_len+4 <= opt_lenb && buf != (char*)0) {
+                       /* 4: two words for the lengths */
+#endif
+        /* The test buf != NULL is only necessary if LIT_BUFSIZE > WSIZE.
+         * Otherwise we can't have processed more than WSIZE input bytes since
+         * the last block flush, because compression would have been
+         * successful. If LIT_BUFSIZE <= WSIZE, it is never too late to
+         * transform a block into a stored block.
+         */
+        _tr_stored_block(s, buf, stored_len, last);
+
+#ifdef FORCE_STATIC
+    } else if (static_lenb >= 0) { /* force static trees */
+#else
+    } else if (s->strategy == Z_FIXED || static_lenb == opt_lenb) {
+#endif
+        send_bits(s, (STATIC_TREES<<1)+last, 3);
+        compress_block(s, (const ct_data *)static_ltree,
+                       (const ct_data *)static_dtree);
+#ifdef ZLIB_DEBUG
+        s->compressed_len += 3 + s->static_len;
+#endif
+    } else {
+        send_bits(s, (DYN_TREES<<1)+last, 3);
+        send_all_trees(s, s->l_desc.max_code+1, s->d_desc.max_code+1,
+                       max_blindex+1);
+        compress_block(s, (const ct_data *)s->dyn_ltree,
+                       (const ct_data *)s->dyn_dtree);
+#ifdef ZLIB_DEBUG
+        s->compressed_len += 3 + s->opt_len;
+#endif
+    }
+    Assert (s->compressed_len == s->bits_sent, "bad compressed size");
+    /* The above check is made mod 2^32, for files larger than 512 MB
+     * and uLong implemented on 32 bits.
+     */
+    init_block(s);
+
+    if (last) {
+        bi_windup(s);
+#ifdef ZLIB_DEBUG
+        s->compressed_len += 7;  /* align on byte boundary */
+#endif
+    }
+    Tracev((stderr,"\ncomprlen %lu(%lu) ", s->compressed_len>>3,
+           s->compressed_len-7*last));
+}
+
+/* ===========================================================================
+ * Save the match info and tally the frequency counts. Return true if
+ * the current block must be flushed.
+ */
+int ZLIB_INTERNAL _tr_tally (s, dist, lc)
+    deflate_state *s;
+    unsigned dist;  /* distance of matched string */
+    unsigned lc;    /* match length-MIN_MATCH or unmatched char (if dist==0) */
+{
+    s->d_buf[s->last_lit] = (ush)dist;
+    s->l_buf[s->last_lit++] = (uch)lc;
+    if (dist == 0) {
+        /* lc is the unmatched char */
+        s->dyn_ltree[lc].Freq++;
+    } else {
+        s->matches++;
+        /* Here, lc is the match length - MIN_MATCH */
+        dist--;             /* dist = match distance - 1 */
+        Assert((ush)dist < (ush)MAX_DIST(s) &&
+               (ush)lc <= (ush)(MAX_MATCH-MIN_MATCH) &&
+               (ush)d_code(dist) < (ush)D_CODES,  "_tr_tally: bad match");
+
+        s->dyn_ltree[_length_code[lc]+LITERALS+1].Freq++;
+        s->dyn_dtree[d_code(dist)].Freq++;
+    }
+
+#ifdef TRUNCATE_BLOCK
+    /* Try to guess if it is profitable to stop the current block here */
+    if ((s->last_lit & 0x1fff) == 0 && s->level > 2) {
+        /* Compute an upper bound for the compressed length */
+        ulg out_length = (ulg)s->last_lit*8L;
+        ulg in_length = (ulg)((long)s->strstart - s->block_start);
+        int dcode;
+        for (dcode = 0; dcode < D_CODES; dcode++) {
+            out_length += (ulg)s->dyn_dtree[dcode].Freq *
+                (5L+extra_dbits[dcode]);
+        }
+        out_length >>= 3;
+        Tracev((stderr,"\nlast_lit %u, in %ld, out ~%ld(%ld%%) ",
+               s->last_lit, in_length, out_length,
+               100L - out_length*100L/in_length));
+        if (s->matches < s->last_lit/2 && out_length < in_length/2) return 1;
+    }
+#endif
+    return (s->last_lit == s->lit_bufsize-1);
+    /* We avoid equality with lit_bufsize because of wraparound at 64K
+     * on 16 bit machines and because stored blocks are restricted to
+     * 64K-1 bytes.
+     */
+}
+
+/* ===========================================================================
+ * Send the block data compressed using the given Huffman trees
+ */
+local void compress_block(s, ltree, dtree)
+    deflate_state *s;
+    const ct_data *ltree; /* literal tree */
+    const ct_data *dtree; /* distance tree */
+{
+    unsigned dist;      /* distance of matched string */
+    int lc;             /* match length or unmatched char (if dist == 0) */
+    unsigned lx = 0;    /* running index in l_buf */
+    unsigned code;      /* the code to send */
+    int extra;          /* number of extra bits to send */
+
+    if (s->last_lit != 0) do {
+        dist = s->d_buf[lx];
+        lc = s->l_buf[lx++];
+        if (dist == 0) {
+            send_code(s, lc, ltree); /* send a literal byte */
+            Tracecv(isgraph(lc), (stderr," '%c' ", lc));
+        } else {
+            /* Here, lc is the match length - MIN_MATCH */
+            code = _length_code[lc];
+            send_code(s, code+LITERALS+1, ltree); /* send the length code */
+            extra = extra_lbits[code];
+            if (extra != 0) {
+                lc -= base_length[code];
+                send_bits(s, lc, extra);       /* send the extra length bits */
+            }
+            dist--; /* dist is now the match distance - 1 */
+            code = d_code(dist);
+            Assert (code < D_CODES, "bad d_code");
+
+            send_code(s, code, dtree);       /* send the distance code */
+            extra = extra_dbits[code];
+            if (extra != 0) {
+                dist -= (unsigned)base_dist[code];
+                send_bits(s, dist, extra);   /* send the extra distance bits */
+            }
+        } /* literal or match pair ? */
+
+        /* Check that the overlay between pending_buf and d_buf+l_buf is ok: */
+        Assert((uInt)(s->pending) < s->lit_bufsize + 2*lx,
+               "pendingBuf overflow");
+
+    } while (lx < s->last_lit);
+
+    send_code(s, END_BLOCK, ltree);
+}
+
+/* ===========================================================================
+ * Check if the data type is TEXT or BINARY, using the following algorithm:
+ * - TEXT if the two conditions below are satisfied:
+ *    a) There are no non-portable control characters belonging to the
+ *       "black list" (0..6, 14..25, 28..31).
+ *    b) There is at least one printable character belonging to the
+ *       "white list" (9 {TAB}, 10 {LF}, 13 {CR}, 32..255).
+ * - BINARY otherwise.
+ * - The following partially-portable control characters form a
+ *   "gray list" that is ignored in this detection algorithm:
+ *   (7 {BEL}, 8 {BS}, 11 {VT}, 12 {FF}, 26 {SUB}, 27 {ESC}).
+ * IN assertion: the fields Freq of dyn_ltree are set.
+ */
+local int detect_data_type(s)
+    deflate_state *s;
+{
+    /* black_mask is the bit mask of black-listed bytes
+     * set bits 0..6, 14..25, and 28..31
+     * 0xf3ffc07f = binary 11110011111111111100000001111111
+     */
+    unsigned long black_mask = 0xf3ffc07fUL;
+    int n;
+
+    /* Check for non-textual ("black-listed") bytes. */
+    for (n = 0; n <= 31; n++, black_mask >>= 1)
+        if ((black_mask & 1) && (s->dyn_ltree[n].Freq != 0))
+            return Z_BINARY;
+
+    /* Check for textual ("white-listed") bytes. */
+    if (s->dyn_ltree[9].Freq != 0 || s->dyn_ltree[10].Freq != 0
+            || s->dyn_ltree[13].Freq != 0)
+        return Z_TEXT;
+    for (n = 32; n < LITERALS; n++)
+        if (s->dyn_ltree[n].Freq != 0)
+            return Z_TEXT;
+
+    /* There are no "black-listed" or "white-listed" bytes:
+     * this stream either is empty or has tolerated ("gray-listed") bytes only.
+     */
+    return Z_BINARY;
+}
+
+/* ===========================================================================
+ * Reverse the first len bits of a code, using straightforward code (a faster
+ * method would use a table)
+ * IN assertion: 1 <= len <= 15
+ */
+local unsigned bi_reverse(code, len)
+    unsigned code; /* the value to invert */
+    int len;       /* its bit length */
+{
+    register unsigned res = 0;
+    do {
+        res |= code & 1;
+        code >>= 1, res <<= 1;
+    } while (--len > 0);
+    return res >> 1;
+}
+
+/* ===========================================================================
+ * Flush the bit buffer, keeping at most 7 bits in it.
+ */
+local void bi_flush(s)
+    deflate_state *s;
+{
+    if (s->bi_valid == 16) {
+        put_short(s, s->bi_buf);
+        s->bi_buf = 0;
+        s->bi_valid = 0;
+    } else if (s->bi_valid >= 8) {
+        put_byte(s, (Byte)s->bi_buf);
+        s->bi_buf >>= 8;
+        s->bi_valid -= 8;
+    }
+}
+
+/* ===========================================================================
+ * Flush the bit buffer and align the output on a byte boundary
+ */
+local void bi_windup(s)
+    deflate_state *s;
+{
+    if (s->bi_valid > 8) {
+        put_short(s, s->bi_buf);
+    } else if (s->bi_valid > 0) {
+        put_byte(s, (Byte)s->bi_buf);
+    }
+    s->bi_buf = 0;
+    s->bi_valid = 0;
+#ifdef ZLIB_DEBUG
+    s->bits_sent = (s->bits_sent+7) & ~7;
+#endif
+}

ADDED   3rd_party/zlib/trees.h
Index: 3rd_party/zlib/trees.h
==================================================================
--- 3rd_party/zlib/trees.h
+++ 3rd_party/zlib/trees.h
@@ -0,0 +1,128 @@
+/* header created automatically with -DGEN_TREES_H */
+
+local const ct_data static_ltree[L_CODES+2] = {
+{{ 12},{  8}}, {{140},{  8}}, {{ 76},{  8}}, {{204},{  8}}, {{ 44},{  8}},
+{{172},{  8}}, {{108},{  8}}, {{236},{  8}}, {{ 28},{  8}}, {{156},{  8}},
+{{ 92},{  8}}, {{220},{  8}}, {{ 60},{  8}}, {{188},{  8}}, {{124},{  8}},
+{{252},{  8}}, {{  2},{  8}}, {{130},{  8}}, {{ 66},{  8}}, {{194},{  8}},
+{{ 34},{  8}}, {{162},{  8}}, {{ 98},{  8}}, {{226},{  8}}, {{ 18},{  8}},
+{{146},{  8}}, {{ 82},{  8}}, {{210},{  8}}, {{ 50},{  8}}, {{178},{  8}},
+{{114},{  8}}, {{242},{  8}}, {{ 10},{  8}}, {{138},{  8}}, {{ 74},{  8}},
+{{202},{  8}}, {{ 42},{  8}}, {{170},{  8}}, {{106},{  8}}, {{234},{  8}},
+{{ 26},{  8}}, {{154},{  8}}, {{ 90},{  8}}, {{218},{  8}}, {{ 58},{  8}},
+{{186},{  8}}, {{122},{  8}}, {{250},{  8}}, {{  6},{  8}}, {{134},{  8}},
+{{ 70},{  8}}, {{198},{  8}}, {{ 38},{  8}}, {{166},{  8}}, {{102},{  8}},
+{{230},{  8}}, {{ 22},{  8}}, {{150},{  8}}, {{ 86},{  8}}, {{214},{  8}},
+{{ 54},{  8}}, {{182},{  8}}, {{118},{  8}}, {{246},{  8}}, {{ 14},{  8}},
+{{142},{  8}}, {{ 78},{  8}}, {{206},{  8}}, {{ 46},{  8}}, {{174},{  8}},
+{{110},{  8}}, {{238},{  8}}, {{ 30},{  8}}, {{158},{  8}}, {{ 94},{  8}},
+{{222},{  8}}, {{ 62},{  8}}, {{190},{  8}}, {{126},{  8}}, {{254},{  8}},
+{{  1},{  8}}, {{129},{  8}}, {{ 65},{  8}}, {{193},{  8}}, {{ 33},{  8}},
+{{161},{  8}}, {{ 97},{  8}}, {{225},{  8}}, {{ 17},{  8}}, {{145},{  8}},
+{{ 81},{  8}}, {{209},{  8}}, {{ 49},{  8}}, {{177},{  8}}, {{113},{  8}},
+{{241},{  8}}, {{  9},{  8}}, {{137},{  8}}, {{ 73},{  8}}, {{201},{  8}},
+{{ 41},{  8}}, {{169},{  8}}, {{105},{  8}}, {{233},{  8}}, {{ 25},{  8}},
+{{153},{  8}}, {{ 89},{  8}}, {{217},{  8}}, {{ 57},{  8}}, {{185},{  8}},
+{{121},{  8}}, {{249},{  8}}, {{  5},{  8}}, {{133},{  8}}, {{ 69},{  8}},
+{{197},{  8}}, {{ 37},{  8}}, {{165},{  8}}, {{101},{  8}}, {{229},{  8}},
+{{ 21},{  8}}, {{149},{  8}}, {{ 85},{  8}}, {{213},{  8}}, {{ 53},{  8}},
+{{181},{  8}}, {{117},{  8}}, {{245},{  8}}, {{ 13},{  8}}, {{141},{  8}},
+{{ 77},{  8}}, {{205},{  8}}, {{ 45},{  8}}, {{173},{  8}}, {{109},{  8}},
+{{237},{  8}}, {{ 29},{  8}}, {{157},{  8}}, {{ 93},{  8}}, {{221},{  8}},
+{{ 61},{  8}}, {{189},{  8}}, {{125},{  8}}, {{253},{  8}}, {{ 19},{  9}},
+{{275},{  9}}, {{147},{  9}}, {{403},{  9}}, {{ 83},{  9}}, {{339},{  9}},
+{{211},{  9}}, {{467},{  9}}, {{ 51},{  9}}, {{307},{  9}}, {{179},{  9}},
+{{435},{  9}}, {{115},{  9}}, {{371},{  9}}, {{243},{  9}}, {{499},{  9}},
+{{ 11},{  9}}, {{267},{  9}}, {{139},{  9}}, {{395},{  9}}, {{ 75},{  9}},
+{{331},{  9}}, {{203},{  9}}, {{459},{  9}}, {{ 43},{  9}}, {{299},{  9}},
+{{171},{  9}}, {{427},{  9}}, {{107},{  9}}, {{363},{  9}}, {{235},{  9}},
+{{491},{  9}}, {{ 27},{  9}}, {{283},{  9}}, {{155},{  9}}, {{411},{  9}},
+{{ 91},{  9}}, {{347},{  9}}, {{219},{  9}}, {{475},{  9}}, {{ 59},{  9}},
+{{315},{  9}}, {{187},{  9}}, {{443},{  9}}, {{123},{  9}}, {{379},{  9}},
+{{251},{  9}}, {{507},{  9}}, {{  7},{  9}}, {{263},{  9}}, {{135},{  9}},
+{{391},{  9}}, {{ 71},{  9}}, {{327},{  9}}, {{199},{  9}}, {{455},{  9}},
+{{ 39},{  9}}, {{295},{  9}}, {{167},{  9}}, {{423},{  9}}, {{103},{  9}},
+{{359},{  9}}, {{231},{  9}}, {{487},{  9}}, {{ 23},{  9}}, {{279},{  9}},
+{{151},{  9}}, {{407},{  9}}, {{ 87},{  9}}, {{343},{  9}}, {{215},{  9}},
+{{471},{  9}}, {{ 55},{  9}}, {{311},{  9}}, {{183},{  9}}, {{439},{  9}},
+{{119},{  9}}, {{375},{  9}}, {{247},{  9}}, {{503},{  9}}, {{ 15},{  9}},
+{{271},{  9}}, {{143},{  9}}, {{399},{  9}}, {{ 79},{  9}}, {{335},{  9}},
+{{207},{  9}}, {{463},{  9}}, {{ 47},{  9}}, {{303},{  9}}, {{175},{  9}},
+{{431},{  9}}, {{111},{  9}}, {{367},{  9}}, {{239},{  9}}, {{495},{  9}},
+{{ 31},{  9}}, {{287},{  9}}, {{159},{  9}}, {{415},{  9}}, {{ 95},{  9}},
+{{351},{  9}}, {{223},{  9}}, {{479},{  9}}, {{ 63},{  9}}, {{319},{  9}},
+{{191},{  9}}, {{447},{  9}}, {{127},{  9}}, {{383},{  9}}, {{255},{  9}},
+{{511},{  9}}, {{  0},{  7}}, {{ 64},{  7}}, {{ 32},{  7}}, {{ 96},{  7}},
+{{ 16},{  7}}, {{ 80},{  7}}, {{ 48},{  7}}, {{112},{  7}}, {{  8},{  7}},
+{{ 72},{  7}}, {{ 40},{  7}}, {{104},{  7}}, {{ 24},{  7}}, {{ 88},{  7}},
+{{ 56},{  7}}, {{120},{  7}}, {{  4},{  7}}, {{ 68},{  7}}, {{ 36},{  7}},
+{{100},{  7}}, {{ 20},{  7}}, {{ 84},{  7}}, {{ 52},{  7}}, {{116},{  7}},
+{{  3},{  8}}, {{131},{  8}}, {{ 67},{  8}}, {{195},{  8}}, {{ 35},{  8}},
+{{163},{  8}}, {{ 99},{  8}}, {{227},{  8}}
+};
+
+local const ct_data static_dtree[D_CODES] = {
+{{ 0},{ 5}}, {{16},{ 5}}, {{ 8},{ 5}}, {{24},{ 5}}, {{ 4},{ 5}},
+{{20},{ 5}}, {{12},{ 5}}, {{28},{ 5}}, {{ 2},{ 5}}, {{18},{ 5}},
+{{10},{ 5}}, {{26},{ 5}}, {{ 6},{ 5}}, {{22},{ 5}}, {{14},{ 5}},
+{{30},{ 5}}, {{ 1},{ 5}}, {{17},{ 5}}, {{ 9},{ 5}}, {{25},{ 5}},
+{{ 5},{ 5}}, {{21},{ 5}}, {{13},{ 5}}, {{29},{ 5}}, {{ 3},{ 5}},
+{{19},{ 5}}, {{11},{ 5}}, {{27},{ 5}}, {{ 7},{ 5}}, {{23},{ 5}}
+};
+
+const uch ZLIB_INTERNAL _dist_code[DIST_CODE_LEN] = {
+ 0,  1,  2,  3,  4,  4,  5,  5,  6,  6,  6,  6,  7,  7,  7,  7,  8,  8,  8,  8,
+ 8,  8,  8,  8,  9,  9,  9,  9,  9,  9,  9,  9, 10, 10, 10, 10, 10, 10, 10, 10,
+10, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,
+11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,
+12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13,
+13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13,
+13, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14,
+14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14,
+14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14,
+14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 15, 15, 15, 15, 15, 15, 15, 15,
+15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,
+15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,
+15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,  0,  0, 16, 17,
+18, 18, 19, 19, 20, 20, 20, 20, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22, 22, 22,
+23, 23, 23, 23, 23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
+24, 24, 24, 24, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
+26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26,
+26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 27,
+27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
+27, 27, 27, 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28,
+28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28,
+28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28,
+28, 28, 28, 28, 28, 28, 28, 28, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29,
+29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29,
+29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29,
+29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29
+};
+
+const uch ZLIB_INTERNAL _length_code[MAX_MATCH-MIN_MATCH+1]= {
+ 0,  1,  2,  3,  4,  5,  6,  7,  8,  8,  9,  9, 10, 10, 11, 11, 12, 12, 12, 12,
+13, 13, 13, 13, 14, 14, 14, 14, 15, 15, 15, 15, 16, 16, 16, 16, 16, 16, 16, 16,
+17, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19,
+19, 19, 19, 19, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,
+21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 22, 22, 22, 22,
+22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, 23, 23, 23, 23,
+23, 23, 23, 23, 23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
+24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
+25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
+25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 26, 26, 26, 26, 26, 26, 26, 26,
+26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26,
+26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27,
+27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 28
+};
+
+local const int base_length[LENGTH_CODES] = {
+0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, 28, 32, 40, 48, 56,
+64, 80, 96, 112, 128, 160, 192, 224, 0
+};
+
+local const int base_dist[D_CODES] = {
+    0,     1,     2,     3,     4,     6,     8,    12,    16,    24,
+   32,    48,    64,    96,   128,   192,   256,   384,   512,   768,
+ 1024,  1536,  2048,  3072,  4096,  6144,  8192, 12288, 16384, 24576
+};
+

ADDED   3rd_party/zlib/uncompr.c
Index: 3rd_party/zlib/uncompr.c
==================================================================
--- 3rd_party/zlib/uncompr.c
+++ 3rd_party/zlib/uncompr.c
@@ -0,0 +1,93 @@
+/* uncompr.c -- decompress a memory buffer
+ * Copyright (C) 1995-2003, 2010, 2014, 2016 Jean-loup Gailly, Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* @(#) $Id$ */
+
+#define ZLIB_INTERNAL
+#include "zlib.h"
+
+/* ===========================================================================
+     Decompresses the source buffer into the destination buffer.  *sourceLen is
+   the byte length of the source buffer. Upon entry, *destLen is the total size
+   of the destination buffer, which must be large enough to hold the entire
+   uncompressed data. (The size of the uncompressed data must have been saved
+   previously by the compressor and transmitted to the decompressor by some
+   mechanism outside the scope of this compression library.) Upon exit,
+   *destLen is the size of the decompressed data and *sourceLen is the number
+   of source bytes consumed. Upon return, source + *sourceLen points to the
+   first unused input byte.
+
+     uncompress returns Z_OK if success, Z_MEM_ERROR if there was not enough
+   memory, Z_BUF_ERROR if there was not enough room in the output buffer, or
+   Z_DATA_ERROR if the input data was corrupted, including if the input data is
+   an incomplete zlib stream.
+*/
+int ZEXPORT uncompress2 (dest, destLen, source, sourceLen)
+    Bytef *dest;
+    uLongf *destLen;
+    const Bytef *source;
+    uLong *sourceLen;
+{
+    z_stream stream;
+    int err;
+    const uInt max = (uInt)-1;
+    uLong len, left;
+    Byte buf[1];    /* for detection of incomplete stream when *destLen == 0 */
+
+    len = *sourceLen;
+    if (*destLen) {
+        left = *destLen;
+        *destLen = 0;
+    }
+    else {
+        left = 1;
+        dest = buf;
+    }
+
+    stream.next_in = (z_const Bytef *)source;
+    stream.avail_in = 0;
+    stream.zalloc = (alloc_func)0;
+    stream.zfree = (free_func)0;
+    stream.opaque = (voidpf)0;
+
+    err = inflateInit(&stream);
+    if (err != Z_OK) return err;
+
+    stream.next_out = dest;
+    stream.avail_out = 0;
+
+    do {
+        if (stream.avail_out == 0) {
+            stream.avail_out = left > (uLong)max ? max : (uInt)left;
+            left -= stream.avail_out;
+        }
+        if (stream.avail_in == 0) {
+            stream.avail_in = len > (uLong)max ? max : (uInt)len;
+            len -= stream.avail_in;
+        }
+        err = inflate(&stream, Z_NO_FLUSH);
+    } while (err == Z_OK);
+
+    *sourceLen -= len + stream.avail_in;
+    if (dest != buf)
+        *destLen = stream.total_out;
+    else if (stream.total_out && err == Z_BUF_ERROR)
+        left = 1;
+
+    inflateEnd(&stream);
+    return err == Z_STREAM_END ? Z_OK :
+           err == Z_NEED_DICT ? Z_DATA_ERROR  :
+           err == Z_BUF_ERROR && left + stream.avail_out ? Z_DATA_ERROR :
+           err;
+}
+
+int ZEXPORT uncompress (dest, destLen, source, sourceLen)
+    Bytef *dest;
+    uLongf *destLen;
+    const Bytef *source;
+    uLong sourceLen;
+{
+    return uncompress2(dest, destLen, source, &sourceLen);
+}

ADDED   3rd_party/zlib/watcom/watcom_f.mak
Index: 3rd_party/zlib/watcom/watcom_f.mak
==================================================================
--- 3rd_party/zlib/watcom/watcom_f.mak
+++ 3rd_party/zlib/watcom/watcom_f.mak
@@ -0,0 +1,43 @@
+# Makefile for zlib
+# OpenWatcom flat model
+# Last updated: 28-Dec-2005
+
+# To use, do "wmake -f watcom_f.mak"
+
+C_SOURCE =  adler32.c  compress.c crc32.c   deflate.c    &
+	    gzclose.c  gzlib.c    gzread.c  gzwrite.c    &
+            infback.c  inffast.c  inflate.c inftrees.c   &
+            trees.c    uncompr.c  zutil.c
+
+OBJS =      adler32.obj  compress.obj crc32.obj   deflate.obj    &
+	    gzclose.obj  gzlib.obj    gzread.obj  gzwrite.obj    &
+            infback.obj  inffast.obj  inflate.obj inftrees.obj   &
+            trees.obj    uncompr.obj  zutil.obj
+
+CC       = wcc386
+LINKER   = wcl386
+CFLAGS   = -zq -mf -3r -fp3 -s -bt=dos -oilrtfm -fr=nul -wx
+ZLIB_LIB = zlib_f.lib
+
+.C.OBJ:
+        $(CC) $(CFLAGS) $[@
+
+all: $(ZLIB_LIB) example.exe minigzip.exe
+
+$(ZLIB_LIB): $(OBJS)
+	wlib -b -c $(ZLIB_LIB) -+adler32.obj  -+compress.obj -+crc32.obj
+	wlib -b -c $(ZLIB_LIB) -+gzclose.obj  -+gzlib.obj    -+gzread.obj   -+gzwrite.obj
+        wlib -b -c $(ZLIB_LIB) -+deflate.obj  -+infback.obj
+        wlib -b -c $(ZLIB_LIB) -+inffast.obj  -+inflate.obj  -+inftrees.obj
+        wlib -b -c $(ZLIB_LIB) -+trees.obj    -+uncompr.obj  -+zutil.obj
+
+example.exe: $(ZLIB_LIB) example.obj
+	$(LINKER) -ldos32a -fe=example.exe example.obj $(ZLIB_LIB)
+
+minigzip.exe: $(ZLIB_LIB) minigzip.obj
+	$(LINKER) -ldos32a -fe=minigzip.exe minigzip.obj $(ZLIB_LIB)
+
+clean: .SYMBOLIC
+          del *.obj
+          del $(ZLIB_LIB)
+          @echo Cleaning done

ADDED   3rd_party/zlib/watcom/watcom_l.mak
Index: 3rd_party/zlib/watcom/watcom_l.mak
==================================================================
--- 3rd_party/zlib/watcom/watcom_l.mak
+++ 3rd_party/zlib/watcom/watcom_l.mak
@@ -0,0 +1,43 @@
+# Makefile for zlib
+# OpenWatcom large model
+# Last updated: 28-Dec-2005
+
+# To use, do "wmake -f watcom_l.mak"
+
+C_SOURCE =  adler32.c  compress.c crc32.c   deflate.c    &
+	    gzclose.c  gzlib.c    gzread.c  gzwrite.c    &
+            infback.c  inffast.c  inflate.c inftrees.c   &
+            trees.c    uncompr.c  zutil.c
+
+OBJS =      adler32.obj  compress.obj crc32.obj   deflate.obj    &
+	    gzclose.obj  gzlib.obj    gzread.obj  gzwrite.obj    &
+            infback.obj  inffast.obj  inflate.obj inftrees.obj   &
+            trees.obj    uncompr.obj  zutil.obj
+
+CC       = wcc
+LINKER   = wcl
+CFLAGS   = -zq -ml -s -bt=dos -oilrtfm -fr=nul -wx
+ZLIB_LIB = zlib_l.lib
+
+.C.OBJ:
+        $(CC) $(CFLAGS) $[@
+
+all: $(ZLIB_LIB) example.exe minigzip.exe
+
+$(ZLIB_LIB): $(OBJS)
+	wlib -b -c $(ZLIB_LIB) -+adler32.obj  -+compress.obj -+crc32.obj
+	wlib -b -c $(ZLIB_LIB) -+gzclose.obj  -+gzlib.obj    -+gzread.obj   -+gzwrite.obj
+        wlib -b -c $(ZLIB_LIB) -+deflate.obj  -+infback.obj
+        wlib -b -c $(ZLIB_LIB) -+inffast.obj  -+inflate.obj  -+inftrees.obj
+        wlib -b -c $(ZLIB_LIB) -+trees.obj    -+uncompr.obj  -+zutil.obj
+
+example.exe: $(ZLIB_LIB) example.obj
+	$(LINKER) -fe=example.exe example.obj $(ZLIB_LIB)
+
+minigzip.exe: $(ZLIB_LIB) minigzip.obj
+	$(LINKER) -fe=minigzip.exe minigzip.obj $(ZLIB_LIB)
+
+clean: .SYMBOLIC
+          del *.obj
+          del $(ZLIB_LIB)
+          @echo Cleaning done

ADDED   3rd_party/zlib/win32/DLL_FAQ.txt
Index: 3rd_party/zlib/win32/DLL_FAQ.txt
==================================================================
--- 3rd_party/zlib/win32/DLL_FAQ.txt
+++ 3rd_party/zlib/win32/DLL_FAQ.txt
@@ -0,0 +1,397 @@
+
+            Frequently Asked Questions about ZLIB1.DLL
+
+
+This document describes the design, the rationale, and the usage
+of the official DLL build of zlib, named ZLIB1.DLL.  If you have
+general questions about zlib, you should see the file "FAQ" found
+in the zlib distribution, or at the following location:
+  http://www.gzip.org/zlib/zlib_faq.html
+
+
+ 1. What is ZLIB1.DLL, and how can I get it?
+
+  - ZLIB1.DLL is the official build of zlib as a DLL.
+    (Please remark the character '1' in the name.)
+
+    Pointers to a precompiled ZLIB1.DLL can be found in the zlib
+    web site at:
+      http://www.zlib.net/
+
+    Applications that link to ZLIB1.DLL can rely on the following
+    specification:
+
+    * The exported symbols are exclusively defined in the source
+      files "zlib.h" and "zlib.def", found in an official zlib
+      source distribution.
+    * The symbols are exported by name, not by ordinal.
+    * The exported names are undecorated.
+    * The calling convention of functions is "C" (CDECL).
+    * The ZLIB1.DLL binary is linked to MSVCRT.DLL.
+
+    The archive in which ZLIB1.DLL is bundled contains compiled
+    test programs that must run with a valid build of ZLIB1.DLL.
+    It is recommended to download the prebuilt DLL from the zlib
+    web site, instead of building it yourself, to avoid potential
+    incompatibilities that could be introduced by your compiler
+    and build settings.  If you do build the DLL yourself, please
+    make sure that it complies with all the above requirements,
+    and it runs with the precompiled test programs, bundled with
+    the original ZLIB1.DLL distribution.
+
+    If, for any reason, you need to build an incompatible DLL,
+    please use a different file name.
+
+
+ 2. Why did you change the name of the DLL to ZLIB1.DLL?
+    What happened to the old ZLIB.DLL?
+
+  - The old ZLIB.DLL, built from zlib-1.1.4 or earlier, required
+    compilation settings that were incompatible to those used by
+    a static build.  The DLL settings were supposed to be enabled
+    by defining the macro ZLIB_DLL, before including "zlib.h".
+    Incorrect handling of this macro was silently accepted at
+    build time, resulting in two major problems:
+
+    * ZLIB_DLL was missing from the old makefile.  When building
+      the DLL, not all people added it to the build options.  In
+      consequence, incompatible incarnations of ZLIB.DLL started
+      to circulate around the net.
+
+    * When switching from using the static library to using the
+      DLL, applications had to define the ZLIB_DLL macro and
+      to recompile all the sources that contained calls to zlib
+      functions.  Failure to do so resulted in creating binaries
+      that were unable to run with the official ZLIB.DLL build.
+
+    The only possible solution that we could foresee was to make
+    a binary-incompatible change in the DLL interface, in order to
+    remove the dependency on the ZLIB_DLL macro, and to release
+    the new DLL under a different name.
+
+    We chose the name ZLIB1.DLL, where '1' indicates the major
+    zlib version number.  We hope that we will not have to break
+    the binary compatibility again, at least not as long as the
+    zlib-1.x series will last.
+
+    There is still a ZLIB_DLL macro, that can trigger a more
+    efficient build and use of the DLL, but compatibility no
+    longer dependents on it.
+
+
+ 3. Can I build ZLIB.DLL from the new zlib sources, and replace
+    an old ZLIB.DLL, that was built from zlib-1.1.4 or earlier?
+
+  - In principle, you can do it by assigning calling convention
+    keywords to the macros ZEXPORT and ZEXPORTVA.  In practice,
+    it depends on what you mean by "an old ZLIB.DLL", because the
+    old DLL exists in several mutually-incompatible versions.
+    You have to find out first what kind of calling convention is
+    being used in your particular ZLIB.DLL build, and to use the
+    same one in the new build.  If you don't know what this is all
+    about, you might be better off if you would just leave the old
+    DLL intact.
+
+
+ 4. Can I compile my application using the new zlib interface, and
+    link it to an old ZLIB.DLL, that was built from zlib-1.1.4 or
+    earlier?
+
+  - The official answer is "no"; the real answer depends again on
+    what kind of ZLIB.DLL you have.  Even if you are lucky, this
+    course of action is unreliable.
+
+    If you rebuild your application and you intend to use a newer
+    version of zlib (post- 1.1.4), it is strongly recommended to
+    link it to the new ZLIB1.DLL.
+
+
+ 5. Why are the zlib symbols exported by name, and not by ordinal?
+
+  - Although exporting symbols by ordinal is a little faster, it
+    is risky.  Any single glitch in the maintenance or use of the
+    DEF file that contains the ordinals can result in incompatible
+    builds and frustrating crashes.  Simply put, the benefits of
+    exporting symbols by ordinal do not justify the risks.
+
+    Technically, it should be possible to maintain ordinals in
+    the DEF file, and still export the symbols by name.  Ordinals
+    exist in every DLL, and even if the dynamic linking performed
+    at the DLL startup is searching for names, ordinals serve as
+    hints, for a faster name lookup.  However, if the DEF file
+    contains ordinals, the Microsoft linker automatically builds
+    an implib that will cause the executables linked to it to use
+    those ordinals, and not the names.  It is interesting to
+    notice that the GNU linker for Win32 does not suffer from this
+    problem.
+
+    It is possible to avoid the DEF file if the exported symbols
+    are accompanied by a "__declspec(dllexport)" attribute in the
+    source files.  You can do this in zlib by predefining the
+    ZLIB_DLL macro.
+
+
+ 6. I see that the ZLIB1.DLL functions use the "C" (CDECL) calling
+    convention.  Why not use the STDCALL convention?
+    STDCALL is the standard convention in Win32, and I need it in
+    my Visual Basic project!
+
+    (For readability, we use CDECL to refer to the convention
+     triggered by the "__cdecl" keyword, STDCALL to refer to
+     the convention triggered by "__stdcall", and FASTCALL to
+     refer to the convention triggered by "__fastcall".)
+
+  - Most of the native Windows API functions (without varargs) use
+    indeed the WINAPI convention (which translates to STDCALL in
+    Win32), but the standard C functions use CDECL.  If a user
+    application is intrinsically tied to the Windows API (e.g.
+    it calls native Windows API functions such as CreateFile()),
+    sometimes it makes sense to decorate its own functions with
+    WINAPI.  But if ANSI C or POSIX portability is a goal (e.g.
+    it calls standard C functions such as fopen()), it is not a
+    sound decision to request the inclusion of <windows.h>, or to
+    use non-ANSI constructs, for the sole purpose to make the user
+    functions STDCALL-able.
+
+    The functionality offered by zlib is not in the category of
+    "Windows functionality", but is more like "C functionality".
+
+    Technically, STDCALL is not bad; in fact, it is slightly
+    faster than CDECL, and it works with variable-argument
+    functions, just like CDECL.  It is unfortunate that, in spite
+    of using STDCALL in the Windows API, it is not the default
+    convention used by the C compilers that run under Windows.
+    The roots of the problem reside deep inside the unsafety of
+    the K&R-style function prototypes, where the argument types
+    are not specified; but that is another story for another day.
+
+    The remaining fact is that CDECL is the default convention.
+    Even if an explicit convention is hard-coded into the function
+    prototypes inside C headers, problems may appear.  The
+    necessity to expose the convention in users' callbacks is one
+    of these problems.
+
+    The calling convention issues are also important when using
+    zlib in other programming languages.  Some of them, like Ada
+    (GNAT) and Fortran (GNU G77), have C bindings implemented
+    initially on Unix, and relying on the C calling convention.
+    On the other hand, the pre- .NET versions of Microsoft Visual
+    Basic require STDCALL, while Borland Delphi prefers, although
+    it does not require, FASTCALL.
+
+    In fairness to all possible uses of zlib outside the C
+    programming language, we choose the default "C" convention.
+    Anyone interested in different bindings or conventions is
+    encouraged to maintain specialized projects.  The "contrib/"
+    directory from the zlib distribution already holds a couple
+    of foreign bindings, such as Ada, C++, and Delphi.
+
+
+ 7. I need a DLL for my Visual Basic project.  What can I do?
+
+  - Define the ZLIB_WINAPI macro before including "zlib.h", when
+    building both the DLL and the user application (except that
+    you don't need to define anything when using the DLL in Visual
+    Basic).  The ZLIB_WINAPI macro will switch on the WINAPI
+    (STDCALL) convention.  The name of this DLL must be different
+    than the official ZLIB1.DLL.
+
+    Gilles Vollant has contributed a build named ZLIBWAPI.DLL,
+    with the ZLIB_WINAPI macro turned on, and with the minizip
+    functionality built in.  For more information, please read
+    the notes inside "contrib/vstudio/readme.txt", found in the
+    zlib distribution.
+
+
+ 8. I need to use zlib in my Microsoft .NET project.  What can I
+    do?
+
+  - Henrik Ravn has contributed a .NET wrapper around zlib.  Look
+    into contrib/dotzlib/, inside the zlib distribution.
+
+
+ 9. If my application uses ZLIB1.DLL, should I link it to
+    MSVCRT.DLL?  Why?
+
+  - It is not required, but it is recommended to link your
+    application to MSVCRT.DLL, if it uses ZLIB1.DLL.
+
+    The executables (.EXE, .DLL, etc.) that are involved in the
+    same process and are using the C run-time library (i.e. they
+    are calling standard C functions), must link to the same
+    library.  There are several libraries in the Win32 system:
+    CRTDLL.DLL, MSVCRT.DLL, the static C libraries, etc.
+    Since ZLIB1.DLL is linked to MSVCRT.DLL, the executables that
+    depend on it should also be linked to MSVCRT.DLL.
+
+
+10. Why are you saying that ZLIB1.DLL and my application should
+    be linked to the same C run-time (CRT) library?  I linked my
+    application and my DLLs to different C libraries (e.g. my
+    application to a static library, and my DLLs to MSVCRT.DLL),
+    and everything works fine.
+
+  - If a user library invokes only pure Win32 API (accessible via
+    <windows.h> and the related headers), its DLL build will work
+    in any context.  But if this library invokes standard C API,
+    things get more complicated.
+
+    There is a single Win32 library in a Win32 system.  Every
+    function in this library resides in a single DLL module, that
+    is safe to call from anywhere.  On the other hand, there are
+    multiple versions of the C library, and each of them has its
+    own separate internal state.  Standalone executables and user
+    DLLs that call standard C functions must link to a C run-time
+    (CRT) library, be it static or shared (DLL).  Intermixing
+    occurs when an executable (not necessarily standalone) and a
+    DLL are linked to different CRTs, and both are running in the
+    same process.
+
+    Intermixing multiple CRTs is possible, as long as their
+    internal states are kept intact.  The Microsoft Knowledge Base
+    articles KB94248 "HOWTO: Use the C Run-Time" and KB140584
+    "HOWTO: Link with the Correct C Run-Time (CRT) Library"
+    mention the potential problems raised by intermixing.
+
+    If intermixing works for you, it's because your application
+    and DLLs are avoiding the corruption of each of the CRTs'
+    internal states, maybe by careful design, or maybe by fortune.
+
+    Also note that linking ZLIB1.DLL to non-Microsoft CRTs, such
+    as those provided by Borland, raises similar problems.
+
+
+11. Why are you linking ZLIB1.DLL to MSVCRT.DLL?
+
+  - MSVCRT.DLL exists on every Windows 95 with a new service pack
+    installed, or with Microsoft Internet Explorer 4 or later, and
+    on all other Windows 4.x or later (Windows 98, Windows NT 4,
+    or later).  It is freely distributable; if not present in the
+    system, it can be downloaded from Microsoft or from other
+    software provider for free.
+
+    The fact that MSVCRT.DLL does not exist on a virgin Windows 95
+    is not so problematic.  Windows 95 is scarcely found nowadays,
+    Microsoft ended its support a long time ago, and many recent
+    applications from various vendors, including Microsoft, do not
+    even run on it.  Furthermore, no serious user should run
+    Windows 95 without a proper update installed.
+
+
+12. Why are you not linking ZLIB1.DLL to
+    <<my favorite C run-time library>> ?
+
+  - We considered and abandoned the following alternatives:
+
+    * Linking ZLIB1.DLL to a static C library (LIBC.LIB, or
+      LIBCMT.LIB) is not a good option.  People are using the DLL
+      mainly to save disk space.  If you are linking your program
+      to a static C library, you may as well consider linking zlib
+      in statically, too.
+
+    * Linking ZLIB1.DLL to CRTDLL.DLL looks appealing, because
+      CRTDLL.DLL is present on every Win32 installation.
+      Unfortunately, it has a series of problems: it does not
+      work properly with Microsoft's C++ libraries, it does not
+      provide support for 64-bit file offsets, (and so on...),
+      and Microsoft discontinued its support a long time ago.
+
+    * Linking ZLIB1.DLL to MSVCR70.DLL or MSVCR71.DLL, supplied
+      with the Microsoft .NET platform, and Visual C++ 7.0/7.1,
+      raises problems related to the status of ZLIB1.DLL as a
+      system component.  According to the Microsoft Knowledge Base
+      article KB326922 "INFO: Redistribution of the Shared C
+      Runtime Component in Visual C++ .NET", MSVCR70.DLL and
+      MSVCR71.DLL are not supposed to function as system DLLs,
+      because they may clash with MSVCRT.DLL.  Instead, the
+      application's installer is supposed to put these DLLs
+      (if needed) in the application's private directory.
+      If ZLIB1.DLL depends on a non-system runtime, it cannot
+      function as a redistributable system component.
+
+    * Linking ZLIB1.DLL to non-Microsoft runtimes, such as
+      Borland's, or Cygwin's, raises problems related to the
+      reliable presence of these runtimes on Win32 systems.
+      It's easier to let the DLL build of zlib up to the people
+      who distribute these runtimes, and who may proceed as
+      explained in the answer to Question 14.
+
+
+13. If ZLIB1.DLL cannot be linked to MSVCR70.DLL or MSVCR71.DLL,
+    how can I build/use ZLIB1.DLL in Microsoft Visual C++ 7.0
+    (Visual Studio .NET) or newer?
+
+  - Due to the problems explained in the Microsoft Knowledge Base
+    article KB326922 (see the previous answer), the C runtime that
+    comes with the VC7 environment is no longer considered a
+    system component.  That is, it should not be assumed that this
+    runtime exists, or may be installed in a system directory.
+    Since ZLIB1.DLL is supposed to be a system component, it may
+    not depend on a non-system component.
+
+    In order to link ZLIB1.DLL and your application to MSVCRT.DLL
+    in VC7, you need the library of Visual C++ 6.0 or older.  If
+    you don't have this library at hand, it's probably best not to
+    use ZLIB1.DLL.
+
+    We are hoping that, in the future, Microsoft will provide a
+    way to build applications linked to a proper system runtime,
+    from the Visual C++ environment.  Until then, you have a
+    couple of alternatives, such as linking zlib in statically.
+    If your application requires dynamic linking, you may proceed
+    as explained in the answer to Question 14.
+
+
+14. I need to link my own DLL build to a CRT different than
+    MSVCRT.DLL.  What can I do?
+
+  - Feel free to rebuild the DLL from the zlib sources, and link
+    it the way you want.  You should, however, clearly state that
+    your build is unofficial.  You should give it a different file
+    name, and/or install it in a private directory that can be
+    accessed by your application only, and is not visible to the
+    others (i.e. it's neither in the PATH, nor in the SYSTEM or
+    SYSTEM32 directories).  Otherwise, your build may clash with
+    applications that link to the official build.
+
+    For example, in Cygwin, zlib is linked to the Cygwin runtime
+    CYGWIN1.DLL, and it is distributed under the name CYGZ.DLL.
+
+
+15. May I include additional pieces of code that I find useful,
+    link them in ZLIB1.DLL, and export them?
+
+  - No.  A legitimate build of ZLIB1.DLL must not include code
+    that does not originate from the official zlib source code.
+    But you can make your own private DLL build, under a different
+    file name, as suggested in the previous answer.
+
+    For example, zlib is a part of the VCL library, distributed
+    with Borland Delphi and C++ Builder.  The DLL build of VCL
+    is a redistributable file, named VCLxx.DLL.
+
+
+16. May I remove some functionality out of ZLIB1.DLL, by enabling
+    macros like NO_GZCOMPRESS or NO_GZIP at compile time?
+
+  - No.  A legitimate build of ZLIB1.DLL must provide the complete
+    zlib functionality, as implemented in the official zlib source
+    code.  But you can make your own private DLL build, under a
+    different file name, as suggested in the previous answer.
+
+
+17. I made my own ZLIB1.DLL build.  Can I test it for compliance?
+
+  - We prefer that you download the official DLL from the zlib
+    web site.  If you need something peculiar from this DLL, you
+    can send your suggestion to the zlib mailing list.
+
+    However, in case you do rebuild the DLL yourself, you can run
+    it with the test programs found in the DLL distribution.
+    Running these test programs is not a guarantee of compliance,
+    but a failure can imply a detected problem.
+
+**
+
+This document is written and maintained by
+Cosmin Truta <cosmint@cs.ubbcluj.ro>

ADDED   3rd_party/zlib/win32/Makefile.bor
Index: 3rd_party/zlib/win32/Makefile.bor
==================================================================
--- 3rd_party/zlib/win32/Makefile.bor
+++ 3rd_party/zlib/win32/Makefile.bor
@@ -0,0 +1,110 @@
+# Makefile for zlib
+# Borland C++ for Win32
+#
+# Usage:
+#  make -f win32/Makefile.bor
+#  make -f win32/Makefile.bor LOCAL_ZLIB=-DASMV OBJA=match.obj OBJPA=+match.obj
+
+# ------------ Borland C++ ------------
+
+# Optional nonstandard preprocessor flags (e.g. -DMAX_MEM_LEVEL=7)
+# should be added to the environment via "set LOCAL_ZLIB=-DFOO" or
+# added to the declaration of LOC here:
+LOC = $(LOCAL_ZLIB)
+
+CC = bcc32
+AS = bcc32
+LD = bcc32
+AR = tlib
+CFLAGS  = -a -d -k- -O2 $(LOC)
+ASFLAGS = $(LOC)
+LDFLAGS = $(LOC)
+
+
+# variables
+ZLIB_LIB = zlib.lib
+
+OBJ1 = adler32.obj compress.obj crc32.obj deflate.obj gzclose.obj gzlib.obj gzread.obj
+OBJ2 = gzwrite.obj infback.obj inffast.obj inflate.obj inftrees.obj trees.obj uncompr.obj zutil.obj
+#OBJA =
+OBJP1 = +adler32.obj+compress.obj+crc32.obj+deflate.obj+gzclose.obj+gzlib.obj+gzread.obj
+OBJP2 = +gzwrite.obj+infback.obj+inffast.obj+inflate.obj+inftrees.obj+trees.obj+uncompr.obj+zutil.obj
+#OBJPA=
+
+
+# targets
+all: $(ZLIB_LIB) example.exe minigzip.exe
+
+.c.obj:
+	$(CC) -c $(CFLAGS) $<
+
+.asm.obj:
+	$(AS) -c $(ASFLAGS) $<
+
+adler32.obj: adler32.c zlib.h zconf.h
+
+compress.obj: compress.c zlib.h zconf.h
+
+crc32.obj: crc32.c zlib.h zconf.h crc32.h
+
+deflate.obj: deflate.c deflate.h zutil.h zlib.h zconf.h
+
+gzclose.obj: gzclose.c zlib.h zconf.h gzguts.h
+
+gzlib.obj: gzlib.c zlib.h zconf.h gzguts.h
+
+gzread.obj: gzread.c zlib.h zconf.h gzguts.h
+
+gzwrite.obj: gzwrite.c zlib.h zconf.h gzguts.h
+
+infback.obj: infback.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h inffixed.h
+
+inffast.obj: inffast.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h
+
+inflate.obj: inflate.c zutil.h zlib.h zconf.h inftrees.h inflate.h \
+ inffast.h inffixed.h
+
+inftrees.obj: inftrees.c zutil.h zlib.h zconf.h inftrees.h
+
+trees.obj: trees.c zutil.h zlib.h zconf.h deflate.h trees.h
+
+uncompr.obj: uncompr.c zlib.h zconf.h
+
+zutil.obj: zutil.c zutil.h zlib.h zconf.h
+
+example.obj: test/example.c zlib.h zconf.h
+
+minigzip.obj: test/minigzip.c zlib.h zconf.h
+
+
+# For the sake of the old Borland make,
+# the command line is cut to fit in the MS-DOS 128 byte limit:
+$(ZLIB_LIB): $(OBJ1) $(OBJ2) $(OBJA)
+	-del $(ZLIB_LIB)
+	$(AR) $(ZLIB_LIB) $(OBJP1)
+	$(AR) $(ZLIB_LIB) $(OBJP2)
+	$(AR) $(ZLIB_LIB) $(OBJPA)
+
+
+# testing
+test: example.exe minigzip.exe
+	example
+	echo hello world | minigzip | minigzip -d
+
+example.exe: example.obj $(ZLIB_LIB)
+	$(LD) $(LDFLAGS) example.obj $(ZLIB_LIB)
+
+minigzip.exe: minigzip.obj $(ZLIB_LIB)
+	$(LD) $(LDFLAGS) minigzip.obj $(ZLIB_LIB)
+
+
+# cleanup
+clean:
+	-del $(ZLIB_LIB)
+	-del *.obj
+	-del *.exe
+	-del *.tds
+	-del zlib.bak
+	-del foo.gz

ADDED   3rd_party/zlib/win32/Makefile.gcc
Index: 3rd_party/zlib/win32/Makefile.gcc
==================================================================
--- 3rd_party/zlib/win32/Makefile.gcc
+++ 3rd_party/zlib/win32/Makefile.gcc
@@ -0,0 +1,182 @@
+# Makefile for zlib, derived from Makefile.dj2.
+# Modified for mingw32 by C. Spieler, 6/16/98.
+# Updated for zlib 1.2.x by Christian Spieler and Cosmin Truta, Mar-2003.
+# Last updated: Mar 2012.
+# Tested under Cygwin and MinGW.
+
+# Copyright (C) 1995-2003 Jean-loup Gailly.
+# For conditions of distribution and use, see copyright notice in zlib.h
+
+# To compile, or to compile and test, type from the top level zlib directory:
+#
+#   make -fwin32/Makefile.gcc;  make test testdll -fwin32/Makefile.gcc
+#
+# To use the asm code, type:
+#   cp contrib/asm?86/match.S ./match.S
+#   make LOC=-DASMV OBJA=match.o -fwin32/Makefile.gcc
+#
+# To install libz.a, zconf.h and zlib.h in the system directories, type:
+#
+#   make install -fwin32/Makefile.gcc
+#
+# BINARY_PATH, INCLUDE_PATH and LIBRARY_PATH must be set.
+#
+# To install the shared lib, append SHARED_MODE=1 to the make command :
+#
+#   make install -fwin32/Makefile.gcc SHARED_MODE=1
+
+# Note:
+# If the platform is *not* MinGW (e.g. it is Cygwin or UWIN),
+# the DLL name should be changed from "zlib1.dll".
+
+STATICLIB = libz.a
+SHAREDLIB = zlib1.dll
+IMPLIB    = libz.dll.a
+
+#
+# Set to 1 if shared object needs to be installed
+#
+SHARED_MODE=0
+
+#LOC = -DASMV
+#LOC = -DZLIB_DEBUG -g
+
+PREFIX =
+CC = $(PREFIX)gcc
+CFLAGS = $(LOC) -O3 -Wall
+
+AS = $(CC)
+ASFLAGS = $(LOC) -Wall
+
+LD = $(CC)
+LDFLAGS = $(LOC)
+
+AR = $(PREFIX)ar
+ARFLAGS = rcs
+
+RC = $(PREFIX)windres
+RCFLAGS = --define GCC_WINDRES
+
+STRIP = $(PREFIX)strip
+
+CP = cp -fp
+# If GNU install is available, replace $(CP) with install.
+INSTALL = $(CP)
+RM = rm -f
+
+prefix ?= /usr/local
+exec_prefix = $(prefix)
+
+OBJS = adler32.o compress.o crc32.o deflate.o gzclose.o gzlib.o gzread.o \
+       gzwrite.o infback.o inffast.o inflate.o inftrees.o trees.o uncompr.o zutil.o
+OBJA =
+
+all: $(STATICLIB) $(SHAREDLIB) $(IMPLIB) example.exe minigzip.exe example_d.exe minigzip_d.exe
+
+test: example.exe minigzip.exe
+	./example
+	echo hello world | ./minigzip | ./minigzip -d
+
+testdll: example_d.exe minigzip_d.exe
+	./example_d
+	echo hello world | ./minigzip_d | ./minigzip_d -d
+
+.c.o:
+	$(CC) $(CFLAGS) -c -o $@ $<
+
+.S.o:
+	$(AS) $(ASFLAGS) -c -o $@ $<
+
+$(STATICLIB): $(OBJS) $(OBJA)
+	$(AR) $(ARFLAGS) $@ $(OBJS) $(OBJA)
+
+$(IMPLIB): $(SHAREDLIB)
+
+$(SHAREDLIB): win32/zlib.def $(OBJS) $(OBJA) zlibrc.o
+	$(CC) -shared -Wl,--out-implib,$(IMPLIB) $(LDFLAGS) \
+	-o $@ win32/zlib.def $(OBJS) $(OBJA) zlibrc.o
+	$(STRIP) $@
+
+example.exe: example.o $(STATICLIB)
+	$(LD) $(LDFLAGS) -o $@ example.o $(STATICLIB)
+	$(STRIP) $@
+
+minigzip.exe: minigzip.o $(STATICLIB)
+	$(LD) $(LDFLAGS) -o $@ minigzip.o $(STATICLIB)
+	$(STRIP) $@
+
+example_d.exe: example.o $(IMPLIB)
+	$(LD) $(LDFLAGS) -o $@ example.o $(IMPLIB)
+	$(STRIP) $@
+
+minigzip_d.exe: minigzip.o $(IMPLIB)
+	$(LD) $(LDFLAGS) -o $@ minigzip.o $(IMPLIB)
+	$(STRIP) $@
+
+example.o: test/example.c zlib.h zconf.h
+	$(CC) $(CFLAGS) -I. -c -o $@ test/example.c
+
+minigzip.o: test/minigzip.c zlib.h zconf.h
+	$(CC) $(CFLAGS) -I. -c -o $@ test/minigzip.c
+
+zlibrc.o: win32/zlib1.rc
+	$(RC) $(RCFLAGS) -o $@ win32/zlib1.rc
+
+.PHONY: install uninstall clean
+
+install: zlib.h zconf.h $(STATICLIB) $(IMPLIB)
+	@if test -z "$(DESTDIR)$(INCLUDE_PATH)" -o -z "$(DESTDIR)$(LIBRARY_PATH)" -o -z "$(DESTDIR)$(BINARY_PATH)"; then \
+		echo INCLUDE_PATH, LIBRARY_PATH, and BINARY_PATH must be specified; \
+		exit 1; \
+	fi
+	-@mkdir -p '$(DESTDIR)$(INCLUDE_PATH)'
+	-@mkdir -p '$(DESTDIR)$(LIBRARY_PATH)' '$(DESTDIR)$(LIBRARY_PATH)'/pkgconfig
+	-if [ "$(SHARED_MODE)" = "1" ]; then \
+		mkdir -p '$(DESTDIR)$(BINARY_PATH)'; \
+		$(INSTALL) $(SHAREDLIB) '$(DESTDIR)$(BINARY_PATH)'; \
+		$(INSTALL) $(IMPLIB) '$(DESTDIR)$(LIBRARY_PATH)'; \
+	fi
+	-$(INSTALL) zlib.h '$(DESTDIR)$(INCLUDE_PATH)'
+	-$(INSTALL) zconf.h '$(DESTDIR)$(INCLUDE_PATH)'
+	-$(INSTALL) $(STATICLIB) '$(DESTDIR)$(LIBRARY_PATH)'
+	sed \
+		-e 's|@prefix@|${prefix}|g' \
+		-e 's|@exec_prefix@|${exec_prefix}|g' \
+		-e 's|@libdir@|$(LIBRARY_PATH)|g' \
+		-e 's|@sharedlibdir@|$(LIBRARY_PATH)|g' \
+		-e 's|@includedir@|$(INCLUDE_PATH)|g' \
+		-e 's|@VERSION@|'`sed -n -e '/VERSION "/s/.*"\(.*\)".*/\1/p' zlib.h`'|g' \
+		zlib.pc.in > '$(DESTDIR)$(LIBRARY_PATH)'/pkgconfig/zlib.pc
+
+uninstall:
+	-if [ "$(SHARED_MODE)" = "1" ]; then \
+		$(RM) '$(DESTDIR)$(BINARY_PATH)'/$(SHAREDLIB); \
+		$(RM) '$(DESTDIR)$(LIBRARY_PATH)'/$(IMPLIB); \
+	fi
+	-$(RM) '$(DESTDIR)$(INCLUDE_PATH)'/zlib.h
+	-$(RM) '$(DESTDIR)$(INCLUDE_PATH)'/zconf.h
+	-$(RM) '$(DESTDIR)$(LIBRARY_PATH)'/$(STATICLIB)
+
+clean:
+	-$(RM) $(STATICLIB)
+	-$(RM) $(SHAREDLIB)
+	-$(RM) $(IMPLIB)
+	-$(RM) *.o
+	-$(RM) *.exe
+	-$(RM) foo.gz
+
+adler32.o: zlib.h zconf.h
+compress.o: zlib.h zconf.h
+crc32.o: crc32.h zlib.h zconf.h
+deflate.o: deflate.h zutil.h zlib.h zconf.h
+gzclose.o: zlib.h zconf.h gzguts.h
+gzlib.o: zlib.h zconf.h gzguts.h
+gzread.o: zlib.h zconf.h gzguts.h
+gzwrite.o: zlib.h zconf.h gzguts.h
+inffast.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+inflate.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+infback.o: zutil.h zlib.h zconf.h inftrees.h inflate.h inffast.h
+inftrees.o: zutil.h zlib.h zconf.h inftrees.h
+trees.o: deflate.h zutil.h zlib.h zconf.h trees.h
+uncompr.o: zlib.h zconf.h
+zutil.o: zutil.h zlib.h zconf.h

ADDED   3rd_party/zlib/win32/Makefile.msc
Index: 3rd_party/zlib/win32/Makefile.msc
==================================================================
--- 3rd_party/zlib/win32/Makefile.msc
+++ 3rd_party/zlib/win32/Makefile.msc
@@ -0,0 +1,163 @@
+# Makefile for zlib using Microsoft (Visual) C
+# zlib is copyright (C) 1995-2017 Jean-loup Gailly and Mark Adler
+#
+# Usage:
+#   nmake -f win32/Makefile.msc                          (standard build)
+#   nmake -f win32/Makefile.msc LOC=-DFOO                (nonstandard build)
+#   nmake -f win32/Makefile.msc LOC="-DASMV -DASMINF" \
+#         OBJA="inffas32.obj match686.obj"               (use ASM code, x86)
+#   nmake -f win32/Makefile.msc AS=ml64 LOC="-DASMV -DASMINF -I." \
+#         OBJA="inffasx64.obj gvmat64.obj inffas8664.obj"  (use ASM code, x64)
+
+# The toplevel directory of the source tree.
+#
+TOP = .
+
+# optional build flags
+LOC =
+
+# variables
+STATICLIB = zlib.lib
+SHAREDLIB = zlib1.dll
+IMPLIB    = zdll.lib
+
+CC = cl
+AS = ml
+LD = link
+AR = lib
+RC = rc
+CFLAGS  = -nologo -MD -W3 -O2 -Oy- -Zi -Fd"zlib" $(LOC)
+WFLAGS  = -D_CRT_SECURE_NO_DEPRECATE -D_CRT_NONSTDC_NO_DEPRECATE
+ASFLAGS = -coff -Zi $(LOC)
+LDFLAGS = -nologo -debug -incremental:no -opt:ref
+ARFLAGS = -nologo
+RCFLAGS = /dWIN32 /r
+
+OBJS = adler32.obj compress.obj crc32.obj deflate.obj gzclose.obj gzlib.obj gzread.obj \
+       gzwrite.obj infback.obj inflate.obj inftrees.obj inffast.obj trees.obj uncompr.obj zutil.obj
+OBJA =
+
+
+# targets
+all: $(STATICLIB) $(SHAREDLIB) $(IMPLIB) \
+     example.exe minigzip.exe example_d.exe minigzip_d.exe
+
+$(STATICLIB): $(OBJS) $(OBJA)
+	$(AR) $(ARFLAGS) -out:$@ $(OBJS) $(OBJA)
+
+$(IMPLIB): $(SHAREDLIB)
+
+$(SHAREDLIB): $(TOP)/win32/zlib.def $(OBJS) $(OBJA) zlib1.res
+	$(LD) $(LDFLAGS) -def:$(TOP)/win32/zlib.def -dll -implib:$(IMPLIB) \
+	  -out:$@ -base:0x5A4C0000 $(OBJS) $(OBJA) zlib1.res
+	if exist $@.manifest \
+	  mt -nologo -manifest $@.manifest -outputresource:$@;2
+
+example.exe: example.obj $(STATICLIB)
+	$(LD) $(LDFLAGS) example.obj $(STATICLIB)
+	if exist $@.manifest \
+	  mt -nologo -manifest $@.manifest -outputresource:$@;1
+
+minigzip.exe: minigzip.obj $(STATICLIB)
+	$(LD) $(LDFLAGS) minigzip.obj $(STATICLIB)
+	if exist $@.manifest \
+	  mt -nologo -manifest $@.manifest -outputresource:$@;1
+
+example_d.exe: example.obj $(IMPLIB)
+	$(LD) $(LDFLAGS) -out:$@ example.obj $(IMPLIB)
+	if exist $@.manifest \
+	  mt -nologo -manifest $@.manifest -outputresource:$@;1
+
+minigzip_d.exe: minigzip.obj $(IMPLIB)
+	$(LD) $(LDFLAGS) -out:$@ minigzip.obj $(IMPLIB)
+	if exist $@.manifest \
+	  mt -nologo -manifest $@.manifest -outputresource:$@;1
+
+{$(TOP)}.c.obj:
+	$(CC) -c $(WFLAGS) $(CFLAGS) $<
+
+{$(TOP)/test}.c.obj:
+	$(CC) -c -I$(TOP) $(WFLAGS) $(CFLAGS) $<
+
+{$(TOP)/contrib/masmx64}.c.obj:
+	$(CC) -c $(WFLAGS) $(CFLAGS) $<
+
+{$(TOP)/contrib/masmx64}.asm.obj:
+	$(AS) -c $(ASFLAGS) $<
+
+{$(TOP)/contrib/masmx86}.asm.obj:
+	$(AS) -c $(ASFLAGS) $<
+
+adler32.obj: $(TOP)/adler32.c $(TOP)/zlib.h $(TOP)/zconf.h
+
+compress.obj: $(TOP)/compress.c $(TOP)/zlib.h $(TOP)/zconf.h
+
+crc32.obj: $(TOP)/crc32.c $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/crc32.h
+
+deflate.obj: $(TOP)/deflate.c $(TOP)/deflate.h $(TOP)/zutil.h $(TOP)/zlib.h $(TOP)/zconf.h
+
+gzclose.obj: $(TOP)/gzclose.c $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/gzguts.h
+
+gzlib.obj: $(TOP)/gzlib.c $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/gzguts.h
+
+gzread.obj: $(TOP)/gzread.c $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/gzguts.h
+
+gzwrite.obj: $(TOP)/gzwrite.c $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/gzguts.h
+
+infback.obj: $(TOP)/infback.c $(TOP)/zutil.h $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/inftrees.h $(TOP)/inflate.h \
+             $(TOP)/inffast.h $(TOP)/inffixed.h
+
+inffast.obj: $(TOP)/inffast.c $(TOP)/zutil.h $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/inftrees.h $(TOP)/inflate.h \
+             $(TOP)/inffast.h
+
+inflate.obj: $(TOP)/inflate.c $(TOP)/zutil.h $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/inftrees.h $(TOP)/inflate.h \
+             $(TOP)/inffast.h $(TOP)/inffixed.h
+
+inftrees.obj: $(TOP)/inftrees.c $(TOP)/zutil.h $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/inftrees.h
+
+trees.obj: $(TOP)/trees.c $(TOP)/zutil.h $(TOP)/zlib.h $(TOP)/zconf.h $(TOP)/deflate.h $(TOP)/trees.h
+
+uncompr.obj: $(TOP)/uncompr.c $(TOP)/zlib.h $(TOP)/zconf.h
+
+zutil.obj: $(TOP)/zutil.c $(TOP)/zutil.h $(TOP)/zlib.h $(TOP)/zconf.h
+
+gvmat64.obj: $(TOP)/contrib\masmx64\gvmat64.asm
+
+inffasx64.obj: $(TOP)/contrib\masmx64\inffasx64.asm
+
+inffas8664.obj: $(TOP)/contrib\masmx64\inffas8664.c $(TOP)/zutil.h $(TOP)/zlib.h $(TOP)/zconf.h \
+		$(TOP)/inftrees.h $(TOP)/inflate.h $(TOP)/inffast.h
+
+inffas32.obj: $(TOP)/contrib\masmx86\inffas32.asm
+
+match686.obj: $(TOP)/contrib\masmx86\match686.asm
+
+example.obj: $(TOP)/test/example.c $(TOP)/zlib.h $(TOP)/zconf.h
+
+minigzip.obj: $(TOP)/test/minigzip.c $(TOP)/zlib.h $(TOP)/zconf.h
+
+zlib1.res: $(TOP)/win32/zlib1.rc
+	$(RC) $(RCFLAGS) /fo$@ $(TOP)/win32/zlib1.rc
+
+# testing
+test: example.exe minigzip.exe
+	example
+	echo hello world | minigzip | minigzip -d
+
+testdll: example_d.exe minigzip_d.exe
+	example_d
+	echo hello world | minigzip_d | minigzip_d -d
+
+
+# cleanup
+clean:
+	-del $(STATICLIB)
+	-del $(SHAREDLIB)
+	-del $(IMPLIB)
+	-del *.obj
+	-del *.res
+	-del *.exp
+	-del *.exe
+	-del *.pdb
+	-del *.manifest
+	-del foo.gz

ADDED   3rd_party/zlib/win32/README-WIN32.txt
Index: 3rd_party/zlib/win32/README-WIN32.txt
==================================================================
--- 3rd_party/zlib/win32/README-WIN32.txt
+++ 3rd_party/zlib/win32/README-WIN32.txt
@@ -0,0 +1,103 @@
+ZLIB DATA COMPRESSION LIBRARY
+
+zlib 1.2.11 is a general purpose data compression library.  All the code is
+thread safe.  The data format used by the zlib library is described by RFCs
+(Request for Comments) 1950 to 1952 in the files
+http://www.ietf.org/rfc/rfc1950.txt (zlib format), rfc1951.txt (deflate format)
+and rfc1952.txt (gzip format).
+
+All functions of the compression library are documented in the file zlib.h
+(volunteer to write man pages welcome, contact zlib@gzip.org).  Two compiled
+examples are distributed in this package, example and minigzip.  The example_d
+and minigzip_d flavors validate that the zlib1.dll file is working correctly.
+
+Questions about zlib should be sent to <zlib@gzip.org>.  The zlib home page
+is http://zlib.net/ .  Before reporting a problem, please check this site to
+verify that you have the latest version of zlib; otherwise get the latest
+version and check whether the problem still exists or not.
+
+PLEASE read DLL_FAQ.txt, and the the zlib FAQ http://zlib.net/zlib_faq.html
+before asking for help.
+
+
+Manifest:
+
+The package zlib-1.2.11-win32-x86.zip will contain the following files:
+
+  README-WIN32.txt This document
+  ChangeLog        Changes since previous zlib packages
+  DLL_FAQ.txt      Frequently asked questions about zlib1.dll
+  zlib.3.pdf       Documentation of this library in Adobe Acrobat format
+
+  example.exe      A statically-bound example (using zlib.lib, not the dll)
+  example.pdb      Symbolic information for debugging example.exe
+
+  example_d.exe    A zlib1.dll bound example (using zdll.lib)
+  example_d.pdb    Symbolic information for debugging example_d.exe
+
+  minigzip.exe     A statically-bound test program (using zlib.lib, not the dll)
+  minigzip.pdb     Symbolic information for debugging minigzip.exe
+
+  minigzip_d.exe   A zlib1.dll bound test program (using zdll.lib)
+  minigzip_d.pdb   Symbolic information for debugging minigzip_d.exe
+
+  zlib.h           Install these files into the compilers' INCLUDE path to
+  zconf.h          compile programs which use zlib.lib or zdll.lib
+
+  zdll.lib         Install these files into the compilers' LIB path if linking
+  zdll.exp         a compiled program to the zlib1.dll binary
+
+  zlib.lib         Install these files into the compilers' LIB path to link zlib
+  zlib.pdb         into compiled programs, without zlib1.dll runtime dependency
+                   (zlib.pdb provides debugging info to the compile time linker)
+
+  zlib1.dll        Install this binary shared library into the system PATH, or
+                   the program's runtime directory (where the .exe resides)
+  zlib1.pdb        Install in the same directory as zlib1.dll, in order to debug
+                   an application crash using WinDbg or similar tools.
+
+All .pdb files above are entirely optional, but are very useful to a developer
+attempting to diagnose program misbehavior or a crash.  Many additional
+important files for developers can be found in the zlib127.zip source package
+available from http://zlib.net/ - review that package's README file for details.
+
+
+Acknowledgments:
+
+The deflate format used by zlib was defined by Phil Katz.  The deflate and
+zlib specifications were written by L.  Peter Deutsch.  Thanks to all the
+people who reported problems and suggested various improvements in zlib; they
+are too numerous to cite here.
+
+
+Copyright notice:
+
+  (C) 1995-2017 Jean-loup Gailly and Mark Adler
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the authors be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
+
+  Jean-loup Gailly        Mark Adler
+  jloup@gzip.org          madler@alumni.caltech.edu
+
+If you use the zlib library in a product, we would appreciate *not* receiving
+lengthy legal documents to sign.  The sources are provided for free but without
+warranty of any kind.  The library has been entirely written by Jean-loup
+Gailly and Mark Adler; it does not include third-party code.
+
+If you redistribute modified sources, we would appreciate that you include in
+the file ChangeLog history information documenting your changes.  Please read
+the FAQ for more information on the distribution of modified source versions.

ADDED   3rd_party/zlib/win32/VisualC.txt
Index: 3rd_party/zlib/win32/VisualC.txt
==================================================================
--- 3rd_party/zlib/win32/VisualC.txt
+++ 3rd_party/zlib/win32/VisualC.txt
@@ -0,0 +1,3 @@
+
+To build zlib using the Microsoft Visual C++ environment,
+use the appropriate project from the contrib/vstudio/ directory.

ADDED   3rd_party/zlib/win32/zlib.def
Index: 3rd_party/zlib/win32/zlib.def
==================================================================
--- 3rd_party/zlib/win32/zlib.def
+++ 3rd_party/zlib/win32/zlib.def
@@ -0,0 +1,94 @@
+; zlib data compression library
+EXPORTS
+; basic functions
+    zlibVersion
+    deflate
+    deflateEnd
+    inflate
+    inflateEnd
+; advanced functions
+    deflateSetDictionary
+    deflateGetDictionary
+    deflateCopy
+    deflateReset
+    deflateParams
+    deflateTune
+    deflateBound
+    deflatePending
+    deflatePrime
+    deflateSetHeader
+    inflateSetDictionary
+    inflateGetDictionary
+    inflateSync
+    inflateCopy
+    inflateReset
+    inflateReset2
+    inflatePrime
+    inflateMark
+    inflateGetHeader
+    inflateBack
+    inflateBackEnd
+    zlibCompileFlags
+; utility functions
+    compress
+    compress2
+    compressBound
+    uncompress
+    uncompress2
+    gzopen
+    gzdopen
+    gzbuffer
+    gzsetparams
+    gzread
+    gzfread
+    gzwrite
+    gzfwrite
+    gzprintf
+    gzvprintf
+    gzputs
+    gzgets
+    gzputc
+    gzgetc
+    gzungetc
+    gzflush
+    gzseek
+    gzrewind
+    gztell
+    gzoffset
+    gzeof
+    gzdirect
+    gzclose
+    gzclose_r
+    gzclose_w
+    gzerror
+    gzclearerr
+; large file functions
+    gzopen64
+    gzseek64
+    gztell64
+    gzoffset64
+    adler32_combine64
+    crc32_combine64
+; checksum functions
+    adler32
+    adler32_z
+    crc32
+    crc32_z
+    adler32_combine
+    crc32_combine
+; various hacks, don't look :)
+    deflateInit_
+    deflateInit2_
+    inflateInit_
+    inflateInit2_
+    inflateBackInit_
+    gzgetc_
+    zError
+    inflateSyncPoint
+    get_crc_table
+    inflateUndermine
+    inflateValidate
+    inflateCodesUsed
+    inflateResetKeep
+    deflateResetKeep
+    gzopen_w

ADDED   3rd_party/zlib/win32/zlib1.rc
Index: 3rd_party/zlib/win32/zlib1.rc
==================================================================
--- 3rd_party/zlib/win32/zlib1.rc
+++ 3rd_party/zlib/win32/zlib1.rc
@@ -0,0 +1,40 @@
+#include <winver.h>
+#include "../zlib.h"
+
+#ifdef GCC_WINDRES
+VS_VERSION_INFO		VERSIONINFO
+#else
+VS_VERSION_INFO		VERSIONINFO	MOVEABLE IMPURE LOADONCALL DISCARDABLE
+#endif
+  FILEVERSION		ZLIB_VER_MAJOR,ZLIB_VER_MINOR,ZLIB_VER_REVISION,0
+  PRODUCTVERSION	ZLIB_VER_MAJOR,ZLIB_VER_MINOR,ZLIB_VER_REVISION,0
+  FILEFLAGSMASK		VS_FFI_FILEFLAGSMASK
+#ifdef _DEBUG
+  FILEFLAGS		1
+#else
+  FILEFLAGS		0
+#endif
+  FILEOS		VOS__WINDOWS32
+  FILETYPE		VFT_DLL
+  FILESUBTYPE		0	// not used
+BEGIN
+  BLOCK "StringFileInfo"
+  BEGIN
+    BLOCK "040904E4"
+    //language ID = U.S. English, char set = Windows, Multilingual
+    BEGIN
+      VALUE "FileDescription",	"zlib data compression library\0"
+      VALUE "FileVersion",	ZLIB_VERSION "\0"
+      VALUE "InternalName",	"zlib1.dll\0"
+      VALUE "LegalCopyright",	"(C) 1995-2017 Jean-loup Gailly & Mark Adler\0"
+      VALUE "OriginalFilename",	"zlib1.dll\0"
+      VALUE "ProductName",	"zlib\0"
+      VALUE "ProductVersion",	ZLIB_VERSION "\0"
+      VALUE "Comments",		"For more information visit http://www.zlib.net/\0"
+    END
+  END
+  BLOCK "VarFileInfo"
+  BEGIN
+    VALUE "Translation", 0x0409, 1252
+  END
+END

ADDED   3rd_party/zlib/wscript
Index: 3rd_party/zlib/wscript
==================================================================
--- 3rd_party/zlib/wscript
+++ 3rd_party/zlib/wscript
@@ -0,0 +1,13 @@
+import os.path
+
+def build( bld ):
+	sources = bld.path.ant_glob( '*.c' )
+	headers = bld.path.ant_glob( '*.h' )
+	bld.stlib(
+		target = 'zlib',
+		source = sources,
+		features = [ 'c' ],
+		includes = './',
+		cflags = '-O3 -fPIC',
+		export_includes = './'
+	)

ADDED   3rd_party/zlib/zconf.h
Index: 3rd_party/zlib/zconf.h
==================================================================
--- 3rd_party/zlib/zconf.h
+++ 3rd_party/zlib/zconf.h
@@ -0,0 +1,534 @@
+/* zconf.h -- configuration of the zlib compression library
+ * Copyright (C) 1995-2016 Jean-loup Gailly, Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* @(#) $Id$ */
+
+#ifndef ZCONF_H
+#define ZCONF_H
+
+/*
+ * If you *really* need a unique prefix for all types and library functions,
+ * compile with -DZ_PREFIX. The "standard" zlib should be compiled without it.
+ * Even better than compiling with -DZ_PREFIX would be to use configure to set
+ * this permanently in zconf.h using "./configure --zprefix".
+ */
+#ifdef Z_PREFIX     /* may be set to #if 1 by ./configure */
+#  define Z_PREFIX_SET
+
+/* all linked symbols and init macros */
+#  define _dist_code            z__dist_code
+#  define _length_code          z__length_code
+#  define _tr_align             z__tr_align
+#  define _tr_flush_bits        z__tr_flush_bits
+#  define _tr_flush_block       z__tr_flush_block
+#  define _tr_init              z__tr_init
+#  define _tr_stored_block      z__tr_stored_block
+#  define _tr_tally             z__tr_tally
+#  define adler32               z_adler32
+#  define adler32_combine       z_adler32_combine
+#  define adler32_combine64     z_adler32_combine64
+#  define adler32_z             z_adler32_z
+#  ifndef Z_SOLO
+#    define compress              z_compress
+#    define compress2             z_compress2
+#    define compressBound         z_compressBound
+#  endif
+#  define crc32                 z_crc32
+#  define crc32_combine         z_crc32_combine
+#  define crc32_combine64       z_crc32_combine64
+#  define crc32_z               z_crc32_z
+#  define deflate               z_deflate
+#  define deflateBound          z_deflateBound
+#  define deflateCopy           z_deflateCopy
+#  define deflateEnd            z_deflateEnd
+#  define deflateGetDictionary  z_deflateGetDictionary
+#  define deflateInit           z_deflateInit
+#  define deflateInit2          z_deflateInit2
+#  define deflateInit2_         z_deflateInit2_
+#  define deflateInit_          z_deflateInit_
+#  define deflateParams         z_deflateParams
+#  define deflatePending        z_deflatePending
+#  define deflatePrime          z_deflatePrime
+#  define deflateReset          z_deflateReset
+#  define deflateResetKeep      z_deflateResetKeep
+#  define deflateSetDictionary  z_deflateSetDictionary
+#  define deflateSetHeader      z_deflateSetHeader
+#  define deflateTune           z_deflateTune
+#  define deflate_copyright     z_deflate_copyright
+#  define get_crc_table         z_get_crc_table
+#  ifndef Z_SOLO
+#    define gz_error              z_gz_error
+#    define gz_intmax             z_gz_intmax
+#    define gz_strwinerror        z_gz_strwinerror
+#    define gzbuffer              z_gzbuffer
+#    define gzclearerr            z_gzclearerr
+#    define gzclose               z_gzclose
+#    define gzclose_r             z_gzclose_r
+#    define gzclose_w             z_gzclose_w
+#    define gzdirect              z_gzdirect
+#    define gzdopen               z_gzdopen
+#    define gzeof                 z_gzeof
+#    define gzerror               z_gzerror
+#    define gzflush               z_gzflush
+#    define gzfread               z_gzfread
+#    define gzfwrite              z_gzfwrite
+#    define gzgetc                z_gzgetc
+#    define gzgetc_               z_gzgetc_
+#    define gzgets                z_gzgets
+#    define gzoffset              z_gzoffset
+#    define gzoffset64            z_gzoffset64
+#    define gzopen                z_gzopen
+#    define gzopen64              z_gzopen64
+#    ifdef _WIN32
+#      define gzopen_w              z_gzopen_w
+#    endif
+#    define gzprintf              z_gzprintf
+#    define gzputc                z_gzputc
+#    define gzputs                z_gzputs
+#    define gzread                z_gzread
+#    define gzrewind              z_gzrewind
+#    define gzseek                z_gzseek
+#    define gzseek64              z_gzseek64
+#    define gzsetparams           z_gzsetparams
+#    define gztell                z_gztell
+#    define gztell64              z_gztell64
+#    define gzungetc              z_gzungetc
+#    define gzvprintf             z_gzvprintf
+#    define gzwrite               z_gzwrite
+#  endif
+#  define inflate               z_inflate
+#  define inflateBack           z_inflateBack
+#  define inflateBackEnd        z_inflateBackEnd
+#  define inflateBackInit       z_inflateBackInit
+#  define inflateBackInit_      z_inflateBackInit_
+#  define inflateCodesUsed      z_inflateCodesUsed
+#  define inflateCopy           z_inflateCopy
+#  define inflateEnd            z_inflateEnd
+#  define inflateGetDictionary  z_inflateGetDictionary
+#  define inflateGetHeader      z_inflateGetHeader
+#  define inflateInit           z_inflateInit
+#  define inflateInit2          z_inflateInit2
+#  define inflateInit2_         z_inflateInit2_
+#  define inflateInit_          z_inflateInit_
+#  define inflateMark           z_inflateMark
+#  define inflatePrime          z_inflatePrime
+#  define inflateReset          z_inflateReset
+#  define inflateReset2         z_inflateReset2
+#  define inflateResetKeep      z_inflateResetKeep
+#  define inflateSetDictionary  z_inflateSetDictionary
+#  define inflateSync           z_inflateSync
+#  define inflateSyncPoint      z_inflateSyncPoint
+#  define inflateUndermine      z_inflateUndermine
+#  define inflateValidate       z_inflateValidate
+#  define inflate_copyright     z_inflate_copyright
+#  define inflate_fast          z_inflate_fast
+#  define inflate_table         z_inflate_table
+#  ifndef Z_SOLO
+#    define uncompress            z_uncompress
+#    define uncompress2           z_uncompress2
+#  endif
+#  define zError                z_zError
+#  ifndef Z_SOLO
+#    define zcalloc               z_zcalloc
+#    define zcfree                z_zcfree
+#  endif
+#  define zlibCompileFlags      z_zlibCompileFlags
+#  define zlibVersion           z_zlibVersion
+
+/* all zlib typedefs in zlib.h and zconf.h */
+#  define Byte                  z_Byte
+#  define Bytef                 z_Bytef
+#  define alloc_func            z_alloc_func
+#  define charf                 z_charf
+#  define free_func             z_free_func
+#  ifndef Z_SOLO
+#    define gzFile                z_gzFile
+#  endif
+#  define gz_header             z_gz_header
+#  define gz_headerp            z_gz_headerp
+#  define in_func               z_in_func
+#  define intf                  z_intf
+#  define out_func              z_out_func
+#  define uInt                  z_uInt
+#  define uIntf                 z_uIntf
+#  define uLong                 z_uLong
+#  define uLongf                z_uLongf
+#  define voidp                 z_voidp
+#  define voidpc                z_voidpc
+#  define voidpf                z_voidpf
+
+/* all zlib structs in zlib.h and zconf.h */
+#  define gz_header_s           z_gz_header_s
+#  define internal_state        z_internal_state
+
+#endif
+
+#if defined(__MSDOS__) && !defined(MSDOS)
+#  define MSDOS
+#endif
+#if (defined(OS_2) || defined(__OS2__)) && !defined(OS2)
+#  define OS2
+#endif
+#if defined(_WINDOWS) && !defined(WINDOWS)
+#  define WINDOWS
+#endif
+#if defined(_WIN32) || defined(_WIN32_WCE) || defined(__WIN32__)
+#  ifndef WIN32
+#    define WIN32
+#  endif
+#endif
+#if (defined(MSDOS) || defined(OS2) || defined(WINDOWS)) && !defined(WIN32)
+#  if !defined(__GNUC__) && !defined(__FLAT__) && !defined(__386__)
+#    ifndef SYS16BIT
+#      define SYS16BIT
+#    endif
+#  endif
+#endif
+
+/*
+ * Compile with -DMAXSEG_64K if the alloc function cannot allocate more
+ * than 64k bytes at a time (needed on systems with 16-bit int).
+ */
+#ifdef SYS16BIT
+#  define MAXSEG_64K
+#endif
+#ifdef MSDOS
+#  define UNALIGNED_OK
+#endif
+
+#ifdef __STDC_VERSION__
+#  ifndef STDC
+#    define STDC
+#  endif
+#  if __STDC_VERSION__ >= 199901L
+#    ifndef STDC99
+#      define STDC99
+#    endif
+#  endif
+#endif
+#if !defined(STDC) && (defined(__STDC__) || defined(__cplusplus))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(__GNUC__) || defined(__BORLANDC__))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(MSDOS) || defined(WINDOWS) || defined(WIN32))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(OS2) || defined(__HOS_AIX__))
+#  define STDC
+#endif
+
+#if defined(__OS400__) && !defined(STDC)    /* iSeries (formerly AS/400). */
+#  define STDC
+#endif
+
+#ifndef STDC
+#  ifndef const /* cannot use !defined(STDC) && !defined(const) on Mac */
+#    define const       /* note: need a more gentle solution here */
+#  endif
+#endif
+
+#if defined(ZLIB_CONST) && !defined(z_const)
+#  define z_const const
+#else
+#  define z_const
+#endif
+
+#ifdef Z_SOLO
+   typedef unsigned long z_size_t;
+#else
+#  define z_longlong long long
+#  if defined(NO_SIZE_T)
+     typedef unsigned NO_SIZE_T z_size_t;
+#  elif defined(STDC)
+#    include <stddef.h>
+     typedef size_t z_size_t;
+#  else
+     typedef unsigned long z_size_t;
+#  endif
+#  undef z_longlong
+#endif
+
+/* Maximum value for memLevel in deflateInit2 */
+#ifndef MAX_MEM_LEVEL
+#  ifdef MAXSEG_64K
+#    define MAX_MEM_LEVEL 8
+#  else
+#    define MAX_MEM_LEVEL 9
+#  endif
+#endif
+
+/* Maximum value for windowBits in deflateInit2 and inflateInit2.
+ * WARNING: reducing MAX_WBITS makes minigzip unable to extract .gz files
+ * created by gzip. (Files created by minigzip can still be extracted by
+ * gzip.)
+ */
+#ifndef MAX_WBITS
+#  define MAX_WBITS   15 /* 32K LZ77 window */
+#endif
+
+/* The memory requirements for deflate are (in bytes):
+            (1 << (windowBits+2)) +  (1 << (memLevel+9))
+ that is: 128K for windowBits=15  +  128K for memLevel = 8  (default values)
+ plus a few kilobytes for small objects. For example, if you want to reduce
+ the default memory requirements from 256K to 128K, compile with
+     make CFLAGS="-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7"
+ Of course this will generally degrade compression (there's no free lunch).
+
+   The memory requirements for inflate are (in bytes) 1 << windowBits
+ that is, 32K for windowBits=15 (default value) plus about 7 kilobytes
+ for small objects.
+*/
+
+                        /* Type declarations */
+
+#ifndef OF /* function prototypes */
+#  ifdef STDC
+#    define OF(args)  args
+#  else
+#    define OF(args)  ()
+#  endif
+#endif
+
+#ifndef Z_ARG /* function prototypes for stdarg */
+#  if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#    define Z_ARG(args)  args
+#  else
+#    define Z_ARG(args)  ()
+#  endif
+#endif
+
+/* The following definitions for FAR are needed only for MSDOS mixed
+ * model programming (small or medium model with some far allocations).
+ * This was tested only with MSC; for other MSDOS compilers you may have
+ * to define NO_MEMCPY in zutil.h.  If you don't need the mixed model,
+ * just define FAR to be empty.
+ */
+#ifdef SYS16BIT
+#  if defined(M_I86SM) || defined(M_I86MM)
+     /* MSC small or medium model */
+#    define SMALL_MEDIUM
+#    ifdef _MSC_VER
+#      define FAR _far
+#    else
+#      define FAR far
+#    endif
+#  endif
+#  if (defined(__SMALL__) || defined(__MEDIUM__))
+     /* Turbo C small or medium model */
+#    define SMALL_MEDIUM
+#    ifdef __BORLANDC__
+#      define FAR _far
+#    else
+#      define FAR far
+#    endif
+#  endif
+#endif
+
+#if defined(WINDOWS) || defined(WIN32)
+   /* If building or using zlib as a DLL, define ZLIB_DLL.
+    * This is not mandatory, but it offers a little performance increase.
+    */
+#  ifdef ZLIB_DLL
+#    if defined(WIN32) && (!defined(__BORLANDC__) || (__BORLANDC__ >= 0x500))
+#      ifdef ZLIB_INTERNAL
+#        define ZEXTERN extern __declspec(dllexport)
+#      else
+#        define ZEXTERN extern __declspec(dllimport)
+#      endif
+#    endif
+#  endif  /* ZLIB_DLL */
+   /* If building or using zlib with the WINAPI/WINAPIV calling convention,
+    * define ZLIB_WINAPI.
+    * Caution: the standard ZLIB1.DLL is NOT compiled using ZLIB_WINAPI.
+    */
+#  ifdef ZLIB_WINAPI
+#    ifdef FAR
+#      undef FAR
+#    endif
+#    include <windows.h>
+     /* No need for _export, use ZLIB.DEF instead. */
+     /* For complete Windows compatibility, use WINAPI, not __stdcall. */
+#    define ZEXPORT WINAPI
+#    ifdef WIN32
+#      define ZEXPORTVA WINAPIV
+#    else
+#      define ZEXPORTVA FAR CDECL
+#    endif
+#  endif
+#endif
+
+#if defined (__BEOS__)
+#  ifdef ZLIB_DLL
+#    ifdef ZLIB_INTERNAL
+#      define ZEXPORT   __declspec(dllexport)
+#      define ZEXPORTVA __declspec(dllexport)
+#    else
+#      define ZEXPORT   __declspec(dllimport)
+#      define ZEXPORTVA __declspec(dllimport)
+#    endif
+#  endif
+#endif
+
+#ifndef ZEXTERN
+#  define ZEXTERN extern
+#endif
+#ifndef ZEXPORT
+#  define ZEXPORT
+#endif
+#ifndef ZEXPORTVA
+#  define ZEXPORTVA
+#endif
+
+#ifndef FAR
+#  define FAR
+#endif
+
+#if !defined(__MACTYPES__)
+typedef unsigned char  Byte;  /* 8 bits */
+#endif
+typedef unsigned int   uInt;  /* 16 bits or more */
+typedef unsigned long  uLong; /* 32 bits or more */
+
+#ifdef SMALL_MEDIUM
+   /* Borland C/C++ and some old MSC versions ignore FAR inside typedef */
+#  define Bytef Byte FAR
+#else
+   typedef Byte  FAR Bytef;
+#endif
+typedef char  FAR charf;
+typedef int   FAR intf;
+typedef uInt  FAR uIntf;
+typedef uLong FAR uLongf;
+
+#ifdef STDC
+   typedef void const *voidpc;
+   typedef void FAR   *voidpf;
+   typedef void       *voidp;
+#else
+   typedef Byte const *voidpc;
+   typedef Byte FAR   *voidpf;
+   typedef Byte       *voidp;
+#endif
+
+#if !defined(Z_U4) && !defined(Z_SOLO) && defined(STDC)
+#  include <limits.h>
+#  if (UINT_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned
+#  elif (ULONG_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned long
+#  elif (USHRT_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned short
+#  endif
+#endif
+
+#ifdef Z_U4
+   typedef Z_U4 z_crc_t;
+#else
+   typedef unsigned long z_crc_t;
+#endif
+
+#ifdef HAVE_UNISTD_H    /* may be set to #if 1 by ./configure */
+#  define Z_HAVE_UNISTD_H
+#endif
+
+#ifdef HAVE_STDARG_H    /* may be set to #if 1 by ./configure */
+#  define Z_HAVE_STDARG_H
+#endif
+
+#ifdef STDC
+#  ifndef Z_SOLO
+#    include <sys/types.h>      /* for off_t */
+#  endif
+#endif
+
+#if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#  ifndef Z_SOLO
+#    include <stdarg.h>         /* for va_list */
+#  endif
+#endif
+
+#ifdef _WIN32
+#  ifndef Z_SOLO
+#    include <stddef.h>         /* for wchar_t */
+#  endif
+#endif
+
+/* a little trick to accommodate both "#define _LARGEFILE64_SOURCE" and
+ * "#define _LARGEFILE64_SOURCE 1" as requesting 64-bit operations, (even
+ * though the former does not conform to the LFS document), but considering
+ * both "#undef _LARGEFILE64_SOURCE" and "#define _LARGEFILE64_SOURCE 0" as
+ * equivalently requesting no 64-bit operations
+ */
+#if defined(_LARGEFILE64_SOURCE) && -_LARGEFILE64_SOURCE - -1 == 1
+#  undef _LARGEFILE64_SOURCE
+#endif
+
+#if defined(__WATCOMC__) && !defined(Z_HAVE_UNISTD_H)
+#  define Z_HAVE_UNISTD_H
+#endif
+#ifndef Z_SOLO
+#  if defined(Z_HAVE_UNISTD_H) || defined(_LARGEFILE64_SOURCE)
+#    include <unistd.h>         /* for SEEK_*, off_t, and _LFS64_LARGEFILE */
+#    ifdef VMS
+#      include <unixio.h>       /* for off_t */
+#    endif
+#    ifndef z_off_t
+#      define z_off_t off_t
+#    endif
+#  endif
+#endif
+
+#if defined(_LFS64_LARGEFILE) && _LFS64_LARGEFILE-0
+#  define Z_LFS64
+#endif
+
+#if defined(_LARGEFILE64_SOURCE) && defined(Z_LFS64)
+#  define Z_LARGE64
+#endif
+
+#if defined(_FILE_OFFSET_BITS) && _FILE_OFFSET_BITS-0 == 64 && defined(Z_LFS64)
+#  define Z_WANT64
+#endif
+
+#if !defined(SEEK_SET) && !defined(Z_SOLO)
+#  define SEEK_SET        0       /* Seek from beginning of file.  */
+#  define SEEK_CUR        1       /* Seek from current position.  */
+#  define SEEK_END        2       /* Set file pointer to EOF plus "offset" */
+#endif
+
+#ifndef z_off_t
+#  define z_off_t long
+#endif
+
+#if !defined(_WIN32) && defined(Z_LARGE64)
+#  define z_off64_t off64_t
+#else
+#  if defined(_WIN32) && !defined(__GNUC__) && !defined(Z_SOLO)
+#    define z_off64_t __int64
+#  else
+#    define z_off64_t z_off_t
+#  endif
+#endif
+
+/* MVS linker does not support external names larger than 8 bytes */
+#if defined(__MVS__)
+  #pragma map(deflateInit_,"DEIN")
+  #pragma map(deflateInit2_,"DEIN2")
+  #pragma map(deflateEnd,"DEEND")
+  #pragma map(deflateBound,"DEBND")
+  #pragma map(inflateInit_,"ININ")
+  #pragma map(inflateInit2_,"ININ2")
+  #pragma map(inflateEnd,"INEND")
+  #pragma map(inflateSync,"INSY")
+  #pragma map(inflateSetDictionary,"INSEDI")
+  #pragma map(compressBound,"CMBND")
+  #pragma map(inflate_table,"INTABL")
+  #pragma map(inflate_fast,"INFA")
+  #pragma map(inflate_copyright,"INCOPY")
+#endif
+
+#endif /* ZCONF_H */

ADDED   3rd_party/zlib/zconf.h.cmakein
Index: 3rd_party/zlib/zconf.h.cmakein
==================================================================
--- 3rd_party/zlib/zconf.h.cmakein
+++ 3rd_party/zlib/zconf.h.cmakein
@@ -0,0 +1,536 @@
+/* zconf.h -- configuration of the zlib compression library
+ * Copyright (C) 1995-2016 Jean-loup Gailly, Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* @(#) $Id$ */
+
+#ifndef ZCONF_H
+#define ZCONF_H
+#cmakedefine Z_PREFIX
+#cmakedefine Z_HAVE_UNISTD_H
+
+/*
+ * If you *really* need a unique prefix for all types and library functions,
+ * compile with -DZ_PREFIX. The "standard" zlib should be compiled without it.
+ * Even better than compiling with -DZ_PREFIX would be to use configure to set
+ * this permanently in zconf.h using "./configure --zprefix".
+ */
+#ifdef Z_PREFIX     /* may be set to #if 1 by ./configure */
+#  define Z_PREFIX_SET
+
+/* all linked symbols and init macros */
+#  define _dist_code            z__dist_code
+#  define _length_code          z__length_code
+#  define _tr_align             z__tr_align
+#  define _tr_flush_bits        z__tr_flush_bits
+#  define _tr_flush_block       z__tr_flush_block
+#  define _tr_init              z__tr_init
+#  define _tr_stored_block      z__tr_stored_block
+#  define _tr_tally             z__tr_tally
+#  define adler32               z_adler32
+#  define adler32_combine       z_adler32_combine
+#  define adler32_combine64     z_adler32_combine64
+#  define adler32_z             z_adler32_z
+#  ifndef Z_SOLO
+#    define compress              z_compress
+#    define compress2             z_compress2
+#    define compressBound         z_compressBound
+#  endif
+#  define crc32                 z_crc32
+#  define crc32_combine         z_crc32_combine
+#  define crc32_combine64       z_crc32_combine64
+#  define crc32_z               z_crc32_z
+#  define deflate               z_deflate
+#  define deflateBound          z_deflateBound
+#  define deflateCopy           z_deflateCopy
+#  define deflateEnd            z_deflateEnd
+#  define deflateGetDictionary  z_deflateGetDictionary
+#  define deflateInit           z_deflateInit
+#  define deflateInit2          z_deflateInit2
+#  define deflateInit2_         z_deflateInit2_
+#  define deflateInit_          z_deflateInit_
+#  define deflateParams         z_deflateParams
+#  define deflatePending        z_deflatePending
+#  define deflatePrime          z_deflatePrime
+#  define deflateReset          z_deflateReset
+#  define deflateResetKeep      z_deflateResetKeep
+#  define deflateSetDictionary  z_deflateSetDictionary
+#  define deflateSetHeader      z_deflateSetHeader
+#  define deflateTune           z_deflateTune
+#  define deflate_copyright     z_deflate_copyright
+#  define get_crc_table         z_get_crc_table
+#  ifndef Z_SOLO
+#    define gz_error              z_gz_error
+#    define gz_intmax             z_gz_intmax
+#    define gz_strwinerror        z_gz_strwinerror
+#    define gzbuffer              z_gzbuffer
+#    define gzclearerr            z_gzclearerr
+#    define gzclose               z_gzclose
+#    define gzclose_r             z_gzclose_r
+#    define gzclose_w             z_gzclose_w
+#    define gzdirect              z_gzdirect
+#    define gzdopen               z_gzdopen
+#    define gzeof                 z_gzeof
+#    define gzerror               z_gzerror
+#    define gzflush               z_gzflush
+#    define gzfread               z_gzfread
+#    define gzfwrite              z_gzfwrite
+#    define gzgetc                z_gzgetc
+#    define gzgetc_               z_gzgetc_
+#    define gzgets                z_gzgets
+#    define gzoffset              z_gzoffset
+#    define gzoffset64            z_gzoffset64
+#    define gzopen                z_gzopen
+#    define gzopen64              z_gzopen64
+#    ifdef _WIN32
+#      define gzopen_w              z_gzopen_w
+#    endif
+#    define gzprintf              z_gzprintf
+#    define gzputc                z_gzputc
+#    define gzputs                z_gzputs
+#    define gzread                z_gzread
+#    define gzrewind              z_gzrewind
+#    define gzseek                z_gzseek
+#    define gzseek64              z_gzseek64
+#    define gzsetparams           z_gzsetparams
+#    define gztell                z_gztell
+#    define gztell64              z_gztell64
+#    define gzungetc              z_gzungetc
+#    define gzvprintf             z_gzvprintf
+#    define gzwrite               z_gzwrite
+#  endif
+#  define inflate               z_inflate
+#  define inflateBack           z_inflateBack
+#  define inflateBackEnd        z_inflateBackEnd
+#  define inflateBackInit       z_inflateBackInit
+#  define inflateBackInit_      z_inflateBackInit_
+#  define inflateCodesUsed      z_inflateCodesUsed
+#  define inflateCopy           z_inflateCopy
+#  define inflateEnd            z_inflateEnd
+#  define inflateGetDictionary  z_inflateGetDictionary
+#  define inflateGetHeader      z_inflateGetHeader
+#  define inflateInit           z_inflateInit
+#  define inflateInit2          z_inflateInit2
+#  define inflateInit2_         z_inflateInit2_
+#  define inflateInit_          z_inflateInit_
+#  define inflateMark           z_inflateMark
+#  define inflatePrime          z_inflatePrime
+#  define inflateReset          z_inflateReset
+#  define inflateReset2         z_inflateReset2
+#  define inflateResetKeep      z_inflateResetKeep
+#  define inflateSetDictionary  z_inflateSetDictionary
+#  define inflateSync           z_inflateSync
+#  define inflateSyncPoint      z_inflateSyncPoint
+#  define inflateUndermine      z_inflateUndermine
+#  define inflateValidate       z_inflateValidate
+#  define inflate_copyright     z_inflate_copyright
+#  define inflate_fast          z_inflate_fast
+#  define inflate_table         z_inflate_table
+#  ifndef Z_SOLO
+#    define uncompress            z_uncompress
+#    define uncompress2           z_uncompress2
+#  endif
+#  define zError                z_zError
+#  ifndef Z_SOLO
+#    define zcalloc               z_zcalloc
+#    define zcfree                z_zcfree
+#  endif
+#  define zlibCompileFlags      z_zlibCompileFlags
+#  define zlibVersion           z_zlibVersion
+
+/* all zlib typedefs in zlib.h and zconf.h */
+#  define Byte                  z_Byte
+#  define Bytef                 z_Bytef
+#  define alloc_func            z_alloc_func
+#  define charf                 z_charf
+#  define free_func             z_free_func
+#  ifndef Z_SOLO
+#    define gzFile                z_gzFile
+#  endif
+#  define gz_header             z_gz_header
+#  define gz_headerp            z_gz_headerp
+#  define in_func               z_in_func
+#  define intf                  z_intf
+#  define out_func              z_out_func
+#  define uInt                  z_uInt
+#  define uIntf                 z_uIntf
+#  define uLong                 z_uLong
+#  define uLongf                z_uLongf
+#  define voidp                 z_voidp
+#  define voidpc                z_voidpc
+#  define voidpf                z_voidpf
+
+/* all zlib structs in zlib.h and zconf.h */
+#  define gz_header_s           z_gz_header_s
+#  define internal_state        z_internal_state
+
+#endif
+
+#if defined(__MSDOS__) && !defined(MSDOS)
+#  define MSDOS
+#endif
+#if (defined(OS_2) || defined(__OS2__)) && !defined(OS2)
+#  define OS2
+#endif
+#if defined(_WINDOWS) && !defined(WINDOWS)
+#  define WINDOWS
+#endif
+#if defined(_WIN32) || defined(_WIN32_WCE) || defined(__WIN32__)
+#  ifndef WIN32
+#    define WIN32
+#  endif
+#endif
+#if (defined(MSDOS) || defined(OS2) || defined(WINDOWS)) && !defined(WIN32)
+#  if !defined(__GNUC__) && !defined(__FLAT__) && !defined(__386__)
+#    ifndef SYS16BIT
+#      define SYS16BIT
+#    endif
+#  endif
+#endif
+
+/*
+ * Compile with -DMAXSEG_64K if the alloc function cannot allocate more
+ * than 64k bytes at a time (needed on systems with 16-bit int).
+ */
+#ifdef SYS16BIT
+#  define MAXSEG_64K
+#endif
+#ifdef MSDOS
+#  define UNALIGNED_OK
+#endif
+
+#ifdef __STDC_VERSION__
+#  ifndef STDC
+#    define STDC
+#  endif
+#  if __STDC_VERSION__ >= 199901L
+#    ifndef STDC99
+#      define STDC99
+#    endif
+#  endif
+#endif
+#if !defined(STDC) && (defined(__STDC__) || defined(__cplusplus))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(__GNUC__) || defined(__BORLANDC__))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(MSDOS) || defined(WINDOWS) || defined(WIN32))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(OS2) || defined(__HOS_AIX__))
+#  define STDC
+#endif
+
+#if defined(__OS400__) && !defined(STDC)    /* iSeries (formerly AS/400). */
+#  define STDC
+#endif
+
+#ifndef STDC
+#  ifndef const /* cannot use !defined(STDC) && !defined(const) on Mac */
+#    define const       /* note: need a more gentle solution here */
+#  endif
+#endif
+
+#if defined(ZLIB_CONST) && !defined(z_const)
+#  define z_const const
+#else
+#  define z_const
+#endif
+
+#ifdef Z_SOLO
+   typedef unsigned long z_size_t;
+#else
+#  define z_longlong long long
+#  if defined(NO_SIZE_T)
+     typedef unsigned NO_SIZE_T z_size_t;
+#  elif defined(STDC)
+#    include <stddef.h>
+     typedef size_t z_size_t;
+#  else
+     typedef unsigned long z_size_t;
+#  endif
+#  undef z_longlong
+#endif
+
+/* Maximum value for memLevel in deflateInit2 */
+#ifndef MAX_MEM_LEVEL
+#  ifdef MAXSEG_64K
+#    define MAX_MEM_LEVEL 8
+#  else
+#    define MAX_MEM_LEVEL 9
+#  endif
+#endif
+
+/* Maximum value for windowBits in deflateInit2 and inflateInit2.
+ * WARNING: reducing MAX_WBITS makes minigzip unable to extract .gz files
+ * created by gzip. (Files created by minigzip can still be extracted by
+ * gzip.)
+ */
+#ifndef MAX_WBITS
+#  define MAX_WBITS   15 /* 32K LZ77 window */
+#endif
+
+/* The memory requirements for deflate are (in bytes):
+            (1 << (windowBits+2)) +  (1 << (memLevel+9))
+ that is: 128K for windowBits=15  +  128K for memLevel = 8  (default values)
+ plus a few kilobytes for small objects. For example, if you want to reduce
+ the default memory requirements from 256K to 128K, compile with
+     make CFLAGS="-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7"
+ Of course this will generally degrade compression (there's no free lunch).
+
+   The memory requirements for inflate are (in bytes) 1 << windowBits
+ that is, 32K for windowBits=15 (default value) plus about 7 kilobytes
+ for small objects.
+*/
+
+                        /* Type declarations */
+
+#ifndef OF /* function prototypes */
+#  ifdef STDC
+#    define OF(args)  args
+#  else
+#    define OF(args)  ()
+#  endif
+#endif
+
+#ifndef Z_ARG /* function prototypes for stdarg */
+#  if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#    define Z_ARG(args)  args
+#  else
+#    define Z_ARG(args)  ()
+#  endif
+#endif
+
+/* The following definitions for FAR are needed only for MSDOS mixed
+ * model programming (small or medium model with some far allocations).
+ * This was tested only with MSC; for other MSDOS compilers you may have
+ * to define NO_MEMCPY in zutil.h.  If you don't need the mixed model,
+ * just define FAR to be empty.
+ */
+#ifdef SYS16BIT
+#  if defined(M_I86SM) || defined(M_I86MM)
+     /* MSC small or medium model */
+#    define SMALL_MEDIUM
+#    ifdef _MSC_VER
+#      define FAR _far
+#    else
+#      define FAR far
+#    endif
+#  endif
+#  if (defined(__SMALL__) || defined(__MEDIUM__))
+     /* Turbo C small or medium model */
+#    define SMALL_MEDIUM
+#    ifdef __BORLANDC__
+#      define FAR _far
+#    else
+#      define FAR far
+#    endif
+#  endif
+#endif
+
+#if defined(WINDOWS) || defined(WIN32)
+   /* If building or using zlib as a DLL, define ZLIB_DLL.
+    * This is not mandatory, but it offers a little performance increase.
+    */
+#  ifdef ZLIB_DLL
+#    if defined(WIN32) && (!defined(__BORLANDC__) || (__BORLANDC__ >= 0x500))
+#      ifdef ZLIB_INTERNAL
+#        define ZEXTERN extern __declspec(dllexport)
+#      else
+#        define ZEXTERN extern __declspec(dllimport)
+#      endif
+#    endif
+#  endif  /* ZLIB_DLL */
+   /* If building or using zlib with the WINAPI/WINAPIV calling convention,
+    * define ZLIB_WINAPI.
+    * Caution: the standard ZLIB1.DLL is NOT compiled using ZLIB_WINAPI.
+    */
+#  ifdef ZLIB_WINAPI
+#    ifdef FAR
+#      undef FAR
+#    endif
+#    include <windows.h>
+     /* No need for _export, use ZLIB.DEF instead. */
+     /* For complete Windows compatibility, use WINAPI, not __stdcall. */
+#    define ZEXPORT WINAPI
+#    ifdef WIN32
+#      define ZEXPORTVA WINAPIV
+#    else
+#      define ZEXPORTVA FAR CDECL
+#    endif
+#  endif
+#endif
+
+#if defined (__BEOS__)
+#  ifdef ZLIB_DLL
+#    ifdef ZLIB_INTERNAL
+#      define ZEXPORT   __declspec(dllexport)
+#      define ZEXPORTVA __declspec(dllexport)
+#    else
+#      define ZEXPORT   __declspec(dllimport)
+#      define ZEXPORTVA __declspec(dllimport)
+#    endif
+#  endif
+#endif
+
+#ifndef ZEXTERN
+#  define ZEXTERN extern
+#endif
+#ifndef ZEXPORT
+#  define ZEXPORT
+#endif
+#ifndef ZEXPORTVA
+#  define ZEXPORTVA
+#endif
+
+#ifndef FAR
+#  define FAR
+#endif
+
+#if !defined(__MACTYPES__)
+typedef unsigned char  Byte;  /* 8 bits */
+#endif
+typedef unsigned int   uInt;  /* 16 bits or more */
+typedef unsigned long  uLong; /* 32 bits or more */
+
+#ifdef SMALL_MEDIUM
+   /* Borland C/C++ and some old MSC versions ignore FAR inside typedef */
+#  define Bytef Byte FAR
+#else
+   typedef Byte  FAR Bytef;
+#endif
+typedef char  FAR charf;
+typedef int   FAR intf;
+typedef uInt  FAR uIntf;
+typedef uLong FAR uLongf;
+
+#ifdef STDC
+   typedef void const *voidpc;
+   typedef void FAR   *voidpf;
+   typedef void       *voidp;
+#else
+   typedef Byte const *voidpc;
+   typedef Byte FAR   *voidpf;
+   typedef Byte       *voidp;
+#endif
+
+#if !defined(Z_U4) && !defined(Z_SOLO) && defined(STDC)
+#  include <limits.h>
+#  if (UINT_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned
+#  elif (ULONG_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned long
+#  elif (USHRT_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned short
+#  endif
+#endif
+
+#ifdef Z_U4
+   typedef Z_U4 z_crc_t;
+#else
+   typedef unsigned long z_crc_t;
+#endif
+
+#ifdef HAVE_UNISTD_H    /* may be set to #if 1 by ./configure */
+#  define Z_HAVE_UNISTD_H
+#endif
+
+#ifdef HAVE_STDARG_H    /* may be set to #if 1 by ./configure */
+#  define Z_HAVE_STDARG_H
+#endif
+
+#ifdef STDC
+#  ifndef Z_SOLO
+#    include <sys/types.h>      /* for off_t */
+#  endif
+#endif
+
+#if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#  ifndef Z_SOLO
+#    include <stdarg.h>         /* for va_list */
+#  endif
+#endif
+
+#ifdef _WIN32
+#  ifndef Z_SOLO
+#    include <stddef.h>         /* for wchar_t */
+#  endif
+#endif
+
+/* a little trick to accommodate both "#define _LARGEFILE64_SOURCE" and
+ * "#define _LARGEFILE64_SOURCE 1" as requesting 64-bit operations, (even
+ * though the former does not conform to the LFS document), but considering
+ * both "#undef _LARGEFILE64_SOURCE" and "#define _LARGEFILE64_SOURCE 0" as
+ * equivalently requesting no 64-bit operations
+ */
+#if defined(_LARGEFILE64_SOURCE) && -_LARGEFILE64_SOURCE - -1 == 1
+#  undef _LARGEFILE64_SOURCE
+#endif
+
+#if defined(__WATCOMC__) && !defined(Z_HAVE_UNISTD_H)
+#  define Z_HAVE_UNISTD_H
+#endif
+#ifndef Z_SOLO
+#  if defined(Z_HAVE_UNISTD_H) || defined(_LARGEFILE64_SOURCE)
+#    include <unistd.h>         /* for SEEK_*, off_t, and _LFS64_LARGEFILE */
+#    ifdef VMS
+#      include <unixio.h>       /* for off_t */
+#    endif
+#    ifndef z_off_t
+#      define z_off_t off_t
+#    endif
+#  endif
+#endif
+
+#if defined(_LFS64_LARGEFILE) && _LFS64_LARGEFILE-0
+#  define Z_LFS64
+#endif
+
+#if defined(_LARGEFILE64_SOURCE) && defined(Z_LFS64)
+#  define Z_LARGE64
+#endif
+
+#if defined(_FILE_OFFSET_BITS) && _FILE_OFFSET_BITS-0 == 64 && defined(Z_LFS64)
+#  define Z_WANT64
+#endif
+
+#if !defined(SEEK_SET) && !defined(Z_SOLO)
+#  define SEEK_SET        0       /* Seek from beginning of file.  */
+#  define SEEK_CUR        1       /* Seek from current position.  */
+#  define SEEK_END        2       /* Set file pointer to EOF plus "offset" */
+#endif
+
+#ifndef z_off_t
+#  define z_off_t long
+#endif
+
+#if !defined(_WIN32) && defined(Z_LARGE64)
+#  define z_off64_t off64_t
+#else
+#  if defined(_WIN32) && !defined(__GNUC__) && !defined(Z_SOLO)
+#    define z_off64_t __int64
+#  else
+#    define z_off64_t z_off_t
+#  endif
+#endif
+
+/* MVS linker does not support external names larger than 8 bytes */
+#if defined(__MVS__)
+  #pragma map(deflateInit_,"DEIN")
+  #pragma map(deflateInit2_,"DEIN2")
+  #pragma map(deflateEnd,"DEEND")
+  #pragma map(deflateBound,"DEBND")
+  #pragma map(inflateInit_,"ININ")
+  #pragma map(inflateInit2_,"ININ2")
+  #pragma map(inflateEnd,"INEND")
+  #pragma map(inflateSync,"INSY")
+  #pragma map(inflateSetDictionary,"INSEDI")
+  #pragma map(compressBound,"CMBND")
+  #pragma map(inflate_table,"INTABL")
+  #pragma map(inflate_fast,"INFA")
+  #pragma map(inflate_copyright,"INCOPY")
+#endif
+
+#endif /* ZCONF_H */

ADDED   3rd_party/zlib/zconf.h.in
Index: 3rd_party/zlib/zconf.h.in
==================================================================
--- 3rd_party/zlib/zconf.h.in
+++ 3rd_party/zlib/zconf.h.in
@@ -0,0 +1,534 @@
+/* zconf.h -- configuration of the zlib compression library
+ * Copyright (C) 1995-2016 Jean-loup Gailly, Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* @(#) $Id$ */
+
+#ifndef ZCONF_H
+#define ZCONF_H
+
+/*
+ * If you *really* need a unique prefix for all types and library functions,
+ * compile with -DZ_PREFIX. The "standard" zlib should be compiled without it.
+ * Even better than compiling with -DZ_PREFIX would be to use configure to set
+ * this permanently in zconf.h using "./configure --zprefix".
+ */
+#ifdef Z_PREFIX     /* may be set to #if 1 by ./configure */
+#  define Z_PREFIX_SET
+
+/* all linked symbols and init macros */
+#  define _dist_code            z__dist_code
+#  define _length_code          z__length_code
+#  define _tr_align             z__tr_align
+#  define _tr_flush_bits        z__tr_flush_bits
+#  define _tr_flush_block       z__tr_flush_block
+#  define _tr_init              z__tr_init
+#  define _tr_stored_block      z__tr_stored_block
+#  define _tr_tally             z__tr_tally
+#  define adler32               z_adler32
+#  define adler32_combine       z_adler32_combine
+#  define adler32_combine64     z_adler32_combine64
+#  define adler32_z             z_adler32_z
+#  ifndef Z_SOLO
+#    define compress              z_compress
+#    define compress2             z_compress2
+#    define compressBound         z_compressBound
+#  endif
+#  define crc32                 z_crc32
+#  define crc32_combine         z_crc32_combine
+#  define crc32_combine64       z_crc32_combine64
+#  define crc32_z               z_crc32_z
+#  define deflate               z_deflate
+#  define deflateBound          z_deflateBound
+#  define deflateCopy           z_deflateCopy
+#  define deflateEnd            z_deflateEnd
+#  define deflateGetDictionary  z_deflateGetDictionary
+#  define deflateInit           z_deflateInit
+#  define deflateInit2          z_deflateInit2
+#  define deflateInit2_         z_deflateInit2_
+#  define deflateInit_          z_deflateInit_
+#  define deflateParams         z_deflateParams
+#  define deflatePending        z_deflatePending
+#  define deflatePrime          z_deflatePrime
+#  define deflateReset          z_deflateReset
+#  define deflateResetKeep      z_deflateResetKeep
+#  define deflateSetDictionary  z_deflateSetDictionary
+#  define deflateSetHeader      z_deflateSetHeader
+#  define deflateTune           z_deflateTune
+#  define deflate_copyright     z_deflate_copyright
+#  define get_crc_table         z_get_crc_table
+#  ifndef Z_SOLO
+#    define gz_error              z_gz_error
+#    define gz_intmax             z_gz_intmax
+#    define gz_strwinerror        z_gz_strwinerror
+#    define gzbuffer              z_gzbuffer
+#    define gzclearerr            z_gzclearerr
+#    define gzclose               z_gzclose
+#    define gzclose_r             z_gzclose_r
+#    define gzclose_w             z_gzclose_w
+#    define gzdirect              z_gzdirect
+#    define gzdopen               z_gzdopen
+#    define gzeof                 z_gzeof
+#    define gzerror               z_gzerror
+#    define gzflush               z_gzflush
+#    define gzfread               z_gzfread
+#    define gzfwrite              z_gzfwrite
+#    define gzgetc                z_gzgetc
+#    define gzgetc_               z_gzgetc_
+#    define gzgets                z_gzgets
+#    define gzoffset              z_gzoffset
+#    define gzoffset64            z_gzoffset64
+#    define gzopen                z_gzopen
+#    define gzopen64              z_gzopen64
+#    ifdef _WIN32
+#      define gzopen_w              z_gzopen_w
+#    endif
+#    define gzprintf              z_gzprintf
+#    define gzputc                z_gzputc
+#    define gzputs                z_gzputs
+#    define gzread                z_gzread
+#    define gzrewind              z_gzrewind
+#    define gzseek                z_gzseek
+#    define gzseek64              z_gzseek64
+#    define gzsetparams           z_gzsetparams
+#    define gztell                z_gztell
+#    define gztell64              z_gztell64
+#    define gzungetc              z_gzungetc
+#    define gzvprintf             z_gzvprintf
+#    define gzwrite               z_gzwrite
+#  endif
+#  define inflate               z_inflate
+#  define inflateBack           z_inflateBack
+#  define inflateBackEnd        z_inflateBackEnd
+#  define inflateBackInit       z_inflateBackInit
+#  define inflateBackInit_      z_inflateBackInit_
+#  define inflateCodesUsed      z_inflateCodesUsed
+#  define inflateCopy           z_inflateCopy
+#  define inflateEnd            z_inflateEnd
+#  define inflateGetDictionary  z_inflateGetDictionary
+#  define inflateGetHeader      z_inflateGetHeader
+#  define inflateInit           z_inflateInit
+#  define inflateInit2          z_inflateInit2
+#  define inflateInit2_         z_inflateInit2_
+#  define inflateInit_          z_inflateInit_
+#  define inflateMark           z_inflateMark
+#  define inflatePrime          z_inflatePrime
+#  define inflateReset          z_inflateReset
+#  define inflateReset2         z_inflateReset2
+#  define inflateResetKeep      z_inflateResetKeep
+#  define inflateSetDictionary  z_inflateSetDictionary
+#  define inflateSync           z_inflateSync
+#  define inflateSyncPoint      z_inflateSyncPoint
+#  define inflateUndermine      z_inflateUndermine
+#  define inflateValidate       z_inflateValidate
+#  define inflate_copyright     z_inflate_copyright
+#  define inflate_fast          z_inflate_fast
+#  define inflate_table         z_inflate_table
+#  ifndef Z_SOLO
+#    define uncompress            z_uncompress
+#    define uncompress2           z_uncompress2
+#  endif
+#  define zError                z_zError
+#  ifndef Z_SOLO
+#    define zcalloc               z_zcalloc
+#    define zcfree                z_zcfree
+#  endif
+#  define zlibCompileFlags      z_zlibCompileFlags
+#  define zlibVersion           z_zlibVersion
+
+/* all zlib typedefs in zlib.h and zconf.h */
+#  define Byte                  z_Byte
+#  define Bytef                 z_Bytef
+#  define alloc_func            z_alloc_func
+#  define charf                 z_charf
+#  define free_func             z_free_func
+#  ifndef Z_SOLO
+#    define gzFile                z_gzFile
+#  endif
+#  define gz_header             z_gz_header
+#  define gz_headerp            z_gz_headerp
+#  define in_func               z_in_func
+#  define intf                  z_intf
+#  define out_func              z_out_func
+#  define uInt                  z_uInt
+#  define uIntf                 z_uIntf
+#  define uLong                 z_uLong
+#  define uLongf                z_uLongf
+#  define voidp                 z_voidp
+#  define voidpc                z_voidpc
+#  define voidpf                z_voidpf
+
+/* all zlib structs in zlib.h and zconf.h */
+#  define gz_header_s           z_gz_header_s
+#  define internal_state        z_internal_state
+
+#endif
+
+#if defined(__MSDOS__) && !defined(MSDOS)
+#  define MSDOS
+#endif
+#if (defined(OS_2) || defined(__OS2__)) && !defined(OS2)
+#  define OS2
+#endif
+#if defined(_WINDOWS) && !defined(WINDOWS)
+#  define WINDOWS
+#endif
+#if defined(_WIN32) || defined(_WIN32_WCE) || defined(__WIN32__)
+#  ifndef WIN32
+#    define WIN32
+#  endif
+#endif
+#if (defined(MSDOS) || defined(OS2) || defined(WINDOWS)) && !defined(WIN32)
+#  if !defined(__GNUC__) && !defined(__FLAT__) && !defined(__386__)
+#    ifndef SYS16BIT
+#      define SYS16BIT
+#    endif
+#  endif
+#endif
+
+/*
+ * Compile with -DMAXSEG_64K if the alloc function cannot allocate more
+ * than 64k bytes at a time (needed on systems with 16-bit int).
+ */
+#ifdef SYS16BIT
+#  define MAXSEG_64K
+#endif
+#ifdef MSDOS
+#  define UNALIGNED_OK
+#endif
+
+#ifdef __STDC_VERSION__
+#  ifndef STDC
+#    define STDC
+#  endif
+#  if __STDC_VERSION__ >= 199901L
+#    ifndef STDC99
+#      define STDC99
+#    endif
+#  endif
+#endif
+#if !defined(STDC) && (defined(__STDC__) || defined(__cplusplus))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(__GNUC__) || defined(__BORLANDC__))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(MSDOS) || defined(WINDOWS) || defined(WIN32))
+#  define STDC
+#endif
+#if !defined(STDC) && (defined(OS2) || defined(__HOS_AIX__))
+#  define STDC
+#endif
+
+#if defined(__OS400__) && !defined(STDC)    /* iSeries (formerly AS/400). */
+#  define STDC
+#endif
+
+#ifndef STDC
+#  ifndef const /* cannot use !defined(STDC) && !defined(const) on Mac */
+#    define const       /* note: need a more gentle solution here */
+#  endif
+#endif
+
+#if defined(ZLIB_CONST) && !defined(z_const)
+#  define z_const const
+#else
+#  define z_const
+#endif
+
+#ifdef Z_SOLO
+   typedef unsigned long z_size_t;
+#else
+#  define z_longlong long long
+#  if defined(NO_SIZE_T)
+     typedef unsigned NO_SIZE_T z_size_t;
+#  elif defined(STDC)
+#    include <stddef.h>
+     typedef size_t z_size_t;
+#  else
+     typedef unsigned long z_size_t;
+#  endif
+#  undef z_longlong
+#endif
+
+/* Maximum value for memLevel in deflateInit2 */
+#ifndef MAX_MEM_LEVEL
+#  ifdef MAXSEG_64K
+#    define MAX_MEM_LEVEL 8
+#  else
+#    define MAX_MEM_LEVEL 9
+#  endif
+#endif
+
+/* Maximum value for windowBits in deflateInit2 and inflateInit2.
+ * WARNING: reducing MAX_WBITS makes minigzip unable to extract .gz files
+ * created by gzip. (Files created by minigzip can still be extracted by
+ * gzip.)
+ */
+#ifndef MAX_WBITS
+#  define MAX_WBITS   15 /* 32K LZ77 window */
+#endif
+
+/* The memory requirements for deflate are (in bytes):
+            (1 << (windowBits+2)) +  (1 << (memLevel+9))
+ that is: 128K for windowBits=15  +  128K for memLevel = 8  (default values)
+ plus a few kilobytes for small objects. For example, if you want to reduce
+ the default memory requirements from 256K to 128K, compile with
+     make CFLAGS="-O -DMAX_WBITS=14 -DMAX_MEM_LEVEL=7"
+ Of course this will generally degrade compression (there's no free lunch).
+
+   The memory requirements for inflate are (in bytes) 1 << windowBits
+ that is, 32K for windowBits=15 (default value) plus about 7 kilobytes
+ for small objects.
+*/
+
+                        /* Type declarations */
+
+#ifndef OF /* function prototypes */
+#  ifdef STDC
+#    define OF(args)  args
+#  else
+#    define OF(args)  ()
+#  endif
+#endif
+
+#ifndef Z_ARG /* function prototypes for stdarg */
+#  if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#    define Z_ARG(args)  args
+#  else
+#    define Z_ARG(args)  ()
+#  endif
+#endif
+
+/* The following definitions for FAR are needed only for MSDOS mixed
+ * model programming (small or medium model with some far allocations).
+ * This was tested only with MSC; for other MSDOS compilers you may have
+ * to define NO_MEMCPY in zutil.h.  If you don't need the mixed model,
+ * just define FAR to be empty.
+ */
+#ifdef SYS16BIT
+#  if defined(M_I86SM) || defined(M_I86MM)
+     /* MSC small or medium model */
+#    define SMALL_MEDIUM
+#    ifdef _MSC_VER
+#      define FAR _far
+#    else
+#      define FAR far
+#    endif
+#  endif
+#  if (defined(__SMALL__) || defined(__MEDIUM__))
+     /* Turbo C small or medium model */
+#    define SMALL_MEDIUM
+#    ifdef __BORLANDC__
+#      define FAR _far
+#    else
+#      define FAR far
+#    endif
+#  endif
+#endif
+
+#if defined(WINDOWS) || defined(WIN32)
+   /* If building or using zlib as a DLL, define ZLIB_DLL.
+    * This is not mandatory, but it offers a little performance increase.
+    */
+#  ifdef ZLIB_DLL
+#    if defined(WIN32) && (!defined(__BORLANDC__) || (__BORLANDC__ >= 0x500))
+#      ifdef ZLIB_INTERNAL
+#        define ZEXTERN extern __declspec(dllexport)
+#      else
+#        define ZEXTERN extern __declspec(dllimport)
+#      endif
+#    endif
+#  endif  /* ZLIB_DLL */
+   /* If building or using zlib with the WINAPI/WINAPIV calling convention,
+    * define ZLIB_WINAPI.
+    * Caution: the standard ZLIB1.DLL is NOT compiled using ZLIB_WINAPI.
+    */
+#  ifdef ZLIB_WINAPI
+#    ifdef FAR
+#      undef FAR
+#    endif
+#    include <windows.h>
+     /* No need for _export, use ZLIB.DEF instead. */
+     /* For complete Windows compatibility, use WINAPI, not __stdcall. */
+#    define ZEXPORT WINAPI
+#    ifdef WIN32
+#      define ZEXPORTVA WINAPIV
+#    else
+#      define ZEXPORTVA FAR CDECL
+#    endif
+#  endif
+#endif
+
+#if defined (__BEOS__)
+#  ifdef ZLIB_DLL
+#    ifdef ZLIB_INTERNAL
+#      define ZEXPORT   __declspec(dllexport)
+#      define ZEXPORTVA __declspec(dllexport)
+#    else
+#      define ZEXPORT   __declspec(dllimport)
+#      define ZEXPORTVA __declspec(dllimport)
+#    endif
+#  endif
+#endif
+
+#ifndef ZEXTERN
+#  define ZEXTERN extern
+#endif
+#ifndef ZEXPORT
+#  define ZEXPORT
+#endif
+#ifndef ZEXPORTVA
+#  define ZEXPORTVA
+#endif
+
+#ifndef FAR
+#  define FAR
+#endif
+
+#if !defined(__MACTYPES__)
+typedef unsigned char  Byte;  /* 8 bits */
+#endif
+typedef unsigned int   uInt;  /* 16 bits or more */
+typedef unsigned long  uLong; /* 32 bits or more */
+
+#ifdef SMALL_MEDIUM
+   /* Borland C/C++ and some old MSC versions ignore FAR inside typedef */
+#  define Bytef Byte FAR
+#else
+   typedef Byte  FAR Bytef;
+#endif
+typedef char  FAR charf;
+typedef int   FAR intf;
+typedef uInt  FAR uIntf;
+typedef uLong FAR uLongf;
+
+#ifdef STDC
+   typedef void const *voidpc;
+   typedef void FAR   *voidpf;
+   typedef void       *voidp;
+#else
+   typedef Byte const *voidpc;
+   typedef Byte FAR   *voidpf;
+   typedef Byte       *voidp;
+#endif
+
+#if !defined(Z_U4) && !defined(Z_SOLO) && defined(STDC)
+#  include <limits.h>
+#  if (UINT_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned
+#  elif (ULONG_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned long
+#  elif (USHRT_MAX == 0xffffffffUL)
+#    define Z_U4 unsigned short
+#  endif
+#endif
+
+#ifdef Z_U4
+   typedef Z_U4 z_crc_t;
+#else
+   typedef unsigned long z_crc_t;
+#endif
+
+#ifdef HAVE_UNISTD_H    /* may be set to #if 1 by ./configure */
+#  define Z_HAVE_UNISTD_H
+#endif
+
+#ifdef HAVE_STDARG_H    /* may be set to #if 1 by ./configure */
+#  define Z_HAVE_STDARG_H
+#endif
+
+#ifdef STDC
+#  ifndef Z_SOLO
+#    include <sys/types.h>      /* for off_t */
+#  endif
+#endif
+
+#if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#  ifndef Z_SOLO
+#    include <stdarg.h>         /* for va_list */
+#  endif
+#endif
+
+#ifdef _WIN32
+#  ifndef Z_SOLO
+#    include <stddef.h>         /* for wchar_t */
+#  endif
+#endif
+
+/* a little trick to accommodate both "#define _LARGEFILE64_SOURCE" and
+ * "#define _LARGEFILE64_SOURCE 1" as requesting 64-bit operations, (even
+ * though the former does not conform to the LFS document), but considering
+ * both "#undef _LARGEFILE64_SOURCE" and "#define _LARGEFILE64_SOURCE 0" as
+ * equivalently requesting no 64-bit operations
+ */
+#if defined(_LARGEFILE64_SOURCE) && -_LARGEFILE64_SOURCE - -1 == 1
+#  undef _LARGEFILE64_SOURCE
+#endif
+
+#if defined(__WATCOMC__) && !defined(Z_HAVE_UNISTD_H)
+#  define Z_HAVE_UNISTD_H
+#endif
+#ifndef Z_SOLO
+#  if defined(Z_HAVE_UNISTD_H) || defined(_LARGEFILE64_SOURCE)
+#    include <unistd.h>         /* for SEEK_*, off_t, and _LFS64_LARGEFILE */
+#    ifdef VMS
+#      include <unixio.h>       /* for off_t */
+#    endif
+#    ifndef z_off_t
+#      define z_off_t off_t
+#    endif
+#  endif
+#endif
+
+#if defined(_LFS64_LARGEFILE) && _LFS64_LARGEFILE-0
+#  define Z_LFS64
+#endif
+
+#if defined(_LARGEFILE64_SOURCE) && defined(Z_LFS64)
+#  define Z_LARGE64
+#endif
+
+#if defined(_FILE_OFFSET_BITS) && _FILE_OFFSET_BITS-0 == 64 && defined(Z_LFS64)
+#  define Z_WANT64
+#endif
+
+#if !defined(SEEK_SET) && !defined(Z_SOLO)
+#  define SEEK_SET        0       /* Seek from beginning of file.  */
+#  define SEEK_CUR        1       /* Seek from current position.  */
+#  define SEEK_END        2       /* Set file pointer to EOF plus "offset" */
+#endif
+
+#ifndef z_off_t
+#  define z_off_t long
+#endif
+
+#if !defined(_WIN32) && defined(Z_LARGE64)
+#  define z_off64_t off64_t
+#else
+#  if defined(_WIN32) && !defined(__GNUC__) && !defined(Z_SOLO)
+#    define z_off64_t __int64
+#  else
+#    define z_off64_t z_off_t
+#  endif
+#endif
+
+/* MVS linker does not support external names larger than 8 bytes */
+#if defined(__MVS__)
+  #pragma map(deflateInit_,"DEIN")
+  #pragma map(deflateInit2_,"DEIN2")
+  #pragma map(deflateEnd,"DEEND")
+  #pragma map(deflateBound,"DEBND")
+  #pragma map(inflateInit_,"ININ")
+  #pragma map(inflateInit2_,"ININ2")
+  #pragma map(inflateEnd,"INEND")
+  #pragma map(inflateSync,"INSY")
+  #pragma map(inflateSetDictionary,"INSEDI")
+  #pragma map(compressBound,"CMBND")
+  #pragma map(inflate_table,"INTABL")
+  #pragma map(inflate_fast,"INFA")
+  #pragma map(inflate_copyright,"INCOPY")
+#endif
+
+#endif /* ZCONF_H */

ADDED   3rd_party/zlib/zlib.3
Index: 3rd_party/zlib/zlib.3
==================================================================
--- 3rd_party/zlib/zlib.3
+++ 3rd_party/zlib/zlib.3
@@ -0,0 +1,149 @@
+.TH ZLIB 3 "15 Jan 2017"
+.SH NAME
+zlib \- compression/decompression library
+.SH SYNOPSIS
+[see
+.I zlib.h
+for full description]
+.SH DESCRIPTION
+The
+.I zlib
+library is a general purpose data compression library.
+The code is thread safe, assuming that the standard library functions
+used are thread safe, such as memory allocation routines.
+It provides in-memory compression and decompression functions,
+including integrity checks of the uncompressed data.
+This version of the library supports only one compression method (deflation)
+but other algorithms may be added later
+with the same stream interface.
+.LP
+Compression can be done in a single step if the buffers are large enough
+or can be done by repeated calls of the compression function.
+In the latter case,
+the application must provide more input and/or consume the output
+(providing more output space) before each call.
+.LP
+The library also supports reading and writing files in
+.IR gzip (1)
+(.gz) format
+with an interface similar to that of stdio.
+.LP
+The library does not install any signal handler.
+The decoder checks the consistency of the compressed data,
+so the library should never crash even in the case of corrupted input.
+.LP
+All functions of the compression library are documented in the file
+.IR zlib.h .
+The distribution source includes examples of use of the library
+in the files
+.I test/example.c
+and
+.IR test/minigzip.c,
+as well as other examples in the
+.IR examples/
+directory.
+.LP
+Changes to this version are documented in the file
+.I ChangeLog
+that accompanies the source.
+.LP
+.I zlib
+is built in to many languages and operating systems, including but not limited to
+Java, Python, .NET, PHP, Perl, Ruby, Swift, and Go.
+.LP
+An experimental package to read and write files in the .zip format,
+written on top of
+.I zlib
+by Gilles Vollant (info@winimage.com),
+is available at:
+.IP
+http://www.winimage.com/zLibDll/minizip.html
+and also in the
+.I contrib/minizip
+directory of the main
+.I zlib
+source distribution.
+.SH "SEE ALSO"
+The
+.I zlib
+web site can be found at:
+.IP
+http://zlib.net/
+.LP
+The data format used by the
+.I zlib
+library is described by RFC
+(Request for Comments) 1950 to 1952 in the files:
+.IP
+http://tools.ietf.org/html/rfc1950 (for the zlib header and trailer format)
+.br
+http://tools.ietf.org/html/rfc1951 (for the deflate compressed data format)
+.br
+http://tools.ietf.org/html/rfc1952 (for the gzip header and trailer format)
+.LP
+Mark Nelson wrote an article about
+.I zlib
+for the Jan. 1997 issue of  Dr. Dobb's Journal;
+a copy of the article is available at:
+.IP
+http://marknelson.us/1997/01/01/zlib-engine/
+.SH "REPORTING PROBLEMS"
+Before reporting a problem,
+please check the
+.I zlib
+web site to verify that you have the latest version of
+.IR zlib ;
+otherwise,
+obtain the latest version and see if the problem still exists.
+Please read the
+.I zlib
+FAQ at:
+.IP
+http://zlib.net/zlib_faq.html
+.LP
+before asking for help.
+Send questions and/or comments to zlib@gzip.org,
+or (for the Windows DLL version) to Gilles Vollant (info@winimage.com).
+.SH AUTHORS AND LICENSE
+Version 1.2.11
+.LP
+Copyright (C) 1995-2017 Jean-loup Gailly and Mark Adler
+.LP
+This software is provided 'as-is', without any express or implied
+warranty.  In no event will the authors be held liable for any damages
+arising from the use of this software.
+.LP
+Permission is granted to anyone to use this software for any purpose,
+including commercial applications, and to alter it and redistribute it
+freely, subject to the following restrictions:
+.LP
+.nr step 1 1
+.IP \n[step]. 3
+The origin of this software must not be misrepresented; you must not
+claim that you wrote the original software. If you use this software
+in a product, an acknowledgment in the product documentation would be
+appreciated but is not required.
+.IP \n+[step].
+Altered source versions must be plainly marked as such, and must not be
+misrepresented as being the original software.
+.IP \n+[step].
+This notice may not be removed or altered from any source distribution.
+.LP
+Jean-loup Gailly        Mark Adler
+.br
+jloup@gzip.org          madler@alumni.caltech.edu
+.LP
+The deflate format used by
+.I zlib
+was defined by Phil Katz.
+The deflate and
+.I zlib
+specifications were written by L. Peter Deutsch.
+Thanks to all the people who reported problems and suggested various
+improvements in
+.IR zlib ;
+who are too numerous to cite here.
+.LP
+UNIX manual page by R. P. C. Rodgers,
+U.S. National Library of Medicine (rodgers@nlm.nih.gov).
+.\" end of man page

ADDED   3rd_party/zlib/zlib.3.pdf
Index: 3rd_party/zlib/zlib.3.pdf
==================================================================
--- 3rd_party/zlib/zlib.3.pdf
+++ 3rd_party/zlib/zlib.3.pdf
cannot compute difference between binary files

ADDED   3rd_party/zlib/zlib.h
Index: 3rd_party/zlib/zlib.h
==================================================================
--- 3rd_party/zlib/zlib.h
+++ 3rd_party/zlib/zlib.h
@@ -0,0 +1,1912 @@
+/* zlib.h -- interface of the 'zlib' general purpose compression library
+  version 1.2.11, January 15th, 2017
+
+  Copyright (C) 1995-2017 Jean-loup Gailly and Mark Adler
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the authors be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
+
+  Jean-loup Gailly        Mark Adler
+  jloup@gzip.org          madler@alumni.caltech.edu
+
+
+  The data format used by the zlib library is described by RFCs (Request for
+  Comments) 1950 to 1952 in the files http://tools.ietf.org/html/rfc1950
+  (zlib format), rfc1951 (deflate format) and rfc1952 (gzip format).
+*/
+
+#ifndef ZLIB_H
+#define ZLIB_H
+
+#include "zconf.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+#define ZLIB_VERSION "1.2.11"
+#define ZLIB_VERNUM 0x12b0
+#define ZLIB_VER_MAJOR 1
+#define ZLIB_VER_MINOR 2
+#define ZLIB_VER_REVISION 11
+#define ZLIB_VER_SUBREVISION 0
+
+/*
+    The 'zlib' compression library provides in-memory compression and
+  decompression functions, including integrity checks of the uncompressed data.
+  This version of the library supports only one compression method (deflation)
+  but other algorithms will be added later and will have the same stream
+  interface.
+
+    Compression can be done in a single step if the buffers are large enough,
+  or can be done by repeated calls of the compression function.  In the latter
+  case, the application must provide more input and/or consume the output
+  (providing more output space) before each call.
+
+    The compressed data format used by default by the in-memory functions is
+  the zlib format, which is a zlib wrapper documented in RFC 1950, wrapped
+  around a deflate stream, which is itself documented in RFC 1951.
+
+    The library also supports reading and writing files in gzip (.gz) format
+  with an interface similar to that of stdio using the functions that start
+  with "gz".  The gzip format is different from the zlib format.  gzip is a
+  gzip wrapper, documented in RFC 1952, wrapped around a deflate stream.
+
+    This library can optionally read and write gzip and raw deflate streams in
+  memory as well.
+
+    The zlib format was designed to be compact and fast for use in memory
+  and on communications channels.  The gzip format was designed for single-
+  file compression on file systems, has a larger header than zlib to maintain
+  directory information, and uses a different, slower check method than zlib.
+
+    The library does not install any signal handler.  The decoder checks
+  the consistency of the compressed data, so the library should never crash
+  even in the case of corrupted input.
+*/
+
+typedef voidpf (*alloc_func) OF((voidpf opaque, uInt items, uInt size));
+typedef void   (*free_func)  OF((voidpf opaque, voidpf address));
+
+struct internal_state;
+
+typedef struct z_stream_s {
+    z_const Bytef *next_in;     /* next input byte */
+    uInt     avail_in;  /* number of bytes available at next_in */
+    uLong    total_in;  /* total number of input bytes read so far */
+
+    Bytef    *next_out; /* next output byte will go here */
+    uInt     avail_out; /* remaining free space at next_out */
+    uLong    total_out; /* total number of bytes output so far */
+
+    z_const char *msg;  /* last error message, NULL if no error */
+    struct internal_state FAR *state; /* not visible by applications */
+
+    alloc_func zalloc;  /* used to allocate the internal state */
+    free_func  zfree;   /* used to free the internal state */
+    voidpf     opaque;  /* private data object passed to zalloc and zfree */
+
+    int     data_type;  /* best guess about the data type: binary or text
+                           for deflate, or the decoding state for inflate */
+    uLong   adler;      /* Adler-32 or CRC-32 value of the uncompressed data */
+    uLong   reserved;   /* reserved for future use */
+} z_stream;
+
+typedef z_stream FAR *z_streamp;
+
+/*
+     gzip header information passed to and from zlib routines.  See RFC 1952
+  for more details on the meanings of these fields.
+*/
+typedef struct gz_header_s {
+    int     text;       /* true if compressed data believed to be text */
+    uLong   time;       /* modification time */
+    int     xflags;     /* extra flags (not used when writing a gzip file) */
+    int     os;         /* operating system */
+    Bytef   *extra;     /* pointer to extra field or Z_NULL if none */
+    uInt    extra_len;  /* extra field length (valid if extra != Z_NULL) */
+    uInt    extra_max;  /* space at extra (only when reading header) */
+    Bytef   *name;      /* pointer to zero-terminated file name or Z_NULL */
+    uInt    name_max;   /* space at name (only when reading header) */
+    Bytef   *comment;   /* pointer to zero-terminated comment or Z_NULL */
+    uInt    comm_max;   /* space at comment (only when reading header) */
+    int     hcrc;       /* true if there was or will be a header crc */
+    int     done;       /* true when done reading gzip header (not used
+                           when writing a gzip file) */
+} gz_header;
+
+typedef gz_header FAR *gz_headerp;
+
+/*
+     The application must update next_in and avail_in when avail_in has dropped
+   to zero.  It must update next_out and avail_out when avail_out has dropped
+   to zero.  The application must initialize zalloc, zfree and opaque before
+   calling the init function.  All other fields are set by the compression
+   library and must not be updated by the application.
+
+     The opaque value provided by the application will be passed as the first
+   parameter for calls of zalloc and zfree.  This can be useful for custom
+   memory management.  The compression library attaches no meaning to the
+   opaque value.
+
+     zalloc must return Z_NULL if there is not enough memory for the object.
+   If zlib is used in a multi-threaded application, zalloc and zfree must be
+   thread safe.  In that case, zlib is thread-safe.  When zalloc and zfree are
+   Z_NULL on entry to the initialization function, they are set to internal
+   routines that use the standard library functions malloc() and free().
+
+     On 16-bit systems, the functions zalloc and zfree must be able to allocate
+   exactly 65536 bytes, but will not be required to allocate more than this if
+   the symbol MAXSEG_64K is defined (see zconf.h).  WARNING: On MSDOS, pointers
+   returned by zalloc for objects of exactly 65536 bytes *must* have their
+   offset normalized to zero.  The default allocation function provided by this
+   library ensures this (see zutil.c).  To reduce memory requirements and avoid
+   any allocation of 64K objects, at the expense of compression ratio, compile
+   the library with -DMAX_WBITS=14 (see zconf.h).
+
+     The fields total_in and total_out can be used for statistics or progress
+   reports.  After compression, total_in holds the total size of the
+   uncompressed data and may be saved for use by the decompressor (particularly
+   if the decompressor wants to decompress everything in a single step).
+*/
+
+                        /* constants */
+
+#define Z_NO_FLUSH      0
+#define Z_PARTIAL_FLUSH 1
+#define Z_SYNC_FLUSH    2
+#define Z_FULL_FLUSH    3
+#define Z_FINISH        4
+#define Z_BLOCK         5
+#define Z_TREES         6
+/* Allowed flush values; see deflate() and inflate() below for details */
+
+#define Z_OK            0
+#define Z_STREAM_END    1
+#define Z_NEED_DICT     2
+#define Z_ERRNO        (-1)
+#define Z_STREAM_ERROR (-2)
+#define Z_DATA_ERROR   (-3)
+#define Z_MEM_ERROR    (-4)
+#define Z_BUF_ERROR    (-5)
+#define Z_VERSION_ERROR (-6)
+/* Return codes for the compression/decompression functions. Negative values
+ * are errors, positive values are used for special but normal events.
+ */
+
+#define Z_NO_COMPRESSION         0
+#define Z_BEST_SPEED             1
+#define Z_BEST_COMPRESSION       9
+#define Z_DEFAULT_COMPRESSION  (-1)
+/* compression levels */
+
+#define Z_FILTERED            1
+#define Z_HUFFMAN_ONLY        2
+#define Z_RLE                 3
+#define Z_FIXED               4
+#define Z_DEFAULT_STRATEGY    0
+/* compression strategy; see deflateInit2() below for details */
+
+#define Z_BINARY   0
+#define Z_TEXT     1
+#define Z_ASCII    Z_TEXT   /* for compatibility with 1.2.2 and earlier */
+#define Z_UNKNOWN  2
+/* Possible values of the data_type field for deflate() */
+
+#define Z_DEFLATED   8
+/* The deflate compression method (the only one supported in this version) */
+
+#define Z_NULL  0  /* for initializing zalloc, zfree, opaque */
+
+#define zlib_version zlibVersion()
+/* for compatibility with versions < 1.0.2 */
+
+
+                        /* basic functions */
+
+ZEXTERN const char * ZEXPORT zlibVersion OF((void));
+/* The application can compare zlibVersion and ZLIB_VERSION for consistency.
+   If the first character differs, the library code actually used is not
+   compatible with the zlib.h header file used by the application.  This check
+   is automatically made by deflateInit and inflateInit.
+ */
+
+/*
+ZEXTERN int ZEXPORT deflateInit OF((z_streamp strm, int level));
+
+     Initializes the internal stream state for compression.  The fields
+   zalloc, zfree and opaque must be initialized before by the caller.  If
+   zalloc and zfree are set to Z_NULL, deflateInit updates them to use default
+   allocation functions.
+
+     The compression level must be Z_DEFAULT_COMPRESSION, or between 0 and 9:
+   1 gives best speed, 9 gives best compression, 0 gives no compression at all
+   (the input data is simply copied a block at a time).  Z_DEFAULT_COMPRESSION
+   requests a default compromise between speed and compression (currently
+   equivalent to level 6).
+
+     deflateInit returns Z_OK if success, Z_MEM_ERROR if there was not enough
+   memory, Z_STREAM_ERROR if level is not a valid compression level, or
+   Z_VERSION_ERROR if the zlib library version (zlib_version) is incompatible
+   with the version assumed by the caller (ZLIB_VERSION).  msg is set to null
+   if there is no error message.  deflateInit does not perform any compression:
+   this will be done by deflate().
+*/
+
+
+ZEXTERN int ZEXPORT deflate OF((z_streamp strm, int flush));
+/*
+    deflate compresses as much data as possible, and stops when the input
+  buffer becomes empty or the output buffer becomes full.  It may introduce
+  some output latency (reading input without producing any output) except when
+  forced to flush.
+
+    The detailed semantics are as follows.  deflate performs one or both of the
+  following actions:
+
+  - Compress more input starting at next_in and update next_in and avail_in
+    accordingly.  If not all input can be processed (because there is not
+    enough room in the output buffer), next_in and avail_in are updated and
+    processing will resume at this point for the next call of deflate().
+
+  - Generate more output starting at next_out and update next_out and avail_out
+    accordingly.  This action is forced if the parameter flush is non zero.
+    Forcing flush frequently degrades the compression ratio, so this parameter
+    should be set only when necessary.  Some output may be provided even if
+    flush is zero.
+
+    Before the call of deflate(), the application should ensure that at least
+  one of the actions is possible, by providing more input and/or consuming more
+  output, and updating avail_in or avail_out accordingly; avail_out should
+  never be zero before the call.  The application can consume the compressed
+  output when it wants, for example when the output buffer is full (avail_out
+  == 0), or after each call of deflate().  If deflate returns Z_OK and with
+  zero avail_out, it must be called again after making room in the output
+  buffer because there might be more output pending. See deflatePending(),
+  which can be used if desired to determine whether or not there is more ouput
+  in that case.
+
+    Normally the parameter flush is set to Z_NO_FLUSH, which allows deflate to
+  decide how much data to accumulate before producing output, in order to
+  maximize compression.
+
+    If the parameter flush is set to Z_SYNC_FLUSH, all pending output is
+  flushed to the output buffer and the output is aligned on a byte boundary, so
+  that the decompressor can get all input data available so far.  (In
+  particular avail_in is zero after the call if enough output space has been
+  provided before the call.) Flushing may degrade compression for some
+  compression algorithms and so it should be used only when necessary.  This
+  completes the current deflate block and follows it with an empty stored block
+  that is three bits plus filler bits to the next byte, followed by four bytes
+  (00 00 ff ff).
+
+    If flush is set to Z_PARTIAL_FLUSH, all pending output is flushed to the
+  output buffer, but the output is not aligned to a byte boundary.  All of the
+  input data so far will be available to the decompressor, as for Z_SYNC_FLUSH.
+  This completes the current deflate block and follows it with an empty fixed
+  codes block that is 10 bits long.  This assures that enough bytes are output
+  in order for the decompressor to finish the block before the empty fixed
+  codes block.
+
+    If flush is set to Z_BLOCK, a deflate block is completed and emitted, as
+  for Z_SYNC_FLUSH, but the output is not aligned on a byte boundary, and up to
+  seven bits of the current block are held to be written as the next byte after
+  the next deflate block is completed.  In this case, the decompressor may not
+  be provided enough bits at this point in order to complete decompression of
+  the data provided so far to the compressor.  It may need to wait for the next
+  block to be emitted.  This is for advanced applications that need to control
+  the emission of deflate blocks.
+
+    If flush is set to Z_FULL_FLUSH, all output is flushed as with
+  Z_SYNC_FLUSH, and the compression state is reset so that decompression can
+  restart from this point if previous compressed data has been damaged or if
+  random access is desired.  Using Z_FULL_FLUSH too often can seriously degrade
+  compression.
+
+    If deflate returns with avail_out == 0, this function must be called again
+  with the same value of the flush parameter and more output space (updated
+  avail_out), until the flush is complete (deflate returns with non-zero
+  avail_out).  In the case of a Z_FULL_FLUSH or Z_SYNC_FLUSH, make sure that
+  avail_out is greater than six to avoid repeated flush markers due to
+  avail_out == 0 on return.
+
+    If the parameter flush is set to Z_FINISH, pending input is processed,
+  pending output is flushed and deflate returns with Z_STREAM_END if there was
+  enough output space.  If deflate returns with Z_OK or Z_BUF_ERROR, this
+  function must be called again with Z_FINISH and more output space (updated
+  avail_out) but no more input data, until it returns with Z_STREAM_END or an
+  error.  After deflate has returned Z_STREAM_END, the only possible operations
+  on the stream are deflateReset or deflateEnd.
+
+    Z_FINISH can be used in the first deflate call after deflateInit if all the
+  compression is to be done in a single step.  In order to complete in one
+  call, avail_out must be at least the value returned by deflateBound (see
+  below).  Then deflate is guaranteed to return Z_STREAM_END.  If not enough
+  output space is provided, deflate will not return Z_STREAM_END, and it must
+  be called again as described above.
+
+    deflate() sets strm->adler to the Adler-32 checksum of all input read
+  so far (that is, total_in bytes).  If a gzip stream is being generated, then
+  strm->adler will be the CRC-32 checksum of the input read so far.  (See
+  deflateInit2 below.)
+
+    deflate() may update strm->data_type if it can make a good guess about
+  the input data type (Z_BINARY or Z_TEXT).  If in doubt, the data is
+  considered binary.  This field is only for information purposes and does not
+  affect the compression algorithm in any manner.
+
+    deflate() returns Z_OK if some progress has been made (more input
+  processed or more output produced), Z_STREAM_END if all input has been
+  consumed and all output has been produced (only when flush is set to
+  Z_FINISH), Z_STREAM_ERROR if the stream state was inconsistent (for example
+  if next_in or next_out was Z_NULL or the state was inadvertently written over
+  by the application), or Z_BUF_ERROR if no progress is possible (for example
+  avail_in or avail_out was zero).  Note that Z_BUF_ERROR is not fatal, and
+  deflate() can be called again with more input and more output space to
+  continue compressing.
+*/
+
+
+ZEXTERN int ZEXPORT deflateEnd OF((z_streamp strm));
+/*
+     All dynamically allocated data structures for this stream are freed.
+   This function discards any unprocessed input and does not flush any pending
+   output.
+
+     deflateEnd returns Z_OK if success, Z_STREAM_ERROR if the
+   stream state was inconsistent, Z_DATA_ERROR if the stream was freed
+   prematurely (some input or output was discarded).  In the error case, msg
+   may be set but then points to a static string (which must not be
+   deallocated).
+*/
+
+
+/*
+ZEXTERN int ZEXPORT inflateInit OF((z_streamp strm));
+
+     Initializes the internal stream state for decompression.  The fields
+   next_in, avail_in, zalloc, zfree and opaque must be initialized before by
+   the caller.  In the current version of inflate, the provided input is not
+   read or consumed.  The allocation of a sliding window will be deferred to
+   the first call of inflate (if the decompression does not complete on the
+   first call).  If zalloc and zfree are set to Z_NULL, inflateInit updates
+   them to use default allocation functions.
+
+     inflateInit returns Z_OK if success, Z_MEM_ERROR if there was not enough
+   memory, Z_VERSION_ERROR if the zlib library version is incompatible with the
+   version assumed by the caller, or Z_STREAM_ERROR if the parameters are
+   invalid, such as a null pointer to the structure.  msg is set to null if
+   there is no error message.  inflateInit does not perform any decompression.
+   Actual decompression will be done by inflate().  So next_in, and avail_in,
+   next_out, and avail_out are unused and unchanged.  The current
+   implementation of inflateInit() does not process any header information --
+   that is deferred until inflate() is called.
+*/
+
+
+ZEXTERN int ZEXPORT inflate OF((z_streamp strm, int flush));
+/*
+    inflate decompresses as much data as possible, and stops when the input
+  buffer becomes empty or the output buffer becomes full.  It may introduce
+  some output latency (reading input without producing any output) except when
+  forced to flush.
+
+  The detailed semantics are as follows.  inflate performs one or both of the
+  following actions:
+
+  - Decompress more input starting at next_in and update next_in and avail_in
+    accordingly.  If not all input can be processed (because there is not
+    enough room in the output buffer), then next_in and avail_in are updated
+    accordingly, and processing will resume at this point for the next call of
+    inflate().
+
+  - Generate more output starting at next_out and update next_out and avail_out
+    accordingly.  inflate() provides as much output as possible, until there is
+    no more input data or no more space in the output buffer (see below about
+    the flush parameter).
+
+    Before the call of inflate(), the application should ensure that at least
+  one of the actions is possible, by providing more input and/or consuming more
+  output, and updating the next_* and avail_* values accordingly.  If the
+  caller of inflate() does not provide both available input and available
+  output space, it is possible that there will be no progress made.  The
+  application can consume the uncompressed output when it wants, for example
+  when the output buffer is full (avail_out == 0), or after each call of
+  inflate().  If inflate returns Z_OK and with zero avail_out, it must be
+  called again after making room in the output buffer because there might be
+  more output pending.
+
+    The flush parameter of inflate() can be Z_NO_FLUSH, Z_SYNC_FLUSH, Z_FINISH,
+  Z_BLOCK, or Z_TREES.  Z_SYNC_FLUSH requests that inflate() flush as much
+  output as possible to the output buffer.  Z_BLOCK requests that inflate()
+  stop if and when it gets to the next deflate block boundary.  When decoding
+  the zlib or gzip format, this will cause inflate() to return immediately
+  after the header and before the first block.  When doing a raw inflate,
+  inflate() will go ahead and process the first block, and will return when it
+  gets to the end of that block, or when it runs out of data.
+
+    The Z_BLOCK option assists in appending to or combining deflate streams.
+  To assist in this, on return inflate() always sets strm->data_type to the
+  number of unused bits in the last byte taken from strm->next_in, plus 64 if
+  inflate() is currently decoding the last block in the deflate stream, plus
+  128 if inflate() returned immediately after decoding an end-of-block code or
+  decoding the complete header up to just before the first byte of the deflate
+  stream.  The end-of-block will not be indicated until all of the uncompressed
+  data from that block has been written to strm->next_out.  The number of
+  unused bits may in general be greater than seven, except when bit 7 of
+  data_type is set, in which case the number of unused bits will be less than
+  eight.  data_type is set as noted here every time inflate() returns for all
+  flush options, and so can be used to determine the amount of currently
+  consumed input in bits.
+
+    The Z_TREES option behaves as Z_BLOCK does, but it also returns when the
+  end of each deflate block header is reached, before any actual data in that
+  block is decoded.  This allows the caller to determine the length of the
+  deflate block header for later use in random access within a deflate block.
+  256 is added to the value of strm->data_type when inflate() returns
+  immediately after reaching the end of the deflate block header.
+
+    inflate() should normally be called until it returns Z_STREAM_END or an
+  error.  However if all decompression is to be performed in a single step (a
+  single call of inflate), the parameter flush should be set to Z_FINISH.  In
+  this case all pending input is processed and all pending output is flushed;
+  avail_out must be large enough to hold all of the uncompressed data for the
+  operation to complete.  (The size of the uncompressed data may have been
+  saved by the compressor for this purpose.)  The use of Z_FINISH is not
+  required to perform an inflation in one step.  However it may be used to
+  inform inflate that a faster approach can be used for the single inflate()
+  call.  Z_FINISH also informs inflate to not maintain a sliding window if the
+  stream completes, which reduces inflate's memory footprint.  If the stream
+  does not complete, either because not all of the stream is provided or not
+  enough output space is provided, then a sliding window will be allocated and
+  inflate() can be called again to continue the operation as if Z_NO_FLUSH had
+  been used.
+
+     In this implementation, inflate() always flushes as much output as
+  possible to the output buffer, and always uses the faster approach on the
+  first call.  So the effects of the flush parameter in this implementation are
+  on the return value of inflate() as noted below, when inflate() returns early
+  when Z_BLOCK or Z_TREES is used, and when inflate() avoids the allocation of
+  memory for a sliding window when Z_FINISH is used.
+
+     If a preset dictionary is needed after this call (see inflateSetDictionary
+  below), inflate sets strm->adler to the Adler-32 checksum of the dictionary
+  chosen by the compressor and returns Z_NEED_DICT; otherwise it sets
+  strm->adler to the Adler-32 checksum of all output produced so far (that is,
+  total_out bytes) and returns Z_OK, Z_STREAM_END or an error code as described
+  below.  At the end of the stream, inflate() checks that its computed Adler-32
+  checksum is equal to that saved by the compressor and returns Z_STREAM_END
+  only if the checksum is correct.
+
+    inflate() can decompress and check either zlib-wrapped or gzip-wrapped
+  deflate data.  The header type is detected automatically, if requested when
+  initializing with inflateInit2().  Any information contained in the gzip
+  header is not retained unless inflateGetHeader() is used.  When processing
+  gzip-wrapped deflate data, strm->adler32 is set to the CRC-32 of the output
+  produced so far.  The CRC-32 is checked against the gzip trailer, as is the
+  uncompressed length, modulo 2^32.
+
+    inflate() returns Z_OK if some progress has been made (more input processed
+  or more output produced), Z_STREAM_END if the end of the compressed data has
+  been reached and all uncompressed output has been produced, Z_NEED_DICT if a
+  preset dictionary is needed at this point, Z_DATA_ERROR if the input data was
+  corrupted (input stream not conforming to the zlib format or incorrect check
+  value, in which case strm->msg points to a string with a more specific
+  error), Z_STREAM_ERROR if the stream structure was inconsistent (for example
+  next_in or next_out was Z_NULL, or the state was inadvertently written over
+  by the application), Z_MEM_ERROR if there was not enough memory, Z_BUF_ERROR
+  if no progress was possible or if there was not enough room in the output
+  buffer when Z_FINISH is used.  Note that Z_BUF_ERROR is not fatal, and
+  inflate() can be called again with more input and more output space to
+  continue decompressing.  If Z_DATA_ERROR is returned, the application may
+  then call inflateSync() to look for a good compression block if a partial
+  recovery of the data is to be attempted.
+*/
+
+
+ZEXTERN int ZEXPORT inflateEnd OF((z_streamp strm));
+/*
+     All dynamically allocated data structures for this stream are freed.
+   This function discards any unprocessed input and does not flush any pending
+   output.
+
+     inflateEnd returns Z_OK if success, or Z_STREAM_ERROR if the stream state
+   was inconsistent.
+*/
+
+
+                        /* Advanced functions */
+
+/*
+    The following functions are needed only in some special applications.
+*/
+
+/*
+ZEXTERN int ZEXPORT deflateInit2 OF((z_streamp strm,
+                                     int  level,
+                                     int  method,
+                                     int  windowBits,
+                                     int  memLevel,
+                                     int  strategy));
+
+     This is another version of deflateInit with more compression options.  The
+   fields next_in, zalloc, zfree and opaque must be initialized before by the
+   caller.
+
+     The method parameter is the compression method.  It must be Z_DEFLATED in
+   this version of the library.
+
+     The windowBits parameter is the base two logarithm of the window size
+   (the size of the history buffer).  It should be in the range 8..15 for this
+   version of the library.  Larger values of this parameter result in better
+   compression at the expense of memory usage.  The default value is 15 if
+   deflateInit is used instead.
+
+     For the current implementation of deflate(), a windowBits value of 8 (a
+   window size of 256 bytes) is not supported.  As a result, a request for 8
+   will result in 9 (a 512-byte window).  In that case, providing 8 to
+   inflateInit2() will result in an error when the zlib header with 9 is
+   checked against the initialization of inflate().  The remedy is to not use 8
+   with deflateInit2() with this initialization, or at least in that case use 9
+   with inflateInit2().
+
+     windowBits can also be -8..-15 for raw deflate.  In this case, -windowBits
+   determines the window size.  deflate() will then generate raw deflate data
+   with no zlib header or trailer, and will not compute a check value.
+
+     windowBits can also be greater than 15 for optional gzip encoding.  Add
+   16 to windowBits to write a simple gzip header and trailer around the
+   compressed data instead of a zlib wrapper.  The gzip header will have no
+   file name, no extra data, no comment, no modification time (set to zero), no
+   header crc, and the operating system will be set to the appropriate value,
+   if the operating system was determined at compile time.  If a gzip stream is
+   being written, strm->adler is a CRC-32 instead of an Adler-32.
+
+     For raw deflate or gzip encoding, a request for a 256-byte window is
+   rejected as invalid, since only the zlib header provides a means of
+   transmitting the window size to the decompressor.
+
+     The memLevel parameter specifies how much memory should be allocated
+   for the internal compression state.  memLevel=1 uses minimum memory but is
+   slow and reduces compression ratio; memLevel=9 uses maximum memory for
+   optimal speed.  The default value is 8.  See zconf.h for total memory usage
+   as a function of windowBits and memLevel.
+
+     The strategy parameter is used to tune the compression algorithm.  Use the
+   value Z_DEFAULT_STRATEGY for normal data, Z_FILTERED for data produced by a
+   filter (or predictor), Z_HUFFMAN_ONLY to force Huffman encoding only (no
+   string match), or Z_RLE to limit match distances to one (run-length
+   encoding).  Filtered data consists mostly of small values with a somewhat
+   random distribution.  In this case, the compression algorithm is tuned to
+   compress them better.  The effect of Z_FILTERED is to force more Huffman
+   coding and less string matching; it is somewhat intermediate between
+   Z_DEFAULT_STRATEGY and Z_HUFFMAN_ONLY.  Z_RLE is designed to be almost as
+   fast as Z_HUFFMAN_ONLY, but give better compression for PNG image data.  The
+   strategy parameter only affects the compression ratio but not the
+   correctness of the compressed output even if it is not set appropriately.
+   Z_FIXED prevents the use of dynamic Huffman codes, allowing for a simpler
+   decoder for special applications.
+
+     deflateInit2 returns Z_OK if success, Z_MEM_ERROR if there was not enough
+   memory, Z_STREAM_ERROR if any parameter is invalid (such as an invalid
+   method), or Z_VERSION_ERROR if the zlib library version (zlib_version) is
+   incompatible with the version assumed by the caller (ZLIB_VERSION).  msg is
+   set to null if there is no error message.  deflateInit2 does not perform any
+   compression: this will be done by deflate().
+*/
+
+ZEXTERN int ZEXPORT deflateSetDictionary OF((z_streamp strm,
+                                             const Bytef *dictionary,
+                                             uInt  dictLength));
+/*
+     Initializes the compression dictionary from the given byte sequence
+   without producing any compressed output.  When using the zlib format, this
+   function must be called immediately after deflateInit, deflateInit2 or
+   deflateReset, and before any call of deflate.  When doing raw deflate, this
+   function must be called either before any call of deflate, or immediately
+   after the completion of a deflate block, i.e. after all input has been
+   consumed and all output has been delivered when using any of the flush
+   options Z_BLOCK, Z_PARTIAL_FLUSH, Z_SYNC_FLUSH, or Z_FULL_FLUSH.  The
+   compressor and decompressor must use exactly the same dictionary (see
+   inflateSetDictionary).
+
+     The dictionary should consist of strings (byte sequences) that are likely
+   to be encountered later in the data to be compressed, with the most commonly
+   used strings preferably put towards the end of the dictionary.  Using a
+   dictionary is most useful when the data to be compressed is short and can be
+   predicted with good accuracy; the data can then be compressed better than
+   with the default empty dictionary.
+
+     Depending on the size of the compression data structures selected by
+   deflateInit or deflateInit2, a part of the dictionary may in effect be
+   discarded, for example if the dictionary is larger than the window size
+   provided in deflateInit or deflateInit2.  Thus the strings most likely to be
+   useful should be put at the end of the dictionary, not at the front.  In
+   addition, the current implementation of deflate will use at most the window
+   size minus 262 bytes of the provided dictionary.
+
+     Upon return of this function, strm->adler is set to the Adler-32 value
+   of the dictionary; the decompressor may later use this value to determine
+   which dictionary has been used by the compressor.  (The Adler-32 value
+   applies to the whole dictionary even if only a subset of the dictionary is
+   actually used by the compressor.) If a raw deflate was requested, then the
+   Adler-32 value is not computed and strm->adler is not set.
+
+     deflateSetDictionary returns Z_OK if success, or Z_STREAM_ERROR if a
+   parameter is invalid (e.g.  dictionary being Z_NULL) or the stream state is
+   inconsistent (for example if deflate has already been called for this stream
+   or if not at a block boundary for raw deflate).  deflateSetDictionary does
+   not perform any compression: this will be done by deflate().
+*/
+
+ZEXTERN int ZEXPORT deflateGetDictionary OF((z_streamp strm,
+                                             Bytef *dictionary,
+                                             uInt  *dictLength));
+/*
+     Returns the sliding dictionary being maintained by deflate.  dictLength is
+   set to the number of bytes in the dictionary, and that many bytes are copied
+   to dictionary.  dictionary must have enough space, where 32768 bytes is
+   always enough.  If deflateGetDictionary() is called with dictionary equal to
+   Z_NULL, then only the dictionary length is returned, and nothing is copied.
+   Similary, if dictLength is Z_NULL, then it is not set.
+
+     deflateGetDictionary() may return a length less than the window size, even
+   when more than the window size in input has been provided. It may return up
+   to 258 bytes less in that case, due to how zlib's implementation of deflate
+   manages the sliding window and lookahead for matches, where matches can be
+   up to 258 bytes long. If the application needs the last window-size bytes of
+   input, then that would need to be saved by the application outside of zlib.
+
+     deflateGetDictionary returns Z_OK on success, or Z_STREAM_ERROR if the
+   stream state is inconsistent.
+*/
+
+ZEXTERN int ZEXPORT deflateCopy OF((z_streamp dest,
+                                    z_streamp source));
+/*
+     Sets the destination stream as a complete copy of the source stream.
+
+     This function can be useful when several compression strategies will be
+   tried, for example when there are several ways of pre-processing the input
+   data with a filter.  The streams that will be discarded should then be freed
+   by calling deflateEnd.  Note that deflateCopy duplicates the internal
+   compression state which can be quite large, so this strategy is slow and can
+   consume lots of memory.
+
+     deflateCopy returns Z_OK if success, Z_MEM_ERROR if there was not
+   enough memory, Z_STREAM_ERROR if the source stream state was inconsistent
+   (such as zalloc being Z_NULL).  msg is left unchanged in both source and
+   destination.
+*/
+
+ZEXTERN int ZEXPORT deflateReset OF((z_streamp strm));
+/*
+     This function is equivalent to deflateEnd followed by deflateInit, but
+   does not free and reallocate the internal compression state.  The stream
+   will leave the compression level and any other attributes that may have been
+   set unchanged.
+
+     deflateReset returns Z_OK if success, or Z_STREAM_ERROR if the source
+   stream state was inconsistent (such as zalloc or state being Z_NULL).
+*/
+
+ZEXTERN int ZEXPORT deflateParams OF((z_streamp strm,
+                                      int level,
+                                      int strategy));
+/*
+     Dynamically update the compression level and compression strategy.  The
+   interpretation of level and strategy is as in deflateInit2().  This can be
+   used to switch between compression and straight copy of the input data, or
+   to switch to a different kind of input data requiring a different strategy.
+   If the compression approach (which is a function of the level) or the
+   strategy is changed, and if any input has been consumed in a previous
+   deflate() call, then the input available so far is compressed with the old
+   level and strategy using deflate(strm, Z_BLOCK).  There are three approaches
+   for the compression levels 0, 1..3, and 4..9 respectively.  The new level
+   and strategy will take effect at the next call of deflate().
+
+     If a deflate(strm, Z_BLOCK) is performed by deflateParams(), and it does
+   not have enough output space to complete, then the parameter change will not
+   take effect.  In this case, deflateParams() can be called again with the
+   same parameters and more output space to try again.
+
+     In order to assure a change in the parameters on the first try, the
+   deflate stream should be flushed using deflate() with Z_BLOCK or other flush
+   request until strm.avail_out is not zero, before calling deflateParams().
+   Then no more input data should be provided before the deflateParams() call.
+   If this is done, the old level and strategy will be applied to the data
+   compressed before deflateParams(), and the new level and strategy will be
+   applied to the the data compressed after deflateParams().
+
+     deflateParams returns Z_OK on success, Z_STREAM_ERROR if the source stream
+   state was inconsistent or if a parameter was invalid, or Z_BUF_ERROR if
+   there was not enough output space to complete the compression of the
+   available input data before a change in the strategy or approach.  Note that
+   in the case of a Z_BUF_ERROR, the parameters are not changed.  A return
+   value of Z_BUF_ERROR is not fatal, in which case deflateParams() can be
+   retried with more output space.
+*/
+
+ZEXTERN int ZEXPORT deflateTune OF((z_streamp strm,
+                                    int good_length,
+                                    int max_lazy,
+                                    int nice_length,
+                                    int max_chain));
+/*
+     Fine tune deflate's internal compression parameters.  This should only be
+   used by someone who understands the algorithm used by zlib's deflate for
+   searching for the best matching string, and even then only by the most
+   fanatic optimizer trying to squeeze out the last compressed bit for their
+   specific input data.  Read the deflate.c source code for the meaning of the
+   max_lazy, good_length, nice_length, and max_chain parameters.
+
+     deflateTune() can be called after deflateInit() or deflateInit2(), and
+   returns Z_OK on success, or Z_STREAM_ERROR for an invalid deflate stream.
+ */
+
+ZEXTERN uLong ZEXPORT deflateBound OF((z_streamp strm,
+                                       uLong sourceLen));
+/*
+     deflateBound() returns an upper bound on the compressed size after
+   deflation of sourceLen bytes.  It must be called after deflateInit() or
+   deflateInit2(), and after deflateSetHeader(), if used.  This would be used
+   to allocate an output buffer for deflation in a single pass, and so would be
+   called before deflate().  If that first deflate() call is provided the
+   sourceLen input bytes, an output buffer allocated to the size returned by
+   deflateBound(), and the flush value Z_FINISH, then deflate() is guaranteed
+   to return Z_STREAM_END.  Note that it is possible for the compressed size to
+   be larger than the value returned by deflateBound() if flush options other
+   than Z_FINISH or Z_NO_FLUSH are used.
+*/
+
+ZEXTERN int ZEXPORT deflatePending OF((z_streamp strm,
+                                       unsigned *pending,
+                                       int *bits));
+/*
+     deflatePending() returns the number of bytes and bits of output that have
+   been generated, but not yet provided in the available output.  The bytes not
+   provided would be due to the available output space having being consumed.
+   The number of bits of output not provided are between 0 and 7, where they
+   await more bits to join them in order to fill out a full byte.  If pending
+   or bits are Z_NULL, then those values are not set.
+
+     deflatePending returns Z_OK if success, or Z_STREAM_ERROR if the source
+   stream state was inconsistent.
+ */
+
+ZEXTERN int ZEXPORT deflatePrime OF((z_streamp strm,
+                                     int bits,
+                                     int value));
+/*
+     deflatePrime() inserts bits in the deflate output stream.  The intent
+   is that this function is used to start off the deflate output with the bits
+   leftover from a previous deflate stream when appending to it.  As such, this
+   function can only be used for raw deflate, and must be used before the first
+   deflate() call after a deflateInit2() or deflateReset().  bits must be less
+   than or equal to 16, and that many of the least significant bits of value
+   will be inserted in the output.
+
+     deflatePrime returns Z_OK if success, Z_BUF_ERROR if there was not enough
+   room in the internal buffer to insert the bits, or Z_STREAM_ERROR if the
+   source stream state was inconsistent.
+*/
+
+ZEXTERN int ZEXPORT deflateSetHeader OF((z_streamp strm,
+                                         gz_headerp head));
+/*
+     deflateSetHeader() provides gzip header information for when a gzip
+   stream is requested by deflateInit2().  deflateSetHeader() may be called
+   after deflateInit2() or deflateReset() and before the first call of
+   deflate().  The text, time, os, extra field, name, and comment information
+   in the provided gz_header structure are written to the gzip header (xflag is
+   ignored -- the extra flags are set according to the compression level).  The
+   caller must assure that, if not Z_NULL, name and comment are terminated with
+   a zero byte, and that if extra is not Z_NULL, that extra_len bytes are
+   available there.  If hcrc is true, a gzip header crc is included.  Note that
+   the current versions of the command-line version of gzip (up through version
+   1.3.x) do not support header crc's, and will report that it is a "multi-part
+   gzip file" and give up.
+
+     If deflateSetHeader is not used, the default gzip header has text false,
+   the time set to zero, and os set to 255, with no extra, name, or comment
+   fields.  The gzip header is returned to the default state by deflateReset().
+
+     deflateSetHeader returns Z_OK if success, or Z_STREAM_ERROR if the source
+   stream state was inconsistent.
+*/
+
+/*
+ZEXTERN int ZEXPORT inflateInit2 OF((z_streamp strm,
+                                     int  windowBits));
+
+     This is another version of inflateInit with an extra parameter.  The
+   fields next_in, avail_in, zalloc, zfree and opaque must be initialized
+   before by the caller.
+
+     The windowBits parameter is the base two logarithm of the maximum window
+   size (the size of the history buffer).  It should be in the range 8..15 for
+   this version of the library.  The default value is 15 if inflateInit is used
+   instead.  windowBits must be greater than or equal to the windowBits value
+   provided to deflateInit2() while compressing, or it must be equal to 15 if
+   deflateInit2() was not used.  If a compressed stream with a larger window
+   size is given as input, inflate() will return with the error code
+   Z_DATA_ERROR instead of trying to allocate a larger window.
+
+     windowBits can also be zero to request that inflate use the window size in
+   the zlib header of the compressed stream.
+
+     windowBits can also be -8..-15 for raw inflate.  In this case, -windowBits
+   determines the window size.  inflate() will then process raw deflate data,
+   not looking for a zlib or gzip header, not generating a check value, and not
+   looking for any check values for comparison at the end of the stream.  This
+   is for use with other formats that use the deflate compressed data format
+   such as zip.  Those formats provide their own check values.  If a custom
+   format is developed using the raw deflate format for compressed data, it is
+   recommended that a check value such as an Adler-32 or a CRC-32 be applied to
+   the uncompressed data as is done in the zlib, gzip, and zip formats.  For
+   most applications, the zlib format should be used as is.  Note that comments
+   above on the use in deflateInit2() applies to the magnitude of windowBits.
+
+     windowBits can also be greater than 15 for optional gzip decoding.  Add
+   32 to windowBits to enable zlib and gzip decoding with automatic header
+   detection, or add 16 to decode only the gzip format (the zlib format will
+   return a Z_DATA_ERROR).  If a gzip stream is being decoded, strm->adler is a
+   CRC-32 instead of an Adler-32.  Unlike the gunzip utility and gzread() (see
+   below), inflate() will not automatically decode concatenated gzip streams.
+   inflate() will return Z_STREAM_END at the end of the gzip stream.  The state
+   would need to be reset to continue decoding a subsequent gzip stream.
+
+     inflateInit2 returns Z_OK if success, Z_MEM_ERROR if there was not enough
+   memory, Z_VERSION_ERROR if the zlib library version is incompatible with the
+   version assumed by the caller, or Z_STREAM_ERROR if the parameters are
+   invalid, such as a null pointer to the structure.  msg is set to null if
+   there is no error message.  inflateInit2 does not perform any decompression
+   apart from possibly reading the zlib header if present: actual decompression
+   will be done by inflate().  (So next_in and avail_in may be modified, but
+   next_out and avail_out are unused and unchanged.) The current implementation
+   of inflateInit2() does not process any header information -- that is
+   deferred until inflate() is called.
+*/
+
+ZEXTERN int ZEXPORT inflateSetDictionary OF((z_streamp strm,
+                                             const Bytef *dictionary,
+                                             uInt  dictLength));
+/*
+     Initializes the decompression dictionary from the given uncompressed byte
+   sequence.  This function must be called immediately after a call of inflate,
+   if that call returned Z_NEED_DICT.  The dictionary chosen by the compressor
+   can be determined from the Adler-32 value returned by that call of inflate.
+   The compressor and decompressor must use exactly the same dictionary (see
+   deflateSetDictionary).  For raw inflate, this function can be called at any
+   time to set the dictionary.  If the provided dictionary is smaller than the
+   window and there is already data in the window, then the provided dictionary
+   will amend what's there.  The application must insure that the dictionary
+   that was used for compression is provided.
+
+     inflateSetDictionary returns Z_OK if success, Z_STREAM_ERROR if a
+   parameter is invalid (e.g.  dictionary being Z_NULL) or the stream state is
+   inconsistent, Z_DATA_ERROR if the given dictionary doesn't match the
+   expected one (incorrect Adler-32 value).  inflateSetDictionary does not
+   perform any decompression: this will be done by subsequent calls of
+   inflate().
+*/
+
+ZEXTERN int ZEXPORT inflateGetDictionary OF((z_streamp strm,
+                                             Bytef *dictionary,
+                                             uInt  *dictLength));
+/*
+     Returns the sliding dictionary being maintained by inflate.  dictLength is
+   set to the number of bytes in the dictionary, and that many bytes are copied
+   to dictionary.  dictionary must have enough space, where 32768 bytes is
+   always enough.  If inflateGetDictionary() is called with dictionary equal to
+   Z_NULL, then only the dictionary length is returned, and nothing is copied.
+   Similary, if dictLength is Z_NULL, then it is not set.
+
+     inflateGetDictionary returns Z_OK on success, or Z_STREAM_ERROR if the
+   stream state is inconsistent.
+*/
+
+ZEXTERN int ZEXPORT inflateSync OF((z_streamp strm));
+/*
+     Skips invalid compressed data until a possible full flush point (see above
+   for the description of deflate with Z_FULL_FLUSH) can be found, or until all
+   available input is skipped.  No output is provided.
+
+     inflateSync searches for a 00 00 FF FF pattern in the compressed data.
+   All full flush points have this pattern, but not all occurrences of this
+   pattern are full flush points.
+
+     inflateSync returns Z_OK if a possible full flush point has been found,
+   Z_BUF_ERROR if no more input was provided, Z_DATA_ERROR if no flush point
+   has been found, or Z_STREAM_ERROR if the stream structure was inconsistent.
+   In the success case, the application may save the current current value of
+   total_in which indicates where valid compressed data was found.  In the
+   error case, the application may repeatedly call inflateSync, providing more
+   input each time, until success or end of the input data.
+*/
+
+ZEXTERN int ZEXPORT inflateCopy OF((z_streamp dest,
+                                    z_streamp source));
+/*
+     Sets the destination stream as a complete copy of the source stream.
+
+     This function can be useful when randomly accessing a large stream.  The
+   first pass through the stream can periodically record the inflate state,
+   allowing restarting inflate at those points when randomly accessing the
+   stream.
+
+     inflateCopy returns Z_OK if success, Z_MEM_ERROR if there was not
+   enough memory, Z_STREAM_ERROR if the source stream state was inconsistent
+   (such as zalloc being Z_NULL).  msg is left unchanged in both source and
+   destination.
+*/
+
+ZEXTERN int ZEXPORT inflateReset OF((z_streamp strm));
+/*
+     This function is equivalent to inflateEnd followed by inflateInit,
+   but does not free and reallocate the internal decompression state.  The
+   stream will keep attributes that may have been set by inflateInit2.
+
+     inflateReset returns Z_OK if success, or Z_STREAM_ERROR if the source
+   stream state was inconsistent (such as zalloc or state being Z_NULL).
+*/
+
+ZEXTERN int ZEXPORT inflateReset2 OF((z_streamp strm,
+                                      int windowBits));
+/*
+     This function is the same as inflateReset, but it also permits changing
+   the wrap and window size requests.  The windowBits parameter is interpreted
+   the same as it is for inflateInit2.  If the window size is changed, then the
+   memory allocated for the window is freed, and the window will be reallocated
+   by inflate() if needed.
+
+     inflateReset2 returns Z_OK if success, or Z_STREAM_ERROR if the source
+   stream state was inconsistent (such as zalloc or state being Z_NULL), or if
+   the windowBits parameter is invalid.
+*/
+
+ZEXTERN int ZEXPORT inflatePrime OF((z_streamp strm,
+                                     int bits,
+                                     int value));
+/*
+     This function inserts bits in the inflate input stream.  The intent is
+   that this function is used to start inflating at a bit position in the
+   middle of a byte.  The provided bits will be used before any bytes are used
+   from next_in.  This function should only be used with raw inflate, and
+   should be used before the first inflate() call after inflateInit2() or
+   inflateReset().  bits must be less than or equal to 16, and that many of the
+   least significant bits of value will be inserted in the input.
+
+     If bits is negative, then the input stream bit buffer is emptied.  Then
+   inflatePrime() can be called again to put bits in the buffer.  This is used
+   to clear out bits leftover after feeding inflate a block description prior
+   to feeding inflate codes.
+
+     inflatePrime returns Z_OK if success, or Z_STREAM_ERROR if the source
+   stream state was inconsistent.
+*/
+
+ZEXTERN long ZEXPORT inflateMark OF((z_streamp strm));
+/*
+     This function returns two values, one in the lower 16 bits of the return
+   value, and the other in the remaining upper bits, obtained by shifting the
+   return value down 16 bits.  If the upper value is -1 and the lower value is
+   zero, then inflate() is currently decoding information outside of a block.
+   If the upper value is -1 and the lower value is non-zero, then inflate is in
+   the middle of a stored block, with the lower value equaling the number of
+   bytes from the input remaining to copy.  If the upper value is not -1, then
+   it is the number of bits back from the current bit position in the input of
+   the code (literal or length/distance pair) currently being processed.  In
+   that case the lower value is the number of bytes already emitted for that
+   code.
+
+     A code is being processed if inflate is waiting for more input to complete
+   decoding of the code, or if it has completed decoding but is waiting for
+   more output space to write the literal or match data.
+
+     inflateMark() is used to mark locations in the input data for random
+   access, which may be at bit positions, and to note those cases where the
+   output of a code may span boundaries of random access blocks.  The current
+   location in the input stream can be determined from avail_in and data_type
+   as noted in the description for the Z_BLOCK flush parameter for inflate.
+
+     inflateMark returns the value noted above, or -65536 if the provided
+   source stream state was inconsistent.
+*/
+
+ZEXTERN int ZEXPORT inflateGetHeader OF((z_streamp strm,
+                                         gz_headerp head));
+/*
+     inflateGetHeader() requests that gzip header information be stored in the
+   provided gz_header structure.  inflateGetHeader() may be called after
+   inflateInit2() or inflateReset(), and before the first call of inflate().
+   As inflate() processes the gzip stream, head->done is zero until the header
+   is completed, at which time head->done is set to one.  If a zlib stream is
+   being decoded, then head->done is set to -1 to indicate that there will be
+   no gzip header information forthcoming.  Note that Z_BLOCK or Z_TREES can be
+   used to force inflate() to return immediately after header processing is
+   complete and before any actual data is decompressed.
+
+     The text, time, xflags, and os fields are filled in with the gzip header
+   contents.  hcrc is set to true if there is a header CRC.  (The header CRC
+   was valid if done is set to one.) If extra is not Z_NULL, then extra_max
+   contains the maximum number of bytes to write to extra.  Once done is true,
+   extra_len contains the actual extra field length, and extra contains the
+   extra field, or that field truncated if extra_max is less than extra_len.
+   If name is not Z_NULL, then up to name_max characters are written there,
+   terminated with a zero unless the length is greater than name_max.  If
+   comment is not Z_NULL, then up to comm_max characters are written there,
+   terminated with a zero unless the length is greater than comm_max.  When any
+   of extra, name, or comment are not Z_NULL and the respective field is not
+   present in the header, then that field is set to Z_NULL to signal its
+   absence.  This allows the use of deflateSetHeader() with the returned
+   structure to duplicate the header.  However if those fields are set to
+   allocated memory, then the application will need to save those pointers
+   elsewhere so that they can be eventually freed.
+
+     If inflateGetHeader is not used, then the header information is simply
+   discarded.  The header is always checked for validity, including the header
+   CRC if present.  inflateReset() will reset the process to discard the header
+   information.  The application would need to call inflateGetHeader() again to
+   retrieve the header from the next gzip stream.
+
+     inflateGetHeader returns Z_OK if success, or Z_STREAM_ERROR if the source
+   stream state was inconsistent.
+*/
+
+/*
+ZEXTERN int ZEXPORT inflateBackInit OF((z_streamp strm, int windowBits,
+                                        unsigned char FAR *window));
+
+     Initialize the internal stream state for decompression using inflateBack()
+   calls.  The fields zalloc, zfree and opaque in strm must be initialized
+   before the call.  If zalloc and zfree are Z_NULL, then the default library-
+   derived memory allocation routines are used.  windowBits is the base two
+   logarithm of the window size, in the range 8..15.  window is a caller
+   supplied buffer of that size.  Except for special applications where it is
+   assured that deflate was used with small window sizes, windowBits must be 15
+   and a 32K byte window must be supplied to be able to decompress general
+   deflate streams.
+
+     See inflateBack() for the usage of these routines.
+
+     inflateBackInit will return Z_OK on success, Z_STREAM_ERROR if any of
+   the parameters are invalid, Z_MEM_ERROR if the internal state could not be
+   allocated, or Z_VERSION_ERROR if the version of the library does not match
+   the version of the header file.
+*/
+
+typedef unsigned (*in_func) OF((void FAR *,
+                                z_const unsigned char FAR * FAR *));
+typedef int (*out_func) OF((void FAR *, unsigned char FAR *, unsigned));
+
+ZEXTERN int ZEXPORT inflateBack OF((z_streamp strm,
+                                    in_func in, void FAR *in_desc,
+                                    out_func out, void FAR *out_desc));
+/*
+     inflateBack() does a raw inflate with a single call using a call-back
+   interface for input and output.  This is potentially more efficient than
+   inflate() for file i/o applications, in that it avoids copying between the
+   output and the sliding window by simply making the window itself the output
+   buffer.  inflate() can be faster on modern CPUs when used with large
+   buffers.  inflateBack() trusts the application to not change the output
+   buffer passed by the output function, at least until inflateBack() returns.
+
+     inflateBackInit() must be called first to allocate the internal state
+   and to initialize the state with the user-provided window buffer.
+   inflateBack() may then be used multiple times to inflate a complete, raw
+   deflate stream with each call.  inflateBackEnd() is then called to free the
+   allocated state.
+
+     A raw deflate stream is one with no zlib or gzip header or trailer.
+   This routine would normally be used in a utility that reads zip or gzip
+   files and writes out uncompressed files.  The utility would decode the
+   header and process the trailer on its own, hence this routine expects only
+   the raw deflate stream to decompress.  This is different from the default
+   behavior of inflate(), which expects a zlib header and trailer around the
+   deflate stream.
+
+     inflateBack() uses two subroutines supplied by the caller that are then
+   called by inflateBack() for input and output.  inflateBack() calls those
+   routines until it reads a complete deflate stream and writes out all of the
+   uncompressed data, or until it encounters an error.  The function's
+   parameters and return types are defined above in the in_func and out_func
+   typedefs.  inflateBack() will call in(in_desc, &buf) which should return the
+   number of bytes of provided input, and a pointer to that input in buf.  If
+   there is no input available, in() must return zero -- buf is ignored in that
+   case -- and inflateBack() will return a buffer error.  inflateBack() will
+   call out(out_desc, buf, len) to write the uncompressed data buf[0..len-1].
+   out() should return zero on success, or non-zero on failure.  If out()
+   returns non-zero, inflateBack() will return with an error.  Neither in() nor
+   out() are permitted to change the contents of the window provided to
+   inflateBackInit(), which is also the buffer that out() uses to write from.
+   The length written by out() will be at most the window size.  Any non-zero
+   amount of input may be provided by in().
+
+     For convenience, inflateBack() can be provided input on the first call by
+   setting strm->next_in and strm->avail_in.  If that input is exhausted, then
+   in() will be called.  Therefore strm->next_in must be initialized before
+   calling inflateBack().  If strm->next_in is Z_NULL, then in() will be called
+   immediately for input.  If strm->next_in is not Z_NULL, then strm->avail_in
+   must also be initialized, and then if strm->avail_in is not zero, input will
+   initially be taken from strm->next_in[0 ..  strm->avail_in - 1].
+
+     The in_desc and out_desc parameters of inflateBack() is passed as the
+   first parameter of in() and out() respectively when they are called.  These
+   descriptors can be optionally used to pass any information that the caller-
+   supplied in() and out() functions need to do their job.
+
+     On return, inflateBack() will set strm->next_in and strm->avail_in to
+   pass back any unused input that was provided by the last in() call.  The
+   return values of inflateBack() can be Z_STREAM_END on success, Z_BUF_ERROR
+   if in() or out() returned an error, Z_DATA_ERROR if there was a format error
+   in the deflate stream (in which case strm->msg is set to indicate the nature
+   of the error), or Z_STREAM_ERROR if the stream was not properly initialized.
+   In the case of Z_BUF_ERROR, an input or output error can be distinguished
+   using strm->next_in which will be Z_NULL only if in() returned an error.  If
+   strm->next_in is not Z_NULL, then the Z_BUF_ERROR was due to out() returning
+   non-zero.  (in() will always be called before out(), so strm->next_in is
+   assured to be defined if out() returns non-zero.)  Note that inflateBack()
+   cannot return Z_OK.
+*/
+
+ZEXTERN int ZEXPORT inflateBackEnd OF((z_streamp strm));
+/*
+     All memory allocated by inflateBackInit() is freed.
+
+     inflateBackEnd() returns Z_OK on success, or Z_STREAM_ERROR if the stream
+   state was inconsistent.
+*/
+
+ZEXTERN uLong ZEXPORT zlibCompileFlags OF((void));
+/* Return flags indicating compile-time options.
+
+    Type sizes, two bits each, 00 = 16 bits, 01 = 32, 10 = 64, 11 = other:
+     1.0: size of uInt
+     3.2: size of uLong
+     5.4: size of voidpf (pointer)
+     7.6: size of z_off_t
+
+    Compiler, assembler, and debug options:
+     8: ZLIB_DEBUG
+     9: ASMV or ASMINF -- use ASM code
+     10: ZLIB_WINAPI -- exported functions use the WINAPI calling convention
+     11: 0 (reserved)
+
+    One-time table building (smaller code, but not thread-safe if true):
+     12: BUILDFIXED -- build static block decoding tables when needed
+     13: DYNAMIC_CRC_TABLE -- build CRC calculation tables when needed
+     14,15: 0 (reserved)
+
+    Library content (indicates missing functionality):
+     16: NO_GZCOMPRESS -- gz* functions cannot compress (to avoid linking
+                          deflate code when not needed)
+     17: NO_GZIP -- deflate can't write gzip streams, and inflate can't detect
+                    and decode gzip streams (to avoid linking crc code)
+     18-19: 0 (reserved)
+
+    Operation variations (changes in library functionality):
+     20: PKZIP_BUG_WORKAROUND -- slightly more permissive inflate
+     21: FASTEST -- deflate algorithm with only one, lowest compression level
+     22,23: 0 (reserved)
+
+    The sprintf variant used by gzprintf (zero is best):
+     24: 0 = vs*, 1 = s* -- 1 means limited to 20 arguments after the format
+     25: 0 = *nprintf, 1 = *printf -- 1 means gzprintf() not secure!
+     26: 0 = returns value, 1 = void -- 1 means inferred string length returned
+
+    Remainder:
+     27-31: 0 (reserved)
+ */
+
+#ifndef Z_SOLO
+
+                        /* utility functions */
+
+/*
+     The following utility functions are implemented on top of the basic
+   stream-oriented functions.  To simplify the interface, some default options
+   are assumed (compression level and memory usage, standard memory allocation
+   functions).  The source code of these utility functions can be modified if
+   you need special options.
+*/
+
+ZEXTERN int ZEXPORT compress OF((Bytef *dest,   uLongf *destLen,
+                                 const Bytef *source, uLong sourceLen));
+/*
+     Compresses the source buffer into the destination buffer.  sourceLen is
+   the byte length of the source buffer.  Upon entry, destLen is the total size
+   of the destination buffer, which must be at least the value returned by
+   compressBound(sourceLen).  Upon exit, destLen is the actual size of the
+   compressed data.  compress() is equivalent to compress2() with a level
+   parameter of Z_DEFAULT_COMPRESSION.
+
+     compress returns Z_OK if success, Z_MEM_ERROR if there was not
+   enough memory, Z_BUF_ERROR if there was not enough room in the output
+   buffer.
+*/
+
+ZEXTERN int ZEXPORT compress2 OF((Bytef *dest,   uLongf *destLen,
+                                  const Bytef *source, uLong sourceLen,
+                                  int level));
+/*
+     Compresses the source buffer into the destination buffer.  The level
+   parameter has the same meaning as in deflateInit.  sourceLen is the byte
+   length of the source buffer.  Upon entry, destLen is the total size of the
+   destination buffer, which must be at least the value returned by
+   compressBound(sourceLen).  Upon exit, destLen is the actual size of the
+   compressed data.
+
+     compress2 returns Z_OK if success, Z_MEM_ERROR if there was not enough
+   memory, Z_BUF_ERROR if there was not enough room in the output buffer,
+   Z_STREAM_ERROR if the level parameter is invalid.
+*/
+
+ZEXTERN uLong ZEXPORT compressBound OF((uLong sourceLen));
+/*
+     compressBound() returns an upper bound on the compressed size after
+   compress() or compress2() on sourceLen bytes.  It would be used before a
+   compress() or compress2() call to allocate the destination buffer.
+*/
+
+ZEXTERN int ZEXPORT uncompress OF((Bytef *dest,   uLongf *destLen,
+                                   const Bytef *source, uLong sourceLen));
+/*
+     Decompresses the source buffer into the destination buffer.  sourceLen is
+   the byte length of the source buffer.  Upon entry, destLen is the total size
+   of the destination buffer, which must be large enough to hold the entire
+   uncompressed data.  (The size of the uncompressed data must have been saved
+   previously by the compressor and transmitted to the decompressor by some
+   mechanism outside the scope of this compression library.) Upon exit, destLen
+   is the actual size of the uncompressed data.
+
+     uncompress returns Z_OK if success, Z_MEM_ERROR if there was not
+   enough memory, Z_BUF_ERROR if there was not enough room in the output
+   buffer, or Z_DATA_ERROR if the input data was corrupted or incomplete.  In
+   the case where there is not enough room, uncompress() will fill the output
+   buffer with the uncompressed data up to that point.
+*/
+
+ZEXTERN int ZEXPORT uncompress2 OF((Bytef *dest,   uLongf *destLen,
+                                    const Bytef *source, uLong *sourceLen));
+/*
+     Same as uncompress, except that sourceLen is a pointer, where the
+   length of the source is *sourceLen.  On return, *sourceLen is the number of
+   source bytes consumed.
+*/
+
+                        /* gzip file access functions */
+
+/*
+     This library supports reading and writing files in gzip (.gz) format with
+   an interface similar to that of stdio, using the functions that start with
+   "gz".  The gzip format is different from the zlib format.  gzip is a gzip
+   wrapper, documented in RFC 1952, wrapped around a deflate stream.
+*/
+
+typedef struct gzFile_s *gzFile;    /* semi-opaque gzip file descriptor */
+
+/*
+ZEXTERN gzFile ZEXPORT gzopen OF((const char *path, const char *mode));
+
+     Opens a gzip (.gz) file for reading or writing.  The mode parameter is as
+   in fopen ("rb" or "wb") but can also include a compression level ("wb9") or
+   a strategy: 'f' for filtered data as in "wb6f", 'h' for Huffman-only
+   compression as in "wb1h", 'R' for run-length encoding as in "wb1R", or 'F'
+   for fixed code compression as in "wb9F".  (See the description of
+   deflateInit2 for more information about the strategy parameter.)  'T' will
+   request transparent writing or appending with no compression and not using
+   the gzip format.
+
+     "a" can be used instead of "w" to request that the gzip stream that will
+   be written be appended to the file.  "+" will result in an error, since
+   reading and writing to the same gzip file is not supported.  The addition of
+   "x" when writing will create the file exclusively, which fails if the file
+   already exists.  On systems that support it, the addition of "e" when
+   reading or writing will set the flag to close the file on an execve() call.
+
+     These functions, as well as gzip, will read and decode a sequence of gzip
+   streams in a file.  The append function of gzopen() can be used to create
+   such a file.  (Also see gzflush() for another way to do this.)  When
+   appending, gzopen does not test whether the file begins with a gzip stream,
+   nor does it look for the end of the gzip streams to begin appending.  gzopen
+   will simply append a gzip stream to the existing file.
+
+     gzopen can be used to read a file which is not in gzip format; in this
+   case gzread will directly read from the file without decompression.  When
+   reading, this will be detected automatically by looking for the magic two-
+   byte gzip header.
+
+     gzopen returns NULL if the file could not be opened, if there was
+   insufficient memory to allocate the gzFile state, or if an invalid mode was
+   specified (an 'r', 'w', or 'a' was not provided, or '+' was provided).
+   errno can be checked to determine if the reason gzopen failed was that the
+   file could not be opened.
+*/
+
+ZEXTERN gzFile ZEXPORT gzdopen OF((int fd, const char *mode));
+/*
+     gzdopen associates a gzFile with the file descriptor fd.  File descriptors
+   are obtained from calls like open, dup, creat, pipe or fileno (if the file
+   has been previously opened with fopen).  The mode parameter is as in gzopen.
+
+     The next call of gzclose on the returned gzFile will also close the file
+   descriptor fd, just like fclose(fdopen(fd, mode)) closes the file descriptor
+   fd.  If you want to keep fd open, use fd = dup(fd_keep); gz = gzdopen(fd,
+   mode);.  The duplicated descriptor should be saved to avoid a leak, since
+   gzdopen does not close fd if it fails.  If you are using fileno() to get the
+   file descriptor from a FILE *, then you will have to use dup() to avoid
+   double-close()ing the file descriptor.  Both gzclose() and fclose() will
+   close the associated file descriptor, so they need to have different file
+   descriptors.
+
+     gzdopen returns NULL if there was insufficient memory to allocate the
+   gzFile state, if an invalid mode was specified (an 'r', 'w', or 'a' was not
+   provided, or '+' was provided), or if fd is -1.  The file descriptor is not
+   used until the next gz* read, write, seek, or close operation, so gzdopen
+   will not detect if fd is invalid (unless fd is -1).
+*/
+
+ZEXTERN int ZEXPORT gzbuffer OF((gzFile file, unsigned size));
+/*
+     Set the internal buffer size used by this library's functions.  The
+   default buffer size is 8192 bytes.  This function must be called after
+   gzopen() or gzdopen(), and before any other calls that read or write the
+   file.  The buffer memory allocation is always deferred to the first read or
+   write.  Three times that size in buffer space is allocated.  A larger buffer
+   size of, for example, 64K or 128K bytes will noticeably increase the speed
+   of decompression (reading).
+
+     The new buffer size also affects the maximum length for gzprintf().
+
+     gzbuffer() returns 0 on success, or -1 on failure, such as being called
+   too late.
+*/
+
+ZEXTERN int ZEXPORT gzsetparams OF((gzFile file, int level, int strategy));
+/*
+     Dynamically update the compression level or strategy.  See the description
+   of deflateInit2 for the meaning of these parameters.  Previously provided
+   data is flushed before the parameter change.
+
+     gzsetparams returns Z_OK if success, Z_STREAM_ERROR if the file was not
+   opened for writing, Z_ERRNO if there is an error writing the flushed data,
+   or Z_MEM_ERROR if there is a memory allocation error.
+*/
+
+ZEXTERN int ZEXPORT gzread OF((gzFile file, voidp buf, unsigned len));
+/*
+     Reads the given number of uncompressed bytes from the compressed file.  If
+   the input file is not in gzip format, gzread copies the given number of
+   bytes into the buffer directly from the file.
+
+     After reaching the end of a gzip stream in the input, gzread will continue
+   to read, looking for another gzip stream.  Any number of gzip streams may be
+   concatenated in the input file, and will all be decompressed by gzread().
+   If something other than a gzip stream is encountered after a gzip stream,
+   that remaining trailing garbage is ignored (and no error is returned).
+
+     gzread can be used to read a gzip file that is being concurrently written.
+   Upon reaching the end of the input, gzread will return with the available
+   data.  If the error code returned by gzerror is Z_OK or Z_BUF_ERROR, then
+   gzclearerr can be used to clear the end of file indicator in order to permit
+   gzread to be tried again.  Z_OK indicates that a gzip stream was completed
+   on the last gzread.  Z_BUF_ERROR indicates that the input file ended in the
+   middle of a gzip stream.  Note that gzread does not return -1 in the event
+   of an incomplete gzip stream.  This error is deferred until gzclose(), which
+   will return Z_BUF_ERROR if the last gzread ended in the middle of a gzip
+   stream.  Alternatively, gzerror can be used before gzclose to detect this
+   case.
+
+     gzread returns the number of uncompressed bytes actually read, less than
+   len for end of file, or -1 for error.  If len is too large to fit in an int,
+   then nothing is read, -1 is returned, and the error state is set to
+   Z_STREAM_ERROR.
+*/
+
+ZEXTERN z_size_t ZEXPORT gzfread OF((voidp buf, z_size_t size, z_size_t nitems,
+                                     gzFile file));
+/*
+     Read up to nitems items of size size from file to buf, otherwise operating
+   as gzread() does.  This duplicates the interface of stdio's fread(), with
+   size_t request and return types.  If the library defines size_t, then
+   z_size_t is identical to size_t.  If not, then z_size_t is an unsigned
+   integer type that can contain a pointer.
+
+     gzfread() returns the number of full items read of size size, or zero if
+   the end of the file was reached and a full item could not be read, or if
+   there was an error.  gzerror() must be consulted if zero is returned in
+   order to determine if there was an error.  If the multiplication of size and
+   nitems overflows, i.e. the product does not fit in a z_size_t, then nothing
+   is read, zero is returned, and the error state is set to Z_STREAM_ERROR.
+
+     In the event that the end of file is reached and only a partial item is
+   available at the end, i.e. the remaining uncompressed data length is not a
+   multiple of size, then the final partial item is nevetheless read into buf
+   and the end-of-file flag is set.  The length of the partial item read is not
+   provided, but could be inferred from the result of gztell().  This behavior
+   is the same as the behavior of fread() implementations in common libraries,
+   but it prevents the direct use of gzfread() to read a concurrently written
+   file, reseting and retrying on end-of-file, when size is not 1.
+*/
+
+ZEXTERN int ZEXPORT gzwrite OF((gzFile file,
+                                voidpc buf, unsigned len));
+/*
+     Writes the given number of uncompressed bytes into the compressed file.
+   gzwrite returns the number of uncompressed bytes written or 0 in case of
+   error.
+*/
+
+ZEXTERN z_size_t ZEXPORT gzfwrite OF((voidpc buf, z_size_t size,
+                                      z_size_t nitems, gzFile file));
+/*
+     gzfwrite() writes nitems items of size size from buf to file, duplicating
+   the interface of stdio's fwrite(), with size_t request and return types.  If
+   the library defines size_t, then z_size_t is identical to size_t.  If not,
+   then z_size_t is an unsigned integer type that can contain a pointer.
+
+     gzfwrite() returns the number of full items written of size size, or zero
+   if there was an error.  If the multiplication of size and nitems overflows,
+   i.e. the product does not fit in a z_size_t, then nothing is written, zero
+   is returned, and the error state is set to Z_STREAM_ERROR.
+*/
+
+ZEXTERN int ZEXPORTVA gzprintf Z_ARG((gzFile file, const char *format, ...));
+/*
+     Converts, formats, and writes the arguments to the compressed file under
+   control of the format string, as in fprintf.  gzprintf returns the number of
+   uncompressed bytes actually written, or a negative zlib error code in case
+   of error.  The number of uncompressed bytes written is limited to 8191, or
+   one less than the buffer size given to gzbuffer().  The caller should assure
+   that this limit is not exceeded.  If it is exceeded, then gzprintf() will
+   return an error (0) with nothing written.  In this case, there may also be a
+   buffer overflow with unpredictable consequences, which is possible only if
+   zlib was compiled with the insecure functions sprintf() or vsprintf()
+   because the secure snprintf() or vsnprintf() functions were not available.
+   This can be determined using zlibCompileFlags().
+*/
+
+ZEXTERN int ZEXPORT gzputs OF((gzFile file, const char *s));
+/*
+     Writes the given null-terminated string to the compressed file, excluding
+   the terminating null character.
+
+     gzputs returns the number of characters written, or -1 in case of error.
+*/
+
+ZEXTERN char * ZEXPORT gzgets OF((gzFile file, char *buf, int len));
+/*
+     Reads bytes from the compressed file until len-1 characters are read, or a
+   newline character is read and transferred to buf, or an end-of-file
+   condition is encountered.  If any characters are read or if len == 1, the
+   string is terminated with a null character.  If no characters are read due
+   to an end-of-file or len < 1, then the buffer is left untouched.
+
+     gzgets returns buf which is a null-terminated string, or it returns NULL
+   for end-of-file or in case of error.  If there was an error, the contents at
+   buf are indeterminate.
+*/
+
+ZEXTERN int ZEXPORT gzputc OF((gzFile file, int c));
+/*
+     Writes c, converted to an unsigned char, into the compressed file.  gzputc
+   returns the value that was written, or -1 in case of error.
+*/
+
+ZEXTERN int ZEXPORT gzgetc OF((gzFile file));
+/*
+     Reads one byte from the compressed file.  gzgetc returns this byte or -1
+   in case of end of file or error.  This is implemented as a macro for speed.
+   As such, it does not do all of the checking the other functions do.  I.e.
+   it does not check to see if file is NULL, nor whether the structure file
+   points to has been clobbered or not.
+*/
+
+ZEXTERN int ZEXPORT gzungetc OF((int c, gzFile file));
+/*
+     Push one character back onto the stream to be read as the first character
+   on the next read.  At least one character of push-back is allowed.
+   gzungetc() returns the character pushed, or -1 on failure.  gzungetc() will
+   fail if c is -1, and may fail if a character has been pushed but not read
+   yet.  If gzungetc is used immediately after gzopen or gzdopen, at least the
+   output buffer size of pushed characters is allowed.  (See gzbuffer above.)
+   The pushed character will be discarded if the stream is repositioned with
+   gzseek() or gzrewind().
+*/
+
+ZEXTERN int ZEXPORT gzflush OF((gzFile file, int flush));
+/*
+     Flushes all pending output into the compressed file.  The parameter flush
+   is as in the deflate() function.  The return value is the zlib error number
+   (see function gzerror below).  gzflush is only permitted when writing.
+
+     If the flush parameter is Z_FINISH, the remaining data is written and the
+   gzip stream is completed in the output.  If gzwrite() is called again, a new
+   gzip stream will be started in the output.  gzread() is able to read such
+   concatenated gzip streams.
+
+     gzflush should be called only when strictly necessary because it will
+   degrade compression if called too often.
+*/
+
+/*
+ZEXTERN z_off_t ZEXPORT gzseek OF((gzFile file,
+                                   z_off_t offset, int whence));
+
+     Sets the starting position for the next gzread or gzwrite on the given
+   compressed file.  The offset represents a number of bytes in the
+   uncompressed data stream.  The whence parameter is defined as in lseek(2);
+   the value SEEK_END is not supported.
+
+     If the file is opened for reading, this function is emulated but can be
+   extremely slow.  If the file is opened for writing, only forward seeks are
+   supported; gzseek then compresses a sequence of zeroes up to the new
+   starting position.
+
+     gzseek returns the resulting offset location as measured in bytes from
+   the beginning of the uncompressed stream, or -1 in case of error, in
+   particular if the file is opened for writing and the new starting position
+   would be before the current position.
+*/
+
+ZEXTERN int ZEXPORT    gzrewind OF((gzFile file));
+/*
+     Rewinds the given file. This function is supported only for reading.
+
+     gzrewind(file) is equivalent to (int)gzseek(file, 0L, SEEK_SET)
+*/
+
+/*
+ZEXTERN z_off_t ZEXPORT    gztell OF((gzFile file));
+
+     Returns the starting position for the next gzread or gzwrite on the given
+   compressed file.  This position represents a number of bytes in the
+   uncompressed data stream, and is zero when starting, even if appending or
+   reading a gzip stream from the middle of a file using gzdopen().
+
+     gztell(file) is equivalent to gzseek(file, 0L, SEEK_CUR)
+*/
+
+/*
+ZEXTERN z_off_t ZEXPORT gzoffset OF((gzFile file));
+
+     Returns the current offset in the file being read or written.  This offset
+   includes the count of bytes that precede the gzip stream, for example when
+   appending or when using gzdopen() for reading.  When reading, the offset
+   does not include as yet unused buffered input.  This information can be used
+   for a progress indicator.  On error, gzoffset() returns -1.
+*/
+
+ZEXTERN int ZEXPORT gzeof OF((gzFile file));
+/*
+     Returns true (1) if the end-of-file indicator has been set while reading,
+   false (0) otherwise.  Note that the end-of-file indicator is set only if the
+   read tried to go past the end of the input, but came up short.  Therefore,
+   just like feof(), gzeof() may return false even if there is no more data to
+   read, in the event that the last read request was for the exact number of
+   bytes remaining in the input file.  This will happen if the input file size
+   is an exact multiple of the buffer size.
+
+     If gzeof() returns true, then the read functions will return no more data,
+   unless the end-of-file indicator is reset by gzclearerr() and the input file
+   has grown since the previous end of file was detected.
+*/
+
+ZEXTERN int ZEXPORT gzdirect OF((gzFile file));
+/*
+     Returns true (1) if file is being copied directly while reading, or false
+   (0) if file is a gzip stream being decompressed.
+
+     If the input file is empty, gzdirect() will return true, since the input
+   does not contain a gzip stream.
+
+     If gzdirect() is used immediately after gzopen() or gzdopen() it will
+   cause buffers to be allocated to allow reading the file to determine if it
+   is a gzip file.  Therefore if gzbuffer() is used, it should be called before
+   gzdirect().
+
+     When writing, gzdirect() returns true (1) if transparent writing was
+   requested ("wT" for the gzopen() mode), or false (0) otherwise.  (Note:
+   gzdirect() is not needed when writing.  Transparent writing must be
+   explicitly requested, so the application already knows the answer.  When
+   linking statically, using gzdirect() will include all of the zlib code for
+   gzip file reading and decompression, which may not be desired.)
+*/
+
+ZEXTERN int ZEXPORT    gzclose OF((gzFile file));
+/*
+     Flushes all pending output if necessary, closes the compressed file and
+   deallocates the (de)compression state.  Note that once file is closed, you
+   cannot call gzerror with file, since its structures have been deallocated.
+   gzclose must not be called more than once on the same file, just as free
+   must not be called more than once on the same allocation.
+
+     gzclose will return Z_STREAM_ERROR if file is not valid, Z_ERRNO on a
+   file operation error, Z_MEM_ERROR if out of memory, Z_BUF_ERROR if the
+   last read ended in the middle of a gzip stream, or Z_OK on success.
+*/
+
+ZEXTERN int ZEXPORT gzclose_r OF((gzFile file));
+ZEXTERN int ZEXPORT gzclose_w OF((gzFile file));
+/*
+     Same as gzclose(), but gzclose_r() is only for use when reading, and
+   gzclose_w() is only for use when writing or appending.  The advantage to
+   using these instead of gzclose() is that they avoid linking in zlib
+   compression or decompression code that is not used when only reading or only
+   writing respectively.  If gzclose() is used, then both compression and
+   decompression code will be included the application when linking to a static
+   zlib library.
+*/
+
+ZEXTERN const char * ZEXPORT gzerror OF((gzFile file, int *errnum));
+/*
+     Returns the error message for the last error which occurred on the given
+   compressed file.  errnum is set to zlib error number.  If an error occurred
+   in the file system and not in the compression library, errnum is set to
+   Z_ERRNO and the application may consult errno to get the exact error code.
+
+     The application must not modify the returned string.  Future calls to
+   this function may invalidate the previously returned string.  If file is
+   closed, then the string previously returned by gzerror will no longer be
+   available.
+
+     gzerror() should be used to distinguish errors from end-of-file for those
+   functions above that do not distinguish those cases in their return values.
+*/
+
+ZEXTERN void ZEXPORT gzclearerr OF((gzFile file));
+/*
+     Clears the error and end-of-file flags for file.  This is analogous to the
+   clearerr() function in stdio.  This is useful for continuing to read a gzip
+   file that is being written concurrently.
+*/
+
+#endif /* !Z_SOLO */
+
+                        /* checksum functions */
+
+/*
+     These functions are not related to compression but are exported
+   anyway because they might be useful in applications using the compression
+   library.
+*/
+
+ZEXTERN uLong ZEXPORT adler32 OF((uLong adler, const Bytef *buf, uInt len));
+/*
+     Update a running Adler-32 checksum with the bytes buf[0..len-1] and
+   return the updated checksum.  If buf is Z_NULL, this function returns the
+   required initial value for the checksum.
+
+     An Adler-32 checksum is almost as reliable as a CRC-32 but can be computed
+   much faster.
+
+   Usage example:
+
+     uLong adler = adler32(0L, Z_NULL, 0);
+
+     while (read_buffer(buffer, length) != EOF) {
+       adler = adler32(adler, buffer, length);
+     }
+     if (adler != original_adler) error();
+*/
+
+ZEXTERN uLong ZEXPORT adler32_z OF((uLong adler, const Bytef *buf,
+                                    z_size_t len));
+/*
+     Same as adler32(), but with a size_t length.
+*/
+
+/*
+ZEXTERN uLong ZEXPORT adler32_combine OF((uLong adler1, uLong adler2,
+                                          z_off_t len2));
+
+     Combine two Adler-32 checksums into one.  For two sequences of bytes, seq1
+   and seq2 with lengths len1 and len2, Adler-32 checksums were calculated for
+   each, adler1 and adler2.  adler32_combine() returns the Adler-32 checksum of
+   seq1 and seq2 concatenated, requiring only adler1, adler2, and len2.  Note
+   that the z_off_t type (like off_t) is a signed integer.  If len2 is
+   negative, the result has no meaning or utility.
+*/
+
+ZEXTERN uLong ZEXPORT crc32   OF((uLong crc, const Bytef *buf, uInt len));
+/*
+     Update a running CRC-32 with the bytes buf[0..len-1] and return the
+   updated CRC-32.  If buf is Z_NULL, this function returns the required
+   initial value for the crc.  Pre- and post-conditioning (one's complement) is
+   performed within this function so it shouldn't be done by the application.
+
+   Usage example:
+
+     uLong crc = crc32(0L, Z_NULL, 0);
+
+     while (read_buffer(buffer, length) != EOF) {
+       crc = crc32(crc, buffer, length);
+     }
+     if (crc != original_crc) error();
+*/
+
+ZEXTERN uLong ZEXPORT crc32_z OF((uLong adler, const Bytef *buf,
+                                  z_size_t len));
+/*
+     Same as crc32(), but with a size_t length.
+*/
+
+/*
+ZEXTERN uLong ZEXPORT crc32_combine OF((uLong crc1, uLong crc2, z_off_t len2));
+
+     Combine two CRC-32 check values into one.  For two sequences of bytes,
+   seq1 and seq2 with lengths len1 and len2, CRC-32 check values were
+   calculated for each, crc1 and crc2.  crc32_combine() returns the CRC-32
+   check value of seq1 and seq2 concatenated, requiring only crc1, crc2, and
+   len2.
+*/
+
+
+                        /* various hacks, don't look :) */
+
+/* deflateInit and inflateInit are macros to allow checking the zlib version
+ * and the compiler's view of z_stream:
+ */
+ZEXTERN int ZEXPORT deflateInit_ OF((z_streamp strm, int level,
+                                     const char *version, int stream_size));
+ZEXTERN int ZEXPORT inflateInit_ OF((z_streamp strm,
+                                     const char *version, int stream_size));
+ZEXTERN int ZEXPORT deflateInit2_ OF((z_streamp strm, int  level, int  method,
+                                      int windowBits, int memLevel,
+                                      int strategy, const char *version,
+                                      int stream_size));
+ZEXTERN int ZEXPORT inflateInit2_ OF((z_streamp strm, int  windowBits,
+                                      const char *version, int stream_size));
+ZEXTERN int ZEXPORT inflateBackInit_ OF((z_streamp strm, int windowBits,
+                                         unsigned char FAR *window,
+                                         const char *version,
+                                         int stream_size));
+#ifdef Z_PREFIX_SET
+#  define z_deflateInit(strm, level) \
+          deflateInit_((strm), (level), ZLIB_VERSION, (int)sizeof(z_stream))
+#  define z_inflateInit(strm) \
+          inflateInit_((strm), ZLIB_VERSION, (int)sizeof(z_stream))
+#  define z_deflateInit2(strm, level, method, windowBits, memLevel, strategy) \
+          deflateInit2_((strm),(level),(method),(windowBits),(memLevel),\
+                        (strategy), ZLIB_VERSION, (int)sizeof(z_stream))
+#  define z_inflateInit2(strm, windowBits) \
+          inflateInit2_((strm), (windowBits), ZLIB_VERSION, \
+                        (int)sizeof(z_stream))
+#  define z_inflateBackInit(strm, windowBits, window) \
+          inflateBackInit_((strm), (windowBits), (window), \
+                           ZLIB_VERSION, (int)sizeof(z_stream))
+#else
+#  define deflateInit(strm, level) \
+          deflateInit_((strm), (level), ZLIB_VERSION, (int)sizeof(z_stream))
+#  define inflateInit(strm) \
+          inflateInit_((strm), ZLIB_VERSION, (int)sizeof(z_stream))
+#  define deflateInit2(strm, level, method, windowBits, memLevel, strategy) \
+          deflateInit2_((strm),(level),(method),(windowBits),(memLevel),\
+                        (strategy), ZLIB_VERSION, (int)sizeof(z_stream))
+#  define inflateInit2(strm, windowBits) \
+          inflateInit2_((strm), (windowBits), ZLIB_VERSION, \
+                        (int)sizeof(z_stream))
+#  define inflateBackInit(strm, windowBits, window) \
+          inflateBackInit_((strm), (windowBits), (window), \
+                           ZLIB_VERSION, (int)sizeof(z_stream))
+#endif
+
+#ifndef Z_SOLO
+
+/* gzgetc() macro and its supporting function and exposed data structure.  Note
+ * that the real internal state is much larger than the exposed structure.
+ * This abbreviated structure exposes just enough for the gzgetc() macro.  The
+ * user should not mess with these exposed elements, since their names or
+ * behavior could change in the future, perhaps even capriciously.  They can
+ * only be used by the gzgetc() macro.  You have been warned.
+ */
+struct gzFile_s {
+    unsigned have;
+    unsigned char *next;
+    z_off64_t pos;
+};
+ZEXTERN int ZEXPORT gzgetc_ OF((gzFile file));  /* backward compatibility */
+#ifdef Z_PREFIX_SET
+#  undef z_gzgetc
+#  define z_gzgetc(g) \
+          ((g)->have ? ((g)->have--, (g)->pos++, *((g)->next)++) : (gzgetc)(g))
+#else
+#  define gzgetc(g) \
+          ((g)->have ? ((g)->have--, (g)->pos++, *((g)->next)++) : (gzgetc)(g))
+#endif
+
+/* provide 64-bit offset functions if _LARGEFILE64_SOURCE defined, and/or
+ * change the regular functions to 64 bits if _FILE_OFFSET_BITS is 64 (if
+ * both are true, the application gets the *64 functions, and the regular
+ * functions are changed to 64 bits) -- in case these are set on systems
+ * without large file support, _LFS64_LARGEFILE must also be true
+ */
+#ifdef Z_LARGE64
+   ZEXTERN gzFile ZEXPORT gzopen64 OF((const char *, const char *));
+   ZEXTERN z_off64_t ZEXPORT gzseek64 OF((gzFile, z_off64_t, int));
+   ZEXTERN z_off64_t ZEXPORT gztell64 OF((gzFile));
+   ZEXTERN z_off64_t ZEXPORT gzoffset64 OF((gzFile));
+   ZEXTERN uLong ZEXPORT adler32_combine64 OF((uLong, uLong, z_off64_t));
+   ZEXTERN uLong ZEXPORT crc32_combine64 OF((uLong, uLong, z_off64_t));
+#endif
+
+#if !defined(ZLIB_INTERNAL) && defined(Z_WANT64)
+#  ifdef Z_PREFIX_SET
+#    define z_gzopen z_gzopen64
+#    define z_gzseek z_gzseek64
+#    define z_gztell z_gztell64
+#    define z_gzoffset z_gzoffset64
+#    define z_adler32_combine z_adler32_combine64
+#    define z_crc32_combine z_crc32_combine64
+#  else
+#    define gzopen gzopen64
+#    define gzseek gzseek64
+#    define gztell gztell64
+#    define gzoffset gzoffset64
+#    define adler32_combine adler32_combine64
+#    define crc32_combine crc32_combine64
+#  endif
+#  ifndef Z_LARGE64
+     ZEXTERN gzFile ZEXPORT gzopen64 OF((const char *, const char *));
+     ZEXTERN z_off_t ZEXPORT gzseek64 OF((gzFile, z_off_t, int));
+     ZEXTERN z_off_t ZEXPORT gztell64 OF((gzFile));
+     ZEXTERN z_off_t ZEXPORT gzoffset64 OF((gzFile));
+     ZEXTERN uLong ZEXPORT adler32_combine64 OF((uLong, uLong, z_off_t));
+     ZEXTERN uLong ZEXPORT crc32_combine64 OF((uLong, uLong, z_off_t));
+#  endif
+#else
+   ZEXTERN gzFile ZEXPORT gzopen OF((const char *, const char *));
+   ZEXTERN z_off_t ZEXPORT gzseek OF((gzFile, z_off_t, int));
+   ZEXTERN z_off_t ZEXPORT gztell OF((gzFile));
+   ZEXTERN z_off_t ZEXPORT gzoffset OF((gzFile));
+   ZEXTERN uLong ZEXPORT adler32_combine OF((uLong, uLong, z_off_t));
+   ZEXTERN uLong ZEXPORT crc32_combine OF((uLong, uLong, z_off_t));
+#endif
+
+#else /* Z_SOLO */
+
+   ZEXTERN uLong ZEXPORT adler32_combine OF((uLong, uLong, z_off_t));
+   ZEXTERN uLong ZEXPORT crc32_combine OF((uLong, uLong, z_off_t));
+
+#endif /* !Z_SOLO */
+
+/* undocumented functions */
+ZEXTERN const char   * ZEXPORT zError           OF((int));
+ZEXTERN int            ZEXPORT inflateSyncPoint OF((z_streamp));
+ZEXTERN const z_crc_t FAR * ZEXPORT get_crc_table    OF((void));
+ZEXTERN int            ZEXPORT inflateUndermine OF((z_streamp, int));
+ZEXTERN int            ZEXPORT inflateValidate OF((z_streamp, int));
+ZEXTERN unsigned long  ZEXPORT inflateCodesUsed OF ((z_streamp));
+ZEXTERN int            ZEXPORT inflateResetKeep OF((z_streamp));
+ZEXTERN int            ZEXPORT deflateResetKeep OF((z_streamp));
+#if (defined(_WIN32) || defined(__CYGWIN__)) && !defined(Z_SOLO)
+ZEXTERN gzFile         ZEXPORT gzopen_w OF((const wchar_t *path,
+                                            const char *mode));
+#endif
+#if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#  ifndef Z_SOLO
+ZEXTERN int            ZEXPORTVA gzvprintf Z_ARG((gzFile file,
+                                                  const char *format,
+                                                  va_list va));
+#  endif
+#endif
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif /* ZLIB_H */

ADDED   3rd_party/zlib/zlib.map
Index: 3rd_party/zlib/zlib.map
==================================================================
--- 3rd_party/zlib/zlib.map
+++ 3rd_party/zlib/zlib.map
@@ -0,0 +1,94 @@
+ZLIB_1.2.0 {
+  global:
+    compressBound;
+    deflateBound;
+    inflateBack;
+    inflateBackEnd;
+    inflateBackInit_;
+    inflateCopy;
+  local:
+    deflate_copyright;
+    inflate_copyright;
+    inflate_fast;
+    inflate_table;
+    zcalloc;
+    zcfree;
+    z_errmsg;
+    gz_error;
+    gz_intmax;
+    _*;
+};
+
+ZLIB_1.2.0.2 {
+    gzclearerr;
+    gzungetc;
+    zlibCompileFlags;
+} ZLIB_1.2.0;
+
+ZLIB_1.2.0.8 {
+    deflatePrime;
+} ZLIB_1.2.0.2;
+
+ZLIB_1.2.2 {
+    adler32_combine;
+    crc32_combine;
+    deflateSetHeader;
+    inflateGetHeader;
+} ZLIB_1.2.0.8;
+
+ZLIB_1.2.2.3 {
+    deflateTune;
+    gzdirect;
+} ZLIB_1.2.2;
+
+ZLIB_1.2.2.4 {
+    inflatePrime;
+} ZLIB_1.2.2.3;
+
+ZLIB_1.2.3.3 {
+    adler32_combine64;
+    crc32_combine64;
+    gzopen64;
+    gzseek64;
+    gztell64;
+    inflateUndermine;
+} ZLIB_1.2.2.4;
+
+ZLIB_1.2.3.4 {
+    inflateReset2;
+    inflateMark;
+} ZLIB_1.2.3.3;
+
+ZLIB_1.2.3.5 {
+    gzbuffer;
+    gzoffset;
+    gzoffset64;
+    gzclose_r;
+    gzclose_w;
+} ZLIB_1.2.3.4;
+
+ZLIB_1.2.5.1 {
+    deflatePending;
+} ZLIB_1.2.3.5;
+
+ZLIB_1.2.5.2 {
+    deflateResetKeep;
+    gzgetc_;
+    inflateResetKeep;
+} ZLIB_1.2.5.1;
+
+ZLIB_1.2.7.1 {
+    inflateGetDictionary;
+    gzvprintf;
+} ZLIB_1.2.5.2;
+
+ZLIB_1.2.9 {
+    inflateCodesUsed;
+    inflateValidate;
+    uncompress2;
+    gzfread;
+    gzfwrite;
+    deflateGetDictionary;
+    adler32_z;
+    crc32_z;
+} ZLIB_1.2.7.1;

ADDED   3rd_party/zlib/zlib.pc.cmakein
Index: 3rd_party/zlib/zlib.pc.cmakein
==================================================================
--- 3rd_party/zlib/zlib.pc.cmakein
+++ 3rd_party/zlib/zlib.pc.cmakein
@@ -0,0 +1,13 @@
+prefix=@CMAKE_INSTALL_PREFIX@
+exec_prefix=@CMAKE_INSTALL_PREFIX@
+libdir=@INSTALL_LIB_DIR@
+sharedlibdir=@INSTALL_LIB_DIR@
+includedir=@INSTALL_INC_DIR@
+
+Name: zlib
+Description: zlib compression library
+Version: @VERSION@
+
+Requires:
+Libs: -L${libdir} -L${sharedlibdir} -lz
+Cflags: -I${includedir}

ADDED   3rd_party/zlib/zlib.pc.in
Index: 3rd_party/zlib/zlib.pc.in
==================================================================
--- 3rd_party/zlib/zlib.pc.in
+++ 3rd_party/zlib/zlib.pc.in
@@ -0,0 +1,13 @@
+prefix=@prefix@
+exec_prefix=@exec_prefix@
+libdir=@libdir@
+sharedlibdir=@sharedlibdir@
+includedir=@includedir@
+
+Name: zlib
+Description: zlib compression library
+Version: @VERSION@
+
+Requires:
+Libs: -L${libdir} -L${sharedlibdir} -lz
+Cflags: -I${includedir}

ADDED   3rd_party/zlib/zlib2ansi
Index: 3rd_party/zlib/zlib2ansi
==================================================================
--- 3rd_party/zlib/zlib2ansi
+++ 3rd_party/zlib/zlib2ansi
@@ -0,0 +1,152 @@
+#!/usr/bin/perl
+
+# Transform K&R C function definitions into ANSI equivalent.
+#
+# Author: Paul Marquess
+# Version: 1.0
+# Date: 3 October 2006
+
+# TODO
+#
+# Asumes no function pointer parameters. unless they are typedefed.
+# Assumes no literal strings that look like function definitions
+# Assumes functions start at the beginning of a line
+
+use strict;
+use warnings;
+
+local $/;
+$_ = <>;
+
+my $sp = qr{ \s* (?: /\* .*? \*/ )? \s* }x; # assume no nested comments
+
+my $d1    = qr{ $sp (?: [\w\*\s]+ $sp)* $sp \w+ $sp [\[\]\s]* $sp }x ;
+my $decl  = qr{ $sp (?: \w+ $sp )+ $d1 }xo ;
+my $dList = qr{ $sp $decl (?: $sp , $d1 )* $sp ; $sp }xo ;
+
+
+while (s/^
+            (                  # Start $1
+                (              #   Start $2
+                    .*?        #     Minimal eat content
+                    ( ^ \w [\w\s\*]+ )    #     $3 -- function name
+                    \s*        #     optional whitespace
+                )              # $2 - Matched up to before parameter list
+
+                \( \s*         # Literal "(" + optional whitespace
+                ( [^\)]+ )     # $4 - one or more anythings except ")"
+                \s* \)         # optional whitespace surrounding a Literal ")"
+
+                ( (?: $dList )+ ) # $5
+
+                $sp ^ {        # literal "{" at start of line
+            )                  # Remember to $1
+        //xsom
+      )
+{
+    my $all = $1 ;
+    my $prefix = $2;
+    my $param_list = $4 ;
+    my $params = $5;
+
+    StripComments($params);
+    StripComments($param_list);
+    $param_list =~ s/^\s+//;
+    $param_list =~ s/\s+$//;
+
+    my $i = 0 ;
+    my %pList = map { $_ => $i++ }
+                split /\s*,\s*/, $param_list;
+    my $pMatch = '(\b' . join('|', keys %pList) . '\b)\W*$' ;
+
+    my @params = split /\s*;\s*/, $params;
+    my @outParams = ();
+    foreach my $p (@params)
+    {
+        if ($p =~ /,/)
+        {
+            my @bits = split /\s*,\s*/, $p;
+            my $first = shift @bits;
+            $first =~ s/^\s*//;
+            push @outParams, $first;
+            $first =~ /^(\w+\s*)/;
+            my $type = $1 ;
+            push @outParams, map { $type . $_ } @bits;
+        }
+        else
+        {
+            $p =~ s/^\s+//;
+            push @outParams, $p;
+        }
+    }
+
+
+    my %tmp = map { /$pMatch/;  $_ => $pList{$1}  }
+              @outParams ;
+
+    @outParams = map  { "    $_" }
+                 sort { $tmp{$a} <=> $tmp{$b} }
+                 @outParams ;
+
+    print $prefix ;
+    print "(\n" . join(",\n", @outParams) . ")\n";
+    print "{" ;
+
+}
+
+# Output any trailing code.
+print ;
+exit 0;
+
+
+sub StripComments
+{
+
+  no warnings;
+
+  # Strip C & C++ coments
+  # From the perlfaq
+  $_[0] =~
+
+    s{
+       /\*         ##  Start of /* ... */ comment
+       [^*]*\*+    ##  Non-* followed by 1-or-more *'s
+       (
+         [^/*][^*]*\*+
+       )*          ##  0-or-more things which don't start with /
+                   ##    but do end with '*'
+       /           ##  End of /* ... */ comment
+
+     |         ##     OR  C++ Comment
+       //          ## Start of C++ comment //
+       [^\n]*      ## followed by 0-or-more non end of line characters
+
+     |         ##     OR  various things which aren't comments:
+
+       (
+         "           ##  Start of " ... " string
+         (
+           \\.           ##  Escaped char
+         |               ##    OR
+           [^"\\]        ##  Non "\
+         )*
+         "           ##  End of " ... " string
+
+       |         ##     OR
+
+         '           ##  Start of ' ... ' string
+         (
+           \\.           ##  Escaped char
+         |               ##    OR
+           [^'\\]        ##  Non '\
+         )*
+         '           ##  End of ' ... ' string
+
+       |         ##     OR
+
+         .           ##  Anything other char
+         [^/"'\\]*   ##  Chars which doesn't start a comment, string or escape
+       )
+     }{$2}gxs;
+
+}

ADDED   3rd_party/zlib/zutil.c
Index: 3rd_party/zlib/zutil.c
==================================================================
--- 3rd_party/zlib/zutil.c
+++ 3rd_party/zlib/zutil.c
@@ -0,0 +1,325 @@
+/* zutil.c -- target dependent utility functions for the compression library
+ * Copyright (C) 1995-2017 Jean-loup Gailly
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* @(#) $Id$ */
+
+#include "zutil.h"
+#ifndef Z_SOLO
+#  include "gzguts.h"
+#endif
+
+z_const char * const z_errmsg[10] = {
+    (z_const char *)"need dictionary",     /* Z_NEED_DICT       2  */
+    (z_const char *)"stream end",          /* Z_STREAM_END      1  */
+    (z_const char *)"",                    /* Z_OK              0  */
+    (z_const char *)"file error",          /* Z_ERRNO         (-1) */
+    (z_const char *)"stream error",        /* Z_STREAM_ERROR  (-2) */
+    (z_const char *)"data error",          /* Z_DATA_ERROR    (-3) */
+    (z_const char *)"insufficient memory", /* Z_MEM_ERROR     (-4) */
+    (z_const char *)"buffer error",        /* Z_BUF_ERROR     (-5) */
+    (z_const char *)"incompatible version",/* Z_VERSION_ERROR (-6) */
+    (z_const char *)""
+};
+
+
+const char * ZEXPORT zlibVersion()
+{
+    return ZLIB_VERSION;
+}
+
+uLong ZEXPORT zlibCompileFlags()
+{
+    uLong flags;
+
+    flags = 0;
+    switch ((int)(sizeof(uInt))) {
+    case 2:     break;
+    case 4:     flags += 1;     break;
+    case 8:     flags += 2;     break;
+    default:    flags += 3;
+    }
+    switch ((int)(sizeof(uLong))) {
+    case 2:     break;
+    case 4:     flags += 1 << 2;        break;
+    case 8:     flags += 2 << 2;        break;
+    default:    flags += 3 << 2;
+    }
+    switch ((int)(sizeof(voidpf))) {
+    case 2:     break;
+    case 4:     flags += 1 << 4;        break;
+    case 8:     flags += 2 << 4;        break;
+    default:    flags += 3 << 4;
+    }
+    switch ((int)(sizeof(z_off_t))) {
+    case 2:     break;
+    case 4:     flags += 1 << 6;        break;
+    case 8:     flags += 2 << 6;        break;
+    default:    flags += 3 << 6;
+    }
+#ifdef ZLIB_DEBUG
+    flags += 1 << 8;
+#endif
+#if defined(ASMV) || defined(ASMINF)
+    flags += 1 << 9;
+#endif
+#ifdef ZLIB_WINAPI
+    flags += 1 << 10;
+#endif
+#ifdef BUILDFIXED
+    flags += 1 << 12;
+#endif
+#ifdef DYNAMIC_CRC_TABLE
+    flags += 1 << 13;
+#endif
+#ifdef NO_GZCOMPRESS
+    flags += 1L << 16;
+#endif
+#ifdef NO_GZIP
+    flags += 1L << 17;
+#endif
+#ifdef PKZIP_BUG_WORKAROUND
+    flags += 1L << 20;
+#endif
+#ifdef FASTEST
+    flags += 1L << 21;
+#endif
+#if defined(STDC) || defined(Z_HAVE_STDARG_H)
+#  ifdef NO_vsnprintf
+    flags += 1L << 25;
+#    ifdef HAS_vsprintf_void
+    flags += 1L << 26;
+#    endif
+#  else
+#    ifdef HAS_vsnprintf_void
+    flags += 1L << 26;
+#    endif
+#  endif
+#else
+    flags += 1L << 24;
+#  ifdef NO_snprintf
+    flags += 1L << 25;
+#    ifdef HAS_sprintf_void
+    flags += 1L << 26;
+#    endif
+#  else
+#    ifdef HAS_snprintf_void
+    flags += 1L << 26;
+#    endif
+#  endif
+#endif
+    return flags;
+}
+
+#ifdef ZLIB_DEBUG
+#include <stdlib.h>
+#  ifndef verbose
+#    define verbose 0
+#  endif
+int ZLIB_INTERNAL z_verbose = verbose;
+
+void ZLIB_INTERNAL z_error (m)
+    char *m;
+{
+    fprintf(stderr, "%s\n", m);
+    exit(1);
+}
+#endif
+
+/* exported to allow conversion of error code to string for compress() and
+ * uncompress()
+ */
+const char * ZEXPORT zError(err)
+    int err;
+{
+    return ERR_MSG(err);
+}
+
+#if defined(_WIN32_WCE)
+    /* The Microsoft C Run-Time Library for Windows CE doesn't have
+     * errno.  We define it as a global variable to simplify porting.
+     * Its value is always 0 and should not be used.
+     */
+    int errno = 0;
+#endif
+
+#ifndef HAVE_MEMCPY
+
+void ZLIB_INTERNAL zmemcpy(dest, source, len)
+    Bytef* dest;
+    const Bytef* source;
+    uInt  len;
+{
+    if (len == 0) return;
+    do {
+        *dest++ = *source++; /* ??? to be unrolled */
+    } while (--len != 0);
+}
+
+int ZLIB_INTERNAL zmemcmp(s1, s2, len)
+    const Bytef* s1;
+    const Bytef* s2;
+    uInt  len;
+{
+    uInt j;
+
+    for (j = 0; j < len; j++) {
+        if (s1[j] != s2[j]) return 2*(s1[j] > s2[j])-1;
+    }
+    return 0;
+}
+
+void ZLIB_INTERNAL zmemzero(dest, len)
+    Bytef* dest;
+    uInt  len;
+{
+    if (len == 0) return;
+    do {
+        *dest++ = 0;  /* ??? to be unrolled */
+    } while (--len != 0);
+}
+#endif
+
+#ifndef Z_SOLO
+
+#ifdef SYS16BIT
+
+#ifdef __TURBOC__
+/* Turbo C in 16-bit mode */
+
+#  define MY_ZCALLOC
+
+/* Turbo C malloc() does not allow dynamic allocation of 64K bytes
+ * and farmalloc(64K) returns a pointer with an offset of 8, so we
+ * must fix the pointer. Warning: the pointer must be put back to its
+ * original form in order to free it, use zcfree().
+ */
+
+#define MAX_PTR 10
+/* 10*64K = 640K */
+
+local int next_ptr = 0;
+
+typedef struct ptr_table_s {
+    voidpf org_ptr;
+    voidpf new_ptr;
+} ptr_table;
+
+local ptr_table table[MAX_PTR];
+/* This table is used to remember the original form of pointers
+ * to large buffers (64K). Such pointers are normalized with a zero offset.
+ * Since MSDOS is not a preemptive multitasking OS, this table is not
+ * protected from concurrent access. This hack doesn't work anyway on
+ * a protected system like OS/2. Use Microsoft C instead.
+ */
+
+voidpf ZLIB_INTERNAL zcalloc (voidpf opaque, unsigned items, unsigned size)
+{
+    voidpf buf;
+    ulg bsize = (ulg)items*size;
+
+    (void)opaque;
+
+    /* If we allocate less than 65520 bytes, we assume that farmalloc
+     * will return a usable pointer which doesn't have to be normalized.
+     */
+    if (bsize < 65520L) {
+        buf = farmalloc(bsize);
+        if (*(ush*)&buf != 0) return buf;
+    } else {
+        buf = farmalloc(bsize + 16L);
+    }
+    if (buf == NULL || next_ptr >= MAX_PTR) return NULL;
+    table[next_ptr].org_ptr = buf;
+
+    /* Normalize the pointer to seg:0 */
+    *((ush*)&buf+1) += ((ush)((uch*)buf-0) + 15) >> 4;
+    *(ush*)&buf = 0;
+    table[next_ptr++].new_ptr = buf;
+    return buf;
+}
+
+void ZLIB_INTERNAL zcfree (voidpf opaque, voidpf ptr)
+{
+    int n;
+
+    (void)opaque;
+
+    if (*(ush*)&ptr != 0) { /* object < 64K */
+        farfree(ptr);
+        return;
+    }
+    /* Find the original pointer */
+    for (n = 0; n < next_ptr; n++) {
+        if (ptr != table[n].new_ptr) continue;
+
+        farfree(table[n].org_ptr);
+        while (++n < next_ptr) {
+            table[n-1] = table[n];
+        }
+        next_ptr--;
+        return;
+    }
+    Assert(0, "zcfree: ptr not found");
+}
+
+#endif /* __TURBOC__ */
+
+
+#ifdef M_I86
+/* Microsoft C in 16-bit mode */
+
+#  define MY_ZCALLOC
+
+#if (!defined(_MSC_VER) || (_MSC_VER <= 600))
+#  define _halloc  halloc
+#  define _hfree   hfree
+#endif
+
+voidpf ZLIB_INTERNAL zcalloc (voidpf opaque, uInt items, uInt size)
+{
+    (void)opaque;
+    return _halloc((long)items, size);
+}
+
+void ZLIB_INTERNAL zcfree (voidpf opaque, voidpf ptr)
+{
+    (void)opaque;
+    _hfree(ptr);
+}
+
+#endif /* M_I86 */
+
+#endif /* SYS16BIT */
+
+
+#ifndef MY_ZCALLOC /* Any system without a special alloc function */
+
+#ifndef STDC
+extern voidp  malloc OF((uInt size));
+extern voidp  calloc OF((uInt items, uInt size));
+extern void   free   OF((voidpf ptr));
+#endif
+
+voidpf ZLIB_INTERNAL zcalloc (opaque, items, size)
+    voidpf opaque;
+    unsigned items;
+    unsigned size;
+{
+    (void)opaque;
+    return sizeof(uInt) > 2 ? (voidpf)malloc(items * size) :
+                              (voidpf)calloc(items, size);
+}
+
+void ZLIB_INTERNAL zcfree (opaque, ptr)
+    voidpf opaque;
+    voidpf ptr;
+{
+    (void)opaque;
+    free(ptr);
+}
+
+#endif /* MY_ZCALLOC */
+
+#endif /* !Z_SOLO */

ADDED   3rd_party/zlib/zutil.h
Index: 3rd_party/zlib/zutil.h
==================================================================
--- 3rd_party/zlib/zutil.h
+++ 3rd_party/zlib/zutil.h
@@ -0,0 +1,271 @@
+/* zutil.h -- internal interface and configuration of the compression library
+ * Copyright (C) 1995-2016 Jean-loup Gailly, Mark Adler
+ * For conditions of distribution and use, see copyright notice in zlib.h
+ */
+
+/* WARNING: this file should *not* be used by applications. It is
+   part of the implementation of the compression library and is
+   subject to change. Applications should only use zlib.h.
+ */
+
+/* @(#) $Id$ */
+
+#ifndef ZUTIL_H
+#define ZUTIL_H
+
+#ifdef HAVE_HIDDEN
+#  define ZLIB_INTERNAL __attribute__((visibility ("hidden")))
+#else
+#  define ZLIB_INTERNAL
+#endif
+
+#include "zlib.h"
+
+#if defined(STDC) && !defined(Z_SOLO)
+#  if !(defined(_WIN32_WCE) && defined(_MSC_VER))
+#    include <stddef.h>
+#  endif
+#  include <string.h>
+#  include <stdlib.h>
+#endif
+
+#ifdef Z_SOLO
+   typedef long ptrdiff_t;  /* guess -- will be caught if guess is wrong */
+#endif
+
+#ifndef local
+#  define local static
+#endif
+/* since "static" is used to mean two completely different things in C, we
+   define "local" for the non-static meaning of "static", for readability
+   (compile with -Dlocal if your debugger can't find static symbols) */
+
+typedef unsigned char  uch;
+typedef uch FAR uchf;
+typedef unsigned short ush;
+typedef ush FAR ushf;
+typedef unsigned long  ulg;
+
+extern z_const char * const z_errmsg[10]; /* indexed by 2-zlib_error */
+/* (size given to avoid silly warnings with Visual C++) */
+
+#define ERR_MSG(err) z_errmsg[Z_NEED_DICT-(err)]
+
+#define ERR_RETURN(strm,err) \
+  return (strm->msg = ERR_MSG(err), (err))
+/* To be used only when the state is known to be valid */
+
+        /* common constants */
+
+#ifndef DEF_WBITS
+#  define DEF_WBITS MAX_WBITS
+#endif
+/* default windowBits for decompression. MAX_WBITS is for compression only */
+
+#if MAX_MEM_LEVEL >= 8
+#  define DEF_MEM_LEVEL 8
+#else
+#  define DEF_MEM_LEVEL  MAX_MEM_LEVEL
+#endif
+/* default memLevel */
+
+#define STORED_BLOCK 0
+#define STATIC_TREES 1
+#define DYN_TREES    2
+/* The three kinds of block type */
+
+#define MIN_MATCH  3
+#define MAX_MATCH  258
+/* The minimum and maximum match lengths */
+
+#define PRESET_DICT 0x20 /* preset dictionary flag in zlib header */
+
+        /* target dependencies */
+
+#if defined(MSDOS) || (defined(WINDOWS) && !defined(WIN32))
+#  define OS_CODE  0x00
+#  ifndef Z_SOLO
+#    if defined(__TURBOC__) || defined(__BORLANDC__)
+#      if (__STDC__ == 1) && (defined(__LARGE__) || defined(__COMPACT__))
+         /* Allow compilation with ANSI keywords only enabled */
+         void _Cdecl farfree( void *block );
+         void *_Cdecl farmalloc( unsigned long nbytes );
+#      else
+#        include <alloc.h>
+#      endif
+#    else /* MSC or DJGPP */
+#      include <malloc.h>
+#    endif
+#  endif
+#endif
+
+#ifdef AMIGA
+#  define OS_CODE  1
+#endif
+
+#if defined(VAXC) || defined(VMS)
+#  define OS_CODE  2
+#  define F_OPEN(name, mode) \
+     fopen((name), (mode), "mbc=60", "ctx=stm", "rfm=fix", "mrs=512")
+#endif
+
+#ifdef __370__
+#  if __TARGET_LIB__ < 0x20000000
+#    define OS_CODE 4
+#  elif __TARGET_LIB__ < 0x40000000
+#    define OS_CODE 11
+#  else
+#    define OS_CODE 8
+#  endif
+#endif
+
+#if defined(ATARI) || defined(atarist)
+#  define OS_CODE  5
+#endif
+
+#ifdef OS2
+#  define OS_CODE  6
+#  if defined(M_I86) && !defined(Z_SOLO)
+#    include <malloc.h>
+#  endif
+#endif
+
+#if defined(MACOS) || defined(TARGET_OS_MAC)
+#  define OS_CODE  7
+#  ifndef Z_SOLO
+#    if defined(__MWERKS__) && __dest_os != __be_os && __dest_os != __win32_os
+#      include <unix.h> /* for fdopen */
+#    else
+#      ifndef fdopen
+#        define fdopen(fd,mode) NULL /* No fdopen() */
+#      endif
+#    endif
+#  endif
+#endif
+
+#ifdef __acorn
+#  define OS_CODE 13
+#endif
+
+#if defined(WIN32) && !defined(__CYGWIN__)
+#  define OS_CODE  10
+#endif
+
+#ifdef _BEOS_
+#  define OS_CODE  16
+#endif
+
+#ifdef __TOS_OS400__
+#  define OS_CODE 18
+#endif
+
+#ifdef __APPLE__
+#  define OS_CODE 19
+#endif
+
+#if defined(_BEOS_) || defined(RISCOS)
+#  define fdopen(fd,mode) NULL /* No fdopen() */
+#endif
+
+#if (defined(_MSC_VER) && (_MSC_VER > 600)) && !defined __INTERIX
+#  if defined(_WIN32_WCE)
+#    define fdopen(fd,mode) NULL /* No fdopen() */
+#    ifndef _PTRDIFF_T_DEFINED
+       typedef int ptrdiff_t;
+#      define _PTRDIFF_T_DEFINED
+#    endif
+#  else
+#    define fdopen(fd,type)  _fdopen(fd,type)
+#  endif
+#endif
+
+#if defined(__BORLANDC__) && !defined(MSDOS)
+  #pragma warn -8004
+  #pragma warn -8008
+  #pragma warn -8066
+#endif
+
+/* provide prototypes for these when building zlib without LFS */
+#if !defined(_WIN32) && \
+    (!defined(_LARGEFILE64_SOURCE) || _LFS64_LARGEFILE-0 == 0)
+    ZEXTERN uLong ZEXPORT adler32_combine64 OF((uLong, uLong, z_off_t));
+    ZEXTERN uLong ZEXPORT crc32_combine64 OF((uLong, uLong, z_off_t));
+#endif
+
+        /* common defaults */
+
+#ifndef OS_CODE
+#  define OS_CODE  3     /* assume Unix */
+#endif
+
+#ifndef F_OPEN
+#  define F_OPEN(name, mode) fopen((name), (mode))
+#endif
+
+         /* functions */
+
+#if defined(pyr) || defined(Z_SOLO)
+#  define NO_MEMCPY
+#endif
+#if defined(SMALL_MEDIUM) && !defined(_MSC_VER) && !defined(__SC__)
+ /* Use our own functions for small and medium model with MSC <= 5.0.
+  * You may have to use the same strategy for Borland C (untested).
+  * The __SC__ check is for Symantec.
+  */
+#  define NO_MEMCPY
+#endif
+#if defined(STDC) && !defined(HAVE_MEMCPY) && !defined(NO_MEMCPY)
+#  define HAVE_MEMCPY
+#endif
+#ifdef HAVE_MEMCPY
+#  ifdef SMALL_MEDIUM /* MSDOS small or medium model */
+#    define zmemcpy _fmemcpy
+#    define zmemcmp _fmemcmp
+#    define zmemzero(dest, len) _fmemset(dest, 0, len)
+#  else
+#    define zmemcpy memcpy
+#    define zmemcmp memcmp
+#    define zmemzero(dest, len) memset(dest, 0, len)
+#  endif
+#else
+   void ZLIB_INTERNAL zmemcpy OF((Bytef* dest, const Bytef* source, uInt len));
+   int ZLIB_INTERNAL zmemcmp OF((const Bytef* s1, const Bytef* s2, uInt len));
+   void ZLIB_INTERNAL zmemzero OF((Bytef* dest, uInt len));
+#endif
+
+/* Diagnostic functions */
+#ifdef ZLIB_DEBUG
+#  include <stdio.h>
+   extern int ZLIB_INTERNAL z_verbose;
+   extern void ZLIB_INTERNAL z_error OF((char *m));
+#  define Assert(cond,msg) {if(!(cond)) z_error(msg);}
+#  define Trace(x) {if (z_verbose>=0) fprintf x ;}
+#  define Tracev(x) {if (z_verbose>0) fprintf x ;}
+#  define Tracevv(x) {if (z_verbose>1) fprintf x ;}
+#  define Tracec(c,x) {if (z_verbose>0 && (c)) fprintf x ;}
+#  define Tracecv(c,x) {if (z_verbose>1 && (c)) fprintf x ;}
+#else
+#  define Assert(cond,msg)
+#  define Trace(x)
+#  define Tracev(x)
+#  define Tracevv(x)
+#  define Tracec(c,x)
+#  define Tracecv(c,x)
+#endif
+
+#ifndef Z_SOLO
+   voidpf ZLIB_INTERNAL zcalloc OF((voidpf opaque, unsigned items,
+                                    unsigned size));
+   void ZLIB_INTERNAL zcfree  OF((voidpf opaque, voidpf ptr));
+#endif
+
+#define ZALLOC(strm, items, size) \
+           (*((strm)->zalloc))((strm)->opaque, (items), (size))
+#define ZFREE(strm, addr)  (*((strm)->zfree))((strm)->opaque, (voidpf)(addr))
+#define TRY_FREE(s, p) {if (p) ZFREE(s, p);}
+
+/* Reverse the bytes in a 32-bit value */
+#define ZSWAP32(q) ((((q) >> 24) & 0xff) + (((q) >> 8) & 0xff00) + \
+                    (((q) & 0xff00) << 8) + (((q) & 0xff) << 24))
+
+#endif /* ZUTIL_H */

ADDED   3rd_party/zstd-1.1.0/wscript
Index: 3rd_party/zstd-1.1.0/wscript
==================================================================
--- 3rd_party/zstd-1.1.0/wscript
+++ 3rd_party/zstd-1.1.0/wscript
@@ -0,0 +1,24 @@
+import os.path
+
+def build( bld ):
+	sources = [
+		'lib/common/zstd_common.c',
+		'lib/common/entropy_common.c',
+		'lib/common/fse_decompress.c',
+		'lib/common/xxhash.c',
+		'lib/decompress/huf_decompress.c',
+		'lib/decompress/zbuff_decompress.c',
+		'lib/decompress/zstd_decompress.c',
+		'lib/compress/fse_compress.c',
+		'lib/compress/huf_compress.c',
+		'lib/compress/zbuff_compress.c',
+		'lib/compress/zstd_compress.c'
+	]
+	bld.stlib(
+		name = 'zstd',
+		target = 'zstd',
+		source = sources,
+		cflags = '-fPIC',
+		includes = [ 'lib', 'lib/common', 'lib/compress', 'lib/decompress' ],
+		export_includes = 'lib/'
+	)

DELETED CHANGELOG.txt
Index: CHANGELOG.txt
==================================================================
--- CHANGELOG.txt
+++ CHANGELOG.txt
@@ -1,54 +0,0 @@
-CHANGELOG for QCTOOL:
-
-** Version 1.4, released June 2014 **
-
-* fix a bug with gzipped output that sometimes produced files with incorrect checksum.
-* Fix crashing bug with Hardy-Weinberg P-value computation for large sample sizes (>45,000).
-
-** Version 1.3, released September 2013 **
-
-* A new option pair -[in|ex]cl-snps has been added. This reads a list of SNPs in the format output by the -write-snp-excl-list option. This is a file with 6 named columns, SNPID, rsid, chromosome, position, alleleA, alleleB.
-* A bug preventing the -incl-snpids option from working correctly was fixed.
-
-** Version 1.2, released June 2012 **
-
-* Fix a bug handling VCF files with more than 10000 variants.
-* Get line numbers right in errors relating to VCF files.
-* Support bgzipped files via a tweak to boost (see boost TRAC ticket #6994 and #5904).
-* Make -sort use temporary files in the same directory as the target (rather than a system directory.) This should improve its use on compute clusters.
-* Support use of -sort with output .vcf files.
-* New options -incl-positions and -excl-positions have been added.  Each takes a file containing a whitespace-separated list of genomic positions in the form chromosome:position.
-
-** Version 1.1, released April 2012 **
-
-New features:
-
-* QCTOOL now has initial support for VCF files.
-* New/renamed options for selection of SNPs: -[in|ex]clude-range, -[in|ex]cl-rsids, -[in|ex]cl-snpids, -[in|ex]cl-snps-matching.
-	These replace -snp-excl-list, -snp-interval, and -snpid-filter.
-	These are AND'd together to form the SNP filter, with the exception that repeated invocations of each -incl-X option are first
-	combined.  Thus the command qctool -g example.gen -incl-range 06:25000000-40000000 11:0-10000000 -excl-rsids my_snps.txt
-	will include all SNPs in either region that are not in the exclusion list.
-* SNP filters which filter on SNP id fields (-[in|ex]clude-range, -[in|ex]cl-rsids, -[in|ex]cl-snpids, -[in|ex]cl-snps-matching)
-    are now applied before the main qctool processing pipeline.  The practical consequence is that SNP exclusion lists written using
-    -write-snp-excl-list do not contain the SNPs in any exclusion lists passed in.
-* New option -condition-on, similar to SNPTEST's -condition_on, adds genotypic dosages to the output sample file.
-* New -quantile-normalise option: quantile-normalisation of columns in the sample file.
-* New -assume-chromosome option.  If this is used, QCTOOL will fill in missing chromosome values with the given one.
-* New: support for multiple cohorts (by specifying -g and/or -s several times.)  SNPs are matched between cohorts using the fields
-  specified by -snp-match-fields (which must include position).  If cohorts have the same alleles but they may be coded in opposite ways
-	(e.g. cohort1 has "T C" and cohort2 has "C T"), use -match-alleles-to-cohort1 to flip the alleles appropriately.
-* New option -sort, which sorts the output file.  Currently this works with BGEN, unzipped GEN, and unzipped VCF files.
-* QCTOOL now writes a chromosome column in GEN file output by default.  This is understood by recent builds of SNPTEST but possibly not by other
-    tools.  To suppress it, use -omit-chromosome.
-* Change to the way the -snp-stats, -sample-stats, -write-sample-excl-list and -write-snp-excl-list options behave.
-    Now each takes the name of a file to output, which must be specified.
-* File output by -snp-stats has changed format slightly, removing the first column of numbers.
-* QCTOOL no longer writes a log file by default: use -log to specify it.
-* QCTOOL no longer has a default output sample file name.  You must specify -os whenever an output sample file is needed.
-* QCTOOL now does not count lines in GEN or VCF files first.  This speeds up processing of large files.
-* Fix bug where values in screen output are rounded to too low precision.
-
-** Version 1.0, released 2008 **
-- First release version.
-

ADDED   R/simulate/R/analyse_host_para.R
Index: R/simulate/R/analyse_host_para.R
==================================================================
--- R/simulate/R/analyse_host_para.R
+++ R/simulate/R/analyse_host_para.R
@@ -0,0 +1,115 @@
+logistic <- function(x) {
+	exp(x) / (1+exp(x))
+}
+
+dlogf <- function( x, nu1, nu2 ) {
+	a = nu1/2
+	b = nu2/2
+	l = logistic(x)
+	(l^a * (1 - l)^b)/beta(a,b)
+}
+
+plogf <- function( x, nu1, nu2 ) {
+	a = nu1/2
+	b = nu2/2
+	pbeta( logistic(x), shape1 = a+1, shape2 = b+1 )
+}
+
+dlogf <- function( x, nu1, nu2 ) {
+	a = nu1/2
+	b = nu2/2
+	exp(-b * x ) / (( 1 + exp(-x))^(a+b) * beta(a,b))
+}
+
+dnmixture <- function( x, sds = c( 0.05, 0.1, 0.2, 0.4 ), alphas = rep( 0.25, 4 ) ) {
+	result = numeric(length(x))
+	for( i in 1:length( sds )) {
+		result = result + alphas[i] * dnorm( x, sd = sds[i] )
+	}
+	return( result )
+}
+
+hptest = "../../../build/release/hptest_v2.1-dev" 
+system(
+	sprintf( "%s -predictor host.vcf -outcome parasite.vcf -s samples.sample -o /tmp/output.txt", hptest )
+)
+X = read.table( "/tmp/output.txt", hea=T, as.is=T, comment = '#', check.names = F )
+host.spec = read.table( "host_spec.txt", hea=T, as.is= T)
+interactors = host.spec[ !is.na( host.spec$interactors ), ]
+interactors$index = match(
+	paste( interactors$variant, interactors$interactors, sep = ':'),
+	paste( X$`predictor:rsid`, X$`outcome:rsid`, sep = ':' )
+)
+
+X$col = 'black'
+X$col[ interactors$index ] = 'red'
+X$true_beta = 0
+X$true_beta[ interactors$index ] = interactors$beta
+X$fit_beta = X$`model_1:beta_1:add/gp=1`
+X$fit_beta_lower = X$fit_beta - 1.96 * X$`model_1:se_1`
+X$fit_beta_upper = X$fit_beta + 1.96 * X$`model_1:se_1`
+
+X = X[ order( X$`model_1:log10_bf`, decreasing = T ), ]
+
+par( mfrow = c( 2, 3 ))
+plot( X$true_beta, X$fit_beta, pch = 19, cex = 0.75, col = X$col )
+abline( a = 0, b = 1, col = 'red' )
+segments( x0 = X$true_beta, x1 = X$true_beta, y0 = X$fit_beta_lower, y1 = X$fit_beta_upper, col = 'grey' )
+legend(
+	"bottomright",
+	legend = c( "beta = 0", "|beta| != 0" ),
+	pch = 19,
+	col = c( "black", "red" )
+)
+
+## ROC curve
+plot(
+	cumsum( X$true_beta == 0 ) / nrow(X), cumsum( X$true_beta != 0 ) / sum( X$true_beta != 0.0 ),
+	type = 'l',
+	xlab = "False positive rate",
+	ylab = "True positive rate"
+)
+points(
+	cumsum( X$true_beta == 0 ) / nrow(X), cumsum( abs( X$true_beta ) > 0.2 ) / sum( abs( X$true_beta ) > 0.2 ),
+	type = 'l',
+	col = 'grey'
+)
+points(
+	cumsum( X$true_beta == 0 ) / nrow(X), cumsum( abs( X$true_beta ) > 0.5 ) / sum( abs( X$true_beta ) > 0.5 ),
+	type = 'l',
+	col = 'blue'
+)
+legend(
+	"bottomright",
+	legend = c( "beta!=0", "|beta| > 0.2", "|beta| > 0.5" ),
+	pch = 19,
+	col = c( "black", "grey", "blue" )
+)
+abline( a = 0, b = 1, col = 'red' )
+
+### Compute rates
+quantiles = c( 0.01, 0.025, 0.05 )
+rates = data.frame(
+	quantile = quantiles,
+	rate = sapply(
+		quantiles,
+		function(q) {
+			length( which( ( abs( X$fit_beta - X$true_beta ) / X$`model_1:se_1` ) > qnorm( 1 - (q/2) ))) / nrow(X)
+		}
+	)
+)
+
+x = seq( from = -5, to = 5, by = 0.01 )
+plot( x, dnmixture( x ), type = 'l', lty = 2, col = 'black' )
+points( x, dnmixture( x, sds = c( 0.2, 0.4, 0.6, 0.8 ), alphas = rep( 0.25, 4 ) ), type = 'l', lty = 2, col = 'grey' )
+points( x, dnmixture( x, sds = c( 0.2 ), alphas = 1 ), type = 'l', lty = 2, col = 'green' )
+
+points( x, dlogf( x, 16, 16 ), type = 'l', col = 'black' )
+points( x, dlogf( x, 32, 32 ), type = 'l', col = 'red' )
+points( x, dlogf( x, 64, 64 ), type = 'l', col = 'blue' )
+
+plot( x, dlogf( x, 4, 4 ), type = 'l', col = 'blue' )
+points( x, dlogf( x, 1, 1 ), type = 'l', col = 'black' )
+points( x, dlogf( x, 2, 2 ), type = 'l', col = 'red' )
+
+hist( X$`model_1:iterations`, 100 )

ADDED   R/simulate/R/simulate_host_para.R
Index: R/simulate/R/simulate_host_para.R
==================================================================
--- R/simulate/R/simulate_host_para.R
+++ R/simulate/R/simulate_host_para.R
@@ -0,0 +1,249 @@
+library( argparse )
+parser <- ArgumentParser( description = 'Generate and test snp and samples stats for randomly generated genotype files')
+parser$add_argument(
+	"--samples",
+	type = "integer",
+	nargs = 1,
+	help = "Number of samples to simulate",
+	default = 1000
+)
+parser$add_argument(
+	"--variants",
+	type = "integer",
+	nargs = 1,
+	help = "Number of variants to simulate",
+	default = 200
+)
+parser$add_argument(
+	"--interactors",
+	type = "integer",
+	nargs = 1,
+	help = "Number of interactions to include in simulation",
+	default = 100
+)
+parser$add_argument(
+	"--fakehomozygotes",
+	action = 'store_true',
+	default = FALSE,
+	help = "Sample 1 allele for each parasite then report as homozygous"
+)
+parser$add_argument(
+	"--tag",
+	type = "character",
+	nargs = 1,
+	help = "Tag to add to filename"
+)
+parser$add_argument(
+	"--covariates",
+	type = "integer",
+	nargs = 1,
+	help = "Number of (std normal) covariates",
+	default = 0
+)
+opts = parser$parse_args()
+
+N = opts$samples
+L = opts$variants
+
+host = matrix( NA, nrow = L, ncol = N )
+covariates = matrix( rnorm( N*opts$covariates ), nrow = N, ncol = opts$covariates )
+covariate.betas = matrix( rnorm( opts$covariates*L, mean = 0, sd = 1 ), byrow = T, nrow = L, ncol = ncol( covariates ))
+covariate.host.betas = covariate.betas
+for( i in 1:nrow( covariate.betas )) {
+	# Simulate confounding by having effect of covariate on host as well
+	x = rbeta( 1, shape2 = 1, shape1 = 20 )
+	covariate.host.betas[i,] = ( covariate.host.betas[1,] * x )
+}
+colnames( covariate.betas ) = sprintf( "cov%d.beta", 1:ncol( covariates ))
+para = matrix( NA, nrow = L, ncol = N )
+
+# Simulate host genotypes
+# Frequency of the b allle
+fHost = rbeta( L, shape1 = 1, shape2 = 10 )
+
+# Frequency in host = 0 parasites
+fParaH0 = rbeta( L, shape1 = 1, shape2 = 10 )
+
+interactions = list(
+	host = 1:L,
+	para = 1:L
+)
+
+simulate <- function( N, f.baseline, spec, size = 2 ) {
+	logodds.baseline = log( f.baseline / ( 1 - f.baseline ))
+	x = rep( logodds.baseline, N ) ;
+	for( i in 1:length( spec )) {
+		x = x + spec[[i]]$value * spec[[i]]$beta
+	}
+	f = exp( x ) / ( 1 + exp( x ))
+	sapply( f, function(p) { rbinom( 1, prob = p, size = size ) } )
+}
+
+host.spec = data.frame()
+parasite.spec = data.frame()
+for( i in 1:L ) {
+	host.covariate.spec = lapply( 1:ncol( covariates ), function(j) { list( beta = covariate.host.betas[i,j], value = covariates[,j] ) } )
+	host[i,] = simulate( N, fHost[i], host.covariate.spec )
+	para.covariate.spec = lapply( 1:ncol( covariates ), function(j) { list( beta = covariate.betas[i,j], value = covariates[,j] ) } )
+	if( opts$fakehomozygotes ) {
+		para[i,] = simulate(
+			N, fParaH0[i], para.covariate.spec, size = 1
+		) * 2
+	} else {
+		para[i,] = simulate(
+			N, fParaH0[i], para.covariate.spec, size = 2
+		)
+	}
+	host.spec = rbind(
+		host.spec,
+		data.frame(
+			variant = sprintf( "H%d", i ),
+			frequency = fHost[i],
+			interactors = NA,
+			beta = NA
+		)
+	)
+	parasite.spec = rbind(
+		parasite.spec,
+		data.frame(
+			variant = sprintf( "P%d", i ),
+			frequency = fParaH0[i],
+			interactors = NA
+		)
+	)
+}
+host.spec = cbind( host.spec, covariate.betas )
+for( i in 1:opts$interactors ) {
+	host.i = interactions$host[i]
+	para.i = interactions$para[i]
+	beta = rnorm( 1, mean = 0, sd = 1 )
+	predictor.spec = c(
+		list( list( beta = beta, value = host[host.i,] )),
+		lapply( 1:ncol( covariates ), function(j) { list( beta = covariate.betas[para.i,j], value = covariates[,j] ) } )
+	)
+	if( opts$fakehomozygotes ) {
+		para[para.i,] = simulate(
+			N, fParaH0[para.i], predictor.spec, size = 1
+		) * 2
+	} else {
+		para[para.i,] = simulate(
+			N, fParaH0[para.i], predictor.spec, size = 2
+		)
+	}
+	host.spec[host.i,]$interactors = sprintf( "P%d", para.i )
+	host.spec[host.i,]$beta = beta
+	parasite.spec[para.i,]$interactors = sprintf( "H%d", host.i )
+}
+
+colnames( host ) = sprintf( "sample_%d", 1:N )
+colnames( para ) = sprintf( "sample_%d", 1:N )
+
+# Add sporatdic missingness to both host and parasite
+para[ sample( 1:(nrow(para) * ncol(para)), nrow(para) * ncol(para) * 0.01 ) ] = "./."
+host[ sample( 1:(nrow(host) * ncol(host)), nrow(para) * ncol(para) * 0.01 ) ] = "./."
+
+samples = cbind(
+	data.frame(
+		ID = c( sprintf( "sample_%d", 1:N ))
+	),
+	covariates
+)
+if( ncol( covariates ) > 0 ) {
+	colnames( samples ) = c( "ID", sprintf( "cov%d", 1:ncol( covariates )))
+}
+
+write.vcf <- function(
+	samples,
+	variants,
+	genotypes,
+	filename
+) {
+	cat( "##fileformat=VCFv4.2\n", file = filename )
+	cat( "##FORMAT=<ID=GT,Type=String,Number=1,Description=\"Genotype\">\n", file = filename, append = T )
+	cat(
+		sprintf(
+			"#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO\tFORMAT\t%s\n",
+			paste( samples, collapse = "\t" )
+		),
+		file = filename,
+		append = T
+	)
+	mode( genotypes ) = "character"
+	genotypes[ which(genotypes == 0) ] = "0/0"
+	genotypes[ which(genotypes == 1) ] = "0/1"
+	genotypes[ which(genotypes == 2) ] = "1/1"
+	write.table(
+		cbind(
+			data.frame(
+				CHROM = variants$chromosome,
+				POS = variants$position,
+				ID = variants$rsid,
+				REF = variants$alleleA,
+				ALT = variants$alleleB,
+				QUAL = ".",
+				FILTER = ".",
+				INFO = ".",
+				FORMAT = "GT"
+			),
+			genotypes
+		),
+		file = filename,
+		append = T,
+		col.names = F,
+		row.names = F,
+		quote = F,
+		sep = "\t"
+	)
+}
+
+if( is.null( opts$tag )) {
+	tag = ""
+} else {
+	tag = sprintf( ".%s", opts$tag )
+}
+
+
+write.vcf(
+	samples = samples$ID,
+	variants = data.frame(
+		chromosome = "H1",
+		SNPID = sprintf( "H%d", 1:L ),
+		rsid = sprintf( "H%d", 1:L ),
+		position = 1:L,
+		alleleA = "A",
+		alleleB = "G"
+	),
+	host,
+	sprintf( "host%s.vcf", tag )
+)
+
+write.vcf(
+	samples = samples$ID,
+	variants = data.frame(
+		chromosome = "P1",
+		SNPID = sprintf( "P%d", 1:L ),
+		rsid = sprintf( "P%d", 1:L ),
+		position = 1:L,
+		alleleA = "C",
+		alleleB = "T"
+	),
+	para,
+	sprintf( "parasite%s.vcf", tag )
+)
+
+write( colnames( samples ), file = sprintf( "samples%s.sample", tag ), ncol = ncol( samples ) )
+colnames( samples )[1] = "0"
+if( ncol( samples ) > 1 ) {
+	colnames( samples )[2:ncol( samples )] = "C"
+}
+write.table(
+	samples,
+	file = sprintf( "samples%s.sample", tag ),
+	row.names = F,
+	col.names = T,
+	quote = F,
+	append = T
+)
+
+write.table( host.spec, file = sprintf( 'host_spec%s.txt', tag ), col.names = T, row.names = F, quote = F )
+write.table( parasite.spec, file = sprintf( 'parasite_spec%s.txt', tag ), col.names = T, row.names = F, quote = F )

ADDED   R/simulate/R/simulation.R
Index: R/simulate/R/simulation.R
==================================================================
--- R/simulate/R/simulation.R
+++ R/simulate/R/simulation.R
@@ -0,0 +1,601 @@
+library( RSQLite )
+qqplot <- function( ps, plot.new = TRUE, limit = 50, CI = 0.95, thin = TRUE, ... ) {
+    cat( "Sorting p-values...\n" )
+    ps = sort(ps)
+    lambda = -log10( median( ps ) )
+    lambda = lambda / -log10( 0.5 )
+
+    cat( "Converting to log10 scale...\n" )
+    qs = -log10( ps )
+    expected = (1:length(ps))/(length(ps)+1)
+    expected = -log10( expected )
+
+    cat( "Computing quantiles...\n" )
+    lower.quantile = qbeta( 1-(1-CI)/2, (1:length(ps)), length(ps):1 )
+    upper.quantile = qbeta( (1-CI)/2, (1:length(ps)), length(ps):1 )
+    lower.quantile = -log10( lower.quantile )
+    upper.quantile = -log10( upper.quantile )
+    # We're not much interested in anything that lies near the diagonal line.  So don't plot them.
+    cat( "Thinning...\n" )
+    if( thin ) {
+        wDiag = which( abs( qs - expected ) < 0.1 & qs < 5 )
+        wNotDiag = which( qs >= 5 | abs( qs - expected ) >= 0.1 )
+        wDiag = sample( wDiag, min( 10000, length( wDiag ) ))
+        o = order( qs[ c( wDiag, wNotDiag )] )
+        qs = qs[ c( wDiag, wNotDiag ) ][o]
+        expected = expected[ c( wDiag, wNotDiag ) ][o]
+        lower.quantile = lower.quantile[ c( wDiag, wNotDiag ) ][o]
+        upper.quantile = upper.quantile[ c( wDiag, wNotDiag ) ][o]
+    }
+    cat( "Plotting...\n" )
+    pch = rep( 46, length( qs )) # = '.'
+    pch[ which( qs > upper.quantile | qs < lower.quantile )] = 1
+    if( plot.new ) {
+        plot( pmin( expected, limit ), pmin( qs, limit ), pch = pch, ... )
+        points( pmin( expected, limit ), pmin( lower.quantile, limit ), type = 'l', lty = 2 )
+        points( pmin( expected, limit ), pmin( upper.quantile, limit ), type = 'l', lty = 2 )
+    } else {
+        points( pmin( expected, limit ), pmin( qs, limit ), pch = pch, ... )
+        points( pmin( expected, limit ), pmin( lower.quantile, limit ), type = 'l', lty = 2 )
+        points( pmin( expected, limit ), pmin( upper.quantile, limit ), type = 'l', lty = 2 )
+    }
+    abline( a = 0, b = 1, col = "red")
+    return( lambda )
+}
+
+prob.phenotype.given.genotype <- function(
+	mu,
+	genotypes,
+	genotype.levels,
+	effect.sizes,
+	pcs = NULL,
+	pc.effects = NULL
+) {
+	# If there are N phenotypes, mu has length N and effect.sizes has length 2N
+	# First N are additive effects, followed by heterozygote effects.
+	
+	# If there are d pcs, pc.effects is a dxN matrix with pc effects for each outcome.
+	stopifnot( length( effect.sizes ) == 2 * length( mu ))
+	result = matrix( nrow = length( genotypes ), ncol = length( mu ) )
+	for( i in 1:length( mu )) {
+		predictor = (
+			mu[i]
+			+ ( effect.sizes[i] * genotype.levels[ genotypes + 1 ] )
+			+ ( effect.sizes[i + length(mu) ] * ( genotypes == 1 ) )
+		)
+		if( !is.null( pcs )) {
+			predictor = predictor + ( pcs %*% pc.effects )
+		}
+		result[,i] = exp( predictor )
+	}
+	for( i in 1:nrow( result )) {
+		result[i,] = result[i,] / sum( result[i,] ) ;
+	}
+	return( result )
+}
+
+prob.genotype.given.phenotype <- function( phenotypes, mu, effect.sizes, population.frequencies, pcs = NULL, pc.effects = NULL, verbose = FALSE ) {
+#	P( G | D ) = P( D | G ) P( G ), normalised by P(D) = sum of the top half.
+	stopifnot( length( effect.sizes ) == 2 * length( mu ) )
+	stopifnot( length( population.frequencies ) == 3 )
+	N = length( phenotypes )
+	# Make an indexing matrix
+	phenotypes = matrix( c( 1:N, phenotypes ), ncol = 2 )
+	# Make the result
+	result = matrix( NA, nrow = N, ncol = 3 )
+	# mean genotype
+	mean.genotype = population.frequencies[2] + 2 * population.frequencies[3]
+	genotype.levels = 0:2 - mean.genotype
+	# Make phenotypes into an indexing matrix.
+	for( g in 0:2 ) {
+		# Compute probability of each phenotype
+		x = prob.phenotype.given.genotype( mu, rep( g, N ), genotype.levels, effect.sizes, pcs, pc.effects ) ;
+		if( verbose ) {
+			print(x)
+			print( phenotypes )
+		}
+		# Compute probability of the given phenotype for each sample
+		x = x[ phenotypes ]
+		# Compute unnormalised probability of the genotype given phenotype
+		result[,g+1] = x * population.frequencies[g+1] ;
+	}
+#	print( result )
+	for( i in 1:nrow( result )) {
+		result[i,] = result[i,] / sum( result[i,] ) ;
+	}
+	return( result )
+}
+
+# mu[i] is the log-odds of phenotype i for an average genotype.
+# Let's put this pretty low for disease cases.
+
+numberOfSamples = 2000 # number of cases and number of controls
+phenotypes = c( "control", "case1", "case2", "case3" )
+phenotype = factor( sample( phenotypes, numberOfSamples, replace = T, prob = c( 0.5, 0.5/3, 0.5/3, 0.5/3) ), levels = phenotypes )
+
+numberOfNullSNPs = 1000
+numberOfEffectSNPs = 200
+numberOfSNPs = numberOfNullSNPs + numberOfEffectSNPs
+
+frequency = rbeta( numberOfSNPs, shape1 = 1.1, shape2 = 5 )
+pop.frequencies = matrix(
+	c( ( 1 - frequency )^2, 2 * frequency * ( 1 - frequency ), frequency^2 ),
+	nrow = numberOfSNPs,
+	ncol = 3
+)
+
+effect.size.scale = 0.5
+effect.sizes = matrix(
+	0,
+	nrow = numberOfEffectSNPs,
+	ncol = 2 * length( phenotypes ),
+	dimnames = list(
+		c( sprintf( "binomial%d", 1:100 ), sprintf( "multinomial%d", 1:100 ) ),
+		c( sprintf( "%s:add", phenotypes ), sprintf( "%s:het", phenotypes ))
+	)
+)
+# 100 SNPs that are case/control
+for( i in 1:100 ) {
+	w = 2:length(phenotypes)
+	effect = rbeta( 1, shape1 = 4, shape2 = 3 ) * effect.size.scale
+	effect.sizes[i,w] = effect
+	# 
+}
+# 5 of those have non-additive effects
+for( i in 95:100 ) {
+	wAdd = 1:length(phenotypes)
+	wHet = wAdd + length(phenotypes)
+	a = runif(1)
+	if( a < 0.3333 ) {
+		# dom model
+		effect.sizes[i,wHet] = effect.sizes[i,wAdd]
+	} else if( a < 0.66666 ) {
+		# dom model
+		effect.sizes[i,wHet] = -effect.sizes[i,wAdd]
+	} else {
+		# het model
+		effect.sizes[i,wHet] = effect.sizes[i,wAdd]
+		effect.sizes[i,wAdd] = 0
+	}
+}
+
+# 100 SNPs with independent effects
+for( i in 101:200 ) {
+	w = 2:length(phenotypes)
+	effect.sizes[i,w] = rbeta( length(phenotypes)-1, shape1 = 4, shape2 = 3 ) * effect.size.scale
+	a = runif( length( phenotypes ) - 1, -1, 1 )
+	effect.sizes[i,w] = effect.sizes[i,w] * sign( a )
+}
+# 5 of those have non-additive effects
+for( i in 195:200 ) {
+	wAdd = 1:length(phenotypes)
+	wHet = wAdd + length(phenotypes)
+	a = runif(1)
+	if( a < 0.3333 ) {
+		# dom model
+		effect.sizes[i,wHet] = effect.sizes[i,wAdd]
+	} else if( a < 0.66666 ) {
+		# dom model
+		effect.sizes[i,wHet] = -effect.sizes[i,wAdd]
+	} else {
+		# het model
+		effect.sizes[i,wHet] = effect.sizes[i,wAdd]
+		effect.sizes[i,wAdd] = 0
+	}
+}
+
+# 2000 NULL SNPs
+effect.sizes = rbind(
+	effect.sizes,
+	matrix( 0, nrow = numberOfNullSNPs, ncol = (2 * length( phenotypes )))
+)
+
+# simulate two principal components
+scale = 1.5
+pcs = matrix( NA, nrow = length( phenotype ), ncol = 2 )
+w = which( phenotype %in% c( "control" ))
+pcs[ w, 1 ] = rbeta( length( w ), shape1 = 2*scale, shape2 = 5*scale ) + rnorm( length(w), mean = 0, sd = 0.1 )
+pcs[ w, 2 ] = rbeta( length( w ), shape1 = 5*scale, shape2 = 2*scale ) + rnorm( length(w), mean = 0, sd = 0.1 )
+w = which( phenotype %in% c( "case1", "case2", "case3" ))
+pcs[ w, 1 ] = rbeta( w, shape1 = 5*scale, shape2 = 3*scale ) + rnorm( length(w), mean = 0, sd = 0.1 )
+w = which( phenotype %in% c( "case2" ))
+pcs[ w, 2 ] = rbeta( length( w ), shape1 = 4*scale, shape2 = 3*scale ) + rnorm( length(w), mean = 0, sd = 0.1 )
+w = which( phenotype %in% c( "case1", "case3" ))
+pcs[ w, 2 ] = rbeta( length( w ), shape1 = 2*scale, shape2 = 5*scale ) + rnorm( length(w), mean = 0, sd = 0.1 )
+dir.create( "images" )
+
+pdf( file = "images/pcs.pdf", width = 4, height = 4 )
+plot( pcs[,1], pcs[,2], col = phenotype, xlab = "PC 1", ylab = "PC 2", xlim = c( -0.2, 1.5 ), ylim = c( -0.2, 1.5 ) )
+legend( "topright", col = 1:length( phenotype ), legend = levels( phenotype ), pch = 19, bty = 'n' )
+dev.off()
+
+pc.effects = matrix( c( -0.3, 0.2 ), ncol = 1 )
+
+mu = c( 0, -3, -3, -3 )
+# Show the phenotype probs for each genotype:
+print( prob.phenotype.given.genotype( mu, 0, 0:2, c(0,0,0,0,0,0,0,0) ) ) 
+print( prob.genotype.given.phenotype( 1:length(phenotypes), mu, c(0,0,0,0,0,0,0,0), pop.frequencies[1,] ) )
+print( prob.genotype.given.phenotype( 1:length(phenotypes), mu, c(0,0,1,0,0,0,0,1), pop.frequencies[1,] ) )
+
+# Now simulate genotypes.
+G = matrix( NA, nrow = numberOfSNPs, ncol = numberOfSamples )
+for( i in 1:nrow(G) ) {
+	cat( i, "of", nrow(G), "...\n" )
+	p = prob.genotype.given.phenotype( phenotype, mu, effect.sizes[i,], pop.frequencies[i,], pcs, pc.effects )
+	genotypes = sapply( 1:numberOfSamples, function(i) { rmultinom( 1, 1, prob = p[i,] ) } )
+	G[i,] = sapply( 1:ncol( genotypes ), function(i) { which( genotypes[,i] == 1 ) } ) - 1
+}
+sample.frequency = rowSums( G ) / ( 2 * ncol(G) )
+plot( sample.frequency, frequency, xlim = c( 0, 1 ), ylim = c( 0, 1 ), col = ( rowSums( effect.sizes ) > 0 ) + 1 )
+
+
+######################################
+# Shall we do a quick check?
+# First 100 are case/cnotrol
+library( nnet )
+g = glm( as.integer( phenotype != "control" ) ~ G[2,] + pcs, family="binomial"); summary(g)$coeff
+g = multinom( phenotype ~ as.factor( G[1,] ) + pcs ); summary(g)
+g = multinom( phenotype ~ G[101,] ); summary(g)
+g = multinom( phenotype ~ G[201,] ); summary(g)
+
+
+######################################
+# Write a sample file and a vcf file
+dir.create( "data" )
+version = "v3"
+output.file = sprintf( "data/test_data_%s.vcf", version )
+sample.filename = sprintf( "data/test_data_%s.sample", version )
+samples = data.frame(
+	ID_1 = sprintf( "sample_%d", 1:ncol( vcf )),
+	ID_2 = sprintf( "sample_%d", 1:ncol( vcf )),
+	missing = 0,
+	case = as.integer( phenotype != 'control' ),
+	sub = phenotype,
+	pc1 = pcs[,1],
+	pc2 = pcs[,1]
+)
+
+write( colnames( samples ), sample.filename, ncolumns = 7 )
+write( c( 0, 0, 0, 'B', 'D', 'C', 'C' ), sample.filename, ncolumns = 7, append = T )
+write.table( samples, file = sample.filename, col.names = F, row.names = F, quote = F, append = T )
+
+# Write a VCF file with the results...
+vcf = G
+mode( vcf ) = "character"
+vcf[ which( G == 0 )] = '0/0'
+vcf[ which( G == 1 )] = '0/1'
+vcf[ which( G == 2 )] = '1/1'
+
+colnames( vcf ) = sprintf( "sample_%d", 1:ncol( vcf ))
+
+variants = data.frame(
+	CHROM = '22',
+	POS = 1:numberOfSNPs,
+	ID = c( sprintf( "binomial%d", 1:94 ), sprintf( "binomial%d_nonadd", 95:100 ), sprintf( "multinomial%d", 1:94 ), sprintf( "multinomial_nonadd%d", 95:100 ), sprintf( "null%d", 1:numberOfNullSNPs ) ),
+	REF = 'A',
+	ALT = 'G',
+	QUAL = '.',
+	FILTER = '.',
+	INFO = '.',
+	FORMAT = 'GT'
+)
+write( "##fileformat=VCFv4.1", output.file )
+write( "##FORMAT=<ID=GT,Number=1,Type=String,Description=\"Genotype calls\">", output.file, append = T )
+write.table( cbind( variants, vcf ), file = output.file, quote = F, append = T, col.names = T, row.names = F, sep = "\t" )
+
+######################################
+# Run SNPTEST
+dir.create( 'scans' )
+system(
+	paste(
+		'snptest_v2.6-dev -data data/test_data_v3.vcf data/test_data_v3.sample -genotype_field GT',
+		'-cov_names pc1 pc2',
+		'-method newml -frequentist add -pheno case',
+		'-o scans/test_data_case_v3.snptest',
+		'-max_iterations 100'
+	)
+)
+system(
+	paste(
+		'snptest_v2.6-dev -data data/test_data_v3.vcf data/test_data_v3.sample -genotype_field GT',
+		'-cov_names pc1 pc2',
+		'-method newml -frequentist add -pheno case',
+		'-full_parameter_estimates -o scans/test_data_case_v3_full.snptest',
+		'-max_iterations 100'
+	)
+)
+
+system(
+	paste(
+		'snptest_v2.6-dev -data data/test_data_v3.vcf data/test_data_v3.sample -genotype_field GT',
+		'-cov_names pc1 pc2',
+		'-method newml -frequentist add -pheno sub',
+		'-baseline_phenotype control -o scans/test_data_sub_v3.snptest',
+		'-max_iterations 100'
+	)
+)
+
+system(
+	paste(
+		'snptest_v2.6-dev -data data/test_data_v3.vcf data/test_data_v3.sample -genotype_field GT',
+		'-cov_names pc1 pc2',
+		'-method newml -frequentist gen -pheno sub ',
+		'-baseline_phenotype control -o scans/test_data_sub_gen_v3.snptest',
+		'-max_iterations 100'
+	)
+)
+
+system(
+	paste(
+		'snptest_v2.6-dev -data data/test_data_v3.vcf data/test_data_v3.sample -genotype_field GT',
+		'-cov_names pc1 pc2',
+		'-method newml -frequentist gen -pheno sub ',
+		'-baseline_phenotype control',
+		'-o /tmp/snptest.out',
+		'-max_iterations 100',
+		'-debug',
+		'-snpid binomial1'
+	)
+)
+
+######################################
+# Run Bingwa
+
+dir.create( 'meta' )
+file.remove( 'meta/test_data_v3.sqlite' )
+system(
+	paste(
+		'bingwa_v2.0-dev -data scans/test_data_case_v3.snptest',
+		'-cohort-names test',
+		'-define-sd-set .=0.2,0.75,1',
+		'-simple-prior rho=1/sd=[.]',
+		'-simple-prior-name fix-add',
+		'-o meta/test_data_v3.sqlite',
+		'-analysis-name case',
+		'-table-name CC',
+		'-extra-columns comment'
+	)
+)
+
+system(
+	paste(
+		'bingwa_v2.0-dev -data scans/test_data_sub_v3.snptest',
+		'-cohort-names test',
+		'-define-sd-set .=0.2,0.75,1',
+		'-simple-prior rho=1/sd=[.],[.],[.]/cor=1,1,1',
+		'-simple-prior rho=1/sd=[.],[.],[.]/cor=0,0,0',
+		'-simple-prior-name fix-add',
+		'-simple-prior-name ind-add',
+		'-o meta/test_data_v3.sqlite',
+		'-analysis-name "sub:add"',
+		'-table-name subAdd',
+		'-extra-columns comment'
+	)
+)
+
+
+# add 1 0 1 0 1 0
+# het   1 0 1 0 1
+# add     1 0 1 0
+# het       1 0 1
+# add         1 0
+# het           1
+system(
+	paste(
+		'bingwa_v2.0-dev -data scans/test_data_sub_gen_v3.snptest',
+		'-cohort-names test',
+		'-define-sd-set .=0.2,0.75,1',
+		'-simple-prior rho=1/sd=[.],0.01,[.],0.01,[.],0.01/cor=0,1,0,1,0,0,1,0,1,0,1,0,0,1,0',
+		'-simple-prior-name fix-add',
+		'-simple-prior rho=1/sd=[.],0.01,[.],0.01,[.],0.01/cor=0,0,0,0,0,0,0,0,0,0,0,0,0,0,0',
+		'-simple-prior-name ind-add',
+		'-simple-prior rho=1/sd=[.],[.],[.],[.],[.],[.]/cor=0,1,0,1,0,0,1,0,1,0,1,0,0,1,0',
+		'-simple-prior-name fix-gen',
+		'-simple-prior rho=1/sd=[.],[.],[.],[.],[.],[.]/cor=0,0,0,0,0,0,0,0,0,0,0,0,0,0,0',
+		'-simple-prior-name ind-gen',
+		'-o meta/test_data_v3.sqlite',
+		'-analysis-name "sub:gen"',
+		'-table-name subGen3',
+		'-extra-columns comment'
+		
+	)
+)
+
+######################################
+# Look at results
+db = dbConnect( dbDriver( "SQLite" ), "meta/test_data_v3.sqlite" )
+D = dbGetQuery(
+	db,
+	paste(
+		'SELECT CC.rsid AS rsid, CC."test:B_allele_frequency" AS B_allele_frequency,',
+		'CC."FixedEffect:pvalue" AS CC_meta_pvalue,',
+		'"Bayesian:fix-add/sd=0.2/cor=:bf" AS CC_fix_add_small,',
+		'"Bayesian:fix-add/sd=0.75/cor=:bf" AS CC_fix_add_medium,',
+		'"Bayesian:fix-add/sd=1/cor=:bf" AS CC_fix_add_large,',
+		'CC."test:comment" AS CC_comment,',
+		'"Bayesian:fix-add/sd=0.2,0.2,0.2/cor=1,1,1:bf" AS SA_fix_add_small,',
+		'"Bayesian:fix-add/sd=0.75,0.75,0.75/cor=1,1,1:bf" AS SA_fix_add_medium,',
+		'"Bayesian:fix-add/sd=0.75,0.75,0.75/cor=1,1,1:bf" AS SA_fix_add_large,',
+		'"Bayesian:ind-add/sd=0.2,0.2,0.2/cor=0,0,0:bf" AS SA_ind_add_small,',
+		'"Bayesian:ind-add/sd=0.75,0.75,0.75/cor=0,0,0:bf" AS SA_ind_add_medium,',
+		'"Bayesian:ind-add/sd=1,1,1/cor=0,0,0:bf" AS SA_ind_add_large,',
+		'SA."test:comment" AS SA_comment,',
+		'"Bayesian:fix-add/sd=0.2,0.01,0.2,0.01,0.2,0.01/cor=0,1,0,1,0,0,1,0,1,0,1,0,0,1,0:bf" AS SG_fix_add_small,',
+		'"Bayesian:fix-add/sd=0.75,0.01,0.75,0.01,0.75,0.01/cor=0,1,0,1,0,0,1,0,1,0,1,0,0,1,0:bf" AS SG_fix_add_medium,',
+		'"Bayesian:fix-add/sd=1,0.01,1,0.01,1,0.01/cor=0,1,0,1,0,0,1,0,1,0,1,0,0,1,0:bf" AS SG_fix_add_large,',
+		'"Bayesian:ind-add/sd=0.2,0.01,0.2,0.01,0.2,0.01/cor=0,0,0,0,0,0,0,0,0,0,0,0,0,0,0:bf" AS SG_ind_add_small,',
+		'"Bayesian:ind-add/sd=0.75,0.01,0.75,0.01,0.75,0.01/cor=0,0,0,0,0,0,0,0,0,0,0,0,0,0,0:bf" AS SG_ind_add_medium,',
+		'"Bayesian:ind-add/sd=1,0.01,1,0.01,1,0.01/cor=0,0,0,0,0,0,0,0,0,0,0,0,0,0,0:bf" AS SG_ind_add_large,',
+		'"Bayesian:fix-gen/sd=0.2,0.2,0.2,0.2,0.2,0.2/cor=0,1,0,1,0,0,1,0,1,0,1,0,0,1,0:bf" AS SG_fix_gen_small,',
+		'"Bayesian:fix-gen/sd=0.75,0.75,0.75,0.75,0.75,0.75/cor=0,1,0,1,0,0,1,0,1,0,1,0,0,1,0:bf" AS SG_fix_gen_medium,',
+		'"Bayesian:fix-gen/sd=1,1,1,1,1,1/cor=0,1,0,1,0,0,1,0,1,0,1,0,0,1,0:bf" AS SG_fix_gen_large,',
+		'"Bayesian:ind-gen/sd=0.2,0.2,0.2,0.2,0.2,0.2/cor=0,0,0,0,0,0,0,0,0,0,0,0,0,0,0:bf" AS SG_ind_gen_small,',
+		'"Bayesian:ind-gen/sd=0.75,0.75,0.75,0.75,0.75,0.75/cor=0,0,0,0,0,0,0,0,0,0,0,0,0,0,0:bf" AS SG_ind_gen_medium,',
+		'"Bayesian:ind-gen/sd=1,1,1,1,1,1/cor=0,0,0,0,0,0,0,0,0,0,0,0,0,0,0:bf" AS SG_ind_gen_large,',
+		'SG."test:comment" AS SG_comment',
+		'FROM CCView CC',
+		'INNER JOIN subAdd SA ON SA.variant_id == CC.variant_id',
+		'INNER JOIN subGen3 SG ON SG.variant_id == CC.variant_id'
+	)
+)
+
+D$CC_fix_add = ( D$CC_fix_add_small + D$CC_fix_add_medium + D$CC_fix_add_large ) / 3
+D$SA_fix_add = ( D$SA_fix_add_small + D$SA_fix_add_medium + D$SA_fix_add_large ) / 3
+D$SA_ind_add = ( D$SA_ind_add_small + D$SA_ind_add_medium + D$SA_ind_add_large ) / 3
+D$SG_fix_add = ( D$SG_fix_add_small + D$SG_fix_add_medium + D$SG_fix_add_large ) / 3
+D$SG_fix_gen = ( D$SG_fix_gen_small + D$SG_fix_gen_medium + D$SG_fix_gen_large ) / 3
+D$SG_ind_add = ( D$SG_ind_add_small + D$SG_ind_add_medium + D$SG_ind_add_large ) / 3
+D$SG_ind_gen = ( D$SG_ind_gen_small + D$SG_ind_gen_medium + D$SG_ind_gen_large ) / 3
+
+D$CC_mean_bf = D$CC_fix_add
+D$SA_mean_bf = 0.8 * D$SA_fix_add + 0.2 * D$SA_ind_add
+D$SG_mean_bf = 0.8 * D$SG_fix_add + 0.2 * D$SG_ind_add
+D$SG_mean_bf = 0.8^2* D$SG_fix_add + 0.8*0.2 * D$SG_fix_gen + 0.2 * 0.8 * D$SG_ind_add + 0.2^2 * D$SG_ind_gen
+
+D$maf = D$B_allele_frequency
+D$maf = pmin( D$maf, 1 - D$maf )
+D$maf_cut = cut( D$maf, breaks = c( 0, 0.1, 0.2, 0.3, 0.4, 0.5 ))
+shapes = c( 1, 3, 4, 8 )
+model.names = c( "null", "additive; case/control", "additive non case/control", "general" )
+pch = rep( shapes[1], nrow(D) )
+pch[ grep( "binomial", D$rsid ) ] = shapes[2]
+pch[ grep( "multinomial", D$rsid ) ] = shapes[3]
+pch[ grep( "nonadd", D$rsid ) ] = shapes[4]
+
+pdf( file = "images/qqplot.pdf", width = 4, height = 4, xlab = "Exptected -log10( P-value )", ylab = "Observed -log10( P-value )" )
+qqplot( D$CC_meta_pvalue[ grep( "null", D$rsid )], )
+dev.off()
+
+#
+mar = c( 4, 5, 2, 2 )
+width = 6
+height = 5
+pdf( file = "images/fixed_effect_pvalue_comparison.pdf", width = width, height = height )
+par( mar = mar )
+plot( log10( D$CC_fix_add ), -log10( D$CC_meta_pvalue ), col = D$maf_cut, pch = pch,
+	xlab = "log10( fixed effect Bayes factor )",
+	ylab = "-log10( Wald p-value )"
+)
+legend( "bottomright", col = 1:length( levels( D$maf_cut )), legend = levels( D$maf_cut ), pch = 19 )
+legend( "topleft", legend = model.names, pch = shapes )
+dev.off()
+
+pdf( file = "images/fixed_effect_pvalue_comparison_zoom.pdf", width = width, height = height )
+par( mar = mar )
+plot( log10( D$CC_fix_add ), -log10( D$CC_meta_pvalue ), col = D$maf_cut, pch = pch, xlim = c( -1, 2 ), ylim = c( 0, 3 ),
+	xlab = "log10( case/control Bayes factor )",
+	ylab = "-log10( case/control Wald p-value )"
+)
+legend( "bottomright", col = 1:length( levels( D$maf_cut )), legend = levels( D$maf_cut ), pch = 19 )
+legend( "topleft", legend = model.names, pch = shapes )
+dev.off()
+
+pdf( file = "images/cc_fix_add_vs_sa_fix_add.pdf", width = width, height = height )
+par( mar = mar )
+plot( log10( D$CC_fix_add ), log10( D$SA_fix_add ), col = D$maf_cut, pch = pch,
+	xlab = "log10( additive c/c BF )\n(logit model)",
+	ylab = "log10( additive c/c BF )\n(multinomial model)"
+)
+abline( a = 0, b = 1, col = 'red' )
+legend( "bottomright", col = 1:length( levels( D$maf_cut )), legend = levels( D$maf_cut ), pch = 19 )
+legend( "topleft", legend = model.names, pch = shapes )
+dev.off()
+
+w = 1:nrow(D); #which( D$SG_comment == 'NA' )
+pdf( file = "images/cc_fix_add_vs_sg_fix_add.pdf", width = width, height = height )
+par( mar = mar )
+plot( log10( D$CC_fix_add[w] ), log10( D$SG_fix_add[w] ), col = D$maf_cut[w], pch = pch[w],
+xlab = "log10( additive c/c BF )\n(logit model)",
+ylab = "log10( additive c/c BF )\n(general multinomial model)"
+)
+abline( a = 0, b = 1, col = 'red' )
+legend( "bottomright", col = 1:length( levels( D$maf_cut )), legend = levels( D$maf_cut ), pch = 19 )
+legend( "topleft", legend = model.names, pch = shapes )
+dev.off()
+
+w = 1:nrow(D); #which( D$SG_comment == 'NA' )
+pdf( file = "images/cc_fix_add_vs_sg_fix_gen.pdf", width = width, height = height )
+par( mar = mar )
+plot( log10( D$CC_fix_add[w] ), log10( D$SG_fix_gen[w] ), col = D$maf_cut[w], pch = pch[w],
+xlab = "log10( additive c/c BF )\n(logit model)",
+ylab = "log10( general c/c BF )\n(general multinomial model)"
+)
+abline( a = 0, b = 1, col = 'red' )
+legend( "bottomright", col = 1:length( levels( D$maf_cut )), legend = levels( D$maf_cut ), pch = 19 )
+legend( "topleft", legend = model.names, pch = shapes )
+dev.off()
+
+w = 1:nrow(D); #which( D$SG_comment == 'NA' )
+pdf( file = "images/cc_fix_add_vs_sg_mean_bf.pdf", width = width, height = height )
+par( mar = mar )
+plot( log10( D$CC_fix_add[w] ), log10( D$SG_mean_bf[w] ), col = D$maf_cut[w], pch = pch[w],
+xlab = "log10( additive c/c BF )\n(logit model)",
+ylab = "log10( model-averaged BF )\n(general multinomial model)"
+)
+abline( a = 0, b = 1, col = 'red' )
+legend( "bottomright", col = 1:length( levels( D$maf_cut )), legend = levels( D$maf_cut ), pch = 19 )
+legend( "topright", legend = model.names, pch = shapes )
+dev.off()
+
+###############################################################
+# ROC curve
+w = which( !is.na( D$SG_mean_bf ) & D$SG_mean_bf != 0 )
+D2 = D[w, ]
+ROC.data = data.frame()
+D2 = D2[ order( D2$CC_mean_bf, decreasing = T ), ]
+ROC.data = rbind(
+	ROC.data,
+	data.frame(
+		method = "additive, case/control",
+		true.positive = cumsum( !1:nrow(D2) %in% grep( "null", D2$rsid )),
+		false.positive = cumsum( 1:nrow(D2) %in% grep( "null", D2$rsid ))
+	)
+)
+D2 = D2[ order( D2$SA_mean_bf, decreasing = T ), ]
+ROC.data = rbind(
+	ROC.data,
+	data.frame(
+		method = "additive, multinomial mean BF",
+		true.positive = cumsum( !1:nrow(D2) %in% grep( "null", D2$rsid )),
+		false.positive = cumsum( 1:nrow(D2) %in% grep( "null", D2$rsid ))
+	)
+)
+D2 = D2[ order( D2$SG_mean_bf, decreasing = T ), ]
+ROC.data = rbind(
+	ROC.data,
+	data.frame(
+		method = "general, multinomial mean BF",
+		true.positive = cumsum( !1:nrow(D2) %in% grep( "null", D2$rsid )),
+		false.positive = cumsum( 1:nrow(D2) %in% grep( "null", D2$rsid ))
+	)
+)
+
+pdf( file = "images/power.pdf", width = 8, height = 5 )
+( ggplot( data = ROC.data ) + geom_line( aes( x = false.positive, y = true.positive, col = method ))
++ xlab( "Number of false positives" )
++ ylab( "Number of true positives" )
++ theme_bw( 16 )
+)
+dev.off()
+
+
+
+###############################################################
+# plot effect sizes
+CC = dbGetQuery( db, "SELECT * FROM CCView" )
+SA = dbGetQuery( db, "SELECT * FROM SubAddView" )
+count = 1
+for( term in c( "add", "het" )) {
+	count = count + 1
+	for( case in c( "case1", "case2", "case3" )) {
+		effect.size.name = sprintf( "%s:%s", case, term )
+		estimate.name = sprintf( "test:beta_.*:%s/sub=%s", term, case )
+		if( count == 2 ) {
+			plot( E[, grep( estimate.name, colnames( E ) ) ], effect.sizes[, effect.size.name ], xlim = c( -0.5, 0.5 ), ylim = c( -0.5, 0.5 )  )
+		} else {
+			points( E[, grep( estimate.name, colnames( E ) ) ], effect.sizes[, effect.size.name ] )
+		}
+		count = count + 1
+	}
+}
+

Index: README.md
==================================================================
--- README.md
+++ README.md
@@ -1,22 +1,43 @@
 # qctool - README
-Copyright 2009-2016 Gavin Band, University of Oxford
+Copyright 2009-2021 Gavin Band
+
+This repository contains the source code for QCTOOL and a number of other command-line programs
+that manipulate gwas datasets and other genomic data. The repository is hosted [at code.enkre.net](https://code.enkre.net/qctool) and is also mirrored [on github](https://github.com/gavinband/qctool).  The programs included are:
 
-This package comprises the QCTOOL program for quality control of a set of SNP marker data,
-together with some other utility programs.  For full details see <http://www.well.ox.ac.uk/~gav/qctool_v2>.
+* [QCTOOL](http://www.well.ox.ac.uk/~gav/qctool), a program for manipulation and quality control of gwas datasets and other genome-wide data.  Read [the QCTOOL documentation](http://www.well.ox.ac.uk/~gav/qctool).
+* [Inthinnerator](http://www.well.ox.ac.uk/~gav/inthinnerator), a program for thinning genetic variants using a recombination map.  Read [the inthinnerator documentation](http://www.well.ox.ac.uk/~gav/inthinnerator).
+* [HPTEST](http://www.well.ox.ac.uk/~gav/hptest), a program for testing for association between host and parasite genotypes. Read the [HPTEST documentation](http://www.well.ox.ac.uk/~gav/hptest) for more details.
+* [LDBIRD](http://www.well.ox.ac.uk/~gav/ldbird), a program for computing LD metrics between all pairs of variants in a genomic region or across whole genomes.  Read the [LDBIRD documentation](http://www.well.ox.ac.uk/~gav/ldbird) for more details.
 
 ## Obtaining QCTOOL ##
 
-Basic instructions for obtaining and/or compiling QCTOOL can be found on the [QCTOOL download page](http://www.well.ox.ac.uk/~gav/qctool_v2/#download).  For further information, see the wiki page on [compiling QCTOOL](https://bitbucket.org/gavinband/qctool/wiki/Compiling%20QCTOOL).
+Basic instructions for obtaining and/or compiling this package can be found on the
+[QCTOOL download page](http://www.well.ox.ac.uk/~gav/qctool/documentation/download.html).
+For further information, see the wiki page on [compiling QCTOOL](/wiki/Compiling%20QCTOOL).
+
+## Reporting issues ##
+
+Issues should be reported on the [issue tracker](https://enkre.net/cgi-bin/code/qctool/rptview?rn=2).
+
+## License ##
+
+The QCTOOL package is copyright Gavin Band released under the [Boost software license](LICENSE_1_0.txt). QCTOOL uses
+code from 3rd party packages described below, that use their own licenses. These include the BSD License and the GNU
+General Public License. See the [respective folders for these packages](/dir?ci=tip&name=3rd_party) for details.
 
 ## Acknowledgements ##
 
 QCTOOL was written by Gavin Band, based on an initial design by Gavin Band and Jonathan Marchini.
 
+Inthinnerator, HPTEST, LDBIRD and all other included software was written by Gavin Band.
+
 QCTOOL gratefully makes use of functionality from the following projects:
 
-- zlib (http://zlib.net/)
+- zlib (<http://zlib.net/>)
 - the boost C++ libraries (<http://www.boost.org>)
 - sqlite3 (<http://www.sqlite.org>),
 - the Eigen library (<http://eigen.tuxfamily.org>)
-- the SNPHWE code from Wigginton et al (http://www.sph.umich.edu/csg/abecasis/Exact)
-- the Zstandard library(http://www.zstd.net).
+- the SNPHWE code from Wigginton et al (<http://www.sph.umich.edu/csg/abecasis/Exact>)
+- the Zstandard library(<http://www.zstd.net>).
+
+Quang Si Le contributed an implementation of the VCF format used for testing.

DELETED analysis/info.R
Index: analysis/info.R
==================================================================
--- analysis/info.R
+++ analysis/info.R
@@ -1,312 +0,0 @@
-info.strange <- function( genotypes ) {
-    I = sum( rowSums( genotypes ))
-    N = nrow( genotypes )
-    
-    return( I / N ) ;
-}
-
-info.original <- function( genotypes ) {
-    I = sum( rowSums( genotypes ))
-    if( I == 0 ) {
-        return( 0 ) ;
-    }
-    N = nrow( genotypes )
-    f = genotypes[, 2] + 4 * genotypes[, 3]
-    e = genotypes[, 2] + 2 * genotypes[, 3]
-    theta = sum(e) / (2*I)
-    if( theta == 0 || theta == 1 ) {
-        return( 1 )
-    }
-    ratio = sum( f-e^2 ) / ( 2*N*theta*(1-theta) )
-    return( 1 - ratio )
-}
-
-info.original.terms <- function( genotypes ) {
-    I = sum( rowSums( genotypes ))
-    if( I == 0 ) {
-        return( 0 ) ;
-    }
-    N = nrow( genotypes )
-    f = genotypes[, 2] + 4 * genotypes[, 3]
-    e = genotypes[, 2] + 2 * genotypes[, 3]
-    theta = sum(e) / (2*I)
-    ratio = sum( f-e^2 ) / ( 2*N*theta*(1-theta) )
-    return( list( info = 1 - ratio, variance.terms = sum( f-e^2 ), denominator = ( 2*N*theta*(1-theta) ) ))
-}
-
-info.variant1 <- function( genotypes ) {
-    I = sum( rowSums( genotypes ))
-    if( I == 0 ) {
-        return( 0 ) ;
-    }
-    N = nrow( genotypes )
-    f = genotypes[, 2] + 4 * genotypes[, 3]
-    e = genotypes[, 2] + 2 * genotypes[, 3]
-    adj1 = ( 1.0 - rowSums( genotypes ) ) * e
-    adj2 = ( 1.0 - rowSums( genotypes ) )^2
-
-    theta = sum(e) / (2*I)
-    if( theta == 0 || theta == 1 ) {
-        return( 1 )
-    }
-    ratio = sum( f-e^2 ) / ( 2*N*theta*(1-theta) )
-
-    numerator = sum( f - e^2 ) + (( N - I ) * ( 2 * theta * ( 1 + theta ))) - 4 * theta * sum( adj1 ) - 4 * theta^2 * sum( adj2 )
-    denominator = 2*N*theta*(1-theta)
-    return( 1 - ( numerator / denominator ))
-}
-
-info.variant1.terms <- function( genotypes ) {
-    I = sum( rowSums( genotypes ))
-    if( I == 0 ) {
-        return( 0 ) ;
-    }
-    N = nrow( genotypes )
-    f = genotypes[, 2] + 4 * genotypes[, 3]
-    e = genotypes[, 2] + 2 * genotypes[, 3]
-    adj1 = ( 1.0 - rowSums( genotypes ) ) * e
-    adj2 = ( 1.0 - rowSums( genotypes ) )^2
-
-    theta = sum(e) / (2*I)
-    ratio = sum( f-e^2 ) / ( 2*N*theta*(1-theta) )
-
-    numerator1 = sum( f - e^2 )
-    numerator2 = (( N - I ) * ( 2 * theta * ( 1 + theta ))) - 4 * theta * sum( adj1 ) - 4 * theta^2 * sum( adj2 )
-    numerator = numerator1 + numerator2
-    denominator = 2*N*theta*(1-theta)
-
-    return( list( info = 1 - ( numerator / denominator ), variance.terms = numerator1, covariance.terms = numerator2, denominator = denominator ))
-}
-
-info.variant2 <- function( g ) {
-    I = sum( g[, 1:3] )
-    if( I == 0 ) {
-        return( 0 ) ;
-    }
-    N = nrow( g )
-    e = g[,2] + 2*g[,3]
-    theta.hat = sum(e) / ( 2 * I )
-    if( theta.hat == 0 || theta.hat == 1 ) {
-        return( 1 )
-    }
-
-    vF0 = sum(g[,1]*(1-g[,1]))
-    vF1 = sum(g[,2]*(1-g[,2]))
-    vF2 = sum(g[,3]*(1-g[,3]))
-
-    c01 = -sum(g[,2]*g[,1])
-    c02 = -sum(g[,1]*g[,3])
-    c12 = -sum(g[,2]*g[,3])
-
-
-    numerator1 = ( 4 * (theta.hat^2) * vF0 ) + ((1-(2*theta.hat))^2 * vF1) + (4*(1-theta.hat)^2 * vF2)
-
-    numerator2 = - (4*theta.hat*(1-(2*theta.hat))*c01) + (4*(1-theta.hat)*(1-(2*theta.hat))*c12) - (8*theta.hat*(1-theta.hat)*c02)
-    numerator = numerator1 + numerator2
-    denominator = 2 * I * theta.hat * ( 1 - theta.hat )
-
-    #cat( "theta_mle =", theta.hat, "v0 =", vF0, "v1 =", vF1, "v2 =", vF2, "c01 =", c01, "c02 =", c02, "c12 =", c12, ".\n" )
-    #cat( "numerator1 =", numerator, "numerator2 =", numerator2, "numerator =", numerator, ".\n" )
-    return( 1.0 - ( numerator / denominator ) )
-}
-
-info.variant2.terms <- function( g ) {
-    I = sum( g[, 1:3] )
-    if( I == 0 ) {
-        return( 0 ) ;
-    }
-    N = nrow( g )
-    e = g[,2] + 2*g[,3]
-    theta.hat = sum(e) / ( 2 * I )
-
-    vF0 = sum(g[,1]*(1-g[,1]))
-    vF1 = sum(g[,2]*(1-g[,2]))
-    vF2 = sum(g[,3]*(1-g[,3]))
-
-    c01 = -sum(g[,2]*g[,1])
-    c02 = -sum(g[,1]*g[,3])
-    c12 = -sum(g[,2]*g[,3])
-
-
-    numerator1 = ( 4 * (theta.hat^2) * vF0 ) + ((1-(2*theta.hat))^2 * vF1) + (4*(1-theta.hat)^2 * vF2)
-
-    numerator2 = - (4*theta.hat*(1-(2*theta.hat))*c01) + (4*(1-theta.hat)*(1-(2*theta.hat))*c12) - (8*theta.hat*(1-theta.hat)*c02)
-    numerator = numerator1 + numerator2
-    denominator = 2 * I * theta.hat * ( 1 - theta.hat )
-    return( list( info = ( 1 - ( numerator / denominator )), variance.terms = numerator1, covariance.terms = numerator2, denominator = denominator ))
-}
-
-load.snp.stats <- function( filename, info_filename = NULL ) {
-    X = read.table( filename )
-    X$I = rowSums( X[, c( "AA", "AB", "BB" )])
-
-    if( !is.null( info_filename )) {
-        info = read.table( info_filename, as.is = T, header = F )
-        colnames( info )[c(1:3,7)] = c( "SNPID", "rsid", "position", "type" )
-        stopifnot( X$rsid == info$rsid )
-        X$type = info$type
-        X$type = factor( X$type, levels = c( 1, 2 ))
-        levels( X$type ) = c( "imputed", "genotyped" )
-    } else {
-        X$type = factor( "genotyped", levels = c( "imputed", "genotyped" ))
-    }
-
-    X = melt( X, measure.vars = c("information", "jonathans_information" ))
-    X$variable = as.character( X$variable )
-    X$variable[ which( X$variable == "information" )] = "info.variant1"
-    X$variable[ which( X$variable == "jonathans_information" )] = "info.variant2"
-    return( X )
-}
-
-library( ggplot2 )
-
-genotyped = load.snp.stats( "PS_01_illumina.snp-stats" )
-imputed = load.snp.stats( "PS.illumina.22.80.500.imputed.gz.snp-stats", "PS.illumina.22.80.500.info" )
-
-make.plot <- function( data ) {
-    #X11( type = "Xlib" )
-    p = ggplot( data = data )
-    p = p + layer( mapping = aes( x = old_information, y = value, colour = MAF, shape = type, solid = type ), geom = "point" )
-    p = p + scale_shape_manual( value =  c( 20, 3 ) )
-    #p = p + scale_colour_manual( values = c( "red", "lightblue" ) )
-    #p = p + stat_abline( xintercept = 0, slope = 1, colour = "red" )
-    p = p + facet_wrap( ~ variable )
-    p = p + xlab( "Original information measure" )
-    p = p + ylab( "New information measure" )
-    p = p + scale_colour_continuous( high = "black", low = "red" )
-    return( p )
-}
-p = make.plot( imputed )
-p = p + opts( title = "(PS chr22 imputed / genotyped data) info variant versus original" )
-#print(p)
-print(p + scale_x_continuous( limits = c( 0.9, 1.0 ) ) + scale_y_continuous( limits = c( 0.9, 1.0 ) ) )
-ggsave( p, file = "PS.illumina.22.80.500.imputed_info_comparison.png", dpi = 72, width = 16, height = 8 )
-ggsave( p + scale_x_continuous( limits = c( 0.9, 1.0 ) ) + scale_y_continuous( limits = c( 0.9, 1.0 ) ), file = "PS.illumina.22.80.500.imputed_info_comparison_zoom.png", dpi = 72, width = 16, height = 8 )
-
-q = make.plot( genotyped )
-q = q + opts( title = "(PS chr1 genotyped data) info variant versus original" )
-print( q + scale_x_continuous( limits = c( 0.9, 1.0 ) ) + scale_y_continuous( limits = c( 0.9, 1.0 ) ) )
-ggsave( q + scale_x_continuous( limits = c( 0.0, 1.0 ) ) + scale_y_continuous( limits = c( 0.0, 1.0 ) ), file = "PS_01_info_comparison.png", dpi = 72, width = 16, height = 8 )
-ggsave( q + scale_x_continuous( limits = c( 0.9, 1.0 ) ) + scale_y_continuous( limits = c( 0.9, 1.0 ) ), file = "PS_01_info_comparison_zoom.png", dpi = 72, width = 16, height = 8 )
-
-genotyped$missing_category = cut( genotyped$I, breaks = c( 0, 1000, 2000, 2500, 2600, 2610, 2620, 2622 ), labels = c( "I >= 0", "I >= 1000", "I >= 2000", "I >= 2500", "I >= 2600", "I >= 2610", "I >= 2620" ))
-genotyped$MAF_category = cut( genotyped$MAF, breaks = c( -1, 0.01, 0.1, 0.2, 0.3, 0.4, 0.5 ), labels = c( "MAF < 0.01", "MAF < 0.1", "MAF < 0.2", "MAF < 0.3", "MAF < 0.4", "MAF < 0.5" ))
-
-p = ggplot( data = genotyped[ which( !is.na( genotyped$MAF )), ] )
-p = p + layer( mapping = aes( x = old_information, y = value, colour = -log10( missing ), shape = MAF_category ), geom = "point" )
-#p = p + scale_colour_manual( values = c( "red", "lightblue" ) )
-#p = p + stat_abline( xintercept = 0, slope = 1, colour = "red" )
-p = p + facet_wrap( ~ variable )
-p = p + xlab( "Original information measure" )
-p = p + ylab( "New information measure" )
-p = p + scale_colour_continuous( high = "black", low = "red" )
-print(p + scale_x_continuous( limits = c( 0.0, 1.0 ) ) + scale_y_continuous( limits = c( 0.0, 1.0 ) ))
-ggsave( p + scale_x_continuous( limits = c( 0.0, 1.0 ) ) + scale_y_continuous( limits = c( 0.0, 1.0 ) ), file = "PS_01_info_comparison_coloured_by_missingness.png", dpi = 72, width = 16, height = 16 )
-ggsave( p + scale_x_continuous( limits = c( 0.9, 1.0 ) ) + scale_y_continuous( limits = c( 0.9, 1.0 ) ), file = "PS_01_info_comparison_coloured_by_missingness_zoom.png", dpi = 72, width = 16, height = 16 )
-
-p = ggplot( data = genotyped[ which( !is.na( genotyped$MAF )), ] )
-p = p + layer( mapping = aes( x = old_information, y = value, colour = -log10( missing ) ), geom = "point" )
-#p = p + scale_shape_manual( value =  c( 20, 3 ) )
-#p = p + scale_colour_manual( values = c( "red", "lightblue" ) )
-#p = p + stat_abline( xintercept = 0, slope = 1, colour = "red" )
-p = p + facet_grid( MAF_category ~ variable )
-p = p + xlab( "Original information measure" )
-p = p + ylab( "New information measure" )
-p = p + scale_colour_continuous( high = "black", low = "red" )
-p = p + opts( title = "(PS chr1 genotyped data) Info variants vs original,facetted by MAF")
-print(p + scale_x_continuous( limits = c( 0.0, 1.0 ) ) + scale_y_continuous( limits = c( 0.0, 1.0 ) ) )
-ggsave( p + scale_x_continuous( limits = c( 0.0, 1.0 ) ) + scale_y_continuous( limits = c( 0.0, 1.0 ) ), file = "PS_01_info_by_MAF.png", dpi = 72, width = 16, height = 24 )
-ggsave( p + scale_x_continuous( limits = c( 0.9, 1.0 ) ) + scale_y_continuous( limits = c( 0.9, 1.0 ) ), file = "PS_01_info_by_MAF_zoom.png", dpi = 72, width = 16, height = 24 )
-
-snp.stats = read.table( "PS_01_illumina.snp-stats" )
-snp.stats$MAF_category = cut( snp.stats$MAF, breaks = c( -1, 0.01, 0.1, 0.2, 0.3, 0.4, 0.5 ), labels = c( "MAF < 0.01", "MAF < 0.1", "MAF < 0.2", "MAF < 0.3", "MAF < 0.4", "MAF < 0.5" ))
-snp.stats$I = rowSums( snp.stats[, c( "AA", "AB", "BB" )] )
-snp.stats$I_category = cut( snp.stats$I, breaks = c( 0, 1000, 2000, 2500, 2600, 2610, 2620, 2625 ), labels = c( "I < 1000", "I < 2000", "I < 2500", "I < 2600", "I < 2610", "I < 2620", "I <= 2622" ))
-
-p = ggplot( data = snp.stats[ which( !is.na( snp.stats$MAF )), ] )
-p = p + layer( mapping = aes( x = jonathans_information, y = information, colour = -log10( missing ), shape = MAF_category ), geom = "point" )
-#p = p + scale_shape_manual( value =  c( 20, 3 ) )
-#p = p + scale_colour_manual( values = c( "red", "lightblue" ) )
-#p = p + stat_abline( xintercept = 0, slope = 1, colour = "red" )
-p = p + xlab( "info variant2" )
-p = p + ylab( "info variant1" )
-#p = p + facet_wrap( ~MAF_category )
-
-p = p + scale_colour_continuous( high = "black", low = "red" )
-p = p + opts( title = "(PS chr01 genotyped data).  Info variant 1 vs variant 2.")
-print(p)
-ggsave( p, file = "PS_01_info_variant1_vs_variant2.png", dpi = 72, width = 8, height = 8 )
-
-which( genotyped$rsid %in% imputed$rsid )
-
-##########################
-
-
-genotypes = read.table( gzfile( "PS_01_illumina.top.gen.gz" ), hea=F, as.is = T )
-colnames( genotypes )[1:5] = c( "SNPID", "rsid", "pos", "allele1", "allele2" )
-
-genotypes = read.table( "PS_master_01_illumina.top.gen", hea=F, as.is = T )
-colnames( genotypes )[1:5] = c( "SNPID", "rsid", "pos", "allele1", "allele2" )
-
-D = data.frame(
-    rsid = genotypes$rsid,
-    pos = genotypes$pos,
-    AA = NA,
-    AB = NA,
-    BB = NA,
-    missing = NA,
-    original = NA,
-    variant1 = NA,
-    variant2 = NA,
-    strange = NA,
-    original.flipped = NA,
-    variant1.flipped = NA,
-    variant2.flipped = NA,
-    strange.flipped = NA
-)
-
-for( i in 1:100) {
-    if( i %% 10 == 0 ) {
-        cat( i, 'of', nrow(D), '...' )
-    }
-    G = matrix( data = as.numeric( genotypes[i, 6:ncol( genotypes) ]), ncol = 3, byrow = T )
-    G.flipped = G[, c(3,2,1)]
-
-    D$AA[i] = sum( G[, 1] )
-    D$AB[i] = sum( G[, 2] )
-    D$BB[i] = sum( G[, 3] )
-    D$missing[i] = ( nrow(G) - sum( G[, 1:3] )) / nrow( G )
-    D$original[i] = info.original( G )
-    D$variant1[i] = info.variant1( G )
-    D$variant2[i] = info.variant2( G )
-    D$strange[i] = info.strange( G )
-
-    D$original.flipped[i] = info.original( G.flipped )
-    D$variant1.flipped[i] = info.variant1( G.flipped )
-    D$variant2.flipped[i] = info.variant2( G.flipped )
-    D$strange.flipped[i] = info.strange( G.flipped )
-}
-cat( i, 'of', nrow(D), '\n' )
-
-which( abs( D$original - D$original.flipped ) > 0.0001 )
-which( abs( D$variant1 - D$variant1.flipped ) > 0.0001 )
-which( abs( D$variant2 - D$variant2.flipped ) > 0.0001 )
-
-original.terms = sapply( 1:10, function( i ) {
-    G = matrix( data = as.numeric( genotypes[i, 6:ncol( genotypes) ]), ncol = 3, byrow = T )
-    return( info.original.terms( G ) )
-})
-
-variant1.terms = sapply( 1:10, function( i ) {
-    G = matrix( data = as.numeric( genotypes[i, 6:ncol( genotypes) ]), ncol = 3, byrow = T )
-    return( info.variant1.terms( G ) )
-})
-
-variant2.terms = sapply( 1:10, function( i ) {
-    G = matrix( data = as.numeric( genotypes[i, 6:ncol( genotypes) ]), ncol = 3, byrow = T )
-    return( info.variant2.terms( G ) )
-})
-
-original.terms
-variant1.terms
-variant2.terms

Index: appcontext/include/appcontext/ApplicationContext.hpp
==================================================================
--- appcontext/include/appcontext/ApplicationContext.hpp
+++ appcontext/include/appcontext/ApplicationContext.hpp
@@ -43,11 +43,12 @@
 		) ;
 
 		virtual ~ApplicationContext() ;
 		OptionProcessor& options() const ;
 		virtual UIContext& get_ui_context() const ;
-
+		UIContext& ui() const { return get_ui_context() ; }
+		OptionProcessor::OptionValueMap get_application_metadata() const ;
 		std::string const& application_name() const ;
 
 	private:
 		
 		void process_options( int argc, char** argv, std::string const& log_option, OptionChecker checker ) ;

Index: appcontext/include/appcontext/OptionDefinition.hpp
==================================================================
--- appcontext/include/appcontext/OptionDefinition.hpp
+++ appcontext/include/appcontext/OptionDefinition.hpp
@@ -5,20 +5,22 @@
 #include <limits>
 #include <set>
 #include <string>
 #include <sstream>
 #include <cassert>
+#include <boost/function.hpp>
 
 namespace appcontext {
 	struct OptionDefinition {
 		enum { eUntilNextOption = 2147483647 } ;
 		public:
 			OptionDefinition( std::string const& name = "" ) ;
 			OptionDefinition( OptionDefinition const& other ) ;
 			OptionDefinition& operator=( OptionDefinition const& other ) ;
 
-			typedef void (*value_checker_t)( std::string const&, std::vector< std::string > const& ) ;
+			// typedef void (*value_checker_t)( std::string const&, std::vector< std::string > const& ) ;
+			typedef boost::function< bool( std::string const&, std::vector< std::string > const& ) > value_checker_t ;
 			typedef std::vector< std::string > (*value_preprocessor_t)( std::string const&, std::vector< std::string > const& ) ;
 
 			std::string const& group() const { return m_group ; }
 			std::string description() const { return m_description ; } 
 			bool is_required() const { return m_minimum_multiplicity > 0 ; }
@@ -63,11 +65,11 @@
 			}
 			OptionDefinition& set_takes_values_until_next_option() {
 				m_number_of_values_per_use = eUntilNextOption ;	
 				return *this ;
 			}
-			OptionDefinition& add_value_checker( value_checker_t value_checker ) {
+			OptionDefinition& set_check( value_checker_t value_checker ) {
 				assert( value_checker != 0 ) ;
 				m_value_checkers.push_back( value_checker ) ; 
 				return *this ; 
 			}
 			template< typename T > OptionDefinition& set_default_value( T const& value ) {

Index: appcontext/include/appcontext/appcontext.hpp
==================================================================
--- appcontext/include/appcontext/appcontext.hpp
+++ appcontext/include/appcontext/appcontext.hpp
@@ -9,7 +9,8 @@
 
 #include "appcontext/CmdLineOptionProcessor.hpp"
 #include "appcontext/ApplicationContext.hpp"
 #include "appcontext/UIContext.hpp"
 #include "appcontext/ProgramFlow.hpp"
+#include "appcontext/get_current_time_as_string.hpp"
 
 #endif

ADDED   appcontext/include/appcontext/string_utils.hpp
Index: appcontext/include/appcontext/string_utils.hpp
==================================================================
--- appcontext/include/appcontext/string_utils.hpp
+++ appcontext/include/appcontext/string_utils.hpp
@@ -0,0 +1,27 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef APPCONTEXT_STRING_UTILS_HPP
+#define APPCONTEXT_STRING_UTILS_HPP
+
+#include <vector>
+#include <string>
+#include <sstream>
+#include <exception>
+
+namespace appcontext {
+	namespace string_utils {
+		std::string to_lower( std::string aString ) ;
+		void to_lower( std::string* aString ) ;
+		std::string to_upper( std::string aString ) ;
+		void to_upper( std::string* aString ) ;
+
+		std::string join( std::vector< std::string > const& strings, std::string const& joiner ) ;
+		std::string wrap( std::string const& string_to_wrap, unsigned int wrap_column, unsigned int starting_column, std::size_t indent_amount ) ;
+	}
+}
+
+#endif

Index: appcontext/src/ApplicationContext.cpp
==================================================================
--- appcontext/src/ApplicationContext.cpp
+++ appcontext/src/ApplicationContext.cpp
@@ -139,13 +139,13 @@
 	}
 
 	void ApplicationContext::write_start_banner() {
 		m_ui_context->logger() << "\nWelcome to " << m_application_name << "\n" ;
 		if( m_application_version != "" ) {
-			m_ui_context->logger() << "(version: " << m_application_version << ")\n" ;
+			m_ui_context->logger() << "(" << m_application_version << ")\n" ;
 		}
-		m_ui_context->logger() << "\n(C) 2009-2017 University of Oxford\n\n";
+		m_ui_context->logger() << "\n(C) 2009-2020 University of Oxford\n\n";
 	}
 
 	void ApplicationContext::write_end_banner() {
 		m_ui_context->logger() << "\n"
 			<< "Thank you for using " << m_application_name << ".\n" ;
@@ -153,6 +153,21 @@
 	
 	std::string const& ApplicationContext::application_name() const {
 		return m_application_name ;
 	}
 	
+	OptionProcessor::OptionValueMap ApplicationContext::get_application_metadata() const {
+		// typedef std::map< std::string, std::pair< std::vector< std::string >, std::string > > OptionValueMap ;
+		
+		OptionProcessor::OptionValueMap result = options().get_values_as_map() ;
+		result.insert(
+			std::make_pair(
+				"$",
+				std::make_pair(
+					std::vector< std::string >( 1, m_application_name + "(" + m_application_version + ")" ),
+					"user-supplied"
+				)
+			)
+		) ;
+		return result ;
+	}
 }

Index: appcontext/src/OptionDefinition.cpp
==================================================================
--- appcontext/src/OptionDefinition.cpp
+++ appcontext/src/OptionDefinition.cpp
@@ -63,11 +63,15 @@
 
 		std::vector< value_checker_t >::const_iterator
 			i = m_value_checkers.begin(),
 			end_i = m_value_checkers.end() ;
 		for( ; i != end_i; ++i ) {
-			(*i)( option_name, option_values ) ;
+			if( !(*i)( option_name, option_values ) ) {
+				std::ostringstream ostr ;
+				ostr << "Option \"" << option_name << "\": illegal value." ;
+				throw OptionValueInvalidException( option_name, option_values, ostr.str() ) ;
+			} ;
 		}
 	}
 	
 	namespace {
 		std::string json_escape( std::string const& value ) {

Index: appcontext/src/OptionProcessor.cpp
==================================================================
--- appcontext/src/OptionProcessor.cpp
+++ appcontext/src/OptionProcessor.cpp
@@ -12,11 +12,11 @@
 #include <iostream>
 #include <iomanip>
 #include <cassert>
 #include "appcontext/OptionDefinition.hpp"
 #include "appcontext/OptionProcessor.hpp"
-#include "genfile/string_utils.hpp"
+#include "appcontext/string_utils.hpp"
 
 namespace appcontext {
 	OptionProcessingException::OptionProcessingException( std::string option, std::vector< std::string > values, std::string msg )
 	: 	m_option( option ),
 		m_values( values ),
@@ -346,10 +346,13 @@
 	}
 
 	std::string OptionProcessor::get_default_value( std::string const& arg ) const {
 		std::map< std::string, OptionDefinition >::const_iterator defn_i
 			= m_option_definitions.find( arg ) ;
+		if( defn_i == m_option_definitions.end() ) {
+			std::cerr << "Argument \"" + arg + "\" not found.\n" ;
+		}
 		assert( defn_i != m_option_definitions.end() ) ;
 		assert( defn_i->second.has_default_value() ) ;
 		return defn_i->second.default_value() ;
 	}
 
@@ -427,13 +430,13 @@
 		aStream << ": " ;
 		unsigned int current_column = max_option_length+4 ;
 
 		std::string description = (*this)[option_name].description() ;
 		if( (*this)[option_name].has_default_value() ) {
-			description += "  Defaults to \"" + genfile::string_utils::join( (*this)[option_name].default_values(), ", " ) + "\"." ;
+			description += "  Defaults to \"" + string_utils::join( (*this)[option_name].default_values(), ", " ) + "\"." ;
 		}
-		aStream << genfile::string_utils::wrap( description, 120, current_column, current_column )
+		aStream << string_utils::wrap( description, 120, current_column, current_column )
 			<< "\n" ;
 	}
 
 	std::size_t OptionProcessor::get_maximum_option_length() const {
 		OptionDefinitions::const_iterator

ADDED   appcontext/src/string_utils.cpp
Index: appcontext/src/string_utils.cpp
==================================================================
--- appcontext/src/string_utils.cpp
+++ appcontext/src/string_utils.cpp
@@ -0,0 +1,126 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <limits>
+#include <vector>
+#include <string>
+#include <sstream>
+#include <exception>
+#include <algorithm>
+#include <cassert>
+#include <cstdlib>
+#include "appcontext/string_utils.hpp"
+
+namespace appcontext {
+	namespace string_utils {
+		std::string to_lower( std::string aString ) {
+			for( std::string::iterator i = aString.begin(); i != aString.end(); ++i ) {
+				if( *i >= 'A' && *i <= 'Z' ) {
+					*i += 32 ;
+				}
+			}
+			return aString ;
+		}
+
+		void to_lower( std::string* aString ) {
+			for( std::string::iterator i = aString->begin(); i != aString->end(); ++i ) {
+				if( *i >= 'A' && *i <= 'Z' ) {
+					*i += 32 ;
+				}
+			}
+		}
+
+		std::string to_upper( std::string aString ) {
+			for( std::string::iterator i = aString.begin(); i != aString.end(); ++i ) {
+				if( *i >= 'a' && *i <= 'z' ) {
+					*i -= 32 ;
+				}
+			}
+			return aString ;
+		}
+
+		void to_upper( std::string* aString ) {
+			for( std::string::iterator i = aString->begin(); i != aString->end(); ++i ) {
+				if( *i >= 'a' && *i <= 'z' ) {
+					*i -= 32 ;
+				}
+			}
+		}
+
+		std::string join( std::vector< std::string > const& strings, std::string const& joiner ) {
+			std::string result ;
+			for( std::size_t i = 0; i < strings.size(); ++i ) {
+					if( i > 0 ) {
+							result += joiner ;
+					}
+					result += strings[i] ;
+			}
+			return result ;
+		}
+
+		namespace impl {
+			bool is_alphabetic( char c) {
+					return (c >= 'A' && c <= 'Z') || (c >= 'a' && c <= 'z') ;
+			}
+
+			bool is_blank( char c) {
+					return c == ' ' || c == '\n' ;
+			}
+		}
+	
+	
+
+		std::string wrap( std::string const& string_to_wrap, unsigned int wrap_column, unsigned int starting_column, std::size_t indent_amount ) { 
+			assert( wrap_column > starting_column ) ; 
+			assert( wrap_column > indent_amount ) ; 
+
+			if( string_to_wrap.size() < (wrap_column - starting_column) ) { 
+					return string_to_wrap ;
+			}	
+
+			std::string result ;
+			unsigned int current_column = starting_column ;
+			std::string indent( indent_amount, ' ' ) ; 
+
+			std::string::const_iterator
+					this_char = string_to_wrap.begin(),
+					next_char = string_to_wrap.begin() ;
+			for( ++next_char; this_char < string_to_wrap.end(); ++this_char, ++next_char ) { 
+					if( current_column == 0 ) { 
+							result.append( indent ) ; 
+							current_column = indent_amount ;
+							// skip whitespace at beginning of line
+							for( ; this_char < string_to_wrap.end() && impl::is_blank( *this_char ); ++this_char, ++next_char ) ; 
+					}	
+
+					if( this_char < string_to_wrap.end() ) { 
+							result.push_back( *this_char ) ; 
+							if( *this_char == '\n' ) { 
+									current_column = 0 ; 
+							}	
+							else if( ++current_column < wrap_column || next_char == string_to_wrap.end() ) { 
+							}	
+							else {
+									if( impl::is_alphabetic( *this_char ) && impl::is_alphabetic( *next_char )) {
+											// we are in the middle of a word.
+											result.push_back( '-' ) ;
+											result.push_back( '\n' ) ;
+											current_column = 0 ;
+									}
+									else if( impl::is_blank( *this_char ) || impl::is_blank( *next_char )) {
+											result.push_back( '\n' ) ;
+											current_column = 0 ;
+									}
+									else {
+											// do nothing in case this is something which can't be split.
+									}
+							}
+					}
+			}
+			return result ;
+		}
+	}
+}

Index: appcontext/wscript
==================================================================
--- appcontext/wscript
+++ appcontext/wscript
@@ -1,43 +1,9 @@
-import os.path
-import glob
-#import UnitTest
-
-def configure( conf ):
-	pass
-
-def create_test( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = [  'test/' + name + '.cpp' ],
-		uselib_local = 'worker',
-		uselib = 'BOOST_THREAD',
-		includes='./include',
-		unit_test=1
-	)
-
-def create_benchmark( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = [  'benchmarks/' + name + '.cpp' ],
-		uselib_local = 'worker',
-		includes='./include'
-	)
-
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld(
-		features = 'cxx cstaticlib',
-		target = 'appcontext',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib_local = 'genfile',
-		uselib = 'BOOST',
-		export_incdirs = './include'	
+def build( bld ):
+	bld.stlib(
+		target = 'appcontext',
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		use = 'boost',
+		includes='./include',
+		cxxflags = [ '-std=c++11' ],
+		export_includes = './include'	
 	)

ADDED   apps/bingwa.cpp
Index: apps/bingwa.cpp
==================================================================
--- apps/bingwa.cpp
+++ apps/bingwa.cpp
@@ -0,0 +1,2514 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <sstream>
+#include <iomanip>
+#include <memory>
+#include <set>
+#include <map>
+#include <algorithm>
+#include <utility>
+#include <fstream>
+#include <boost/bimap.hpp>
+#include <boost/bind.hpp>
+#include <boost/signals2/signal.hpp>
+#include <boost/ptr_container/ptr_vector.hpp>
+#include <boost/function.hpp>
+#include <boost/format.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/tuple/tuple_io.hpp>
+#include <boost/tuple/tuple_comparison.hpp>
+#include <boost/foreach.hpp>
+#include <boost/regex.hpp>
+#include <boost/filesystem.hpp>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <Eigen/Core>
+#include <Eigen/Cholesky>
+#include <Eigen/LU>
+#include <Eigen/QR>
+#include "appcontext/CmdLineOptionProcessor.hpp"
+#include "appcontext/ApplicationContext.hpp"
+#include "appcontext/get_current_time_as_string.hpp"
+#include "appcontext/ProgramFlow.hpp"
+#include "genfile/FileUtils.hpp"
+#include "genfile/utility.hpp"
+#include "genfile/string_utils/string_utils.hpp"
+#include "genfile/string_utils/slice.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantIdentifyingDataTest.hpp"
+#include "genfile/CommonSNPFilter.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "statfile/BuiltInTypeStatSource.hpp"
+#include "statfile/BuiltInTypeStatSourceChain.hpp"
+#include "statfile/SNPDataSourceAdapter.hpp"
+#include "statfile/FilteringStatSource.hpp"
+#include "qcdb/MultiTableStorage.hpp"
+#include "qcdb/MultiFileOutputter.hpp"
+#include "qcdb/MultiTableDBOutputter.hpp"
+#include "bingwa/FrequentistGenomeWideAssociationResults.hpp"
+#include "bingwa/EffectParameterNamePack.hpp"
+#include "bingwa/SNPTESTResults.hpp"
+#include "bingwa/MMMResults.hpp"
+#include "bingwa/BingwaComputation.hpp"
+#include "bingwa/PerCohortValueReporter.hpp"
+#include "bingwa/PerCohortCountsReporter.hpp"
+#include "bingwa/MultivariateFixedEffectMetaAnalysis.hpp"
+#include "bingwa/ModelAveragingBayesFactorAnalysis.hpp"
+#include "bingwa/PerCohortBayesFactor.hpp"
+
+// #define DEBUG_BINGWA 1
+
+namespace globals {
+	std::string const program_name = "bingwa" ;
+	std::string const program_version = "0.2" ;
+}
+
+namespace {
+	double const NA = std::numeric_limits< double >::quiet_NaN() ;
+	double const Infinity = std::numeric_limits< double >::infinity() ;
+}
+
+
+struct BingwaOptions: public appcontext::CmdLineOptionProcessor {
+	std::string get_program_name() const { return globals::program_name ; }
+
+	void declare_options( appcontext::OptionProcessor& options ) {
+		options.set_help_option( "-help" ) ;
+
+		{
+			options.declare_group( "Input data options" ) ;
+			options[ "-data" ]
+				.set_description( "Specify the path of a file containing SNPTEST or MMM results to load." )
+				.set_is_required()
+				.set_takes_values_until_next_option()
+				.set_minimum_multiplicity( 1 )
+				.set_maximum_multiplicity( 100 )
+			;
+			options[ "-extra-columns" ]
+				.set_description( "Specify extra columns in input files whose values will be considered as variables to be reported in the output."
+				 	" Currently these must be columns of numerical data.  (A single wildcard character * at the start or end of the column name may"
+					" be used to match any initial or terminal sequence of characters; but take care to escape this from the shell.)" )
+					.set_takes_values_until_next_option()
+					.set_minimum_multiplicity( 0 )
+					.set_maximum_multiplicity( 100 )
+				;
+			
+			options[ "-snp-match-fields" ]
+				.set_description( "Use this option to specify a comma-separated list of SNP-identifying fields that should be used "
+					"to match SNPs between cohorts.  Possible fields "
+					"are \"position\", \"alleles\", \"rsid\", or \"snpid\"; you must always specify \"position\" as the first entry." )
+				.set_takes_single_value()
+				.set_default_value( "position,alleles" ) ;
+		}
+		{
+			options.declare_group( "SNP inclusion / exclusion options" ) ;
+			options[ "-excl-snpids" ]
+				.set_description( "Exclude all SNPs whose SNPID is in the given file(s) from the analysis.")
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-excl-rsids" ]
+				.set_description( "Exclude all SNPs whose RSID is in the given file(s) from the analysis.")
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-incl-snpids" ]
+				.set_description( "Exclude all SNPs whose SNPID is not in the given file(s) from the analysis.")
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-incl-rsids" ]
+				.set_description( "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.")
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-excl-positions" ]
+				.set_description( "Exclude all SNPs whose position is in the given file(s) from the analysis. "
+					"Positions should be in the form [chromosome]:[position] and separated by whitespace." )
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-incl-positions" ]
+				.set_description( "Exclude all SNPs whose position is not in the given file(s) from the analysis. "
+					"Positions should be in the form [chromosome]:[position] and separated by whitespace." )
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-excl-snps-matching" ]
+				.set_description( "Filter out snps whose rsid or SNPID matches the given value. "
+					"The value should be a string which can contain a % wildcard character (which matches any substring). "
+					"Optionally, prefix the argument with snpid~ or rsid~ to only match against the SNPID or rsid fields." )
+				.set_takes_single_value() ;
+			options[ "-incl-snps-matching" ]
+				.set_description( "Filter out snps whose rsid or SNPID does not match the given value. "
+					"The value should be a string which can contain a % wildcard character (which matches any substring). "
+					"Optionally, prefix the argument with snpid~ or rsid~ to only match against the SNPID or rsid fields." )
+				.set_takes_single_value() ;
+			options[ "-incl-range" ]
+				.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. "
+					"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+					"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+					"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+				.set_takes_single_value() ;
+			options[ "-excl-range" ]
+				.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to exclude from operation. "
+					"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+					"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+					"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+				.set_takes_single_value() ;
+				
+			options[ "-excl-snpids-per-cohort" ]
+				.set_description( "Exclude all SNPs whose SNPID is in the given file(s) from the corresponding cohort. "
+					"The i-th value should be a comma-separated list of files containing rsids to exclude from the i-th cohort." )
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-excl-rsids-per-cohort" ]
+				.set_description( "Exclude all SNPs whose RSID is in the given file(s) from the corresponding cohort. "
+					"The i-th value should be a comma-separated list of files containing rsids to exclude from the i-th cohort." )
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-incl-snpids-per-cohort" ]
+				.set_description( "Exclude all SNPs whose SNPID is not in the given file(s) from the corresponding cohort."
+					"The i-th value should be a comma-separated list of files containing rsids to exclude from the i-th cohort." )
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-incl-rsids-per-cohort" ]
+				.set_description( "Exclude all SNPs whose RSID is not in the given file(s) from the corresponding cohort."
+					"The i-th value should be a comma-separated list of files containing rsids to exclude from the i-th cohort." )
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-excl-snps-per-cohort" ]
+				.set_description( "Exclude all SNPs in the given file(s) from the corresponding cohort. "
+					"The i-th value should be a comma-separated list of files containing snps to exclude from the i-th cohort, in the format output by gen-grep." )
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-incl-snps-per-cohort" ]
+				.set_description( "Exclude all SNPs not in the given file(s) from the corresponding cohort."
+					"The i-th value should be a comma-separated list of files containing rsids to exclude from the i-th cohort, in the format output by gen-grep." )
+				.set_takes_values_until_next_option() 
+				.set_maximum_multiplicity( 100 ) ;
+			options[ "-excl-snps-where" ]
+				.set_description( "Exclude SNPs that match a condition applied to columns of the input file." )
+				.set_takes_single_value()
+				.set_maximum_multiplicity(100) ;
+
+			options[ "-incl-snps-where" ]
+				.set_description( "Exclude SNPs that do not match a condition applied to columns of the input file." )
+				.set_takes_single_value()
+				.set_maximum_multiplicity(100) ;
+
+			options[ "-trust-variants-where" ]
+				.set_description( "Exclude *from the meta-analysis* summary statistics for SNPs that match a condition applied to columns of the input file." )
+				.set_takes_values_until_next_option()
+				.set_maximum_multiplicity(100) ;
+		}
+
+		{
+			options.declare_group( "Options for adjusting variants" ) ;
+			options[ "-flip-alleles" ]
+				.set_description( "Specify that, where alleles do not match between cohorts, bingwa will try to match them by flipping." )
+			;
+			options[ "-assume-chromosome" ]
+				.set_description( "Specify that bingwa should treat all SNPs with missing chromosome as having the given one." )
+				.set_takes_single_value() ;
+		}
+
+		{
+			options.declare_group( "Options affecting output" ) ;
+
+			options[ "-o" ]
+				.set_description( "Specify the path to the output file." )
+				.set_is_required()
+				.set_takes_single_value() ;
+
+			options[ "-noindex" ]
+				.set_description( "Specify that " + globals::program_name + " should not create large indices on database tables when finalising storage."
+					" Indices are usually desired.  However, when running very large jobs parallelised across subsets, it is generally faster to"
+					" use -noindex and create indices manually when all jobs have completed." ) ;
+			options[ "-no-identifiers" ]
+				.set_description( "Specify that " + globals::program_name + " should not record all variant identifiers that differ from"
+					" the primary identifer.  This identifiers will appear in a table called \"VariantIdentifier\"." ) ;
+			options[ "-analysis-name" ]
+				.set_description( "Specify a name for the current analysis." )
+				.set_takes_single_value()
+				.set_default_value( "bingwa analysis" ) ;
+			options[ "-analysis-chunk" ]
+				.set_description( "Specify a name denoting the current genomic region or chunk on which this is run.  This is intended for use in parallel environments." )
+				.set_takes_single_value()
+				.set_default_value( genfile::MissingValue() ) ;
+			options[ "-analysis-id" ]
+				.set_description( "Specify an integer ID for the current analysis." )
+				.set_takes_single_value() ;
+			options[ "-cohort-names" ]
+				.set_description( "Specify a name to label results from this analysis with" )
+				.set_takes_values_until_next_option() ;
+			options[ "-table-prefix" ]
+				.set_description( "Specify a prefix for table names for the current analysis." )
+				.set_takes_single_value()
+				.set_default_value( "Bingwa" ) ;
+
+			options[ "-log" ]
+				.set_description( "Specify the path of a log file; all screen output will be copied to the file." )
+				.set_takes_single_value() ;
+			options[ "-verbose" ]
+				.set_description( "Be verbose about screen/log output." ) ;
+		}
+
+		{
+			options.declare_group( "Analysis options" ) ;
+		
+			options[ "-no-meta-analysis" ]
+				.set_description( "Don't do a fixed effect meta-analysis.  Instead, just match up SNPs and store per-cohort values." ) ;
+			options[ "-no-counts" ]
+				.set_description( "Don't output per-cohort allele or genotype counts." ) ;
+			options[ "-output-all-variants" ]
+				.set_description( "Output all variants, even those where there is no trustworthy data" ) ;
+			options[ "-rename-parameters" ]
+				.set_description( "Specify the name of a file containing updated names for parameters. "
+					"This file should have at least two named columns; the first column should contain"
+					" the original name of each parameter; the second column should contain the name is it should"
+					" appear in the output file." )
+				.set_takes_single_value() ;
+		}
+		{
+			options.declare_group( "Bayesian analysis options" ) ;
+			options[ "-null-sd" ]
+				.set_description( "Define the standard deviation of the prior for null model." )
+				.set_takes_single_value()
+				.set_default_value( 0 )
+			;
+			options[ "-define-sd-set" ]
+				.set_description( "Define set(s) of standard deviations to use in prior specifications. "
+					"The value should be a whitespace-separated list of elements of the form "
+					"\"[name of set]=[sd1],[sd2],[sd3]...\"." )
+				.set_takes_values_until_next_option()
+				.set_minimum_multiplicity( 0 )
+				.set_maximum_multiplicity( 1 ) ;
+
+			options[ "-subsets" ]
+				.set_description(
+					"Specify that all cross-population priors should be applied to subsets of cohorts.\n"
+					"Possible values are \"all\" (generate all 2^k subsets) or \"contiguous\" (generate all contiguous subsets)"
+				)
+				.set_takes_single_value() ;
+
+			options.declare_group( "Bayesian meta-analysis options" ) ;
+			options[ "-define-tau-set" ]
+				.set_description( "Define set(s) of correlations to use in prior specifications. "
+					"The value should be a whitespace-separated list of elements of the form "
+					"\"[name of set]=[value],[value],[value]...\"." )
+				.set_takes_values_until_next_option()
+				.set_minimum_multiplicity( 0 )
+				.set_maximum_multiplicity( 1 ) ;
+			
+			options[ "-prior" ]
+				.set_description( "Specify a prior model to use when computing a bayes factor.\n"
+					"The format of the argument is as follows:\n"
+					"[<name>:][tau=<tau>/]sd=<sds>/cor=<cor>\n"
+					" where tau denotes between-cohort correlations, cor denotes the upper diagonal of a correlation matrix,"
+					"and sd is a list of standard errors."
+					"If tau is supplied the standard errors and cors are specified within-cohort,"
+					"otherwise they specify the full matrix across cohorts."
+					"The name is optional, and if not supplied a name will be generated."
+				)
+				.set_takes_values_until_next_option()
+				.set_minimum_multiplicity( 0 )
+				.set_maximum_multiplicity( 1 ) ;
+
+			options[ "-prior-file" ]
+				.set_description( "Specify a file containing prior models to load." )
+				.set_takes_single_value()
+				.set_minimum_multiplicity( 0 )
+				.set_maximum_multiplicity( 1 ) ;
+
+			options[ "-per-cohort-prior" ]
+				.set_description( "Specify a prior model to use when computing bayes factor in each population.\n" )
+				.set_takes_single_value() ;
+
+			options[ "-prior-weights" ]
+				.set_description( "Specify prior weights for each model. Each argument must be of the form"
+					"<model name>=<weight>, where <model name> is the name of a model specified by -prior."
+					"models that are not assigned weights are given the implicit weight of 1."
+				)
+				.set_takes_values_until_next_option()
+				.set_minimum_multiplicity( 0 )
+				.set_maximum_multiplicity( 1 ) ;
+
+			options.option_excludes_option( "-no-meta-analysis", "-prior" ) ;
+			options.option_excludes_option( "-prior-file", "-prior" ) ;
+		}
+	}
+} ;
+
+
+namespace impl {
+	std::vector< std::string > parse_sqlite_filespec( std::string const& spec ) {
+		std::vector< std::string > elts = genfile::string_utils::split( spec, ":" ) ;
+		if( spec.size() > 9 && spec.substr(0,9) == "sqlite://" ) {
+			elts.erase( elts.begin() ) ;
+			elts[0] = elts[0].substr( 2, elts[0].size() ) ;
+		}
+		assert( elts.size() >= 1 ) ;
+		if( elts.size() > 3 ) {
+			throw genfile::BadArgumentError(
+				"QCToolProcessor::parse_sqlite_filespace()",
+				"spec=\"" + spec + "\"",
+				"Expected format for sqlite filespec is sqlite://<file name>[:<bf table name>][:<count table name>]."
+			) ;
+		}
+		return( elts ) ;
+	}
+	
+	std::string get_output_filetype( std::string const& filename ) {
+		if( (filename.size() >= 7 && filename.substr( 0, 9 ) == "sqlite://" )
+			|| ( filename.size() >= 7 && filename.substr( filename.size() - 7, 7 ) == ".sqlite" )
+		) {
+			return "sqlite" ;
+		} else {
+			return "flat" ;
+		}
+	}
+
+	template< typename Container >
+	void insert_into_map( Container* container, std::string const& a, std::string const& b ) {
+		container->insert( container->end(), std::make_pair( a, b ) ) ;
+	}
+	
+	typedef std::map< std::string, std::string > VariableMap ;
+	bool contains_variable( VariableMap const& map, std::string const& variable ) {
+		bool result = (map.find( variable ) != map.end() ) ;
+		return result ;
+	}
+}
+
+namespace impl {
+	std::string get_model_names(
+		std::vector< bingwa::ModelAveragingBayesFactorAnalysis::ModelSpec > const& models,
+		std::size_t i
+	) {
+		return models[i].name() ;
+	}
+
+	double get_model_weights(
+		std::vector< bingwa::ModelAveragingBayesFactorAnalysis::ModelSpec > const& models,
+		std::size_t i
+	) {
+		return models[i].weight() ;
+	}
+}
+
+struct BingwaProcessor: public boost::noncopyable
+{
+public:
+		typedef std::auto_ptr< BingwaProcessor > UniquePtr ;
+public:
+	static UniquePtr create( genfile::VariantIdentifyingData::CompareFields const& compare_fields ) {
+		return UniquePtr( new BingwaProcessor( compare_fields ) ) ;
+	}
+	
+	BingwaProcessor( genfile::VariantIdentifyingData::CompareFields const& compare_fields ):
+		m_snps( compare_fields ),
+		m_flip_alleles_if_necessary( false ),
+		m_output_all_variants( false )
+	{
+	}
+	
+	void set_flip_alleles( void ) {
+		m_flip_alleles_if_necessary = true ;
+	}
+
+	void set_output_all_variants() {
+		m_output_all_variants = true ;
+	}
+	
+	void add_cohort( std::string const& name, FrequentistGenomeWideAssociationResults::UniquePtr results ) {
+		assert( results.get() ) ;
+		m_cohort_names.push_back( name ) ;
+		m_cohorts.push_back( results ) ;
+	}
+	
+	std::size_t get_number_of_cohorts() const {
+		return m_cohorts.size() ;
+	}
+
+	FrequentistGenomeWideAssociationResults const& get_cohort( std::size_t i ) const {
+		return m_cohorts[i] ;
+	}
+	
+	void summarise( appcontext::UIContext& ui_context ) {
+		using genfile::string_utils::to_string ;
+
+#if DEBUG_BINGWA
+		ui_context.logger() << "================================================\n" ;
+		ui_context.logger() << "Cohort summary:\n" ;
+		for( std::size_t i = 0; i < m_cohorts.size(); ++i ) {
+			ui_context.logger() << " - Cohort " << (i+1) << ":\n" ;
+			ui_context.logger() << m_cohorts[i].get_summary( "   - " ) ;
+			ui_context.logger() << "\n   - First few SNPs are:\n" ;
+			for( std::size_t snp_i = 0; snp_i < std::min( std::size_t( 5 ), m_cohorts[i].get_number_of_SNPs() ); ++snp_i ) {
+				ui_context.logger() << "     " << m_cohorts[i].get_SNP( snp_i ) << "\n";
+			}
+		}
+#endif
+		
+		ui_context.logger() << "\n================================================\n" ;
+		ui_context.logger() << "SNP Categories:\n" ;
+		ui_context.logger() << "  " ;
+		for( std::size_t i = 0; i < m_cohorts.size(); ++i ) {
+			ui_context.logger() << std::setw( 12 ) << ( "in scan " + to_string( i+1 )) ;
+		}
+		ui_context.logger() << "\n" ;
+		for( CategoryCounts::const_iterator i = m_category_counts.begin(); i != m_category_counts.end(); ++i ) {
+			ui_context.logger() << "  " ;
+			for( std::size_t j = 0; j < m_cohorts.size(); ++j ) {	
+				ui_context.logger() << std::setw(12) << ( i->first[j] ? '*' : ' ' ) ;
+			}
+			ui_context.logger() << ": " << i->second << "\n" ;
+		}
+		ui_context.logger() << " TOTAL: " << m_snps.size() << "\n" ;
+		ui_context.logger() << "================================================\n" ;
+	}
+	
+	void add_computation( std::string const& table, bingwa::BingwaComputation::UniquePtr computation ) {
+		m_computations.push_back( computation ) ;
+		m_computations.back().set_effect_parameter_names( m_effect_parameter_names ) ;
+	}
+
+	void set_effect_parameter_names( bingwa::EffectParameterNamePack const& names ) {
+		m_effect_parameter_names = names ;
+	}
+
+	bingwa::EffectParameterNamePack const get_effect_parameter_names() const {
+		return m_effect_parameter_names ;
+	}
+
+	int const get_number_of_effect_parameters() const {
+		return int( m_effect_parameter_names.size() ) ;
+	}
+
+	void get_variables( boost::function< void ( std::string, std::string ) > callback ) const {
+		for( std::size_t i = 0; i < m_computations.size(); ++i ) {
+			m_computations[i].get_variables( callback ) ;
+		}
+	}
+
+	void setup( appcontext::UIContext& ui_context ) {
+		unsafe_setup( ui_context ) ;
+	}
+
+	void process( appcontext::UIContext& ui_context ) {
+		unsafe_process( ui_context ) ;
+	}
+
+	typedef boost::signals2::signal<
+		void (
+			genfile::VariantIdentifyingData const& snp,
+			std::string const& value_name,
+			genfile::VariantEntry const& value
+		)
+	> ResultSignal ;
+
+	void send_results_to( ResultSignal::slot_type callback ) {
+		m_result_signal.connect( callback ) ;
+	}
+	
+private:
+	std::vector< std::string > m_cohort_names ;
+	boost::ptr_vector< FrequentistGenomeWideAssociationResults > m_cohorts ;
+	bingwa::EffectParameterNamePack m_effect_parameter_names ;
+	boost::ptr_vector< bingwa::BingwaComputation > m_computations ;
+	std::map< std::string, std::map< std::string, std::string > > m_table_specs ;
+	struct SnpMatch {
+	public:
+		SnpMatch( std::size_t index_, bool flip_ ): index( index_ ), flip( flip_ ) {}
+		SnpMatch(): index(0), flip( false ) {}
+		SnpMatch( SnpMatch const& other ): index( other.index ), flip( other.flip ) {}
+		SnpMatch& operator=( SnpMatch const& other ) { index = other.index ; flip = other.flip ; return *this ; }
+	public:
+		std::size_t index ;
+		bool flip ;
+	} ;
+	typedef boost::optional< SnpMatch > OptionalSnpMatch ;
+	typedef std::map<
+		genfile::VariantIdentifyingData,
+		std::vector< OptionalSnpMatch >,
+		genfile::VariantIdentifyingData::CompareFields
+	> SnpMap ;
+	SnpMap m_snps ;
+	typedef std::map< std::vector< bool >, std::size_t > CategoryCounts ;
+	CategoryCounts m_category_counts ;
+	bool m_flip_alleles_if_necessary ;
+	bool m_output_all_variants ;
+	
+	ResultSignal m_result_signal ;
+
+private:
+	struct DataGetter: public bingwa::BingwaComputation::DataGetter {
+		DataGetter(
+			boost::ptr_vector< FrequentistGenomeWideAssociationResults > const& cohorts,
+			std::vector< OptionalSnpMatch >const& indices
+		):
+			m_cohorts( cohorts ),
+			m_indices( indices )
+		{}
+		
+		std::size_t get_number_of_cohorts() const { return m_cohorts.size() ; }
+
+		bool has_useful_data() const {
+			bool result = false ;
+			for( std::size_t i = 0; i < m_cohorts.size(); ++i ) {
+				result = result || ( is_non_missing(i) && m_cohorts[i].is_trusted( m_indices[i]->index )) ;
+			}
+			return result ;
+		}
+		
+		bool is_non_missing( std::size_t i ) const {
+			return( m_indices[i] ) ;
+		}
+
+		bool is_trusted( std::size_t i ) const {
+			assert( is_non_missing(i) ) ;
+			return m_cohorts[i].is_trusted( m_indices[i]->index ) ;
+		}
+	
+		/* Genotype counts are returned as a vector of length 6 in this order:
+		* haploid A, B, diploid AA, AB, BB, NULL call. */
+		void get_counts( std::size_t i, Eigen::VectorXd* result ) const {
+			if( is_non_missing( i ) ) {
+				m_cohorts[i].get_counts( m_indices[i]->index, result ) ;
+				if( m_indices[i]->flip ) {
+					// Swap genotype counts for haploid:
+					result->segment( 0, 2 ).reverseInPlace() ;
+					// ...and diploid samples:
+					result->segment( 2, 3 ).reverseInPlace() ;
+				}
+			}
+		}
+		void get_betas( std::size_t i, Eigen::VectorXd* result ) const {
+			if( is_non_missing( i ) ) {
+				m_cohorts[i].get_betas( m_indices[i]->index, result ) ;
+				if( m_indices[i]->flip ) {
+					(*result) *= -1 ;
+				}
+			}
+		}
+		void get_ses( std::size_t i, Eigen::VectorXd* result ) const {
+			if( is_non_missing( i ) ) {
+				m_cohorts[i].get_ses( m_indices[i]->index, result ) ;
+			}
+		}
+		void get_covariance_upper_triangle( std::size_t i, Eigen::VectorXd* result ) const {
+			if( is_non_missing( i ) ) {
+				m_cohorts[i].get_covariance_upper_triangle( m_indices[i]->index, result ) ;
+			}
+		}
+		void get_pvalue( std::size_t i, double* result ) const {
+			if( is_non_missing( i ) ) {
+				m_cohorts[i].get_pvalue( m_indices[i]->index, result ) ;
+			}
+		}
+		void get_info( std::size_t i, double* result ) const {
+			if( is_non_missing( i ) ) {
+				m_cohorts[i].get_info( m_indices[i]->index, result ) ;
+			}
+		}
+		void get_variable( std::string const& variable, std::size_t i, std::string* result ) const {
+			m_cohorts[i].get_variable( m_indices[i]->index, variable, result ) ;
+		}
+
+		private:
+			boost::ptr_vector< FrequentistGenomeWideAssociationResults > const& m_cohorts ;
+			std::vector< OptionalSnpMatch > const& m_indices ;
+	} ;
+
+private:
+	void unsafe_setup( appcontext::UIContext& ui_context ) {
+		link_data( ui_context ) ;
+		categorise_by_missingness() ;
+	}
+	
+	void add_SNP_callback( std::size_t cohort_i, std::size_t snp_i, genfile::VariantIdentifyingData const& snp ) {
+		// Find the SNP that matches the given one (if it exists)
+		std::pair< SnpMap::iterator, SnpMap::iterator > range = m_snps.equal_range( snp ) ;
+		SnpMatch snp_match( snp_i, false ) ;
+
+		if( range.second == range.first && m_flip_alleles_if_necessary ) {
+			genfile::VariantIdentifyingData swapped_snp = snp ;
+			swapped_snp.swap_alleles() ;
+			range = m_snps.equal_range( swapped_snp ) ;
+			snp_match.flip = ( range.second != range.first ) ;
+		}
+		
+		if( range.second == range.first ) {
+			// no match to existing data, so add as a new SNP.
+			std::vector< OptionalSnpMatch >& snp_matches = m_snps[ snp ] ;
+			snp_matches.resize( m_cohorts.size() ) ;
+			snp_matches[ cohort_i ] = snp_match ;
+		}
+		else {
+			// There is a match.  We make sure to record all the IDs
+			// presented for this variant, but take the first rsid seen
+			// as the rsid.
+			// First save the currently-stored data and erase the current record.
+			genfile::VariantIdentifyingData stored_snp = range.first->first ;
+			std::vector< OptionalSnpMatch > snp_matches = range.first->second ;
+			m_snps.erase( range.first ) ;
+			
+			stored_snp.add_identifier( snp.get_primary_id() ) ;
+			snp.get_identifiers( boost::bind( &genfile::VariantIdentifyingData::add_identifier, &stored_snp, _1 ) ) ;
+
+			snp_matches[ cohort_i ] = snp_match ;
+			m_snps[ stored_snp ] = snp_matches ;
+		}
+	}
+
+	void link_data( appcontext::UIContext& ui_context ) {
+		appcontext::UIContext::ProgressContext progress_context = ui_context.get_progress_context( "Linking SNPs" ) ;
+		progress_context( 0, m_cohorts.size() ) ;
+		for( std::size_t cohort_i = 0; cohort_i < m_cohorts.size(); ++cohort_i ) {
+			m_cohorts[ cohort_i].get_SNPs(
+				boost::bind(
+					&BingwaProcessor::add_SNP_callback,
+					this,
+					cohort_i,
+					_1,
+					_2
+				)
+			) ;
+			progress_context( cohort_i+1, m_cohorts.size() ) ;
+		}
+	}
+	
+	void categorise_by_missingness() {
+		SnpMap::const_iterator snp_i = m_snps.begin(), end_i = m_snps.end() ;
+		for( ; snp_i != end_i; ++snp_i ) {
+			std::vector< OptionalSnpMatch > const& indices = snp_i->second ;
+			std::vector< bool > indicator( indices.size(), false ) ;
+			for( std::size_t i = 0; i < indices.size(); ++i ) {
+				indicator[i] = bool( indices[i] ) ;
+			}
+			++m_category_counts[ indicator ] ;
+		}
+	}
+
+	void unsafe_process( appcontext::UIContext& ui_context ) {
+		Eigen::MatrixXd cohort_counts( 4, m_cohorts.size() ) ;
+		Eigen::MatrixXd cohort_betas( 2, m_cohorts.size() ) ;
+		Eigen::MatrixXd cohort_ses( 2, m_cohorts.size() ) ;
+		Eigen::VectorXd non_missingness( m_cohorts.size() ) ;
+
+		{
+			appcontext::UIContext::ProgressContext progress_context = ui_context.get_progress_context( "Storing meta-analysis results" ) ;
+			SnpMap::const_iterator snp_i = m_snps.begin() ;
+			SnpMap::const_iterator const end_i = m_snps.end() ;
+			for( std::size_t snp_index = 0; snp_i != end_i; ++snp_i, ++snp_index ) {
+				std::vector< OptionalSnpMatch > const& indices = snp_i->second ;
+				DataGetter data_getter( m_cohorts, indices ) ;
+				if( m_output_all_variants || data_getter.has_useful_data() ) {
+					for( std::size_t i = 0; i < m_computations.size(); ++i ) {
+						m_computations[i](
+							data_getter,
+							boost::bind(
+								boost::ref( m_result_signal ),
+								snp_i->first,
+								_1, _2
+							)
+						) ;
+					}
+				}
+
+				progress_context( snp_index + 1, m_snps.size() ) ;
+			}
+		}
+	}
+} ;
+
+
+struct BingwaApplication: public appcontext::ApplicationContext {
+public:
+	typedef std::map< std::string, std::vector< std::string > > GroupDefinition ;
+	typedef std::map< std::string, std::vector< std::string > > ValueListSet ;
+	typedef std::map< std::string, ValueListSet > SetOfValueListSets ;
+	typedef std::set< std::string > PriorNames ;
+	typedef std::map< std::string, double > PriorWeights ;
+	enum { eBetweenPopulationCorrelation = 0, eSD = 1, eCorrelation = 2 } ;
+	typedef boost::tuple< std::vector< std::string >, std::vector< std::string >, std::vector< std::string > > CovarianceSpec ;
+	typedef std::vector< CovarianceSpec > CovarianceSpecs ;
+	typedef std::pair< CovarianceSpec, Eigen::MatrixXd > Prior ;
+	typedef std::multimap< std::string, Prior > Priors ;
+
+public:
+	BingwaApplication( int argc, char **argv ):
+		appcontext::ApplicationContext(
+			globals::program_name,
+			globals::program_version,
+			std::auto_ptr< appcontext::OptionProcessor >( new BingwaOptions ),
+			argc,
+			argv,
+			"-log"
+		),
+		m_processor( BingwaProcessor::create( genfile::VariantIdentifyingData::CompareFields( options().get< std::string > ( "-snp-match-fields" )) ) )
+	{
+		if( options().check( "-flip-alleles" )) {
+			m_processor->set_flip_alleles() ;
+		}
+		if( options().check( "-output-all-variants" )) {
+			m_processor->set_output_all_variants() ;
+		}
+	}
+	
+	void run() {
+		try {
+			unsafe_run() ;
+		}
+		catch( genfile::InputError const& e ) {
+			ui().logger() << "!! Error (" << e.what() << "): " << e.format_message() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::FileNotFoundError const& e ) {
+			ui().logger() << "!! Error: No file matching \"" << e.filespec() << "\" could be found.\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::OperationFailedError const& e ) {
+			ui().logger() << "!! Error: operation failed: " << e.get_message() << "\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::db::Error const& e ) {
+			ui().logger() << "!! Database error (" << e.what() << "): " << e.description() << ".\n" ;
+			ui().logger() << "!! Error code is " << e.error_code() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( appcontext::OptionProcessingException const& e ) {
+			ui().logger() << "!! Option error (" << e.what() << "): " << e.message() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( statfile::InvalidColumnNameError const& e ) {
+			ui().logger() << "!! Column name \"" << e.name() << "\" was invalid.\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+	}
+
+	void unsafe_run() {
+		load_data() ;
+
+		m_processor->setup( ui() ) ;
+		m_processor->summarise( ui() ) ;
+		
+		qcdb::MultiTableStorage::SharedPtr storage ;
+		
+		if( impl::get_output_filetype( options().get< std::string >( "-o" )) == "sqlite" ) {
+			std::vector< std::string > elts = impl::parse_sqlite_filespec( options().get< std::string >( "-o" ) ) ;
+			assert( elts.size() > 0 ) ;
+			boost::optional< genfile::db::Connection::RowId > analysis_id ;
+			if( options().check( "-analysis-id" )) {
+				analysis_id = options().get< genfile::db::Connection::RowId >( "-analysis-id" ) ;
+			}
+			qcdb::MultiTableDBOutputter::SharedPtr table_storage = qcdb::MultiTableDBOutputter::create_shared(
+				"file:" + elts[0] + "?nolock=1",
+				options().get< std::string >( "-analysis-name" ),
+				options().get< std::string >( "-analysis-chunk" ),
+				options().get_values_as_map(),
+				options().get< std::string >( "-snp-match-fields" ),
+				analysis_id
+			) ;
+			table_storage->set_record_alternative_identifiers( !options().check( "-no-identifiers") ) ;
+			storage = table_storage ;
+		} else {
+			storage = qcdb::MultiFileOutputter::create_shared(
+				options().get< std::string >( "-o" ),
+				options().get< std::string >( "-analysis-name" ),
+				options().get_values_as_map()
+			) ;
+		}
+
+		m_processor->send_results_to(
+			boost::bind(
+				&qcdb::MultiTableStorage::store_per_variant_data,
+				storage,
+				_1, _2, _3
+			)
+		) ;
+
+		std::vector< std::string > cohort_names ;
+		if( options().check( "-cohort-names" )) {
+			cohort_names = options().get_values< std::string >( "-cohort-names" ) ;
+			if( cohort_names.size() != options().get_values< std::string >( "-data" ).size() ) {
+				throw genfile::BadArgumentError(
+					"BingwaApplication::unsafe_run()", "-cohort-names=\"" + genfile::string_utils::join( cohort_names, " " ) + "\"",
+					"Number of cohort names does not match number of data files"
+				) ;
+			}
+		}
+		else {
+			cohort_names.resize( options().get_values< std::string >( "-data" ).size() ) ;
+			for( std::size_t i = 0; i < cohort_names.size(); ++i ) {
+				cohort_names[i] = "cohort " + genfile::string_utils::to_string( i + 1 ) ;
+			}
+		}
+
+		if( options().check( "-data" ) && options().get_values< std::string >( "-data" ).size() > 0 ) {
+			impl::VariableMap meta_variables ;
+			impl::VariableMap per_cohort_variables ;
+			impl::VariableMap extra_variables ;
+
+			{
+				bingwa::BingwaComputation::UniquePtr computation(
+					new bingwa::PerCohortValueReporter(
+						cohort_names,
+						m_cohort_constraint_variables,
+						!options().check( "-no-counts" )
+					)
+				) ;
+				computation->set_effect_parameter_names( m_processor->get_effect_parameter_names() ) ;
+				computation->get_variables( boost::bind( impl::insert_into_map< impl::VariableMap >, &per_cohort_variables, _1, _2 ) ) ;
+				m_processor->add_computation( "PerCohortValueReporter", computation ) ;
+			}
+
+			if( options().check( "-extra-columns" )) {
+				bingwa::BingwaComputation::UniquePtr computation(
+					new bingwa::PerCohortCountsReporter(
+						cohort_names,
+						m_cohort_variables
+					)
+				) ;
+				computation->set_effect_parameter_names( m_processor->get_effect_parameter_names() ) ;
+				computation->get_variables( boost::bind( impl::insert_into_map< impl::VariableMap >, &extra_variables, _1, _2 ) ) ;
+				m_processor->add_computation( "PerCohortCountsReporter", computation ) ;
+			}
+			if( options().check( "-no-meta-analysis" )) {
+				// No more computations.
+			}
+			else {
+				bingwa::BingwaComputation::Filter filter = get_filter( options() ) ;
+
+				// Prior sd and tau sets
+				if( options().check( "-define-sd-set" )) {
+					m_value_sets[ "sd" ] = parse_value_list( options().get_values< std::string >( "-define-sd-set" )) ;
+				} else {
+					m_value_sets[ "sd" ] ; // empty map
+				}
+
+				if( options().check( "-define-tau-set" )) {
+					m_value_sets[ "tau" ] = parse_value_list( options().get_values< std::string >( "-define-tau-set" )) ;
+				} else {
+					m_value_sets[ "tau" ] ; // empty map
+				}
+
+				// Per-cohort priors...
+				if( options().check( "-per-cohort-prior" )) {
+					Priors const priors = get_per_cohort_priors( options().get< std::string >( "-per-cohort-prior" ) ) ;
+					bingwa::PerCohortBayesFactor::UniquePtr bf = bingwa::PerCohortBayesFactor::create(
+						cohort_names,
+						bingwa::ModelSpec(
+							"per-cohort",
+							priors.begin(), priors.end(),
+							1.0
+						)
+					) ;
+					bf->get_variables( boost::bind( impl::insert_into_map< impl::VariableMap >, &meta_variables, _1, _2 ) ) ;
+					m_processor->add_computation(
+						"per-cohort",
+						bingwa::BingwaComputation::UniquePtr( bf.release() )
+					) ;
+				}
+		
+				{
+					bingwa::MultivariateFixedEffectMetaAnalysis::UniquePtr computation(
+						new bingwa::MultivariateFixedEffectMetaAnalysis( "FixedEffectMetaAnalysis" )
+					) ;
+					computation->set_effect_parameter_names( m_processor->get_effect_parameter_names() ) ;
+					computation->set_filter( filter ) ;
+					computation->get_variables( boost::bind( impl::insert_into_map< impl::VariableMap >, &meta_variables, _1, _2 ) ) ;
+					m_processor->add_computation(
+						"FixedEffectMetaAnalysis",
+						bingwa::BingwaComputation::UniquePtr( computation.release() )
+					) ;
+				}
+
+				if( options().check_if_option_was_supplied_in_group( "Bayesian meta-analysis options" ) ) {
+					Priors const priors = get_cross_cohort_priors( options(), cohort_names ) ;
+					PriorNames const prior_names = get_prior_names( priors ) ;
+					std::map< std::string, double > prior_weights = get_prior_weights( options(), prior_names ) ;
+					assert( priors.size() > 0 ) ;
+					{
+						double total_weight = 0 ;
+						for( std::map< std::string, double >::const_iterator i = prior_weights.begin(); i != prior_weights.end(); ++i ) {
+							total_weight += i->second ;
+						}
+						if( std::abs( total_weight - 1.0 ) > 1E-9 ) {
+							throw genfile::BadArgumentError(
+								"BingwaProcessor::unsafe_run()",
+								"-prior-weights",
+								( boost::format( "Specified weights sum to %f, not one." ) % total_weight ).str()
+							) ;
+						}
+					}
+					bingwa::ModelAveragingBayesFactorAnalysis::UniquePtr averager( new bingwa::ModelAveragingBayesFactorAnalysis ) ;
+					assert( priors.size() > 0 ) ;
+					{
+						PriorNames::const_iterator i = prior_names.begin() ;
+						PriorNames::const_iterator end_i = prior_names.end() ;
+						for( ; i != end_i; ++i ) {
+							averager->add_model(
+								bingwa::ModelAveragingBayesFactorAnalysis::ModelSpec(
+									*i,
+									priors.lower_bound( *i ),
+									priors.upper_bound( *i ),
+									prior_weights[ *i ]
+								)
+							) ;
+						}
+						averager->set_filter( filter ) ;
+					
+						averager->get_variables(
+							boost::bind( impl::insert_into_map< impl::VariableMap >, &meta_variables, _1, _2 )
+						) ;
+						
+						storage->add_meta_table(
+							options().get_value( "-table-prefix" ) + "Prior",
+							"default",
+							averager->get_models().size(),
+							boost::bind( &impl::get_model_names, averager->get_models(), _1 ),
+							boost::bind( &impl::get_model_weights, averager->get_models(), _1 )
+						) ;
+						
+						m_processor->add_computation(
+							"Average",
+							bingwa::BingwaComputation::UniquePtr( averager.release() )
+						) ;
+					}
+					summarise_priors( priors, prior_names, prior_weights, cohort_names ) ;
+				}
+				if( per_cohort_variables.size() > 0 ) {
+					storage->add_table(
+						options().get_value( "-table-prefix" ) + "PerCohort",
+						boost::bind( &impl::contains_variable, per_cohort_variables, _1 )
+					) ;
+				}
+				if( meta_variables.size() > 0 ) {
+					storage->add_table(
+						options().get_value( "-table-prefix" ) + "Meta",
+						boost::bind( &impl::contains_variable, meta_variables, _1 )
+					) ;
+				}
+				if( extra_variables.size() > 0 ) {
+#if DEBUG
+					std::cerr << "Extra variables are:\n" ;
+					for( impl::VariableMap::const_iterator j = extra_variables.begin(); j != extra_variables.end(); ++j ) {
+						std::cerr << "\"" << j->first << "\" -> \"" << j->second << "\".\n" ;
+					}
+#endif
+					storage->add_table(
+						options().get_value( "-table-prefix" ) + "Extra",
+						boost::bind( &impl::contains_variable, extra_variables, _1 )
+					) ;
+				}
+			}
+		}
+		
+		m_processor->get_variables(
+			boost::bind(
+				&qcdb::MultiTableStorage::add_variable,
+				storage,
+				_1, _2
+			)
+		) ;
+		
+		m_processor->process( ui() ) ;
+		
+		ui().logger() << "Finalising storage...\n" ;
+
+		long finalise_options = ( options().check( "-noindex" ) ? 0 : qcdb::eCreateIndices ) ;
+		storage->finalise( finalise_options ) ;
+	}
+	
+	bingwa::BingwaComputation::Filter get_filter( appcontext::OptionProcessor const& options ) const {
+		bingwa::BingwaComputation::Filter filter( &bingwa::impl::basic_trust_filter ) ;
+		return filter ;
+	}
+
+	void get_simple_priors(
+		int const number_of_cohorts,
+		std::vector< std::string > const& model_specs,
+		boost::optional< std::vector< std::string > > model_names,
+		Priors* result
+	) const {
+		using namespace genfile::string_utils ;
+		if( model_names && model_names.get().size() != model_specs.size() ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::get_simple_priors()",
+				"model_names=\"" + join( model_names.get(), " " ) + "\"",
+				"Wrong number of simple prior names specified (" +
+					to_string( model_names.get().size() )
+					+ ", should be " + to_string( model_specs.size() ) + ")"
+			) ;
+		}
+		
+		for( std::size_t i = 0; i < model_specs.size(); ++i ) {
+			std::string model_name ;
+			std::string model_spec ;
+			{
+				std::size_t const colon_pos = model_specs[i].find( ':' ) ;
+				assert( colon_pos != std::string::npos ) ;
+				if( colon_pos != std::string::npos ) {
+					model_name = model_specs[i].substr( 0, colon_pos ) ;
+					model_spec = model_specs[i].substr( colon_pos + 1, model_specs[i].size() ) ;
+				}
+			}
+			std::vector< CovarianceSpec > const covariance_specs = parse_covariance_spec( model_spec, m_value_sets ) ;
+
+#if DEBUG_BINGWA
+			std::cerr << "get_simple_priors(): for model " << model_spec << ", got " << covariance_specs.size() << " specs.\n" ;
+#endif
+
+			std::vector< uint32_t > cohort_masks ;
+			if( options().check( "-subsets" )) {
+				cohort_masks = compute_cohort_masks( number_of_cohorts, options().get< std::string >( "-subsets" )) ;
+			}
+
+			for( std::size_t j = 0; j < covariance_specs.size(); ++j ) {
+				CovarianceSpec const& covariance_spec = covariance_specs[j] ;
+				if( covariance_spec.get< eBetweenPopulationCorrelation >().size() > 0 ) {
+					if( cohort_masks.size() > 0 ) {
+						for( std::size_t mask_i = 0; mask_i < cohort_masks.size(); ++mask_i ) {
+							uint32_t const& mask = cohort_masks[mask_i] ;
+							std::string const mask_name = stringify_mask( number_of_cohorts, mask ) ;
+							get_uniform_population_prior(
+								number_of_cohorts,
+								model_specs[ i ],
+								covariance_spec,
+								model_name + ":" + mask_name,
+								result,
+								mask
+							) ;
+						}
+					} else {
+						get_uniform_population_prior(
+							number_of_cohorts,
+							model_specs[ i ],
+							covariance_spec,
+							model_name,
+							result,
+							uint32_t( 0xFFFFFFFFFFFFFFFF ) >> (32-number_of_cohorts)
+						) ;
+					}
+				} else {
+					get_all_population_prior(
+						number_of_cohorts,
+						model_specs[ i ],
+						covariance_spec,
+						model_name,
+						result
+					) ;
+				}
+			}
+		}
+	}
+
+	std::vector< uint32_t > compute_cohort_masks( std::size_t const number_of_cohorts, std::string const& type ) const {
+		assert( number_of_cohorts <= 16 ) ;
+		assert( type == "all" || type == "contiguous" ) ;
+		if( type == "all" ) {
+			return compute_all_subset_masks( number_of_cohorts ) ;
+		} else if( type == "contiguous" ) {
+			return compute_contiguous_subset_masks( number_of_cohorts ) ;
+		} else {
+			assert(0) ;
+		}
+	}
+
+	std::string stringify_mask( std::size_t const number_of_cohorts, uint32_t mask ) const {
+		std::string result( number_of_cohorts, ' ' ) ;
+		for( std::size_t bit = 0; bit < number_of_cohorts; ++bit ) {
+			result[bit] = (( mask >> bit ) & 0x1 ) ? '1' : '0' ;
+		}
+		return result ;
+	}
+
+	std::vector< uint32_t > compute_all_subset_masks( std::size_t const number_of_cohorts ) const {
+		std::vector< uint32_t > result ;
+		uint32_t const max = uint32_t( 0xFFFFFFFF ) >> (32-number_of_cohorts) ;
+		std::string maskStr( number_of_cohorts, '.' ) ;
+		for( uint32_t mask = 0x1 ; mask <= max; ++mask ) {
+			result.push_back( mask ) ;
+		}
+		return result ;
+	}
+
+	std::vector< uint32_t > compute_contiguous_subset_masks( std::size_t const number_of_cohorts ) const {
+		std::vector< uint32_t > result ;
+		std::string maskStr( number_of_cohorts, '.' ) ;
+		for( std::size_t nBits = 1; nBits <= number_of_cohorts; ++nBits ) {
+			for( std::size_t pos = 0; pos <= number_of_cohorts-nBits; ++pos ) {
+				uint32_t mask = (uint32_t( 0xFFFFFFFFFFFFFFFF ) >> (32 - nBits)) << pos ;
+				result.push_back( mask ) ;
+			}
+		}
+		return result ;
+	}
+
+	std::string format_covariance_spec( CovarianceSpec const& covariance_spec ) const {
+		std::string result ;
+		if( covariance_spec.get<eBetweenPopulationCorrelation>().size() > 0 ) {
+			result += "tau=" ;
+			for( std::size_t j = 0; j < covariance_spec.get<eBetweenPopulationCorrelation>().size(); ++j ) {
+				result += (j>0 ? "," : "" ) + covariance_spec.get<eBetweenPopulationCorrelation>()[j] ;
+			}
+		}
+		if( covariance_spec.get<eSD>().size() > 0 ) {
+			result += "/sd=" ;
+			for( std::size_t j = 0; j < covariance_spec.get<eSD>().size(); ++j ) {
+				result += (j>0 ? "," : "" ) + covariance_spec.get<eSD>()[j] ;
+			}
+		}
+		if( covariance_spec.get<eCorrelation>().size() > 0 ) {
+			result += "/cor=" ;
+			for( std::size_t j = 0; j < covariance_spec.get<eCorrelation>().size(); ++j ) {
+				result += (j>0 ? "," : "" ) + covariance_spec.get<eCorrelation>()[j] ;
+			}
+		}
+		return result ;
+	}
+
+	double parse_sd( std::string sd_spec ) const {
+		using namespace genfile::string_utils ;
+		std::size_t pos = sd_spec.find( '*' ) ;
+		double factor = 1.0 ;
+		if( pos != std::string::npos ) {
+			factor = to_repr< double >( sd_spec.substr( 0, pos )) ;
+			++pos ;
+		} else {
+			pos = 0 ;
+			factor = 1.0 ;
+		}
+		return factor * to_repr< double >( sd_spec.substr( pos, sd_spec.size() - pos )) ;
+	}
+
+	void get_uniform_population_prior(
+		int const number_of_cohorts,
+		std::string const& model_spec,
+		CovarianceSpec const& covariance_spec,
+		std::string model_name,
+		Priors* result,
+		uint32_t const cohort_mask
+	) const {
+		using namespace genfile::string_utils ;
+#if DEBUG_BINGWA
+		std::cerr << format_covariance_spec( covariance_spec ) ;
+#endif
+
+		assert( cohort_mask <= uint32_t( 0xFFFFFFFFFFFFFFFF ) >> (32-number_of_cohorts) ) ;
+
+		try {
+			if( covariance_spec.get<eBetweenPopulationCorrelation>().size() != 1 ) {
+				throw genfile::BadArgumentError(
+					"BingwaProcessor::get_simple_priors()",
+					"model_spec=\"" + model_spec + "\"",
+					"In model spec \"" + model_spec + "\", number of correlations specified ("
+					+ to_string( covariance_spec.get<eBetweenPopulationCorrelation>().size() )
+					+ ") is not 1"
+				) ;
+			}
+			if( int( covariance_spec.get<eSD>().size() ) != m_processor->get_number_of_effect_parameters() ) {
+				throw genfile::BadArgumentError(
+					"BingwaProcessor::get_simple_priors()",
+					"model_spec=\"" + model_spec + "\"",
+					"In model spec \"" + model_spec + "\", number of sds specified ("
+					+ to_string( covariance_spec.get<eSD>().size() )
+					+ ") does not match number of effect size parameters (" + to_string( m_processor->get_number_of_effect_parameters() ) + ")"
+				) ;
+			}
+
+			{
+				int const N = m_processor->get_number_of_cohorts() ;
+				int const D = m_processor->get_number_of_effect_parameters() ;
+				Eigen::MatrixXd correlation = Eigen::MatrixXd::Zero( N * D, N * D ) ;
+
+				// We start by computing the correlation matrix.
+				// Prior is layed out in order of parameter (not cohort).
+				// Thus the first NxN block is for the first effect size parameter.
+				// We start with the diagonal blocks.  These do not involve the between-parameter correlation.
+				for( int block_i = 0; block_i < D; ++block_i ) {
+					correlation.block( block_i * N, block_i * N, N, N ) = get_prior_matrix(
+						number_of_cohorts,
+						to_repr< double >( covariance_spec.get<eBetweenPopulationCorrelation>()[0] ),
+						1
+					) ;
+				}
+				// ...and move on to the off-diagonal blocks which involve between-cohort and between-parameter correlation.
+				// We compute this using the diagonal block
+				int c = 0 ;
+				for( int block_i = 0; block_i < D; ++block_i ) {
+					if( covariance_spec.get<eCorrelation>()[ c++ ] != "1" ) {
+						throw genfile::BadArgumentError(
+							"BingwaProcessor::get_simple_priors()",
+							"model_spec=\"" + model_spec + "\"",
+							"Between-parameter correlation matrix must have 1's on diagonal"
+						) ;
+					}
+					for( int block_j = block_i + 1; block_j < D; ++block_j, ++c ) {
+						correlation.block( block_i * N, block_j * N, N, N ).array()
+							= get_prior_matrix(
+								number_of_cohorts,
+								to_repr< double >( covariance_spec.get<eBetweenPopulationCorrelation>()[0] ),
+								1
+							) * to_repr< double >( covariance_spec.get<eCorrelation>()[c] ) ;
+						;
+						correlation.block( block_j * N, block_i * N, N, N ) = correlation.block( block_i * N, block_j * N, N, N ) ;
+					}
+				}
+
+				Eigen::VectorXd sd_matrix( N * D ) ;
+				for( int block_i = 0; block_i < D; ++block_i ) {
+					sd_matrix.segment( block_i * N, N ).setConstant( parse_sd( covariance_spec.get<eSD>()[block_i] ) ) ;
+				}
+				// Deal with masked populations here.
+				for( int population_i = 0; population_i < N; ++population_i ) {
+					if( ((cohort_mask >> population_i) & 0x1 ) == 0 ) {
+						for( int block_i = 0; block_i < D; ++block_i ) {
+							sd_matrix( block_i*N + population_i ) = 0 ;
+						}
+					}
+				}
+				Eigen::MatrixXd const covariance = sd_matrix.asDiagonal() * correlation * sd_matrix.asDiagonal() ;
+
+				result->insert( std::make_pair( model_name, std::make_pair( covariance_spec, covariance ) )) ;
+				
+#if DEBUG_BINGWA
+				std::cerr << "For model " << model_name << ":\n"
+					<< "correlation =\n" << correlation << "\n"
+					<< "covariance = \n" << covariance << "\n" ;
+#endif
+			}
+		}
+		catch( StringConversionError const& e ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::get_simple_priors()",
+				"model_spec=\"" + model_spec + "\"",
+				"Expected a numerical value."
+			) ;
+		}
+	}
+
+	void get_all_population_prior(
+		int const number_of_cohorts,
+		std::string const& model_spec,
+		CovarianceSpec const& covariance_spec,
+		std::string model_name,
+		Priors* result
+	) const {
+		using namespace genfile::string_utils ;
+
+		int const N = m_processor->get_number_of_cohorts() ;
+		int const D = m_processor->get_number_of_effect_parameters() ;
+		int const dimension = N*D ;
+
+#if DEBUG_BINGWA
+		std::cerr << format_covariance_spec( covariance_spec ) << std::endl ;
+#endif
+
+		try {
+			if( covariance_spec.get<eBetweenPopulationCorrelation>().size() != 0 ) {
+				throw genfile::BadArgumentError(
+					"BingwaProcessor::get_all_population_prior()",
+					"model_spec=\"" + model_spec + "\"",
+					"In model spec \"" + model_spec + "\", number of between-cohort correlations specified ("
+					+ to_string( covariance_spec.get<eBetweenPopulationCorrelation>().size() )
+					+ ") is not 0"
+				) ;
+			}
+			if( int( covariance_spec.get<eSD>().size() ) != dimension ) {
+				throw genfile::BadArgumentError(
+					"BingwaProcessor::get_all_population_prior()",
+					"model_spec=\"" + model_spec + "\"",
+					"In model spec \"" + model_spec + "\", number of sds specified ("
+					+ to_string( covariance_spec.get<eSD>().size() )
+					+ ") does not match number of effect size parameters (" + to_string( dimension ) + ")"
+				) ;
+			}
+
+			std::size_t const numberOfCorrelations = ( dimension * ( dimension + 1 ) / 2 ) ;
+			if( int( covariance_spec.get<eCorrelation>().size() ) != numberOfCorrelations ) {
+				throw genfile::BadArgumentError(
+					"BingwaProcessor::get_all_population_prior()",
+					"model_spec=\"" + model_spec + "\"",
+					"In model spec \"" + model_spec + "\", number of correlations specified ("
+					+ to_string( covariance_spec.get<eCorrelation>().size() )
+					+ ") does not match number of effect size parameters (" + to_string( numberOfCorrelations ) + ")"
+				) ;
+			}
+
+			{
+				Eigen::MatrixXd correlation = Eigen::MatrixXd::Zero( dimension, dimension ) ;
+				// We start by parsing the correlation matrix into the matrix.
+				for( int c = 0, i = 0; i < correlation.rows(); ++i ) {
+					for( int j = i; j < correlation.cols(); ++j, ++c ) {
+						correlation(i,j) = to_repr< double >( covariance_spec.get<eCorrelation>()[c] ) ;
+						if( j > i ) {
+							correlation(j,i) = correlation(i,j) ;
+						}
+					}
+				}
+
+				Eigen::VectorXd sd_vector( dimension ) ;
+				for( int i = 0; i < dimension; ++i ) {
+					sd_vector(i) = parse_sd( covariance_spec.get<eSD>()[ i ] ) ;
+				}
+
+				Eigen::MatrixXd const covariance = sd_vector.asDiagonal() * correlation * sd_vector.asDiagonal() ;
+
+				result->insert( std::make_pair( model_name, std::make_pair( covariance_spec, covariance ) ) ) ;
+				
+#if DEBUG_BINGWA
+				std::cerr << "For model " << model_name << ":\n"
+					<< "correlation =\n" << correlation << "\n"
+					<< "covariance = \n" << covariance << "\n" ;
+#endif
+			}
+		}
+		catch( StringConversionError const& e ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::get_full_prior()",
+				"model_spec=\"" + model_spec + "\"",
+				"Expected a numerical value."
+			) ;
+		}
+	}
+	
+	std::vector< std::string > get_group_members( std::string const& group_name, GroupDefinition const& groups ) const {
+		GroupDefinition::const_iterator where = groups.find( group_name ) ;
+		if( where == groups.end() ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::get_group_members()",
+				"group_name=\"" + group_name + "\"",
+				"Group name \"" + group_name + "\" is not recognised, please define cohort groups using -groups."
+			) ;
+		}
+		return where->second ;
+	}
+	
+	std::vector< int > get_cohort_indices( std::vector< std::string > cohorts, std::vector< std::string > const& all_cohorts ) const {
+		std::vector< int > result( cohorts.size() ) ;
+		for( std::size_t k = 0; k < cohorts.size(); ++k ) {
+			std::vector< std::string >::const_iterator const cohort_i = std::find( all_cohorts.begin(), all_cohorts.end(), cohorts[k] ) ;
+			if( cohort_i == all_cohorts.end() ) {
+				throw genfile::BadArgumentError(
+					"BingwaProcessor::get_cohort_indices()",
+					"cohort=\"" + cohorts[k] + "\"",
+					"\"" + cohorts[k] + "\" is not a cohort name."
+				) ;
+			}
+			result[k] = int( cohort_i - all_cohorts.begin() ) ;
+		}
+		return result ;
+	}
+	
+	std::vector< std::string > parse_tau( std::string const& spec ) {
+		using namespace genfile::string_utils ;
+		if( spec.substr( 0, 4 ) != "tau=" ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::parse_tau()",
+				"spec=\"" + spec + "\"",
+				"Parameter spec \"" + spec + "\" is malformed, should be of the form tau=[tau]/sd=[sd]."
+			) ;
+		}
+		return split_and_strip_discarding_empty_entries( spec.substr( 4, spec.size() ), " " ) ;
+	}
+
+	// Given a CovarianceSpec, expand each use of a name from the sets
+	//
+	template< int element >
+	std::vector< CovarianceSpec > expand(
+		CovarianceSpec const& covariance_spec,
+		std::map< std::string, std::vector< std::string > > const& sets
+	) const {
+		std::vector< CovarianceSpec > result ;
+		// currently we just expand sds according to the sets in sets.
+		std::vector< std::string > const& elements = covariance_spec.get< element >() ;
+		std::vector< std::string > set_names ;
+		std::vector< std::size_t > working_indices ;
+		for( std::map< std::string, std::vector< std::string > >::const_iterator i = sets.begin(); i != sets.end(); ++i ) {
+			working_indices.push_back( 0 ) ;
+			set_names.push_back( i->first ) ;
+#if DEBUG_BINGWA
+			std::cerr << "expand(): added set name " << set_names.back() << ".\n" ;
+#endif
+		}
+			
+		bool complete = false ;
+		while( !complete ) {
+			// construct the configuration
+			std::vector< std::string > these_elements = elements ;
+			for( std::size_t i = 0; i < set_names.size(); ++i ) {
+				std::string const set_name = set_names[i] ;
+				for( std::size_t j = 0; j < elements.size(); ++j ) {
+					these_elements[j] = genfile::string_utils::replace_all(
+						these_elements[j],
+						"[" + set_name + "]",
+						sets.find( set_name )->second.at( working_indices[ i ] )
+					) ;
+#if DEBUG_BINGWA
+					std::cerr << "...got \"" << these_elements[j] << "\".\n" ;
+#endif
+				}
+			}
+#if DEBUG_BINGWA
+			std::cerr << "expand(): these_elements =" ;
+			for( std::size_t k = 0; k < these_elements.size(); ++k ) {
+				std::cerr << " " << these_elements[k] ;
+			}
+			std::cerr << "\n" ;
+#endif
+			CovarianceSpec new_spec( covariance_spec ) ;
+			new_spec.get< element >() = these_elements ;
+			if( std::find( result.begin(), result.end(), new_spec ) == result.end() ) {
+				result.push_back( new_spec ) ;
+			}
+			
+			// move to next configuration of sds and taus.
+			// The rather ungainly code below steps through substitutable values of sds and then of taus in right-to-left order.
+			std::size_t k = 0 ;
+			for( ; k < set_names.size(); ++k ) {
+				std::size_t j = set_names.size() - k - 1 ;
+				std::string const set_name = set_names[j] ;
+				if( ++working_indices[j] == sets.find( set_name )->second.size() ) {
+					working_indices[j] = 0 ;
+				} else {
+					break ;
+				}
+			}
+			if( k == set_names.size() ) {
+				complete = true ;
+			}
+		}
+
+		return result ;
+	}
+	
+	template< int element >
+	std::vector< CovarianceSpec > expand(
+		std::vector< CovarianceSpec > const& covariance_specs,
+		std::map< std::string, std::vector< std::string > > const& sets
+	) const {
+		std::vector< CovarianceSpec > result ;
+		for( std::size_t i = 0; i < covariance_specs.size(); ++i ) {
+			std::vector< CovarianceSpec > const& this_result = expand< element >( covariance_specs[i], sets ) ;
+			result.insert( result.end(), this_result.begin(), this_result.end() ) ;
+		}
+		return result ;
+	}
+	
+	std::vector< CovarianceSpec > expand_taus_and_sds(
+		CovarianceSpec const& covariance_spec,
+		std::map< std::string, std::vector< std::string > > const& sd_sets,
+		std::map< std::string, std::vector< std::string > > const& tau_sets
+	) const {
+		std::vector< CovarianceSpec > result;
+		result = expand< eSD >( covariance_spec, sd_sets ) ;
+		result = expand< eBetweenPopulationCorrelation >( result, tau_sets ) ;
+		return result ;
+	}
+	
+	std::vector< CovarianceSpec > parse_covariance_spec( std::string const& spec, SetOfValueListSets const& value_sets ) const {
+		using namespace genfile::string_utils ;
+		std::vector< std::string > parameters = split_and_strip( spec, "/" ) ;
+
+		int const tau_index = (( parameters.size() > 0 ) && parameters[0].substr(0,4) == "tau=" ) ? 0 : -1 ;
+		int const sd_index = (( parameters.size() > (tau_index+1) ) && parameters[ tau_index+1 ].substr(0,3) == "sd=" ) ? (tau_index+1) : -1 ;
+		int const cor_index = (( parameters.size() > (sd_index+1) ) && parameters[ sd_index+1 ].substr(0,4) == "cor=" ) ? (sd_index+1) : -1 ;
+		bool have_tau = ( tau_index >= 0 ) ;
+		bool have_sd = ( sd_index >= 0 ) ;
+		bool have_cor = ( cor_index >= 0 ) ;
+
+#if DEBUG_BINGWA
+		std::cerr << ( boost::format( "parse_covariance_spec(): spec = %s, tau_index = %d, sd_index = %d, cor_index = %d\n" ) % spec % tau_index % sd_index % cor_index ) ;
+#endif		
+			
+		// Only sd is required.
+		if(
+			( parameters.size() < 1 || parameters.size() > 3 )
+			|| ( !have_sd )
+			|| ( parameters.size() == 2 && !( have_cor || have_tau ))
+			|| ( parameters.size() == 3 && !( have_cor && have_tau ) )
+		) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::parse_covariance_spec()",
+				"spec=\"" + spec + "\"",
+				"Parameter spec \"" + spec + "\" is malformed, should be of one of these forms:\n"
+				" - tau=[tau]/sd=[sd] for a multi-cohort prior with a single parameter\n"
+				" - tau=[tau]/sd=[sd1 sd1...]/cor=[cor12 cor13...] for a multi-cohort prior"
+				" - sd=[sd1 sd2...]/cor=[cor11 cor12 cor13...] for a single-cohort prior, or full multi-cohort prior"
+			) ;
+		}
+
+		std::vector< std::string > const taus = ( have_tau ? split_and_strip( parameters[ tau_index ].substr( 4, parameters[ tau_index ].size() ), "," ) : std::vector< std::string >() ) ;
+		std::vector< std::string > const sds = ( have_sd ? split_and_strip( parameters[ sd_index ].substr( 3, parameters[ sd_index ].size() ), "," ) : std::vector< std::string >() ) ;
+		std::vector< std::string > const cor = ( have_cor ? split_and_strip_discarding_empty_entries( parameters[ cor_index ].substr( 4, parameters[ cor_index ].size() ), "," ) : std::vector< std::string >() ) ;
+
+		if( sds.size() > 1 && !have_cor ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::parse_covariance_spec()",
+				"spec=\"" + spec + "\"",
+				"Parameter spec \"" + spec + "\" is malformed, you must supply cor= if there is more than one sd."
+			) ;
+		}
+
+		std::size_t const expectedNumberOfCorrelations = ( sds.size() * ( sds.size() + 1 ) ) / 2 ;
+		if( taus.size() > 1 ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::parse_covariance_spec()",
+				"spec=\"" + spec + "\"",
+				( boost::format( "Wrong number of taus (%d, should be at most %d)" ) % taus.size() % 1 ).str()
+			) ;
+		}
+		if( cor.size() != expectedNumberOfCorrelations ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::parse_covariance_spec()",
+				"spec=\"" + spec + "\"",
+				( boost::format( "Wrong number of correlations (%d, should be %d)" ) % cor.size() % expectedNumberOfCorrelations ).str()
+			) ;
+		}
+		
+		return expand_taus_and_sds(
+			CovarianceSpec( taus, sds, cor ),
+			value_sets.at( "sd" ),
+			value_sets.at( "tau" )
+		) ;
+	}
+
+	std::vector< CovarianceSpec > expand_taus_and_sds(
+		std::vector< std::string > taus,
+		std::vector< std::string > sds,
+		std::vector< std::string > cor,
+		std::map< std::string, std::vector< std::string > > const& sd_sets,
+		std::map< std::string, std::vector< std::string > > const& tau_sets
+	) const {
+		std::vector< CovarianceSpec > result ;
+		// currently we just expand sds according to the sets in sd_sets.
+		std::vector< std::string > working_sds = sds ;
+		std::vector< std::string > working_taus = taus ;
+		std::vector< std::size_t > working_sd_indices( sds.size(), 0 ) ;
+		std::vector< std::size_t > working_tau_indices( taus.size(), 0 ) ;
+
+		bool complete = false ;
+		while( !complete ) {
+			// construct this configuration
+			for( std::size_t j = 0; j < sds.size(); ++j ) {
+				std::string spec = sds[j] ;
+				if( spec.size() > 0 ) {
+					std::size_t pos = spec.find( '[' ) ;
+					if( pos != std::string::npos ) {
+						std::size_t end_pos = spec.find( ']', pos + 1 ) ;
+						if( end_pos != std::string::npos ) {
+							std::map< std::string, std::vector< std::string > >::const_iterator where
+								= sd_sets.find( spec.substr( pos+1, end_pos - pos - 1 ) ) ;
+							if( where != sd_sets.end() ) {
+								spec.replace( pos, end_pos - pos + 1, where->second.at( working_sd_indices[j] ) ) ;
+								working_sds[ j ] = spec ;
+							}
+						}
+					}
+				}
+			}
+			for( std::size_t j = 0; j < taus.size(); ++j ) {
+				if( taus[j].size() > 0 && taus[j][0] == '[' && taus[j][taus[j].size() - 1] == ']' ) {
+					std::map< std::string, std::vector< std::string > >::const_iterator where
+						= tau_sets.find( taus[j].substr( 1, taus[j].size() - 2 ) ) ;
+					if( where != tau_sets.end() ) {
+						working_taus[ j ] = where->second.at( working_tau_indices[j] ) ;
+					}
+				}
+			}
+			result.push_back( boost::make_tuple( working_taus, working_sds, cor ) ) ;
+			
+			// move to next configuration of sds and taus.
+			// The rather ungainly code below steps through substitutable values of sds and then of taus in right-to-left order.
+			std::size_t k = 0 ;
+			for( ; k < sds.size(); ++k ) {
+				std::size_t j = sds.size() - k - 1 ;
+				if( sds[j].size() > 1 && sds[j][0] == '[' && sds[j][sds[j].size() - 1] == ']' ) {
+					std::map< std::string, std::vector< std::string > >::const_iterator where = sd_sets.find( sds[j].substr( 1, sds[j].size() - 2 ) ) ;
+					if( where != sd_sets.end() ) {
+						working_sd_indices[ j ] = ( working_sd_indices[ j ] + 1 ) % where->second.size() ;
+						if( working_sd_indices[ j ] > 0 ) {
+							break ;
+						}
+					}
+				}
+			}
+			if( k == sds.size() ) {
+				// No more sds to substitute, so move on to taus...
+				std::size_t k_tau = 0 ;
+				for( ; k_tau < taus.size(); ++k_tau ) {
+					std::size_t j = taus.size() - k_tau - 1 ;
+					if( taus[j].size() > 1 && taus[j][0] == '[' && taus[j][taus[j].size() - 1] == ']' ) {
+						std::map< std::string, std::vector< std::string > >::const_iterator where = tau_sets.find( taus[j].substr( 1, taus[j].size() - 2 ) ) ;
+						if( where != tau_sets.end() ) {
+							working_tau_indices[ j ] = ( working_tau_indices[ j ] + 1 ) % where->second.size() ;
+							if( working_tau_indices[ j ] > 0 ) {
+								break ;
+							}
+						}
+					}
+				}
+				if( k_tau == taus.size() ) {
+					complete = true ;
+				}
+			}
+		}
+
+		return result ;
+	}
+
+	Priors get_per_cohort_priors( std::string model_spec ) {
+		using genfile::string_utils::to_string ;
+		Priors result ;
+		std::vector< CovarianceSpec > const covariance_specs = parse_covariance_spec( model_spec, m_value_sets ) ;
+
+		int const D = m_processor->get_number_of_effect_parameters() ;
+
+		std::vector< std::pair< std::string, Prior > > components ;
+		for( std::size_t i = 0; i < covariance_specs.size(); ++i ) {
+			CovarianceSpec const& covariance_spec = covariance_specs[i] ;
+			if( int( covariance_spec.get<eBetweenPopulationCorrelation>().size() ) != 0 ) {
+				throw genfile::BadArgumentError(
+					"BingwaProcessor::get_per_cohort_prior()",
+					"model_spec=\"" + model_spec + "\"",
+					"In model spec \"" + model_spec + "\", you can't specify between-cohort correlation in a per-cohort prior."
+				) ;
+			}
+			if( int( covariance_spec.get<eSD>().size() ) != D ) {
+				throw genfile::BadArgumentError(
+					"BingwaProcessor::get_per_cohort_prior()",
+					"model_spec=\"" + model_spec + "\"",
+					"In model spec \"" + model_spec + "\", number of sds specified ("
+					+ to_string( covariance_spec.get<eSD>().size() )
+					+ ") does not match number of effect size parameters (" + to_string( D ) + ")"
+				) ;
+			}
+			
+			Eigen::MatrixXd const covariance = parse_covariance_matrix( covariance_specs[i].get< eSD >(), covariance_specs[i].get< eCorrelation >() ) ;
+			result.insert(
+				std::make_pair(
+					"per-cohort",
+					Prior( covariance_spec, covariance )
+				)
+			) ;
+		}
+		return result ;
+	}
+
+	Priors get_cross_cohort_priors(
+		appcontext::OptionProcessor const& options,
+		std::vector< std::string > const& cohort_names
+	) {
+		Priors result ;
+		using genfile::string_utils::to_string ;
+		using genfile::string_utils::to_repr ;
+		using genfile::string_utils::split_and_strip_discarding_empty_entries ;
+		int const N = options.get_values< std::string >( "-data" ).size() ;
+		
+		{
+			std::vector< std::string > model_specs ;
+			if( options.check( "-prior" ) ) {
+				model_specs = options.get_values< std::string >( "-prior" ) ;
+			} else if( options.check( "-prior-file" ) ) {
+				model_specs = parse_prior_spec_file( options.get< std::string >( "-prior-file" ) ) ;
+			}
+			if( model_specs.size() > 0 ) {
+				boost::optional< std::vector< std::string > > model_names ;
+				get_simple_priors(
+					N,
+					model_specs,
+					model_names,
+					&result
+				) ;
+			}
+		}
+		if( options.check( "-subset-prior" )) {
+			
+		}
+		
+
+		return result ;
+	}
+
+	ValueListSet parse_value_list( std::vector< std::string > const& spec ) const {
+
+		using namespace genfile::string_utils ;
+		std::map< std::string, std::vector< std::string > > result ;
+		for( std::size_t i = 0; i < spec.size(); ++i ) {
+			std::vector< std::string > elts = split_and_strip_discarding_empty_entries( spec[i], "=", " \t" ) ;
+			if( elts.size() != 2 ) {
+				throw genfile::BadArgumentError(
+					"BingwaApplication::parse_value_list()",
+					"spec=\"" + spec[i] + "\"",
+					"expected specification of the form \"[set name]=[value],[value],[value],...\"."
+				) ;
+			}
+			std::vector< std::string > sds = split_and_strip_discarding_empty_entries( elts[1], ",", " \t" ) ;
+			
+			// These must be numbers!  Check we can parse them
+			for( std::size_t j = 0; j < sds.size(); ++j ) {
+				try {
+					to_repr< double >( sds[j] ) ;
+				}
+				catch( StringConversionError const& e ) {
+					throw genfile::BadArgumentError(
+						"BingwaApplication::parse_value_list()",
+						"spec=\"" + spec[i] + "\"",
+						"found non-numerical values in value list."
+					) ;
+				}
+			}
+			
+			result[ elts[0] ] = sds ;
+		}
+		
+#if DEBUG_BINGWA
+			std::map< std::string, std::vector< std::string > >::const_iterator
+				i = result.begin(),
+				end_i = result.end() ;
+			std::cerr << "BingwaApplication::parse_value_list(): parsed value lists:\n" ;
+			for( ; i != end_i; ++i ) {
+				std::cerr << i->first << ": " ;
+				for( std::size_t j = 0; j < i->second.size(); ++j ) {
+					std::cerr << "\"" << i->second[j] << "\" " ;
+				}
+				std::cerr << "\n" ;
+			}
+#endif
+		
+		return result ;
+	}
+
+	std::vector< std::string > parse_prior_spec_file( std::string const& filename ) const {
+		std::auto_ptr< std::istream > file = genfile::open_text_file_for_input( filename ) ;
+		std::vector< std::string > result ;
+		std::string line ;
+		std::string spec ;
+		std::size_t lineCount = 0 ;
+		for( ; std::getline( *file, line ); ++lineCount ) {
+			line = genfile::string_utils::strip( line, " \t\r\n" ) ;
+			// spec ends on a blank line or a line that starts with a non-numeric character
+			if( line.size() > 0 && line[0] == '#' ) {
+				// ignore this line
+			} else {
+				// a spec ends on a blank line or current spec doesn't end on a continuation mark
+				if( line.size() == 0 || ( spec.size() > 0 && spec[spec.size()-1] != ':' && spec[spec.size()-1] != '/' && spec[spec.size()-1] != ',' ) ) {
+					if( spec.size() > 0 ) {
+						std::cerr << "Read " << lineCount << " lines, adding spec \"" << spec << "\".\n" ;
+						result.push_back( spec ) ;
+						spec = "" ;
+					}
+				}
+				spec += line ;
+			}
+		}
+		if( spec != "" ) {
+			result.push_back( spec ) ;
+		}
+		return result ;
+	}
+
+	Eigen::MatrixXd get_prior_matrix( int const n, double const tau, double const sd ) const {
+		return get_correlation_matrix( n, tau ) * sd * sd ;
+	}
+
+	Eigen::MatrixXd get_correlation_matrix( int const n, double tau ) const {
+		Eigen::MatrixXd result = Eigen::MatrixXd::Identity( n, n ) ;
+		for( int i = 0; i < (n-1); ++i ) {
+			for( int j = (i+1); j < n; ++j ) {
+				result( i, j ) = result( j, i ) = tau ;
+			}
+		}
+		return result ;
+	}
+
+	Eigen::MatrixXd parse_covariance_matrix(
+		std::vector< std::string > const sd_spec,
+		std::vector< std::string > const& correlation_spec
+	) const {
+		using namespace genfile::string_utils ;
+		int const N = sd_spec.size() ;
+		Eigen::MatrixXd result = parse_correlation_matrix( N, correlation_spec ) ;
+		Eigen::MatrixXd sds = Eigen::MatrixXd::Identity( N, N ) ;
+		for( std::size_t i = 0; i < sd_spec.size(); ++i ) {
+			sds(i,i) = to_repr< double >( sd_spec[i] ) ;
+		}
+		result = sds * result * sds ;
+		return result ;
+	}
+
+	Eigen::MatrixXd parse_correlation_matrix( int const N, std::vector< std::string > const& correlations ) const {
+		using namespace genfile::string_utils ;
+		Eigen::MatrixXd result = Eigen::MatrixXd::Zero( N, N ) ;
+		if( correlations.size() != (( N * (N+1) ) / 2 ) ) {
+			throw genfile::BadArgumentError(
+				"BingwaProcessor::parse_correlation_matrix()",
+				"matrix_spec=\"" + join( correlations, "," ) + "\"",
+				"Number of values (" + to_string( correlations.size() ) + ") is not consistent with the upper triangle of an "
+					+ to_string(N) + "x" + to_string(N) + " matrix (should be " + to_string( ( N * (N+1) ) / 2 ) + ")"
+			) ;
+		}
+
+		{
+			int index = 0 ;
+			for( int i = 0; i < N; ++i ) {
+				for( int j = 0; j < N; ++j ) {
+					result( i, j )
+						= ( j >= i ) ?
+							genfile::string_utils::to_repr< double >( correlations[ index++ ] )
+							:
+							result( j, i ) ;
+				}
+			}
+		}
+		return result ;
+	}
+
+	PriorNames get_prior_names( Priors const& priors ) const {
+		PriorNames result ;
+		{
+			Priors::const_iterator i = priors.begin() ;
+			Priors::const_iterator const end_i = priors.end() ;
+			for( ; i != end_i; ++i ) {
+				result.insert( i->first ) ;
+			}
+		}
+		return result ;
+	}
+
+	PriorWeights get_prior_weights( appcontext::OptionProcessor const& options, PriorNames const& prior_names ) const {
+		using namespace genfile::string_utils ;
+		PriorWeights result ;
+		// Initialise with weight=0 for all priors.
+		
+		if( options.check( "-prior-weights" )) {
+			{
+				PriorNames::const_iterator i = prior_names.begin() ;
+				PriorNames::const_iterator const end_i = prior_names.end() ;
+				for( ; i != end_i; ++i ) {
+					result[ *i ] = 0 ;
+				}
+			}
+
+			std::vector< std::string > const weight_specs = options.get_values< std::string >( "-prior-weights" ) ;
+			for( std::size_t j = 0; j < weight_specs.size(); ++j ) {
+				std::vector< std::string > weight_spec ;
+				if( boost::filesystem::exists( weight_specs[j] )) {
+					std::ifstream str( weight_specs[j].c_str() ) ;
+					std::copy( std::istream_iterator< std::string >( str ), std::istream_iterator< std::string >(), std::back_inserter< std::vector< std::string > >( weight_spec )) ;
+				} else {
+					weight_spec.push_back( weight_specs[j] ) ;
+				}
+				for( std::size_t i = 0; i < weight_spec.size(); ++i ) {
+					std::vector< std::string > elts = split_and_strip_discarding_empty_entries( weight_spec[i], "=", " \t\r\n" ) ;
+					if( elts.size() != 2 ) {
+						throw genfile::BadArgumentError(
+							"BingwaApplication::get_prior_names()",
+							"-prior-weights " + join( weight_spec, " " ),
+							"Spec \"" + weight_spec[i] + "\" appears malformed.  It should be of the form <model name>=<weight>."
+						) ;
+					}
+					if( result.find( elts[0] ) == result.end() ) {
+						throw genfile::BadArgumentError(
+							"BingwaApplication::get_prior_names()",
+							"-prior-weights " + join( weight_spec, " " ),
+							"Spec \"" + weight_spec[i] + "\" refers to a model (\"" + elts[0] + "\") that has not been specified."
+						) ;
+					}
+					try {
+						double weight = to_repr< double >( elts[1] ) ;
+						result[ elts[0] ] = weight ;
+					} catch( StringConversionError const& e ) {
+						throw genfile::BadArgumentError(
+							"BingwaApplication::get_prior_names()",
+							"-prior-weights " + join( weight_spec, " " ),
+							"In spec \"" + weight_spec[i] + ", the weight appears malformed."
+						) ;
+					}
+				}
+			}
+		} else {
+			PriorNames::const_iterator i = prior_names.begin() ;
+			PriorNames::const_iterator const end_i = prior_names.end() ;
+			for( ; i != end_i; ++i ) {
+				result[ *i ] = 1.0 / prior_names.size() ;
+			}
+		}
+		return result ;
+	}
+
+	void summarise_priors(
+		Priors const& priors,
+		PriorNames const& prior_names,
+		PriorWeights const& prior_weights,
+		std::vector< std::string > const& cohort_names
+	) const {
+		ui().logger() << "\n================================================\n" ;
+		ui().logger() << "I will output the following bayesian models:\n\n" ;
+
+		ui().logger() << std::setprecision( 3 ) ;
+		
+		std::size_t max_model_name_width = 0 ;
+		{
+			PriorNames::const_iterator
+				name_i = prior_names.begin(),
+				end_name_i = prior_names.end() ;
+			for( ; name_i != end_name_i; ++name_i ) {
+				max_model_name_width = std::max( max_model_name_width, name_i->size() + 2 ) ;
+			}
+		}
+
+		bingwa::EffectParameterNamePack const& parameter_names = m_processor->get_effect_parameter_names() ;
+		int const D = parameter_names.size() ;
+		int const N = cohort_names.size() ;
+
+		std::vector< std::size_t > column_widths( (D*N), 6 ) ;
+		std::size_t max_prefix_width = 6 ;
+		for( std::size_t i = 0; i < (D*N); ++i ) {
+			std::string const parameter_name = parameter_names.parameter_name( i / N ) ;
+			std::string const cohort_name = cohort_names[i % N] ;
+			column_widths[i] = 6ul ;//std::max( cohort_name.size() + parameter_name.size() + 2, 6ul ) ;
+			max_prefix_width = std::max( max_prefix_width, cohort_name.size() + parameter_name.size() + 7 ) ;
+		}
+		max_model_name_width = std::max( max_model_name_width, max_prefix_width ) ;
+
+		PriorNames::const_iterator
+			name_i = prior_names.begin(),
+			end_name_i = prior_names.end() ;
+
+		
+		for( std::size_t model_count = 0; name_i != end_name_i; ++name_i, ++model_count ) {
+			ui().logger() << "Model " << *name_i ;
+			{
+				PriorWeights::const_iterator where = prior_weights.find( *name_i ) ;
+				assert( where != prior_weights.end() ) ;
+				ui().logger() << " " << ( boost::format( "(weight %.2f)\n" ) % where->second ).str() ;
+			}
+
+			Priors::const_iterator
+				prior_i = priors.lower_bound( *name_i ),
+				end_prior_i = priors.upper_bound( *name_i ) ;
+			std::size_t count = 0 ;
+			for( ; prior_i != end_prior_i; ++prior_i, ++count ) {
+				ui().logger() << ( boost::format( "-- (#%.3d) " ) % count ) << format_covariance_spec( prior_i->second.first ) << ":\n" ;
+				std::string const padding = "  " + std::string( ( max_model_name_width > max_prefix_width ) ? ( max_model_name_width - max_prefix_width ): 0, ' ' ) + "   " ;
+				Eigen::MatrixXd const& prior = prior_i->second.second ;
+				assert( prior.rows() == D*N ) ;
+				ui().logger() << "  " << std::setw( max_model_name_width ) << " " << "  " ;
+				for( std::size_t i = 0; i < (D*N); ++i ) {
+					ui().logger() << (( i > 0 ) ? " " : "" ) ;
+					ui().logger() << std::setw( column_widths[i] ) << i ;
+				}
+				ui().logger() << "\n" ;
+
+				for( int i = 0; i < prior.rows(); ++i ) {
+	//				ui().logger() << padding ;
+					std::string const parameter_name = parameter_names.parameter_name( i / N ) ;
+					std::string const cohort_name = cohort_names[i % N] ;
+					ui().logger()
+						<< "  " << std::setw( max_model_name_width )
+						<< std::right
+						<< ( "(" + cohort_name + ":" + parameter_name + ") " + genfile::string_utils::to_string( i )) << "  "
+						<< std::left ;
+					for( int j = 0; j < prior.cols(); ++j ) {
+						ui().logger() << (( j > 0 ) ? " " : "" ) ;
+						ui().logger() << std::setw( column_widths[j] ) ;
+						if( j < i ) {
+							ui().logger() << " " ;
+						} else {
+							ui().logger() << prior(i,j) ;
+						}
+					}
+					ui().logger() << "\n" ;
+				}
+				ui().logger() << "\n";
+				
+				if( !options().check( "-verbose" ) ) {
+					ui().logger() << "-- ...(+" << (prior.rows()-1) << " other submodels, use -verbose to output these too)\n\n" ;
+					break ;
+				}
+			}
+			
+			if( (!options().check( "-verbose" )) && model_count > 10 ) {
+				ui().logger() << "...(+" << (prior_names.size()-model_count) << " other models, use -verbose to output these too.\n" ;
+				break ;
+			}
+		}
+
+		ui().logger() << "================================================\n" ;
+	}
+
+	void post_summarise() const {
+		std::string const output_file = options().get< std::string >( "-o" ) ;
+		std::string const analysis = options().get< std::string >( "-analysis-name" ) ;
+		std::string const SQL = "SELECT * FROM SummaryDataView WHERE analysis == '" + analysis + "'" ;
+		ui().logger() << "\n" << globals::program_name << ": Analysis complete.\n" ;
+		ui().logger() << "\n-------------------------\n" ;
+		
+	}
+	
+	FrequentistGenomeWideAssociationResults::UniquePtr create_cohort(
+		std::vector< genfile::wildcard::FilenameMatch > const& filenames,
+		boost::optional< std::string > const& effect_size_column_regex,
+		std::vector< std::string > const& columns,
+		genfile::VariantIdentifyingDataTest::UniquePtr test,
+		boost::optional< genfile::Chromosome > chromosome_hint,
+		FlatFileFrequentistGenomeWideAssociationResults::SNPResultCallback result_callback,
+		FlatFileFrequentistGenomeWideAssociationResults::ProgressCallback progress_callback
+	) {
+		// peek at the file to determine file type
+	
+		std::string type = "unknown" ;
+
+		if( filenames.size() > 0 ) {
+			std::auto_ptr< std::istream > file = genfile::open_text_file_for_input( filenames[0].filename() ) ;
+			std::string line ;
+			std::getline( *file, line ) ;
+			std::vector< std::string > const elts = genfile::string_utils::split( line, " \t," ) ;
+			if( elts.size() > 4
+				&& elts[0] == "chr"
+				&& elts[1] == "snp_id1"
+				&& elts[2] == "snp_id2"
+				&& elts[3] == "pos"
+				&& elts[4] == "allele_0"
+			) {
+				type = "mmm" ; // Matti's mixed model, http://www.well.ox.ac.uk/~mpirinen/
+			}
+			else if(
+				elts.size() > 5
+				&& elts[0] == "snp_id1"
+				&& elts[1] == "snp_id2"
+				&& elts[2] == "pos"
+				&& elts[3] == "allele_0"
+				&& elts[4] == "allele_1"
+				&& elts[5] == "n_included"
+			) {
+				type = "mmm" ; // Matti's mixed model, http://www.well.ox.ac.uk/~mpirinen/
+			}
+			else if( line.substr( 0, 40 ) == "id rsid chromosome pos allele_A allele_B" ) {
+					type = "snptest" ;
+			}
+		}
+
+		FlatFileFrequentistGenomeWideAssociationResults::UniquePtr result ;
+		if( type == "snptest" || type == "unknown" ) {
+			result.reset( new bingwa::SNPTESTResults( test, chromosome_hint ) ) ; 
+		}
+		else if( type == "mmm" ) {
+			result.reset( new bingwa::MMMResults( test, chromosome_hint ) ) ;
+		}
+	
+		if( effect_size_column_regex ) {
+			result->set_effect_size_column_regex( effect_size_column_regex.get() ) ;
+		}
+
+		BOOST_FOREACH( std::string const& column, columns ) {
+			result->add_variable( column ) ;
+		}
+
+		if( options().check( "-trust-variants-where" )) {
+			std::vector< std::string > const specs = options().get_values< std::string >( "-trust-variants-where" ) ;
+			for( std::size_t i = 0; i < specs.size(); ++i ) {
+				result->add_trust_constraint(
+					statfile::BoundConstraint::parse( specs[i] )
+				) ;
+			}
+		}
+
+		statfile::BuiltInTypeStatSource::UniquePtr source(
+			statfile::BuiltInTypeStatSourceChain::open( filenames )
+		) ;
+	
+		if( options().check( "-incl-snps-where" ) ) {
+			std::vector< std::string > const specs = options().get_values< std::string >( "-incl-snps-where" ) ;
+			for( std::size_t i = 0; i < specs.size(); ++i ) {
+				source = statfile::FilteringStatSource::create(
+					source,
+					statfile::BoundConstraint::parse( specs[i] )
+				) ;
+			}
+		}
+
+		if( options().check( "-excl-snps-where" ) ) {
+			std::vector< std::string > const specs = options().get_values< std::string >( "-excl-snps-where" ) ;
+			for( std::size_t i = 0; i < specs.size(); ++i ) {
+				source = statfile::FilteringStatSource::create(
+					source,
+					statfile::BoundConstraint::parse( specs[i] ).negation()
+				) ;
+			}
+		}
+		
+		result->add_data(
+			source,
+			result_callback,
+			progress_callback
+		) ;
+		
+		return FrequentistGenomeWideAssociationResults::UniquePtr( result.release() ) ;
+	}
+
+	typedef
+		boost::function< void ( genfile::VariantIdentifyingData const&, std::string const&, genfile::VariantEntry const& ) > 
+		ResultCallback ;
+
+	void load_data() {
+		std::vector< std::string > cohort_files = options().get_values< std::string >( "-data" ) ;
+		for( std::size_t cohort_i = 0; cohort_i < cohort_files.size(); ++cohort_i ) {
+			load_data_for_cohort( cohort_i, cohort_files ) ;
+		}
+	}
+	
+	void load_data_for_cohort( std::size_t cohort_i, std::vector< std::string > const& cohort_files ) {
+		using genfile::string_utils::to_string ;
+		using genfile::string_utils::join ;
+
+		UIContext::ProgressContext progress_context = ui().get_progress_context( "Loading scan results \"" + cohort_files[cohort_i] + "\"" ) ;
+
+		genfile::VariantIdentifyingDataTestConjunction::UniquePtr test( new genfile::VariantIdentifyingDataTestConjunction() ) ;
+
+		if( options().check_if_option_was_supplied_in_group( "SNP inclusion / exclusion options" ) ) {
+			genfile::CommonSNPFilter::UniquePtr snp_filter = get_snp_exclusion_filter( cohort_i ) ;
+			if( snp_filter.get() ) {
+				test->add_subtest( genfile::VariantIdentifyingDataTest::UniquePtr( snp_filter.release() ) ) ;
+			}
+		}
+
+		boost::optional< std::string > effect_size_column_regex ;
+		if( options().check( "-effect-size-column-regex" ) ) {
+			std::vector< std::string > values = options().get_values< std::string >( "-effect-size-column-regex" ) ;
+			if( values.size() != cohort_files.size() ) {
+				throw genfile::BadArgumentError(
+					"BingwaApplication::load_data()",
+					"-effect-size-column-regex=\"" + to_string( genfile::string_utils::join( values, " " ) ) + "\"",
+					"Expected " + to_string( cohort_files.size() ) + " values but found " + to_string( values.size() ) + "."
+				) ;
+			}
+			effect_size_column_regex = values[ cohort_i ] ;
+		}
+
+		boost::optional< genfile::Chromosome > chromosome_hint ;
+		if( options().check( "-assume-chromosome" ) ) {
+			chromosome_hint = genfile::Chromosome( options().get< std::string >( "-assume-chromosome" ) ) ;
+		}
+		FrequentistGenomeWideAssociationResults::UniquePtr results = create_cohort(
+			genfile::wildcard::find_files_by_chromosome( cohort_files[cohort_i] ),
+			effect_size_column_regex,
+			options().check( "-extra-columns" ) ? options().get_values< std::string >( "-extra-columns" ) : std::vector< std::string >(),
+			genfile::VariantIdentifyingDataTest::UniquePtr( test.release() ),
+			chromosome_hint,
+			bingwa::SNPTESTResults::SNPResultCallback(),
+			progress_context
+		) ;
+		
+		// summarise right now so as to see memory used.
+		ui().logger() << "Cohort " << (cohort_i+1) << " summary: " << results->get_summary() << ".\n" ;
+		
+		bingwa::EffectParameterNamePack parameters = results->get_effect_parameter_names() ;
+		if( options().check( "-rename-parameters" )) {
+			rename_parameters(
+				options().get< std::string >( "-rename-parameters" ),
+				&parameters
+			) ;
+		}
+
+		if( cohort_i == 0 ) {
+			m_processor->set_effect_parameter_names( parameters ) ;
+		}
+		else if( parameters != m_processor->get_effect_parameter_names() ) {
+			throw genfile::MalformedInputError(
+				cohort_files[ cohort_i ],
+				"Names of effect parameters in cohort " + to_string( cohort_i+1 )
+					+ " ("
+					+ results->get_effect_parameter_names().get_summary()
+					+ ") do not match that in cohort 1 ("
+					+ m_processor->get_effect_parameter_names().get_summary()
+					+ ")",
+				0
+			) ;
+		}
+		m_cohort_variables.push_back( results->list_variables() ) ;
+		m_cohort_constraint_variables.push_back( results->list_trust_constraint_variables() ) ;
+		m_processor->add_cohort( "cohort_" + to_string( cohort_i+1 ), results ) ;
+	}
+	
+	void rename_parameters(
+		std::string const& renameFile,
+		bingwa::EffectParameterNamePack* parameters
+	) const {
+		statfile::BuiltInTypeStatSource::UniquePtr renames = statfile::BuiltInTypeStatSource::open( renameFile ) ;
+		if( renames->number_of_columns() < 2 ) {
+			throw genfile::MalformedInputError(
+				renameFile,
+				"Expected a two-column file.",
+				0
+			) ;
+		}
+
+#if DEBUG_BINGWA
+		for( std::size_t i = 0; i < parameters->size(); ++i ) {
+			std::cerr << "PARAMETER: \"" + parameters->parameter_name(i) << "\", se = \"" + parameters->se_name(i) << ".\n" ;
+		}
+#endif
+		std::string key, value ;
+		using genfile::string_utils::slice ;
+		while( (*renames) >> key >> value ) {
+			
+			std::size_t const where = parameters->find( key ) ;
+			if( where != bingwa::EffectParameterNamePack::npos ) {
+				std::vector< slice > elts = slice( value ).split( ":" ) ;
+				assert( elts.size() == 2 ) ;
+				std::vector< slice > bits = elts[0].split( "_" ) ;
+				assert( bits.size() == 2 ) ;
+				parameters->rename(
+					where,
+					bits[0],
+					bits[1],
+					elts[1]
+				) ;
+
+#if DEBUG_BINGWA
+				std::cerr << "After replacing \"" << key << "\":\n" ;
+				for( std::size_t i = 0; i < parameters->size(); ++i ) {
+					std::cerr << "PARAMETER: \"" + parameters->parameter_name(i) << "\", se = \"" + parameters->se_name(i) << ".\n" ;
+				}
+#endif
+			}
+			(*renames) >> statfile::ignore_all() ;
+		}
+	}
+	
+	genfile::CommonSNPFilter::UniquePtr get_snp_exclusion_filter( std::size_t cohort_i ) const {
+		genfile::CommonSNPFilter::UniquePtr snp_filter ;
+		using genfile::string_utils::join ;
+		using genfile::string_utils::split_and_strip_discarding_empty_entries ;
+
+		if( options().check_if_option_was_supplied_in_group( "SNP inclusion / exclusion options" )) {
+			snp_filter.reset( new genfile::CommonSNPFilter ) ;
+
+			if( options().check_if_option_was_supplied( "-excl-snpids" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-excl-snpids" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->exclude_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::SNPIDs
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-incl-snpids" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-incl-snpids" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->include_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::SNPIDs
+					) ;
+				}
+			}
+
+
+			if( options().check_if_option_was_supplied( "-excl-rsids" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-excl-rsids" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->exclude_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::RSIDs
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-incl-rsids" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-incl-rsids" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->include_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::RSIDs
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-excl-positions" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-excl-positions" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->exclude_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::Positions
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-incl-positions" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-incl-positions" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->include_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::Positions
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-excl-snpids-per-cohort" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-excl-snpids-per-cohort" ) ;
+				if( files.size() != options().get_values< std::string >( "-data" ).size() ) {
+					throw genfile::BadArgumentError( "BingwaApplication::get_snp_exclusion_filter()", "-excl-snpids-per-cohort=\"" + join( files, " " ) + "\"" ) ;
+				}
+				std::vector< std::string > this_cohort_files = split_and_strip_discarding_empty_entries( files[ cohort_i ], ",", " \t" ) ;
+				BOOST_FOREACH( std::string const& filename, this_cohort_files ) {
+					snp_filter->exclude_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::SNPIDs
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-incl-snpids-per-cohort" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-incl-snpids-per-cohort" ) ;
+				if( files.size() != options().get_values< std::string >( "-data" ).size() ) {
+					throw genfile::BadArgumentError( "BingwaApplication::get_snp_exclusion_filter()", "-incl-snpids-per-cohort=\"" + join( files, " " ) + "\"" ) ;
+				}
+				std::vector< std::string > this_cohort_files = split_and_strip_discarding_empty_entries( files[ cohort_i ], ",", " \t" ) ;
+				BOOST_FOREACH( std::string const& filename, this_cohort_files ) {
+					snp_filter->include_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::SNPIDs
+					) ;
+				}
+			}
+
+
+			if( options().check_if_option_was_supplied( "-excl-rsids-per-cohort" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-excl-rsids-per-cohort" ) ;
+				if( files.size() != options().get_values< std::string >( "-data" ).size() ) {
+					throw genfile::BadArgumentError( "BingwaApplication::get_snp_exclusion_filter()", "-excl-rsids-per-cohort=\"" + join( files, " " ) + "\"" ) ;
+				}
+				std::vector< std::string > this_cohort_files = split_and_strip_discarding_empty_entries( files[ cohort_i ], ",", " \t" ) ;
+				BOOST_FOREACH( std::string const& filename, this_cohort_files ) {
+					snp_filter->exclude_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::RSIDs
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-incl-rsids-per-cohort" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-incl-rsids-per-cohort" ) ;
+				if( files.size() != options().get_values< std::string >( "-data" ).size() ) {
+					throw genfile::BadArgumentError( "BingwaApplication::get_snp_exclusion_filter()", "-incl-rsids-per-cohort=\"" + join( files, " " ) + "\"" ) ;
+				}
+				std::vector< std::string > this_cohort_files = split_and_strip_discarding_empty_entries( files[ cohort_i ], ",", " \t" ) ;
+				BOOST_FOREACH( std::string const& filename, this_cohort_files ) {
+					snp_filter->include_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::RSIDs
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-excl-snps-per-cohort" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-excl-snps-per-cohort" ) ;
+				if( files.size() != options().get_values< std::string >( "-data" ).size() ) {
+					throw genfile::BadArgumentError( "BingwaApplication::get_snp_exclusion_filter()", "-excl-snps-per-cohort=\"" + join( files, " " ) + "\"" ) ;
+				}
+				std::vector< std::string > this_cohort_files = split_and_strip_discarding_empty_entries( files[ cohort_i ], ",", " \t" ) ;
+				BOOST_FOREACH( std::string const& filename, this_cohort_files ) {
+					genfile::SNPDataSource::UniquePtr source ;
+					source.reset(
+						new statfile::SNPDataSourceAdapter(
+							statfile::BuiltInTypeStatSource::open(
+								genfile::wildcard::find_files_by_chromosome( filename )
+							)
+						)
+					) ;
+
+					snp_filter->exclude_snps(
+						source->list_snps(),
+						genfile::VariantIdentifyingData::CompareFields( options().get_value< std::string >( "-snp-match-fields" ) )
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-incl-snps-per-cohort" )) {
+				std::vector< std::string > files = options().get_values< std::string > ( "-incl-snps-per-cohort" ) ;
+				if( files.size() != options().get_values< std::string >( "-data" ).size() ) {
+					throw genfile::BadArgumentError( "BingwaApplication::get_snp_exclusion_filter()", "-incl-snps-per-cohort=\"" + join( files, " " ) + "\"" ) ;
+				}
+				std::vector< std::string > this_cohort_files = split_and_strip_discarding_empty_entries( files[ cohort_i ], ",", " \t" ) ;
+				BOOST_FOREACH( std::string const& filename, this_cohort_files ) {
+					genfile::SNPDataSource::UniquePtr source ;
+					source.reset(
+						new statfile::SNPDataSourceAdapter(
+							statfile::BuiltInTypeStatSource::open(
+								genfile::wildcard::find_files_by_chromosome( filename )
+							)
+						)
+					) ;
+
+					snp_filter->include_snps(
+						source->list_snps(),
+						genfile::VariantIdentifyingData::CompareFields( options().get_value< std::string >( "-snp-match-fields" ) )
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-excl-snps-matching" )) {
+				std::string const it = options().get< std::string > ( "-excl-snps-matching" ) ;
+				std::vector< std::string > specs = genfile::string_utils::split_and_strip_discarding_empty_entries( it, ",", " \t" ) ;
+				BOOST_FOREACH( std::string const& spec, specs ) {
+					snp_filter->exclude_snps_matching(
+						spec
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-incl-snps-matching" )) {
+				std::string const it = options().get< std::string > ( "-incl-snps-matching" ) ;
+				std::vector< std::string > specs = genfile::string_utils::split_and_strip_discarding_empty_entries( it, ",", " \t" ) ;
+				BOOST_FOREACH( std::string const& spec, specs ) {
+					snp_filter->include_snps_matching(
+						spec
+					) ;
+				}
+			}
+			
+			if( options().check_if_option_was_supplied( "-incl-range" )) {
+				std::vector< std::string > const specs = options().get_values< std::string >( "-incl-range" ) ;
+				for ( std::size_t i = 0; i < specs.size(); ++i ) {
+					snp_filter->include_snps_in_range(
+						genfile::GenomePositionRange::parse( specs[i] )
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-excl-range" )) {
+				std::vector< std::string > specs = options().get_values< std::string >( "-excl-range" ) ;
+				for ( std::size_t i = 0; i < specs.size(); ++i ) {
+					snp_filter->exclude_snps_in_range(
+						genfile::GenomePositionRange::parse( specs[i] )
+					) ;
+				}
+			}
+		}
+		return snp_filter ;
+	}
+	
+private:
+	SetOfValueListSets m_value_sets ;
+	BingwaProcessor::UniquePtr m_processor ;
+	std::vector< std::vector< std::string > > m_cohort_variables ;
+	std::vector< std::vector< std::string > > m_cohort_constraint_variables ;
+} ;
+
+int main( int argc, char **argv ) {
+	try {
+		BingwaApplication app( argc, argv ) ;	
+		app.run() ;
+		app.post_summarise() ;
+	}
+	catch( appcontext::HaltProgramWithReturnCode const& e ) {
+		return e.return_code() ;
+	}
+	return 0 ;
+}

DELETED apps/binit.cpp
Index: apps/binit.cpp
==================================================================
--- apps/binit.cpp
+++ apps/binit.cpp
@@ -1,285 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <memory>
-#include <set>
-#include <iostream>
-#include <boost/format.hpp>
-#include <boost/optional.hpp>
-
-#include "appcontext/CmdLineOptionProcessor.hpp"
-#include "appcontext/ApplicationContext.hpp"
-#include "appcontext/get_current_time_as_string.hpp"
-#include "appcontext/ProgramFlow.hpp"
-
-#include "genfile/Error.hpp"
-#include "genfile/GenomePositionRange.hpp"
-#include "genfile/string_utils/string_utils.hpp"
-#include "genfile/VariantEntry.hpp"
-#include "genfile/FileUtils.hpp"
-
-#define DEBUG_BINIT 1
-
-namespace globals {
-	std::string const program_name = "binit" ;
-	std::string const program_version = "0.1" ;
-}
-
-struct BinitOptions: public appcontext::CmdLineOptionProcessor {
-	std::string get_program_name() const { return globals::program_name ; }
-
-	void declare_options( appcontext::OptionProcessor& options ) {
-		options.set_help_option( "-help" ) ;
-
-		options[ "-bin-size" ]
-			.set_description( "Number of input items to put in each bin. "
-				"A value of 0 specifies a single bin containing all the data." )
-			.set_takes_single_value()
-			.set_is_required()
-			.set_default_value( 0 )
-		;
-
-		options[ "-assume-range" ]
-			.set_description( "A chromosome and position range (e.g. <chr>:<start>-<end>). "
-				"If this is given it is assumed that the N numbers passed into the standard input "
-				"correspond to the positions start - end on the given chromosome (and binit "
-				"will check that N = end - start + 1)."
-			)
-			.set_takes_single_value()
-		;
-
-		options[ "-at-positions" ]
-			.set_description( "Specify a file containing a list of positions. "
-				"Only values at the specified positions will be used. "
-				"If -assume-range is specified, positions should be in the form chr:position. "
-				"Otherwise, they should be indices in the range 1...N"
-			)
-			.set_takes_single_value()
-		;
-
-		options[ "-ignore-lines-starting-with" ]
-			.set_description( "Specify a string to treat as a comment, e.g. such that lines beginning "
-				"with this string will be ignored.  Multiple values may be given." )
-			.set_takes_values_until_next_option()
-			.set_maximum_multiplicity( 100 )
-		;
-
-		options[ "-analysis-name" ]
-			.set_description( "Specify a name for the analysis. This will be included in the output." )
-			.set_takes_single_value()
-			.set_default_value( appcontext::get_current_time_as_string() ) ;
-		;
-
-		options[ "-precision" ]
-			.set_description( "Number of significant digits to output results to." )
-			.set_takes_single_value()
-			.set_default_value( 5 )
-		;
-
-		options[ "-log" ]
-			.set_description( "Path of log file." )
-			.set_takes_single_value()
-		;
-	}
-} ;
-
-struct BinitApplication: public appcontext::ApplicationContext {
-public:
-	BinitApplication( int argc, char **argv ):
-		appcontext::ApplicationContext(
-			globals::program_name,
-			globals::program_version,
-			std::auto_ptr< appcontext::OptionProcessor >( new BinitOptions ),
-			argc,
-			argv,
-			"-log"
-		),
-		m_bin_size( options().get< std::size_t >( "-bin-size" ) )
-	{
-		if( options().check( "-assume-range" )) {
-			m_range = genfile::GenomePositionRange::parse( options().get< std::string >( "-assume-range" ) ) ;
-		}
-		if( options().check( "-ignore-lines-starting-with" )) {
-			m_ignore_strings = options().get_values< std::string >( "-ignore-lines-starting-with" ) ;
-		}
-		if( options().check( "-at-positions" )) {
-			m_inclusions = std::set< genfile::VariantEntry >() ;
-			std::auto_ptr< std::istream > stream( genfile::open_text_file_for_input( options().get< std::string >( "-at-positions" )) ) ;
-			std::string line ;
-			while( std::getline( *stream, line ) ) {
-				if( m_range ) {
-					m_inclusions->insert( genfile::GenomePosition( line )) ;
-				} else {
-					m_inclusions->insert( genfile::string_utils::to_repr< int64_t >( line )) ;
-				}
-			}
-		}
-	}
-
-	void run() {
-		process( std::cin ) ;
-	}
-private:
-	
-	std::size_t const m_bin_size ;
-	std::vector< std::string > m_ignore_strings ;
-	boost::optional< genfile::GenomePositionRange > m_range ;
-	boost::optional< std::set< genfile::VariantEntry > > m_inclusions ;
-	
-private:
-	void process( std::istream& input ) {
-		try {
-			unsafe_process( input ) ;
-		} catch( genfile::InputError const& e ) {
-			std::cerr << "!! (" << e.what() << "): " << e.format_message() << ".\n" ;
-			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
-		} catch( genfile::string_utils::StringConversionError const& e ) {
-			std::cerr << "!! (" << e.what() << "): input should be numerical.\n" ;
-			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
-		}
-	}
-	
-	void unsafe_process( std::istream& input ) {
-		boost::optional< std::string > analysis_name ;
-		if( options().check( "-analysis-name" ) ) {
-			analysis_name = options().get< std::string >( "-analysis-name" ) ;
-			std::cout << "analysis\t" ;
-		}
-		if( m_range ) {
-			std::cout << "chromosome\tstart\tend\tcount\taverage\n" ;
-		} else {
-			std::cout << "start\tend\tcount\taverage\n" ;
-		}
-
-		char const tab = '\t' ;
-		std::cout << std::setprecision( options().get< std::size_t >( "-precision" ) ) ;
-
-		std::size_t count = 0 ;
-		std::size_t index = 0 ;
-		double accumulation = 0 ;
-		std::string line ;
-		while( input >> line ) {
-			bool ignore = false ;
-			if( m_ignore_strings.size() > 0 ) {
-				for( std::size_t i = 0; !ignore && i < m_ignore_strings.size(); ++i ) {
-					if( line.compare( 0, m_ignore_strings[i].size(), m_ignore_strings[i] ) == 0 ) {
-						// ignore a line.
-						std::getline( input, line ) ;
-						ignore = true ;
-					}
-				}
-			}
-
-			if( !ignore ) {
-				++index ;
-			}
-
-			if( m_inclusions && !ignore ) {
-				// only include if it's in the inclusions file
-				if( m_range ) {
-					genfile::GenomePosition position( m_range->chromosome(), m_range->start().position() + index - 1 ) ;
-					ignore = ( m_inclusions->find( position ) == m_inclusions->end() ) ;
-				} else {
-					int64_t position = index ;
-					ignore = ( m_inclusions->find( position ) == m_inclusions->end() ) ;
-				}
-			}
-			
-			if( !ignore ) {
-				accumulation += genfile::string_utils::to_repr< double >( line ) ;
-				++count ;
-			}
-			
-			if( m_bin_size > 0 && ( index % m_bin_size ) == 0 ) {
-				genfile::VariantEntry mean ;
-				if( count > 0 ) {
-					mean = ( accumulation / count ) ;
-				}
-				if( analysis_name ) {
-					std::cout << (*analysis_name) << tab ;
-				}
-				if( m_range ) {
-					std::cout
-						<< m_range->chromosome()
-						<< tab
-						<< (m_range->start().position() + index - m_bin_size )
-						<< tab
-						<< (m_range->start().position() + index - 1 )
-						<< tab
-						<< count
-						<< tab
-						<< mean
-						<< "\n" ;
-				} else {
-					std::cout
-						<< index - m_bin_size + 1
-						<< tab
-						<< index
-						<< tab
-						<< count
-						<< tab
-						<< mean
-						<< "\n" ;
-				}
-				accumulation = 0 ;
-				count = 0 ;
-			}
-		}
-		std::size_t const last_bin_count = ( m_bin_size > 0 ) ? (count % m_bin_size) : count ;
-		if( last_bin_count != 0 ) {
-			double const mean = ( accumulation / last_bin_count ) ;
-			if( analysis_name ) {
-				std::cout << (*analysis_name) << tab ;
-			}
-			if( m_range ) {
-				std::cout
-					<< m_range->chromosome()
-					<< tab
-					<< (m_range->start().position() + index - ( index % m_bin_size ) )
-					<< tab
-					<< (m_range->start().position() + index - 1 )
-					<< tab
-					<< last_bin_count
-					<< tab
-					<< mean
-					<< "\n" ;
-			} else {
-				std::cout
-					<< index - (index % m_bin_size) + 1
-					<< tab
-					<< index
-					<< tab
-					<< last_bin_count
-					<< tab
-					<< mean
-					<< "\n" ;
-			}
-		}
-		
-		if( m_range ) {
-			std::size_t expected = m_range->end().position() - m_range->start().position() + 1 ;
-			if( index != expected ) {
-				throw genfile::MalformedInputError(
-					"(stdin)",
-					( boost::format( "Length of range (%d) does not match number of elements in input (%d)." ) % expected % index ).str(),
-					index
-				) ;
-			}
-		}
-	}
-} ;
-
-
-int main( int argc, char **argv ) {
-	try {
-		BinitApplication app( argc, argv ) ;	
-		app.run() ;
-	}
-	catch( appcontext::HaltProgramWithReturnCode const& e ) {
-		return e.return_code() ;
-	}
-	return 0 ;
-}

DELETED apps/checkvcf.cpp
Index: apps/checkvcf.cpp
==================================================================
--- apps/checkvcf.cpp
+++ apps/checkvcf.cpp
@@ -1,357 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <string>
-#include <fstream>
-#include <boost/unordered_map.hpp>
-#include <boost/tuple/tuple.hpp>
-#include <boost/filesystem.hpp>
-#include <boost/algorithm/string/replace.hpp>
-#include "genfile/FileUtils.hpp"
-#include "genfile/GenomePosition.hpp"
-#include "genfile/VariantIdentifyingData.hpp"
-#include "genfile/VariantIdentifyingData.hpp"
-#include "genfile/string_utils/string_utils.hpp"
-#include "statfile/DelimitedStatSource.hpp"
-#include "statfile/read_values.hpp"
-#include "appcontext/CmdLineOptionProcessor.hpp"
-#include "appcontext/OptionProcessor.hpp"
-#include "appcontext/ApplicationContext.hpp"
-#include "config/qctool_version_autogenerated.hpp"
-
-namespace globals {
-	std::string const program_name = "checkvcf" ;
-	std::string const program_version = qctool_revision ;
-}
-
-struct FixVcfOptionProcessor: public appcontext::CmdLineOptionProcessor
-{
-public:
-	std::string get_program_name() const { return globals::program_name ; }
-
-	void declare_options( appcontext::OptionProcessor& options ) {
-		// Meta-options
-		options.set_help_option( "-help" ) ;
-
-		// File options
-		options.declare_group( "Input file options" ) ;
-	    options[ "-manifest" ]
-	        .set_description( "Path of manifest file to compare VCF with." )
-			.set_takes_values( 1 )
-			.set_is_required() ;
-	    options[ "-i" ]
-	        .set_description( "Path of input VCF file." )
-			.set_takes_values( 1 )
-			.set_is_required()
-		;
-	    options[ "-o" ]
-	        .set_description( "Path of output VCF file." )
-			.set_takes_values( 1 )
-		;
-		options[ "-ignore-alleles" ]
-			.set_description( "Do not check correctness of alleles" ) ;
-		options.declare_group( "Other options" ) ;
-		options[ "-fix-format" ]
-			.set_description( "Specify that " + globals::program_name + " should replace x/x with ./. and nan with . and -nan with ." ) ;
-		options[ "-replace-header-with" ]
-			.set_description( "Specify that " + globals::program_name + " should replace the VCF header (including #CHROM line) with one from the given file." )
-			.set_takes_single_value() ;
-		options [ "-log" ]
-			.set_description( "Specify that " + globals::program_name + " should write a log file to the given file." )
-			.set_takes_single_value() ;
-		options[ "-continue-on-error" ]
-			.set_description( "Specify that " + globals::program_name + " should continue if errors are found (lines with errors are skipped from output)." )
-		;
-
-		options.option_implies_option( "-fix-format", "-o" ) ;
-		options.option_implies_option( "-replace-header-with", "-o" ) ;
-	}
-} ;
-
-struct FixVCFApplication: public appcontext::ApplicationContext
-{
-public:
-	FixVCFApplication( int argc, char** argv ):
-		appcontext::ApplicationContext(
-			globals::program_name,
-			globals::program_version,
-			std::auto_ptr< appcontext::OptionProcessor >( new FixVcfOptionProcessor ),
-			argc,
-			argv,
-			"-log"
-		)
-	{
-		if( options().check( "-o" ) && boost::filesystem::exists( options().get< std::string >( "-o" ) ) ) {
-			get_ui_context().logger() << "Output file \"" <<  options().get< std::string >( "-o" ) << "\" exists, I will not overwrite.\n" ;
-			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
-		}
-		loadManifest( options().get< std::string >( "-manifest" ) ) ;
-		summarise() ;
-		process() ;
-	}
-
-private:
-	
-	typedef boost::unordered_map< std::string, genfile::VariantIdentifyingData > VariantMap ;
-	VariantMap m_map ;
-	
-	void loadManifest( std::string const& filename ) {
-		std::string const& wantedColumns = "IlmnID|Name|Chr|MapInfo|SNP" ;
-		statfile::DelimitedStatSource::UniquePtr source(
-			new statfile::DelimitedStatSource(
-				filename,
-				",",
-				std::string( "[Assay]" ), std::string( "[Controls]" )
-			)
-		) ;
-		std::map< std::size_t, std::size_t > const wantedColumnMap = statfile::impl::get_indices_of_columns(
-			source->column_names(),
-			wantedColumns
-		) ;
-		std::string IlmnID ;
-		std::string Name ;
-		std::string Chr ;
-		genfile::Position position ;
-		std::string alleleString ;
-		
-		appcontext::UIContext::ProgressContext progress_context = get_ui_context().get_progress_context( "Loading manifest variants" ) ;
-		progress_context( 0, source->number_of_rows() ) ;
-		
-		while(
-			statfile::read_values(
-				*source,
-				wantedColumnMap,
-				boost::tie( IlmnID, Name, Chr, position, alleleString )
-			)
-		) {
-			// parse alleles
-			if( alleleString.size() != 5 || alleleString[0] != '[' || alleleString[4] != ']' || alleleString[2] != '/' ) {
-				throw genfile::MalformedInputError(
-					"FixVCFApplication::loadManifest()",
-					"Alleles for SNP " + IlmnID + " (\"" + alleleString + "\") appear malformed.",
-					source->number_of_rows_read()
-				) ;
-			}
-			std::string const allele1 = alleleString.substr( 1, 1 ) ;
-			std::string const allele2 = alleleString.substr( 3, 1 ) ;
-			
-			genfile::VariantIdentifyingData snp(
-				IlmnID, Name, genfile::GenomePosition( Chr, position ), allele1, allele2
-			) ;
-			
-			VariantMap::const_iterator where = m_map.find( Name ) ;
-			if( where != m_map.end() ) {
-				throw genfile::DuplicateEntryError(
-					"FixVCFApplication::loadManifest()",
-					filename,
-					Name,
-					"Name",
-					"SNP with name \"" + Name + "\" appears twice in manifest." ) ;
-			}
-			m_map[ Name ] = snp ;
-			(*source) >> statfile::ignore_all() ;
-			progress_context( source->number_of_rows_read(), source->number_of_rows() ) ;
-		}
-	}
-	
-	void summarise() const {
-		get_ui_context().logger() << std::string( 72, '=' ) << "\n\n" ;
-
-		get_ui_context().logger() << "Loaded manifest (\"" + options().get< std::string >( "-manifest" ) + "\") with the following properties:\n" ;
-		get_ui_context().logger() << " -- Number of variants: " << m_map.size() << ".\n" ;
-		get_ui_context().logger() << " -- First few variants: " << m_map.size() << ".\n" ;
-		{
-			VariantMap::const_iterator i = m_map.begin() ;
-			VariantMap::const_iterator end_i = m_map.end() ;
-			for( std::size_t count = 0; count < std::min( 10ul, m_map.size() ) && i != end_i; ++i, ++count ) {
-				get_ui_context().logger() << " -- \"" << i->first << "\": " << i->second << ".\n" ;
-			}
-			get_ui_context().logger() << "\n" ;
-		}
-		
-		get_ui_context().logger() << std::string( 72, '=' ) << "\n\n" ;
-	}
-
-	void process() {
-		try {
-			unsafe_process() ;
-		}
-		catch( genfile::InputError const& e ) {
-			get_ui_context().logger() << "!! Error (" << e.what() << "): " << e.format_message() << ".\n" ;
-			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
-		}
-		catch( genfile::FileNotFoundError const& e ) {
-			get_ui_context().logger() << "\nError: No file matching \"" << e.filespec() << "\" could be found.\n" ;
-			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
-		}
-	}
-
-	void unsafe_process() {
-		using genfile::string_utils::to_string ;
-		
-		bool const continueOnError = options().check( "-continue-on-error" ) ;
-		bool const compareAlleles = !options().check( "-ignore-alleles" ) ;
-		bool const replaceHeader = options().check( "-replace-header-with" ) ;
-		bool const fixFormat = options().check( "-fix-format" ) ;
-
-		std::string line ;
-		std::auto_ptr< std::istream > inStreamHolder ;
-		std::istream* inStream = 0 ;
-		if( options().get< std::string >( "-i" ) == "-" ) {
-			inStream = &(std::cin) ;
-		} else {
-			inStreamHolder = genfile::open_text_file_for_input( options().get< std::string >( "-i" ) );
-			inStream = inStreamHolder.get() ;
-		}
-
-		std::auto_ptr< std::ostream > outStream ;
-		if( options().check( "-o" )) {
-			outStream = genfile::open_text_file_for_output( options().get< std::string >( "-o" ) ) ;
-		}
-		
-		appcontext::UIContext::ProgressContext progress_context = get_ui_context().get_progress_context( "Processing vcf file" ) ;
-		progress_context( 0, boost::optional< std::size_t >() ) ;
-		
-		// Ignore metadata
-		std::size_t lineCount = 0 ;
-		while( std::getline( *inStream, line ) && line.size() > 1 && line[0] == '#' && line[1] == '#' ) {
-			if( outStream.get() && !replaceHeader ) {
-				outStream->write( line.data(), line.size() ).put( '\n' ) ;
-			}
-			++lineCount ;
-		}
-		
-		if( line.substr( 0, 6 ) != "#CHROM" ) {
-			throw genfile::MalformedInputError( "FixVCFApplication::process()", "vcf has malformed header line", lineCount ) ;
-		}
-		if( outStream.get() && !replaceHeader ) {
-			outStream->write( line.data(), line.size() ).put( '\n' ) ;
-		}
-
-		if( outStream.get() && replaceHeader ) {
-			std::ifstream file( options().get< std::string >( "-replace-header-with" ).c_str() ) ;
-			std::string line ;
-			while( std::getline( file, line ) ) {
-				outStream->write( line.data(), line.size() ).put( '\n' ) ;
-			}
-		}
-
-		std::vector< std::size_t > fieldPos( 6, 0 ) ;
-
-		std::size_t totalVariantCount = 0 ;
-		std::size_t goodVariantCount = 0 ;
-
-		for( ; std::getline( *inStream, line ); ++lineCount, ++totalVariantCount ) {
-			try {
-				// otherwise look up SNP by name
-				// id is third column
-				for( std::size_t i = 1; i < fieldPos.size(); ++i ) {
-					fieldPos[i] = line.find( '\t', fieldPos[i-1] ) ; 
-					if( fieldPos[i] == std::string::npos ) {
-						throw genfile::MalformedInputError(
-							"FixVCFApplication::process()",
-							"vcf line has fewer than " + genfile::string_utils::to_string( i+1) + " tab characters",
-							lineCount
-						) ;
-					}
-					++fieldPos[i] ; // skip the delimiter
-				}
-
-				std::string rsid = line.substr( fieldPos[2], fieldPos[3] - fieldPos[2] - 1 ) ;
-				if( rsid.size() > 0 ) {
-					// Just take the first ID.
-					rsid = genfile::string_utils::slice( rsid ).split( "," )[0] ;
-				}
-				genfile::Chromosome chromosome( line.substr( fieldPos[0], fieldPos[1] - fieldPos[0] - 1 ) ) ;
-				genfile::Position position = genfile::string_utils::to_repr< genfile::Position >( line.substr( fieldPos[1], fieldPos[2] - fieldPos[1] - 1 ) ) ;
-
-				VariantMap::const_iterator where = m_map.find( rsid ) ;
-				if( where == m_map.end() ) {
-					throw genfile::MalformedInputError(
-						"FixVCFApplication::process()",
-						"vcf contains id (" + rsid + ") that is not in the variant map.",
-						lineCount
-					) ;
-				}
-				if( chromosome != where->second.get_position().chromosome() ) {
-					throw genfile::MalformedInputError(
-						"FixVCFApplication::process()",
-						"Chromosome for SNP " + rsid + " (" + to_string( chromosome ) + ") does not match manifest chromosome (" + to_string( where->second.get_position().chromosome() ) + ")",
-						lineCount
-					) ;
-				}
-				if( position != where->second.get_position().position() ) {
-					throw genfile::MalformedInputError(
-						"FixVCFApplication::process()",
-						"Position for SNP " + rsid + " (" + to_string( position ) + ") does not match manifest chromosome (" + to_string( where->second.get_position().position() ) + ")",
-						lineCount
-					) ;
-				}
-				if( compareAlleles ) {
-					if( line.compare( fieldPos[3], fieldPos[4] - fieldPos[3] - 1, where->second.get_allele(0) ) != 0 ) {
-						throw genfile::MalformedInputError(
-							"FixVCFApplication::process()",
-							"REF allele for SNP " + rsid + " (\"" + line.substr( fieldPos[3], fieldPos[4] - fieldPos[3] - 1 )
-								+ "\") does not match manifest allele (\"" + where->second.get_allele(0) + "\")",
-							lineCount
-						) ;
-					}
-					if( line.compare( fieldPos[4], fieldPos[5] - fieldPos[4] - 1, where->second.get_allele(1) ) != 0 ) {
-						throw genfile::MalformedInputError(
-							"FixVCFApplication::process()",
-							"REF allele for SNP " + rsid + " (\"" + line.substr( fieldPos[4], fieldPos[5] - fieldPos[4] - 1 )
-								+ "\") does not match manifest allele (\"" + where->second.get_allele(1) + "\")",
-							lineCount
-						) ;
-					}
-				}
-				rsid += "," + where->second.get_identifiers_as_string( ",", 1 ) ;
-
-				if( outStream.get() ) {
-					outStream->write( line.data(), fieldPos[2] ) ;
-					outStream->write( rsid.data(), rsid.size() ) ;
-					outStream->put( '\t' ) ;
-					std::string rest = line.substr( fieldPos[3], line.size() ) ;
-					if( fixFormat ) {
-						boost::algorithm::replace_all( rest, "Index=", "id=" ) ;
-						boost::algorithm::replace_all( rest, "x/x", "./." ) ;
-						boost::algorithm::replace_all( rest, "nan,nan,nan", ".,.,." ) ;
-						boost::algorithm::replace_all( rest, "-nan,-nan,-nan", ".,.,." ) ;
-						boost::algorithm::replace_all( rest, "nan,nan", ".,." ) ;
-						boost::algorithm::replace_all( rest, "-nan,-nan", ".,." ) ;
-						boost::algorithm::replace_all( rest, "-nan", "." ) ;
-						boost::algorithm::replace_all( rest, "nan", "." ) ;
-					}
-					outStream->write( rest.data(), rest.size() ) ;
-					outStream->put( '\n' ) ;
-				}
-
-				++goodVariantCount ;
-			}
-			catch( genfile::MalformedInputError const& e ) {
-				get_ui_context().logger() << "\n!! Error (" << e.what() << "): " << e.format_message() << ".\n" ;
-				if( !continueOnError ) {
-					throw ;
-				}
-			}
-			
-			progress_context( lineCount, boost::optional< std::size_t >() ) ;
-		}
-		progress_context( lineCount, lineCount ) ;
-
-		get_ui_context().logger() << "\nVisited " << totalVariantCount << " variants of which " << goodVariantCount << " matched SNPs in the manifest.\n" ;
-	}	
-} ;
-
-int main( int argc, char** argv ) {
-    try {
-		FixVCFApplication app( argc, argv ) ;
-    }
-	catch( appcontext::HaltProgramWithReturnCode const& e ) {
-		return e.return_code() ;
-	}
-	return 0 ;
-}

DELETED apps/edit-bgen.cpp
Index: apps/edit-bgen.cpp
==================================================================
--- apps/edit-bgen.cpp
+++ apps/edit-bgen.cpp
@@ -1,158 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <string>
-#include <iostream>
-#include <fstream>
-#include <boost/filesystem.hpp>
-#include <boost/format.hpp>
-#include <boost/ptr_container/ptr_vector.hpp>
-#include <algorithm>
-#include "genfile/FileUtils.hpp"
-#include "genfile/VariantIdentifyingData.hpp"
-#include "genfile/Error.hpp"
-#include "genfile/bgen/bgen.hpp"
-#include "appcontext/CmdLineOptionProcessor.hpp"
-#include "appcontext/OptionProcessor.hpp"
-#include "appcontext/ApplicationContext.hpp"
-#include "config/qctool_version_autogenerated.hpp"
-
-namespace globals {
-	std::string const program_name = "edit-bgen" ;
-	std::string const program_version = qctool_revision ;
-}
-
-struct EditBgenOptionProcessor: public appcontext::CmdLineOptionProcessor
-{
-public:
-	std::string get_program_name() const { return globals::program_name ; }
-
-	void declare_options( appcontext::OptionProcessor& options ) {
-		// Meta-options
-		options.set_help_option( "-help" ) ;
-
-		options.declare_group( "Input / output file options" ) ;
-	    options[ "-g" ]
-	        .set_description(
-				"Path of bgen file(s) whose free data area to set. "
-				"The free data area must have the same size in each bgen file."
-			)
-			.set_takes_values_until_next_option()
-		;
-
-	    options[ "-set-free-data" ]
-	        .set_description(
-				"Free data to set.  This must be a string exactly the length of the free data area in each file."
-			)
-			.set_takes_single_value()
-			.set_is_required()
-		;
-	}
-} ;
-
-struct EditBgenApplication: public appcontext::ApplicationContext
-{
-public:
-	EditBgenApplication( int argc, char** argv ):
-		appcontext::ApplicationContext(
-			globals::program_name,
-			globals::program_version,
-			std::auto_ptr< appcontext::OptionProcessor >( new EditBgenOptionProcessor ),
-			argc,
-			argv,
-			"-log"
-		)
-	{
-		process() ;
-	}
-
-	void process() {
-		try {
-			unsafe_process() ;
-		}
-		catch( genfile::MalformedInputError const& e ) {
-			get_ui_context().logger() << "\nError (" << e.what() <<"): " << e.format_message() << ".\n" ;
-			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
-		}
-		catch( genfile::BadArgumentError const& e ) {
-			get_ui_context().logger() << "\nError (" << e.what() <<"): " << e.format_message() << ".\n" ;
-			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
-		}
-	}
-	
-	void unsafe_process() {
-		std::string const free_data = options().get< std::string >( "-set-free-data" ) ;
-		std::vector< std::string > filenames = options().get_values< std::string >( "-g" ) ;
-		std::auto_ptr< boost::ptr_vector< std::fstream > > streams  = open_bgen_files( filenames, free_data ) ;
-		edit_free_data( filenames, *streams, free_data ) ;
-	}
-	
-	std::auto_ptr< boost::ptr_vector< std::fstream > > open_bgen_files( std::vector< std::string > const& filenames, std::string const& new_free_data ) const {
-		boost::ptr_vector< std::fstream > streams ;
-		for( std::size_t i = 0; i < filenames.size(); ++i ) {
-			streams.push_back(
-				std::auto_ptr< std::fstream >(
-					new std::fstream(
-						filenames[i].c_str(),
-						std::ios::in | std::ios::out | std::ios::binary
-					)
-				)
-			) ;
-						
-			// Verify header block has the right size.
-			streams.back().seekg( 4 ) ;
-			genfile::bgen::Context context ;
-			genfile::bgen::read_header_block( streams.back(), &context ) ;
-			if( context.free_data.size() != new_free_data.size() ) {
-				throw genfile::BadArgumentError(
-					"EditBgenApplication::unsafe_process()",
-					"free_data=\"" + new_free_data + "\"",
-					( boost::format( "In bgen file \"%s\": size of new free data (%d bytes) does not match that of free data in file (\"%s\", %d bytes)." )
-						% filenames[i] % new_free_data.size() % context.free_data % context.free_data.size() ).str()
-				) ;
-			}
-		}
-		return streams.release() ;
-	}
-	
-	void edit_free_data(
-		std::vector< std::string > const& filenames,
-		boost::ptr_vector< std::fstream >& streams,
-		std::string const& free_data
-	) const {
-		assert( filenames.size() == streams.size() ) ;
-		for( std::size_t i = 0; i < filenames.size(); ++i ) {
-			edit_free_data( filenames[i], streams[i], free_data ) ;
-		}
-	}
-
-	void edit_free_data( std::string const& filename, std::fstream& stream, std::string const& free_data ) const {
-		get_ui_context().logger() << boost::format( "Setting free data for \"%s\" to \"%s\"..." ) % filename % free_data ;
-
-		// Read (and double-check) the header
-		// We checked this earlier, so assert if this fails.
-		stream.seekg( 4 ) ;
-		genfile::bgen::Context context ;
-		genfile::bgen::read_header_block( stream, &context ) ;
-		assert( context.free_data.size() == free_data.size() ) ;
-		
-		// free data always starts at byte 20.
-		stream.seekp( 20, std::ios::beg ) ;
-		stream.write( free_data.data(), free_data.size() ) ;
-		stream.close() ;
-		get_ui_context().logger() << "ok.\n" ;
-	}
-} ;
-
-int main( int argc, char** argv ) {
-    try {
-		EditBgenApplication app( argc, argv ) ;
-    }
-	catch( appcontext::HaltProgramWithReturnCode const& e ) {
-		return e.return_code() ;
-	}
-	return 0 ;
-}

DELETED apps/gen-grep.cpp
Index: apps/gen-grep.cpp
==================================================================
--- apps/gen-grep.cpp
+++ apps/gen-grep.cpp
@@ -1,241 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <limits>
-
-#include "genfile/SNPDataSource.hpp"
-#include "genfile/SNPDataSourceChain.hpp"
-#include "genfile/GenomePositionRange.hpp"
-#include "genfile/get_set.hpp"
-#include "genfile/wildcard.hpp"
-#include "genfile/FileUtils.hpp"
-#include "appcontext/CmdLineOptionProcessor.hpp"
-#include "appcontext/ProgramFlow.hpp"
-
-using namespace appcontext ;
-
-namespace globals {
-	std::string program_name = "gen-grep" ;
-}
-
-typedef genfile::GenomePositionRange PositionRange ;
-
-namespace {
-	// Read a set of things from a file (optionally gzipped).
-	template< typename Set >
-	Set read_set_from_file( std::string const& filename ) {
-		Set aSet ;
-		std::auto_ptr< std::istream > aStream( genfile::open_text_file_for_input( filename )) ;
-		if( aStream.get() && aStream->good() ) {
-			std::copy( std::istream_iterator< typename Set::value_type >( *aStream ),
-			           std::istream_iterator< typename Set::value_type >(),
-			           std::inserter( aSet, aSet.end() )) ;
-		}
-
-		return aSet ;
-	}
-}
-
-struct IDDataPrinterOptionProcessor: public CmdLineOptionProcessor
-{
-	std::string get_program_name() const { return globals::program_name ; }
-	void declare_options( OptionProcessor& options ) {
-		// Meta-options
-		options.set_help_option( "-help" ) ;
-		options.declare_group( "File-related options" ) ;
-		options[ "-g" ]
-			.set_description( "Specify the name (or names) of gen files to process." )
-			.set_is_required()
-			.set_takes_single_value()
-			.set_takes_value_by_position( 1 ) ;
-			
-		options.declare_group( "SNP Selection options" ) ;
-		options[ "-snp-interval" ]
-			.set_description( "Only output SNPs in the given interval" )
-			.set_takes_values( 2 )
-			.set_maximum_multiplicity( 1 ) ;
-			
-		options[ "-snp-id-file" ]
-			.set_description( "Specify a file containing SNP ids to match" )
-			.set_takes_single_value() ;
-
-		options[ "-rsid-file" ]
-			.set_description( "Specify a file containing RSids to match" )
-			.set_takes_single_value() ;
-	}
-	
-	
-	std::string gen_filename() const {
-		return get_value< std::string > ( "-g" ) ;
-	}
-
-	std::set< std::string > snp_ids() const {
-		std::set< std::string > result ;
-		if( check_if_option_was_supplied( "-snp-id-file" )) {
-			result = read_set_from_file< std::set< std::string > >( get_value< std::string >( "-snp-id-file" ) ) ;
-		}
-		return result ;
-	}
-
-	std::set< std::string > rsids() const {
-		std::set< std::string > result ;
-		if( check_if_option_was_supplied( "-rsid-file" )) {
-			result = read_set_from_file< std::set< std::string > >( get_value< std::string >( "-rsid-file" ) ) ;
-		}
-		return result ;
-	}
-	
-	bool have_snp_ids() const {
-		return check_if_option_was_supplied( "-snp-id-file" ) ;
-	}
-
-	bool have_rsids() const {
-		return check_if_option_was_supplied( "-rsid-file" ) ;
-	}
-	
-	PositionRange position_range() const {
-		if( check_if_option_was_supplied( "-snp-interval" )) {
-			std::vector< std::size_t > values = get_values< std::size_t > ( "-snp-interval" ) ;
-			assert( values.size() == 2 ) ;
-			return PositionRange( values[0], values[1] ) ;
-		}
-		else {
-			return PositionRange( 0, std::numeric_limits< uint32_t >::max() ) ;
-		}
-	}
-} ;
-
-
-struct IDDataPrinterContext
-{
-	IDDataPrinterContext( int argc, char** argv ) {
-		//write_start_banner() ;
-		try {
-			m_options.process( argc, argv ) ;
-		}
-		catch( appcontext::OptionProcessorHelpRequestedException const& e ) {
-			std::cerr << "Usage: "
-			<< globals::program_name << " <options>\n"
-			<< "\nOPTIONS:\n"
-			<< m_options
-			<< "\n" ;
-			throw HaltProgramWithReturnCode( 0 );
-		}
-		
-		construct_snp_data_source() ;
-		if( m_options.have_snp_ids() ) {
-			m_snp_ids = m_options.snp_ids() ;
-		}
-		if( m_options.have_rsids() ) {
-			m_rsids = m_options.rsids() ;
-		}
-		write_preamble() ;
-	}
-
-	~IDDataPrinterContext() {
-		//write_end_banner() ;
-	}
-
-	genfile::SNPDataSource& snp_data_source() { return *m_snp_data_source ; }
-
-	PositionRange const position_range() const { return m_options.position_range() ; }
-
- 	bool have_snp_ids() const { return m_options.have_snp_ids() ; }
-	std::set< std::string > const& snp_ids() const { return m_snp_ids ; }
-
- 	bool have_rsids() const { return m_options.have_rsids() ; }
-	std::set< std::string > const& rsids() const { return m_rsids ; }
-	
-private:
-
-	void write_start_banner() {
-		std::cout << "Welcome to " << globals::program_name << ".\n"
-		 	<< "(C) 2009 University of Oxford\n\n";
-	}
-
-	void write_end_banner() {
-		std::cout << "\nThank you for using " << globals::program_name << ".\n" ;
-	}
-
-	void write_preamble() {
-		
-	}
-
-	void construct_snp_data_source() {
-		genfile::SNPDataSourceChain::UniquePtr chain = genfile::SNPDataSourceChain::create(
-			genfile::wildcard::find_files_by_chromosome(
-				m_options.gen_filename(),
-				genfile::wildcard::eALL_CHROMOSOMES
-			)
-		) ;
-		
-		m_snp_data_source.reset( chain.release() ) ;
-	}
-	
-private:
-	IDDataPrinterOptionProcessor m_options ;
-	std::auto_ptr< genfile::SNPDataSource > m_snp_data_source ;
-	std::set< std::string > m_snp_ids ;
-	std::set< std::string > m_rsids ;
-} ;
-
-struct IDDataPrinter
-{
-	IDDataPrinter( IDDataPrinterContext& context )
-		: m_context( context )
-	{}
-
-	void process() {
-		std::cout << "alternate_identifiers rsid chromosome position first_allele other_alleles number_of_alleles\n" ;
-		genfile::VariantIdentifyingData snp ;
-		while( m_context.snp_data_source().get_snp_identifying_data( &snp )) {
-			bool include = m_context.position_range().contains( snp.get_position() ) ;
-			if( m_context.have_snp_ids() ) {
-				std::vector< genfile::string_utils::slice > const& identifiers = snp.get_identifiers() ;
-				bool found = false ;
-				for( std::size_t i = 0; i < identifiers.size(); ++i ) {
-					if( m_context.snp_ids().find( identifiers[i] ) != m_context.snp_ids().end() ) {
-						found = true ;
-						break ;
-					}
-				}
-				include = include && found ;
-			}
-			if( m_context.have_rsids() ) {
-				include = include && ( m_context.rsids().find( snp.get_primary_id() ) != m_context.rsids().end() ) ;
-			}
-			if( include ) {
-				std::cout
-					<< ( (snp.number_of_identifiers() > 1) ? snp.get_identifiers_as_string( ",", 1 ) : "." )
-					<< " " << snp.get_primary_id()
-					<< " " << snp.get_position().chromosome() << " " << snp.get_position().position()
-					<< " " << snp.get_allele(0) << " " ;
-				for( std::size_t i = 1; i < snp.number_of_alleles(); ++i ) {
-					std::cout << (i>1 ? "," : "") << snp.get_allele(i) ;
-				}
-				std::cout << " " << snp.number_of_alleles() << "\n" ;
-			}
-			m_context.snp_data_source().ignore_snp_probability_data() ;
-		}
-	}
-	
-private:
-	
-	IDDataPrinterContext& m_context ;
-} ;
-
-
-int main( int argc, char** argv ) {
-	try {
-		IDDataPrinterContext context( argc, argv ) ;
-		IDDataPrinter printer( context ) ;
-		printer.process() ;
-	}
-	catch( HaltProgramWithReturnCode const& e ) {
-		return e.return_code() ;
-	}
-	return 0 ;
-}

ADDED   apps/hptest.cpp
Index: apps/hptest.cpp
==================================================================
--- apps/hptest.cpp
+++ apps/hptest.cpp
@@ -0,0 +1,2392 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <iostream>
+#include <limits>
+#include <typeinfo>
+#include <fstream>
+
+#include <boost/filesystem.hpp>
+#include <boost/format.hpp>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/timer/timer.hpp>
+#include <boost/ptr_container/ptr_vector.hpp>
+#include <boost/bind.hpp>
+#include <boost/foreach.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+
+#include "config/package_revision_autogenerated.hpp"
+
+#include "appcontext/CmdLineOptionProcessor.hpp"
+#include "appcontext/ApplicationContext.hpp"
+
+#include "genfile/SNPDataSource.hpp"
+#include "genfile/SNPDataSourceChain.hpp"
+#include "genfile/ThreshholdingSNPDataSource.hpp"
+#include "genfile/ToGP.hpp"
+#include "genfile/CommonSNPFilter.hpp"
+#include "genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp"
+#include "genfile/CrossCohortCovariateValueMapping.hpp"
+#include "genfile/SampleFilter.hpp"
+#include "genfile/SampleFilteringSNPDataSource.hpp"
+#include "genfile/SampleFilteringCohortIndividualSource.hpp"
+#include "genfile/DataLinkingCohortIndividualSource.hpp"
+#include "genfile/CompoundSampleFilter.hpp"
+#include "genfile/SampleFilterNegation.hpp"
+#include "genfile/VariableInSetSampleFilter.hpp"
+#include "genfile/GPThresholdingGTSetter.hpp"
+#include "genfile/db/Error.hpp"
+#include "genfile/CartesianProductVisitor.hpp"
+
+#include "components/SNPSummaryComponent/InfoComputation.hpp"
+
+#include "metro/constants.hpp"
+#include "metro/regression/Design.hpp"
+#include "metro/SampleRange.hpp"
+#include "metro/intersect_ranges.hpp"
+#include "metro/count_range.hpp"
+#include "metro/regression/BinomialLogistic.hpp"
+#include "metro/regression/ThreadedLogLikelihood.hpp"
+#include "metro/regression/IndependentNormalWeightedLogLikelihood.hpp"
+#include "metro/regression/IndependentLogFWeightedLogLikelihood.hpp"
+#include "metro/regression/LogPosteriorDensity.hpp"
+#include "metro/ValueStabilisesStoppingCondition.hpp"
+#include "metro/Snptest25StoppingCondition.hpp"
+#include "metro/maximisation.hpp"
+#include "metro/fit_model.hpp"
+#include "metro/CholeskyStepper.hpp"
+#include "metro/SampleStratification.hpp"
+
+#include "qcdb/MultiVariantStorage.hpp"
+#include "qcdb/FlatTableDBOutputter.hpp"
+
+#include <Eigen/Core>
+#include <Eigen/QR>
+#include "Eigen/Eigenvalues"
+
+#define DEBUG 0
+
+namespace globals {
+	std::string const program_name = "hptest" ;
+	std::string const program_version = package_version ;
+	std::string const program_revision =  std::string( package_revision ).substr( 0, 7 ) ;
+}
+
+namespace {
+	bool in_set( std::string const& arg, std::vector< std::string > const& values, std::set< std::string > const& permitted ) {
+		for( auto v: values ) {
+			if( permitted.find( v ) == permitted.end() ) {
+				throw appcontext::OptionValueInvalidException(
+					arg,
+					values,
+					arg + ": unexpected value (\"" + v + "\")"
+				) ;
+			}
+		}
+		return true ;
+	}
+	
+	std::vector< std::string > collect_unique_ids( std::vector< std::string > const& ids_or_filenames ) {
+		std::vector< std::string > result ;
+		for( auto elt: ids_or_filenames ) {
+			if( boost::filesystem::exists( elt )) {
+				std::ifstream f( elt ) ;
+				std::copy(
+					std::istream_iterator< std::string >( f ),
+					std::istream_iterator< std::string >(),
+					std::back_inserter< std::vector< std::string > >( result )
+				) ;
+			} else {
+				result.push_back( elt ) ;
+			}
+		}
+		// now sort and uniqueify them...
+		std::sort( result.begin(), result.end() ) ;
+		std::vector< std::string >::const_iterator newBack = std::unique( result.begin(), result.end() ) ;
+		result.resize( newBack - result.begin() ) ;
+		return result ;
+	}
+
+	double extract_mapped_continuous_value(
+		std::size_t sample_index,
+		genfile::CohortIndividualSource const& samples,
+		std::size_t column_index,
+		genfile::CrossCohortCovariateValueMapping const& mapping
+	) {
+		double value = metro::NA ;
+		genfile::VariantEntry entry = samples.get_entry( sample_index, column_index ) ;
+		if( !entry.is_missing() ) {
+			value = mapping.get_mapped_value( entry ).as< double >() ;
+		}
+		return value ;
+	}
+
+	int extract_mapped_categorical_value(
+		std::size_t sample_index,
+		genfile::CohortIndividualSource const& samples,
+		std::size_t column_index,
+		genfile::CrossCohortCovariateValueMapping const& mapping
+	) {
+		int value = -1 ;
+		genfile::VariantEntry entry = samples.get_entry( sample_index, column_index ) ;
+		if( !entry.is_missing() ) {
+			value = mapping.get_mapped_value( entry ).as< int >() ;
+		}
+		return value ;
+	}
+
+	std::string get_unmapped_level(
+		genfile::CrossCohortCovariateValueMapping const& mapping,
+		int level
+	) {
+		genfile::VariantEntry entry = mapping.get_unmapped_value( level ) ;
+		return entry.as< std::string >() ;
+	}
+}
+
+struct HPTestOptions: public appcontext::CmdLineOptionProcessor
+{
+public:
+	std::string get_program_name() const { return globals::program_name ; }
+
+	void declare_options( appcontext::OptionProcessor& options ) {
+		// Meta-options
+		options.set_help_option( "-help" ) ;
+		options.set_spec_option( "-spec" ) ;
+
+		// File options
+		options.declare_group( "Input file options" ) ;
+	    options[ "-predictor" ]
+	        .set_description( 	"Path to predictor genotype files."
+								"The given filename may contain the wildcard character '#', which expands to match a"
+								"one- or two-character chromosome identifier." )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 1 )
+			.set_maximum_multiplicity( 1 ) ;
+		options[ "-incl-predictor-rsids" ]
+			.set_description( "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.")
+			.set_takes_values_until_next_option()
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-incl-predictor-range" ]
+			.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. "
+				"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+				"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+				"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+			.set_takes_values_until_next_option() ;
+
+		options[ "-outcome-genotypes" ]
+			.set_description(
+				"Path to outcome genotype files."
+				"The given filename may contain the wildcard character '#', which expands to match a"
+				"one- or two-character chromosome identifier." )
+			.set_takes_values( 1 )
+			.set_maximum_multiplicity( 1 ) ;
+		options[ "-outcome-name" ]
+			.set_description( "Specify a name for the outcome variable" )
+			.set_takes_single_value()
+			.set_default_value( "outcome" ) ;
+		options[ "-incl-outcome-rsids" ]
+			.set_description( "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.")
+			.set_takes_values_until_next_option()
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-incl-outcome-range" ]
+			.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. "
+				"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+				"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+				"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+			.set_takes_values_until_next_option() ;
+		options[ "-coerce-outcome-to-haploid" ]
+			.set_description( "Turn outcome homozygous genotype calls into haploid calls. "
+				"Heterozygous calls will be treated as missing" ) ;
+		options.option_implies_option(
+			"-coerce-outcome-to-haploid",
+			"-outcome-genotypes"
+		) ;
+		options[ "-coerce-predictor-to-haploid" ]
+			.set_description( "Turn predictor homozygous genotype calls or probabilities into haploid calls or probabilities. "
+				"Samples with nonzero probability of heterozygous genotype will be treated as missing." ) ;
+		options[ "-s" ]
+			.set_description( "Path of sample file" )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 1 )
+			.set_maximum_multiplicity( 1 ) ;
+
+		options[ "-sample-data" ]
+			.set_description( "Path of additional sample file(s) (in the same format(s) as accepted by -s) to read. "
+				"These files are used to look up additional sample information, using a sample ID in the first column as key. "
+				"For each sample and column, the relevant entry will be taken from the superset of all sample files supplied. "
+				"(It is an error to supply two different, non-missing values for columns with the same name for the same sample.)"
+			)
+			.set_takes_values_until_next_option()
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+
+		options.declare_group( "Output file options" ) ;
+		options[ "-o" ]
+			.set_description( "Output file" )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 1 )
+			.set_maximum_multiplicity( 1 ) ;
+		options[ "-output-models" ]
+			.set_description( "Specify which models to output estimates, standard errors, and Wald P-values for. "
+				"This can be either \"alternative\", in which case only non-null models are output, or \"all\" in which "
+				"case all models are output. "
+			)
+			.set_takes_single_value()
+			.set_default_value( "alternative" )
+			.set_check( boost::bind( &in_set, _1, _2, std::set< std::string >({"all", "alternative"}) ) ) ;
+		options[ "-output-parameters" ]
+			.set_description( "Specify which parameters to output estimates, standard errors, and Wald P-values for."
+				"By default only data on the genetic parameters are output; specify \"all\" to output all parameters."
+			)
+			.set_takes_single_value()
+			.set_default_value( "genetic" )
+			.set_check( boost::bind( &in_set, _1, _2, std::set< std::string >({"all", "genetic"}) ) ) ;
+		options[ "-output-counts" ]
+			.set_description( "Specify that hptest should output full cross-tabulated predictor and outcome genotype counts" ) ;
+		options[ "-output-all-variants" ]
+			.set_description( "Specify that hptest should output all variant combinations, even those where tests are skipped." ) ;
+		
+		options.declare_group( "Model options" ) ;
+		options[ "-model" ]
+			.set_description( "Specify models to fit.  Syntax is <name>:<model>" )
+			.set_takes_values_until_next_option()
+			.set_default_value( "gen:add+het" ) ;
+		options[ "-incl-samples"]
+			.set_description( "Filter out samples whose sample ID does not lie in the given file(s).")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-excl-samples"]
+			.set_description( "Filter out samples whose sample ID lies in the given file.")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-incl-samples-where"]
+			.set_description( "Include samples by specifying conditions on the values of columns in the sample file.")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-excl-samples-where"]
+			.set_description( "Exclude samples by specifying conditions on the values of columns in the sample file.")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-minimum-predictor-count" ]
+			.set_description( "Skip predictors that have less than this minor allele count" )
+			.set_takes_values(1)
+			.set_default_value( 10 ) ;
+		options[ "-minimum-outcome-count" ]
+			.set_description( "Skip outcomes that have less than this count" )
+			.set_takes_values(1)
+			.set_default_value( 10 ) ;
+		options[ "-prior" ]
+			.set_description( "Specify a prior for bayesian computation."
+				"Prior spec should be in the form <parameter name>~<distribution family>(parameters)."
+				"(It is recommended to put single quotes round the whole argument to protect from shell expansion.)"
+				"Currently, logF and gaussian priors are supported."
+			)
+			.set_takes_values_until_next_option()
+			.set_default_value( "add/[stratum]/[outcome]=1~logf(2,2)" )
+			.set_default_value( "overdominance/[stratum]/[outcome]=1~logf(4,4)" )
+			.set_default_value( "het/[stratum]/[outcome]=1~logf(2,2)" )
+			.set_default_value( "dom/[stratum]/[outcome]=1~logf(2,2)" )
+			.set_default_value( "rec/[stratum]/[outcome]=1~logf(2,2)" )
+		;
+		options[ "-no-prior" ]
+			.set_description( "Specify that no prior should be used.  Only frequentist summaries will be output." ) ;
+		options[ "-no-covariate-priors" ]
+			.set_description( "Specify that no default prior should be placed on covariates. "
+				"(By default a N(0,1000) prior is used)." ) ;
+		options[ "-covariates" ]
+			.set_description( "Specify the name of one or more covariates to include in the model."
+				" These must be columns named in the sample file." )
+			.set_takes_values_until_next_option() ;
+		options[ "-stratify" ]
+			.set_description( "Specify the name of a discrete covariate to stratify across" )
+			.set_takes_single_value() ;
+		options.declare_group( "Model fitting options" ) ;
+		options[ "-tolerance" ]
+			.set_description( "Tolerance" )
+			.set_takes_values(1)
+			.set_default_value( 0.001 ) ;
+		options[ "-max-iterations" ]
+			.set_description( "Maximum fitting iterations" )
+			.set_takes_values(1)
+			.set_default_value( 100 ) ;
+
+		options.option_excludes_option( "-prior", "-no-prior" ) ;
+
+		options.declare_group( "Output options" ) ;
+		options[ "-analysis-name" ]
+			.set_description( "Specify a name to label results from this analysis with." )
+			.set_takes_single_value()
+			.set_default_value( "hptest analysis" ) ;
+		options[ "-analysis-chunk" ]
+			.set_description( "Specify a name denoting the current genomic region or chunk on which this is run.  This is intended for use in parallel environments." )
+			.set_takes_single_value()
+			.set_default_value( genfile::MissingValue() ) ;
+		options[ "-analysis-id" ]
+			.set_description( "Specify an integer ID for the current analysis." )
+			.set_takes_single_value() ;
+		options[ "-outcome-genotype-call-threshold" ]
+			.set_description( "The threshold to apply to outcome genotype probabilities, if necessary, to make calls." )
+			.set_takes_single_value()
+			.set_default_value( 0.9 ) ;
+		options[ "-predictor-genotype-call-threshold" ]
+			.set_description( "The threshold to apply to outcome genotype probabilities, if necessary, to make calls." )
+			.set_takes_single_value() ;
+		options[ "-compare-variants-by" ]
+			.set_description( "A comma-separated list of fields to compare variants by."
+				" This affects how results for variants"
+				" (position, rsid, snpid, and alleles.)"
+				" Use this option to specify a comma-separated subset of those fields to use instead."
+				" The first entry must be \"position\"."
+				" This option can be used, for example, when cohorts are typed on different platforms so have different SNPID fields." )
+			.set_takes_single_value()
+			.set_default_value( "position,alleles,ids" ) ;
+
+		options[ "-debug" ]
+			.set_description( "Output debugging information." ) ;
+		options[ "-threads" ]
+			.set_description( "Number of additional threads to use in likelihood computations."
+				" The value 0 indicates that all work will take place in the main thread." )
+			.set_takes_single_value()
+			.set_default_value(0) ;
+	}
+} ;
+
+
+namespace {
+	// counts the number of each allele carried by each sample
+	// Outputs count of 1st allele in column 0 of output genotypes,
+	// 2nd allele in column 1, etc.
+	struct AlleleCounter: public genfile::VariantDataReader::PerSampleSetter {
+		typedef std::vector< metro::SampleRange > SampleRanges ;
+		
+		AlleleCounter(
+			Eigen::MatrixXd* genotypes,
+			Eigen::VectorXd* ploidy,
+			SampleRanges* nonmissing_samples
+		):
+			m_genotypes( genotypes ),
+			m_ploidy( ploidy ),
+			m_nonmissing_samples( nonmissing_samples ),
+			m_sample_i(0),
+			m_coerce_to_haploid( false )
+		{
+			assert( genotypes != 0 && nonmissing_samples != 0 && ploidy != 0 ) ;
+		}
+
+		void set_coerce_to_haploid() { m_coerce_to_haploid = true ; }
+
+		void initialise( std::size_t nSamples, std::size_t nAlleles ) {
+			if( nAlleles != 2 ) {
+				throw genfile::BadArgumentError(
+					"AlleleCounter::initialise()",
+					"nAlleles=" + genfile::string_utils::to_string( nAlleles ),
+					"I only support biallelic variants"
+				) ;
+			}
+			m_genotypes->resize( nSamples, nAlleles ) ;
+			m_genotypes->setZero() ;
+
+			m_ploidy->resize( nSamples ) ;
+			m_ploidy->setZero() ;
+
+			m_nonmissing_samples->clear() ;
+			m_last_nonmissing_sample_i = 0 ;
+		}
+
+		bool set_sample( std::size_t n ) {
+			m_sample_i = n ;
+			return true ;
+		}
+
+		void set_number_of_entries(
+			uint32_t ploidy, std::size_t n,
+			genfile::OrderType const order_type,
+			genfile::ValueType const value_type
+		) {
+			if( value_type != genfile::eAlleleIndex ) {
+				throw genfile::BadArgumentError(
+					"AlleleCounter::set_number_of_entries()",
+					"value_type=" + genfile::string_utils::to_string( value_type ),
+					"Expected a hard-called genotype, consider using threshholded calls."
+				) ;
+			}
+			if( order_type != genfile::ePerOrderedHaplotype && order_type != genfile::ePerUnorderedHaplotype ) {
+				throw genfile::BadArgumentError(
+					"AlleleCounter::set_number_of_entries()",
+					"order_type=" + genfile::string_utils::to_string( order_type ),
+					"Expected a hard-called genotype, consider using threshholded calls."
+				) ;
+			}
+			if( m_coerce_to_haploid ) {
+				(*m_ploidy)(m_sample_i) = 1 ;
+			} else {
+				(*m_ploidy)(m_sample_i) = ploidy ;
+			}
+		}
+
+		void set_value( std::size_t entry_i, genfile::MissingValue const value ) {
+			// This sample has missing data, end our current sample range here.
+			record_missing_sample() ;
+		}
+		
+		void set_value( std::size_t entry_i, Integer const value ) {
+			// Only accumulate if not already set missing
+			if( m_sample_i >= m_last_nonmissing_sample_i ) {
+				if( m_coerce_to_haploid && entry_i > 0 ) {
+					// Set anything that isn't homozygous to missing
+					if( (*m_genotypes)(m_sample_i,value) != 1 ) {
+						(*m_genotypes).row(m_sample_i).setZero() ;
+						record_missing_sample() ;
+					}
+				} else {
+					(*m_genotypes)(m_sample_i,value) += 1 ;
+				}
+			}
+		}
+
+		void set_value( std::size_t entry_i, double const value ) {
+			assert(0) ; // expecting GT field
+		}
+
+		void record_missing_sample() {
+			if( m_sample_i > m_last_nonmissing_sample_i ) {
+				m_nonmissing_samples->push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i )
+				) ;
+			}
+			m_last_nonmissing_sample_i = m_sample_i + 1 ;
+		}
+
+		void finalise() {
+			// add the final sample range if needed.
+			if( m_sample_i+1 > m_last_nonmissing_sample_i ) {
+				m_nonmissing_samples->push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i+1 )
+				) ;
+			}
+		}
+		
+	private:
+		Eigen::MatrixXd* m_genotypes ;
+		Eigen::VectorXd* m_ploidy ;
+		SampleRanges* m_nonmissing_samples ;
+		std::size_t m_last_nonmissing_sample_i ;
+		std::size_t m_sample_i ;
+		bool m_coerce_to_haploid ;
+	} ;
+	
+	struct ProbSetter: public genfile::VariantDataReader::PerSampleSetter {
+		typedef std::vector< metro::SampleRange > SampleRanges ;
+
+		ProbSetter(
+			Eigen::MatrixXd* genotypes,
+			Eigen::VectorXi* ploidy,
+			SampleRanges* nonmissing_samples
+		):
+			m_genotypes( genotypes ),
+			m_ploidy( ploidy ),
+			m_coerce_to_haploid( false ),
+			m_threshold( 0.0 ),
+			m_nonmissing_samples( nonmissing_samples ),
+			m_sample_i(0),
+			m_number_of_entries(0)
+		{
+			assert( genotypes != 0 && nonmissing_samples != 0 && ploidy != 0 ) ;
+		}
+
+		void set_coerce_to_haploid() {
+			m_coerce_to_haploid = true ;
+		}
+
+		void set_threshold(
+			double threshold
+		) {
+			assert( threshold > 0.0 ) ;
+			m_threshold = threshold ;
+		}
+
+		void initialise( std::size_t nSamples, std::size_t nAlleles ) {
+			if( nAlleles != 2 ) {
+				throw genfile::BadArgumentError(
+					"ProbSetter::initialise()",
+					"nAlleles=" + genfile::string_utils::to_string( nAlleles ),
+					"I only support biallelic variants"
+				) ;
+			}
+			// This currently supports constant ploidy only, up to ploidy = 2
+			// Allocate enough space for this with biallelic variants
+			m_genotypes->resize( nSamples, 3 ) ;
+			m_genotypes->setZero() ;
+			m_ploidy->resize( nSamples ) ;
+			m_ploidy->setZero() ;
+			
+			m_nonmissing_samples->clear() ;
+			m_last_nonmissing_sample_i = 0 ;
+		}
+
+		bool set_sample( std::size_t n ) {
+			m_sample_i = n ;
+			return true ;
+		}
+
+		void set_number_of_entries(
+			uint32_t ploidy,
+			std::size_t number_of_entries,
+			genfile::OrderType const order_type,
+			genfile::ValueType const value_type
+		) {
+			if( value_type != genfile::eProbability ) {
+				throw genfile::BadArgumentError(
+					"Probsetter::set_number_of_entries()",
+					"value_type=" + genfile::string_utils::to_string( value_type ),
+					"Expected genotype call probabilities (e.g. GP field)."
+				) ;
+			}
+			if( order_type != genfile::ePerUnorderedGenotype ) {
+				throw genfile::BadArgumentError(
+					"ProbSetter::set_number_of_entries()",
+					"order_type=" + genfile::string_utils::to_string( order_type ),
+					"Expected genotype call probabilities (e.g. GP field)."
+				) ;
+			}
+			if( ploidy > 2 ) {
+				throw genfile::BadArgumentError(
+					"ProbSetter::set_number_of_entries()",
+					"order_type=" + genfile::string_utils::to_string( order_type ),
+					"Expected an at-most diploid sample."
+				) ;
+			}
+			(*m_ploidy)(m_sample_i) = m_coerce_to_haploid ? 1 : ploidy ;
+			m_number_of_entries = number_of_entries ;
+		}
+
+		void set_value( std::size_t entry_i, genfile::MissingValue const value ) {
+			// This sample has missing data, end our current sample range here.
+			record_missing_sample() ;
+		}
+
+		void set_value( std::size_t entry_i, Integer const value ) {
+			assert(0) ; // expected a probabilty
+		}
+
+		void set_value( std::size_t entry_i, double const value ) {
+			double thresholded_value = (
+				(m_threshold > 0.0)
+				? ( (value >= m_threshold) ? 1.0 : 0.0 )
+				: value
+			) ;
+			//std::cerr << "set_value( " << entry_i << ", " << value << " ): number_of_entries = " << m_number_of_entries << ", thresholded = " << thresholded_value << "\n" ;
+			if( (m_sample_i >= m_last_nonmissing_sample_i) && (thresholded_value >= 0.0) ) {
+				if( m_coerce_to_haploid ) {
+					int const index = (entry_i / (m_number_of_entries-1)) ;
+					//std::cerr << "     --> index = " << index << ".\n" ;
+					if( ( entry_i == 0 || (entry_i+1) == m_number_of_entries )) {
+						(*m_genotypes)(m_sample_i, index) = thresholded_value ;
+					} else {
+						if( thresholded_value > 0.0 ) {
+							record_missing_sample() ;
+						}
+					}
+				} else {
+					(*m_genotypes)(m_sample_i, entry_i) = thresholded_value ;
+				}
+			}
+		}
+
+		void finalise() {
+			// Add the final sample range if needed.
+			if( (m_sample_i+1) > m_last_nonmissing_sample_i ) {
+				m_nonmissing_samples->push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i+1 )
+				) ;
+			}
+			
+			// For probability data, we need to handle the case of missingness encoded as zero probabilities.
+			// Do that now by inspecting the genotypes.
+			{
+				std::vector< metro::SampleRange > ranges ;
+				std::size_t last_nonmissing_sample_i = 0 ;
+				std::size_t i = 0 ;
+				for( ; i < m_genotypes->rows(); ++i ) {
+					if( m_genotypes->row(i).sum() == 0.0 ) {
+						if( i > last_nonmissing_sample_i ) {
+							ranges.push_back( metro::SampleRange( last_nonmissing_sample_i, i )) ;
+						}
+						last_nonmissing_sample_i = i+1 ;
+					}
+				}
+				if( i > last_nonmissing_sample_i ) {
+					ranges.push_back( metro::SampleRange( last_nonmissing_sample_i, i )) ;
+				}
+				
+				*m_nonmissing_samples = metro::impl::intersect_ranges( *m_nonmissing_samples, ranges ) ;
+			}
+		}
+		
+	private:
+		Eigen::MatrixXd* m_genotypes ;
+		Eigen::VectorXi* m_ploidy ;
+		bool m_coerce_to_haploid ;
+		double m_threshold ;
+		SampleRanges* m_nonmissing_samples ;
+		std::size_t m_last_nonmissing_sample_i ;
+		std::size_t m_sample_i ;
+		std::size_t m_number_of_entries ;
+		
+		void record_missing_sample() {
+			if( m_sample_i > m_last_nonmissing_sample_i ) {
+				// remember the current range of nonmissing samples
+				m_nonmissing_samples->push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i )
+				) ;
+			}
+			// Record this sample as missing
+			m_last_nonmissing_sample_i = m_sample_i + 1 ;
+		}
+	} ;
+}
+
+struct HPTestApplication: public appcontext::ApplicationContext
+{
+public:
+	
+	typedef Eigen::MatrixXd Matrix ;
+	typedef Eigen::VectorXd Vector ;
+	typedef Eigen::VectorXi IntegerVector ;
+	typedef Eigen::RowVectorXd RowVector ;
+	
+public:
+	HPTestApplication( int argc, char** argv ):
+		appcontext::ApplicationContext(
+			globals::program_name,
+			"version: " + globals::program_version + ", revision: " + globals::program_revision,
+			std::auto_ptr< appcontext::OptionProcessor >( new HPTestOptions ),
+			argc,
+			argv,
+			"-log"
+		)
+	{
+		process() ;
+	}
+	
+private:
+
+	metro::concurrency::threadpool::UniquePtr m_pool ;
+	metro::SampleStratification m_stratification ;
+	std::vector< std::string > m_prior_specs ;
+	Eigen::MatrixXd m_regression_predictor_probs ;
+private:
+	void process() {
+		try {
+			unsafe_process() ;
+		}
+		catch( genfile::InputError const& e ) {
+			get_ui_context().logger() << "!! Error (" << e.what() << "): " << e.format_message() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::FileNotFoundError const& e ) {
+			get_ui_context().logger() << "\nError: No file matching \"" << e.filespec() << "\" could be found.\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::db::Error const& e ) {
+			get_ui_context().logger() << "!! Error (" << e.what() << ") with the following statement: \""
+				<< e.sql()
+				<< "\".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+	}
+	
+	void unsafe_process() {
+		using genfile::string_utils::to_string ;
+		
+		genfile::SampleFilterConjunction::UniquePtr sample_filter = get_sample_filter() ;
+
+		genfile::CohortIndividualSource::UniquePtr
+			samples = genfile::CohortIndividualSource::create( options().get< std::string >( "-s" ) ) ;
+
+		if( options().check( "-sample-data" )) {
+			samples = open_sample_data( samples, options().get_values< std::string > ( "-sample-data" )) ;
+		}
+
+		std::set< std::size_t > const excluded_samples = compute_excluded_samples( *sample_filter, *samples ) ;
+		if( excluded_samples.size() > 0 ) {
+			samples.reset(
+				genfile::SampleFilteringCohortIndividualSource::create( samples, excluded_samples ).release()
+			) ;
+		}
+
+		std::size_t const N = samples->size() ;
+
+		if( options().check( "-stratify" )) {
+			m_stratification = compute_stratification( *samples, options().get< std::string >( "-stratify" )) ;
+			std::cerr << "Stratification:\n"
+				<< m_stratification << ".\n" ;
+		}
+
+		boost::optional< genfile::db::Connection::RowId > analysis_id ;
+		if( options().check( "-analysis-id" ) ) {
+			analysis_id = options().get< genfile::db::Connection::RowId >( "-analysis-id" ) ;
+		}
+
+		genfile::CartesianProductVisitor visitor ;
+
+		genfile::SNPDataSource::UniquePtr host, para ;
+		{
+			host = open_genotype_data_sources(
+				options().get< std::string >( "-predictor" ),
+				get_variant_filter(
+					"-incl-predictor-range",
+					"-incl-predictor-rsids"
+				),
+				excluded_samples
+			) ;
+			if( host->number_of_samples() != N ) {
+				throw genfile::BadArgumentError(
+					"HPTestApplication::unsafe_process()",
+					"-predictor \"" + options().get< std::string >( "-predictor" ) + "\"",
+					"Wrong number of samples (" + to_string(host->number_of_samples()) + ", expected " + to_string(N) + ")"
+				) ;
+			}
+			visitor.add_source( "predictor", host.get() ) ;
+		}
+
+		enum OutcomeSource { eGenotypeFile = 0, eSampleFile = 1 } ;
+		OutcomeSource const outcome_source = (
+			options().check( "-outcome-genotypes" )
+				? eGenotypeFile
+				: eSampleFile
+		) ;
+		std::string const& outcome_name = options().get< std::string >( "-outcome-name" ) ;
+		if( outcome_source == eGenotypeFile ) {
+			std::string const& filename = options().get< std::string >( "-outcome-genotypes" ) ;
+			para = open_genotype_data_sources(
+				filename,
+				get_variant_filter(
+					"-incl-outcome-range",
+					"-incl-outcome-rsids"
+				),
+				excluded_samples
+			) ;
+
+			if( para->number_of_samples() != N ) {
+				throw genfile::BadArgumentError(
+					"HPTestApplication::unsafe_process()",
+					"-outcome-genotypes \"" + filename + "\"",
+					"Wrong number of samples (" + to_string(para->number_of_samples()) + ", expected " + to_string(N) + ")"
+				) ;
+			}
+			
+			if( !options().check( "-no-prior" )) {
+				m_prior_specs = expand_prior_specs( options().get_values< std::string >( "-prior" )) ;
+			}
+		
+			visitor.add_source( "outcome", para.get() ) ;
+		}
+				
+		{
+			qcdb::MultiVariantStorage::UniquePtr storage = qcdb::MultiVariantStorage::create(
+				options().get< std::string > ( "-o" ),
+				((outcome_source == eSampleFile) ? 1 : 2 ),
+				options().get< std::string > ( "-analysis-name" ),
+				options().get< std::string > ( "-analysis-chunk" ),
+				get_application_metadata(),
+				options().get< std::string > ( "-compare-variants-by" ),
+				analysis_id
+			) ;
+	
+			std::vector< std::string > model_names ;
+			boost::ptr_vector< metro::regression::Design > designs ;
+			std::vector< Eigen::MatrixXd > predictorCodings ;
+			build_models( *samples, &model_names, &designs, &predictorCodings ) ;
+
+			if( outcome_source == eSampleFile ) {
+				set_outcome_from_sample_column(
+					*samples,
+					outcome_name,
+					&designs
+				) ;
+				storage->set_variant_names( std::vector< std::string >({ "predictor" })) ;
+				write_preamble( *samples, *host, outcome_name, designs[0].outcome(), designs[0].nonmissing_outcome() ) ;
+			} else {
+				storage->set_variant_names( std::vector< std::string >({ "predictor", "outcome" })) ;
+				write_preamble( *samples, *host, *para ) ;
+			}
+
+			test(
+				visitor,
+				model_names,
+				designs,
+				predictorCodings,
+				*storage
+			) ;
+			storage->finalise() ;
+		}
+	}
+	
+	genfile::CohortIndividualSource::UniquePtr open_sample_data( genfile::CohortIndividualSource::UniquePtr samples, std::vector< std::string > sample_files ) const {
+		genfile::DataLinkingCohortIndividualSource::UniquePtr result( new genfile::DataLinkingCohortIndividualSource( samples )) ;
+		for( std::size_t i = 0; i < sample_files.size(); ++i ) {
+			result->add_source( genfile::CohortIndividualSource::create( sample_files[i] )) ;
+		}
+		return genfile::CohortIndividualSource::UniquePtr( result.release() ) ;
+	}
+	
+	genfile::CommonSNPFilter::UniquePtr get_variant_filter(
+		std::string const& incl_range_option,
+		std::string const& incl_ids_option
+	) const {
+		genfile::CommonSNPFilter::UniquePtr result ;
+		if( options().check( incl_range_option ) || options().check( incl_ids_option ) ) {
+			result.reset( new genfile::CommonSNPFilter() ) ;
+			if( options().check( incl_range_option )) {
+				std::vector< std::string > specs = collect_unique_ids( options().get_values< std::string >( incl_range_option ) ) ;
+				for ( std::size_t i = 0; i < specs.size(); ++i ) {
+					result->include_snps_in_range(
+						genfile::GenomePositionRange::parse( specs[i] )
+					) ;
+				}
+			}
+			if( options().check( incl_ids_option )) {
+				std::vector< std::string > files = collect_unique_ids( options().get_values< std::string > ( incl_ids_option ) ) ;
+				result->include_snps_in_set(
+					std::set< std::string >( files.begin(), files.end() ),
+					genfile::CommonSNPFilter::RSIDs
+				) ;
+			}
+		}
+		return result ;
+	}
+	
+	genfile::SampleFilterConjunction::UniquePtr get_sample_filter() const {
+		genfile::SampleFilterConjunction::UniquePtr filter( new genfile::SampleFilterConjunction() ) ;
+		genfile::SampleFilterDisjunction::UniquePtr sample_inclusion_filter( new genfile::SampleFilterDisjunction() ) ;
+
+		if( options().check_if_option_was_supplied( "-incl-samples" ) ) {
+			genfile::SampleFilter::UniquePtr id1_filter = get_sample_id_filter(
+				options().get_values< std::string >( "-incl-samples" )
+			) ;
+			sample_inclusion_filter->add_clause( genfile::SampleFilter::UniquePtr( id1_filter.release() ) ) ;
+		}
+
+		if( options().check_if_option_was_supplied( "-excl-samples" ) ) {
+			genfile::SampleFilter::UniquePtr id1_filter = get_sample_id_filter(
+				options().get_values< std::string >( "-excl-samples" )
+			) ;
+			filter->add_clause(
+				genfile::SampleFilter::UniquePtr(
+					new genfile::SampleFilterNegation(
+						id1_filter
+					)
+				)
+			) ;
+		}
+
+		if( options().check_if_option_was_supplied( "-incl-samples-where" ) ) {
+			std::vector< std::string > conditions = options().get_values< std::string >( "-incl-samples-where" ) ;
+			// we OR together different WHERE clauses.
+			for( std::size_t i = 0; i < conditions.size(); ++i ) {
+				sample_inclusion_filter->add_clause( genfile::SampleFilter::create( conditions[i] )) ;
+			}
+		}
+
+		if( options().check_if_option_was_supplied( "-excl-samples-where" ) ) {
+			std::vector< std::string > conditions = options().get_values< std::string >( "-excl-samples-where" ) ;
+			// we AND together different WHERE clauses.
+			genfile::SampleFilterDisjunction::UniquePtr where( new genfile::SampleFilterDisjunction() ) ;
+			for( std::size_t i = 0; i < conditions.size(); ++i ) {
+				where->add_clause( genfile::SampleFilter::create( conditions[i] )) ;
+			}
+			filter->add_clause(
+				genfile::SampleFilter::UniquePtr(
+					new genfile::SampleFilterNegation(
+						genfile::SampleFilter::UniquePtr( where.release() )
+					)
+				)
+			) ;
+		}
+		if( sample_inclusion_filter->number_of_clauses() > 0 ) {
+			filter->add_clause( genfile::SampleFilter::UniquePtr( sample_inclusion_filter.release() ) ) ;
+		}
+
+		return filter ;
+	}
+
+	std::set< std::size_t > compute_excluded_samples( genfile::SampleFilter const& filter, genfile::CohortIndividualSource const& samples ) const {
+		std::vector< std::size_t > included_samples ;
+		void(std::vector<std::size_t>::*push_back)(std::size_t const&) = &std::vector<std::size_t>::push_back ;
+		filter.test(
+			samples,
+			boost::bind(
+				push_back,
+				&included_samples,
+				_1
+			)
+		) ;
+		std::set< std::size_t > excluded_samples(
+			boost::counting_iterator< std::size_t >(0),
+			boost::counting_iterator< std::size_t >( samples.get_number_of_individuals() )
+		) ;
+		for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+			excluded_samples.erase( included_samples[i] ) ;
+		}
+		return excluded_samples ;
+	}
+
+	genfile::SampleFilter::UniquePtr get_sample_id_filter( std::vector< std::string > const& filenames ) const {
+		genfile::VariableInSetSampleFilter::UniquePtr result( new genfile::VariableInSetSampleFilter( "ID_1" )) ;
+		for( std::size_t i = 0; i < filenames.size(); ++i ) {
+			std::string elt ;
+			std::ifstream is( filenames[i].c_str() ) ;
+			while( is >> elt ) {
+				result->add_level( elt ) ;
+			}
+		}
+		return genfile::SampleFilter::UniquePtr( result.release() ) ;
+	}
+	
+	metro::SampleStratification compute_stratification(
+		genfile::CohortIndividualSource const& samples,
+		std::string const& column
+	) const {
+		using genfile::string_utils::to_string ;
+
+		metro::SampleStratification result ;
+		genfile::CohortIndividualSource::ColumnSpec const& column_spec = samples.get_column_spec() ;
+
+		if( !column_spec[ column ].is_discrete() ) {
+			throw genfile::BadArgumentError(
+				"PerVariantComputationManager::get_stratification()",
+				"column=\"" + column + "\"",
+				"argument to -stratify must be a discrete covariate in the sample file."
+			) ;
+		}
+		// Add strata.
+		// We do this via the a value mapping in order to ensure that values are taken in sorted order.
+		genfile::CrossCohortCovariateValueMapping::UniquePtr mapping
+			= genfile::CrossCohortCovariateValueMapping::create( column_spec[ column ] ) ;
+		mapping->add_source( samples ) ;
+		int const highest_level = int( mapping->get_number_of_distinct_mapped_values() ) ;
+		for( int level = 0; level < highest_level; ++level ) {
+			genfile::VariantEntry const unmapped_value = mapping->get_unmapped_value( level ) ;
+			std::vector< std::size_t > const samples_in_strata = samples.find_samples_by_value( column, unmapped_value ) ;
+			for( std::size_t i = 0; i < samples_in_strata.size(); ++i ) {
+				result.add_sample( column + "=" + to_string( unmapped_value ), samples_in_strata[i] ) ;
+			}
+		}
+		return result ;
+	}
+	
+	genfile::SNPDataSource::UniquePtr open_genotype_data_sources(
+		std::string const& filename,
+		genfile::CommonSNPFilter::UniquePtr filter,
+		std::set< std::size_t > const& excluded_samples,
+		bool threshold = false
+	) {
+		std::vector< genfile::wildcard::FilenameMatch > filenames
+			= genfile::wildcard::find_files_by_chromosome(
+				filename,
+				genfile::wildcard::eALL_CHROMOSOMES
+			) ;
+
+		genfile::SNPDataSource::UniquePtr source( 
+			genfile::SNPDataSourceChain::create(
+				filenames
+			).release()
+		) ;
+		if( filter.get() ) {
+			source.reset(
+				genfile::VariantIdentifyingDataFilteringSNPDataSource::create(
+					source,
+					genfile::VariantIdentifyingDataTest::UniquePtr( filter.release() )
+				).release()
+			) ;
+		}
+		if( threshold ) {
+			source.reset(
+				new genfile::ThreshholdingSNPDataSource( source, 0.9 )
+			) ;
+		}
+		if( excluded_samples.size() > 0 ) {
+			source.reset(
+				new genfile::SampleFilteringSNPDataSource( source, excluded_samples )
+			) ;
+		}
+		return source ;
+	}
+
+	void write_preamble(
+		genfile::CohortIndividualSource const& samples,
+		genfile::SNPDataSource const& host,
+		std::string const& outcome_name,
+		Eigen::MatrixXd const& outcome,
+		std::vector< metro::SampleRange > const& nonmissing_outcome
+	) {
+		std::size_t const N = samples.size() ;
+		get_ui_context().logger() << "Loaded data for " << N << " samples.\n" ;
+		get_ui_context().logger() << "  Predictor data:\n" << host.get_summary() << "\n" ;
+		get_ui_context().logger() << "         Outcome: \"" + outcome_name + "\": "
+			<< "0 (" << outcome.col(0).sum() << "), "
+			<< "1 (" << outcome.col(1).sum() << "), "
+			<< "NA (" << (N - metro::impl::count_range( nonmissing_outcome )) << ")\n" ;
+	}
+
+	void write_preamble(
+		genfile::CohortIndividualSource const& samples,
+		genfile::SNPDataSource const& host,
+		genfile::SNPDataSource const& para
+	) {
+		get_ui_context().logger() << "Loaded data for " << samples.size() << " samples.\n" ;
+		get_ui_context().logger() << "  Predictor data:\n" << host.get_summary() << "\n" ;
+		get_ui_context().logger() << "    Outcome data:\n" << para.get_summary() << "\n" ;
+	}
+
+	void test(
+		genfile::CartesianProductVisitor& visitor,
+		std::vector< std::string > const& model_names,
+		boost::ptr_vector< metro::regression::Design >& designs,
+		std::vector< Eigen::MatrixXd > const& predictorCodings,
+		qcdb::MultiVariantStorage& output
+	) {
+		using namespace metro ;
+		typedef std::vector< SampleRange > SampleRanges ;
+		int const N = designs[0].matrix().rows() ;
+
+		// Reserve some space for our variants
+		std::vector< genfile::VariantIdentifyingData > variants( 2 ) ;
+//		genfile::VariantIdentifyingData& pv = variants[0] ;
+//		genfile::VariantIdentifyingData& ov = variants[1] ;
+
+		// Storage for outcome gnenotypes
+		Matrix outcome = Matrix::Zero( N, 2 ) ;
+		Vector outcome_ploidy = Vector::Zero( N ) ;
+		SampleRanges nonmissing_outcome ;
+
+		// Storage for predictor gnenotypes
+		Matrix predictor_probabilities = Matrix::Zero( N, 3 ) ;
+		IntegerVector predictor_ploidy = IntegerVector::Zero( N ) ;
+		SampleRanges nonmissing_predictor ;
+
+		stats::impl::InfoComputation info_computation;
+
+		{
+			appcontext::UIContext::ProgressContext progress_context = get_ui_context().get_progress_context( "Testing" ) ;
+			std::size_t count = 0 ;
+			
+			bool have_summarised_models = false ;
+			bool outputAllVariants = options().check( "-output-all-variants" ) ;
+			bool const debug = options().check( "-debug" ) ;
+
+			while(
+				visitor.step(
+					[&] (
+						std::vector< int > const& changed,
+						std::vector< genfile::VariantIdentifyingData > const& variants,
+						std::vector< genfile::VariantDataReader::SharedPtr > const& readers
+					) {
+						bool predictorIncluded = true ;
+						double predictorCount = 0.0 ;
+						bool outcomeIncluded = true ;
+						double outcomeCount = 0.0 ;
+						if( changed[0] == 1 ) {
+//							std::cerr << "Predictor changed!" << ".\n" ;
+							predictorCount = set_predictor(
+								variants[0],
+								readers[0],
+								&predictor_probabilities,
+								&predictor_ploidy,
+								&nonmissing_predictor,
+								predictorCodings,
+								&designs
+							) ;
+							predictorIncluded = (predictorCount >= options().get< double >( "-minimum-predictor-count" )) ;
+						}
+
+						if( (changed.size() > 1) && (changed[1] == 1) ) {
+//							std::cerr << "Outcome changed!" << ".\n" ;
+							set_outcome_from_genotypes(
+								variants[1],
+								readers[1],
+								&outcome,
+								&outcome_ploidy,
+								&nonmissing_outcome,
+								&designs
+							) ;
+						}
+
+						{
+							outcomeCount = std::min(
+								designs[0].outcome().col(0).sum(),
+								designs[0].outcome().col(1).sum()
+							) ;
+							outcomeIncluded = (outcomeCount >= options().get< double >( "-minimum-outcome-count" )) ;
+						}
+
+						if( !have_summarised_models ) {
+							summarise_models( model_names, designs ) ;
+							have_summarised_models = true ;
+						}
+					
+						if( outputAllVariants || (predictorIncluded && outcomeIncluded)) {
+							output_design( designs[1], variants, designs[1].nonmissing_samples(), output ) ;
+
+							output.store_data_for_key( variants, "minimum_outcome_count", outcomeCount ) ;
+							output.store_data_for_key( variants, "minimum_predictor_count", predictorCount ) ;
+						
+							std::vector< metro::SampleRange > const included_samples = metro::impl::intersect_ranges(
+								nonmissing_predictor,
+								nonmissing_outcome
+							) ;
+
+							if( debug ) {
+								std::cerr << "INCLUDED SAMPLES: " << included_samples << "\n" ;
+							}
+						
+							output_cross_counts(
+								variants,
+								output,
+								cross_tabulate(
+									predictor_probabilities,
+									outcome,
+									outcome_ploidy,
+									included_samples
+								)
+							) ;
+								
+							info_computation.compute(
+								variants[0],
+								predictor_probabilities,
+								predictor_ploidy,
+								included_samples
+							) ;
+							output.store_data_for_key( variants, "predictor_info", info_computation.info() ) ;
+						}
+						// Set up ll
+						if( predictorIncluded && outcomeIncluded ) {
+							test( model_names, designs, variants, output ) ;
+						} 
+					}
+				)
+			) {
+				progress_context( ++count, visitor.count() ) ;
+			}
+		}
+	}
+
+	double set_predictor(
+		genfile::VariantIdentifyingData const& variant,
+		genfile::VariantDataReader::SharedPtr predictor_source,
+		Matrix* predictor_probabilities,
+		IntegerVector* predictor_ploidy,
+		std::vector< metro::SampleRange >* nonmissing_predictor,
+		std::vector< Eigen::MatrixXd > const& predictorCodings,
+		boost::ptr_vector< metro::regression::Design >* designs
+	) {
+		bool const debug = options().check( "-debug" ) ;
+
+		ProbSetter predictor_setter( predictor_probabilities, predictor_ploidy, nonmissing_predictor ) ;
+		if( options().check( "-coerce-predictor-to-haploid" )) {
+			predictor_setter.set_coerce_to_haploid() ;
+		}
+		if( options().check( "-predictor-genotype-call-threshold" )) {
+			predictor_setter.set_threshold( options().get< double >( "-predictor-genotype-call-threshold" )) ;
+		}
+		predictor_source->get( ":genotypes:", genfile::to_GP_unphased( predictor_setter )) ;
+
+		Eigen::MatrixXd stratified_predictor_probs ;
+
+		stratify_predictors(
+			*predictor_probabilities,
+			m_stratification,
+			&m_regression_predictor_probs
+		) ;
+		int const D = m_regression_predictor_probs.cols() ;
+		
+		// designs[0] is null model, specify a 0-column matrix.
+		// To avoid any miscounting between this and alt models,
+		// the samples are wrighted by total probability.
+		// This should make no difference in most cases but in some genotype data
+		// a 'null' genotype probability was called.
+		(*designs)[0].set_predictors(
+			Eigen::MatrixXd::Zero( 1, 0 ),
+			m_regression_predictor_probs.rowwise().sum(),
+			*nonmissing_predictor
+		) ;
+
+		// designs[1..] are alternative models
+		for( std::size_t i = 1; i < designs->size(); ++i ) {
+			assert( predictorCodings[i].rows() == D ) ;
+			(*designs)[i].set_predictors(
+				predictorCodings[i],
+				m_regression_predictor_probs,
+				*nonmissing_predictor
+			) ;
+		}
+
+		double const predictorCount = 
+			std::min(
+				(predictor_probabilities->col(1) + 2.0 * predictor_probabilities->col(2)).array().sum(),
+				(predictor_probabilities->col(1) + 2.0 * predictor_probabilities->col(0)).array().sum()
+			) ;
+
+		if( debug ) {
+			std::cerr << "PREDICTOR PROBS:\n"
+				<< predictor_probabilities->block(
+					0, 0,
+					std::min( 30, int( predictor_probabilities->rows() ) ), predictor_probabilities->cols()
+				).transpose() << "\n" ;
+			std::cerr << "PREDICTOR INCLUDED SAMPLES: " << (*nonmissing_predictor) << "\n" ;
+			std::cerr << "PREDICTOR CODINGS:\n" ;
+			for( std::size_t i = 1; i < designs->size(); ++i ) {
+				std::cerr << predictorCodings[i] << ".\n" ;
+			}
+		}
+
+		return predictorCount ;
+	}
+
+	void set_outcome_from_sample_column(
+		genfile::CohortIndividualSource const& samples,
+		std::string const& outcome_name,
+		boost::ptr_vector< metro::regression::Design >* designs
+	) {
+		if( samples.get_column_spec()[outcome_name].type() != genfile::CohortIndividualSource::e_BINARY_PHENOTYPE ) {
+			throw genfile::BadArgumentError(
+				"set_outcome_from_sample_column()",
+				"outcome_name=\"" + outcome_name + "\"",
+				"The column must be a binary phenotype column (type B)"
+			) ;
+		}
+
+		std::size_t N = samples.size() ;
+		Eigen::MatrixXd outcome = Eigen::MatrixXd::Zero( N, 2 ) ;
+		std::vector< metro::SampleRange > nonmissing_outcome ;
+
+		{
+			std::size_t start = 0 ;
+			samples.get_column_values(
+				outcome_name,
+				[&]( std::size_t i, genfile::VariantEntry const& value ) {
+					if( value.is_missing() ) {
+						if( i > start ) {
+							nonmissing_outcome.push_back(
+								metro::SampleRange( start, i )
+							) ;
+						}
+						start = i+1 ;
+					} else {
+						int const column = value.as< int >() ;
+						assert( column == 0 || column == 1 ) ;
+						outcome(i,column) = 1 ;
+					}
+					if( i == N-1 && !value.is_missing() ) {
+						nonmissing_outcome.push_back(
+							metro::SampleRange( start, i+1 )
+						) ;
+					}
+				}
+			) ;
+		}
+
+		for( std::size_t i = 0; i < designs->size(); ++i ) {
+			designs->at(i).set_outcome(
+				outcome,
+				nonmissing_outcome,
+				std::vector< std::string >({outcome_name + "=0", outcome_name + "=1"} )
+			) ;
+		}
+	}
+
+	void set_outcome_from_genotypes(
+		genfile::VariantIdentifyingData const& variant,
+		genfile::VariantDataReader::SharedPtr outcomeReader,
+		Matrix* outcome,
+		Vector* outcome_ploidy,
+		std::vector< metro::SampleRange >* nonmissing_outcome,
+		boost::ptr_vector< metro::regression::Design >* designs
+	) {
+		bool result = true ;
+		bool const debug = options().check( "-debug" ) ;
+		AlleleCounter counter( outcome, outcome_ploidy, nonmissing_outcome ) ;
+		if( options().check( "-coerce-outcome-to-haploid" )) {
+			counter.set_coerce_to_haploid() ;
+		}
+		if( outcomeReader->supports( "GT" )) {
+			outcomeReader->get( "GT", counter ) ;
+		} else if( outcomeReader->supports( "GP" )) {
+			outcomeReader->get(
+				"GP",
+				genfile::GPThresholdingGTSetter(
+					counter,
+					options().get< double >( "-outcome-genotype-call-threshold" )
+				)
+			) ;
+		} else {
+			throw genfile::BadArgumentError(
+				"HPTestApplication::test()",
+				"outcome_source",
+				"Source must support hard genotype calls (GT) or genotype probabilities (GP) field."
+			) ;
+		}
+		if( debug ) {
+			std::cerr << "OUTCOME:\n" << outcome->block(
+				0, 0,
+				std::min( 30, int( outcome->rows() ) ), outcome->cols()
+			).transpose() << ".\n" ;
+			std::cerr << "OUTCOME INCLUDED SAMPLES: " << (*nonmissing_outcome) << "\n" ;
+		}
+
+		std::string const& outcomeName = options().get< std::string >( "-outcome-name" ) ;
+
+		for( std::size_t i = 0; i < designs->size(); ++i ) {
+			(*designs)[i].set_outcome(
+				*outcome,
+				*nonmissing_outcome,
+				std::vector< std::string >({outcomeName + "=0", outcomeName + "=1"} )
+			) ;
+		}
+	}
+
+	Matrix cross_tabulate(
+		Matrix const& predictor,
+		Matrix const& outcome,
+		Vector const& outcome_ploidy,
+		std::vector< metro::SampleRange > const& ranges
+	) {
+		typedef Eigen::Block< Matrix > MatrixBlock ;
+		typedef Eigen::Block< Matrix const > ConstMatrixBlock ;
+
+		Matrix result = Matrix::Zero( outcome.cols(), predictor.cols() ) ;
+		for( std::size_t i = 0; i < ranges.size(); ++i ) {
+			metro::SampleRange const& range = ranges[i] ;
+			ConstMatrixBlock outcome_block = outcome.block( range.begin(), 0, range.size(), outcome.cols() ) ;
+			ConstMatrixBlock predictor_block = predictor.block( range.begin(), 0, range.size(), predictor.cols() ) ;
+			for( int j = 0; j < outcome.cols(); ++j ) {
+				for( int k = 0; k < predictor.cols(); ++k ) {
+					result(j, k) += ( outcome_block.col( j ).transpose() * predictor_block.col(k) ) ;
+				}
+			}
+		}
+		return result ;
+	}
+
+	void output_cross_counts(
+		std::vector< genfile::VariantIdentifyingData > const& variants,
+		qcdb::MultiVariantStorage& output,
+		Matrix const& cross_counts
+	) {
+
+		{
+			Matrix conversion( 3, 2 ) ;
+			conversion << 	2, 0,
+							1, 1,
+							0, 2 ;
+			Matrix predictorCount = cross_counts * conversion ;
+			Matrix::Index row, col ;
+			double const minimum_expected_predictor_count = predictorCount.minCoeff( &row, &col ) ;
+			output.store_data_for_key( variants, "minimum_expected_predictor_allele_count", minimum_expected_predictor_count ) ;
+			output.store_data_for_key(
+				variants,
+				"minimum_expected_predictor_allele_count_genotype",
+				( boost::format( "outcome=%d/predictor=%d" ) % row % col ).str()
+			) ;
+		}
+		
+		if( options().check( "-output-counts" )) {
+			for( int outcome_i = 0; outcome_i < cross_counts.rows(); ++outcome_i ) {
+				for( int predictor_i = 0; predictor_i < cross_counts.cols(); ++predictor_i ) {
+					output.store_data_for_key(
+						variants,
+						( boost::format( "outcome=%d/predictor=%d" ) % outcome_i % predictor_i ).str(),
+						cross_counts( outcome_i, predictor_i )
+					) ;
+				}
+			}
+		}
+	}
+
+	void build_models(
+		genfile::CohortIndividualSource const& samples,
+		std::vector< std::string >* names,
+		boost::ptr_vector< metro::regression::Design >* designs,
+		std::vector< Eigen::MatrixXd >* predictorCodings
+	) {
+		build_unadjusted_models( samples, names, designs, predictorCodings ) ;
+		if( options().check( "-covariates" )) {
+			add_covariates( samples, designs, options().get_values< std::string >( "-covariates" ) ) ;
+		}
+	}
+
+	void build_unadjusted_models(
+		genfile::CohortIndividualSource const& samples,
+		std::vector< std::string >* names,
+		boost::ptr_vector< metro::regression::Design >* designs,
+		std::vector< Eigen::MatrixXd >* predictorCodings
+	) {
+		typedef std::vector< metro::SampleRange > SampleRanges ;
+		typedef std::vector< std::string > Names ;
+
+		std::string const& outcomeName = options().get< std::string >( "-outcome-name" ) ;
+
+		// baseline model, no predictor
+		{
+			names->push_back( "null" ) ;
+			designs->push_back(
+				metro::regression::Design::create(
+					Matrix::Zero( samples.size(), 2 ), SampleRanges(), Names({ outcomeName + "=0", outcomeName + "=1" }),
+					Names() // only baseline
+				)
+			) ;
+			predictorCodings->push_back( Eigen::MatrixXd(3,0) ) ;
+		}
+
+		// alternative models
+		std::vector< std::string > const& models = options().get_values< std::string >( "-model" ) ;
+		// Null model encoding
+
+		using genfile::string_utils::slice ;
+		// Alternative models encoding
+		for( std::size_t i = 0; i < models.size(); ++i ) {
+			std::vector< slice > elts = parse_model_spec( models[i] ) ;
+			std::string const& predictorCoding = elts[1] ;
+		
+			Matrix predictor_levels ;
+			Names predictorNames ;
+			if( predictorCoding == "add+het" ) {
+				predictor_levels = Eigen::MatrixXd::Zero( 3, 2 ) ;
+				// add predictor
+				predictor_levels(0,0) = 0 ;
+				predictor_levels(1,0) = 1 ;
+				predictor_levels(2,0) = 2 ;
+				// het predictor
+				predictor_levels(1,1) = 1 ;
+				predictorNames = Names({"add", "overdominance"}) ;
+			} else if( predictorCoding == "add" ) {
+				predictor_levels = Eigen::MatrixXd::Zero( 3, 1 ) ;
+				// add predictor
+				predictor_levels(0,0) = 0 ;
+				predictor_levels(1,0) = 1 ;
+				predictor_levels(2,0) = 2 ;
+				predictorNames = Names({"add"}) ;
+			} else if( predictorCoding == "dom" ) {
+				predictor_levels = Eigen::MatrixXd::Zero( 3, 1 ) ;
+				// add predictor
+				predictor_levels(0,0) = 0 ;
+				predictor_levels(1,0) = 1 ;
+				predictor_levels(2,0) = 1 ;
+				predictorNames = Names({"dom"}) ;
+			} else if( predictorCoding == "rec" ) {
+				predictor_levels = Eigen::MatrixXd::Zero( 3, 1 ) ;
+				// add predictor
+				predictor_levels(0,0) = 0 ;
+				predictor_levels(1,0) = 0 ;
+				predictor_levels(2,0) = 1 ;
+				predictorNames = Names({"rec"}) ;
+			} else if( predictorCoding == "het" ) {
+				predictor_levels = Eigen::MatrixXd::Zero( 3, 1 ) ;
+				// add predictor
+				predictor_levels(0,0) = 0 ;
+				predictor_levels(1,0) = 1 ;
+				predictor_levels(2,0) = 0 ;
+				predictorNames = Names({"het"}) ;
+			} else if( predictorCoding == "haploid" ) {
+				predictor_levels = Eigen::MatrixXd::Zero( 2, 1 ) ;
+				predictor_levels(0,0) = 0 ;
+				predictor_levels(1,0) = 1 ;
+				predictorNames = Names({"haploid"}) ;
+			} else if( predictorCoding == "coerced-haploid" ) {
+				predictor_levels = Eigen::MatrixXd::Zero( 3, 1 ) ;
+				predictor_levels(0,0) = 0 ;
+				predictor_levels(2,0) = 1 ;
+				predictorNames = Names({"coerced-haploid"}) ;
+			} else {
+				assert(0) ;
+			}
+
+			if( m_stratification.size() > 0 ) {
+				stratify_model( &predictor_levels, &predictorNames, m_stratification ) ;
+			}
+
+			names->push_back( elts[0] ) ;
+			designs->push_back(
+				metro::regression::Design::create(
+					Matrix::Zero( samples.size(), 2 ), SampleRanges(), Names({ "outcome=0", "outcome=1" }),
+					predictorNames
+				)
+			) ;
+			predictorCodings->push_back( predictor_levels ) ;
+		}
+	}
+	
+	// This must be implemented to match stratify_predictors() below.
+	// Each column of the levels corresponds to a parameter and each row to a predictor level.
+	// We expand the predictors so that each parameter is split into one parameter per strata.
+	void stratify_model(
+		Eigen::MatrixXd* predictor_levels,
+		std::vector< std::string >* predictor_names,
+		metro::SampleStratification const& stratification
+	) {
+		int const L = predictor_levels->rows() ;
+		int const P = predictor_levels->cols() ;
+		Eigen::MatrixXd stratified(
+			L * stratification.number_of_strata(),
+			P * stratification.number_of_strata()
+		) ;
+		stratified.setZero() ;
+		std::vector< std::string > stratified_names ;
+		for( std::size_t stratum_i = 0; stratum_i < stratification.number_of_strata(); ++stratum_i ) {
+			for( std::size_t j = 0; j < stratification.stratum(stratum_i).size(); ++j ) {
+				stratified.block(
+					stratum_i * L, stratum_i,
+					L, P
+				) = (*predictor_levels) ;
+			}
+			for( std::size_t name_i = 0; name_i < predictor_names->size(); ++name_i ) {
+				stratified_names.push_back( predictor_names->at(name_i) + "/" + stratification.stratum_name( stratum_i )) ;
+			}
+		}
+		
+		(*predictor_levels) = stratified ;
+		(*predictor_names) = stratified_names ;
+	}
+	
+	// This must be implemented to match stratify_models() above.
+	void stratify_predictors(
+		Eigen::MatrixXd const& predictor_probs,
+		metro::SampleStratification const& stratification,
+		Eigen::MatrixXd* result
+	) {
+		if( stratification.size() == 0 ) {
+			*result = predictor_probs ;
+			return ;
+		}
+		int const N = predictor_probs.rows() ;
+		int const L = predictor_probs.cols() ;
+
+		Eigen::MatrixXd stratified_predictor_probs( N, L * stratification.size() ) ;
+		stratified_predictor_probs.setZero() ;
+		for( std::size_t i = 0; i < stratification.size(); ++i ) {
+			for( std::size_t j = 0; j < stratification.stratum(i).size(); ++j ) {
+				metro::SampleRange const& range = stratification.stratum(i)[j] ;
+				Eigen::Block< Eigen::MatrixXd const > const block = predictor_probs.block(
+					range.begin(), 0,
+					range.size(), L
+				) ;
+				stratified_predictor_probs.block(
+					range.begin(), L * i,
+					range.size(), L
+				) = block ;
+			}
+		}
+		
+		*result = stratified_predictor_probs ;
+	}
+	
+	std::vector< genfile::string_utils::slice > parse_model_spec( genfile::string_utils::slice const& spec ) {
+		std::vector< genfile::string_utils::slice > result = spec.split( ":" ) ;
+		if( result.size() == 1 ) {
+			// model name is same as spec
+			result.insert( result.begin(), result[0] ) ;
+		}
+		if( result.size() != 2 ) {
+			throw genfile::BadArgumentError(
+				"HPTestApplication::parse_model_spec()",
+				"spec=\"" + spec + "\"",
+				"Expected a model spec in the form <name>:<model>"
+			) ;
+		}
+		return result ;
+	}
+
+	void add_covariates(
+		genfile::CohortIndividualSource const& samples,
+		boost::ptr_vector< metro::regression::Design >* designs,
+		std::vector< std::string > const& covariates
+	) {
+		get_ui_context().logger() << "Adding covariates...\n" ;
+
+		genfile::CohortIndividualSource::ColumnSpec const& spec = samples.get_column_spec() ;
+		for( std::size_t i = 0; i < covariates.size(); ++i ) {
+			std::string const& covariateName = covariates[i] ;
+			genfile::CohortIndividualSource::SingleColumnSpec columnSpec = spec[covariateName] ;
+			genfile::CrossCohortCovariateValueMapping::UniquePtr mapping
+				= genfile::CrossCohortCovariateValueMapping::create( columnSpec, true ) ;
+			mapping->add_source( samples ) ;
+		
+			if( mapping->get_number_of_distinct_mapped_values() == 0 ) {
+				throw genfile::BadArgumentError(
+					"add_covariates()",
+					"-covarariates"
+					"Covariate \"" + covariates[i] + "\" has no non-missing levels in this set of samples."
+				) ;
+			}
+			for( std::size_t model_i = 0; model_i < designs->size(); ++model_i ) {
+				metro::regression::Design& design = designs->at(model_i) ;
+				
+				if( columnSpec.is_discrete() ) {
+					design.add_discrete_covariate(
+						covariateName,
+						boost::bind(
+							&extract_mapped_categorical_value,
+							_1,
+							boost::cref( samples ),
+							spec.find_column( covariateName ),
+							boost::cref( *mapping )
+						),
+						boost::bind(
+							&get_unmapped_level,
+							boost::cref( *mapping ),
+							_1
+						),
+						mapping->get_number_of_distinct_mapped_values()
+					) ;
+				} else {
+					design.add_single_covariate(
+						covariateName,
+						boost::bind(
+							&extract_mapped_continuous_value,
+							_1,
+							boost::cref( samples ),
+							spec.find_column( covariateName ),
+							boost::cref( *mapping )
+						)
+					) ;
+				}
+			}
+			
+			get_ui_context().logger()
+				<< "++ Added covariate: \"" + covariateName + "\":\n"
+				<<  mapping->get_summary( "     " )
+				<< "\n\n" ;
+		}
+	}
+	
+	void summarise_models(
+		std::vector< std::string > const& model_names,
+		boost::ptr_vector< metro::regression::Design >& designs
+	) {
+		get_ui_context().logger() << "Models are:\n" ;
+		for( std::size_t i = 0; i < designs.size(); ++i ) {
+			metro::regression::LogLikelihood::UniquePtr model = create_loglikelihood( designs[i] ) ; 
+			get_ui_context().logger() << "- Model " << (i+1) << " (\"" + model_names[i] << "\"): "
+				<< model->get_summary() << "\n" ;
+		}
+		get_ui_context().logger() << "Model design for first test:\n" << designs.back().get_summary() << ".\n" ;
+		get_ui_context().logger() << "\n" ;
+	}
+	
+	void output_design(
+		metro::regression::Design& design,
+		std::vector< genfile::VariantIdentifyingData > const& variants,
+		std::vector< metro::SampleRange > const& included_samples,
+		qcdb::MultiVariantStorage& output
+	) {
+		metro::regression::Design::Matrix const& outcome = design.outcome() ;
+#if DEBUG
+		//std::cerr << "OUTCOME:\n" << outcome << "\n" ;
+#endif
+		std::map< int, int > outcomeCounts ;
+		int const maxOutcome = std::max( outcome.array().maxCoeff(), 2.0 ) ;
+		for( int i = 0; i <= maxOutcome; ++i ) {
+			outcomeCounts[i] = 0 ;
+		}
+		// Count outcome levels, sensitive to the included samples
+		int total = 0 ;
+		for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+			total += (included_samples[i].end() - included_samples[i].begin()) ;
+			for( int j = included_samples[i].begin(); j < included_samples[i].end(); ++j ) {
+				++outcomeCounts[outcome(j,1)] ;
+			}
+		}
+
+		output.store_data_for_key( variants, "N", total ) ;
+		output.store_data_for_key( variants, "missing", int( design.outcome().rows() - total ) ) ;
+		
+		for(
+			std::map< int, int >::const_iterator i = outcomeCounts.begin();
+			i != outcomeCounts.end();
+			++i
+		) {
+			output.store_data_for_key(
+				variants,
+				( boost::format( "outcome=%d" ) % i->first ).str(),
+				i->second
+			) ;
+		}
+		
+		for( int g = 0; g < design.get_number_of_predictor_levels(); ++g ) {
+			double sum = 0.0 ;
+			for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+				sum += design.get_predictor_level_probabilities().col(g).segment(
+					included_samples[i].begin(),
+					included_samples[i].end() - included_samples[i].begin() 
+				).sum() ;
+			}
+			
+			output.store_data_for_key(
+				variants,
+				( boost::format( "predictor=%d" ) % g ).str(),
+				sum
+			) ;
+		}
+	}
+
+	metro::regression::LogLikelihood::UniquePtr create_loglikelihood( metro::regression::Design& design ) {
+		uint32_t const threads = options().get< uint32_t >( "-threads" ) ;
+		metro::regression::LogLikelihood::UniquePtr ll ;
+		if( threads > 0 ) {
+			if( !m_pool.get() ) {
+				m_pool = metro::concurrency::threadpool::create( threads ) ;
+			}
+			ll.reset(
+				metro::regression::ThreadedLogLikelihood::create(
+					design,
+					[]( metro::regression::Design& design, std::vector< metro::SampleRange > range ) {
+						metro::regression::LogLikelihood::UniquePtr ll(
+							metro::regression::BinomialLogistic::create( design, range ).release()
+						) ;
+						return ll ;
+					},
+					*m_pool
+				).release()
+			) ;
+		} else {
+			ll.reset(
+				metro::regression::BinomialLogistic::create( design ).release()
+			) ;
+		}
+		if( !options().check_if_option_has_value( "-no-prior" )) {
+			ll = apply_priors( ll, m_prior_specs ) ;
+		}
+		return ll ;
+	}
+
+	std::vector< std::string > expand_prior_specs(
+		std::vector< std::string > const& specs
+	) const {
+		// Expand any specs by the stratification, if needed
+		std::string const& outcome_name = options().get< std::string >( "-outcome-name" ) ;
+		std::vector< std::string > result;
+		for( std::size_t i = 0; i < specs.size(); ++i ) {
+			std::string spec = specs[i] ;
+
+			// replace [outcome] with outcome name
+			{
+				std::size_t where = spec.find( "[outcome]" ) ;
+				if( where != std::string::npos ) {
+					spec = spec.substr( 0, where )
+						+ outcome_name
+						+ spec.substr( where + 9, spec.size() ) ;
+				}
+			}
+
+			std::size_t where = spec.find( "/[stratum]" ) ;
+			if( where == std::string::npos ) {
+				result.push_back( specs[i] ) ;
+			} else if( m_stratification.size() == 0 ) {
+				// no stratification, remove /[stratum] part of spec
+				result.push_back( 
+					spec.substr( 0, where )
+					+ spec.substr( where + 10, spec.size() )
+				) ;
+			} else {
+				for( std::size_t j = 0; j < m_stratification.size(); ++j ) {
+					result.push_back( 
+					spec.substr( 0, where )
+						+ "/" + m_stratification.stratum_name(j)
+						+ spec.substr( where + 10, spec.size() )
+					) ;
+				}
+			}
+		}
+		return result ;	
+	}
+
+	metro::regression::LogLikelihood::UniquePtr apply_priors(
+		metro::regression::LogLikelihood::UniquePtr ll,
+		std::vector< std::string > specs
+	) const {
+		std::vector< int > gaussian_parameter_indices ;
+		std::vector< double > gaussian_variances ;
+		std::vector< double > gaussian_means ;
+		std::vector< int > logF_parameter_indices ;
+		std::vector< double > logF_nu1 ;
+		std::vector< double > logF_nu2 ;
+		std::map< std::string, int > used_parameters ;
+
+		using genfile::string_utils::to_lower ;
+		using genfile::string_utils::to_repr ;
+
+		typedef std::map< std::string, int > ParameterNameMap ;
+		ParameterNameMap parameter_index_by_name ;
+		{
+			metro::regression::LogLikelihood::IntegerMatrix const identity = ll->identify_parameters() ;
+			for( int i = 0; i < identity.rows(); ++i ) {
+				parameter_index_by_name[ ll->get_parameter_name(i) ] = i ;
+			}
+		}
+	
+		// Gather and parse all the data
+		for( std::size_t i = 0; i < specs.size(); ++i ) {
+			//std::cerr << "SPEC: \"" << specs[i] << "\".\n" ;
+			std::string parameter_name ;
+			std::string distribution ;
+			std::vector< std::string > parameters ;
+			parse_prior_spec(
+				specs[i],
+				&parameter_name,
+				&distribution,
+				&parameters,
+				options().get< std::string >( "-outcome-name" )
+			) ;
+
+			++used_parameters[parameter_name] ;
+			if( used_parameters[parameter_name] > 1 ) {
+				throw genfile::BadArgumentError(
+					"PerVariantComputationManager::apply_priors()",
+					"spec=\"" + specs[i] + "\"",
+					(boost::format(
+						"More than one prior specified for parameter \"%s\"" ) % parameter_name ).str()
+				) ;
+			}
+			
+			ParameterNameMap::const_iterator where = parameter_index_by_name.find( parameter_name ) ;
+			if( where != parameter_index_by_name.end() ) {
+				if( to_lower( distribution ) == "gaussian" ) {
+					if( parameters.size() != 2 ) {
+						throw genfile::BadArgumentError(
+							"PerVariantComputationManager::apply_priors()",
+							"spec=\"" + specs[i] + "\"",
+							(boost::format(
+								"Wrong number of parameters found for gaussian distribution (\"%d\", expected 2) - please specify mean and variance."
+									) % parameters.size()).str()
+						) ;
+					}
+				
+					gaussian_means.push_back( to_repr< double >( parameters[0] )) ;
+					gaussian_variances.push_back( to_repr< double >( parameters[1] )) ;
+					gaussian_parameter_indices.push_back( where->second ) ;
+				} else if( to_lower( distribution ) == "logf" ) {
+					if( parameters.size() != 2 ) {
+						throw genfile::BadArgumentError(
+							"PerVariantComputationManager::apply_priors()",
+							"spec=\"" + specs[i] + "\"",
+							(boost::format(
+								"Wrong number of parameters found for log F distribution (\"%d\", expected 2) - please specify nu1 and nu2"
+									) % parameters.size()).str()
+						) ;
+					}
+					logF_nu1.push_back( to_repr< double >( parameters[0] )) ;
+					logF_nu2.push_back( to_repr< double >( parameters[1] )) ;
+					logF_parameter_indices.push_back( where->second ) ;
+				} else {
+					throw genfile::BadArgumentError(
+						"PerVariantComputationManager::apply_priors()",
+						"spec=\"" + specs[i] + "\"",
+						(boost::format( "Unrecognised distribution specified (\"%s\"), should be \"gaussian\" or \"logF\"" ) % distribution).str()
+					) ;
+				}
+			}
+		}
+		
+		if( !options().check( "-no-covariate-priors" )) {
+			metro::regression::LogLikelihood::IntegerMatrix const identity = ll->identify_parameters() ;
+			for( int i = 0; i < identity.rows(); ++i ) {
+				std::string const& parameter_name = ll->get_parameter_name(i) ;
+				if( identity(i,1) > ll->design().number_of_predictors() && used_parameters[parameter_name] == 0 ) {
+					logF_parameter_indices.push_back(i) ;
+					// Choose a logF distribution with 95% coverage interval
+					// equivalent to a gaussian(0,40^2) distribution.
+					logF_nu1.push_back( 0.07704070 ) ;
+					logF_nu2.push_back( 0.07704070 ) ;
+				}
+			}
+		}
+		
+		
+		// Now apply the priors:
+		metro::regression::LogLikelihood::UniquePtr result( ll.release() ) ;
+		if( gaussian_parameter_indices.size() > 0 ) {
+			result.reset(
+				metro::regression::IndependentNormalWeightedLogLikelihood::create(
+					result,
+					gaussian_parameter_indices,
+					gaussian_means, gaussian_variances
+				).release()
+			) ;
+		}
+		if( logF_parameter_indices.size() > 0 ) {
+			result.reset(
+				metro::regression::IndependentLogFWeightedLogLikelihood::create(
+					result,
+					logF_parameter_indices,
+					logF_nu1, logF_nu2
+				).release()
+			) ;
+		}
+		return( result ) ;
+	}
+
+	// parse a parameter prior distribution specification string
+	// The spec should be of the form:
+	// <parameter_name>~<family>(<parameters>)
+	// Currently acceptable families are:
+	// logf (for a logF distribution)
+	// gaussian (for a gaussian distribution)
+	void parse_prior_spec(
+		std::string const& spec,
+		std::string* parameter_name,
+		std::string* distribution,
+		std::vector< std::string >* parameters,
+		std::string const& outcome_name
+	) const {
+		using genfile::string_utils::split ;
+		using genfile::string_utils::to_repr ;
+		using genfile::string_utils::slice ;
+		std::vector< slice > const elts = slice( spec ).split( "~" ) ;
+		if( elts.size() != 2 ) {
+			throw genfile::BadArgumentError(
+				"PerVariantComputationManager::parse_prior_spec()",
+				"spec=\"" + spec + "\"",
+				(boost::format(
+					"Malformatted value (\"%s\") specified, should be of the form <parameter name>~<family>(<parameters>)\n"
+						" where family is one of \"gaussian\" or \"logF\"") % spec).str()
+			) ;
+		}
+		std::vector< slice > const distribution_spec = elts[1].split( "()" ) ;
+		if(
+			distribution_spec.size() != 3
+			|| distribution_spec[1].size() < 2
+			|| distribution_spec[2].size() > 0
+		) {
+			throw genfile::BadArgumentError(
+				"PerVariantComputationManager::parse_prior_spec()",
+				"spec=\"" + spec + "\"",
+				(boost::format(
+					"Malformatted distribution (\"%s\") specified, should be of the form <family>(<parameters>)\n"
+						" where family is one of \"gaussian\" or \"logF\"") % elts[1]).str()
+			) ;
+		}
+		std::vector< slice > const parameter_spec = distribution_spec[1].split( "," ) ;
+
+		{
+			std::string parameterSpec = elts[0] ;
+			std::size_t where = parameterSpec.find( "[outcome]" ) ;
+			if( where != std::string::npos ) {
+				parameterSpec = parameterSpec.substr( 0, where )
+					+ outcome_name
+					+ parameterSpec.substr( where + 9, parameterSpec.size() ) ;
+			}
+			*parameter_name = parameterSpec ;
+		}
+
+		{
+			std::string parameterSpec = elts[0] ;
+			std::size_t where = parameterSpec.find( "/[stratum]" ) ;
+			if( where != std::string::npos ) {
+				if( m_stratification.size() == 0 ) {
+					parameterSpec = parameterSpec.substr( 0, where )
+						+ ""
+						+ parameterSpec.substr( where + 9, parameterSpec.size() ) ;
+				}
+			}
+			*parameter_name = parameterSpec ;
+		}
+		
+		*distribution = distribution_spec[0] ;
+		parameters->assign( parameter_spec.begin(), parameter_spec.end() ) ;
+	}
+
+	void test(
+		std::vector< std::string > const& model_names,
+		boost::ptr_vector< metro::regression::Design >& designs,
+		std::vector< genfile::VariantIdentifyingData > const& variants,
+		qcdb::MultiVariantStorage& output
+	) {
+		using namespace metro::regression ;
+		boost::ptr_vector< LogLikelihood > lls ;
+		for( std::size_t i = 0; i < designs.size(); ++i ) {
+			lls.push_back( create_loglikelihood( designs[i] )) ;
+		}
+
+		std::string const output_models = options().get< std::string > ( "-output-models" ) ;
+		if( output_models != "all" && output_models != "alternative" ) {
+			throw genfile::BadArgumentError(
+				"HPTestApplication::test()",
+				"output_models=\"" + output_models + "\"",
+				"Please specify \"alternative\" or \"all\"."
+			) ;
+		}
+		std::vector< std::string > comments ;
+		for( std::size_t model = 0; model < lls.size(); ++model ) {
+			boost::timer::cpu_timer timer ;
+			LogLikelihood& ll = lls[model] ;
+			std::string const& model_name = model_names[model] ;
+
+			metro::CholeskyStepper::Tracer tracer ;
+			if( options().check( "-debug" )) {
+				tracer = [this] ( 
+					int iteration,
+					double ll,
+					double target_ll,
+					metro::CholeskyStepper::Vector const& point,
+					metro::CholeskyStepper::Vector const& first_derivative,
+					metro::CholeskyStepper::Vector const& step,
+					bool converged
+				) {
+					this->get_ui_context().logger()
+						<< " ITERATION:" << iteration << "\n"
+						<< "        LL:" << ll << "\n"
+						<< "    TARGET:" << target_ll << "\n"
+						<< "     POINT:" << point.transpose() << "\n"
+						<< "DERIVATIVE:" << first_derivative.transpose() << "\n"
+						<< "      STEP:" << step.transpose() << "\n"
+						<< " CONVERGED:" << ( converged ? "yes" : "no" ) << "\n" ;
+				} ;
+			}
+
+			metro::CholeskyStepper stopping_condition(
+					options().get_value< double >( "-tolerance" ),
+					options().get_value< double >( "-max-iterations" ),
+					tracer
+				) ;
+
+			std::pair< bool, int > result = metro::fit_model(
+				ll,
+				model_name,
+				Eigen::VectorXd::Zero( ll.parameters().size() ),
+				stopping_condition,
+				&comments
+			) ;
+
+#if DEBUG
+			std::cerr << "hptest::test(): fit model in " << result.second << " iterations with " << ( result.first ? "convergence" : "no convergence" ) << ".\n" ;
+			for( std::size_t i = 0; i < ll.identify_parameters().rows(); ++i ) {
+				std::cerr << "model " << "NAME OF PARAMETER " << i << ": \"" << ll.get_parameter_name(i) << "\".\n" ;
+			}
+#endif
+		
+			output.store_data_for_key( variants, model_name + ":converged", result.first ? "1" : "0" ) ;
+			output.store_data_for_key( variants, model_name + ":iterations", result.second ) ;
+			output.store_data_for_key( variants, model_name + ":fit_time", boost::timer::format( timer.elapsed(), 4, "%t" ) ) ;
+			output.store_data_for_key( variants, model_name + ":ll", ll.get_value_of_function() ) ;
+			output.store_data_for_key(
+				variants,
+				model_name + ":degrees_of_freedom",
+				int( ll.parameters().size() - lls[0].parameters().size() )
+			) ;
+		
+			if( ( model > 0 || output_models == "all" ) && result.first ) {
+				output_results( lls[0], ll, variants, output, model_name, &comments ) ;
+			}
+		}
+		
+		if( comments.size() > 0 ) {
+			output.store_data_for_key(
+				variants,
+				"comment",
+				genfile::string_utils::join( comments, "," )
+			) ;
+		} else {
+			output.store_data_for_key(
+				variants,
+				"comment",
+				genfile::MissingValue()
+			) ;
+		}
+	}
+
+	void output_results(
+		metro::regression::LogLikelihood const& null_ll,
+		metro::regression::LogLikelihood const& ll,
+		std::vector< genfile::VariantIdentifyingData > const& variants,
+		qcdb::MultiVariantStorage& output,
+		std::string const& model_name,
+		std::vector< std::string >* comments
+	) {
+		Eigen::ColPivHouseholderQR< Matrix > null_solver ;
+		Eigen::ColPivHouseholderQR< Matrix > solver ;
+		Matrix const& information = -ll.get_value_of_second_derivative() ;
+		null_solver.compute( -null_ll.get_value_of_second_derivative() ) ;
+		solver.compute( information ) ;
+		Matrix const covariance = solver.solve( Matrix::Identity( information.rows(), information.cols() ) ) ;
+#if DEBUG
+		std::cerr << "Model " << model_name << ": information:\n"
+			<< information
+				<< ".\n" ;
+#endif
+		if( check_model_fit( information, covariance, model_name, comments ) ) {
+			std::vector< int > const parametersToOutput = get_parameters_to_output( ll ) ;
+			output_parameter_estimates( ll, variants, model_name, covariance, output, parametersToOutput ) ;
+		
+			metro::regression::LogPosteriorDensity const* posterior = dynamic_cast< metro::regression::LogPosteriorDensity const* >( &ll ) ;
+			if( posterior ) {	
+				compute_bayesian_summary(
+					null_ll, null_solver.logAbsDeterminant(),
+					*posterior, solver.logAbsDeterminant(), covariance,
+					model_name,
+					variants, output,
+					parametersToOutput,
+					comments
+				) ;
+			} else {
+				compute_frequentist_summary(
+					null_ll, ll,
+					model_name,
+					variants, output,
+					comments
+				) ;
+			}
+		}
+	}
+
+	bool check_model_fit(
+		Matrix const& information,
+		Matrix const& covariance,
+		std::string const& model_name,
+		std::vector< std::string >* comments
+	) const {
+		double const relative_error = (( information * covariance ) - Matrix::Identity( information.rows(), information.cols() ) ).norm() ;
+		if( relative_error != relative_error || relative_error > options().get< double >( "-tolerance" ) ) {
+			if( comments ) {
+				comments->push_back( model_name + ":singular" ) ;
+			}
+			return false ;
+		} else {
+			return true ;
+		}
+	}
+	
+	std::vector< int > get_parameters_to_output( metro::regression::LogLikelihood const& ll ) {
+		std::vector< int > result ;
+		int lower = 0 ;
+		int upper = 0 ;
+		std::string const output_parameters = options().get< std::string >( "-output-parameters" ) ;
+		if( options().get< std::string >( "-output-parameters" ) == "all" ) {
+			lower = 0 ;
+			upper = ll.parameters().size() ;
+		} else if( output_parameters == "genetic" ) {
+			lower = 1 ;
+			upper = lower + ll.design().number_of_predictors() ;
+		} else {
+			throw genfile::BadArgumentError(
+				"HPTestApplication::output_parameter_estimates()",
+				"-output-paramaters=\"" + output_parameters + "\"",
+				"Expected \"all\" or \"genetic\"."
+			) ;
+		}
+		for( int i = lower; i < upper; ++i ) {
+			result.push_back(i) ;
+		}
+		return result ;
+	}
+	
+	void output_parameter_estimates(
+		metro::regression::LogLikelihood const& ll,
+		std::vector< genfile::VariantIdentifyingData > const& variants,
+		std::string const& model_name,
+		Matrix const& covariance,
+		qcdb::MultiVariantStorage& output,
+		std::vector< int > const parametersToOutput
+	) const {
+		// Output parameter estimates, standard errors, etc.
+		metro::regression::LogLikelihood::IntegerMatrix const parameter_identity = ll.identify_parameters() ;
+		using genfile::string_utils::to_string ;
+
+		Vector const& parameters = ll.parameters() ;
+
+		for( std::size_t parameter_i = 0; parameter_i < parametersToOutput.size(); ++parameter_i ) {
+			int const i = parametersToOutput[parameter_i] ;
+			std::string const parameter_name = ll.get_parameter_name(i) ;
+			output.store_data_for_key( variants, model_name + ":beta_" + to_string( i ) + ":" + parameter_name, parameters( i ) ) ;
+		}
+
+		for( std::size_t parameter_i = 0; parameter_i < parametersToOutput.size(); ++parameter_i ) {
+			int const i = parametersToOutput[parameter_i] ;
+			output.store_data_for_key( variants, model_name + ":sd_" + to_string( i ) /*+ ":" + parameter_naming_scheme( i ) */, std::sqrt( covariance( i, i ) ) ) ;
+		}
+		for( std::size_t parameter_i = 0; parameter_i < parametersToOutput.size(); ++parameter_i ) {
+			int const i = parametersToOutput[parameter_i] ;
+			for( std::size_t parameter_j = parameter_i+1; parameter_j < parametersToOutput.size(); ++parameter_j ) {
+				int const j = parametersToOutput[parameter_j] ;
+				output.store_data_for_key( variants, model_name + ":cov_" + to_string( i ) + "," + to_string( j ), covariance( i, j ) ) ;
+			}
+		}
+	}
+	
+	double compute_twosided_wald_pvalue( double const beta, double const se ) const {
+		double result = std::numeric_limits< double >::quiet_NaN() ;
+		if( beta == beta && se > 0 ) {
+			boost::math::normal N( 0, se ) ;
+			result = 2 * boost::math::cdf( N, -std::abs( beta ) ) ;
+		}
+		return result ;
+	}
+	
+	void compute_bayesian_summary(
+		metro::regression::LogLikelihood const& null_ll,
+		double const logAbsNullDeterminant,
+		metro::regression::LogPosteriorDensity const& ll,
+		double const logAbsFullDeterminant,
+		Eigen::MatrixXd const& posterior_covariance,
+		std::string const& model_name,
+		std::vector< genfile::VariantIdentifyingData > const& variants,
+		qcdb::MultiVariantStorage& output,
+		std::vector< int > const parametersToOutput,
+		std::vector< std::string >* comments
+	) const {
+		//  P(alt|D)       P(D|alt)    P(alt)           P(alt)
+		// ---------   =   -------- x  ------    = BF x ------ 
+		// P(null|D)       P(D|null)   P(null)          P(null)
+		//
+		// where
+		//      ∫ P(theta|alt)P(D|theta)
+		// BF = -------------------------
+		//      ∫ P(theta|null)P(D|theta)
+		//
+		// We have only un-normalised estimates of the top and bottom integrand.
+		
+		// Use a laplace approximation to compute numerator and denominator of the BF
+		// The point is that we have an (approximate) estimate of the unnormalised posterior
+		// under the null and alternative models.  The normalising constant gives us the
+		// posterior.
+		Vector const& alternative_parameters = ll.parameters() ;
+		Vector const& null_parameters = null_ll.parameters() ;
+		double const log_2pi = std::log( 2.0 * 3.1415926535897932384626 ) ;
+		double const log_numerator
+			= ll.get_value_of_function()
+				+ 0.5 * ( (alternative_parameters.size() * log_2pi) - logAbsFullDeterminant ) ;
+		double const log_denominator
+			= null_ll.get_value_of_function()
+				+ 0.5 * ( (null_parameters.size() * log_2pi) - logAbsNullDeterminant ) ;
+		double const log10_bf = ( log_numerator - log_denominator ) / std::log(10) ;
+
+		output.store_data_for_key(
+			variants,
+			model_name + ":log10_bf",
+			log10_bf
+		) ;
+		
+		metro::regression::LogPosteriorDensity const* posterior = &ll ;
+		assert( posterior ) ;
+		if( posterior ) {
+			Eigen::VectorXd const prior_mode = posterior->get_prior_mode() ;
+			Matrix const ll_information = -posterior->get_loglikelihood_second_derivative() ;
+			Matrix const approxSamplingCovariance = posterior_covariance * ll_information * posterior_covariance ;
+			Eigen::ColPivHouseholderQR< Matrix > solver( approxSamplingCovariance ) ;
+			if( solver.info() == Eigen::Success ) {
+	#if 0
+				std::cerr << "      Posterior covariance:\n" << posterior_covariance << ",\n" ;
+				std::cerr << "Approx sampling covariance:\n" << approxSamplingCovariance << ".\n" ;
+				std::cerr << "                  Approx Z:\n" << z << ".\n" ;
+	#endif		
+				using genfile::string_utils::to_string ;
+				for( std::size_t parameter_i = 0; parameter_i < parametersToOutput.size(); ++parameter_i ) {
+					int const i = parametersToOutput[parameter_i] ;
+					output.store_data_for_key(
+						variants,
+						model_name + ":prior_mode_" + to_string(i),
+						prior_mode(i)
+					) ;
+					double const sampling_se = std::sqrt( approxSamplingCovariance(i,i)) ;
+					double const posterior_sd = std::sqrt( posterior_covariance(i,i)) ;
+					output.store_data_for_key(
+						variants,
+						model_name + ":se_" + to_string(i),
+						sampling_se
+					) ;
+			
+					std::string const parameter_name = ll.get_parameter_name(i) ;
+					if( sampling_se < posterior_sd / 10 ) {
+						output.store_data_for_key(
+							variants,
+							model_name + ":pvalue_" + to_string( i ),
+							metro::NA
+						) ;
+						comments->push_back(
+							parameter_name + ":sampling_se_<<_posterior_sd:_p-value_may_be_unreliable"
+						) ;
+					} else {
+						output.store_data_for_key(
+							variants,
+							model_name + ":pvalue_" + to_string( i ),
+							compute_twosided_wald_pvalue( alternative_parameters(i), std::sqrt( approxSamplingCovariance(i,i) ) )
+						) ;
+					}
+				}
+			}
+		}
+	}
+
+	void compute_frequentist_summary(
+		metro::regression::LogLikelihood const& null_ll,
+		metro::regression::LogLikelihood const& ll,
+		std::string const& model_name,
+		std::vector< genfile::VariantIdentifyingData > const& variants,
+		qcdb::MultiVariantStorage& output,
+		std::vector< std::string >* comments
+	) const {
+		Vector const& parameters = ll.parameters() ;
+		Vector const& null_parameters = null_ll.parameters() ;
+		// Now output the test statistic and p-value
+		double p_value = compute_lrt_pvalue(
+			null_ll.get_value_of_function(), ll.get_value_of_function(),
+			parameters.size() - null_parameters.size(),
+			options().get< double >( "-tolerance" )
+		) ;
+		if( p_value != p_value || p_value < 0 ) {
+			if( comments ) {
+				// This should not happen because the convergence criterion checks for this.
+				comments->push_back( model_name + ":numerical_error" ) ;
+			}
+			p_value = std::numeric_limits< double >::quiet_NaN() ;
+		}
+		output.store_data_for_key(
+			variants,
+			model_name + ":lrt_pvalue",
+			p_value
+		) ;
+	}	
+	
+	double compute_lrt_pvalue(
+		double const null_ll,
+		double const alternative_ll,
+		int degrees_of_freedom,
+		double const tolerance
+	) const {
+		double p_value = std::numeric_limits< double >::quiet_NaN() ;
+		double test_statistic = -2.0 * ( null_ll - alternative_ll ) ;
+		if( degrees_of_freedom > 0 && test_statistic >= -tolerance ) {
+			test_statistic = std::max( 0.0, test_statistic ) ;
+			boost::math::chi_squared_distribution< double > chi_squared_distribution( degrees_of_freedom ) ;
+			p_value = boost::math::cdf(
+				boost::math::complement(
+					chi_squared_distribution,
+					test_statistic
+				)
+			) ;
+		}
+		return p_value ;
+	}
+	
+} ;
+
+int main( int argc, char** argv ) {
+    try {
+		HPTestApplication app( argc, argv ) ;
+    }
+	catch( appcontext::HaltProgramWithReturnCode const& e ) {
+		return e.return_code() ;
+	}
+	return 0 ;
+}
+

ADDED   apps/index-kmers.cpp
Index: apps/index-kmers.cpp
==================================================================
--- apps/index-kmers.cpp
+++ apps/index-kmers.cpp
@@ -0,0 +1,492 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <map>
+#include <algorithm>
+#include <boost/unordered_map.hpp>
+#include <boost/bimap.hpp>
+#include "appcontext/CmdLineOptionProcessor.hpp"
+#include "appcontext/ApplicationContext.hpp"
+#include "appcontext/get_current_time_as_string.hpp"
+#include "genfile/MissingValue.hpp"
+#include "genfile/string_utils/string_utils.hpp"
+#include "components/SNPSummaryComponent/GenomeSequence.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLite3Connection.hpp"
+#include "genfile/db/SQLite3Statement.hpp"
+#include "genfile/db/Error.hpp"
+
+// #define DEBUG_IndexKmer 1
+
+namespace globals {
+	std::string const program_name = "index-kmers" ;
+	std::string const program_version = "dev" ;
+}
+
+namespace {
+	double const NA = std::numeric_limits< double >::quiet_NaN() ;
+	namespace impl {
+		char complement_allele( char a ) {
+			switch( a ) {
+				case 'A': a = 'T'; break ;
+				case 'G': a = 'C'; break ;
+				case 'C': a = 'G'; break ;
+				case 'T': a = 'A'; break ;
+			}
+			return a ;
+		}
+	
+		void reverse_complement( std::string* sequence ) {
+			std::reverse( sequence->begin(), sequence->end() ) ;
+			std::transform( sequence->begin(), sequence->end(), sequence->begin(), &impl::complement_allele ) ;
+		}
+	}
+}
+
+struct IndexKmerOptions: public appcontext::CmdLineOptionProcessor {
+	std::string get_program_name() const { return globals::program_name ; }
+
+	void declare_options( appcontext::OptionProcessor& options ) {
+		options.set_help_option( "-help" ) ;
+
+		{
+			options.declare_group( "Input data options" ) ;
+			options[ "-sequence" ]
+				.set_description( "Specify the path of a file containing sequence to load." )
+				.set_is_required()
+				.set_takes_values_until_next_option() ;
+			;
+		}
+		{
+			options.declare_group( "Analysis options" ) ;
+			options[ "-range" ]
+				.set_description( "Specify one or more ranges of SNPs to operate on. "
+					"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+					"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+					"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+				.set_takes_values_until_next_option()
+			;
+			options[ "-kmer-size" ]
+				.set_is_required()
+				.set_takes_single_value()
+				.set_description( "Specify the size of kmer to compute using." )
+			;
+			options[ "-analysis-name" ]
+				.set_description( "Specify a name to label results from this analysis with.  (This applies to modules which store their results in a qcdb file.)" )
+				.set_takes_single_value()
+				.set_default_value( "qctool analysis" ) ;
+			options[ "-analysis-chunk" ]
+				.set_description( "Specify a name denoting the current genomic region or chunk on which this is run.  This is intended for use in parallel environments." )
+				.set_takes_single_value()
+				.set_default_value( genfile::MissingValue() ) ;
+			options[ "-table-prefix" ]
+				.set_description( "Specify a prefix for the output table names." )
+				.set_takes_single_value()
+				.set_default_value( "" ) ;
+		}
+		{
+			options.declare_group( "Options affecting output" ) ;
+			options[ "-o" ]
+				.set_description( "Specify the path to the output file." )
+				.set_takes_single_value()
+				.set_is_required() ;
+			options[ "-include-diagonal" ]
+				.set_description( "Specify whether IndexKmer should include uniquely-mapping kmers in the output. "
+					"To reduce the size of the output, these are not output by default." )
+				;
+			options[ "-log" ]
+				.set_description( "Specify the path of a log file; all screen output will be copied to the file." )
+				.set_takes_single_value() ;
+			options[ "-omit-sequence" ]
+				.set_description(
+					"Do not output sequence of kmers, just the counts. "
+					"(This reduces the output file size but means kmer sequence will need "
+					"to be looked up again if needed for downstream analysis.)")
+			;
+				
+		}
+
+		{
+			options.declare_group( "Analysis options" ) ;
+		}
+	}
+} ;
+
+struct IndexKmerApplication: public appcontext::ApplicationContext {
+public:
+	typedef std::map< std::string, std::vector< std::string > > GroupDefinition ;
+	typedef std::map< std::string, std::vector< std::string > > ValueListSet ;
+
+public:
+	IndexKmerApplication( int argc, char **argv ):
+		appcontext::ApplicationContext(
+			globals::program_name,
+			globals::program_version,
+			std::auto_ptr< appcontext::OptionProcessor >( new IndexKmerOptions ),
+			argc,
+			argv,
+			"-log"
+		),
+		m_sequences(
+			GenomeSequence::create(
+				options().get_values< std::string >( "-sequence" ),
+				get_ui_context().get_progress_context( "Reading sequence" )
+			)
+		),
+		m_kmer_size( options().get< std::size_t >( "-kmer-size" ) ),
+		m_number_of_distinct_kmers(0)
+	{}
+	
+	std::vector< genfile::GenomePositionRange > parse_ranges( std::vector< std::string > const& spec ) {
+		std::vector< genfile::GenomePositionRange > result ;
+		result.reserve( spec.size() ) ;
+		for( std::size_t i = 0; i < spec.size(); ++i ) {
+			result.push_back( genfile::GenomePositionRange::parse( spec[i] ) ) ;
+		}
+		return result ;
+	}
+
+public:
+	void pre_summarise() {
+		get_ui_context().logger() << "IndexKmerApplication: running with the following parameters:\n"
+			<< "Sequence: " << m_sequences->get_summary( "  " ) << "\n"
+			<< "Ranges: " ;
+		for( std::size_t i = 0; i < m_ranges.size(); ++i ) {
+			get_ui_context().logger() << ( i > 0 ? " " : "" ) << m_ranges[i] ;
+		}
+		get_ui_context().logger() << "\n" << "kmer size: " << m_kmer_size << "bp.\n" ;
+	}
+
+	void run() {
+		try {
+			unsafe_run() ;
+		}
+		catch( genfile::InputError const& e ) {
+			get_ui_context().logger() << "!! (" << e.what() << "): " << e.format_message() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::db::StatementPreparationError const& e ) {
+			get_ui_context().logger() << "!! (" << e.what() << "): " << e.description() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::db::StatementStepError const& e ) {
+			get_ui_context().logger() << "!! (" << e.what() << "): " << e.description() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+	}
+
+	void post_summarise() {}
+
+private:
+	GenomeSequence::UniquePtr m_sequences ;
+	std::size_t m_kmer_size ;
+	std::vector< genfile::GenomePositionRange > m_ranges ;
+	std::size_t m_number_of_distinct_kmers ;
+
+	typedef std::pair< genfile::GenomePosition, char > KmerPosition ;
+	typedef std::vector< KmerPosition > KmerPositions ;
+	typedef std::pair< int, KmerPositions > KmerCountAndPositions ;
+	//typedef std::map< std::string, KmerPositions > KmerMap ;
+	typedef boost::unordered_map< std::string, KmerCountAndPositions > KmerMap ;
+	
+private:
+
+	void unsafe_run() {
+		if( options().check( "-range" )) {
+			m_ranges = parse_ranges( options().get_values< std::string >( "-range" ) ) ;
+		} else {
+			m_ranges = m_sequences->get_ranges() ;
+		}
+
+		KmerMap kmerMap ;
+        for( std::size_t i = 0; i < m_ranges.size(); ++i ) {
+            process_range( m_ranges[i], &kmerMap ) ;
+        }
+		write_output( kmerMap, open_storage() ) ;
+    }
+
+    void process_range(
+        genfile::GenomePositionRange const& genomeRange,
+        KmerMap* result
+    ) {
+        using genfile::string_utils::to_string ;
+        
+        genfile::GenomePosition const& start = genomeRange.start() ;
+        genfile::GenomePosition const& end = genomeRange.end() ;
+		if( end.position() <= start.position() + m_kmer_size ) {
+			get_ui_context().logger() << "!! No kmers of length " << m_kmer_size << " in the range (of length " << ( end.position() - start.position() + 1 ) << ")\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		std::string kmer ;
+		std::string kmer_reverse_complement ;
+		std::string const* kmer_stored = 0;
+
+		GenomeSequence::PhysicalSequenceRange range = m_sequences->get_sequence( start.chromosome(), start.position(), end.position() ) ;
+		genfile::Position rangePosition = range.first.start().position() ;
+		GenomeSequence::ConstSequenceIterator kmer_start = range.second.first ;
+		GenomeSequence::ConstSequenceIterator kmer_end = kmer_start + m_kmer_size ;
+
+		{
+			appcontext::UIContext::ProgressContext progress_context = get_ui_context().get_progress_context( "Processing kmers (" + to_string( genomeRange ) + ")" ) ;
+
+			for( ; kmer_end != range.second.second; ++kmer_start, ++kmer_end, ++rangePosition ) {
+				progress_context.notify_progress( rangePosition, range.first.end().position() - m_kmer_size ) ;
+	#if DEBUG_IndexKmer
+				std::cerr << "IndexKmerApplication:run(): looking at kmer: " << kmer << "...\n" ;
+	#endif
+				kmer.assign( kmer_start, kmer_end ) ;
+				genfile::string_utils::to_upper( &kmer ) ;
+				kmer_reverse_complement.assign( kmer ) ;
+				impl::reverse_complement( &kmer_reverse_complement ) ;
+				char orientation = '+' ;
+				if( kmer.find( 'N' ) == std::string::npos ) {
+					kmer_stored = &kmer ;
+					if( kmer_reverse_complement < kmer ) {
+						orientation = '-' ;
+						kmer_stored = &kmer_reverse_complement ;
+					}
+					KmerPosition kmer_position(
+						genfile::GenomePosition( start.chromosome(), rangePosition ),
+						orientation
+					) ;
+					KmerMap::iterator where = result->find( *kmer_stored ) ;
+					if( where == result->end() ) {
+						result->insert(
+							std::make_pair(
+								*kmer_stored,
+								KmerCountAndPositions(
+									m_number_of_distinct_kmers++,
+									KmerPositions( 1, kmer_position )
+								)
+							)
+						) ;
+					} else {
+						where->second.second.push_back( kmer_position ) ;
+					}
+				}
+			}
+			progress_context.notify_progress( rangePosition, range.first.end().position() - m_kmer_size ) ;
+		}
+			
+#if DEBUG_IndexKmer
+			std::cerr << "IndexKmerApplication:run(): kmerMap.size() = " << result->size() << ".\n" ;
+#endif
+	}
+
+	struct Storage {
+	public: 
+		typedef std::unique_ptr< Storage > UniquePtr ;
+		typedef genfile::db::Connection::RowId KmerId ;
+		struct Location {
+			public:
+				Location(): kmer_id(0) {}	
+				Location(
+					KmerId kmer_id_,
+					uint32_t size_,
+					genfile::GenomePosition position_,
+					char orientation_
+				):
+					kmer_id( kmer_id_ ),
+					size( size_ ),
+					position( position_ ),
+					orientation( orientation_ )
+				{}
+			public:	
+				KmerId kmer_id ;
+				uint32_t size ;
+				genfile::GenomePosition position ;
+				char orientation ;
+		} ;
+
+	public:
+		static UniquePtr create( std::string const& filename, std::string const& prefix ) {
+			return UniquePtr( new Storage( filename, prefix )) ;
+		}
+
+		Storage( std::string const& filename, std::string const& table_prefix ):
+			m_filename( filename ),
+			m_prefix( table_prefix ),
+			m_connection( genfile::db::Connection::create( "file:" + filename + "?nolock=1" )),
+			m_max_buffered( 10000 )
+		{
+			setup_storage() ;
+		}
+		
+	public:
+		
+		void store_kmer(
+			std::string const& kmer,
+			KmerId const& id,
+			int count
+		) {
+			m_insert_kmer_stmt
+				->bind( 1, kmer )
+				.bind( 2, id )
+				.bind( 3, count )
+				.step() ;
+			m_insert_kmer_stmt->reset() ;
+		}
+
+		void store_location(
+			KmerId const& kmer_id,
+			int64_t const size,
+			genfile::GenomePosition const& position,
+			char const orientation
+		) {
+			m_locations.push_back(
+				Location(
+					kmer_id,
+					size,
+					position,
+					orientation
+				)
+			) ;
+			if( m_locations.size() > m_max_buffered ) {
+				store_locations() ;
+				m_locations.resize(0) ;
+			}
+		}
+
+		void finalise() {
+			std::cerr << "++ Storing remaining locations...\n" ;
+			if( m_locations.size() > 0 ) {
+				store_locations() ;
+				m_locations.resize(0) ;
+			}
+			std::cerr << "++ Indexing...\n" ;
+			m_connection->run_statement( "CREATE INDEX LocationIndex On Location( chromosome, position )" ) ;
+		}
+		
+	private:
+		std::string const m_filename ;
+		std::string const m_prefix ;
+		genfile::db::Connection::UniquePtr m_connection ;
+		genfile::db::Connection::StatementPtr m_insert_kmer_stmt ;
+		genfile::db::Connection::StatementPtr m_insert_location_stmt ;
+		std::vector< Location > m_locations ;
+		std::size_t m_max_buffered ;
+
+	private:
+		void setup_storage() {
+			// Performance options
+			// Assume this program will write once, so we don't need
+			// extensive ACID options.
+			m_connection->run_statement( "PRAGMA locking_mode = EXCLUSIVE ;" ) ;
+			m_connection->run_statement( "PRAGMA journal_mode = MEMORY ;" ) ;
+			m_connection->run_statement( "PRAGMA synchronous = OFF ;" ) ;
+			
+			m_connection->run_statement(
+				"CREATE TABLE `" + m_prefix + "Kmer` ( sequence TEXT NOT NULL PRIMARY KEY, id INT NOT NULL, `count` INT NOT NULL ) WITHOUT ROWID ;"
+			) ;
+			
+			m_connection->run_statement(
+				"CREATE TABLE IF NOT EXISTS `" + m_prefix + "Location` ( "
+					"kmer_id INT NOT NULL REFERENCES `" + m_prefix + "Kmer`(id), "
+					"k INT NOT NULL, "
+					"chromosome TEXT NOT NULL, position TEXT NOT NULL, orientation TEXT NOT NULL"
+				") ;"
+			) ;
+			
+			m_insert_kmer_stmt = m_connection->get_statement(
+				"INSERT INTO `" + m_prefix + "Kmer` (sequence, id, count) VALUES( ?, ?, ? ) ;"
+			) ;
+
+			m_insert_location_stmt = m_connection->get_statement(
+				"INSERT INTO `" + m_prefix + "Location` VALUES( ?, ?, ?, ?, ? ) ;"
+			) ;
+		}
+
+		void store_locations() {
+			genfile::db::Connection::ScopedTransactionPtr transaction = m_connection->open_transaction( 7200 ) ;
+			for( std::size_t i = 0; i < m_locations.size(); ++i ) {
+				Location const& o = m_locations[i] ;
+				m_insert_location_stmt
+					->bind( 1, o.kmer_id )
+					.bind( 2, o.size )
+					.bind( 3, std::string( o.position.chromosome() ))
+					.bind( 4, o.position.position() )
+					.bind( 5, std::string( 1, o.orientation ) )
+					.step() ;
+				m_insert_location_stmt->reset() ;
+			}
+		}
+	} ;
+
+	Storage::UniquePtr open_storage() const {
+		return Storage::create(
+			options().get< std::string >( "-o" ),
+			options().get< std::string >( "-table-prefix" )
+		) ;
+	}
+
+	void write_output( KmerMap const& kmerMap, Storage::UniquePtr storage ) {
+		//bool const include_diagonal = options().check( "-include-diagonal" ) ;
+		bool const output_sequence = !options().check( "-omit-sequence" ) ;
+		using genfile::string_utils::to_string ;
+		//genfile::GenomePosition position ( m_range.start().chromosome(), 0 ) ;
+
+		{
+			appcontext::UIContext::ProgressContext progress_context
+				= get_ui_context().get_progress_context( "Storing kmers" ) ;
+			KmerMap::const_iterator kmer_i = kmerMap.begin() ;
+			KmerMap::const_iterator end_i = kmerMap.end() ;
+			std::size_t count = 0 ;
+			for( ; kmer_i != end_i; ++kmer_i, ++count ) {
+				std::string const& kmer = kmer_i->first ;
+				KmerCountAndPositions const& count_and_positions = kmer_i->second ;
+				KmerPositions const& positions = count_and_positions.second ;
+
+				Storage::KmerId const kmer_id = count_and_positions.first ;
+				storage->store_kmer(
+					output_sequence ? kmer : ".", kmer_id, positions.size()
+				) ;
+				progress_context.notify_progress( count+1, kmerMap.size() ) ;
+			}
+		}
+
+		{	
+			appcontext::UIContext::ProgressContext progress_context
+				= get_ui_context().get_progress_context( "Storing overlaps" ) ;
+			KmerMap::const_iterator kmer_i = kmerMap.begin() ;
+			KmerMap::const_iterator end_i = kmerMap.end() ;
+			std::size_t count = 0 ;
+			for( ; kmer_i != end_i; ++kmer_i, ++count ) {
+				std::string const& kmer = kmer_i->first ;
+				KmerCountAndPositions const& count_and_positions = kmer_i->second ;
+				Storage::KmerId const kmer_id = count_and_positions.first ;
+				KmerPositions const& positions = count_and_positions.second ;
+
+				for( std::size_t j = 0; j < positions.size(); ++j ) {
+					genfile::GenomePosition const& position = positions[j].first ;
+					char const orientation = positions[j].second ;
+					storage->store_location(
+						kmer_id,
+						kmer.size(),
+						position,
+						orientation
+					) ;
+				}
+			}
+			progress_context.notify_progress( count+1, kmerMap.size() ) ;
+		}
+		storage->finalise() ;
+	}
+} ;
+
+int main( int argc, char** argv ) {
+	try {
+		IndexKmerApplication app( argc, argv ) ;	
+		app.pre_summarise() ;
+		app.run() ;
+		app.post_summarise() ;
+	}
+	catch( appcontext::HaltProgramWithReturnCode const& e ) {
+		return e.return_code() ;
+	}
+	return 0 ;
+}

DELETED apps/inflation.cpp
Index: apps/inflation.cpp
==================================================================
--- apps/inflation.cpp
+++ apps/inflation.cpp
@@ -1,171 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <string>
-#include <deque>
-#include <iostream>
-#include <algorithm>
-#include <boost/math/distributions/chi_squared.hpp>
-#include "genfile/string_utils.hpp"
-#include "appcontext/OptionProcessor.hpp"
-#include "appcontext/ApplicationContext.hpp"
-#include "appcontext/get_current_time_as_string.hpp"
-#include "appcontext/ProgramFlow.hpp"
-#include "config/qctool_version_autogenerated.hpp"
-#include "config/config.hpp"
-#if HAVE_MGL
-	#include "mgl/mgl.h"
-	#include "mgl/mgl_zb.h"
-#endif
-
-namespace globals {
-	std::string const program_name = "inflation" ;
-	std::string const program_version = qctool_revision ;
-}
-
-struct InflationApplication: public appcontext::ApplicationContext
-{
-public:
-	static void declare_options( appcontext::OptionProcessor& options ) {
-		options.set_help_option( "-help" ) ;
-		options[ "-analysis-name" ]
-			.set_description( "Specify a name to label results from this analysis with.  (This applies to modules which store their results in a qcdb file.)" )
-			.set_takes_single_value()
-			.set_default_value( "inflation analysis, started " + appcontext::get_current_time_as_string() ) ;
-		options [ "-qq-plot" ]
-			.set_description( "Specify that " + globals::program_name + " should make a qq-plot in the file with the given name." )
-			.set_takes_single_value() ;
-		options [ "-log" ]
-			.set_description( "Specify that " + globals::program_name + " should write a log file to the given file." )
-			.set_takes_single_value() ;
-	}
-
-public:
-	InflationApplication( appcontext::OptionProcessor::UniquePtr options, int argc, char** argv ):
-		appcontext::ApplicationContext( globals::program_name, globals::program_version , options, argc, argv, "-log" )
-	{
-	}
-	
-	void process() {
-		unsafe_process(); 
-	}
-private:
-	
-	void unsafe_process() {
-		get_ui_context().logger() << application_name() << ": reading..." ;
-
-		std::string line ;
-		std::deque< float > numbers ;
-		std::size_t missing_count = 0 ;
-		while( std::getline( std::cin, line )) {
-			if( line.empty() || line.find_first_not_of( "0123456789.E+-" ) != std::string::npos ) {
-				++missing_count ;
-			} else {
-				numbers.push_back( genfile::string_utils::to_repr< float >( line ) ) ;
-			}
-
-			if( ( numbers.size() + missing_count ) % 1000000 == 0 ) {
-				get_ui_context().logger() << ( numbers.size() + missing_count ) << ".." ;
-			}
-		}
-
-		get_ui_context().logger() << ( numbers.size() / 1000000 ) << ".\n" ;
-		get_ui_context().logger() << "inflation.cpp: read " << numbers.size() << " P-values from std::cin.\n" ;
-		get_ui_context().logger() << "inflation.cpp: converting to chi-squared statistics...\n" ;
-		using namespace boost::math ;
-		chi_squared_distribution< float > chi_square( 1 ) ;
-		for( std::size_t i = 0; i < numbers.size(); ++i ) {
-			numbers[i] = quantile( complement( chi_square, numbers[i] )) ;
-		}
-
-		get_ui_context().logger() << "inflation.cpp: finding median...\n" ;
-
-		std::cout << "analysis,N,missing,median,lambda,1pc_adjusted_median,1pc_adjusted_lambda\n" ;
-		std::cout
-			<< options().get< std::string >( "-analysis-name" ) << ","
-			<< numbers.size() << ","
-			<< missing_count ;
-		// Compute basic lambda
-		{
-			std::size_t const mid = numbers.size() / 2 ;
-			std::nth_element( numbers.begin(), numbers.begin() + mid, numbers.end() ) ;
-			double const median = numbers[ mid ] ;
-			std::cout << "," << median << "," << (median / quantile( complement( chi_square, 0.5 ))) ;
-		}
-
-		if( options().check( "-qq-plot" )) {
-#if HAVE_MGL
-			get_ui_context().logger() << "inflation.cpp: making qq-plot...\n" ;	
-			plot( numbers, options().get< std::string >( "-qq-plot" ), options().get< std::string >( "-analysis-name" ) ) ;
-#else
-			get_ui_context().logger() << "!! InflationApplication::unsafe_process(): you must build with MathGL support for -qq-plot to be supported.  Skipping plots...\n" ;
-#endif
-		}
-
-		// Compute lambda after removing top 99% of signal
-		{
-			std::size_t const top_one_percent = numbers.size() * 0.99 ;
-			std::deque< float >::iterator top_one_percent_i = numbers.begin() + top_one_percent ;
-			numbers.erase( top_one_percent_i, numbers.end() ) ;
-		}
-
-		{
-			std::size_t const mid = numbers.size() / 2 ;
-			std::nth_element( numbers.begin(), numbers.begin() + mid, numbers.end() ) ;
-			double const median = numbers[ mid ] ;
-			std::cout << "," << median << "," << (median / quantile( complement( chi_square, 0.5 ))) ;
-		}
-		std::cout << "\n" ;
-	}
-	
-#if HAVE_MGL
-	void plot( std::deque< float >& numbers, std::string const& filename, std::string const& title ) {
-		std::sort( numbers.begin(), numbers.end() ) ;
-
-		mglData
-			observed( numbers.size() ),
-			expected( numbers.size() )
-		;
-		
-		using namespace boost::math ;
-		{
-			chi_squared_distribution< float > chi_squared( 1 ) ;
-			for( std::size_t i = 0; i < numbers.size(); ++i ) {
-				observed.a[i] = numbers[i] ;
-				expected.a[i] = quantile( complement( chi_squared, float( numbers.size() - i ) / ( numbers.size() + 1 ) ) ) ;
-			}
-		}
-		mglGraphZB graph( 800, 800 ) ;
-		graph.Light( true ) ;
-		graph.Clf( mglColor( 1.0, 1.0, 1.0 ) ) ;
-		graph.Title( title.c_str(), 0, 4 ) ;
-		graph.SetTickLen( 0.04 ) ;
-		graph.SetRanges(
-			0.0, 30,
-			0.0, 30
-		) ;
-		graph.Axis( "x", true ) ;
-		graph.Axis( "y", true ) ;
-		graph.CAxis( 0.0, 3.0 ) ;
-
-		graph.Plot( expected, observed ) ; //, observed ) ;
-		graph.WritePNG( filename.c_str(), "", false ) ;
-	}
-#endif
-} ;
-
-int main( int argc, char** argv ) {
-	try {
-		appcontext::OptionProcessor::UniquePtr options( new appcontext::OptionProcessor ) ;
-		InflationApplication::declare_options( *options ) ;
-		InflationApplication app( options, argc, argv ) ;
-		app.process() ;
-	} catch ( appcontext::HaltProgramWithReturnCode const& e ) {
-		return e.return_code() ;
-	}
-	return 0 ;
-}
-

Index: apps/inthinnerator.cpp
==================================================================
--- apps/inthinnerator.cpp
+++ apps/inthinnerator.cpp
@@ -43,21 +43,25 @@
 #include "genfile/vcf/StrictMetadataParser.hpp"
 
 #include "statfile/BuiltInTypeStatSourceChain.hpp"
 #include "statfile/DelimitedStatSource.hpp"
 
-#include "db/SQLite3Connection.hpp"
+#include "genfile/db/SQLite3Connection.hpp"
 #include "genfile/FromFilesGeneticMap.hpp"
 //#include "FileUtil.hpp"
 #include "qcdb/Storage.hpp"
 #include "qcdb/FlatTableDBOutputter.hpp"
 #include "qcdb/FlatFileOutputter.hpp"
 
+#include "config/package_revision_autogenerated.hpp"
+
 //#define DEBUG_INTHINNERATOR 1
 
 namespace globals {
 	std::string const program_name = "inthinnerator" ;
+	std::string const program_version = package_version ;
+	std::string const program_revision =  std::string( package_revision ).substr( 0, 7 ) ;
 }
 
 namespace {
 	std::size_t get_random_seed() {
 		std::size_t seed ;
@@ -161,14 +165,19 @@
 		options[ "-map" ]
 			.set_description( "Set the path of the genetic map panel to use." )
 			.set_takes_single_value()
 		;
 		options[ "-g" ]
-			.set_description( "Specify a file containing the SNPs to operate on." )
-			.set_is_required()
+			.set_description( "Specify a GEN, BGEN, or VCF file containing the SNPs to operate on." )
+			.set_takes_values( 1 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-tsv" ]
+			.set_description( "Specify a TSV file containing the SNPs to operate on." )
 			.set_takes_values( 1 )
 			.set_maximum_multiplicity( 100 ) ;
+		options.option_excludes_option( "-g", "-tsv" ) ;
+
 		options[ "-metadata" ]
 			.set_description(
 				"Specify the name of a file containing VCF metadata to be used to parse "
 				"a VCF file.  Keys in this file must either not be present in the VCF file, or must have "
 				"identical values."
@@ -1235,11 +1244,18 @@
 
 class InthinneratorApplication: public appcontext::ApplicationContext
 {
 public:
 	InthinneratorApplication( int argc, char** argv ):
-		ApplicationContext( globals::program_name, std::auto_ptr< appcontext::OptionProcessor >( new InthinneratorOptionProcessor() ), argc, argv, "-log" )
+		ApplicationContext(
+			globals::program_name,
+			"version: " + globals::program_version + ", revision: " + globals::program_revision,
+			std::auto_ptr< appcontext::OptionProcessor >( new InthinneratorOptionProcessor() ),
+			argc,
+			argv,
+			"-log"
+		)
 	{
 		process() ;
 	}
 
 private:
@@ -1279,11 +1295,11 @@
 		}
 		catch( statfile::FileNotOpenedError const& e ) {
 			get_ui_context().logger() << "!! Error (" << e.what() << "): The file \"" << e.filename() << "\" could not be opened.\n" ;
 			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
 		}
-		catch( db::StatementStepError const& e ) {
+		catch( genfile::db::StatementStepError const& e ) {
 			get_ui_context().logger() << "!! Error (" << e.what() << "): error with SQL: " << e.sql() << "\n"
 				<< e.description() << ".\n" ;
 			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
 		}
 	}
@@ -1299,11 +1315,10 @@
 			assert( map.get() ) ;
 			get_ui_context().logger() << "Loaded: " << map->get_summary() << "\n";
 		}
 
 		get_variants(
-			options().get_value< std::string >( "-g" ),
 			map,
 			&m_variants,
 			&m_extra_column_names
 		) ;
 		boost::optional< std::vector< double > > recombination_offsets ;
@@ -1391,25 +1406,27 @@
 		
 		return filter ;
 	}
 
 	void get_variants(
-		std::string const& filename,
 		genfile::GeneticMap::UniquePtr const& map,
 		std::vector< TaggedSnp >* result,
 		std::vector< std::string >* other_column_names
 	) const {
 		std::vector< TaggedSnp > filtered_snps ;
 		std::vector< std::string > names ;
-		try {
-			 get_variants_from_gen_file( filename, &filtered_snps ) ;
-		}
-		catch( std::exception const& e ) {
-			get_ui_context().logger() << "File \"" << filename << "\" is not a GEN-style file.  Trying text format with columns SNPID rsid chromosome position...\n" ;
-			// Not a GEN format file.  Try a different format.
+		if( options().check( "-g" )) {
+			get_variants_from_gen_file( options().get< std::string >( "-g" ), &filtered_snps ) ;
+		} else if( options().check( "-tsv" )) {
 			boost::optional< std::string > tag_column = ( options().check( "-tag-column" ) ? options().get< std::string >( "-tag-column" ) : boost::optional< std::string >() ) ;
-			get_variants_from_text_file( filename, tag_column, &filtered_snps, &names ) ;
+			get_variants_from_text_file( options().get< std::string >( "-tsv" ), tag_column, &filtered_snps, &names ) ;
+		} else {
+			throw genfile::BadArgumentError(
+				"get_variants()",
+				"options()",
+				"Expected either -g or -tsv option to be supplied."
+			) ;
 		}
 		
 		genfile::CommonSNPFilter::UniquePtr filter = get_filter() ;
 		if( map.get() ) {
 			filter->exclude_chromosomes_not_in_set( map->get_chromosomes() ) ;
@@ -1485,11 +1502,11 @@
 				if( !tag_column_index || i != *tag_column_index ) {
 					other_column_names->push_back( chain->name_of_column(i) ) ;
 				}
 			}
 		}
-		
+	
 		std::string SNPID ;
 		std::string rsid ;
 		std::string chromosome ;
 		genfile::Position position ;
 		std::string alleleA = "?" ;
@@ -1816,11 +1833,15 @@
 		SNPPicker const& snp_picker
 	) const {
 		get_ui_context().logger() << "Genetic map file(s): "
 			<< ( options().check( "-map" ) ? options().get_value< std::string >( "-map" ) : std::string( "(none specified)" ) )
 			<< ".\n" ;
-		get_ui_context().logger() << "Genotype file(s): " << options().get_value< std::string >( "-g" ) << ".\n" ;
+		if( options().check( "-g" )) {
+			get_ui_context().logger() << "Genotype file(s): " << options().get_value< std::string >( "-g" ) << ".\n" ;
+		} else {
+			get_ui_context().logger() << "Input tsv file(s): " << options().get_value< std::string >( "-tsv" ) << ".\n" ;
+		}
 
 		if( map.get() ) {
 			get_ui_context().logger() << "Genetic map covers these chromosome(s): " ;
 			std::set< genfile::Chromosome > chromosomes = map->get_chromosomes() ;
 			for( std::set< genfile::Chromosome >::const_iterator i = chromosomes.begin(); i != chromosomes.end(); ++i ) {
@@ -1861,11 +1882,10 @@
 		std::vector< TaggedSnp > const& snps = m_variants ;
 		std::size_t const N = options().get_value< std::size_t >( "-N" ) ;
 		assert( N > 0 ) ;
 		std::size_t const start_N = options().get_value< std::size_t >( "-start-N" ) ;
 		std::size_t const max_num_picks = options().check( "-max-picks" ) ? options().get_value< std::size_t >( "-max-picks" ) : snps.size() ;
-		std::size_t const number_of_digits = std::max( std::size_t( std::log10( N + start_N ) ) + 1, std::size_t( 3u )) ;
 
 		std::vector< boost::optional< std::string > > pick_tags ;
 		if( options().check( "-match-tag" )) {
 			std::vector< TaggedSnp > snps_to_match ;
 			get_variants_from_text_file(
@@ -2248,16 +2268,29 @@
 					) ;
 				}
 			}
 			
 			if( m_extra_column_names.size() > 0 ) {
+				bool const have_rank_column = options().check( "-rank-column" ) ;
+				std::string const rank_column = have_rank_column ? options().get< std::string >( "-rank-column" ) : "" ;
 				for( std::size_t i = 0; i < m_extra_column_names.size(); ++i ) {
-					storage.store_per_variant_data(
-						snps[snp_i].snp(),
-						m_extra_column_names[i],
-						snps[snp_i].datum(i)
-					) ;
+					std::string const& column = m_extra_column_names[i] ;
+					if( have_rank_column && column == rank_column ) {
+						// output as float
+						storage.store_per_variant_data(
+							snps[snp_i].snp(),
+							column,
+							genfile::string_utils::to_repr< double >( snps[snp_i].datum(i) )
+						) ;
+					} else {
+						// output as string
+						storage.store_per_variant_data(
+							snps[snp_i].snp(),
+							column,
+							snps[snp_i].datum(i)
+						) ;
+					}
 				}
 			}
 
 			if( genes.get() ) {
 				std::pair<

ADDED   apps/ldbird.cpp
Index: apps/ldbird.cpp
==================================================================
--- apps/ldbird.cpp
+++ apps/ldbird.cpp
@@ -0,0 +1,1210 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <iostream>
+#include <limits>
+#include <typeinfo>
+#include <fstream>
+#include <unordered_map>
+
+#include <boost/filesystem.hpp>
+#include <boost/format.hpp>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/timer/timer.hpp>
+#include <boost/ptr_container/ptr_vector.hpp>
+#include <boost/bind.hpp>
+#include <boost/foreach.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+
+#include "config/package_revision_autogenerated.hpp"
+
+#include "appcontext/CmdLineOptionProcessor.hpp"
+#include "appcontext/ApplicationContext.hpp"
+
+#include "genfile/SNPDataSource.hpp"
+#include "genfile/SNPDataSourceChain.hpp"
+#include "genfile/ThreshholdingSNPDataSource.hpp"
+#include "genfile/ToGP.hpp"
+#include "genfile/CommonSNPFilter.hpp"
+#include "genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp"
+#include "genfile/CrossCohortCovariateValueMapping.hpp"
+#include "genfile/SampleFilter.hpp"
+#include "genfile/SampleFilteringSNPDataSource.hpp"
+#include "genfile/SampleFilteringCohortIndividualSource.hpp"
+#include "genfile/CompoundSampleFilter.hpp"
+#include "genfile/SampleFilterNegation.hpp"
+#include "genfile/VariableInSetSampleFilter.hpp"
+#include "genfile/GPThresholdingGTSetter.hpp"
+#include "genfile/db/Error.hpp"
+#include "genfile/CartesianProductVisitor.hpp"
+
+#include "metro/constants.hpp"
+#include "metro/regression/Design.hpp"
+#include "metro/SampleRange.hpp"
+#include "metro/intersect_ranges.hpp"
+#include "metro/count_range.hpp"
+#include "metro/regression/BinomialLogistic.hpp"
+#include "metro/regression/ThreadedLogLikelihood.hpp"
+#include "metro/regression/IndependentNormalWeightedLogLikelihood.hpp"
+#include "metro/regression/IndependentLogFWeightedLogLikelihood.hpp"
+#include "metro/regression/LogPosteriorDensity.hpp"
+#include "metro/ValueStabilisesStoppingCondition.hpp"
+#include "metro/Snptest25StoppingCondition.hpp"
+#include "metro/maximisation.hpp"
+#include "metro/fit_model.hpp"
+#include "metro/CholeskyStepper.hpp"
+#include "metro/FishersExactTest.hpp"
+
+#include "qcdb/MultiVariantStorage.hpp"
+#include "qcdb/FlatTableDBOutputter.hpp"
+
+#include <Eigen/Core>
+#include <Eigen/QR>
+#include "Eigen/Eigenvalues"
+
+// #define DEBUG 1
+
+namespace globals {
+	std::string const program_name = "ldbird" ;
+	std::string const program_version = package_version ;
+	std::string const program_revision =  std::string( package_revision ).substr( 0, 7 ) ;
+}
+
+namespace {
+	std::vector< std::string > collect_unique_ids( std::vector< std::string > const& ids_or_filenames ) {
+		std::vector< std::string > result ;
+		for( auto elt: ids_or_filenames ) {
+			if( boost::filesystem::exists( elt )) {
+				std::ifstream f( elt ) ;
+				std::copy(
+					std::istream_iterator< std::string >( f ),
+					std::istream_iterator< std::string >(),
+					std::back_inserter< std::vector< std::string > >( result )
+				) ;
+			} else {
+				result.push_back( elt ) ;
+			}
+		}
+		// now sort and uniqueify them...
+		std::sort( result.begin(), result.end() ) ;
+		std::vector< std::string >::const_iterator newBack = std::unique( result.begin(), result.end() ) ;
+		result.resize( newBack - result.begin() ) ;
+		return result ;
+	}
+
+}
+
+struct CorrelatorOptions: public appcontext::CmdLineOptionProcessor
+{
+public:
+	std::string get_program_name() const { return globals::program_name ; }
+
+	void declare_options( appcontext::OptionProcessor& options ) {
+		// Meta-options
+		options.set_help_option( "-help" ) ;
+		options.set_spec_option( "-spec" ) ;
+
+		// File options
+		options.declare_group( "Input file options" ) ;
+		options[ "-g1" ]
+			.set_description( 	"Path to first genotype file."
+								"The given filename may contain the wildcard character '#', which expands to match a"
+								"one- or two-character chromosome identifier." )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 1 )
+			.set_maximum_multiplicity( 1 ) ;
+		options[ "-g1-incl-rsids" ]
+			.set_description( "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.")
+			.set_takes_values_until_next_option()
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-g1-incl-range" ]
+			.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. "
+				"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+				"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+				"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+			.set_takes_values_until_next_option() ;
+
+		options.option_implies_option( "-g1-incl-range", "-g1" ) ;
+		options.option_implies_option( "-g1-incl-rsids", "-g1" ) ;
+
+		options[ "-g2" ]
+			.set_description( 	"Path to second genotype file.  If not given the first genotype file will be used."
+								"The given filename may contain the wildcard character '#', which expands to match a"
+								"one- or two-character chromosome identifier." )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 1 ) ;
+
+		options[ "-g2-incl-rsids" ]
+			.set_description( "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.")
+			.set_takes_values_until_next_option()
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-g2-incl-range" ]
+			.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. "
+				"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+				"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+				"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+			.set_takes_values_until_next_option() ;
+
+		options.option_implies_option( "-g2-incl-range", "-g2" ) ;
+		options.option_implies_option( "-g2-incl-rsids", "-g2" ) ;
+
+		options[ "-s" ]
+			.set_description( "Path of sample file" )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 1 )
+			.set_maximum_multiplicity( 1 ) ;
+
+		options.declare_group( "Output file options" ) ;
+		options[ "-o" ]
+			.set_description( "Output file" )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 1 )
+			.set_maximum_multiplicity( 1 ) ;
+		options[ "-details" ]
+			.set_description( "Output counts and a Fisher's exact test P-value. "
+				"Currently only supported if genotypes are haploid." ) ;
+		
+		options.declare_group( "Model options" ) ;
+		options[ "-incl-samples"]
+			.set_description( "Filter out samples whose sample ID does not lie in the given file(s).")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-excl-samples"]
+			.set_description( "Filter out samples whose sample ID lies in the given file.")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-incl-samples-where"]
+			.set_description( "Include samples by specifying conditions on the values of columns in the sample file.")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-excl-samples-where"]
+			.set_description( "Exclude samples by specifying conditions on the values of columns in the sample file.")
+			.set_takes_single_value()
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-min-r2" ]
+			.set_description( "Do not output results where r^2 is lower than this threshold. "
+					" (These values are still computed and contribute to the histogram.)" )
+			.set_takes_single_value()
+			.set_default_value( 0.05 ) ;
+		options[ "-min-maf" ]
+			.set_description( "Do not compute correlation results where the maf of either variant is lower than this threshold." )
+			.set_takes_single_value()
+			.set_default_value( 0 ) ;
+		options[ "-min-N" ]
+			.set_description( "Do not compute results where the total number of pairwise non-missing genotypes is below this threshold." )
+			.set_takes_single_value()
+			.set_default_value( 0 ) ;
+		options[ "-min-N-propn" ]
+			.set_description( "Ignore (do not compute or output) results where the propn of pairwise non-missing genotypes is below this threshold." )
+			.set_takes_single_value()
+			.set_default_value( 0.0 ) ;
+		options[ "-min-distance" ]
+			.set_description( "Ignore (do not compute or output) results where the variants are on the same chromosome and closer than this physical distance." )
+			.set_takes_single_value()
+			.set_default_value( 0 ) ;
+		options[ "-assume-haploid" ]
+			.set_description( "Convert all data to haploid calls.  This converts homozygous calls"
+				" to haploid calls, and treats any heterozygous calls as missing.")
+		;
+		options[ "-prior-weight" ]
+			.set_description( "Specify a prior weight for samples.  "
+				" This augments data with one of each of the four possible haploid genotype combinations "
+				" for each pairwise comparison, with the total weight given."
+				" For example, a value of 1 indicates each haplotype is given 1/4 weight."
+			)
+			.set_takes_single_value()
+			.set_default_value( "0" )
+		;
+		options.declare_group( "Miscellaneous options" ) ;
+		options[ "-analysis-name" ]
+			.set_description( "Specify a name to label results from this analysis with." )
+			.set_takes_single_value()
+			.set_default_value( "ldbird analysis" ) ;
+		options[ "-analysis-chunk" ]
+			.set_description( "Specify a name denoting the current genomic region or chunk on which this is run.  This is intended for use in parallel environments." )
+			.set_takes_single_value()
+			.set_default_value( genfile::MissingValue() ) ;
+		options[ "-analysis-id" ]
+			.set_description( "Specify an integer ID for the current analysis." )
+			.set_takes_single_value() ;
+		options[ "-table-prefix" ]
+			.set_description( "Specify a prefix to add to tables.  They will be called <prefix>Frequency and <prefix>R." )
+			.set_takes_single_value()
+			.set_default_value( "" ) ;
+		options[ "-threshold" ]
+			.set_description( "The threshold to apply to genotype probabilities, if necessary, to make calls." )
+			.set_takes_single_value()
+			.set_default_value( 0.9 ) ;
+		options.declare_group( "Miscellaneous options" ) ;
+		options[ "-debug" ]
+			.set_description( "Output debugging information." ) ;
+	}
+} ;
+
+
+namespace {
+	struct ProbSetter: public genfile::VariantDataReader::PerSampleSetter {
+		typedef std::vector< metro::SampleRange > SampleRanges ;
+
+		ProbSetter(
+			Eigen::MatrixXd* genotypes,
+			Eigen::VectorXi* ploidy,
+			SampleRanges* nonmissing_samples
+		):
+			m_genotypes( genotypes ),
+			m_ploidy( ploidy ),
+			m_nonmissing_samples( nonmissing_samples ),
+			m_sample_i(0)
+		{
+			assert( genotypes != 0 && nonmissing_samples != 0 && ploidy != 0 ) ;
+		}
+
+		void initialise( std::size_t nSamples, std::size_t nAlleles ) {
+			if( nAlleles != 2 ) {
+				throw genfile::BadArgumentError(
+					"ProbSetter::initialise()",
+					"nAlleles=" + genfile::string_utils::to_string( nAlleles ),
+					"I only support biallelic variants"
+				) ;
+			}
+			m_genotypes->resize( nSamples, 3 ) ;
+			m_genotypes->setZero() ;
+			m_ploidy->resize( nSamples ) ;
+			m_ploidy->setZero() ;
+			
+			m_nonmissing_samples->clear() ;
+			m_last_nonmissing_sample_i = 0 ;
+		}
+
+		bool set_sample( std::size_t n ) {
+			m_sample_i = n ;
+			return true ;
+		}
+
+		void set_number_of_entries(
+			uint32_t ploidy, std::size_t n,
+			genfile::OrderType const order_type,
+			genfile::ValueType const value_type
+		) {
+			if( value_type != genfile::eProbability ) {
+				throw genfile::BadArgumentError(
+					"Callsetter::set_number_of_entries()",
+					"value_type=" + genfile::string_utils::to_string( value_type ),
+					"Expected genotype call probabilities (e.g. GP field)."
+				) ;
+			}
+			if( order_type != genfile::ePerUnorderedGenotype ) {
+				throw genfile::BadArgumentError(
+					"Callsetter::set_number_of_entries()",
+					"order_type=" + genfile::string_utils::to_string( order_type ),
+					"Expected genotype call probabilities (e.g. GP field)."
+				) ;
+			}
+			if( ploidy != 2 ) {
+				throw genfile::BadArgumentError(
+					"Callsetter::set_number_of_entries()",
+					"order_type=" + genfile::string_utils::to_string( order_type ),
+					"Expected a diploid sample."
+				) ;
+			}
+			(*m_ploidy)(m_sample_i) = ploidy ;
+		}
+
+		void set_value( std::size_t entry_i, genfile::MissingValue const value ) {
+			// This sample has missing data, end our current sample range here.
+			if( m_sample_i > m_last_nonmissing_sample_i ) {
+				m_nonmissing_samples->push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i )
+				) ;
+			}
+			// Skip this sample for next range.
+			m_last_nonmissing_sample_i = m_sample_i + 1 ;
+		}
+
+		void set_value( std::size_t entry_i, Integer const value ) {
+			assert(0) ; // expected a probabilty
+		}
+
+		void set_value( std::size_t entry_i, double const value ) {
+			if( m_sample_i >= m_last_nonmissing_sample_i ) {
+				(*m_genotypes)(m_sample_i, entry_i) = value ;
+			}
+		}
+
+		void finalise() {
+			// Add the final sample range if needed.
+			if( (m_sample_i+1) > m_last_nonmissing_sample_i ) {
+				m_nonmissing_samples->push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i+1 )
+				) ;
+			}
+			
+			// For probability data, we need to handle the case of missingness encoded as zero probabilities.
+			// Do that now by inspecting the genotypes.
+			{
+				std::vector< metro::SampleRange > ranges ;
+				std::size_t last_nonmissing_sample_i = 0 ;
+				std::size_t i = 0 ;
+				for( ; i < m_genotypes->rows(); ++i ) {
+					if( m_genotypes->row(i).sum() == 0.0 ) {
+						if( i > last_nonmissing_sample_i ) {
+							ranges.push_back( metro::SampleRange( last_nonmissing_sample_i, i )) ;
+						}
+						last_nonmissing_sample_i = i+1 ;
+					}
+				}
+				if( i > last_nonmissing_sample_i ) {
+					ranges.push_back( metro::SampleRange( last_nonmissing_sample_i, i )) ;
+				}
+				
+				*m_nonmissing_samples = metro::impl::intersect_ranges( *m_nonmissing_samples, ranges ) ;
+			}
+		}
+		
+	private:
+		Eigen::MatrixXd* m_genotypes ;
+		Eigen::VectorXi* m_ploidy ;
+		SampleRanges* m_nonmissing_samples ;
+		std::size_t m_last_nonmissing_sample_i ;
+		std::size_t m_sample_i ;
+	} ;
+}
+
+struct LDbirdApplication: public appcontext::ApplicationContext
+{
+public:
+	
+	typedef Eigen::MatrixXd Matrix ;
+	typedef Eigen::VectorXd Vector ;
+	typedef Eigen::VectorXi IntegerVector ;
+	typedef Eigen::RowVectorXd RowVector ;
+	
+public:
+	LDbirdApplication( int argc, char** argv ):
+		appcontext::ApplicationContext(
+			globals::program_name,
+			globals::program_version + ", revision " + globals::program_revision,
+			std::auto_ptr< appcontext::OptionProcessor >( new CorrelatorOptions ),
+			argc,
+			argv,
+			"-log"
+		)
+	{
+		process() ;
+	}
+	
+private:
+	void process() {
+		try {
+			unsafe_process() ;
+		}
+		catch( genfile::InputError const& e ) {
+			get_ui_context().logger() << "!! Error (" << e.what() << "): " << e.format_message() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::FileNotFoundError const& e ) {
+			get_ui_context().logger() << "\nError: No file matching \"" << e.filespec() << "\" could be found.\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::db::Error const& e ) {
+			get_ui_context().logger() << "!! Error (" << e.what() << ") with the following statement: \""
+				<< e.sql()
+				<< "\".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+	}
+	
+	void unsafe_process() {
+		using genfile::string_utils::to_string ;
+		
+		genfile::SampleFilterConjunction::UniquePtr sample_filter = get_sample_filter() ;
+
+		genfile::CohortIndividualSource::UniquePtr
+			samples = genfile::CohortIndividualSource::create( options().get< std::string >( "-s" ) ) ;
+
+		std::set< std::size_t > const excluded_samples = compute_excluded_samples( *sample_filter, *samples ) ;
+		if( excluded_samples.size() > 0 ) {
+			samples.reset(
+				genfile::SampleFilteringCohortIndividualSource::create( samples, excluded_samples ).release()
+			) ;
+		}
+
+		genfile::SNPDataSource::UniquePtr g1 = open_genotype_data_sources(
+			options().get< std::string >( "-g1" ),
+			get_variant_filter(
+				"-g1-incl-range",
+				"-g1-incl-rsids"
+			),
+			excluded_samples
+		) ;
+
+		genfile::SNPDataSource::UniquePtr g2 ;
+		if( options().check( "-g2" )) {
+			// Two files given, we'll do a full carThis mechanism chooses a full cartesian product or a lower triangle implementation.
+			// TODO: make this more obvious / cleaner.
+			g2 = open_genotype_data_sources(
+				options().get< std::string >( "-g2" ),
+				get_variant_filter(
+					"-g2-incl-range",
+					"-g2-incl-rsids"
+				),
+				excluded_samples
+			) ;
+		} else {
+			g2 = open_genotype_data_sources(
+				options().get< std::string >( "-g1" ),
+				get_variant_filter(
+					"-g1-incl-range",
+					"-g1-incl-rsids"
+				),
+				excluded_samples
+			) ;
+		}
+		
+		std::size_t const N = samples->size() ;
+		if( g1->number_of_samples() != N ) {
+			throw genfile::BadArgumentError(
+				"LDbirdApplication::unsafe_process()",
+				"-g1 \"" + options().get< std::string >( "-g1" ) + "\"",
+				"Wrong number of samples (" + to_string(g1->number_of_samples()) + ", expected " + to_string(N) + ")"
+			) ;
+		}
+		if( g2->number_of_samples() != N ) {
+			throw genfile::BadArgumentError(
+				"LDbirdApplication::unsafe_process()",
+				"-g2 \"" + options().get< std::string >( "-g2" ) + "\"",
+				"Wrong number of samples (" + to_string(g2->number_of_samples()) + ", expected " + to_string(N) + ")"
+			) ;
+		}
+		
+		write_preamble( *g1, *g2, *samples ) ;
+		
+		std::vector< int64_t > histogram( 2049, 0 ) ;
+		
+		boost::optional< genfile::db::Connection::RowId > analysis_id ;
+		if( options().check( "-analysis-id" ) ) {
+			analysis_id = options().get< genfile::db::Connection::RowId >( "-analysis-id" ) ;
+		}
+
+		std::string const fileSpec = options().get< std::string > ( "-o" ) ;
+		std::string const tablePrefix = options().get< std::string > ( "-table-prefix" ) ;
+
+		{
+			qcdb::Storage::UniquePtr frequencyStorage = qcdb::Storage::create(
+				fileSpec + ":" + tablePrefix + "Frequency",
+				options().get< std::string > ( "-analysis-name" ),
+				options().get< std::string > ( "-analysis-chunk" ),
+				get_application_metadata(),
+				"position,alleles",
+				analysis_id
+			) ;
+			analysis_id = frequencyStorage->analysis_id() ;
+
+			frequencyStorage->add_variable( "number_of_haplotypes" ) ;
+			frequencyStorage->add_variable( "frequency" ) ;
+			//frequencyStorage->set_variant_names( std::vector< std::string >({ "g1", "g2" })) ;
+
+			qcdb::MultiVariantStorage::UniquePtr correlationStorage = qcdb::MultiVariantStorage::create(
+				fileSpec + ":" + tablePrefix + "R+without rowid",
+				2,
+				options().get< std::string > ( "-analysis-name" ),
+				options().get< std::string > ( "-analysis-chunk" ),
+				get_application_metadata(),
+				"position,alleles",
+				analysis_id
+			) ;
+
+			correlationStorage->set_variant_names( std::vector< std::string >({ "g1", "g2" })) ;
+			correlationStorage->add_variable( "N" ) ;
+			correlationStorage->add_variable( "encoded_r" ) ;
+
+			if( options().check( "-details" )) {
+				for( int i = 0; i < 2; ++i ) {
+					for( int j = 0; j < 2; ++j ) {
+						correlationStorage->add_variable( "n_" + to_string(i) + to_string(j) ) ;
+					}
+				}
+				
+				correlationStorage->add_variable( "fet_pvalue" ) ;
+			}
+			// This mechanism chooses a full cartesian product or a lower triangle implementation
+			// TODO: make this more obvious / cleaner.
+			genfile::CartesianProductVisitor visitor( !options().check( "-g2" ) ) ;
+			visitor.add_source( "g1", g1.get() ) ;
+			visitor.add_source( "g2", g2.get() ) ;
+
+			if( options().check( "-min-distance" )) {
+				visitor.set_min_distance( options().get< int64_t >( "-min-distance" )) ;
+			}
+
+			run( visitor, *samples, *frequencyStorage, *correlationStorage, &histogram ) ;
+
+			frequencyStorage->finalise() ;
+			correlationStorage->finalise() ;
+		}
+		
+		{
+			qcdb::MultiVariantStorage::UniquePtr histogramStorage = qcdb::MultiVariantStorage::create(
+				fileSpec + ":" + tablePrefix + "Histogram",
+				0,
+				options().get< std::string > ( "-analysis-name" ),
+				options().get< std::string > ( "-analysis-chunk" ),
+				get_application_metadata(),
+				"position,alleles",
+				analysis_id
+			) ;
+			histogramStorage->add_variable( "encoded_r" ) ;
+			histogramStorage->add_variable( "count" ) ;
+			qcdb::MultiVariantStorage::Key const key ;
+			for( std::size_t i = 0; i < histogram.size(); ++i ) {
+				histogramStorage->create_new_key( key ) ;
+				histogramStorage->store_data_for_key( key, "encoded_r", int64_t(i) ) ;
+				histogramStorage->store_data_for_key( key, "count", histogram[i] ) ;
+			}
+			histogramStorage->finalise() ;
+		}
+	}
+	
+	genfile::CommonSNPFilter::UniquePtr get_variant_filter(
+		std::string const& incl_range_option,
+		std::string const& incl_ids_option
+	) const {
+		genfile::CommonSNPFilter::UniquePtr result ;
+		if( options().check( incl_range_option ) || options().check( incl_ids_option ) ) {
+			result.reset( new genfile::CommonSNPFilter() ) ;
+			if( options().check( incl_range_option )) {
+				std::vector< std::string > specs = collect_unique_ids( options().get_values< std::string >( incl_range_option ) ) ;
+				for ( std::size_t i = 0; i < specs.size(); ++i ) {
+					result->include_snps_in_range(
+						genfile::GenomePositionRange::parse( specs[i] )
+					) ;
+				}
+			}
+			if( options().check( incl_ids_option )) {
+				std::vector< std::string > files = collect_unique_ids( options().get_values< std::string > ( incl_ids_option ) ) ;
+				result->include_snps_in_set(
+					std::set< std::string >( files.begin(), files.end() ),
+					genfile::CommonSNPFilter::RSIDs
+				) ;
+			}
+		}
+		return result ;
+	}
+	
+	genfile::SampleFilterConjunction::UniquePtr get_sample_filter() const {
+		genfile::SampleFilterConjunction::UniquePtr filter( new genfile::SampleFilterConjunction() ) ;
+		genfile::SampleFilterDisjunction::UniquePtr sample_inclusion_filter( new genfile::SampleFilterDisjunction() ) ;
+
+		if( options().check_if_option_was_supplied( "-incl-samples" ) ) {
+			genfile::SampleFilter::UniquePtr id1_filter = get_sample_id_filter(
+				options().get_values< std::string >( "-incl-samples" )
+			) ;
+			sample_inclusion_filter->add_clause( genfile::SampleFilter::UniquePtr( id1_filter.release() ) ) ;
+		}
+
+		if( options().check_if_option_was_supplied( "-excl-samples" ) ) {
+			genfile::SampleFilter::UniquePtr id1_filter = get_sample_id_filter(
+				options().get_values< std::string >( "-excl-samples" )
+			) ;
+			filter->add_clause(
+				genfile::SampleFilter::UniquePtr(
+					new genfile::SampleFilterNegation(
+						id1_filter
+					)
+				)
+			) ;
+		}
+
+		if( options().check_if_option_was_supplied( "-incl-samples-where" ) ) {
+			std::vector< std::string > conditions = options().get_values< std::string >( "-incl-samples-where" ) ;
+			// we OR together different WHERE clauses.
+			for( std::size_t i = 0; i < conditions.size(); ++i ) {
+				sample_inclusion_filter->add_clause( genfile::SampleFilter::create( conditions[i] )) ;
+			}
+		}
+
+		if( options().check_if_option_was_supplied( "-excl-samples-where" ) ) {
+			std::vector< std::string > conditions = options().get_values< std::string >( "-excl-samples-where" ) ;
+			// we AND together different WHERE clauses.
+			genfile::SampleFilterDisjunction::UniquePtr where( new genfile::SampleFilterDisjunction() ) ;
+			for( std::size_t i = 0; i < conditions.size(); ++i ) {
+				where->add_clause( genfile::SampleFilter::create( conditions[i] )) ;
+			}
+			filter->add_clause(
+				genfile::SampleFilter::UniquePtr(
+					new genfile::SampleFilterNegation(
+						genfile::SampleFilter::UniquePtr( where.release() )
+					)
+				)
+			) ;
+		}
+		if( sample_inclusion_filter->number_of_clauses() > 0 ) {
+			filter->add_clause( genfile::SampleFilter::UniquePtr( sample_inclusion_filter.release() ) ) ;
+		}
+
+		return filter ;
+	}
+
+	std::set< std::size_t > compute_excluded_samples( genfile::SampleFilter const& filter, genfile::CohortIndividualSource const& samples ) const {
+		std::vector< std::size_t > included_samples ;
+		void(std::vector<std::size_t>::*push_back)(std::size_t const&) = &std::vector<std::size_t>::push_back ;
+		filter.test(
+			samples,
+			boost::bind(
+				push_back,
+				&included_samples,
+				_1
+			)
+		) ;
+		std::set< std::size_t > excluded_samples(
+			boost::counting_iterator< std::size_t >(0),
+			boost::counting_iterator< std::size_t >( samples.get_number_of_individuals() )
+		) ;
+		for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+			excluded_samples.erase( included_samples[i] ) ;
+		}
+		return excluded_samples ;
+	}
+
+	genfile::SampleFilter::UniquePtr get_sample_id_filter( std::vector< std::string > const& filenames ) const {
+		genfile::VariableInSetSampleFilter::UniquePtr result( new genfile::VariableInSetSampleFilter( "ID_1" )) ;
+		for( std::size_t i = 0; i < filenames.size(); ++i ) {
+			std::string elt ;
+			std::ifstream is( filenames[i].c_str() ) ;
+			while( is >> elt ) {
+				result->add_level( elt ) ;
+			}
+		}
+		return genfile::SampleFilter::UniquePtr( result.release() ) ;
+	}
+	
+	genfile::SNPDataSource::UniquePtr open_genotype_data_sources(
+		std::string const& filename,
+		genfile::CommonSNPFilter::UniquePtr filter,
+		std::set< std::size_t > const& excluded_samples,
+		bool threshold = false
+	) {
+		std::vector< genfile::wildcard::FilenameMatch > filenames
+			= genfile::wildcard::find_files_by_chromosome(
+				filename,
+				genfile::wildcard::eALL_CHROMOSOMES
+			) ;
+
+		genfile::SNPDataSource::UniquePtr source( 
+			genfile::SNPDataSourceChain::create(
+				filenames
+			).release()
+		) ;
+		if( filter.get() ) {
+			source.reset(
+				genfile::VariantIdentifyingDataFilteringSNPDataSource::create(
+					source,
+					genfile::VariantIdentifyingDataTest::UniquePtr( filter.release() )
+				).release()
+			) ;
+		}
+		if( threshold ) {
+			source.reset(
+				new genfile::ThreshholdingSNPDataSource( source, 0.9 )
+			) ;
+		}
+		if( excluded_samples.size() > 0 ) {
+			source.reset(
+				new genfile::SampleFilteringSNPDataSource( source, excluded_samples )
+			) ;
+		}
+		return source ;
+	}
+
+	void write_preamble(
+		genfile::SNPDataSource const& host,
+		genfile::SNPDataSource const& para,
+		genfile::CohortIndividualSource const& samples
+	) {
+		get_ui_context().logger() << "Loaded data for " << samples.size() << " samples.\n" ;
+		get_ui_context().logger() << "  First dataset:\n" << host.get_summary() << "\n" ;
+		get_ui_context().logger() << " Second dataset:\n" << para.get_summary() << "\n" ;
+	}
+
+
+	void run(
+		genfile::MultiSourceVisitor& visitor,
+		genfile::CohortIndividualSource const& samples,
+		qcdb::Storage& frequencyOutput,
+		qcdb::MultiVariantStorage& correlationOutput,
+		std::vector< int64_t >* histogram
+	) {
+		appcontext::UIContext::ProgressContext progress_context = get_ui_context().get_progress_context( "Testing" ) ;
+		histogram->resize( 2049 ) ;
+		std::fill( histogram->begin(), histogram->end(), 0 ) ;
+		for(
+			std::size_t count = 0;
+			visitor.step(
+				[this,&frequencyOutput,&correlationOutput,&histogram](
+					std::vector< int > const& changed,
+					std::vector< genfile::VariantIdentifyingData > const& variants,
+					std::vector< genfile::VariantDataReader::SharedPtr > const& readers
+				) {
+					this->process_one(
+						changed,
+						variants,
+						readers,
+						frequencyOutput,
+						correlationOutput,
+						histogram
+					) ;
+				}
+			) ;
+			++count
+		) {
+			progress_context( count, visitor.count() ) ;
+		} ;
+		progress_context.finish() ;
+	}
+	
+	void process_one(
+		std::vector< int > const& changed,
+		std::vector< genfile::VariantIdentifyingData > const& variants,
+		std::vector< genfile::VariantDataReader::SharedPtr > const& readers,
+		qcdb::Storage& frequencyOutput,
+		qcdb::MultiVariantStorage& correlationOutput,
+		std::vector< int64_t >* histogram
+	) {
+		using genfile::string_utils::to_string ;
+
+		if( m_dosages.size() != changed.size() ) {
+			m_dosages.resize( changed.size() ) ;
+			m_ploidy.resize( changed.size() ) ;
+			m_nonmissingness.resize( changed.size() ) ;
+		}
+		double const prior_weight = options().get< double >( "-prior-weight" ) ;
+		double min_maf = 0.5 ;
+		for( std::size_t i = 0; i < changed.size(); ++i ) {
+			if( changed[i] == 1 ) {
+				DosageSetter setter( &(m_dosages[i]), &(m_ploidy[i]), &(m_nonmissingness[i]), options().check( "-assume-haploid" )) ;
+				readers[i]->get( ":genotypes:", genfile::to_GP_unphased( setter )) ;
+			}
+			
+#if DEBUG
+			std::cerr << globals::program_name + ":process_one(): variant " << i << ": " << variants[i] << ":\n" ;
+			std::cerr << "Loaded data with nonmissingness: " << m_nonmissingness[i] << ".\n" ;
+#endif
+
+			FrequencyStore::const_iterator where = m_frequencies.find( variants[i] ) ;
+			double frequency = 0.0 ;
+			if( where != m_frequencies.end() ) {
+				frequency = where->second ;
+			} else {
+				std::pair< double, int64_t > computedFrequency = compute_regularised_frequency( m_dosages[i], m_ploidy[i], m_nonmissingness[i], prior_weight ) ;
+				frequency = computedFrequency.first ;
+				
+				// not yet computed, so store it
+				m_frequencies[ variants[i] ] = frequency ;
+				// Output the sample count and the frequency
+				frequencyOutput.store_per_variant_data(
+					variants[i],
+					"number_of_haplotypes",
+					computedFrequency.second
+				) ;
+				frequencyOutput.store_per_variant_data(
+					variants[i],
+					"frequency",
+					frequency
+				) ;
+			}
+			min_maf = std::min( min_maf, std::min( frequency, 1.0 - frequency )) ;
+		}
+		
+		// Bail out if any of the variants are too rare
+		if( min_maf < options().get< double >( "-min-maf" )) {
+			return ;
+		}
+		
+		int const total_number_of_samples = m_dosages[0].size() ;
+		std::vector< metro::SampleRange > included_samples( 1, metro::SampleRange( 0, total_number_of_samples )) ;
+		for( std::size_t i = 0; i < changed.size(); ++i ) {
+			included_samples = metro::impl::intersect_ranges( included_samples, m_nonmissingness[i] ) ;
+		}
+		
+		// Bail out if there aren't enough samples in the pairwise comparison
+		{
+			std::size_t count = metro::impl::count_range( included_samples ) ;
+			if(
+				(count < options().get< double >( "-min-N" ))
+			 	   || (( double(count)/total_number_of_samples ) < options().get< double >( "-min-N-propn" ))
+			) {
+				return ;
+			}
+		}
+
+		double covariance = 0.0, correlation = 0.0, N = 0.0 ;
+		
+		compute_regularised_correlation(
+			m_dosages, m_ploidy, included_samples,
+			&covariance, &correlation, &N,
+			prior_weight
+		) ;
+		
+		// ints in sqlite use only 2 bytes if up to +ve integer 2287.
+		// We map -1...1 to 0...2048, such that the transformation
+		//
+		// correlation = (stored_value / 1024) - 1.0
+		// or
+		// correlation = (stored_value - 1024.0) / 1024.0
+		// maps back to correlation space.
+		//
+		int64_t const encoded_r = ( std::round((correlation + 1.0) * 1024 )) ;
+		++((*histogram)[ encoded_r ]) ;
+
+		if( ( correlation * correlation ) >= options().get< double >( "-min-r2" ) ) {
+			correlationOutput.store_data_for_key(
+				variants,
+				"N",
+				int64_t(N)
+			) ;
+			// We store correlations as integers on the scale -16384 to 16384.
+			// This is because sqlite has compression for integer storage, such that
+			// reals take 8 bytes but integers take
+			correlationOutput.store_data_for_key(
+				variants,
+				"encoded_r",
+				encoded_r
+			) ;
+			
+			if( options().check( "-details" )) {
+				Eigen::MatrixXd const table = tabulate( m_dosages, m_ploidy, included_samples ) ;
+				for( int i = 0; i < table.rows(); ++i ) {
+					for( int j = 0; j < table.cols(); ++j ) {
+						correlationOutput.store_data_for_key(
+							variants,
+							"n_" + to_string(i) + to_string(j),
+							table(i,j)
+						) ;
+					}
+				}
+				
+				if( m_ploidy[0].maxCoeff() == 1 ) {
+					metro::FishersExactTest test( table ) ;
+					double pvalue = test.get_pvalue( metro::FishersExactTest::eTwoSided ) ;
+					correlationOutput.store_data_for_key(
+						variants,
+						"fet_pvalue",
+						pvalue
+					) ;
+				}
+			}
+		}
+#if DEBUG
+		std::cerr << globals::program_name + ":process_one():\n" ;
+		std::cerr << "dosage1: " << m_dosages[0].head( 15 ).transpose() << "...\n" ; 
+		std::cerr << "dosage2: " << m_dosages[1].head( 15 ).transpose() << "...\n" ; 
+		std::cerr << "N: " << N << ".\n" ;
+		std::cerr << "covariance: " << covariance << ".\n" ;
+		std::cerr << "correlation: " << correlation << ".\n" ;
+		std::cerr << "included: " << included_samples << ".\n" ;
+#endif
+			
+	}
+	
+private:
+	std::vector< Eigen::VectorXd > m_dosages ;
+	std::vector< Eigen::VectorXd > m_ploidy ;
+	std::vector< std::vector< metro::SampleRange > > m_nonmissingness ;
+	typedef std::map< genfile::VariantIdentifyingData, double > FrequencyStore ;
+	FrequencyStore m_frequencies ;
+	
+private:
+	
+	std::pair< double, int64_t > compute_regularised_frequency(
+		Eigen::VectorXd const& dosages,
+		Eigen::VectorXd const& ploidy,
+		std::vector< metro::SampleRange > const& included_samples,
+		double prior_weight = 1.0
+	) {
+		double result = 0.0 ;
+		double N = 0.0 ;
+		for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+			metro::SampleRange const& range = included_samples[i] ;
+			result += dosages.segment( range.begin(), range.size() ).sum() ;
+			N += ploidy.segment( range.begin(), range.size() ).sum() ;
+		}
+		// Assume we have additional data adding up to prior_weight haploid samples
+		// evenly split between both alleles
+		result += prior_weight / 2 ;
+		N += prior_weight ;
+		return std::make_pair( result / N, int64_t( N ) ) ;
+	}
+
+	void compute_regularised_correlation(
+		std::vector< Eigen::VectorXd > const& dosages,
+		std::vector< Eigen::VectorXd > const& ploidy,
+		std::vector< metro::SampleRange > const& included_samples,
+		double* covariance,
+		double* correlation,
+		double* number_of_samples,
+		double const prior_weight = 1.0
+	) {
+		assert( dosages.size() == 2 ) ;
+		assert( covariance ) ;
+		assert( correlation ) ;
+		assert( number_of_samples ) ;
+		assert( ploidy[0] == ploidy[1] ) ;
+		std::vector< double > frequencies( dosages.size(), 0.0 ) ;
+
+		typedef Eigen::VectorBlock< Eigen::VectorXd const > ConstBlock ;
+		typedef Eigen::VectorBlock< Eigen::VectorXi const > ConstIntegerBlock ;
+
+		// Although frequencies are computed above, we recompute here because the
+		// number of included samples may differ for the pairwise test.
+		for( std::size_t v = 0; v < frequencies.size(); ++v ) {
+			frequencies[v] = compute_regularised_frequency(
+				dosages[v], ploidy[v], included_samples, prior_weight
+			).first ;
+		}
+
+		double result = 0.0 ;
+		double N = 0.0 ;
+		std::vector< double > variances( dosages.size(), 0.0 ) ;
+		for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+			metro::SampleRange const& range = included_samples[i] ;
+			ConstBlock d0 = dosages[0].segment( range.begin(), range.size() ) ;
+			ConstBlock d1 = dosages[1].segment( range.begin(), range.size() ) ;
+			ConstBlock p = ploidy[0].segment( range.begin(), range.size() ) ;
+			result += (
+				( d0 - p * frequencies[0] ).array()
+				* ( d1 - p * frequencies[1] ).array()
+			).sum() ;
+			N += p.array().sum() ;
+			for( std::size_t v = 0; v < frequencies.size(); ++v ) {
+				ConstBlock d = dosages[v].segment( range.begin(), range.size() ) ;
+				ConstBlock p = ploidy[v].segment( range.begin(), range.size() ) ;
+				variances[v] += ( d - p * frequencies[v] ).array().square().sum() ;
+			}
+		}
+		
+		// Add regularising information consisting of a total of
+		// prior_weight haploid samples, split evenly between
+		// the four possible genotype combinations
+		result += (0 - frequencies[0]) * (0 - frequencies[1] ) * (prior_weight / 4) ;
+		result += (0 - frequencies[0]) * (1 - frequencies[1] ) * (prior_weight / 4) ;
+		result += (1 - frequencies[0]) * (0 - frequencies[1] ) * (prior_weight / 4) ;
+		result += (1 - frequencies[0]) * (1 - frequencies[1] ) * (prior_weight / 4) ;
+		for( std::size_t v = 0; v < frequencies.size(); ++v ) {
+			variances[v] += ( 0 - frequencies[v] ) * ( 0 - frequencies[v] ) * (prior_weight / 2.0) ;
+			variances[v] += ( 1 - frequencies[v] ) * ( 1 - frequencies[v] ) * (prior_weight / 2.0) ;
+		}
+		N += prior_weight ;
+
+		*covariance = result / N ;
+		*correlation = result / (std::sqrt( variances[0] ) * std::sqrt( variances[1] )) ;
+		*number_of_samples = N ;
+	}
+	
+	Eigen::MatrixXd tabulate(
+		std::vector< Eigen::VectorXd > const& dosages,
+		std::vector< Eigen::VectorXd > const& ploidy,
+		std::vector< metro::SampleRange > const& included_samples
+	) const {
+		typedef Eigen::VectorBlock< Eigen::VectorXd const > ConstBlock ;
+		typedef Eigen::VectorBlock< Eigen::VectorXi const > ConstIntegerBlock ;
+
+		int maxPloidy0 = 0 ;
+		int maxPloidy1 = 0 ;
+		for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+			metro::SampleRange const& range = included_samples[i] ;
+			maxPloidy0 = std::max( maxPloidy0, int( ploidy[0].segment( range.begin(), range.size() ).array().maxCoeff()) ) ;
+			maxPloidy1 = std::max( maxPloidy1, int( ploidy[1].segment( range.begin(), range.size() ).array().maxCoeff()) ) ;
+		}
+		Eigen::MatrixXd result = Eigen::MatrixXd::Zero( maxPloidy0 + 1, maxPloidy1 + 1 ) ;
+		for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+			metro::SampleRange const& range = included_samples[i] ;
+			for( int j = range.begin(); j < range.end(); ++j ) {
+				++result( dosages[0][j], dosages[1][j] ) ;
+			}
+		}
+		return result ;
+	}
+
+	struct DosageSetter: public genfile::VariantDataReader::PerSampleSetter {
+		typedef std::vector< metro::SampleRange > SampleRanges ;
+
+		DosageSetter(
+			Eigen::VectorXd* dosages,
+			Eigen::VectorXd* ploidy,
+			SampleRanges* nonmissing_samples,
+			bool treat_as_haploid = false
+		):
+			m_dosages( dosages ),
+			m_ploidy( ploidy ),
+			m_total_prob(0.0),
+			m_treat_as_haploid( treat_as_haploid ),
+			m_number_of_entries( 0 ),
+			m_nonmissing_samples( nonmissing_samples ),
+			m_sample_i(0)
+		{
+			assert( dosages != 0 && nonmissing_samples != 0 && ploidy != 0 ) ;
+		}
+
+		void initialise( std::size_t nSamples, std::size_t nAlleles ) {
+			if( nAlleles != 2 ) {
+				throw genfile::BadArgumentError(
+					"ProbSetter::initialise()",
+					"nAlleles=" + genfile::string_utils::to_string( nAlleles ),
+					"I only support biallelic variants"
+				) ;
+			}
+			m_dosages->resize( nSamples ) ;
+			m_dosages->setZero() ;
+			m_ploidy->resize( nSamples ) ;
+			m_ploidy->setZero() ;
+			
+			m_nonmissing_samples->clear() ;
+			m_last_nonmissing_sample_i = 0 ;
+		}
+
+		bool set_sample( std::size_t n ) {
+			m_sample_i = n ;
+			return true ;
+		}
+
+		void set_number_of_entries(
+			uint32_t ploidy, std::size_t n,
+			genfile::OrderType const order_type,
+			genfile::ValueType const value_type
+		) {
+			if( value_type != genfile::eProbability ) {
+				throw genfile::BadArgumentError(
+					"Callsetter::set_number_of_entries()",
+					"value_type=" + genfile::string_utils::to_string( value_type ),
+					"Expected genotype call probabilities (e.g. GP field)."
+				) ;
+			}
+			if( order_type != genfile::ePerUnorderedGenotype ) {
+				throw genfile::BadArgumentError(
+					"Callsetter::set_number_of_entries()",
+					"order_type=" + genfile::string_utils::to_string( order_type ),
+					"Expected genotype call probabilities (e.g. GP field)."
+				) ;
+			}
+			if( m_treat_as_haploid ) {
+				(*m_ploidy)(m_sample_i) = 1 ;
+			} else {
+				(*m_ploidy)(m_sample_i) = ploidy ;
+			}
+			m_number_of_entries = n ;
+			m_total_prob = 0.0 ;
+		}
+
+		void set_value( std::size_t entry_i, genfile::MissingValue const value ) {
+			// This sample has missing data, end our current sample range here.
+			if( m_sample_i > m_last_nonmissing_sample_i ) {
+				m_nonmissing_samples->push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i )
+				) ;
+#if DEBUG > 2
+				std::cerr << "DosageSetter::set_value(): added sample range: " << m_nonmissing_samples->back() << ".\n" ;
+#endif
+			}
+			// Skip this sample for next range.
+			m_last_nonmissing_sample_i = m_sample_i + 1 ;
+		}
+
+		void set_value( std::size_t entry_i, Integer const value ) {
+			assert(0) ; // expected a probabilty
+		}
+
+		void set_value( std::size_t entry_i, double const value ) {
+			if( !sample_recorded_missing() ) {
+				bool const last_entry = ((entry_i+1) == m_number_of_entries ) ;
+				// we assume two alleles, so entry_i is also the count of the B allele 
+				// in the genotype.
+				if( m_treat_as_haploid ) {
+					// only homozygous genotypes are counted, others are assumed missing
+					// entry_i == 0 contributes 0 dosage anyway so just count the last entry
+					//
+					// Sample considered missing if has nonzero probability on non-homozygous genotype
+					// (caught here), or if it has total 0 probability on homozygous genotypes (handled below).
+					if( entry_i == 0 || last_entry ) {
+						(*m_dosages)(m_sample_i) += ( last_entry ? value : 0.0 );
+						m_total_prob += value ;
+					} else if( value != 0 ) {
+						record_missing_sample() ;
+					}
+				} else {
+					(*m_dosages)(m_sample_i) += value * entry_i ;
+					m_total_prob += value ;
+				}
+
+				// handle missing data encoded as zeroes
+				if( last_entry && m_total_prob == 0.0 ) {
+					record_missing_sample() ;
+				}
+				
+#if DEBUG > 2
+				std::cerr << "DosageSetter::set_value(): added value " << (value * entry_i) << " to entry " << entry_i << " for sample " << m_sample_i << ".\n" ;
+#endif
+			}
+		}
+
+		void finalise() {
+			// Add the final sample range if needed.
+			if( (m_sample_i+1) > m_last_nonmissing_sample_i ) {
+				m_nonmissing_samples->push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i+1 )
+				) ;
+#if DEBUG > 2
+				std::cerr << "DosageSetter::finalise(): added sample range: " << m_nonmissing_samples->back() << ".\n" ;
+#endif
+			}
+#if DEBUG > 2
+				std::cerr << "DosageSetter::finalise(): complete.\n" ;
+#endif
+		}
+		
+	private:
+		Eigen::VectorXd* m_dosages ;
+		Eigen::VectorXd* m_ploidy ;
+		double m_total_prob ;
+		bool m_treat_as_haploid ;
+
+		std::size_t m_number_of_entries ;
+		SampleRanges* m_nonmissing_samples ;
+		std::size_t m_last_nonmissing_sample_i ;
+		std::size_t m_sample_i ;
+	private:
+		
+		bool sample_recorded_missing() const {
+			return m_sample_i < m_last_nonmissing_sample_i ;
+		}
+
+		void record_missing_sample() {
+			// missing
+			m_nonmissing_samples->push_back(
+				metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i )
+			) ;
+			// Skip this sample for next range.
+			m_last_nonmissing_sample_i = m_sample_i + 1 ;
+		}
+	} ;
+} ;
+
+int main( int argc, char** argv ) {
+    try {
+		LDbirdApplication app( argc, argv ) ;
+    }
+	catch( appcontext::HaltProgramWithReturnCode const& e ) {
+		return e.return_code() ;
+	}
+	return 0 ;
+}
+

ADDED   apps/multifinemap.cpp
Index: apps/multifinemap.cpp
==================================================================
--- apps/multifinemap.cpp
+++ apps/multifinemap.cpp
@@ -0,0 +1,1081 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+
+#include <vector>
+#include <unordered_map>
+#include <ctime>
+#include <boost/function.hpp>
+#include <boost/format.hpp>
+#include <boost/filesystem.hpp>
+#include <boost/timer/timer.hpp>
+#include <boost/functional/hash.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/discrete_distribution.hpp>
+#include <boost/bind.hpp>
+
+#include "config/package_revision_autogenerated.hpp"
+
+#include "metro/constants.hpp"
+#include "metro/ShotgunStochasticSearch.hpp"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/Logistic.hpp"
+#include "metro/IndependentParameterDistribution.hpp"
+#include "metro/distributions/LogF.hpp"
+#include "metro/distributions/Flat.hpp"
+#include "metro/regression/LogUnnormalisedPosterior.hpp"
+#include "metro/intersect_ranges.hpp"
+#include "metro/fit_model.hpp"
+#include "metro/CholeskyStepper.hpp"
+#include "metro/SampleRange.hpp"
+#include "metro/log_sum_exp.hpp"
+
+#include "appcontext/CmdLineOptionProcessor.hpp"
+#include "appcontext/ApplicationContext.hpp"
+
+#include "genfile/MissingValue.hpp"
+#include "genfile/bgen/View.hpp"
+#include "genfile/bgen/Query.hpp"
+#include "genfile/SNPDataSource.hpp"
+#include "genfile/db/Error.hpp"
+#include "genfile/ToGP.hpp"
+#include "genfile/CrossCohortCovariateValueMapping.hpp"
+#include "genfile/CommonSNPFilter.hpp"
+#include "genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp"
+
+#include "qcdb/FlatFileMultiVariantOutputter.hpp"
+
+namespace bfs = boost::filesystem ;
+
+// #define DEBUG 1
+// #define DEBUG_DOSAGESTORE 1
+
+namespace globals {
+	std::string const program_name = "multifinemap" ;
+	std::string const program_version = package_version ;
+	std::string const program_revision =  std::string( package_revision ).substr( 0, 7 ) ;
+}
+
+namespace {
+	std::string print_state( std::size_t N, std::vector< std::size_t > const& states ) {
+		std::string result = "[";
+		std::size_t begin = 0 ;
+		for( std::size_t i = 0; i <= states.size(); ++i ) {
+			std::size_t end = (i==states.size()) ? N : states[i] ;
+			for( std::size_t j = begin; j < end; ++j ) {
+				result.push_back( '0' ) ;
+			}
+			if( end != N ) {
+				result.push_back( '1' ) ;
+			}
+			begin = end+1 ;
+		}
+		result += ']' ;
+		return result ;
+	}
+}
+
+struct MFMOptions: public appcontext::CmdLineOptionProcessor
+{
+public:
+	std::string get_program_name() const { return globals::program_name ; }
+
+	void declare_options( appcontext::OptionProcessor& options ) {
+		// Meta-options
+		options.set_help_option( "-help" ) ;
+		options.set_spec_option( "-spec" ) ;
+
+		// File options
+		options.declare_group( "Input file options" ) ;
+	    options[ "-g" ]
+	        .set_description( 	"Path to BGEN file giving genotypes." )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 1 )
+			.set_maximum_multiplicity( 1 ) ;
+	    options[ "-filetype" ]
+			.set_description(
+				"Specify the filetype of the genotype files specified by -g. "
+				"By default, qctool will guess the file type.  Use this option to override that guess. "
+				"Possible types are: \"" + genfile::string_utils::join( genfile::SNPDataSource::get_file_types(), "\",\"" ) + "\"." )
+			.set_takes_single_value()
+			.set_default_value( "guess" ) ;
+
+	    options[ "-assume-chromosome" ]
+	        .set_description( "Chromosome to assume if not in genetic data." )
+			.set_takes_single_value() ;
+	    options[ "-s" ]
+	        .set_description( "Path of sample file to input.  If specified, this option must occur as often as the -g option"
+							" to specify one sample file per cohort." )
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 1 )
+			.set_maximum_multiplicity( 1000 ) ;
+		options[ "-outcome" ]
+			.set_description( "Name of column containing outcome.  Currently must be a binary outcome." )
+			.set_takes_single_value()
+			.set_is_required() ;
+		
+		options.declare_group( "Input filtering options" ) ;
+		options[ "-incl-range" ]
+			.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. "
+				"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+				"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+				"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+			.set_takes_values_until_next_option() ;
+		options[ "-excl-range" ]
+			.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to exclude from operation. "
+				"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
+				"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
+				"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
+			.set_takes_values_until_next_option() ;
+		options[ "-incl-ranges" ]
+			.set_description( "Like -incl-range, but read the ranges from the specified file."
+				"The file must contain a whitespace-separated list of genomic ranges to include in the analysis." )
+			.set_takes_values_until_next_option() ;
+		options[ "-excl-ranges" ]
+			.set_description( "Like -excl-range, but read the ranges from the specified file."
+				"The file must contain a whitespace-separated list of genomic ranges to exclude from the analysis." )
+			.set_takes_values_until_next_option() ;
+		
+		options.declare_group( "Output file options" ) ;
+		options[ "-o" ]
+			.set_description( "Path to output file.  Use \"-\" for stdout." )
+			.set_takes_single_value()
+			.set_default_value( "-" ) ;
+
+		options.declare_group( "Model options" ) ;
+		options[ "-incl-samples"]
+			.set_description( "Filter out samples whose sample ID does not lie in the given file(s).")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-excl-samples"]
+			.set_description( "Filter out samples whose sample ID lies in the given file.")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-incl-samples-where"]
+			.set_description( "Include samples by specifying conditions on the values of columns in the sample file.")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-excl-samples-where"]
+			.set_description( "Exclude samples by specifying conditions on the values of columns in the sample file.")
+			.set_takes_values( 1 )
+			.set_minimum_multiplicity( 0 )
+			.set_maximum_multiplicity( 100 ) ;
+		options[ "-minimum-allele-count" ]
+			.set_description( "Skip predictors that have less than this minor allele count" )
+			.set_takes_values(1)
+			.set_default_value( 10 ) ;
+		options[ "-covariates" ]
+			.set_description( "Specify the name of one or more covariates to include in the model."
+				" These must be columns named in the sample file." )
+			.set_takes_values_until_next_option() ;
+			
+		options.declare_group( "Model fitting options" ) ;
+		options[ "-tolerance" ]
+			.set_description( "Tolerance to use when model fitting" )
+			.set_takes_values(1)
+			.set_default_value( 0.001 ) ;
+		options[ "-max-iterations" ]
+			.set_description( "Maximum iterations to allow when model fitting" )
+			.set_takes_values(1)
+			.set_default_value( 100 ) ;
+		options[ "-max-causal-variants" ]
+			.set_description( "Set the maximum number of variants allowed in a causal configuration")
+			.set_takes_values(1)
+			.set_default_value(5)
+		;
+		options[ "-additive" ]
+			.set_description( "Specify that only additive effects are allowed for" ) ;
+		;
+		options.declare_group( "Miscellaneous options" ) ;
+		options[ "-analysis-name" ]
+			.set_description( "Specify a name to label results from this analysis with." )
+			.set_takes_single_value()
+			.set_default_value( "qctool analysis" ) ;
+		options[ "-analysis-chunk" ]
+			.set_description( "Specify a name denoting the current genomic region or chunk on which this is run.  This is intended for use in parallel environments." )
+			.set_takes_single_value()
+			.set_default_value( genfile::MissingValue() ) ;
+		options.declare_group( "Miscellaneous options" ) ;
+		options[ "-debug" ]
+			.set_description( "Output debugging information." ) ;
+		options [ "-log" ]
+			.set_description( "Specify that " + globals::program_name + " should write a log file to the given file." )
+			.set_takes_single_value() ;
+	}
+} ;
+
+struct DosageStore {
+public:
+	typedef boost::function< void( std::size_t const, boost::optional< std::size_t > const ) > ProgressCallback ;
+	typedef std::unique_ptr< DosageStore > UniquePtr ;
+
+	static UniquePtr create() {
+		return UniquePtr( new DosageStore() ) ;
+	}
+public:
+	DosageStore() {}
+	
+	void load( genfile::SNPDataSource::UniquePtr source, ProgressCallback callback ) {
+		load_unsafe( *source, callback ) ;
+	}
+	
+	std::size_t number_of_samples() const { return m_ploidy[0].size() ; }
+	std::size_t number_of_variants() const { return m_variants.size() ; }
+	genfile::VariantIdentifyingData const& variant( std::size_t i ) const { return m_variants[i] ; }
+
+	std::size_t estimate_memory_usage() const {
+		std::size_t result = 0 ;
+		for( std::size_t i = 0; i < m_variants.size(); ++i ) {
+			result += m_variants[i].estimate_bytes_used() ;
+			result += m_ploidy[i].size() ;
+			result += m_AB[i].size() ;
+			result += m_BB[i].size() ;
+		}
+		return result ;
+	}
+	
+	std::string get_summary() const {
+		using boost::format ;
+		return (
+			boost::format( "DosageStore: %d variants, %d samples, approx %.2fMb memory usage.\n" )
+				% m_variants.size()
+				% (m_variants.size() > 0 ? m_AB[0].size() : 0 )
+				% (estimate_memory_usage() / 1000000.0)
+		).str() ;
+	}
+	
+	genfile::VariantIdentifyingData const get_variant( std::size_t i ) const {
+		assert( i < m_variants.size() ) ;
+		return m_variants[i] ;
+	}
+	
+	template< typename Callback >
+	void get_dosages( std::size_t i, Callback callback ) const {
+		assert( i < m_variants.size() ) ;
+		double const constant = double(0xFFFFFFFF >> 24) ;
+		assert( i < m_variants.size() ) ;
+		for( std::size_t j = 0; j < m_AB[i].size(); ++j ) {
+			// unpack 8 bit bgen encoding
+#if DEBUG_DOSAGESTORE
+			if( j < 10 ) {
+				std::cerr << "get_dosages(): " << j << ": " << int( m_AB[i][j] ) << ", " << int( m_BB[i][j] ) << ".\n" ;
+			}
+#endif
+			callback( j, double( m_AB[i][j] ) / constant, double( m_BB[i][j] ) / constant ) ;
+		}
+	}
+	
+	std::vector< metro::SampleRange > const nonmissing_samples( std::size_t i ) const {
+		assert( i < m_variants.size() ) ;
+		return m_nonmissing_samples[i] ;
+	}
+
+private:
+
+	/* Store genotype probabilities in 8 bit, BGEN-like encoding */
+	struct DosageSetter {
+		DosageSetter(
+			std::vector< uint8_t >* ploidy,
+			std::vector< uint8_t >* AB,
+			std::vector< uint8_t >* BB
+		):
+			m_ploidy( ploidy ),
+			m_AB( AB ),
+			m_BB( BB ),
+			m_bits(8),
+			m_constant( double(0xFFFFFFFF >> (32 - m_bits))),
+			m_sample_i(0),
+			m_order_type( genfile::eUnknownOrderType )
+		{}
+		
+		void initialise( std::size_t nSamples, std::size_t nAlleles ) {
+			assert( nAlleles == 2 ) ;
+			m_ploidy->resize( nSamples ) ;
+			std::fill( m_ploidy->begin(), m_ploidy->end(), 0x80 ) ;
+			m_AB->resize( nSamples ) ;
+			std::fill( m_AB->begin(), m_AB->end(), 0 ) ;
+			m_BB->resize( nSamples ) ;
+			std::fill( m_BB->begin(), m_BB->end(), 0 ) ;
+			m_last_nonmissing_sample_i = 0 ;
+		}
+
+		bool set_sample( std::size_t n ) {
+			m_sample_i = n ;
+			m_order_type = genfile::eUnknownOrderType ;
+			return true ;
+		}
+
+		void set_number_of_entries(
+			uint32_t ploidy, std::size_t n,
+			genfile::OrderType const order_type,
+			genfile::ValueType const value_type
+		) {
+			assert( ploidy <= 2 ) ;
+			assert( (order_type == genfile::ePerOrderedHaplotype || genfile::ePerUnorderedGenotype) && value_type == genfile::eProbability ) ;
+			(*m_ploidy)[m_sample_i] = ploidy ;
+			m_order_type = order_type ;
+		}
+
+		void set_value( std::size_t entry_i, genfile::MissingValue const value ) {
+			uint8_t& ploidy = (*m_ploidy)[m_sample_i] ;
+			uint8_t& AB = (*m_AB)[m_sample_i] ;
+			uint8_t& BB = (*m_BB)[m_sample_i] ;
+			ploidy |= 0x80 ;
+			AB = BB = 0 ;
+			record_missing_sample( m_sample_i ) ;
+		}
+
+		void set_value( std::size_t entry_i, double const value ) {
+			uint8_t& ploidy = (*m_ploidy)[m_sample_i] ;
+			uint8_t& AB = (*m_AB)[m_sample_i] ;
+			uint8_t& BB = (*m_BB)[m_sample_i] ;
+
+#if DEBUG_DOSAGESTORE
+			if( m_sample_i < 10 ) {
+				std::cerr << "DosageSetter::set_value(): " << m_sample_i << ", " << entry_i << ": " << value << ".\n" ;
+			}
+#endif
+			if( !(ploidy & 0x80) ) {
+				if( entry_i == 1 ) {
+					AB = value * m_constant ;
+				} else if (entry_i == 2 ) {
+					BB = value * m_constant ;
+				}
+			}
+		}
+
+		void set_value( std::size_t entry_i, genfile::Integer const value ) {
+			assert(0) ; // expecting GT field
+		}
+
+		void finalise() {
+			// add the final sample range if needed.
+			record_missing_sample( m_ploidy->size() ) ;
+		}
+		
+		std::vector< metro::SampleRange > const nonmissing_samples() { return m_nonmissing_samples ; }
+		
+		private:
+			std::vector< uint8_t >* m_ploidy ;
+			std::vector< uint8_t >* m_AB ;
+			std::vector< uint8_t >* m_BB ;
+			uint32_t m_bits ;
+			double m_constant ;
+			std::size_t m_sample_i ;
+			std::size_t m_last_nonmissing_sample_i ;
+			genfile::OrderType m_order_type ;
+			std::vector< metro::SampleRange > m_nonmissing_samples ;
+			
+		void record_missing_sample( std::size_t sample_i ) {
+			if( sample_i >= m_last_nonmissing_sample_i ) {
+				m_nonmissing_samples.push_back(
+					metro::SampleRange( m_last_nonmissing_sample_i, m_sample_i )
+				) ;
+			}
+			m_last_nonmissing_sample_i = sample_i + 1 ;
+		}
+	} ;
+
+	void load_unsafe( genfile::SNPDataSource& source, ProgressCallback callback ) {
+		if( source.total_number_of_snps() ) {
+			std::size_t N = *source.total_number_of_snps() ;
+			m_variants.reserve( N ) ;
+			m_ploidy.reserve( N ) ;
+			m_AB.reserve( N ) ;
+			m_BB.reserve( N ) ;
+		}
+
+		genfile::VariantIdentifyingData variant ;
+		std::vector< uint16_t > data ;
+		std::size_t count = 0 ;
+		std::vector< uint8_t > ploidy, AB, BB ;
+		
+		while( source.get_snp_identifying_data( &variant )) {
+			// ok, read dosages.
+			std::cerr << "LOADING " << variant << ".\n" ;
+			DosageSetter setter( &ploidy, &AB, &BB ) ;
+			source.read_variant_data()->get( ":genotypes:", genfile::to_GP_unphased( setter ) ) ;
+			m_variants.push_back( variant ) ;
+			m_nonmissing_samples.push_back( setter.nonmissing_samples() ) ;
+			m_ploidy.push_back( ploidy ) ;
+			m_AB.push_back( AB ) ;
+			m_BB.push_back( BB ) ;
+			//m_data.push_back( data ) ;
+			if( callback ) {
+				callback( ++count, source.total_number_of_snps() ) ;
+			}
+		}
+	}
+	
+	std::vector< genfile::VariantIdentifyingData > m_variants ;
+	// To avoid using too much space, we encode dosage data as 16-bit integer
+	// and expand to required format when requested.
+	std::vector< std::vector< metro::SampleRange > > m_nonmissing_samples ;
+	std::vector< std::vector< uint8_t > > m_ploidy ;
+	std::vector< std::vector< uint8_t > > m_AB ;
+	std::vector< std::vector< uint8_t > > m_BB ;
+} ;
+
+struct MFMApplication: public appcontext::ApplicationContext {
+	MFMApplication( int argc, char** argv ):
+		appcontext::ApplicationContext(
+			globals::program_name,
+			"version: " + globals::program_version + ", revision: " + globals::program_revision,
+			std::auto_ptr< appcontext::OptionProcessor >( new MFMOptions ),
+			argc,
+			argv,
+			"-log"
+		)
+	{
+		process() ;
+	}
+	
+private:
+	
+	void process() {
+		try {
+			unsafe_process() ;
+		} catch( genfile::InputError const& e ) {
+			ui().logger() << "!! Error (" << e.what() << "): " << e.format_message() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::FileNotFoundError const& e ) {
+			ui().logger() << "\nError: No file matching \"" << e.filespec() << "\" could be found.\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::db::Error const& e ) {
+			ui().logger() << "!! Error (" << e.what() << ") with the following statement: \""
+				<< e.sql()
+				<< "\".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+	}
+	
+	void unsafe_process() {
+		DosageStore::UniquePtr store = load_genotypes() ;
+
+		genfile::CohortIndividualSource::UniquePtr
+			samples = genfile::CohortIndividualSource::create( options().get< std::string >( "-s" ) ) ;
+
+		metro::regression::LogLikelihood::UniquePtr
+			ll = create_loglikelihood( samples->size() ) ;
+
+		if( options().check( "-covariates" )) {
+			add_covariates( ll->design(), *samples, options().get_values< std::string >( "-covariates" ) ) ;
+		}
+	
+		set_outcome( *ll, *samples, options().get_value< std::string >( "-outcome" )) ;
+
+		std::cerr << ll->design().get_summary() << "\n" ;
+
+		run_search( *store, *ll ) ;
+	}
+	
+	DosageStore::UniquePtr load_genotypes() {
+		appcontext::UIContext::ProgressContext progress_context = ui().get_progress_context( "Loading data" ) ;
+		DosageStore::UniquePtr store = DosageStore::create() ;
+		store->load(
+			open_snp_data_source( options().get< std::string >( "-g" ) ),
+			progress_context
+		) ;
+		ui().logger() << store->get_summary() ;
+		return store ;
+	}
+	
+	genfile::SNPDataSource::UniquePtr
+	open_snp_data_source( std::string const& filename ) const {
+		genfile::Chromosome chromosome_hint ;
+		std::string chromosome_indicator ;
+		if( options().check_if_option_was_supplied( "-assume-chromosome" )) {
+			chromosome_indicator = options().get_value< std::string >( "-assume-chromosome" ) ;
+		}
+		if( chromosome_indicator != "" ) {
+			chromosome_hint = chromosome_indicator ;
+		}
+
+		genfile::SNPDataSource::UniquePtr source ;
+
+		std::pair< std::string, std::string > uf = genfile::uniformise( filename ) ;
+
+		{
+			boost::optional< genfile::vcf::MetadataParser::Metadata > metadata ;
+//			if( m_options.check( "-metadata" )) {
+//				metadata = genfile::vcf::StrictMetadataParser(
+//					m_options.get_value< std::string >( "-metadata" )
+//				).get_metadata() ;
+//			}
+			source = genfile::SNPDataSource::create(
+				filename,
+				chromosome_hint,
+				metadata,
+				options().get< std::string >( "-filetype" )
+			) ;
+		}
+		
+		genfile::CommonSNPFilter::UniquePtr snp_filter = construct_snp_filter() ;
+		// Filter SNPs if necessary
+		if( snp_filter.get() ) {
+			genfile::VariantIdentifyingDataFilteringSNPDataSource::UniquePtr snp_filtering_source
+				= genfile::VariantIdentifyingDataFilteringSNPDataSource::create(
+					source,
+					genfile::VariantIdentifyingDataTest::UniquePtr( snp_filter.release() )
+				) ;
+
+			source.reset(
+				snp_filtering_source.release()
+			) ;
+		}
+		
+		return source ;
+	}
+
+	genfile::CommonSNPFilter::UniquePtr construct_snp_filter() const {
+		genfile::CommonSNPFilter::UniquePtr snp_filter ;
+
+		if( options().check_if_option_was_supplied_in_group( "Input filtering options" )) {
+			snp_filter.reset( new genfile::CommonSNPFilter ) ;
+			if( options().check_if_option_was_supplied( "-incl-range" )) {
+				std::vector< std::string > specs = options().get_values< std::string >( "-incl-range" ) ;
+				for ( std::size_t i = 0; i < specs.size(); ++i ) {
+					snp_filter->include_snps_in_range(
+						genfile::GenomePositionRange::parse( specs[i] )
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-excl-range" )) {
+				std::vector< std::string > specs = options().get_values< std::string >( "-excl-range" ) ;
+				for ( std::size_t i = 0; i < specs.size(); ++i ) {
+					snp_filter->exclude_snps_in_range(
+						genfile::GenomePositionRange::parse( specs[i] )
+					) ;
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-incl-ranges" )) {
+				std::vector< std::string > files = options().get_values< std::string >( "-incl-ranges" ) ;
+				for( std::string const& filename: files ) {
+					std::auto_ptr< std::istream > in = genfile::open_text_file_for_input( filename ) ;
+					std::string range ;
+					while( (*in) >> range ) {
+						snp_filter->include_snps_in_range(
+							genfile::GenomePositionRange::parse( range )
+						) ;
+					}
+				}
+			}
+
+			if( options().check_if_option_was_supplied( "-excl-ranges" )) {
+				std::vector< std::string > files = options().get_values< std::string >( "-excl-ranges" ) ;
+				for( std::string const& filename: files ) {
+					std::auto_ptr< std::istream > in = genfile::open_text_file_for_input( filename ) ;
+					std::string range ;
+					while( (*in) >> range ) {
+						snp_filter->exclude_snps_in_range(
+							genfile::GenomePositionRange::parse( range )
+						) ;
+					}
+				}
+			}
+		}
+		return snp_filter ;
+	}
+	
+	metro::regression::LogLikelihood::UniquePtr create_loglikelihood( std::size_t number_of_samples ) {
+		typedef std::vector< std::string > Names ;
+		typedef std::vector< metro::SampleRange > SampleRanges ;
+		using namespace metro::regression ;
+
+		Eigen::MatrixXd outcome = Eigen::MatrixXd::Zero( number_of_samples, 2 ) ;
+
+		Design::UniquePtr design = Design::create(
+			outcome, SampleRanges(), Names({ "outcome=0", "outcome=1"} ),
+			Names({
+				"add1", "het1",
+				"add2", "het2",
+				"add3", "het3",
+				"add4", "het4",
+				"add5", "het5"
+			})
+		) ;
+		LogLikelihood::UniquePtr ll( metro::regression::Logistic::create( design ).release() ) ;
+		return ll ;
+	}
+	
+	void add_covariates(
+		metro::regression::Design& design,
+		genfile::CohortIndividualSource const& samples,
+		std::vector< std::string > const& covariates
+	) {
+		ui().logger() << "Adding covariates...\n" ;
+		{
+			std::set< std::string > uniqueCovariates( covariates.begin(), covariates.end() ) ;
+			if( uniqueCovariates.size() != covariates.size() ) {
+				throw genfile::BadArgumentError(
+					"add_covariates()",
+					"covariates=\"" + genfile::string_utils::join( covariates, " " ) + "\"",
+					"Covariates should not be duplicated."
+				) ;
+			}
+		}
+		genfile::CohortIndividualSource::ColumnSpec const& spec = samples.get_column_spec() ;
+		for( std::size_t i = 0; i < covariates.size(); ++i ) {
+			std::string const& covariateName = covariates[i] ;
+			std::size_t const column_index = spec.find_column( covariateName ) ;
+			genfile::CohortIndividualSource::SingleColumnSpec columnSpec = spec[ column_index ] ;
+			genfile::CrossCohortCovariateValueMapping::UniquePtr mapping
+				= genfile::CrossCohortCovariateValueMapping::create( columnSpec, true ) ;
+			mapping->add_source( samples ) ;
+			if( columnSpec.is_discrete() ) {
+				design.add_discrete_covariate(
+					covariateName,
+					[&samples, &column_index, &mapping] ( std::size_t sample_index ) {
+						int value = -1 ;
+						genfile::VariantEntry entry = samples.get_entry( sample_index, column_index ) ;
+						if( !entry.is_missing() ) {
+							value = mapping->get_mapped_value( entry ).as< int >() ;
+						}
+						return value ;
+					},
+					[&mapping]( int level ) {
+						genfile::VariantEntry entry = mapping->get_unmapped_value( level ) ;
+						return entry.as< std::string >() ;
+					},
+					mapping->get_number_of_distinct_mapped_values()
+				) ;
+			} else {
+				design.add_single_covariate(
+					covariateName,
+					[&samples, &column_index, &mapping]( std::size_t sample_index ) {
+						double value = metro::NA ;
+						genfile::VariantEntry entry = samples.get_entry( sample_index, column_index ) ;
+						if( !entry.is_missing() ) {
+							value = mapping->get_mapped_value( entry ).as< double >() ;
+						}
+						return value ;
+					}
+				) ;
+			}
+			
+			ui().logger()
+				<< "++ Added covariate: \"" + covariateName + "\":\n"
+				<<  mapping->get_summary( "     " )
+				<< "\n\n" ;
+		}
+	}
+
+	void set_outcome(
+		metro::regression::LogLikelihood& ll,
+		genfile::CohortIndividualSource const& samples,
+		std::string const& column
+	) const {
+		typedef std::vector< std::string > Names ;
+		typedef std::vector< metro::SampleRange > SampleRanges ;
+		Eigen::MatrixXd outcome = Eigen::MatrixXd::Zero( samples.size(), 2 ) ;
+		SampleRanges nonmissingness ;
+		get_binary_outcome( samples, column, &outcome, &nonmissingness ) ;
+		ll.design().set_outcome(
+			outcome, nonmissingness,
+			Names({ column + "=0", column + "=1" })
+		) ;
+	}
+
+	void get_binary_outcome(
+		genfile::CohortIndividualSource const& samples,
+		std::string const& column,
+		Eigen::MatrixXd* outcome,
+		std::vector< metro::SampleRange >* nonmissingness
+	) const {
+		std::size_t column_i = samples.get_column_spec().find_column( column ) ;
+		assert( samples.get_column_spec()[ column_i ].is_discrete() ) ;
+		std::size_t last_nonmissing_sample_i = 0 ;
+		outcome->setZero( samples.size(), 2 ) ;
+		for( std::size_t i = 0; i < samples.size(); ++i ) {
+			genfile::VariantEntry const& entry = samples.get_entry( i, column_i ) ;
+			if( entry.is_missing() ) {
+				nonmissingness->push_back( metro::SampleRange( last_nonmissing_sample_i, i )) ;
+				last_nonmissing_sample_i = i+1 ;
+			} else {
+				int value = entry.as< int >() ;
+				assert( value == 0 || value == 1 ) ;
+				(*outcome)(i,value) = 1 ;
+			}
+		}
+		if( last_nonmissing_sample_i < samples.size() ) {
+			nonmissingness->push_back( metro::SampleRange( last_nonmissing_sample_i, samples.size() )) ;
+		}
+#if DEBUG
+		std::cerr << "get_outcome(): outcome is:\n"
+			<< outcome->block(0,0,10,2 ) << "\n"
+			<< "nonmissingness: " << *nonmissingness << "\n" ;
+#endif
+	}
+
+
+	typedef std::map< std::vector< metro::SampleRange >, std::pair< Eigen::VectorXd, double > > NullLLStore ;
+
+	double test_variant(
+		metro::ShotgunStochasticSearch::SelectedStates const& pick,
+		DosageStore const& store,
+		metro::regression::LogLikelihood& ll,
+		NullLLStore& null_ll_store
+	) {
+#if DEBUG
+		std::cerr << "   TESTING: " << print_state( store.number_of_variants(), pick ) << ".\n" ;
+#endif
+		using namespace metro::regression ;
+		using metro::SampleRange ;
+		
+		double const minus_infinity = -std::numeric_limits< double >::infinity() ;
+		double const log_weight = ( (pick.size() == 0) || (pick.size() > 5) )
+			? minus_infinity
+			: (pick.size() * std::log( 1.0 / store.number_of_variants() )) ;
+	
+		if( log_weight == minus_infinity ) {
+			// Disallowed state, don't bother fitting.
+			return minus_infinity ;
+		}
+
+		boost::format parameter_format( "%s%d/%s" ) ;
+		bool const debug = options().check( "-debug" ) ;
+
+		assert( pick.size() < 6 ) ;
+		Eigen::MatrixXd predictors = Eigen::MatrixXd::Zero( store.number_of_samples(), 10 ) ;
+		std::vector< metro::SampleRange > nonmissing_samples( 1, metro::SampleRange( 0, store.number_of_samples() )) ;
+
+		metro::IndependentParameterDistribution prior( ll.get_parameter_names() ) ;
+		metro::IndependentParameterDistribution null_prior( ll.get_parameter_names() ) ;
+
+		double const add_prior_obs = 32.0 ;
+		double const het_prior_obs = options().check( "-additive" ) ? 1000.0 : 32.0 ;
+
+		for( std::size_t i = 0; i < 5; ++i ) {
+			null_prior.set_prior(
+				(parameter_format % "add" % (i+1) % ll.design().get_outcome_name(1) ).str(),
+				metro::distributions::LogF::create( 10000.0, 10000.0 )
+			) ;
+			null_prior.set_prior(
+				(parameter_format % "het" % (i+1) % ll.design().get_outcome_name(1) ).str(),
+				metro::distributions::LogF::create( 10000.0, 10000.0 )
+			) ;
+		}
+		
+		for( std::size_t i = 0; i < pick.size(); ++i ) {
+			store.get_dosages(
+				pick[i],
+				[&predictors,i] ( int sample, double ab, double bb ){
+					predictors( sample, i*2+0) = ab + 2*bb ;
+					predictors( sample, i*2+1) = ab ;
+				}
+			) ;
+			nonmissing_samples = metro::impl::intersect_ranges(
+				nonmissing_samples,
+				store.nonmissing_samples(pick[i])
+			) ;
+			prior.set_prior(
+				(parameter_format % "add" % (i+1) % ll.design().get_outcome_name(1) ).str(),
+				metro::distributions::LogF::create( add_prior_obs, add_prior_obs )
+			) ;
+			prior.set_prior(
+				(parameter_format % "het" % (i+1) % ll.design().get_outcome_name(1) ).str(),
+				metro::distributions::LogF::create( het_prior_obs, het_prior_obs )
+			) ;
+		}
+		for( std::size_t i = pick.size(); i < 5; ++i ) {
+			prior.set_prior(
+				(parameter_format % "add" % (i+1) % ll.design().get_outcome_name(1) ).str(),
+				metro::distributions::LogF::create( add_prior_obs, add_prior_obs )
+			) ;
+			prior.set_prior(
+				(parameter_format % "het" % (i+1) % ll.design().get_outcome_name(1) ).str(),
+				metro::distributions::LogF::create( het_prior_obs, het_prior_obs )
+			) ;
+		}
+
+		// Set up a trace for model fitting iterations.
+		metro::CholeskyStepper::Tracer tracer ;
+		if( debug ) {
+			tracer = [this] ( 
+				int iteration,
+				double ll,
+				double target_ll,
+				metro::CholeskyStepper::Vector const& point,
+				metro::CholeskyStepper::Vector const& first_derivative,
+				metro::CholeskyStepper::Vector const& step,
+				bool converged
+			) {
+				this->ui().logger()
+					<< " ITERATION: " << iteration << "\n"
+					<< "        LL: " << ll << "\n"
+					<< "    TARGET: " << target_ll << "\n"
+					<< "     POINT: " << point.transpose() << "\n"
+					<< "DERIVATIVE: " << first_derivative.transpose() << "\n"
+					<< "      STEP: " << step.transpose() << "\n"
+					<< " CONVERGED: " << ( converged ? "yes" : "no" ) << "\n" ;
+			} ;
+		}
+
+		// To compute the BF we need the null model.
+		// The null model does not depend on the SNPs, but might depend on the missing samples.
+		// We cache the value for speed if the nonmissing samples don't change.
+		std::vector< std::string > comments ;
+		// null_ll will be log-marginal likelihood of null model
+		// i.e. logarithm of prior x likelihood, integrated over parameters.
+		double null_ll = 0.0 ;
+		Eigen::VectorXd null_parameters ;
+		{
+			NullLLStore::const_iterator where = null_ll_store.find( nonmissing_samples ) ;
+			if( where == null_ll_store.end() ) {
+				if( debug ) {
+					this->ui().logger() << "---> fitting NULL...\n" ;
+				}
+				ll.design().set_predictors( Eigen::MatrixXd::Zero( store.number_of_samples(), 10 ), nonmissing_samples ) ;
+				LogUnnormalisedPosterior posterior( ll, null_prior ) ;
+				metro::CholeskyStepper stopping_condition( 0.01, 100, tracer ) ;
+				std::pair< bool, int > fit = metro::fit_model(
+					posterior,
+					"null",
+					Eigen::VectorXd::Zero( ll.identify_parameters().rows() ),
+					stopping_condition,
+					&comments
+				) ;
+					
+				null_ll = laplace_approximate( posterior ) ;
+				null_parameters = posterior.parameters() ;
+				//null_ll = posterior.get_value_of_function() ;
+				where = null_ll_store.insert(
+					NullLLStore::value_type(
+						nonmissing_samples,
+						NullLLStore::mapped_type(
+							ll.parameters(),
+							null_ll
+						)
+					)
+				).first ;
+			} else {
+				null_parameters = where->second.first ;
+				null_ll = where->second.second ;
+			}
+		}
+
+		ll.design().set_predictors( predictors, nonmissing_samples ) ;
+		LogUnnormalisedPosterior posterior( ll, prior ) ;
+
+		double posterior_weight = minus_infinity ;
+		double result = minus_infinity ;
+
+		if( log_weight > minus_infinity ) {
+			if( debug ) {
+				this->ui().logger() << "---> fitting full...\n" ;
+			}
+			metro::CholeskyStepper stopping_condition( 0.01, 100, tracer ) ;
+			std::pair< bool, int > fit = metro::fit_model(
+				posterior,
+				"full",
+				null_parameters,
+				stopping_condition,
+				&comments
+			) ;
+			if( fit.first ) {
+				result = laplace_approximate( posterior ) - null_ll + log_weight ;
+				//result = posterior.get_value_of_function() - null_ll + log_weight ;
+			}
+
+#if DEBUG
+			std::cerr << print_state( store.number_of_variants(), pick ) << ".\n" ;
+			//std::cerr << nonmissing_samples << ".\n" ;
+			// std::cerr << "PREDICTORS:\n" << predictors.block( 0, 0, 10, predictors.cols() ) << ".\n" ;
+			std::cerr << posterior.get_summary() << "\n" ;
+			std::cerr << "  INCLUDED: " << posterior.ll().design().nonmissing_samples() << "\n" ;
+			std::cerr << " CONVERGED: " << (fit.first ? "1" : "0") << "\n" ;
+			std::cerr << "        LL: " << posterior.get_value_of_function() << "\n" ;
+			std::cerr << "      NULL: " << null_ll << "\n" ;
+			std::cerr << " pick.size: " << pick.size() << "\n" ;
+			std::cerr << "LOG WEIGHT: " << log_weight << "\n" ;
+			std::cerr << "    RESULT: " << result << "\n" ;
+		
+			std::cerr << "\n+++++++++++++++++++++++++\n" ;
+#endif		
+		}
+		
+		return result ;
+	}
+	
+	// Compute laplace approximation.
+	// It is assumed that the function has already been maximised.
+	double laplace_approximate( metro::SmoothFunction const& function ) const {
+		double const fx = function.get_value_of_function() ;
+		metro::SmoothFunction::Matrix const& H = function.get_value_of_second_derivative() ;
+		double const log_2pi = std::log( 2.0 * 3.1415926535897932384626 ) ;
+		Eigen::ColPivHouseholderQR< metro::SmoothFunction::Matrix > solver( -H ) ;
+		return
+			fx + 0.5 * ( function.number_of_parameters() * log_2pi - solver.logAbsDeterminant() ) ;
+	}
+
+	void run_search( DosageStore& store, metro::regression::LogLikelihood& ll ) {
+		// Do a test search for now
+		NullLLStore null_ll_store ;
+
+		ui().logger() << "Running shotgun stochastic search...\n" ;
+
+		metro::ShotgunStochasticSearch ss(
+			store.number_of_variants(),
+			[this, &store, &ll, &null_ll_store]( metro::ShotgunStochasticSearch::SelectedStates const& s ) {
+				return this->test_variant( s, store, ll, null_ll_store ) ;
+			},
+			static_cast<std::uint32_t>(std::time(0))
+		) ;
+
+		for( std::size_t i = 0; i < 100; ++i ) {
+			boost::timer::cpu_timer timer ;
+			metro::ShotgunStochasticSearch::SelectedStates const& pick = ss.update() ;
+			
+			ui().logger() << "Iteration " << i << ": "
+				<< "took " << boost::timer::format( timer.elapsed(), 2, "%ts" )
+				<< ", state is: " << print_state( store.number_of_variants(), pick )
+				<< "\n" ;
+		}
+
+		ui().logger() << "Outputting search results...\n" ;
+		output_search_results( ss, store ) ;
+
+		ui().logger() << "Fine-mapping complete.\n" ;
+	}
+	
+	void output_search_results(
+		metro::ShotgunStochasticSearch const& ss,
+		DosageStore const& store
+	) {
+		qcdb::MultiVariantStorage::UniquePtr outputter
+			= qcdb::MultiVariantStorage::create(
+				options().get< std::string >( "-o" ),
+				5,
+				options().get< std::string >( "-analysis-name" ),
+				options().get< std::string >( "-analysis-chunk" ),
+				get_application_metadata()
+		) ;
+		outputter->add_variable( "loglikelihood" ) ;
+		outputter->add_variable( "logposterior" ) ;
+		outputter->add_variable( "posterior" ) ;
+
+		std::vector< genfile::VariantIdentifyingData > variants ;
+
+		auto comparator = []( double a, double b ) { return a > b ; } ;
+		typedef std::multimap< double, metro::ShotgunStochasticSearch::SelectedStates, decltype(comparator) > OrderedStates ;
+		OrderedStates ordered_states( comparator ) ;
+		std::vector< double > posterior_weights ;
+		ss.visited_states(
+			[&ordered_states, &posterior_weights](
+				metro::ShotgunStochasticSearch::SelectedStates const& states,
+				double value
+			) {
+				std::cerr << "GOT: " << states.size() << ", " << value << "\n" ;
+				ordered_states.insert( std::make_pair( value, states )) ;
+				posterior_weights.push_back( value ) ;
+			}
+		) ;
+
+		double const total_log_weight = metro::log_sum_exp( posterior_weights ) ;
+		ui().logger() << "TOTAL LOG WEIGHT:" << total_log_weight << "\n" ;
+		int count = 0 ;
+		for( OrderedStates::const_iterator i = ordered_states.begin(); i != ordered_states.end(); ++i, ++count ) {
+			metro::ShotgunStochasticSearch::SelectedStates const& states = i->second ;
+			variants.resize( states.size() ) ;
+			for( std::size_t i = 0; i < states.size(); ++i ) {
+				variants[i] = store.variant( states[i] ) ;
+			}
+			outputter->store_data_for_key(
+				variants,
+				"rank",
+				count
+			) ;
+			outputter->store_data_for_key(
+				variants,
+				"loglikelihood",
+				i->first
+			) ;
+			outputter->store_data_for_key(
+				variants,
+				"logposterior",
+				i->first - total_log_weight
+			) ;
+			outputter->store_data_for_key(
+				variants,
+				"posterior",
+				std::exp( i->first - total_log_weight )
+			) ;
+		}
+		outputter->finalise() ;
+	}
+
+#if 0
+	void create_query( genfile::bgen::Query* query ) {
+		if( options().check( "-incl-range" )) {
+			auto const elts = options().get_values< std::string >( "-incl-range" ) ;
+			for( std::string const& elt: elts ) {
+				query->include_range( parse_range( elt )) ;
+			}
+		}
+		if( options().check( "-excl-range" )) {
+			auto const elts = options().get_values< std::string >( "-excl-range" ) ;
+			for( std::string const& elt: elts ) {
+				query->exclude_range( parse_range( elt )) ;
+			}
+		}
+		if( options().check( "-incl-rsids" )) {
+			auto const ids = options().get_values< std::string >( "-incl-rsids" ) ;
+			query->include_rsids( ids ) ;
+		}
+
+		if( options().check( "-excl-rsids" )) {
+			auto const ids = options().get_values< std::string >( "-excl-rsids" ) ;
+			query->exclude_rsids( ids ) ;
+		}
+	}
+	
+	genfile::bgen::IndexQuery::GenomicRange parse_range( std::string const& spec ) const {
+		std::size_t colon_pos = spec.find( ':' ) ;
+		if ( colon_pos == std::string::npos ) {
+			throw std::invalid_argument( "spec=\"" + spec + "\"" ) ;
+		}
+
+		std::vector< std::string > pieces ;
+		pieces.push_back( spec.substr( 0, colon_pos )) ;
+		pieces.push_back( spec.substr( colon_pos+1, spec.size() )) ;
+
+		if( pieces.size() != 2 ) {
+			throw std::invalid_argument( "spec=\"" + spec + "\"" ) ;
+		}
+
+		std::size_t separator_pos = pieces[1].find( '-' ) ;
+		if ( separator_pos == std::string::npos ) {
+			throw std::invalid_argument( "spec=\"" + spec + "\"" ) ;
+		}
+
+		std::string chromosome( pieces[0] ) ;
+		int pos1 = (separator_pos == 0) ? 0 : std::stoi( pieces[1].substr( 0, separator_pos ) ) ;
+		int pos2 = (separator_pos == (pieces[1].size()-1)) ? std::numeric_limits< int >::max() : std::stoi( pieces[1].substr( separator_pos + 1, pieces[1].size() ) ) ;
+		assert( pos1 >= 0 ) ;
+		assert( pos2 >= pos1 ) ;
+
+		return genfile::bgen::IndexQuery::GenomicRange( chromosome, pos1, pos2 ) ;
+	}
+#endif
+} ;
+
+int main( int argc, char** argv ) {
+	try {
+		MFMApplication app( argc, argv ) ;
+	}
+	catch( appcontext::HaltProgramWithReturnCode const& e ) {
+		return e.return_code() ;
+	}
+	return 0 ;
+}
+

DELETED apps/overrep.cpp
Index: apps/overrep.cpp
==================================================================
--- apps/overrep.cpp
+++ apps/overrep.cpp
@@ -1,586 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <string>
-#include <memory>
-#include <set>
-#include <map>
-#include <utility>
-#include <boost/bind.hpp>
-#include <boost/function.hpp>
-#include <boost/foreach.hpp>
-#define foreach BOOST_FOREACH
-#include <boost/regex.hpp>
-#include <boost/math/distributions/hypergeometric.hpp>
-#include "appcontext/CmdLineOptionProcessor.hpp"
-#include "appcontext/ApplicationContext.hpp"
-#include "appcontext/ProgramFlow.hpp"
-#include "appcontext/get_current_time_as_string.hpp"
-#include "genfile/FileUtils.hpp"
-#include "genfile/utility.hpp"
-#include "statfile/BuiltInTypeStatSource.hpp"
-#include <Eigen/Core>
-
-namespace globals {
-	std::string const program_name = "overrep" ;
-	std::string const program_version = "0.1" ;
-}
-
-struct OverrepOptions: public appcontext::CmdLineOptionProcessor {
-	std::string get_program_name() const { return globals::program_name ; }
-
-	void declare_options( appcontext::OptionProcessor& options ) {
-		options.set_help_option( "-help" ) ;
-
-		options.declare_group( "File handling options" ) ;
-		options[ "-p" ]
-			.set_description( "Specify the path of a file containing pathway definitions to load."
-			 	" This file must have at least three columns; the first should be an identifier for the pathway (no whitespace),"
-				" the second should be the pathway name, and the third should contain gene identifiers." )
-			.set_takes_values_until_next_option()
-			.set_minimum_multiplicity( 1 )
-			.set_maximum_multiplicity( 100 )
-		;
-
-		options[ "-c" ]
-			.set_description( "Specify the path of a file containing gene clusters to load." )
-			.set_takes_single_value()
-		;
-
-		options[ "-u" ]
-			.set_description( "Specify the path of a file containing a list of genes to treat as the gene \"universe\"." )
-			.set_takes_single_value()
-			.set_is_required()
-		;
-
-		options[ "-g" ]
-			.set_description( "Specify the path of a file containing a list of genes to test with." )
-			.set_takes_single_value()
-		;
-
-		options.declare_group( "Miscellaneous options" ) ;
-		options[ "-P-value" ]
-			.set_description( "Output lists of genes for all pathways getting this P-value or better." )
-			.set_takes_single_value()
-			.set_default_value( 0.000001 )
-		;
-		options[ "-analysis-name" ]
-			.set_description( "Specify a name to label results from this analysis with.  (This applies to modules which store their results in a qcdb file.)" )
-			.set_takes_single_value()
-			.set_is_required() ;
-
-		options[ "-intersect" ]
-			.set_description( "Specify that the universe should only include genes that actuall occur in pathways." ) ;
-
-		options[ "-log" ]
-			.set_description( "Specify the path of the log file." )
-			.set_takes_single_value()
-			.set_default_value( "overrep.log" ) ;
-	}
-} ;
-
-// Fisher's exact test between categories
-//               red           black
-//     good |     a      |       b        |
-//      bad |     c      |       d        |
-//
-// Under the null that both rows are distributed the same, a is hypergeometrically
-// distributed.  Fishers' p-value is then the mass under the hypergeometric distribution
-// of all values of a greater than or equal to the one given that are consistent with
-// the given margins of the table.
-struct FishersExactTest {
-	FishersExactTest( Eigen::Matrix2d const& matrix ):
-		m_matrix( matrix ),
-		m_distribution( m_matrix.col( 0 ).sum(), m_matrix.row( 0 ).sum(), m_matrix.sum() )
-	{}
-	
-	double get_OR() const {
-		return ( m_matrix(0,0) * m_matrix(1,1) ) / ( m_matrix(0,1)*m_matrix(1,0) ) ;
-	}
-
-	std::pair< double, double > get_confidence_interval() const {
-		assert(0) ;
-	}
-
-	double get_pvalue() const {
-		using boost::math::cdf ;
-		using boost::math::complement ;
-
-		if( m_matrix(0,0) == 0 ) {
-			return 1 ;
-		} else {
-			return cdf( complement( m_distribution, m_matrix( 0, 0 ) - 1.0 )) ;
-		}
-	}
-
-	private:
-		Eigen::Matrix2d const m_matrix ;
-		boost::math::hypergeometric m_distribution ;
-} ;
-
-void load_list_of_strings( std::string const& filename, boost::function< void ( std::string const& ) > setter ) {
-	std::auto_ptr< std::istream > f = genfile::open_text_file_for_input( filename ) ;
-	std::string element ;
-	while( (*f) >> element ) {
-		setter( element ) ;
-	}
-}
-
-void load_pathways_list(
-	statfile::BuiltInTypeStatSource& source,
-	boost::function< void ( std::string const&, std::string const& ) > set_pathway_name,
-	boost::function< void ( std::string const&, std::string const& ) > set_pathway_gene
-) {
-	std::string pathway_id ;
-	std::string pathway_name ;
-	std::string gene_id ;
-	while( source >> pathway_id ) {
-		source >> pathway_name >> gene_id >> statfile::ignore_all() ;
-		set_pathway_name( pathway_id, pathway_name ) ;
-		set_pathway_gene( pathway_id, gene_id ) ;
-	}
-}
-
-void load_clusters(
-	statfile::BuiltInTypeStatSource& source,
-	boost::function< void ( std::string const&, std::string const& ) > set_cluster_member = boost::function< void ( std::string const&, std::string const& ) >(),
-	boost::function< void ( std::string const&, std::string const& ) > set_cluster_comment = boost::function< void ( std::string const&, std::string const& ) >()
-) {
-	std::string cluster_id ;
-	std::string cluster_comment ;
-	std::string gene_regexp ;
-	while( source >> cluster_id ) {
-		source >> gene_regexp >> cluster_comment >> statfile::ignore_all() ;
-		if( set_cluster_comment ) {
-			set_cluster_comment( cluster_id, cluster_comment ) ;
-		}
-		if( set_cluster_member ) {
-			set_cluster_member( cluster_id, gene_regexp ) ;
-		}
-	}
-}
-
-namespace impl {
-	struct MapSetter {
-		typedef std::string A ;
-		typedef std::string B ;
-		typedef std::map< A, B > Map ;
-		MapSetter( Map& map ): m_map( &map ) {} ;
-		MapSetter( MapSetter const& other ): m_map( other.m_map ) {} ;
-		MapSetter& operator=( MapSetter const& other ) {
-			m_map = other.m_map ;
-			return *this ;
-		} 
-		
-		void operator()( std::string const& left, std::string const& right ) const {
-			(*m_map)[ left ] = right ;
-		}
-		
-	private:
-		Map* m_map ;
-	} ;
-	
-	struct MapSetSetter {
-		typedef std::string A ;
-		typedef std::set< std::string > B ;
-		typedef std::map< A, B > Map ;
-		MapSetSetter( Map& map ): m_map( &map ) {} ;
-		MapSetSetter( MapSetSetter const& other ): m_map( other.m_map ) {} ;
-		MapSetSetter& operator=( MapSetSetter const& other ) {
-			m_map = other.m_map ;
-			return *this ;
-		} 
-		
-		void operator()( std::string const& left, std::string const& right ) const {
-			(*m_map)[ left ].insert( right ) ;
-		}
-		
-	private:
-		mutable Map* m_map ;
-	} ;
-	
-	template< typename Container >
-	void insert_into( typename Container::value_type const& value, Container* X ) {
-		X->insert( value ) ;
-	}
-	
-	template< typename Container >
-	bool in( typename Container::value_type const& value, Container const& X ) {
-		return X.find( value ) != X.end() ;
-	}
-}
-
-struct OverrepApplication: public appcontext::ApplicationContext {
-public:
-	OverrepApplication( int argc, char **argv ):
-		appcontext::ApplicationContext(
-			globals::program_name,
-			globals::program_version,
-			std::auto_ptr< appcontext::OptionProcessor >( new OverrepOptions ),
-			argc,
-			argv,
-			"-log"
-		)
-	{}
-	
-	void process() {
-		unsafe_process() ;
-	}
-	
-private:
-	typedef std::set< std::string > StringSet ;
-	typedef std::map< std::string, std::string > StringStringMap ;
-	typedef std::map< std::string, std::set< std::string > > StringStringSetMap ;
-
-	void unsafe_process() {
-		load_data() ;
-		m_cluster_mapping = get_cluster_mapping() ;
-		map_genes_through_clusters( m_cluster_mapping ) ;
-
-		summarise() ;
-		
-		run_tests() ;
-	}
-
-	void load_data() {
-		StringStringMap pathway_names ;
-		StringStringSetMap pathway_members ;
-		StringStringSetMap clusters ;
-		StringStringMap cluster_descriptions ;
-		StringSet universe ;
-		StringSet test_genes ;
-		
-	
-		assert( options().check( "-u" ) ) ;	
-		if( options().check( "-u" )) {
-			load_list_of_strings(
-				options().get< std::string >( "-u" ),
-				boost::bind(
-					&impl::insert_into< StringSet >,
-					_1,
-					&universe
-				)
-			) ;
-
-			get_ui_context().logger()
-				<< "I loaded " << universe.size() << " universe genes.  First few are:\n" ;
-			StringSet::const_iterator
-				i = universe.begin(),
-				end_i = universe.end() ;
-			for( std::size_t count = 0; count < 5 && i != end_i; ++count, ++i ) {
-				get_ui_context().logger() << "  " << *i << "\n" ;
-			}
-		}
-		
-		if( options().check( "-c" )) {
-			statfile::BuiltInTypeStatSource::UniquePtr source = statfile::BuiltInTypeStatSource::open(
-				options().get< std::string >( "-c" )
-			) ;
-			load_clusters(
-				*source,
-				impl::MapSetSetter( clusters ),
-				impl::MapSetter( cluster_descriptions )
-			) ;
-			get_ui_context().logger() << "Loaded " << clusters.size() << " clusters:\n" ;
-			foreach( StringStringSetMap::value_type const& elt, clusters ) {
-				get_ui_context().logger()
-					<< "  " << elt.first << ": " ;
-				foreach( StringSet::value_type const& value, elt.second ) {
-					get_ui_context().logger() << value << " " ;
-				}
-				get_ui_context().logger() << "\n" ;
-			}
-		}
-
-		if( options().check( "-p" )) {
-			std::vector< std::string > elts = options().get_values< std::string >( "-p" ) ;
-			foreach( std::string const& elt, elts ) {
-				statfile::BuiltInTypeStatSource::UniquePtr source = statfile::BuiltInTypeStatSource::open(
-					genfile::wildcard::find_files_by_chromosome( elt )
-				) ;
-				load_pathways_list(
-					*source,
-					impl::MapSetter( pathway_names ),
-					impl::MapSetSetter( pathway_members )
-				) ;
-			}
-
-			typedef std::pair< std::string, std::set< std::string > > StringStringSet ;
-			if( options().check( "-intersect" )) {
-				StringSet pathway_universe ;
-				foreach( StringStringSet const& entry, pathway_members ) {
-					pathway_universe.insert( entry.second.begin(), entry.second.end() ) ;
-				}
-				get_ui_context().logger() << "Created pathway universe of " << universe.size() << " genes based on all genes in pathways.\n" ;
-				std::size_t const N = universe.size() ;
-				universe = genfile::utility::intersect( universe, pathway_universe ) ;
-				get_ui_context().logger() << "Formed intersection with universe (" << universe.size() << " of " << N << " in original universe.\n" ;
-				
-			}
-
-			std::map< std::string, StringSet > universe_pathway_members ;
-			foreach( StringStringSet const& entry, pathway_members ) {
-				universe_pathway_members[ entry.first ] = genfile::utility::intersect( entry.second, universe ) ;
-			}
-			
-			get_ui_context().logger()
-				<< "I loaded " << pathway_names.size() << " pathways.  First few are:\n" ;
-			std::map< std::string, std::string >::const_iterator
-				pathway_i = pathway_names.begin(),
-				pathway_end = pathway_names.end() ;
-			for( std::size_t count = 0; count < 5 && pathway_i != pathway_end; ++count, ++pathway_i ) {
-				get_ui_context().logger() << "  " << pathway_i->first << ": " << pathway_i->second
-					<< " (" << pathway_members[pathway_i->first].size()
-					<< " genes of which "
-					<< universe_pathway_members[pathway_i->first].size()
-					<<" are in the universe)\n" ;
-			}
-			
-			pathway_members = universe_pathway_members ;
-		}
-		
-		if( options().check( "-g" )) {
-			load_list_of_strings(
-				options().get< std::string >( "-g" ),
-				boost::bind(
-					impl::insert_into< StringSet >,
-					_1,
-					&test_genes
-				)
-			) ;
-			
-			get_ui_context().logger()
-				<< "I loaded " << test_genes.size() << " test genes " ;
-			test_genes = genfile::utility::intersect( test_genes, universe ) ;
-			get_ui_context().logger()
-				<< "of which " << test_genes.size() << " are in the universe.  First few are:\n" ;
-			StringSet::const_iterator
-				i = test_genes.begin(),
-				end_i = test_genes.end() ;
-			for( std::size_t count = 0; count < 5 && i != end_i; ++count, ++i ) {
-				get_ui_context().logger() << "  " << *i << "\n" ;
-			}
-		}
-		
-		m_pathway_names = pathway_names ;
-		m_pathway_members = pathway_members ;
-		m_clusters = clusters ;
-		m_cluster_descriptions = cluster_descriptions ;
-		m_universe = universe ;
-		m_test_genes = test_genes ;
-	}
-	
-	StringStringMap get_cluster_mapping() {
-		get_ui_context().logger() << "Computing gene->cluster mapping...\n" ;
-		StringStringMap result ;
-		foreach( StringStringSetMap::value_type const& cluster, m_clusters ) {
-			foreach( std::string const& regex_string, cluster.second ) {
-				boost::regex regex( regex_string ) ;
-				StringStringMap const& this_map = get_cluster_mapping( regex, cluster.first ) ;
-				result.insert( this_map.begin(), this_map.end() ) ;
-			}
-		}
-		
-		return result ;
-	}
-	
-	StringStringMap get_cluster_mapping( boost::regex const& regex, std::string const& replacement ) {
-		StringStringMap result ;
-		get_cluster_mapping( m_universe, regex, replacement, boost::bind( impl::insert_into< StringStringMap >, _1, &result )) ;
-		get_cluster_mapping( m_test_genes, regex, replacement, boost::bind( impl::insert_into< StringStringMap >, _1, &result )) ;
-		foreach( StringStringSetMap::value_type& value, m_pathway_members ) {
-			get_cluster_mapping( value.second, regex, replacement, boost::bind( impl::insert_into< StringStringMap >, _1, &result )) ;
-		}
-		return result ;
-	}
-
-	
-	void get_cluster_mapping(
-		StringSet& values,
-		boost::regex const& regex,
-		std::string const& replacement,
-		boost::function< void ( std::pair< std::string, std::string > const& ) > output
-	) {
-		StringSet::iterator i = values.begin(), end_i = values.end() ;
-		for( ; i != end_i; ++i ) {
-			std::string value = *i ;
-			value = boost::regex_replace( value, regex, replacement ) ;
-			if( value != *i ) {
-				output( std::make_pair( *i, value ) ) ;
-			}
-		}
-	}
-
-	void map_genes_through_clusters( StringStringMap const& mapping ) {
-		get_ui_context().logger() << "Mapping genes through clusters...\n" ;
-		std::size_t n = m_universe.size() ;
-		m_universe = map_genes_through_clusters( mapping, m_universe ) ;
-		get_ui_context().logger() << "Mapped " << n << " genes to " << m_universe.size() << " in universe.\n" ;
-		n = m_test_genes.size() ;
-		m_test_genes = map_genes_through_clusters( mapping, m_test_genes ) ;
-		get_ui_context().logger() << "Mapped " << n << " genes to " << m_test_genes.size() << " in test genes.\n" ;
-		foreach( StringStringSetMap::value_type& value, m_pathway_members ) {
-			value.second = map_genes_through_clusters( mapping, value.second ) ;
-		}
-	}
-
-	StringSet map_genes_through_clusters( StringStringMap const& mapping, StringSet const& genes ) {
-		StringSet result ;
-		foreach( StringSet::value_type const& value, genes ) {
-			StringStringMap::const_iterator where = mapping.find( value ) ;
-			if( where != mapping.end() ) {
-				result.insert( where->second ) ;
-			} else {
-				result.insert( value ) ;
-			}
-        }
-		return result ;
-	}
-
-	void summarise() {
-		get_ui_context().logger() << "\n-------------------------\n\n" ;
-		if( m_clusters.size() > 0 ) {
-			get_ui_context().logger() << std::setw( 12 ) << "Cluster mapping:\n" ;
-            StringStringSetMap backMap ;
-			foreach( StringStringMap::value_type const& key_value, m_cluster_mapping ) {
-                backMap[ key_value.second ].insert( key_value.first ) ;
-			}
-            foreach( StringStringSetMap::value_type const& k, backMap ) {
-                get_ui_context().logger() << std::setw( 12 ) << k.first << ":" ;
-				std::size_t count = 0 ;
-				for( StringSet::const_iterator i = k.second.begin(); i != k.second.end(); ++i, ++count ) {
-                    get_ui_context().logger() << " " << *i ;
-					if( count == 10 ) {
-						get_ui_context().logger() << " (+ " << k.second.size() - 10 << " others)..." ;
-						break ;
-					}
-                }
-                get_ui_context().logger() << "\n" ;
-            }
-		}
-#if 0
-		if( m_clusters.size() > 0 ) {
-			get_ui_context().logger() << std::setw( 12 ) << "Cluster mapping:\n" ;
-			foreach( StringStringMap::value_type const& key_value, m_cluster_mapping ) {
-				get_ui_context().logger() << std::setw( 12 ) << key_value.first << ": "  << key_value.second << "\n" ;
-			}
-		}
-#endif
-		get_ui_context().logger() << std::setw( 12 ) << "Test genes:" << "  " << m_test_genes.size() << " genes\n" ;
-		get_ui_context().logger() << std::setw( 12 ) << "Pathways:" << "  " << m_pathway_names.size() << " pathways\n" ;
-		get_ui_context().logger() << std::setw( 12 ) << "Universe:" << "  " << m_universe.size() << " genes\n" ;
-	}
-
-	void run_tests() {
-		// table is
-		//                 in pathway | not in pathway |  
-		//     test gene |     a      |       b        |
-		// Not test gene |     c      |       d        |
-		//
-		Eigen::Matrix2d table ;
-		
-		using std::setw ;
-		std::string const tab = "\t" ;
-		std::cout
-		//get_ui_context().logger()
-			<< "analysis" << tab
-			<< "pathway id" << tab
-			<< "pathway name" << tab
-			<< "hits in pathway" << tab
-			<< "hits not in pathway" << tab
-			<< "nonhits in pathway" << tab
-			<< "nonhits not in pathway" << tab
-			<< "total in pathway" << tab
-			<< "total genes" << tab
-			<< "sample odds ratio" << tab
-			<< "fishers exact test p value" << tab
-			<< "ids.of.hits.in.pathway"
-			<< "\n" ;
-
-		std::string const analysis = options().get< std::string >( "-analysis-name" ) ;
-		double const pvalue_threshhold = options().get< double >( "-P-value" ) ;
-		std::ostringstream hit_genes_in_pathway ;
-		foreach( StringStringSetMap::value_type const& pathway, m_pathway_members ) {
-			hit_genes_in_pathway.str( "" ) ;
-			table = Eigen::Matrix2d::Zero() ;
-
-			foreach( std::string const& value, m_universe ) {
-				int i = 0, j = 0 ;
-				if( impl::in( value, m_test_genes )) {
-					i = 0 ;
-				} else {
-					i = 1 ;
-				}
-
-				if( impl::in( value, pathway.second ) ) {
-					j = 0 ;
-				} else {
-					j = 1 ;
-				}
-				
-				++table( i, j ) ;
-
-				if( i == 0 && j == 0 ) {
-					if( hit_genes_in_pathway.str().size() == 0 ) {
-						hit_genes_in_pathway << value ;
-					}
-					else {
-						hit_genes_in_pathway << "," << value ;
-					}
-				}
-			}
-
-			//get_ui_context().logger()
-			std::cout
-				<< analysis << tab	
-				<< pathway.first << tab
-				<< "\"" << m_pathway_names[ pathway.first ] << "\"" << tab
-				<< table( 0, 0 ) << tab
-				<< table( 0, 1 ) << tab
-				<< table( 1, 0 ) << tab
-				<< table( 1, 1 ) << tab
-				<< table.col( 0 ).sum() << tab
-				<< table.sum() << tab ;
-			try {
-				FishersExactTest test( table ) ;
-				//get_ui_context().logger()
-				std::cout
-					<< test.get_OR() << tab << test.get_pvalue() ;
-				if( test.get_pvalue() <= pvalue_threshhold ) {
-					std::cout << tab << hit_genes_in_pathway.str() ;
-				} else {
-					std::cout << tab << "NA" ;
-				}
-			}
-			catch( std::exception const& ) {
-				// get_ui_context().logger()
-				std::cout
-					<< "NA\tNA\t" ;	
-			}
-			std::cout << "\n" ;
-		}
-	}
-	
-private:
-	StringStringMap m_pathway_names ;
-	StringStringSetMap m_pathway_members ;
-	StringStringSetMap m_clusters ;
-	StringStringMap m_cluster_descriptions ;
-	StringStringMap m_cluster_mapping ;
-	StringSet m_universe ;
-	StringSet m_test_genes ;
-} ;
-
-int main( int argc, char **argv ) {
-	try {
-		OverrepApplication app( argc, argv ) ;	
-		app.process() ;
-	}
-	catch( appcontext::HaltProgramWithReturnCode const& e ) {
-		return e.return_code() ;
-	}
-	return 0 ;
-}

Index: apps/qctool.cpp
==================================================================
--- apps/qctool.cpp
+++ apps/qctool.cpp
@@ -28,17 +28,13 @@
 #include <boost/filesystem.hpp>
 #include <boost/uuid/uuid.hpp>
 #include <boost/uuid/random_generator.hpp>
 #include <boost/uuid/uuid_io.hpp>
 
-#include "appcontext/CmdLineOptionProcessor.hpp"
-#include "appcontext/OptionProcessor.hpp"
-#include "appcontext/get_current_time_as_string.hpp"
-//#include "FileUtil.hpp"
+#include "appcontext/appcontext.hpp"
 
-#include "db/Error.hpp"
-
+#include "genfile/db/Error.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "genfile/SNPDataSourceChain.hpp"
 #include "genfile/SNPDataSourceRack.hpp"
 #include "genfile/MergingSNPDataSource.hpp"
 #include "genfile/SampleMappingSNPDataSource.hpp"
@@ -60,11 +56,11 @@
 #include "genfile/PloidyConvertingSNPDataSource.hpp"
 #include "genfile/CommonSNPFilter.hpp"
 #include "genfile/SNPFilteringSNPDataSource.hpp"
 #include "genfile/ReorderingSNPDataSource.hpp"
 #include "genfile/ReorderingCohortIndividualSource.hpp"
-#include "genfile/SNPIdentifyingDataFilteringSNPDataSource.hpp"
+#include "genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp"
 #include "genfile/utility.hpp"
 #include "genfile/QuantileNormalisingCrossCohortCovariateValueMapping.hpp"
 #include "genfile/ValueMappingCohortIndividualSource.hpp"
 #include "genfile/vcf/StrictMetadataParser.hpp"
 #include "genfile/WithSNPDosagesCohortIndividualSource.hpp"
@@ -82,16 +78,13 @@
 #include "statfile/SNPDataSourceAdapter.hpp"
 
 #include "qcdb/FlatFileOutputter.hpp"
 #include "qcdb/FlatTableDBOutputter.hpp"
 
-#include "appcontext/appcontext.hpp"
-
 #include "worker/QueuedMultiThreadedWorker.hpp"
 #include "worker/SynchronousWorker.hpp"
 
-#include "FileBackupCreator.hpp"
 #include "InputToOutputFilenameMapper.hpp"
 #include "SNPIDSink.hpp"
 #include "statfile/BuiltInTypeStatSink.hpp"
 #include "DataReadTest.hpp"
 #include "components/RelatednessComponent/RelatednessComponent.hpp"
@@ -102,23 +95,33 @@
 #include "components/SNPOutputComponent/SQLiteGenotypesSNPDataSink.hpp"
 #include "components/SampleSummaryComponent/SampleSummaryComponent.hpp"
 #include "components/SampleSummaryComponent/FlatTableDBOutputter.hpp"
 #include "components/SampleSummaryComponent/FlatFileOutputter.hpp"
 
-#include "config/qctool_version_autogenerated.hpp"
+#include "config/package_revision_autogenerated.hpp"
 
 namespace globals {
 	std::string const program_name = "qctool" ;
-	std::string const program_version = qctool_version ;
-	std::string const program_revision =  std::string( qctool_revision ).substr( 0, 7 ) ;
+	std::string const program_version = package_version ;
+	std::string const program_revision =  std::string( package_revision ).substr( 0, 7 ) ;
 }
 
 namespace impl {
-	void set_vector_entry( std::vector< std::string >* vector, std::size_t i, std::string const& value ) {
+	void set_vector_entry( std::vector< genfile::VariantEntry >* vector, std::size_t i, std::string const& value ) {
+		assert( i < vector->size() ) ;
+		(*vector)[i] = value ;
+	}		
+
+	void set_vector_entry_string( std::vector< std::string >* vector, std::size_t i, std::string const& value ) {
 		assert( i < vector->size() ) ;
 		(*vector)[i] = value ;
 	}
+
+	void set_vector_entry_variant( std::vector< std::string >* vector, std::size_t i, genfile::VariantEntry const& value ) {
+		assert( i < vector->size() ) ;
+		(*vector)[i] = value.as< std::string >() ;
+	}
 }
 
 struct QCToolOptionProcessor: public appcontext::CmdLineOptionProcessor
 {
 public:
@@ -227,10 +230,12 @@
 			.set_description( "Specify whether haploid samples (e.g. males on the non-pseudoautosomal region of the X chromosome)"
 			" are coded as heterozygotes (\"het\") or homozygotes (\"hom\")." )
 			.set_takes_single_value()
 			.set_default_value( "hom" )
 		;
+		
+		options.option_implies_option( "-infer-ploidy-from", "-s" ) ;
 
 /*	    options[ "-i" ]
 	        .set_description( 	"Path of intensity file(s) to input.  "
 								"If specified, this option must occur the same number of times as the -g option, to specify"
 								" one intensity file per cohort."
@@ -310,21 +315,29 @@
 			.set_description( "Filter out snps whose rsid or SNPID does not match the given value. "
 				"The value should be a string which can contain a % wildcard character (which matches any substring). "
 				"Optionally, prefix the argument with snpid~ or rsid~ to only match against the SNPID or rsid fields." )
 			.set_takes_values_until_next_option() ;
 		options[ "-incl-range" ]
-			.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. "
+			.set_description( "Specify a range or ranges of SNPs to operate on. "
 				"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
 				"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
 				"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
 			.set_takes_values_until_next_option() ;
 		options[ "-excl-range" ]
-			.set_description( "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to exclude from operation. "
+			.set_description( "Specify a range or ranges of SNPs to exclude from operation. "
 				"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
 				"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
 				"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
 			.set_takes_values_until_next_option() ;
+		options[ "-incl-ranges" ]
+			.set_description( "Like -incl-range, but read the ranges from the specified file."
+				"The file must contain a whitespace-separated list of genomic ranges to include in the analysis." )
+			.set_takes_values_until_next_option() ;
+		options[ "-excl-ranges" ]
+			.set_description( "Like -excl-range, but read the ranges from the specified file."
+				"The file must contain a whitespace-separated list of genomic ranges to exclude from the analysis." )
+			.set_takes_values_until_next_option() ;
 
 		options.declare_group( "Options for adjusting SNPs" ) ;
 	    options[ "-strand" ]
 	        .set_description( 
 				"Path of strand file(s) to input.  "
@@ -447,10 +460,18 @@
 		;
 		options[ "-bgen-omit-sample-identifier-block" ]
 			.set_description( "For use when outputting BGEN files only.  Tell QCTOOL to omit the sample identifier block.  By default"
 				" this is written whenever -s is specified." )
 		;
+		
+		options.declare_group( "sqlite-specific options" ) ;
+		options[ "-sqlite-dont-link-variants" ]
+			.set_description( "Do not attempt to link to existing variants when outputting to a sqlite file. " )
+		;
+		options[ "-sqlite-store-alt-identifiers" ]
+			.set_description( "Store variant alternate identifiers. This adds information but can be slower." )
+		;
 
 		options.option_implies_option( "-sort", "-og" ) ;
 		options.option_implies_option( "-omit-chromosome", "-og" ) ;
 		options.option_implies_option( "-output-sample-format", "-os" ) ;
 
@@ -914,10 +935,11 @@
 		}
 	}
 	
 	void write_postamble() {
 		m_ui_context.logger() << std::string( 72, '=' ) << "\n\n" ;
+#if 0
 		if( m_backup_creator.backed_up_files().size() > 0 ) {
 			m_ui_context.logger() << std::setw(36) << "I took backups of the following files before overwriting:\n" ;
 			std::size_t max_length = 0u ;
 			for(
 				std::map< std::string, std::string >::const_iterator i = m_backup_creator.backed_up_files().begin() ;
@@ -936,11 +958,11 @@
 			}
 
 			m_ui_context.logger() << "\n" ;
 			m_ui_context.logger() << std::string( 72, '=' ) << "\n\n" ;
 		}
-
+#endif
 		m_ui_context.logger() << std::setw(36) << "Number of SNPs:\n"
 			<< std::setw(36) << " -- in input file(s):" ;
 		if( m_snp_data_source->total_number_of_snps() ) {
 			m_ui_context.logger() << "  " << *m_snp_data_source->total_number_of_snps() << ".\n" ;
 		}
@@ -1041,12 +1063,10 @@
 	mutable genfile::CommonSNPFilter::UniquePtr m_snp_filter ;
 	Eigen::MatrixXd m_sample_filter_diagnostic_matrix ;
 
 	std::vector< std::size_t > m_indices_of_filtered_out_samples ;
 	
-	ToNumberedFileBackupCreator m_backup_creator ;
-	
 	std::vector< std::string > m_warnings ;
 	std::vector< std::string > m_errors ;
 	
 private:
 	
@@ -1063,77 +1083,17 @@
 				m_options.get_values< std::string >( "-strand" ),
 				m_options.get< std::string >( "-compare-variants-by" )
 			) ;
 		}
 
-#if 1
 		open_data_sources(
 			m_mangled_options.gen_filenames(),
 			m_options.check( "-s" ) ? m_options.get_values< std::string >( "-s" ) : boost::optional< std::vector< std::string > >(),
 			m_options.check( "-merge-in" ) ? m_options.get_values< std::string >( "-merge-in" ) : boost::optional< std::vector< std::string > >(),
 			&m_snp_data_source,
 			&m_samples
 		) ;
-#else
-		m_snp_data_source = open_snp_data_sources(
-			m_mangled_options.gen_filenames(),
-			m_options.check( "-flip-to-match-cohort1" )
-		) ;
-	
-		if( !m_samples ) {
-			m_samples = create_dummy_samples( m_snp_data_source ) ;
-		}
-
-		if( m_samples->get_number_of_individuals() != m_snp_data_source->number_of_samples() ) {
-			throw genfile::MismatchError(
-				"QCToolCmdLineContext::unsafe_open_samples()",
-				m_samples->get_source_spec(),
-				"number of samples = " + genfile::string_utils::to_string( m_samples->get_number_of_individuals() ),
-				"expected number of samples = " + genfile::string_utils::to_string( m_snp_data_source->number_of_samples() )
-			) ;
-		}
-
-		if( m_options.check( "-merge-in" )) {
-			m_snp_data_source = open_merged_data_sources( m_options.get_values< std::string >( "-merge-in" ) ) ;
-		}
-
-		if( m_options.check( "-infer-ploidy-from" )) {
-			std::string const sex_column = m_options.get< std::string >( "-infer-ploidy-from" ) ;
-			std::vector< char > sexes( m_samples->size(), '.' ) ;
-			for( std::size_t i = 0; i < m_samples->size(); ++i ) {
-				genfile::VariantEntry const& entry = m_samples->get_entry( i, sex_column ) ;
-				if( !entry.is_missing() ) {
-					std::string const sex = genfile::string_utils::to_lower( entry.as< std::string >() ) ;
-					if( sex == "1" || sex == "m" || sex == "male" ) {
-						sexes[i] = 'm' ;
-					} else if( sex == "2" || sex == "f" || sex == "female" ) {
-						sexes[i] = 'f' ;
-					} else {
-						throw genfile::MalformedInputError(
-							m_samples->get_source_spec(),
-							"Malformed sex value \"" + sex + "\"",
-							i,
-							m_samples->get_column_spec().find_column( sex_column )
-						) ;
-					}
-				}
-			}
-		
-			m_snp_data_source.reset(
-				genfile::PloidyConvertingSNPDataSource::create(
-					m_snp_data_source,
-					boost::bind( &genfile::get_ploidy_from_sex, sexes, _1, _2 )
-				).release()
-			) ;
-		}
-
-		if( m_options.check( "-threshold" )) {
-			m_snp_data_source.reset(
-				new genfile::ThreshholdingSNPDataSource( m_snp_data_source, m_options.get< double >( "-threshold" ))
-			) ;
-		}
-#endif
 
 		if( m_options.check( "-sample-data" )) {
 			m_samples = open_sample_data( m_samples, m_options.get_values< std::string > ( "-sample-data" )) ;
 		}
 
@@ -1191,10 +1151,18 @@
 				for( std::size_t i = 0; i < m_samples->size(); ++i ) {
 					ids[i] = m_samples->get_entry( i, "ID_1" ).as< std::string >() ;
 				}
 			}
 			if( boost::filesystem::exists( order_type ) ) {
+				if( !m_options.check( "-s" ) && !m_snp_data_source->has_sample_ids() ) {
+					throw genfile::BadArgumentError(
+						"QCToolCmdLineContext::setup()",
+						"-reorder " + order_type,
+						"Cannot reorder samples because the input files do not contain sample IDs.  (Do you need to specify -s?)"
+					) ;
+				}
+				
 				// order type is a file specifying the order.
 				std::auto_ptr< std::istream > file = genfile::open_text_file_for_input( order_type ) ;
 				std::vector< std::string > id_order ;
 				std::copy( std::istream_iterator< std::string >( *file ), std::istream_iterator< std::string >(), std::back_inserter< std::vector< std::string > >( id_order )) ;
 				if( id_order.size() != ids.size() ) {
@@ -1383,11 +1351,11 @@
 						}
 						result->at(i)[ snp ] = StrandFlipSpec( strand[0], flip ) ;
 						(*source) >> statfile::ignore_all() ;
 					}
 				}
-				catch( genfile::InputError ) {
+				catch( genfile::InputError const& ) {
 					++summaries[i].second ; // failure count
 					(*source) >> statfile::ignore_all() ;
 					//throw ;
 				}
 			}
@@ -1440,12 +1408,17 @@
 			assert( sample_filenames->size() == gen_filenames.size() ) ;
 			samples = open_samples( *sample_filenames ) ;
 		}
 		snp_data_source = open_snp_data_sources( gen_filenames, m_options.check( "-flip-to-match-cohort1" ) ) ;
 
-		// Create a dummy sample file if none was provided
-		if( !samples.get() ) {
+		// From this point on we need a sample source.
+		// Either one was provided (in which case we check its IDs against the genotype file, if there are any)
+		// or none was provided (in which case we create an in-memory one.)
+		if( samples.get() && snp_data_source->has_sample_ids() ) {
+			check_sample_ids( *samples, *snp_data_source ) ;
+		} else if( !samples.get() ) {
+			// Create a dummy sample file if none was provided
 			samples = create_dummy_samples( *snp_data_source ) ;
 		}
 		
 		// Check Sample and snp data sources match.
 		if( samples->get_number_of_individuals() != snp_data_source->number_of_samples() ) {
@@ -1509,10 +1482,46 @@
 		
 		// Put results in output variables
 		*result_samples = samples ;
 		*result_snp_data_source = snp_data_source ;
 	}
+
+private:
+	
+	void check_sample_ids(
+		genfile::CohortIndividualSource const& samples,
+		genfile::SNPDataSource const& snp_data_source
+	) const {
+		// check sample identifiers agree
+		// if not, abort unless -force is specified
+		std::vector< std::string > sample_file_ids( samples.size() ) ;
+		std::vector< std::string > genotype_file_ids( snp_data_source.number_of_samples() ) ;
+		samples.get_column_values( "ID_1", boost::bind( &impl::set_vector_entry_variant, &sample_file_ids, _1, _2 )) ;
+		snp_data_source.get_sample_ids( boost::bind( &impl::set_vector_entry_string, &genotype_file_ids, _1, _2 )) ;
+		assert( sample_file_ids.size() == genotype_file_ids.size() ) ;
+		if( sample_file_ids != genotype_file_ids ) {
+			// find first mismatch for a useful error message
+			std::size_t k = 0 ;
+			for( ; k < sample_file_ids.size(); ++k ) {
+				if( sample_file_ids[k] != genotype_file_ids[k] ) {
+					break ;
+				}
+			}
+			m_ui_context.logger() << "!! Error: sample file and genotype file sample IDs do not match!\n" ;
+			m_ui_context.logger() << "!! First mismatch is at sample " << (k+1) << ": IDs are \"" << sample_file_ids[k] << "\" and \"" << genotype_file_ids[k] << "\".\n" ;
+			if( m_options.check( "-force" ) ) {
+				m_ui_context.logger() << "!! ...continuing anyway as -force was specified.\n" ;
+			} else {
+				throw genfile::MismatchError(
+					"QCToolCmdLineContext::check_sample_ids()",
+					genfile::string_utils::join( m_options.get_values< std::string >( "-s" ), "," ),
+					sample_file_ids[k],
+					genotype_file_ids[k]
+				) ;
+			}
+		}
+	}
 
 private:
 	genfile::SNPDataSource::UniquePtr open_snp_data_sources(
 		std::vector< std::vector< genfile::wildcard::FilenameMatch > > const& filenames,
 		bool match_alleles_between_cohorts
@@ -1869,171 +1878,201 @@
 			(*source) >> statfile::end_row() ;
 			progress_context( source->number_of_rows_read(), source->number_of_rows() ) ;
 		}
 		return result ;
 	}
-		
-	genfile::CommonSNPFilter* get_snp_filter() const {
-		if( !m_snp_filter.get() ) {
-			genfile::CommonSNPFilter::UniquePtr snp_filter ;
-
-			if( m_options.check_if_option_was_supplied_in_group( "SNP exclusion options" )) {
-				snp_filter.reset( new genfile::CommonSNPFilter ) ;
-
-				if( m_options.check_if_option_was_supplied( "-excl-variants" )) {
-					std::vector< std::string > files = m_options.get_values< std::string > ( "-excl-variants" ) ;
-				
-					BOOST_FOREACH( std::string const& filename, files ) {
-						genfile::SNPDataSource::UniquePtr source ;
-						try {
-							source.reset(
-								new statfile::SNPDataSourceAdapter(
-									statfile::BuiltInTypeStatSource::open(
-										genfile::wildcard::find_files_by_chromosome( filename )
-									)
-								)
-							) ;
-						} catch( genfile::InputError const& e ) {
-							source.reset(
-								genfile::SNPDataSourceChain::create(
-									genfile::wildcard::find_files_by_chromosome( filename )
-								).release()
-							) ;
-						}
-						snp_filter->exclude_snps(
-							source->list_snps(),
-							genfile::VariantIdentifyingData::CompareFields( m_options.get_value< std::string >( "-compare-variants-by" ) )
-						) ;
-					}
-				}
-
-				if( m_options.check_if_option_was_supplied( "-incl-variants" )) {
-					std::vector< std::string > files = m_options.get_values< std::string > ( "-incl-variants" ) ;
-					BOOST_FOREACH( std::string const& filename, files ) {
-						genfile::SNPDataSource::UniquePtr source ;
-						try {
-							source.reset(
-								new statfile::SNPDataSourceAdapter(
-									statfile::BuiltInTypeStatSource::open(
-										genfile::wildcard::find_files_by_chromosome( filename )
-									)
-								)
-							) ;
-						} catch( genfile::InputError const& e ) {
-							std::cerr << "Uh-oh...\n" ;
-							source.reset(
-								genfile::SNPDataSourceChain::create(
-									genfile::wildcard::find_files_by_chromosome( filename )
-								).release()
-							) ;
-						}
-						snp_filter->include_snps(
-							source->list_snps(),
-							genfile::VariantIdentifyingData::CompareFields( m_options.get_value< std::string >( "-compare-variants-by" ) )
-						) ;
-					}
-				}
-
-				if( m_options.check_if_option_was_supplied( "-excl-snpids" )) {
-					std::vector< std::string > files = m_options.get_values< std::string > ( "-excl-snpids" ) ;
-					BOOST_FOREACH( std::string const& filename, files ) {
-						snp_filter->exclude_snps_in_file(
-							filename,
-							genfile::CommonSNPFilter::SNPIDs
-						) ;
-					}
-				}
-
-				if( m_options.check_if_option_was_supplied( "-incl-snpids" )) {
-					std::vector< std::string > files = m_options.get_values< std::string > ( "-incl-snpids" ) ;
-					BOOST_FOREACH( std::string const& filename, files ) {
-						snp_filter->include_snps_in_file(
-							filename,
-							genfile::CommonSNPFilter::SNPIDs
-						) ;
-					}
-				}
-
-
-				if( m_options.check_if_option_was_supplied( "-excl-rsids" )) {
-					std::vector< std::string > files = m_options.get_values< std::string > ( "-excl-rsids" ) ;
-					BOOST_FOREACH( std::string const& filename, files ) {
-						snp_filter->exclude_snps_in_file(
-							filename,
-							genfile::CommonSNPFilter::RSIDs
-						) ;
-					}
-				}
-
-				if( m_options.check_if_option_was_supplied( "-incl-rsids" )) {
-					std::vector< std::string > files = m_options.get_values< std::string > ( "-incl-rsids" ) ;
-					BOOST_FOREACH( std::string const& filename, files ) {
-						snp_filter->include_snps_in_file(
-							filename,
-							genfile::CommonSNPFilter::RSIDs
-						) ;
-					}
-				}
-
-				if( m_options.check_if_option_was_supplied( "-excl-positions" )) {
-					std::vector< std::string > files = m_options.get_values< std::string > ( "-excl-positions" ) ;
-					BOOST_FOREACH( std::string const& filename, files ) {
-						snp_filter->exclude_snps_in_file(
-							filename,
-							genfile::CommonSNPFilter::Positions
-						) ;
-					}
-				}
-
-				if( m_options.check_if_option_was_supplied( "-incl-positions" )) {
-					std::vector< std::string > files = m_options.get_values< std::string > ( "-incl-positions" ) ;
-					BOOST_FOREACH( std::string const& filename, files ) {
-						snp_filter->include_snps_in_file(
-							filename,
-							genfile::CommonSNPFilter::Positions
-						) ;
-					}
-				}
-				if( m_options.check_if_option_was_supplied( "-excl-variants-matching" )) {
-					std::vector< std::string > specs = m_options.get_values< std::string >( "-excl-variants-matching" ) ;
-					BOOST_FOREACH( std::string const& spec, specs ) {
-						snp_filter->exclude_snps_matching(
-							spec
-						) ;
-					}
-				}
-
-				if( m_options.check_if_option_was_supplied( "-incl-variants-matching" )) {
-					std::vector< std::string > specs = m_options.get_values< std::string >( "-incl-variants-matching" ) ;
-					BOOST_FOREACH( std::string const& spec, specs ) {
-						snp_filter->include_snps_matching(
-							spec
-						) ;
-					}
-				}
-			
-				if( m_options.check_if_option_was_supplied( "-incl-range" )) {
-					std::vector< std::string > specs = m_options.get_values< std::string >( "-incl-range" ) ;
-					for ( std::size_t i = 0; i < specs.size(); ++i ) {
-						snp_filter->include_snps_in_range(
-							genfile::GenomePositionRange::parse( specs[i] )
-						) ;
-					}
-				}
-
-				if( m_options.check_if_option_was_supplied( "-excl-range" )) {
-					std::vector< std::string > specs = m_options.get_values< std::string >( "-excl-range" ) ;
-					for ( std::size_t i = 0; i < specs.size(); ++i ) {
-						snp_filter->exclude_snps_in_range(
-							genfile::GenomePositionRange::parse( specs[i] )
-						) ;
-					}
-				}
-			}
-			m_snp_filter = snp_filter ;
-		}
-		return m_snp_filter.get() ;
+
+	genfile::CommonSNPFilter* get_snp_filter() const {
+		if( !m_snp_filter.get() ) {
+			m_snp_filter = construct_snp_filter() ;
+		}
+		return m_snp_filter.get() ;
+	}
+		
+	genfile::CommonSNPFilter::UniquePtr construct_snp_filter() const {
+		genfile::CommonSNPFilter::UniquePtr snp_filter ;
+
+		if( m_options.check_if_option_was_supplied_in_group( "SNP exclusion options" )) {
+			snp_filter.reset( new genfile::CommonSNPFilter ) ;
+
+			if( m_options.check_if_option_was_supplied( "-excl-variants" )) {
+				std::vector< std::string > files = m_options.get_values< std::string > ( "-excl-variants" ) ;
+			
+				BOOST_FOREACH( std::string const& filename, files ) {
+					genfile::SNPDataSource::UniquePtr source ;
+					try {
+						source.reset(
+							new statfile::SNPDataSourceAdapter(
+								statfile::BuiltInTypeStatSource::open(
+									genfile::wildcard::find_files_by_chromosome( filename )
+								)
+							)
+						) ;
+					} catch( genfile::InputError const& e ) {
+						source.reset(
+							genfile::SNPDataSourceChain::create(
+								genfile::wildcard::find_files_by_chromosome( filename )
+							).release()
+						) ;
+					}
+					snp_filter->exclude_snps(
+						source->list_snps(),
+						genfile::VariantIdentifyingData::CompareFields( m_options.get_value< std::string >( "-compare-variants-by" ) )
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-incl-variants" )) {
+				std::vector< std::string > files = m_options.get_values< std::string > ( "-incl-variants" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					genfile::SNPDataSource::UniquePtr source ;
+					try {
+						source.reset(
+							new statfile::SNPDataSourceAdapter(
+								statfile::BuiltInTypeStatSource::open(
+									genfile::wildcard::find_files_by_chromosome( filename )
+								)
+							)
+						) ;
+					} catch( genfile::InputError const& e ) {
+						std::cerr << "Uh-oh...\n" ;
+						source.reset(
+							genfile::SNPDataSourceChain::create(
+								genfile::wildcard::find_files_by_chromosome( filename )
+							).release()
+						) ;
+					}
+					snp_filter->include_snps(
+						source->list_snps(),
+						genfile::VariantIdentifyingData::CompareFields( m_options.get_value< std::string >( "-compare-variants-by" ) )
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-excl-snpids" )) {
+				std::vector< std::string > files = m_options.get_values< std::string > ( "-excl-snpids" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->exclude_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::SNPIDs
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-incl-snpids" )) {
+				std::vector< std::string > files = m_options.get_values< std::string > ( "-incl-snpids" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->include_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::SNPIDs
+					) ;
+				}
+			}
+
+
+			if( m_options.check_if_option_was_supplied( "-excl-rsids" )) {
+				std::vector< std::string > files = m_options.get_values< std::string > ( "-excl-rsids" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->exclude_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::RSIDs
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-incl-rsids" )) {
+				std::vector< std::string > files = m_options.get_values< std::string > ( "-incl-rsids" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->include_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::RSIDs
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-excl-positions" )) {
+				std::vector< std::string > files = m_options.get_values< std::string > ( "-excl-positions" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->exclude_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::Positions
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-incl-positions" )) {
+				std::vector< std::string > files = m_options.get_values< std::string > ( "-incl-positions" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					snp_filter->include_snps_in_file(
+						filename,
+						genfile::CommonSNPFilter::Positions
+					) ;
+				}
+			}
+			if( m_options.check_if_option_was_supplied( "-excl-variants-matching" )) {
+				std::vector< std::string > specs = m_options.get_values< std::string >( "-excl-variants-matching" ) ;
+				BOOST_FOREACH( std::string const& spec, specs ) {
+					snp_filter->exclude_snps_matching(
+						spec
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-incl-variants-matching" )) {
+				std::vector< std::string > specs = m_options.get_values< std::string >( "-incl-variants-matching" ) ;
+				BOOST_FOREACH( std::string const& spec, specs ) {
+					snp_filter->include_snps_matching(
+						spec
+					) ;
+				}
+			}
+		
+			if( m_options.check_if_option_was_supplied( "-incl-range" )) {
+				std::vector< std::string > specs = m_options.get_values< std::string >( "-incl-range" ) ;
+				for ( std::size_t i = 0; i < specs.size(); ++i ) {
+					snp_filter->include_snps_in_range(
+						genfile::GenomePositionRange::parse( specs[i] )
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-excl-range" )) {
+				std::vector< std::string > specs = m_options.get_values< std::string >( "-excl-range" ) ;
+				for ( std::size_t i = 0; i < specs.size(); ++i ) {
+					snp_filter->exclude_snps_in_range(
+						genfile::GenomePositionRange::parse( specs[i] )
+					) ;
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-incl-ranges" )) {
+				std::vector< std::string > files = m_options.get_values< std::string >( "-incl-ranges" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					std::auto_ptr< std::istream > in = genfile::open_text_file_for_input( filename ) ;
+					std::string range ;
+					while( (*in) >> range ) {
+						snp_filter->include_snps_in_range(
+							genfile::GenomePositionRange::parse( range )
+						) ;
+					}
+				}
+			}
+
+			if( m_options.check_if_option_was_supplied( "-excl-ranges" )) {
+				std::vector< std::string > files = m_options.get_values< std::string >( "-excl-ranges" ) ;
+				BOOST_FOREACH( std::string const& filename, files ) {
+					std::auto_ptr< std::istream > in = genfile::open_text_file_for_input( filename ) ;
+					std::string range ;
+					while( (*in) >> range ) {
+						snp_filter->exclude_snps_in_range(
+							genfile::GenomePositionRange::parse( range )
+						) ;
+					}
+				}
+			}
+		}
+		return snp_filter ;
 	}
 	
 	void move_to_next_output_file( std::size_t index ) {
 		// Kludge: don't move through outputs until they are actually created.
 		// Actually, we only want to move through outputs once during the main
@@ -2081,11 +2120,11 @@
 							qcdb::DBOutputter::create(
 								filename,
 								m_options.get< std::string >( "-analysis-name" ),
 								m_options.get< std::string >( "-analysis-chunk" ),
 								m_options.get_values_as_map(),
-								boost::optional< db::Connection::RowId >(),
+								boost::optional< genfile::db::Connection::RowId >(),
 								m_options.get< std::string >( "-compare-variants-by" )
 							),
 							*m_samples
 						)
 					) ;
@@ -2095,11 +2134,11 @@
 							qcdb::DBOutputter::create(
 								filename,
 								m_options.get< std::string >( "-analysis-name" ),
 								m_options.get< std::string >( "-analysis-chunk" ),
 								m_options.get_values_as_map(),
-								boost::optional< db::Connection::RowId >(),
+								boost::optional< genfile::db::Connection::RowId >(),
 								m_options.get< std::string >( "-compare-variants-by" )
 							),
 							*m_samples
 						)
 					) ;
@@ -2133,11 +2172,14 @@
 
 							if( m_options.check( "-bgen-free-data" )) {
 								bgen_sink->set_free_data( m_options.get< std::string >( "-bgen-free-data" ) ) ;
 							}
 							
-							bgen_sink->set_write_sample_identifier_block( m_options.check( "-s" ) && ! m_options.check( "-bgen-omit-sample-identifier-block" )) ;
+							bgen_sink->set_write_sample_identifier_block(
+								(m_snp_data_source->has_sample_ids() || m_options.check( "-s" ))
+								&& ! m_options.check( "-bgen-omit-sample-identifier-block" )
+							) ;
 						}
 					}
 					// gen-specific options
 					{
 						genfile::GenFileSNPDataSink* gen_sink = dynamic_cast< genfile::GenFileSNPDataSink* >( sink.get() ) ;
@@ -2304,15 +2346,11 @@
 
 	genfile::CohortIndividualSource::UniquePtr create_dummy_samples(
 		genfile::SNPDataSource const& snp_data_source
 	) {
 		genfile::CohortIndividualSource::UniquePtr result ;
-		std::vector< std::string > sample_ids( snp_data_source.number_of_samples() ) ;
-		boost::format fmt( "sample_%d" ) ;
-		for( std::size_t i = 0; i < sample_ids.size(); ++i ) {
-			sample_ids[i] = ( fmt % i ).str() ;
-		}
+		std::vector< genfile::VariantEntry > sample_ids( snp_data_source.number_of_samples(), genfile::MissingValue() ) ;
 		snp_data_source.get_sample_ids( boost::bind( &impl::set_vector_entry, &sample_ids, _1, _2 )) ;
 		result.reset( new genfile::CountingCohortIndividualSource( sample_ids ) ) ;
 		return result ;
 	}
 
@@ -2525,11 +2563,11 @@
 	
 public:
 	QCToolApplication( int argc, char** argv ):
 		appcontext::ApplicationContext(
 			globals::program_name,
-			globals::program_version + ", revision " + globals::program_revision,
+			"version: " + globals::program_version + ", revision: " + globals::program_revision,
 			std::auto_ptr< appcontext::OptionProcessor >( new QCToolOptionProcessor ),
 			argc,
 			argv,
 			"-log",
 			QCToolApplication::check_options
@@ -2550,11 +2588,11 @@
 		}
 		catch( genfile::FileNotFoundError const& e ) {
 			get_ui_context().logger() << "\nError: No file matching \"" << e.filespec() << "\" could be found.\n" ;
 			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
 		}
-		catch( db::Error const& e ) {
+		catch( genfile::db::Error const& e ) {
 			get_ui_context().logger() << "!! Error (" << e.what() << ") with the following statement: \""
 				<< e.sql()
 				<< "\".\n" ;
 			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
 		}
@@ -2705,16 +2743,18 @@
 			if( file_spec[0] == "sqlite" ) {
 				qcdb::FlatTableDBOutputter::SharedPtr table_storage = qcdb::FlatTableDBOutputter::create_shared(
 					file_spec[1],
 					options().get< std::string >( "-analysis-name" ),
 					options().get< std::string >( "-analysis-chunk" ),
-					options().get_values_as_map(),
+					get_application_metadata(),
 					options().get< std::string >( "-compare-variants-by" )
 				) ;
 				if( file_spec.size() == 3 ) {
 					table_storage->set_table_name( file_spec[2] ) ;
 				}
+				table_storage->set_link_variants( !options().check( "-sqlite-dont-link-variants" ) ) ;
+				table_storage->set_record_nonprimary_identifiers( options().check( "-sqlite-store-alt-identifiers" ) ) ;
 				per_snp_storage = table_storage ;
 			} else {
 				assert( file_spec[0] == "flat" ) ;
 				per_snp_storage = qcdb::FlatFileOutputter::create_shared(
 					file_spec[1],
@@ -2735,11 +2775,11 @@
 		sample_stats::SampleStorage::SharedPtr per_sample_storage ;
 		if( options().check( "-osample" )) {
 			std::vector< std::string > const file_spec = parse_filespec( options().get< std::string >( "-osample" ) ) ;
 			if( file_spec[0] == "sqlite" ) {
 				// Catch the case where we write both to the same db.
-				boost::optional< db::Connection::RowId > analysis_id ;
+				boost::optional< genfile::db::Connection::RowId > analysis_id ;
 				if( options().check( "-osnp" ) && file_spec[1] == options().get< std::string >( "-osnp" ) && per_snp_storage ) {
 					analysis_id = per_snp_storage->analysis_id() ;
 				}
 				sample_stats::FlatTableDBOutputter::SharedPtr
 					dbStorage = sample_stats::FlatTableDBOutputter::create_shared(

Index: apps/selfmap.cpp
==================================================================
--- apps/selfmap.cpp
+++ apps/selfmap.cpp
@@ -13,14 +13,15 @@
 #include "appcontext/ApplicationContext.hpp"
 #include "appcontext/get_current_time_as_string.hpp"
 #include "genfile/MissingValue.hpp"
 #include "genfile/string_utils/string_utils.hpp"
 #include "components/SNPSummaryComponent/GenomeSequence.hpp"
-#include "components/SNPSummaryComponent/DBOutputter.hpp"
-#include "qcdb/Storage.hpp"
-#include "qcdb/FlatTableDBOutputter.hpp"
-#include "qcdb/FlatFileOutputter.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLite3Connection.hpp"
+#include "genfile/db/SQLite3Statement.hpp"
+#include "genfile/db/Error.hpp"
 
 // #define DEBUG_SELFMAP 1
 
 namespace globals {
 	std::string const program_name = "selfmap" ;
@@ -56,11 +57,11 @@
 		{
 			options.declare_group( "Input data options" ) ;
 			options[ "-sequence" ]
 				.set_description( "Specify the path of a file containing sequence to load." )
 				.set_is_required()
-				.set_takes_single_value() ;
+				.set_takes_values_until_next_option() ;
 			;
 		}
 		{
 			options.declare_group( "Analysis options" ) ;
 			options[ "-range" ]
@@ -67,11 +68,11 @@
 				.set_description( "Specify one or more ranges of SNPs to operate on. "
 					"Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the "
 					"start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. "
 					"You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome." )
 				.set_takes_values_until_next_option()
-				.set_is_required() ;
+			;
 			options[ "-kmer-size" ]
 				.set_is_required()
 				.set_takes_single_value()
 				.set_description( "Specify the size of kmer to compute using." )
 			;
@@ -81,27 +82,35 @@
 				.set_default_value( "qctool analysis" ) ;
 			options[ "-analysis-chunk" ]
 				.set_description( "Specify a name denoting the current genomic region or chunk on which this is run.  This is intended for use in parallel environments." )
 				.set_takes_single_value()
 				.set_default_value( genfile::MissingValue() ) ;
-			options[ "-table-name" ]
-				.set_description( "Specify a name for the table to use when using -flat-table." )
-				.set_takes_single_value() ;
+			options[ "-table-prefix" ]
+				.set_description( "Specify a prefix for the output table names." )
+				.set_takes_single_value()
+				.set_default_value( "" ) ;
 		}
 		{
 			options.declare_group( "Options affecting output" ) ;
 			options[ "-o" ]
 				.set_description( "Specify the path to the output file." )
-				.set_is_required()
-				.set_takes_single_value() ;
+				.set_takes_single_value()
+				.set_is_required() ;
 			options[ "-include-diagonal" ]
 				.set_description( "Specify whether selfmap should include uniquely-mapping kmers in the output. "
 					"To reduce the size of the output, these are not output by default." )
 				;
 			options[ "-log" ]
 				.set_description( "Specify the path of a log file; all screen output will be copied to the file." )
 				.set_takes_single_value() ;
+			options[ "-omit-sequence" ]
+				.set_description(
+					"Do not output sequence of kmers, just the counts. "
+					"(This reduces the output file size but means kmer sequence will need "
+					"to be looked up again if needed for downstream analysis.)")
+			;
+				
 		}
 
 		{
 			options.declare_group( "Analysis options" ) ;
 		}
@@ -121,63 +130,85 @@
 			std::auto_ptr< appcontext::OptionProcessor >( new SelfMapOptions ),
 			argc,
 			argv,
 			"-log"
 		),
-		m_sequence( GenomeSequence::create( options().get< std::string >( "-sequence" ), get_ui_context().get_progress_context( "Reading sequence" ) ) ),
+		m_sequences(
+			GenomeSequence::create(
+				options().get_values< std::string >( "-sequence" ),
+				get_ui_context().get_progress_context( "Reading sequence" )
+			)
+		),
 		m_kmer_size( options().get< std::size_t >( "-kmer-size" ) ),
-		m_ranges( parse_ranges( options().get_values< std::string >( "-range" ) ) )
+		m_number_of_distinct_kmers(0)
 	{
 	}
 	
-    std::vector< genfile::GenomePositionRange > parse_ranges( std::vector< std::string > const& spec ) {
-        std::vector< genfile::GenomePositionRange > result ;
-        result.reserve( spec.size() ) ;
-        for( std::size_t i = 0; i < spec.size(); ++i ) {
-            result.push_back( genfile::GenomePositionRange::parse( spec[i] ) ) ;
-        }
-        return result ;
-    }
+	std::vector< genfile::GenomePositionRange > parse_ranges( std::vector< std::string > const& spec ) {
+		std::vector< genfile::GenomePositionRange > result ;
+		result.reserve( spec.size() ) ;
+		for( std::size_t i = 0; i < spec.size(); ++i ) {
+			result.push_back( genfile::GenomePositionRange::parse( spec[i] ) ) ;
+		}
+		return result ;
+	}
     
 public:
 	void pre_summarise() {
 		get_ui_context().logger() << "SelfMapApplication: running with the following parameters:\n"
-			<< "Sequence: " << m_sequence->get_summary( "  " ) << "\n"
+			<< "Sequence: " << m_sequences->get_summary( "  " ) << "\n"
 			<< "Ranges: " ;
-            for( std::size_t i = 0; i < m_ranges.size(); ++i ) {
-                get_ui_context().logger() << ( i > 0 ? " " : "" ) << m_ranges[i] ;
-            }
-            
-			get_ui_context().logger() << "\n" << "kmer size: " << m_kmer_size << "bp.\n" ;
+		for( std::size_t i = 0; i < m_ranges.size(); ++i ) {
+			get_ui_context().logger() << ( i > 0 ? " " : "" ) << m_ranges[i] ;
+		}
+		get_ui_context().logger() << "\n" << "kmer size: " << m_kmer_size << "bp.\n" ;
 	}
+
 	void run() {
 		try {
 			unsafe_run() ;
 		}
 		catch( genfile::InputError const& e ) {
 			get_ui_context().logger() << "!! (" << e.what() << "): " << e.format_message() << ".\n" ;
 			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
 		}
-		catch( db::StatementPreparationError const& e ) {
+		catch( genfile::db::StatementPreparationError const& e ) {
+			get_ui_context().logger() << "!! (" << e.what() << "): " << e.description() << ".\n" ;
+			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
+		}
+		catch( genfile::db::StatementStepError const& e ) {
 			get_ui_context().logger() << "!! (" << e.what() << "): " << e.description() << ".\n" ;
 			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
 		}
 	}
+
 	void post_summarise() {
 	}
+
 private:
-	GenomeSequence::UniquePtr m_sequence ;
+	GenomeSequence::UniquePtr m_sequences ;
 	std::size_t m_kmer_size ;
 	std::vector< genfile::GenomePositionRange > m_ranges ;
+	std::size_t m_number_of_distinct_kmers ;
 
-	typedef std::map< std::string, std::vector< std::pair< genfile::GenomePosition, char > > > KmerMap ;
+	typedef std::pair< genfile::GenomePosition, char > KmerPosition ;
+	typedef std::vector< KmerPosition > KmerPositions ;
+	typedef std::pair< int, KmerPositions > KmerCountAndPositions ;
+	//typedef std::map< std::string, KmerPositions > KmerMap ;
+	typedef boost::unordered_map< std::string, KmerCountAndPositions > KmerMap ;
 	//typedef boost::unordered_map< std::string, std::vector< std::pair< genfile::Position, char > > > KmerMap ;
 	typedef boost::bimap< std::string, std::pair< genfile::GenomePosition, char > > KmerBimap ;
 	
 private:
 
 	void unsafe_run() {
+		if( options().check( "-range" )) {
+			m_ranges = parse_ranges( options().get_values< std::string >( "-range" ) ) ;
+		} else {
+			m_ranges = m_sequences->get_ranges() ;
+		}
+
 		KmerMap kmerMap ;
         for( std::size_t i = 0; i < m_ranges.size(); ++i ) {
             process_range( m_ranges[i], &kmerMap ) ;
         }
 		write_output( kmerMap, open_storage() ) ;
@@ -194,12 +225,14 @@
 		if( end.position() <= start.position() + m_kmer_size ) {
 			get_ui_context().logger() << "!! No kmers of length " << m_kmer_size << " in the range (of length " << ( end.position() - start.position() + 1 ) << ")\n" ;
 			throw appcontext::HaltProgramWithReturnCode( -1 ) ;
 		}
 		std::string kmer ;
+		std::string kmer_reverse_complement ;
+		std::string const* kmer_stored = 0;
 
-		GenomeSequence::PhysicalSequenceRange range = m_sequence->get_sequence( start.chromosome(), start.position(), end.position() ) ;
+		GenomeSequence::PhysicalSequenceRange range = m_sequences->get_sequence( start.chromosome(), start.position(), end.position() ) ;
 		genfile::Position rangePosition = range.first.start().position() ;
 		GenomeSequence::ConstSequenceIterator kmer_start = range.second.first ;
 		GenomeSequence::ConstSequenceIterator kmer_end = kmer_start + m_kmer_size ;
 
 		{
@@ -210,24 +243,37 @@
 	#if DEBUG_SELFMAP
 				std::cerr << "SelfMapApplication:run(): looking at kmer: " << kmer << "...\n" ;
 	#endif
 				kmer.assign( kmer_start, kmer_end ) ;
 				genfile::string_utils::to_upper( &kmer ) ;
+				kmer_reverse_complement.assign( kmer ) ;
+				impl::reverse_complement( &kmer_reverse_complement ) ;
+				char orientation = '+' ;
 				if( kmer.find( 'N' ) == std::string::npos ) {
-					(*result)[ kmer ].push_back(
-                        std::make_pair(
-                            genfile::GenomePosition( start.chromosome(), rangePosition ),
-                            '+'
-                        )
-                    ) ;
-					impl::reverse_complement( &kmer ) ;
-					(*result)[ kmer ].push_back(
-                        std::make_pair(
-                            genfile::GenomePosition( start.chromosome(), rangePosition + m_kmer_size ),
-                            '-'
-                        )
-                    ) ;
+					kmer_stored = &kmer ;
+					if( kmer_reverse_complement < kmer ) {
+						orientation = '-' ;
+						kmer_stored = &kmer_reverse_complement ;
+					}
+					KmerPosition kmer_position(
+						genfile::GenomePosition( start.chromosome(), rangePosition ),
+						orientation
+					) ;
+					KmerMap::iterator where = result->find( *kmer_stored ) ;
+					if( where == result->end() ) {
+						result->insert(
+							std::make_pair(
+								*kmer_stored,
+								KmerCountAndPositions(
+									m_number_of_distinct_kmers++,
+									KmerPositions( 1, kmer_position )
+								)
+							)
+						) ;
+					} else {
+						where->second.second.push_back( kmer_position ) ;
+					}
 				}
 			}
 			progress_context.notify_progress( rangePosition, range.first.end().position() - m_kmer_size ) ;
 		}
 			
@@ -234,90 +280,228 @@
 #if DEBUG_SELFMAP
 			std::cerr << "SelfMapApplication:run(): kmerMap.size() = " << result->size() << ".\n" ;
 #endif
 	}
 
-	qcdb::Storage::SharedPtr open_storage() const {
-		qcdb::Storage::SharedPtr storage ;
-		std::string const& filename = options().get< std::string >( "-o" ) ;
-
-		if( filename.size() > 7 && filename.substr( filename.size() - 7, 7 ) == ".sqlite" ) {
-			snp_summary_component::DBOutputter::SharedPtr outputter = snp_summary_component::DBOutputter::create_shared(
-				options().get< std::string >( "-o" ),
-				options().get< std::string >( "-analysis-name" ),
-				options().get< std::string >( "-analysis-chunk" ),
-				options().get_values_as_map()
-			) ;
-			if( options().check( "-table-name" )) {
-				outputter->set_table_name( options().get< std::string >(  "-table-name" )) ;
-			}
-			storage = outputter ;
-		} else {
-			storage = qcdb::FlatFileOutputter::create_shared(
-				options().get< std::string >( "-o" ),
-				options().get< std::string >( "-analysis-name" ),
-				options().get_values_as_map()
-			) ;
-		}
-		return storage ;
-	}
-
-	void write_output( KmerMap const& kmerMap, qcdb::Storage::SharedPtr storage ) {
-		appcontext::UIContext::ProgressContext progress_context = get_ui_context().get_progress_context( "Storing results" ) ;
-
-		storage->add_variable( "orientation" ) ;
-		storage->add_variable( "other_chromosome" ) ;
-		storage->add_variable( "other_position" ) ;
-		storage->add_variable( "other_orientation" ) ;
-
-		bool const include_diagonal = options().check( "-include-diagonal" ) ;
-		using genfile::string_utils::to_string ;
-		//genfile::GenomePosition position ( m_range.start().chromosome(), 0 ) ;
-		KmerMap::const_iterator i = kmerMap.begin() ;
-		KmerMap::const_iterator end_i = kmerMap.end() ;
-		std::size_t count = 0 ;
-		for( ; i != end_i; ++i, ++count ) {
-			genfile::GenomePosition const& position = i->second[0].first ;
-			genfile::VariantIdentifyingData snp(
-				to_string( position ),
-				".",
-				position,
-				i->first, "."
-			) ;
-			for( std::size_t j = 0; j < i->second.size(); ++j ) {
-				if( i->second[j].second == '+' ) {
-					snp.set_position( i->second[j].first ) ;
-					for( std::size_t k = ( j + ( include_diagonal ? 0 : 1 ) ); k < i->second.size(); ++k ) {
-						storage->create_new_variant( snp ) ;
-						storage->store_per_variant_data(
-							snp,
-							"orientation",
-							std::string( 1, i->second[j].second )
-						) ;
-						storage->store_per_variant_data(
-							snp,
-							"other_chromosome",
-							i->second[k].first.chromosome()
-						) ;
-
-						storage->store_per_variant_data(
-							snp,
-							"other_position",
-							genfile::VariantEntry::Integer( i->second[k].first.position() )
-						) ;
-
-						storage->store_per_variant_data(
-							snp,
-							"other_orientation",
-							std::string( 1, i->second[k].second )
-						) ;
-					}
-				}
-			}
-			progress_context.notify_progress( count+1, kmerMap.size() ) ;
-		}
-
+	struct Storage {
+	public: 
+		typedef std::unique_ptr< Storage > UniquePtr ;
+		typedef genfile::db::Connection::RowId KmerId ;
+		struct Overlap {
+		public:
+			Overlap():kmer_id(0) {}	
+			Overlap(
+				KmerId kmer_id_,
+				uint32_t size_,
+				genfile::GenomePosition position1_,
+				char orientation1_,
+				genfile::GenomePosition position2_,
+				char orientation2_
+			):
+				kmer_id( kmer_id_ ),
+				size( size_ ),
+				position1( position1_ ),
+				orientation1( orientation1_ ),
+				position2( position2_ ),
+				orientation2( orientation2_ )
+			{}
+		public:	
+			KmerId kmer_id ;
+			uint32_t size ;
+			genfile::GenomePosition position1 ;
+			char orientation1 ;
+			genfile::GenomePosition position2 ;
+			char orientation2 ;	
+		} ;
+
+	public:
+		static UniquePtr create( std::string const& filename, std::string const& prefix ) {
+			return UniquePtr( new Storage( filename, prefix )) ;
+		}
+
+		Storage( std::string const& filename, std::string const& table_prefix ):
+			m_filename( filename ),
+			m_prefix( table_prefix ),
+			m_connection( genfile::db::Connection::create( "file:" + filename + "?nolock=1" )),
+			m_max_buffered( 10000 )
+		{
+			setup_storage() ;
+		}
+		
+	public:
+		
+		void store_kmer(
+			std::string const& kmer,
+			KmerId const& id,
+			int count
+		) {
+			m_insert_kmer_stmt
+				->bind( 1, kmer )
+				.bind( 2, id )
+				.bind( 3, count )
+				.step() ;
+			m_insert_kmer_stmt->reset() ;
+		}
+
+		void store_overlap(
+			KmerId const& kmer_id,
+			int64_t const size,
+			genfile::GenomePosition const& position1,
+			char const orientation1,
+			genfile::GenomePosition const& position2,
+			char const orientation2
+		) {
+			m_overlaps.push_back(
+				Overlap(
+					kmer_id,
+					size,
+					position1,
+					orientation1,
+					position2,
+					orientation2
+				)
+			) ;
+			if( m_overlaps.size() > m_max_buffered ) {
+				store_overlaps() ;
+				m_overlaps.resize(0) ;
+			}
+		}
+
+		void finalise() {
+			std::cerr << "++ Storing remaining overlaps...\n" ;
+			if( m_overlaps.size() > 0 ) {
+				store_overlaps() ;
+				m_overlaps.resize(0) ;
+			}
+			std::cerr << "++ Indexing...\n" ;
+			m_connection->run_statement( "CREATE INDEX OverlapChr1Index On Overlap( chromosome1, position1 )" ) ;
+			m_connection->run_statement( "CREATE INDEX OverlapChr2Index On Overlap( chromosome2, position2 )" ) ;
+		}
+		
+	private:
+		std::string const m_filename ;
+		std::string const m_prefix ;
+		genfile::db::Connection::UniquePtr m_connection ;
+		genfile::db::Connection::StatementPtr m_insert_kmer_stmt ;
+		genfile::db::Connection::StatementPtr m_insert_overlap_stmt ;
+		std::vector< Overlap > m_overlaps ;
+		std::size_t m_max_buffered ;
+	private:
+		void setup_storage() {
+			// Performance options
+			// Assume this program will write once, so we don't need
+			// extensive ACID options.
+			m_connection->run_statement( "PRAGMA locking_mode = EXCLUSIVE ;" ) ;
+			m_connection->run_statement( "PRAGMA journal_mode = MEMORY ;" ) ;
+			m_connection->run_statement( "PRAGMA synchronous = OFF ;" ) ;
+			
+			m_connection->run_statement(
+				"CREATE TABLE `" + m_prefix + "Kmer` ( sequence TEXT NOT NULL PRIMARY KEY, id INT NOT NULL, `count` INT NOT NULL ) WITHOUT ROWID ;"
+			) ;
+			
+			m_connection->run_statement(
+				"CREATE TABLE IF NOT EXISTS `" + m_prefix + "Overlap` ( "
+					"kmer_id INT NOT NULL REFERENCES `" + m_prefix + "Kmer`(id), "
+					"k INT NOT NULL, "
+					"chromosome1 TEXT NOT NULL, position1 TEXT NOT NULL, orientation1 TEXT NOT NULL, "
+					"chromosome2 TEXT NOT NULL, position2 TEXT NOT NULL, orientation2 TEXT NOT NULL"
+				") ;"
+			) ;
+			
+			m_insert_kmer_stmt = m_connection->get_statement(
+				"INSERT INTO `" + m_prefix + "Kmer` (sequence, id, count) VALUES( ?, ?, ? ) ;"
+			) ;
+
+			m_insert_overlap_stmt = m_connection->get_statement(
+				"INSERT INTO `" + m_prefix + "Overlap` VALUES( ?, ?, ?, ?, ?, ?, ?, ? ) ;"
+			) ;
+		}
+
+		void store_overlaps() {
+			genfile::db::Connection::ScopedTransactionPtr transaction = m_connection->open_transaction( 7200 ) ;
+			for( std::size_t i = 0; i < m_overlaps.size(); ++i ) {
+				Overlap const& o = m_overlaps[i] ;
+				m_insert_overlap_stmt
+					->bind( 1, o.kmer_id )
+					.bind( 2, o.size )
+					.bind( 3, std::string( o.position1.chromosome() ))
+					.bind( 4, o.position1.position() )
+					.bind( 5, std::string( 1, o.orientation1 ) )
+					.bind( 6, std::string( o.position2.chromosome() ))
+					.bind( 7, o.position2.position() )
+					.bind( 8, std::string( 1, o.orientation2 ) )
+					.step() ;
+				m_insert_overlap_stmt->reset() ;
+			}
+		}
+		
+	} ;
+
+	Storage::UniquePtr open_storage() const {
+		return Storage::create(
+			options().get< std::string >( "-o" ),
+			options().get< std::string >( "-table-prefix" )
+		) ;
+	}
+
+	void write_output( KmerMap const& kmerMap, Storage::UniquePtr storage ) {
+
+		bool const include_diagonal = options().check( "-include-diagonal" ) ;
+		bool const output_sequence = !options().check( "-omit-sequence" ) ;
+		using genfile::string_utils::to_string ;
+		//genfile::GenomePosition position ( m_range.start().chromosome(), 0 ) ;
+
+		{
+			appcontext::UIContext::ProgressContext progress_context
+				= get_ui_context().get_progress_context( "Storing kmers" ) ;
+			KmerMap::const_iterator kmer_i = kmerMap.begin() ;
+			KmerMap::const_iterator end_i = kmerMap.end() ;
+			std::size_t count = 0 ;
+			for( ; kmer_i != end_i; ++kmer_i, ++count ) {
+				std::string const& kmer = kmer_i->first ;
+				KmerCountAndPositions const& count_and_positions = kmer_i->second ;
+				KmerPositions const& positions = count_and_positions.second ;
+
+				Storage::KmerId const kmer_id = count_and_positions.first ;
+				storage->store_kmer(
+					output_sequence ? kmer : ".", kmer_id, positions.size()
+				) ;
+				progress_context.notify_progress( count+1, kmerMap.size() ) ;
+			}
+		}
+
+		{	
+			appcontext::UIContext::ProgressContext progress_context
+				= get_ui_context().get_progress_context( "Storing overlaps" ) ;
+			KmerMap::const_iterator kmer_i = kmerMap.begin() ;
+			KmerMap::const_iterator end_i = kmerMap.end() ;
+			std::size_t count = 0 ;
+			for( ; kmer_i != end_i; ++kmer_i, ++count ) {
+				std::string const& kmer = kmer_i->first ;
+				KmerCountAndPositions const& count_and_positions = kmer_i->second ;
+				Storage::KmerId const kmer_id = count_and_positions.first ;
+				KmerPositions const& positions = count_and_positions.second ;
+
+				for( std::size_t j = 0; j < positions.size(); ++j ) {
+					for( std::size_t k = j+(include_diagonal ? 0 : 1); k < positions.size(); ++k ) {
+						genfile::GenomePosition const& position1 = positions[j].first ;
+						char const orientation1 = positions[j].second ;
+						genfile::GenomePosition const& position2 = positions[k].first ;
+						char const orientation2 = positions[k].second ;
+						storage->store_overlap(
+							kmer_id,
+							kmer.size(),
+							position1,
+							orientation1,
+							position2,
+							orientation2
+						) ;
+					}
+				}
+				progress_context.notify_progress( count+1, kmerMap.size() ) ;
+			}
+		}
 		storage->finalise() ;
 	}
 } ;
 
 int main( int argc, char** argv ) {

ADDED   apps/wscript
Index: apps/wscript
==================================================================
--- apps/wscript
+++ apps/wscript
@@ -0,0 +1,34 @@
+def configure( cfg ):
+	pass
+
+def create_app( bld, name, use = [] ):
+	import os
+	bld.program(
+		target =  '%s_v%s' % ( name, bld.env['VERSION'] ),
+		source = name + '.cpp',
+		includes = './ include',
+		use = use,
+		install_path = os.path.join( bld.env[ 'PREFIX' ], 'bin' )
+	)
+
+external = [ "boost", "ZLIB", "pthread", "CBLAS", "CLAPACK", "rt" ]
+components = [ 'SNPSummaryComponent', 'SampleSummaryComponent', 'HaplotypeFrequencyComponent', 'RelatednessComponent', 'SNPOutputComponent' ]
+base = [ 'appcontext', 'genfile', 'statfile', 'qcdb', 'metro', 'qctool-lib', 'package_revision' ]
+
+dependencies = {
+	"qctool": external + components + base,
+	"hptest": external + components + base,
+	"ldbird": external + components + base,
+	#"multifinemap": external + components + base,
+	"selfmap": external + components + base,
+	"index-kmers": external + components + base,
+	"inthinnerator": external + components + base,
+	"bingwa": external + components + base + ["bingwa-impl"]
+}
+
+def build( bld ):
+	for appName in dependencies.keys():
+		create_app( bld, appName, dependencies[appName] )
+
+	
+

ADDED   bingwa/include/bingwa/BingwaComputation.hpp
Index: bingwa/include/bingwa/BingwaComputation.hpp
==================================================================
--- bingwa/include/bingwa/BingwaComputation.hpp
+++ bingwa/include/bingwa/BingwaComputation.hpp
@@ -0,0 +1,59 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BINGWA_BINGWA_COMPUTATION_HPP
+#define BINGWA_BINGWA_COMPUTATION_HPP
+
+#include <memory>
+#include <string>
+#include <vector>
+#include <map>
+#include <boost/function.hpp>
+#include <boost/noncopyable.hpp>
+#include <Eigen/Core>
+#include "genfile/VariantEntry.hpp"
+#include "EffectParameterNamePack.hpp"
+#include "appcontext/OptionProcessor.hpp"
+
+namespace bingwa {
+	struct BingwaComputation: public boost::noncopyable {
+		typedef std::auto_ptr< BingwaComputation > UniquePtr ;
+		static UniquePtr create(
+			std::string const& name,
+			std::vector< std::string > const& cohort_names,
+			appcontext::OptionProcessor const&
+		) ;
+		virtual ~BingwaComputation() {}
+		typedef boost::function< void ( std::string const& value_name, genfile::VariantEntry const& value ) > ResultCallback ;
+	
+		struct DataGetter: public boost::noncopyable {
+			virtual ~DataGetter() {} ;
+			virtual std::size_t get_number_of_cohorts() const = 0 ;
+			virtual bool is_non_missing( std::size_t i ) const = 0 ;
+			virtual bool is_trusted( std::size_t i ) const = 0 ;
+			virtual void get_counts( std::size_t, Eigen::VectorXd* result ) const = 0 ;
+			virtual void get_betas( std::size_t i, Eigen::VectorXd* result ) const = 0 ;
+			virtual void get_ses( std::size_t i, Eigen::VectorXd* result  ) const = 0 ;
+			virtual void get_covariance_upper_triangle( std::size_t i, Eigen::VectorXd* result  ) const = 0 ;
+			virtual void get_pvalue( std::size_t i, double* result ) const = 0 ;
+			virtual void get_info( std::size_t i, double* result ) const = 0 ;
+			virtual void get_variable( std::string const& variable, std::size_t i, std::string* result ) const = 0 ;
+		} ;
+
+		typedef boost::function< bool ( DataGetter const&, int i ) > Filter ;
+	
+		virtual void set_effect_parameter_names( EffectParameterNamePack const& names ) = 0 ;
+		virtual void get_variables( boost::function< void ( std::string, std::string ) > ) const = 0 ;
+		virtual void operator()(
+			DataGetter const& data_getter,
+			ResultCallback callback
+		) = 0 ;
+		virtual std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const = 0 ;
+		virtual std::string get_spec() const = 0 ;
+	} ;
+}
+
+#endif

ADDED   bingwa/include/bingwa/EffectParameterNamePack.hpp
Index: bingwa/include/bingwa/EffectParameterNamePack.hpp
==================================================================
--- bingwa/include/bingwa/EffectParameterNamePack.hpp
+++ bingwa/include/bingwa/EffectParameterNamePack.hpp
@@ -0,0 +1,51 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef EFFECTPARAMETERNAMEPACK_HPP
+#define EFFECTPARAMETERNAMEPACK_HPP
+
+#include <string>
+#include <vector>
+
+namespace bingwa {
+	struct EffectParameterNamePack {
+	public:
+		static std::size_t const npos = std::string::npos ;
+		EffectParameterNamePack() ;
+		EffectParameterNamePack(
+			std::vector< std::string > betas,
+			std::vector< std::string > ses,
+			std::vector< std::string > cov
+		) ;
+
+		EffectParameterNamePack( EffectParameterNamePack const& other ) ;
+		EffectParameterNamePack& operator=( EffectParameterNamePack const& other ) ;
+
+		std::size_t size() const ;
+		std::size_t find( std::string const& ) const ;
+		std::string parameter_name( std::size_t i ) const ;
+		std::string se_name( std::size_t i ) const ;
+		std::string wald_pvalue_name( std::size_t i ) const ;
+		std::string covariance_name( std::size_t i, std::size_t j ) const ;
+	
+		/* rename a parameter, e.g. as beta_1:add, se_1 */
+		void rename( std::size_t parameter_i, std::string const& newName, std::string const& newNumber, std::string const& identifier ) ;
+
+		bool operator==( EffectParameterNamePack const& other ) const ;
+		bool operator!=( EffectParameterNamePack const& other ) const ;
+	
+		std::string get_summary() const ;
+
+	private:
+		std::vector< std::string > m_betas ;
+		std::vector< std::string > m_ses ;
+		std::vector< std::string > m_cov ;
+		
+		std::size_t get_index_of_covariance( std::size_t i, std::size_t j ) const ;
+	} ;
+}
+
+#endif

ADDED   bingwa/include/bingwa/FlatFileFrequentistGenomeWideAssociationResults.hpp
Index: bingwa/include/bingwa/FlatFileFrequentistGenomeWideAssociationResults.hpp
==================================================================
--- bingwa/include/bingwa/FlatFileFrequentistGenomeWideAssociationResults.hpp
+++ bingwa/include/bingwa/FlatFileFrequentistGenomeWideAssociationResults.hpp
@@ -0,0 +1,168 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef FLAT_FILE_FREQUENTISTGENOMEWIDEASSOCIATIONRESULTS_HPP
+#define FLAT_FILE_FREQUENTISTGENOMEWIDEASSOCIATIONRESULTS_HPP
+
+#include <boost/bimap.hpp>
+#include <boost/regex.hpp>
+#include "statfile/BuiltInTypeStatSource.hpp"
+#include "statfile/FilteringStatSource.hpp"
+#include "bingwa/FrequentistGenomeWideAssociationResults.hpp"
+
+/*
+* Class FlatFileFrequentistGenomeWideAssociationResults.
+* This is a utility base class for classes reading scan results flat files.
+* It provides:
+* - storage for values read.
+* - 
+*
+* - and implements the FrequentistGenomeWideAssociationResults interface for retrieving tresults..
+*/
+struct FlatFileFrequentistGenomeWideAssociationResults:  public FrequentistGenomeWideAssociationResults {
+public:
+	typedef std::auto_ptr< FlatFileFrequentistGenomeWideAssociationResults > UniquePtr ;
+public:
+	virtual void set_effect_size_column_regex( std::string const& beta_column_regex ) = 0 ;
+
+	void add_data(
+		statfile::BuiltInTypeStatSource::UniquePtr source,
+		SNPResultCallback callback,
+		ProgressCallback progress_callback
+	) ;
+
+	void add_variable( std::string const& variable ) ;
+	void add_trust_constraint( statfile::BoundConstraint constraint ) ;
+
+	std::size_t get_number_of_SNPs() const ;
+
+	genfile::VariantIdentifyingData const& get_SNP( std::size_t snp_i ) const ;
+	bool is_trusted( std::size_t snp_i ) const ;
+	void get_betas( std::size_t snp_i, Eigen::VectorXd* result ) const ;
+	void get_ses( std::size_t snp_i, Eigen::VectorXd* result ) const ;
+	void get_covariance_upper_triangle( std::size_t snp_i, Eigen::VectorXd* result ) const ; 
+	void get_pvalue( std::size_t snp_i, double* result ) const ;
+	void get_info( std::size_t snp_i, double* result ) const ;
+	/* Get genotype counts, as a vector of length 6 in this order:
+	* haploid A, B, diploid AA, AB, BB, NULL call. */
+	void get_counts( std::size_t snp_i, Eigen::VectorXd* result ) const ;
+	virtual genfile::VariantEntry get_value( std::size_t snp_i, std::string const& variable ) const = 0 ;
+
+	/* Get values for user-specified or otherwise required / requested variables */
+	std::vector< std::string > list_variables() const ;
+	std::vector< std::string > list_trust_constraint_variables() const ;
+	void get_variable( std::size_t snp_i, std::string const& variable, std::string* value ) const ;
+	std::string get_summary( std::string const& prefix, std::size_t target_column ) const ;
+
+
+public:
+	struct ColumnSpec {
+		ColumnSpec():
+			 m_required( false )
+		{}
+		ColumnSpec( std::string const& name, boost::regex const& pattern, std::size_t index, bool required, std::string const& type ):
+			m_name( name ),
+			m_simplified_name( name ),
+			m_pattern( pattern ),
+			m_index( index ),
+			m_required( required ),
+			m_type( type )
+		{}
+		ColumnSpec( ColumnSpec const& other ):
+			m_name( other.m_name ),
+			m_simplified_name( other.m_simplified_name ),
+			m_pattern( other.m_pattern ),
+			m_index( other.m_index ),
+			m_required( other.m_required ),
+			m_type( other.m_type )
+		{}
+		ColumnSpec& operator=( ColumnSpec const& other ) {
+			m_name = other.m_name ;
+			m_name = other.m_simplified_name ;
+			m_pattern = other.m_pattern ;
+			m_index = other.m_index ;
+			m_required = other.m_required ;
+			m_type = other.m_type ;
+			return *this ;
+		}
+		bool operator<( ColumnSpec const& other ) const {
+			return m_name < other.m_name ;
+		}
+		bool operator==( ColumnSpec const& other ) const {
+			return (m_name == other.m_name) ;
+		}
+		std::string const& name() const { return m_name ; }
+		std::string const& simplified_name() const { return m_simplified_name ; }
+		boost::regex const& pattern() const { return m_pattern ; }
+		std::size_t index() const { return m_index ; }
+		bool const& required() const { return m_required ; }
+		std::string const& type() const { return m_type ; }
+
+		void set_simplified_name( std::string const& name ) { m_simplified_name = name ; }
+	private:
+		std::string m_name ;
+		std::string m_simplified_name ;
+		boost::regex m_pattern ;
+		std::size_t m_index ;
+		bool m_required ;
+		std::string m_type ;
+	} ;
+	typedef std::vector< ColumnSpec > DesiredColumns ;
+ 	typedef boost::bimap< ColumnSpec, std::size_t > SourceColumnMap ;
+	
+protected:
+	std::string const m_missing_value ;
+	genfile::VariantIdentifyingDataTest::UniquePtr m_exclusion_test ;
+
+	DesiredColumns m_desired_columns ;
+	boost::optional< SourceColumnMap > m_column_map ;
+	
+	std::vector< genfile::VariantIdentifyingData > m_snps ;
+	std::vector< unsigned char > m_trusted ;
+	int m_degrees_of_freedom ;
+	Eigen::MatrixXf m_betas ;
+	Eigen::MatrixXf m_ses ;
+	Eigen::MatrixXf m_covariance ;
+	Eigen::VectorXf m_pvalues ;
+	Eigen::VectorXf m_info ;
+	Eigen::MatrixXf m_sample_counts ;
+	typedef Eigen::MatrixXf::ConstRowXpr Row ;
+	typedef std::map< std::string, std::vector< std::string > > ExtraVariables ;
+	ExtraVariables m_extra_variable_storage ;
+	std::set< std::string > m_variables ;
+	std::vector< statfile::BoundConstraint > m_trust_constraints ;
+	
+	FlatFileFrequentistGenomeWideAssociationResults() ;
+	
+	virtual DesiredColumns setup_columns( std::vector< std::string > const& column_names ) = 0 ;
+	virtual bool read_snp( statfile::BuiltInTypeStatSource& source, genfile::SNPIdentifyingData& snp ) const = 0 ;
+	bool check_if_snp_trusted( std::size_t snp_index ) const ;
+	virtual bool check_if_snp_accepted( std::size_t snp_index ) const = 0 ;
+	virtual void store_value( int snp_index, std::string const& variable, std::string const& value ) = 0 ;
+	
+private:
+
+	void setup(
+		statfile::BuiltInTypeStatSource::UniquePtr source,
+		SNPResultCallback callback,
+		ProgressCallback progress_callback
+	) ;
+	
+	SourceColumnMap get_source_column_map(
+		statfile::BuiltInTypeStatSource const& source,
+		DesiredColumns const&
+	) const ;
+	void check_columns(
+		statfile::BuiltInTypeStatSource const& source,
+		SourceColumnMap const& column_map
+	) const ;
+
+	void resize_storage( Eigen::MatrixXf::Index const N_snps, Eigen::MatrixXf::Index const degrees_of_freedom ) ;
+	
+	void free_unused_memory() ;
+} ;
+
+#endif

ADDED   bingwa/include/bingwa/FrequentistGenomeWideAssociationResults.hpp
Index: bingwa/include/bingwa/FrequentistGenomeWideAssociationResults.hpp
==================================================================
--- bingwa/include/bingwa/FrequentistGenomeWideAssociationResults.hpp
+++ bingwa/include/bingwa/FrequentistGenomeWideAssociationResults.hpp
@@ -0,0 +1,71 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef FREQUENTISTGENOMEWIDEASSOCIATIONRESULTS_HPP
+#define FREQUENTISTGENOMEWIDEASSOCIATIONRESULTS_HPP
+
+#include <memory>
+#include <string>
+#include <boost/noncopyable.hpp>
+#include <boost/function.hpp>
+#include <boost/optional.hpp>
+#include <Eigen/Core>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/Chromosome.hpp"
+#include "genfile/VariantIdentifyingDataTest.hpp"
+#include "genfile/wildcard.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "bingwa/EffectParameterNamePack.hpp"
+
+struct FrequentistGenomeWideAssociationResults: public boost::noncopyable {
+public:
+	typedef std::auto_ptr< FrequentistGenomeWideAssociationResults > UniquePtr ;
+	typedef boost::function< void ( std::size_t i, genfile::VariantIdentifyingData const& snp ) > GetSNPCallback ;
+	typedef
+		boost::function< void ( genfile::VariantIdentifyingData const&, std::string const&, genfile::VariantEntry const& ) > 
+		SNPResultCallback ;
+	typedef boost::function< void ( std::size_t, boost::optional< std::size_t > ) > ProgressCallback ;
+
+	static UniquePtr create(
+		std::vector< genfile::wildcard::FilenameMatch > const& filenames,
+		boost::optional< std::string > const& effect_size_column_regex,
+		std::vector< std::string > const& columns,
+		genfile::VariantIdentifyingDataTest::UniquePtr test,
+		boost::optional< genfile::Chromosome > chromosome_hint = boost::optional< genfile::Chromosome >(),
+		SNPResultCallback callback = SNPResultCallback(),
+		ProgressCallback progress_callback = ProgressCallback()
+	) ;
+	
+public:
+	virtual ~FrequentistGenomeWideAssociationResults() {}
+	
+	virtual void add_variable( std::string const& variable ) = 0 ;
+	virtual void set_effect_size_column_regex( std::string const& ) = 0 ;
+	virtual std::size_t get_number_of_SNPs() const = 0 ;
+	virtual genfile::VariantIdentifyingData const& get_SNP( std::size_t snp_i ) const = 0 ;
+	virtual bingwa::EffectParameterNamePack get_effect_parameter_names() const = 0 ;
+	virtual bool is_trusted( std::size_t snp_i ) const = 0 ;
+	virtual void get_betas( std::size_t snp_i, Eigen::VectorXd* result ) const = 0 ;
+	virtual void get_ses( std::size_t snp_i, Eigen::VectorXd* result ) const = 0 ; 
+	virtual void get_covariance_upper_triangle( std::size_t snp_i, Eigen::VectorXd* result ) const = 0 ; 
+	virtual void get_pvalue( std::size_t snp_i, double* result ) const = 0 ;
+	virtual void get_info( std::size_t snp_i, double* result ) const = 0 ;
+	virtual void get_counts( std::size_t snp_i, Eigen::VectorXd* result ) const = 0 ;
+	virtual std::vector< std::string > list_variables() const = 0 ; 
+	virtual std::vector< std::string > list_trust_constraint_variables() const = 0 ; 
+	virtual void get_variable( std::size_t snp_i, std::string const& variable, std::string* result ) const = 0 ;
+	
+	virtual std::string get_summary( std::string const& prefix = "", std::size_t target_column = 80 ) const = 0 ;
+
+	// Legacy function: this should probably be removed.
+	void get_SNPs( GetSNPCallback callback ) const {
+		for( std::size_t i = 0; i < get_number_of_SNPs(); ++i ) {
+			callback( i, get_SNP( i ) ) ;
+		}
+	}
+} ;
+
+#endif

ADDED   bingwa/include/bingwa/MMMResults.hpp
Index: bingwa/include/bingwa/MMMResults.hpp
==================================================================
--- bingwa/include/bingwa/MMMResults.hpp
+++ bingwa/include/bingwa/MMMResults.hpp
@@ -0,0 +1,51 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef MMM_RESULTS_HPP
+#define MMM_RESULTS_HPP
+
+#include <boost/optional.hpp>
+#include "genfile/Chromosome.hpp"
+#include "genfile/VariantIdentifyingDataTest.hpp"
+#include "FlatFileFrequentistGenomeWideAssociationResults.hpp"
+
+namespace bingwa {
+	struct MMMResults: public FlatFileFrequentistGenomeWideAssociationResults {
+		MMMResults(
+			genfile::VariantIdentifyingDataTest::UniquePtr test,
+			boost::optional< genfile::Chromosome > const chromosome_hint = boost::optional< genfile::Chromosome >()
+		) ;
+
+		void set_effect_size_column_regex( std::string const& beta_column_regex ) ;
+		void add_variable( std::string const& variable ) ;
+		std::string get_summary( std::string const& prefix, std::size_t target_column ) const ;
+		int get_number_of_effect_parameters() const ;
+		bingwa::EffectParameterNamePack get_effect_parameter_names() const ;
+
+		genfile::VariantEntry get_value( std::size_t snp_i, std::string const& variable ) const ;
+
+	private:
+		genfile::VariantIdentifyingDataTest::UniquePtr m_exclusion_test ;
+		std::string m_effect_column_regex ;
+		std::string m_se_column_regex ;
+		boost::optional< genfile::Chromosome > m_chromosome_hint ;
+		std::set< std::string > m_variables ;
+		DesiredColumns m_required_columns ;
+	
+	private:
+		DesiredColumns setup_columns( std::vector< std::string > const& column_names ) ;
+		bool read_snp( statfile::BuiltInTypeStatSource& source, genfile::SNPIdentifyingData& snp ) const ;
+		bool check_if_snp_accepted( std::size_t snp_i ) const ;
+		void store_value(
+			int snp_index,
+			std::string const& variable,
+			std::string const& value
+		) ;
+	} ;
+
+}
+
+#endif

ADDED   bingwa/include/bingwa/ModelAveragingBayesFactorAnalysis.hpp
Index: bingwa/include/bingwa/ModelAveragingBayesFactorAnalysis.hpp
==================================================================
--- bingwa/include/bingwa/ModelAveragingBayesFactorAnalysis.hpp
+++ bingwa/include/bingwa/ModelAveragingBayesFactorAnalysis.hpp
@@ -0,0 +1,77 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BINGWA_MODEL_AVERAGING_ANALYSIS_HPP
+#define BINGWA_MODEL_AVERAGING_ANALYSIS_HPP
+
+#include "bingwa/BingwaComputation.hpp"
+
+namespace bingwa {
+	struct ModelSpec {
+	public:
+		// between populat
+		typedef boost::tuple< std::vector< std::string >, std::vector< std::string >, std::vector< std::string > > CovarianceSpec ;
+		typedef std::pair< std::string, std::pair< CovarianceSpec, Eigen::MatrixXd > > Covariance ;
+
+	public:
+		template< typename IteratorBegin, typename IteratorEnd >
+		ModelSpec( std::string const& name, IteratorBegin begin, IteratorEnd end, double weight ):
+			m_name( name ),
+			m_covariances( begin, end ),
+			m_weight( weight )
+		{}
+		ModelSpec( std::string const& name, Covariance const& covariance, double weight ) ;
+		ModelSpec( ModelSpec const& other ) ;
+		ModelSpec& operator=( ModelSpec const& other ) ;
+		
+		std::string const& name() const { return m_name ; }
+		std::size_t size() const { return m_covariances.size() ; }
+		Eigen::MatrixXd const& covariance( std::size_t i ) const { return m_covariances[i].second.second ; }
+		double weight() const { return m_weight ; }
+
+	private:
+		std::string  m_name ;
+		std::vector< Covariance > m_covariances ;
+		double m_weight ;
+	} ;
+		
+	struct ModelAveragingBayesFactorAnalysis: public bingwa::BingwaComputation {
+	public:
+		typedef std::auto_ptr< ModelAveragingBayesFactorAnalysis > UniquePtr ;
+		typedef bingwa::ModelSpec ModelSpec ;
+		static UniquePtr create() ;
+
+	public:
+		ModelAveragingBayesFactorAnalysis() ;
+		~ModelAveragingBayesFactorAnalysis() ;
+		
+		void add_model( ModelSpec const& model_spec ) ;
+		void set_filter( Filter filter ) ;
+		void set_null_sd( double sd ) ;
+		void set_effect_parameter_names( bingwa::EffectParameterNamePack const& names ) ;
+		void get_variables( boost::function< void ( std::string, std::string ) > callback ) const ;
+		void operator()(
+			DataGetter const& data_getter,
+			ResultCallback callback
+		) ;
+
+		std::string get_spec() const ;
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+		std::vector< ModelSpec > const& get_models() const ;
+
+	private:
+		std::string const m_name ;
+		std::string const m_prefix ;
+		double m_null_sd ;
+		Eigen::MatrixXd const m_sigma ;
+		Filter m_filter ;
+		bingwa::EffectParameterNamePack m_effect_parameter_names ;
+
+		std::vector< ModelSpec > m_models ;
+	} ;
+}
+
+#endif

ADDED   bingwa/include/bingwa/MultivariateFixedEffectMetaAnalysis.hpp
Index: bingwa/include/bingwa/MultivariateFixedEffectMetaAnalysis.hpp
==================================================================
--- bingwa/include/bingwa/MultivariateFixedEffectMetaAnalysis.hpp
+++ bingwa/include/bingwa/MultivariateFixedEffectMetaAnalysis.hpp
@@ -0,0 +1,41 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BINGWA_MULTIVARIATE_FIXED_EFFECTS_HPP
+#define BINGWA_MULTIVARIATE_FIXED_EFFECTS_HPP
+
+#include <string>
+#include <utility>
+#include <Eigen/Core>
+#include "bingwa/BingwaComputation.hpp"
+#include "bingwa/impl/impl.hpp"
+
+namespace bingwa {
+	struct MultivariateFixedEffectMetaAnalysis: public bingwa::BingwaComputation {
+		typedef std::auto_ptr< MultivariateFixedEffectMetaAnalysis > UniquePtr ;
+		
+		MultivariateFixedEffectMetaAnalysis( std::string const& name ) ;
+		void set_filter( Filter filter ) ;
+		void set_effect_parameter_names( bingwa::EffectParameterNamePack const& names ) ;
+		void get_variables( boost::function< void ( std::string, std::string ) > callback ) const ;
+		void operator()(
+			DataGetter const& data_getter,
+			ResultCallback callback
+		) ;
+		std::string get_spec() const ;
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+
+	private:
+		
+		std::string const m_name ;
+		std::string const m_prefix ;
+		Eigen::MatrixXd const m_sigma ;
+		Filter m_filter ;
+		bingwa::EffectParameterNamePack m_effect_parameter_names ;
+	} ;
+}
+
+#endif

ADDED   bingwa/include/bingwa/PerCohortBayesFactor.hpp
Index: bingwa/include/bingwa/PerCohortBayesFactor.hpp
==================================================================
--- bingwa/include/bingwa/PerCohortBayesFactor.hpp
+++ bingwa/include/bingwa/PerCohortBayesFactor.hpp
@@ -0,0 +1,44 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BINGWA_PER_COHORT_BF_HPP
+#define BINGWA_PER_COHORT_BF_HPP
+
+#include "bingwa/BingwaComputation.hpp"
+#include "bingwa/ModelAveragingBayesFactorAnalysis.hpp"
+
+namespace bingwa {
+	struct PerCohortBayesFactor: public bingwa::BingwaComputation {
+	public:
+		typedef std::auto_ptr< PerCohortBayesFactor > UniquePtr ;
+		typedef bingwa::ModelAveragingBayesFactorAnalysis::ModelSpec ModelSpec ;
+		static UniquePtr create( std::vector< std::string > const& cohort_names, ModelSpec const& model ) ;
+
+	public:
+		PerCohortBayesFactor( std::vector< std::string > const& cohort_names, ModelSpec const& model ) ;
+		
+		void add_variable( std::string const& variable ) ;
+		void set_effect_parameter_names( bingwa::EffectParameterNamePack const& names ) ;
+		void get_variables( boost::function< void ( std::string, std::string ) > callback ) const ;
+		void operator()(
+			DataGetter const& data_getter,
+			ResultCallback callback
+		) ;
+		
+		std::string get_spec() const ;
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+
+		private:
+			std::vector< std::string > const m_cohort_names ;
+			std::set< std::string > m_extra_variables ;
+			bingwa::EffectParameterNamePack m_effect_parameter_names ;
+			bingwa::ModelSpec m_model ;
+			double m_null_sd ;
+	} ;
+
+}
+
+#endif

ADDED   bingwa/include/bingwa/PerCohortCountsReporter.hpp
Index: bingwa/include/bingwa/PerCohortCountsReporter.hpp
==================================================================
--- bingwa/include/bingwa/PerCohortCountsReporter.hpp
+++ bingwa/include/bingwa/PerCohortCountsReporter.hpp
@@ -0,0 +1,49 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+
+#ifndef BINGWA_PER_COHORT_COUNTS_REPORTER_HPP
+#define BINGWA_PER_COHORT_COUNTS_REPORTER_HPP
+
+#include <memory>
+#include <string>
+#include <vector>
+#include <boost/function.hpp>
+#include <Eigen/Core>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "appcontext/OptionProcessor.hpp"
+#include "bingwa/BingwaComputation.hpp"
+
+namespace bingwa {	
+	struct PerCohortCountsReporter: public bingwa::BingwaComputation {
+		public:
+			typedef std::auto_ptr< PerCohortCountsReporter > UniquePtr ;
+	
+		public:
+			PerCohortCountsReporter(
+				std::vector< std::string > const& cohort_names,
+				std::vector< std::vector< std::string > > const& variables
+			) ;
+			void add_variable( std::string const& variable ) ;
+			void get_variables( boost::function< void ( std::string, std::string ) > callback ) const ;
+			void set_effect_parameter_names( EffectParameterNamePack const& names ) ;
+
+			void operator()(
+				DataGetter const& data_getter,
+				ResultCallback callback
+			) ;
+
+			std::string get_spec() const ;
+			std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+
+		private:
+			std::vector< std::string > const m_cohort_names ;
+			std::vector< std::vector< std::string > > m_variables ;
+	} ;
+}
+
+#endif

ADDED   bingwa/include/bingwa/PerCohortValueReporter.hpp
Index: bingwa/include/bingwa/PerCohortValueReporter.hpp
==================================================================
--- bingwa/include/bingwa/PerCohortValueReporter.hpp
+++ bingwa/include/bingwa/PerCohortValueReporter.hpp
@@ -0,0 +1,52 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+
+#ifndef BINGWA_PER_VALUE_COHORT_REPORTER_HPP
+#define BINGWA_PER_VALUE_COHORT_REPORTER_HPP
+
+#include <memory>
+#include <string>
+#include <vector>
+#include <boost/function.hpp>
+#include <Eigen/Core>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "appcontext/OptionProcessor.hpp"
+#include "bingwa/EffectParameterNamePack.hpp"
+#include "bingwa/BingwaComputation.hpp"
+
+namespace bingwa {	
+	struct PerCohortValueReporter: public bingwa::BingwaComputation {
+		public:
+			typedef std::auto_ptr< PerCohortValueReporter > UniquePtr ;
+	
+		public:
+			PerCohortValueReporter(
+				std::vector< std::string > const& cohort_names,
+				std::vector< std::vector< std::string > > const& cohort_variables,
+				bool report_counts
+			) ;
+			void set_effect_parameter_names( EffectParameterNamePack const& names ) ;
+			void get_variables( boost::function< void ( std::string, std::string ) > callback ) const ;
+
+			void operator()(
+				DataGetter const& data_getter,
+				ResultCallback callback
+			) ;
+
+			std::string get_spec() const ;
+			std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+
+		private:
+			std::vector< std::string > const m_cohort_names ;
+			std::vector< std::vector< std::string > > m_variables ;
+			bool const m_report_counts ;
+			EffectParameterNamePack m_effect_parameter_names ;
+	} ;
+}
+
+#endif

ADDED   bingwa/include/bingwa/SNPTESTResults.hpp
Index: bingwa/include/bingwa/SNPTESTResults.hpp
==================================================================
--- bingwa/include/bingwa/SNPTESTResults.hpp
+++ bingwa/include/bingwa/SNPTESTResults.hpp
@@ -0,0 +1,55 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_RESULTS_HPP
+#define SNPTEST_RESULTS_HPP
+
+#include <boost/optional.hpp>
+#include <boost/function.hpp>
+#include "genfile/Chromosome.hpp"
+#include "statfile/FilteringStatSource.hpp"
+#include "FlatFileFrequentistGenomeWideAssociationResults.hpp"
+
+namespace bingwa {
+	struct SNPTESTResults: public FlatFileFrequentistGenomeWideAssociationResults {
+		typedef boost::function< bool ( double info, double maf, Row const& betas, Row const& ses, Row const& counts ) > Filter ;
+
+		SNPTESTResults(
+			genfile::VariantIdentifyingDataTest::UniquePtr test,
+			boost::optional< genfile::Chromosome > const chromosome_hint = boost::optional< genfile::Chromosome >()
+		) ;
+
+		void set_effect_size_column_regex( std::string const& beta_column_regex ) ;
+		bingwa::EffectParameterNamePack get_effect_parameter_names() const ;
+	
+		std::string get_summary( std::string const& prefix, std::size_t target_column ) const ;
+
+		genfile::VariantEntry get_value( std::size_t snp_i, std::string const& variable ) const ;
+
+	private:
+		genfile::VariantIdentifyingDataTest::UniquePtr m_exclusion_test ;
+		std::string m_beta_column_regex ;
+		boost::optional< genfile::Chromosome > m_chromosome_hint ;
+		std::vector< std::string > m_beta_columns ;
+		std::vector< std::string > m_se_columns ;
+		std::vector< std::string > m_cov_columns ;
+		std::string m_pvalue_column ;
+		std::string m_info_column ;
+
+	private:
+		DesiredColumns setup_columns( std::vector< std::string > const& column_names ) ;
+		bool read_snp( statfile::BuiltInTypeStatSource& source, genfile::SNPIdentifyingData& snp ) const ;
+		bool check_if_snp_accepted( std::size_t snp_i ) const ;
+		void store_value(
+			int snp_index,
+			std::string const& variable,
+			std::string const& value
+		) ;
+	} ;
+}
+
+#endif
+

ADDED   bingwa/include/bingwa/impl/impl.hpp
Index: bingwa/include/bingwa/impl/impl.hpp
==================================================================
--- bingwa/include/bingwa/impl/impl.hpp
+++ bingwa/include/bingwa/impl/impl.hpp
@@ -0,0 +1,136 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BINGWA_IMPL_HPP
+#define BINGWA_IMPL_HPP
+
+#include <Eigen/Cholesky>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/distributions/chi_squared.hpp>
+#include "bingwa/special_values.hpp"
+#include "bingwa/BingwaComputation.hpp"
+
+namespace bingwa {
+	namespace impl {
+		bool basic_missingness_filter( bingwa::BingwaComputation::DataGetter const& data_getter, int i ) ;
+		bool basic_trust_filter( bingwa::BingwaComputation::DataGetter const& data_getter, int i ) ;
+		bool single_population_filter( bingwa::BingwaComputation::DataGetter const& data_getter, int i, int population ) ;
+		
+		bool get_betas_and_ses_for_cohort(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& betas,
+			Eigen::VectorXd& ses,
+			Eigen::VectorXd& non_missingness
+		) ;
+
+		bool get_betas_and_ses_one_per_cohort(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& betas,
+			Eigen::VectorXd& ses,
+			Eigen::VectorXd& non_missingness
+		) ;
+		
+		// Betas from each study are assumed to come in the same order.
+		// Covariances in each study are assumed to reflect the upper triangle of covariances
+		// and come in the order cov_1,2 cov_1,3, ..., cov_2,3, cov_2,4, ...
+		bool get_betas_and_covariance_for_cohort(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& betas,
+			Eigen::MatrixXd& covariance,
+			Eigen::VectorXd& non_missingness,
+			int const numberOfEffects,
+			std::size_t cohort
+		) ;
+
+		void get_total_counts(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& counts
+		) ;
+
+		// Read betas and ses for all cohorts into an output vector and matrix,
+		// along with an indicator of non-missingness.
+		// The layout depends on the `layout` argument:
+		// If layout == eByBeta then all beta_1's go in one contiguous block,
+		// followed by all beta_2's, etc.
+		// If layout == eByPopulation then beta_1, 2, etc. for population 1 go in one block,
+		// followed by beta_1, 2 etc for population 2.
+		// If there is only one beta both layouts are the same
+		//
+		// Betas from each study are assumed to come in the same order.
+		// Covariances in each study are assumed to reflect the upper triangle of covariances
+		// and come in the order cov_1,2 cov_1,3, ..., cov_2,3, cov_2,4, ...
+		enum Layout { eByBeta = 0, eByCohort = 1 } ;
+
+		bool get_betas_and_covariance_across_cohorts(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& betas,
+			Eigen::MatrixXd& covariance,
+			Eigen::VectorXd& non_missingness,
+			int const numberOfEffects,
+			Layout const layout = eByBeta
+		) ;
+
+		std::string serialise( Eigen::VectorXd const& vector ) ;
+		std::string to_01_string( Eigen::VectorXd const v ) ;
+
+		template< typename M >
+		std::string format_matrix( M const& m ) {
+			std::ostringstream s ;
+			s << "matrix( nrow=" << m.rows() << ", ncol=" << m.cols() << ", data = c(" ;
+			for( int i = 0; i < m.rows(); ++i ) {
+				if( i > 0 ) {
+					s << "," ;
+				}
+				for( int j = 0; j < m.cols(); ++j ) {
+					if( j > 0 ) {
+						s << "," ;
+					}
+					s << m(i,j) ;
+				}
+			}
+			s << "))" ;
+			return s.str() ;
+		}
+
+		//
+		// Bayesian meta-analysis treating the prior as normal with mean 0 and variance matrix \Sigma
+		// and the likelihood as normal and given by
+		// the estimated betas and ses.
+		//
+		double compute_bayes_factor( Eigen::MatrixXd const& prior, Eigen::MatrixXd const& null_prior, Eigen::MatrixXd const& V, Eigen::VectorXd const& betas ) ;
+
+		void compute_fixed_effect_meta_and_variance(
+			Eigen::MatrixXd const& V,
+			Eigen::VectorXd const& betas,
+			int const numberOfCohorts,
+			int const numberOfEffects,
+			Eigen::VectorXd* metaBeta,
+			Eigen::MatrixXd* metaVariance,
+			double* chi_squared
+		) ;
+		
+		enum Tail { eLower = 0, eUpper = 1, eBoth = 2 } ;
+		double compute_chisquared_pvalue( double statistic, int const numberOfEffects ) ;
+		double compute_normal_pvalue( double statistic, double variance, Tail const tail = eBoth ) ;
+
+		Eigen::MatrixXd get_nonmissing_coefficient_selector(
+			Eigen::VectorXd const& non_missingness
+		) ;
+
+		Eigen::MatrixXd get_nonmissing_cohort_selector(
+			Eigen::VectorXd const& non_missingness,
+			int const numberOfCohorts,
+			int const numberOfEffects
+		) ;
+	}
+}
+
+#endif

ADDED   bingwa/include/bingwa/special_values.hpp
Index: bingwa/include/bingwa/special_values.hpp
==================================================================
--- bingwa/include/bingwa/special_values.hpp
+++ bingwa/include/bingwa/special_values.hpp
@@ -0,0 +1,17 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BINGWA_SPECIAL_VALUES_HPP
+#define BINGWA_SPECIAL_VALUES_HPP
+
+#include <numeric>
+
+namespace bingwa {
+	double const NA = std::numeric_limits< double >::quiet_NaN() ;
+	double const Infinity = std::numeric_limits< double >::infinity() ;
+}
+
+#endif

ADDED   bingwa/src/EffectParameterNamePack.cpp
Index: bingwa/src/EffectParameterNamePack.cpp
==================================================================
--- bingwa/src/EffectParameterNamePack.cpp
+++ bingwa/src/EffectParameterNamePack.cpp
@@ -0,0 +1,137 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <vector>
+#include <cassert>
+#include "genfile/string_utils/string_utils.hpp"
+#include "genfile/string_utils/slice.hpp"
+#include "bingwa/EffectParameterNamePack.hpp"
+
+namespace bingwa {
+	EffectParameterNamePack::EffectParameterNamePack() {}
+	EffectParameterNamePack::EffectParameterNamePack(
+		std::vector< std::string > betas,
+		std::vector< std::string > ses,
+		std::vector< std::string > cov
+	):
+		m_betas( betas ),
+		m_ses( ses ),
+		m_cov( cov )
+	{
+		assert( m_ses.size() == m_betas.size() ) ;
+		assert( m_cov.size() == ( m_betas.size() * ( m_betas.size() - 1 )) / 2 ) ;
+	}
+
+	EffectParameterNamePack::EffectParameterNamePack( EffectParameterNamePack const& other ):
+		m_betas( other.m_betas ),
+		m_ses( other.m_ses ),
+		m_cov( other.m_cov )
+	{
+	}
+
+	EffectParameterNamePack& EffectParameterNamePack::operator=( EffectParameterNamePack const& other ) {
+		m_betas = other.m_betas ;
+		m_ses = other.m_ses ;
+		m_cov = other.m_cov ;
+		return *this ;
+	}
+
+	std::size_t EffectParameterNamePack::size() const {
+		return m_betas.size() ;
+	}
+
+	std::size_t EffectParameterNamePack::find( std::string const& name ) const {
+		std::vector< std::string >::const_iterator where = std::find( m_betas.begin(), m_betas.end(), name ) ;
+		if( where == m_betas.end() ) {
+			return npos ;
+		} else {
+			return std::size_t( where - m_betas.begin() ) ;
+		}
+	}
+
+	std::string EffectParameterNamePack::parameter_name( std::size_t i ) const {
+		return m_betas[i] ;
+	}
+
+	std::string EffectParameterNamePack::se_name( std::size_t i ) const {
+		return m_ses[i] ;
+	}
+
+	std::string EffectParameterNamePack::wald_pvalue_name( std::size_t i ) const {
+		std::string result = m_ses[i] ;
+		std::size_t pos = result.find( "se_" ) ;
+		assert( pos != std::string::npos ) ;
+		result.replace( pos, 3, "wald_pvalue_" ) ;
+		return result ;
+	}
+
+	std::string EffectParameterNamePack::covariance_name( std::size_t i, std::size_t j ) const {
+		return m_cov[ get_index_of_covariance(i,j) ] ;
+	}
+
+	std::size_t EffectParameterNamePack::get_index_of_covariance( std::size_t i, std::size_t j ) const {
+		assert( j > i ) ;
+		// index in cov skips the lower diagonal.
+		// Lower diagonal has ((i+1)*(i+2)/2) entries since i is a 0-based index.
+		// index in full array would be i*N+j
+		std::size_t const N = m_betas.size() ;
+		return i*N + j - ( (i+1)*(i+2)/2 ) ;
+	}
+
+	void EffectParameterNamePack::rename(
+		std::size_t parameter_i,
+		std::string const& newName,
+		std::string const& newSubscript,
+		std::string const& identifier
+	) {
+		using genfile::string_utils::to_string ;
+		using genfile::string_utils::slice ;
+		std::size_t const N = m_betas.size() ;
+		assert( parameter_i < N ) ;
+		m_betas[parameter_i] = newName + "_" + newSubscript + ":" + identifier ;
+		m_ses[parameter_i] = "se_" + newSubscript ;
+		// Rename covariance parameters
+		// They are expected to be of the form <name>_i,j
+		{
+			std::size_t j = parameter_i ;
+			for( std::size_t i = 0; i < parameter_i; ++i ) {
+				std::size_t index = get_index_of_covariance(i,j) ;
+				std::vector< slice > elts = slice( m_cov[index] ).split( "_" ) ;
+				assert( elts.size() == 2 ) ;
+				std::vector< slice > elts2 = elts[1].split( "," ) ;
+				assert( elts2.size() == 2 ) ;
+				m_cov[index] = elts[0] + "_" + elts2[0] + "," + newSubscript ;
+			}
+		}
+		{
+			std::size_t i = parameter_i ;
+			for( std::size_t j = parameter_i+1; j < N; ++j ) {
+				std::size_t index = get_index_of_covariance(i,j) ;
+				std::vector< slice > elts = slice( m_cov[index] ).split( "_" ) ;
+				assert( elts.size() == 2 ) ;
+				std::vector< slice > elts2 = elts[1].split( "," ) ;
+				assert( elts2.size() == 2 ) ;
+				m_cov[index] = elts[0] + "_" + newSubscript + "," + elts2[1] ;
+			}
+		}
+	}
+
+	bool EffectParameterNamePack::operator==( EffectParameterNamePack const& other ) const {
+		return m_betas == other.m_betas && m_ses == other.m_ses && m_cov == other.m_cov ;
+	}
+
+	bool EffectParameterNamePack::operator!=( EffectParameterNamePack const& other ) const {
+		return !operator==( other ) ;
+	}
+
+	std::string EffectParameterNamePack::get_summary() const {
+		using genfile::string_utils::join ;
+		std::ostringstream ostr ;
+		ostr << "(" << join( m_betas, "," ) << "; " << join( m_ses, "," ) << "; " << join( m_cov, ", " ) << ")" ;
+		return ostr.str() ;
+	}
+}

ADDED   bingwa/src/FlatFileFrequentistGenomeWideAssociationResults.cpp
Index: bingwa/src/FlatFileFrequentistGenomeWideAssociationResults.cpp
==================================================================
--- bingwa/src/FlatFileFrequentistGenomeWideAssociationResults.cpp
+++ bingwa/src/FlatFileFrequentistGenomeWideAssociationResults.cpp
@@ -0,0 +1,366 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <limits>
+#include <boost/regex.hpp>
+#include <boost/format.hpp>
+#include "bingwa/FlatFileFrequentistGenomeWideAssociationResults.hpp"
+
+namespace {
+	double const NA = std::numeric_limits< double >::quiet_NaN() ;
+}
+
+/*
+* Class FlatFileFrequentistGenomeWideAssociationResults.
+* This is a utility base class for classes reading scan results flat files.
+* It provides:
+* - storage for values read.
+* - 
+*
+* - and implements the FrequentistGenomeWideAssociationResults interface for retrieving tresults..
+*/
+void FlatFileFrequentistGenomeWideAssociationResults::add_data(
+	statfile::BuiltInTypeStatSource::UniquePtr source,
+	SNPResultCallback callback,
+	ProgressCallback progress_callback
+) {
+	setup( source, callback, progress_callback ) ;
+}
+
+std::size_t FlatFileFrequentistGenomeWideAssociationResults::get_number_of_SNPs() const {
+	return m_snps.size() ;
+}
+
+genfile::VariantIdentifyingData const& FlatFileFrequentistGenomeWideAssociationResults::get_SNP( std::size_t snp_i ) const {
+	assert( snp_i < m_snps.size() ) ;
+	return m_snps[ snp_i ] ;
+}
+
+bool FlatFileFrequentistGenomeWideAssociationResults::is_trusted( std::size_t snp_i ) const {
+	return bool( m_trusted[ snp_i ] ) ;
+}
+void FlatFileFrequentistGenomeWideAssociationResults::get_betas( std::size_t snp_i, Eigen::VectorXd* result ) const {
+	*result = m_betas.row( snp_i ).cast< double >() ;
+}
+void FlatFileFrequentistGenomeWideAssociationResults::get_ses( std::size_t snp_i, Eigen::VectorXd* result ) const {
+	*result = m_ses.row( snp_i ).cast< double >() ;
+}
+void FlatFileFrequentistGenomeWideAssociationResults::get_covariance_upper_triangle( std::size_t snp_i, Eigen::VectorXd* result ) const {
+	*result = m_covariance.row( snp_i ).cast< double >() ;
+}
+void FlatFileFrequentistGenomeWideAssociationResults::get_pvalue( std::size_t snp_i, double* result ) const {
+	*result = m_pvalues( snp_i ) ;
+}
+void FlatFileFrequentistGenomeWideAssociationResults::get_info( std::size_t snp_i, double* result ) const {
+	*result = m_info( snp_i ) ;
+}
+void FlatFileFrequentistGenomeWideAssociationResults::get_counts( std::size_t snp_i, Eigen::VectorXd* result ) const {
+	*result = m_sample_counts.row( snp_i ).cast< double >() ;
+}
+std::vector< std::string > FlatFileFrequentistGenomeWideAssociationResults::list_variables() const {
+	std::vector< std::string > result( m_variables.begin(), m_variables.end() ) ;
+	return result ;
+}
+std::vector< std::string > FlatFileFrequentistGenomeWideAssociationResults::list_trust_constraint_variables() const {
+	std::vector< std::string > result ;
+	for( std::size_t i = 0; i < m_trust_constraints.size(); ++i ) {
+		result.push_back( m_trust_constraints[i].variable() ) ;
+	}
+	return result ;
+}
+void FlatFileFrequentistGenomeWideAssociationResults::get_variable( std::size_t snp_i, std::string const& variable, std::string* value ) const {
+	std::map< std::string, std::vector< std::string > >::const_iterator where = m_extra_variable_storage.find( variable ) ;
+	assert( where != m_extra_variable_storage.end() ) ;
+	*value = where->second[ snp_i ] ;
+}
+
+std::string FlatFileFrequentistGenomeWideAssociationResults::get_summary( std::string const& prefix, std::size_t target_column ) const {
+	using genfile::string_utils::to_string ;
+	
+	// estimate memory used in SNPs.
+	unsigned long mem_used = 0 ;
+	for( std::size_t i = 0; i < m_snps.size(); ++i ) {
+		mem_used += m_snps[i].estimate_bytes_used() ;
+	}
+	
+	std::string result = "scan results object ("
+		+ to_string( m_snps.size() )
+		+ " SNPs"
+		+ ", ~"
+		+ to_string(
+			(
+				(
+					m_betas.size()
+					+ m_ses.size()
+					+ m_pvalues.size()
+					+ m_info.size()
+					+ m_sample_counts.size()
+				) * sizeof( float )
+				+ mem_used
+			)
+			/ 1000000.0
+		) + "Mb in use.)\n" ;
+	
+	std::ostringstream str( result ) ;
+#if 0
+	str << "\n" << " -- using the following columns:\n" ;
+
+	SourceColumnMap::right_const_iterator
+		i = m_column_map.get().right.begin(),
+		end_i = m_column_map.get().right.end() ;
+	
+	for( std::size_t count = 0; i != end_i; ++i, ++count ) {
+		str << " -- column " << i->first << ": " << "(\"" << i->second.name() << "\", matching \"" << i->second.pattern().str() << "\")\n" ;
+	}
+#endif
+
+	return str.str() ;
+}
+
+void FlatFileFrequentistGenomeWideAssociationResults::add_variable( std::string const& variable ) {
+	/* Don't do anything if variable is already added */
+	for( std::size_t i = 0; i < m_desired_columns.size(); ++i ) {
+		if( variable == m_desired_columns[i].name() ) {
+			return ;
+		}
+	}
+	m_variables.insert( variable ) ;
+	/* Make sure we prepare storage. */
+	m_extra_variable_storage[ variable ] ;
+}
+
+void FlatFileFrequentistGenomeWideAssociationResults::add_trust_constraint( statfile::BoundConstraint constraint ) {
+	add_variable( constraint.variable() ) ;
+	m_trust_constraints.push_back( constraint ) ;
+}
+
+bool FlatFileFrequentistGenomeWideAssociationResults::check_if_snp_trusted( std::size_t snp_index ) const {
+	bool result = true ;
+	for( std::size_t constraint_i = 0; constraint_i < m_trust_constraints.size(); ++constraint_i ) {
+		std::string const& variable = m_trust_constraints[constraint_i].variable() ;
+		result = result && m_trust_constraints[constraint_i].constraint().test( get_value( snp_index, variable ) ) ;
+	}
+	return result ;
+}
+
+FlatFileFrequentistGenomeWideAssociationResults::FlatFileFrequentistGenomeWideAssociationResults():
+	m_missing_value( "NA" ),
+	m_degrees_of_freedom( 0 )
+{}
+
+void FlatFileFrequentistGenomeWideAssociationResults::setup(
+	statfile::BuiltInTypeStatSource::UniquePtr source,
+	SNPResultCallback callback,
+	ProgressCallback progress_callback
+) {
+	if( !m_column_map ) {
+		m_desired_columns = setup_columns( source->column_names() ) ;
+		m_column_map = get_source_column_map( *source, m_desired_columns ) ;
+	} else {
+		check_columns( *source, m_column_map.get() ) ;
+	}
+	assert( m_column_map ) ;
+	int const degrees_of_freedom = get_effect_parameter_names().size() ;
+	
+	std::size_t snp_index = m_snps.size() ;
+
+	genfile::SNPIdentifyingData snp ;
+	
+	for( ; read_snp( *source, snp ); (*source) >> statfile::ignore_all() ) {
+		
+		if( snp_index >= m_snps.size() ) {
+			resize_storage( snp_index + 100000, degrees_of_freedom ) ;
+		}
+		
+		// Deal with strange non-ids.  This isn't a general solution but 
+		if(
+			snp.get_SNPID() == "---" // IMPUTE2
+			|| snp.get_SNPID() == "?" // QCTOOL under some usages
+			|| snp.get_SNPID() == "NA" // dunno.
+		) {
+			snp.set_SNPID( "" ) ;
+		}
+
+		// read data columns.
+		// We use the index-to-regex map to iterate over required columns in the right order.
+		SourceColumnMap::right_const_iterator i = m_column_map.get().right.begin(), end_i = m_column_map.get().right.end() ;
+		std::string value ;
+		for( ; i != end_i; ++i ) {
+			(*source)
+				>> statfile::ignore( i->first - source->current_column() )
+				>> value ;
+
+			store_value(
+				snp_index,
+				i->second.simplified_name(),
+				value
+			) ;
+		}
+
+		m_snps[ snp_index ] = snp ;
+		if( check_if_snp_accepted( snp_index )) {
+			m_trusted[ snp_index ] = check_if_snp_trusted( snp_index ) ;
+			++snp_index ;
+		}
+		
+		if( progress_callback ) {
+			progress_callback( double( source->number_of_rows_read() + 1 ), source->number_of_rows() ) ;
+		}
+	}
+	
+	// Now deallocate any unused memory.
+	m_snps.resize( snp_index ) ;
+	resize_storage( snp_index, degrees_of_freedom ) ;
+}
+
+FlatFileFrequentistGenomeWideAssociationResults::SourceColumnMap FlatFileFrequentistGenomeWideAssociationResults::get_source_column_map(
+	statfile::BuiltInTypeStatSource const& source,
+	DesiredColumns const& desired_columns
+) const {
+	SourceColumnMap result ;
+	for( std::size_t i = 0; i < desired_columns.size(); ++i ) {
+		std::pair< SourceColumnMap::iterator, bool > insertion = result.insert(
+			SourceColumnMap::value_type(
+				desired_columns[i], desired_columns[i].index()
+			)
+		) ;
+		if( !insertion.second ) {
+			throw genfile::OperationFailedError(
+				"FlatFileFrequentistGenomeWideAssociationResults::get_source_column_map()",
+				"m_column_map",
+				"Insertion of value for column \"" + desired_columns[i].name() + "\" (matching \"" + desired_columns[i].pattern().str() + "\")."
+			) ;
+		}
+	}
+	return result ;
+}
+
+void FlatFileFrequentistGenomeWideAssociationResults::check_columns(
+	statfile::BuiltInTypeStatSource const& source,
+	SourceColumnMap const& column_map
+) const {
+	std::vector< std::string > const& column_names = source.column_names() ;
+	// typedef boost::bimap< std::string, std::size_t > SourceColumnMap ;
+
+	boost::format fmt( "Column %d (\"%s\") does not match expected name \"%s\"." ) ;
+	SourceColumnMap::const_iterator
+		i = column_map.begin(),
+		end_i = column_map.end() ;
+	for( ; i != end_i; ++i ) {
+		std::string const& column_name = column_names[ i->right ] ;
+		std::string const& expected_name = i->left.name() ;
+		if( column_name != expected_name ) {
+			throw genfile::BadArgumentError(
+				"FlatFileFrequentistGenomeWideAssociationResults::check_columns()",
+				"source=\"" + source.get_source_spec() + "\"",
+				( fmt % ( i->right + 1 ) % column_name % expected_name ).str()
+			) ;
+		} ;
+	}
+}
+
+void FlatFileFrequentistGenomeWideAssociationResults::resize_storage( Eigen::MatrixXf::Index const N_snps, Eigen::MatrixXf::Index const degrees_of_freedom ) {
+	using std::min ;
+	int const current_N = min( N_snps, Eigen::MatrixXf::Index( m_snps.size() ) ) ;
+	{
+		// free any unused memory for SNPs.
+		std::vector< genfile::VariantIdentifyingData > snps( N_snps ) ;
+		std::copy( m_snps.begin(), m_snps.end(), snps.begin() ) ;
+		m_snps.swap( snps ) ;
+		std::vector< unsigned char > trusted( N_snps ) ;
+		std::copy( m_trusted.begin(), m_trusted.begin() + current_N, trusted.begin() ) ;
+		m_trusted.swap( trusted ) ;
+	}
+	{
+		Eigen::MatrixXf betas = Eigen::MatrixXf::Zero( N_snps, degrees_of_freedom ) ;
+		if( m_betas.rows() > 0 ) {
+			betas.block( 0, 0, current_N, degrees_of_freedom ) = m_betas.block( 0, 0, current_N, degrees_of_freedom ) ;
+		}
+		m_betas.swap( betas ) ;
+	}
+	{
+		Eigen::MatrixXf ses = Eigen::MatrixXf::Zero( N_snps, degrees_of_freedom )  ;
+		if( m_ses.rows() > 0 ) {
+			ses.block( 0, 0, current_N, degrees_of_freedom ) = m_ses.block( 0, 0, current_N, degrees_of_freedom ) ;
+		}
+		m_ses.swap( ses ) ;
+	}
+	{
+		Eigen::MatrixXf covariance = Eigen::MatrixXf::Zero( N_snps, ( degrees_of_freedom - 1 ) * degrees_of_freedom / 2 )  ;
+		if( m_covariance.rows() > 0 ) {
+			covariance.block( 0, 0, current_N, covariance.cols() ) = m_covariance.block( 0, 0, current_N, covariance.cols() ) ;
+		}
+		m_covariance.swap( covariance ) ;
+	}
+	{
+		Eigen::VectorXf pvalues = Eigen::VectorXf::Zero( N_snps ) ;
+		pvalues.head( current_N ) = m_pvalues.head( current_N ) ;
+		m_pvalues.swap( pvalues ) ;
+	}
+	{
+		Eigen::VectorXf info = Eigen::VectorXf::Zero( N_snps ) ;
+		info.head( current_N ) = m_info.head( current_N ) ;
+		m_info.swap( info ) ;
+	}
+	{
+		Eigen::MatrixXf sample_counts = Eigen::MatrixXf::Zero( N_snps, 6 ) ;
+		if( m_sample_counts.rows() > 0 ) {
+			sample_counts.block( 0, 0, current_N, 6 ) = m_sample_counts.block( 0, 0, current_N, 6 ) ;
+		}
+		m_sample_counts.swap( sample_counts ) ;
+	}
+	{
+		for( ExtraVariables::iterator i = m_extra_variable_storage.begin(); i != m_extra_variable_storage.end(); ++i ) {
+			i->second.resize( N_snps ) ; // std::vector resize does not lose data.
+			std::vector< std::string > v = i->second ;
+			i->second.swap( v ) ;
+		}
+	}
+}
+
+void FlatFileFrequentistGenomeWideAssociationResults::free_unused_memory() {
+	std::size_t const N_snps = m_snps.size() ;
+	{
+		std::vector< genfile::VariantIdentifyingData > snps( m_snps.begin(), m_snps.end() ) ;
+		m_snps.swap( snps ) ;
+	}
+	{
+		std::vector< unsigned char > trusted( m_trusted.begin(), m_trusted.end() ) ;
+		m_trusted.swap( trusted ) ;
+	}
+	{
+		Eigen::MatrixXf betas = m_betas.block( 0, 0, N_snps, m_betas.cols() ) ;
+		m_betas.swap( betas ) ;
+	}
+	{
+		Eigen::MatrixXf ses = m_ses.block( 0, 0, N_snps, m_betas.cols() ) ; ;
+		m_ses.swap( ses ) ;
+	}
+	{
+		Eigen::MatrixXf covariance = m_covariance.block( 0, 0, N_snps, m_covariance.cols() ) ; ;
+		m_covariance.swap( covariance ) ;
+	}
+	{
+		Eigen::VectorXf pvalues = m_pvalues.head( N_snps ) ;
+		m_pvalues.swap( pvalues ) ;
+	}
+	{
+		Eigen::VectorXf info = m_info.head( N_snps ) ;
+		m_info.swap( info ) ;
+	}
+	{
+		Eigen::MatrixXf sample_counts = m_sample_counts.block( 0, 0, N_snps, m_sample_counts.cols() ) ;
+		m_sample_counts.swap( sample_counts ) ;
+	}
+	{
+		for( ExtraVariables::iterator i = m_extra_variable_storage.begin(); i != m_extra_variable_storage.end(); ++i ) {
+			i->second.resize( N_snps ) ;
+			std::vector< std::string > v = i->second ;
+			i->second.swap( v ) ;
+		}
+	}
+}
+

ADDED   bingwa/src/MMMResults.cpp
Index: bingwa/src/MMMResults.cpp
==================================================================
--- bingwa/src/MMMResults.cpp
+++ bingwa/src/MMMResults.cpp
@@ -0,0 +1,162 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/regex.hpp>
+#include <boost/optional.hpp>
+#include "genfile/Chromosome.hpp"
+#include "bingwa/MMMResults.hpp"
+#include "bingwa/EffectParameterNamePack.hpp"
+
+// #define DEBUG_MMMRESULTS 1
+namespace bingwa {
+	namespace {
+		namespace impl {	
+			boost::optional< MMMResults::ColumnSpec > get_matching_name(
+				std::vector< std::string > names,
+				boost::regex const& regex,
+				bool required,
+				std::string const& type
+			) {
+				boost::optional< MMMResults::ColumnSpec > result ;
+				std::size_t i = 0 ;
+				for( i = 0; i < names.size(); ++i ) {
+	#if DEBUG_MMMRESULTS
+					std::cerr << "Looking for regex " << regex.str() << "in " << names[i] << "...\n" ;
+	#endif
+					if( boost::regex_match( names[ i ], regex ) ) {
+	#if DEBUG_MMMRESULTS
+						std::cerr << "Found!\n" ;
+	#endif
+						break ;
+					}
+				}
+				if( i < names.size() ) {
+					result = MMMResults::ColumnSpec( names[i], regex, i, required, type ) ;
+				}
+				return result ;
+			}
+		}
+	}
+	MMMResults::MMMResults(
+		genfile::VariantIdentifyingDataTest::UniquePtr test,
+		boost::optional< genfile::Chromosome > const chromosome_hint
+	):
+	 	m_exclusion_test( test ),
+		m_effect_column_regex( "z_est" ),
+		m_se_column_regex( "z_se" ),
+		m_chromosome_hint( chromosome_hint )
+	{}
+
+	void MMMResults::add_variable( std::string const& variable ) {
+		m_variables.insert( variable ) ;
+	}
+
+	void MMMResults::set_effect_size_column_regex( std::string const& effect_column_regex ) {
+		m_effect_column_regex = effect_column_regex ;
+		m_se_column_regex = genfile::string_utils::replace_all( effect_column_regex, "_est", "_se" ) ;
+	}
+
+	std::string MMMResults::get_summary( std::string const& prefix, std::size_t target_column ) const {
+		return prefix + "mmm " + FlatFileFrequentistGenomeWideAssociationResults::get_summary( "", target_column ) ;
+	}
+
+	int MMMResults::get_number_of_effect_parameters() const {
+		return 1 ;
+	}
+
+	bingwa::EffectParameterNamePack MMMResults::get_effect_parameter_names() const {
+		return bingwa::EffectParameterNamePack(
+			std::vector< std::string >( 1, m_effect_column_regex ),
+			std::vector< std::string >( 1, m_se_column_regex ),
+			std::vector< std::string >()
+		) ;
+	}
+
+
+	bool MMMResults::read_snp( statfile::BuiltInTypeStatSource& source, genfile::SNPIdentifyingData& snp ) const {
+		if( m_chromosome_hint ) {
+			snp.position().chromosome() = *m_chromosome_hint ;
+		}
+		return( source >> snp.SNPID() >> snp.rsid() >> snp.position().position() >> snp.first_allele() >> snp.second_allele() ) ;
+	}
+
+	bool MMMResults::check_if_snp_accepted( std::size_t snp_i ) const {
+		return
+			!m_exclusion_test.get()
+			|| m_exclusion_test->operator()( m_snps[ snp_i ] )
+		;
+	}
+
+	MMMResults::DesiredColumns MMMResults::setup_columns( std::vector< std::string > const& columns ) {
+		DesiredColumns result ;
+		using boost::regex ;
+		result.push_back( *impl::get_matching_name( columns, regex( m_effect_column_regex ), true, "beta" ) ) ;
+		result.push_back( *impl::get_matching_name( columns, regex( m_se_column_regex ), true, "se" ) ) ;
+		result.push_back( *impl::get_matching_name( columns, regex( "pval" ), true, "pvalue" ) ) ;
+		result.push_back( *impl::get_matching_name( columns, regex( "gen_00" ), true, "counts" ) ) ;
+		result.push_back( *impl::get_matching_name( columns, regex( "gen_01" ), true, "counts" ) ) ;
+		result.push_back( *impl::get_matching_name( columns, regex( "gen_11" ), true, "counts" ) ) ;
+		result.push_back( *impl::get_matching_name( columns, regex( "gen_NULL" ), true, "counts" ) ) ;
+	
+		return result ;	
+	}
+
+	void MMMResults::store_value(
+		int snp_index,
+		std::string const& variable,
+		std::string const& value
+	) {
+		using genfile::string_utils::to_repr ;
+	    double const NA = std::numeric_limits< double >::quiet_NaN() ;
+		if( variable == m_effect_column_regex ) {
+			m_betas( snp_index, 0 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == m_se_column_regex ) {
+			m_ses( snp_index, 0 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "pval" ) {
+			m_pvalues( snp_index ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "gen_00" ) {
+			m_sample_counts( snp_index, 2 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "gen_01" ) {
+			m_sample_counts( snp_index, 3 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "gen_11" ) {
+			m_sample_counts( snp_index, 4 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "gen_NULL" ) {
+			m_sample_counts( snp_index, 5 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+	}
+	
+	genfile::VariantEntry MMMResults::get_value( std::size_t snp_index, std::string const& variable ) const {
+		if( variable == m_effect_column_regex ) {
+			return m_betas( snp_index, 0 ) ;
+		}
+		else if( variable == m_se_column_regex ) {
+			return m_ses( snp_index, 0 ) ;
+		}
+		else if( variable == "pval" ) {
+			return m_pvalues( snp_index ) ;
+		}
+		else if( variable == "gen_00" ) {
+			return m_sample_counts( snp_index, 2 ) ;
+		}
+		else if( variable == "gen_01" ) {
+			return m_sample_counts( snp_index, 3 ) ;
+		}
+		else if( variable == "gen_11" ) {
+			return m_sample_counts( snp_index, 4 ) ;
+		}
+		else if( variable == "gen_NULL" ) {
+			return m_sample_counts( snp_index, 5 ) ;
+		} else {
+			assert(0) ;
+		}
+	}
+}

ADDED   bingwa/src/ModelAveragingBayesFactorAnalysis.cpp
Index: bingwa/src/ModelAveragingBayesFactorAnalysis.cpp
==================================================================
--- bingwa/src/ModelAveragingBayesFactorAnalysis.cpp
+++ bingwa/src/ModelAveragingBayesFactorAnalysis.cpp
@@ -0,0 +1,190 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include "bingwa/BingwaComputation.hpp"
+#include "bingwa/ModelAveragingBayesFactorAnalysis.hpp"
+#include "bingwa/impl/impl.hpp"
+
+namespace bingwa {
+	ModelSpec::ModelSpec( std::string const& name, Covariance const& covariance, double weight ):
+		m_name( name ),
+		m_covariances( 1, covariance ),
+		m_weight( weight )
+	{}
+		
+	ModelSpec::ModelSpec( ModelSpec const& other ):
+		m_name( other.m_name ),
+		m_covariances( other.m_covariances ),
+		m_weight( other.m_weight )
+	{}
+
+	ModelSpec& ModelSpec::operator=( ModelSpec const& other ) {
+		m_name = other.m_name ;
+		m_covariances = other.m_covariances ;
+		m_weight = other.m_weight ;
+		return *this ;
+	}
+	
+	ModelAveragingBayesFactorAnalysis::UniquePtr ModelAveragingBayesFactorAnalysis::create() {
+		return UniquePtr( new ModelAveragingBayesFactorAnalysis ) ;
+	}
+
+	ModelAveragingBayesFactorAnalysis::ModelAveragingBayesFactorAnalysis():
+		m_prefix( "ModelAveragingBayesFactorAnalysis" ),
+		m_null_sd( 0.0 )
+	{}
+
+	ModelAveragingBayesFactorAnalysis::~ModelAveragingBayesFactorAnalysis() {}
+	
+	void ModelAveragingBayesFactorAnalysis::add_model( ModelSpec const& model_spec ) {
+		m_models.push_back( model_spec ) ;
+	}
+
+	void ModelAveragingBayesFactorAnalysis::set_filter( Filter filter ) {
+		m_filter = filter ;
+	}
+
+	void ModelAveragingBayesFactorAnalysis::set_null_sd( double sd ) {
+		assert( sd >= 0.0 ) ;
+		m_null_sd = sd ;
+	}
+
+	void ModelAveragingBayesFactorAnalysis::set_effect_parameter_names( bingwa::EffectParameterNamePack const& names ) {
+		m_effect_parameter_names = names ;
+	}
+
+	void ModelAveragingBayesFactorAnalysis::get_variables( boost::function< void ( std::string, std::string ) > callback ) const {
+		for( std::size_t i = 0; i < m_models.size(); ++i ) {
+			callback( m_models[i].name() + ":bf", "FLOAT" ) ;
+		}
+		
+		callback( "mean_bf", "FLOAT" ) ;
+		callback( "max_bf_model", "TEXT" ) ;
+		callback( "max_bf", "FLOAT" ) ;
+		callback( "best_posterior_model", "TEXT" ) ;
+		callback( "best_posterior", "FLOAT" ) ;
+		callback( "2nd_best_posterior_model", "TEXT" ) ;
+		callback( "2nd_best_posterior", "FLOAT" ) ;
+	}
+
+	void ModelAveragingBayesFactorAnalysis::operator()(
+		DataGetter const& data_getter,
+		ResultCallback callback
+	) {
+		std::size_t const N = data_getter.get_number_of_cohorts() ;
+		if( N == 0 ) {
+			return ;
+		}
+
+		Eigen::VectorXd betas ;
+		Eigen::MatrixXd covariance ;
+		Eigen::VectorXd non_missingness ;
+	
+		if(
+			!impl::get_betas_and_covariance_across_cohorts( data_getter, m_filter, betas, covariance, non_missingness, m_effect_parameter_names.size() )
+			|| non_missingness.sum() == 0
+		) {
+			return ;
+		}
+
+		Eigen::MatrixXd const nonmissingness_selector = impl::get_nonmissing_coefficient_selector( non_missingness ) ;
+		betas = nonmissingness_selector * betas ;
+		covariance = nonmissingness_selector * covariance * nonmissingness_selector.transpose() ;
+
+		Eigen::MatrixXd const null_prior = Eigen::MatrixXd::Identity( covariance.rows(), covariance.cols() ) * ( m_null_sd * m_null_sd ) ;
+
+		std::vector< double > bfs( m_models.size(), NA ) ;
+		std::vector< double > weighted_bfs( m_models.size(), NA ) ;
+		double total_weight = 0 ;
+		double mean_bf = 0 ;
+		double max_bf = -Infinity ;
+		std::size_t max_bf_i = m_models.size() ;
+
+		std::vector< std::size_t > best_posterior_models( std::min( std::size_t(2), m_models.size() ), m_models.size() ) ;
+		std::vector< double > best_weighted_bfs( std::min( std::size_t(2), m_models.size() ), -Infinity ) ;
+
+		for( std::size_t i = 0; i < m_models.size(); ++i ) {
+			double model_bf = 0 ;
+			for( std::size_t j = 0; j < m_models[i].size(); ++j ) {
+				Eigen::MatrixXd const prior = nonmissingness_selector * m_models[i].covariance(j) * nonmissingness_selector.transpose() ;
+				double bf = impl::compute_bayes_factor( prior, null_prior, covariance, betas ) ;
+				if( bf != bf ) {
+					bf = 1 ;
+				}
+				model_bf += bf ;
+			}
+			model_bf /= m_models[i].size() ;
+			double const weight = m_models[i].weight() ;
+			double const weighted_bf = weight * model_bf ;
+			total_weight += weight ;
+			mean_bf += weighted_bf ;
+
+			bfs[i] = model_bf ;
+			weighted_bfs[i] = weighted_bf ;
+
+			if( model_bf >= max_bf ) {
+				max_bf = model_bf ;
+				max_bf_i = i ;
+			}
+
+			for( std::size_t j = 0; j < best_weighted_bfs.size(); ++j ) {
+				// std::cerr << "weighted_bf = " << weighted_bf << ", best[0] = " << best_weighted_bfs[0] << ", best[1] = " << best_weighted_bfs[1] << ".\n" ;
+				if( weighted_bf > best_weighted_bfs[ j ]) {
+					std::rotate(
+						best_weighted_bfs.begin() + j,
+						best_weighted_bfs.begin() + best_weighted_bfs.size()-1,
+						best_weighted_bfs.end()
+					) ;
+					std::rotate(
+						best_posterior_models.begin() + j,
+						best_posterior_models.begin() + best_posterior_models.size() - 1,
+						best_posterior_models.end()
+					) ;
+					best_weighted_bfs[ j ] = weighted_bf ;
+					best_posterior_models[ j ] = i ;
+					break ;
+				}
+			}
+		}
+		
+		mean_bf /= total_weight ;
+
+		for( std::size_t i = 0; i < m_models.size(); ++i ) {
+			if( bfs[i] == bfs[i] ) {
+				callback( m_models[i].name() + ":bf", bfs[i] ) ;
+			} else {
+				callback( m_models[i].name() + ":bf", genfile::MissingValue() ) ;
+			}
+		}
+
+		callback( "mean_bf", mean_bf / total_weight ) ;
+		if( max_bf_i < m_models.size() ) {
+			callback( "max_bf", max_bf ) ;
+			callback( "max_bf_model", m_models[max_bf_i].name() ) ;
+		}
+		if( best_posterior_models[0] < m_models.size() ) {
+			callback( "best_posterior", (best_weighted_bfs[0] / total_weight) / mean_bf ) ;
+			callback( "best_posterior_model", m_models[ best_posterior_models[0] ].name() ) ;
+		}
+		if( best_posterior_models[1] < m_models.size() ) {
+			callback( "2nd_best_posterior", (best_weighted_bfs[1] / total_weight) / mean_bf ) ;
+			callback( "2nd_best_posterior_model", m_models[ best_posterior_models[1] ].name() ) ;
+		}
+	}
+
+	std::string ModelAveragingBayesFactorAnalysis::get_spec() const {
+		return "ModelAveragingBayesFactorAnalysis( " + m_name + " )" ;
+	}
+
+	std::string ModelAveragingBayesFactorAnalysis::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		return prefix + get_spec() ;
+	}
+	
+	std::vector< ModelAveragingBayesFactorAnalysis::ModelSpec > const&
+	ModelAveragingBayesFactorAnalysis::get_models() const { return m_models ; }
+}
+

ADDED   bingwa/src/MultivariateFixedEffectMetaAnalysis.cpp
Index: bingwa/src/MultivariateFixedEffectMetaAnalysis.cpp
==================================================================
--- bingwa/src/MultivariateFixedEffectMetaAnalysis.cpp
+++ bingwa/src/MultivariateFixedEffectMetaAnalysis.cpp
@@ -0,0 +1,154 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <utility>
+#include <Eigen/Core>
+#include "bingwa/BingwaComputation.hpp"
+#include "bingwa/MultivariateFixedEffectMetaAnalysis.hpp"
+
+// #define DEBUG_BINGWA 1
+
+namespace bingwa {
+	namespace {
+		bool default_filter( bingwa::BingwaComputation::DataGetter const& data_getter, int i ) {
+			return data_getter.is_non_missing( i ) && data_getter.is_trusted( i ) ;
+		}
+	}
+	MultivariateFixedEffectMetaAnalysis::MultivariateFixedEffectMetaAnalysis(
+		std::string const& name
+	):
+		m_name( name ),
+		m_prefix( name ),
+		m_filter( &default_filter )
+	{}
+
+	void MultivariateFixedEffectMetaAnalysis::set_filter( Filter filter ) {
+		m_filter = filter ;
+	}
+
+	void MultivariateFixedEffectMetaAnalysis::set_effect_parameter_names( bingwa::EffectParameterNamePack const& names ) {
+		m_effect_parameter_names = names ;
+	}
+
+	void MultivariateFixedEffectMetaAnalysis::get_variables( boost::function< void ( std::string, std::string ) > callback ) const {
+		std::size_t const numberOfEffects = m_effect_parameter_names.size() ;
+		callback( m_prefix + ":included_betas", "TEXT" ) ;
+		callback( m_prefix + ":A", "FLOAT" ) ;
+		callback( m_prefix + ":B", "FLOAT" ) ;
+		callback( m_prefix + ":AA", "FLOAT" ) ;
+		callback( m_prefix + ":AB", "FLOAT" ) ;
+		callback( m_prefix + ":BB", "FLOAT" ) ;
+		callback( m_prefix + ":N", "FLOAT" ) ;
+		if( numberOfEffects > 0 ) {
+			for( std::size_t i = 0; i < numberOfEffects; ++i ) {
+				//callback( m_prefix + ( boost::format( ":beta_%d" ) % (i+1)).str(), "FLOAT" ) ;
+				callback( m_prefix + ":" + m_effect_parameter_names.parameter_name(i), "FLOAT" ) ;
+			}
+			for( std::size_t i = 0; i < numberOfEffects; ++i ) {
+				callback( m_prefix + ":" + m_effect_parameter_names.se_name(i), "FLOAT" ) ;
+			}
+			for( std::size_t i = 0; i < numberOfEffects; ++i ) {
+				callback( m_prefix + ":" + m_effect_parameter_names.wald_pvalue_name(i), "FLOAT" ) ;
+			}
+			for( std::size_t i = 0; i < (numberOfEffects-1); ++i ) {
+				for( std::size_t j = i+1; j < numberOfEffects; ++j ) {
+					callback( m_prefix + ":" + m_effect_parameter_names.covariance_name(i,j), "FLOAT" ) ;
+				}
+			}
+		}
+		callback( m_prefix + ":pvalue", "FLOAT" ) ;
+	}
+
+	void MultivariateFixedEffectMetaAnalysis::operator()(
+		DataGetter const& data_getter,
+		ResultCallback callback
+	) {
+		std::size_t const numberOfEffects = m_effect_parameter_names.size() ;
+		if( data_getter.get_number_of_cohorts() == 0 || numberOfEffects == 0 ) {
+			return ;
+		}
+		
+		Eigen::VectorXd betas ;
+		Eigen::MatrixXd covariance ;
+		Eigen::VectorXd non_missingness ;
+		Eigen::VectorXd counts ;
+		
+		if(
+			impl::get_betas_and_covariance_across_cohorts( data_getter, m_filter, betas, covariance, non_missingness, numberOfEffects, impl::eByCohort )
+		) {
+			impl::get_total_counts( data_getter, m_filter, counts ) ;
+			callback( m_prefix + ":included_betas", impl::to_01_string( non_missingness ) ) ;
+			callback( m_prefix + ":A", counts(0) ) ;
+			callback( m_prefix + ":B", counts(1) ) ;
+			callback( m_prefix + ":AA", counts(2) ) ;
+			callback( m_prefix + ":AB", counts(3) ) ;
+			callback( m_prefix + ":BB", counts(4) ) ;
+			callback( m_prefix + ":N", counts.segment( 0, 5 ).sum() ) ;
+
+			if( non_missingness.sum() > 0 ) {
+				Eigen::MatrixXd nonmissingness_selector = impl::get_nonmissing_cohort_selector( non_missingness, data_getter.get_number_of_cohorts(), numberOfEffects ) ;
+	#if DEBUG_BINGWA
+				std::cerr << "MultivariateFixedEffectMetaAnalysis::operator(): pre-selector, N = " << data_getter.get_number_of_cohorts() << "\n"
+					<< "betas = " << betas.transpose() << ".\n"
+						<< "covariance = \n" << covariance << ".\n" ;
+	#endif
+
+				if( nonmissingness_selector.rows() > 0 ) {
+					betas = nonmissingness_selector * betas ;
+					covariance = nonmissingness_selector * covariance * nonmissingness_selector.transpose() ;
+
+					std::size_t const N = betas.size() / numberOfEffects ;
+		#if DEBUG_BINGWA
+					std::cerr << "post-selector, N = " << N << "\n"
+						<< "betas = " << betas.transpose() << ".\n" ;
+					std::cerr << "variance =\n" << impl::format_matrix( covariance ) << ".\n" ;
+		#endif
+					Eigen::MatrixXd metaVariance ;
+					Eigen::VectorXd metaBeta ;
+					double chi_squared = 0 ;
+					impl::compute_fixed_effect_meta_and_variance( covariance, betas, N, numberOfEffects, &metaBeta, &metaVariance, &chi_squared ) ;
+					double const pvalue = impl::compute_chisquared_pvalue( chi_squared, numberOfEffects ) ;
+
+		#if DEBUG_BINGWA
+					std::cerr << "metaBeta = " << metaBeta.transpose() << ".\n" ;
+					std::cerr << "metaVariance =\n" << metaVariance << ".\n" ;
+					std::cerr << "chi_squared =\n" << chi_squared << ".\n" ;
+					std::cerr << "pvalue =\n" << pvalue << ".\n" ;
+		#endif
+
+					for( std::size_t i = 0; i < numberOfEffects; ++i ) {
+						// callback( m_prefix + ( boost::format( ":beta_%d" ) % (i+1)).str(), metaBeta(i) ) ;
+						callback( m_prefix + ":" + m_effect_parameter_names.parameter_name(i), metaBeta(i) ) ;
+					}
+					for( std::size_t i = 0; i < numberOfEffects; ++i ) {
+						callback( m_prefix + ":" + m_effect_parameter_names.se_name(i), std::sqrt( metaVariance(i,i) ) ) ;
+					}
+					for( std::size_t i = 0; i < numberOfEffects; ++i ) {
+						callback(
+							m_prefix + ":" + m_effect_parameter_names.wald_pvalue_name(i),
+							impl::compute_normal_pvalue( metaBeta(i), metaVariance(i,i), impl::eBoth )
+						) ;
+					}
+					for( std::size_t i = 0; i < (numberOfEffects-1); ++i ) {
+						for( std::size_t j = i+1; j < numberOfEffects; ++j ) {
+							callback( m_prefix + ":" + m_effect_parameter_names.covariance_name(i,j), metaVariance(i,j) ) ;
+						}
+					}
+					callback( m_prefix + ":pvalue", pvalue ) ;
+				}
+			}
+		}
+	}
+		
+	std::string MultivariateFixedEffectMetaAnalysis::get_spec() const {
+		return "MultivariateFixedEffectMetaAnalysis( " + m_name + " )" ;
+	}
+
+	std::string MultivariateFixedEffectMetaAnalysis::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		return prefix + get_spec() ;
+	}
+}

ADDED   bingwa/src/PerCohortBayesFactor.cpp
Index: bingwa/src/PerCohortBayesFactor.cpp
==================================================================
--- bingwa/src/PerCohortBayesFactor.cpp
+++ bingwa/src/PerCohortBayesFactor.cpp
@@ -0,0 +1,106 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include "genfile/string_utils/string_utils.hpp"
+#include "bingwa/BingwaComputation.hpp"
+#include "bingwa/ModelAveragingBayesFactorAnalysis.hpp"
+#include "bingwa/PerCohortBayesFactor.hpp"
+#include "bingwa/impl/impl.hpp"
+
+namespace bingwa {
+	PerCohortBayesFactor::UniquePtr PerCohortBayesFactor::create(
+		std::vector< std::string > const& cohort_names,
+		ModelSpec const& model
+	) {
+		return PerCohortBayesFactor::UniquePtr(
+			new PerCohortBayesFactor( cohort_names, model )
+		) ;
+	}
+
+	PerCohortBayesFactor::PerCohortBayesFactor( std::vector< std::string > const& cohort_names, ModelSpec const& model ):
+		m_cohort_names( cohort_names ),
+		m_model( model ),
+		m_null_sd( 0.0 )
+	{}
+	
+	void PerCohortBayesFactor::add_variable( std::string const& variable ) {
+		m_extra_variables.insert( variable ) ;
+	}
+	
+	void PerCohortBayesFactor::set_effect_parameter_names( bingwa::EffectParameterNamePack const& names ) {
+		m_effect_parameter_names = names ;
+	}
+	
+	void PerCohortBayesFactor::get_variables( boost::function< void ( std::string, std::string ) > callback ) const {
+		using genfile::string_utils::to_string ;
+		
+		std::size_t const N = m_cohort_names.size() ;
+		for( std::size_t i = 0; i < N; ++i ) {
+			callback( m_cohort_names[ i ] + ":bf", "FLOAT" ) ;
+		}
+	}
+	
+	void PerCohortBayesFactor::operator()(
+		DataGetter const& data_getter,
+		ResultCallback callback
+	) {
+		std::size_t const N = data_getter.get_number_of_cohorts() ;
+		if( N == 0 ) {
+			return ;
+		}
+		Eigen::VectorXd betas ;
+		Eigen::MatrixXd covariance ;
+		Eigen::VectorXd non_missingness ;
+		Eigen::MatrixXd const null_prior = Eigen::MatrixXd::Identity( m_effect_parameter_names.size(), m_effect_parameter_names.size() ) * (m_null_sd * m_null_sd) ;
+		for( std::size_t i = 0; i < N; ++i ) {
+			bool const obtained = (
+				bingwa::impl::get_betas_and_covariance_for_cohort(
+					data_getter,
+					&bingwa::impl::basic_missingness_filter,
+					betas,
+					covariance,
+					non_missingness,
+					m_effect_parameter_names.size(),
+					i
+				) && ( non_missingness.sum() == m_effect_parameter_names.size() )
+			) ;
+
+			if( !obtained ) {
+				callback( m_cohort_names[i] + ":bf", genfile::MissingValue() ) ;
+			}
+			else {
+				double mean_bf = 0.0 ;
+				for( std::size_t model_i = 0; model_i < m_model.size(); ++model_i ) {
+					Eigen::MatrixXd const prior = m_model.covariance(model_i) ;
+#if DEBUG_BINGWA
+					std::cerr << "PRIOR = \n" << prior << ".\n" ;
+					std::cerr << "BETAs = \n" << betas.transpose() << ".\n" ;
+					std::cerr << "NONMISSINGNESS = \n" << non_missingness << ".\n" ;
+					std::cerr << "COV = \n" << covariance << ".\n" ;
+#endif
+					double bf = bingwa::impl::compute_bayes_factor( prior, null_prior, covariance, betas ) ;
+					if( bf != bf ) {
+						bf = 1 ;
+					}
+					mean_bf += bf ;
+				}
+				mean_bf /= m_model.size() ;
+				callback( m_cohort_names[i] + ":bf", mean_bf ) ;
+			}
+		}
+	}
+	
+	std::string PerCohortBayesFactor::get_spec() const {
+		return "PerCohortBayesFactor" ;
+	}
+	
+	std::string PerCohortBayesFactor::get_summary(
+		std::string const& prefix,
+		std::size_t column_width
+	) const {
+		return prefix + get_spec() ;
+	}
+}

ADDED   bingwa/src/PerCohortCountsReporter.cpp
Index: bingwa/src/PerCohortCountsReporter.cpp
==================================================================
--- bingwa/src/PerCohortCountsReporter.cpp
+++ bingwa/src/PerCohortCountsReporter.cpp
@@ -0,0 +1,73 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <memory>
+#include <string>
+#include <vector>
+#include <boost/function.hpp>
+#include <boost/foreach.hpp>
+#include <Eigen/Core>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/string_utils.hpp"
+#include "appcontext/OptionProcessor.hpp"
+#include "bingwa/BingwaComputation.hpp"
+#include "bingwa/PerCohortCountsReporter.hpp"
+
+namespace bingwa {
+	PerCohortCountsReporter::PerCohortCountsReporter(
+		std::vector< std::string > const& cohort_names,
+		std::vector< std::vector< std::string > > const& variables
+	):
+		m_cohort_names( cohort_names ),
+		m_variables( variables )
+	{}
+	
+	void PerCohortCountsReporter::set_effect_parameter_names( EffectParameterNamePack const& names ) {
+	}
+	
+	void PerCohortCountsReporter::get_variables( boost::function< void ( std::string, std::string ) > callback ) const {
+		using genfile::string_utils::to_string ;
+		
+		std::size_t const N = m_cohort_names.size() ;
+		for( std::size_t i = 0; i < N; ++i ) {
+			std::string prefix = m_cohort_names[ i ] + ":" ;
+			BOOST_FOREACH( std::string const& variable, m_variables[i] ) {
+				callback( prefix + variable, "NULL" ) ;
+			}
+		}
+	}
+	
+	void PerCohortCountsReporter::operator()(
+		DataGetter const& data_getter,
+		ResultCallback callback
+	) {
+		std::size_t const N = m_cohort_names.size() ;
+		for( std::size_t i = 0; i < N; ++i ) {
+			if( data_getter.is_non_missing( i ) ) {
+				Eigen::VectorXd counts ;
+				
+				using genfile::string_utils::to_string ;
+				std::string prefix = m_cohort_names[ i ] + ":" ;
+				{
+					std::string value ;
+					BOOST_FOREACH( std::string const& variable, m_variables[i] ) {
+						data_getter.get_variable( variable, i, &value ) ;
+						callback( prefix + variable, value ) ;
+					}
+				}
+			}
+		}
+	}
+	
+	std::string PerCohortCountsReporter::get_spec() const {
+		return "PerCohortCountsReporter" ;
+	}
+	
+	std::string PerCohortCountsReporter::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		return prefix + get_spec() ;
+	}
+}

ADDED   bingwa/src/PerCohortValueReporter.cpp
Index: bingwa/src/PerCohortValueReporter.cpp
==================================================================
--- bingwa/src/PerCohortValueReporter.cpp
+++ bingwa/src/PerCohortValueReporter.cpp
@@ -0,0 +1,187 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <memory>
+#include <string>
+#include <vector>
+#include <boost/function.hpp>
+#include <boost/foreach.hpp>
+#include <Eigen/Core>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/string_utils.hpp"
+#include "appcontext/OptionProcessor.hpp"
+#include "bingwa/BingwaComputation.hpp"
+#include "bingwa/PerCohortValueReporter.hpp"
+
+namespace bingwa {
+	PerCohortValueReporter::PerCohortValueReporter(
+		std::vector< std::string > const& cohort_names,
+		std::vector< std::vector< std::string > > const& cohort_variables,
+		bool report_counts
+	):
+		m_cohort_names( cohort_names ),
+		m_variables( cohort_variables ),
+		m_report_counts( report_counts )
+	{
+		std::vector< std::string > defaults ;
+		defaults.push_back( "A" ) ;
+		defaults.push_back( "B" ) ;
+		defaults.push_back( "AA" ) ;
+		defaults.push_back( "AB" ) ;
+		defaults.push_back( "BB" ) ;
+		defaults.push_back( "NULL" ) ;
+		defaults.push_back( "N" ) ;
+		defaults.push_back( "B_allele_frequency" ) ;
+		defaults.push_back( "trusted" ) ;
+		defaults.push_back( "pvalue" ) ;
+		for( std::size_t cohort = 0; cohort < m_variables.size(); ++cohort ) {
+			for( std::size_t j = 0; j < defaults.size(); ++j ) {
+				std::vector< std::string >::iterator where = std::find( m_variables[cohort].begin(), m_variables[cohort].end(), defaults[j] ) ;
+				if( where != m_variables[cohort].end() ) {
+					m_variables[cohort].erase( where ) ;
+				}
+			}
+		}
+	}
+	
+	void PerCohortValueReporter::set_effect_parameter_names( EffectParameterNamePack const& names ) {
+		m_effect_parameter_names = names ;
+	}
+	
+	void PerCohortValueReporter::get_variables( boost::function< void ( std::string, std::string ) > callback ) const {
+		using genfile::string_utils::to_string ;
+		
+		std::size_t const N = m_cohort_names.size() ;
+		for( std::size_t cohort = 0; cohort < N; ++cohort ) {
+			std::string prefix = m_cohort_names[ cohort ] + ":" ;
+
+			if( m_report_counts ) {
+				callback( prefix + "A", "FLOAT" ) ;
+				callback( prefix + "B", "FLOAT" ) ;
+				callback( prefix + "AA", "FLOAT" ) ;
+				callback( prefix + "AB", "FLOAT" ) ;
+				callback( prefix + "BB", "FLOAT" ) ;
+				callback( prefix + "NULL", "FLOAT" ) ;
+			}
+
+			callback( prefix + "N", "FLOAT" ) ;
+			callback( prefix + "B_allele_frequency", "FLOAT" ) ;
+			
+			BOOST_FOREACH( std::string const& variable, m_variables[cohort] ) {
+				callback( prefix + variable, "NULL" ) ;
+			}
+
+			callback( prefix + "trusted", "INTEGER" ) ;
+
+			for( std::size_t i = 0; i < m_effect_parameter_names.size(); ++i ) {
+//				callback( prefix + "beta_" + to_string( i+1 ) ) ;
+//				callback( prefix + "se_" + to_string( i+1 ) ) ;
+				callback( prefix + m_effect_parameter_names.parameter_name(i), "FLOAT" ) ;
+				callback( prefix + m_effect_parameter_names.se_name(i), "FLOAT" ) ;
+			}
+			for( std::size_t i = 0; i < m_effect_parameter_names.size(); ++i ) {
+				for( std::size_t j = i+1; j < m_effect_parameter_names.size(); ++j ) {
+					callback( prefix + m_effect_parameter_names.covariance_name(i,j), "FLOAT" ) ;
+				}
+			}
+			callback( prefix + "pvalue", "FLOAT" ) ;
+			for( std::size_t k = 0; k < m_variables[cohort].size(); ++k ) {
+				callback( prefix + m_variables[cohort][k], "NULL" ) ;
+			}
+		}
+	}
+	
+	void PerCohortValueReporter::operator()(
+		DataGetter const& data_getter,
+		ResultCallback callback
+	) {
+		std::size_t const N = m_cohort_names.size() ;
+		for( std::size_t i = 0; i < N; ++i ) {
+			if( data_getter.is_non_missing( i ) ) {
+				Eigen::VectorXd betas ;
+				Eigen::VectorXd ses ;
+				Eigen::VectorXd covariance ;
+				Eigen::VectorXd counts ;
+				double pvalue ;
+				double info ;
+				data_getter.get_betas( i, &betas ) ;
+				data_getter.get_ses( i, &ses ) ;
+				data_getter.get_covariance_upper_triangle( i, &covariance ) ;
+				data_getter.get_pvalue( i, &pvalue ) ;
+				data_getter.get_info( i, &info ) ;
+				data_getter.get_counts( i, &counts ) ;
+
+				using genfile::string_utils::to_string ;
+				std::string prefix = m_cohort_names[ i ] + ":" ;
+
+				if( m_report_counts ) {
+					callback( prefix + "A", counts(0) ) ;
+					callback( prefix + "B", counts(1) ) ;
+					callback( prefix + "AA", counts(2) ) ;
+					callback( prefix + "AB", counts(3) ) ;
+					callback( prefix + "BB", counts(4) ) ;
+					callback( prefix + "NULL", counts(5) ) ;
+				}
+
+				callback( prefix + "N", counts.segment(0,5).sum() ) ;
+				
+				double B_allele_count = 0 ;
+				double total_allele_count = 0 ;
+				if( counts(0) == counts(0) ) {
+					B_allele_count += counts(1) ;
+					total_allele_count += counts(0) + counts(1) ;
+				}
+				if( counts(2) == counts(2) ) {
+					B_allele_count += counts(3) + 2 * counts(4) ;
+					total_allele_count += 2.0 * ( counts(2) + counts(3) + counts(4) ) ;
+				}
+				callback( prefix + "B_allele_frequency", B_allele_count / total_allele_count ) ;
+				{
+					std::string value ;
+					BOOST_FOREACH( std::string const& variable, m_variables[i] ) {
+						data_getter.get_variable( variable, i, &value ) ;
+						try {
+							callback( prefix + variable, genfile::string_utils::to_repr< double >( value ) ) ;
+						} catch( ... ) {
+							callback( prefix + variable, value ) ;
+						}
+					}
+				}
+				
+				callback( prefix + "trusted", genfile::VariantEntry::Integer( data_getter.is_trusted( i ) )) ;
+				
+				assert( betas.size() == ses.size() ) ;
+				assert( covariance.size() == ( betas.size() - 1 ) * betas.size() / 2 ) ;
+				for( int j = 0; j < betas.size(); ++j ) {
+//					callback( prefix + "beta_" + to_string( j+1 ), betas(j) ) ;
+					callback( prefix + m_effect_parameter_names.parameter_name(j), betas(j) ) ;
+				}
+				for( int j = 0; j < betas.size(); ++j ) {
+					callback( prefix + m_effect_parameter_names.se_name(j), ses(j) ) ;
+				}
+				{
+					int index = 0 ;
+					for( int j = 0; j < betas.size(); ++j ) {
+						for( int k = j+1; k < betas.size(); ++k, ++index ) {
+							callback( prefix + m_effect_parameter_names.covariance_name(j,k), covariance( index ) ) ;
+						}
+					}
+					assert( index == covariance.size() ) ;
+				}
+				callback( prefix + "pvalue", pvalue ) ;
+			}
+		}
+	}
+	
+	std::string PerCohortValueReporter::get_spec() const {
+		return "PerCohortValueReporter" ;
+	}
+	
+	std::string PerCohortValueReporter::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		return prefix + get_spec() ;
+	}
+}

ADDED   bingwa/src/SNPTESTResults.cpp
Index: bingwa/src/SNPTESTResults.cpp
==================================================================
--- bingwa/src/SNPTESTResults.cpp
+++ bingwa/src/SNPTESTResults.cpp
@@ -0,0 +1,341 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <algorithm>
+#include <boost/regex.hpp>
+#include <boost/format.hpp>
+#include "genfile/Error.hpp"
+#include "genfile/string_utils/string_utils.hpp"
+#include "bingwa/SNPTESTResults.hpp"
+#include "bingwa/EffectParameterNamePack.hpp"
+
+namespace bingwa {
+	SNPTESTResults::SNPTESTResults(
+		genfile::VariantIdentifyingDataTest::UniquePtr test,
+		boost::optional< genfile::Chromosome > const chromosome_hint
+	):
+	 	m_exclusion_test( test ),
+		m_beta_column_regex( ".*_beta_<i>($|[^0-9].*)" ),
+		m_chromosome_hint( chromosome_hint )
+	{}
+
+	std::string SNPTESTResults::get_summary( std::string const& prefix, std::size_t target_column ) const {
+		return prefix + "SNPTEST " + FlatFileFrequentistGenomeWideAssociationResults::get_summary( "", target_column ) ;
+	}
+
+	void SNPTESTResults::set_effect_size_column_regex( std::string const& beta_column_regex ) {
+	//	m_beta_column_regex = beta_column_regex ;
+	}
+
+	EffectParameterNamePack SNPTESTResults::get_effect_parameter_names() const {
+		return EffectParameterNamePack(
+			m_beta_columns,
+			m_se_columns,
+			m_cov_columns
+		) ;
+	}
+
+	namespace impl {
+		boost::optional< SNPTESTResults::ColumnSpec > get_matching_name(
+			std::vector< std::string > names,
+			boost::regex const& regex,
+			bool required,
+			std::string const& type
+		) {
+			boost::optional< SNPTESTResults::ColumnSpec > result ;
+			std::size_t i = 0 ;
+			for( i = 0; i < names.size(); ++i ) {
+				if( boost::regex_match( names[ i ], regex ) ) {
+					break ;
+				}
+			}
+			if( i < names.size() ) {
+				result = SNPTESTResults::ColumnSpec( names[i], regex, i, required, type ) ;
+			}
+			return result ;
+		}
+	
+		void insert_if_matched(
+			std::vector< std::string > names,
+			boost::regex const& regex,
+			std::string const& type,
+			std::vector< SNPTESTResults::ColumnSpec >* result
+		) {
+			assert( result ) ;
+			boost::optional< SNPTESTResults::ColumnSpec > matched = get_matching_name( names, regex, false, type ) ;
+			if( matched ) {
+				if( std::find( result->begin(), result->end(), static_cast< SNPTESTResults::ColumnSpec const >( matched.get() ) ) == result->end() ) {
+					result->push_back( matched.get() ) ;
+				}
+			}
+		}
+
+		void insert_matched(
+			std::vector< std::string > names,
+			boost::regex const& regex,
+			std::string const& type,
+			std::vector< SNPTESTResults::ColumnSpec >* result
+		) {
+			assert( result ) ;
+			boost::optional< SNPTESTResults::ColumnSpec > matched = get_matching_name( names, regex, true, type ) ;
+			if( matched ) {
+				if( std::find( result->begin(), result->end(), matched.get()) == result->end() ) {
+					result->push_back( matched.get() ) ;
+				}
+			} else {
+				std::cerr << "NAME: " << names[0] << "\n" ;
+				throw genfile::BadArgumentError(
+					"impl::insert_matched()",
+					"names",
+					( boost::format( "No name matched \"%s\"" ) % regex.str() ).str()
+				) ;
+			}
+		}
+	}
+
+
+	SNPTESTResults::DesiredColumns SNPTESTResults::setup_columns( std::vector< std::string > const& column_names ) {
+		using namespace genfile::string_utils ;
+		using boost::regex ;
+		DesiredColumns result ;
+	
+		{
+			regex unwanted_column_details( "^.*(bayesian|frequentist)_(add|dom|het|gen|rec|het[+]hom)(_newml|ml|score|em|threshhold|expected)*_" ) ;
+
+			std::vector< std::size_t > beta_indices ;
+			for( std::size_t i = 0; i < 1000; ++i ) {
+				regex const beta_regex = regex( replace_all( m_beta_column_regex, "<i>", to_string(i) ) ) ;
+				regex const se_regex = regex( replace_all( replace_all( m_beta_column_regex, "<i>", to_string(i) ), "_beta", "_se" ) ) ;
+
+				boost::optional< ColumnSpec > matched_beta_column = impl::get_matching_name( column_names, beta_regex, true, "beta" ) ;
+				if( matched_beta_column ) {
+					boost::optional< ColumnSpec > matched_se_column = impl::get_matching_name( column_names, se_regex, true, "se" ) ;
+					if( !matched_se_column ) {
+						throw genfile::BadArgumentError(
+							"SNPTESTResults::setup_columns()",
+							"column_names",
+							( boost::format( "No column matching \"%s\" although one matches \"%s\"." ) % se_regex % beta_regex ).str()
+						) ;
+					}
+				
+					matched_beta_column->set_simplified_name(
+						boost::regex_replace( matched_beta_column->name(), unwanted_column_details, "" )
+					) ;
+					matched_se_column->set_simplified_name(
+						boost::regex_replace( matched_se_column->name(), unwanted_column_details, "" )
+					) ;
+
+					result.push_back( *matched_beta_column ) ;
+					result.push_back( *matched_se_column ) ;
+					m_beta_columns.push_back( matched_beta_column->simplified_name() ) ;
+					m_se_columns.push_back( matched_se_column->simplified_name() ) ;
+					beta_indices.push_back( i ) ;
+				}
+			}
+	
+			for( std::size_t i = 0; i < beta_indices.size(); ++i ) {
+				for( std::size_t j = i+1; j < beta_indices.size(); ++j ) {
+					std::string const cov_regex = replace_all(
+						replace_all( m_beta_column_regex, "<i>", to_string( beta_indices[i] ) + "," + to_string( beta_indices[j] ) ),
+						"_beta",
+						"_cov"
+					) ;
+					boost::optional< ColumnSpec > matched_cov_column = impl::get_matching_name( column_names, regex( cov_regex ), true, "cov" ) ;
+					if( !matched_cov_column ) {
+						throw genfile::BadArgumentError(
+							"SNPTESTResults::setup_columns()",
+							"column_names",
+							( boost::format( "No column matching \"%s\"." ) % cov_regex ).str()
+						) ;
+					}
+					matched_cov_column->set_simplified_name(
+						boost::regex_replace( matched_cov_column->name(), unwanted_column_details, "" )
+					) ;
+					result.push_back( *matched_cov_column ) ;
+					m_cov_columns.push_back( matched_cov_column->simplified_name() ) ;
+				}
+			}
+		
+			if( m_beta_columns.size() == 0 ) {
+				throw genfile::BadArgumentError(
+					"SNPTESTResults::setup_columns()",
+					"column_names",
+					( boost::format( "No column matching beta regex (\"%s\") could be found." ) % m_beta_column_regex ).str()
+				) ;
+			}
+		}
+
+		{
+			regex const pvalue_regex( replace_all( m_beta_column_regex, "_beta_<i>", ".*(bayesian|frequentist)_(add|dom|het|gen|rec|het[+]hom)(_ml|_em|_score|_threshhold|_lrt)*_pvalue" ) ) ;
+			boost::optional< ColumnSpec > matched_pvalue_column = impl::get_matching_name( column_names, pvalue_regex, true, "pvalue" ) ;
+			if( !matched_pvalue_column ) {
+				throw genfile::BadArgumentError(
+					"SNPTESTResults::setup_columns()",
+					"column_names",
+					( boost::format( "No column matching overall pvalue regex (\"%s\") could be found." ) % pvalue_regex.str() ).str()
+				) ;
+			}
+			result.push_back( matched_pvalue_column.get() ) ;
+			m_pvalue_column = matched_pvalue_column.get().name() ;
+		}
+
+#if 0
+		{
+			regex const info_regex( "(all_)?info" ) ;
+			boost::optional< ColumnSpec > matched_info_column = impl::get_matching_name( column_names, info_regex, true, "info" ) ;
+			if( !matched_info_column ) {
+				throw genfile::BadArgumentError(
+					"SNPTESTResults::setup_columns()",
+					"column_names",
+					( boost::format( "No column matching overall info regex (\"%s\") could be found." ) % info_regex.str() ).str()
+				) ;
+			}
+			result.push_back( matched_info_column.get() ) ;
+			m_info_column = matched_info_column.get().name() ;
+		}
+#endif		
+		impl::insert_matched( column_names, regex( "all_AA" ), "counts", &result ) ;
+		impl::insert_matched( column_names, regex( "all_AB" ), "counts", &result ) ;
+		impl::insert_matched( column_names, regex( "all_BB" ), "counts", &result ) ;
+		impl::insert_if_matched( column_names, regex( "all_A" ), "counts", &result ) ;
+		impl::insert_if_matched( column_names, regex( "all_B" ), "counts", &result ) ;
+		impl::insert_matched( column_names, regex( "all_NULL" ), "counts", &result ) ;
+
+		// Remove anything specific from extra variables.
+		for( std::size_t i = 0; i < result.size(); ++i ) {
+			std::set< std::string >::iterator where = m_variables.find( result[i].name() ) ;
+			if( where != m_variables.end() ) {
+				m_variables.erase( where ) ;
+			}
+		}
+
+		impl::insert_if_matched( column_names, regex( "cases_AA" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "cases_AB" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "cases_BB" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "cases_A" ), "counts", &result ) ;
+		impl::insert_if_matched( column_names, regex( "cases_B" ), "counts", &result ) ;
+		impl::insert_if_matched( column_names, regex( "cases_NULL" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "controls_AA" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "controls_AB" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "controls_BB" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "controls_A" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "controls_B" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "controls_NULL" ), "extra", &result ) ;
+		impl::insert_if_matched( column_names, regex( "comment" ), "extra", &result ) ;
+
+		for( std::set< std::string >::const_iterator i = m_variables.begin(); i != m_variables.end(); ++i ) {
+			impl::insert_matched( column_names, regex( *i ), "extra", &result ) ;
+		}
+	
+		return result ;
+	}
+
+	bool SNPTESTResults::read_snp( statfile::BuiltInTypeStatSource& source, genfile::SNPIdentifyingData& snp ) const {
+		source >> snp.SNPID() >> snp.rsid() >> snp.position().chromosome() >> snp.position().position() >> snp.first_allele() >> snp.second_allele() ;
+		if( m_chromosome_hint && snp.get_position().chromosome() == genfile::Chromosome() ) {
+			snp.position().chromosome() = *m_chromosome_hint ;
+		}
+		return source ;
+	}
+
+	bool SNPTESTResults::check_if_snp_accepted( std::size_t i ) const {
+		return ( (!m_exclusion_test.get()) || m_exclusion_test->operator()( m_snps[ i ] ) ) ;
+	}
+
+	void SNPTESTResults::store_value(
+		int snp_index,
+		std::string const& variable,
+		std::string const& value
+	) {
+		using genfile::string_utils::to_repr ;
+		bool matched = false ;
+		double const NA = std::numeric_limits< double >::quiet_NaN() ;
+	
+		for( std::size_t i = 0; !matched && i < m_beta_columns.size(); ++i ) {
+			if( variable == m_beta_columns[i] ) {
+				m_betas( snp_index, i ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+				matched = true ;
+			} else if( variable == m_se_columns[i] ) {
+				if( value == "NA" ) {
+					m_ses( snp_index, i ) = NA ;
+				} else {
+					double se = to_repr< double >( value ) ;
+					// To avoid issues with non-negative definite matrices,
+					// we need to ensure covariance is not larger than possible given sds.
+					// In practice the sds we read here are rounded.  We assume they are accurate to 6dps
+					// and act conservatively by adding a small epsilon to each sd in the 5th significant digit.
+					double const epsilon = 5 * std::pow(10,(std::log10(std::ceil(se))-5)) ;
+					m_ses( snp_index, i ) = se + epsilon ;
+				}	
+				matched = true ;
+			}
+		}
+		for( std::size_t i = 0; !matched && i < m_cov_columns.size(); ++i ) {
+			if( variable == m_cov_columns[i] ) {
+				m_covariance( snp_index, i ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+				matched = true ;
+			}
+		}
+
+		if( matched ) {
+			return ;
+		}
+		if( variable == m_pvalue_column ) {
+			m_pvalues( snp_index ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "all_A" ) {
+			m_sample_counts( snp_index, 0 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "all_B" ) {
+			m_sample_counts( snp_index, 1 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "all_AA" ) {
+			m_sample_counts( snp_index, 2 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "all_AB" ) {
+			m_sample_counts( snp_index, 3 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "all_BB" ) {
+			m_sample_counts( snp_index, 4 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( variable == "all_NULL" ) {
+			m_sample_counts( snp_index, 5 ) = ( value == "NA" ? NA: to_repr< double >( value ) ) ;
+		}
+		else if( m_variables.find( variable ) != m_variables.end() ) {
+			m_extra_variable_storage[ variable ][ snp_index ] = value ;
+		}
+	}
+	
+	genfile::VariantEntry SNPTESTResults::get_value( std::size_t snp_index, std::string const& variable ) const {
+		if( variable == m_pvalue_column ) {
+			return m_pvalues( snp_index ) ;
+		}
+		else if( variable == "all_A" ) {
+			return m_sample_counts( snp_index, 0 ) ;
+		}
+		else if( variable == "all_B" ) {
+			return m_sample_counts( snp_index, 1 ) ;
+		}
+		else if( variable == "all_AA" ) {
+			return m_sample_counts( snp_index, 2 ) ;
+		}
+		else if( variable == "all_AB" ) {
+			return m_sample_counts( snp_index, 3 ) ;
+		}
+		else if( variable == "all_BB" ) {
+			return m_sample_counts( snp_index, 4 ) ;
+		}
+		else if( variable == "all_NULL" ) {
+			return m_sample_counts( snp_index, 5 ) ;
+		}
+		else {
+			ExtraVariables::const_iterator where = m_extra_variable_storage.find( variable ) ;
+			assert( where != m_extra_variable_storage.end() ) ;
+			return where->second[ snp_index ] ;
+		}
+	}
+	
+}

ADDED   bingwa/src/impl/impl.cpp
Index: bingwa/src/impl/impl.cpp
==================================================================
--- bingwa/src/impl/impl.cpp
+++ bingwa/src/impl/impl.cpp
@@ -0,0 +1,450 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <Eigen/Core>
+#include <Eigen/Cholesky>
+#include <Eigen/LU>
+#include "bingwa/special_values.hpp"
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <bingwa/impl/impl.hpp>
+
+namespace bingwa {
+	namespace impl {
+		bool basic_missingness_filter( bingwa::BingwaComputation::DataGetter const& data_getter, int i ) {
+			return data_getter.is_non_missing( i ) ;
+		}
+		
+		bool basic_trust_filter( bingwa::BingwaComputation::DataGetter const& data_getter, int i ) {
+			return data_getter.is_non_missing( i ) && data_getter.is_trusted( i ) ;
+		}
+		
+		bool single_population_filter( bingwa::BingwaComputation::DataGetter const& data_getter, int i, int population ) {
+			return ( i == population ) ;
+		}
+		
+		bool get_betas_and_ses_for_cohort(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& betas,
+			Eigen::VectorXd& ses,
+			Eigen::VectorXd& non_missingness
+		) {
+			std::size_t N = data_getter.get_number_of_cohorts() ;
+			betas.resize( N ) ;
+			ses.resize( N ) ;
+			non_missingness.resize( 2 * N ) ;
+			for( std::size_t i = 0; i < N; ++i ) {
+				non_missingness( i ) = filter( data_getter, i ) ? 1.0 : 0.0 ;
+
+				if( non_missingness( i )) {
+					Eigen::VectorXd data ;
+					data_getter.get_betas( i, &data ) ;
+					if( data.size() != 1 ) {
+						return false ;
+					}
+					betas(i) = data(0) ;
+
+					data_getter.get_ses( i, &data ) ;
+					if( data.size() != 1 ) {
+						return false ;
+					}
+					ses(i) = data(0) ;
+					
+					if( betas(i) != betas(i) || ses(i) != ses(i) ) {
+						non_missingness(i) = 0 ;
+					}
+				}
+			}
+			return true ;
+		}
+
+		bool get_betas_and_ses_one_per_cohort(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& betas,
+			Eigen::VectorXd& ses,
+			Eigen::VectorXd& non_missingness
+		) {
+			std::size_t N = data_getter.get_number_of_cohorts() ;
+			betas.resize( N ) ;
+			ses.resize( N ) ;
+			non_missingness.resize( 2 * N ) ;
+			for( std::size_t i = 0; i < N; ++i ) {
+				non_missingness( i ) = filter( data_getter, i ) ? 1.0 : 0.0 ;
+
+				if( non_missingness( i )) {
+					Eigen::VectorXd data ;
+					data_getter.get_betas( i, &data ) ;
+					if( data.size() != 1 ) {
+						return false ;
+					}
+					betas(i) = data(0) ;
+
+					data_getter.get_ses( i, &data ) ;
+					if( data.size() != 1 ) {
+						return false ;
+					}
+					ses(i) = data(0) ;
+					
+					if( betas(i) != betas(i) || ses(i) != ses(i) ) {
+						non_missingness(i) = 0 ;
+					}
+				}
+			}
+			return true ;
+		}
+		
+		// Betas from each study are assumed to come in the same order.
+		// Covariances in each study are assumed to reflect the upper triangle of covariances
+		// and come in the order cov_1,2 cov_1,3, ..., cov_2,3, cov_2,4, ...
+		bool get_betas_and_covariance_for_cohort(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& betas,
+			Eigen::MatrixXd& covariance,
+			Eigen::VectorXd& non_missingness,
+			int const numberOfEffects,
+			std::size_t cohort
+		) {
+			std::size_t N = data_getter.get_number_of_cohorts() ;
+			assert( cohort < N ) ;
+			betas.setZero( numberOfEffects ) ;
+			non_missingness.setZero( numberOfEffects ) ;
+			covariance.setZero( numberOfEffects, numberOfEffects ) ;
+
+			if( filter( data_getter, cohort ) ) {
+				Eigen::VectorXd this_betas, this_ses, this_covariance ;
+				data_getter.get_betas( cohort, &this_betas ) ;
+				data_getter.get_ses( cohort, &this_ses ) ;
+				data_getter.get_covariance_upper_triangle( cohort, &this_covariance ) ;
+				if(
+					this_betas.size() != numberOfEffects
+					||
+					this_ses.size() != numberOfEffects
+					||
+					this_covariance.size() != ((numberOfEffects-1) * numberOfEffects / 2 ) ) {
+					return false ;
+				}
+				if( this_betas.sum() == this_betas.sum() && this_covariance.sum() == this_covariance.sum() ) {
+					betas = this_betas ;
+					int covariance_i = 0 ;
+					for( std::size_t i = 0; i < std::size_t( numberOfEffects ); ++i ) {
+						covariance( i, i ) = this_ses(i) * this_ses(i) ;
+						for( std::size_t j = i+1; j < std::size_t( numberOfEffects ); ++j ) {
+							covariance( j, i ) = covariance( i, j ) = this_covariance( covariance_i++ );
+						}
+					}
+					non_missingness.setConstant( 1 ) ;
+				}
+			}
+			return true ;
+		}
+
+		void get_total_counts(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& counts
+		) {
+			counts.setZero( 6 ) ;
+			std::size_t N = data_getter.get_number_of_cohorts() ;
+			for( std::size_t i = 0; i < N; ++i ) {
+				if( filter( data_getter, i ) ) {
+					Eigen::VectorXd this_counts ;
+					data_getter.get_counts( i, &this_counts ) ;
+					counts += this_counts ;
+				}
+			}
+		}
+
+		// Read betas and ses for all cohorts into an output vector and matrix,
+		// along with an indicator of non-missingness.
+		// The layout depends on the `layout` argument:
+		// If layout == eByBeta then all beta_1's go in one contiguous block,
+		// followed by all beta_2's, etc.
+		// If layout == eByPopulation then beta_1, 2, etc. for population 1 go in one block,
+		// followed by beta_1, 2 etc for population 2.
+		// If there is only one beta both layouts are the same
+		//
+		// Betas from each study are assumed to come in the same order.
+		// Covariances in each study are assumed to reflect the upper triangle of covariances
+		// and come in the order cov_1,2 cov_1,3, ..., cov_2,3, cov_2,4, ...
+		bool get_betas_and_covariance_across_cohorts(
+			bingwa::BingwaComputation::DataGetter const& data_getter,
+			bingwa::BingwaComputation::Filter filter,
+			Eigen::VectorXd& betas,
+			Eigen::MatrixXd& covariance,
+			Eigen::VectorXd& non_missingness,
+			int const numberOfEffects,
+			Layout const layout
+		) {
+			std::size_t N = data_getter.get_number_of_cohorts() ;
+
+			betas.setConstant( numberOfEffects*N, 0 ) ;
+			non_missingness.setConstant( numberOfEffects*N, 0 ) ;
+			covariance.setZero( numberOfEffects*N, numberOfEffects*N ) ;
+
+			for( std::size_t i = 0; i < N; ++i ) {
+				if( filter( data_getter, i ) ) {
+					Eigen::VectorXd this_betas, this_ses, this_covariance ;
+					data_getter.get_betas( i, &this_betas ) ;
+					data_getter.get_ses( i, &this_ses ) ;
+					data_getter.get_covariance_upper_triangle( i, &this_covariance ) ;
+					if( this_betas.size() != numberOfEffects || this_ses.size() != numberOfEffects || this_covariance.size() != ((numberOfEffects-1) * numberOfEffects / 2 ) ) {
+						return false ;
+					}
+					int cov_i = 0 ;
+					for( int j = 0; j < numberOfEffects; ++j ) {
+						int const index = (layout == eByBeta ) ? ((j*N)+i) : ((numberOfEffects*i)+j) ;
+						// To avoid NaNs propagating through downstream computations,
+						// we convert NAs to zero values and return missingness information in
+						// the non_missingness vector.
+						if( this_betas(j) == this_betas(j) && this_ses(j) == this_ses(j) ) {
+							non_missingness( index ) = 1 ;
+							betas( index ) = this_betas(j) ;
+							covariance( index, index ) = this_ses(j) * this_ses(j) ;
+							for( int k = (j+1); k < numberOfEffects; ++k, ++cov_i ) {
+								int const index2 = (layout == eByBeta) ? ((k*N)+i) : ((numberOfEffects*i)+k) ;
+								covariance( index, index2 ) = covariance( index2, index ) = this_covariance( cov_i ) ;
+							}
+						} else {
+							cov_i += numberOfEffects - j - 1 ;
+						}
+					}
+				}
+			}
+			return true ;
+		}
+
+		std::string serialise( Eigen::VectorXd const& vector ) {
+			std::ostringstream ostr ;
+			for( int i = 0; i < vector.size(); ++i ) {
+				if( i > 0 ) {
+					ostr << "," ;
+				}
+				if( vector(i) == vector(i) ) {
+					ostr << vector(i) ;
+				} else {
+					ostr << "NA" ;
+				}
+			}
+			return ostr.str() ;
+		}
+
+		std::string to_01_string( Eigen::VectorXd const v ) {
+			std::string result( v.size(), ' ' ) ;
+			for( int i = 0; i < v.size(); ++i ) {
+				result[i] = ( v(i) != 0.0 ) ? '1' : '0' ;
+			}
+			return result ;
+		}
+
+		//
+		// Bayesian meta-analysis treating the prior as normal with mean 0 and variance matrix \Sigma
+		// and the likelihood as normal and given by
+		// the estimated betas and ses.
+		//
+		// Here is R code for the same computation:
+		/*
+			compute.bayesian_meta_analysis <- function( betas, ses = NULL, V = NULL, prior ) {
+				if( is.null( V )) {
+					if( length( ses ) > 1 ) {
+						V = diag( ses^2 ) ;
+					} else {
+						V = matrix( data = ses^2, nrow = 1, ncol = 1 )
+					}
+				} else {
+					stopifnot( is.null( ses ))
+				}
+				betas = matrix( betas, ncol = 1, nrow = length( betas )) ;
+				wNotNA = which( !is.na( diag(V)) & !is.na( betas ))
+				if( length( wNotNA ) == 0 ) { return( NA ) }
+				betas = betas[wNotNA,,drop=F]
+				V = V[wNotNA,wNotNA,drop= F]
+				constant = sqrt( det( V ) / det( V + prior ) ) ;
+				exponent = 0.5 * t( betas ) %*% ( solve( V ) - solve( V + prior ) ) %*% betas
+				print( V )
+				#print( betas )
+				#print( constant )
+				#print( exponent )
+				return( constant * exp( exponent ))
+			}
+		*/
+		double compute_bayes_factor( Eigen::MatrixXd const& prior, Eigen::MatrixXd const& null_prior, Eigen::MatrixXd const& V, Eigen::VectorXd const& betas ) {
+		#if DEBUG_BINGWA
+			std::cerr << "impl::compute_bayes_factor()\n" ;
+			std::cerr << std::resetiosflags( std::ios::floatfield ) ;
+			std::cerr << "prior = " << prior << ".\n" ;
+			std::cerr << "null prior = " << null_prior << ".\n" ;
+			std::cerr << "V = " << V << ".\n" ;
+		#endif
+			// I hope LDLT copes with noninvertible matrices.
+			// Maybe it doesn't...but let's find out.
+			Eigen::LDLT< Eigen::MatrixXd > Vsolver( V + null_prior ) ;
+			Eigen::LDLT< Eigen::MatrixXd > V_plus_prior_solver( V + prior ) ;
+			//Eigen::ColPivHouseholderQR< Eigen::MatrixXd > Vsolver( V ) ;
+			//Eigen::ColPivHouseholderQR< Eigen::MatrixXd > V_plus_prior_solver( V+prior ) ;
+			//Eigen::FullPivLU< Eigen::MatrixXd > V_plus_prior_solver( V + prior ) ;
+			Eigen::VectorXd const exponent = betas.transpose() * ( Vsolver.solve( betas ) - V_plus_prior_solver.solve( betas ) ) ;
+			double const detV = Vsolver.vectorD().prod() ;
+			double const detV_plus_prior = V_plus_prior_solver.vectorD().prod() ;
+			double const constant = std::sqrt( detV / detV_plus_prior ) ;
+
+		#if DEBUG_BINGWA
+			std::cerr << std::setprecision(15) ;
+			std::cerr << "betas = " << betas.transpose() << ".\n" ;
+			std::cerr << "V-solved betas = " << Vsolver.solve( betas ).transpose() << ".\n" ;
+			std::cerr << "V+prior-solved betas = " << V_plus_prior_solver.solve( betas ).transpose() << ".\n" ;
+			//std::cerr << "log determinant(V) = " << Vsolver.logAbsDeterminant() << "\n" ;
+			//std::cerr << "log determinant(V+prior) = " << V_plus_prior_solver.logAbsDeterminant() << "\n" ;
+			std::cerr << "determinant(V) = " << Vsolver.vectorD().prod() << " or " << V.determinant() << "\n" ;
+			std::cerr << "determinant(V+prior) = " << V_plus_prior_solver.vectorD().prod() << " or " << (V+prior).determinant() << "\n" ;
+			std::cerr << "Vsolver: " << ((Vsolver.info() == Eigen::Success) ? "success" : "fail" ) << ".\n" ;
+			std::cerr << "Vppsolver: " << ((V_plus_prior_solver.info() == Eigen::Success) ? "success" : "fail" ) << ".\n" ;
+			std::cerr << "constant = " << constant << ".\n" ;
+			std::cerr << "exponent= " << exponent.transpose() << ".\n" ;
+		#endif
+			//double const constant = std::sqrt( std::exp( Vsolver.logAbsDeterminant() - V_plus_prior_solver.logAbsDeterminant() )) ;
+			double const result = (
+					( Vsolver.info() != Eigen::Success || Vsolver.isNegative() || detV < 0.0 ||	V_plus_prior_solver.info() != Eigen::Success || V_plus_prior_solver.isNegative() || detV_plus_prior < 0.0 )
+				)
+				? NA
+				: constant * std::exp( 0.5 * exponent(0) ) ;
+
+		#if DEBUG_BINGWA
+			std::cerr << "BF = " << result << ".\n" ;
+		#endif
+			return result ;
+		}
+
+		void compute_fixed_effect_meta_and_variance(
+			Eigen::MatrixXd const& V,
+			Eigen::VectorXd const& betas,
+			int const numberOfCohorts,
+			int const numberOfEffects,
+			Eigen::VectorXd* metaBeta,
+			Eigen::MatrixXd* metaVariance,
+			double* chi_squared
+		) {
+		#if DEBUG_BINGWA
+			std::cerr << "impl::compute_fixed_effect_meta_and_variance()\n" ;
+			std::cerr << std::resetiosflags( std::ios::floatfield ) ;
+			std::cerr << "betas = " << betas.transpose() << ".\n" ;
+			std::cerr << "V = " << V << ".\n" ;
+		#endif
+			metaVariance->setZero( numberOfEffects, numberOfEffects ) ;
+			metaBeta->setZero( numberOfEffects ) ;
+			Eigen::MatrixXd Wi ;
+			Eigen::VectorXd beta = Eigen::VectorXd::Zero( numberOfEffects ) ;
+			for( int cohort = 0; cohort < numberOfCohorts; ++cohort ) {
+				Wi = V.block( cohort * numberOfEffects, cohort * numberOfEffects, numberOfEffects, numberOfEffects ).inverse() ;
+				Eigen::Block< Eigen::VectorXd const > beta_i = betas.block( cohort * numberOfEffects, 0, numberOfEffects, 1 ) ;
+				(*metaVariance) += Wi ;
+				beta += Wi * beta_i ;
+			}
+			
+			(*metaVariance) = metaVariance->inverse() ;
+			(*metaBeta) = (*metaVariance) * beta ;
+			*chi_squared = ( beta.array() * metaBeta->array() ).sum() ;
+		}
+
+		double compute_chisquared_pvalue( double statistic, int const numberOfEffects ) {
+			double pvalue = NA ;
+			if( statistic == statistic && statistic >= 0 ) {
+				typedef boost::math::chi_squared ChiSquareDistribution ;
+				ChiSquareDistribution chi( numberOfEffects ) ;
+				pvalue = boost::math::cdf( boost::math::complement( chi, statistic ) ) ;
+			}
+
+	#if DEBUG_BINGWA
+			std::cerr << "impl::compute_chisquared_pvalue(): df = " << numberOfEffects << ", stat = " << statistic << ", pvalue = " << pvalue << ".\n" ;
+	#endif
+			return pvalue ;
+		}
+		
+		double compute_normal_pvalue( double statistic, double variance, Tail const tail ) {
+			typedef boost::math::normal NormalDistribution ;
+			double result = NA ;
+			if( variance == variance && variance > 0 ) {
+				NormalDistribution normal( 0, std::sqrt( variance ) ) ;
+				switch( tail ) {
+					case eBoth:
+						result = 2.0 * boost::math::cdf( boost::math::complement( normal, std::abs( statistic ) ) ) ;
+						break ;
+					case eLower:
+						result = boost::math::cdf( normal, statistic ) ;
+						break ;
+					case eUpper:
+						result = boost::math::cdf( boost::math::complement( normal, statistic ) ) ;
+						break ;
+				}
+			}
+			return result ;
+		}
+
+		Eigen::MatrixXd get_nonmissing_coefficient_selector(
+			Eigen::VectorXd const& non_missingness
+		) {
+			int const number_of_included_effects = (
+				( non_missingness.array() > 0 ).cast< double >()
+			).sum() ;
+			
+			Eigen::MatrixXd result = Eigen::MatrixXd::Zero( number_of_included_effects, non_missingness.size() ) ;
+			
+			if( number_of_included_effects > 0 ) {
+				int count = 0 ;
+				for( int i = 0; i < non_missingness.size(); ++i ) {
+					// std::cerr << "i=" << i << ", non_missingness(i) = " << non_missingness(i) << ", sigma( i, i ) = " << sigma(i,i) << ".\n" ;
+					if( non_missingness(i) ) {
+						result( count++, i ) = 1 ;
+					}
+				}
+				
+	#if DEBUG_BINGWA	
+				std::cerr << "impl::get_nonmissing_coefficient_selector()" << ": selector is:\n" << result << "\n" ;
+	#endif
+			}
+			return result ;
+		}
+
+		Eigen::MatrixXd get_nonmissing_cohort_selector(
+			Eigen::VectorXd const& non_missingness,
+			int const numberOfCohorts,
+			int const numberOfEffects
+		) {
+	#if DEBUG_BINGWA
+			std::cerr << "impl::get_nonmissing_cohort_selector()" << ": non_missingness is:" << non_missingness.transpose() << "\n" ;
+			std::cerr << "impl::get_nonmissing_cohort_selector()" << ": numberOfCohorts = " << numberOfCohorts << ".\n" ;
+			std::cerr << "impl::get_nonmissing_cohort_selector()" << ": numberOfEffects = " << numberOfEffects << ".\n" ;
+	#endif
+			Eigen::MatrixXd selector = Eigen::MatrixXd::Zero( non_missingness.size(), non_missingness.size() ) ;
+			int numberOfIncludedCohorts = 0 ;
+			for( int i = 0; i < numberOfCohorts; ++i ) {
+				double const betaSum = non_missingness.segment( i * numberOfEffects, numberOfEffects ).sum() ;
+				if( betaSum == numberOfEffects ) {
+					for( int k = 0; k < numberOfEffects; ++k ) {
+						selector( numberOfEffects * numberOfIncludedCohorts + k, numberOfEffects * i + k ) = 1 ;
+					}
+					++numberOfIncludedCohorts ;
+				}
+	#if DEBUG_BINGWA
+				std::cerr << "impl::get_nonmissing_cohort_selector()" << ": after cohort " << i << " selector is:\n" << selector << "\n" ;
+	#endif
+			}
+			
+			Eigen::MatrixXd result = selector.block(
+				0, 0,
+				numberOfIncludedCohorts * numberOfEffects, selector.cols()
+			) ;
+			
+	#if DEBUG_BINGWA
+			std::cerr << "impl::get_nonmissing_cohort_selector()" << ": selector is:\n" << result << "\n" ;
+	#endif
+			return result ;
+		}
+	}
+}
+

ADDED   bingwa/wscript
Index: bingwa/wscript
==================================================================
--- bingwa/wscript
+++ bingwa/wscript
@@ -0,0 +1,12 @@
+def configure( conf ):
+	pass
+
+def build( bld ):
+	bld.stlib(
+		target = 'bingwa-impl',
+		source = bld.path.ant_glob( 'src/*.cpp' ) + bld.path.ant_glob( 'src/impl/*.cpp' ),
+		use = 'genfile sqlite3 statfile appcontext boost',
+		includes = './include',
+		export_includes = './include'
+	)
+

DELETED bitbucket-pipelines.yml
Index: bitbucket-pipelines.yml
==================================================================
--- bitbucket-pipelines.yml
+++ bitbucket-pipelines.yml
@@ -1,18 +0,0 @@
-# This is a sample build configuration for other languages.
-# Check our guides at https://confluence.atlassian.com/x/VYk8Lw for more examples.
-# Only use spaces to indent your .yml configuration.
-# -----
-# You can specify a custom docker image from Docker Hub as your build environment.
-#image: atlassian/default-image:2
-image: gavinband/ubuntu-16.04-build
-pipelines:
-  default:
-    - step:
-        size: 2x
-        script:
-          - ./waf-1.5.18 configure
-          - ./waf-1.5.18
-          - cd release/test
-          - mkdir -p test-reports
-          - /usr/local/bin/pybot -d test-reports -o NONE -l NONE -r NONE -x xunit.xml ./tests.txt
-

DELETED components/AssociationTestComponent/wscript
Index: components/AssociationTestComponent/wscript
==================================================================
--- components/AssociationTestComponent/wscript
+++ components/AssociationTestComponent/wscript
@@ -1,37 +0,0 @@
-import os.path
-import glob
-#import UnitTest
-
-def configure( conf ):
-	pass
-
-def create_tests( bld ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'test_association_test',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'genfile',
-		uselib = 'BOOST BOOST_SYSTEM BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
-		target = 'AssociationTestComponent',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = 'ZLIB BOOST BOOST_IOSTREAMS BOOST_SYSTEM BOOST_FILESYSTEM',
-		uselib_local = 'eigen genfile db statfile integration appcontext',
-		export_incdirs = './include'
-	)
-
-	#create_tests( bld )

Index: components/HaplotypeFrequencyComponent/include/components/HaplotypeFrequencyComponent/FlatTableDBOutputter.hpp
==================================================================
--- components/HaplotypeFrequencyComponent/include/components/HaplotypeFrequencyComponent/FlatTableDBOutputter.hpp
+++ components/HaplotypeFrequencyComponent/include/components/HaplotypeFrequencyComponent/FlatTableDBOutputter.hpp
@@ -13,12 +13,12 @@
 #include <boost/tuple/tuple.hpp>
 #include <boost/bimap.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/CohortIndividualSource.hpp"
 #include "genfile/VariantEntry.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "qcdb/Storage.hpp"
 #include "qcdb/DBOutputter.hpp"
 
 namespace haplotype_frequency_component {
 	struct FlatTableDBOutputter {
@@ -62,11 +62,11 @@
 
 	private:
 		qcdb::DBOutputter m_outputter ;
 		std::string m_table_name ;
 		std::size_t const m_max_variants_per_block ;
-		db::Connection::StatementPtr m_insert_data_sql ;
+		genfile::db::Connection::StatementPtr m_insert_data_sql ;
 		std::vector< std::pair< genfile::VariantIdentifyingData, genfile::VariantIdentifyingData > > m_variants ;
 		typedef boost::bimap< std::string, std::size_t > VariableMap ;
 		VariableMap m_variables ;
 		typedef std::map< std::pair< std::size_t, std::size_t >, genfile::VariantEntry > ValueMap ;
 		ValueMap m_values ;
@@ -75,14 +75,14 @@
 		std::string get_table_name() const ;
 		void store_block() ;
 		void create_schema() ;
 		void store_data_for_variants(
 			std::size_t const variant_i,
-			db::Connection::RowId const analysis_id,
-			db::Connection::RowId const variant1_id,
-			db::Connection::RowId const variant2_id
+			genfile::db::Connection::RowId const analysis_id,
+			genfile::db::Connection::RowId const variant1_id,
+			genfile::db::Connection::RowId const variant2_id
 		) ;
 		// void create_variables() ;
 	} ;
 }
 
 #endif

Index: components/HaplotypeFrequencyComponent/include/components/HaplotypeFrequencyComponent/HaplotypeFrequencyComponent.hpp
==================================================================
--- components/HaplotypeFrequencyComponent/include/components/HaplotypeFrequencyComponent/HaplotypeFrequencyComponent.hpp
+++ components/HaplotypeFrequencyComponent/include/components/HaplotypeFrequencyComponent/HaplotypeFrequencyComponent.hpp
@@ -53,39 +53,44 @@
 		genfile::VariantDataReader& source_data_reader,
 		genfile::VariantIdentifyingData const& target_snp,
 		genfile::VariantDataReader& target_data_reader
 	) ;
 
-	void compute_ld_measures(
-		genfile::VariantIdentifyingData const& source_snp,
-		std::vector< int > const& source_calls,
-		std::vector< uint32_t > const& source_ploidy,
-		genfile::VariantIdentifyingData const& target_snp,
-		std::vector< int > const& target_calls,
-		std::vector< uint32_t > const& target_ploidy,
-		Eigen::MatrixXd const& dosages,
-		Eigen::MatrixXd const& nonmissingness,
-		bool const doEM
-	) ;
-
-	bool compute_dosage_ld_measures(
-		genfile::VariantIdentifyingData const& source_snp,
-		genfile::VariantIdentifyingData const& target_snp,
-		Eigen::MatrixXd const& dosages,
-		Eigen::MatrixXd const& nonmissingness,
-		std::string const& variable_name_stub,
-		std::vector< genfile::SampleRange > const& sample_set,
-		bool const alwaysOutput
-	) ;
-
-	bool compute_em_ld_measures(
-		genfile::VariantIdentifyingData const& source_snp,
-		std::vector< int > const& source_calls,
-		std::vector< uint32_t > const& source_ploidy,
-		genfile::VariantIdentifyingData const& target_snp,
-		std::vector< int > const& target_calls,
-		std::vector< uint32_t > const& target_ploidy,
+	bool compute_dosage_ld_measures(
+		genfile::VariantIdentifyingData const& source_snp,
+		std::vector< uint32_t > const& source_ploidy,
+		genfile::VariantIdentifyingData const& target_snp,
+		std::vector< uint32_t > const& target_ploidy,
+		Eigen::MatrixXd const& dosages,
+		Eigen::MatrixXd const& nonmissingness
+	) ;
+
+	double compute_dosage_correlation(
+		genfile::VariantIdentifyingData const& source_snp,
+		genfile::VariantIdentifyingData const& target_snp,
+		Eigen::MatrixXd const& dosages,
+		Eigen::MatrixXd const& nonmissingness,
+		std::vector< genfile::SampleRange > const& sample_set
+	) ;
+
+	bool compute_em_ld_measures(
+		genfile::VariantIdentifyingData const& source_snp,
+		std::vector< uint32_t > const& source_ploidy,
+		std::vector< int > const& source_calls,
+		genfile::VariantIdentifyingData const& target_snp,
+		std::vector< uint32_t > const& target_ploidy,
+		std::vector< int > const& target_calls,
+		Eigen::MatrixXd const& nonmissingness
+	) ;
+
+	bool compute_em_ld_measures(
+		genfile::VariantIdentifyingData const& source_snp,
+		std::vector< uint32_t > const& source_ploidy,
+		std::vector< int > const& source_calls,
+		genfile::VariantIdentifyingData const& target_snp,
+		std::vector< uint32_t > const& target_ploidy,
+		std::vector< int > const& target_calls,
 		std::string const& variable_name_stub,
 		std::vector< genfile::SampleRange > const& sample_set,
 		bool const alwaysOutput
 	) ;
 

Index: components/HaplotypeFrequencyComponent/src/FlatTableDBOutputter.cpp
==================================================================
--- components/HaplotypeFrequencyComponent/src/FlatTableDBOutputter.cpp
+++ components/HaplotypeFrequencyComponent/src/FlatTableDBOutputter.cpp
@@ -10,12 +10,12 @@
 #include <boost/tuple/tuple.hpp>
 #include <boost/thread/thread.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/Error.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "appcontext/get_current_time_as_string.hpp"
 #include "components/HaplotypeFrequencyComponent/FlatTableDBOutputter.hpp"
 
 // #define DEBUG_FLATTABLEDBOUTPUTTER 1
 
@@ -32,11 +32,11 @@
 		std::string const& analysis_name,
 		std::string const& analysis_description,
 		Metadata const& metadata,
 		std::string const& snp_match_fields
 	):
-		m_outputter( filename, analysis_name, analysis_description, metadata, boost::optional< db::Connection::RowId >(), snp_match_fields ),
+		m_outputter( filename, analysis_name, analysis_description, metadata, boost::optional< genfile::db::Connection::RowId >(), snp_match_fields ),
 		m_table_name( "ld_analysis" + genfile::string_utils::to_string( m_outputter.analysis_id() ) ),
 		m_max_variants_per_block( 1000 )
 	{}
 
 	FlatTableDBOutputter::~FlatTableDBOutputter() {
@@ -57,11 +57,11 @@
 		store_block() ;
 		m_variants.clear() ;
 		m_values.clear() ;
 
 		if( options & qcdb::eCreateIndices ) {
-			db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
+			genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
 			m_outputter.connection().run_statement( "CREATE INDEX IF NOT EXISTS " + m_table_name + "_index ON " + m_table_name + "( variant1_id, variant2_id )" ) ;
 		}
 
 		m_outputter.finalise( options ) ;
 	}
@@ -121,19 +121,19 @@
 		// Store the value of this variable
 		m_values[ std::make_pair( m_variants.size() - 1, where->second ) ] = value ;
 	}
 
 	void FlatTableDBOutputter::store_block() {
-		db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
 
 		if( !m_insert_data_sql.get() ) {
 			create_schema() ;
 			// create_variables() ;
 		}
 		for( std::size_t i = 0; i < m_variants.size(); ++i ) {
-			db::Connection::RowId const variant1_id = m_outputter.get_or_create_variant( m_variants[i].first ) ;
-			db::Connection::RowId const variant2_id = m_outputter.get_or_create_variant( m_variants[i].second ) ;
+			genfile::db::Connection::RowId const variant1_id = m_outputter.get_or_create_variant( m_variants[i].first ) ;
+			genfile::db::Connection::RowId const variant2_id = m_outputter.get_or_create_variant( m_variants[i].second ) ;
 			store_data_for_variants( i, m_outputter.analysis_id(), variant1_id, variant2_id ) ;
 		}
 	}
 
 	std::string FlatTableDBOutputter::get_table_name() const {
@@ -231,13 +231,13 @@
 	}
 	*/
 	
 	void FlatTableDBOutputter::store_data_for_variants(
 		std::size_t const variant_i,
-		db::Connection::RowId const analysis_id,
-		db::Connection::RowId const variant1_id,
-		db::Connection::RowId const variant2_id
+		genfile::db::Connection::RowId const analysis_id,
+		genfile::db::Connection::RowId const variant1_id,
+		genfile::db::Connection::RowId const variant2_id
 	) {
 		m_insert_data_sql->bind( 1, analysis_id ) ;
 		m_insert_data_sql->bind( 2, variant1_id ) ;
 		m_insert_data_sql->bind( 3, variant2_id ) ;
 		

Index: components/HaplotypeFrequencyComponent/src/HaplotypeFrequencyComponent.cpp
==================================================================
--- components/HaplotypeFrequencyComponent/src/HaplotypeFrequencyComponent.cpp
+++ components/HaplotypeFrequencyComponent/src/HaplotypeFrequencyComponent.cpp
@@ -14,15 +14,13 @@
 #include "genfile/SampleFilteringSNPDataSource.hpp"
 #include "genfile/SampleMappingSNPDataSource.hpp"
 #include "genfile/wildcard.hpp"
 #include "genfile/ToGP.hpp"
 #include "statfile/BuiltInTypeStatSink.hpp"
-#include "integration/NewtonRaphson.hpp"
-#include "integration/Derivative.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
-#include "db/Error.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+#include "genfile/db/Error.hpp"
 #include "components/HaplotypeFrequencyComponent/FlatTableDBOutputter.hpp"
 #include "components/HaplotypeFrequencyComponent/HaplotypeFrequencyComponent.hpp"
 
 // #define DEBUG_HAPLOTYPE_FREQUENCY_COMPONENT 1
 struct HaplotypeFrequencyLogLikelihood ;
@@ -277,13 +275,13 @@
 		}
 
 		void initialise( std::size_t nSamples, std::size_t nAlleles ) {
 			if( nAlleles != 2 ) {
 				throw genfile::BadArgumentError(
-					"Callsetter::initialise()",
+					"CallSetter::initialise()",
 					"nAlleles=" + genfile::string_utils::to_string( nAlleles ),
-					"Only biallelic variants are currently supported."
+					"I only support biallelic variants"
 				) ;
 			}
 			m_result->clear() ; // ploidy 2
 			m_result->resize( nSamples, -1 ) ;
 			m_ploidy->clear() ;
@@ -534,111 +532,145 @@
 			if( nonmissingness.row(i).sum() < 2 ) {
 				nonmissingness.row(i).setZero() ;
 			}
 		}
 		
-		compute_ld_measures(
-			source_snp,
-			source_calls,
-			source_ploidy,
-			target_snp,
-			target_calls,
-			target_ploidy,
-			dosages,
-			nonmissingness,
-			haveCalls
-		) ;
-	}
-}
-
-void HaplotypeFrequencyComponent::compute_ld_measures(
-	genfile::VariantIdentifyingData const& source_snp,
-	std::vector< int > const& source_calls,
-	std::vector< uint32_t > const& source_ploidy,
-	genfile::VariantIdentifyingData const& target_snp,
-	std::vector< int > const& target_calls,
-	std::vector< uint32_t > const& target_ploidy,
-	Eigen::MatrixXd const& dosages,
-	Eigen::MatrixXd const& nonmissingness,
-	bool const runEM
-) {
-	if( m_stratification ) {
-		bool output = (m_min_r2 == 0.0 ) ;
-		for( std::size_t i = 0; i < m_stratification->number_of_strata(); ++i ) {
-			try {
-				if( runEM ) {
-					output = compute_em_ld_measures(
-						source_snp,
-						source_calls,
-						source_ploidy,
-						target_snp,
-						target_calls,
-						target_ploidy,
-						m_stratification->stratum_name(i) + ":",
-						m_stratification->stratum(i),
-						output
-					) || output ;
-				}
-				output = compute_dosage_ld_measures(
-					source_snp,
-					target_snp,
-					dosages,
-					nonmissingness,
-					m_stratification->stratum_name(i) + ":",
-					m_stratification->stratum(i),
-					output
-				) || output ;
-			} catch( genfile::OperationFailedError const& e ) {
-				m_ui_context.logger() << "!! HaplotypeFrequencyComponent::compute_ld_measures(): "
+		compute_dosage_ld_measures(
+			source_snp,
+			source_ploidy,
+			target_snp,
+			target_ploidy,
+			dosages,
+			nonmissingness
+		) ;
+
+		if( haveCalls ) {
+			compute_em_ld_measures(
+				source_snp,
+				source_ploidy,
+				source_calls,
+				target_snp,
+				target_ploidy,
+				target_calls,
+				nonmissingness
+			) ;
+		}
+	}
+}
+
+bool HaplotypeFrequencyComponent::compute_dosage_ld_measures(
+	genfile::VariantIdentifyingData const& source_snp,
+	std::vector< uint32_t > const& source_ploidy,
+	genfile::VariantIdentifyingData const& target_snp,
+	std::vector< uint32_t > const& target_ploidy,
+	Eigen::MatrixXd const& dosages,
+	Eigen::MatrixXd const& nonmissingness
+) {
+	bool output = (m_min_r2 == 0.0) ;
+	if( m_stratification ) {
+		double const NA = std::numeric_limits< double >::quiet_NaN() ;
+		std::vector< double > correlations( m_stratification->number_of_strata(), NA ) ;
+		double max_squared_correlation = 0.0 ;
+		for( std::size_t i = 0; i < m_stratification->number_of_strata(); ++i ) {
+			try {
+				correlations[i] = compute_dosage_correlation(
+					source_snp,
+					target_snp,
+					dosages,
+					nonmissingness,
+					m_stratification->stratum(i)
+				) ;
+				max_squared_correlation = std::max(
+					max_squared_correlation,
+					correlations[i] * correlations[i]
+				) ;
+			} catch( genfile::OperationFailedError const& e ) {
+				m_ui_context.logger() << "!! HaplotypeFrequencyComponent::compute_dosage_ld_measures(): "
 					<< "stratum " << m_stratification->stratum_name(i) << ": "
 					<< "could not compute LD measures between SNPs "
 					<< source_snp << " and " << target_snp << ".\n"
 					<< "!! reason: " << e.get_message() << "\n" ;
 			}
+		}
+		output = output | (max_squared_correlation >= m_min_r2) ;
+
+		if( output ) {
+			for( std::size_t i = 0; i < m_stratification->number_of_strata(); ++i ) {
+				m_sink->store_per_variant_pair_data( source_snp, target_snp, m_stratification->stratum_name(i) + ":dosage_r", correlations[i]  ) ;
+			}
+		}
+	} else {
+		double r = compute_dosage_correlation(
+			source_snp,
+			target_snp,
+			dosages,
+			nonmissingness,
+			std::vector< genfile::SampleRange >( 1, genfile::SampleRange( 0, dosages.rows() ) )
+		) ;
+		if( output || (r*r) >= m_min_r2 ) {
+			m_sink->store_per_variant_pair_data( source_snp, target_snp, "dosage_r", r ) ;
+		}
+	}
+	return output ;
+}
+
+bool HaplotypeFrequencyComponent::compute_em_ld_measures(
+	genfile::VariantIdentifyingData const& source_snp,
+	std::vector< uint32_t > const& source_ploidy,
+	std::vector< int > const& source_calls,
+	genfile::VariantIdentifyingData const& target_snp,
+	std::vector< uint32_t > const& target_ploidy,
+	std::vector< int > const& target_calls,
+	Eigen::MatrixXd const& nonmissingness
+) {
+	bool output = (m_min_r2 == 0.0) ;
+	if( m_stratification ) {
+		for( std::size_t i = 0; i < m_stratification->number_of_strata(); ++i ) {
+			for( std::size_t i = 0; i < m_stratification->number_of_strata(); ++i ) {
+				try {
+					output = compute_em_ld_measures(
+						source_snp, source_ploidy, source_calls,
+						target_snp, target_ploidy, target_calls,
+						m_stratification->stratum_name(i) + ":",
+						m_stratification->stratum(i),
+						output
+					) || output ;
+				} catch( genfile::OperationFailedError const& e ) {
+					m_ui_context.logger() << "!! HaplotypeFrequencyComponent::compute_em_ld_measures(): "
+						<< "stratum " << m_stratification->stratum_name(i) << ": "
+						<< "could not compute LD measures between SNPs "
+						<< source_snp << " and " << target_snp << ".\n"
+						<< "!! reason: " << e.get_message() << "\n" ;
+				}
+			}
 		}
 	} else {
 		try {
-			bool output = (m_min_r2 == 0.0 ) ;
-			if( runEM ) {
-				output = compute_em_ld_measures(
-					source_snp,
-					source_calls, source_ploidy,
-					target_snp,
-					target_calls, target_ploidy,
-					"",
-					std::vector< genfile::SampleRange  >( 1, genfile::SampleRange( 0, dosages.rows() ) ),
-					output
-				) ;
-			}
-			compute_dosage_ld_measures(
-				source_snp,
-				target_snp,
-				dosages,
-				nonmissingness,
-				"",
-				std::vector< genfile::SampleRange  >( 1, genfile::SampleRange( 0, dosages.rows() ) ),
+			compute_em_ld_measures(
+				source_snp, source_ploidy, source_calls, 
+				target_snp, target_ploidy, target_calls, 
+				"",
+				std::vector< genfile::SampleRange  >( 1, genfile::SampleRange( 0, source_calls.size() ) ),
 				output
 			) ;
 		} catch( genfile::OperationFailedError const& e ) {
-			m_ui_context.logger() << "!! HaplotypeFrequencyComponent::compute_ld_measures(): "
+			m_ui_context.logger() << "!! HaplotypeFrequencyComponent::compute_em_ld_measures(): "
 				<< "could not compute LD measures between SNPs "
 				<< source_snp << " and " << target_snp << ".\n"
 				<< "!! reason: " << e.get_message() << "\n" ;
 		}
 	}
+	return output ;
 }
 
-bool HaplotypeFrequencyComponent::compute_dosage_ld_measures(
+double HaplotypeFrequencyComponent::compute_dosage_correlation(
 	genfile::VariantIdentifyingData const& source_snp,
 	genfile::VariantIdentifyingData const& target_snp,
 	Eigen::MatrixXd const& dosages,
 	Eigen::MatrixXd const& nonmissingness,
-	std::string const& variable_name_stub,
-	std::vector< genfile::SampleRange > const& sample_set,
-	bool alwaysOutput
+	std::vector< genfile::SampleRange > const& sample_set
 ) {
-	bool includeInOutput = alwaysOutput ;
 	Eigen::RowVectorXd means = Eigen::RowVectorXd::Zero(2) ;
 	Eigen::RowVectorXd totals = Eigen::RowVectorXd::Zero(2) ;
 	for( std::size_t i = 0; i < sample_set.size(); ++i ) {
 
 #if DEBUG_HAPLOTYPE_FREQUENCY_COMPONENT
@@ -652,12 +684,33 @@
 			* nonmissingness.block( sample_set[i].begin(), 0, sample_set[i].end() - sample_set[i].begin(), 2 ).array()
 		).colwise().sum() ;
 		
 		totals += nonmissingness.block( sample_set[i].begin(), 0, sample_set[i].end() - sample_set[i].begin(), 2 ).colwise().sum() ;
 	}
-
-	means.array() /= totals.array() ;
+	
+	//
+	// Here is R code for this computation:
+	/*
+		bayesr <- function( genotypes, prior.weight = 1 ) {
+			w = prior.weight
+			M = matrix( c( 0, 0, 0, 2, 2, 0, 2, 2 ), byrow = T, ncol = 2 )
+			means = ( colSums( genotypes ) + c( 0.5*w, 0.5*w )) / (nrow(genotypes) + (0.5*w))
+			print( means )
+			genotypes[,1] = genotypes[,1] - means[1]
+			genotypes[,2] = genotypes[,2] - means[2]
+			covariance = t(genotypes) %*% genotypes
+			covariance = covariance + (w/8.0 * t(M-means) %*% (M-means))
+			covariance[1,2] / sqrt( covariance[1,1] * covariance[2,2])
+		}
+	*/
+	
+	// We conceptually add one of each of the four haplotypes to the data weighted by the prior
+	// or alternatively, four individuals, each homozygous for one of the possible haplotypes.
+	// Individuals are then weighted as w/8 so that the total weight is w/2.
+	// These individuals also contribute a dosage of 4*2/8 = 0.5*w.
+	double const w = m_prior.sum() ;
+	means.array() = ( means.array() + (0.5*w) ) / ( totals.array() + (0.5*w) );
 
 	Eigen::Matrix2d covariance = Eigen::Matrix2d::Zero() ;
 	Eigen::Matrix2d nonmissing = Eigen::Matrix2d::Zero() ;
 	for( std::size_t i = 0; i < sample_set.size(); ++i ) {
 		//Eigen::MatrixBase< Eigen::MatrixXd > block = (
@@ -670,36 +723,47 @@
 		) ;
 
 		covariance += block.transpose() * block ;
 		nonmissing += nonmissing_block.transpose() * nonmissing_block ;
 	}
-	// Compute correlation as:
-	// 
+
+	// Incorporate prior information
+	{
+		Eigen::MatrixXd priorGenotypes = Eigen::MatrixXd::Zero( 4, 2 ) ;
+		// priorHaps = (
+		//   0 0
+		//   0 2
+		//   2 0
+		//   2 2
+		// )
+		// We treat this like data but weighted by w/8.
+		priorGenotypes(1,1) = 2 ;
+		priorGenotypes(2,0) = 2 ;
+		priorGenotypes(3,0) = 2 ;
+		priorGenotypes(3,1) = 2 ;
+		priorGenotypes = priorGenotypes.rowwise() - means ;
+		covariance += (w/8.0) * priorGenotypes.transpose() * priorGenotypes ;
+	}
+
 	double r = covariance(0,1) / std::sqrt( covariance(0,0) * covariance(1,1) ) ;
-
-	includeInOutput = includeInOutput || (r*r >= m_min_r2 ) ;
-
+		
 #if DEBUG_HAPLOTYPE_FREQUENCY_COMPONENT
 	std::cerr << "means = " << means << ".\n" ;
 	std::cerr << "cov =\n" << covariance << ".\n" ;
 	std::cerr << "r =\n" << r << ".\n" ;
 #endif
 
-	if( includeInOutput ) {
-		m_sink->store_per_variant_pair_data( source_snp, target_snp, variable_name_stub + "dosage_r", r  ) ;
-		m_sink->store_per_variant_pair_data( source_snp, target_snp, variable_name_stub + "dosage_r2", r*r ) ;
-	}
-	return includeInOutput ;
+	return r ;
 }
 
 bool HaplotypeFrequencyComponent::compute_em_ld_measures(
 	genfile::VariantIdentifyingData const& source_snp,
-	std::vector< int > const& source_calls,
 	std::vector< uint32_t > const& source_ploidy,
+	std::vector< int > const& source_calls,
 	genfile::VariantIdentifyingData const& target_snp,
-	std::vector< int > const& target_calls,
 	std::vector< uint32_t > const& target_ploidy,
+	std::vector< int > const& target_calls,
 	std::string const& variable_name_stub,
 	std::vector< genfile::SampleRange > const& sample_set,
 	bool alwaysOutput
 ) {
 	// Construct table of genotypes at each SNP.

Index: components/HaplotypeFrequencyComponent/wscript
==================================================================
--- components/HaplotypeFrequencyComponent/wscript
+++ components/HaplotypeFrequencyComponent/wscript
@@ -3,35 +3,22 @@
 #import UnitTest
 
 def configure( conf ):
 	pass
 
-def create_tests( bld ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'test_haplotype_frequency_component',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'genfile HaplotypeFrequencyComponent boost-unit_test_framework',
-		uselib = 'BOOST BOOST_SYSTEM BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
- 		target = 'HaplotypeFrequencyComponent',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = 'ZLIB BOOST BOOST_IOSTREAMS BOOST_SYSTEM BOOST_FILESYSTEM',
-		uselib_local = 'eigen genfile db statfile integration appcontext qcdb',
-		export_incdirs = './include'
-	)
-
-	create_tests( bld )
+def build( bld ):
+	bld.stlib(
+ 		target = 'HaplotypeFrequencyComponent',
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		includes='./include',
+		use = 'eigen genfile statfile integration appcontext qcdb boost ZLIB',
+		export_includes = './include'
+	)
+
+	bld.program(
+		target = 'test_haplotype_frequency_component',
+		source = bld.path.ant_glob( 'test/*.cpp' ),
+		use = 'HaplotypeFrequencyComponent boost boost_unit_test_framework',
+		includes='./include',
+		unit_test = 1,
+		install_path = None
+	)

DELETED components/Illumina/include/components/Illumina/include/IlluminaManifest.hpp
Index: components/Illumina/include/components/Illumina/include/IlluminaManifest.hpp
==================================================================
--- components/Illumina/include/components/Illumina/include/IlluminaManifest.hpp
+++ components/Illumina/include/components/Illumina/include/IlluminaManifest.hpp
@@ -1,55 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef ILLUMINA_ILLUMINA_MANIFEST_HPP
-#define ILLUMINA_ILLUMINA_MANIFEST_HPP
-
-#include "genfile/FileUtils.hpp"
-
-namespace illumina {
-	struct Manifest {
-		Manifest( std::string const& filename ):
-			m_filename( filename )
-		{
-			setup( filename )
-		}
-		
-		
-	private:
-		
-		
-		
-		void setup( std::string const& filename ) {
-			std::auto_ptr< std::istream > file = genfile::open_binary_file_for_input( filename ) ;
-			setup( *file, filename )
-		}
-
-		void setup( std::istream& file, std::string const& filename ) {
-			std::string signature( 3, ' ' ) ;
-			file.read( &signature[0], 3 ) ;
-			if( signature != 'BPM' ) {
-				throw genfile::MalformedInputError(
-					"illumina::Manifest::setup()",
-					"File (" + filename + ") does not appear to be an Illumina manifest (.bpm) file."
-				) ;
-			}
-			unsigned char version_major ;
-			uint32_t version_minor ;
-			file.read( &version_major, 1 ) ;
-			file.read( &version_minor, 4 ) ;
-			if( version_major != 1 || version_minor != 4 ) {
-				throw genfile::MalformedInputError(
-					"illumina::Manifest::setup()",
-					"Illumina manifest (" + filename + ") does not appear to have the right version (" + int( version_major ) + "," + version_minor + " instead of 1,4)"
-				) ;
-			}
-
-			
-		}
-	} ;
-}
-
-#endif

DELETED components/Illumina/wscript
Index: components/Illumina/wscript
==================================================================
--- components/Illumina/wscript
+++ components/Illumina/wscript
@@ -1,37 +0,0 @@
-import os.path
-import glob
-#import UnitTest
-
-def configure( conf ):
-	pass
-
-def create_tests( bld ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'test_illumina',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'genfile boost-unit_test_framework',
-		uselib = 'BOOST BOOST_SYSTEM BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
-		target = 'Illumina',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = '',
-		uselib_local = '',
-		export_incdirs = './include'
-	)
-
-	#create_tests( bld )

Index: components/RelatednessComponent/include/components/RelatednessComponent/KinshipCoefficientComputer.hpp
==================================================================
--- components/RelatednessComponent/include/components/RelatednessComponent/KinshipCoefficientComputer.hpp
+++ components/RelatednessComponent/include/components/RelatednessComponent/KinshipCoefficientComputer.hpp
@@ -80,12 +80,10 @@
 		int end_sample_i ;
 		int begin_sample_j ;
 		int end_sample_j ;
 	} ;
 	
-	struct Dispatcher ;
-
 	struct NTaskDispatcher {
 	public:
 		typedef std::auto_ptr< NTaskDispatcher > UniquePtr ;
 	public:
 			
@@ -104,31 +102,10 @@
 	private:
 			boost::ptr_vector< boost::nullable< worker::Task > > m_tasks ;
 			worker::Worker* m_worker ;
 	} ;
 	
-	struct NormaliseGenotypesAndComputeXXt: public KinshipCoefficientComputer::Computation {
-		static UniquePtr create( worker::Worker*, std::string const& method ) ;
-		NormaliseGenotypesAndComputeXXt( worker::Worker*, std::string const& method ) ;
-
-		Computation::Matrix const& result() const ;
-		Computation::IntegerMatrix const& nonmissingness() const ;
-		std::string get_summary() const ;
-		
-		void begin_processing_snps( std::size_t number_of_samples, genfile::SNPDataSource::Metadata const& ) ;
-		void processed_snp( genfile::VariantIdentifyingData const& id_data, genfile::VariantDataReader::SharedPtr data_reader ) ;
-		void end_processing_snps() ;
-		std::size_t number_of_snps_included() const ;
-	private:
-		double const m_call_threshhold ;
-		double const m_allele_frequency_threshhold ;
-		std::size_t m_number_of_snps_included ;
-		Computation::Matrix m_result ;
-		Computation::IntegerMatrix m_nonmissingness ;
-		std::auto_ptr< Dispatcher > m_dispatcher ;
-	} ;
-
 	struct NormaliseGenotypesAndComputeXXtFast: public KinshipCoefficientComputer::Computation {
 		static UniquePtr create( worker::Worker*, std::size_t const number_of_snps_per_computation ) ;
 		
 		NormaliseGenotypesAndComputeXXtFast(
 			worker::Worker* worker,

Index: components/RelatednessComponent/src/KinshipCoefficientComputer.cpp
==================================================================
--- components/RelatednessComponent/src/KinshipCoefficientComputer.cpp
+++ components/RelatednessComponent/src/KinshipCoefficientComputer.cpp
@@ -33,261 +33,25 @@
 #include "appcontext/get_current_time_as_string.hpp"
 #include "components/RelatednessComponent/KinshipCoefficientComputer.hpp"
 #include "components/RelatednessComponent/PCAComputer.hpp"
 #include "components/RelatednessComponent/mean_centre_genotypes.hpp"
 
+#define USING_BOOST_THREADPOOL 0
+#if USING_BOOST_THREADPOOL
 #include "boost/threadpool.hpp"
+#else
+#include "metro/concurrency/threadpool.hpp"
+#endif
 
 // #define DEBUG_KINSHIP_COEFFICIENT_COMPUTER 2
-#define USING_BOOST_THREADPOOL 1
 
 namespace impl {
-	#if HAVE_EIGEN
-		template< typename Vector, typename Matrix >
-		void accumulate_xxt_using_eigen(
-			Vector* data,
-			Matrix* result,
-			int const begin_sample_i, int const end_sample_i,
-			int const begin_sample_j, int const end_sample_j,
-			double const scale
-		) {
-			
-			if( begin_sample_i == begin_sample_j && end_sample_i == end_sample_j ) {
-				result
-					->block( begin_sample_i, begin_sample_j, end_sample_i - begin_sample_i, end_sample_j - begin_sample_j )
-					.template selfadjointView< Eigen::Lower >()
-					.rankUpdate( data->segment( begin_sample_i, end_sample_i - begin_sample_i ), scale ) ;
-			} else {
-				result
-					->block(  begin_sample_i, begin_sample_j, end_sample_i - begin_sample_i, end_sample_j - begin_sample_j ).noalias()
-					+= scale * (
-						data->segment( begin_sample_i, end_sample_i - begin_sample_i )
-						*
-						data->segment( begin_sample_j, end_sample_j - begin_sample_j ).transpose()
-					) ;
-			}
-		}
-	#endif
-	#if HAVE_CBLAS
-		void accumulate_xxt_using_cblas(
-			KinshipCoefficientComputer::Computation::Vector* data,
-			KinshipCoefficientComputer::Computation::Matrix* result,
-			int const begin_sample_i, int const end_sample_i,
-			int const begin_sample_j, int const end_sample_j,
-			double const scale
-		) {
-			assert( result ) ;
-			assert( data ) ;
-			int const N = data->size() ;
-			assert( N == result->cols() ) ;
-			if( begin_sample_i == begin_sample_j && end_sample_i == end_sample_j ) {
-				cblas_dsyr(
-					CblasColMajor,
-					CblasLower,
-					end_sample_i - begin_sample_i,
-					scale,
-					data->segment( begin_sample_i, end_sample_i - begin_sample_i ).data(),
-					1,
-					result->block( begin_sample_i, begin_sample_j, end_sample_i - begin_sample_i, end_sample_j - begin_sample_j ).data(),
-					result->outerStride()
-				) ;
-			} else {
-				cblas_dger(
-					CblasColMajor,
-					end_sample_i - begin_sample_i,
-					end_sample_j - begin_sample_j,
-					scale,
-					data->segment( begin_sample_i, end_sample_i - begin_sample_i ).data(), 1,
-					data->segment( begin_sample_j, end_sample_j - begin_sample_j ).data(), 1,
-					result->block( begin_sample_i, begin_sample_j, end_sample_i - begin_sample_i, end_sample_j - begin_sample_j ).data(),
-					result->outerStride()
-				) ;
-			}
-		}
-	#endif
-
 	std::ostream& operator<<( std::ostream& out, SampleBounds const& b ) {
 		out << "[" << b.begin_sample_i << "-" << b.end_sample_i << ", " << b.begin_sample_j << "-" << b.end_sample_j << "]" ;
 		return out ;
 	}
-
-	struct ComputeXXtTask: public boost::noncopyable
-	{
-		typedef KinshipCoefficientComputer::Computation::Vector Vector ;
-		typedef KinshipCoefficientComputer::Computation::Matrix Matrix ;
-		typedef KinshipCoefficientComputer::Computation::IntegerVector IntegerVector ;
-		typedef KinshipCoefficientComputer::Computation::IntegerMatrix IntegerMatrix ;
-		typedef std::auto_ptr< ComputeXXtTask > UniquePtr ;
-		
-		virtual ~ComputeXXtTask() {}
-
-		virtual void add_data(
-			KinshipCoefficientComputer::Computation::Vector&,
-			KinshipCoefficientComputer::Computation::IntegerVector&
-		) = 0 ;
-
-		virtual void operator()() = 0 ;
-		
-		static UniquePtr create(
-			Matrix* result,
-			IntegerMatrix* counts,
-			SampleBounds const bounds,
-			std::string const& method
-		) ;
-	} ;
-
-	struct ComputeXXtTaskImpl: public ComputeXXtTask {
-		typedef boost::function< void (
-			Vector* data,
-			Matrix* result,
-			int const begin_sample_i, int const end_sample_i,
-			int const begin_sample_j, int const end_sample_j,
-			double const scale
-		) >
-		AccumulateXXt ;
-
-		typedef boost::function< void (
-			IntegerVector* data,
-			IntegerMatrix* result,
-			int const begin_sample_i, int const end_sample_i,
-			int const begin_sample_j, int const end_sample_j,
-			double const scale
-		) >
-		AccumulateXXtInteger ;
-		
-		ComputeXXtTaskImpl(
-			Matrix* result,
-			IntegerMatrix* counts,
-			SampleBounds const bounds,
-			AccumulateXXt accumulate_xxt,
-			AccumulateXXtInteger accumulate_xxt_integer
-		):
-			m_result( result ),
-			m_counts( counts ),
-			m_bounds( bounds ),
-			m_accumulate_xxt( accumulate_xxt ),
-			m_accumulate_xxt_integer( accumulate_xxt_integer )
-		{
-			assert( result ) ;
-			assert( m_accumulate_xxt ) ;
-		}
-
-		void add_data(
-			Vector& data,
-			IntegerVector& nonmissingness
-		) {
-			m_data.push_back( &data ) ;
-			m_nonmissingness.push_back( &nonmissingness ) ;
-		}
-
-		std::size_t number_of_snps() const { return m_data.size() ; }
-
-		void operator()() {
-			for( std::size_t snp_i = 0; snp_i < m_data.size(); ++snp_i ) {
-				m_accumulate_xxt(
-					m_data[ snp_i ],
-					m_result,
-					m_bounds.begin_sample_i, m_bounds.end_sample_i,
-					m_bounds.begin_sample_j, m_bounds.end_sample_j,
-					1.0
-				) ;
-
-				m_accumulate_xxt_integer(
-					m_nonmissingness[ snp_i ],
-					m_counts,
-					m_bounds.begin_sample_i, m_bounds.end_sample_i,
-					m_bounds.begin_sample_j, m_bounds.end_sample_j,
-					1.0
-				) ;
-			}
-		}
-		
-	protected:
-		Matrix* m_result ;
-		IntegerMatrix* m_counts ;
-		SampleBounds const m_bounds ;
-		std::vector< Vector* > m_data ;
-		std::vector< IntegerVector* > m_nonmissingness ;
-		AccumulateXXt m_accumulate_xxt ;
-		AccumulateXXtInteger m_accumulate_xxt_integer ;
-	} ;
-	
-	struct ComputeXXtUsingEigenTask: public ComputeXXtTaskImpl {
-		ComputeXXtUsingEigenTask(
-			Matrix* result,
-			IntegerMatrix* counts,
-			SampleBounds const bounds
-		):
-			ComputeXXtTaskImpl(
-				result, counts, bounds,
-				&impl::accumulate_xxt_using_eigen< Vector, Matrix >, &impl::accumulate_xxt_using_eigen< IntegerVector, IntegerMatrix >
-			)
-		{}
-	} ;
-
-#if HAVE_CBLAS
-	struct ComputeXXtUsingCBlasTask: public ComputeXXtTaskImpl {
-		ComputeXXtUsingCBlasTask(
-			Matrix* result,
-			IntegerMatrix* counts,
-			SampleBounds const bounds
-		):
-			ComputeXXtTaskImpl(
-				result, counts, bounds,
-				&impl::accumulate_xxt_using_cblas, &impl::accumulate_xxt_using_eigen< IntegerVector, IntegerMatrix >
-			)
-		{}
-	} ;
-#endif
-	
-	ComputeXXtTask::UniquePtr ComputeXXtTask::create(
-		Matrix* result,
-		IntegerMatrix* counts,
-		SampleBounds const bounds,
-		std::string const& method
-	) {
-#if HAVE_CBLAS
-		if( method == "cblas" ) {
-			return ComputeXXtTask::UniquePtr(
-				new ComputeXXtUsingCBlasTask(
-					result, counts, bounds
-				)
-			) ;
-		} else
-#endif
-		 if( method == "eigen" ) {
-			return ComputeXXtTask::UniquePtr(
-				new ComputeXXtUsingEigenTask(
-					result, counts, bounds
-				)
-			) ;
-		} else {
-			assert(0) ;
-		}
-	}
-
-	struct Dispatcher {
-		typedef std::auto_ptr< Dispatcher > UniquePtr ;
-		typedef KinshipCoefficientComputer::Computation::Vector Vector ;
-		typedef KinshipCoefficientComputer::Computation::Matrix Matrix ;
-		typedef KinshipCoefficientComputer::Computation::IntegerVector IntegerVector ;
-		typedef KinshipCoefficientComputer::Computation::IntegerMatrix IntegerMatrix ;
-		typedef boost::function<
-			ComputeXXtTask::UniquePtr ( Matrix*, IntegerMatrix*, SampleBounds const )
-		> TaskFactory ;
-
-		virtual ~Dispatcher() {}
-		virtual void setup( std::size_t number_of_samples ) = 0 ;
-		virtual void get_storage( Vector* data, IntegerVector* nonmissingness ) = 0 ;
-		virtual void add_data( Vector* data, IntegerVector* nonmissingness ) = 0 ;
-		virtual void finalise() = 0 ;
-		virtual void wait_until_complete() = 0 ;
-	} ;
-
-
-
-	//
+	
 	// Return a tiling of a dxd matrix into (roughly) B blocks.
 	// Blocks should be roughly evenly sized.
 	// This implementation makes off-diagonal blocks half the size of diagonal blocks.
 	std::vector< SampleBounds > get_matrix_lower_diagonal_tiling( std::size_t d, std::size_t B ) {
 		// Because off-diagonal blocks involve about twice as much computation,
@@ -380,212 +144,11 @@
 //#if DEBUG_KINSHIP_COEFFICIENT_COMPUTER
 		std::cerr << "get_matrix_lower_diagonal_horizontal_strip_tiling: tiling has " << result.size() << " blocks in total.\n" ;
 //#endif
 		return result ;
 	}
-	struct MultiThreadedDispatcher: public Dispatcher {
-		typedef void (*accumulate_xxt_t)( Vector*, Matrix*, int const begin_sample_i, int const end_sample_i, int const begin_sample_j, int const end_sample_j, double const ) ;
-		typedef void (*accumulate_xxt_integer_t)( IntegerVector*, IntegerMatrix*, int const begin_sample_i, int const end_sample_i, int const begin_sample_j, int const end_sample_j, double const ) ;
-
-		MultiThreadedDispatcher(
-			Matrix& result,
-			IntegerMatrix& nonmissingness,
-			worker::Worker* worker,
-			TaskFactory task_factory
-		):
-			m_result( result ),
-			m_nonmissingness( nonmissingness ),
-			m_worker( worker ),
-			m_task_factory( task_factory ),
-			m_storage( 100, std::make_pair( Vector(), IntegerVector() ) ),
-			m_storage_index( 0 ),
-			m_data_index( 0 )
-#if USING_BOOST_THREADPOOL
-			,m_pool( m_worker->get_number_of_worker_threads() )
-#endif
-		{
-		}
-
-		~MultiThreadedDispatcher() {
-		}
-		
-		void setup( std::size_t number_of_samples ) {
-			// If there are N worker threads go for about two jobs per thread.
-			std::size_t numberOfTasks = 2 * std::sqrt( m_worker->get_number_of_worker_threads() ) ;
-
-			m_bounds = get_matrix_lower_diagonal_tiling( number_of_samples, numberOfTasks ) ;
-			for( std::size_t i = 0; i < m_bounds.size(); ++i ) {
-				m_tasks.push_back( 0 ) ;
-			}
-		}
-
-		void get_storage( Vector* data, IntegerVector* nonmissingness ) {
-			data->swap( m_storage[ m_storage_index % m_storage.size() ].first ) ;
-			nonmissingness->swap( m_storage[ m_storage_index % m_storage.size() ].second ) ;
-		}
-
-		void add_data( Vector* data, IntegerVector* nonmissingness ) {
-			// Take the data (without copying it).
-			data->swap( m_storage[ m_storage_index % m_storage.size() ].first ) ;
-			nonmissingness->swap( m_storage[ m_storage_index % m_storage.size() ].second ) ;
-	
-			// Add 20 SNPs at a time before submitting.
-			bool const schedule = ( m_data_index % 20 ) == 0 ;
-			++m_data_index ;
-
-			for( std::size_t task_index = 0; task_index < m_bounds.size(); ++task_index ) {
-				std::size_t const bound_index = task_index ;
-				
-				if( m_tasks.is_null( task_index ) ) {
-					ComputeXXtTask::UniquePtr new_task = m_task_factory(
-						&m_result,
-						&m_nonmissingness,
-						m_bounds[ bound_index ]
-					) ;
-					m_tasks.replace( task_index, new_task ) ;
-				}
-				m_tasks[ task_index ].add_data(
-					m_storage[ m_storage_index % m_storage.size() ].first,
-					m_storage[ m_storage_index % m_storage.size() ].second
-				) ;
-
-				if( schedule ) {
-					m_pool.schedule( boost::bind( &ComputeXXtTask::operator(), &m_tasks[ task_index ] )) ;
-				}
-			}
-			if( schedule ) {
-				m_pool.wait() ;
-				for( std::size_t i = 0; i < m_tasks.size(); ++i ) {
-					m_tasks.replace( i, 0 ) ;
-				}
-			}
-
-			++m_storage_index ;
-		}
-	
-		void finalise() {
-			if( m_storage_index % m_storage.size() > 0 ) {
-				// we have unprocessed data.
-				for( std::size_t task_index = 0; task_index < m_bounds.size(); ++task_index ) {
-					m_pool.schedule( boost::bind( &ComputeXXtTask::operator(), &m_tasks[ task_index ] )) ;
-				}
-				m_pool.wait() ;
-				for( std::size_t i = 0; i < m_tasks.size(); ++i ) {
-					m_tasks.replace( i, 0 ) ;
-				}
-			}
-		}
-
-		void wait_until_complete() {
-		}
-
-	private:
-		Matrix& m_result ;
-		IntegerMatrix& m_nonmissingness ;
-		worker::Worker* m_worker ;
-		TaskFactory m_task_factory ;
-		std::vector< SampleBounds > m_bounds ;
-		boost::ptr_deque< boost::nullable< ComputeXXtTask > > m_tasks ;
-		std::vector<
-			std::pair<
-				KinshipCoefficientComputer::Computation::Vector,
-				KinshipCoefficientComputer::Computation::IntegerVector
-			>
-		> m_storage ;
-		std::size_t m_storage_index ;
-		std::size_t m_data_index ;
-#if USING_BOOST_THREADPOOL
-		boost::threadpool::pool m_pool ;
-#endif
-	} ;
-
-	NormaliseGenotypesAndComputeXXt::UniquePtr NormaliseGenotypesAndComputeXXt::create( worker::Worker* worker, std::string const& method ) {
-		return NormaliseGenotypesAndComputeXXt::UniquePtr( new NormaliseGenotypesAndComputeXXt( worker, method) ) ;
-	}
-
-	NormaliseGenotypesAndComputeXXt::NormaliseGenotypesAndComputeXXt(
-		worker::Worker* worker,
-		std::string const& method
-	):
-		m_call_threshhold( 0.9 ),
-		m_allele_frequency_threshhold( 0.001 ),
-		m_number_of_snps_included( 0 ),
-		m_dispatcher(
-			new impl::MultiThreadedDispatcher(
-				m_result,
-				m_nonmissingness,
-				worker,
-				boost::bind(
-					&ComputeXXtTask::create,
-					_1, _2, _3, method
-				)
-			)
-		)
-	{}
-
-	KinshipCoefficientComputer::Computation::Matrix const& NormaliseGenotypesAndComputeXXt::result() const { return m_result ; }
-	KinshipCoefficientComputer::Computation::IntegerMatrix const& NormaliseGenotypesAndComputeXXt::nonmissingness() const { return m_nonmissingness ; }
-
-	std::string NormaliseGenotypesAndComputeXXt::get_summary() const {
-		return (
-			boost::format( "NormaliseGenotypesAndComputeXXt( min allele frequency %.3f)" )
-			% m_allele_frequency_threshhold
-		).str()
-		;
-	}
-
-	void NormaliseGenotypesAndComputeXXt::begin_processing_snps( std::size_t number_of_samples, genfile::SNPDataSource::Metadata const& ) {
-		m_result.setZero( number_of_samples, number_of_samples ) ;
-		m_nonmissingness.setZero( number_of_samples, number_of_samples ) ;
-		m_dispatcher->setup( number_of_samples ) ;
-	}
-	
-	void NormaliseGenotypesAndComputeXXt::processed_snp(
-		genfile::VariantIdentifyingData const& id_data,
-		genfile::VariantDataReader::SharedPtr data_reader
-	) {
-		KinshipCoefficientComputer::Computation::Vector genotypes ;
-		KinshipCoefficientComputer::Computation::IntegerVector nonmissingness ;
-
-		m_dispatcher->get_storage( &genotypes, &nonmissingness ) ;
-
-		genotypes.setZero( m_result.rows() ) ;
-		nonmissingness.setZero( m_result.rows() ) ;
-
-		data_reader->get(
-			":genotypes:",
-			genfile::vcf::get_threshholded_calls( genotypes, nonmissingness, m_call_threshhold, 0, 0, 1, 2 )
-		) ;
-
-		// estimate allele frequency using data augmentation:
-		// add two haplotypes, one with each allele.
-		// This prevents the estimate becoming one or zero.
-		double const posterior_allele_frequency = (1 + genotypes.sum()) / ( 2 + (2.0 * nonmissingness.sum()) ) ;
-		double const allele_frequency = genotypes.sum() / (2.0 * nonmissingness.sum()) ;
-		if( std::min( allele_frequency, 1.0 - allele_frequency ) > m_allele_frequency_threshhold ) {
-			pca::mean_centre_genotypes( &genotypes, nonmissingness, allele_frequency ) ;
-			// Could compute actual SNP sd:
-			//double const sd = std::sqrt( ( genotypes.array().square().sum() - ( genotypes.sum() * genotypes.sum() ) ) / ( nonmissingness.sum() - 1 ) ) ;
-			// Or sd based on allele frequency:
-			double const sd = std::sqrt( ( 2.0 * posterior_allele_frequency * ( 1.0 - posterior_allele_frequency )) ) ;
-			genotypes /= sd ;
-			m_dispatcher->add_data( &genotypes, &nonmissingness ) ;
-			++m_number_of_snps_included ;
-		}
-	}
-	
-	void NormaliseGenotypesAndComputeXXt::end_processing_snps() {
-		m_dispatcher->finalise() ;
-		m_result.array() /= m_nonmissingness.array().cast< double >() ;
-	}
-	
-	std::size_t NormaliseGenotypesAndComputeXXt::number_of_snps_included() const {
-		return m_number_of_snps_included ;
-	}
-}
-
-namespace impl {
+
 	NTaskDispatcher::NTaskDispatcher(
 		worker::Worker* worker
 	):
 		m_worker( worker )
 	{

Index: components/RelatednessComponent/src/RelatednessComponent.cpp
==================================================================
--- components/RelatednessComponent/src/RelatednessComponent.cpp
+++ components/RelatednessComponent/src/RelatednessComponent.cpp
@@ -10,11 +10,10 @@
 #include "genfile/VariantDataReader.hpp"
 #include "genfile/SNPDataSourceProcessor.hpp"
 #include "genfile/SingleSNPGenotypeProbabilities.hpp"
 #include "statfile/BuiltInTypeStatSink.hpp"
 #include "statfile/BuiltInTypeStatSource.hpp"
-#include "worker/Task.hpp"
 #include "appcontext/FileUtil.hpp"
 #include "appcontext/get_current_time_as_string.hpp"
 #include "components/SampleSummaryComponent/SampleStorage.hpp"
 #include "components/RelatednessComponent/RelatednessComponent.hpp"
 #include "components/RelatednessComponent/PCAComputer.hpp"
@@ -56,13 +55,12 @@
 		 	"Put the output in the file specified in the second argument." )
 		.set_takes_values_until_next_option()
 		.set_maximum_multiplicity(1) ;
 	options[ "-kinship-method" ]
 		.set_description( "Method to use for relatedness matrix computation."
-			"The default is \"lookup-table\", which uses a lookup table to compute kinship values across"
-			" several SNPs at a time.  This is usually fastest.  Alternatives are \"cblas\""
-			" or \"eigen\", which use those linear algebra libraries to compute the matrix."
+			"The only permitted value is \"lookup-table\", which uses a lookup table to compute kinship values across"
+			" several SNPs at a time.  This is usually fastest."
 		)
 		.set_takes_single_value()
 		.set_default_value( "lookup-table" )
 	;
 
@@ -189,29 +187,21 @@
 	}
 	
 	if( m_options.check( "-kinship" )) {
 		KinshipCoefficientComputer::Computation::UniquePtr computation ;
 		std::string const& method = m_options.get< std::string >( "-kinship-method" ) ;
-		if( method == "cblas" ) {
-			computation.reset(
-				impl::NormaliseGenotypesAndComputeXXt::create( m_worker, "cblas" ).release()
-			) ;
-		} else if( method == "eigen" ) {
-			computation.reset(
-				impl::NormaliseGenotypesAndComputeXXt::create( m_worker, "eigen" ).release()
-			) ;
-		} else if( method == "lookup-table" ) {
+		if( method == "lookup-table" ) {
 			computation.reset(
 				impl::NormaliseGenotypesAndComputeXXtFast::create(
 					m_worker, 4
 				).release()
 			) ;
 		} else {
 			throw genfile::BadArgumentError(
 				"RelatednessComponent::setup()",
 				"-method " + method,
-				"Method must be \"fast\", \"cblas\", or \"eigen\""
+				"Method must be \"lookup-table\""
 			) ;
 		}
 		
 		m_ui_context.logger() << "RelatednessComponent::setup(): using computation: " << computation->get_summary() << ".\n" ;
 

Index: components/RelatednessComponent/wscript
==================================================================
--- components/RelatednessComponent/wscript
+++ components/RelatednessComponent/wscript
@@ -1,37 +1,11 @@
-import os.path
-import glob
-#import UnitTest
-
 def configure( conf ):
 	pass
 
-def create_tests( bld ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'test_snp_summary_component',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'genfile boost boost-unit_test_framework',
-		uselib = 'BOOST BOOST_SYSTEM BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
-		target = 'RelatednessComponent',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = 'ZLIB BOOST BOOST_IOSTREAMS BOOST_SYSTEM BOOST_FILESYSTEM CBLAS LAPACK',
-		uselib_local = 'eigen threadpool db statfile appcontext worker genfile boost SampleSummaryComponent',
-		export_incdirs = './include'
-	)
-
-	#create_tests( bld )
+def build( bld ):
+	bld.stlib(
+		target = 'RelatednessComponent',
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		includes='./include',
+		use = 'eigen metro statfile appcontext worker genfile boost SampleSummaryComponent ZLIB CBLAS LAPACK',
+		export_includes = './include'
+	)

Index: components/SNPOutputComponent/include/components/SNPOutputComponent/SQLiteGenotypesSNPDataSink.hpp
==================================================================
--- components/SNPOutputComponent/include/components/SNPOutputComponent/SQLiteGenotypesSNPDataSink.hpp
+++ components/SNPOutputComponent/include/components/SNPOutputComponent/SQLiteGenotypesSNPDataSink.hpp
@@ -37,13 +37,13 @@
 	private:
         std::string m_genotype_field ;
         std::string m_intensity_field ;
 		qcdb::DBOutputter::UniquePtr m_outputter ;
         genfile::CohortIndividualSource const& m_samples ;
-		db::Connection::StatementPtr m_insert_sample_stmnt ;
-		db::Connection::StatementPtr m_insert_genotype_stmnt ;
-		db::Connection::StatementPtr m_insert_intensity_stmnt ;
+		genfile::db::Connection::StatementPtr m_insert_sample_stmnt ;
+		genfile::db::Connection::StatementPtr m_insert_genotype_stmnt ;
+		genfile::db::Connection::StatementPtr m_insert_intensity_stmnt ;
 
 		std::vector< genfile::VariantIdentifyingData > m_genotype_snps ;
 		std::vector< std::vector< uint8_t > > m_genotype_data ;
 		std::size_t m_genotype_data_i ;
 

Index: components/SNPOutputComponent/include/components/SNPOutputComponent/SQLiteHaplotypesSNPDataSink.hpp
==================================================================
--- components/SNPOutputComponent/include/components/SNPOutputComponent/SQLiteHaplotypesSNPDataSink.hpp
+++ components/SNPOutputComponent/include/components/SNPOutputComponent/SQLiteHaplotypesSNPDataSink.hpp
@@ -32,11 +32,11 @@
 		
 	private:
 		std::string m_genotype_field ; 
 		qcdb::DBOutputter::UniquePtr m_outputter ;
 		genfile::CohortIndividualSource const& m_samples ;
-		db::Connection::StatementPtr m_insert_data_stmnt ;
+		genfile::db::Connection::StatementPtr m_insert_data_stmnt ;
 
 		std::vector< genfile::VariantIdentifyingData > m_snps ;
 		std::vector< std::vector< uint8_t > > m_data ;
 		std::size_t m_data_i ;
 

Index: components/SNPOutputComponent/src/SQLiteGenotypesSNPDataSink.cpp
==================================================================
--- components/SNPOutputComponent/src/SQLiteGenotypesSNPDataSink.cpp
+++ components/SNPOutputComponent/src/SQLiteGenotypesSNPDataSink.cpp
@@ -31,11 +31,11 @@
 	m_outputter( outputter ),
 	m_samples( samples ),
 	m_genotype_data_i( 0 ),
 	m_intensity_data_i( 0 )
 {
-	db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 2400 ) ;
+	genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 2400 ) ;
 	m_outputter->connection().run_statement(
 		"CREATE TABLE IF NOT EXISTS Genotype ( "
 		"  analysis_id INT NOT NULL REFERENCES Analysis( id ), "
 		"  variant_id INT NOT NULL REFERENCES Variant( id ), "
 		"  N INT NOT NULL,"
@@ -432,11 +432,11 @@
 		flush_intensity_data( m_intensity_data_i ) ;
 		m_intensity_data_i = 0 ;
 	}
 	
 	{
-		db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 2400 ) ;
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 2400 ) ;
 		m_outputter->connection().run_statement( "CREATE INDEX IF NOT EXISTS IntensityVariantIndex ON Intensity ( variant_id )" ) ;
 		m_outputter->connection().run_statement( "CREATE INDEX IF NOT EXISTS IntensityAnalysisVariantIndex ON Intensity ( analysis_id, variant_id )" ) ;
 		m_outputter->connection().run_statement( "CREATE INDEX IF NOT EXISTS GenotypeVariantIndex ON Genotype ( variant_id )" ) ;
 		m_outputter->connection().run_statement( "CREATE INDEX IF NOT EXISTS GenotypeAnalysisVariantIndex ON Genotype ( analysis_id, variant_id )" ) ;
 	}
@@ -443,17 +443,17 @@
 
 	m_outputter->finalise() ;
 }
 
 void SQLiteGenotypesSNPDataSink::flush_genotype_data( std::size_t const data_count ) {
-	db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 2400 ) ;
+	genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 2400 ) ;
 
 #if DEBUG_SQLITEGENOTYPESNPDATASINK
 	std::cerr << "Flushing " << data_count << " genotypes..." ;
 	std::size_t max_data_size = 0 ;
 #endif
-	std::vector< db::Connection::RowId > variant_ids( data_count ) ;
+	std::vector< genfile::db::Connection::RowId > variant_ids( data_count ) ;
 	for( std::size_t i = 0; i < data_count; ++i ) {
 		variant_ids[i] = m_outputter->get_or_create_variant( m_genotype_snps[i] ) ;
 	}
 #if DEBUG_SQLITEGENOTYPESNPDATASINK
 	std::cerr << "stored variants..." ;
@@ -477,17 +477,17 @@
 	std::cerr << "Done, max data size was " << max_data_size << ".\n" ;
 #endif
 }
 
 void SQLiteGenotypesSNPDataSink::flush_intensity_data( std::size_t const data_count ) {
-	db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 1200 ) ;
+	genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 1200 ) ;
 
 #if DEBUG_SQLITEGENOTYPESNPDATASINK
 	std::cerr << "Flushing " << data_count << " intensities..." ;
 	std::size_t max_data_size = 0 ;
 #endif
-	std::vector< db::Connection::RowId > variant_ids( data_count ) ;
+	std::vector< genfile::db::Connection::RowId > variant_ids( data_count ) ;
 	for( std::size_t i = 0; i < data_count; ++i ) {
 		variant_ids[i] = m_outputter->get_or_create_variant( m_intensity_snps[i] ) ;
 	}
 #if DEBUG_SQLITEGENOTYPESNPDATASINK
 	std::cerr << "stored variants..." ;

Index: components/SNPOutputComponent/src/SQLiteHaplotypesSNPDataSink.cpp
==================================================================
--- components/SNPOutputComponent/src/SQLiteHaplotypesSNPDataSink.cpp
+++ components/SNPOutputComponent/src/SQLiteHaplotypesSNPDataSink.cpp
@@ -327,17 +327,17 @@
 	}
 	m_outputter->finalise() ;
 }
 
 void SQLiteHaplotypesSNPDataSink::flush_data( std::size_t const data_count ) {
-	db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 600 ) ;
+	genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter->connection().open_transaction( 600 ) ;
 
 #if DEBUG_SQLITEHAPLOTYPESSNPDATASINK
 	std::cerr << "Flushing " << data_count << " elements..." ;
 	std::size_t max_data_size = 0 ;
 #endif
-	std::vector< db::Connection::RowId > variant_ids( data_count ) ;
+	std::vector< genfile::db::Connection::RowId > variant_ids( data_count ) ;
 	for( std::size_t i = 0; i < data_count; ++i ) {
 		variant_ids[i] = m_outputter->get_or_create_variant( m_snps[i] ) ;
 	}
 #if DEBUG_SQLITEHAPLOTYPESSNPDATASINK
 	std::cerr << "stored variants..." ;

Index: components/SNPOutputComponent/wscript
==================================================================
--- components/SNPOutputComponent/wscript
+++ components/SNPOutputComponent/wscript
@@ -1,37 +1,11 @@
-import os.path
-import glob
-#import UnitTest
-
 def configure( conf ):
 	pass
-
-def create_tests( bld ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'test_snp_output_component',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'genfile',
-		uselib = 'BOOST BOOST_SYSTEM BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
 
 def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
+	bld.stlib(
 		target = 'SNPOutputComponent',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = 'ZLIB BOOST BOOST_IOSTREAMS BOOST_SYSTEM BOOST_FILESYSTEM',
-		uselib_local = 'eigen genfile db statfile integration appcontext qcdb metro',
-		export_incdirs = './include'
-	)
-
-	#create_tests( bld )
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		includes = './include',
+		use = 'eigen genfile statfile integration appcontext qcdb metro ZLIB boost',
+		export_includes = './include'
+	)

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/AssociationTest.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/AssociationTest.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/AssociationTest.hpp
@@ -12,21 +12,23 @@
 #include <limits>
 #include "genfile/CohortIndividualSource.hpp"
 #include "appcontext/OptionProcessor.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-struct AssociationTest: public SNPSummaryComputation {
-	typedef Eigen::VectorXd Vector ;
-	typedef Eigen::MatrixXd Matrix ;
-
-	static UniquePtr create(
-		std::string const& type,
-		std::string const& phenotype_name,
-		std::vector< std::string > const& covariate_names,
-		genfile::CohortIndividualSource const& samples,
-		appcontext::OptionProcessor const& options
-	) ;
-
-private:
-} ;
+namespace stats {
+	struct AssociationTest: public SNPSummaryComputation {
+		typedef Eigen::VectorXd Vector ;
+		typedef Eigen::MatrixXd Matrix ;
+
+		static UniquePtr create(
+			std::string const& type,
+			std::string const& phenotype_name,
+			std::vector< std::string > const& covariate_names,
+			genfile::CohortIndividualSource const& samples,
+			appcontext::OptionProcessor const& options
+		) ;
+
+	private:
+	} ;
+}
 
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/Bed3Annotation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/Bed3Annotation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/Bed3Annotation.hpp
@@ -15,31 +15,33 @@
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 #include "genfile/Chromosome.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/wildcard.hpp"
 
-// Annotate each variant with a set of 1's or 0's according to whether
-// it lies in ranges in one or more BED files (plus or minus a margin).
-// This just uses the first three columns (chrom, start, end) of the BED file.
-// Filenames of BED files are passed in using the add_annotation() function.
-// This class translates between BED style 0-based, half-open coordinates
-// and the 1-based coordinates used in qctool implicitly.
-struct Bed3Annotation: public SNPSummaryComputation
-{
-public:
-	typedef std::auto_ptr< Bed3Annotation > UniquePtr ;
-	static UniquePtr create() ;
-
-public:
-	Bed3Annotation() ;
-	void add_annotation( std::string const& name, std::string const& filename, int left_margin_bp = 0, int right_margin_bp = 0 ) ;
-	void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
-
-	std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
-private:
-	typedef boost::icl::interval_set< genfile::GenomePosition > Annotation ;
-	typedef std::map< std::string, Annotation > AnnotationMap ;
-	AnnotationMap m_annotations ;
-	std::vector< std::string > m_annotation_names ;
-} ;
+namespace stats {
+	// Annotate each variant with a set of 1's or 0's according to whether
+	// it lies in ranges in one or more BED files (plus or minus a margin).
+	// This just uses the first three columns (chrom, start, end) of the BED file.
+	// Filenames of BED files are passed in using the add_annotation() function.
+	// This class translates between BED style 0-based, half-open coordinates
+	// and the 1-based coordinates used in qctool implicitly.
+	struct Bed3Annotation: public SNPSummaryComputation
+	{
+	public:
+		typedef std::auto_ptr< Bed3Annotation > UniquePtr ;
+		static UniquePtr create() ;
+
+	public:
+		Bed3Annotation() ;
+		void add_annotation( std::string const& name, std::string const& filename, int left_margin_bp = 0, int right_margin_bp = 0 ) ;
+		void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
+
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+	private:
+		typedef boost::icl::interval_set< genfile::GenomePosition > Annotation ;
+		typedef std::map< std::string, Annotation > AnnotationMap ;
+		AnnotationMap m_annotations ;
+		std::vector< std::string > m_annotation_names ;
+	} ;
+}
 
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/Bed4Annotation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/Bed4Annotation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/Bed4Annotation.hpp
@@ -15,32 +15,34 @@
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 #include "genfile/Chromosome.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/wildcard.hpp"
 
-// Annotate each variant with a set values assigned to ranges in one or more BED files
-// (plus or minus a margin).
-// This uses the first four columns of the BED file (chrom, start, end, value).
-// Filenames of BED files are passed in using the add_annotation() function.
-// This class translates between BED style 0-based, half-open coordinates
-// and the 1-based coordinates used in qctool implicitly.
-struct Bed4Annotation: public SNPSummaryComputation
-{
-public:
-	typedef std::auto_ptr< Bed4Annotation > UniquePtr ;
-	static UniquePtr create() ;
-
-public:
-	Bed4Annotation() ;
-	void add_annotation( std::string const& name, std::string const& filename, int left_margin_bp = 0, int right_margin_bp = 0 ) ;
-	void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
-
-	std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
-private:
-	typedef std::set< std::string > Payload ;
-	typedef boost::icl::interval_map< genfile::GenomePosition, Payload > Annotation ;
-	typedef std::map< std::string, Annotation > AnnotationMap ;
-	AnnotationMap m_annotations ;
-	std::vector< std::string > m_annotation_names ;
-} ;
+namespace stats {
+	// Annotate each variant with a set values assigned to ranges in one or more BED files
+	// (plus or minus a margin).
+	// This uses the first four columns of the BED file (chrom, start, end, value).
+	// Filenames of BED files are passed in using the add_annotation() function.
+	// This class translates between BED style 0-based, half-open coordinates
+	// and the 1-based coordinates used in qctool implicitly.
+	struct Bed4Annotation: public SNPSummaryComputation
+	{
+	public:
+		typedef std::auto_ptr< Bed4Annotation > UniquePtr ;
+		static UniquePtr create() ;
+
+	public:
+		Bed4Annotation() ;
+		void add_annotation( std::string const& name, std::string const& filename, int left_margin_bp = 0, int right_margin_bp = 0 ) ;
+		void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
+
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+	private:
+		typedef std::set< std::string > Payload ;
+		typedef boost::icl::interval_map< genfile::GenomePosition, Payload > Annotation ;
+		typedef std::map< std::string, Annotation > AnnotationMap ;
+		AnnotationMap m_annotations ;
+		std::vector< std::string > m_annotation_names ;
+	} ;
+}
 
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/CallComparerComponent.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/CallComparerComponent.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/CallComparerComponent.hpp
@@ -14,60 +14,61 @@
 #include "PairwiseCallComparerManager.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputationManager.hpp"
 #include "qcdb/Storage.hpp"
 
-struct CallComparerProcessor: public SNPSummaryComputation
-{
-public:
-	typedef std::auto_ptr< CallComparerProcessor > UniquePtr ;
-	static UniquePtr create(
-		PairwiseCallComparerManager::UniquePtr call_comparer,
-		std::vector< std::string > const& call_fields
-	) ;
-
-public:
-	CallComparerProcessor(
-		PairwiseCallComparerManager::UniquePtr call_comparer,
-		std::vector< std::string > const& call_fields
-	) ;
-
-	public:
-
-		void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
-		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
-
-	private:
-		PairwiseCallComparerManager::UniquePtr m_call_comparer ;
-		std::vector< std::string > m_call_fields ;
-		bool m_begun ;
-		PairwiseCallComparerManager::MergeClient::UniquePtr m_consensus_caller ;
-		Eigen::MatrixXd m_calls ;
-} ;
-
-struct CallComparerComponent: public boost::noncopyable
-{
-	static void declare_options( appcontext::OptionProcessor& options ) ;
-
-	typedef std::auto_ptr< CallComparerComponent > UniquePtr ;
-	static UniquePtr create(
-		genfile::CohortIndividualSource const& samples,
-		appcontext::OptionProcessor const& options,
-		appcontext::UIContext& ui_context
-	) ;
-
-public:
-	CallComparerComponent(
-		genfile::CohortIndividualSource const& m_samples,
-		appcontext::OptionProcessor const& options,
-		appcontext::UIContext& ui_context
-	) ;
-	
-	void setup( SNPSummaryComputationManager&, qcdb::Storage::SharedPtr ) const ;
-
-private:
-	genfile::CohortIndividualSource const& m_samples ;
-	appcontext::OptionProcessor const& m_options ;
-} ;
-
+namespace stats {
+	struct CallComparerProcessor: public SNPSummaryComputation
+	{
+	public:
+		typedef std::auto_ptr< CallComparerProcessor > UniquePtr ;
+		static UniquePtr create(
+			PairwiseCallComparerManager::UniquePtr call_comparer,
+			std::vector< std::string > const& call_fields
+		) ;
+
+	public:
+		CallComparerProcessor(
+			PairwiseCallComparerManager::UniquePtr call_comparer,
+			std::vector< std::string > const& call_fields
+		) ;
+
+		public:
+
+			void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
+			std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+
+		private:
+			PairwiseCallComparerManager::UniquePtr m_call_comparer ;
+			std::vector< std::string > m_call_fields ;
+			bool m_begun ;
+			PairwiseCallComparerManager::MergeClient::UniquePtr m_consensus_caller ;
+			Eigen::MatrixXd m_calls ;
+	} ;
+
+	struct CallComparerComponent: public boost::noncopyable
+	{
+		static void declare_options( appcontext::OptionProcessor& options ) ;
+
+		typedef std::auto_ptr< CallComparerComponent > UniquePtr ;
+		static UniquePtr create(
+			genfile::CohortIndividualSource const& samples,
+			appcontext::OptionProcessor const& options,
+			appcontext::UIContext& ui_context
+		) ;
+
+	public:
+		CallComparerComponent(
+			genfile::CohortIndividualSource const& m_samples,
+			appcontext::OptionProcessor const& options,
+			appcontext::UIContext& ui_context
+		) ;
+	
+		void setup( SNPSummaryComputationManager&, qcdb::Storage::SharedPtr ) const ;
+
+	private:
+		genfile::CohortIndividualSource const& m_samples ;
+		appcontext::OptionProcessor const& m_options ;
+	} ;
+}
 
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/ClusterFitComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/ClusterFitComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/ClusterFitComputation.hpp
@@ -17,11 +17,11 @@
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/VariantDataReader.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-namespace snp_summary_component {
+namespace stats {
 	struct ClusterFitComputation: public SNPSummaryComputation {
 		typedef std::auto_ptr< ClusterFitComputation > UniquePtr ;
 		ClusterFitComputation(
 			double nu,
 			double regularisationVariance = 0.5,

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/CrossDataSetConcordanceComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/CrossDataSetConcordanceComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/CrossDataSetConcordanceComputation.hpp
@@ -12,11 +12,11 @@
 #include <Eigen/Core>
 #include "genfile/CohortIndividualSource.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-namespace snp_stats {
+namespace stats {
 	struct CrossDataSetSampleMapper
 	{
 	public:
 		typedef std::vector< genfile::VariantEntry > SampleIdList ;
 		typedef std::multimap< std::size_t, std::size_t > SampleMapping ;

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/CrossDataSetHaplotypeComparisonComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/CrossDataSetHaplotypeComparisonComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/CrossDataSetHaplotypeComparisonComputation.hpp
@@ -13,11 +13,11 @@
 #include "genfile/CohortIndividualSource.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 #include "components/SNPSummaryComponent/CrossDataSetConcordanceComputation.hpp"
 
-namespace snp_stats {
+namespace stats {
 	struct CrossDataSetHaplotypeComparisonComputation: public CrossDataSetComparison
 	{
 	public:
 		CrossDataSetHaplotypeComparisonComputation(
 			genfile::CohortIndividualSource const& m_samples,

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/DifferentialMissingnessComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/DifferentialMissingnessComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/DifferentialMissingnessComputation.hpp
@@ -17,21 +17,22 @@
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/VariantDataReader.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-struct DifferentialMissingnessComputation: public SNPSummaryComputation {
-	typedef std::map< genfile::VariantEntry, std::vector< int > > StrataMembers ;
-	static UniquePtr create( std::string const& stratification_name, StrataMembers const& strata_members ) ;
-	DifferentialMissingnessComputation( std::string const& stratification_name, StrataMembers const& strata_members, double threshhold = 0.9 ) ;
-	void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
-	std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
-private:
-	std::string const m_stratification_name ;
-	StrataMembers const m_strata_members ;
-	std::vector< int > const m_strata_levels ;
-	double const m_threshhold ;
-private:
-	std::vector< int > compute_strata_levels( StrataMembers const& strata_members ) const ;
-} ;
-
+namespace stats {
+	struct DifferentialMissingnessComputation: public SNPSummaryComputation {
+		typedef std::map< genfile::VariantEntry, std::vector< int > > StrataMembers ;
+		static UniquePtr create( std::string const& stratification_name, StrataMembers const& strata_members ) ;
+		DifferentialMissingnessComputation( std::string const& stratification_name, StrataMembers const& strata_members, double threshhold = 0.9 ) ;
+		void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+	private:
+		std::string const m_stratification_name ;
+		StrataMembers const m_strata_members ;
+		std::vector< int > const m_strata_levels ;
+		double const m_threshhold ;
+	private:
+		std::vector< int > compute_strata_levels( StrataMembers const& strata_members ) const ;
+	} ;
+}
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/FileOutputter.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/FileOutputter.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/FileOutputter.hpp
@@ -12,11 +12,11 @@
 #include "genfile/VariantEntry.hpp"
 #include "genfile/VariantIdentifyingData.hpp"
 #include "statfile/BuiltInTypeStatSink.hpp"
 #include "components/SNPSummaryComponent/Storage.hpp"
 
-namespace snp_summary_component {
+namespace stats {
 	struct FileOutputter: public Storage {
 		static UniquePtr create( std::string const& filename ) { return UniquePtr( new FileOutputter( filename ) ) ; }
 		static SharedPtr create_shared( std::string const& filename ) { return SharedPtr( new FileOutputter( filename ) ) ; }
 
 		FileOutputter( std::string const& filename ):

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/GeneticMapAnnotation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/GeneticMapAnnotation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/GeneticMapAnnotation.hpp
@@ -12,28 +12,29 @@
 #include "genfile/wildcard.hpp"
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantDataReader.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-struct GeneticMapAnnotation: public SNPSummaryComputation
-{
-public:
-	typedef std::auto_ptr< GeneticMapAnnotation > UniquePtr ;
-	typedef boost::function< void ( std::size_t, std::size_t ) > ProgressCallback ;
-	static UniquePtr create(
-		std::vector< genfile::wildcard::FilenameMatch > const& filenames,
-		ProgressCallback = ProgressCallback()
-	) ;
-
-public:
-	GeneticMapAnnotation(
-		std::vector< genfile::wildcard::FilenameMatch > const& filenames,
-		ProgressCallback = ProgressCallback()
-	) ;
-	void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
-	std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
-private:
-	genfile::GeneticMap::UniquePtr m_map ;
-	std::set< genfile::Chromosome > m_map_chromosomes ;
-} ;
-
+namespace stats {
+	struct GeneticMapAnnotation: public SNPSummaryComputation
+	{
+	public:
+		typedef std::auto_ptr< GeneticMapAnnotation > UniquePtr ;
+		typedef boost::function< void ( std::size_t, std::size_t ) > ProgressCallback ;
+		static UniquePtr create(
+			std::vector< genfile::wildcard::FilenameMatch > const& filenames,
+			ProgressCallback = ProgressCallback()
+		) ;
+
+	public:
+		GeneticMapAnnotation(
+			std::vector< genfile::wildcard::FilenameMatch > const& filenames,
+			ProgressCallback = ProgressCallback()
+		) ;
+		void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+	private:
+		genfile::GeneticMap::UniquePtr m_map ;
+		std::set< genfile::Chromosome > m_map_chromosomes ;
+	} ;
+}
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/GenomeSequence.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/GenomeSequence.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/GenomeSequence.hpp
@@ -30,38 +30,34 @@
 	typedef std::pair< std::pair< genfile::Position, genfile::Position >, ChromosomeSequence > ChromosomeRangeAndSequence ;
 	typedef std::map< Chromosome, ChromosomeRangeAndSequence > SequenceData ;
 	typedef genfile::VariantEntry OptionalString ;
 	typedef boost::function< void ( std::size_t, boost::optional< std::size_t > ) > ProgressCallback ;
 public:
-	static UniquePtr create( std::string const& fasta_filename, ProgressCallback ) ;
+	static UniquePtr create( std::vector< std::string > const& fasta_filenames, ProgressCallback ) ;
 
 public:
 
 	GenomeSequence( std::string const& fasta_filename, ProgressCallback ) ;
+	GenomeSequence( std::vector< std::string > const& fasta_filenames, ProgressCallback ) ;
 
-	SequenceData const& sequence() const { return m_sequence ; }
-	std::string const get_spec() const { return m_fasta_filename ; }
+	SequenceData const& sequence() const { return m_data ; }
+	std::string const get_spec() const ;
 	std::string get_summary( std::string const& prefix, std::size_t column_width = 80 ) const ;
+	std::vector< genfile::GenomePositionRange > get_ranges() const ;
 
 	bool has_chromosome( genfile::Chromosome const& chromosome ) const ;
 	char get_base( genfile::GenomePosition const& position ) const ;
 	void get_sequence( genfile::Chromosome const& chromosome, genfile::Position start, genfile::Position end, std::deque< char >* result ) const ;
 	PhysicalSequenceRange get_sequence( genfile::Chromosome const& chromosome, genfile::Position start, genfile::Position end ) const ;
 
 private:
-	std::string const m_fasta_filename ;
-	SequenceData m_sequence ;
+	std::vector< std::string > const m_fasta_filenames ;
+	SequenceData m_data ;
 	std::map< genfile::Chromosome, std::string > m_identifiers ;
 	boost::optional< std::string > m_build ;
 	boost::optional< std::string > m_organism ;
 	
-	void load_sequence( std::vector< genfile::wildcard::FilenameMatch > const& files, SequenceData* sequence, ProgressCallback callback ) ;
-	void load_sequence(
-		genfile::wildcard::FilenameMatch const& file,
-		Chromosome* chromosome,
-		ChromosomeSequence* sequence,
-		std::pair< genfile::Position, genfile::Position >* range,
-		std::string* identifier
-	) ;
+	void load_sequence( std::vector< std::string > const& filenames, ProgressCallback callback ) ;
+	void load_sequence( std::string const& name, std::string const& filename ) ;
 } ;
 
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/HWEComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/HWEComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/HWEComputation.hpp
@@ -15,12 +15,12 @@
 #include "genfile/Error.hpp"
 #include "metro/likelihood/Multinomial.hpp"
 #include "components/SNPSummaryComponent/SNPHWE.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-namespace snp_summary_component {
-	struct HWEComputation: public SNPSummaryComputation
+namespace stats {
+	struct HWEComputation: public stats::SNPSummaryComputation
 	{
 		HWEComputation() ;
 	
 		void operator()( VariantIdentifyingData const& snp, Genotypes const& genotypes, Ploidy const& ploidy, genfile::VariantDataReader&, ResultCallback callback ) ;
 		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;

ADDED   components/SNPSummaryComponent/include/components/SNPSummaryComponent/InfoComputation.hpp
Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/InfoComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/InfoComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/InfoComputation.hpp
@@ -0,0 +1,85 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef QCTOOL_INFO_COMPUTATION_HPP
+#define QCTOOL_INFO_COMPUTATION_HPP
+
+#include <string>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include <boost/function.hpp>
+#include <Eigen/Core>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/VariantDataReader.hpp"
+#include "appcontext/OptionProcessor.hpp"
+#include "metro/SampleRange.hpp"
+#include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
+
+namespace stats {
+	namespace impl {
+		struct InfoComputation: public boost::noncopyable {
+		public:
+			typedef SNPSummaryComputation::VariantIdentifyingData VariantIdentifyingData ;
+			typedef SNPSummaryComputation::Genotypes Genotypes ;
+			typedef SNPSummaryComputation::Ploidy Ploidy ;
+
+		public:
+			InfoComputation() ;
+			
+			void compute(
+				VariantIdentifyingData const& snp,
+				Genotypes const& genotypes,
+				Ploidy const& ploidy
+			) ;
+
+			void compute(
+				VariantIdentifyingData const& snp,
+				Genotypes const& genotypes,
+				Ploidy const& ploidy,
+				std::vector< metro::SampleRange > const& included_samples 
+			) ;
+		
+			double info() const { return m_info ;}
+			double impute_info() const { return m_impute_info ;}
+
+		private:
+			double m_info ;
+			double m_impute_info ;
+			Eigen::VectorXd m_diploid_fallback_distribution ;
+			Eigen::VectorXd m_haploid_fallback_distribution ;
+			Eigen::VectorXd const m_diploid_levels ;
+			Eigen::VectorXd const m_haploid_levels ;
+			
+		private:
+			void compute_impl(
+				VariantIdentifyingData const& snp,
+				Genotypes const& genotypes,
+				Ploidy const& ploidy,
+				std::vector< metro::SampleRange > const& included_samples 
+			) ;
+		} ;
+	}
+
+	struct InfoComputation: public SNPSummaryComputation {
+		void operator()(
+			VariantIdentifyingData const& snp,
+			Genotypes const& genotypes,
+			Ploidy const& ploidy,
+			genfile::VariantDataReader&,
+			ResultCallback callback
+		) ;
+		
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+		
+	private:
+		impl::InfoComputation m_computation ;
+	} ;
+
+}
+
+
+#endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/IntensitySummaryComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/IntensitySummaryComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/IntensitySummaryComputation.hpp
@@ -17,11 +17,11 @@
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/VariantDataReader.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-namespace snp_summary_component {
+namespace stats {
 	struct IntensitySummaryComputation: public SNPSummaryComputation {
 		IntensitySummaryComputation( double call_threshhold = 0.9 ) ;
 		void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
 		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
 	private:

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComponent.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComponent.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComponent.hpp
@@ -47,17 +47,17 @@
 		qcdb::Storage::SharedPtr storage
 	) ;
 	qcdb::Storage::SharedPtr get_storage() const ;
 
 private:
-	SNPSummaryComputationManager::UniquePtr create_manager( qcdb::Storage::SharedPtr ) ;
-	void add_computations( SNPSummaryComputationManager& manager, qcdb::Storage::SharedPtr ) const ;
-	SNPSummaryComputation::UniquePtr create_computation( std::string const& name ) const ;
+	stats::SNPSummaryComputationManager::UniquePtr create_manager( qcdb::Storage::SharedPtr ) ;
+	void add_computations( stats::SNPSummaryComputationManager& manager, qcdb::Storage::SharedPtr ) const ;
+	stats::SNPSummaryComputation::UniquePtr create_computation( std::string const& name ) const ;
 
 private:
 	genfile::CohortIndividualSource const& m_samples ;
 	appcontext::OptionProcessor const& m_options ;
 	appcontext::UIContext& m_ui_context ;
 	qcdb::Storage::SharedPtr m_storage ;
 } ;
 
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComputation.hpp
@@ -15,32 +15,34 @@
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/VariantDataReader.hpp"
 #include "appcontext/OptionProcessor.hpp"
 
-struct SNPSummaryComputation: public boost::noncopyable {
-	typedef std::auto_ptr< SNPSummaryComputation > UniquePtr ;
-	virtual ~SNPSummaryComputation() {}
-	static UniquePtr create( std::string const& name ) ;
-
-	typedef genfile::VariantIdentifyingData VariantIdentifyingData ;
-	typedef Eigen::MatrixXd Genotypes ;
-	typedef boost::function< void ( std::string const& value_name ) > NameCallback ;
-	typedef boost::function< void ( std::string const& value_name, genfile::VariantEntry const& value ) > ResultCallback ;
-	typedef boost::function< void ( std::size_t sample_i, std::string const& value_name, genfile::VariantEntry const& value ) > PerSampleResultCallback ;
-	typedef Eigen::VectorXi Ploidy ;
-	
-	virtual std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const = 0 ;
-
-	virtual void list_variables( NameCallback ) const {}
-	virtual void begin_processing_snps( std::size_t ) {}
-	virtual void operator()(
-		VariantIdentifyingData const&,
-		Genotypes const&,
-		Ploidy const&,
-		genfile::VariantDataReader&,
-		ResultCallback
-	) = 0 ;
-	virtual void end_processing_snps( PerSampleResultCallback ) {}
-} ;
+namespace stats {
+	struct SNPSummaryComputation: public boost::noncopyable {
+		typedef std::auto_ptr< SNPSummaryComputation > UniquePtr ;
+		virtual ~SNPSummaryComputation() {}
+		static UniquePtr create( std::string const& name ) ;
+
+		typedef genfile::VariantIdentifyingData VariantIdentifyingData ;
+		typedef Eigen::MatrixXd Genotypes ;
+		typedef boost::function< void ( std::string const& value_name ) > NameCallback ;
+		typedef boost::function< void ( std::string const& value_name, genfile::VariantEntry const& value ) > ResultCallback ;
+		typedef boost::function< void ( std::size_t sample_i, std::string const& value_name, genfile::VariantEntry const& value ) > PerSampleResultCallback ;
+		typedef Eigen::VectorXi Ploidy ;
+	
+		virtual std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const = 0 ;
+
+		virtual void list_variables( NameCallback ) const {}
+		virtual void begin_processing_snps( std::size_t ) {}
+		virtual void operator()(
+			VariantIdentifyingData const&,
+			Genotypes const&,
+			Ploidy const&,
+			genfile::VariantDataReader&,
+			ResultCallback
+		) = 0 ;
+		virtual void end_processing_snps( PerSampleResultCallback ) {}
+	} ;
+}
 
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComputationManager.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComputationManager.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/SNPSummaryComputationManager.hpp
@@ -17,77 +17,79 @@
 #include "genfile/CohortIndividualSource.hpp"
 #include "appcontext/OptionProcessor.hpp"
 #include "appcontext/UIContext.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-struct SNPSummaryComputationManager: public genfile::SNPDataSourceProcessor::Callback, public boost::noncopyable {
-public:
-	typedef std::auto_ptr< SNPSummaryComputationManager > UniquePtr ;
-	typedef boost::signals2::signal<
-		void (
-			genfile::VariantIdentifyingData const& snp,
-			std::string const& value_name,
-			genfile::VariantEntry const& value
-		)
-	> ResultSignal ;
-	typedef ResultSignal::slot_type ResultCallback ;
-
-	typedef boost::signals2::signal<
-		void (
-			std::size_t sample_i,
-			std::string const& value_name,
-			genfile::VariantEntry const& value
-		)
-	> PerSampleResultSignal ;
-	typedef PerSampleResultSignal::slot_type PerSampleResultCallback ;
-
-	typedef std::map< genfile::VariantEntry, std::vector< int > > StrataMembers ;
-
-public:
-	SNPSummaryComputationManager( genfile::CohortIndividualSource const& samples, std::string const& sex_column_name ) ;
-	
-	void begin_processing_snps( std::size_t number_of_samples, genfile::SNPDataSource::Metadata const& ) ;
-	void processed_snp( genfile::VariantIdentifyingData const&, genfile::VariantDataReader& data_reader ) ;
-	void end_processing_snps() ;
-
-	std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) ;
-	
-	void add_computation( std::string const& name, SNPSummaryComputation::UniquePtr computation ) ;
-	void add_result_callback( ResultCallback ) ;
-	void add_per_sample_result_callback( PerSampleResultCallback ) ;
-
-	void stratify_by( StrataMembers const&, std::string const& ) ;
-	
-	void set_haploid_genotype_coding( int coding ) ;
-	
-private:
-	genfile::CohortIndividualSource const& m_samples ;
-	typedef boost::ptr_map< std::string, SNPSummaryComputation > Computations ;
-	Computations m_computations ;
-
-	ResultSignal m_result_signal ;
-	PerSampleResultSignal m_per_sample_result_signal ;
-	
-	int m_haploid_coding_column ;
-
-	std::size_t m_snp_index ;
-	SNPSummaryComputation::Genotypes m_genotypes ;
-	SNPSummaryComputation::Ploidy m_ploidy ;
-
-private:
-	std::vector< char > get_sexes( genfile::CohortIndividualSource const& samples, std::string const& sex_column_name ) const ;
-	std::map< char, std::vector< int > > get_samples_by_sex( std::vector< char > const& sex ) const ;
-
-	void fix_sex_chromosome_genotypes(
-		genfile::VariantIdentifyingData const& snp,
-		SNPSummaryComputation::Genotypes* genotypes,
-		boost::function< void ( std::string const& value_name, genfile::VariantEntry const& value ) > callback
-	) ;
-
-	int determine_male_coding_column(
-		genfile::VariantIdentifyingData const& snp,
-		SNPSummaryComputation::Genotypes const& genotypes,
-		std::vector< int > const& males
-	) const ;
-} ;
+namespace stats {
+	struct SNPSummaryComputationManager: public genfile::SNPDataSourceProcessor::Callback, public boost::noncopyable {
+	public:
+		typedef std::auto_ptr< SNPSummaryComputationManager > UniquePtr ;
+		typedef boost::signals2::signal<
+			void (
+				genfile::VariantIdentifyingData const& snp,
+				std::string const& value_name,
+				genfile::VariantEntry const& value
+			)
+		> ResultSignal ;
+		typedef ResultSignal::slot_type ResultCallback ;
+
+		typedef boost::signals2::signal<
+			void (
+				std::size_t sample_i,
+				std::string const& value_name,
+				genfile::VariantEntry const& value
+			)
+		> PerSampleResultSignal ;
+		typedef PerSampleResultSignal::slot_type PerSampleResultCallback ;
+
+		typedef std::map< genfile::VariantEntry, std::vector< int > > StrataMembers ;
+
+	public:
+		SNPSummaryComputationManager( genfile::CohortIndividualSource const& samples, std::string const& sex_column_name ) ;
+	
+		void begin_processing_snps( std::size_t number_of_samples, genfile::SNPDataSource::Metadata const& ) ;
+		void processed_snp( genfile::VariantIdentifyingData const&, genfile::VariantDataReader& data_reader ) ;
+		void end_processing_snps() ;
+
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) ;
+	
+		void add_computation( std::string const& name, stats::SNPSummaryComputation::UniquePtr computation ) ;
+		void add_result_callback( ResultCallback ) ;
+		void add_per_sample_result_callback( PerSampleResultCallback ) ;
+
+		void stratify_by( StrataMembers const&, std::string const& ) ;
+	
+		void set_haploid_genotype_coding( int coding ) ;
+	
+	private:
+		genfile::CohortIndividualSource const& m_samples ;
+		typedef boost::ptr_map< std::string, stats::SNPSummaryComputation > Computations ;
+		Computations m_computations ;
+
+		ResultSignal m_result_signal ;
+		PerSampleResultSignal m_per_sample_result_signal ;
+	
+		int m_haploid_coding_column ;
+
+		std::size_t m_snp_index ;
+		SNPSummaryComputation::Genotypes m_genotypes ;
+		SNPSummaryComputation::Ploidy m_ploidy ;
+
+	private:
+		std::vector< char > get_sexes( genfile::CohortIndividualSource const& samples, std::string const& sex_column_name ) const ;
+		std::map< char, std::vector< int > > get_samples_by_sex( std::vector< char > const& sex ) const ;
+
+		void fix_sex_chromosome_genotypes(
+			genfile::VariantIdentifyingData const& snp,
+			SNPSummaryComputation::Genotypes* genotypes,
+			boost::function< void ( std::string const& value_name, genfile::VariantEntry const& value ) > callback
+		) ;
+
+		int determine_male_coding_column(
+			genfile::VariantIdentifyingData const& snp,
+			SNPSummaryComputation::Genotypes const& genotypes,
+			std::vector< int > const& males
+		) const ;
+	} ;
+}
 
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/SequenceAnnotation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/SequenceAnnotation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/SequenceAnnotation.hpp
@@ -15,26 +15,27 @@
 #include "genfile/Chromosome.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/wildcard.hpp"
 #include "GenomeSequence.hpp"
 
-struct SequenceAnnotation: public SNPSummaryComputation
-{
-	typedef std::auto_ptr< SequenceAnnotation > UniquePtr ;
-	
-	typedef boost::function< void ( std::size_t, boost::optional< std::size_t > ) > ProgressCallback ;
-	SequenceAnnotation( std::string const& annotation_name, std::string const& fasta_filename, ProgressCallback ) ;
-	void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
-
-	std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
-	
-	void set_flanking( std::size_t left, std::size_t right ) ;
-private:
-	std::string const m_annotation_name ;
-	std::string const m_fasta_filename ;
-	std::vector< genfile::wildcard::FilenameMatch > const m_filenames ;
-	
-	GenomeSequence m_sequence ;
-	std::pair< genfile::Position, genfile::Position > m_flanking ;
-} ;
-
+namespace stats {
+	struct SequenceAnnotation: public SNPSummaryComputation
+	{
+		typedef std::auto_ptr< SequenceAnnotation > UniquePtr ;
+	
+		typedef boost::function< void ( std::size_t, boost::optional< std::size_t > ) > ProgressCallback ;
+		SequenceAnnotation( std::string const& annotation_name, std::string const& fasta_filename, ProgressCallback ) ;
+		void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
+
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+	
+		void set_flanking( std::size_t left, std::size_t right ) ;
+	private:
+		std::string const m_annotation_name ;
+		std::string const m_fasta_filename ;
+		std::vector< genfile::wildcard::FilenameMatch > const m_filenames ;
+	
+		GenomeSequence m_sequence ;
+		std::pair< genfile::Position, genfile::Position > m_flanking ;
+	} ;
+}
 #endif

Index: components/SNPSummaryComponent/include/components/SNPSummaryComponent/StratifyingSNPSummaryComputation.hpp
==================================================================
--- components/SNPSummaryComponent/include/components/SNPSummaryComponent/StratifyingSNPSummaryComputation.hpp
+++ components/SNPSummaryComponent/include/components/SNPSummaryComponent/StratifyingSNPSummaryComputation.hpp
@@ -13,17 +13,19 @@
 #include <Eigen/Core>
 #include "genfile/CohortIndividualSource.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 
-struct StratifyingSNPSummaryComputation: public SNPSummaryComputation {
-	typedef std::map< genfile::VariantEntry, std::vector< int > > StrataMembers ;
-	StratifyingSNPSummaryComputation( SNPSummaryComputation::UniquePtr computation, std::string const& stratification_name, StrataMembers const& strata_members ) ;
-	void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
-	std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
-private:
-	SNPSummaryComputation::UniquePtr m_computation ;
-	std::string const m_stratification_name ;
-	StrataMembers m_strata_members ;
-} ;
+namespace stats {
+	struct StratifyingSNPSummaryComputation: public SNPSummaryComputation {
+		typedef std::map< genfile::VariantEntry, std::vector< int > > StrataMembers ;
+		StratifyingSNPSummaryComputation( SNPSummaryComputation::UniquePtr computation, std::string const& stratification_name, StrataMembers const& strata_members ) ;
+		void operator()( VariantIdentifyingData const&, Genotypes const&, Ploidy const&, genfile::VariantDataReader&, ResultCallback ) ;
+		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
+	private:
+		SNPSummaryComputation::UniquePtr m_computation ;
+		std::string const m_stratification_name ;
+		StrataMembers m_strata_members ;
+	} ;
+}
 
 #endif

Index: components/SNPSummaryComponent/src/Bed3Annotation.cpp
==================================================================
--- components/SNPSummaryComponent/src/Bed3Annotation.cpp
+++ components/SNPSummaryComponent/src/Bed3Annotation.cpp
@@ -15,74 +15,76 @@
 #include "genfile/VariantEntry.hpp"
 #include "genfile/wildcard.hpp"
 #include "genfile/FileUtils.hpp"
 #include "components/SNPSummaryComponent/Bed3Annotation.hpp"
 
-Bed3Annotation::UniquePtr Bed3Annotation::create() {
-	return UniquePtr( new Bed3Annotation() ) ;
-}
-
-Bed3Annotation::Bed3Annotation() {
-	
-}
-
-void Bed3Annotation::add_annotation( std::string const& name, std::string const& filename, int left_margin_bp, int right_margin_bp ) {
-	std::auto_ptr< std::istream > in = genfile::open_text_file_for_input( filename ) ;
-	std::string line ;
-	std::getline( *in, line ) ;
-	if( (line.size() >=7 && line.substr( 0, 7 ) == "browser") || (line.size() >= 5 && line.substr(0,5) == "track" )) {
-		// skip this header line
-		std::getline( *in, line ) ;
-	}
-	using genfile::string_utils::slice ;
-	using genfile::string_utils::to_repr ;
-	std::vector< slice > elts ;
-
-	while(*in) {
-		elts.clear() ;
-		slice( line ).split( "\t", &elts ) ;
-		assert( elts.size() > 2 ) ;
-		genfile::Chromosome chromosome( elts[0] ) ;
-		uint32_t start( to_repr< uint32_t >( elts[1] ) ) ;
-		uint32_t end( to_repr< uint32_t >( elts[2] ) ) ;
-		
-		// Bed file is 0-based, right-open.
-		// We store annotations as 1-based, closed intervals.
-		// Therefore add 1 to start coord.
-		Annotation::interval_type interval(
-			genfile::GenomePosition( chromosome, start + 1 - left_margin_bp ),
-			genfile::GenomePosition( chromosome, end + 1 + right_margin_bp )
-		) ;
-		AnnotationMap::iterator where = m_annotations.find( name ) ;
-		if( where == m_annotations.end() ) {
-			m_annotation_names.push_back( name ) ;
-		}
-		m_annotations[ name ].insert( interval ) ;
-		std::getline( *in, line ) ;
-	}
-}
-
-void Bed3Annotation::operator()(
-	VariantIdentifyingData const& variant,
-	Genotypes const&,
-	Ploidy const&,
-	genfile::VariantDataReader&,
-	ResultCallback callback
-) {
-	for( std::size_t i = 0; i < m_annotation_names.size(); ++i ) {
-		AnnotationMap::const_iterator ai = m_annotations.find( m_annotation_names[i] ) ;
-		assert( ai != m_annotations.end() ) ;
-		int64_t const result = boost::icl::contains( ai->second, variant.get_position() ) ? 1 : 0 ;
-		callback( m_annotation_names[i], result ) ;
-	}
-}
-
-std::string Bed3Annotation::get_summary( std::string const& prefix, std::size_t column_width ) const {
-	std::ostringstream o ;
-	o << prefix << boost::format( "Bed3Annotation with %d annotations:\n" ) % m_annotation_names.size() ;
-	for( std::size_t i = 0; i < m_annotation_names.size(); ++i ) {
-		AnnotationMap::const_iterator ai = m_annotations.find( m_annotation_names[i] ) ;
-		assert( ai != m_annotations.end() ) ;
-		o << prefix << " - " << ( boost::format( "%s (%d disjoint intervals)\n" ) % m_annotation_names[i] % ai->second.iterative_size() ).str() ;
-	}
-	return o.str() ;
+namespace stats {
+	Bed3Annotation::UniquePtr Bed3Annotation::create() {
+		return UniquePtr( new Bed3Annotation() ) ;
+	}
+
+	Bed3Annotation::Bed3Annotation() {
+	
+	}
+
+	void Bed3Annotation::add_annotation( std::string const& name, std::string const& filename, int left_margin_bp, int right_margin_bp ) {
+		std::auto_ptr< std::istream > in = genfile::open_text_file_for_input( filename ) ;
+		std::string line ;
+		std::getline( *in, line ) ;
+		if( (line.size() >=7 && line.substr( 0, 7 ) == "browser") || (line.size() >= 5 && line.substr(0,5) == "track" )) {
+			// skip this header line
+			std::getline( *in, line ) ;
+		}
+		using genfile::string_utils::slice ;
+		using genfile::string_utils::to_repr ;
+		std::vector< slice > elts ;
+
+		while(*in) {
+			elts.clear() ;
+			slice( line ).split( "\t", &elts ) ;
+			assert( elts.size() > 2 ) ;
+			genfile::Chromosome chromosome( elts[0] ) ;
+			uint32_t start( to_repr< uint32_t >( elts[1] ) ) ;
+			uint32_t end( to_repr< uint32_t >( elts[2] ) ) ;
+		
+			// Bed file is 0-based, right-open.
+			// We store annotations as 1-based, closed intervals.
+			// Therefore add 1 to start coord.
+			Annotation::interval_type interval(
+				genfile::GenomePosition( chromosome, start + 1 - left_margin_bp ),
+				genfile::GenomePosition( chromosome, end + 1 + right_margin_bp )
+			) ;
+			AnnotationMap::iterator where = m_annotations.find( name ) ;
+			if( where == m_annotations.end() ) {
+				m_annotation_names.push_back( name ) ;
+			}
+			m_annotations[ name ].insert( interval ) ;
+			std::getline( *in, line ) ;
+		}
+	}
+
+	void Bed3Annotation::operator()(
+		VariantIdentifyingData const& variant,
+		Genotypes const&,
+		Ploidy const&,
+		genfile::VariantDataReader&,
+		ResultCallback callback
+	) {
+		for( std::size_t i = 0; i < m_annotation_names.size(); ++i ) {
+			AnnotationMap::const_iterator ai = m_annotations.find( m_annotation_names[i] ) ;
+			assert( ai != m_annotations.end() ) ;
+			int64_t const result = boost::icl::contains( ai->second, variant.get_position() ) ? 1 : 0 ;
+			callback( m_annotation_names[i], result ) ;
+		}
+	}
+
+	std::string Bed3Annotation::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		std::ostringstream o ;
+		o << prefix << boost::format( "Bed3Annotation with %d annotations:\n" ) % m_annotation_names.size() ;
+		for( std::size_t i = 0; i < m_annotation_names.size(); ++i ) {
+			AnnotationMap::const_iterator ai = m_annotations.find( m_annotation_names[i] ) ;
+			assert( ai != m_annotations.end() ) ;
+			o << prefix << " - " << ( boost::format( "%s (%d disjoint intervals)\n" ) % m_annotation_names[i] % ai->second.iterative_size() ).str() ;
+		}
+		return o.str() ;
+	}
 }

Index: components/SNPSummaryComponent/src/Bed4Annotation.cpp
==================================================================
--- components/SNPSummaryComponent/src/Bed4Annotation.cpp
+++ components/SNPSummaryComponent/src/Bed4Annotation.cpp
@@ -16,95 +16,97 @@
 #include "genfile/wildcard.hpp"
 #include "genfile/FileUtils.hpp"
 #include "genfile/Error.hpp"
 #include "components/SNPSummaryComponent/Bed4Annotation.hpp"
 
-Bed4Annotation::UniquePtr Bed4Annotation::create() {
-	return UniquePtr( new Bed4Annotation() ) ;
-}
-
-Bed4Annotation::Bed4Annotation() {
-	
-}
-
-void Bed4Annotation::add_annotation( std::string const& name, std::string const& filename, int left_margin_bp, int right_margin_bp ) {
-	std::auto_ptr< std::istream > in = genfile::open_text_file_for_input( filename ) ;
-	std::string line ;
-	std::getline( *in, line ) ;
-	if( (line.size() >=7 && line.substr( 0, 7 ) == "browser") || (line.size() >= 5 && line.substr(0,5) == "track" )) {
-		// skip this header line
-		std::getline( *in, line ) ;
-	}
-	using genfile::string_utils::slice ;
-	using genfile::string_utils::to_repr ;
-	std::vector< slice > elts ;
-	std::size_t lineCount = 1 ;
-	while(*in) {
-		elts.clear() ;
-		slice( line ).split( "\t", &elts ) ;
-		if( elts.size() < 4 ) {
-			throw genfile::MalformedInputError(
-				filename,
-				"Expected at least 4 columns in BED4 file",
-				lineCount
-			) ;
-		}
-		assert( elts.size() > 3 ) ;
-		genfile::Chromosome chromosome( elts[0] ) ;
-		uint32_t start( to_repr< uint32_t >( elts[1] ) ) ;
-		uint32_t end( to_repr< uint32_t >( elts[2] ) ) ;
-		std::set< std::string > values ;
-		values.insert( elts[3] ) ;
-
-		// Bed file is 0-based, right-open.
-		// We store annotations as 1-based, closed intervals.
-		// Therefore add 1 to start coord.
-		Annotation::interval_type interval(
-			genfile::GenomePosition( chromosome, start + 1 - left_margin_bp ),
-			genfile::GenomePosition( chromosome, end + 1 + right_margin_bp )
-		) ;
-		AnnotationMap::iterator where = m_annotations.find( name ) ;
-		if( where == m_annotations.end() ) {
-			m_annotation_names.push_back( name ) ;
-		}
-		m_annotations[ name ].add( std::make_pair( interval, values ) ) ;
-		std::getline( *in, line ) ;
-		++lineCount ;
-	}
-}
-
-void Bed4Annotation::operator()(
-	VariantIdentifyingData const& variant,
-	Genotypes const&,
-	Ploidy const&,
-	genfile::VariantDataReader&,
-	ResultCallback callback
-) {
-	for( std::size_t i = 0; i < m_annotation_names.size(); ++i ) {
-		AnnotationMap::const_iterator ai = m_annotations.find( m_annotation_names[i] ) ;
-		assert( ai != m_annotations.end() ) ;
-		Annotation const& a = ai->second ;
-		Annotation::const_iterator ri = a.find( variant.get_position() ) ;
-		if( ri == a.end() ) {
-			callback( m_annotation_names[i], genfile::MissingValue() ) ;
-		} else {
-			std::string value ;
-			Payload::const_iterator pi = ri->second.begin(), pi_end = ri->second.end() ;
-			
-			for( std::size_t c = 0; pi != pi_end; ++pi, ++c ) {
-				value += (c>0?",":"" ) + *pi ;
-			}
-			callback( m_annotation_names[i], value ) ;
-		}
-	}
-}
-
-std::string Bed4Annotation::get_summary( std::string const& prefix, std::size_t column_width ) const {
-	std::ostringstream o ;
-	o << prefix << boost::format( "Bed4Annotation with %d annotations:\n" ) % m_annotation_names.size() ;
-	for( std::size_t i = 0; i < m_annotation_names.size(); ++i ) {
-		AnnotationMap::const_iterator ai = m_annotations.find( m_annotation_names[i] ) ;
-		assert( ai != m_annotations.end() ) ;
-		o << prefix << " - " << ( boost::format( "%s (%d disjoint intervals)\n" ) % m_annotation_names[i] % ai->second.iterative_size() ).str() ;
-	}
-	return o.str() ;
+namespace stats {
+	Bed4Annotation::UniquePtr Bed4Annotation::create() {
+		return UniquePtr( new Bed4Annotation() ) ;
+	}
+
+	Bed4Annotation::Bed4Annotation() {
+	
+	}
+
+	void Bed4Annotation::add_annotation( std::string const& name, std::string const& filename, int left_margin_bp, int right_margin_bp ) {
+		std::auto_ptr< std::istream > in = genfile::open_text_file_for_input( filename ) ;
+		std::string line ;
+		std::getline( *in, line ) ;
+		if( (line.size() >=7 && line.substr( 0, 7 ) == "browser") || (line.size() >= 5 && line.substr(0,5) == "track" )) {
+			// skip this header line
+			std::getline( *in, line ) ;
+		}
+		using genfile::string_utils::slice ;
+		using genfile::string_utils::to_repr ;
+		std::vector< slice > elts ;
+		std::size_t lineCount = 1 ;
+		while(*in) {
+			elts.clear() ;
+			slice( line ).split( "\t", &elts ) ;
+			if( elts.size() < 4 ) {
+				throw genfile::MalformedInputError(
+					filename,
+					"Expected at least 4 columns in BED4 file",
+					lineCount
+				) ;
+			}
+			assert( elts.size() > 3 ) ;
+			genfile::Chromosome chromosome( elts[0] ) ;
+			uint32_t start( to_repr< uint32_t >( elts[1] ) ) ;
+			uint32_t end( to_repr< uint32_t >( elts[2] ) ) ;
+			std::set< std::string > values ;
+			values.insert( elts[3] ) ;
+
+			// Bed file is 0-based, right-open.
+			// We store annotations as 1-based, closed intervals.
+			// Therefore add 1 to start coord.
+			Annotation::interval_type interval(
+				genfile::GenomePosition( chromosome, start + 1 - left_margin_bp ),
+				genfile::GenomePosition( chromosome, end + 1 + right_margin_bp )
+			) ;
+			AnnotationMap::iterator where = m_annotations.find( name ) ;
+			if( where == m_annotations.end() ) {
+				m_annotation_names.push_back( name ) ;
+			}
+			m_annotations[ name ].add( std::make_pair( interval, values ) ) ;
+			std::getline( *in, line ) ;
+			++lineCount ;
+		}
+	}
+
+	void Bed4Annotation::operator()(
+		VariantIdentifyingData const& variant,
+		Genotypes const&,
+		Ploidy const&,
+		genfile::VariantDataReader&,
+		ResultCallback callback
+	) {
+		for( std::size_t i = 0; i < m_annotation_names.size(); ++i ) {
+			AnnotationMap::const_iterator ai = m_annotations.find( m_annotation_names[i] ) ;
+			assert( ai != m_annotations.end() ) ;
+			Annotation const& a = ai->second ;
+			Annotation::const_iterator ri = a.find( variant.get_position() ) ;
+			if( ri == a.end() ) {
+				callback( m_annotation_names[i], genfile::MissingValue() ) ;
+			} else {
+				std::string value ;
+				Payload::const_iterator pi = ri->second.begin(), pi_end = ri->second.end() ;
+			
+				for( std::size_t c = 0; pi != pi_end; ++pi, ++c ) {
+					value += (c>0?",":"" ) + *pi ;
+				}
+				callback( m_annotation_names[i], value ) ;
+			}
+		}
+	}
+
+	std::string Bed4Annotation::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		std::ostringstream o ;
+		o << prefix << boost::format( "Bed4Annotation with %d annotations:\n" ) % m_annotation_names.size() ;
+		for( std::size_t i = 0; i < m_annotation_names.size(); ++i ) {
+			AnnotationMap::const_iterator ai = m_annotations.find( m_annotation_names[i] ) ;
+			assert( ai != m_annotations.end() ) ;
+			o << prefix << " - " << ( boost::format( "%s (%d disjoint intervals)\n" ) % m_annotation_names[i] % ai->second.iterative_size() ).str() ;
+		}
+		return o.str() ;
+	}
 }

Index: components/SNPSummaryComponent/src/CallComparerComponent.cpp
==================================================================
--- components/SNPSummaryComponent/src/CallComparerComponent.cpp
+++ components/SNPSummaryComponent/src/CallComparerComponent.cpp
@@ -18,236 +18,238 @@
 #include "genfile/get_set_eigen.hpp"
 #include "genfile/vcf/get_set_eigen.hpp"
 
 #include "statfile/BuiltInTypeStatSink.hpp"
 
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "qcdb/FlatFileOutputter.hpp"
 
 #include "components/SNPSummaryComponent/PairwiseCallComparer.hpp"
 #include "components/SNPSummaryComponent/PairwiseCallComparerManager.hpp"
 #include "components/SNPSummaryComponent/CallComparerComponent.hpp"
 #include "components/SNPSummaryComponent/FrequentistTestCallMerger.hpp"
 #include "components/SNPSummaryComponent/LeastMissingConsensusCaller.hpp"
 
 
-CallComparerProcessor::UniquePtr CallComparerProcessor::create( PairwiseCallComparerManager::UniquePtr comparer, std::vector< std::string > const& call_fields ) {
-	UniquePtr result(
-		new CallComparerProcessor( comparer, call_fields )
-	) ;
-	return result ;
-}
-
-CallComparerProcessor::CallComparerProcessor( PairwiseCallComparerManager::UniquePtr call_comparer, std::vector< std::string > const& call_fields  ):
-	m_call_comparer( call_comparer ),
-	m_call_fields( call_fields ),
-	m_begun( false )
-{}
-
-void CallComparerProcessor::operator()(
-	VariantIdentifyingData const& snp,
-	Genotypes const& genotypes,
-	Ploidy const&,
-	genfile::VariantDataReader& data_reader,
-	ResultCallback callback
-) {
-	if( !m_begun ) {
-		m_call_comparer->begin_processing_snps( genotypes.rows() ) ;
-		m_begun = true ;
-	}
-	
-	// Add all the calls to the call comparer.
-	m_call_comparer->begin_processing_snp( snp ) ;
-	for( std::size_t i = 0; i < m_call_fields.size(); ++i ) {
-		genfile::vcf::GenotypeSetter< Eigen::MatrixBase< Eigen::MatrixXd > > setter( m_calls ) ;
-		data_reader.get( m_call_fields[i], setter ) ;
-		m_call_comparer->add_calls( m_call_fields[i], m_calls ) ;
-	}
-	m_call_comparer->end_processing_snp() ;
-}
-
-std::string CallComparerProcessor::get_summary( std::string const& prefix, std::size_t column_width ) const {
-	return prefix + "CallComparerProcessor" ;
-}
-
-void CallComparerComponent::declare_options( appcontext::OptionProcessor& options ) {
-	options.declare_group( "Call comparison options" ) ;
-	options[ "-compare-calls" ]
-		.set_description( "Compare genotype calls from the given fields of a VCF or other file. "
-		 	"The value should be a comma-separated list of genotype call fields in the data.")
-		.set_takes_values_until_next_option() ;
-	options[ "-tabulate-call-comparison" ]
-		.set_description( "Specify that a table of counts should be output for each pair of callsets at each SNP" ) ;
-	options[ "-consensus-call" ]
-		.set_description( "Combine calls from several different genotypers into a single consensus callset. "
-			"The calls to use are specified using the -compare-calls option. "
-			"A consensus call at each SNP is made when no significant difference is found "
-			"between N-1 of the N callsets." )
-		.set_takes_single_value()
-		.set_default_value( "call-comparisons.vcf" ) ;
-
-	options[ "-comparison-model" ]
-		.set_description( "Set the model used for call comparison.  Currently this must be \"GenotypeFrequencyTest\". or \"AcceptAll\"." )
-		.set_takes_single_value()
-		.set_default_value( "GenotypeFrequencyTest" ) ;
-
-	options[ "-consensus-model" ]
-		.set_description( "Model used to combine calls in the consensus set of calls. "
-		 	"Currently this can be \"LeastMissing\" or \"QuangStyle\"." )
-		.set_takes_single_value()
-		.set_default_value( "LeastMissing" ) ;
-	options[ "-consensus-call-pvalue-threshold" ]
-		.set_description( "Treat calls in call comparison treated as distinct if the p-value of an association test between them "
-			"is less than or equal to this value." )
-		.set_takes_single_value()
-		.set_default_value( 0.001 ) ;
-
-	options.option_implies_option( "-consensus-call", "-s" ) ;
-	options.option_implies_option( "-compare-calls", "-s" ) ;
-	options.option_implies_option( "-tabulate-call-comparison", "-compare-calls" ) ;
-	options.option_implies_option( "-consensus-call", "-compare-calls" ) ;
-	options.option_implies_option( "-consensus-call-pvalue-threshold", "-compare-calls" ) ;
-}
-
-CallComparerComponent::UniquePtr CallComparerComponent::create(
-	genfile::CohortIndividualSource const& samples,
-	appcontext::OptionProcessor const& options,
-	appcontext::UIContext& ui_context
-) {
-	CallComparerComponent::UniquePtr result(
-		new CallComparerComponent( samples, options, ui_context )
-	) ;
-	return result ;
-}
-
-CallComparerComponent::CallComparerComponent(
-	genfile::CohortIndividualSource const& samples,
-	appcontext::OptionProcessor const& options,
-	appcontext::UIContext&
-):
-	m_samples( samples ),
-	m_options( options )
-{}
-
-namespace {
-	genfile::VariantEntry get_sample_entry( genfile::CohortIndividualSource const& samples, std::string const& name, std::size_t i ) {
-		return samples.get_entry( i, name ) ;
-	}
-	
-	void send_results_to_sink(
-		genfile::SNPDataSink::SharedPtr sink,
-		genfile::VariantIdentifyingData const& snp,
-		Eigen::MatrixXd const& genotypes,
-		std::map< std::string, std::vector< genfile::VariantEntry > > const& info
-	) {
-		sink->write_snp(
-			genotypes.rows(),
-			snp,
-			genfile::GenotypeGetter< Eigen::MatrixXd >( genotypes, 0ul ),
-			genfile::GenotypeGetter< Eigen::MatrixXd >( genotypes, 1ul ),
-			genfile::GenotypeGetter< Eigen::MatrixXd >( genotypes, 2ul ),
-			info
-		) ;
-	}
-}
-
-namespace {
-	// Adapter to adapt SNPSummaryComponent outputters to be used here.
-	struct SNPSummaryOutputter: public PairwiseCallComparerManager::ComparisonClient {
-	public:
-		static UniquePtr create( qcdb::Storage::SharedPtr outputter ) {
-			return UniquePtr( new SNPSummaryOutputter( outputter ) ) ;
-		}
-
-		static SharedPtr create_shared( qcdb::Storage::SharedPtr outputter ) {
-			return SharedPtr( new SNPSummaryOutputter( outputter ) ) ;
-		}
-
-	public:
-		SNPSummaryOutputter( qcdb::Storage::SharedPtr outputter ):
-			m_outputter( outputter )
-		{}
-
-		void begin_comparisons( genfile::VariantIdentifyingData const& snp ) {
-			m_snp = snp ;
-		} ;
-
-		void end_comparisons() {} 
-		
-		void set_result(
-			std::string const& first_callset,
-			std::string const& second_callset,
-			std::string const& comparison,
-			std::string const& variable,
-			genfile::VariantEntry const& value
-		) {
-			m_outputter->store_per_variant_data(
-				m_snp,
-				comparison + ":" + first_callset + "/" + second_callset + ":" + variable,
-				value
-			) ;
-		}
-
-	private:
-		qcdb::Storage::SharedPtr m_outputter ;
-		genfile::VariantIdentifyingData m_snp ;
-	} ;	
-}
-
-void CallComparerComponent::setup( SNPSummaryComputationManager& snp_summary_component_manager, qcdb::Storage::SharedPtr storage ) const {
-	PairwiseCallComparerManager::UniquePtr manager( PairwiseCallComparerManager::create().release() ) ;
-
-	SNPSummaryOutputter::SharedPtr snp_outputter = SNPSummaryOutputter::create_shared(
-		storage 
-	) ;
-	
-	manager->send_comparisons_to( snp_outputter ) ;
-	
-	std::string const comparison_model = m_options.get< std::string >( "-comparison-model" ) ;
-	if( comparison_model != "AcceptAll" ) {
-		manager->add_comparer( comparison_model, PairwiseCallComparer::create( comparison_model ) ) ;
-	}
-	if( m_options.check( "-tabulate-call-comparison" )) {
-		manager->add_comparer( "GenotypeTabulatingCallComparer", PairwiseCallComparer::create( "GenotypeTabulatingCallComparer" ) ) ;
-	}
-
-	manager->set_merger( PairwiseCallComparerManager::Merger::create( comparison_model, m_options ) ) ;
-
-	if( m_options.check( "-consensus-call" )) {
-		ConsensusCaller::SharedPtr consensus_caller ;
-		{
-			genfile::SNPDataSink::SharedPtr sink(
-				genfile::SNPDataSink::create(
-					m_options.get< std::string >( "-consensus-call" )
-				).release()
-			) ;
-			sink->set_sample_names(
-				m_samples.get_number_of_individuals(),
-				boost::bind( get_sample_entry, boost::ref( m_samples ), "ID_1", _1 )
-			) ;
-			consensus_caller = ConsensusCaller::create_shared( m_options.get< std::string >( "-consensus-model" ) ) ;
-			consensus_caller->send_results_to(
-				boost::bind(
-					&send_results_to_sink,
-					sink,
-					_1,
-					_2,
-					_3
-				)
-			) ;
-		}
-		manager->send_merge_to( consensus_caller ) ;
-	}
-	
-
-	CallComparerProcessor::UniquePtr ccc = CallComparerProcessor::create(
-		manager,
-		m_options.get_values< std::string >( "-compare-calls" )
-	) ;
-	
-	snp_summary_component_manager.add_computation(
-		"call_comparison",
-		SNPSummaryComputation::UniquePtr( ccc.release() )
-	) ;
+namespace stats {
+	CallComparerProcessor::UniquePtr CallComparerProcessor::create( PairwiseCallComparerManager::UniquePtr comparer, std::vector< std::string > const& call_fields ) {
+		UniquePtr result(
+			new CallComparerProcessor( comparer, call_fields )
+		) ;
+		return result ;
+	}
+
+	CallComparerProcessor::CallComparerProcessor( PairwiseCallComparerManager::UniquePtr call_comparer, std::vector< std::string > const& call_fields  ):
+		m_call_comparer( call_comparer ),
+		m_call_fields( call_fields ),
+		m_begun( false )
+	{}
+
+	void CallComparerProcessor::operator()(
+		VariantIdentifyingData const& snp,
+		Genotypes const& genotypes,
+		Ploidy const&,
+		genfile::VariantDataReader& data_reader,
+		ResultCallback callback
+	) {
+		if( !m_begun ) {
+			m_call_comparer->begin_processing_snps( genotypes.rows() ) ;
+			m_begun = true ;
+		}
+	
+		// Add all the calls to the call comparer.
+		m_call_comparer->begin_processing_snp( snp ) ;
+		for( std::size_t i = 0; i < m_call_fields.size(); ++i ) {
+			genfile::vcf::GenotypeSetter< Eigen::MatrixBase< Eigen::MatrixXd > > setter( m_calls ) ;
+			data_reader.get( m_call_fields[i], setter ) ;
+			m_call_comparer->add_calls( m_call_fields[i], m_calls ) ;
+		}
+		m_call_comparer->end_processing_snp() ;
+	}
+
+	std::string CallComparerProcessor::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		return prefix + "CallComparerProcessor" ;
+	}
+
+	void CallComparerComponent::declare_options( appcontext::OptionProcessor& options ) {
+		options.declare_group( "Call comparison options" ) ;
+		options[ "-compare-calls" ]
+			.set_description( "Compare genotype calls from the given fields of a VCF or other file. "
+			 	"The value should be a comma-separated list of genotype call fields in the data.")
+			.set_takes_values_until_next_option() ;
+		options[ "-tabulate-call-comparison" ]
+			.set_description( "Specify that a table of counts should be output for each pair of callsets at each SNP" ) ;
+		options[ "-consensus-call" ]
+			.set_description( "Combine calls from several different genotypers into a single consensus callset. "
+				"The calls to use are specified using the -compare-calls option. "
+				"A consensus call at each SNP is made when no significant difference is found "
+				"between N-1 of the N callsets." )
+			.set_takes_single_value()
+			.set_default_value( "call-comparisons.vcf" ) ;
+
+		options[ "-comparison-model" ]
+			.set_description( "Set the model used for call comparison.  Currently this must be \"GenotypeFrequencyTest\". or \"AcceptAll\"." )
+			.set_takes_single_value()
+			.set_default_value( "GenotypeFrequencyTest" ) ;
+
+		options[ "-consensus-model" ]
+			.set_description( "Model used to combine calls in the consensus set of calls. "
+			 	"Currently this can be \"LeastMissing\" or \"QuangStyle\"." )
+			.set_takes_single_value()
+			.set_default_value( "LeastMissing" ) ;
+		options[ "-consensus-call-pvalue-threshold" ]
+			.set_description( "Treat calls in call comparison treated as distinct if the p-value of an association test between them "
+				"is less than or equal to this value." )
+			.set_takes_single_value()
+			.set_default_value( 0.001 ) ;
+
+		options.option_implies_option( "-consensus-call", "-s" ) ;
+		options.option_implies_option( "-compare-calls", "-s" ) ;
+		options.option_implies_option( "-tabulate-call-comparison", "-compare-calls" ) ;
+		options.option_implies_option( "-consensus-call", "-compare-calls" ) ;
+		options.option_implies_option( "-consensus-call-pvalue-threshold", "-compare-calls" ) ;
+	}
+
+	CallComparerComponent::UniquePtr CallComparerComponent::create(
+		genfile::CohortIndividualSource const& samples,
+		appcontext::OptionProcessor const& options,
+		appcontext::UIContext& ui_context
+	) {
+		CallComparerComponent::UniquePtr result(
+			new CallComparerComponent( samples, options, ui_context )
+		) ;
+		return result ;
+	}
+
+	CallComparerComponent::CallComparerComponent(
+		genfile::CohortIndividualSource const& samples,
+		appcontext::OptionProcessor const& options,
+		appcontext::UIContext&
+	):
+		m_samples( samples ),
+		m_options( options )
+	{}
+
+	namespace {
+		genfile::VariantEntry get_sample_entry( genfile::CohortIndividualSource const& samples, std::string const& name, std::size_t i ) {
+			return samples.get_entry( i, name ) ;
+		}
+	
+		void send_results_to_sink(
+			genfile::SNPDataSink::SharedPtr sink,
+			genfile::VariantIdentifyingData const& snp,
+			Eigen::MatrixXd const& genotypes,
+			std::map< std::string, std::vector< genfile::VariantEntry > > const& info
+		) {
+			sink->write_snp(
+				genotypes.rows(),
+				snp,
+				genfile::GenotypeGetter< Eigen::MatrixXd >( genotypes, 0ul ),
+				genfile::GenotypeGetter< Eigen::MatrixXd >( genotypes, 1ul ),
+				genfile::GenotypeGetter< Eigen::MatrixXd >( genotypes, 2ul ),
+				info
+			) ;
+		}
+	}
+
+	namespace {
+		// Adapter to adapt SNPSummaryComponent outputters to be used here.
+		struct SNPSummaryOutputter: public PairwiseCallComparerManager::ComparisonClient {
+		public:
+			static UniquePtr create( qcdb::Storage::SharedPtr outputter ) {
+				return UniquePtr( new SNPSummaryOutputter( outputter ) ) ;
+			}
+
+			static SharedPtr create_shared( qcdb::Storage::SharedPtr outputter ) {
+				return SharedPtr( new SNPSummaryOutputter( outputter ) ) ;
+			}
+
+		public:
+			SNPSummaryOutputter( qcdb::Storage::SharedPtr outputter ):
+				m_outputter( outputter )
+			{}
+
+			void begin_comparisons( genfile::VariantIdentifyingData const& snp ) {
+				m_snp = snp ;
+			} ;
+
+			void end_comparisons() {} 
+		
+			void set_result(
+				std::string const& first_callset,
+				std::string const& second_callset,
+				std::string const& comparison,
+				std::string const& variable,
+				genfile::VariantEntry const& value
+			) {
+				m_outputter->store_per_variant_data(
+					m_snp,
+					comparison + ":" + first_callset + "/" + second_callset + ":" + variable,
+					value
+				) ;
+			}
+
+		private:
+			qcdb::Storage::SharedPtr m_outputter ;
+			genfile::VariantIdentifyingData m_snp ;
+		} ;	
+	}
+
+	void CallComparerComponent::setup( SNPSummaryComputationManager& snp_summary_component_manager, qcdb::Storage::SharedPtr storage ) const {
+		PairwiseCallComparerManager::UniquePtr manager( PairwiseCallComparerManager::create().release() ) ;
+
+		SNPSummaryOutputter::SharedPtr snp_outputter = SNPSummaryOutputter::create_shared(
+			storage 
+		) ;
+	
+		manager->send_comparisons_to( snp_outputter ) ;
+	
+		std::string const comparison_model = m_options.get< std::string >( "-comparison-model" ) ;
+		if( comparison_model != "AcceptAll" ) {
+			manager->add_comparer( comparison_model, PairwiseCallComparer::create( comparison_model ) ) ;
+		}
+		if( m_options.check( "-tabulate-call-comparison" )) {
+			manager->add_comparer( "GenotypeTabulatingCallComparer", PairwiseCallComparer::create( "GenotypeTabulatingCallComparer" ) ) ;
+		}
+
+		manager->set_merger( PairwiseCallComparerManager::Merger::create( comparison_model, m_options ) ) ;
+
+		if( m_options.check( "-consensus-call" )) {
+			ConsensusCaller::SharedPtr consensus_caller ;
+			{
+				genfile::SNPDataSink::SharedPtr sink(
+					genfile::SNPDataSink::create(
+						m_options.get< std::string >( "-consensus-call" )
+					).release()
+				) ;
+				sink->set_sample_names(
+					m_samples.get_number_of_individuals(),
+					boost::bind( get_sample_entry, boost::ref( m_samples ), "ID_1", _1 )
+				) ;
+				consensus_caller = ConsensusCaller::create_shared( m_options.get< std::string >( "-consensus-model" ) ) ;
+				consensus_caller->send_results_to(
+					boost::bind(
+						&send_results_to_sink,
+						sink,
+						_1,
+						_2,
+						_3
+					)
+				) ;
+			}
+			manager->send_merge_to( consensus_caller ) ;
+		}
+	
+
+		CallComparerProcessor::UniquePtr ccc = CallComparerProcessor::create(
+			manager,
+			m_options.get_values< std::string >( "-compare-calls" )
+		) ;
+	
+		snp_summary_component_manager.add_computation(
+			"call_comparison",
+			SNPSummaryComputation::UniquePtr( ccc.release() )
+		) ;
+	}
 }
 

Index: components/SNPSummaryComponent/src/ClusterFitComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/ClusterFitComputation.cpp
+++ components/SNPSummaryComponent/src/ClusterFitComputation.cpp
@@ -20,11 +20,11 @@
 #include "metro/ValueStabilisesStoppingCondition.hpp"
 #include "metro/log_sum_exp.hpp"
 
 // #define DEBUG_CLUSTERFITCOMPUTATION 1
 
-namespace snp_summary_component {
+namespace stats {
 	ClusterFitComputation::ClusterFitComputation(
 		double nu,
 		double regularisationVariance,
 		double regularisationWeight,
 		double call_threshhold

Index: components/SNPSummaryComponent/src/CrossDataSetConcordanceComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/CrossDataSetConcordanceComputation.cpp
+++ components/SNPSummaryComponent/src/CrossDataSetConcordanceComputation.cpp
@@ -13,11 +13,11 @@
 #include "genfile/SNPDataSource.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 #include "components/SNPSummaryComponent/CrossDataSetConcordanceComputation.hpp"
 #include "metro/correlation.hpp"
 
-namespace snp_stats {
+namespace stats {
 	namespace impl {
 		CrossDataSetSampleMapper::SampleMapping create_sample_mapping(
 			CrossDataSetSampleMapper::SampleIdList const& set1,
 			CrossDataSetSampleMapper::SampleIdList const& set2
 		) {

Index: components/SNPSummaryComponent/src/CrossDataSetHaplotypeComparisonComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/CrossDataSetHaplotypeComparisonComputation.cpp
+++ components/SNPSummaryComponent/src/CrossDataSetHaplotypeComparisonComputation.cpp
@@ -12,11 +12,11 @@
 #include "genfile/CohortIndividualSource.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 #include "components/SNPSummaryComponent/CrossDataSetHaplotypeComparisonComputation.hpp"
 
-namespace snp_stats {
+namespace stats {
 	CrossDataSetHaplotypeComparisonComputation::CrossDataSetHaplotypeComparisonComputation(
 		genfile::CohortIndividualSource const& samples,
 		std::string const& main_dataset_sample_id_column
 	):
 		m_sample_mapper( samples, main_dataset_sample_id_column ),

Index: components/SNPSummaryComponent/src/DifferentialMissingnessComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/DifferentialMissingnessComputation.cpp
+++ components/SNPSummaryComponent/src/DifferentialMissingnessComputation.cpp
@@ -6,117 +6,119 @@
 #include "components/SNPSummaryComponent/DifferentialMissingnessComputation.hpp"
 #include "metro/FishersExactTest.hpp"
 #include "metro/likelihood/Multinomial.hpp"
 #include "metro/likelihood/ProductOfMultinomials.hpp"
 
-DifferentialMissingnessComputation::UniquePtr DifferentialMissingnessComputation::create( std::string const& stratification_name, StrataMembers const& strata_members ) {
-	return DifferentialMissingnessComputation::UniquePtr(
-		new DifferentialMissingnessComputation( stratification_name, strata_members )
-	) ;
-}
-
-DifferentialMissingnessComputation::DifferentialMissingnessComputation( std::string const& stratification_name, StrataMembers const& strata_members, double threshhold ):
-	m_stratification_name( stratification_name ),
-	m_strata_members( strata_members ),
-	m_strata_levels( compute_strata_levels( m_strata_members ) ),
-	m_threshhold( threshhold )
-{
-#if 0
-	if( strata_members.size() != 2 ) {
-		throw genfile::BadArgumentError( "DifferentialMissingnessComputation::DifferentialMissingnessComputation()", "strata_members( size " + genfile::string_utils::to_string( strata_members.size() ) + ")" ) ;
-	}
-#endif
-}
-
-std::vector< int > DifferentialMissingnessComputation::compute_strata_levels( StrataMembers const& strata_members ) const {
-	std::vector< int > result ;
-	int level = 0 ;
-	for( StrataMembers::const_iterator i = strata_members.begin(); i != strata_members.end(); ++i, ++level ) {
-		for( std::size_t j = 0; j < i->second.size(); ++j ) {
-			std::size_t const index = i->second[j] ;
-			result.resize( std::max( result.size(), index+1 ), -1 ) ;
-			result[ index ] = level ;
-		}
-	}
-	return result ;
-}
-
-void DifferentialMissingnessComputation::operator()( VariantIdentifyingData const& snp, Genotypes const& genotypes, Ploidy const&, genfile::VariantDataReader&, ResultCallback callback ) {
-	// construct a table
-	// 
-	//                 missing     not missing
-	//   stratum 1       a              b
-	//   stratum 2       c              d
-	// 
-	// on which we can do a Fisher's exact test or a product of binomial-type test.
-	//
-	int const number_of_strata = 1 + *std::max_element( m_strata_levels.begin(), m_strata_levels.end() ) ;
-	Eigen::MatrixXd table( number_of_strata, 2 ) ;
-	table.setZero() ;
-	for( int i = 0; i < genotypes.rows(); ++i ) {
-		if( m_strata_levels[i] >= 0 ) {
-			if( genotypes.row( i ).sum() < m_threshhold ) {
-				table( m_strata_levels[i], 0 )++ ;
-			}
-			else {
-				table( m_strata_levels[i], 1 )++ ;
-			}
-		}
-	}
-	
-	{
-		StrataMembers::const_iterator i = m_strata_members.begin() ;
-		StrataMembers::const_iterator const end_i = m_strata_members.end() ;
-		for( int level = 0; i != end_i; ++level, ++i ) {
-			std::string tag = "[" + m_stratification_name + "=" + genfile::string_utils::to_string( i->first ) + "]" ;
-			callback( "missing" + tag, table( level, 0 ) ) ;
-			callback( "non_missing" + tag, table( level, 1 ) ) ;
-		}
-	}
-
-	std::string const stub = "missingness_by_" + m_stratification_name ;
-//	callback( stub + "_sample_odds_ratio", table(0,0) * table(1,1) / ( table(0,1) * table(1,0) ) ) ;
-	
-	if( table.row(0).sum() > 0 && table.row(1).sum() > 0 ) {
-		// perform the exact test.  For speed reasons this is only done if the chi-square approximation may be inaccurate.
-		if( table.rows() == 2 ) {
-			try {
-				metro::FishersExactTest test( table ) ;
-				callback( stub + "_exact_pvalue", test.get_pvalue( metro::FishersExactTest::eTwoSided ) )  ;
-			}
-			catch( std::exception const& e ) {
-				callback( stub + "_exact_pvalue", genfile::MissingValue() ) ;
-			}
-		} else {
-			callback( stub + "_exact_pvalue", genfile::MissingValue() ) ;
-		}
-		{
-			metro::likelihood::Multinomial< double, Eigen::VectorXd, Eigen::MatrixXd > null_model( table.colwise().sum() ) ;
-			null_model.evaluate_at( null_model.get_MLE() ) ;
-			metro::likelihood::ProductOfMultinomials< double, Eigen::VectorXd, Eigen::MatrixXd > alternative_model( table ) ;
-			alternative_model.evaluate_at( alternative_model.get_MLE() ) ;
-			double likelihood_ratio_statistic = -2.0 * ( null_model.get_value_of_function() - alternative_model.get_value_of_function() ) ;
-
-			if( likelihood_ratio_statistic != likelihood_ratio_statistic || likelihood_ratio_statistic < 0.0 ) {
-				likelihood_ratio_statistic = std::numeric_limits< double >::quiet_NaN() ;
-			}
-			else {
-				boost::math::chi_squared_distribution< double > chi_squared( table.rows() - 1 ) ;
-
-				double p_value = boost::math::cdf(
-					boost::math::complement(
-						chi_squared,
-						likelihood_ratio_statistic
-					)
-				) ;
-				
-				
-				callback( stub + "_lrt_pvalue", p_value ) ;
-				callback( stub + "_lrt_df", genfile::VariantEntry::Integer( table.rows() - 1 )) ;
-			}
-		}
-	}
-}
-
-std::string DifferentialMissingnessComputation::get_summary( std::string const& prefix, std::size_t column_width ) const {
-	return prefix + "DifferentialMissingnessComputation" ;
+namespace stats {
+	DifferentialMissingnessComputation::UniquePtr DifferentialMissingnessComputation::create( std::string const& stratification_name, StrataMembers const& strata_members ) {
+		return DifferentialMissingnessComputation::UniquePtr(
+			new DifferentialMissingnessComputation( stratification_name, strata_members )
+		) ;
+	}
+
+	DifferentialMissingnessComputation::DifferentialMissingnessComputation( std::string const& stratification_name, StrataMembers const& strata_members, double threshhold ):
+		m_stratification_name( stratification_name ),
+		m_strata_members( strata_members ),
+		m_strata_levels( compute_strata_levels( m_strata_members ) ),
+		m_threshhold( threshhold )
+	{
+	#if 0
+		if( strata_members.size() != 2 ) {
+			throw genfile::BadArgumentError( "DifferentialMissingnessComputation::DifferentialMissingnessComputation()", "strata_members( size " + genfile::string_utils::to_string( strata_members.size() ) + ")" ) ;
+		}
+	#endif
+	}
+
+	std::vector< int > DifferentialMissingnessComputation::compute_strata_levels( StrataMembers const& strata_members ) const {
+		std::vector< int > result ;
+		int level = 0 ;
+		for( StrataMembers::const_iterator i = strata_members.begin(); i != strata_members.end(); ++i, ++level ) {
+			for( std::size_t j = 0; j < i->second.size(); ++j ) {
+				std::size_t const index = i->second[j] ;
+				result.resize( std::max( result.size(), index+1 ), -1 ) ;
+				result[ index ] = level ;
+			}
+		}
+		return result ;
+	}
+
+	void DifferentialMissingnessComputation::operator()( VariantIdentifyingData const& snp, Genotypes const& genotypes, Ploidy const&, genfile::VariantDataReader&, ResultCallback callback ) {
+		// construct a table
+		// 
+		//                 missing     not missing
+		//   stratum 1       a              b
+		//   stratum 2       c              d
+		// 
+		// on which we can do a Fisher's exact test or a product of binomial-type test.
+		//
+		int const number_of_strata = 1 + *std::max_element( m_strata_levels.begin(), m_strata_levels.end() ) ;
+		Eigen::MatrixXd table( number_of_strata, 2 ) ;
+		table.setZero() ;
+		for( int i = 0; i < genotypes.rows(); ++i ) {
+			if( m_strata_levels[i] >= 0 ) {
+				if( genotypes.row( i ).sum() < m_threshhold ) {
+					table( m_strata_levels[i], 0 )++ ;
+				}
+				else {
+					table( m_strata_levels[i], 1 )++ ;
+				}
+			}
+		}
+	
+		{
+			StrataMembers::const_iterator i = m_strata_members.begin() ;
+			StrataMembers::const_iterator const end_i = m_strata_members.end() ;
+			for( int level = 0; i != end_i; ++level, ++i ) {
+				std::string tag = "[" + m_stratification_name + "=" + genfile::string_utils::to_string( i->first ) + "]" ;
+				callback( "missing" + tag, table( level, 0 ) ) ;
+				callback( "non_missing" + tag, table( level, 1 ) ) ;
+			}
+		}
+
+		std::string const stub = "missingness_by_" + m_stratification_name ;
+	//	callback( stub + "_sample_odds_ratio", table(0,0) * table(1,1) / ( table(0,1) * table(1,0) ) ) ;
+	
+		if( table.row(0).sum() > 0 && table.row(1).sum() > 0 ) {
+			// perform the exact test.  For speed reasons this is only done if the chi-square approximation may be inaccurate.
+			if( table.rows() == 2 ) {
+				try {
+					metro::FishersExactTest test( table ) ;
+					callback( stub + "_exact_pvalue", test.get_pvalue( metro::FishersExactTest::eTwoSided ) )  ;
+				}
+				catch( std::exception const& e ) {
+					callback( stub + "_exact_pvalue", genfile::MissingValue() ) ;
+				}
+			} else {
+				callback( stub + "_exact_pvalue", genfile::MissingValue() ) ;
+			}
+			{
+				metro::likelihood::Multinomial< double, Eigen::VectorXd, Eigen::MatrixXd > null_model( table.colwise().sum() ) ;
+				null_model.evaluate_at( null_model.get_MLE() ) ;
+				metro::likelihood::ProductOfMultinomials< double, Eigen::VectorXd, Eigen::MatrixXd > alternative_model( table ) ;
+				alternative_model.evaluate_at( alternative_model.get_MLE() ) ;
+				double likelihood_ratio_statistic = -2.0 * ( null_model.get_value_of_function() - alternative_model.get_value_of_function() ) ;
+
+				if( likelihood_ratio_statistic != likelihood_ratio_statistic || likelihood_ratio_statistic < 0.0 ) {
+					likelihood_ratio_statistic = std::numeric_limits< double >::quiet_NaN() ;
+				}
+				else {
+					boost::math::chi_squared_distribution< double > chi_squared( table.rows() - 1 ) ;
+
+					double p_value = boost::math::cdf(
+						boost::math::complement(
+							chi_squared,
+							likelihood_ratio_statistic
+						)
+					) ;
+				
+				
+					callback( stub + "_lrt_pvalue", p_value ) ;
+					callback( stub + "_lrt_df", genfile::VariantEntry::Integer( table.rows() - 1 )) ;
+				}
+			}
+		}
+	}
+
+	std::string DifferentialMissingnessComputation::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		return prefix + "DifferentialMissingnessComputation" ;
+	}
 }

Index: components/SNPSummaryComponent/src/GeneticMapAnnotation.cpp
==================================================================
--- components/SNPSummaryComponent/src/GeneticMapAnnotation.cpp
+++ components/SNPSummaryComponent/src/GeneticMapAnnotation.cpp
@@ -9,47 +9,49 @@
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantDataReader.hpp"
 #include "genfile/FromFilesGeneticMap.hpp"
 #include "components/SNPSummaryComponent/GeneticMapAnnotation.hpp"
 
-GeneticMapAnnotation::UniquePtr GeneticMapAnnotation::create(
-	std::vector< genfile::wildcard::FilenameMatch > const& filenames,
-	ProgressCallback callback
-) {
-	return GeneticMapAnnotation::UniquePtr(
-		new GeneticMapAnnotation( filenames, callback )
-	) ;
-}
-
-GeneticMapAnnotation::GeneticMapAnnotation(
-	std::vector< genfile::wildcard::FilenameMatch > const& filenames,
-	ProgressCallback callback
-):
-	m_map(
-		new genfile::FromFilesGeneticMap( filenames, callback )
-	),
-	m_map_chromosomes( m_map->get_chromosomes() )
-{}
-
-void GeneticMapAnnotation::operator()(
-	VariantIdentifyingData const& snp,
-	Genotypes const&,
-	Ploidy const&,
-	genfile::VariantDataReader&,
-	ResultCallback callback
-) {
-	if( m_map_chromosomes.find( snp.get_position().chromosome() ) != m_map_chromosomes.end() ) {
-		callback(
-			"cM_per_Mb",
-			m_map->find_rate_at_position( snp.get_position() )
-		) ;
-		callback(
-			"cM_from_start_of_chromosome",
-			m_map->find_cM_from_beginning_of_chromosome_at_position( snp.get_position() )
-		) ;
-	}
-}
-
-std::string GeneticMapAnnotation::get_summary( std::string const& prefix, std::size_t column_width ) const {
-	std::string result = prefix + "GeneticMapAnnotation: using " + m_map->get_summary() ;
-	return result ;
+namespace stats {
+	GeneticMapAnnotation::UniquePtr GeneticMapAnnotation::create(
+		std::vector< genfile::wildcard::FilenameMatch > const& filenames,
+		ProgressCallback callback
+	) {
+		return GeneticMapAnnotation::UniquePtr(
+			new GeneticMapAnnotation( filenames, callback )
+		) ;
+	}
+
+	GeneticMapAnnotation::GeneticMapAnnotation(
+		std::vector< genfile::wildcard::FilenameMatch > const& filenames,
+		ProgressCallback callback
+	):
+		m_map(
+			new genfile::FromFilesGeneticMap( filenames, callback )
+		),
+		m_map_chromosomes( m_map->get_chromosomes() )
+	{}
+
+	void GeneticMapAnnotation::operator()(
+		VariantIdentifyingData const& snp,
+		Genotypes const&,
+		Ploidy const&,
+		genfile::VariantDataReader&,
+		ResultCallback callback
+	) {
+		if( m_map_chromosomes.find( snp.get_position().chromosome() ) != m_map_chromosomes.end() ) {
+			callback(
+				"cM_per_Mb",
+				m_map->find_rate_at_position( snp.get_position() )
+			) ;
+			callback(
+				"cM_from_start_of_chromosome",
+				m_map->find_cM_from_beginning_of_chromosome_at_position( snp.get_position() )
+			) ;
+		}
+	}
+
+	std::string GeneticMapAnnotation::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		std::string result = prefix + "GeneticMapAnnotation: using " + m_map->get_summary() ;
+		return result ;
+	}
 }

Index: components/SNPSummaryComponent/src/GenomeSequence.cpp
==================================================================
--- components/SNPSummaryComponent/src/GenomeSequence.cpp
+++ components/SNPSummaryComponent/src/GenomeSequence.cpp
@@ -14,126 +14,210 @@
 #include "genfile/Error.hpp"
 #include "genfile/string_utils/slice.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "components/SNPSummaryComponent/GenomeSequence.hpp"
 
-GenomeSequence::UniquePtr GenomeSequence::create( std::string const& fasta_filename, ProgressCallback callback ) {
+GenomeSequence::UniquePtr GenomeSequence::create( std::vector< std::string > const& fasta_filenames, ProgressCallback callback ) {
 	return GenomeSequence::UniquePtr(
-		new GenomeSequence( fasta_filename, callback )
+		new GenomeSequence( fasta_filenames, callback )
 	) ;
 }
 
 GenomeSequence::GenomeSequence( std::string const& fasta_filename, ProgressCallback callback ):
-	m_fasta_filename( fasta_filename )
-{
-	load_sequence( genfile::wildcard::find_files_by_chromosome( fasta_filename, genfile::wildcard::eALL_CHROMOSOMES ), &m_sequence, callback ) ;
-}
-
-void GenomeSequence::load_sequence( std::vector< genfile::wildcard::FilenameMatch > const& files, SequenceData* sequence, ProgressCallback callback ) {
-	assert( sequence ) ;
-	for( std::size_t i = 0; i < files.size(); ++i ) {
-		ChromosomeRangeAndSequence data ;
-		Chromosome chromosome ;
-		std::string identifier ;
-		load_sequence( files[i], &chromosome, &data.second, &data.first, &identifier ) ;
-		if( m_sequence.find( chromosome ) != m_sequence.end() ) {
-			throw genfile::DuplicateKeyError( m_fasta_filename, "chromosome=\"" + files[i].match() + "\"" ) ;
-		}
-		m_sequence[ chromosome ].first = data.first ;
-		m_sequence[ chromosome ].second.swap( data.second ) ;
-		m_identifiers[ chromosome ] = identifier ;
-		if( callback ) {
-			callback( i + 1, files.size() ) ;
+	m_fasta_filenames( 1, fasta_filename )
+{
+	load_sequence( m_fasta_filenames, callback ) ;
+}
+
+GenomeSequence::GenomeSequence( std::vector< std::string > const& fasta_filenames, ProgressCallback callback ):
+	m_fasta_filenames( fasta_filenames )
+{
+	load_sequence( fasta_filenames, callback ) ;
+}
+
+std::string const GenomeSequence::get_spec() const {
+	return "GenomeSequence(" + genfile::string_utils::join( m_fasta_filenames, "\",\"" ) + ")" ;
+}
+
+void GenomeSequence::load_sequence(
+	std::vector< std::string > const& filenames,
+	ProgressCallback callback
+) {
+	for( std::size_t i = 0; i < filenames.size(); ++i ) {
+		std::vector< std::string > elts = genfile::string_utils::split( filenames[i], "~" ) ;
+		if( elts.size() == 1 ) {
+			elts.insert( elts.begin(), "" ) ;
+		} else if( elts.size() > 2 ) {
+			throw genfile::BadArgumentError(
+				"GenomeSequence::load_sequence()",
+				"filenames[" + genfile::string_utils::to_string(i) + "]=\"" + filenames[i] + "\"",
+				"Filespec should be in the form: name=<path> or just <path>"
+			) ;
+		}
+		load_sequence( elts[0], elts[1] ) ;
+		if( callback ) {
+			callback( i + 1, filenames.size() ) ;
 		}
 	}
 }
 
 void GenomeSequence::load_sequence(
-	genfile::wildcard::FilenameMatch const& file,
-	Chromosome* chromosome,
-	ChromosomeSequence* sequence,
-	std::pair< genfile::Position, genfile::Position >* limits,
-	std::string* identifier
+	std::string const& name,
+	std::string const& filename
 ) {
-	assert( sequence ) ;
-	assert( sequence->empty() ) ;
 	using genfile::string_utils::to_string ;
 
 	// read header
-	std::auto_ptr< std::istream > stream( genfile::open_text_file_for_input( file.filename() )) ;
-	std::string line ;
-	std::getline( *stream, line ) ;
+	std::auto_ptr< std::istream > stream( genfile::open_text_file_for_input( filename )) ;
 	if( !*stream ) {
-		throw genfile::MalformedInputError( file.filename(), 0 ) ;
-	}
-	if( line.size() == 0 || line[0] != '>' ) {
-		throw genfile::MalformedInputError(
-			file.filename(),
-			"File does not appear to be a FASTA file (it does not start with a line \">....\")",
-			0
-		) ;
-	}
-	line = line.substr( 1, line.size() ) ;
-	*identifier = line ;
-	*chromosome = genfile::Chromosome( file.match() ) ;
-	
+		throw genfile::MalformedInputError( filename, 0 ) ;
+	}
+
 	// Ok, now read the data
 	std::size_t const BUFFER_SIZE = 1024*1024 ;
 	std::vector< char > buffer( BUFFER_SIZE ) ;
 	std::size_t line_count = 0 ;
-	do {
+	std::string sequenceName = "" ;
+	enum State { eHeader = 0, eSequence = 1 } ;
+	State state = eHeader ;
+	ChromosomeSequence sequence ;
+
+	{
+		// State machine
+		// We are either reading a header line,
+		// or reading sequence lines.
+		enum State { eHeader = 0, eSequence = 1 } ;
+		State state = eHeader ;
+
+		// try to read more data
 		stream->read( &buffer[0], BUFFER_SIZE ) ;
 		std::size_t const count = stream->gcount() ;
-		char const* p_end = &buffer[0] + count ;
-		for(
-			char const* p = &buffer[0] ;
-			p < p_end;
-			++p
-		 ) {
-			char const* segment_end = std::find( p, p_end, '\n' ) ;
-			sequence->insert( sequence->end(), p, segment_end ) ;
-			p = segment_end ;
-			++line_count ;
-			if( (p < p_end) && (*(p+1) == '>') ) {
-				throw genfile::MalformedInputError(
-					file.filename(),
-					"Only single-sequence FASTA files are supported",
-					0
-				) ;
-			}
-		}
-	} while( *stream ) ;
-	
-	limits->first = 1 ;
-	limits->second = sequence->size() + 1 ;
+		char const* p = &buffer[0] ;
+		char const* data_end = &buffer[0] + count ;
+
+		std::string const prefix = ( name == "" ? "" : ( name + ":" )) ;
+
+		while( (*stream) || p < data_end ) { // while there is more data
+			char const* const line_or_data_end = std::find( p, data_end, '\n' ) ;
+
+			if( state == eHeader ) {
+				assert( p != data_end ) ;
+				if( *p != '>' ) {
+					throw genfile::MalformedInputError(
+						filename,
+						"File does not appear to be a FASTA file (sequence does not start with a \">\" character)",
+						0
+					) ;
+				}
+				// assume header line fits in one \n-terminated line
+				if( line_or_data_end == data_end ) {
+					throw genfile::MalformedInputError(
+						filename,
+						"File does not appear to be a FASTA file (sequence header line appears excessively long)",
+						0
+					) ;
+				}
+				sequenceName.assign( p+1, line_or_data_end ) ;
+				sequence.clear() ;
+				state = eSequence ;
+			} else {
+				// state == eSequence
+				sequence.insert( sequence.end(), p, line_or_data_end ) ;
+			}
+			p = std::min( line_or_data_end + 1, data_end ) ;
+			
+			// Deal with loading additional data if needed
+			if( p == data_end && *stream ) {
+				// try to read more data
+				stream->read( &buffer[0], BUFFER_SIZE ) ;
+				std::size_t const count = stream->gcount() ;
+				p = &buffer[0] ;
+				data_end = &buffer[0] + count ;
+			}
+			
+			// Store the existing sequence if it has ended
+			if( p == data_end || *p == '>' ) {
+				 // First try to parse useful info out of sequence header line
+				std::size_t colon = sequenceName.find( ':' ) ;
+				uint32_t sequenceStart = 1 ;
+				if( colon != -1 ) {
+					std::string range = sequenceName.substr( colon+1, sequenceName.size() ) ;
+					std::size_t dash = range.find( '-' ) ;
+					if( dash != -1 ) {
+						try {
+							sequenceStart = genfile::string_utils::to_repr< uint32_t >(
+								range.substr( 1, dash )
+							) ;
+						}
+						catch( genfile::string_utils::StringConversionError const& e ) {
+							// ignore
+						}
+					}
+				}
+				// Sanity check...
+				if( m_data.find( sequenceName ) != m_data.end() ) {
+					throw genfile::DuplicateKeyError( filename, "sequence name=\"" + sequenceName + "\"" ) ;
+				}
+				
+				// Only take the first whitespace-seperated string from the fasta header as the sequence name
+				std::size_t pos = sequenceName.find( ' ' ) ;
+				if( pos != std::string::npos ) {
+					sequenceName.resize( pos ) ;
+				}
+				
+				// ...and store sequence
+				m_data[ prefix + sequenceName ] = ChromosomeRangeAndSequence(
+					std::make_pair( sequenceStart, sequenceStart + sequence.size() ),
+					sequence
+				) ;
+
+				state = eHeader ;
+			}
+		}
+	}
 }
 
 std::string GenomeSequence::get_summary( std::string const& prefix, std::size_t column_width ) const {
 	using genfile::string_utils::to_string ;
 	std::string result = prefix + "GenomeSequence ("
 		+ ( m_organism ? m_organism.get() : "unknown organism" ) + ", "
 		+ ( m_build ? m_build.get() : "unknown build" ) + ") "
 		+ "for the following regions:" ;
 	std::size_t count = 0 ;
-	for( SequenceData::const_iterator i = m_sequence.begin(); i != m_sequence.end(); ++i, ++count ) {
+	for( SequenceData::const_iterator i = m_data.begin(); i != m_data.end(); ++i, ++count ) {
 		std::string const& identifier = m_identifiers.find( i->first )->second ;
 		result += "\n" + prefix + " - chromosome " + to_string( i->first ) + " (" + identifier + "):"
 			+ to_string( i->second.first.first ) + "-" + to_string( i->second.first.second )
 			+  " (length " + to_string( i->second.first.second - i->second.first.first ) + ")" ;
 	}
 	return result ;
 }
+
+std::vector< genfile::GenomePositionRange > GenomeSequence::get_ranges() const {
+	std::vector< genfile::GenomePositionRange > result ;
+	SequenceData::const_iterator i = m_data.begin(), end_i = m_data.end() ;
+	for( ; i != end_i; ++i ) {
+		result.push_back(
+			genfile::GenomePositionRange(
+				i->first,
+				i->second.first.first,
+				i->second.first.second - 1
+			)
+		) ;
+	}
+	return result ;
+}
 
 bool GenomeSequence::has_chromosome( genfile::Chromosome const& chromosome ) const {
-	SequenceData::const_iterator where = m_sequence.find( chromosome ) ;
-	return where != m_sequence.end() ;
+	SequenceData::const_iterator where = m_data.find( chromosome ) ;
+	return where != m_data.end() ;
 }
 
 char GenomeSequence::get_base( genfile::GenomePosition const& position ) const {
 	using namespace genfile::string_utils ;
-	SequenceData::const_iterator where = m_sequence.find( position.chromosome() ) ;
-	if( where == m_sequence.end() ) {
+	SequenceData::const_iterator where = m_data.find( position.chromosome() ) ;
+	if( where == m_data.end() ) {
 		throw genfile::BadArgumentError(
 			"GenomeSequence::get_base()",
 			"chromosome=\"" + to_string( position.chromosome() ) + "\"",
 			"Chromosome is not in the stored sequence."
 		) ;
@@ -162,12 +246,12 @@
 
 GenomeSequence::PhysicalSequenceRange
 GenomeSequence::get_sequence( genfile::Chromosome const& chromosome, genfile::Position start, genfile::Position end ) const {
 	using namespace genfile::string_utils ;
 	assert( end >= start ) ;
-	SequenceData::const_iterator where = m_sequence.find( chromosome ) ;
-	if( where == m_sequence.end() ) {
+	SequenceData::const_iterator where = m_data.find( chromosome ) ;
+	if( where == m_data.end() ) {
 		throw genfile::BadArgumentError(
 			"GenomeSequence::get_sequence()",
 			"chromosome=\"" + to_string( chromosome ) + "\"",
 			"Chromosome is not in the stored sequence."
 		) ;
@@ -186,10 +270,10 @@
 	return PhysicalSequenceRange(
 		genfile::GenomePositionRange(
 			chromosome, actual_start, actual_end
 		),
 		ConstSequenceRange(
-			where->second.second.begin() + start - sequence_start,
-			where->second.second.begin() + end - sequence_start
+			where->second.second.begin() + (start - sequence_start),
+			where->second.second.begin() + (end - sequence_start)
 		)
 	) ;
 }

Index: components/SNPSummaryComponent/src/GenotypeFrequencyTestCallComparer.cpp
==================================================================
--- components/SNPSummaryComponent/src/GenotypeFrequencyTestCallComparer.cpp
+++ components/SNPSummaryComponent/src/GenotypeFrequencyTestCallComparer.cpp
@@ -9,11 +9,10 @@
 #include <cmath>
 #include <cassert>
 #include <boost/function.hpp>
 #include <Eigen/Core>
 #include "genfile/SingleSNPGenotypeProbabilities.hpp"
-#include "integration/NewtonRaphson.hpp"
 #include "components/SNPSummaryComponent/GenotypeFrequencyTestCallComparer.hpp"
 #include "metro/likelihood/Multinomial.hpp"
 #include "metro/likelihood/ProductOfMultinomials.hpp"
 #include "metro/rBF.hpp"
 

Index: components/SNPSummaryComponent/src/HWEComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/HWEComputation.cpp
+++ components/SNPSummaryComponent/src/HWEComputation.cpp
@@ -17,11 +17,11 @@
 #include "metro/likelihood/ProductOfMultinomials.hpp"
 #include "metro/FishersExactTest.hpp"
 
 // #define DEBUG_HWE_COMPUTATION 1
 
-namespace snp_summary_component {
+namespace stats {
 	HWEComputation::HWEComputation():
 		m_threshhold( 0.9 ),
 		m_chi_squared_1df( 1.0 ),
 		m_chi_squared_2df( 2.0 )
 	{}

ADDED   components/SNPSummaryComponent/src/InfoComputation.cpp
Index: components/SNPSummaryComponent/src/InfoComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/InfoComputation.cpp
+++ components/SNPSummaryComponent/src/InfoComputation.cpp
@@ -0,0 +1,197 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include <boost/function.hpp>
+#include <Eigen/Core>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/VariantDataReader.hpp"
+#include "appcontext/OptionProcessor.hpp"
+#include "components/SNPSummaryComponent/InfoComputation.hpp"
+
+namespace stats {
+	void InfoComputation::operator()(
+		VariantIdentifyingData const& snp,
+		Genotypes const& genotypes,
+		Ploidy const& ploidy,
+		genfile::VariantDataReader&,
+		ResultCallback callback
+	) {
+		m_computation.compute( snp, genotypes, ploidy ) ;
+		callback( "info", m_computation.info() ) ;
+		callback( "impute_info", m_computation.impute_info() ) ;
+	}
+	
+	std::string InfoComputation::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		return prefix + "InfoComputation" ;
+	}
+	
+	namespace impl {
+		namespace {
+			double compute_variance( Eigen::VectorXd const& levels, Eigen::VectorXd const& levels_squared, Eigen::VectorXd const& probs ) {
+				double const mean = ( probs.transpose() * levels )(0) ;
+				double const variance = ( probs.transpose() * levels_squared )(0) - ( mean * mean ) ;
+				return variance ;
+			}
+
+			// treat the rows of the probabilities matrix as probabilities.
+			// distribution for individual i is taken as a mixture of the distribution given by row i of probabilities,
+			// and the fallback distribution if the sum of row i < 1, appropriately weighted.
+			// Only individuals with inclusion = 1 are used.
+			template< typename Probabilities, typename InclusionIndicator >
+			double compute_sum_of_variances( Eigen::VectorXd const& levels, Probabilities const& probabilities, Eigen::VectorXd const& fallback, InclusionIndicator const& inclusion ) {
+				assert( levels.size() == fallback.size() ) ;
+				assert( levels.size() == probabilities.cols() ) ;
+				assert( inclusion.size() == probabilities.rows() ) ;
+				Eigen::VectorXd levels_squared = ( levels.array() * levels.array() ) ;
+
+				double result = 0.0 ;
+				for( int i = 0; i < probabilities.rows(); ++i ) {
+					if( inclusion( i ) == 1 ) {
+						double const c = probabilities.row( i ).sum() ;
+						result += compute_variance( levels, levels_squared, probabilities.row( i ).transpose() + ( 1 - c ) * fallback ) ;
+					}
+				}
+				return result ;
+			}
+	
+		}
+		
+		InfoComputation::InfoComputation():
+			m_diploid_fallback_distribution( Eigen::VectorXd::Zero( 3 )),
+			m_haploid_fallback_distribution( Eigen::VectorXd::Zero( 2 )),
+			m_diploid_levels( Eigen::VectorXd::LinSpaced( 3, 0, 2 )),
+			m_haploid_levels( Eigen::VectorXd::LinSpaced( 2, 0, 1 ))
+		{}
+		
+		void InfoComputation::compute(
+			VariantIdentifyingData const& snp,
+			Genotypes const& genotypes,
+			Ploidy const& ploidy
+		) {
+			compute(
+				snp, genotypes, ploidy,
+				std::vector< metro::SampleRange >( 1, metro::SampleRange( 0, genotypes.rows()) )
+			) ;
+		}
+			
+		void InfoComputation::compute(
+			VariantIdentifyingData const& snp,
+			Genotypes const& genotypes,
+			Ploidy const& ploidy,
+			std::vector< metro::SampleRange > const& included_samples
+		) {
+			m_info = std::numeric_limits< double >::quiet_NaN() ;
+			m_impute_info = std::numeric_limits< double >::quiet_NaN() ;
+
+			// we don't compute for multiallelics currently
+			if( snp.number_of_alleles() == 2 ) {
+				compute_impl( snp, genotypes, ploidy, included_samples ) ;
+			}
+		}
+	
+		void InfoComputation::compute_impl(
+			VariantIdentifyingData const& snp,
+			Genotypes const& genotypes,
+			Ploidy const& ploidy,
+			std::vector< metro::SampleRange > const& included_samples
+		) {
+			typedef Eigen::Block< Genotypes const > GenotypeBlock ;
+			typedef Eigen::VectorBlock< Eigen::VectorXd const > PloidyBlock ;
+
+			// This function assumes every sample is haploid or diploid.
+			Eigen::VectorXd const haploids = ( ploidy.array() == 1 ).cast< double >() ;
+			Eigen::VectorXd const diploids = ( ploidy.array() == 2 ).cast< double >() ;
+			
+			double b_allele_count = 0 ;
+			double total_allele_count = 0 ;
+			double autosomal_b_allele_count = 0 ;		// for computations that pretend ploidy == 2 everywhere.
+			double autosomal_total_allele_count = 0 ;	// for computations that pretend ploidy == 2 everywhere.
+
+			double number_of_haploid_info_samples = 0 ;
+			double number_of_diploid_info_samples = 0 ;
+			double total_probability = 0 ;
+			for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+				GenotypeBlock const block = genotypes.block( included_samples[i].begin(), 0, included_samples[i].end() - included_samples[i].begin(), genotypes.cols() ) ;
+				PloidyBlock const haploid_block = haploids.segment( included_samples[i].begin(), included_samples[i].size() ) ;
+				PloidyBlock const diploid_block = diploids.segment( included_samples[i].begin(), included_samples[i].size() ) ;
+		
+				b_allele_count += (( block.col( 1 ) + 2.0 * block.col( 2 ) ).array() * diploid_block.array() ).sum() ;
+				b_allele_count += (( block.col( 1 ) ).array() * haploid_block.array() ).sum() ;
+
+				total_allele_count += 2 * ( block.rowwise().sum().array() * diploid_block.array() ).sum() ;
+				total_allele_count += ( block.rowwise().sum().array() * haploid_block.array() ).sum() ;
+
+				autosomal_b_allele_count += ( block.col( 1 ) + 2.0 * block.col( 2 ) ).array().sum() ;
+				autosomal_total_allele_count += 2 * block.sum() ;
+			
+				number_of_haploid_info_samples += haploid_block.sum() ;
+				number_of_diploid_info_samples += diploid_block.sum() ;
+				total_probability += block.sum() ;
+			}
+			
+			// MLE estimate of allele frequency
+			double const theta_mle = b_allele_count / total_allele_count ;
+			double const autosomal_theta_mle = autosomal_b_allele_count / autosomal_total_allele_count ;
+			double const theta_est = theta_mle ;
+
+			m_diploid_fallback_distribution( 0 ) = ( 1 - theta_mle ) * ( 1 - theta_mle ) ;
+			m_diploid_fallback_distribution( 1 ) = 2.0 * theta_mle * ( 1 - theta_mle ) ;
+			m_diploid_fallback_distribution( 2 ) = theta_mle * theta_mle ;
+		
+			m_haploid_fallback_distribution( 0 ) = 1 - theta_mle ;
+			m_haploid_fallback_distribution( 1 ) = theta_mle ;
+		
+			//std::cerr << "theta = " << theta_mle << ", fallback_distribution = " << fallback_distribution.transpose() << ".\n" ;
+		
+			double diploid_info_term = 0.0 ;
+			double haploid_info_term = 0.0 ;
+			double impute_info_term = 0.0 ;
+			for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+				GenotypeBlock const diploid_genotype_block = genotypes.block( included_samples[i].begin(), 0, included_samples[i].size(), genotypes.cols() ) ;
+				GenotypeBlock const haploid_genotype_block = genotypes.block( included_samples[i].begin(), 0, included_samples[i].size(), 2 ) ;
+				PloidyBlock const haploid_block = haploids.segment( included_samples[i].begin(), included_samples[i].size() ) ;
+				PloidyBlock const diploid_block = diploids.segment( included_samples[i].begin(), included_samples[i].size() ) ;
+
+				haploid_info_term -= compute_sum_of_variances(
+					m_haploid_levels, haploid_genotype_block,
+					m_haploid_fallback_distribution, haploid_block
+				)
+				/ ( theta_mle * ( 1 - theta_mle ) ) ;
+
+				diploid_info_term -= compute_sum_of_variances(
+					m_diploid_levels, diploid_genotype_block,
+					m_diploid_fallback_distribution, diploid_block
+				)
+				/ ( 2.0 * theta_mle * ( 1 - theta_mle ) ) ;
+			
+				impute_info_term -= compute_sum_of_variances(
+					m_diploid_levels, diploid_genotype_block,
+					Eigen::VectorXd::Zero( 3 ), Eigen::VectorXd::Constant( diploid_genotype_block.rows(), 1 )
+				)
+				/ ( 2.0 * autosomal_theta_mle * ( 1 - autosomal_theta_mle ) ) ;
+			}
+		
+			double info = std::numeric_limits< double >::quiet_NaN() ;
+			double impute_info = std::numeric_limits< double >::quiet_NaN() ;
+
+			if(( number_of_haploid_info_samples + number_of_diploid_info_samples ) > 0 ) {
+				info = 1.0 + (haploid_info_term + diploid_info_term) / ( number_of_haploid_info_samples + number_of_diploid_info_samples ) ;
+			}
+			
+			if( total_probability > 0 ) {
+				impute_info = 1.0 + impute_info_term / total_probability ;
+			}
+
+			m_info = info ;
+			m_impute_info = impute_info ;
+		}
+
+	}
+}

Index: components/SNPSummaryComponent/src/IntensitySummaryComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/IntensitySummaryComputation.cpp
+++ components/SNPSummaryComponent/src/IntensitySummaryComputation.cpp
@@ -12,11 +12,11 @@
 #include "genfile/VariantDataReader.hpp"
 #include "genfile/vcf/get_set.hpp"
 #include "components/SNPSummaryComponent/IntensitySummaryComputation.hpp"
 #include "metro/mean_and_covariance.hpp"
 
-namespace snp_summary_component {
+namespace stats {
 	IntensitySummaryComputation::IntensitySummaryComputation( double call_threshhold ):
 		m_call_threshhold( call_threshhold )
 	{}
 
 	void IntensitySummaryComputation::operator()(

Index: components/SNPSummaryComponent/src/PairwiseCallComparerManager.cpp
==================================================================
--- components/SNPSummaryComponent/src/PairwiseCallComparerManager.cpp
+++ components/SNPSummaryComponent/src/PairwiseCallComparerManager.cpp
@@ -10,12 +10,12 @@
 #include "genfile/SNPDataSourceProcessor.hpp"
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/Error.hpp"
 #include "statfile/BuiltInTypeStatSink.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "components/SNPSummaryComponent/PairwiseCallComparer.hpp"
 #include "components/SNPSummaryComponent/PairwiseCallComparerManager.hpp"
 #include "components/SNPSummaryComponent/FrequentistTestCallMerger.hpp"
 #include "components/SNPSummaryComponent/AcceptAllCallMerger.hpp"
 

Index: components/SNPSummaryComponent/src/SNPSummaryComponent.cpp
==================================================================
--- components/SNPSummaryComponent/src/SNPSummaryComponent.cpp
+++ components/SNPSummaryComponent/src/SNPSummaryComponent.cpp
@@ -161,14 +161,14 @@
 	processor.add_callback( genfile::SNPDataSourceProcessor::Callback::UniquePtr(
 		create_manager( storage ).release() )
 	) ;
 }
 
-SNPSummaryComputationManager::UniquePtr SNPSummaryComponent::create_manager(
+stats::SNPSummaryComputationManager::UniquePtr SNPSummaryComponent::create_manager(
 	qcdb::Storage::SharedPtr storage
 ) {
-	SNPSummaryComputationManager::UniquePtr manager( new SNPSummaryComputationManager( m_samples, m_options.get_value< std::string >( "-sex-column" ) ) ) ;
+	stats::SNPSummaryComputationManager::UniquePtr manager( new stats::SNPSummaryComputationManager( m_samples, m_options.get_value< std::string >( "-sex-column" ) ) ) ;
 	{
 		std::string const coding_string = m_options.get< std::string >( "-haploid-genotype-coding" ) ;
 		if( coding_string == "hom" ) {
 			manager->set_haploid_genotype_coding( 2 ) ; 
 		} else if( coding_string == "het" ) {
@@ -227,11 +227,11 @@
 
 namespace {
 	void parse_bed_annotation_spec( std::string const& spec, std::vector< genfile::string_utils::slice >* filenames, unsigned int* margin ) ;
 }
 	
-void SNPSummaryComponent::add_computations( SNPSummaryComputationManager& manager, qcdb::Storage::SharedPtr storage ) const {
+void SNPSummaryComponent::add_computations( stats::SNPSummaryComputationManager& manager, qcdb::Storage::SharedPtr storage ) const {
 	using genfile::string_utils::split_and_strip_discarding_empty_entries ;
 	using boost::regex_replace ;
 	using boost::regex ;
 
 	typedef std::map< std::string, qcdb::Storage::SharedPtr > Outputters ;
@@ -238,23 +238,23 @@
 	Outputters outputters ;
 
 	if( m_options.check( "-snp-stats" )) {
 		std::vector< std::string > elts = split_and_strip_discarding_empty_entries( m_options.get_value< std::string >( "-snp-stats-columns" ), ",", " \t" ) ;
 		BOOST_FOREACH( std::string const& elt, elts ) {
-			manager.add_computation( elt, SNPSummaryComputation::create( elt )) ;
+			manager.add_computation( elt, stats::SNPSummaryComputation::create( elt )) ;
 		}
 	}
 	
 	if( m_options.check( "-snp-stats" )) {
 		std::vector< std::string > elts = split_and_strip_discarding_empty_entries( m_options.get_value< std::string >( "-snp-stats-columns" ), ",", " \t" ) ;
 		BOOST_FOREACH( std::string const& elt, elts ) {
-			manager.add_computation( elt, SNPSummaryComputation::create( elt )) ;
+			manager.add_computation( elt, stats::SNPSummaryComputation::create( elt )) ;
 		}
 	}
 
 	if( m_options.check( "-intensity-stats" )) {
-		manager.add_computation( "intensity-stats", SNPSummaryComputation::create( "intensity-stats" )) ;
+		manager.add_computation( "intensity-stats", stats::SNPSummaryComputation::create( "intensity-stats" )) ;
 	}
 
 	if( m_options.check( "-fit-clusters" )) {
 		std::vector< std::string > params = m_options.get_values( "-fit-cluster-parameters" ) ;
 		double nu = 0 ;
@@ -263,19 +263,19 @@
 		} else {
 			nu = genfile::string_utils::to_repr< double >( params[0] ) ;
 		}
 		double regularisationVariance = genfile::string_utils::to_repr< double >( params[1] ) ;
 		double regularisationCount = genfile::string_utils::to_repr< double >( params[2] ) ;
-		snp_summary_component::ClusterFitComputation::UniquePtr computation(
-			new snp_summary_component::ClusterFitComputation(
+		stats::ClusterFitComputation::UniquePtr computation(
+			new stats::ClusterFitComputation(
 				nu, regularisationVariance, regularisationCount
 			)
 		) ;
 		computation->set_scale( m_options.get< std::string >( "-fit-cluster-scale" )) ;
 		manager.add_computation(
 			"fit-clusters",
-			SNPSummaryComputation::UniquePtr( computation.release() )
+			stats::SNPSummaryComputation::UniquePtr( computation.release() )
 		) ;
 	}
 
 	if( m_options.check( "-compare-to" )) {
 		std::vector< std::string > filenames = m_options.get_values< std::string >( "-compare-to" ) ;
@@ -290,21 +290,21 @@
 				"SNPSummaryComponent::add_computations()",
 				"-match-sample-ids " + m_options.get< std::string >( "-match-sample-ids" ),
 				"Value should be of the form <id in main dataset>~<id in compared-to dataset>"
 			) ;
 		}
-		snp_stats::CrossDataSetComparison::UniquePtr computation ;
+		stats::CrossDataSetComparison::UniquePtr computation ;
 		if( m_options.check( "-haplotypic" ) ) {
 			computation.reset(
-				new snp_stats::CrossDataSetHaplotypeComparisonComputation(
+				new stats::CrossDataSetHaplotypeComparisonComputation(
 					m_samples,
 					sample_id_columns[0]
 				)
 			) ;
 		} else {
 			computation.reset(
-				new snp_stats::CrossDataSetConcordanceComputation(
+				new stats::CrossDataSetConcordanceComputation(
 					m_samples,
 					sample_id_columns[0]
 				)
 			) ;
 		}
@@ -336,11 +336,11 @@
 			alternate_dataset
 		) ;
 
 		manager.add_computation(
 			"dataset_comparison",
-			SNPSummaryComputation::UniquePtr(
+			stats::SNPSummaryComputation::UniquePtr(
 				computation.release()
 			)
 		) ;
 	}
 
@@ -347,11 +347,11 @@
 	if( m_options.check( "-differential" )) {
 		std::string const variable = m_options.get< std::string >( "-differential" ) ;
 		impl::StrataMembers strata = impl::compute_strata( m_samples, variable ) ;
 		manager.add_computation(
 			"differential_missingness",
-			DifferentialMissingnessComputation::create( variable, strata )
+			stats::DifferentialMissingnessComputation::create( variable, strata )
 		) ;
 	}
 
 	if( m_options.check( "-stratify" )) {
 		std::string const variable = m_options.get< std::string >( "-stratify" ) ;
@@ -368,12 +368,12 @@
 				"-annotate-sequence " + genfile::string_utils::join( elts, " " ),
 				"-annotate-sequence takes an even number of arguments: <filename> <annotation name>..."
 			) ;
 		}
 		for( std::size_t i = 0; i < elts.size(); i += 2 ) {
-			SequenceAnnotation::UniquePtr computation(
-				new SequenceAnnotation( elts[i+1], elts[i], progress )
+			stats::SequenceAnnotation::UniquePtr computation(
+				new stats::SequenceAnnotation( elts[i+1], elts[i], progress )
 			) ;
 		
 			if( m_options.check( "-flanking" )) {
 				std::vector< std::size_t > data = m_options.get_values< std::size_t >( "-flanking" ) ;
 				assert( data.size() == 2 ) ;
@@ -380,56 +380,36 @@
 				computation->set_flanking( data[0], data[1] ) ;
 			}
 		
 			manager.add_computation(
 				elts[1] + "_sequence",
-				SNPSummaryComputation::UniquePtr(
+				stats::SNPSummaryComputation::UniquePtr(
 					computation.release()
 				)
 			) ;
 		}
 	}
 
-	if( m_options.check( "-annotate-ancestral" )) {
-		appcontext::UIContext::ProgressContext progress = m_ui_context.get_progress_context( "Loading ancestral sequence" ) ;
-		SequenceAnnotation::UniquePtr computation(
-			new SequenceAnnotation( "ancestral", m_options.get< std::string >( "-annotate-ancestral" ), progress )
-		) ;
-		
-		if( m_options.check( "-flanking" )) {
-			std::vector< std::size_t > data = m_options.get_values< std::size_t >( "-flanking" ) ;
-			assert( data.size() == 2 ) ;
-			computation->set_flanking( data[0], data[1] ) ;
-		}
-
-		manager.add_computation(
-			"ancestral_sequence",
-			SNPSummaryComputation::UniquePtr(
-				computation.release()
-			)
-		) ;
-	}
-
 	if( m_options.check( "-annotate-genetic-map" )) {
 		appcontext::UIContext::ProgressContext progress = m_ui_context.get_progress_context( "Loading genetic map" ) ;
-		GeneticMapAnnotation::UniquePtr computation = GeneticMapAnnotation::create(
+		stats::GeneticMapAnnotation::UniquePtr computation = stats::GeneticMapAnnotation::create(
 			genfile::wildcard::find_files_by_chromosome(
 				m_options.get< std::string >( "-annotate-genetic-map" )
 			),
 			progress
 		) ;
 		
 		manager.add_computation(
 			"genetic_map",
-			SNPSummaryComputation::UniquePtr(
+			stats::SNPSummaryComputation::UniquePtr(
 				computation.release()
 			)
 		) ;
 	}
 
 	if( m_options.check( "-annotate-bed3" )) {
-		Bed3Annotation::UniquePtr annotation = Bed3Annotation::create() ;
+		stats::Bed3Annotation::UniquePtr annotation = stats::Bed3Annotation::create() ;
 
 		{
 			appcontext::UIContext::ProgressContext progress = m_ui_context.get_progress_context( "Loading bed intervals" ) ;
 			std::vector< std::string > const& specs = m_options.get_values< std::string >( "-annotate-bed3" ) ;
 			progress( 0, specs.size() ) ;
@@ -450,18 +430,18 @@
 			}
 		}
 		
 		manager.add_computation(
 			"bed3_annotation",
-			SNPSummaryComputation::UniquePtr(
+			stats::SNPSummaryComputation::UniquePtr(
 				annotation.release()
 			)
 		) ;
 	}
 
 	if( m_options.check( "-annotate-bed4" )) {
-		Bed4Annotation::UniquePtr annotation = Bed4Annotation::create() ;
+		stats::Bed4Annotation::UniquePtr annotation = stats::Bed4Annotation::create() ;
 
 		{
 			appcontext::UIContext::ProgressContext progress = m_ui_context.get_progress_context( "Loading bed values" ) ;
 			std::vector< std::string > const& specs = m_options.get_values< std::string >( "-annotate-bed4" ) ;
 			progress( 0, specs.size() ) ;
@@ -482,27 +462,15 @@
 			}
 		}
 		
 		manager.add_computation(
 			"bed4_annotation",
-			SNPSummaryComputation::UniquePtr(
+			stats::SNPSummaryComputation::UniquePtr(
 				annotation.release()
 			)
 		) ;
 	}
-
-#if 0
-	if( m_options.check_if_option_was_supplied_in_group( "Call comparison options" ) ) {
-		CallComparerComponent::UniquePtr cc = CallComparerComponent::create(
-			m_samples,
-			m_options,
-			m_ui_context
-		) ;
-
-		cc->setup( manager, storage ) ;
-	}
-#endif
 }
 
 namespace {
 	void parse_bed_annotation_spec(
 		std::string const& spec,
@@ -534,13 +502,5 @@
 			*margin = to_repr< unsigned int >( elts[1].substr( 0, elts[1].size() - 2 )) ; 
 		}
 		*filenames = elts[0].split( "," ) ;
 	}
 }
-
-SNPSummaryComputation::UniquePtr SNPSummaryComponent::create_computation( std::string const& name ) const {
-	if( name != "association_test" ) {
-		return SNPSummaryComputation::UniquePtr( SNPSummaryComputation::create( name )) ;
-	} else {
-		assert(0) ;
-	}
-}

Index: components/SNPSummaryComponent/src/SNPSummaryComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/SNPSummaryComputation.cpp
+++ components/SNPSummaryComponent/src/SNPSummaryComputation.cpp
@@ -16,15 +16,15 @@
 #include "components/SNPSummaryComponent/SNPHWE.hpp"
 #include "components/SNPSummaryComponent/SNPSummaryComputation.hpp"
 #include "components/SNPSummaryComponent/HWEComputation.hpp"
 #include "components/SNPSummaryComponent/IntensitySummaryComputation.hpp"
 #include "components/SNPSummaryComponent/ClusterFitComputation.hpp"
+#include "components/SNPSummaryComponent/InfoComputation.hpp"
 
 // #define DEBUG_SNP_SUMMARY_COMPUTATION 1
 
-namespace snp_summary_component {
-	
+namespace stats {	
 	namespace {
 		struct AlleleCountClient: public genfile::VariantDataReader::PerSampleSetter {
 			AlleleCountClient( std::vector< double >* counts ):
 				m_counts( counts ),
 				m_number_of_alleles( 0 )
@@ -156,11 +156,10 @@
 			Genotypes const& genotypes,
 			Ploidy const& ploidy,
 			genfile::VariantDataReader&,
 			ResultCallback callback
 		) {
-			genfile::Chromosome const& chromosome = snp.get_position().chromosome() ;
 			if( snp.number_of_alleles() == 2 ) {
 				bool const allDiploid = ( ploidy.array() == 2 ).cast< int >().sum() == ploidy.size() ;
 				if( allDiploid ) {
 					compute_autosomal_frequency( snp, genotypes, callback ) ;
 				} else {
@@ -268,11 +267,10 @@
 		CallMassComputation( double const threshhold = 0.9 ):
 			m_threshhold(threshhold)
 		{}
 
 		void operator()( VariantIdentifyingData const& snp, Genotypes const& genotypes, Ploidy const& ploidy, genfile::VariantDataReader&, ResultCallback callback ) {
-			genfile::Chromosome const& chromosome = snp.get_position().chromosome() ;
 			bool const allDiploid = ( ploidy.array() == 2 ).cast< int >().sum() == ploidy.size() ;
 			if( allDiploid ) {
 				compute_autosomal_call_mass( snp, genotypes, callback ) ;
 			} else {
 				return ;
@@ -340,11 +338,10 @@
 			std::map< int, double > null_counts ;
 			counts[ -1 ] = Eigen::VectorXd::Zero( 3 ) ;
 			counts[ 0 ] = Eigen::VectorXd::Zero( 3 ) ;
 			counts[ 1 ] = Eigen::VectorXd::Zero( 3 ) ;
 			counts[ 2 ] = Eigen::VectorXd::Zero( 3 ) ;
-			char countKey[5] = { '.', '.', 'm', 'f', '.' } ;
 			std::map< int, std::size_t > sample_counts ;
 
 			for( std::size_t i = 0; i < ploidy.size(); ++i ) {
 				counts[ ploidy(i) ] += genotypes.row( i ) ;
 				null_counts[ ploidy(i) ] += ( 1 - genotypes.row(i).sum() ) ;
@@ -369,219 +366,23 @@
 		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const { return prefix + "MissingnessComputation" ; }
 	private:
 		double const m_call_threshhold ;
 	} ;
 
-	struct InfoComputation: public SNPSummaryComputation {
-		void operator()(
-			VariantIdentifyingData const& snp,
-			Genotypes const& genotypes,
-			Ploidy const& ploidy,
-			genfile::VariantDataReader&,
-			ResultCallback callback
-		) {
-			if( snp.number_of_alleles() == 2 ) {
-				bool const allDiploid = ( ploidy.array() == 2 ).cast< int >().sum() == ploidy.size() ;
-				if( allDiploid ) {
-					compute_autosomal_info( snp, genotypes, callback ) ;
-				} else {
-					compute_sex_chromosome_info( snp, genotypes, ploidy, callback ) ;
-				}
-			} else {
-				// we don't compute for multiallelics currently
-			}
-		}
-		
-		void compute_autosomal_info( VariantIdentifyingData const& snp, Genotypes const& genotypes, ResultCallback callback ) {
-			double const theta_mle = ( genotypes.col( 1 ).sum() + 2.0 * genotypes.col( 2 ).sum() ) / ( 2.0 * genotypes.sum() ) ;
-			double const theta_est = theta_mle ;
-			
-			Eigen::VectorXd const impute_fallback_distribution = Eigen::VectorXd::Zero( 3 ) ;
-			Eigen::VectorXd fallback_distribution = Eigen::VectorXd::Zero( 3 ) ;
-			fallback_distribution( 0 ) = ( 1 - theta_est ) * ( 1 - theta_est ) ;
-			fallback_distribution( 1 ) = 2.0 * theta_est * ( 1 - theta_est ) ;
-			fallback_distribution( 2 ) = theta_est * theta_est ;
-			
-			//std::cerr << "theta = " << theta_est << ", fallback_distribution = " << fallback_distribution.transpose() << ".\n" ;
-			
-			Eigen::VectorXd const levels = Eigen::VectorXd::LinSpaced( 3, 0, 2 ) ;
-
-			double const info = 1.0 - (
-				compute_sum_of_variances( levels, genotypes, fallback_distribution )
-				/ ( genotypes.rows() * 2.0 * theta_est * ( 1 - theta_est ) )
-			) ;
-
-			double const impute_info = 1.0 - (
-				compute_sum_of_variances( levels, genotypes, impute_fallback_distribution )
-				/ ( genotypes.sum() * 2.0 * theta_mle * ( 1 - theta_mle ) )
-			) ;
-		
-			callback( "info", info ) ;
-			callback( "impute_info", impute_info ) ;
-		}
-
-		void compute_sex_chromosome_info(
-			VariantIdentifyingData const& snp,
-			Genotypes const& genotypes,
-			Ploidy const& ploidy,
-			ResultCallback callback
-		) {
-			Eigen::MatrixXd hap_or_diploid( genotypes.rows(), 2 ) ;
-			for( std::size_t i = 0; i < ploidy.size(); ++i ) {
-				if( ploidy(i) == 1 ) {
-					hap_or_diploid(i,0) = 1 ;
-					hap_or_diploid(i,1) = 0 ;
-				}
-				else if( ploidy[ i ] == 2 ) {
-					hap_or_diploid(i,0) = 0 ;
-					hap_or_diploid(i,1) = 1 ;
-				}
-				else {
-					// Don't understand, so treat ploidy as missing.
-					// individuals with missing sex do not contribute to the computation.
-					// I think this is the least surprising thing to do.
-					hap_or_diploid(i,0) = 0 ;
-					hap_or_diploid(i,1) = 0 ;
-				}
-			}
-
-			double const a_allele_count_diploid = (
-					( genotypes.col( 1 ) + 2.0 * genotypes.col( 0 ) ).array() * ( hap_or_diploid.col(1).array() )
-				).sum() ;
-			double const b_allele_count_diploid = (
-					( genotypes.col( 1 ) + 2.0 * genotypes.col( 2 ) ).array() * ( hap_or_diploid.col(1).array() )
-				).sum() ;
-			double const a_allele_count_haploid = 	(
-					genotypes.col( 0 ).array() * hap_or_diploid.col(0).array() 
-				).sum() ;
-			double const b_allele_count_haploid = 	(
-					genotypes.col( 1 ).array() * hap_or_diploid.col(0).array() 
-				).sum() ;
-			
-			// MLE estimate of allele frequency
-			double const theta_mle = ( b_allele_count_diploid + b_allele_count_haploid )
-				/ ( a_allele_count_diploid + b_allele_count_diploid + a_allele_count_haploid + b_allele_count_haploid ) ;
-
-			// For the new info measure, could regularise by data augmentation, adding one allele of each type.
-			// This makes info better behaved at low frequencies.
-			// Note adding one of each allele constitutes minimal prior information that the variant is polymorphic.
-			// double const theta_est = ( b_allele_count_diploid + b_allele_count_haploid + 1 )
-			//	/ ( a_allele_count_diploid + b_allele_count_diploid + a_allele_count_haploid + b_allele_count_haploid + 2 ) ;
-			
-			// ...but don't actually do that; it is less conservative at rare SNPs.
-			double const theta_est = theta_mle ;
-
-			Eigen::VectorXd diploid_fallback_distribution = Eigen::VectorXd::Zero( 3 ) ;
-			diploid_fallback_distribution( 0 ) = ( 1 - theta_est ) * ( 1 - theta_est ) ;
-			diploid_fallback_distribution( 1 ) = 2.0 * theta_est * ( 1 - theta_est ) ;
-			diploid_fallback_distribution( 2 ) = theta_est * theta_est ;
-			
-			Eigen::VectorXd haploid_fallback_distribution = Eigen::VectorXd::Zero( 3 ) ;
-			haploid_fallback_distribution( 0 ) = 1 - theta_est ;
-			haploid_fallback_distribution( 1 ) = theta_est ;
-			
-			//std::cerr << "theta = " << theta_mle << ", fallback_distribution = " << fallback_distribution.transpose() << ".\n" ;
-			
-			Eigen::VectorXd const levels = Eigen::VectorXd::LinSpaced( 3, 0, 2 ) ;
-			
-			double info = 0.0 ;
-			Eigen::VectorXd const haploids = ( hap_or_diploid.col( 0 ).array() == 1 ).cast< double >() ;
-			Eigen::VectorXd const diploids = ( hap_or_diploid.col( 1 ).array() == 1 ).cast< double >() ;
-			{
-				if( haploids.sum() > 0 ) {
-					info -= compute_sum_of_variances( levels, genotypes, haploid_fallback_distribution, haploids )
-						/ ( theta_est * ( 1 - theta_est ) ) ;
-				}
-
-				if( diploids.sum() > 0 ) {
-					info -= compute_sum_of_variances( levels, genotypes, diploid_fallback_distribution, diploids )
-						/ ( 2.0 * theta_est * ( 1 - theta_est ) ) ;
-				}
-
-				double const totalProb = (
-					( genotypes.block( 0, 0, genotypes.rows(), 2 ).rowwise().sum().array() * haploids.array() ).sum()
-					+ ( genotypes.rowwise().sum().array() * diploids.array() ).sum() 
-				) ;
-
-				info = 1.0 + (info / (haploids.sum() + diploids.sum() )) ;
-			}
-			
-			{
-				// IMPUTE-style MLE, treat all samples as diploid ignoring gender.
-				// Haploids are encoded in the 0/1 columns here so we have to reverse-engineer the
-				// original info computation to allow for this.
-				double const autosomal_theta_mle = (
-					( 2.0 * genotypes.col( 1 ).array() * haploids.array() )
-					+ (( genotypes.col( 1 ) + 2.0 * genotypes.col( 2 ) ).array() * ( 1.0 - haploids.array() ))
-				).sum() / ( 2.0 * genotypes.sum() ) ;
-
-#if DEBUG
-				std::cerr << "autosomal_theta_mle  = " << std::setprecision(10) << autosomal_theta_mle << ".\n" ;
-				std::cerr << genotypes << ".\n" ;
-#endif
-				Eigen::VectorXd haploidLevels = Eigen::VectorXd::Zero(3) ;
-				haploidLevels(1) = 2 ;
-				double const impute_info = 1.0 - (
-					(
-						compute_sum_of_variances( haploidLevels, genotypes, Eigen::VectorXd::Zero( 3 ), haploids )
-						+ compute_sum_of_variances( levels, genotypes, Eigen::VectorXd::Zero( 3 ), 1.0 - haploids.array() )
-					) / ( genotypes.sum() * 2.0 * autosomal_theta_mle * ( 1 - autosomal_theta_mle ) )
-				) ;
-			
-				callback( "info", info ) ;
-				callback( "impute_info", impute_info ) ;
-			}
-		}
-
-		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const { return prefix + "InfoComputation" ; }
-		
-	private:
-		double compute_sum_of_variances( Eigen::VectorXd const& levels, Eigen::MatrixXd const& probabilities, Eigen::VectorXd const& fallback ) const {
-			return compute_sum_of_variances( levels, probabilities, fallback, Eigen::VectorXd::Constant( probabilities.rows(), 1 ) ) ;
-		}
-		
-		// treat the rows of the probabilities matrix as probabilities.
-		// distribution for individual i is taken as a mixture of the distribution given by row i of probabilities,
-		// and the fallback distribution if the sum of row i < 1, appropriately weighted.
-		// Only individuals with inclusion = 1 are used.
-		double compute_sum_of_variances( Eigen::VectorXd const& levels, Eigen::MatrixXd const& probabilities, Eigen::VectorXd const& fallback, Eigen::VectorXd const& inclusion ) const {
-			assert( levels.size() == fallback.size() ) ;
-			assert( levels.size() == probabilities.cols() ) ;
-			assert( inclusion.size() == probabilities.rows() ) ;
-			Eigen::VectorXd levels_squared = ( levels.array() * levels.array() ) ;
-
-			double result = 0.0 ;
-			for( int i = 0; i < probabilities.rows(); ++i ) {
-				if( inclusion( i ) == 1 ) {
-					double const c = probabilities.row( i ).sum() ;
-					result += compute_variance( levels, levels_squared, probabilities.row( i ).transpose() + ( 1 - c ) * fallback ) ;
-				}
-			}
-			return result ;
-		}
-		
-		double compute_variance( Eigen::VectorXd const& levels, Eigen::VectorXd const& levels_squared, Eigen::VectorXd const& probs ) const {
-			double const mean = ( probs.transpose() * levels )(0) ;
-			double const variance = ( probs.transpose() * levels_squared )(0) - ( mean * mean ) ;
-			// std::cerr << "compute_variance: levels = " << levels.transpose() << ", levels_squared = " << levels_squared.transpose() << ", probs = " << probs.transpose() << ", variance = " << variance << ".\n" ;
-			return variance ;
-		}
-	} ;
-}
-
-SNPSummaryComputation::UniquePtr SNPSummaryComputation::create(
-	std::string const& name
-) {
-	UniquePtr result ;
-	if( name == "allele-frequencies" ) { result.reset( new snp_summary_component::AlleleFrequencyComputation( "everything" )) ; }
-	else if( name == "allele-counts" ) { result.reset( new snp_summary_component::AlleleFrequencyComputation( "counts" )) ; }
-	else if( name == "HWE" ) { result.reset( new snp_summary_component::HWEComputation()) ; }
-	else if( name == "missingness" ) { result.reset( new snp_summary_component::MissingnessComputation()) ; }
-	else if( name == "info" ) { result.reset( new snp_summary_component::InfoComputation()) ; }
-	else if( name == "call-mass-proportion" ) { result.reset( new snp_summary_component::CallMassComputation()) ; }
-	else if( name == "intensity-stats" ) { result.reset( new snp_summary_component::IntensitySummaryComputation() ) ; }
-	else if( name == "multi-allele-counts" ) { result.reset( new snp_summary_component::AlleleCountComputation() ) ; }
-	else {
-		throw genfile::BadArgumentError( "SNPSummaryComputation::create()", "name=\"" + name + "\"" ) ;
-	}
-	return result ;
+	SNPSummaryComputation::UniquePtr SNPSummaryComputation::create(
+		std::string const& name
+	) {
+		UniquePtr result ;
+		if( name == "allele-frequencies" ) { result.reset( new stats::AlleleFrequencyComputation( "everything" )) ; }
+		else if( name == "allele-counts" ) { result.reset( new stats::AlleleFrequencyComputation( "counts" )) ; }
+		else if( name == "HWE" ) { result.reset( new stats::HWEComputation()) ; }
+		else if( name == "missingness" ) { result.reset( new stats::MissingnessComputation()) ; }
+		else if( name == "info" ) { result.reset( new stats::InfoComputation()) ; }
+		else if( name == "call-mass-proportion" ) { result.reset( new stats::CallMassComputation()) ; }
+		else if( name == "intensity-stats" ) { result.reset( new stats::IntensitySummaryComputation() ) ; }
+		else if( name == "multi-allele-counts" ) { result.reset( new stats::AlleleCountComputation() ) ; }
+		else {
+			throw genfile::BadArgumentError( "SNPSummaryComputation::create()", "name=\"" + name + "\"" ) ;
+		}
+		return result ;
+	}
 }

Index: components/SNPSummaryComponent/src/SNPSummaryComputationManager.cpp
==================================================================
--- components/SNPSummaryComponent/src/SNPSummaryComputationManager.cpp
+++ components/SNPSummaryComponent/src/SNPSummaryComputationManager.cpp
@@ -19,215 +19,217 @@
 #include "components/SNPSummaryComponent/SNPSummaryComputationManager.hpp"
 #include "components/SNPSummaryComponent/StratifyingSNPSummaryComputation.hpp"
 
 // #define DEBUG_SNP_SUMMARY_COMPUTATION_MANAGER 1
 
-SNPSummaryComputationManager::SNPSummaryComputationManager(
-	genfile::CohortIndividualSource const& samples,
-	std::string const& sex_column_name
-):
-	m_samples( samples ),
-	m_haploid_coding_column( -1 )
-{}
-
-std::vector< char > SNPSummaryComputationManager::get_sexes( genfile::CohortIndividualSource const& samples, std::string const& sex_column_name ) const {
-	std::vector< char > result( samples.get_number_of_individuals(), '.' ) ;
-	genfile::CohortIndividualSource::ColumnSpec column_spec = samples.get_column_spec() ;
-	if( column_spec.check_for_column( sex_column_name ) ) {
-		if( column_spec[ sex_column_name ].is_discrete() ) {
-			for( std::size_t i = 0; i < samples.get_number_of_individuals(); ++i ) {
-				genfile::CohortIndividualSource::Entry const entry = samples.get_entry( i, sex_column_name ) ;
-				if( !entry.is_missing() ) {
-					std::string const sex = genfile::string_utils::to_lower( entry.as< std::string >() ) ;
-					if( sex == "m" || sex == "male" || sex == "1" ) {
-						result[i] = 'm' ;
-					} else if( sex == "f" || sex == "female" || sex == "2" ) {
-						result[i] = 'f' ;
-					}
-					else {
-						throw genfile::MalformedInputError( samples.get_source_spec(), i+2, column_spec.find_column( sex_column_name )) ;
-					}
-				}
-			}
-		}
-		else {
-			std::cerr << "!! (SNPSummaryComputationManager::get_sexes): sex column found but it has the wrong type!\n" ;
-			throw genfile::MalformedInputError( samples.get_source_spec(), 1, column_spec.find_column( sex_column_name )) ;
-		}
-	}
-	return result ;
-}
-
-std::map< char, std::vector< int > > SNPSummaryComputationManager::get_samples_by_sex( std::vector< char > const& sexes ) const {
-	std::map< char, std::vector< int > > result ;
-	result[ 'm' ] ;
-	result[ 'f' ] ;
-	result[ '.' ] ;
-
-	for( std::size_t i = 0; i < sexes.size(); ++i ) {
-		result[ sexes[i] ].push_back( i ) ;
-	}
-
-	return result ;
-}
-
-void SNPSummaryComputationManager::add_computation( std::string const& name, SNPSummaryComputation::UniquePtr computation ) {
-	m_computations.insert( name, computation ) ;
-}
-
-void SNPSummaryComputationManager::add_result_callback( ResultCallback callback ) {
-	m_result_signal.connect( callback ) ;
-}
-
-void SNPSummaryComputationManager::add_per_sample_result_callback( PerSampleResultCallback callback ) {
-	m_per_sample_result_signal.connect( callback ) ;
-}
-
-void SNPSummaryComputationManager::set_haploid_genotype_coding( int coding ) {
-	assert( coding == 1 || coding == 2 ) ;
-	m_haploid_coding_column = coding ;	
-}
-
-void SNPSummaryComputationManager::begin_processing_snps( std::size_t number_of_samples, genfile::SNPDataSource::Metadata const& ) {
-	m_snp_index = 0 ;
-	m_genotypes.resize( number_of_samples, 3 ) ;
-	Computations::iterator i = m_computations.begin(), end_i = m_computations.end() ;
-	for( ; i != end_i; ++i ) {
-		i->second->begin_processing_snps( number_of_samples ) ;
-	}
-}
-
-namespace {
-	struct GPSetter: public genfile::VariantDataReader::PerSampleSetter {
-		~GPSetter() throw() {}
-		GPSetter(
-			Eigen::MatrixXd* genotypes,
-			SNPSummaryComputation::Ploidy* ploidy
-		):
-			m_genotypes( genotypes ),
-			m_ploidy( ploidy ),
-			m_sample_i( 0 )
-		{
-			assert( genotypes != 0 ) ;
-			assert( ploidy != 0 ) ;
-		}
-
-		void initialise( std::size_t number_of_samples, std::size_t number_of_alleles ) {
-#if DEBUG_PER_VARIANT_COMPUTATION_MANAGER
-			std::cerr << "GPSetter::initialise( " << number_of_samples << ", " << number_of_alleles << " ).\n" ;
-#endif
-			// assume at most diploidy, max entries is number of alleles choose 2.
-			m_genotypes->resize( number_of_samples, number_of_alleles * (number_of_alleles+1)/2 ) ;
-			m_genotypes->setZero() ;
-			m_ploidy->resize( number_of_samples ) ;
-			m_ploidy->setConstant( -1 ) ;
-			m_sample_i = 0 ;
-			m_max_ploidy = 0 ;
-			m_min_ploidy = std::numeric_limits< uint32_t >::max() ;
-		}
-
-		bool set_sample( std::size_t i ) {
-			m_sample_i = i ;
-			return true ;
-		}
-		
-		void set_number_of_entries( uint32_t ploidy, std::size_t n, OrderType const order_type, ValueType const value_type ) {
-			assert( order_type == genfile::ePerUnorderedGenotype ) ;
-			assert( value_type == genfile::eProbability ) ;
-			(*m_ploidy)( m_sample_i ) = ploidy ;
-			m_min_ploidy = std::min( ploidy, m_min_ploidy ) ;
-			m_max_ploidy = std::max( ploidy, m_max_ploidy ) ;
-		}
-		
-		void set_value( std::size_t value_i, genfile::MissingValue const value ) {
-			// GEnotypes already set to 0, nothing to do.
-		}
-
-		void set_value( std::size_t value_i, double const value ) {
-#if DEBUG_PER_VARIANT_COMPUTATION_MANAGER
-			std::cerr << "GPSetter::set_value( " << value_i << ", " << value << " ).\n" ;
-			std::cerr << "GPSetter: m_ploidy[" << m_sample_i << "] = " << m_ploidy[ m_sample_i ] << ".\n" ;
-#endif
-			assert( value_i < m_genotypes->cols() ) ;
-			(*m_genotypes)( m_sample_i, value_i ) = value ;
-		}
-
-		void finalise() {}
-
-		uint32_t max_ploidy() const { return m_max_ploidy ; }
-		uint32_t min_ploidy() const { return m_min_ploidy ; }
-
-	private:
-		Eigen::MatrixXd* m_genotypes ;
-		SNPSummaryComputation::Ploidy* m_ploidy ;
-		int m_sample_i ;
-		uint32_t m_max_ploidy ;
-		uint32_t m_min_ploidy ;
-	} ;
-}
-
-void SNPSummaryComputationManager::processed_snp(
-	genfile::VariantIdentifyingData const& snp,
-	genfile::VariantDataReader& data_reader
-) {
-	try {
-		GPSetter setter( &m_genotypes, &m_ploidy ) ;
-		data_reader.get( ":genotypes:", genfile::to_GP_unphased( setter )) ;
-
-#if DEBUG_SNP_SUMMARY_COMPUTATION_MANAGER
-		std::cerr << "SNPSummaryComputationManager::processed_snp(): ploidy = " << m_ploidy.transpose() << "...\n" ;
-#endif
-
-		boost::function< void ( std::string const& value_name, genfile::VariantEntry const& value ) > callback
-			= boost::bind( boost::ref( m_result_signal ), snp, _1, _2 ) ;
-
-		Computations::iterator i = m_computations.begin(), end_i = m_computations.end() ;
-		for( ; i != end_i; ++i ) {
-			i->second->operator()(
-				snp,
-				m_genotypes,
-				m_ploidy,
-				data_reader,
-				callback
-			) ;
-		}
-
-		if( snp.number_of_alleles() != 2 ) {
-			m_result_signal( snp, "comment", "non-biallelic" ) ;
-		}
-	}
-	catch( genfile::MalformedInputError const& e ) {
-		m_result_signal( snp, "comment", "!! Error reading data for variant " + genfile::string_utils::to_string( snp ) + ": " + e.format_message() ) ;
-	}
-	++m_snp_index ;
-}
-
-void SNPSummaryComputationManager::end_processing_snps() {
-	Computations::iterator i = m_computations.begin(), end_i = m_computations.end() ;
-	for( ; i != end_i; ++i ) {
-		i->second->end_processing_snps(
-			boost::bind( boost::ref( m_per_sample_result_signal ), _1, _2, _3 )
-		) ;
-	}
-}
-
-void SNPSummaryComputationManager::stratify_by( StrataMembers const& strata, std::string const& stratification_name ) {
-	Computations::iterator computation_i = m_computations.begin(), end_computations = m_computations.end() ;
-	for( ; computation_i != end_computations; ) {
-		Computations::iterator this_computation_i = computation_i++ ;
-		std::string const this_name = this_computation_i->first ;
-		SNPSummaryComputation::UniquePtr computation( m_computations.release( this_computation_i ).release() ) ;
-		m_computations.insert(
-			this_name,
-			SNPSummaryComputation::UniquePtr( new StratifyingSNPSummaryComputation( computation, stratification_name, strata ))
-		) ;
-	}
-}
-
-std::string SNPSummaryComputationManager::get_summary( std::string const& prefix, std::size_t column_width ) {
-	std::string result ;
-	Computations::const_iterator i = m_computations.begin(), end_i = m_computations.end() ;
-	for( ; i != end_i; ++i ) {
-		result += i->second->get_summary( prefix, column_width ) + "\n";
-	}
-	return result ;
+namespace stats {
+	SNPSummaryComputationManager::SNPSummaryComputationManager(
+		genfile::CohortIndividualSource const& samples,
+		std::string const& sex_column_name
+	):
+		m_samples( samples ),
+		m_haploid_coding_column( -1 )
+	{}
+
+	std::vector< char > SNPSummaryComputationManager::get_sexes( genfile::CohortIndividualSource const& samples, std::string const& sex_column_name ) const {
+		std::vector< char > result( samples.get_number_of_individuals(), '.' ) ;
+		genfile::CohortIndividualSource::ColumnSpec column_spec = samples.get_column_spec() ;
+		if( column_spec.check_for_column( sex_column_name ) ) {
+			if( column_spec[ sex_column_name ].is_discrete() ) {
+				for( std::size_t i = 0; i < samples.get_number_of_individuals(); ++i ) {
+					genfile::CohortIndividualSource::Entry const entry = samples.get_entry( i, sex_column_name ) ;
+					if( !entry.is_missing() ) {
+						std::string const sex = genfile::string_utils::to_lower( entry.as< std::string >() ) ;
+						if( sex == "m" || sex == "male" || sex == "1" ) {
+							result[i] = 'm' ;
+						} else if( sex == "f" || sex == "female" || sex == "2" ) {
+							result[i] = 'f' ;
+						}
+						else {
+							throw genfile::MalformedInputError( samples.get_source_spec(), i+2, column_spec.find_column( sex_column_name )) ;
+						}
+					}
+				}
+			}
+			else {
+				std::cerr << "!! (SNPSummaryComputationManager::get_sexes): sex column found but it has the wrong type!\n" ;
+				throw genfile::MalformedInputError( samples.get_source_spec(), 1, column_spec.find_column( sex_column_name )) ;
+			}
+		}
+		return result ;
+	}
+
+	std::map< char, std::vector< int > > SNPSummaryComputationManager::get_samples_by_sex( std::vector< char > const& sexes ) const {
+		std::map< char, std::vector< int > > result ;
+		result[ 'm' ] ;
+		result[ 'f' ] ;
+		result[ '.' ] ;
+
+		for( std::size_t i = 0; i < sexes.size(); ++i ) {
+			result[ sexes[i] ].push_back( i ) ;
+		}
+
+		return result ;
+	}
+
+	void SNPSummaryComputationManager::add_computation( std::string const& name, SNPSummaryComputation::UniquePtr computation ) {
+		m_computations.insert( name, computation ) ;
+	}
+
+	void SNPSummaryComputationManager::add_result_callback( ResultCallback callback ) {
+		m_result_signal.connect( callback ) ;
+	}
+
+	void SNPSummaryComputationManager::add_per_sample_result_callback( PerSampleResultCallback callback ) {
+		m_per_sample_result_signal.connect( callback ) ;
+	}
+
+	void SNPSummaryComputationManager::set_haploid_genotype_coding( int coding ) {
+		assert( coding == 1 || coding == 2 ) ;
+		m_haploid_coding_column = coding ;	
+	}
+
+	void SNPSummaryComputationManager::begin_processing_snps( std::size_t number_of_samples, genfile::SNPDataSource::Metadata const& ) {
+		m_snp_index = 0 ;
+		m_genotypes.resize( number_of_samples, 3 ) ;
+		Computations::iterator i = m_computations.begin(), end_i = m_computations.end() ;
+		for( ; i != end_i; ++i ) {
+			i->second->begin_processing_snps( number_of_samples ) ;
+		}
+	}
+
+	namespace {
+		struct GPSetter: public genfile::VariantDataReader::PerSampleSetter {
+			~GPSetter() throw() {}
+			GPSetter(
+				Eigen::MatrixXd* genotypes,
+				SNPSummaryComputation::Ploidy* ploidy
+			):
+				m_genotypes( genotypes ),
+				m_ploidy( ploidy ),
+				m_sample_i( 0 )
+			{
+				assert( genotypes != 0 ) ;
+				assert( ploidy != 0 ) ;
+			}
+
+			void initialise( std::size_t number_of_samples, std::size_t number_of_alleles ) {
+	#if DEBUG_PER_VARIANT_COMPUTATION_MANAGER
+				std::cerr << "GPSetter::initialise( " << number_of_samples << ", " << number_of_alleles << " ).\n" ;
+	#endif
+				// assume at most diploidy, max entries is number of alleles choose 2.
+				m_genotypes->resize( number_of_samples, number_of_alleles * (number_of_alleles+1)/2 ) ;
+				m_genotypes->setZero() ;
+				m_ploidy->resize( number_of_samples ) ;
+				m_ploidy->setConstant( -1 ) ;
+				m_sample_i = 0 ;
+				m_max_ploidy = 0 ;
+				m_min_ploidy = std::numeric_limits< uint32_t >::max() ;
+			}
+
+			bool set_sample( std::size_t i ) {
+				m_sample_i = i ;
+				return true ;
+			}
+		
+			void set_number_of_entries( uint32_t ploidy, std::size_t n, OrderType const order_type, ValueType const value_type ) {
+				assert( order_type == genfile::ePerUnorderedGenotype ) ;
+				assert( value_type == genfile::eProbability ) ;
+				(*m_ploidy)( m_sample_i ) = ploidy ;
+				m_min_ploidy = std::min( ploidy, m_min_ploidy ) ;
+				m_max_ploidy = std::max( ploidy, m_max_ploidy ) ;
+			}
+		
+			void set_value( std::size_t value_i, genfile::MissingValue const value ) {
+				// GEnotypes already set to 0, nothing to do.
+			}
+
+			void set_value( std::size_t value_i, double const value ) {
+	#if DEBUG_PER_VARIANT_COMPUTATION_MANAGER
+				std::cerr << "GPSetter::set_value( " << value_i << ", " << value << " ).\n" ;
+				std::cerr << "GPSetter: m_ploidy[" << m_sample_i << "] = " << m_ploidy[ m_sample_i ] << ".\n" ;
+	#endif
+				assert( value_i < m_genotypes->cols() ) ;
+				(*m_genotypes)( m_sample_i, value_i ) = value ;
+			}
+
+			void finalise() {}
+
+			uint32_t max_ploidy() const { return m_max_ploidy ; }
+			uint32_t min_ploidy() const { return m_min_ploidy ; }
+
+		private:
+			Eigen::MatrixXd* m_genotypes ;
+			SNPSummaryComputation::Ploidy* m_ploidy ;
+			int m_sample_i ;
+			uint32_t m_max_ploidy ;
+			uint32_t m_min_ploidy ;
+		} ;
+	}
+
+	void SNPSummaryComputationManager::processed_snp(
+		genfile::VariantIdentifyingData const& snp,
+		genfile::VariantDataReader& data_reader
+	) {
+		try {
+			GPSetter setter( &m_genotypes, &m_ploidy ) ;
+			data_reader.get( ":genotypes:", genfile::to_GP_unphased( setter )) ;
+
+	#if DEBUG_SNP_SUMMARY_COMPUTATION_MANAGER
+			std::cerr << "SNPSummaryComputationManager::processed_snp(): ploidy = " << m_ploidy.transpose() << "...\n" ;
+	#endif
+
+			boost::function< void ( std::string const& value_name, genfile::VariantEntry const& value ) > callback
+				= boost::bind( boost::ref( m_result_signal ), snp, _1, _2 ) ;
+
+			Computations::iterator i = m_computations.begin(), end_i = m_computations.end() ;
+			for( ; i != end_i; ++i ) {
+				i->second->operator()(
+					snp,
+					m_genotypes,
+					m_ploidy,
+					data_reader,
+					callback
+				) ;
+			}
+
+			if( snp.number_of_alleles() != 2 ) {
+				m_result_signal( snp, "comment", "non-biallelic" ) ;
+			}
+		}
+		catch( genfile::MalformedInputError const& e ) {
+			m_result_signal( snp, "comment", "!! Error reading data for variant " + genfile::string_utils::to_string( snp ) + ": " + e.format_message() ) ;
+		}
+		++m_snp_index ;
+	}
+
+	void SNPSummaryComputationManager::end_processing_snps() {
+		Computations::iterator i = m_computations.begin(), end_i = m_computations.end() ;
+		for( ; i != end_i; ++i ) {
+			i->second->end_processing_snps(
+				boost::bind( boost::ref( m_per_sample_result_signal ), _1, _2, _3 )
+			) ;
+		}
+	}
+
+	void SNPSummaryComputationManager::stratify_by( StrataMembers const& strata, std::string const& stratification_name ) {
+		Computations::iterator computation_i = m_computations.begin(), end_computations = m_computations.end() ;
+		for( ; computation_i != end_computations; ) {
+			Computations::iterator this_computation_i = computation_i++ ;
+			std::string const this_name = this_computation_i->first ;
+			SNPSummaryComputation::UniquePtr computation( m_computations.release( this_computation_i ).release() ) ;
+			m_computations.insert(
+				this_name,
+				SNPSummaryComputation::UniquePtr( new StratifyingSNPSummaryComputation( computation, stratification_name, strata ))
+			) ;
+		}
+	}
+
+	std::string SNPSummaryComputationManager::get_summary( std::string const& prefix, std::size_t column_width ) {
+		std::string result ;
+		Computations::const_iterator i = m_computations.begin(), end_i = m_computations.end() ;
+		for( ; i != end_i; ++i ) {
+			result += i->second->get_summary( prefix, column_width ) + "\n";
+		}
+		return result ;
+	}
 }

Index: components/SNPSummaryComponent/src/SequenceAnnotation.cpp
==================================================================
--- components/SNPSummaryComponent/src/SequenceAnnotation.cpp
+++ components/SNPSummaryComponent/src/SequenceAnnotation.cpp
@@ -14,78 +14,80 @@
 #include "genfile/Error.hpp"
 #include "genfile/string_utils/slice.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "components/SNPSummaryComponent/SequenceAnnotation.hpp"
 
-SequenceAnnotation::SequenceAnnotation( std::string const& annotation_name, std::string const& fasta_filename, ProgressCallback callback ):
-	m_annotation_name( annotation_name ),
-	m_fasta_filename( fasta_filename ),
-	m_filenames( genfile::wildcard::find_files_by_chromosome( fasta_filename ) ),
-	m_sequence( fasta_filename, callback ),
-	m_flanking( std::make_pair( 0, 0 ))
-{}
-
-std::string SequenceAnnotation::get_summary( std::string const& prefix, std::size_t column_width ) const {
-	using genfile::string_utils::to_string ;
-	std::string result = prefix + "SequenceAnnotation: loaded " + m_annotation_name + " sequence:\n"
-		+ m_sequence.get_summary( prefix + "  ", column_width ) ;
-	return result ;
-}
-
-void SequenceAnnotation::set_flanking( std::size_t left, std::size_t right ) {
-	m_flanking.first = left ;
-	m_flanking.second = right ;
-}
-
-void SequenceAnnotation::operator()( VariantIdentifyingData const& snp, Genotypes const& genotypes, Ploidy const&, genfile::VariantDataReader&, ResultCallback callback ) {
-	using namespace genfile::string_utils ;
-	std::deque< char > flankingSequence ;
-	std::size_t const first_allele_size = snp.get_allele(0).size() ;
-	std::size_t const second_allele_size = snp.get_allele(1).size() ;
-	try {
-		bool match = false ;
-		m_sequence.get_sequence(
-			snp.get_position().chromosome(),
-			snp.get_position().position() - m_flanking.first,
-			snp.get_position().position() + first_allele_size + m_flanking.second,
-			&flankingSequence
-		) ;
-		assert( flankingSequence.size() == m_flanking.first + m_flanking.second + first_allele_size ) ;
-		std::string const reference_allele( flankingSequence.begin() + m_flanking.first, flankingSequence.begin() + m_flanking.first + first_allele_size ) ;
-		callback( m_annotation_name + "_" + "alleleA", reference_allele ) ;
-		if( m_flanking.first > 0 ) {
-			callback( m_annotation_name + "_" + "left_flanking", std::string( flankingSequence.begin(), flankingSequence.begin() + m_flanking.first ) ) ;
-		}
-		if( m_flanking.second > 0 ) {
-			callback( m_annotation_name + "_" + "right_flanking", std::string( flankingSequence.begin() + m_flanking.first + first_allele_size, flankingSequence.end() ) ) ;
-		}
-
-		if( to_upper( reference_allele ) == to_upper( snp.get_allele(0) ) ) {
-			match = true ;
-		}
-		
-		if( first_allele_size == second_allele_size ) {
-			if( to_upper( reference_allele ) == to_upper( snp.get_allele(1) ) ) {
-				match = true ;
-			}
-			callback( m_annotation_name + "_" + "alleleB_if_indel", genfile::MissingValue() ) ;
-			if( m_flanking.second > 0 ) {
-				callback( m_annotation_name + "_" + "alleleB_right_flanking_if_indel", genfile::MissingValue() ) ;
-			}
-		} else {
-			m_sequence.get_sequence( snp.get_position().chromosome(), snp.get_position().position() - m_flanking.first, snp.get_position().position() + second_allele_size + m_flanking.second, &flankingSequence ) ;
-			assert( flankingSequence.size() == m_flanking.first + m_flanking.second + second_allele_size ) ;
-			std::string const second_reference_allele( flankingSequence.begin() + m_flanking.first, flankingSequence.begin() + m_flanking.first + second_allele_size ) ;
-			callback( m_annotation_name + "_" + "alleleB_if_indel", second_reference_allele ) ;
-			if( m_flanking.second > 0 ) {
-				callback( m_annotation_name + "_" + "alleleB_right_flanking_if_indel", std::string( flankingSequence.begin() + m_flanking.first + second_allele_size, flankingSequence.end() ) ) ;
-			}
-
-			if( to_upper( second_reference_allele ) == to_upper( snp.get_allele(1) ) ) {
-				match = true ;
-			}
-		}
-	}
-	catch( genfile::BadArgumentError const& e ) {
-		// nowt to do.
+namespace stats {
+	SequenceAnnotation::SequenceAnnotation( std::string const& annotation_name, std::string const& fasta_filename, ProgressCallback callback ):
+		m_annotation_name( annotation_name ),
+		m_fasta_filename( fasta_filename ),
+		m_filenames( genfile::wildcard::find_files_by_chromosome( fasta_filename ) ),
+		m_sequence( fasta_filename, callback ),
+		m_flanking( std::make_pair( 0, 0 ))
+	{}
+
+	std::string SequenceAnnotation::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		using genfile::string_utils::to_string ;
+		std::string result = prefix + "SequenceAnnotation: loaded " + m_annotation_name + " sequence:\n"
+			+ m_sequence.get_summary( prefix + "  ", column_width ) ;
+		return result ;
+	}
+
+	void SequenceAnnotation::set_flanking( std::size_t left, std::size_t right ) {
+		m_flanking.first = left ;
+		m_flanking.second = right ;
+	}
+
+	void SequenceAnnotation::operator()( VariantIdentifyingData const& snp, Genotypes const& genotypes, Ploidy const&, genfile::VariantDataReader&, ResultCallback callback ) {
+		using namespace genfile::string_utils ;
+		std::deque< char > flankingSequence ;
+		std::size_t const first_allele_size = snp.get_allele(0).size() ;
+		std::size_t const second_allele_size = snp.get_allele(1).size() ;
+		try {
+			bool match = false ;
+			m_sequence.get_sequence(
+				snp.get_position().chromosome(),
+				snp.get_position().position() - m_flanking.first,
+				snp.get_position().position() + first_allele_size + m_flanking.second,
+				&flankingSequence
+			) ;
+			assert( flankingSequence.size() == m_flanking.first + m_flanking.second + first_allele_size ) ;
+			std::string const reference_allele( flankingSequence.begin() + m_flanking.first, flankingSequence.begin() + m_flanking.first + first_allele_size ) ;
+			callback( m_annotation_name + "_" + "alleleA", reference_allele ) ;
+			if( m_flanking.first > 0 ) {
+				callback( m_annotation_name + "_" + "left_flanking", std::string( flankingSequence.begin(), flankingSequence.begin() + m_flanking.first ) ) ;
+			}
+			if( m_flanking.second > 0 ) {
+				callback( m_annotation_name + "_" + "right_flanking", std::string( flankingSequence.begin() + m_flanking.first + first_allele_size, flankingSequence.end() ) ) ;
+			}
+
+			if( to_upper( reference_allele ) == to_upper( snp.get_allele(0) ) ) {
+				match = true ;
+			}
+		
+			if( first_allele_size == second_allele_size ) {
+				if( to_upper( reference_allele ) == to_upper( snp.get_allele(1) ) ) {
+					match = true ;
+				}
+				callback( m_annotation_name + "_" + "alleleB_if_indel", genfile::MissingValue() ) ;
+				if( m_flanking.second > 0 ) {
+					callback( m_annotation_name + "_" + "alleleB_right_flanking_if_indel", genfile::MissingValue() ) ;
+				}
+			} else {
+				m_sequence.get_sequence( snp.get_position().chromosome(), snp.get_position().position() - m_flanking.first, snp.get_position().position() + second_allele_size + m_flanking.second, &flankingSequence ) ;
+				assert( flankingSequence.size() == m_flanking.first + m_flanking.second + second_allele_size ) ;
+				std::string const second_reference_allele( flankingSequence.begin() + m_flanking.first, flankingSequence.begin() + m_flanking.first + second_allele_size ) ;
+				callback( m_annotation_name + "_" + "alleleB_if_indel", second_reference_allele ) ;
+				if( m_flanking.second > 0 ) {
+					callback( m_annotation_name + "_" + "alleleB_right_flanking_if_indel", std::string( flankingSequence.begin() + m_flanking.first + second_allele_size, flankingSequence.end() ) ) ;
+				}
+
+				if( to_upper( second_reference_allele ) == to_upper( snp.get_allele(1) ) ) {
+					match = true ;
+				}
+			}
+		}
+		catch( genfile::BadArgumentError const& e ) {
+			// nowt to do.
+		}
 	}
 }

Index: components/SNPSummaryComponent/src/StratifyingSNPSummaryComputation.cpp
==================================================================
--- components/SNPSummaryComponent/src/StratifyingSNPSummaryComputation.cpp
+++ components/SNPSummaryComponent/src/StratifyingSNPSummaryComputation.cpp
@@ -6,76 +6,77 @@
 
 #include <string>
 #include <map>
 #include "genfile/CohortIndividualSource.hpp"
 #include "components/SNPSummaryComponent/StratifyingSNPSummaryComputation.hpp"
-                                                       
-StratifyingSNPSummaryComputation::StratifyingSNPSummaryComputation( SNPSummaryComputation::UniquePtr computation, std::string const& stratification_name, StrataMembers const& strata_members ):
- 	m_computation( computation ),
-	m_stratification_name( stratification_name ),
-	m_strata_members( strata_members )
-{}
-
-namespace impl {
-	struct NameMungingSNPComputationCallback {
-		NameMungingSNPComputationCallback( SNPSummaryComputation::ResultCallback callback, std::string const& prefix, std::string const& suffix ):
-			m_callback( callback ),
-			m_prefix( prefix ),
-			m_suffix( suffix )
-		{
-			assert( m_callback ) ;
-		}
-
-		NameMungingSNPComputationCallback( NameMungingSNPComputationCallback const& other ):
-			m_callback( other.m_callback ),
-			m_prefix( other.m_prefix ),
-			m_suffix( other.m_suffix )
-		{}
-
-		NameMungingSNPComputationCallback& operator=( NameMungingSNPComputationCallback const& other ) {
-			m_callback = other.m_callback ;
-			m_prefix = other.m_prefix ;
-			m_suffix = other.m_suffix ;
-			return *this ;
-		}
-		
-		void operator()( std::string const& value_name, genfile::VariantEntry const& value ) const {
-			m_callback( m_prefix + value_name + m_suffix, value ) ;
-		}
-		
-	private:
-		SNPSummaryComputation::ResultCallback m_callback ;
-		std::string m_prefix ;
-		std::string m_suffix ;
-	} ;
-}
-
-void StratifyingSNPSummaryComputation::operator()(
-	VariantIdentifyingData const& snp,
-	Genotypes const& genotypes,
-	Ploidy const& ploidy,
-	genfile::VariantDataReader& data_reader,
-	ResultCallback callback
-) {
-	for( StrataMembers::const_iterator strata_i = m_strata_members.begin(); strata_i != m_strata_members.end(); ++strata_i ) {
-		std::vector< int > const& members = strata_i->second ;
-		Genotypes strata_genotypes = Genotypes::Constant( members.size(), genotypes.cols(), 0 ) ;
-		Ploidy strata_ploidy = Ploidy::Zero( members.size() ) ;
-		for( std::size_t i = 0; i < members.size(); ++i ) {
-			strata_genotypes.row( i ) = genotypes.row( members[i] ) ;
-			strata_ploidy(i) = ploidy( members[i] ) ;
-		}
-		
-		m_computation->operator()(
-			snp,
-			strata_genotypes,
-			strata_ploidy,
-			data_reader,
-			impl::NameMungingSNPComputationCallback( callback, "", "[" + m_stratification_name + "=" + genfile::string_utils::to_string( strata_i->first ) + "]" )
-		) ;
-	}
-}
-
-std::string StratifyingSNPSummaryComputation::get_summary( std::string const& prefix, std::size_t column_width ) const {
-	return m_computation->get_summary( prefix, column_width ) + ", stratified on \"" + m_stratification_name + "\"." ;
-}
-
+
+namespace stats {
+	StratifyingSNPSummaryComputation::StratifyingSNPSummaryComputation( SNPSummaryComputation::UniquePtr computation, std::string const& stratification_name, StrataMembers const& strata_members ):
+	 	m_computation( computation ),
+		m_stratification_name( stratification_name ),
+		m_strata_members( strata_members )
+	{}
+
+	namespace impl {
+		struct NameMungingSNPComputationCallback {
+			NameMungingSNPComputationCallback( SNPSummaryComputation::ResultCallback callback, std::string const& prefix, std::string const& suffix ):
+				m_callback( callback ),
+				m_prefix( prefix ),
+				m_suffix( suffix )
+			{
+				assert( m_callback ) ;
+			}
+
+			NameMungingSNPComputationCallback( NameMungingSNPComputationCallback const& other ):
+				m_callback( other.m_callback ),
+				m_prefix( other.m_prefix ),
+				m_suffix( other.m_suffix )
+			{}
+
+			NameMungingSNPComputationCallback& operator=( NameMungingSNPComputationCallback const& other ) {
+				m_callback = other.m_callback ;
+				m_prefix = other.m_prefix ;
+				m_suffix = other.m_suffix ;
+				return *this ;
+			}
+		
+			void operator()( std::string const& value_name, genfile::VariantEntry const& value ) const {
+				m_callback( m_prefix + value_name + m_suffix, value ) ;
+			}
+		
+		private:
+			SNPSummaryComputation::ResultCallback m_callback ;
+			std::string m_prefix ;
+			std::string m_suffix ;
+		} ;
+	}
+
+	void StratifyingSNPSummaryComputation::operator()(
+		VariantIdentifyingData const& snp,
+		Genotypes const& genotypes,
+		Ploidy const& ploidy,
+		genfile::VariantDataReader& data_reader,
+		ResultCallback callback
+	) {
+		for( StrataMembers::const_iterator strata_i = m_strata_members.begin(); strata_i != m_strata_members.end(); ++strata_i ) {
+			std::vector< int > const& members = strata_i->second ;
+			Genotypes strata_genotypes = Genotypes::Constant( members.size(), genotypes.cols(), 0 ) ;
+			Ploidy strata_ploidy = Ploidy::Zero( members.size() ) ;
+			for( std::size_t i = 0; i < members.size(); ++i ) {
+				strata_genotypes.row( i ) = genotypes.row( members[i] ) ;
+				strata_ploidy(i) = ploidy( members[i] ) ;
+			}
+		
+			m_computation->operator()(
+				snp,
+				strata_genotypes,
+				strata_ploidy,
+				data_reader,
+				impl::NameMungingSNPComputationCallback( callback, "", "[" + m_stratification_name + "=" + genfile::string_utils::to_string( strata_i->first ) + "]" )
+			) ;
+		}
+	}
+
+	std::string StratifyingSNPSummaryComputation::get_summary( std::string const& prefix, std::size_t column_width ) const {
+		return m_computation->get_summary( prefix, column_width ) + ", stratified on \"" + m_stratification_name + "\"." ;
+	}
+}

Index: components/SNPSummaryComponent/wscript
==================================================================
--- components/SNPSummaryComponent/wscript
+++ components/SNPSummaryComponent/wscript
@@ -1,37 +1,11 @@
-import os.path
-import glob
-#import UnitTest
-
 def configure( conf ):
 	pass
-
-def create_tests( bld ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'test_snp_summary_component',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'genfile boost-unit_test_framework',
-		uselib = 'BOOST BOOST_SYSTEM BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
 
 def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
+	bld.stlib(
 		target = 'SNPSummaryComponent',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = 'ZLIB BOOST BOOST_IOSTREAMS BOOST_SYSTEM BOOST_FILESYSTEM',
-		uselib_local = 'eigen db statfile integration appcontext qcdb genfile metro boost',
-		export_incdirs = './include'
-	)
-
-	#create_tests( bld )
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		use = 'eigen statfile integration appcontext genfile qcdb metro boost ZLIB',
+		includes = './include',
+		export_includes = './include'
+	)

Index: components/SampleSummaryComponent/include/components/SampleSummaryComponent/FlatTableDBOutputter.hpp
==================================================================
--- components/SampleSummaryComponent/include/components/SampleSummaryComponent/FlatTableDBOutputter.hpp
+++ components/SampleSummaryComponent/include/components/SampleSummaryComponent/FlatTableDBOutputter.hpp
@@ -14,12 +14,12 @@
 #include <boost/tuple/tuple.hpp>
 #include <boost/bimap.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/CohortIndividualSource.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "qcdb/DBOutputter.hpp"
 #include "components/SampleSummaryComponent/SampleStorage.hpp"
 #include "qcdb/StorageOptions.hpp"
 
 namespace sample_stats {
@@ -31,28 +31,28 @@
 			std::string const& filename,
 			std::string const& analysis_name,
 			std::string const& analysis_description,
 			qcdb::DBOutputter::Metadata const& metadata,
 			genfile::CohortIndividualSource const& samples,
-			boost::optional< db::Connection::RowId > analysis_id
+			boost::optional< genfile::db::Connection::RowId > analysis_id
 		) ;
 		static SharedPtr create_shared(
 			std::string const& filename,
 			std::string const& analysis_name,
 			std::string const& analysis_description,
 			qcdb::DBOutputter::Metadata const& metadata,
 			genfile::CohortIndividualSource const& samples,
-			boost::optional< db::Connection::RowId > analysis_id
+			boost::optional< genfile::db::Connection::RowId > analysis_id
 		) ;
 
 		FlatTableDBOutputter(
 			std::string const& filename,
 			std::string const& analysis_name,
 			std::string const& analysis_description,
 			qcdb::DBOutputter::Metadata const& metadata,
 			genfile::CohortIndividualSource const& samples,
-			boost::optional< db::Connection::RowId > analysis_id
+			boost::optional< genfile::db::Connection::RowId > analysis_id
 		) ;
 		~FlatTableDBOutputter() ;
 
 		void store_per_sample_data(
 			std::string const& computation_name,
@@ -71,14 +71,14 @@
 		AnalysisId analysis_id() const ;
 
 	private:
 		qcdb::DBOutputter m_outputter ;
 		std::string m_table_name ;
-		db::Connection::RowId m_variable_id ;
-		db::Connection::StatementPtr m_find_sample_statement ;
-		db::Connection::StatementPtr m_insert_sample_statement ;
-		db::Connection::StatementPtr m_insert_data_sql ;
+		genfile::db::Connection::RowId m_variable_id ;
+		genfile::db::Connection::StatementPtr m_find_sample_statement ;
+		genfile::db::Connection::StatementPtr m_insert_sample_statement ;
+		genfile::db::Connection::StatementPtr m_insert_data_sql ;
 
 		std::vector< genfile::VariantEntry > m_sample_ids ;
 		typedef std::vector< boost::tuple< std::string, std::size_t, std::string, std::string, genfile::VariantEntry > > Data ;
 		Data m_data ;
 
@@ -91,12 +91,12 @@
 		VariableMap::left_const_iterator add_variable_impl( std::string const& ) ;
 		void create_schema() ;
 		void create_variables() ;
 		void construct_statements() ;
 		void store_samples( genfile::CohortIndividualSource const& samples ) ;
-		db::Connection::RowId get_or_create_sample( genfile::VariantEntry const& identifier, std::size_t index ) const ;
+		genfile::db::Connection::RowId get_or_create_sample( genfile::VariantEntry const& identifier, std::size_t index ) const ;
 		void store_block() ;
-		void store_data_for_sample( db::Connection::RowId analysis_id, std::size_t sample_index, genfile::VariantEntry const& sample_id ) ;
+		void store_data_for_sample( genfile::db::Connection::RowId analysis_id, std::size_t sample_index, genfile::VariantEntry const& sample_id ) ;
 	} ;
 }
 
 #endif

Index: components/SampleSummaryComponent/src/FlatTableDBOutputter.cpp
==================================================================
--- components/SampleSummaryComponent/src/FlatTableDBOutputter.cpp
+++ components/SampleSummaryComponent/src/FlatTableDBOutputter.cpp
@@ -10,12 +10,12 @@
 #include <boost/tuple/tuple.hpp>
 #include <boost/thread/thread.hpp>
 #include "genfile/VariantEntry.hpp"
 #include "genfile/Error.hpp"
 #include "genfile/string_utils.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "components/SampleSummaryComponent/FlatTableDBOutputter.hpp"
 #include "qcdb/DBOutputter.hpp"
 
 //#define DEBUG_FLATTABLEDBOUTPUTTER 1
 
@@ -24,11 +24,11 @@
 		std::string const& filename,
 		std::string const& analysis_name,
 		std::string const& analysis_description,
 		qcdb::DBOutputter::Metadata const& metadata,
 		genfile::CohortIndividualSource const& samples,
-		boost::optional< db::Connection::RowId > analysis_id
+		boost::optional< genfile::db::Connection::RowId > analysis_id
 	) {
 		return UniquePtr( new FlatTableDBOutputter( filename, analysis_name, analysis_description, metadata, samples, analysis_id ) ) ;
 	}
 
 	FlatTableDBOutputter::SharedPtr FlatTableDBOutputter::create_shared(
@@ -35,11 +35,11 @@
 		std::string const& filename,
 		std::string const& analysis_name,
 		std::string const& analysis_description,
 		qcdb::DBOutputter::Metadata const& metadata,
 		genfile::CohortIndividualSource const& samples,
-		boost::optional< db::Connection::RowId > analysis_id
+		boost::optional< genfile::db::Connection::RowId > analysis_id
 	) {
 		return SharedPtr( new FlatTableDBOutputter( filename, analysis_name, analysis_description, metadata, samples, analysis_id ) ) ;
 	}
 
 	FlatTableDBOutputter::FlatTableDBOutputter(
@@ -46,16 +46,16 @@
 		std::string const& filename,
 		std::string const& analysis_name,
 		std::string const& analysis_description,
 		qcdb::DBOutputter::Metadata const& metadata,
 		genfile::CohortIndividualSource const& samples, // unused at present
-		boost::optional< db::Connection::RowId > analysis_id
+		boost::optional< genfile::db::Connection::RowId > analysis_id
 	):
 		m_outputter( filename, analysis_name, analysis_description, metadata, analysis_id ),
 		m_table_name( "Analysis" + genfile::string_utils::to_string( m_outputter.analysis_id() ) + "SampleData" )
 	{
-		db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 240 ) ;
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 240 ) ;
 		m_outputter.connection().run_statement(
 				"CREATE TABLE IF NOT EXISTS Sample ( "
 				"analysis_id INTEGER NOT NULL REFERENCES Entity( id ), "
 				"id TEXT NOT NULL, "
 				"index_in_data INTEGER NOT NULL, "
@@ -111,11 +111,11 @@
 		}
 		return where ;
 	}
 	
 	void FlatTableDBOutputter::store_block() {
-		db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 3600 ) ;
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 3600 ) ;
 
 		if( !m_insert_data_sql.get() ) {
 			create_schema() ;
 			create_variables() ;
 		}
@@ -226,11 +226,11 @@
 		if( !m_values.empty() ) {
 			store_block() ;
 			m_values.clear() ;
 		}
 		if( options & qcdb::eCreateIndices ) {
-			db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 600 ) ;
+			genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 600 ) ;
 			m_outputter.connection().run_statement( "CREATE INDEX IF NOT EXISTS SampleIndex ON Sample( id )" ) ;
 			m_outputter.connection().run_statement( "CREATE INDEX IF NOT EXISTS " + m_table_name + "_index ON " + m_table_name + "( sample_id )" ) ;
 			m_outputter.connection().run_statement( "CREATE INDEX IF NOT EXISTS " + m_table_name + "_index2 ON " + m_table_name + "( analysis_id, sample_id )" ) ;
 		}
 
@@ -244,12 +244,12 @@
 			get_or_create_sample( id, index ) ;
 			m_sample_ids[index] = id ;
 		}
 	}
 
-	db::Connection::RowId FlatTableDBOutputter::get_or_create_sample( genfile::VariantEntry const& identifier, std::size_t index ) const {
-		db::Connection::RowId result ;
+	genfile::db::Connection::RowId FlatTableDBOutputter::get_or_create_sample( genfile::VariantEntry const& identifier, std::size_t index ) const {
+		genfile::db::Connection::RowId result ;
 
 		if( identifier.is_missing() ) {
 			throw genfile::BadArgumentError( "impl::FlatTableDBOutputter::get_or_create_sample()", "identifier=NA" ) ;
 		}
 
@@ -268,19 +268,19 @@
 			result = m_outputter.connection().get_last_insert_row_id() ;
 
 			m_insert_sample_statement->reset() ;
 		}
 		else {
-			result = m_find_sample_statement->get< db::Connection::RowId >( 0 ) ;
+			result = m_find_sample_statement->get< genfile::db::Connection::RowId >( 0 ) ;
 		}
 
 		m_find_sample_statement->reset() ;
 
 		return result ;
 	}
 	
-	void FlatTableDBOutputter::store_data_for_sample( db::Connection::RowId analysis_id, std::size_t sample_index, genfile::VariantEntry const& sample_id ) {
+	void FlatTableDBOutputter::store_data_for_sample( genfile::db::Connection::RowId analysis_id, std::size_t sample_index, genfile::VariantEntry const& sample_id ) {
 		m_insert_data_sql->bind( 1, analysis_id ) ;
 		m_insert_data_sql->bind( 2, sample_id ) ;
 		
 		VariableMap::right_const_iterator
 			var_i = m_variables.right.begin(),

Index: components/SampleSummaryComponent/wscript
==================================================================
--- components/SampleSummaryComponent/wscript
+++ components/SampleSummaryComponent/wscript
@@ -1,35 +1,11 @@
-import os.path
-import glob
-#import UnitTest
-
 def configure( conf ):
 	pass
-
-def create_tests( bld ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'test_sample_summary_component',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'genfile',
-		uselib = 'BOOST BOOST_SYSTEM BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
 
 def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
+	bld.stlib(
 		target = 'SampleSummaryComponent',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = 'ZLIB BOOST BOOST_IOSTREAMS BOOST_SYSTEM BOOST_FILESYSTEM',
-		uselib_local = 'eigen genfile db statfile appcontext qcdb metro',
-		export_incdirs = './include'
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		includes = './include',
+		use = 'eigen genfile statfile appcontext qcdb metro boost ZLIB',
+		export_includes = './include'
 	)

Index: components/wscript
==================================================================
--- components/wscript
+++ components/wscript
@@ -1,5 +1,4 @@
+subdirs = [ 'HaplotypeFrequencyComponent', 'SNPSummaryComponent', 'RelatednessComponent', 'SampleSummaryComponent', 'SNPOutputComponent' ]
 def build( bld ):
-	subdirs = [ 'HaplotypeFrequencyComponent', 'SNPSummaryComponent', 'RelatednessComponent', 'SampleSummaryComponent', 'SNPOutputComponent' ]
-	for subdir in subdirs:
-		bld.add_subdirs( subdir )
+	bld.recurse( subdirs )
 

DELETED db/include/db/Connection.hpp
Index: db/include/db/Connection.hpp
==================================================================
--- db/include/db/Connection.hpp
+++ db/include/db/Connection.hpp
@@ -1,41 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_CONNECTION_HPP
-#define DB_CONNECTION_HPP
-
-#include <memory>
-#include <string>
-#include <stdint.h>
-#include "db/Transaction.hpp"
-
-namespace db {
-
-	class SQLStatement ;
-	
-	class Connection
-		// Base class for classes representing a connection to a database.
-		// The only supported operation is getting a query representing some SQL.
-	{
-	public:
-		typedef std::auto_ptr< Connection > UniquePtr ;
-		typedef std::auto_ptr< SQLStatement > StatementPtr ;
-		
-		static UniquePtr create( std::string const& filename ) ;
-		
-		virtual ~Connection() {}
-
-		virtual StatementPtr get_statement( std::string const& SQL ) = 0 ;
-		virtual void run_statement( std::string const& SQL ) ;
-		virtual std::string get_spec() const = 0 ;
-		typedef int64_t RowId ;
-		virtual RowId get_last_insert_row_id() const = 0 ;
-		typedef Transaction::UniquePtr ScopedTransactionPtr ;
-		virtual ScopedTransactionPtr open_transaction( double max_seconds_to_wait = 0.1 ) = 0 ;
-	} ;	
-}
-
-#endif

DELETED db/include/db/Error.hpp
Index: db/include/db/Error.hpp
==================================================================
--- db/include/db/Error.hpp
+++ db/include/db/Error.hpp
@@ -1,70 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_SQL_ERROR_HPP
-#define DB_SQL_ERROR_HPP
-
-namespace db {
-	struct Error: public std::exception
-	{
-		Error( std::string const& caller, std::string const& db_spec, int error, std::string const& sql = "(unknown)" ) ;
-		~Error() throw() ;
-		char const* what() const throw() { return "db::Error" ; }
-
-		int const& error_code() const { return m_error ; }
-		std::string const& spec() const { return m_spec ; }
-		std::string description() const ;
-		std::string sql() const { return m_sql ; }
-	private:
-		std::string const m_caller ;
-		std::string const m_spec ;
-		int const m_error ;
-		std::string const m_sql ;
-	} ;
-	
-	struct ConnectionError: public Error
-	{
-		ConnectionError( std::string const& caller, std::string const& db_spec, int error_code ): Error( caller, db_spec, error_code ) {}
-		char const* what() const throw() { return "db::ConnectionError" ; }
-	} ;
-
-	struct TransactionError: public Error
-	{
-		TransactionError( std::string const& caller, std::string const& db_spec, int error_code, std::string const& sql = "(unknown)" ): Error( caller, db_spec, error_code, sql ) {}
-		char const* what() const throw() { return "db::TransactionError" ; }
-	} ;
-
-	struct StatementPreparationError: public Error
-	{
-		StatementPreparationError( std::string const& caller, std::string const& db_spec, int error_code, std::string const& sql = "(unknown)" ): Error( caller, db_spec, error_code, sql ) {}
-		~StatementPreparationError() throw() {}
-		char const* what() const throw() { return "db::StatementPreparationError" ; }
-	} ;
-
-	struct StatementStepError: public Error
-	{
-		StatementStepError( std::string const& caller, std::string const& db_spec, int error_code, std::string const& sql = "(unknown)" ): Error( caller, db_spec, error_code, sql ) {}
-		char const* what() const throw() { return "db::StatementStepError" ; }
-	} ;
-
-	struct ValueBindError: public Error
-	{
-		~ValueBindError() throw() {}
-		ValueBindError(
-			std::string const& caller,
-			std::string const& db_spec,
-			int error_code,
-			std::string const& slot
-		): Error( caller, db_spec, error_code ), m_slot( slot ) {}
-		char const* what() const throw() { return "db::StatementStepError" ; }
-		std::string const& slot() const { return m_slot ; }
-	private:
-		std::string const m_slot ;
-	} ;
-	
-}
-
-#endif

DELETED db/include/db/MySQLConnection.hpp
Index: db/include/db/MySQLConnection.hpp
==================================================================
--- db/include/db/MySQLConnection.hpp
+++ db/include/db/MySQLConnection.hpp
@@ -1,64 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_MYSQL_CONNECTION_HPP
-#define DB_MYSQL_CONNECTION_HPP
-
-#include <cassert>
-#include <string>
-#include <exception>
-#include "mysql/mysql.h"
-#include "db/Connection.hpp"
-#include "db/Transaction.hpp"
-#include "db/Error.hpp"
-
-namespace db {
-	class MySQLConnection: public Connection
-	{
-	public:
-		// Open a connection to an on-disk database.
-		// If the filename is ":memory:", open instead a connection
-		// to a new private in-memory DB.
-		MySQLConnection( std::string const& db_spec, bool overwrite = true ) ;
-		virtual ~MySQLConnection() ;
-
-	public:
-
-		StatementPtr get_statement( std::string const& SQL ) ;
-		RowId get_last_insert_row_id() const ;
-
-	public:
-		MYSQL_STMT* prepare_sql( std::string const& SQL ) const ;
-		void finalise_statement( MYSQL_STMT* statement ) ;
-		void step_statement( MYSQL_STMT* statement ) ;
-		void execute_statement( MYSQL_STMT* statement ) ;
-	
-		std::string get_spec() const {
-			return m_filename ;
-		}
-
-	private:
-		struct Transaction: public db::Transaction {
-			Transaction( MySQLConnection& connection ) ;
-			~Transaction() ;
-		private:
-			MySQLConnection& m_connection ;
-		} ;
-	public:
-		ScopedTransactionPtr open_transaction( double max_seconds_to_wait = 0.1 ) ;
-	private:
-		std::string const db_spec ;
-		MYSQL* m_db_connection ;
-		bool m_managed ;
-
-	private:
-		void open_db_connection( std::string const& filename, bool overwrite ) ;
-		void close_db_connection_if_necessary() ;
-		void finalise_prepared_statements() ;
-	} ;
-}
-
-#endif

DELETED db/include/db/MySQLStatement.hpp
Index: db/include/db/MySQLStatement.hpp
==================================================================
--- db/include/db/MySQLStatement.hpp
+++ db/include/db/MySQLStatement.hpp
@@ -1,63 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_MYSQL_STATEMENT_HPP
-#define DB_MYSQL_STATEMENT_HPP
-
-#include <cassert>
-#include <string>
-#include <exception>
-#include "config.hpp"
-#if HAVE_MYSQL
-	#include "mysql.h"
-#endif
-#include "db/MySQLConnection.hpp"
-#include "db/SQLStatement.hpp"
-
-namespace db {
-	class MySQLStatement: public SQLStatement
-	{
-	public:
-		MySQLStatement( SQLite3Connection* connection, std::string const& SQL ) ;
-		~MySQLStatement() ;
-		bool step() ;
-		bool empty() const ;
-		
-		std::size_t get_number_of_columns() const ;
-		std::string get_name_of_column( std::size_t i ) const ;
-		bool is_null( int column_id ) const ;
-		std::string get_sql() const ;
-
-		MySQLStatement& bind( std::size_t i, int32_t value ) ;
-		MySQLStatement& bind( std::size_t i, uint32_t value ) ;
-		MySQLStatement& bind( std::size_t i, int64_t value ) ;
-		MySQLStatement& bind( std::size_t i, uint64_t value ) ;
-		MySQLStatement& bind( std::size_t i, double value ) ;
-		MySQLStatement& bind( std::size_t i, std::string const& value ) ;
-		MySQLStatement& bind( std::size_t i, char const* buffer, char const* const end ) ;
-		MySQLStatement& bind_NULL( std::size_t i ) ;
-		MySQLStatement& reset() ;
-
-	protected:
-		
-		int64_t get_column_int64( int column_id ) const ;
-		int get_column_int( int column_id ) const ;
-		double get_column_double( int column_id ) const ;
-		std::string get_column_string( int column_id ) const ;
-		char get_column_char( int column_id ) const ;
-		
-		int get_column_count() const ;
-
-	private:
-		std::string const m_sql ;
-		std::auto_ptr< MYSQL_STMT > m_statement ;
-		MySQLConnection* m_connection ;	
-		bool m_executed ;
-		bool m_have_results ;
-	} ;
-}
-
-#endif

DELETED db/include/db/SQLStatement.hpp
Index: db/include/db/SQLStatement.hpp
==================================================================
--- db/include/db/SQLStatement.hpp
+++ db/include/db/SQLStatement.hpp
@@ -1,99 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_SQL_STATEMENT_HPP
-#define DB_SQL_STATEMENT_HPP
-
-#include <cassert>
-#include <string>
-#include <exception>
-#include <stdint.h>
-#include "sqlite3/sqlite3.h"
-#include "db/SQLite3Connection.hpp"
-#include "genfile/VariantEntry.hpp"
-#include "genfile/string_utils/slice.hpp"
-
-namespace db {
-	
-	struct SQLError: public std::exception
-	{
-		virtual ~SQLError() throw() {}
-		char const* what() const throw() { return "db::SQLError" ; }
-		virtual std::string description() const = 0 ;
-	} ;
-	
-	class SQLStatement
-	{
-	public:
-		typedef std::auto_ptr< SQLStatement > UniquePtr ;
-	public:
-		virtual ~SQLStatement() ;
-		
-		// Step to the next result row.  The entries can be accessed using get_column().
-		// Return false if there is no next row, otherwise true.
-		virtual bool step() = 0 ;
-		// Return 
-		virtual bool empty() const = 0 ;
-		
-		// Get the result for the given column.
-		// Columns are 0-indexed.
-		template< typename T > T get_column( int column_id ) const ;
-		template< typename T > T get( int column_id ) const { return get_column< T >( column_id ) ; }
-		virtual bool is_null( int column_id ) const = 0 ;
-
-		virtual std::size_t get_number_of_columns() const = 0 ;
-		virtual std::string get_name_of_column( std::size_t i ) const = 0 ;
-
-		// For parameterised queries, bind an integer value to the ith placeholder.
-		// Placeholders are indexed starting from 1 on the left.
-		// Named placeholders with the same name have the same index.
-		virtual SQLStatement& bind( std::size_t i, int32_t value ) = 0 ;
-		virtual SQLStatement& bind( std::size_t i, uint32_t value ) = 0 ;
-		virtual SQLStatement& bind( std::size_t i, int64_t value ) = 0 ;
-		virtual SQLStatement& bind( std::size_t i, uint64_t value ) = 0 ;
-		virtual SQLStatement& bind( std::size_t i, double value ) = 0 ;
-		// For parameterised queries, bind a string value to the ith placeholder.
-		// Placeholders are indexed starting from 1 on the left.
-		// Named placeholders with the same name have the same index.
-		// The string will be copied so the caller need not preserve it beyond the call site.
-		virtual SQLStatement& bind( std::size_t i, std::string const& value ) = 0 ;
-		SQLStatement& bind( std::size_t i, char const* value ) ;
-		SQLStatement& bind( std::size_t i, genfile::string_utils::slice const& value ) ;
-		// For parameterised queries, bind a BLOB value (array of chars) to the ith placeholder.
-		// Placeholders are indexed starting from 1 on the left.
-		// Named placeholders with the same name have the same index.
-		// The data will not be copied and so the caller must preserve the data until
-		// such time as no further steps() are performed, or the parameter is re-bound.
-		virtual SQLStatement& bind( std::size_t i, char const* buffer, char const* const end ) = 0 ;
-		virtual SQLStatement& bind( std::size_t i, uint8_t const* buffer, uint8_t const* const end ) = 0 ;
-
-		// bind NULL to a parameter
-		virtual SQLStatement& bind_NULL( std::size_t i ) = 0 ;
-
-		// Bind a genfile::VariantEntry
-		SQLStatement& bind( std::size_t, genfile::VariantEntry const& value ) ;
-
-		// Reset the statement, ready to be re-executed.
-		virtual SQLStatement& reset() = 0 ;
-		
-		// Return the SQL this statement contains.
-		virtual std::string get_sql() const = 0 ;
-		
-	protected:
-		virtual int get_column_int( int column_id ) const = 0 ;
-		virtual int64_t get_column_int64( int column_id ) const = 0 ;
-		virtual double get_column_double( int column_id ) const = 0 ;
-		virtual std::string get_column_string( int column_id ) const = 0 ;
-		virtual char get_column_char( int column_id ) const = 0 ;
-	} ;
-	
-	template<> int SQLStatement::get_column< int >( int column_id ) const ;
-	template<> int64_t SQLStatement::get_column< int64_t >( int column_id ) const ;
-	template<> double SQLStatement::get_column< double >( int column_id ) const ;
-	template<> std::string SQLStatement::get_column< std::string >( int column_id ) const ;
-}
-
-#endif

DELETED db/include/db/SQLite3Connection.hpp
Index: db/include/db/SQLite3Connection.hpp
==================================================================
--- db/include/db/SQLite3Connection.hpp
+++ db/include/db/SQLite3Connection.hpp
@@ -1,68 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef SQLITE3_CONNECTOR_HPP
-#define SQLITE3_CONNECTOR_HPP
-
-#include <cassert>
-#include <string>
-#include <exception>
-#include "sqlite3/sqlite3.h"
-#include "db/Connection.hpp"
-#include "db/Transaction.hpp"
-#include "db/Error.hpp"
-
-extern "C" {
-	void sqlite3_trace_callback( void* udp, const char* sql ) ;
-	int sqlite3_busy_callback( void*, int number_of_tries ) ;
-}
-
-namespace db {
-	class SQLite3Connection: public Connection
-	{
-	public:
-		// Open a connection to an on-disk database.
-		// If the filename is ":memory:", open instead a connection
-		// to a new private in-memory DB.
-		SQLite3Connection( std::string const& filename, bool overwrite = true ) ;
-		virtual ~SQLite3Connection() ;
-
-	public:
-
-		StatementPtr get_statement( std::string const& SQL ) ;
-		RowId get_last_insert_row_id() const ;
-
-	public:
-		sqlite3_stmt* prepare_sql( std::string const& SQL ) const ;
-		int finalise_statement( sqlite3_stmt* statement ) ;
-		int step_statement( sqlite3_stmt* statement ) ;
-	
-		std::string get_spec() const {
-			return m_filename ;
-		}
-
-	private:
-		struct Transaction: public db::Transaction {
-			Transaction( SQLite3Connection& connection ) ;
-			~Transaction() ;
-		private:
-			SQLite3Connection& m_connection ;
-		} ;
-	public:
-		ScopedTransactionPtr open_transaction( double max_seconds_to_wait = 0.1 ) ;
-	private:
-		std::string m_filename ;
-		sqlite3* m_db_connection ;
-		bool m_managed ;
-
-	private:
-		void open_db_connection( std::string const& filename, bool overwrite ) ;
-		void close_db_connection_if_necessary() ;
-		void finalise_prepared_statements() ;
-	} ;
-}
-
-#endif

DELETED db/include/db/SQLite3Error.hpp
Index: db/include/db/SQLite3Error.hpp
==================================================================
--- db/include/db/SQLite3Error.hpp
+++ db/include/db/SQLite3Error.hpp
@@ -1,17 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_SQLITE3_ERROR_HPP
-#define DB_SQLITE3_ERROR_HPP
-
-#include <string>
-#include "db/SQLStatement.hpp"
-
-namespace db {
-}
-
-#endif
-

DELETED db/include/db/SQLite3Statement.hpp
Index: db/include/db/SQLite3Statement.hpp
==================================================================
--- db/include/db/SQLite3Statement.hpp
+++ db/include/db/SQLite3Statement.hpp
@@ -1,95 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_SQLITE3_STATEMENT_HPP
-#define DB_SQLITE3_STATEMENT_HPP
-
-#include <cassert>
-#include <string>
-#include <exception>
-
-#include "sqlite3/sqlite3.h"
-#include "db/SQLite3Connection.hpp"
-#include "db/SQLStatement.hpp"
-
-namespace db {
-	class SQLite3Statement: public SQLStatement
-	{
-	public:
-		SQLite3Statement( SQLite3Connection* connector, std::string const& SQL ) ;
-		~SQLite3Statement() ;
-		bool step() ;
-		bool empty() const ;
-		
-		std::size_t get_number_of_columns() const ;
-		std::string get_name_of_column( std::size_t i ) const ;
-		bool is_null( int column_id ) const ;
-		SQLite3Statement& bind( std::size_t i, int32_t value ) ;
-		SQLite3Statement& bind( std::size_t i, uint32_t value ) ;
-		SQLite3Statement& bind( std::size_t i, int64_t value ) ;
-		SQLite3Statement& bind( std::size_t i, uint64_t value ) ;
-		SQLite3Statement& bind( std::size_t i, double value ) ;
-		SQLite3Statement& bind( std::size_t i, std::string const& value ) ;
-		SQLite3Statement& bind( std::size_t i, char const* buffer, char const* const end ) ;
-		SQLite3Statement& bind( std::size_t i, uint8_t const* buffer, uint8_t const* const end ) ;
-		SQLite3Statement& bind_NULL( std::size_t i ) ;
-
-		SQLite3Statement& reset() ;
-
-		std::string get_sql() const ;
-
-		struct Error {
-			enum {
-				OK			= SQLITE_OK,
-				ERROR		= SQLITE_ERROR,			/* SQL error or missing database */
-				INTERNAL	= SQLITE_INTERNAL,		/* Internal logic error in SQLite */
-				PERM		= SQLITE_PERM,			/* Access permission denied */
-				ABORT		= SQLITE_ABORT,			/* Callback routine requested an abort */
-				BUSY		= SQLITE_BUSY,			/* The database file is locked */
-				LOCKED		= SQLITE_LOCKED,		/* A table in the database is locked */
-				NOMEM		= SQLITE_NOMEM,			/* A malloc() failed */
-				READONLY	= SQLITE_READONLY,		/* Attempt to write a readonly database */
-				INTERRUPT	= SQLITE_INTERRUPT,		/* Operation terminated by sqlite3_interrupt()*/
-				IOERR		= SQLITE_IOERR,			/* Some kind of disk I/O error occurred */
-				CORRUPT		= SQLITE_CORRUPT,		/* The database disk image is malformed */
-				NOTFOUND	= SQLITE_NOTFOUND,		/* NOT USED. Table or record not found */
-				FULL		= SQLITE_FULL,			/* Insertion failed because database is full */
-				CANTOPEN	= SQLITE_CANTOPEN,		/* Unable to open the database file */
-				PROTOCOL	= SQLITE_PROTOCOL,		/* Database lock protocol error */
-				EMPTY		= SQLITE_EMPTY,			/* Database is empty */
-				SCHEMA		= SQLITE_SCHEMA,		/* The database schema changed */
-				TOOBIG		= SQLITE_TOOBIG,		/* String or BLOB exceeds size limit */
-				CONSTRAINT	= SQLITE_CONSTRAINT,	/* Abort due to constraint violation */
-				MISMATCH	= SQLITE_MISMATCH,		/* Data type mismatch */
-				MISUSE		= SQLITE_MISUSE,		/* Library used incorrectly */
-				NOLFS		= SQLITE_NOLFS,			/* Uses OS features not supported on host */
-				AUTH		= SQLITE_AUTH,			/* Authorization denied */
-				FORMAT		= SQLITE_FORMAT,		/* Auxiliary database format error */
-				RANGE		= SQLITE_RANGE,			/* 2nd parameter to sqlite3_bind out of range */
-				NOTADB		= SQLITE_NOTADB,		/* File opened that is not a database file */
-				ROW			= SQLITE_ROW,			/* sqlite3_step() has another row ready */
-				DONE		= SQLITE_DONE			/* sqlite3_step() has finished executing */
-			} ;
-		} ;
-	protected:
-		
-		int64_t get_column_int64( int column_id ) const ;
-		int get_column_int( int column_id ) const ;
-		double get_column_double( int column_id ) const ;
-		std::string get_column_string( int column_id ) const ;
-		char get_column_char( int column_id ) const ;
-		
-		int get_column_count() const ;
-
-	private:
-		sqlite3_stmt* m_statement ;
-		SQLite3Connection* m_connection ;	
-		bool m_have_results ;
-	} ;
-
-}
-
-#endif

DELETED db/include/db/Transaction.hpp
Index: db/include/db/Transaction.hpp
==================================================================
--- db/include/db/Transaction.hpp
+++ db/include/db/Transaction.hpp
@@ -1,20 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_TRANSACTION_HPP
-#define DB_TRANSACTION_HPP
-
-#include <memory>
-
-namespace db {
-	class Transaction {
-	public:
-		typedef std::auto_ptr< Transaction > UniquePtr ;
-		virtual ~Transaction() {}
-	} ;
-}
-
-#endif

DELETED db/include/db/fill_SQL.hpp
Index: db/include/db/fill_SQL.hpp
==================================================================
--- db/include/db/fill_SQL.hpp
+++ db/include/db/fill_SQL.hpp
@@ -1,36 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_FILL_SQL_HPP
-#define DB_FILL_SQL_HPP
-
-#include <cassert>
-#include <string>
-#include <sstream>
-
-namespace db {
-	
-	std::string fill_SQL( std::string SQL ) ;
-	std::string fill_SQL( std::string SQL, std::string const& value1 ) ;
-	std::string fill_SQL( std::string SQL, char const* value1 ) ;
-	template< typename T1 >
-	std::string fill_SQL( std::string SQL, T1 const& value1 ) {
-		std::ostringstream ostr ;
-		ostr << value1 ;
-		std::size_t pos = SQL.find( "%s" ) ;
-		assert( pos != std::string::npos ) ;
-		SQL.replace( pos, 2, ostr.str() ) ;
-		return SQL ;
-	}
-
-	template< typename T1, typename T2 >
-	std::string fill_SQL( std::string SQL, T1 const& value1, T2 const& value2 ) {
-		return fill_SQL( fill_SQL( SQL, value1 ), value2 ) ;
-	}
-}
-
-#endif
-

DELETED db/include/db/get_unique_id.hpp
Index: db/include/db/get_unique_id.hpp
==================================================================
--- db/include/db/get_unique_id.hpp
+++ db/include/db/get_unique_id.hpp
@@ -1,25 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_GET_UNIQUE_ID_HPP
-#define DB_GET_UNIQUE_ID_HPP
-
-#include "db/Connection.hpp"
-
-namespace db {
-	// Given a table, an "id" column of ints and a where clause,
-	// return the id for the row matching the where clause.
-	// throw a error::KeyError if there is not a unique matching row.
-	int get_unique_id(
-		Connection* connection,
-		std::string const& table,
-		std::string const& id_column,
-		std::string const& where_clause
-	) ;
-}
-
-#endif
-

DELETED db/include/db/load_key_value_pairs.hpp
Index: db/include/db/load_key_value_pairs.hpp
==================================================================
--- db/include/db/load_key_value_pairs.hpp
+++ db/include/db/load_key_value_pairs.hpp
@@ -1,68 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef DB_LOAD_KEY_VALUE_PAIRS_HPP
-#define DB_LOAD_KEY_VALUE_PAIRS_HPP
-
-#include <map>
-#include <string>
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
-#include "genfile/Error.hpp"
-#include "genfile/string_utils.hpp"
-
-namespace db {
-	template< typename Key, typename Value >
-	std::map< Key, Value > load_key_value_pairs(
-		Connection* connection,
-		std::string const& table_or_view,
-		std::string const& key_column,
-		std::string const& value_column		
-	)
-	// Load key/value pairs from the given columns of the given table, returning the result as a std::map.
-	// If a duplicate key is found, a KeyNotUniqueError is thrown.
-	{
-		typename std::map< Key, Value > result ;
-		db::Connection::StatementPtr statement = connection->get_statement(
-			"SELECT " + key_column + ", " + value_column + " FROM " + table_or_view + ";"
-		) ;
-	
-		while( statement->step() ) {
-			Key key = statement->get_column< Key >( 0 ) ;
-			if( result.find( key ) != result.end() ) {
-				throw genfile::DuplicateKeyError(
-					"db::load_key_value_pairs()",
-					connection->get_spec() + ":" + table_or_view + ", key=\"" + genfile::string_utils::to_string( key ) + "\""
-				) ;
-			}
-			result.insert(
-				std::make_pair(
-			 		key,
-					statement->get_column< Value >( 1 )
-				)
-			) ;
-		}
-
-		return result ;
-	}
-	
-	template< typename Key, typename Value >
-	std::map< Key, Value > load_key_value_pairs(
-		Connection::UniquePtr& connection,
-		std::string const& table_or_view,
-		std::string const& key_column,
-		std::string const& value_column		
-	) {
-		return load_key_value_pairs< Key, Value >(
-			connection.get(),
-			table_or_view,
-			key_column,
-			value_column
-		) ;
-	}
-}
-
-#endif

DELETED db/src/Connection.cpp
Index: db/src/Connection.cpp
==================================================================
--- db/src/Connection.cpp
+++ db/src/Connection.cpp
@@ -1,19 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include "db/Connection.hpp"
-#include "db/SQLite3Connection.hpp"
-#include "db/SQLStatement.hpp"
-
-namespace db {
-	Connection::UniquePtr Connection::create( std::string const& filename ) {
-		return Connection::UniquePtr( new SQLite3Connection( filename )) ;
-	}
-
-	void Connection::run_statement( std::string const& SQL ) {
-		get_statement( SQL )->step() ;
-	}
-}

DELETED db/src/Error.cpp
Index: db/src/Error.cpp
==================================================================
--- db/src/Error.cpp
+++ db/src/Error.cpp
@@ -1,60 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <string>
-#include "db/SQLite3Statement.hpp"
-#include "db/Error.hpp"
-
-namespace db {
-	Error::Error( std::string const& caller, std::string const& db_spec, int error, std::string const& sql ):
-		m_spec( db_spec ),
-		m_error( error ),
-		m_sql( sql )
-	{
-		assert( m_error != SQLite3Statement::Error::OK ) ;
-	}
-	
-	Error::~Error() throw() {}
-	
-	std::string Error::description() const {
-		typedef db::SQLite3Statement::Error Error ;
-		std::string result ;
-		switch( m_error ) {
-			case Error::ERROR: 		result = "SQL error or missing database"; break ;
-			case Error::INTERNAL: 	result = "Internal logic error in SQLite"; break ;
-			case Error::PERM: 		result = "Access permission denied"; break ;
-			case Error::ABORT: 		result = "Callback routine requested an abort"; break ;
-			case Error::BUSY: 		result = "The database file is locked"; break ;
-			case Error::LOCKED: 	result = "A table in the database is locked"; break ;
-			case Error::NOMEM: 		result = "A malloc() failed"; break ;
-			case Error::READONLY: 	result = "Attempt to write a readonly database"; break ;
-			case Error::INTERRUPT: 	result = "Operation terminated by sqlite3_interrupt()"; break ;
-			case Error::IOERR: 		result = "Some kind of disk I/O error occurred"; break ;
-			case Error::CORRUPT: 	result = "The database disk image is malformed"; break ;
-			case Error::NOTFOUND: 	result = "NOT USED. Table or record not found"; break ;
-			case Error::FULL: 		result = "Insertion failed because database is full"; break ;
-			case Error::CANTOPEN: 	result = "Unable to open the database file"; break ;
-			case Error::PROTOCOL: 	result = "Database lock protocol error"; break ;
-			case Error::EMPTY: 		result = "Database is empty"; break ;
-			case Error::SCHEMA: 	result = "The database schema changed"; break ;
-			case Error::TOOBIG: 	result = "String or BLOB exceeds size limit"; break ;
-			case Error::CONSTRAINT: result = "Abort due to constraint violation"; break ;
-			case Error::MISMATCH: 	result = "Data type mismatch"; break ;
-			case Error::MISUSE: 	result = "Library used incorrectly"; break ;
-			case Error::NOLFS: 		result = "Uses OS features not supported on host"; break ;
-			case Error::AUTH: 		result = "Authorization denied"; break ;
-			case Error::FORMAT: 	result = "Auxiliary database format error"; break ;
-			case Error::RANGE: 		result = "2nd parameter to sqlite3_bind out of range"; break ;
-			case Error::NOTADB: 	result = "File opened that is not a database file"; break ;
-			case Error::ROW: 		result = "sqlite3_step() has another row ready"; break ;
-			case Error::DONE: 		result = "sqlite3_step() has finished executing"; break ;
-			default: 				assert(0) ;
-		}
-		result += ", in statement \"" + m_sql + "\"" ;
-		return result ;
-	}
-}
-

DELETED db/src/MySQLConnection.cpp
Index: db/src/MySQLConnection.cpp
==================================================================
--- db/src/MySQLConnection.cpp
+++ db/src/MySQLConnection.cpp
@@ -1,108 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-#if 0
-
-#include <iostream>
-#include <stdint.h>
-#include <boost/date_time/posix_time/posix_time_types.hpp>
-#include <boost/thread/thread_time.hpp>
-#include <boost/thread/thread.hpp>
-#include "db/MySQLConnection.hpp"
-// #include "db/MySQLStatement.hpp"
-#include "db/Error.hpp"
-
-namespace db {
-	struct MySQLStatement ;
-
-	MySQLConnection::MySQLConnection( std::string const& filename, bool overwrite ):
-		m_filename( filename ),
-		m_db_connection(0),
-		m_managed( true )
-	{
-		open_db_connection( filename, overwrite ) ;
-	}
-
-	MySQLConnection::~MySQLConnection() {
-		close_db_connection_if_necessary() ;
-	}
-
-	
-	MySQLConnection::StatementPtr MySQLConnection::get_statement( std::string const& SQL ) {
-		return StatementPtr( new MySQLStatement( this, SQL ) ) ;
-	}	
-
-	Connection::RowId MySQLConnection::get_last_insert_row_id() const {
-		uint64_t result = sqlite3_last_insert_rowid( m_db_connection ) ;
-		return result ;
-	}
-
-	void MySQLConnection::open_db_connection( std::string const& connection_string, bool overwrite ) {
-		std::map< std::string, std::string > bits = parse_connection_string( connection_string ) ;
-		open_db_connection( connection_spec, overwrite ) ;
-	}
-
-
-	void MySQLConnection::open_db_connection( std::map< std::string, std::string > const& connection_spec, bool overwrite ) {
-		int flags = SQLITE_OPEN_READWRITE ;
-		if( overwrite ) {
-			flags |= SQLITE_OPEN_CREATE ;
-		}
-		int code = sqlite3_open_v2( filename.c_str(), &m_db_connection, flags, NULL ) ;
-		if( code != SQLITE_OK ) {
-			throw ConnectionError( "MySQLConnection::open_db_connection()", get_spec(), code ) ;
-		}
-		// We add a busy handler.  This makes the database more robust by retrying failed transactions.
-		sqlite3_busy_handler( m_db_connection, &sqlite3_busy_callback, NULL ) ;
-		// Uncomment the next line to trace SQL statements executed.
-		//sqlite3_trace( m_db_connection, &sqlite3_trace_callback, NULL ) ;
-	}
-
-	void MySQLConnection::close_db_connection_if_necessary() {
-		if( m_managed && m_db_connection != 0 ) {
-			// According to SQLite docs, we must finalise any prepared statements
-			// before we can close the db connection.
-			finalise_prepared_statements() ;
-			sqlite3_close( m_db_connection ) ;
-			m_db_connection = 0 ;
-		}
-	}
-
-	void MySQLConnection::finalise_prepared_statements() {
-		assert( m_db_connection != 0 ) ;
-#if SQLITE_VERSION_NUMBER > 3006000
-		sqlite3_stmt* statement ;
-		while(( statement = sqlite3_next_stmt( m_db_connection, 0)) != 0 ) {
-			finalise_statement( statement ) ;
-		}
-#endif
-	}
-	
-	MySQLConnection::ScopedTransactionPtr MySQLConnection::open_transaction( double max_seconds_to_wait ) {		
-		ScopedTransactionPtr transaction ;
-		for( std::size_t i = 0; i < max_seconds_to_wait * 100; ++i ) {
-			try {
-				transaction.reset( new MySQLConnection::Transaction( *this ) ) ;
-				break ;
-			}
-			catch( db::StatementStepError const& e ) {
-				boost::this_thread::sleep( boost::posix_time::milliseconds( 10 ) ) ;
-			}
-		}
-		return transaction ;
-	}
-	
-	MySQLConnection::Transaction::Transaction( MySQLConnection& connection ):
-		m_connection( connection )
-	{
-		m_connection.run_statement( "BEGIN IMMEDIATE TRANSACTION" ) ;
-	}
-	
-	MySQLConnection::Transaction::~Transaction() {
-		m_connection.run_statement( "COMMIT" ) ;
-	}
-}
-
-#endif

DELETED db/src/SQLStatement.cpp
Index: db/src/SQLStatement.cpp
==================================================================
--- db/src/SQLStatement.cpp
+++ db/src/SQLStatement.cpp
@@ -1,80 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <cassert>
-#include <string>
-#include <stdint.h>
-#include "sqlite3/sqlite3.h"
-#include "db/SQLStatement.hpp"
-#include "genfile/VariantEntry.hpp"
-#include "genfile/string_utils.hpp"
-
-namespace db {
-	SQLStatement::~SQLStatement() {}
-	
-	template<>
-	int SQLStatement::get_column< int >( int column_id ) const {
-		return this->get_column_int( column_id ) ;
-	}
-
-	template<>
-	int64_t SQLStatement::get_column< int64_t >( int column_id ) const {
-		return this->get_column_int64( column_id ) ;
-	}
-
-	template<>
-	double SQLStatement::get_column< double >( int column_id ) const {
-		return this->get_column_double( column_id ) ;
-	}
-
-	template<>
-	std::string SQLStatement::get_column< std::string >( int column_id ) const {
-		return this->get_column_string( column_id ) ;
-	}
-
-	template<>
-	char SQLStatement::get_column< char >( int column_id ) const {
-		return this->get_column_char( column_id ) ;
-	}
-	
-	SQLStatement& SQLStatement::bind( std::size_t i, char const* value ) {
-		bind( i, std::string( value )) ;
-		return *this ;
-	}
-
-	SQLStatement& SQLStatement::bind( std::size_t i, genfile::string_utils::slice const& value ) {
-		bind( i, std::string( value )) ;
-		return *this ;
-	}
-	
-	namespace impl {
-		struct variant_binder: public boost::static_visitor<>
-		{
-			variant_binder( std::size_t index, SQLStatement& statement ): m_index( index ), m_statement( statement ) {}
-			template< typename T >
-			void operator()( T const& value ) {
-				m_statement.bind( m_index, value ) ;
-			}
-			void operator()( genfile::Chromosome const& value ) {
-				m_statement.bind( m_index, std::string( value ) ) ;
-			}
-			void operator()( genfile::MissingValue const& value ) {
-				m_statement.bind_NULL( m_index ) ;
-			}
-			void operator()( genfile::GenomePosition const& value ) {
-				m_statement.bind( m_index, genfile::string_utils::to_string( value ) ) ;
-			}
-		private:
-			std::size_t const m_index ;
-			SQLStatement& m_statement ;
-		} ;
-	}
-
-	SQLStatement& SQLStatement::bind( std::size_t index, genfile::VariantEntry const& value ) {
-		genfile::apply_visitor( impl::variant_binder( index, *this ), value ) ;
-		return *this ;
-	}
-}

DELETED db/src/SQLite3Connection.cpp
Index: db/src/SQLite3Connection.cpp
==================================================================
--- db/src/SQLite3Connection.cpp
+++ db/src/SQLite3Connection.cpp
@@ -1,152 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <iostream>
-#include <stdint.h>
-#include <boost/date_time/posix_time/posix_time_types.hpp>
-#include <boost/thread/thread_time.hpp>
-#include <boost/thread/thread.hpp>
-#include "db/SQLite3Connection.hpp"
-#include "db/SQLite3Statement.hpp"
-#include "db/Error.hpp"
-
-extern "C" {
-	void sqlite3_trace_callback( void* udp, const char* sql ) {
-		std::cerr << "SQLite3 trace: SQL = \"" << sql << "\".\n" ;
-	}
-	
-	int sqlite3_busy_callback( void*, int number_of_tries ) {
-		if( number_of_tries > 10 ) {
-			return 0 ;
-		}
-		boost::this_thread::sleep( boost::posix_time::milliseconds( 10 ) ) ;
-		return 1 ;
-	}
-}
-
-namespace db {
-	SQLite3Connection::SQLite3Connection( std::string const& filename, bool overwrite ):
-		m_filename( filename ),
-		m_db_connection(0),
-		m_managed( true )
-	{
-		open_db_connection( filename, overwrite ) ;
-	}
-
-	SQLite3Connection::~SQLite3Connection() {
-		close_db_connection_if_necessary() ;
-	}
-
-	
-	SQLite3Connection::StatementPtr SQLite3Connection::get_statement( std::string const& SQL ) {
-		return StatementPtr( new SQLite3Statement( this, SQL ) ) ;
-	}	
-
-	Connection::RowId SQLite3Connection::get_last_insert_row_id() const {
-		uint64_t result = sqlite3_last_insert_rowid( m_db_connection ) ;
-		return result ;
-	}
-
-	sqlite3_stmt* SQLite3Connection::prepare_sql( std::string const& SQL ) const {
-		assert( m_db_connection != 0 ) ;
-		sqlite3_stmt* statement ;
-		int code = sqlite3_prepare_v2(
-			m_db_connection,
-			SQL.c_str(),
-			static_cast< int >( SQL.size()+1 ), // +1 accounts for null terminating byte.
-			&statement,
-			0 // ignore pzTail
-		) ;
-		if( code != SQLITE_OK ) {
-			throw StatementPreparationError( "SQLite3Connection::prepare_sql()", get_spec(), code, SQL ) ;
-		}
-		// SQLite might return 0 if the SQL consisted of comments and whitespace only
-		// but I want to treat this as a programmer error.
-		assert( statement != 0 ) ;
-		return statement ;
-	}
-
-	int SQLite3Connection::finalise_statement( sqlite3_stmt* statement ) {
-		assert( statement != 0 ) ;
-		return sqlite3_finalize( statement ) ;
-	}
-
-	int SQLite3Connection::step_statement( sqlite3_stmt* statement ) {
-		int code = sqlite3_step( statement ) ;
-		if( code != SQLITE_ROW && code != SQLITE_DONE ) {
-			throw StatementStepError( "SQLite3Connection::step_statement()", get_spec(), code, std::string( sqlite3_sql( statement ) ) ) ;
-		}
-		return (code == SQLITE_ROW);
-	}
-	
-	void SQLite3Connection::open_db_connection( std::string const& filename, bool overwrite ) {
-		int flags = SQLITE_OPEN_READWRITE ;
-		if( overwrite ) {
-			flags |= SQLITE_OPEN_CREATE ;
-		}
-		int code = sqlite3_open_v2( filename.c_str(), &m_db_connection, flags, NULL ) ;
-		if( code != SQLITE_OK ) {
-			throw ConnectionError( "SQLite3Connection::open_db_connection()", get_spec(), code ) ;
-		}
-		// We add a busy handler.  This makes the database more robust by retrying failed transactions.
-		sqlite3_busy_handler( m_db_connection, &sqlite3_busy_callback, NULL ) ;
-		// Uncomment the next line to trace SQL statements executed.
-		//sqlite3_trace( m_db_connection, &sqlite3_trace_callback, NULL ) ;
-	}
-
-	void SQLite3Connection::close_db_connection_if_necessary() {
-		if( m_managed && m_db_connection != 0 ) {
-			// According to SQLite docs, we must finalise any prepared statements
-			// before we can close the db connection.
-			finalise_prepared_statements() ;
-			sqlite3_close( m_db_connection ) ;
-			m_db_connection = 0 ;
-		}
-	}
-
-	void SQLite3Connection::finalise_prepared_statements() {
-		assert( m_db_connection != 0 ) ;
-#if SQLITE_VERSION_NUMBER > 3006000
-		sqlite3_stmt* statement ;
-		while(( statement = sqlite3_next_stmt( m_db_connection, 0)) != 0 ) {
-			finalise_statement( statement ) ;
-		}
-#endif
-	}
-	
-	SQLite3Connection::ScopedTransactionPtr SQLite3Connection::open_transaction( double max_seconds_to_wait ) {		
-		ScopedTransactionPtr transaction ;
-		// we wait 10 milliseconds between attempts.
-		
-		for( std::size_t count = 0 ; true; ++count ) {
-			try {
-				transaction.reset( new SQLite3Connection::Transaction( *this ) ) ;
-				break ;
-			}
-			catch( db::StatementStepError const& e ) {
-				// Because of the busy handler (see top of this file)
-				// each attempt takes ~0.1s anyway
-				// We wait an additional 0.1s so that each attempt takes 0.2s in total.
-				if( ( count * 0.2 ) > max_seconds_to_wait ) {
-					std::cerr << "Open transaction: failure count=" << count << " (~" << count*0.2 << "s).  Bailing out.\n" ;
-					boost::this_thread::sleep( boost::posix_time::milliseconds( 100 ) ) ;
-					throw TransactionError( "SQLite3Connection::open_transaction()", get_spec(), e.error_code(), e.sql() ) ;
-				}
-			}
-		}
-		return transaction ;
-	}
-	
-	SQLite3Connection::Transaction::Transaction( SQLite3Connection& connection ):
-		m_connection( connection )
-	{
-		m_connection.run_statement( "BEGIN IMMEDIATE TRANSACTION" ) ;
-	}
-	
-	SQLite3Connection::Transaction::~Transaction() {
-		m_connection.run_statement( "COMMIT" ) ;
-	}
-}

DELETED db/src/SQLite3Statement.cpp
Index: db/src/SQLite3Statement.cpp
==================================================================
--- db/src/SQLite3Statement.cpp
+++ db/src/SQLite3Statement.cpp
@@ -1,184 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <iostream>
-#include <cassert>
-#include <string>
-#include <exception>
-
-#include "sqlite3/sqlite3.h"
-#include "genfile/string_utils/string_utils.hpp"
-#include "db/SQLite3Connection.hpp"
-#include "db/SQLStatement.hpp"
-#include "db/SQLite3Statement.hpp"
-#include "db/SQLite3Error.hpp"
-
-namespace db {
-	SQLite3Statement::SQLite3Statement( SQLite3Connection* connection, std::string const& SQL ):
-		m_connection( connection ),
-		m_have_results( false )
-	{
-		assert( m_connection ) ;
-		m_statement = m_connection->prepare_sql( SQL ) ;
-		//std::cerr << "SQLite3Statement::SQLite3Statement(): statement is \"" + SQL + "\".\n" ;
-		assert( m_statement != 0 ) ;
-	}
-	
-	SQLite3Statement::~SQLite3Statement() {
-		m_connection->finalise_statement( m_statement ) ;
-	}
-
-	bool SQLite3Statement::step() {
-		m_have_results = m_connection->step_statement( m_statement ) ;
-		return m_have_results ;
-	}
-
-	bool SQLite3Statement::empty() const {
-		return !m_have_results ;
-	}
-
-	std::size_t SQLite3Statement::get_number_of_columns() const {
-		return std::size_t( get_column_count() ) ;
-	}
-
-	std::string SQLite3Statement::get_name_of_column( std::size_t i ) const {
-		assert( m_statement != 0 ) ;
-		assert( i < get_number_of_columns() ) ;
-		return std::string( sqlite3_column_origin_name( m_statement, i )) ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind( std::size_t i, int32_t value ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_int( m_statement, i, value ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind( std::size_t i, uint32_t value ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_int( m_statement, i, value ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind( std::size_t i, int64_t value ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_int64( m_statement, i, sqlite3_int64( value ) ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind( std::size_t i, uint64_t value ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_int64( m_statement, i, sqlite3_int64( value ) ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind( std::size_t i, double value ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_double( m_statement, i, value ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind( std::size_t i, std::string const& value ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_text( m_statement, i, value.c_str(), value.size(), SQLITE_TRANSIENT ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind( std::size_t i, char const* buffer, char const* const end ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_blob( m_statement, i, reinterpret_cast< void const* >( buffer ), int( end - buffer ), SQLITE_TRANSIENT ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind( std::size_t i, uint8_t const* buffer, uint8_t const* const end ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_blob( m_statement, i, reinterpret_cast< void const* >( buffer ), int( end - buffer ), SQLITE_TRANSIENT ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::bind_NULL( std::size_t i ) {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_bind_null( m_statement, i ) ;
-		if( error != SQLITE_OK ) {
-			throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
-		}
-		return *this ;
-	}
-
-	SQLite3Statement& SQLite3Statement::reset() {
-		assert( m_statement != 0 ) ;
-		int error = sqlite3_reset( m_statement ) ;
-		if( error != SQLITE_OK ) {
-			throw db::Error( "SQLite3Statement::reset()", m_connection->get_spec(), error ) ;
-		}
-		return *this ;
-	}
-
-	std::string SQLite3Statement::get_sql() const {
-		assert( m_statement != 0 ) ;
-		return std::string( sqlite3_sql( m_statement )) ;
-	}
-
-	bool SQLite3Statement::is_null( int column_id ) const {
-		return ( sqlite3_column_type( m_statement, column_id ) == SQLITE_NULL ) ;
-	}
-
-	int SQLite3Statement::get_column_int( int column_id ) const {
-		assert( m_statement != 0 ) ;
-		return sqlite3_column_int( m_statement, column_id ) ;
-	}
-
-	int64_t SQLite3Statement::get_column_int64( int column_id ) const {
-		assert( m_statement != 0 ) ;
-		return sqlite3_column_int64( m_statement, column_id ) ;
-	}
-
-	double SQLite3Statement::get_column_double( int column_id ) const {
-		assert( m_statement != 0 ) ;
-		return sqlite3_column_double( m_statement, column_id ) ;
-	}
-	
-	std::string SQLite3Statement::get_column_string( int column_id ) const {
-		assert( m_statement != 0 ) ;
-		return reinterpret_cast< char const * >( sqlite3_column_text( m_statement, column_id ) ) ;
-	}
-
-	char SQLite3Statement::get_column_char( int column_id ) const {
-		assert( m_statement != 0 ) ;
-		char const* p = reinterpret_cast< char const * >( sqlite3_column_text( m_statement, column_id )) ;
-		int bytes = sqlite3_column_bytes( m_statement, column_id ) ;
-		assert( bytes == 1 ) ;
-		return *p ;
-	}
-	
-	int SQLite3Statement::get_column_count() const {
-		assert( m_statement != 0 ) ;
-		return sqlite3_column_count( m_statement ) ;
-	}
-}

DELETED db/src/fill_SQL.cpp
Index: db/src/fill_SQL.cpp
==================================================================
--- db/src/fill_SQL.cpp
+++ db/src/fill_SQL.cpp
@@ -1,26 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <string>
-#include "db/fill_SQL.hpp"
-
-namespace db {
-	std::string fill_SQL( std::string SQL ) {
-		return SQL ;
-	}
-
-	std::string fill_SQL( std::string SQL, std::string const& value1 ) {
-		std::size_t pos = SQL.find( "%s" ) ;
-		assert( pos != std::string::npos ) ;
-		SQL.replace( pos, 2, "\"" + value1 + "\"" ) ;
-		return SQL ;
-	}
-
-	std::string fill_SQL( std::string SQL, char const* value1 ) {
-		return fill_SQL( SQL, std::string( value1 )) ;
-	}
-}
-

DELETED db/src/get_unique_id.cpp
Index: db/src/get_unique_id.cpp
==================================================================
--- db/src/get_unique_id.cpp
+++ db/src/get_unique_id.cpp
@@ -1,31 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
-#include "db/get_unique_id.hpp"
-#include "genfile/Error.hpp"
-
-namespace db {
-	int get_unique_id(
-		Connection* connection,
-		std::string const& table,
-		std::string const& id_column,
-		std::string const& where_clause
-	) {
-		db::Connection::StatementPtr statement = connection->get_statement(
-			"SELECT " + id_column + " FROM " + table + " " + where_clause + ";"
-		) ;
-		if( !statement->step() ) {
-			throw genfile::DuplicateKeyError( "db::get_unique_id()", connection->get_spec() + ", <where clause> = \"" + where_clause + "\"" ) ;
-		}
-		int result = statement->get_column< int >( 0 ) ;
-		if( statement->step() ) {
-			throw genfile::DuplicateKeyError( "db::get_unique_id()", connection->get_spec() + ", <where clause> = \"" + where_clause + "\"" ) ;
-		}
-		return result ;
-	}
-}

DELETED db/test/test_case.hpp
Index: db/test/test_case.hpp
==================================================================
--- db/test/test_case.hpp
+++ db/test/test_case.hpp
@@ -1,30 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef CASE_CONTROL_TOOLS_TEST_CASE_HPP
-#define CASE_CONTROL_TOOLS_TEST_CASE_HPP
-
-#include <cassert>
-#include "config/config.hpp"
-
-#if HAVE_BOOST_UNIT_TEST
-	#define BOOST_AUTO_TEST_MAIN
-	#include "boost/test/auto_unit_test.hpp"
-	#define AUTO_TEST_CASE( param ) BOOST_AUTO_TEST_CASE(param)
-	#define TEST_ASSERT( param ) BOOST_ASSERT( param )
-#else
-	#define AUTO_TEST_CASE( param ) void param()
-	#define TEST_ASSERT( param ) assert( param )
-#endif	
-
-
-#ifdef HAVE_BOOST_UNIT_TEST
-#define AUTO_TEST_MAIN void dummy_func()
-#else
-#define AUTO_TEST_MAIN int main( int argc, char** argv )
-#endif
-
-#endif

DELETED db/test/test_fill_SQL.cpp
Index: db/test/test_fill_SQL.cpp
==================================================================
--- db/test/test_fill_SQL.cpp
+++ db/test/test_fill_SQL.cpp
@@ -1,29 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <iostream>
-#include "test_case.hpp"
-#include "db/fill_SQL.hpp"
-
-AUTO_TEST_CASE( test_fill_SQL ) {
-	std::cerr << "test_fill_SQL()..." ;
-	
-	TEST_ASSERT( db::fill_SQL( "" ) == "" ) ;
-	TEST_ASSERT( db::fill_SQL( "A string" ) == "A string" ) ;
-	TEST_ASSERT( db::fill_SQL( "%s", "hello" ) == "\"hello\"" ) ;
-	TEST_ASSERT( db::fill_SQL( "%s", 5 ) == "5" ) ;
-	TEST_ASSERT( db::fill_SQL( "%s", 5.56 ) == "5.56" ) ;
-
-	TEST_ASSERT( db::fill_SQL( "%s %s", "hello", "goodbye" ) == "\"hello\" \"goodbye\"" ) ;
-	TEST_ASSERT( db::fill_SQL( "%s %s", "hello", 0 ) == "\"hello\" 0" ) ;
-	TEST_ASSERT( db::fill_SQL( "%s %s", 4, 0 ) == "4 0" ) ;
-	TEST_ASSERT( db::fill_SQL( "%s%s", 4, "doof" ) == "4\"doof\"" ) ;
-	std::cerr << "success.\n" ;
-}
-
-AUTO_TEST_MAIN {
-	test_fill_SQL() ;
-}

DELETED db/test/test_get_unique_id.cpp
Index: db/test/test_get_unique_id.cpp
==================================================================
--- db/test/test_get_unique_id.cpp
+++ db/test/test_get_unique_id.cpp
@@ -1,74 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <iostream>
-#include <sstream>
-#include "test_case.hpp"
-#include "sqlite3/sqlite3.h"
-#include "genfile/Error.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLite3Connection.hpp"
-#include "db/SQLite3Statement.hpp"
-#include "db/Connection.hpp"
-#include "db/get_unique_id.hpp"
-
-AUTO_TEST_CASE( test_get_unique_id ) {
-	std::cerr << "test_get_unique_id()\n" ;
-	db::Connection::UniquePtr connection( new db::SQLite3Connection( ":memory:" )) ;
-	typedef db::Connection::StatementPtr StatementPtr ;
-	
-	// Construct a table
-	{
-		StatementPtr statement = connection->get_statement(
-			"CREATE TABLE Fields ( id INT, value INT ) ;"
-		) ;
-		statement->step() ;
-	}
-	
-	{
-		StatementPtr statement = connection->get_statement(
-			"INSERT INTO Fields VALUES( ?1, ?2 ) ;"
-		) ;
-		
-		for( uint64_t i = 0; i < 10; ++i ) {
-			statement->reset() ;
-			statement->bind( 1, i ) ;
-			statement->bind( 2, i*2 ) ;
-			TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
-		}
-
-		// make a duplicate key with value 10
-		statement->reset() ;
-		statement->bind( 1, 99 ) ;
-		statement->bind( 2, 10 ) ;
-		TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
-	}
-	
-	for( std::size_t value = 0; value < 20; ++value ) {
-		try {
-			std::ostringstream ostr ;
-			ostr << "WHERE value == " << value ;
-			int id = db::get_unique_id( connection.get(), "Fields", "id", ostr.str() ) ;
-			std::cerr << "value " << value << " found id " << id << ".\n" ;
-			TEST_ASSERT( value % 2 == 0 ) ;
-			TEST_ASSERT( id == int( value )/2 ) ;
-			TEST_ASSERT( id != 5 ) ;
-		}
-		catch( genfile::KeyNotFoundError const& e ) {
-			TEST_ASSERT( value % 2 == 1 ) ;
-			std::cerr << "value " << value << " found no ids.\n" ;
-		}
-		catch( genfile::DuplicateKeyError const& e ) {
-			TEST_ASSERT( value == 10 ) ;
-			std::cerr << "value " << value << " found duplicate ids.\n" ;
-		}
-	}
-	std::cerr << "success.\n" ;
-}
-
-AUTO_TEST_MAIN {
-	test_get_unique_id() ;
-}

DELETED db/test/test_load_key_value_pairs.cpp
Index: db/test/test_load_key_value_pairs.cpp
==================================================================
--- db/test/test_load_key_value_pairs.cpp
+++ db/test/test_load_key_value_pairs.cpp
@@ -1,100 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <iostream>
-#include <sstream>
-#include "test_case.hpp"
-#include "sqlite3/sqlite3.h"
-#include "db/Connection.hpp"
-#include "db/SQLite3Connection.hpp"
-#include "db/SQLite3Statement.hpp"
-#include "db/Connection.hpp"
-#include "db/load_key_value_pairs.hpp"
-
-AUTO_TEST_CASE( test_load_key_value_pairs ) {
-	std::cerr << "test_load_key_value_pairs()\n" ;
-	db::Connection::UniquePtr connection( new db::SQLite3Connection( ":memory:" )) ;
-	typedef db::Connection::StatementPtr StatementPtr ;
-	
-	// Construct a table
-	{
-		StatementPtr statement = connection->get_statement(
-			"CREATE TABLE KeyValue ( key TEXT, value TEXT ) ;"
-		) ;
-		TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
-	}
-	
-	{
-		StatementPtr statement = connection->get_statement(
-			"INSERT INTO KeyValue VALUES( ?1, ?2 ) ;"
-		) ;
-		
-		for( std::size_t i = 0; i < 10; ++i ) {
-			statement->reset() ;
-			std::string key( i, 'x' ) ;
-			std::string value( i*2, '*' ) ;
-			statement->bind( 1, key ) ;
-			statement->bind( 2, value ) ;
-			TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
-		}
-	}
-	typedef std::map< std::string, std::string > Map ;
-	Map values = db::load_key_value_pairs< std::string, std::string >( connection, "KeyValue", "key", "value" ) ;
-	TEST_ASSERT( values.size() == 10 ) ;
-	for( std::size_t i = 0; i < 10; ++i ) {
-		Map::const_iterator where = values.find( std::string( i, 'x' ) ) ;
-		TEST_ASSERT( where != values.end() ) ;
-		TEST_ASSERT( where->second == std::string( i*2, '*' )) ;
-	}
-
-	std::cerr << "success.\n" ;
-}
-
-AUTO_TEST_CASE( test_load_key_value_pairs_duplicates ) {
-	std::cerr << "test_load_key_value_pairs_duplicates()\n" ;
-	db::Connection::UniquePtr connection( new db::SQLite3Connection( ":memory:" )) ;
-	typedef db::Connection::StatementPtr StatementPtr ;
-	// Construct a table
-	{
-		StatementPtr statement = connection->get_statement(
-			"CREATE TABLE KeyValue ( key TEXT, value TEXT ) ;"
-		) ;
-		TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
-	}
-	
-	{
-		StatementPtr statement = connection->get_statement(
-			"INSERT INTO KeyValue VALUES( ?1, ?2 ) ;"
-		) ;
-		
-		for( std::size_t i = 0; i < 10; ++i ) {
-			statement->reset() ;
-			statement->bind( 1, std::string( i, 'x' ) ) ;
-			statement->bind( 2, std::string( i*2, '*' )) ;
-			TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
-		}
-		
-		statement->reset() ;
-		statement->bind( 1, std::string( 1, 'x' )) ;
-		TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
-	}
-
-	try {
-		std::map< std::string, std::string > values = db::load_key_value_pairs< std::string, std::string >( connection, "KeyValue", "key", "value" ) ;
-		TEST_ASSERT( 0 ) ;
-	}
-	catch( genfile::DuplicateKeyError const& e ) {
-		// as expected.
-	}
-	std::cerr << "success.\n" ;
-}
-
-
-AUTO_TEST_MAIN {
-	test_load_key_value_pairs() ;
-	test_load_key_value_pairs_duplicates() ;
-}
-

DELETED db/wscript
Index: db/wscript
==================================================================
--- db/wscript
+++ db/wscript
@@ -1,49 +0,0 @@
-import os.path
-import glob
-#import UnitTest
-
-def configure( conf ):
-	pass
-
-def create_test( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = [  'test/' + name + '.cpp' ],
-		uselib_local = 'db',
-		uselib = 'BOOST_THREAD PTHREAD BOOST_DATE_TIME BOOST_IOSTREAMS BOOST_UNIT_TEST_FRAMEWORK DL ZLIB',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
-def create_benchmark( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = [  'benchmarks/' + name + '.cpp' ],
-		uselib_local = 'db',
-		includes='./include',
-		install_path=None
-	)
-
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld(
-		features = 'cxx cstaticlib',
-		target = 'db',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = 'BOOST_DATE_TIME ZLIB BOOST_IOSTREAMS ZLIB',
-		uselib_local = 'genfile sqlite3',
-		export_incdirs = './include'
-	)
-	
-	create_test( bld, "test_fill_SQL" ) ;
-	create_test( bld, "test_get_unique_id" ) ;
-	create_test( bld, "test_load_key_value_pairs" ) ;

DELETED doc/html/bingwa/example/cohort1.snptest
Index: doc/html/bingwa/example/cohort1.snptest
==================================================================
--- doc/html/bingwa/example/cohort1.snptest
+++ doc/html/bingwa/example/cohort1.snptest
@@ -1,212 +0,0 @@
-# Analysis: "SNPTEST analysis, started 2015-08-05 16:58:22"
-#  started: 2015-08-05 16:58:22
-# 
-# Analysis properties:
-#   -data cohort1.gen cohort1.sample (user-supplied)
-#   -frequentist add (user-supplied)
-#   -method newml (user-supplied)
-#   -o cohort1.snptest (user-supplied)
-#   -pheno bin2 (user-supplied)
-# 
-alternate_ids rsid chromosome position alleleA alleleB incorrectly_coded all_A all_B all_AA all_AB all_BB all_NULL all_total all_maf all_info all_impute_info cases_A cases_B cases_AA cases_AB cases_BB cases_NULL cases_total cases_maf cases_info cases_impute_info controls_A controls_B controls_AA controls_AB controls_BB controls_NULL controls_total controls_maf controls_info controls_impute_info frequentist_add_null_ll frequentist_add_alternative_ll frequentist_add_beta_1:add/bin2=1 frequentist_add_se_1 frequentist_add_wald_pvalue_1 frequentist_add_degrees_of_freedom frequentist_add_lrt_pvalue iterations model_fit_time comment
-INSERTION_1 RSID_1 NA 0 A AGTGCTA NA 0 0 0 0 0 499 499 NA 1 1 0 0 0 0 0 263 263 NA 1 1 0 0 0 0 0 236 236 NA 1 1 0 0 NA NA NA 1 1 1 0.000 frequentist_add:information_matrix_is_near_singular
-DELETION_1 RSID_2 NA 2 A - NA 0 0 24.189 149.192 325.619 3.98792e-13 499 0.197966 0.667255 0.667255 0 0 12.4794 78.491 172.03 -2.22045e-15 263 0.196673 0.664116 0.664116 0 0 11.7096 70.7013 153.589 3.33067e-15 236 0.199408 0.670709 0.670709 -345.15 -345.142 0.0237288 0.186739 0.898886 1 0.898888 2 0.000 NA
-SNPID_3 RSID_3 NA 3 A G NA 0 0 132.675 249.23 117.095 -5.59552e-14 499 0.484388 0.95128 0.95128 0 0 72.4474 133.936 56.6163 2.66454e-15 263 0.469903 0.952055 0.952055 0 0 60.2281 115.293 60.4785 -1.44329e-15 236 0.499469 0.950323 0.950323 -345.15 -344.658 -0.129094 0.13036 0.322032 1 0.321488 2 0.000 NA
-SNPID_4 RSID_4 NA 4 A G NA 0 0 26.8545 163.01 309.135 8.88178e-16 499 0.217154 0.949656 0.949656 0 0 15.9838 89.9278 157.088 5.32907e-15 263 0.23174 0.951081 0.951081 0 0 10.8707 73.0827 152.047 3.33067e-16 236 0.200899 0.947739 0.947739 -345.15 -344.444 -0.184503 0.155752 0.23618 1 0.234696 2 0.000 NA
-SNPID_5 RSID_5 NA 5 A G NA 0 0 190.116 230.709 78.1756 -1.12799e-13 499 0.387836 0.94137 0.94137 0 0 98.613 129.274 35.1129 -8.32667e-15 263 0.379277 0.943539 0.943539 0 0 91.5028 101.435 43.0627 2.55351e-15 236 0.397373 0.938951 0.938951 -345.15 -344.972 -0.0787883 0.132337 0.551603 1 0.551503 2 0.000 NA
-SNPID_6 RSID_6 NA 6 A G NA 0 0 101.813 253.837 143.35 -6.03961e-14 499 0.45838 0.971178 0.971178 0 0 46.4678 137.329 79.2033 1.55431e-15 263 0.437765 0.970415 0.970415 0 0 55.3452 116.508 64.1467 -1.08802e-14 236 0.481353 0.9719 0.9719 -345.15 -344.143 0.185912 0.13131 0.156827 1 0.155943 2 0.000 NA
-SNPID_7 RSID_7 NA 7 A G NA 0 0 89.4939 222.988 186.518 7.9492e-13 499 0.402782 0.951642 0.951642 0 0 45.8257 111.551 105.624 -3.10862e-15 263 0.386316 0.950049 0.950049 0 0 43.6682 111.438 80.8943 -5.88418e-15 236 0.421131 0.95324 0.95324 -345.15 -344.537 0.141613 0.128043 0.268735 1 0.268228 2 0.000 NA
-SNPID_8 RSID_8 NA 8 A G NA 0 0 2.12512 45.5001 451.375 -1.77636e-15 499 0.0498501 0.791922 0.791922 0 0 1.11462 22.8318 239.054 6.43929e-15 263 0.0476446 0.784521 0.784521 0 0 1.0105 22.6683 212.321 -7.77156e-16 236 0.0523079 0.799423 0.799423 -345.15 -345.081 0.118509 0.319442 0.710647 1 0.710729 2 0.000 NA
-SNPID_9 RSID_9 NA 9 A G NA 0 0 16.9371 152.49 329.57 0.003 499 0.186739 0.915575 0.915505 0 0 8.638 80.3213 174.038 0.003 263 0.185548 0.911474 0.91134 0 0 8.29912 72.169 155.532 1.77636e-15 236 0.188066 0.920096 0.920096 -345.153 -345.147 0.0182324 0.170524 0.914852 1 0.914858 2 0.010 NA
-SNPID_10 RSID_10 NA 10 A G NA 0 0 4.46361 471.162 23.3745 -7.95808e-13 499 0.481051 0.96536 0.96536 0 0 2.5386 250.56 9.9011 -1.79856e-14 263 0.486003 0.963896 0.963896 0 0 1.925 220.602 13.4734 1.55431e-14 236 0.475533 0.966987 0.966987 -345.15 -344.416 -0.566981 0.474446 0.232072 1 0.225798 2 0.000 NA
-SNPID_11 RSID_11 NA 11 A G NA 0 0 239.853 213.226 45.9203 -1.73195e-13 499 0.305678 0.954284 0.954284 0 0 123.475 116.491 23.0343 2.88658e-15 263 0.309048 0.954439 0.954439 0 0 116.379 96.7354 22.886 5.21805e-15 236 0.301922 0.954104 0.954104 -345.15 -345.118 0.0354461 0.141441 0.802118 1 0.802082 2 0.000 NA
-SNPID_12 RSID_12 NA 12 A G NA 0 0 18.607 161.95 318.443 -2.85993e-13 499 0.199563 0.904789 0.904789 0 0 10.6569 84.0969 168.246 1.31006e-14 263 0.200401 0.910607 0.910607 0 0 7.95011 77.8527 150.197 2.22045e-15 236 0.198629 0.898261 0.898261 -345.15 -345.147 -0.0124884 0.168351 0.940867 1 0.940862 2 0.000 NA
-SNPID_13 RSID_13 NA 13 A G NA 0 0 94.5306 272.777 131.692 -8.88178e-16 499 0.462764 0.93406 0.93406 0 0 50.3227 142.278 70.3993 5.55112e-16 263 0.461832 0.933487 0.933487 0 0 44.2079 130.499 61.2929 -6.88338e-15 236 0.463803 0.934698 0.934698 -345.15 -345.147 0.00949919 0.139179 0.945585 1 0.945585 2 0.000 NA
-SNPID_14 RSID_14 NA 14 A G NA 0 0 398.93 89.0229 11.0467 0 499 0.111339 0.815042 0.815042 0 0 200.107 54.749 8.14415 -1.11022e-15 263 0.135052 0.845267 0.845267 0 0 198.824 34.2739 2.90253 -6.66134e-16 236 0.0849131 0.761251 0.761251 -345.15 -341.616 0.576665 0.222292 0.00948179 1 0.00785395 3 0.000 NA
-SNPID_15 RSID_15 NA 15 A G NA 0 0 34.9834 176.834 287.183 1.69642e-13 499 0.247295 0.781208 0.781208 0 0 19.3005 95.0475 148.652 -2.55351e-15 263 0.254085 0.787439 0.787439 0 0 15.6829 81.7866 138.531 1.9984e-15 236 0.23973 0.773857 0.773857 -345.15 -344.983 -0.0931683 0.161715 0.564529 1 0.564193 2 0.000 no_comment
-SNPID_16 RSID_16 NA 16 A G NA 0 0 11.4698 137.352 350.176 0.00167696 499 0.160614 0.948553 0.94855 0 0 7.7719 73.1438 182.083 0.00167696 263 0.168609 0.948491 0.948484 0 0 3.69791 64.2086 168.094 7.32747e-15 236 0.151704 0.94857 0.94857 -345.151 -344.867 -0.135597 0.179982 0.451215 1 0.450447 2 0.000 NA
-SNPID_17 RSID_17 NA 17 A G NA 0 0 451.501 41.3625 6.13645 3.41949e-13 499 0.0537429 0.615868 0.615868 0 0 242.959 16.8111 3.22957 -1.85407e-14 263 0.0442401 0.525183 0.525183 0 0 208.542 24.5513 2.90688 -2.22045e-16 236 0.0643328 0.6855 0.6855 -345.15 -343.91 -0.500867 0.322925 0.120894 1 0.115314 2 0.000 NA
-SNPID_18 RSID_18 NA 18 A G NA 0 0 164.013 256.021 78.966 3.97016e-13 499 0.414783 0.975421 0.975421 0 0 83.1535 142.342 37.5049 8.43769e-15 263 0.413216 0.976287 0.976287 0 0 80.859 113.68 41.4611 7.21645e-15 236 0.41653 0.974457 0.974457 -345.15 -345.143 -0.0148653 0.134272 0.911846 1 0.911847 2 0.000 NA
-SNPID_19 RSID_19 NA 19 A G NA 0 0 4.99436 43.1979 450.808 -5.14255e-13 499 0.0532932 0.716886 0.716886 0 0 2.51254 28.0859 232.402 -5.44009e-15 263 0.0629487 0.766566 0.766566 0 0 2.48182 15.112 218.406 -9.99201e-16 236 0.0425331 0.635168 0.635168 -345.15 -343.925 -0.490123 0.320004 0.125617 1 0.117625 3 0.000 NA
-SNPID_20 RSID_20 NA 20 A G NA 0 0 35.4391 178.972 284.589 -1.72307e-13 499 0.25035 0.961892 0.961892 0 0 17.7406 97.8937 147.366 9.65894e-15 263 0.253564 0.962772 0.962772 0 0 17.6985 81.0779 137.224 7.77156e-15 236 0.246769 0.960889 0.960889 -345.15 -345.119 -0.0360049 0.14599 0.805198 1 0.80515 2 0.000 NA
-SNPID_21 RSID_21 NA 21 A G NA 0 0 450.121 44.991 3.88833 1.77636e-15 499 0.0528734 0.729862 0.729862 0 0 238.403 22.0865 2.51082 -1.66533e-15 263 0.0515364 0.723522 0.723522 0 0 211.718 22.9045 1.37751 4.996e-15 236 0.0543634 0.736559 0.736559 -345.15 -345.126 -0.06797 0.310761 0.826867 1 0.826906 2 0.000 NA
-SNPID_22 RSID_22 NA 22 A G NA 0 0 380.468 105.714 12.8185 1.14575e-13 499 0.131614 0.809885 0.809885 0 0 199.464 57.7431 5.79324 -8.77076e-15 263 0.131805 0.806431 0.806431 0 0 181.004 47.9708 7.0253 3.21965e-15 236 0.131401 0.813743 0.813743 -345.15 -345.149 0.00400163 0.199534 0.984 1 0.983998 1 0.000 NA
-SNPID_23 RSID_23 NA 23 A G NA 0 0 18.3807 136.589 344.03 -5.70211e-13 499 0.173698 0.922874 0.922874 0 0 9.1632 70.3924 183.444 -8.21565e-15 263 0.168667 0.924058 0.924058 0 0 9.2175 66.1968 160.586 -5.55112e-16 236 0.179305 0.921586 0.921586 -345.15 -345.048 0.07641 0.169877 0.652858 1 0.652901 2 0.000 NA
-SNPID_24 RSID_24 NA 24 A G NA 0 0 2.04158 25.8116 471.147 -5.86198e-14 499 0.0299546 0.661566 0.661566 0 0 1.13337 15.9187 245.948 -2.55351e-15 263 0.034573 0.696476 0.696476 0 0 0.908212 9.89292 225.199 -1.07692e-14 236 0.0248079 0.607188 0.607188 -345.15 -344.616 -0.443019 0.434353 0.307752 1 0.301648 2 0.000 NA
-SNPID_25 RSID_25 NA 25 A G NA 0 0 6.33985 116.287 376.373 -5.10703e-13 499 0.129225 0.867399 0.867399 0 0 2.74528 67.486 192.769 5.66214e-15 263 0.138739 0.879102 0.879102 0 0 3.59457 48.8012 183.604 -5.55112e-16 236 0.118624 0.852223 0.852223 -345.15 -344.61 -0.216309 0.208804 0.300227 1 0.298745 2 0.000 NA
-SNPID_26 RSID_26 NA 26 A G NA 0 0 389.229 98.71 11.0612 6.83897e-13 499 0.121075 0.779816 0.779816 0 0 207.856 48.4817 6.6627 9.32587e-15 263 0.117504 0.777655 0.777655 0 0 181.373 50.2283 4.39851 -2.66454e-15 236 0.125054 0.782037 0.782037 -345.15 -345.071 -0.0833705 0.210626 0.692236 1 0.69228 2 0.000 NA
-SNPID_27 RSID_27 NA 27 A G NA 0 0 32.4957 173.091 293.413 -2.83329e-13 499 0.238559 0.863362 0.863362 0 0 17.0852 86.9914 158.923 -1.39888e-14 263 0.230346 0.860539 0.860539 0 0 15.4104 86.0995 134.49 5.55112e-16 236 0.247713 0.866238 0.866238 -345.15 -344.922 0.105175 0.156059 0.500347 1 0.500249 2 0.000 NA
-SNPID_28 RSID_28 NA 28 A G NA 0 0 29.8306 189.77 279.4 -1.7053e-13 499 0.249931 0.955836 0.955836 0 0 17.9189 97.8979 147.183 2.22045e-16 263 0.25425 0.957832 0.957832 0 0 11.9117 91.8719 132.216 -5.21805e-15 236 0.245117 0.953546 0.953546 -345.15 -345.091 -0.0517992 0.151073 0.731693 1 0.731595 2 0.000 NA
-SNPID_29 RSID_29 NA 29 A G NA 0 0 2.04361 8.05274 488.904 5.86198e-14 499 0.0121643 0.157274 0.157274 0 0 1.12943 4.05417 257.816 -4.996e-15 263 0.012002 0.120355 0.120355 0 0 0.914178 3.99857 231.087 8.65974e-15 236 0.0123452 0.197283 0.197283 -345.15 -345.147 0.0585841 0.82941 0.943689 1 0.943639 2 0.000 NA
-SNPID_30 RSID_30 NA 30 A G NA 0 0 14.0768 120.789 364.134 3.97016e-13 499 0.149241 0.821309 0.821309 0 0 8.5446 62.3331 192.122 -5.32907e-15 263 0.150993 0.819207 0.819207 0 0 5.53219 58.4558 172.012 4.77396e-15 236 0.147288 0.823691 0.823691 -345.15 -345.134 -0.0336129 0.191046 0.86034 1 0.860308 2 0.010 NA
-SNPID_31 RSID_31 NA 31 A G NA 0 0 36.1516 183.221 279.627 -3.41061e-13 499 0.256036 0.924252 0.924252 0 0 18.6942 94.7463 149.559 6.55032e-15 263 0.251207 0.922502 0.922502 0 0 17.4575 88.4747 130.068 1.44329e-15 236 0.261419 0.92613 0.92613 -345.15 -345.079 0.0557871 0.148171 0.706542 1 0.706555 2 0.000 NA
-SNPID_32 RSID_32 NA 32 A G NA 0 0 3.96944 74.6955 420.335 1.77636e-15 499 0.0828 0.825421 0.825421 0 0 2.52025 39.0391 221.441 1.52101e-14 263 0.0838015 0.828848 0.828848 0 0 1.44919 35.6564 198.894 3.33067e-15 236 0.0816839 0.821507 0.821507 -345.15 -345.141 -0.0332334 0.251274 0.894779 1 0.894748 2 0.000 NA
-SNPID_33 RSID_33 NA 33 A G NA 0 0 1.77848 43.255 453.967 -1.13687e-13 499 0.0469058 0.813575 0.813575 0 0 0.965375 29.6092 232.425 9.65894e-15 263 0.059962 0.850286 0.850286 0 0 0.813108 13.6458 221.541 2.22045e-15 236 0.0323559 0.737532 0.737532 -345.15 -342.571 -0.768478 0.349676 0.0279714 1 0.0231515 3 0.000 NA
-SNPID_34 RSID_34 NA 34 A G NA 0 0 3.25594 438.018 57.7265 -3.41061e-13 499 0.44542 0.967559 0.967559 0 0 1.74386 238.698 22.5586 3.66374e-15 263 0.460428 0.968216 0.968216 0 0 1.51209 199.32 35.1678 6.32827e-15 236 0.428695 0.966746 0.966746 -345.15 -342.482 -0.68216 0.300513 0.0232083 1 0.0209094 2 0.000 NA
-SNPID_35 RSID_35 NA 35 A G NA 0 0 219.511 221.85 57.6386 -1.72307e-13 499 0.337803 0.910178 0.910178 0 0 107.579 126.427 28.9944 -1.65423e-14 263 0.350599 0.914988 0.914988 0 0 111.932 95.4238 28.6442 4.21885e-15 236 0.323543 0.904443 0.904443 -345.15 -344.705 0.132406 0.140567 0.346224 1 0.345441 2 0.000 NA
-SNPID_36 RSID_36 NA 36 A G NA 0 0 122.928 256.936 119.136 -2.26485e-13 499 0.496201 0.86662 0.86662 0 0 60.8937 143.168 58.9388 2.44249e-15 263 0.496283 0.873152 0.873152 0 0 62.0343 113.768 60.1977 1.0103e-14 236 0.496109 0.859341 0.859341 -345.15 -345.15 0.000835632 0.138688 0.995193 1 0.995193 1 0.000 NA
-SNPID_37 RSID_37 NA 37 A G NA 0 0 109.398 222.491 167.111 9.69003e-13 499 0.442172 0.701896 0.701896 0 0 56.3134 118.969 87.7172 1.44329e-15 263 0.440297 0.697695 0.697695 0 0 53.0846 103.522 79.3935 2.22045e-16 236 0.444261 0.706558 0.706558 -345.15 -345.14 0.0201246 0.142857 0.887971 1 0.887971 2 0.000 NA
-SNPID_38 RSID_38 NA 38 A G NA 0 0 22.9221 165.166 310.912 -5.59552e-14 499 0.211433 0.946788 0.946788 0 0 14.0464 84.085 164.869 -3.55271e-15 263 0.213266 0.947386 0.947386 0 0 8.87577 81.0806 146.044 9.32587e-15 236 0.20939 0.946111 0.946111 -345.15 -345.138 -0.0243701 0.159028 0.878206 1 0.878187 2 0.000 NA
-SNPID_39 RSID_39 NA 39 A G NA 0 0 225.381 215.401 58.2186 7.9492e-13 499 0.332503 0.747196 0.747196 0 0 116.823 115.936 30.2411 6.99441e-15 263 0.335395 0.752892 0.752892 0 0 108.558 99.4648 27.9775 1.27676e-14 236 0.329279 0.740767 0.740767 -345.15 -345.123 0.035607 0.153015 0.815993 1 0.815961 2 0.000 NA
-SNPID_40 RSID_40 NA 40 A G NA 0 0 214.304 234.036 50.6594 -1.72307e-13 499 0.336027 0.96311 0.96311 0 0 115.684 120.416 26.9002 2.66454e-15 263 0.33121 0.962246 0.962246 0 0 98.6206 113.62 23.7592 5.55112e-15 236 0.341395 0.96405 0.96405 -345.15 -345.086 -0.0500398 0.140539 0.721799 1 0.721788 2 0.000 NA
-SNPID_41 RSID_41 NA 41 A G NA 0 0 11.432 95.6505 391.918 -4.56524e-13 499 0.118752 0.844489 0.844489 0 0 5.8343 45.9752 211.191 -4.32987e-15 263 0.109589 0.830542 0.830542 0 0 5.59765 49.6754 180.727 3.88578e-15 236 0.128963 0.857716 0.857716 -345.15 -344.67 0.199206 0.203628 0.327934 1 0.327266 2 0.000 NA
-SNPID_42 RSID_42 NA 42 A G NA 0 0 10.5012 463.569 24.9295 2.85993e-13 499 0.485543 0.914636 0.914636 0 0 5.69819 244.814 12.4876 1.65423e-14 263 0.487092 0.913144 0.913144 0 0 4.80298 218.755 12.4419 -2.44249e-15 236 0.483816 0.916297 0.916297 -345.15 -345.053 -0.236404 0.539028 0.66097 1 0.660617 2 0.000 NA
-SNPID_43 RSID_43 NA 43 A G NA 0 0 370.27 114.084 14.6456 -8.50875e-13 499 0.143663 0.869138 0.869138 0 0 196.334 56.7951 9.87068 -6.21725e-15 263 0.145507 0.865389 0.865389 0 0 173.936 57.2893 4.77487 -3.21965e-15 236 0.141608 0.873403 0.873403 -345.15 -345.133 0.0337134 0.186515 0.856561 1 0.856525 2 0.000 NA
-SNPID_44 RSID_44 NA 44 A G NA 0 0 271.034 194.786 33.1806 -4.53859e-13 499 0.26167 0.94813 0.94813 0 0 154.84 90.0764 18.0834 -1.44329e-15 263 0.240006 0.943888 0.943888 0 0 116.193 104.709 15.0972 -1.44329e-15 236 0.285813 0.952074 0.952074 -345.15 -343.708 -0.253373 0.149699 0.0905409 1 0.0895562 2 0.000 NA
-SNPID_45 RSID_45 NA 45 A G NA 0 0 21.4256 138.902 338.673 -2.84217e-13 499 0.182117 0.859297 0.859297 0 0 12.3931 67.7432 182.864 -4.996e-15 263 0.175912 0.849787 0.849787 0 0 9.03241 71.1584 155.809 -7.10543e-15 236 0.189032 0.869236 0.869236 -345.15 -344.994 0.0950931 0.170684 0.577439 1 0.577415 2 0.000 NA
-SNPID_46 RSID_46 NA 46 A G NA 0 0 378.168 110.043 10.7892 -7.93143e-13 499 0.131885 0.890722 0.890722 0 0 197.864 59.7038 5.43188 -9.76996e-15 263 0.134159 0.894596 0.894596 0 0 180.304 50.3388 5.35736 -1.17684e-14 236 0.129351 0.886257 0.886257 -345.15 -345.123 0.0453355 0.194814 0.815985 1 0.815903 2 0.000 NA
-SNPID_47 RSID_47 NA 47 A G NA 0 0 28.6027 141.171 329.227 -1.15463e-13 499 0.198773 0.841588 0.841588 0 0 18.0422 78.4527 166.505 -3.55271e-15 263 0.217751 0.843047 0.843047 0 0 10.5605 62.7178 162.722 -9.4369e-15 236 0.177624 0.838771 0.838771 -345.15 -343.825 -0.266459 0.164733 0.105767 1 0.103654 2 0.000 NA
-SNPID_48 RSID_48 NA 48 A G NA 0 0 2.71792 68.155 428.127 -1.69642e-13 499 0.0737383 0.881471 0.881471 0 0 1.88508 37.5661 223.549 2.66454e-15 263 0.078586 0.890614 0.890614 0 0 0.832845 30.5889 204.578 -5.55112e-16 236 0.0683361 0.86978 0.86978 -345.15 -344.932 -0.171219 0.260082 0.510326 1 0.509227 2 0.000 NA
-SNPID_49 RSID_49 NA 49 A G NA 0 0 10.5565 104.889 383.554 -5.12479e-13 499 0.126255 0.897015 0.897015 0 0 5.3983 54.5641 203.038 1.38778e-14 263 0.12426 0.89049 0.89049 0 0 5.15822 50.3253 180.516 -1.19904e-14 236 0.128478 0.904073 0.904073 -345.15 -345.128 0.0404486 0.196287 0.836738 1 0.836758 2 0.000 NA
-SNPID_50 RSID_50 NA 50 A G NA 0 0 435.209 55.2063 8.58466 8.53539e-13 499 0.0725206 0.491533 0.491533 0 0 231.246 26.8864 4.86737 -3.77476e-15 263 0.0696219 0.479348 0.479348 0 0 203.963 28.3199 3.71729 2.10942e-15 236 0.075751 0.503952 0.503952 -345.15 -345.046 -0.135902 0.298249 0.648631 1 0.648815 2 0.000 NA
-SNPID_51 RSID_51 NA 51 A G NA 0 0 45.9888 207.149 245.862 3.42837e-13 499 0.299726 0.956303 0.956303 0 0 27.9199 118.537 116.543 -5.44009e-15 263 0.331514 0.961682 0.961682 0 0 18.0689 88.6125 129.319 -9.4369e-15 236 0.264302 0.948936 0.948936 -345.15 -342.362 -0.335427 0.143237 0.0191929 1 0.0182131 2 0.010 NA
-SNPID_52 RSID_52 NA 52 A G NA 0 0 70.9124 184.814 243.273 -3.40172e-13 499 0.327294 0.484607 0.484607 0 0 32.9757 98.5512 131.473 3.21965e-15 263 0.312742 0.460767 0.460767 0 0 37.9368 86.2632 111.8 1.66533e-15 236 0.34351 0.508789 0.508789 -345.15 -344.321 0.216812 0.168912 0.199289 1 0.197956 2 0.000 NA
-SNPID_53 RSID_53 NA 53 A G NA 0 0 12.2881 115.938 370.774 3.97016e-13 499 0.140796 0.914012 0.914012 0 0 8.19383 69.303 185.503 3.44169e-15 263 0.16291 0.926006 0.926006 0 0 4.09422 46.6353 185.27 8.88178e-16 236 0.116152 0.895292 0.895292 -345.15 -342.763 -0.414413 0.192187 0.0310601 1 0.0288976 3 0.000 NA
-SNPID_54 RSID_54 NA 54 A G NA 0 0 28.6284 177.768 292.603 -4.53859e-13 499 0.235496 0.935266 0.935266 0 0 13.3815 99.6887 149.93 -7.21645e-15 263 0.240402 0.937523 0.937523 0 0 15.2469 78.0797 142.673 -7.77156e-16 236 0.230028 0.932652 0.932652 -345.15 -345.071 -0.0609933 0.15384 0.691756 1 0.691613 2 0.000 NA
-SNPID_55 RSID_55 NA 55 A G NA 0 0 55.0131 249.983 194.004 -2.27374e-13 499 0.360731 0.938494 0.938494 0 0 26.7145 132.018 104.268 1.04361e-14 263 0.35256 0.934858 0.934858 0 0 28.2986 117.966 89.7357 -4.996e-15 236 0.369837 0.94242 0.94242 -345.15 -344.961 0.0878743 0.143043 0.539003 1 0.538879 2 0.000 NA
-SNPID_56 RSID_56 NA 56 A G NA 0 0 152.764 250.077 96.1589 -1.13687e-13 499 0.443281 0.927092 0.927092 0 0 84.3408 134.338 44.3211 2.22045e-15 263 0.423917 0.927887 0.927887 0 0 68.4234 115.739 51.8378 6.66134e-15 236 0.464861 0.925964 0.925964 -345.15 -344.222 -0.182435 0.134205 0.17403 1 0.173113 2 0.000 NA
-SNPID_57 RSID_57 NA 57 A G NA 0 0 135.721 238.482 124.796 1.1191e-13 499 0.489053 0.841661 0.841661 0 0 69.7341 129.256 64.01 9.99201e-16 263 0.489118 0.839467 0.839467 0 0 65.9873 109.226 60.7863 -9.76996e-15 236 0.488981 0.844106 0.844106 -345.15 -345.15 0.000617904 0.134776 0.996342 1 0.996342 1 0.000 NA
-SNPID_58 RSID_58 NA 58 A G NA 0 0 290.455 171.039 37.5065 -3.41061e-13 499 0.246545 0.787094 0.787094 0 0 154.586 87.786 20.628 -3.33067e-16 263 0.245327 0.775488 0.775488 0 0 135.869 83.2527 16.8784 -7.77156e-15 236 0.247902 0.799934 0.799934 -345.15 -345.144 -0.0160065 0.158082 0.919348 1 0.919351 2 0.000 NA
-SNPID_59 RSID_59 NA 59 A G NA 0 0 154.893 264.453 79.6542 1.02496e-12 499 0.42461 0.961204 0.961204 0 0 85.0233 137.142 40.8349 -9.76996e-15 263 0.415992 0.960268 0.960268 0 0 69.8699 127.311 38.8193 1.88738e-15 236 0.434215 0.962209 0.962209 -345.15 -344.957 -0.085124 0.13711 0.534703 1 0.53452 2 0.000 NA
-SNPID_60 RSID_60 NA 60 A G NA 0 0 208.434 229.299 61.267 -6.23501e-13 499 0.352538 0.968078 0.968078 0 0 112.757 118.658 31.5852 1.11022e-16 263 0.345682 0.968947 0.968947 0 0 95.6771 110.641 29.6818 7.77156e-15 236 0.360179 0.967114 0.967114 -345.15 -345.031 -0.0660615 0.135361 0.625521 1 0.625476 2 0.010 NA
-SNPID_61 RSID_61 NA 61 A G NA 0 0 4.02962 462.53 32.4401 -7.96696e-13 499 0.471533 0.963466 0.963466 0 0 2.3099 244.08 16.6104 2.66454e-15 263 0.472813 0.963253 0.963253 0 0 1.71973 218.451 15.8297 -1.44329e-15 236 0.470106 0.963703 0.963703 -345.15 -345.114 -0.104483 0.393489 0.790601 1 0.790736 2 0.000 NA
-SNPID_62 RSID_62 NA 62 A G NA 0 0 41.0577 195.482 262.461 1.11022e-13 499 0.278153 0.95298 0.95298 0 0 25.0895 99.7121 138.198 1.25455e-14 263 0.284964 0.95225 0.95225 0 0 15.9682 95.7695 124.262 2.33147e-15 236 0.270563 0.953794 0.953794 -345.15 -345.018 -0.073453 0.14331 0.608268 1 0.608055 2 0.000 NA
-SNPID_63 RSID_63 NA 63 A G NA 0 0 315.18 150.312 33.5077 -2.85993e-13 499 0.217763 0.626352 0.626352 0 0 171.129 76.3955 15.4751 5.21805e-15 263 0.204079 0.591771 0.591771 0 0 144.051 73.9165 18.0325 8.88178e-16 236 0.233012 0.660454 0.660454 -345.15 -344.328 -0.228533 0.178738 0.20104 1 0.199929 2 0.000 NA
-SNPID_64 RSID_64 NA 64 A G NA 0 0 4.30075 23.1619 471.537 2.85105e-13 499 0.0318271 0.323411 0.323411 0 0 2.34393 11.9645 248.692 -5.9952e-15 263 0.0316585 0.313539 0.313539 0 0 1.95682 11.1974 222.846 -2.66454e-15 236 0.0320149 0.334292 0.334292 -345.15 -345.149 0.0202566 0.478016 0.966199 1 0.966197 1 0.000 NA
-SNPID_65 RSID_65 NA 65 A G NA 0 0 42.9049 162.932 293.163 2.27374e-13 499 0.249241 0.492273 0.492273 0 0 21.8454 84.6589 156.496 -1.55431e-15 263 0.244011 0.489758 0.489758 0 0 21.0595 78.2735 136.667 2.22045e-15 236 0.255069 0.494822 0.494822 -345.15 -345.018 0.0953618 0.186209 0.608565 1 0.608505 2 0.000 NA
-SNPID_66 RSID_66 NA 66 A G NA 0 0 174.93 234.09 89.9809 4.52971e-13 499 0.414881 0.96961 0.96961 0 0 93.0556 132.334 37.6107 -3.9968e-15 263 0.394592 0.968589 0.968589 0 0 81.8739 101.756 52.3701 -2.07612e-14 236 0.437492 0.970594 0.970594 -345.15 -344.209 -0.176456 0.128888 0.170978 1 0.170208 2 0.000 NA
-SNPID_67 RSID_67 NA 67 A G NA 0 0 202.723 221.45 74.827 1.7053e-13 499 0.371847 0.97414 0.97414 0 0 95.9585 126.622 40.4194 4.55191e-15 263 0.394412 0.97758 0.97758 0 0 106.765 94.8276 34.4076 -2.88658e-15 236 0.346701 0.969961 0.969961 -345.15 -343.962 0.200523 0.130543 0.12452 1 0.123323 2 0.000 NA
-SNPID_68 RSID_68 NA 68 A G NA 0 0 256.721 198.496 43.7823 6.86562e-13 499 0.286634 0.958211 0.958211 0 0 131.415 107.699 23.8858 3.66374e-15 263 0.295572 0.960532 0.960532 0 0 125.307 90.7969 19.8965 -2.55351e-15 236 0.276673 0.95548 0.95548 -345.15 -344.929 0.0939788 0.141572 0.506804 1 0.506399 2 0.000 NA
-SNPID_69 RSID_69 NA 69 A G NA 0 0 383.301 102.684 13.0148 3.39284e-13 499 0.128972 0.756111 0.756111 0 0 199.415 58.2653 5.3198 -8.10463e-15 263 0.130998 0.758079 0.758079 0 0 183.886 44.419 7.69505 -1.13243e-14 236 0.126714 0.753833 0.753833 -345.15 -345.125 0.0454248 0.206586 0.825962 1 0.825889 2 0.000 NA
-SNPID_70 RSID_70 NA 70 A G NA 0 0 333.001 149.111 16.8883 5.59552e-14 499 0.183254 0.943426 0.943426 0 0 174.972 81.1059 6.92194 -1.60982e-14 263 0.180513 0.944912 0.944912 0 0 158.029 68.0047 9.96631 3.77476e-15 236 0.186308 0.941803 0.941803 -345.15 -345.12 -0.0409498 0.168502 0.807987 1 0.808014 2 0.000 NA
-SNPID_71 RSID_71 NA 71 A G NA 0 0 60.1779 219.376 219.446 7.37188e-13 499 0.340412 0.970671 0.970671 0 0 32.7495 105.769 124.481 -5.77316e-15 263 0.325605 0.966556 0.966556 0 0 27.4285 113.606 94.9653 1.26565e-14 236 0.356914 0.974992 0.974992 -345.15 -344.602 0.140603 0.134501 0.295854 1 0.295445 2 0.000 NA
-SNPID_72 RSID_72 NA 72 A G NA 0 0 5.78095 90.7842 402.435 -1.14575e-13 499 0.102551 0.911341 0.911341 0 0 0.948292 55.333 206.719 1.11022e-16 263 0.108801 0.920352 0.920352 0 0 4.83266 35.4512 195.716 1.88738e-15 236 0.0955859 0.899982 0.899982 -345.15 -344.893 -0.156556 0.219042 0.474776 1 0.4736 2 0.000 NA
-SNPID_73 RSID_73 NA 73 A G NA 0 0 3.67769 14.8622 480.46 -1.71418e-13 499 0.0222621 0.164115 0.164115 0 0 2.06291 9.06502 251.872 1.07692e-14 263 0.0250776 0.216328 0.216328 0 0 1.61478 5.79721 228.588 -8.88178e-16 236 0.0191245 0.087447 0.087447 -345.15 -344.735 -0.562419 0.626937 0.369671 1 0.362671 2 0.000 NA
-SNPID_74 RSID_74 NA 74 A G NA 0 0 47.8052 205.372 245.823 -6.81233e-13 499 0.301585 0.957851 0.957851 0 0 20.0276 109.583 133.389 -1.55431e-15 263 0.284484 0.958982 0.958982 0 0 27.7776 95.7882 112.434 -3.66374e-15 236 0.320643 0.956539 0.956539 -345.15 -344.362 0.175145 0.139761 0.210143 1 0.209554 2 0.000 NA
-SNPID_75 RSID_75 NA 75 A G NA 0 0 4.28031 35.1062 459.613 5.77316e-14 499 0.0437544 0.502536 0.502536 0 0 2.28126 13.2162 247.502 1.26565e-14 263 0.0338 0.357398 0.357398 0 0 1.99905 21.89 212.111 1.06581e-14 236 0.0548476 0.602189 0.602189 -345.15 -343.141 0.778548 0.397789 0.0503255 1 0.0450228 3 0.000 NA
-SNPID_76 RSID_76 NA 76 A G NA 0 0 79.3374 236.147 183.516 3.97016e-13 499 0.395613 0.939498 0.939498 0 0 42.0987 125.802 95.099 1.24345e-14 263 0.399239 0.939158 0.939158 0 0 37.2387 110.344 88.417 -6.88338e-15 236 0.391571 0.939872 0.939872 -345.15 -345.117 -0.0337638 0.133063 0.799694 1 0.799674 2 0.000 NA
-SNPID_77 RSID_77 NA 77 A G NA 0 0 30.0759 194.379 274.545 6.03961e-14 499 0.255041 0.868221 0.868221 0 0 15.3727 97.2 150.427 7.99361e-15 263 0.243242 0.860652 0.860652 0 0 14.7031 97.1794 124.117 -5.10703e-15 236 0.26819 0.875912 0.875912 -345.15 -344.667 0.155705 0.158569 0.326132 1 0.325693 2 0.000 NA
-SNPID_78 RSID_78 NA 78 A G NA 0 0 5.59251 77.4675 415.94 3.40172e-13 499 0.0888302 0.856171 0.856171 0 0 4.25499 41.7848 216.96 1.9873e-14 263 0.0956175 0.871189 0.871189 0 0 1.33752 35.6827 198.98 -1.17684e-14 236 0.0812664 0.836579 0.836579 -345.15 -344.795 -0.199441 0.237694 0.401432 1 0.399543 2 0.000 NA
-SNPID_79 RSID_79 NA 79 A G NA 0 0 123 242.396 133.603 1.30829e-12 499 0.489376 0.958072 0.958072 0 0 70.41 126.156 66.4341 -1.59872e-14 263 0.492441 0.958294 0.958294 0 0 52.5904 116.24 67.1693 5.55112e-16 236 0.469112 0.957694 0.957694 -345.15 -344.403 -0.156315 0.128104 0.222381 1 0.221665 2 0.000 NA
-SNPID_80 RSID_80 NA 80 A G NA 0 0 352.963 131.602 14.4355 -5.64881e-13 499 0.160794 0.917058 0.917058 0 0 184.514 71.1996 7.28619 1.9984e-15 263 0.163065 0.919164 0.919164 0 0 168.449 60.4022 7.14926 9.21485e-15 236 0.158264 0.914646 0.914646 -345.15 -345.127 0.0378875 0.178205 0.831634 1 0.83158 2 0.000 NA
-SNPID_81 RSID_81 NA 81 A G NA 0 0 7.75453 25.9071 465.338 2.84217e-13 499 0.0414991 0.0909706 0.0909706 0 0 4.18702 14.5049 244.308 7.43849e-15 263 0.0434962 0.121368 0.121368 0 0 3.56751 11.4021 221.03 -5.32907e-15 236 0.0392736 0.0533922 0.0533922 -345.15 -345.023 -0.242475 0.482713 0.615445 1 0.61417 2 0.000 NA
-SNPID_82 RSID_82 NA 82 A G NA 0 0 5.03384 73.186 420.78 3.97904e-13 499 0.0834205 0.87844 0.87844 0 0 3.05006 40.6595 219.29 2.10942e-15 263 0.0888966 0.884089 0.884089 0 0 1.98377 32.5265 201.49 4.77396e-15 236 0.0773178 0.871172 0.871172 -345.15 -344.912 -0.16562 0.240729 0.491455 1 0.490243 2 0.000 NA
-SNPID_83 RSID_83 NA 83 A G NA 0 0 49.9623 207.108 241.93 9.07718e-13 499 0.307648 0.811033 0.811033 0 0 26.6987 108.549 127.752 -4.77396e-15 263 0.307884 0.811313 0.811313 0 0 23.2636 98.5584 114.178 -4.44089e-15 236 0.307385 0.81072 0.81072 -345.15 -345.149 -0.00279897 0.150187 0.985131 1 0.98513 1 0.000 NA
-SNPID_84 RSID_84 NA 84 A G NA 0 0 7.25407 55.1109 436.635 3.41061e-13 499 0.0697585 0.548088 0.548088 0 0 4.04587 30.5152 228.439 3.44169e-15 263 0.0733973 0.595355 0.595355 0 0 3.2082 24.5956 208.196 1.34337e-14 236 0.0657035 0.4895 0.4895 -345.15 -344.985 -0.172722 0.302333 0.567798 1 0.566082 2 0.000 NA
-SNPID_85 RSID_85 NA 85 A G NA 0 0 30.4057 153.993 314.601 -2.28262e-13 499 0.215235 0.78537 0.78537 0 0 17.2673 85.1856 160.547 7.99361e-15 263 0.227605 0.801112 0.801112 0 0 13.1384 68.8077 154.054 1.55431e-15 236 0.20145 0.765717 0.765717 -345.15 -344.57 -0.178644 0.166352 0.282869 1 0.281488 2 0.000 NA
-SNPID_86 RSID_86 NA 86 A G NA 0 0 280.014 200.449 18.5373 -5.68434e-14 499 0.237999 0.962523 0.962523 0 0 150.47 105.655 6.87469 2.22045e-15 263 0.227005 0.960999 0.960999 0 0 129.544 94.7932 11.6626 4.44089e-15 236 0.250251 0.964054 0.964054 -345.15 -344.716 -0.149891 0.16111 0.352182 1 0.351897 2 0.000 NA
-SNPID_87 RSID_87 NA 87 A G NA 0 0 10.7972 27.3004 460.902 1.13687e-13 499 0.0489927 -0.0793418 -0.0793418 0 0 5.16898 17.3642 240.467 1.78746e-14 263 0.0526658 0.0683742 0.0683742 0 0 5.62818 9.93614 220.436 6.66134e-16 236 0.0448994 -0.271662 -0.271662 -345.15 -344.591 -0.618216 0.622039 0.320294 1 0.290369 3 0.000 NA
-SNPID_88 RSID_88 NA 88 A G NA 0 0 283.091 176.551 39.3585 6.83009e-13 499 0.25578 0.873735 0.873735 0 0 151.392 89.8276 21.7805 -4.996e-15 263 0.253591 0.873196 0.873196 0 0 131.699 86.7233 17.578 4.996e-15 236 0.258219 0.874321 0.874321 -345.15 -345.135 -0.0257402 0.149505 0.863305 1 0.863312 2 0.000 NA
-SNPID_89 RSID_89 NA 89 A G NA 0 0 83.3966 244.912 170.692 8.88178e-16 499 0.41253 0.935987 0.935987 0 0 42.2659 134.783 85.9513 6.66134e-15 263 0.416948 0.940414 0.940414 0 0 41.1307 110.129 84.7403 3.9968e-15 236 0.407607 0.931008 0.931008 -345.15 -345.101 -0.0417785 0.134119 0.755418 1 0.755374 2 0.000 NA
-SNPID_90 RSID_90 NA 90 A G NA 0 0 2.72756 48.2504 448.022 5.68434e-14 499 0.0538131 0.840918 0.840918 0 0 0.901519 27.6031 234.495 1.14353e-14 263 0.0559053 0.848409 0.848409 0 0 1.82604 20.6473 213.527 -4.77396e-15 236 0.0514817 0.831861 0.831861 -345.15 -345.096 -0.097798 0.298694 0.743351 1 0.743013 2 0.000 NA
-SNPID_91 RSID_91 NA 91 A G NA 0 0 186.673 233.146 79.1804 -7.38964e-13 499 0.392292 0.968208 0.968208 0 0 104.725 115.618 42.6567 -1.18794e-14 263 0.381999 0.968062 0.968062 0 0 81.9482 117.528 36.5237 4.32987e-15 236 0.403762 0.968335 0.968335 -345.15 -344.9 -0.092384 0.13069 0.479634 1 0.479472 2 0.010 NA
-SNPID_92 RSID_92 NA 92 A G NA 0 0 11.6764 111.738 375.586 -2.27374e-13 499 0.135361 0.933518 0.933518 0 0 2.94484 60.3411 199.714 4.21885e-15 263 0.125914 0.927197 0.927197 0 0 8.73156 51.3966 175.872 -4.21885e-15 236 0.145889 0.939627 0.939627 -345.15 -344.716 0.174559 0.187618 0.352167 1 0.351726 2 0.000 NA
-SNPID_93 RSID_93 NA 93 A G NA 0 0 476.905 18.7684 3.32642 1.12799e-13 499 0.0254722 0.358089 0.358089 0 0 250.905 10.3304 1.7642 2.88658e-15 263 0.0263476 0.385756 0.385756 0 0 226 8.43798 1.56223 -1.19904e-14 236 0.0244967 0.324942 0.324942 -345.15 -345.121 0.124894 0.522287 0.811005 1 0.810638 2 0.000 NA
-SNPID_94 RSID_94 NA 94 A G NA 0 0 407.8 75.9678 15.2326 -5.68434e-13 499 0.106646 0.488191 0.488191 0 0 213.02 41.7899 8.19023 5.44009e-15 263 0.11059 0.557934 0.557934 0 0 194.78 34.1778 7.04234 1.9984e-15 236 0.102251 0.404706 0.404706 -345.15 -345.016 0.129748 0.251806 0.606365 1 0.604677 2 0.000 NA
-SNPID_95 RSID_95 NA 95 A G NA 0 0 51.3608 205.563 242.076 1.13687e-13 499 0.308903 0.967178 0.967178 0 0 24.7848 110.801 127.414 -5.44009e-15 263 0.304888 0.968669 0.968669 0 0 26.576 94.7619 114.662 3.88578e-15 236 0.313377 0.965536 0.965536 -345.15 -345.108 0.0396671 0.13704 0.772232 1 0.772243 2 0.000 NA
-SNPID_96 RSID_96 NA 96 A G NA 0 0 72.3532 214.009 212.638 -2.84217e-13 499 0.359434 0.630886 0.630886 0 0 38.0019 117.45 107.548 1.11022e-15 263 0.367783 0.654174 0.654174 0 0 34.3513 96.5588 105.09 -1.59872e-14 236 0.35013 0.604099 0.604099 -345.15 -344.908 -0.11025 0.158778 0.487452 1 0.486787 2 0.000 NA
-SNPID_97 RSID_97 NA 97 A G NA 0 0 31.7916 163.821 303.388 5.13367e-13 499 0.22786 0.772555 0.772555 0 0 17.7433 80.6342 164.622 1.9984e-15 263 0.220762 0.760396 0.760396 0 0 14.0483 83.1865 138.765 1.15463e-14 236 0.235769 0.785342 0.785342 -345.15 -344.96 0.101498 0.164964 0.538372 1 0.53821 2 0.000 NA
-SNPID_98 RSID_98 NA 98 A G NA 0 0 280.655 195.595 22.7491 3.40172e-13 499 0.241577 0.960102 0.960102 0 0 147.28 107.746 7.9743 1.0103e-14 263 0.235161 0.959961 0.959961 0 0 133.376 87.8495 14.7748 4.88498e-15 236 0.248727 0.960232 0.960232 -345.15 -345.009 -0.0831245 0.156942 0.596355 1 0.596337 2 0.000 NA
-SNPID_99 RSID_99 NA 99 A G NA 0 0 4.41342 58.4045 436.182 1.72307e-13 499 0.0673661 0.745416 0.745416 0 0 2.815 33.1024 227.083 2.22045e-16 263 0.0736359 0.763926 0.763926 0 0 1.59842 25.3021 209.1 6.43929e-15 236 0.0603791 0.720199 0.720199 -345.15 -344.72 -0.261445 0.283461 0.356356 1 0.354011 2 0.000 NA
-SNPID_100 RSID_100 NA 100 A G NA 0 0 84.1983 255.126 159.676 1.14575e-13 499 0.424371 0.847278 0.847278 0 0 41.4306 136.537 85.0326 -8.10463e-15 263 0.417106 0.84989 0.84989 0 0 42.7677 118.589 74.6433 2.22045e-16 236 0.432467 0.844316 0.844316 -345.15 -345 0.0785739 0.143458 0.583888 1 0.58376 2 0.000 NA
-SNPID_101 RSID_101 NA 101 A G NA 0 0 87.8791 240.242 170.879 7.38076e-13 499 0.416833 0.974429 0.974429 0 0 48.4909 126.582 87.927 -1.60982e-14 263 0.425026 0.974791 0.974791 0 0 39.3882 113.66 82.9523 9.65894e-15 236 0.407703 0.974003 0.974003 -345.15 -344.994 -0.0724705 0.129757 0.576497 1 0.576327 2 0.000 NA
-SNPID_102 RSID_102 NA 102 A G NA 0 0 325.619 149.192 24.189 -9.63674e-13 499 0.197966 0.667255 0.667255 0 0 172.03 78.491 12.4794 -2.22045e-15 263 0.196673 0.664116 0.664116 0 0 153.589 70.7013 11.7096 -3.77476e-15 236 0.199408 0.670709 0.670709 -345.15 -345.142 -0.0237288 0.186739 0.898886 1 0.898888 2 0.000 NA
-SNPID_103 RSID_103 NA 103 A G NA 0 0 117.095 249.23 132.675 -4.53859e-13 499 0.484388 0.95128 0.95128 0 0 56.6163 133.936 72.4474 5.88418e-15 263 0.469903 0.952055 0.952055 0 0 60.4785 115.293 60.2281 -9.76996e-15 236 0.499469 0.950323 0.950323 -345.15 -344.658 0.129094 0.13036 0.322032 1 0.321488 2 0.000 NA
-SNPID_104 RSID_104 NA 104 A G NA 0 0 309.135 163.01 26.8545 -1.3074e-12 499 0.217154 0.949656 0.949656 0 0 157.088 89.9278 15.9838 1.0103e-14 263 0.23174 0.951081 0.951081 0 0 152.047 73.0827 10.8707 -5.55112e-16 236 0.200899 0.947739 0.947739 -345.15 -344.444 0.184503 0.155752 0.23618 1 0.234696 2 0.000 NA
-SNPID_105 RSID_105 NA 105 A G NA 0 0 78.1756 230.709 190.116 -6.81233e-13 499 0.387836 0.94137 0.94137 0 0 35.1129 129.274 98.613 -6.55032e-15 263 0.379277 0.943539 0.943539 0 0 43.0627 101.435 91.5028 1.33227e-15 236 0.397373 0.938951 0.938951 -345.15 -344.972 0.0787883 0.132337 0.551603 1 0.551503 2 0.000 NA
-SNPID_106 RSID_106 NA 106 A G NA 0 0 143.35 253.837 101.813 6.80345e-13 499 0.45838 0.971178 0.971178 0 0 79.2033 137.329 46.4678 -4.55191e-15 263 0.437765 0.970415 0.970415 0 0 64.1467 116.508 55.3452 -9.99201e-15 236 0.481353 0.9719 0.9719 -345.15 -344.143 -0.185912 0.13131 0.156827 1 0.155943 2 0.000 NA
-SNPID_107 RSID_107 NA 107 A G NA 0 0 186.518 222.988 89.4939 -1.13687e-13 499 0.402782 0.951642 0.951642 0 0 105.624 111.551 45.8257 -1.11022e-15 263 0.386316 0.950049 0.950049 0 0 80.8943 111.438 43.6682 -3.44169e-15 236 0.421131 0.95324 0.95324 -345.15 -344.537 -0.141613 0.128043 0.268735 1 0.268228 2 0.000 NA
-SNPID_108 RSID_108 NA 108 A G NA 0 0 451.375 45.5001 2.12512 -6.84786e-13 499 0.0498501 0.791922 0.791922 0 0 239.054 22.8318 1.11462 1.03251e-14 263 0.0476446 0.784521 0.784521 0 0 212.321 22.6683 1.0105 -3.88578e-15 236 0.0523079 0.799423 0.799423 -345.15 -345.081 -0.118509 0.319442 0.710647 1 0.710729 2 0.000 NA
-SNPID_109 RSID_109 NA 109 A G NA 0 0 329.57 152.49 16.9401 1.25056e-12 499 0.186744 0.915506 0.915506 0 0 174.038 80.3213 8.641 1.5099e-14 263 0.185558 0.911343 0.911343 0 0 155.532 72.169 8.29912 -4.44089e-16 236 0.188066 0.920096 0.920096 -345.15 -345.144 -0.0181504 0.170526 0.915235 1 0.91524 2 0.000 NA
-SNPID_110 RSID_110 NA 110 A G NA 0 0 23.3745 471.162 4.46361 -7.38076e-13 499 0.481051 0.96536 0.96536 0 0 9.9011 250.56 2.5386 -1.5099e-14 263 0.486003 0.963896 0.963896 0 0 13.4734 220.602 1.925 1.22125e-14 236 0.475533 0.966987 0.966987 -345.15 -344.416 0.566981 0.474446 0.232072 1 0.225798 2 0.000 NA
-SNPID_111 RSID_111 NA 111 A G NA 0 0 45.9203 213.226 239.853 5.50671e-14 499 0.305678 0.954284 0.954284 0 0 23.0343 116.491 123.475 1.23235e-14 263 0.309048 0.954439 0.954439 0 0 22.886 96.7354 116.379 4.44089e-16 236 0.301922 0.954104 0.954104 -345.15 -345.118 -0.0354461 0.141441 0.802118 1 0.802082 2 0.000 NA
-SNPID_112 RSID_112 NA 112 A G NA 0 0 318.443 161.95 18.607 -5.9508e-14 499 0.199563 0.904789 0.904789 0 0 168.246 84.0969 10.6569 9.76996e-15 263 0.200401 0.910607 0.910607 0 0 150.197 77.8527 7.95011 3.33067e-15 236 0.198629 0.898261 0.898261 -345.15 -345.147 0.0124884 0.168351 0.940867 1 0.940862 2 0.000 NA
-SNPID_113 RSID_113 NA 113 A G NA 0 0 131.692 272.777 94.5306 -1.14575e-13 499 0.462764 0.93406 0.93406 0 0 70.3993 142.278 50.3227 1.44329e-15 263 0.461832 0.933487 0.933487 0 0 61.2929 130.499 44.2079 -6.55032e-15 236 0.463803 0.934698 0.934698 -345.15 -345.147 -0.00949919 0.139179 0.945585 1 0.945585 2 0.000 NA
-SNPID_114 RSID_114 NA 114 A G NA 0 0 11.0467 89.0229 398.93 1.12799e-13 499 0.111339 0.815042 0.815042 0 0 8.14415 54.749 200.107 -3.21965e-15 263 0.135052 0.845267 0.845267 0 0 2.90253 34.2739 198.824 0 236 0.0849131 0.761251 0.761251 -345.15 -341.616 -0.576665 0.222292 0.00948179 1 0.00785395 3 0.000 NA
-SNPID_115 RSID_115 NA 115 A G NA 0 0 287.183 176.834 34.9834 -3.42837e-13 499 0.247295 0.781208 0.781208 0 0 148.652 95.0475 19.3005 8.88178e-16 263 0.254085 0.787439 0.787439 0 0 138.531 81.7866 15.6829 -3.9968e-15 236 0.23973 0.773857 0.773857 -345.15 -344.983 0.0931683 0.161715 0.564529 1 0.564193 2 0.000 NA
-SNPID_116 RSID_116 NA 116 A G NA 0 0 350.176 137.352 11.4715 -2.26485e-13 499 0.160617 0.948551 0.948551 0 0 182.083 73.1438 7.77358 3.55271e-15 263 0.168614 0.948485 0.948485 0 0 168.094 64.2086 3.69791 4.66294e-15 236 0.151704 0.94857 0.94857 -345.15 -344.865 0.13562 0.17998 0.451135 1 0.450366 2 0.000 NA
-SNPID_117 RSID_117 NA 117 A G NA 0 0 6.13645 41.3625 451.501 2.85993e-13 499 0.0537429 0.615868 0.615868 0 0 3.22957 16.8111 242.959 -6.99441e-15 263 0.0442401 0.525183 0.525183 0 0 2.90688 24.5513 208.542 1.22125e-15 236 0.0643328 0.6855 0.6855 -345.15 -343.91 0.500867 0.322925 0.120894 1 0.115314 2 0.000 NA
-SNPID_118 RSID_118 NA 118 A G NA 0 0 78.966 256.021 164.013 1.69642e-13 499 0.414783 0.975421 0.975421 0 0 37.5049 142.342 83.1535 7.43849e-15 263 0.413216 0.976287 0.976287 0 0 41.4611 113.68 80.859 1.13243e-14 236 0.41653 0.974457 0.974457 -345.15 -345.143 0.0148653 0.134272 0.911846 1 0.911847 2 0.000 NA
-SNPID_119 RSID_119 NA 119 A G NA 0 0 450.808 43.1979 4.99436 -2.2915e-13 499 0.0532932 0.716886 0.716886 0 0 232.402 28.0859 2.51254 -1.70974e-14 263 0.0629487 0.766566 0.766566 0 0 218.406 15.112 2.48182 -5.55112e-15 236 0.0425331 0.635168 0.635168 -345.15 -343.925 0.490123 0.320004 0.125617 1 0.117625 3 0.000 NA
-SNPID_120 RSID_120 NA 120 A G NA 0 0 284.589 178.972 35.4391 -9.09495e-13 499 0.25035 0.961892 0.961892 0 0 147.366 97.8937 17.7406 4.66294e-15 263 0.253564 0.962772 0.962772 0 0 137.224 81.0779 17.6985 2.77556e-15 236 0.246769 0.960889 0.960889 -345.15 -345.119 0.0360049 0.14599 0.805198 1 0.80515 2 0.000 NA
-SNPID_121 RSID_121 NA 121 A G NA 0 0 3.88833 44.991 450.121 5.77316e-14 499 0.0528734 0.729862 0.729862 0 0 2.51082 22.0865 238.403 -1.88738e-15 263 0.0515364 0.723522 0.723522 0 0 1.37751 22.9045 211.718 -1.22125e-15 236 0.0543634 0.736559 0.736559 -345.15 -345.126 0.06797 0.310761 0.826867 1 0.826906 2 0.000 NA
-SNPID_122 RSID_122 NA 122 A G NA 0 0 12.8185 105.714 380.468 2.27374e-13 499 0.131614 0.809885 0.809885 0 0 5.79324 57.7431 199.464 -7.32747e-15 263 0.131805 0.806431 0.806431 0 0 7.0253 47.9708 181.004 9.32587e-15 236 0.131401 0.813743 0.813743 -345.15 -345.149 -0.00400163 0.199534 0.984 1 0.983998 1 0.000 NA
-SNPID_123 RSID_123 NA 123 A G NA 0 0 344.03 136.589 18.3807 -1.71418e-13 499 0.173698 0.922874 0.922874 0 0 183.444 70.3924 9.1632 -1.55431e-15 263 0.168667 0.924058 0.924058 0 0 160.586 66.1968 9.2175 5.55112e-16 236 0.179305 0.921586 0.921586 -345.15 -345.048 -0.07641 0.169877 0.652858 1 0.652901 2 0.000 NA
-SNPID_124 RSID_124 NA 124 A G NA 0 0 471.147 25.8116 2.04158 5.64881e-13 499 0.0299546 0.661566 0.661566 0 0 245.948 15.9187 1.13337 -4.77396e-15 263 0.034573 0.696476 0.696476 0 0 225.199 9.89292 0.908212 -1.02141e-14 236 0.0248079 0.607188 0.607188 -345.15 -344.616 0.443019 0.434353 0.307752 1 0.301648 2 0.000 NA
-SNPID_125 RSID_125 NA 125 A G NA 0 0 376.373 116.287 6.33985 6.26166e-13 499 0.129225 0.867399 0.867399 0 0 192.769 67.486 2.74528 -9.99201e-16 263 0.138739 0.879102 0.879102 0 0 183.604 48.8012 3.59457 -4.44089e-15 236 0.118624 0.852223 0.852223 -345.15 -344.61 0.216309 0.208804 0.300227 1 0.298745 2 0.000 NA
-SNPID_126 RSID_126 NA 126 A G NA 0 0 11.0612 98.71 389.229 3.41949e-13 499 0.121075 0.779816 0.779816 0 0 6.6627 48.4817 207.856 1.03251e-14 263 0.117504 0.777655 0.777655 0 0 4.39851 50.2283 181.373 -4.10783e-15 236 0.125054 0.782037 0.782037 -345.15 -345.071 0.0833705 0.210626 0.692236 1 0.69228 2 0.000 NA
-SNPID_127 RSID_127 NA 127 A G NA 0 0 293.413 173.091 32.4957 -2.83329e-13 499 0.238559 0.863362 0.863362 0 0 158.923 86.9914 17.0852 -1.93179e-14 263 0.230346 0.860539 0.860539 0 0 134.49 86.0995 15.4104 0 236 0.247713 0.866238 0.866238 -345.15 -344.922 -0.105175 0.156059 0.500347 1 0.500249 2 0.000 NA
-SNPID_128 RSID_128 NA 128 A G NA 0 0 279.4 189.77 29.8306 -2.82441e-13 499 0.249931 0.955836 0.955836 0 0 147.183 97.8979 17.9189 7.99361e-15 263 0.25425 0.957832 0.957832 0 0 132.216 91.8719 11.9117 -9.10383e-15 236 0.245117 0.953546 0.953546 -345.15 -345.091 0.0517992 0.151073 0.731693 1 0.731595 2 0.000 NA
-SNPID_129 RSID_129 NA 129 A G NA 0 0 488.904 8.05274 2.04361 -2.83329e-13 499 0.0121643 0.157274 0.157274 0 0 257.816 4.05417 1.12943 -6.10623e-15 263 0.012002 0.120355 0.120355 0 0 231.087 3.99857 0.914178 7.66054e-15 236 0.0123452 0.197283 0.197283 -345.15 -345.147 -0.0585841 0.82941 0.943689 1 0.943639 2 0.000 NA
-SNPID_130 RSID_130 NA 130 A G NA 0 0 364.134 120.789 14.0768 0 499 0.149241 0.821309 0.821309 0 0 192.122 62.3331 8.5446 -2.19824e-14 263 0.150993 0.819207 0.819207 0 0 172.012 58.4558 5.53219 1.23235e-14 236 0.147288 0.823691 0.823691 -345.15 -345.134 0.0336129 0.191046 0.86034 1 0.860308 2 0.000 NA
-SNPID_131 RSID_131 NA 131 A G NA 0 0 279.627 183.221 36.1516 7.38076e-13 499 0.256036 0.924252 0.924252 0 0 149.559 94.7463 18.6942 -7.21645e-15 263 0.251207 0.922502 0.922502 0 0 130.068 88.4747 17.4575 -3.10862e-15 236 0.261419 0.92613 0.92613 -345.15 -345.079 -0.0557871 0.148171 0.706542 1 0.706555 2 0.000 NA
-SNPID_132 RSID_132 NA 132 A G NA 0 0 420.335 74.6955 3.96944 5.71987e-13 499 0.0828 0.825421 0.825421 0 0 221.441 39.0391 2.52025 8.43769e-15 263 0.0838015 0.828848 0.828848 0 0 198.894 35.6564 1.44919 3.33067e-16 236 0.0816839 0.821507 0.821507 -345.15 -345.141 0.0332334 0.251274 0.894779 1 0.894748 2 0.000 NA
-SNPID_133 RSID_133 NA 133 A G NA 0 0 453.967 43.255 1.77848 -7.95808e-13 499 0.0469058 0.813575 0.813575 0 0 232.425 29.6092 0.965375 4.21885e-15 263 0.059962 0.850286 0.850286 0 0 221.541 13.6458 0.813108 -3.55271e-15 236 0.0323559 0.737532 0.737532 -345.15 -342.571 0.768478 0.349676 0.0279714 1 0.0231515 3 0.000 NA
-SNPID_134 RSID_134 NA 134 A G NA 0 0 57.7265 438.018 3.25594 2.85105e-13 499 0.44542 0.967559 0.967559 0 0 22.5586 238.698 1.74386 8.54872e-15 263 0.460428 0.968216 0.968216 0 0 35.1678 199.32 1.51209 4.88498e-15 236 0.428695 0.966746 0.966746 -345.15 -342.482 0.68216 0.300513 0.0232083 1 0.0209094 2 0.000 NA
-SNPID_135 RSID_135 NA 135 A G NA 0 0 57.6386 221.85 219.511 5.66658e-13 499 0.337803 0.910178 0.910178 0 0 28.9944 126.427 107.579 -4.44089e-15 263 0.350599 0.914988 0.914988 0 0 28.6442 95.4238 111.932 5.21805e-15 236 0.323543 0.904443 0.904443 -345.15 -344.705 -0.132406 0.140567 0.346224 1 0.345441 2 0.000 NA
-SNPID_136 RSID_136 NA 136 A G NA 0 0 119.136 256.936 122.928 -3.97016e-13 499 0.496201 0.86662 0.86662 0 0 58.9388 143.168 60.8937 8.65974e-15 263 0.496283 0.873152 0.873152 0 0 60.1977 113.768 62.0343 1.17684e-14 236 0.496109 0.859341 0.859341 -345.15 -345.15 -0.000835632 0.138688 0.995193 1 0.995193 1 0.000 NA
-SNPID_137 RSID_137 NA 137 A G NA 0 0 167.111 222.491 109.398 -3.96128e-13 499 0.442172 0.701896 0.701896 0 0 87.7172 118.969 56.3134 9.32587e-15 263 0.440297 0.697695 0.697695 0 0 79.3935 103.522 53.0846 1.33227e-15 236 0.444261 0.706558 0.706558 -345.15 -345.14 -0.0201246 0.142857 0.887971 1 0.887971 2 0.000 NA
-SNPID_138 RSID_138 NA 138 A G NA 0 0 310.912 165.166 22.9221 8.88178e-16 499 0.211433 0.946788 0.946788 0 0 164.869 84.085 14.0464 0 263 0.213266 0.947386 0.947386 0 0 146.044 81.0806 8.87577 8.54872e-15 236 0.20939 0.946111 0.946111 -345.15 -345.138 0.0243701 0.159028 0.878206 1 0.878187 2 0.010 NA
-SNPID_139 RSID_139 NA 139 A G NA 0 0 58.2186 215.401 225.381 2.83329e-13 499 0.332503 0.747196 0.747196 0 0 30.2411 115.936 116.823 2.33147e-15 263 0.335395 0.752892 0.752892 0 0 27.9775 99.4648 108.558 8.43769e-15 236 0.329279 0.740767 0.740767 -345.15 -345.123 -0.035607 0.153015 0.815993 1 0.815961 2 0.000 NA
-SNPID_140 RSID_140 NA 140 A G NA 0 0 50.6594 234.036 214.304 -1.15463e-13 499 0.336027 0.96311 0.96311 0 0 26.9002 120.416 115.684 1.22125e-15 263 0.33121 0.962246 0.962246 0 0 23.7592 113.62 98.6206 3.9968e-15 236 0.341395 0.96405 0.96405 -345.15 -345.086 0.0500398 0.140539 0.721799 1 0.721788 2 0.000 NA
-SNPID_141 RSID_141 NA 141 A G NA 0 0 391.918 95.6505 11.432 6.80345e-13 499 0.118752 0.844489 0.844489 0 0 211.191 45.9752 5.8343 -5.21805e-15 263 0.109589 0.830542 0.830542 0 0 180.727 49.6754 5.59765 4.55191e-15 236 0.128963 0.857716 0.857716 -345.15 -344.67 -0.199206 0.203628 0.327934 1 0.327266 2 0.000 NA
-SNPID_142 RSID_142 NA 142 A G NA 0 0 24.9295 463.569 10.5012 3.97904e-13 499 0.485543 0.914636 0.914636 0 0 12.4876 244.814 5.69819 1.37668e-14 263 0.487092 0.913144 0.913144 0 0 12.4419 218.755 4.80298 -3.66374e-15 236 0.483816 0.916297 0.916297 -345.15 -345.053 0.236404 0.539028 0.66097 1 0.660617 2 0.000 NA
-SNPID_143 RSID_143 NA 143 A G NA 0 0 14.6456 114.084 370.27 -3.97016e-13 499 0.143663 0.869138 0.869138 0 0 9.87068 56.7951 196.334 -3.66374e-15 263 0.145507 0.865389 0.865389 0 0 4.77487 57.2893 173.936 -7.88258e-15 236 0.141608 0.873403 0.873403 -345.15 -345.133 -0.0337134 0.186515 0.856561 1 0.856525 2 0.000 NA
-SNPID_144 RSID_144 NA 144 A G NA 0 0 33.1806 194.786 271.034 6.82121e-13 499 0.26167 0.94813 0.94813 0 0 18.0834 90.0764 154.84 1.66533e-15 263 0.240006 0.943888 0.943888 0 0 15.0972 104.709 116.193 -4.55191e-15 236 0.285813 0.952074 0.952074 -345.15 -343.708 0.253373 0.149699 0.0905409 1 0.0895562 2 0.000 NA
-SNPID_145 RSID_145 NA 145 A G NA 0 0 338.673 138.902 21.4256 -1.08269e-12 499 0.182117 0.859297 0.859297 0 0 182.864 67.7432 12.3931 -8.54872e-15 263 0.175912 0.849787 0.849787 0 0 155.809 71.1584 9.03241 -6.77236e-15 236 0.189032 0.869236 0.869236 -345.15 -344.994 -0.0950931 0.170684 0.577439 1 0.577415 2 0.000 NA
-SNPID_146 RSID_146 NA 146 A G NA 0 0 10.7892 110.043 378.168 4.00568e-13 499 0.131885 0.890722 0.890722 0 0 5.43188 59.7038 197.864 -7.10543e-15 263 0.134159 0.894596 0.894596 0 0 5.35736 50.3388 180.304 -2.77556e-15 236 0.129351 0.886257 0.886257 -345.15 -345.123 -0.0453355 0.194814 0.815985 1 0.815903 2 0.000 NA
-SNPID_147 RSID_147 NA 147 A G NA 0 0 329.227 141.171 28.6027 -1.16351e-13 499 0.198773 0.841588 0.841588 0 0 166.505 78.4527 18.0422 3.88578e-15 263 0.217751 0.843047 0.843047 0 0 162.722 62.7178 10.5605 -8.32667e-15 236 0.177624 0.838771 0.838771 -345.15 -343.825 0.266459 0.164733 0.105767 1 0.103654 2 0.000 NA
-SNPID_148 RSID_148 NA 148 A G NA 0 0 428.127 68.155 2.71792 -6.24389e-13 499 0.0737383 0.881471 0.881471 0 0 223.549 37.5661 1.88508 -6.55032e-15 263 0.078586 0.890614 0.890614 0 0 204.578 30.5889 0.832845 4.44089e-16 236 0.0683361 0.86978 0.86978 -345.15 -344.932 0.171219 0.260082 0.510326 1 0.509227 2 0.010 NA
-SNPID_149 RSID_149 NA 149 A G NA 0 0 383.554 104.889 10.5565 1.7053e-13 499 0.126255 0.897015 0.897015 0 0 203.038 54.5641 5.3983 2.33147e-14 263 0.12426 0.89049 0.89049 0 0 180.516 50.3253 5.15822 -9.88098e-15 236 0.128478 0.904073 0.904073 -345.15 -345.128 -0.0404486 0.196287 0.836738 1 0.836758 2 0.000 NA
-SNPID_150 RSID_150 NA 150 A G NA 0 0 8.58466 55.2063 435.209 1.77636e-15 499 0.0725206 0.491533 0.491533 0 0 4.86737 26.8864 231.246 -1.55431e-15 263 0.0696219 0.479348 0.479348 0 0 3.71729 28.3199 203.963 7.32747e-15 236 0.075751 0.503952 0.503952 -345.15 -345.046 0.135902 0.298249 0.648631 1 0.648815 2 0.000 NA
-SNPID_151 RSID_151 NA 151 A G NA 0 0 245.862 207.149 45.9888 -5.50671e-14 499 0.299726 0.956303 0.956303 0 0 116.543 118.537 27.9199 -9.4369e-15 263 0.331514 0.961682 0.961682 0 0 129.319 88.6125 18.0689 -7.10543e-15 236 0.264302 0.948936 0.948936 -345.15 -342.362 0.335427 0.143237 0.0191929 1 0.0182131 2 0.000 NA
-SNPID_152 RSID_152 NA 152 A G NA 0 0 243.273 184.814 70.9124 1.77636e-15 499 0.327294 0.484607 0.484607 0 0 131.473 98.5512 32.9757 1.04361e-14 263 0.312742 0.460767 0.460767 0 0 111.8 86.2632 37.9368 -2.22045e-15 236 0.34351 0.508789 0.508789 -345.15 -344.321 -0.216812 0.168912 0.199289 1 0.197956 2 0.000 NA
-SNPID_153 RSID_153 NA 153 A G NA 0 0 370.774 115.938 12.2881 3.97016e-13 499 0.140796 0.914012 0.914012 0 0 185.503 69.303 8.19383 3.88578e-15 263 0.16291 0.926006 0.926006 0 0 185.27 46.6353 4.09422 -5.9952e-15 236 0.116152 0.895292 0.895292 -345.15 -342.763 0.414413 0.192187 0.0310601 1 0.0288976 3 0.000 NA
-SNPID_154 RSID_154 NA 154 A G NA 0 0 292.603 177.768 28.6284 3.39284e-13 499 0.235496 0.935266 0.935266 0 0 149.93 99.6887 13.3815 -4.66294e-15 263 0.240402 0.937523 0.937523 0 0 142.673 78.0797 15.2469 -3.88578e-15 236 0.230028 0.932652 0.932652 -345.15 -345.071 0.0609933 0.15384 0.691756 1 0.691613 2 0.000 NA
-SNPID_155 RSID_155 NA 155 A G NA 0 0 194.004 249.983 55.0131 -1.69642e-13 499 0.360731 0.938494 0.938494 0 0 104.268 132.018 26.7145 3.66374e-15 263 0.35256 0.934858 0.934858 0 0 89.7357 117.966 28.2986 -9.99201e-16 236 0.369837 0.94242 0.94242 -345.15 -344.961 -0.0878743 0.143043 0.539003 1 0.538879 2 0.000 NA
-SNPID_156 RSID_156 NA 156 A G NA 0 0 96.1589 250.077 152.764 9.09495e-13 499 0.443281 0.927092 0.927092 0 0 44.3211 134.338 84.3408 -1.11022e-16 263 0.423917 0.927887 0.927887 0 0 51.8378 115.739 68.4234 5.21805e-15 236 0.464861 0.925964 0.925964 -345.15 -344.222 0.182435 0.134205 0.17403 1 0.173113 2 0.000 NA
-SNPID_157 RSID_157 NA 157 A G NA 0 0 124.796 238.482 135.721 3.40172e-13 499 0.489053 0.841661 0.841661 0 0 64.01 129.256 69.7341 2.44249e-15 263 0.489118 0.839467 0.839467 0 0 60.7863 109.226 65.9873 -1.18794e-14 236 0.488981 0.844106 0.844106 -345.15 -345.15 -0.000617904 0.134776 0.996342 1 0.996342 1 0.000 NA
-SNPID_158 RSID_158 NA 158 A G NA 0 0 37.5065 171.039 290.455 -2.84217e-13 499 0.246545 0.787094 0.787094 0 0 20.628 87.786 154.586 2.22045e-16 263 0.245327 0.775488 0.775488 0 0 16.8784 83.2527 135.869 -4.996e-15 236 0.247902 0.799934 0.799934 -345.15 -345.144 0.0160065 0.158082 0.919348 1 0.919351 2 0.000 NA
-SNPID_159 RSID_159 NA 159 A G NA 0 0 79.6542 264.453 154.893 -5.50671e-14 499 0.42461 0.961204 0.961204 0 0 40.8349 137.142 85.0233 -4.77396e-15 263 0.415992 0.960268 0.960268 0 0 38.8193 127.311 69.8699 4.44089e-16 236 0.434215 0.962209 0.962209 -345.15 -344.957 0.085124 0.13711 0.534703 1 0.53452 2 0.000 NA
-SNPID_160 RSID_160 NA 160 A G NA 0 0 61.267 229.299 208.434 -4.53859e-13 499 0.352538 0.968078 0.968078 0 0 31.5852 118.658 112.757 1.55431e-15 263 0.345682 0.968947 0.968947 0 0 29.6818 110.641 95.6771 4.21885e-15 236 0.360179 0.967114 0.967114 -345.15 -345.031 0.0660615 0.135361 0.625521 1 0.625476 2 0.000 NA
-SNPID_161 RSID_161 NA 161 A G NA 0 0 32.4401 462.53 4.02962 -4.00568e-13 499 0.471533 0.963466 0.963466 0 0 16.6104 244.08 2.3099 -1.09912e-14 263 0.472813 0.963253 0.963253 0 0 15.8297 218.451 1.71973 1.16573e-14 236 0.470106 0.963703 0.963703 -345.15 -345.114 0.104483 0.393489 0.790601 1 0.790736 2 0.000 NA
-SNPID_162 RSID_162 NA 162 A G NA 0 0 262.461 195.482 41.0577 2.83329e-13 499 0.278153 0.95298 0.95298 0 0 138.198 99.7121 25.0895 1.37668e-14 263 0.284964 0.95225 0.95225 0 0 124.262 95.7695 15.9682 5.77316e-15 236 0.270563 0.953794 0.953794 -345.15 -345.018 0.073453 0.14331 0.608268 1 0.608055 2 0.000 NA
-SNPID_163 RSID_163 NA 163 A G NA 0 0 33.5077 150.312 315.18 -3.42837e-13 499 0.217763 0.626352 0.626352 0 0 15.4751 76.3955 171.129 4.66294e-15 263 0.204079 0.591771 0.591771 0 0 18.0325 73.9165 144.051 6.43929e-15 236 0.233012 0.660454 0.660454 -345.15 -344.328 0.228533 0.178738 0.20104 1 0.199929 2 0.000 NA
-SNPID_164 RSID_164 NA 164 A G NA 0 0 471.537 23.1619 4.30075 2.84217e-13 499 0.0318271 0.323411 0.323411 0 0 248.692 11.9645 2.34393 -5.21805e-15 263 0.0316585 0.313539 0.313539 0 0 222.846 11.1974 1.95682 -6.32827e-15 236 0.0320149 0.334292 0.334292 -345.15 -345.149 -0.0202566 0.478016 0.966199 1 0.966197 1 0.000 NA
-SNPID_165 RSID_165 NA 165 A G NA 0 0 293.163 162.932 42.9049 -1.70619e-12 499 0.249241 0.492273 0.492273 0 0 156.496 84.6589 21.8454 4.44089e-15 263 0.244011 0.489758 0.489758 0 0 136.667 78.2735 21.0595 2.88658e-15 236 0.255069 0.494822 0.494822 -345.15 -345.018 -0.0953618 0.186209 0.608565 1 0.608505 2 0.000 NA
-SNPID_166 RSID_166 NA 166 A G NA 0 0 89.9809 234.09 174.93 -1.71418e-13 499 0.414881 0.96961 0.96961 0 0 37.6107 132.334 93.0556 -6.55032e-15 263 0.394592 0.968589 0.968589 0 0 52.3701 101.756 81.8739 -1.87628e-14 236 0.437492 0.970594 0.970594 -345.15 -344.209 0.176456 0.128888 0.170978 1 0.170208 2 0.000 NA
-SNPID_167 RSID_167 NA 167 A G NA 0 0 74.827 221.45 202.723 1.02496e-12 499 0.371847 0.97414 0.97414 0 0 40.4194 126.622 95.9585 1.11022e-16 263 0.394412 0.97758 0.97758 0 0 34.4076 94.8276 106.765 -7.88258e-15 236 0.346701 0.969961 0.969961 -345.15 -343.962 -0.200523 0.130543 0.12452 1 0.123323 2 0.000 NA
-SNPID_168 RSID_168 NA 168 A G NA 0 0 43.7823 198.496 256.721 -3.40172e-13 499 0.286634 0.958211 0.958211 0 0 23.8858 107.699 131.415 2.55351e-15 263 0.295572 0.960532 0.960532 0 0 19.8965 90.7969 125.307 1.33227e-15 236 0.276673 0.95548 0.95548 -345.15 -344.929 -0.0939788 0.141572 0.506804 1 0.506399 2 0.000 NA
-SNPID_169 RSID_169 NA 169 A G NA 0 0 13.0148 102.684 383.301 -2.85993e-13 499 0.128972 0.756111 0.756111 0 0 5.3198 58.2653 199.415 4.77396e-15 263 0.130998 0.758079 0.758079 0 0 7.69505 44.419 183.886 -8.32667e-15 236 0.126714 0.753833 0.753833 -345.15 -345.125 -0.0454248 0.206586 0.825962 1 0.825889 2 0.000 NA
-SNPID_170 RSID_170 NA 170 A G NA 0 0 16.8883 149.111 333.001 2.82441e-13 499 0.183254 0.943426 0.943426 0 0 6.92194 81.1059 174.972 -1.09912e-14 263 0.180513 0.944912 0.944912 0 0 9.96631 68.0047 158.029 -2.9976e-15 236 0.186308 0.941803 0.941803 -345.15 -345.12 0.0409498 0.168502 0.807987 1 0.808014 2 0.000 NA
-SNPID_171 RSID_171 NA 171 A G NA 0 0 219.446 219.376 60.1779 1.68754e-13 499 0.340412 0.970671 0.970671 0 0 124.481 105.769 32.7495 -1.4766e-14 263 0.325605 0.966556 0.966556 0 0 94.9653 113.606 27.4285 1.87628e-14 236 0.356914 0.974992 0.974992 -345.15 -344.602 -0.140603 0.134501 0.295854 1 0.295445 2 0.000 NA
-SNPID_172 RSID_172 NA 172 A G NA 0 0 402.435 90.7842 5.78095 1.12799e-13 499 0.102551 0.911341 0.911341 0 0 206.719 55.333 0.948292 -2.44249e-15 263 0.108801 0.920352 0.920352 0 0 195.716 35.4512 4.83266 -2.55351e-15 236 0.0955859 0.899982 0.899982 -345.15 -344.893 0.156556 0.219042 0.474776 1 0.4736 2 0.000 NA
-SNPID_173 RSID_173 NA 173 A G NA 0 0 480.46 14.8622 3.67769 -7.39853e-13 499 0.0222621 0.164115 0.164115 0 0 251.872 9.06502 2.06291 7.88258e-15 263 0.0250776 0.216328 0.216328 0 0 228.588 5.79721 1.61478 -9.32587e-15 236 0.0191245 0.087447 0.087447 -345.15 -344.735 0.562419 0.626937 0.369671 1 0.362671 2 0.000 NA
-SNPID_174 RSID_174 NA 174 A G NA 0 0 245.823 205.372 47.8052 1.7053e-13 499 0.301585 0.957851 0.957851 0 0 133.389 109.583 20.0276 -1.9984e-15 263 0.284484 0.958982 0.958982 0 0 112.434 95.7882 27.7776 4.44089e-15 236 0.320643 0.956539 0.956539 -345.15 -344.362 -0.175145 0.139761 0.210143 1 0.209554 2 0.000 NA
-SNPID_175 RSID_175 NA 175 A G NA 0 0 459.613 35.1062 4.28031 -1.69642e-13 499 0.0437544 0.502536 0.502536 0 0 247.502 13.2162 2.28126 1.24345e-14 263 0.0338 0.357398 0.357398 0 0 212.111 21.89 1.99905 9.88098e-15 236 0.0548476 0.602189 0.602189 -345.15 -343.141 -0.778548 0.397789 0.0503255 1 0.0450228 3 0.000 NA
-SNPID_176 RSID_176 NA 176 A G NA 0 0 183.516 236.147 79.3374 -3.97016e-13 499 0.395613 0.939498 0.939498 0 0 95.099 125.802 42.0987 1.13243e-14 263 0.399239 0.939158 0.939158 0 0 88.417 110.344 37.2387 -7.88258e-15 236 0.391571 0.939872 0.939872 -345.15 -345.117 0.0337638 0.133063 0.799694 1 0.799674 2 0.000 NA
-SNPID_177 RSID_177 NA 177 A G NA 0 0 274.545 194.379 30.0759 8.54428e-13 499 0.255041 0.868221 0.868221 0 0 150.427 97.2 15.3727 4.10783e-15 263 0.243242 0.860652 0.860652 0 0 124.117 97.1794 14.7031 -3.55271e-15 236 0.26819 0.875912 0.875912 -345.15 -344.667 -0.155705 0.158569 0.326132 1 0.325693 2 0.000 NA
-SNPID_178 RSID_178 NA 178 A G NA 0 0 415.94 77.4675 5.59251 -1.14575e-13 499 0.0888302 0.856171 0.856171 0 0 216.96 41.7848 4.25499 5.9952e-15 263 0.0956175 0.871189 0.871189 0 0 198.98 35.6827 1.33752 -1.12133e-14 236 0.0812664 0.836579 0.836579 -345.15 -344.795 0.199441 0.237694 0.401432 1 0.399543 2 0.000 NA
-SNPID_179 RSID_179 NA 179 A G NA 0 0 133.603 242.396 123 5.10703e-13 499 0.489376 0.958072 0.958072 0 0 66.4341 126.156 70.41 -1.67644e-14 263 0.492441 0.958294 0.958294 0 0 67.1693 116.24 52.5904 -6.66134e-16 236 0.469112 0.957694 0.957694 -345.15 -344.403 0.156315 0.128104 0.222381 1 0.221665 2 0.010 NA
-SNPID_180 RSID_180 NA 180 A G NA 0 0 14.4355 131.602 352.963 -3.94351e-13 499 0.160794 0.917058 0.917058 0 0 7.28619 71.1996 184.514 -1.22125e-15 263 0.163065 0.919164 0.919164 0 0 7.14926 60.4022 168.449 -1.44329e-15 236 0.158264 0.914646 0.914646 -345.15 -345.127 -0.0378875 0.178205 0.831634 1 0.83158 2 0.000 NA
-SNPID_181 RSID_181 NA 181 A G NA 0 0 465.338 25.9071 7.75453 -9.6545e-13 499 0.0414991 0.0909706 0.0909706 0 0 244.308 14.5049 4.18702 8.43769e-15 263 0.0434962 0.121368 0.121368 0 0 221.03 11.4021 3.56751 -2.10942e-15 236 0.0392736 0.0533922 0.0533922 -345.15 -345.023 0.242475 0.482713 0.615445 1 0.61417 2 0.000 NA
-SNPID_182 RSID_182 NA 182 A G NA 0 0 420.78 73.186 5.03384 -9.68114e-13 499 0.0834205 0.87844 0.87844 0 0 219.29 40.6595 3.05006 8.65974e-15 263 0.0888966 0.884089 0.884089 0 0 201.49 32.5265 1.98377 7.54952e-15 236 0.0773178 0.871172 0.871172 -345.15 -344.912 0.16562 0.240729 0.491455 1 0.490243 2 0.000 NA
-SNPID_183 RSID_183 NA 183 A G NA 0 0 241.93 207.108 49.9623 5.6577e-13 499 0.307648 0.811033 0.811033 0 0 127.752 108.549 26.6987 -4.21885e-15 263 0.307884 0.811313 0.811313 0 0 114.178 98.5584 23.2636 -4.77396e-15 236 0.307385 0.81072 0.81072 -345.15 -345.149 0.00279897 0.150187 0.985131 1 0.98513 1 0.000 NA
-SNPID_184 RSID_184 NA 184 A G NA 0 0 436.635 55.1109 7.25407 -2.24709e-13 499 0.0697585 0.548088 0.548088 0 0 228.439 30.5152 4.04587 4.32987e-15 263 0.0733973 0.595355 0.595355 0 0 208.196 24.5956 3.2082 1.37668e-14 236 0.0657035 0.4895 0.4895 -345.15 -344.985 0.172722 0.302333 0.567798 1 0.566082 2 0.000 NA
-SNPID_185 RSID_185 NA 185 A G NA 0 0 314.601 153.993 30.4057 1.12799e-13 499 0.215235 0.78537 0.78537 0 0 160.547 85.1856 17.2673 1.07692e-14 263 0.227605 0.801112 0.801112 0 0 154.054 68.8077 13.1384 3.33067e-16 236 0.20145 0.765717 0.765717 -345.15 -344.57 0.178644 0.166352 0.282869 1 0.281488 2 0.000 NA
-SNPID_186 RSID_186 NA 186 A G NA 0 0 18.5373 200.449 280.014 -1.1191e-13 499 0.237999 0.962523 0.962523 0 0 6.87469 105.655 150.47 1.77636e-15 263 0.227005 0.960999 0.960999 0 0 11.6626 94.7932 129.544 1.77636e-15 236 0.250251 0.964054 0.964054 -345.15 -344.716 0.149891 0.16111 0.352182 1 0.351897 2 0.000 NA
-SNPID_187 RSID_187 NA 187 A G NA 0 0 460.902 27.3004 10.7972 -8.88178e-16 499 0.0489927 -0.0793418 -0.0793418 0 0 240.467 17.3642 5.16898 1.09912e-14 263 0.0526658 0.0683742 0.0683742 0 0 220.436 9.93614 5.62818 3.77476e-15 236 0.0448994 -0.271662 -0.271662 -345.15 -344.591 0.618216 0.622039 0.320294 1 0.290369 3 0.000 NA
-SNPID_188 RSID_188 NA 188 A G NA 0 0 39.3585 176.551 283.091 1.13687e-13 499 0.25578 0.873735 0.873735 0 0 21.7805 89.8276 151.392 -6.21725e-15 263 0.253591 0.873196 0.873196 0 0 17.578 86.7233 131.699 7.77156e-16 236 0.258219 0.874321 0.874321 -345.15 -345.135 0.0257402 0.149505 0.863305 1 0.863312 2 0.000 NA
-SNPID_189 RSID_189 NA 189 A G NA 0 0 170.692 244.912 83.3966 -5.68434e-14 499 0.41253 0.935987 0.935987 0 0 85.9513 134.783 42.2659 -4.44089e-16 263 0.416948 0.940414 0.940414 0 0 84.7403 110.129 41.1307 2.9976e-15 236 0.407607 0.931008 0.931008 -345.15 -345.101 0.0417785 0.134119 0.755418 1 0.755374 2 0.010 NA
-SNPID_190 RSID_190 NA 190 A G NA 0 0 448.022 48.2504 2.72756 3.41949e-13 499 0.0538131 0.840918 0.840918 0 0 234.495 27.6031 0.901519 8.54872e-15 263 0.0559053 0.848409 0.848409 0 0 213.527 20.6473 1.82604 -1.11022e-16 236 0.0514817 0.831861 0.831861 -345.15 -345.096 0.097798 0.298694 0.743351 1 0.743013 2 0.000 NA
-SNPID_191 RSID_191 NA 191 A G NA 0 0 79.1804 233.146 186.673 -5.68434e-14 499 0.392292 0.968208 0.968208 0 0 42.6567 115.618 104.725 -8.21565e-15 263 0.381999 0.968062 0.968062 0 0 36.5237 117.528 81.9482 3.9968e-15 236 0.403762 0.968335 0.968335 -345.15 -344.9 0.092384 0.13069 0.479634 1 0.479472 2 0.000 NA
-SNPID_192 RSID_192 NA 192 A G NA 0 0 375.586 111.738 11.6764 -3.97904e-13 499 0.135361 0.933518 0.933518 0 0 199.714 60.3411 2.94484 7.77156e-16 263 0.125914 0.927197 0.927197 0 0 175.872 51.3966 8.73156 -6.32827e-15 236 0.145889 0.939627 0.939627 -345.15 -344.716 -0.174559 0.187618 0.352167 1 0.351726 2 0.000 NA
-SNPID_193 RSID_193 NA 193 A G NA 0 0 3.32642 18.7684 476.905 1.7053e-13 499 0.0254722 0.358089 0.358089 0 0 1.7642 10.3304 250.905 4.88498e-15 263 0.0263476 0.385756 0.385756 0 0 1.56223 8.43798 226 -1.07692e-14 236 0.0244967 0.324942 0.324942 -345.15 -345.121 -0.124894 0.522287 0.811005 1 0.810638 2 0.000 NA
-SNPID_194 RSID_194 NA 194 A G NA 0 0 15.2326 75.9678 407.8 -3.40172e-13 499 0.106646 0.488191 0.488191 0 0 8.19023 41.7899 213.02 -2.33147e-15 263 0.11059 0.557934 0.557934 0 0 7.04234 34.1778 194.78 4.88498e-15 236 0.102251 0.404706 0.404706 -345.15 -345.016 -0.129748 0.251806 0.606365 1 0.604677 2 0.000 NA
-SNPID_195 RSID_195 NA 195 A G NA 0 0 242.076 205.563 51.3608 -5.70211e-13 499 0.308903 0.967178 0.967178 0 0 127.414 110.801 24.7848 -2.22045e-16 263 0.304888 0.968669 0.968669 0 0 114.662 94.7619 26.576 3.33067e-16 236 0.313377 0.965536 0.965536 -345.15 -345.108 -0.0396671 0.13704 0.772232 1 0.772243 2 0.000 NA
-SNPID_196 RSID_196 NA 196 A G NA 0 0 212.638 214.009 72.3532 3.39284e-13 499 0.359434 0.630886 0.630886 0 0 107.548 117.45 38.0019 -1.28786e-14 263 0.367783 0.654174 0.654174 0 0 105.09 96.5588 34.3513 -5.66214e-15 236 0.35013 0.604099 0.604099 -345.15 -344.908 0.11025 0.158778 0.487452 1 0.486787 2 0.000 NA
-SNPID_197 RSID_197 NA 197 A G NA 0 0 303.388 163.821 31.7916 7.96696e-13 499 0.22786 0.772555 0.772555 0 0 164.622 80.6342 17.7433 -7.54952e-15 263 0.220762 0.760396 0.760396 0 0 138.765 83.1865 14.0483 1.25455e-14 236 0.235769 0.785342 0.785342 -345.15 -344.96 -0.101498 0.164964 0.538372 1 0.53821 2 0.000 NA
-SNPID_198 RSID_198 NA 198 A G NA 0 0 22.7491 195.595 280.655 -1.15463e-13 499 0.241577 0.960102 0.960102 0 0 7.9743 107.746 147.28 1.35447e-14 263 0.235161 0.959961 0.959961 0 0 14.7748 87.8495 133.376 2.66454e-15 236 0.248727 0.960232 0.960232 -345.15 -345.009 0.0831245 0.156942 0.596355 1 0.596337 2 0.000 NA
-SNPID_199 RSID_199 NA 199 A G NA 0 0 436.182 58.4045 4.41342 1.7053e-13 499 0.0673661 0.745416 0.745416 0 0 227.083 33.1024 2.815 -1.0103e-14 263 0.0736359 0.763926 0.763926 0 0 209.1 25.3021 1.59842 3.9968e-15 236 0.0603791 0.720199 0.720199 -345.15 -344.72 0.261445 0.283461 0.356356 1 0.354011 2 0.000 NA
-SNPID_200 RSID_200 NA 200 A G NA 0 0 159.676 255.126 84.1983 -2.27374e-13 499 0.424371 0.847278 0.847278 0 0 85.0326 136.537 41.4306 -1.77636e-15 263 0.417106 0.84989 0.84989 0 0 74.6433 118.589 42.7677 -2.9976e-15 236 0.432467 0.844316 0.844316 -345.15 -345 -0.0785739 0.143458 0.583888 1 0.58376 2 0.000 NA
-# Completed successfully at 2015-08-05 16:58:22

DELETED doc/html/bingwa/example/cohort2.snptest
Index: doc/html/bingwa/example/cohort2.snptest
==================================================================
--- doc/html/bingwa/example/cohort2.snptest
+++ doc/html/bingwa/example/cohort2.snptest
@@ -1,212 +0,0 @@
-# Analysis: "SNPTEST analysis, started 2015-08-05 16:58:28"
-#  started: 2015-08-05 16:58:28
-# 
-# Analysis properties:
-#   -data cohort2.gen cohort2.sample (user-supplied)
-#   -frequentist add (user-supplied)
-#   -method newml (user-supplied)
-#   -o cohort2.snptest (user-supplied)
-#   -pheno bin2 (user-supplied)
-# 
-alternate_ids rsid chromosome position alleleA alleleB incorrectly_coded all_A all_B all_AA all_AB all_BB all_NULL all_total all_maf all_info all_impute_info cases_A cases_B cases_AA cases_AB cases_BB cases_NULL cases_total cases_maf cases_info cases_impute_info controls_A controls_B controls_AA controls_AB controls_BB controls_NULL controls_total controls_maf controls_info controls_impute_info frequentist_add_null_ll frequentist_add_alternative_ll frequentist_add_beta_1:add/bin2=1 frequentist_add_se_1 frequentist_add_wald_pvalue_1 frequentist_add_degrees_of_freedom frequentist_add_lrt_pvalue iterations model_fit_time comment
-INSERTION_1 RSID_1 NA 0 A AGTGCTA NA 0 0 176.803 250.978 71.2191 -2.2915e-13 499 0.394204 0.970861 0.970861 0 0 87.8776 134.474 38.6484 -4.21885e-15 261 0.405691 0.970729 0.970729 0 0 88.9254 116.504 32.5707 -4.21885e-15 238 0.381608 0.970972 0.970972 -345.35 -345.021 0.110038 0.13564 0.417223 1 0.416791 2 0.000 NA
-DELETION_1b RSID_2 NA 2 A - NA 0 0 28.2372 142.957 327.806 5.11591e-13 499 0.199831 0.662841 0.662841 0 0 15.41 77.0627 168.527 1.77636e-15 261 0.206672 0.685034 0.685034 0 0 12.8272 65.8939 159.279 -9.99201e-16 238 0.192328 0.636918 0.636918 -345.35 -345.141 -0.117561 0.181867 0.51801 1 0.517305 2 0.000 NA
-SNPID_3b RSID_3b NA 3 A G NA 0 0 143.459 260.019 95.522 2.26485e-13 499 0.451967 0.951854 0.951854 0 0 74.3028 134.982 51.7154 4.66294e-15 261 0.456729 0.95019 0.95019 0 0 69.1562 125.037 43.8066 6.88338e-15 238 0.446745 0.953676 0.953676 -345.35 -345.295 0.0447937 0.134267 0.73867 1 0.738627 2 0.000 NA
-SNPID_4 RSID_4 NA 4 A G NA 0 0 27.8211 168.962 302.217 -2.84217e-13 499 0.225054 0.950761 0.950761 0 0 13.9821 90.9271 156.091 -4.32987e-15 261 0.227761 0.950426 0.950426 0 0 13.8389 78.0348 146.126 4.44089e-16 238 0.222085 0.951131 0.951131 -345.35 -345.327 -0.0332223 0.153374 0.828513 1 0.828478 2 0.000 NA
-SNPID_5 RSID_5 NA 5 A G NA 0 0 204.343 238.368 56.2891 -1.12799e-13 499 0.35165 0.941939 0.941939 0 0 103.704 131.015 26.281 -5.88418e-15 261 0.351679 0.944917 0.944917 0 0 100.638 107.354 30.008 -3.44169e-15 238 0.351617 0.938672 0.938672 -345.35 -345.35 0.00030686 0.140374 0.998256 1 0.998256 1 0.000 NA
-SNPID_6 RSID_6 NA 6 A G NA 0 0 116.716 251.764 130.52 9.66338e-13 499 0.486167 0.972745 0.972745 0 0 59.4139 135.263 66.323 1.32117e-14 261 0.486764 0.972004 0.972004 0 0 57.3017 116.501 64.1974 -7.10543e-15 238 0.485513 0.973557 0.973557 -345.35 -345.349 -0.005201 0.129216 0.967894 1 0.967894 1 0.000 NA
-SNPID_7 RSID_7 NA 7 A G NA 0 0 80.8018 215.881 202.317 2.86882e-13 499 0.378241 0.947861 0.947861 0 0 41.9088 116.263 102.829 -3.10862e-15 261 0.383296 0.949904 0.949904 0 0 38.8929 99.6184 99.4887 -1.08802e-14 238 0.372698 0.945583 0.945583 -345.35 -345.292 -0.0438599 0.128973 0.733804 1 0.733745 2 0.010 NA
-SNPID_8 RSID_8 NA 8 A G NA 0 0 2.00873 48.6402 448.351 5.59552e-14 499 0.0527632 0.810249 0.810249 0 0 1.07141 21.9383 237.99 -5.55112e-15 261 0.0461323 0.777435 0.777435 0 0 0.937326 26.7019 210.361 6.55032e-15 238 0.0600348 0.83797 0.83797 -345.35 -344.774 0.333565 0.31176 0.284645 1 0.283022 2 0.000 NA
-SNPID_9 RSID_9 NA 9 A G NA 0 0 26.8289 149.548 322.623 -7.99361e-13 499 0.203613 0.922561 0.922561 0 0 17.4334 81.095 162.472 -8.32667e-15 261 0.222149 0.930305 0.930305 0 0 9.39546 68.4527 160.152 8.21565e-15 238 0.183285 0.912348 0.912348 -345.35 -344.183 -0.242267 0.159375 0.128486 1 0.126489 2 0.000 NA
-SNPID_10 RSID_10 NA 10 A G NA 0 0 3.96096 479.095 15.9444 1.08002e-12 499 0.487992 0.966555 0.966555 0 0 1.86949 250.027 9.10366 -1.44329e-15 261 0.486141 0.967852 0.967852 0 0 2.09148 229.068 6.84079 -7.32747e-15 238 0.490022 0.965133 0.965133 -345.35 -345.183 0.348305 0.607059 0.566131 1 0.562912 2 0.000 NA
-SNPID_11 RSID_11 NA 11 A G NA 0 0 246.63 202.463 49.9071 2.84217e-13 499 0.302883 0.952836 0.952836 0 0 132.275 100.758 27.9666 1.4877e-14 261 0.300175 0.95085 0.95085 0 0 114.355 101.705 21.9405 -9.10383e-15 238 0.305852 0.954989 0.954989 -345.35 -345.331 -0.0270935 0.138447 0.844849 1 0.844852 2 0.000 NA
-SNPID_12 RSID_12 NA 12 A G NA 0 0 26.492 134.448 338.06 -1.15463e-13 499 0.187807 0.894237 0.894237 0 0 18.6116 64.502 177.886 -8.88178e-16 261 0.194876 0.895428 0.895428 0 0 7.8804 69.9457 160.174 -7.77156e-16 238 0.180056 0.892766 0.892766 -345.35 -345.173 -0.0962864 0.161792 0.55176 1 0.551316 2 0.000 NA
-SNPID_13 RSID_13 NA 13 A G NA 0 0 120.219 251.197 127.584 -2.24709e-13 499 0.49262 0.927654 0.927654 0 0 57.8339 146.187 56.9791 6.66134e-15 261 0.498362 0.930081 0.930081 0 0 62.3851 105.01 70.6048 1.04361e-14 238 0.482732 0.924935 0.924935 -345.35 -345.157 -0.0822252 0.132249 0.534111 1 0.533924 2 0.000 NA
-SNPID_14 RSID_14 NA 14 A G NA 0 0 399.39 91.6676 7.94191 1.19282e-12 499 0.107767 0.818438 0.818438 0 0 209.873 47.0084 4.11863 1.03251e-14 261 0.105835 0.809452 0.809452 0 0 189.518 44.6592 3.82328 -1.64313e-14 238 0.109886 0.827957 0.827957 -345.35 -345.326 -0.048758 0.219825 0.824467 1 0.824482 2 0.000 NA
-SNPID_15 RSID_15 NA 15 A G NA 0 0 36.719 147.621 314.66 1.12799e-13 499 0.221502 0.755606 0.755606 0 0 20.865 77.5232 162.612 9.99201e-15 261 0.228454 0.762682 0.762682 0 0 15.854 70.0982 152.048 3.33067e-15 238 0.213879 0.747309 0.747309 -345.35 -345.179 -0.0943537 0.161483 0.559023 1 0.558608 2 0.000 NA
-SNPID_16 RSID_16 NA 16 A G NA 0 0 14.5577 123.447 360.995 1.69642e-13 499 0.152868 0.943892 0.943892 0 0 7.74088 65.2942 187.965 -7.77156e-15 261 0.154743 0.946608 0.946608 0 0 6.81682 58.1529 173.03 -2.9976e-15 238 0.150812 0.940847 0.940847 -345.35 -345.335 -0.0307284 0.177255 0.862371 1 0.862337 2 0.000 NA
-SNPID_17 RSID_17 NA 17 A G NA 0 0 442.29 51.2885 5.42159 7.98472e-13 499 0.0622562 0.648692 0.648692 0 0 228.983 28.6817 3.33489 -7.77156e-16 261 0.0677232 0.668707 0.668707 0 0 213.307 22.6067 2.0867 1.25455e-14 238 0.0562608 0.622138 0.622138 -345.35 -344.984 0.257185 0.302032 0.394484 1 0.392377 2 0.000 NA
-SNPID_18 RSID_18 NA 18 A G NA 0 0 167.997 251.142 79.8613 -2.81553e-13 499 0.411688 0.976621 0.976621 0 0 83.0211 125.599 52.3798 -2.66454e-15 261 0.4413 0.976032 0.976032 0 0 84.976 125.543 27.4815 -5.10703e-15 238 0.379213 0.977098 0.977098 -345.35 -343.229 0.275355 0.134391 0.0404713 1 0.0394484 2 0.000 NA
-SNPID_19 RSID_19 NA 19 A G NA 0 0 2.93516 37.4663 458.598 -3.41061e-13 499 0.0434235 0.661199 0.661199 0 0 1.46344 17.2898 242.247 -1.0103e-14 261 0.0387293 0.635761 0.635761 0 0 1.47172 20.1765 216.352 2.33147e-15 238 0.0485714 0.683301 0.683301 -345.35 -344.968 0.311921 0.357103 0.382404 1 0.381868 2 0.000 NA
-SNPID_20 RSID_20 NA 20 A G NA 0 0 49.3613 172.759 276.88 1.77636e-15 499 0.272026 0.962058 0.962058 0 0 22.7889 88.8261 149.385 1.04361e-14 261 0.257479 0.959623 0.959623 0 0 26.5724 83.9329 127.495 9.65894e-15 238 0.287978 0.964458 0.964458 -345.35 -344.813 0.141578 0.136692 0.300318 1 0.299897 2 0.000 NA
-SNPID_21 RSID_21 NA 21 A G NA 0 0 457.89 37.1884 3.92139 5.11591e-13 499 0.0451215 0.681434 0.681434 0 0 240.314 19.0994 1.58667 1.96509e-14 261 0.0426682 0.659434 0.659434 0 0 217.576 18.089 2.33472 3.10862e-15 238 0.0478119 0.702983 0.702983 -345.35 -345.257 -0.146074 0.337981 0.6656 1 0.6654 2 0.000 NA
-SNPID_22 RSID_22 NA 22 A G NA 0 0 376.942 113.163 8.89532 1.77636e-15 499 0.131216 0.808478 0.808478 0 0 196.963 59.3935 4.64379 -4.32987e-15 261 0.131573 0.802649 0.802649 0 0 179.979 53.7693 4.25153 2.22045e-16 238 0.130824 0.814902 0.814902 -345.35 -345.349 0.00806365 0.208016 0.969078 1 0.969074 1 0.000 NA
-SNPID_23 RSID_23 NA 23 A G NA 0 0 20.451 144.446 334.103 3.97016e-13 499 0.18572 0.925376 0.925376 0 0 11.1397 73.2439 176.616 1.09912e-14 261 0.182995 0.928243 0.928243 0 0 9.31132 71.2025 157.486 -4.66294e-15 238 0.188708 0.922297 0.922297 -345.35 -345.322 0.0390091 0.165568 0.813737 1 0.81376 2 0.000 NA
-SNPID_24 RSID_24 NA 24 A G NA 0 0 2.04329 15.939 481.018 5.59552e-14 499 0.0200657 0.488441 0.488441 0 0 1.09378 9.0247 250.882 1.33227e-14 261 0.0214794 0.511026 0.511026 0 0 0.949509 6.9143 230.136 -1.88738e-15 238 0.0185154 0.459665 0.459665 -345.35 -345.268 -0.223641 0.552861 0.685834 1 0.684891 2 0.000 NA
-SNPID_25 RSID_25 NA 25 A G NA 0 0 11.1851 111.271 376.544 3.38396e-13 499 0.133909 0.870027 0.870027 0 0 6.5762 58.7239 195.7 1.77636e-15 261 0.137694 0.877087 0.877087 0 0 4.60886 52.5471 180.844 6.55032e-15 238 0.129758 0.861847 0.861847 -345.35 -345.276 -0.0754698 0.195658 0.699701 1 0.699477 2 0.000 NA
-SNPID_26 RSID_26 NA 26 A G NA 0 0 396.297 91.319 11.3843 -5.77316e-14 499 0.114316 0.764145 0.764145 0 0 208.762 44.3845 7.85358 2.66454e-15 261 0.115118 0.758784 0.758784 0 0 187.535 46.9345 3.53073 1.46549e-14 238 0.113437 0.770097 0.770097 -345.35 -345.346 0.0192898 0.214703 0.928411 1 0.928404 2 0.000 NA
-SNPID_27 RSID_27 NA 27 A G NA 0 0 36.5649 164.057 298.378 2.30038e-13 499 0.237662 0.864642 0.864642 0 0 19.3697 90.7154 150.915 -4.21885e-15 261 0.247998 0.865307 0.865307 0 0 17.1951 73.3421 147.463 2.06501e-14 238 0.226328 0.863675 0.863675 -345.35 -345.013 -0.125213 0.152663 0.412106 1 0.411393 2 0.000 NA
-SNPID_28 RSID_28 NA 28 A G NA 0 0 31.8393 190.669 276.491 -7.9492e-13 499 0.254858 0.955913 0.955913 0 0 12.9998 93.9939 154.006 -3.10862e-15 261 0.229873 0.953228 0.953228 0 0 18.8394 96.6755 122.485 -1.77636e-15 238 0.282257 0.958174 0.958174 -345.35 -343.454 0.291455 0.150288 0.0524642 1 0.0514927 2 0.000 NA
-SNPID_29 RSID_29 NA 29 A G NA 0 0 2.01002 4.93874 492.051 -5.9508e-14 499 0.00897674 -0.109181 -0.109181 0 0 1.05098 3.90233 256.047 1.19904e-14 261 0.0115025 0.152123 0.152123 0 0 0.959039 1.03641 236.005 1.11022e-16 238 0.00620692 -0.640026 -0.640026 -345.35 -343.594 -8.98149 57.133 0.875085 1 0.0608798 8 0.000 NA
-SNPID_30 RSID_30 NA 30 A G NA 0 0 14.6102 94.924 389.466 1.15463e-13 499 0.124393 0.763389 0.763389 0 0 5.03075 48.3859 207.583 1.19904e-14 261 0.111968 0.739708 0.739708 0 0 9.57942 46.5382 181.882 1.04361e-14 238 0.138019 0.784387 0.784387 -345.35 -344.479 0.269039 0.204521 0.188357 1 0.186873 2 0.000 NA
-SNPID_31 RSID_31 NA 31 A G NA 0 0 40.7178 195.326 262.956 2.83329e-13 499 0.277316 0.934467 0.934467 0 0 19.3156 98.8687 142.816 1.55431e-15 261 0.26341 0.933035 0.933035 0 0 21.4022 96.4573 120.141 -1.17684e-14 238 0.292566 0.935797 0.935797 -345.35 -344.799 0.151953 0.144862 0.294202 1 0.293716 2 0.000 NA
-SNPID_32 RSID_32 NA 32 A G NA 0 0 5.88733 75.496 417.617 5.10703e-13 499 0.0874455 0.836934 0.836934 0 0 2.51216 38.6784 219.809 -7.43849e-15 261 0.0837216 0.834012 0.834012 0 0 3.37516 36.8176 197.807 5.55112e-15 238 0.0915293 0.839827 0.839827 -345.35 -345.243 0.109973 0.237825 0.643786 1 0.643787 2 0.000 NA
-SNPID_33 RSID_33 NA 33 A G NA 0 0 3.79611 36.3463 458.858 4.56524e-13 499 0.0440266 0.798168 0.798168 0 0 1.93319 22.615 236.452 -4.66294e-15 261 0.0507306 0.828925 0.828925 0 0 1.86292 13.7313 222.406 -4.66294e-15 238 0.0366747 0.751601 0.751601 -345.35 -344.715 -0.36663 0.329691 0.26612 1 0.259728 2 0.000 NA
-SNPID_34 RSID_34 NA 34 A G NA 0 0 3.6359 424.413 70.951 -3.41949e-13 499 0.43255 0.966631 0.966631 0 0 1.95927 222.14 36.901 -1.11022e-16 261 0.433062 0.967173 0.967173 0 0 1.67663 202.273 34.05 -2.10942e-15 238 0.431989 0.966036 0.966036 -345.35 -345.348 -0.018679 0.264356 0.943669 1 0.943676 2 0.000 NA
-SNPID_35 RSID_35 NA 35 A G NA 0 0 238.36 206.548 54.0912 -3.94351e-13 499 0.315361 0.902792 0.902792 0 0 129.459 104.192 27.3485 5.21805e-15 261 0.304385 0.897625 0.897625 0 0 108.901 102.356 26.7427 -1.45439e-14 238 0.327398 0.908119 0.908119 -345.35 -345.027 -0.112852 0.140435 0.421634 1 0.421387 2 0.000 NA
-SNPID_36 RSID_36 NA 36 A G NA 0 0 115.399 252.64 130.961 -7.9492e-13 499 0.484407 0.864298 0.864298 0 0 58.7871 139.879 62.3337 6.10623e-15 261 0.493206 0.868902 0.868902 0 0 56.6123 112.76 68.6273 2.10942e-15 238 0.474758 0.85914 0.85914 -345.35 -345.151 -0.0869182 0.137668 0.527804 1 0.527575 2 0.000 NA
-SNPID_37 RSID_37 NA 37 A G NA 0 0 107.514 236.715 154.771 2.28262e-13 499 0.452648 0.708027 0.708027 0 0 55.6388 126.358 79.0028 3.33067e-16 261 0.455241 0.694429 0.694429 0 0 51.875 110.357 75.7682 -6.21725e-15 238 0.449804 0.722952 0.722952 -345.35 -345.33 -0.0291821 0.146833 0.842463 1 0.842455 2 0.000 NA
-SNPID_38 RSID_38 NA 38 A G NA 0 0 29.9618 167.037 302.001 1.7053e-13 499 0.227416 0.946377 0.946377 0 0 13.9526 81.1686 165.879 2.55351e-15 261 0.208954 0.944204 0.944204 0 0 16.0092 85.8687 136.122 2.88658e-15 238 0.247662 0.948266 0.948266 -345.35 -344.282 0.221936 0.152167 0.144703 1 0.143826 2 0.000 NA
-SNPID_39 RSID_39 NA 39 A G NA 0 0 254.015 187.176 57.8095 -7.37188e-13 499 0.303402 0.72408 0.72408 0 0 130.694 101.921 28.3854 -3.77476e-15 261 0.304007 0.719763 0.719763 0 0 123.321 85.2551 29.4241 9.21485e-15 238 0.302738 0.728823 0.728823 -345.35 -345.349 0.00717068 0.150685 0.962045 1 0.962044 2 0.000 NA
-SNPID_40 RSID_40 NA 40 A G NA 0 0 218.264 214.496 66.24 1.12799e-13 499 0.347671 0.965661 0.965661 0 0 117.577 109.773 33.6502 -6.55032e-15 261 0.339221 0.963963 0.963963 0 0 100.687 104.723 32.5898 -3.10862e-15 238 0.356938 0.967454 0.967454 -345.35 -345.181 -0.0767274 0.131922 0.56083 1 0.560744 2 0.000 NA
-SNPID_41 RSID_41 NA 41 A G NA 0 0 10.3723 101.432 387.196 1.68754e-13 499 0.122422 0.85829 0.85829 0 0 6.64746 49.9473 204.405 -2.22045e-15 261 0.121154 0.856534 0.856534 0 0 3.72485 51.4849 182.79 3.88578e-15 238 0.123812 0.860176 0.860176 -345.35 -345.341 0.0271117 0.20236 0.89342 1 0.893431 2 0.000 NA
-SNPID_42 RSID_42 NA 42 A G NA 0 0 10.0811 463.854 25.0652 2.27374e-13 499 0.484986 0.916241 0.916241 0 0 4.89724 244.073 12.0293 0 261 0.486337 0.91849 0.91849 0 0 5.1839 219.78 13.0359 9.32587e-15 238 0.483504 0.913773 0.913773 -345.35 -345.278 -0.206565 0.543966 0.704139 1 0.703059 2 0.000 NA
-SNPID_43 RSID_43 NA 43 A G NA 0 0 365.761 122.481 10.7585 -1.14575e-13 499 0.144286 0.864369 0.864369 0 0 193.306 62.8228 4.87067 2.77556e-15 261 0.139012 0.869044 0.869044 0 0 172.454 59.6578 5.88786 -1.77636e-15 238 0.15007 0.85949 0.85949 -345.35 -345.209 -0.102842 0.193188 0.59449 1 0.594569 2 0.000 NA
-SNPID_44 RSID_44 NA 44 A G NA 0 0 275.01 192.699 31.2903 6.81233e-13 499 0.255792 0.944161 0.944161 0 0 141.047 107.647 12.3058 1.08802e-14 261 0.253369 0.942359 0.942359 0 0 133.963 85.0524 18.9846 3.55271e-15 238 0.258449 0.946108 0.946108 -345.35 -345.332 -0.0286871 0.1506 0.848928 1 0.848934 2 0.000 NA
-SNPID_45 RSID_45 NA 45 A G NA 0 0 18.5348 162.189 318.276 -6.82121e-13 499 0.199658 0.88062 0.88062 0 0 10.2086 78.3099 172.481 2.9976e-15 261 0.189133 0.876714 0.876714 0 0 8.32617 83.8792 145.795 1.44329e-15 238 0.211201 0.884381 0.884381 -345.35 -344.911 0.159904 0.170746 0.349015 1 0.348659 2 0.000 NA
-SNPID_46 RSID_46 NA 46 A G NA 0 0 383.146 105.125 10.7289 1.02407e-12 499 0.126836 0.884721 0.884721 0 0 193.177 62.3598 5.46338 -1.66533e-15 261 0.140396 0.897602 0.897602 0 0 189.969 42.7652 5.26553 -1.46549e-14 238 0.111967 0.867084 0.867084 -345.35 -344.37 0.278248 0.200078 0.164317 1 0.161548 2 0.000 NA
-SNPID_47 RSID_47 NA 47 A G NA 0 0 23.2074 142.739 333.054 5.68434e-14 499 0.189533 0.846748 0.846748 0 0 14.6099 67.6208 178.769 -1.19904e-14 261 0.185519 0.838103 0.838103 0 0 8.59746 75.1182 154.284 -6.55032e-15 238 0.193935 0.855875 0.855875 -345.35 -345.288 0.0597851 0.168917 0.72339 1 0.723376 2 0.000 NA
-SNPID_48 RSID_48 NA 48 A G NA 0 0 5.59741 67.0657 426.337 -5.68434e-14 499 0.0784173 0.895392 0.895392 0 0 3.77831 33.5727 223.649 7.43849e-15 261 0.0787919 0.899758 0.899758 0 0 1.81909 33.493 202.688 2.33147e-15 238 0.0780066 0.890559 0.890559 -345.35 -345.349 -0.0112612 0.24004 0.962582 1 0.962578 2 0.000 NA
-SNPID_49 RSID_49 NA 49 A G NA 0 0 10.4832 107.031 381.486 -5.12479e-13 499 0.128254 0.897202 0.897202 0 0 5.30753 58.5026 197.19 -9.99201e-15 261 0.132409 0.903861 0.903861 0 0 5.17568 48.528 184.296 5.88418e-15 238 0.123696 0.889425 0.889425 -345.35 -345.26 -0.0833054 0.196239 0.671194 1 0.670888 2 0.010 NA
-SNPID_50 RSID_50 NA 50 A G NA 0 0 426.989 63.0225 8.98872 2.25597e-13 499 0.0811623 0.573883 0.573883 0 0 224.051 32.2918 4.65708 -8.54872e-15 261 0.079705 0.576654 0.576654 0 0 202.938 30.7307 4.33163 3.33067e-15 238 0.0827604 0.570921 0.570921 -345.35 -345.329 -0.0563642 0.272098 0.835895 1 0.835933 2 0.000 NA
-SNPID_51 RSID_51 NA 51 A G NA 0 0 45.7353 227.08 226.185 -3.98792e-13 499 0.319189 0.961061 0.961061 0 0 23.8909 121.479 115.63 1.0103e-14 261 0.324254 0.962658 0.962658 0 0 21.8444 105.601 110.554 8.32667e-15 238 0.313635 0.959269 0.959269 -345.35 -345.279 -0.0535078 0.142325 0.70695 1 0.706861 2 0.000 NA
-SNPID_52 RSID_52 NA 52 A G NA 0 0 72.5854 188.303 238.111 -3.41061e-13 499 0.334142 0.498582 0.498582 0 0 33.4018 103.495 124.103 1.44329e-14 261 0.326243 0.503134 0.503134 0 0 39.1836 84.8083 114.008 -4.88498e-15 238 0.342806 0.493391 0.493391 -345.35 -345.114 0.114549 0.166775 0.492178 1 0.491924 2 0.000 NA
-SNPID_53 RSID_53 NA 53 A G NA 0 0 14.3402 108.099 376.56 1.7053e-13 499 0.137054 0.903963 0.903963 0 0 7.25991 55.6871 198.053 -1.33227e-14 261 0.134496 0.897283 0.897283 0 0 7.08025 52.4122 178.508 -7.77156e-15 238 0.139859 0.911039 0.911039 -345.35 -345.32 0.0458395 0.185263 0.804576 1 0.804594 2 0.000 NA
-SNPID_54 RSID_54 NA 54 A G NA 0 0 37.2667 178.908 282.825 2.84217e-13 499 0.25395 0.94241 0.94241 0 0 27.0813 90.0825 143.836 -4.55191e-15 261 0.276331 0.942395 0.942395 0 0 10.1854 88.826 138.989 2.29816e-14 238 0.229405 0.942055 0.942055 -345.35 -343.892 -0.250488 0.147409 0.0892687 1 0.0876953 2 0.000 NA
-SNPID_55 RSID_55 NA 55 A G NA 0 0 70.2514 236.443 192.306 -3.97016e-13 499 0.377701 0.938672 0.938672 0 0 39.1042 117.312 104.584 -3.10862e-15 261 0.37456 0.936358 0.936358 0 0 31.1472 119.131 87.7218 5.55112e-16 238 0.381146 0.941185 0.941185 -345.35 -345.326 0.0300977 0.135482 0.824195 1 0.824194 2 0.000 NA
-SNPID_56 RSID_56 NA 56 A G NA 0 0 148.167 240.211 110.622 1.71418e-13 499 0.46238 0.924108 0.924108 0 0 74.4561 131.46 55.084 1.56541e-14 261 0.462889 0.930042 0.930042 0 0 73.7108 108.751 55.5382 6.32827e-15 238 0.461822 0.917598 0.917598 -345.35 -345.35 0.00449049 0.130057 0.972457 1 0.972456 1 0.000 NA
-SNPID_57 RSID_57 NA 57 A G NA 0 0 145.862 247.197 105.94 7.38964e-13 499 0.459998 0.847877 0.847877 0 0 72.0721 127.927 61.0007 5.44009e-15 261 0.47879 0.85162 0.85162 0 0 73.7902 119.27 44.9397 -3.33067e-16 238 0.43939 0.843217 0.843217 -345.35 -344.434 0.187021 0.138536 0.177021 1 0.175921 2 0.000 NA
-SNPID_58 RSID_58 NA 58 A G NA 0 0 289.491 183.158 26.351 -1.77636e-15 499 0.236333 0.773314 0.773314 0 0 149.836 100.16 11.0044 2.66454e-15 261 0.234039 0.797676 0.797676 0 0 139.655 82.9983 15.3466 5.32907e-15 238 0.238848 0.746956 0.746956 -345.35 -345.329 -0.03531 0.171688 0.837054 1 0.837087 2 0.000 NA
-SNPID_59 RSID_59 NA 59 A G NA 0 0 188.469 234.777 75.7536 5.59552e-14 499 0.387058 0.957273 0.957273 0 0 101.69 121.319 37.9915 2.9976e-15 261 0.377973 0.953591 0.953591 0 0 86.7798 113.458 37.7622 2.55351e-15 238 0.397022 0.961204 0.961204 -345.35 -345.153 -0.0831404 0.132462 0.53023 1 0.530086 2 0.000 NA
-SNPID_60 RSID_60 NA 60 A G NA 0 0 203.64 225.344 70.016 2.26485e-13 499 0.366108 0.969883 0.969883 0 0 110.684 116.737 33.5784 1.24345e-14 261 0.352287 0.968897 0.968897 0 0 92.9556 108.607 36.4376 8.88178e-16 238 0.381265 0.970874 0.970874 -345.35 -344.898 -0.125303 0.131913 0.342167 1 0.341806 2 0.010 NA
-SNPID_61 RSID_61 NA 61 A G NA 0 0 4.23891 477.362 17.3994 -3.40172e-13 499 0.486813 0.962915 0.962915 0 0 2.10852 250.652 8.23998 7.21645e-15 261 0.488254 0.964276 0.964276 0 0 2.1304 226.71 9.15941 -7.10543e-15 238 0.485233 0.961421 0.961421 -345.35 -345.256 -0.251172 0.579765 0.664847 1 0.664024 2 0.000 NA
-SNPID_62 RSID_62 NA 62 A G NA 0 0 35.8387 183.747 279.414 1.12799e-13 499 0.255936 0.952102 0.952102 0 0 20.0403 100.716 140.244 8.77076e-15 261 0.269724 0.952475 0.952475 0 0 15.7984 83.0317 139.17 1.27676e-14 238 0.240816 0.951547 0.951547 -345.35 -344.795 -0.154611 0.146991 0.292873 1 0.291859 2 0.000 NA
-SNPID_63 RSID_63 NA 63 A G NA 0 0 317.314 155.464 26.2219 8.51763e-13 499 0.208324 0.63399 0.63399 0 0 166.212 80.0256 14.7622 2.9976e-15 261 0.209866 0.640441 0.640441 0 0 151.102 75.4382 11.4598 -6.99441e-15 238 0.206634 0.626822 0.626822 -345.35 -345.339 0.028447 0.188054 0.879762 1 0.879749 2 0.000 NA
-SNPID_64 RSID_64 NA 64 A G NA 0 0 4.02621 27.9273 467.046 -2.2915e-13 499 0.0360519 0.435257 0.435257 0 0 2.10764 16.944 241.948 -1.9984e-15 261 0.0405351 0.496304 0.496304 0 0 1.91857 10.9833 225.098 1.90958e-14 238 0.0311354 0.34808 0.34808 -345.35 -344.842 -0.438453 0.440356 0.319406 1 0.313307 2 0.000 NA
-SNPID_65 RSID_65 NA 65 A G NA 0 0 44.9781 166.824 287.198 2.25597e-13 499 0.257295 0.515349 0.515349 0 0 22.6305 81.3541 157.015 2.44249e-15 261 0.242558 0.514164 0.514164 0 0 22.3476 85.4699 130.182 -1.22125e-15 238 0.273456 0.515333 0.515333 -345.35 -344.378 0.253237 0.182142 0.164429 1 0.163085 2 0.000 NA
-SNPID_66 RSID_66 NA 66 A G NA 0 0 155.158 255.857 87.9854 -2.82441e-13 499 0.432693 0.97172 0.97172 0 0 84.0837 132.363 44.553 5.55112e-16 261 0.424271 0.971448 0.971448 0 0 71.0743 123.493 43.4323 -1.44329e-15 238 0.441929 0.971997 0.971997 -345.35 -345.18 -0.0775971 0.132913 0.559342 1 0.559212 2 0.000 NA
-SNPID_67 RSID_67 NA 67 A G NA 0 0 218.464 211.434 69.1018 -3.96128e-13 499 0.350338 0.97156 0.97156 0 0 110.81 110.616 39.5737 -3.10862e-15 261 0.363532 0.971562 0.971562 0 0 107.654 100.817 29.5282 1.83187e-14 238 0.335869 0.971507 0.971507 -345.35 -344.948 0.117023 0.130566 0.370106 1 0.36953 2 0.000 NA
-SNPID_68 RSID_68 NA 68 A G NA 0 0 260.574 206.359 32.0669 2.83329e-13 499 0.271035 0.954226 0.954226 0 0 130.287 113.686 17.0272 1.06581e-14 261 0.283027 0.95671 0.95671 0 0 130.286 92.6738 15.0398 4.77396e-15 238 0.257885 0.951258 0.951258 -345.35 -344.911 0.140627 0.150226 0.349219 1 0.348431 2 0.000 NA
-SNPID_69 RSID_69 NA 69 A G NA 0 0 389.327 93.3991 16.2735 -1.68754e-13 499 0.126198 0.738748 0.738748 0 0 210.58 42.9998 7.41979 1.06581e-14 261 0.110803 0.693441 0.693441 0 0 178.747 50.3994 8.85367 -5.9952e-15 238 0.143081 0.777514 0.777514 -345.35 -344.027 -0.33086 0.204805 0.106205 1 0.103725 2 0.000 NA
-SNPID_70 RSID_70 NA 70 A G NA 0 0 347.808 135.262 15.93 -1.13687e-13 499 0.167457 0.938216 0.938216 0 0 194.707 60.2709 6.02218 5.66214e-15 261 0.138535 0.925996 0.925996 0 0 153.101 74.9913 9.9078 -8.10463e-15 238 0.199174 0.947499 0.947499 -345.35 -341.939 -0.45483 0.175966 0.00974472 1 0.00899725 2 0.000 NA
-SNPID_71 RSID_71 NA 71 A G NA 0 0 56.4758 235.048 207.477 -2.28262e-13 499 0.348696 0.96791 0.96791 0 0 34.7957 120.451 105.754 -7.77156e-15 261 0.364065 0.966243 0.966243 0 0 21.6801 114.597 101.723 3.33067e-16 238 0.331843 0.969742 0.969742 -345.35 -344.738 -0.1528 0.138338 0.26936 1 0.268524 2 0.000 NA
-SNPID_72 RSID_72 NA 72 A G NA 0 0 3.68878 98.6779 396.633 -3.41949e-13 499 0.106268 0.921734 0.921734 0 0 1.93409 54.2795 204.786 -4.996e-15 261 0.111394 0.922531 0.922531 0 0 1.75468 44.3984 191.847 -1.34337e-14 238 0.100646 0.920727 0.920727 -345.35 -345.178 -0.128781 0.219759 0.55787 1 0.557384 2 0.000 NA
-SNPID_73 RSID_73 NA 73 A G NA 0 0 3.69606 27.8474 467.457 -1.7053e-13 499 0.0353101 0.461292 0.461292 0 0 1.92533 14.0134 245.061 7.10543e-15 261 0.0342223 0.450017 0.450017 0 0 1.77074 13.834 222.395 3.21965e-15 238 0.0365031 0.472869 0.472869 -345.35 -345.321 0.104157 0.428017 0.807736 1 0.8078 2 0.000 NA
-SNPID_74 RSID_74 NA 74 A G NA 0 0 30.0598 202.578 266.362 6.83009e-13 499 0.263224 0.951306 0.951306 0 0 17.0724 102.865 141.063 1.42109e-14 261 0.262471 0.950339 0.950339 0 0 12.9874 99.7132 125.299 1.13243e-14 238 0.26405 0.952362 0.952362 -345.35 -345.348 0.00900133 0.151289 0.952556 1 0.952557 2 0.000 NA
-SNPID_75 RSID_75 NA 75 A G NA 0 0 4.60089 31.0637 463.335 8.88178e-16 499 0.0403462 0.440481 0.440481 0 0 2.45632 16.0616 242.482 -1.0103e-14 261 0.0401806 0.42649 0.42649 0 0 2.14457 15.0021 220.853 7.32747e-15 238 0.0405278 0.455697 0.455697 -345.35 -345.35 0.0140618 0.40333 0.972188 1 0.972188 1 0.000 NA
-SNPID_76 RSID_76 NA 76 A G NA 0 0 61.7279 239.24 198.032 -6.83009e-13 499 0.363422 0.939833 0.939833 0 0 27.6039 128.922 104.475 4.77396e-15 261 0.352738 0.937288 0.937288 0 0 34.1239 110.318 93.5578 2.9976e-15 238 0.375139 0.942484 0.942484 -345.35 -345.051 0.107166 0.138713 0.439776 1 0.43953 2 0.000 NA
-SNPID_77 RSID_77 NA 77 A G NA 0 0 31.649 184.515 282.836 5.68434e-14 499 0.24831 0.862565 0.862565 0 0 15.0311 104.33 141.639 3.10862e-15 261 0.257456 0.871141 0.871141 0 0 16.618 80.1858 141.196 6.66134e-16 238 0.238281 0.852514 0.852514 -345.35 -345.068 -0.118173 0.157628 0.453438 1 0.452829 2 0.000 NA
-SNPID_78 RSID_78 NA 78 A G NA 0 0 4.70081 85.5054 408.794 -5.9508e-14 499 0.0950972 0.857142 0.857142 0 0 2.41648 44.8255 213.758 -3.21965e-15 261 0.0951311 0.85701 0.85701 0 0 2.28433 40.6799 195.036 -3.33067e-15 238 0.09506 0.857287 0.857287 -345.35 -345.35 -0.000959091 0.232761 0.996712 1 0.996712 1 0.000 NA
-SNPID_79 RSID_79 NA 79 A G NA 0 0 141.718 223.753 133.529 -5.77316e-14 499 0.491795 0.952896 0.952896 0 0 74.3323 114.313 72.3545 -8.10463e-15 261 0.496211 0.950982 0.950982 0 0 67.3855 109.44 61.1748 5.77316e-15 238 0.486952 0.954987 0.954987 -345.35 -345.31 0.0350839 0.123384 0.776145 1 0.776124 2 0.000 NA
-SNPID_80 RSID_80 NA 80 A G NA 0 0 356.777 128.53 13.6931 1.69642e-13 499 0.156229 0.909649 0.909649 0 0 177.443 75.1549 8.4023 1.02141e-14 261 0.176168 0.919207 0.919207 0 0 179.334 53.3753 5.29075 -5.44009e-15 238 0.134363 0.895861 0.895861 -345.35 -343.566 0.344936 0.184226 0.0611584 1 0.0589243 2 0.000 NA
-SNPID_81 RSID_81 NA 81 A G NA 0 0 8.67152 24.4025 465.926 2.82441e-13 499 0.0418292 0.103722 0.103722 0 0 4.16659 12.504 244.329 1.44329e-14 261 0.0399179 0.0309269 0.0309269 0 0 4.50493 11.8986 221.597 1.11022e-15 238 0.0439253 0.176393 0.176393 -345.35 -345.249 0.203517 0.455215 0.654817 1 0.652986 2 0.000 NA
-SNPID_82 RSID_82 NA 82 A G NA 0 0 4.10973 54.5475 440.343 -6.27942e-13 499 0.0628927 0.829522 0.829522 0 0 2.07953 33.7749 225.146 3.10862e-15 261 0.0726704 0.85615 0.85615 0 0 2.03019 20.7726 215.197 -1.33227e-14 238 0.0521701 0.78897 0.78897 -345.35 -344.353 -0.394575 0.283008 0.163252 1 0.157868 2 0.000 NA
-SNPID_83 RSID_83 NA 83 A G NA 0 0 62.0678 201.263 235.669 3.39284e-13 499 0.326051 0.808999 0.808999 0 0 37.3816 103.615 120.003 -2.22045e-15 261 0.341721 0.810825 0.810825 0 0 24.6863 97.6476 115.666 2.66454e-15 238 0.308866 0.806383 0.806383 -345.35 -344.662 -0.168501 0.144091 0.24224 1 0.24088 2 0.000 NA
-SNPID_84 RSID_84 NA 84 A G NA 0 0 7.53542 47.3867 444.078 -5.41789e-14 499 0.0625827 0.481313 0.481313 0 0 3.30445 21.146 236.55 4.88498e-15 261 0.0531703 0.410026 0.410026 0 0 4.23097 26.2407 207.528 -6.10623e-15 238 0.0729046 0.537979 0.537979 -345.35 -344.124 0.500735 0.322447 0.120442 1 0.117322 2 0.000 NA
-SNPID_85 RSID_85 NA 85 A G NA 0 0 29.7911 157.515 311.694 -2.85993e-13 499 0.217532 0.791115 0.791115 0 0 14.2181 86.9961 159.786 -2.55351e-15 261 0.221135 0.803089 0.803089 0 0 15.573 70.5187 151.908 -2.77556e-15 238 0.213581 0.777613 0.777613 -345.35 -345.302 -0.0514839 0.165578 0.75585 1 0.755734 2 0.000 NA
-SNPID_86 RSID_86 NA 86 A G NA 0 0 288.804 177.79 32.4053 -3.9968e-13 499 0.243087 0.963415 0.963415 0 0 156.306 86.0071 18.6867 -1.11022e-16 261 0.236361 0.963123 0.963123 0 0 132.498 91.7833 13.7186 -1.26565e-14 238 0.250463 0.963702 0.963702 -345.35 -345.215 -0.0769865 0.148086 0.603149 1 0.603119 2 0.000 NA
-SNPID_87 RSID_87 NA 87 A G NA 0 0 11.6655 24.4549 462.88 -6.24389e-13 499 0.0478817 -0.159554 -0.159554 0 0 5.80653 12.3045 242.889 4.21885e-15 261 0.0458191 -0.173651 -0.173651 0 0 5.85901 12.1504 219.991 -1.43219e-14 238 0.0501437 -0.145603 -0.145603 -345.35 -345.184 0.305803 0.527688 0.562242 1 0.564343 2 0.000 NA
-SNPID_88 RSID_88 NA 88 A G NA 0 0 262.429 195.892 40.6789 -3.97904e-13 499 0.277806 0.881548 0.881548 0 0 128.367 113.022 19.6115 1.53211e-14 261 0.291657 0.891165 0.891165 0 0 134.062 82.8708 21.0674 1.08802e-14 238 0.262617 0.870026 0.870026 -345.35 -344.769 0.161082 0.14978 0.282169 1 0.280962 2 0.000 NA
-SNPID_89 RSID_89 NA 89 A G NA 0 0 86.3628 238.711 173.926 -6.24389e-13 499 0.412261 0.936003 0.936003 0 0 42.5208 123.596 94.8828 1.44329e-15 261 0.39969 0.929469 0.929469 0 0 43.8419 115.115 79.0433 7.32747e-15 238 0.426048 0.942939 0.942939 -345.35 -344.974 0.114665 0.13232 0.386174 1 0.385805 2 0.000 NA
-SNPID_90 RSID_90 NA 90 A G NA 0 0 3.6455 50.2087 445.146 -1.14575e-13 499 0.0576149 0.856748 0.856748 0 0 1.90856 24.7436 234.348 5.55112e-15 261 0.054714 0.838639 0.838639 0 0 1.73694 25.4651 210.798 -2.33147e-15 238 0.0607962 0.874687 0.874687 -345.35 -345.259 0.120269 0.281968 0.669718 1 0.669576 2 0.000 NA
-SNPID_91 RSID_91 NA 91 A G NA 0 0 197.564 238.104 63.3314 -6.27054e-13 499 0.365498 0.968028 0.968028 0 0 103.717 121.61 35.6725 7.43849e-15 261 0.369646 0.968356 0.968356 0 0 93.8468 116.494 27.6589 1.88738e-15 238 0.36095 0.967661 0.967661 -345.35 -345.307 0.0399392 0.135855 0.76877 1 0.768729 2 0.000 NA
-SNPID_92 RSID_92 NA 92 A G NA 0 0 8.79753 113.654 376.548 -2.85993e-13 499 0.131513 0.929542 0.929542 0 0 2.88904 63.2585 194.853 -9.99201e-15 261 0.132254 0.934376 0.934376 0 0 5.90849 50.396 181.696 7.88258e-15 238 0.1307 0.924186 0.924186 -345.35 -345.347 -0.0146056 0.1943 0.940079 1 0.940073 2 0.010 NA
-SNPID_93 RSID_93 NA 93 A G NA 0 0 477.644 17.0239 4.33259 -3.9968e-13 499 0.0257405 0.357602 0.357602 0 0 249.484 8.61095 2.90479 -1.26565e-14 261 0.0276255 0.353108 0.353108 0 0 228.159 8.41292 1.42781 -1.94289e-14 238 0.0236734 0.363103 0.363103 -345.35 -345.237 0.230073 0.484428 0.634831 1 0.634208 2 0.000 NA
-SNPID_94 RSID_94 NA 94 A G NA 0 0 390.169 88.5066 20.324 -2.26485e-13 499 0.129413 0.590131 0.590131 0 0 199.765 50.6523 10.5832 6.32827e-15 261 0.137584 0.608366 0.608366 0 0 190.405 37.8543 9.74085 1.11022e-16 238 0.120454 0.567143 0.567143 -345.35 -344.945 0.190697 0.212708 0.369973 1 0.367919 2 0.000 NA
-SNPID_95 RSID_95 NA 95 A G NA 0 0 46.2036 228.363 224.434 2.26485e-13 499 0.321413 0.970638 0.970638 0 0 27.6352 113.718 119.647 1.12133e-14 261 0.323732 0.967177 0.967177 0 0 18.5684 114.645 104.787 2.22045e-16 238 0.318869 0.974462 0.974462 -345.35 -345.336 -0.0241937 0.141366 0.864112 1 0.864102 2 0.000 NA
-SNPID_96 RSID_96 NA 96 A G NA 0 0 81.318 225.17 192.512 -8.88178e-16 499 0.388583 0.666167 0.666167 0 0 39.4871 119.824 101.689 1.34337e-14 261 0.380839 0.662487 0.662487 0 0 41.8309 105.346 90.8227 -2.22045e-15 238 0.397076 0.669949 0.669949 -345.35 -345.158 0.0953387 0.153643 0.534915 1 0.534743 2 0.000 NA
-SNPID_97 RSID_97 NA 97 A G NA 0 0 31.8581 165.444 301.698 -3.97904e-13 499 0.229619 0.768599 0.768599 0 0 17.4229 85.7325 157.845 -9.21485e-15 261 0.230993 0.757351 0.757351 0 0 14.4352 79.7115 143.853 6.66134e-15 238 0.228113 0.781039 0.781039 -345.35 -345.343 -0.0195544 0.165156 0.905751 1 0.905746 2 0.000 NA
-SNPID_98 RSID_98 NA 98 A G NA 0 0 301.478 173.939 23.5826 3.41061e-13 499 0.221547 0.958507 0.958507 0 0 152.336 93.863 14.8014 1.33227e-14 261 0.236525 0.961208 0.961208 0 0 149.143 80.0761 8.78112 1.77636e-15 238 0.205123 0.955095 0.955095 -345.35 -344.597 0.193092 0.157798 0.22108 1 0.21971 2 0.000 NA
-SNPID_99 RSID_99 NA 99 A G NA 0 0 7.4611 59.3449 432.194 -6.83009e-13 499 0.0744159 0.764039 0.764039 0 0 4.71228 28.2949 227.993 -1.28786e-14 261 0.0722595 0.76339 0.76339 0 0 2.74881 31.05 204.201 -1.9762e-14 238 0.0767807 0.764677 0.764677 -345.35 -345.309 0.0728116 0.25421 0.774554 1 0.774613 2 0.000 NA
-SNPID_100 RSID_100 NA 100 A G NA 0 0 75.1365 241.746 182.117 -6.81233e-13 499 0.392805 0.832737 0.832737 0 0 36.0138 127.348 97.6385 -5.21805e-15 261 0.381945 0.824181 0.824181 0 0 39.1227 114.399 84.4787 -9.76996e-15 238 0.404714 0.841742 0.841742 -345.35 -345.019 0.116772 0.143653 0.416291 1 0.415951 2 0.000 NA
-SNPID_101 RSID_101 NA 101 A G NA 0 0 71.2191 250.978 176.803 -4.53859e-13 499 0.394204 0.970861 0.970861 0 0 38.6484 134.474 87.8776 6.66134e-16 261 0.405691 0.970729 0.970729 0 0 32.5707 116.504 88.9254 -3.9968e-15 238 0.381608 0.970972 0.970972 -345.35 -345.021 -0.110038 0.13564 0.417223 1 0.416791 2 0.000 NA
-SNPID_102 RSID_102 NA 102 A G NA 0 0 327.806 142.957 28.2372 1.7053e-13 499 0.199831 0.662841 0.662841 0 0 168.527 77.0627 15.41 -1.88738e-15 261 0.206672 0.685034 0.685034 0 0 159.279 65.8939 12.8272 1.88738e-15 238 0.192328 0.636918 0.636918 -345.35 -345.141 0.117561 0.181867 0.51801 1 0.517305 2 0.000 NA
-SNPID_103 RSID_103 NA 103 A G NA 0 0 95.522 260.019 143.459 4.54747e-13 499 0.451967 0.951854 0.951854 0 0 51.7154 134.982 74.3028 -4.21885e-15 261 0.456729 0.95019 0.95019 0 0 43.8066 125.037 69.1562 9.88098e-15 238 0.446745 0.953676 0.953676 -345.35 -345.295 -0.0447937 0.134267 0.73867 1 0.738627 2 0.000 NA
-SNPID_104 RSID_104 NA 104 A G NA 0 0 302.217 168.962 27.8211 -5.67546e-13 499 0.225054 0.950761 0.950761 0 0 156.091 90.9271 13.9821 -1.35447e-14 261 0.227761 0.950426 0.950426 0 0 146.126 78.0348 13.8389 -4.44089e-15 238 0.222085 0.951131 0.951131 -345.35 -345.327 0.0332223 0.153374 0.828513 1 0.828478 2 0.000 NA
-SNPID_105 RSID_105 NA 105 A G NA 0 0 56.2891 238.368 204.343 -5.12479e-13 499 0.35165 0.941939 0.941939 0 0 26.281 131.015 103.704 -5.77316e-15 261 0.351679 0.944917 0.944917 0 0 30.008 107.354 100.638 1.11022e-15 238 0.351617 0.938672 0.938672 -345.35 -345.35 -0.00030686 0.140374 0.998256 1 0.998256 1 0.000 NA
-SNPID_106 RSID_106 NA 106 A G NA 0 0 130.52 251.764 116.716 1.77636e-15 499 0.486167 0.972745 0.972745 0 0 66.323 135.263 59.4139 1.18794e-14 261 0.486764 0.972004 0.972004 0 0 64.1974 116.501 57.3017 -3.88578e-15 238 0.485513 0.973557 0.973557 -345.35 -345.349 0.005201 0.129216 0.967894 1 0.967894 1 0.010 NA
-SNPID_107 RSID_107 NA 107 A G NA 0 0 202.317 215.881 80.8018 3.41949e-13 499 0.378241 0.947861 0.947861 0 0 102.829 116.263 41.9088 -3.44169e-15 261 0.383296 0.949904 0.949904 0 0 99.4887 99.6184 38.8929 -1.09912e-14 238 0.372698 0.945583 0.945583 -345.35 -345.292 0.0438599 0.128973 0.733804 1 0.733745 2 0.000 NA
-SNPID_108 RSID_108 NA 108 A G NA 0 0 448.351 48.6402 2.00873 1.12799e-13 499 0.0527632 0.810249 0.810249 0 0 237.99 21.9383 1.07141 -7.21645e-15 261 0.0461323 0.777435 0.777435 0 0 210.361 26.7019 0.937326 5.21805e-15 238 0.0600348 0.83797 0.83797 -345.35 -344.774 -0.333565 0.31176 0.284645 1 0.283022 2 0.000 NA
-SNPID_109 RSID_109 NA 109 A G NA 0 0 322.623 149.548 26.8289 -4.00568e-13 499 0.203613 0.922561 0.922561 0 0 162.472 81.095 17.4334 -1.89848e-14 261 0.222149 0.930305 0.930305 0 0 160.152 68.4527 9.39546 6.43929e-15 238 0.183285 0.912348 0.912348 -345.35 -344.183 0.242267 0.159375 0.128486 1 0.126489 2 0.000 NA
-SNPID_110 RSID_110 NA 110 A G NA 0 0 15.9444 479.095 3.96096 2.26485e-13 499 0.487992 0.966555 0.966555 0 0 9.10366 250.027 1.86949 -6.55032e-15 261 0.486141 0.967852 0.967852 0 0 6.84079 229.068 2.09148 -7.10543e-15 238 0.490022 0.965133 0.965133 -345.35 -345.183 -0.348305 0.607059 0.566131 1 0.562912 2 0.000 NA
-SNPID_111 RSID_111 NA 111 A G NA 0 0 49.9071 202.463 246.63 -1.14575e-13 499 0.302883 0.952836 0.952836 0 0 27.9666 100.758 132.275 9.21485e-15 261 0.300175 0.95085 0.95085 0 0 21.9405 101.705 114.355 -1.59872e-14 238 0.305852 0.954989 0.954989 -345.35 -345.331 0.0270935 0.138447 0.844849 1 0.844852 2 0.000 NA
-SNPID_112 RSID_112 NA 112 A G NA 0 0 338.06 134.448 26.492 5.64881e-13 499 0.187807 0.894237 0.894237 0 0 177.886 64.502 18.6116 7.43849e-15 261 0.194876 0.895428 0.895428 0 0 160.174 69.9457 7.8804 4.66294e-15 238 0.180056 0.892766 0.892766 -345.35 -345.173 0.0962864 0.161792 0.55176 1 0.551316 2 0.000 NA
-SNPID_113 RSID_113 NA 113 A G NA 0 0 127.584 251.197 120.219 -2.27374e-13 499 0.49262 0.927654 0.927654 0 0 56.9791 146.187 57.8339 1.18794e-14 261 0.498362 0.930081 0.930081 0 0 70.6048 105.01 62.3851 1.03251e-14 238 0.482732 0.924935 0.924935 -345.35 -345.157 0.0822252 0.132249 0.534111 1 0.533924 2 0.000 NA
-SNPID_114 RSID_114 NA 114 A G NA 0 0 7.94191 91.6676 399.39 1.69642e-13 499 0.107767 0.818438 0.818438 0 0 4.11863 47.0084 209.873 1.63203e-14 261 0.105835 0.809452 0.809452 0 0 3.82328 44.6592 189.518 -1.52101e-14 238 0.109886 0.827957 0.827957 -345.35 -345.326 0.048758 0.219825 0.824467 1 0.824482 2 0.000 NA
-SNPID_115 RSID_115 NA 115 A G NA 0 0 314.66 147.621 36.719 4.53859e-13 499 0.221502 0.755606 0.755606 0 0 162.612 77.5232 20.865 -3.55271e-15 261 0.228454 0.762682 0.762682 0 0 152.048 70.0982 15.854 2.55351e-15 238 0.213879 0.747309 0.747309 -345.35 -345.179 0.0943537 0.161483 0.559023 1 0.558608 2 0.000 NA
-SNPID_116 RSID_116 NA 116 A G NA 0 0 360.995 123.447 14.5577 -5.69322e-13 499 0.152868 0.943892 0.943892 0 0 187.965 65.2942 7.74088 -1.43219e-14 261 0.154743 0.946608 0.946608 0 0 173.03 58.1529 6.81682 2.22045e-16 238 0.150812 0.940847 0.940847 -345.35 -345.335 0.0307284 0.177255 0.862371 1 0.862337 2 0.000 NA
-SNPID_117 RSID_117 NA 117 A G NA 0 0 5.42159 51.2885 442.29 6.27054e-13 499 0.0622562 0.648692 0.648692 0 0 3.33489 28.6817 228.983 6.66134e-16 261 0.0677232 0.668707 0.668707 0 0 2.0867 22.6067 213.307 1.72085e-14 238 0.0562608 0.622138 0.622138 -345.35 -344.984 -0.257185 0.302032 0.394484 1 0.392377 2 0.010 NA
-SNPID_118 RSID_118 NA 118 A G NA 0 0 79.8613 251.142 167.997 -1.69642e-13 499 0.411688 0.976621 0.976621 0 0 52.3798 125.599 83.0211 -2.33147e-15 261 0.4413 0.976032 0.976032 0 0 27.4815 125.543 84.976 7.77156e-16 238 0.379213 0.977098 0.977098 -345.35 -343.229 -0.275355 0.134391 0.0404713 1 0.0394484 2 0.000 NA
-SNPID_119 RSID_119 NA 119 A G NA 0 0 458.598 37.4663 2.93516 2.85105e-13 499 0.0434235 0.661199 0.661199 0 0 242.247 17.2898 1.46344 -5.32907e-15 261 0.0387293 0.635761 0.635761 0 0 216.352 20.1765 1.47172 -1.88738e-15 238 0.0485714 0.683301 0.683301 -345.35 -344.968 -0.311921 0.357103 0.382404 1 0.381868 2 0.000 NA
-SNPID_120 RSID_120 NA 120 A G NA 0 0 276.88 172.759 49.3613 -7.95808e-13 499 0.272026 0.962058 0.962058 0 0 149.385 88.8261 22.7889 1.28786e-14 261 0.257479 0.959623 0.959623 0 0 127.495 83.9329 26.5724 9.4369e-15 238 0.287978 0.964458 0.964458 -345.35 -344.813 -0.141578 0.136692 0.300318 1 0.299897 2 0.000 NA
-SNPID_121 RSID_121 NA 121 A G NA 0 0 3.92139 37.1884 457.89 4.56524e-13 499 0.0451215 0.681434 0.681434 0 0 1.58667 19.0994 240.314 1.73195e-14 261 0.0426682 0.659434 0.659434 0 0 2.33472 18.089 217.576 2.22045e-16 238 0.0478119 0.702983 0.702983 -345.35 -345.257 0.146074 0.337981 0.6656 1 0.6654 2 0.000 NA
-SNPID_122 RSID_122 NA 122 A G NA 0 0 8.89532 113.163 376.942 -3.96128e-13 499 0.131216 0.808478 0.808478 0 0 4.64379 59.3935 196.963 1.32117e-14 261 0.131573 0.802649 0.802649 0 0 4.25153 53.7693 179.979 -2.88658e-15 238 0.130824 0.814902 0.814902 -345.35 -345.349 -0.00806365 0.208016 0.969078 1 0.969074 1 0.000 NA
-SNPID_123 RSID_123 NA 123 A G NA 0 0 334.103 144.446 20.451 -2.30038e-13 499 0.18572 0.925376 0.925376 0 0 176.616 73.2439 11.1397 9.99201e-15 261 0.182995 0.928243 0.928243 0 0 157.486 71.2025 9.31132 -1.21014e-14 238 0.188708 0.922297 0.922297 -345.35 -345.322 -0.0390091 0.165568 0.813737 1 0.81376 2 0.000 NA
-SNPID_124 RSID_124 NA 124 A G NA 0 0 481.018 15.939 2.04329 5.59552e-14 499 0.0200657 0.488441 0.488441 0 0 250.882 9.0247 1.09378 8.54872e-15 261 0.0214794 0.511026 0.511026 0 0 230.136 6.9143 0.949509 0 238 0.0185154 0.459665 0.459665 -345.35 -345.268 0.223641 0.552861 0.685834 1 0.684891 2 0.000 NA
-SNPID_125 RSID_125 NA 125 A G NA 0 0 376.544 111.271 11.1851 -1.77636e-15 499 0.133909 0.870027 0.870027 0 0 195.7 58.7239 6.5762 0 261 0.137694 0.877087 0.877087 0 0 180.844 52.5471 4.60886 2.77556e-15 238 0.129758 0.861847 0.861847 -345.35 -345.276 0.0754698 0.195658 0.699701 1 0.699477 2 0.000 NA
-SNPID_126 RSID_126 NA 126 A G NA 0 0 11.3843 91.319 396.297 -8.88178e-16 499 0.114316 0.764145 0.764145 0 0 7.85358 44.3845 208.762 5.66214e-15 261 0.115118 0.758784 0.758784 0 0 3.53073 46.9345 187.535 6.43929e-15 238 0.113437 0.770097 0.770097 -345.35 -345.346 -0.0192898 0.214703 0.928411 1 0.928404 2 0.000 NA
-SNPID_127 RSID_127 NA 127 A G NA 0 0 298.378 164.057 36.5649 4.00568e-13 499 0.237662 0.864642 0.864642 0 0 150.915 90.7154 19.3697 -3.10862e-15 261 0.247998 0.865307 0.865307 0 0 147.463 73.3421 17.1951 2.33147e-14 238 0.226328 0.863675 0.863675 -345.35 -345.013 0.125213 0.152663 0.412106 1 0.411393 2 0.000 NA
-SNPID_128 RSID_128 NA 128 A G NA 0 0 276.491 190.669 31.8393 -1.25056e-12 499 0.254858 0.955913 0.955913 0 0 154.006 93.9939 12.9998 -5.44009e-15 261 0.229873 0.953228 0.953228 0 0 122.485 96.6755 18.8394 -1.11022e-16 238 0.282257 0.958174 0.958174 -345.35 -343.454 -0.291455 0.150288 0.0524642 1 0.0514927 2 0.000 NA
-SNPID_129 RSID_129 NA 129 A G NA 0 0 492.051 4.93874 2.01002 5.41789e-14 499 0.00897674 -0.109181 -0.109181 0 0 256.047 3.90233 1.05098 1.54321e-14 261 0.0115025 0.152123 0.152123 0 0 236.005 1.03641 0.959039 -1.11022e-16 238 0.00620692 -0.640026 -0.640026 -345.35 -343.594 8.98149 57.133 0.875085 1 0.0608798 8 0.000 NA
-SNPID_130 RSID_130 NA 130 A G NA 0 0 389.466 94.924 14.6102 5.68434e-14 499 0.124393 0.763389 0.763389 0 0 207.583 48.3859 5.03075 1.27676e-14 261 0.111968 0.739708 0.739708 0 0 181.882 46.5382 9.57942 1.28786e-14 238 0.138019 0.784387 0.784387 -345.35 -344.479 -0.269039 0.204521 0.188357 1 0.186873 2 0.000 NA
-SNPID_131 RSID_131 NA 131 A G NA 0 0 262.956 195.326 40.7178 -5.10703e-13 499 0.277316 0.934467 0.934467 0 0 142.816 98.8687 19.3156 -3.55271e-15 261 0.26341 0.933035 0.933035 0 0 120.141 96.4573 21.4022 -1.84297e-14 238 0.292566 0.935797 0.935797 -345.35 -344.799 -0.151953 0.144862 0.294202 1 0.293716 2 0.000 NA
-SNPID_132 RSID_132 NA 132 A G NA 0 0 417.617 75.496 5.88733 3.98792e-13 499 0.0874455 0.836934 0.836934 0 0 219.809 38.6784 2.51216 -9.88098e-15 261 0.0837216 0.834012 0.834012 0 0 197.807 36.8176 3.37516 6.66134e-15 238 0.0915293 0.839827 0.839827 -345.35 -345.243 -0.109973 0.237825 0.643786 1 0.643787 2 0.000 NA
-SNPID_133 RSID_133 NA 133 A G NA 0 0 458.858 36.3463 3.79611 2.27374e-13 499 0.0440266 0.798168 0.798168 0 0 236.452 22.615 1.93319 -8.10463e-15 261 0.0507306 0.828925 0.828925 0 0 222.406 13.7313 1.86292 -5.66214e-15 238 0.0366747 0.751601 0.751601 -345.35 -344.715 0.36663 0.329691 0.26612 1 0.259728 2 0.000 NA
-SNPID_134 RSID_134 NA 134 A G NA 0 0 70.951 424.413 3.6359 1.68754e-13 499 0.43255 0.966631 0.966631 0 0 36.901 222.14 1.95927 2.66454e-15 261 0.433062 0.967173 0.967173 0 0 34.05 202.273 1.67663 -1.33227e-15 238 0.431989 0.966036 0.966036 -345.35 -345.348 0.018679 0.264356 0.943669 1 0.943676 2 0.000 NA
-SNPID_135 RSID_135 NA 135 A G NA 0 0 54.0912 206.548 238.36 7.99361e-13 499 0.315361 0.902792 0.902792 0 0 27.3485 104.192 129.459 6.21725e-15 261 0.304385 0.897625 0.897625 0 0 26.7427 102.356 108.901 -1.33227e-14 238 0.327398 0.908119 0.908119 -345.35 -345.027 0.112852 0.140435 0.421634 1 0.421387 2 0.000 NA
-SNPID_136 RSID_136 NA 136 A G NA 0 0 130.961 252.64 115.399 -2.26485e-13 499 0.484407 0.864298 0.864298 0 0 62.3337 139.879 58.7871 1.45439e-14 261 0.493206 0.868902 0.868902 0 0 68.6273 112.76 56.6123 2.55351e-15 238 0.474758 0.85914 0.85914 -345.35 -345.151 0.0869182 0.137668 0.527804 1 0.527575 2 0.000 NA
-SNPID_137 RSID_137 NA 137 A G NA 0 0 154.771 236.715 107.514 2.84217e-13 499 0.452648 0.708027 0.708027 0 0 79.0028 126.358 55.6388 8.77076e-15 261 0.455241 0.694429 0.694429 0 0 75.7682 110.357 51.875 -7.66054e-15 238 0.449804 0.722952 0.722952 -345.35 -345.33 0.0291821 0.146833 0.842463 1 0.842455 2 0.000 NA
-SNPID_138 RSID_138 NA 138 A G NA 0 0 302.001 167.037 29.9618 2.2915e-13 499 0.227416 0.946377 0.946377 0 0 165.879 81.1686 13.9526 3.9968e-15 261 0.208954 0.944204 0.944204 0 0 136.122 85.8687 16.0092 -3.44169e-15 238 0.247662 0.948266 0.948266 -345.35 -344.282 -0.221936 0.152167 0.144703 1 0.143826 2 0.000 NA
-SNPID_139 RSID_139 NA 139 A G NA 0 0 57.8095 187.176 254.015 5.11591e-13 499 0.303402 0.72408 0.72408 0 0 28.3854 101.921 130.694 2.9976e-15 261 0.304007 0.719763 0.719763 0 0 29.4241 85.2551 123.321 7.54952e-15 238 0.302738 0.728823 0.728823 -345.35 -345.349 -0.00717068 0.150685 0.962045 1 0.962044 2 0.010 NA
-SNPID_140 RSID_140 NA 140 A G NA 0 0 66.24 214.496 218.264 -7.38964e-13 499 0.347671 0.965661 0.965661 0 0 33.6502 109.773 117.577 5.32907e-15 261 0.339221 0.963963 0.963963 0 0 32.5898 104.723 100.687 1.22125e-15 238 0.356938 0.967454 0.967454 -345.35 -345.181 0.0767274 0.131922 0.56083 1 0.560744 2 0.000 NA
-SNPID_141 RSID_141 NA 141 A G NA 0 0 387.196 101.432 10.3723 -6.03961e-14 499 0.122422 0.85829 0.85829 0 0 204.405 49.9473 6.64746 3.33067e-15 261 0.121154 0.856534 0.856534 0 0 182.79 51.4849 3.72485 1.55431e-15 238 0.123812 0.860176 0.860176 -345.35 -345.341 -0.0271117 0.20236 0.89342 1 0.893431 2 0.000 NA
-SNPID_142 RSID_142 NA 142 A G NA 0 0 25.0652 463.854 10.0811 1.12799e-13 499 0.484986 0.916241 0.916241 0 0 12.0293 244.073 4.89724 3.33067e-16 261 0.486337 0.91849 0.91849 0 0 13.0359 219.78 5.1839 9.54792e-15 238 0.483504 0.913773 0.913773 -345.35 -345.278 0.206565 0.543966 0.704139 1 0.703059 2 0.000 NA
-SNPID_143 RSID_143 NA 143 A G NA 0 0 10.7585 122.481 365.761 -1.77636e-15 499 0.144286 0.864369 0.864369 0 0 4.87067 62.8228 193.306 -1.44329e-15 261 0.139012 0.869044 0.869044 0 0 5.88786 59.6578 172.454 7.77156e-16 238 0.15007 0.85949 0.85949 -345.35 -345.209 0.102842 0.193188 0.59449 1 0.594569 2 0.000 NA
-SNPID_144 RSID_144 NA 144 A G NA 0 0 31.2903 192.699 275.01 -1.13687e-12 499 0.255792 0.944161 0.944161 0 0 12.3058 107.647 141.047 9.99201e-15 261 0.253369 0.942359 0.942359 0 0 18.9846 85.0524 133.963 3.77476e-15 238 0.258449 0.946108 0.946108 -345.35 -345.332 0.0286871 0.1506 0.848928 1 0.848934 2 0.000 NA
-SNPID_145 RSID_145 NA 145 A G NA 0 0 318.276 162.189 18.5348 7.95808e-13 499 0.199658 0.88062 0.88062 0 0 172.481 78.3099 10.2086 8.21565e-15 261 0.189133 0.876714 0.876714 0 0 145.795 83.8792 8.32617 4.77396e-15 238 0.211201 0.884381 0.884381 -345.35 -344.911 -0.159904 0.170746 0.349015 1 0.348659 2 0.000 NA
-SNPID_146 RSID_146 NA 146 A G NA 0 0 10.7289 105.125 383.146 3.40172e-13 499 0.126836 0.884721 0.884721 0 0 5.46338 62.3598 193.177 -1.11022e-16 261 0.140396 0.897602 0.897602 0 0 5.26553 42.7652 189.969 -1.39888e-14 238 0.111967 0.867084 0.867084 -345.35 -344.37 -0.278248 0.200078 0.164317 1 0.161548 2 0.000 NA
-SNPID_147 RSID_147 NA 147 A G NA 0 0 333.054 142.739 23.2074 -1.3074e-12 499 0.189533 0.846748 0.846748 0 0 178.769 67.6208 14.6099 -1.90958e-14 261 0.185519 0.838103 0.838103 0 0 154.284 75.1182 8.59746 -6.66134e-15 238 0.193935 0.855875 0.855875 -345.35 -345.288 -0.0597851 0.168917 0.72339 1 0.723376 2 0.000 NA
-SNPID_148 RSID_148 NA 148 A G NA 0 0 426.337 67.0657 5.59741 -7.97584e-13 499 0.0784173 0.895392 0.895392 0 0 223.649 33.5727 3.77831 7.32747e-15 261 0.0787919 0.899758 0.899758 0 0 202.688 33.493 1.81909 8.88178e-16 238 0.0780066 0.890559 0.890559 -345.35 -345.349 0.0112612 0.24004 0.962582 1 0.962578 2 0.000 NA
-SNPID_149 RSID_149 NA 149 A G NA 0 0 381.486 107.031 10.4832 6.80345e-13 499 0.128254 0.897202 0.897202 0 0 197.19 58.5026 5.30753 2.22045e-16 261 0.132409 0.903861 0.903861 0 0 184.296 48.528 5.17568 6.21725e-15 238 0.123696 0.889425 0.889425 -345.35 -345.26 0.0833054 0.196239 0.671194 1 0.670888 2 0.000 NA
-SNPID_150 RSID_150 NA 150 A G NA 0 0 8.98872 63.0225 426.989 -2.66454e-15 499 0.0811623 0.573883 0.573883 0 0 4.65708 32.2918 224.051 -6.10623e-15 261 0.079705 0.576654 0.576654 0 0 4.33163 30.7307 202.938 7.43849e-15 238 0.0827604 0.570921 0.570921 -345.35 -345.329 0.0563642 0.272098 0.835895 1 0.835933 2 0.000 NA
-SNPID_151 RSID_151 NA 151 A G NA 0 0 226.185 227.08 45.7353 7.40741e-13 499 0.319189 0.961061 0.961061 0 0 115.63 121.479 23.8909 5.77316e-15 261 0.324254 0.962658 0.962658 0 0 110.554 105.601 21.8444 8.54872e-15 238 0.313635 0.959269 0.959269 -345.35 -345.279 0.0535078 0.142325 0.70695 1 0.706861 2 0.000 NA
-SNPID_152 RSID_152 NA 152 A G NA 0 0 238.111 188.303 72.5854 9.64562e-13 499 0.334142 0.498582 0.498582 0 0 124.103 103.495 33.4018 9.65894e-15 261 0.326243 0.503134 0.503134 0 0 114.008 84.8083 39.1836 -5.21805e-15 238 0.342806 0.493391 0.493391 -345.35 -345.114 -0.114549 0.166775 0.492178 1 0.491924 2 0.000 NA
-SNPID_153 RSID_153 NA 153 A G NA 0 0 376.56 108.099 14.3402 5.10703e-13 499 0.137054 0.903963 0.903963 0 0 198.053 55.6871 7.25991 -1.21014e-14 261 0.134496 0.897283 0.897283 0 0 178.508 52.4122 7.08025 -6.55032e-15 238 0.139859 0.911039 0.911039 -345.35 -345.32 -0.0458395 0.185263 0.804576 1 0.804594 2 0.000 NA
-SNPID_154 RSID_154 NA 154 A G NA 0 0 282.825 178.908 37.2667 5.70211e-13 499 0.25395 0.94241 0.94241 0 0 143.836 90.0825 27.0813 1.22125e-15 261 0.276331 0.942395 0.942395 0 0 138.989 88.826 10.1854 2.66454e-14 238 0.229405 0.942055 0.942055 -345.35 -343.892 0.250488 0.147409 0.0892687 1 0.0876953 2 0.000 NA
-SNPID_155 RSID_155 NA 155 A G NA 0 0 192.306 236.443 70.2514 1.7053e-13 499 0.377701 0.938672 0.938672 0 0 104.584 117.312 39.1042 -1.18794e-14 261 0.37456 0.936358 0.936358 0 0 87.7218 119.131 31.1472 2.44249e-15 238 0.381146 0.941185 0.941185 -345.35 -345.326 -0.0300977 0.135482 0.824195 1 0.824194 2 0.000 NA
-SNPID_156 RSID_156 NA 156 A G NA 0 0 110.622 240.211 148.167 -5.68434e-13 499 0.46238 0.924108 0.924108 0 0 55.084 131.46 74.4561 1.46549e-14 261 0.462889 0.930042 0.930042 0 0 55.5382 108.751 73.7108 7.32747e-15 238 0.461822 0.917598 0.917598 -345.35 -345.35 -0.00449049 0.130057 0.972457 1 0.972456 1 0.000 NA
-SNPID_157 RSID_157 NA 157 A G NA 0 0 105.94 247.197 145.862 -1.02318e-12 499 0.459998 0.847877 0.847877 0 0 61.0007 127.927 72.0721 4.21885e-15 261 0.47879 0.85162 0.85162 0 0 44.9397 119.27 73.7902 -1.66533e-15 238 0.43939 0.843217 0.843217 -345.35 -344.434 -0.187021 0.138536 0.177021 1 0.175921 2 0.000 NA
-SNPID_158 RSID_158 NA 158 A G NA 0 0 26.351 183.158 289.491 -2.30038e-13 499 0.236333 0.773314 0.773314 0 0 11.0044 100.16 149.836 8.77076e-15 261 0.234039 0.797676 0.797676 0 0 15.3466 82.9983 139.655 2.9976e-15 238 0.238848 0.746956 0.746956 -345.35 -345.329 0.03531 0.171688 0.837054 1 0.837087 2 0.000 NA
-SNPID_159 RSID_159 NA 159 A G NA 0 0 75.7536 234.777 188.469 -4.55636e-13 499 0.387058 0.957273 0.957273 0 0 37.9915 121.319 101.69 -3.44169e-15 261 0.377973 0.953591 0.953591 0 0 37.7622 113.458 86.7798 9.99201e-16 238 0.397022 0.961204 0.961204 -345.35 -345.153 0.0831404 0.132462 0.53023 1 0.530086 2 0.000 NA
-SNPID_160 RSID_160 NA 160 A G NA 0 0 70.016 225.344 203.64 -1.77636e-15 499 0.366108 0.969883 0.969883 0 0 33.5784 116.737 110.684 5.44009e-15 261 0.352287 0.968897 0.968897 0 0 36.4376 108.607 92.9556 2.22045e-15 238 0.381265 0.970874 0.970874 -345.35 -344.898 0.125303 0.131913 0.342167 1 0.341806 2 0.000 NA
-SNPID_161 RSID_161 NA 161 A G NA 0 0 17.3994 477.362 4.23891 1.15463e-13 499 0.486813 0.962915 0.962915 0 0 8.23998 250.652 2.10852 4.77396e-15 261 0.488254 0.964276 0.964276 0 0 9.15941 226.71 2.1304 -9.4369e-15 238 0.485233 0.961421 0.961421 -345.35 -345.256 0.251172 0.579765 0.664847 1 0.664024 2 0.000 NA
-SNPID_162 RSID_162 NA 162 A G NA 0 0 279.414 183.747 35.8387 5.10703e-13 499 0.255936 0.952102 0.952102 0 0 140.244 100.716 20.0403 4.77396e-15 261 0.269724 0.952475 0.952475 0 0 139.17 83.0317 15.7984 7.32747e-15 238 0.240816 0.951547 0.951547 -345.35 -344.795 0.154611 0.146991 0.292873 1 0.291859 2 0.000 NA
-SNPID_163 RSID_163 NA 163 A G NA 0 0 26.2219 155.464 317.314 -6.24389e-13 499 0.208324 0.63399 0.63399 0 0 14.7622 80.0256 166.212 6.66134e-15 261 0.209866 0.640441 0.640441 0 0 11.4598 75.4382 151.102 -4.44089e-16 238 0.206634 0.626822 0.626822 -345.35 -345.339 -0.028447 0.188054 0.879762 1 0.879749 2 0.000 NA
-SNPID_164 RSID_164 NA 164 A G NA 0 0 467.046 27.9273 4.02621 -1.73195e-13 499 0.0360519 0.435257 0.435257 0 0 241.948 16.944 2.10764 -1.22125e-15 261 0.0405351 0.496304 0.496304 0 0 225.098 10.9833 1.91857 1.92069e-14 238 0.0311354 0.34808 0.34808 -345.35 -344.842 0.438453 0.440356 0.319406 1 0.313307 2 0.000 NA
-SNPID_165 RSID_165 NA 165 A G NA 0 0 287.198 166.824 44.9781 5.50671e-14 499 0.257295 0.515349 0.515349 0 0 157.015 81.3541 22.6305 -1.44329e-15 261 0.242558 0.514164 0.514164 0 0 130.182 85.4699 22.3476 4.77396e-15 238 0.273456 0.515333 0.515333 -345.35 -344.378 -0.253237 0.182142 0.164429 1 0.163085 2 0.000 NA
-SNPID_166 RSID_166 NA 166 A G NA 0 0 87.9854 255.857 155.158 5.15143e-13 499 0.432693 0.97172 0.97172 0 0 44.553 132.363 84.0837 6.43929e-15 261 0.424271 0.971448 0.971448 0 0 43.4323 123.493 71.0743 -2.66454e-15 238 0.441929 0.971997 0.971997 -345.35 -345.18 0.0775971 0.132913 0.559342 1 0.559212 2 0.000 NA
-SNPID_167 RSID_167 NA 167 A G NA 0 0 69.1018 211.434 218.464 8.88178e-16 499 0.350338 0.97156 0.97156 0 0 39.5737 110.616 110.81 -7.99361e-15 261 0.363532 0.971562 0.971562 0 0 29.5282 100.817 107.654 1.68754e-14 238 0.335869 0.971507 0.971507 -345.35 -344.948 -0.117023 0.130566 0.370106 1 0.36953 2 0.000 NA
-SNPID_168 RSID_168 NA 168 A G NA 0 0 32.0669 206.359 260.574 2.84217e-13 499 0.271035 0.954226 0.954226 0 0 17.0272 113.686 130.287 6.66134e-15 261 0.283027 0.95671 0.95671 0 0 15.0398 92.6738 130.286 1.77636e-15 238 0.257885 0.951258 0.951258 -345.35 -344.911 -0.140627 0.150226 0.349219 1 0.348431 2 0.000 NA
-SNPID_169 RSID_169 NA 169 A G NA 0 0 16.2735 93.3991 389.327 -8.50875e-13 499 0.126198 0.738748 0.738748 0 0 7.41979 42.9998 210.58 8.77076e-15 261 0.110803 0.693441 0.693441 0 0 8.85367 50.3994 178.747 -3.33067e-15 238 0.143081 0.777514 0.777514 -345.35 -344.027 0.33086 0.204805 0.106205 1 0.103725 2 0.000 NA
-SNPID_170 RSID_170 NA 170 A G NA 0 0 15.93 135.262 347.808 5.68434e-14 499 0.167457 0.938216 0.938216 0 0 6.02218 60.2709 194.707 3.66374e-15 261 0.138535 0.925996 0.925996 0 0 9.9078 74.9913 153.101 -1.9984e-15 238 0.199174 0.947499 0.947499 -345.35 -341.939 0.45483 0.175966 0.00974472 1 0.00899725 2 0.000 NA
-SNPID_171 RSID_171 NA 171 A G NA 0 0 207.477 235.048 56.4758 -2.85993e-13 499 0.348696 0.96791 0.96791 0 0 105.754 120.451 34.7957 1.77636e-15 261 0.364065 0.966243 0.966243 0 0 101.723 114.597 21.6801 4.77396e-15 238 0.331843 0.969742 0.969742 -345.35 -344.738 0.1528 0.138338 0.26936 1 0.268524 2 0.000 NA
-SNPID_172 RSID_172 NA 172 A G NA 0 0 396.633 98.6779 3.68878 -7.96696e-13 499 0.106268 0.921734 0.921734 0 0 204.786 54.2795 1.93409 -1.05471e-14 261 0.111394 0.922531 0.922531 0 0 191.847 44.3984 1.75468 -1.5099e-14 238 0.100646 0.920727 0.920727 -345.35 -345.178 0.128781 0.219759 0.55787 1 0.557384 2 0.000 NA
-SNPID_173 RSID_173 NA 173 A G NA 0 0 467.457 27.8474 3.69606 4.52971e-13 499 0.0353101 0.461292 0.461292 0 0 245.061 14.0134 1.92533 9.65894e-15 261 0.0342223 0.450017 0.450017 0 0 222.395 13.834 1.77074 1.33227e-15 238 0.0365031 0.472869 0.472869 -345.35 -345.321 -0.104157 0.428017 0.807736 1 0.8078 2 0.000 NA
-SNPID_174 RSID_174 NA 174 A G NA 0 0 266.362 202.578 30.0598 -1.68754e-13 499 0.263224 0.951306 0.951306 0 0 141.063 102.865 17.0724 1.24345e-14 261 0.262471 0.950339 0.950339 0 0 125.299 99.7132 12.9874 3.44169e-15 238 0.26405 0.952362 0.952362 -345.35 -345.348 -0.00900133 0.151289 0.952556 1 0.952557 2 0.000 NA
-SNPID_175 RSID_175 NA 175 A G NA 0 0 463.335 31.0637 4.60089 -3.96128e-13 499 0.0403462 0.440481 0.440481 0 0 242.482 16.0616 2.45632 -4.55191e-15 261 0.0401806 0.42649 0.42649 0 0 220.853 15.0021 2.14457 9.54792e-15 238 0.0405278 0.455697 0.455697 -345.35 -345.35 -0.0140618 0.40333 0.972188 1 0.972188 1 0.000 NA
-SNPID_176 RSID_176 NA 176 A G NA 0 0 198.032 239.24 61.7279 -6.26166e-13 499 0.363422 0.939833 0.939833 0 0 104.475 128.922 27.6039 -8.10463e-15 261 0.352738 0.937288 0.937288 0 0 93.5578 110.318 34.1239 9.4369e-15 238 0.375139 0.942484 0.942484 -345.35 -345.051 -0.107166 0.138713 0.439776 1 0.43953 2 0.000 NA
-SNPID_177 RSID_177 NA 177 A G NA 0 0 282.836 184.515 31.649 -2.25597e-13 499 0.24831 0.862565 0.862565 0 0 141.639 104.33 15.0311 1.66533e-15 261 0.257456 0.871141 0.871141 0 0 141.196 80.1858 16.618 -1.55431e-15 238 0.238281 0.852514 0.852514 -345.35 -345.068 0.118173 0.157628 0.453438 1 0.452829 2 0.000 NA
-SNPID_178 RSID_178 NA 178 A G NA 0 0 408.794 85.5054 4.70081 -1.1724e-13 499 0.0950972 0.857142 0.857142 0 0 213.758 44.8255 2.41648 -2.9976e-15 261 0.0951311 0.85701 0.85701 0 0 195.036 40.6799 2.28433 -6.10623e-15 238 0.09506 0.857287 0.857287 -345.35 -345.35 0.000959091 0.232761 0.996712 1 0.996712 1 0.000 NA
-SNPID_179 RSID_179 NA 179 A G NA 0 0 133.529 223.753 141.718 2.26485e-13 499 0.491795 0.952896 0.952896 0 0 72.3545 114.313 74.3323 -1.22125e-14 261 0.496211 0.950982 0.950982 0 0 61.1748 109.44 67.3855 2.77556e-15 238 0.486952 0.954987 0.954987 -345.35 -345.31 -0.0350839 0.123384 0.776145 1 0.776124 2 0.000 NA
-SNPID_180 RSID_180 NA 180 A G NA 0 0 13.6931 128.53 356.777 -3.41949e-13 499 0.156229 0.909649 0.909649 0 0 8.4023 75.1549 177.443 1.77636e-15 261 0.176168 0.919207 0.919207 0 0 5.29075 53.3753 179.334 -8.54872e-15 238 0.134363 0.895861 0.895861 -345.35 -343.566 -0.344936 0.184226 0.0611584 1 0.0589243 2 0.000 NA
-SNPID_181 RSID_181 NA 181 A G NA 0 0 465.926 24.4025 8.67152 1.13687e-13 499 0.0418292 0.103722 0.103722 0 0 244.329 12.504 4.16659 1.34337e-14 261 0.0399179 0.0309269 0.0309269 0 0 221.597 11.8986 4.50493 5.21805e-15 238 0.0439253 0.176393 0.176393 -345.35 -345.249 -0.203517 0.455215 0.654817 1 0.652986 2 0.000 NA
-SNPID_182 RSID_182 NA 182 A G NA 0 0 440.343 54.5475 4.10973 -3.41949e-13 499 0.0628927 0.829522 0.829522 0 0 225.146 33.7749 2.07953 -2.9976e-15 261 0.0726704 0.85615 0.85615 0 0 215.197 20.7726 2.03019 -9.54792e-15 238 0.0521701 0.78897 0.78897 -345.35 -344.353 0.394575 0.283008 0.163252 1 0.157868 2 0.000 NA
-SNPID_183 RSID_183 NA 183 A G NA 0 0 235.669 201.263 62.0678 1.11022e-13 499 0.326051 0.808999 0.808999 0 0 120.003 103.615 37.3816 -1.05471e-14 261 0.341721 0.810825 0.810825 0 0 115.666 97.6476 24.6863 1.22125e-15 238 0.308866 0.806383 0.806383 -345.35 -344.662 0.168501 0.144091 0.24224 1 0.24088 2 0.000 NA
-SNPID_184 RSID_184 NA 184 A G NA 0 0 444.078 47.3867 7.53542 -4.51195e-13 499 0.0625827 0.481313 0.481313 0 0 236.55 21.146 3.30445 -1.02141e-14 261 0.0531703 0.410026 0.410026 0 0 207.528 26.2407 4.23097 -1.05471e-14 238 0.0729046 0.537979 0.537979 -345.35 -344.124 -0.500735 0.322447 0.120442 1 0.117322 2 0.000 NA
-SNPID_185 RSID_185 NA 185 A G NA 0 0 311.694 157.515 29.7911 -5.86198e-14 499 0.217532 0.791115 0.791115 0 0 159.786 86.9961 14.2181 4.88498e-15 261 0.221135 0.803089 0.803089 0 0 151.908 70.5187 15.573 -4.21885e-15 238 0.213581 0.777613 0.777613 -345.35 -345.302 0.0514839 0.165578 0.75585 1 0.755734 2 0.000 NA
-SNPID_186 RSID_186 NA 186 A G NA 0 0 32.4053 177.79 288.804 6.21725e-13 499 0.243087 0.963415 0.963415 0 0 18.6867 86.0071 156.306 -1.08802e-14 261 0.236361 0.963123 0.963123 0 0 13.7186 91.7833 132.498 -1.36557e-14 238 0.250463 0.963702 0.963702 -345.35 -345.215 0.0769865 0.148086 0.603149 1 0.603119 2 0.000 NA
-SNPID_187 RSID_187 NA 187 A G NA 0 0 462.88 24.4549 11.6655 -6.25278e-13 499 0.0478817 -0.159554 -0.159554 0 0 242.889 12.3045 5.80653 1.06581e-14 261 0.0458191 -0.173651 -0.173651 0 0 219.991 12.1504 5.85901 -1.83187e-14 238 0.0501437 -0.145603 -0.145603 -345.35 -345.184 -0.305803 0.527688 0.562242 1 0.564343 2 0.000 NA
-SNPID_188 RSID_188 NA 188 A G NA 0 0 40.6789 195.892 262.429 -9.6545e-13 499 0.277806 0.881548 0.881548 0 0 19.6115 113.022 128.367 8.88178e-15 261 0.291657 0.891165 0.891165 0 0 21.0674 82.8708 134.062 5.77316e-15 238 0.262617 0.870026 0.870026 -345.35 -344.769 -0.161082 0.14978 0.282169 1 0.280962 2 0.000 NA
-SNPID_189 RSID_189 NA 189 A G NA 0 0 173.926 238.711 86.3628 2.82441e-13 499 0.412261 0.936003 0.936003 0 0 94.8828 123.596 42.5208 -1.44329e-15 261 0.39969 0.929469 0.929469 0 0 79.0433 115.115 43.8419 4.77396e-15 238 0.426048 0.942939 0.942939 -345.35 -344.974 -0.114665 0.13232 0.386174 1 0.385805 2 0.000 NA
-SNPID_190 RSID_190 NA 190 A G NA 0 0 445.146 50.2087 3.6455 3.38396e-13 499 0.0576149 0.856748 0.856748 0 0 234.348 24.7436 1.90856 6.10623e-15 261 0.054714 0.838639 0.838639 0 0 210.798 25.4651 1.73694 -5.21805e-15 238 0.0607962 0.874687 0.874687 -345.35 -345.259 -0.120269 0.281968 0.669718 1 0.669576 2 0.000 NA
-SNPID_191 RSID_191 NA 191 A G NA 0 0 63.3314 238.104 197.564 -8.88178e-16 499 0.365498 0.968028 0.968028 0 0 35.6725 121.61 103.717 9.4369e-15 261 0.369646 0.968356 0.968356 0 0 27.6589 116.494 93.8468 2.22045e-15 238 0.36095 0.967661 0.967661 -345.35 -345.307 -0.0399392 0.135855 0.76877 1 0.768729 2 0.000 NA
-SNPID_192 RSID_192 NA 192 A G NA 0 0 376.548 113.654 8.79753 4.54747e-13 499 0.131513 0.929542 0.929542 0 0 194.853 63.2585 2.88904 -8.88178e-15 261 0.132254 0.934376 0.934376 0 0 181.696 50.396 5.90849 8.65974e-15 238 0.1307 0.924186 0.924186 -345.35 -345.347 0.0146056 0.1943 0.940079 1 0.940073 2 0.000 NA
-SNPID_193 RSID_193 NA 193 A G NA 0 0 4.33259 17.0239 477.644 -3.41061e-13 499 0.0257405 0.357602 0.357602 0 0 2.90479 8.61095 249.484 -9.21485e-15 261 0.0276255 0.353108 0.353108 0 0 1.42781 8.41292 228.159 -1.07692e-14 238 0.0236734 0.363103 0.363103 -345.35 -345.237 -0.230073 0.484428 0.634831 1 0.634208 2 0.000 NA
-SNPID_194 RSID_194 NA 194 A G NA 0 0 20.324 88.5066 390.169 1.1191e-13 499 0.129413 0.590131 0.590131 0 0 10.5832 50.6523 199.765 -4.44089e-16 261 0.137584 0.608366 0.608366 0 0 9.74085 37.8543 190.405 2.10942e-15 238 0.120454 0.567143 0.567143 -345.35 -344.945 -0.190697 0.212708 0.369973 1 0.367919 2 0.000 NA
-SNPID_195 RSID_195 NA 195 A G NA 0 0 224.434 228.363 46.2036 1.69642e-13 499 0.321413 0.970638 0.970638 0 0 119.647 113.718 27.6352 2.55351e-15 261 0.323732 0.967177 0.967177 0 0 104.787 114.645 18.5684 5.55112e-16 238 0.318869 0.974462 0.974462 -345.35 -345.336 0.0241937 0.141366 0.864112 1 0.864102 2 0.000 NA
-SNPID_196 RSID_196 NA 196 A G NA 0 0 192.512 225.17 81.318 1.13776e-12 499 0.388583 0.666167 0.666167 0 0 101.689 119.824 39.4871 1.4766e-14 261 0.380839 0.662487 0.662487 0 0 90.8227 105.346 41.8309 -9.32587e-15 238 0.397076 0.669949 0.669949 -345.35 -345.158 -0.0953387 0.153643 0.534915 1 0.534743 2 0.000 NA
-SNPID_197 RSID_197 NA 197 A G NA 0 0 301.698 165.444 31.8581 -5.67546e-13 499 0.229619 0.768599 0.768599 0 0 157.845 85.7325 17.4229 -3.88578e-15 261 0.230993 0.757351 0.757351 0 0 143.853 79.7115 14.4352 6.32827e-15 238 0.228113 0.781039 0.781039 -345.35 -345.343 0.0195544 0.165156 0.905751 1 0.905746 2 0.000 NA
-SNPID_198 RSID_198 NA 198 A G NA 0 0 23.5826 173.939 301.478 -5.59552e-14 499 0.221547 0.958507 0.958507 0 0 14.8014 93.863 152.336 1.80966e-14 261 0.236525 0.961208 0.961208 0 0 8.78112 80.0761 149.143 -1.55431e-15 238 0.205123 0.955095 0.955095 -345.35 -344.597 -0.193092 0.157798 0.22108 1 0.21971 2 0.000 NA
-SNPID_199 RSID_199 NA 199 A G NA 0 0 432.194 59.3449 7.4611 2.30038e-13 499 0.0744159 0.764039 0.764039 0 0 227.993 28.2949 4.71228 -9.88098e-15 261 0.0722595 0.76339 0.76339 0 0 204.201 31.05 2.74881 -1.67644e-14 238 0.0767807 0.764677 0.764677 -345.35 -345.309 -0.0728116 0.25421 0.774554 1 0.774613 2 0.000 NA
-SNPID_200 RSID_200 NA 200 A G NA 0 0 182.117 241.746 75.1365 -2.25597e-13 499 0.392805 0.832737 0.832737 0 0 97.6385 127.348 36.0138 -1.27676e-14 261 0.381945 0.824181 0.824181 0 0 84.4787 114.399 39.1227 -9.21485e-15 238 0.404714 0.841742 0.841742 -345.35 -345.019 -0.116772 0.143653 0.416291 1 0.415951 2 0.000 NA
-# Completed successfully at 2015-08-05 16:58:28

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-    <body>
-        <div class="header" id="header1">
-            <div class="header_text">
-				bingwa
-			</div>
-            <div class="header_subtext">
-				model-based meta-analysis for genome-wide association studies
-            </div>
-        </div>
-        <div class="button_bar">
-            <div class="nav_button" name="overview">
-                <span class = "nav_button_content" >
-                    overview
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-                    documentation
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-                    tutorial
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-                    file formats
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-            <div id="overview" style="display:none">
-                <p>
-					<em>This page documents version 2.0-dev of bingwa, which is currently considered experimental</em>.
-				</p>
-                <p>
-					<strong>Introduction.</strong>
-					<span class="program_name">bingwa</span> is a command-line tool used to carry out meta-analysis of genome-wide association studies.
-					It is particularly suited for use with the program <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html">SNPTEST</a>,
-					but can also be used with other association testing programs such as <a href="http://www.helsinki.fi/~mjxpirin/download.html">MMM</a>.
-					Features of bingwa include:
-				</p>
-				<ul>
-					<li>
-						Direct support for SNPTEST output files.
-					</li>
-					<li>
-						Support for fixed-effect frequentist and a flexible bayesian meta-analysis method.
-					</li>
-					<li>
-						Support for both univariate and multivariate meta-analysis (including support
-						for meta-analysing tests performed using  <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html#multinomial_tests">SNPTEST's multinomial test</a>).
-					</li>
-				</ul>
-                <p>
-                    <strong>Disclaimer.</strong>
-					This page documents version 2.0-dev of bingwa which is currently considered <b>experimental</b>.
-					This means we expect some features not to work, or
-					not to work well, or to work wrongly, or to destroy your computer or sanity.
-                </p>
-                <p>
-					<strong>References.</strong>
-					If you make use of bingwa, please cite the following paper, which describes the key methodology underlying the program:
-					<ul>
-					<li>
-						"<em>Imputation-Based Meta-Analysis of Severe Malaria in Three African Populations</em>",
-						Band et al, PLOS Genetics (2013)
-					</li>
-				</ul>
-				</p>
-				<p>
-					Similar methodology was also developed in these papers:
-				<ul>
-					<li>
-						"<em>Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke</em>",
-						International Stroke Genetics Consortium (ISGC) and Wellcome Trust Case Control Consortium 2 (WTCCC2), Nat. Genetics (2012)
-					</li>
-					<li>"<em>Reappraisal of known malaria resistance loci in a large multi-centre study</em>", Rockett et al, Nat. Genetics (2014).</li>
-				</ul>
-                <p>
-                    <strong>Acknowledgements.</strong> Bingwa was developed at the <a href="http://www.well.ox.ac.uk/home">Wellcome Trust Centre for Human Genetics</a>, Oxford, UK.
-					A full list of people who contributed to the methodology will appear here.
-                </p>
-            </div>
-            <div id="documentation" style="display:none">
-                <div class="display_diagram_right">
-                    <!--<object data="style/images/inthinnerator-flow.svg"  type="image/svg+xml" align="center">
-					</object>-->
-                </div>
-                <p>
-                    The general process followed by bingwa is shown on the right.  In brief, bingwa proceeds by
-					<ol>
-						<li>Loading association test data from a set of cohorts (e.g. SNPTEST files).</li>
-						<li>Matching variants between cohorts.</li>
-						<li>Computing frequentist meta-analysis and one or more Bayes factors.</li>
-						<li>Writing results.</li>
-					</ol>
-                </p>
-				<p>
-					We'll update this page with more details on the method soon.  In the meantime the <a href="#tutorial">tutorial</a>
-					has usage examples.
-                </p>
-			</div>
-            <div id="tutorial" style="display:none">
-				<h2>
-					Running bingwa
-				</h2>
-                <div class="tutorial_header">
-                    This page shows common command lines to use bingwa.  These examples assume the program is being run from a directory
-					containing two SNPTEST files, <span class="monospace">cohort1.snptest</span> and <span class="monospace">cohort2.snptest</span>.
-					You can see example files in the <a href="example/">examples directory</a>.
-                </div>
-                <div class="tutorial_separator">
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        View the program usage page
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -help | less
-                    </div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Compute fixed-effect meta-analysis of the two files
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest cohort2.snptest -o output.sqlite
-					</div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest cohort2.snptest -flat-file -o output.csv
-                    </div>
-                    <div class="task_notes">
-                        <b>Note</b>: By default bingwa writes output to a sqlite file (more details below).  Use <code>-flat-file</code> to write a flat file instead.
-							Flat files are space, tab or comma-delimited according to the filename extension.
-                    </div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Compute a fixed-effect bayesian meta-analysis
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest cohort2.snptest -o output.sqlite -prior sd=0.2,0.2/cor=1,1,1 
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: The above specifies a multivariate normal (MVN) prior on the 'true' effects
-						that is centred at zero and has variance-covariance matrix with every entry equal 0.2<sup>2</sup>.
-						(Bingwa will print this model to the screen output so you can double-check this).
-						Under this model the true effects in the two populations are assumed perfectly correlated; the only
-						variation comes from estimation effects represented by the within-study standard errors.
-						The bayes factor for this model will be stored in a column named <code>sd=0.2,0.2/cor=1,1,1:bf</code>.
-                    </div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Compute both a fixed and independent-effect bayesian meta-analysis
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest cohort2.snptest -o output.sqlite -prior fixed:sd=0.2,0.2/cor=1,1,1 -prior independent:sd=0.2,0.2/cor=1,0,1 
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: In the above command we've named the models to avoid confusion - now the
-						output will contain <code>fixed:bf</code> and <code>independent:bf</code> columns.
-						Here, the independent model assumes that true effects are uncorrelated between the cohorts - i.e.
-						they have diagonal variance-covariance matrix.
-                        In addition to the two model-specific bayes factors, bingwa will compute a model-averaged bayes factor
-						over all the models specified, named <code>mean_bf</code>.
-                    </div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Avoiding typing all those sds and cors.
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest ... cohort&lt;n&gt;.snptest -o output.sqlite -prior fixed:tau=1/sd=0.2/cor=1 -prior independent:tau=0/sd=0.2/cor=1
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: In the above command we use a short-hand version of the prior specification.
-						The first part (tau) denotes the between-cohort correlation.  The rest now denotes the prior
-						covariance matrix within each cohort.  Thus as before the fixed-effect model reflects a prior
-						covariance with all entries equal to 0.2<sup>2</sup>, while the independent-effect model
-						reflects a diagonal covariance matrix.
-                    </div>
-					<div class="task_notes">
-						We advise always checking the screen output to debug model definitions.
-					</div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Getting nicer output
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest cohort2.snptest -o output.sqlite -table-name Meta -cohort-names set1 set2
-						-analysis-name "My first meta-analysis" 
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: Bingwa includes a number of options that help in giving more interpretable names
-						to the output.  In the above command, we set the name of the table in which the primary output is produced
-						(see the <a href="#file_formats">file formats page for details</a>), a name for the analysis overall,
-						and names for each of the cohorts.
-                    </div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Reweighting models
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest cohort2.snptest -o output.sqlite -prior fixed:sd=0.2,0.2/cor=1,1,1 independent:sd=0.2,0.2/cor=1,0,1 -prior-weights fixed=1 independent=0.5
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: By default all models are equally weighted in the model-average bayes factor.  Use the <code>-prior-weights</code>
-						option to reweight them.  Weights are renormalised to sum to one in the mean bayes factor computation - i.e.
-						the mean Bayes factor is computed as
-						$$\text{BF}_{\text{avg}} = \frac{\sum_i \text{weight}_i \cdot \text{BF}_i}{\sum_i \text{weight}_i}$$
-						where $\text{weight}_i$ and $\text{BF}_i$ are the specified weight and Bayes factor for model $i$.
-						If <code>-prior-weights</code> is specified, any model not specified in the argument is given weight zero in the mean Bayes factor.
-                    </div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Specifying priors in a file
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest cohort2.snptest -o output.sqlite -priors priors.txt
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: When there are many cohorts and several priors to specify, command lines can get rather
-						large an unwieldy.  The <code>-priors</code> option can be used to tell bingwa to load priors
-						from a file instead of the command-line.  Prior files additionally allow for comments and use of
-						whitespace.  See <a href="#file_formats">file formats page</a> for the
-						format of this file.  For example, the above priors could be specified
-                    </div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Getting extra columns in the output
-                    </div>
-                    <div class="task_command_line">
-                        $ bingwa -data cohort1.snptest cohort2.snptest -o output.sqlite -priors priors.txt -extra-columns controls_AA controls_AB controls_BB cases_AA cases_AB cases_BB frequentist_add_null_ll frequentist_add_alternative_ll
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: It's often useful to record extra information from the input files in the output.
-						The <code>-extra-variables</code> option tells bingwa to output a given set of columns
-						in the output.
-                    </div>
-                </div>
-				<div class="tutorial_separator"></div>
-				<h3>
-					Understanding bingwa sqlite output files
-				</h3>
-				<div>
-					<p>
-						Below we've given some examples of using the shell or various programming languages to extract data from a bingwa
-						<a href="http://www.sqlite.org">sqlite</a> file.
-						We assume the file is named <code>bingwa.sqlite</code> and the meta-analysis results were stored
-						in the <code>MetaAnalysis</code> table.
-					</p>
-					<p>
-	                    <b>Note</b>: The <code>sqlite3</code> program is installed by default on most UNIX-like systems.
-						It's quite flexible, and can be used in interactive mode, or to run queries directly from the command-line.
-						We'll use both methods below.
-						See the <a href="https://www.sqlite.org/cli.html">sqlite3 command shell documentation</a> for a full list of options.
-					</p>
-					<h4>Inspecting the contents of the results file</h4>
-					<p>
-						sqlite files can be inspected using the sqlite3 command shell.  Open the file by typing:
-					</p>
-	                    <code>
-							$ sqlite3 -column -header bingwa.sqlite <br/>
-						</code>
-					<p>
-						You should see the sqlite prompt (<code>sqlite3&gt;</code>).  Let's see what tables are stored in this file:
-					</p>
-					<pre>
-sqlite3&gt; .tables
-Analysis                Entity                  MetaAnalysis          
-AnalysisProperty        EntityData              MetaAnalysisView      
-AnalysisPropertyView    EntityDataView          Variant               
-AnalysisStatus          EntityRelationship      VariantIdentifier     
-AnalysisStatusView      EntityRelationshipView  VariantView
-					</pre>
-                    <p>
-                        Here, the main results are stored in the <code>MetaAnalysis</code> table,
-						and bingwa has also created the <code>MetaAnalysisView</code> view which provides a nicer view of the results.
-						(The <code>-table-name</code> option can be used to change the name of the main results table.
-						By default it is a name of the form <code>Analysis&lt;n&gt;</code>, where n is an integer.)
-						The <code>Analysis*</code> and <code>Entity*</code> tables are used to store
-						metadata about the analyses you have run.  Let's see what's stored in this file:
-					</p>
-                    <pre>
-sqlite> SELECT * FROM Analysis ;
-id          name             chunk     
-----------  ---------------  ----------
-1           bingwa analysis  NA        
-
-sqlite> SELECT COUNT(*) AS count FROM MetaAnalysisView
-count  
--------
-200
-					</pre>
-					<p>
-						So this file stores meta-analysis results for 200 variants from a single analysis called "bingwa analysis".
-					</p>
-					<p>
-						In a large, real analysis, it's often useful to use the <code>-analysis-name</code> and <code>-analysis-chunk</code> options to give the analysis a 
-						more descriptive name and explain what part of the data it corresponds to.  It's possible to store several analyses in the same sqlite file
-						(or even in the same table, provided analysis columns are compatible), so this information becomes important to understand the results.
-					</p>
-					<p>
-						Let's have a look at what the results actually look like.  Because there are lots of columns we'll switch sqlite3 to line-based output:
-					</p>
-					<pre>
-sqlite3&gt; .mode line
-sqlite3&gt; SELECT * FROM MetaAnalysisView LIMIT 1 ;
-                                             rsid = KGP1
-                                          alleleA = A
-                                          alleleB = G
-                                         analysis = bingwa analysis
-                                      analysis_id = 1
-                                       variant_id = 1
-                                       chromosome = NA
-                                         position = 1000
-                                       cohort 1:A = 0.0
-                                       cohort 1:B = 0.0
-                                      cohort 1:AA = 168.889999389648
-                                      cohort 1:AB = 240.240005493164
-                                      cohort 1:BB = 87.870002746582
-                                    cohort 1:NULL = 0.0
-                      cohort 1:B_allele_frequency = 0.418490950302478
-                                     cohort 1:maf = 0.418489992618561
-                               cohort 1:ml_beta_1 = 0.100000001490116
-                                 cohort 1:ml_se_1 = 0.0199999995529652
-                                  cohort 1:pvalue = 0.100000001490116
-                                    cohort 1:info = 0.374507993459702
-                                       cohort 2:A = 0.0
-                                       cohort 2:B = 0.0
-                                      cohort 2:AA = 176.800003051758
-                                      cohort 2:AB = 250.979995727539
-                                      cohort 2:BB = 71.2190017700195
-                                    cohort 2:NULL = 0.0
-                      cohort 2:B_allele_frequency = 0.394207201652197
-                                     cohort 2:maf = 0.394199997186661
-                               cohort 2:ml_beta_1 = 0.0799999982118607
-                                 cohort 2:ml_se_1 = 0.0199999995529652
-                                  cohort 2:pvalue = 0.94200998544693
-                                    cohort 2:info = 0.97086101770401
-                   FixedEffectMetaAnalysis:beta_1 = 0.0899999998509884
-                     FixedEffectMetaAnalysis:se_1 = 0.0141421353076296
-            FixedEffectMetaAnalysis:wald_pvalue_1 = 1.96615875463349e-10
-                   FixedEffectMetaAnalysis:pvalue = 1.96615875463348e-10
-			        </pre>
-			   	 	<p>
-						This analysis contains the results of a fixed-effect frequentist analysis of two cohorts, by default called "cohort 1" and "cohort 2".
-						The results file contains columns reflecting genotype counts and model fits in each cohort, and columns containing meta-analysed
-						effect size estimate, standard error, and a two-tailed fixed-effect meta-analysis P-value.
-					</p>
-					<p>
-						<b>Note</b>: the <code>-cohort-names</code> option can be used to name the cohorts in a more useful way.
-					</p>
-				</div>
-                <div class="tutorial_separator"></div>
-				<h2>
-					Processing bingwa sqlite output files
-				</h2>
-				<p>
-					Below are some example commands that process bingwa output in the command-line or in R.
-					See above for a full description of bingwa's sqlite output.
-				</p>
-                <div class="task">
-                    <div class="task_name">
-                        Extract a csv file of all results.
-                    </div>
-                    <div class="task_command_line">
-                        $ sqlite3 -header -csv bingwa.sqlite "SELECT * FROM MetaAnalysisView" > my_file.csv
-					</div>
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Extract results from a specific region.
-                    </div>
-                    <div class="task_command_line">
-                        $ sqlite3 -header -csv bingwa.sqlite "SELECT * FROM MetaAnalysisView WHERE chromosome == '05' AND position BETWEEN 120000000 AND 121000000" > my_file.csv
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: bingwa always stores chromosome identifiers as strings.  Currently these will be two-character strings with single-digit
-						chromosomes appearing as <code>01</code>, <code>02</code>, etc.
-                    </div>
-					
-                </div>
-                <div class="task">
-                    <div class="task_name">
-                        Read bingwa results into R
-                    </div>
-                    <div class="task_command_line">
-						# R code to load bingwa results <br/>
-                        > library( RSQLite )<br/>
-                        > db = dbConnect( dbDriver( "SQLite" ), "bingwa.sqlite" )<br/>
-                        > D = dbGetQuery( db, "SELECT * FROM MetaAnalysisView" )
-					</div>
-                    <div class="task_notes">
-                        <b>Note</b>: You need the RSQLite library installed to process sqlite files from R.
-                    </div>
-					
-                </div>
-            </div>
-            <div id="file_formats" style="display:none">
-				<h3>Input file formats</h3>
-                <div>
-                    Bingwa supports reading SNPTEST output files.  Files are assumed space-, comma- or tab-delimited
-								according to the file extension (<code>.txt</code>, <code>.csv</code> or <code>.tsv</code>).
-                </div>
-				<h3>Output file formats</h3>
-				<p>
-					Bingwa can either output to a flat file or to a table in a sqlite database.  Both have pros and cons.
-				</p>
-				<p>
-				<b>Flat files</b> are simple and easy to use.  However, they can become difficult to read from for very large analyses
-				(such as genome-wide analyses of datasets imputed into recent reference panels) which may require writing
-				special file-handling code.
-				</p>
-				<p>
-					Flat files are written when the <code>-flat-file</code> option is specified.
-				</p>
-				<p>
-					<b>Sqlite files</b> are easy to use via the <a href="https://www.sqlite.org/cli.html">sqlite3 command shell</a>,
-					which is installed on most UNIX-like systems.  They can also be read directly from programming languages,
-					e.g. by using the <a href="https://cran.r-project.org/package=RSQLite">RSQLite package</a> in <a href="">R</a> or
-					the <a href="https://docs.python.org/2/library/sqlite3.html">sqlite3</a> module in python.
-					An attractive feature is that they are <em>indexed</em>, so that data for specific regions of the genome or specific variants can
-					be easily found.  See the <a href='#tutorial'>examples page</a> for code snippets for processing bingwa-produced sqlite files.
-				</p>
-				<p>Sqlite is the default output format for bingwa.</p>
-				<h3>Specifying priors</h3>
-				<p>
-					The file format used for the <code>-priors</code> option follows the following rules.
-					<ul>
-						<li>Blank lines and lines starting with # (comment lines) are ignored.</li>
-						<li>Every other line is part of a prior specification.</li>
-						<li>Each prior may optionally start with a name specification of the form <code>&lt;name&gt;:</code>.
-							(Unnamed priors are given computed names, but it's usually best to name them.)</li>
-						<li>Two forms of prior specification are permissible, <em>full</em> and <em>shorthand</em> prior specification.</li>
-						<li>
-							A <em>full</em> prior specification is of the form <code>sd=&lt;a,b,c,...&gt;/cor=1,x,y,...</code>.
-								Here <code>a,b,c,...</code> are real numbers.  The number of sds specified must be <code>d</code>, the number
-								of parameters in all cohorts put together; the number of correlations specified must be equal to <code>d&times;(d+1)/2</code>.
-								The values of <code>sd</code> specify a diagonal matrix &sigma; with standard deviations on its diagonal, while the values of <code>cor</code> specify the upper triangle of a correlation matrix &Rho;.
-								The resulting prior is &sigma;&times;&Rho;&times;&sigma;
-								
-						</li>
-						<li>
-							A <em>shorthand</em> prior specification is of the form <code>tau=&lt;a&gt;/sd=&lt;b,c,d,...&gt;/cor=1,...</code>.
-								Here <code>a,b,c,...</code> are real numbers.  The number of sds specified must be <code>d</code>, the number
-								of parameters in each cohort; the number of correlations specified must be equal to <code>d&times;(d+1)/2</code>.
-						</li>
-							
-							Prior may be of the form <code>[name:]sd=&lt;value2&gt;[,&lt;value2&lt;&gt;,...]/cor=1[,x,y,z...]</code></li>
-					</ul>
-            </div>
-            <div id="download" style="display:none">
-                <div>
-                    <p>
-                        Bingwa is available either as binaries or as source code.
-                    </p>
-                    <h3>
-                        Binaries
-                    </h3>
-                    <p>
-                        Pre-compiled binaries are available for the following platforms.
-						(See <a href="http://www.well.ox.ac.uk/~gav/resources">here</a> for other builds.)
-                    </p>
-                    <table>
-                        <tr>
-                            <th>
-                                Version
-                            </th>
-                            <th>
-                                Platform
-                            </th>
-                            <th>
-                                File
-                            </th>
-                        </tr>
-                        <tr>
-                            <td>v2-dev<sup>&dagger;</sup></td>
-                            <td>
-                                Ubuntu 12.04 <small>x86-64</small>
-                            </td>
-                            <td>
-                                <a href="http://www.well.ox.ac.uk/~gav/resources/bingwa_v2.0-dev-linux-x86_64.tgz">bingwa_v2.0-dev-linux-x86_64.tgz</a>
-                            </td>
-                        </tr>
-                        <tr>
-                            <td>v2-dev<sup>&dagger;</sup></td>
-                            <td>
-                                CentOS6.5 <small>x86-64</small>
-                            </td>
-                            <td>
-                                <a href="http://www.well.ox.ac.uk/~gav/resources/bingwa_v2.0-dev-linux-x86_64.tgz">bingwa_v2.0-dev-CentOS6.5-x86_64.tgz</a>
-                            </td>
-                        </tr>
-                        <tr>
-                            <td>v2-dev<sup>&dagger;</sup></td>
-                            <td>
-                                Mac OS X
-                            </td>
-                            <td>
-                                <a href="http://www.well.ox.ac.uk/~gav/resources/bingwa_v2.0-dev-osx.tgz">bingwa_v2.0-dev-osx.tgz</a>
-                            </td>
-                        </tr>
-                    </table>
-                    <p>
-					<sup>&dagger;</sup><span class="smalltext">This version of bingwa is considered experimental.
-					</p>
-                    <p>
-                        To run bingwa, download the relevant file and extract it as follows.
-                    </p>
-                    <pre>
-$ tar -xzf bingwa_v2.0-dev-[machine].tgz
-$ cd bingwa_v2.0-dev-[machine]
-$ ./bingwa_v2.0-dev -help
-</pre>
-                    <h3>
-                        Source
-                    </h3>
-                    <p>
-                        The source code to bingwa is built as part of the <a href="http://bitbucket.org/gavinband/qctool">qctool package on bitbucket</a>.
-						See <a href="https://bitbucket.org/gavinband/qctool/wiki/Home">the qctool wiki page</a> for more details.
-					</p>
-                </div>
-            </div>
-        </div>
-    </body>
-</html>

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==================================================================
--- doc/html/bingwa/js/jquery-1.4.2.min.js
+++ doc/html/bingwa/js/jquery-1.4.2.min.js
@@ -1,154 +0,0 @@
-/*!
- * jQuery JavaScript Library v1.4.2
- * http://jquery.com/
- *
- * Copyright 2010, John Resig
- * Dual licensed under the MIT or GPL Version 2 licenses.
- * http://jquery.org/license
- *
- * Includes Sizzle.js
- * http://sizzlejs.com/
- * Copyright 2010, The Dojo Foundation
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- * Date: Sat Feb 13 22:33:48 2010 -0500
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-e&&e.document?e.document.compatMode==="CSS1Compat"&&e.document.documentElement["client"+b]||e.document.body["client"+b]:e.nodeType===9?Math.max(e.documentElement["client"+b],e.body["scroll"+b],e.documentElement["scroll"+b],e.body["offset"+b],e.documentElement["offset"+b]):f===w?c.css(e,d):this.css(d,typeof f==="string"?f:f+"px")}});A.jQuery=A.$=c})(window);

DELETED doc/html/bingwa/js/jquery.ba-hashchange.min.js
Index: doc/html/bingwa/js/jquery.ba-hashchange.min.js
==================================================================
--- doc/html/bingwa/js/jquery.ba-hashchange.min.js
+++ doc/html/bingwa/js/jquery.ba-hashchange.min.js
@@ -1,9 +0,0 @@
-/*
- * jQuery hashchange event - v1.2 - 2/11/2010
- * http://benalman.com/projects/jquery-hashchange-plugin/
- * 
- * Copyright (c) 2010 "Cowboy" Ben Alman
- * Dual licensed under the MIT and GPL licenses.
- * http://benalman.com/about/license/
- */
-(function($,i,b){var j,k=$.event.special,c="location",d="hashchange",l="href",f=$.browser,g=document.documentMode,h=f.msie&&(g===b||g<8),e="on"+d in i&&!h;function a(m){m=m||i[c][l];return m.replace(/^[^#]*#?(.*)$/,"$1")}$[d+"Delay"]=100;k[d]=$.extend(k[d],{setup:function(){if(e){return false}$(j.start)},teardown:function(){if(e){return false}$(j.stop)}});j=(function(){var m={},r,n,o,q;function p(){o=q=function(s){return s};if(h){n=$('<iframe src="javascript:0"/>').hide().insertAfter("body")[0].contentWindow;q=function(){return a(n.document[c][l])};o=function(u,s){if(u!==s){var t=n.document;t.open().close();t[c].hash="#"+u}};o(a())}}m.start=function(){if(r){return}var t=a();o||p();(function s(){var v=a(),u=q(t);if(v!==t){o(t=v,u);$(i).trigger(d)}else{if(u!==t){i[c][l]=i[c][l].replace(/#.*/,"")+"#"+u}}r=setTimeout(s,$[d+"Delay"])})()};m.stop=function(){if(!n){r&&clearTimeout(r);r=0}};return m})()})(jQuery,this);

DELETED doc/html/bingwa/js/local.js
Index: doc/html/bingwa/js/local.js
==================================================================
--- doc/html/bingwa/js/local.js
+++ doc/html/bingwa/js/local.js
@@ -1,60 +0,0 @@
-var globals = {
-	current_page: "none"
-} ;
-
-var setPage = function( page ) {
-	$( ".nav_button" ).children( "span" ).each( function( i ) { $(this).removeClass( "nav_button_selected" ) ; } ) ;
-	$( '[name=' + page + '].nav_button' ).children( 'span' ).addClass( "nav_button_selected" ) ;
-	$( '#' + page ).fadeIn( 30 ) ;
-}
-
-var changePage = function( page ) {
-	if( page != globals.current_page ) {
-		if( globals.current_page != "none" ) {
-			$( '#' + globals.current_page ).fadeOut( 30,
-				function() {
-					setPage( page ) ;
-				} ) ;
-		} else {
-			setPage( page ) ;
-		}
-		globals.current_page = page ;
-		location.hash = page ;
-	}
-}
-
-var setFirstPage = function( default_page ) {
-	if( location.hash == "" ) {
-		location.hash = "#" + default_page ;
-	} else {
-		$( window ).trigger( 'hashchange' ) ;
-	}
-}
-
-$(document).ready(
-	function() {
-		$( ".nav_button" ).hover(
-			function( eventObject ) {
-				name = $(this).attr( "name" ) ;
-				$(this).attr( "src", $(this).attr( "active_src" ) ) ;
-			},
-			function( eventObject ) {
-				name = $(this).attr( "name" ) ;
-				$(this).attr( "src", $(this).attr( "inactive_src" )) ;
-			}
-		)
-		
-		$( ".nav_button" ).click(
-			function( eventObject ) {
-				page = $( this ).attr( 'name' ) ;
-				location.hash = page ;
-			}
-		) ;
-		
-		$(window).bind( 'hashchange', function() {
-			// Get the page.  Omit the leading '#'.
-			var page = location.hash.substring( 1 ) ;
-			changePage( page ) ;
-		} ) ;
-	}
-) ;

DELETED doc/html/bingwa/style/css/default.css
Index: doc/html/bingwa/style/css/default.css
==================================================================
--- doc/html/bingwa/style/css/default.css
+++ doc/html/bingwa/style/css/default.css
@@ -1,202 +0,0 @@
-/*
-img {
-	border: 1px solid red;
-}
-div {
-	border: 1px dotted blue ;
-}
-*/
-
-body {
-	width: 1000px ;
-	margin-left: auto ;
-	margin-right: auto ;
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-img.header_img {
-	float: left ;
-	padding-left: 10px ;
-	padding-right: 10px ;
-}
-
-img.header_arrow {
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-
-.header_text {
-	float: left ;
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-	font-family: Arial, Helvetica, Tahoma, sans-serif;
-	font-size: 40px ;
-}
-
-div.header_subtext > b {
-	font-size: 105% ;
-}
-
-div.header_subtext {
-	padding-top: 20px ;
-	padding-left: 20px ;
-}
-
-div.header {
-	border-bottom: 2px solid black ;
-	font-family: sans-serif ;
-	font-size: 15px ;
-}
-
-strong {
-	font-family: sans-serif ;
-}
-
-.nav_button {
-	margin-top: 10px ;
-	padding-left: 3% ;
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-	width: 14% ;
-	float: left ;
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-	font-family: sans-serif ;
-	font-size: 22px ;
-	text-align: center ;
-	color: #000000;
-}
-
-.nav_button_content {
-	padding-left: 5px ;
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-}
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-.nav_button:hover {
-	color: #AA0000 ;
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-.nav_button_selected {
-	border-bottom: 2px solid black ;
-}
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-div.button_bar {
-	width:900px ;
-	margin-left: auto ;
-	margin-right: auto ;
-	overflow: auto ; /* Forces div to contain its floats. */
-	/* border: 1px solid red ; */
-}
-
-dt {
-	font-weight: bold ;
-	font-style: italic ;
-}
-
-div.main_text {
-	width: 800px ;
-	padding-top: 20px ;
-	margin-left: auto ;
-	margin-right: auto ;
-	font-family: serif ;
-	//border: 1px dotted red ;
-}
-
-.main_text .display_diagram {
-	padding-top: 20px ;
-	width: 460px ;
-	margin-left: auto ;
-	margin-right: auto ;
-}
-
-.display_diagram_right {
-	padding-top: 0px ;
-	margin-left: 50px ;
-	float: right ;
-}
-
-.main_text .terminal_display {
-	height: 110px ;
-	overflow: auto ;
-	padding: 10px ;
-	margin-top: 10px ;
-	border: 1px dotted black ;
-	background-color: #22AD57 ;
-}
-
-#download table {
-	text-align: left ;
-	width: 600px ;
-	border: 1px solid black ;
-	background-color: #CCCCCC ;
-	padding: 10px ;
-}
-
-th {
-	border-bottom: 1px solid black ;
-	font-family: sans-serif ;
-}
-
-h1, h2, h3, h4 {
-	font-family: sans-serif ;
-}
-
-.tutorial_header {
-	width: 100% ;
-	margin: 2px ;
-	overflow: auto ;
-}
-
-.tutorial_separator {
-	width: 100% ;
-	margin: 10px ;
-	border-bottom: 2px solid black ;
-}
-.task {
-	width: 100% ;
-	margin: 2px;
-	margin-top: 10px ;
-	overflow: auto ;
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-
-.task_name {
-	font-family: sans-serif ;
-	font-weight: bold ;
-	float: left ;
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-.task_notes {
-	margin-top: 1px ;
-	margin-bottom: 1px ;
-	float: left ;
-	clear: left ;
-	font-family: sans-serif ;
-	font-size: 0.8em;
-	padding: 5px ;
-}
-
-.monospace {
-	font-family: monospace ;
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-.task_command_line {
-	margin-top: 1px ;
-	margin-bottom: 1px ;
-	padding: 5px ;
-	font-family: monospace ;
-	background-color: #82BD77 ;
-	float: left ;
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-
-.file_formats {
-	width: 90% ;
-	margin-left: auto ;
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-}
-
-.smalltext {
-	font-size: 80% ;
-}

ADDED   doc/html/build-docs.py
Index: doc/html/build-docs.py
==================================================================
--- doc/html/build-docs.py
+++ doc/html/build-docs.py
@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+
+import glob
+import markdown
+import os
+import argparse
+
+parser = argparse.ArgumentParser( description = """Build a documentation website by processing .content.html files into .html files.
+A header and footer is added to each file, and the contents are processed through python-markdown.""" )
+parser.add_argument(
+	'--path', '-p',
+	help = 'Path to operate on'
+)
+parser.add_argument(
+	'--header', 
+	help = 'File containing header text, relative to --path',
+	default = 'header.html'
+)
+parser.add_argument(
+	'--footer',
+	help = 'File containing footer text, relative to --path',
+	default = 'footer.html'
+)
+
+args = parser.parse_args()
+
+print( "Building docs in %s..." % args.path )
+
+contentPath = os.path.join( args.path, 'content' )
+
+headerFilename = "%s/header.html" % contentPath
+footerFilename = "%s/footer.html" % contentPath
+print( "++ Reading header from %s..." % headerFilename )
+header = open( headerFilename, 'r' ).read()
+print( "++ Reading footer from %s..." % headerFilename )
+footer = open( footerFilename, 'r' ).read()
+
+initialDepth = contentPath.count(os.sep)
+total = 0
+for directory, dnames, filenames in os.walk( contentPath ):
+	directoryParts = directory.split( os.sep )
+	outputDirectory = os.sep.join( [ directoryParts[0] ] + directoryParts[2:] )
+	directoryLevel = (directory.count( os.sep ) - initialDepth)
+	for filename in filenames:
+		if filename.endswith( ".content.html" ):
+			print( "++ Processing %s..." % filename )
+			total = total + 1
+			print( "++ Reading content from %s..." % os.path.join( directory, filename ))
+			content = open( os.path.join( directory, filename ), 'r' ).read() ;
+			content = (
+				header.replace( "[ROOT]/", "../" * directoryLevel ) + "\n"
+				+ markdown.markdown(
+					content.replace( "[ROOT]/", "../" * directoryLevel ),
+					extensions=['markdown.extensions.md_in_html', 'mdx_math', 'markdown.extensions.fenced_code', 'tables' ],
+					extension_configs = {
+						"mdx_math": { "enable_dollar_delimiter": True }
+					}
+				) + "\n"
+				+ footer.replace( "[ROOT]/", "../" * directoryLevel )
+			)
+
+			outputFilename = os.path.join( outputDirectory, filename.replace( ".content.html", ".html" ))
+			print( "++ Writing %s..." % outputFilename )
+			outputFile = open( outputFilename, 'w' )
+			outputFile.write( content )
+			outputFile.close()
+
+print( "++ Success, formatted a total of %d files." % total )
+print( "++ Thanks for using build.py" )

ADDED   doc/html/hptest/content/documentation/alphabetical_options.content.html
Index: doc/html/hptest/content/documentation/alphabetical_options.content.html
==================================================================
--- doc/html/hptest/content/documentation/alphabetical_options.content.html
+++ doc/html/hptest/content/documentation/alphabetical_options.content.html
@@ -0,0 +1,66 @@
+<section class="main_text">
+	<h2>Table of options</h2>
+	<p>Below is a list of all options supported by HPTEST.</p>
+	<table class="option_table">
+		<colgroup>
+			<col class="option"></col>
+			<col class="description"></col>
+			<col class="default"></col>
+		</colgroup>
+		<thead>
+			<tr>
+				<th>
+					Option
+				</th>
+				<th>
+					Description
+				</th>
+				<th>
+					Default value?
+				</th>
+			</tr>
+		</thead>
+		<tbody>
+		</tbody>
+	</table>
+</section>
+
+<script>
+	$(document).ready(
+		function() {
+			$.getJSON( "../resources/options.json", function( data ) {
+				console.log( 'gotit' ) ;
+				var options = [] ;
+				$.each( data, function( key, value ) {
+					options.push( key ) ;
+					console.log( key ) ;
+				} ) ;
+				
+				options.sort( function(a,b) {
+					return a.toLowerCase().localeCompare( b.toLowerCase() ) ;
+				}) ;
+				
+				for( var i = 0; i < options.length; ++i ) {
+					$(".option_table > tbody").append(
+						'<tr>'
+						+ '<td>' + options[i] + '</td>'
+						+ '<td>' + data[options[i]]['description'] + '</td>'
+						+ '<td>' + ( data[options[i]].length == 0 ? "N/A" : data[options[i]].default.join( ", " )) + '</td>'
+						+ '/tr>'
+					)
+				}
+				
+				$( ".option_table" ).DataTable(
+					{
+						"paging": false,
+						"language": {
+							"search": "Search command-line options:"
+						}
+					}
+				) ;
+				
+				$('.dataTables_filter').css('float', 'left') ;
+			}) ;
+		}
+	) ;
+</script>

ADDED   doc/html/hptest/content/documentation/download.content.html
Index: doc/html/hptest/content/documentation/download.content.html
==================================================================
--- doc/html/hptest/content/documentation/download.content.html
+++ doc/html/hptest/content/documentation/download.content.html
@@ -0,0 +1,44 @@
+<section class="main_text" markdown="1" >
+###Obtaining HPTEST###
+
+The source code to HPTEST is available as part of the QCTOOL package, which is currently hosted at
+<a href="https://code.enkre.net/qctool">code.enkre.net</a>. To obtain HPTEST you need to download
+version 2.1.9 or above of QCTOOL. The source code can be downloaded from the following link:
+
+<a href="https://code.enkre.net/qctool/zip/v2.1.9/qctool.tgz">https://code.enkre.net/qctool/zip/v2.1.9/qctool.tgz</a>
+
+Please be aware this tarball is generated on the fly and may take a few minutes to download.
+
+###Compiling HPTEST###
+
+QCTOOL uses the <a href="https://waf.io">Waf build system</a> to manage the compilation process.
+For this to work you need python to be installed. (Waf itself is bundled with QCTOOL). A basic
+compilation process goes as follows:
+
+```
+$ ./waf configure
+$ ./waf
+```
+
+The first command configures the project (i.e. makes sure various prerequisites are in place). The
+second part compiles the QCTOOL package.  
+
+If successful you should now be able to try hptest:
+
+```
+$ ./build/release/apps/hptest_v2.1.9
+!! Error (OptionProcessingException): Option "-o" must be supplied..
+!! Run hptest -help for usage information.
+```
+
+The following is a more advanced example that specifies a path to a relevant C and C++ compiler and
+an installation directory.
+
+```
+$ CXX=/path/to/g++ CC=/path/to/gcc ./waf configure --prefix=/path/to/installation/dir
+$ ./waf install
+```
+
+If successful hptest (along with qctool and other tools) will be installed in ``/path/to/installation/dir/usr/bin``
+
+</section>

ADDED   doc/html/hptest/content/documentation/filtering.content.html
Index: doc/html/hptest/content/documentation/filtering.content.html
==================================================================
--- doc/html/hptest/content/documentation/filtering.content.html
+++ doc/html/hptest/content/documentation/filtering.content.html
@@ -0,0 +1,29 @@
+<section class="main_text" markdown="1" >
+
+### Filtering variants ###
+
+The following options can be used to filter variants from the analysis. Each of these options comes in an inclusiong
+variant (``-incl-...``), which tells HPTEST to only focus on the specified variants, and an exclusion variant
+(``-excl-...``) which tells HPTEST to ignore the specified variants, and each applies either to the predictor or outcome genotypes:
+
+* ``-[in|ex]cl-outcome-range``: specify a genomic range or list of ranges to include or exclude outcome variants from.
+
+* ``-[in|ex]cl-outcome-rsids``: specify a set of variant IDs to include or exclude outcome variants from.
+
+* ``-[in|ex]cl-predictor-range``: specify a genomic range or list of ranges to include or exclude predictor variants from.
+
+* ``-[in|ex]cl-predictor-rsids``: specify a set of variant IDs to include or exclude predictor variants from.
+
+### Filtering samples ###
+
+The following options can be used to filter samples from the analysis:
+
+* ``-[in|ex]cl-samples``: specify a list of samples to include or exclude from the analysis. For this purpose, samples are identified
+by their identifier in the first column of the sample file.
+
+* ``-[in|ex]cl-samples-where``: specify a condition to apply to rows of the sample file to determine if the sample
+  should be included or excluded. The general syntax is ``-[in|ex]cl-samples-where '<column>[=|==|!=]<value>'``, which
+  will cause HPTEST to compare the values in the column named <column> of the sample file to the given value, and
+  include/exclude samples based on whether the values match (= or ==) or mismatch (!=).
+
+</section>

ADDED   doc/html/hptest/content/documentation/getting_started.content.html
Index: doc/html/hptest/content/documentation/getting_started.content.html
==================================================================
--- doc/html/hptest/content/documentation/getting_started.content.html
+++ doc/html/hptest/content/documentation/getting_started.content.html
@@ -0,0 +1,217 @@
+<section class="main_text" markdown="1" >
+
+### Getting started with HPTEST ###
+	
+HPTEST tests for association between two sets of genotypes - for example between genotypes of a
+host and of a pathogen infecting those hosts. To do this, it implements the binomial logistic
+regression model:
+
+(1) $$\text{log-odds}( \text{outcome genotype} ) = \left( \text{predictor genotypes}, \text{covariates}... \right) \times \beta$$
+
+in which $\beta$ is a vector of parameters (the regression coefficients). For each predictor and
+outcome genetic variant, HPTEST finds the value of $\beta$ that maximises the corresponding
+likelihood, estimates its standard error (by inspecting the curvature of the likelihood near the
+maximum) and outputs these along with other summaries to the output file. 
+
+By default, HPTEST computes estimates under a weakly informative prior that helps to regularise the
+estimates (this can be turned off with the ``-no-prior`` option.)
+
+For example, the following command:
+```
+$ hptest \
+-outcome parasite.vcf \
+-predictor host.vcf \
+-s samples.sample \
+-o output.csv
+```
+
+regresses each parasite variant (from ``parasite.vcf``) on each host variant (from ``host.vcf``).
+The genotype counts, maximum posterior estimates and other quantities are output to the output file
+(``output.csv``). Additional options allow you to add covariates (``-covariates``), to adjust the
+prior being used (``-prior``) or remove it entirely (``-no-prior``), or to filter the list of
+samples or variants included (e.g. ``-incl-samples``, ``-excl-samples-where``, or
+``-incl-outcome-range``) - see the <a href="[ROOT]/documentation/alphabetical_options.html">list of
+options</a> for more.
+
+### Obtaining HPTEST ###
+
+HPTEST is currently included as part of the <a href="https://code.enkre.net/qctool">QCTOOL
+package</a>, which is currently hosted at <a href="https://code.enkre.net">code.enkre.net</a>. To
+obtain it you will need to download and compile the source code (you need QCTOOL version >= 2.1.9
+for this). See the <a href="[ROOT]/documentation/download.html">download page</a> for more details
+on obtaining and installing HPTEST.
+
+### Running HPTEST ###
+
+In the most basic form HPTEST is run like this:
+```
+hptest -outcome outcome.vcf -predictor predictor.vcf -s samples.sample -o test.csv
+```
+
+where ``outcome.vcf`` and ``predictor.vcf`` contain genotype calls, and ``samples.sample`` contains
+information on the included samples. All three files must represent the same set of individuals and
+they must be in the same order in each file. (The <a
+href="http://www.well.ox.ac.uk/~gav/qctool_v2/documentation/examples/sorting.html">``-reorder``
+option to QCTOOL</a> can help to set this up).
+
+For each predictor and outcome variant, HPTEST will do the following:
+
+1. Both sets of genotypes are loaded. HPTEST can interpret both hard-called genotypes (e.g. GT
+field in a <a href="http://samtools.github.io/hts-specs/">vcf file</a>), and imputed genotype
+probabilities (e.g. GP field in a vcf file, or a <a href="https://www.bgenformat.org">BGEN
+format</a> file). For outcome genotypes, imputed genotypes are thresholded to produce hard calls -
+by default any genotypes with probability < 0.9 are treated as missing. For the predictor genotype,
+HPTEST will sum over the imputed probability distribution as described in <a
+href="[ROOT]/documentation/technical_details.html">technical details</a>.
+
+2. Genotypes are internally tabulated.  Since rare variants are likely not very useful, by default the rest of 
+the analysis is skipped if the count of the minor allele is < 10 in either predictor or outcome genotypes.
+
+3. Assuming the variants are common enough, HPTEST fits the above binomial logistic regression
+model to the two genotypes and any specified covariates. When the outcome is haploid, this is the
+same as a regular logistic regression. If the outcome is diploid or has higher ploidy, this is the
+same except that the outcome genotypes are treated as arising from multiple independent draws of a
+alleles with the modelled probability distribution (1). 
+
+4. HPTEST currently assumes predictor genotypes are diploid, and uses a 'general' model for the
+predictor by default, including both an additive and an overdominance term. Alternative models can
+be specified using the ``-model`` option. Multiple models can also be specified in the same run.
+
+5. Parameters are estimated under a weak regularising prior by default. Specifically, a
+$\text{log-F}(2,2)$ prior is applied to the additive effect; this is a lot like a normal
+distribution with mean 0 and standard deviation around 1.87, but has somewhat fatter tails. The
+prior can be altered using the ``-prior`` option, or turned off entirely using the ``-no-prior``
+option. By default, both a Bayes factor and an approximate P-value (both computed under assumptions
+about the asymptotic normality of the likelihood) are output. 
+
+6. If desired, covariates can be included in the analysis using the -covariates option. They are
+loaded from the sample file. They can be continuous (e.g. a principal component, with type `C` in the
+sample file) or discrete (e.g. a population label, with type `D` in the sample file.) 
+
+### Interpreting HPTEST output ###
+
+HPTEST prints a wealth of information to the output file (and/or to a log file specified with the
+-log option). A basic run looks like this: 
+```
+$ hptest_v2.1.9 -predictor host.vcf -outcome parasite.vcf -s samples.sample -o test.tsv -covariates discrete1
+
+Welcome to hptest
+(version: 2.1.9, revision: 7b2ccee)
+
+(C) 2009-2020 University of Oxford
+
+Loaded data for 2000 samples.
+  Predictor data:
+                     (not computed)  "host.vcf"
+                     (total 1 sources, number of snps not computed).
+  Number of samples: 2000
+
+    Outcome data:
+                     (not computed)  "parasite.vcf"
+                     (total 1 sources, number of snps not computed).
+  Number of samples: 2000
+
+Adding covariates...
+++ Added covariate: "discrete1":
+     missing  levels
+     0        0(995) 1(1005)
+
+Models are:
+- Model 1 ("null"): BinomialLogistic( 2000 of 2000 samples ): (outcome=1) ~ baseline/outcome=1 + discrete1=1/outcome=1
+  with priors:
+  discrete1=1/outcome=1 ~ logF( 0.0770407, 0.0770407 ).
+
+- Model 2 ("gen"): BinomialLogistic( 2000 of 2000 samples ): (outcome=1) ~ baseline/outcome=1 + add/outcome=1 + overdominance/outcome=1 + discrete1=1/outcome=1
+  with priors:
+            add/outcome=1 ~ logF( 2, 2 ).
+  overdominance/outcome=1 ~ logF( 4, 4 ).
+    discrete1=1/outcome=1 ~ logF( 0.0770407, 0.0770407 ).
+
+Model design for first test:
+           outcome   baseline     add overdominance discrete1=1
+      0      2   0          1       1             1           1
+      1      2   0          1       1             1           1
+      2      1   1          1       0             0           1
+      3      2   0          1       0             0           1
+      4      2   0          1       0             0           1
+      5      2   0          1       0             0           1
+      6      1   1          1       0             0           0
+      7      0   0          1       0             0           1
+      8      2   0 ~        1       0             0           1
+               .         .       .             .           .
+               .         .       .             .           .
+               .         .       .             .           .
+   1994      2   0          1       0             0           1
+   1995      2   0          1       1             1           1
+   1996      2   0          1       1             1           1
+   1997      2   0          1       0             0           1
+   1998      0   0          1       0             0           0
+   1999      2   0          1       2             0           1
+.
+
+Testing                                                     :  (10000/?,44.9s,222.7/s)
+
+Thank you for using hptest.
+```
+
+In general it is always worth inspecting this output carefully to check that HPTEST has interpreted
+your data correctly. In particular, the above output shows that HPTEST has loaded data on 2,000
+samples, has included a discrete covariate with no missing data, and is planning to fit a null
+model and a genotypic model alternative at each pair of variants. As a further diagnostic it also
+outputs the first and last few rows of the model design (the outcome and predictor levels) for the
+first test.
+
+The output file looks like this:
+```bash
+$ cat test.tsv 
+# Analysis: "hptest analysis"
+#  started: 2021-03-28 12:48:00
+# 
+# Analysis properties:
+#   $ hptest(version: 2.1.9, revision: 7b2ccee) (user-supplied)
+#   -covariates discrete1 (user-supplied)
+#   -o test.tsv (user-supplied)
+#   -outcome parasite.vcf (user-supplied)
+#   -predictor host.vcf (user-supplied)
+#   -s samples.sample (user-supplied)
+# 
+predictor:alternate_ids	predictor:rsid	predictor:chromosome	predictor:position	predictor:alleleA	predictor:alleleB	outcome:alternate_ids	outcome:rsid	outcome:chromosome	outcome:position	outcome:alleleA	outcome:alleleB	N	missing	outcome=0	outcome=1	outcome=2	predictor=0	predictor=1	predictor=2	minimum_outcome_count	minimum_predictor_count	minimum_expected_predictor_allele_count	minimum_expected_predictor_allele_count_genotype	predictor_info	null:converged	null:iterations	null:fit_time	null:ll	null:degrees_of_freedom	gen:converged	gen:iterations	gen:fit_time	gen:ll	gen:degrees_of_freedom	gen:beta_1:add/outcome=1	gen:beta_2:overdominance/outcome=1	gen:sd_1	gen:sd_2	gen:cov_1,2	gen:log10_bf	gen:prior_mode_1	gen:se_1	gen:pvalue_1	gen:prior_mode_2	gen:se_2	gen:pvalue_2	comment
+NA	H1	H1	1	A	G	NA	P1	P1	1	C	T	1998	2	1805	188	5	1351	570	77	198	724	20	outcome=1/predictor=1	1	1	5	0.0000	-787.892	0	1	7	0.0000	-757.823	2	-1.60157	0.219057	0.581235	0.59473	-0.318002	12.9939	0	0.453919	0.00041819	0	0.449276	0.625848	NA
+NA	H1	H1	1	A	G	NA	P2	P1	2	C	T	2000	0	1501	464	35	1353	570	77	534	0	175	outcome=1/predictor=1	1	1	4	0.0100	-1571.85	0	1	4	0.0000	-1570.6	2	-0.163177	0.0487432	0.133177	0.159307	-0.0160542	-0.51645	0	0.131615	0.215046	0	0.156866	0.756005	NA
+NA	H1	H1	1	A	G	NA	P3	P1	3	C	T	1999	1	1347	595	57	1352	570	77	709	0	271	outcome=1/predictor=1	1	1	4	0.0000	-1868.36	0	1	4	0.0000	-1867.71	2	0.108302	-0.0544743	0.101935	0.127023	-0.00904929	-0.955588	0	0.101268	0.284863	0	0.125833	0.66508	NA
+...
+NA	H100	H1	100	A	G	NA	P99	P1	99	C	T	2000	0	1959	40	1	1991	9	0	42	0	0	outcome=1/predictor=1	1	1	7	0.0000	-233.146	0	1	7	0.0000	-233.11	2	-0.258997	-0.128958	1.28596	0.954733	-0.187642	0.897732	0	0.523405	0.620719	0	0.258434	0.617781	NA
+NA	H100	H1	100	A	G	NA	P100	P1	100	C	T	2000	0	1523	451	26	1991	9	0	503	0	2	outcome=1/predictor=1	1	1	4	0.0000	-1512.89	0	1	4	0.0000	-1512.87	2	-0.0798289	-0.0398986	0.935746	0.848044	-0.56311	0.552519	0	0.419414	0.849047	0	0.209456	0.848928	NA
+# Completed successfully at 2021-03-28 12:48:38
+```
+
+In the output file, HPTEST first outputs metadata sufficient to figure out what command generated
+this file, a (long!) row of column names, and then the results for each pair of predictor and
+outcome variants. The last line shows that HPTEST successfully completed the job.
+
+See the page on <a href="[ROOT]/documentation/interpreting_hptest_output.html">interpreting HPTEST
+output</a> for more information on interpreting the output.
+
+### Additional features ###
+
+HPTEST includes a number of features to make it easy to run:
+
+* HPTEST has several filtering options that can be used to adjust the set of samples (e.g.
+  ``-incl-samples`` or ``-excl-samples-where`` ) or variants (e.g. ``-incl-predictor-range``,
+  ``-excl-outcome-rsids``) included in the analysis. See the <a
+  href="[ROOT]/documentation/filtering.html">page on filtering</a> for details.
+
+* Options to adjust or remove the priors (``-prior``, ``-no-prior``, ``-no-covariate-priors`` ).
+  See <a href="[ROOT]/documentation/specifying_priors.html">the page on specifying priors</a> for
+  details.
+
+* As illustrated above HPTEST can output to a variety of flat file output formats. It currently
+  decides upon the format based on the file extension (``.csv`` => comma-separated; ``.txt`` ->
+  space separated; ``.tsv`` -> tab-separated). Additionally if the output file ends with ``.gz``
+  then it will be compressed with gzip.
+
+* HPTEST can also output to the <a href="https://www.sqlite.org">sqlite3</a> database format. This
+  is the way I usually run HPTEST and is useful in several ways - see the <a
+  href="[ROOT]/documentation/sqlite_output.html">page on sqlite output</a> for details.
+
+</section>

ADDED   doc/html/hptest/content/documentation/interpreting_hptest_output.content.html
Index: doc/html/hptest/content/documentation/interpreting_hptest_output.content.html
==================================================================
--- doc/html/hptest/content/documentation/interpreting_hptest_output.content.html
+++ doc/html/hptest/content/documentation/interpreting_hptest_output.content.html
@@ -0,0 +1,55 @@
+<section class="main_text">
+	<h2>Column names</h2>
+	<p>The table below describes the columns found in HPTEST output.</p>
+	<table class="option_table">
+		<colgroup>
+			<col class="option"></col>
+			<col class="description"></col>
+		</colgroup>
+		<thead>
+			<tr>
+				<th>
+					Column name
+				</th>
+				<th>
+					Description
+				</th>
+			</tr>
+		</thead>
+		<tbody>
+		</tbody>
+	</table>
+</section>
+
+<script>
+	$(document).ready(
+		function() {
+			$.getJSON( "../resources/columns.json", function( data ) {
+				var options = data ;
+				//options.sort( function(a,b) {
+				//	return a.name.toLowerCase().localeCompare( b.name.toLowerCase() ) ;
+				//}) ;
+				
+				for( var i = 0; i < options.length; ++i ) {
+					$(".option_table > tbody").append(
+						'<tr>'
+						+ '<td>' + options[i].name + '</td>'
+						+ '<td>' + options[i].description + '</td>'
+						+ '/tr>'
+					)
+				}
+				
+				$( ".option_table" ).DataTable(
+					{
+						"paging": false,
+						"language": {
+							"search": "Search command-line options:"
+						}
+					}
+				) ;
+				
+				$('.dataTables_filter').css('float', 'left') ;
+			}) ;
+		}
+	) ;
+</script>

ADDED   doc/html/hptest/content/documentation/naming_things.content.html
Index: doc/html/hptest/content/documentation/naming_things.content.html
==================================================================
--- doc/html/hptest/content/documentation/naming_things.content.html
+++ doc/html/hptest/content/documentation/naming_things.content.html
@@ -0,0 +1,20 @@
+<section class="main_text" markdown="1">
+
+To make analysis files nice to use, HPTEST lets you name a few things:
+
+1. You can use ``-analysis-name`` to specify a name for your analysis. This is recorded in the
+metadata in the output file. In sqlite output format, this becomes a bit more useful: it gets
+recorded in the ``Analysis`` table, its start/end times in the ``AnalysisStatus`` table, and its
+command-line options in the ``AnalysisProperty`` table. This lets you keep track of multiple HPTEST
+runs output into the same sqlite output file.
+
+2. Use ``-outcome-name`` to specify a name for the outcome variable. By default this is "outcome",
+but it's often nicer to get HPTEST to put its real name into the output file. For example, in our
+malaria study I used ``-outcome-name Pf``; the output columns were named e.g.
+``add:beta_1:add/Pf=1`` instead of ``add:beta_1:add/outcome=1``.
+
+3. Models can be given names - e.g. instead of ``-model add`` you can write ``-model
+my_favourite:add``. (This is admittedly mostly useful for the ``add+het`` model, which is set up as
+``-model gen:add+het`` by default so that the output columns are called "gen".)
+
+</section>	

ADDED   doc/html/hptest/content/documentation/specifying_priors.content.html
Index: doc/html/hptest/content/documentation/specifying_priors.content.html
==================================================================
--- doc/html/hptest/content/documentation/specifying_priors.content.html
+++ doc/html/hptest/content/documentation/specifying_priors.content.html
@@ -0,0 +1,218 @@
+<section class="main_text" markdown="1" >
+
+By default HPTEST fits the model under a regularising prior. Priors are seperately specified for
+each parameter (i.e. each parameter is a priori assumed independent).  By default the priors are as follows.
+
+For the genetic predictor: a $\text{log-F}(2,2)$ prior is placed on the main effect, and a
+$\text{log-F}(4,4)$ prior on the overdominance effect in the general model.
+
+For covariates: a diffuse $\text{log-F}$ distribution with 95% of its mass similar to that of a
+$N(0,40^2)$ prior is currently specified (this is $\text{log-F}(0.077,0.077)$).
+
+<center>
+<svg class="plot1">
+</svg>
+<svg class="plot2">
+</svg>
+</center>
+
+You have the following options for specifying priors.
+
+* Use the ``-prior`` option to specify a different prior for each parameter. The syntax is:
+```
+-prior '[parameter name]/[outcome]=1~logf(<a>,<b>)'
+```
+
+which specifies a log-F prior with the given parameters, or
+
+```
+-prior '[parameter name]/[outcome]=1~gaussian(<mean>,<variance>)'
+```
+
+which specifies a Gaussian prior with the
+given mean and variance. See the <a href="[ROOT]/documentation/alphabetical_options.html">help for
+``-prior``</a> for examples.
+
+*Warning:* when using ``-prior`` you should check the output log file carefully to ensure that
+HPTEST has applied your priors properly. You should see something along the following lines in the
+output:
+
+```
+- Model 2 ("gen"): BinomialLogistic( 2000 of 2000 samples ): (outcome=1) ~ baseline/outcome=1 + add/outcome=1 + overdominance/outcome=1
+  with priors:
+            add/outcome=1 ~ logF( 2, 2 ).
+  overdominance/outcome=1 ~ logF( 4, 4 ).
+```
+
+If there is no 'with priors' line, or if priors for one of the parameters is missing, then it means
+HPTEST has not correctly interpreted your prior specification. (This is usually because the
+parameter names are not specified correctly - check the log output for the correct parameter names.)
+
+* Use the ``-no-covariate-priors`` option to turn off the priors on covariates.
+
+* Use the ``-no-prior`` to turn off all priors - on the main genetic effect and on the covariates.
+(This therefore implements an unpenalised regression.)
+
+</section>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/6.6.2/d3.min.js"></script>
+<script src="https://cdn.jsdelivr.net/npm/jstat@latest/dist/jstat.min.js"></script>
+<script>
+	let geom = {
+		width: 380,
+		height: 200,
+		margin: {
+			top: 10,
+			left: 60,
+			bottom: 40,
+			right: 10
+		}
+	} ;
+	function dlogf( x, nu1, nu2 ) {
+		if( x > 0 ) {
+			return dlogf( -x, nu2, nu1 ) ;
+		}
+		let a = nu1/2 ;
+		let b = nu2/2 ;
+		let l = 1/(1 + Math.exp(-x)) ;
+		let constant = -(jStat.betaln(a, b)) ;
+		let result = a * Math.log(l) + b * Math.log(1 - l) + constant ;
+		return Math.exp( result ) ;
+	} ;
+	let dnorm = jStat.normal.pdf ;
+
+	function plotDistributions( svg, params, range, geom ) {
+		let data = [
+			{
+				type: "logF",
+				data: (
+					d3.range( range[0], range[1], 0.1 )
+						.map( elt => ({
+							x: elt,
+							y: dlogf( elt, params.nu1, params.nu2 )
+						}))
+				)
+			},
+			{
+				type: "gaussian",
+				data: (
+					d3.range( range[0], range[1], 0.1 )
+						.map( elt => ({
+							x: elt,
+							y: dnorm( elt, params.mean, params.sd )
+						}))
+				)
+			}
+		] ;
+		console.log("DATA", data) ;
+	
+		let scales = {
+			x: d3.scaleLinear()
+				.domain( range )
+				.range( [ geom.margin.left, geom.width - geom.margin.right ]),
+			y: d3.scaleLinear()
+				.domain( [0, d3.max( data[0].data, elt => elt.y )])
+				.range( [ geom.height - geom.margin.bottom, geom.margin.top ])
+		} ;
+	
+		svg
+			.attr( 'width', geom.width )
+			.attr( 'height', geom.height ) ;
+	
+		svg.selectAll( 'g.yAxis' )
+			.data( [1] )
+			.enter()
+			.append( 'g' )
+			.attr( 'class', 'yAxis' )
+			.attr( 'transform', 'translate( ' + (scales.x.range()[0] - 10) + ", 0)" )
+			.call( d3.axisLeft( scales.y ).ticks(5) ) ;
+
+		svg.selectAll( 'g.xAxis' )
+			.data( [1] )
+			.enter()
+			.append( 'g' )
+			.attr( 'class', 'xAxis' )
+			.attr( 'transform', 'translate( 0,' + (scales.y.range()[0] + 10) + ")" )
+			.call( d3.axisBottom( scales.x ).ticks(5) ) ;
+
+		let styles = {
+			"logF": {
+				"dasharray": "1 0"
+			},
+			"gaussian": {
+				"dasharray": "4 4"
+			}
+		}
+		
+		let line = svg.selectAll( 'path.pt' )
+			.data( data )
+			.enter()
+			.append( 'path' )
+			.attr( 'class', 'pt' )
+			.attr( 'stroke', 'black' )
+			.attr( 'stroke-width', 1.5 )
+			.attr( 'stroke-dasharray', elt => styles[elt.type].dasharray )
+			.attr( 'fill', 'none' ) ;
+	
+		line
+			.merge(line)
+			.attr(
+				'd',
+				function( d ) {
+					return d3.line()
+						.x( elt => scales.x(elt.x) )
+						.y( elt => scales.y(elt.y) )
+					( d.data ) ;
+				}
+			) ;
+		
+		let legend = svg.selectAll( 'g.legend' )
+			.data( [
+				{ type: "logF", display: "log-F(" + params.nu1 + ", " + params.nu2 + ")" },
+				{ type: "gaussian", display: "N(" + params.mean + ", " + params.sd + "²)" }
+			])
+			.enter()
+			.append( 'g' )
+			.attr( 'transform', ( elt, index ) => 'translate(' + ( geom.width - geom.margin.right - 100 ) + "," + (geom.margin.top+10+20*index) + ")" )
+		;
+		legend
+			.append( 'line' )
+			.attr( 'x1', -10 )
+			.attr( 'x2', 0 )
+			.attr( 'y1', 0 )
+			.attr( 'y2', 0 )
+			.attr( 'stroke-width', 1.5 )
+			.attr( 'stroke', 'black' )
+			.attr( 'stroke-dasharray', elt => styles[elt.type].dasharray ) ;
+		legend.append( 'text' )
+			.attr( 'x', 5 )
+			.attr( 'y', 0 )
+			.attr( 'alignment-baseline', 'middle' )
+			.attr( 'font-size', '10pt' )
+			.text( elt => elt.display ) ;
+	} ;
+	
+	plotDistributions(
+		d3.select( 'svg.plot1' ),
+		params = {
+			nu1: 2,
+			nu2: 2,
+			mean: 0,
+			sd: 1.87
+		},
+		range = [ -10, 10 ],
+		geom
+	) ;
+
+	plotDistributions(
+		d3.select( 'svg.plot2' ),
+		params = {
+			nu1: 0.077,
+			nu2: 0.077,
+			mean: 0,
+			sd: 40
+		},
+		range = [ -100, 100 ],
+		geom
+	) ;
+	
+</script>

ADDED   doc/html/hptest/content/documentation/sqlite_output.content.html
Index: doc/html/hptest/content/documentation/sqlite_output.content.html
==================================================================
--- doc/html/hptest/content/documentation/sqlite_output.content.html
+++ doc/html/hptest/content/documentation/sqlite_output.content.html
@@ -0,0 +1,67 @@
+<section class="main_text" markdown="1" >
+### The sqlite output format ###
+
+If you use an output file of one of the following forms:
+	
+* ``myfile.sqlite``
+* ``myfile.sqlite:&lt;name&gt;``
+* ``sqlite://myfile.sqlite``
+* ``sqlite://myfile.sqlite:&lt;name&gt;``
+
+then HPTEST will output results to a sqlite file instead of a flat file.  This has the following behaviour:
+
+* The analysis, its start/stop times and command-line arguments are recorded in the ``Analysis``,
+  ``AnalysisStatus``, and ``AnalysisProperty`` tables.
+
+* The main results are placed in a table called ``<name>``; if no name is supplied then the table is
+  called ``analysis&lt;n&gt;`` where n is one more than the number of analyses currently recorded
+  in the `Analysis` table, if any.
+  
+* The main results table does not contain full variant information; instead, genetic variants are
+  placed into a seperate ``Variant`` table. A view called ``nameView`` is also created which links
+  the main result, ``Analysis``, and ``Variant`` tables through the ``analysis_id``,
+  ``predictor_id`` and ``outcome_id`` fields.
+
+* The main results table is indexed by default by the ``predictor_id`` and ``outcome_id`` fields.
+
+* You can record more than one analysis in the same sqlite file. The only caveat is that analyses
+  that output different column names have to be stored in different results tables.
+
+### Using the sqlite output file programmatically ###
+
+Data from the sqlite output files can be read directly into analysis programs.
+For example, suppose you have named the output table ``Result``.  Then in R:
+```R
+library( RSQLite )
+db = DBI::dbConnect(RSQLite::SQLite(), "myfile.sqlite" )
+data = dbGetQuery( db, "SELECT * FROM ResultView LIMIT 100" )
+```
+
+...or if you are using the <a href="https://dbplyr.tidyverse.org">tidyverse</a>:
+```R
+library( dplyr )
+db = DBI::dbConnect(RSQLite::SQLite(), "myfile.sqlite")
+results = tbl( db, "ResultView" )
+results
+```
+
+Or it can be loaded in python using <a href="https://pandas.pydata.org">pandas</a>:
+```python
+import pandas
+db = sqlite3.connect( "myfile.sqlite" )
+pandas.read_sql(
+	"SELECT * FROM ResultView LIMIT 100" ),
+	db
+)
+```
+
+### Using the sqlite output file from a web service ###
+
+Another thing you can do with the sqlite output format is to turn it into a web service. <a
+href="https://datasette.readthedocs.io">Datasette</a> is an extremely useful tool which turns a sqlite file into a RESTful web service like this:
+```
+$ datasette myfile.sqlite
+```
+Now you can access the database at ``http://localhost:8001``.  This can be used to create web-based visualisations of the results.
+
+</section>

ADDED   doc/html/hptest/content/documentation/technical_details.content.html
Index: doc/html/hptest/content/documentation/technical_details.content.html
==================================================================
--- doc/html/hptest/content/documentation/technical_details.content.html
+++ doc/html/hptest/content/documentation/technical_details.content.html
@@ -0,0 +1,34 @@
+<section class="main_text" markdown="1" >
+	
+HPTEST fits the following model:
+
+$$\text{log-odds}( \text{outcome genotype} = 1 ) = X^t \cdot \beta$$
+
+where $X$ is a function of the predictor genotype and covariates,
+
+$$X = \left( \begin{matrix} 1 \\ F(\text{predictor genotype}) \\ Z \end{matrix} \right)$$
+
+and $\beta$ is a vector of regression coefficients to be maximised over. The full likelihood is
+obtained as the product of the above over all samples in the data.
+
+HPTEST currently assumes that both outcome and predictor variants are biallelic (or at least that
+they have been split into biallelic records before running through HPTEST). The outcome and
+predictor genotypes are measured with respect to those alleles, i.e. the effect is always
+interpreted as effect of the second predictor allele on the second outcome allele. If the outcome
+has ploidy larger than 1, then its alleles are regarded as forming independent draws from the
+Bernoulli distribution modelled above (i.e. it's a binomial logistic regression model with number
+of trials equal to the ploidy).
+
+The predictor genotype is currently assumed to be diploid. To handle different possible modes of
+inheritance, HPTEST uses a variety of function $F$ above as follows. If $g \in \{0,1,2\}$ denotes
+the predictor genotype then the following functions $F$ are used:
+
+Mode of inheritance  | F                                               | Specified by
+-------------------  | ----------                                      | --------------------
+additive             | $F(g) = g$                                      | ``-model add``      
+dominant             | $F(g) = 1$ if $g > 0$, or $0$ otherwise         | ``-model dom``      
+recessive            | $F(g) = 1$ if $g = 2$, or $0$ otherwise         | ``-model rec``      
+heterozygote         | $F(g) = 1$ if $g = 1$, or $0$ otherwise         | ``-model het``      
+general              | $F(g) = (g,1)$ if $g = 1$, or $(g,0)$ otherwise | ``-model add+het``  
+
+</section>

ADDED   doc/html/hptest/content/footer.html
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==================================================================
--- doc/html/hptest/content/footer.html
+++ doc/html/hptest/content/footer.html
@@ -0,0 +1,26 @@
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="[ROOT]/index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="[ROOT]/documentation/getting_started.html">Getting started</a></li>
+						<li><a href="[ROOT]/documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="[ROOT]/documentation/naming_things.html">Naming things</a></li>
+						<li><a href="[ROOT]/documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="[ROOT]/documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="[ROOT]/documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="[ROOT]/documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="[ROOT]/documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="[ROOT]/documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/content/header.html
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==================================================================
--- doc/html/hptest/content/header.html
+++ doc/html/hptest/content/header.html
@@ -0,0 +1,26 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="[ROOT]/js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="[ROOT]/js/datatables.min.js"></script>
+		<script type="text/javascript" src="[ROOT]/js/local.js"></script>
+
+		<link href="[ROOT]/style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="[ROOT]/style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="[ROOT]/style/images/logo.png">
+		</div>

ADDED   doc/html/hptest/content/index.content.html
Index: doc/html/hptest/content/index.content.html
==================================================================
--- doc/html/hptest/content/index.content.html
+++ doc/html/hptest/content/index.content.html
@@ -0,0 +1,51 @@
+<section class="main_text" markdown="1">
+<div id="overview" markdown="1">
+
+### Introduction ###
+
+HPTEST is a command-line program to test for association between genotypes at pairs of genetic
+variants. The motivating use case is to test for association between hosts and pathogens, using
+genotype data from hosts and from the pathogens infecting those hosts, but HPTEST also has other
+potential use-cases, such as estimating LD between variants while controlling for confounding
+variables.
+
+The method currently implemented in HPTEST is logistic regression in which one set of genotypes
+(e.g. the host genotypes) are included as predictors and the second set (e.g. pathogen genotypes)
+are included as the outcome. Covariates can also be included. For each pair of variants, HPTEST
+outputs the genotype counts and a summary of the evidence for association.
+
+For an introduction to running HPTEST, please see the <a
+href="[ROOT]/documentation/getting_started.html">getting started</a> page.
+
+### Obtaining and running HPTEST ###
+
+HPTEST is currently included as part of the <a href="https://code.enkre.net/qctool">QCTOOL
+package</a>, which is currently hosted at <a href="https://code.enkre.net">code.enkre.net</a> and
+mirrored <a href="https://github.com/gavinband/qctool">on github<a>. See the <a
+href="[ROOT]/documentation/download.html">download page</a> for full details on obtaining and
+installing HPTEST.
+
+### References ###
+
+HPTEST was originally developed for a study of human and malaria parasite variation in samples
+collected for <a href="https://www.malariagen.net/projects/consortial-project-1">MalariaGEN
+Consortial Project 1</a>. If you use HPTEST in published work, please cite the following preprint (or
+its published equivalent):
+
+<div class="citation" style="padding-left: 20px; padding-right: 20px; font-family:Palatino" markdown="1">
+"**The protective effect of sickle cell haemoglobin against severe malaria depends on parasite genotype**",
+bioRxiv <https://doi.org/10.1101/2021.03.30.437659> <br>
+<small>Gavin Band, Ellen M. Leffler, Muminatou Jallow, Fatoumatta Sisay-Joof, Carolyne M. Ndila, Alexander W. Macharia,
+	Christina Hubbart, Anna E. Jeffreys, Kate Rowlands, Thuy Nguyen, Sonia M. Goncalves, Cristina V. Ariani,
+	Jim Stalker, Richard D. Pearson, Roberto Amato, Eleanor Drury, Giorgio Sirugo, Umberto d'Alessandro,
+	Kalifa A. Bojang, Kevin Marsh, Norbert N.P. Peshu, David J. Conway,
+	Thomas N. Williams, Kirk A. Rockett, Dominic P. Kwiatkowski
+</small>
+</div>
+
+### Contact ###
+
+For more information or questions, please contact me at ``gavin [dot] band (at) well.ox.ac.uk``.
+	
+</div>
+</section>

ADDED   doc/html/hptest/documentation/alphabetical_options.html
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==================================================================
--- doc/html/hptest/documentation/alphabetical_options.html
+++ doc/html/hptest/documentation/alphabetical_options.html
@@ -0,0 +1,119 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+    <h2>Table of options</h2>
+    <p>Below is a list of all options supported by HPTEST.</p>
+    <table class="option_table">
+        <colgroup>
+            <col class="option"></col>
+            <col class="description"></col>
+            <col class="default"></col>
+        </colgroup>
+        <thead>
+            <tr>
+                <th>
+                    Option
+                </th>
+                <th>
+                    Description
+                </th>
+                <th>
+                    Default value?
+                </th>
+            </tr>
+        </thead>
+        <tbody>
+        </tbody>
+    </table>
+</section>
+
+<script>
+    $(document).ready(
+        function() {
+            $.getJSON( "../resources/options.json", function( data ) {
+                console.log( 'gotit' ) ;
+                var options = [] ;
+                $.each( data, function( key, value ) {
+                    options.push( key ) ;
+                    console.log( key ) ;
+                } ) ;
+
+                options.sort( function(a,b) {
+                    return a.toLowerCase().localeCompare( b.toLowerCase() ) ;
+                }) ;
+
+                for( var i = 0; i < options.length; ++i ) {
+                    $(".option_table > tbody").append(
+                        '<tr>'
+                        + '<td>' + options[i] + '</td>'
+                        + '<td>' + data[options[i]]['description'] + '</td>'
+                        + '<td>' + ( data[options[i]].length == 0 ? "N/A" : data[options[i]].default.join( ", " )) + '</td>'
+                        + '/tr>'
+                    )
+                }
+
+                $( ".option_table" ).DataTable(
+                    {
+                        "paging": false,
+                        "language": {
+                            "search": "Search command-line options:"
+                        }
+                    }
+                ) ;
+
+                $('.dataTables_filter').css('float', 'left') ;
+            }) ;
+        }
+    ) ;
+</script>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/download.html
Index: doc/html/hptest/documentation/download.html
==================================================================
--- doc/html/hptest/documentation/download.html
+++ doc/html/hptest/documentation/download.html
@@ -0,0 +1,81 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+<h3>Obtaining HPTEST</h3>
+<p>The source code to HPTEST is available as part of the QCTOOL package, which is currently hosted at
+<a href="https://code.enkre.net/qctool">code.enkre.net</a>. To obtain HPTEST you need to download
+version 2.1.9 or above of QCTOOL. The source code can be downloaded from the following link:</p>
+<p><a href="https://code.enkre.net/qctool/zip/v2.1.9/qctool.tgz">https://code.enkre.net/qctool/zip/v2.1.9/qctool.tgz</a></p>
+<p>Please be aware this tarball is generated on the fly and may take a few minutes to download.</p>
+<h3>Compiling HPTEST</h3>
+<p>QCTOOL uses the <a href="https://waf.io">Waf build system</a> to manage the compilation process.
+For this to work you need python to be installed. (Waf itself is bundled with QCTOOL). A basic
+compilation process goes as follows:</p>
+<pre><code>$ ./waf configure
+$ ./waf
+</code></pre>
+<p>The first command configures the project (i.e. makes sure various prerequisites are in place). The
+second part compiles the QCTOOL package.  </p>
+<p>If successful you should now be able to try hptest:</p>
+<pre><code>$ ./build/release/apps/hptest_v2.1.9
+!! Error (OptionProcessingException): Option &quot;-o&quot; must be supplied..
+!! Run hptest -help for usage information.
+</code></pre>
+<p>The following is a more advanced example that specifies a path to a relevant C and C++ compiler and
+an installation directory.</p>
+<pre><code>$ CXX=/path/to/g++ CC=/path/to/gcc ./waf configure --prefix=/path/to/installation/dir
+$ ./waf install
+</code></pre>
+<p>If successful hptest (along with qctool and other tools) will be installed in <code>/path/to/installation/dir/usr/bin</code></p>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/filtering.html
Index: doc/html/hptest/documentation/filtering.html
==================================================================
--- doc/html/hptest/documentation/filtering.html
+++ doc/html/hptest/documentation/filtering.html
@@ -0,0 +1,87 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+<h3>Filtering variants</h3>
+<p>The following options can be used to filter variants from the analysis. Each of these options comes in an inclusiong
+variant (<code>-incl-...</code>), which tells HPTEST to only focus on the specified variants, and an exclusion variant
+(<code>-excl-...</code>) which tells HPTEST to ignore the specified variants, and each applies either to the predictor or outcome genotypes:</p>
+<ul>
+<li>
+<p><code>-[in|ex]cl-outcome-range</code>: specify a genomic range or list of ranges to include or exclude outcome variants from.</p>
+</li>
+<li>
+<p><code>-[in|ex]cl-outcome-rsids</code>: specify a set of variant IDs to include or exclude outcome variants from.</p>
+</li>
+<li>
+<p><code>-[in|ex]cl-predictor-range</code>: specify a genomic range or list of ranges to include or exclude predictor variants from.</p>
+</li>
+<li>
+<p><code>-[in|ex]cl-predictor-rsids</code>: specify a set of variant IDs to include or exclude predictor variants from.</p>
+</li>
+</ul>
+<h3>Filtering samples</h3>
+<p>The following options can be used to filter samples from the analysis:</p>
+<ul>
+<li>
+<p><code>-[in|ex]cl-samples</code>: specify a list of samples to include or exclude from the analysis. For this purpose, samples are identified
+by their identifier in the first column of the sample file.</p>
+</li>
+<li>
+<p><code>-[in|ex]cl-samples-where</code>: specify a condition to apply to rows of the sample file to determine if the sample
+  should be included or excluded. The general syntax is <code>-[in|ex]cl-samples-where '&lt;column&gt;[=|==|!=]&lt;value&gt;'</code>, which
+  will cause HPTEST to compare the values in the column named <column> of the sample file to the given value, and
+  include/exclude samples based on whether the values match (= or ==) or mismatch (!=).</p>
+</li>
+</ul>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/getting_started.html
Index: doc/html/hptest/documentation/getting_started.html
==================================================================
--- doc/html/hptest/documentation/getting_started.html
+++ doc/html/hptest/documentation/getting_started.html
@@ -0,0 +1,259 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+<h3>Getting started with HPTEST</h3>
+<p>HPTEST tests for association between two sets of genotypes - for example between genotypes of a
+host and of a pathogen infecting those hosts. To do this, it implements the binomial logistic
+regression model:</p>
+<p>(1) <script type="math/tex; mode=display">\text{log-odds}( \text{outcome genotype} ) = \left( \text{predictor genotypes}, \text{covariates}... \right) \times \beta</script>
+</p>
+<p>in which <script type="math/tex">\beta</script> is a vector of parameters (the regression coefficients). For each predictor and
+outcome genetic variant, HPTEST finds the value of <script type="math/tex">\beta</script> that maximises the corresponding
+likelihood, estimates its standard error (by inspecting the curvature of the likelihood near the
+maximum) and outputs these along with other summaries to the output file. </p>
+<p>By default, HPTEST computes estimates under a weakly informative prior that helps to regularise the
+estimates (this can be turned off with the <code>-no-prior</code> option.)</p>
+<p>For example, the following command:</p>
+<pre><code>$ hptest \
+-outcome parasite.vcf \
+-predictor host.vcf \
+-s samples.sample \
+-o output.csv
+</code></pre>
+<p>regresses each parasite variant (from <code>parasite.vcf</code>) on each host variant (from <code>host.vcf</code>).
+The genotype counts, maximum posterior estimates and other quantities are output to the output file
+(<code>output.csv</code>). Additional options allow you to add covariates (<code>-covariates</code>), to adjust the
+prior being used (<code>-prior</code>) or remove it entirely (<code>-no-prior</code>), or to filter the list of
+samples or variants included (e.g. <code>-incl-samples</code>, <code>-excl-samples-where</code>, or
+<code>-incl-outcome-range</code>) - see the <a href="../documentation/alphabetical_options.html">list of
+options</a> for more.</p>
+<h3>Obtaining HPTEST</h3>
+<p>HPTEST is currently included as part of the <a href="https://code.enkre.net/qctool">QCTOOL
+package</a>, which is currently hosted at <a href="https://code.enkre.net">code.enkre.net</a>. To
+obtain it you will need to download and compile the source code (you need QCTOOL version &gt;= 2.1.9
+for this). See the <a href="../documentation/download.html">download page</a> for more details
+on obtaining and installing HPTEST.</p>
+<h3>Running HPTEST</h3>
+<p>In the most basic form HPTEST is run like this:</p>
+<pre><code>hptest -outcome outcome.vcf -predictor predictor.vcf -s samples.sample -o test.csv
+</code></pre>
+<p>where <code>outcome.vcf</code> and <code>predictor.vcf</code> contain genotype calls, and <code>samples.sample</code> contains
+information on the included samples. All three files must represent the same set of individuals and
+they must be in the same order in each file. (The <a
+href="http://www.well.ox.ac.uk/~gav/qctool_v2/documentation/examples/sorting.html"><code>-reorder</code>
+option to QCTOOL</a> can help to set this up).</p>
+<p>For each predictor and outcome variant, HPTEST will do the following:</p>
+<ol>
+<li>
+<p>Both sets of genotypes are loaded. HPTEST can interpret both hard-called genotypes (e.g. GT
+field in a <a href="http://samtools.github.io/hts-specs/">vcf file</a>), and imputed genotype
+probabilities (e.g. GP field in a vcf file, or a <a href="https://www.bgenformat.org">BGEN
+format</a> file). For outcome genotypes, imputed genotypes are thresholded to produce hard calls -
+by default any genotypes with probability &lt; 0.9 are treated as missing. For the predictor genotype,
+HPTEST will sum over the imputed probability distribution as described in <a
+href="../documentation/technical_details.html">technical details</a>.</p>
+</li>
+<li>
+<p>Genotypes are internally tabulated.  Since rare variants are likely not very useful, by default the rest of 
+the analysis is skipped if the count of the minor allele is &lt; 10 in either predictor or outcome genotypes.</p>
+</li>
+<li>
+<p>Assuming the variants are common enough, HPTEST fits the above binomial logistic regression
+model to the two genotypes and any specified covariates. When the outcome is haploid, this is the
+same as a regular logistic regression. If the outcome is diploid or has higher ploidy, this is the
+same except that the outcome genotypes are treated as arising from multiple independent draws of a
+alleles with the modelled probability distribution (1). </p>
+</li>
+<li>
+<p>HPTEST currently assumes predictor genotypes are diploid, and uses a 'general' model for the
+predictor by default, including both an additive and an overdominance term. Alternative models can
+be specified using the <code>-model</code> option. Multiple models can also be specified in the same run.</p>
+</li>
+<li>
+<p>Parameters are estimated under a weak regularising prior by default. Specifically, a
+<script type="math/tex">\text{log-F}(2,2)</script> prior is applied to the additive effect; this is a lot like a normal
+distribution with mean 0 and standard deviation around 1.87, but has somewhat fatter tails. The
+prior can be altered using the <code>-prior</code> option, or turned off entirely using the <code>-no-prior</code>
+option. By default, both a Bayes factor and an approximate P-value (both computed under assumptions
+about the asymptotic normality of the likelihood) are output. </p>
+</li>
+<li>
+<p>If desired, covariates can be included in the analysis using the -covariates option. They are
+loaded from the sample file. They can be continuous (e.g. a principal component, with type <code>C</code> in the
+sample file) or discrete (e.g. a population label, with type <code>D</code> in the sample file.) </p>
+</li>
+</ol>
+<h3>Interpreting HPTEST output</h3>
+<p>HPTEST prints a wealth of information to the output file (and/or to a log file specified with the
+-log option). A basic run looks like this: </p>
+<pre><code>$ hptest_v2.1.9 -predictor host.vcf -outcome parasite.vcf -s samples.sample -o test.tsv -covariates discrete1
+
+Welcome to hptest
+(version: 2.1.9, revision: 7b2ccee)
+
+(C) 2009-2020 University of Oxford
+
+Loaded data for 2000 samples.
+  Predictor data:
+                     (not computed)  &quot;host.vcf&quot;
+                     (total 1 sources, number of snps not computed).
+  Number of samples: 2000
+
+    Outcome data:
+                     (not computed)  &quot;parasite.vcf&quot;
+                     (total 1 sources, number of snps not computed).
+  Number of samples: 2000
+
+Adding covariates...
+++ Added covariate: &quot;discrete1&quot;:
+     missing  levels
+     0        0(995) 1(1005)
+
+Models are:
+- Model 1 (&quot;null&quot;): BinomialLogistic( 2000 of 2000 samples ): (outcome=1) ~ baseline/outcome=1 + discrete1=1/outcome=1
+  with priors:
+  discrete1=1/outcome=1 ~ logF( 0.0770407, 0.0770407 ).
+
+- Model 2 (&quot;gen&quot;): BinomialLogistic( 2000 of 2000 samples ): (outcome=1) ~ baseline/outcome=1 + add/outcome=1 + overdominance/outcome=1 + discrete1=1/outcome=1
+  with priors:
+            add/outcome=1 ~ logF( 2, 2 ).
+  overdominance/outcome=1 ~ logF( 4, 4 ).
+    discrete1=1/outcome=1 ~ logF( 0.0770407, 0.0770407 ).
+
+Model design for first test:
+           outcome   baseline     add overdominance discrete1=1
+      0      2   0          1       1             1           1
+      1      2   0          1       1             1           1
+      2      1   1          1       0             0           1
+      3      2   0          1       0             0           1
+      4      2   0          1       0             0           1
+      5      2   0          1       0             0           1
+      6      1   1          1       0             0           0
+      7      0   0          1       0             0           1
+      8      2   0 ~        1       0             0           1
+               .         .       .             .           .
+               .         .       .             .           .
+               .         .       .             .           .
+   1994      2   0          1       0             0           1
+   1995      2   0          1       1             1           1
+   1996      2   0          1       1             1           1
+   1997      2   0          1       0             0           1
+   1998      0   0          1       0             0           0
+   1999      2   0          1       2             0           1
+.
+
+Testing                                                     :  (10000/?,44.9s,222.7/s)
+
+Thank you for using hptest.
+</code></pre>
+<p>In general it is always worth inspecting this output carefully to check that HPTEST has interpreted
+your data correctly. In particular, the above output shows that HPTEST has loaded data on 2,000
+samples, has included a discrete covariate with no missing data, and is planning to fit a null
+model and a genotypic model alternative at each pair of variants. As a further diagnostic it also
+outputs the first and last few rows of the model design (the outcome and predictor levels) for the
+first test.</p>
+<p>The output file looks like this:</p>
+<pre><code class="language-bash">$ cat test.tsv 
+# Analysis: &quot;hptest analysis&quot;
+#  started: 2021-03-28 12:48:00
+# 
+# Analysis properties:
+#   $ hptest(version: 2.1.9, revision: 7b2ccee) (user-supplied)
+#   -covariates discrete1 (user-supplied)
+#   -o test.tsv (user-supplied)
+#   -outcome parasite.vcf (user-supplied)
+#   -predictor host.vcf (user-supplied)
+#   -s samples.sample (user-supplied)
+# 
+predictor:alternate_ids predictor:rsid  predictor:chromosome    predictor:position  predictor:alleleA   predictor:alleleB   outcome:alternate_ids   outcome:rsid    outcome:chromosome  outcome:position    outcome:alleleA outcome:alleleB N   missing outcome=0   outcome=1   outcome=2   predictor=0 predictor=1 predictor=2 minimum_outcome_count   minimum_predictor_count minimum_expected_predictor_allele_count minimum_expected_predictor_allele_count_genotype    predictor_info  null:converged  null:iterations null:fit_time   null:ll null:degrees_of_freedom gen:converged   gen:iterations  gen:fit_time    gen:ll  gen:degrees_of_freedom  gen:beta_1:add/outcome=1    gen:beta_2:overdominance/outcome=1  gen:sd_1    gen:sd_2    gen:cov_1,2 gen:log10_bf    gen:prior_mode_1    gen:se_1    gen:pvalue_1    gen:prior_mode_2    gen:se_2    gen:pvalue_2    comment
+NA  H1  H1  1   A   G   NA  P1  P1  1   C   T   1998    2   1805    188 5   1351    570 77  198 724 20  outcome=1/predictor=1   1   1   5   0.0000  -787.892    0   1   7   0.0000  -757.823    2   -1.60157    0.219057    0.581235    0.59473 -0.318002   12.9939 0   0.453919    0.00041819  0   0.449276    0.625848    NA
+NA  H1  H1  1   A   G   NA  P2  P1  2   C   T   2000    0   1501    464 35  1353    570 77  534 0   175 outcome=1/predictor=1   1   1   4   0.0100  -1571.85    0   1   4   0.0000  -1570.6 2   -0.163177   0.0487432   0.133177    0.159307    -0.0160542  -0.51645    0   0.131615    0.215046    0   0.156866    0.756005    NA
+NA  H1  H1  1   A   G   NA  P3  P1  3   C   T   1999    1   1347    595 57  1352    570 77  709 0   271 outcome=1/predictor=1   1   1   4   0.0000  -1868.36    0   1   4   0.0000  -1867.71    2   0.108302    -0.0544743  0.101935    0.127023    -0.00904929 -0.955588   0   0.101268    0.284863    0   0.125833    0.66508 NA
+...
+NA  H100    H1  100 A   G   NA  P99 P1  99  C   T   2000    0   1959    40  1   1991    9   0   42  0   0   outcome=1/predictor=1   1   1   7   0.0000  -233.146    0   1   7   0.0000  -233.11 2   -0.258997   -0.128958   1.28596 0.954733    -0.187642   0.897732    0   0.523405    0.620719    0   0.258434    0.617781    NA
+NA  H100    H1  100 A   G   NA  P100    P1  100 C   T   2000    0   1523    451 26  1991    9   0   503 0   2   outcome=1/predictor=1   1   1   4   0.0000  -1512.89    0   1   4   0.0000  -1512.87    2   -0.0798289  -0.0398986  0.935746    0.848044    -0.56311    0.552519    0   0.419414    0.849047    0   0.209456    0.848928    NA
+# Completed successfully at 2021-03-28 12:48:38
+</code></pre>
+<p>In the output file, HPTEST first outputs metadata sufficient to figure out what command generated
+this file, a (long!) row of column names, and then the results for each pair of predictor and
+outcome variants. The last line shows that HPTEST successfully completed the job.</p>
+<p>See the page on <a href="../documentation/interpreting_hptest_output.html">interpreting HPTEST
+output</a> for more information on interpreting the output.</p>
+<h3>Additional features</h3>
+<p>HPTEST includes a number of features to make it easy to run:</p>
+<ul>
+<li>
+<p>HPTEST has several filtering options that can be used to adjust the set of samples (e.g.
+  <code>-incl-samples</code> or <code>-excl-samples-where</code> ) or variants (e.g. <code>-incl-predictor-range</code>,
+  <code>-excl-outcome-rsids</code>) included in the analysis. See the <a
+  href="../documentation/filtering.html">page on filtering</a> for details.</p>
+</li>
+<li>
+<p>Options to adjust or remove the priors (<code>-prior</code>, <code>-no-prior</code>, <code>-no-covariate-priors</code> ).
+  See <a href="../documentation/specifying_priors.html">the page on specifying priors</a> for
+  details.</p>
+</li>
+<li>
+<p>As illustrated above HPTEST can output to a variety of flat file output formats. It currently
+  decides upon the format based on the file extension (<code>.csv</code> =&gt; comma-separated; <code>.txt</code> -&gt;
+  space separated; <code>.tsv</code> -&gt; tab-separated). Additionally if the output file ends with <code>.gz</code>
+  then it will be compressed with gzip.</p>
+</li>
+<li>
+<p>HPTEST can also output to the <a href="https://www.sqlite.org">sqlite3</a> database format. This
+  is the way I usually run HPTEST and is useful in several ways - see the <a
+  href="../documentation/sqlite_output.html">page on sqlite output</a> for details.</p>
+</li>
+</ul>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/interpreting_hptest_output.html
Index: doc/html/hptest/documentation/interpreting_hptest_output.html
==================================================================
--- doc/html/hptest/documentation/interpreting_hptest_output.html
+++ doc/html/hptest/documentation/interpreting_hptest_output.html
@@ -0,0 +1,108 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+    <h2>Column names</h2>
+    <p>The table below describes the columns found in HPTEST output.</p>
+    <table class="option_table">
+        <colgroup>
+            <col class="option"></col>
+            <col class="description"></col>
+        </colgroup>
+        <thead>
+            <tr>
+                <th>
+                    Column name
+                </th>
+                <th>
+                    Description
+                </th>
+            </tr>
+        </thead>
+        <tbody>
+        </tbody>
+    </table>
+</section>
+
+<script>
+    $(document).ready(
+        function() {
+            $.getJSON( "../resources/columns.json", function( data ) {
+                var options = data ;
+                //options.sort( function(a,b) {
+                //  return a.name.toLowerCase().localeCompare( b.name.toLowerCase() ) ;
+                //}) ;
+
+                for( var i = 0; i < options.length; ++i ) {
+                    $(".option_table > tbody").append(
+                        '<tr>'
+                        + '<td>' + options[i].name + '</td>'
+                        + '<td>' + options[i].description + '</td>'
+                        + '/tr>'
+                    )
+                }
+
+                $( ".option_table" ).DataTable(
+                    {
+                        "paging": false,
+                        "language": {
+                            "search": "Search command-line options:"
+                        }
+                    }
+                ) ;
+
+                $('.dataTables_filter').css('float', 'left') ;
+            }) ;
+        }
+    ) ;
+</script>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/naming_things.html
Index: doc/html/hptest/documentation/naming_things.html
==================================================================
--- doc/html/hptest/documentation/naming_things.html
+++ doc/html/hptest/documentation/naming_things.html
@@ -0,0 +1,76 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+<p>To make analysis files nice to use, HPTEST lets you name a few things:</p>
+<ol>
+<li>
+<p>You can use <code>-analysis-name</code> to specify a name for your analysis. This is recorded in the
+metadata in the output file. In sqlite output format, this becomes a bit more useful: it gets
+recorded in the <code>Analysis</code> table, its start/end times in the <code>AnalysisStatus</code> table, and its
+command-line options in the <code>AnalysisProperty</code> table. This lets you keep track of multiple HPTEST
+runs output into the same sqlite output file.</p>
+</li>
+<li>
+<p>Use <code>-outcome-name</code> to specify a name for the outcome variable. By default this is "outcome",
+but it's often nicer to get HPTEST to put its real name into the output file. For example, in our
+malaria study I used <code>-outcome-name Pf</code>; the output columns were named e.g.
+<code>add:beta_1:add/Pf=1</code> instead of <code>add:beta_1:add/outcome=1</code>.</p>
+</li>
+<li>
+<p>Models can be given names - e.g. instead of <code>-model add</code> you can write <code>-model
+my_favourite:add</code>. (This is admittedly mostly useful for the <code>add+het</code> model, which is set up as
+<code>-model gen:add+het</code> by default so that the output columns are called "gen".)</p>
+</li>
+</ol>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/specifying_priors.html
Index: doc/html/hptest/documentation/specifying_priors.html
==================================================================
--- doc/html/hptest/documentation/specifying_priors.html
+++ doc/html/hptest/documentation/specifying_priors.html
@@ -0,0 +1,261 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+<p>By default HPTEST fits the model under a regularising prior. Priors are seperately specified for
+each parameter (i.e. each parameter is a priori assumed independent).  By default the priors are as follows.</p>
+<p>For the genetic predictor: a <script type="math/tex">\text{log-F}(2,2)</script> prior is placed on the main effect, and a
+<script type="math/tex">\text{log-F}(4,4)</script> prior on the overdominance effect in the general model.</p>
+<p>For covariates: a diffuse <script type="math/tex">\text{log-F}</script> distribution with 95% of its mass similar to that of a
+<script type="math/tex">N(0,40^2)</script> prior is currently specified (this is <script type="math/tex">\text{log-F}(0.077,0.077)</script>).</p>
+<p><center>
+<svg class="plot1">
+</svg>
+<svg class="plot2">
+</svg>
+</center></p>
+<p>You have the following options for specifying priors.</p>
+<ul>
+<li>Use the <code>-prior</code> option to specify a different prior for each parameter. The syntax is:</li>
+</ul>
+<pre><code>-prior '[parameter name]/[outcome]=1~logf(&lt;a&gt;,&lt;b&gt;)'
+</code></pre>
+<p>which specifies a log-F prior with the given parameters, or</p>
+<pre><code>-prior '[parameter name]/[outcome]=1~gaussian(&lt;mean&gt;,&lt;variance&gt;)'
+</code></pre>
+<p>which specifies a Gaussian prior with the
+given mean and variance. See the <a href="../documentation/alphabetical_options.html">help for
+<code>-prior</code></a> for examples.</p>
+<p><em>Warning:</em> when using <code>-prior</code> you should check the output log file carefully to ensure that
+HPTEST has applied your priors properly. You should see something along the following lines in the
+output:</p>
+<pre><code>- Model 2 (&quot;gen&quot;): BinomialLogistic( 2000 of 2000 samples ): (outcome=1) ~ baseline/outcome=1 + add/outcome=1 + overdominance/outcome=1
+  with priors:
+            add/outcome=1 ~ logF( 2, 2 ).
+  overdominance/outcome=1 ~ logF( 4, 4 ).
+</code></pre>
+<p>If there is no 'with priors' line, or if priors for one of the parameters is missing, then it means
+HPTEST has not correctly interpreted your prior specification. (This is usually because the
+parameter names are not specified correctly - check the log output for the correct parameter names.)</p>
+<ul>
+<li>
+<p>Use the <code>-no-covariate-priors</code> option to turn off the priors on covariates.</p>
+</li>
+<li>
+<p>Use the <code>-no-prior</code> to turn off all priors - on the main genetic effect and on the covariates.
+(This therefore implements an unpenalised regression.)</p>
+</li>
+</ul>
+</section>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/6.6.2/d3.min.js"></script>
+<script src="https://cdn.jsdelivr.net/npm/jstat@latest/dist/jstat.min.js"></script>
+<script>
+    let geom = {
+        width: 380,
+        height: 200,
+        margin: {
+            top: 10,
+            left: 60,
+            bottom: 40,
+            right: 10
+        }
+    } ;
+    function dlogf( x, nu1, nu2 ) {
+        if( x > 0 ) {
+            return dlogf( -x, nu2, nu1 ) ;
+        }
+        let a = nu1/2 ;
+        let b = nu2/2 ;
+        let l = 1/(1 + Math.exp(-x)) ;
+        let constant = -(jStat.betaln(a, b)) ;
+        let result = a * Math.log(l) + b * Math.log(1 - l) + constant ;
+        return Math.exp( result ) ;
+    } ;
+    let dnorm = jStat.normal.pdf ;
+
+    function plotDistributions( svg, params, range, geom ) {
+        let data = [
+            {
+                type: "logF",
+                data: (
+                    d3.range( range[0], range[1], 0.1 )
+                        .map( elt => ({
+                            x: elt,
+                            y: dlogf( elt, params.nu1, params.nu2 )
+                        }))
+                )
+            },
+            {
+                type: "gaussian",
+                data: (
+                    d3.range( range[0], range[1], 0.1 )
+                        .map( elt => ({
+                            x: elt,
+                            y: dnorm( elt, params.mean, params.sd )
+                        }))
+                )
+            }
+        ] ;
+        console.log("DATA", data) ;
+
+        let scales = {
+            x: d3.scaleLinear()
+                .domain( range )
+                .range( [ geom.margin.left, geom.width - geom.margin.right ]),
+            y: d3.scaleLinear()
+                .domain( [0, d3.max( data[0].data, elt => elt.y )])
+                .range( [ geom.height - geom.margin.bottom, geom.margin.top ])
+        } ;
+
+        svg
+            .attr( 'width', geom.width )
+            .attr( 'height', geom.height ) ;
+
+        svg.selectAll( 'g.yAxis' )
+            .data( [1] )
+            .enter()
+            .append( 'g' )
+            .attr( 'class', 'yAxis' )
+            .attr( 'transform', 'translate( ' + (scales.x.range()[0] - 10) + ", 0)" )
+            .call( d3.axisLeft( scales.y ).ticks(5) ) ;
+
+        svg.selectAll( 'g.xAxis' )
+            .data( [1] )
+            .enter()
+            .append( 'g' )
+            .attr( 'class', 'xAxis' )
+            .attr( 'transform', 'translate( 0,' + (scales.y.range()[0] + 10) + ")" )
+            .call( d3.axisBottom( scales.x ).ticks(5) ) ;
+
+        let styles = {
+            "logF": {
+                "dasharray": "1 0"
+            },
+            "gaussian": {
+                "dasharray": "4 4"
+            }
+        }
+
+        let line = svg.selectAll( 'path.pt' )
+            .data( data )
+            .enter()
+            .append( 'path' )
+            .attr( 'class', 'pt' )
+            .attr( 'stroke', 'black' )
+            .attr( 'stroke-width', 1.5 )
+            .attr( 'stroke-dasharray', elt => styles[elt.type].dasharray )
+            .attr( 'fill', 'none' ) ;
+
+        line
+            .merge(line)
+            .attr(
+                'd',
+                function( d ) {
+                    return d3.line()
+                        .x( elt => scales.x(elt.x) )
+                        .y( elt => scales.y(elt.y) )
+                    ( d.data ) ;
+                }
+            ) ;
+
+        let legend = svg.selectAll( 'g.legend' )
+            .data( [
+                { type: "logF", display: "log-F(" + params.nu1 + ", " + params.nu2 + ")" },
+                { type: "gaussian", display: "N(" + params.mean + ", " + params.sd + "²)" }
+            ])
+            .enter()
+            .append( 'g' )
+            .attr( 'transform', ( elt, index ) => 'translate(' + ( geom.width - geom.margin.right - 100 ) + "," + (geom.margin.top+10+20*index) + ")" )
+        ;
+        legend
+            .append( 'line' )
+            .attr( 'x1', -10 )
+            .attr( 'x2', 0 )
+            .attr( 'y1', 0 )
+            .attr( 'y2', 0 )
+            .attr( 'stroke-width', 1.5 )
+            .attr( 'stroke', 'black' )
+            .attr( 'stroke-dasharray', elt => styles[elt.type].dasharray ) ;
+        legend.append( 'text' )
+            .attr( 'x', 5 )
+            .attr( 'y', 0 )
+            .attr( 'alignment-baseline', 'middle' )
+            .attr( 'font-size', '10pt' )
+            .text( elt => elt.display ) ;
+    } ;
+
+    plotDistributions(
+        d3.select( 'svg.plot1' ),
+        params = {
+            nu1: 2,
+            nu2: 2,
+            mean: 0,
+            sd: 1.87
+        },
+        range = [ -10, 10 ],
+        geom
+    ) ;
+
+    plotDistributions(
+        d3.select( 'svg.plot2' ),
+        params = {
+            nu1: 0.077,
+            nu2: 0.077,
+            mean: 0,
+            sd: 40
+        },
+        range = [ -100, 100 ],
+        geom
+    ) ;
+
+</script>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/sqlite_output.html
Index: doc/html/hptest/documentation/sqlite_output.html
==================================================================
--- doc/html/hptest/documentation/sqlite_output.html
+++ doc/html/hptest/documentation/sqlite_output.html
@@ -0,0 +1,115 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+<h3>The sqlite output format</h3>
+<p>If you use an output file of one of the following forms:</p>
+<ul>
+<li><code>myfile.sqlite</code></li>
+<li><code>myfile.sqlite:&lt;name&gt;</code></li>
+<li><code>sqlite://myfile.sqlite</code></li>
+<li><code>sqlite://myfile.sqlite:&lt;name&gt;</code></li>
+</ul>
+<p>then HPTEST will output results to a sqlite file instead of a flat file.  This has the following behaviour:</p>
+<ul>
+<li>
+<p>The analysis, its start/stop times and command-line arguments are recorded in the <code>Analysis</code>,
+  <code>AnalysisStatus</code>, and <code>AnalysisProperty</code> tables.</p>
+</li>
+<li>
+<p>The main results are placed in a table called <code>&lt;name&gt;</code>; if no name is supplied then the table is
+  called <code>analysis&lt;n&gt;</code> where n is one more than the number of analyses currently recorded
+  in the <code>Analysis</code> table, if any.</p>
+</li>
+<li>
+<p>The main results table does not contain full variant information; instead, genetic variants are
+  placed into a seperate <code>Variant</code> table. A view called <code>nameView</code> is also created which links
+  the main result, <code>Analysis</code>, and <code>Variant</code> tables through the <code>analysis_id</code>,
+  <code>predictor_id</code> and <code>outcome_id</code> fields.</p>
+</li>
+<li>
+<p>The main results table is indexed by default by the <code>predictor_id</code> and <code>outcome_id</code> fields.</p>
+</li>
+<li>
+<p>You can record more than one analysis in the same sqlite file. The only caveat is that analyses
+  that output different column names have to be stored in different results tables.</p>
+</li>
+</ul>
+<h3>Using the sqlite output file programmatically</h3>
+<p>Data from the sqlite output files can be read directly into analysis programs.
+For example, suppose you have named the output table <code>Result</code>.  Then in R:</p>
+<pre><code class="language-R">library( RSQLite )
+db = DBI::dbConnect(RSQLite::SQLite(), &quot;myfile.sqlite&quot; )
+data = dbGetQuery( db, &quot;SELECT * FROM ResultView LIMIT 100&quot; )
+</code></pre>
+<p>...or if you are using the <a href="https://dbplyr.tidyverse.org">tidyverse</a>:</p>
+<pre><code class="language-R">library( dplyr )
+db = DBI::dbConnect(RSQLite::SQLite(), &quot;myfile.sqlite&quot;)
+results = tbl( db, &quot;ResultView&quot; )
+results
+</code></pre>
+<p>Or it can be loaded in python using <a href="https://pandas.pydata.org">pandas</a>:</p>
+<pre><code class="language-python">import pandas
+db = sqlite3.connect( &quot;myfile.sqlite&quot; )
+pandas.read_sql(
+    &quot;SELECT * FROM ResultView LIMIT 100&quot; ),
+    db
+)
+</code></pre>
+<h3>Using the sqlite output file from a web service</h3>
+<p>Another thing you can do with the sqlite output format is to turn it into a web service. <a
+href="https://datasette.readthedocs.io">Datasette</a> is an extremely useful tool which turns a sqlite file into a RESTful web service like this:</p>
+<pre><code>$ datasette myfile.sqlite
+</code></pre>
+<p>Now you can access the database at <code>http://localhost:8001</code>.  This can be used to create web-based visualisations of the results.</p>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/technical_datails.html
Index: doc/html/hptest/documentation/technical_datails.html
==================================================================
--- doc/html/hptest/documentation/technical_datails.html
+++ doc/html/hptest/documentation/technical_datails.html
@@ -0,0 +1,60 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<script type="text/javascript" async
+		  src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+		</div>
+
+<section class="main_text">
+<p>HPTEST fits the following model:</p>
+<p>
+<script type="math/tex; mode=display">\text{log-odds}( Y = 1 } ) = X^t \cdot \beta</script>
+</p>
+<p>where <script type="math/tex">Y</script> is the outcome genotype, and <script type="math/tex">X</script> is a function of the predictor genotype and covariates,</p>
+<p>
+<script type="math/tex; mode=display">X = \left( \begin{matrix} 1 \\ F(\text{predictor}) \\ Z \end{matrix} \right)</script>
+</p>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/documentation/technical_details.html
Index: doc/html/hptest/documentation/technical_details.html
==================================================================
--- doc/html/hptest/documentation/technical_details.html
+++ doc/html/hptest/documentation/technical_details.html
@@ -0,0 +1,117 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="../style/images/logo.png">
+		</div>
+
+<section class="main_text">
+<p>HPTEST fits the following model:</p>
+<p>
+<script type="math/tex; mode=display">\text{log-odds}( \text{outcome genotype} = 1 ) = X^t \cdot \beta</script>
+</p>
+<p>where <script type="math/tex">X</script> is a function of the predictor genotype and covariates,</p>
+<p>
+<script type="math/tex; mode=display">X = \left( \begin{matrix} 1 \\ F(\text{predictor genotype}) \\ Z \end{matrix} \right)</script>
+</p>
+<p>and <script type="math/tex">\beta</script> is a vector of regression coefficients to be maximised over. The full likelihood is
+obtained as the product of the above over all samples in the data.</p>
+<p>HPTEST currently assumes that both outcome and predictor variants are biallelic (or at least that
+they have been split into biallelic records before running through HPTEST). The outcome and
+predictor genotypes are measured with respect to those alleles, i.e. the effect is always
+interpreted as effect of the second predictor allele on the second outcome allele. If the outcome
+has ploidy larger than 1, then its alleles are regarded as forming independent draws from the
+Bernoulli distribution modelled above (i.e. it's a binomial logistic regression model with number
+of trials equal to the ploidy).</p>
+<p>The predictor genotype is currently assumed to be diploid. To handle different possible modes of
+inheritance, HPTEST uses a variety of function <script type="math/tex">F</script> above as follows. If <script type="math/tex">g \in \{0,1,2\}</script> denotes
+the predictor genotype then the following functions <script type="math/tex">F</script> are used:</p>
+<table>
+<thead>
+<tr>
+<th>Mode of inheritance</th>
+<th>F</th>
+<th>Specified by</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>additive</td>
+<td>
+<script type="math/tex">F(g) = g</script>
+</td>
+<td><code>-model add</code></td>
+</tr>
+<tr>
+<td>dominant</td>
+<td>
+<script type="math/tex">F(g) = 1</script> if <script type="math/tex">g > 0</script>, or <script type="math/tex">0</script> otherwise</td>
+<td><code>-model dom</code></td>
+</tr>
+<tr>
+<td>recessive</td>
+<td>
+<script type="math/tex">F(g) = 1</script> if <script type="math/tex">g = 2</script>, or <script type="math/tex">0</script> otherwise</td>
+<td><code>-model rec</code></td>
+</tr>
+<tr>
+<td>heterozygote</td>
+<td>
+<script type="math/tex">F(g) = 1</script> if <script type="math/tex">g = 1</script>, or <script type="math/tex">0</script> otherwise</td>
+<td><code>-model het</code></td>
+</tr>
+<tr>
+<td>general</td>
+<td>
+<script type="math/tex">F(g) = (g,1)</script> if <script type="math/tex">g = 1</script>, or <script type="math/tex">(g,0)</script> otherwise</td>
+<td><code>-model add+het</code></td>
+</tr>
+</tbody>
+</table>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="../documentation/naming_things.html">Naming things</a></li>
+						<li><a href="../documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="../documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="../documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="../documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="../documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/hptest/index.html
Index: doc/html/hptest/index.html
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+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="js/datatables.min.js"></script>
+		<script type="text/javascript" src="js/local.js"></script>
+
+		<link href="style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="style/css/default.css" rel="stylesheet" type="text/css">
+		<title>HPTEST</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				HPTEST
+			</div>
+			<div class="header_subtext">
+				Software to test for genetic association between hosts and pathogens.
+			</div>
+			<img class="logo" src="style/images/logo.png">
+		</div>
+
+<section class="main_text">
+<div id="overview">
+<h3>Introduction</h3>
+<p>HPTEST is a command-line program to test for association between genotypes at pairs of genetic
+variants. The motivating use case is to test for association between hosts and pathogens, using
+genotype data from hosts and from the pathogens infecting those hosts, but HPTEST also has other
+potential use-cases, such as estimating LD between variants while controlling for confounding
+variables.</p>
+<p>The method currently implemented in HPTEST is logistic regression in which one set of genotypes
+(e.g. the host genotypes) are included as predictors and the second set (e.g. pathogen genotypes)
+are included as the outcome. Covariates can also be included. For each pair of variants, HPTEST
+outputs the genotype counts and a summary of the evidence for association.</p>
+<p>For an introduction to running HPTEST, please see the <a
+href="documentation/getting_started.html">getting started</a> page.</p>
+<h3>Obtaining and running HPTEST</h3>
+<p>HPTEST is currently included as part of the <a href="https://code.enkre.net/qctool">QCTOOL
+package</a>, which is currently hosted at <a href="https://code.enkre.net">code.enkre.net</a>. See
+the <a href="documentation/download.html">download page</a> for full details on obtaining
+and installing HPTEST.</p>
+<h3>References</h3>
+<p>HPTEST was originally developed for a study of human and malaria parasite variation in samples
+collected for <a href="https://www.malariagen.net/projects/consortial-project-1">MalariaGEN
+Consortial Project 1</a>. If you use HPTEST in published work, please cite the following preprint (or
+its published equivalent):</p>
+<div class="citation" style="padding-left: 20px; padding-right: 20px; font-family:Palatino">
+<p>"<strong>The protective effect of sickle cell haemoglobin against severe malaria depends on parasite genotype</strong>",
+bioRxiv <a href="https://doi.org/10.1101/2021.03.30.437659">https://doi.org/10.1101/2021.03.30.437659</a> <br>
+<small>Gavin Band, Ellen M. Leffler, Muminatou Jallow, Fatoumatta Sisay-Joof, Carolyne M. Ndila, Alexander W. Macharia,
+    Christina Hubbart, Anna E. Jeffreys, Kate Rowlands, Thuy Nguyen, Sonia M. Goncalves, Cristina V. Ariani,
+    Jim Stalker, Richard D. Pearson, Roberto Amato, Eleanor Drury, Giorgio Sirugo, Umberto d'Alessandro,
+    Kalifa A. Bojang, Kevin Marsh, Norbert N.P. Peshu, David J. Conway,
+    Thomas N. Williams, Kirk A. Rockett, Dominic P. Kwiatkowski
+</small></p>
+</div>
+<h3>Contact</h3>
+<p>For more information or questions, please contact me at <code>gavin [dot] band (at) well.ox.ac.uk</code>.</p>
+</div>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="documentation/getting_started.html">Getting started</a></li>
+						<li><a href="documentation/alphabetical_options.html">List of options</a></li>
+						<li><a href="documentation/naming_things.html">Naming things</a></li>
+						<li><a href="documentation/specifying_priors.html">Specifying priors</a></li>
+						<li><a href="documentation/interpreting_hptest_output.html">Interpreting HPTEST output</a></li>
+						<li><a href="documentation/sqlite_output.html">The sqlite output format</a></li>
+						<li><a href="documentation/filtering.html">Filtering variants and samples</a></li>
+						<li><a href="documentation/technical_details.html">Technical details</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

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+" "+l,"aria-controls":a.sTableId,"aria-label":i[r],"data-dt-idx":m,tabindex:a.iTabIndex,id:c===0&&typeof r==="string"?a.sTableId+"_"+r:null}).html(n).appendTo(b);Va(u,{action:r},v);m++}}}},s;try{s=h(b).find(G.activeElement).data("dt-idx")}catch(u){}o(h(b).empty(),d);s!==k&&h(b).find("[data-dt-idx="+s+"]").focus()}}});h.extend(m.ext.type.detect,[function(a,b){var c=b.oLanguage.sDecimal;return Ya(a,c)?"num"+c:null},function(a){if(a&&!(a instanceof Date)&&!Zb.test(a))return null;var b=Date.parse(a);
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+
+

ADDED   doc/html/hptest/js/jquery-3.2.1.min.js
Index: doc/html/hptest/js/jquery-3.2.1.min.js
==================================================================
--- doc/html/hptest/js/jquery-3.2.1.min.js
+++ doc/html/hptest/js/jquery-3.2.1.min.js
@@ -0,0 +1,4 @@
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ADDED   doc/html/hptest/js/local.js
Index: doc/html/hptest/js/local.js
==================================================================
--- doc/html/hptest/js/local.js
+++ doc/html/hptest/js/local.js
@@ -0,0 +1,12 @@
+$(document).ready(
+	function() {
+		$( '.nav_button' ).hover(
+			function( elt ) {
+				$(elt.currentTarget).addClass( "open" ) ;
+			},
+			function( elt ) {
+				$(elt.currentTarget).removeClass( "open" ) ;
+			}
+		)
+	}
+) ;

ADDED   doc/html/hptest/resources/columns.json
Index: doc/html/hptest/resources/columns.json
==================================================================
--- doc/html/hptest/resources/columns.json
+++ doc/html/hptest/resources/columns.json
@@ -0,0 +1,43 @@
+[
+  { "name": "predictor:alternate_ids", "description": "Predictor variant id(s)" },
+  { "name": "predictor:rsid", "description": "Primary predictor variant id" },
+  { "name": "predictor:chromosome ", "description": "Predictor chromosome" },
+  { "name": "predictor:position", "description": "Predictor base pair position" },
+  { "name": "predictor:alleleA ", "description": "predictor 1st allele" },
+  { "name": "predictor:alleleB ", "description": "predictor 2nd allele (effect estimates are for this allele)" },
+  { "name": "outcome:alternate_ids", "description": "Outcome variant id(s)" },
+  { "name": "outcome:rsid", "description": "Primary outcome variant id" },
+  { "name": "outcome:chromosome", "description": "outcome chromosome" },
+  { "name": "outcome:position", "description": "outcome base pair position" },
+  { "name": "outcome:alleleA", "description": "outcome 1st allele" },
+  { "name": "outcome:alleleB", "description": "outcome 2nd allele (effect estimates are for this allele)" },
+  { "name": "N", "description": "Total number of samples" },
+  { "name": "missing", "description": "Number of samples with missing data" },
+  { "name": "outcome=0", "description": "Count of outcome=0 genotypes" },
+  { "name": "outcome=1", "description": "Count of outcome=1 genotypes" },
+  { "name": "outcome=2", "description": "Count of outcome=2 genotypes" },
+  { "name": "predictor=0", "description": "Count of outcome=0 genotypes" },
+  { "name": "predictor=1", "description": "Count of outcome=1 genotypes" },
+  { "name": "predictor=2", "description": "Count of outcome=2 genotypes" },
+  { "name": "minimum_outcome_count", "description": "Minimum count of outcome alleleA or alleleB" },
+  { "name": "minimum_predictor_count", "description": "Minimum count of predictor alleleA or alleleB" },
+  { "name": "predictor_info", "description": "imputation info score for the predictor (reflecting uncertainty in imputed genotype distribution)." },
+  { "name": "null:converged", "description": "Did the null model (i.e. the model with baseline and covariates but no predictor genotypes) converge? (1=yes, 0 = no)" },
+  { "name": "null:iterations", "description": "How many iterations the null model took to converge" },
+  { "name": "null:fit_time", "description": "How much time the null model took to converge" },
+  { "name": "null:ll", "description": "Null model log-likelihood" },
+  { "name": "null:degrees_of_freedom", "description": "number of paramameters in null model" },
+  { "name": "[name]:converged", "description": "Did the full model [model name] converge?" },
+  { "name": "[name]:iterations", "description": "How many iterations?" },
+  { "name": "[name]:fit_time", "description": "Approximately how long the model took to fit in seconds." },
+  { "name": "[name]:ll", "description": "Full model log-likelihood (with prior penalisation)" },
+  { "name": "[name]:degrees_of_freedom", "description": "Number of parameters in full model" },
+  { "name": "[name]:beta_i:[parameter name]/outcome=1", "description": "Estimate of parameter i in full model named [name]" },
+  { "name": "[name]:sd_i", "description": "Estimated posterior standard deviation for beta_i" },
+  { "name": "[name]:cov_i,[j]", "description": "Estimated posterior covariance between parameters i and j" },
+  { "name": "[name]:log10_bf", "description": "log10 Bayes factor for full model [model name] against the null model" },
+  { "name": "[name]:prior_mode_i", "description": "Mode of the prior on parameter i (usually 0)" },
+  { "name": "[name]:se_i", "description": "Approximate frequentist standard error for beta_i" },
+  { "name": "[name]:pvalue_i", "description": "Approximate P-value for beta_i" },
+  { "name": "comment", "description": "Comments or notifications of errors (will be NA if nothing unusual occurred)." }
+]

ADDED   doc/html/hptest/resources/options.json
Index: doc/html/hptest/resources/options.json
==================================================================
--- doc/html/hptest/resources/options.json
+++ doc/html/hptest/resources/options.json
@@ -0,0 +1,376 @@
+{
+  "-analysis-chunk": {
+    "group": "",
+    "description": "Specify a name denoting the current genomic region or chunk on which this is run.  This is intended for use in parallel environments.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "NA" ]
+  },
+  "-analysis-id": {
+    "group": "",
+    "description": "Specify an integer ID for the current analysis.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-analysis-name": {
+    "group": "",
+    "description": "Specify a name to label results from this analysis with.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "hptest analysis" ]
+  },
+  "-covariates": {
+    "group": "",
+    "description": "Specify the name of one or more covariates to include in the model. These must be columns named in the sample file.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-debug": {
+    "group": "",
+    "description": "Output debugging information.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-details": {
+    "group": "",
+    "description": "Specify that hptest should produce detailed output for each test.",
+    "is_required": 14,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-excl-samples": {
+    "group": "",
+    "description": "Filter out samples whose sample ID lies in the given file.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-excl-samples-where": {
+    "group": "",
+    "description": "Exclude samples by specifying conditions on the values of columns in the sample file.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-incl-outcome-range": {
+    "group": "",
+    "description": "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-incl-outcome-rsids": {
+    "group": "",
+    "description": "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-incl-predictor-range": {
+    "group": "",
+    "description": "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-incl-predictor-rsids": {
+    "group": "",
+    "description": "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-incl-samples": {
+    "group": "",
+    "description": "Filter out samples whose sample ID does not lie in the given file(s).",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-incl-samples-where": {
+    "group": "",
+    "description": "Include samples by specifying conditions on the values of columns in the sample file.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-max-iterations": {
+    "group": "",
+    "description": "Maximum fitting iterations",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "100" ]
+  },
+  "-minimum-outcome-count": {
+    "group": "",
+    "description": "Skip outcomes that have less than this count",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "10" ]
+  },
+  "-minimum-predictor-count": {
+    "group": "",
+    "description": "Skip predictors that have less than this minor allele count",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "10" ]
+  },
+  "-model": {
+    "group": "",
+    "description": "Specify models to fit.  Syntax is <name>:<model>",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": "untilNextOption",
+    "default": [ "gen:add+het" ]
+  },
+  "-no-covariate-priors": {
+    "group": "",
+    "description": "Specify that no default prior should be placed on covariates. (By default a N(0,1000) prior is used).",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-no-prior": {
+    "group": "",
+    "description": "Specify that no prior should be used.  Only frequentist summaries will be output.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-o": {
+    "group": "",
+    "description": "Output file",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 1,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-outcome": {
+    "group": "",
+    "description": "Path to parasite genotype files.The given filename may contain the wildcard character '#', which expands to match aone- or two-character chromosome identifier.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 1,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-outcome-genotype-call-threshold": {
+    "group": "",
+    "description": "The threshold to apply to outcome genotype probabilities, if necessary, to make calls.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0.9" ]
+  },
+  "-outcome-name": {
+    "group": "",
+    "description": "Specify a name for the outcome variable",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "outcome" ]
+  },
+  "-output-all-variants": {
+    "group": "",
+    "description": "Specify that hptest should output all variant combinations, even those where tests are skipped.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-output-counts": {
+    "group": "",
+    "description": "Specify that hptest should output predictor and outcome genotype counts",
+    "is_required": 72,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-output-models": {
+    "group": "",
+    "description": "Specify which models to output estimates, standard errors, and Wald P-values for. This can be either \"alternative\", in which case only non-null models are output, or \"all\" in which case all models are output. ",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "alternative" ]
+  },
+  "-output-parameters": {
+    "group": "",
+    "description": "Specify which parameters to output estimates, standard errors, and Wald P-values for.By default only data on the genetic parameters are output; specify \"all\" to output all parameters.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "genetic" ]
+  },
+  "-predictor": {
+    "group": "",
+    "description": "Path to host genotype files.The given filename may contain the wildcard character '#', which expands to match aone- or two-character chromosome identifier.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 1,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-prior": {
+    "group": "",
+    "description": "Specify a prior for bayesian computation.Prior spec should be in the form <parameter name>~<distribution family>(parameters).(It is recommended to put single quotes round the whole argument to protect from shell expansion.)Currently, logF and gaussian priors are supported.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": "untilNextOption",
+    "default": [ "add/[outcome]=1~logf(2,2)", "overdominance/[outcome]=1~logf(4,4)", "het/[outcome]=1~logf(2,2)", "dom/[outcome]=1~logf(2,2)", "rec/[outcome]=1~logf(2,2)" ]
+  },
+  "-s": {
+    "group": "",
+    "description": "Path of sample file",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 1,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-threads": {
+    "group": "",
+    "description": "Number of additional threads to use in likelihood computations. The value 0 indicates that all work will take place in the main thread.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0" ]
+  },
+  "-tolerance": {
+    "group": "",
+    "description": "Tolerance",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0.001" ]
+  },
+  "-treat-outcome-as-haploid": {
+    "group": "",
+    "description": "Turn outcome homozygous genotype calls into haploid calls. Heterozygous calls will be treated as missing",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  }
+}

ADDED   doc/html/hptest/style/css/datatables.min.css
Index: doc/html/hptest/style/css/datatables.min.css
==================================================================
--- doc/html/hptest/style/css/datatables.min.css
+++ doc/html/hptest/style/css/datatables.min.css
@@ -0,0 +1,15 @@
+/*
+ * This combined file was created by the DataTables downloader builder:
+ *   https://datatables.net/download
+ *
+ * To rebuild or modify this file with the latest versions of the included
+ * software please visit:
+ *   https://datatables.net/download/#dt/dt-1.10.16
+ *
+ * Included libraries:
+ *   DataTables 1.10.16
+ */
+
+table.dataTable{width:100%;margin:0 auto;clear:both;border-collapse:separate;border-spacing:0}table.dataTable thead th,table.dataTable tfoot th{font-weight:bold}table.dataTable thead th,table.dataTable thead td{padding:10px 18px;border-bottom:1px solid #111}table.dataTable thead th:active,table.dataTable thead td:active{outline:none}table.dataTable tfoot th,table.dataTable tfoot td{padding:10px 18px 6px 18px;border-top:1px solid #111}table.dataTable thead .sorting,table.dataTable thead .sorting_asc,table.dataTable thead .sorting_desc,table.dataTable thead .sorting_asc_disabled,table.dataTable thead .sorting_desc_disabled{cursor:pointer;*cursor:hand;background-repeat:no-repeat;background-position:center right}table.dataTable thead .sorting{background-image:url("DataTables-1.10.16/images/sort_both.png")}table.dataTable thead .sorting_asc{background-image:url("DataTables-1.10.16/images/sort_asc.png")}table.dataTable thead .sorting_desc{background-image:url("DataTables-1.10.16/images/sort_desc.png")}table.dataTable thead .sorting_asc_disabled{background-image:url("DataTables-1.10.16/images/sort_asc_disabled.png")}table.dataTable thead .sorting_desc_disabled{background-image:url("DataTables-1.10.16/images/sort_desc_disabled.png")}table.dataTable tbody tr{background-color:#ffffff}table.dataTable tbody tr.selected{background-color:#B0BED9}table.dataTable tbody th,table.dataTable tbody td{padding:8px 10px}table.dataTable.row-border tbody th,table.dataTable.row-border tbody td,table.dataTable.display tbody th,table.dataTable.display tbody td{border-top:1px solid #ddd}table.dataTable.row-border tbody tr:first-child th,table.dataTable.row-border tbody tr:first-child td,table.dataTable.display tbody tr:first-child th,table.dataTable.display tbody tr:first-child td{border-top:none}table.dataTable.cell-border tbody th,table.dataTable.cell-border tbody td{border-top:1px solid #ddd;border-right:1px solid #ddd}table.dataTable.cell-border tbody tr th:first-child,table.dataTable.cell-border tbody tr td:first-child{border-left:1px solid #ddd}table.dataTable.cell-border tbody tr:first-child th,table.dataTable.cell-border tbody tr:first-child td{border-top:none}table.dataTable.stripe tbody tr.odd,table.dataTable.display tbody tr.odd{background-color:#f9f9f9}table.dataTable.stripe tbody tr.odd.selected,table.dataTable.display tbody tr.odd.selected{background-color:#acbad4}table.dataTable.hover tbody tr:hover,table.dataTable.display tbody tr:hover{background-color:#f6f6f6}table.dataTable.hover tbody tr:hover.selected,table.dataTable.display tbody tr:hover.selected{background-color:#aab7d1}table.dataTable.order-column tbody tr>.sorting_1,table.dataTable.order-column tbody tr>.sorting_2,table.dataTable.order-column tbody tr>.sorting_3,table.dataTable.display tbody tr>.sorting_1,table.dataTable.display tbody tr>.sorting_2,table.dataTable.display tbody tr>.sorting_3{background-color:#fafafa}table.dataTable.order-column tbody tr.selected>.sorting_1,table.dataTable.order-column tbody tr.selected>.sorting_2,table.dataTable.order-column tbody tr.selected>.sorting_3,table.dataTable.display tbody tr.selected>.sorting_1,table.dataTable.display tbody tr.selected>.sorting_2,table.dataTable.display tbody tr.selected>.sorting_3{background-color:#acbad5}table.dataTable.display tbody tr.odd>.sorting_1,table.dataTable.order-column.stripe tbody tr.odd>.sorting_1{background-color:#f1f1f1}table.dataTable.display tbody tr.odd>.sorting_2,table.dataTable.order-column.stripe tbody tr.odd>.sorting_2{background-color:#f3f3f3}table.dataTable.display tbody tr.odd>.sorting_3,table.dataTable.order-column.stripe tbody tr.odd>.sorting_3{background-color:whitesmoke}table.dataTable.display tbody tr.odd.selected>.sorting_1,table.dataTable.order-column.stripe tbody tr.odd.selected>.sorting_1{background-color:#a6b4cd}table.dataTable.display tbody tr.odd.selected>.sorting_2,table.dataTable.order-column.stripe tbody tr.odd.selected>.sorting_2{background-color:#a8b5cf}table.dataTable.display tbody tr.odd.selected>.sorting_3,table.dataTable.order-column.stripe tbody tr.odd.selected>.sorting_3{background-color:#a9b7d1}table.dataTable.display tbody tr.even>.sorting_1,table.dataTable.order-column.stripe tbody tr.even>.sorting_1{background-color:#fafafa}table.dataTable.display tbody tr.even>.sorting_2,table.dataTable.order-column.stripe tbody tr.even>.sorting_2{background-color:#fcfcfc}table.dataTable.display tbody tr.even>.sorting_3,table.dataTable.order-column.stripe tbody tr.even>.sorting_3{background-color:#fefefe}table.dataTable.display tbody tr.even.selected>.sorting_1,table.dataTable.order-column.stripe tbody tr.even.selected>.sorting_1{background-color:#acbad5}table.dataTable.display tbody tr.even.selected>.sorting_2,table.dataTable.order-column.stripe tbody tr.even.selected>.sorting_2{background-color:#aebcd6}table.dataTable.display tbody tr.even.selected>.sorting_3,table.dataTable.order-column.stripe tbody tr.even.selected>.sorting_3{background-color:#afbdd8}table.dataTable.display tbody tr:hover>.sorting_1,table.dataTable.order-column.hover tbody tr:hover>.sorting_1{background-color:#eaeaea}table.dataTable.display tbody tr:hover>.sorting_2,table.dataTable.order-column.hover tbody tr:hover>.sorting_2{background-color:#ececec}table.dataTable.display tbody tr:hover>.sorting_3,table.dataTable.order-column.hover tbody tr:hover>.sorting_3{background-color:#efefef}table.dataTable.display tbody tr:hover.selected>.sorting_1,table.dataTable.order-column.hover tbody tr:hover.selected>.sorting_1{background-color:#a2aec7}table.dataTable.display tbody tr:hover.selected>.sorting_2,table.dataTable.order-column.hover tbody tr:hover.selected>.sorting_2{background-color:#a3b0c9}table.dataTable.display tbody tr:hover.selected>.sorting_3,table.dataTable.order-column.hover tbody tr:hover.selected>.sorting_3{background-color:#a5b2cb}table.dataTable.no-footer{border-bottom:1px solid #111}table.dataTable.nowrap th,table.dataTable.nowrap td{white-space:nowrap}table.dataTable.compact thead th,table.dataTable.compact thead td{padding:4px 17px 4px 4px}table.dataTable.compact tfoot th,table.dataTable.compact tfoot td{padding:4px}table.dataTable.compact tbody th,table.dataTable.compact tbody td{padding:4px}table.dataTable th.dt-left,table.dataTable td.dt-left{text-align:left}table.dataTable th.dt-center,table.dataTable td.dt-center,table.dataTable td.dataTables_empty{text-align:center}table.dataTable th.dt-right,table.dataTable td.dt-right{text-align:right}table.dataTable th.dt-justify,table.dataTable td.dt-justify{text-align:justify}table.dataTable th.dt-nowrap,table.dataTable td.dt-nowrap{white-space:nowrap}table.dataTable thead th.dt-head-left,table.dataTable thead td.dt-head-left,table.dataTable tfoot th.dt-head-left,table.dataTable tfoot td.dt-head-left{text-align:left}table.dataTable thead th.dt-head-center,table.dataTable thead td.dt-head-center,table.dataTable tfoot th.dt-head-center,table.dataTable tfoot td.dt-head-center{text-align:center}table.dataTable thead th.dt-head-right,table.dataTable thead td.dt-head-right,table.dataTable tfoot th.dt-head-right,table.dataTable tfoot td.dt-head-right{text-align:right}table.dataTable thead th.dt-head-justify,table.dataTable thead td.dt-head-justify,table.dataTable tfoot th.dt-head-justify,table.dataTable tfoot td.dt-head-justify{text-align:justify}table.dataTable thead th.dt-head-nowrap,table.dataTable thead td.dt-head-nowrap,table.dataTable tfoot th.dt-head-nowrap,table.dataTable tfoot td.dt-head-nowrap{white-space:nowrap}table.dataTable tbody th.dt-body-left,table.dataTable tbody td.dt-body-left{text-align:left}table.dataTable tbody th.dt-body-center,table.dataTable tbody td.dt-body-center{text-align:center}table.dataTable tbody th.dt-body-right,table.dataTable tbody td.dt-body-right{text-align:right}table.dataTable tbody th.dt-body-justify,table.dataTable tbody td.dt-body-justify{text-align:justify}table.dataTable tbody th.dt-body-nowrap,table.dataTable tbody td.dt-body-nowrap{white-space:nowrap}table.dataTable,table.dataTable th,table.dataTable td{box-sizing:content-box}.dataTables_wrapper{position:relative;clear:both;*zoom:1;zoom:1}.dataTables_wrapper .dataTables_length{float:left}.dataTables_wrapper .dataTables_filter{float:right;text-align:right}.dataTables_wrapper .dataTables_filter input{margin-left:0.5em}.dataTables_wrapper .dataTables_info{clear:both;float:left;padding-top:0.755em}.dataTables_wrapper .dataTables_paginate{float:right;text-align:right;padding-top:0.25em}.dataTables_wrapper .dataTables_paginate .paginate_button{box-sizing:border-box;display:inline-block;min-width:1.5em;padding:0.5em 1em;margin-left:2px;text-align:center;text-decoration:none !important;cursor:pointer;*cursor:hand;color:#333 !important;border:1px solid transparent;border-radius:2px}.dataTables_wrapper .dataTables_paginate .paginate_button.current,.dataTables_wrapper .dataTables_paginate .paginate_button.current:hover{color:#333 !important;border:1px solid #979797;background-color:white;background:-webkit-gradient(linear, left top, left bottom, color-stop(0%, #fff), color-stop(100%, #dcdcdc));background:-webkit-linear-gradient(top, #fff 0%, #dcdcdc 100%);background:-moz-linear-gradient(top, #fff 0%, #dcdcdc 100%);background:-ms-linear-gradient(top, #fff 0%, #dcdcdc 100%);background:-o-linear-gradient(top, #fff 0%, #dcdcdc 100%);background:linear-gradient(to bottom, #fff 0%, #dcdcdc 100%)}.dataTables_wrapper .dataTables_paginate .paginate_button.disabled,.dataTables_wrapper .dataTables_paginate .paginate_button.disabled:hover,.dataTables_wrapper .dataTables_paginate .paginate_button.disabled:active{cursor:default;color:#666 !important;border:1px solid transparent;background:transparent;box-shadow:none}.dataTables_wrapper .dataTables_paginate .paginate_button:hover{color:white !important;border:1px solid #111;background-color:#585858;background:-webkit-gradient(linear, left top, left bottom, color-stop(0%, #585858), color-stop(100%, #111));background:-webkit-linear-gradient(top, #585858 0%, #111 100%);background:-moz-linear-gradient(top, #585858 0%, #111 100%);background:-ms-linear-gradient(top, #585858 0%, #111 100%);background:-o-linear-gradient(top, #585858 0%, #111 100%);background:linear-gradient(to bottom, #585858 0%, #111 100%)}.dataTables_wrapper .dataTables_paginate .paginate_button:active{outline:none;background-color:#2b2b2b;background:-webkit-gradient(linear, left top, left bottom, color-stop(0%, #2b2b2b), color-stop(100%, #0c0c0c));background:-webkit-linear-gradient(top, #2b2b2b 0%, #0c0c0c 100%);background:-moz-linear-gradient(top, #2b2b2b 0%, #0c0c0c 100%);background:-ms-linear-gradient(top, #2b2b2b 0%, #0c0c0c 100%);background:-o-linear-gradient(top, #2b2b2b 0%, #0c0c0c 100%);background:linear-gradient(to bottom, #2b2b2b 0%, #0c0c0c 100%);box-shadow:inset 0 0 3px #111}.dataTables_wrapper .dataTables_paginate .ellipsis{padding:0 1em}.dataTables_wrapper .dataTables_processing{position:absolute;top:50%;left:50%;width:100%;height:40px;margin-left:-50%;margin-top:-25px;padding-top:20px;text-align:center;font-size:1.2em;background-color:white;background:-webkit-gradient(linear, left top, right top, color-stop(0%, rgba(255,255,255,0)), color-stop(25%, rgba(255,255,255,0.9)), color-stop(75%, rgba(255,255,255,0.9)), color-stop(100%, rgba(255,255,255,0)));background:-webkit-linear-gradient(left, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%);background:-moz-linear-gradient(left, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%);background:-ms-linear-gradient(left, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%);background:-o-linear-gradient(left, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%);background:linear-gradient(to right, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%)}.dataTables_wrapper .dataTables_length,.dataTables_wrapper .dataTables_filter,.dataTables_wrapper .dataTables_info,.dataTables_wrapper .dataTables_processing,.dataTables_wrapper .dataTables_paginate{color:#333}.dataTables_wrapper .dataTables_scroll{clear:both}.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody{*margin-top:-1px;-webkit-overflow-scrolling:touch}.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>thead>tr>th,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>thead>tr>td,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>tbody>tr>th,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>tbody>tr>td{vertical-align:middle}.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>thead>tr>th>div.dataTables_sizing,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>thead>tr>td>div.dataTables_sizing,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>tbody>tr>th>div.dataTables_sizing,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>tbody>tr>td>div.dataTables_sizing{height:0;overflow:hidden;margin:0 !important;padding:0 !important}.dataTables_wrapper.no-footer .dataTables_scrollBody{border-bottom:1px solid #111}.dataTables_wrapper.no-footer div.dataTables_scrollHead table.dataTable,.dataTables_wrapper.no-footer div.dataTables_scrollBody>table{border-bottom:none}.dataTables_wrapper:after{visibility:hidden;display:block;content:"";clear:both;height:0}@media screen and (max-width: 767px){.dataTables_wrapper .dataTables_info,.dataTables_wrapper .dataTables_paginate{float:none;text-align:center}.dataTables_wrapper .dataTables_paginate{margin-top:0.5em}}@media screen and (max-width: 640px){.dataTables_wrapper .dataTables_length,.dataTables_wrapper .dataTables_filter{float:none;text-align:center}.dataTables_wrapper .dataTables_filter{margin-top:0.5em}}
+
+

ADDED   doc/html/hptest/style/css/default.css
Index: doc/html/hptest/style/css/default.css
==================================================================
--- doc/html/hptest/style/css/default.css
+++ doc/html/hptest/style/css/default.css
@@ -0,0 +1,132 @@
+@import "nav.css" ;
+@import "header.css" ;
+@import "table.css" ;
+
+body {
+	position: relative ;
+	width: 1000px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	overflow-y: auto ;
+	padding-bottom: 50px ;
+	font-family: "Palatino" ;
+	font-size: 12pt ;
+	/* border: 1px solid red; */
+}
+
+strong {
+	font-family: sans-serif ;
+}
+
+
+dt {
+	font-weight: bold ;
+	font-style: italic ;
+}
+
+section {
+	width: 800px ;
+	padding-top: 2em ;
+	margin-left: auto ;
+	margin-right: auto ;
+	font-family: serif ;
+	/*border: 1px dotted red ;*/
+}
+
+.main_text .display_diagram {
+	padding-top: 20px ;
+	margin-left: auto ;
+	margin-right: auto ;
+}
+
+.display_diagram_right {
+	padding-top: 0px ;
+	margin-left: 50px ;
+	float: right ;
+}
+
+.main_text .terminal_display {
+	height: 110px ;
+	overflow: auto ;
+	padding: 10px ;
+	margin-top: 10px ;
+	border: 1px dotted black ;
+	background-color: #22AD57 ;
+}
+
+
+
+h1, h2, h3, h4 {
+	font-family: sans-serif ;
+}
+
+.tutorial_header {
+	width: 100% ;
+	margin: 2px ;
+	overflow: auto ;
+}
+
+.tutorial_separator {
+	width: 100% ;
+	margin: 10px ;
+	border-bottom: 2px solid black ;
+}
+.task {
+	width: 100% ;
+	margin: 2px;
+	margin-top: 10px ;
+	overflow: auto ;
+}
+
+.task_name {
+	font-family: sans-serif ;
+	font-weight: bold ;
+	float: left ;
+}
+
+.task_notes {
+	clear: both ;
+	margin-top: 1px ;
+	margin-bottom: 1px ;
+	float: left ;
+	font-family: sans-serif ;
+	font-size: 0.8em;
+	padding: 5px ;
+}
+
+.monospace {
+	font-family: monospace ;
+}
+
+.task_command_line {
+	margin-top: 1px ;
+	margin-bottom: 1px ;
+	padding: 5px ;
+	font-family: monospace ;
+	background-color: #82BD77 ;
+	float: left ;
+	clear: left ;
+}
+
+.smalltext {
+	font-size: 80% ;
+}
+
+.column_definition lh {
+    font-size: 100% ;
+    margin-top: 10px ;
+    margin-bottom: 10px ;
+    font-family: sans-serif ;
+}
+
+pre > code {
+	display: block ;
+	width: 800px;
+	font-size: 10pt ;
+	background-color: #82BD77 ;
+	overflow-x: auto ;
+	overflow-y: auto ;
+	max-height: 20em ;
+	padding: 10px ;
+	padding-top, padding-bottom: 20px ;
+}

ADDED   doc/html/hptest/style/css/header.css
Index: doc/html/hptest/style/css/header.css
==================================================================
--- doc/html/hptest/style/css/header.css
+++ doc/html/hptest/style/css/header.css
@@ -0,0 +1,48 @@
+.header {
+	position: relative ;
+	height: 37px ;
+	width: 1000px ;
+}
+
+img.header_img {
+	float: left ;
+	padding-left: 10px ;
+	padding-right: 10px ;
+}
+
+img.header_arrow {
+	float: left;
+	clear: left ;
+	padding-left: 80px ;
+}
+
+.header_text {
+	float: left ;
+	padding-left: 10px ;
+	padding-right: 10px ;
+	font-family: Tahoma, Arial, Helvetica, Tahoma, sans-serif;
+	font-size: 40px ;
+}
+
+div.header_subtext {
+	position: absolute ;
+	padding-top: 20px ;
+	left: 0px ;
+	width: 100% ;
+	text-align: center ;
+}
+
+div.header {
+	border-bottom: 1px solid black ;
+	padding-bottom: 2px ;
+	font-family: sans-serif ;
+	font-size: 15px ;
+}
+
+.header .logo {
+	position: absolute ;
+	height: 40px ;
+	top: 3px ;
+	right: 15px ;
+	transform: rotate(10deg);
+}

ADDED   doc/html/hptest/style/css/nav.css
Index: doc/html/hptest/style/css/nav.css
==================================================================
--- doc/html/hptest/style/css/nav.css
+++ doc/html/hptest/style/css/nav.css
@@ -0,0 +1,92 @@
+nav {
+	width: 1000px ;
+	position: absolute ;
+	top: 2em;
+	height: 1.5em;
+//	left: 20px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	font-family: helvetica, sans-serif ;
+	font-size: 16pt ;
+	color: #000000;
+	padding-top: 0px ;
+	padding-bottom: 10px ;
+	padding-left: 0px ;
+	margin-top:0px ;
+	margin-bottom:0px ;
+	border-radius: 2px ;
+	/*border: 1px solid black ;*/
+}
+
+nav > div {
+	width: 500px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	//background-color: rgba( 220, 220, 220, 0.95 ) ;
+}
+
+.nav_button {
+	display: inline-block;
+	position: relative;
+	box-sizing: border-box ;
+	//margin-top: 10px ;
+	padding-left: 25px ;
+	padding-right: 25px ;
+	padding-top: 3px ;
+	padding-bottom: 0px ;
+	text-align: left ;
+}
+
+.nav_button.open {
+	background-color: rgba( 51, 176, 254, 0.9 ) ;
+}
+
+.nav_button ul a:hover {
+	background-color: rgba( 51, 176, 254, 0.9 ) ;
+}
+
+.nav_button a {
+	padding-left: 5px ;
+	padding-right: 5px ;
+	display: inline-block ;
+}
+
+.nav_button ul {
+	display:none ;
+	float: left ;
+	clear: both ;
+	box-sizing: border-box;
+	position: absolute ;
+	box-sizing: content-box ;
+	list-style: none;
+	text-align: left ;
+	left: 0px ;
+	min-width: 300px ;
+	background-color: white ;
+	padding: 3px ;
+	margin: 0px ;
+	font-size: 14px ;
+	/*width: 180px ;*/
+	padding-left: 3px ;
+	padding-right: 3px ;
+	background-color: rgba( 220, 220, 220, 0.95 ) ;
+	border-radius: 0px 0px 4px 4px;
+	box-shadow: 4px 4px 4px 0px rgba(0,0,0,0.2);
+}
+
+.nav_button ul a {
+	display: block;
+	width: auto;
+	padding-top: 2px ;
+	padding-bottom: 2px ;
+	padding-left: 15px ;
+}
+
+nav a, nav a:hover, nav a:visited {
+	color: black;
+	text-decoration: none ;
+}
+
+.nav_button.open ul {
+	display:block ;
+}

ADDED   doc/html/hptest/style/css/table.css
Index: doc/html/hptest/style/css/table.css
==================================================================
--- doc/html/hptest/style/css/table.css
+++ doc/html/hptest/style/css/table.css
@@ -0,0 +1,79 @@
+#download table {
+	text-align: left ;
+	width: 600px ;
+	border: 1px solid black ;
+	background-color: #CCCCCC ;
+	padding: 10px ;
+}
+
+.file_formats, .option_table {
+	table-layout: fixed ;
+	width: 800px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	font-family: helvetica, sans-serif ;
+	border-collapse: collapse ;
+}
+
+.file_formats thead, .option_table thead {
+	font-size: 14px ;
+	text-align: left ;
+	margin-bottom: 2px ;
+	vertical-align: bottom ;
+}
+
+.file_formats tbody, .option_table tbody {
+	font-size: 12px ;
+}
+
+.file_formats tr, .option_table tr {
+	margin-top: 10px ;
+	margin-bottom: 10px ;
+}
+
+tr:nth-child(even) {
+	background: "grey" ;
+}
+
+tr:nth-child(odd) {
+	background: "red" ;
+}
+
+table.dataTable tr.odd { background-color: #eeeeee; }
+
+.file_formats th, .option_table th {
+	padding-top: 3px ;
+	padding-bottom: 3px ;
+	border-bottom: 1px solid black ;
+}
+
+.file_formats td, .option_table td {
+	height: 100% ;
+	vertical-align: top ;
+	padding-top: 20px ;
+	padding-bottom: 20px ;
+}
+
+.file_formats .acronym {
+	width: 150px ;
+}
+
+.file_formats .notes {
+	width: 400px ;
+}
+
+.file_formats .io {
+	width: 50px ;
+}
+
+.file_formats .filetype {
+	width: 150px ;
+}
+
+.option_table .option {
+	width: 200px ;
+}
+
+.option_table .description {
+	width: 500px ;
+}

ADDED   doc/html/hptest/style/images/logo.png
Index: doc/html/hptest/style/images/logo.png
==================================================================
--- doc/html/hptest/style/images/logo.png
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+<section class="main_text">
+	<h2>Table of options</h2>
+	<p>Below is a list of all options supported by LDBIRD.</p>
+	<table class="option_table">
+		<colgroup>
+			<col class="option"></col>
+			<col class="description"></col>
+			<col class="default"></col>
+		</colgroup>
+		<thead>
+			<tr>
+				<th>
+					Option
+				</th>
+				<th>
+					Description
+				</th>
+				<th>
+					Default value?
+				</th>
+			</tr>
+		</thead>
+		<tbody>
+		</tbody>
+	</table>
+</section>
+
+<script>
+	$(document).ready(
+		function() {
+			$.getJSON( "../resources/options.json", function( data ) {
+				console.log( 'gotit' ) ;
+				var options = [] ;
+				$.each( data, function( key, value ) {
+					options.push( key ) ;
+					console.log( key ) ;
+				} ) ;
+				
+				options.sort( function(a,b) {
+					return a.toLowerCase().localeCompare( b.toLowerCase() ) ;
+				}) ;
+				
+				for( var i = 0; i < options.length; ++i ) {
+					$(".option_table > tbody").append(
+						'<tr>'
+						+ '<td>' + options[i] + '</td>'
+						+ '<td>' + data[options[i]]['description'] + '</td>'
+						+ '<td>' + ( data[options[i]].length == 0 ? "N/A" : data[options[i]].default.join( ", " )) + '</td>'
+						+ '/tr>'
+					)
+				}
+				
+				$( ".option_table" ).DataTable(
+					{
+						"paging": false,
+						"language": {
+							"search": "Search command-line options:"
+						}
+					}
+				) ;
+				
+				$('.dataTables_filter').css('float', 'left') ;
+			}) ;
+		}
+	) ;
+</script>

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+<section class="main_text" markdown="1" >
+###Obtaining LDBIRD###
+
+The source code to LDBIRD is available as part of the QCTOOL package, which is currently hosted at
+<a href="https://code.enkre.net/qctool">code.enkre.net</a>. To obtain LDBIRD you need to download
+version 2.1.9 or above of QCTOOL. The source code can be downloaded from the following link:
+
+<a href="https://code.enkre.net/qctool/zip/v2.1.9/qctool.tgz">https://code.enkre.net/qctool/zip/v2.1.9/qctool.tgz</a>
+
+Please be aware this tarball is generated on the fly and may take a few minutes to download.
+
+###Compiling LDBIRD###
+
+QCTOOL uses the <a href="https://waf.io">Waf build system</a> to manage the compilation process.
+For this to work you need python to be installed. (Waf itself is bundled with QCTOOL). A basic
+compilation process goes as follows:
+
+```
+$ ./waf configure
+$ ./waf
+```
+
+The first command configures the project (i.e. makes sure various prerequisites are in place). The
+second part compiles the QCTOOL package.  
+
+If successful you should now be able to try hptest:
+
+```
+$ ./build/release/apps/ldbird_v2.1.9
+!! Error (OptionProcessingException): Option "-g1" must be supplied..
+!! Run hptest -help for usage information.
+```
+
+The following is a more advanced example that specifies a path to a relevant C and C++ compiler and
+an installation directory.
+
+```
+$ CXX=/path/to/g++ CC=/path/to/gcc ./waf configure --prefix=/path/to/installation/dir
+$ ./waf install
+```
+
+If successful hptest (along with qctool and other tools) will be installed in ``/path/to/installation/dir/usr/bin``
+
+</section>

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+<section class="main_text" markdown="1" >
+
+### Filtering variants ###
+
+The following options can be used to filter variants from the analysis. Each of these options comes in an inclusiong
+variant (``-incl-...``), which tells LDBIRD to only focus on the specified variants, and an exclusion variant
+(``-excl-...``) which tells LDBIRD to ignore the specified variants, and each applies either to the predictor or
+outcome genotypes:
+
+* ``-g1-[in|ex]cl-range``: specify a genomic range or list of ranges to include or exclude outcome variants from, applied to the file specified by ``-g1``.
+
+* ``-g1-[in|ex]cl-rsids``: specify a set of variant IDs to include or exclude outcome variants from, applied to the file specified by ``-g1``.
+
+* ``-g2-[in|ex]cl-range``: as above but for the file specified by ``-g2``.
+
+* ``-g2-[in|ex]cl-rsids``: as above but for the file specified by ``-g2``.
+
+### Filtering samples ###
+
+The following options can be used to filter samples from the analysis:
+
+* ``-[in|ex]cl-samples``: specify a list of samples to include or exclude from the analysis. For this purpose, samples are identified
+by their identifier in the first column of the sample file.
+
+* ``-[in|ex]cl-samples-where``: specify a condition to apply to rows of the sample file to determine if the sample
+  should be included or excluded. The general syntax is ``-[in|ex]cl-samples-where '<column>[=|==|!=]<value>'``, which
+  will cause HPTEST to compare the values in the column named <column> of the sample file to the given value, and
+  include/exclude samples based on whether the values match (= or ==) or mismatch (!=).
+
+</section>

ADDED   doc/html/ldbird/content/documentation/getting_started.content.html
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+<section class="main_text" markdown="1">
+### Getting started ###
+
+LDBIRD computes LD metrics (i.e. the genotype correlation $R$) between all pairs of variants in two sets of genotypes
+specified on the command line, or between all pairs in one set of genotypes. It records a histogram of the LD values it
+sees and outputs specific pairs meeting specific thresholds.  The two ways to run it are:
+
+**Run with one genotypes file**:
+
+```
+ldbird -g1 <file.bgen> -s samples.sample -o ldbird.sqlite
+```
+
+This computes genotype counts and correlation ($r$) between every pair of variants in ``file.bgen``. By default only
+those with $r^2 > 0.05$ will be output, but if you specify ``-min-r2 0`` then the number of output rows will be $L \times (L+1) / 2$.
+
+**Run with two genotypes files**:
+```
+ldbird -g1 <file1.bgen> -g2 <file2.bgen> -s samples.sample -o ldbird.sqlite
+```
+
+This computes genotype counts and correlation between every variant in ``file1.bgen`` and in ``file2.bgen``. By default
+only those with $r^2 > 0.05$ will be output, but if you specify ``-min-r2 0`` then the number of output rows will be $L_1
+\times L_2$, where $L_i$ is the number of variants in ``file<i>.bgen``.
+
+### Supported file formats ###
+
+You don't necessarily need to use <a href="https://www.bgenformat.org">BGEN files</a> - LDBIRD also supports VCF
+format and a subset of other formats supported by <a href="https://www.well.ox.ac.uk/~gav/qctool">QCTOOL</a>.
+
+Samples must be supplied in a sample file of the type understood by QCTOOL - see the <a
+href="https://www.well.ox.ac.uk/~gav/qctool/documentation/sample_file_formats.html">QCTOOL file formats page</a> for
+details.
+
+### What you can put in ###
+
+At the time of writing there are three types of genotype you can put in. First, the input files can contain haploid
+genotypes. If so then the ``R`` table will contain a table of counts at both loci as well as the computed R value.
+Second, diploid genotypes can be put in - in this case the table of counts is currently not output. 
+
+A third option is to input haploid genotypes that are encoded as if they were diploid. The ``-assume-haploid`` option
+tells LDBIRD to convert these internally to haploid genotypes - it does this by treating heterozygous calls as missing
+and converting each homozygous call to the corresponding haploid genotype.
+
+### Understanding the output ###
+
+LDBIRD always outputs results to a <a href="https://www.sqlite.org">sqlite</a> database. The output file has the
+following features:
+
+* The analysis name, its start and stop times, and the command-line arguments are recorded in the ``Analysis``,
+  ``AnalysisStatus``, and ``AnalysisProperty`` tables.
+  
+* LDBIRD computes the frequency of each variant it sees. The variants are stored in the ``Variant`` table and the
+  frequencies are stored in the ``Frequency`` table. A convenient view, ``FrequencyView`` is also created to link these
+  tables together.
+
+* The main results are stored in the ``R`` table. A more convenient view, ``RView`` is also created which links the
+  ``R``, ``Analysis``, and ``Variant`` tables.
+
+* A histogram of $r$ values is also stored in the ``Histogram`` table - again there is a more convenient
+  ``HistogramView`` view which joins this to the ``Analysis`` table.
+
+### Using the ``R`` table ###
+
+To save space in the output file, LDBIRD currently encodes correlations by the following formula:
+$$
+\text{encoded r} = \text{round}\left(r+1.0) * 1024\right)
+$$
+
+This is stored in the ``encoded_r`` column of the ``R`` table. Because sqlite uses a variable-length integer encoding,
+this value only takes up one or two bytes of space in the output file.
+
+To convert ``encoded_r`` back to correlation, you can use the formula:
+$$
+r = (\text{encoded r} - 1024)/1024.0
+$$
+E.g. in sqlite:
+```
+$ sqlite3 ldbird.sqlite
+> SELECT *, (encoded_r-1024.0)/1024.0 AS r FROM R
+```
+(NB. the form ``1024.0`` is needed here to force sqlite to treat the result as a floating-point number.)
+
+The above means that LDBIRD stores a quantized version of the correlation - it is always encoded as an integer between
+0 and 2048 (inclusive). Correlation is expressed with respect to the second allele of each variant - this values in the range 0-1023
+represent -ve correlation between the second allele, and values in the range 1025-2048 represent positive correlation.
+
+### Controlling what comparisons are made ###
+
+There are three additional options which control what variants LDBIRD computes LD for:
+
+* The ``-min-distance`` option tells LDBIRD not to compute LD for any variants that are too close together on the same chromosome.
+
+* The ``-min-maf`` option tells LDBIRD not to compute LD for any variants that have too low minor allele frequency
+
+* The ``-min-N`` option tells LDBIRD to not compute LD for any pair of variants with fewer than this number of
+  samples having non-missing genotypes (taken pairwise across the two variants).
+
+* The ``-min-N-propn`` option tells LDBIRD to not compute LD for any pair of variants with fewer than this *proportion*
+  of samples having of non-missing genotypes (taken pairwise across the two variants).
+
+* Finally, the ``-min-r2`` option tells LDBIRD not to output results in the ``R`` table for any variants where the
+  computed $r^2$ is less than the given threshold. (This is slightly different to the above options because LD is still
+  computed and contributes to the ``Histogram`` table).
+
+Additionally a number of options are provided to filter the set of samples included in the analysis, or to filter the genomic ranges or IDs of variants that are included.
+See the <a href="[ROOT]/documentation/filtering_samples.html">page on filtering samples</a> for more information.
+
+### Using the ``Histogram`` table ###
+
+At the end of the run, LDBIRD stores a histogram of LD in the ``Histogram`` table. This is set up as follows: for each
+value of ``encoded_r``, the corresponding row of ``Histogram`` stores the number of variant pairs that were observed to
+have that ``encoded_r`` value. The column ``encoded_r`` can be converted back to $r$ as shown above. The ``Histogram``
+table always has 2049 rows (or 2049 per analysis, if you run multiple analyses into the same output file) corresponding
+to the 2049 possible values of ``encoded_r``.
+
+The ``Histogram`` table ignores any minimum $r^2$ value specified using ``-min-r2`` - in cases of testing long-range LD
+it will therefore likely contain a peak of LD values near $r=0$ (i.e. around $\text{encoded r} = 1024$), while if you
+test nearby variants you will get a spike near $r=1$ ($\text{encoded r}=2048). However, it respects the other filtering
+options outlined above, i.e. only variants with sufficient frequency and levels of non-missingness will be represented.
+
+### Setting up convenience views ###
+
+It is generally most useful to wrap all the above into a combined view of the frequencies and LD. We recommend setting
+this up by running the following SQL in the output file:
+
+```
+CREATE VIEW MyRView AS
+SELECT A.name AS `analysis`,
+V1.id AS g1_id, V1.rsid AS `g1_rsid`, V1.chromosome AS `g1_chromosome`, V1.position AS `g1_position`,
+V2.id AS g2_id, V2.rsid AS `g2_rsid`, V2.chromosome AS `g2_chromosome`, V2.position AS `g2_position`,
+R.*, (R.encoded_r-1024.0)/1024 AS r,
+F1.frequency AS g1_frequency, F2.frequency AS g2_frequency
+FROM R
+INNER JOIN Variant V1 ON V1.id = g1_id
+INNER JOIN Variant V2 ON V2.id = g2_id
+CROSS JOIN Analysis A ON A.id = R.analysis_id
+CROSS JOIN Frequency F1 ON F1.analysis_id == R.analysis_id AND F1.variant_id == R.g1_id
+CROSS JOIN Frequency F2 ON F2.analysis_id == R.analysis_id AND F2.variant_id == R.g2_id;
+```
+
+Which can be used to produce output like this (here run on test data):
+```
+$ sqlite3 -column -header ldbird.sqlite "SELECT * FROM MyRView LIMIT 10"
+analysis         g1_id       g1_rsid     g1_chromosome  g1_position  g2_id       g2_rsid     g2_chromosome  g2_position  analysis_id  g1_id:1     g2_id:1     N           encoded_r   r           g1_frequency  g2_frequency
+---------------  ----------  ----------  -------------  -----------  ----------  ----------  -------------  -----------  -----------  ----------  ----------  ----------  ----------  ----------  ------------  ------------
+ldbird analysis  1           H1          H1             1            1           H1          H1             1            1            1           1           4000        2048        1.0         0.181         0.181       
+ldbird analysis  1           H1          H1             1            2           H2          H1             2            1            1           2           4000        1041        0.01660156  0.181         0.14225     
+ldbird analysis  1           H1          H1             1            3           H3          H1             3            1            1           3           4000        1017        -0.0068359  0.181         0.19        
+ldbird analysis  1           H1          H1             1            4           H4          H1             4            1            1           4           4000        1051        0.02636718  0.181         0.01025     
+ldbird analysis  1           H1          H1             1            5           H5          H1             5            1            1           5           4000        1022        -0.0019531  0.181         0.31725     
+ldbird analysis  1           H1          H1             1            6           H6          H1             6            1            1           6           4000        982         -0.0410156  0.181         0.00525     
+ldbird analysis  1           H1          H1             1            7           H7          H1             7            1            1           7           4000        992         -0.03125    0.181         0.14725     
+ldbird analysis  1           H1          H1             1            8           H8          H1             8            1            1           8           4000        1022        -0.0019531  0.181         0.1465      
+ldbird analysis  1           H1          H1             1            9           H9          H1             9            1            1           9           4000        1026        0.00195312  0.181         0.039       
+ldbird analysis  1           H1          H1             1            10          H10         H1             10           1            1           10          4000        1002        -0.0214843  0.181         0.405       
+```
+
+LDBIRD doesn't create this view by itself currently, but a future version might do so. A similar view of the Histogram
+table can also be made.
+
+</section>

ADDED   doc/html/ldbird/content/footer.html
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--- doc/html/ldbird/content/footer.html
+++ doc/html/ldbird/content/footer.html
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+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="[ROOT]/index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="[ROOT]/documentation/getting_started.html">Getting started</a></li>
+						<li><a href="[ROOT]/documentation/alphabetical_options.html">List of options</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="[ROOT]/documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/ldbird/content/header.html
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--- doc/html/ldbird/content/header.html
+++ doc/html/ldbird/content/header.html
@@ -0,0 +1,26 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="[ROOT]/js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="[ROOT]/js/datatables.min.js"></script>
+		<script type="text/javascript" src="[ROOT]/js/local.js"></script>
+
+		<link href="[ROOT]/style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="[ROOT]/style/css/default.css" rel="stylesheet" type="text/css">
+		<title>LDBIRD</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				LDBIRD
+			</div>
+			<div class="header_subtext">
+				Software to compute and histogram pairwise LD metrics
+			</div>
+			<img class="bird" src="[ROOT]/style/images/ldbird.png">
+		</div>

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--- doc/html/ldbird/content/index.content.html
+++ doc/html/ldbird/content/index.content.html
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+<section class="main_text" markdown="1">
+<div id="overview" markdown="1">
+
+### Introduction ###
+
+LDBIRD is a command-line program for computing LD metrics between all pairs of variants in its input files.
+
+In working on the paper described below, I needed a way to quickly assess the distribution of between-chromosome LD in
+*P.falciparum* populations - as well as finding individual pairs of variants with outlying LD. Thus LDBIRD was born.
+The key features LDBIRD has are:
+
+* It computes a histogram of LD values across pairs of variants as well as identifying individual pairs with strong LD.
+* It handles haploid genotypes (as well as diploid genotypes, and haploid genotypes encoded as if they were diploid).
+* It accepts a variety of different genotype file formats (a subset of those accepted by <a
+  href="https://www.well.ox.ac.uk/~gav/qctool">QCTOOL</a>) and has helpful options for filtering samples and variants.
+* Its output format (in a <a href="https://www.sqlite.org">sqlite</a> db) is reasonably compact and readibly post-processable.
+* It's reasonably fast (given what it does).
+
+For an introduction to running LDBIRD, please see the <a href="[ROOT]/documentation/getting_started.html">getting
+started</a> page.
+
+#### How fast is LDBIRD? ####
+
+LDBIRD is likely not the fastest way you can compute LD. It limits itself to loading variants one
+(or rather two) at a time, and thus its algorithm is quadratic in the number of variants. If LDBIRD
+doesn't meet your needs, other ways to compute LD are to use <a
+href="https://www.cog-genomics.org/plink/2.0/">plink</a> or <a
+href="http://www.christianbenner.com/">LDStore</a>, or possibly <a
+href="https://tskit.dev/tskit/docs/stable/">tskit</a>.
+
+### Obtaining LDBIRD ###
+
+LDBIRD is currently included as part of the <a href="https://code.enkre.net/qctool">QCTOOL
+package</a>, which is currently hosted at <a href="https://code.enkre.net">code.enkre.net</a> and
+mirrored <a href="https://github.com/gavinband/qctool">on github<a>. See the <a
+href="[ROOT]/documentation/download.html">download page</a> for full details on obtaining and
+installing LDBIRD.
+
+### References ###
+
+LDBIRD was originally developed for a study of human and malaria parasite variation in samples collected for <a
+href="https://www.malariagen.net/projects/consortial-project-1">MalariaGEN Consortial Project 1</a>. If you use LDBIRD
+in published work, please cite the following preprint (or its published equivalent):
+
+<div class="citation" style="padding-left: 20px; padding-right: 20px; font-family:Palatino" markdown="1">
+"**The protective effect of sickle cell haemoglobin against severe malaria depends on parasite genotype**",
+bioRxiv <https://doi.org/10.1101/2021.03.30.437659> <br>
+<small>Gavin Band, Ellen M. Leffler, Muminatou Jallow, Fatoumatta Sisay-Joof, Carolyne M. Ndila, Alexander W. Macharia,
+	Christina Hubbart, Anna E. Jeffreys, Kate Rowlands, Thuy Nguyen, Sonia M. Goncalves, Cristina V. Ariani,
+	Jim Stalker, Richard D. Pearson, Roberto Amato, Eleanor Drury, Giorgio Sirugo, Umberto d'Alessandro,
+	Kalifa A. Bojang, Kevin Marsh, Norbert N.P. Peshu, David J. Conway,
+	Thomas N. Williams, Kirk A. Rockett, Dominic P. Kwiatkowski
+</small>
+</div>
+
+### Contact ###
+
+For more information or questions, please contact me at ``gavin [dot] band (at) well.ox.ac.uk``.
+	
+</div>
+</section>

ADDED   doc/html/ldbird/documentation/alphabetical_options.html
Index: doc/html/ldbird/documentation/alphabetical_options.html
==================================================================
--- doc/html/ldbird/documentation/alphabetical_options.html
+++ doc/html/ldbird/documentation/alphabetical_options.html
@@ -0,0 +1,113 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>LDBIRD</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				LDBIRD
+			</div>
+			<div class="header_subtext">
+				Software to compute and histogram pairwise LD metrics
+			</div>
+			<img class="bird" src="../style/images/ldbird.png">
+		</div>
+
+<section class="main_text">
+    <h2>Table of options</h2>
+    <p>Below is a list of all options supported by LDBIRD.</p>
+    <table class="option_table">
+        <colgroup>
+            <col class="option"></col>
+            <col class="description"></col>
+            <col class="default"></col>
+        </colgroup>
+        <thead>
+            <tr>
+                <th>
+                    Option
+                </th>
+                <th>
+                    Description
+                </th>
+                <th>
+                    Default value?
+                </th>
+            </tr>
+        </thead>
+        <tbody>
+        </tbody>
+    </table>
+</section>
+
+<script>
+    $(document).ready(
+        function() {
+            $.getJSON( "../resources/options.json", function( data ) {
+                console.log( 'gotit' ) ;
+                var options = [] ;
+                $.each( data, function( key, value ) {
+                    options.push( key ) ;
+                    console.log( key ) ;
+                } ) ;
+
+                options.sort( function(a,b) {
+                    return a.toLowerCase().localeCompare( b.toLowerCase() ) ;
+                }) ;
+
+                for( var i = 0; i < options.length; ++i ) {
+                    $(".option_table > tbody").append(
+                        '<tr>'
+                        + '<td>' + options[i] + '</td>'
+                        + '<td>' + data[options[i]]['description'] + '</td>'
+                        + '<td>' + ( data[options[i]].length == 0 ? "N/A" : data[options[i]].default.join( ", " )) + '</td>'
+                        + '/tr>'
+                    )
+                }
+
+                $( ".option_table" ).DataTable(
+                    {
+                        "paging": false,
+                        "language": {
+                            "search": "Search command-line options:"
+                        }
+                    }
+                ) ;
+
+                $('.dataTables_filter').css('float', 'left') ;
+            }) ;
+        }
+    ) ;
+</script>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/ldbird/documentation/download.html
Index: doc/html/ldbird/documentation/download.html
==================================================================
--- doc/html/ldbird/documentation/download.html
+++ doc/html/ldbird/documentation/download.html
@@ -0,0 +1,75 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>LDBIRD</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				LDBIRD
+			</div>
+			<div class="header_subtext">
+				Software to compute and histogram pairwise LD metrics
+			</div>
+			<img class="bird" src="../style/images/ldbird.png">
+		</div>
+
+<section class="main_text">
+<h3>Obtaining LDBIRD</h3>
+<p>The source code to LDBIRD is available as part of the QCTOOL package, which is currently hosted at
+<a href="https://code.enkre.net/qctool">code.enkre.net</a>. To obtain LDBIRD you need to download
+version 2.1.9 or above of QCTOOL. The source code can be downloaded from the following link:</p>
+<p><a href="https://code.enkre.net/qctool/zip/v2.1.9/qctool.tgz">https://code.enkre.net/qctool/zip/v2.1.9/qctool.tgz</a></p>
+<p>Please be aware this tarball is generated on the fly and may take a few minutes to download.</p>
+<h3>Compiling LDBIRD</h3>
+<p>QCTOOL uses the <a href="https://waf.io">Waf build system</a> to manage the compilation process.
+For this to work you need python to be installed. (Waf itself is bundled with QCTOOL). A basic
+compilation process goes as follows:</p>
+<pre><code>$ ./waf configure
+$ ./waf
+</code></pre>
+<p>The first command configures the project (i.e. makes sure various prerequisites are in place). The
+second part compiles the QCTOOL package.  </p>
+<p>If successful you should now be able to try hptest:</p>
+<pre><code>$ ./build/release/apps/ldbird_v2.1.9
+!! Error (OptionProcessingException): Option &quot;-g1&quot; must be supplied..
+!! Run hptest -help for usage information.
+</code></pre>
+<p>The following is a more advanced example that specifies a path to a relevant C and C++ compiler and
+an installation directory.</p>
+<pre><code>$ CXX=/path/to/g++ CC=/path/to/gcc ./waf configure --prefix=/path/to/installation/dir
+$ ./waf install
+</code></pre>
+<p>If successful hptest (along with qctool and other tools) will be installed in <code>/path/to/installation/dir/usr/bin</code></p>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/ldbird/documentation/filtering_samples.html
Index: doc/html/ldbird/documentation/filtering_samples.html
==================================================================
--- doc/html/ldbird/documentation/filtering_samples.html
+++ doc/html/ldbird/documentation/filtering_samples.html
@@ -0,0 +1,82 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>LDBIRD</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				LDBIRD
+			</div>
+			<div class="header_subtext">
+				Software to compute and histogram pairwise LD metrics
+			</div>
+			<img class="bird" src="../style/images/ldbird.png">
+		</div>
+
+<section class="main_text">
+<h3>Filtering variants</h3>
+<p>The following options can be used to filter variants from the analysis. Each of these options comes in an inclusiong
+variant (<code>-incl-...</code>), which tells LDBIRD to only focus on the specified variants, and an exclusion variant
+(<code>-excl-...</code>) which tells LDBIRD to ignore the specified variants, and each applies either to the predictor or
+outcome genotypes:</p>
+<ul>
+<li>
+<p><code>-g1-[in|ex]cl-range</code>: specify a genomic range or list of ranges to include or exclude outcome variants from, applied to the file specified by <code>-g1</code>.</p>
+</li>
+<li>
+<p><code>-g1-[in|ex]cl-rsids</code>: specify a set of variant IDs to include or exclude outcome variants from, applied to the file specified by <code>-g1</code>.</p>
+</li>
+<li>
+<p><code>-g2-[in|ex]cl-range</code>: as above but for the file specified by <code>-g2</code>.</p>
+</li>
+<li>
+<p><code>-g2-[in|ex]cl-rsids</code>: as above but for the file specified by <code>-g2</code>.</p>
+</li>
+</ul>
+<h3>Filtering samples</h3>
+<p>The following options can be used to filter samples from the analysis:</p>
+<ul>
+<li>
+<p><code>-[in|ex]cl-samples</code>: specify a list of samples to include or exclude from the analysis. For this purpose, samples are identified
+by their identifier in the first column of the sample file.</p>
+</li>
+<li>
+<p><code>-[in|ex]cl-samples-where</code>: specify a condition to apply to rows of the sample file to determine if the sample
+  should be included or excluded. The general syntax is <code>-[in|ex]cl-samples-where '&lt;column&gt;[=|==|!=]&lt;value&gt;'</code>, which
+  will cause HPTEST to compare the values in the column named <column> of the sample file to the given value, and
+  include/exclude samples based on whether the values match (= or ==) or mismatch (!=).</p>
+</li>
+</ul>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/ldbird/documentation/getting_started.html
Index: doc/html/ldbird/documentation/getting_started.html
==================================================================
--- doc/html/ldbird/documentation/getting_started.html
+++ doc/html/ldbird/documentation/getting_started.html
@@ -0,0 +1,187 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
+		<script type="text/javascript" src="../js/local.js"></script>
+
+		<link href="../style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
+		<title>LDBIRD</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				LDBIRD
+			</div>
+			<div class="header_subtext">
+				Software to compute and histogram pairwise LD metrics
+			</div>
+			<img class="bird" src="../style/images/ldbird.png">
+		</div>
+
+<section class="main_text">
+<h3>Getting started</h3>
+<p>LDBIRD computes LD metrics (i.e. the genotype correlation <script type="math/tex">R</script>) between all pairs of variants in two sets of genotypes
+specified on the command line, or between all pairs in one set of genotypes. It records a histogram of the LD values it
+sees and outputs specific pairs meeting specific thresholds.  The two ways to run it are:</p>
+<p><strong>Run with one genotypes file</strong>:</p>
+<pre><code>ldbird -g1 &lt;file.bgen&gt; -s samples.sample -o ldbird.sqlite
+</code></pre>
+<p>This computes genotype counts and correlation (<script type="math/tex">r</script>) between every pair of variants in <code>file.bgen</code>. By default only
+those with <script type="math/tex">r^2 > 0.05</script> will be output, but if you specify <code>-min-r2 0</code> then the number of output rows will be <script type="math/tex">L \times (L+1) / 2</script>.</p>
+<p><strong>Run with two genotypes files</strong>:</p>
+<pre><code>ldbird -g1 &lt;file1.bgen&gt; -g2 &lt;file2.bgen&gt; -s samples.sample -o ldbird.sqlite
+</code></pre>
+<p>This computes genotype counts and correlation between every variant in <code>file1.bgen</code> and in <code>file2.bgen</code>. By default
+only those with <script type="math/tex">r^2 > 0.05</script> will be output, but if you specify <code>-min-r2 0</code> then the number of output rows will be <script type="math/tex">L_1
+\times L_2</script>, where <script type="math/tex">L_i</script> is the number of variants in <code>file&lt;i&gt;.bgen</code>.</p>
+<h3>Supported file formats</h3>
+<p>You don't necessarily need to use <a href="https://www.bgenformat.org">BGEN files</a> - LDBIRD also supports VCF
+format and a subset of other formats supported by <a href="https://www.well.ox.ac.uk/~gav/qctool">QCTOOL</a>.</p>
+<p>Samples must be supplied in a sample file of the type understood by QCTOOL - see the <a
+href="https://www.well.ox.ac.uk/~gav/qctool/documentation/sample_file_formats.html">QCTOOL file formats page</a> for
+details.</p>
+<h3>What you can put in</h3>
+<p>At the time of writing there are three types of genotype you can put in. First, the input files can contain haploid
+genotypes. If so then the <code>R</code> table will contain a table of counts at both loci as well as the computed R value.
+Second, diploid genotypes can be put in - in this case the table of counts is currently not output. </p>
+<p>A third option is to input haploid genotypes that are encoded as if they were diploid. The <code>-assume-haploid</code> option
+tells LDBIRD to convert these internally to haploid genotypes - it does this by treating heterozygous calls as missing
+and converting each homozygous call to the corresponding haploid genotype.</p>
+<h3>Understanding the output</h3>
+<p>LDBIRD always outputs results to a <a href="https://www.sqlite.org">sqlite</a> database. The output file has the
+following features:</p>
+<ul>
+<li>
+<p>The analysis name, its start and stop times, and the command-line arguments are recorded in the <code>Analysis</code>,
+  <code>AnalysisStatus</code>, and <code>AnalysisProperty</code> tables.</p>
+</li>
+<li>
+<p>LDBIRD computes the frequency of each variant it sees. The variants are stored in the <code>Variant</code> table and the
+  frequencies are stored in the <code>Frequency</code> table. A convenient view, <code>FrequencyView</code> is also created to link these
+  tables together.</p>
+</li>
+<li>
+<p>The main results are stored in the <code>R</code> table. A more convenient view, <code>RView</code> is also created which links the
+  <code>R</code>, <code>Analysis</code>, and <code>Variant</code> tables.</p>
+</li>
+<li>
+<p>A histogram of <script type="math/tex">r</script> values is also stored in the <code>Histogram</code> table - again there is a more convenient
+  <code>HistogramView</code> view which joins this to the <code>Analysis</code> table.</p>
+</li>
+</ul>
+<h3>Using the <code>R</code> table</h3>
+<p>To save space in the output file, LDBIRD currently encodes correlations by the following formula:
+<script type="math/tex; mode=display">
+\text{encoded r} = \text{round}\left(r+1.0) * 1024\right)
+</script>
+</p>
+<p>This is stored in the <code>encoded_r</code> column of the <code>R</code> table. Because sqlite uses a variable-length integer encoding,
+this value only takes up one or two bytes of space in the output file.</p>
+<p>To convert <code>encoded_r</code> back to correlation, you can use the formula:
+<script type="math/tex; mode=display">
+r = (\text{encoded r} - 1024)/1024.0
+</script>
+E.g. in sqlite:</p>
+<pre><code>$ sqlite3 ldbird.sqlite
+&gt; SELECT *, (encoded_r-1024.0)/1024.0 AS r FROM R
+</code></pre>
+<p>(NB. the form <code>1024.0</code> is needed here to force sqlite to treat the result as a floating-point number.)</p>
+<p>The above means that LDBIRD stores a quantized version of the correlation - it is always encoded as an integer between
+0 and 2048 (inclusive). Correlation is expressed with respect to the second allele of each variant - this values in the range 0-1023
+represent -ve correlation between the second allele, and values in the range 1025-2048 represent positive correlation.</p>
+<h3>Controlling what comparisons are made</h3>
+<p>There are three additional options which control what variants LDBIRD computes LD for:</p>
+<ul>
+<li>
+<p>The <code>-min-distance</code> option tells LDBIRD not to compute LD for any variants that are too close together on the same chromosome.</p>
+</li>
+<li>
+<p>The <code>-min-maf</code> option tells LDBIRD not to compute LD for any variants that have too low minor allele frequency</p>
+</li>
+<li>
+<p>The <code>-min-N</code> option tells LDBIRD to not compute LD for any pair of variants with fewer than this number of
+  samples having non-missing genotypes (taken pairwise across the two variants).</p>
+</li>
+<li>
+<p>The <code>-min-N-propn</code> option tells LDBIRD to not compute LD for any pair of variants with fewer than this <em>proportion</em>
+  of samples having of non-missing genotypes (taken pairwise across the two variants).</p>
+</li>
+<li>
+<p>Finally, the <code>-min-r2</code> option tells LDBIRD not to output results in the <code>R</code> table for any variants where the
+  computed <script type="math/tex">r^2</script> is less than the given threshold. (This is slightly different to the above options because LD is still
+  computed and contributes to the <code>Histogram</code> table).</p>
+</li>
+</ul>
+<p>Additionally a number of options are provided to filter the set of samples included in the analysis, or to filter the genomic ranges or IDs of variants that are included.
+See the <a href="../documentation/filtering_samples.html">page on filtering samples</a> for more information.</p>
+<h3>Using the <code>Histogram</code> table</h3>
+<p>At the end of the run, LDBIRD stores a histogram of LD in the <code>Histogram</code> table. This is set up as follows: for each
+value of <code>encoded_r</code>, the corresponding row of <code>Histogram</code> stores the number of variant pairs that were observed to
+have that <code>encoded_r</code> value. The column <code>encoded_r</code> can be converted back to <script type="math/tex">r</script> as shown above. The <code>Histogram</code>
+table always has 2049 rows (or 2049 per analysis, if you run multiple analyses into the same output file) corresponding
+to the 2049 possible values of <code>encoded_r</code>.</p>
+<p>The <code>Histogram</code> table ignores any minimum <script type="math/tex">r^2</script> value specified using <code>-min-r2</code> - in cases of testing long-range LD
+it will therefore likely contain a peak of LD values near <script type="math/tex">r=0</script> (i.e. around <script type="math/tex">\text{encoded r} = 1024</script>), while if you
+test nearby variants you will get a spike near <script type="math/tex">r=1</script> ($\text{encoded r}=2048). However, it respects the other filtering
+options outlined above, i.e. only variants with sufficient frequency and levels of non-missingness will be represented.</p>
+<h3>Setting up convenience views</h3>
+<p>It is generally most useful to wrap all the above into a combined view of the frequencies and LD. We recommend setting
+this up by running the following SQL in the output file:</p>
+<pre><code>CREATE VIEW MyRView AS
+SELECT A.name AS `analysis`,
+V1.id AS g1_id, V1.rsid AS `g1_rsid`, V1.chromosome AS `g1_chromosome`, V1.position AS `g1_position`,
+V2.id AS g2_id, V2.rsid AS `g2_rsid`, V2.chromosome AS `g2_chromosome`, V2.position AS `g2_position`,
+R.*, (R.encoded_r-1024.0)/1024 AS r,
+F1.frequency AS g1_frequency, F2.frequency AS g2_frequency
+FROM R
+INNER JOIN Variant V1 ON V1.id = g1_id
+INNER JOIN Variant V2 ON V2.id = g2_id
+CROSS JOIN Analysis A ON A.id = R.analysis_id
+CROSS JOIN Frequency F1 ON F1.analysis_id == R.analysis_id AND F1.variant_id == R.g1_id
+CROSS JOIN Frequency F2 ON F2.analysis_id == R.analysis_id AND F2.variant_id == R.g2_id;
+</code></pre>
+<p>Which can be used to produce output like this (here run on test data):</p>
+<pre><code>$ sqlite3 -column -header ldbird.sqlite &quot;SELECT * FROM MyRView LIMIT 10&quot;
+analysis         g1_id       g1_rsid     g1_chromosome  g1_position  g2_id       g2_rsid     g2_chromosome  g2_position  analysis_id  g1_id:1     g2_id:1     N           encoded_r   r           g1_frequency  g2_frequency
+---------------  ----------  ----------  -------------  -----------  ----------  ----------  -------------  -----------  -----------  ----------  ----------  ----------  ----------  ----------  ------------  ------------
+ldbird analysis  1           H1          H1             1            1           H1          H1             1            1            1           1           4000        2048        1.0         0.181         0.181       
+ldbird analysis  1           H1          H1             1            2           H2          H1             2            1            1           2           4000        1041        0.01660156  0.181         0.14225     
+ldbird analysis  1           H1          H1             1            3           H3          H1             3            1            1           3           4000        1017        -0.0068359  0.181         0.19        
+ldbird analysis  1           H1          H1             1            4           H4          H1             4            1            1           4           4000        1051        0.02636718  0.181         0.01025     
+ldbird analysis  1           H1          H1             1            5           H5          H1             5            1            1           5           4000        1022        -0.0019531  0.181         0.31725     
+ldbird analysis  1           H1          H1             1            6           H6          H1             6            1            1           6           4000        982         -0.0410156  0.181         0.00525     
+ldbird analysis  1           H1          H1             1            7           H7          H1             7            1            1           7           4000        992         -0.03125    0.181         0.14725     
+ldbird analysis  1           H1          H1             1            8           H8          H1             8            1            1           8           4000        1022        -0.0019531  0.181         0.1465      
+ldbird analysis  1           H1          H1             1            9           H9          H1             9            1            1           9           4000        1026        0.00195312  0.181         0.039       
+ldbird analysis  1           H1          H1             1            10          H10         H1             10           1            1           10          4000        1002        -0.0214843  0.181         0.405       
+</code></pre>
+<p>LDBIRD doesn't create this view by itself currently, but a future version might do so. A similar view of the Histogram
+table can also be made.</p>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="../index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="../documentation/getting_started.html">Getting started</a></li>
+						<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="../documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/ldbird/index.html
Index: doc/html/ldbird/index.html
==================================================================
--- doc/html/ldbird/index.html
+++ doc/html/ldbird/index.html
@@ -0,0 +1,93 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+		<meta charset="utf-8">
+		<script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_CHTML">
+		</script>
+		<script type="text/javascript" src="js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="js/datatables.min.js"></script>
+		<script type="text/javascript" src="js/local.js"></script>
+
+		<link href="style/css/datatables.min.css" rel="stylesheet" type="text/css">
+		<link href="style/css/default.css" rel="stylesheet" type="text/css">
+		<title>LDBIRD</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				LDBIRD
+			</div>
+			<div class="header_subtext">
+				Software to compute and histogram pairwise LD metrics
+			</div>
+			<img class="bird" src="style/images/ldbird.png">
+		</div>
+
+<section class="main_text">
+<div id="overview">
+<h3>Introduction</h3>
+<p>LDBIRD is a command-line program for computing LD metrics between all pairs of variants in its input files.</p>
+<p>In working on the paper described below, I needed a way to quickly assess the distribution of between-chromosome LD in
+<em>P.falciparum</em> populations - as well as finding individual pairs of variants with outlying LD. Thus LDBIRD was born.
+The key features LDBIRD has are:</p>
+<ul>
+<li>It computes a histogram of LD values across pairs of variants as well as identifying individual pairs with strong LD.</li>
+<li>It handles haploid genotypes (as well as diploid genotypes, and haploid genotypes encoded as if they were diploid).</li>
+<li>It accepts a variety of different genotype file formats (a subset of those accepted by <a
+  href="https://www.well.ox.ac.uk/~gav/qctool">QCTOOL</a>) and has helpful options for filtering samples and variants.</li>
+<li>Its output format (in a <a href="https://www.sqlite.org">sqlite</a> db) is reasonably compact and readibly post-processable.</li>
+<li>It's reasonably fast (given what it does).</li>
+</ul>
+<p>For an introduction to running LDBIRD, please see the <a href="documentation/getting_started.html">getting
+started</a> page.</p>
+<h4>How fast is LDBIRD?</h4>
+<p>LDBIRD is likely not the fastest way you can compute LD. It limits itself to loading variants one (or rather two) at a
+time, and thus its algorithm is quadratic in the number of variants. If LDBIRD doesn't meet your needs, other ways to
+compute LD are to use <a href="https://www.cog-genomics.org/plink/2.0/">plink</a> or <a
+href="http://www.christianbenner.com/">LDStore</a> - or possibly <a
+href="https://tskit.dev/tskit/docs/stable/">tskit</a>.</p>
+<h3>Obtaining LDBIRD</h3>
+<p>LDBIRD is currently included as part of the <a href="https://code.enkre.net/qctool">QCTOOL
+package</a>, which is currently hosted at <a href="https://code.enkre.net">code.enkre.net</a>. See
+the <a href="documentation/download.html">download page</a> for full details on obtaining
+and installing LDBIRD.</p>
+<h3>References</h3>
+<p>LDBIRD was originally developed for a study of human and malaria parasite variation in samples collected for <a
+href="https://www.malariagen.net/projects/consortial-project-1">MalariaGEN Consortial Project 1</a>. If you use LDBIRD
+in published work, please cite the following preprint (or its published equivalent):</p>
+<div class="citation" style="padding-left: 20px; padding-right: 20px; font-family:Palatino">
+<p>"<strong>The protective effect of sickle cell haemoglobin against severe malaria depends on parasite genotype</strong>",
+bioRxiv <a href="https://doi.org/10.1101/2021.03.30.437659">https://doi.org/10.1101/2021.03.30.437659</a> <br>
+<small>Gavin Band, Ellen M. Leffler, Muminatou Jallow, Fatoumatta Sisay-Joof, Carolyne M. Ndila, Alexander W. Macharia,
+    Christina Hubbart, Anna E. Jeffreys, Kate Rowlands, Thuy Nguyen, Sonia M. Goncalves, Cristina V. Ariani,
+    Jim Stalker, Richard D. Pearson, Roberto Amato, Eleanor Drury, Giorgio Sirugo, Umberto d'Alessandro,
+    Kalifa A. Bojang, Kevin Marsh, Norbert N.P. Peshu, David J. Conway,
+    Thomas N. Williams, Kirk A. Rockett, Dominic P. Kwiatkowski
+</small></p>
+</div>
+<h3>Contact</h3>
+<p>For more information or questions, please contact me at <code>gavin [dot] band (at) well.ox.ac.uk</code>.</p>
+</div>
+</section>
+		<nav class="button_bar">
+			<div>
+				<div class="nav_button" name="overview">
+					<a href="index.html">overview</a>
+				</div>
+				<div class="nav_button" name="documentation">
+					documentation
+					<ul class="menu">
+						<li><a href="documentation/getting_started.html">Getting started</a></li>
+						<li><a href="documentation/alphabetical_options.html">List of options</a></li>
+					</ul>
+				</div>
+				<div class="nav_button" name="download">
+					<a href="documentation/download.html">download</a>
+				</div>
+			</div>
+		</nav>
+
+	</body>
+</html>

ADDED   doc/html/ldbird/js/datatables.min.js
Index: doc/html/ldbird/js/datatables.min.js
==================================================================
--- doc/html/ldbird/js/datatables.min.js
+++ doc/html/ldbird/js/datatables.min.js
@@ -0,0 +1,178 @@
+/*
+ * This combined file was created by the DataTables downloader builder:
+ *   https://datatables.net/download
+ *
+ * To rebuild or modify this file with the latest versions of the included
+ * software please visit:
+ *   https://datatables.net/download/#dt/dt-1.10.16
+ *
+ * Included libraries:
+ *   DataTables 1.10.16
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+
+

ADDED   doc/html/ldbird/js/jquery-3.2.1.min.js
Index: doc/html/ldbird/js/jquery-3.2.1.min.js
==================================================================
--- doc/html/ldbird/js/jquery-3.2.1.min.js
+++ doc/html/ldbird/js/jquery-3.2.1.min.js
@@ -0,0 +1,4 @@
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ADDED   doc/html/ldbird/js/local.js
Index: doc/html/ldbird/js/local.js
==================================================================
--- doc/html/ldbird/js/local.js
+++ doc/html/ldbird/js/local.js
@@ -0,0 +1,12 @@
+$(document).ready(
+	function() {
+		$( '.nav_button' ).hover(
+			function( elt ) {
+				$(elt.currentTarget).addClass( "open" ) ;
+			},
+			function( elt ) {
+				$(elt.currentTarget).removeClass( "open" ) ;
+			}
+		)
+	}
+) ;

ADDED   doc/html/ldbird/resources/options.json
Index: doc/html/ldbird/resources/options.json
==================================================================
--- doc/html/ldbird/resources/options.json
+++ doc/html/ldbird/resources/options.json
@@ -0,0 +1,288 @@
+{
+  "-analysis-chunk": {
+    "group": "",
+    "description": "Specify a name denoting the current genomic region or chunk on which this is run.  This is intended for use in parallel environments.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "NA" ]
+  },
+  "-analysis-id": {
+    "group": "",
+    "description": "Specify an integer ID for the current analysis.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-analysis-name": {
+    "group": "",
+    "description": "Specify a name to label results from this analysis with.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "qctool analysis" ]
+  },
+  "-assume-haploid": {
+    "group": "",
+    "description": "Convert all data to haploid calls.  This converts homozygous calls to haploid calls, and treats any heterozygous calls as missing.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-debug": {
+    "group": "",
+    "description": "Output debugging information.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-details": {
+    "group": "",
+    "description": "Output counts and a Fisher's exact test P-value. Currently only supported if genotypes are haploid.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 0,
+    "default": []
+  },
+  "-excl-samples": {
+    "group": "",
+    "description": "Filter out samples whose sample ID lies in the given file.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-excl-samples-where": {
+    "group": "",
+    "description": "Exclude samples by specifying conditions on the values of columns in the sample file.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-g1": {
+    "group": "",
+    "description": "Path to first genotype file.The given filename may contain the wildcard character '#', which expands to match aone- or two-character chromosome identifier.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 1,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-g1-incl-range": {
+    "group": "",
+    "description": "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-g1-incl-rsids": {
+    "group": "",
+    "description": "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-g2": {
+    "group": "",
+    "description": "Path to second genotype file.  If not given the first genotype file will be used.The given filename may contain the wildcard character '#', which expands to match aone- or two-character chromosome identifier.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-g2-incl-range": {
+    "group": "",
+    "description": "Specify a range of SNPs (or comma-separated list of ranges of SNPs) to operate on. Each range should be in the format CC:xxxx-yyyy where CC is the chromosome and xxxx and yyyy are the start and end coordinates, or just xxxx-yyyy which matches that range from all chromosomes. You can also omit either of xxxx or yyyy to get all SNPs from the start or to the end of a chromosome.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-g2-incl-rsids": {
+    "group": "",
+    "description": "Exclude all SNPs whose RSID is not in the given file(s) from the analysis.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": "untilNextOption",
+    "default": []
+  },
+  "-incl-samples": {
+    "group": "",
+    "description": "Filter out samples whose sample ID does not lie in the given file(s).",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-incl-samples-where": {
+    "group": "",
+    "description": "Include samples by specifying conditions on the values of columns in the sample file.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 100
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-min-N": {
+    "group": "",
+    "description": "Do not compute results where the total number of pairwise non-missing genotypes is below this threshold.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0" ]
+  },
+  "-min-N-propn": {
+    "group": "",
+    "description": "Ignore (do not compute or output) results where the propn of pairwise non-missing genotypes is below this threshold.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0" ]
+  },
+  "-min-distance": {
+    "group": "",
+    "description": "Ignore (do not compute or output) results where the variants are on the same chromosome and closer than this physical distance.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0" ]
+  },
+  "-min-maf": {
+    "group": "",
+    "description": "Do not compute correlation results where the maf of either variant is lower than this threshold.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0" ]
+  },
+  "-min-r2": {
+    "group": "",
+    "description": "Do not output results where r^2 is lower than this threshold.  (These values are still computed and contribute to the histogram.)",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0.05" ]
+  },
+  "-o": {
+    "group": "",
+    "description": "Output file",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 1,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-prior-weight": {
+    "group": "",
+    "description": "Specify a prior weight for samples.   This augments data with one of each of the four possible haploid genotype combinations  for each pairwise comparison, with the total weight given. For example, a value of 1 indicates each haplotype is given 1/4 weight.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0" ]
+  },
+  "-s": {
+    "group": "",
+    "description": "Path of sample file",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 1,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": []
+  },
+  "-table-prefix": {
+    "group": "",
+    "description": "Specify a prefix to add to tables.  They will be called <prefix>Frequency and <prefix>R.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "" ]
+  },
+  "-threshold": {
+    "group": "",
+    "description": "The threshold to apply to genotype probabilities, if necessary, to make calls.",
+    "is_required": 0,
+    "multiplicity": {
+      "min": 0,
+      "max": 1
+    },
+    "values_per_use": 1,
+    "default": [ "0.9" ]
+  }
+}

ADDED   doc/html/ldbird/style/css/datatables.min.css
Index: doc/html/ldbird/style/css/datatables.min.css
==================================================================
--- doc/html/ldbird/style/css/datatables.min.css
+++ doc/html/ldbird/style/css/datatables.min.css
@@ -0,0 +1,15 @@
+/*
+ * This combined file was created by the DataTables downloader builder:
+ *   https://datatables.net/download
+ *
+ * To rebuild or modify this file with the latest versions of the included
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+ *   https://datatables.net/download/#dt/dt-1.10.16
+ *
+ * Included libraries:
+ *   DataTables 1.10.16
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tr:hover.selected>.sorting_3,table.dataTable.order-column.hover tbody tr:hover.selected>.sorting_3{background-color:#a5b2cb}table.dataTable.no-footer{border-bottom:1px solid #111}table.dataTable.nowrap th,table.dataTable.nowrap td{white-space:nowrap}table.dataTable.compact thead th,table.dataTable.compact thead td{padding:4px 17px 4px 4px}table.dataTable.compact tfoot th,table.dataTable.compact tfoot td{padding:4px}table.dataTable.compact tbody th,table.dataTable.compact tbody td{padding:4px}table.dataTable th.dt-left,table.dataTable td.dt-left{text-align:left}table.dataTable th.dt-center,table.dataTable td.dt-center,table.dataTable td.dataTables_empty{text-align:center}table.dataTable th.dt-right,table.dataTable td.dt-right{text-align:right}table.dataTable th.dt-justify,table.dataTable td.dt-justify{text-align:justify}table.dataTable th.dt-nowrap,table.dataTable td.dt-nowrap{white-space:nowrap}table.dataTable thead th.dt-head-left,table.dataTable thead td.dt-head-left,table.dataTable tfoot th.dt-head-left,table.dataTable tfoot td.dt-head-left{text-align:left}table.dataTable thead th.dt-head-center,table.dataTable thead td.dt-head-center,table.dataTable tfoot th.dt-head-center,table.dataTable tfoot td.dt-head-center{text-align:center}table.dataTable thead th.dt-head-right,table.dataTable thead td.dt-head-right,table.dataTable tfoot th.dt-head-right,table.dataTable tfoot td.dt-head-right{text-align:right}table.dataTable thead th.dt-head-justify,table.dataTable thead td.dt-head-justify,table.dataTable tfoot th.dt-head-justify,table.dataTable tfoot td.dt-head-justify{text-align:justify}table.dataTable thead th.dt-head-nowrap,table.dataTable thead td.dt-head-nowrap,table.dataTable tfoot th.dt-head-nowrap,table.dataTable tfoot td.dt-head-nowrap{white-space:nowrap}table.dataTable tbody th.dt-body-left,table.dataTable tbody td.dt-body-left{text-align:left}table.dataTable tbody th.dt-body-center,table.dataTable tbody td.dt-body-center{text-align:center}table.dataTable tbody th.dt-body-right,table.dataTable tbody td.dt-body-right{text-align:right}table.dataTable tbody th.dt-body-justify,table.dataTable tbody td.dt-body-justify{text-align:justify}table.dataTable tbody th.dt-body-nowrap,table.dataTable tbody td.dt-body-nowrap{white-space:nowrap}table.dataTable,table.dataTable th,table.dataTable td{box-sizing:content-box}.dataTables_wrapper{position:relative;clear:both;*zoom:1;zoom:1}.dataTables_wrapper .dataTables_length{float:left}.dataTables_wrapper .dataTables_filter{float:right;text-align:right}.dataTables_wrapper .dataTables_filter input{margin-left:0.5em}.dataTables_wrapper .dataTables_info{clear:both;float:left;padding-top:0.755em}.dataTables_wrapper .dataTables_paginate{float:right;text-align:right;padding-top:0.25em}.dataTables_wrapper .dataTables_paginate .paginate_button{box-sizing:border-box;display:inline-block;min-width:1.5em;padding:0.5em 1em;margin-left:2px;text-align:center;text-decoration:none !important;cursor:pointer;*cursor:hand;color:#333 !important;border:1px solid transparent;border-radius:2px}.dataTables_wrapper .dataTables_paginate .paginate_button.current,.dataTables_wrapper .dataTables_paginate .paginate_button.current:hover{color:#333 !important;border:1px solid #979797;background-color:white;background:-webkit-gradient(linear, left top, left bottom, color-stop(0%, #fff), color-stop(100%, #dcdcdc));background:-webkit-linear-gradient(top, #fff 0%, #dcdcdc 100%);background:-moz-linear-gradient(top, #fff 0%, #dcdcdc 100%);background:-ms-linear-gradient(top, #fff 0%, #dcdcdc 100%);background:-o-linear-gradient(top, #fff 0%, #dcdcdc 100%);background:linear-gradient(to bottom, #fff 0%, #dcdcdc 100%)}.dataTables_wrapper .dataTables_paginate .paginate_button.disabled,.dataTables_wrapper .dataTables_paginate .paginate_button.disabled:hover,.dataTables_wrapper .dataTables_paginate .paginate_button.disabled:active{cursor:default;color:#666 !important;border:1px solid transparent;background:transparent;box-shadow:none}.dataTables_wrapper .dataTables_paginate .paginate_button:hover{color:white !important;border:1px solid #111;background-color:#585858;background:-webkit-gradient(linear, left top, left bottom, color-stop(0%, #585858), color-stop(100%, #111));background:-webkit-linear-gradient(top, #585858 0%, #111 100%);background:-moz-linear-gradient(top, #585858 0%, #111 100%);background:-ms-linear-gradient(top, #585858 0%, #111 100%);background:-o-linear-gradient(top, #585858 0%, #111 100%);background:linear-gradient(to bottom, #585858 0%, #111 100%)}.dataTables_wrapper .dataTables_paginate .paginate_button:active{outline:none;background-color:#2b2b2b;background:-webkit-gradient(linear, left top, left bottom, color-stop(0%, #2b2b2b), color-stop(100%, #0c0c0c));background:-webkit-linear-gradient(top, #2b2b2b 0%, #0c0c0c 100%);background:-moz-linear-gradient(top, #2b2b2b 0%, #0c0c0c 100%);background:-ms-linear-gradient(top, #2b2b2b 0%, #0c0c0c 100%);background:-o-linear-gradient(top, #2b2b2b 0%, #0c0c0c 100%);background:linear-gradient(to bottom, #2b2b2b 0%, #0c0c0c 100%);box-shadow:inset 0 0 3px #111}.dataTables_wrapper .dataTables_paginate .ellipsis{padding:0 1em}.dataTables_wrapper .dataTables_processing{position:absolute;top:50%;left:50%;width:100%;height:40px;margin-left:-50%;margin-top:-25px;padding-top:20px;text-align:center;font-size:1.2em;background-color:white;background:-webkit-gradient(linear, left top, right top, color-stop(0%, rgba(255,255,255,0)), color-stop(25%, rgba(255,255,255,0.9)), color-stop(75%, rgba(255,255,255,0.9)), color-stop(100%, rgba(255,255,255,0)));background:-webkit-linear-gradient(left, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%);background:-moz-linear-gradient(left, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%);background:-ms-linear-gradient(left, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%);background:-o-linear-gradient(left, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%);background:linear-gradient(to right, rgba(255,255,255,0) 0%, rgba(255,255,255,0.9) 25%, rgba(255,255,255,0.9) 75%, rgba(255,255,255,0) 100%)}.dataTables_wrapper .dataTables_length,.dataTables_wrapper .dataTables_filter,.dataTables_wrapper .dataTables_info,.dataTables_wrapper .dataTables_processing,.dataTables_wrapper .dataTables_paginate{color:#333}.dataTables_wrapper .dataTables_scroll{clear:both}.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody{*margin-top:-1px;-webkit-overflow-scrolling:touch}.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>thead>tr>th,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>thead>tr>td,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>tbody>tr>th,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>tbody>tr>td{vertical-align:middle}.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>thead>tr>th>div.dataTables_sizing,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>thead>tr>td>div.dataTables_sizing,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>tbody>tr>th>div.dataTables_sizing,.dataTables_wrapper .dataTables_scroll div.dataTables_scrollBody>table>tbody>tr>td>div.dataTables_sizing{height:0;overflow:hidden;margin:0 !important;padding:0 !important}.dataTables_wrapper.no-footer .dataTables_scrollBody{border-bottom:1px solid #111}.dataTables_wrapper.no-footer div.dataTables_scrollHead table.dataTable,.dataTables_wrapper.no-footer div.dataTables_scrollBody>table{border-bottom:none}.dataTables_wrapper:after{visibility:hidden;display:block;content:"";clear:both;height:0}@media screen and (max-width: 767px){.dataTables_wrapper .dataTables_info,.dataTables_wrapper .dataTables_paginate{float:none;text-align:center}.dataTables_wrapper .dataTables_paginate{margin-top:0.5em}}@media screen and (max-width: 640px){.dataTables_wrapper .dataTables_length,.dataTables_wrapper .dataTables_filter{float:none;text-align:center}.dataTables_wrapper .dataTables_filter{margin-top:0.5em}}
+
+

ADDED   doc/html/ldbird/style/css/default.css
Index: doc/html/ldbird/style/css/default.css
==================================================================
--- doc/html/ldbird/style/css/default.css
+++ doc/html/ldbird/style/css/default.css
@@ -0,0 +1,132 @@
+@import "nav.css" ;
+@import "header.css" ;
+@import "table.css" ;
+
+body {
+	position: relative ;
+	width: 1000px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	overflow-y: auto ;
+	padding-bottom: 50px ;
+	font-family: "Palatino" ;
+	font-size: 12pt ;
+	/* border: 1px solid red; */
+}
+
+strong {
+	font-family: sans-serif ;
+}
+
+
+dt {
+	font-weight: bold ;
+	font-style: italic ;
+}
+
+section {
+	width: 800px ;
+	padding-top: 2em ;
+	margin-left: auto ;
+	margin-right: auto ;
+	font-family: serif ;
+	/*border: 1px dotted red ;*/
+}
+
+.main_text .display_diagram {
+	padding-top: 20px ;
+	margin-left: auto ;
+	margin-right: auto ;
+}
+
+.display_diagram_right {
+	padding-top: 0px ;
+	margin-left: 50px ;
+	float: right ;
+}
+
+.main_text .terminal_display {
+	height: 110px ;
+	overflow: auto ;
+	padding: 10px ;
+	margin-top: 10px ;
+	border: 1px dotted black ;
+	background-color: #22AD57 ;
+}
+
+
+
+h1, h2, h3, h4 {
+	font-family: sans-serif ;
+}
+
+.tutorial_header {
+	width: 100% ;
+	margin: 2px ;
+	overflow: auto ;
+}
+
+.tutorial_separator {
+	width: 100% ;
+	margin: 10px ;
+	border-bottom: 2px solid black ;
+}
+.task {
+	width: 100% ;
+	margin: 2px;
+	margin-top: 10px ;
+	overflow: auto ;
+}
+
+.task_name {
+	font-family: sans-serif ;
+	font-weight: bold ;
+	float: left ;
+}
+
+.task_notes {
+	clear: both ;
+	margin-top: 1px ;
+	margin-bottom: 1px ;
+	float: left ;
+	font-family: sans-serif ;
+	font-size: 0.8em;
+	padding: 5px ;
+}
+
+.monospace {
+	font-family: monospace ;
+}
+
+.task_command_line {
+	margin-top: 1px ;
+	margin-bottom: 1px ;
+	padding: 5px ;
+	font-family: monospace ;
+	background-color: #82BD77 ;
+	float: left ;
+	clear: left ;
+}
+
+.smalltext {
+	font-size: 80% ;
+}
+
+.column_definition lh {
+    font-size: 100% ;
+    margin-top: 10px ;
+    margin-bottom: 10px ;
+    font-family: sans-serif ;
+}
+
+pre > code {
+	display: block ;
+	width: 800px;
+	font-size: 10pt ;
+	background-color: #82BD77 ;
+	overflow-x: auto ;
+	overflow-y: auto ;
+	max-height: 20em ;
+	padding: 10px ;
+	padding-top, padding-bottom: 20px ;
+}

ADDED   doc/html/ldbird/style/css/header.css
Index: doc/html/ldbird/style/css/header.css
==================================================================
--- doc/html/ldbird/style/css/header.css
+++ doc/html/ldbird/style/css/header.css
@@ -0,0 +1,47 @@
+.header {
+	position: relative ;
+	height: 37px ;
+	width: 1000px ;
+}
+
+img.header_img {
+	float: left ;
+	padding-left: 10px ;
+	padding-right: 10px ;
+}
+
+img.header_arrow {
+	float: left;
+	clear: left ;
+	padding-left: 80px ;
+}
+
+.header_text {
+	float: left ;
+	padding-left: 10px ;
+	padding-right: 10px ;
+	font-family: Tahoma, Arial, Helvetica, Tahoma, sans-serif;
+	font-size: 40px ;
+}
+
+div.header_subtext {
+	position: absolute ;
+	padding-top: 20px ;
+	left: 0px ;
+	width: 100% ;
+	text-align: center ;
+}
+
+div.header {
+	border-bottom: 1px solid black ;
+	padding-bottom: 2px ;
+	font-family: sans-serif ;
+	font-size: 15px ;
+}
+
+.header .bird {
+	position: absolute ;
+	height: 40px ;
+	top: 3px ;
+	right: 15px ;
+}

ADDED   doc/html/ldbird/style/css/nav.css
Index: doc/html/ldbird/style/css/nav.css
==================================================================
--- doc/html/ldbird/style/css/nav.css
+++ doc/html/ldbird/style/css/nav.css
@@ -0,0 +1,92 @@
+nav {
+	width: 1000px ;
+	position: absolute ;
+	top: 2em;
+	height: 1.5em;
+//	left: 20px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	font-family: helvetica, sans-serif ;
+	font-size: 16pt ;
+	color: #000000;
+	padding-top: 0px ;
+	padding-bottom: 10px ;
+	padding-left: 0px ;
+	margin-top:0px ;
+	margin-bottom:0px ;
+	border-radius: 2px ;
+	/*border: 1px solid black ;*/
+}
+
+nav > div {
+	width: 500px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	//background-color: rgba( 220, 220, 220, 0.95 ) ;
+}
+
+.nav_button {
+	display: inline-block;
+	position: relative;
+	box-sizing: border-box ;
+	//margin-top: 10px ;
+	padding-left: 25px ;
+	padding-right: 25px ;
+	padding-top: 3px ;
+	padding-bottom: 0px ;
+	text-align: left ;
+}
+
+.nav_button.open {
+	background-color: rgba( 51, 176, 254, 0.9 ) ;
+}
+
+.nav_button ul a:hover {
+	background-color: rgba( 51, 176, 254, 0.9 ) ;
+}
+
+.nav_button a {
+	padding-left: 5px ;
+	padding-right: 5px ;
+	display: inline-block ;
+}
+
+.nav_button ul {
+	display:none ;
+	float: left ;
+	clear: both ;
+	box-sizing: border-box;
+	position: absolute ;
+	box-sizing: content-box ;
+	list-style: none;
+	text-align: left ;
+	left: 0px ;
+	min-width: 300px ;
+	background-color: white ;
+	padding: 3px ;
+	margin: 0px ;
+	font-size: 14px ;
+	/*width: 180px ;*/
+	padding-left: 3px ;
+	padding-right: 3px ;
+	background-color: rgba( 220, 220, 220, 0.95 ) ;
+	border-radius: 0px 0px 4px 4px;
+	box-shadow: 4px 4px 4px 0px rgba(0,0,0,0.2);
+}
+
+.nav_button ul a {
+	display: block;
+	width: auto;
+	padding-top: 2px ;
+	padding-bottom: 2px ;
+	padding-left: 15px ;
+}
+
+nav a, nav a:hover, nav a:visited {
+	color: black;
+	text-decoration: none ;
+}
+
+.nav_button.open ul {
+	display:block ;
+}

ADDED   doc/html/ldbird/style/css/table.css
Index: doc/html/ldbird/style/css/table.css
==================================================================
--- doc/html/ldbird/style/css/table.css
+++ doc/html/ldbird/style/css/table.css
@@ -0,0 +1,79 @@
+#download table {
+	text-align: left ;
+	width: 600px ;
+	border: 1px solid black ;
+	background-color: #CCCCCC ;
+	padding: 10px ;
+}
+
+.file_formats, .option_table {
+	table-layout: fixed ;
+	width: 800px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	font-family: helvetica, sans-serif ;
+	border-collapse: collapse ;
+}
+
+.file_formats thead, .option_table thead {
+	font-size: 14px ;
+	text-align: left ;
+	margin-bottom: 2px ;
+	vertical-align: bottom ;
+}
+
+.file_formats tbody, .option_table tbody {
+	font-size: 12px ;
+}
+
+.file_formats tr, .option_table tr {
+	margin-top: 10px ;
+	margin-bottom: 10px ;
+}
+
+tr:nth-child(even) {
+	background: "grey" ;
+}
+
+tr:nth-child(odd) {
+	background: "red" ;
+}
+
+table.dataTable tr.odd { background-color: #eeeeee; }
+
+.file_formats th, .option_table th {
+	padding-top: 3px ;
+	padding-bottom: 3px ;
+	border-bottom: 1px solid black ;
+}
+
+.file_formats td, .option_table td {
+	height: 100% ;
+	vertical-align: top ;
+	padding-top: 20px ;
+	padding-bottom: 20px ;
+}
+
+.file_formats .acronym {
+	width: 150px ;
+}
+
+.file_formats .notes {
+	width: 400px ;
+}
+
+.file_formats .io {
+	width: 50px ;
+}
+
+.file_formats .filetype {
+	width: 150px ;
+}
+
+.option_table .option {
+	width: 200px ;
+}
+
+.option_table .description {
+	width: 500px ;
+}

ADDED   doc/html/qctool/content/documentation/alphabetical_options.content.html
Index: doc/html/qctool/content/documentation/alphabetical_options.content.html
==================================================================
--- doc/html/qctool/content/documentation/alphabetical_options.content.html
+++ doc/html/qctool/content/documentation/alphabetical_options.content.html
@@ -0,0 +1,65 @@
+<section class="main_text">
+	<h2>Table of options</h2>
+	<p>Below is a list of all options supported by QCTOOL. (See also the <a href="../documentation/diagram_of_options.html">diagram of options</a>).</p>
+	<table class="option_table">
+		<colgroup>
+			<col class="option">
+			<col class="description">
+			<col class="default">
+		</colgroup>
+		<thead>
+			<tr>
+				<th>
+					Option
+				</th>
+				<th>
+					Description
+				</th>
+				<th>
+					Default value?
+				</th>
+			</tr>
+		</thead>
+		<tbody>
+		</tbody>
+	</table>
+</section>
+
+<script>
+	$(document).ready(
+		function() {
+			$.getJSON( "../resources/options.json", function( data ) {
+				console.log( 'gotit' ) ;
+				var options = [] ;
+				$.each( data, function( key, value ) {
+					options.push( key ) ;
+					console.log( key ) ;
+				} ) ;
+				
+				options.sort( function(a,b) {
+					return a.toLowerCase().localeCompare( b.toLowerCase() ) ;
+				}) ;
+				
+				for( var i = 0; i < options.length; ++i ) {
+					$(".option_table > tbody").append(
+						'<tr>'
+						+ '<td>' + options[i] + '</td>'
+						+ '<td>' + data[options[i]]['description'] + '</td>'
+						+ '<td>' + ( data[options[i]].length == 0 ? "N/A" : ( "(" + data[options[i]].default.join( ", " ) + ")" ) + '</td>' )
+						+ '</tr>'
+					)
+				}
+				
+				$( ".option_table" ).DataTable(
+					{
+						"paging": false,
+						"language": {
+							"search": "Search command-line options:"
+						}
+					}
+				) ;
+				$('.dataTables_filter').css('float', 'left') ;
+			}) ;
+		}
+	) ;
+</script>

ADDED   doc/html/qctool/content/documentation/changes.content.html
Index: doc/html/qctool/content/documentation/changes.content.html
==================================================================
--- doc/html/qctool/content/documentation/changes.content.html
+++ doc/html/qctool/content/documentation/changes.content.html
@@ -0,0 +1,62 @@
+<section class="main_text" markdown="1">
+### Change history ###
+
+**Changes in v2.2.0**:
+
+* <a href="https://www.well.ox.ac.uk/~gav/hptest">HPTEST</a> and <a
+  href="https://www.well.ox.ac.uk/~gav/ldbird">LDBIRD</a> have been added to the repository. See
+  their respective pages for documentation.
+
+* QCTOOL: added <code>-[in|ex]cl-ranges</code>, which behave like <code>-[in|ex]cl-range</code> but
+  read ranges from a file.
+
+* Fix compilation issues: <a
+  href="https://enkre.net/cgi-bin/code/qctool/tktview?name=9c01ec9ee1">9c01ec9ee1</a> and <a
+  href="https://enkre.net/cgi-bin/code/qctool/tktview?name=a31af45e24">a31af45e24</a>.
+
+**Changes in v2.0.8**:
+
+* Permit GP field without GT field in VCF format, fixing ticket <a href="https://code.enkre.net/qctool/tktview?name=4d88dff8cc">4d88dff8cc</a>.
+* ``qctool``: always get sample identifiers from input file when they are available and no ``-s`` option is supplied.
+  In BGEN format, default is now to write sample identifiers whenever possible unless
+  ``-bgen-omit-sample-identifier-block`` is specified. Fixes ticket <a
+  href="https://code.enkre.net/qctool/info/b952a6be">b952a6be</a>.
+* ``inthinnerator``: make sure column specified by ``-rank-column`` is output as a `FLOAT` in sqlite output.
+
+**Changes in v2.0.7**: 
+
+* Use (and expect) semicolons not commas to separate VCF variant IDs.
+* Solve compilation failure issue on some versions of gcc.
+
+**Changes in v2.0.6**:
+
+* ``qctool``: Fix bug in ``info`` metric computation when there is missing data.
+* ``inthinnerator``: output all columns from the input file.
+
+**Changes in v2.0.5**
+
+* ``qctool``: fix bug when using ``-flip-to-match-cohort1`` and/or strand alignment with multiple sources.
+* ``inthinnerator``: use ``-o`` not ``-odb`` and add ``-compare-variants-by``.
+* ``inthinnerator``: (re-)implement nearest gene-finding algorithm.
+
+**Changes in v2.0.1**:
+
+* fix bug when reading IMPUTE haplotypes format data.
+
+**Changes in v2.0 series**:
+
+QCTOOL v2 differs in several important ways from the v1 release series. Some important changes in QCTOOL v2 relative to
+v1 are:
+
+* *Support for more file formats*: QCTOOL v2 supports a diverse array of common file formats - 
+	see the <a href="documentation/genotype_file_formats.html">file formats page</a> for more information.
+* *Support for more features*: QCTOOL v2 has a bunch of features not found in v1 - for example it
+	can <a href="documentation/examples/computing_ld.html">compute LD metrics</a>,
+	<a href="documentation/examples/altering_id_data.html">apply strand alignments</a>,
+	<a href="documentation/examples/annotating.html">annotate variants</a> with information from external sources, and more.
+* *Removal of on-the-fly filtering options*: The options for direct filtering based on summary statistics (<code>-maf</code>, <code>-hwe</code>, <code>-snp-missing-rate</code>, etc.) have been removed. Instead, it's expected you will inspect summary statistics and manually create lists of variants and/or samples for removal, using the <code>-incl-</code> and <code>-excl-</code> options
+	to exclude them in a seperate QCTOOL run <a href="documentation/examples/filtering_samples.html">as described here</a> and <a href="documentation/examples/filtering_variants.html">here</a>. (That's often what you want anyway, since it's useful to have a record of what you've removed.)
+* *Treatment of chromosomes*: QCTOOL v1 always converted chromosomes to a two-digit form (<code>01</code>,<code>02</code>, ...) and would treat chromosomes as missing if they were not of specific forms pertinent to human datasets. QCTOOL v2 instead allows arbitrary strings to be used as chromosomes. This change brings QCTOOL into line with other tools, e.g. those that use contig identifiers from a reference genome build. However, this also breaks some workflows that would previously have worked, namely when matching between datasets that have differently encoded chromosome names. A possible workaround is to <a href="documentation/examples/altering_id_data.html">use the <code>-map-id-data</code> option</a> to replace chromosome identifiers on the fly during analysis.
+* *Changes to output of summary stats*: QCTOOL performs several types of per-variant summary computation, that are specified using options like <code>-snp-stats</code> and the <code>-annotate-</code> options. When outputting results, all output is sent to a single output file that is specified using the <code>-osnp</code> option. This file will automatically inherit columns from each requested computation. Similarly, all per-sample summary computations are output the file specified by <code>-osample</code>.
+
+</section>

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+<section class="main_text">
+	<h2>Diagram of options</h2>
+	<p>Data flows through qctool in a fixed pipeline according to the schema below.
+		Relevant options for each pipeline stage are noted.  (See also the <a href="../documentation/alphabetical_options.html">alphabetical list of options</a>).</p>
+	<div class="display_diagram">
+		<object data="../style/images/qctool_cheatsheet.svg" style="position: relative; left: -100px; width: 1000px; margin-left:auto; margin-right: auto" width="1000" type="image/svg+xml" align="center">
+			</object>
+	</div>
+	<p>See also the <a href="alphabetical_options.html">alphabetical list of options</a>.</p>
+</section>

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==================================================================
--- doc/html/qctool/content/documentation/download.content.html
+++ doc/html/qctool/content/documentation/download.content.html
@@ -0,0 +1,94 @@
+<section class="main_text">
+	<h2>Obtaining QCTOOL</h2>
+		<p>
+
+			QCTOOL is available either as binaries or as source code. The recommended approach is to download and compile the QCTOOL
+			source code on the machine(s) you will be working on. However, for convenience a small number of precompiled binary packages are
+			provided below. These provided as-is and will not work on all platforms; if a suitable version is not available please download
+			the QCTOOL source code and compile instead.
+			
+		</p>
+		<table class="download">
+			<colgroup>
+				<col span="1" style="width: 15%;">
+				<col span="1" style="width: 25%;">
+				<col span="1" style="width: 60%;">
+			</colgroup>
+			<thead>
+				<tr><th>Version</th>
+				<th>Platform</th>
+				<th>file</th></tr>
+			</thead>
+			<tbody>
+                <tr><td>v2.2.1<sup>*</sup></td><td>Mac OS X (Apple)</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.2.1-osx-m1.tgz">qctool_v2.2.1-osx-m1.tgz</a></td></tr>
+                <tr><td>v2.2.0<sup>*</sup></td><td>Mac OS X (Intel)</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.2.0-osx.tgz">qctool_v2.2.0-osx.tgz</a></td></tr>
+                <tr><td>v2.2.0<sup>*</sup></td><td>CentOS Linux 7.8</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.2.0-CentOS_Linux7.8.2003-x86_64.tgz">qctool_v2.2.0-CentOS_Linux7.8.2003-x86_64.tgz</a></td></tr>
+                <tr><td>v2.0.8</td><td>Mac OS X</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.0.8-osx.tgz">qctool_v2.0.8-osx.tgz</a></td></tr>
+                <tr><td>v2.0.8</td><td>CentOS Linux 7.6</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.0.8-CentOS_Linux7.6.1810-x86_64.tgz">qctool_v2.0.8-CentOS_Linux7.6.1810-x86_64.tgz</a></td></tr>
+                <tr><td>v2.2.0</td><td>Mac OS X</td><td><a href="https://www.chg.ox.ac.uk/~gav/resources/qctool_v2.2.0-osx.tgz">qctool_v2.2.0-osx.tgz</a></td></tr>
+                <tr><td>v2.2.0</td><td>CentOS Linux 7.8</td><td><a href="https://www.chg.ox.ac.uk/~gav/resources/qctool_v2.2.0-CentOS_Linux7.8.2003-x86_64.tgz">qctool_v2.2.0-CentOS_Linux7.8.2003-x86_64.tgz</a></td></tr>
+                <tr><td>v2.2.5</td><td>Mac OS X, Apple silicon</td><td><a href="https://www.chg.ox.ac.uk/~gav/resources/qctool_v2.2.5-osx-arm64.tgz">qctool_v2.2.5-osx-arm64.tgz</a></td></tr>
+                <tr><td>v2.2.5</td><td>CentOS Linux 7.9</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.2.5-CentOS_Linux7.9-x86_64.tgz">qctool_v2.2.5-CentOS_Linux7.9-x86_64.tgz</a></td></tr>
+			</tbody>
+		</table>
+		<small><sup>*</sup> This is the recommended version; older versions are unsupported but may still appear here for posterity.</small>
+		<h3>
+			Downloading source
+		</h3>
+		<p>
+			The source code to qctool is available as a <a href="https://fossil-scm.org">fossil</a> repository
+			at <a href="https://code.enkre.net/qctool">https://code.enkre.net/qctool</a>.
+			To obtain source code, use the fossil command-line client, or alternatively download a
+			tarball from this table.  (Note that this currently generates a tarball on the fly, which may take a while).
+		</p>
+		<table class="download">
+			<colgroup>
+				<col span="1" style="width: 40%;">
+				<col span="1" style="width: 60%;">
+			</colgroup>
+			<thead>
+				<tr><th>Version</th><th>file</th>
+			</thead>
+			<tbody>
+				<tr><td>release<sup>*</sup></td><td><a href="https://code.enkre.net/qctool/tarball/release/qctool.tgz">https://code.enkre.net/qctool/tarball/release/qctool.tgz</a></td>
+				<tr><td>development</td><td><a href="https://code.enkre.net/qctool/zip/tarball/qctool.tgz">https://code.enkre.net/qctool/tarball/trunk/qctool.tgz</a></td>
+			</tbody>
+		</table>
+		<small><sup>*</sup> This is the recommended version; only use the development version if you want to try recently implemented features.</small>
+		<h3>
+			Versioning scheme
+		</h3>
+		<p>
+			As of version 2.1, QCTOOL will follow a versioning scheme whereby odd minor numbers (2.1.x etc.) represent
+			development work while even numbers (2.2.x etc.) represent release versions.
+			The current latest release versions are 2.2 version.
+		</p>
+		<h3>
+			Compiling
+		</h3>
+		<p>
+			Having downloaded the source code (and extracted it if necessary), a basic compilation sequence would then be:
+		</p>
+<pre>
+$ cd qctool
+$ ./waf configure
+$ ./waf
+</pre>
+		<p>
+			If all is successful, this produces an executable
+			<code>./build/release/qctool_v&lt;version&gt;</code>
+		</p>
+		</div>
+	<p>
+		You can check qctool is working by running it:
+	</p>
+	<pre>
+$ ./build/release/qctool_v&lt;version&gt; -help
+</pre>
+	<p>which should print out a list of options.</p>
+	<h3>Further information</h3>
+	<p>
+		The <a href="https://code.enkre.net/qctool/wiki?name=Home">QCTOOL wiki</a> contains further information
+		which may be useful if you are unable to compile QCTOOL or need to tweak compilation for specific platforms.
+	</p>
+</section>

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+<section class="main_text">
+	<h2>Manipulating the sample file</h2>
+		<div class="task">
+			<div class="task_name">
+				Add genotype dosages for given variants to the sample file
+			</div>
+			<div class="task_notes">
+				The <code>-condition-on</code> option can be used to extract genotype dosages for specific given variants
+				and place them as columns in the sample file.  E.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example_#.gen -s example.sample -os example.sample -condition-on rs1234
+			</div>
+			<div class="task_notes">
+				This adds a column with name <span class="monospace">rs1234:additive_dosage</span>, containing the
+				additive dosage from the SNP.  You can also select SNPs by position:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example_#.gen -s example.sample -os example.sample -condition-on pos~03:10001
+			</div>
+			<div class="task_notes">
+				It is also possible to select dominant, recessive, or heterozygote dosages from the SNP.  For example,
+				to select additive and heterozygote dosages:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example_#.gen 
+				-s example.sample 
+				-os example.sample 
+				-condition-on "rs1234(add|het)"
+			</div>
+			<div class="task_notes">
+				<p>
+				<b>Note:</b> as shown above, it is sometimes necessary to place the argument in quotation marks
+				to avoid problems with the system shell.
+			</p>
+				<p>
+					The full syntax for this option is: <code>-condition-on [selector~]value[(dosage1[|dosage2...])]</code>
+					where <code>selector</code> is either "rsid", "snpid", or "position" or "pos", <code>value</code>
+					is a string specifying the ID or position of the required variant, and dosage can be
+					<code>add</code>, <code>dom</code>, <code>rec</code>, <code>het</code>.
+					The value <code>gen</code> adds both additive and heterozygote dosages.
+				</p>
+				<p>
+					Note: these options behave in a similar way to the <code>-condition_on</code> option
+					found in <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html">SNPTEST</a>,
+					but may be preferable because they can write the data into the sample file directly where it can be
+					later inspected.
+				</p>
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Quantile-normalise columns of the sample file
+			</div>
+			<div class="task_notes">
+				The <code>-quantile-normalise</code> option takes a numerical column in the sample file,
+				and adds a new column reflecting the same data after mapping empirical quantiles to those of a 
+				standard gaussian distribution.  E.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -os example.sample -quantile-normalise column1
+			</div>
+			<div class="task_notes">
+				<p>
+					This adds a column with name <code>column1:quantile-normalised</code> to the sample file.
+					The specified columns must be continuous, i.e. of type 'P' or 'C'.
+					(Note that even though the SNPs are not used here, currently you must still specify the -g option.)
+				</p>
+				<p>
+					The screen output (and log file) will contain details of the column values before and after normalisation.
+				</p>
+				<p>
+					<b>Technical note</b>: specifically, suppose there are <em>N</em> samples.  This option
+					first computes the quantiles <em>q<sub>j</sub> = &Phi;<sup>-1</sup>(j/N+1)</em> for each <em>j=1,...,N</em>,
+					where <em>&Phi;</em> is the cumulative distribution function of a standard Gaussian.
+					The normalised value for sample <em>i</em> is then obtained as <em>n<sub>i</sub> = q<sub>r(i)</sub></em>
+						where <em>r(i)</em> is the rank of the sample among the values of the given column.
+						If several samples are tied, we instead set <em>n<sub>i</sub></em> to the average of q<sub>r(i)</sub>
+						across all samples with the same column value.  This makes the normalised value well-defined
+						(i.e. independent of the ranking of these samples), and means that samples with
+						identical values of the input column will also have identical values
+						in the computed quantile-normalised column.
+				</p>
+				<p>
+					Note that <code>-quantile-normalise</code> can be given a list of columns:
+				</p>
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -os example.sample -quantile-normalise column1 column2...
+			</div>
+			<div class="task_notes">
+				This produces a set of quantile-normalised columns, one for each specified input column.
+			</div>
+		</div>
+	</div>
+</section>

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+<section class="main_text">
+	<h2>Altering variant identifying data</h2>
+		<div class="task">
+			<div class="task_name">
+				Filling in missing chromosome information
+			</div>
+			<div class="task_notes">
+				The <code>-assume-chromosome</code> option fills in any missing chromosome information in input data
+				with the specified value.  E.g.:
+			</div>
+			
+			<div class="task_command_line">
+				$ qctool -g &lt;input file&gt; -og output.bgen -assume-chromosome &lt;chromosome&gt;
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Updating identifying data
+			</div>
+			<div class="task_notes">
+				The <code>-map-id-data</code> option can be used to update the identifying data for each variant
+				with a new set of data. E.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g &lt;input file(s)&gt; -og output.bgen -map-id-data &lt;map file&gt; [+other options]
+			</div>
+			<div class="task_notes">
+				<p>Ffor example, this might be useful when updating files to match a new genome build.</p>
+				<p>The "map" file given to <code>-map-id-data</code> must be a text file
+				with twelve named columns, in the following order: the current SNPID, rsid, chromosome, position, first and second alleles,
+				followed by the desired updated SNPID, rsid, chromosome, position and alleles.  The first line is treated as column names
+				(currently it doesn't matter what these are called.)  Variants not in this file are not affected by the mapping, and will
+				be output unchanged.
+			</p>
+			<p>Matching of variants to the map file is controlled by the <code>-compare-variants-by</code>
+				option - see the <a href="sorting.html">page on sorting data</a> for more on this option.</p>
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Aligning alleles
+			</div>
+			<div class="task_notes">
+				<p>
+				The <code>-strand</code> option can be used to update alleles and flip genotype data according
+				to strand information supplied in an external file.  The general format is:
+			</p>
+			</div>
+			<div class="task_command_line">
+				$ qctool -g &lt;input file(s)&gt; -og output.bgen -strand &lt;strand file&gt; [-flip-to-match-allele &lt;column name&gt;]
+			</div>
+			<div class="task_notes">
+				<p>The most common use of this option is to align alleles to match the forward strand of a reference sequence,
+					and to flip genotypes so that the first allele is the reference allele.
+				</p>
+				<p>
+					Strand files should have six columns which must be named as follows:
+					<code>SNPID</code>,
+					<code>rsid</code>,
+					<code>chromosome</code>,
+					<code>position</code>,
+					<code>alleleA</code>,
+					<code>alleleB</code>,
+					<code>strand</code>, plus any additional columns.
+					Strand information is read from the <code>strand</code> column.
+					Alleles at variants where the strand is '+' will be processed unchanged; alleles
+					at variants where the strand is '-' will be complemented (i.e. A&lt;-&gt;T, G&lt;-&gt;C);
+					alleles at variants which have missing strand information - encoded as "?", or "NA", or for variants
+					that are missing from the file - will be omitted from the output.
+				</p>
+				<p>
+					The <code>-compare-variants-by</code> option controls how variants between the genotype data
+					and the strand file.
+					See <a href="sorting.html">the page on sorting</a> for more information.
+				</p>
+				<p>
+					If the <code>-flip-to-match-allele</code> option is given, the strand file must contain a column
+					with the specified name.  Each value in this column should be one of the two alleles of the variant.
+					Alleles and genotypes are then also recoded so that the allele in the specified
+					column is the first allele and the other allele the second allele.
+					Note that the strand alignment is applied first - e.g. if the variant alleles are 'A' and 'G' and the
+					strand is -, <code>-flip-to-match-allele</code> the column should contain 'T' or 'C'.
+				</p>
+			</div>
+		</div>
+	</div>
+</section>

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--- doc/html/qctool/content/documentation/examples/annotating.content.html
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+<section class="main_text">
+	<h2>Computing annotations</h2>
+	<div class="task">
+		<div class="task_name">
+			Annotating with sequence bases
+		</div>
+		<div class="task_notes">
+			The <code>-annotate-sequence</code> option can be used to extract sequence bases from FASTA file(s)
+			and annotate the output file with them.  E.g.:
+		</div>
+		
+		<div class="task_command_line">
+			$ qctool -g &lt;input file&gt; -osnp output.txt -annotate-sequence chr#.fa reference
+		</div>
+		<div class="task_notes">
+			<b>Note</b> Currently, to be used with this option, FASTA files must be split into one file
+			per chromosome; the chromosome is then inferred from the file name (using the chromosomal wildcard character #) as in the command above.  Also,
+			it's assumed that the FASTA file starts at base pair 1 so that bases may be looked up in the file.
+			I have used this to annotate alleles from the human reference sequence
+			(e.g. <a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/">this one</a>)
+			or ancestral sequence (e.g. <a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/">this one</a>).
+		</div>
+		<div class="task_name">
+			Annotating with flanking sequence
+		</div>
+		<div class="task_notes">
+			When using <code>-annotate-sequence</code>, the <code>-flanking</code> option tells QCTOOL to additionally annotate output with flanking sequence
+			from FASTA files.  For example:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g &lt;input file&gt; -osnp output.txt -annotate-sequence chr#.fa reference -flanking 200 200
+		</div>
+		<div class="task_notes">
+			This will output the 200bp from the FASTA file preceding and following each variant, and the
+			bases covered by the variant's alleles.
+		</div>
+	</div>
+	<div class="task">
+		<div class="task_name">
+			Annotating with genetic map information
+		</div>
+		<div class="task_notes">
+			The <code>-annotate-genetic-map</code> option can be used to output genetic (recombination) map coordinates
+			for each variant, e.g:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g &lt;input file(s)&gt; -annotate-genetic-map genetic_map_chr#.txt -osnp output.txt
+		</div>
+		<div class="task_notes">
+			<p>The genetic map files should be in the 'hapmap' format, i.e. one file per chromosome
+				with three columns specifying position, recombination rate in centimorgans per megabase,
+				and the accumulated recombination map position.  It is expected that genetic map files
+				are split by chromosome, and the chromosome is inferred from the filename.
+				Suitable genetic map files for human build 37 can be found
+				on the <a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#reference">IMPUTE2 website</a>.
+				The output will contain columns <Code>cM_per_Mb</code> and <code>cM_from_start_of_chromosome</code>.
+			</p>
+		</div>
+	</div>
+
+	<div class="task">
+		<div class="task_name">
+			Interval annotations
+		</div>
+		<div class="task_notes">
+			The <code>-annotate-bed3</code> and <code>-annotated-bed4</code> options can be used to compute
+			membership of the intervals 
+			in a <a href="https://genome.ucsc.edu/FAQ/FAQformat.html">BED file</a>, or
+			the value(s) assigned to intervals in a bed file, at each input variant:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g &lt;input file(s)&gt; -annotate-bed3 file1.bed -annotated-bed4 file2.bed
+		</div>
+		<div class="task_notes">
+			<p>
+				Output will contain a column with the same name as the BED file (minus the
+				<code>.bed</code> or <code>.bed.gz</code> extension).
+				For <code>-annotate-bed3</code>, this column will contain a 1 if the variant was contained
+				in an interval in the file, or 0 otherwise.  For <code>-annotate-bed4</code>, the column
+				will contain a comma-separated list of values from the fourth column of the BED file,
+				for those intervals which the variant is in.
+			</p>
+			<p>
+				<b>Note:</b> BED files are assumed to contain intervals in 0-based, right-open coordinates, while
+				QCTOOL by convention assumes genotype data is expressed in 1-based coordinates.  QCTOOL handles this
+				internally by adding 1 to the start coordinate of each interval.
+			</p>
+			<p>
+				It's also possible to compute membership of intervals in a set of BED files in the same column.
+				The general syntax is
+				<code>-annotate-bed[3|4] file1.bed[,file2.bed[,...]][+&lt;N&gt;bp]</code>.  
+				This internally concatenates <code>file1.bed</code>, <code>file2.bed</code>, etc. into a single
+				list of intervals.  Further, if the <code>+&lt;N&gt;bp</code> modifier is added, where <em>N</em>
+				is an integer, then all intervals are expanded by <em>N</em> bases to the left and the right
+				before processing.  For example:
+			</p>
+		</div>
+		<div class="task_command_line">
+			$ qctool -g &lt;input file(s)&gt; -annotate-bed4 file1.bed,file2.bed+100bp
+		</div>
+		<div class="task_notes">
+			This command will annotate each variant with the values of all intervals that it lies within 100bp of.
+		</div>
+	</div>
+</section>

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+<section class="main_text">
+	<h2>Basic examples</h2>
+		<div class="tutorial_header">
+
+		This and the other pages in the 'examples' menu show some basic command lines used to carry out common tasks
+		with QCTOOL. For more information see also the <a href="[ROOT]/documentation/alphabetical_options.html">list of
+		options</a> and the <a href="[ROOT]/documentation/diagram_of_options.html">diagram of options</a>."
+
+		</div>
+		<div class="tutorial_separator">
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Run qctool
+			</div>
+			<div class="task_command_line">
+				$ qctool
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				View the program usage page
+			</div>
+			<div class="task_command_line">
+				$ qctool -help | less
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Get a computer-readable list of options
+			</div>
+			<div class="task_command_line">
+				$ qctool -spec
+			</div>
+			<div class="task_notes">
+				<b>Note:</b> output is is JSON format.  This option is used to construct the <a href="../alphabetical_options.html">table of options</a>.
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Capture screen output in log file
+			</div>
+			<div class="task_command_line">
+				$ qctool [other options] -log log.txt
+			</div>
+		</div>
+
+		<div class="task">
+			<div class="task_name">
+				Get some summary information about a genotypes file
+			</div>
+			<div class="task_command_line">
+				$ qctool -g &lt;genotypes file&gt;
+			</div>
+		</div>
+</section>

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+<section class="main_text">
+	<h2>Combining datasets</h2>
+	<div class="task">
+		<div class="task_name">
+			Combining several datasets into a larger one
+		</div>
+		<div class="task_notes">
+			QCTOOL's <code>-g</code> and <code>-s</code> options can be specified several times, with the effect of combining
+			data into one larger dataset.  E.g.:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g cohort1.bgen -s cohort1.sample -g cohort2.bgen -s cohort2.sample -og joined.gen -os joined.sample
+		</div>
+		<div class="task_notes">
+			<p>
+				QCTOOL will produce both a combined genotype file and a combined sample file.
+				The output files
+				will have <em>N<sub>1</sub>+N<sub>2</sub></em> samples, where <em>N<sub>1</sub></em> and <em>N<sub>2</sub></em>
+				are the numbers of samples in the two input datasets, and it will contain all variants that can be matched between
+				the input datasets.
+			</p>
+			<p>
+				QCTOOL attempts to merge the columns of the sample files based on column name and type.
+				Columns are dropped if they have the same name but different types.	 Otherwise, each column
+				in the input sample files appears in the output sample file, possibly with missing values for those cohorts
+				for which that column is not present.
+			</p>
+			<p>
+				QCTOOL attempts to combine data at each variant that is present in all input datasets.  To do this,
+				it makes the assumption that <em>data is sorted uniquely and in the same way in all input datasets</em>.
+				If this is not the case then QCTOOL may be unable to match some variants.  Any variant that does not match
+				between datasets will be omitted from the output.
+			</p>
+			<p>
+
+				QCTOOL processed variant identifiers in the following way: it uses the primary identifier from
+				the first dataset as the overall primary identifier. It also keeps a list of all other identifiers observed
+				across the datasets. (When the input file is a VCF, the first identifier is treated as the primary identifier.
+				When the input is in GEN or BGEN format, the `rsid` column is treated as containing the primary identifier, and
+				alternative identifiers from the `SNPID` column are also processed.). The `-map-id-data` option can also
+				be used to force specific adjustments to these data.
+
+			</p>
+		</div>
+		<div class="task_name">
+			Controlling how variants are matched
+		</div>
+		<div class="task_notes">
+			<p>
+				The <code>-compare-variants-by</code> option can be used to
+				control what fields QCTOOL compares when matching variants.  (The default behaviour is to match variants by the
+				genomic position, alleles, and ID fields).  For example, in the command:
+			</p>
+		</div>
+		<div class="task_command_line">
+			$ qctool -g cohort1.bgen -s cohort1.sample -g cohort2.bgen -s cohort2.sample -og joined.gen -os joined.sample -compare-variants-by position,alleles
+		</div>
+		<div class="task_notes">
+		<p>
+			QCTOOL will match variants by position and alleles (variants will match even if ID fields differ).  
+			As in the example, <code>position</code> (the genomic position) must always be the first field matched on.
+		</p>
+		<p><b>Note:</b> careful use of these options is especially important when datasets contain multiple variants 
+			sharing the same genomic position.  The recommendation is to ensure all datasets are encoded
+			uniformly before combining them.  (See the pages on <a href="sorting.html">sorting</a>,
+			<a href="altering_id_data.html">aligning alleles</a> and <a href="altering_id_data.html">altering ID data</a>
+			for options that can help with this.)
+		</p>
+	</div>
+		<div class="task_name">
+			Allowing for allele mismatches
+		</div>
+		<div class="task_notes">
+		<p>
+			It is sometimes the case that data is sorted in each dataset but that alleles are mixed up.
+			The <code>-match-alleles-to-cohort1</code> option tells QCTOOL to attempt to match data allowing for this
+			type of mismatch:
+		</p>
+	</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -s example.sample -g second_cohort_#.gen -s second_cohort.sample
+			-og joined.gen -os joined.sample -compare-variants-by position,alleles -match-alleles-to-cohort1
+		</div>
+		<div class="task_notes">
+			<p>
+			  Here, if the variant is biallelic and the alleles in the second dataset are the same as those
+				in the first cohort, but coded the other way round (e.g. cohort1 = A/G, cohort2 = G/A), then the
+				alleles and genotypes are flipped accordingly.  No other transformation (e.g. strand flips, or matching multiallelics)
+				is performed by this operation.  Thus, although this option can be convenient, the general recommendation
+				is to arrange each dataset to be encoded and sorted unformly before combining.
+			</p>
+		</div>
+	</div>
+</section>

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+<section class="main_text">
+	<h2>Assessing linkage disequilibrium</h2>
+		<div class="task">
+			<div class="task_name">
+				Computing LD metrics
+			</div>
+			<div class="task_notes">
+				The <code>-compute-ld-with</code> option can be used to compute LD metrics between
+				the genotype data and a seperate set of genotype contained in a second file.  E.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD
+			</div>
+			<div class="task_notes">
+				<p>
+					For each biallelic variant in <code>example.bgen</code>, and each biallelic variant in <code>second.bgen</code>,
+					QCTOOL constructs the pairwise table of non-missing genotypes, uses an EM algorithm to resolve phase
+					of the double heterozygotes, and then outputs the frequency of each haplotype and the <em>D'</em>
+					and <em>r<sup>2</sup></em> statistics.  (Multiallelic variants are currently not handled.)
+			</p>
+			<p>
+				<b>Note</b>: to compute LD, samples are matched between datasets using the primary ID (the first column
+				in the sample files) by default.  To alter this, use the <code>-match-sample-ids</code> option.
+				This is described further on the <a href="merging.html">page on merging datasets</a>.
+			</p>
+			<p>
+				<b>Note</b>:
+				Currently LD output is always to a sqlite database file.  In the above command,
+				results are placed in the file <code>ld.sqlite</code> and in a table called
+				<code>LD</code>; a convenience view, called <code>LDView</code> is also constructed.  The simplest way
+				to view that data is to use the <a href="https://sqlite.org/cli.html">sqlite3 command-line client<a>
+					(which is already installed on most linux systems by default).  E.g. the command:
+				</p>
+			</div>
+				<div class="task_command_line">
+					$ sqlite3 -csv -header ld.sqlite "SELECT * FROM LDView LIMIT 10"
+				</div>
+				<div class="task_notes">
+						Will list the first ten LD records in CSV format.  The file can equally be accessed programmatically,
+						for example using the <a href="https://docs.python.org/2/library/sqlite3.html">sqlite3 module</a> in python, or the <a href="https://cran.r-project.org/web/packages/RSQLite/index.html">RSQLite</a> package in R.
+						We may add flat file support in future.
+				</div>
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Controlling what is output
+			</div>
+			<div class="task_notes">
+				Pairwise LD computation can generate a massive amount of data.  To reduce this the <code>-min-r2</code> and <code>-max-ld-distance</code>
+				options can be used, e.g.
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -min-r2 0.05 -max-ld-distance 1Mb
+			</div>
+			<div class="task_notes">
+				will output results only for variants estimated to have <em>r<sup>2</sup> > 0.05</em>, and within a megabase of each other.
+				For the latter option, you can also specify distances in base pairs (e.g. <code>-max-ld-distance 1000</code>), in kilobases (e.g. <code>-max-ld-distance 1kb</code>),
+				or in megabases as in the example above.
+			</div>
+		
+		<div class="task">
+			<div class="task_name">
+				Adjusting the degree of shrinkage
+			</div>
+			<div class="task_notes">
+					QCTOOL outputs shrinkage estimates of LD by default.
+					Specifically, haplotype frequencies are estimated under a <em>Dirichlet(x,x,x,x)</em> prior,
+					with x=1.25 by default; roughly speaking this is equivalent to adding a quarter of an observation of each of the four haplotypes to the data.
+					Intuitively this corresponds to weak prior assumptions that 1: both variants are polymorphic
+					and 2: there is at least some recombination between them.
+			</div>
+			<div class="task_notes">
+					The <code>-prior-ld-weight</code> option can be used to adjust the strength of this prior, e.g. the command
+			</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -ld-prior-weight &lt;w&gt;
+		</div>
+		<div class="task_notes">
+			estimates LD under a <em>Dirichlet(1+w/4,1+w/4,1+w/4,1+w/4)</em> prior; setting <em>w=0</em> removes the prior altogether.
+		</div>
+	</div>
+
+		<div class="task">
+			<div class="task_name">
+				Stratifying LD computations across subsets
+			</div>
+			<div class="task_notes">
+				As for <code>-snp-stats</code>, the <code>-stratify</code> option tells QCTOOL to compute LD statistics stratified over
+				subsets of the data. E.g. suppose the sample file contains a column called <code>POP</code>
+				which reflects the population group of each sample.  Then the command:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -stratify POP
+			</div>
+			<div class="task_notes">
+				<p>
+					will compute LD statistics for all pairs of variants in each population.  Output columns will be named
+					in the form <code>POP=&lt;level&gt;:&lt;variable&gt;</code>.
+				</p>
+				<p>
+					For example, suppose we've extracted data for the <a href="">O blood group mutation</a> rs8176719 from the
+					<a href="">1000 Genomes Project</a> data into a file named <code>rs8176719.vcf</code>.  This command will
+						find all tagging SNPs in the flanking region:
+				</p>
+			</div>
+				<div class="task_command_line">
+					$ qctool -g ALL.chr9.phase3_shapeit2_mvncall_integrated_v5.20130502.genotypes.vcf.gz
+					-s 1000G.sample
+					-compute-ld-with rs8176719.vcf 1000G.sample
+					-old sqlite://ld.sqlite:LD
+					-stratify POP
+					-min-r2 0.75
+					-max-distance 1Mb
+				</div>
+				<div class="task_notes">
+				<p>
+					Note that currently it's first necessary to make a sample file in the
+					format <a href="../sample_file_formats.html">described here</a> for this to work.
+				</p>
+				<p>
+					<b>Note:</b> This will also take a while to run, since at present it scans the whole of chromosome 9.
+					A quicker way would be to use <a href="https://bitbucket.org/gavinband/bgen">bgenix</a> together with QCTOOL in 
+					 <a href="pipelining.html">in a pipeline</a>.
+				</p>
+			</div>
+		</div>
+
+</section>

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+<section class="main_text">
+	<h2>Computing principal components</h2>
+		<div class="task">
+			<div class="task_name">
+				Computing PCs
+			</div>
+			<div class="task_notes">
+				QCTOOL computes PCs by first estimating a relatedness or 'kinship' matrix, and then forming the eigendecomposition. 
+				In short you use the <code>-kinship</code> option to compute a
+				relatedness matrix, the <code>-UDUT</code> option to eigendecompose it, and the <code>-PCs</code> option
+				to output PCs.  A complete example would look like this:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
+			</div>
+			<div class="task_notes">
+				<p>
+					This outputs the first 20 PCs to the file <code>PCs.csv</code>, in addition to the estimated kinship
+					matrix and its eigendecomposition.  The following sections show the use of these options in more detail.
+			</p>
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Computing a kinship matrix
+			</div>
+			<div class="task_notes">
+				The <code>-kinship</code> option can be used to estimate a kinship matrix, as in:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -kinship kinship.csv
+			</div>
+			<div class="task_notes">
+				<p>
+					This outputs pairwise kinship values to the file <code>kinship.csv</code>, which is stored in a 'long' format
+					with columns holding the first sample id, second sample id, the number of pairwise non-missing genotypes,
+					and the estimated kinship value.  (Only the upper triangle of this matrix is output).
+				</p>
+				<p>
+					More precisely,  Suppose <em>X</em> is the <em>L&times;N</em> matrix of
+					genotypes, with variants indexed by row.
+					Let <em>f<sub>i</sub></em> be an estimate of the frequency of the <em>i</em>th variant.
+					We write <em>Z</em> for the matrix <em>X</em> after centring and rescaling each row based on the allele frequency,
+				</p>
+				<p>
+					<em>Z<sub>i&middot;</sub> = (X<sub>i&middot;</sub> - mean(X<sub>i&middot;</sub>)) / &Sqrt; (2 f<sub>i</sub> (1-f<sub>i</sub>))</em>
+				</p>
+				<p>
+					QCTOOL estimates the kinship matrix as <em>1/L Z^t Z</em>.
+					In forming <em>Z</em>, QCTOOL uses a posterior estimate of allele
+					frequency <em>f<sub>i</sub></em> under a <em>Beta(2,2)</em>
+					distribution, i.e. <em>f<sub>i</sub> = (1+N<sub>b</sub>)/(2+2N))</em> where <em>N<sub>b</sub></em> is
+					the count number of 'b' alleles in the data.  This can be understood as implicitly adding
+					a single haplotype of each allelic type to the data before
+					computing the frequency, which in turn ensures that the frequency estimate is not zero or 1.  
+				</p>
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Eigendecomposing a kinship matrix and computing PCs
+			</div>
+			<div class="task_notes">
+				The <code>-UDUT</code> option can be used to compute a UDUT decomposition (i.e. an eigendecomposition)
+				of the computed kinship matrix.
+					E.g.
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv
+			</div>
+			<div class="task_notes">
+				The output is an <em>N&times;(N+1)</em> matrix in which the first column represents the diagonal elements
+				of <em>D</em>, i.e. the eigenvalues, and the following <em>N</em> columns are the right eigenvectors
+				(i.e. the columns of <em>U</em>).  To additionally output principal components (PCs),
+				additionally add the <code>-PCs</code> option:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
+			</div>
+			<div class="task_notes">
+			<p>
+				The argument is the number of PCs to output.
+			</p>
+			<p>
+				<b>Note</b>: the PCs computed are simply rescaled entries of the right eigenvectors;
+				they are computed as <em>PC<sub>i</sub></em> = &Sqrt;(1/L) &times; U<sub>&middot;i</sub> D<sup>-1/2</sup></em>.
+				This scaling ensures the PCs do not grow with the number of variants.
+			</p>
+			<p>
+				<b>Note:</b> PCs are output to the file specified by <code>-osample</code>.
+				Depending on the command line, other values might also be output to this file.  For example, 
+				if you specify both <code>-sample-stats</code> and <code>-PCs</code>, the output file will contain both
+				per-sample summary statistics and PCs.
+				See the <a href="../../documentation/summary_file_formats.html">page
+					on summary statistic file formats</a> for more information on the format of the output.
+			</p>
+			<p>
+				In some contexts it may be preferable to load a previously
+				computed kinship matrix, rather than to recompute a new one. This can be acheived with the
+				<code>-load-kinship</code> option:
+			</p>
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -load-kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
+			</div>
+		</div>
+
+		<div class="task">
+			<div class="task_name">
+				Computing PC loadings
+			</div>
+			<div class="task_notes">
+				Having computed the UDUT decomposition, per-variant loadings can be
+				computed using the <code>-loadings</code> option, e.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -load-udut udut.csv -loadings loadings.csv
+			</div>
+			<div class="task_notes">
+				The <code>-PCs</code> option can again be used to adjust how many loadings are computed.
+				<b>Note</b>: you should ensure the same set of variants is used to compute
+				loadings as were used in constructing the kinship matrix.
+			</div>
+		</div>
+
+		<div class="task">
+			<div class="task_name">
+				Projecting additional samples onto a principal components decomposition
+			</div>
+			<div class="task_notes">
+				Given a set of loadings, additional samples can be projected onto the loadings using
+				the <code>-project-onto</code> option:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -project-onto loadings.csv projection.sample
+			</div>
+			<div class="task_notes">
+				The first argument is a set of loadings to load, while the second argument is the output file to compute.
+				Again, we advise using the same set of variants that were used to compute the PCs.
+			</div>
+		</div>
+</section>

ADDED   doc/html/qctool/content/documentation/examples/converting.content.html
Index: doc/html/qctool/content/documentation/examples/converting.content.html
==================================================================
--- doc/html/qctool/content/documentation/examples/converting.content.html
+++ doc/html/qctool/content/documentation/examples/converting.content.html
@@ -0,0 +1,87 @@
+<section class="main_text">
+			<h2>Converting between file formats</h2>
+		<div class="task">
+			<div class="task_name">
+				Basic conversions
+			</div>
+			<div class="task_notes">
+				The basic format of a conversion command is:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g &lt;input file&gt; [-filetype &lt;input type&gt;] -og &lt;output file&gt; [-ofiletype &lt;output type&gt;] [+modifier options]
+			</div>
+			<div class="task_notes">
+				QCTOOL normally deduces file types from the file extension.
+				However, for filetypes that are not automatically recognised, or if you want to specify,
+				the <code>-filetype</code> and <code>-ofiletype</code> options can be used to specify the types.
+				The <a href="../../documentation/genotype_file_formats.html">genotype file formats page</a> lists file type specifiers and
+				any applicable modifier options.
+			</div>
+			<div class="task_notes">
+				E.g. to convert between between bgen and vcf formats:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -og example.vcf
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Handling files split by chromosome
+			</div>
+			<div class="task_notes">
+				If the input filename contains a # character, e.g. <code>example_#.gen</code> this is treated as a
+				chromosomal wildcard and will match all (human) chromosomes. This will also be used to
+				infer the chromosome for each variant if chromosome information is not present in the files themselves.
+				For example, the command:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example_#.gen -og example.bgen
+			</div>
+			<div class="task_notes">
+				will process all 22 example files, and if the input GEN files have no chromosome information included,
+				the output data will have chromosome identifiers taken from the filenames.
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Including sample information in conversions
+			</div>
+			<div class="task_notes">
+				 Although specifying a sample file in conversions is optional, it's sometimes preferable to include one so that output files have
+				the correct sample identifiers (e.g. when converting GEN format to BGEN or VCF), e.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example_#.gen -og example.bgen -s example.sample
+			</div>
+			<div class="task_notes">
+				which will produce a BGEN file with a sample identifier block.
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Converting from VCF format
+			</div>
+			<div class="task_notes">
+				By default QCTOOL reads genotype calls from the <span class="monospace">GT</span> field in the VCF file.
+				The <code>-vcf-genotype-field</code> can be used to alter this, e.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.vcf -vcf-genotype-field GP -og converted.bgen
+			</div>
+			<div class="task_notes">
+				QCTOOL also assumes that VCF metadata is correct (according to the VCF v4.2 spec)- and it will
+				fail with an error if that's not the case.
+				To work around this, the <code>-metadata</code> option can be used to tell QCTOOL to load metadata from an
+				external file:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.vcf -og converted.bgen -metadata metadata.txt
+			</div>
+			<div class="task_notes">
+				The specified metadata file should contain complete VCF metadata, starting
+				with the <code>##fileformat=VCFv4.2</code> line, up to but not
+				including the <code>#CHROM...</code> line.
+			</div>
+		</div>
+	</div>
+</section>

ADDED   doc/html/qctool/content/documentation/examples/converting_genotypes.content.html
Index: doc/html/qctool/content/documentation/examples/converting_genotypes.content.html
==================================================================
--- doc/html/qctool/content/documentation/examples/converting_genotypes.content.html
+++ doc/html/qctool/content/documentation/examples/converting_genotypes.content.html
@@ -0,0 +1,30 @@
+<section class="main_text">
+			<h2>Converting genotypes</h2>
+		<div class="task">
+			<div class="task_name">
+				Computing genotype calls by thresholding
+			</div>
+			<div class="task_notes">
+				The <code>-threshold</code> option tells QCTOOL to compute thresholded genotype calls from genotype probabilities found in the input. For example:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g input.gen -threshold 0.9 -og thresholded.vcf
+			</div>
+			<div class="task_notes">
+				This will read genotype probabilities (e.g. from imputation) from the input file, and for each sample at each variant will
+				compute a genotype call (if one of the probabilities is above the threshold) or a missing call (if none are).
+			</div>
+			<div class="task_notes">
+				In the example above, the output VCF file will contain two FORMAT fields, namely GT (the threshholded call) and GP (the original
+				imputed probabilities).  More generally, <code>-threshold</code> makes the thresholded call the primary analysis genotype,
+				thus for example in the command:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g input.gen -threshold 0.9 -snp-stats -osnp &lt;output file&gt;
+			</div>
+			<div class="task_notes">
+				the output will reflect summary statistics computed on the thresholded calls.
+			</div>
+		</div>
+	</div>
+</section>

ADDED   doc/html/qctool/content/documentation/examples/filtering_samples.content.html
Index: doc/html/qctool/content/documentation/examples/filtering_samples.content.html
==================================================================
--- doc/html/qctool/content/documentation/examples/filtering_samples.content.html
+++ doc/html/qctool/content/documentation/examples/filtering_samples.content.html
@@ -0,0 +1,80 @@
+<section class="main_text">
+	<h2>Filtering samples</h2>
+		<div class="task">
+			<div class="task_name">
+				Filtering samples by identifier
+			</div>
+			<div class="task_notes">
+				The <code>-incl-samples</code> and <code>-excl-samples</code> options can be used to select a subset of
+				samples to process.  E.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen 
+				-s example.sample 
+				-og filtered.bgen
+				-excl-samples samples.txt
+			</div>
+			<div class="task_notes">
+				This command excludes all samples whose identifier is in the file <code>samples.txt</code>
+				(which should contain a whitespace-separated list of identifiers).
+				Samples are identified by the first identifier field (often <code>ID_1</code>) in the sample file, or if no
+				sample file is specified, by sample identifiers specified in genotype data
+				source (e.g. by the header in vcf or bgen formats).  The option <code>-incl-samples</code>
+				behaves similarly but includes only samples with identifier in the given file.
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Filtering samples by sample file column
+			</div>
+			<div class="task_notes">
+				It's also possible to filter samples based on the value of a column in the sample file.  The general command is:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g &lt;genotype file&gt; -s &lt;sample file&gt;
+				-[in|ex]cl-samples-where &lt;column&gt;[=|==|!=]&lt;value&gt; [+other options]
+			</div>
+			<div class="task_notes">
+				For example, the following command will write a new filtered genotype file excluding
+				all samples listed as "male" in the "sex" column of the sample file:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen
+				-s example.sample
+				-og filtered.bgen
+				-excl-samples-where 'sex = male'
+			</div>
+			<div class="task_notes">
+				<p>
+					You can currently filter sample file column values
+					for equality (using <code>=</code> or <code>==</code>) or inequality (<code>!=</code>).
+					<b>Note</b>: depending on the column names and expression used, it may be necessary
+					to place quotation marks around the expression to stop it being expanded by the shell.
+					As in the example above this also allows you to use whitespace to format the condition.
+				</p>
+				<p>
+					The <code>-incl-samples-where</code> behaves similarly, but includes only samples matching the condition.
+				</p>
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Combining filters
+			</div>
+			<div class="task_notes">
+				In general inclusion and exclusion options come in pairs of the form <code>-incl-&lt;option&gt;</code>, <code>-excl-&lt;option&gt;</code>.
+				If multiple overlapping conditions are specified, the logic is that samples that satisfy any of the specified exclusion criteria will
+				be excluded, and likewise samples that do not satisfy any of the specified inclusion criteria will be excluded.  This in the following command:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen
+				-s example.sample
+				-og filtered.bgen
+				-excl-samples-where 'sex = male'
+				-incl-samples samples.txt
+			</div>
+			<div class="task_notes">
+				The output will contain only male samples that are also listed in the file <code>samples.txt</code>.
+			</div>
+		</div>
+</section>

ADDED   doc/html/qctool/content/documentation/examples/filtering_variants.content.html
Index: doc/html/qctool/content/documentation/examples/filtering_variants.content.html
==================================================================
--- doc/html/qctool/content/documentation/examples/filtering_variants.content.html
+++ doc/html/qctool/content/documentation/examples/filtering_variants.content.html
@@ -0,0 +1,121 @@
+<section class="main_text">
+	<h2>Filtering variants</h2>
+	<div class="task">
+		<div class="task_name">
+			Filtering variants based on an external file
+		</div>
+		<div class="task_notes">
+			QCTOOL has a set of options to filter variants, each namely:
+			<code>-[in|ex]cl-rsids</code>,
+			<code>-[in|ex]cl-snpids</code>,
+			<code>-[in|ex]cl-positions</code>,
+			<code>-[in|ex]cl-variants</code>,
+			<code>-[in|ex]cl-variants-matching</code>.
+			Here are examples of these options:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -excl-rsids &lt;filename&gt;
+		</div>
+		<div class="task_notes">
+			Here the specified file should contain a whitespace-separated list of rsids that will be excluded from processing.
+		</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -excl-snpids &lt;filename&gt;
+		</div>
+		<div class="task_notes">
+			Ditto, but for alternate IDs.
+		</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -excl-positions &lt;filename&gt;
+		</div>
+		<div class="task_notes">
+			The specified file should contain a list of genomic positions in the format <code>[chromosome:]position</code>.
+			The chromosome should be omitted if you want to specify variants that have missing chromosome information.
+		</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -excl-variants &lt;filename&gt;
+		</div>
+		<div class="task_notes">
+			The specified file should contain a list of variants.  Currently this must be a text file with six named
+		 	 columns; the first four must be <code>SNPID</code>, <code>rsid</code>, <code>chromosome</code>, <code>position</code>,
+			 followed by columns containing the first and second alleles.  The <code>-compare-variants-by</code> option control
+			 how variants are matched to this file - see the page on <a href="sorting.html">sorting data</a> for more information
+			 on this option.
+		</div>
+	</div>
+
+	<div class="task">
+		<div class="task_name">
+			Range filtering
+		</div>
+		<div class="task_notes">
+			The <code>-[in|ex]cl-range</code> option filters variants by range.  E.g.:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -[in|ex]cl-range [chromosome]:[start]-[end]
+		</div>
+		<div class="task_notes">
+			This includes / excludes any variant in the given range.  Ranges are treated as closed ranges,
+			i.e. the range includes both start and end positions.
+			Optionally you can omit the chromosome; this will additionally capture variants that
+			have missing chromosome information. Also, either the start or end positions can be omitted, in which case the range is treated as containing
+			all positions up to the end coordinate, or all variants from the start coordinate onwards respectively.
+			Examples of valid ranges are:
+			<code>1:100-200</code>, <code>1:-200</code>, or <code>X:1000000-</code>.
+		</div>
+	</div>
+
+	<div class="task">
+		<div class="task_name">
+			Wildcard variant filtering
+		</div>
+		<div class="task_notes">
+			You can filter variants based on a wildcard match of ID fields.  E.g.:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -incl-variants-matching rsid~rs1%
+		</div>
+		<div class="task_notes">
+			This command will retain all variants that have rsid starting with 'rs1'.  The general format of this command is:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -incl-variants-matching [field~][value]
+		</div>
+		<div class="task_notes">
+			Here <code>field</code> can be 'snpid' (matching all alternate IDs) or 'rsid' (matching the first, or rs id),
+			or it can be omitted to match any id.  The value can optionally contain a single '%' character, which will
+			expand to match any string value.  A complete match is required, hence the value 'a%b'
+			will match the ID 'ab', 'a1b', etc., but not 'zab' or 'ab2'.
+		</div>
+	</div>
+	<div class="task">
+		<div class="task_name">
+			Combining multiple filters in the same command
+		</div>
+		<div class="task_notes">
+			<p>
+			The logic for processing multiple inclusion/exclusion options is as follows.
+			First, if any inclusion option is specified multiple times, the results are logically ORd together.
+			(Thus, for example specifying <code>-incl-range</code> twice results in including variants in either range).
+			Second, the resulting conditions are ANDed together.  This means that a variant will then be
+			included if it is included by each of the inclusion options and is not
+			excluded by any exclusion option.
+		</p>
+		<p>
+			For example, the following command includes any variant that is in either range and that is not in the given file:
+		</p>
+	</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -incl-range 1:-1000 -incl-range 2:-1000 -excl-rsids rsids.txt
+		</div>
+		<div class="task_notes">
+			<p>
+				while the following command includes only
+				variants that are in the given range and have rsid staring with "rs1":
+			</p>
+		</div>
+		<div class="task_command_line">
+			$ qctool -g example.bgen -og subsetted.bgen -incl-range 1:-1000 -incl-variants-matching rsid~rs1%
+		</div>
+	</div>
+</section>

ADDED   doc/html/qctool/content/documentation/examples/inferring_ploidy.content.html
Index: doc/html/qctool/content/documentation/examples/inferring_ploidy.content.html
==================================================================
--- doc/html/qctool/content/documentation/examples/inferring_ploidy.content.html
+++ doc/html/qctool/content/documentation/examples/inferring_ploidy.content.html
@@ -0,0 +1,60 @@
+<section class="main_text">
+	<h2>Working with sex chromosomes</h2>
+		<div class="task">
+			<div class="task_name">
+				Handling haploid and diploid samples
+			</div>
+			<div class="task_notes">
+				Several operations in QCTOOL, including  <code>-snp-stats</code> and <code>-compute-ld-with</code>,
+				handle haploid and diploid genotypes directly.  For example, consider the command:
+			</div>
+			
+			<div class="task_command_line">
+				$ qctool -g &lt;input file&gt; -snp-stats -osnp &lt;output file&gt;
+			</div>
+			<div class="task_notes">
+				When the input file contains X chromosome variants, the output file will contain relevant
+				information including haploid and diploid genotype counts, tests for equal frequency between
+				haploid and diploid samples, and appropriately estimated frequency and imputation certainty metrics.
+			</div>
+		</div>
+	</div
+	<div class="task">
+		<div class="task_name">
+			Inferring ploidy from sex information
+		</div>
+		<div class="task_notes">
+			In order for this to work, it is important that haploid genotypes are encoded appropriately in input files - e.g.
+			by using haploid calls in vcf GT field, or haploid data in BGEN-format files.  However, some file formats (e.g. GEN format)
+			do not support haploid calls, and some datasets (E.g. the 1000 Genomes Project genotype files) choose to encode all calls
+			as diploid even when the underlying genotype is haploid (i.e. for males on the X chromosome).  To work around this,
+			qctool can infer the ploidy from sex information supplied in a sample file.  (This functionality currently has
+			hard-coded ampping of chromosome identifiers to ploidy appropriate for humans).
+		</div>
+		<div class="task_notes">
+			This works as follows.  Suppose <code>sex</code> is the name of a column in the sample file containing sex information
+			- this must be of type 'D', and valid values are <code>male</code>, <code>M</code>, or <code>1</code> for male samples,
+			and <code>female</code>, <code>F</code>, or <code>2</code> for female.  Then, the <code>-infer-ploidy-from</code> option
+			can be used to tell QCTOOL to interpret diploid calls as haploid (or zero-ploid) as appropriate:
+		</div>
+		<div class="task_command_line">
+			$ qctool -g &lt;input file&gt; -s &lt;sample file&gt; -infer-ploidy-from sex -snp-stats -osnp &lt;output file&gt;
+		</div>
+		<div class="task_notes">
+			For each genotype QCTOOL applies the following rules:
+			<ol>
+				<li> If input genotype is not diploid, raise an error and terminate program.</li>
+				<li> If the sex of the sample is missing, set the genotype to missing.</li>
+				<li> Otherwise, compute the ploidy of the sample based on the chromosome identifier and the sample sex.</li>
+				<li> If the inferred ploidy is diploid, output the input genotype unchanged.</li>
+				<li> If the inferred ploidy is haploid, check whether the input genotype is homozygous (or, for
+				genotype probabilities, has 100% of the probability mass on homozygous calls).  If so, set the
+				genotype to the corresponding haploid call.  Otherwise, set the genotype to missing.</li>
+			</ol>
+		</div>
+		<div class="task_notes">
+			These rules apply to both hard-coded genotype calls (e.g. vcf GT field) and to
+			genotype probabilities (e.g. vcf GP field / GEN format / BGEN format data).
+		</div>
+	</div>
+</section>

ADDED   doc/html/qctool/content/documentation/examples/intensities.content.html
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==================================================================
--- doc/html/qctool/content/documentation/examples/intensities.content.html
+++ doc/html/qctool/content/documentation/examples/intensities.content.html
@@ -0,0 +1,4 @@
+<section class="main_text">
+	<h2>Processing intensity data</h2>
+	(under construction)
+</section>

ADDED   doc/html/qctool/content/documentation/examples/merging.content.html
Index: doc/html/qctool/content/documentation/examples/merging.content.html
==================================================================
--- doc/html/qctool/content/documentation/examples/merging.content.html
+++ doc/html/qctool/content/documentation/examples/merging.content.html
@@ -0,0 +1,82 @@
+<section class="main_text">
+	<h2>Merging variants from one dataset into another</h2>
+		<div class="task">
+			<div class="task_name">
+				Merging data
+			</div>
+			<div class="task_notes">
+				The <code>-merge-in</code> option can be used to merge variants in one dataset into another.  For example:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen
+			</div>
+			<div class="task_notes">
+				<p>
+				This command produces a dataset that contains a record for each variant
+				from <code>first.bgen</code> and a record for each variant from <code>second.bgen</code>
+				- i.e. it has <em>L<sub>1</sub>+L<sub>2</sub></em> variants,
+				where <em>L<sub>1</sub></em> and <em>L<sub>2</sub></em> are the
+				number of variants in the two datsets.
+			</p>
+			<p>
+				Data is output for the set of samples in the first dataset; any other samples in the merged-in dataset are ignored.
+			</p>
+		</div>
+	</div>
+
+	<div class="task">
+			<div class="task_name">
+				Controlling how samples are matched between datasets
+			</div>
+			<div class="task_notes">
+			<p>
+				By default, samples are matched by the first ID column in each dataset.
+				The <code>-match-sample-ids</code> option can be used to change this.  For example:
+			</p>
+			</div>
+			<div class="task_command_line">
+				$ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen -match-sample-ids column1~column2
+			</div>
+			<div class="task_notes">
+				Where <code>column1</code> and <code>column2</code> are columns in <code>first.sample</code> and <code>second.sample</code> respectively,
+					containing the fields to match on.
+					We recommend that sample file columns used to match samples should contain unique sample identifiers.
+			</div>
+		</div>
+		
+	<div class="task">
+			<div class="task_name">
+				Controlling what variants appear in the output
+			</div>
+			<div class="task_notes">
+				<p>
+					The <code>-merge-strategy</code> option controls what happens when the same variant appears in both
+					datasets.  Possible values are <code>-keep-all</code> (the default) or <code>-drop-duplicates</code>.
+					For example:
+				</p>
+			</div>
+				<div class="task_command_line">
+					$ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen -merge-strategy drop-duplicates
+				</div>
+			<div class="task_notes">
+				<p>
+					In this command, if the same variant appears in <code>first.bgen</code> and in <code>second.bgen</code>,
+					only the first will be output.  As when  <a href="combining.html">combining datasets</a>,
+					the <code>-compare-variants-by</code> option is used to control how variants are compared, and it is assumed
+					that variants are sorted by these fields in each input dataset.
+			</p>
+			<p>
+				To further help disambiguate the source of data in the output file,
+				the <code>-merge-prefix</code> option can also be used to add a prefix to the identifier of each merged-in -variant, e.g.:
+			</p>
+		</div>
+			<div class="task_command_line">
+				$ qctool -g first.bgen -s first.sample -merge-in second.bgen -s second.sample -og merged.bgen -merge-prefix "merged:"
+			</div>
+			<div class="task_notes">
+			<p>
+				Currently this only affects the 'alternate' identifier fields (e.g. the SNPID field of GEN or BGEN files).
+			</p>
+		</div>
+	</div>
+</section>

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+<section class="main_text">
+	<h2>Using qctool in a pipeline</h2>
+		<div class="task">
+			<div class="task_name">
+				Outputting data to stdout
+			</div>
+			<div class="task_notes">
+				Using "-" as an output file specifier will output data to standard output, that can then be redirected
+				or piped into other commands.  For example:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -og -
+			</div>
+			<div class="task_notes">
+				This outputs genotype data to stdout.
+				(By default output is in VCF format; use the <code>-ofiletype</code> option to alter this).
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -snp-stats -osnp -
+			</div>
+			<div class="task_notes">
+				This outputs SNP summary statistics to standard output.
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Inputting data from stdin
+			</div>
+			<div class="task_notes">
+				QCTOOL has limited support for reading data from stdin.
+				To do this, specify "-" as the argument to <code>-g</code>, and specify the format of the input data
+				using the <code>-filetype</code> option, e.g.:
+			</div>
+			<div class="task_command_line">
+				$ cat file.bgen | qctool -g - -filetype bgen [other options]
+			</div>
+			<div class="task_notes">
+			  <p>
+					This functionality is currently limited to input data in BGEN format (<code>-filetype bgen</code>)
+					or in VCF format (<code>-filetype vcf</code>).  VCF format data should be streamed uncompressed, e.g.:
+				</p>
+			<div class="task_command_line">
+				$ cat file.vcf.gz | gunzip -c | qctool -g - -filetype vcf [other options]
+			</div>
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Pipelining QCTOOL with other tools
+			</div>
+			<div class="task_notes">
+				As an example, the following command uses <a href="http://bitbucket.org/gavinband/bgen">bgenix</a> with QCTOOL to
+				compute snp summary statistics from a subset of a BGEN file, and view the result on the fly using
+				<a href="https://en.wikipedia.org/wiki/Less_(Unix)"><code>less</code></a>.
+			</div>
+			<div class="task_command_line">
+				$ bgenix -g file.bgen -range 11:3500000-6500000 | qctool -g - -filetype bgen -snp-stats -osnp - | less -S
+			</div>
+		</div>
+</section>

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--- doc/html/qctool/content/documentation/examples/sorting.content.html
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+<section class="main_text">
+	<h2>Sorting and reordering data</h2>
+		<div class="task">
+			<div class="task_name">
+				Sorting variants
+			</div>
+			<div class="task_notes">
+				The <code>-sort</code> option tells QCTOOL to sort variants in its output file:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -og sorted.bgen -sort
+			</div>
+			<div class="task_notes">
+				<p>
+					The way this works is that QCTOOL first writes the data to a temporary file in the order that it is processed,
+					keeping a record of the file locations of each variant in memory.  It then copies each variant from the
+					temporary file to the destination in the desired order.
+				</p>
+				<p>
+					The sort operation currently works for BGEN, unzipped GEN, and unzipped VCF output formats.
+			</p>
+
+				</p>
+				<p>
+				By default QCTOOL sorts based on on genomic position,
+				alleles, and ID fields.  You can change this by specifying the <code>-compare-variants-by</code> option, e.g.:
+			</p>
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -og sorted.bgen -sort -compare-variants-by ids
+			</div>
+			<div class="task_notes">
+				<p>
+					Possible fields that can be sorted on are: <code>position</code>, <code>alleles</code>,
+				<code>ids</code>, <code>rsid</code> (which refers to the first or primary ID in the dataset),
+				or <code>snpid</code> (which refers all but the first ID in each dataset).
+			</p>
+			</div>
+		</div>
+		<div class="task">
+			<div class="task_name">
+				Reordering samples
+			</div>
+			<div class="task_notes">
+				The <code>-reorder</code> option tells QCTOOL to reorder samples in its input.  The format is:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -og reordered.bgen -reorder &lt;filename&gt;
+			</div>
+			<div class="task_notes">
+				<p>
+				where <code>&lt;filename&gt;</code> is the name of a readable file containing sample identifiers.
+				This file must contain exactly <em>N</em> identifiers (if there are <em>N</em> samples being processed)
+				and each identifer must be the primary identifier of a sample being processed.</p>
+				<p>Alternatively, <code>-reorder</code> can take one of following the two special values:
+					<code>-reorder backwards</code> will reverse the order of samples, and <code>-reorder randomly</code> will
+					randomly reorder samples.
+				</p>
+			</div>
+			
+			
+			
+			
+		</div>
+</section>

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+<section class="main_text">
+	<h2>Computing summary statistics</h2>
+		<div class="task">
+			<div class="task_name">
+				Per-sample summary statistics
+			</div>
+			<div class="task_notes">
+				The <code>-sample-stats</code> option can be used to compute per-sample summary statistics.
+				The output goes to a file specified by the <code>-osample</code> option.  E.g:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -sample-stats -osample sample-stats.txt
+			</div>
+			<div class="task_notes">
+				<p>
+					This computes per-sample summary statistics (average missingness and heterozygosity) and places
+					them in the file <Code>sample-stats.txt</code>.  Additionally, if array intensity data
+					is available (see <a href="intensities.html">processing intensity data</a>), average X channel, Y
+					channel, total (X+Y) and difference (X-Y) of intensities will be computed.
+					These can be used useful for QC purposes - for example,
+					average intensity on the X and Y chromosomes can be used to directly determine sample gender.
+				</p>
+				<p>
+					<b>Note:</b> the output file can be formatted in various of ways, controlled by the file extension.
+					See the page on <a href="../summary_file_formats.html">summary statistic file formats</a> for
+					information on output file formatting.
+				</p>
+			</div>
+		</div>
+
+		<div class="task">
+			<div class="task_name">
+				Per-variant summary statistics
+			</div>
+			<div class="task_notes">
+				The basic option to compute per-variant summary statistics is <code>-snp-stats</code>.  E.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -snp-stats -osnp snp-stats.txt
+			</div>
+			<div class="task_notes">
+				<p>
+					This will compute genotype counts, allele counts and frequencies, missing data rates, info metrics, and a P-value
+					against the null that genotypes are in Hardy-Weinberg proportions in diploid samples.  Output is sent to the
+					file specified in the <code>-osnp</code> option.  See the page on <a href="../summary_file_formats.html">summary statistic file formats</a> for
+					information on output file formatting.
+				</p>
+				<p>
+					Analysis on the sex chromosomes is complicated by the fact that males and females have differing ploidy.
+					To process sex chromosomes correctly, QCTOOL relies on the ploidy being correct in the input genotype files.
+					However, some data sets (and some file formats) instead encode males as diploid homozygotes.
+					The <code>-infer-ploidy-from</code> can be used to deal with such data - see the
+					page on <a href="inferring_ploidy.html">inferring ploidy</a> .
+				</p>
+				<p>
+					For sex chromosomes, QCTOOL outputs both diploid and haploid
+					genotype counts, as well an appropriate allele frequency, a sex-chromosome specific info metric,
+					and a test for difference in frequency between males and females.  
+				</p>
+			</div>
+		</div>
+
+		<div class="task">
+			<div class="task_name">
+				Differential missingness
+			</div>
+			<div class="task_notes">
+				It's often useful to compare levels of missingness between different samples.  The <code>-differential</code>
+				option can be used to compare levels of missingness between samples having different levels of a covariate
+				in the sample file.  E.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -osnp snp-stats.txt -differential &lt;column&gt;
+			</div>
+			<div class="task_notes">
+				This computes: the count of missing and non-missing genotypes in each level of the covariate specified in
+				the specified column, and a likelihood ratio test P-value comparing missing data rates in the different levels.
+				Additionally, if the covariate has exactly two levels, a Fishers exact test P-value is also computed.
+			</div>
+		</div>
+		
+		<div class="task">
+			<div class="task_name">
+				Combining options
+			</div>
+			<div class="task_notes">
+				Summary statistic options can be combined; e.g:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -osnp snp-stats.txt -differential &lt;column&gt;
+			</div>
+			<div class="task_notes">
+				This computes both basic summary statistics and values for differential missingness, and places it in the same output file.
+			</div>
+		</div>
+
+		<div class="task">
+			<div class="task_name">
+				Stratifying summary statistics
+			</div>
+			<div class="task_notes">
+				The <code>-stratify</code> option can be used to compute summary statistics stratified over
+				subsets of the data. E.g.:
+			</div>
+			<div class="task_command_line">
+				$ qctool -g example.bgen -s example.sample -snp-stats -osnp snp-stats.txt -stratify &lt;column&gt;
+			</div>
+			<div class="task_notes">
+				<p>The argument must be the name of a column in the sample file containing discrete
+					values (i.e. it must be of type <code>B</code> or <code>D</code>).  Summary statistic calculations will
+				be computed for each subset of samples having the same value in that column.
+				The output will contain the same fields as for <code>-snp-stats</code>, but each column will
+				appear multiple times with a suffix of the form <code>[&lt;column&gt;=&lt;value&gt;]</code>
+				to denote which strata the values are computed for.
+			</p>
+				<p>
+					This feature has several possible use cases - for example, it can be used to compute allele counts across ethnic groups in a
+					sample of mixed ancestry, or to inspect deviation from Hardy-Weinberg equilibrium seperately in disease cases and controls.
+				</p>
+			</div>
+		</div>
+</section>

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+<section class="main_text">
+	<h2>Genotype file formats</h2>
+	<p>
+		QCTOOL supports the following file formats for genotype data:
+	</p>
+	<table class="file_formats">
+		<colgroup>
+			<col class="acronym" style="width:20%">
+			<col class="filetype" style="width:20%">
+			<col class="notes" style="width:65%">
+		</colgroup>
+		<thead>
+			<tr>
+			<th>
+				<div>Format</div> <small>(recognised extensions)</small>
+			</th>
+			<th>
+				<div>Filetype</div>
+				<small>(For <span><nobr><code>-[o]filetype</code></nobr></span>)</small>
+			</th>
+			<th>
+				Notes
+			</th>
+		</tr>
+	</thead>
+		<tbody>
+		<tr>
+			<td>
+				<div><a href="https://www.well.ox.ac.uk/~gav/snptest/#input_file_formats">GEN</a></div>
+				<code>(.gen, .gen.gz)</code>
+				<br><small>(Input / output)</small>
+			</td>
+			<td><code>gen</code></td>
+			<td>
+				Optionally, an extra initial column containing chromosomes can be included in the input.  QCTOOL auto-detects this
+				in input files by counting the columns in the file.
+				To suppress this column in output files, use the <span class="monospace">-omit-chromosome</span> option.
+				The GEN format is further described <a href="https://www.well.ox.ac.uk/~gav/snptest/#input_file_formats">here</a>.
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<div><a href="http://www.bgenformat.org">BGEN</a></div>
+				<code>(.bgen)</code>
+				<br><small>(Input / output)</small>
+			</td>
+			<td><code>bgen</code></td>
+			<td>
+				<p>Output files are in BGEN v1.2 with 16 bits per probability and compressed
+				using <a href="http://www.zlib.net">zlib</a> by default. 
+				The <code>-bgen-bits</code> option can be used to adjust the number of bits used.
+				The <code>-bgen-compression</code> option can be used to choose the method of compression
+				(either zlib or <a href="http://www.zstd.net">zstd</a>).<p>
+				<p>Use <code>-ofiletype bgen_v1.1</code> to force writing files compatible with the BGEN v1.1 spec.</p>
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<div><a href="http://samtools.github.io/hts-specs/VCFv4.2.pdf">VCF</a></div>
+				<code>(.vcf, .vcf.gz)</code>
+				<br><small>(Input / output)</small>
+			</td>
+			<td><code>vcf</code></td>
+			<td>
+				<p>QCTOOL is strict about VCF metadata in input files for the fields it reads.  Since 
+				metadata is not always correct a <span class="monospace">-metadata</span> option is
+				provided to override the input file metadata. Currently, only genotypes are output
+				when outputting VCF files.</p>
+				<p>Note that QCTOOL does not apply PHRED scaling to probabilities
+				in the GP field.</p>
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<div><a href="https://www.cog-genomics.org/plink/2.0/formats">PLINK binary format</a></div>
+				<code>(.bed, .bim, .fam)</code>
+				<br><small>(Input / output)</small>
+			</td>
+			<td><code>binary_ped</code></td>
+			<td>
+				Note that QCTOOL currently does only the most basic processing of
+				FAM files: when reading, it uses them to count the number of samples in the BED file, when writing it writes a FAM file
+				with missing data in all fields except the ID field.  You will therefore need to create fuller FAM files seperately for use with
+				other tools.
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<div><a href="https://mathgen.stats.ox.ac.uk/genetics_software/shapeit/shapeit.html#hapsample">SHAPEIT</a> <small>haplotype format</small></div>
+				<br><small>(Input / output)</small>
+			</td>
+			<td><code>shapeit_haplotypes</code></td>
+			<td>
+
+				This format has five initial columns (`SNPID`, `rsid`, `position`, first and seconda alleles) followed
+				by two columns for each sample representing the two haplotypes. These columns contain 0 (representing the first
+				allele) or 1 (representing the second allele). The first column is sometimes used to record the chromosome instead
+				of a seperate ID, but to my knowledge this is a convention. QCTOOL does not interpret the first column as
+				chromosome information, but the `-assume-chromosome` option can be used to work around this.
+				To convert haplotypes to genotypes, QCTOOL assumes that the two haplotypes for each individual are
+				consecutive columns in the file. (This format is described <a
+				href="https://mathgen.stats.ox.ac.uk/genetics_software/shapeit/shapeit.html#hapsample">here</a>.)
+
+			</td>
+		</tr>
+		<tr>
+			<td>
+				IMPUTE <small>allele probabilities format</small></div>
+				<br><small>(Input / output)</small>
+			</td>
+			<td><code>impute_allele_probs</code></td>
+			<td>
+
+				This file format is like the shapeit haplotype format but contains a probability for each haplotype
+				(i.e. two probabilities per individual), specifying the probability that the haplotype carries the second allele.
+
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<div><a href="http://mathgen.stats.ox.ac.uk/impute/impute_v2.html">IMPUTE</a> <small>haplotype format</small></div>
+				<br><small>(Input only)</small>
+			</td>
+			<td><code>impute_haplotypes</code></td>
+			<td>
+				It is assumed the legend file name is the same as the haplotypes file name, minus extension,
+				with <span class="monospace">.legend</span> appended; QCTOOL will also remove/add the
+				<code>.gz</code> extension as appropriate.
+				For genotypic computations, genotypes are formed from pairs of haplotypes;
+				it is assumed that the two haplotypes for each individual are consecutive columns in the haplotypes file.
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<div><a href="https://oxfordhla.well.ox.ac.uk/hla/">HLAIMP</a> <small>probability format</small></div>
+				<br><small>(Input only)</small>
+			</td>
+			<td><code>hlaimp</code></td>
+			<td>
+				Currently, this input format implicitly splits each HLA locus as a series of bi-allelic variants.
+			</td>
+		</tr>
+		<tr>
+			<td>
+				QCTOOL <small>'long' format</small>
+				<br><small>(Input only)</small>
+			</td>
+			<td><code>long</code></td>
+			<td>
+				Input must be a file with columns <code>SNPID, rsid, chromosome, position, number_of_alleles,
+					allele1, other_alleles, sample_id, ploidy, genotype</code>.
+				Further columns may also be included (but QCTOOL ignores these).
+				Allelesin the other_alleles column must be comma-separated (as with <a href="http://samtools.github.io/hts-specs/VCFv4.2.pdf">VCF</a> ALT alleles).
+				When outputting to vcf format, both genotype (GT) and a field 'typed' indicating whether a row for each
+				sample and variant was present will be output.
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<a href="http://penncnv.openbioinformatics.org/en/latest/">PennCNV</a>
+				/ <a href="https://sites.google.com/site/quantisnp/">QuantiSNP</a> format
+				<br><small>(Output only)</small>
+			</td>
+			<td><code>penncnv</code></td>
+			<td>
+				PennCNV uses a single sample per input file, this can be acheived using the sample filtering options,
+				e.g. <code>-incl-samples-where ID_1=&lt;identifier&gt;</code>
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<div><a href="http://stephenslab.uchicago.edu/software.html#bimbam">BIMBAM</a> <small>dosage format</small>;</div>
+				<div>QCTOOL <small>dosage format</small></div>
+				<code>(.dosage[.gz])</code>
+				<br><small>(Output only)</small>
+			</td>
+			<td><code>bimbam_dosage</code> or <code>dosage</code></td>
+			<td>
+				This file outputs a single column per sample (named by the sample identifier) containing the
+				expected second allele dosage for the sample at each variant.
+				The formats differ in that BIMBAM format has no chromosome/position information.
+			</td>
+		</tr>
+		<tr>
+			<td>
+				<div>QCTOOL <small>intensity text format</small></div>
+				<code>.intensity[.gz]</code>
+				<br><small>(Output only)</small>
+			</td>
+			<td><code>intensity</code></td>
+			<td>
+				The output file has two columns per sample, representing X and Y channel intensities for the
+				sample at each variant.  Currently data must be read from a VCF file; the field is specified
+				using the <code>-vcf-intensity-field</code> option.
+			</td>
+		</tr>
+		<tbody>
+	</table>
+</section>

ADDED   doc/html/qctool/content/documentation/sample_file_formats.content.html
Index: doc/html/qctool/content/documentation/sample_file_formats.content.html
==================================================================
--- doc/html/qctool/content/documentation/sample_file_formats.content.html
+++ doc/html/qctool/content/documentation/sample_file_formats.content.html
@@ -0,0 +1,56 @@
+<section class="main_text">
+	<h2>Sample file formats</h2>
+	<h3>SNPTEST sample file format</h3>
+	<p>QCTOOL uses the same sample file format as <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html">SNPTEST</a>.
+		This is a space-separated file with two header lines followed by data, as follows.
+	</p>
+		<dl>
+			<dt>Header line</dt>
+			<dd>This line lists the name of each column.  Column names can be arbitrary printable characters, not including whitespace.</dd>
+			<dt>Column type line</dt>
+			<dd>This line lists the 'type' of each column and is used by QCTOOL to process data in an appropriate way.
+				There must be one type for each column.  Allowable column types are:
+				<ul>
+					<li>0 (for the first identifier column)</li>
+					<li>D (for a column containing discrete values, e.g. a set of strings)</li>
+					<li>P or C - for columns containing continuous value - each value must be numerical, or a missing value.</li>
+					<li>B - for a column containing a binary trait.  The values in this column must be '0', '1', 'control', or 'case'.</li>
+				</ul>
+				In addition to the first column, QCTOOL optionally allows
+				there to be a column called 'ID_2' and/or a column called 'missing' that have type '0'.
+				Internally these are treated like columns of type 'D'.
+			</dd>
+			<dt>
+				Data lines
+			</dt>
+			<dd>Data for each sample.  There should be one data line per sample in the genotypes file, and these must be in the same
+				order that they appear in the genotypes file.
+			</dd>
+		</dl>
+		<p>
+			By default 'NA' is used for missing values in the sample file. Any value in any column that is equal (as a string literal)
+			to "NA" will be treated as missing.  (The option <code>-missing-code</code> can be
+			used to alter what is treated as a missing value.)
+		</p>
+		<p>
+			The first column in a sample file must always be of type '0' and it is always treated as sample identifiers.
+			We strongly recommend that the identifiers used are chosen to be unique across a project.
+		</p>
+		<p>
+			Relative to the traditional format used in SNPTEST, QCTOOL allows some modifications:
+		</p>
+		<ul>
+			<li>The only mandatory column is the first column, which must of type '0' and contains sample identifiers.</li>
+		</ul>
+		<p>An example of a sample file is:</p>
+		<code>
+ID sex case covariate<br/>
+0 D B C<br/>
+sample1 M control 0.1<br/>
+sample2 F control 0.2<br/>
+sample3 F control -0.15<br/>
+sample4 F case -0.01<br/>
+sample4 NA NA 0.025<br/>
+(etc.)<br/>
+		</code>
+</section>

ADDED   doc/html/qctool/content/documentation/summary_file_formats.content.html
Index: doc/html/qctool/content/documentation/summary_file_formats.content.html
==================================================================
--- doc/html/qctool/content/documentation/summary_file_formats.content.html
+++ doc/html/qctool/content/documentation/summary_file_formats.content.html
@@ -0,0 +1,4 @@
+<section class="main_text">
+	<h2>Summary statistic file formats</h2>
+	<p>(This page is under construction.)</p>
+</section>

ADDED   doc/html/qctool/content/footer.html
Index: doc/html/qctool/content/footer.html
==================================================================
--- doc/html/qctool/content/footer.html
+++ doc/html/qctool/content/footer.html
@@ -0,0 +1,47 @@
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
+				<a href="[ROOT]/index.html">overview</a>
+			</div>
+			<div class="nav_button" name="documentation">
+				documentation
+				<ul class="menu">
+					<li><a href="[ROOT]/documentation/diagram_of_options.html">Diagram of options</a></li>
+					<li><a href="[ROOT]/documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="[ROOT]/documentation/changes.html">Change history</a></li>
+				</ul>
+			</div>
+			<div class="nav_button" name="tutorial">
+				examples
+				<ul class="menu">
+					<li><a href="[ROOT]/documentation/examples/basic.html">Basic usage</a></li>
+					<li><a href="[ROOT]/documentation/examples/converting.html">Converting file formats</a></li>
+					<li><a href="[ROOT]/documentation/examples/converting_genotypes.html">Thresholding genotypes</a></li>
+					<li><a href="[ROOT]/documentation/examples/sorting.html">Sorting and reordering data</a></li>
+					<li><a href="[ROOT]/documentation/examples/combining.html">Combining datasets</a></li>
+					<li><a href="[ROOT]/documentation/examples/merging.html">Merging in variants</a></li>
+					<li><a href="[ROOT]/documentation/examples/altering_id_data.html">Altering variant identifying data</a></li>
+					<li><a href="[ROOT]/documentation/examples/pipelining.html">Using qctool in a pipeline</a></li>
+					<li><a href="[ROOT]/documentation/examples/filtering_samples.html">Filtering samples</a></li>
+					<li><a href="[ROOT]/documentation/examples/filtering_variants.html">Filtering variants</a></li>
+					<li><a href="[ROOT]/documentation/examples/summary_statistics.html">Computing summary statistics</a></li>
+					<li><a href="[ROOT]/documentation/examples/annotating.html">Computing annotations</a></li>
+					<li><a href="[ROOT]/documentation/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
+					<li><a href="[ROOT]/documentation/examples/computing_ld.html">Computing LD</a></li>
+					<li><a href="[ROOT]/documentation/examples/computing_pcs.html">Computing principal components</a></li>
+					<li><a href="[ROOT]/documentation/examples/inferring_ploidy.html">Working with sex chromosomes</a></li>
+				</ul>
+			</div>
+			<div class="nav_button" name="file_formats">
+				file formats
+				<ul class="menu">
+					<a href="[ROOT]/documentation/genotype_file_formats.html">Genotype file formats</a>
+					<a href="[ROOT]/documentation/sample_file_formats.html">Sample file formats</a>
+					<a href="[ROOT]/documentation/summary_file_formats.html">Summary statistic file formats</a>
+			</div>
+			<div class="nav_button" name="download">
+				<a href="[ROOT]/documentation/download.html">download</a>
+			</div>
+</div>
+</nav>
+
+	</body>
+</html>

ADDED   doc/html/qctool/content/header.html
Index: doc/html/qctool/content/header.html
==================================================================
--- doc/html/qctool/content/header.html
+++ doc/html/qctool/content/header.html
@@ -0,0 +1,22 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
+"http://www.w3.org/TR/html4/strict.dtd">
+<html>
+	<head>
+
+		<script type="text/javascript" src="[ROOT]/js/jquery-3.2.1.min.js"></script>
+		<script type="text/javascript" src="[ROOT]/js/local.js"></script>
+		<script type="text/javascript" src="[ROOT]/js/datatables.min.js"></script>
+		<link href="[ROOT]/style/css/default.css" rel="stylesheet" type="text/css">
+		<title>QCTOOL v2</title>
+	</head>
+	<body>
+		<div class="header" id="header1">
+			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
+			<div class="header_text">
+				qctool v2
+			</div>
+			<div class="header_subtext">
+				A tool for quality control and analysis of gwas datasets.
+			</div>
+			<img src="[ROOT]/style/images/qctool.png" class="logo">
+		</div>

ADDED   doc/html/qctool/content/index.content.html
Index: doc/html/qctool/content/index.content.html
==================================================================
--- doc/html/qctool/content/index.content.html
+++ doc/html/qctool/content/index.content.html
@@ -0,0 +1,50 @@
+<section class="main_text" markdown="1">
+### Introduction ###
+
+QCTOOL is a command-line utility program for manipulation and quality control of gwas datasets and other genome-wide data. QCTOOL can be used
+
+* To compute per-variant and per-sample QC metrics.
+* To filter out samples or variants.
+* To merge datasets in various ways.
+* To convert dataset between file formats. (In particular QCTOOL can
+	read and write <a href="http://www.well.ox.ac.uk/~gav/bgen_format/bgen_format.html">BGEN</a> files,
+	including full support for the BGEN v1.2 format that has been used for
+	the <a href="http://www.ukbiobank.ac.uk/scientists-3/genetic-data/">UK Biobank imputed data full release</a>).
+* To manipulate datasets in various ways - e.g. by updating data fields or aligning alleles to a reference sequence based on information in a strand file.
+* To annotate variants with information from BED files, sequence from FASTA files, or with genetic map positions.
+* To compute LD metrics between variants.
+* To compare genotypes for individuals typed or imputed or phased in different datasets.
+* To compute between-sample relatedness and principal components.
+* To compute 'genetic risk predictor' scores.
+
+QCTOOL is designed to be as easy-to-use as possible and we hope you find it so. See the <a
+href="[ROOT]/documentation/examples/basic.html">basic usage page</a> for a quick start on running QCTOOL, and the
+<a href='[ROOT]/documentation/diagram_of_options.html'>diagram of options</a> for an overview of how QCTOOL works.
+
+**IMPORTANT**: this page documents QCTOOL version 2, which differs in several important ways from the 
+original <a href="http://www.well.ox.ac.uk/~gav/qctool_v1">QCTOOL v1</a>.
+Version 1 is still available but is now unsupported.
+
+### Obtaining QCTOOL ###
+
+The QCTOOL source code is currently hosted at <a href="https://code.enkre.net">code.enkre.net</a>. You may also be able
+to obtain precompiled binaries from <a href="https://www.well.ox.ac.uk/~gav/resources/">this folder</a>. See the <a
+href="[ROOT]/documentation/download.html">download page</a> for full details on obtaining and installing QCTOOL.
+
+### Change history ###
+
+See the <a href="[ROOT]/documentation/changes.html">change history page</a>.
+
+### Acknowledgements ###
+
+The following people contributed to the design and implementation of qctool:
+* <a href="http://www.well.ox.ac.uk/~gav/">Gavin Band</a>
+* <a href="http://www.stats.ox.ac.uk/~marchini/">Jonathan Marchini</a>
+
+In addition, QCTOOL contains the <a href="http://www.sph.umich.edu/csg/abecasis/Exact/index.html">SNP-HWE</a> code by Jan Wigginton et al., described in "A Note on Exact Tests of Hardy-Weinberg Equilibrium", Wigginton et al, <i>Am. J. Hum. Genet</i> (2005) 76:887-93.
+Further acknowledgements can be found on the <a href="https://code.enkre.net/qctool">QCTOOL repository main page</a>.
+
+### Getting support ###
+
+For more information or questions, please contact the OXSTATGEN mailing list at ``oxstatgen (at) jiscmail.ac.uk``
+</section>

Index: doc/html/qctool/documentation/alphabetical_options.html
==================================================================
--- doc/html/qctool/documentation/alphabetical_options.html
+++ doc/html/qctool/documentation/alphabetical_options.html
@@ -2,61 +2,13 @@
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
 
 		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
-		<script type="text/javascript" src="../js/datatables.min.js"></script>
 		<script type="text/javascript" src="../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
-		<script>
-			$(document).ready(
-				function() {
-					$.getJSON( "../resources/options.json", function( data ) {
-						console.log( 'gotit' ) ;
-						var options = [] ;
-						$.each( data, function( key, value ) {
-							options.push( key ) ;
-							console.log( key ) ;
-						} ) ;
-						
-						options.sort( function(a,b) {
-							return a.toLowerCase().localeCompare( b.toLowerCase() ) ;
-						}) ;
-						
-						for( var i = 0; i < options.length; ++i ) {
-							$(".option_table > tbody").append(
-								'<tr><td>' + options[i] + '</td><td>' + data[options[i]]['description'] + '</tr>'
-							)
-						}
-						
-						$( ".option_table" ).DataTable(
-							{
-								"paging": false,
-							  "language": {
-							    "search": "Search command-line options:"
-							  }
-							}
-						) ;
-						
-						$('.dataTables_filter').css('float', 'left') ;
-					}) ;
-				}
-			) ;
-		</script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
 		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
-		<link rel="stylesheet" type="text/css" href="../style/css/datatables.min.css"/>
 		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
@@ -64,44 +16,87 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
+			<img src="../style/images/qctool.png" class="logo">
 		</div>
-		
-		<section class="main_text">
-			<h2>Table of options</h2>
-			<p>Below is a list of all options supported by QCTOOL. (See also the <a href="../documentation/diagram_of_options.html">diagram of options</a>).</p>
-			<table class="option_table">
-				<colgroup>
-					<col class="option"></col>
-					<col class="description"></col>
-				</colgroup>
-				<thead>
-					<tr>
-						<th>
-							Option
-						</th>
-						<th>
-							Description
-						</th>
-					</tr>
-				</thead>
-				<tbody>
-				</tbody>
-			</table>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+
+<section class="main_text">
+    <h2>Table of options</h2>
+    <p>Below is a list of all options supported by QCTOOL. (See also the <a href="../documentation/diagram_of_options.html">diagram of options</a>).</p>
+    <table class="option_table">
+        <colgroup>
+            <col class="option">
+            <col class="description">
+            <col class="default">
+        </colgroup>
+        <thead>
+            <tr>
+                <th>
+                    Option
+                </th>
+                <th>
+                    Description
+                </th>
+                <th>
+                    Default value?
+                </th>
+            </tr>
+        </thead>
+        <tbody>
+        </tbody>
+    </table>
+</section>
+
+<script>
+    $(document).ready(
+        function() {
+            $.getJSON( "../resources/options.json", function( data ) {
+                console.log( 'gotit' ) ;
+                var options = [] ;
+                $.each( data, function( key, value ) {
+                    options.push( key ) ;
+                    console.log( key ) ;
+                } ) ;
+
+                options.sort( function(a,b) {
+                    return a.toLowerCase().localeCompare( b.toLowerCase() ) ;
+                }) ;
+
+                for( var i = 0; i < options.length; ++i ) {
+                    $(".option_table > tbody").append(
+                        '<tr>'
+                        + '<td>' + options[i] + '</td>'
+                        + '<td>' + data[options[i]]['description'] + '</td>'
+                        + '<td>' + ( data[options[i]].length == 0 ? "N/A" : ( "(" + data[options[i]].default.join( ", " ) + ")" ) + '</td>' )
+                        + '</tr>'
+                    )
+                }
+
+                $( ".option_table" ).DataTable(
+                    {
+                        "paging": false,
+                        "language": {
+                            "search": "Search command-line options:"
+                        }
+                    }
+                ) ;
+                $('.dataTables_filter').css('float', 'left') ;
+            }) ;
+        }
+    ) ;
+</script>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -131,10 +126,10 @@
 					<a href="../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
 
 	</body>
 </html>

Index: doc/html/qctool/documentation/diagram_of_options.html
==================================================================
--- doc/html/qctool/documentation/diagram_of_options.html
+++ doc/html/qctool/documentation/diagram_of_options.html
@@ -1,25 +1,13 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
 
-		<script type="text/javascript" src="../js/jquery-1.4.2.min.js"></script>
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
-
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
 		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
 		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
@@ -28,32 +16,32 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-		<section class="main_text">
-			<h2>Diagram of options</h2>
-			<p>Data flows through qctool in a fixed pipeline according to the schema below.
-				Relevant options for each pipeline stage are noted.  (See also the <a href="../documentation/alphabetical_options.html">alphabetical list of options</a>).</p>
-			<div class="display_diagram">
-				<object data="../style/images/qctool_cheatsheet.svg" width="800" type="image/svg+xml" align="center">
-					</object>
-			</div>
-			<p>See also the <a href="alphabetical_options.html">alphabetical list of options</a>.</p>
-		</section>
-
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+			<img src="../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Diagram of options</h2>
+    <p>Data flows through qctool in a fixed pipeline according to the schema below.
+        Relevant options for each pipeline stage are noted.  (See also the <a href="../documentation/alphabetical_options.html">alphabetical list of options</a>).</p>
+    <div class="display_diagram">
+        <object data="../style/images/qctool_cheatsheet.svg" style="position: relative; left: -100px; width: 1000px; margin-left:auto; margin-right: auto" width="1000" type="image/svg+xml" align="center">
+            </object>
+    </div>
+    <p>See also the <a href="alphabetical_options.html">alphabetical list of options</a>.</p>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -83,10 +71,10 @@
 					<a href="../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
 
 	</body>
 </html>

Index: doc/html/qctool/documentation/download.html
==================================================================
--- doc/html/qctool/documentation/download.html
+++ doc/html/qctool/documentation/download.html
@@ -1,35 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../js/jquery-1.4.2.min.js"></script>
-		<script type="text/javascript" src="../js/jquery.ba-hashchange.min.js"></script>
+
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../js/local.js"></script>
-
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
-
-		<script type="text/javascript">
-			$(document).ready(
-				function() {
-					setFirstPage( "overview" ) ;
-				}
-			) ;
-		</script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
 		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -36,80 +16,116 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Obtaining QCTOOL</h2>
-				<p>
-					QCTOOL is available either as binaries or as source code.  The recommended approach is to download and compile
-					the QCTOOL source code on the machine(s) you will be working on.  However, for convenience a small number of
-					precompiled binary packages can be found <a href="http://www.well.ox.ac.uk/~gav/resources/">here</a>.
-					These provided as-is and will not work on all platforms; if a suitable version is not available please
-					download the QCTOOL source code and compile instead.
-				</p>
-				<h3>
-					Downloading source
-				</h3>
-				<p>
-					The source code to qctool is available as a mercurial repository
-					hosted <a href="http://www.bitbucket.org/gavinband/qctool">on bitbucket</a>.
-					To obtain source code, use the mercurial command-line client <code>hg</code>, a GUI client such as
-					<a href="https://www.sourcetreeapp.com">SourceTree</a>, or alternatively download a
-					tarball from the <a href="https://bitbucket.org/gavinband/qctool/downloads/?tab=branches">Downloads page on bitbucket</a>.
-				</p>
-				<p>
-					Please note QCTOOL v2 is currently in 'release candidate' status, please make sure you download code for the <code>beta</code> branch.
-					For example, using the <code>hg</code> command-line tool, the command
-				</p>
-					<div class="terminal">
-						<code>$ hg clone -r beta https://gavinband@bitbucket.org/gavinband/qctool</code>
-					</div>
-					<p>
-					will download source code for the latest beta branch and place it in a newly created <code>qctool</code> directory.
-				</p>
-				<h3>
-					Compiling
-				</h3>
-				<p>
-					Having downloaded the source code (and extracted it if necessary), a basic compilation sequence would then be:
-				</p>
-<pre>
-$ cd qctool
-$ ./waf-1.5.18 configure
-$ ./waf-1.5.18
-</pre>
-				<p>
-					If all is successful, this produces an executable
-					<code>./build/release/qctool_v2.0-&lt;version&gt;</code>
-				</p>
-				</div>
-			<p>
-				You can check qctool is working by running it:
-			</p>
-			<pre>
-$ ./build/release/qctool_v2.0-&lt;version&gt; -help
-</pre>
-			<p>which should print out a list of options.</p>
-			<h3>Further information</h3>
-			<p>
-				The <a href="https://bitbucket.org/gavinband/qctool/wiki/Home">QCTOOL wiki</a> contains further information
-				which may be useful if you are unable to compile QCTOOL or need to tweak compilation for specific platforms.
-			</p>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+			<img src="../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Obtaining QCTOOL</h2>
+        <p>
+
+            QCTOOL is available either as binaries or as source code. The recommended approach is to download and compile the QCTOOL
+            source code on the machine(s) you will be working on. However, for convenience a small number of precompiled binary packages are
+            provided below. These provided as-is and will not work on all platforms; if a suitable version is not available please download
+            the QCTOOL source code and compile instead.
+
+        </p>
+        <table class="download">
+            <colgroup>
+                <col span="1" style="width: 15%;">
+                <col span="1" style="width: 25%;">
+                <col span="1" style="width: 60%;">
+            </colgroup>
+            <thead>
+                <tr><th>Version</th>
+                <th>Platform</th>
+                <th>file</th></tr>
+            </thead>
+            <tbody>
+                <tr><td>v2.2.1<sup>*</sup></td><td>Mac OS X (Apple)</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.2.1-osx-m1.tgz">qctool_v2.2.1-osx-m1.tgz</a></td></tr>
+                <tr><td>v2.2.0<sup>*</sup></td><td>Mac OS X (Intel)</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.2.0-osx.tgz">qctool_v2.2.0-osx.tgz</a></td></tr>
+                <tr><td>v2.2.0<sup>*</sup></td><td>CentOS Linux 7.8</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.2.0-CentOS_Linux7.8.2003-x86_64.tgz">qctool_v2.2.0-CentOS_Linux7.8.2003-x86_64.tgz</a></td></tr>
+                <tr><td>v2.0.8</td><td>Mac OS X</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.0.8-osx.tgz">qctool_v2.0.8-osx.tgz</a></td></tr>
+                <tr><td>v2.0.8</td><td>CentOS Linux 7.6</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.0.8-CentOS_Linux7.6.1810-x86_64.tgz">qctool_v2.0.8-CentOS_Linux7.6.1810-x86_64.tgz</a></td></tr>
+                <tr><td>v2.2.0</td><td>Mac OS X</td><td><a href="https://www.chg.ox.ac.uk/~gav/resources/qctool_v2.2.0-osx.tgz">qctool_v2.2.0-osx.tgz</a></td></tr>
+                <tr><td>v2.2.0</td><td>CentOS Linux 7.8</td><td><a href="https://www.chg.ox.ac.uk/~gav/resources/qctool_v2.2.0-CentOS_Linux7.8.2003-x86_64.tgz">qctool_v2.2.0-CentOS_Linux7.8.2003-x86_64.tgz</a></td></tr>
+                <tr><td>v2.2.5</td><td>Mac OS X, Apple silicon</td><td><a href="https://www.chg.ox.ac.uk/~gav/resources/qctool_v2.2.5-osx-arm64.tgz">qctool_v2.2.5-osx-arm64.tgz</a></td></tr>
+                <tr><td>v2.2.5</td><td>CentOS Linux 7.9</td><td><a href="https://www.well.ox.ac.uk/~gav/resources/qctool_v2.2.5-CentOS_Linux7.9-x86_64.tgz">qctool_v2.2.5-CentOS_Linux7.9-x86_64.tgz</a></td></tr>
+            </tbody>
+        </table>
+        <small><sup>*</sup> This is the recommended version; older versions are unsupported but may still appear here for posterity.</small>
+        <h3>
+            Downloading source
+        </h3>
+        <p>
+            The source code to qctool is available as a <a href="https://fossil-scm.org">fossil</a> repository
+            at <a href="https://code.enkre.net/qctool">https://code.enkre.net/qctool</a>.
+            To obtain source code, use the fossil command-line client, or alternatively download a
+            tarball from this table.  (Note that this currently generates a tarball on the fly, which may take a while).
+        </p>
+        <table class="download">
+            <colgroup>
+                <col span="1" style="width: 40%;">
+                <col span="1" style="width: 60%;">
+            </colgroup>
+            <thead>
+                <tr><th>Version</th><th>file</th>
+            </thead>
+            <tbody>
+                <tr><td>release<sup>*</sup></td><td><a href="https://code.enkre.net/qctool/tarball/release/qctool.tgz">https://code.enkre.net/qctool/tarball/release/qctool.tgz</a></td>
+                <tr><td>development</td><td><a href="https://code.enkre.net/qctool/zip/tarball/qctool.tgz">https://code.enkre.net/qctool/tarball/trunk/qctool.tgz</a></td>
+            </tbody>
+        </table>
+        <small><sup>*</sup> This is the recommended version; only use the development version if you want to try recently implemented features.</small>
+        <h3>
+            Versioning scheme
+        </h3>
+        <p>
+            As of version 2.1, QCTOOL will follow a versioning scheme whereby odd minor numbers (2.1.x etc.) represent
+            development work while even numbers (2.2.x etc.) represent release versions.
+            The current latest release versions are 2.2 version.
+        </p>
+        <h3>
+            Compiling
+        </h3>
+        <p>
+            Having downloaded the source code (and extracted it if necessary), a basic compilation sequence would then be:
+        </p>
+<pre>
+$ cd qctool
+$ ./waf configure
+$ ./waf
+</pre>
+        <p>
+            If all is successful, this produces an executable
+            <code>./build/release/qctool_v&lt;version&gt;</code>
+        </p>
+        </div>
+    <p>
+        You can check qctool is working by running it:
+    </p>
+    <pre>
+$ ./build/release/qctool_v&lt;version&gt; -help
+</pre>
+    <p>which should print out a list of options.</p>
+    <h3>Further information</h3>
+    <p>
+        The <a href="https://code.enkre.net/qctool/wiki?name=Home">QCTOOL wiki</a> contains further information
+        which may be useful if you are unable to compile QCTOOL or need to tweak compilation for specific platforms.
+    </p>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -139,10 +155,10 @@
 					<a href="../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/adding_to_sample_file.html
==================================================================
--- doc/html/qctool/documentation/examples/adding_to_sample_file.html
+++ doc/html/qctool/documentation/examples/adding_to_sample_file.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,118 +16,118 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Manipulating the sample file</h2>
-				<div class="task">
-					<div class="task_name">
-						Add genotype dosages for given variants to the sample file
-					</div>
-					<div class="task_notes">
-						The <code>-condition-on</code> option can be used to extract genotype dosages for specific given variants
-						and place them as columns in the sample file.  E.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example_#.gen -s example.sample -os example.sample -condition-on rs1234
-					</div>
-					<div class="task_notes">
-						This adds a column with name <span class="monospace">rs1234:additive_dosage</span>, containing the
-						additive dosage from the SNP.  You can also select SNPs by position:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example_#.gen -s example.sample -os example.sample -condition-on pos~03:10001
-					</div>
-					<div class="task_notes">
-						It is also possible to select dominant, recessive, or heterozygote dosages from the SNP.  For example,
-						to select additive and heterozygote dosages:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example_#.gen 
-						-s example.sample 
-						-os example.sample 
-						-condition-on "rs1234(add|het)"
-					</div>
-					<div class="task_notes">
-						<p>
-						<b>Note:</b> as shown above, it is sometimes necessary to place the argument in quotation marks
-						to avoid problems with the system shell.
-					</p>
-						<p>
-							The full syntax for this option is: <code>-condition-on [selector~]value[(dosage1[|dosage2...])]</code>
-							where <code>selector</code> is either "rsid", "snpid", or "position" or "pos", <code>value</code>
-							is a string specifying the ID or position of the required variant, and dosage can be
-							<code>add</code>, <code>dom</code>, <code>rec</code>, <code>het</code>.
-							The value <code>gen</code> adds both additive and heterozygote dosages.
-						</p>
-						<p>
-							Note: these options behave in a similar way to the <code>-condition_on</code> option
-							found in <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html">SNPTEST</a>,
-							but may be preferable because they can write the data into the sample file directly where it can be
-							later inspected.
-						</p>
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Quantile-normalise columns of the sample file
-					</div>
-					<div class="task_notes">
-						The <code>-quantile-normalise</code> option takes a numerical column in the sample file,
-						and adds a new column reflecting the same data after mapping empirical quantiles to those of a 
-						standard gaussian distribution.  E.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -os example.sample -quantile-normalise column1
-					</div>
-					<div class="task_notes">
-						<p>
-							This adds a column with name <code>column1:quantile-normalised</code> to the sample file.
-							The specified columns must be continuous, i.e. of type 'P' or 'C'.
-							(Note that even though the SNPs are not used here, currently you must still specify the -g option.)
-						</p>
-						<p>
-							The screen output (and log file) will contain details of the column values before and after normalisation.
-						</p>
-						<p>
-							<b>Technical note</b>: specifically, suppose there are <em>N</em> samples.  This option
-							first computes the quantiles <em>q<sub>j</sub> = &Phi;<sup>-1</sup>(j/N+1)</em> for each <em>j=1,...,N</em>,
-							where <em>&Phi;</em> is the cumulative distribution function of a standard Gaussian.
-							The normalised value for sample <em>i</em> is then obtained as <em>n<sub>i</sub> = q<sub>r(i)</sub></em>
-								where <em>r(i)</em> is the rank of the sample among the values of the given column.
-								If several samples are tied, we instead set <em>n<sub>i</sub></em> to the average of q<sub>r(i)</sub>
-								across all samples with the same column value.  This makes the normalised value well-defined
-								(i.e. independent of the ranking of these samples), and means that samples with
-								identical values of the input column will also have identical values
-								in the computed quantile-normalised column.
-						</p>
-						<p>
-							Note that <code>-quantile-normalise</code> can be given a list of columns:
-						</p>
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -os example.sample -quantile-normalise column1 column2...
-					</div>
-					<div class="task_notes">
-						This produces a set of quantile-normalised columns, one for each specified input column.
-					</div>
-				</div>
-			</div>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Manipulating the sample file</h2>
+        <div class="task">
+            <div class="task_name">
+                Add genotype dosages for given variants to the sample file
+            </div>
+            <div class="task_notes">
+                The <code>-condition-on</code> option can be used to extract genotype dosages for specific given variants
+                and place them as columns in the sample file.  E.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example_#.gen -s example.sample -os example.sample -condition-on rs1234
+            </div>
+            <div class="task_notes">
+                This adds a column with name <span class="monospace">rs1234:additive_dosage</span>, containing the
+                additive dosage from the SNP.  You can also select SNPs by position:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example_#.gen -s example.sample -os example.sample -condition-on pos~03:10001
+            </div>
+            <div class="task_notes">
+                It is also possible to select dominant, recessive, or heterozygote dosages from the SNP.  For example,
+                to select additive and heterozygote dosages:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example_#.gen 
+                -s example.sample 
+                -os example.sample 
+                -condition-on "rs1234(add|het)"
+            </div>
+            <div class="task_notes">
+                <p>
+                <b>Note:</b> as shown above, it is sometimes necessary to place the argument in quotation marks
+                to avoid problems with the system shell.
+            </p>
+                <p>
+                    The full syntax for this option is: <code>-condition-on [selector~]value[(dosage1[|dosage2...])]</code>
+                    where <code>selector</code> is either "rsid", "snpid", or "position" or "pos", <code>value</code>
+                    is a string specifying the ID or position of the required variant, and dosage can be
+                    <code>add</code>, <code>dom</code>, <code>rec</code>, <code>het</code>.
+                    The value <code>gen</code> adds both additive and heterozygote dosages.
+                </p>
+                <p>
+                    Note: these options behave in a similar way to the <code>-condition_on</code> option
+                    found in <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html">SNPTEST</a>,
+                    but may be preferable because they can write the data into the sample file directly where it can be
+                    later inspected.
+                </p>
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Quantile-normalise columns of the sample file
+            </div>
+            <div class="task_notes">
+                The <code>-quantile-normalise</code> option takes a numerical column in the sample file,
+                and adds a new column reflecting the same data after mapping empirical quantiles to those of a 
+                standard gaussian distribution.  E.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -os example.sample -quantile-normalise column1
+            </div>
+            <div class="task_notes">
+                <p>
+                    This adds a column with name <code>column1:quantile-normalised</code> to the sample file.
+                    The specified columns must be continuous, i.e. of type 'P' or 'C'.
+                    (Note that even though the SNPs are not used here, currently you must still specify the -g option.)
+                </p>
+                <p>
+                    The screen output (and log file) will contain details of the column values before and after normalisation.
+                </p>
+                <p>
+                    <b>Technical note</b>: specifically, suppose there are <em>N</em> samples.  This option
+                    first computes the quantiles <em>q<sub>j</sub> = &Phi;<sup>-1</sup>(j/N+1)</em> for each <em>j=1,...,N</em>,
+                    where <em>&Phi;</em> is the cumulative distribution function of a standard Gaussian.
+                    The normalised value for sample <em>i</em> is then obtained as <em>n<sub>i</sub> = q<sub>r(i)</sub></em>
+                        where <em>r(i)</em> is the rank of the sample among the values of the given column.
+                        If several samples are tied, we instead set <em>n<sub>i</sub></em> to the average of q<sub>r(i)</sub>
+                        across all samples with the same column value.  This makes the normalised value well-defined
+                        (i.e. independent of the ranking of these samples), and means that samples with
+                        identical values of the input column will also have identical values
+                        in the computed quantile-normalised column.
+                </p>
+                <p>
+                    Note that <code>-quantile-normalise</code> can be given a list of columns:
+                </p>
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -os example.sample -quantile-normalise column1 column2...
+            </div>
+            <div class="task_notes">
+                This produces a set of quantile-normalised columns, one for each specified input column.
+            </div>
+        </div>
+    </div>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -169,8 +159,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/altering_id_data.html
==================================================================
--- doc/html/qctool/documentation/examples/altering_id_data.html
+++ doc/html/qctool/documentation/examples/altering_id_data.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,108 +16,109 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Altering variant identifying data</h2>
-				<div class="task">
-					<div class="task_name">
-						Filling in missing chromosome information
-					</div>
-					<div class="task_notes">
-						The <code>-assume-chromosome</code> option fills in any missing chromosome information in input data
-						with the specified value.  E.g.:
-					</div>
-					
-					<div class="task_command_line">
-						$ qctool -g &lt;input file&gt; -og output.bgen -assume-chromosome &lt;chromosome&gt;
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Updating identifying data
-					</div>
-					<div class="task_notes">
-						The <code>-map-id-data</code> option can be used to update the identifying data for each variant
-						with a new set of data. E.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g &lt;input file(s)&gt; -og output.bgen -map-id-data &lt;map file&gt; [+other options]
-					</div>
-					<div class="task_notes">
-						<p>Ffor example, this might be useful when updating files to match a new genome build.</p>
-						<p>The "map" file given to <code>-map-id-data</code> must be a text file
-						with twelve named columns, in the following order: the current SNPID, rsid, chromosome, position, first and second alleles,
-						followed by the desired updated SNPID, rsid, chromosome, position and alleles.  The first line is treated as column names
-						(currently it doesn't matter what these are called.)  Variants not in this file are not affected by the mapping, and will
-						be output unchanged.
-					</p>
-					<p>Matching of variants to the map file is controlled by the <code>-compare-variants-by</code>
-						option - see the <a href="sorting.html">page on sorting data</a> for more on this option.</p>
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Aligning alleles
-					</div>
-					<div class="task_notes">
-						<p>
-						The <code>-strand</code> option can be used to update alleles and flip genotype data according
-						to strand information supplied in an external file.  The general format is:
-					</p>
-					</div>
-					<div class="task_command_line">
-						$ qctool -g &lt;input file(s)&gt; -og output.bgen -strand &lt;strand file&gt; [-flip-to-match-allele &lt;column name&gt;]
-					</div>
-					<div class="task_notes">
-						<p>The most common use of this option is to align alleles to match the forward strand of a reference sequence,
-							and to flip genotypes so that the first allele is the reference allele.
-						</p>
-						<p>
-							Strand files should have six columns which must be named as follows:
-							<code>SNPID</code>,
-							<code>rsid</code>,
-							<code>chromosome</code>,
-							<code>position</code>,
-							<code>alleleA</code>,
-							<code>alleleB</code>,
-							<code>strand</code>, plus any additional columns.
-							Strand information is read from the <code>strand</code> column.
-							Alleles at variants where the strand is '+' will be processed unchanged; alleles
-							at variants where the strand is '-' will be complemented (i.e. A&lt;-&gt;T, G&lt;-&gt;C);
-							alleles at variants which have missing strand information - encoded as "?", or "NA", or for variants
-							that are missing from the file - will be omitted from the output.
-						</p>
-						<p>
-							The <code>-compare-variants-by</code> option controls how variants between the genotype data
-							and the strand file.
-							See <a href="sorting.html">the page on sorting</a> for more information.
-						</p>
-						<p>
-							If the <code>-flip-to-match-allele</code> option is given, the strand file must contain a column
-							with the specified name.  Each value in this column should be one of the two alleles of the variant.
-							Alleles and genotypes are then also recoded so that the allele in the specified
-							column is the first allele and the other allele the second allele.
-							Note that the strand alignment is applied first - e.g. if the variant alleles are 'A' and 'G' and the
-							strand is -, <code>-flip-to-match-allele</code> the column should contain 'T' or 'C'.
-						</p>
-					</div>
-				</div>
-			</div>
-		</section>
-
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Altering variant identifying data</h2>
+        <div class="task">
+            <div class="task_name">
+                Filling in missing chromosome information
+            </div>
+            <div class="task_notes">
+                The <code>-assume-chromosome</code> option fills in any missing chromosome information in input data
+                with the specified value.  E.g.:
+            </div>
+
+            <div class="task_command_line">
+                $ qctool -g &lt;input file&gt; -og output.bgen -assume-chromosome &lt;chromosome&gt;
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Updating identifying data
+            </div>
+            <div class="task_notes">
+                The <code>-map-id-data</code> option can be used to update the identifying data for each variant
+                with a new set of data. E.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g &lt;input file(s)&gt; -og output.bgen -map-id-data &lt;map file&gt; [+other options]
+            </div>
+            <div class="task_notes">
+                <p>Ffor example, this might be useful when updating files to match a new genome build.</p>
+                <p>The "map" file given to <code>-map-id-data</code> must be a text file
+                with twelve named columns, in the following order: the current SNPID, rsid, chromosome, position, first and second alleles,
+                followed by the desired updated SNPID, rsid, chromosome, position and alleles.  The first line is treated as column names
+                (currently it doesn't matter what these are called.)  Variants not in this file are not affected by the mapping, and will
+                be output unchanged.
+            </p>
+            <p>Matching of variants to the map file is controlled by the <code>-compare-variants-by</code>
+                option - see the <a href="sorting.html">page on sorting data</a> for more on this option.</p>
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Aligning alleles
+            </div>
+            <div class="task_notes">
+                <p>
+                The <code>-strand</code> option can be used to update alleles and flip genotype data according
+                to strand information supplied in an external file.  The general format is:
+            </p>
+            </div>
+            <div class="task_command_line">
+                $ qctool -g &lt;input file(s)&gt; -og output.bgen -strand &lt;strand file&gt; [-flip-to-match-allele &lt;column name&gt;]
+            </div>
+            <div class="task_notes">
+                <p>The most common use of this option is to align alleles to match the forward strand of a reference sequence,
+                    and to flip genotypes so that the first allele is the reference allele.
+                </p>
+                <p>
+                    Strand files should have six columns which must be named as follows:
+                    <code>SNPID</code>,
+                    <code>rsid</code>,
+                    <code>chromosome</code>,
+                    <code>position</code>,
+                    <code>alleleA</code>,
+                    <code>alleleB</code>,
+                    <code>strand</code>, plus any additional columns.
+                    Strand information is read from the <code>strand</code> column.
+                    Alleles at variants where the strand is '+' will be processed unchanged; alleles
+                    at variants where the strand is '-' will be complemented (i.e. A&lt;-&gt;T, G&lt;-&gt;C);
+                    alleles at variants which have missing strand information - encoded as "?", or "NA", or for variants
+                    that are missing from the file - will be omitted from the output.
+                </p>
+                <p>
+                    The <code>-compare-variants-by</code> option controls how variants between the genotype data
+                    and the strand file.
+                    See <a href="sorting.html">the page on sorting</a> for more information.
+                </p>
+                <p>
+                    If the <code>-flip-to-match-allele</code> option is given, the strand file must contain a column
+                    with the specified name.  Each value in this column should be one of the two alleles of the variant.
+                    Alleles and genotypes are then also recoded so that the allele in the specified
+                    column is the first allele and the other allele the second allele.
+                    Note that the strand alignment is applied first - e.g. if the variant alleles are 'A' and 'G' and the
+                    strand is -, <code>-flip-to-match-allele</code> the column should contain 'T' or 'C'.
+                </p>
+            </div>
+        </div>
+    </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -159,8 +150,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/annotating.html
==================================================================
--- doc/html/qctool/documentation/examples/annotating.html
+++ doc/html/qctool/documentation/examples/annotating.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,126 +16,127 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Computing annotations</h2>
-			<div class="task">
-				<div class="task_name">
-					Annotating with sequence bases
-				</div>
-				<div class="task_notes">
-					The <code>-annotate-sequence</code> option can be used to extract sequence bases from FASTA file(s)
-					and annotate the output file with them.  E.g.:
-				</div>
-				
-				<div class="task_command_line">
-					$ qctool -g &lt;input file&gt; -osnp output.txt -annotate-sequence chr#.fa reference
-				</div>
-				<div class="task_notes">
-					<b>Note</b> Currently, to be used with this option, FASTA files must be split into one file
-					per chromosome; the chromosome is then inferred from the file name (using the chromosomal wildcard character #) as in the command above.  Also,
-					it's assumed that the FASTA file starts at base pair 1 so that bases may be looked up in the file.
-					I have used this to annotate alleles from the human reference sequence
-					(e.g. <a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/">this one</a>)
-					or ancestral sequence (e.g. <a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/">this one</a>).
-				</div>
-				<div class="task_name">
-					Annotating with flanking sequence
-				</div>
-				<div class="task_notes">
-					When using <code>-annotate-sequence</code>, the <code>-flanking</code> option tells QCTOOL to additionally annotate output with flanking sequence
-					from FASTA files.  For example:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g &lt;input file&gt; -osnp output.txt -annotate-sequence chr#.fa reference -flanking 200 200
-				</div>
-				<div class="task_notes">
-					This will output the 200bp from the FASTA file preceding and following each variant, and the
-					bases covered by the variant's alleles.
-				</div>
-			</div>
-			<div class="task">
-				<div class="task_name">
-					Annotating with genetic map information
-				</div>
-				<div class="task_notes">
-					The <code>-annotate-genetic-map</code> option can be used to output genetic (recombination) map coordinates
-					for each variant, e.g:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g &lt;input file(s)&gt; -annotate-genetic-map genetic_map_chr#.txt -osnp output.txt
-				</div>
-				<div class="task_notes">
-					<p>The genetic map files should be in the 'hapmap' format, i.e. one file per chromosome
-						with three columns specifying position, recombination rate in centimorgans per megabase,
-						and the accumulated recombination map position.  It is expected that genetic map files
-						are split by chromosome, and the chromosome is inferred from the filename.
-						Suitable genetic map files for human build 37 can be found
-						on the <a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#reference">IMPUTE2 website</a>.
-						The output will contain columns <Code>cM_per_Mb</code> and <code>cM_from_start_of_chromosome</code>.
-					</p>
-				</div>
-			</div>
-
-			<div class="task">
-				<div class="task_name">
-					Interval annotations
-				</div>
-				<div class="task_notes">
-					The <code>-annotate-bed3</code> and <code>-annotated-bed4</code> options can be used to compute
-					membership of the intervals 
-					in a <a href="https://genome.ucsc.edu/FAQ/FAQformat.html">BED file</a>, or
-					the value(s) assigned to intervals in a bed file, at each input variant:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g &lt;input file(s)&gt; -annotate-bed3 file1.bed -annotated-bed4 file2.bed
-				</div>
-				<div class="task_notes">
-					<p>
-						Output will contain a column with the same name as the BED file (minus the
-						<code>.bed</code> or <code>.bed.gz</code> extension).
-						For <code>-annotate-bed3</code>, this column will contain a 1 if the variant was contained
-						in an interval in the file, or 0 otherwise.  For <code>-annotate-bed4</code>, the column
-						will contain a comma-separated list of values from the fourth column of the BED file,
-						for those intervals which the variant is in.
-					</p>
-					<p>
-						<b>Note:</b> BED files are assumed to contain intervals in 0-based, right-open coordinates, while
-						QCTOOL by convention assumes genotype data is expressed in 1-based coordinates.  QCTOOL handles this
-						internally by adding 1 to the start coordinate of each interval.
-					</p>
-					<p>
-						It's also possible to compute membership of intervals in a set of BED files in the same column.
-						The general syntax is
-						<code>-annotate-bed[3|4] file1.bed[,file2.bed[,...]][+&lt;N&gt;bp]</code>.  
-						This internally concatenates <code>file1.bed</code>, <code>file2.bed</code>, etc. into a single
-						list of intervals.  Further, if the <code>+&lt;N&gt;bp</code> modifier is added, where <em>N</em>
-						is an integer, then all intervals are expanded by <em>N</em> bases to the left and the right
-						before processing.  For example:
-					</p>
-				</div>
-				<div class="task_command_line">
-					$ qctool -g &lt;input file(s)&gt; -annotate-bed4 file1.bed,file2.bed+100bp
-				</div>
-				<div class="task_notes">
-					This command will annotate each variant with the values of all intervals that it lies within 100bp of.
-				</div>
-			</div>
-		</section>
-
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Computing annotations</h2>
+    <div class="task">
+        <div class="task_name">
+            Annotating with sequence bases
+        </div>
+        <div class="task_notes">
+            The <code>-annotate-sequence</code> option can be used to extract sequence bases from FASTA file(s)
+            and annotate the output file with them.  E.g.:
+        </div>
+
+        <div class="task_command_line">
+            $ qctool -g &lt;input file&gt; -osnp output.txt -annotate-sequence chr#.fa reference
+        </div>
+        <div class="task_notes">
+            <b>Note</b> Currently, to be used with this option, FASTA files must be split into one file
+            per chromosome; the chromosome is then inferred from the file name (using the chromosomal wildcard character #) as in the command above.  Also,
+            it's assumed that the FASTA file starts at base pair 1 so that bases may be looked up in the file.
+            I have used this to annotate alleles from the human reference sequence
+            (e.g. <a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/">this one</a>)
+            or ancestral sequence (e.g. <a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/">this one</a>).
+        </div>
+        <div class="task_name">
+            Annotating with flanking sequence
+        </div>
+        <div class="task_notes">
+            When using <code>-annotate-sequence</code>, the <code>-flanking</code> option tells QCTOOL to additionally annotate output with flanking sequence
+            from FASTA files.  For example:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g &lt;input file&gt; -osnp output.txt -annotate-sequence chr#.fa reference -flanking 200 200
+        </div>
+        <div class="task_notes">
+            This will output the 200bp from the FASTA file preceding and following each variant, and the
+            bases covered by the variant's alleles.
+        </div>
+    </div>
+    <div class="task">
+        <div class="task_name">
+            Annotating with genetic map information
+        </div>
+        <div class="task_notes">
+            The <code>-annotate-genetic-map</code> option can be used to output genetic (recombination) map coordinates
+            for each variant, e.g:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g &lt;input file(s)&gt; -annotate-genetic-map genetic_map_chr#.txt -osnp output.txt
+        </div>
+        <div class="task_notes">
+            <p>The genetic map files should be in the 'hapmap' format, i.e. one file per chromosome
+                with three columns specifying position, recombination rate in centimorgans per megabase,
+                and the accumulated recombination map position.  It is expected that genetic map files
+                are split by chromosome, and the chromosome is inferred from the filename.
+                Suitable genetic map files for human build 37 can be found
+                on the <a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#reference">IMPUTE2 website</a>.
+                The output will contain columns <Code>cM_per_Mb</code> and <code>cM_from_start_of_chromosome</code>.
+            </p>
+        </div>
+    </div>
+
+    <div class="task">
+        <div class="task_name">
+            Interval annotations
+        </div>
+        <div class="task_notes">
+            The <code>-annotate-bed3</code> and <code>-annotated-bed4</code> options can be used to compute
+            membership of the intervals 
+            in a <a href="https://genome.ucsc.edu/FAQ/FAQformat.html">BED file</a>, or
+            the value(s) assigned to intervals in a bed file, at each input variant:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g &lt;input file(s)&gt; -annotate-bed3 file1.bed -annotated-bed4 file2.bed
+        </div>
+        <div class="task_notes">
+            <p>
+                Output will contain a column with the same name as the BED file (minus the
+                <code>.bed</code> or <code>.bed.gz</code> extension).
+                For <code>-annotate-bed3</code>, this column will contain a 1 if the variant was contained
+                in an interval in the file, or 0 otherwise.  For <code>-annotate-bed4</code>, the column
+                will contain a comma-separated list of values from the fourth column of the BED file,
+                for those intervals which the variant is in.
+            </p>
+            <p>
+                <b>Note:</b> BED files are assumed to contain intervals in 0-based, right-open coordinates, while
+                QCTOOL by convention assumes genotype data is expressed in 1-based coordinates.  QCTOOL handles this
+                internally by adding 1 to the start coordinate of each interval.
+            </p>
+            <p>
+                It's also possible to compute membership of intervals in a set of BED files in the same column.
+                The general syntax is
+                <code>-annotate-bed[3|4] file1.bed[,file2.bed[,...]][+&lt;N&gt;bp]</code>.  
+                This internally concatenates <code>file1.bed</code>, <code>file2.bed</code>, etc. into a single
+                list of intervals.  Further, if the <code>+&lt;N&gt;bp</code> modifier is added, where <em>N</em>
+                is an integer, then all intervals are expanded by <em>N</em> bases to the left and the right
+                before processing.  For example:
+            </p>
+        </div>
+        <div class="task_command_line">
+            $ qctool -g &lt;input file(s)&gt; -annotate-bed4 file1.bed,file2.bed+100bp
+        </div>
+        <div class="task_notes">
+            This command will annotate each variant with the values of all intervals that it lies within 100bp of.
+        </div>
+    </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -177,8 +168,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/basic.html
==================================================================
--- doc/html/qctool/documentation/examples/basic.html
+++ doc/html/qctool/documentation/examples/basic.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,68 +16,78 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Basic examples</h2>
-				<div class="tutorial_header">
-				This page shows command lines used to carry out common tasks with QCTOOL.
-				We assume the program is being run from a directory containing a sample file <span class="monospace">example.sample</span> and 22 GEN files named <span class="monospace">example_01.gen, example_02.gen</span>, etc.
-				As one of the first examples, we convert these files to BGEN format and use this in subsequent examples.
-				 See also the <a href="../../documentation/alphabetical_options.html">list of options</a>.
-				</div>
-				<div class="tutorial_separator">
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Run qctool
-					</div>
-					<div class="task_command_line">
-						$ qctool
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						View the program usage page
-					</div>
-					<div class="task_command_line">
-						$ qctool -help | less
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Get a computer-readable list of options
-					</div>
-					<div class="task_command_line">
-						$ qctool -spec
-					</div>
-					<div class="task_notes">
-						<b>Note:</b> output is is JSON format.  This option is used to construct the <a href="../alphabetical_options.html">table of options</a>.
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Capture screen output in log file
-					</div>
-					<div class="task_command_line">
-						$ qctool [other options] -log log.txt
-					</div>
-				</div>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Basic examples</h2>
+        <div class="tutorial_header">
+
+        This and the other pages in the 'examples' menu show some basic command lines used to carry out common tasks
+        with QCTOOL. For more information see also the <a href="../../documentation/alphabetical_options.html">list of
+        options</a> and the <a href="../../documentation/diagram_of_options.html">diagram of options</a>."
+
+        </div>
+        <div class="tutorial_separator">
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Run qctool
+            </div>
+            <div class="task_command_line">
+                $ qctool
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                View the program usage page
+            </div>
+            <div class="task_command_line">
+                $ qctool -help | less
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Get a computer-readable list of options
+            </div>
+            <div class="task_command_line">
+                $ qctool -spec
+            </div>
+            <div class="task_notes">
+                <b>Note:</b> output is is JSON format.  This option is used to construct the <a href="../alphabetical_options.html">table of options</a>.
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Capture screen output in log file
+            </div>
+            <div class="task_command_line">
+                $ qctool [other options] -log log.txt
+            </div>
+        </div>
+
+        <div class="task">
+            <div class="task_name">
+                Get some summary information about a genotypes file
+            </div>
+            <div class="task_command_line">
+                $ qctool -g &lt;genotypes file&gt;
+            </div>
+        </div>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -94,19 +94,20 @@
 					<li><a href="../../documentation/examples/basic.html">Basic usage</a></li>
 					<li><a href="../../documentation/examples/converting.html">Converting file formats</a></li>
 					<li><a href="../../documentation/examples/converting_genotypes.html">Thresholding genotypes</a></li>
 					<li><a href="../../documentation/examples/sorting.html">Sorting and reordering data</a></li>
 					<li><a href="../../documentation/examples/combining.html">Combining datasets</a></li>
-<li><a href="../../documentation/examples/merging.html">Merging in variants</a></li>
+					<li><a href="../../documentation/examples/merging.html">Merging in variants</a></li>
 					<li><a href="../../documentation/examples/altering_id_data.html">Altering variant identifying data</a></li>
 					<li><a href="../../documentation/examples/pipelining.html">Using qctool in a pipeline</a></li>
 					<li><a href="../../documentation/examples/filtering_samples.html">Filtering samples</a></li>
-<li><a href="../../documentation/examples/filtering_variants.html">Filtering variants</a></li>
+					<li><a href="../../documentation/examples/filtering_variants.html">Filtering variants</a></li>
 					<li><a href="../../documentation/examples/summary_statistics.html">Computing summary statistics</a></li>
 					<li><a href="../../documentation/examples/annotating.html">Computing annotations</a></li>
-					<li><a href="../../documentation/examples/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
-<li><a href="../../documentation/examples/computing_pcs.html">Computing principal components</a></li>
+					<li><a href="../../documentation/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
+					<li><a href="../../documentation/examples/computing_ld.html">Computing LD</a></li>
+					<li><a href="../../documentation/examples/computing_pcs.html">Computing principal components</a></li>
 					<li><a href="../../documentation/examples/inferring_ploidy.html">Working with sex chromosomes</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="file_formats">
 				file formats
@@ -116,10 +117,10 @@
 					<a href="../../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/combining.html
==================================================================
--- doc/html/qctool/documentation/examples/combining.html
+++ doc/html/qctool/documentation/examples/combining.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,106 +16,116 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Combining datasets</h2>
-			<div class="task">
-				<div class="task_name">
-					Combining several datasets into a larger one
-				</div>
-				<div class="task_notes">
-					QCTOOL's <code>-g</code> and <code>-s</code> options can be specified several times, with the effect of combining
-					data into one larger dataset.  E.g.:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g cohort1.bgen -s cohort1.sample -g cohort2.bgen -s cohort2.sample -og joined.gen -os joined.sample
-				</div>
-				<div class="task_notes">
-					<p>
-						QCTOOL will produce both a combined genotype file and a combined sample file.
-						The output files
-						will have <em>N<sub>1</sub>+N<sub>2</sub></em> samples, where <em>N<sub>1</sub></em> and <em>N<sub>2</sub></em>
-						are the numbers of samples in the two input datasets, and it will contain all variants that can be matched between
-						the input datasets.
-					</p>
-					<p>
-						QCTOOL attempts to merge the columns of the sample files based on column name and type.
-						Columns are dropped if they have the same name but different types.	 Otherwise, each column
-						in the input sample files appears in the output sample file, possibly with missing values for those cohorts
-						for which that column is not present.
-					</p>
-					<p>
-						QCTOOL attempts to combine data at each variant that is present in all input datasets.  To do this,
-						it makes the assumption that <em>data is sorted uniquely and in the same way in all input datasets</em>.
-						If this is not the case then QCTOOL may be unable to match some variants.  Any variant that does not match
-						between datasets will be omitted from the output.
-					</p>
-				</div>
-				<div class="task_name">
-					Controlling how variants are matched
-				</div>
-				<div class="task_notes">
-					<p>
-						The <code>-compare-variants-by</code> option can be used to
-						control what fields QCTOOL compares when matching variants.  (The default behaviour is to match variants by the
-						genomic position, alleles, and ID fields).  For example, in the command:
-					</p>
-				</div>
-				<div class="task_command_line">
-					$ qctool -g cohort1.bgen -s cohort1.sample -g cohort2.bgen -s cohort2.sample -og joined.gen -os joined.sample -compare-variants-by position,alleles
-				</div>
-				<div class="task_notes">
-				<p>
-					QCTOOL will match variants by position and alleles (variants will match even if ID fields differ).  
-					As in the example, <code>position</code> (the genomic position) must always be the first field matched on.
-				</p>
-				<p><b>Note:</b> careful use of these options is especially important when datasets contain multiple variants 
-					sharing the same genomic position.  The recommendation is to ensure all datasets are encoded
-					uniformly before combining them.  (See the pages on <a href="sorting.html">sorting</a>,
-					<a href="altering_id_data.html">aligning alleles</a> and <a href="altering_id_data.html">altering ID data</a>
-					for options that can help with this.)
-				</p>
-			</div>
-				<div class="task_name">
-					Allowing for allele mismatches
-				</div>
-				<div class="task_notes">
-				<p>
-					It is sometimes the case that data is sorted in each dataset but that alleles are mixed up.
-					The <code>-match-alleles-to-cohort1</code> option tells QCTOOL to attempt to match data allowing for this
-					type of mismatch:
-				</p>
-			</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -s example.sample -g second_cohort_#.gen -s second_cohort.sample
-					-og joined.gen -os joined.sample -compare-variants-by position,alleles -match-alleles-to-cohort1
-				</div>
-				<div class="task_notes">
-					<p>
-					  Here, if the variant is biallelic and the alleles in the second dataset are the same as those
-						in the first cohort, but coded the other way round (e.g. cohort1 = A/G, cohort2 = G/A), then the
-						alleles and genotypes are flipped accordingly.  No other transformation (e.g. strand flips, or matching multiallelics)
-						is performed by this operation.  Thus, although this option can be convenient, the general recommendation
-						is to arrange each dataset to be encoded and sorted unformly before combining.
-					</p>
-				</div>
-			</div>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Combining datasets</h2>
+    <div class="task">
+        <div class="task_name">
+            Combining several datasets into a larger one
+        </div>
+        <div class="task_notes">
+            QCTOOL's <code>-g</code> and <code>-s</code> options can be specified several times, with the effect of combining
+            data into one larger dataset.  E.g.:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g cohort1.bgen -s cohort1.sample -g cohort2.bgen -s cohort2.sample -og joined.gen -os joined.sample
+        </div>
+        <div class="task_notes">
+            <p>
+                QCTOOL will produce both a combined genotype file and a combined sample file.
+                The output files
+                will have <em>N<sub>1</sub>+N<sub>2</sub></em> samples, where <em>N<sub>1</sub></em> and <em>N<sub>2</sub></em>
+                are the numbers of samples in the two input datasets, and it will contain all variants that can be matched between
+                the input datasets.
+            </p>
+            <p>
+                QCTOOL attempts to merge the columns of the sample files based on column name and type.
+                Columns are dropped if they have the same name but different types.  Otherwise, each column
+                in the input sample files appears in the output sample file, possibly with missing values for those cohorts
+                for which that column is not present.
+            </p>
+            <p>
+                QCTOOL attempts to combine data at each variant that is present in all input datasets.  To do this,
+                it makes the assumption that <em>data is sorted uniquely and in the same way in all input datasets</em>.
+                If this is not the case then QCTOOL may be unable to match some variants.  Any variant that does not match
+                between datasets will be omitted from the output.
+            </p>
+            <p>
+
+                QCTOOL processed variant identifiers in the following way: it uses the primary identifier from
+                the first dataset as the overall primary identifier. It also keeps a list of all other identifiers observed
+                across the datasets. (When the input file is a VCF, the first identifier is treated as the primary identifier.
+                When the input is in GEN or BGEN format, the `rsid` column is treated as containing the primary identifier, and
+                alternative identifiers from the `SNPID` column are also processed.). The `-map-id-data` option can also
+                be used to force specific adjustments to these data.
+
+            </p>
+        </div>
+        <div class="task_name">
+            Controlling how variants are matched
+        </div>
+        <div class="task_notes">
+            <p>
+                The <code>-compare-variants-by</code> option can be used to
+                control what fields QCTOOL compares when matching variants.  (The default behaviour is to match variants by the
+                genomic position, alleles, and ID fields).  For example, in the command:
+            </p>
+        </div>
+        <div class="task_command_line">
+            $ qctool -g cohort1.bgen -s cohort1.sample -g cohort2.bgen -s cohort2.sample -og joined.gen -os joined.sample -compare-variants-by position,alleles
+        </div>
+        <div class="task_notes">
+        <p>
+            QCTOOL will match variants by position and alleles (variants will match even if ID fields differ).  
+            As in the example, <code>position</code> (the genomic position) must always be the first field matched on.
+        </p>
+        <p><b>Note:</b> careful use of these options is especially important when datasets contain multiple variants 
+            sharing the same genomic position.  The recommendation is to ensure all datasets are encoded
+            uniformly before combining them.  (See the pages on <a href="sorting.html">sorting</a>,
+            <a href="altering_id_data.html">aligning alleles</a> and <a href="altering_id_data.html">altering ID data</a>
+            for options that can help with this.)
+        </p>
+    </div>
+        <div class="task_name">
+            Allowing for allele mismatches
+        </div>
+        <div class="task_notes">
+        <p>
+            It is sometimes the case that data is sorted in each dataset but that alleles are mixed up.
+            The <code>-match-alleles-to-cohort1</code> option tells QCTOOL to attempt to match data allowing for this
+            type of mismatch:
+        </p>
+    </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -s example.sample -g second_cohort_#.gen -s second_cohort.sample
+            -og joined.gen -os joined.sample -compare-variants-by position,alleles -match-alleles-to-cohort1
+        </div>
+        <div class="task_notes">
+            <p>
+              Here, if the variant is biallelic and the alleles in the second dataset are the same as those
+                in the first cohort, but coded the other way round (e.g. cohort1 = A/G, cohort2 = G/A), then the
+                alleles and genotypes are flipped accordingly.  No other transformation (e.g. strand flips, or matching multiallelics)
+                is performed by this operation.  Thus, although this option can be convenient, the general recommendation
+                is to arrange each dataset to be encoded and sorted unformly before combining.
+            </p>
+        </div>
+    </div>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -139,11 +139,12 @@
 					<li><a href="../../documentation/examples/pipelining.html">Using qctool in a pipeline</a></li>
 					<li><a href="../../documentation/examples/filtering_samples.html">Filtering samples</a></li>
 					<li><a href="../../documentation/examples/filtering_variants.html">Filtering variants</a></li>
 					<li><a href="../../documentation/examples/summary_statistics.html">Computing summary statistics</a></li>
 					<li><a href="../../documentation/examples/annotating.html">Computing annotations</a></li>
-					<li><a href="../../documentation/examples/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
+					<li><a href="../../documentation/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
+					<li><a href="../../documentation/examples/computing_ld.html">Computing LD</a></li>
 					<li><a href="../../documentation/examples/computing_pcs.html">Computing principal components</a></li>
 					<li><a href="../../documentation/examples/inferring_ploidy.html">Working with sex chromosomes</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="file_formats">
@@ -154,10 +155,10 @@
 					<a href="../../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/computing_ld.html
==================================================================
--- doc/html/qctool/documentation/examples/computing_ld.html
+++ doc/html/qctool/documentation/examples/computing_ld.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,154 +16,151 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Assessing linkage disequilibrium</h2>
-				<div class="task">
-					<div class="task_name">
-						Computing LD metrics
-					</div>
-					<div class="task_notes">
-						The <code>-compute-ld-with</code> option can be used to compute LD metrics between
-						the genotype data and a seperate set of genotype contained in a second file.  E.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD
-					</div>
-					<div class="task_notes">
-						<p>
-							For each biallelic variant in <code>example.bgen</code>, and each biallelic variant in <code>second.bgen</code>,
-							QCTOOL constructs the pairwise table of non-missing genotypes, uses an EM algorithm to resolve phase
-							of the double heterozygotes, and then outputs the frequency of each haplotype and the <em>D'</em>
-							and <em>r<sup>2</sup></em> statistics.  (Multiallelic variants are currently not handled.)
-					</p>
-					<p>
-						<b>Note</b>: to compute LD, samples are matched between datasets using the primary ID (the first column
-						in the sample files) by default.  To alter this, use the <code>-match-sample-ids</code> option.
-						This is described further on the <a href="merging.html">page on merging datasets</a>.
-					</p>
-					<p>
-						<b>Note</b>:
-						Currently LD output is always to a sqlite database file.  In the above command,
-						results are placed in the file <code>ld.sqlite</code> and in a table called
-						<code>LD</code>; a convenience view, called <code>LDView</code> is also constructed.  The simplest way
-						to view that data is to use the <a href="https://sqlite.org/cli.html">sqlite3 command-line client<a>
-							(which is already installed on most linux systems by default).  E.g. the command:
-						</p>
-					</div>
-						<div class="task_command_line">
-							$ sqlite3 -csv -header ld.sqlite "SELECT * FROM LDView LIMIT 10"
-						</div>
-						<div class="task_notes">
-								Will list the first ten LD records in CSV format.  The file can equally be accessed programmatically,
-								for example using the <a href="https://docs.python.org/2/library/sqlite3.html">sqlite3 module</a> in python, or the <a href="https://cran.r-project.org/web/packages/RSQLite/index.html">RSQLite</a> package in R.
-								We may add flat file support in future.
-						</div>
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Controlling what is output
-					</div>
-					<div class="task_notes">
-						Pairwise LD computation can generate a massive amount of data.  To reduce this the <code>-min-r2</code> and <code>-max-ld-distance</code>
-						options can be used, e.g.
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -min-r2 0.05 -max-ld-distance 1Mb
-					</div>
-					<div class="task_notes">
-						will output results only for variants estimated to have <em>r<sup>2</sup> > 0.05</em>, and within a megabase of each other.
-						For the latter option, you can also specify distances in base pairs (e.g. <code>-max-ld-distance 1000</code>), in kilobases (e.g. <code>-max-ld-distance 1kb</code>),
-						or in megabases as in the example above.
-					</div>
-				
-				<div class="task">
-					<div class="task_name">
-						Adjusting the degree of shrinkage
-					</div>
-					<div class="task_notes">
-							QCTOOL outputs shrinkage estimates of LD by default.
-							Specifically, haplotype frequencies are estimated under a <em>Dirichlet(x,x,x,x)</em> prior,
-							with x=1.25 by default; roughly speaking this is equivalent to adding a quarter of an observation of each of the four haplotypes to the data.
-							Intuitively this corresponds to weak prior assumptions that 1: both variants are polymorphic
-							and 2: there is at least some recombination between them.
-					</div>
-					<div class="task_notes">
-							The <code>-prior-ld-weight</code> option can be used to adjust the strength of this prior, e.g. the command
-					</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -ld-prior-weight &lt;w&gt;
-				</div>
-				<div class="task_notes">
-					estimates LD under a <em>Dirichlet(1+w/4,1+w/4,1+w/4,1+w/4)</em> prior; setting <em>w=0</em> removes the prior altogether.
-				</div>
-				<div class="task_notes">
-					(Note that dosage-based estimates of LD are currently computed without including prior information.)
-				</div>
-			</div>
-
-				<div class="task">
-					<div class="task_name">
-						Stratifying LD computations across subsets
-					</div>
-					<div class="task_notes">
-						As for <code>-snp-stats</code>, the <code>-stratify</code> option tells QCTOOL to compute LD statistics stratified over
-						subsets of the data. E.g. suppose the sample file contains a column called <code>POP</code>
-						which reflects the population group of each sample.  Then the command:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -stratify POP
-					</div>
-					<div class="task_notes">
-						<p>
-							will compute LD statistics for all pairs of variants in each population.  Output columns will be named
-							in the form <code>POP=&lt;level&gt;:&lt;variable&gt;</code>.
-						</p>
-						<p>
-							For example, suppose we've extracted data for the <a href="">O blood group mutation</a> rs8176719 from the
-							<a href="">1000 Genomes Project</a> data into a file named <code>rs8176719.vcf</code>.  This command will
-								find all tagging SNPs in the flanking region:
-						</p>
-					</div>
-						<div class="task_command_line">
-							$ qctool -g ALL.chr9.phase3_shapeit2_mvncall_integrated_v5.20130502.genotypes.vcf.gz
-							-s 1000G.sample
-							-compute-ld-with rs8176719.vcf 1000G.sample
-							-old sqlite://ld.sqlite:LD
-							-stratify POP
-							-min-r2 0.75
-							-max-distance 1Mb
-						</div>
-						<div class="task_notes">
-						<p>
-							Note that currently it's first necessary to make a sample file in the
-							format <a href="../sample_file_formats.html">described here</a> for this to work.
-						</p>
-						<p>
-							<b>Note:</b> This will also take a while to run, since at present it scans the whole of chromosome 9.
-							A quicker way would be to use <a href="https://bitbucket.org/gavinband/bgen">bgenix</a> together with QCTOOL in 
-							 <a href="pipelining.html">in a pipeline</a>.
-						</p>
-					</div>
-				</div>
-
-		</section>
-
-		<nav class="button_bar"><div>
-							<div class="nav_button" name="overview">
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Assessing linkage disequilibrium</h2>
+        <div class="task">
+            <div class="task_name">
+                Computing LD metrics
+            </div>
+            <div class="task_notes">
+                The <code>-compute-ld-with</code> option can be used to compute LD metrics between
+                the genotype data and a seperate set of genotype contained in a second file.  E.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD
+            </div>
+            <div class="task_notes">
+                <p>
+                    For each biallelic variant in <code>example.bgen</code>, and each biallelic variant in <code>second.bgen</code>,
+                    QCTOOL constructs the pairwise table of non-missing genotypes, uses an EM algorithm to resolve phase
+                    of the double heterozygotes, and then outputs the frequency of each haplotype and the <em>D'</em>
+                    and <em>r<sup>2</sup></em> statistics.  (Multiallelic variants are currently not handled.)
+            </p>
+            <p>
+                <b>Note</b>: to compute LD, samples are matched between datasets using the primary ID (the first column
+                in the sample files) by default.  To alter this, use the <code>-match-sample-ids</code> option.
+                This is described further on the <a href="merging.html">page on merging datasets</a>.
+            </p>
+            <p>
+                <b>Note</b>:
+                Currently LD output is always to a sqlite database file.  In the above command,
+                results are placed in the file <code>ld.sqlite</code> and in a table called
+                <code>LD</code>; a convenience view, called <code>LDView</code> is also constructed.  The simplest way
+                to view that data is to use the <a href="https://sqlite.org/cli.html">sqlite3 command-line client<a>
+                    (which is already installed on most linux systems by default).  E.g. the command:
+                </p>
+            </div>
+                <div class="task_command_line">
+                    $ sqlite3 -csv -header ld.sqlite "SELECT * FROM LDView LIMIT 10"
+                </div>
+                <div class="task_notes">
+                        Will list the first ten LD records in CSV format.  The file can equally be accessed programmatically,
+                        for example using the <a href="https://docs.python.org/2/library/sqlite3.html">sqlite3 module</a> in python, or the <a href="https://cran.r-project.org/web/packages/RSQLite/index.html">RSQLite</a> package in R.
+                        We may add flat file support in future.
+                </div>
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Controlling what is output
+            </div>
+            <div class="task_notes">
+                Pairwise LD computation can generate a massive amount of data.  To reduce this the <code>-min-r2</code> and <code>-max-ld-distance</code>
+                options can be used, e.g.
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -min-r2 0.05 -max-ld-distance 1Mb
+            </div>
+            <div class="task_notes">
+                will output results only for variants estimated to have <em>r<sup>2</sup> > 0.05</em>, and within a megabase of each other.
+                For the latter option, you can also specify distances in base pairs (e.g. <code>-max-ld-distance 1000</code>), in kilobases (e.g. <code>-max-ld-distance 1kb</code>),
+                or in megabases as in the example above.
+            </div>
+
+        <div class="task">
+            <div class="task_name">
+                Adjusting the degree of shrinkage
+            </div>
+            <div class="task_notes">
+                    QCTOOL outputs shrinkage estimates of LD by default.
+                    Specifically, haplotype frequencies are estimated under a <em>Dirichlet(x,x,x,x)</em> prior,
+                    with x=1.25 by default; roughly speaking this is equivalent to adding a quarter of an observation of each of the four haplotypes to the data.
+                    Intuitively this corresponds to weak prior assumptions that 1: both variants are polymorphic
+                    and 2: there is at least some recombination between them.
+            </div>
+            <div class="task_notes">
+                    The <code>-prior-ld-weight</code> option can be used to adjust the strength of this prior, e.g. the command
+            </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -ld-prior-weight &lt;w&gt;
+        </div>
+        <div class="task_notes">
+            estimates LD under a <em>Dirichlet(1+w/4,1+w/4,1+w/4,1+w/4)</em> prior; setting <em>w=0</em> removes the prior altogether.
+        </div>
+    </div>
+
+        <div class="task">
+            <div class="task_name">
+                Stratifying LD computations across subsets
+            </div>
+            <div class="task_notes">
+                As for <code>-snp-stats</code>, the <code>-stratify</code> option tells QCTOOL to compute LD statistics stratified over
+                subsets of the data. E.g. suppose the sample file contains a column called <code>POP</code>
+                which reflects the population group of each sample.  Then the command:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -compute-ld-with second.bgen second.sample -old sqlite://ld.sqlite:LD -stratify POP
+            </div>
+            <div class="task_notes">
+                <p>
+                    will compute LD statistics for all pairs of variants in each population.  Output columns will be named
+                    in the form <code>POP=&lt;level&gt;:&lt;variable&gt;</code>.
+                </p>
+                <p>
+                    For example, suppose we've extracted data for the <a href="">O blood group mutation</a> rs8176719 from the
+                    <a href="">1000 Genomes Project</a> data into a file named <code>rs8176719.vcf</code>.  This command will
+                        find all tagging SNPs in the flanking region:
+                </p>
+            </div>
+                <div class="task_command_line">
+                    $ qctool -g ALL.chr9.phase3_shapeit2_mvncall_integrated_v5.20130502.genotypes.vcf.gz
+                    -s 1000G.sample
+                    -compute-ld-with rs8176719.vcf 1000G.sample
+                    -old sqlite://ld.sqlite:LD
+                    -stratify POP
+                    -min-r2 0.75
+                    -max-distance 1Mb
+                </div>
+                <div class="task_notes">
+                <p>
+                    Note that currently it's first necessary to make a sample file in the
+                    format <a href="../sample_file_formats.html">described here</a> for this to work.
+                </p>
+                <p>
+                    <b>Note:</b> This will also take a while to run, since at present it scans the whole of chromosome 9.
+                    A quicker way would be to use <a href="https://bitbucket.org/gavinband/bgen">bgenix</a> together with QCTOOL in 
+                     <a href="pipelining.html">in a pipeline</a>.
+                </p>
+            </div>
+        </div>
+
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -205,8 +192,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/computing_pcs.html
==================================================================
--- doc/html/qctool/documentation/examples/computing_pcs.html
+++ doc/html/qctool/documentation/examples/computing_pcs.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,163 +16,164 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Computing principal components</h2>
-				<div class="task">
-					<div class="task_name">
-						Computing PCs
-					</div>
-					<div class="task_notes">
-						QCTOOL computes PCs by first estimating a relatedness or 'kinship' matrix, and then forming the eigendecomposition. 
-						In short you use the <code>-kinship</code> option to compute a
-						relatedness matrix, the <code>-UDUT</code> option to eigendecompose it, and the <code>-PCs</code> option
-						to output PCs.  A complete example would look like this:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
-					</div>
-					<div class="task_notes">
-						<p>
-							This outputs the first 20 PCs to the file <code>PCs.csv</code>, in addition to the estimated kinship
-							matrix and its eigendecomposition.  The following sections show the use of these options in more detail.
-					</p>
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Computing a kinship matrix
-					</div>
-					<div class="task_notes">
-						The <code>-kinship</code> option can be used to estimate a kinship matrix, as in:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -kinship kinship.csv
-					</div>
-					<div class="task_notes">
-						<p>
-							This outputs pairwise kinship values to the file <code>kinship.csv</code>, which is stored in a 'long' format
-							with columns holding the first sample id, second sample id, the number of pairwise non-missing genotypes,
-							and the estimated kinship value.  (Only the upper triangle of this matrix is output).
-						</p>
-						<p>
-							More precisely,  Suppose <em>X</em> is the <em>L&times;N</em> matrix of
-							genotypes, with variants indexed by row.
-							Let <em>f<sub>i</sub></em> be an estimate of the frequency of the <em>i</em>th variant.
-							We write <em>Z</em> for the matrix <em>X</em> after centring and rescaling each row based on the allele frequency,
-						</p>
-						<p>
-							<em>Z<sub>i&middot;</sub> = (X<sub>i&middot;</sub> - mean(X<sub>i&middot;</sub>)) / &Sqrt; (2 f<sub>i</sub> (1-f<sub>i</sub>))</em>
-						</p>
-						<p>
-							QCTOOL estimates the kinship matrix as <em>1/L Z^t Z</em>.
-							In forming <em>Z</em>, QCTOOL uses a posterior estimate of allele
-							frequency <em>f<sub>i</sub></em> under a <em>Beta(2,2)</em>
-							distribution, i.e. <em>f<sub>i</sub> = (1+N<sub>b</sub>)/(2+2N))</em> where <em>N<sub>b</sub></em> is
-							the count number of 'b' alleles in the data.  This can be understood as implicitly adding
-							a single haplotype of each allelic type to the data before
-							computing the frequency, which in turn ensures that the frequency estimate is not zero or 1.  
-						</p>
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Eigendecomposing a kinship matrix and computing PCs
-					</div>
-					<div class="task_notes">
-						The <code>-UDUT</code> option can be used to compute a UDUT decomposition (i.e. an eigendecomposition)
-						of the computed kinship matrix.
-							E.g.
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv
-					</div>
-					<div class="task_notes">
-						The output is an <em>N&times;(N+1)</em> matrix in which the first column represents the diagonal elements
-						of <em>D</em>, i.e. the eigenvalues, and the following <em>N</em> columns are the right eigenvectors
-						(i.e. the columns of <em>U</em>).  To additionally output principal components (PCs),
-						additionally add the <code>-PCs</code> option:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
-					</div>
-					<div class="task_notes">
-					<p>
-						The argument is the number of PCs to output.
-					</p>
-					<p>
-						<b>Note</b>: the PCs computed are simply rescaled entries of the right eigenvectors;
-						they are computed as <em>PC<sub>i</sub></em> = &Sqrt;(1/L) &times; U<sub>&middot;i</sub> D<sup>-1/2</sup></em>.
-						This scaling ensures the PCs do not grow with the number of variants.
-					</p>
-					<p>
-						<b>Note:</b> PCs are output to the file specified by <code>-osample</code>.
-						Depending on the command line, other values might also be output to this file.  For example, 
-						if you specify both <code>-sample-stats</code> and <code>-PCs</code>, the output file will contain both
-						per-sample summary statistics and PCs.
-						See the <a href="../../documentation/summary_file_formats.html">page
-							on summary statistic file formats</a> for more information on the format of the output.
-					</p>
-					<p>
-						In some contexts it may be preferable to load a previously
-						computed kinship matrix, rather than to recompute a new one. This can be acheived with the
-						<code>-load-kinship</code> option:
-					</p>
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -load-kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
-					</div>
-				</div>
-
-				<div class="task">
-					<div class="task_name">
-						Computing PC loadings
-					</div>
-					<div class="task_notes">
-						Having computed the UDUT decomposition, per-variant loadings can be
-						computed using the <code>-loadings</code> option, e.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -load-udut udut.csv -loadings loadings.csv
-					</div>
-					<div class="task_notes">
-						The <code>-PCs</code> option can again be used to adjust how many loadings are computed.
-						<b>Note</b>: you should ensure the same set of variants is used to compute
-						loadings as were used in constructing the kinship matrix.
-					</div>
-				</div>
-
-				<div class="task">
-					<div class="task_name">
-						Projecting additional samples onto a principal components decomposition
-					</div>
-					<div class="task_notes">
-						Given a set of loadings, additional samples can be projected onto the loadings using
-						the <code>-project-onto</code> option:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -project-onto loadings.csv projection.sample
-					</div>
-					<div class="task_notes">
-						The first argument is a set of loadings to load, while the second argument is the output file to compute.
-						Again, we advise using the same set of variants that were used to compute the PCs.
-					</div>
-				</div>
-		</section>
-
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Computing principal components</h2>
+        <div class="task">
+            <div class="task_name">
+                Computing PCs
+            </div>
+            <div class="task_notes">
+                QCTOOL computes PCs by first estimating a relatedness or 'kinship' matrix, and then forming the eigendecomposition. 
+                In short you use the <code>-kinship</code> option to compute a
+                relatedness matrix, the <code>-UDUT</code> option to eigendecompose it, and the <code>-PCs</code> option
+                to output PCs.  A complete example would look like this:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
+            </div>
+            <div class="task_notes">
+                <p>
+                    This outputs the first 20 PCs to the file <code>PCs.csv</code>, in addition to the estimated kinship
+                    matrix and its eigendecomposition.  The following sections show the use of these options in more detail.
+            </p>
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Computing a kinship matrix
+            </div>
+            <div class="task_notes">
+                The <code>-kinship</code> option can be used to estimate a kinship matrix, as in:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -kinship kinship.csv
+            </div>
+            <div class="task_notes">
+                <p>
+                    This outputs pairwise kinship values to the file <code>kinship.csv</code>, which is stored in a 'long' format
+                    with columns holding the first sample id, second sample id, the number of pairwise non-missing genotypes,
+                    and the estimated kinship value.  (Only the upper triangle of this matrix is output).
+                </p>
+                <p>
+                    More precisely,  Suppose <em>X</em> is the <em>L&times;N</em> matrix of
+                    genotypes, with variants indexed by row.
+                    Let <em>f<sub>i</sub></em> be an estimate of the frequency of the <em>i</em>th variant.
+                    We write <em>Z</em> for the matrix <em>X</em> after centring and rescaling each row based on the allele frequency,
+                </p>
+                <p>
+                    <em>Z<sub>i&middot;</sub> = (X<sub>i&middot;</sub> - mean(X<sub>i&middot;</sub>)) / &Sqrt; (2 f<sub>i</sub> (1-f<sub>i</sub>))</em>
+                </p>
+                <p>
+                    QCTOOL estimates the kinship matrix as <em>1/L Z^t Z</em>.
+                    In forming <em>Z</em>, QCTOOL uses a posterior estimate of allele
+                    frequency <em>f<sub>i</sub></em> under a <em>Beta(2,2)</em>
+                    distribution, i.e. <em>f<sub>i</sub> = (1+N<sub>b</sub>)/(2+2N))</em> where <em>N<sub>b</sub></em> is
+                    the count number of 'b' alleles in the data.  This can be understood as implicitly adding
+                    a single haplotype of each allelic type to the data before
+                    computing the frequency, which in turn ensures that the frequency estimate is not zero or 1.  
+                </p>
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Eigendecomposing a kinship matrix and computing PCs
+            </div>
+            <div class="task_notes">
+                The <code>-UDUT</code> option can be used to compute a UDUT decomposition (i.e. an eigendecomposition)
+                of the computed kinship matrix.
+                    E.g.
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv
+            </div>
+            <div class="task_notes">
+                The output is an <em>N&times;(N+1)</em> matrix in which the first column represents the diagonal elements
+                of <em>D</em>, i.e. the eigenvalues, and the following <em>N</em> columns are the right eigenvectors
+                (i.e. the columns of <em>U</em>).  To additionally output principal components (PCs),
+                additionally add the <code>-PCs</code> option:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
+            </div>
+            <div class="task_notes">
+            <p>
+                The argument is the number of PCs to output.
+            </p>
+            <p>
+                <b>Note</b>: the PCs computed are simply rescaled entries of the right eigenvectors;
+                they are computed as <em>PC<sub>i</sub></em> = &Sqrt;(1/L) &times; U<sub>&middot;i</sub> D<sup>-1/2</sup></em>.
+                This scaling ensures the PCs do not grow with the number of variants.
+            </p>
+            <p>
+                <b>Note:</b> PCs are output to the file specified by <code>-osample</code>.
+                Depending on the command line, other values might also be output to this file.  For example, 
+                if you specify both <code>-sample-stats</code> and <code>-PCs</code>, the output file will contain both
+                per-sample summary statistics and PCs.
+                See the <a href="../../documentation/summary_file_formats.html">page
+                    on summary statistic file formats</a> for more information on the format of the output.
+            </p>
+            <p>
+                In some contexts it may be preferable to load a previously
+                computed kinship matrix, rather than to recompute a new one. This can be acheived with the
+                <code>-load-kinship</code> option:
+            </p>
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -load-kinship kinship.csv -UDUT udut.csv -PCs 20 -osample PCs.csv
+            </div>
+        </div>
+
+        <div class="task">
+            <div class="task_name">
+                Computing PC loadings
+            </div>
+            <div class="task_notes">
+                Having computed the UDUT decomposition, per-variant loadings can be
+                computed using the <code>-loadings</code> option, e.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -load-udut udut.csv -loadings loadings.csv
+            </div>
+            <div class="task_notes">
+                The <code>-PCs</code> option can again be used to adjust how many loadings are computed.
+                <b>Note</b>: you should ensure the same set of variants is used to compute
+                loadings as were used in constructing the kinship matrix.
+            </div>
+        </div>
+
+        <div class="task">
+            <div class="task_name">
+                Projecting additional samples onto a principal components decomposition
+            </div>
+            <div class="task_notes">
+                Given a set of loadings, additional samples can be projected onto the loadings using
+                the <code>-project-onto</code> option:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -project-onto loadings.csv projection.sample
+            </div>
+            <div class="task_notes">
+                The first argument is a set of loadings to load, while the second argument is the output file to compute.
+                Again, we advise using the same set of variants that were used to compute the PCs.
+            </div>
+        </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -214,8 +205,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/converting.html
==================================================================
--- doc/html/qctool/documentation/examples/converting.html
+++ doc/html/qctool/documentation/examples/converting.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,109 +16,109 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-					<h2>Converting between file formats</h2>
-				<div class="task">
-					<div class="task_name">
-						Basic conversions
-					</div>
-					<div class="task_notes">
-						The basic format of a conversion command is:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g &lt;input file&gt; [-filetype &lt;input type&gt;] -og &lt;output file&gt; [-ofiletype &lt;output type&gt;] [+modifier options]
-					</div>
-					<div class="task_notes">
-						QCTOOL normally deduces file types from the file extension.
-						However, for filetypes that are not automatically recognised, or if you want to specify,
-						the <code>-filetype</code> and <code>-ofiletype</code> options can be used to specify the types.
-						The <a href="../../documentation/genotype_file_formats.html">genotype file formats page</a> lists file type specifiers and
-						any applicable modifier options.
-					</div>
-					<div class="task_notes">
-						E.g. to convert between between bgen and vcf formats:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -og example.vcf
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Handling files split by chromosome
-					</div>
-					<div class="task_notes">
-						If the input filename contains a # character, e.g. <code>example_#.gen</code> this is treated as a
-						chromosomal wildcard and will match all (human) chromosomes. This will also be used to
-						infer the chromosome for each variant if chromosome information is not present in the files themselves.
-						For example, the command:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example_#.gen -og example.bgen
-					</div>
-					<div class="task_notes">
-						will process all 22 example files, and if the input GEN files have no chromosome information included,
-						the output data will have chromosome identifiers taken from the filenames.
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Including sample information in conversions
-					</div>
-					<div class="task_notes">
-						 Although specifying a sample file in conversions is optional, it's sometimes preferable to include one so that output files have
-						the correct sample identifiers (e.g. when converting GEN format to BGEN or VCF), e.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example_#.gen -og example.bgen -s example.sample
-					</div>
-					<div class="task_notes">
-						which will produce a BGEN file with a sample identifier block.
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Converting from VCF format
-					</div>
-					<div class="task_notes">
-						By default QCTOOL reads genotype calls from the <span class="monospace">GT</span> field in the VCF file.
-						The <code>-vcf-genotype-field</code> can be used to alter this, e.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.vcf -vcf-genotype-field GP -og converted.bgen
-					</div>
-					<div class="task_notes">
-						QCTOOL also assumes that VCF metadata is correct (according to the VCF v4.2 spec)- and it will
-						fail with an error if that's not the case.
-						To work around this, the <code>-metadata</code> option can be used to tell QCTOOL to load metadata from an
-						external file:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.vcf -og converted.bgen -metadata metadata.txt
-					</div>
-					<div class="task_notes">
-						The specified metadata file should contain complete VCF metadata, starting
-						with the <code>##fileformat=VCFv4.2</code> line, up to but not
-						including the <code>#CHROM...</code> line.
-					</div>
-				</div>
-			</div>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+            <h2>Converting between file formats</h2>
+        <div class="task">
+            <div class="task_name">
+                Basic conversions
+            </div>
+            <div class="task_notes">
+                The basic format of a conversion command is:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g &lt;input file&gt; [-filetype &lt;input type&gt;] -og &lt;output file&gt; [-ofiletype &lt;output type&gt;] [+modifier options]
+            </div>
+            <div class="task_notes">
+                QCTOOL normally deduces file types from the file extension.
+                However, for filetypes that are not automatically recognised, or if you want to specify,
+                the <code>-filetype</code> and <code>-ofiletype</code> options can be used to specify the types.
+                The <a href="../../documentation/genotype_file_formats.html">genotype file formats page</a> lists file type specifiers and
+                any applicable modifier options.
+            </div>
+            <div class="task_notes">
+                E.g. to convert between between bgen and vcf formats:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -og example.vcf
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Handling files split by chromosome
+            </div>
+            <div class="task_notes">
+                If the input filename contains a # character, e.g. <code>example_#.gen</code> this is treated as a
+                chromosomal wildcard and will match all (human) chromosomes. This will also be used to
+                infer the chromosome for each variant if chromosome information is not present in the files themselves.
+                For example, the command:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example_#.gen -og example.bgen
+            </div>
+            <div class="task_notes">
+                will process all 22 example files, and if the input GEN files have no chromosome information included,
+                the output data will have chromosome identifiers taken from the filenames.
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Including sample information in conversions
+            </div>
+            <div class="task_notes">
+                 Although specifying a sample file in conversions is optional, it's sometimes preferable to include one so that output files have
+                the correct sample identifiers (e.g. when converting GEN format to BGEN or VCF), e.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example_#.gen -og example.bgen -s example.sample
+            </div>
+            <div class="task_notes">
+                which will produce a BGEN file with a sample identifier block.
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Converting from VCF format
+            </div>
+            <div class="task_notes">
+                By default QCTOOL reads genotype calls from the <span class="monospace">GT</span> field in the VCF file.
+                The <code>-vcf-genotype-field</code> can be used to alter this, e.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.vcf -vcf-genotype-field GP -og converted.bgen
+            </div>
+            <div class="task_notes">
+                QCTOOL also assumes that VCF metadata is correct (according to the VCF v4.2 spec)- and it will
+                fail with an error if that's not the case.
+                To work around this, the <code>-metadata</code> option can be used to tell QCTOOL to load metadata from an
+                external file:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.vcf -og converted.bgen -metadata metadata.txt
+            </div>
+            <div class="task_notes">
+                The specified metadata file should contain complete VCF metadata, starting
+                with the <code>##fileformat=VCFv4.2</code> line, up to but not
+                including the <code>#CHROM...</code> line.
+            </div>
+        </div>
+    </div>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -135,19 +125,20 @@
 					<li><a href="../../documentation/examples/basic.html">Basic usage</a></li>
 					<li><a href="../../documentation/examples/converting.html">Converting file formats</a></li>
 					<li><a href="../../documentation/examples/converting_genotypes.html">Thresholding genotypes</a></li>
 					<li><a href="../../documentation/examples/sorting.html">Sorting and reordering data</a></li>
 					<li><a href="../../documentation/examples/combining.html">Combining datasets</a></li>
-<li><a href="../../documentation/examples/merging.html">Merging in variants</a></li>
+					<li><a href="../../documentation/examples/merging.html">Merging in variants</a></li>
 					<li><a href="../../documentation/examples/altering_id_data.html">Altering variant identifying data</a></li>
 					<li><a href="../../documentation/examples/pipelining.html">Using qctool in a pipeline</a></li>
 					<li><a href="../../documentation/examples/filtering_samples.html">Filtering samples</a></li>
-<li><a href="../../documentation/examples/filtering_variants.html">Filtering variants</a></li>
+					<li><a href="../../documentation/examples/filtering_variants.html">Filtering variants</a></li>
 					<li><a href="../../documentation/examples/summary_statistics.html">Computing summary statistics</a></li>
 					<li><a href="../../documentation/examples/annotating.html">Computing annotations</a></li>
-					<li><a href="../../documentation/examples/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
-<li><a href="../../documentation/examples/computing_pcs.html">Computing principal components</a></li>
+					<li><a href="../../documentation/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
+					<li><a href="../../documentation/examples/computing_ld.html">Computing LD</a></li>
+					<li><a href="../../documentation/examples/computing_pcs.html">Computing principal components</a></li>
 					<li><a href="../../documentation/examples/inferring_ploidy.html">Working with sex chromosomes</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="file_formats">
 				file formats
@@ -157,9 +148,10 @@
 					<a href="../../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
-		</div>
-		
+</div>
+</nav>
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/converting_genotypes.html
==================================================================
--- doc/html/qctool/documentation/examples/converting_genotypes.html
+++ doc/html/qctool/documentation/examples/converting_genotypes.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,71 +16,72 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-					<h2>Converting genotypes</h2>
-				<div class="task">
-					<div class="task_name">
-						Computing genotype calls by thresholding
-					</div>
-					<div class="task_notes">
-						The <code>-threshold</code> option tells QCTOOL to compute thresholded genotype calls from genotype probabilities found in the input. For example:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g input.gen -threshold 0.9 -og thresholded.vcf
-					</div>
-					<div class="task_notes">
-						This will read genotype probabilities (e.g. from imputation) from the input file, and for each sample at each variant will
-						compute a genotype call (if one of the probabilities is above the threshold) or a missing call (if none are).
-					</div>
-					<div class="task_notes">
-						In the example above, the output VCF file will contain two FORMAT fields, namely GT (the threshholded call) and GP (the original
-						imputed probabilities).  More generally, <code>-threshold</code> makes the thresholded call the primary analysis genotype,
-						thus for example in the command:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g input.gen -threshold 0.9 -snp-stats -osnp &lt;output file&gt;
-					</div>
-					<div class="task_notes">
-						the output will reflect summary statistics computed on the thresholded calls.
-					</div>
-				</div>
-			</div>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+            <h2>Converting genotypes</h2>
+        <div class="task">
+            <div class="task_name">
+                Computing genotype calls by thresholding
+            </div>
+            <div class="task_notes">
+                The <code>-threshold</code> option tells QCTOOL to compute thresholded genotype calls from genotype probabilities found in the input. For example:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g input.gen -threshold 0.9 -og thresholded.vcf
+            </div>
+            <div class="task_notes">
+                This will read genotype probabilities (e.g. from imputation) from the input file, and for each sample at each variant will
+                compute a genotype call (if one of the probabilities is above the threshold) or a missing call (if none are).
+            </div>
+            <div class="task_notes">
+                In the example above, the output VCF file will contain two FORMAT fields, namely GT (the threshholded call) and GP (the original
+                imputed probabilities).  More generally, <code>-threshold</code> makes the thresholded call the primary analysis genotype,
+                thus for example in the command:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g input.gen -threshold 0.9 -snp-stats -osnp &lt;output file&gt;
+            </div>
+            <div class="task_notes">
+                the output will reflect summary statistics computed on the thresholded calls.
+            </div>
+        </div>
+    </div>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
 					<li><a href="../../documentation/examples/basic.html">Basic usage</a></li>
 					<li><a href="../../documentation/examples/converting.html">Converting file formats</a></li>
 					<li><a href="../../documentation/examples/converting_genotypes.html">Thresholding genotypes</a></li>
-<li><a href="([a-zA-Z/.]*)sorting.html">Sorting and reordering data</a></li>
-				<li><a href="../../documentation/examples/combining.html">Combining datasets</a></li>
-<li><a href="../../documentation/examples/merging.html">Merging in variants</a></li>
+					<li><a href="../../documentation/examples/sorting.html">Sorting and reordering data</a></li>
+					<li><a href="../../documentation/examples/combining.html">Combining datasets</a></li>
+					<li><a href="../../documentation/examples/merging.html">Merging in variants</a></li>
 					<li><a href="../../documentation/examples/altering_id_data.html">Altering variant identifying data</a></li>
 					<li><a href="../../documentation/examples/pipelining.html">Using qctool in a pipeline</a></li>
 					<li><a href="../../documentation/examples/filtering_samples.html">Filtering samples</a></li>
-<li><a href="../../documentation/examples/filtering_variants.html">Filtering variants</a></li>
+					<li><a href="../../documentation/examples/filtering_variants.html">Filtering variants</a></li>
 					<li><a href="../../documentation/examples/summary_statistics.html">Computing summary statistics</a></li>
 					<li><a href="../../documentation/examples/annotating.html">Computing annotations</a></li>
-					<li><a href="../../documentation/examples/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
-<li><a href="../../documentation/examples/computing_pcs.html">Computing principal components</a></li>
+					<li><a href="../../documentation/examples/adding_to_sample_file.html">Adding data to a sample file</a></li>
+					<li><a href="../../documentation/examples/computing_ld.html">Computing LD</a></li>
+					<li><a href="../../documentation/examples/computing_pcs.html">Computing principal components</a></li>
 					<li><a href="../../documentation/examples/inferring_ploidy.html">Working with sex chromosomes</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="file_formats">
 				file formats
@@ -100,9 +91,10 @@
 					<a href="../../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
-		</div>
-		
+</div>
+</nav>
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/filtering_samples.html
==================================================================
--- doc/html/qctool/documentation/examples/filtering_samples.html
+++ doc/html/qctool/documentation/examples/filtering_samples.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,101 +16,102 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Filtering samples</h2>
-				<div class="task">
-					<div class="task_name">
-						Filtering samples by identifier
-					</div>
-					<div class="task_notes">
-						The <code>-incl-samples</code> and <code>-excl-samples</code> options can be used to select a subset of
-						samples to process.  E.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen 
-						-s example.sample 
-						-og filtered.bgen
-						-excl-samples samples.txt
-					</div>
-					<div class="task_notes">
-						This command excludes all samples whose identifier is in the file <code>samples.txt</code>
-						(which should contain a whitespace-separated list of identifiers).
-						Samples are identified by the first identifier field (often <code>ID_1</code>) in the sample file, or if no
-						sample file is specified, by sample identifiers specified in genotype data
-						source (e.g. by the header in vcf or bgen formats).  The option <code>-incl-samples</code>
-						behaves similarly but includes only samples with identifier in the given file.
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Filtering samples by sample file column
-					</div>
-					<div class="task_notes">
-						It's also possible to filter samples based on the value of a column in the sample file.  The general command is:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g &lt;genotype file&gt; -s &lt;sample file&gt;
-						-[in|ex]cl-samples-where &lt;column&gt;[=|==|!=]&lt;value&gt; [+other options]
-					</div>
-					<div class="task_notes">
-						For example, the following command will write a new filtered genotype file excluding
-						all samples listed as "male" in the "sex" column of the sample file:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen
-						-s example.sample
-						-og filtered.bgen
-						-excl-samples-where 'sex = male'
-					</div>
-					<div class="task_notes">
-						<p>
-							You can currently filter sample file column values
-							for equality (using <code>=</code> or <code>==</code>) or inequality (<code>!=</code>).
-							<b>Note</b>: depending on the column names and expression used, it may be necessary
-							to place quotation marks around the expression to stop it being expanded by the shell.
-							As in the example above this also allows you to use whitespace to format the condition.
-						</p>
-						<p>
-							The <code>-incl-samples-where</code> behaves similarly, but includes only samples matching the condition.
-						</p>
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Combining filters
-					</div>
-					<div class="task_notes">
-						In general inclusion and exclusion options come in pairs of the form <code>-incl-&lt;option&gt;</code>, <code>-excl-&lt;option&gt;</code>.
-						If multiple overlapping conditions are specified, the logic is that samples that satisfy any of the specified exclusion criteria will
-						be excluded, and likewise samples that do not satisfy any of the specified inclusion criteria will be excluded.  This in the following command:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen
-						-s example.sample
-						-og filtered.bgen
-						-excl-samples-where 'sex = male'
-						-incl-samples samples.txt
-					</div>
-					<div class="task_notes">
-						The output will contain only male samples that are also listed in the file <code>samples.txt</code>.
-					</div>
-				</div>
-		</section>
-
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Filtering samples</h2>
+        <div class="task">
+            <div class="task_name">
+                Filtering samples by identifier
+            </div>
+            <div class="task_notes">
+                The <code>-incl-samples</code> and <code>-excl-samples</code> options can be used to select a subset of
+                samples to process.  E.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen 
+                -s example.sample 
+                -og filtered.bgen
+                -excl-samples samples.txt
+            </div>
+            <div class="task_notes">
+                This command excludes all samples whose identifier is in the file <code>samples.txt</code>
+                (which should contain a whitespace-separated list of identifiers).
+                Samples are identified by the first identifier field (often <code>ID_1</code>) in the sample file, or if no
+                sample file is specified, by sample identifiers specified in genotype data
+                source (e.g. by the header in vcf or bgen formats).  The option <code>-incl-samples</code>
+                behaves similarly but includes only samples with identifier in the given file.
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Filtering samples by sample file column
+            </div>
+            <div class="task_notes">
+                It's also possible to filter samples based on the value of a column in the sample file.  The general command is:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g &lt;genotype file&gt; -s &lt;sample file&gt;
+                -[in|ex]cl-samples-where &lt;column&gt;[=|==|!=]&lt;value&gt; [+other options]
+            </div>
+            <div class="task_notes">
+                For example, the following command will write a new filtered genotype file excluding
+                all samples listed as "male" in the "sex" column of the sample file:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen
+                -s example.sample
+                -og filtered.bgen
+                -excl-samples-where 'sex = male'
+            </div>
+            <div class="task_notes">
+                <p>
+                    You can currently filter sample file column values
+                    for equality (using <code>=</code> or <code>==</code>) or inequality (<code>!=</code>).
+                    <b>Note</b>: depending on the column names and expression used, it may be necessary
+                    to place quotation marks around the expression to stop it being expanded by the shell.
+                    As in the example above this also allows you to use whitespace to format the condition.
+                </p>
+                <p>
+                    The <code>-incl-samples-where</code> behaves similarly, but includes only samples matching the condition.
+                </p>
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Combining filters
+            </div>
+            <div class="task_notes">
+                In general inclusion and exclusion options come in pairs of the form <code>-incl-&lt;option&gt;</code>, <code>-excl-&lt;option&gt;</code>.
+                If multiple overlapping conditions are specified, the logic is that samples that satisfy any of the specified exclusion criteria will
+                be excluded, and likewise samples that do not satisfy any of the specified inclusion criteria will be excluded.  This in the following command:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen
+                -s example.sample
+                -og filtered.bgen
+                -excl-samples-where 'sex = male'
+                -incl-samples samples.txt
+            </div>
+            <div class="task_notes">
+                The output will contain only male samples that are also listed in the file <code>samples.txt</code>.
+            </div>
+        </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -152,8 +143,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/filtering_variants.html
==================================================================
--- doc/html/qctool/documentation/examples/filtering_variants.html
+++ doc/html/qctool/documentation/examples/filtering_variants.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,142 +16,143 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Filtering variants</h2>
-			<div class="task">
-				<div class="task_name">
-					Filtering variants based on an external file
-				</div>
-				<div class="task_notes">
-					QCTOOL has a set of options to filter variants, each namely:
-					<code>-[in|ex]cl-rsids</code>,
-					<code>-[in|ex]cl-snpids</code>,
-					<code>-[in|ex]cl-positions</code>,
-					<code>-[in|ex]cl-variants</code>,
-					<code>-[in|ex]cl-variants-matching</code>.
-					Here are examples of these options:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -excl-rsids &lt;filename&gt;
-				</div>
-				<div class="task_notes">
-					Here the specified file should contain a whitespace-separated list of rsids that will be excluded from processing.
-				</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -excl-snpids &lt;filename&gt;
-				</div>
-				<div class="task_notes">
-					Ditto, but for alternate IDs.
-				</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -excl-positions &lt;filename&gt;
-				</div>
-				<div class="task_notes">
-					The specified file should contain a list of genomic positions in the format <code>[chromosome:]position</code>.
-					The chromosome should be omitted if you want to specify variants that have missing chromosome information.
-				</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -excl-variants &lt;filename&gt;
-				</div>
-				<div class="task_notes">
-					The specified file should contain a list of variants.  Currently this must be a text file with six named
-				 	 columns; the first four must be <code>SNPID</code>, <code>rsid</code>, <code>chromosome</code>, <code>position</code>,
-					 followed by columns containing the first and second alleles.  The <code>-compare-variants-by</code> option control
-					 how variants are matched to this file - see the page on <a href="sorting.html">sorting data</a> for more information
-					 on this option.
-				</div>
-			</div>
-
-			<div class="task">
-				<div class="task_name">
-					Range filtering
-				</div>
-				<div class="task_notes">
-					The <code>-[in|ex]cl-range</code> option filters variants by range.  E.g.:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -[in|ex]cl-range [chromosome]:[start]-[end]
-				</div>
-				<div class="task_notes">
-					This includes / excludes any variant in the given range.  Ranges are treated as closed ranges,
-					i.e. the range includes both start and end positions.
-					Optionally you can omit the chromosome; this will additionally capture variants that
-					have missing chromosome information. Also, either the start or end positions can be omitted, in which case the range is treated as containing
-					all positions up to the end coordinate, or all variants from the start coordinate onwards respectively.
-					Examples of valid ranges are:
-					<code>1:100-200</code>, <code>1:-200</code>, or <code>X:1000000-</code>.
-				</div>
-			</div>
-
-			<div class="task">
-				<div class="task_name">
-					Wildcard variant filtering
-				</div>
-				<div class="task_notes">
-					You can filter variants based on a wildcard match of ID fields.  E.g.:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -incl-variants-matching rsid~rs1%
-				</div>
-				<div class="task_notes">
-					This command will retain all variants that have rsid starting with 'rs1'.  The general format of this command is:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -incl-variants-matching [field~][value]
-				</div>
-				<div class="task_notes">
-					Here <code>field</code> can be 'snpid' (matching all alternate IDs) or 'rsid' (matching the first, or rs id),
-					or it can be omitted to match any id.  The value can optionally contain a single '%' character, which will
-					expand to match any string value.  A complete match is required, hence the value 'a%b'
-					will match the ID 'ab', 'a1b', etc., but not 'zab' or 'ab2'.
-				</div>
-			</div>
-			<div class="task">
-				<div class="task_name">
-					Combining multiple filters in the same command
-				</div>
-				<div class="task_notes">
-					<p>
-					The logic for processing multiple inclusion/exclusion options is as follows.
-					First, if any inclusion option is specified multiple times, the results are logically ORd together.
-					(Thus, for example specifying <code>-incl-range</code> twice results in including variants in either range).
-					Second, the resulting conditions are ANDed together.  This means that a variant will then be
-					included if it is included by each of the inclusion options and is not
-					excluded by any exclusion option.
-				</p>
-				<p>
-					For example, the following command includes any variant that is in either range and that is not in the given file:
-				</p>
-			</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -incl-range 1:-1000 -incl-range 2:-1000 -excl-rsids rsids.txt
-				</div>
-				<div class="task_notes">
-					<p>
-						while the following command includes only
-						variants that are in the given range and have rsid staring with "rs1":
-					</p>
-				</div>
-				<div class="task_command_line">
-					$ qctool -g example.bgen -og subsetted.bgen -incl-range 1:-1000 -incl-variants-matching rsid~rs1%
-				</div>
-			</div>
-		</section>
-
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Filtering variants</h2>
+    <div class="task">
+        <div class="task_name">
+            Filtering variants based on an external file
+        </div>
+        <div class="task_notes">
+            QCTOOL has a set of options to filter variants, each namely:
+            <code>-[in|ex]cl-rsids</code>,
+            <code>-[in|ex]cl-snpids</code>,
+            <code>-[in|ex]cl-positions</code>,
+            <code>-[in|ex]cl-variants</code>,
+            <code>-[in|ex]cl-variants-matching</code>.
+            Here are examples of these options:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -excl-rsids &lt;filename&gt;
+        </div>
+        <div class="task_notes">
+            Here the specified file should contain a whitespace-separated list of rsids that will be excluded from processing.
+        </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -excl-snpids &lt;filename&gt;
+        </div>
+        <div class="task_notes">
+            Ditto, but for alternate IDs.
+        </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -excl-positions &lt;filename&gt;
+        </div>
+        <div class="task_notes">
+            The specified file should contain a list of genomic positions in the format <code>[chromosome:]position</code>.
+            The chromosome should be omitted if you want to specify variants that have missing chromosome information.
+        </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -excl-variants &lt;filename&gt;
+        </div>
+        <div class="task_notes">
+            The specified file should contain a list of variants.  Currently this must be a text file with six named
+             columns; the first four must be <code>SNPID</code>, <code>rsid</code>, <code>chromosome</code>, <code>position</code>,
+             followed by columns containing the first and second alleles.  The <code>-compare-variants-by</code> option control
+             how variants are matched to this file - see the page on <a href="sorting.html">sorting data</a> for more information
+             on this option.
+        </div>
+    </div>
+
+    <div class="task">
+        <div class="task_name">
+            Range filtering
+        </div>
+        <div class="task_notes">
+            The <code>-[in|ex]cl-range</code> option filters variants by range.  E.g.:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -[in|ex]cl-range [chromosome]:[start]-[end]
+        </div>
+        <div class="task_notes">
+            This includes / excludes any variant in the given range.  Ranges are treated as closed ranges,
+            i.e. the range includes both start and end positions.
+            Optionally you can omit the chromosome; this will additionally capture variants that
+            have missing chromosome information. Also, either the start or end positions can be omitted, in which case the range is treated as containing
+            all positions up to the end coordinate, or all variants from the start coordinate onwards respectively.
+            Examples of valid ranges are:
+            <code>1:100-200</code>, <code>1:-200</code>, or <code>X:1000000-</code>.
+        </div>
+    </div>
+
+    <div class="task">
+        <div class="task_name">
+            Wildcard variant filtering
+        </div>
+        <div class="task_notes">
+            You can filter variants based on a wildcard match of ID fields.  E.g.:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -incl-variants-matching rsid~rs1%
+        </div>
+        <div class="task_notes">
+            This command will retain all variants that have rsid starting with 'rs1'.  The general format of this command is:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -incl-variants-matching [field~][value]
+        </div>
+        <div class="task_notes">
+            Here <code>field</code> can be 'snpid' (matching all alternate IDs) or 'rsid' (matching the first, or rs id),
+            or it can be omitted to match any id.  The value can optionally contain a single '%' character, which will
+            expand to match any string value.  A complete match is required, hence the value 'a%b'
+            will match the ID 'ab', 'a1b', etc., but not 'zab' or 'ab2'.
+        </div>
+    </div>
+    <div class="task">
+        <div class="task_name">
+            Combining multiple filters in the same command
+        </div>
+        <div class="task_notes">
+            <p>
+            The logic for processing multiple inclusion/exclusion options is as follows.
+            First, if any inclusion option is specified multiple times, the results are logically ORd together.
+            (Thus, for example specifying <code>-incl-range</code> twice results in including variants in either range).
+            Second, the resulting conditions are ANDed together.  This means that a variant will then be
+            included if it is included by each of the inclusion options and is not
+            excluded by any exclusion option.
+        </p>
+        <p>
+            For example, the following command includes any variant that is in either range and that is not in the given file:
+        </p>
+    </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -incl-range 1:-1000 -incl-range 2:-1000 -excl-rsids rsids.txt
+        </div>
+        <div class="task_notes">
+            <p>
+                while the following command includes only
+                variants that are in the given range and have rsid staring with "rs1":
+            </p>
+        </div>
+        <div class="task_command_line">
+            $ qctool -g example.bgen -og subsetted.bgen -incl-range 1:-1000 -incl-variants-matching rsid~rs1%
+        </div>
+    </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -193,8 +184,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/inferring_ploidy.html
==================================================================
--- doc/html/qctool/documentation/examples/inferring_ploidy.html
+++ doc/html/qctool/documentation/examples/inferring_ploidy.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,81 +16,82 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Working with sex chromosomes</h2>
-				<div class="task">
-					<div class="task_name">
-						Handling haploid and diploid samples
-					</div>
-					<div class="task_notes">
-						Several operations in QCTOOL, including  <code>-snp-stats</code> and <code>-compute-ld-with</code>,
-						handle haploid and diploid genotypes directly.  For example, consider the command:
-					</div>
-					
-					<div class="task_command_line">
-						$ qctool -g &lt;input file&gt; -snp-stats -osnp &lt;output file&gt;
-					</div>
-					<div class="task_notes">
-						When the input file contains X chromosome variants, the output file will contain relevant
-						information including haploid and diploid genotype counts, tests for equal frequency between
-						haploid and diploid samples, and appropriately estimated frequency and imputation certainty metrics.
-					</div>
-				</div>
-			</div
-			<div class="task">
-				<div class="task_name">
-					Inferring ploidy from sex information
-				</div>
-				<div class="task_notes">
-					In order for this to work, it is important that haploid genotypes are encoded appropriately in input files - e.g.
-					by using haploid calls in vcf GT field, or haploid data in BGEN-format files.  However, some file formats (e.g. GEN format)
-					do not support haploid calls, and some datasets (E.g. the 1000 Genomes Project genotype files) choose to encode all calls
-					as diploid even when the underlying genotype is haploid (i.e. for males on the X chromosome).  To work around this,
-					qctool can infer the ploidy from sex information supplied in a sample file.  (This functionality currently has
-					hard-coded ampping of chromosome identifiers to ploidy appropriate for humans).
-				</div>
-				<div class="task_notes">
-					This works as follows.  Suppose <code>sex</code> is the name of a column in the sample file containing sex information
-					- this must be of type 'D', and valid values are <code>male</code>, <code>M</code>, or <code>1</code> for male samples,
-					and <code>female</code>, <code>F</code>, or <code>2</code> for female.  Then, the <code>-infer-ploidy-from</code> option
-					can be used to tell QCTOOL to interpret diploid calls as haploid (or zero-ploid) as appropriate:
-				</div>
-				<div class="task_command_line">
-					$ qctool -g &lt;input file&gt; -infer-ploidy-from sex -snp-stats -osnp &lt;output file&gt;
-				</div>
-				<div class="task_notes">
-					For each genotype QCTOOL applies the following rules:
-					<ol>
-						<li> If input genotype is not diploid, raise an error and terminate program.</li>
-						<li> If the sex of the sample is missing, set the genotype to missing.</li>
-						<li> Otherwise, compute the ploidy of the sample based on the chromosome identifier and the sample sex.</li>
-						<li> If the inferred ploidy is diploid, output the input genotype unchanged.</li>
-						<li> If the inferred ploidy is haploid, check whether the input genotype is homozygous (or, for
-						genotype probabilities, has 100% of the probability mass on homozygous calls).  If so, set the
-						genotype to the corresponding haploid call.  Otherwise, set the genotype to missing.</li>
-					</ol>
-				</div>
-				<div class="task_notes">
-					These rules apply to both hard-coded genotype calls (e.g. vcf GT field) and to
-					genotype probabilities (e.g. vcf GP field / GEN format / BGEN format data).
-				</div>
-			</div>
-		</section>
-
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Working with sex chromosomes</h2>
+        <div class="task">
+            <div class="task_name">
+                Handling haploid and diploid samples
+            </div>
+            <div class="task_notes">
+                Several operations in QCTOOL, including  <code>-snp-stats</code> and <code>-compute-ld-with</code>,
+                handle haploid and diploid genotypes directly.  For example, consider the command:
+            </div>
+
+            <div class="task_command_line">
+                $ qctool -g &lt;input file&gt; -snp-stats -osnp &lt;output file&gt;
+            </div>
+            <div class="task_notes">
+                When the input file contains X chromosome variants, the output file will contain relevant
+                information including haploid and diploid genotype counts, tests for equal frequency between
+                haploid and diploid samples, and appropriately estimated frequency and imputation certainty metrics.
+            </div>
+        </div>
+    </div
+    <div class="task">
+        <div class="task_name">
+            Inferring ploidy from sex information
+        </div>
+        <div class="task_notes">
+            In order for this to work, it is important that haploid genotypes are encoded appropriately in input files - e.g.
+            by using haploid calls in vcf GT field, or haploid data in BGEN-format files.  However, some file formats (e.g. GEN format)
+            do not support haploid calls, and some datasets (E.g. the 1000 Genomes Project genotype files) choose to encode all calls
+            as diploid even when the underlying genotype is haploid (i.e. for males on the X chromosome).  To work around this,
+            qctool can infer the ploidy from sex information supplied in a sample file.  (This functionality currently has
+            hard-coded ampping of chromosome identifiers to ploidy appropriate for humans).
+        </div>
+        <div class="task_notes">
+            This works as follows.  Suppose <code>sex</code> is the name of a column in the sample file containing sex information
+            - this must be of type 'D', and valid values are <code>male</code>, <code>M</code>, or <code>1</code> for male samples,
+            and <code>female</code>, <code>F</code>, or <code>2</code> for female.  Then, the <code>-infer-ploidy-from</code> option
+            can be used to tell QCTOOL to interpret diploid calls as haploid (or zero-ploid) as appropriate:
+        </div>
+        <div class="task_command_line">
+            $ qctool -g &lt;input file&gt; -s &lt;sample file&gt; -infer-ploidy-from sex -snp-stats -osnp &lt;output file&gt;
+        </div>
+        <div class="task_notes">
+            For each genotype QCTOOL applies the following rules:
+            <ol>
+                <li> If input genotype is not diploid, raise an error and terminate program.</li>
+                <li> If the sex of the sample is missing, set the genotype to missing.</li>
+                <li> Otherwise, compute the ploidy of the sample based on the chromosome identifier and the sample sex.</li>
+                <li> If the inferred ploidy is diploid, output the input genotype unchanged.</li>
+                <li> If the inferred ploidy is haploid, check whether the input genotype is homozygous (or, for
+                genotype probabilities, has 100% of the probability mass on homozygous calls).  If so, set the
+                genotype to the corresponding haploid call.  Otherwise, set the genotype to missing.</li>
+            </ol>
+        </div>
+        <div class="task_notes">
+            These rules apply to both hard-coded genotype calls (e.g. vcf GT field) and to
+            genotype probabilities (e.g. vcf GP field / GEN format / BGEN format data).
+        </div>
+    </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -132,8 +123,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/intensities.html
==================================================================
--- doc/html/qctool/documentation/examples/intensities.html
+++ doc/html/qctool/documentation/examples/intensities.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,25 +16,26 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
+			<img src="../../style/images/qctool.png" class="logo">
 		</div>
 
-		<section class="main_text">
-			<h2>Processing intensity data</h2>
-			(under construction)
-		</section>
-
+<section class="main_text">
+    <h2>Processing intensity data</h2>
+    (under construction)
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -76,8 +67,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/merging.html
==================================================================
--- doc/html/qctool/documentation/examples/merging.html
+++ doc/html/qctool/documentation/examples/merging.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,103 +16,104 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Merging variants from one dataset into another</h2>
-				<div class="task">
-					<div class="task_name">
-						Merging data
-					</div>
-					<div class="task_notes">
-						The <code>-merge-in</code> option can be used to merge variants in one dataset into another.  For example:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen
-					</div>
-					<div class="task_notes">
-						<p>
-						This command produces a dataset that contains a record for each variant
-						from <code>first.bgen</code> and a record for each variant from <code>second.bgen</code>
-						- i.e. it has <em>L<sub>1</sub>+L<sub>2</sub></em> variants,
-						where <em>L<sub>1</sub></em> and <em>L<sub>2</sub></em> are the
-						number of variants in the two datsets.
-					</p>
-					<p>
-						Data is output for the set of samples in the first dataset; any other samples in the merged-in dataset are ignored.
-					</p>
-				</div>
-			</div>
-
-			<div class="task">
-					<div class="task_name">
-						Controlling how samples are matched between datasets
-					</div>
-					<div class="task_notes">
-					<p>
-						By default, samples are matched by the first ID column in each dataset.
-						The <code>-match-sample-ids</code> option can be used to change this.  For example:
-					</p>
-					</div>
-					<div class="task_command_line">
-						$ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen -match-sample-ids column1~column2
-					</div>
-					<div class="task_notes">
-						Where <code>column1</code> and <code>column2</code> are columns in <code>first.sample</code> and <code>second.sample</code> respectively,
-							containing the fields to match on.
-							We recommend that sample file columns used to match samples should contain unique sample identifiers.
-					</div>
-				</div>
-				
-			<div class="task">
-					<div class="task_name">
-						Controlling what variants appear in the output
-					</div>
-					<div class="task_notes">
-						<p>
-							The <code>-merge-strategy</code> option controls what happens when the same variant appears in both
-							datasets.  Possible values are <code>-keep-all</code> (the default) or <code>-drop-duplicates</code>.
-							For example:
-						</p>
-					</div>
-						<div class="task_command_line">
-							$ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen -merge-strategy drop-duplicates
-						</div>
-					<div class="task_notes">
-						<p>
-							In this command, if the same variant appears in <code>first.bgen</code> and in <code>second.bgen</code>,
-							only the first will be output.  As when  <a href="combining.html">combining datasets</a>,
-							the <code>-compare-variants-by</code> option is used to control how variants are compared, and it is assumed
-							that variants are sorted by these fields in each input dataset.
-					</p>
-					<p>
-						To further help disambiguate the source of data in the output file,
-						the <code>-merge-prefix</code> option can also be used to add a prefix to the identifier of each merged-in -variant, e.g.:
-					</p>
-				</div>
-					<div class="task_command_line">
-						$ qctool -g first.bgen -s first.sample -merge-in second.bgen -s second.sample -og merged.bgen -merge-prefix "merged:"
-					</div>
-					<div class="task_notes">
-					<p>
-						Currently this only affects the 'alternate' identifier fields (e.g. the SNPID field of GEN or BGEN files).
-					</p>
-				</div>
-			</div>
-		</section>
-
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Merging variants from one dataset into another</h2>
+        <div class="task">
+            <div class="task_name">
+                Merging data
+            </div>
+            <div class="task_notes">
+                The <code>-merge-in</code> option can be used to merge variants in one dataset into another.  For example:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen
+            </div>
+            <div class="task_notes">
+                <p>
+                This command produces a dataset that contains a record for each variant
+                from <code>first.bgen</code> and a record for each variant from <code>second.bgen</code>
+                - i.e. it has <em>L<sub>1</sub>+L<sub>2</sub></em> variants,
+                where <em>L<sub>1</sub></em> and <em>L<sub>2</sub></em> are the
+                number of variants in the two datsets.
+            </p>
+            <p>
+                Data is output for the set of samples in the first dataset; any other samples in the merged-in dataset are ignored.
+            </p>
+        </div>
+    </div>
+
+    <div class="task">
+            <div class="task_name">
+                Controlling how samples are matched between datasets
+            </div>
+            <div class="task_notes">
+            <p>
+                By default, samples are matched by the first ID column in each dataset.
+                The <code>-match-sample-ids</code> option can be used to change this.  For example:
+            </p>
+            </div>
+            <div class="task_command_line">
+                $ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen -match-sample-ids column1~column2
+            </div>
+            <div class="task_notes">
+                Where <code>column1</code> and <code>column2</code> are columns in <code>first.sample</code> and <code>second.sample</code> respectively,
+                    containing the fields to match on.
+                    We recommend that sample file columns used to match samples should contain unique sample identifiers.
+            </div>
+        </div>
+
+    <div class="task">
+            <div class="task_name">
+                Controlling what variants appear in the output
+            </div>
+            <div class="task_notes">
+                <p>
+                    The <code>-merge-strategy</code> option controls what happens when the same variant appears in both
+                    datasets.  Possible values are <code>-keep-all</code> (the default) or <code>-drop-duplicates</code>.
+                    For example:
+                </p>
+            </div>
+                <div class="task_command_line">
+                    $ qctool -g first.bgen -s first.sample -merge-in second.bgen second.sample -og merged.bgen -merge-strategy drop-duplicates
+                </div>
+            <div class="task_notes">
+                <p>
+                    In this command, if the same variant appears in <code>first.bgen</code> and in <code>second.bgen</code>,
+                    only the first will be output.  As when  <a href="combining.html">combining datasets</a>,
+                    the <code>-compare-variants-by</code> option is used to control how variants are compared, and it is assumed
+                    that variants are sorted by these fields in each input dataset.
+            </p>
+            <p>
+                To further help disambiguate the source of data in the output file,
+                the <code>-merge-prefix</code> option can also be used to add a prefix to the identifier of each merged-in -variant, e.g.:
+            </p>
+        </div>
+            <div class="task_command_line">
+                $ qctool -g first.bgen -s first.sample -merge-in second.bgen -s second.sample -og merged.bgen -merge-prefix "merged:"
+            </div>
+            <div class="task_notes">
+            <p>
+                Currently this only affects the 'alternate' identifier fields (e.g. the SNPID field of GEN or BGEN files).
+            </p>
+        </div>
+    </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -154,8 +145,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/pipelining.html
==================================================================
--- doc/html/qctool/documentation/examples/pipelining.html
+++ doc/html/qctool/documentation/examples/pipelining.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,82 +16,82 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Using qctool in a pipeline</h2>
-				<div class="task">
-					<div class="task_name">
-						Outputting data to stdout
-					</div>
-					<div class="task_notes">
-						Using "-" as an output file specifier will output data to standard output, that can then be redirected
-						or piped into other commands.  For example:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -og -
-					</div>
-					<div class="task_notes">
-						This outputs genotype data to stdout.
-						(By default output is in VCF format; use the <code>-ofiletype</code> option to alter this).
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -snp-stats -osnp -
-					</div>
-					<div class="task_notes">
-						This outputs SNP summary statistics to standard output.
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Inputting data from stdin
-					</div>
-					<div class="task_notes">
-						QCTOOL has limited support for reading data from stdin.
-						To do this, specify "-" as the argument to <code>-g</code>, and specify the format of the input data
-						using the <code>-filetype</code> option, e.g.:
-					</div>
-					<div class="task_command_line">
-						$ cat file.bgen | qctool -g - -filetype bgen [other options]
-					</div>
-					<div class="task_notes">
-					  <p>
-							This functionality is currently limited to input data in BGEN format (<code>-filetype bgen</code>)
-							or in VCF format (<code>-filetype vcf</code>).  VCF format data should be streamed uncompressed, e.g.:
-						</p>
-					<div class="task_command_line">
-						$ cat file.vcf.gz | gunzip -c | qctool -g - -filetype vcf [other options]
-					</div>
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Pipelining QCTOOL with other tools
-					</div>
-					<div class="task_notes">
-						As an example, the following command uses <a href="http://bitbucket.org/gavinband/bgen">bgenix</a> with QCTOOL to
-						compute snp summary statistics from a subset of a BGEN file, and view the result on the fly using
-						<a href="https://en.wikipedia.org/wiki/Less_(Unix)"><code>less</code></a>.
-					</div>
-					<div class="task_command_line">
-						$ bgenix -g file.bgen -range 11:3500000-6500000 | qctool -g - -filetype bgen -snp-stats -osnp - | less -S
-					</div>
-				</div>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Using qctool in a pipeline</h2>
+        <div class="task">
+            <div class="task_name">
+                Outputting data to stdout
+            </div>
+            <div class="task_notes">
+                Using "-" as an output file specifier will output data to standard output, that can then be redirected
+                or piped into other commands.  For example:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -og -
+            </div>
+            <div class="task_notes">
+                This outputs genotype data to stdout.
+                (By default output is in VCF format; use the <code>-ofiletype</code> option to alter this).
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -snp-stats -osnp -
+            </div>
+            <div class="task_notes">
+                This outputs SNP summary statistics to standard output.
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Inputting data from stdin
+            </div>
+            <div class="task_notes">
+                QCTOOL has limited support for reading data from stdin.
+                To do this, specify "-" as the argument to <code>-g</code>, and specify the format of the input data
+                using the <code>-filetype</code> option, e.g.:
+            </div>
+            <div class="task_command_line">
+                $ cat file.bgen | qctool -g - -filetype bgen [other options]
+            </div>
+            <div class="task_notes">
+              <p>
+                    This functionality is currently limited to input data in BGEN format (<code>-filetype bgen</code>)
+                    or in VCF format (<code>-filetype vcf</code>).  VCF format data should be streamed uncompressed, e.g.:
+                </p>
+            <div class="task_command_line">
+                $ cat file.vcf.gz | gunzip -c | qctool -g - -filetype vcf [other options]
+            </div>
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Pipelining QCTOOL with other tools
+            </div>
+            <div class="task_notes">
+                As an example, the following command uses <a href="http://bitbucket.org/gavinband/bgen">bgenix</a> with QCTOOL to
+                compute snp summary statistics from a subset of a BGEN file, and view the result on the fly using
+                <a href="https://en.wikipedia.org/wiki/Less_(Unix)"><code>less</code></a>.
+            </div>
+            <div class="task_command_line">
+                $ bgenix -g file.bgen -range 11:3500000-6500000 | qctool -g - -filetype bgen -snp-stats -osnp - | less -S
+            </div>
+        </div>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -131,10 +121,10 @@
 					<a href="../../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/sorting.html
==================================================================
--- doc/html/qctool/documentation/examples/sorting.html
+++ doc/html/qctool/documentation/examples/sorting.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,86 +16,87 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Sorting and reordering data</h2>
-				<div class="task">
-					<div class="task_name">
-						Sorting variants
-					</div>
-					<div class="task_notes">
-						The <code>-sort</code> option tells QCTOOL to sort variants in its output file:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -og sorted.bgen -sort
-					</div>
-					<div class="task_notes">
-						<p>
-							The way this works is that QCTOOL first writes the data to a temporary file in the order that it is processed,
-							keeping a record of the file locations of each variant in memory.  It then copies each variant from the
-							temporary file to the destination in the desired order.
-						</p>
-						<p>
-							The sort operation currently works for BGEN, unzipped GEN, and unzipped VCF output formats.
-					</p>
-
-						</p>
-						<p>
-						By default QCTOOL sorts based on on genomic position,
-						alleles, and ID fields.  You can change this by specifying the <code>-compare-variants-by</code> option, e.g.:
-					</p>
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -og sorted.bgen -sort -compare-variants-by ids
-					</div>
-					<div class="task_notes">
-						<p>
-							Possible fields that can be sorted on are: <code>position</code>, <code>alleles</code>,
-						<code>ids</code>, <code>rsid</code> (which refers to the first or primary ID in the dataset),
-						or <code>snpid</code> (which refers all but the first ID in each dataset).
-					</p>
-					</div>
-				</div>
-				<div class="task">
-					<div class="task_name">
-						Reordering samples
-					</div>
-					<div class="task_notes">
-						The <code>-reorder</code> option tells QCTOOL to reorder samples in its input.  The format is:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -og reordered.bgen -reorder &lt;filename&gt;
-					</div>
-					<div class="task_notes">
-						<p>
-						where <code>&lt;filename&gt;</code> is the name of a readable file containing sample identifiers.
-						This file must contain exactly <em>N</em> identifiers (if there are <em>N</em> samples being processed)
-						and each identifer must be the primary identifier of a sample being processed.</p>
-						<p>Alternatively, <code>-reorder</code> can take one of following the two special values:
-							<code>-reorder backwards</code> will reverse the order of samples, and <code>-reorder randomly</code> will
-							randomly reorder samples.
-						</p>
-					</div>
-					
-					
-					
-					
-				</div>
-		</section>
-		
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Sorting and reordering data</h2>
+        <div class="task">
+            <div class="task_name">
+                Sorting variants
+            </div>
+            <div class="task_notes">
+                The <code>-sort</code> option tells QCTOOL to sort variants in its output file:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -og sorted.bgen -sort
+            </div>
+            <div class="task_notes">
+                <p>
+                    The way this works is that QCTOOL first writes the data to a temporary file in the order that it is processed,
+                    keeping a record of the file locations of each variant in memory.  It then copies each variant from the
+                    temporary file to the destination in the desired order.
+                </p>
+                <p>
+                    The sort operation currently works for BGEN, unzipped GEN, and unzipped VCF output formats.
+            </p>
+
+                </p>
+                <p>
+                By default QCTOOL sorts based on on genomic position,
+                alleles, and ID fields.  You can change this by specifying the <code>-compare-variants-by</code> option, e.g.:
+            </p>
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -og sorted.bgen -sort -compare-variants-by ids
+            </div>
+            <div class="task_notes">
+                <p>
+                    Possible fields that can be sorted on are: <code>position</code>, <code>alleles</code>,
+                <code>ids</code>, <code>rsid</code> (which refers to the first or primary ID in the dataset),
+                or <code>snpid</code> (which refers all but the first ID in each dataset).
+            </p>
+            </div>
+        </div>
+        <div class="task">
+            <div class="task_name">
+                Reordering samples
+            </div>
+            <div class="task_notes">
+                The <code>-reorder</code> option tells QCTOOL to reorder samples in its input.  The format is:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -og reordered.bgen -reorder &lt;filename&gt;
+            </div>
+            <div class="task_notes">
+                <p>
+                where <code>&lt;filename&gt;</code> is the name of a readable file containing sample identifiers.
+                This file must contain exactly <em>N</em> identifiers (if there are <em>N</em> samples being processed)
+                and each identifer must be the primary identifier of a sample being processed.</p>
+                <p>Alternatively, <code>-reorder</code> can take one of following the two special values:
+                    <code>-reorder backwards</code> will reverse the order of samples, and <code>-reorder randomly</code> will
+                    randomly reorder samples.
+                </p>
+            </div>
+
+
+
+
+        </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -137,8 +128,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/examples/summary_statistics.html
==================================================================
--- doc/html/qctool/documentation/examples/summary_statistics.html
+++ doc/html/qctool/documentation/examples/summary_statistics.html
@@ -1,25 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../../js/jquery-1.4.2.min.js"></script>
+
+		<script type="text/javascript" src="../../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../../js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="../../js/datatables.min.js"></script>
 		<link href="../../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -26,143 +16,144 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<h2>Computing summary statistics</h2>
-				<div class="task">
-					<div class="task_name">
-						Per-sample summary statistics
-					</div>
-					<div class="task_notes">
-						The <code>-sample-stats</code> option can be used to compute per-sample summary statistics.
-						The output goes to a file specified by the <code>-osample</code> option.  E.g:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -sample-stats -osample sample-stats.txt
-					</div>
-					<div class="task_notes">
-						<p>
-							This computes per-sample summary statistics (average missingness and heterozygosity) and places
-							them in the file <Code>sample-stats.txt</code>.  Additionally, if array intensity data
-							is available (see <a href="intensities.html">processing intensity data</a>), average X channel, Y
-							channel, total (X+Y) and difference (X-Y) of intensities will be computed.
-							These can be used useful for QC purposes - for example,
-							average intensity on the X and Y chromosomes can be used to directly determine sample gender.
-						</p>
-						<p>
-							<b>Note:</b> the output file can be formatted in various of ways, controlled by the file extension.
-							See the page on <a href="../summary_file_formats.html">summary statistic file formats</a> for
-							information on output file formatting.
-						</p>
-					</div>
-				</div>
-
-				<div class="task">
-					<div class="task_name">
-						Per-variant summary statistics
-					</div>
-					<div class="task_notes">
-						The basic option to compute per-variant summary statistics is <code>-snp-stats</code>.  E.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -snp-stats -osnp snp-stats.txt
-					</div>
-					<div class="task_notes">
-						<p>
-							This will compute genotype counts, allele counts and frequencies, missing data rates, info metrics, and a P-value
-							against the null that genotypes are in Hardy-Weinberg proportions in diploid samples.  Output is sent to the
-							file specified in the <code>-osnp</code> option.  See the page on <a href="../summary_file_formats.html">summary statistic file formats</a> for
-							information on output file formatting.
-						</p>
-						<p>
-							Analysis on the sex chromosomes is complicated by the fact that males and females have differing ploidy.
-							To process sex chromosomes correctly, QCTOOL relies on the ploidy being correct in the input genotype files.
-							However, some data sets (and some file formats) instead encode males as diploid homozygotes.
-							The <code>-infer-ploidy-from</code> can be used to deal with such data - see the
-							page on <a href="inferring_ploidy.html">inferring ploidy</a> .
-						</p>
-						<p>
-							For sex chromosomes, QCTOOL outputs both diploid and haploid
-							genotype counts, as well an appropriate allele frequency, a sex-chromosome specific info metric,
-							and a test for difference in frequency between males and females.  
-						</p>
-					</div>
-				</div>
-
-				<div class="task">
-					<div class="task_name">
-						Differential missingness
-					</div>
-					<div class="task_notes">
-						It's often useful to compare levels of missingness between different samples.  The <code>-differential</code>
-						option can be used to compare levels of missingness between samples having different levels of a covariate
-						in the sample file.  E.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -osnp snp-stats.txt -differential &lt;column&gt;
-					</div>
-					<div class="task_notes">
-						This computes: the count of missing and non-missing genotypes in each level of the covariate specified in
-						the specified column, and a likelihood ratio test P-value comparing missing data rates in the different levels.
-						Additionally, if the covariate has exactly two levels, a Fishers exact test P-value is also computed.
-					</div>
-				</div>
-				
-				<div class="task">
-					<div class="task_name">
-						Combining options
-					</div>
-					<div class="task_notes">
-						Summary statistic options can be combined; e.g:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -osnp snp-stats.txt -differential &lt;column&gt;
-					</div>
-					<div class="task_notes">
-						This computes both basic summary statistics and values for differential missingness, and places it in the same output file.
-					</div>
-				</div>
-
-				<div class="task">
-					<div class="task_name">
-						Stratifying summary statistics
-					</div>
-					<div class="task_notes">
-						The <code>-stratify</code> option can be used to compute summary statistics stratified over
-						subsets of the data. E.g.:
-					</div>
-					<div class="task_command_line">
-						$ qctool -g example.bgen -s example.sample -snp-stats -osnp snp-stats.txt -stratify &lt;column&gt;
-					</div>
-					<div class="task_notes">
-						<p>The argument must be the name of a column in the sample file containing discrete
-							values (i.e. it must be of type <code>B</code> or <code>D</code>).  Summary statistic calculations will
-						be computed for each subset of samples having the same value in that column.
-						The output will contain the same fields as for <code>-snp-stats</code>, but each column will
-						appear multiple times with a suffix of the form <code>[&lt;column&gt;=&lt;value&gt;]</code>
-						to denote which strata the values are computed for.
-					</p>
-						<p>
-							This feature has several possible use cases - for example, it can be used to compute allele counts across ethnic groups in a
-							sample of mixed ancestry, or to inspect deviation from Hardy-Weinberg equilibrium seperately in disease cases and controls.
-						</p>
-					</div>
-				</div>
-		</section>
-
+			<img src="../../style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+    <h2>Computing summary statistics</h2>
+        <div class="task">
+            <div class="task_name">
+                Per-sample summary statistics
+            </div>
+            <div class="task_notes">
+                The <code>-sample-stats</code> option can be used to compute per-sample summary statistics.
+                The output goes to a file specified by the <code>-osample</code> option.  E.g:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -sample-stats -osample sample-stats.txt
+            </div>
+            <div class="task_notes">
+                <p>
+                    This computes per-sample summary statistics (average missingness and heterozygosity) and places
+                    them in the file <Code>sample-stats.txt</code>.  Additionally, if array intensity data
+                    is available (see <a href="intensities.html">processing intensity data</a>), average X channel, Y
+                    channel, total (X+Y) and difference (X-Y) of intensities will be computed.
+                    These can be used useful for QC purposes - for example,
+                    average intensity on the X and Y chromosomes can be used to directly determine sample gender.
+                </p>
+                <p>
+                    <b>Note:</b> the output file can be formatted in various of ways, controlled by the file extension.
+                    See the page on <a href="../summary_file_formats.html">summary statistic file formats</a> for
+                    information on output file formatting.
+                </p>
+            </div>
+        </div>
+
+        <div class="task">
+            <div class="task_name">
+                Per-variant summary statistics
+            </div>
+            <div class="task_notes">
+                The basic option to compute per-variant summary statistics is <code>-snp-stats</code>.  E.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -snp-stats -osnp snp-stats.txt
+            </div>
+            <div class="task_notes">
+                <p>
+                    This will compute genotype counts, allele counts and frequencies, missing data rates, info metrics, and a P-value
+                    against the null that genotypes are in Hardy-Weinberg proportions in diploid samples.  Output is sent to the
+                    file specified in the <code>-osnp</code> option.  See the page on <a href="../summary_file_formats.html">summary statistic file formats</a> for
+                    information on output file formatting.
+                </p>
+                <p>
+                    Analysis on the sex chromosomes is complicated by the fact that males and females have differing ploidy.
+                    To process sex chromosomes correctly, QCTOOL relies on the ploidy being correct in the input genotype files.
+                    However, some data sets (and some file formats) instead encode males as diploid homozygotes.
+                    The <code>-infer-ploidy-from</code> can be used to deal with such data - see the
+                    page on <a href="inferring_ploidy.html">inferring ploidy</a> .
+                </p>
+                <p>
+                    For sex chromosomes, QCTOOL outputs both diploid and haploid
+                    genotype counts, as well an appropriate allele frequency, a sex-chromosome specific info metric,
+                    and a test for difference in frequency between males and females.  
+                </p>
+            </div>
+        </div>
+
+        <div class="task">
+            <div class="task_name">
+                Differential missingness
+            </div>
+            <div class="task_notes">
+                It's often useful to compare levels of missingness between different samples.  The <code>-differential</code>
+                option can be used to compare levels of missingness between samples having different levels of a covariate
+                in the sample file.  E.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -osnp snp-stats.txt -differential &lt;column&gt;
+            </div>
+            <div class="task_notes">
+                This computes: the count of missing and non-missing genotypes in each level of the covariate specified in
+                the specified column, and a likelihood ratio test P-value comparing missing data rates in the different levels.
+                Additionally, if the covariate has exactly two levels, a Fishers exact test P-value is also computed.
+            </div>
+        </div>
+
+        <div class="task">
+            <div class="task_name">
+                Combining options
+            </div>
+            <div class="task_notes">
+                Summary statistic options can be combined; e.g:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -osnp snp-stats.txt -differential &lt;column&gt;
+            </div>
+            <div class="task_notes">
+                This computes both basic summary statistics and values for differential missingness, and places it in the same output file.
+            </div>
+        </div>
+
+        <div class="task">
+            <div class="task_name">
+                Stratifying summary statistics
+            </div>
+            <div class="task_notes">
+                The <code>-stratify</code> option can be used to compute summary statistics stratified over
+                subsets of the data. E.g.:
+            </div>
+            <div class="task_command_line">
+                $ qctool -g example.bgen -s example.sample -snp-stats -osnp snp-stats.txt -stratify &lt;column&gt;
+            </div>
+            <div class="task_notes">
+                <p>The argument must be the name of a column in the sample file containing discrete
+                    values (i.e. it must be of type <code>B</code> or <code>D</code>).  Summary statistic calculations will
+                be computed for each subset of samples having the same value in that column.
+                The output will contain the same fields as for <code>-snp-stats</code>, but each column will
+                appear multiple times with a suffix of the form <code>[&lt;column&gt;=&lt;value&gt;]</code>
+                to denote which strata the values are computed for.
+            </p>
+                <p>
+                    This feature has several possible use cases - for example, it can be used to compute allele counts across ethnic groups in a
+                    sample of mixed ancestry, or to inspect deviation from Hardy-Weinberg equilibrium seperately in disease cases and controls.
+                </p>
+            </div>
+        </div>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -194,8 +185,8 @@
 			<div class="nav_button" name="download">
 				<a href="../../documentation/download.html">download</a>
 			</div>
 </div>
 </nav>
-		
+
 	</body>
 </html>

Index: doc/html/qctool/documentation/genotype_file_formats.html
==================================================================
--- doc/html/qctool/documentation/genotype_file_formats.html
+++ doc/html/qctool/documentation/genotype_file_formats.html
@@ -1,35 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../js/jquery-1.4.2.min.js"></script>
-		<script type="text/javascript" src="../js/jquery.ba-hashchange.min.js"></script>
+
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../js/local.js"></script>
-
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
-
-		<script type="text/javascript">
-			$(document).ready(
-				function() {
-					setFirstPage( "overview" ) ;
-				}
-			) ;
-		</script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
 		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -36,217 +16,221 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
+			<img src="../style/images/qctool.png" class="logo">
 		</div>
 
-		<section class="main_text">
-			<h2>Genotype file formats</h2>
-				<p>
-					QCTOOL supports the following file formats for genotype data:
-				</p>
-					<table class="file_formats">
-						<colgroup>
-							<col class="acronym">
-							<col class="io">
-							<col class="filetype">
-							<col class="notes">
-						</colgroup>
-						<thead>
-							<tr>
-							<th>
-								<div>Format</div> <small>(recognised extensions)</small>
-							</th>
-							<th>
-								I/O
-							</th>
-							<th>
-								<div>Filetype</div>
-								<small>(For <span><nobr><code>-[o]filetype</code></nobr></span>)</small>
-							</th>
-							<th>
-								Notes
-							</th>
-						</tr>
-					</thead>
-						<tbody>
-						<tr>
-							<td>
-								<div><a href="http://www.stats.ox.ac.uk/%7Emarchini/software/gwas/file_format.html">GEN</a></div>
-								<code>(.gen, .gen.gz)</code>
-							</td>
-							<td>both</td>
-							<td><code>gen</code></td>
-							<td>
-								Optionally, an extra initial column containing chromosomes can be included in the input.  QCTOOL auto-detects this
-								in input files by counting the columns in the file.
-								To suppress this column in output files, use the <span class="monospace">-omit-chromosome</span> option.
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="http://www.well.ox.ac.uk/~gav/bgen_format/bgen_format.html">BGEN</a></div>
-								<code>(.bgen)</code>
-							</td>
-							<td>both</td>
-							<td><code>bgen</code></td>
-							<td>
-								<p>Output files are in BGEN v1.2 with 16 bits per probability and compressed
-								using <a href="http://www.zlib.net">zlib</a> by default. 
-								The <code>-bgen-bits</code> option can be used to adjust the number of bits used.
-								The <code>-bgen-compression</code> option can be used to choose the method of compression
-								(either zlib or <a href="http://www.zstd.net">zstd</a>).<p>
-								<p>Use <code>-ofiletype bgen_v1.1</code> to force writing files compatible with the BGEN v1.1 spec.</p>
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="http://samtools.github.io/hts-specs/VCFv4.2.pdf">VCF</a></div>
-								<code>(.vcf, .vcf.gz)</code>
-							</td>
-							<td>both</td>
-							<td><code>vcf</code></td>
-							<td>
-								<p>QCTOOL is strict about VCF metadata in input files for the fields it reads.  Since 
-								metadata is not always correct a <span class="monospace">-metadata</span> option is
-								provided to override the input file metadata. Currently, only genotypes are output
-								when outputting VCF files.</p>
-								<p>Note that QCTOOL does not apply PHRED scaling to probabilities
-								in the GP field.</p>
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="">PLINK binary format</a></div>
-								<code>(.bed, .bim, .fam)</code>
-							</td>
-							<td>both</td>
-							<td><code>binary_ped</code></td>
-							<td>
-								Note that QCTOOL currently does only the most basic processing of
-								FAM files: when reading, it uses them to count the number of samples in the BED file, when writing it writes a FAM file
-								with missing data in all fields except the ID field.  You will therefore need to create fuller FAM files seperately for use with
-								other tools.
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="https://mathgen.stats.ox.ac.uk/genetics_software/shapeit/shapeit.html#hapsample">SHAPEIT</a> haplotype format</div>
-							</td>
-							<td>both</td>
-							<td><code>shapeit_haplotypes</code></td>
-							<td>
-								For genotypic computations, genotypes are formed from pairs of haplotypes; it is assumed that the two haplotypes for each individual
-								are consecutive columns in the file. (This format is
-								described <a href="http://www.shapeit.fr/pages/hapssample.html">here</a>.)
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="http://mathgen.stats.ox.ac.uk/impute/impute_v2.html">IMPUTE</a> allele probabilities format</div>
-							</td>
-							<td>both</td>
-							<td><code>impute_allele_probs</code></td>
-							<td>
-								to specify reading or writing this filetype.  This file format is like the
-								shapeit haplotype format but contains a probability for
-								each haplotype (i.e. two probabilities per individual),
-								specifying the probability that the haplotype carries the second allele.
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="http://mathgen.stats.ox.ac.uk/impute/impute_v2.html">IMPUTE</a> haplotype format</div>
-							</td>
-							<td>Input only</td>
-							<td><code>impute_haplotypes</code></td>
-							<td>
-								It is assumed the legend file name is the same as the haplotypes file name, minus extension,
-								with <span class="monospace">.legend</span> appended; QCTOOL will also remove/add the
-								<code>.gz</code> extension as appropriate.
-								For genotypic computations, genotypes are formed from pairs of haplotypes;
-								it is assumed that the two haplotypes for each individual are consecutive columns in the haplotypes file.
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="https://oxfordhla.well.ox.ac.uk/hla/">HLAIMP</a> probability format</div>
-							</td>
-							<td>Input only</td>
-							<td><code>hlaimp</code></td>
-							<td>
-								Currently, this input format implicitly splits each HLA locus as a series of bi-allelic variants.
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div>QCTOOL 'long' format</div>
-							</td>
-							<td>Input only</td>
-							<td><code>long</code></td>
-							<td>
-								Input must be a file with columns <code>SNPID, rsid, chromosome, position, number_of_alleles,
-									allele1, other_alleles, sample_id, ploidy, genotype</code>.
-								Further columns may also be included (but QCTOOL ignores these).
-								Allelesin the other_alleles column must be comma-separated (as with <a href="http://samtools.github.io/hts-specs/VCFv4.2.pdf">VCF</a> ALT alleles).
-								When outputting to vcf format, both genotype (GT) and a field 'typed' indicating whether a row for each
-								sample and variant was present will be output.
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="http://penncnv.openbioinformatics.org/en/latest/">PennCNV</a>
-								/ <a href="https://sites.google.com/site/quantisnp/">QuantiSNP</a> format</div>
-							</td>
-							<td>Output only</td>
-							<td><code>penncnv</code></td>
-							<td>
-								PennCNV uses a single sample per input file, this can be acheived using the sample filtering options,
-								e.g. <code>-incl-samples-where ID_1=&lt;identifier&gt;</code>
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div><a href="http://stephenslab.uchicago.edu/software.html#bimbam">BIMBAM</a> dosage format;</div>
-								<div>QCTOOL dosage format</div>
-								<code>(.dosage[.gz])</code>
-							</td>
-							<td>Output only</td>
-							<td><code>bimbam_dosage</code> or <code>dosage</code></td>
-							<td>
-								This file outputs a single column per sample (named by the sample identifier) containing the
-								expected second allele dosage for the sample at each variant.
-								The formats differ in that BIMBAM format has no chromosome/position information.
-							</td>
-						</tr>
-						<tr>
-							<td>
-								<div>QCTOOL intensity text format</div>
-								<code>.intensity[.gz]</code>
-							</td>
-							<td>Output only</td>
-							<td><code>intensity</code></td>
-							<td>
-								The output file has two columns per sample, representing X and Y channel intensities for the
-								sample at each variant.  Currently data must be read from a VCF file; the field is specified
-								using the <code>-vcf-intensity-field</code> option.
-							</td>
-						</tr>
-						<tbody>
-					</table>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+<section class="main_text">
+    <h2>Genotype file formats</h2>
+    <p>
+        QCTOOL supports the following file formats for genotype data:
+    </p>
+    <table class="file_formats">
+        <colgroup>
+            <col class="acronym" style="width:20%">
+            <col class="filetype" style="width:20%">
+            <col class="notes" style="width:65%">
+        </colgroup>
+        <thead>
+            <tr>
+            <th>
+                <div>Format</div> <small>(recognised extensions)</small>
+            </th>
+            <th>
+                <div>Filetype</div>
+                <small>(For <span><nobr><code>-[o]filetype</code></nobr></span>)</small>
+            </th>
+            <th>
+                Notes
+            </th>
+        </tr>
+    </thead>
+        <tbody>
+        <tr>
+            <td>
+                <div><a href="https://www.well.ox.ac.uk/~gav/snptest/#input_file_formats">GEN</a></div>
+                <code>(.gen, .gen.gz)</code>
+                <br><small>(Input / output)</small>
+            </td>
+            <td><code>gen</code></td>
+            <td>
+                Optionally, an extra initial column containing chromosomes can be included in the input.  QCTOOL auto-detects this
+                in input files by counting the columns in the file.
+                To suppress this column in output files, use the <span class="monospace">-omit-chromosome</span> option.
+                The GEN format is further described <a href="https://www.well.ox.ac.uk/~gav/snptest/#input_file_formats">here</a>.
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <div><a href="http://www.bgenformat.org">BGEN</a></div>
+                <code>(.bgen)</code>
+                <br><small>(Input / output)</small>
+            </td>
+            <td><code>bgen</code></td>
+            <td>
+                <p>Output files are in BGEN v1.2 with 16 bits per probability and compressed
+                using <a href="http://www.zlib.net">zlib</a> by default. 
+                The <code>-bgen-bits</code> option can be used to adjust the number of bits used.
+                The <code>-bgen-compression</code> option can be used to choose the method of compression
+                (either zlib or <a href="http://www.zstd.net">zstd</a>).<p>
+                <p>Use <code>-ofiletype bgen_v1.1</code> to force writing files compatible with the BGEN v1.1 spec.</p>
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <div><a href="http://samtools.github.io/hts-specs/VCFv4.2.pdf">VCF</a></div>
+                <code>(.vcf, .vcf.gz)</code>
+                <br><small>(Input / output)</small>
+            </td>
+            <td><code>vcf</code></td>
+            <td>
+                <p>QCTOOL is strict about VCF metadata in input files for the fields it reads.  Since 
+                metadata is not always correct a <span class="monospace">-metadata</span> option is
+                provided to override the input file metadata. Currently, only genotypes are output
+                when outputting VCF files.</p>
+                <p>Note that QCTOOL does not apply PHRED scaling to probabilities
+                in the GP field.</p>
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <div><a href="https://www.cog-genomics.org/plink/2.0/formats">PLINK binary format</a></div>
+                <code>(.bed, .bim, .fam)</code>
+                <br><small>(Input / output)</small>
+            </td>
+            <td><code>binary_ped</code></td>
+            <td>
+                Note that QCTOOL currently does only the most basic processing of
+                FAM files: when reading, it uses them to count the number of samples in the BED file, when writing it writes a FAM file
+                with missing data in all fields except the ID field.  You will therefore need to create fuller FAM files seperately for use with
+                other tools.
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <div><a href="https://mathgen.stats.ox.ac.uk/genetics_software/shapeit/shapeit.html#hapsample">SHAPEIT</a> <small>haplotype format</small></div>
+                <br><small>(Input / output)</small>
+            </td>
+            <td><code>shapeit_haplotypes</code></td>
+            <td>
+
+                This format has five initial columns (`SNPID`, `rsid`, `position`, first and seconda alleles) followed
+                by two columns for each sample representing the two haplotypes. These columns contain 0 (representing the first
+                allele) or 1 (representing the second allele). The first column is sometimes used to record the chromosome instead
+                of a seperate ID, but to my knowledge this is a convention. QCTOOL does not interpret the first column as
+                chromosome information, but the `-assume-chromosome` option can be used to work around this.
+                To convert haplotypes to genotypes, QCTOOL assumes that the two haplotypes for each individual are
+                consecutive columns in the file. (This format is described <a
+                href="https://mathgen.stats.ox.ac.uk/genetics_software/shapeit/shapeit.html#hapsample">here</a>.)
+
+            </td>
+        </tr>
+        <tr>
+            <td>
+                IMPUTE <small>allele probabilities format</small></div>
+                <br><small>(Input / output)</small>
+            </td>
+            <td><code>impute_allele_probs</code></td>
+            <td>
+
+                This file format is like the shapeit haplotype format but contains a probability for each haplotype
+                (i.e. two probabilities per individual), specifying the probability that the haplotype carries the second allele.
+
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <div><a href="http://mathgen.stats.ox.ac.uk/impute/impute_v2.html">IMPUTE</a> <small>haplotype format</small></div>
+                <br><small>(Input only)</small>
+            </td>
+            <td><code>impute_haplotypes</code></td>
+            <td>
+                It is assumed the legend file name is the same as the haplotypes file name, minus extension,
+                with <span class="monospace">.legend</span> appended; QCTOOL will also remove/add the
+                <code>.gz</code> extension as appropriate.
+                For genotypic computations, genotypes are formed from pairs of haplotypes;
+                it is assumed that the two haplotypes for each individual are consecutive columns in the haplotypes file.
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <div><a href="https://oxfordhla.well.ox.ac.uk/hla/">HLAIMP</a> <small>probability format</small></div>
+                <br><small>(Input only)</small>
+            </td>
+            <td><code>hlaimp</code></td>
+            <td>
+                Currently, this input format implicitly splits each HLA locus as a series of bi-allelic variants.
+            </td>
+        </tr>
+        <tr>
+            <td>
+                QCTOOL <small>'long' format</small>
+                <br><small>(Input only)</small>
+            </td>
+            <td><code>long</code></td>
+            <td>
+                Input must be a file with columns <code>SNPID, rsid, chromosome, position, number_of_alleles,
+                    allele1, other_alleles, sample_id, ploidy, genotype</code>.
+                Further columns may also be included (but QCTOOL ignores these).
+                Allelesin the other_alleles column must be comma-separated (as with <a href="http://samtools.github.io/hts-specs/VCFv4.2.pdf">VCF</a> ALT alleles).
+                When outputting to vcf format, both genotype (GT) and a field 'typed' indicating whether a row for each
+                sample and variant was present will be output.
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <a href="http://penncnv.openbioinformatics.org/en/latest/">PennCNV</a>
+                / <a href="https://sites.google.com/site/quantisnp/">QuantiSNP</a> format
+                <br><small>(Output only)</small>
+            </td>
+            <td><code>penncnv</code></td>
+            <td>
+                PennCNV uses a single sample per input file, this can be acheived using the sample filtering options,
+                e.g. <code>-incl-samples-where ID_1=&lt;identifier&gt;</code>
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <div><a href="http://stephenslab.uchicago.edu/software.html#bimbam">BIMBAM</a> <small>dosage format</small>;</div>
+                <div>QCTOOL <small>dosage format</small></div>
+                <code>(.dosage[.gz])</code>
+                <br><small>(Output only)</small>
+            </td>
+            <td><code>bimbam_dosage</code> or <code>dosage</code></td>
+            <td>
+                This file outputs a single column per sample (named by the sample identifier) containing the
+                expected second allele dosage for the sample at each variant.
+                The formats differ in that BIMBAM format has no chromosome/position information.
+            </td>
+        </tr>
+        <tr>
+            <td>
+                <div>QCTOOL <small>intensity text format</small></div>
+                <code>.intensity[.gz]</code>
+                <br><small>(Output only)</small>
+            </td>
+            <td><code>intensity</code></td>
+            <td>
+                The output file has two columns per sample, representing X and Y channel intensities for the
+                sample at each variant.  Currently data must be read from a VCF file; the field is specified
+                using the <code>-vcf-intensity-field</code> option.
+            </td>
+        </tr>
+        <tbody>
+    </table>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -276,10 +260,10 @@
 					<a href="../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
 
 	</body>
 </html>

Index: doc/html/qctool/documentation/sample_file_formats.html
==================================================================
--- doc/html/qctool/documentation/sample_file_formats.html
+++ doc/html/qctool/documentation/sample_file_formats.html
@@ -1,35 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../js/jquery-1.4.2.min.js"></script>
-		<script type="text/javascript" src="../js/jquery.ba-hashchange.min.js"></script>
+
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../js/local.js"></script>
-
-		<!-- Google Analytics tracking code-->
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-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
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-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
-
-		<script type="text/javascript">
-			$(document).ready(
-				function() {
-					setFirstPage( "overview" ) ;
-				}
-			) ;
-		</script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
 		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -36,78 +16,78 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
+			<img src="../style/images/qctool.png" class="logo">
 		</div>
 
-		<section class="main_text">
-			<h2>Sample file formats</h2>
-			<h3>SNPTEST sample file format</h3>
-			<p>QCTOOL uses the same sample file format as <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html">SNPTEST</a>.
-				This is a space-separated file with two header lines followed by data, as follows.
-			</p>
-				<dl>
-					<dt>Header line</dt>
-					<dd>This line lists the name of each column.  Column names can be arbitrary printable characters, not including whitespace.</dd>
-					<dt>Column type line</dt>
-					<dd>This line lists the 'type' of each column and is used by QCTOOL to process data in an appropriate way.
-						There must be one type for each column.  Allowable column types are:
-						<ul>
-							<li>0 (for the first identifier column)</li>
-							<li>D (for a column containing discrete values, e.g. a set of strings)</li>
-							<li>P or C - for columns containing continuous value - each value must be numerical, or a missing value.</li>
-							<li>B - for a column containing a binary trait.  The values in this column must be '0', '1', 'control', or 'case'.</li>
-						</ul>
-						In addition to the first column, QCTOOL optionally allows
-						there to be a column called 'ID_2' and/or a column called 'missing' that have type '0'.
-						Internally these are treated like columns of type 'D'.
-					</dd>
-					<dt>
-						Data lines
-					</dt>
-					<dd>Data for each sample.  There should be one data line per sample in the genotypes file, and these must be in the same
-						order that they appear in the genotypes file.
-					</dd>
-				</dl>
-				<p>
-					By default 'NA' is used for missing values in the sample file. Any value in any column that is equal (as a string literal)
-					to "NA" will be treated as missing.  (The option <code>-missing-code</code> can be
-					used to alter what is treated as a missing value.)
-				</p>
-				<p>
-					The first column in a sample file must always be of type '0' and it is always treated as sample identifiers.
-					We strongly recommend that the identifiers used are chosen to be unique across a project.
-				</p>
-				<p>
-					Relative to the traditional format used in SNPTEST, QCTOOL allows some modifications:
-				</p>
-				<ul>
-					<li>The only mandatory column is the first column, which must of type '0' and contains sample identifiers.</li>
-				</ul>
-				<p>An example of a sample file is:</p>
-				<code>
+<section class="main_text">
+    <h2>Sample file formats</h2>
+    <h3>SNPTEST sample file format</h3>
+    <p>QCTOOL uses the same sample file format as <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html">SNPTEST</a>.
+        This is a space-separated file with two header lines followed by data, as follows.
+    </p>
+        <dl>
+            <dt>Header line</dt>
+            <dd>This line lists the name of each column.  Column names can be arbitrary printable characters, not including whitespace.</dd>
+            <dt>Column type line</dt>
+            <dd>This line lists the 'type' of each column and is used by QCTOOL to process data in an appropriate way.
+                There must be one type for each column.  Allowable column types are:
+                <ul>
+                    <li>0 (for the first identifier column)</li>
+                    <li>D (for a column containing discrete values, e.g. a set of strings)</li>
+                    <li>P or C - for columns containing continuous value - each value must be numerical, or a missing value.</li>
+                    <li>B - for a column containing a binary trait.  The values in this column must be '0', '1', 'control', or 'case'.</li>
+                </ul>
+                In addition to the first column, QCTOOL optionally allows
+                there to be a column called 'ID_2' and/or a column called 'missing' that have type '0'.
+                Internally these are treated like columns of type 'D'.
+            </dd>
+            <dt>
+                Data lines
+            </dt>
+            <dd>Data for each sample.  There should be one data line per sample in the genotypes file, and these must be in the same
+                order that they appear in the genotypes file.
+            </dd>
+        </dl>
+        <p>
+            By default 'NA' is used for missing values in the sample file. Any value in any column that is equal (as a string literal)
+            to "NA" will be treated as missing.  (The option <code>-missing-code</code> can be
+            used to alter what is treated as a missing value.)
+        </p>
+        <p>
+            The first column in a sample file must always be of type '0' and it is always treated as sample identifiers.
+            We strongly recommend that the identifiers used are chosen to be unique across a project.
+        </p>
+        <p>
+            Relative to the traditional format used in SNPTEST, QCTOOL allows some modifications:
+        </p>
+        <ul>
+            <li>The only mandatory column is the first column, which must of type '0' and contains sample identifiers.</li>
+        </ul>
+        <p>An example of a sample file is:</p>
+        <code>
 ID sex case covariate<br/>
 0 D B C<br/>
 sample1 M control 0.1<br/>
 sample2 F control 0.2<br/>
 sample3 F control -0.15<br/>
 sample4 F case -0.01<br/>
 sample4 NA NA 0.025<br/>
 (etc.)<br/>
-				</code>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+        </code>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -137,10 +117,10 @@
 					<a href="../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
 
 	</body>
 </html>

Index: doc/html/qctool/documentation/summary_file_formats.html
==================================================================
--- doc/html/qctool/documentation/summary_file_formats.html
+++ doc/html/qctool/documentation/summary_file_formats.html
@@ -1,35 +1,15 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
-		<script type="text/javascript" src="../js/jquery-1.4.2.min.js"></script>
-		<script type="text/javascript" src="../js/jquery.ba-hashchange.min.js"></script>
+
+		<script type="text/javascript" src="../js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="../js/local.js"></script>
-
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
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-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
-
-		<script type="text/javascript">
-			$(document).ready(
-				function() {
-					setFirstPage( "overview" ) ;
-				}
-			) ;
-		</script>
+		<script type="text/javascript" src="../js/datatables.min.js"></script>
 		<link href="../style/css/default.css" rel="stylesheet" type="text/css">
-		<title></title>
+		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->
 			<div class="header_text">
@@ -36,26 +16,26 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
+			<img src="../style/images/qctool.png" class="logo">
 		</div>
 
-		<section class="main_text">
-			<h2>Summary statistic file formats</h2>
-			<p>(This page is under construction.)</p>
-		</section>
-
-		<nav class="button_bar"><div>
-			<div class="nav_button" name="overview">
+<section class="main_text">
+    <h2>Summary statistic file formats</h2>
+    <p>(This page is under construction.)</p>
+</section>
+		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="../index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="../documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="../documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="../documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">
@@ -85,10 +65,10 @@
 					<a href="../documentation/summary_file_formats.html">Summary statistic file formats</a>
 			</div>
 			<div class="nav_button" name="download">
 				<a href="../documentation/download.html">download</a>
 			</div>
-		</div>
+</div>
 </nav>
 
 	</body>
 </html>

Index: doc/html/qctool/index.html
==================================================================
--- doc/html/qctool/index.html
+++ doc/html/qctool/index.html
@@ -1,24 +1,13 @@
 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN"
 "http://www.w3.org/TR/html4/strict.dtd">
 <html>
 	<head>
 
-		<script type="text/javascript" src="js/jquery-1.4.2.min.js"></script>
+		<script type="text/javascript" src="js/jquery-3.2.1.min.js"></script>
 		<script type="text/javascript" src="js/local.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
+		<script type="text/javascript" src="js/datatables.min.js"></script>
 		<link href="style/css/default.css" rel="stylesheet" type="text/css">
 		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
@@ -27,111 +16,61 @@
 				qctool v2
 			</div>
 			<div class="header_subtext">
 				A tool for quality control and analysis of gwas datasets.
 			</div>
-		</div>
-
-		<section class="main_text">
-			<div id="overview">
-				<p>
-					QCTOOL is a command-line utility program for manipulation and quality control of gwas datasets and other genome-wide data. QCTOOL can be used
-				</p>
-				<ul>
-					<li>To compute per-variant and per-sample QC metrics.
-					</li>
-					<li>To filter out samples or variants.
-					</li>
-					<li>To merge datasets in various ways.
-					</li>
-					<li>To convert dataset between file formats. (In particular QCTOOL can
-						read and write <a href="http://www.well.ox.ac.uk/~gav/bgen_format/bgen_format.html">BGEN</a> files,
-						including full support for the BGEN v1.2 format that has been used for
-						the <a href="http://www.ukbiobank.ac.uk/scientists-3/genetic-data/">UK Biobank imputed data full release</a>).
-					</li>
-					<li>To manipulate datasets in various ways - e.g. by updating data fields or aligning alleles to a reference sequence based on information in a strand file.
-					</li>
-					<li>To annotate variants with information from BED files, sequence from FASTA files, or with genetic map positions.
-					</li>
-					<li>To compute LD metrics between variants.
-					</li>
-					<li>To compare genotypes for individuals typed or imputed or phased in different datasets.
-					</li>
-					<li>To compute between-sample relatedness and principal components.
-					</li>
-					<li>To compute 'genetic risk predictor' scores.
-					</li>
-				</ul>
-				<p>
-					QCTOOL is designed to be as easy-to-use as possible and we hope you find it so. See the <a href='#documentation'>documentation page</a> for a description of how QCTOOL works.
-				</p>
-				<p>
-					<b>IMPORTANT</b>: this page documents QCTOOL version 2, which differs in several important ways from the 
-					original <a href="http://www.well.ox.ac.uk/~gav/qctool">QCTOOL v1</a>.
-					Version 1 is still available but is now unsupported.
-				</p>
-				
-				<p>
-					<strong>Change history.</strong> QCTOOL version 2 is currently in 'release candidate' state.  This means some features may not work, or not work well,
-					or work wrongly, or destroy your computer, or your sanity. The best place to receive support is on
-					the <a href="http://www.jiscmail.ac.uk/cgi-bin/webadmin?A0=OXSTATGEN">OXSTATGEN mailing list</a>.
-					QCTOOL also has a public <a href="">issue tracker</a>, but please 
-				</p>QCTOOL v2 also differs in several important ways from the v1 release series. Some important changes in QCTOOL v2 relative to v1 are:
-				<ul>
-					<li>
-						<b>Support for more file formats</b>: QCTOOL v2 supports a diverse array of common file formats - 
-						see the <a href="documentation/genotype_file_formats.html">file formats page</a> for more information.
-					</li>
-					<li>
-						<b>Support for more features</b>: QCTOOL v2 has a bunch of features not found in v1 - for example it
-						can <a href="documentation/examples/computing_ld.html">compute LD metrics</a>,
-						<a href="documentation/examples/altering_id_data.html">apply strand alignments</a>,
-						<a href="documentation/examples/annotating.html">annotate variants</a> with information from external sources, and more.
-					</li>
-					<li>
-						<b>Removal of on-the-fly filtering options</b>: The options for direct filtering based on summary statistics (<code>-maf</code>, <code>-hwe</code>, <code>-snp-missing-rate</code>, etc.) have been removed. Instead, it's expected you will inspect summary statistics and manually create lists of variants and/or samples for removal, using the <code>-incl-</code> and <code>-excl-</code> options
-						to exclude them in a seperate QCTOOL run <a href="documentation/examples/filtering_samples.html">as described here</a> and <a href="documentation/examples/filtering_variants.html">here</a>. (That's often what you want anyway, since it's useful to have a record of what you've removed.)
-					</li>
-					<li>
-						<b>Treatment of chromosomes</b>: QCTOOL v1 always converted chromosomes to a two-digit form (<code>01</code>,<code>02</code>, ...) and would treat chromosomes as missing if they were not of specific forms pertinent to human datasets. QCTOOL v2 instead allows arbitrary strings to be used as chromosomes. This change brings QCTOOL into line with other tools, e.g. those that use contig identifiers from a reference genome build. However, this also breaks some workflows that would previously have worked, namely when matching between datasets that have differently encoded chromosome names. A possible workaround is to <a href="documentation/examples/altering_id_data.html">use the <code>-map-id-data</code> option</a> to replace chromosome identifiers on the fly during analysis.
-					</li>
-					<li>
-						<b>Changes to output of summary stats</b>: QCTOOL performs several types of per-variant summary computation, that are specified using options like <code>-snp-stats</code> and the <code>-annotate-</code> options. When outputting results, all output is sent to a single output file that is specified using the <code>-osnp</code> option. This file will automatically inherit columns from each requested computation. Similarly, all per-sample summary computations are output the file specified by <code>-osample</code>.
-					</li>
-				</ul>
-				<p>
-					<strong>Acknowledgements.</strong> The following people contributed to the design and implementation of qctool:
-				</p>
-				<ul>
-					<li>
-						<a href="http://www.well.ox.ac.uk/~gav/">Gavin Band</a>
-					</li>
-					<li>
-						<a href="http://www.stats.ox.ac.uk/~marchini/">Jonathan Marchini</a>
-					</li>
-				</ul>
-				<p>
-					In addition, QCTOOL contains the <a href="http://www.sph.umich.edu/csg/abecasis/Exact/index.html">SNP-HWE</a> code by Jan Wigginton et al., described in "A Note on Exact Tests of Hardy-Weinberg Equilibrium", Wigginton et al, <i>Am. J. Hum. Genet</i> (2005) 76:887-93.
-					Further acknowledgements can be found on the <a href="https://bitbucket.org/gavinband/qctool/wiki/Home">QCTOOL wiki</a>.
-				</p>
-				<p>
-					<strong>Contact.</strong> For more information or questions, please contact the oxstatgen mailing list at
-				</p>
-				<pre class="monospace">
-						oxstatgen (at) jiscmail.ac.uk
-				</pre>
-			</div>
-		</section>
-
+			<img src="style/images/qctool.png" class="logo">
+		</div>
+
+<section class="main_text">
+<h3>Introduction</h3>
+<p>QCTOOL is a command-line utility program for manipulation and quality control of gwas datasets and other genome-wide data. QCTOOL can be used</p>
+<ul>
+<li>To compute per-variant and per-sample QC metrics.</li>
+<li>To filter out samples or variants.</li>
+<li>To merge datasets in various ways.</li>
+<li>To convert dataset between file formats. (In particular QCTOOL can
+    read and write <a href="http://www.well.ox.ac.uk/~gav/bgen_format/bgen_format.html">BGEN</a> files,
+    including full support for the BGEN v1.2 format that has been used for
+    the <a href="http://www.ukbiobank.ac.uk/scientists-3/genetic-data/">UK Biobank imputed data full release</a>).</li>
+<li>To manipulate datasets in various ways - e.g. by updating data fields or aligning alleles to a reference sequence based on information in a strand file.</li>
+<li>To annotate variants with information from BED files, sequence from FASTA files, or with genetic map positions.</li>
+<li>To compute LD metrics between variants.</li>
+<li>To compare genotypes for individuals typed or imputed or phased in different datasets.</li>
+<li>To compute between-sample relatedness and principal components.</li>
+<li>To compute 'genetic risk predictor' scores.</li>
+</ul>
+<p>QCTOOL is designed to be as easy-to-use as possible and we hope you find it so. See the <a
+href="documentation/examples/basic.html">basic usage page</a> for a quick start on running QCTOOL, and the
+<a href='documentation/diagram_of_options.html'>diagram of options</a> for an overview of how QCTOOL works.</p>
+<p><strong>IMPORTANT</strong>: this page documents QCTOOL version 2, which differs in several important ways from the 
+original <a href="http://www.well.ox.ac.uk/~gav/qctool_v1">QCTOOL v1</a>.
+Version 1 is still available but is now unsupported.</p>
+<h3>Obtaining QCTOOL</h3>
+<p>The QCTOOL source code is currently hosted at <a href="https://code.enkre.net">code.enkre.net</a>. You may also be able
+to obtain precompiled binaries from <a href="https://www.well.ox.ac.uk/~gav/resources/">this folder</a>. See the <a
+href="documentation/download.html">download page</a> for full details on obtaining and installing QCTOOL.</p>
+<h3>Change history</h3>
+<p>See the <a href="documentation/changes.html">change history page</a>.</p>
+<h3>Acknowledgements</h3>
+<p>The following people contributed to the design and implementation of qctool:
+* <a href="http://www.well.ox.ac.uk/~gav/">Gavin Band</a>
+* <a href="http://www.stats.ox.ac.uk/~marchini/">Jonathan Marchini</a></p>
+<p>In addition, QCTOOL contains the <a href="http://www.sph.umich.edu/csg/abecasis/Exact/index.html">SNP-HWE</a> code by Jan Wigginton et al., described in "A Note on Exact Tests of Hardy-Weinberg Equilibrium", Wigginton et al, <i>Am. J. Hum. Genet</i> (2005) 76:887-93.
+Further acknowledgements can be found on the <a href="https://code.enkre.net/qctool">QCTOOL repository main page</a>.</p>
+<h3>Getting support</h3>
+<p>For more information or questions, please contact the OXSTATGEN mailing list at <code>oxstatgen (at) jiscmail.ac.uk</code></p>
+</section>
 		<nav class="button_bar"><div>			<div class="nav_button" name="overview">
 				<a href="index.html">overview</a>
 			</div>
 			<div class="nav_button" name="documentation">
 				documentation
 				<ul class="menu">
 					<li><a href="documentation/diagram_of_options.html">Diagram of options</a></li>
 					<li><a href="documentation/alphabetical_options.html">List of options</a></li>
+					<li><a href="documentation/changes.html">Change history</a></li>
 				</ul>
 			</div>
 			<div class="nav_button" name="tutorial">
 				examples
 				<ul class="menu">

ADDED   doc/html/qctool/js/datatables.js
Index: doc/html/qctool/js/datatables.js
==================================================================
--- doc/html/qctool/js/datatables.js
+++ doc/html/qctool/js/datatables.js
@@ -0,0 +1,15257 @@
+/*
+ * This combined file was created by the DataTables downloader builder:
+ *   https://datatables.net/download
+ *
+ * To rebuild or modify this file with the latest versions of the included
+ * software please visit:
+ *   https://datatables.net/download/#dt/dt-1.10.16
+ *
+ * Included libraries:
+ *   DataTables 1.10.16
+ */
+
+/*! DataTables 1.10.16
+ * ©2008-2017 SpryMedia Ltd - datatables.net/license
+ */
+
+/**
+ * @summary     DataTables
+ * @description Paginate, search and order HTML tables
+ * @version     1.10.16
+ * @file        jquery.dataTables.js
+ * @author      SpryMedia Ltd
+ * @contact     www.datatables.net
+ * @copyright   Copyright 2008-2017 SpryMedia Ltd.
+ *
+ * This source file is free software, available under the following license:
+ *   MIT license - http://datatables.net/license
+ *
+ * This source file is distributed in the hope that it will be useful, but
+ * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
+ * or FITNESS FOR A PARTICULAR PURPOSE. See the license files for details.
+ *
+ * For details please refer to: http://www.datatables.net
+ */
+
+/*jslint evil: true, undef: true, browser: true */
+/*globals $,require,jQuery,define,_selector_run,_selector_opts,_selector_first,_selector_row_indexes,_ext,_Api,_api_register,_api_registerPlural,_re_new_lines,_re_html,_re_formatted_numeric,_re_escape_regex,_empty,_intVal,_numToDecimal,_isNumber,_isHtml,_htmlNumeric,_pluck,_pluck_order,_range,_stripHtml,_unique,_fnBuildAjax,_fnAjaxUpdate,_fnAjaxParameters,_fnAjaxUpdateDraw,_fnAjaxDataSrc,_fnAddColumn,_fnColumnOptions,_fnAdjustColumnSizing,_fnVisibleToColumnIndex,_fnColumnIndexToVisible,_fnVisbleColumns,_fnGetColumns,_fnColumnTypes,_fnApplyColumnDefs,_fnHungarianMap,_fnCamelToHungarian,_fnLanguageCompat,_fnBrowserDetect,_fnAddData,_fnAddTr,_fnNodeToDataIndex,_fnNodeToColumnIndex,_fnGetCellData,_fnSetCellData,_fnSplitObjNotation,_fnGetObjectDataFn,_fnSetObjectDataFn,_fnGetDataMaster,_fnClearTable,_fnDeleteIndex,_fnInvalidate,_fnGetRowElements,_fnCreateTr,_fnBuildHead,_fnDrawHead,_fnDraw,_fnReDraw,_fnAddOptionsHtml,_fnDetectHeader,_fnGetUniqueThs,_fnFeatureHtmlFilter,_fnFilterComplete,_fnFilterCustom,_fnFilterColumn,_fnFilter,_fnFilterCreateSearch,_fnEscapeRegex,_fnFilterData,_fnFeatureHtmlInfo,_fnUpdateInfo,_fnInfoMacros,_fnInitialise,_fnInitComplete,_fnLengthChange,_fnFeatureHtmlLength,_fnFeatureHtmlPaginate,_fnPageChange,_fnFeatureHtmlProcessing,_fnProcessingDisplay,_fnFeatureHtmlTable,_fnScrollDraw,_fnApplyToChildren,_fnCalculateColumnWidths,_fnThrottle,_fnConvertToWidth,_fnGetWidestNode,_fnGetMaxLenString,_fnStringToCss,_fnSortFlatten,_fnSort,_fnSortAria,_fnSortListener,_fnSortAttachListener,_fnSortingClasses,_fnSortData,_fnSaveState,_fnLoadState,_fnSettingsFromNode,_fnLog,_fnMap,_fnBindAction,_fnCallbackReg,_fnCallbackFire,_fnLengthOverflow,_fnRenderer,_fnDataSource,_fnRowAttributes*/
+
+(function( factory ) {
+	"use strict";
+
+	if ( typeof define === 'function' && define.amd ) {
+		// AMD
+		define( ['jquery'], function ( $ ) {
+			return factory( $, window, document );
+		} );
+	}
+	else if ( typeof exports === 'object' ) {
+		// CommonJS
+		module.exports = function (root, $) {
+			if ( ! root ) {
+				// CommonJS environments without a window global must pass a
+				// root. This will give an error otherwise
+				root = window;
+			}
+
+			if ( ! $ ) {
+				$ = typeof window !== 'undefined' ? // jQuery's factory checks for a global window
+					require('jquery') :
+					require('jquery')( root );
+			}
+
+			return factory( $, root, root.document );
+		};
+	}
+	else {
+		// Browser
+		factory( jQuery, window, document );
+	}
+}
+(function( $, window, document, undefined ) {
+	"use strict";
+
+	/**
+	 * DataTables is a plug-in for the jQuery Javascript library. It is a highly
+	 * flexible tool, based upon the foundations of progressive enhancement,
+	 * which will add advanced interaction controls to any HTML table. For a
+	 * full list of features please refer to
+	 * [DataTables.net](href="http://datatables.net).
+	 *
+	 * Note that the `DataTable` object is not a global variable but is aliased
+	 * to `jQuery.fn.DataTable` and `jQuery.fn.dataTable` through which it may
+	 * be  accessed.
+	 *
+	 *  @class
+	 *  @param {object} [init={}] Configuration object for DataTables. Options
+	 *    are defined by {@link DataTable.defaults}
+	 *  @requires jQuery 1.7+
+	 *
+	 *  @example
+	 *    // Basic initialisation
+	 *    $(document).ready( function {
+	 *      $('#example').dataTable();
+	 *    } );
+	 *
+	 *  @example
+	 *    // Initialisation with configuration options - in this case, disable
+	 *    // pagination and sorting.
+	 *    $(document).ready( function {
+	 *      $('#example').dataTable( {
+	 *        "paginate": false,
+	 *        "sort": false
+	 *      } );
+	 *    } );
+	 */
+	var DataTable = function ( options )
+	{
+		/**
+		 * Perform a jQuery selector action on the table's TR elements (from the tbody) and
+		 * return the resulting jQuery object.
+		 *  @param {string|node|jQuery} sSelector jQuery selector or node collection to act on
+		 *  @param {object} [oOpts] Optional parameters for modifying the rows to be included
+		 *  @param {string} [oOpts.filter=none] Select TR elements that meet the current filter
+		 *    criterion ("applied") or all TR elements (i.e. no filter).
+		 *  @param {string} [oOpts.order=current] Order of the TR elements in the processed array.
+		 *    Can be either 'current', whereby the current sorting of the table is used, or
+		 *    'original' whereby the original order the data was read into the table is used.
+		 *  @param {string} [oOpts.page=all] Limit the selection to the currently displayed page
+		 *    ("current") or not ("all"). If 'current' is given, then order is assumed to be
+		 *    'current' and filter is 'applied', regardless of what they might be given as.
+		 *  @returns {object} jQuery object, filtered by the given selector.
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Highlight every second row
+		 *      oTable.$('tr:odd').css('backgroundColor', 'blue');
+		 *    } );
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Filter to rows with 'Webkit' in them, add a background colour and then
+		 *      // remove the filter, thus highlighting the 'Webkit' rows only.
+		 *      oTable.fnFilter('Webkit');
+		 *      oTable.$('tr', {"search": "applied"}).css('backgroundColor', 'blue');
+		 *      oTable.fnFilter('');
+		 *    } );
+		 */
+		this.$ = function ( sSelector, oOpts )
+		{
+			return this.api(true).$( sSelector, oOpts );
+		};
+		
+		
+		/**
+		 * Almost identical to $ in operation, but in this case returns the data for the matched
+		 * rows - as such, the jQuery selector used should match TR row nodes or TD/TH cell nodes
+		 * rather than any descendants, so the data can be obtained for the row/cell. If matching
+		 * rows are found, the data returned is the original data array/object that was used to
+		 * create the row (or a generated array if from a DOM source).
+		 *
+		 * This method is often useful in-combination with $ where both functions are given the
+		 * same parameters and the array indexes will match identically.
+		 *  @param {string|node|jQuery} sSelector jQuery selector or node collection to act on
+		 *  @param {object} [oOpts] Optional parameters for modifying the rows to be included
+		 *  @param {string} [oOpts.filter=none] Select elements that meet the current filter
+		 *    criterion ("applied") or all elements (i.e. no filter).
+		 *  @param {string} [oOpts.order=current] Order of the data in the processed array.
+		 *    Can be either 'current', whereby the current sorting of the table is used, or
+		 *    'original' whereby the original order the data was read into the table is used.
+		 *  @param {string} [oOpts.page=all] Limit the selection to the currently displayed page
+		 *    ("current") or not ("all"). If 'current' is given, then order is assumed to be
+		 *    'current' and filter is 'applied', regardless of what they might be given as.
+		 *  @returns {array} Data for the matched elements. If any elements, as a result of the
+		 *    selector, were not TR, TD or TH elements in the DataTable, they will have a null
+		 *    entry in the array.
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Get the data from the first row in the table
+		 *      var data = oTable._('tr:first');
+		 *
+		 *      // Do something useful with the data
+		 *      alert( "First cell is: "+data[0] );
+		 *    } );
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Filter to 'Webkit' and get all data for
+		 *      oTable.fnFilter('Webkit');
+		 *      var data = oTable._('tr', {"search": "applied"});
+		 *
+		 *      // Do something with the data
+		 *      alert( data.length+" rows matched the search" );
+		 *    } );
+		 */
+		this._ = function ( sSelector, oOpts )
+		{
+			return this.api(true).rows( sSelector, oOpts ).data();
+		};
+		
+		
+		/**
+		 * Create a DataTables Api instance, with the currently selected tables for
+		 * the Api's context.
+		 * @param {boolean} [traditional=false] Set the API instance's context to be
+		 *   only the table referred to by the `DataTable.ext.iApiIndex` option, as was
+		 *   used in the API presented by DataTables 1.9- (i.e. the traditional mode),
+		 *   or if all tables captured in the jQuery object should be used.
+		 * @return {DataTables.Api}
+		 */
+		this.api = function ( traditional )
+		{
+			return traditional ?
+				new _Api(
+					_fnSettingsFromNode( this[ _ext.iApiIndex ] )
+				) :
+				new _Api( this );
+		};
+		
+		
+		/**
+		 * Add a single new row or multiple rows of data to the table. Please note
+		 * that this is suitable for client-side processing only - if you are using
+		 * server-side processing (i.e. "bServerSide": true), then to add data, you
+		 * must add it to the data source, i.e. the server-side, through an Ajax call.
+		 *  @param {array|object} data The data to be added to the table. This can be:
+		 *    <ul>
+		 *      <li>1D array of data - add a single row with the data provided</li>
+		 *      <li>2D array of arrays - add multiple rows in a single call</li>
+		 *      <li>object - data object when using <i>mData</i></li>
+		 *      <li>array of objects - multiple data objects when using <i>mData</i></li>
+		 *    </ul>
+		 *  @param {bool} [redraw=true] redraw the table or not
+		 *  @returns {array} An array of integers, representing the list of indexes in
+		 *    <i>aoData</i> ({@link DataTable.models.oSettings}) that have been added to
+		 *    the table.
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    // Global var for counter
+		 *    var giCount = 2;
+		 *
+		 *    $(document).ready(function() {
+		 *      $('#example').dataTable();
+		 *    } );
+		 *
+		 *    function fnClickAddRow() {
+		 *      $('#example').dataTable().fnAddData( [
+		 *        giCount+".1",
+		 *        giCount+".2",
+		 *        giCount+".3",
+		 *        giCount+".4" ]
+		 *      );
+		 *
+		 *      giCount++;
+		 *    }
+		 */
+		this.fnAddData = function( data, redraw )
+		{
+			var api = this.api( true );
+		
+			/* Check if we want to add multiple rows or not */
+			var rows = $.isArray(data) && ( $.isArray(data[0]) || $.isPlainObject(data[0]) ) ?
+				api.rows.add( data ) :
+				api.row.add( data );
+		
+			if ( redraw === undefined || redraw ) {
+				api.draw();
+			}
+		
+			return rows.flatten().toArray();
+		};
+		
+		
+		/**
+		 * This function will make DataTables recalculate the column sizes, based on the data
+		 * contained in the table and the sizes applied to the columns (in the DOM, CSS or
+		 * through the sWidth parameter). This can be useful when the width of the table's
+		 * parent element changes (for example a window resize).
+		 *  @param {boolean} [bRedraw=true] Redraw the table or not, you will typically want to
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable( {
+		 *        "sScrollY": "200px",
+		 *        "bPaginate": false
+		 *      } );
+		 *
+		 *      $(window).on('resize', function () {
+		 *        oTable.fnAdjustColumnSizing();
+		 *      } );
+		 *    } );
+		 */
+		this.fnAdjustColumnSizing = function ( bRedraw )
+		{
+			var api = this.api( true ).columns.adjust();
+			var settings = api.settings()[0];
+			var scroll = settings.oScroll;
+		
+			if ( bRedraw === undefined || bRedraw ) {
+				api.draw( false );
+			}
+			else if ( scroll.sX !== "" || scroll.sY !== "" ) {
+				/* If not redrawing, but scrolling, we want to apply the new column sizes anyway */
+				_fnScrollDraw( settings );
+			}
+		};
+		
+		
+		/**
+		 * Quickly and simply clear a table
+		 *  @param {bool} [bRedraw=true] redraw the table or not
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Immediately 'nuke' the current rows (perhaps waiting for an Ajax callback...)
+		 *      oTable.fnClearTable();
+		 *    } );
+		 */
+		this.fnClearTable = function( bRedraw )
+		{
+			var api = this.api( true ).clear();
+		
+			if ( bRedraw === undefined || bRedraw ) {
+				api.draw();
+			}
+		};
+		
+		
+		/**
+		 * The exact opposite of 'opening' a row, this function will close any rows which
+		 * are currently 'open'.
+		 *  @param {node} nTr the table row to 'close'
+		 *  @returns {int} 0 on success, or 1 if failed (can't find the row)
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable;
+		 *
+		 *      // 'open' an information row when a row is clicked on
+		 *      $('#example tbody tr').click( function () {
+		 *        if ( oTable.fnIsOpen(this) ) {
+		 *          oTable.fnClose( this );
+		 *        } else {
+		 *          oTable.fnOpen( this, "Temporary row opened", "info_row" );
+		 *        }
+		 *      } );
+		 *
+		 *      oTable = $('#example').dataTable();
+		 *    } );
+		 */
+		this.fnClose = function( nTr )
+		{
+			this.api( true ).row( nTr ).child.hide();
+		};
+		
+		
+		/**
+		 * Remove a row for the table
+		 *  @param {mixed} target The index of the row from aoData to be deleted, or
+		 *    the TR element you want to delete
+		 *  @param {function|null} [callBack] Callback function
+		 *  @param {bool} [redraw=true] Redraw the table or not
+		 *  @returns {array} The row that was deleted
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Immediately remove the first row
+		 *      oTable.fnDeleteRow( 0 );
+		 *    } );
+		 */
+		this.fnDeleteRow = function( target, callback, redraw )
+		{
+			var api = this.api( true );
+			var rows = api.rows( target );
+			var settings = rows.settings()[0];
+			var data = settings.aoData[ rows[0][0] ];
+		
+			rows.remove();
+		
+			if ( callback ) {
+				callback.call( this, settings, data );
+			}
+		
+			if ( redraw === undefined || redraw ) {
+				api.draw();
+			}
+		
+			return data;
+		};
+		
+		
+		/**
+		 * Restore the table to it's original state in the DOM by removing all of DataTables
+		 * enhancements, alterations to the DOM structure of the table and event listeners.
+		 *  @param {boolean} [remove=false] Completely remove the table from the DOM
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      // This example is fairly pointless in reality, but shows how fnDestroy can be used
+		 *      var oTable = $('#example').dataTable();
+		 *      oTable.fnDestroy();
+		 *    } );
+		 */
+		this.fnDestroy = function ( remove )
+		{
+			this.api( true ).destroy( remove );
+		};
+		
+		
+		/**
+		 * Redraw the table
+		 *  @param {bool} [complete=true] Re-filter and resort (if enabled) the table before the draw.
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Re-draw the table - you wouldn't want to do it here, but it's an example :-)
+		 *      oTable.fnDraw();
+		 *    } );
+		 */
+		this.fnDraw = function( complete )
+		{
+			// Note that this isn't an exact match to the old call to _fnDraw - it takes
+			// into account the new data, but can hold position.
+			this.api( true ).draw( complete );
+		};
+		
+		
+		/**
+		 * Filter the input based on data
+		 *  @param {string} sInput String to filter the table on
+		 *  @param {int|null} [iColumn] Column to limit filtering to
+		 *  @param {bool} [bRegex=false] Treat as regular expression or not
+		 *  @param {bool} [bSmart=true] Perform smart filtering or not
+		 *  @param {bool} [bShowGlobal=true] Show the input global filter in it's input box(es)
+		 *  @param {bool} [bCaseInsensitive=true] Do case-insensitive matching (true) or not (false)
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Sometime later - filter...
+		 *      oTable.fnFilter( 'test string' );
+		 *    } );
+		 */
+		this.fnFilter = function( sInput, iColumn, bRegex, bSmart, bShowGlobal, bCaseInsensitive )
+		{
+			var api = this.api( true );
+		
+			if ( iColumn === null || iColumn === undefined ) {
+				api.search( sInput, bRegex, bSmart, bCaseInsensitive );
+			}
+			else {
+				api.column( iColumn ).search( sInput, bRegex, bSmart, bCaseInsensitive );
+			}
+		
+			api.draw();
+		};
+		
+		
+		/**
+		 * Get the data for the whole table, an individual row or an individual cell based on the
+		 * provided parameters.
+		 *  @param {int|node} [src] A TR row node, TD/TH cell node or an integer. If given as
+		 *    a TR node then the data source for the whole row will be returned. If given as a
+		 *    TD/TH cell node then iCol will be automatically calculated and the data for the
+		 *    cell returned. If given as an integer, then this is treated as the aoData internal
+		 *    data index for the row (see fnGetPosition) and the data for that row used.
+		 *  @param {int} [col] Optional column index that you want the data of.
+		 *  @returns {array|object|string} If mRow is undefined, then the data for all rows is
+		 *    returned. If mRow is defined, just data for that row, and is iCol is
+		 *    defined, only data for the designated cell is returned.
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    // Row data
+		 *    $(document).ready(function() {
+		 *      oTable = $('#example').dataTable();
+		 *
+		 *      oTable.$('tr').click( function () {
+		 *        var data = oTable.fnGetData( this );
+		 *        // ... do something with the array / object of data for the row
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Individual cell data
+		 *    $(document).ready(function() {
+		 *      oTable = $('#example').dataTable();
+		 *
+		 *      oTable.$('td').click( function () {
+		 *        var sData = oTable.fnGetData( this );
+		 *        alert( 'The cell clicked on had the value of '+sData );
+		 *      } );
+		 *    } );
+		 */
+		this.fnGetData = function( src, col )
+		{
+			var api = this.api( true );
+		
+			if ( src !== undefined ) {
+				var type = src.nodeName ? src.nodeName.toLowerCase() : '';
+		
+				return col !== undefined || type == 'td' || type == 'th' ?
+					api.cell( src, col ).data() :
+					api.row( src ).data() || null;
+			}
+		
+			return api.data().toArray();
+		};
+		
+		
+		/**
+		 * Get an array of the TR nodes that are used in the table's body. Note that you will
+		 * typically want to use the '$' API method in preference to this as it is more
+		 * flexible.
+		 *  @param {int} [iRow] Optional row index for the TR element you want
+		 *  @returns {array|node} If iRow is undefined, returns an array of all TR elements
+		 *    in the table's body, or iRow is defined, just the TR element requested.
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Get the nodes from the table
+		 *      var nNodes = oTable.fnGetNodes( );
+		 *    } );
+		 */
+		this.fnGetNodes = function( iRow )
+		{
+			var api = this.api( true );
+		
+			return iRow !== undefined ?
+				api.row( iRow ).node() :
+				api.rows().nodes().flatten().toArray();
+		};
+		
+		
+		/**
+		 * Get the array indexes of a particular cell from it's DOM element
+		 * and column index including hidden columns
+		 *  @param {node} node this can either be a TR, TD or TH in the table's body
+		 *  @returns {int} If nNode is given as a TR, then a single index is returned, or
+		 *    if given as a cell, an array of [row index, column index (visible),
+		 *    column index (all)] is given.
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      $('#example tbody td').click( function () {
+		 *        // Get the position of the current data from the node
+		 *        var aPos = oTable.fnGetPosition( this );
+		 *
+		 *        // Get the data array for this row
+		 *        var aData = oTable.fnGetData( aPos[0] );
+		 *
+		 *        // Update the data array and return the value
+		 *        aData[ aPos[1] ] = 'clicked';
+		 *        this.innerHTML = 'clicked';
+		 *      } );
+		 *
+		 *      // Init DataTables
+		 *      oTable = $('#example').dataTable();
+		 *    } );
+		 */
+		this.fnGetPosition = function( node )
+		{
+			var api = this.api( true );
+			var nodeName = node.nodeName.toUpperCase();
+		
+			if ( nodeName == 'TR' ) {
+				return api.row( node ).index();
+			}
+			else if ( nodeName == 'TD' || nodeName == 'TH' ) {
+				var cell = api.cell( node ).index();
+		
+				return [
+					cell.row,
+					cell.columnVisible,
+					cell.column
+				];
+			}
+			return null;
+		};
+		
+		
+		/**
+		 * Check to see if a row is 'open' or not.
+		 *  @param {node} nTr the table row to check
+		 *  @returns {boolean} true if the row is currently open, false otherwise
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable;
+		 *
+		 *      // 'open' an information row when a row is clicked on
+		 *      $('#example tbody tr').click( function () {
+		 *        if ( oTable.fnIsOpen(this) ) {
+		 *          oTable.fnClose( this );
+		 *        } else {
+		 *          oTable.fnOpen( this, "Temporary row opened", "info_row" );
+		 *        }
+		 *      } );
+		 *
+		 *      oTable = $('#example').dataTable();
+		 *    } );
+		 */
+		this.fnIsOpen = function( nTr )
+		{
+			return this.api( true ).row( nTr ).child.isShown();
+		};
+		
+		
+		/**
+		 * This function will place a new row directly after a row which is currently
+		 * on display on the page, with the HTML contents that is passed into the
+		 * function. This can be used, for example, to ask for confirmation that a
+		 * particular record should be deleted.
+		 *  @param {node} nTr The table row to 'open'
+		 *  @param {string|node|jQuery} mHtml The HTML to put into the row
+		 *  @param {string} sClass Class to give the new TD cell
+		 *  @returns {node} The row opened. Note that if the table row passed in as the
+		 *    first parameter, is not found in the table, this method will silently
+		 *    return.
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable;
+		 *
+		 *      // 'open' an information row when a row is clicked on
+		 *      $('#example tbody tr').click( function () {
+		 *        if ( oTable.fnIsOpen(this) ) {
+		 *          oTable.fnClose( this );
+		 *        } else {
+		 *          oTable.fnOpen( this, "Temporary row opened", "info_row" );
+		 *        }
+		 *      } );
+		 *
+		 *      oTable = $('#example').dataTable();
+		 *    } );
+		 */
+		this.fnOpen = function( nTr, mHtml, sClass )
+		{
+			return this.api( true )
+				.row( nTr )
+				.child( mHtml, sClass )
+				.show()
+				.child()[0];
+		};
+		
+		
+		/**
+		 * Change the pagination - provides the internal logic for pagination in a simple API
+		 * function. With this function you can have a DataTables table go to the next,
+		 * previous, first or last pages.
+		 *  @param {string|int} mAction Paging action to take: "first", "previous", "next" or "last"
+		 *    or page number to jump to (integer), note that page 0 is the first page.
+		 *  @param {bool} [bRedraw=true] Redraw the table or not
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *      oTable.fnPageChange( 'next' );
+		 *    } );
+		 */
+		this.fnPageChange = function ( mAction, bRedraw )
+		{
+			var api = this.api( true ).page( mAction );
+		
+			if ( bRedraw === undefined || bRedraw ) {
+				api.draw(false);
+			}
+		};
+		
+		
+		/**
+		 * Show a particular column
+		 *  @param {int} iCol The column whose display should be changed
+		 *  @param {bool} bShow Show (true) or hide (false) the column
+		 *  @param {bool} [bRedraw=true] Redraw the table or not
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Hide the second column after initialisation
+		 *      oTable.fnSetColumnVis( 1, false );
+		 *    } );
+		 */
+		this.fnSetColumnVis = function ( iCol, bShow, bRedraw )
+		{
+			var api = this.api( true ).column( iCol ).visible( bShow );
+		
+			if ( bRedraw === undefined || bRedraw ) {
+				api.columns.adjust().draw();
+			}
+		};
+		
+		
+		/**
+		 * Get the settings for a particular table for external manipulation
+		 *  @returns {object} DataTables settings object. See
+		 *    {@link DataTable.models.oSettings}
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *      var oSettings = oTable.fnSettings();
+		 *
+		 *      // Show an example parameter from the settings
+		 *      alert( oSettings._iDisplayStart );
+		 *    } );
+		 */
+		this.fnSettings = function()
+		{
+			return _fnSettingsFromNode( this[_ext.iApiIndex] );
+		};
+		
+		
+		/**
+		 * Sort the table by a particular column
+		 *  @param {int} iCol the data index to sort on. Note that this will not match the
+		 *    'display index' if you have hidden data entries
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Sort immediately with columns 0 and 1
+		 *      oTable.fnSort( [ [0,'asc'], [1,'asc'] ] );
+		 *    } );
+		 */
+		this.fnSort = function( aaSort )
+		{
+			this.api( true ).order( aaSort ).draw();
+		};
+		
+		
+		/**
+		 * Attach a sort listener to an element for a given column
+		 *  @param {node} nNode the element to attach the sort listener to
+		 *  @param {int} iColumn the column that a click on this node will sort on
+		 *  @param {function} [fnCallback] callback function when sort is run
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *
+		 *      // Sort on column 1, when 'sorter' is clicked on
+		 *      oTable.fnSortListener( document.getElementById('sorter'), 1 );
+		 *    } );
+		 */
+		this.fnSortListener = function( nNode, iColumn, fnCallback )
+		{
+			this.api( true ).order.listener( nNode, iColumn, fnCallback );
+		};
+		
+		
+		/**
+		 * Update a table cell or row - this method will accept either a single value to
+		 * update the cell with, an array of values with one element for each column or
+		 * an object in the same format as the original data source. The function is
+		 * self-referencing in order to make the multi column updates easier.
+		 *  @param {object|array|string} mData Data to update the cell/row with
+		 *  @param {node|int} mRow TR element you want to update or the aoData index
+		 *  @param {int} [iColumn] The column to update, give as null or undefined to
+		 *    update a whole row.
+		 *  @param {bool} [bRedraw=true] Redraw the table or not
+		 *  @param {bool} [bAction=true] Perform pre-draw actions or not
+		 *  @returns {int} 0 on success, 1 on error
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *      oTable.fnUpdate( 'Example update', 0, 0 ); // Single cell
+		 *      oTable.fnUpdate( ['a', 'b', 'c', 'd', 'e'], $('tbody tr')[0] ); // Row
+		 *    } );
+		 */
+		this.fnUpdate = function( mData, mRow, iColumn, bRedraw, bAction )
+		{
+			var api = this.api( true );
+		
+			if ( iColumn === undefined || iColumn === null ) {
+				api.row( mRow ).data( mData );
+			}
+			else {
+				api.cell( mRow, iColumn ).data( mData );
+			}
+		
+			if ( bAction === undefined || bAction ) {
+				api.columns.adjust();
+			}
+		
+			if ( bRedraw === undefined || bRedraw ) {
+				api.draw();
+			}
+			return 0;
+		};
+		
+		
+		/**
+		 * Provide a common method for plug-ins to check the version of DataTables being used, in order
+		 * to ensure compatibility.
+		 *  @param {string} sVersion Version string to check for, in the format "X.Y.Z". Note that the
+		 *    formats "X" and "X.Y" are also acceptable.
+		 *  @returns {boolean} true if this version of DataTables is greater or equal to the required
+		 *    version, or false if this version of DataTales is not suitable
+		 *  @method
+		 *  @dtopt API
+		 *  @deprecated Since v1.10
+		 *
+		 *  @example
+		 *    $(document).ready(function() {
+		 *      var oTable = $('#example').dataTable();
+		 *      alert( oTable.fnVersionCheck( '1.9.0' ) );
+		 *    } );
+		 */
+		this.fnVersionCheck = _ext.fnVersionCheck;
+		
+
+		var _that = this;
+		var emptyInit = options === undefined;
+		var len = this.length;
+
+		if ( emptyInit ) {
+			options = {};
+		}
+
+		this.oApi = this.internal = _ext.internal;
+
+		// Extend with old style plug-in API methods
+		for ( var fn in DataTable.ext.internal ) {
+			if ( fn ) {
+				this[fn] = _fnExternApiFunc(fn);
+			}
+		}
+
+		this.each(function() {
+			// For each initialisation we want to give it a clean initialisation
+			// object that can be bashed around
+			var o = {};
+			var oInit = len > 1 ? // optimisation for single table case
+				_fnExtend( o, options, true ) :
+				options;
+
+			/*global oInit,_that,emptyInit*/
+			var i=0, iLen, j, jLen, k, kLen;
+			var sId = this.getAttribute( 'id' );
+			var bInitHandedOff = false;
+			var defaults = DataTable.defaults;
+			var $this = $(this);
+			
+			
+			/* Sanity check */
+			if ( this.nodeName.toLowerCase() != 'table' )
+			{
+				_fnLog( null, 0, 'Non-table node initialisation ('+this.nodeName+')', 2 );
+				return;
+			}
+			
+			/* Backwards compatibility for the defaults */
+			_fnCompatOpts( defaults );
+			_fnCompatCols( defaults.column );
+			
+			/* Convert the camel-case defaults to Hungarian */
+			_fnCamelToHungarian( defaults, defaults, true );
+			_fnCamelToHungarian( defaults.column, defaults.column, true );
+			
+			/* Setting up the initialisation object */
+			_fnCamelToHungarian( defaults, $.extend( oInit, $this.data() ) );
+			
+			
+			
+			/* Check to see if we are re-initialising a table */
+			var allSettings = DataTable.settings;
+			for ( i=0, iLen=allSettings.length ; i<iLen ; i++ )
+			{
+				var s = allSettings[i];
+			
+				/* Base check on table node */
+				if ( s.nTable == this || s.nTHead.parentNode == this || (s.nTFoot && s.nTFoot.parentNode == this) )
+				{
+					var bRetrieve = oInit.bRetrieve !== undefined ? oInit.bRetrieve : defaults.bRetrieve;
+					var bDestroy = oInit.bDestroy !== undefined ? oInit.bDestroy : defaults.bDestroy;
+			
+					if ( emptyInit || bRetrieve )
+					{
+						return s.oInstance;
+					}
+					else if ( bDestroy )
+					{
+						s.oInstance.fnDestroy();
+						break;
+					}
+					else
+					{
+						_fnLog( s, 0, 'Cannot reinitialise DataTable', 3 );
+						return;
+					}
+				}
+			
+				/* If the element we are initialising has the same ID as a table which was previously
+				 * initialised, but the table nodes don't match (from before) then we destroy the old
+				 * instance by simply deleting it. This is under the assumption that the table has been
+				 * destroyed by other methods. Anyone using non-id selectors will need to do this manually
+				 */
+				if ( s.sTableId == this.id )
+				{
+					allSettings.splice( i, 1 );
+					break;
+				}
+			}
+			
+			/* Ensure the table has an ID - required for accessibility */
+			if ( sId === null || sId === "" )
+			{
+				sId = "DataTables_Table_"+(DataTable.ext._unique++);
+				this.id = sId;
+			}
+			
+			/* Create the settings object for this table and set some of the default parameters */
+			var oSettings = $.extend( true, {}, DataTable.models.oSettings, {
+				"sDestroyWidth": $this[0].style.width,
+				"sInstance":     sId,
+				"sTableId":      sId
+			} );
+			oSettings.nTable = this;
+			oSettings.oApi   = _that.internal;
+			oSettings.oInit  = oInit;
+			
+			allSettings.push( oSettings );
+			
+			// Need to add the instance after the instance after the settings object has been added
+			// to the settings array, so we can self reference the table instance if more than one
+			oSettings.oInstance = (_that.length===1) ? _that : $this.dataTable();
+			
+			// Backwards compatibility, before we apply all the defaults
+			_fnCompatOpts( oInit );
+			
+			if ( oInit.oLanguage )
+			{
+				_fnLanguageCompat( oInit.oLanguage );
+			}
+			
+			// If the length menu is given, but the init display length is not, use the length menu
+			if ( oInit.aLengthMenu && ! oInit.iDisplayLength )
+			{
+				oInit.iDisplayLength = $.isArray( oInit.aLengthMenu[0] ) ?
+					oInit.aLengthMenu[0][0] : oInit.aLengthMenu[0];
+			}
+			
+			// Apply the defaults and init options to make a single init object will all
+			// options defined from defaults and instance options.
+			oInit = _fnExtend( $.extend( true, {}, defaults ), oInit );
+			
+			
+			// Map the initialisation options onto the settings object
+			_fnMap( oSettings.oFeatures, oInit, [
+				"bPaginate",
+				"bLengthChange",
+				"bFilter",
+				"bSort",
+				"bSortMulti",
+				"bInfo",
+				"bProcessing",
+				"bAutoWidth",
+				"bSortClasses",
+				"bServerSide",
+				"bDeferRender"
+			] );
+			_fnMap( oSettings, oInit, [
+				"asStripeClasses",
+				"ajax",
+				"fnServerData",
+				"fnFormatNumber",
+				"sServerMethod",
+				"aaSorting",
+				"aaSortingFixed",
+				"aLengthMenu",
+				"sPaginationType",
+				"sAjaxSource",
+				"sAjaxDataProp",
+				"iStateDuration",
+				"sDom",
+				"bSortCellsTop",
+				"iTabIndex",
+				"fnStateLoadCallback",
+				"fnStateSaveCallback",
+				"renderer",
+				"searchDelay",
+				"rowId",
+				[ "iCookieDuration", "iStateDuration" ], // backwards compat
+				[ "oSearch", "oPreviousSearch" ],
+				[ "aoSearchCols", "aoPreSearchCols" ],
+				[ "iDisplayLength", "_iDisplayLength" ]
+			] );
+			_fnMap( oSettings.oScroll, oInit, [
+				[ "sScrollX", "sX" ],
+				[ "sScrollXInner", "sXInner" ],
+				[ "sScrollY", "sY" ],
+				[ "bScrollCollapse", "bCollapse" ]
+			] );
+			_fnMap( oSettings.oLanguage, oInit, "fnInfoCallback" );
+			
+			/* Callback functions which are array driven */
+			_fnCallbackReg( oSettings, 'aoDrawCallback',       oInit.fnDrawCallback,      'user' );
+			_fnCallbackReg( oSettings, 'aoServerParams',       oInit.fnServerParams,      'user' );
+			_fnCallbackReg( oSettings, 'aoStateSaveParams',    oInit.fnStateSaveParams,   'user' );
+			_fnCallbackReg( oSettings, 'aoStateLoadParams',    oInit.fnStateLoadParams,   'user' );
+			_fnCallbackReg( oSettings, 'aoStateLoaded',        oInit.fnStateLoaded,       'user' );
+			_fnCallbackReg( oSettings, 'aoRowCallback',        oInit.fnRowCallback,       'user' );
+			_fnCallbackReg( oSettings, 'aoRowCreatedCallback', oInit.fnCreatedRow,        'user' );
+			_fnCallbackReg( oSettings, 'aoHeaderCallback',     oInit.fnHeaderCallback,    'user' );
+			_fnCallbackReg( oSettings, 'aoFooterCallback',     oInit.fnFooterCallback,    'user' );
+			_fnCallbackReg( oSettings, 'aoInitComplete',       oInit.fnInitComplete,      'user' );
+			_fnCallbackReg( oSettings, 'aoPreDrawCallback',    oInit.fnPreDrawCallback,   'user' );
+			
+			oSettings.rowIdFn = _fnGetObjectDataFn( oInit.rowId );
+			
+			/* Browser support detection */
+			_fnBrowserDetect( oSettings );
+			
+			var oClasses = oSettings.oClasses;
+			
+			$.extend( oClasses, DataTable.ext.classes, oInit.oClasses );
+			$this.addClass( oClasses.sTable );
+			
+			
+			if ( oSettings.iInitDisplayStart === undefined )
+			{
+				/* Display start point, taking into account the save saving */
+				oSettings.iInitDisplayStart = oInit.iDisplayStart;
+				oSettings._iDisplayStart = oInit.iDisplayStart;
+			}
+			
+			if ( oInit.iDeferLoading !== null )
+			{
+				oSettings.bDeferLoading = true;
+				var tmp = $.isArray( oInit.iDeferLoading );
+				oSettings._iRecordsDisplay = tmp ? oInit.iDeferLoading[0] : oInit.iDeferLoading;
+				oSettings._iRecordsTotal = tmp ? oInit.iDeferLoading[1] : oInit.iDeferLoading;
+			}
+			
+			/* Language definitions */
+			var oLanguage = oSettings.oLanguage;
+			$.extend( true, oLanguage, oInit.oLanguage );
+			
+			if ( oLanguage.sUrl )
+			{
+				/* Get the language definitions from a file - because this Ajax call makes the language
+				 * get async to the remainder of this function we use bInitHandedOff to indicate that
+				 * _fnInitialise will be fired by the returned Ajax handler, rather than the constructor
+				 */
+				$.ajax( {
+					dataType: 'json',
+					url: oLanguage.sUrl,
+					success: function ( json ) {
+						_fnLanguageCompat( json );
+						_fnCamelToHungarian( defaults.oLanguage, json );
+						$.extend( true, oLanguage, json );
+						_fnInitialise( oSettings );
+					},
+					error: function () {
+						// Error occurred loading language file, continue on as best we can
+						_fnInitialise( oSettings );
+					}
+				} );
+				bInitHandedOff = true;
+			}
+			
+			/*
+			 * Stripes
+			 */
+			if ( oInit.asStripeClasses === null )
+			{
+				oSettings.asStripeClasses =[
+					oClasses.sStripeOdd,
+					oClasses.sStripeEven
+				];
+			}
+			
+			/* Remove row stripe classes if they are already on the table row */
+			var stripeClasses = oSettings.asStripeClasses;
+			var rowOne = $this.children('tbody').find('tr').eq(0);
+			if ( $.inArray( true, $.map( stripeClasses, function(el, i) {
+				return rowOne.hasClass(el);
+			} ) ) !== -1 ) {
+				$('tbody tr', this).removeClass( stripeClasses.join(' ') );
+				oSettings.asDestroyStripes = stripeClasses.slice();
+			}
+			
+			/*
+			 * Columns
+			 * See if we should load columns automatically or use defined ones
+			 */
+			var anThs = [];
+			var aoColumnsInit;
+			var nThead = this.getElementsByTagName('thead');
+			if ( nThead.length !== 0 )
+			{
+				_fnDetectHeader( oSettings.aoHeader, nThead[0] );
+				anThs = _fnGetUniqueThs( oSettings );
+			}
+			
+			/* If not given a column array, generate one with nulls */
+			if ( oInit.aoColumns === null )
+			{
+				aoColumnsInit = [];
+				for ( i=0, iLen=anThs.length ; i<iLen ; i++ )
+				{
+					aoColumnsInit.push( null );
+				}
+			}
+			else
+			{
+				aoColumnsInit = oInit.aoColumns;
+			}
+			
+			/* Add the columns */
+			for ( i=0, iLen=aoColumnsInit.length ; i<iLen ; i++ )
+			{
+				_fnAddColumn( oSettings, anThs ? anThs[i] : null );
+			}
+			
+			/* Apply the column definitions */
+			_fnApplyColumnDefs( oSettings, oInit.aoColumnDefs, aoColumnsInit, function (iCol, oDef) {
+				_fnColumnOptions( oSettings, iCol, oDef );
+			} );
+			
+			/* HTML5 attribute detection - build an mData object automatically if the
+			 * attributes are found
+			 */
+			if ( rowOne.length ) {
+				var a = function ( cell, name ) {
+					return cell.getAttribute( 'data-'+name ) !== null ? name : null;
+				};
+			
+				$( rowOne[0] ).children('th, td').each( function (i, cell) {
+					var col = oSettings.aoColumns[i];
+			
+					if ( col.mData === i ) {
+						var sort = a( cell, 'sort' ) || a( cell, 'order' );
+						var filter = a( cell, 'filter' ) || a( cell, 'search' );
+			
+						if ( sort !== null || filter !== null ) {
+							col.mData = {
+								_:      i+'.display',
+								sort:   sort !== null   ? i+'.@data-'+sort   : undefined,
+								type:   sort !== null   ? i+'.@data-'+sort   : undefined,
+								filter: filter !== null ? i+'.@data-'+filter : undefined
+							};
+			
+							_fnColumnOptions( oSettings, i );
+						}
+					}
+				} );
+			}
+			
+			var features = oSettings.oFeatures;
+			var loadedInit = function () {
+				/*
+				 * Sorting
+				 * @todo For modularisation (1.11) this needs to do into a sort start up handler
+				 */
+			
+				// If aaSorting is not defined, then we use the first indicator in asSorting
+				// in case that has been altered, so the default sort reflects that option
+				if ( oInit.aaSorting === undefined ) {
+					var sorting = oSettings.aaSorting;
+					for ( i=0, iLen=sorting.length ; i<iLen ; i++ ) {
+						sorting[i][1] = oSettings.aoColumns[ i ].asSorting[0];
+					}
+				}
+			
+				/* Do a first pass on the sorting classes (allows any size changes to be taken into
+				 * account, and also will apply sorting disabled classes if disabled
+				 */
+				_fnSortingClasses( oSettings );
+			
+				if ( features.bSort ) {
+					_fnCallbackReg( oSettings, 'aoDrawCallback', function () {
+						if ( oSettings.bSorted ) {
+							var aSort = _fnSortFlatten( oSettings );
+							var sortedColumns = {};
+			
+							$.each( aSort, function (i, val) {
+								sortedColumns[ val.src ] = val.dir;
+							} );
+			
+							_fnCallbackFire( oSettings, null, 'order', [oSettings, aSort, sortedColumns] );
+							_fnSortAria( oSettings );
+						}
+					} );
+				}
+			
+				_fnCallbackReg( oSettings, 'aoDrawCallback', function () {
+					if ( oSettings.bSorted || _fnDataSource( oSettings ) === 'ssp' || features.bDeferRender ) {
+						_fnSortingClasses( oSettings );
+					}
+				}, 'sc' );
+			
+			
+				/*
+				 * Final init
+				 * Cache the header, body and footer as required, creating them if needed
+				 */
+			
+				// Work around for Webkit bug 83867 - store the caption-side before removing from doc
+				var captions = $this.children('caption').each( function () {
+					this._captionSide = $(this).css('caption-side');
+				} );
+			
+				var thead = $this.children('thead');
+				if ( thead.length === 0 ) {
+					thead = $('<thead/>').appendTo($this);
+				}
+				oSettings.nTHead = thead[0];
+			
+				var tbody = $this.children('tbody');
+				if ( tbody.length === 0 ) {
+					tbody = $('<tbody/>').appendTo($this);
+				}
+				oSettings.nTBody = tbody[0];
+			
+				var tfoot = $this.children('tfoot');
+				if ( tfoot.length === 0 && captions.length > 0 && (oSettings.oScroll.sX !== "" || oSettings.oScroll.sY !== "") ) {
+					// If we are a scrolling table, and no footer has been given, then we need to create
+					// a tfoot element for the caption element to be appended to
+					tfoot = $('<tfoot/>').appendTo($this);
+				}
+			
+				if ( tfoot.length === 0 || tfoot.children().length === 0 ) {
+					$this.addClass( oClasses.sNoFooter );
+				}
+				else if ( tfoot.length > 0 ) {
+					oSettings.nTFoot = tfoot[0];
+					_fnDetectHeader( oSettings.aoFooter, oSettings.nTFoot );
+				}
+			
+				/* Check if there is data passing into the constructor */
+				if ( oInit.aaData ) {
+					for ( i=0 ; i<oInit.aaData.length ; i++ ) {
+						_fnAddData( oSettings, oInit.aaData[ i ] );
+					}
+				}
+				else if ( oSettings.bDeferLoading || _fnDataSource( oSettings ) == 'dom' ) {
+					/* Grab the data from the page - only do this when deferred loading or no Ajax
+					 * source since there is no point in reading the DOM data if we are then going
+					 * to replace it with Ajax data
+					 */
+					_fnAddTr( oSettings, $(oSettings.nTBody).children('tr') );
+				}
+			
+				/* Copy the data index array */
+				oSettings.aiDisplay = oSettings.aiDisplayMaster.slice();
+			
+				/* Initialisation complete - table can be drawn */
+				oSettings.bInitialised = true;
+			
+				/* Check if we need to initialise the table (it might not have been handed off to the
+				 * language processor)
+				 */
+				if ( bInitHandedOff === false ) {
+					_fnInitialise( oSettings );
+				}
+			};
+			
+			/* Must be done after everything which can be overridden by the state saving! */
+			if ( oInit.bStateSave )
+			{
+				features.bStateSave = true;
+				_fnCallbackReg( oSettings, 'aoDrawCallback', _fnSaveState, 'state_save' );
+				_fnLoadState( oSettings, oInit, loadedInit );
+			}
+			else {
+				loadedInit();
+			}
+			
+		} );
+		_that = null;
+		return this;
+	};
+
+	
+	/*
+	 * It is useful to have variables which are scoped locally so only the
+	 * DataTables functions can access them and they don't leak into global space.
+	 * At the same time these functions are often useful over multiple files in the
+	 * core and API, so we list, or at least document, all variables which are used
+	 * by DataTables as private variables here. This also ensures that there is no
+	 * clashing of variable names and that they can easily referenced for reuse.
+	 */
+	
+	
+	// Defined else where
+	//  _selector_run
+	//  _selector_opts
+	//  _selector_first
+	//  _selector_row_indexes
+	
+	var _ext; // DataTable.ext
+	var _Api; // DataTable.Api
+	var _api_register; // DataTable.Api.register
+	var _api_registerPlural; // DataTable.Api.registerPlural
+	
+	var _re_dic = {};
+	var _re_new_lines = /[\r\n]/g;
+	var _re_html = /<.*?>/g;
+	
+	// This is not strict ISO8601 - Date.parse() is quite lax, although
+	// implementations differ between browsers.
+	var _re_date = /^\d{2,4}[\.\/\-]\d{1,2}[\.\/\-]\d{1,2}([T ]{1}\d{1,2}[:\.]\d{2}([\.:]\d{2})?)?$/;
+	
+	// Escape regular expression special characters
+	var _re_escape_regex = new RegExp( '(\\' + [ '/', '.', '*', '+', '?', '|', '(', ')', '[', ']', '{', '}', '\\', '$', '^', '-' ].join('|\\') + ')', 'g' );
+	
+	// http://en.wikipedia.org/wiki/Foreign_exchange_market
+	// - \u20BD - Russian ruble.
+	// - \u20a9 - South Korean Won
+	// - \u20BA - Turkish Lira
+	// - \u20B9 - Indian Rupee
+	// - R - Brazil (R$) and South Africa
+	// - fr - Swiss Franc
+	// - kr - Swedish krona, Norwegian krone and Danish krone
+	// - \u2009 is thin space and \u202F is narrow no-break space, both used in many
+	//   standards as thousands separators.
+	var _re_formatted_numeric = /[',$£€¥%\u2009\u202F\u20BD\u20a9\u20BArfk]/gi;
+	
+	
+	var _empty = function ( d ) {
+		return !d || d === true || d === '-' ? true : false;
+	};
+	
+	
+	var _intVal = function ( s ) {
+		var integer = parseInt( s, 10 );
+		return !isNaN(integer) && isFinite(s) ? integer : null;
+	};
+	
+	// Convert from a formatted number with characters other than `.` as the
+	// decimal place, to a Javascript number
+	var _numToDecimal = function ( num, decimalPoint ) {
+		// Cache created regular expressions for speed as this function is called often
+		if ( ! _re_dic[ decimalPoint ] ) {
+			_re_dic[ decimalPoint ] = new RegExp( _fnEscapeRegex( decimalPoint ), 'g' );
+		}
+		return typeof num === 'string' && decimalPoint !== '.' ?
+			num.replace( /\./g, '' ).replace( _re_dic[ decimalPoint ], '.' ) :
+			num;
+	};
+	
+	
+	var _isNumber = function ( d, decimalPoint, formatted ) {
+		var strType = typeof d === 'string';
+	
+		// If empty return immediately so there must be a number if it is a
+		// formatted string (this stops the string "k", or "kr", etc being detected
+		// as a formatted number for currency
+		if ( _empty( d ) ) {
+			return true;
+		}
+	
+		if ( decimalPoint && strType ) {
+			d = _numToDecimal( d, decimalPoint );
+		}
+	
+		if ( formatted && strType ) {
+			d = d.replace( _re_formatted_numeric, '' );
+		}
+	
+		return !isNaN( parseFloat(d) ) && isFinite( d );
+	};
+	
+	
+	// A string without HTML in it can be considered to be HTML still
+	var _isHtml = function ( d ) {
+		return _empty( d ) || typeof d === 'string';
+	};
+	
+	
+	var _htmlNumeric = function ( d, decimalPoint, formatted ) {
+		if ( _empty( d ) ) {
+			return true;
+		}
+	
+		var html = _isHtml( d );
+		return ! html ?
+			null :
+			_isNumber( _stripHtml( d ), decimalPoint, formatted ) ?
+				true :
+				null;
+	};
+	
+	
+	var _pluck = function ( a, prop, prop2 ) {
+		var out = [];
+		var i=0, ien=a.length;
+	
+		// Could have the test in the loop for slightly smaller code, but speed
+		// is essential here
+		if ( prop2 !== undefined ) {
+			for ( ; i<ien ; i++ ) {
+				if ( a[i] && a[i][ prop ] ) {
+					out.push( a[i][ prop ][ prop2 ] );
+				}
+			}
+		}
+		else {
+			for ( ; i<ien ; i++ ) {
+				if ( a[i] ) {
+					out.push( a[i][ prop ] );
+				}
+			}
+		}
+	
+		return out;
+	};
+	
+	
+	// Basically the same as _pluck, but rather than looping over `a` we use `order`
+	// as the indexes to pick from `a`
+	var _pluck_order = function ( a, order, prop, prop2 )
+	{
+		var out = [];
+		var i=0, ien=order.length;
+	
+		// Could have the test in the loop for slightly smaller code, but speed
+		// is essential here
+		if ( prop2 !== undefined ) {
+			for ( ; i<ien ; i++ ) {
+				if ( a[ order[i] ][ prop ] ) {
+					out.push( a[ order[i] ][ prop ][ prop2 ] );
+				}
+			}
+		}
+		else {
+			for ( ; i<ien ; i++ ) {
+				out.push( a[ order[i] ][ prop ] );
+			}
+		}
+	
+		return out;
+	};
+	
+	
+	var _range = function ( len, start )
+	{
+		var out = [];
+		var end;
+	
+		if ( start === undefined ) {
+			start = 0;
+			end = len;
+		}
+		else {
+			end = start;
+			start = len;
+		}
+	
+		for ( var i=start ; i<end ; i++ ) {
+			out.push( i );
+		}
+	
+		return out;
+	};
+	
+	
+	var _removeEmpty = function ( a )
+	{
+		var out = [];
+	
+		for ( var i=0, ien=a.length ; i<ien ; i++ ) {
+			if ( a[i] ) { // careful - will remove all falsy values!
+				out.push( a[i] );
+			}
+		}
+	
+		return out;
+	};
+	
+	
+	var _stripHtml = function ( d ) {
+		return d.replace( _re_html, '' );
+	};
+	
+	
+	/**
+	 * Determine if all values in the array are unique. This means we can short
+	 * cut the _unique method at the cost of a single loop. A sorted array is used
+	 * to easily check the values.
+	 *
+	 * @param  {array} src Source array
+	 * @return {boolean} true if all unique, false otherwise
+	 * @ignore
+	 */
+	var _areAllUnique = function ( src ) {
+		if ( src.length < 2 ) {
+			return true;
+		}
+	
+		var sorted = src.slice().sort();
+		var last = sorted[0];
+	
+		for ( var i=1, ien=sorted.length ; i<ien ; i++ ) {
+			if ( sorted[i] === last ) {
+				return false;
+			}
+	
+			last = sorted[i];
+		}
+	
+		return true;
+	};
+	
+	
+	/**
+	 * Find the unique elements in a source array.
+	 *
+	 * @param  {array} src Source array
+	 * @return {array} Array of unique items
+	 * @ignore
+	 */
+	var _unique = function ( src )
+	{
+		if ( _areAllUnique( src ) ) {
+			return src.slice();
+		}
+	
+		// A faster unique method is to use object keys to identify used values,
+		// but this doesn't work with arrays or objects, which we must also
+		// consider. See jsperf.com/compare-array-unique-versions/4 for more
+		// information.
+		var
+			out = [],
+			val,
+			i, ien=src.length,
+			j, k=0;
+	
+		again: for ( i=0 ; i<ien ; i++ ) {
+			val = src[i];
+	
+			for ( j=0 ; j<k ; j++ ) {
+				if ( out[j] === val ) {
+					continue again;
+				}
+			}
+	
+			out.push( val );
+			k++;
+		}
+	
+		return out;
+	};
+	
+	
+	/**
+	 * DataTables utility methods
+	 * 
+	 * This namespace provides helper methods that DataTables uses internally to
+	 * create a DataTable, but which are not exclusively used only for DataTables.
+	 * These methods can be used by extension authors to save the duplication of
+	 * code.
+	 *
+	 *  @namespace
+	 */
+	DataTable.util = {
+		/**
+		 * Throttle the calls to a function. Arguments and context are maintained
+		 * for the throttled function.
+		 *
+		 * @param {function} fn Function to be called
+		 * @param {integer} freq Call frequency in mS
+		 * @return {function} Wrapped function
+		 */
+		throttle: function ( fn, freq ) {
+			var
+				frequency = freq !== undefined ? freq : 200,
+				last,
+				timer;
+	
+			return function () {
+				var
+					that = this,
+					now  = +new Date(),
+					args = arguments;
+	
+				if ( last && now < last + frequency ) {
+					clearTimeout( timer );
+	
+					timer = setTimeout( function () {
+						last = undefined;
+						fn.apply( that, args );
+					}, frequency );
+				}
+				else {
+					last = now;
+					fn.apply( that, args );
+				}
+			};
+		},
+	
+	
+		/**
+		 * Escape a string such that it can be used in a regular expression
+		 *
+		 *  @param {string} val string to escape
+		 *  @returns {string} escaped string
+		 */
+		escapeRegex: function ( val ) {
+			return val.replace( _re_escape_regex, '\\$1' );
+		}
+	};
+	
+	
+	
+	/**
+	 * Create a mapping object that allows camel case parameters to be looked up
+	 * for their Hungarian counterparts. The mapping is stored in a private
+	 * parameter called `_hungarianMap` which can be accessed on the source object.
+	 *  @param {object} o
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnHungarianMap ( o )
+	{
+		var
+			hungarian = 'a aa ai ao as b fn i m o s ',
+			match,
+			newKey,
+			map = {};
+	
+		$.each( o, function (key, val) {
+			match = key.match(/^([^A-Z]+?)([A-Z])/);
+	
+			if ( match && hungarian.indexOf(match[1]+' ') !== -1 )
+			{
+				newKey = key.replace( match[0], match[2].toLowerCase() );
+				map[ newKey ] = key;
+	
+				if ( match[1] === 'o' )
+				{
+					_fnHungarianMap( o[key] );
+				}
+			}
+		} );
+	
+		o._hungarianMap = map;
+	}
+	
+	
+	/**
+	 * Convert from camel case parameters to Hungarian, based on a Hungarian map
+	 * created by _fnHungarianMap.
+	 *  @param {object} src The model object which holds all parameters that can be
+	 *    mapped.
+	 *  @param {object} user The object to convert from camel case to Hungarian.
+	 *  @param {boolean} force When set to `true`, properties which already have a
+	 *    Hungarian value in the `user` object will be overwritten. Otherwise they
+	 *    won't be.
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnCamelToHungarian ( src, user, force )
+	{
+		if ( ! src._hungarianMap ) {
+			_fnHungarianMap( src );
+		}
+	
+		var hungarianKey;
+	
+		$.each( user, function (key, val) {
+			hungarianKey = src._hungarianMap[ key ];
+	
+			if ( hungarianKey !== undefined && (force || user[hungarianKey] === undefined) )
+			{
+				// For objects, we need to buzz down into the object to copy parameters
+				if ( hungarianKey.charAt(0) === 'o' )
+				{
+					// Copy the camelCase options over to the hungarian
+					if ( ! user[ hungarianKey ] ) {
+						user[ hungarianKey ] = {};
+					}
+					$.extend( true, user[hungarianKey], user[key] );
+	
+					_fnCamelToHungarian( src[hungarianKey], user[hungarianKey], force );
+				}
+				else {
+					user[hungarianKey] = user[ key ];
+				}
+			}
+		} );
+	}
+	
+	
+	/**
+	 * Language compatibility - when certain options are given, and others aren't, we
+	 * need to duplicate the values over, in order to provide backwards compatibility
+	 * with older language files.
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnLanguageCompat( lang )
+	{
+		var defaults = DataTable.defaults.oLanguage;
+		var zeroRecords = lang.sZeroRecords;
+	
+		/* Backwards compatibility - if there is no sEmptyTable given, then use the same as
+		 * sZeroRecords - assuming that is given.
+		 */
+		if ( ! lang.sEmptyTable && zeroRecords &&
+			defaults.sEmptyTable === "No data available in table" )
+		{
+			_fnMap( lang, lang, 'sZeroRecords', 'sEmptyTable' );
+		}
+	
+		/* Likewise with loading records */
+		if ( ! lang.sLoadingRecords && zeroRecords &&
+			defaults.sLoadingRecords === "Loading..." )
+		{
+			_fnMap( lang, lang, 'sZeroRecords', 'sLoadingRecords' );
+		}
+	
+		// Old parameter name of the thousands separator mapped onto the new
+		if ( lang.sInfoThousands ) {
+			lang.sThousands = lang.sInfoThousands;
+		}
+	
+		var decimal = lang.sDecimal;
+		if ( decimal ) {
+			_addNumericSort( decimal );
+		}
+	}
+	
+	
+	/**
+	 * Map one parameter onto another
+	 *  @param {object} o Object to map
+	 *  @param {*} knew The new parameter name
+	 *  @param {*} old The old parameter name
+	 */
+	var _fnCompatMap = function ( o, knew, old ) {
+		if ( o[ knew ] !== undefined ) {
+			o[ old ] = o[ knew ];
+		}
+	};
+	
+	
+	/**
+	 * Provide backwards compatibility for the main DT options. Note that the new
+	 * options are mapped onto the old parameters, so this is an external interface
+	 * change only.
+	 *  @param {object} init Object to map
+	 */
+	function _fnCompatOpts ( init )
+	{
+		_fnCompatMap( init, 'ordering',      'bSort' );
+		_fnCompatMap( init, 'orderMulti',    'bSortMulti' );
+		_fnCompatMap( init, 'orderClasses',  'bSortClasses' );
+		_fnCompatMap( init, 'orderCellsTop', 'bSortCellsTop' );
+		_fnCompatMap( init, 'order',         'aaSorting' );
+		_fnCompatMap( init, 'orderFixed',    'aaSortingFixed' );
+		_fnCompatMap( init, 'paging',        'bPaginate' );
+		_fnCompatMap( init, 'pagingType',    'sPaginationType' );
+		_fnCompatMap( init, 'pageLength',    'iDisplayLength' );
+		_fnCompatMap( init, 'searching',     'bFilter' );
+	
+		// Boolean initialisation of x-scrolling
+		if ( typeof init.sScrollX === 'boolean' ) {
+			init.sScrollX = init.sScrollX ? '100%' : '';
+		}
+		if ( typeof init.scrollX === 'boolean' ) {
+			init.scrollX = init.scrollX ? '100%' : '';
+		}
+	
+		// Column search objects are in an array, so it needs to be converted
+		// element by element
+		var searchCols = init.aoSearchCols;
+	
+		if ( searchCols ) {
+			for ( var i=0, ien=searchCols.length ; i<ien ; i++ ) {
+				if ( searchCols[i] ) {
+					_fnCamelToHungarian( DataTable.models.oSearch, searchCols[i] );
+				}
+			}
+		}
+	}
+	
+	
+	/**
+	 * Provide backwards compatibility for column options. Note that the new options
+	 * are mapped onto the old parameters, so this is an external interface change
+	 * only.
+	 *  @param {object} init Object to map
+	 */
+	function _fnCompatCols ( init )
+	{
+		_fnCompatMap( init, 'orderable',     'bSortable' );
+		_fnCompatMap( init, 'orderData',     'aDataSort' );
+		_fnCompatMap( init, 'orderSequence', 'asSorting' );
+		_fnCompatMap( init, 'orderDataType', 'sortDataType' );
+	
+		// orderData can be given as an integer
+		var dataSort = init.aDataSort;
+		if ( typeof dataSort === 'number' && ! $.isArray( dataSort ) ) {
+			init.aDataSort = [ dataSort ];
+		}
+	}
+	
+	
+	/**
+	 * Browser feature detection for capabilities, quirks
+	 *  @param {object} settings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnBrowserDetect( settings )
+	{
+		// We don't need to do this every time DataTables is constructed, the values
+		// calculated are specific to the browser and OS configuration which we
+		// don't expect to change between initialisations
+		if ( ! DataTable.__browser ) {
+			var browser = {};
+			DataTable.__browser = browser;
+	
+			// Scrolling feature / quirks detection
+			var n = $('<div/>')
+				.css( {
+					position: 'fixed',
+					top: 0,
+					left: $(window).scrollLeft()*-1, // allow for scrolling
+					height: 1,
+					width: 1,
+					overflow: 'hidden'
+				} )
+				.append(
+					$('<div/>')
+						.css( {
+							position: 'absolute',
+							top: 1,
+							left: 1,
+							width: 100,
+							overflow: 'scroll'
+						} )
+						.append(
+							$('<div/>')
+								.css( {
+									width: '100%',
+									height: 10
+								} )
+						)
+				)
+				.appendTo( 'body' );
+	
+			var outer = n.children();
+			var inner = outer.children();
+	
+			// Numbers below, in order, are:
+			// inner.offsetWidth, inner.clientWidth, outer.offsetWidth, outer.clientWidth
+			//
+			// IE6 XP:                           100 100 100  83
+			// IE7 Vista:                        100 100 100  83
+			// IE 8+ Windows:                     83  83 100  83
+			// Evergreen Windows:                 83  83 100  83
+			// Evergreen Mac with scrollbars:     85  85 100  85
+			// Evergreen Mac without scrollbars: 100 100 100 100
+	
+			// Get scrollbar width
+			browser.barWidth = outer[0].offsetWidth - outer[0].clientWidth;
+	
+			// IE6/7 will oversize a width 100% element inside a scrolling element, to
+			// include the width of the scrollbar, while other browsers ensure the inner
+			// element is contained without forcing scrolling
+			browser.bScrollOversize = inner[0].offsetWidth === 100 && outer[0].clientWidth !== 100;
+	
+			// In rtl text layout, some browsers (most, but not all) will place the
+			// scrollbar on the left, rather than the right.
+			browser.bScrollbarLeft = Math.round( inner.offset().left ) !== 1;
+	
+			// IE8- don't provide height and width for getBoundingClientRect
+			browser.bBounding = n[0].getBoundingClientRect().width ? true : false;
+	
+			n.remove();
+		}
+	
+		$.extend( settings.oBrowser, DataTable.__browser );
+		settings.oScroll.iBarWidth = DataTable.__browser.barWidth;
+	}
+	
+	
+	/**
+	 * Array.prototype reduce[Right] method, used for browsers which don't support
+	 * JS 1.6. Done this way to reduce code size, since we iterate either way
+	 *  @param {object} settings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnReduce ( that, fn, init, start, end, inc )
+	{
+		var
+			i = start,
+			value,
+			isSet = false;
+	
+		if ( init !== undefined ) {
+			value = init;
+			isSet = true;
+		}
+	
+		while ( i !== end ) {
+			if ( ! that.hasOwnProperty(i) ) {
+				continue;
+			}
+	
+			value = isSet ?
+				fn( value, that[i], i, that ) :
+				that[i];
+	
+			isSet = true;
+			i += inc;
+		}
+	
+		return value;
+	}
+	
+	/**
+	 * Add a column to the list used for the table with default values
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {node} nTh The th element for this column
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnAddColumn( oSettings, nTh )
+	{
+		// Add column to aoColumns array
+		var oDefaults = DataTable.defaults.column;
+		var iCol = oSettings.aoColumns.length;
+		var oCol = $.extend( {}, DataTable.models.oColumn, oDefaults, {
+			"nTh": nTh ? nTh : document.createElement('th'),
+			"sTitle":    oDefaults.sTitle    ? oDefaults.sTitle    : nTh ? nTh.innerHTML : '',
+			"aDataSort": oDefaults.aDataSort ? oDefaults.aDataSort : [iCol],
+			"mData": oDefaults.mData ? oDefaults.mData : iCol,
+			idx: iCol
+		} );
+		oSettings.aoColumns.push( oCol );
+	
+		// Add search object for column specific search. Note that the `searchCols[ iCol ]`
+		// passed into extend can be undefined. This allows the user to give a default
+		// with only some of the parameters defined, and also not give a default
+		var searchCols = oSettings.aoPreSearchCols;
+		searchCols[ iCol ] = $.extend( {}, DataTable.models.oSearch, searchCols[ iCol ] );
+	
+		// Use the default column options function to initialise classes etc
+		_fnColumnOptions( oSettings, iCol, $(nTh).data() );
+	}
+	
+	
+	/**
+	 * Apply options for a column
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {int} iCol column index to consider
+	 *  @param {object} oOptions object with sType, bVisible and bSearchable etc
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnColumnOptions( oSettings, iCol, oOptions )
+	{
+		var oCol = oSettings.aoColumns[ iCol ];
+		var oClasses = oSettings.oClasses;
+		var th = $(oCol.nTh);
+	
+		// Try to get width information from the DOM. We can't get it from CSS
+		// as we'd need to parse the CSS stylesheet. `width` option can override
+		if ( ! oCol.sWidthOrig ) {
+			// Width attribute
+			oCol.sWidthOrig = th.attr('width') || null;
+	
+			// Style attribute
+			var t = (th.attr('style') || '').match(/width:\s*(\d+[pxem%]+)/);
+			if ( t ) {
+				oCol.sWidthOrig = t[1];
+			}
+		}
+	
+		/* User specified column options */
+		if ( oOptions !== undefined && oOptions !== null )
+		{
+			// Backwards compatibility
+			_fnCompatCols( oOptions );
+	
+			// Map camel case parameters to their Hungarian counterparts
+			_fnCamelToHungarian( DataTable.defaults.column, oOptions );
+	
+			/* Backwards compatibility for mDataProp */
+			if ( oOptions.mDataProp !== undefined && !oOptions.mData )
+			{
+				oOptions.mData = oOptions.mDataProp;
+			}
+	
+			if ( oOptions.sType )
+			{
+				oCol._sManualType = oOptions.sType;
+			}
+	
+			// `class` is a reserved word in Javascript, so we need to provide
+			// the ability to use a valid name for the camel case input
+			if ( oOptions.className && ! oOptions.sClass )
+			{
+				oOptions.sClass = oOptions.className;
+			}
+			if ( oOptions.sClass ) {
+				th.addClass( oOptions.sClass );
+			}
+	
+			$.extend( oCol, oOptions );
+			_fnMap( oCol, oOptions, "sWidth", "sWidthOrig" );
+	
+			/* iDataSort to be applied (backwards compatibility), but aDataSort will take
+			 * priority if defined
+			 */
+			if ( oOptions.iDataSort !== undefined )
+			{
+				oCol.aDataSort = [ oOptions.iDataSort ];
+			}
+			_fnMap( oCol, oOptions, "aDataSort" );
+		}
+	
+		/* Cache the data get and set functions for speed */
+		var mDataSrc = oCol.mData;
+		var mData = _fnGetObjectDataFn( mDataSrc );
+		var mRender = oCol.mRender ? _fnGetObjectDataFn( oCol.mRender ) : null;
+	
+		var attrTest = function( src ) {
+			return typeof src === 'string' && src.indexOf('@') !== -1;
+		};
+		oCol._bAttrSrc = $.isPlainObject( mDataSrc ) && (
+			attrTest(mDataSrc.sort) || attrTest(mDataSrc.type) || attrTest(mDataSrc.filter)
+		);
+		oCol._setter = null;
+	
+		oCol.fnGetData = function (rowData, type, meta) {
+			var innerData = mData( rowData, type, undefined, meta );
+	
+			return mRender && type ?
+				mRender( innerData, type, rowData, meta ) :
+				innerData;
+		};
+		oCol.fnSetData = function ( rowData, val, meta ) {
+			return _fnSetObjectDataFn( mDataSrc )( rowData, val, meta );
+		};
+	
+		// Indicate if DataTables should read DOM data as an object or array
+		// Used in _fnGetRowElements
+		if ( typeof mDataSrc !== 'number' ) {
+			oSettings._rowReadObject = true;
+		}
+	
+		/* Feature sorting overrides column specific when off */
+		if ( !oSettings.oFeatures.bSort )
+		{
+			oCol.bSortable = false;
+			th.addClass( oClasses.sSortableNone ); // Have to add class here as order event isn't called
+		}
+	
+		/* Check that the class assignment is correct for sorting */
+		var bAsc = $.inArray('asc', oCol.asSorting) !== -1;
+		var bDesc = $.inArray('desc', oCol.asSorting) !== -1;
+		if ( !oCol.bSortable || (!bAsc && !bDesc) )
+		{
+			oCol.sSortingClass = oClasses.sSortableNone;
+			oCol.sSortingClassJUI = "";
+		}
+		else if ( bAsc && !bDesc )
+		{
+			oCol.sSortingClass = oClasses.sSortableAsc;
+			oCol.sSortingClassJUI = oClasses.sSortJUIAscAllowed;
+		}
+		else if ( !bAsc && bDesc )
+		{
+			oCol.sSortingClass = oClasses.sSortableDesc;
+			oCol.sSortingClassJUI = oClasses.sSortJUIDescAllowed;
+		}
+		else
+		{
+			oCol.sSortingClass = oClasses.sSortable;
+			oCol.sSortingClassJUI = oClasses.sSortJUI;
+		}
+	}
+	
+	
+	/**
+	 * Adjust the table column widths for new data. Note: you would probably want to
+	 * do a redraw after calling this function!
+	 *  @param {object} settings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnAdjustColumnSizing ( settings )
+	{
+		/* Not interested in doing column width calculation if auto-width is disabled */
+		if ( settings.oFeatures.bAutoWidth !== false )
+		{
+			var columns = settings.aoColumns;
+	
+			_fnCalculateColumnWidths( settings );
+			for ( var i=0 , iLen=columns.length ; i<iLen ; i++ )
+			{
+				columns[i].nTh.style.width = columns[i].sWidth;
+			}
+		}
+	
+		var scroll = settings.oScroll;
+		if ( scroll.sY !== '' || scroll.sX !== '')
+		{
+			_fnScrollDraw( settings );
+		}
+	
+		_fnCallbackFire( settings, null, 'column-sizing', [settings] );
+	}
+	
+	
+	/**
+	 * Covert the index of a visible column to the index in the data array (take account
+	 * of hidden columns)
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {int} iMatch Visible column index to lookup
+	 *  @returns {int} i the data index
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnVisibleToColumnIndex( oSettings, iMatch )
+	{
+		var aiVis = _fnGetColumns( oSettings, 'bVisible' );
+	
+		return typeof aiVis[iMatch] === 'number' ?
+			aiVis[iMatch] :
+			null;
+	}
+	
+	
+	/**
+	 * Covert the index of an index in the data array and convert it to the visible
+	 *   column index (take account of hidden columns)
+	 *  @param {int} iMatch Column index to lookup
+	 *  @param {object} oSettings dataTables settings object
+	 *  @returns {int} i the data index
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnColumnIndexToVisible( oSettings, iMatch )
+	{
+		var aiVis = _fnGetColumns( oSettings, 'bVisible' );
+		var iPos = $.inArray( iMatch, aiVis );
+	
+		return iPos !== -1 ? iPos : null;
+	}
+	
+	
+	/**
+	 * Get the number of visible columns
+	 *  @param {object} oSettings dataTables settings object
+	 *  @returns {int} i the number of visible columns
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnVisbleColumns( oSettings )
+	{
+		var vis = 0;
+	
+		// No reduce in IE8, use a loop for now
+		$.each( oSettings.aoColumns, function ( i, col ) {
+			if ( col.bVisible && $(col.nTh).css('display') !== 'none' ) {
+				vis++;
+			}
+		} );
+	
+		return vis;
+	}
+	
+	
+	/**
+	 * Get an array of column indexes that match a given property
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {string} sParam Parameter in aoColumns to look for - typically
+	 *    bVisible or bSearchable
+	 *  @returns {array} Array of indexes with matched properties
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnGetColumns( oSettings, sParam )
+	{
+		var a = [];
+	
+		$.map( oSettings.aoColumns, function(val, i) {
+			if ( val[sParam] ) {
+				a.push( i );
+			}
+		} );
+	
+		return a;
+	}
+	
+	
+	/**
+	 * Calculate the 'type' of a column
+	 *  @param {object} settings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnColumnTypes ( settings )
+	{
+		var columns = settings.aoColumns;
+		var data = settings.aoData;
+		var types = DataTable.ext.type.detect;
+		var i, ien, j, jen, k, ken;
+		var col, cell, detectedType, cache;
+	
+		// For each column, spin over the 
+		for ( i=0, ien=columns.length ; i<ien ; i++ ) {
+			col = columns[i];
+			cache = [];
+	
+			if ( ! col.sType && col._sManualType ) {
+				col.sType = col._sManualType;
+			}
+			else if ( ! col.sType ) {
+				for ( j=0, jen=types.length ; j<jen ; j++ ) {
+					for ( k=0, ken=data.length ; k<ken ; k++ ) {
+						// Use a cache array so we only need to get the type data
+						// from the formatter once (when using multiple detectors)
+						if ( cache[k] === undefined ) {
+							cache[k] = _fnGetCellData( settings, k, i, 'type' );
+						}
+	
+						detectedType = types[j]( cache[k], settings );
+	
+						// If null, then this type can't apply to this column, so
+						// rather than testing all cells, break out. There is an
+						// exception for the last type which is `html`. We need to
+						// scan all rows since it is possible to mix string and HTML
+						// types
+						if ( ! detectedType && j !== types.length-1 ) {
+							break;
+						}
+	
+						// Only a single match is needed for html type since it is
+						// bottom of the pile and very similar to string
+						if ( detectedType === 'html' ) {
+							break;
+						}
+					}
+	
+					// Type is valid for all data points in the column - use this
+					// type
+					if ( detectedType ) {
+						col.sType = detectedType;
+						break;
+					}
+				}
+	
+				// Fall back - if no type was detected, always use string
+				if ( ! col.sType ) {
+					col.sType = 'string';
+				}
+			}
+		}
+	}
+	
+	
+	/**
+	 * Take the column definitions and static columns arrays and calculate how
+	 * they relate to column indexes. The callback function will then apply the
+	 * definition found for a column to a suitable configuration object.
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {array} aoColDefs The aoColumnDefs array that is to be applied
+	 *  @param {array} aoCols The aoColumns array that defines columns individually
+	 *  @param {function} fn Callback function - takes two parameters, the calculated
+	 *    column index and the definition for that column.
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnApplyColumnDefs( oSettings, aoColDefs, aoCols, fn )
+	{
+		var i, iLen, j, jLen, k, kLen, def;
+		var columns = oSettings.aoColumns;
+	
+		// Column definitions with aTargets
+		if ( aoColDefs )
+		{
+			/* Loop over the definitions array - loop in reverse so first instance has priority */
+			for ( i=aoColDefs.length-1 ; i>=0 ; i-- )
+			{
+				def = aoColDefs[i];
+	
+				/* Each definition can target multiple columns, as it is an array */
+				var aTargets = def.targets !== undefined ?
+					def.targets :
+					def.aTargets;
+	
+				if ( ! $.isArray( aTargets ) )
+				{
+					aTargets = [ aTargets ];
+				}
+	
+				for ( j=0, jLen=aTargets.length ; j<jLen ; j++ )
+				{
+					if ( typeof aTargets[j] === 'number' && aTargets[j] >= 0 )
+					{
+						/* Add columns that we don't yet know about */
+						while( columns.length <= aTargets[j] )
+						{
+							_fnAddColumn( oSettings );
+						}
+	
+						/* Integer, basic index */
+						fn( aTargets[j], def );
+					}
+					else if ( typeof aTargets[j] === 'number' && aTargets[j] < 0 )
+					{
+						/* Negative integer, right to left column counting */
+						fn( columns.length+aTargets[j], def );
+					}
+					else if ( typeof aTargets[j] === 'string' )
+					{
+						/* Class name matching on TH element */
+						for ( k=0, kLen=columns.length ; k<kLen ; k++ )
+						{
+							if ( aTargets[j] == "_all" ||
+							     $(columns[k].nTh).hasClass( aTargets[j] ) )
+							{
+								fn( k, def );
+							}
+						}
+					}
+				}
+			}
+		}
+	
+		// Statically defined columns array
+		if ( aoCols )
+		{
+			for ( i=0, iLen=aoCols.length ; i<iLen ; i++ )
+			{
+				fn( i, aoCols[i] );
+			}
+		}
+	}
+	
+	/**
+	 * Add a data array to the table, creating DOM node etc. This is the parallel to
+	 * _fnGatherData, but for adding rows from a Javascript source, rather than a
+	 * DOM source.
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {array} aData data array to be added
+	 *  @param {node} [nTr] TR element to add to the table - optional. If not given,
+	 *    DataTables will create a row automatically
+	 *  @param {array} [anTds] Array of TD|TH elements for the row - must be given
+	 *    if nTr is.
+	 *  @returns {int} >=0 if successful (index of new aoData entry), -1 if failed
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnAddData ( oSettings, aDataIn, nTr, anTds )
+	{
+		/* Create the object for storing information about this new row */
+		var iRow = oSettings.aoData.length;
+		var oData = $.extend( true, {}, DataTable.models.oRow, {
+			src: nTr ? 'dom' : 'data',
+			idx: iRow
+		} );
+	
+		oData._aData = aDataIn;
+		oSettings.aoData.push( oData );
+	
+		/* Create the cells */
+		var nTd, sThisType;
+		var columns = oSettings.aoColumns;
+	
+		// Invalidate the column types as the new data needs to be revalidated
+		for ( var i=0, iLen=columns.length ; i<iLen ; i++ )
+		{
+			columns[i].sType = null;
+		}
+	
+		/* Add to the display array */
+		oSettings.aiDisplayMaster.push( iRow );
+	
+		var id = oSettings.rowIdFn( aDataIn );
+		if ( id !== undefined ) {
+			oSettings.aIds[ id ] = oData;
+		}
+	
+		/* Create the DOM information, or register it if already present */
+		if ( nTr || ! oSettings.oFeatures.bDeferRender )
+		{
+			_fnCreateTr( oSettings, iRow, nTr, anTds );
+		}
+	
+		return iRow;
+	}
+	
+	
+	/**
+	 * Add one or more TR elements to the table. Generally we'd expect to
+	 * use this for reading data from a DOM sourced table, but it could be
+	 * used for an TR element. Note that if a TR is given, it is used (i.e.
+	 * it is not cloned).
+	 *  @param {object} settings dataTables settings object
+	 *  @param {array|node|jQuery} trs The TR element(s) to add to the table
+	 *  @returns {array} Array of indexes for the added rows
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnAddTr( settings, trs )
+	{
+		var row;
+	
+		// Allow an individual node to be passed in
+		if ( ! (trs instanceof $) ) {
+			trs = $(trs);
+		}
+	
+		return trs.map( function (i, el) {
+			row = _fnGetRowElements( settings, el );
+			return _fnAddData( settings, row.data, el, row.cells );
+		} );
+	}
+	
+	
+	/**
+	 * Take a TR element and convert it to an index in aoData
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {node} n the TR element to find
+	 *  @returns {int} index if the node is found, null if not
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnNodeToDataIndex( oSettings, n )
+	{
+		return (n._DT_RowIndex!==undefined) ? n._DT_RowIndex : null;
+	}
+	
+	
+	/**
+	 * Take a TD element and convert it into a column data index (not the visible index)
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {int} iRow The row number the TD/TH can be found in
+	 *  @param {node} n The TD/TH element to find
+	 *  @returns {int} index if the node is found, -1 if not
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnNodeToColumnIndex( oSettings, iRow, n )
+	{
+		return $.inArray( n, oSettings.aoData[ iRow ].anCells );
+	}
+	
+	
+	/**
+	 * Get the data for a given cell from the internal cache, taking into account data mapping
+	 *  @param {object} settings dataTables settings object
+	 *  @param {int} rowIdx aoData row id
+	 *  @param {int} colIdx Column index
+	 *  @param {string} type data get type ('display', 'type' 'filter' 'sort')
+	 *  @returns {*} Cell data
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnGetCellData( settings, rowIdx, colIdx, type )
+	{
+		var draw           = settings.iDraw;
+		var col            = settings.aoColumns[colIdx];
+		var rowData        = settings.aoData[rowIdx]._aData;
+		var defaultContent = col.sDefaultContent;
+		var cellData       = col.fnGetData( rowData, type, {
+			settings: settings,
+			row:      rowIdx,
+			col:      colIdx
+		} );
+	
+		if ( cellData === undefined ) {
+			if ( settings.iDrawError != draw && defaultContent === null ) {
+				_fnLog( settings, 0, "Requested unknown parameter "+
+					(typeof col.mData=='function' ? '{function}' : "'"+col.mData+"'")+
+					" for row "+rowIdx+", column "+colIdx, 4 );
+				settings.iDrawError = draw;
+			}
+			return defaultContent;
+		}
+	
+		// When the data source is null and a specific data type is requested (i.e.
+		// not the original data), we can use default column data
+		if ( (cellData === rowData || cellData === null) && defaultContent !== null && type !== undefined ) {
+			cellData = defaultContent;
+		}
+		else if ( typeof cellData === 'function' ) {
+			// If the data source is a function, then we run it and use the return,
+			// executing in the scope of the data object (for instances)
+			return cellData.call( rowData );
+		}
+	
+		if ( cellData === null && type == 'display' ) {
+			return '';
+		}
+		return cellData;
+	}
+	
+	
+	/**
+	 * Set the value for a specific cell, into the internal data cache
+	 *  @param {object} settings dataTables settings object
+	 *  @param {int} rowIdx aoData row id
+	 *  @param {int} colIdx Column index
+	 *  @param {*} val Value to set
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSetCellData( settings, rowIdx, colIdx, val )
+	{
+		var col     = settings.aoColumns[colIdx];
+		var rowData = settings.aoData[rowIdx]._aData;
+	
+		col.fnSetData( rowData, val, {
+			settings: settings,
+			row:      rowIdx,
+			col:      colIdx
+		}  );
+	}
+	
+	
+	// Private variable that is used to match action syntax in the data property object
+	var __reArray = /\[.*?\]$/;
+	var __reFn = /\(\)$/;
+	
+	/**
+	 * Split string on periods, taking into account escaped periods
+	 * @param  {string} str String to split
+	 * @return {array} Split string
+	 */
+	function _fnSplitObjNotation( str )
+	{
+		return $.map( str.match(/(\\.|[^\.])+/g) || [''], function ( s ) {
+			return s.replace(/\\\./g, '.');
+		} );
+	}
+	
+	
+	/**
+	 * Return a function that can be used to get data from a source object, taking
+	 * into account the ability to use nested objects as a source
+	 *  @param {string|int|function} mSource The data source for the object
+	 *  @returns {function} Data get function
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnGetObjectDataFn( mSource )
+	{
+		if ( $.isPlainObject( mSource ) )
+		{
+			/* Build an object of get functions, and wrap them in a single call */
+			var o = {};
+			$.each( mSource, function (key, val) {
+				if ( val ) {
+					o[key] = _fnGetObjectDataFn( val );
+				}
+			} );
+	
+			return function (data, type, row, meta) {
+				var t = o[type] || o._;
+				return t !== undefined ?
+					t(data, type, row, meta) :
+					data;
+			};
+		}
+		else if ( mSource === null )
+		{
+			/* Give an empty string for rendering / sorting etc */
+			return function (data) { // type, row and meta also passed, but not used
+				return data;
+			};
+		}
+		else if ( typeof mSource === 'function' )
+		{
+			return function (data, type, row, meta) {
+				return mSource( data, type, row, meta );
+			};
+		}
+		else if ( typeof mSource === 'string' && (mSource.indexOf('.') !== -1 ||
+			      mSource.indexOf('[') !== -1 || mSource.indexOf('(') !== -1) )
+		{
+			/* If there is a . in the source string then the data source is in a
+			 * nested object so we loop over the data for each level to get the next
+			 * level down. On each loop we test for undefined, and if found immediately
+			 * return. This allows entire objects to be missing and sDefaultContent to
+			 * be used if defined, rather than throwing an error
+			 */
+			var fetchData = function (data, type, src) {
+				var arrayNotation, funcNotation, out, innerSrc;
+	
+				if ( src !== "" )
+				{
+					var a = _fnSplitObjNotation( src );
+	
+					for ( var i=0, iLen=a.length ; i<iLen ; i++ )
+					{
+						// Check if we are dealing with special notation
+						arrayNotation = a[i].match(__reArray);
+						funcNotation = a[i].match(__reFn);
+	
+						if ( arrayNotation )
+						{
+							// Array notation
+							a[i] = a[i].replace(__reArray, '');
+	
+							// Condition allows simply [] to be passed in
+							if ( a[i] !== "" ) {
+								data = data[ a[i] ];
+							}
+							out = [];
+	
+							// Get the remainder of the nested object to get
+							a.splice( 0, i+1 );
+							innerSrc = a.join('.');
+	
+							// Traverse each entry in the array getting the properties requested
+							if ( $.isArray( data ) ) {
+								for ( var j=0, jLen=data.length ; j<jLen ; j++ ) {
+									out.push( fetchData( data[j], type, innerSrc ) );
+								}
+							}
+	
+							// If a string is given in between the array notation indicators, that
+							// is used to join the strings together, otherwise an array is returned
+							var join = arrayNotation[0].substring(1, arrayNotation[0].length-1);
+							data = (join==="") ? out : out.join(join);
+	
+							// The inner call to fetchData has already traversed through the remainder
+							// of the source requested, so we exit from the loop
+							break;
+						}
+						else if ( funcNotation )
+						{
+							// Function call
+							a[i] = a[i].replace(__reFn, '');
+							data = data[ a[i] ]();
+							continue;
+						}
+	
+						if ( data === null || data[ a[i] ] === undefined )
+						{
+							return undefined;
+						}
+						data = data[ a[i] ];
+					}
+				}
+	
+				return data;
+			};
+	
+			return function (data, type) { // row and meta also passed, but not used
+				return fetchData( data, type, mSource );
+			};
+		}
+		else
+		{
+			/* Array or flat object mapping */
+			return function (data, type) { // row and meta also passed, but not used
+				return data[mSource];
+			};
+		}
+	}
+	
+	
+	/**
+	 * Return a function that can be used to set data from a source object, taking
+	 * into account the ability to use nested objects as a source
+	 *  @param {string|int|function} mSource The data source for the object
+	 *  @returns {function} Data set function
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSetObjectDataFn( mSource )
+	{
+		if ( $.isPlainObject( mSource ) )
+		{
+			/* Unlike get, only the underscore (global) option is used for for
+			 * setting data since we don't know the type here. This is why an object
+			 * option is not documented for `mData` (which is read/write), but it is
+			 * for `mRender` which is read only.
+			 */
+			return _fnSetObjectDataFn( mSource._ );
+		}
+		else if ( mSource === null )
+		{
+			/* Nothing to do when the data source is null */
+			return function () {};
+		}
+		else if ( typeof mSource === 'function' )
+		{
+			return function (data, val, meta) {
+				mSource( data, 'set', val, meta );
+			};
+		}
+		else if ( typeof mSource === 'string' && (mSource.indexOf('.') !== -1 ||
+			      mSource.indexOf('[') !== -1 || mSource.indexOf('(') !== -1) )
+		{
+			/* Like the get, we need to get data from a nested object */
+			var setData = function (data, val, src) {
+				var a = _fnSplitObjNotation( src ), b;
+				var aLast = a[a.length-1];
+				var arrayNotation, funcNotation, o, innerSrc;
+	
+				for ( var i=0, iLen=a.length-1 ; i<iLen ; i++ )
+				{
+					// Check if we are dealing with an array notation request
+					arrayNotation = a[i].match(__reArray);
+					funcNotation = a[i].match(__reFn);
+	
+					if ( arrayNotation )
+					{
+						a[i] = a[i].replace(__reArray, '');
+						data[ a[i] ] = [];
+	
+						// Get the remainder of the nested object to set so we can recurse
+						b = a.slice();
+						b.splice( 0, i+1 );
+						innerSrc = b.join('.');
+	
+						// Traverse each entry in the array setting the properties requested
+						if ( $.isArray( val ) )
+						{
+							for ( var j=0, jLen=val.length ; j<jLen ; j++ )
+							{
+								o = {};
+								setData( o, val[j], innerSrc );
+								data[ a[i] ].push( o );
+							}
+						}
+						else
+						{
+							// We've been asked to save data to an array, but it
+							// isn't array data to be saved. Best that can be done
+							// is to just save the value.
+							data[ a[i] ] = val;
+						}
+	
+						// The inner call to setData has already traversed through the remainder
+						// of the source and has set the data, thus we can exit here
+						return;
+					}
+					else if ( funcNotation )
+					{
+						// Function call
+						a[i] = a[i].replace(__reFn, '');
+						data = data[ a[i] ]( val );
+					}
+	
+					// If the nested object doesn't currently exist - since we are
+					// trying to set the value - create it
+					if ( data[ a[i] ] === null || data[ a[i] ] === undefined )
+					{
+						data[ a[i] ] = {};
+					}
+					data = data[ a[i] ];
+				}
+	
+				// Last item in the input - i.e, the actual set
+				if ( aLast.match(__reFn ) )
+				{
+					// Function call
+					data = data[ aLast.replace(__reFn, '') ]( val );
+				}
+				else
+				{
+					// If array notation is used, we just want to strip it and use the property name
+					// and assign the value. If it isn't used, then we get the result we want anyway
+					data[ aLast.replace(__reArray, '') ] = val;
+				}
+			};
+	
+			return function (data, val) { // meta is also passed in, but not used
+				return setData( data, val, mSource );
+			};
+		}
+		else
+		{
+			/* Array or flat object mapping */
+			return function (data, val) { // meta is also passed in, but not used
+				data[mSource] = val;
+			};
+		}
+	}
+	
+	
+	/**
+	 * Return an array with the full table data
+	 *  @param {object} oSettings dataTables settings object
+	 *  @returns array {array} aData Master data array
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnGetDataMaster ( settings )
+	{
+		return _pluck( settings.aoData, '_aData' );
+	}
+	
+	
+	/**
+	 * Nuke the table
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnClearTable( settings )
+	{
+		settings.aoData.length = 0;
+		settings.aiDisplayMaster.length = 0;
+		settings.aiDisplay.length = 0;
+		settings.aIds = {};
+	}
+	
+	
+	 /**
+	 * Take an array of integers (index array) and remove a target integer (value - not
+	 * the key!)
+	 *  @param {array} a Index array to target
+	 *  @param {int} iTarget value to find
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnDeleteIndex( a, iTarget, splice )
+	{
+		var iTargetIndex = -1;
+	
+		for ( var i=0, iLen=a.length ; i<iLen ; i++ )
+		{
+			if ( a[i] == iTarget )
+			{
+				iTargetIndex = i;
+			}
+			else if ( a[i] > iTarget )
+			{
+				a[i]--;
+			}
+		}
+	
+		if ( iTargetIndex != -1 && splice === undefined )
+		{
+			a.splice( iTargetIndex, 1 );
+		}
+	}
+	
+	
+	/**
+	 * Mark cached data as invalid such that a re-read of the data will occur when
+	 * the cached data is next requested. Also update from the data source object.
+	 *
+	 * @param {object} settings DataTables settings object
+	 * @param {int}    rowIdx   Row index to invalidate
+	 * @param {string} [src]    Source to invalidate from: undefined, 'auto', 'dom'
+	 *     or 'data'
+	 * @param {int}    [colIdx] Column index to invalidate. If undefined the whole
+	 *     row will be invalidated
+	 * @memberof DataTable#oApi
+	 *
+	 * @todo For the modularisation of v1.11 this will need to become a callback, so
+	 *   the sort and filter methods can subscribe to it. That will required
+	 *   initialisation options for sorting, which is why it is not already baked in
+	 */
+	function _fnInvalidate( settings, rowIdx, src, colIdx )
+	{
+		var row = settings.aoData[ rowIdx ];
+		var i, ien;
+		var cellWrite = function ( cell, col ) {
+			// This is very frustrating, but in IE if you just write directly
+			// to innerHTML, and elements that are overwritten are GC'ed,
+			// even if there is a reference to them elsewhere
+			while ( cell.childNodes.length ) {
+				cell.removeChild( cell.firstChild );
+			}
+	
+			cell.innerHTML = _fnGetCellData( settings, rowIdx, col, 'display' );
+		};
+	
+		// Are we reading last data from DOM or the data object?
+		if ( src === 'dom' || ((! src || src === 'auto') && row.src === 'dom') ) {
+			// Read the data from the DOM
+			row._aData = _fnGetRowElements(
+					settings, row, colIdx, colIdx === undefined ? undefined : row._aData
+				)
+				.data;
+		}
+		else {
+			// Reading from data object, update the DOM
+			var cells = row.anCells;
+	
+			if ( cells ) {
+				if ( colIdx !== undefined ) {
+					cellWrite( cells[colIdx], colIdx );
+				}
+				else {
+					for ( i=0, ien=cells.length ; i<ien ; i++ ) {
+						cellWrite( cells[i], i );
+					}
+				}
+			}
+		}
+	
+		// For both row and cell invalidation, the cached data for sorting and
+		// filtering is nulled out
+		row._aSortData = null;
+		row._aFilterData = null;
+	
+		// Invalidate the type for a specific column (if given) or all columns since
+		// the data might have changed
+		var cols = settings.aoColumns;
+		if ( colIdx !== undefined ) {
+			cols[ colIdx ].sType = null;
+		}
+		else {
+			for ( i=0, ien=cols.length ; i<ien ; i++ ) {
+				cols[i].sType = null;
+			}
+	
+			// Update DataTables special `DT_*` attributes for the row
+			_fnRowAttributes( settings, row );
+		}
+	}
+	
+	
+	/**
+	 * Build a data source object from an HTML row, reading the contents of the
+	 * cells that are in the row.
+	 *
+	 * @param {object} settings DataTables settings object
+	 * @param {node|object} TR element from which to read data or existing row
+	 *   object from which to re-read the data from the cells
+	 * @param {int} [colIdx] Optional column index
+	 * @param {array|object} [d] Data source object. If `colIdx` is given then this
+	 *   parameter should also be given and will be used to write the data into.
+	 *   Only the column in question will be written
+	 * @returns {object} Object with two parameters: `data` the data read, in
+	 *   document order, and `cells` and array of nodes (they can be useful to the
+	 *   caller, so rather than needing a second traversal to get them, just return
+	 *   them from here).
+	 * @memberof DataTable#oApi
+	 */
+	function _fnGetRowElements( settings, row, colIdx, d )
+	{
+		var
+			tds = [],
+			td = row.firstChild,
+			name, col, o, i=0, contents,
+			columns = settings.aoColumns,
+			objectRead = settings._rowReadObject;
+	
+		// Allow the data object to be passed in, or construct
+		d = d !== undefined ?
+			d :
+			objectRead ?
+				{} :
+				[];
+	
+		var attr = function ( str, td  ) {
+			if ( typeof str === 'string' ) {
+				var idx = str.indexOf('@');
+	
+				if ( idx !== -1 ) {
+					var attr = str.substring( idx+1 );
+					var setter = _fnSetObjectDataFn( str );
+					setter( d, td.getAttribute( attr ) );
+				}
+			}
+		};
+	
+		// Read data from a cell and store into the data object
+		var cellProcess = function ( cell ) {
+			if ( colIdx === undefined || colIdx === i ) {
+				col = columns[i];
+				contents = $.trim(cell.innerHTML);
+	
+				if ( col && col._bAttrSrc ) {
+					var setter = _fnSetObjectDataFn( col.mData._ );
+					setter( d, contents );
+	
+					attr( col.mData.sort, cell );
+					attr( col.mData.type, cell );
+					attr( col.mData.filter, cell );
+				}
+				else {
+					// Depending on the `data` option for the columns the data can
+					// be read to either an object or an array.
+					if ( objectRead ) {
+						if ( ! col._setter ) {
+							// Cache the setter function
+							col._setter = _fnSetObjectDataFn( col.mData );
+						}
+						col._setter( d, contents );
+					}
+					else {
+						d[i] = contents;
+					}
+				}
+			}
+	
+			i++;
+		};
+	
+		if ( td ) {
+			// `tr` element was passed in
+			while ( td ) {
+				name = td.nodeName.toUpperCase();
+	
+				if ( name == "TD" || name == "TH" ) {
+					cellProcess( td );
+					tds.push( td );
+				}
+	
+				td = td.nextSibling;
+			}
+		}
+		else {
+			// Existing row object passed in
+			tds = row.anCells;
+	
+			for ( var j=0, jen=tds.length ; j<jen ; j++ ) {
+				cellProcess( tds[j] );
+			}
+		}
+	
+		// Read the ID from the DOM if present
+		var rowNode = row.firstChild ? row : row.nTr;
+	
+		if ( rowNode ) {
+			var id = rowNode.getAttribute( 'id' );
+	
+			if ( id ) {
+				_fnSetObjectDataFn( settings.rowId )( d, id );
+			}
+		}
+	
+		return {
+			data: d,
+			cells: tds
+		};
+	}
+	/**
+	 * Create a new TR element (and it's TD children) for a row
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {int} iRow Row to consider
+	 *  @param {node} [nTrIn] TR element to add to the table - optional. If not given,
+	 *    DataTables will create a row automatically
+	 *  @param {array} [anTds] Array of TD|TH elements for the row - must be given
+	 *    if nTr is.
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnCreateTr ( oSettings, iRow, nTrIn, anTds )
+	{
+		var
+			row = oSettings.aoData[iRow],
+			rowData = row._aData,
+			cells = [],
+			nTr, nTd, oCol,
+			i, iLen;
+	
+		if ( row.nTr === null )
+		{
+			nTr = nTrIn || document.createElement('tr');
+	
+			row.nTr = nTr;
+			row.anCells = cells;
+	
+			/* Use a private property on the node to allow reserve mapping from the node
+			 * to the aoData array for fast look up
+			 */
+			nTr._DT_RowIndex = iRow;
+	
+			/* Special parameters can be given by the data source to be used on the row */
+			_fnRowAttributes( oSettings, row );
+	
+			/* Process each column */
+			for ( i=0, iLen=oSettings.aoColumns.length ; i<iLen ; i++ )
+			{
+				oCol = oSettings.aoColumns[i];
+	
+				nTd = nTrIn ? anTds[i] : document.createElement( oCol.sCellType );
+				nTd._DT_CellIndex = {
+					row: iRow,
+					column: i
+				};
+				
+				cells.push( nTd );
+	
+				// Need to create the HTML if new, or if a rendering function is defined
+				if ( (!nTrIn || oCol.mRender || oCol.mData !== i) &&
+					 (!$.isPlainObject(oCol.mData) || oCol.mData._ !== i+'.display')
+				) {
+					nTd.innerHTML = _fnGetCellData( oSettings, iRow, i, 'display' );
+				}
+	
+				/* Add user defined class */
+				if ( oCol.sClass )
+				{
+					nTd.className += ' '+oCol.sClass;
+				}
+	
+				// Visibility - add or remove as required
+				if ( oCol.bVisible && ! nTrIn )
+				{
+					nTr.appendChild( nTd );
+				}
+				else if ( ! oCol.bVisible && nTrIn )
+				{
+					nTd.parentNode.removeChild( nTd );
+				}
+	
+				if ( oCol.fnCreatedCell )
+				{
+					oCol.fnCreatedCell.call( oSettings.oInstance,
+						nTd, _fnGetCellData( oSettings, iRow, i ), rowData, iRow, i
+					);
+				}
+			}
+	
+			_fnCallbackFire( oSettings, 'aoRowCreatedCallback', null, [nTr, rowData, iRow] );
+		}
+	
+		// Remove once webkit bug 131819 and Chromium bug 365619 have been resolved
+		// and deployed
+		row.nTr.setAttribute( 'role', 'row' );
+	}
+	
+	
+	/**
+	 * Add attributes to a row based on the special `DT_*` parameters in a data
+	 * source object.
+	 *  @param {object} settings DataTables settings object
+	 *  @param {object} DataTables row object for the row to be modified
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnRowAttributes( settings, row )
+	{
+		var tr = row.nTr;
+		var data = row._aData;
+	
+		if ( tr ) {
+			var id = settings.rowIdFn( data );
+	
+			if ( id ) {
+				tr.id = id;
+			}
+	
+			if ( data.DT_RowClass ) {
+				// Remove any classes added by DT_RowClass before
+				var a = data.DT_RowClass.split(' ');
+				row.__rowc = row.__rowc ?
+					_unique( row.__rowc.concat( a ) ) :
+					a;
+	
+				$(tr)
+					.removeClass( row.__rowc.join(' ') )
+					.addClass( data.DT_RowClass );
+			}
+	
+			if ( data.DT_RowAttr ) {
+				$(tr).attr( data.DT_RowAttr );
+			}
+	
+			if ( data.DT_RowData ) {
+				$(tr).data( data.DT_RowData );
+			}
+		}
+	}
+	
+	
+	/**
+	 * Create the HTML header for the table
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnBuildHead( oSettings )
+	{
+		var i, ien, cell, row, column;
+		var thead = oSettings.nTHead;
+		var tfoot = oSettings.nTFoot;
+		var createHeader = $('th, td', thead).length === 0;
+		var classes = oSettings.oClasses;
+		var columns = oSettings.aoColumns;
+	
+		if ( createHeader ) {
+			row = $('<tr/>').appendTo( thead );
+		}
+	
+		for ( i=0, ien=columns.length ; i<ien ; i++ ) {
+			column = columns[i];
+			cell = $( column.nTh ).addClass( column.sClass );
+	
+			if ( createHeader ) {
+				cell.appendTo( row );
+			}
+	
+			// 1.11 move into sorting
+			if ( oSettings.oFeatures.bSort ) {
+				cell.addClass( column.sSortingClass );
+	
+				if ( column.bSortable !== false ) {
+					cell
+						.attr( 'tabindex', oSettings.iTabIndex )
+						.attr( 'aria-controls', oSettings.sTableId );
+	
+					_fnSortAttachListener( oSettings, column.nTh, i );
+				}
+			}
+	
+			if ( column.sTitle != cell[0].innerHTML ) {
+				cell.html( column.sTitle );
+			}
+	
+			_fnRenderer( oSettings, 'header' )(
+				oSettings, cell, column, classes
+			);
+		}
+	
+		if ( createHeader ) {
+			_fnDetectHeader( oSettings.aoHeader, thead );
+		}
+		
+		/* ARIA role for the rows */
+	 	$(thead).find('>tr').attr('role', 'row');
+	
+		/* Deal with the footer - add classes if required */
+		$(thead).find('>tr>th, >tr>td').addClass( classes.sHeaderTH );
+		$(tfoot).find('>tr>th, >tr>td').addClass( classes.sFooterTH );
+	
+		// Cache the footer cells. Note that we only take the cells from the first
+		// row in the footer. If there is more than one row the user wants to
+		// interact with, they need to use the table().foot() method. Note also this
+		// allows cells to be used for multiple columns using colspan
+		if ( tfoot !== null ) {
+			var cells = oSettings.aoFooter[0];
+	
+			for ( i=0, ien=cells.length ; i<ien ; i++ ) {
+				column = columns[i];
+				column.nTf = cells[i].cell;
+	
+				if ( column.sClass ) {
+					$(column.nTf).addClass( column.sClass );
+				}
+			}
+		}
+	}
+	
+	
+	/**
+	 * Draw the header (or footer) element based on the column visibility states. The
+	 * methodology here is to use the layout array from _fnDetectHeader, modified for
+	 * the instantaneous column visibility, to construct the new layout. The grid is
+	 * traversed over cell at a time in a rows x columns grid fashion, although each
+	 * cell insert can cover multiple elements in the grid - which is tracks using the
+	 * aApplied array. Cell inserts in the grid will only occur where there isn't
+	 * already a cell in that position.
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param array {objects} aoSource Layout array from _fnDetectHeader
+	 *  @param {boolean} [bIncludeHidden=false] If true then include the hidden columns in the calc,
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnDrawHead( oSettings, aoSource, bIncludeHidden )
+	{
+		var i, iLen, j, jLen, k, kLen, n, nLocalTr;
+		var aoLocal = [];
+		var aApplied = [];
+		var iColumns = oSettings.aoColumns.length;
+		var iRowspan, iColspan;
+	
+		if ( ! aoSource )
+		{
+			return;
+		}
+	
+		if (  bIncludeHidden === undefined )
+		{
+			bIncludeHidden = false;
+		}
+	
+		/* Make a copy of the master layout array, but without the visible columns in it */
+		for ( i=0, iLen=aoSource.length ; i<iLen ; i++ )
+		{
+			aoLocal[i] = aoSource[i].slice();
+			aoLocal[i].nTr = aoSource[i].nTr;
+	
+			/* Remove any columns which are currently hidden */
+			for ( j=iColumns-1 ; j>=0 ; j-- )
+			{
+				if ( !oSettings.aoColumns[j].bVisible && !bIncludeHidden )
+				{
+					aoLocal[i].splice( j, 1 );
+				}
+			}
+	
+			/* Prep the applied array - it needs an element for each row */
+			aApplied.push( [] );
+		}
+	
+		for ( i=0, iLen=aoLocal.length ; i<iLen ; i++ )
+		{
+			nLocalTr = aoLocal[i].nTr;
+	
+			/* All cells are going to be replaced, so empty out the row */
+			if ( nLocalTr )
+			{
+				while( (n = nLocalTr.firstChild) )
+				{
+					nLocalTr.removeChild( n );
+				}
+			}
+	
+			for ( j=0, jLen=aoLocal[i].length ; j<jLen ; j++ )
+			{
+				iRowspan = 1;
+				iColspan = 1;
+	
+				/* Check to see if there is already a cell (row/colspan) covering our target
+				 * insert point. If there is, then there is nothing to do.
+				 */
+				if ( aApplied[i][j] === undefined )
+				{
+					nLocalTr.appendChild( aoLocal[i][j].cell );
+					aApplied[i][j] = 1;
+	
+					/* Expand the cell to cover as many rows as needed */
+					while ( aoLocal[i+iRowspan] !== undefined &&
+					        aoLocal[i][j].cell == aoLocal[i+iRowspan][j].cell )
+					{
+						aApplied[i+iRowspan][j] = 1;
+						iRowspan++;
+					}
+	
+					/* Expand the cell to cover as many columns as needed */
+					while ( aoLocal[i][j+iColspan] !== undefined &&
+					        aoLocal[i][j].cell == aoLocal[i][j+iColspan].cell )
+					{
+						/* Must update the applied array over the rows for the columns */
+						for ( k=0 ; k<iRowspan ; k++ )
+						{
+							aApplied[i+k][j+iColspan] = 1;
+						}
+						iColspan++;
+					}
+	
+					/* Do the actual expansion in the DOM */
+					$(aoLocal[i][j].cell)
+						.attr('rowspan', iRowspan)
+						.attr('colspan', iColspan);
+				}
+			}
+		}
+	}
+	
+	
+	/**
+	 * Insert the required TR nodes into the table for display
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnDraw( oSettings )
+	{
+		/* Provide a pre-callback function which can be used to cancel the draw is false is returned */
+		var aPreDraw = _fnCallbackFire( oSettings, 'aoPreDrawCallback', 'preDraw', [oSettings] );
+		if ( $.inArray( false, aPreDraw ) !== -1 )
+		{
+			_fnProcessingDisplay( oSettings, false );
+			return;
+		}
+	
+		var i, iLen, n;
+		var anRows = [];
+		var iRowCount = 0;
+		var asStripeClasses = oSettings.asStripeClasses;
+		var iStripes = asStripeClasses.length;
+		var iOpenRows = oSettings.aoOpenRows.length;
+		var oLang = oSettings.oLanguage;
+		var iInitDisplayStart = oSettings.iInitDisplayStart;
+		var bServerSide = _fnDataSource( oSettings ) == 'ssp';
+		var aiDisplay = oSettings.aiDisplay;
+	
+		oSettings.bDrawing = true;
+	
+		/* Check and see if we have an initial draw position from state saving */
+		if ( iInitDisplayStart !== undefined && iInitDisplayStart !== -1 )
+		{
+			oSettings._iDisplayStart = bServerSide ?
+				iInitDisplayStart :
+				iInitDisplayStart >= oSettings.fnRecordsDisplay() ?
+					0 :
+					iInitDisplayStart;
+	
+			oSettings.iInitDisplayStart = -1;
+		}
+	
+		var iDisplayStart = oSettings._iDisplayStart;
+		var iDisplayEnd = oSettings.fnDisplayEnd();
+	
+		/* Server-side processing draw intercept */
+		if ( oSettings.bDeferLoading )
+		{
+			oSettings.bDeferLoading = false;
+			oSettings.iDraw++;
+			_fnProcessingDisplay( oSettings, false );
+		}
+		else if ( !bServerSide )
+		{
+			oSettings.iDraw++;
+		}
+		else if ( !oSettings.bDestroying && !_fnAjaxUpdate( oSettings ) )
+		{
+			return;
+		}
+	
+		if ( aiDisplay.length !== 0 )
+		{
+			var iStart = bServerSide ? 0 : iDisplayStart;
+			var iEnd = bServerSide ? oSettings.aoData.length : iDisplayEnd;
+	
+			for ( var j=iStart ; j<iEnd ; j++ )
+			{
+				var iDataIndex = aiDisplay[j];
+				var aoData = oSettings.aoData[ iDataIndex ];
+				if ( aoData.nTr === null )
+				{
+					_fnCreateTr( oSettings, iDataIndex );
+				}
+	
+				var nRow = aoData.nTr;
+	
+				/* Remove the old striping classes and then add the new one */
+				if ( iStripes !== 0 )
+				{
+					var sStripe = asStripeClasses[ iRowCount % iStripes ];
+					if ( aoData._sRowStripe != sStripe )
+					{
+						$(nRow).removeClass( aoData._sRowStripe ).addClass( sStripe );
+						aoData._sRowStripe = sStripe;
+					}
+				}
+	
+				// Row callback functions - might want to manipulate the row
+				// iRowCount and j are not currently documented. Are they at all
+				// useful?
+				_fnCallbackFire( oSettings, 'aoRowCallback', null,
+					[nRow, aoData._aData, iRowCount, j] );
+	
+				anRows.push( nRow );
+				iRowCount++;
+			}
+		}
+		else
+		{
+			/* Table is empty - create a row with an empty message in it */
+			var sZero = oLang.sZeroRecords;
+			if ( oSettings.iDraw == 1 &&  _fnDataSource( oSettings ) == 'ajax' )
+			{
+				sZero = oLang.sLoadingRecords;
+			}
+			else if ( oLang.sEmptyTable && oSettings.fnRecordsTotal() === 0 )
+			{
+				sZero = oLang.sEmptyTable;
+			}
+	
+			anRows[ 0 ] = $( '<tr/>', { 'class': iStripes ? asStripeClasses[0] : '' } )
+				.append( $('<td />', {
+					'valign':  'top',
+					'colSpan': _fnVisbleColumns( oSettings ),
+					'class':   oSettings.oClasses.sRowEmpty
+				} ).html( sZero ) )[0];
+		}
+	
+		/* Header and footer callbacks */
+		_fnCallbackFire( oSettings, 'aoHeaderCallback', 'header', [ $(oSettings.nTHead).children('tr')[0],
+			_fnGetDataMaster( oSettings ), iDisplayStart, iDisplayEnd, aiDisplay ] );
+	
+		_fnCallbackFire( oSettings, 'aoFooterCallback', 'footer', [ $(oSettings.nTFoot).children('tr')[0],
+			_fnGetDataMaster( oSettings ), iDisplayStart, iDisplayEnd, aiDisplay ] );
+	
+		var body = $(oSettings.nTBody);
+	
+		body.children().detach();
+		body.append( $(anRows) );
+	
+		/* Call all required callback functions for the end of a draw */
+		_fnCallbackFire( oSettings, 'aoDrawCallback', 'draw', [oSettings] );
+	
+		/* Draw is complete, sorting and filtering must be as well */
+		oSettings.bSorted = false;
+		oSettings.bFiltered = false;
+		oSettings.bDrawing = false;
+	}
+	
+	
+	/**
+	 * Redraw the table - taking account of the various features which are enabled
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {boolean} [holdPosition] Keep the current paging position. By default
+	 *    the paging is reset to the first page
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnReDraw( settings, holdPosition )
+	{
+		var
+			features = settings.oFeatures,
+			sort     = features.bSort,
+			filter   = features.bFilter;
+	
+		if ( sort ) {
+			_fnSort( settings );
+		}
+	
+		if ( filter ) {
+			_fnFilterComplete( settings, settings.oPreviousSearch );
+		}
+		else {
+			// No filtering, so we want to just use the display master
+			settings.aiDisplay = settings.aiDisplayMaster.slice();
+		}
+	
+		if ( holdPosition !== true ) {
+			settings._iDisplayStart = 0;
+		}
+	
+		// Let any modules know about the draw hold position state (used by
+		// scrolling internally)
+		settings._drawHold = holdPosition;
+	
+		_fnDraw( settings );
+	
+		settings._drawHold = false;
+	}
+	
+	
+	/**
+	 * Add the options to the page HTML for the table
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnAddOptionsHtml ( oSettings )
+	{
+		var classes = oSettings.oClasses;
+		var table = $(oSettings.nTable);
+		var holding = $('<div/>').insertBefore( table ); // Holding element for speed
+		var features = oSettings.oFeatures;
+	
+		// All DataTables are wrapped in a div
+		var insert = $('<div/>', {
+			id:      oSettings.sTableId+'_wrapper',
+			'class': classes.sWrapper + (oSettings.nTFoot ? '' : ' '+classes.sNoFooter)
+		} );
+	
+		oSettings.nHolding = holding[0];
+		oSettings.nTableWrapper = insert[0];
+		oSettings.nTableReinsertBefore = oSettings.nTable.nextSibling;
+	
+		/* Loop over the user set positioning and place the elements as needed */
+		var aDom = oSettings.sDom.split('');
+		var featureNode, cOption, nNewNode, cNext, sAttr, j;
+		for ( var i=0 ; i<aDom.length ; i++ )
+		{
+			featureNode = null;
+			cOption = aDom[i];
+	
+			if ( cOption == '<' )
+			{
+				/* New container div */
+				nNewNode = $('<div/>')[0];
+	
+				/* Check to see if we should append an id and/or a class name to the container */
+				cNext = aDom[i+1];
+				if ( cNext == "'" || cNext == '"' )
+				{
+					sAttr = "";
+					j = 2;
+					while ( aDom[i+j] != cNext )
+					{
+						sAttr += aDom[i+j];
+						j++;
+					}
+	
+					/* Replace jQuery UI constants @todo depreciated */
+					if ( sAttr == "H" )
+					{
+						sAttr = classes.sJUIHeader;
+					}
+					else if ( sAttr == "F" )
+					{
+						sAttr = classes.sJUIFooter;
+					}
+	
+					/* The attribute can be in the format of "#id.class", "#id" or "class" This logic
+					 * breaks the string into parts and applies them as needed
+					 */
+					if ( sAttr.indexOf('.') != -1 )
+					{
+						var aSplit = sAttr.split('.');
+						nNewNode.id = aSplit[0].substr(1, aSplit[0].length-1);
+						nNewNode.className = aSplit[1];
+					}
+					else if ( sAttr.charAt(0) == "#" )
+					{
+						nNewNode.id = sAttr.substr(1, sAttr.length-1);
+					}
+					else
+					{
+						nNewNode.className = sAttr;
+					}
+	
+					i += j; /* Move along the position array */
+				}
+	
+				insert.append( nNewNode );
+				insert = $(nNewNode);
+			}
+			else if ( cOption == '>' )
+			{
+				/* End container div */
+				insert = insert.parent();
+			}
+			// @todo Move options into their own plugins?
+			else if ( cOption == 'l' && features.bPaginate && features.bLengthChange )
+			{
+				/* Length */
+				featureNode = _fnFeatureHtmlLength( oSettings );
+			}
+			else if ( cOption == 'f' && features.bFilter )
+			{
+				/* Filter */
+				featureNode = _fnFeatureHtmlFilter( oSettings );
+			}
+			else if ( cOption == 'r' && features.bProcessing )
+			{
+				/* pRocessing */
+				featureNode = _fnFeatureHtmlProcessing( oSettings );
+			}
+			else if ( cOption == 't' )
+			{
+				/* Table */
+				featureNode = _fnFeatureHtmlTable( oSettings );
+			}
+			else if ( cOption ==  'i' && features.bInfo )
+			{
+				/* Info */
+				featureNode = _fnFeatureHtmlInfo( oSettings );
+			}
+			else if ( cOption == 'p' && features.bPaginate )
+			{
+				/* Pagination */
+				featureNode = _fnFeatureHtmlPaginate( oSettings );
+			}
+			else if ( DataTable.ext.feature.length !== 0 )
+			{
+				/* Plug-in features */
+				var aoFeatures = DataTable.ext.feature;
+				for ( var k=0, kLen=aoFeatures.length ; k<kLen ; k++ )
+				{
+					if ( cOption == aoFeatures[k].cFeature )
+					{
+						featureNode = aoFeatures[k].fnInit( oSettings );
+						break;
+					}
+				}
+			}
+	
+			/* Add to the 2D features array */
+			if ( featureNode )
+			{
+				var aanFeatures = oSettings.aanFeatures;
+	
+				if ( ! aanFeatures[cOption] )
+				{
+					aanFeatures[cOption] = [];
+				}
+	
+				aanFeatures[cOption].push( featureNode );
+				insert.append( featureNode );
+			}
+		}
+	
+		/* Built our DOM structure - replace the holding div with what we want */
+		holding.replaceWith( insert );
+		oSettings.nHolding = null;
+	}
+	
+	
+	/**
+	 * Use the DOM source to create up an array of header cells. The idea here is to
+	 * create a layout grid (array) of rows x columns, which contains a reference
+	 * to the cell that that point in the grid (regardless of col/rowspan), such that
+	 * any column / row could be removed and the new grid constructed
+	 *  @param array {object} aLayout Array to store the calculated layout in
+	 *  @param {node} nThead The header/footer element for the table
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnDetectHeader ( aLayout, nThead )
+	{
+		var nTrs = $(nThead).children('tr');
+		var nTr, nCell;
+		var i, k, l, iLen, jLen, iColShifted, iColumn, iColspan, iRowspan;
+		var bUnique;
+		var fnShiftCol = function ( a, i, j ) {
+			var k = a[i];
+	                while ( k[j] ) {
+				j++;
+			}
+			return j;
+		};
+	
+		aLayout.splice( 0, aLayout.length );
+	
+		/* We know how many rows there are in the layout - so prep it */
+		for ( i=0, iLen=nTrs.length ; i<iLen ; i++ )
+		{
+			aLayout.push( [] );
+		}
+	
+		/* Calculate a layout array */
+		for ( i=0, iLen=nTrs.length ; i<iLen ; i++ )
+		{
+			nTr = nTrs[i];
+			iColumn = 0;
+	
+			/* For every cell in the row... */
+			nCell = nTr.firstChild;
+			while ( nCell ) {
+				if ( nCell.nodeName.toUpperCase() == "TD" ||
+				     nCell.nodeName.toUpperCase() == "TH" )
+				{
+					/* Get the col and rowspan attributes from the DOM and sanitise them */
+					iColspan = nCell.getAttribute('colspan') * 1;
+					iRowspan = nCell.getAttribute('rowspan') * 1;
+					iColspan = (!iColspan || iColspan===0 || iColspan===1) ? 1 : iColspan;
+					iRowspan = (!iRowspan || iRowspan===0 || iRowspan===1) ? 1 : iRowspan;
+	
+					/* There might be colspan cells already in this row, so shift our target
+					 * accordingly
+					 */
+					iColShifted = fnShiftCol( aLayout, i, iColumn );
+	
+					/* Cache calculation for unique columns */
+					bUnique = iColspan === 1 ? true : false;
+	
+					/* If there is col / rowspan, copy the information into the layout grid */
+					for ( l=0 ; l<iColspan ; l++ )
+					{
+						for ( k=0 ; k<iRowspan ; k++ )
+						{
+							aLayout[i+k][iColShifted+l] = {
+								"cell": nCell,
+								"unique": bUnique
+							};
+							aLayout[i+k].nTr = nTr;
+						}
+					}
+				}
+				nCell = nCell.nextSibling;
+			}
+		}
+	}
+	
+	
+	/**
+	 * Get an array of unique th elements, one for each column
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {node} nHeader automatically detect the layout from this node - optional
+	 *  @param {array} aLayout thead/tfoot layout from _fnDetectHeader - optional
+	 *  @returns array {node} aReturn list of unique th's
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnGetUniqueThs ( oSettings, nHeader, aLayout )
+	{
+		var aReturn = [];
+		if ( !aLayout )
+		{
+			aLayout = oSettings.aoHeader;
+			if ( nHeader )
+			{
+				aLayout = [];
+				_fnDetectHeader( aLayout, nHeader );
+			}
+		}
+	
+		for ( var i=0, iLen=aLayout.length ; i<iLen ; i++ )
+		{
+			for ( var j=0, jLen=aLayout[i].length ; j<jLen ; j++ )
+			{
+				if ( aLayout[i][j].unique &&
+					 (!aReturn[j] || !oSettings.bSortCellsTop) )
+				{
+					aReturn[j] = aLayout[i][j].cell;
+				}
+			}
+		}
+	
+		return aReturn;
+	}
+	
+	/**
+	 * Create an Ajax call based on the table's settings, taking into account that
+	 * parameters can have multiple forms, and backwards compatibility.
+	 *
+	 * @param {object} oSettings dataTables settings object
+	 * @param {array} data Data to send to the server, required by
+	 *     DataTables - may be augmented by developer callbacks
+	 * @param {function} fn Callback function to run when data is obtained
+	 */
+	function _fnBuildAjax( oSettings, data, fn )
+	{
+		// Compatibility with 1.9-, allow fnServerData and event to manipulate
+		_fnCallbackFire( oSettings, 'aoServerParams', 'serverParams', [data] );
+	
+		// Convert to object based for 1.10+ if using the old array scheme which can
+		// come from server-side processing or serverParams
+		if ( data && $.isArray(data) ) {
+			var tmp = {};
+			var rbracket = /(.*?)\[\]$/;
+	
+			$.each( data, function (key, val) {
+				var match = val.name.match(rbracket);
+	
+				if ( match ) {
+					// Support for arrays
+					var name = match[0];
+	
+					if ( ! tmp[ name ] ) {
+						tmp[ name ] = [];
+					}
+					tmp[ name ].push( val.value );
+				}
+				else {
+					tmp[val.name] = val.value;
+				}
+			} );
+			data = tmp;
+		}
+	
+		var ajaxData;
+		var ajax = oSettings.ajax;
+		var instance = oSettings.oInstance;
+		var callback = function ( json ) {
+			_fnCallbackFire( oSettings, null, 'xhr', [oSettings, json, oSettings.jqXHR] );
+			fn( json );
+		};
+	
+		if ( $.isPlainObject( ajax ) && ajax.data )
+		{
+			ajaxData = ajax.data;
+	
+			var newData = $.isFunction( ajaxData ) ?
+				ajaxData( data, oSettings ) :  // fn can manipulate data or return
+				ajaxData;                      // an object object or array to merge
+	
+			// If the function returned something, use that alone
+			data = $.isFunction( ajaxData ) && newData ?
+				newData :
+				$.extend( true, data, newData );
+	
+			// Remove the data property as we've resolved it already and don't want
+			// jQuery to do it again (it is restored at the end of the function)
+			delete ajax.data;
+		}
+	
+		var baseAjax = {
+			"data": data,
+			"success": function (json) {
+				var error = json.error || json.sError;
+				if ( error ) {
+					_fnLog( oSettings, 0, error );
+				}
+	
+				oSettings.json = json;
+				callback( json );
+			},
+			"dataType": "json",
+			"cache": false,
+			"type": oSettings.sServerMethod,
+			"error": function (xhr, error, thrown) {
+				var ret = _fnCallbackFire( oSettings, null, 'xhr', [oSettings, null, oSettings.jqXHR] );
+	
+				if ( $.inArray( true, ret ) === -1 ) {
+					if ( error == "parsererror" ) {
+						_fnLog( oSettings, 0, 'Invalid JSON response', 1 );
+					}
+					else if ( xhr.readyState === 4 ) {
+						_fnLog( oSettings, 0, 'Ajax error', 7 );
+					}
+				}
+	
+				_fnProcessingDisplay( oSettings, false );
+			}
+		};
+	
+		// Store the data submitted for the API
+		oSettings.oAjaxData = data;
+	
+		// Allow plug-ins and external processes to modify the data
+		_fnCallbackFire( oSettings, null, 'preXhr', [oSettings, data] );
+	
+		if ( oSettings.fnServerData )
+		{
+			// DataTables 1.9- compatibility
+			oSettings.fnServerData.call( instance,
+				oSettings.sAjaxSource,
+				$.map( data, function (val, key) { // Need to convert back to 1.9 trad format
+					return { name: key, value: val };
+				} ),
+				callback,
+				oSettings
+			);
+		}
+		else if ( oSettings.sAjaxSource || typeof ajax === 'string' )
+		{
+			// DataTables 1.9- compatibility
+			oSettings.jqXHR = $.ajax( $.extend( baseAjax, {
+				url: ajax || oSettings.sAjaxSource
+			} ) );
+		}
+		else if ( $.isFunction( ajax ) )
+		{
+			// Is a function - let the caller define what needs to be done
+			oSettings.jqXHR = ajax.call( instance, data, callback, oSettings );
+		}
+		else
+		{
+			// Object to extend the base settings
+			oSettings.jqXHR = $.ajax( $.extend( baseAjax, ajax ) );
+	
+			// Restore for next time around
+			ajax.data = ajaxData;
+		}
+	}
+	
+	
+	/**
+	 * Update the table using an Ajax call
+	 *  @param {object} settings dataTables settings object
+	 *  @returns {boolean} Block the table drawing or not
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnAjaxUpdate( settings )
+	{
+		if ( settings.bAjaxDataGet ) {
+			settings.iDraw++;
+			_fnProcessingDisplay( settings, true );
+	
+			_fnBuildAjax(
+				settings,
+				_fnAjaxParameters( settings ),
+				function(json) {
+					_fnAjaxUpdateDraw( settings, json );
+				}
+			);
+	
+			return false;
+		}
+		return true;
+	}
+	
+	
+	/**
+	 * Build up the parameters in an object needed for a server-side processing
+	 * request. Note that this is basically done twice, is different ways - a modern
+	 * method which is used by default in DataTables 1.10 which uses objects and
+	 * arrays, or the 1.9- method with is name / value pairs. 1.9 method is used if
+	 * the sAjaxSource option is used in the initialisation, or the legacyAjax
+	 * option is set.
+	 *  @param {object} oSettings dataTables settings object
+	 *  @returns {bool} block the table drawing or not
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnAjaxParameters( settings )
+	{
+		var
+			columns = settings.aoColumns,
+			columnCount = columns.length,
+			features = settings.oFeatures,
+			preSearch = settings.oPreviousSearch,
+			preColSearch = settings.aoPreSearchCols,
+			i, data = [], dataProp, column, columnSearch,
+			sort = _fnSortFlatten( settings ),
+			displayStart = settings._iDisplayStart,
+			displayLength = features.bPaginate !== false ?
+				settings._iDisplayLength :
+				-1;
+	
+		var param = function ( name, value ) {
+			data.push( { 'name': name, 'value': value } );
+		};
+	
+		// DataTables 1.9- compatible method
+		param( 'sEcho',          settings.iDraw );
+		param( 'iColumns',       columnCount );
+		param( 'sColumns',       _pluck( columns, 'sName' ).join(',') );
+		param( 'iDisplayStart',  displayStart );
+		param( 'iDisplayLength', displayLength );
+	
+		// DataTables 1.10+ method
+		var d = {
+			draw:    settings.iDraw,
+			columns: [],
+			order:   [],
+			start:   displayStart,
+			length:  displayLength,
+			search:  {
+				value: preSearch.sSearch,
+				regex: preSearch.bRegex
+			}
+		};
+	
+		for ( i=0 ; i<columnCount ; i++ ) {
+			column = columns[i];
+			columnSearch = preColSearch[i];
+			dataProp = typeof column.mData=="function" ? 'function' : column.mData ;
+	
+			d.columns.push( {
+				data:       dataProp,
+				name:       column.sName,
+				searchable: column.bSearchable,
+				orderable:  column.bSortable,
+				search:     {
+					value: columnSearch.sSearch,
+					regex: columnSearch.bRegex
+				}
+			} );
+	
+			param( "mDataProp_"+i, dataProp );
+	
+			if ( features.bFilter ) {
+				param( 'sSearch_'+i,     columnSearch.sSearch );
+				param( 'bRegex_'+i,      columnSearch.bRegex );
+				param( 'bSearchable_'+i, column.bSearchable );
+			}
+	
+			if ( features.bSort ) {
+				param( 'bSortable_'+i, column.bSortable );
+			}
+		}
+	
+		if ( features.bFilter ) {
+			param( 'sSearch', preSearch.sSearch );
+			param( 'bRegex', preSearch.bRegex );
+		}
+	
+		if ( features.bSort ) {
+			$.each( sort, function ( i, val ) {
+				d.order.push( { column: val.col, dir: val.dir } );
+	
+				param( 'iSortCol_'+i, val.col );
+				param( 'sSortDir_'+i, val.dir );
+			} );
+	
+			param( 'iSortingCols', sort.length );
+		}
+	
+		// If the legacy.ajax parameter is null, then we automatically decide which
+		// form to use, based on sAjaxSource
+		var legacy = DataTable.ext.legacy.ajax;
+		if ( legacy === null ) {
+			return settings.sAjaxSource ? data : d;
+		}
+	
+		// Otherwise, if legacy has been specified then we use that to decide on the
+		// form
+		return legacy ? data : d;
+	}
+	
+	
+	/**
+	 * Data the data from the server (nuking the old) and redraw the table
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {object} json json data return from the server.
+	 *  @param {string} json.sEcho Tracking flag for DataTables to match requests
+	 *  @param {int} json.iTotalRecords Number of records in the data set, not accounting for filtering
+	 *  @param {int} json.iTotalDisplayRecords Number of records in the data set, accounting for filtering
+	 *  @param {array} json.aaData The data to display on this page
+	 *  @param {string} [json.sColumns] Column ordering (sName, comma separated)
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnAjaxUpdateDraw ( settings, json )
+	{
+		// v1.10 uses camelCase variables, while 1.9 uses Hungarian notation.
+		// Support both
+		var compat = function ( old, modern ) {
+			return json[old] !== undefined ? json[old] : json[modern];
+		};
+	
+		var data = _fnAjaxDataSrc( settings, json );
+		var draw            = compat( 'sEcho',                'draw' );
+		var recordsTotal    = compat( 'iTotalRecords',        'recordsTotal' );
+		var recordsFiltered = compat( 'iTotalDisplayRecords', 'recordsFiltered' );
+	
+		if ( draw ) {
+			// Protect against out of sequence returns
+			if ( draw*1 < settings.iDraw ) {
+				return;
+			}
+			settings.iDraw = draw * 1;
+		}
+	
+		_fnClearTable( settings );
+		settings._iRecordsTotal   = parseInt(recordsTotal, 10);
+		settings._iRecordsDisplay = parseInt(recordsFiltered, 10);
+	
+		for ( var i=0, ien=data.length ; i<ien ; i++ ) {
+			_fnAddData( settings, data[i] );
+		}
+		settings.aiDisplay = settings.aiDisplayMaster.slice();
+	
+		settings.bAjaxDataGet = false;
+		_fnDraw( settings );
+	
+		if ( ! settings._bInitComplete ) {
+			_fnInitComplete( settings, json );
+		}
+	
+		settings.bAjaxDataGet = true;
+		_fnProcessingDisplay( settings, false );
+	}
+	
+	
+	/**
+	 * Get the data from the JSON data source to use for drawing a table. Using
+	 * `_fnGetObjectDataFn` allows the data to be sourced from a property of the
+	 * source object, or from a processing function.
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param  {object} json Data source object / array from the server
+	 *  @return {array} Array of data to use
+	 */
+	function _fnAjaxDataSrc ( oSettings, json )
+	{
+		var dataSrc = $.isPlainObject( oSettings.ajax ) && oSettings.ajax.dataSrc !== undefined ?
+			oSettings.ajax.dataSrc :
+			oSettings.sAjaxDataProp; // Compatibility with 1.9-.
+	
+		// Compatibility with 1.9-. In order to read from aaData, check if the
+		// default has been changed, if not, check for aaData
+		if ( dataSrc === 'data' ) {
+			return json.aaData || json[dataSrc];
+		}
+	
+		return dataSrc !== "" ?
+			_fnGetObjectDataFn( dataSrc )( json ) :
+			json;
+	}
+	
+	/**
+	 * Generate the node required for filtering text
+	 *  @returns {node} Filter control element
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFeatureHtmlFilter ( settings )
+	{
+		var classes = settings.oClasses;
+		var tableId = settings.sTableId;
+		var language = settings.oLanguage;
+		var previousSearch = settings.oPreviousSearch;
+		var features = settings.aanFeatures;
+		var input = '<input type="search" class="'+classes.sFilterInput+'"/>';
+	
+		var str = language.sSearch;
+		str = str.match(/_INPUT_/) ?
+			str.replace('_INPUT_', input) :
+			str+input;
+	
+		var filter = $('<div/>', {
+				'id': ! features.f ? tableId+'_filter' : null,
+				'class': classes.sFilter
+			} )
+			.append( $('<label/>' ).append( str ) );
+	
+		var searchFn = function() {
+			/* Update all other filter input elements for the new display */
+			var n = features.f;
+			var val = !this.value ? "" : this.value; // mental IE8 fix :-(
+	
+			/* Now do the filter */
+			if ( val != previousSearch.sSearch ) {
+				_fnFilterComplete( settings, {
+					"sSearch": val,
+					"bRegex": previousSearch.bRegex,
+					"bSmart": previousSearch.bSmart ,
+					"bCaseInsensitive": previousSearch.bCaseInsensitive
+				} );
+	
+				// Need to redraw, without resorting
+				settings._iDisplayStart = 0;
+				_fnDraw( settings );
+			}
+		};
+	
+		var searchDelay = settings.searchDelay !== null ?
+			settings.searchDelay :
+			_fnDataSource( settings ) === 'ssp' ?
+				400 :
+				0;
+	
+		var jqFilter = $('input', filter)
+			.val( previousSearch.sSearch )
+			.attr( 'placeholder', language.sSearchPlaceholder )
+			.on(
+				'keyup.DT search.DT input.DT paste.DT cut.DT',
+				searchDelay ?
+					_fnThrottle( searchFn, searchDelay ) :
+					searchFn
+			)
+			.on( 'keypress.DT', function(e) {
+				/* Prevent form submission */
+				if ( e.keyCode == 13 ) {
+					return false;
+				}
+			} )
+			.attr('aria-controls', tableId);
+	
+		// Update the input elements whenever the table is filtered
+		$(settings.nTable).on( 'search.dt.DT', function ( ev, s ) {
+			if ( settings === s ) {
+				// IE9 throws an 'unknown error' if document.activeElement is used
+				// inside an iframe or frame...
+				try {
+					if ( jqFilter[0] !== document.activeElement ) {
+						jqFilter.val( previousSearch.sSearch );
+					}
+				}
+				catch ( e ) {}
+			}
+		} );
+	
+		return filter[0];
+	}
+	
+	
+	/**
+	 * Filter the table using both the global filter and column based filtering
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {object} oSearch search information
+	 *  @param {int} [iForce] force a research of the master array (1) or not (undefined or 0)
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFilterComplete ( oSettings, oInput, iForce )
+	{
+		var oPrevSearch = oSettings.oPreviousSearch;
+		var aoPrevSearch = oSettings.aoPreSearchCols;
+		var fnSaveFilter = function ( oFilter ) {
+			/* Save the filtering values */
+			oPrevSearch.sSearch = oFilter.sSearch;
+			oPrevSearch.bRegex = oFilter.bRegex;
+			oPrevSearch.bSmart = oFilter.bSmart;
+			oPrevSearch.bCaseInsensitive = oFilter.bCaseInsensitive;
+		};
+		var fnRegex = function ( o ) {
+			// Backwards compatibility with the bEscapeRegex option
+			return o.bEscapeRegex !== undefined ? !o.bEscapeRegex : o.bRegex;
+		};
+	
+		// Resolve any column types that are unknown due to addition or invalidation
+		// @todo As per sort - can this be moved into an event handler?
+		_fnColumnTypes( oSettings );
+	
+		/* In server-side processing all filtering is done by the server, so no point hanging around here */
+		if ( _fnDataSource( oSettings ) != 'ssp' )
+		{
+			/* Global filter */
+			_fnFilter( oSettings, oInput.sSearch, iForce, fnRegex(oInput), oInput.bSmart, oInput.bCaseInsensitive );
+			fnSaveFilter( oInput );
+	
+			/* Now do the individual column filter */
+			for ( var i=0 ; i<aoPrevSearch.length ; i++ )
+			{
+				_fnFilterColumn( oSettings, aoPrevSearch[i].sSearch, i, fnRegex(aoPrevSearch[i]),
+					aoPrevSearch[i].bSmart, aoPrevSearch[i].bCaseInsensitive );
+			}
+	
+			/* Custom filtering */
+			_fnFilterCustom( oSettings );
+		}
+		else
+		{
+			fnSaveFilter( oInput );
+		}
+	
+		/* Tell the draw function we have been filtering */
+		oSettings.bFiltered = true;
+		_fnCallbackFire( oSettings, null, 'search', [oSettings] );
+	}
+	
+	
+	/**
+	 * Apply custom filtering functions
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFilterCustom( settings )
+	{
+		var filters = DataTable.ext.search;
+		var displayRows = settings.aiDisplay;
+		var row, rowIdx;
+	
+		for ( var i=0, ien=filters.length ; i<ien ; i++ ) {
+			var rows = [];
+	
+			// Loop over each row and see if it should be included
+			for ( var j=0, jen=displayRows.length ; j<jen ; j++ ) {
+				rowIdx = displayRows[ j ];
+				row = settings.aoData[ rowIdx ];
+	
+				if ( filters[i]( settings, row._aFilterData, rowIdx, row._aData, j ) ) {
+					rows.push( rowIdx );
+				}
+			}
+	
+			// So the array reference doesn't break set the results into the
+			// existing array
+			displayRows.length = 0;
+			$.merge( displayRows, rows );
+		}
+	}
+	
+	
+	/**
+	 * Filter the table on a per-column basis
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {string} sInput string to filter on
+	 *  @param {int} iColumn column to filter
+	 *  @param {bool} bRegex treat search string as a regular expression or not
+	 *  @param {bool} bSmart use smart filtering or not
+	 *  @param {bool} bCaseInsensitive Do case insenstive matching or not
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFilterColumn ( settings, searchStr, colIdx, regex, smart, caseInsensitive )
+	{
+		if ( searchStr === '' ) {
+			return;
+		}
+	
+		var data;
+		var out = [];
+		var display = settings.aiDisplay;
+		var rpSearch = _fnFilterCreateSearch( searchStr, regex, smart, caseInsensitive );
+	
+		for ( var i=0 ; i<display.length ; i++ ) {
+			data = settings.aoData[ display[i] ]._aFilterData[ colIdx ];
+	
+			if ( rpSearch.test( data ) ) {
+				out.push( display[i] );
+			}
+		}
+	
+		settings.aiDisplay = out;
+	}
+	
+	
+	/**
+	 * Filter the data table based on user input and draw the table
+	 *  @param {object} settings dataTables settings object
+	 *  @param {string} input string to filter on
+	 *  @param {int} force optional - force a research of the master array (1) or not (undefined or 0)
+	 *  @param {bool} regex treat as a regular expression or not
+	 *  @param {bool} smart perform smart filtering or not
+	 *  @param {bool} caseInsensitive Do case insenstive matching or not
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFilter( settings, input, force, regex, smart, caseInsensitive )
+	{
+		var rpSearch = _fnFilterCreateSearch( input, regex, smart, caseInsensitive );
+		var prevSearch = settings.oPreviousSearch.sSearch;
+		var displayMaster = settings.aiDisplayMaster;
+		var display, invalidated, i;
+		var filtered = [];
+	
+		// Need to take account of custom filtering functions - always filter
+		if ( DataTable.ext.search.length !== 0 ) {
+			force = true;
+		}
+	
+		// Check if any of the rows were invalidated
+		invalidated = _fnFilterData( settings );
+	
+		// If the input is blank - we just want the full data set
+		if ( input.length <= 0 ) {
+			settings.aiDisplay = displayMaster.slice();
+		}
+		else {
+			// New search - start from the master array
+			if ( invalidated ||
+				 force ||
+				 prevSearch.length > input.length ||
+				 input.indexOf(prevSearch) !== 0 ||
+				 settings.bSorted // On resort, the display master needs to be
+				                  // re-filtered since indexes will have changed
+			) {
+				settings.aiDisplay = displayMaster.slice();
+			}
+	
+			// Search the display array
+			display = settings.aiDisplay;
+	
+			for ( i=0 ; i<display.length ; i++ ) {
+				if ( rpSearch.test( settings.aoData[ display[i] ]._sFilterRow ) ) {
+					filtered.push( display[i] );
+				}
+			}
+	
+			settings.aiDisplay = filtered;
+		}
+	}
+	
+	
+	/**
+	 * Build a regular expression object suitable for searching a table
+	 *  @param {string} sSearch string to search for
+	 *  @param {bool} bRegex treat as a regular expression or not
+	 *  @param {bool} bSmart perform smart filtering or not
+	 *  @param {bool} bCaseInsensitive Do case insensitive matching or not
+	 *  @returns {RegExp} constructed object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFilterCreateSearch( search, regex, smart, caseInsensitive )
+	{
+		search = regex ?
+			search :
+			_fnEscapeRegex( search );
+		
+		if ( smart ) {
+			/* For smart filtering we want to allow the search to work regardless of
+			 * word order. We also want double quoted text to be preserved, so word
+			 * order is important - a la google. So this is what we want to
+			 * generate:
+			 * 
+			 * ^(?=.*?\bone\b)(?=.*?\btwo three\b)(?=.*?\bfour\b).*$
+			 */
+			var a = $.map( search.match( /"[^"]+"|[^ ]+/g ) || [''], function ( word ) {
+				if ( word.charAt(0) === '"' ) {
+					var m = word.match( /^"(.*)"$/ );
+					word = m ? m[1] : word;
+				}
+	
+				return word.replace('"', '');
+			} );
+	
+			search = '^(?=.*?'+a.join( ')(?=.*?' )+').*$';
+		}
+	
+		return new RegExp( search, caseInsensitive ? 'i' : '' );
+	}
+	
+	
+	/**
+	 * Escape a string such that it can be used in a regular expression
+	 *  @param {string} sVal string to escape
+	 *  @returns {string} escaped string
+	 *  @memberof DataTable#oApi
+	 */
+	var _fnEscapeRegex = DataTable.util.escapeRegex;
+	
+	var __filter_div = $('<div>')[0];
+	var __filter_div_textContent = __filter_div.textContent !== undefined;
+	
+	// Update the filtering data for each row if needed (by invalidation or first run)
+	function _fnFilterData ( settings )
+	{
+		var columns = settings.aoColumns;
+		var column;
+		var i, j, ien, jen, filterData, cellData, row;
+		var fomatters = DataTable.ext.type.search;
+		var wasInvalidated = false;
+	
+		for ( i=0, ien=settings.aoData.length ; i<ien ; i++ ) {
+			row = settings.aoData[i];
+	
+			if ( ! row._aFilterData ) {
+				filterData = [];
+	
+				for ( j=0, jen=columns.length ; j<jen ; j++ ) {
+					column = columns[j];
+	
+					if ( column.bSearchable ) {
+						cellData = _fnGetCellData( settings, i, j, 'filter' );
+	
+						if ( fomatters[ column.sType ] ) {
+							cellData = fomatters[ column.sType ]( cellData );
+						}
+	
+						// Search in DataTables 1.10 is string based. In 1.11 this
+						// should be altered to also allow strict type checking.
+						if ( cellData === null ) {
+							cellData = '';
+						}
+	
+						if ( typeof cellData !== 'string' && cellData.toString ) {
+							cellData = cellData.toString();
+						}
+					}
+					else {
+						cellData = '';
+					}
+	
+					// If it looks like there is an HTML entity in the string,
+					// attempt to decode it so sorting works as expected. Note that
+					// we could use a single line of jQuery to do this, but the DOM
+					// method used here is much faster http://jsperf.com/html-decode
+					if ( cellData.indexOf && cellData.indexOf('&') !== -1 ) {
+						__filter_div.innerHTML = cellData;
+						cellData = __filter_div_textContent ?
+							__filter_div.textContent :
+							__filter_div.innerText;
+					}
+	
+					if ( cellData.replace ) {
+						cellData = cellData.replace(/[\r\n]/g, '');
+					}
+	
+					filterData.push( cellData );
+				}
+	
+				row._aFilterData = filterData;
+				row._sFilterRow = filterData.join('  ');
+				wasInvalidated = true;
+			}
+		}
+	
+		return wasInvalidated;
+	}
+	
+	
+	/**
+	 * Convert from the internal Hungarian notation to camelCase for external
+	 * interaction
+	 *  @param {object} obj Object to convert
+	 *  @returns {object} Inverted object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSearchToCamel ( obj )
+	{
+		return {
+			search:          obj.sSearch,
+			smart:           obj.bSmart,
+			regex:           obj.bRegex,
+			caseInsensitive: obj.bCaseInsensitive
+		};
+	}
+	
+	
+	
+	/**
+	 * Convert from camelCase notation to the internal Hungarian. We could use the
+	 * Hungarian convert function here, but this is cleaner
+	 *  @param {object} obj Object to convert
+	 *  @returns {object} Inverted object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSearchToHung ( obj )
+	{
+		return {
+			sSearch:          obj.search,
+			bSmart:           obj.smart,
+			bRegex:           obj.regex,
+			bCaseInsensitive: obj.caseInsensitive
+		};
+	}
+	
+	/**
+	 * Generate the node required for the info display
+	 *  @param {object} oSettings dataTables settings object
+	 *  @returns {node} Information element
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFeatureHtmlInfo ( settings )
+	{
+		var
+			tid = settings.sTableId,
+			nodes = settings.aanFeatures.i,
+			n = $('<div/>', {
+				'class': settings.oClasses.sInfo,
+				'id': ! nodes ? tid+'_info' : null
+			} );
+	
+		if ( ! nodes ) {
+			// Update display on each draw
+			settings.aoDrawCallback.push( {
+				"fn": _fnUpdateInfo,
+				"sName": "information"
+			} );
+	
+			n
+				.attr( 'role', 'status' )
+				.attr( 'aria-live', 'polite' );
+	
+			// Table is described by our info div
+			$(settings.nTable).attr( 'aria-describedby', tid+'_info' );
+		}
+	
+		return n[0];
+	}
+	
+	
+	/**
+	 * Update the information elements in the display
+	 *  @param {object} settings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnUpdateInfo ( settings )
+	{
+		/* Show information about the table */
+		var nodes = settings.aanFeatures.i;
+		if ( nodes.length === 0 ) {
+			return;
+		}
+	
+		var
+			lang  = settings.oLanguage,
+			start = settings._iDisplayStart+1,
+			end   = settings.fnDisplayEnd(),
+			max   = settings.fnRecordsTotal(),
+			total = settings.fnRecordsDisplay(),
+			out   = total ?
+				lang.sInfo :
+				lang.sInfoEmpty;
+	
+		if ( total !== max ) {
+			/* Record set after filtering */
+			out += ' ' + lang.sInfoFiltered;
+		}
+	
+		// Convert the macros
+		out += lang.sInfoPostFix;
+		out = _fnInfoMacros( settings, out );
+	
+		var callback = lang.fnInfoCallback;
+		if ( callback !== null ) {
+			out = callback.call( settings.oInstance,
+				settings, start, end, max, total, out
+			);
+		}
+	
+		$(nodes).html( out );
+	}
+	
+	
+	function _fnInfoMacros ( settings, str )
+	{
+		// When infinite scrolling, we are always starting at 1. _iDisplayStart is used only
+		// internally
+		var
+			formatter  = settings.fnFormatNumber,
+			start      = settings._iDisplayStart+1,
+			len        = settings._iDisplayLength,
+			vis        = settings.fnRecordsDisplay(),
+			all        = len === -1;
+	
+		return str.
+			replace(/_START_/g, formatter.call( settings, start ) ).
+			replace(/_END_/g,   formatter.call( settings, settings.fnDisplayEnd() ) ).
+			replace(/_MAX_/g,   formatter.call( settings, settings.fnRecordsTotal() ) ).
+			replace(/_TOTAL_/g, formatter.call( settings, vis ) ).
+			replace(/_PAGE_/g,  formatter.call( settings, all ? 1 : Math.ceil( start / len ) ) ).
+			replace(/_PAGES_/g, formatter.call( settings, all ? 1 : Math.ceil( vis / len ) ) );
+	}
+	
+	
+	
+	/**
+	 * Draw the table for the first time, adding all required features
+	 *  @param {object} settings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnInitialise ( settings )
+	{
+		var i, iLen, iAjaxStart=settings.iInitDisplayStart;
+		var columns = settings.aoColumns, column;
+		var features = settings.oFeatures;
+		var deferLoading = settings.bDeferLoading; // value modified by the draw
+	
+		/* Ensure that the table data is fully initialised */
+		if ( ! settings.bInitialised ) {
+			setTimeout( function(){ _fnInitialise( settings ); }, 200 );
+			return;
+		}
+	
+		/* Show the display HTML options */
+		_fnAddOptionsHtml( settings );
+	
+		/* Build and draw the header / footer for the table */
+		_fnBuildHead( settings );
+		_fnDrawHead( settings, settings.aoHeader );
+		_fnDrawHead( settings, settings.aoFooter );
+	
+		/* Okay to show that something is going on now */
+		_fnProcessingDisplay( settings, true );
+	
+		/* Calculate sizes for columns */
+		if ( features.bAutoWidth ) {
+			_fnCalculateColumnWidths( settings );
+		}
+	
+		for ( i=0, iLen=columns.length ; i<iLen ; i++ ) {
+			column = columns[i];
+	
+			if ( column.sWidth ) {
+				column.nTh.style.width = _fnStringToCss( column.sWidth );
+			}
+		}
+	
+		_fnCallbackFire( settings, null, 'preInit', [settings] );
+	
+		// If there is default sorting required - let's do it. The sort function
+		// will do the drawing for us. Otherwise we draw the table regardless of the
+		// Ajax source - this allows the table to look initialised for Ajax sourcing
+		// data (show 'loading' message possibly)
+		_fnReDraw( settings );
+	
+		// Server-side processing init complete is done by _fnAjaxUpdateDraw
+		var dataSrc = _fnDataSource( settings );
+		if ( dataSrc != 'ssp' || deferLoading ) {
+			// if there is an ajax source load the data
+			if ( dataSrc == 'ajax' ) {
+				_fnBuildAjax( settings, [], function(json) {
+					var aData = _fnAjaxDataSrc( settings, json );
+	
+					// Got the data - add it to the table
+					for ( i=0 ; i<aData.length ; i++ ) {
+						_fnAddData( settings, aData[i] );
+					}
+	
+					// Reset the init display for cookie saving. We've already done
+					// a filter, and therefore cleared it before. So we need to make
+					// it appear 'fresh'
+					settings.iInitDisplayStart = iAjaxStart;
+	
+					_fnReDraw( settings );
+	
+					_fnProcessingDisplay( settings, false );
+					_fnInitComplete( settings, json );
+				}, settings );
+			}
+			else {
+				_fnProcessingDisplay( settings, false );
+				_fnInitComplete( settings );
+			}
+		}
+	}
+	
+	
+	/**
+	 * Draw the table for the first time, adding all required features
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {object} [json] JSON from the server that completed the table, if using Ajax source
+	 *    with client-side processing (optional)
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnInitComplete ( settings, json )
+	{
+		settings._bInitComplete = true;
+	
+		// When data was added after the initialisation (data or Ajax) we need to
+		// calculate the column sizing
+		if ( json || settings.oInit.aaData ) {
+			_fnAdjustColumnSizing( settings );
+		}
+	
+		_fnCallbackFire( settings, null, 'plugin-init', [settings, json] );
+		_fnCallbackFire( settings, 'aoInitComplete', 'init', [settings, json] );
+	}
+	
+	
+	function _fnLengthChange ( settings, val )
+	{
+		var len = parseInt( val, 10 );
+		settings._iDisplayLength = len;
+	
+		_fnLengthOverflow( settings );
+	
+		// Fire length change event
+		_fnCallbackFire( settings, null, 'length', [settings, len] );
+	}
+	
+	
+	/**
+	 * Generate the node required for user display length changing
+	 *  @param {object} settings dataTables settings object
+	 *  @returns {node} Display length feature node
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFeatureHtmlLength ( settings )
+	{
+		var
+			classes  = settings.oClasses,
+			tableId  = settings.sTableId,
+			menu     = settings.aLengthMenu,
+			d2       = $.isArray( menu[0] ),
+			lengths  = d2 ? menu[0] : menu,
+			language = d2 ? menu[1] : menu;
+	
+		var select = $('<select/>', {
+			'name':          tableId+'_length',
+			'aria-controls': tableId,
+			'class':         classes.sLengthSelect
+		} );
+	
+		for ( var i=0, ien=lengths.length ; i<ien ; i++ ) {
+			select[0][ i ] = new Option(
+				typeof language[i] === 'number' ?
+					settings.fnFormatNumber( language[i] ) :
+					language[i],
+				lengths[i]
+			);
+		}
+	
+		var div = $('<div><label/></div>').addClass( classes.sLength );
+		if ( ! settings.aanFeatures.l ) {
+			div[0].id = tableId+'_length';
+		}
+	
+		div.children().append(
+			settings.oLanguage.sLengthMenu.replace( '_MENU_', select[0].outerHTML )
+		);
+	
+		// Can't use `select` variable as user might provide their own and the
+		// reference is broken by the use of outerHTML
+		$('select', div)
+			.val( settings._iDisplayLength )
+			.on( 'change.DT', function(e) {
+				_fnLengthChange( settings, $(this).val() );
+				_fnDraw( settings );
+			} );
+	
+		// Update node value whenever anything changes the table's length
+		$(settings.nTable).on( 'length.dt.DT', function (e, s, len) {
+			if ( settings === s ) {
+				$('select', div).val( len );
+			}
+		} );
+	
+		return div[0];
+	}
+	
+	
+	
+	/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
+	 * Note that most of the paging logic is done in
+	 * DataTable.ext.pager
+	 */
+	
+	/**
+	 * Generate the node required for default pagination
+	 *  @param {object} oSettings dataTables settings object
+	 *  @returns {node} Pagination feature node
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFeatureHtmlPaginate ( settings )
+	{
+		var
+			type   = settings.sPaginationType,
+			plugin = DataTable.ext.pager[ type ],
+			modern = typeof plugin === 'function',
+			redraw = function( settings ) {
+				_fnDraw( settings );
+			},
+			node = $('<div/>').addClass( settings.oClasses.sPaging + type )[0],
+			features = settings.aanFeatures;
+	
+		if ( ! modern ) {
+			plugin.fnInit( settings, node, redraw );
+		}
+	
+		/* Add a draw callback for the pagination on first instance, to update the paging display */
+		if ( ! features.p )
+		{
+			node.id = settings.sTableId+'_paginate';
+	
+			settings.aoDrawCallback.push( {
+				"fn": function( settings ) {
+					if ( modern ) {
+						var
+							start      = settings._iDisplayStart,
+							len        = settings._iDisplayLength,
+							visRecords = settings.fnRecordsDisplay(),
+							all        = len === -1,
+							page = all ? 0 : Math.ceil( start / len ),
+							pages = all ? 1 : Math.ceil( visRecords / len ),
+							buttons = plugin(page, pages),
+							i, ien;
+	
+						for ( i=0, ien=features.p.length ; i<ien ; i++ ) {
+							_fnRenderer( settings, 'pageButton' )(
+								settings, features.p[i], i, buttons, page, pages
+							);
+						}
+					}
+					else {
+						plugin.fnUpdate( settings, redraw );
+					}
+				},
+				"sName": "pagination"
+			} );
+		}
+	
+		return node;
+	}
+	
+	
+	/**
+	 * Alter the display settings to change the page
+	 *  @param {object} settings DataTables settings object
+	 *  @param {string|int} action Paging action to take: "first", "previous",
+	 *    "next" or "last" or page number to jump to (integer)
+	 *  @param [bool] redraw Automatically draw the update or not
+	 *  @returns {bool} true page has changed, false - no change
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnPageChange ( settings, action, redraw )
+	{
+		var
+			start     = settings._iDisplayStart,
+			len       = settings._iDisplayLength,
+			records   = settings.fnRecordsDisplay();
+	
+		if ( records === 0 || len === -1 )
+		{
+			start = 0;
+		}
+		else if ( typeof action === "number" )
+		{
+			start = action * len;
+	
+			if ( start > records )
+			{
+				start = 0;
+			}
+		}
+		else if ( action == "first" )
+		{
+			start = 0;
+		}
+		else if ( action == "previous" )
+		{
+			start = len >= 0 ?
+				start - len :
+				0;
+	
+			if ( start < 0 )
+			{
+			  start = 0;
+			}
+		}
+		else if ( action == "next" )
+		{
+			if ( start + len < records )
+			{
+				start += len;
+			}
+		}
+		else if ( action == "last" )
+		{
+			start = Math.floor( (records-1) / len) * len;
+		}
+		else
+		{
+			_fnLog( settings, 0, "Unknown paging action: "+action, 5 );
+		}
+	
+		var changed = settings._iDisplayStart !== start;
+		settings._iDisplayStart = start;
+	
+		if ( changed ) {
+			_fnCallbackFire( settings, null, 'page', [settings] );
+	
+			if ( redraw ) {
+				_fnDraw( settings );
+			}
+		}
+	
+		return changed;
+	}
+	
+	
+	
+	/**
+	 * Generate the node required for the processing node
+	 *  @param {object} settings dataTables settings object
+	 *  @returns {node} Processing element
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFeatureHtmlProcessing ( settings )
+	{
+		return $('<div/>', {
+				'id': ! settings.aanFeatures.r ? settings.sTableId+'_processing' : null,
+				'class': settings.oClasses.sProcessing
+			} )
+			.html( settings.oLanguage.sProcessing )
+			.insertBefore( settings.nTable )[0];
+	}
+	
+	
+	/**
+	 * Display or hide the processing indicator
+	 *  @param {object} settings dataTables settings object
+	 *  @param {bool} show Show the processing indicator (true) or not (false)
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnProcessingDisplay ( settings, show )
+	{
+		if ( settings.oFeatures.bProcessing ) {
+			$(settings.aanFeatures.r).css( 'display', show ? 'block' : 'none' );
+		}
+	
+		_fnCallbackFire( settings, null, 'processing', [settings, show] );
+	}
+	
+	/**
+	 * Add any control elements for the table - specifically scrolling
+	 *  @param {object} settings dataTables settings object
+	 *  @returns {node} Node to add to the DOM
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnFeatureHtmlTable ( settings )
+	{
+		var table = $(settings.nTable);
+	
+		// Add the ARIA grid role to the table
+		table.attr( 'role', 'grid' );
+	
+		// Scrolling from here on in
+		var scroll = settings.oScroll;
+	
+		if ( scroll.sX === '' && scroll.sY === '' ) {
+			return settings.nTable;
+		}
+	
+		var scrollX = scroll.sX;
+		var scrollY = scroll.sY;
+		var classes = settings.oClasses;
+		var caption = table.children('caption');
+		var captionSide = caption.length ? caption[0]._captionSide : null;
+		var headerClone = $( table[0].cloneNode(false) );
+		var footerClone = $( table[0].cloneNode(false) );
+		var footer = table.children('tfoot');
+		var _div = '<div/>';
+		var size = function ( s ) {
+			return !s ? null : _fnStringToCss( s );
+		};
+	
+		if ( ! footer.length ) {
+			footer = null;
+		}
+	
+		/*
+		 * The HTML structure that we want to generate in this function is:
+		 *  div - scroller
+		 *    div - scroll head
+		 *      div - scroll head inner
+		 *        table - scroll head table
+		 *          thead - thead
+		 *    div - scroll body
+		 *      table - table (master table)
+		 *        thead - thead clone for sizing
+		 *        tbody - tbody
+		 *    div - scroll foot
+		 *      div - scroll foot inner
+		 *        table - scroll foot table
+		 *          tfoot - tfoot
+		 */
+		var scroller = $( _div, { 'class': classes.sScrollWrapper } )
+			.append(
+				$(_div, { 'class': classes.sScrollHead } )
+					.css( {
+						overflow: 'hidden',
+						position: 'relative',
+						border: 0,
+						width: scrollX ? size(scrollX) : '100%'
+					} )
+					.append(
+						$(_div, { 'class': classes.sScrollHeadInner } )
+							.css( {
+								'box-sizing': 'content-box',
+								width: scroll.sXInner || '100%'
+							} )
+							.append(
+								headerClone
+									.removeAttr('id')
+									.css( 'margin-left', 0 )
+									.append( captionSide === 'top' ? caption : null )
+									.append(
+										table.children('thead')
+									)
+							)
+					)
+			)
+			.append(
+				$(_div, { 'class': classes.sScrollBody } )
+					.css( {
+						position: 'relative',
+						overflow: 'auto',
+						width: size( scrollX )
+					} )
+					.append( table )
+			);
+	
+		if ( footer ) {
+			scroller.append(
+				$(_div, { 'class': classes.sScrollFoot } )
+					.css( {
+						overflow: 'hidden',
+						border: 0,
+						width: scrollX ? size(scrollX) : '100%'
+					} )
+					.append(
+						$(_div, { 'class': classes.sScrollFootInner } )
+							.append(
+								footerClone
+									.removeAttr('id')
+									.css( 'margin-left', 0 )
+									.append( captionSide === 'bottom' ? caption : null )
+									.append(
+										table.children('tfoot')
+									)
+							)
+					)
+			);
+		}
+	
+		var children = scroller.children();
+		var scrollHead = children[0];
+		var scrollBody = children[1];
+		var scrollFoot = footer ? children[2] : null;
+	
+		// When the body is scrolled, then we also want to scroll the headers
+		if ( scrollX ) {
+			$(scrollBody).on( 'scroll.DT', function (e) {
+				var scrollLeft = this.scrollLeft;
+	
+				scrollHead.scrollLeft = scrollLeft;
+	
+				if ( footer ) {
+					scrollFoot.scrollLeft = scrollLeft;
+				}
+			} );
+		}
+	
+		$(scrollBody).css(
+			scrollY && scroll.bCollapse ? 'max-height' : 'height', 
+			scrollY
+		);
+	
+		settings.nScrollHead = scrollHead;
+		settings.nScrollBody = scrollBody;
+		settings.nScrollFoot = scrollFoot;
+	
+		// On redraw - align columns
+		settings.aoDrawCallback.push( {
+			"fn": _fnScrollDraw,
+			"sName": "scrolling"
+		} );
+	
+		return scroller[0];
+	}
+	
+	
+	
+	/**
+	 * Update the header, footer and body tables for resizing - i.e. column
+	 * alignment.
+	 *
+	 * Welcome to the most horrible function DataTables. The process that this
+	 * function follows is basically:
+	 *   1. Re-create the table inside the scrolling div
+	 *   2. Take live measurements from the DOM
+	 *   3. Apply the measurements to align the columns
+	 *   4. Clean up
+	 *
+	 *  @param {object} settings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnScrollDraw ( settings )
+	{
+		// Given that this is such a monster function, a lot of variables are use
+		// to try and keep the minimised size as small as possible
+		var
+			scroll         = settings.oScroll,
+			scrollX        = scroll.sX,
+			scrollXInner   = scroll.sXInner,
+			scrollY        = scroll.sY,
+			barWidth       = scroll.iBarWidth,
+			divHeader      = $(settings.nScrollHead),
+			divHeaderStyle = divHeader[0].style,
+			divHeaderInner = divHeader.children('div'),
+			divHeaderInnerStyle = divHeaderInner[0].style,
+			divHeaderTable = divHeaderInner.children('table'),
+			divBodyEl      = settings.nScrollBody,
+			divBody        = $(divBodyEl),
+			divBodyStyle   = divBodyEl.style,
+			divFooter      = $(settings.nScrollFoot),
+			divFooterInner = divFooter.children('div'),
+			divFooterTable = divFooterInner.children('table'),
+			header         = $(settings.nTHead),
+			table          = $(settings.nTable),
+			tableEl        = table[0],
+			tableStyle     = tableEl.style,
+			footer         = settings.nTFoot ? $(settings.nTFoot) : null,
+			browser        = settings.oBrowser,
+			ie67           = browser.bScrollOversize,
+			dtHeaderCells  = _pluck( settings.aoColumns, 'nTh' ),
+			headerTrgEls, footerTrgEls,
+			headerSrcEls, footerSrcEls,
+			headerCopy, footerCopy,
+			headerWidths=[], footerWidths=[],
+			headerContent=[], footerContent=[],
+			idx, correction, sanityWidth,
+			zeroOut = function(nSizer) {
+				var style = nSizer.style;
+				style.paddingTop = "0";
+				style.paddingBottom = "0";
+				style.borderTopWidth = "0";
+				style.borderBottomWidth = "0";
+				style.height = 0;
+			};
+	
+		// If the scrollbar visibility has changed from the last draw, we need to
+		// adjust the column sizes as the table width will have changed to account
+		// for the scrollbar
+		var scrollBarVis = divBodyEl.scrollHeight > divBodyEl.clientHeight;
+		
+		if ( settings.scrollBarVis !== scrollBarVis && settings.scrollBarVis !== undefined ) {
+			settings.scrollBarVis = scrollBarVis;
+			_fnAdjustColumnSizing( settings );
+			return; // adjust column sizing will call this function again
+		}
+		else {
+			settings.scrollBarVis = scrollBarVis;
+		}
+	
+		/*
+		 * 1. Re-create the table inside the scrolling div
+		 */
+	
+		// Remove the old minimised thead and tfoot elements in the inner table
+		table.children('thead, tfoot').remove();
+	
+		if ( footer ) {
+			footerCopy = footer.clone().prependTo( table );
+			footerTrgEls = footer.find('tr'); // the original tfoot is in its own table and must be sized
+			footerSrcEls = footerCopy.find('tr');
+		}
+	
+		// Clone the current header and footer elements and then place it into the inner table
+		headerCopy = header.clone().prependTo( table );
+		headerTrgEls = header.find('tr'); // original header is in its own table
+		headerSrcEls = headerCopy.find('tr');
+		headerCopy.find('th, td').removeAttr('tabindex');
+	
+	
+		/*
+		 * 2. Take live measurements from the DOM - do not alter the DOM itself!
+		 */
+	
+		// Remove old sizing and apply the calculated column widths
+		// Get the unique column headers in the newly created (cloned) header. We want to apply the
+		// calculated sizes to this header
+		if ( ! scrollX )
+		{
+			divBodyStyle.width = '100%';
+			divHeader[0].style.width = '100%';
+		}
+	
+		$.each( _fnGetUniqueThs( settings, headerCopy ), function ( i, el ) {
+			idx = _fnVisibleToColumnIndex( settings, i );
+			el.style.width = settings.aoColumns[idx].sWidth;
+		} );
+	
+		if ( footer ) {
+			_fnApplyToChildren( function(n) {
+				n.style.width = "";
+			}, footerSrcEls );
+		}
+	
+		// Size the table as a whole
+		sanityWidth = table.outerWidth();
+		if ( scrollX === "" ) {
+			// No x scrolling
+			tableStyle.width = "100%";
+	
+			// IE7 will make the width of the table when 100% include the scrollbar
+			// - which is shouldn't. When there is a scrollbar we need to take this
+			// into account.
+			if ( ie67 && (table.find('tbody').height() > divBodyEl.offsetHeight ||
+				divBody.css('overflow-y') == "scroll")
+			) {
+				tableStyle.width = _fnStringToCss( table.outerWidth() - barWidth);
+			}
+	
+			// Recalculate the sanity width
+			sanityWidth = table.outerWidth();
+		}
+		else if ( scrollXInner !== "" ) {
+			// legacy x scroll inner has been given - use it
+			tableStyle.width = _fnStringToCss(scrollXInner);
+	
+			// Recalculate the sanity width
+			sanityWidth = table.outerWidth();
+		}
+	
+		// Hidden header should have zero height, so remove padding and borders. Then
+		// set the width based on the real headers
+	
+		// Apply all styles in one pass
+		_fnApplyToChildren( zeroOut, headerSrcEls );
+	
+		// Read all widths in next pass
+		_fnApplyToChildren( function(nSizer) {
+			headerContent.push( nSizer.innerHTML );
+			headerWidths.push( _fnStringToCss( $(nSizer).css('width') ) );
+		}, headerSrcEls );
+	
+		// Apply all widths in final pass
+		_fnApplyToChildren( function(nToSize, i) {
+			// Only apply widths to the DataTables detected header cells - this
+			// prevents complex headers from having contradictory sizes applied
+			if ( $.inArray( nToSize, dtHeaderCells ) !== -1 ) {
+				nToSize.style.width = headerWidths[i];
+			}
+		}, headerTrgEls );
+	
+		$(headerSrcEls).height(0);
+	
+		/* Same again with the footer if we have one */
+		if ( footer )
+		{
+			_fnApplyToChildren( zeroOut, footerSrcEls );
+	
+			_fnApplyToChildren( function(nSizer) {
+				footerContent.push( nSizer.innerHTML );
+				footerWidths.push( _fnStringToCss( $(nSizer).css('width') ) );
+			}, footerSrcEls );
+	
+			_fnApplyToChildren( function(nToSize, i) {
+				nToSize.style.width = footerWidths[i];
+			}, footerTrgEls );
+	
+			$(footerSrcEls).height(0);
+		}
+	
+	
+		/*
+		 * 3. Apply the measurements
+		 */
+	
+		// "Hide" the header and footer that we used for the sizing. We need to keep
+		// the content of the cell so that the width applied to the header and body
+		// both match, but we want to hide it completely. We want to also fix their
+		// width to what they currently are
+		_fnApplyToChildren( function(nSizer, i) {
+			nSizer.innerHTML = '<div class="dataTables_sizing" style="height:0;overflow:hidden;">'+headerContent[i]+'</div>';
+			nSizer.style.width = headerWidths[i];
+		}, headerSrcEls );
+	
+		if ( footer )
+		{
+			_fnApplyToChildren( function(nSizer, i) {
+				nSizer.innerHTML = '<div class="dataTables_sizing" style="height:0;overflow:hidden;">'+footerContent[i]+'</div>';
+				nSizer.style.width = footerWidths[i];
+			}, footerSrcEls );
+		}
+	
+		// Sanity check that the table is of a sensible width. If not then we are going to get
+		// misalignment - try to prevent this by not allowing the table to shrink below its min width
+		if ( table.outerWidth() < sanityWidth )
+		{
+			// The min width depends upon if we have a vertical scrollbar visible or not */
+			correction = ((divBodyEl.scrollHeight > divBodyEl.offsetHeight ||
+				divBody.css('overflow-y') == "scroll")) ?
+					sanityWidth+barWidth :
+					sanityWidth;
+	
+			// IE6/7 are a law unto themselves...
+			if ( ie67 && (divBodyEl.scrollHeight >
+				divBodyEl.offsetHeight || divBody.css('overflow-y') == "scroll")
+			) {
+				tableStyle.width = _fnStringToCss( correction-barWidth );
+			}
+	
+			// And give the user a warning that we've stopped the table getting too small
+			if ( scrollX === "" || scrollXInner !== "" ) {
+				_fnLog( settings, 1, 'Possible column misalignment', 6 );
+			}
+		}
+		else
+		{
+			correction = '100%';
+		}
+	
+		// Apply to the container elements
+		divBodyStyle.width = _fnStringToCss( correction );
+		divHeaderStyle.width = _fnStringToCss( correction );
+	
+		if ( footer ) {
+			settings.nScrollFoot.style.width = _fnStringToCss( correction );
+		}
+	
+	
+		/*
+		 * 4. Clean up
+		 */
+		if ( ! scrollY ) {
+			/* IE7< puts a vertical scrollbar in place (when it shouldn't be) due to subtracting
+			 * the scrollbar height from the visible display, rather than adding it on. We need to
+			 * set the height in order to sort this. Don't want to do it in any other browsers.
+			 */
+			if ( ie67 ) {
+				divBodyStyle.height = _fnStringToCss( tableEl.offsetHeight+barWidth );
+			}
+		}
+	
+		/* Finally set the width's of the header and footer tables */
+		var iOuterWidth = table.outerWidth();
+		divHeaderTable[0].style.width = _fnStringToCss( iOuterWidth );
+		divHeaderInnerStyle.width = _fnStringToCss( iOuterWidth );
+	
+		// Figure out if there are scrollbar present - if so then we need a the header and footer to
+		// provide a bit more space to allow "overflow" scrolling (i.e. past the scrollbar)
+		var bScrolling = table.height() > divBodyEl.clientHeight || divBody.css('overflow-y') == "scroll";
+		var padding = 'padding' + (browser.bScrollbarLeft ? 'Left' : 'Right' );
+		divHeaderInnerStyle[ padding ] = bScrolling ? barWidth+"px" : "0px";
+	
+		if ( footer ) {
+			divFooterTable[0].style.width = _fnStringToCss( iOuterWidth );
+			divFooterInner[0].style.width = _fnStringToCss( iOuterWidth );
+			divFooterInner[0].style[padding] = bScrolling ? barWidth+"px" : "0px";
+		}
+	
+		// Correct DOM ordering for colgroup - comes before the thead
+		table.children('colgroup').insertBefore( table.children('thead') );
+	
+		/* Adjust the position of the header in case we loose the y-scrollbar */
+		divBody.scroll();
+	
+		// If sorting or filtering has occurred, jump the scrolling back to the top
+		// only if we aren't holding the position
+		if ( (settings.bSorted || settings.bFiltered) && ! settings._drawHold ) {
+			divBodyEl.scrollTop = 0;
+		}
+	}
+	
+	
+	
+	/**
+	 * Apply a given function to the display child nodes of an element array (typically
+	 * TD children of TR rows
+	 *  @param {function} fn Method to apply to the objects
+	 *  @param array {nodes} an1 List of elements to look through for display children
+	 *  @param array {nodes} an2 Another list (identical structure to the first) - optional
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnApplyToChildren( fn, an1, an2 )
+	{
+		var index=0, i=0, iLen=an1.length;
+		var nNode1, nNode2;
+	
+		while ( i < iLen ) {
+			nNode1 = an1[i].firstChild;
+			nNode2 = an2 ? an2[i].firstChild : null;
+	
+			while ( nNode1 ) {
+				if ( nNode1.nodeType === 1 ) {
+					if ( an2 ) {
+						fn( nNode1, nNode2, index );
+					}
+					else {
+						fn( nNode1, index );
+					}
+	
+					index++;
+				}
+	
+				nNode1 = nNode1.nextSibling;
+				nNode2 = an2 ? nNode2.nextSibling : null;
+			}
+	
+			i++;
+		}
+	}
+	
+	
+	
+	var __re_html_remove = /<.*?>/g;
+	
+	
+	/**
+	 * Calculate the width of columns for the table
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnCalculateColumnWidths ( oSettings )
+	{
+		var
+			table = oSettings.nTable,
+			columns = oSettings.aoColumns,
+			scroll = oSettings.oScroll,
+			scrollY = scroll.sY,
+			scrollX = scroll.sX,
+			scrollXInner = scroll.sXInner,
+			columnCount = columns.length,
+			visibleColumns = _fnGetColumns( oSettings, 'bVisible' ),
+			headerCells = $('th', oSettings.nTHead),
+			tableWidthAttr = table.getAttribute('width'), // from DOM element
+			tableContainer = table.parentNode,
+			userInputs = false,
+			i, column, columnIdx, width, outerWidth,
+			browser = oSettings.oBrowser,
+			ie67 = browser.bScrollOversize;
+	
+		var styleWidth = table.style.width;
+		if ( styleWidth && styleWidth.indexOf('%') !== -1 ) {
+			tableWidthAttr = styleWidth;
+		}
+	
+		/* Convert any user input sizes into pixel sizes */
+		for ( i=0 ; i<visibleColumns.length ; i++ ) {
+			column = columns[ visibleColumns[i] ];
+	
+			if ( column.sWidth !== null ) {
+				column.sWidth = _fnConvertToWidth( column.sWidthOrig, tableContainer );
+	
+				userInputs = true;
+			}
+		}
+	
+		/* If the number of columns in the DOM equals the number that we have to
+		 * process in DataTables, then we can use the offsets that are created by
+		 * the web- browser. No custom sizes can be set in order for this to happen,
+		 * nor scrolling used
+		 */
+		if ( ie67 || ! userInputs && ! scrollX && ! scrollY &&
+		     columnCount == _fnVisbleColumns( oSettings ) &&
+		     columnCount == headerCells.length
+		) {
+			for ( i=0 ; i<columnCount ; i++ ) {
+				var colIdx = _fnVisibleToColumnIndex( oSettings, i );
+	
+				if ( colIdx !== null ) {
+					columns[ colIdx ].sWidth = _fnStringToCss( headerCells.eq(i).width() );
+				}
+			}
+		}
+		else
+		{
+			// Otherwise construct a single row, worst case, table with the widest
+			// node in the data, assign any user defined widths, then insert it into
+			// the DOM and allow the browser to do all the hard work of calculating
+			// table widths
+			var tmpTable = $(table).clone() // don't use cloneNode - IE8 will remove events on the main table
+				.css( 'visibility', 'hidden' )
+				.removeAttr( 'id' );
+	
+			// Clean up the table body
+			tmpTable.find('tbody tr').remove();
+			var tr = $('<tr/>').appendTo( tmpTable.find('tbody') );
+	
+			// Clone the table header and footer - we can't use the header / footer
+			// from the cloned table, since if scrolling is active, the table's
+			// real header and footer are contained in different table tags
+			tmpTable.find('thead, tfoot').remove();
+			tmpTable
+				.append( $(oSettings.nTHead).clone() )
+				.append( $(oSettings.nTFoot).clone() );
+	
+			// Remove any assigned widths from the footer (from scrolling)
+			tmpTable.find('tfoot th, tfoot td').css('width', '');
+	
+			// Apply custom sizing to the cloned header
+			headerCells = _fnGetUniqueThs( oSettings, tmpTable.find('thead')[0] );
+	
+			for ( i=0 ; i<visibleColumns.length ; i++ ) {
+				column = columns[ visibleColumns[i] ];
+	
+				headerCells[i].style.width = column.sWidthOrig !== null && column.sWidthOrig !== '' ?
+					_fnStringToCss( column.sWidthOrig ) :
+					'';
+	
+				// For scrollX we need to force the column width otherwise the
+				// browser will collapse it. If this width is smaller than the
+				// width the column requires, then it will have no effect
+				if ( column.sWidthOrig && scrollX ) {
+					$( headerCells[i] ).append( $('<div/>').css( {
+						width: column.sWidthOrig,
+						margin: 0,
+						padding: 0,
+						border: 0,
+						height: 1
+					} ) );
+				}
+			}
+	
+			// Find the widest cell for each column and put it into the table
+			if ( oSettings.aoData.length ) {
+				for ( i=0 ; i<visibleColumns.length ; i++ ) {
+					columnIdx = visibleColumns[i];
+					column = columns[ columnIdx ];
+	
+					$( _fnGetWidestNode( oSettings, columnIdx ) )
+						.clone( false )
+						.append( column.sContentPadding )
+						.appendTo( tr );
+				}
+			}
+	
+			// Tidy the temporary table - remove name attributes so there aren't
+			// duplicated in the dom (radio elements for example)
+			$('[name]', tmpTable).removeAttr('name');
+	
+			// Table has been built, attach to the document so we can work with it.
+			// A holding element is used, positioned at the top of the container
+			// with minimal height, so it has no effect on if the container scrolls
+			// or not. Otherwise it might trigger scrolling when it actually isn't
+			// needed
+			var holder = $('<div/>').css( scrollX || scrollY ?
+					{
+						position: 'absolute',
+						top: 0,
+						left: 0,
+						height: 1,
+						right: 0,
+						overflow: 'hidden'
+					} :
+					{}
+				)
+				.append( tmpTable )
+				.appendTo( tableContainer );
+	
+			// When scrolling (X or Y) we want to set the width of the table as 
+			// appropriate. However, when not scrolling leave the table width as it
+			// is. This results in slightly different, but I think correct behaviour
+			if ( scrollX && scrollXInner ) {
+				tmpTable.width( scrollXInner );
+			}
+			else if ( scrollX ) {
+				tmpTable.css( 'width', 'auto' );
+				tmpTable.removeAttr('width');
+	
+				// If there is no width attribute or style, then allow the table to
+				// collapse
+				if ( tmpTable.width() < tableContainer.clientWidth && tableWidthAttr ) {
+					tmpTable.width( tableContainer.clientWidth );
+				}
+			}
+			else if ( scrollY ) {
+				tmpTable.width( tableContainer.clientWidth );
+			}
+			else if ( tableWidthAttr ) {
+				tmpTable.width( tableWidthAttr );
+			}
+	
+			// Get the width of each column in the constructed table - we need to
+			// know the inner width (so it can be assigned to the other table's
+			// cells) and the outer width so we can calculate the full width of the
+			// table. This is safe since DataTables requires a unique cell for each
+			// column, but if ever a header can span multiple columns, this will
+			// need to be modified.
+			var total = 0;
+			for ( i=0 ; i<visibleColumns.length ; i++ ) {
+				var cell = $(headerCells[i]);
+				var border = cell.outerWidth() - cell.width();
+	
+				// Use getBounding... where possible (not IE8-) because it can give
+				// sub-pixel accuracy, which we then want to round up!
+				var bounding = browser.bBounding ?
+					Math.ceil( headerCells[i].getBoundingClientRect().width ) :
+					cell.outerWidth();
+	
+				// Total is tracked to remove any sub-pixel errors as the outerWidth
+				// of the table might not equal the total given here (IE!).
+				total += bounding;
+	
+				// Width for each column to use
+				columns[ visibleColumns[i] ].sWidth = _fnStringToCss( bounding - border );
+			}
+	
+			table.style.width = _fnStringToCss( total );
+	
+			// Finished with the table - ditch it
+			holder.remove();
+		}
+	
+		// If there is a width attr, we want to attach an event listener which
+		// allows the table sizing to automatically adjust when the window is
+		// resized. Use the width attr rather than CSS, since we can't know if the
+		// CSS is a relative value or absolute - DOM read is always px.
+		if ( tableWidthAttr ) {
+			table.style.width = _fnStringToCss( tableWidthAttr );
+		}
+	
+		if ( (tableWidthAttr || scrollX) && ! oSettings._reszEvt ) {
+			var bindResize = function () {
+				$(window).on('resize.DT-'+oSettings.sInstance, _fnThrottle( function () {
+					_fnAdjustColumnSizing( oSettings );
+				} ) );
+			};
+	
+			// IE6/7 will crash if we bind a resize event handler on page load.
+			// To be removed in 1.11 which drops IE6/7 support
+			if ( ie67 ) {
+				setTimeout( bindResize, 1000 );
+			}
+			else {
+				bindResize();
+			}
+	
+			oSettings._reszEvt = true;
+		}
+	}
+	
+	
+	/**
+	 * Throttle the calls to a function. Arguments and context are maintained for
+	 * the throttled function
+	 *  @param {function} fn Function to be called
+	 *  @param {int} [freq=200] call frequency in mS
+	 *  @returns {function} wrapped function
+	 *  @memberof DataTable#oApi
+	 */
+	var _fnThrottle = DataTable.util.throttle;
+	
+	
+	/**
+	 * Convert a CSS unit width to pixels (e.g. 2em)
+	 *  @param {string} width width to be converted
+	 *  @param {node} parent parent to get the with for (required for relative widths) - optional
+	 *  @returns {int} width in pixels
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnConvertToWidth ( width, parent )
+	{
+		if ( ! width ) {
+			return 0;
+		}
+	
+		var n = $('<div/>')
+			.css( 'width', _fnStringToCss( width ) )
+			.appendTo( parent || document.body );
+	
+		var val = n[0].offsetWidth;
+		n.remove();
+	
+		return val;
+	}
+	
+	
+	/**
+	 * Get the widest node
+	 *  @param {object} settings dataTables settings object
+	 *  @param {int} colIdx column of interest
+	 *  @returns {node} widest table node
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnGetWidestNode( settings, colIdx )
+	{
+		var idx = _fnGetMaxLenString( settings, colIdx );
+		if ( idx < 0 ) {
+			return null;
+		}
+	
+		var data = settings.aoData[ idx ];
+		return ! data.nTr ? // Might not have been created when deferred rendering
+			$('<td/>').html( _fnGetCellData( settings, idx, colIdx, 'display' ) )[0] :
+			data.anCells[ colIdx ];
+	}
+	
+	
+	/**
+	 * Get the maximum strlen for each data column
+	 *  @param {object} settings dataTables settings object
+	 *  @param {int} colIdx column of interest
+	 *  @returns {string} max string length for each column
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnGetMaxLenString( settings, colIdx )
+	{
+		var s, max=-1, maxIdx = -1;
+	
+		for ( var i=0, ien=settings.aoData.length ; i<ien ; i++ ) {
+			s = _fnGetCellData( settings, i, colIdx, 'display' )+'';
+			s = s.replace( __re_html_remove, '' );
+			s = s.replace( /&nbsp;/g, ' ' );
+	
+			if ( s.length > max ) {
+				max = s.length;
+				maxIdx = i;
+			}
+		}
+	
+		return maxIdx;
+	}
+	
+	
+	/**
+	 * Append a CSS unit (only if required) to a string
+	 *  @param {string} value to css-ify
+	 *  @returns {string} value with css unit
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnStringToCss( s )
+	{
+		if ( s === null ) {
+			return '0px';
+		}
+	
+		if ( typeof s == 'number' ) {
+			return s < 0 ?
+				'0px' :
+				s+'px';
+		}
+	
+		// Check it has a unit character already
+		return s.match(/\d$/) ?
+			s+'px' :
+			s;
+	}
+	
+	
+	
+	function _fnSortFlatten ( settings )
+	{
+		var
+			i, iLen, k, kLen,
+			aSort = [],
+			aiOrig = [],
+			aoColumns = settings.aoColumns,
+			aDataSort, iCol, sType, srcCol,
+			fixed = settings.aaSortingFixed,
+			fixedObj = $.isPlainObject( fixed ),
+			nestedSort = [],
+			add = function ( a ) {
+				if ( a.length && ! $.isArray( a[0] ) ) {
+					// 1D array
+					nestedSort.push( a );
+				}
+				else {
+					// 2D array
+					$.merge( nestedSort, a );
+				}
+			};
+	
+		// Build the sort array, with pre-fix and post-fix options if they have been
+		// specified
+		if ( $.isArray( fixed ) ) {
+			add( fixed );
+		}
+	
+		if ( fixedObj && fixed.pre ) {
+			add( fixed.pre );
+		}
+	
+		add( settings.aaSorting );
+	
+		if (fixedObj && fixed.post ) {
+			add( fixed.post );
+		}
+	
+		for ( i=0 ; i<nestedSort.length ; i++ )
+		{
+			srcCol = nestedSort[i][0];
+			aDataSort = aoColumns[ srcCol ].aDataSort;
+	
+			for ( k=0, kLen=aDataSort.length ; k<kLen ; k++ )
+			{
+				iCol = aDataSort[k];
+				sType = aoColumns[ iCol ].sType || 'string';
+	
+				if ( nestedSort[i]._idx === undefined ) {
+					nestedSort[i]._idx = $.inArray( nestedSort[i][1], aoColumns[iCol].asSorting );
+				}
+	
+				aSort.push( {
+					src:       srcCol,
+					col:       iCol,
+					dir:       nestedSort[i][1],
+					index:     nestedSort[i]._idx,
+					type:      sType,
+					formatter: DataTable.ext.type.order[ sType+"-pre" ]
+				} );
+			}
+		}
+	
+		return aSort;
+	}
+	
+	/**
+	 * Change the order of the table
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 *  @todo This really needs split up!
+	 */
+	function _fnSort ( oSettings )
+	{
+		var
+			i, ien, iLen, j, jLen, k, kLen,
+			sDataType, nTh,
+			aiOrig = [],
+			oExtSort = DataTable.ext.type.order,
+			aoData = oSettings.aoData,
+			aoColumns = oSettings.aoColumns,
+			aDataSort, data, iCol, sType, oSort,
+			formatters = 0,
+			sortCol,
+			displayMaster = oSettings.aiDisplayMaster,
+			aSort;
+	
+		// Resolve any column types that are unknown due to addition or invalidation
+		// @todo Can this be moved into a 'data-ready' handler which is called when
+		//   data is going to be used in the table?
+		_fnColumnTypes( oSettings );
+	
+		aSort = _fnSortFlatten( oSettings );
+	
+		for ( i=0, ien=aSort.length ; i<ien ; i++ ) {
+			sortCol = aSort[i];
+	
+			// Track if we can use the fast sort algorithm
+			if ( sortCol.formatter ) {
+				formatters++;
+			}
+	
+			// Load the data needed for the sort, for each cell
+			_fnSortData( oSettings, sortCol.col );
+		}
+	
+		/* No sorting required if server-side or no sorting array */
+		if ( _fnDataSource( oSettings ) != 'ssp' && aSort.length !== 0 )
+		{
+			// Create a value - key array of the current row positions such that we can use their
+			// current position during the sort, if values match, in order to perform stable sorting
+			for ( i=0, iLen=displayMaster.length ; i<iLen ; i++ ) {
+				aiOrig[ displayMaster[i] ] = i;
+			}
+	
+			/* Do the sort - here we want multi-column sorting based on a given data source (column)
+			 * and sorting function (from oSort) in a certain direction. It's reasonably complex to
+			 * follow on it's own, but this is what we want (example two column sorting):
+			 *  fnLocalSorting = function(a,b){
+			 *    var iTest;
+			 *    iTest = oSort['string-asc']('data11', 'data12');
+			 *      if (iTest !== 0)
+			 *        return iTest;
+			 *    iTest = oSort['numeric-desc']('data21', 'data22');
+			 *    if (iTest !== 0)
+			 *      return iTest;
+			 *    return oSort['numeric-asc']( aiOrig[a], aiOrig[b] );
+			 *  }
+			 * Basically we have a test for each sorting column, if the data in that column is equal,
+			 * test the next column. If all columns match, then we use a numeric sort on the row
+			 * positions in the original data array to provide a stable sort.
+			 *
+			 * Note - I know it seems excessive to have two sorting methods, but the first is around
+			 * 15% faster, so the second is only maintained for backwards compatibility with sorting
+			 * methods which do not have a pre-sort formatting function.
+			 */
+			if ( formatters === aSort.length ) {
+				// All sort types have formatting functions
+				displayMaster.sort( function ( a, b ) {
+					var
+						x, y, k, test, sort,
+						len=aSort.length,
+						dataA = aoData[a]._aSortData,
+						dataB = aoData[b]._aSortData;
+	
+					for ( k=0 ; k<len ; k++ ) {
+						sort = aSort[k];
+	
+						x = dataA[ sort.col ];
+						y = dataB[ sort.col ];
+	
+						test = x<y ? -1 : x>y ? 1 : 0;
+						if ( test !== 0 ) {
+							return sort.dir === 'asc' ? test : -test;
+						}
+					}
+	
+					x = aiOrig[a];
+					y = aiOrig[b];
+					return x<y ? -1 : x>y ? 1 : 0;
+				} );
+			}
+			else {
+				// Depreciated - remove in 1.11 (providing a plug-in option)
+				// Not all sort types have formatting methods, so we have to call their sorting
+				// methods.
+				displayMaster.sort( function ( a, b ) {
+					var
+						x, y, k, l, test, sort, fn,
+						len=aSort.length,
+						dataA = aoData[a]._aSortData,
+						dataB = aoData[b]._aSortData;
+	
+					for ( k=0 ; k<len ; k++ ) {
+						sort = aSort[k];
+	
+						x = dataA[ sort.col ];
+						y = dataB[ sort.col ];
+	
+						fn = oExtSort[ sort.type+"-"+sort.dir ] || oExtSort[ "string-"+sort.dir ];
+						test = fn( x, y );
+						if ( test !== 0 ) {
+							return test;
+						}
+					}
+	
+					x = aiOrig[a];
+					y = aiOrig[b];
+					return x<y ? -1 : x>y ? 1 : 0;
+				} );
+			}
+		}
+	
+		/* Tell the draw function that we have sorted the data */
+		oSettings.bSorted = true;
+	}
+	
+	
+	function _fnSortAria ( settings )
+	{
+		var label;
+		var nextSort;
+		var columns = settings.aoColumns;
+		var aSort = _fnSortFlatten( settings );
+		var oAria = settings.oLanguage.oAria;
+	
+		// ARIA attributes - need to loop all columns, to update all (removing old
+		// attributes as needed)
+		for ( var i=0, iLen=columns.length ; i<iLen ; i++ )
+		{
+			var col = columns[i];
+			var asSorting = col.asSorting;
+			var sTitle = col.sTitle.replace( /<.*?>/g, "" );
+			var th = col.nTh;
+	
+			// IE7 is throwing an error when setting these properties with jQuery's
+			// attr() and removeAttr() methods...
+			th.removeAttribute('aria-sort');
+	
+			/* In ARIA only the first sorting column can be marked as sorting - no multi-sort option */
+			if ( col.bSortable ) {
+				if ( aSort.length > 0 && aSort[0].col == i ) {
+					th.setAttribute('aria-sort', aSort[0].dir=="asc" ? "ascending" : "descending" );
+					nextSort = asSorting[ aSort[0].index+1 ] || asSorting[0];
+				}
+				else {
+					nextSort = asSorting[0];
+				}
+	
+				label = sTitle + ( nextSort === "asc" ?
+					oAria.sSortAscending :
+					oAria.sSortDescending
+				);
+			}
+			else {
+				label = sTitle;
+			}
+	
+			th.setAttribute('aria-label', label);
+		}
+	}
+	
+	
+	/**
+	 * Function to run on user sort request
+	 *  @param {object} settings dataTables settings object
+	 *  @param {node} attachTo node to attach the handler to
+	 *  @param {int} colIdx column sorting index
+	 *  @param {boolean} [append=false] Append the requested sort to the existing
+	 *    sort if true (i.e. multi-column sort)
+	 *  @param {function} [callback] callback function
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSortListener ( settings, colIdx, append, callback )
+	{
+		var col = settings.aoColumns[ colIdx ];
+		var sorting = settings.aaSorting;
+		var asSorting = col.asSorting;
+		var nextSortIdx;
+		var next = function ( a, overflow ) {
+			var idx = a._idx;
+			if ( idx === undefined ) {
+				idx = $.inArray( a[1], asSorting );
+			}
+	
+			return idx+1 < asSorting.length ?
+				idx+1 :
+				overflow ?
+					null :
+					0;
+		};
+	
+		// Convert to 2D array if needed
+		if ( typeof sorting[0] === 'number' ) {
+			sorting = settings.aaSorting = [ sorting ];
+		}
+	
+		// If appending the sort then we are multi-column sorting
+		if ( append && settings.oFeatures.bSortMulti ) {
+			// Are we already doing some kind of sort on this column?
+			var sortIdx = $.inArray( colIdx, _pluck(sorting, '0') );
+	
+			if ( sortIdx !== -1 ) {
+				// Yes, modify the sort
+				nextSortIdx = next( sorting[sortIdx], true );
+	
+				if ( nextSortIdx === null && sorting.length === 1 ) {
+					nextSortIdx = 0; // can't remove sorting completely
+				}
+	
+				if ( nextSortIdx === null ) {
+					sorting.splice( sortIdx, 1 );
+				}
+				else {
+					sorting[sortIdx][1] = asSorting[ nextSortIdx ];
+					sorting[sortIdx]._idx = nextSortIdx;
+				}
+			}
+			else {
+				// No sort on this column yet
+				sorting.push( [ colIdx, asSorting[0], 0 ] );
+				sorting[sorting.length-1]._idx = 0;
+			}
+		}
+		else if ( sorting.length && sorting[0][0] == colIdx ) {
+			// Single column - already sorting on this column, modify the sort
+			nextSortIdx = next( sorting[0] );
+	
+			sorting.length = 1;
+			sorting[0][1] = asSorting[ nextSortIdx ];
+			sorting[0]._idx = nextSortIdx;
+		}
+		else {
+			// Single column - sort only on this column
+			sorting.length = 0;
+			sorting.push( [ colIdx, asSorting[0] ] );
+			sorting[0]._idx = 0;
+		}
+	
+		// Run the sort by calling a full redraw
+		_fnReDraw( settings );
+	
+		// callback used for async user interaction
+		if ( typeof callback == 'function' ) {
+			callback( settings );
+		}
+	}
+	
+	
+	/**
+	 * Attach a sort handler (click) to a node
+	 *  @param {object} settings dataTables settings object
+	 *  @param {node} attachTo node to attach the handler to
+	 *  @param {int} colIdx column sorting index
+	 *  @param {function} [callback] callback function
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSortAttachListener ( settings, attachTo, colIdx, callback )
+	{
+		var col = settings.aoColumns[ colIdx ];
+	
+		_fnBindAction( attachTo, {}, function (e) {
+			/* If the column is not sortable - don't to anything */
+			if ( col.bSortable === false ) {
+				return;
+			}
+	
+			// If processing is enabled use a timeout to allow the processing
+			// display to be shown - otherwise to it synchronously
+			if ( settings.oFeatures.bProcessing ) {
+				_fnProcessingDisplay( settings, true );
+	
+				setTimeout( function() {
+					_fnSortListener( settings, colIdx, e.shiftKey, callback );
+	
+					// In server-side processing, the draw callback will remove the
+					// processing display
+					if ( _fnDataSource( settings ) !== 'ssp' ) {
+						_fnProcessingDisplay( settings, false );
+					}
+				}, 0 );
+			}
+			else {
+				_fnSortListener( settings, colIdx, e.shiftKey, callback );
+			}
+		} );
+	}
+	
+	
+	/**
+	 * Set the sorting classes on table's body, Note: it is safe to call this function
+	 * when bSort and bSortClasses are false
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSortingClasses( settings )
+	{
+		var oldSort = settings.aLastSort;
+		var sortClass = settings.oClasses.sSortColumn;
+		var sort = _fnSortFlatten( settings );
+		var features = settings.oFeatures;
+		var i, ien, colIdx;
+	
+		if ( features.bSort && features.bSortClasses ) {
+			// Remove old sorting classes
+			for ( i=0, ien=oldSort.length ; i<ien ; i++ ) {
+				colIdx = oldSort[i].src;
+	
+				// Remove column sorting
+				$( _pluck( settings.aoData, 'anCells', colIdx ) )
+					.removeClass( sortClass + (i<2 ? i+1 : 3) );
+			}
+	
+			// Add new column sorting
+			for ( i=0, ien=sort.length ; i<ien ; i++ ) {
+				colIdx = sort[i].src;
+	
+				$( _pluck( settings.aoData, 'anCells', colIdx ) )
+					.addClass( sortClass + (i<2 ? i+1 : 3) );
+			}
+		}
+	
+		settings.aLastSort = sort;
+	}
+	
+	
+	// Get the data to sort a column, be it from cache, fresh (populating the
+	// cache), or from a sort formatter
+	function _fnSortData( settings, idx )
+	{
+		// Custom sorting function - provided by the sort data type
+		var column = settings.aoColumns[ idx ];
+		var customSort = DataTable.ext.order[ column.sSortDataType ];
+		var customData;
+	
+		if ( customSort ) {
+			customData = customSort.call( settings.oInstance, settings, idx,
+				_fnColumnIndexToVisible( settings, idx )
+			);
+		}
+	
+		// Use / populate cache
+		var row, cellData;
+		var formatter = DataTable.ext.type.order[ column.sType+"-pre" ];
+	
+		for ( var i=0, ien=settings.aoData.length ; i<ien ; i++ ) {
+			row = settings.aoData[i];
+	
+			if ( ! row._aSortData ) {
+				row._aSortData = [];
+			}
+	
+			if ( ! row._aSortData[idx] || customSort ) {
+				cellData = customSort ?
+					customData[i] : // If there was a custom sort function, use data from there
+					_fnGetCellData( settings, i, idx, 'sort' );
+	
+				row._aSortData[ idx ] = formatter ?
+					formatter( cellData ) :
+					cellData;
+			}
+		}
+	}
+	
+	
+	
+	/**
+	 * Save the state of a table
+	 *  @param {object} oSettings dataTables settings object
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSaveState ( settings )
+	{
+		if ( !settings.oFeatures.bStateSave || settings.bDestroying )
+		{
+			return;
+		}
+	
+		/* Store the interesting variables */
+		var state = {
+			time:    +new Date(),
+			start:   settings._iDisplayStart,
+			length:  settings._iDisplayLength,
+			order:   $.extend( true, [], settings.aaSorting ),
+			search:  _fnSearchToCamel( settings.oPreviousSearch ),
+			columns: $.map( settings.aoColumns, function ( col, i ) {
+				return {
+					visible: col.bVisible,
+					search: _fnSearchToCamel( settings.aoPreSearchCols[i] )
+				};
+			} )
+		};
+	
+		_fnCallbackFire( settings, "aoStateSaveParams", 'stateSaveParams', [settings, state] );
+	
+		settings.oSavedState = state;
+		settings.fnStateSaveCallback.call( settings.oInstance, settings, state );
+	}
+	
+	
+	/**
+	 * Attempt to load a saved table state
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {object} oInit DataTables init object so we can override settings
+	 *  @param {function} callback Callback to execute when the state has been loaded
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnLoadState ( settings, oInit, callback )
+	{
+		var i, ien;
+		var columns = settings.aoColumns;
+		var loaded = function ( s ) {
+			if ( ! s || ! s.time ) {
+				callback();
+				return;
+			}
+	
+			// Allow custom and plug-in manipulation functions to alter the saved data set and
+			// cancelling of loading by returning false
+			var abStateLoad = _fnCallbackFire( settings, 'aoStateLoadParams', 'stateLoadParams', [settings, s] );
+			if ( $.inArray( false, abStateLoad ) !== -1 ) {
+				callback();
+				return;
+			}
+	
+			// Reject old data
+			var duration = settings.iStateDuration;
+			if ( duration > 0 && s.time < +new Date() - (duration*1000) ) {
+				callback();
+				return;
+			}
+	
+			// Number of columns have changed - all bets are off, no restore of settings
+			if ( s.columns && columns.length !== s.columns.length ) {
+				callback();
+				return;
+			}
+	
+			// Store the saved state so it might be accessed at any time
+			settings.oLoadedState = $.extend( true, {}, s );
+	
+			// Restore key features - todo - for 1.11 this needs to be done by
+			// subscribed events
+			if ( s.start !== undefined ) {
+				settings._iDisplayStart    = s.start;
+				settings.iInitDisplayStart = s.start;
+			}
+			if ( s.length !== undefined ) {
+				settings._iDisplayLength   = s.length;
+			}
+	
+			// Order
+			if ( s.order !== undefined ) {
+				settings.aaSorting = [];
+				$.each( s.order, function ( i, col ) {
+					settings.aaSorting.push( col[0] >= columns.length ?
+						[ 0, col[1] ] :
+						col
+					);
+				} );
+			}
+	
+			// Search
+			if ( s.search !== undefined ) {
+				$.extend( settings.oPreviousSearch, _fnSearchToHung( s.search ) );
+			}
+	
+			// Columns
+			//
+			if ( s.columns ) {
+				for ( i=0, ien=s.columns.length ; i<ien ; i++ ) {
+					var col = s.columns[i];
+	
+					// Visibility
+					if ( col.visible !== undefined ) {
+						columns[i].bVisible = col.visible;
+					}
+	
+					// Search
+					if ( col.search !== undefined ) {
+						$.extend( settings.aoPreSearchCols[i], _fnSearchToHung( col.search ) );
+					}
+				}
+			}
+	
+			_fnCallbackFire( settings, 'aoStateLoaded', 'stateLoaded', [settings, s] );
+			callback();
+		}
+	
+		if ( ! settings.oFeatures.bStateSave ) {
+			callback();
+			return;
+		}
+	
+		var state = settings.fnStateLoadCallback.call( settings.oInstance, settings, loaded );
+	
+		if ( state !== undefined ) {
+			loaded( state );
+		}
+		// otherwise, wait for the loaded callback to be executed
+	}
+	
+	
+	/**
+	 * Return the settings object for a particular table
+	 *  @param {node} table table we are using as a dataTable
+	 *  @returns {object} Settings object - or null if not found
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnSettingsFromNode ( table )
+	{
+		var settings = DataTable.settings;
+		var idx = $.inArray( table, _pluck( settings, 'nTable' ) );
+	
+		return idx !== -1 ?
+			settings[ idx ] :
+			null;
+	}
+	
+	
+	/**
+	 * Log an error message
+	 *  @param {object} settings dataTables settings object
+	 *  @param {int} level log error messages, or display them to the user
+	 *  @param {string} msg error message
+	 *  @param {int} tn Technical note id to get more information about the error.
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnLog( settings, level, msg, tn )
+	{
+		msg = 'DataTables warning: '+
+			(settings ? 'table id='+settings.sTableId+' - ' : '')+msg;
+	
+		if ( tn ) {
+			msg += '. For more information about this error, please see '+
+			'http://datatables.net/tn/'+tn;
+		}
+	
+		if ( ! level  ) {
+			// Backwards compatibility pre 1.10
+			var ext = DataTable.ext;
+			var type = ext.sErrMode || ext.errMode;
+	
+			if ( settings ) {
+				_fnCallbackFire( settings, null, 'error', [ settings, tn, msg ] );
+			}
+	
+			if ( type == 'alert' ) {
+				alert( msg );
+			}
+			else if ( type == 'throw' ) {
+				throw new Error(msg);
+			}
+			else if ( typeof type == 'function' ) {
+				type( settings, tn, msg );
+			}
+		}
+		else if ( window.console && console.log ) {
+			console.log( msg );
+		}
+	}
+	
+	
+	/**
+	 * See if a property is defined on one object, if so assign it to the other object
+	 *  @param {object} ret target object
+	 *  @param {object} src source object
+	 *  @param {string} name property
+	 *  @param {string} [mappedName] name to map too - optional, name used if not given
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnMap( ret, src, name, mappedName )
+	{
+		if ( $.isArray( name ) ) {
+			$.each( name, function (i, val) {
+				if ( $.isArray( val ) ) {
+					_fnMap( ret, src, val[0], val[1] );
+				}
+				else {
+					_fnMap( ret, src, val );
+				}
+			} );
+	
+			return;
+		}
+	
+		if ( mappedName === undefined ) {
+			mappedName = name;
+		}
+	
+		if ( src[name] !== undefined ) {
+			ret[mappedName] = src[name];
+		}
+	}
+	
+	
+	/**
+	 * Extend objects - very similar to jQuery.extend, but deep copy objects, and
+	 * shallow copy arrays. The reason we need to do this, is that we don't want to
+	 * deep copy array init values (such as aaSorting) since the dev wouldn't be
+	 * able to override them, but we do want to deep copy arrays.
+	 *  @param {object} out Object to extend
+	 *  @param {object} extender Object from which the properties will be applied to
+	 *      out
+	 *  @param {boolean} breakRefs If true, then arrays will be sliced to take an
+	 *      independent copy with the exception of the `data` or `aaData` parameters
+	 *      if they are present. This is so you can pass in a collection to
+	 *      DataTables and have that used as your data source without breaking the
+	 *      references
+	 *  @returns {object} out Reference, just for convenience - out === the return.
+	 *  @memberof DataTable#oApi
+	 *  @todo This doesn't take account of arrays inside the deep copied objects.
+	 */
+	function _fnExtend( out, extender, breakRefs )
+	{
+		var val;
+	
+		for ( var prop in extender ) {
+			if ( extender.hasOwnProperty(prop) ) {
+				val = extender[prop];
+	
+				if ( $.isPlainObject( val ) ) {
+					if ( ! $.isPlainObject( out[prop] ) ) {
+						out[prop] = {};
+					}
+					$.extend( true, out[prop], val );
+				}
+				else if ( breakRefs && prop !== 'data' && prop !== 'aaData' && $.isArray(val) ) {
+					out[prop] = val.slice();
+				}
+				else {
+					out[prop] = val;
+				}
+			}
+		}
+	
+		return out;
+	}
+	
+	
+	/**
+	 * Bind an event handers to allow a click or return key to activate the callback.
+	 * This is good for accessibility since a return on the keyboard will have the
+	 * same effect as a click, if the element has focus.
+	 *  @param {element} n Element to bind the action to
+	 *  @param {object} oData Data object to pass to the triggered function
+	 *  @param {function} fn Callback function for when the event is triggered
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnBindAction( n, oData, fn )
+	{
+		$(n)
+			.on( 'click.DT', oData, function (e) {
+					n.blur(); // Remove focus outline for mouse users
+					fn(e);
+				} )
+			.on( 'keypress.DT', oData, function (e){
+					if ( e.which === 13 ) {
+						e.preventDefault();
+						fn(e);
+					}
+				} )
+			.on( 'selectstart.DT', function () {
+					/* Take the brutal approach to cancelling text selection */
+					return false;
+				} );
+	}
+	
+	
+	/**
+	 * Register a callback function. Easily allows a callback function to be added to
+	 * an array store of callback functions that can then all be called together.
+	 *  @param {object} oSettings dataTables settings object
+	 *  @param {string} sStore Name of the array storage for the callbacks in oSettings
+	 *  @param {function} fn Function to be called back
+	 *  @param {string} sName Identifying name for the callback (i.e. a label)
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnCallbackReg( oSettings, sStore, fn, sName )
+	{
+		if ( fn )
+		{
+			oSettings[sStore].push( {
+				"fn": fn,
+				"sName": sName
+			} );
+		}
+	}
+	
+	
+	/**
+	 * Fire callback functions and trigger events. Note that the loop over the
+	 * callback array store is done backwards! Further note that you do not want to
+	 * fire off triggers in time sensitive applications (for example cell creation)
+	 * as its slow.
+	 *  @param {object} settings dataTables settings object
+	 *  @param {string} callbackArr Name of the array storage for the callbacks in
+	 *      oSettings
+	 *  @param {string} eventName Name of the jQuery custom event to trigger. If
+	 *      null no trigger is fired
+	 *  @param {array} args Array of arguments to pass to the callback function /
+	 *      trigger
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnCallbackFire( settings, callbackArr, eventName, args )
+	{
+		var ret = [];
+	
+		if ( callbackArr ) {
+			ret = $.map( settings[callbackArr].slice().reverse(), function (val, i) {
+				return val.fn.apply( settings.oInstance, args );
+			} );
+		}
+	
+		if ( eventName !== null ) {
+			var e = $.Event( eventName+'.dt' );
+	
+			$(settings.nTable).trigger( e, args );
+	
+			ret.push( e.result );
+		}
+	
+		return ret;
+	}
+	
+	
+	function _fnLengthOverflow ( settings )
+	{
+		var
+			start = settings._iDisplayStart,
+			end = settings.fnDisplayEnd(),
+			len = settings._iDisplayLength;
+	
+		/* If we have space to show extra rows (backing up from the end point - then do so */
+		if ( start >= end )
+		{
+			start = end - len;
+		}
+	
+		// Keep the start record on the current page
+		start -= (start % len);
+	
+		if ( len === -1 || start < 0 )
+		{
+			start = 0;
+		}
+	
+		settings._iDisplayStart = start;
+	}
+	
+	
+	function _fnRenderer( settings, type )
+	{
+		var renderer = settings.renderer;
+		var host = DataTable.ext.renderer[type];
+	
+		if ( $.isPlainObject( renderer ) && renderer[type] ) {
+			// Specific renderer for this type. If available use it, otherwise use
+			// the default.
+			return host[renderer[type]] || host._;
+		}
+		else if ( typeof renderer === 'string' ) {
+			// Common renderer - if there is one available for this type use it,
+			// otherwise use the default
+			return host[renderer] || host._;
+		}
+	
+		// Use the default
+		return host._;
+	}
+	
+	
+	/**
+	 * Detect the data source being used for the table. Used to simplify the code
+	 * a little (ajax) and to make it compress a little smaller.
+	 *
+	 *  @param {object} settings dataTables settings object
+	 *  @returns {string} Data source
+	 *  @memberof DataTable#oApi
+	 */
+	function _fnDataSource ( settings )
+	{
+		if ( settings.oFeatures.bServerSide ) {
+			return 'ssp';
+		}
+		else if ( settings.ajax || settings.sAjaxSource ) {
+			return 'ajax';
+		}
+		return 'dom';
+	}
+	
+
+	
+	
+	/**
+	 * Computed structure of the DataTables API, defined by the options passed to
+	 * `DataTable.Api.register()` when building the API.
+	 *
+	 * The structure is built in order to speed creation and extension of the Api
+	 * objects since the extensions are effectively pre-parsed.
+	 *
+	 * The array is an array of objects with the following structure, where this
+	 * base array represents the Api prototype base:
+	 *
+	 *     [
+	 *       {
+	 *         name:      'data'                -- string   - Property name
+	 *         val:       function () {},       -- function - Api method (or undefined if just an object
+	 *         methodExt: [ ... ],              -- array    - Array of Api object definitions to extend the method result
+	 *         propExt:   [ ... ]               -- array    - Array of Api object definitions to extend the property
+	 *       },
+	 *       {
+	 *         name:     'row'
+	 *         val:       {},
+	 *         methodExt: [ ... ],
+	 *         propExt:   [
+	 *           {
+	 *             name:      'data'
+	 *             val:       function () {},
+	 *             methodExt: [ ... ],
+	 *             propExt:   [ ... ]
+	 *           },
+	 *           ...
+	 *         ]
+	 *       }
+	 *     ]
+	 *
+	 * @type {Array}
+	 * @ignore
+	 */
+	var __apiStruct = [];
+	
+	
+	/**
+	 * `Array.prototype` reference.
+	 *
+	 * @type object
+	 * @ignore
+	 */
+	var __arrayProto = Array.prototype;
+	
+	
+	/**
+	 * Abstraction for `context` parameter of the `Api` constructor to allow it to
+	 * take several different forms for ease of use.
+	 *
+	 * Each of the input parameter types will be converted to a DataTables settings
+	 * object where possible.
+	 *
+	 * @param  {string|node|jQuery|object} mixed DataTable identifier. Can be one
+	 *   of:
+	 *
+	 *   * `string` - jQuery selector. Any DataTables' matching the given selector
+	 *     with be found and used.
+	 *   * `node` - `TABLE` node which has already been formed into a DataTable.
+	 *   * `jQuery` - A jQuery object of `TABLE` nodes.
+	 *   * `object` - DataTables settings object
+	 *   * `DataTables.Api` - API instance
+	 * @return {array|null} Matching DataTables settings objects. `null` or
+	 *   `undefined` is returned if no matching DataTable is found.
+	 * @ignore
+	 */
+	var _toSettings = function ( mixed )
+	{
+		var idx, jq;
+		var settings = DataTable.settings;
+		var tables = $.map( settings, function (el, i) {
+			return el.nTable;
+		} );
+	
+		if ( ! mixed ) {
+			return [];
+		}
+		else if ( mixed.nTable && mixed.oApi ) {
+			// DataTables settings object
+			return [ mixed ];
+		}
+		else if ( mixed.nodeName && mixed.nodeName.toLowerCase() === 'table' ) {
+			// Table node
+			idx = $.inArray( mixed, tables );
+			return idx !== -1 ? [ settings[idx] ] : null;
+		}
+		else if ( mixed && typeof mixed.settings === 'function' ) {
+			return mixed.settings().toArray();
+		}
+		else if ( typeof mixed === 'string' ) {
+			// jQuery selector
+			jq = $(mixed);
+		}
+		else if ( mixed instanceof $ ) {
+			// jQuery object (also DataTables instance)
+			jq = mixed;
+		}
+	
+		if ( jq ) {
+			return jq.map( function(i) {
+				idx = $.inArray( this, tables );
+				return idx !== -1 ? settings[idx] : null;
+			} ).toArray();
+		}
+	};
+	
+	
+	/**
+	 * DataTables API class - used to control and interface with  one or more
+	 * DataTables enhanced tables.
+	 *
+	 * The API class is heavily based on jQuery, presenting a chainable interface
+	 * that you can use to interact with tables. Each instance of the API class has
+	 * a "context" - i.e. the tables that it will operate on. This could be a single
+	 * table, all tables on a page or a sub-set thereof.
+	 *
+	 * Additionally the API is designed to allow you to easily work with the data in
+	 * the tables, retrieving and manipulating it as required. This is done by
+	 * presenting the API class as an array like interface. The contents of the
+	 * array depend upon the actions requested by each method (for example
+	 * `rows().nodes()` will return an array of nodes, while `rows().data()` will
+	 * return an array of objects or arrays depending upon your table's
+	 * configuration). The API object has a number of array like methods (`push`,
+	 * `pop`, `reverse` etc) as well as additional helper methods (`each`, `pluck`,
+	 * `unique` etc) to assist your working with the data held in a table.
+	 *
+	 * Most methods (those which return an Api instance) are chainable, which means
+	 * the return from a method call also has all of the methods available that the
+	 * top level object had. For example, these two calls are equivalent:
+	 *
+	 *     // Not chained
+	 *     api.row.add( {...} );
+	 *     api.draw();
+	 *
+	 *     // Chained
+	 *     api.row.add( {...} ).draw();
+	 *
+	 * @class DataTable.Api
+	 * @param {array|object|string|jQuery} context DataTable identifier. This is
+	 *   used to define which DataTables enhanced tables this API will operate on.
+	 *   Can be one of:
+	 *
+	 *   * `string` - jQuery selector. Any DataTables' matching the given selector
+	 *     with be found and used.
+	 *   * `node` - `TABLE` node which has already been formed into a DataTable.
+	 *   * `jQuery` - A jQuery object of `TABLE` nodes.
+	 *   * `object` - DataTables settings object
+	 * @param {array} [data] Data to initialise the Api instance with.
+	 *
+	 * @example
+	 *   // Direct initialisation during DataTables construction
+	 *   var api = $('#example').DataTable();
+	 *
+	 * @example
+	 *   // Initialisation using a DataTables jQuery object
+	 *   var api = $('#example').dataTable().api();
+	 *
+	 * @example
+	 *   // Initialisation as a constructor
+	 *   var api = new $.fn.DataTable.Api( 'table.dataTable' );
+	 */
+	_Api = function ( context, data )
+	{
+		if ( ! (this instanceof _Api) ) {
+			return new _Api( context, data );
+		}
+	
+		var settings = [];
+		var ctxSettings = function ( o ) {
+			var a = _toSettings( o );
+			if ( a ) {
+				settings = settings.concat( a );
+			}
+		};
+	
+		if ( $.isArray( context ) ) {
+			for ( var i=0, ien=context.length ; i<ien ; i++ ) {
+				ctxSettings( context[i] );
+			}
+		}
+		else {
+			ctxSettings( context );
+		}
+	
+		// Remove duplicates
+		this.context = _unique( settings );
+	
+		// Initial data
+		if ( data ) {
+			$.merge( this, data );
+		}
+	
+		// selector
+		this.selector = {
+			rows: null,
+			cols: null,
+			opts: null
+		};
+	
+		_Api.extend( this, this, __apiStruct );
+	};
+	
+	DataTable.Api = _Api;
+	
+	// Don't destroy the existing prototype, just extend it. Required for jQuery 2's
+	// isPlainObject.
+	$.extend( _Api.prototype, {
+		any: function ()
+		{
+			return this.count() !== 0;
+		},
+	
+	
+		concat:  __arrayProto.concat,
+	
+	
+		context: [], // array of table settings objects
+	
+	
+		count: function ()
+		{
+			return this.flatten().length;
+		},
+	
+	
+		each: function ( fn )
+		{
+			for ( var i=0, ien=this.length ; i<ien; i++ ) {
+				fn.call( this, this[i], i, this );
+			}
+	
+			return this;
+		},
+	
+	
+		eq: function ( idx )
+		{
+			var ctx = this.context;
+	
+			return ctx.length > idx ?
+				new _Api( ctx[idx], this[idx] ) :
+				null;
+		},
+	
+	
+		filter: function ( fn )
+		{
+			var a = [];
+	
+			if ( __arrayProto.filter ) {
+				a = __arrayProto.filter.call( this, fn, this );
+			}
+			else {
+				// Compatibility for browsers without EMCA-252-5 (JS 1.6)
+				for ( var i=0, ien=this.length ; i<ien ; i++ ) {
+					if ( fn.call( this, this[i], i, this ) ) {
+						a.push( this[i] );
+					}
+				}
+			}
+	
+			return new _Api( this.context, a );
+		},
+	
+	
+		flatten: function ()
+		{
+			var a = [];
+			return new _Api( this.context, a.concat.apply( a, this.toArray() ) );
+		},
+	
+	
+		join:    __arrayProto.join,
+	
+	
+		indexOf: __arrayProto.indexOf || function (obj, start)
+		{
+			for ( var i=(start || 0), ien=this.length ; i<ien ; i++ ) {
+				if ( this[i] === obj ) {
+					return i;
+				}
+			}
+			return -1;
+		},
+	
+		iterator: function ( flatten, type, fn, alwaysNew ) {
+			var
+				a = [], ret,
+				i, ien, j, jen,
+				context = this.context,
+				rows, items, item,
+				selector = this.selector;
+	
+			// Argument shifting
+			if ( typeof flatten === 'string' ) {
+				alwaysNew = fn;
+				fn = type;
+				type = flatten;
+				flatten = false;
+			}
+	
+			for ( i=0, ien=context.length ; i<ien ; i++ ) {
+				var apiInst = new _Api( context[i] );
+	
+				if ( type === 'table' ) {
+					ret = fn.call( apiInst, context[i], i );
+	
+					if ( ret !== undefined ) {
+						a.push( ret );
+					}
+				}
+				else if ( type === 'columns' || type === 'rows' ) {
+					// this has same length as context - one entry for each table
+					ret = fn.call( apiInst, context[i], this[i], i );
+	
+					if ( ret !== undefined ) {
+						a.push( ret );
+					}
+				}
+				else if ( type === 'column' || type === 'column-rows' || type === 'row' || type === 'cell' ) {
+					// columns and rows share the same structure.
+					// 'this' is an array of column indexes for each context
+					items = this[i];
+	
+					if ( type === 'column-rows' ) {
+						rows = _selector_row_indexes( context[i], selector.opts );
+					}
+	
+					for ( j=0, jen=items.length ; j<jen ; j++ ) {
+						item = items[j];
+	
+						if ( type === 'cell' ) {
+							ret = fn.call( apiInst, context[i], item.row, item.column, i, j );
+						}
+						else {
+							ret = fn.call( apiInst, context[i], item, i, j, rows );
+						}
+	
+						if ( ret !== undefined ) {
+							a.push( ret );
+						}
+					}
+				}
+			}
+	
+			if ( a.length || alwaysNew ) {
+				var api = new _Api( context, flatten ? a.concat.apply( [], a ) : a );
+				var apiSelector = api.selector;
+				apiSelector.rows = selector.rows;
+				apiSelector.cols = selector.cols;
+				apiSelector.opts = selector.opts;
+				return api;
+			}
+			return this;
+		},
+	
+	
+		lastIndexOf: __arrayProto.lastIndexOf || function (obj, start)
+		{
+			// Bit cheeky...
+			return this.indexOf.apply( this.toArray.reverse(), arguments );
+		},
+	
+	
+		length:  0,
+	
+	
+		map: function ( fn )
+		{
+			var a = [];
+	
+			if ( __arrayProto.map ) {
+				a = __arrayProto.map.call( this, fn, this );
+			}
+			else {
+				// Compatibility for browsers without EMCA-252-5 (JS 1.6)
+				for ( var i=0, ien=this.length ; i<ien ; i++ ) {
+					a.push( fn.call( this, this[i], i ) );
+				}
+			}
+	
+			return new _Api( this.context, a );
+		},
+	
+	
+		pluck: function ( prop )
+		{
+			return this.map( function ( el ) {
+				return el[ prop ];
+			} );
+		},
+	
+		pop:     __arrayProto.pop,
+	
+	
+		push:    __arrayProto.push,
+	
+	
+		// Does not return an API instance
+		reduce: __arrayProto.reduce || function ( fn, init )
+		{
+			return _fnReduce( this, fn, init, 0, this.length, 1 );
+		},
+	
+	
+		reduceRight: __arrayProto.reduceRight || function ( fn, init )
+		{
+			return _fnReduce( this, fn, init, this.length-1, -1, -1 );
+		},
+	
+	
+		reverse: __arrayProto.reverse,
+	
+	
+		// Object with rows, columns and opts
+		selector: null,
+	
+	
+		shift:   __arrayProto.shift,
+	
+	
+		slice: function () {
+			return new _Api( this.context, this );
+		},
+	
+	
+		sort:    __arrayProto.sort, // ? name - order?
+	
+	
+		splice:  __arrayProto.splice,
+	
+	
+		toArray: function ()
+		{
+			return __arrayProto.slice.call( this );
+		},
+	
+	
+		to$: function ()
+		{
+			return $( this );
+		},
+	
+	
+		toJQuery: function ()
+		{
+			return $( this );
+		},
+	
+	
+		unique: function ()
+		{
+			return new _Api( this.context, _unique(this) );
+		},
+	
+	
+		unshift: __arrayProto.unshift
+	} );
+	
+	
+	_Api.extend = function ( scope, obj, ext )
+	{
+		// Only extend API instances and static properties of the API
+		if ( ! ext.length || ! obj || ( ! (obj instanceof _Api) && ! obj.__dt_wrapper ) ) {
+			return;
+		}
+	
+		var
+			i, ien,
+			j, jen,
+			struct, inner,
+			methodScoping = function ( scope, fn, struc ) {
+				return function () {
+					var ret = fn.apply( scope, arguments );
+	
+					// Method extension
+					_Api.extend( ret, ret, struc.methodExt );
+					return ret;
+				};
+			};
+	
+		for ( i=0, ien=ext.length ; i<ien ; i++ ) {
+			struct = ext[i];
+	
+			// Value
+			obj[ struct.name ] = typeof struct.val === 'function' ?
+				methodScoping( scope, struct.val, struct ) :
+				$.isPlainObject( struct.val ) ?
+					{} :
+					struct.val;
+	
+			obj[ struct.name ].__dt_wrapper = true;
+	
+			// Property extension
+			_Api.extend( scope, obj[ struct.name ], struct.propExt );
+		}
+	};
+	
+	
+	// @todo - Is there need for an augment function?
+	// _Api.augment = function ( inst, name )
+	// {
+	// 	// Find src object in the structure from the name
+	// 	var parts = name.split('.');
+	
+	// 	_Api.extend( inst, obj );
+	// };
+	
+	
+	//     [
+	//       {
+	//         name:      'data'                -- string   - Property name
+	//         val:       function () {},       -- function - Api method (or undefined if just an object
+	//         methodExt: [ ... ],              -- array    - Array of Api object definitions to extend the method result
+	//         propExt:   [ ... ]               -- array    - Array of Api object definitions to extend the property
+	//       },
+	//       {
+	//         name:     'row'
+	//         val:       {},
+	//         methodExt: [ ... ],
+	//         propExt:   [
+	//           {
+	//             name:      'data'
+	//             val:       function () {},
+	//             methodExt: [ ... ],
+	//             propExt:   [ ... ]
+	//           },
+	//           ...
+	//         ]
+	//       }
+	//     ]
+	
+	_Api.register = _api_register = function ( name, val )
+	{
+		if ( $.isArray( name ) ) {
+			for ( var j=0, jen=name.length ; j<jen ; j++ ) {
+				_Api.register( name[j], val );
+			}
+			return;
+		}
+	
+		var
+			i, ien,
+			heir = name.split('.'),
+			struct = __apiStruct,
+			key, method;
+	
+		var find = function ( src, name ) {
+			for ( var i=0, ien=src.length ; i<ien ; i++ ) {
+				if ( src[i].name === name ) {
+					return src[i];
+				}
+			}
+			return null;
+		};
+	
+		for ( i=0, ien=heir.length ; i<ien ; i++ ) {
+			method = heir[i].indexOf('()') !== -1;
+			key = method ?
+				heir[i].replace('()', '') :
+				heir[i];
+	
+			var src = find( struct, key );
+			if ( ! src ) {
+				src = {
+					name:      key,
+					val:       {},
+					methodExt: [],
+					propExt:   []
+				};
+				struct.push( src );
+			}
+	
+			if ( i === ien-1 ) {
+				src.val = val;
+			}
+			else {
+				struct = method ?
+					src.methodExt :
+					src.propExt;
+			}
+		}
+	};
+	
+	
+	_Api.registerPlural = _api_registerPlural = function ( pluralName, singularName, val ) {
+		_Api.register( pluralName, val );
+	
+		_Api.register( singularName, function () {
+			var ret = val.apply( this, arguments );
+	
+			if ( ret === this ) {
+				// Returned item is the API instance that was passed in, return it
+				return this;
+			}
+			else if ( ret instanceof _Api ) {
+				// New API instance returned, want the value from the first item
+				// in the returned array for the singular result.
+				return ret.length ?
+					$.isArray( ret[0] ) ?
+						new _Api( ret.context, ret[0] ) : // Array results are 'enhanced'
+						ret[0] :
+					undefined;
+			}
+	
+			// Non-API return - just fire it back
+			return ret;
+		} );
+	};
+	
+	
+	/**
+	 * Selector for HTML tables. Apply the given selector to the give array of
+	 * DataTables settings objects.
+	 *
+	 * @param {string|integer} [selector] jQuery selector string or integer
+	 * @param  {array} Array of DataTables settings objects to be filtered
+	 * @return {array}
+	 * @ignore
+	 */
+	var __table_selector = function ( selector, a )
+	{
+		// Integer is used to pick out a table by index
+		if ( typeof selector === 'number' ) {
+			return [ a[ selector ] ];
+		}
+	
+		// Perform a jQuery selector on the table nodes
+		var nodes = $.map( a, function (el, i) {
+			return el.nTable;
+		} );
+	
+		return $(nodes)
+			.filter( selector )
+			.map( function (i) {
+				// Need to translate back from the table node to the settings
+				var idx = $.inArray( this, nodes );
+				return a[ idx ];
+			} )
+			.toArray();
+	};
+	
+	
+	
+	/**
+	 * Context selector for the API's context (i.e. the tables the API instance
+	 * refers to.
+	 *
+	 * @name    DataTable.Api#tables
+	 * @param {string|integer} [selector] Selector to pick which tables the iterator
+	 *   should operate on. If not given, all tables in the current context are
+	 *   used. This can be given as a jQuery selector (for example `':gt(0)'`) to
+	 *   select multiple tables or as an integer to select a single table.
+	 * @returns {DataTable.Api} Returns a new API instance if a selector is given.
+	 */
+	_api_register( 'tables()', function ( selector ) {
+		// A new instance is created if there was a selector specified
+		return selector ?
+			new _Api( __table_selector( selector, this.context ) ) :
+			this;
+	} );
+	
+	
+	_api_register( 'table()', function ( selector ) {
+		var tables = this.tables( selector );
+		var ctx = tables.context;
+	
+		// Truncate to the first matched table
+		return ctx.length ?
+			new _Api( ctx[0] ) :
+			tables;
+	} );
+	
+	
+	_api_registerPlural( 'tables().nodes()', 'table().node()' , function () {
+		return this.iterator( 'table', function ( ctx ) {
+			return ctx.nTable;
+		}, 1 );
+	} );
+	
+	
+	_api_registerPlural( 'tables().body()', 'table().body()' , function () {
+		return this.iterator( 'table', function ( ctx ) {
+			return ctx.nTBody;
+		}, 1 );
+	} );
+	
+	
+	_api_registerPlural( 'tables().header()', 'table().header()' , function () {
+		return this.iterator( 'table', function ( ctx ) {
+			return ctx.nTHead;
+		}, 1 );
+	} );
+	
+	
+	_api_registerPlural( 'tables().footer()', 'table().footer()' , function () {
+		return this.iterator( 'table', function ( ctx ) {
+			return ctx.nTFoot;
+		}, 1 );
+	} );
+	
+	
+	_api_registerPlural( 'tables().containers()', 'table().container()' , function () {
+		return this.iterator( 'table', function ( ctx ) {
+			return ctx.nTableWrapper;
+		}, 1 );
+	} );
+	
+	
+	
+	/**
+	 * Redraw the tables in the current context.
+	 */
+	_api_register( 'draw()', function ( paging ) {
+		return this.iterator( 'table', function ( settings ) {
+			if ( paging === 'page' ) {
+				_fnDraw( settings );
+			}
+			else {
+				if ( typeof paging === 'string' ) {
+					paging = paging === 'full-hold' ?
+						false :
+						true;
+				}
+	
+				_fnReDraw( settings, paging===false );
+			}
+		} );
+	} );
+	
+	
+	
+	/**
+	 * Get the current page index.
+	 *
+	 * @return {integer} Current page index (zero based)
+	 *//**
+	 * Set the current page.
+	 *
+	 * Note that if you attempt to show a page which does not exist, DataTables will
+	 * not throw an error, but rather reset the paging.
+	 *
+	 * @param {integer|string} action The paging action to take. This can be one of:
+	 *  * `integer` - The page index to jump to
+	 *  * `string` - An action to take:
+	 *    * `first` - Jump to first page.
+	 *    * `next` - Jump to the next page
+	 *    * `previous` - Jump to previous page
+	 *    * `last` - Jump to the last page.
+	 * @returns {DataTables.Api} this
+	 */
+	_api_register( 'page()', function ( action ) {
+		if ( action === undefined ) {
+			return this.page.info().page; // not an expensive call
+		}
+	
+		// else, have an action to take on all tables
+		return this.iterator( 'table', function ( settings ) {
+			_fnPageChange( settings, action );
+		} );
+	} );
+	
+	
+	/**
+	 * Paging information for the first table in the current context.
+	 *
+	 * If you require paging information for another table, use the `table()` method
+	 * with a suitable selector.
+	 *
+	 * @return {object} Object with the following properties set:
+	 *  * `page` - Current page index (zero based - i.e. the first page is `0`)
+	 *  * `pages` - Total number of pages
+	 *  * `start` - Display index for the first record shown on the current page
+	 *  * `end` - Display index for the last record shown on the current page
+	 *  * `length` - Display length (number of records). Note that generally `start
+	 *    + length = end`, but this is not always true, for example if there are
+	 *    only 2 records to show on the final page, with a length of 10.
+	 *  * `recordsTotal` - Full data set length
+	 *  * `recordsDisplay` - Data set length once the current filtering criterion
+	 *    are applied.
+	 */
+	_api_register( 'page.info()', function ( action ) {
+		if ( this.context.length === 0 ) {
+			return undefined;
+		}
+	
+		var
+			settings   = this.context[0],
+			start      = settings._iDisplayStart,
+			len        = settings.oFeatures.bPaginate ? settings._iDisplayLength : -1,
+			visRecords = settings.fnRecordsDisplay(),
+			all        = len === -1;
+	
+		return {
+			"page":           all ? 0 : Math.floor( start / len ),
+			"pages":          all ? 1 : Math.ceil( visRecords / len ),
+			"start":          start,
+			"end":            settings.fnDisplayEnd(),
+			"length":         len,
+			"recordsTotal":   settings.fnRecordsTotal(),
+			"recordsDisplay": visRecords,
+			"serverSide":     _fnDataSource( settings ) === 'ssp'
+		};
+	} );
+	
+	
+	/**
+	 * Get the current page length.
+	 *
+	 * @return {integer} Current page length. Note `-1` indicates that all records
+	 *   are to be shown.
+	 *//**
+	 * Set the current page length.
+	 *
+	 * @param {integer} Page length to set. Use `-1` to show all records.
+	 * @returns {DataTables.Api} this
+	 */
+	_api_register( 'page.len()', function ( len ) {
+		// Note that we can't call this function 'length()' because `length`
+		// is a Javascript property of functions which defines how many arguments
+		// the function expects.
+		if ( len === undefined ) {
+			return this.context.length !== 0 ?
+				this.context[0]._iDisplayLength :
+				undefined;
+		}
+	
+		// else, set the page length
+		return this.iterator( 'table', function ( settings ) {
+			_fnLengthChange( settings, len );
+		} );
+	} );
+	
+	
+	
+	var __reload = function ( settings, holdPosition, callback ) {
+		// Use the draw event to trigger a callback
+		if ( callback ) {
+			var api = new _Api( settings );
+	
+			api.one( 'draw', function () {
+				callback( api.ajax.json() );
+			} );
+		}
+	
+		if ( _fnDataSource( settings ) == 'ssp' ) {
+			_fnReDraw( settings, holdPosition );
+		}
+		else {
+			_fnProcessingDisplay( settings, true );
+	
+			// Cancel an existing request
+			var xhr = settings.jqXHR;
+			if ( xhr && xhr.readyState !== 4 ) {
+				xhr.abort();
+			}
+	
+			// Trigger xhr
+			_fnBuildAjax( settings, [], function( json ) {
+				_fnClearTable( settings );
+	
+				var data = _fnAjaxDataSrc( settings, json );
+				for ( var i=0, ien=data.length ; i<ien ; i++ ) {
+					_fnAddData( settings, data[i] );
+				}
+	
+				_fnReDraw( settings, holdPosition );
+				_fnProcessingDisplay( settings, false );
+			} );
+		}
+	};
+	
+	
+	/**
+	 * Get the JSON response from the last Ajax request that DataTables made to the
+	 * server. Note that this returns the JSON from the first table in the current
+	 * context.
+	 *
+	 * @return {object} JSON received from the server.
+	 */
+	_api_register( 'ajax.json()', function () {
+		var ctx = this.context;
+	
+		if ( ctx.length > 0 ) {
+			return ctx[0].json;
+		}
+	
+		// else return undefined;
+	} );
+	
+	
+	/**
+	 * Get the data submitted in the last Ajax request
+	 */
+	_api_register( 'ajax.params()', function () {
+		var ctx = this.context;
+	
+		if ( ctx.length > 0 ) {
+			return ctx[0].oAjaxData;
+		}
+	
+		// else return undefined;
+	} );
+	
+	
+	/**
+	 * Reload tables from the Ajax data source. Note that this function will
+	 * automatically re-draw the table when the remote data has been loaded.
+	 *
+	 * @param {boolean} [reset=true] Reset (default) or hold the current paging
+	 *   position. A full re-sort and re-filter is performed when this method is
+	 *   called, which is why the pagination reset is the default action.
+	 * @returns {DataTables.Api} this
+	 */
+	_api_register( 'ajax.reload()', function ( callback, resetPaging ) {
+		return this.iterator( 'table', function (settings) {
+			__reload( settings, resetPaging===false, callback );
+		} );
+	} );
+	
+	
+	/**
+	 * Get the current Ajax URL. Note that this returns the URL from the first
+	 * table in the current context.
+	 *
+	 * @return {string} Current Ajax source URL
+	 *//**
+	 * Set the Ajax URL. Note that this will set the URL for all tables in the
+	 * current context.
+	 *
+	 * @param {string} url URL to set.
+	 * @returns {DataTables.Api} this
+	 */
+	_api_register( 'ajax.url()', function ( url ) {
+		var ctx = this.context;
+	
+		if ( url === undefined ) {
+			// get
+			if ( ctx.length === 0 ) {
+				return undefined;
+			}
+			ctx = ctx[0];
+	
+			return ctx.ajax ?
+				$.isPlainObject( ctx.ajax ) ?
+					ctx.ajax.url :
+					ctx.ajax :
+				ctx.sAjaxSource;
+		}
+	
+		// set
+		return this.iterator( 'table', function ( settings ) {
+			if ( $.isPlainObject( settings.ajax ) ) {
+				settings.ajax.url = url;
+			}
+			else {
+				settings.ajax = url;
+			}
+			// No need to consider sAjaxSource here since DataTables gives priority
+			// to `ajax` over `sAjaxSource`. So setting `ajax` here, renders any
+			// value of `sAjaxSource` redundant.
+		} );
+	} );
+	
+	
+	/**
+	 * Load data from the newly set Ajax URL. Note that this method is only
+	 * available when `ajax.url()` is used to set a URL. Additionally, this method
+	 * has the same effect as calling `ajax.reload()` but is provided for
+	 * convenience when setting a new URL. Like `ajax.reload()` it will
+	 * automatically redraw the table once the remote data has been loaded.
+	 *
+	 * @returns {DataTables.Api} this
+	 */
+	_api_register( 'ajax.url().load()', function ( callback, resetPaging ) {
+		// Same as a reload, but makes sense to present it for easy access after a
+		// url change
+		return this.iterator( 'table', function ( ctx ) {
+			__reload( ctx, resetPaging===false, callback );
+		} );
+	} );
+	
+	
+	
+	
+	var _selector_run = function ( type, selector, selectFn, settings, opts )
+	{
+		var
+			out = [], res,
+			a, i, ien, j, jen,
+			selectorType = typeof selector;
+	
+		// Can't just check for isArray here, as an API or jQuery instance might be
+		// given with their array like look
+		if ( ! selector || selectorType === 'string' || selectorType === 'function' || selector.length === undefined ) {
+			selector = [ selector ];
+		}
+	
+		for ( i=0, ien=selector.length ; i<ien ; i++ ) {
+			// Only split on simple strings - complex expressions will be jQuery selectors
+			a = selector[i] && selector[i].split && ! selector[i].match(/[\[\(:]/) ?
+				selector[i].split(',') :
+				[ selector[i] ];
+	
+			for ( j=0, jen=a.length ; j<jen ; j++ ) {
+				res = selectFn( typeof a[j] === 'string' ? $.trim(a[j]) : a[j] );
+	
+				if ( res && res.length ) {
+					out = out.concat( res );
+				}
+			}
+		}
+	
+		// selector extensions
+		var ext = _ext.selector[ type ];
+		if ( ext.length ) {
+			for ( i=0, ien=ext.length ; i<ien ; i++ ) {
+				out = ext[i]( settings, opts, out );
+			}
+		}
+	
+		return _unique( out );
+	};
+	
+	
+	var _selector_opts = function ( opts )
+	{
+		if ( ! opts ) {
+			opts = {};
+		}
+	
+		// Backwards compatibility for 1.9- which used the terminology filter rather
+		// than search
+		if ( opts.filter && opts.search === undefined ) {
+			opts.search = opts.filter;
+		}
+	
+		return $.extend( {
+			search: 'none',
+			order: 'current',
+			page: 'all'
+		}, opts );
+	};
+	
+	
+	var _selector_first = function ( inst )
+	{
+		// Reduce the API instance to the first item found
+		for ( var i=0, ien=inst.length ; i<ien ; i++ ) {
+			if ( inst[i].length > 0 ) {
+				// Assign the first element to the first item in the instance
+				// and truncate the instance and context
+				inst[0] = inst[i];
+				inst[0].length = 1;
+				inst.length = 1;
+				inst.context = [ inst.context[i] ];
+	
+				return inst;
+			}
+		}
+	
+		// Not found - return an empty instance
+		inst.length = 0;
+		return inst;
+	};
+	
+	
+	var _selector_row_indexes = function ( settings, opts )
+	{
+		var
+			i, ien, tmp, a=[],
+			displayFiltered = settings.aiDisplay,
+			displayMaster = settings.aiDisplayMaster;
+	
+		var
+			search = opts.search,  // none, applied, removed
+			order  = opts.order,   // applied, current, index (original - compatibility with 1.9)
+			page   = opts.page;    // all, current
+	
+		if ( _fnDataSource( settings ) == 'ssp' ) {
+			// In server-side processing mode, most options are irrelevant since
+			// rows not shown don't exist and the index order is the applied order
+			// Removed is a special case - for consistency just return an empty
+			// array
+			return search === 'removed' ?
+				[] :
+				_range( 0, displayMaster.length );
+		}
+		else if ( page == 'current' ) {
+			// Current page implies that order=current and fitler=applied, since it is
+			// fairly senseless otherwise, regardless of what order and search actually
+			// are
+			for ( i=settings._iDisplayStart, ien=settings.fnDisplayEnd() ; i<ien ; i++ ) {
+				a.push( displayFiltered[i] );
+			}
+		}
+		else if ( order == 'current' || order == 'applied' ) {
+			a = search == 'none' ?
+				displayMaster.slice() :                      // no search
+				search == 'applied' ?
+					displayFiltered.slice() :                // applied search
+					$.map( displayMaster, function (el, i) { // removed search
+						return $.inArray( el, displayFiltered ) === -1 ? el : null;
+					} );
+		}
+		else if ( order == 'index' || order == 'original' ) {
+			for ( i=0, ien=settings.aoData.length ; i<ien ; i++ ) {
+				if ( search == 'none' ) {
+					a.push( i );
+				}
+				else { // applied | removed
+					tmp = $.inArray( i, displayFiltered );
+	
+					if ((tmp === -1 && search == 'removed') ||
+						(tmp >= 0   && search == 'applied') )
+					{
+						a.push( i );
+					}
+				}
+			}
+		}
+	
+		return a;
+	};
+	
+	
+	/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
+	 * Rows
+	 *
+	 * {}          - no selector - use all available rows
+	 * {integer}   - row aoData index
+	 * {node}      - TR node
+	 * {string}    - jQuery selector to apply to the TR elements
+	 * {array}     - jQuery array of nodes, or simply an array of TR nodes
+	 *
+	 */
+	
+	
+	var __row_selector = function ( settings, selector, opts )
+	{
+		var rows;
+		var run = function ( sel ) {
+			var selInt = _intVal( sel );
+			var i, ien;
+	
+			// Short cut - selector is a number and no options provided (default is
+			// all records, so no need to check if the index is in there, since it
+			// must be - dev error if the index doesn't exist).
+			if ( selInt !== null && ! opts ) {
+				return [ selInt ];
+			}
+	
+			if ( ! rows ) {
+				rows = _selector_row_indexes( settings, opts );
+			}
+	
+			if ( selInt !== null && $.inArray( selInt, rows ) !== -1 ) {
+				// Selector - integer
+				return [ selInt ];
+			}
+			else if ( sel === null || sel === undefined || sel === '' ) {
+				// Selector - none
+				return rows;
+			}
+	
+			// Selector - function
+			if ( typeof sel === 'function' ) {
+				return $.map( rows, function (idx) {
+					var row = settings.aoData[ idx ];
+					return sel( idx, row._aData, row.nTr ) ? idx : null;
+				} );
+			}
+	
+			// Get nodes in the order from the `rows` array with null values removed
+			var nodes = _removeEmpty(
+				_pluck_order( settings.aoData, rows, 'nTr' )
+			);
+	
+			// Selector - node
+			if ( sel.nodeName ) {
+				if ( sel._DT_RowIndex !== undefined ) {
+					return [ sel._DT_RowIndex ]; // Property added by DT for fast lookup
+				}
+				else if ( sel._DT_CellIndex ) {
+					return [ sel._DT_CellIndex.row ];
+				}
+				else {
+					var host = $(sel).closest('*[data-dt-row]');
+					return host.length ?
+						[ host.data('dt-row') ] :
+						[];
+				}
+			}
+	
+			// ID selector. Want to always be able to select rows by id, regardless
+			// of if the tr element has been created or not, so can't rely upon
+			// jQuery here - hence a custom implementation. This does not match
+			// Sizzle's fast selector or HTML4 - in HTML5 the ID can be anything,
+			// but to select it using a CSS selector engine (like Sizzle or
+			// querySelect) it would need to need to be escaped for some characters.
+			// DataTables simplifies this for row selectors since you can select
+			// only a row. A # indicates an id any anything that follows is the id -
+			// unescaped.
+			if ( typeof sel === 'string' && sel.charAt(0) === '#' ) {
+				// get row index from id
+				var rowObj = settings.aIds[ sel.replace( /^#/, '' ) ];
+				if ( rowObj !== undefined ) {
+					return [ rowObj.idx ];
+				}
+	
+				// need to fall through to jQuery in case there is DOM id that
+				// matches
+			}
+	
+			// Selector - jQuery selector string, array of nodes or jQuery object/
+			// As jQuery's .filter() allows jQuery objects to be passed in filter,
+			// it also allows arrays, so this will cope with all three options
+			return $(nodes)
+				.filter( sel )
+				.map( function () {
+					return this._DT_RowIndex;
+				} )
+				.toArray();
+		};
+	
+		return _selector_run( 'row', selector, run, settings, opts );
+	};
+	
+	
+	_api_register( 'rows()', function ( selector, opts ) {
+		// argument shifting
+		if ( selector === undefined ) {
+			selector = '';
+		}
+		else if ( $.isPlainObject( selector ) ) {
+			opts = selector;
+			selector = '';
+		}
+	
+		opts = _selector_opts( opts );
+	
+		var inst = this.iterator( 'table', function ( settings ) {
+			return __row_selector( settings, selector, opts );
+		}, 1 );
+	
+		// Want argument shifting here and in __row_selector?
+		inst.selector.rows = selector;
+		inst.selector.opts = opts;
+	
+		return inst;
+	} );
+	
+	_api_register( 'rows().nodes()', function () {
+		return this.iterator( 'row', function ( settings, row ) {
+			return settings.aoData[ row ].nTr || undefined;
+		}, 1 );
+	} );
+	
+	_api_register( 'rows().data()', function () {
+		return this.iterator( true, 'rows', function ( settings, rows ) {
+			return _pluck_order( settings.aoData, rows, '_aData' );
+		}, 1 );
+	} );
+	
+	_api_registerPlural( 'rows().cache()', 'row().cache()', function ( type ) {
+		return this.iterator( 'row', function ( settings, row ) {
+			var r = settings.aoData[ row ];
+			return type === 'search' ? r._aFilterData : r._aSortData;
+		}, 1 );
+	} );
+	
+	_api_registerPlural( 'rows().invalidate()', 'row().invalidate()', function ( src ) {
+		return this.iterator( 'row', function ( settings, row ) {
+			_fnInvalidate( settings, row, src );
+		} );
+	} );
+	
+	_api_registerPlural( 'rows().indexes()', 'row().index()', function () {
+		return this.iterator( 'row', function ( settings, row ) {
+			return row;
+		}, 1 );
+	} );
+	
+	_api_registerPlural( 'rows().ids()', 'row().id()', function ( hash ) {
+		var a = [];
+		var context = this.context;
+	
+		// `iterator` will drop undefined values, but in this case we want them
+		for ( var i=0, ien=context.length ; i<ien ; i++ ) {
+			for ( var j=0, jen=this[i].length ; j<jen ; j++ ) {
+				var id = context[i].rowIdFn( context[i].aoData[ this[i][j] ]._aData );
+				a.push( (hash === true ? '#' : '' )+ id );
+			}
+		}
+	
+		return new _Api( context, a );
+	} );
+	
+	_api_registerPlural( 'rows().remove()', 'row().remove()', function () {
+		var that = this;
+	
+		this.iterator( 'row', function ( settings, row, thatIdx ) {
+			var data = settings.aoData;
+			var rowData = data[ row ];
+			var i, ien, j, jen;
+			var loopRow, loopCells;
+	
+			data.splice( row, 1 );
+	
+			// Update the cached indexes
+			for ( i=0, ien=data.length ; i<ien ; i++ ) {
+				loopRow = data[i];
+				loopCells = loopRow.anCells;
+	
+				// Rows
+				if ( loopRow.nTr !== null ) {
+					loopRow.nTr._DT_RowIndex = i;
+				}
+	
+				// Cells
+				if ( loopCells !== null ) {
+					for ( j=0, jen=loopCells.length ; j<jen ; j++ ) {
+						loopCells[j]._DT_CellIndex.row = i;
+					}
+				}
+			}
+	
+			// Delete from the display arrays
+			_fnDeleteIndex( settings.aiDisplayMaster, row );
+			_fnDeleteIndex( settings.aiDisplay, row );
+			_fnDeleteIndex( that[ thatIdx ], row, false ); // maintain local indexes
+	
+			// For server-side processing tables - subtract the deleted row from the count
+			if ( settings._iRecordsDisplay > 0 ) {
+				settings._iRecordsDisplay--;
+			}
+	
+			// Check for an 'overflow' they case for displaying the table
+			_fnLengthOverflow( settings );
+	
+			// Remove the row's ID reference if there is one
+			var id = settings.rowIdFn( rowData._aData );
+			if ( id !== undefined ) {
+				delete settings.aIds[ id ];
+			}
+		} );
+	
+		this.iterator( 'table', function ( settings ) {
+			for ( var i=0, ien=settings.aoData.length ; i<ien ; i++ ) {
+				settings.aoData[i].idx = i;
+			}
+		} );
+	
+		return this;
+	} );
+	
+	
+	_api_register( 'rows.add()', function ( rows ) {
+		var newRows = this.iterator( 'table', function ( settings ) {
+				var row, i, ien;
+				var out = [];
+	
+				for ( i=0, ien=rows.length ; i<ien ; i++ ) {
+					row = rows[i];
+	
+					if ( row.nodeName && row.nodeName.toUpperCase() === 'TR' ) {
+						out.push( _fnAddTr( settings, row )[0] );
+					}
+					else {
+						out.push( _fnAddData( settings, row ) );
+					}
+				}
+	
+				return out;
+			}, 1 );
+	
+		// Return an Api.rows() extended instance, so rows().nodes() etc can be used
+		var modRows = this.rows( -1 );
+		modRows.pop();
+		$.merge( modRows, newRows );
+	
+		return modRows;
+	} );
+	
+	
+	
+	
+	
+	/**
+	 *
+	 */
+	_api_register( 'row()', function ( selector, opts ) {
+		return _selector_first( this.rows( selector, opts ) );
+	} );
+	
+	
+	_api_register( 'row().data()', function ( data ) {
+		var ctx = this.context;
+	
+		if ( data === undefined ) {
+			// Get
+			return ctx.length && this.length ?
+				ctx[0].aoData[ this[0] ]._aData :
+				undefined;
+		}
+	
+		// Set
+		ctx[0].aoData[ this[0] ]._aData = data;
+	
+		// Automatically invalidate
+		_fnInvalidate( ctx[0], this[0], 'data' );
+	
+		return this;
+	} );
+	
+	
+	_api_register( 'row().node()', function () {
+		var ctx = this.context;
+	
+		return ctx.length && this.length ?
+			ctx[0].aoData[ this[0] ].nTr || null :
+			null;
+	} );
+	
+	
+	_api_register( 'row.add()', function ( row ) {
+		// Allow a jQuery object to be passed in - only a single row is added from
+		// it though - the first element in the set
+		if ( row instanceof $ && row.length ) {
+			row = row[0];
+		}
+	
+		var rows = this.iterator( 'table', function ( settings ) {
+			if ( row.nodeName && row.nodeName.toUpperCase() === 'TR' ) {
+				return _fnAddTr( settings, row )[0];
+			}
+			return _fnAddData( settings, row );
+		} );
+	
+		// Return an Api.rows() extended instance, with the newly added row selected
+		return this.row( rows[0] );
+	} );
+	
+	
+	
+	var __details_add = function ( ctx, row, data, klass )
+	{
+		// Convert to array of TR elements
+		var rows = [];
+		var addRow = function ( r, k ) {
+			// Recursion to allow for arrays of jQuery objects
+			if ( $.isArray( r ) || r instanceof $ ) {
+				for ( var i=0, ien=r.length ; i<ien ; i++ ) {
+					addRow( r[i], k );
+				}
+				return;
+			}
+	
+			// If we get a TR element, then just add it directly - up to the dev
+			// to add the correct number of columns etc
+			if ( r.nodeName && r.nodeName.toLowerCase() === 'tr' ) {
+				rows.push( r );
+			}
+			else {
+				// Otherwise create a row with a wrapper
+				var created = $('<tr><td/></tr>').addClass( k );
+				$('td', created)
+					.addClass( k )
+					.html( r )
+					[0].colSpan = _fnVisbleColumns( ctx );
+	
+				rows.push( created[0] );
+			}
+		};
+	
+		addRow( data, klass );
+	
+		if ( row._details ) {
+			row._details.detach();
+		}
+	
+		row._details = $(rows);
+	
+		// If the children were already shown, that state should be retained
+		if ( row._detailsShow ) {
+			row._details.insertAfter( row.nTr );
+		}
+	};
+	
+	
+	var __details_remove = function ( api, idx )
+	{
+		var ctx = api.context;
+	
+		if ( ctx.length ) {
+			var row = ctx[0].aoData[ idx !== undefined ? idx : api[0] ];
+	
+			if ( row && row._details ) {
+				row._details.remove();
+	
+				row._detailsShow = undefined;
+				row._details = undefined;
+			}
+		}
+	};
+	
+	
+	var __details_display = function ( api, show ) {
+		var ctx = api.context;
+	
+		if ( ctx.length && api.length ) {
+			var row = ctx[0].aoData[ api[0] ];
+	
+			if ( row._details ) {
+				row._detailsShow = show;
+	
+				if ( show ) {
+					row._details.insertAfter( row.nTr );
+				}
+				else {
+					row._details.detach();
+				}
+	
+				__details_events( ctx[0] );
+			}
+		}
+	};
+	
+	
+	var __details_events = function ( settings )
+	{
+		var api = new _Api( settings );
+		var namespace = '.dt.DT_details';
+		var drawEvent = 'draw'+namespace;
+		var colvisEvent = 'column-visibility'+namespace;
+		var destroyEvent = 'destroy'+namespace;
+		var data = settings.aoData;
+	
+		api.off( drawEvent +' '+ colvisEvent +' '+ destroyEvent );
+	
+		if ( _pluck( data, '_details' ).length > 0 ) {
+			// On each draw, insert the required elements into the document
+			api.on( drawEvent, function ( e, ctx ) {
+				if ( settings !== ctx ) {
+					return;
+				}
+	
+				api.rows( {page:'current'} ).eq(0).each( function (idx) {
+					// Internal data grab
+					var row = data[ idx ];
+	
+					if ( row._detailsShow ) {
+						row._details.insertAfter( row.nTr );
+					}
+				} );
+			} );
+	
+			// Column visibility change - update the colspan
+			api.on( colvisEvent, function ( e, ctx, idx, vis ) {
+				if ( settings !== ctx ) {
+					return;
+				}
+	
+				// Update the colspan for the details rows (note, only if it already has
+				// a colspan)
+				var row, visible = _fnVisbleColumns( ctx );
+	
+				for ( var i=0, ien=data.length ; i<ien ; i++ ) {
+					row = data[i];
+	
+					if ( row._details ) {
+						row._details.children('td[colspan]').attr('colspan', visible );
+					}
+				}
+			} );
+	
+			// Table destroyed - nuke any child rows
+			api.on( destroyEvent, function ( e, ctx ) {
+				if ( settings !== ctx ) {
+					return;
+				}
+	
+				for ( var i=0, ien=data.length ; i<ien ; i++ ) {
+					if ( data[i]._details ) {
+						__details_remove( api, i );
+					}
+				}
+			} );
+		}
+	};
+	
+	// Strings for the method names to help minification
+	var _emp = '';
+	var _child_obj = _emp+'row().child';
+	var _child_mth = _child_obj+'()';
+	
+	// data can be:
+	//  tr
+	//  string
+	//  jQuery or array of any of the above
+	_api_register( _child_mth, function ( data, klass ) {
+		var ctx = this.context;
+	
+		if ( data === undefined ) {
+			// get
+			return ctx.length && this.length ?
+				ctx[0].aoData[ this[0] ]._details :
+				undefined;
+		}
+		else if ( data === true ) {
+			// show
+			this.child.show();
+		}
+		else if ( data === false ) {
+			// remove
+			__details_remove( this );
+		}
+		else if ( ctx.length && this.length ) {
+			// set
+			__details_add( ctx[0], ctx[0].aoData[ this[0] ], data, klass );
+		}
+	
+		return this;
+	} );
+	
+	
+	_api_register( [
+		_child_obj+'.show()',
+		_child_mth+'.show()' // only when `child()` was called with parameters (without
+	], function ( show ) {   // it returns an object and this method is not executed)
+		__details_display( this, true );
+		return this;
+	} );
+	
+	
+	_api_register( [
+		_child_obj+'.hide()',
+		_child_mth+'.hide()' // only when `child()` was called with parameters (without
+	], function () {         // it returns an object and this method is not executed)
+		__details_display( this, false );
+		return this;
+	} );
+	
+	
+	_api_register( [
+		_child_obj+'.remove()',
+		_child_mth+'.remove()' // only when `child()` was called with parameters (without
+	], function () {           // it returns an object and this method is not executed)
+		__details_remove( this );
+		return this;
+	} );
+	
+	
+	_api_register( _child_obj+'.isShown()', function () {
+		var ctx = this.context;
+	
+		if ( ctx.length && this.length ) {
+			// _detailsShown as false or undefined will fall through to return false
+			return ctx[0].aoData[ this[0] ]._detailsShow || false;
+		}
+		return false;
+	} );
+	
+	
+	
+	/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
+	 * Columns
+	 *
+	 * {integer}           - column index (>=0 count from left, <0 count from right)
+	 * "{integer}:visIdx"  - visible column index (i.e. translate to column index)  (>=0 count from left, <0 count from right)
+	 * "{integer}:visible" - alias for {integer}:visIdx  (>=0 count from left, <0 count from right)
+	 * "{string}:name"     - column name
+	 * "{string}"          - jQuery selector on column header nodes
+	 *
+	 */
+	
+	// can be an array of these items, comma separated list, or an array of comma
+	// separated lists
+	
+	var __re_column_selector = /^([^:]+):(name|visIdx|visible)$/;
+	
+	
+	// r1 and r2 are redundant - but it means that the parameters match for the
+	// iterator callback in columns().data()
+	var __columnData = function ( settings, column, r1, r2, rows ) {
+		var a = [];
+		for ( var row=0, ien=rows.length ; row<ien ; row++ ) {
+			a.push( _fnGetCellData( settings, rows[row], column ) );
+		}
+		return a;
+	};
+	
+	
+	var __column_selector = function ( settings, selector, opts )
+	{
+		var
+			columns = settings.aoColumns,
+			names = _pluck( columns, 'sName' ),
+			nodes = _pluck( columns, 'nTh' );
+	
+		var run = function ( s ) {
+			var selInt = _intVal( s );
+	
+			// Selector - all
+			if ( s === '' ) {
+				return _range( columns.length );
+			}
+	
+			// Selector - index
+			if ( selInt !== null ) {
+				return [ selInt >= 0 ?
+					selInt : // Count from left
+					columns.length + selInt // Count from right (+ because its a negative value)
+				];
+			}
+	
+			// Selector = function
+			if ( typeof s === 'function' ) {
+				var rows = _selector_row_indexes( settings, opts );
+	
+				return $.map( columns, function (col, idx) {
+					return s(
+							idx,
+							__columnData( settings, idx, 0, 0, rows ),
+							nodes[ idx ]
+						) ? idx : null;
+				} );
+			}
+	
+			// jQuery or string selector
+			var match = typeof s === 'string' ?
+				s.match( __re_column_selector ) :
+				'';
+	
+			if ( match ) {
+				switch( match[2] ) {
+					case 'visIdx':
+					case 'visible':
+						var idx = parseInt( match[1], 10 );
+						// Visible index given, convert to column index
+						if ( idx < 0 ) {
+							// Counting from the right
+							var visColumns = $.map( columns, function (col,i) {
+								return col.bVisible ? i : null;
+							} );
+							return [ visColumns[ visColumns.length + idx ] ];
+						}
+						// Counting from the left
+						return [ _fnVisibleToColumnIndex( settings, idx ) ];
+	
+					case 'name':
+						// match by name. `names` is column index complete and in order
+						return $.map( names, function (name, i) {
+							return name === match[1] ? i : null;
+						} );
+	
+					default:
+						return [];
+				}
+			}
+	
+			// Cell in the table body
+			if ( s.nodeName && s._DT_CellIndex ) {
+				return [ s._DT_CellIndex.column ];
+			}
+	
+			// jQuery selector on the TH elements for the columns
+			var jqResult = $( nodes )
+				.filter( s )
+				.map( function () {
+					return $.inArray( this, nodes ); // `nodes` is column index complete and in order
+				} )
+				.toArray();
+	
+			if ( jqResult.length || ! s.nodeName ) {
+				return jqResult;
+			}
+	
+			// Otherwise a node which might have a `dt-column` data attribute, or be
+			// a child or such an element
+			var host = $(s).closest('*[data-dt-column]');
+			return host.length ?
+				[ host.data('dt-column') ] :
+				[];
+		};
+	
+		return _selector_run( 'column', selector, run, settings, opts );
+	};
+	
+	
+	var __setColumnVis = function ( settings, column, vis ) {
+		var
+			cols = settings.aoColumns,
+			col  = cols[ column ],
+			data = settings.aoData,
+			row, cells, i, ien, tr;
+	
+		// Get
+		if ( vis === undefined ) {
+			return col.bVisible;
+		}
+	
+		// Set
+		// No change
+		if ( col.bVisible === vis ) {
+			return;
+		}
+	
+		if ( vis ) {
+			// Insert column
+			// Need to decide if we should use appendChild or insertBefore
+			var insertBefore = $.inArray( true, _pluck(cols, 'bVisible'), column+1 );
+	
+			for ( i=0, ien=data.length ; i<ien ; i++ ) {
+				tr = data[i].nTr;
+				cells = data[i].anCells;
+	
+				if ( tr ) {
+					// insertBefore can act like appendChild if 2nd arg is null
+					tr.insertBefore( cells[ column ], cells[ insertBefore ] || null );
+				}
+			}
+		}
+		else {
+			// Remove column
+			$( _pluck( settings.aoData, 'anCells', column ) ).detach();
+		}
+	
+		// Common actions
+		col.bVisible = vis;
+		_fnDrawHead( settings, settings.aoHeader );
+		_fnDrawHead( settings, settings.aoFooter );
+	
+		_fnSaveState( settings );
+	};
+	
+	
+	_api_register( 'columns()', function ( selector, opts ) {
+		// argument shifting
+		if ( selector === undefined ) {
+			selector = '';
+		}
+		else if ( $.isPlainObject( selector ) ) {
+			opts = selector;
+			selector = '';
+		}
+	
+		opts = _selector_opts( opts );
+	
+		var inst = this.iterator( 'table', function ( settings ) {
+			return __column_selector( settings, selector, opts );
+		}, 1 );
+	
+		// Want argument shifting here and in _row_selector?
+		inst.selector.cols = selector;
+		inst.selector.opts = opts;
+	
+		return inst;
+	} );
+	
+	_api_registerPlural( 'columns().header()', 'column().header()', function ( selector, opts ) {
+		return this.iterator( 'column', function ( settings, column ) {
+			return settings.aoColumns[column].nTh;
+		}, 1 );
+	} );
+	
+	_api_registerPlural( 'columns().footer()', 'column().footer()', function ( selector, opts ) {
+		return this.iterator( 'column', function ( settings, column ) {
+			return settings.aoColumns[column].nTf;
+		}, 1 );
+	} );
+	
+	_api_registerPlural( 'columns().data()', 'column().data()', function () {
+		return this.iterator( 'column-rows', __columnData, 1 );
+	} );
+	
+	_api_registerPlural( 'columns().dataSrc()', 'column().dataSrc()', function () {
+		return this.iterator( 'column', function ( settings, column ) {
+			return settings.aoColumns[column].mData;
+		}, 1 );
+	} );
+	
+	_api_registerPlural( 'columns().cache()', 'column().cache()', function ( type ) {
+		return this.iterator( 'column-rows', function ( settings, column, i, j, rows ) {
+			return _pluck_order( settings.aoData, rows,
+				type === 'search' ? '_aFilterData' : '_aSortData', column
+			);
+		}, 1 );
+	} );
+	
+	_api_registerPlural( 'columns().nodes()', 'column().nodes()', function () {
+		return this.iterator( 'column-rows', function ( settings, column, i, j, rows ) {
+			return _pluck_order( settings.aoData, rows, 'anCells', column ) ;
+		}, 1 );
+	} );
+	
+	_api_registerPlural( 'columns().visible()', 'column().visible()', function ( vis, calc ) {
+		var ret = this.iterator( 'column', function ( settings, column ) {
+			if ( vis === undefined ) {
+				return settings.aoColumns[ column ].bVisible;
+			} // else
+			__setColumnVis( settings, column, vis );
+		} );
+	
+		// Group the column visibility changes
+		if ( vis !== undefined ) {
+			// Second loop once the first is done for events
+			this.iterator( 'column', function ( settings, column ) {
+				_fnCallbackFire( settings, null, 'column-visibility', [settings, column, vis, calc] );
+			} );
+	
+			if ( calc === undefined || calc ) {
+				this.columns.adjust();
+			}
+		}
+	
+		return ret;
+	} );
+	
+	_api_registerPlural( 'columns().indexes()', 'column().index()', function ( type ) {
+		return this.iterator( 'column', function ( settings, column ) {
+			return type === 'visible' ?
+				_fnColumnIndexToVisible( settings, column ) :
+				column;
+		}, 1 );
+	} );
+	
+	_api_register( 'columns.adjust()', function () {
+		return this.iterator( 'table', function ( settings ) {
+			_fnAdjustColumnSizing( settings );
+		}, 1 );
+	} );
+	
+	_api_register( 'column.index()', function ( type, idx ) {
+		if ( this.context.length !== 0 ) {
+			var ctx = this.context[0];
+	
+			if ( type === 'fromVisible' || type === 'toData' ) {
+				return _fnVisibleToColumnIndex( ctx, idx );
+			}
+			else if ( type === 'fromData' || type === 'toVisible' ) {
+				return _fnColumnIndexToVisible( ctx, idx );
+			}
+		}
+	} );
+	
+	_api_register( 'column()', function ( selector, opts ) {
+		return _selector_first( this.columns( selector, opts ) );
+	} );
+	
+	
+	
+	var __cell_selector = function ( settings, selector, opts )
+	{
+		var data = settings.aoData;
+		var rows = _selector_row_indexes( settings, opts );
+		var cells = _removeEmpty( _pluck_order( data, rows, 'anCells' ) );
+		var allCells = $( [].concat.apply([], cells) );
+		var row;
+		var columns = settings.aoColumns.length;
+		var a, i, ien, j, o, host;
+	
+		var run = function ( s ) {
+			var fnSelector = typeof s === 'function';
+	
+			if ( s === null || s === undefined || fnSelector ) {
+				// All cells and function selectors
+				a = [];
+	
+				for ( i=0, ien=rows.length ; i<ien ; i++ ) {
+					row = rows[i];
+	
+					for ( j=0 ; j<columns ; j++ ) {
+						o = {
+							row: row,
+							column: j
+						};
+	
+						if ( fnSelector ) {
+							// Selector - function
+							host = data[ row ];
+	
+							if ( s( o, _fnGetCellData(settings, row, j), host.anCells ? host.anCells[j] : null ) ) {
+								a.push( o );
+							}
+						}
+						else {
+							// Selector - all
+							a.push( o );
+						}
+					}
+				}
+	
+				return a;
+			}
+			
+			// Selector - index
+			if ( $.isPlainObject( s ) ) {
+				return [s];
+			}
+	
+			// Selector - jQuery filtered cells
+			var jqResult = allCells
+				.filter( s )
+				.map( function (i, el) {
+					return { // use a new object, in case someone changes the values
+						row:    el._DT_CellIndex.row,
+						column: el._DT_CellIndex.column
+	 				};
+				} )
+				.toArray();
+	
+			if ( jqResult.length || ! s.nodeName ) {
+				return jqResult;
+			}
+	
+			// Otherwise the selector is a node, and there is one last option - the
+			// element might be a child of an element which has dt-row and dt-column
+			// data attributes
+			host = $(s).closest('*[data-dt-row]');
+			return host.length ?
+				[ {
+					row: host.data('dt-row'),
+					column: host.data('dt-column')
+				} ] :
+				[];
+		};
+	
+		return _selector_run( 'cell', selector, run, settings, opts );
+	};
+	
+	
+	
+	
+	_api_register( 'cells()', function ( rowSelector, columnSelector, opts ) {
+		// Argument shifting
+		if ( $.isPlainObject( rowSelector ) ) {
+			// Indexes
+			if ( rowSelector.row === undefined ) {
+				// Selector options in first parameter
+				opts = rowSelector;
+				rowSelector = null;
+			}
+			else {
+				// Cell index objects in first parameter
+				opts = columnSelector;
+				columnSelector = null;
+			}
+		}
+		if ( $.isPlainObject( columnSelector ) ) {
+			opts = columnSelector;
+			columnSelector = null;
+		}
+	
+		// Cell selector
+		if ( columnSelector === null || columnSelector === undefined ) {
+			return this.iterator( 'table', function ( settings ) {
+				return __cell_selector( settings, rowSelector, _selector_opts( opts ) );
+			} );
+		}
+	
+		// Row + column selector
+		var columns = this.columns( columnSelector, opts );
+		var rows = this.rows( rowSelector, opts );
+		var a, i, ien, j, jen;
+	
+		var cells = this.iterator( 'table', function ( settings, idx ) {
+			a = [];
+	
+			for ( i=0, ien=rows[idx].length ; i<ien ; i++ ) {
+				for ( j=0, jen=columns[idx].length ; j<jen ; j++ ) {
+					a.push( {
+						row:    rows[idx][i],
+						column: columns[idx][j]
+					} );
+				}
+			}
+	
+			return a;
+		}, 1 );
+	
+		$.extend( cells.selector, {
+			cols: columnSelector,
+			rows: rowSelector,
+			opts: opts
+		} );
+	
+		return cells;
+	} );
+	
+	
+	_api_registerPlural( 'cells().nodes()', 'cell().node()', function () {
+		return this.iterator( 'cell', function ( settings, row, column ) {
+			var data = settings.aoData[ row ];
+	
+			return data && data.anCells ?
+				data.anCells[ column ] :
+				undefined;
+		}, 1 );
+	} );
+	
+	
+	_api_register( 'cells().data()', function () {
+		return this.iterator( 'cell', function ( settings, row, column ) {
+			return _fnGetCellData( settings, row, column );
+		}, 1 );
+	} );
+	
+	
+	_api_registerPlural( 'cells().cache()', 'cell().cache()', function ( type ) {
+		type = type === 'search' ? '_aFilterData' : '_aSortData';
+	
+		return this.iterator( 'cell', function ( settings, row, column ) {
+			return settings.aoData[ row ][ type ][ column ];
+		}, 1 );
+	} );
+	
+	
+	_api_registerPlural( 'cells().render()', 'cell().render()', function ( type ) {
+		return this.iterator( 'cell', function ( settings, row, column ) {
+			return _fnGetCellData( settings, row, column, type );
+		}, 1 );
+	} );
+	
+	
+	_api_registerPlural( 'cells().indexes()', 'cell().index()', function () {
+		return this.iterator( 'cell', function ( settings, row, column ) {
+			return {
+				row: row,
+				column: column,
+				columnVisible: _fnColumnIndexToVisible( settings, column )
+			};
+		}, 1 );
+	} );
+	
+	
+	_api_registerPlural( 'cells().invalidate()', 'cell().invalidate()', function ( src ) {
+		return this.iterator( 'cell', function ( settings, row, column ) {
+			_fnInvalidate( settings, row, src, column );
+		} );
+	} );
+	
+	
+	
+	_api_register( 'cell()', function ( rowSelector, columnSelector, opts ) {
+		return _selector_first( this.cells( rowSelector, columnSelector, opts ) );
+	} );
+	
+	
+	_api_register( 'cell().data()', function ( data ) {
+		var ctx = this.context;
+		var cell = this[0];
+	
+		if ( data === undefined ) {
+			// Get
+			return ctx.length && cell.length ?
+				_fnGetCellData( ctx[0], cell[0].row, cell[0].column ) :
+				undefined;
+		}
+	
+		// Set
+		_fnSetCellData( ctx[0], cell[0].row, cell[0].column, data );
+		_fnInvalidate( ctx[0], cell[0].row, 'data', cell[0].column );
+	
+		return this;
+	} );
+	
+	
+	
+	/**
+	 * Get current ordering (sorting) that has been applied to the table.
+	 *
+	 * @returns {array} 2D array containing the sorting information for the first
+	 *   table in the current context. Each element in the parent array represents
+	 *   a column being sorted upon (i.e. multi-sorting with two columns would have
+	 *   2 inner arrays). The inner arrays may have 2 or 3 elements. The first is
+	 *   the column index that the sorting condition applies to, the second is the
+	 *   direction of the sort (`desc` or `asc`) and, optionally, the third is the
+	 *   index of the sorting order from the `column.sorting` initialisation array.
+	 *//**
+	 * Set the ordering for the table.
+	 *
+	 * @param {integer} order Column index to sort upon.
+	 * @param {string} direction Direction of the sort to be applied (`asc` or `desc`)
+	 * @returns {DataTables.Api} this
+	 *//**
+	 * Set the ordering for the table.
+	 *
+	 * @param {array} order 1D array of sorting information to be applied.
+	 * @param {array} [...] Optional additional sorting conditions
+	 * @returns {DataTables.Api} this
+	 *//**
+	 * Set the ordering for the table.
+	 *
+	 * @param {array} order 2D array of sorting information to be applied.
+	 * @returns {DataTables.Api} this
+	 */
+	_api_register( 'order()', function ( order, dir ) {
+		var ctx = this.context;
+	
+		if ( order === undefined ) {
+			// get
+			return ctx.length !== 0 ?
+				ctx[0].aaSorting :
+				undefined;
+		}
+	
+		// set
+		if ( typeof order === 'number' ) {
+			// Simple column / direction passed in
+			order = [ [ order, dir ] ];
+		}
+		else if ( order.length && ! $.isArray( order[0] ) ) {
+			// Arguments passed in (list of 1D arrays)
+			order = Array.prototype.slice.call( arguments );
+		}
+		// otherwise a 2D array was passed in
+	
+		return this.iterator( 'table', function ( settings ) {
+			settings.aaSorting = order.slice();
+		} );
+	} );
+	
+	
+	/**
+	 * Attach a sort listener to an element for a given column
+	 *
+	 * @param {node|jQuery|string} node Identifier for the element(s) to attach the
+	 *   listener to. This can take the form of a single DOM node, a jQuery
+	 *   collection of nodes or a jQuery selector which will identify the node(s).
+	 * @param {integer} column the column that a click on this node will sort on
+	 * @param {function} [callback] callback function when sort is run
+	 * @returns {DataTables.Api} this
+	 */
+	_api_register( 'order.listener()', function ( node, column, callback ) {
+		return this.iterator( 'table', function ( settings ) {
+			_fnSortAttachListener( settings, node, column, callback );
+		} );
+	} );
+	
+	
+	_api_register( 'order.fixed()', function ( set ) {
+		if ( ! set ) {
+			var ctx = this.context;
+			var fixed = ctx.length ?
+				ctx[0].aaSortingFixed :
+				undefined;
+	
+			return $.isArray( fixed ) ?
+				{ pre: fixed } :
+				fixed;
+		}
+	
+		return this.iterator( 'table', function ( settings ) {
+			settings.aaSortingFixed = $.extend( true, {}, set );
+		} );
+	} );
+	
+	
+	// Order by the selected column(s)
+	_api_register( [
+		'columns().order()',
+		'column().order()'
+	], function ( dir ) {
+		var that = this;
+	
+		return this.iterator( 'table', function ( settings, i ) {
+			var sort = [];
+	
+			$.each( that[i], function (j, col) {
+				sort.push( [ col, dir ] );
+			} );
+	
+			settings.aaSorting = sort;
+		} );
+	} );
+	
+	
+	
+	_api_register( 'search()', function ( input, regex, smart, caseInsen ) {
+		var ctx = this.context;
+	
+		if ( input === undefined ) {
+			// get
+			return ctx.length !== 0 ?
+				ctx[0].oPreviousSearch.sSearch :
+				undefined;
+		}
+	
+		// set
+		return this.iterator( 'table', function ( settings ) {
+			if ( ! settings.oFeatures.bFilter ) {
+				return;
+			}
+	
+			_fnFilterComplete( settings, $.extend( {}, settings.oPreviousSearch, {
+				"sSearch": input+"",
+				"bRegex":  regex === null ? false : regex,
+				"bSmart":  smart === null ? true  : smart,
+				"bCaseInsensitive": caseInsen === null ? true : caseInsen
+			} ), 1 );
+		} );
+	} );
+	
+	
+	_api_registerPlural(
+		'columns().search()',
+		'column().search()',
+		function ( input, regex, smart, caseInsen ) {
+			return this.iterator( 'column', function ( settings, column ) {
+				var preSearch = settings.aoPreSearchCols;
+	
+				if ( input === undefined ) {
+					// get
+					return preSearch[ column ].sSearch;
+				}
+	
+				// set
+				if ( ! settings.oFeatures.bFilter ) {
+					return;
+				}
+	
+				$.extend( preSearch[ column ], {
+					"sSearch": input+"",
+					"bRegex":  regex === null ? false : regex,
+					"bSmart":  smart === null ? true  : smart,
+					"bCaseInsensitive": caseInsen === null ? true : caseInsen
+				} );
+	
+				_fnFilterComplete( settings, settings.oPreviousSearch, 1 );
+			} );
+		}
+	);
+	
+	/*
+	 * State API methods
+	 */
+	
+	_api_register( 'state()', function () {
+		return this.context.length ?
+			this.context[0].oSavedState :
+			null;
+	} );
+	
+	
+	_api_register( 'state.clear()', function () {
+		return this.iterator( 'table', function ( settings ) {
+			// Save an empty object
+			settings.fnStateSaveCallback.call( settings.oInstance, settings, {} );
+		} );
+	} );
+	
+	
+	_api_register( 'state.loaded()', function () {
+		return this.context.length ?
+			this.context[0].oLoadedState :
+			null;
+	} );
+	
+	
+	_api_register( 'state.save()', function () {
+		return this.iterator( 'table', function ( settings ) {
+			_fnSaveState( settings );
+		} );
+	} );
+	
+	
+	
+	/**
+	 * Provide a common method for plug-ins to check the version of DataTables being
+	 * used, in order to ensure compatibility.
+	 *
+	 *  @param {string} version Version string to check for, in the format "X.Y.Z".
+	 *    Note that the formats "X" and "X.Y" are also acceptable.
+	 *  @returns {boolean} true if this version of DataTables is greater or equal to
+	 *    the required version, or false if this version of DataTales is not
+	 *    suitable
+	 *  @static
+	 *  @dtopt API-Static
+	 *
+	 *  @example
+	 *    alert( $.fn.dataTable.versionCheck( '1.9.0' ) );
+	 */
+	DataTable.versionCheck = DataTable.fnVersionCheck = function( version )
+	{
+		var aThis = DataTable.version.split('.');
+		var aThat = version.split('.');
+		var iThis, iThat;
+	
+		for ( var i=0, iLen=aThat.length ; i<iLen ; i++ ) {
+			iThis = parseInt( aThis[i], 10 ) || 0;
+			iThat = parseInt( aThat[i], 10 ) || 0;
+	
+			// Parts are the same, keep comparing
+			if (iThis === iThat) {
+				continue;
+			}
+	
+			// Parts are different, return immediately
+			return iThis > iThat;
+		}
+	
+		return true;
+	};
+	
+	
+	/**
+	 * Check if a `<table>` node is a DataTable table already or not.
+	 *
+	 *  @param {node|jquery|string} table Table node, jQuery object or jQuery
+	 *      selector for the table to test. Note that if more than more than one
+	 *      table is passed on, only the first will be checked
+	 *  @returns {boolean} true the table given is a DataTable, or false otherwise
+	 *  @static
+	 *  @dtopt API-Static
+	 *
+	 *  @example
+	 *    if ( ! $.fn.DataTable.isDataTable( '#example' ) ) {
+	 *      $('#example').dataTable();
+	 *    }
+	 */
+	DataTable.isDataTable = DataTable.fnIsDataTable = function ( table )
+	{
+		var t = $(table).get(0);
+		var is = false;
+	
+		if ( table instanceof DataTable.Api ) {
+			return true;
+		}
+	
+		$.each( DataTable.settings, function (i, o) {
+			var head = o.nScrollHead ? $('table', o.nScrollHead)[0] : null;
+			var foot = o.nScrollFoot ? $('table', o.nScrollFoot)[0] : null;
+	
+			if ( o.nTable === t || head === t || foot === t ) {
+				is = true;
+			}
+		} );
+	
+		return is;
+	};
+	
+	
+	/**
+	 * Get all DataTable tables that have been initialised - optionally you can
+	 * select to get only currently visible tables.
+	 *
+	 *  @param {boolean} [visible=false] Flag to indicate if you want all (default)
+	 *    or visible tables only.
+	 *  @returns {array} Array of `table` nodes (not DataTable instances) which are
+	 *    DataTables
+	 *  @static
+	 *  @dtopt API-Static
+	 *
+	 *  @example
+	 *    $.each( $.fn.dataTable.tables(true), function () {
+	 *      $(table).DataTable().columns.adjust();
+	 *    } );
+	 */
+	DataTable.tables = DataTable.fnTables = function ( visible )
+	{
+		var api = false;
+	
+		if ( $.isPlainObject( visible ) ) {
+			api = visible.api;
+			visible = visible.visible;
+		}
+	
+		var a = $.map( DataTable.settings, function (o) {
+			if ( !visible || (visible && $(o.nTable).is(':visible')) ) {
+				return o.nTable;
+			}
+		} );
+	
+		return api ?
+			new _Api( a ) :
+			a;
+	};
+	
+	
+	/**
+	 * Convert from camel case parameters to Hungarian notation. This is made public
+	 * for the extensions to provide the same ability as DataTables core to accept
+	 * either the 1.9 style Hungarian notation, or the 1.10+ style camelCase
+	 * parameters.
+	 *
+	 *  @param {object} src The model object which holds all parameters that can be
+	 *    mapped.
+	 *  @param {object} user The object to convert from camel case to Hungarian.
+	 *  @param {boolean} force When set to `true`, properties which already have a
+	 *    Hungarian value in the `user` object will be overwritten. Otherwise they
+	 *    won't be.
+	 */
+	DataTable.camelToHungarian = _fnCamelToHungarian;
+	
+	
+	
+	/**
+	 *
+	 */
+	_api_register( '$()', function ( selector, opts ) {
+		var
+			rows   = this.rows( opts ).nodes(), // Get all rows
+			jqRows = $(rows);
+	
+		return $( [].concat(
+			jqRows.filter( selector ).toArray(),
+			jqRows.find( selector ).toArray()
+		) );
+	} );
+	
+	
+	// jQuery functions to operate on the tables
+	$.each( [ 'on', 'one', 'off' ], function (i, key) {
+		_api_register( key+'()', function ( /* event, handler */ ) {
+			var args = Array.prototype.slice.call(arguments);
+	
+			// Add the `dt` namespace automatically if it isn't already present
+			args[0] = $.map( args[0].split( /\s/ ), function ( e ) {
+				return ! e.match(/\.dt\b/) ?
+					e+'.dt' :
+					e;
+				} ).join( ' ' );
+	
+			var inst = $( this.tables().nodes() );
+			inst[key].apply( inst, args );
+			return this;
+		} );
+	} );
+	
+	
+	_api_register( 'clear()', function () {
+		return this.iterator( 'table', function ( settings ) {
+			_fnClearTable( settings );
+		} );
+	} );
+	
+	
+	_api_register( 'settings()', function () {
+		return new _Api( this.context, this.context );
+	} );
+	
+	
+	_api_register( 'init()', function () {
+		var ctx = this.context;
+		return ctx.length ? ctx[0].oInit : null;
+	} );
+	
+	
+	_api_register( 'data()', function () {
+		return this.iterator( 'table', function ( settings ) {
+			return _pluck( settings.aoData, '_aData' );
+		} ).flatten();
+	} );
+	
+	
+	_api_register( 'destroy()', function ( remove ) {
+		remove = remove || false;
+	
+		return this.iterator( 'table', function ( settings ) {
+			var orig      = settings.nTableWrapper.parentNode;
+			var classes   = settings.oClasses;
+			var table     = settings.nTable;
+			var tbody     = settings.nTBody;
+			var thead     = settings.nTHead;
+			var tfoot     = settings.nTFoot;
+			var jqTable   = $(table);
+			var jqTbody   = $(tbody);
+			var jqWrapper = $(settings.nTableWrapper);
+			var rows      = $.map( settings.aoData, function (r) { return r.nTr; } );
+			var i, ien;
+	
+			// Flag to note that the table is currently being destroyed - no action
+			// should be taken
+			settings.bDestroying = true;
+	
+			// Fire off the destroy callbacks for plug-ins etc
+			_fnCallbackFire( settings, "aoDestroyCallback", "destroy", [settings] );
+	
+			// If not being removed from the document, make all columns visible
+			if ( ! remove ) {
+				new _Api( settings ).columns().visible( true );
+			}
+	
+			// Blitz all `DT` namespaced events (these are internal events, the
+			// lowercase, `dt` events are user subscribed and they are responsible
+			// for removing them
+			jqWrapper.off('.DT').find(':not(tbody *)').off('.DT');
+			$(window).off('.DT-'+settings.sInstance);
+	
+			// When scrolling we had to break the table up - restore it
+			if ( table != thead.parentNode ) {
+				jqTable.children('thead').detach();
+				jqTable.append( thead );
+			}
+	
+			if ( tfoot && table != tfoot.parentNode ) {
+				jqTable.children('tfoot').detach();
+				jqTable.append( tfoot );
+			}
+	
+			settings.aaSorting = [];
+			settings.aaSortingFixed = [];
+			_fnSortingClasses( settings );
+	
+			$( rows ).removeClass( settings.asStripeClasses.join(' ') );
+	
+			$('th, td', thead).removeClass( classes.sSortable+' '+
+				classes.sSortableAsc+' '+classes.sSortableDesc+' '+classes.sSortableNone
+			);
+	
+			// Add the TR elements back into the table in their original order
+			jqTbody.children().detach();
+			jqTbody.append( rows );
+	
+			// Remove the DataTables generated nodes, events and classes
+			var removedMethod = remove ? 'remove' : 'detach';
+			jqTable[ removedMethod ]();
+			jqWrapper[ removedMethod ]();
+	
+			// If we need to reattach the table to the document
+			if ( ! remove && orig ) {
+				// insertBefore acts like appendChild if !arg[1]
+				orig.insertBefore( table, settings.nTableReinsertBefore );
+	
+				// Restore the width of the original table - was read from the style property,
+				// so we can restore directly to that
+				jqTable
+					.css( 'width', settings.sDestroyWidth )
+					.removeClass( classes.sTable );
+	
+				// If the were originally stripe classes - then we add them back here.
+				// Note this is not fool proof (for example if not all rows had stripe
+				// classes - but it's a good effort without getting carried away
+				ien = settings.asDestroyStripes.length;
+	
+				if ( ien ) {
+					jqTbody.children().each( function (i) {
+						$(this).addClass( settings.asDestroyStripes[i % ien] );
+					} );
+				}
+			}
+	
+			/* Remove the settings object from the settings array */
+			var idx = $.inArray( settings, DataTable.settings );
+			if ( idx !== -1 ) {
+				DataTable.settings.splice( idx, 1 );
+			}
+		} );
+	} );
+	
+	
+	// Add the `every()` method for rows, columns and cells in a compact form
+	$.each( [ 'column', 'row', 'cell' ], function ( i, type ) {
+		_api_register( type+'s().every()', function ( fn ) {
+			var opts = this.selector.opts;
+			var api = this;
+	
+			return this.iterator( type, function ( settings, arg1, arg2, arg3, arg4 ) {
+				// Rows and columns:
+				//  arg1 - index
+				//  arg2 - table counter
+				//  arg3 - loop counter
+				//  arg4 - undefined
+				// Cells:
+				//  arg1 - row index
+				//  arg2 - column index
+				//  arg3 - table counter
+				//  arg4 - loop counter
+				fn.call(
+					api[ type ](
+						arg1,
+						type==='cell' ? arg2 : opts,
+						type==='cell' ? opts : undefined
+					),
+					arg1, arg2, arg3, arg4
+				);
+			} );
+		} );
+	} );
+	
+	
+	// i18n method for extensions to be able to use the language object from the
+	// DataTable
+	_api_register( 'i18n()', function ( token, def, plural ) {
+		var ctx = this.context[0];
+		var resolved = _fnGetObjectDataFn( token )( ctx.oLanguage );
+	
+		if ( resolved === undefined ) {
+			resolved = def;
+		}
+	
+		if ( plural !== undefined && $.isPlainObject( resolved ) ) {
+			resolved = resolved[ plural ] !== undefined ?
+				resolved[ plural ] :
+				resolved._;
+		}
+	
+		return resolved.replace( '%d', plural ); // nb: plural might be undefined,
+	} );
+
+	/**
+	 * Version string for plug-ins to check compatibility. Allowed format is
+	 * `a.b.c-d` where: a:int, b:int, c:int, d:string(dev|beta|alpha). `d` is used
+	 * only for non-release builds. See http://semver.org/ for more information.
+	 *  @member
+	 *  @type string
+	 *  @default Version number
+	 */
+	DataTable.version = "1.10.16";
+
+	/**
+	 * Private data store, containing all of the settings objects that are
+	 * created for the tables on a given page.
+	 *
+	 * Note that the `DataTable.settings` object is aliased to
+	 * `jQuery.fn.dataTableExt` through which it may be accessed and
+	 * manipulated, or `jQuery.fn.dataTable.settings`.
+	 *  @member
+	 *  @type array
+	 *  @default []
+	 *  @private
+	 */
+	DataTable.settings = [];
+
+	/**
+	 * Object models container, for the various models that DataTables has
+	 * available to it. These models define the objects that are used to hold
+	 * the active state and configuration of the table.
+	 *  @namespace
+	 */
+	DataTable.models = {};
+	
+	
+	
+	/**
+	 * Template object for the way in which DataTables holds information about
+	 * search information for the global filter and individual column filters.
+	 *  @namespace
+	 */
+	DataTable.models.oSearch = {
+		/**
+		 * Flag to indicate if the filtering should be case insensitive or not
+		 *  @type boolean
+		 *  @default true
+		 */
+		"bCaseInsensitive": true,
+	
+		/**
+		 * Applied search term
+		 *  @type string
+		 *  @default <i>Empty string</i>
+		 */
+		"sSearch": "",
+	
+		/**
+		 * Flag to indicate if the search term should be interpreted as a
+		 * regular expression (true) or not (false) and therefore and special
+		 * regex characters escaped.
+		 *  @type boolean
+		 *  @default false
+		 */
+		"bRegex": false,
+	
+		/**
+		 * Flag to indicate if DataTables is to use its smart filtering or not.
+		 *  @type boolean
+		 *  @default true
+		 */
+		"bSmart": true
+	};
+	
+	
+	
+	
+	/**
+	 * Template object for the way in which DataTables holds information about
+	 * each individual row. This is the object format used for the settings
+	 * aoData array.
+	 *  @namespace
+	 */
+	DataTable.models.oRow = {
+		/**
+		 * TR element for the row
+		 *  @type node
+		 *  @default null
+		 */
+		"nTr": null,
+	
+		/**
+		 * Array of TD elements for each row. This is null until the row has been
+		 * created.
+		 *  @type array nodes
+		 *  @default []
+		 */
+		"anCells": null,
+	
+		/**
+		 * Data object from the original data source for the row. This is either
+		 * an array if using the traditional form of DataTables, or an object if
+		 * using mData options. The exact type will depend on the passed in
+		 * data from the data source, or will be an array if using DOM a data
+		 * source.
+		 *  @type array|object
+		 *  @default []
+		 */
+		"_aData": [],
+	
+		/**
+		 * Sorting data cache - this array is ostensibly the same length as the
+		 * number of columns (although each index is generated only as it is
+		 * needed), and holds the data that is used for sorting each column in the
+		 * row. We do this cache generation at the start of the sort in order that
+		 * the formatting of the sort data need be done only once for each cell
+		 * per sort. This array should not be read from or written to by anything
+		 * other than the master sorting methods.
+		 *  @type array
+		 *  @default null
+		 *  @private
+		 */
+		"_aSortData": null,
+	
+		/**
+		 * Per cell filtering data cache. As per the sort data cache, used to
+		 * increase the performance of the filtering in DataTables
+		 *  @type array
+		 *  @default null
+		 *  @private
+		 */
+		"_aFilterData": null,
+	
+		/**
+		 * Filtering data cache. This is the same as the cell filtering cache, but
+		 * in this case a string rather than an array. This is easily computed with
+		 * a join on `_aFilterData`, but is provided as a cache so the join isn't
+		 * needed on every search (memory traded for performance)
+		 *  @type array
+		 *  @default null
+		 *  @private
+		 */
+		"_sFilterRow": null,
+	
+		/**
+		 * Cache of the class name that DataTables has applied to the row, so we
+		 * can quickly look at this variable rather than needing to do a DOM check
+		 * on className for the nTr property.
+		 *  @type string
+		 *  @default <i>Empty string</i>
+		 *  @private
+		 */
+		"_sRowStripe": "",
+	
+		/**
+		 * Denote if the original data source was from the DOM, or the data source
+		 * object. This is used for invalidating data, so DataTables can
+		 * automatically read data from the original source, unless uninstructed
+		 * otherwise.
+		 *  @type string
+		 *  @default null
+		 *  @private
+		 */
+		"src": null,
+	
+		/**
+		 * Index in the aoData array. This saves an indexOf lookup when we have the
+		 * object, but want to know the index
+		 *  @type integer
+		 *  @default -1
+		 *  @private
+		 */
+		"idx": -1
+	};
+	
+	
+	/**
+	 * Template object for the column information object in DataTables. This object
+	 * is held in the settings aoColumns array and contains all the information that
+	 * DataTables needs about each individual column.
+	 *
+	 * Note that this object is related to {@link DataTable.defaults.column}
+	 * but this one is the internal data store for DataTables's cache of columns.
+	 * It should NOT be manipulated outside of DataTables. Any configuration should
+	 * be done through the initialisation options.
+	 *  @namespace
+	 */
+	DataTable.models.oColumn = {
+		/**
+		 * Column index. This could be worked out on-the-fly with $.inArray, but it
+		 * is faster to just hold it as a variable
+		 *  @type integer
+		 *  @default null
+		 */
+		"idx": null,
+	
+		/**
+		 * A list of the columns that sorting should occur on when this column
+		 * is sorted. That this property is an array allows multi-column sorting
+		 * to be defined for a column (for example first name / last name columns
+		 * would benefit from this). The values are integers pointing to the
+		 * columns to be sorted on (typically it will be a single integer pointing
+		 * at itself, but that doesn't need to be the case).
+		 *  @type array
+		 */
+		"aDataSort": null,
+	
+		/**
+		 * Define the sorting directions that are applied to the column, in sequence
+		 * as the column is repeatedly sorted upon - i.e. the first value is used
+		 * as the sorting direction when the column if first sorted (clicked on).
+		 * Sort it again (click again) and it will move on to the next index.
+		 * Repeat until loop.
+		 *  @type array
+		 */
+		"asSorting": null,
+	
+		/**
+		 * Flag to indicate if the column is searchable, and thus should be included
+		 * in the filtering or not.
+		 *  @type boolean
+		 */
+		"bSearchable": null,
+	
+		/**
+		 * Flag to indicate if the column is sortable or not.
+		 *  @type boolean
+		 */
+		"bSortable": null,
+	
+		/**
+		 * Flag to indicate if the column is currently visible in the table or not
+		 *  @type boolean
+		 */
+		"bVisible": null,
+	
+		/**
+		 * Store for manual type assignment using the `column.type` option. This
+		 * is held in store so we can manipulate the column's `sType` property.
+		 *  @type string
+		 *  @default null
+		 *  @private
+		 */
+		"_sManualType": null,
+	
+		/**
+		 * Flag to indicate if HTML5 data attributes should be used as the data
+		 * source for filtering or sorting. True is either are.
+		 *  @type boolean
+		 *  @default false
+		 *  @private
+		 */
+		"_bAttrSrc": false,
+	
+		/**
+		 * Developer definable function that is called whenever a cell is created (Ajax source,
+		 * etc) or processed for input (DOM source). This can be used as a compliment to mRender
+		 * allowing you to modify the DOM element (add background colour for example) when the
+		 * element is available.
+		 *  @type function
+		 *  @param {element} nTd The TD node that has been created
+		 *  @param {*} sData The Data for the cell
+		 *  @param {array|object} oData The data for the whole row
+		 *  @param {int} iRow The row index for the aoData data store
+		 *  @default null
+		 */
+		"fnCreatedCell": null,
+	
+		/**
+		 * Function to get data from a cell in a column. You should <b>never</b>
+		 * access data directly through _aData internally in DataTables - always use
+		 * the method attached to this property. It allows mData to function as
+		 * required. This function is automatically assigned by the column
+		 * initialisation method
+		 *  @type function
+		 *  @param {array|object} oData The data array/object for the array
+		 *    (i.e. aoData[]._aData)
+		 *  @param {string} sSpecific The specific data type you want to get -
+		 *    'display', 'type' 'filter' 'sort'
+		 *  @returns {*} The data for the cell from the given row's data
+		 *  @default null
+		 */
+		"fnGetData": null,
+	
+		/**
+		 * Function to set data for a cell in the column. You should <b>never</b>
+		 * set the data directly to _aData internally in DataTables - always use
+		 * this method. It allows mData to function as required. This function
+		 * is automatically assigned by the column initialisation method
+		 *  @type function
+		 *  @param {array|object} oData The data array/object for the array
+		 *    (i.e. aoData[]._aData)
+		 *  @param {*} sValue Value to set
+		 *  @default null
+		 */
+		"fnSetData": null,
+	
+		/**
+		 * Property to read the value for the cells in the column from the data
+		 * source array / object. If null, then the default content is used, if a
+		 * function is given then the return from the function is used.
+		 *  @type function|int|string|null
+		 *  @default null
+		 */
+		"mData": null,
+	
+		/**
+		 * Partner property to mData which is used (only when defined) to get
+		 * the data - i.e. it is basically the same as mData, but without the
+		 * 'set' option, and also the data fed to it is the result from mData.
+		 * This is the rendering method to match the data method of mData.
+		 *  @type function|int|string|null
+		 *  @default null
+		 */
+		"mRender": null,
+	
+		/**
+		 * Unique header TH/TD element for this column - this is what the sorting
+		 * listener is attached to (if sorting is enabled.)
+		 *  @type node
+		 *  @default null
+		 */
+		"nTh": null,
+	
+		/**
+		 * Unique footer TH/TD element for this column (if there is one). Not used
+		 * in DataTables as such, but can be used for plug-ins to reference the
+		 * footer for each column.
+		 *  @type node
+		 *  @default null
+		 */
+		"nTf": null,
+	
+		/**
+		 * The class to apply to all TD elements in the table's TBODY for the column
+		 *  @type string
+		 *  @default null
+		 */
+		"sClass": null,
+	
+		/**
+		 * When DataTables calculates the column widths to assign to each column,
+		 * it finds the longest string in each column and then constructs a
+		 * temporary table and reads the widths from that. The problem with this
+		 * is that "mmm" is much wider then "iiii", but the latter is a longer
+		 * string - thus the calculation can go wrong (doing it properly and putting
+		 * it into an DOM object and measuring that is horribly(!) slow). Thus as
+		 * a "work around" we provide this option. It will append its value to the
+		 * text that is found to be the longest string for the column - i.e. padding.
+		 *  @type string
+		 */
+		"sContentPadding": null,
+	
+		/**
+		 * Allows a default value to be given for a column's data, and will be used
+		 * whenever a null data source is encountered (this can be because mData
+		 * is set to null, or because the data source itself is null).
+		 *  @type string
+		 *  @default null
+		 */
+		"sDefaultContent": null,
+	
+		/**
+		 * Name for the column, allowing reference to the column by name as well as
+		 * by index (needs a lookup to work by name).
+		 *  @type string
+		 */
+		"sName": null,
+	
+		/**
+		 * Custom sorting data type - defines which of the available plug-ins in
+		 * afnSortData the custom sorting will use - if any is defined.
+		 *  @type string
+		 *  @default std
+		 */
+		"sSortDataType": 'std',
+	
+		/**
+		 * Class to be applied to the header element when sorting on this column
+		 *  @type string
+		 *  @default null
+		 */
+		"sSortingClass": null,
+	
+		/**
+		 * Class to be applied to the header element when sorting on this column -
+		 * when jQuery UI theming is used.
+		 *  @type string
+		 *  @default null
+		 */
+		"sSortingClassJUI": null,
+	
+		/**
+		 * Title of the column - what is seen in the TH element (nTh).
+		 *  @type string
+		 */
+		"sTitle": null,
+	
+		/**
+		 * Column sorting and filtering type
+		 *  @type string
+		 *  @default null
+		 */
+		"sType": null,
+	
+		/**
+		 * Width of the column
+		 *  @type string
+		 *  @default null
+		 */
+		"sWidth": null,
+	
+		/**
+		 * Width of the column when it was first "encountered"
+		 *  @type string
+		 *  @default null
+		 */
+		"sWidthOrig": null
+	};
+	
+	
+	/*
+	 * Developer note: The properties of the object below are given in Hungarian
+	 * notation, that was used as the interface for DataTables prior to v1.10, however
+	 * from v1.10 onwards the primary interface is camel case. In order to avoid
+	 * breaking backwards compatibility utterly with this change, the Hungarian
+	 * version is still, internally the primary interface, but is is not documented
+	 * - hence the @name tags in each doc comment. This allows a Javascript function
+	 * to create a map from Hungarian notation to camel case (going the other direction
+	 * would require each property to be listed, which would at around 3K to the size
+	 * of DataTables, while this method is about a 0.5K hit.
+	 *
+	 * Ultimately this does pave the way for Hungarian notation to be dropped
+	 * completely, but that is a massive amount of work and will break current
+	 * installs (therefore is on-hold until v2).
+	 */
+	
+	/**
+	 * Initialisation options that can be given to DataTables at initialisation
+	 * time.
+	 *  @namespace
+	 */
+	DataTable.defaults = {
+		/**
+		 * An array of data to use for the table, passed in at initialisation which
+		 * will be used in preference to any data which is already in the DOM. This is
+		 * particularly useful for constructing tables purely in Javascript, for
+		 * example with a custom Ajax call.
+		 *  @type array
+		 *  @default null
+		 *
+		 *  @dtopt Option
+		 *  @name DataTable.defaults.data
+		 *
+		 *  @example
+		 *    // Using a 2D array data source
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "data": [
+		 *          ['Trident', 'Internet Explorer 4.0', 'Win 95+', 4, 'X'],
+		 *          ['Trident', 'Internet Explorer 5.0', 'Win 95+', 5, 'C'],
+		 *        ],
+		 *        "columns": [
+		 *          { "title": "Engine" },
+		 *          { "title": "Browser" },
+		 *          { "title": "Platform" },
+		 *          { "title": "Version" },
+		 *          { "title": "Grade" }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using an array of objects as a data source (`data`)
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "data": [
+		 *          {
+		 *            "engine":   "Trident",
+		 *            "browser":  "Internet Explorer 4.0",
+		 *            "platform": "Win 95+",
+		 *            "version":  4,
+		 *            "grade":    "X"
+		 *          },
+		 *          {
+		 *            "engine":   "Trident",
+		 *            "browser":  "Internet Explorer 5.0",
+		 *            "platform": "Win 95+",
+		 *            "version":  5,
+		 *            "grade":    "C"
+		 *          }
+		 *        ],
+		 *        "columns": [
+		 *          { "title": "Engine",   "data": "engine" },
+		 *          { "title": "Browser",  "data": "browser" },
+		 *          { "title": "Platform", "data": "platform" },
+		 *          { "title": "Version",  "data": "version" },
+		 *          { "title": "Grade",    "data": "grade" }
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"aaData": null,
+	
+	
+		/**
+		 * If ordering is enabled, then DataTables will perform a first pass sort on
+		 * initialisation. You can define which column(s) the sort is performed
+		 * upon, and the sorting direction, with this variable. The `sorting` array
+		 * should contain an array for each column to be sorted initially containing
+		 * the column's index and a direction string ('asc' or 'desc').
+		 *  @type array
+		 *  @default [[0,'asc']]
+		 *
+		 *  @dtopt Option
+		 *  @name DataTable.defaults.order
+		 *
+		 *  @example
+		 *    // Sort by 3rd column first, and then 4th column
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "order": [[2,'asc'], [3,'desc']]
+		 *      } );
+		 *    } );
+		 *
+		 *    // No initial sorting
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "order": []
+		 *      } );
+		 *    } );
+		 */
+		"aaSorting": [[0,'asc']],
+	
+	
+		/**
+		 * This parameter is basically identical to the `sorting` parameter, but
+		 * cannot be overridden by user interaction with the table. What this means
+		 * is that you could have a column (visible or hidden) which the sorting
+		 * will always be forced on first - any sorting after that (from the user)
+		 * will then be performed as required. This can be useful for grouping rows
+		 * together.
+		 *  @type array
+		 *  @default null
+		 *
+		 *  @dtopt Option
+		 *  @name DataTable.defaults.orderFixed
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "orderFixed": [[0,'asc']]
+		 *      } );
+		 *    } )
+		 */
+		"aaSortingFixed": [],
+	
+	
+		/**
+		 * DataTables can be instructed to load data to display in the table from a
+		 * Ajax source. This option defines how that Ajax call is made and where to.
+		 *
+		 * The `ajax` property has three different modes of operation, depending on
+		 * how it is defined. These are:
+		 *
+		 * * `string` - Set the URL from where the data should be loaded from.
+		 * * `object` - Define properties for `jQuery.ajax`.
+		 * * `function` - Custom data get function
+		 *
+		 * `string`
+		 * --------
+		 *
+		 * As a string, the `ajax` property simply defines the URL from which
+		 * DataTables will load data.
+		 *
+		 * `object`
+		 * --------
+		 *
+		 * As an object, the parameters in the object are passed to
+		 * [jQuery.ajax](http://api.jquery.com/jQuery.ajax/) allowing fine control
+		 * of the Ajax request. DataTables has a number of default parameters which
+		 * you can override using this option. Please refer to the jQuery
+		 * documentation for a full description of the options available, although
+		 * the following parameters provide additional options in DataTables or
+		 * require special consideration:
+		 *
+		 * * `data` - As with jQuery, `data` can be provided as an object, but it
+		 *   can also be used as a function to manipulate the data DataTables sends
+		 *   to the server. The function takes a single parameter, an object of
+		 *   parameters with the values that DataTables has readied for sending. An
+		 *   object may be returned which will be merged into the DataTables
+		 *   defaults, or you can add the items to the object that was passed in and
+		 *   not return anything from the function. This supersedes `fnServerParams`
+		 *   from DataTables 1.9-.
+		 *
+		 * * `dataSrc` - By default DataTables will look for the property `data` (or
+		 *   `aaData` for compatibility with DataTables 1.9-) when obtaining data
+		 *   from an Ajax source or for server-side processing - this parameter
+		 *   allows that property to be changed. You can use Javascript dotted
+		 *   object notation to get a data source for multiple levels of nesting, or
+		 *   it my be used as a function. As a function it takes a single parameter,
+		 *   the JSON returned from the server, which can be manipulated as
+		 *   required, with the returned value being that used by DataTables as the
+		 *   data source for the table. This supersedes `sAjaxDataProp` from
+		 *   DataTables 1.9-.
+		 *
+		 * * `success` - Should not be overridden it is used internally in
+		 *   DataTables. To manipulate / transform the data returned by the server
+		 *   use `ajax.dataSrc`, or use `ajax` as a function (see below).
+		 *
+		 * `function`
+		 * ----------
+		 *
+		 * As a function, making the Ajax call is left up to yourself allowing
+		 * complete control of the Ajax request. Indeed, if desired, a method other
+		 * than Ajax could be used to obtain the required data, such as Web storage
+		 * or an AIR database.
+		 *
+		 * The function is given four parameters and no return is required. The
+		 * parameters are:
+		 *
+		 * 1. _object_ - Data to send to the server
+		 * 2. _function_ - Callback function that must be executed when the required
+		 *    data has been obtained. That data should be passed into the callback
+		 *    as the only parameter
+		 * 3. _object_ - DataTables settings object for the table
+		 *
+		 * Note that this supersedes `fnServerData` from DataTables 1.9-.
+		 *
+		 *  @type string|object|function
+		 *  @default null
+		 *
+		 *  @dtopt Option
+		 *  @name DataTable.defaults.ajax
+		 *  @since 1.10.0
+		 *
+		 * @example
+		 *   // Get JSON data from a file via Ajax.
+		 *   // Note DataTables expects data in the form `{ data: [ ...data... ] }` by default).
+		 *   $('#example').dataTable( {
+		 *     "ajax": "data.json"
+		 *   } );
+		 *
+		 * @example
+		 *   // Get JSON data from a file via Ajax, using `dataSrc` to change
+		 *   // `data` to `tableData` (i.e. `{ tableData: [ ...data... ] }`)
+		 *   $('#example').dataTable( {
+		 *     "ajax": {
+		 *       "url": "data.json",
+		 *       "dataSrc": "tableData"
+		 *     }
+		 *   } );
+		 *
+		 * @example
+		 *   // Get JSON data from a file via Ajax, using `dataSrc` to read data
+		 *   // from a plain array rather than an array in an object
+		 *   $('#example').dataTable( {
+		 *     "ajax": {
+		 *       "url": "data.json",
+		 *       "dataSrc": ""
+		 *     }
+		 *   } );
+		 *
+		 * @example
+		 *   // Manipulate the data returned from the server - add a link to data
+		 *   // (note this can, should, be done using `render` for the column - this
+		 *   // is just a simple example of how the data can be manipulated).
+		 *   $('#example').dataTable( {
+		 *     "ajax": {
+		 *       "url": "data.json",
+		 *       "dataSrc": function ( json ) {
+		 *         for ( var i=0, ien=json.length ; i<ien ; i++ ) {
+		 *           json[i][0] = '<a href="/message/'+json[i][0]+'>View message</a>';
+		 *         }
+		 *         return json;
+		 *       }
+		 *     }
+		 *   } );
+		 *
+		 * @example
+		 *   // Add data to the request
+		 *   $('#example').dataTable( {
+		 *     "ajax": {
+		 *       "url": "data.json",
+		 *       "data": function ( d ) {
+		 *         return {
+		 *           "extra_search": $('#extra').val()
+		 *         };
+		 *       }
+		 *     }
+		 *   } );
+		 *
+		 * @example
+		 *   // Send request as POST
+		 *   $('#example').dataTable( {
+		 *     "ajax": {
+		 *       "url": "data.json",
+		 *       "type": "POST"
+		 *     }
+		 *   } );
+		 *
+		 * @example
+		 *   // Get the data from localStorage (could interface with a form for
+		 *   // adding, editing and removing rows).
+		 *   $('#example').dataTable( {
+		 *     "ajax": function (data, callback, settings) {
+		 *       callback(
+		 *         JSON.parse( localStorage.getItem('dataTablesData') )
+		 *       );
+		 *     }
+		 *   } );
+		 */
+		"ajax": null,
+	
+	
+		/**
+		 * This parameter allows you to readily specify the entries in the length drop
+		 * down menu that DataTables shows when pagination is enabled. It can be
+		 * either a 1D array of options which will be used for both the displayed
+		 * option and the value, or a 2D array which will use the array in the first
+		 * position as the value, and the array in the second position as the
+		 * displayed options (useful for language strings such as 'All').
+		 *
+		 * Note that the `pageLength` property will be automatically set to the
+		 * first value given in this array, unless `pageLength` is also provided.
+		 *  @type array
+		 *  @default [ 10, 25, 50, 100 ]
+		 *
+		 *  @dtopt Option
+		 *  @name DataTable.defaults.lengthMenu
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "lengthMenu": [[10, 25, 50, -1], [10, 25, 50, "All"]]
+		 *      } );
+		 *    } );
+		 */
+		"aLengthMenu": [ 10, 25, 50, 100 ],
+	
+	
+		/**
+		 * The `columns` option in the initialisation parameter allows you to define
+		 * details about the way individual columns behave. For a full list of
+		 * column options that can be set, please see
+		 * {@link DataTable.defaults.column}. Note that if you use `columns` to
+		 * define your columns, you must have an entry in the array for every single
+		 * column that you have in your table (these can be null if you don't which
+		 * to specify any options).
+		 *  @member
+		 *
+		 *  @name DataTable.defaults.column
+		 */
+		"aoColumns": null,
+	
+		/**
+		 * Very similar to `columns`, `columnDefs` allows you to target a specific
+		 * column, multiple columns, or all columns, using the `targets` property of
+		 * each object in the array. This allows great flexibility when creating
+		 * tables, as the `columnDefs` arrays can be of any length, targeting the
+		 * columns you specifically want. `columnDefs` may use any of the column
+		 * options available: {@link DataTable.defaults.column}, but it _must_
+		 * have `targets` defined in each object in the array. Values in the `targets`
+		 * array may be:
+		 *   <ul>
+		 *     <li>a string - class name will be matched on the TH for the column</li>
+		 *     <li>0 or a positive integer - column index counting from the left</li>
+		 *     <li>a negative integer - column index counting from the right</li>
+		 *     <li>the string "_all" - all columns (i.e. assign a default)</li>
+		 *   </ul>
+		 *  @member
+		 *
+		 *  @name DataTable.defaults.columnDefs
+		 */
+		"aoColumnDefs": null,
+	
+	
+		/**
+		 * Basically the same as `search`, this parameter defines the individual column
+		 * filtering state at initialisation time. The array must be of the same size
+		 * as the number of columns, and each element be an object with the parameters
+		 * `search` and `escapeRegex` (the latter is optional). 'null' is also
+		 * accepted and the default will be used.
+		 *  @type array
+		 *  @default []
+		 *
+		 *  @dtopt Option
+		 *  @name DataTable.defaults.searchCols
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "searchCols": [
+		 *          null,
+		 *          { "search": "My filter" },
+		 *          null,
+		 *          { "search": "^[0-9]", "escapeRegex": false }
+		 *        ]
+		 *      } );
+		 *    } )
+		 */
+		"aoSearchCols": [],
+	
+	
+		/**
+		 * An array of CSS classes that should be applied to displayed rows. This
+		 * array may be of any length, and DataTables will apply each class
+		 * sequentially, looping when required.
+		 *  @type array
+		 *  @default null <i>Will take the values determined by the `oClasses.stripe*`
+		 *    options</i>
+		 *
+		 *  @dtopt Option
+		 *  @name DataTable.defaults.stripeClasses
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "stripeClasses": [ 'strip1', 'strip2', 'strip3' ]
+		 *      } );
+		 *    } )
+		 */
+		"asStripeClasses": null,
+	
+	
+		/**
+		 * Enable or disable automatic column width calculation. This can be disabled
+		 * as an optimisation (it takes some time to calculate the widths) if the
+		 * tables widths are passed in using `columns`.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.autoWidth
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "autoWidth": false
+		 *      } );
+		 *    } );
+		 */
+		"bAutoWidth": true,
+	
+	
+		/**
+		 * Deferred rendering can provide DataTables with a huge speed boost when you
+		 * are using an Ajax or JS data source for the table. This option, when set to
+		 * true, will cause DataTables to defer the creation of the table elements for
+		 * each row until they are needed for a draw - saving a significant amount of
+		 * time.
+		 *  @type boolean
+		 *  @default false
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.deferRender
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "ajax": "sources/arrays.txt",
+		 *        "deferRender": true
+		 *      } );
+		 *    } );
+		 */
+		"bDeferRender": false,
+	
+	
+		/**
+		 * Replace a DataTable which matches the given selector and replace it with
+		 * one which has the properties of the new initialisation object passed. If no
+		 * table matches the selector, then the new DataTable will be constructed as
+		 * per normal.
+		 *  @type boolean
+		 *  @default false
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.destroy
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "srollY": "200px",
+		 *        "paginate": false
+		 *      } );
+		 *
+		 *      // Some time later....
+		 *      $('#example').dataTable( {
+		 *        "filter": false,
+		 *        "destroy": true
+		 *      } );
+		 *    } );
+		 */
+		"bDestroy": false,
+	
+	
+		/**
+		 * Enable or disable filtering of data. Filtering in DataTables is "smart" in
+		 * that it allows the end user to input multiple words (space separated) and
+		 * will match a row containing those words, even if not in the order that was
+		 * specified (this allow matching across multiple columns). Note that if you
+		 * wish to use filtering in DataTables this must remain 'true' - to remove the
+		 * default filtering input box and retain filtering abilities, please use
+		 * {@link DataTable.defaults.dom}.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.searching
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "searching": false
+		 *      } );
+		 *    } );
+		 */
+		"bFilter": true,
+	
+	
+		/**
+		 * Enable or disable the table information display. This shows information
+		 * about the data that is currently visible on the page, including information
+		 * about filtered data if that action is being performed.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.info
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "info": false
+		 *      } );
+		 *    } );
+		 */
+		"bInfo": true,
+	
+	
+		/**
+		 * Allows the end user to select the size of a formatted page from a select
+		 * menu (sizes are 10, 25, 50 and 100). Requires pagination (`paginate`).
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.lengthChange
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "lengthChange": false
+		 *      } );
+		 *    } );
+		 */
+		"bLengthChange": true,
+	
+	
+		/**
+		 * Enable or disable pagination.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.paging
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "paging": false
+		 *      } );
+		 *    } );
+		 */
+		"bPaginate": true,
+	
+	
+		/**
+		 * Enable or disable the display of a 'processing' indicator when the table is
+		 * being processed (e.g. a sort). This is particularly useful for tables with
+		 * large amounts of data where it can take a noticeable amount of time to sort
+		 * the entries.
+		 *  @type boolean
+		 *  @default false
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.processing
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "processing": true
+		 *      } );
+		 *    } );
+		 */
+		"bProcessing": false,
+	
+	
+		/**
+		 * Retrieve the DataTables object for the given selector. Note that if the
+		 * table has already been initialised, this parameter will cause DataTables
+		 * to simply return the object that has already been set up - it will not take
+		 * account of any changes you might have made to the initialisation object
+		 * passed to DataTables (setting this parameter to true is an acknowledgement
+		 * that you understand this). `destroy` can be used to reinitialise a table if
+		 * you need.
+		 *  @type boolean
+		 *  @default false
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.retrieve
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      initTable();
+		 *      tableActions();
+		 *    } );
+		 *
+		 *    function initTable ()
+		 *    {
+		 *      return $('#example').dataTable( {
+		 *        "scrollY": "200px",
+		 *        "paginate": false,
+		 *        "retrieve": true
+		 *      } );
+		 *    }
+		 *
+		 *    function tableActions ()
+		 *    {
+		 *      var table = initTable();
+		 *      // perform API operations with oTable
+		 *    }
+		 */
+		"bRetrieve": false,
+	
+	
+		/**
+		 * When vertical (y) scrolling is enabled, DataTables will force the height of
+		 * the table's viewport to the given height at all times (useful for layout).
+		 * However, this can look odd when filtering data down to a small data set,
+		 * and the footer is left "floating" further down. This parameter (when
+		 * enabled) will cause DataTables to collapse the table's viewport down when
+		 * the result set will fit within the given Y height.
+		 *  @type boolean
+		 *  @default false
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.scrollCollapse
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "scrollY": "200",
+		 *        "scrollCollapse": true
+		 *      } );
+		 *    } );
+		 */
+		"bScrollCollapse": false,
+	
+	
+		/**
+		 * Configure DataTables to use server-side processing. Note that the
+		 * `ajax` parameter must also be given in order to give DataTables a
+		 * source to obtain the required data for each draw.
+		 *  @type boolean
+		 *  @default false
+		 *
+		 *  @dtopt Features
+		 *  @dtopt Server-side
+		 *  @name DataTable.defaults.serverSide
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "serverSide": true,
+		 *        "ajax": "xhr.php"
+		 *      } );
+		 *    } );
+		 */
+		"bServerSide": false,
+	
+	
+		/**
+		 * Enable or disable sorting of columns. Sorting of individual columns can be
+		 * disabled by the `sortable` option for each column.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.ordering
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "ordering": false
+		 *      } );
+		 *    } );
+		 */
+		"bSort": true,
+	
+	
+		/**
+		 * Enable or display DataTables' ability to sort multiple columns at the
+		 * same time (activated by shift-click by the user).
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.orderMulti
+		 *
+		 *  @example
+		 *    // Disable multiple column sorting ability
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "orderMulti": false
+		 *      } );
+		 *    } );
+		 */
+		"bSortMulti": true,
+	
+	
+		/**
+		 * Allows control over whether DataTables should use the top (true) unique
+		 * cell that is found for a single column, or the bottom (false - default).
+		 * This is useful when using complex headers.
+		 *  @type boolean
+		 *  @default false
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.orderCellsTop
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "orderCellsTop": true
+		 *      } );
+		 *    } );
+		 */
+		"bSortCellsTop": false,
+	
+	
+		/**
+		 * Enable or disable the addition of the classes `sorting\_1`, `sorting\_2` and
+		 * `sorting\_3` to the columns which are currently being sorted on. This is
+		 * presented as a feature switch as it can increase processing time (while
+		 * classes are removed and added) so for large data sets you might want to
+		 * turn this off.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.orderClasses
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "orderClasses": false
+		 *      } );
+		 *    } );
+		 */
+		"bSortClasses": true,
+	
+	
+		/**
+		 * Enable or disable state saving. When enabled HTML5 `localStorage` will be
+		 * used to save table display information such as pagination information,
+		 * display length, filtering and sorting. As such when the end user reloads
+		 * the page the display display will match what thy had previously set up.
+		 *
+		 * Due to the use of `localStorage` the default state saving is not supported
+		 * in IE6 or 7. If state saving is required in those browsers, use
+		 * `stateSaveCallback` to provide a storage solution such as cookies.
+		 *  @type boolean
+		 *  @default false
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.stateSave
+		 *
+		 *  @example
+		 *    $(document).ready( function () {
+		 *      $('#example').dataTable( {
+		 *        "stateSave": true
+		 *      } );
+		 *    } );
+		 */
+		"bStateSave": false,
+	
+	
+		/**
+		 * This function is called when a TR element is created (and all TD child
+		 * elements have been inserted), or registered if using a DOM source, allowing
+		 * manipulation of the TR element (adding classes etc).
+		 *  @type function
+		 *  @param {node} row "TR" element for the current row
+		 *  @param {array} data Raw data array for this row
+		 *  @param {int} dataIndex The index of this row in the internal aoData array
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.createdRow
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "createdRow": function( row, data, dataIndex ) {
+		 *          // Bold the grade for all 'A' grade browsers
+		 *          if ( data[4] == "A" )
+		 *          {
+		 *            $('td:eq(4)', row).html( '<b>A</b>' );
+		 *          }
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnCreatedRow": null,
+	
+	
+		/**
+		 * This function is called on every 'draw' event, and allows you to
+		 * dynamically modify any aspect you want about the created DOM.
+		 *  @type function
+		 *  @param {object} settings DataTables settings object
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.drawCallback
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "drawCallback": function( settings ) {
+		 *          alert( 'DataTables has redrawn the table' );
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnDrawCallback": null,
+	
+	
+		/**
+		 * Identical to fnHeaderCallback() but for the table footer this function
+		 * allows you to modify the table footer on every 'draw' event.
+		 *  @type function
+		 *  @param {node} foot "TR" element for the footer
+		 *  @param {array} data Full table data (as derived from the original HTML)
+		 *  @param {int} start Index for the current display starting point in the
+		 *    display array
+		 *  @param {int} end Index for the current display ending point in the
+		 *    display array
+		 *  @param {array int} display Index array to translate the visual position
+		 *    to the full data array
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.footerCallback
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "footerCallback": function( tfoot, data, start, end, display ) {
+		 *          tfoot.getElementsByTagName('th')[0].innerHTML = "Starting index is "+start;
+		 *        }
+		 *      } );
+		 *    } )
+		 */
+		"fnFooterCallback": null,
+	
+	
+		/**
+		 * When rendering large numbers in the information element for the table
+		 * (i.e. "Showing 1 to 10 of 57 entries") DataTables will render large numbers
+		 * to have a comma separator for the 'thousands' units (e.g. 1 million is
+		 * rendered as "1,000,000") to help readability for the end user. This
+		 * function will override the default method DataTables uses.
+		 *  @type function
+		 *  @member
+		 *  @param {int} toFormat number to be formatted
+		 *  @returns {string} formatted string for DataTables to show the number
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.formatNumber
+		 *
+		 *  @example
+		 *    // Format a number using a single quote for the separator (note that
+		 *    // this can also be done with the language.thousands option)
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "formatNumber": function ( toFormat ) {
+		 *          return toFormat.toString().replace(
+		 *            /\B(?=(\d{3})+(?!\d))/g, "'"
+		 *          );
+		 *        };
+		 *      } );
+		 *    } );
+		 */
+		"fnFormatNumber": function ( toFormat ) {
+			return toFormat.toString().replace(
+				/\B(?=(\d{3})+(?!\d))/g,
+				this.oLanguage.sThousands
+			);
+		},
+	
+	
+		/**
+		 * This function is called on every 'draw' event, and allows you to
+		 * dynamically modify the header row. This can be used to calculate and
+		 * display useful information about the table.
+		 *  @type function
+		 *  @param {node} head "TR" element for the header
+		 *  @param {array} data Full table data (as derived from the original HTML)
+		 *  @param {int} start Index for the current display starting point in the
+		 *    display array
+		 *  @param {int} end Index for the current display ending point in the
+		 *    display array
+		 *  @param {array int} display Index array to translate the visual position
+		 *    to the full data array
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.headerCallback
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "fheaderCallback": function( head, data, start, end, display ) {
+		 *          head.getElementsByTagName('th')[0].innerHTML = "Displaying "+(end-start)+" records";
+		 *        }
+		 *      } );
+		 *    } )
+		 */
+		"fnHeaderCallback": null,
+	
+	
+		/**
+		 * The information element can be used to convey information about the current
+		 * state of the table. Although the internationalisation options presented by
+		 * DataTables are quite capable of dealing with most customisations, there may
+		 * be times where you wish to customise the string further. This callback
+		 * allows you to do exactly that.
+		 *  @type function
+		 *  @param {object} oSettings DataTables settings object
+		 *  @param {int} start Starting position in data for the draw
+		 *  @param {int} end End position in data for the draw
+		 *  @param {int} max Total number of rows in the table (regardless of
+		 *    filtering)
+		 *  @param {int} total Total number of rows in the data set, after filtering
+		 *  @param {string} pre The string that DataTables has formatted using it's
+		 *    own rules
+		 *  @returns {string} The string to be displayed in the information element.
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.infoCallback
+		 *
+		 *  @example
+		 *    $('#example').dataTable( {
+		 *      "infoCallback": function( settings, start, end, max, total, pre ) {
+		 *        return start +" to "+ end;
+		 *      }
+		 *    } );
+		 */
+		"fnInfoCallback": null,
+	
+	
+		/**
+		 * Called when the table has been initialised. Normally DataTables will
+		 * initialise sequentially and there will be no need for this function,
+		 * however, this does not hold true when using external language information
+		 * since that is obtained using an async XHR call.
+		 *  @type function
+		 *  @param {object} settings DataTables settings object
+		 *  @param {object} json The JSON object request from the server - only
+		 *    present if client-side Ajax sourced data is used
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.initComplete
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "initComplete": function(settings, json) {
+		 *          alert( 'DataTables has finished its initialisation.' );
+		 *        }
+		 *      } );
+		 *    } )
+		 */
+		"fnInitComplete": null,
+	
+	
+		/**
+		 * Called at the very start of each table draw and can be used to cancel the
+		 * draw by returning false, any other return (including undefined) results in
+		 * the full draw occurring).
+		 *  @type function
+		 *  @param {object} settings DataTables settings object
+		 *  @returns {boolean} False will cancel the draw, anything else (including no
+		 *    return) will allow it to complete.
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.preDrawCallback
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "preDrawCallback": function( settings ) {
+		 *          if ( $('#test').val() == 1 ) {
+		 *            return false;
+		 *          }
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnPreDrawCallback": null,
+	
+	
+		/**
+		 * This function allows you to 'post process' each row after it have been
+		 * generated for each table draw, but before it is rendered on screen. This
+		 * function might be used for setting the row class name etc.
+		 *  @type function
+		 *  @param {node} row "TR" element for the current row
+		 *  @param {array} data Raw data array for this row
+		 *  @param {int} displayIndex The display index for the current table draw
+		 *  @param {int} displayIndexFull The index of the data in the full list of
+		 *    rows (after filtering)
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.rowCallback
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "rowCallback": function( row, data, displayIndex, displayIndexFull ) {
+		 *          // Bold the grade for all 'A' grade browsers
+		 *          if ( data[4] == "A" ) {
+		 *            $('td:eq(4)', row).html( '<b>A</b>' );
+		 *          }
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnRowCallback": null,
+	
+	
+		/**
+		 * __Deprecated__ The functionality provided by this parameter has now been
+		 * superseded by that provided through `ajax`, which should be used instead.
+		 *
+		 * This parameter allows you to override the default function which obtains
+		 * the data from the server so something more suitable for your application.
+		 * For example you could use POST data, or pull information from a Gears or
+		 * AIR database.
+		 *  @type function
+		 *  @member
+		 *  @param {string} source HTTP source to obtain the data from (`ajax`)
+		 *  @param {array} data A key/value pair object containing the data to send
+		 *    to the server
+		 *  @param {function} callback to be called on completion of the data get
+		 *    process that will draw the data on the page.
+		 *  @param {object} settings DataTables settings object
+		 *
+		 *  @dtopt Callbacks
+		 *  @dtopt Server-side
+		 *  @name DataTable.defaults.serverData
+		 *
+		 *  @deprecated 1.10. Please use `ajax` for this functionality now.
+		 */
+		"fnServerData": null,
+	
+	
+		/**
+		 * __Deprecated__ The functionality provided by this parameter has now been
+		 * superseded by that provided through `ajax`, which should be used instead.
+		 *
+		 *  It is often useful to send extra data to the server when making an Ajax
+		 * request - for example custom filtering information, and this callback
+		 * function makes it trivial to send extra information to the server. The
+		 * passed in parameter is the data set that has been constructed by
+		 * DataTables, and you can add to this or modify it as you require.
+		 *  @type function
+		 *  @param {array} data Data array (array of objects which are name/value
+		 *    pairs) that has been constructed by DataTables and will be sent to the
+		 *    server. In the case of Ajax sourced data with server-side processing
+		 *    this will be an empty array, for server-side processing there will be a
+		 *    significant number of parameters!
+		 *  @returns {undefined} Ensure that you modify the data array passed in,
+		 *    as this is passed by reference.
+		 *
+		 *  @dtopt Callbacks
+		 *  @dtopt Server-side
+		 *  @name DataTable.defaults.serverParams
+		 *
+		 *  @deprecated 1.10. Please use `ajax` for this functionality now.
+		 */
+		"fnServerParams": null,
+	
+	
+		/**
+		 * Load the table state. With this function you can define from where, and how, the
+		 * state of a table is loaded. By default DataTables will load from `localStorage`
+		 * but you might wish to use a server-side database or cookies.
+		 *  @type function
+		 *  @member
+		 *  @param {object} settings DataTables settings object
+		 *  @param {object} callback Callback that can be executed when done. It
+		 *    should be passed the loaded state object.
+		 *  @return {object} The DataTables state object to be loaded
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.stateLoadCallback
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "stateSave": true,
+		 *        "stateLoadCallback": function (settings, callback) {
+		 *          $.ajax( {
+		 *            "url": "/state_load",
+		 *            "dataType": "json",
+		 *            "success": function (json) {
+		 *              callback( json );
+		 *            }
+		 *          } );
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnStateLoadCallback": function ( settings ) {
+			try {
+				return JSON.parse(
+					(settings.iStateDuration === -1 ? sessionStorage : localStorage).getItem(
+						'DataTables_'+settings.sInstance+'_'+location.pathname
+					)
+				);
+			} catch (e) {}
+		},
+	
+	
+		/**
+		 * Callback which allows modification of the saved state prior to loading that state.
+		 * This callback is called when the table is loading state from the stored data, but
+		 * prior to the settings object being modified by the saved state. Note that for
+		 * plug-in authors, you should use the `stateLoadParams` event to load parameters for
+		 * a plug-in.
+		 *  @type function
+		 *  @param {object} settings DataTables settings object
+		 *  @param {object} data The state object that is to be loaded
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.stateLoadParams
+		 *
+		 *  @example
+		 *    // Remove a saved filter, so filtering is never loaded
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "stateSave": true,
+		 *        "stateLoadParams": function (settings, data) {
+		 *          data.oSearch.sSearch = "";
+		 *        }
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Disallow state loading by returning false
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "stateSave": true,
+		 *        "stateLoadParams": function (settings, data) {
+		 *          return false;
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnStateLoadParams": null,
+	
+	
+		/**
+		 * Callback that is called when the state has been loaded from the state saving method
+		 * and the DataTables settings object has been modified as a result of the loaded state.
+		 *  @type function
+		 *  @param {object} settings DataTables settings object
+		 *  @param {object} data The state object that was loaded
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.stateLoaded
+		 *
+		 *  @example
+		 *    // Show an alert with the filtering value that was saved
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "stateSave": true,
+		 *        "stateLoaded": function (settings, data) {
+		 *          alert( 'Saved filter was: '+data.oSearch.sSearch );
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnStateLoaded": null,
+	
+	
+		/**
+		 * Save the table state. This function allows you to define where and how the state
+		 * information for the table is stored By default DataTables will use `localStorage`
+		 * but you might wish to use a server-side database or cookies.
+		 *  @type function
+		 *  @member
+		 *  @param {object} settings DataTables settings object
+		 *  @param {object} data The state object to be saved
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.stateSaveCallback
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "stateSave": true,
+		 *        "stateSaveCallback": function (settings, data) {
+		 *          // Send an Ajax request to the server with the state object
+		 *          $.ajax( {
+		 *            "url": "/state_save",
+		 *            "data": data,
+		 *            "dataType": "json",
+		 *            "method": "POST"
+		 *            "success": function () {}
+		 *          } );
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnStateSaveCallback": function ( settings, data ) {
+			try {
+				(settings.iStateDuration === -1 ? sessionStorage : localStorage).setItem(
+					'DataTables_'+settings.sInstance+'_'+location.pathname,
+					JSON.stringify( data )
+				);
+			} catch (e) {}
+		},
+	
+	
+		/**
+		 * Callback which allows modification of the state to be saved. Called when the table
+		 * has changed state a new state save is required. This method allows modification of
+		 * the state saving object prior to actually doing the save, including addition or
+		 * other state properties or modification. Note that for plug-in authors, you should
+		 * use the `stateSaveParams` event to save parameters for a plug-in.
+		 *  @type function
+		 *  @param {object} settings DataTables settings object
+		 *  @param {object} data The state object to be saved
+		 *
+		 *  @dtopt Callbacks
+		 *  @name DataTable.defaults.stateSaveParams
+		 *
+		 *  @example
+		 *    // Remove a saved filter, so filtering is never saved
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "stateSave": true,
+		 *        "stateSaveParams": function (settings, data) {
+		 *          data.oSearch.sSearch = "";
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"fnStateSaveParams": null,
+	
+	
+		/**
+		 * Duration for which the saved state information is considered valid. After this period
+		 * has elapsed the state will be returned to the default.
+		 * Value is given in seconds.
+		 *  @type int
+		 *  @default 7200 <i>(2 hours)</i>
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.stateDuration
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "stateDuration": 60*60*24; // 1 day
+		 *      } );
+		 *    } )
+		 */
+		"iStateDuration": 7200,
+	
+	
+		/**
+		 * When enabled DataTables will not make a request to the server for the first
+		 * page draw - rather it will use the data already on the page (no sorting etc
+		 * will be applied to it), thus saving on an XHR at load time. `deferLoading`
+		 * is used to indicate that deferred loading is required, but it is also used
+		 * to tell DataTables how many records there are in the full table (allowing
+		 * the information element and pagination to be displayed correctly). In the case
+		 * where a filtering is applied to the table on initial load, this can be
+		 * indicated by giving the parameter as an array, where the first element is
+		 * the number of records available after filtering and the second element is the
+		 * number of records without filtering (allowing the table information element
+		 * to be shown correctly).
+		 *  @type int | array
+		 *  @default null
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.deferLoading
+		 *
+		 *  @example
+		 *    // 57 records available in the table, no filtering applied
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "serverSide": true,
+		 *        "ajax": "scripts/server_processing.php",
+		 *        "deferLoading": 57
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // 57 records after filtering, 100 without filtering (an initial filter applied)
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "serverSide": true,
+		 *        "ajax": "scripts/server_processing.php",
+		 *        "deferLoading": [ 57, 100 ],
+		 *        "search": {
+		 *          "search": "my_filter"
+		 *        }
+		 *      } );
+		 *    } );
+		 */
+		"iDeferLoading": null,
+	
+	
+		/**
+		 * Number of rows to display on a single page when using pagination. If
+		 * feature enabled (`lengthChange`) then the end user will be able to override
+		 * this to a custom setting using a pop-up menu.
+		 *  @type int
+		 *  @default 10
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.pageLength
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "pageLength": 50
+		 *      } );
+		 *    } )
+		 */
+		"iDisplayLength": 10,
+	
+	
+		/**
+		 * Define the starting point for data display when using DataTables with
+		 * pagination. Note that this parameter is the number of records, rather than
+		 * the page number, so if you have 10 records per page and want to start on
+		 * the third page, it should be "20".
+		 *  @type int
+		 *  @default 0
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.displayStart
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "displayStart": 20
+		 *      } );
+		 *    } )
+		 */
+		"iDisplayStart": 0,
+	
+	
+		/**
+		 * By default DataTables allows keyboard navigation of the table (sorting, paging,
+		 * and filtering) by adding a `tabindex` attribute to the required elements. This
+		 * allows you to tab through the controls and press the enter key to activate them.
+		 * The tabindex is default 0, meaning that the tab follows the flow of the document.
+		 * You can overrule this using this parameter if you wish. Use a value of -1 to
+		 * disable built-in keyboard navigation.
+		 *  @type int
+		 *  @default 0
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.tabIndex
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "tabIndex": 1
+		 *      } );
+		 *    } );
+		 */
+		"iTabIndex": 0,
+	
+	
+		/**
+		 * Classes that DataTables assigns to the various components and features
+		 * that it adds to the HTML table. This allows classes to be configured
+		 * during initialisation in addition to through the static
+		 * {@link DataTable.ext.oStdClasses} object).
+		 *  @namespace
+		 *  @name DataTable.defaults.classes
+		 */
+		"oClasses": {},
+	
+	
+		/**
+		 * All strings that DataTables uses in the user interface that it creates
+		 * are defined in this object, allowing you to modified them individually or
+		 * completely replace them all as required.
+		 *  @namespace
+		 *  @name DataTable.defaults.language
+		 */
+		"oLanguage": {
+			/**
+			 * Strings that are used for WAI-ARIA labels and controls only (these are not
+			 * actually visible on the page, but will be read by screenreaders, and thus
+			 * must be internationalised as well).
+			 *  @namespace
+			 *  @name DataTable.defaults.language.aria
+			 */
+			"oAria": {
+				/**
+				 * ARIA label that is added to the table headers when the column may be
+				 * sorted ascending by activing the column (click or return when focused).
+				 * Note that the column header is prefixed to this string.
+				 *  @type string
+				 *  @default : activate to sort column ascending
+				 *
+				 *  @dtopt Language
+				 *  @name DataTable.defaults.language.aria.sortAscending
+				 *
+				 *  @example
+				 *    $(document).ready( function() {
+				 *      $('#example').dataTable( {
+				 *        "language": {
+				 *          "aria": {
+				 *            "sortAscending": " - click/return to sort ascending"
+				 *          }
+				 *        }
+				 *      } );
+				 *    } );
+				 */
+				"sSortAscending": ": activate to sort column ascending",
+	
+				/**
+				 * ARIA label that is added to the table headers when the column may be
+				 * sorted descending by activing the column (click or return when focused).
+				 * Note that the column header is prefixed to this string.
+				 *  @type string
+				 *  @default : activate to sort column ascending
+				 *
+				 *  @dtopt Language
+				 *  @name DataTable.defaults.language.aria.sortDescending
+				 *
+				 *  @example
+				 *    $(document).ready( function() {
+				 *      $('#example').dataTable( {
+				 *        "language": {
+				 *          "aria": {
+				 *            "sortDescending": " - click/return to sort descending"
+				 *          }
+				 *        }
+				 *      } );
+				 *    } );
+				 */
+				"sSortDescending": ": activate to sort column descending"
+			},
+	
+			/**
+			 * Pagination string used by DataTables for the built-in pagination
+			 * control types.
+			 *  @namespace
+			 *  @name DataTable.defaults.language.paginate
+			 */
+			"oPaginate": {
+				/**
+				 * Text to use when using the 'full_numbers' type of pagination for the
+				 * button to take the user to the first page.
+				 *  @type string
+				 *  @default First
+				 *
+				 *  @dtopt Language
+				 *  @name DataTable.defaults.language.paginate.first
+				 *
+				 *  @example
+				 *    $(document).ready( function() {
+				 *      $('#example').dataTable( {
+				 *        "language": {
+				 *          "paginate": {
+				 *            "first": "First page"
+				 *          }
+				 *        }
+				 *      } );
+				 *    } );
+				 */
+				"sFirst": "First",
+	
+	
+				/**
+				 * Text to use when using the 'full_numbers' type of pagination for the
+				 * button to take the user to the last page.
+				 *  @type string
+				 *  @default Last
+				 *
+				 *  @dtopt Language
+				 *  @name DataTable.defaults.language.paginate.last
+				 *
+				 *  @example
+				 *    $(document).ready( function() {
+				 *      $('#example').dataTable( {
+				 *        "language": {
+				 *          "paginate": {
+				 *            "last": "Last page"
+				 *          }
+				 *        }
+				 *      } );
+				 *    } );
+				 */
+				"sLast": "Last",
+	
+	
+				/**
+				 * Text to use for the 'next' pagination button (to take the user to the
+				 * next page).
+				 *  @type string
+				 *  @default Next
+				 *
+				 *  @dtopt Language
+				 *  @name DataTable.defaults.language.paginate.next
+				 *
+				 *  @example
+				 *    $(document).ready( function() {
+				 *      $('#example').dataTable( {
+				 *        "language": {
+				 *          "paginate": {
+				 *            "next": "Next page"
+				 *          }
+				 *        }
+				 *      } );
+				 *    } );
+				 */
+				"sNext": "Next",
+	
+	
+				/**
+				 * Text to use for the 'previous' pagination button (to take the user to
+				 * the previous page).
+				 *  @type string
+				 *  @default Previous
+				 *
+				 *  @dtopt Language
+				 *  @name DataTable.defaults.language.paginate.previous
+				 *
+				 *  @example
+				 *    $(document).ready( function() {
+				 *      $('#example').dataTable( {
+				 *        "language": {
+				 *          "paginate": {
+				 *            "previous": "Previous page"
+				 *          }
+				 *        }
+				 *      } );
+				 *    } );
+				 */
+				"sPrevious": "Previous"
+			},
+	
+			/**
+			 * This string is shown in preference to `zeroRecords` when the table is
+			 * empty of data (regardless of filtering). Note that this is an optional
+			 * parameter - if it is not given, the value of `zeroRecords` will be used
+			 * instead (either the default or given value).
+			 *  @type string
+			 *  @default No data available in table
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.emptyTable
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "emptyTable": "No data available in table"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sEmptyTable": "No data available in table",
+	
+	
+			/**
+			 * This string gives information to the end user about the information
+			 * that is current on display on the page. The following tokens can be
+			 * used in the string and will be dynamically replaced as the table
+			 * display updates. This tokens can be placed anywhere in the string, or
+			 * removed as needed by the language requires:
+			 *
+			 * * `\_START\_` - Display index of the first record on the current page
+			 * * `\_END\_` - Display index of the last record on the current page
+			 * * `\_TOTAL\_` - Number of records in the table after filtering
+			 * * `\_MAX\_` - Number of records in the table without filtering
+			 * * `\_PAGE\_` - Current page number
+			 * * `\_PAGES\_` - Total number of pages of data in the table
+			 *
+			 *  @type string
+			 *  @default Showing _START_ to _END_ of _TOTAL_ entries
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.info
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "info": "Showing page _PAGE_ of _PAGES_"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sInfo": "Showing _START_ to _END_ of _TOTAL_ entries",
+	
+	
+			/**
+			 * Display information string for when the table is empty. Typically the
+			 * format of this string should match `info`.
+			 *  @type string
+			 *  @default Showing 0 to 0 of 0 entries
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.infoEmpty
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "infoEmpty": "No entries to show"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sInfoEmpty": "Showing 0 to 0 of 0 entries",
+	
+	
+			/**
+			 * When a user filters the information in a table, this string is appended
+			 * to the information (`info`) to give an idea of how strong the filtering
+			 * is. The variable _MAX_ is dynamically updated.
+			 *  @type string
+			 *  @default (filtered from _MAX_ total entries)
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.infoFiltered
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "infoFiltered": " - filtering from _MAX_ records"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sInfoFiltered": "(filtered from _MAX_ total entries)",
+	
+	
+			/**
+			 * If can be useful to append extra information to the info string at times,
+			 * and this variable does exactly that. This information will be appended to
+			 * the `info` (`infoEmpty` and `infoFiltered` in whatever combination they are
+			 * being used) at all times.
+			 *  @type string
+			 *  @default <i>Empty string</i>
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.infoPostFix
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "infoPostFix": "All records shown are derived from real information."
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sInfoPostFix": "",
+	
+	
+			/**
+			 * This decimal place operator is a little different from the other
+			 * language options since DataTables doesn't output floating point
+			 * numbers, so it won't ever use this for display of a number. Rather,
+			 * what this parameter does is modify the sort methods of the table so
+			 * that numbers which are in a format which has a character other than
+			 * a period (`.`) as a decimal place will be sorted numerically.
+			 *
+			 * Note that numbers with different decimal places cannot be shown in
+			 * the same table and still be sortable, the table must be consistent.
+			 * However, multiple different tables on the page can use different
+			 * decimal place characters.
+			 *  @type string
+			 *  @default 
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.decimal
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "decimal": ","
+			 *          "thousands": "."
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sDecimal": "",
+	
+	
+			/**
+			 * DataTables has a build in number formatter (`formatNumber`) which is
+			 * used to format large numbers that are used in the table information.
+			 * By default a comma is used, but this can be trivially changed to any
+			 * character you wish with this parameter.
+			 *  @type string
+			 *  @default ,
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.thousands
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "thousands": "'"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sThousands": ",",
+	
+	
+			/**
+			 * Detail the action that will be taken when the drop down menu for the
+			 * pagination length option is changed. The '_MENU_' variable is replaced
+			 * with a default select list of 10, 25, 50 and 100, and can be replaced
+			 * with a custom select box if required.
+			 *  @type string
+			 *  @default Show _MENU_ entries
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.lengthMenu
+			 *
+			 *  @example
+			 *    // Language change only
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "lengthMenu": "Display _MENU_ records"
+			 *        }
+			 *      } );
+			 *    } );
+			 *
+			 *  @example
+			 *    // Language and options change
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "lengthMenu": 'Display <select>'+
+			 *            '<option value="10">10</option>'+
+			 *            '<option value="20">20</option>'+
+			 *            '<option value="30">30</option>'+
+			 *            '<option value="40">40</option>'+
+			 *            '<option value="50">50</option>'+
+			 *            '<option value="-1">All</option>'+
+			 *            '</select> records'
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sLengthMenu": "Show _MENU_ entries",
+	
+	
+			/**
+			 * When using Ajax sourced data and during the first draw when DataTables is
+			 * gathering the data, this message is shown in an empty row in the table to
+			 * indicate to the end user the the data is being loaded. Note that this
+			 * parameter is not used when loading data by server-side processing, just
+			 * Ajax sourced data with client-side processing.
+			 *  @type string
+			 *  @default Loading...
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.loadingRecords
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "loadingRecords": "Please wait - loading..."
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sLoadingRecords": "Loading...",
+	
+	
+			/**
+			 * Text which is displayed when the table is processing a user action
+			 * (usually a sort command or similar).
+			 *  @type string
+			 *  @default Processing...
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.processing
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "processing": "DataTables is currently busy"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sProcessing": "Processing...",
+	
+	
+			/**
+			 * Details the actions that will be taken when the user types into the
+			 * filtering input text box. The variable "_INPUT_", if used in the string,
+			 * is replaced with the HTML text box for the filtering input allowing
+			 * control over where it appears in the string. If "_INPUT_" is not given
+			 * then the input box is appended to the string automatically.
+			 *  @type string
+			 *  @default Search:
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.search
+			 *
+			 *  @example
+			 *    // Input text box will be appended at the end automatically
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "search": "Filter records:"
+			 *        }
+			 *      } );
+			 *    } );
+			 *
+			 *  @example
+			 *    // Specify where the filter should appear
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "search": "Apply filter _INPUT_ to table"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sSearch": "Search:",
+	
+	
+			/**
+			 * Assign a `placeholder` attribute to the search `input` element
+			 *  @type string
+			 *  @default 
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.searchPlaceholder
+			 */
+			"sSearchPlaceholder": "",
+	
+	
+			/**
+			 * All of the language information can be stored in a file on the
+			 * server-side, which DataTables will look up if this parameter is passed.
+			 * It must store the URL of the language file, which is in a JSON format,
+			 * and the object has the same properties as the oLanguage object in the
+			 * initialiser object (i.e. the above parameters). Please refer to one of
+			 * the example language files to see how this works in action.
+			 *  @type string
+			 *  @default <i>Empty string - i.e. disabled</i>
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.url
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "url": "http://www.sprymedia.co.uk/dataTables/lang.txt"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sUrl": "",
+	
+	
+			/**
+			 * Text shown inside the table records when the is no information to be
+			 * displayed after filtering. `emptyTable` is shown when there is simply no
+			 * information in the table at all (regardless of filtering).
+			 *  @type string
+			 *  @default No matching records found
+			 *
+			 *  @dtopt Language
+			 *  @name DataTable.defaults.language.zeroRecords
+			 *
+			 *  @example
+			 *    $(document).ready( function() {
+			 *      $('#example').dataTable( {
+			 *        "language": {
+			 *          "zeroRecords": "No records to display"
+			 *        }
+			 *      } );
+			 *    } );
+			 */
+			"sZeroRecords": "No matching records found"
+		},
+	
+	
+		/**
+		 * This parameter allows you to have define the global filtering state at
+		 * initialisation time. As an object the `search` parameter must be
+		 * defined, but all other parameters are optional. When `regex` is true,
+		 * the search string will be treated as a regular expression, when false
+		 * (default) it will be treated as a straight string. When `smart`
+		 * DataTables will use it's smart filtering methods (to word match at
+		 * any point in the data), when false this will not be done.
+		 *  @namespace
+		 *  @extends DataTable.models.oSearch
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.search
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "search": {"search": "Initial search"}
+		 *      } );
+		 *    } )
+		 */
+		"oSearch": $.extend( {}, DataTable.models.oSearch ),
+	
+	
+		/**
+		 * __Deprecated__ The functionality provided by this parameter has now been
+		 * superseded by that provided through `ajax`, which should be used instead.
+		 *
+		 * By default DataTables will look for the property `data` (or `aaData` for
+		 * compatibility with DataTables 1.9-) when obtaining data from an Ajax
+		 * source or for server-side processing - this parameter allows that
+		 * property to be changed. You can use Javascript dotted object notation to
+		 * get a data source for multiple levels of nesting.
+		 *  @type string
+		 *  @default data
+		 *
+		 *  @dtopt Options
+		 *  @dtopt Server-side
+		 *  @name DataTable.defaults.ajaxDataProp
+		 *
+		 *  @deprecated 1.10. Please use `ajax` for this functionality now.
+		 */
+		"sAjaxDataProp": "data",
+	
+	
+		/**
+		 * __Deprecated__ The functionality provided by this parameter has now been
+		 * superseded by that provided through `ajax`, which should be used instead.
+		 *
+		 * You can instruct DataTables to load data from an external
+		 * source using this parameter (use aData if you want to pass data in you
+		 * already have). Simply provide a url a JSON object can be obtained from.
+		 *  @type string
+		 *  @default null
+		 *
+		 *  @dtopt Options
+		 *  @dtopt Server-side
+		 *  @name DataTable.defaults.ajaxSource
+		 *
+		 *  @deprecated 1.10. Please use `ajax` for this functionality now.
+		 */
+		"sAjaxSource": null,
+	
+	
+		/**
+		 * This initialisation variable allows you to specify exactly where in the
+		 * DOM you want DataTables to inject the various controls it adds to the page
+		 * (for example you might want the pagination controls at the top of the
+		 * table). DIV elements (with or without a custom class) can also be added to
+		 * aid styling. The follow syntax is used:
+		 *   <ul>
+		 *     <li>The following options are allowed:
+		 *       <ul>
+		 *         <li>'l' - Length changing</li>
+		 *         <li>'f' - Filtering input</li>
+		 *         <li>'t' - The table!</li>
+		 *         <li>'i' - Information</li>
+		 *         <li>'p' - Pagination</li>
+		 *         <li>'r' - pRocessing</li>
+		 *       </ul>
+		 *     </li>
+		 *     <li>The following constants are allowed:
+		 *       <ul>
+		 *         <li>'H' - jQueryUI theme "header" classes ('fg-toolbar ui-widget-header ui-corner-tl ui-corner-tr ui-helper-clearfix')</li>
+		 *         <li>'F' - jQueryUI theme "footer" classes ('fg-toolbar ui-widget-header ui-corner-bl ui-corner-br ui-helper-clearfix')</li>
+		 *       </ul>
+		 *     </li>
+		 *     <li>The following syntax is expected:
+		 *       <ul>
+		 *         <li>'&lt;' and '&gt;' - div elements</li>
+		 *         <li>'&lt;"class" and '&gt;' - div with a class</li>
+		 *         <li>'&lt;"#id" and '&gt;' - div with an ID</li>
+		 *       </ul>
+		 *     </li>
+		 *     <li>Examples:
+		 *       <ul>
+		 *         <li>'&lt;"wrapper"flipt&gt;'</li>
+		 *         <li>'&lt;lf&lt;t&gt;ip&gt;'</li>
+		 *       </ul>
+		 *     </li>
+		 *   </ul>
+		 *  @type string
+		 *  @default lfrtip <i>(when `jQueryUI` is false)</i> <b>or</b>
+		 *    <"H"lfr>t<"F"ip> <i>(when `jQueryUI` is true)</i>
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.dom
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "dom": '&lt;"top"i&gt;rt&lt;"bottom"flp&gt;&lt;"clear"&gt;'
+		 *      } );
+		 *    } );
+		 */
+		"sDom": "lfrtip",
+	
+	
+		/**
+		 * Search delay option. This will throttle full table searches that use the
+		 * DataTables provided search input element (it does not effect calls to
+		 * `dt-api search()`, providing a delay before the search is made.
+		 *  @type integer
+		 *  @default 0
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.searchDelay
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "searchDelay": 200
+		 *      } );
+		 *    } )
+		 */
+		"searchDelay": null,
+	
+	
+		/**
+		 * DataTables features six different built-in options for the buttons to
+		 * display for pagination control:
+		 *
+		 * * `numbers` - Page number buttons only
+		 * * `simple` - 'Previous' and 'Next' buttons only
+		 * * 'simple_numbers` - 'Previous' and 'Next' buttons, plus page numbers
+		 * * `full` - 'First', 'Previous', 'Next' and 'Last' buttons
+		 * * `full_numbers` - 'First', 'Previous', 'Next' and 'Last' buttons, plus page numbers
+		 * * `first_last_numbers` - 'First' and 'Last' buttons, plus page numbers
+		 *  
+		 * Further methods can be added using {@link DataTable.ext.oPagination}.
+		 *  @type string
+		 *  @default simple_numbers
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.pagingType
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "pagingType": "full_numbers"
+		 *      } );
+		 *    } )
+		 */
+		"sPaginationType": "simple_numbers",
+	
+	
+		/**
+		 * Enable horizontal scrolling. When a table is too wide to fit into a
+		 * certain layout, or you have a large number of columns in the table, you
+		 * can enable x-scrolling to show the table in a viewport, which can be
+		 * scrolled. This property can be `true` which will allow the table to
+		 * scroll horizontally when needed, or any CSS unit, or a number (in which
+		 * case it will be treated as a pixel measurement). Setting as simply `true`
+		 * is recommended.
+		 *  @type boolean|string
+		 *  @default <i>blank string - i.e. disabled</i>
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.scrollX
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "scrollX": true,
+		 *        "scrollCollapse": true
+		 *      } );
+		 *    } );
+		 */
+		"sScrollX": "",
+	
+	
+		/**
+		 * This property can be used to force a DataTable to use more width than it
+		 * might otherwise do when x-scrolling is enabled. For example if you have a
+		 * table which requires to be well spaced, this parameter is useful for
+		 * "over-sizing" the table, and thus forcing scrolling. This property can by
+		 * any CSS unit, or a number (in which case it will be treated as a pixel
+		 * measurement).
+		 *  @type string
+		 *  @default <i>blank string - i.e. disabled</i>
+		 *
+		 *  @dtopt Options
+		 *  @name DataTable.defaults.scrollXInner
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "scrollX": "100%",
+		 *        "scrollXInner": "110%"
+		 *      } );
+		 *    } );
+		 */
+		"sScrollXInner": "",
+	
+	
+		/**
+		 * Enable vertical scrolling. Vertical scrolling will constrain the DataTable
+		 * to the given height, and enable scrolling for any data which overflows the
+		 * current viewport. This can be used as an alternative to paging to display
+		 * a lot of data in a small area (although paging and scrolling can both be
+		 * enabled at the same time). This property can be any CSS unit, or a number
+		 * (in which case it will be treated as a pixel measurement).
+		 *  @type string
+		 *  @default <i>blank string - i.e. disabled</i>
+		 *
+		 *  @dtopt Features
+		 *  @name DataTable.defaults.scrollY
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "scrollY": "200px",
+		 *        "paginate": false
+		 *      } );
+		 *    } );
+		 */
+		"sScrollY": "",
+	
+	
+		/**
+		 * __Deprecated__ The functionality provided by this parameter has now been
+		 * superseded by that provided through `ajax`, which should be used instead.
+		 *
+		 * Set the HTTP method that is used to make the Ajax call for server-side
+		 * processing or Ajax sourced data.
+		 *  @type string
+		 *  @default GET
+		 *
+		 *  @dtopt Options
+		 *  @dtopt Server-side
+		 *  @name DataTable.defaults.serverMethod
+		 *
+		 *  @deprecated 1.10. Please use `ajax` for this functionality now.
+		 */
+		"sServerMethod": "GET",
+	
+	
+		/**
+		 * DataTables makes use of renderers when displaying HTML elements for
+		 * a table. These renderers can be added or modified by plug-ins to
+		 * generate suitable mark-up for a site. For example the Bootstrap
+		 * integration plug-in for DataTables uses a paging button renderer to
+		 * display pagination buttons in the mark-up required by Bootstrap.
+		 *
+		 * For further information about the renderers available see
+		 * DataTable.ext.renderer
+		 *  @type string|object
+		 *  @default null
+		 *
+		 *  @name DataTable.defaults.renderer
+		 *
+		 */
+		"renderer": null,
+	
+	
+		/**
+		 * Set the data property name that DataTables should use to get a row's id
+		 * to set as the `id` property in the node.
+		 *  @type string
+		 *  @default DT_RowId
+		 *
+		 *  @name DataTable.defaults.rowId
+		 */
+		"rowId": "DT_RowId"
+	};
+	
+	_fnHungarianMap( DataTable.defaults );
+	
+	
+	
+	/*
+	 * Developer note - See note in model.defaults.js about the use of Hungarian
+	 * notation and camel case.
+	 */
+	
+	/**
+	 * Column options that can be given to DataTables at initialisation time.
+	 *  @namespace
+	 */
+	DataTable.defaults.column = {
+		/**
+		 * Define which column(s) an order will occur on for this column. This
+		 * allows a column's ordering to take multiple columns into account when
+		 * doing a sort or use the data from a different column. For example first
+		 * name / last name columns make sense to do a multi-column sort over the
+		 * two columns.
+		 *  @type array|int
+		 *  @default null <i>Takes the value of the column index automatically</i>
+		 *
+		 *  @name DataTable.defaults.column.orderData
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "orderData": [ 0, 1 ], "targets": [ 0 ] },
+		 *          { "orderData": [ 1, 0 ], "targets": [ 1 ] },
+		 *          { "orderData": 2, "targets": [ 2 ] }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "orderData": [ 0, 1 ] },
+		 *          { "orderData": [ 1, 0 ] },
+		 *          { "orderData": 2 },
+		 *          null,
+		 *          null
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"aDataSort": null,
+		"iDataSort": -1,
+	
+	
+		/**
+		 * You can control the default ordering direction, and even alter the
+		 * behaviour of the sort handler (i.e. only allow ascending ordering etc)
+		 * using this parameter.
+		 *  @type array
+		 *  @default [ 'asc', 'desc' ]
+		 *
+		 *  @name DataTable.defaults.column.orderSequence
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "orderSequence": [ "asc" ], "targets": [ 1 ] },
+		 *          { "orderSequence": [ "desc", "asc", "asc" ], "targets": [ 2 ] },
+		 *          { "orderSequence": [ "desc" ], "targets": [ 3 ] }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          null,
+		 *          { "orderSequence": [ "asc" ] },
+		 *          { "orderSequence": [ "desc", "asc", "asc" ] },
+		 *          { "orderSequence": [ "desc" ] },
+		 *          null
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"asSorting": [ 'asc', 'desc' ],
+	
+	
+		/**
+		 * Enable or disable filtering on the data in this column.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @name DataTable.defaults.column.searchable
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "searchable": false, "targets": [ 0 ] }
+		 *        ] } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "searchable": false },
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          null
+		 *        ] } );
+		 *    } );
+		 */
+		"bSearchable": true,
+	
+	
+		/**
+		 * Enable or disable ordering on this column.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @name DataTable.defaults.column.orderable
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "orderable": false, "targets": [ 0 ] }
+		 *        ] } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "orderable": false },
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          null
+		 *        ] } );
+		 *    } );
+		 */
+		"bSortable": true,
+	
+	
+		/**
+		 * Enable or disable the display of this column.
+		 *  @type boolean
+		 *  @default true
+		 *
+		 *  @name DataTable.defaults.column.visible
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "visible": false, "targets": [ 0 ] }
+		 *        ] } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "visible": false },
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          null
+		 *        ] } );
+		 *    } );
+		 */
+		"bVisible": true,
+	
+	
+		/**
+		 * Developer definable function that is called whenever a cell is created (Ajax source,
+		 * etc) or processed for input (DOM source). This can be used as a compliment to mRender
+		 * allowing you to modify the DOM element (add background colour for example) when the
+		 * element is available.
+		 *  @type function
+		 *  @param {element} td The TD node that has been created
+		 *  @param {*} cellData The Data for the cell
+		 *  @param {array|object} rowData The data for the whole row
+		 *  @param {int} row The row index for the aoData data store
+		 *  @param {int} col The column index for aoColumns
+		 *
+		 *  @name DataTable.defaults.column.createdCell
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [ {
+		 *          "targets": [3],
+		 *          "createdCell": function (td, cellData, rowData, row, col) {
+		 *            if ( cellData == "1.7" ) {
+		 *              $(td).css('color', 'blue')
+		 *            }
+		 *          }
+		 *        } ]
+		 *      });
+		 *    } );
+		 */
+		"fnCreatedCell": null,
+	
+	
+		/**
+		 * This parameter has been replaced by `data` in DataTables to ensure naming
+		 * consistency. `dataProp` can still be used, as there is backwards
+		 * compatibility in DataTables for this option, but it is strongly
+		 * recommended that you use `data` in preference to `dataProp`.
+		 *  @name DataTable.defaults.column.dataProp
+		 */
+	
+	
+		/**
+		 * This property can be used to read data from any data source property,
+		 * including deeply nested objects / properties. `data` can be given in a
+		 * number of different ways which effect its behaviour:
+		 *
+		 * * `integer` - treated as an array index for the data source. This is the
+		 *   default that DataTables uses (incrementally increased for each column).
+		 * * `string` - read an object property from the data source. There are
+		 *   three 'special' options that can be used in the string to alter how
+		 *   DataTables reads the data from the source object:
+		 *    * `.` - Dotted Javascript notation. Just as you use a `.` in
+		 *      Javascript to read from nested objects, so to can the options
+		 *      specified in `data`. For example: `browser.version` or
+		 *      `browser.name`. If your object parameter name contains a period, use
+		 *      `\\` to escape it - i.e. `first\\.name`.
+		 *    * `[]` - Array notation. DataTables can automatically combine data
+		 *      from and array source, joining the data with the characters provided
+		 *      between the two brackets. For example: `name[, ]` would provide a
+		 *      comma-space separated list from the source array. If no characters
+		 *      are provided between the brackets, the original array source is
+		 *      returned.
+		 *    * `()` - Function notation. Adding `()` to the end of a parameter will
+		 *      execute a function of the name given. For example: `browser()` for a
+		 *      simple function on the data source, `browser.version()` for a
+		 *      function in a nested property or even `browser().version` to get an
+		 *      object property if the function called returns an object. Note that
+		 *      function notation is recommended for use in `render` rather than
+		 *      `data` as it is much simpler to use as a renderer.
+		 * * `null` - use the original data source for the row rather than plucking
+		 *   data directly from it. This action has effects on two other
+		 *   initialisation options:
+		 *    * `defaultContent` - When null is given as the `data` option and
+		 *      `defaultContent` is specified for the column, the value defined by
+		 *      `defaultContent` will be used for the cell.
+		 *    * `render` - When null is used for the `data` option and the `render`
+		 *      option is specified for the column, the whole data source for the
+		 *      row is used for the renderer.
+		 * * `function` - the function given will be executed whenever DataTables
+		 *   needs to set or get the data for a cell in the column. The function
+		 *   takes three parameters:
+		 *    * Parameters:
+		 *      * `{array|object}` The data source for the row
+		 *      * `{string}` The type call data requested - this will be 'set' when
+		 *        setting data or 'filter', 'display', 'type', 'sort' or undefined
+		 *        when gathering data. Note that when `undefined` is given for the
+		 *        type DataTables expects to get the raw data for the object back<
+		 *      * `{*}` Data to set when the second parameter is 'set'.
+		 *    * Return:
+		 *      * The return value from the function is not required when 'set' is
+		 *        the type of call, but otherwise the return is what will be used
+		 *        for the data requested.
+		 *
+		 * Note that `data` is a getter and setter option. If you just require
+		 * formatting of data for output, you will likely want to use `render` which
+		 * is simply a getter and thus simpler to use.
+		 *
+		 * Note that prior to DataTables 1.9.2 `data` was called `mDataProp`. The
+		 * name change reflects the flexibility of this property and is consistent
+		 * with the naming of mRender. If 'mDataProp' is given, then it will still
+		 * be used by DataTables, as it automatically maps the old name to the new
+		 * if required.
+		 *
+		 *  @type string|int|function|null
+		 *  @default null <i>Use automatically calculated column index</i>
+		 *
+		 *  @name DataTable.defaults.column.data
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Read table data from objects
+		 *    // JSON structure for each row:
+		 *    //   {
+		 *    //      "engine": {value},
+		 *    //      "browser": {value},
+		 *    //      "platform": {value},
+		 *    //      "version": {value},
+		 *    //      "grade": {value}
+		 *    //   }
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "ajaxSource": "sources/objects.txt",
+		 *        "columns": [
+		 *          { "data": "engine" },
+		 *          { "data": "browser" },
+		 *          { "data": "platform" },
+		 *          { "data": "version" },
+		 *          { "data": "grade" }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Read information from deeply nested objects
+		 *    // JSON structure for each row:
+		 *    //   {
+		 *    //      "engine": {value},
+		 *    //      "browser": {value},
+		 *    //      "platform": {
+		 *    //         "inner": {value}
+		 *    //      },
+		 *    //      "details": [
+		 *    //         {value}, {value}
+		 *    //      ]
+		 *    //   }
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "ajaxSource": "sources/deep.txt",
+		 *        "columns": [
+		 *          { "data": "engine" },
+		 *          { "data": "browser" },
+		 *          { "data": "platform.inner" },
+		 *          { "data": "platform.details.0" },
+		 *          { "data": "platform.details.1" }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `data` as a function to provide different information for
+		 *    // sorting, filtering and display. In this case, currency (price)
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [ {
+		 *          "targets": [ 0 ],
+		 *          "data": function ( source, type, val ) {
+		 *            if (type === 'set') {
+		 *              source.price = val;
+		 *              // Store the computed dislay and filter values for efficiency
+		 *              source.price_display = val=="" ? "" : "$"+numberFormat(val);
+		 *              source.price_filter  = val=="" ? "" : "$"+numberFormat(val)+" "+val;
+		 *              return;
+		 *            }
+		 *            else if (type === 'display') {
+		 *              return source.price_display;
+		 *            }
+		 *            else if (type === 'filter') {
+		 *              return source.price_filter;
+		 *            }
+		 *            // 'sort', 'type' and undefined all just use the integer
+		 *            return source.price;
+		 *          }
+		 *        } ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using default content
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [ {
+		 *          "targets": [ 0 ],
+		 *          "data": null,
+		 *          "defaultContent": "Click to edit"
+		 *        } ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using array notation - outputting a list from an array
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [ {
+		 *          "targets": [ 0 ],
+		 *          "data": "name[, ]"
+		 *        } ]
+		 *      } );
+		 *    } );
+		 *
+		 */
+		"mData": null,
+	
+	
+		/**
+		 * This property is the rendering partner to `data` and it is suggested that
+		 * when you want to manipulate data for display (including filtering,
+		 * sorting etc) without altering the underlying data for the table, use this
+		 * property. `render` can be considered to be the the read only companion to
+		 * `data` which is read / write (then as such more complex). Like `data`
+		 * this option can be given in a number of different ways to effect its
+		 * behaviour:
+		 *
+		 * * `integer` - treated as an array index for the data source. This is the
+		 *   default that DataTables uses (incrementally increased for each column).
+		 * * `string` - read an object property from the data source. There are
+		 *   three 'special' options that can be used in the string to alter how
+		 *   DataTables reads the data from the source object:
+		 *    * `.` - Dotted Javascript notation. Just as you use a `.` in
+		 *      Javascript to read from nested objects, so to can the options
+		 *      specified in `data`. For example: `browser.version` or
+		 *      `browser.name`. If your object parameter name contains a period, use
+		 *      `\\` to escape it - i.e. `first\\.name`.
+		 *    * `[]` - Array notation. DataTables can automatically combine data
+		 *      from and array source, joining the data with the characters provided
+		 *      between the two brackets. For example: `name[, ]` would provide a
+		 *      comma-space separated list from the source array. If no characters
+		 *      are provided between the brackets, the original array source is
+		 *      returned.
+		 *    * `()` - Function notation. Adding `()` to the end of a parameter will
+		 *      execute a function of the name given. For example: `browser()` for a
+		 *      simple function on the data source, `browser.version()` for a
+		 *      function in a nested property or even `browser().version` to get an
+		 *      object property if the function called returns an object.
+		 * * `object` - use different data for the different data types requested by
+		 *   DataTables ('filter', 'display', 'type' or 'sort'). The property names
+		 *   of the object is the data type the property refers to and the value can
+		 *   defined using an integer, string or function using the same rules as
+		 *   `render` normally does. Note that an `_` option _must_ be specified.
+		 *   This is the default value to use if you haven't specified a value for
+		 *   the data type requested by DataTables.
+		 * * `function` - the function given will be executed whenever DataTables
+		 *   needs to set or get the data for a cell in the column. The function
+		 *   takes three parameters:
+		 *    * Parameters:
+		 *      * {array|object} The data source for the row (based on `data`)
+		 *      * {string} The type call data requested - this will be 'filter',
+		 *        'display', 'type' or 'sort'.
+		 *      * {array|object} The full data source for the row (not based on
+		 *        `data`)
+		 *    * Return:
+		 *      * The return value from the function is what will be used for the
+		 *        data requested.
+		 *
+		 *  @type string|int|function|object|null
+		 *  @default null Use the data source value.
+		 *
+		 *  @name DataTable.defaults.column.render
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Create a comma separated list from an array of objects
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "ajaxSource": "sources/deep.txt",
+		 *        "columns": [
+		 *          { "data": "engine" },
+		 *          { "data": "browser" },
+		 *          {
+		 *            "data": "platform",
+		 *            "render": "[, ].name"
+		 *          }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Execute a function to obtain data
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [ {
+		 *          "targets": [ 0 ],
+		 *          "data": null, // Use the full data source object for the renderer's source
+		 *          "render": "browserName()"
+		 *        } ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // As an object, extracting different data for the different types
+		 *    // This would be used with a data source such as:
+		 *    //   { "phone": 5552368, "phone_filter": "5552368 555-2368", "phone_display": "555-2368" }
+		 *    // Here the `phone` integer is used for sorting and type detection, while `phone_filter`
+		 *    // (which has both forms) is used for filtering for if a user inputs either format, while
+		 *    // the formatted phone number is the one that is shown in the table.
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [ {
+		 *          "targets": [ 0 ],
+		 *          "data": null, // Use the full data source object for the renderer's source
+		 *          "render": {
+		 *            "_": "phone",
+		 *            "filter": "phone_filter",
+		 *            "display": "phone_display"
+		 *          }
+		 *        } ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Use as a function to create a link from the data source
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [ {
+		 *          "targets": [ 0 ],
+		 *          "data": "download_link",
+		 *          "render": function ( data, type, full ) {
+		 *            return '<a href="'+data+'">Download</a>';
+		 *          }
+		 *        } ]
+		 *      } );
+		 *    } );
+		 */
+		"mRender": null,
+	
+	
+		/**
+		 * Change the cell type created for the column - either TD cells or TH cells. This
+		 * can be useful as TH cells have semantic meaning in the table body, allowing them
+		 * to act as a header for a row (you may wish to add scope='row' to the TH elements).
+		 *  @type string
+		 *  @default td
+		 *
+		 *  @name DataTable.defaults.column.cellType
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Make the first column use TH cells
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [ {
+		 *          "targets": [ 0 ],
+		 *          "cellType": "th"
+		 *        } ]
+		 *      } );
+		 *    } );
+		 */
+		"sCellType": "td",
+	
+	
+		/**
+		 * Class to give to each cell in this column.
+		 *  @type string
+		 *  @default <i>Empty string</i>
+		 *
+		 *  @name DataTable.defaults.column.class
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "class": "my_class", "targets": [ 0 ] }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "class": "my_class" },
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          null
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"sClass": "",
+	
+		/**
+		 * When DataTables calculates the column widths to assign to each column,
+		 * it finds the longest string in each column and then constructs a
+		 * temporary table and reads the widths from that. The problem with this
+		 * is that "mmm" is much wider then "iiii", but the latter is a longer
+		 * string - thus the calculation can go wrong (doing it properly and putting
+		 * it into an DOM object and measuring that is horribly(!) slow). Thus as
+		 * a "work around" we provide this option. It will append its value to the
+		 * text that is found to be the longest string for the column - i.e. padding.
+		 * Generally you shouldn't need this!
+		 *  @type string
+		 *  @default <i>Empty string<i>
+		 *
+		 *  @name DataTable.defaults.column.contentPadding
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          {
+		 *            "contentPadding": "mmm"
+		 *          }
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"sContentPadding": "",
+	
+	
+		/**
+		 * Allows a default value to be given for a column's data, and will be used
+		 * whenever a null data source is encountered (this can be because `data`
+		 * is set to null, or because the data source itself is null).
+		 *  @type string
+		 *  @default null
+		 *
+		 *  @name DataTable.defaults.column.defaultContent
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          {
+		 *            "data": null,
+		 *            "defaultContent": "Edit",
+		 *            "targets": [ -1 ]
+		 *          }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          {
+		 *            "data": null,
+		 *            "defaultContent": "Edit"
+		 *          }
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"sDefaultContent": null,
+	
+	
+		/**
+		 * This parameter is only used in DataTables' server-side processing. It can
+		 * be exceptionally useful to know what columns are being displayed on the
+		 * client side, and to map these to database fields. When defined, the names
+		 * also allow DataTables to reorder information from the server if it comes
+		 * back in an unexpected order (i.e. if you switch your columns around on the
+		 * client-side, your server-side code does not also need updating).
+		 *  @type string
+		 *  @default <i>Empty string</i>
+		 *
+		 *  @name DataTable.defaults.column.name
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "name": "engine", "targets": [ 0 ] },
+		 *          { "name": "browser", "targets": [ 1 ] },
+		 *          { "name": "platform", "targets": [ 2 ] },
+		 *          { "name": "version", "targets": [ 3 ] },
+		 *          { "name": "grade", "targets": [ 4 ] }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "name": "engine" },
+		 *          { "name": "browser" },
+		 *          { "name": "platform" },
+		 *          { "name": "version" },
+		 *          { "name": "grade" }
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"sName": "",
+	
+	
+		/**
+		 * Defines a data source type for the ordering which can be used to read
+		 * real-time information from the table (updating the internally cached
+		 * version) prior to ordering. This allows ordering to occur on user
+		 * editable elements such as form inputs.
+		 *  @type string
+		 *  @default std
+		 *
+		 *  @name DataTable.defaults.column.orderDataType
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "orderDataType": "dom-text", "targets": [ 2, 3 ] },
+		 *          { "type": "numeric", "targets": [ 3 ] },
+		 *          { "orderDataType": "dom-select", "targets": [ 4 ] },
+		 *          { "orderDataType": "dom-checkbox", "targets": [ 5 ] }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          null,
+		 *          null,
+		 *          { "orderDataType": "dom-text" },
+		 *          { "orderDataType": "dom-text", "type": "numeric" },
+		 *          { "orderDataType": "dom-select" },
+		 *          { "orderDataType": "dom-checkbox" }
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"sSortDataType": "std",
+	
+	
+		/**
+		 * The title of this column.
+		 *  @type string
+		 *  @default null <i>Derived from the 'TH' value for this column in the
+		 *    original HTML table.</i>
+		 *
+		 *  @name DataTable.defaults.column.title
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "title": "My column title", "targets": [ 0 ] }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "title": "My column title" },
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          null
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"sTitle": null,
+	
+	
+		/**
+		 * The type allows you to specify how the data for this column will be
+		 * ordered. Four types (string, numeric, date and html (which will strip
+		 * HTML tags before ordering)) are currently available. Note that only date
+		 * formats understood by Javascript's Date() object will be accepted as type
+		 * date. For example: "Mar 26, 2008 5:03 PM". May take the values: 'string',
+		 * 'numeric', 'date' or 'html' (by default). Further types can be adding
+		 * through plug-ins.
+		 *  @type string
+		 *  @default null <i>Auto-detected from raw data</i>
+		 *
+		 *  @name DataTable.defaults.column.type
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "type": "html", "targets": [ 0 ] }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "type": "html" },
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          null
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"sType": null,
+	
+	
+		/**
+		 * Defining the width of the column, this parameter may take any CSS value
+		 * (3em, 20px etc). DataTables applies 'smart' widths to columns which have not
+		 * been given a specific width through this interface ensuring that the table
+		 * remains readable.
+		 *  @type string
+		 *  @default null <i>Automatic</i>
+		 *
+		 *  @name DataTable.defaults.column.width
+		 *  @dtopt Columns
+		 *
+		 *  @example
+		 *    // Using `columnDefs`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columnDefs": [
+		 *          { "width": "20%", "targets": [ 0 ] }
+		 *        ]
+		 *      } );
+		 *    } );
+		 *
+		 *  @example
+		 *    // Using `columns`
+		 *    $(document).ready( function() {
+		 *      $('#example').dataTable( {
+		 *        "columns": [
+		 *          { "width": "20%" },
+		 *          null,
+		 *          null,
+		 *          null,
+		 *          null
+		 *        ]
+		 *      } );
+		 *    } );
+		 */
+		"sWidth": null
+	};
+	
+	_fnHungarianMap( DataTable.defaults.column );
+	
+	
+	
+	/**
+	 * DataTables settings object - this holds all the information needed for a
+	 * given table, including configuration, data and current application of the
+	 * table options. DataTables does not have a single instance for each DataTable
+	 * with the settings attached to that instance, but rather instances of the
+	 * DataTable "class" are created on-the-fly as needed (typically by a
+	 * $().dataTable() call) and the settings object is then applied to that
+	 * instance.
+	 *
+	 * Note that this object is related to {@link DataTable.defaults} but this
+	 * one is the internal data store for DataTables's cache of columns. It should
+	 * NOT be manipulated outside of DataTables. Any configuration should be done
+	 * through the initialisation options.
+	 *  @namespace
+	 *  @todo Really should attach the settings object to individual instances so we
+	 *    don't need to create new instances on each $().dataTable() call (if the
+	 *    table already exists). It would also save passing oSettings around and
+	 *    into every single function. However, this is a very significant
+	 *    architecture change for DataTables and will almost certainly break
+	 *    backwards compatibility with older installations. This is something that
+	 *    will be done in 2.0.
+	 */
+	DataTable.models.oSettings = {
+		/**
+		 * Primary features of DataTables and their enablement state.
+		 *  @namespace
+		 */
+		"oFeatures": {
+	
+			/**
+			 * Flag to say if DataTables should automatically try to calculate the
+			 * optimum table and columns widths (true) or not (false).
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bAutoWidth": null,
+	
+			/**
+			 * Delay the creation of TR and TD elements until they are actually
+			 * needed by a driven page draw. This can give a significant speed
+			 * increase for Ajax source and Javascript source data, but makes no
+			 * difference at all fro DOM and server-side processing tables.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bDeferRender": null,
+	
+			/**
+			 * Enable filtering on the table or not. Note that if this is disabled
+			 * then there is no filtering at all on the table, including fnFilter.
+			 * To just remove the filtering input use sDom and remove the 'f' option.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bFilter": null,
+	
+			/**
+			 * Table information element (the 'Showing x of y records' div) enable
+			 * flag.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bInfo": null,
+	
+			/**
+			 * Present a user control allowing the end user to change the page size
+			 * when pagination is enabled.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bLengthChange": null,
+	
+			/**
+			 * Pagination enabled or not. Note that if this is disabled then length
+			 * changing must also be disabled.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bPaginate": null,
+	
+			/**
+			 * Processing indicator enable flag whenever DataTables is enacting a
+			 * user request - typically an Ajax request for server-side processing.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bProcessing": null,
+	
+			/**
+			 * Server-side processing enabled flag - when enabled DataTables will
+			 * get all data from the server for every draw - there is no filtering,
+			 * sorting or paging done on the client-side.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bServerSide": null,
+	
+			/**
+			 * Sorting enablement flag.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bSort": null,
+	
+			/**
+			 * Multi-column sorting
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bSortMulti": null,
+	
+			/**
+			 * Apply a class to the columns which are being sorted to provide a
+			 * visual highlight or not. This can slow things down when enabled since
+			 * there is a lot of DOM interaction.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bSortClasses": null,
+	
+			/**
+			 * State saving enablement flag.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bStateSave": null
+		},
+	
+	
+		/**
+		 * Scrolling settings for a table.
+		 *  @namespace
+		 */
+		"oScroll": {
+			/**
+			 * When the table is shorter in height than sScrollY, collapse the
+			 * table container down to the height of the table (when true).
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type boolean
+			 */
+			"bCollapse": null,
+	
+			/**
+			 * Width of the scrollbar for the web-browser's platform. Calculated
+			 * during table initialisation.
+			 *  @type int
+			 *  @default 0
+			 */
+			"iBarWidth": 0,
+	
+			/**
+			 * Viewport width for horizontal scrolling. Horizontal scrolling is
+			 * disabled if an empty string.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type string
+			 */
+			"sX": null,
+	
+			/**
+			 * Width to expand the table to when using x-scrolling. Typically you
+			 * should not need to use this.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type string
+			 *  @deprecated
+			 */
+			"sXInner": null,
+	
+			/**
+			 * Viewport height for vertical scrolling. Vertical scrolling is disabled
+			 * if an empty string.
+			 * Note that this parameter will be set by the initialisation routine. To
+			 * set a default use {@link DataTable.defaults}.
+			 *  @type string
+			 */
+			"sY": null
+		},
+	
+		/**
+		 * Language information for the table.
+		 *  @namespace
+		 *  @extends DataTable.defaults.oLanguage
+		 */
+		"oLanguage": {
+			/**
+			 * Information callback function. See
+			 * {@link DataTable.defaults.fnInfoCallback}
+			 *  @type function
+			 *  @default null
+			 */
+			"fnInfoCallback": null
+		},
+	
+		/**
+		 * Browser support parameters
+		 *  @namespace
+		 */
+		"oBrowser": {
+			/**
+			 * Indicate if the browser incorrectly calculates width:100% inside a
+			 * scrolling element (IE6/7)
+			 *  @type boolean
+			 *  @default false
+			 */
+			"bScrollOversize": false,
+	
+			/**
+			 * Determine if the vertical scrollbar is on the right or left of the
+			 * scrolling container - needed for rtl language layout, although not
+			 * all browsers move the scrollbar (Safari).
+			 *  @type boolean
+			 *  @default false
+			 */
+			"bScrollbarLeft": false,
+	
+			/**
+			 * Flag for if `getBoundingClientRect` is fully supported or not
+			 *  @type boolean
+			 *  @default false
+			 */
+			"bBounding": false,
+	
+			/**
+			 * Browser scrollbar width
+			 *  @type integer
+			 *  @default 0
+			 */
+			"barWidth": 0
+		},
+	
+	
+		"ajax": null,
+	
+	
+		/**
+		 * Array referencing the nodes which are used for the features. The
+		 * parameters of this object match what is allowed by sDom - i.e.
+		 *   <ul>
+		 *     <li>'l' - Length changing</li>
+		 *     <li>'f' - Filtering input</li>
+		 *     <li>'t' - The table!</li>
+		 *     <li>'i' - Information</li>
+		 *     <li>'p' - Pagination</li>
+		 *     <li>'r' - pRocessing</li>
+		 *   </ul>
+		 *  @type array
+		 *  @default []
+		 */
+		"aanFeatures": [],
+	
+		/**
+		 * Store data information - see {@link DataTable.models.oRow} for detailed
+		 * information.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoData": [],
+	
+		/**
+		 * Array of indexes which are in the current display (after filtering etc)
+		 *  @type array
+		 *  @default []
+		 */
+		"aiDisplay": [],
+	
+		/**
+		 * Array of indexes for display - no filtering
+		 *  @type array
+		 *  @default []
+		 */
+		"aiDisplayMaster": [],
+	
+		/**
+		 * Map of row ids to data indexes
+		 *  @type object
+		 *  @default {}
+		 */
+		"aIds": {},
+	
+		/**
+		 * Store information about each column that is in use
+		 *  @type array
+		 *  @default []
+		 */
+		"aoColumns": [],
+	
+		/**
+		 * Store information about the table's header
+		 *  @type array
+		 *  @default []
+		 */
+		"aoHeader": [],
+	
+		/**
+		 * Store information about the table's footer
+		 *  @type array
+		 *  @default []
+		 */
+		"aoFooter": [],
+	
+		/**
+		 * Store the applied global search information in case we want to force a
+		 * research or compare the old search to a new one.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @namespace
+		 *  @extends DataTable.models.oSearch
+		 */
+		"oPreviousSearch": {},
+	
+		/**
+		 * Store the applied search for each column - see
+		 * {@link DataTable.models.oSearch} for the format that is used for the
+		 * filtering information for each column.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoPreSearchCols": [],
+	
+		/**
+		 * Sorting that is applied to the table. Note that the inner arrays are
+		 * used in the following manner:
+		 * <ul>
+		 *   <li>Index 0 - column number</li>
+		 *   <li>Index 1 - current sorting direction</li>
+		 * </ul>
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type array
+		 *  @todo These inner arrays should really be objects
+		 */
+		"aaSorting": null,
+	
+		/**
+		 * Sorting that is always applied to the table (i.e. prefixed in front of
+		 * aaSorting).
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type array
+		 *  @default []
+		 */
+		"aaSortingFixed": [],
+	
+		/**
+		 * Classes to use for the striping of a table.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type array
+		 *  @default []
+		 */
+		"asStripeClasses": null,
+	
+		/**
+		 * If restoring a table - we should restore its striping classes as well
+		 *  @type array
+		 *  @default []
+		 */
+		"asDestroyStripes": [],
+	
+		/**
+		 * If restoring a table - we should restore its width
+		 *  @type int
+		 *  @default 0
+		 */
+		"sDestroyWidth": 0,
+	
+		/**
+		 * Callback functions array for every time a row is inserted (i.e. on a draw).
+		 *  @type array
+		 *  @default []
+		 */
+		"aoRowCallback": [],
+	
+		/**
+		 * Callback functions for the header on each draw.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoHeaderCallback": [],
+	
+		/**
+		 * Callback function for the footer on each draw.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoFooterCallback": [],
+	
+		/**
+		 * Array of callback functions for draw callback functions
+		 *  @type array
+		 *  @default []
+		 */
+		"aoDrawCallback": [],
+	
+		/**
+		 * Array of callback functions for row created function
+		 *  @type array
+		 *  @default []
+		 */
+		"aoRowCreatedCallback": [],
+	
+		/**
+		 * Callback functions for just before the table is redrawn. A return of
+		 * false will be used to cancel the draw.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoPreDrawCallback": [],
+	
+		/**
+		 * Callback functions for when the table has been initialised.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoInitComplete": [],
+	
+	
+		/**
+		 * Callbacks for modifying the settings to be stored for state saving, prior to
+		 * saving state.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoStateSaveParams": [],
+	
+		/**
+		 * Callbacks for modifying the settings that have been stored for state saving
+		 * prior to using the stored values to restore the state.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoStateLoadParams": [],
+	
+		/**
+		 * Callbacks for operating on the settings object once the saved state has been
+		 * loaded
+		 *  @type array
+		 *  @default []
+		 */
+		"aoStateLoaded": [],
+	
+		/**
+		 * Cache the table ID for quick access
+		 *  @type string
+		 *  @default <i>Empty string</i>
+		 */
+		"sTableId": "",
+	
+		/**
+		 * The TABLE node for the main table
+		 *  @type node
+		 *  @default null
+		 */
+		"nTable": null,
+	
+		/**
+		 * Permanent ref to the thead element
+		 *  @type node
+		 *  @default null
+		 */
+		"nTHead": null,
+	
+		/**
+		 * Permanent ref to the tfoot element - if it exists
+		 *  @type node
+		 *  @default null
+		 */
+		"nTFoot": null,
+	
+		/**
+		 * Permanent ref to the tbody element
+		 *  @type node
+		 *  @default null
+		 */
+		"nTBody": null,
+	
+		/**
+		 * Cache the wrapper node (contains all DataTables controlled elements)
+		 *  @type node
+		 *  @default null
+		 */
+		"nTableWrapper": null,
+	
+		/**
+		 * Indicate if when using server-side processing the loading of data
+		 * should be deferred until the second draw.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type boolean
+		 *  @default false
+		 */
+		"bDeferLoading": false,
+	
+		/**
+		 * Indicate if all required information has been read in
+		 *  @type boolean
+		 *  @default false
+		 */
+		"bInitialised": false,
+	
+		/**
+		 * Information about open rows. Each object in the array has the parameters
+		 * 'nTr' and 'nParent'
+		 *  @type array
+		 *  @default []
+		 */
+		"aoOpenRows": [],
+	
+		/**
+		 * Dictate the positioning of DataTables' control elements - see
+		 * {@link DataTable.model.oInit.sDom}.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type string
+		 *  @default null
+		 */
+		"sDom": null,
+	
+		/**
+		 * Search delay (in mS)
+		 *  @type integer
+		 *  @default null
+		 */
+		"searchDelay": null,
+	
+		/**
+		 * Which type of pagination should be used.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type string
+		 *  @default two_button
+		 */
+		"sPaginationType": "two_button",
+	
+		/**
+		 * The state duration (for `stateSave`) in seconds.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type int
+		 *  @default 0
+		 */
+		"iStateDuration": 0,
+	
+		/**
+		 * Array of callback functions for state saving. Each array element is an
+		 * object with the following parameters:
+		 *   <ul>
+		 *     <li>function:fn - function to call. Takes two parameters, oSettings
+		 *       and the JSON string to save that has been thus far created. Returns
+		 *       a JSON string to be inserted into a json object
+		 *       (i.e. '"param": [ 0, 1, 2]')</li>
+		 *     <li>string:sName - name of callback</li>
+		 *   </ul>
+		 *  @type array
+		 *  @default []
+		 */
+		"aoStateSave": [],
+	
+		/**
+		 * Array of callback functions for state loading. Each array element is an
+		 * object with the following parameters:
+		 *   <ul>
+		 *     <li>function:fn - function to call. Takes two parameters, oSettings
+		 *       and the object stored. May return false to cancel state loading</li>
+		 *     <li>string:sName - name of callback</li>
+		 *   </ul>
+		 *  @type array
+		 *  @default []
+		 */
+		"aoStateLoad": [],
+	
+		/**
+		 * State that was saved. Useful for back reference
+		 *  @type object
+		 *  @default null
+		 */
+		"oSavedState": null,
+	
+		/**
+		 * State that was loaded. Useful for back reference
+		 *  @type object
+		 *  @default null
+		 */
+		"oLoadedState": null,
+	
+		/**
+		 * Source url for AJAX data for the table.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type string
+		 *  @default null
+		 */
+		"sAjaxSource": null,
+	
+		/**
+		 * Property from a given object from which to read the table data from. This
+		 * can be an empty string (when not server-side processing), in which case
+		 * it is  assumed an an array is given directly.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type string
+		 */
+		"sAjaxDataProp": null,
+	
+		/**
+		 * Note if draw should be blocked while getting data
+		 *  @type boolean
+		 *  @default true
+		 */
+		"bAjaxDataGet": true,
+	
+		/**
+		 * The last jQuery XHR object that was used for server-side data gathering.
+		 * This can be used for working with the XHR information in one of the
+		 * callbacks
+		 *  @type object
+		 *  @default null
+		 */
+		"jqXHR": null,
+	
+		/**
+		 * JSON returned from the server in the last Ajax request
+		 *  @type object
+		 *  @default undefined
+		 */
+		"json": undefined,
+	
+		/**
+		 * Data submitted as part of the last Ajax request
+		 *  @type object
+		 *  @default undefined
+		 */
+		"oAjaxData": undefined,
+	
+		/**
+		 * Function to get the server-side data.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type function
+		 */
+		"fnServerData": null,
+	
+		/**
+		 * Functions which are called prior to sending an Ajax request so extra
+		 * parameters can easily be sent to the server
+		 *  @type array
+		 *  @default []
+		 */
+		"aoServerParams": [],
+	
+		/**
+		 * Send the XHR HTTP method - GET or POST (could be PUT or DELETE if
+		 * required).
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type string
+		 */
+		"sServerMethod": null,
+	
+		/**
+		 * Format numbers for display.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type function
+		 */
+		"fnFormatNumber": null,
+	
+		/**
+		 * List of options that can be used for the user selectable length menu.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type array
+		 *  @default []
+		 */
+		"aLengthMenu": null,
+	
+		/**
+		 * Counter for the draws that the table does. Also used as a tracker for
+		 * server-side processing
+		 *  @type int
+		 *  @default 0
+		 */
+		"iDraw": 0,
+	
+		/**
+		 * Indicate if a redraw is being done - useful for Ajax
+		 *  @type boolean
+		 *  @default false
+		 */
+		"bDrawing": false,
+	
+		/**
+		 * Draw index (iDraw) of the last error when parsing the returned data
+		 *  @type int
+		 *  @default -1
+		 */
+		"iDrawError": -1,
+	
+		/**
+		 * Paging display length
+		 *  @type int
+		 *  @default 10
+		 */
+		"_iDisplayLength": 10,
+	
+		/**
+		 * Paging start point - aiDisplay index
+		 *  @type int
+		 *  @default 0
+		 */
+		"_iDisplayStart": 0,
+	
+		/**
+		 * Server-side processing - number of records in the result set
+		 * (i.e. before filtering), Use fnRecordsTotal rather than
+		 * this property to get the value of the number of records, regardless of
+		 * the server-side processing setting.
+		 *  @type int
+		 *  @default 0
+		 *  @private
+		 */
+		"_iRecordsTotal": 0,
+	
+		/**
+		 * Server-side processing - number of records in the current display set
+		 * (i.e. after filtering). Use fnRecordsDisplay rather than
+		 * this property to get the value of the number of records, regardless of
+		 * the server-side processing setting.
+		 *  @type boolean
+		 *  @default 0
+		 *  @private
+		 */
+		"_iRecordsDisplay": 0,
+	
+		/**
+		 * The classes to use for the table
+		 *  @type object
+		 *  @default {}
+		 */
+		"oClasses": {},
+	
+		/**
+		 * Flag attached to the settings object so you can check in the draw
+		 * callback if filtering has been done in the draw. Deprecated in favour of
+		 * events.
+		 *  @type boolean
+		 *  @default false
+		 *  @deprecated
+		 */
+		"bFiltered": false,
+	
+		/**
+		 * Flag attached to the settings object so you can check in the draw
+		 * callback if sorting has been done in the draw. Deprecated in favour of
+		 * events.
+		 *  @type boolean
+		 *  @default false
+		 *  @deprecated
+		 */
+		"bSorted": false,
+	
+		/**
+		 * Indicate that if multiple rows are in the header and there is more than
+		 * one unique cell per column, if the top one (true) or bottom one (false)
+		 * should be used for sorting / title by DataTables.
+		 * Note that this parameter will be set by the initialisation routine. To
+		 * set a default use {@link DataTable.defaults}.
+		 *  @type boolean
+		 */
+		"bSortCellsTop": null,
+	
+		/**
+		 * Initialisation object that is used for the table
+		 *  @type object
+		 *  @default null
+		 */
+		"oInit": null,
+	
+		/**
+		 * Destroy callback functions - for plug-ins to attach themselves to the
+		 * destroy so they can clean up markup and events.
+		 *  @type array
+		 *  @default []
+		 */
+		"aoDestroyCallback": [],
+	
+	
+		/**
+		 * Get the number of records in the current record set, before filtering
+		 *  @type function
+		 */
+		"fnRecordsTotal": function ()
+		{
+			return _fnDataSource( this ) == 'ssp' ?
+				this._iRecordsTotal * 1 :
+				this.aiDisplayMaster.length;
+		},
+	
+		/**
+		 * Get the number of records in the current record set, after filtering
+		 *  @type function
+		 */
+		"fnRecordsDisplay": function ()
+		{
+			return _fnDataSource( this ) == 'ssp' ?
+				this._iRecordsDisplay * 1 :
+				this.aiDisplay.length;
+		},
+	
+		/**
+		 * Get the display end point - aiDisplay index
+		 *  @type function
+		 */
+		"fnDisplayEnd": function ()
+		{
+			var
+				len      = this._iDisplayLength,
+				start    = this._iDisplayStart,
+				calc     = start + len,
+				records  = this.aiDisplay.length,
+				features = this.oFeatures,
+				paginate = features.bPaginate;
+	
+			if ( features.bServerSide ) {
+				return paginate === false || len === -1 ?
+					start + records :
+					Math.min( start+len, this._iRecordsDisplay );
+			}
+			else {
+				return ! paginate || calc>records || len===-1 ?
+					records :
+					calc;
+			}
+		},
+	
+		/**
+		 * The DataTables object for this table
+		 *  @type object
+		 *  @default null
+		 */
+		"oInstance": null,
+	
+		/**
+		 * Unique identifier for each instance of the DataTables object. If there
+		 * is an ID on the table node, then it takes that value, otherwise an
+		 * incrementing internal counter is used.
+		 *  @type string
+		 *  @default null
+		 */
+		"sInstance": null,
+	
+		/**
+		 * tabindex attribute value that is added to DataTables control elements, allowing
+		 * keyboard navigation of the table and its controls.
+		 */
+		"iTabIndex": 0,
+	
+		/**
+		 * DIV container for the footer scrolling table if scrolling
+		 */
+		"nScrollHead": null,
+	
+		/**
+		 * DIV container for the footer scrolling table if scrolling
+		 */
+		"nScrollFoot": null,
+	
+		/**
+		 * Last applied sort
+		 *  @type array
+		 *  @default []
+		 */
+		"aLastSort": [],
+	
+		/**
+		 * Stored plug-in instances
+		 *  @type object
+		 *  @default {}
+		 */
+		"oPlugins": {},
+	
+		/**
+		 * Function used to get a row's id from the row's data
+		 *  @type function
+		 *  @default null
+		 */
+		"rowIdFn": null,
+	
+		/**
+		 * Data location where to store a row's id
+		 *  @type string
+		 *  @default null
+		 */
+		"rowId": null
+	};
+
+	/**
+	 * Extension object for DataTables that is used to provide all extension
+	 * options.
+	 *
+	 * Note that the `DataTable.ext` object is available through
+	 * `jQuery.fn.dataTable.ext` where it may be accessed and manipulated. It is
+	 * also aliased to `jQuery.fn.dataTableExt` for historic reasons.
+	 *  @namespace
+	 *  @extends DataTable.models.ext
+	 */
+	
+	
+	/**
+	 * DataTables extensions
+	 * 
+	 * This namespace acts as a collection area for plug-ins that can be used to
+	 * extend DataTables capabilities. Indeed many of the build in methods
+	 * use this method to provide their own capabilities (sorting methods for
+	 * example).
+	 *
+	 * Note that this namespace is aliased to `jQuery.fn.dataTableExt` for legacy
+	 * reasons
+	 *
+	 *  @namespace
+	 */
+	DataTable.ext = _ext = {
+		/**
+		 * Buttons. For use with the Buttons extension for DataTables. This is
+		 * defined here so other extensions can define buttons regardless of load
+		 * order. It is _not_ used by DataTables core.
+		 *
+		 *  @type object
+		 *  @default {}
+		 */
+		buttons: {},
+	
+	
+		/**
+		 * Element class names
+		 *
+		 *  @type object
+		 *  @default {}
+		 */
+		classes: {},
+	
+	
+		/**
+		 * DataTables build type (expanded by the download builder)
+		 *
+		 *  @type string
+		 */
+		build:"dt/dt-1.10.16",
+	
+	
+		/**
+		 * Error reporting.
+		 * 
+		 * How should DataTables report an error. Can take the value 'alert',
+		 * 'throw', 'none' or a function.
+		 *
+		 *  @type string|function
+		 *  @default alert
+		 */
+		errMode: "alert",
+	
+	
+		/**
+		 * Feature plug-ins.
+		 * 
+		 * This is an array of objects which describe the feature plug-ins that are
+		 * available to DataTables. These feature plug-ins are then available for
+		 * use through the `dom` initialisation option.
+		 * 
+		 * Each feature plug-in is described by an object which must have the
+		 * following properties:
+		 * 
+		 * * `fnInit` - function that is used to initialise the plug-in,
+		 * * `cFeature` - a character so the feature can be enabled by the `dom`
+		 *   instillation option. This is case sensitive.
+		 *
+		 * The `fnInit` function has the following input parameters:
+		 *
+		 * 1. `{object}` DataTables settings object: see
+		 *    {@link DataTable.models.oSettings}
+		 *
+		 * And the following return is expected:
+		 * 
+		 * * {node|null} The element which contains your feature. Note that the
+		 *   return may also be void if your plug-in does not require to inject any
+		 *   DOM elements into DataTables control (`dom`) - for example this might
+		 *   be useful when developing a plug-in which allows table control via
+		 *   keyboard entry
+		 *
+		 *  @type array
+		 *
+		 *  @example
+		 *    $.fn.dataTable.ext.features.push( {
+		 *      "fnInit": function( oSettings ) {
+		 *        return new TableTools( { "oDTSettings": oSettings } );
+		 *      },
+		 *      "cFeature": "T"
+		 *    } );
+		 */
+		feature: [],
+	
+	
+		/**
+		 * Row searching.
+		 * 
+		 * This method of searching is complimentary to the default type based
+		 * searching, and a lot more comprehensive as it allows you complete control
+		 * over the searching logic. Each element in this array is a function
+		 * (parameters described below) that is called for every row in the table,
+		 * and your logic decides if it should be included in the searching data set
+		 * or not.
+		 *
+		 * Searching functions have the following input parameters:
+		 *
+		 * 1. `{object}` DataTables settings object: see
+		 *    {@link DataTable.models.oSettings}
+		 * 2. `{array|object}` Data for the row to be processed (same as the
+		 *    original format that was passed in as the data source, or an array
+		 *    from a DOM data source
+		 * 3. `{int}` Row index ({@link DataTable.models.oSettings.aoData}), which
+		 *    can be useful to retrieve the `TR` element if you need DOM interaction.
+		 *
+		 * And the following return is expected:
+		 *
+		 * * {boolean} Include the row in the searched result set (true) or not
+		 *   (false)
+		 *
+		 * Note that as with the main search ability in DataTables, technically this
+		 * is "filtering", since it is subtractive. However, for consistency in
+		 * naming we call it searching here.
+		 *
+		 *  @type array
+		 *  @default []
+		 *
+		 *  @example
+		 *    // The following example shows custom search being applied to the
+		 *    // fourth column (i.e. the data[3] index) based on two input values
+		 *    // from the end-user, matching the data in a certain range.
+		 *    $.fn.dataTable.ext.search.push(
+		 *      function( settings, data, dataIndex ) {
+		 *        var min = document.getElementById('min').value * 1;
+		 *        var max = document.getElementById('max').value * 1;
+		 *        var version = data[3] == "-" ? 0 : data[3]*1;
+		 *
+		 *        if ( min == "" && max == "" ) {
+		 *          return true;
+		 *        }
+		 *        else if ( min == "" && version < max ) {
+		 *          return true;
+		 *        }
+		 *        else if ( min < version && "" == max ) {
+		 *          return true;
+		 *        }
+		 *        else if ( min < version && version < max ) {
+		 *          return true;
+		 *        }
+		 *        return false;
+		 *      }
+		 *    );
+		 */
+		search: [],
+	
+	
+		/**
+		 * Selector extensions
+		 *
+		 * The `selector` option can be used to extend the options available for the
+		 * selector modifier options (`selector-modifier` object data type) that
+		 * each of the three built in selector types offer (row, column and cell +
+		 * their plural counterparts). For example the Select extension uses this
+		 * mechanism to provide an option to select only rows, columns and cells
+		 * that have been marked as selected by the end user (`{selected: true}`),
+		 * which can be used in conjunction with the existing built in selector
+		 * options.
+		 *
+		 * Each property is an array to which functions can be pushed. The functions
+		 * take three attributes:
+		 *
+		 * * Settings object for the host table
+		 * * Options object (`selector-modifier` object type)
+		 * * Array of selected item indexes
+		 *
+		 * The return is an array of the resulting item indexes after the custom
+		 * selector has been applied.
+		 *
+		 *  @type object
+		 */
+		selector: {
+			cell: [],
+			column: [],
+			row: []
+		},
+	
+	
+		/**
+		 * Internal functions, exposed for used in plug-ins.
+		 * 
+		 * Please note that you should not need to use the internal methods for
+		 * anything other than a plug-in (and even then, try to avoid if possible).
+		 * The internal function may change between releases.
+		 *
+		 *  @type object
+		 *  @default {}
+		 */
+		internal: {},
+	
+	
+		/**
+		 * Legacy configuration options. Enable and disable legacy options that
+		 * are available in DataTables.
+		 *
+		 *  @type object
+		 */
+		legacy: {
+			/**
+			 * Enable / disable DataTables 1.9 compatible server-side processing
+			 * requests
+			 *
+			 *  @type boolean
+			 *  @default null
+			 */
+			ajax: null
+		},
+	
+	
+		/**
+		 * Pagination plug-in methods.
+		 * 
+		 * Each entry in this object is a function and defines which buttons should
+		 * be shown by the pagination rendering method that is used for the table:
+		 * {@link DataTable.ext.renderer.pageButton}. The renderer addresses how the
+		 * buttons are displayed in the document, while the functions here tell it
+		 * what buttons to display. This is done by returning an array of button
+		 * descriptions (what each button will do).
+		 *
+		 * Pagination types (the four built in options and any additional plug-in
+		 * options defined here) can be used through the `paginationType`
+		 * initialisation parameter.
+		 *
+		 * The functions defined take two parameters:
+		 *
+		 * 1. `{int} page` The current page index
+		 * 2. `{int} pages` The number of pages in the table
+		 *
+		 * Each function is expected to return an array where each element of the
+		 * array can be one of:
+		 *
+		 * * `first` - Jump to first page when activated
+		 * * `last` - Jump to last page when activated
+		 * * `previous` - Show previous page when activated
+		 * * `next` - Show next page when activated
+		 * * `{int}` - Show page of the index given
+		 * * `{array}` - A nested array containing the above elements to add a
+		 *   containing 'DIV' element (might be useful for styling).
+		 *
+		 * Note that DataTables v1.9- used this object slightly differently whereby
+		 * an object with two functions would be defined for each plug-in. That
+		 * ability is still supported by DataTables 1.10+ to provide backwards
+		 * compatibility, but this option of use is now decremented and no longer
+		 * documented in DataTables 1.10+.
+		 *
+		 *  @type object
+		 *  @default {}
+		 *
+		 *  @example
+		 *    // Show previous, next and current page buttons only
+		 *    $.fn.dataTableExt.oPagination.current = function ( page, pages ) {
+		 *      return [ 'previous', page, 'next' ];
+		 *    };
+		 */
+		pager: {},
+	
+	
+		renderer: {
+			pageButton: {},
+			header: {}
+		},
+	
+	
+		/**
+		 * Ordering plug-ins - custom data source
+		 * 
+		 * The extension options for ordering of data available here is complimentary
+		 * to the default type based ordering that DataTables typically uses. It
+		 * allows much greater control over the the data that is being used to
+		 * order a column, but is necessarily therefore more complex.
+		 * 
+		 * This type of ordering is useful if you want to do ordering based on data
+		 * live from the DOM (for example the contents of an 'input' element) rather
+		 * than just the static string that DataTables knows of.
+		 * 
+		 * The way these plug-ins work is that you create an array of the values you
+		 * wish to be ordering for the column in question and then return that
+		 * array. The data in the array much be in the index order of the rows in
+		 * the table (not the currently ordering order!). Which order data gathering
+		 * function is run here depends on the `dt-init columns.orderDataType`
+		 * parameter that is used for the column (if any).
+		 *
+		 * The functions defined take two parameters:
+		 *
+		 * 1. `{object}` DataTables settings object: see
+		 *    {@link DataTable.models.oSettings}
+		 * 2. `{int}` Target column index
+		 *
+		 * Each function is expected to return an array:
+		 *
+		 * * `{array}` Data for the column to be ordering upon
+		 *
+		 *  @type array
+		 *
+		 *  @example
+		 *    // Ordering using `input` node values
+		 *    $.fn.dataTable.ext.order['dom-text'] = function  ( settings, col )
+		 *    {
+		 *      return this.api().column( col, {order:'index'} ).nodes().map( function ( td, i ) {
+		 *        return $('input', td).val();
+		 *      } );
+		 *    }
+		 */
+		order: {},
+	
+	
+		/**
+		 * Type based plug-ins.
+		 *
+		 * Each column in DataTables has a type assigned to it, either by automatic
+		 * detection or by direct assignment using the `type` option for the column.
+		 * The type of a column will effect how it is ordering and search (plug-ins
+		 * can also make use of the column type if required).
+		 *
+		 * @namespace
+		 */
+		type: {
+			/**
+			 * Type detection functions.
+			 *
+			 * The functions defined in this object are used to automatically detect
+			 * a column's type, making initialisation of DataTables super easy, even
+			 * when complex data is in the table.
+			 *
+			 * The functions defined take two parameters:
+			 *
+		     *  1. `{*}` Data from the column cell to be analysed
+		     *  2. `{settings}` DataTables settings object. This can be used to
+		     *     perform context specific type detection - for example detection
+		     *     based on language settings such as using a comma for a decimal
+		     *     place. Generally speaking the options from the settings will not
+		     *     be required
+			 *
+			 * Each function is expected to return:
+			 *
+			 * * `{string|null}` Data type detected, or null if unknown (and thus
+			 *   pass it on to the other type detection functions.
+			 *
+			 *  @type array
+			 *
+			 *  @example
+			 *    // Currency type detection plug-in:
+			 *    $.fn.dataTable.ext.type.detect.push(
+			 *      function ( data, settings ) {
+			 *        // Check the numeric part
+			 *        if ( ! $.isNumeric( data.substring(1) ) ) {
+			 *          return null;
+			 *        }
+			 *
+			 *        // Check prefixed by currency
+			 *        if ( data.charAt(0) == '$' || data.charAt(0) == '&pound;' ) {
+			 *          return 'currency';
+			 *        }
+			 *        return null;
+			 *      }
+			 *    );
+			 */
+			detect: [],
+	
+	
+			/**
+			 * Type based search formatting.
+			 *
+			 * The type based searching functions can be used to pre-format the
+			 * data to be search on. For example, it can be used to strip HTML
+			 * tags or to de-format telephone numbers for numeric only searching.
+			 *
+			 * Note that is a search is not defined for a column of a given type,
+			 * no search formatting will be performed.
+			 * 
+			 * Pre-processing of searching data plug-ins - When you assign the sType
+			 * for a column (or have it automatically detected for you by DataTables
+			 * or a type detection plug-in), you will typically be using this for
+			 * custom sorting, but it can also be used to provide custom searching
+			 * by allowing you to pre-processing the data and returning the data in
+			 * the format that should be searched upon. This is done by adding
+			 * functions this object with a parameter name which matches the sType
+			 * for that target column. This is the corollary of <i>afnSortData</i>
+			 * for searching data.
+			 *
+			 * The functions defined take a single parameter:
+			 *
+		     *  1. `{*}` Data from the column cell to be prepared for searching
+			 *
+			 * Each function is expected to return:
+			 *
+			 * * `{string|null}` Formatted string that will be used for the searching.
+			 *
+			 *  @type object
+			 *  @default {}
+			 *
+			 *  @example
+			 *    $.fn.dataTable.ext.type.search['title-numeric'] = function ( d ) {
+			 *      return d.replace(/\n/g," ").replace( /<.*?>/g, "" );
+			 *    }
+			 */
+			search: {},
+	
+	
+			/**
+			 * Type based ordering.
+			 *
+			 * The column type tells DataTables what ordering to apply to the table
+			 * when a column is sorted upon. The order for each type that is defined,
+			 * is defined by the functions available in this object.
+			 *
+			 * Each ordering option can be described by three properties added to
+			 * this object:
+			 *
+			 * * `{type}-pre` - Pre-formatting function
+			 * * `{type}-asc` - Ascending order function
+			 * * `{type}-desc` - Descending order function
+			 *
+			 * All three can be used together, only `{type}-pre` or only
+			 * `{type}-asc` and `{type}-desc` together. It is generally recommended
+			 * that only `{type}-pre` is used, as this provides the optimal
+			 * implementation in terms of speed, although the others are provided
+			 * for compatibility with existing Javascript sort functions.
+			 *
+			 * `{type}-pre`: Functions defined take a single parameter:
+			 *
+		     *  1. `{*}` Data from the column cell to be prepared for ordering
+			 *
+			 * And return:
+			 *
+			 * * `{*}` Data to be sorted upon
+			 *
+			 * `{type}-asc` and `{type}-desc`: Functions are typical Javascript sort
+			 * functions, taking two parameters:
+			 *
+		     *  1. `{*}` Data to compare to the second parameter
+		     *  2. `{*}` Data to compare to the first parameter
+			 *
+			 * And returning:
+			 *
+			 * * `{*}` Ordering match: <0 if first parameter should be sorted lower
+			 *   than the second parameter, ===0 if the two parameters are equal and
+			 *   >0 if the first parameter should be sorted height than the second
+			 *   parameter.
+			 * 
+			 *  @type object
+			 *  @default {}
+			 *
+			 *  @example
+			 *    // Numeric ordering of formatted numbers with a pre-formatter
+			 *    $.extend( $.fn.dataTable.ext.type.order, {
+			 *      "string-pre": function(x) {
+			 *        a = (a === "-" || a === "") ? 0 : a.replace( /[^\d\-\.]/g, "" );
+			 *        return parseFloat( a );
+			 *      }
+			 *    } );
+			 *
+			 *  @example
+			 *    // Case-sensitive string ordering, with no pre-formatting method
+			 *    $.extend( $.fn.dataTable.ext.order, {
+			 *      "string-case-asc": function(x,y) {
+			 *        return ((x < y) ? -1 : ((x > y) ? 1 : 0));
+			 *      },
+			 *      "string-case-desc": function(x,y) {
+			 *        return ((x < y) ? 1 : ((x > y) ? -1 : 0));
+			 *      }
+			 *    } );
+			 */
+			order: {}
+		},
+	
+		/**
+		 * Unique DataTables instance counter
+		 *
+		 * @type int
+		 * @private
+		 */
+		_unique: 0,
+	
+	
+		//
+		// Depreciated
+		// The following properties are retained for backwards compatiblity only.
+		// The should not be used in new projects and will be removed in a future
+		// version
+		//
+	
+		/**
+		 * Version check function.
+		 *  @type function
+		 *  @depreciated Since 1.10
+		 */
+		fnVersionCheck: DataTable.fnVersionCheck,
+	
+	
+		/**
+		 * Index for what 'this' index API functions should use
+		 *  @type int
+		 *  @deprecated Since v1.10
+		 */
+		iApiIndex: 0,
+	
+	
+		/**
+		 * jQuery UI class container
+		 *  @type object
+		 *  @deprecated Since v1.10
+		 */
+		oJUIClasses: {},
+	
+	
+		/**
+		 * Software version
+		 *  @type string
+		 *  @deprecated Since v1.10
+		 */
+		sVersion: DataTable.version
+	};
+	
+	
+	//
+	// Backwards compatibility. Alias to pre 1.10 Hungarian notation counter parts
+	//
+	$.extend( _ext, {
+		afnFiltering: _ext.search,
+		aTypes:       _ext.type.detect,
+		ofnSearch:    _ext.type.search,
+		oSort:        _ext.type.order,
+		afnSortData:  _ext.order,
+		aoFeatures:   _ext.feature,
+		oApi:         _ext.internal,
+		oStdClasses:  _ext.classes,
+		oPagination:  _ext.pager
+	} );
+	
+	
+	$.extend( DataTable.ext.classes, {
+		"sTable": "dataTable",
+		"sNoFooter": "no-footer",
+	
+		/* Paging buttons */
+		"sPageButton": "paginate_button",
+		"sPageButtonActive": "current",
+		"sPageButtonDisabled": "disabled",
+	
+		/* Striping classes */
+		"sStripeOdd": "odd",
+		"sStripeEven": "even",
+	
+		/* Empty row */
+		"sRowEmpty": "dataTables_empty",
+	
+		/* Features */
+		"sWrapper": "dataTables_wrapper",
+		"sFilter": "dataTables_filter",
+		"sInfo": "dataTables_info",
+		"sPaging": "dataTables_paginate paging_", /* Note that the type is postfixed */
+		"sLength": "dataTables_length",
+		"sProcessing": "dataTables_processing",
+	
+		/* Sorting */
+		"sSortAsc": "sorting_asc",
+		"sSortDesc": "sorting_desc",
+		"sSortable": "sorting", /* Sortable in both directions */
+		"sSortableAsc": "sorting_asc_disabled",
+		"sSortableDesc": "sorting_desc_disabled",
+		"sSortableNone": "sorting_disabled",
+		"sSortColumn": "sorting_", /* Note that an int is postfixed for the sorting order */
+	
+		/* Filtering */
+		"sFilterInput": "",
+	
+		/* Page length */
+		"sLengthSelect": "",
+	
+		/* Scrolling */
+		"sScrollWrapper": "dataTables_scroll",
+		"sScrollHead": "dataTables_scrollHead",
+		"sScrollHeadInner": "dataTables_scrollHeadInner",
+		"sScrollBody": "dataTables_scrollBody",
+		"sScrollFoot": "dataTables_scrollFoot",
+		"sScrollFootInner": "dataTables_scrollFootInner",
+	
+		/* Misc */
+		"sHeaderTH": "",
+		"sFooterTH": "",
+	
+		// Deprecated
+		"sSortJUIAsc": "",
+		"sSortJUIDesc": "",
+		"sSortJUI": "",
+		"sSortJUIAscAllowed": "",
+		"sSortJUIDescAllowed": "",
+		"sSortJUIWrapper": "",
+		"sSortIcon": "",
+		"sJUIHeader": "",
+		"sJUIFooter": ""
+	} );
+	
+	
+	var extPagination = DataTable.ext.pager;
+	
+	function _numbers ( page, pages ) {
+		var
+			numbers = [],
+			buttons = extPagination.numbers_length,
+			half = Math.floor( buttons / 2 ),
+			i = 1;
+	
+		if ( pages <= buttons ) {
+			numbers = _range( 0, pages );
+		}
+		else if ( page <= half ) {
+			numbers = _range( 0, buttons-2 );
+			numbers.push( 'ellipsis' );
+			numbers.push( pages-1 );
+		}
+		else if ( page >= pages - 1 - half ) {
+			numbers = _range( pages-(buttons-2), pages );
+			numbers.splice( 0, 0, 'ellipsis' ); // no unshift in ie6
+			numbers.splice( 0, 0, 0 );
+		}
+		else {
+			numbers = _range( page-half+2, page+half-1 );
+			numbers.push( 'ellipsis' );
+			numbers.push( pages-1 );
+			numbers.splice( 0, 0, 'ellipsis' );
+			numbers.splice( 0, 0, 0 );
+		}
+	
+		numbers.DT_el = 'span';
+		return numbers;
+	}
+	
+	
+	$.extend( extPagination, {
+		simple: function ( page, pages ) {
+			return [ 'previous', 'next' ];
+		},
+	
+		full: function ( page, pages ) {
+			return [  'first', 'previous', 'next', 'last' ];
+		},
+	
+		numbers: function ( page, pages ) {
+			return [ _numbers(page, pages) ];
+		},
+	
+		simple_numbers: function ( page, pages ) {
+			return [ 'previous', _numbers(page, pages), 'next' ];
+		},
+	
+		full_numbers: function ( page, pages ) {
+			return [ 'first', 'previous', _numbers(page, pages), 'next', 'last' ];
+		},
+		
+		first_last_numbers: function (page, pages) {
+	 		return ['first', _numbers(page, pages), 'last'];
+	 	},
+	
+		// For testing and plug-ins to use
+		_numbers: _numbers,
+	
+		// Number of number buttons (including ellipsis) to show. _Must be odd!_
+		numbers_length: 7
+	} );
+	
+	
+	$.extend( true, DataTable.ext.renderer, {
+		pageButton: {
+			_: function ( settings, host, idx, buttons, page, pages ) {
+				var classes = settings.oClasses;
+				var lang = settings.oLanguage.oPaginate;
+				var aria = settings.oLanguage.oAria.paginate || {};
+				var btnDisplay, btnClass, counter=0;
+	
+				var attach = function( container, buttons ) {
+					var i, ien, node, button;
+					var clickHandler = function ( e ) {
+						_fnPageChange( settings, e.data.action, true );
+					};
+	
+					for ( i=0, ien=buttons.length ; i<ien ; i++ ) {
+						button = buttons[i];
+	
+						if ( $.isArray( button ) ) {
+							var inner = $( '<'+(button.DT_el || 'div')+'/>' )
+								.appendTo( container );
+							attach( inner, button );
+						}
+						else {
+							btnDisplay = null;
+							btnClass = '';
+	
+							switch ( button ) {
+								case 'ellipsis':
+									container.append('<span class="ellipsis">&#x2026;</span>');
+									break;
+	
+								case 'first':
+									btnDisplay = lang.sFirst;
+									btnClass = button + (page > 0 ?
+										'' : ' '+classes.sPageButtonDisabled);
+									break;
+	
+								case 'previous':
+									btnDisplay = lang.sPrevious;
+									btnClass = button + (page > 0 ?
+										'' : ' '+classes.sPageButtonDisabled);
+									break;
+	
+								case 'next':
+									btnDisplay = lang.sNext;
+									btnClass = button + (page < pages-1 ?
+										'' : ' '+classes.sPageButtonDisabled);
+									break;
+	
+								case 'last':
+									btnDisplay = lang.sLast;
+									btnClass = button + (page < pages-1 ?
+										'' : ' '+classes.sPageButtonDisabled);
+									break;
+	
+								default:
+									btnDisplay = button + 1;
+									btnClass = page === button ?
+										classes.sPageButtonActive : '';
+									break;
+							}
+	
+							if ( btnDisplay !== null ) {
+								node = $('<a>', {
+										'class': classes.sPageButton+' '+btnClass,
+										'aria-controls': settings.sTableId,
+										'aria-label': aria[ button ],
+										'data-dt-idx': counter,
+										'tabindex': settings.iTabIndex,
+										'id': idx === 0 && typeof button === 'string' ?
+											settings.sTableId +'_'+ button :
+											null
+									} )
+									.html( btnDisplay )
+									.appendTo( container );
+	
+								_fnBindAction(
+									node, {action: button}, clickHandler
+								);
+	
+								counter++;
+							}
+						}
+					}
+				};
+	
+				// IE9 throws an 'unknown error' if document.activeElement is used
+				// inside an iframe or frame. Try / catch the error. Not good for
+				// accessibility, but neither are frames.
+				var activeEl;
+	
+				try {
+					// Because this approach is destroying and recreating the paging
+					// elements, focus is lost on the select button which is bad for
+					// accessibility. So we want to restore focus once the draw has
+					// completed
+					activeEl = $(host).find(document.activeElement).data('dt-idx');
+				}
+				catch (e) {}
+	
+				attach( $(host).empty(), buttons );
+	
+				if ( activeEl !== undefined ) {
+					$(host).find( '[data-dt-idx='+activeEl+']' ).focus();
+				}
+			}
+		}
+	} );
+	
+	
+	
+	// Built in type detection. See model.ext.aTypes for information about
+	// what is required from this methods.
+	$.extend( DataTable.ext.type.detect, [
+		// Plain numbers - first since V8 detects some plain numbers as dates
+		// e.g. Date.parse('55') (but not all, e.g. Date.parse('22')...).
+		function ( d, settings )
+		{
+			var decimal = settings.oLanguage.sDecimal;
+			return _isNumber( d, decimal ) ? 'num'+decimal : null;
+		},
+	
+		// Dates (only those recognised by the browser's Date.parse)
+		function ( d, settings )
+		{
+			// V8 tries _very_ hard to make a string passed into `Date.parse()`
+			// valid, so we need to use a regex to restrict date formats. Use a
+			// plug-in for anything other than ISO8601 style strings
+			if ( d && !(d instanceof Date) && ! _re_date.test(d) ) {
+				return null;
+			}
+			var parsed = Date.parse(d);
+			return (parsed !== null && !isNaN(parsed)) || _empty(d) ? 'date' : null;
+		},
+	
+		// Formatted numbers
+		function ( d, settings )
+		{
+			var decimal = settings.oLanguage.sDecimal;
+			return _isNumber( d, decimal, true ) ? 'num-fmt'+decimal : null;
+		},
+	
+		// HTML numeric
+		function ( d, settings )
+		{
+			var decimal = settings.oLanguage.sDecimal;
+			return _htmlNumeric( d, decimal ) ? 'html-num'+decimal : null;
+		},
+	
+		// HTML numeric, formatted
+		function ( d, settings )
+		{
+			var decimal = settings.oLanguage.sDecimal;
+			return _htmlNumeric( d, decimal, true ) ? 'html-num-fmt'+decimal : null;
+		},
+	
+		// HTML (this is strict checking - there must be html)
+		function ( d, settings )
+		{
+			return _empty( d ) || (typeof d === 'string' && d.indexOf('<') !== -1) ?
+				'html' : null;
+		}
+	] );
+	
+	
+	
+	// Filter formatting functions. See model.ext.ofnSearch for information about
+	// what is required from these methods.
+	// 
+	// Note that additional search methods are added for the html numbers and
+	// html formatted numbers by `_addNumericSort()` when we know what the decimal
+	// place is
+	
+	
+	$.extend( DataTable.ext.type.search, {
+		html: function ( data ) {
+			return _empty(data) ?
+				data :
+				typeof data === 'string' ?
+					data
+						.replace( _re_new_lines, " " )
+						.replace( _re_html, "" ) :
+					'';
+		},
+	
+		string: function ( data ) {
+			return _empty(data) ?
+				data :
+				typeof data === 'string' ?
+					data.replace( _re_new_lines, " " ) :
+					data;
+		}
+	} );
+	
+	
+	
+	var __numericReplace = function ( d, decimalPlace, re1, re2 ) {
+		if ( d !== 0 && (!d || d === '-') ) {
+			return -Infinity;
+		}
+	
+		// If a decimal place other than `.` is used, it needs to be given to the
+		// function so we can detect it and replace with a `.` which is the only
+		// decimal place Javascript recognises - it is not locale aware.
+		if ( decimalPlace ) {
+			d = _numToDecimal( d, decimalPlace );
+		}
+	
+		if ( d.replace ) {
+			if ( re1 ) {
+				d = d.replace( re1, '' );
+			}
+	
+			if ( re2 ) {
+				d = d.replace( re2, '' );
+			}
+		}
+	
+		return d * 1;
+	};
+	
+	
+	// Add the numeric 'deformatting' functions for sorting and search. This is done
+	// in a function to provide an easy ability for the language options to add
+	// additional methods if a non-period decimal place is used.
+	function _addNumericSort ( decimalPlace ) {
+		$.each(
+			{
+				// Plain numbers
+				"num": function ( d ) {
+					return __numericReplace( d, decimalPlace );
+				},
+	
+				// Formatted numbers
+				"num-fmt": function ( d ) {
+					return __numericReplace( d, decimalPlace, _re_formatted_numeric );
+				},
+	
+				// HTML numeric
+				"html-num": function ( d ) {
+					return __numericReplace( d, decimalPlace, _re_html );
+				},
+	
+				// HTML numeric, formatted
+				"html-num-fmt": function ( d ) {
+					return __numericReplace( d, decimalPlace, _re_html, _re_formatted_numeric );
+				}
+			},
+			function ( key, fn ) {
+				// Add the ordering method
+				_ext.type.order[ key+decimalPlace+'-pre' ] = fn;
+	
+				// For HTML types add a search formatter that will strip the HTML
+				if ( key.match(/^html\-/) ) {
+					_ext.type.search[ key+decimalPlace ] = _ext.type.search.html;
+				}
+			}
+		);
+	}
+	
+	
+	// Default sort methods
+	$.extend( _ext.type.order, {
+		// Dates
+		"date-pre": function ( d ) {
+			return Date.parse( d ) || -Infinity;
+		},
+	
+		// html
+		"html-pre": function ( a ) {
+			return _empty(a) ?
+				'' :
+				a.replace ?
+					a.replace( /<.*?>/g, "" ).toLowerCase() :
+					a+'';
+		},
+	
+		// string
+		"string-pre": function ( a ) {
+			// This is a little complex, but faster than always calling toString,
+			// http://jsperf.com/tostring-v-check
+			return _empty(a) ?
+				'' :
+				typeof a === 'string' ?
+					a.toLowerCase() :
+					! a.toString ?
+						'' :
+						a.toString();
+		},
+	
+		// string-asc and -desc are retained only for compatibility with the old
+		// sort methods
+		"string-asc": function ( x, y ) {
+			return ((x < y) ? -1 : ((x > y) ? 1 : 0));
+		},
+	
+		"string-desc": function ( x, y ) {
+			return ((x < y) ? 1 : ((x > y) ? -1 : 0));
+		}
+	} );
+	
+	
+	// Numeric sorting types - order doesn't matter here
+	_addNumericSort( '' );
+	
+	
+	$.extend( true, DataTable.ext.renderer, {
+		header: {
+			_: function ( settings, cell, column, classes ) {
+				// No additional mark-up required
+				// Attach a sort listener to update on sort - note that using the
+				// `DT` namespace will allow the event to be removed automatically
+				// on destroy, while the `dt` namespaced event is the one we are
+				// listening for
+				$(settings.nTable).on( 'order.dt.DT', function ( e, ctx, sorting, columns ) {
+					if ( settings !== ctx ) { // need to check this this is the host
+						return;               // table, not a nested one
+					}
+	
+					var colIdx = column.idx;
+	
+					cell
+						.removeClass(
+							column.sSortingClass +' '+
+							classes.sSortAsc +' '+
+							classes.sSortDesc
+						)
+						.addClass( columns[ colIdx ] == 'asc' ?
+							classes.sSortAsc : columns[ colIdx ] == 'desc' ?
+								classes.sSortDesc :
+								column.sSortingClass
+						);
+				} );
+			},
+	
+			jqueryui: function ( settings, cell, column, classes ) {
+				$('<div/>')
+					.addClass( classes.sSortJUIWrapper )
+					.append( cell.contents() )
+					.append( $('<span/>')
+						.addClass( classes.sSortIcon+' '+column.sSortingClassJUI )
+					)
+					.appendTo( cell );
+	
+				// Attach a sort listener to update on sort
+				$(settings.nTable).on( 'order.dt.DT', function ( e, ctx, sorting, columns ) {
+					if ( settings !== ctx ) {
+						return;
+					}
+	
+					var colIdx = column.idx;
+	
+					cell
+						.removeClass( classes.sSortAsc +" "+classes.sSortDesc )
+						.addClass( columns[ colIdx ] == 'asc' ?
+							classes.sSortAsc : columns[ colIdx ] == 'desc' ?
+								classes.sSortDesc :
+								column.sSortingClass
+						);
+	
+					cell
+						.find( 'span.'+classes.sSortIcon )
+						.removeClass(
+							classes.sSortJUIAsc +" "+
+							classes.sSortJUIDesc +" "+
+							classes.sSortJUI +" "+
+							classes.sSortJUIAscAllowed +" "+
+							classes.sSortJUIDescAllowed
+						)
+						.addClass( columns[ colIdx ] == 'asc' ?
+							classes.sSortJUIAsc : columns[ colIdx ] == 'desc' ?
+								classes.sSortJUIDesc :
+								column.sSortingClassJUI
+						);
+				} );
+			}
+		}
+	} );
+	
+	/*
+	 * Public helper functions. These aren't used internally by DataTables, or
+	 * called by any of the options passed into DataTables, but they can be used
+	 * externally by developers working with DataTables. They are helper functions
+	 * to make working with DataTables a little bit easier.
+	 */
+	
+	var __htmlEscapeEntities = function ( d ) {
+		return typeof d === 'string' ?
+			d.replace(/</g, '&lt;').replace(/>/g, '&gt;').replace(/"/g, '&quot;') :
+			d;
+	};
+	
+	/**
+	 * Helpers for `columns.render`.
+	 *
+	 * The options defined here can be used with the `columns.render` initialisation
+	 * option to provide a display renderer. The following functions are defined:
+	 *
+	 * * `number` - Will format numeric data (defined by `columns.data`) for
+	 *   display, retaining the original unformatted data for sorting and filtering.
+	 *   It takes 5 parameters:
+	 *   * `string` - Thousands grouping separator
+	 *   * `string` - Decimal point indicator
+	 *   * `integer` - Number of decimal points to show
+	 *   * `string` (optional) - Prefix.
+	 *   * `string` (optional) - Postfix (/suffix).
+	 * * `text` - Escape HTML to help prevent XSS attacks. It has no optional
+	 *   parameters.
+	 *
+	 * @example
+	 *   // Column definition using the number renderer
+	 *   {
+	 *     data: "salary",
+	 *     render: $.fn.dataTable.render.number( '\'', '.', 0, '$' )
+	 *   }
+	 *
+	 * @namespace
+	 */
+	DataTable.render = {
+		number: function ( thousands, decimal, precision, prefix, postfix ) {
+			return {
+				display: function ( d ) {
+					if ( typeof d !== 'number' && typeof d !== 'string' ) {
+						return d;
+					}
+	
+					var negative = d < 0 ? '-' : '';
+					var flo = parseFloat( d );
+	
+					// If NaN then there isn't much formatting that we can do - just
+					// return immediately, escaping any HTML (this was supposed to
+					// be a number after all)
+					if ( isNaN( flo ) ) {
+						return __htmlEscapeEntities( d );
+					}
+	
+					flo = flo.toFixed( precision );
+					d = Math.abs( flo );
+	
+					var intPart = parseInt( d, 10 );
+					var floatPart = precision ?
+						decimal+(d - intPart).toFixed( precision ).substring( 2 ):
+						'';
+	
+					return negative + (prefix||'') +
+						intPart.toString().replace(
+							/\B(?=(\d{3})+(?!\d))/g, thousands
+						) +
+						floatPart +
+						(postfix||'');
+				}
+			};
+		},
+	
+		text: function () {
+			return {
+				display: __htmlEscapeEntities
+			};
+		}
+	};
+	
+	
+	/*
+	 * This is really a good bit rubbish this method of exposing the internal methods
+	 * publicly... - To be fixed in 2.0 using methods on the prototype
+	 */
+	
+	
+	/**
+	 * Create a wrapper function for exporting an internal functions to an external API.
+	 *  @param {string} fn API function name
+	 *  @returns {function} wrapped function
+	 *  @memberof DataTable#internal
+	 */
+	function _fnExternApiFunc (fn)
+	{
+		return function() {
+			var args = [_fnSettingsFromNode( this[DataTable.ext.iApiIndex] )].concat(
+				Array.prototype.slice.call(arguments)
+			);
+			return DataTable.ext.internal[fn].apply( this, args );
+		};
+	}
+	
+	
+	/**
+	 * Reference to internal functions for use by plug-in developers. Note that
+	 * these methods are references to internal functions and are considered to be
+	 * private. If you use these methods, be aware that they are liable to change
+	 * between versions.
+	 *  @namespace
+	 */
+	$.extend( DataTable.ext.internal, {
+		_fnExternApiFunc: _fnExternApiFunc,
+		_fnBuildAjax: _fnBuildAjax,
+		_fnAjaxUpdate: _fnAjaxUpdate,
+		_fnAjaxParameters: _fnAjaxParameters,
+		_fnAjaxUpdateDraw: _fnAjaxUpdateDraw,
+		_fnAjaxDataSrc: _fnAjaxDataSrc,
+		_fnAddColumn: _fnAddColumn,
+		_fnColumnOptions: _fnColumnOptions,
+		_fnAdjustColumnSizing: _fnAdjustColumnSizing,
+		_fnVisibleToColumnIndex: _fnVisibleToColumnIndex,
+		_fnColumnIndexToVisible: _fnColumnIndexToVisible,
+		_fnVisbleColumns: _fnVisbleColumns,
+		_fnGetColumns: _fnGetColumns,
+		_fnColumnTypes: _fnColumnTypes,
+		_fnApplyColumnDefs: _fnApplyColumnDefs,
+		_fnHungarianMap: _fnHungarianMap,
+		_fnCamelToHungarian: _fnCamelToHungarian,
+		_fnLanguageCompat: _fnLanguageCompat,
+		_fnBrowserDetect: _fnBrowserDetect,
+		_fnAddData: _fnAddData,
+		_fnAddTr: _fnAddTr,
+		_fnNodeToDataIndex: _fnNodeToDataIndex,
+		_fnNodeToColumnIndex: _fnNodeToColumnIndex,
+		_fnGetCellData: _fnGetCellData,
+		_fnSetCellData: _fnSetCellData,
+		_fnSplitObjNotation: _fnSplitObjNotation,
+		_fnGetObjectDataFn: _fnGetObjectDataFn,
+		_fnSetObjectDataFn: _fnSetObjectDataFn,
+		_fnGetDataMaster: _fnGetDataMaster,
+		_fnClearTable: _fnClearTable,
+		_fnDeleteIndex: _fnDeleteIndex,
+		_fnInvalidate: _fnInvalidate,
+		_fnGetRowElements: _fnGetRowElements,
+		_fnCreateTr: _fnCreateTr,
+		_fnBuildHead: _fnBuildHead,
+		_fnDrawHead: _fnDrawHead,
+		_fnDraw: _fnDraw,
+		_fnReDraw: _fnReDraw,
+		_fnAddOptionsHtml: _fnAddOptionsHtml,
+		_fnDetectHeader: _fnDetectHeader,
+		_fnGetUniqueThs: _fnGetUniqueThs,
+		_fnFeatureHtmlFilter: _fnFeatureHtmlFilter,
+		_fnFilterComplete: _fnFilterComplete,
+		_fnFilterCustom: _fnFilterCustom,
+		_fnFilterColumn: _fnFilterColumn,
+		_fnFilter: _fnFilter,
+		_fnFilterCreateSearch: _fnFilterCreateSearch,
+		_fnEscapeRegex: _fnEscapeRegex,
+		_fnFilterData: _fnFilterData,
+		_fnFeatureHtmlInfo: _fnFeatureHtmlInfo,
+		_fnUpdateInfo: _fnUpdateInfo,
+		_fnInfoMacros: _fnInfoMacros,
+		_fnInitialise: _fnInitialise,
+		_fnInitComplete: _fnInitComplete,
+		_fnLengthChange: _fnLengthChange,
+		_fnFeatureHtmlLength: _fnFeatureHtmlLength,
+		_fnFeatureHtmlPaginate: _fnFeatureHtmlPaginate,
+		_fnPageChange: _fnPageChange,
+		_fnFeatureHtmlProcessing: _fnFeatureHtmlProcessing,
+		_fnProcessingDisplay: _fnProcessingDisplay,
+		_fnFeatureHtmlTable: _fnFeatureHtmlTable,
+		_fnScrollDraw: _fnScrollDraw,
+		_fnApplyToChildren: _fnApplyToChildren,
+		_fnCalculateColumnWidths: _fnCalculateColumnWidths,
+		_fnThrottle: _fnThrottle,
+		_fnConvertToWidth: _fnConvertToWidth,
+		_fnGetWidestNode: _fnGetWidestNode,
+		_fnGetMaxLenString: _fnGetMaxLenString,
+		_fnStringToCss: _fnStringToCss,
+		_fnSortFlatten: _fnSortFlatten,
+		_fnSort: _fnSort,
+		_fnSortAria: _fnSortAria,
+		_fnSortListener: _fnSortListener,
+		_fnSortAttachListener: _fnSortAttachListener,
+		_fnSortingClasses: _fnSortingClasses,
+		_fnSortData: _fnSortData,
+		_fnSaveState: _fnSaveState,
+		_fnLoadState: _fnLoadState,
+		_fnSettingsFromNode: _fnSettingsFromNode,
+		_fnLog: _fnLog,
+		_fnMap: _fnMap,
+		_fnBindAction: _fnBindAction,
+		_fnCallbackReg: _fnCallbackReg,
+		_fnCallbackFire: _fnCallbackFire,
+		_fnLengthOverflow: _fnLengthOverflow,
+		_fnRenderer: _fnRenderer,
+		_fnDataSource: _fnDataSource,
+		_fnRowAttributes: _fnRowAttributes,
+		_fnCalculateEnd: function () {} // Used by a lot of plug-ins, but redundant
+		                                // in 1.10, so this dead-end function is
+		                                // added to prevent errors
+	} );
+	
+
+	// jQuery access
+	$.fn.dataTable = DataTable;
+
+	// Provide access to the host jQuery object (circular reference)
+	DataTable.$ = $;
+
+	// Legacy aliases
+	$.fn.dataTableSettings = DataTable.settings;
+	$.fn.dataTableExt = DataTable.ext;
+
+	// With a capital `D` we return a DataTables API instance rather than a
+	// jQuery object
+	$.fn.DataTable = function ( opts ) {
+		return $(this).dataTable( opts ).api();
+	};
+
+	// All properties that are available to $.fn.dataTable should also be
+	// available on $.fn.DataTable
+	$.each( DataTable, function ( prop, val ) {
+		$.fn.DataTable[ prop ] = val;
+	} );
+
+
+	// Information about events fired by DataTables - for documentation.
+	/**
+	 * Draw event, fired whenever the table is redrawn on the page, at the same
+	 * point as fnDrawCallback. This may be useful for binding events or
+	 * performing calculations when the table is altered at all.
+	 *  @name DataTable#draw.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 */
+
+	/**
+	 * Search event, fired when the searching applied to the table (using the
+	 * built-in global search, or column filters) is altered.
+	 *  @name DataTable#search.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 */
+
+	/**
+	 * Page change event, fired when the paging of the table is altered.
+	 *  @name DataTable#page.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 */
+
+	/**
+	 * Order event, fired when the ordering applied to the table is altered.
+	 *  @name DataTable#order.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 */
+
+	/**
+	 * DataTables initialisation complete event, fired when the table is fully
+	 * drawn, including Ajax data loaded, if Ajax data is required.
+	 *  @name DataTable#init.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} oSettings DataTables settings object
+	 *  @param {object} json The JSON object request from the server - only
+	 *    present if client-side Ajax sourced data is used</li></ol>
+	 */
+
+	/**
+	 * State save event, fired when the table has changed state a new state save
+	 * is required. This event allows modification of the state saving object
+	 * prior to actually doing the save, including addition or other state
+	 * properties (for plug-ins) or modification of a DataTables core property.
+	 *  @name DataTable#stateSaveParams.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} oSettings DataTables settings object
+	 *  @param {object} json The state information to be saved
+	 */
+
+	/**
+	 * State load event, fired when the table is loading state from the stored
+	 * data, but prior to the settings object being modified by the saved state
+	 * - allowing modification of the saved state is required or loading of
+	 * state for a plug-in.
+	 *  @name DataTable#stateLoadParams.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} oSettings DataTables settings object
+	 *  @param {object} json The saved state information
+	 */
+
+	/**
+	 * State loaded event, fired when state has been loaded from stored data and
+	 * the settings object has been modified by the loaded data.
+	 *  @name DataTable#stateLoaded.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} oSettings DataTables settings object
+	 *  @param {object} json The saved state information
+	 */
+
+	/**
+	 * Processing event, fired when DataTables is doing some kind of processing
+	 * (be it, order, searcg or anything else). It can be used to indicate to
+	 * the end user that there is something happening, or that something has
+	 * finished.
+	 *  @name DataTable#processing.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} oSettings DataTables settings object
+	 *  @param {boolean} bShow Flag for if DataTables is doing processing or not
+	 */
+
+	/**
+	 * Ajax (XHR) event, fired whenever an Ajax request is completed from a
+	 * request to made to the server for new data. This event is called before
+	 * DataTables processed the returned data, so it can also be used to pre-
+	 * process the data returned from the server, if needed.
+	 *
+	 * Note that this trigger is called in `fnServerData`, if you override
+	 * `fnServerData` and which to use this event, you need to trigger it in you
+	 * success function.
+	 *  @name DataTable#xhr.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 *  @param {object} json JSON returned from the server
+	 *
+	 *  @example
+	 *     // Use a custom property returned from the server in another DOM element
+	 *     $('#table').dataTable().on('xhr.dt', function (e, settings, json) {
+	 *       $('#status').html( json.status );
+	 *     } );
+	 *
+	 *  @example
+	 *     // Pre-process the data returned from the server
+	 *     $('#table').dataTable().on('xhr.dt', function (e, settings, json) {
+	 *       for ( var i=0, ien=json.aaData.length ; i<ien ; i++ ) {
+	 *         json.aaData[i].sum = json.aaData[i].one + json.aaData[i].two;
+	 *       }
+	 *       // Note no return - manipulate the data directly in the JSON object.
+	 *     } );
+	 */
+
+	/**
+	 * Destroy event, fired when the DataTable is destroyed by calling fnDestroy
+	 * or passing the bDestroy:true parameter in the initialisation object. This
+	 * can be used to remove bound events, added DOM nodes, etc.
+	 *  @name DataTable#destroy.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 */
+
+	/**
+	 * Page length change event, fired when number of records to show on each
+	 * page (the length) is changed.
+	 *  @name DataTable#length.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 *  @param {integer} len New length
+	 */
+
+	/**
+	 * Column sizing has changed.
+	 *  @name DataTable#column-sizing.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 */
+
+	/**
+	 * Column visibility has changed.
+	 *  @name DataTable#column-visibility.dt
+	 *  @event
+	 *  @param {event} e jQuery event object
+	 *  @param {object} o DataTables settings object {@link DataTable.models.oSettings}
+	 *  @param {int} column Column index
+	 *  @param {bool} vis `false` if column now hidden, or `true` if visible
+	 */
+
+	return $.fn.dataTable;
+}));
+
+

DELETED doc/html/qctool/js/jquery-1.4.2.min.js
Index: doc/html/qctool/js/jquery-1.4.2.min.js
==================================================================
--- doc/html/qctool/js/jquery-1.4.2.min.js
+++ doc/html/qctool/js/jquery-1.4.2.min.js
@@ -1,154 +0,0 @@
-/*!
- * jQuery JavaScript Library v1.4.2
- * http://jquery.com/
- *
- * Copyright 2010, John Resig
- * Dual licensed under the MIT or GPL Version 2 licenses.
- * http://jquery.org/license
- *
- * Includes Sizzle.js
- * http://sizzlejs.com/
- * Copyright 2010, The Dojo Foundation
- * Released under the MIT, BSD, and GPL Licenses.
- *
- * Date: Sat Feb 13 22:33:48 2010 -0500
- */
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Index: doc/html/qctool/reference.html
==================================================================
--- doc/html/qctool/reference.html
+++ doc/html/qctool/reference.html
@@ -3,23 +3,11 @@
 <html>
 	<head>
 
 		<script type="text/javascript" src="js/jquery-1.4.2.min.js"></script>
 		<script type="text/javascript" src="js/jquery.ba-hashchange.min.js"></script>
-		<!-- Google Analytics tracking code-->
-		<script type="text/javascript">
-			var _gaq = _gaq || [];
-			_gaq.push(['_setAccount', 'UA-16521993-1']);
-			_gaq.push(['_trackPageview']);
-
-			(function() {
-				var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
-				ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
-				var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
-			})();
-		</script>
-		<link href="style/css/default.css" rel="stylesheet" type="text/css">
+ 		<link href="style/css/default.css" rel="stylesheet" type="text/css">
 		<title>QCTOOL v2</title>
 	</head>
 	<body>
 		<div class="header" id="header1">
 			<!--<img src = "style/images/qctool.png" class = "header_img" ></img>-->

Index: doc/html/qctool/resources/options.json
==================================================================
--- doc/html/qctool/resources/options.json
+++ doc/html/qctool/resources/options.json
@@ -76,11 +76,11 @@
     "values_per_use": 1,
     "default": []
   },
   "-annotate-sequence": {
     "group": "",
-    "description": "Specify a FASTA-formatted file containing reference alleles to annotate variants with. This will appear as <name>_allele where <name> is the second argument.",
+    "description": "Specify a FASTA-formatted file containing reference alleles to annotate variants with. This will appear as &lt;name&gt;_allele where &lt;name&gt; is the second argument.",
     "is_required": 0,
     "multiplicity": {
       "min": 0,
       "max": 100
     },
@@ -171,11 +171,11 @@
     "multiplicity": {
       "min": 0,
       "max": 1
     },
     "values_per_use": 1,
-    "default": [ "position,alleles,ids" ]
+    "default": [ "position, alleles, ids" ]
   },
   "-compute-ld-with": {
     "group": "",
     "description": "Compute LD pairwise metrics between the main dataset and SNPs.",
     "is_required": 0,
@@ -296,11 +296,11 @@
     "values_per_use": "untilNextOption",
     "default": []
   },
   "-filetype": {
     "group": "",
-    "description": "Specify the filetype of the genotype files specified by -g. By default, qctool will guess the file type.  Use this option to override that guess. Possible types are: \"gen\",\"bgen\",\"vcf\",\"hapmap_haplotypes\",\"impute_haplotypes\",\"impute_allele_probs\",\"shapeit_haplotypes\",\"binary_ped\",\"long\",\"hlaimp\".",
+    "description": "Specify the filetype of the genotype files specified by -g. By default, qctool will guess the file type.  Use this option to override that guess. Possible types are: \"gen\", \"bgen\", \"vcf\", \"hapmap_haplotypes\", \"impute_haplotypes\", \"impute_allele_probs\", \"shapeit_haplotypes\", \"binary_ped\", \"long\", \"hlaimp\".",
     "is_required": 0,
     "multiplicity": {
       "min": 0,
       "max": 1
     },
@@ -703,11 +703,11 @@
     "values_per_use": 0,
     "default": []
   },
   "-ofiletype": {
     "group": "",
-    "description": "Specify the filetype of the output genotype files specified by -og. By default, qctool will guess the file type.  Use this option to override that guess. Possible types are: \"gen\",\"bgen\",\"bgen_v1.2\",\"bgen_v1.1\",\"vcf\",\"binary_ped\",\"shapeit_haplotypes\",\"shapeit\",\"impute_allele_probs\",\"dosage\",\"bimbam_dosage\",\"intensity\",\"penncnv\",\"cnvhap\".",
+    "description": "Specify the filetype of the output genotype files specified by -og. By default, qctool will guess the file type.  Use this option to override that guess. Possible types are: \"gen\", \"bgen\", \"bgen_v1.2\", \"bgen_v1.1\", \"vcf\", \"binary_ped\", \"shapeit_haplotypes\", \"shapeit\", \"impute_allele_probs\", \"dosage\", \"bimbam_dosage\", \"intensity\", \"penncnv\", \"cnvhap\".",
     "is_required": 112,
     "multiplicity": {
       "min": 0,
       "max": 1
     },
@@ -941,11 +941,11 @@
     "multiplicity": {
       "min": 0,
       "max": 1
     },
     "values_per_use": 1,
-    "default": [ "allele-frequencies,HWE,missingness,info" ]
+    "default": [ "allele-frequencies, HWE, missingness, info" ]
   },
   "-sort": {
     "group": "",
     "description": "Sort the genotypes in the output file.  Currently this is only supported if BGEN, unzipped GEN, unzipped VCF format is output.",
     "is_required": 0,
@@ -978,11 +978,11 @@
     "values_per_use": 1,
     "default": []
   },
   "-threads": {
     "group": "",
-    "description": "Specify the number of worker threads to use in computationally intensive tasks.",
+    "description": "Specify the number of worker threads to use in computationally intensive tasks.  This currently only applies to principal components computation (-PCs).",
     "is_required": 0,
     "multiplicity": {
       "min": 0,
       "max": 1
     },

Index: doc/html/qctool/style/css/default.css
==================================================================
--- doc/html/qctool/style/css/default.css
+++ doc/html/qctool/style/css/default.css
@@ -1,5 +1,9 @@
+@import "nav.css" ;
+@import "header.css" ;
+@import "table.css" ;
+
 /*
 img {
 	border: 1px solid red;
 }
 div {
@@ -13,133 +17,14 @@
 	margin-right: auto ;
 	overflow-y: scroll ;
 	/* border: 1px solid red; */
 }
 
-img.header_img {
-	float: left ;
-	padding-left: 10px ;
-	padding-right: 10px ;
-}
-
-img.header_arrow {
-	float: left;
-	clear: left ;
-	padding-left: 80px ;
-}
-
-.header_text {
-	float: left ;
-	padding-left: 10px ;
-	padding-right: 10px ;
-	font-family: Arial, Helvetica, Tahoma, sans-serif;
-	font-size: 40px ;
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-
-div.header_subtext {
-	padding-top: 20px ;
-	padding-left: 20px ;
-}
-
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-	border-bottom: 2px solid black ;
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-nav {
-	width: 900px ;
-	width: 1000px ;
-	position: absolute;
-	position: absolute;
-	top: 3em;
-	height: 3em;
-	margin-left: auto ;
-	margin-right: auto ;
-	font-family: helvetica, sans-serif ;
-	color: #000000;
-	background-color: white ;
-	/*border: 1px solid black ;*/
-}
-
-nav > div {
-	width: 800px ;
-	margin-left: auto ;
-	margin-right: auto ;
-}
-
-.nav_button {
-	display: inline-block;
-	position: relative;
-	box-sizing: border-box ;
-	margin-top: 10px ;
-	padding-left: 15px ;
-	padding-right: 15px ;
-	padding-top: 3px ;
-	padding-bottom: 0px ;
-	font-size: 22px ;
-	text-align: left ;
-}
-
-.nav_button.open {
-	background-color: rgba( 51, 176, 254, 0.9 ) ;
-}
-
-.nav_button ul a:hover {
-	background-color: rgba( 51, 176, 254, 0.9 ) ;
-}
-
-.nav_button a {
-	padding-left: 5px ;
-	padding-right: 5px ;
-	display: inline-block ;
-}
-
-.nav_button ul {
-	display:none ;
-	float: left ;
-	clear: both ;
-	box-sizing: border-box;
-	position: absolute ;
-	box-sizing: content-box ;
-	list-style: none;
-	text-align: left ;
-	left: 0px ;
-	min-width: 300px ;
-	background-color: white ;
-	padding: 3px ;
-	margin: 0px ;
-	font-size: 14px ;
-	/*width: 180px ;*/
-	padding-left: 3px ;
-	padding-right: 3px ;
-	background-color: rgba( 220, 220, 220, 0.95 ) ;
-	border-radius: 0px 0px 4px 4px;
-	box-shadow: 4px 4px 4px 0px rgba(0,0,0,0.2);
-}
-
-.nav_button ul a {
-	display: block;
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-
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-	color: black;
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-
-.nav_button.open ul {
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-
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 	font-style: italic ;
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@@ -170,81 +55,10 @@
 	padding: 10px ;
 	margin-top: 10px ;
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 	background-color: #22AD57 ;
 }
-
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-	background-color: #CCCCCC ;
-	padding: 10px ;
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-
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-	table-layout: fixed ;
-	width: 800px ;
-	margin-left: auto ;
-	margin-right: auto ;
-	font-family: helvetica, sans-serif ;
-	border-collapse: collapse ;
-}
-
-.file_formats thead, .option_table thead {
-	font-size: 14px ;
-	text-align: left ;
-	margin-bottom: 2px ;
-	vertical-align: bottom ;
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-
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-	font-size: 12px ;
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-.file_formats tr, .option_table tr {
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-.file_formats .acronym {
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-
-.file_formats .notes {
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-.file_formats .io {
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-.file_formats .filetype {
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-
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 h1, h2, h3, h4 {
 	font-family: sans-serif ;
 }
 

ADDED   doc/html/qctool/style/css/header.css
Index: doc/html/qctool/style/css/header.css
==================================================================
--- doc/html/qctool/style/css/header.css
+++ doc/html/qctool/style/css/header.css
@@ -0,0 +1,47 @@
+.header {
+	position: relative ;
+	height: 37px ;
+	width: 1000px ;
+}
+
+img.header_img {
+	float: left ;
+	padding-left: 10px ;
+	padding-right: 10px ;
+}
+
+img.header_arrow {
+	float: left;
+	clear: left ;
+	padding-left: 80px ;
+}
+
+.header_text {
+	float: left ;
+	padding-left: 10px ;
+	padding-right: 10px ;
+	font-family: Arial, Helvetica, Tahoma, sans-serif;
+	font-size: 40px ;
+}
+
+div.header_subtext {
+	position: absolute ;
+	padding-top: 20px ;
+	left: 0px ;
+	width: 100% ;
+	text-align: center ;
+}
+
+div.header {
+	border-bottom: 1px solid black ;
+	padding-bottom: 2px ;
+	font-family: sans-serif ;
+	font-size: 15px ;
+}
+
+.header .logo {
+	position: absolute ;
+	height: 40px ;
+	top: 3px ;
+	right: 15px ;
+}

ADDED   doc/html/qctool/style/css/nav.css
Index: doc/html/qctool/style/css/nav.css
==================================================================
--- doc/html/qctool/style/css/nav.css
+++ doc/html/qctool/style/css/nav.css
@@ -0,0 +1,97 @@
+nav {
+	width: 1000px ;
+	position: absolute ;
+	top: 2.5em;
+	height: 1.5em;
+//	left: 20px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	font-family: helvetica, sans-serif ;
+	font-size: 16pt ;
+	color: #000000;
+	padding-top: 0px ;
+	padding-bottom: 10px ;
+	padding-left: 0px ;
+	margin-top:0px ;
+	margin-bottom:0px ;
+	border-radius: 2px ;
+	/*border: 1px solid black ;*/
+}
+
+nav > div {
+	width: 1000px ;
+	box-sizing: border-box ;
+	padding-left: 140px;
+	padding-right: 140px;
+	margin-left: auto ;
+	margin-right: auto ;
+	//background-color: rgba( 220, 220, 220, 0.95 ) ;
+	background: #FAFAFA ;
+	border-radius: 5px ;
+}
+
+.nav_button {
+	display: inline-block;
+	position: relative;
+	box-sizing: border-box ;
+	box-sizing: border-box ;
+	padding-left: 15px ;
+	padding-right: 15px ;
+	padding-top: 3px ;
+	padding-bottom: 0px ;
+	text-align: left ;
+}
+
+.nav_button.open {
+	background-color: rgba( 51, 176, 254, 0.9 ) ;
+}
+
+.nav_button ul a:hover {
+	background-color: rgba( 51, 176, 254, 0.9 ) ;
+}
+
+.nav_button a {
+	padding-left: 5px ;
+	padding-right: 5px ;
+	display: inline-block ;
+}
+
+.nav_button ul {
+	display:none ;
+	float: left ;
+	clear: both ;
+	box-sizing: border-box;
+	position: absolute ;
+	box-sizing: content-box ;
+	list-style: none;
+	text-align: left ;
+	left: 0px ;
+	min-width: 300px ;
+	background-color: white ;
+	padding: 3px ;
+	margin: 0px ;
+	font-size: 14px ;
+	/*width: 180px ;*/
+	padding-left: 3px ;
+	padding-right: 3px ;
+	background-color: rgba( 220, 220, 220, 0.95 ) ;
+	border-radius: 0px 0px 4px 4px;
+	box-shadow: 4px 4px 4px 0px rgba(0,0,0,0.2);
+}
+
+.nav_button ul a {
+	display: block;
+	width: auto;
+	padding-top: 2px ;
+	padding-bottom: 2px ;
+	padding-left: 15px ;
+}
+
+nav a, nav a:hover, nav a:visited {
+	color: black;
+	text-decoration: none ;
+}
+
+.nav_button.open ul {
+	display:block ;
+}

ADDED   doc/html/qctool/style/css/table.css
Index: doc/html/qctool/style/css/table.css
==================================================================
--- doc/html/qctool/style/css/table.css
+++ doc/html/qctool/style/css/table.css
@@ -0,0 +1,80 @@
+#download table {
+	text-align: left ;
+	width: 600px ;
+	border: 1px solid black ;
+	background-color: #CCCCCC ;
+	padding: 10px ;
+	font-size: 16pt ;
+}
+
+.file_formats, .option_table, .download {
+	table-layout: fixed ;
+	width: 800px ;
+	margin-left: auto ;
+	margin-right: auto ;
+	font-family: monospace, helvetica, sans-serif ;
+	border-collapse: separate ;
+	text-align: left ;
+	border-spacing: 0px ;
+}
+
+table thead {
+	font-size: 16px ;
+	text-align: left ;
+	margin-bottom: 2px ;
+	vertical-align: bottom ;
+	border-bottom: 1px solid black ;
+}
+
+table tbody {
+	font-size: 12px ;
+}
+
+table code {
+	font-size: 10px ;
+}
+
+table tbody tr:nth-child(odd) {
+	background: #eeeeee ;
+}
+
+table.dataTable tr.odd { background-color: #eeeeee; }
+
+table thead th {
+	padding-top: 3px ;
+	padding-bottom: 3px ;
+	padding-left: 5px ;
+	border-bottom: 1px solid black ;
+	//text-align: left ;
+}
+
+table tbody td {
+	vertical-align: top ;
+	padding-top: 5px ;
+	padding-bottom: 5px ;
+}
+/*
+.file_formats .acronym {
+	width: 100px ;
+}
+
+.file_formats .notes {
+	width: 400px ;
+}
+
+.file_formats .io {
+	width: 50px ;
+}
+
+.file_formats .filetype {
+	width: 150px ;
+}
+*/
+
+.option_table .option {
+	width: 200px ;
+}
+
+.option_table .description {
+	width: 500px ;
+}

Index: doc/html/qctool/style/images/qctool.png
==================================================================
--- doc/html/qctool/style/images/qctool.png
+++ doc/html/qctool/style/images/qctool.png
cannot compute difference between binary files

ADDED   doc/html/qctool/style/images/qctool.svg
Index: doc/html/qctool/style/images/qctool.svg
==================================================================
--- doc/html/qctool/style/images/qctool.svg
+++ doc/html/qctool/style/images/qctool.svg
@@ -0,0 +1,98 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<svg
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+   xmlns:cc="http://creativecommons.org/ns#"
+   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
+   xmlns:svg="http://www.w3.org/2000/svg"
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+   xmlns:sodipodi="http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd"
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+   inkscape:export-xdpi="85.517021"
+   inkscape:export-filename="/Users/gav/Projects/Web/code.enkre.net/style/images/qctool.png"
+   sodipodi:docname="qctool.svg"
+   inkscape:version="1.0 (4035a4f, 2020-05-01)"
+   id="svg3196"
+   version="1.1"
+   viewBox="0 0 64 64"
+   height="64mm"
+   width="64mm">
+  <defs
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+  <sodipodi:namedview
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+     inkscape:document-rotation="0"
+     inkscape:current-layer="g867"
+     inkscape:document-units="mm"
+     inkscape:cy="61.792551"
+     inkscape:cx="59.815985"
+     inkscape:zoom="4.459781"
+     inkscape:pageshadow="2"
+     inkscape:pageopacity="0.0"
+     borderopacity="1.0"
+     bordercolor="#666666"
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+      <cc:Work
+         rdf:about="">
+        <dc:format>image/svg+xml</dc:format>
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+        <dc:title />
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+         y="21.008009"
+         x="13.434908"
+         style="font-style:normal;font-weight:normal;font-size:5.11976px;line-height:1.25;font-family:sans-serif;letter-spacing:0px;fill:#000000;fill-opacity:1;stroke:none;stroke-width:0.127994"
+         xml:space="preserve"><tspan
+           style="font-style:normal;font-variant:normal;font-weight:600;font-stretch:normal;font-size:2.73054px;font-family:'.Aqua Kana';-inkscape-font-specification:'.Aqua Kana Semi-Bold';fill:#feffff;fill-opacity:1;stroke-width:0.127994"
+           y="21.008009"
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+         style="fill:#000000;fill-opacity:1;stroke:#000000;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
+         sodipodi:nodetypes="cccccccccccc" />
+    </g>
+  </g>
+</svg>

Index: fputils/wscript
==================================================================
--- fputils/wscript
+++ fputils/wscript
@@ -8,11 +8,11 @@
 def create_test( bld, name ):
 	bld(
 		features = 'cxx cprogram',
 		target = name,
 		source = [  'test/' + name + '.cpp' ],
-		uselib_local = 'fputils boost-unit_test_framework',
+		uselib_local = 'fputils boost_unit_test_framework',
 		uselib = 'BOOST_UNIT_TEST_FRAMEWORK',
 		includes='./include',
 		unit_test=1,
 		install_path = None
 	)
@@ -33,14 +33,14 @@
 	# libs
 	#---------------------
 	bld(
 		features = 'cxx cstaticlib',
 		target = 'fputils',
-		source = bld.glob( 'src/*.cpp' ),
+		source = bld.path.ant_glob 'src/*.cpp' ),
 		includes='./include',
 		uselib_local = 'boost',
 		uselib = 'BOOST',
-		export_incdirs = './include'
+		export_includes = './include'
 	)
 	
 	create_test( bld, 'test_log_sum_exp' )
 	create_test( bld, 'test_log_multiply_exp' )

Index: genfile/include/genfile/BGenFileSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/BGenFileSNPDataSource.hpp
+++ genfile/include/genfile/BGenFileSNPDataSource.hpp
@@ -30,10 +30,11 @@
 		BGenFileSNPDataSource( std::string const& filename, Chromosome missing_chromosome = Chromosome() ) ;
 
 		Metadata get_metadata() const ;
 
 		unsigned int number_of_samples() const { return m_bgen_context.number_of_samples ; }
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 		OptionalSnpCount total_number_of_snps() const { return m_bgen_context.number_of_variants ; }
 		operator bool() const { return m_stream_ptr->good() ; }
 
 		std::istream& stream() { return *m_stream_ptr ; }

Index: genfile/include/genfile/BedFileSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/BedFileSNPDataSource.hpp
+++ genfile/include/genfile/BedFileSNPDataSource.hpp
@@ -26,10 +26,11 @@
 	public:
 		BedFileSNPDataSource( std::string const& bedFilename, std::string const& bimFilename, std::string const& famFilename ) ;
 
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const { return m_number_of_samples ; }
+		bool has_sample_ids() const { return false ; }
 		OptionalSnpCount total_number_of_snps() const { return m_total_number_of_snps ; }
 		operator bool() const { return !m_exhausted && *m_bed_stream_ptr ; }
 
 		std::istream& stream() { return *m_bed_stream_ptr ; }
 		std::istream const& stream() const { return *m_bed_stream_ptr ; }

ADDED   genfile/include/genfile/CartesianProductVisitor.hpp
Index: genfile/include/genfile/CartesianProductVisitor.hpp
==================================================================
--- genfile/include/genfile/CartesianProductVisitor.hpp
+++ genfile/include/genfile/CartesianProductVisitor.hpp
@@ -0,0 +1,71 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_CARTESIANPRODUCTVISITOR_HPP
+#define GENFILE_CARTESIANPRODUCTVISITOR_HPP 1
+
+#include <vector>
+#include "boost/optional.hpp"
+#include "boost/noncopyable.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantDataReader.hpp"
+#include "genfile/SNPDataSource.hpp"
+#include "genfile/MultiSourceVisitor.hpp"
+
+namespace genfile {
+	struct CartesianProductVisitor: public MultiSourceVisitor {
+	public:
+		CartesianProductVisitor( bool lower_triangle = false ) ;
+
+		void add_source(
+			std::string const& name,
+			genfile::SNPDataSource* source
+		) ;
+
+		// Specify that the visitor should skip any configuration
+		// containing two variants with the same chromosome and
+		// within the given distance
+		void set_min_distance( int64_t distance ) ;
+
+		// Return the next configuration via the callback
+		// Callback receives:
+		// - A 0-1 vector indicating which variants have changed
+		// since the last call to step() (or all ones on the first call.)
+		// - The list of VariantIdentifyingData structures
+		// - The VariantDataReaders.
+		bool step( Callback callback ) ;
+
+		// Return the number of combinations that will be returned,
+		// if it can be computed.
+		boost::optional< std::size_t > count() const ;
+
+		// return the number of components that will be iterated over
+		std::size_t size() const { return m_sources.size() ; }
+
+	private:
+		std::vector< std::string > m_names ;
+		bool const m_lower_triangle ;
+		int64_t m_min_distance ;
+		std::vector< genfile::SNPDataSource* > m_sources ;
+		std::vector< genfile::VariantIdentifyingData > m_variants ;
+		std::vector< genfile::VariantDataReader::SharedPtr > m_readers ;
+		std::vector< int > m_changed ;
+	
+	private:
+	
+		bool step_impl() ;
+		void reset_source( std::size_t i ) ;
+
+		// utility function to return minimum physical distance between any pair
+		// of variants on same chromosome, or maximum +pve value of int64 if all
+		// on different chromosomes
+		int64_t compute_min_distance(
+			std::vector< genfile::VariantIdentifyingData > const& variants
+		) const ;
+	} ;
+}
+
+#endif

Index: genfile/include/genfile/CategoricalCrossCohortCovariateValueMapping.hpp
==================================================================
--- genfile/include/genfile/CategoricalCrossCohortCovariateValueMapping.hpp
+++ genfile/include/genfile/CategoricalCrossCohortCovariateValueMapping.hpp
@@ -23,12 +23,12 @@
 			std::string const& column_name
 		) ;
 		
 		std::size_t get_number_of_distinct_mapped_values() const ;
 
-		// Return the entry corresponding to level i.
-		// i must be a positive integer in the range 1...number of distinct entries
+		// Return the entry corresponding to the given level.
+		// level must be a positive integer in the half-open range 0...number of distinct entries
 		Entry get_unmapped_value( Entry const& level ) const ;
 		
 		// Return the level (positive integer) corresponding to the given entry.
 		// It is an error to pass this method an entry not present in the relevant column of the sources
 		// this object has had added.

Index: genfile/include/genfile/CountingCohortIndividualSource.hpp
==================================================================
--- genfile/include/genfile/CountingCohortIndividualSource.hpp
+++ genfile/include/genfile/CountingCohortIndividualSource.hpp
@@ -1,22 +1,23 @@
 #ifndef GENFILE_COUNTING_COHORT_INDIVIDUAL_SOURCE_HPP
 #define GENFILE_COUNTING_COHORT_INDIVIDUAL_SOURCE_HPP
 
 #include "genfile/CohortIndividualSource.hpp"
+#include "genfile/VariantEntry.hpp"
 
 namespace genfile {
 	struct CountingCohortIndividualSource: public CohortIndividualSource
 	{
 		CountingCohortIndividualSource( std::size_t number_of_samples, std::string const& sample_name_template ) ;
-		CountingCohortIndividualSource( std::vector< std::string > const& sample_ids ) ;
+		CountingCohortIndividualSource( std::vector< genfile::VariantEntry > const& sample_ids ) ;
 		std::size_t get_number_of_individuals() const ;
 		ColumnSpec get_column_spec() const ;
 		bool check_for_column( std::string const& column_name ) const ;
 		Entry get_entry( std::size_t sample_i, std::string const& column_name ) const ;
 		Entry get_entry( std::size_t sample_i, std::size_t const column_index ) const ;
 		std::string get_source_spec() const ;
 	private:
-		std::vector< std::string > m_sample_ids ;
+		std::vector< genfile::VariantEntry > m_sample_ids ;
 	} ;
 }
 #endif
 

Index: genfile/include/genfile/CrossCohortCovariateValueMapping.hpp
==================================================================
--- genfile/include/genfile/CrossCohortCovariateValueMapping.hpp
+++ genfile/include/genfile/CrossCohortCovariateValueMapping.hpp
@@ -17,11 +17,11 @@
 		// Base classes for classes which map a given column of phenotypes or covariates,
 		// across several cohorts, to transformed values.
 	{
 	public:
 		typedef std::auto_ptr< CrossCohortCovariateValueMapping > UniquePtr ;
-		static UniquePtr create( CohortIndividualSource::SingleColumnSpec const& column_spec ) ;
+		static UniquePtr create( CohortIndividualSource::SingleColumnSpec const& column_spec, bool normalise = false ) ;
 
 		typedef CohortIndividualSource::Entry Entry ;
 		typedef std::map< Entry, unsigned int > Histogram ;
 	public:
 		virtual ~CrossCohortCovariateValueMapping() {}

Index: genfile/include/genfile/DosageFileSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/DosageFileSNPDataSource.hpp
+++ genfile/include/genfile/DosageFileSNPDataSource.hpp
@@ -33,10 +33,11 @@
 			CompressionType compression_type
 		) ;
 
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const { return m_number_of_samples ; }
+		bool has_sample_ids() const { return false ; } // reading IDs not currently implemented
 		OptionalSnpCount total_number_of_snps() const { return m_total_number_of_snps ; }
 		
 		operator bool() const { return m_stream_ptr->good() ; }
 		std::istream& stream() { return *m_stream_ptr ; }
 		std::istream const& stream() const { return *m_stream_ptr ; }

ADDED   genfile/include/genfile/GPThresholdingGTSetter.hpp
Index: genfile/include/genfile/GPThresholdingGTSetter.hpp
==================================================================
--- genfile/include/genfile/GPThresholdingGTSetter.hpp
+++ genfile/include/genfile/GPThresholdingGTSetter.hpp
@@ -0,0 +1,42 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_GP_THRESHOLDING_GT_SETTER
+#define GENFILE_GP_THRESHOLDING_GT_SETTER
+
+#include "genfile/VariantDataReader.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/types.hpp"
+
+namespace genfile {
+	struct GPThresholdingGTSetter: public VariantDataReader::PerSampleSetter {
+		GPThresholdingGTSetter( VariantDataReader::PerSampleSetter& target, double const threshhold ) ;
+		~GPThresholdingGTSetter() throw() ;
+		
+		void initialise( std::size_t nSamples, std::size_t nAlleles ) ;
+		bool set_sample( std::size_t i ) ;
+		void set_number_of_entries( uint32_t ploidy, std::size_t number_of_entries, OrderType const order_type, ValueType const value_type ) ;
+		void set_value( std::size_t, MissingValue const value ) ;
+		void set_value( std::size_t, std::string& value ) ;
+		void set_value( std::size_t, Integer const value ) ;
+		void set_value( std::size_t, double const value ) ;
+		void finalise() ;
+	private:
+		VariantDataReader::PerSampleSetter& m_target ;
+		double const m_threshhold ;
+		std::size_t m_number_of_alleles ;
+		OrderType m_order_type ;
+		uint32_t m_ploidy ;
+		int m_entry_i ;
+		Eigen::VectorXd m_calls ;
+		bool m_missing ;
+	
+	private:
+		void send_results() ;
+	} ;
+}
+
+#endif

Index: genfile/include/genfile/GenFileSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/GenFileSNPDataSource.hpp
+++ genfile/include/genfile/GenFileSNPDataSource.hpp
@@ -28,10 +28,11 @@
 		GenFileSNPDataSource( std::string const& filename, Chromosome chromosome ) ;
 
 		Metadata get_metadata() const ;
 
 		unsigned int number_of_samples() const { return m_number_of_samples ; }
+		bool has_sample_ids() const { return false ; }
 		OptionalSnpCount total_number_of_snps() const { return m_total_number_of_snps ; }
 		
 		operator bool() const { return m_stream_ptr->good() ; }
 		std::istream& stream() { return *m_stream_ptr ; }
 		std::istream const& stream() const { return *m_stream_ptr ; }

Index: genfile/include/genfile/HLAIMPAsBiallelicVariantDataSource.hpp
==================================================================
--- genfile/include/genfile/HLAIMPAsBiallelicVariantDataSource.hpp
+++ genfile/include/genfile/HLAIMPAsBiallelicVariantDataSource.hpp
@@ -31,10 +31,11 @@
 
 	public:
 		Metadata get_metadata() const ;
 
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const { return true ; }
 		void get_sample_ids( GetSampleIds ) const ;
 
 		OptionalSnpCount total_number_of_snps() const ;
 		operator bool() const ;
 

Index: genfile/include/genfile/HapmapHaplotypesSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/HapmapHaplotypesSNPDataSource.hpp
+++ genfile/include/genfile/HapmapHaplotypesSNPDataSource.hpp
@@ -23,10 +23,11 @@
 		HapmapHaplotypesSNPDataSource( std::string const& filename, Chromosome chromosome, CompressionType compression_type ) ;
 
 		Metadata get_metadata() const ;
 
 		unsigned int number_of_samples() const { return m_number_of_samples ; }
+		bool has_sample_ids() const { return false ; }
 		OptionalSnpCount total_number_of_snps() const { return m_total_number_of_snps ; }
 		
 		operator bool() const { return m_stream_ptr->good() ; }
 		std::istream& stream() { return *m_stream_ptr ; }
 		std::istream const& stream() const { return *m_stream_ptr ; }

Index: genfile/include/genfile/ImputeHapProbsSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/ImputeHapProbsSNPDataSource.hpp
+++ genfile/include/genfile/ImputeHapProbsSNPDataSource.hpp
@@ -28,10 +28,11 @@
 		ImputeHapProbsSNPDataSource( std::string const& filename, Chromosome chromosome ) ;
 
 		Metadata get_metadata() const ;
 
 		unsigned int number_of_samples() const { return m_number_of_samples ; }
+		bool has_sample_ids() const { return false ; }
 		OptionalSnpCount total_number_of_snps() const { return m_total_number_of_snps ; }
 		
 		operator bool() const { return m_stream_ptr->good() ; }
 		std::istream& stream() { return *m_stream_ptr ; }
 		std::istream const& stream() const { return *m_stream_ptr ; }

Index: genfile/include/genfile/ImputeHaplotypesSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/ImputeHaplotypesSNPDataSource.hpp
+++ genfile/include/genfile/ImputeHaplotypesSNPDataSource.hpp
@@ -24,10 +24,11 @@
 		ImputeHaplotypesSNPDataSource( std::string const& haplotypes_filename, Chromosome chromosome, CompressionType compression_type ) ;
 
 		Metadata get_metadata() const ;
 
 		unsigned int number_of_samples() const { return m_number_of_samples ; }
+		bool has_sample_ids() const { return false ; }
 		OptionalSnpCount total_number_of_snps() const { return m_snps.size() ; }
 		
 		operator bool() const { return m_good ; }
 		std::istream& stream() { return *m_stream_ptr ; }
 		std::istream const& stream() const { return *m_stream_ptr ; }

ADDED   genfile/include/genfile/ListSNPDataSink.hpp
Index: genfile/include/genfile/ListSNPDataSink.hpp
==================================================================
--- genfile/include/genfile/ListSNPDataSink.hpp
+++ genfile/include/genfile/ListSNPDataSink.hpp
@@ -0,0 +1,64 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef LISTSNPDATASINK_HPP
+#define LISTSNPDATASINK_HPP
+
+#include <iostream>
+#include <string>
+#include "genfile/snp_data_utils.hpp"
+#include "genfile/SNPDataSink.hpp"
+#include "genfile/bgen/bgen.hpp"
+#include "genfile/Error.hpp"
+
+namespace genfile {
+
+	// This class encapsulates the basic method of writing a BGen file.
+	class ListSNPDataSink: public SNPDataSink
+	{
+	public:
+		// This class is intended to be used via a derived class.
+		ListSNPDataSink(
+			std::string const& filename,
+			CompressionType compression_type
+		) ;
+
+		ListSNPDataSink(
+			std::auto_ptr< std::ostream > stream_ptr,
+			std::string const& filename,
+			CompressionType compression_type
+		) ;
+
+		SinkPos get_stream_pos() const ;
+		std::string get_spec() const ;
+
+	public:
+		// Methods required by SNPDataSink
+		operator bool() const ;
+		
+		void write_variant_data_impl(
+			VariantIdentifyingData const& id_data,
+			VariantDataReader& data_reader,
+			Info const& info
+		) ;
+		void set_sample_names_impl( std::size_t number_of_samples, SampleNameGetter sample_name_getter ) ;
+
+	protected:
+		// Other methods.
+		std::auto_ptr< std::ostream >& stream_ptr() ;
+		std::string const& filename() const ;
+		
+	private:
+
+		void setup() ;
+
+		std::string m_filename ;
+		std::auto_ptr< std::ostream > m_stream_ptr ;
+	} ;
+}
+
+#endif
+

Index: genfile/include/genfile/LongFormatSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/LongFormatSNPDataSource.hpp
+++ genfile/include/genfile/LongFormatSNPDataSource.hpp
@@ -28,10 +28,11 @@
 
 	public:
 		Metadata get_metadata() const ;
 
 		unsigned int number_of_samples() const { return m_samples.size() ; }
+		bool has_sample_ids() const { return true ; }
 		void get_sample_ids( GetSampleIds ) const ;
 
 		OptionalSnpCount total_number_of_snps() const { return m_variant_map.size() ; }
 		operator bool() const { return !m_exhausted ; }
 

Index: genfile/include/genfile/MergingSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/MergingSNPDataSource.hpp
+++ genfile/include/genfile/MergingSNPDataSource.hpp
@@ -29,19 +29,21 @@
 		Metadata get_metadata() const ;
 
 		operator bool() const ;
 		// Return the number of samples represented in the snps in this source.
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const ;
+		void get_sample_ids( GetSampleIds getter ) const ;
+
 		// Return the total number of snps the source contains.
 		OptionalSnpCount total_number_of_snps() const ;
 
 		// Return a string identifying the source of the SNP data
 		std::string get_source_spec() const ;
 
 	private:
-		void get_snp_identifying_data_impl( 
-VariantIdentifyingData* variant		) ;	
+		void get_snp_identifying_data_impl( VariantIdentifyingData* variant ) ;	
 
 		VariantDataReader::UniquePtr read_variant_data_impl()  ;
 
 		void ignore_snp_probability_data_impl() ;
 		void reset_to_start_impl() ;

ADDED   genfile/include/genfile/MultiSourceVisitor.hpp
Index: genfile/include/genfile/MultiSourceVisitor.hpp
==================================================================
--- genfile/include/genfile/MultiSourceVisitor.hpp
+++ genfile/include/genfile/MultiSourceVisitor.hpp
@@ -0,0 +1,32 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_MULTISOURCEVISITOR_HPP
+#define GENFILE_MULTISOURCEVISITOR_HPP 1
+
+#include <vector>
+#include "boost/optional.hpp"
+#include "boost/noncopyable.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantDataReader.hpp"
+
+namespace genfile {
+	struct MultiSourceVisitor: public boost::noncopyable {
+	public:
+		typedef boost::function<
+			void (
+				std::vector< int > const& changed,
+				std::vector< genfile::VariantIdentifyingData > const& variants,
+				std::vector< genfile::VariantDataReader::SharedPtr > const& readers
+		) > Callback ;
+	public:
+		~MultiSourceVisitor() {} ;
+		virtual bool step( Callback callback ) = 0 ;
+		virtual boost::optional< std::size_t > count() const = 0 ;
+	} ;
+}
+
+#endif

Index: genfile/include/genfile/PloidyConvertingSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/PloidyConvertingSNPDataSource.hpp
+++ genfile/include/genfile/PloidyConvertingSNPDataSource.hpp
@@ -36,10 +36,11 @@
 
 	public:
 		operator bool() const { return *m_source ; }
 		Metadata get_metadata() const { return m_source->get_metadata() ; }
 		unsigned int number_of_samples() const { return m_source->number_of_samples() ;}
+		bool has_sample_ids() const { return m_source->has_sample_ids() ; }
 		void get_sample_ids( GetSampleIds getter ) const { return m_source->get_sample_ids( getter ) ; }
 
 		OptionalSnpCount total_number_of_snps() const { return m_source->total_number_of_snps() ; }
 		std::string get_source_spec() const { return "PloidyConverting:" + m_source->get_source_spec() ; }
 		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const {

Index: genfile/include/genfile/ReorderingSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/ReorderingSNPDataSource.hpp
+++ genfile/include/genfile/ReorderingSNPDataSource.hpp
@@ -53,10 +53,12 @@
 			return m_source->operator bool() ;
 		} ;
 		unsigned int number_of_samples() const {
 			return m_order.size() ;
 		};
+		bool has_sample_ids() const ;
+		void get_sample_ids( GetSampleIds ) const ;
 		OptionalSnpCount total_number_of_snps() const {
 			return m_source->total_number_of_snps() ;
 		} ;
 		std::string get_source_spec() const {
 			return "reordered:" + m_source->get_source_spec() ;
@@ -103,12 +105,12 @@
 		std::vector< std::pair< OrderType, ValueType > > m_types ;
 		std::vector< std::vector< char > > m_entry_types ;
 		std::vector< std::vector< Integer > > m_ints ;
 		std::vector< std::vector< std::string > > m_strings ;
 		std::vector< std::vector< double > > m_doubles ;
-		
+		std::vector< std::string > m_sample_ids ;
+
 		friend struct ReorderingVariantDataReader ;
-		
 	} ;
 }
 
 #endif

Index: genfile/include/genfile/SNPDataSource.hpp
==================================================================
--- genfile/include/genfile/SNPDataSource.hpp
+++ genfile/include/genfile/SNPDataSource.hpp
@@ -169,15 +169,17 @@
 		virtual operator bool() const = 0 ;
 		// Return the number of samples represented in the snps in this source.
 		virtual unsigned int number_of_samples() const = 0;
 
 		typedef boost::function< void( std::size_t, std::string ) > GetSampleIds ;
-		virtual void get_sample_ids( GetSampleIds ) const {} ;
+		virtual bool has_sample_ids() const = 0 ;
+		virtual void get_sample_ids( GetSampleIds ) const ;
 
 		// Return the total number of snps the source contains.
 		typedef boost::optional< std::size_t > OptionalSnpCount ;
-		virtual OptionalSnpCount total_number_of_snps() const = 0 ;
+		virtual OptionalSnpCount total_number_of_snps() const = 0 ; // deprecated
+		OptionalSnpCount size() const { return total_number_of_snps() ; }
 
 		// Return a string identifying the source of the SNP data
 		virtual std::string get_source_spec() const = 0 ;
 		
 		// In order to support filtered views of source data, we interpret the source
@@ -195,13 +197,13 @@
 		
 		virtual std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
 
 	protected:
 
-		virtual void get_snp_identifying_data_impl( 
+		virtual void get_snp_identifying_data_impl(
 			VariantIdentifyingData* variant
-		) = 0 ;	
+		) = 0 ;
 
 		void read_snp_probability_data_impl(
 			GenotypeProbabilitySetter const& ,
 			std::string const& genotype_field
 		) ;

Index: genfile/include/genfile/SNPDataSourceChain.hpp
==================================================================
--- genfile/include/genfile/SNPDataSourceChain.hpp
+++ genfile/include/genfile/SNPDataSourceChain.hpp
@@ -46,10 +46,11 @@
 
 		void add_source( std::auto_ptr< SNPDataSource > source ) ;
 
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 
 		OptionalSnpCount total_number_of_snps() const ;
 		unsigned int number_of_sources() const ;
 		OptionalSnpCount number_of_snps_in_source( std::size_t source_index ) const ;

Index: genfile/include/genfile/SNPDataSourceRack.hpp
==================================================================
--- genfile/include/genfile/SNPDataSourceRack.hpp
+++ genfile/include/genfile/SNPDataSourceRack.hpp
@@ -81,10 +81,11 @@
 		std::size_t number_of_sources() const ;
 		SNPDataSource& get_source( std::size_t ) const ;
 
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 
 		OptionalSnpCount total_number_of_snps() const ;
 		operator bool() const ;
 		std::string get_source_spec() const ;

Index: genfile/include/genfile/SNPFilteringSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/SNPFilteringSNPDataSource.hpp
+++ genfile/include/genfile/SNPFilteringSNPDataSource.hpp
@@ -31,10 +31,11 @@
 		SNPFilteringSNPDataSource( SNPDataSource::UniquePtr source, IndexList indices_of_snps_to_include ) ;
 
 		operator bool() const ;
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 		OptionalSnpCount total_number_of_snps() const ;
 		OptionalSnpCount total_number_of_snps_before_filtering() const ;
 		std::string get_source_spec() const ;
 

DELETED genfile/include/genfile/SNPIdentifyingDataFilteringSNPDataSource.hpp
Index: genfile/include/genfile/SNPIdentifyingDataFilteringSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/SNPIdentifyingDataFilteringSNPDataSource.hpp
+++ genfile/include/genfile/SNPIdentifyingDataFilteringSNPDataSource.hpp
@@ -1,73 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef GENFILE_SNPIDENTIFYINGDATAFILTERINGSNPDATASOURCE_HPP
-#define GENFILE_SNPIDENTIFYINGDATAFILTERINGSNPDATASOURCE_HPP
-
-#include <vector>
-#include <set>
-#include <memory>
-#include <boost/signals2/signal.hpp>
-#include "genfile/Error.hpp"
-#include "genfile/SNPDataSource.hpp"
-#include "genfile/VariantIdentifyingDataTest.hpp"
-#include "genfile/CommonSNPFilter.hpp"
-
-namespace genfile {
-	// class VariantIdentifyingDataFilteringSNPDataSource
-	// This class represents a view of its parent SNPDataSource such that
-	// only SNPs whose chromosome, position, id fields and alleles satisfy the
-	// given test are visible.
-	class VariantIdentifyingDataFilteringSNPDataSource: public SNPDataSource
-	{
-	public:
-		typedef std::auto_ptr< VariantIdentifyingDataFilteringSNPDataSource > UniquePtr ;
-		// Create a VariantIdentifyingDataFilteringSNPDataSource from the given source and the given test.
-		// The test should return true for tests that are in and false for those excluded.
-		static UniquePtr create( SNPDataSource::UniquePtr source, VariantIdentifyingDataTest::UniquePtr test ) ;
-		static UniquePtr create( SNPDataSource::UniquePtr source, VariantIdentifyingDataTest const& test ) ;
-		
-	public:
-		~VariantIdentifyingDataFilteringSNPDataSource() ;
-		VariantIdentifyingDataFilteringSNPDataSource( SNPDataSource::UniquePtr source, VariantIdentifyingDataTest::UniquePtr test ) ;
-		VariantIdentifyingDataFilteringSNPDataSource( SNPDataSource::UniquePtr source, VariantIdentifyingDataTest const& test ) ;
-
-		operator bool() const ;
-		Metadata get_metadata() const ;
-		unsigned int number_of_samples() const ;
-		void get_sample_ids( GetSampleIds ) const ;
-		OptionalSnpCount total_number_of_snps() const ;
-		std::string get_source_spec() const ;
-
-		SNPDataSource const& get_parent_source() const ;
-		SNPDataSource const& get_base_source() const ;
-		
-		typedef boost::signals2::signal< void ( VariantIdentifyingData const& ) > SNPSignal ;
-		void send_filtered_out_SNPs_to( SNPSignal::slot_type ) ;
-
-	private:
-		void reset_to_start_impl() ;
-
-		void get_snp_identifying_data_impl( 
-VariantIdentifyingData* variant		) ;
-
-		VariantDataReader::UniquePtr read_variant_data_impl() ;
-
-		void ignore_snp_probability_data_impl() ;
-
-	protected:
-		SNPDataSource& source() { return *m_source ; }
-		
-	private:
-		
-		SNPDataSource::UniquePtr m_source ;
-		bool const m_manage_test ;
-		VariantIdentifyingDataTest const* m_test ;
-		SNPSignal m_filtered_out_snp_signal ;
-	} ;
-}
-
-#endif

Index: genfile/include/genfile/SNPTranslatingSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/SNPTranslatingSNPDataSource.hpp
+++ genfile/include/genfile/SNPTranslatingSNPDataSource.hpp
@@ -42,10 +42,18 @@
 		}
 		
 		unsigned int number_of_samples() const {
 			return m_source->number_of_samples() ;
 		}
+
+		bool has_sample_ids() const {
+			return m_source->has_sample_ids() ;
+		}
+
+		void get_sample_ids( GetSampleIds callback ) const {
+			return m_source->get_sample_ids( callback ) ;
+		}
 
 		OptionalSnpCount total_number_of_snps() const {
 			return m_source->total_number_of_snps() ;
 		}
 

Index: genfile/include/genfile/SampleFilteringSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/SampleFilteringSNPDataSource.hpp
+++ genfile/include/genfile/SampleFilteringSNPDataSource.hpp
@@ -33,10 +33,11 @@
 	public:
 
 		operator bool() const ;
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 		OptionalSnpCount total_number_of_snps() const ;
 		std::string get_source_spec() const ;
 		
 		SNPDataSource const& get_parent_source() const ;

Index: genfile/include/genfile/SampleMappingSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/SampleMappingSNPDataSource.hpp
+++ genfile/include/genfile/SampleMappingSNPDataSource.hpp
@@ -28,10 +28,11 @@
 		) ;
 
 		operator bool() const ;
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 		OptionalSnpCount total_number_of_snps() const ;
 		std::string get_source_spec() const ;
 		SNPDataSource const& get_parent_source() const ;
 

Index: genfile/include/genfile/SampleRange.hpp
==================================================================
--- genfile/include/genfile/SampleRange.hpp
+++ genfile/include/genfile/SampleRange.hpp
@@ -6,10 +6,11 @@
 
 #ifndef GENFILE_SAMPLE_RANGE_HPP
 #define GENFILE_SAMPLE_RANGE_HPP
 
 #include <iostream>
+#include <vector>
 
 namespace genfile {
 	struct SampleRange {
 		SampleRange() ;
 		SampleRange( SampleRange const& other ) ;
@@ -27,8 +28,9 @@
 	
 	bool operator== ( SampleRange const& left, SampleRange const& right ) ;
 	bool operator< ( SampleRange const& left, SampleRange const& right ) ;
 	
 	std::ostream& operator<<( std::ostream& out, SampleRange const& range ) ;
+	std::ostream& operator<<( std::ostream& out, std::vector< SampleRange > const& range ) ;
 }
 
 #endif

Index: genfile/include/genfile/ShapeITHaplotypesSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/ShapeITHaplotypesSNPDataSource.hpp
+++ genfile/include/genfile/ShapeITHaplotypesSNPDataSource.hpp
@@ -22,10 +22,11 @@
 		ShapeITHaplotypesSNPDataSource( std::string const& haplotypes_filename, Chromosome chromosome, CompressionType compression_type ) ;
 
 		Metadata get_metadata() const ;
 
 		unsigned int number_of_samples() const { return m_number_of_samples ; }
+		bool has_sample_ids() const { return false ; }
 		OptionalSnpCount total_number_of_snps() const { return OptionalSnpCount() ; }
 		
 		operator bool() const { return m_good ; }
 		std::istream& stream() { return *m_stream_ptr ; }
 		std::istream const& stream() const { return *m_stream_ptr ; }

Index: genfile/include/genfile/StrandAligningSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/StrandAligningSNPDataSource.hpp
+++ genfile/include/genfile/StrandAligningSNPDataSource.hpp
@@ -73,10 +73,11 @@
 		
 	public:
 		operator bool() const { return *m_source ; }
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const { return m_source->number_of_samples() ; }
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 		OptionalSnpCount total_number_of_snps() const { return m_source->total_number_of_snps() ; }
 		std::string get_source_spec() const { return "strand-aligned:" + m_source->get_source_spec() ; }
 		SNPDataSource const& get_parent_source() const {
 			return *m_source ;

Index: genfile/include/genfile/ThreshholdingSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/ThreshholdingSNPDataSource.hpp
+++ genfile/include/genfile/ThreshholdingSNPDataSource.hpp
@@ -23,10 +23,11 @@
 	public:
 		ThreshholdingSNPDataSource( SNPDataSource::UniquePtr source, double const threshhold ) ;
 		operator bool() const ;
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 		OptionalSnpCount total_number_of_snps() const ;
 		std::string get_source_spec() const ;
 		SNPDataSource const& get_parent_source() const ;
 		SNPDataSource const& get_base_source() const ;

Index: genfile/include/genfile/ToGP.hpp
==================================================================
--- genfile/include/genfile/ToGP.hpp
+++ genfile/include/genfile/ToGP.hpp
@@ -231,11 +231,12 @@
 #if DEBUG_TO_GP
 				std::cerr << "count = " << count << ", call is ./././.\n" ;
 #endif
 				
 				for( std::size_t i = 0 ; i < count; ++i ) {
-					m_setter->set_value( i, 0.0 ) ;
+					//m_setter->set_value( i, 0.0 ) ;
+					m_setter->set_value( i, genfile::MissingValue() ) ;
 				}
 			} else {
 				std::size_t index_of_nonzero_probability = m_tables[ m_ploidy ].second[ m_encoded_call ] ;
 #if DEBUG_TO_GP
 				std::cerr << "count = " << count << ", call is: " << impl::format_call( m_encoded_call, m_tables[ m_ploidy ].first ) ;

Index: genfile/include/genfile/VCFFormatSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/VCFFormatSNPDataSource.hpp
+++ genfile/include/genfile/VCFFormatSNPDataSource.hpp
@@ -44,10 +44,11 @@
 		) ;
 	public:
 		operator bool() const ;
 		Metadata get_metadata() const ;
 		unsigned int number_of_samples() const ;
+		bool has_sample_ids() const ;
 		void get_sample_ids( GetSampleIds ) const ;
 
 		OptionalSnpCount total_number_of_snps() const ;
 		std::string get_source_spec() const ;
 		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;

Index: genfile/include/genfile/VariantEntry.hpp
==================================================================
--- genfile/include/genfile/VariantEntry.hpp
+++ genfile/include/genfile/VariantEntry.hpp
@@ -32,10 +32,15 @@
 
 		template< typename Visitor >
 		friend void apply_visitor( Visitor visitor, VariantEntry const& ) ;
 		template< typename Visitor >
 		friend void apply_visitor( Visitor visitor, VariantEntry& ) ;
+
+	public:
+		// unordered container support
+		friend std::size_t hash_value( VariantEntry const& key ) ;
+
 	public:
 		bool operator==( VariantEntry const& rhs ) const ;
 		bool operator!=( VariantEntry const& rhs ) const ;
 		bool operator<( VariantEntry const& rhs ) const ;
 		bool operator<=( VariantEntry const& rhs ) const ;
@@ -85,8 +90,37 @@
 	template< typename Visitor >
 	void apply_visitor( Visitor visitor, VariantEntry& value ) {
 		return boost::apply_visitor( visitor, value.m_entrydata ) ;
 		
 	}
+	
+	inline std::size_t hash_value( VariantEntry const& key ) {
+		return boost::hash_value( key.m_entrydata ) ;
+	}
+
+	inline bool VariantEntry::operator==( VariantEntry const& rhs ) const {
+		return m_entrydata == rhs.m_entrydata ;
+	}
+
+	inline bool VariantEntry::operator!=( VariantEntry const& rhs ) const {
+		return !( m_entrydata == rhs.m_entrydata ) ;
+	}
+	
+	inline bool VariantEntry::operator<( VariantEntry const& rhs ) const {
+		return m_entrydata < rhs.m_entrydata ;
+	}
+
+	inline bool VariantEntry::operator<=( VariantEntry const& rhs ) const {
+		return m_entrydata < rhs.m_entrydata || m_entrydata == rhs.m_entrydata ;
+	}
+
+	inline bool VariantEntry::operator>( VariantEntry const& rhs ) const {
+		return !( m_entrydata < rhs.m_entrydata ) && !( m_entrydata == rhs.m_entrydata ) ;
+	}
+
+	inline bool VariantEntry::operator>=( VariantEntry const& rhs ) const {
+		return !( m_entrydata < rhs.m_entrydata ) ;
+	}
+	
 }
 
 #endif

ADDED   genfile/include/genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp
Index: genfile/include/genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp
==================================================================
--- genfile/include/genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp
+++ genfile/include/genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp
@@ -0,0 +1,74 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_SNPIDENTIFYINGDATAFILTERINGSNPDATASOURCE_HPP
+#define GENFILE_SNPIDENTIFYINGDATAFILTERINGSNPDATASOURCE_HPP
+
+#include <vector>
+#include <set>
+#include <memory>
+#include <boost/signals2/signal.hpp>
+#include "genfile/Error.hpp"
+#include "genfile/SNPDataSource.hpp"
+#include "genfile/VariantIdentifyingDataTest.hpp"
+#include "genfile/CommonSNPFilter.hpp"
+
+namespace genfile {
+	// class VariantIdentifyingDataFilteringSNPDataSource
+	// This class represents a view of its parent SNPDataSource such that
+	// only SNPs whose chromosome, position, id fields and alleles satisfy the
+	// given test are visible.
+	class VariantIdentifyingDataFilteringSNPDataSource: public SNPDataSource
+	{
+	public:
+		typedef std::auto_ptr< VariantIdentifyingDataFilteringSNPDataSource > UniquePtr ;
+		// Create a VariantIdentifyingDataFilteringSNPDataSource from the given source and the given test.
+		// The test should return true for tests that are in and false for those excluded.
+		static UniquePtr create( SNPDataSource::UniquePtr source, VariantIdentifyingDataTest::UniquePtr test ) ;
+		static UniquePtr create( SNPDataSource::UniquePtr source, VariantIdentifyingDataTest const& test ) ;
+		
+	public:
+		~VariantIdentifyingDataFilteringSNPDataSource() ;
+		VariantIdentifyingDataFilteringSNPDataSource( SNPDataSource::UniquePtr source, VariantIdentifyingDataTest::UniquePtr test ) ;
+		VariantIdentifyingDataFilteringSNPDataSource( SNPDataSource::UniquePtr source, VariantIdentifyingDataTest const& test ) ;
+
+		operator bool() const ;
+		Metadata get_metadata() const ;
+		unsigned int number_of_samples() const ;
+		virtual bool has_sample_ids() const ;
+		void get_sample_ids( GetSampleIds ) const ;
+		OptionalSnpCount total_number_of_snps() const ;
+		std::string get_source_spec() const ;
+
+		SNPDataSource const& get_parent_source() const ;
+		SNPDataSource const& get_base_source() const ;
+		
+		typedef boost::signals2::signal< void ( VariantIdentifyingData const& ) > SNPSignal ;
+		void send_filtered_out_SNPs_to( SNPSignal::slot_type ) ;
+
+	private:
+		void reset_to_start_impl() ;
+
+		void get_snp_identifying_data_impl( 
+VariantIdentifyingData* variant		) ;
+
+		VariantDataReader::UniquePtr read_variant_data_impl() ;
+
+		void ignore_snp_probability_data_impl() ;
+
+	protected:
+		SNPDataSource& source() { return *m_source ; }
+		
+	private:
+		
+		SNPDataSource::UniquePtr m_source ;
+		bool const m_manage_test ;
+		VariantIdentifyingDataTest const* m_test ;
+		SNPSignal m_filtered_out_snp_signal ;
+	} ;
+}
+
+#endif

ADDED   genfile/include/genfile/bgen/IndexQuery.hpp
Index: genfile/include/genfile/bgen/IndexQuery.hpp
==================================================================
--- genfile/include/genfile/bgen/IndexQuery.hpp
+++ genfile/include/genfile/bgen/IndexQuery.hpp
@@ -0,0 +1,130 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BGEN_INDEX_QUERY_HPP
+#define BGEN_INDEX_QUERY_HPP
+
+#include <boost/function.hpp>
+#include <boost/optional.hpp>
+#include <stdint.h>
+#include <vector>
+#include <string>
+#include <ctime>
+#include "genfile/db/sqlite3.hpp"
+#include "genfile/bgen/Query.hpp"
+
+namespace genfile {
+	namespace bgen {
+		// Base class representing a query against a BGEN file index
+		struct IndexQuery {
+		public:
+			// We use std::auto_ptr to avoid using C++11 features here.
+			typedef std::auto_ptr< IndexQuery > UniquePtr ;
+			typedef uint8_t byte_t ;
+			typedef boost::function< void ( std::size_t n, boost::optional< std::size_t > total ) > ProgressCallback ;
+			struct FileMetadata ;
+			typedef boost::optional< FileMetadata > OptionalFileMetadata ;
+			typedef Query::GenomicRange GenomicRange ;
+			typedef std::pair< int64_t, int64_t> FileRange ;
+
+		public:
+			static UniquePtr create(
+				std::string const& filename,
+				Query const& query,
+				ProgressCallback callback = ProgressCallback(),
+				std::string const& table_name = "Variant"
+			) ;
+
+		public:
+			virtual ~IndexQuery() {} ;
+			virtual OptionalFileMetadata const& file_metadata() const = 0 ;
+
+		public:
+			// Report the number of variants in this query.
+			virtual std::size_t number_of_variants() const = 0 ;
+			// Report the number of variants in this query.
+			virtual FileRange locate_variant( std::size_t index ) const = 0 ;
+
+			struct FileMetadata {
+				FileMetadata():
+					size(-1)
+				{}
+
+				FileMetadata( FileMetadata const& other ):
+					filename( other.filename ),
+					size( other.size ),
+					last_write_time( other.last_write_time ),
+					first_bytes( other.first_bytes )
+				{}
+
+				FileMetadata& operator=( FileMetadata const& other ) {
+					filename = other.filename ;
+					size = other.size ;
+					last_write_time = other.last_write_time ;
+					first_bytes = other.first_bytes ;
+					return *this ;
+				}
+
+				std::string filename ;
+				int64_t size ;
+				std::time_t last_write_time ;
+				std::vector< byte_t > first_bytes ;
+			} ;
+		} ;
+		
+		// Class for index queries implemented using a sqlite file, a la bgenix.
+		struct SqliteIndexQuery: public IndexQuery {
+		public:
+			// We use auto_ptr to avoid using C++11 features here.
+			typedef std::auto_ptr< SqliteIndexQuery > UniquePtr ;
+
+		public:
+			SqliteIndexQuery( std::string const& filename, Query const& query, ProgressCallback callback = ProgressCallback(), std::string const& table_name = "Variant" ) ;
+			OptionalFileMetadata const& file_metadata() const ;
+			std::size_t number_of_variants() const ;
+			FileRange locate_variant( std::size_t index ) const ;
+
+		private:
+			db::Connection::UniquePtr open_connection( std::string const& filename ) const ;
+			OptionalFileMetadata load_metadata( db::Connection& connection ) const ;
+			db::Connection::StatementPtr build_query() const ;
+
+			// Implement the specified query.
+			void implement_query( Query const& query, ProgressCallback callback = ProgressCallback() ) ;
+			// Internal query implementation methods
+			// Include variants in a range
+			SqliteIndexQuery& include_range( GenomicRange const& range ) ;
+			// Exclude variants in a range
+			SqliteIndexQuery& exclude_range( GenomicRange const& range ) ;
+			// Include variants in a range
+			SqliteIndexQuery& include_ranges( std::vector< GenomicRange > const& ranges ) ;
+			// Exclude variants in a range
+			SqliteIndexQuery& exclude_ranges( std::vector< GenomicRange > const& ranges ) ;
+			// Include variants with one of the given rsids.  The list provided must be unique.
+			SqliteIndexQuery& include_rsids( std::vector< std::string > const& ids ) ;
+			// Exclude variants with one of the given rsids.  The list provided must be unique.
+			SqliteIndexQuery& exclude_rsids( std::vector< std::string > const& ids ) ;
+			// Initialise query with the above
+			void initialise( ProgressCallback callback = ProgressCallback() ) ;
+
+		private:
+			db::Connection::UniquePtr m_connection ;
+			OptionalFileMetadata const m_metadata ;
+			std::string const m_index_table_name ;
+			struct QueryParts {
+				std::string join ;
+				std::string inclusion ;
+				std::string exclusion ;
+			} ;
+			QueryParts m_query_parts ;
+			bool m_initialised ;
+			std::vector< std::pair< int64_t, int64_t> > m_positions ;
+		} ;
+		
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/bgen/Query.hpp
Index: genfile/include/genfile/bgen/Query.hpp
==================================================================
--- genfile/include/genfile/bgen/Query.hpp
+++ genfile/include/genfile/bgen/Query.hpp
@@ -0,0 +1,90 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BGEN_QUERY_HPP
+#define BGEN_QUERY_HPP
+
+#include <boost/function.hpp>
+#include <boost/optional.hpp>
+#include <stdint.h>
+#include <vector>
+#include <string>
+
+namespace genfile {
+	namespace bgen {
+		// Base class representing a query against a BGEN file or index
+		struct Query {
+		public:
+			// We use std::auto_ptr to avoid using C++11 features here.
+			typedef uint8_t byte_t ;
+			typedef std::auto_ptr< Query > UniquePtr ;
+			
+			static UniquePtr create() ;
+
+		public:
+			struct GenomicRange {
+				GenomicRange(): m_start(0), m_end(0) {}
+				GenomicRange( GenomicRange const& other ):
+					m_chromosome( other.m_chromosome ),
+					m_start( other.m_start ),
+					m_end( other.m_end )
+				{}
+					
+				GenomicRange& operator=( GenomicRange const& other ) {
+					m_chromosome = other.m_chromosome ;
+					m_start = other.m_start ;
+					m_end = other.m_end ;
+					return *this ;
+				}
+				GenomicRange(
+					std::string const& chromosome,
+					uint32_t start,
+					uint32_t end
+				):
+					m_chromosome( chromosome ),
+					m_start( start ),
+					m_end( end )
+				{
+					if( m_end < m_start ) {
+						throw std::invalid_argument( "end" ) ;
+					}
+				}
+
+				std::string const& chromosome() const { return m_chromosome ; }
+				uint32_t const& start() const { return m_start ; }
+				uint32_t const& end() const { return m_end ; }
+				
+			private:
+				std::string m_chromosome ;
+				uint32_t m_start ;
+				uint32_t m_end ;
+			} ;
+
+		public:
+			// Methods for building queries
+			// Each method returns this object, allowing methods to be chained
+			Query& include_range( GenomicRange const& range ) ;
+			Query& exclude_range( GenomicRange const& range ) ;
+			Query& include_ranges( std::vector< GenomicRange > const& ranges ) ;
+			Query& exclude_ranges( std::vector< GenomicRange > const& ranges ) ;
+			Query& include_rsids( std::vector< std::string > const& ids ) ;
+			Query& exclude_rsids( std::vector< std::string > const& ids ) ;
+			
+			std::vector< std::string > const& included_rsids() const { return m_included_rsids ; }
+			std::vector< std::string > const& excluded_rsids() const { return m_excluded_rsids ; }
+			std::vector< GenomicRange > const& included_ranges() const { return m_included_ranges ; }
+			std::vector< GenomicRange > const& excluded_ranges() const { return m_excluded_ranges ; }
+			
+		private:
+			std::vector< std::string > m_included_rsids ;
+			std::vector< std::string > m_excluded_rsids ;
+			std::vector< GenomicRange > m_included_ranges ;
+			std::vector< GenomicRange > m_excluded_ranges ;
+		} ;
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/bgen/View.hpp
Index: genfile/include/genfile/bgen/View.hpp
==================================================================
--- genfile/include/genfile/bgen/View.hpp
+++ genfile/include/genfile/bgen/View.hpp
@@ -0,0 +1,162 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_BGEN_READVIEW_HPP
+#define GENFILE_BGEN_READVIEW_HPP
+
+#include <memory>
+#include <vector>
+#include <string>
+#include <iostream>
+#include <sstream>
+#include "genfile/bgen/bgen.hpp"
+#include "genfile/bgen/Query.hpp"
+#include "genfile/bgen/IndexQuery.hpp"
+
+namespace {
+	std::string to_string( std::size_t i ) {
+		std::stringstream s ;
+		s << i ;
+		return s.str() ;
+	}
+}
+
+namespace genfile {
+	namespace bgen {
+		struct View {
+		public:
+			typedef std::auto_ptr< View > UniquePtr ;
+			typedef genfile::bgen::IndexQuery IndexQuery ;
+			typedef genfile::bgen::IndexQuery::FileMetadata FileMetadata ;
+
+			static UniquePtr create( std::string const& filename ) ;
+
+		public:
+			View( std::string const& filename ) ;
+
+			// Restrict this reader to a set of variants specified by the given query
+			void set_query( Query const& query ) ;
+
+			// Report high-level information about the file
+			uint32_t number_of_variants() const ;
+			std::size_t number_of_samples() const ;
+			std::ostream& summarise( std::ostream& o ) const ;
+
+			// Report the sample IDs in the file using the given setter object
+			// (If there are no sample IDs in the file, report a dummy identifier).
+			// Setter object must be callable as setter( index of sample, sample identifier ).
+			template< typename Setter >
+			void get_sample_ids( Setter setter ) const {
+				if( m_have_sample_ids ) {
+					for( std::size_t i = 0; i < m_context.number_of_samples; ++i ) {
+						setter( m_sample_ids[i] ) ;
+					}
+				} else {
+					for( std::size_t i = 0; i < m_context.number_of_samples; ++i ) {
+						setter( "(anonymous_sample_" + to_string( i+1 ) + ")" ) ;
+					}
+				}
+			}
+
+			// Report low-level information about the file.
+			genfile::bgen::Context const& context() const ;
+			FileMetadata const& file_metadata() const ;
+			std::streampos current_file_position() const ;
+
+			// Attempt to read identifying information about the next available variant from the
+			// returning data in the given fields.
+			// If this method returns true, data was successfully read, and it should be safe to call
+			// read_genotype_data_block(), ignore_genotype_data_block(), or read_and_unpack_v12_genotype_data_block().
+			// If this method returns false, data could not be read indicating end of the file.
+			bool read_variant(
+				std::string* SNPID,
+				std::string* rsid,
+				std::string* chromosome,
+				uint32_t* position,
+				std::vector< std::string >* alleles
+			) ;
+
+			// Read, uncompress, and parse genotype probability data for the variant just read by read_variant().
+			// Data is returned via a setter object, using the parse_genotype_data API documented on the wiki.
+			// An example using this API is found in the bgen_to_vcf.cpp example program.
+			template< typename ProbSetter >
+			void read_genotype_data_block( ProbSetter& setter ) {
+				assert( m_state == e_ReadyForProbs ) ;
+				genfile::bgen::read_and_parse_genotype_data_block< ProbSetter >(
+					*m_stream,
+					m_context,
+					setter,
+					&m_buffer1,
+					&m_buffer2
+				) ;
+				m_file_position = m_stream->tellg() ;
+				m_state = e_ReadyForVariant ;
+				++m_variant_i ;
+			}
+	
+			// Read, uncompress, and unpack data for the variant just read by read_variant()
+			// without doing a full parse of all the probability data.
+			// This method is useful for applications that want to manipulate the bgen-formatted
+			// data directly, e.g. for efficiency reasons.
+			// Currently this function works for 'layout=2' files, e.g. v1.2 and above only.
+			// The function will assert() if the data is not in this format.
+			// Data is returned in the fields of the supplied 'pack' object.  See bgen.hpp for the
+			// declaration of this object.
+			void read_and_unpack_v12_genotype_data_block(
+				genfile::bgen::v12::GenotypeDataBlock* pack
+			) ;
+
+			// Skip over (i.e. ignore) genotype probability data for the current variant.
+			void ignore_genotype_data_block() ;
+
+		private:
+			// Open the bgen file, read header data and gather metadata.
+			void setup( std::string const& filename ) ;
+
+			// Utility function to read and uncompress variant genotype probability data
+			// without further processing.
+			std::vector< byte_t > const& read_and_uncompress_genotype_data_block() ;
+
+		private:
+			std::string const m_filename ;
+			std::auto_ptr< std::istream > m_stream ;
+			std::size_t m_variant_i ;
+			IndexQuery::UniquePtr m_index_query ;
+
+			// meta data used to avoid stale index files.
+			FileMetadata m_file_metadata ;
+
+			// offset byte from top of bgen file.
+			uint32_t m_offset ;
+
+			// bgen::Context object holds information from the header block,
+			// including bgen flags
+			genfile::bgen::Context m_context ;
+	
+			bool m_have_sample_ids ;
+			std::vector< std::string > m_sample_ids ;
+
+			// All data following header up to the first variant data block.
+			std::vector< byte_t > m_postheader_data ;
+
+			// We keep track of our state in the file.
+			// This is not strictly necessary for this implentation but makes it clear that
+			// the sequence of calls must be read_variant() followed by
+			// ignore_genotype_data_block() or ignore_genotype_data_block() repeatedly.
+			enum State { e_NotOpen = 0, e_Open = 1, e_ReadyForVariant = 2, e_ReadyForProbs = 3, eComplete = 4 } ;
+			State m_state ;
+	
+			// To avoid issues with tellg() and failbit, we store the stream position at suitable points
+			std::streampos m_file_position ;
+	
+			// Two buffers for processing
+			std::vector< byte_t > m_buffer1 ;
+			std::vector< byte_t > m_buffer2 ;
+		} ;
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/db/Connection.hpp
Index: genfile/include/genfile/db/Connection.hpp
==================================================================
--- genfile/include/genfile/db/Connection.hpp
+++ genfile/include/genfile/db/Connection.hpp
@@ -0,0 +1,43 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_CONNECTION_HPP
+#define GENFILE_DB_CONNECTION_HPP
+
+#include <memory>
+#include <string>
+#include <stdint.h>
+#include "genfile/db/Transaction.hpp"
+
+namespace genfile {
+	namespace db {
+
+		class SQLStatement ;
+	
+		class Connection
+			// Base class for classes representing a connection to a database.
+			// The only supported operation is getting a query representing some SQL.
+		{
+		public:
+			typedef std::auto_ptr< Connection > UniquePtr ;
+			typedef std::auto_ptr< SQLStatement > StatementPtr ;
+		
+			static UniquePtr create( std::string const& filename, std::string const& mode = "rw" ) ;
+		
+			virtual ~Connection() {}
+
+			virtual StatementPtr get_statement( std::string const& SQL ) = 0 ;
+			virtual void run_statement( std::string const& SQL ) ;
+			virtual std::string get_spec() const = 0 ;
+			typedef int64_t RowId ;
+			virtual RowId get_last_insert_row_id() const = 0 ;
+			typedef Transaction::UniquePtr ScopedTransactionPtr ;
+			virtual ScopedTransactionPtr open_transaction( double max_seconds_to_wait = 0.1 ) = 0 ;
+		} ;	
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/db/Error.hpp
Index: genfile/include/genfile/db/Error.hpp
==================================================================
--- genfile/include/genfile/db/Error.hpp
+++ genfile/include/genfile/db/Error.hpp
@@ -0,0 +1,75 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_SQL_ERROR_HPP
+#define GENFILE_DB_SQL_ERROR_HPP
+
+#include <string>
+#include <exception>
+
+namespace genfile {
+	namespace db {
+		struct Error: public std::exception
+		{
+			Error( std::string const& caller, std::string const& db_spec, int error, std::string const& sql = "(unknown)" ) ;
+			~Error() throw() ;
+			char const* what() const throw() { return "db::Error" ; }
+
+			int const& error_code() const { return m_error ; }
+			std::string const& spec() const { return m_spec ; }
+			std::string description() const ;
+			std::string sql() const { return m_sql ; }
+		private:
+			std::string const m_caller ;
+			std::string const m_spec ;
+			int const m_error ;
+			std::string const m_sql ;
+		} ;
+	
+		struct ConnectionError: public Error
+		{
+			ConnectionError( std::string const& caller, std::string const& db_spec, int error_code ): Error( caller, db_spec, error_code ) {}
+			char const* what() const throw() { return "db::ConnectionError" ; }
+		} ;
+
+		struct TransactionError: public Error
+		{
+			TransactionError( std::string const& caller, std::string const& db_spec, int error_code, std::string const& sql = "(unknown)" ): Error( caller, db_spec, error_code, sql ) {}
+			char const* what() const throw() { return "db::TransactionError" ; }
+		} ;
+
+		struct StatementPreparationError: public Error
+		{
+			StatementPreparationError( std::string const& caller, std::string const& db_spec, int error_code, std::string const& sql = "(unknown)" ): Error( caller, db_spec, error_code, sql ) {}
+			~StatementPreparationError() throw() {}
+			char const* what() const throw() { return "db::StatementPreparationError" ; }
+		} ;
+
+		struct StatementStepError: public Error
+		{
+			StatementStepError( std::string const& caller, std::string const& db_spec, int error_code, std::string const& sql = "(unknown)" ): Error( caller, db_spec, error_code, sql ) {}
+			char const* what() const throw() { return "db::StatementStepError" ; }
+		} ;
+
+		struct ValueBindError: public Error
+		{
+			~ValueBindError() throw() {}
+			ValueBindError(
+				std::string const& caller,
+				std::string const& db_spec,
+				int error_code,
+				std::string const& slot
+			): Error( caller, db_spec, error_code ), m_slot( slot ) {}
+			char const* what() const throw() { return "db::StatementStepError" ; }
+			std::string const& slot() const { return m_slot ; }
+		private:
+			std::string const m_slot ;
+		} ;
+	
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/db/SQLStatement.hpp
Index: genfile/include/genfile/db/SQLStatement.hpp
==================================================================
--- genfile/include/genfile/db/SQLStatement.hpp
+++ genfile/include/genfile/db/SQLStatement.hpp
@@ -0,0 +1,103 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_SQL_STATEMENT_HPP
+#define GENFILE_DB_SQL_STATEMENT_HPP
+
+#include <cassert>
+#include <string>
+#include <vector>
+#include <exception>
+#include <stdint.h>
+#include "sqlite3/sqlite3.h"
+#include "genfile/db/SQLite3Connection.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/string_utils/slice.hpp"
+
+namespace genfile {
+	namespace db {
+	
+		struct SQLError: public std::exception
+		{
+			virtual ~SQLError() throw() {}
+			char const* what() const throw() { return "db::SQLError" ; }
+			virtual std::string description() const = 0 ;
+		} ;
+	
+		class SQLStatement
+		{
+		public:
+			typedef std::auto_ptr< SQLStatement > UniquePtr ;
+		public:
+			virtual ~SQLStatement() ;
+		
+			// Step to the next result row.  The entries can be accessed using get_column().
+			// Return false if there is no next row, otherwise true.
+			virtual bool step() = 0 ;
+			// Return 
+			virtual bool empty() const = 0 ;
+		
+			// Get the result for the given column.
+			// Columns are 0-indexed.
+			template< typename T > T get_column( int column_id ) const ;
+			template< typename T > T get( int column_id ) const { return get_column< T >( column_id ) ; }
+			virtual bool is_null( int column_id ) const = 0 ;
+
+			virtual std::size_t get_number_of_columns() const = 0 ;
+			virtual std::string get_name_of_column( std::size_t i ) const = 0 ;
+
+			// For parameterised queries, bind an integer value to the ith placeholder.
+			// Placeholders are indexed starting from 1 on the left.
+			// Named placeholders with the same name have the same index.
+			virtual SQLStatement& bind( std::size_t i, int32_t value ) = 0 ;
+			virtual SQLStatement& bind( std::size_t i, uint32_t value ) = 0 ;
+			virtual SQLStatement& bind( std::size_t i, int64_t value ) = 0 ;
+			virtual SQLStatement& bind( std::size_t i, uint64_t value ) = 0 ;
+			virtual SQLStatement& bind( std::size_t i, double value ) = 0 ;
+			// For parameterised queries, bind a string value to the ith placeholder.
+			// Placeholders are indexed starting from 1 on the left.
+			// Named placeholders with the same name have the same index.
+			// The string will be copied so the caller need not preserve it beyond the call site.
+			virtual SQLStatement& bind( std::size_t i, std::string const& value ) = 0 ;
+			SQLStatement& bind( std::size_t i, char const* value ) ;
+			SQLStatement& bind( std::size_t i, genfile::string_utils::slice const& value ) ;
+			// For parameterised queries, bind a BLOB value (array of chars) to the ith placeholder.
+			// Placeholders are indexed starting from 1 on the left.
+			// Named placeholders with the same name have the same index.
+			// The data will not be copied and so the caller must preserve the data until
+			// such time as no further steps() are performed, or the parameter is re-bound.
+			virtual SQLStatement& bind( std::size_t i, char const* buffer, char const* const end ) = 0 ;
+			virtual SQLStatement& bind( std::size_t i, uint8_t const* buffer, uint8_t const* const end ) = 0 ;
+
+			// bind NULL to a parameter
+			virtual SQLStatement& bind_NULL( std::size_t i ) = 0 ;
+
+			// Bind a genfile::VariantEntry
+			SQLStatement& bind( std::size_t, genfile::VariantEntry const& value ) ;
+
+			// Reset the statement, ready to be re-executed.
+			virtual SQLStatement& reset() = 0 ;
+		
+			// Return the SQL this statement contains.
+			virtual std::string get_sql() const = 0 ;
+		
+		protected:
+			virtual int get_column_int( int column_id ) const = 0 ;
+			virtual int64_t get_column_int64( int column_id ) const = 0 ;
+			virtual double get_column_double( int column_id ) const = 0 ;
+			virtual std::string get_column_string( int column_id ) const = 0 ;
+			virtual char get_column_char( int column_id ) const = 0 ;
+			virtual std::vector< uint8_t > get_column_blob( int column_id ) const = 0 ;
+		} ;
+	
+		template<> int SQLStatement::get_column< int >( int column_id ) const ;
+		template<> int64_t SQLStatement::get_column< int64_t >( int column_id ) const ;
+		template<> double SQLStatement::get_column< double >( int column_id ) const ;
+		template<> std::string SQLStatement::get_column< std::string >( int column_id ) const ;
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/db/SQLite3Connection.hpp
Index: genfile/include/genfile/db/SQLite3Connection.hpp
==================================================================
--- genfile/include/genfile/db/SQLite3Connection.hpp
+++ genfile/include/genfile/db/SQLite3Connection.hpp
@@ -0,0 +1,70 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_SQLITE3_CONNECTOR_HPP
+#define GENFILE_SQLITE3_CONNECTOR_HPP
+
+#include <cassert>
+#include <string>
+#include <exception>
+#include "sqlite3/sqlite3.h"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/Transaction.hpp"
+#include "genfile/db/Error.hpp"
+
+extern "C" {
+	void sqlite3_trace_callback( void* udp, const char* sql ) ;
+	int sqlite3_busy_callback( void*, int number_of_tries ) ;
+}
+
+namespace genfile {
+	namespace db {
+		class SQLite3Connection: public Connection
+		{
+		public:
+			// Open a connection to an on-disk database.
+			// If the filename is ":memory:", open instead a connection
+			// to a new private in-memory DB.
+			SQLite3Connection( std::string const& filename, bool overwrite = true, std::string const& mode = "rw" ) ;
+			virtual ~SQLite3Connection() ;
+
+		public:
+
+			StatementPtr get_statement( std::string const& SQL ) ;
+			RowId get_last_insert_row_id() const ;
+
+		public:
+			sqlite3_stmt* prepare_sql( std::string const& SQL ) const ;
+			int finalise_statement( sqlite3_stmt* statement ) ;
+			int step_statement( sqlite3_stmt* statement ) ;
+	
+			std::string get_spec() const {
+				return m_filename ;
+			}
+
+		private:
+			struct Transaction: public db::Transaction {
+				Transaction( SQLite3Connection& connection ) ;
+				~Transaction() ;
+			private:
+				SQLite3Connection& m_connection ;
+			} ;
+		public:
+			ScopedTransactionPtr open_transaction( double max_seconds_to_wait = 0.1 ) ;
+		private:
+			std::string m_filename ;
+			sqlite3* m_db_connection ;
+			bool m_managed ;
+
+		private:
+			void open_db_connection( std::string const& filename, bool overwrite, std::string const& mode = "rw" ) ;
+			void close_db_connection_if_necessary() ;
+			void finalise_prepared_statements() ;
+		} ;
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/db/SQLite3Error.hpp
Index: genfile/include/genfile/db/SQLite3Error.hpp
==================================================================
--- genfile/include/genfile/db/SQLite3Error.hpp
+++ genfile/include/genfile/db/SQLite3Error.hpp
@@ -0,0 +1,19 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_SQLITE3_ERROR_HPP
+#define GENFILE_DB_SQLITE3_ERROR_HPP
+
+#include <string>
+#include "genfile/db/SQLStatement.hpp"
+
+namespace genfile {
+	namespace db {
+	}
+}
+
+#endif
+

ADDED   genfile/include/genfile/db/SQLite3Statement.hpp
Index: genfile/include/genfile/db/SQLite3Statement.hpp
==================================================================
--- genfile/include/genfile/db/SQLite3Statement.hpp
+++ genfile/include/genfile/db/SQLite3Statement.hpp
@@ -0,0 +1,99 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_SQLITE3_STATEMENT_HPP
+#define GENFILE_DB_SQLITE3_STATEMENT_HPP
+
+#include <cassert>
+#include <string>
+#include <exception>
+
+#include "sqlite3/sqlite3.h"
+#include "genfile/db/SQLite3Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+
+
+namespace genfile {
+	namespace db {
+		class SQLite3Statement: public SQLStatement
+		{
+		public:
+			SQLite3Statement( SQLite3Connection* connector, std::string const& SQL ) ;
+			~SQLite3Statement() ;
+			bool step() ;
+			bool empty() const ;
+		
+			std::size_t get_number_of_columns() const ;
+			std::string get_name_of_column( std::size_t i ) const ;
+			bool is_null( int column_id ) const ;
+			SQLite3Statement& bind( std::size_t i, int32_t value ) ;
+			SQLite3Statement& bind( std::size_t i, uint32_t value ) ;
+			SQLite3Statement& bind( std::size_t i, int64_t value ) ;
+			SQLite3Statement& bind( std::size_t i, uint64_t value ) ;
+			SQLite3Statement& bind( std::size_t i, double value ) ;
+			SQLite3Statement& bind( std::size_t i, std::string const& value ) ;
+			SQLite3Statement& bind( std::size_t i, char const* buffer, char const* const end ) ;
+			SQLite3Statement& bind( std::size_t i, uint8_t const* buffer, uint8_t const* const end ) ;
+			SQLite3Statement& bind_NULL( std::size_t i ) ;
+
+			SQLite3Statement& reset() ;
+
+			std::string get_sql() const ;
+
+			struct Error {
+				enum {
+					OK			= SQLITE_OK,
+					ERROR		= SQLITE_ERROR,			/* SQL error or missing database */
+					INTERNAL	= SQLITE_INTERNAL,		/* Internal logic error in SQLite */
+					PERM		= SQLITE_PERM,			/* Access permission denied */
+					ABORT		= SQLITE_ABORT,			/* Callback routine requested an abort */
+					BUSY		= SQLITE_BUSY,			/* The database file is locked */
+					LOCKED		= SQLITE_LOCKED,		/* A table in the database is locked */
+					NOMEM		= SQLITE_NOMEM,			/* A malloc() failed */
+					READONLY	= SQLITE_READONLY,		/* Attempt to write a readonly database */
+					INTERRUPT	= SQLITE_INTERRUPT,		/* Operation terminated by sqlite3_interrupt()*/
+					IOERR		= SQLITE_IOERR,			/* Some kind of disk I/O error occurred */
+					CORRUPT		= SQLITE_CORRUPT,		/* The database disk image is malformed */
+					NOTFOUND	= SQLITE_NOTFOUND,		/* NOT USED. Table or record not found */
+					FULL		= SQLITE_FULL,			/* Insertion failed because database is full */
+					CANTOPEN	= SQLITE_CANTOPEN,		/* Unable to open the database file */
+					PROTOCOL	= SQLITE_PROTOCOL,		/* Database lock protocol error */
+					EMPTY		= SQLITE_EMPTY,			/* Database is empty */
+					SCHEMA		= SQLITE_SCHEMA,		/* The database schema changed */
+					TOOBIG		= SQLITE_TOOBIG,		/* String or BLOB exceeds size limit */
+					CONSTRAINT	= SQLITE_CONSTRAINT,	/* Abort due to constraint violation */
+					MISMATCH	= SQLITE_MISMATCH,		/* Data type mismatch */
+					MISUSE		= SQLITE_MISUSE,		/* Library used incorrectly */
+					NOLFS		= SQLITE_NOLFS,			/* Uses OS features not supported on host */
+					AUTH		= SQLITE_AUTH,			/* Authorization denied */
+					FORMAT		= SQLITE_FORMAT,		/* Auxiliary database format error */
+					RANGE		= SQLITE_RANGE,			/* 2nd parameter to sqlite3_bind out of range */
+					NOTADB		= SQLITE_NOTADB,		/* File opened that is not a database file */
+					ROW			= SQLITE_ROW,			/* sqlite3_step() has another row ready */
+					DONE		= SQLITE_DONE			/* sqlite3_step() has finished executing */
+				} ;
+			} ;
+		protected:
+		
+			int64_t get_column_int64( int column_id ) const ;
+			int get_column_int( int column_id ) const ;
+			double get_column_double( int column_id ) const ;
+			std::string get_column_string( int column_id ) const ;
+			char get_column_char( int column_id ) const ;
+			std::vector< uint8_t > get_column_blob( int column_id ) const ;
+
+			int get_column_count() const ;
+
+		private:
+			sqlite3_stmt* m_statement ;
+			SQLite3Connection* m_connection ;	
+			bool m_have_results ;
+		} ;
+
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/db/Transaction.hpp
Index: genfile/include/genfile/db/Transaction.hpp
==================================================================
--- genfile/include/genfile/db/Transaction.hpp
+++ genfile/include/genfile/db/Transaction.hpp
@@ -0,0 +1,22 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_TRANSACTION_HPP
+#define GENFILE_DB_TRANSACTION_HPP
+
+#include <memory>
+
+namespace genfile {
+	namespace db {
+		class Transaction {
+		public:
+			typedef std::auto_ptr< Transaction > UniquePtr ;
+			virtual ~Transaction() {}
+		} ;
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/db/fill_SQL.hpp
Index: genfile/include/genfile/db/fill_SQL.hpp
==================================================================
--- genfile/include/genfile/db/fill_SQL.hpp
+++ genfile/include/genfile/db/fill_SQL.hpp
@@ -0,0 +1,38 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_FILL_SQL_HPP
+#define GENFILE_DB_FILL_SQL_HPP
+
+#include <cassert>
+#include <string>
+#include <sstream>
+
+namespace genfile {
+	namespace db {
+	
+		std::string fill_SQL( std::string SQL ) ;
+		std::string fill_SQL( std::string SQL, std::string const& value1 ) ;
+		std::string fill_SQL( std::string SQL, char const* value1 ) ;
+		template< typename T1 >
+		std::string fill_SQL( std::string SQL, T1 const& value1 ) {
+			std::ostringstream ostr ;
+			ostr << value1 ;
+			std::size_t pos = SQL.find( "%s" ) ;
+			assert( pos != std::string::npos ) ;
+			SQL.replace( pos, 2, ostr.str() ) ;
+			return SQL ;
+		}
+
+		template< typename T1, typename T2 >
+		std::string fill_SQL( std::string SQL, T1 const& value1, T2 const& value2 ) {
+			return fill_SQL( fill_SQL( SQL, value1 ), value2 ) ;
+		}
+	}
+}
+
+#endif
+

ADDED   genfile/include/genfile/db/get_unique_id.hpp
Index: genfile/include/genfile/db/get_unique_id.hpp
==================================================================
--- genfile/include/genfile/db/get_unique_id.hpp
+++ genfile/include/genfile/db/get_unique_id.hpp
@@ -0,0 +1,27 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef DB_GET_UNIQUE_ID_HPP
+#define DB_GET_UNIQUE_ID_HPP
+
+#include "genfile/db/Connection.hpp"
+
+namespace genfile {
+	namespace db {
+		// Given a table, an "id" column of ints and a where clause,
+		// return the id for the row matching the where clause.
+		// throw a error::KeyError if there is not a unique matching row.
+		int get_unique_id(
+			Connection* connection,
+			std::string const& table,
+			std::string const& id_column,
+			std::string const& where_clause
+		) ;
+	}
+}
+
+#endif
+

ADDED   genfile/include/genfile/db/load_key_value_pairs.hpp
Index: genfile/include/genfile/db/load_key_value_pairs.hpp
==================================================================
--- genfile/include/genfile/db/load_key_value_pairs.hpp
+++ genfile/include/genfile/db/load_key_value_pairs.hpp
@@ -0,0 +1,70 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_LOAD_KEY_VALUE_PAIRS_HPP
+#define GENFILE_DB_LOAD_KEY_VALUE_PAIRS_HPP
+
+#include <map>
+#include <string>
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/string_utils.hpp"
+
+namespace genfile {
+	namespace db {
+		template< typename Key, typename Value >
+		std::map< Key, Value > load_key_value_pairs(
+			Connection* connection,
+			std::string const& table_or_view,
+			std::string const& key_column,
+			std::string const& value_column		
+		)
+		// Load key/value pairs from the given columns of the given table, returning the result as a std::map.
+		// If a duplicate key is found, a KeyNotUniqueError is thrown.
+		{
+			typename std::map< Key, Value > result ;
+			db::Connection::StatementPtr statement = connection->get_statement(
+				"SELECT " + key_column + ", " + value_column + " FROM " + table_or_view + ";"
+			) ;
+	
+			while( statement->step() ) {
+				Key key = statement->get_column< Key >( 0 ) ;
+				if( result.find( key ) != result.end() ) {
+					throw genfile::DuplicateKeyError(
+						"db::load_key_value_pairs()",
+						connection->get_spec() + ":" + table_or_view + ", key=\"" + genfile::string_utils::to_string( key ) + "\""
+					) ;
+				}
+				result.insert(
+					std::make_pair(
+				 		key,
+						statement->get_column< Value >( 1 )
+					)
+				) ;
+			}
+
+			return result ;
+		}
+	
+		template< typename Key, typename Value >
+		std::map< Key, Value > load_key_value_pairs(
+			Connection::UniquePtr& connection,
+			std::string const& table_or_view,
+			std::string const& key_column,
+			std::string const& value_column		
+		) {
+			return load_key_value_pairs< Key, Value >(
+				connection.get(),
+				table_or_view,
+				key_column,
+				value_column
+			) ;
+		}
+	}
+}
+
+#endif

ADDED   genfile/include/genfile/db/sqlite3.hpp
Index: genfile/include/genfile/db/sqlite3.hpp
==================================================================
--- genfile/include/genfile/db/sqlite3.hpp
+++ genfile/include/genfile/db/sqlite3.hpp
@@ -0,0 +1,15 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef GENFILE_DB_SQLITE_HPP
+#define GENFILE_DB_SQLITE_HPP
+
+#include "Connection.hpp"
+#include "SQLite3Connection.hpp"
+#include "SQLite3Statement.hpp"
+#include "SQLite3Error.hpp"
+
+#endif

Index: genfile/include/genfile/vcf/Types.hpp
==================================================================
--- genfile/include/genfile/vcf/Types.hpp
+++ genfile/include/genfile/vcf/Types.hpp
@@ -26,11 +26,11 @@
 		typedef genfile::VariantEntry Entry ;
 
 		struct EntrySetter {
 			typedef int64_t Integer ;
 			typedef ::genfile::MissingValue MissingValue ;
-			virtual ~EntrySetter() throw() {}
+			virtual ~EntrySetter() {}
 			virtual void set_value( std::size_t, MissingValue const value ) = 0 ;
 			virtual void set_value( std::size_t, std::string& value ) ;
 			virtual void set_value( std::size_t, Integer const value ) ;
 			virtual void set_value( std::size_t, double const value ) ;
 			void set_value( std::size_t i, VariantEntry const& value ) {
@@ -49,17 +49,17 @@
 		} ;
 
 		struct EntriesSetter: public EntrySetter {
 			typedef genfile::OrderType OrderType ;
 			typedef genfile::ValueType ValueType ;
-			virtual ~EntriesSetter() throw() {}
+			virtual ~EntriesSetter() {}
 			virtual void set_number_of_entries( uint32_t ploidy, std::size_t n, OrderType const order_type, ValueType const value_type ) = 0 ;
 		} ;
 
 		struct PerSampleEntriesSetter: public vcf::EntriesSetter, public boost::noncopyable {
 			typedef std::auto_ptr< PerSampleEntriesSetter > UniquePtr ;
-			virtual ~PerSampleEntriesSetter() throw() {}
+			virtual ~PerSampleEntriesSetter() {}
 			// Prepare to receive values for a variant.
 			virtual void initialise( std::size_t nSamples, std::size_t nAlleles ) = 0 ;
 			// Return true if we want values for this variant, otherwise false.
 			virtual bool set_sample( std::size_t i ) = 0 ;
 			// Finalise.

Index: genfile/src/BGenFileSNPDataSource.cpp
==================================================================
--- genfile/src/BGenFileSNPDataSource.cpp
+++ genfile/src/BGenFileSNPDataSource.cpp
@@ -52,10 +52,14 @@
 		format[ "Description" ] = "Genotype call probabilities" ;
 		SNPDataSource::Metadata result ;
 		result.insert( std::make_pair( "FORMAT", format )) ;
 		return result ;
 	}
+
+	bool BGenFileSNPDataSource::has_sample_ids() const {
+		return m_sample_ids ;
+	}
 
 	void BGenFileSNPDataSource::get_sample_ids( GetSampleIds getter ) const {
 		if( m_sample_ids ) {
 			for( std::size_t i = 0; i < m_sample_ids->size(); ++i ) {
 				getter( i, m_sample_ids->at(i) ) ;

Index: genfile/src/BedFileSNPDataSink.cpp
==================================================================
--- genfile/src/BedFileSNPDataSink.cpp
+++ genfile/src/BedFileSNPDataSink.cpp
@@ -47,11 +47,11 @@
 		}
 		
 		// We write a dummy FAM file with missing info in most fields
 		std::auto_ptr< std::ostream > fam_file = open_text_file_for_output( m_output_filename_stub + ".fam", "no_compression" ) ;
 		for( std::size_t i = 0; i < number_of_samples; ++i ) {
-			(*fam_file) << (i+1) << " " << m_sample_ids[i] << " 0 0 0 0\n" ;
+			(*fam_file) << (i+1) << "\t" << m_sample_ids[i] << "\t0\t0\t0\t0\n" ;
 		}
 	}
 
 	void BedFileSNPDataSink::set_metadata_impl( Metadata const& ) {
 		// do nothing.  Metadata not supported.
@@ -89,16 +89,16 @@
 	) {
 		assert( number_of_samples == m_sample_ids.size() ) ;
 		/* Write BIM file line. */
 		if( chromosome.is_missing() ) {
 			// Missing chromosome encoded as 0
-			(*m_bim_file ) << "0 " ;
+			(*m_bim_file ) << "0\t" ;
 		} else {
-			(*m_bim_file ) << chromosome << " " ;
+			(*m_bim_file ) << chromosome << "\t" ;
 		}
 		
-		(*m_bim_file ) << RSID << " 0 " << SNP_position << " " << first_allele << " " << second_allele << "\n" ;
+		(*m_bim_file ) << RSID << "\t0\t" << SNP_position << "\t" << first_allele << "\t" << second_allele << "\n" ;
 
 		/* Write BED file line */
 		m_buffer.resize( (m_sample_ids.size()+3) / 4, 0 ) ;
 		for( std::size_t group = 0; group < m_sample_ids.size(); group += 4 ) {
 			std::size_t c_i = group / 4 ;

ADDED   genfile/src/CartesianProductVisitor.cpp
Index: genfile/src/CartesianProductVisitor.cpp
==================================================================
--- genfile/src/CartesianProductVisitor.cpp
+++ genfile/src/CartesianProductVisitor.cpp
@@ -0,0 +1,153 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include "boost/optional.hpp"
+#include "boost/noncopyable.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantDataReader.hpp"
+#include "genfile/CartesianProductVisitor.hpp"
+
+namespace genfile {
+	CartesianProductVisitor::CartesianProductVisitor( bool lower_triangle ):
+		m_lower_triangle( lower_triangle ),
+		m_min_distance(0)
+	{}
+
+	void CartesianProductVisitor::add_source(
+		std::string const& name,
+		genfile::SNPDataSource* source
+	) {
+		m_names.push_back( name ) ;
+		m_sources.push_back( source ) ;
+	}
+
+	void CartesianProductVisitor::set_min_distance( int64_t distance ) {
+		assert( distance >= 0 ) ;
+		m_min_distance = distance ;
+	}
+
+	bool CartesianProductVisitor::step(  Callback callback ) {
+		int64_t const distant = std::numeric_limits< int64_t >::max() ;
+		std::vector< int > changed( m_sources.size(), 0 ) ;
+		while( step_impl() ) {
+			// keep track of cumulative changes
+			for( std::size_t i = 0; i < changed.size(); ++i ) {
+				changed[i] = std::max( changed[i], m_changed[i] ) ;
+			}
+			int64_t const min_distance = (m_min_distance == 0) ? distant : compute_min_distance( m_variants ) ;
+			if( min_distance >= m_min_distance ) {
+				callback(
+					changed,
+					m_variants,
+					m_readers
+				) ;
+				return true ;
+			}
+		}
+		return false ;
+	}
+
+	boost::optional< std::size_t > CartesianProductVisitor::count() const {
+		boost::optional< std::size_t > result ;
+		if( m_sources.size() > 0 && (result = m_sources[0]->size() )) {
+			if( m_lower_triangle ) {
+				assert( m_sources.size() == 2 ) ;
+				result = ((*result) * (*result + 1) / 2) ;
+			} else {
+				for( std::size_t i = 1; i < m_sources.size(); ++i ) {
+					boost::optional< std::size_t > source_size = m_sources[i]->size() ;
+					if( !source_size ) {
+						return boost::optional< std::size_t >() ;
+					} else {
+						(*result) *= (*source_size) ;
+					}
+				}
+			}
+		}
+		return result ;
+	}
+
+	bool CartesianProductVisitor::step_impl() {
+		if( m_sources.empty() ) {
+			return false ;
+		}
+		if( m_changed.empty() ) {
+			// First call.  Populate our data structures.
+			m_changed.assign( m_sources.size(), 1 ) ;
+			m_variants.resize( m_sources.size() ) ;
+			assert( m_readers.size() == 0 ) ;
+			for( std::size_t i = 0; i < m_sources.size(); ++i ) {
+				if( !m_sources[i]->get_snp_identifying_data( &m_variants[i] )) {
+					return false ;
+				} ;
+				m_readers.push_back( m_sources[i]->read_variant_data() ) ;
+			}
+		} else {
+			// Move to the next variant.
+			// Use a linearised recursion to step through all combinations.
+			// We start at the last source and step to the next variant.
+			// If a source is exhausted we reset it to the start and recurse to
+			// the preceding source.
+			std::size_t i = m_sources.size() - 1 ;
+			for( ; true; --i ) {
+				if( !m_sources[i]->get_snp_identifying_data( &m_variants[i] )) {
+					if( i == 0 ) {
+						return false ;
+					} else {
+						reset_source(i) ;
+						m_sources[i]->get_snp_identifying_data( &m_variants[i] ) ;
+					}
+				} else {
+					break ;
+				}
+			}
+			m_changed.assign( m_sources.size(), 0 ) ;
+			for( std::size_t j = i; j < m_sources.size(); ++j ) {
+				m_changed[j] = 1 ;
+				m_readers[j] = m_sources[j]->read_variant_data() ;
+			}
+		}
+		return true ;
+	}
+
+	void CartesianProductVisitor::reset_source( std::size_t i ) {
+		m_sources[i]->reset_to_start() ;
+		if( m_lower_triangle ) {
+			assert( m_sources.size() == 2 ) ;
+			if( i == 1 ) {
+				genfile::VariantIdentifyingData variant ;
+				while( m_sources[1]->number_of_snps_read() < m_sources[0]->number_of_snps_read() ) {
+					m_sources[1]->get_snp_identifying_data( &variant ) ;
+					m_sources[1]->ignore_snp_probability_data() ;
+				}
+			}
+		}
+	}
+
+	// return minimum physical distance between any pair of variants on same chromosome,
+	// or maximum +pve value of int64 if all on different chromosomes
+	int64_t CartesianProductVisitor::compute_min_distance( std::vector< genfile::VariantIdentifyingData > const& variants ) const {
+		int64_t const distant = std::numeric_limits< int64_t >::max() ;
+		int64_t result = distant ;
+		for( std::size_t i = 0; i < ( variants.size()-1 ); ++i ) {
+			for( std::size_t j = i+1; j < variants.size(); ++j ) {
+				genfile::GenomePosition const& pos1 = variants[i].get_position() ;
+				genfile::GenomePosition const& pos2 = variants[j].get_position() ;
+				int64_t distance = (
+					(pos1.chromosome() != pos2.chromosome())
+					?
+					distant
+					:
+					std::abs( int64_t(pos1.position()) - int64_t(pos2.position()))
+				) ;
+				result = std::min( result, distance ) ;
+			}
+		}
+		return result ;
+	}
+}
+

Index: genfile/src/CategoricalCrossCohortCovariateValueMapping.cpp
==================================================================
--- genfile/src/CategoricalCrossCohortCovariateValueMapping.cpp
+++ genfile/src/CategoricalCrossCohortCovariateValueMapping.cpp
@@ -11,39 +11,42 @@
 #include <limits>
 #include <cmath>
 #include "genfile/CohortIndividualSource.hpp"
 #include "genfile/CategoricalCrossCohortCovariateValueMapping.hpp"
 #include "genfile/string_utils.hpp"
+
+// #define DEBUG 1
 
 namespace genfile {
 	CategoricalCrossCohortCovariateValueMapping::CategoricalCrossCohortCovariateValueMapping( std::string const& column_name ):
 		LevelCountingCrossCohortCovariateValueMapping( column_name )
 	{	
 	}
 
 	CohortIndividualSource::Entry CategoricalCrossCohortCovariateValueMapping::get_unmapped_value( Entry const& level ) const {
 		int i = level.as< int >() ;
-		assert( i > 0 ) ;
-		// Adjust because levels are always positive integers
-		--i ;
+		assert( i >= 0 ) ;
 		assert( std::size_t( i ) < histogram().size() ) ;
 		Histogram::const_iterator where = histogram().begin() ;
 		std::advance( where, std::size_t( i ) ) ;
 		return where->first ;
 	}
 	
 	CohortIndividualSource::Entry CategoricalCrossCohortCovariateValueMapping::get_mapped_value( Entry const& entry ) const {
+#if DEBUG
+		std::cerr << "CategoricalCrossCohortCovariateValueMapping::get_mapped_value( " << entry << " ).\n" ;
+#endif
 		Histogram::const_iterator where = histogram().find( entry ) ;
 		assert( where != histogram().end() ) ;
-		// We always return positive integers, so add one.
-		return Entry( int( std::distance( histogram().begin(), where ) + 1 ) ) ;
+		return Entry( int( std::distance( histogram().begin(), where ) ) ) ;
 	}
 	
 	
 	std::string CategoricalCrossCohortCovariateValueMapping::get_summary( std::string const& prefix ) const {
 		std::ostringstream ostr ;
-		ostr << "missing  levels\n"
+		ostr << prefix
+			<< "missing  levels\n"
 			<< prefix
 			<< std::setw(8) << std::setfill( ' ' ) << std::left << std::fixed << std::setprecision( 5 )
 			<< get_number_of_missing_values() ;
 		std::size_t count = 0 ;
 		for( Histogram::const_iterator i = histogram().begin(); i != histogram().end() && count < 10; ++i, ++count ) {

Index: genfile/src/Chromosome.cpp
==================================================================
--- genfile/src/Chromosome.cpp
+++ genfile/src/Chromosome.cpp
@@ -92,12 +92,12 @@
 			return "NA" ;
 		}
 	}
 
 	bool Chromosome::is_sex_determining() const {
-        return m_repr && ((*m_repr) == "0X" || (*m_repr) == "0Y" || (*m_repr) == "X" || (*m_repr) == "Y" ) ;
-    }
+		return m_repr && ((*m_repr) == "0X" || (*m_repr) == "0Y" || (*m_repr) == "X" || (*m_repr) == "Y" ) ;
+	}
 
 	bool Chromosome::is_autosome() const {
 		bool result = false ;
 		if( m_repr ) {
 			try {

Index: genfile/src/CohortIndividualSource.cpp
==================================================================
--- genfile/src/CohortIndividualSource.cpp
+++ genfile/src/CohortIndividualSource.cpp
@@ -219,11 +219,11 @@
 	std::size_t CohortIndividualSource::get_number_of_phenotypes() const {
 		return get_column_spec().get_number_of_phenotypes() ;
 	}
 	
 	bool CohortIndividualSource::ColumnSpec::check_for_column( std::string const& column_name ) const {
-		return std::find( m_column_names.begin(), m_column_names.end(), column_name ) != m_column_names.end() ;
+		return column_name == "ID_1" || std::find( m_column_names.begin(), m_column_names.end(), column_name ) != m_column_names.end() ;
 	}
 
 	std::size_t CohortIndividualSource::ColumnSpec::find_column( std::string const& column_name ) const {
 		std::size_t result = 0 ;
 		if( string_utils::to_lower( column_name ) != "id_1" ) {

Index: genfile/src/CountingCohortIndividualSource.cpp
==================================================================
--- genfile/src/CountingCohortIndividualSource.cpp
+++ genfile/src/CountingCohortIndividualSource.cpp
@@ -15,11 +15,11 @@
 		for( std::size_t i = 0; i < m_sample_ids.size(); ++i ) {
 			m_sample_ids[i] = ( boost::format( sample_name_template ) % i ).str() ;
 		}
 	}
 
-	CountingCohortIndividualSource::CountingCohortIndividualSource( std::vector< std::string > const& sample_ids ):
+	CountingCohortIndividualSource::CountingCohortIndividualSource( std::vector< genfile::VariantEntry > const& sample_ids ):
 		m_sample_ids( sample_ids )
 	{}
 
 	std::size_t CountingCohortIndividualSource::get_number_of_individuals() const {
 		return m_sample_ids.size() ;

Index: genfile/src/CrossCohortBaselineRemapping.cpp
==================================================================
--- genfile/src/CrossCohortBaselineRemapping.cpp
+++ genfile/src/CrossCohortBaselineRemapping.cpp
@@ -44,22 +44,22 @@
 				"genfile::CrossCohortBaselineRemapping::recompute_map()",
 				"m_baseline=\"" + genfile::string_utils::to_string( m_baseline ) + "\"",
 				"Baseline level is not found in the source."
 			) ;
 		} else {
-			m_map.insert( Map::value_type( m_baseline, 1 ) ) ;
+			m_map.insert( Map::value_type( m_baseline, 0 ) ) ;
 			for( int i = 0; i < get_number_of_distinct_mapped_values(); ++i ) {
-				Entry const unmapped_value = m_source->get_unmapped_value( i+1 ) ;
+				Entry const unmapped_value = m_source->get_unmapped_value( i ) ;
 				if( unmapped_value == m_baseline ) {
 					// baseline already added
 					std::cerr << "1:" << unmapped_value << "...\n" << std::flush ;
 				} else if( unmapped_value < m_baseline ) {
-					m_map.insert( Map::value_type( unmapped_value, i+2 )) ;
+					m_map.insert( Map::value_type( unmapped_value, i+1 )) ;
 					std::cerr << i+2 << ":" << unmapped_value << "...\n" << std::flush ;
 				} else {
 					std::cerr << i+1 << ":" << unmapped_value << "...\n" << std::flush ;
-					m_map.insert( Map::value_type( unmapped_value, i+1 )) ;
+					m_map.insert( Map::value_type( unmapped_value, i )) ;
 				}
 			}
 		}
 	}
 

Index: genfile/src/CrossCohortCovariateValueMapping.cpp
==================================================================
--- genfile/src/CrossCohortCovariateValueMapping.cpp
+++ genfile/src/CrossCohortCovariateValueMapping.cpp
@@ -16,13 +16,16 @@
 #include "genfile/CategoricalCrossCohortCovariateValueMapping.hpp"
 #include "genfile/ContinuousVariableCrossCohortCovariateValueMapping.hpp"
 #include "genfile/string_utils.hpp"
 
 namespace genfile {
-	CrossCohortCovariateValueMapping::UniquePtr CrossCohortCovariateValueMapping::create( CohortIndividualSource::SingleColumnSpec const& column_spec ) {
-		if( column_spec.is_continuous() ) {
-			if( column_spec.is_phenotype() ) {
+	CrossCohortCovariateValueMapping::UniquePtr CrossCohortCovariateValueMapping::create(
+		CohortIndividualSource::SingleColumnSpec const& column_spec,
+		bool normalise
+	) {
+		if( column_spec.is_continuous()) {
+			if( normalise ) {
 				return UniquePtr( new NormalisingCrossCohortCovariateValueMapping( column_spec.name() )) ;
 			}
 			else {
 				return UniquePtr( new ContinuousVariableCrossCohortCovariateValueMapping( column_spec.name() )) ;
 			}

Index: genfile/src/FromFileCohortIndividualSource.cpp
==================================================================
--- genfile/src/FromFileCohortIndividualSource.cpp
+++ genfile/src/FromFileCohortIndividualSource.cpp
@@ -80,10 +80,13 @@
 	CohortIndividualSource::ColumnSpec FromFileCohortIndividualSource::get_column_spec() const {
 		return ColumnSpec( m_column_names, m_column_types ) ;
 	}
 
 	bool FromFileCohortIndividualSource::check_for_column( std::string const& column_name ) const {
+		if( column_name == "ID_1" ) {
+			return true ;
+		}
 		std::map< std::string, std::size_t >::const_iterator where = m_column_indices.find( string_utils::to_lower( column_name ) ) ;
 		return ( where != m_column_indices.end() ) ;
 	}
 
 	std::vector< std::string >::const_iterator FromFileCohortIndividualSource::find_column_name_impl( std::string const& column_name ) const {
@@ -284,13 +287,10 @@
 					>> '{'
 					>> (
 						lit( "\"" )
 						>> ( +(graph - '\"') ) >> '\"'
 						>> ':'
-						>> '{'
-						>> "\"type\""
-						>> ':'
 						>> '\"'
 						>> ( +(graph - '\"'))
 						>> '\"'
 						>> '}'
 					)

ADDED   genfile/src/GPThresholdingGTSetter.cpp
Index: genfile/src/GPThresholdingGTSetter.cpp
==================================================================
--- genfile/src/GPThresholdingGTSetter.cpp
+++ genfile/src/GPThresholdingGTSetter.cpp
@@ -0,0 +1,197 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <cassert>
+#include "genfile/VariantDataReader.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/GPThresholdingGTSetter.hpp"
+
+
+namespace genfile {
+	GPThresholdingGTSetter::GPThresholdingGTSetter( VariantDataReader::PerSampleSetter& target, double const threshhold ):
+		m_target( target ),
+		m_threshhold( threshhold ),
+		m_number_of_alleles(0),
+		m_order_type( eUnknownOrderType ),
+		m_ploidy(0)
+	{
+		if( m_threshhold <= 0.5 ) {
+			throw BadArgumentError(
+				"genfile::ThreshholdingDataReader::GPThresholdingGTSetter::GPThresholdingGTSetter()",
+				"threshhold",
+				"Only threshholds greater than 0.5 are supported."
+			) ;
+		}
+		assert( m_threshhold > 0.5 ) ;
+	}
+	
+	GPThresholdingGTSetter::~GPThresholdingGTSetter() throw() {}
+		
+	void GPThresholdingGTSetter::initialise( std::size_t nSamples, std::size_t nAlleles ) {
+		m_number_of_alleles = nAlleles ;
+		m_target.initialise( nSamples, nAlleles ) ;
+	} ;
+
+	bool GPThresholdingGTSetter::set_sample( std::size_t i ) {
+		m_target.set_sample( i ) ;
+		m_missing = false ;
+		m_order_type = eUnknownOrderType ;
+		m_ploidy = 0 ;
+		m_entry_i = 0 ;
+		return true ;
+	}
+	
+	void GPThresholdingGTSetter::set_number_of_entries( uint32_t ploidy, std::size_t number_of_entries, OrderType const order_type, ValueType const value_type ) {
+		assert( order_type == ePerUnorderedGenotype || ePerPhasedHaplotypePerAllele ) ;
+		assert( value_type == eProbability ) ;
+		m_order_type = order_type ;
+		
+		m_ploidy = ploidy ;
+		m_calls.setZero( number_of_entries ) ;
+		m_target.set_number_of_entries(
+			m_ploidy, m_ploidy,
+			( m_order_type == ePerUnorderedGenotype ) ? ePerUnorderedHaplotype : ePerOrderedHaplotype,
+			eAlleleIndex
+		) ;
+	}
+	
+	void GPThresholdingGTSetter::set_value( std::size_t, MissingValue const value ) {
+		m_missing = true ;
+		m_entry_i++ ;
+		if( m_entry_i == m_calls.size() ) { 
+			send_results() ;
+		}
+	}
+
+	void GPThresholdingGTSetter::set_value( std::size_t, std::string& value ) {
+		throw BadArgumentError(
+			"genfile::ThreshholdingDataReader::GPThresholdingGTSetter::set_value",
+			"value",
+			"Expected a floating-point value (got a string)."
+		) ;
+	}
+
+	void GPThresholdingGTSetter::set_value( std::size_t, Integer const value ) {
+		throw BadArgumentError(
+			"genfile::ThreshholdingDataReader::GPThresholdingGTSetter::set_value",
+			"value",
+			"Expected a floating-point value (got an integer)."
+		) ;
+	}
+
+	void GPThresholdingGTSetter::set_value( std::size_t, double const value ) {
+		m_calls( m_entry_i++ ) = value ;
+		if( m_entry_i == m_calls.size() ) { 
+			send_results() ;
+		}
+	}
+	
+	void GPThresholdingGTSetter::finalise() {
+		m_target.finalise() ;
+	}
+
+	void GPThresholdingGTSetter::send_results() {
+		if( m_missing || m_calls.array().maxCoeff() < m_threshhold ) {
+			for( uint32_t i = 0 ; i < m_ploidy; ++i ) {
+				m_target.set_value( i, genfile::MissingValue() ) ;
+			}
+		} else {
+			// How to figure out the order here?
+			// Well..it goes like this.
+			if( m_order_type == ePerPhasedHaplotypePerAllele ) {
+				// for phased data it is simple:
+				for( uint32_t i = 0; i < m_ploidy; ++i ) {
+					for( uint32_t j = 0; j < m_number_of_alleles; ++j ) {
+						if( m_calls[i*m_number_of_alleles+j] >= m_threshhold ) {
+							m_target.set_value( i, Integer( j ) ) ;
+							break ;
+						}
+					}
+				}
+			} else if( m_order_type == ePerUnorderedGenotype ) {
+				// For unphased data it is more complex.
+				// We have m_ploidy = n chromosomes in total.
+				// Genotypes are all ways to put n_alleles = k alleles into
+				// those chromosomes.
+				// Represent these as k-vectors that sum to n (i.e. v_i is the count of allele i)
+				// Or (k-1)-vectors that sum to at most n.
+				// The order is chosen so that lower indices are always used first.
+				// 3,0,0 = AAA
+				// 2,1,0 = AAB
+				// 1,2,0 = ABB
+				// 0,3,0 = BBB
+				// 2,0,1 = BBC
+				// 1,1,1 = ABC
+				// 0,2,1 = BBC
+				// 0,1,2 = BCC
+				// 0,0,3 = CCC
+			
+
+				// We fast-path the common (diploid, biallelic) case.
+				if( m_number_of_alleles == 2 && m_ploidy == 2 ) {
+					if( m_calls[0] >= m_threshhold ) {
+						m_target.set_value( 0, Integer(0) ) ;
+						m_target.set_value( 1, Integer(0) ) ;
+					} else if( m_calls[1] >= m_threshhold ) {
+						m_target.set_value( 0, Integer(0) ) ;
+						m_target.set_value( 1, Integer(1) ) ;
+					} else if( m_calls[2] >= m_threshhold ) {
+						m_target.set_value( 0, Integer(1) ) ;
+						m_target.set_value( 1, Integer(1) ) ;
+					} else {
+						m_target.set_value( 0, genfile::MissingValue() ) ;
+						m_target.set_value( 1, genfile::MissingValue() ) ;
+					}
+				} else {
+					// We enumerate vectors in this order and stop when we meet a probabiltiy
+					// meeting the desired threshhold.
+					std::vector< uint16_t > limits( (m_number_of_alleles-1), m_ploidy ) ;
+					std::vector< uint16_t > allele_counts( m_number_of_alleles, 0 ) ;
+					allele_counts[0] = m_ploidy ;
+					bool finished = false ;
+					for( std::size_t index = 0; !finished; ++index ) {
+						if( m_calls[index] >= m_threshhold ) {
+							std::size_t this_index = 0 ;
+							for( std::size_t allele = 0; allele < m_number_of_alleles; ++allele ) {
+								for( uint16_t count = 0; count < allele_counts[allele]; ++count ) {
+									m_target.set_value( ++this_index, Integer( allele )) ;
+								}
+							}
+							break ;
+						}
+						
+						// Move to next possible genotype
+						std::size_t j = 0 ;
+						for( ; j < (m_number_of_alleles-1); ++j ) {
+							uint16_t value = allele_counts[j+1] ;
+							if( value < limits[ j ] ) {
+								++allele_counts[j+1] ;
+								--allele_counts[0] ;
+								for( std::size_t k = 0; k < j; ++k ) {
+									--limits[k] ;
+								}
+								break ;
+							} else {
+								// allele count has reached its limit.
+								// Reset it to zero.
+								// Note that to get here all lower-order counts must be zero.
+								allele_counts[j+1] = 0 ;
+								allele_counts[0] += value ;
+								for( std::size_t k = 0; k < j; ++k ) {
+									limits[k] += value ;
+								}
+							}
+						}
+						if( j == (m_number_of_alleles-1) ) {
+							finished = true ;
+						}
+					}
+				}
+			}
+		}
+	}
+} ;
+

Index: genfile/src/GenFileSNPDataSource.cpp
==================================================================
--- genfile/src/GenFileSNPDataSource.cpp
+++ genfile/src/GenFileSNPDataSource.cpp
@@ -8,10 +8,11 @@
 #include <string>
 #include "genfile/snp_data_utils.hpp"
 #include "genfile/gen.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "genfile/GenFileSNPDataSource.hpp"
+#include "genfile/string_utils/string_utils.hpp"
 
 namespace genfile {
 	GenFileSNPDataSource::GenFileSNPDataSource( std::auto_ptr< std::istream > stream, Chromosome chromosome ):
 		m_filename( "(unnamed stream)" ),
 		m_compression_type( "no_compression" ),
@@ -66,28 +67,37 @@
 		result.insert( std::make_pair( "FORMAT", format )) ;
 		return result ;
 	}
 	
 	void GenFileSNPDataSource::read_snp_identifying_data_impl( VariantIdentifyingData* result ) {
+		using string_utils::slice ;
 		std::string SNPID, rsid, allele1, allele2 ;
 		uint32_t position ;
 		Chromosome chromosome ;
 		try {
 			std::string chromosome_string ;
 			if( m_have_chromosome_column ) {
 				gen::impl::read_snp_identifying_data( stream(), &chromosome_string, &SNPID, &rsid, &position, &allele1, &allele2 ) ;
 				if( *this ) {
 					*result = VariantIdentifyingData(
-						SNPID, rsid, GenomePosition( chromosome_string, position ), allele1, allele2
+						rsid, GenomePosition( chromosome_string, position ), allele1, allele2
 					) ;
+					std::vector< slice > elts = slice(SNPID).split( ";" ) ;
+					for( std::size_t i = 0; i < elts.size(); ++i ) {
+						result->add_identifier( elts[i] ) ;
+					}
 				}
 			} else {
 				gen::impl::read_snp_identifying_data( stream(), &SNPID, &rsid, &position, &allele1, &allele2 ) ;
 				if( *this ) {
 					*result = VariantIdentifyingData(
-						SNPID, rsid, GenomePosition( m_chromosome, position ), allele1, allele2
+						rsid, GenomePosition( m_chromosome, position ), allele1, allele2
 					) ;
+					std::vector< slice > elts = slice(SNPID).split( ";" ) ;
+					for( std::size_t i = 0; i < elts.size(); ++i ) {
+						result->add_identifier( elts[i] ) ;
+					}
 				}
 			}
 		} catch( InputError const& e ) {
 			throw MalformedInputError(
 				m_filename,

Index: genfile/src/GenLikeSNPDataSink.cpp
==================================================================
--- genfile/src/GenLikeSNPDataSink.cpp
+++ genfile/src/GenLikeSNPDataSink.cpp
@@ -54,11 +54,11 @@
 			}
 			else if( m_chromosome != variant.get_position().chromosome() ) {
 				throw BadArgumentError( "GenLikeSNPDataSink::write_variant()", "chromosome=" + string_utils::to_string( variant.get_position().chromosome() ) ) ;
 			}
 		}
-		std::string const& SNPID = ( variant.number_of_identifiers() > 1 ? variant.get_identifiers_as_string(",", 1) : variant.get_identifiers_as_string(",", 0,1) ) ;
+		std::string const& SNPID = ( variant.number_of_identifiers() > 1 ? variant.get_identifiers_as_string(";", 1) : variant.get_identifiers_as_string(";", 0,1) ) ;
 		out << SNPID << " "
 			<< variant.get_primary_id() << " "
 			<< variant.get_position().position() << " "
 			<< variant.get_allele(0) << " "
 			<< variant.get_allele(1) ;

ADDED   genfile/src/ListSNPDataSink.cpp
Index: genfile/src/ListSNPDataSink.cpp
==================================================================
--- genfile/src/ListSNPDataSink.cpp
+++ genfile/src/ListSNPDataSink.cpp
@@ -0,0 +1,77 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <string>
+#include <boost/bind.hpp>
+#include "genfile/snp_data_utils.hpp"
+#include "genfile/SNPDataSink.hpp"
+#include "genfile/bgen/bgen.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/ListSNPDataSink.hpp"
+#include "genfile/ToGP.hpp"
+
+namespace genfile {
+	// This class is intended to be used via a derived class.
+	ListSNPDataSink::ListSNPDataSink(
+		std::string const& filename,
+		CompressionType compression_type
+	)
+	: 	m_filename( filename ),
+		m_stream_ptr( open_text_file_for_output( m_filename, compression_type ) )
+	{
+		setup() ;
+	}
+
+	ListSNPDataSink::ListSNPDataSink(
+		std::auto_ptr< std::ostream > stream_ptr,
+		std::string const& filename,
+		CompressionType compression_type
+	)
+	: 	m_filename( filename ),
+		m_stream_ptr( stream_ptr )
+	{
+		setup() ;
+	}
+
+	void ListSNPDataSink::setup() {
+		(*m_stream_ptr) << "SNPID rsid chromosome position alleleA alleleB\n" ;
+	}
+
+	std::string ListSNPDataSink::get_spec() const {
+		return "list(\"" + m_filename + "\")" ;
+	}
+
+	void ListSNPDataSink::set_sample_names_impl( std::size_t, SampleNameGetter ) {
+	}
+
+	SNPDataSink::SinkPos ListSNPDataSink::get_stream_pos() const {
+		return SinkPos( this, m_stream_ptr->tellp() ) ;
+	}
+	
+	ListSNPDataSink::operator bool() const { return m_stream_ptr->good() ; }
+
+	void ListSNPDataSink::write_variant_data_impl(
+		VariantIdentifyingData const& id_data,
+		VariantDataReader&,
+		Info const&
+	) {
+		std::string const& SNPID = ( id_data.number_of_identifiers() > 1 ? id_data.get_identifiers_as_string(",", 1) : id_data.get_identifiers_as_string(",", 0,1) ) ;
+		std::string chromosome = "NA" ;
+		if( !id_data.get_position().chromosome().is_missing() ) {
+			chromosome = id_data.get_position().chromosome() ;
+		}
+		(*m_stream_ptr) << SNPID
+			<< " " << id_data.get_primary_id()
+			<< " " << chromosome
+			<< " " << id_data.get_position().position()
+			<< " " << id_data.get_allele(0)
+			<< " " << id_data.get_alleles_as_string(",",1)
+			<< "\n" ;
+	}
+
+}
+

Index: genfile/src/LongFormatSNPDataSource.cpp
==================================================================
--- genfile/src/LongFormatSNPDataSource.cpp
+++ genfile/src/LongFormatSNPDataSource.cpp
@@ -270,11 +270,11 @@
 						lineNumber, 7
 					) ;
 				}
 				
 				// parse alternate alleles
-				std::vector< slice > alternate_alleles = elts[6].split( "/" ) ;
+				std::vector< slice > alternate_alleles = elts[6].split( "," ) ;
 				if( alternate_alleles.size() + 1 != to_repr< int >( elts[4] )) {
 					throw genfile::MalformedInputError(
 						m_filename,
 						"Wrong number of alleles found (" + to_string( alternate_alleles.size() + 1 ) + ", expected " + elts[4],
 						lineNumber, 5

Index: genfile/src/MergingSNPDataSource.cpp
==================================================================
--- genfile/src/MergingSNPDataSource.cpp
+++ genfile/src/MergingSNPDataSource.cpp
@@ -136,10 +136,20 @@
 		}
 		else {
 			return m_sources[0]->number_of_samples() ;
 		}
 	}
+	
+	bool MergingSNPDataSource::has_sample_ids() const {
+		return !m_sources.empty() && m_sources[0]->has_sample_ids() ;
+	}
+
+	void MergingSNPDataSource::get_sample_ids( GetSampleIds getter ) const {
+		if( !m_sources.empty() ) {
+			return m_sources[0]->get_sample_ids( getter ) ;
+		}
+	}
 
 	// Return the total number of snps the source contains.
 	SNPDataSource::OptionalSnpCount MergingSNPDataSource::total_number_of_snps() const {
 		unsigned int result = 0 ;
 		for( std::size_t i = 0; i < m_sources.size(); ++i ) {

Index: genfile/src/ReorderingSNPDataSource.cpp
==================================================================
--- genfile/src/ReorderingSNPDataSource.cpp
+++ genfile/src/ReorderingSNPDataSource.cpp
@@ -10,10 +10,12 @@
 #include <set>
 #include <algorithm>
 #include "config/config.hpp"
 #include <boost/optional.hpp>
 #include <boost/function.hpp>
+#include <boost/bind.hpp>
+#include "genfile/string_utils/string_utils.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "genfile/ReorderingSNPDataSource.hpp"
 #include "genfile/VariantDataReader.hpp"
 
 // #define DEBUG_REORDERING_SNP_DATA_SOURCE 1
@@ -80,10 +82,50 @@
 		m_entry_types.resize( m_order.size() ) ;
 		m_ints.resize( m_order.size() ) ;
 		m_strings.resize( m_order.size() ) ;
 		m_doubles.resize( m_order.size() ) ;
 	}
+
+	namespace {
+		void set_reordered_entry(
+			std::size_t i,
+			std::string const& value,
+			std::vector< std::size_t > const& order,
+			std::vector< std::string >* result
+		) {
+			std::size_t const j = order[i] ;
+			if( j != ReorderingSNPDataSource::eNotIncluded ) {
+				(*result)[j] = value ;
+			}
+		}
+	}
+
+	bool ReorderingSNPDataSource::has_sample_ids() const {
+		return m_source->has_sample_ids() ;
+	}
+
+	void ReorderingSNPDataSource::get_sample_ids(
+		GetSampleIds callback
+	) const {
+		std::vector< std::string > sample_ids( m_order.size() ) ;
+		for( std::size_t i = 0; i < m_order.size(); ++i ) {
+			sample_ids[i] = ("(anonymous_sample_" + genfile::string_utils::to_string(i) + ")") ;
+		}
+		if( m_source->has_sample_ids() ) {
+			m_source->get_sample_ids(
+				boost::bind(
+					&set_reordered_entry,
+					_1, _2,
+					m_order,
+					&sample_ids
+				)
+			) ;
+		}
+		for( std::size_t i = 0; i < m_order.size(); ++i ) {
+			callback( i, sample_ids[i] ) ;
+		}
+	}
 	
 	struct ReorderingVariantDataReader: public VariantDataReader {
 		struct SampleSetter: public VariantDataReader::PerSampleSetter {
 
 			enum EntryTypes { eMissing = 0, eString = 1, eInteger = 2, eDouble = 3 } ;

Index: genfile/src/SNPDataSink.cpp
==================================================================
--- genfile/src/SNPDataSink.cpp
+++ genfile/src/SNPDataSink.cpp
@@ -24,10 +24,11 @@
 #include "genfile/PennCNVSNPDataSink.hpp"
 #include "genfile/cnvHapSNPDataSink.hpp"
 #include "genfile/ShapeITHaplotypesSNPDataSink.hpp"
 #include "genfile/VCFFormatSNPDataSink.hpp"
 #include "genfile/ImputeHapProbsSNPDataSink.hpp"
+#include "genfile/ListSNPDataSink.hpp"
 #include "genfile/vcf/get_set_eigen.hpp"
 #include "genfile/get_set_eigen.hpp"
 #include "genfile/get_set.hpp"
 
 namespace genfile {
@@ -46,10 +47,11 @@
 		result.push_back( "dosage" ) ;
 		result.push_back( "bimbam_dosage" ) ;
 		result.push_back( "intensity" ) ;
 		result.push_back( "penncnv" ) ;
 		result.push_back( "cnvhap" ) ;
+		result.push_back( "list" ) ;
 		return result ;
 	}
 
 	SNPDataSink::UniquePtr SNPDataSink::create(
 		std::string const& filename,
@@ -104,15 +106,18 @@
 			return SNPDataSink::UniquePtr( new cnvHapSNPDataSink( filename ) ) ;
 		}
 		else if( d.first == "impute_allele_probs" ) {
 			return SNPDataSink::UniquePtr( new ImputeHapProbsSNPDataSink( filename ) ) ;
 		}
+		else if( d.first == "list" ) {
+			return SNPDataSink::UniquePtr( new ListSNPDataSink( filename, compression_type ) ) ;
+		}
 		else if( d.first == "" ) {
 			return SNPDataSink::UniquePtr( new VCFFormatSNPDataSink( filename ) ) ;
 		}
 		else {
-			throw BadArgumentError( "SNPDataSink::create_impl()", "filename", "Unrecognised file type for file \"" + filename + "\"." ) ;
+			throw BadArgumentError( "SNPDataSink::create_impl()", "filename", "Unrecognised file type (\"" + d.first + "\") for file \"" + filename + "\"." ) ;
 		}
 	}
 	
 	SNPDataSink::SNPDataSink():
 		m_number_of_samples(0u), m_samples_have_been_set( false ), m_number_of_snps_written(0u)

Index: genfile/src/SNPDataSource.cpp
==================================================================
--- genfile/src/SNPDataSource.cpp
+++ genfile/src/SNPDataSource.cpp
@@ -7,10 +7,11 @@
 #include <iostream>
 #include <iomanip>
 #include <string>
 #include <sstream>
 #include <boost/optional.hpp>
+#include <boost/format.hpp>
 #include "genfile/snp_data_utils.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "genfile/GenFileSNPDataSource.hpp"
 #include "genfile/BGenFileSNPDataSource.hpp"
 #include "genfile/SNPDataSourceChain.hpp"
@@ -129,10 +130,17 @@
 		m_state( e_HaveNotReadIdentifyingData ),
 		m_source_reset_callback(0)
 	{}
 
 	SNPDataSource::~SNPDataSource() {}
+
+	void SNPDataSource::get_sample_ids( GetSampleIds callback ) const {
+		boost::format fmt( "sample_%d" ) ;
+		for( std::size_t i = 0; i < number_of_samples(); ++i ) {
+			callback( i, (fmt % i).str() ) ;
+		}
+	}
 
 	void SNPDataSource::reset_to_start() {
 		reset_to_start_impl() ;
 		m_number_of_snps_read = 0 ;
 		m_state = e_HaveNotReadIdentifyingData ;
@@ -326,11 +334,15 @@
 
 	std::string SNPDataSource::get_summary( std::string const& prefix, std::size_t width ) const {
 		std::ostringstream ostr ;
 		ostr << prefix << std::setw( width ) << "Spec: " << get_source_spec() << "\n" ;
 		ostr << prefix << std::setw( width ) << "Number of samples: " <<  number_of_samples() << "\n" ;
-		ostr << prefix << std::setw( width ) << "Number of SNPs: " <<  total_number_of_snps() << "\n" ;
+		if( total_number_of_snps() ) {
+			ostr << prefix << std::setw( width ) << "Number of SNPs: " << *total_number_of_snps() << "\n" ;
+		} else {
+			ostr << prefix << std::setw( width ) << "Number of SNPs: " << "(not computed)\n" ;
+		}
 		return ostr.str() ;
 	}	
 
 }
 

Index: genfile/src/SNPDataSourceChain.cpp
==================================================================
--- genfile/src/SNPDataSourceChain.cpp
+++ genfile/src/SNPDataSourceChain.cpp
@@ -107,10 +107,14 @@
 	}
 
 	unsigned int SNPDataSourceChain::number_of_samples() const {
 		return m_number_of_samples ;
 	}
+
+	bool SNPDataSourceChain::has_sample_ids() const {
+		return m_sources.size() > 0 && m_sources[0]->has_sample_ids() ;
+	}
 
 	void SNPDataSourceChain::get_sample_ids( GetSampleIds setter ) const {
 		if( m_sources.size() > 0 ) {
 			m_sources[0]->get_sample_ids( setter ) ;
 		}

Index: genfile/src/SNPDataSourceRack.cpp
==================================================================
--- genfile/src/SNPDataSourceRack.cpp
+++ genfile/src/SNPDataSourceRack.cpp
@@ -146,10 +146,20 @@
 		private:
 			SNPDataSource::GetSampleIds m_setter ;
 			std::size_t m_offset ;
 		} ;
 	}
+
+	bool SNPDataSourceRack::has_sample_ids() const {
+		for( std::size_t i = 0; i < m_sources.size(); ++i ) {
+			if( m_sources[i]->has_sample_ids() ) {
+				return true ;
+			}
+		}
+		return false ;
+	}
+
 	void SNPDataSourceRack::get_sample_ids( GetSampleIds getter ) const {
 		std::size_t offset = 0 ;
 		for( std::size_t i = 0; i < m_sources.size(); ++i ) {
 			impl::OffsetSetter setter( getter, offset ) ;
 			m_sources[i]->get_sample_ids( setter ) ;
@@ -211,11 +221,11 @@
 	}
 
 	namespace {
 		void combine_ids( std::set< std::string >* target, std::string* combined, std::string const& value ) {
 			if( target->insert( value ).second ) {
-				(*combined) += ( combined->size() > 0 ? "," : "" ) + value ;
+				(*combined) += ( combined->size() > 0 ? "/" : "" ) + value ;
 			}
 		}
 	}
 	
 	void SNPDataSourceRack::get_snp_identifying_data_impl( 
@@ -224,10 +234,11 @@
 		if( m_sources.size() == 0 ) {
 			return ;
 		}
 		
 		VariantIdentifyingData this_snp ;
+		VariantIdentifyingData merged_snp ;
 		std::string merged_SNPID, merged_rsid, merged_allele1, merged_allele2 ;
 		std::set< std::string > rsids ;
 		std::set< std::string > SNPIDs ;
 		std::vector< char > flips( m_sources.size(), eNoFlip ) ;
 		std::size_t source_i = 0 ;
@@ -260,11 +271,11 @@
 #endif
 					if( this_source_snp.number_of_identifiers() > 1 ) {
 						this_source_snp.get_identifiers( boost::bind( &combine_ids, &SNPIDs, &merged_SNPID, _1 ), 1 ) ;
 					}
 					if( rsids.insert( this_source_snp.get_primary_id() ).second ) {
-						merged_rsid += "," + std::string( this_source_snp.get_primary_id() ) ;
+						merged_rsid += ";" + std::string( this_source_snp.get_primary_id() ) ;
 					}
 					if( m_comparator.get_flip_alleles_if_necessary() ) {
 						assert( this_snp.number_of_alleles() == 2 ) ;
 						assert( this_source_snp.number_of_alleles() == 2 ) ;
 						if( this_source_snp.get_allele(0) == this_snp.get_allele(1) && this_source_snp.get_allele(1) == this_snp.get_allele(0) ) {
@@ -290,15 +301,19 @@
 					m_sources[0]->ignore_snp_probability_data() ;
 					m_sources[0]->get_snp_identifying_data( &this_snp ) ;
 				}
 			}
 		}
-		if( SNPIDs.size() == 0 ) {
-			merged_SNPID = "." ;
-		}
 		if( *this ) {
-			*result = VariantIdentifyingData( merged_SNPID, merged_rsid, this_snp.get_position(), merged_allele1, merged_allele2 ) ;
+			VariantIdentifyingData merged_snp( this_snp.get_primary_id(), this_snp.get_position(), merged_allele1, merged_allele2 ) ;
+			for( std::set< std::string >::const_iterator i = rsids.begin(); i != rsids.end(); ++i ) {
+				merged_snp.add_identifier( *i ) ;
+			}
+			for( std::set< std::string >::const_iterator i = SNPIDs.begin(); i != SNPIDs.end(); ++i ) {
+				merged_snp.add_identifier( *i ) ;
+			}
+			*result = merged_snp ;
 			// Remember the flips.
 			m_flips = flips ;
 		}
 	}
 

Index: genfile/src/SNPFilteringSNPDataSource.cpp
==================================================================
--- genfile/src/SNPFilteringSNPDataSource.cpp
+++ genfile/src/SNPFilteringSNPDataSource.cpp
@@ -45,10 +45,14 @@
 	}
 
 	unsigned int SNPFilteringSNPDataSource::number_of_samples() const {
 		return m_source->number_of_samples() ;
 	}
+
+	bool SNPFilteringSNPDataSource::has_sample_ids() const {
+		return m_source->has_sample_ids() ;
+	}
 
 	void SNPFilteringSNPDataSource::get_sample_ids( GetSampleIds getter ) const {
 		return m_source->get_sample_ids( getter ) ;
 	}
 

Index: genfile/src/SNPIdentifyingDataFilteringSNPDataSource.cpp
==================================================================
--- genfile/src/SNPIdentifyingDataFilteringSNPDataSource.cpp
+++ genfile/src/SNPIdentifyingDataFilteringSNPDataSource.cpp
@@ -5,11 +5,11 @@
 //          http://www.boost.org/LICENSE_1_0.txt)
 
 #include "genfile/Error.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "genfile/VariantIdentifyingDataTest.hpp"
-#include "genfile/SNPIdentifyingDataFilteringSNPDataSource.hpp"
+#include "genfile/VariantIdentifyingDataFilteringSNPDataSource.hpp"
 #include "genfile/get_set.hpp"
 
 namespace genfile {
 	// Create a VariantIdentifyingDataFilteringSNPDataSource from the given source and the given sample indices.
 	std::auto_ptr< VariantIdentifyingDataFilteringSNPDataSource > VariantIdentifyingDataFilteringSNPDataSource::create(
@@ -68,10 +68,14 @@
 	}
 
 	unsigned int VariantIdentifyingDataFilteringSNPDataSource::number_of_samples() const {
 		return m_source->number_of_samples() ;
 	}
+
+	bool VariantIdentifyingDataFilteringSNPDataSource::has_sample_ids() const {
+		return m_source->has_sample_ids() ;
+	}
 
 	void VariantIdentifyingDataFilteringSNPDataSource::get_sample_ids( GetSampleIds getter ) const {
 		return m_source->get_sample_ids( getter ) ;
 	}
 

Index: genfile/src/SampleFilteringSNPDataSource.cpp
==================================================================
--- genfile/src/SampleFilteringSNPDataSource.cpp
+++ genfile/src/SampleFilteringSNPDataSource.cpp
@@ -44,12 +44,45 @@
 
 	unsigned int SampleFilteringSNPDataSource::number_of_samples() const {
 		return m_source->number_of_samples() - m_indices_of_samples_to_filter_out.size() ;
 	}
 
-	void SampleFilteringSNPDataSource::get_sample_ids( GetSampleIds getter ) const {
-		return m_source->get_sample_ids( getter ) ;
+	bool SampleFilteringSNPDataSource::has_sample_ids() const {
+		return m_source->has_sample_ids() ;
+	}
+
+	namespace {
+		void set_vector_entry(
+			std::size_t i,
+			std::string const& id,
+			std::vector< std::string >* result
+		) {
+			assert( i < result->size() ) ;
+			(*result)[i] = id ;
+		}
+	}
+
+	void SampleFilteringSNPDataSource::get_sample_ids( GetSampleIds callback ) const {
+		std::vector< std::string > ids( number_of_samples() ) ;
+		m_source->get_sample_ids(
+			boost::bind( &set_vector_entry, _1, _2, &ids )
+		) ;
+		std::vector< std::size_t >::const_iterator
+			i( m_indices_of_samples_to_filter_out.begin() ),
+			end_i( m_indices_of_samples_to_filter_out.end() ) ;
+
+		std::size_t index_of_last_unfiltered_sample = 0 ;
+		std::size_t index_in_output = 0 ;
+		for( ; i != end_i; ++i ) {
+			for( std::size_t sample_i = index_of_last_unfiltered_sample; sample_i < *i; ++sample_i ) {
+				callback( index_in_output++, ids[sample_i] ) ;
+			}
+			index_of_last_unfiltered_sample = (*i) + 1 ;
+		}
+		for( std::size_t sample_i = index_of_last_unfiltered_sample; sample_i < m_source->number_of_samples() ; ++sample_i ) {
+			callback( index_in_output++, ids[sample_i] ) ;
+		}
 	}
 
 	SNPDataSource::OptionalSnpCount SampleFilteringSNPDataSource::total_number_of_snps() const {
 		return m_source->total_number_of_snps() ;
 	}
@@ -87,11 +120,11 @@
 		m_source->get_snp_identifying_data( result ) ;
 	}
 
 	void SampleFilteringSNPDataSource::read_source_probability_data() {
 		m_source->read_snp_probability_data(
-		 	boost::bind( &SampleFilteringSNPDataSource::set_unfiltered_genotype_probabilities, this, _1, _2, _3, _4 )
+			boost::bind( &SampleFilteringSNPDataSource::set_unfiltered_genotype_probabilities, this, _1, _2, _3, _4 )
 		) ;
 	}
 
 	void SampleFilteringSNPDataSource::return_filtered_genotype_probabilities(
 		GenotypeProbabilitySetter const& set_genotype_probabilities

Index: genfile/src/SampleMappingSNPDataSource.cpp
==================================================================
--- genfile/src/SampleMappingSNPDataSource.cpp
+++ genfile/src/SampleMappingSNPDataSource.cpp
@@ -280,10 +280,14 @@
 	}
 
 	unsigned int SampleMappingSNPDataSource::number_of_samples() const {
 		return m_sample_mapping->number_of_source_samples() ;
 	}
+
+	bool SampleMappingSNPDataSource::has_sample_ids() const {
+		return false ; // not implemented
+	}
 
 	void SampleMappingSNPDataSource::get_sample_ids( GetSampleIds ) const {
 		assert(0) ; // requires implementation
 		return ;	
 	}

Index: genfile/src/SampleRange.cpp
==================================================================
--- genfile/src/SampleRange.cpp
+++ genfile/src/SampleRange.cpp
@@ -45,6 +45,13 @@
 	}
 	
 	std::ostream& operator<<( std::ostream& out, SampleRange const& range ) {
 		return out << "[" << range.begin() << "-" << range.end() << ")" ;
 	}
+
+	std::ostream& operator<<( std::ostream& out, std::vector< SampleRange > const& ranges ) {
+		for( std::size_t i = 0; i < ranges.size(); ++i ) {
+			out << (i>0?",":"" ) << ranges[i] ;
+		}
+		return out ;
+	}
 }

Index: genfile/src/SampleStratification.cpp
==================================================================
--- genfile/src/SampleStratification.cpp
+++ genfile/src/SampleStratification.cpp
@@ -103,14 +103,6 @@
 		if( where == m_index_by_strata.end() ) {
 			throw genfile::BadArgumentError( "core::SampleStratification::stratum()", "strata_name=\"" + strata_name + "\"", "no such strata" ) ;
 		}
 		return m_sample_ranges[ where->second ] ;
 	}
-	
-	std::ostream& operator<<( std::ostream& out, std::vector< SampleRange > const& range ) {
-		for( std::size_t i = 0; i < range.size(); ++i ) {
-			out << ((i>0) ? " " : "" ) << range[i] ;
-		}
-		return out ;
-	}
-	
 }

Index: genfile/src/SortingBGenFileSNPDataSink.cpp
==================================================================
--- genfile/src/SortingBGenFileSNPDataSink.cpp
+++ genfile/src/SortingBGenFileSNPDataSink.cpp
@@ -26,12 +26,12 @@
 		SNPDataSink::UniquePtr sink,
 		VariantIdentifyingData::CompareFields comparer
 	):
 		m_filename( filename ),
 		m_sink( sink ),
-		m_offset_of_first_snp( 0 ),
-		m_file_offsets( comparer )
+		m_file_offsets( comparer ),
+		m_offset_of_first_snp( 0 )
 	{
 	}
 
 	std::string SortingBGenFileSNPDataSink::get_spec() const {
 		return m_filename ;

Index: genfile/src/StrandAligningSNPDataSource.cpp
==================================================================
--- genfile/src/StrandAligningSNPDataSource.cpp
+++ genfile/src/StrandAligningSNPDataSource.cpp
@@ -70,10 +70,14 @@
 	}
 	
 	std::string StrandAligningSNPDataSource::get_summary( std::string const& prefix, std::size_t column_width ) const {
 		return m_source->get_summary( prefix + "  " ) ;
 	}
+
+	bool StrandAligningSNPDataSource::has_sample_ids() const {
+		return m_source->has_sample_ids() ;
+	}
 
 	void StrandAligningSNPDataSource::get_sample_ids( GetSampleIds callback ) const {
 		return m_source->get_sample_ids( callback ) ;
 	}
 

Index: genfile/src/ThreshholdingSNPDataSource.cpp
==================================================================
--- genfile/src/ThreshholdingSNPDataSource.cpp
+++ genfile/src/ThreshholdingSNPDataSource.cpp
@@ -9,10 +9,11 @@
 #include <boost/format.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/SNPDataSource.hpp"
 #include "genfile/VariantDataReader.hpp"
 #include "genfile/ThreshholdingSNPDataSource.hpp"
+#include "genfile/GPThresholdingGTSetter.hpp"
 
 namespace genfile {
 // This SNPDataSource applies a threshhold to genotype calls.
 	ThreshholdingSNPDataSource::ThreshholdingSNPDataSource( SNPDataSource::UniquePtr source, double const threshhold ):
 		m_source( source ),
@@ -43,10 +44,13 @@
 		return metadata ;
 	}
 
 	unsigned int ThreshholdingSNPDataSource::number_of_samples() const {
 		return m_source->number_of_samples() ;
+	}
+	bool ThreshholdingSNPDataSource::has_sample_ids() const {
+		return m_source->has_sample_ids() ;
 	}
 	void ThreshholdingSNPDataSource::get_sample_ids( GetSampleIds getter ) const {
 		return m_source->get_sample_ids( getter ) ;
 	}
 	SNPDataSource::OptionalSnpCount ThreshholdingSNPDataSource::total_number_of_snps() const {
@@ -75,198 +79,11 @@
 				m_threshhold( threshhold )
 			{}
 
 			~ThreshholdingDataReader() {}
 
-			struct Threshholder: public VariantDataReader::PerSampleSetter {
-				Threshholder( PerSampleSetter& target, double const threshhold ):
-					m_target( target ),
-					m_threshhold( threshhold ),
-					m_number_of_alleles(0),
-					m_order_type( eUnknownOrderType ),
-					m_ploidy(0)
-				{
-					if( m_threshhold <= 0.5 ) {
-						throw BadArgumentError(
-							"genfile::ThreshholdingDataReader::Threshholder::Threshholder()",
-							"threshhold",
-							"Only threshholds greater than 0.5 are supported."
-						) ;
-					}
-					assert( m_threshhold > 0.5 ) ;
-				}
-				
-				~Threshholder() throw() {}
-					
-				void initialise( std::size_t nSamples, std::size_t nAlleles ) {
-					m_number_of_alleles = nAlleles ;
-					m_target.initialise( nSamples, nAlleles ) ;
-				} ;
-				bool set_sample( std::size_t i ) {
-					m_target.set_sample( i ) ;
-					m_missing = false ;
-					m_order_type = eUnknownOrderType ;
-					m_ploidy = 0 ;
-					m_entry_i = 0 ;
-					return true ;
-				}
-				void set_number_of_entries( uint32_t ploidy, std::size_t number_of_entries, OrderType const order_type, ValueType const value_type ) {
-					assert( order_type == ePerUnorderedGenotype || ePerPhasedHaplotypePerAllele ) ;
-					assert( value_type == eProbability ) ;
-					m_order_type = order_type ;
-					
-					m_ploidy = ploidy ;
-					m_calls.setZero( number_of_entries ) ;
-					m_target.set_number_of_entries(
-						m_ploidy, m_ploidy,
-						( m_order_type == ePerUnorderedGenotype ) ? ePerUnorderedHaplotype : ePerOrderedHaplotype,
-						eAlleleIndex
-					) ;
-				}
-				void set_value( std::size_t, MissingValue const value ) {
-					m_missing = true ;
-					m_entry_i++ ;
-					if( m_entry_i == m_calls.size() ) { 
-						send_results() ;
-					}
-				}
-				void set_value( std::size_t, std::string& value ) {
-					throw BadArgumentError(
-						"genfile::ThreshholdingDataReader::Threshholder::set_value",
-						"value",
-						"Expected a floating-point value (got a string)."
-					) ;
-				}
-				void set_value( std::size_t, Integer const value ) {
-					throw BadArgumentError(
-						"genfile::ThreshholdingDataReader::Threshholder::set_value",
-						"value",
-						"Expected a floating-point value (got an integer)."
-					) ;
-				}
-				void set_value( std::size_t, double const value ) {
-					m_calls( m_entry_i++ ) = value ;
-					if( m_entry_i == m_calls.size() ) { 
-						send_results() ;
-					}
-				}
-				
-				void finalise() {
-					m_target.finalise() ;
-				}
-			private:
-				PerSampleSetter& m_target ;
-				double const m_threshhold ;
-				std::size_t m_number_of_alleles ;
-				OrderType m_order_type ;
-				uint32_t m_ploidy ;
-				int m_entry_i ;
-				Eigen::VectorXd m_calls ;
-				bool m_missing ;
-				
-			private:
-				void send_results() {
-					if( m_missing || m_calls.array().maxCoeff() < m_threshhold ) {
-						for( uint32_t i = 0 ; i < m_ploidy; ++i ) {
-							m_target.set_value( i, genfile::MissingValue() ) ;
-						}
-					} else {
-						// How to figure out the order here?
-						// Well..it goes like this.
-						if( m_order_type == ePerPhasedHaplotypePerAllele ) {
-							// for phased data it is simple:
-							for( uint32_t i = 0; i < m_ploidy; ++i ) {
-								for( uint32_t j = 0; j < m_number_of_alleles; ++j ) {
-									if( m_calls[i*m_number_of_alleles+j] >= m_threshhold ) {
-										m_target.set_value( i, Integer( j ) ) ;
-										break ;
-									}
-								}
-							}
-						} else if( m_order_type == ePerUnorderedGenotype ) {
-							// For unphased data it is more complex.
-							// We have m_ploidy = n chromosomes in total.
-							// Genotypes are all ways to put n_alleles = k alleles into
-							// those chromosomes.
-							// Represent these as k-vectors that sum to n (i.e. v_i is the count of allele i)
-							// Or (k-1)-vectors that sum to at most n.
-							// The order is chosen so that lower indices are always used first.
-							// 3,0,0 = AAA
-							// 2,1,0 = AAB
-							// 1,2,0 = ABB
-							// 0,3,0 = BBB
-							// 2,0,1 = BBC
-							// 1,1,1 = ABC
-							// 0,2,1 = BBC
-							// 0,1,2 = BCC
-							// 0,0,3 = CCC
-						
-
-							// We fast-path the common (diploid, biallelic) case.
-							if( m_number_of_alleles == 2 && m_ploidy == 2 ) {
-								if( m_calls[0] >= m_threshhold ) {
-									m_target.set_value( 0, Integer(0) ) ;
-									m_target.set_value( 1, Integer(0) ) ;
-								} else if( m_calls[1] >= m_threshhold ) {
-									m_target.set_value( 0, Integer(0) ) ;
-									m_target.set_value( 1, Integer(1) ) ;
-								} else if( m_calls[2] >= m_threshhold ) {
-									m_target.set_value( 0, Integer(1) ) ;
-									m_target.set_value( 1, Integer(1) ) ;
-								} else {
-									m_target.set_value( 0, genfile::MissingValue() ) ;
-									m_target.set_value( 1, genfile::MissingValue() ) ;
-								}
-							} else {
-								// We enumerate vectors in this order and stop when we meet a probabiltiy
-								// meeting the desired threshhold.
-								std::vector< uint16_t > limits( (m_number_of_alleles-1), m_ploidy ) ;
-								std::vector< uint16_t > allele_counts( m_number_of_alleles, 0 ) ;
-								allele_counts[0] = m_ploidy ;
-								bool finished = false ;
-								for( std::size_t index = 0; !finished; ++index ) {
-									if( m_calls[index] >= m_threshhold ) {
-										std::size_t this_index = 0 ;
-										for( std::size_t allele = 0; allele < m_number_of_alleles; ++allele ) {
-											for( uint16_t count = 0; count < allele_counts[allele]; ++count ) {
-												m_target.set_value( ++this_index, Integer( allele )) ;
-											}
-										}
-										break ;
-									}
-									
-									// Move to next possible genotype
-									std::size_t j = 0 ;
-									for( ; j < (m_number_of_alleles-1); ++j ) {
-										uint16_t value = allele_counts[j+1] ;
-										if( value < limits[ j ] ) {
-											++allele_counts[j+1] ;
-											--allele_counts[0] ;
-											for( std::size_t k = 0; k < j; ++k ) {
-												--limits[k] ;
-											}
-											break ;
-										} else {
-											// allele count has reached its limit.
-											// Reset it to zero.
-											// Note that to get here all lower-order counts must be zero.
-											allele_counts[j+1] = 0 ;
-											allele_counts[0] += value ;
-											for( std::size_t k = 0; k < j; ++k ) {
-												limits[k] += value ;
-											}
-										}
-									}
-									if( j == (m_number_of_alleles-1) ) {
-										finished = true ;
-									}
-								}
-							}
-						}
-					}
-				}
-			} ;
+			typedef GPThresholdingGTSetter Threshholder ;
 
 			VariantDataReader& get( std::string const& spec, PerSampleSetter& setter ) {
 				if( spec == ":genotypes:" || spec == "GT" ) {
 					if( !m_source->supports( "GP" )) {
 						throw genfile::BadArgumentError(

Index: genfile/src/VCFFormatSNPDataSink.cpp
==================================================================
--- genfile/src/VCFFormatSNPDataSink.cpp
+++ genfile/src/VCFFormatSNPDataSink.cpp
@@ -168,28 +168,28 @@
 		(*m_stream_ptr) << "##fileformat=VCFv4.2\n" ;
 		
 		std::pair< Metadata::const_iterator, Metadata::const_iterator > const
 			formatDefinitions = std::make_pair( m_metadata.begin(), m_metadata.end() ) ;
 
-		boost::format formatFormat( "##FORMAT=<ID=%s,Type=%s,Number=%s,Description=\"%s\">\n" ) ;
+		boost::format formatFormat( "##FORMAT=<ID=%s,Number=%s,Type=%s,Description=\"%s\">\n" ) ;
 
 #if DEBUG_VCFFORMATSNPDATASINK
 		Metadata::const_iterator format_i = m_metadata.begin() ;
 		std::cerr << "VCFFormatSNPDataSink::write_header(): FORMAT entries are:\n" ;
 		for( ; format_i != m_metadata.end(); ++format_i ) {
 			if( format_i->first == "FORMAT" ) {
-				std::cerr << ( formatFormat % format_i->second.at( "ID" ) % format_i->second.at( "Type" ) % format_i->second.at( "Number" ) % format_i->second.at( "Description" ) ) ;
+				std::cerr << ( formatFormat % format_i->second.at( "ID" ) % format_i->second.at( "Number" ) % format_i->second.at( "Type" ) % format_i->second.at( "Description" ) ) ;
 			}
 		}
 		std::cerr << "\n" ;
 #endif
 
 		if( !m_output_fields ) {
 			Metadata::const_iterator format_i = formatDefinitions.first ;
 			for( ; format_i != formatDefinitions.second; ++format_i ) {
 				if( format_i->first == "FORMAT" ) {
-					(*m_stream_ptr) << ( formatFormat % format_i->second.at( "ID" ) % format_i->second.at( "Type" ) % format_i->second.at( "Number" ) % format_i->second.at( "Description" ) ) ;
+					(*m_stream_ptr) << ( formatFormat % format_i->second.at( "ID" ) % format_i->second.at( "Number" ) % format_i->second.at( "Type" ) % format_i->second.at( "Description" ) ) ;
 				}
 			}
 		} else {
 			std::set< std::string >::const_iterator i = m_output_fields->begin() ;
 			std::set< std::string >::const_iterator end_i = m_output_fields->end() ;
@@ -196,11 +196,11 @@
 			for( ; i != end_i; ++i ) {
 				Metadata::const_iterator format_i = formatDefinitions.first ;
 				bool found = false ;
 				for( ; format_i != formatDefinitions.second; ++format_i ) {
 					if( format_i->first == "FORMAT" && format_i->second.at( "ID" ) == *i ) {
-						(*m_stream_ptr) << ( formatFormat % format_i->second.at( "ID" ) % format_i->second.at( "Type" ) % format_i->second.at( "Number" ) % format_i->second.at( "Description" ) ) ;
+						(*m_stream_ptr) << ( formatFormat % format_i->second.at( "ID" ) % format_i->second.at( "Number" ) % format_i->second.at( "Type" ) % format_i->second.at( "Description" ) ) ;
 						found = true ;
 					}
 				}
 				if( !found ) {
 					std::map< std::string, std::string > unknownFormat ;

Index: genfile/src/VCFFormatSNPDataSource.cpp
==================================================================
--- genfile/src/VCFFormatSNPDataSource.cpp
+++ genfile/src/VCFFormatSNPDataSource.cpp
@@ -146,10 +146,14 @@
 	}
 
 	SNPDataSource::Metadata VCFFormatSNPDataSource::get_metadata() const {
 		return m_metadata ;
 	}
+
+	bool VCFFormatSNPDataSource::has_sample_ids() const {
+		return true ;
+	}
 
 	void VCFFormatSNPDataSource::get_sample_ids( GetSampleIds getter ) const {
 		for( std::size_t i = 9; i < m_column_names.size(); ++i ) {
 			getter( i-9, m_column_names[i] ) ;
 		}
@@ -286,11 +290,11 @@
 			m_have_id_data = true ;
 		}
 
 		// If we get here reading was successful.
 		// Now parse these fields into the result.
-		std::vector< std::string > ids = string_utils::split( m_ID, "," ) ;
+		std::vector< std::string > ids = string_utils::split( m_ID, ";" ) ;
 		VariantIdentifyingData variant ;
 		if( ids.size() == 0 ) {
 			variant.set_primary_id( genfile::string_utils::slice( "." ) ) ;
 		}
 		else {

Index: genfile/src/VariableInSetSampleFilter.cpp
==================================================================
--- genfile/src/VariableInSetSampleFilter.cpp
+++ genfile/src/VariableInSetSampleFilter.cpp
@@ -20,11 +20,10 @@
 	{}
 
 	void VariableInSetSampleFilter::summarise( std::ostream& o ) const {
 		o << m_variable << " IN (" ;
 		Levels::const_iterator i = m_levels.begin() ;
-		Levels::const_iterator end_i = m_levels.end() ;
 		for( std::size_t count = 0; count < std::min( std::size_t( 5 ), m_levels.size() ); ++count, ++i ) {
 			o << ( count > 0 ? ", " : "" ) << *i ;
 		}
 		if( m_levels.size() > 5 ) {
 			o << ", ..." ;

Index: genfile/src/VariantEntry.cpp
==================================================================
--- genfile/src/VariantEntry.cpp
+++ genfile/src/VariantEntry.cpp
@@ -61,33 +61,9 @@
 		int result( integer ) ;
 		assert( result == integer ) ;
 		return result ;
 	}
 	
-	bool VariantEntry::operator==( VariantEntry const& rhs ) const {
-		return m_entrydata == rhs.m_entrydata ;
-	}
-
-	bool VariantEntry::operator!=( VariantEntry const& rhs ) const {
-		return !( m_entrydata == rhs.m_entrydata ) ;
-	}
-	
-	bool VariantEntry::operator<( VariantEntry const& rhs ) const {
-		return m_entrydata < rhs.m_entrydata ;
-	}
-
-	bool VariantEntry::operator<=( VariantEntry const& rhs ) const {
-		return m_entrydata < rhs.m_entrydata || m_entrydata == rhs.m_entrydata ;
-	}
-
-	bool VariantEntry::operator>( VariantEntry const& rhs ) const {
-		return !( m_entrydata < rhs.m_entrydata ) && !( m_entrydata == rhs.m_entrydata ) ;
-	}
-
-	bool VariantEntry::operator>=( VariantEntry const& rhs ) const {
-		return !( m_entrydata < rhs.m_entrydata ) ;
-	}
-	
 	std::ostream& operator<<( std::ostream& ostr, VariantEntry const& entry ) {
 		return ostr << entry.m_entrydata ;
 	}
 }

Index: genfile/src/VariantIdentifyingData.cpp
==================================================================
--- genfile/src/VariantIdentifyingData.cpp
+++ genfile/src/VariantIdentifyingData.cpp
@@ -238,11 +238,10 @@
 	void VariantIdentifyingData::clear_identifiers() {
 		m_data.resize( m_allele_starts.back() ) ;
 	}
 
 	void VariantIdentifyingData::add_identifier( slice const& id ) {
-		assert( id.size() > 0 ) ;
 		std::vector< slice > const& ids = get_identifiers(1) ;
 		if( ids.size() > 0 ) {
 			if( std::find( ids.begin(), ids.end(), id ) == ids.end() ) {
 				m_data += "\t" + std::string( id ) ;
 			}

ADDED   genfile/src/bgen/IndexQuery.cpp
Index: genfile/src/bgen/IndexQuery.cpp
==================================================================
--- genfile/src/bgen/IndexQuery.cpp
+++ genfile/src/bgen/IndexQuery.cpp
@@ -0,0 +1,208 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <memory>
+#include <boost/format.hpp>
+#include <boost/optional.hpp>
+#include "genfile/db/sqlite3.hpp"
+#include "genfile/bgen/IndexQuery.hpp"
+#include "genfile/bgen/Query.hpp"
+
+// #define DEBUG 1
+
+namespace genfile {
+	namespace bgen {
+		IndexQuery::UniquePtr IndexQuery::create(
+			std::string const& filename,
+			Query const& query,
+			IndexQuery::ProgressCallback callback,
+			std::string const& table_name
+		) {
+			return IndexQuery::UniquePtr( new SqliteIndexQuery( filename, query, callback, table_name )) ;
+		}
+
+		SqliteIndexQuery::SqliteIndexQuery(
+			std::string const& filename,
+			Query const& query,
+			SqliteIndexQuery::ProgressCallback callback,
+			std::string const& table_name
+		):
+			m_connection( open_connection( filename ) ),
+			m_metadata( load_metadata( *m_connection ) ),
+			m_index_table_name( table_name ),
+			m_initialised( false )
+		{
+			implement_query( query, callback ) ;
+		}
+		
+		void SqliteIndexQuery::implement_query(
+			Query const& query,
+			SqliteIndexQuery::ProgressCallback callback
+		) {
+			include_ranges( query.included_ranges() ) ;
+			exclude_ranges( query.excluded_ranges() ) ;
+			include_rsids( query.included_rsids() ) ;
+			exclude_ranges( query.excluded_ranges() ) ;
+			initialise( callback ) ;
+		}
+	
+		boost::optional< SqliteIndexQuery::FileMetadata > const&
+		SqliteIndexQuery::file_metadata() const {
+			return m_metadata ;
+		}
+
+		void SqliteIndexQuery::initialise( ProgressCallback callback ) {
+			db::Connection::StatementPtr stmt = build_query() ;
+			if( callback ) {
+				callback( 0, boost::optional< std::size_t >() ) ;
+			}
+			m_positions.reserve( 1000000 ) ;
+			std::size_t batch_i = 0 ;
+			for( stmt->step() ; !stmt->empty(); stmt->step(), ++batch_i ) {
+				int64_t const pos = stmt->get< int64_t >( 0 ) ;
+				int64_t const size = stmt->get< int64_t >( 1 ) ;
+				assert( pos >= 0 ) ;
+				assert( size >= 0 ) ;
+				m_positions.push_back( std::make_pair( int64_t( pos ), int64_t( size ))) ;
+				if( callback ) {
+					callback( m_positions.size(), boost::optional< std::size_t >() ) ;
+				}
+			}
+	#if DEBUG
+			std::cerr << "SqliteIndexQuery::initialise(): read positions for " << m_positions.size() << " variants.\n" ;
+	#endif
+	
+			m_initialised = true ;
+		}
+
+		std::size_t SqliteIndexQuery::number_of_variants() const {
+			assert( m_initialised ) ;
+			return m_positions.size() ;
+		}
+
+		SqliteIndexQuery::FileRange SqliteIndexQuery::locate_variant( std::size_t index ) const {
+	#if DEBUG
+			std::cerr << "SqliteIndexQuery::locate_variant(" << index << ")...\n" ;
+	#endif
+			assert( m_initialised ) ;
+			assert( index < m_positions.size() ) ;
+			return m_positions[index] ;
+		}
+
+		SqliteIndexQuery& SqliteIndexQuery::include_range( GenomicRange const& range ) {
+			m_query_parts.inclusion += ((m_query_parts.inclusion.size() > 0) ? " OR " : "" ) + (
+				boost::format( "( chromosome == '%s' AND position BETWEEN %d AND %d )" ) % range.chromosome() % range.start() % range.end()
+			).str() ;
+			m_initialised = false ;
+			return *this ;
+		}
+
+		SqliteIndexQuery& SqliteIndexQuery::exclude_range( GenomicRange const& range ) {
+			m_query_parts.exclusion += ( m_query_parts.exclusion.size() > 0 ? " AND" : "" ) + (
+				boost::format( " NOT ( chromosome == '%s' AND position BETWEEN %d AND %d )" )
+					% range.chromosome() % range.start() % range.end()
+			).str() ;
+			m_initialised = false ;
+			return *this ;
+		}
+
+		SqliteIndexQuery& SqliteIndexQuery::include_ranges( std::vector< GenomicRange > const& ranges ) {
+			for( std::size_t i = 0; i < ranges.size(); ++i ) {
+				include_range( ranges[i] ) ;
+			}
+			return *this ;
+		}
+
+		SqliteIndexQuery& SqliteIndexQuery::exclude_ranges( std::vector< GenomicRange > const& ranges ) {
+			for( std::size_t i = 0; i < ranges.size(); ++i ) {
+				exclude_range( ranges[i] ) ;
+			}
+			return *this ;
+		}
+
+		SqliteIndexQuery& SqliteIndexQuery::include_rsids( std::vector< std::string > const& ids ) {
+			m_connection->run_statement( "CREATE TEMP TABLE IF NOT EXISTS tmpIncludedId( identifier TEXT NOT NULL PRIMARY KEY ) WITHOUT ROWID" ) ;
+			db::Connection::StatementPtr insert_stmt = m_connection->get_statement( "INSERT INTO tmpIncludedId( identifier ) VALUES( ? )" ) ;
+			for( std::size_t i = 0; i < ids.size(); ++i ) {
+				insert_stmt->bind( 1, ids[i] ).step() ;
+				insert_stmt->reset() ;
+			}
+			if( m_query_parts.join.find( "tmpIncludedId" ) == std::string::npos ) {
+				m_query_parts.join += " LEFT OUTER JOIN tmpIncludedId TI ON TI.identifier == V.rsid" ;
+				m_query_parts.inclusion += ( m_query_parts.inclusion.size() > 0 ? " OR" : "" ) + std::string( " TI.identifier IS NOT NULL" ) ;
+			}
+			m_initialised = false ;
+			return *this ;
+		}
+
+		SqliteIndexQuery& SqliteIndexQuery::exclude_rsids( std::vector< std::string > const& ids ) {
+			m_connection->run_statement( "CREATE TEMP TABLE IF NOT EXISTS tmpExcludedId( identifier TEXT NOT NULL PRIMARY KEY ) WITHOUT ROWID" ) ;
+			db::Connection::StatementPtr insert_stmt = m_connection->get_statement( "INSERT INTO tmpExcludedId( identifier ) VALUES( ? )" ) ;
+			for( std::size_t i = 0; i < ids.size(); ++i ) {
+				insert_stmt->bind( 1, ids[i] ).step() ;
+				insert_stmt->reset() ;
+			}
+			if( m_query_parts.join.find( "tmpExcludedId" ) == std::string::npos ) {
+				m_query_parts.join += " LEFT OUTER JOIN tmpExcludedId TE ON TE.identifier == V.rsid" ;
+				m_query_parts.exclusion += ( m_query_parts.exclusion.size() > 0 ? " AND" : "" ) + std::string( " TE.identifier IS NULL" ) ;
+			}
+			m_initialised = false ;
+			return *this ;
+		}
+
+		db::Connection::UniquePtr SqliteIndexQuery::open_connection( std::string const& filename ) const {
+			db::Connection::UniquePtr result ;
+			try {
+				result = db::Connection::create( "file:" + filename + "?nolock=1", "r" ) ;
+				//result = db::Connection::create( filename, "r" ) ;
+			} catch( db::ConnectionError const& e ) {
+				throw std::invalid_argument( "Could not open the index file \"" + filename + "\"" ) ;
+			}
+			return result ;
+		}
+
+		SqliteIndexQuery::OptionalFileMetadata
+		SqliteIndexQuery::load_metadata( db::Connection& connection ) const {
+			OptionalFileMetadata result ;
+			db::Connection::StatementPtr stmt = connection.get_statement( "SELECT * FROM sqlite_master WHERE name == 'Metadata' AND type == 'table'" ) ;
+			stmt->step() ;
+			if( !stmt->empty() ) {
+				db::Connection::StatementPtr mdStmt = connection.get_statement( "SELECT filename, file_size, last_write_time, first_1000_bytes FROM Metadata" ) ;
+				mdStmt->step() ;
+
+				if( mdStmt->empty() ) {
+					throw std::invalid_argument( "Index file appears malformed (empty \"Metadata\" table)" ) ;
+				}
+				FileMetadata metadata ;
+				// Get metadata fields for comparison
+				metadata.filename = mdStmt->get< std::string >( 0 ) ;
+				metadata.size = mdStmt->get< int64_t >( 1 ) ;
+				metadata.last_write_time = mdStmt->get< int64_t >( 2 ) ;
+				metadata.first_bytes = mdStmt->get< std::vector< uint8_t > >( 3 ) ;
+				
+				result = metadata ;
+			}
+			return result ;
+		}
+
+		db::Connection::StatementPtr SqliteIndexQuery::build_query() const {
+			std::string const select = "SELECT file_start_position, size_in_bytes FROM `"
+				+ m_index_table_name + "` V" ;
+			std::string const inclusion = ( m_query_parts.inclusion.size() > 0 ) ? ("(" + m_query_parts.inclusion + ")") : "" ;
+			std::string const exclusion = ((m_query_parts.inclusion.size() > 0 && m_query_parts.exclusion.size() > 0 ) ? "AND " : "" )
+				+ (( m_query_parts.exclusion.size() > 0 ) ? ("(" + m_query_parts.exclusion + ")") : "" ) ;
+			std::string const where = (inclusion.size() > 0 || exclusion.size() > 0) ? ("WHERE " + inclusion + exclusion) : "" ;
+			std::string const orderBy = "ORDER BY chromosome, position, rsid, allele1, allele2" ;
+			std::string const select_sql = select + " " + m_query_parts.join + " " + where + " " + orderBy ;
+	#if DEBUG
+			std::cerr << "BgenIndex::build_query(): SQL is: \"" << select_sql << "\"...\n" ;
+	#endif
+	
+			return m_connection->get_statement( select_sql ) ;
+		}
+	}
+}
+

ADDED   genfile/src/bgen/View.cpp
Index: genfile/src/bgen/View.cpp
==================================================================
--- genfile/src/bgen/View.cpp
+++ genfile/src/bgen/View.cpp
@@ -0,0 +1,241 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <memory>
+#include <vector>
+#include <string>
+#include <iostream>
+#include <fstream>
+#include <boost/tuple/tuple.hpp>
+#include <boost/format.hpp>
+#include <boost/bind.hpp>
+#include <boost/filesystem.hpp>
+#include "genfile/bgen/bgen.hpp"
+#include "genfile/bgen/IndexQuery.hpp"
+#include "genfile/bgen/Query.hpp"
+#include "genfile/bgen/View.hpp"
+
+namespace genfile {
+	namespace bgen {
+		View::UniquePtr View::create( std::string const& filename ) {
+			return View::UniquePtr( new View( filename )) ;
+		}
+
+		/* View implementation */
+		View::View( std::string const& filename ):
+			m_filename( filename ),
+			m_variant_i(0),
+			m_have_sample_ids( false ),
+			m_state( e_NotOpen )
+		{
+			setup( m_filename ) ;
+			m_file_position = m_stream->tellg() ;
+		}
+
+		std::size_t View::number_of_samples() const {
+			return m_context.number_of_samples ;
+		}
+
+		void View::set_query( Query const& query ) {
+			m_index_query = IndexQuery::create( m_filename + ".bgi", query ) ;
+			if( m_index_query->number_of_variants() > 0 ) {
+				m_stream->seekg( m_index_query->locate_variant(0).first ) ;
+			}
+			m_file_position = m_stream->tellg() ;
+		}
+
+		View::FileMetadata const& View::file_metadata() const {
+			return m_file_metadata ;
+		}
+
+		genfile::bgen::Context const& View::context() const {
+			return m_context ;
+		}
+
+		std::streampos View::current_file_position() const {
+			return m_file_position ;
+		}
+
+		uint32_t View::number_of_variants() const {
+			if( m_index_query.get() ) {
+				return m_index_query->number_of_variants() ;
+			} else {
+				return m_context.number_of_variants ;
+			}
+		}
+
+		std::ostream& View::summarise( std::ostream& o ) const {
+			o << "View: bgen file ("
+				<< ( m_context.flags & genfile::bgen::e_Layout2 ? "layout = 2" : "layout = 1" )
+				<< ", " ;
+			std::string compression = "no" ;
+			if( (m_context.flags & genfile::bgen::e_CompressedSNPBlocks) == genfile::bgen::e_ZlibCompression ) {
+				compression = "zlib" ;
+			} else if( (m_context.flags & genfile::bgen::e_CompressedSNPBlocks) == genfile::bgen::e_ZstdCompression ) {
+				compression = "zstd" ;
+			}
+			o << compression << " compression)" ;
+			o << " with " 
+				<< m_context.number_of_samples << " " << ( m_have_sample_ids ? "named" : "anonymous" ) << " samples and "
+				<< m_context.number_of_variants << " variants.\n" ;
+			if( m_index_query.get() ) {
+				o << "IndexQuery: query will return " << m_index_query->number_of_variants() << " variants.\n" ;
+			}
+			return o ;
+		}
+
+		namespace {
+			// callbacks to avoid using C++11 lambda functions
+			void resize_vector( std::vector< std::string >* target, std::size_t n ) {
+				target->resize(n) ;
+			}
+			
+			void set_vector_element( std::vector< std::string >* target, std::size_t i, std::string const& value ) {
+				target->at(i) = value ;
+			}
+
+			void push_back_vector( std::vector< std::string >* target, std::string const& value ) {
+				target->push_back( value ) ;
+			}
+		}
+
+		bool View::read_variant(
+			std::string* SNPID,
+			std::string* rsid,
+			std::string* chromosome,
+			uint32_t* position,
+			std::vector< std::string >* alleles
+		) {
+			assert( m_state == e_ReadyForVariant ) ;
+
+			if( m_index_query.get() ) {
+				if( m_variant_i == m_index_query->number_of_variants() ) {
+					return false ;
+				}
+				IndexQuery::FileRange const range = m_index_query->locate_variant( m_variant_i ) ;
+				m_stream->seekg( range.first ) ;
+			}
+
+			if(
+				genfile::bgen::read_snp_identifying_data(
+					*m_stream, m_context,
+					SNPID, rsid, chromosome, position,
+//					[&alleles]( std::size_t n ) { alleles->resize( n ) ; },
+					boost::bind( &resize_vector, alleles, _1 ),
+//					[&alleles]( std::size_t i, std::string const& allele ) { alleles->at(i) = allele ; }
+					boost::bind( &set_vector_element, alleles, _1, _2 )
+				)
+			) {
+				m_state = e_ReadyForProbs ;
+				return true ;
+			} else {
+				return false ;
+			}
+		}
+
+		// Read and uncompress genotype probability data, and unpack
+		// it into constituent parts, but don't do a full parse.
+		// This can lead to more efficient code paths than a full parse for some operations.
+		//
+		// Currently this function works for 'layout=2' files, e.g. v1.2 and above only.
+		// Data is returned in the fields of the supplied 'pack' object, which
+		// is defined in bgen.hpp.
+		void View::read_and_unpack_v12_genotype_data_block(
+			genfile::bgen::v12::GenotypeDataBlock* pack
+		) {
+			assert( (m_context.flags & genfile::bgen::e_Layout) == genfile::bgen::e_Layout2 ) ;
+			std::vector< byte_t > const& buffer = read_and_uncompress_genotype_data_block() ;
+			pack->initialise( m_context, &buffer[0], &buffer[0] + buffer.size() ) ;
+			++m_variant_i ;
+		}
+
+		// Ignore genotype probability data for the SNP just read using read_variant()
+		// After calling this method it should be safe to call read_variant()
+		// to fetch the next variant from the file.
+		void View::ignore_genotype_data_block() {
+			assert( m_state == e_ReadyForProbs ) ;
+			genfile::bgen::ignore_genotype_data_block( *m_stream, m_context ) ;
+			m_file_position = m_stream->tellg() ;
+			m_state = e_ReadyForVariant ;
+			++m_variant_i ;
+		}
+
+		// Open the bgen file, read header data and gather metadata.
+		void View::setup( std::string const& filename ) {
+			m_file_metadata.filename = filename ;
+			m_file_metadata.last_write_time = boost::filesystem::last_write_time( filename ) ;
+
+			// Open the stream
+			m_stream.reset(
+				new std::ifstream( filename.c_str(), std::ifstream::binary )
+			) ;
+			if( !*m_stream ) {
+				throw std::invalid_argument( filename ) ;
+			}
+
+			// get file size
+			{
+				std::ios::streampos origin = m_stream->tellg() ;
+				m_stream->seekg( 0, std::ios::end ) ;
+				m_file_metadata.size = m_stream->tellg() - origin ;
+				m_stream->seekg( 0, std::ios::beg ) ;
+			}
+			// read first (up to) 1000 bytes.
+			{
+				m_file_metadata.first_bytes.resize( 1000, 0 ) ;
+				m_stream->read( reinterpret_cast< char* >( &m_file_metadata.first_bytes[0] ), 1000 ) ;
+				m_file_metadata.first_bytes.resize( m_stream->gcount() ) ;
+				m_stream->clear() ;
+			}
+
+			m_state = e_Open ;
+
+			// Read the offset, header, and sample IDs if present.
+			m_stream->seekg( 0, std::ios::beg ) ;
+			genfile::bgen::read_offset( *m_stream, &m_offset ) ;
+			genfile::bgen::read_header_block( *m_stream, &m_context ) ;
+
+			if( m_context.flags & genfile::bgen::e_SampleIdentifiers ) {
+				genfile::bgen::read_sample_identifier_block(
+					*m_stream, m_context,
+					boost::bind( &push_back_vector, &m_sample_ids, _1 )
+					//[this]( std::string id ) { m_sample_ids.push_back( id ) ; }
+				) ;
+				m_have_sample_ids = true ;
+			}
+	
+			// read data up to first data block.
+			m_postheader_data.resize( m_offset+4 - m_stream->tellg() ) ;
+			m_stream->read( reinterpret_cast< char* >( &m_postheader_data[0] ), m_postheader_data.size() ) ;
+			if( m_stream->gcount() != m_postheader_data.size() ) {
+				throw std::invalid_argument(
+					(
+						boost::format(
+							"BGEN file (\"%s\") appears malformed - offset specifies more bytes (%d) than are in the file."
+						) % filename % m_offset
+					).str()
+				) ;
+			}
+
+			// Jump to the first variant data block.
+			// m_stream->seekg( m_offset + 4 ) ;
+
+			// We keep track of state (though it's not really needed for this implementation.)
+			m_state = e_ReadyForVariant ;
+		}
+
+		// Utility function to read and uncompress variant genotype probability data
+		// without further processing.
+		std::vector< byte_t > const& View::read_and_uncompress_genotype_data_block() {
+			assert( m_state == e_ReadyForProbs ) ;
+			genfile::bgen::read_genotype_data_block( *m_stream, m_context, &m_buffer1 ) ;
+			m_file_position = m_stream->tellg() ;
+			m_state = e_ReadyForVariant ;
+			genfile::bgen::uncompress_probability_data( m_context, m_buffer1, &m_buffer2 ) ;
+			return m_buffer2 ;
+		}
+	}
+}

ADDED   genfile/src/db/Connection.cpp
Index: genfile/src/db/Connection.cpp
==================================================================
--- genfile/src/db/Connection.cpp
+++ genfile/src/db/Connection.cpp
@@ -0,0 +1,21 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLite3Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+
+namespace genfile {
+	namespace db {
+		Connection::UniquePtr Connection::create( std::string const& filename, std::string const& mode ) {
+			return Connection::UniquePtr( new SQLite3Connection( filename, true, mode )) ;
+		}
+
+		void Connection::run_statement( std::string const& SQL ) {
+			get_statement( SQL )->step() ;
+		}
+	}
+}

ADDED   genfile/src/db/Error.cpp
Index: genfile/src/db/Error.cpp
==================================================================
--- genfile/src/db/Error.cpp
+++ genfile/src/db/Error.cpp
@@ -0,0 +1,62 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include "genfile/db/SQLite3Statement.hpp"
+#include "genfile/db/Error.hpp"
+
+namespace genfile {
+	namespace db {
+		Error::Error( std::string const& caller, std::string const& db_spec, int error, std::string const& sql ):
+			m_spec( db_spec ),
+			m_error( error ),
+			m_sql( sql )
+		{
+			assert( m_error != SQLite3Statement::Error::OK ) ;
+		}
+	
+		Error::~Error() throw() {}
+	
+		std::string Error::description() const {
+			typedef db::SQLite3Statement::Error Error ;
+			std::string result ;
+			switch( m_error ) {
+				case Error::ERROR: 		result = "SQL error or missing database"; break ;
+				case Error::INTERNAL: 	result = "Internal logic error in SQLite"; break ;
+				case Error::PERM: 		result = "Access permission denied"; break ;
+				case Error::ABORT: 		result = "Callback routine requested an abort"; break ;
+				case Error::BUSY: 		result = "The database file is locked"; break ;
+				case Error::LOCKED: 	result = "A table in the database is locked"; break ;
+				case Error::NOMEM: 		result = "A malloc() failed"; break ;
+				case Error::READONLY: 	result = "Attempt to write a readonly database"; break ;
+				case Error::INTERRUPT: 	result = "Operation terminated by sqlite3_interrupt()"; break ;
+				case Error::IOERR: 		result = "Some kind of disk I/O error occurred"; break ;
+				case Error::CORRUPT: 	result = "The database disk image is malformed"; break ;
+				case Error::NOTFOUND: 	result = "NOT USED. Table or record not found"; break ;
+				case Error::FULL: 		result = "Insertion failed because database is full"; break ;
+				case Error::CANTOPEN: 	result = "Unable to open the database file"; break ;
+				case Error::PROTOCOL: 	result = "Database lock protocol error"; break ;
+				case Error::EMPTY: 		result = "Database is empty"; break ;
+				case Error::SCHEMA: 	result = "The database schema changed"; break ;
+				case Error::TOOBIG: 	result = "String or BLOB exceeds size limit"; break ;
+				case Error::CONSTRAINT: result = "Abort due to constraint violation"; break ;
+				case Error::MISMATCH: 	result = "Data type mismatch"; break ;
+				case Error::MISUSE: 	result = "Library used incorrectly"; break ;
+				case Error::NOLFS: 		result = "Uses OS features not supported on host"; break ;
+				case Error::AUTH: 		result = "Authorization denied"; break ;
+				case Error::FORMAT: 	result = "Auxiliary database format error"; break ;
+				case Error::RANGE: 		result = "2nd parameter to sqlite3_bind out of range"; break ;
+				case Error::NOTADB: 	result = "File opened that is not a database file"; break ;
+				case Error::ROW: 		result = "sqlite3_step() has another row ready"; break ;
+				case Error::DONE: 		result = "sqlite3_step() has finished executing"; break ;
+				default: 				assert(0) ;
+			}
+			result += ", in statement \"" + m_sql + "\"" ;
+			return result ;
+		}
+	}
+}
+

ADDED   genfile/src/db/SQLStatement.cpp
Index: genfile/src/db/SQLStatement.cpp
==================================================================
--- genfile/src/db/SQLStatement.cpp
+++ genfile/src/db/SQLStatement.cpp
@@ -0,0 +1,87 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <cassert>
+#include <string>
+#include <stdint.h>
+#include "sqlite3/sqlite3.h"
+#include "genfile/db/SQLStatement.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/string_utils.hpp"
+
+namespace genfile {
+	namespace db {
+		SQLStatement::~SQLStatement() {}
+	
+		template<>
+		int SQLStatement::get_column< int >( int column_id ) const {
+			return this->get_column_int( column_id ) ;
+		}
+
+		template<>
+		int64_t SQLStatement::get_column< int64_t >( int column_id ) const {
+			return this->get_column_int64( column_id ) ;
+		}
+
+		template<>
+		double SQLStatement::get_column< double >( int column_id ) const {
+			return this->get_column_double( column_id ) ;
+		}
+
+		template<>
+		std::string SQLStatement::get_column< std::string >( int column_id ) const {
+			return this->get_column_string( column_id ) ;
+		}
+
+		template<>
+		char SQLStatement::get_column< char >( int column_id ) const {
+			return this->get_column_char( column_id ) ;
+		}
+	
+		template<>
+		std::vector< uint8_t > SQLStatement::get_column< std::vector< uint8_t > >( int column_id ) const {
+			return this->get_column_blob( column_id ) ;
+		}
+	
+		SQLStatement& SQLStatement::bind( std::size_t i, char const* value ) {
+			bind( i, std::string( value )) ;
+			return *this ;
+		}
+
+		SQLStatement& SQLStatement::bind( std::size_t i, genfile::string_utils::slice const& value ) {
+			bind( i, std::string( value )) ;
+			return *this ;
+		}
+	
+		namespace impl {
+			struct variant_binder: public boost::static_visitor<>
+			{
+				variant_binder( std::size_t index, SQLStatement& statement ): m_index( index ), m_statement( statement ) {}
+				template< typename T >
+				void operator()( T const& value ) {
+					m_statement.bind( m_index, value ) ;
+				}
+				void operator()( genfile::Chromosome const& value ) {
+					m_statement.bind( m_index, std::string( value ) ) ;
+				}
+				void operator()( genfile::MissingValue const& value ) {
+					m_statement.bind_NULL( m_index ) ;
+				}
+				void operator()( genfile::GenomePosition const& value ) {
+					m_statement.bind( m_index, genfile::string_utils::to_string( value ) ) ;
+				}
+			private:
+				std::size_t const m_index ;
+				SQLStatement& m_statement ;
+			} ;
+		}
+
+		SQLStatement& SQLStatement::bind( std::size_t index, genfile::VariantEntry const& value ) {
+			genfile::apply_visitor( impl::variant_binder( index, *this ), value ) ;
+			return *this ;
+		}
+	}
+}

ADDED   genfile/src/db/SQLite3Connection.cpp
Index: genfile/src/db/SQLite3Connection.cpp
==================================================================
--- genfile/src/db/SQLite3Connection.cpp
+++ genfile/src/db/SQLite3Connection.cpp
@@ -0,0 +1,161 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <stdint.h>
+#include <boost/date_time/posix_time/posix_time_types.hpp>
+#include <boost/thread/thread_time.hpp>
+#include <boost/thread/thread.hpp>
+#include "genfile/db/SQLite3Connection.hpp"
+#include "genfile/db/SQLite3Statement.hpp"
+#include "genfile/db/Error.hpp"
+
+extern "C" {
+	void sqlite3_trace_callback( void* udp, const char* sql ) {
+		std::cerr << "SQLite3 trace: SQL = \"" << sql << "\".\n" ;
+	}
+	
+	int sqlite3_busy_callback( void*, int number_of_tries ) {
+		if( number_of_tries > 10 ) {
+			return 0 ;
+		}
+		boost::this_thread::sleep( boost::posix_time::milliseconds( 10 ) ) ;
+		return 1 ;
+	}
+}
+
+namespace genfile {
+	namespace db {
+		SQLite3Connection::SQLite3Connection( std::string const& filename, bool overwrite, std::string const& mode ):
+			m_filename( filename ),
+			m_db_connection(0),
+			m_managed( true )
+		{
+			open_db_connection( filename, overwrite, mode ) ;
+		}
+
+		SQLite3Connection::~SQLite3Connection() {
+			close_db_connection_if_necessary() ;
+		}
+
+	
+		SQLite3Connection::StatementPtr SQLite3Connection::get_statement( std::string const& SQL ) {
+			return StatementPtr( new SQLite3Statement( this, SQL ) ) ;
+		}	
+
+		Connection::RowId SQLite3Connection::get_last_insert_row_id() const {
+			uint64_t result = sqlite3_last_insert_rowid( m_db_connection ) ;
+			return result ;
+		}
+
+		sqlite3_stmt* SQLite3Connection::prepare_sql( std::string const& SQL ) const {
+			assert( m_db_connection != 0 ) ;
+			sqlite3_stmt* statement ;
+			int code = sqlite3_prepare_v2(
+				m_db_connection,
+				SQL.c_str(),
+				static_cast< int >( SQL.size()+1 ), // +1 accounts for null terminating byte.
+				&statement,
+				0 // ignore pzTail
+			) ;
+			if( code != SQLITE_OK ) {
+				throw StatementPreparationError( "SQLite3Connection::prepare_sql()", get_spec(), code, SQL ) ;
+			}
+			// SQLite might return 0 if the SQL consisted of comments and whitespace only
+			// but I want to treat this as a programmer error.
+			assert( statement != 0 ) ;
+			return statement ;
+		}
+
+		int SQLite3Connection::finalise_statement( sqlite3_stmt* statement ) {
+			assert( statement != 0 ) ;
+			return sqlite3_finalize( statement ) ;
+		}
+
+		int SQLite3Connection::step_statement( sqlite3_stmt* statement ) {
+			int code = sqlite3_step( statement ) ;
+			if( code != SQLITE_ROW && code != SQLITE_DONE ) {
+				throw StatementStepError( "SQLite3Connection::step_statement()", get_spec(), code, std::string( sqlite3_sql( statement ) ) ) ;
+			}
+			return (code == SQLITE_ROW);
+		}
+	
+		void SQLite3Connection::open_db_connection( std::string const& filename, bool overwrite, std::string const& mode ) {
+			int flags = 0 ;
+			if( mode == "r" ) {
+				flags |= SQLITE_OPEN_READONLY ;
+			} else if( mode == "rw" ) {
+				flags |= SQLITE_OPEN_READWRITE ;
+				if( overwrite ) {
+					flags |= SQLITE_OPEN_CREATE ;
+				}
+			} else {
+				assert( 0 ) ;
+			}
+			int code = sqlite3_open_v2( filename.c_str(), &m_db_connection, flags, NULL ) ;
+			if( code != SQLITE_OK ) {
+				throw ConnectionError( "SQLite3Connection::open_db_connection()", get_spec(), code ) ;
+			}
+			// We add a busy handler.  This makes the database more robust by retrying failed transactions.
+			sqlite3_busy_handler( m_db_connection, &sqlite3_busy_callback, NULL ) ;
+			// Uncomment the next line to trace SQL statements executed.
+			//sqlite3_trace( m_db_connection, &sqlite3_trace_callback, NULL ) ;
+		}
+
+		void SQLite3Connection::close_db_connection_if_necessary() {
+			if( m_managed && m_db_connection != 0 ) {
+				// According to SQLite docs, we must finalise any prepared statements
+				// before we can close the db connection.
+				finalise_prepared_statements() ;
+				sqlite3_close( m_db_connection ) ;
+				m_db_connection = 0 ;
+			}
+		}
+
+		void SQLite3Connection::finalise_prepared_statements() {
+			assert( m_db_connection != 0 ) ;
+	#if SQLITE_VERSION_NUMBER > 3006000
+			sqlite3_stmt* statement ;
+			while(( statement = sqlite3_next_stmt( m_db_connection, 0)) != 0 ) {
+				finalise_statement( statement ) ;
+			}
+	#endif
+		}
+	
+		SQLite3Connection::ScopedTransactionPtr SQLite3Connection::open_transaction( double max_seconds_to_wait ) {		
+			ScopedTransactionPtr transaction ;
+			// we wait 10 milliseconds between attempts.
+		
+			for( std::size_t count = 0 ; true; ++count ) {
+				try {
+					transaction.reset( new SQLite3Connection::Transaction( *this ) ) ;
+					break ;
+				}
+				catch( db::StatementStepError const& e ) {
+					// Because of the busy handler (see top of this file)
+					// each attempt takes ~0.1s anyway
+					// We wait an additional 0.1s so that each attempt takes 0.2s in total.
+					if( ( count * 0.2 ) > max_seconds_to_wait ) {
+						std::cerr << "Open transaction: failure count=" << count << " (~" << count*0.2 << "s).  Bailing out.\n" ;
+						boost::this_thread::sleep( boost::posix_time::milliseconds( 100 ) ) ;
+						throw TransactionError( "SQLite3Connection::open_transaction()", get_spec(), e.error_code(), e.sql() ) ;
+					}
+				}
+			}
+			return transaction ;
+		}
+	
+		SQLite3Connection::Transaction::Transaction( SQLite3Connection& connection ):
+			m_connection( connection )
+		{
+			m_connection.run_statement( "BEGIN IMMEDIATE TRANSACTION" ) ;
+		}
+	
+		SQLite3Connection::Transaction::~Transaction() {
+			m_connection.run_statement( "COMMIT" ) ;
+		}
+	}
+}

ADDED   genfile/src/db/SQLite3Statement.cpp
Index: genfile/src/db/SQLite3Statement.cpp
==================================================================
--- genfile/src/db/SQLite3Statement.cpp
+++ genfile/src/db/SQLite3Statement.cpp
@@ -0,0 +1,193 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <cassert>
+#include <string>
+#include <exception>
+
+#include "sqlite3/sqlite3.h"
+#include "genfile/string_utils/string_utils.hpp"
+#include "genfile/db/SQLite3Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+#include "genfile/db/SQLite3Statement.hpp"
+#include "genfile/db/SQLite3Error.hpp"
+
+namespace genfile {
+	namespace db {
+		SQLite3Statement::SQLite3Statement( SQLite3Connection* connection, std::string const& SQL ):
+			m_connection( connection ),
+			m_have_results( false )
+		{
+			assert( m_connection ) ;
+			m_statement = m_connection->prepare_sql( SQL ) ;
+			//std::cerr << "SQLite3Statement::SQLite3Statement(): statement is \"" + SQL + "\".\n" ;
+			assert( m_statement != 0 ) ;
+		}
+	
+		SQLite3Statement::~SQLite3Statement() {
+			m_connection->finalise_statement( m_statement ) ;
+		}
+
+		bool SQLite3Statement::step() {
+			m_have_results = m_connection->step_statement( m_statement ) ;
+			return m_have_results ;
+		}
+
+		bool SQLite3Statement::empty() const {
+			return !m_have_results ;
+		}
+
+		std::size_t SQLite3Statement::get_number_of_columns() const {
+			return std::size_t( get_column_count() ) ;
+		}
+
+		std::string SQLite3Statement::get_name_of_column( std::size_t i ) const {
+			assert( m_statement != 0 ) ;
+			assert( i < get_number_of_columns() ) ;
+			return std::string( sqlite3_column_origin_name( m_statement, i )) ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind( std::size_t i, int32_t value ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_int( m_statement, i, value ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind( std::size_t i, uint32_t value ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_int( m_statement, i, value ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind( std::size_t i, int64_t value ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_int64( m_statement, i, sqlite3_int64( value ) ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind( std::size_t i, uint64_t value ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_int64( m_statement, i, sqlite3_int64( value ) ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind( std::size_t i, double value ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_double( m_statement, i, value ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind( std::size_t i, std::string const& value ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_text( m_statement, i, value.c_str(), value.size(), SQLITE_TRANSIENT ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind( std::size_t i, char const* buffer, char const* const end ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_blob( m_statement, i, reinterpret_cast< void const* >( buffer ), int( end - buffer ), SQLITE_TRANSIENT ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind( std::size_t i, uint8_t const* buffer, uint8_t const* const end ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_blob( m_statement, i, reinterpret_cast< void const* >( buffer ), int( end - buffer ), SQLITE_TRANSIENT ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::bind_NULL( std::size_t i ) {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_bind_null( m_statement, i ) ;
+			if( error != SQLITE_OK ) {
+				throw ValueBindError( "SQLite3Statement::bind()", m_connection->get_spec(), error, genfile::string_utils::to_string( i ) ) ;
+			}
+			return *this ;
+		}
+
+		SQLite3Statement& SQLite3Statement::reset() {
+			assert( m_statement != 0 ) ;
+			int error = sqlite3_reset( m_statement ) ;
+			if( error != SQLITE_OK ) {
+				throw db::Error( "SQLite3Statement::reset()", m_connection->get_spec(), error ) ;
+			}
+			return *this ;
+		}
+
+		std::string SQLite3Statement::get_sql() const {
+			assert( m_statement != 0 ) ;
+			return std::string( sqlite3_sql( m_statement )) ;
+		}
+
+		bool SQLite3Statement::is_null( int column_id ) const {
+			return ( sqlite3_column_type( m_statement, column_id ) == SQLITE_NULL ) ;
+		}
+
+		int SQLite3Statement::get_column_int( int column_id ) const {
+			assert( m_statement != 0 ) ;
+			return sqlite3_column_int( m_statement, column_id ) ;
+		}
+
+		int64_t SQLite3Statement::get_column_int64( int column_id ) const {
+			assert( m_statement != 0 ) ;
+			return sqlite3_column_int64( m_statement, column_id ) ;
+		}
+
+		double SQLite3Statement::get_column_double( int column_id ) const {
+			assert( m_statement != 0 ) ;
+			return sqlite3_column_double( m_statement, column_id ) ;
+		}
+	
+		std::string SQLite3Statement::get_column_string( int column_id ) const {
+			assert( m_statement != 0 ) ;
+			return reinterpret_cast< char const * >( sqlite3_column_text( m_statement, column_id ) ) ;
+		}
+
+		char SQLite3Statement::get_column_char( int column_id ) const {
+			assert( m_statement != 0 ) ;
+			char const* p = reinterpret_cast< char const * >( sqlite3_column_text( m_statement, column_id )) ;
+			int bytes = sqlite3_column_bytes( m_statement, column_id ) ;
+			assert( bytes == 1 ) ;
+			return *p ;
+		}
+	
+		std::vector< uint8_t > SQLite3Statement::get_column_blob( int column_id ) const {
+			assert( m_statement != 0 ) ;
+			uint8_t const* p = reinterpret_cast< uint8_t const* >( sqlite3_column_blob( m_statement, column_id )) ;
+			int nBytes = sqlite3_column_bytes( m_statement, column_id ) ;
+			return std::vector< uint8_t >( p, p+nBytes ) ;
+		}
+	
+		int SQLite3Statement::get_column_count() const {
+			assert( m_statement != 0 ) ;
+			return sqlite3_column_count( m_statement ) ;
+		}
+	}
+}

ADDED   genfile/src/db/fill_SQL.cpp
Index: genfile/src/db/fill_SQL.cpp
==================================================================
--- genfile/src/db/fill_SQL.cpp
+++ genfile/src/db/fill_SQL.cpp
@@ -0,0 +1,27 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include "genfile/db/fill_SQL.hpp"
+
+namespace genfile {
+	namespace db {
+		std::string fill_SQL( std::string SQL ) {
+			return SQL ;
+		}
+
+		std::string fill_SQL( std::string SQL, std::string const& value1 ) {
+			std::size_t pos = SQL.find( "%s" ) ;
+			assert( pos != std::string::npos ) ;
+			SQL.replace( pos, 2, "\"" + value1 + "\"" ) ;
+			return SQL ;
+		}
+
+		std::string fill_SQL( std::string SQL, char const* value1 ) {
+			return fill_SQL( SQL, std::string( value1 )) ;
+		}
+	}
+}

ADDED   genfile/src/db/get_unique_id.cpp
Index: genfile/src/db/get_unique_id.cpp
==================================================================
--- genfile/src/db/get_unique_id.cpp
+++ genfile/src/db/get_unique_id.cpp
@@ -0,0 +1,33 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+#include "genfile/db/get_unique_id.hpp"
+#include "genfile/Error.hpp"
+
+namespace genfile {
+	namespace db {
+		int get_unique_id(
+			Connection* connection,
+			std::string const& table,
+			std::string const& id_column,
+			std::string const& where_clause
+		) {
+			db::Connection::StatementPtr statement = connection->get_statement(
+				"SELECT " + id_column + " FROM " + table + " " + where_clause + ";"
+			) ;
+			if( !statement->step() ) {
+				throw genfile::DuplicateKeyError( "db::get_unique_id()", connection->get_spec() + ", <where clause> = \"" + where_clause + "\"" ) ;
+			}
+			int result = statement->get_column< int >( 0 ) ;
+			if( statement->step() ) {
+				throw genfile::DuplicateKeyError( "db::get_unique_id()", connection->get_spec() + ", <where clause> = \"" + where_clause + "\"" ) ;
+			}
+			return result ;
+		}
+	}
+}

Index: genfile/src/vcf/CallReader.cpp
==================================================================
--- genfile/src/vcf/CallReader.cpp
+++ genfile/src/vcf/CallReader.cpp
@@ -250,16 +250,26 @@
 		}
 		
 		void CallReader::load_genotypes() {
 			// Find the GT field in the format string...
 			std::size_t const GT_field_pos = std::find( m_format_elts.begin(), m_format_elts.end(), "GT" ) - m_format_elts.begin() ;
-			// ...it is required to be the first field.
-			if( GT_field_pos != 0 ) {
+
+			m_ploidy.resize( m_number_of_samples ) ;
+			if( GT_field_pos == m_format_elts.size() ) {
+				// GT not present.
+				// assume ploidy=2
+				std::fill(
+					m_ploidy.begin(),
+					m_ploidy.end(),
+					2
+				) ;
+				return ;
+			} else if( GT_field_pos != 0 ) {
+				// ...else it is required to be the first field.
 				throw MalformedInputError( "(data)", 0 ) ;
 			}
 
-			m_ploidy.resize( m_number_of_samples ) ;
 			m_order_types.resize( m_number_of_samples ) ;
 			m_genotype_calls.reserve( m_number_of_samples * 2 ) ;
 			std::size_t total_number_of_calls = 0 ;
 			impl::CallReaderGenotypeSetter genotype_setter( m_genotype_calls, m_ploidy ) ;
 			for(

ADDED   genfile/test/catch.hpp
Index: genfile/test/catch.hpp
==================================================================
--- genfile/test/catch.hpp
+++ genfile/test/catch.hpp
@@ -0,0 +1,17970 @@
+/*
+ *  Catch v2.13.9
+ *  Generated: 2022-04-12 22:37:23.260201
+ *  ----------------------------------------------------------
+ *  This file has been merged from multiple headers. Please don't edit it directly
+ *  Copyright (c) 2022 Two Blue Cubes Ltd. All rights reserved.
+ *
+ *  Distributed under the Boost Software License, Version 1.0. (See accompanying
+ *  file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+ */
+#ifndef TWOBLUECUBES_SINGLE_INCLUDE_CATCH_HPP_INCLUDED
+#define TWOBLUECUBES_SINGLE_INCLUDE_CATCH_HPP_INCLUDED
+// start catch.hpp
+
+
+#define CATCH_VERSION_MAJOR 2
+#define CATCH_VERSION_MINOR 13
+#define CATCH_VERSION_PATCH 9
+
+#ifdef __clang__
+#    pragma clang system_header
+#elif defined __GNUC__
+#    pragma GCC system_header
+#endif
+
+// start catch_suppress_warnings.h
+
+#ifdef __clang__
+#   ifdef __ICC // icpc defines the __clang__ macro
+#       pragma warning(push)
+#       pragma warning(disable: 161 1682)
+#   else // __ICC
+#       pragma clang diagnostic push
+#       pragma clang diagnostic ignored "-Wpadded"
+#       pragma clang diagnostic ignored "-Wswitch-enum"
+#       pragma clang diagnostic ignored "-Wcovered-switch-default"
+#    endif
+#elif defined __GNUC__
+     // Because REQUIREs trigger GCC's -Wparentheses, and because still
+     // supported version of g++ have only buggy support for _Pragmas,
+     // Wparentheses have to be suppressed globally.
+#    pragma GCC diagnostic ignored "-Wparentheses" // See #674 for details
+
+#    pragma GCC diagnostic push
+#    pragma GCC diagnostic ignored "-Wunused-variable"
+#    pragma GCC diagnostic ignored "-Wpadded"
+#endif
+// end catch_suppress_warnings.h
+#if defined(CATCH_CONFIG_MAIN) || defined(CATCH_CONFIG_RUNNER)
+#  define CATCH_IMPL
+#  define CATCH_CONFIG_ALL_PARTS
+#endif
+
+// In the impl file, we want to have access to all parts of the headers
+// Can also be used to sanely support PCHs
+#if defined(CATCH_CONFIG_ALL_PARTS)
+#  define CATCH_CONFIG_EXTERNAL_INTERFACES
+#  if defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#    undef CATCH_CONFIG_DISABLE_MATCHERS
+#  endif
+#  if !defined(CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER)
+#    define CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER
+#  endif
+#endif
+
+#if !defined(CATCH_CONFIG_IMPL_ONLY)
+// start catch_platform.h
+
+// See e.g.:
+// https://opensource.apple.com/source/CarbonHeaders/CarbonHeaders-18.1/TargetConditionals.h.auto.html
+#ifdef __APPLE__
+#  include <TargetConditionals.h>
+#  if (defined(TARGET_OS_OSX) && TARGET_OS_OSX == 1) || \
+      (defined(TARGET_OS_MAC) && TARGET_OS_MAC == 1)
+#    define CATCH_PLATFORM_MAC
+#  elif (defined(TARGET_OS_IPHONE) && TARGET_OS_IPHONE == 1)
+#    define CATCH_PLATFORM_IPHONE
+#  endif
+
+#elif defined(linux) || defined(__linux) || defined(__linux__)
+#  define CATCH_PLATFORM_LINUX
+
+#elif defined(WIN32) || defined(__WIN32__) || defined(_WIN32) || defined(_MSC_VER) || defined(__MINGW32__)
+#  define CATCH_PLATFORM_WINDOWS
+#endif
+
+// end catch_platform.h
+
+#ifdef CATCH_IMPL
+#  ifndef CLARA_CONFIG_MAIN
+#    define CLARA_CONFIG_MAIN_NOT_DEFINED
+#    define CLARA_CONFIG_MAIN
+#  endif
+#endif
+
+// start catch_user_interfaces.h
+
+namespace Catch {
+    unsigned int rngSeed();
+}
+
+// end catch_user_interfaces.h
+// start catch_tag_alias_autoregistrar.h
+
+// start catch_common.h
+
+// start catch_compiler_capabilities.h
+
+// Detect a number of compiler features - by compiler
+// The following features are defined:
+//
+// CATCH_CONFIG_COUNTER : is the __COUNTER__ macro supported?
+// CATCH_CONFIG_WINDOWS_SEH : is Windows SEH supported?
+// CATCH_CONFIG_POSIX_SIGNALS : are POSIX signals supported?
+// CATCH_CONFIG_DISABLE_EXCEPTIONS : Are exceptions enabled?
+// ****************
+// Note to maintainers: if new toggles are added please document them
+// in configuration.md, too
+// ****************
+
+// In general each macro has a _NO_<feature name> form
+// (e.g. CATCH_CONFIG_NO_POSIX_SIGNALS) which disables the feature.
+// Many features, at point of detection, define an _INTERNAL_ macro, so they
+// can be combined, en-mass, with the _NO_ forms later.
+
+#ifdef __cplusplus
+
+#  if (__cplusplus >= 201402L) || (defined(_MSVC_LANG) && _MSVC_LANG >= 201402L)
+#    define CATCH_CPP14_OR_GREATER
+#  endif
+
+#  if (__cplusplus >= 201703L) || (defined(_MSVC_LANG) && _MSVC_LANG >= 201703L)
+#    define CATCH_CPP17_OR_GREATER
+#  endif
+
+#endif
+
+// Only GCC compiler should be used in this block, so other compilers trying to
+// mask themselves as GCC should be ignored.
+#if defined(__GNUC__) && !defined(__clang__) && !defined(__ICC) && !defined(__CUDACC__) && !defined(__LCC__)
+#    define CATCH_INTERNAL_START_WARNINGS_SUPPRESSION _Pragma( "GCC diagnostic push" )
+#    define CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION  _Pragma( "GCC diagnostic pop" )
+
+#    define CATCH_INTERNAL_IGNORE_BUT_WARN(...) (void)__builtin_constant_p(__VA_ARGS__)
+
+#endif
+
+#if defined(__clang__)
+
+#    define CATCH_INTERNAL_START_WARNINGS_SUPPRESSION _Pragma( "clang diagnostic push" )
+#    define CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION  _Pragma( "clang diagnostic pop" )
+
+// As of this writing, IBM XL's implementation of __builtin_constant_p has a bug
+// which results in calls to destructors being emitted for each temporary,
+// without a matching initialization. In practice, this can result in something
+// like `std::string::~string` being called on an uninitialized value.
+//
+// For example, this code will likely segfault under IBM XL:
+// ```
+// REQUIRE(std::string("12") + "34" == "1234")
+// ```
+//
+// Therefore, `CATCH_INTERNAL_IGNORE_BUT_WARN` is not implemented.
+#  if !defined(__ibmxl__) && !defined(__CUDACC__)
+#    define CATCH_INTERNAL_IGNORE_BUT_WARN(...) (void)__builtin_constant_p(__VA_ARGS__) /* NOLINT(cppcoreguidelines-pro-type-vararg, hicpp-vararg) */
+#  endif
+
+#    define CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wexit-time-destructors\"" ) \
+         _Pragma( "clang diagnostic ignored \"-Wglobal-constructors\"")
+
+#    define CATCH_INTERNAL_SUPPRESS_PARENTHESES_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wparentheses\"" )
+
+#    define CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wunused-variable\"" )
+
+#    define CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wgnu-zero-variadic-macro-arguments\"" )
+
+#    define CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+         _Pragma( "clang diagnostic ignored \"-Wunused-template\"" )
+
+#endif // __clang__
+
+////////////////////////////////////////////////////////////////////////////////
+// Assume that non-Windows platforms support posix signals by default
+#if !defined(CATCH_PLATFORM_WINDOWS)
+    #define CATCH_INTERNAL_CONFIG_POSIX_SIGNALS
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// We know some environments not to support full POSIX signals
+#if defined(__CYGWIN__) || defined(__QNX__) || defined(__EMSCRIPTEN__) || defined(__DJGPP__)
+    #define CATCH_INTERNAL_CONFIG_NO_POSIX_SIGNALS
+#endif
+
+#ifdef __OS400__
+#       define CATCH_INTERNAL_CONFIG_NO_POSIX_SIGNALS
+#       define CATCH_CONFIG_COLOUR_NONE
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// Android somehow still does not support std::to_string
+#if defined(__ANDROID__)
+#    define CATCH_INTERNAL_CONFIG_NO_CPP11_TO_STRING
+#    define CATCH_INTERNAL_CONFIG_ANDROID_LOGWRITE
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// Not all Windows environments support SEH properly
+#if defined(__MINGW32__)
+#    define CATCH_INTERNAL_CONFIG_NO_WINDOWS_SEH
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// PS4
+#if defined(__ORBIS__)
+#    define CATCH_INTERNAL_CONFIG_NO_NEW_CAPTURE
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// Cygwin
+#ifdef __CYGWIN__
+
+// Required for some versions of Cygwin to declare gettimeofday
+// see: http://stackoverflow.com/questions/36901803/gettimeofday-not-declared-in-this-scope-cygwin
+#   define _BSD_SOURCE
+// some versions of cygwin (most) do not support std::to_string. Use the libstd check.
+// https://gcc.gnu.org/onlinedocs/gcc-4.8.2/libstdc++/api/a01053_source.html line 2812-2813
+# if !((__cplusplus >= 201103L) && defined(_GLIBCXX_USE_C99) \
+           && !defined(_GLIBCXX_HAVE_BROKEN_VSWPRINTF))
+
+#    define CATCH_INTERNAL_CONFIG_NO_CPP11_TO_STRING
+
+# endif
+#endif // __CYGWIN__
+
+////////////////////////////////////////////////////////////////////////////////
+// Visual C++
+#if defined(_MSC_VER)
+
+// Universal Windows platform does not support SEH
+// Or console colours (or console at all...)
+#  if defined(WINAPI_FAMILY) && (WINAPI_FAMILY == WINAPI_FAMILY_APP)
+#    define CATCH_CONFIG_COLOUR_NONE
+#  else
+#    define CATCH_INTERNAL_CONFIG_WINDOWS_SEH
+#  endif
+
+#  if !defined(__clang__) // Handle Clang masquerading for msvc
+
+// MSVC traditional preprocessor needs some workaround for __VA_ARGS__
+// _MSVC_TRADITIONAL == 0 means new conformant preprocessor
+// _MSVC_TRADITIONAL == 1 means old traditional non-conformant preprocessor
+#    if !defined(_MSVC_TRADITIONAL) || (defined(_MSVC_TRADITIONAL) && _MSVC_TRADITIONAL)
+#      define CATCH_INTERNAL_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#    endif // MSVC_TRADITIONAL
+
+// Only do this if we're not using clang on Windows, which uses `diagnostic push` & `diagnostic pop`
+#    define CATCH_INTERNAL_START_WARNINGS_SUPPRESSION __pragma( warning(push) )
+#    define CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION  __pragma( warning(pop) )
+#  endif // __clang__
+
+#endif // _MSC_VER
+
+#if defined(_REENTRANT) || defined(_MSC_VER)
+// Enable async processing, as -pthread is specified or no additional linking is required
+# define CATCH_INTERNAL_CONFIG_USE_ASYNC
+#endif // _MSC_VER
+
+////////////////////////////////////////////////////////////////////////////////
+// Check if we are compiled with -fno-exceptions or equivalent
+#if defined(__EXCEPTIONS) || defined(__cpp_exceptions) || defined(_CPPUNWIND)
+#  define CATCH_INTERNAL_CONFIG_EXCEPTIONS_ENABLED
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+// DJGPP
+#ifdef __DJGPP__
+#  define CATCH_INTERNAL_CONFIG_NO_WCHAR
+#endif // __DJGPP__
+
+////////////////////////////////////////////////////////////////////////////////
+// Embarcadero C++Build
+#if defined(__BORLANDC__)
+    #define CATCH_INTERNAL_CONFIG_POLYFILL_ISNAN
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+
+// Use of __COUNTER__ is suppressed during code analysis in
+// CLion/AppCode 2017.2.x and former, because __COUNTER__ is not properly
+// handled by it.
+// Otherwise all supported compilers support COUNTER macro,
+// but user still might want to turn it off
+#if ( !defined(__JETBRAINS_IDE__) || __JETBRAINS_IDE__ >= 20170300L )
+    #define CATCH_INTERNAL_CONFIG_COUNTER
+#endif
+
+////////////////////////////////////////////////////////////////////////////////
+
+// RTX is a special version of Windows that is real time.
+// This means that it is detected as Windows, but does not provide
+// the same set of capabilities as real Windows does.
+#if defined(UNDER_RTSS) || defined(RTX64_BUILD)
+    #define CATCH_INTERNAL_CONFIG_NO_WINDOWS_SEH
+    #define CATCH_INTERNAL_CONFIG_NO_ASYNC
+    #define CATCH_CONFIG_COLOUR_NONE
+#endif
+
+#if !defined(_GLIBCXX_USE_C99_MATH_TR1)
+#define CATCH_INTERNAL_CONFIG_GLOBAL_NEXTAFTER
+#endif
+
+// Various stdlib support checks that require __has_include
+#if defined(__has_include)
+  // Check if string_view is available and usable
+  #if __has_include(<string_view>) && defined(CATCH_CPP17_OR_GREATER)
+  #    define CATCH_INTERNAL_CONFIG_CPP17_STRING_VIEW
+  #endif
+
+  // Check if optional is available and usable
+  #  if __has_include(<optional>) && defined(CATCH_CPP17_OR_GREATER)
+  #    define CATCH_INTERNAL_CONFIG_CPP17_OPTIONAL
+  #  endif // __has_include(<optional>) && defined(CATCH_CPP17_OR_GREATER)
+
+  // Check if byte is available and usable
+  #  if __has_include(<cstddef>) && defined(CATCH_CPP17_OR_GREATER)
+  #    include <cstddef>
+  #    if defined(__cpp_lib_byte) && (__cpp_lib_byte > 0)
+  #      define CATCH_INTERNAL_CONFIG_CPP17_BYTE
+  #    endif
+  #  endif // __has_include(<cstddef>) && defined(CATCH_CPP17_OR_GREATER)
+
+  // Check if variant is available and usable
+  #  if __has_include(<variant>) && defined(CATCH_CPP17_OR_GREATER)
+  #    if defined(__clang__) && (__clang_major__ < 8)
+         // work around clang bug with libstdc++ https://bugs.llvm.org/show_bug.cgi?id=31852
+         // fix should be in clang 8, workaround in libstdc++ 8.2
+  #      include <ciso646>
+  #      if defined(__GLIBCXX__) && defined(_GLIBCXX_RELEASE) && (_GLIBCXX_RELEASE < 9)
+  #        define CATCH_CONFIG_NO_CPP17_VARIANT
+  #      else
+  #        define CATCH_INTERNAL_CONFIG_CPP17_VARIANT
+  #      endif // defined(__GLIBCXX__) && defined(_GLIBCXX_RELEASE) && (_GLIBCXX_RELEASE < 9)
+  #    else
+  #      define CATCH_INTERNAL_CONFIG_CPP17_VARIANT
+  #    endif // defined(__clang__) && (__clang_major__ < 8)
+  #  endif // __has_include(<variant>) && defined(CATCH_CPP17_OR_GREATER)
+#endif // defined(__has_include)
+
+#if defined(CATCH_INTERNAL_CONFIG_COUNTER) && !defined(CATCH_CONFIG_NO_COUNTER) && !defined(CATCH_CONFIG_COUNTER)
+#   define CATCH_CONFIG_COUNTER
+#endif
+#if defined(CATCH_INTERNAL_CONFIG_WINDOWS_SEH) && !defined(CATCH_CONFIG_NO_WINDOWS_SEH) && !defined(CATCH_CONFIG_WINDOWS_SEH) && !defined(CATCH_INTERNAL_CONFIG_NO_WINDOWS_SEH)
+#   define CATCH_CONFIG_WINDOWS_SEH
+#endif
+// This is set by default, because we assume that unix compilers are posix-signal-compatible by default.
+#if defined(CATCH_INTERNAL_CONFIG_POSIX_SIGNALS) && !defined(CATCH_INTERNAL_CONFIG_NO_POSIX_SIGNALS) && !defined(CATCH_CONFIG_NO_POSIX_SIGNALS) && !defined(CATCH_CONFIG_POSIX_SIGNALS)
+#   define CATCH_CONFIG_POSIX_SIGNALS
+#endif
+// This is set by default, because we assume that compilers with no wchar_t support are just rare exceptions.
+#if !defined(CATCH_INTERNAL_CONFIG_NO_WCHAR) && !defined(CATCH_CONFIG_NO_WCHAR) && !defined(CATCH_CONFIG_WCHAR)
+#   define CATCH_CONFIG_WCHAR
+#endif
+
+#if !defined(CATCH_INTERNAL_CONFIG_NO_CPP11_TO_STRING) && !defined(CATCH_CONFIG_NO_CPP11_TO_STRING) && !defined(CATCH_CONFIG_CPP11_TO_STRING)
+#    define CATCH_CONFIG_CPP11_TO_STRING
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_OPTIONAL) && !defined(CATCH_CONFIG_NO_CPP17_OPTIONAL) && !defined(CATCH_CONFIG_CPP17_OPTIONAL)
+#  define CATCH_CONFIG_CPP17_OPTIONAL
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_STRING_VIEW) && !defined(CATCH_CONFIG_NO_CPP17_STRING_VIEW) && !defined(CATCH_CONFIG_CPP17_STRING_VIEW)
+#  define CATCH_CONFIG_CPP17_STRING_VIEW
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_VARIANT) && !defined(CATCH_CONFIG_NO_CPP17_VARIANT) && !defined(CATCH_CONFIG_CPP17_VARIANT)
+#  define CATCH_CONFIG_CPP17_VARIANT
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_BYTE) && !defined(CATCH_CONFIG_NO_CPP17_BYTE) && !defined(CATCH_CONFIG_CPP17_BYTE)
+#  define CATCH_CONFIG_CPP17_BYTE
+#endif
+
+#if defined(CATCH_CONFIG_EXPERIMENTAL_REDIRECT)
+#  define CATCH_INTERNAL_CONFIG_NEW_CAPTURE
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_NEW_CAPTURE) && !defined(CATCH_INTERNAL_CONFIG_NO_NEW_CAPTURE) && !defined(CATCH_CONFIG_NO_NEW_CAPTURE) && !defined(CATCH_CONFIG_NEW_CAPTURE)
+#  define CATCH_CONFIG_NEW_CAPTURE
+#endif
+
+#if !defined(CATCH_INTERNAL_CONFIG_EXCEPTIONS_ENABLED) && !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+#  define CATCH_CONFIG_DISABLE_EXCEPTIONS
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_POLYFILL_ISNAN) && !defined(CATCH_CONFIG_NO_POLYFILL_ISNAN) && !defined(CATCH_CONFIG_POLYFILL_ISNAN)
+#  define CATCH_CONFIG_POLYFILL_ISNAN
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_USE_ASYNC)  && !defined(CATCH_INTERNAL_CONFIG_NO_ASYNC) && !defined(CATCH_CONFIG_NO_USE_ASYNC) && !defined(CATCH_CONFIG_USE_ASYNC)
+#  define CATCH_CONFIG_USE_ASYNC
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_ANDROID_LOGWRITE) && !defined(CATCH_CONFIG_NO_ANDROID_LOGWRITE) && !defined(CATCH_CONFIG_ANDROID_LOGWRITE)
+#  define CATCH_CONFIG_ANDROID_LOGWRITE
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_GLOBAL_NEXTAFTER) && !defined(CATCH_CONFIG_NO_GLOBAL_NEXTAFTER) && !defined(CATCH_CONFIG_GLOBAL_NEXTAFTER)
+#  define CATCH_CONFIG_GLOBAL_NEXTAFTER
+#endif
+
+// Even if we do not think the compiler has that warning, we still have
+// to provide a macro that can be used by the code.
+#if !defined(CATCH_INTERNAL_START_WARNINGS_SUPPRESSION)
+#   define CATCH_INTERNAL_START_WARNINGS_SUPPRESSION
+#endif
+#if !defined(CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION)
+#   define CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+#endif
+#if !defined(CATCH_INTERNAL_SUPPRESS_PARENTHESES_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_PARENTHESES_WARNINGS
+#endif
+#if !defined(CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS
+#endif
+#if !defined(CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS
+#endif
+#if !defined(CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS
+#endif
+
+// The goal of this macro is to avoid evaluation of the arguments, but
+// still have the compiler warn on problems inside...
+#if !defined(CATCH_INTERNAL_IGNORE_BUT_WARN)
+#   define CATCH_INTERNAL_IGNORE_BUT_WARN(...)
+#endif
+
+#if defined(__APPLE__) && defined(__apple_build_version__) && (__clang_major__ < 10)
+#   undef CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS
+#elif defined(__clang__) && (__clang_major__ < 5)
+#   undef CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS
+#endif
+
+#if !defined(CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS)
+#   define CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS
+#endif
+
+#if defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+#define CATCH_TRY if ((true))
+#define CATCH_CATCH_ALL if ((false))
+#define CATCH_CATCH_ANON(type) if ((false))
+#else
+#define CATCH_TRY try
+#define CATCH_CATCH_ALL catch (...)
+#define CATCH_CATCH_ANON(type) catch (type)
+#endif
+
+#if defined(CATCH_INTERNAL_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR) && !defined(CATCH_CONFIG_NO_TRADITIONAL_MSVC_PREPROCESSOR) && !defined(CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR)
+#define CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#endif
+
+// end catch_compiler_capabilities.h
+#define INTERNAL_CATCH_UNIQUE_NAME_LINE2( name, line ) name##line
+#define INTERNAL_CATCH_UNIQUE_NAME_LINE( name, line ) INTERNAL_CATCH_UNIQUE_NAME_LINE2( name, line )
+#ifdef CATCH_CONFIG_COUNTER
+#  define INTERNAL_CATCH_UNIQUE_NAME( name ) INTERNAL_CATCH_UNIQUE_NAME_LINE( name, __COUNTER__ )
+#else
+#  define INTERNAL_CATCH_UNIQUE_NAME( name ) INTERNAL_CATCH_UNIQUE_NAME_LINE( name, __LINE__ )
+#endif
+
+#include <iosfwd>
+#include <string>
+#include <cstdint>
+
+// We need a dummy global operator<< so we can bring it into Catch namespace later
+struct Catch_global_namespace_dummy {};
+std::ostream& operator<<(std::ostream&, Catch_global_namespace_dummy);
+
+namespace Catch {
+
+    struct CaseSensitive { enum Choice {
+        Yes,
+        No
+    }; };
+
+    class NonCopyable {
+        NonCopyable( NonCopyable const& )              = delete;
+        NonCopyable( NonCopyable && )                  = delete;
+        NonCopyable& operator = ( NonCopyable const& ) = delete;
+        NonCopyable& operator = ( NonCopyable && )     = delete;
+
+    protected:
+        NonCopyable();
+        virtual ~NonCopyable();
+    };
+
+    struct SourceLineInfo {
+
+        SourceLineInfo() = delete;
+        SourceLineInfo( char const* _file, std::size_t _line ) noexcept
+        :   file( _file ),
+            line( _line )
+        {}
+
+        SourceLineInfo( SourceLineInfo const& other )            = default;
+        SourceLineInfo& operator = ( SourceLineInfo const& )     = default;
+        SourceLineInfo( SourceLineInfo&& )              noexcept = default;
+        SourceLineInfo& operator = ( SourceLineInfo&& ) noexcept = default;
+
+        bool empty() const noexcept { return file[0] == '\0'; }
+        bool operator == ( SourceLineInfo const& other ) const noexcept;
+        bool operator < ( SourceLineInfo const& other ) const noexcept;
+
+        char const* file;
+        std::size_t line;
+    };
+
+    std::ostream& operator << ( std::ostream& os, SourceLineInfo const& info );
+
+    // Bring in operator<< from global namespace into Catch namespace
+    // This is necessary because the overload of operator<< above makes
+    // lookup stop at namespace Catch
+    using ::operator<<;
+
+    // Use this in variadic streaming macros to allow
+    //    >> +StreamEndStop
+    // as well as
+    //    >> stuff +StreamEndStop
+    struct StreamEndStop {
+        std::string operator+() const;
+    };
+    template<typename T>
+    T const& operator + ( T const& value, StreamEndStop ) {
+        return value;
+    }
+}
+
+#define CATCH_INTERNAL_LINEINFO \
+    ::Catch::SourceLineInfo( __FILE__, static_cast<std::size_t>( __LINE__ ) )
+
+// end catch_common.h
+namespace Catch {
+
+    struct RegistrarForTagAliases {
+        RegistrarForTagAliases( char const* alias, char const* tag, SourceLineInfo const& lineInfo );
+    };
+
+} // end namespace Catch
+
+#define CATCH_REGISTER_TAG_ALIAS( alias, spec ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+    CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+    namespace{ Catch::RegistrarForTagAliases INTERNAL_CATCH_UNIQUE_NAME( AutoRegisterTagAlias )( alias, spec, CATCH_INTERNAL_LINEINFO ); } \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+// end catch_tag_alias_autoregistrar.h
+// start catch_test_registry.h
+
+// start catch_interfaces_testcase.h
+
+#include <vector>
+
+namespace Catch {
+
+    class TestSpec;
+
+    struct ITestInvoker {
+        virtual void invoke () const = 0;
+        virtual ~ITestInvoker();
+    };
+
+    class TestCase;
+    struct IConfig;
+
+    struct ITestCaseRegistry {
+        virtual ~ITestCaseRegistry();
+        virtual std::vector<TestCase> const& getAllTests() const = 0;
+        virtual std::vector<TestCase> const& getAllTestsSorted( IConfig const& config ) const = 0;
+    };
+
+    bool isThrowSafe( TestCase const& testCase, IConfig const& config );
+    bool matchTest( TestCase const& testCase, TestSpec const& testSpec, IConfig const& config );
+    std::vector<TestCase> filterTests( std::vector<TestCase> const& testCases, TestSpec const& testSpec, IConfig const& config );
+    std::vector<TestCase> const& getAllTestCasesSorted( IConfig const& config );
+
+}
+
+// end catch_interfaces_testcase.h
+// start catch_stringref.h
+
+#include <cstddef>
+#include <string>
+#include <iosfwd>
+#include <cassert>
+
+namespace Catch {
+
+    /// A non-owning string class (similar to the forthcoming std::string_view)
+    /// Note that, because a StringRef may be a substring of another string,
+    /// it may not be null terminated.
+    class StringRef {
+    public:
+        using size_type = std::size_t;
+        using const_iterator = const char*;
+
+    private:
+        static constexpr char const* const s_empty = "";
+
+        char const* m_start = s_empty;
+        size_type m_size = 0;
+
+    public: // construction
+        constexpr StringRef() noexcept = default;
+
+        StringRef( char const* rawChars ) noexcept;
+
+        constexpr StringRef( char const* rawChars, size_type size ) noexcept
+        :   m_start( rawChars ),
+            m_size( size )
+        {}
+
+        StringRef( std::string const& stdString ) noexcept
+        :   m_start( stdString.c_str() ),
+            m_size( stdString.size() )
+        {}
+
+        explicit operator std::string() const {
+            return std::string(m_start, m_size);
+        }
+
+    public: // operators
+        auto operator == ( StringRef const& other ) const noexcept -> bool;
+        auto operator != (StringRef const& other) const noexcept -> bool {
+            return !(*this == other);
+        }
+
+        auto operator[] ( size_type index ) const noexcept -> char {
+            assert(index < m_size);
+            return m_start[index];
+        }
+
+    public: // named queries
+        constexpr auto empty() const noexcept -> bool {
+            return m_size == 0;
+        }
+        constexpr auto size() const noexcept -> size_type {
+            return m_size;
+        }
+
+        // Returns the current start pointer. If the StringRef is not
+        // null-terminated, throws std::domain_exception
+        auto c_str() const -> char const*;
+
+    public: // substrings and searches
+        // Returns a substring of [start, start + length).
+        // If start + length > size(), then the substring is [start, size()).
+        // If start > size(), then the substring is empty.
+        auto substr( size_type start, size_type length ) const noexcept -> StringRef;
+
+        // Returns the current start pointer. May not be null-terminated.
+        auto data() const noexcept -> char const*;
+
+        constexpr auto isNullTerminated() const noexcept -> bool {
+            return m_start[m_size] == '\0';
+        }
+
+    public: // iterators
+        constexpr const_iterator begin() const { return m_start; }
+        constexpr const_iterator end() const { return m_start + m_size; }
+    };
+
+    auto operator += ( std::string& lhs, StringRef const& sr ) -> std::string&;
+    auto operator << ( std::ostream& os, StringRef const& sr ) -> std::ostream&;
+
+    constexpr auto operator "" _sr( char const* rawChars, std::size_t size ) noexcept -> StringRef {
+        return StringRef( rawChars, size );
+    }
+} // namespace Catch
+
+constexpr auto operator "" _catch_sr( char const* rawChars, std::size_t size ) noexcept -> Catch::StringRef {
+    return Catch::StringRef( rawChars, size );
+}
+
+// end catch_stringref.h
+// start catch_preprocessor.hpp
+
+
+#define CATCH_RECURSION_LEVEL0(...) __VA_ARGS__
+#define CATCH_RECURSION_LEVEL1(...) CATCH_RECURSION_LEVEL0(CATCH_RECURSION_LEVEL0(CATCH_RECURSION_LEVEL0(__VA_ARGS__)))
+#define CATCH_RECURSION_LEVEL2(...) CATCH_RECURSION_LEVEL1(CATCH_RECURSION_LEVEL1(CATCH_RECURSION_LEVEL1(__VA_ARGS__)))
+#define CATCH_RECURSION_LEVEL3(...) CATCH_RECURSION_LEVEL2(CATCH_RECURSION_LEVEL2(CATCH_RECURSION_LEVEL2(__VA_ARGS__)))
+#define CATCH_RECURSION_LEVEL4(...) CATCH_RECURSION_LEVEL3(CATCH_RECURSION_LEVEL3(CATCH_RECURSION_LEVEL3(__VA_ARGS__)))
+#define CATCH_RECURSION_LEVEL5(...) CATCH_RECURSION_LEVEL4(CATCH_RECURSION_LEVEL4(CATCH_RECURSION_LEVEL4(__VA_ARGS__)))
+
+#ifdef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define INTERNAL_CATCH_EXPAND_VARGS(...) __VA_ARGS__
+// MSVC needs more evaluations
+#define CATCH_RECURSION_LEVEL6(...) CATCH_RECURSION_LEVEL5(CATCH_RECURSION_LEVEL5(CATCH_RECURSION_LEVEL5(__VA_ARGS__)))
+#define CATCH_RECURSE(...)  CATCH_RECURSION_LEVEL6(CATCH_RECURSION_LEVEL6(__VA_ARGS__))
+#else
+#define CATCH_RECURSE(...)  CATCH_RECURSION_LEVEL5(__VA_ARGS__)
+#endif
+
+#define CATCH_REC_END(...)
+#define CATCH_REC_OUT
+
+#define CATCH_EMPTY()
+#define CATCH_DEFER(id) id CATCH_EMPTY()
+
+#define CATCH_REC_GET_END2() 0, CATCH_REC_END
+#define CATCH_REC_GET_END1(...) CATCH_REC_GET_END2
+#define CATCH_REC_GET_END(...) CATCH_REC_GET_END1
+#define CATCH_REC_NEXT0(test, next, ...) next CATCH_REC_OUT
+#define CATCH_REC_NEXT1(test, next) CATCH_DEFER ( CATCH_REC_NEXT0 ) ( test, next, 0)
+#define CATCH_REC_NEXT(test, next)  CATCH_REC_NEXT1(CATCH_REC_GET_END test, next)
+
+#define CATCH_REC_LIST0(f, x, peek, ...) , f(x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST1) ) ( f, peek, __VA_ARGS__ )
+#define CATCH_REC_LIST1(f, x, peek, ...) , f(x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST0) ) ( f, peek, __VA_ARGS__ )
+#define CATCH_REC_LIST2(f, x, peek, ...)   f(x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST1) ) ( f, peek, __VA_ARGS__ )
+
+#define CATCH_REC_LIST0_UD(f, userdata, x, peek, ...) , f(userdata, x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST1_UD) ) ( f, userdata, peek, __VA_ARGS__ )
+#define CATCH_REC_LIST1_UD(f, userdata, x, peek, ...) , f(userdata, x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST0_UD) ) ( f, userdata, peek, __VA_ARGS__ )
+#define CATCH_REC_LIST2_UD(f, userdata, x, peek, ...)   f(userdata, x) CATCH_DEFER ( CATCH_REC_NEXT(peek, CATCH_REC_LIST1_UD) ) ( f, userdata, peek, __VA_ARGS__ )
+
+// Applies the function macro `f` to each of the remaining parameters, inserts commas between the results,
+// and passes userdata as the first parameter to each invocation,
+// e.g. CATCH_REC_LIST_UD(f, x, a, b, c) evaluates to f(x, a), f(x, b), f(x, c)
+#define CATCH_REC_LIST_UD(f, userdata, ...) CATCH_RECURSE(CATCH_REC_LIST2_UD(f, userdata, __VA_ARGS__, ()()(), ()()(), ()()(), 0))
+
+#define CATCH_REC_LIST(f, ...) CATCH_RECURSE(CATCH_REC_LIST2(f, __VA_ARGS__, ()()(), ()()(), ()()(), 0))
+
+#define INTERNAL_CATCH_EXPAND1(param) INTERNAL_CATCH_EXPAND2(param)
+#define INTERNAL_CATCH_EXPAND2(...) INTERNAL_CATCH_NO## __VA_ARGS__
+#define INTERNAL_CATCH_DEF(...) INTERNAL_CATCH_DEF __VA_ARGS__
+#define INTERNAL_CATCH_NOINTERNAL_CATCH_DEF
+#define INTERNAL_CATCH_STRINGIZE(...) INTERNAL_CATCH_STRINGIZE2(__VA_ARGS__)
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define INTERNAL_CATCH_STRINGIZE2(...) #__VA_ARGS__
+#define INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS(param) INTERNAL_CATCH_STRINGIZE(INTERNAL_CATCH_REMOVE_PARENS(param))
+#else
+// MSVC is adding extra space and needs another indirection to expand INTERNAL_CATCH_NOINTERNAL_CATCH_DEF
+#define INTERNAL_CATCH_STRINGIZE2(...) INTERNAL_CATCH_STRINGIZE3(__VA_ARGS__)
+#define INTERNAL_CATCH_STRINGIZE3(...) #__VA_ARGS__
+#define INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS(param) (INTERNAL_CATCH_STRINGIZE(INTERNAL_CATCH_REMOVE_PARENS(param)) + 1)
+#endif
+
+#define INTERNAL_CATCH_MAKE_NAMESPACE2(...) ns_##__VA_ARGS__
+#define INTERNAL_CATCH_MAKE_NAMESPACE(name) INTERNAL_CATCH_MAKE_NAMESPACE2(name)
+
+#define INTERNAL_CATCH_REMOVE_PARENS(...) INTERNAL_CATCH_EXPAND1(INTERNAL_CATCH_DEF __VA_ARGS__)
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define INTERNAL_CATCH_MAKE_TYPE_LIST2(...) decltype(get_wrapper<INTERNAL_CATCH_REMOVE_PARENS_GEN(__VA_ARGS__)>())
+#define INTERNAL_CATCH_MAKE_TYPE_LIST(...) INTERNAL_CATCH_MAKE_TYPE_LIST2(INTERNAL_CATCH_REMOVE_PARENS(__VA_ARGS__))
+#else
+#define INTERNAL_CATCH_MAKE_TYPE_LIST2(...) INTERNAL_CATCH_EXPAND_VARGS(decltype(get_wrapper<INTERNAL_CATCH_REMOVE_PARENS_GEN(__VA_ARGS__)>()))
+#define INTERNAL_CATCH_MAKE_TYPE_LIST(...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_MAKE_TYPE_LIST2(INTERNAL_CATCH_REMOVE_PARENS(__VA_ARGS__)))
+#endif
+
+#define INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(...)\
+    CATCH_REC_LIST(INTERNAL_CATCH_MAKE_TYPE_LIST,__VA_ARGS__)
+
+#define INTERNAL_CATCH_REMOVE_PARENS_1_ARG(_0) INTERNAL_CATCH_REMOVE_PARENS(_0)
+#define INTERNAL_CATCH_REMOVE_PARENS_2_ARG(_0, _1) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_1_ARG(_1)
+#define INTERNAL_CATCH_REMOVE_PARENS_3_ARG(_0, _1, _2) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_2_ARG(_1, _2)
+#define INTERNAL_CATCH_REMOVE_PARENS_4_ARG(_0, _1, _2, _3) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_3_ARG(_1, _2, _3)
+#define INTERNAL_CATCH_REMOVE_PARENS_5_ARG(_0, _1, _2, _3, _4) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_4_ARG(_1, _2, _3, _4)
+#define INTERNAL_CATCH_REMOVE_PARENS_6_ARG(_0, _1, _2, _3, _4, _5) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_5_ARG(_1, _2, _3, _4, _5)
+#define INTERNAL_CATCH_REMOVE_PARENS_7_ARG(_0, _1, _2, _3, _4, _5, _6) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_6_ARG(_1, _2, _3, _4, _5, _6)
+#define INTERNAL_CATCH_REMOVE_PARENS_8_ARG(_0, _1, _2, _3, _4, _5, _6, _7) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_7_ARG(_1, _2, _3, _4, _5, _6, _7)
+#define INTERNAL_CATCH_REMOVE_PARENS_9_ARG(_0, _1, _2, _3, _4, _5, _6, _7, _8) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_8_ARG(_1, _2, _3, _4, _5, _6, _7, _8)
+#define INTERNAL_CATCH_REMOVE_PARENS_10_ARG(_0, _1, _2, _3, _4, _5, _6, _7, _8, _9) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_9_ARG(_1, _2, _3, _4, _5, _6, _7, _8, _9)
+#define INTERNAL_CATCH_REMOVE_PARENS_11_ARG(_0, _1, _2, _3, _4, _5, _6, _7, _8, _9, _10) INTERNAL_CATCH_REMOVE_PARENS(_0), INTERNAL_CATCH_REMOVE_PARENS_10_ARG(_1, _2, _3, _4, _5, _6, _7, _8, _9, _10)
+
+#define INTERNAL_CATCH_VA_NARGS_IMPL(_0, _1, _2, _3, _4, _5, _6, _7, _8, _9, _10, N, ...) N
+
+#define INTERNAL_CATCH_TYPE_GEN\
+    template<typename...> struct TypeList {};\
+    template<typename...Ts>\
+    constexpr auto get_wrapper() noexcept -> TypeList<Ts...> { return {}; }\
+    template<template<typename...> class...> struct TemplateTypeList{};\
+    template<template<typename...> class...Cs>\
+    constexpr auto get_wrapper() noexcept -> TemplateTypeList<Cs...> { return {}; }\
+    template<typename...>\
+    struct append;\
+    template<typename...>\
+    struct rewrap;\
+    template<template<typename...> class, typename...>\
+    struct create;\
+    template<template<typename...> class, typename>\
+    struct convert;\
+    \
+    template<typename T> \
+    struct append<T> { using type = T; };\
+    template< template<typename...> class L1, typename...E1, template<typename...> class L2, typename...E2, typename...Rest>\
+    struct append<L1<E1...>, L2<E2...>, Rest...> { using type = typename append<L1<E1...,E2...>, Rest...>::type; };\
+    template< template<typename...> class L1, typename...E1, typename...Rest>\
+    struct append<L1<E1...>, TypeList<mpl_::na>, Rest...> { using type = L1<E1...>; };\
+    \
+    template< template<typename...> class Container, template<typename...> class List, typename...elems>\
+    struct rewrap<TemplateTypeList<Container>, List<elems...>> { using type = TypeList<Container<elems...>>; };\
+    template< template<typename...> class Container, template<typename...> class List, class...Elems, typename...Elements>\
+    struct rewrap<TemplateTypeList<Container>, List<Elems...>, Elements...> { using type = typename append<TypeList<Container<Elems...>>, typename rewrap<TemplateTypeList<Container>, Elements...>::type>::type; };\
+    \
+    template<template <typename...> class Final, template< typename...> class...Containers, typename...Types>\
+    struct create<Final, TemplateTypeList<Containers...>, TypeList<Types...>> { using type = typename append<Final<>, typename rewrap<TemplateTypeList<Containers>, Types...>::type...>::type; };\
+    template<template <typename...> class Final, template <typename...> class List, typename...Ts>\
+    struct convert<Final, List<Ts...>> { using type = typename append<Final<>,TypeList<Ts>...>::type; };
+
+#define INTERNAL_CATCH_NTTP_1(signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)> struct Nttp{};\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    constexpr auto get_wrapper() noexcept -> Nttp<__VA_ARGS__> { return {}; } \
+    template<template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class...> struct NttpTemplateTypeList{};\
+    template<template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class...Cs>\
+    constexpr auto get_wrapper() noexcept -> NttpTemplateTypeList<Cs...> { return {}; } \
+    \
+    template< template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class Container, template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class List, INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    struct rewrap<NttpTemplateTypeList<Container>, List<__VA_ARGS__>> { using type = TypeList<Container<__VA_ARGS__>>; };\
+    template< template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class Container, template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class List, INTERNAL_CATCH_REMOVE_PARENS(signature), typename...Elements>\
+    struct rewrap<NttpTemplateTypeList<Container>, List<__VA_ARGS__>, Elements...> { using type = typename append<TypeList<Container<__VA_ARGS__>>, typename rewrap<NttpTemplateTypeList<Container>, Elements...>::type>::type; };\
+    template<template <typename...> class Final, template<INTERNAL_CATCH_REMOVE_PARENS(signature)> class...Containers, typename...Types>\
+    struct create<Final, NttpTemplateTypeList<Containers...>, TypeList<Types...>> { using type = typename append<Final<>, typename rewrap<NttpTemplateTypeList<Containers>, Types...>::type...>::type; };
+
+#define INTERNAL_CATCH_DECLARE_SIG_TEST0(TestName)
+#define INTERNAL_CATCH_DECLARE_SIG_TEST1(TestName, signature)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    static void TestName()
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_X(TestName, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    static void TestName()
+
+#define INTERNAL_CATCH_DEFINE_SIG_TEST0(TestName)
+#define INTERNAL_CATCH_DEFINE_SIG_TEST1(TestName, signature)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    static void TestName()
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_X(TestName, signature,...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    static void TestName()
+
+#define INTERNAL_CATCH_NTTP_REGISTER0(TestFunc, signature)\
+    template<typename Type>\
+    void reg_test(TypeList<Type>, Catch::NameAndTags nameAndTags)\
+    {\
+        Catch::AutoReg( Catch::makeTestInvoker(&TestFunc<Type>), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), nameAndTags);\
+    }
+
+#define INTERNAL_CATCH_NTTP_REGISTER(TestFunc, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    void reg_test(Nttp<__VA_ARGS__>, Catch::NameAndTags nameAndTags)\
+    {\
+        Catch::AutoReg( Catch::makeTestInvoker(&TestFunc<__VA_ARGS__>), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), nameAndTags);\
+    }
+
+#define INTERNAL_CATCH_NTTP_REGISTER_METHOD0(TestName, signature, ...)\
+    template<typename Type>\
+    void reg_test(TypeList<Type>, Catch::StringRef className, Catch::NameAndTags nameAndTags)\
+    {\
+        Catch::AutoReg( Catch::makeTestInvoker(&TestName<Type>::test), CATCH_INTERNAL_LINEINFO, className, nameAndTags);\
+    }
+
+#define INTERNAL_CATCH_NTTP_REGISTER_METHOD(TestName, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)>\
+    void reg_test(Nttp<__VA_ARGS__>, Catch::StringRef className, Catch::NameAndTags nameAndTags)\
+    {\
+        Catch::AutoReg( Catch::makeTestInvoker(&TestName<__VA_ARGS__>::test), CATCH_INTERNAL_LINEINFO, className, nameAndTags);\
+    }
+
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD0(TestName, ClassName)
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD1(TestName, ClassName, signature)\
+    template<typename TestType> \
+    struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName)<TestType> { \
+        void test();\
+    }
+
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X(TestName, ClassName, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)> \
+    struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName)<__VA_ARGS__> { \
+        void test();\
+    }
+
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD0(TestName)
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD1(TestName, signature)\
+    template<typename TestType> \
+    void INTERNAL_CATCH_MAKE_NAMESPACE(TestName)::TestName<TestType>::test()
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X(TestName, signature, ...)\
+    template<INTERNAL_CATCH_REMOVE_PARENS(signature)> \
+    void INTERNAL_CATCH_MAKE_NAMESPACE(TestName)::TestName<__VA_ARGS__>::test()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define INTERNAL_CATCH_NTTP_0
+#define INTERNAL_CATCH_NTTP_GEN(...) INTERNAL_CATCH_VA_NARGS_IMPL(__VA_ARGS__, INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1(__VA_ARGS__), INTERNAL_CATCH_NTTP_1( __VA_ARGS__), INTERNAL_CATCH_NTTP_1( __VA_ARGS__), INTERNAL_CATCH_NTTP_1( __VA_ARGS__), INTERNAL_CATCH_NTTP_1( __VA_ARGS__),INTERNAL_CATCH_NTTP_1( __VA_ARGS__), INTERNAL_CATCH_NTTP_0)
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD(TestName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD1, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD0)(TestName, __VA_ARGS__)
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD(TestName, ClassName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD1, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD0)(TestName, ClassName, __VA_ARGS__)
+#define INTERNAL_CATCH_NTTP_REG_METHOD_GEN(TestName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD0, INTERNAL_CATCH_NTTP_REGISTER_METHOD0)(TestName, __VA_ARGS__)
+#define INTERNAL_CATCH_NTTP_REG_GEN(TestFunc, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER0, INTERNAL_CATCH_NTTP_REGISTER0)(TestFunc, __VA_ARGS__)
+#define INTERNAL_CATCH_DEFINE_SIG_TEST(TestName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DEFINE_SIG_TEST1, INTERNAL_CATCH_DEFINE_SIG_TEST0)(TestName, __VA_ARGS__)
+#define INTERNAL_CATCH_DECLARE_SIG_TEST(TestName, ...) INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DECLARE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST1, INTERNAL_CATCH_DECLARE_SIG_TEST0)(TestName, __VA_ARGS__)
+#define INTERNAL_CATCH_REMOVE_PARENS_GEN(...) INTERNAL_CATCH_VA_NARGS_IMPL(__VA_ARGS__, INTERNAL_CATCH_REMOVE_PARENS_11_ARG,INTERNAL_CATCH_REMOVE_PARENS_10_ARG,INTERNAL_CATCH_REMOVE_PARENS_9_ARG,INTERNAL_CATCH_REMOVE_PARENS_8_ARG,INTERNAL_CATCH_REMOVE_PARENS_7_ARG,INTERNAL_CATCH_REMOVE_PARENS_6_ARG,INTERNAL_CATCH_REMOVE_PARENS_5_ARG,INTERNAL_CATCH_REMOVE_PARENS_4_ARG,INTERNAL_CATCH_REMOVE_PARENS_3_ARG,INTERNAL_CATCH_REMOVE_PARENS_2_ARG,INTERNAL_CATCH_REMOVE_PARENS_1_ARG)(__VA_ARGS__)
+#else
+#define INTERNAL_CATCH_NTTP_0(signature)
+#define INTERNAL_CATCH_NTTP_GEN(...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL(__VA_ARGS__, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_1,INTERNAL_CATCH_NTTP_1, INTERNAL_CATCH_NTTP_0)( __VA_ARGS__))
+#define INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD(TestName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD1, INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD0)(TestName, __VA_ARGS__))
+#define INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD(TestName, ClassName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X,INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD_X, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD1, INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD0)(TestName, ClassName, __VA_ARGS__))
+#define INTERNAL_CATCH_NTTP_REG_METHOD_GEN(TestName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD, INTERNAL_CATCH_NTTP_REGISTER_METHOD0, INTERNAL_CATCH_NTTP_REGISTER_METHOD0)(TestName, __VA_ARGS__))
+#define INTERNAL_CATCH_NTTP_REG_GEN(TestFunc, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER, INTERNAL_CATCH_NTTP_REGISTER0, INTERNAL_CATCH_NTTP_REGISTER0)(TestFunc, __VA_ARGS__))
+#define INTERNAL_CATCH_DEFINE_SIG_TEST(TestName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DEFINE_SIG_TEST1, INTERNAL_CATCH_DEFINE_SIG_TEST0)(TestName, __VA_ARGS__))
+#define INTERNAL_CATCH_DECLARE_SIG_TEST(TestName, ...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL( "dummy", __VA_ARGS__, INTERNAL_CATCH_DECLARE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DEFINE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X,INTERNAL_CATCH_DECLARE_SIG_TEST_X, INTERNAL_CATCH_DECLARE_SIG_TEST1, INTERNAL_CATCH_DECLARE_SIG_TEST0)(TestName, __VA_ARGS__))
+#define INTERNAL_CATCH_REMOVE_PARENS_GEN(...) INTERNAL_CATCH_EXPAND_VARGS(INTERNAL_CATCH_VA_NARGS_IMPL(__VA_ARGS__, INTERNAL_CATCH_REMOVE_PARENS_11_ARG,INTERNAL_CATCH_REMOVE_PARENS_10_ARG,INTERNAL_CATCH_REMOVE_PARENS_9_ARG,INTERNAL_CATCH_REMOVE_PARENS_8_ARG,INTERNAL_CATCH_REMOVE_PARENS_7_ARG,INTERNAL_CATCH_REMOVE_PARENS_6_ARG,INTERNAL_CATCH_REMOVE_PARENS_5_ARG,INTERNAL_CATCH_REMOVE_PARENS_4_ARG,INTERNAL_CATCH_REMOVE_PARENS_3_ARG,INTERNAL_CATCH_REMOVE_PARENS_2_ARG,INTERNAL_CATCH_REMOVE_PARENS_1_ARG)(__VA_ARGS__))
+#endif
+
+// end catch_preprocessor.hpp
+// start catch_meta.hpp
+
+
+#include <type_traits>
+
+namespace Catch {
+    template<typename T>
+    struct always_false : std::false_type {};
+
+    template <typename> struct true_given : std::true_type {};
+    struct is_callable_tester {
+        template <typename Fun, typename... Args>
+        true_given<decltype(std::declval<Fun>()(std::declval<Args>()...))> static test(int);
+        template <typename...>
+        std::false_type static test(...);
+    };
+
+    template <typename T>
+    struct is_callable;
+
+    template <typename Fun, typename... Args>
+    struct is_callable<Fun(Args...)> : decltype(is_callable_tester::test<Fun, Args...>(0)) {};
+
+#if defined(__cpp_lib_is_invocable) && __cpp_lib_is_invocable >= 201703
+    // std::result_of is deprecated in C++17 and removed in C++20. Hence, it is
+    // replaced with std::invoke_result here.
+    template <typename Func, typename... U>
+    using FunctionReturnType = std::remove_reference_t<std::remove_cv_t<std::invoke_result_t<Func, U...>>>;
+#else
+    // Keep ::type here because we still support C++11
+    template <typename Func, typename... U>
+    using FunctionReturnType = typename std::remove_reference<typename std::remove_cv<typename std::result_of<Func(U...)>::type>::type>::type;
+#endif
+
+} // namespace Catch
+
+namespace mpl_{
+    struct na;
+}
+
+// end catch_meta.hpp
+namespace Catch {
+
+template<typename C>
+class TestInvokerAsMethod : public ITestInvoker {
+    void (C::*m_testAsMethod)();
+public:
+    TestInvokerAsMethod( void (C::*testAsMethod)() ) noexcept : m_testAsMethod( testAsMethod ) {}
+
+    void invoke() const override {
+        C obj;
+        (obj.*m_testAsMethod)();
+    }
+};
+
+auto makeTestInvoker( void(*testAsFunction)() ) noexcept -> ITestInvoker*;
+
+template<typename C>
+auto makeTestInvoker( void (C::*testAsMethod)() ) noexcept -> ITestInvoker* {
+    return new(std::nothrow) TestInvokerAsMethod<C>( testAsMethod );
+}
+
+struct NameAndTags {
+    NameAndTags( StringRef const& name_ = StringRef(), StringRef const& tags_ = StringRef() ) noexcept;
+    StringRef name;
+    StringRef tags;
+};
+
+struct AutoReg : NonCopyable {
+    AutoReg( ITestInvoker* invoker, SourceLineInfo const& lineInfo, StringRef const& classOrMethod, NameAndTags const& nameAndTags ) noexcept;
+    ~AutoReg();
+};
+
+} // end namespace Catch
+
+#if defined(CATCH_CONFIG_DISABLE)
+    #define INTERNAL_CATCH_TESTCASE_NO_REGISTRATION( TestName, ... ) \
+        static void TestName()
+    #define INTERNAL_CATCH_TESTCASE_METHOD_NO_REGISTRATION( TestName, ClassName, ... ) \
+        namespace{                        \
+            struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName) { \
+                void test();              \
+            };                            \
+        }                                 \
+        void TestName::test()
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( TestName, TestFunc, Name, Tags, Signature, ... )  \
+        INTERNAL_CATCH_DEFINE_SIG_TEST(TestFunc, INTERNAL_CATCH_REMOVE_PARENS(Signature))
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( TestNameClass, TestName, ClassName, Name, Tags, Signature, ... )    \
+        namespace{                                                                                  \
+            namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName) {                                      \
+            INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD(TestName, ClassName, INTERNAL_CATCH_REMOVE_PARENS(Signature));\
+        }                                                                                           \
+        }                                                                                           \
+        INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD(TestName, INTERNAL_CATCH_REMOVE_PARENS(Signature))
+
+    #ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(Name, Tags, ...) \
+            INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, typename TestType, __VA_ARGS__ )
+    #else
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(Name, Tags, ...) \
+            INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, typename TestType, __VA_ARGS__ ) )
+    #endif
+
+    #ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(Name, Tags, Signature, ...) \
+            INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, Signature, __VA_ARGS__ )
+    #else
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(Name, Tags, Signature, ...) \
+            INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, Signature, __VA_ARGS__ ) )
+    #endif
+
+    #ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION( ClassName, Name, Tags,... ) \
+            INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_C_L_A_S_S_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ) , ClassName, Name, Tags, typename T, __VA_ARGS__ )
+    #else
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION( ClassName, Name, Tags,... ) \
+            INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_C_L_A_S_S_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ) , ClassName, Name, Tags, typename T, __VA_ARGS__ ) )
+    #endif
+
+    #ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION( ClassName, Name, Tags, Signature, ... ) \
+            INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_C_L_A_S_S_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ) , ClassName, Name, Tags, Signature, __VA_ARGS__ )
+    #else
+        #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION( ClassName, Name, Tags, Signature, ... ) \
+            INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_C_L_A_S_S_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ) , ClassName, Name, Tags, Signature, __VA_ARGS__ ) )
+    #endif
+#endif
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_TESTCASE2( TestName, ... ) \
+        static void TestName(); \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        namespace{ Catch::AutoReg INTERNAL_CATCH_UNIQUE_NAME( autoRegistrar )( Catch::makeTestInvoker( &TestName ), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), Catch::NameAndTags{ __VA_ARGS__ } ); } /* NOLINT */ \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        static void TestName()
+    #define INTERNAL_CATCH_TESTCASE( ... ) \
+        INTERNAL_CATCH_TESTCASE2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ), __VA_ARGS__ )
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_METHOD_AS_TEST_CASE( QualifiedMethod, ... ) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        namespace{ Catch::AutoReg INTERNAL_CATCH_UNIQUE_NAME( autoRegistrar )( Catch::makeTestInvoker( &QualifiedMethod ), CATCH_INTERNAL_LINEINFO, "&" #QualifiedMethod, Catch::NameAndTags{ __VA_ARGS__ } ); } /* NOLINT */ \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_TEST_CASE_METHOD2( TestName, ClassName, ... )\
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        namespace{ \
+            struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName) { \
+                void test(); \
+            }; \
+            Catch::AutoReg INTERNAL_CATCH_UNIQUE_NAME( autoRegistrar ) ( Catch::makeTestInvoker( &TestName::test ), CATCH_INTERNAL_LINEINFO, #ClassName, Catch::NameAndTags{ __VA_ARGS__ } ); /* NOLINT */ \
+        } \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        void TestName::test()
+    #define INTERNAL_CATCH_TEST_CASE_METHOD( ClassName, ... ) \
+        INTERNAL_CATCH_TEST_CASE_METHOD2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ), ClassName, __VA_ARGS__ )
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_REGISTER_TESTCASE( Function, ... ) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        Catch::AutoReg INTERNAL_CATCH_UNIQUE_NAME( autoRegistrar )( Catch::makeTestInvoker( Function ), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), Catch::NameAndTags{ __VA_ARGS__ } ); /* NOLINT */ \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+    ///////////////////////////////////////////////////////////////////////////////
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_2(TestName, TestFunc, Name, Tags, Signature, ... )\
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        INTERNAL_CATCH_DECLARE_SIG_TEST(TestFunc, INTERNAL_CATCH_REMOVE_PARENS(Signature));\
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName){\
+            INTERNAL_CATCH_TYPE_GEN\
+            INTERNAL_CATCH_NTTP_GEN(INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            INTERNAL_CATCH_NTTP_REG_GEN(TestFunc,INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            template<typename...Types> \
+            struct TestName{\
+                TestName(){\
+                    int index = 0;                                    \
+                    constexpr char const* tmpl_types[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, __VA_ARGS__)};\
+                    using expander = int[];\
+                    (void)expander{(reg_test(Types{}, Catch::NameAndTags{ Name " - " + std::string(tmpl_types[index]), Tags } ), index++)... };/* NOLINT */ \
+                }\
+            };\
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){\
+            TestName<INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(__VA_ARGS__)>();\
+            return 0;\
+        }();\
+        }\
+        }\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        INTERNAL_CATCH_DEFINE_SIG_TEST(TestFunc,INTERNAL_CATCH_REMOVE_PARENS(Signature))
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE(Name, Tags, ...) \
+        INTERNAL_CATCH_TEMPLATE_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, typename TestType, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE(Name, Tags, ...) \
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, typename TestType, __VA_ARGS__ ) )
+#endif
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG(Name, Tags, Signature, ...) \
+        INTERNAL_CATCH_TEMPLATE_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, Signature, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG(Name, Tags, Signature, ...) \
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, Signature, __VA_ARGS__ ) )
+#endif
+
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2(TestName, TestFuncName, Name, Tags, Signature, TmplTypes, TypesList) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION                      \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS                      \
+        CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS                \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS              \
+        template<typename TestType> static void TestFuncName();       \
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName) {                                     \
+            INTERNAL_CATCH_TYPE_GEN                                                  \
+            INTERNAL_CATCH_NTTP_GEN(INTERNAL_CATCH_REMOVE_PARENS(Signature))         \
+            template<typename... Types>                               \
+            struct TestName {                                         \
+                void reg_tests() {                                          \
+                    int index = 0;                                    \
+                    using expander = int[];                           \
+                    constexpr char const* tmpl_types[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, INTERNAL_CATCH_REMOVE_PARENS(TmplTypes))};\
+                    constexpr char const* types_list[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, INTERNAL_CATCH_REMOVE_PARENS(TypesList))};\
+                    constexpr auto num_types = sizeof(types_list) / sizeof(types_list[0]);\
+                    (void)expander{(Catch::AutoReg( Catch::makeTestInvoker( &TestFuncName<Types> ), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), Catch::NameAndTags{ Name " - " + std::string(tmpl_types[index / num_types]) + "<" + std::string(types_list[index % num_types]) + ">", Tags } ), index++)... };/* NOLINT */\
+                }                                                     \
+            };                                                        \
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){ \
+                using TestInit = typename create<TestName, decltype(get_wrapper<INTERNAL_CATCH_REMOVE_PARENS(TmplTypes)>()), TypeList<INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(INTERNAL_CATCH_REMOVE_PARENS(TypesList))>>::type; \
+                TestInit t;                                           \
+                t.reg_tests();                                        \
+                return 0;                                             \
+            }();                                                      \
+        }                                                             \
+        }                                                             \
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION                       \
+        template<typename TestType>                                   \
+        static void TestFuncName()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE(Name, Tags, ...)\
+        INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, typename T,__VA_ARGS__)
+#else
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE(Name, Tags, ...)\
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, typename T, __VA_ARGS__ ) )
+#endif
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG(Name, Tags, Signature, ...)\
+        INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, Signature, __VA_ARGS__)
+#else
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG(Name, Tags, Signature, ...)\
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, Signature, __VA_ARGS__ ) )
+#endif
+
+    #define INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_2(TestName, TestFunc, Name, Tags, TmplList)\
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        template<typename TestType> static void TestFunc();       \
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName){\
+        INTERNAL_CATCH_TYPE_GEN\
+        template<typename... Types>                               \
+        struct TestName {                                         \
+            void reg_tests() {                                          \
+                int index = 0;                                    \
+                using expander = int[];                           \
+                (void)expander{(Catch::AutoReg( Catch::makeTestInvoker( &TestFunc<Types> ), CATCH_INTERNAL_LINEINFO, Catch::StringRef(), Catch::NameAndTags{ Name " - " + std::string(INTERNAL_CATCH_STRINGIZE(TmplList)) + " - " + std::to_string(index), Tags } ), index++)... };/* NOLINT */\
+            }                                                     \
+        };\
+        static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){ \
+                using TestInit = typename convert<TestName, TmplList>::type; \
+                TestInit t;                                           \
+                t.reg_tests();                                        \
+                return 0;                                             \
+            }();                                                      \
+        }}\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION                       \
+        template<typename TestType>                                   \
+        static void TestFunc()
+
+    #define INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE(Name, Tags, TmplList) \
+        INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), Name, Tags, TmplList )
+
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( TestNameClass, TestName, ClassName, Name, Tags, Signature, ... ) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName){ \
+            INTERNAL_CATCH_TYPE_GEN\
+            INTERNAL_CATCH_NTTP_GEN(INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            INTERNAL_CATCH_DECLARE_SIG_TEST_METHOD(TestName, ClassName, INTERNAL_CATCH_REMOVE_PARENS(Signature));\
+            INTERNAL_CATCH_NTTP_REG_METHOD_GEN(TestName, INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            template<typename...Types> \
+            struct TestNameClass{\
+                TestNameClass(){\
+                    int index = 0;                                    \
+                    constexpr char const* tmpl_types[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, __VA_ARGS__)};\
+                    using expander = int[];\
+                    (void)expander{(reg_test(Types{}, #ClassName, Catch::NameAndTags{ Name " - " + std::string(tmpl_types[index]), Tags } ), index++)... };/* NOLINT */ \
+                }\
+            };\
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){\
+                TestNameClass<INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(__VA_ARGS__)>();\
+                return 0;\
+        }();\
+        }\
+        }\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        INTERNAL_CATCH_DEFINE_SIG_TEST_METHOD(TestName, INTERNAL_CATCH_REMOVE_PARENS(Signature))
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( ClassName, Name, Tags,... ) \
+        INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_C_L_A_S_S_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ) , ClassName, Name, Tags, typename T, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( ClassName, Name, Tags,... ) \
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_C_L_A_S_S_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ) , ClassName, Name, Tags, typename T, __VA_ARGS__ ) )
+#endif
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( ClassName, Name, Tags, Signature, ... ) \
+        INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_C_L_A_S_S_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ) , ClassName, Name, Tags, Signature, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( ClassName, Name, Tags, Signature, ... ) \
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_C_L_A_S_S_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ) , ClassName, Name, Tags, Signature, __VA_ARGS__ ) )
+#endif
+
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2(TestNameClass, TestName, ClassName, Name, Tags, Signature, TmplTypes, TypesList)\
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_ZERO_VARIADIC_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        template<typename TestType> \
+            struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName <TestType>) { \
+                void test();\
+            };\
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestNameClass) {\
+            INTERNAL_CATCH_TYPE_GEN                  \
+            INTERNAL_CATCH_NTTP_GEN(INTERNAL_CATCH_REMOVE_PARENS(Signature))\
+            template<typename...Types>\
+            struct TestNameClass{\
+                void reg_tests(){\
+                    int index = 0;\
+                    using expander = int[];\
+                    constexpr char const* tmpl_types[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, INTERNAL_CATCH_REMOVE_PARENS(TmplTypes))};\
+                    constexpr char const* types_list[] = {CATCH_REC_LIST(INTERNAL_CATCH_STRINGIZE_WITHOUT_PARENS, INTERNAL_CATCH_REMOVE_PARENS(TypesList))};\
+                    constexpr auto num_types = sizeof(types_list) / sizeof(types_list[0]);\
+                    (void)expander{(Catch::AutoReg( Catch::makeTestInvoker( &TestName<Types>::test ), CATCH_INTERNAL_LINEINFO, #ClassName, Catch::NameAndTags{ Name " - " + std::string(tmpl_types[index / num_types]) + "<" + std::string(types_list[index % num_types]) + ">", Tags } ), index++)... };/* NOLINT */ \
+                }\
+            };\
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){\
+                using TestInit = typename create<TestNameClass, decltype(get_wrapper<INTERNAL_CATCH_REMOVE_PARENS(TmplTypes)>()), TypeList<INTERNAL_CATCH_MAKE_TYPE_LISTS_FROM_TYPES(INTERNAL_CATCH_REMOVE_PARENS(TypesList))>>::type;\
+                TestInit t;\
+                t.reg_tests();\
+                return 0;\
+            }(); \
+        }\
+        }\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        template<typename TestType> \
+        void TestName<TestType>::test()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( ClassName, Name, Tags, ... )\
+        INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), ClassName, Name, Tags, typename T, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( ClassName, Name, Tags, ... )\
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), ClassName, Name, Tags, typename T,__VA_ARGS__ ) )
+#endif
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( ClassName, Name, Tags, Signature, ... )\
+        INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), ClassName, Name, Tags, Signature, __VA_ARGS__ )
+#else
+    #define INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( ClassName, Name, Tags, Signature, ... )\
+        INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), ClassName, Name, Tags, Signature,__VA_ARGS__ ) )
+#endif
+
+    #define INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD_2( TestNameClass, TestName, ClassName, Name, Tags, TmplList) \
+        CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+        CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+        CATCH_INTERNAL_SUPPRESS_UNUSED_TEMPLATE_WARNINGS \
+        template<typename TestType> \
+        struct TestName : INTERNAL_CATCH_REMOVE_PARENS(ClassName <TestType>) { \
+            void test();\
+        };\
+        namespace {\
+        namespace INTERNAL_CATCH_MAKE_NAMESPACE(TestName){ \
+            INTERNAL_CATCH_TYPE_GEN\
+            template<typename...Types>\
+            struct TestNameClass{\
+                void reg_tests(){\
+                    int index = 0;\
+                    using expander = int[];\
+                    (void)expander{(Catch::AutoReg( Catch::makeTestInvoker( &TestName<Types>::test ), CATCH_INTERNAL_LINEINFO, #ClassName, Catch::NameAndTags{ Name " - " + std::string(INTERNAL_CATCH_STRINGIZE(TmplList)) + " - " + std::to_string(index), Tags } ), index++)... };/* NOLINT */ \
+                }\
+            };\
+            static int INTERNAL_CATCH_UNIQUE_NAME( globalRegistrar ) = [](){\
+                using TestInit = typename convert<TestNameClass, TmplList>::type;\
+                TestInit t;\
+                t.reg_tests();\
+                return 0;\
+            }(); \
+        }}\
+        CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        template<typename TestType> \
+        void TestName<TestType>::test()
+
+#define INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD(ClassName, Name, Tags, TmplList) \
+        INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD_2( INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_ ), INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_M_P_L_A_T_E_T_E_S_T_F_U_N_C_ ), ClassName, Name, Tags, TmplList )
+
+// end catch_test_registry.h
+// start catch_capture.hpp
+
+// start catch_assertionhandler.h
+
+// start catch_assertioninfo.h
+
+// start catch_result_type.h
+
+namespace Catch {
+
+    // ResultWas::OfType enum
+    struct ResultWas { enum OfType {
+        Unknown = -1,
+        Ok = 0,
+        Info = 1,
+        Warning = 2,
+
+        FailureBit = 0x10,
+
+        ExpressionFailed = FailureBit | 1,
+        ExplicitFailure = FailureBit | 2,
+
+        Exception = 0x100 | FailureBit,
+
+        ThrewException = Exception | 1,
+        DidntThrowException = Exception | 2,
+
+        FatalErrorCondition = 0x200 | FailureBit
+
+    }; };
+
+    bool isOk( ResultWas::OfType resultType );
+    bool isJustInfo( int flags );
+
+    // ResultDisposition::Flags enum
+    struct ResultDisposition { enum Flags {
+        Normal = 0x01,
+
+        ContinueOnFailure = 0x02,   // Failures fail test, but execution continues
+        FalseTest = 0x04,           // Prefix expression with !
+        SuppressFail = 0x08         // Failures are reported but do not fail the test
+    }; };
+
+    ResultDisposition::Flags operator | ( ResultDisposition::Flags lhs, ResultDisposition::Flags rhs );
+
+    bool shouldContinueOnFailure( int flags );
+    inline bool isFalseTest( int flags ) { return ( flags & ResultDisposition::FalseTest ) != 0; }
+    bool shouldSuppressFailure( int flags );
+
+} // end namespace Catch
+
+// end catch_result_type.h
+namespace Catch {
+
+    struct AssertionInfo
+    {
+        StringRef macroName;
+        SourceLineInfo lineInfo;
+        StringRef capturedExpression;
+        ResultDisposition::Flags resultDisposition;
+
+        // We want to delete this constructor but a compiler bug in 4.8 means
+        // the struct is then treated as non-aggregate
+        //AssertionInfo() = delete;
+    };
+
+} // end namespace Catch
+
+// end catch_assertioninfo.h
+// start catch_decomposer.h
+
+// start catch_tostring.h
+
+#include <vector>
+#include <cstddef>
+#include <type_traits>
+#include <string>
+// start catch_stream.h
+
+#include <iosfwd>
+#include <cstddef>
+#include <ostream>
+
+namespace Catch {
+
+    std::ostream& cout();
+    std::ostream& cerr();
+    std::ostream& clog();
+
+    class StringRef;
+
+    struct IStream {
+        virtual ~IStream();
+        virtual std::ostream& stream() const = 0;
+    };
+
+    auto makeStream( StringRef const &filename ) -> IStream const*;
+
+    class ReusableStringStream : NonCopyable {
+        std::size_t m_index;
+        std::ostream* m_oss;
+    public:
+        ReusableStringStream();
+        ~ReusableStringStream();
+
+        auto str() const -> std::string;
+
+        template<typename T>
+        auto operator << ( T const& value ) -> ReusableStringStream& {
+            *m_oss << value;
+            return *this;
+        }
+        auto get() -> std::ostream& { return *m_oss; }
+    };
+}
+
+// end catch_stream.h
+// start catch_interfaces_enum_values_registry.h
+
+#include <vector>
+
+namespace Catch {
+
+    namespace Detail {
+        struct EnumInfo {
+            StringRef m_name;
+            std::vector<std::pair<int, StringRef>> m_values;
+
+            ~EnumInfo();
+
+            StringRef lookup( int value ) const;
+        };
+    } // namespace Detail
+
+    struct IMutableEnumValuesRegistry {
+        virtual ~IMutableEnumValuesRegistry();
+
+        virtual Detail::EnumInfo const& registerEnum( StringRef enumName, StringRef allEnums, std::vector<int> const& values ) = 0;
+
+        template<typename E>
+        Detail::EnumInfo const& registerEnum( StringRef enumName, StringRef allEnums, std::initializer_list<E> values ) {
+            static_assert(sizeof(int) >= sizeof(E), "Cannot serialize enum to int");
+            std::vector<int> intValues;
+            intValues.reserve( values.size() );
+            for( auto enumValue : values )
+                intValues.push_back( static_cast<int>( enumValue ) );
+            return registerEnum( enumName, allEnums, intValues );
+        }
+    };
+
+} // Catch
+
+// end catch_interfaces_enum_values_registry.h
+
+#ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+#include <string_view>
+#endif
+
+#ifdef __OBJC__
+// start catch_objc_arc.hpp
+
+#import <Foundation/Foundation.h>
+
+#ifdef __has_feature
+#define CATCH_ARC_ENABLED __has_feature(objc_arc)
+#else
+#define CATCH_ARC_ENABLED 0
+#endif
+
+void arcSafeRelease( NSObject* obj );
+id performOptionalSelector( id obj, SEL sel );
+
+#if !CATCH_ARC_ENABLED
+inline void arcSafeRelease( NSObject* obj ) {
+    [obj release];
+}
+inline id performOptionalSelector( id obj, SEL sel ) {
+    if( [obj respondsToSelector: sel] )
+        return [obj performSelector: sel];
+    return nil;
+}
+#define CATCH_UNSAFE_UNRETAINED
+#define CATCH_ARC_STRONG
+#else
+inline void arcSafeRelease( NSObject* ){}
+inline id performOptionalSelector( id obj, SEL sel ) {
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Warc-performSelector-leaks"
+#endif
+    if( [obj respondsToSelector: sel] )
+        return [obj performSelector: sel];
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+    return nil;
+}
+#define CATCH_UNSAFE_UNRETAINED __unsafe_unretained
+#define CATCH_ARC_STRONG __strong
+#endif
+
+// end catch_objc_arc.hpp
+#endif
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable:4180) // We attempt to stream a function (address) by const&, which MSVC complains about but is harmless
+#endif
+
+namespace Catch {
+    namespace Detail {
+
+        extern const std::string unprintableString;
+
+        std::string rawMemoryToString( const void *object, std::size_t size );
+
+        template<typename T>
+        std::string rawMemoryToString( const T& object ) {
+          return rawMemoryToString( &object, sizeof(object) );
+        }
+
+        template<typename T>
+        class IsStreamInsertable {
+            template<typename Stream, typename U>
+            static auto test(int)
+                -> decltype(std::declval<Stream&>() << std::declval<U>(), std::true_type());
+
+            template<typename, typename>
+            static auto test(...)->std::false_type;
+
+        public:
+            static const bool value = decltype(test<std::ostream, const T&>(0))::value;
+        };
+
+        template<typename E>
+        std::string convertUnknownEnumToString( E e );
+
+        template<typename T>
+        typename std::enable_if<
+            !std::is_enum<T>::value && !std::is_base_of<std::exception, T>::value,
+        std::string>::type convertUnstreamable( T const& ) {
+            return Detail::unprintableString;
+        }
+        template<typename T>
+        typename std::enable_if<
+            !std::is_enum<T>::value && std::is_base_of<std::exception, T>::value,
+         std::string>::type convertUnstreamable(T const& ex) {
+            return ex.what();
+        }
+
+        template<typename T>
+        typename std::enable_if<
+            std::is_enum<T>::value
+        , std::string>::type convertUnstreamable( T const& value ) {
+            return convertUnknownEnumToString( value );
+        }
+
+#if defined(_MANAGED)
+        //! Convert a CLR string to a utf8 std::string
+        template<typename T>
+        std::string clrReferenceToString( T^ ref ) {
+            if (ref == nullptr)
+                return std::string("null");
+            auto bytes = System::Text::Encoding::UTF8->GetBytes(ref->ToString());
+            cli::pin_ptr<System::Byte> p = &bytes[0];
+            return std::string(reinterpret_cast<char const *>(p), bytes->Length);
+        }
+#endif
+
+    } // namespace Detail
+
+    // If we decide for C++14, change these to enable_if_ts
+    template <typename T, typename = void>
+    struct StringMaker {
+        template <typename Fake = T>
+        static
+        typename std::enable_if<::Catch::Detail::IsStreamInsertable<Fake>::value, std::string>::type
+            convert(const Fake& value) {
+                ReusableStringStream rss;
+                // NB: call using the function-like syntax to avoid ambiguity with
+                // user-defined templated operator<< under clang.
+                rss.operator<<(value);
+                return rss.str();
+        }
+
+        template <typename Fake = T>
+        static
+        typename std::enable_if<!::Catch::Detail::IsStreamInsertable<Fake>::value, std::string>::type
+            convert( const Fake& value ) {
+#if !defined(CATCH_CONFIG_FALLBACK_STRINGIFIER)
+            return Detail::convertUnstreamable(value);
+#else
+            return CATCH_CONFIG_FALLBACK_STRINGIFIER(value);
+#endif
+        }
+    };
+
+    namespace Detail {
+
+        // This function dispatches all stringification requests inside of Catch.
+        // Should be preferably called fully qualified, like ::Catch::Detail::stringify
+        template <typename T>
+        std::string stringify(const T& e) {
+            return ::Catch::StringMaker<typename std::remove_cv<typename std::remove_reference<T>::type>::type>::convert(e);
+        }
+
+        template<typename E>
+        std::string convertUnknownEnumToString( E e ) {
+            return ::Catch::Detail::stringify(static_cast<typename std::underlying_type<E>::type>(e));
+        }
+
+#if defined(_MANAGED)
+        template <typename T>
+        std::string stringify( T^ e ) {
+            return ::Catch::StringMaker<T^>::convert(e);
+        }
+#endif
+
+    } // namespace Detail
+
+    // Some predefined specializations
+
+    template<>
+    struct StringMaker<std::string> {
+        static std::string convert(const std::string& str);
+    };
+
+#ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+    template<>
+    struct StringMaker<std::string_view> {
+        static std::string convert(std::string_view str);
+    };
+#endif
+
+    template<>
+    struct StringMaker<char const *> {
+        static std::string convert(char const * str);
+    };
+    template<>
+    struct StringMaker<char *> {
+        static std::string convert(char * str);
+    };
+
+#ifdef CATCH_CONFIG_WCHAR
+    template<>
+    struct StringMaker<std::wstring> {
+        static std::string convert(const std::wstring& wstr);
+    };
+
+# ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+    template<>
+    struct StringMaker<std::wstring_view> {
+        static std::string convert(std::wstring_view str);
+    };
+# endif
+
+    template<>
+    struct StringMaker<wchar_t const *> {
+        static std::string convert(wchar_t const * str);
+    };
+    template<>
+    struct StringMaker<wchar_t *> {
+        static std::string convert(wchar_t * str);
+    };
+#endif
+
+    // TBD: Should we use `strnlen` to ensure that we don't go out of the buffer,
+    //      while keeping string semantics?
+    template<int SZ>
+    struct StringMaker<char[SZ]> {
+        static std::string convert(char const* str) {
+            return ::Catch::Detail::stringify(std::string{ str });
+        }
+    };
+    template<int SZ>
+    struct StringMaker<signed char[SZ]> {
+        static std::string convert(signed char const* str) {
+            return ::Catch::Detail::stringify(std::string{ reinterpret_cast<char const *>(str) });
+        }
+    };
+    template<int SZ>
+    struct StringMaker<unsigned char[SZ]> {
+        static std::string convert(unsigned char const* str) {
+            return ::Catch::Detail::stringify(std::string{ reinterpret_cast<char const *>(str) });
+        }
+    };
+
+#if defined(CATCH_CONFIG_CPP17_BYTE)
+    template<>
+    struct StringMaker<std::byte> {
+        static std::string convert(std::byte value);
+    };
+#endif // defined(CATCH_CONFIG_CPP17_BYTE)
+    template<>
+    struct StringMaker<int> {
+        static std::string convert(int value);
+    };
+    template<>
+    struct StringMaker<long> {
+        static std::string convert(long value);
+    };
+    template<>
+    struct StringMaker<long long> {
+        static std::string convert(long long value);
+    };
+    template<>
+    struct StringMaker<unsigned int> {
+        static std::string convert(unsigned int value);
+    };
+    template<>
+    struct StringMaker<unsigned long> {
+        static std::string convert(unsigned long value);
+    };
+    template<>
+    struct StringMaker<unsigned long long> {
+        static std::string convert(unsigned long long value);
+    };
+
+    template<>
+    struct StringMaker<bool> {
+        static std::string convert(bool b);
+    };
+
+    template<>
+    struct StringMaker<char> {
+        static std::string convert(char c);
+    };
+    template<>
+    struct StringMaker<signed char> {
+        static std::string convert(signed char c);
+    };
+    template<>
+    struct StringMaker<unsigned char> {
+        static std::string convert(unsigned char c);
+    };
+
+    template<>
+    struct StringMaker<std::nullptr_t> {
+        static std::string convert(std::nullptr_t);
+    };
+
+    template<>
+    struct StringMaker<float> {
+        static std::string convert(float value);
+        static int precision;
+    };
+
+    template<>
+    struct StringMaker<double> {
+        static std::string convert(double value);
+        static int precision;
+    };
+
+    template <typename T>
+    struct StringMaker<T*> {
+        template <typename U>
+        static std::string convert(U* p) {
+            if (p) {
+                return ::Catch::Detail::rawMemoryToString(p);
+            } else {
+                return "nullptr";
+            }
+        }
+    };
+
+    template <typename R, typename C>
+    struct StringMaker<R C::*> {
+        static std::string convert(R C::* p) {
+            if (p) {
+                return ::Catch::Detail::rawMemoryToString(p);
+            } else {
+                return "nullptr";
+            }
+        }
+    };
+
+#if defined(_MANAGED)
+    template <typename T>
+    struct StringMaker<T^> {
+        static std::string convert( T^ ref ) {
+            return ::Catch::Detail::clrReferenceToString(ref);
+        }
+    };
+#endif
+
+    namespace Detail {
+        template<typename InputIterator, typename Sentinel = InputIterator>
+        std::string rangeToString(InputIterator first, Sentinel last) {
+            ReusableStringStream rss;
+            rss << "{ ";
+            if (first != last) {
+                rss << ::Catch::Detail::stringify(*first);
+                for (++first; first != last; ++first)
+                    rss << ", " << ::Catch::Detail::stringify(*first);
+            }
+            rss << " }";
+            return rss.str();
+        }
+    }
+
+#ifdef __OBJC__
+    template<>
+    struct StringMaker<NSString*> {
+        static std::string convert(NSString * nsstring) {
+            if (!nsstring)
+                return "nil";
+            return std::string("@") + [nsstring UTF8String];
+        }
+    };
+    template<>
+    struct StringMaker<NSObject*> {
+        static std::string convert(NSObject* nsObject) {
+            return ::Catch::Detail::stringify([nsObject description]);
+        }
+
+    };
+    namespace Detail {
+        inline std::string stringify( NSString* nsstring ) {
+            return StringMaker<NSString*>::convert( nsstring );
+        }
+
+    } // namespace Detail
+#endif // __OBJC__
+
+} // namespace Catch
+
+//////////////////////////////////////////////////////
+// Separate std-lib types stringification, so it can be selectively enabled
+// This means that we do not bring in
+
+#if defined(CATCH_CONFIG_ENABLE_ALL_STRINGMAKERS)
+#  define CATCH_CONFIG_ENABLE_PAIR_STRINGMAKER
+#  define CATCH_CONFIG_ENABLE_TUPLE_STRINGMAKER
+#  define CATCH_CONFIG_ENABLE_VARIANT_STRINGMAKER
+#  define CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER
+#  define CATCH_CONFIG_ENABLE_OPTIONAL_STRINGMAKER
+#endif
+
+// Separate std::pair specialization
+#if defined(CATCH_CONFIG_ENABLE_PAIR_STRINGMAKER)
+#include <utility>
+namespace Catch {
+    template<typename T1, typename T2>
+    struct StringMaker<std::pair<T1, T2> > {
+        static std::string convert(const std::pair<T1, T2>& pair) {
+            ReusableStringStream rss;
+            rss << "{ "
+                << ::Catch::Detail::stringify(pair.first)
+                << ", "
+                << ::Catch::Detail::stringify(pair.second)
+                << " }";
+            return rss.str();
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_PAIR_STRINGMAKER
+
+#if defined(CATCH_CONFIG_ENABLE_OPTIONAL_STRINGMAKER) && defined(CATCH_CONFIG_CPP17_OPTIONAL)
+#include <optional>
+namespace Catch {
+    template<typename T>
+    struct StringMaker<std::optional<T> > {
+        static std::string convert(const std::optional<T>& optional) {
+            ReusableStringStream rss;
+            if (optional.has_value()) {
+                rss << ::Catch::Detail::stringify(*optional);
+            } else {
+                rss << "{ }";
+            }
+            return rss.str();
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_OPTIONAL_STRINGMAKER
+
+// Separate std::tuple specialization
+#if defined(CATCH_CONFIG_ENABLE_TUPLE_STRINGMAKER)
+#include <tuple>
+namespace Catch {
+    namespace Detail {
+        template<
+            typename Tuple,
+            std::size_t N = 0,
+            bool = (N < std::tuple_size<Tuple>::value)
+            >
+            struct TupleElementPrinter {
+            static void print(const Tuple& tuple, std::ostream& os) {
+                os << (N ? ", " : " ")
+                    << ::Catch::Detail::stringify(std::get<N>(tuple));
+                TupleElementPrinter<Tuple, N + 1>::print(tuple, os);
+            }
+        };
+
+        template<
+            typename Tuple,
+            std::size_t N
+        >
+            struct TupleElementPrinter<Tuple, N, false> {
+            static void print(const Tuple&, std::ostream&) {}
+        };
+
+    }
+
+    template<typename ...Types>
+    struct StringMaker<std::tuple<Types...>> {
+        static std::string convert(const std::tuple<Types...>& tuple) {
+            ReusableStringStream rss;
+            rss << '{';
+            Detail::TupleElementPrinter<std::tuple<Types...>>::print(tuple, rss.get());
+            rss << " }";
+            return rss.str();
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_TUPLE_STRINGMAKER
+
+#if defined(CATCH_CONFIG_ENABLE_VARIANT_STRINGMAKER) && defined(CATCH_CONFIG_CPP17_VARIANT)
+#include <variant>
+namespace Catch {
+    template<>
+    struct StringMaker<std::monostate> {
+        static std::string convert(const std::monostate&) {
+            return "{ }";
+        }
+    };
+
+    template<typename... Elements>
+    struct StringMaker<std::variant<Elements...>> {
+        static std::string convert(const std::variant<Elements...>& variant) {
+            if (variant.valueless_by_exception()) {
+                return "{valueless variant}";
+            } else {
+                return std::visit(
+                    [](const auto& value) {
+                        return ::Catch::Detail::stringify(value);
+                    },
+                    variant
+                );
+            }
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_VARIANT_STRINGMAKER
+
+namespace Catch {
+    // Import begin/ end from std here
+    using std::begin;
+    using std::end;
+
+    namespace detail {
+        template <typename...>
+        struct void_type {
+            using type = void;
+        };
+
+        template <typename T, typename = void>
+        struct is_range_impl : std::false_type {
+        };
+
+        template <typename T>
+        struct is_range_impl<T, typename void_type<decltype(begin(std::declval<T>()))>::type> : std::true_type {
+        };
+    } // namespace detail
+
+    template <typename T>
+    struct is_range : detail::is_range_impl<T> {
+    };
+
+#if defined(_MANAGED) // Managed types are never ranges
+    template <typename T>
+    struct is_range<T^> {
+        static const bool value = false;
+    };
+#endif
+
+    template<typename Range>
+    std::string rangeToString( Range const& range ) {
+        return ::Catch::Detail::rangeToString( begin( range ), end( range ) );
+    }
+
+    // Handle vector<bool> specially
+    template<typename Allocator>
+    std::string rangeToString( std::vector<bool, Allocator> const& v ) {
+        ReusableStringStream rss;
+        rss << "{ ";
+        bool first = true;
+        for( bool b : v ) {
+            if( first )
+                first = false;
+            else
+                rss << ", ";
+            rss << ::Catch::Detail::stringify( b );
+        }
+        rss << " }";
+        return rss.str();
+    }
+
+    template<typename R>
+    struct StringMaker<R, typename std::enable_if<is_range<R>::value && !::Catch::Detail::IsStreamInsertable<R>::value>::type> {
+        static std::string convert( R const& range ) {
+            return rangeToString( range );
+        }
+    };
+
+    template <typename T, int SZ>
+    struct StringMaker<T[SZ]> {
+        static std::string convert(T const(&arr)[SZ]) {
+            return rangeToString(arr);
+        }
+    };
+
+} // namespace Catch
+
+// Separate std::chrono::duration specialization
+#if defined(CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER)
+#include <ctime>
+#include <ratio>
+#include <chrono>
+
+namespace Catch {
+
+template <class Ratio>
+struct ratio_string {
+    static std::string symbol();
+};
+
+template <class Ratio>
+std::string ratio_string<Ratio>::symbol() {
+    Catch::ReusableStringStream rss;
+    rss << '[' << Ratio::num << '/'
+        << Ratio::den << ']';
+    return rss.str();
+}
+template <>
+struct ratio_string<std::atto> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::femto> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::pico> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::nano> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::micro> {
+    static std::string symbol();
+};
+template <>
+struct ratio_string<std::milli> {
+    static std::string symbol();
+};
+
+    ////////////
+    // std::chrono::duration specializations
+    template<typename Value, typename Ratio>
+    struct StringMaker<std::chrono::duration<Value, Ratio>> {
+        static std::string convert(std::chrono::duration<Value, Ratio> const& duration) {
+            ReusableStringStream rss;
+            rss << duration.count() << ' ' << ratio_string<Ratio>::symbol() << 's';
+            return rss.str();
+        }
+    };
+    template<typename Value>
+    struct StringMaker<std::chrono::duration<Value, std::ratio<1>>> {
+        static std::string convert(std::chrono::duration<Value, std::ratio<1>> const& duration) {
+            ReusableStringStream rss;
+            rss << duration.count() << " s";
+            return rss.str();
+        }
+    };
+    template<typename Value>
+    struct StringMaker<std::chrono::duration<Value, std::ratio<60>>> {
+        static std::string convert(std::chrono::duration<Value, std::ratio<60>> const& duration) {
+            ReusableStringStream rss;
+            rss << duration.count() << " m";
+            return rss.str();
+        }
+    };
+    template<typename Value>
+    struct StringMaker<std::chrono::duration<Value, std::ratio<3600>>> {
+        static std::string convert(std::chrono::duration<Value, std::ratio<3600>> const& duration) {
+            ReusableStringStream rss;
+            rss << duration.count() << " h";
+            return rss.str();
+        }
+    };
+
+    ////////////
+    // std::chrono::time_point specialization
+    // Generic time_point cannot be specialized, only std::chrono::time_point<system_clock>
+    template<typename Clock, typename Duration>
+    struct StringMaker<std::chrono::time_point<Clock, Duration>> {
+        static std::string convert(std::chrono::time_point<Clock, Duration> const& time_point) {
+            return ::Catch::Detail::stringify(time_point.time_since_epoch()) + " since epoch";
+        }
+    };
+    // std::chrono::time_point<system_clock> specialization
+    template<typename Duration>
+    struct StringMaker<std::chrono::time_point<std::chrono::system_clock, Duration>> {
+        static std::string convert(std::chrono::time_point<std::chrono::system_clock, Duration> const& time_point) {
+            auto converted = std::chrono::system_clock::to_time_t(time_point);
+
+#ifdef _MSC_VER
+            std::tm timeInfo = {};
+            gmtime_s(&timeInfo, &converted);
+#else
+            std::tm* timeInfo = std::gmtime(&converted);
+#endif
+
+            auto const timeStampSize = sizeof("2017-01-16T17:06:45Z");
+            char timeStamp[timeStampSize];
+            const char * const fmt = "%Y-%m-%dT%H:%M:%SZ";
+
+#ifdef _MSC_VER
+            std::strftime(timeStamp, timeStampSize, fmt, &timeInfo);
+#else
+            std::strftime(timeStamp, timeStampSize, fmt, timeInfo);
+#endif
+            return std::string(timeStamp);
+        }
+    };
+}
+#endif // CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER
+
+#define INTERNAL_CATCH_REGISTER_ENUM( enumName, ... ) \
+namespace Catch { \
+    template<> struct StringMaker<enumName> { \
+        static std::string convert( enumName value ) { \
+            static const auto& enumInfo = ::Catch::getMutableRegistryHub().getMutableEnumValuesRegistry().registerEnum( #enumName, #__VA_ARGS__, { __VA_ARGS__ } ); \
+            return static_cast<std::string>(enumInfo.lookup( static_cast<int>( value ) )); \
+        } \
+    }; \
+}
+
+#define CATCH_REGISTER_ENUM( enumName, ... ) INTERNAL_CATCH_REGISTER_ENUM( enumName, __VA_ARGS__ )
+
+#ifdef _MSC_VER
+#pragma warning(pop)
+#endif
+
+// end catch_tostring.h
+#include <iosfwd>
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable:4389) // '==' : signed/unsigned mismatch
+#pragma warning(disable:4018) // more "signed/unsigned mismatch"
+#pragma warning(disable:4312) // Converting int to T* using reinterpret_cast (issue on x64 platform)
+#pragma warning(disable:4180) // qualifier applied to function type has no meaning
+#pragma warning(disable:4800) // Forcing result to true or false
+#endif
+
+namespace Catch {
+
+    struct ITransientExpression {
+        auto isBinaryExpression() const -> bool { return m_isBinaryExpression; }
+        auto getResult() const -> bool { return m_result; }
+        virtual void streamReconstructedExpression( std::ostream &os ) const = 0;
+
+        ITransientExpression( bool isBinaryExpression, bool result )
+        :   m_isBinaryExpression( isBinaryExpression ),
+            m_result( result )
+        {}
+
+        // We don't actually need a virtual destructor, but many static analysers
+        // complain if it's not here :-(
+        virtual ~ITransientExpression();
+
+        bool m_isBinaryExpression;
+        bool m_result;
+
+    };
+
+    void formatReconstructedExpression( std::ostream &os, std::string const& lhs, StringRef op, std::string const& rhs );
+
+    template<typename LhsT, typename RhsT>
+    class BinaryExpr  : public ITransientExpression {
+        LhsT m_lhs;
+        StringRef m_op;
+        RhsT m_rhs;
+
+        void streamReconstructedExpression( std::ostream &os ) const override {
+            formatReconstructedExpression
+                    ( os, Catch::Detail::stringify( m_lhs ), m_op, Catch::Detail::stringify( m_rhs ) );
+        }
+
+    public:
+        BinaryExpr( bool comparisonResult, LhsT lhs, StringRef op, RhsT rhs )
+        :   ITransientExpression{ true, comparisonResult },
+            m_lhs( lhs ),
+            m_op( op ),
+            m_rhs( rhs )
+        {}
+
+        template<typename T>
+        auto operator && ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator || ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator == ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator != ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator > ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator < ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator >= ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename T>
+        auto operator <= ( T ) const -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<T>::value,
+            "chained comparisons are not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+    };
+
+    template<typename LhsT>
+    class UnaryExpr : public ITransientExpression {
+        LhsT m_lhs;
+
+        void streamReconstructedExpression( std::ostream &os ) const override {
+            os << Catch::Detail::stringify( m_lhs );
+        }
+
+    public:
+        explicit UnaryExpr( LhsT lhs )
+        :   ITransientExpression{ false, static_cast<bool>(lhs) },
+            m_lhs( lhs )
+        {}
+    };
+
+    // Specialised comparison functions to handle equality comparisons between ints and pointers (NULL deduces as an int)
+    template<typename LhsT, typename RhsT>
+    auto compareEqual( LhsT const& lhs, RhsT const& rhs ) -> bool { return static_cast<bool>(lhs == rhs); }
+    template<typename T>
+    auto compareEqual( T* const& lhs, int rhs ) -> bool { return lhs == reinterpret_cast<void const*>( rhs ); }
+    template<typename T>
+    auto compareEqual( T* const& lhs, long rhs ) -> bool { return lhs == reinterpret_cast<void const*>( rhs ); }
+    template<typename T>
+    auto compareEqual( int lhs, T* const& rhs ) -> bool { return reinterpret_cast<void const*>( lhs ) == rhs; }
+    template<typename T>
+    auto compareEqual( long lhs, T* const& rhs ) -> bool { return reinterpret_cast<void const*>( lhs ) == rhs; }
+
+    template<typename LhsT, typename RhsT>
+    auto compareNotEqual( LhsT const& lhs, RhsT&& rhs ) -> bool { return static_cast<bool>(lhs != rhs); }
+    template<typename T>
+    auto compareNotEqual( T* const& lhs, int rhs ) -> bool { return lhs != reinterpret_cast<void const*>( rhs ); }
+    template<typename T>
+    auto compareNotEqual( T* const& lhs, long rhs ) -> bool { return lhs != reinterpret_cast<void const*>( rhs ); }
+    template<typename T>
+    auto compareNotEqual( int lhs, T* const& rhs ) -> bool { return reinterpret_cast<void const*>( lhs ) != rhs; }
+    template<typename T>
+    auto compareNotEqual( long lhs, T* const& rhs ) -> bool { return reinterpret_cast<void const*>( lhs ) != rhs; }
+
+    template<typename LhsT>
+    class ExprLhs {
+        LhsT m_lhs;
+    public:
+        explicit ExprLhs( LhsT lhs ) : m_lhs( lhs ) {}
+
+        template<typename RhsT>
+        auto operator == ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { compareEqual( m_lhs, rhs ), m_lhs, "==", rhs };
+        }
+        auto operator == ( bool rhs ) -> BinaryExpr<LhsT, bool> const {
+            return { m_lhs == rhs, m_lhs, "==", rhs };
+        }
+
+        template<typename RhsT>
+        auto operator != ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { compareNotEqual( m_lhs, rhs ), m_lhs, "!=", rhs };
+        }
+        auto operator != ( bool rhs ) -> BinaryExpr<LhsT, bool> const {
+            return { m_lhs != rhs, m_lhs, "!=", rhs };
+        }
+
+        template<typename RhsT>
+        auto operator > ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs > rhs), m_lhs, ">", rhs };
+        }
+        template<typename RhsT>
+        auto operator < ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs < rhs), m_lhs, "<", rhs };
+        }
+        template<typename RhsT>
+        auto operator >= ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs >= rhs), m_lhs, ">=", rhs };
+        }
+        template<typename RhsT>
+        auto operator <= ( RhsT const& rhs ) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs <= rhs), m_lhs, "<=", rhs };
+        }
+        template <typename RhsT>
+        auto operator | (RhsT const& rhs) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs | rhs), m_lhs, "|", rhs };
+        }
+        template <typename RhsT>
+        auto operator & (RhsT const& rhs) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs & rhs), m_lhs, "&", rhs };
+        }
+        template <typename RhsT>
+        auto operator ^ (RhsT const& rhs) -> BinaryExpr<LhsT, RhsT const&> const {
+            return { static_cast<bool>(m_lhs ^ rhs), m_lhs, "^", rhs };
+        }
+
+        template<typename RhsT>
+        auto operator && ( RhsT const& ) -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<RhsT>::value,
+            "operator&& is not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        template<typename RhsT>
+        auto operator || ( RhsT const& ) -> BinaryExpr<LhsT, RhsT const&> const {
+            static_assert(always_false<RhsT>::value,
+            "operator|| is not supported inside assertions, "
+            "wrap the expression inside parentheses, or decompose it");
+        }
+
+        auto makeUnaryExpr() const -> UnaryExpr<LhsT> {
+            return UnaryExpr<LhsT>{ m_lhs };
+        }
+    };
+
+    void handleExpression( ITransientExpression const& expr );
+
+    template<typename T>
+    void handleExpression( ExprLhs<T> const& expr ) {
+        handleExpression( expr.makeUnaryExpr() );
+    }
+
+    struct Decomposer {
+        template<typename T>
+        auto operator <= ( T const& lhs ) -> ExprLhs<T const&> {
+            return ExprLhs<T const&>{ lhs };
+        }
+
+        auto operator <=( bool value ) -> ExprLhs<bool> {
+            return ExprLhs<bool>{ value };
+        }
+    };
+
+} // end namespace Catch
+
+#ifdef _MSC_VER
+#pragma warning(pop)
+#endif
+
+// end catch_decomposer.h
+// start catch_interfaces_capture.h
+
+#include <string>
+#include <chrono>
+
+namespace Catch {
+
+    class AssertionResult;
+    struct AssertionInfo;
+    struct SectionInfo;
+    struct SectionEndInfo;
+    struct MessageInfo;
+    struct MessageBuilder;
+    struct Counts;
+    struct AssertionReaction;
+    struct SourceLineInfo;
+
+    struct ITransientExpression;
+    struct IGeneratorTracker;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    struct BenchmarkInfo;
+    template <typename Duration = std::chrono::duration<double, std::nano>>
+    struct BenchmarkStats;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    struct IResultCapture {
+
+        virtual ~IResultCapture();
+
+        virtual bool sectionStarted(    SectionInfo const& sectionInfo,
+                                        Counts& assertions ) = 0;
+        virtual void sectionEnded( SectionEndInfo const& endInfo ) = 0;
+        virtual void sectionEndedEarly( SectionEndInfo const& endInfo ) = 0;
+
+        virtual auto acquireGeneratorTracker( StringRef generatorName, SourceLineInfo const& lineInfo ) -> IGeneratorTracker& = 0;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        virtual void benchmarkPreparing( std::string const& name ) = 0;
+        virtual void benchmarkStarting( BenchmarkInfo const& info ) = 0;
+        virtual void benchmarkEnded( BenchmarkStats<> const& stats ) = 0;
+        virtual void benchmarkFailed( std::string const& error ) = 0;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        virtual void pushScopedMessage( MessageInfo const& message ) = 0;
+        virtual void popScopedMessage( MessageInfo const& message ) = 0;
+
+        virtual void emplaceUnscopedMessage( MessageBuilder const& builder ) = 0;
+
+        virtual void handleFatalErrorCondition( StringRef message ) = 0;
+
+        virtual void handleExpr
+                (   AssertionInfo const& info,
+                    ITransientExpression const& expr,
+                    AssertionReaction& reaction ) = 0;
+        virtual void handleMessage
+                (   AssertionInfo const& info,
+                    ResultWas::OfType resultType,
+                    StringRef const& message,
+                    AssertionReaction& reaction ) = 0;
+        virtual void handleUnexpectedExceptionNotThrown
+                (   AssertionInfo const& info,
+                    AssertionReaction& reaction ) = 0;
+        virtual void handleUnexpectedInflightException
+                (   AssertionInfo const& info,
+                    std::string const& message,
+                    AssertionReaction& reaction ) = 0;
+        virtual void handleIncomplete
+                (   AssertionInfo const& info ) = 0;
+        virtual void handleNonExpr
+                (   AssertionInfo const &info,
+                    ResultWas::OfType resultType,
+                    AssertionReaction &reaction ) = 0;
+
+        virtual bool lastAssertionPassed() = 0;
+        virtual void assertionPassed() = 0;
+
+        // Deprecated, do not use:
+        virtual std::string getCurrentTestName() const = 0;
+        virtual const AssertionResult* getLastResult() const = 0;
+        virtual void exceptionEarlyReported() = 0;
+    };
+
+    IResultCapture& getResultCapture();
+}
+
+// end catch_interfaces_capture.h
+namespace Catch {
+
+    struct TestFailureException{};
+    struct AssertionResultData;
+    struct IResultCapture;
+    class RunContext;
+
+    class LazyExpression {
+        friend class AssertionHandler;
+        friend struct AssertionStats;
+        friend class RunContext;
+
+        ITransientExpression const* m_transientExpression = nullptr;
+        bool m_isNegated;
+    public:
+        LazyExpression( bool isNegated );
+        LazyExpression( LazyExpression const& other );
+        LazyExpression& operator = ( LazyExpression const& ) = delete;
+
+        explicit operator bool() const;
+
+        friend auto operator << ( std::ostream& os, LazyExpression const& lazyExpr ) -> std::ostream&;
+    };
+
+    struct AssertionReaction {
+        bool shouldDebugBreak = false;
+        bool shouldThrow = false;
+    };
+
+    class AssertionHandler {
+        AssertionInfo m_assertionInfo;
+        AssertionReaction m_reaction;
+        bool m_completed = false;
+        IResultCapture& m_resultCapture;
+
+    public:
+        AssertionHandler
+            (   StringRef const& macroName,
+                SourceLineInfo const& lineInfo,
+                StringRef capturedExpression,
+                ResultDisposition::Flags resultDisposition );
+        ~AssertionHandler() {
+            if ( !m_completed ) {
+                m_resultCapture.handleIncomplete( m_assertionInfo );
+            }
+        }
+
+        template<typename T>
+        void handleExpr( ExprLhs<T> const& expr ) {
+            handleExpr( expr.makeUnaryExpr() );
+        }
+        void handleExpr( ITransientExpression const& expr );
+
+        void handleMessage(ResultWas::OfType resultType, StringRef const& message);
+
+        void handleExceptionThrownAsExpected();
+        void handleUnexpectedExceptionNotThrown();
+        void handleExceptionNotThrownAsExpected();
+        void handleThrowingCallSkipped();
+        void handleUnexpectedInflightException();
+
+        void complete();
+        void setCompleted();
+
+        // query
+        auto allowThrows() const -> bool;
+    };
+
+    void handleExceptionMatchExpr( AssertionHandler& handler, std::string const& str, StringRef const& matcherString );
+
+} // namespace Catch
+
+// end catch_assertionhandler.h
+// start catch_message.h
+
+#include <string>
+#include <vector>
+
+namespace Catch {
+
+    struct MessageInfo {
+        MessageInfo(    StringRef const& _macroName,
+                        SourceLineInfo const& _lineInfo,
+                        ResultWas::OfType _type );
+
+        StringRef macroName;
+        std::string message;
+        SourceLineInfo lineInfo;
+        ResultWas::OfType type;
+        unsigned int sequence;
+
+        bool operator == ( MessageInfo const& other ) const;
+        bool operator < ( MessageInfo const& other ) const;
+    private:
+        static unsigned int globalCount;
+    };
+
+    struct MessageStream {
+
+        template<typename T>
+        MessageStream& operator << ( T const& value ) {
+            m_stream << value;
+            return *this;
+        }
+
+        ReusableStringStream m_stream;
+    };
+
+    struct MessageBuilder : MessageStream {
+        MessageBuilder( StringRef const& macroName,
+                        SourceLineInfo const& lineInfo,
+                        ResultWas::OfType type );
+
+        template<typename T>
+        MessageBuilder& operator << ( T const& value ) {
+            m_stream << value;
+            return *this;
+        }
+
+        MessageInfo m_info;
+    };
+
+    class ScopedMessage {
+    public:
+        explicit ScopedMessage( MessageBuilder const& builder );
+        ScopedMessage( ScopedMessage& duplicate ) = delete;
+        ScopedMessage( ScopedMessage&& old );
+        ~ScopedMessage();
+
+        MessageInfo m_info;
+        bool m_moved;
+    };
+
+    class Capturer {
+        std::vector<MessageInfo> m_messages;
+        IResultCapture& m_resultCapture = getResultCapture();
+        size_t m_captured = 0;
+    public:
+        Capturer( StringRef macroName, SourceLineInfo const& lineInfo, ResultWas::OfType resultType, StringRef names );
+        ~Capturer();
+
+        void captureValue( size_t index, std::string const& value );
+
+        template<typename T>
+        void captureValues( size_t index, T const& value ) {
+            captureValue( index, Catch::Detail::stringify( value ) );
+        }
+
+        template<typename T, typename... Ts>
+        void captureValues( size_t index, T const& value, Ts const&... values ) {
+            captureValue( index, Catch::Detail::stringify(value) );
+            captureValues( index+1, values... );
+        }
+    };
+
+} // end namespace Catch
+
+// end catch_message.h
+#if !defined(CATCH_CONFIG_DISABLE)
+
+#if !defined(CATCH_CONFIG_DISABLE_STRINGIFICATION)
+  #define CATCH_INTERNAL_STRINGIFY(...) #__VA_ARGS__
+#else
+  #define CATCH_INTERNAL_STRINGIFY(...) "Disabled by CATCH_CONFIG_DISABLE_STRINGIFICATION"
+#endif
+
+#if defined(CATCH_CONFIG_FAST_COMPILE) || defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+
+///////////////////////////////////////////////////////////////////////////////
+// Another way to speed-up compilation is to omit local try-catch for REQUIRE*
+// macros.
+#define INTERNAL_CATCH_TRY
+#define INTERNAL_CATCH_CATCH( capturer )
+
+#else // CATCH_CONFIG_FAST_COMPILE
+
+#define INTERNAL_CATCH_TRY try
+#define INTERNAL_CATCH_CATCH( handler ) catch(...) { handler.handleUnexpectedInflightException(); }
+
+#endif
+
+#define INTERNAL_CATCH_REACT( handler ) handler.complete();
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_TEST( macroName, resultDisposition, ... ) \
+    do { \
+        CATCH_INTERNAL_IGNORE_BUT_WARN(__VA_ARGS__); \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__), resultDisposition ); \
+        INTERNAL_CATCH_TRY { \
+            CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+            CATCH_INTERNAL_SUPPRESS_PARENTHESES_WARNINGS \
+            catchAssertionHandler.handleExpr( Catch::Decomposer() <= __VA_ARGS__ ); \
+            CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+        } INTERNAL_CATCH_CATCH( catchAssertionHandler ) \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( (void)0, (false) && static_cast<bool>( !!(__VA_ARGS__) ) )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_IF( macroName, resultDisposition, ... ) \
+    INTERNAL_CATCH_TEST( macroName, resultDisposition, __VA_ARGS__ ); \
+    if( Catch::getResultCapture().lastAssertionPassed() )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_ELSE( macroName, resultDisposition, ... ) \
+    INTERNAL_CATCH_TEST( macroName, resultDisposition, __VA_ARGS__ ); \
+    if( !Catch::getResultCapture().lastAssertionPassed() )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_NO_THROW( macroName, resultDisposition, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__), resultDisposition ); \
+        try { \
+            static_cast<void>(__VA_ARGS__); \
+            catchAssertionHandler.handleExceptionNotThrownAsExpected(); \
+        } \
+        catch( ... ) { \
+            catchAssertionHandler.handleUnexpectedInflightException(); \
+        } \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_THROWS( macroName, resultDisposition, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__), resultDisposition); \
+        if( catchAssertionHandler.allowThrows() ) \
+            try { \
+                static_cast<void>(__VA_ARGS__); \
+                catchAssertionHandler.handleUnexpectedExceptionNotThrown(); \
+            } \
+            catch( ... ) { \
+                catchAssertionHandler.handleExceptionThrownAsExpected(); \
+            } \
+        else \
+            catchAssertionHandler.handleThrowingCallSkipped(); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_THROWS_AS( macroName, exceptionType, resultDisposition, expr ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(expr) ", " CATCH_INTERNAL_STRINGIFY(exceptionType), resultDisposition ); \
+        if( catchAssertionHandler.allowThrows() ) \
+            try { \
+                static_cast<void>(expr); \
+                catchAssertionHandler.handleUnexpectedExceptionNotThrown(); \
+            } \
+            catch( exceptionType const& ) { \
+                catchAssertionHandler.handleExceptionThrownAsExpected(); \
+            } \
+            catch( ... ) { \
+                catchAssertionHandler.handleUnexpectedInflightException(); \
+            } \
+        else \
+            catchAssertionHandler.handleThrowingCallSkipped(); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_MSG( macroName, messageType, resultDisposition, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, Catch::StringRef(), resultDisposition ); \
+        catchAssertionHandler.handleMessage( messageType, ( Catch::MessageStream() << __VA_ARGS__ + ::Catch::StreamEndStop() ).m_stream.str() ); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_CAPTURE( varName, macroName, ... ) \
+    auto varName = Catch::Capturer( macroName, CATCH_INTERNAL_LINEINFO, Catch::ResultWas::Info, #__VA_ARGS__ ); \
+    varName.captureValues( 0, __VA_ARGS__ )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_INFO( macroName, log ) \
+    Catch::ScopedMessage INTERNAL_CATCH_UNIQUE_NAME( scopedMessage )( Catch::MessageBuilder( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, Catch::ResultWas::Info ) << log );
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_UNSCOPED_INFO( macroName, log ) \
+    Catch::getResultCapture().emplaceUnscopedMessage( Catch::MessageBuilder( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, Catch::ResultWas::Info ) << log )
+
+///////////////////////////////////////////////////////////////////////////////
+// Although this is matcher-based, it can be used with just a string
+#define INTERNAL_CATCH_THROWS_STR_MATCHES( macroName, resultDisposition, matcher, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__) ", " CATCH_INTERNAL_STRINGIFY(matcher), resultDisposition ); \
+        if( catchAssertionHandler.allowThrows() ) \
+            try { \
+                static_cast<void>(__VA_ARGS__); \
+                catchAssertionHandler.handleUnexpectedExceptionNotThrown(); \
+            } \
+            catch( ... ) { \
+                Catch::handleExceptionMatchExpr( catchAssertionHandler, matcher, #matcher##_catch_sr ); \
+            } \
+        else \
+            catchAssertionHandler.handleThrowingCallSkipped(); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+#endif // CATCH_CONFIG_DISABLE
+
+// end catch_capture.hpp
+// start catch_section.h
+
+// start catch_section_info.h
+
+// start catch_totals.h
+
+#include <cstddef>
+
+namespace Catch {
+
+    struct Counts {
+        Counts operator - ( Counts const& other ) const;
+        Counts& operator += ( Counts const& other );
+
+        std::size_t total() const;
+        bool allPassed() const;
+        bool allOk() const;
+
+        std::size_t passed = 0;
+        std::size_t failed = 0;
+        std::size_t failedButOk = 0;
+    };
+
+    struct Totals {
+
+        Totals operator - ( Totals const& other ) const;
+        Totals& operator += ( Totals const& other );
+
+        Totals delta( Totals const& prevTotals ) const;
+
+        int error = 0;
+        Counts assertions;
+        Counts testCases;
+    };
+}
+
+// end catch_totals.h
+#include <string>
+
+namespace Catch {
+
+    struct SectionInfo {
+        SectionInfo
+            (   SourceLineInfo const& _lineInfo,
+                std::string const& _name );
+
+        // Deprecated
+        SectionInfo
+            (   SourceLineInfo const& _lineInfo,
+                std::string const& _name,
+                std::string const& ) : SectionInfo( _lineInfo, _name ) {}
+
+        std::string name;
+        std::string description; // !Deprecated: this will always be empty
+        SourceLineInfo lineInfo;
+    };
+
+    struct SectionEndInfo {
+        SectionInfo sectionInfo;
+        Counts prevAssertions;
+        double durationInSeconds;
+    };
+
+} // end namespace Catch
+
+// end catch_section_info.h
+// start catch_timer.h
+
+#include <cstdint>
+
+namespace Catch {
+
+    auto getCurrentNanosecondsSinceEpoch() -> uint64_t;
+    auto getEstimatedClockResolution() -> uint64_t;
+
+    class Timer {
+        uint64_t m_nanoseconds = 0;
+    public:
+        void start();
+        auto getElapsedNanoseconds() const -> uint64_t;
+        auto getElapsedMicroseconds() const -> uint64_t;
+        auto getElapsedMilliseconds() const -> unsigned int;
+        auto getElapsedSeconds() const -> double;
+    };
+
+} // namespace Catch
+
+// end catch_timer.h
+#include <string>
+
+namespace Catch {
+
+    class Section : NonCopyable {
+    public:
+        Section( SectionInfo const& info );
+        ~Section();
+
+        // This indicates whether the section should be executed or not
+        explicit operator bool() const;
+
+    private:
+        SectionInfo m_info;
+
+        std::string m_name;
+        Counts m_assertions;
+        bool m_sectionIncluded;
+        Timer m_timer;
+    };
+
+} // end namespace Catch
+
+#define INTERNAL_CATCH_SECTION( ... ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+    CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS \
+    if( Catch::Section const& INTERNAL_CATCH_UNIQUE_NAME( catch_internal_Section ) = Catch::SectionInfo( CATCH_INTERNAL_LINEINFO, __VA_ARGS__ ) ) \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+#define INTERNAL_CATCH_DYNAMIC_SECTION( ... ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+    CATCH_INTERNAL_SUPPRESS_UNUSED_WARNINGS \
+    if( Catch::Section const& INTERNAL_CATCH_UNIQUE_NAME( catch_internal_Section ) = Catch::SectionInfo( CATCH_INTERNAL_LINEINFO, (Catch::ReusableStringStream() << __VA_ARGS__).str() ) ) \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+// end catch_section.h
+// start catch_interfaces_exception.h
+
+// start catch_interfaces_registry_hub.h
+
+#include <string>
+#include <memory>
+
+namespace Catch {
+
+    class TestCase;
+    struct ITestCaseRegistry;
+    struct IExceptionTranslatorRegistry;
+    struct IExceptionTranslator;
+    struct IReporterRegistry;
+    struct IReporterFactory;
+    struct ITagAliasRegistry;
+    struct IMutableEnumValuesRegistry;
+
+    class StartupExceptionRegistry;
+
+    using IReporterFactoryPtr = std::shared_ptr<IReporterFactory>;
+
+    struct IRegistryHub {
+        virtual ~IRegistryHub();
+
+        virtual IReporterRegistry const& getReporterRegistry() const = 0;
+        virtual ITestCaseRegistry const& getTestCaseRegistry() const = 0;
+        virtual ITagAliasRegistry const& getTagAliasRegistry() const = 0;
+        virtual IExceptionTranslatorRegistry const& getExceptionTranslatorRegistry() const = 0;
+
+        virtual StartupExceptionRegistry const& getStartupExceptionRegistry() const = 0;
+    };
+
+    struct IMutableRegistryHub {
+        virtual ~IMutableRegistryHub();
+        virtual void registerReporter( std::string const& name, IReporterFactoryPtr const& factory ) = 0;
+        virtual void registerListener( IReporterFactoryPtr const& factory ) = 0;
+        virtual void registerTest( TestCase const& testInfo ) = 0;
+        virtual void registerTranslator( const IExceptionTranslator* translator ) = 0;
+        virtual void registerTagAlias( std::string const& alias, std::string const& tag, SourceLineInfo const& lineInfo ) = 0;
+        virtual void registerStartupException() noexcept = 0;
+        virtual IMutableEnumValuesRegistry& getMutableEnumValuesRegistry() = 0;
+    };
+
+    IRegistryHub const& getRegistryHub();
+    IMutableRegistryHub& getMutableRegistryHub();
+    void cleanUp();
+    std::string translateActiveException();
+
+}
+
+// end catch_interfaces_registry_hub.h
+#if defined(CATCH_CONFIG_DISABLE)
+    #define INTERNAL_CATCH_TRANSLATE_EXCEPTION_NO_REG( translatorName, signature) \
+        static std::string translatorName( signature )
+#endif
+
+#include <exception>
+#include <string>
+#include <vector>
+
+namespace Catch {
+    using exceptionTranslateFunction = std::string(*)();
+
+    struct IExceptionTranslator;
+    using ExceptionTranslators = std::vector<std::unique_ptr<IExceptionTranslator const>>;
+
+    struct IExceptionTranslator {
+        virtual ~IExceptionTranslator();
+        virtual std::string translate( ExceptionTranslators::const_iterator it, ExceptionTranslators::const_iterator itEnd ) const = 0;
+    };
+
+    struct IExceptionTranslatorRegistry {
+        virtual ~IExceptionTranslatorRegistry();
+
+        virtual std::string translateActiveException() const = 0;
+    };
+
+    class ExceptionTranslatorRegistrar {
+        template<typename T>
+        class ExceptionTranslator : public IExceptionTranslator {
+        public:
+
+            ExceptionTranslator( std::string(*translateFunction)( T& ) )
+            : m_translateFunction( translateFunction )
+            {}
+
+            std::string translate( ExceptionTranslators::const_iterator it, ExceptionTranslators::const_iterator itEnd ) const override {
+#if defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+                return "";
+#else
+                try {
+                    if( it == itEnd )
+                        std::rethrow_exception(std::current_exception());
+                    else
+                        return (*it)->translate( it+1, itEnd );
+                }
+                catch( T& ex ) {
+                    return m_translateFunction( ex );
+                }
+#endif
+            }
+
+        protected:
+            std::string(*m_translateFunction)( T& );
+        };
+
+    public:
+        template<typename T>
+        ExceptionTranslatorRegistrar( std::string(*translateFunction)( T& ) ) {
+            getMutableRegistryHub().registerTranslator
+                ( new ExceptionTranslator<T>( translateFunction ) );
+        }
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_TRANSLATE_EXCEPTION2( translatorName, signature ) \
+    static std::string translatorName( signature ); \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION \
+    CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS \
+    namespace{ Catch::ExceptionTranslatorRegistrar INTERNAL_CATCH_UNIQUE_NAME( catch_internal_ExceptionRegistrar )( &translatorName ); } \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION \
+    static std::string translatorName( signature )
+
+#define INTERNAL_CATCH_TRANSLATE_EXCEPTION( signature ) INTERNAL_CATCH_TRANSLATE_EXCEPTION2( INTERNAL_CATCH_UNIQUE_NAME( catch_internal_ExceptionTranslator ), signature )
+
+// end catch_interfaces_exception.h
+// start catch_approx.h
+
+#include <type_traits>
+
+namespace Catch {
+namespace Detail {
+
+    class Approx {
+    private:
+        bool equalityComparisonImpl(double other) const;
+        // Validates the new margin (margin >= 0)
+        // out-of-line to avoid including stdexcept in the header
+        void setMargin(double margin);
+        // Validates the new epsilon (0 < epsilon < 1)
+        // out-of-line to avoid including stdexcept in the header
+        void setEpsilon(double epsilon);
+
+    public:
+        explicit Approx ( double value );
+
+        static Approx custom();
+
+        Approx operator-() const;
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        Approx operator()( T const& value ) const {
+            Approx approx( static_cast<double>(value) );
+            approx.m_epsilon = m_epsilon;
+            approx.m_margin = m_margin;
+            approx.m_scale = m_scale;
+            return approx;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        explicit Approx( T const& value ): Approx(static_cast<double>(value))
+        {}
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator == ( const T& lhs, Approx const& rhs ) {
+            auto lhs_v = static_cast<double>(lhs);
+            return rhs.equalityComparisonImpl(lhs_v);
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator == ( Approx const& lhs, const T& rhs ) {
+            return operator==( rhs, lhs );
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator != ( T const& lhs, Approx const& rhs ) {
+            return !operator==( lhs, rhs );
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator != ( Approx const& lhs, T const& rhs ) {
+            return !operator==( rhs, lhs );
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator <= ( T const& lhs, Approx const& rhs ) {
+            return static_cast<double>(lhs) < rhs.m_value || lhs == rhs;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator <= ( Approx const& lhs, T const& rhs ) {
+            return lhs.m_value < static_cast<double>(rhs) || lhs == rhs;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator >= ( T const& lhs, Approx const& rhs ) {
+            return static_cast<double>(lhs) > rhs.m_value || lhs == rhs;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        friend bool operator >= ( Approx const& lhs, T const& rhs ) {
+            return lhs.m_value > static_cast<double>(rhs) || lhs == rhs;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        Approx& epsilon( T const& newEpsilon ) {
+            double epsilonAsDouble = static_cast<double>(newEpsilon);
+            setEpsilon(epsilonAsDouble);
+            return *this;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        Approx& margin( T const& newMargin ) {
+            double marginAsDouble = static_cast<double>(newMargin);
+            setMargin(marginAsDouble);
+            return *this;
+        }
+
+        template <typename T, typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+        Approx& scale( T const& newScale ) {
+            m_scale = static_cast<double>(newScale);
+            return *this;
+        }
+
+        std::string toString() const;
+
+    private:
+        double m_epsilon;
+        double m_margin;
+        double m_scale;
+        double m_value;
+    };
+} // end namespace Detail
+
+namespace literals {
+    Detail::Approx operator "" _a(long double val);
+    Detail::Approx operator "" _a(unsigned long long val);
+} // end namespace literals
+
+template<>
+struct StringMaker<Catch::Detail::Approx> {
+    static std::string convert(Catch::Detail::Approx const& value);
+};
+
+} // end namespace Catch
+
+// end catch_approx.h
+// start catch_string_manip.h
+
+#include <string>
+#include <iosfwd>
+#include <vector>
+
+namespace Catch {
+
+    bool startsWith( std::string const& s, std::string const& prefix );
+    bool startsWith( std::string const& s, char prefix );
+    bool endsWith( std::string const& s, std::string const& suffix );
+    bool endsWith( std::string const& s, char suffix );
+    bool contains( std::string const& s, std::string const& infix );
+    void toLowerInPlace( std::string& s );
+    std::string toLower( std::string const& s );
+    //! Returns a new string without whitespace at the start/end
+    std::string trim( std::string const& str );
+    //! Returns a substring of the original ref without whitespace. Beware lifetimes!
+    StringRef trim(StringRef ref);
+
+    // !!! Be aware, returns refs into original string - make sure original string outlives them
+    std::vector<StringRef> splitStringRef( StringRef str, char delimiter );
+    bool replaceInPlace( std::string& str, std::string const& replaceThis, std::string const& withThis );
+
+    struct pluralise {
+        pluralise( std::size_t count, std::string const& label );
+
+        friend std::ostream& operator << ( std::ostream& os, pluralise const& pluraliser );
+
+        std::size_t m_count;
+        std::string m_label;
+    };
+}
+
+// end catch_string_manip.h
+#ifndef CATCH_CONFIG_DISABLE_MATCHERS
+// start catch_capture_matchers.h
+
+// start catch_matchers.h
+
+#include <string>
+#include <vector>
+
+namespace Catch {
+namespace Matchers {
+    namespace Impl {
+
+        template<typename ArgT> struct MatchAllOf;
+        template<typename ArgT> struct MatchAnyOf;
+        template<typename ArgT> struct MatchNotOf;
+
+        class MatcherUntypedBase {
+        public:
+            MatcherUntypedBase() = default;
+            MatcherUntypedBase ( MatcherUntypedBase const& ) = default;
+            MatcherUntypedBase& operator = ( MatcherUntypedBase const& ) = delete;
+            std::string toString() const;
+
+        protected:
+            virtual ~MatcherUntypedBase();
+            virtual std::string describe() const = 0;
+            mutable std::string m_cachedToString;
+        };
+
+#ifdef __clang__
+#    pragma clang diagnostic push
+#    pragma clang diagnostic ignored "-Wnon-virtual-dtor"
+#endif
+
+        template<typename ObjectT>
+        struct MatcherMethod {
+            virtual bool match( ObjectT const& arg ) const = 0;
+        };
+
+#if defined(__OBJC__)
+        // Hack to fix Catch GH issue #1661. Could use id for generic Object support.
+        // use of const for Object pointers is very uncommon and under ARC it causes some kind of signature mismatch that breaks compilation
+        template<>
+        struct MatcherMethod<NSString*> {
+            virtual bool match( NSString* arg ) const = 0;
+        };
+#endif
+
+#ifdef __clang__
+#    pragma clang diagnostic pop
+#endif
+
+        template<typename T>
+        struct MatcherBase : MatcherUntypedBase, MatcherMethod<T> {
+
+            MatchAllOf<T> operator && ( MatcherBase const& other ) const;
+            MatchAnyOf<T> operator || ( MatcherBase const& other ) const;
+            MatchNotOf<T> operator ! () const;
+        };
+
+        template<typename ArgT>
+        struct MatchAllOf : MatcherBase<ArgT> {
+            bool match( ArgT const& arg ) const override {
+                for( auto matcher : m_matchers ) {
+                    if (!matcher->match(arg))
+                        return false;
+                }
+                return true;
+            }
+            std::string describe() const override {
+                std::string description;
+                description.reserve( 4 + m_matchers.size()*32 );
+                description += "( ";
+                bool first = true;
+                for( auto matcher : m_matchers ) {
+                    if( first )
+                        first = false;
+                    else
+                        description += " and ";
+                    description += matcher->toString();
+                }
+                description += " )";
+                return description;
+            }
+
+            MatchAllOf<ArgT> operator && ( MatcherBase<ArgT> const& other ) {
+                auto copy(*this);
+                copy.m_matchers.push_back( &other );
+                return copy;
+            }
+
+            std::vector<MatcherBase<ArgT> const*> m_matchers;
+        };
+        template<typename ArgT>
+        struct MatchAnyOf : MatcherBase<ArgT> {
+
+            bool match( ArgT const& arg ) const override {
+                for( auto matcher : m_matchers ) {
+                    if (matcher->match(arg))
+                        return true;
+                }
+                return false;
+            }
+            std::string describe() const override {
+                std::string description;
+                description.reserve( 4 + m_matchers.size()*32 );
+                description += "( ";
+                bool first = true;
+                for( auto matcher : m_matchers ) {
+                    if( first )
+                        first = false;
+                    else
+                        description += " or ";
+                    description += matcher->toString();
+                }
+                description += " )";
+                return description;
+            }
+
+            MatchAnyOf<ArgT> operator || ( MatcherBase<ArgT> const& other ) {
+                auto copy(*this);
+                copy.m_matchers.push_back( &other );
+                return copy;
+            }
+
+            std::vector<MatcherBase<ArgT> const*> m_matchers;
+        };
+
+        template<typename ArgT>
+        struct MatchNotOf : MatcherBase<ArgT> {
+
+            MatchNotOf( MatcherBase<ArgT> const& underlyingMatcher ) : m_underlyingMatcher( underlyingMatcher ) {}
+
+            bool match( ArgT const& arg ) const override {
+                return !m_underlyingMatcher.match( arg );
+            }
+
+            std::string describe() const override {
+                return "not " + m_underlyingMatcher.toString();
+            }
+            MatcherBase<ArgT> const& m_underlyingMatcher;
+        };
+
+        template<typename T>
+        MatchAllOf<T> MatcherBase<T>::operator && ( MatcherBase const& other ) const {
+            return MatchAllOf<T>() && *this && other;
+        }
+        template<typename T>
+        MatchAnyOf<T> MatcherBase<T>::operator || ( MatcherBase const& other ) const {
+            return MatchAnyOf<T>() || *this || other;
+        }
+        template<typename T>
+        MatchNotOf<T> MatcherBase<T>::operator ! () const {
+            return MatchNotOf<T>( *this );
+        }
+
+    } // namespace Impl
+
+} // namespace Matchers
+
+using namespace Matchers;
+using Matchers::Impl::MatcherBase;
+
+} // namespace Catch
+
+// end catch_matchers.h
+// start catch_matchers_exception.hpp
+
+namespace Catch {
+namespace Matchers {
+namespace Exception {
+
+class ExceptionMessageMatcher : public MatcherBase<std::exception> {
+    std::string m_message;
+public:
+
+    ExceptionMessageMatcher(std::string const& message):
+        m_message(message)
+    {}
+
+    bool match(std::exception const& ex) const override;
+
+    std::string describe() const override;
+};
+
+} // namespace Exception
+
+Exception::ExceptionMessageMatcher Message(std::string const& message);
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_exception.hpp
+// start catch_matchers_floating.h
+
+namespace Catch {
+namespace Matchers {
+
+    namespace Floating {
+
+        enum class FloatingPointKind : uint8_t;
+
+        struct WithinAbsMatcher : MatcherBase<double> {
+            WithinAbsMatcher(double target, double margin);
+            bool match(double const& matchee) const override;
+            std::string describe() const override;
+        private:
+            double m_target;
+            double m_margin;
+        };
+
+        struct WithinUlpsMatcher : MatcherBase<double> {
+            WithinUlpsMatcher(double target, uint64_t ulps, FloatingPointKind baseType);
+            bool match(double const& matchee) const override;
+            std::string describe() const override;
+        private:
+            double m_target;
+            uint64_t m_ulps;
+            FloatingPointKind m_type;
+        };
+
+        // Given IEEE-754 format for floats and doubles, we can assume
+        // that float -> double promotion is lossless. Given this, we can
+        // assume that if we do the standard relative comparison of
+        // |lhs - rhs| <= epsilon * max(fabs(lhs), fabs(rhs)), then we get
+        // the same result if we do this for floats, as if we do this for
+        // doubles that were promoted from floats.
+        struct WithinRelMatcher : MatcherBase<double> {
+            WithinRelMatcher(double target, double epsilon);
+            bool match(double const& matchee) const override;
+            std::string describe() const override;
+        private:
+            double m_target;
+            double m_epsilon;
+        };
+
+    } // namespace Floating
+
+    // The following functions create the actual matcher objects.
+    // This allows the types to be inferred
+    Floating::WithinUlpsMatcher WithinULP(double target, uint64_t maxUlpDiff);
+    Floating::WithinUlpsMatcher WithinULP(float target, uint64_t maxUlpDiff);
+    Floating::WithinAbsMatcher WithinAbs(double target, double margin);
+    Floating::WithinRelMatcher WithinRel(double target, double eps);
+    // defaults epsilon to 100*numeric_limits<double>::epsilon()
+    Floating::WithinRelMatcher WithinRel(double target);
+    Floating::WithinRelMatcher WithinRel(float target, float eps);
+    // defaults epsilon to 100*numeric_limits<float>::epsilon()
+    Floating::WithinRelMatcher WithinRel(float target);
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_floating.h
+// start catch_matchers_generic.hpp
+
+#include <functional>
+#include <string>
+
+namespace Catch {
+namespace Matchers {
+namespace Generic {
+
+namespace Detail {
+    std::string finalizeDescription(const std::string& desc);
+}
+
+template <typename T>
+class PredicateMatcher : public MatcherBase<T> {
+    std::function<bool(T const&)> m_predicate;
+    std::string m_description;
+public:
+
+    PredicateMatcher(std::function<bool(T const&)> const& elem, std::string const& descr)
+        :m_predicate(std::move(elem)),
+        m_description(Detail::finalizeDescription(descr))
+    {}
+
+    bool match( T const& item ) const override {
+        return m_predicate(item);
+    }
+
+    std::string describe() const override {
+        return m_description;
+    }
+};
+
+} // namespace Generic
+
+    // The following functions create the actual matcher objects.
+    // The user has to explicitly specify type to the function, because
+    // inferring std::function<bool(T const&)> is hard (but possible) and
+    // requires a lot of TMP.
+    template<typename T>
+    Generic::PredicateMatcher<T> Predicate(std::function<bool(T const&)> const& predicate, std::string const& description = "") {
+        return Generic::PredicateMatcher<T>(predicate, description);
+    }
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_generic.hpp
+// start catch_matchers_string.h
+
+#include <string>
+
+namespace Catch {
+namespace Matchers {
+
+    namespace StdString {
+
+        struct CasedString
+        {
+            CasedString( std::string const& str, CaseSensitive::Choice caseSensitivity );
+            std::string adjustString( std::string const& str ) const;
+            std::string caseSensitivitySuffix() const;
+
+            CaseSensitive::Choice m_caseSensitivity;
+            std::string m_str;
+        };
+
+        struct StringMatcherBase : MatcherBase<std::string> {
+            StringMatcherBase( std::string const& operation, CasedString const& comparator );
+            std::string describe() const override;
+
+            CasedString m_comparator;
+            std::string m_operation;
+        };
+
+        struct EqualsMatcher : StringMatcherBase {
+            EqualsMatcher( CasedString const& comparator );
+            bool match( std::string const& source ) const override;
+        };
+        struct ContainsMatcher : StringMatcherBase {
+            ContainsMatcher( CasedString const& comparator );
+            bool match( std::string const& source ) const override;
+        };
+        struct StartsWithMatcher : StringMatcherBase {
+            StartsWithMatcher( CasedString const& comparator );
+            bool match( std::string const& source ) const override;
+        };
+        struct EndsWithMatcher : StringMatcherBase {
+            EndsWithMatcher( CasedString const& comparator );
+            bool match( std::string const& source ) const override;
+        };
+
+        struct RegexMatcher : MatcherBase<std::string> {
+            RegexMatcher( std::string regex, CaseSensitive::Choice caseSensitivity );
+            bool match( std::string const& matchee ) const override;
+            std::string describe() const override;
+
+        private:
+            std::string m_regex;
+            CaseSensitive::Choice m_caseSensitivity;
+        };
+
+    } // namespace StdString
+
+    // The following functions create the actual matcher objects.
+    // This allows the types to be inferred
+
+    StdString::EqualsMatcher Equals( std::string const& str, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+    StdString::ContainsMatcher Contains( std::string const& str, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+    StdString::EndsWithMatcher EndsWith( std::string const& str, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+    StdString::StartsWithMatcher StartsWith( std::string const& str, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+    StdString::RegexMatcher Matches( std::string const& regex, CaseSensitive::Choice caseSensitivity = CaseSensitive::Yes );
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_string.h
+// start catch_matchers_vector.h
+
+#include <algorithm>
+
+namespace Catch {
+namespace Matchers {
+
+    namespace Vector {
+        template<typename T, typename Alloc>
+        struct ContainsElementMatcher : MatcherBase<std::vector<T, Alloc>> {
+
+            ContainsElementMatcher(T const &comparator) : m_comparator( comparator) {}
+
+            bool match(std::vector<T, Alloc> const &v) const override {
+                for (auto const& el : v) {
+                    if (el == m_comparator) {
+                        return true;
+                    }
+                }
+                return false;
+            }
+
+            std::string describe() const override {
+                return "Contains: " + ::Catch::Detail::stringify( m_comparator );
+            }
+
+            T const& m_comparator;
+        };
+
+        template<typename T, typename AllocComp, typename AllocMatch>
+        struct ContainsMatcher : MatcherBase<std::vector<T, AllocMatch>> {
+
+            ContainsMatcher(std::vector<T, AllocComp> const &comparator) : m_comparator( comparator ) {}
+
+            bool match(std::vector<T, AllocMatch> const &v) const override {
+                // !TBD: see note in EqualsMatcher
+                if (m_comparator.size() > v.size())
+                    return false;
+                for (auto const& comparator : m_comparator) {
+                    auto present = false;
+                    for (const auto& el : v) {
+                        if (el == comparator) {
+                            present = true;
+                            break;
+                        }
+                    }
+                    if (!present) {
+                        return false;
+                    }
+                }
+                return true;
+            }
+            std::string describe() const override {
+                return "Contains: " + ::Catch::Detail::stringify( m_comparator );
+            }
+
+            std::vector<T, AllocComp> const& m_comparator;
+        };
+
+        template<typename T, typename AllocComp, typename AllocMatch>
+        struct EqualsMatcher : MatcherBase<std::vector<T, AllocMatch>> {
+
+            EqualsMatcher(std::vector<T, AllocComp> const &comparator) : m_comparator( comparator ) {}
+
+            bool match(std::vector<T, AllocMatch> const &v) const override {
+                // !TBD: This currently works if all elements can be compared using !=
+                // - a more general approach would be via a compare template that defaults
+                // to using !=. but could be specialised for, e.g. std::vector<T, Alloc> etc
+                // - then just call that directly
+                if (m_comparator.size() != v.size())
+                    return false;
+                for (std::size_t i = 0; i < v.size(); ++i)
+                    if (m_comparator[i] != v[i])
+                        return false;
+                return true;
+            }
+            std::string describe() const override {
+                return "Equals: " + ::Catch::Detail::stringify( m_comparator );
+            }
+            std::vector<T, AllocComp> const& m_comparator;
+        };
+
+        template<typename T, typename AllocComp, typename AllocMatch>
+        struct ApproxMatcher : MatcherBase<std::vector<T, AllocMatch>> {
+
+            ApproxMatcher(std::vector<T, AllocComp> const& comparator) : m_comparator( comparator ) {}
+
+            bool match(std::vector<T, AllocMatch> const &v) const override {
+                if (m_comparator.size() != v.size())
+                    return false;
+                for (std::size_t i = 0; i < v.size(); ++i)
+                    if (m_comparator[i] != approx(v[i]))
+                        return false;
+                return true;
+            }
+            std::string describe() const override {
+                return "is approx: " + ::Catch::Detail::stringify( m_comparator );
+            }
+            template <typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+            ApproxMatcher& epsilon( T const& newEpsilon ) {
+                approx.epsilon(newEpsilon);
+                return *this;
+            }
+            template <typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+            ApproxMatcher& margin( T const& newMargin ) {
+                approx.margin(newMargin);
+                return *this;
+            }
+            template <typename = typename std::enable_if<std::is_constructible<double, T>::value>::type>
+            ApproxMatcher& scale( T const& newScale ) {
+                approx.scale(newScale);
+                return *this;
+            }
+
+            std::vector<T, AllocComp> const& m_comparator;
+            mutable Catch::Detail::Approx approx = Catch::Detail::Approx::custom();
+        };
+
+        template<typename T, typename AllocComp, typename AllocMatch>
+        struct UnorderedEqualsMatcher : MatcherBase<std::vector<T, AllocMatch>> {
+            UnorderedEqualsMatcher(std::vector<T, AllocComp> const& target) : m_target(target) {}
+            bool match(std::vector<T, AllocMatch> const& vec) const override {
+                if (m_target.size() != vec.size()) {
+                    return false;
+                }
+                return std::is_permutation(m_target.begin(), m_target.end(), vec.begin());
+            }
+
+            std::string describe() const override {
+                return "UnorderedEquals: " + ::Catch::Detail::stringify(m_target);
+            }
+        private:
+            std::vector<T, AllocComp> const& m_target;
+        };
+
+    } // namespace Vector
+
+    // The following functions create the actual matcher objects.
+    // This allows the types to be inferred
+
+    template<typename T, typename AllocComp = std::allocator<T>, typename AllocMatch = AllocComp>
+    Vector::ContainsMatcher<T, AllocComp, AllocMatch> Contains( std::vector<T, AllocComp> const& comparator ) {
+        return Vector::ContainsMatcher<T, AllocComp, AllocMatch>( comparator );
+    }
+
+    template<typename T, typename Alloc = std::allocator<T>>
+    Vector::ContainsElementMatcher<T, Alloc> VectorContains( T const& comparator ) {
+        return Vector::ContainsElementMatcher<T, Alloc>( comparator );
+    }
+
+    template<typename T, typename AllocComp = std::allocator<T>, typename AllocMatch = AllocComp>
+    Vector::EqualsMatcher<T, AllocComp, AllocMatch> Equals( std::vector<T, AllocComp> const& comparator ) {
+        return Vector::EqualsMatcher<T, AllocComp, AllocMatch>( comparator );
+    }
+
+    template<typename T, typename AllocComp = std::allocator<T>, typename AllocMatch = AllocComp>
+    Vector::ApproxMatcher<T, AllocComp, AllocMatch> Approx( std::vector<T, AllocComp> const& comparator ) {
+        return Vector::ApproxMatcher<T, AllocComp, AllocMatch>( comparator );
+    }
+
+    template<typename T, typename AllocComp = std::allocator<T>, typename AllocMatch = AllocComp>
+    Vector::UnorderedEqualsMatcher<T, AllocComp, AllocMatch> UnorderedEquals(std::vector<T, AllocComp> const& target) {
+        return Vector::UnorderedEqualsMatcher<T, AllocComp, AllocMatch>( target );
+    }
+
+} // namespace Matchers
+} // namespace Catch
+
+// end catch_matchers_vector.h
+namespace Catch {
+
+    template<typename ArgT, typename MatcherT>
+    class MatchExpr : public ITransientExpression {
+        ArgT const& m_arg;
+        MatcherT m_matcher;
+        StringRef m_matcherString;
+    public:
+        MatchExpr( ArgT const& arg, MatcherT const& matcher, StringRef const& matcherString )
+        :   ITransientExpression{ true, matcher.match( arg ) },
+            m_arg( arg ),
+            m_matcher( matcher ),
+            m_matcherString( matcherString )
+        {}
+
+        void streamReconstructedExpression( std::ostream &os ) const override {
+            auto matcherAsString = m_matcher.toString();
+            os << Catch::Detail::stringify( m_arg ) << ' ';
+            if( matcherAsString == Detail::unprintableString )
+                os << m_matcherString;
+            else
+                os << matcherAsString;
+        }
+    };
+
+    using StringMatcher = Matchers::Impl::MatcherBase<std::string>;
+
+    void handleExceptionMatchExpr( AssertionHandler& handler, StringMatcher const& matcher, StringRef const& matcherString  );
+
+    template<typename ArgT, typename MatcherT>
+    auto makeMatchExpr( ArgT const& arg, MatcherT const& matcher, StringRef const& matcherString  ) -> MatchExpr<ArgT, MatcherT> {
+        return MatchExpr<ArgT, MatcherT>( arg, matcher, matcherString );
+    }
+
+} // namespace Catch
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CHECK_THAT( macroName, matcher, resultDisposition, arg ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(arg) ", " CATCH_INTERNAL_STRINGIFY(matcher), resultDisposition ); \
+        INTERNAL_CATCH_TRY { \
+            catchAssertionHandler.handleExpr( Catch::makeMatchExpr( arg, matcher, #matcher##_catch_sr ) ); \
+        } INTERNAL_CATCH_CATCH( catchAssertionHandler ) \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+///////////////////////////////////////////////////////////////////////////////
+#define INTERNAL_CATCH_THROWS_MATCHES( macroName, exceptionType, resultDisposition, matcher, ... ) \
+    do { \
+        Catch::AssertionHandler catchAssertionHandler( macroName##_catch_sr, CATCH_INTERNAL_LINEINFO, CATCH_INTERNAL_STRINGIFY(__VA_ARGS__) ", " CATCH_INTERNAL_STRINGIFY(exceptionType) ", " CATCH_INTERNAL_STRINGIFY(matcher), resultDisposition ); \
+        if( catchAssertionHandler.allowThrows() ) \
+            try { \
+                static_cast<void>(__VA_ARGS__ ); \
+                catchAssertionHandler.handleUnexpectedExceptionNotThrown(); \
+            } \
+            catch( exceptionType const& ex ) { \
+                catchAssertionHandler.handleExpr( Catch::makeMatchExpr( ex, matcher, #matcher##_catch_sr ) ); \
+            } \
+            catch( ... ) { \
+                catchAssertionHandler.handleUnexpectedInflightException(); \
+            } \
+        else \
+            catchAssertionHandler.handleThrowingCallSkipped(); \
+        INTERNAL_CATCH_REACT( catchAssertionHandler ) \
+    } while( false )
+
+// end catch_capture_matchers.h
+#endif
+// start catch_generators.hpp
+
+// start catch_interfaces_generatortracker.h
+
+
+#include <memory>
+
+namespace Catch {
+
+    namespace Generators {
+        class GeneratorUntypedBase {
+        public:
+            GeneratorUntypedBase() = default;
+            virtual ~GeneratorUntypedBase();
+            // Attempts to move the generator to the next element
+             //
+             // Returns true iff the move succeeded (and a valid element
+             // can be retrieved).
+            virtual bool next() = 0;
+        };
+        using GeneratorBasePtr = std::unique_ptr<GeneratorUntypedBase>;
+
+    } // namespace Generators
+
+    struct IGeneratorTracker {
+        virtual ~IGeneratorTracker();
+        virtual auto hasGenerator() const -> bool = 0;
+        virtual auto getGenerator() const -> Generators::GeneratorBasePtr const& = 0;
+        virtual void setGenerator( Generators::GeneratorBasePtr&& generator ) = 0;
+    };
+
+} // namespace Catch
+
+// end catch_interfaces_generatortracker.h
+// start catch_enforce.h
+
+#include <exception>
+
+namespace Catch {
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+    template <typename Ex>
+    [[noreturn]]
+    void throw_exception(Ex const& e) {
+        throw e;
+    }
+#else // ^^ Exceptions are enabled //  Exceptions are disabled vv
+    [[noreturn]]
+    void throw_exception(std::exception const& e);
+#endif
+
+    [[noreturn]]
+    void throw_logic_error(std::string const& msg);
+    [[noreturn]]
+    void throw_domain_error(std::string const& msg);
+    [[noreturn]]
+    void throw_runtime_error(std::string const& msg);
+
+} // namespace Catch;
+
+#define CATCH_MAKE_MSG(...) \
+    (Catch::ReusableStringStream() << __VA_ARGS__).str()
+
+#define CATCH_INTERNAL_ERROR(...) \
+    Catch::throw_logic_error(CATCH_MAKE_MSG( CATCH_INTERNAL_LINEINFO << ": Internal Catch2 error: " << __VA_ARGS__))
+
+#define CATCH_ERROR(...) \
+    Catch::throw_domain_error(CATCH_MAKE_MSG( __VA_ARGS__ ))
+
+#define CATCH_RUNTIME_ERROR(...) \
+    Catch::throw_runtime_error(CATCH_MAKE_MSG( __VA_ARGS__ ))
+
+#define CATCH_ENFORCE( condition, ... ) \
+    do{ if( !(condition) ) CATCH_ERROR( __VA_ARGS__ ); } while(false)
+
+// end catch_enforce.h
+#include <memory>
+#include <vector>
+#include <cassert>
+
+#include <utility>
+#include <exception>
+
+namespace Catch {
+
+class GeneratorException : public std::exception {
+    const char* const m_msg = "";
+
+public:
+    GeneratorException(const char* msg):
+        m_msg(msg)
+    {}
+
+    const char* what() const noexcept override final;
+};
+
+namespace Generators {
+
+    // !TBD move this into its own location?
+    namespace pf{
+        template<typename T, typename... Args>
+        std::unique_ptr<T> make_unique( Args&&... args ) {
+            return std::unique_ptr<T>(new T(std::forward<Args>(args)...));
+        }
+    }
+
+    template<typename T>
+    struct IGenerator : GeneratorUntypedBase {
+        virtual ~IGenerator() = default;
+
+        // Returns the current element of the generator
+        //
+        // \Precondition The generator is either freshly constructed,
+        // or the last call to `next()` returned true
+        virtual T const& get() const = 0;
+        using type = T;
+    };
+
+    template<typename T>
+    class SingleValueGenerator final : public IGenerator<T> {
+        T m_value;
+    public:
+        SingleValueGenerator(T&& value) : m_value(std::move(value)) {}
+
+        T const& get() const override {
+            return m_value;
+        }
+        bool next() override {
+            return false;
+        }
+    };
+
+    template<typename T>
+    class FixedValuesGenerator final : public IGenerator<T> {
+        static_assert(!std::is_same<T, bool>::value,
+            "FixedValuesGenerator does not support bools because of std::vector<bool>"
+            "specialization, use SingleValue Generator instead.");
+        std::vector<T> m_values;
+        size_t m_idx = 0;
+    public:
+        FixedValuesGenerator( std::initializer_list<T> values ) : m_values( values ) {}
+
+        T const& get() const override {
+            return m_values[m_idx];
+        }
+        bool next() override {
+            ++m_idx;
+            return m_idx < m_values.size();
+        }
+    };
+
+    template <typename T>
+    class GeneratorWrapper final {
+        std::unique_ptr<IGenerator<T>> m_generator;
+    public:
+        GeneratorWrapper(std::unique_ptr<IGenerator<T>> generator):
+            m_generator(std::move(generator))
+        {}
+        T const& get() const {
+            return m_generator->get();
+        }
+        bool next() {
+            return m_generator->next();
+        }
+    };
+
+    template <typename T>
+    GeneratorWrapper<T> value(T&& value) {
+        return GeneratorWrapper<T>(pf::make_unique<SingleValueGenerator<T>>(std::forward<T>(value)));
+    }
+    template <typename T>
+    GeneratorWrapper<T> values(std::initializer_list<T> values) {
+        return GeneratorWrapper<T>(pf::make_unique<FixedValuesGenerator<T>>(values));
+    }
+
+    template<typename T>
+    class Generators : public IGenerator<T> {
+        std::vector<GeneratorWrapper<T>> m_generators;
+        size_t m_current = 0;
+
+        void populate(GeneratorWrapper<T>&& generator) {
+            m_generators.emplace_back(std::move(generator));
+        }
+        void populate(T&& val) {
+            m_generators.emplace_back(value(std::forward<T>(val)));
+        }
+        template<typename U>
+        void populate(U&& val) {
+            populate(T(std::forward<U>(val)));
+        }
+        template<typename U, typename... Gs>
+        void populate(U&& valueOrGenerator, Gs &&... moreGenerators) {
+            populate(std::forward<U>(valueOrGenerator));
+            populate(std::forward<Gs>(moreGenerators)...);
+        }
+
+    public:
+        template <typename... Gs>
+        Generators(Gs &&... moreGenerators) {
+            m_generators.reserve(sizeof...(Gs));
+            populate(std::forward<Gs>(moreGenerators)...);
+        }
+
+        T const& get() const override {
+            return m_generators[m_current].get();
+        }
+
+        bool next() override {
+            if (m_current >= m_generators.size()) {
+                return false;
+            }
+            const bool current_status = m_generators[m_current].next();
+            if (!current_status) {
+                ++m_current;
+            }
+            return m_current < m_generators.size();
+        }
+    };
+
+    template<typename... Ts>
+    GeneratorWrapper<std::tuple<Ts...>> table( std::initializer_list<std::tuple<typename std::decay<Ts>::type...>> tuples ) {
+        return values<std::tuple<Ts...>>( tuples );
+    }
+
+    // Tag type to signal that a generator sequence should convert arguments to a specific type
+    template <typename T>
+    struct as {};
+
+    template<typename T, typename... Gs>
+    auto makeGenerators( GeneratorWrapper<T>&& generator, Gs &&... moreGenerators ) -> Generators<T> {
+        return Generators<T>(std::move(generator), std::forward<Gs>(moreGenerators)...);
+    }
+    template<typename T>
+    auto makeGenerators( GeneratorWrapper<T>&& generator ) -> Generators<T> {
+        return Generators<T>(std::move(generator));
+    }
+    template<typename T, typename... Gs>
+    auto makeGenerators( T&& val, Gs &&... moreGenerators ) -> Generators<T> {
+        return makeGenerators( value( std::forward<T>( val ) ), std::forward<Gs>( moreGenerators )... );
+    }
+    template<typename T, typename U, typename... Gs>
+    auto makeGenerators( as<T>, U&& val, Gs &&... moreGenerators ) -> Generators<T> {
+        return makeGenerators( value( T( std::forward<U>( val ) ) ), std::forward<Gs>( moreGenerators )... );
+    }
+
+    auto acquireGeneratorTracker( StringRef generatorName, SourceLineInfo const& lineInfo ) -> IGeneratorTracker&;
+
+    template<typename L>
+    // Note: The type after -> is weird, because VS2015 cannot parse
+    //       the expression used in the typedef inside, when it is in
+    //       return type. Yeah.
+    auto generate( StringRef generatorName, SourceLineInfo const& lineInfo, L const& generatorExpression ) -> decltype(std::declval<decltype(generatorExpression())>().get()) {
+        using UnderlyingType = typename decltype(generatorExpression())::type;
+
+        IGeneratorTracker& tracker = acquireGeneratorTracker( generatorName, lineInfo );
+        if (!tracker.hasGenerator()) {
+            tracker.setGenerator(pf::make_unique<Generators<UnderlyingType>>(generatorExpression()));
+        }
+
+        auto const& generator = static_cast<IGenerator<UnderlyingType> const&>( *tracker.getGenerator() );
+        return generator.get();
+    }
+
+} // namespace Generators
+} // namespace Catch
+
+#define GENERATE( ... ) \
+    Catch::Generators::generate( INTERNAL_CATCH_STRINGIZE(INTERNAL_CATCH_UNIQUE_NAME(generator)), \
+                                 CATCH_INTERNAL_LINEINFO, \
+                                 [ ]{ using namespace Catch::Generators; return makeGenerators( __VA_ARGS__ ); } ) //NOLINT(google-build-using-namespace)
+#define GENERATE_COPY( ... ) \
+    Catch::Generators::generate( INTERNAL_CATCH_STRINGIZE(INTERNAL_CATCH_UNIQUE_NAME(generator)), \
+                                 CATCH_INTERNAL_LINEINFO, \
+                                 [=]{ using namespace Catch::Generators; return makeGenerators( __VA_ARGS__ ); } ) //NOLINT(google-build-using-namespace)
+#define GENERATE_REF( ... ) \
+    Catch::Generators::generate( INTERNAL_CATCH_STRINGIZE(INTERNAL_CATCH_UNIQUE_NAME(generator)), \
+                                 CATCH_INTERNAL_LINEINFO, \
+                                 [&]{ using namespace Catch::Generators; return makeGenerators( __VA_ARGS__ ); } ) //NOLINT(google-build-using-namespace)
+
+// end catch_generators.hpp
+// start catch_generators_generic.hpp
+
+namespace Catch {
+namespace Generators {
+
+    template <typename T>
+    class TakeGenerator : public IGenerator<T> {
+        GeneratorWrapper<T> m_generator;
+        size_t m_returned = 0;
+        size_t m_target;
+    public:
+        TakeGenerator(size_t target, GeneratorWrapper<T>&& generator):
+            m_generator(std::move(generator)),
+            m_target(target)
+        {
+            assert(target != 0 && "Empty generators are not allowed");
+        }
+        T const& get() const override {
+            return m_generator.get();
+        }
+        bool next() override {
+            ++m_returned;
+            if (m_returned >= m_target) {
+                return false;
+            }
+
+            const auto success = m_generator.next();
+            // If the underlying generator does not contain enough values
+            // then we cut short as well
+            if (!success) {
+                m_returned = m_target;
+            }
+            return success;
+        }
+    };
+
+    template <typename T>
+    GeneratorWrapper<T> take(size_t target, GeneratorWrapper<T>&& generator) {
+        return GeneratorWrapper<T>(pf::make_unique<TakeGenerator<T>>(target, std::move(generator)));
+    }
+
+    template <typename T, typename Predicate>
+    class FilterGenerator : public IGenerator<T> {
+        GeneratorWrapper<T> m_generator;
+        Predicate m_predicate;
+    public:
+        template <typename P = Predicate>
+        FilterGenerator(P&& pred, GeneratorWrapper<T>&& generator):
+            m_generator(std::move(generator)),
+            m_predicate(std::forward<P>(pred))
+        {
+            if (!m_predicate(m_generator.get())) {
+                // It might happen that there are no values that pass the
+                // filter. In that case we throw an exception.
+                auto has_initial_value = nextImpl();
+                if (!has_initial_value) {
+                    Catch::throw_exception(GeneratorException("No valid value found in filtered generator"));
+                }
+            }
+        }
+
+        T const& get() const override {
+            return m_generator.get();
+        }
+
+        bool next() override {
+            return nextImpl();
+        }
+
+    private:
+        bool nextImpl() {
+            bool success = m_generator.next();
+            if (!success) {
+                return false;
+            }
+            while (!m_predicate(m_generator.get()) && (success = m_generator.next()) == true);
+            return success;
+        }
+    };
+
+    template <typename T, typename Predicate>
+    GeneratorWrapper<T> filter(Predicate&& pred, GeneratorWrapper<T>&& generator) {
+        return GeneratorWrapper<T>(std::unique_ptr<IGenerator<T>>(pf::make_unique<FilterGenerator<T, Predicate>>(std::forward<Predicate>(pred), std::move(generator))));
+    }
+
+    template <typename T>
+    class RepeatGenerator : public IGenerator<T> {
+        static_assert(!std::is_same<T, bool>::value,
+            "RepeatGenerator currently does not support bools"
+            "because of std::vector<bool> specialization");
+        GeneratorWrapper<T> m_generator;
+        mutable std::vector<T> m_returned;
+        size_t m_target_repeats;
+        size_t m_current_repeat = 0;
+        size_t m_repeat_index = 0;
+    public:
+        RepeatGenerator(size_t repeats, GeneratorWrapper<T>&& generator):
+            m_generator(std::move(generator)),
+            m_target_repeats(repeats)
+        {
+            assert(m_target_repeats > 0 && "Repeat generator must repeat at least once");
+        }
+
+        T const& get() const override {
+            if (m_current_repeat == 0) {
+                m_returned.push_back(m_generator.get());
+                return m_returned.back();
+            }
+            return m_returned[m_repeat_index];
+        }
+
+        bool next() override {
+            // There are 2 basic cases:
+            // 1) We are still reading the generator
+            // 2) We are reading our own cache
+
+            // In the first case, we need to poke the underlying generator.
+            // If it happily moves, we are left in that state, otherwise it is time to start reading from our cache
+            if (m_current_repeat == 0) {
+                const auto success = m_generator.next();
+                if (!success) {
+                    ++m_current_repeat;
+                }
+                return m_current_repeat < m_target_repeats;
+            }
+
+            // In the second case, we need to move indices forward and check that we haven't run up against the end
+            ++m_repeat_index;
+            if (m_repeat_index == m_returned.size()) {
+                m_repeat_index = 0;
+                ++m_current_repeat;
+            }
+            return m_current_repeat < m_target_repeats;
+        }
+    };
+
+    template <typename T>
+    GeneratorWrapper<T> repeat(size_t repeats, GeneratorWrapper<T>&& generator) {
+        return GeneratorWrapper<T>(pf::make_unique<RepeatGenerator<T>>(repeats, std::move(generator)));
+    }
+
+    template <typename T, typename U, typename Func>
+    class MapGenerator : public IGenerator<T> {
+        // TBD: provide static assert for mapping function, for friendly error message
+        GeneratorWrapper<U> m_generator;
+        Func m_function;
+        // To avoid returning dangling reference, we have to save the values
+        T m_cache;
+    public:
+        template <typename F2 = Func>
+        MapGenerator(F2&& function, GeneratorWrapper<U>&& generator) :
+            m_generator(std::move(generator)),
+            m_function(std::forward<F2>(function)),
+            m_cache(m_function(m_generator.get()))
+        {}
+
+        T const& get() const override {
+            return m_cache;
+        }
+        bool next() override {
+            const auto success = m_generator.next();
+            if (success) {
+                m_cache = m_function(m_generator.get());
+            }
+            return success;
+        }
+    };
+
+    template <typename Func, typename U, typename T = FunctionReturnType<Func, U>>
+    GeneratorWrapper<T> map(Func&& function, GeneratorWrapper<U>&& generator) {
+        return GeneratorWrapper<T>(
+            pf::make_unique<MapGenerator<T, U, Func>>(std::forward<Func>(function), std::move(generator))
+        );
+    }
+
+    template <typename T, typename U, typename Func>
+    GeneratorWrapper<T> map(Func&& function, GeneratorWrapper<U>&& generator) {
+        return GeneratorWrapper<T>(
+            pf::make_unique<MapGenerator<T, U, Func>>(std::forward<Func>(function), std::move(generator))
+        );
+    }
+
+    template <typename T>
+    class ChunkGenerator final : public IGenerator<std::vector<T>> {
+        std::vector<T> m_chunk;
+        size_t m_chunk_size;
+        GeneratorWrapper<T> m_generator;
+        bool m_used_up = false;
+    public:
+        ChunkGenerator(size_t size, GeneratorWrapper<T> generator) :
+            m_chunk_size(size), m_generator(std::move(generator))
+        {
+            m_chunk.reserve(m_chunk_size);
+            if (m_chunk_size != 0) {
+                m_chunk.push_back(m_generator.get());
+                for (size_t i = 1; i < m_chunk_size; ++i) {
+                    if (!m_generator.next()) {
+                        Catch::throw_exception(GeneratorException("Not enough values to initialize the first chunk"));
+                    }
+                    m_chunk.push_back(m_generator.get());
+                }
+            }
+        }
+        std::vector<T> const& get() const override {
+            return m_chunk;
+        }
+        bool next() override {
+            m_chunk.clear();
+            for (size_t idx = 0; idx < m_chunk_size; ++idx) {
+                if (!m_generator.next()) {
+                    return false;
+                }
+                m_chunk.push_back(m_generator.get());
+            }
+            return true;
+        }
+    };
+
+    template <typename T>
+    GeneratorWrapper<std::vector<T>> chunk(size_t size, GeneratorWrapper<T>&& generator) {
+        return GeneratorWrapper<std::vector<T>>(
+            pf::make_unique<ChunkGenerator<T>>(size, std::move(generator))
+        );
+    }
+
+} // namespace Generators
+} // namespace Catch
+
+// end catch_generators_generic.hpp
+// start catch_generators_specific.hpp
+
+// start catch_context.h
+
+#include <memory>
+
+namespace Catch {
+
+    struct IResultCapture;
+    struct IRunner;
+    struct IConfig;
+    struct IMutableContext;
+
+    using IConfigPtr = std::shared_ptr<IConfig const>;
+
+    struct IContext
+    {
+        virtual ~IContext();
+
+        virtual IResultCapture* getResultCapture() = 0;
+        virtual IRunner* getRunner() = 0;
+        virtual IConfigPtr const& getConfig() const = 0;
+    };
+
+    struct IMutableContext : IContext
+    {
+        virtual ~IMutableContext();
+        virtual void setResultCapture( IResultCapture* resultCapture ) = 0;
+        virtual void setRunner( IRunner* runner ) = 0;
+        virtual void setConfig( IConfigPtr const& config ) = 0;
+
+    private:
+        static IMutableContext *currentContext;
+        friend IMutableContext& getCurrentMutableContext();
+        friend void cleanUpContext();
+        static void createContext();
+    };
+
+    inline IMutableContext& getCurrentMutableContext()
+    {
+        if( !IMutableContext::currentContext )
+            IMutableContext::createContext();
+        // NOLINTNEXTLINE(clang-analyzer-core.uninitialized.UndefReturn)
+        return *IMutableContext::currentContext;
+    }
+
+    inline IContext& getCurrentContext()
+    {
+        return getCurrentMutableContext();
+    }
+
+    void cleanUpContext();
+
+    class SimplePcg32;
+    SimplePcg32& rng();
+}
+
+// end catch_context.h
+// start catch_interfaces_config.h
+
+// start catch_option.hpp
+
+namespace Catch {
+
+    // An optional type
+    template<typename T>
+    class Option {
+    public:
+        Option() : nullableValue( nullptr ) {}
+        Option( T const& _value )
+        : nullableValue( new( storage ) T( _value ) )
+        {}
+        Option( Option const& _other )
+        : nullableValue( _other ? new( storage ) T( *_other ) : nullptr )
+        {}
+
+        ~Option() {
+            reset();
+        }
+
+        Option& operator= ( Option const& _other ) {
+            if( &_other != this ) {
+                reset();
+                if( _other )
+                    nullableValue = new( storage ) T( *_other );
+            }
+            return *this;
+        }
+        Option& operator = ( T const& _value ) {
+            reset();
+            nullableValue = new( storage ) T( _value );
+            return *this;
+        }
+
+        void reset() {
+            if( nullableValue )
+                nullableValue->~T();
+            nullableValue = nullptr;
+        }
+
+        T& operator*() { return *nullableValue; }
+        T const& operator*() const { return *nullableValue; }
+        T* operator->() { return nullableValue; }
+        const T* operator->() const { return nullableValue; }
+
+        T valueOr( T const& defaultValue ) const {
+            return nullableValue ? *nullableValue : defaultValue;
+        }
+
+        bool some() const { return nullableValue != nullptr; }
+        bool none() const { return nullableValue == nullptr; }
+
+        bool operator !() const { return nullableValue == nullptr; }
+        explicit operator bool() const {
+            return some();
+        }
+
+    private:
+        T *nullableValue;
+        alignas(alignof(T)) char storage[sizeof(T)];
+    };
+
+} // end namespace Catch
+
+// end catch_option.hpp
+#include <chrono>
+#include <iosfwd>
+#include <string>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    enum class Verbosity {
+        Quiet = 0,
+        Normal,
+        High
+    };
+
+    struct WarnAbout { enum What {
+        Nothing = 0x00,
+        NoAssertions = 0x01,
+        NoTests = 0x02
+    }; };
+
+    struct ShowDurations { enum OrNot {
+        DefaultForReporter,
+        Always,
+        Never
+    }; };
+    struct RunTests { enum InWhatOrder {
+        InDeclarationOrder,
+        InLexicographicalOrder,
+        InRandomOrder
+    }; };
+    struct UseColour { enum YesOrNo {
+        Auto,
+        Yes,
+        No
+    }; };
+    struct WaitForKeypress { enum When {
+        Never,
+        BeforeStart = 1,
+        BeforeExit = 2,
+        BeforeStartAndExit = BeforeStart | BeforeExit
+    }; };
+
+    class TestSpec;
+
+    struct IConfig : NonCopyable {
+
+        virtual ~IConfig();
+
+        virtual bool allowThrows() const = 0;
+        virtual std::ostream& stream() const = 0;
+        virtual std::string name() const = 0;
+        virtual bool includeSuccessfulResults() const = 0;
+        virtual bool shouldDebugBreak() const = 0;
+        virtual bool warnAboutMissingAssertions() const = 0;
+        virtual bool warnAboutNoTests() const = 0;
+        virtual int abortAfter() const = 0;
+        virtual bool showInvisibles() const = 0;
+        virtual ShowDurations::OrNot showDurations() const = 0;
+        virtual double minDuration() const = 0;
+        virtual TestSpec const& testSpec() const = 0;
+        virtual bool hasTestFilters() const = 0;
+        virtual std::vector<std::string> const& getTestsOrTags() const = 0;
+        virtual RunTests::InWhatOrder runOrder() const = 0;
+        virtual unsigned int rngSeed() const = 0;
+        virtual UseColour::YesOrNo useColour() const = 0;
+        virtual std::vector<std::string> const& getSectionsToRun() const = 0;
+        virtual Verbosity verbosity() const = 0;
+
+        virtual bool benchmarkNoAnalysis() const = 0;
+        virtual int benchmarkSamples() const = 0;
+        virtual double benchmarkConfidenceInterval() const = 0;
+        virtual unsigned int benchmarkResamples() const = 0;
+        virtual std::chrono::milliseconds benchmarkWarmupTime() const = 0;
+    };
+
+    using IConfigPtr = std::shared_ptr<IConfig const>;
+}
+
+// end catch_interfaces_config.h
+// start catch_random_number_generator.h
+
+#include <cstdint>
+
+namespace Catch {
+
+    // This is a simple implementation of C++11 Uniform Random Number
+    // Generator. It does not provide all operators, because Catch2
+    // does not use it, but it should behave as expected inside stdlib's
+    // distributions.
+    // The implementation is based on the PCG family (http://pcg-random.org)
+    class SimplePcg32 {
+        using state_type = std::uint64_t;
+    public:
+        using result_type = std::uint32_t;
+        static constexpr result_type (min)() {
+            return 0;
+        }
+        static constexpr result_type (max)() {
+            return static_cast<result_type>(-1);
+        }
+
+        // Provide some default initial state for the default constructor
+        SimplePcg32():SimplePcg32(0xed743cc4U) {}
+
+        explicit SimplePcg32(result_type seed_);
+
+        void seed(result_type seed_);
+        void discard(uint64_t skip);
+
+        result_type operator()();
+
+    private:
+        friend bool operator==(SimplePcg32 const& lhs, SimplePcg32 const& rhs);
+        friend bool operator!=(SimplePcg32 const& lhs, SimplePcg32 const& rhs);
+
+        // In theory we also need operator<< and operator>>
+        // In practice we do not use them, so we will skip them for now
+
+        std::uint64_t m_state;
+        // This part of the state determines which "stream" of the numbers
+        // is chosen -- we take it as a constant for Catch2, so we only
+        // need to deal with seeding the main state.
+        // Picked by reading 8 bytes from `/dev/random` :-)
+        static const std::uint64_t s_inc = (0x13ed0cc53f939476ULL << 1ULL) | 1ULL;
+    };
+
+} // end namespace Catch
+
+// end catch_random_number_generator.h
+#include <random>
+
+namespace Catch {
+namespace Generators {
+
+template <typename Float>
+class RandomFloatingGenerator final : public IGenerator<Float> {
+    Catch::SimplePcg32& m_rng;
+    std::uniform_real_distribution<Float> m_dist;
+    Float m_current_number;
+public:
+
+    RandomFloatingGenerator(Float a, Float b):
+        m_rng(rng()),
+        m_dist(a, b) {
+        static_cast<void>(next());
+    }
+
+    Float const& get() const override {
+        return m_current_number;
+    }
+    bool next() override {
+        m_current_number = m_dist(m_rng);
+        return true;
+    }
+};
+
+template <typename Integer>
+class RandomIntegerGenerator final : public IGenerator<Integer> {
+    Catch::SimplePcg32& m_rng;
+    std::uniform_int_distribution<Integer> m_dist;
+    Integer m_current_number;
+public:
+
+    RandomIntegerGenerator(Integer a, Integer b):
+        m_rng(rng()),
+        m_dist(a, b) {
+        static_cast<void>(next());
+    }
+
+    Integer const& get() const override {
+        return m_current_number;
+    }
+    bool next() override {
+        m_current_number = m_dist(m_rng);
+        return true;
+    }
+};
+
+// TODO: Ideally this would be also constrained against the various char types,
+//       but I don't expect users to run into that in practice.
+template <typename T>
+typename std::enable_if<std::is_integral<T>::value && !std::is_same<T, bool>::value,
+GeneratorWrapper<T>>::type
+random(T a, T b) {
+    return GeneratorWrapper<T>(
+        pf::make_unique<RandomIntegerGenerator<T>>(a, b)
+    );
+}
+
+template <typename T>
+typename std::enable_if<std::is_floating_point<T>::value,
+GeneratorWrapper<T>>::type
+random(T a, T b) {
+    return GeneratorWrapper<T>(
+        pf::make_unique<RandomFloatingGenerator<T>>(a, b)
+    );
+}
+
+template <typename T>
+class RangeGenerator final : public IGenerator<T> {
+    T m_current;
+    T m_end;
+    T m_step;
+    bool m_positive;
+
+public:
+    RangeGenerator(T const& start, T const& end, T const& step):
+        m_current(start),
+        m_end(end),
+        m_step(step),
+        m_positive(m_step > T(0))
+    {
+        assert(m_current != m_end && "Range start and end cannot be equal");
+        assert(m_step != T(0) && "Step size cannot be zero");
+        assert(((m_positive && m_current <= m_end) || (!m_positive && m_current >= m_end)) && "Step moves away from end");
+    }
+
+    RangeGenerator(T const& start, T const& end):
+        RangeGenerator(start, end, (start < end) ? T(1) : T(-1))
+    {}
+
+    T const& get() const override {
+        return m_current;
+    }
+
+    bool next() override {
+        m_current += m_step;
+        return (m_positive) ? (m_current < m_end) : (m_current > m_end);
+    }
+};
+
+template <typename T>
+GeneratorWrapper<T> range(T const& start, T const& end, T const& step) {
+    static_assert(std::is_arithmetic<T>::value && !std::is_same<T, bool>::value, "Type must be numeric");
+    return GeneratorWrapper<T>(pf::make_unique<RangeGenerator<T>>(start, end, step));
+}
+
+template <typename T>
+GeneratorWrapper<T> range(T const& start, T const& end) {
+    static_assert(std::is_integral<T>::value && !std::is_same<T, bool>::value, "Type must be an integer");
+    return GeneratorWrapper<T>(pf::make_unique<RangeGenerator<T>>(start, end));
+}
+
+template <typename T>
+class IteratorGenerator final : public IGenerator<T> {
+    static_assert(!std::is_same<T, bool>::value,
+        "IteratorGenerator currently does not support bools"
+        "because of std::vector<bool> specialization");
+
+    std::vector<T> m_elems;
+    size_t m_current = 0;
+public:
+    template <typename InputIterator, typename InputSentinel>
+    IteratorGenerator(InputIterator first, InputSentinel last):m_elems(first, last) {
+        if (m_elems.empty()) {
+            Catch::throw_exception(GeneratorException("IteratorGenerator received no valid values"));
+        }
+    }
+
+    T const& get() const override {
+        return m_elems[m_current];
+    }
+
+    bool next() override {
+        ++m_current;
+        return m_current != m_elems.size();
+    }
+};
+
+template <typename InputIterator,
+          typename InputSentinel,
+          typename ResultType = typename std::iterator_traits<InputIterator>::value_type>
+GeneratorWrapper<ResultType> from_range(InputIterator from, InputSentinel to) {
+    return GeneratorWrapper<ResultType>(pf::make_unique<IteratorGenerator<ResultType>>(from, to));
+}
+
+template <typename Container,
+          typename ResultType = typename Container::value_type>
+GeneratorWrapper<ResultType> from_range(Container const& cnt) {
+    return GeneratorWrapper<ResultType>(pf::make_unique<IteratorGenerator<ResultType>>(cnt.begin(), cnt.end()));
+}
+
+} // namespace Generators
+} // namespace Catch
+
+// end catch_generators_specific.hpp
+
+// These files are included here so the single_include script doesn't put them
+// in the conditionally compiled sections
+// start catch_test_case_info.h
+
+#include <string>
+#include <vector>
+#include <memory>
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wpadded"
+#endif
+
+namespace Catch {
+
+    struct ITestInvoker;
+
+    struct TestCaseInfo {
+        enum SpecialProperties{
+            None = 0,
+            IsHidden = 1 << 1,
+            ShouldFail = 1 << 2,
+            MayFail = 1 << 3,
+            Throws = 1 << 4,
+            NonPortable = 1 << 5,
+            Benchmark = 1 << 6
+        };
+
+        TestCaseInfo(   std::string const& _name,
+                        std::string const& _className,
+                        std::string const& _description,
+                        std::vector<std::string> const& _tags,
+                        SourceLineInfo const& _lineInfo );
+
+        friend void setTags( TestCaseInfo& testCaseInfo, std::vector<std::string> tags );
+
+        bool isHidden() const;
+        bool throws() const;
+        bool okToFail() const;
+        bool expectedToFail() const;
+
+        std::string tagsAsString() const;
+
+        std::string name;
+        std::string className;
+        std::string description;
+        std::vector<std::string> tags;
+        std::vector<std::string> lcaseTags;
+        SourceLineInfo lineInfo;
+        SpecialProperties properties;
+    };
+
+    class TestCase : public TestCaseInfo {
+    public:
+
+        TestCase( ITestInvoker* testCase, TestCaseInfo&& info );
+
+        TestCase withName( std::string const& _newName ) const;
+
+        void invoke() const;
+
+        TestCaseInfo const& getTestCaseInfo() const;
+
+        bool operator == ( TestCase const& other ) const;
+        bool operator < ( TestCase const& other ) const;
+
+    private:
+        std::shared_ptr<ITestInvoker> test;
+    };
+
+    TestCase makeTestCase(  ITestInvoker* testCase,
+                            std::string const& className,
+                            NameAndTags const& nameAndTags,
+                            SourceLineInfo const& lineInfo );
+}
+
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// end catch_test_case_info.h
+// start catch_interfaces_runner.h
+
+namespace Catch {
+
+    struct IRunner {
+        virtual ~IRunner();
+        virtual bool aborting() const = 0;
+    };
+}
+
+// end catch_interfaces_runner.h
+
+#ifdef __OBJC__
+// start catch_objc.hpp
+
+#import <objc/runtime.h>
+
+#include <string>
+
+// NB. Any general catch headers included here must be included
+// in catch.hpp first to make sure they are included by the single
+// header for non obj-usage
+
+///////////////////////////////////////////////////////////////////////////////
+// This protocol is really only here for (self) documenting purposes, since
+// all its methods are optional.
+@protocol OcFixture
+
+@optional
+
+-(void) setUp;
+-(void) tearDown;
+
+@end
+
+namespace Catch {
+
+    class OcMethod : public ITestInvoker {
+
+    public:
+        OcMethod( Class cls, SEL sel ) : m_cls( cls ), m_sel( sel ) {}
+
+        virtual void invoke() const {
+            id obj = [[m_cls alloc] init];
+
+            performOptionalSelector( obj, @selector(setUp)  );
+            performOptionalSelector( obj, m_sel );
+            performOptionalSelector( obj, @selector(tearDown)  );
+
+            arcSafeRelease( obj );
+        }
+    private:
+        virtual ~OcMethod() {}
+
+        Class m_cls;
+        SEL m_sel;
+    };
+
+    namespace Detail{
+
+        inline std::string getAnnotation(   Class cls,
+                                            std::string const& annotationName,
+                                            std::string const& testCaseName ) {
+            NSString* selStr = [[NSString alloc] initWithFormat:@"Catch_%s_%s", annotationName.c_str(), testCaseName.c_str()];
+            SEL sel = NSSelectorFromString( selStr );
+            arcSafeRelease( selStr );
+            id value = performOptionalSelector( cls, sel );
+            if( value )
+                return [(NSString*)value UTF8String];
+            return "";
+        }
+    }
+
+    inline std::size_t registerTestMethods() {
+        std::size_t noTestMethods = 0;
+        int noClasses = objc_getClassList( nullptr, 0 );
+
+        Class* classes = (CATCH_UNSAFE_UNRETAINED Class *)malloc( sizeof(Class) * noClasses);
+        objc_getClassList( classes, noClasses );
+
+        for( int c = 0; c < noClasses; c++ ) {
+            Class cls = classes[c];
+            {
+                u_int count;
+                Method* methods = class_copyMethodList( cls, &count );
+                for( u_int m = 0; m < count ; m++ ) {
+                    SEL selector = method_getName(methods[m]);
+                    std::string methodName = sel_getName(selector);
+                    if( startsWith( methodName, "Catch_TestCase_" ) ) {
+                        std::string testCaseName = methodName.substr( 15 );
+                        std::string name = Detail::getAnnotation( cls, "Name", testCaseName );
+                        std::string desc = Detail::getAnnotation( cls, "Description", testCaseName );
+                        const char* className = class_getName( cls );
+
+                        getMutableRegistryHub().registerTest( makeTestCase( new OcMethod( cls, selector ), className, NameAndTags( name.c_str(), desc.c_str() ), SourceLineInfo("",0) ) );
+                        noTestMethods++;
+                    }
+                }
+                free(methods);
+            }
+        }
+        return noTestMethods;
+    }
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+
+    namespace Matchers {
+        namespace Impl {
+        namespace NSStringMatchers {
+
+            struct StringHolder : MatcherBase<NSString*>{
+                StringHolder( NSString* substr ) : m_substr( [substr copy] ){}
+                StringHolder( StringHolder const& other ) : m_substr( [other.m_substr copy] ){}
+                StringHolder() {
+                    arcSafeRelease( m_substr );
+                }
+
+                bool match( NSString* str ) const override {
+                    return false;
+                }
+
+                NSString* CATCH_ARC_STRONG m_substr;
+            };
+
+            struct Equals : StringHolder {
+                Equals( NSString* substr ) : StringHolder( substr ){}
+
+                bool match( NSString* str ) const override {
+                    return  (str != nil || m_substr == nil ) &&
+                            [str isEqualToString:m_substr];
+                }
+
+                std::string describe() const override {
+                    return "equals string: " + Catch::Detail::stringify( m_substr );
+                }
+            };
+
+            struct Contains : StringHolder {
+                Contains( NSString* substr ) : StringHolder( substr ){}
+
+                bool match( NSString* str ) const override {
+                    return  (str != nil || m_substr == nil ) &&
+                            [str rangeOfString:m_substr].location != NSNotFound;
+                }
+
+                std::string describe() const override {
+                    return "contains string: " + Catch::Detail::stringify( m_substr );
+                }
+            };
+
+            struct StartsWith : StringHolder {
+                StartsWith( NSString* substr ) : StringHolder( substr ){}
+
+                bool match( NSString* str ) const override {
+                    return  (str != nil || m_substr == nil ) &&
+                            [str rangeOfString:m_substr].location == 0;
+                }
+
+                std::string describe() const override {
+                    return "starts with: " + Catch::Detail::stringify( m_substr );
+                }
+            };
+            struct EndsWith : StringHolder {
+                EndsWith( NSString* substr ) : StringHolder( substr ){}
+
+                bool match( NSString* str ) const override {
+                    return  (str != nil || m_substr == nil ) &&
+                            [str rangeOfString:m_substr].location == [str length] - [m_substr length];
+                }
+
+                std::string describe() const override {
+                    return "ends with: " + Catch::Detail::stringify( m_substr );
+                }
+            };
+
+        } // namespace NSStringMatchers
+        } // namespace Impl
+
+        inline Impl::NSStringMatchers::Equals
+            Equals( NSString* substr ){ return Impl::NSStringMatchers::Equals( substr ); }
+
+        inline Impl::NSStringMatchers::Contains
+            Contains( NSString* substr ){ return Impl::NSStringMatchers::Contains( substr ); }
+
+        inline Impl::NSStringMatchers::StartsWith
+            StartsWith( NSString* substr ){ return Impl::NSStringMatchers::StartsWith( substr ); }
+
+        inline Impl::NSStringMatchers::EndsWith
+            EndsWith( NSString* substr ){ return Impl::NSStringMatchers::EndsWith( substr ); }
+
+    } // namespace Matchers
+
+    using namespace Matchers;
+
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+} // namespace Catch
+
+///////////////////////////////////////////////////////////////////////////////
+#define OC_MAKE_UNIQUE_NAME( root, uniqueSuffix ) root##uniqueSuffix
+#define OC_TEST_CASE2( name, desc, uniqueSuffix ) \
++(NSString*) OC_MAKE_UNIQUE_NAME( Catch_Name_test_, uniqueSuffix ) \
+{ \
+return @ name; \
+} \
++(NSString*) OC_MAKE_UNIQUE_NAME( Catch_Description_test_, uniqueSuffix ) \
+{ \
+return @ desc; \
+} \
+-(void) OC_MAKE_UNIQUE_NAME( Catch_TestCase_test_, uniqueSuffix )
+
+#define OC_TEST_CASE( name, desc ) OC_TEST_CASE2( name, desc, __LINE__ )
+
+// end catch_objc.hpp
+#endif
+
+// Benchmarking needs the externally-facing parts of reporters to work
+#if defined(CATCH_CONFIG_EXTERNAL_INTERFACES) || defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+// start catch_external_interfaces.h
+
+// start catch_reporter_bases.hpp
+
+// start catch_interfaces_reporter.h
+
+// start catch_config.hpp
+
+// start catch_test_spec_parser.h
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wpadded"
+#endif
+
+// start catch_test_spec.h
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wpadded"
+#endif
+
+// start catch_wildcard_pattern.h
+
+namespace Catch
+{
+    class WildcardPattern {
+        enum WildcardPosition {
+            NoWildcard = 0,
+            WildcardAtStart = 1,
+            WildcardAtEnd = 2,
+            WildcardAtBothEnds = WildcardAtStart | WildcardAtEnd
+        };
+
+    public:
+
+        WildcardPattern( std::string const& pattern, CaseSensitive::Choice caseSensitivity );
+        virtual ~WildcardPattern() = default;
+        virtual bool matches( std::string const& str ) const;
+
+    private:
+        std::string normaliseString( std::string const& str ) const;
+        CaseSensitive::Choice m_caseSensitivity;
+        WildcardPosition m_wildcard = NoWildcard;
+        std::string m_pattern;
+    };
+}
+
+// end catch_wildcard_pattern.h
+#include <string>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    struct IConfig;
+
+    class TestSpec {
+        class Pattern {
+        public:
+            explicit Pattern( std::string const& name );
+            virtual ~Pattern();
+            virtual bool matches( TestCaseInfo const& testCase ) const = 0;
+            std::string const& name() const;
+        private:
+            std::string const m_name;
+        };
+        using PatternPtr = std::shared_ptr<Pattern>;
+
+        class NamePattern : public Pattern {
+        public:
+            explicit NamePattern( std::string const& name, std::string const& filterString );
+            bool matches( TestCaseInfo const& testCase ) const override;
+        private:
+            WildcardPattern m_wildcardPattern;
+        };
+
+        class TagPattern : public Pattern {
+        public:
+            explicit TagPattern( std::string const& tag, std::string const& filterString );
+            bool matches( TestCaseInfo const& testCase ) const override;
+        private:
+            std::string m_tag;
+        };
+
+        class ExcludedPattern : public Pattern {
+        public:
+            explicit ExcludedPattern( PatternPtr const& underlyingPattern );
+            bool matches( TestCaseInfo const& testCase ) const override;
+        private:
+            PatternPtr m_underlyingPattern;
+        };
+
+        struct Filter {
+            std::vector<PatternPtr> m_patterns;
+
+            bool matches( TestCaseInfo const& testCase ) const;
+            std::string name() const;
+        };
+
+    public:
+        struct FilterMatch {
+            std::string name;
+            std::vector<TestCase const*> tests;
+        };
+        using Matches = std::vector<FilterMatch>;
+        using vectorStrings = std::vector<std::string>;
+
+        bool hasFilters() const;
+        bool matches( TestCaseInfo const& testCase ) const;
+        Matches matchesByFilter( std::vector<TestCase> const& testCases, IConfig const& config ) const;
+        const vectorStrings & getInvalidArgs() const;
+
+    private:
+        std::vector<Filter> m_filters;
+        std::vector<std::string> m_invalidArgs;
+        friend class TestSpecParser;
+    };
+}
+
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// end catch_test_spec.h
+// start catch_interfaces_tag_alias_registry.h
+
+#include <string>
+
+namespace Catch {
+
+    struct TagAlias;
+
+    struct ITagAliasRegistry {
+        virtual ~ITagAliasRegistry();
+        // Nullptr if not present
+        virtual TagAlias const* find( std::string const& alias ) const = 0;
+        virtual std::string expandAliases( std::string const& unexpandedTestSpec ) const = 0;
+
+        static ITagAliasRegistry const& get();
+    };
+
+} // end namespace Catch
+
+// end catch_interfaces_tag_alias_registry.h
+namespace Catch {
+
+    class TestSpecParser {
+        enum Mode{ None, Name, QuotedName, Tag, EscapedName };
+        Mode m_mode = None;
+        Mode lastMode = None;
+        bool m_exclusion = false;
+        std::size_t m_pos = 0;
+        std::size_t m_realPatternPos = 0;
+        std::string m_arg;
+        std::string m_substring;
+        std::string m_patternName;
+        std::vector<std::size_t> m_escapeChars;
+        TestSpec::Filter m_currentFilter;
+        TestSpec m_testSpec;
+        ITagAliasRegistry const* m_tagAliases = nullptr;
+
+    public:
+        TestSpecParser( ITagAliasRegistry const& tagAliases );
+
+        TestSpecParser& parse( std::string const& arg );
+        TestSpec testSpec();
+
+    private:
+        bool visitChar( char c );
+        void startNewMode( Mode mode );
+        bool processNoneChar( char c );
+        void processNameChar( char c );
+        bool processOtherChar( char c );
+        void endMode();
+        void escape();
+        bool isControlChar( char c ) const;
+        void saveLastMode();
+        void revertBackToLastMode();
+        void addFilter();
+        bool separate();
+
+        // Handles common preprocessing of the pattern for name/tag patterns
+        std::string preprocessPattern();
+        // Adds the current pattern as a test name
+        void addNamePattern();
+        // Adds the current pattern as a tag
+        void addTagPattern();
+
+        inline void addCharToPattern(char c) {
+            m_substring += c;
+            m_patternName += c;
+            m_realPatternPos++;
+        }
+
+    };
+    TestSpec parseTestSpec( std::string const& arg );
+
+} // namespace Catch
+
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// end catch_test_spec_parser.h
+// Libstdc++ doesn't like incomplete classes for unique_ptr
+
+#include <memory>
+#include <vector>
+#include <string>
+
+#ifndef CATCH_CONFIG_CONSOLE_WIDTH
+#define CATCH_CONFIG_CONSOLE_WIDTH 80
+#endif
+
+namespace Catch {
+
+    struct IStream;
+
+    struct ConfigData {
+        bool listTests = false;
+        bool listTags = false;
+        bool listReporters = false;
+        bool listTestNamesOnly = false;
+
+        bool showSuccessfulTests = false;
+        bool shouldDebugBreak = false;
+        bool noThrow = false;
+        bool showHelp = false;
+        bool showInvisibles = false;
+        bool filenamesAsTags = false;
+        bool libIdentify = false;
+
+        int abortAfter = -1;
+        unsigned int rngSeed = 0;
+
+        bool benchmarkNoAnalysis = false;
+        unsigned int benchmarkSamples = 100;
+        double benchmarkConfidenceInterval = 0.95;
+        unsigned int benchmarkResamples = 100000;
+        std::chrono::milliseconds::rep benchmarkWarmupTime = 100;
+
+        Verbosity verbosity = Verbosity::Normal;
+        WarnAbout::What warnings = WarnAbout::Nothing;
+        ShowDurations::OrNot showDurations = ShowDurations::DefaultForReporter;
+        double minDuration = -1;
+        RunTests::InWhatOrder runOrder = RunTests::InDeclarationOrder;
+        UseColour::YesOrNo useColour = UseColour::Auto;
+        WaitForKeypress::When waitForKeypress = WaitForKeypress::Never;
+
+        std::string outputFilename;
+        std::string name;
+        std::string processName;
+#ifndef CATCH_CONFIG_DEFAULT_REPORTER
+#define CATCH_CONFIG_DEFAULT_REPORTER "console"
+#endif
+        std::string reporterName = CATCH_CONFIG_DEFAULT_REPORTER;
+#undef CATCH_CONFIG_DEFAULT_REPORTER
+
+        std::vector<std::string> testsOrTags;
+        std::vector<std::string> sectionsToRun;
+    };
+
+    class Config : public IConfig {
+    public:
+
+        Config() = default;
+        Config( ConfigData const& data );
+        virtual ~Config() = default;
+
+        std::string const& getFilename() const;
+
+        bool listTests() const;
+        bool listTestNamesOnly() const;
+        bool listTags() const;
+        bool listReporters() const;
+
+        std::string getProcessName() const;
+        std::string const& getReporterName() const;
+
+        std::vector<std::string> const& getTestsOrTags() const override;
+        std::vector<std::string> const& getSectionsToRun() const override;
+
+        TestSpec const& testSpec() const override;
+        bool hasTestFilters() const override;
+
+        bool showHelp() const;
+
+        // IConfig interface
+        bool allowThrows() const override;
+        std::ostream& stream() const override;
+        std::string name() const override;
+        bool includeSuccessfulResults() const override;
+        bool warnAboutMissingAssertions() const override;
+        bool warnAboutNoTests() const override;
+        ShowDurations::OrNot showDurations() const override;
+        double minDuration() const override;
+        RunTests::InWhatOrder runOrder() const override;
+        unsigned int rngSeed() const override;
+        UseColour::YesOrNo useColour() const override;
+        bool shouldDebugBreak() const override;
+        int abortAfter() const override;
+        bool showInvisibles() const override;
+        Verbosity verbosity() const override;
+        bool benchmarkNoAnalysis() const override;
+        int benchmarkSamples() const override;
+        double benchmarkConfidenceInterval() const override;
+        unsigned int benchmarkResamples() const override;
+        std::chrono::milliseconds benchmarkWarmupTime() const override;
+
+    private:
+
+        IStream const* openStream();
+        ConfigData m_data;
+
+        std::unique_ptr<IStream const> m_stream;
+        TestSpec m_testSpec;
+        bool m_hasTestFilters = false;
+    };
+
+} // end namespace Catch
+
+// end catch_config.hpp
+// start catch_assertionresult.h
+
+#include <string>
+
+namespace Catch {
+
+    struct AssertionResultData
+    {
+        AssertionResultData() = delete;
+
+        AssertionResultData( ResultWas::OfType _resultType, LazyExpression const& _lazyExpression );
+
+        std::string message;
+        mutable std::string reconstructedExpression;
+        LazyExpression lazyExpression;
+        ResultWas::OfType resultType;
+
+        std::string reconstructExpression() const;
+    };
+
+    class AssertionResult {
+    public:
+        AssertionResult() = delete;
+        AssertionResult( AssertionInfo const& info, AssertionResultData const& data );
+
+        bool isOk() const;
+        bool succeeded() const;
+        ResultWas::OfType getResultType() const;
+        bool hasExpression() const;
+        bool hasMessage() const;
+        std::string getExpression() const;
+        std::string getExpressionInMacro() const;
+        bool hasExpandedExpression() const;
+        std::string getExpandedExpression() const;
+        std::string getMessage() const;
+        SourceLineInfo getSourceInfo() const;
+        StringRef getTestMacroName() const;
+
+    //protected:
+        AssertionInfo m_info;
+        AssertionResultData m_resultData;
+    };
+
+} // end namespace Catch
+
+// end catch_assertionresult.h
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+// start catch_estimate.hpp
+
+ // Statistics estimates
+
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration>
+        struct Estimate {
+            Duration point;
+            Duration lower_bound;
+            Duration upper_bound;
+            double confidence_interval;
+
+            template <typename Duration2>
+            operator Estimate<Duration2>() const {
+                return { point, lower_bound, upper_bound, confidence_interval };
+            }
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_estimate.hpp
+// start catch_outlier_classification.hpp
+
+// Outlier information
+
+namespace Catch {
+    namespace Benchmark {
+        struct OutlierClassification {
+            int samples_seen = 0;
+            int low_severe = 0;     // more than 3 times IQR below Q1
+            int low_mild = 0;       // 1.5 to 3 times IQR below Q1
+            int high_mild = 0;      // 1.5 to 3 times IQR above Q3
+            int high_severe = 0;    // more than 3 times IQR above Q3
+
+            int total() const {
+                return low_severe + low_mild + high_mild + high_severe;
+            }
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_outlier_classification.hpp
+
+#include <iterator>
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+#include <string>
+#include <iosfwd>
+#include <map>
+#include <set>
+#include <memory>
+#include <algorithm>
+
+namespace Catch {
+
+    struct ReporterConfig {
+        explicit ReporterConfig( IConfigPtr const& _fullConfig );
+
+        ReporterConfig( IConfigPtr const& _fullConfig, std::ostream& _stream );
+
+        std::ostream& stream() const;
+        IConfigPtr fullConfig() const;
+
+    private:
+        std::ostream* m_stream;
+        IConfigPtr m_fullConfig;
+    };
+
+    struct ReporterPreferences {
+        bool shouldRedirectStdOut = false;
+        bool shouldReportAllAssertions = false;
+    };
+
+    template<typename T>
+    struct LazyStat : Option<T> {
+        LazyStat& operator=( T const& _value ) {
+            Option<T>::operator=( _value );
+            used = false;
+            return *this;
+        }
+        void reset() {
+            Option<T>::reset();
+            used = false;
+        }
+        bool used = false;
+    };
+
+    struct TestRunInfo {
+        TestRunInfo( std::string const& _name );
+        std::string name;
+    };
+    struct GroupInfo {
+        GroupInfo(  std::string const& _name,
+                    std::size_t _groupIndex,
+                    std::size_t _groupsCount );
+
+        std::string name;
+        std::size_t groupIndex;
+        std::size_t groupsCounts;
+    };
+
+    struct AssertionStats {
+        AssertionStats( AssertionResult const& _assertionResult,
+                        std::vector<MessageInfo> const& _infoMessages,
+                        Totals const& _totals );
+
+        AssertionStats( AssertionStats const& )              = default;
+        AssertionStats( AssertionStats && )                  = default;
+        AssertionStats& operator = ( AssertionStats const& ) = delete;
+        AssertionStats& operator = ( AssertionStats && )     = delete;
+        virtual ~AssertionStats();
+
+        AssertionResult assertionResult;
+        std::vector<MessageInfo> infoMessages;
+        Totals totals;
+    };
+
+    struct SectionStats {
+        SectionStats(   SectionInfo const& _sectionInfo,
+                        Counts const& _assertions,
+                        double _durationInSeconds,
+                        bool _missingAssertions );
+        SectionStats( SectionStats const& )              = default;
+        SectionStats( SectionStats && )                  = default;
+        SectionStats& operator = ( SectionStats const& ) = default;
+        SectionStats& operator = ( SectionStats && )     = default;
+        virtual ~SectionStats();
+
+        SectionInfo sectionInfo;
+        Counts assertions;
+        double durationInSeconds;
+        bool missingAssertions;
+    };
+
+    struct TestCaseStats {
+        TestCaseStats(  TestCaseInfo const& _testInfo,
+                        Totals const& _totals,
+                        std::string const& _stdOut,
+                        std::string const& _stdErr,
+                        bool _aborting );
+
+        TestCaseStats( TestCaseStats const& )              = default;
+        TestCaseStats( TestCaseStats && )                  = default;
+        TestCaseStats& operator = ( TestCaseStats const& ) = default;
+        TestCaseStats& operator = ( TestCaseStats && )     = default;
+        virtual ~TestCaseStats();
+
+        TestCaseInfo testInfo;
+        Totals totals;
+        std::string stdOut;
+        std::string stdErr;
+        bool aborting;
+    };
+
+    struct TestGroupStats {
+        TestGroupStats( GroupInfo const& _groupInfo,
+                        Totals const& _totals,
+                        bool _aborting );
+        TestGroupStats( GroupInfo const& _groupInfo );
+
+        TestGroupStats( TestGroupStats const& )              = default;
+        TestGroupStats( TestGroupStats && )                  = default;
+        TestGroupStats& operator = ( TestGroupStats const& ) = default;
+        TestGroupStats& operator = ( TestGroupStats && )     = default;
+        virtual ~TestGroupStats();
+
+        GroupInfo groupInfo;
+        Totals totals;
+        bool aborting;
+    };
+
+    struct TestRunStats {
+        TestRunStats(   TestRunInfo const& _runInfo,
+                        Totals const& _totals,
+                        bool _aborting );
+
+        TestRunStats( TestRunStats const& )              = default;
+        TestRunStats( TestRunStats && )                  = default;
+        TestRunStats& operator = ( TestRunStats const& ) = default;
+        TestRunStats& operator = ( TestRunStats && )     = default;
+        virtual ~TestRunStats();
+
+        TestRunInfo runInfo;
+        Totals totals;
+        bool aborting;
+    };
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    struct BenchmarkInfo {
+        std::string name;
+        double estimatedDuration;
+        int iterations;
+        int samples;
+        unsigned int resamples;
+        double clockResolution;
+        double clockCost;
+    };
+
+    template <class Duration>
+    struct BenchmarkStats {
+        BenchmarkInfo info;
+
+        std::vector<Duration> samples;
+        Benchmark::Estimate<Duration> mean;
+        Benchmark::Estimate<Duration> standardDeviation;
+        Benchmark::OutlierClassification outliers;
+        double outlierVariance;
+
+        template <typename Duration2>
+        operator BenchmarkStats<Duration2>() const {
+            std::vector<Duration2> samples2;
+            samples2.reserve(samples.size());
+            std::transform(samples.begin(), samples.end(), std::back_inserter(samples2), [](Duration d) { return Duration2(d); });
+            return {
+                info,
+                std::move(samples2),
+                mean,
+                standardDeviation,
+                outliers,
+                outlierVariance,
+            };
+        }
+    };
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    struct IStreamingReporter {
+        virtual ~IStreamingReporter() = default;
+
+        // Implementing class must also provide the following static methods:
+        // static std::string getDescription();
+        // static std::set<Verbosity> getSupportedVerbosities()
+
+        virtual ReporterPreferences getPreferences() const = 0;
+
+        virtual void noMatchingTestCases( std::string const& spec ) = 0;
+
+        virtual void reportInvalidArguments(std::string const&) {}
+
+        virtual void testRunStarting( TestRunInfo const& testRunInfo ) = 0;
+        virtual void testGroupStarting( GroupInfo const& groupInfo ) = 0;
+
+        virtual void testCaseStarting( TestCaseInfo const& testInfo ) = 0;
+        virtual void sectionStarting( SectionInfo const& sectionInfo ) = 0;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        virtual void benchmarkPreparing( std::string const& ) {}
+        virtual void benchmarkStarting( BenchmarkInfo const& ) {}
+        virtual void benchmarkEnded( BenchmarkStats<> const& ) {}
+        virtual void benchmarkFailed( std::string const& ) {}
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        virtual void assertionStarting( AssertionInfo const& assertionInfo ) = 0;
+
+        // The return value indicates if the messages buffer should be cleared:
+        virtual bool assertionEnded( AssertionStats const& assertionStats ) = 0;
+
+        virtual void sectionEnded( SectionStats const& sectionStats ) = 0;
+        virtual void testCaseEnded( TestCaseStats const& testCaseStats ) = 0;
+        virtual void testGroupEnded( TestGroupStats const& testGroupStats ) = 0;
+        virtual void testRunEnded( TestRunStats const& testRunStats ) = 0;
+
+        virtual void skipTest( TestCaseInfo const& testInfo ) = 0;
+
+        // Default empty implementation provided
+        virtual void fatalErrorEncountered( StringRef name );
+
+        virtual bool isMulti() const;
+    };
+    using IStreamingReporterPtr = std::unique_ptr<IStreamingReporter>;
+
+    struct IReporterFactory {
+        virtual ~IReporterFactory();
+        virtual IStreamingReporterPtr create( ReporterConfig const& config ) const = 0;
+        virtual std::string getDescription() const = 0;
+    };
+    using IReporterFactoryPtr = std::shared_ptr<IReporterFactory>;
+
+    struct IReporterRegistry {
+        using FactoryMap = std::map<std::string, IReporterFactoryPtr>;
+        using Listeners = std::vector<IReporterFactoryPtr>;
+
+        virtual ~IReporterRegistry();
+        virtual IStreamingReporterPtr create( std::string const& name, IConfigPtr const& config ) const = 0;
+        virtual FactoryMap const& getFactories() const = 0;
+        virtual Listeners const& getListeners() const = 0;
+    };
+
+} // end namespace Catch
+
+// end catch_interfaces_reporter.h
+#include <algorithm>
+#include <cstring>
+#include <cfloat>
+#include <cstdio>
+#include <cassert>
+#include <memory>
+#include <ostream>
+
+namespace Catch {
+    void prepareExpandedExpression(AssertionResult& result);
+
+    // Returns double formatted as %.3f (format expected on output)
+    std::string getFormattedDuration( double duration );
+
+    //! Should the reporter show
+    bool shouldShowDuration( IConfig const& config, double duration );
+
+    std::string serializeFilters( std::vector<std::string> const& container );
+
+    template<typename DerivedT>
+    struct StreamingReporterBase : IStreamingReporter {
+
+        StreamingReporterBase( ReporterConfig const& _config )
+        :   m_config( _config.fullConfig() ),
+            stream( _config.stream() )
+        {
+            m_reporterPrefs.shouldRedirectStdOut = false;
+            if( !DerivedT::getSupportedVerbosities().count( m_config->verbosity() ) )
+                CATCH_ERROR( "Verbosity level not supported by this reporter" );
+        }
+
+        ReporterPreferences getPreferences() const override {
+            return m_reporterPrefs;
+        }
+
+        static std::set<Verbosity> getSupportedVerbosities() {
+            return { Verbosity::Normal };
+        }
+
+        ~StreamingReporterBase() override = default;
+
+        void noMatchingTestCases(std::string const&) override {}
+
+        void reportInvalidArguments(std::string const&) override {}
+
+        void testRunStarting(TestRunInfo const& _testRunInfo) override {
+            currentTestRunInfo = _testRunInfo;
+        }
+
+        void testGroupStarting(GroupInfo const& _groupInfo) override {
+            currentGroupInfo = _groupInfo;
+        }
+
+        void testCaseStarting(TestCaseInfo const& _testInfo) override  {
+            currentTestCaseInfo = _testInfo;
+        }
+        void sectionStarting(SectionInfo const& _sectionInfo) override {
+            m_sectionStack.push_back(_sectionInfo);
+        }
+
+        void sectionEnded(SectionStats const& /* _sectionStats */) override {
+            m_sectionStack.pop_back();
+        }
+        void testCaseEnded(TestCaseStats const& /* _testCaseStats */) override {
+            currentTestCaseInfo.reset();
+        }
+        void testGroupEnded(TestGroupStats const& /* _testGroupStats */) override {
+            currentGroupInfo.reset();
+        }
+        void testRunEnded(TestRunStats const& /* _testRunStats */) override {
+            currentTestCaseInfo.reset();
+            currentGroupInfo.reset();
+            currentTestRunInfo.reset();
+        }
+
+        void skipTest(TestCaseInfo const&) override {
+            // Don't do anything with this by default.
+            // It can optionally be overridden in the derived class.
+        }
+
+        IConfigPtr m_config;
+        std::ostream& stream;
+
+        LazyStat<TestRunInfo> currentTestRunInfo;
+        LazyStat<GroupInfo> currentGroupInfo;
+        LazyStat<TestCaseInfo> currentTestCaseInfo;
+
+        std::vector<SectionInfo> m_sectionStack;
+        ReporterPreferences m_reporterPrefs;
+    };
+
+    template<typename DerivedT>
+    struct CumulativeReporterBase : IStreamingReporter {
+        template<typename T, typename ChildNodeT>
+        struct Node {
+            explicit Node( T const& _value ) : value( _value ) {}
+            virtual ~Node() {}
+
+            using ChildNodes = std::vector<std::shared_ptr<ChildNodeT>>;
+            T value;
+            ChildNodes children;
+        };
+        struct SectionNode {
+            explicit SectionNode(SectionStats const& _stats) : stats(_stats) {}
+            virtual ~SectionNode() = default;
+
+            bool operator == (SectionNode const& other) const {
+                return stats.sectionInfo.lineInfo == other.stats.sectionInfo.lineInfo;
+            }
+            bool operator == (std::shared_ptr<SectionNode> const& other) const {
+                return operator==(*other);
+            }
+
+            SectionStats stats;
+            using ChildSections = std::vector<std::shared_ptr<SectionNode>>;
+            using Assertions = std::vector<AssertionStats>;
+            ChildSections childSections;
+            Assertions assertions;
+            std::string stdOut;
+            std::string stdErr;
+        };
+
+        struct BySectionInfo {
+            BySectionInfo( SectionInfo const& other ) : m_other( other ) {}
+            BySectionInfo( BySectionInfo const& other ) : m_other( other.m_other ) {}
+            bool operator() (std::shared_ptr<SectionNode> const& node) const {
+                return ((node->stats.sectionInfo.name == m_other.name) &&
+                        (node->stats.sectionInfo.lineInfo == m_other.lineInfo));
+            }
+            void operator=(BySectionInfo const&) = delete;
+
+        private:
+            SectionInfo const& m_other;
+        };
+
+        using TestCaseNode = Node<TestCaseStats, SectionNode>;
+        using TestGroupNode = Node<TestGroupStats, TestCaseNode>;
+        using TestRunNode = Node<TestRunStats, TestGroupNode>;
+
+        CumulativeReporterBase( ReporterConfig const& _config )
+        :   m_config( _config.fullConfig() ),
+            stream( _config.stream() )
+        {
+            m_reporterPrefs.shouldRedirectStdOut = false;
+            if( !DerivedT::getSupportedVerbosities().count( m_config->verbosity() ) )
+                CATCH_ERROR( "Verbosity level not supported by this reporter" );
+        }
+        ~CumulativeReporterBase() override = default;
+
+        ReporterPreferences getPreferences() const override {
+            return m_reporterPrefs;
+        }
+
+        static std::set<Verbosity> getSupportedVerbosities() {
+            return { Verbosity::Normal };
+        }
+
+        void testRunStarting( TestRunInfo const& ) override {}
+        void testGroupStarting( GroupInfo const& ) override {}
+
+        void testCaseStarting( TestCaseInfo const& ) override {}
+
+        void sectionStarting( SectionInfo const& sectionInfo ) override {
+            SectionStats incompleteStats( sectionInfo, Counts(), 0, false );
+            std::shared_ptr<SectionNode> node;
+            if( m_sectionStack.empty() ) {
+                if( !m_rootSection )
+                    m_rootSection = std::make_shared<SectionNode>( incompleteStats );
+                node = m_rootSection;
+            }
+            else {
+                SectionNode& parentNode = *m_sectionStack.back();
+                auto it =
+                    std::find_if(   parentNode.childSections.begin(),
+                                    parentNode.childSections.end(),
+                                    BySectionInfo( sectionInfo ) );
+                if( it == parentNode.childSections.end() ) {
+                    node = std::make_shared<SectionNode>( incompleteStats );
+                    parentNode.childSections.push_back( node );
+                }
+                else
+                    node = *it;
+            }
+            m_sectionStack.push_back( node );
+            m_deepestSection = std::move(node);
+        }
+
+        void assertionStarting(AssertionInfo const&) override {}
+
+        bool assertionEnded(AssertionStats const& assertionStats) override {
+            assert(!m_sectionStack.empty());
+            // AssertionResult holds a pointer to a temporary DecomposedExpression,
+            // which getExpandedExpression() calls to build the expression string.
+            // Our section stack copy of the assertionResult will likely outlive the
+            // temporary, so it must be expanded or discarded now to avoid calling
+            // a destroyed object later.
+            prepareExpandedExpression(const_cast<AssertionResult&>( assertionStats.assertionResult ) );
+            SectionNode& sectionNode = *m_sectionStack.back();
+            sectionNode.assertions.push_back(assertionStats);
+            return true;
+        }
+        void sectionEnded(SectionStats const& sectionStats) override {
+            assert(!m_sectionStack.empty());
+            SectionNode& node = *m_sectionStack.back();
+            node.stats = sectionStats;
+            m_sectionStack.pop_back();
+        }
+        void testCaseEnded(TestCaseStats const& testCaseStats) override {
+            auto node = std::make_shared<TestCaseNode>(testCaseStats);
+            assert(m_sectionStack.size() == 0);
+            node->children.push_back(m_rootSection);
+            m_testCases.push_back(node);
+            m_rootSection.reset();
+
+            assert(m_deepestSection);
+            m_deepestSection->stdOut = testCaseStats.stdOut;
+            m_deepestSection->stdErr = testCaseStats.stdErr;
+        }
+        void testGroupEnded(TestGroupStats const& testGroupStats) override {
+            auto node = std::make_shared<TestGroupNode>(testGroupStats);
+            node->children.swap(m_testCases);
+            m_testGroups.push_back(node);
+        }
+        void testRunEnded(TestRunStats const& testRunStats) override {
+            auto node = std::make_shared<TestRunNode>(testRunStats);
+            node->children.swap(m_testGroups);
+            m_testRuns.push_back(node);
+            testRunEndedCumulative();
+        }
+        virtual void testRunEndedCumulative() = 0;
+
+        void skipTest(TestCaseInfo const&) override {}
+
+        IConfigPtr m_config;
+        std::ostream& stream;
+        std::vector<AssertionStats> m_assertions;
+        std::vector<std::vector<std::shared_ptr<SectionNode>>> m_sections;
+        std::vector<std::shared_ptr<TestCaseNode>> m_testCases;
+        std::vector<std::shared_ptr<TestGroupNode>> m_testGroups;
+
+        std::vector<std::shared_ptr<TestRunNode>> m_testRuns;
+
+        std::shared_ptr<SectionNode> m_rootSection;
+        std::shared_ptr<SectionNode> m_deepestSection;
+        std::vector<std::shared_ptr<SectionNode>> m_sectionStack;
+        ReporterPreferences m_reporterPrefs;
+    };
+
+    template<char C>
+    char const* getLineOfChars() {
+        static char line[CATCH_CONFIG_CONSOLE_WIDTH] = {0};
+        if( !*line ) {
+            std::memset( line, C, CATCH_CONFIG_CONSOLE_WIDTH-1 );
+            line[CATCH_CONFIG_CONSOLE_WIDTH-1] = 0;
+        }
+        return line;
+    }
+
+    struct TestEventListenerBase : StreamingReporterBase<TestEventListenerBase> {
+        TestEventListenerBase( ReporterConfig const& _config );
+
+        static std::set<Verbosity> getSupportedVerbosities();
+
+        void assertionStarting(AssertionInfo const&) override;
+        bool assertionEnded(AssertionStats const&) override;
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_bases.hpp
+// start catch_console_colour.h
+
+namespace Catch {
+
+    struct Colour {
+        enum Code {
+            None = 0,
+
+            White,
+            Red,
+            Green,
+            Blue,
+            Cyan,
+            Yellow,
+            Grey,
+
+            Bright = 0x10,
+
+            BrightRed = Bright | Red,
+            BrightGreen = Bright | Green,
+            LightGrey = Bright | Grey,
+            BrightWhite = Bright | White,
+            BrightYellow = Bright | Yellow,
+
+            // By intention
+            FileName = LightGrey,
+            Warning = BrightYellow,
+            ResultError = BrightRed,
+            ResultSuccess = BrightGreen,
+            ResultExpectedFailure = Warning,
+
+            Error = BrightRed,
+            Success = Green,
+
+            OriginalExpression = Cyan,
+            ReconstructedExpression = BrightYellow,
+
+            SecondaryText = LightGrey,
+            Headers = White
+        };
+
+        // Use constructed object for RAII guard
+        Colour( Code _colourCode );
+        Colour( Colour&& other ) noexcept;
+        Colour& operator=( Colour&& other ) noexcept;
+        ~Colour();
+
+        // Use static method for one-shot changes
+        static void use( Code _colourCode );
+
+    private:
+        bool m_moved = false;
+    };
+
+    std::ostream& operator << ( std::ostream& os, Colour const& );
+
+} // end namespace Catch
+
+// end catch_console_colour.h
+// start catch_reporter_registrars.hpp
+
+
+namespace Catch {
+
+    template<typename T>
+    class ReporterRegistrar {
+
+        class ReporterFactory : public IReporterFactory {
+
+            IStreamingReporterPtr create( ReporterConfig const& config ) const override {
+                return std::unique_ptr<T>( new T( config ) );
+            }
+
+            std::string getDescription() const override {
+                return T::getDescription();
+            }
+        };
+
+    public:
+
+        explicit ReporterRegistrar( std::string const& name ) {
+            getMutableRegistryHub().registerReporter( name, std::make_shared<ReporterFactory>() );
+        }
+    };
+
+    template<typename T>
+    class ListenerRegistrar {
+
+        class ListenerFactory : public IReporterFactory {
+
+            IStreamingReporterPtr create( ReporterConfig const& config ) const override {
+                return std::unique_ptr<T>( new T( config ) );
+            }
+            std::string getDescription() const override {
+                return std::string();
+            }
+        };
+
+    public:
+
+        ListenerRegistrar() {
+            getMutableRegistryHub().registerListener( std::make_shared<ListenerFactory>() );
+        }
+    };
+}
+
+#if !defined(CATCH_CONFIG_DISABLE)
+
+#define CATCH_REGISTER_REPORTER( name, reporterType ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION         \
+    CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS          \
+    namespace{ Catch::ReporterRegistrar<reporterType> catch_internal_RegistrarFor##reporterType( name ); } \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+#define CATCH_REGISTER_LISTENER( listenerType ) \
+    CATCH_INTERNAL_START_WARNINGS_SUPPRESSION   \
+    CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS    \
+    namespace{ Catch::ListenerRegistrar<listenerType> catch_internal_RegistrarFor##listenerType; } \
+    CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+#else // CATCH_CONFIG_DISABLE
+
+#define CATCH_REGISTER_REPORTER(name, reporterType)
+#define CATCH_REGISTER_LISTENER(listenerType)
+
+#endif // CATCH_CONFIG_DISABLE
+
+// end catch_reporter_registrars.hpp
+// Allow users to base their work off existing reporters
+// start catch_reporter_compact.h
+
+namespace Catch {
+
+    struct CompactReporter : StreamingReporterBase<CompactReporter> {
+
+        using StreamingReporterBase::StreamingReporterBase;
+
+        ~CompactReporter() override;
+
+        static std::string getDescription();
+
+        void noMatchingTestCases(std::string const& spec) override;
+
+        void assertionStarting(AssertionInfo const&) override;
+
+        bool assertionEnded(AssertionStats const& _assertionStats) override;
+
+        void sectionEnded(SectionStats const& _sectionStats) override;
+
+        void testRunEnded(TestRunStats const& _testRunStats) override;
+
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_compact.h
+// start catch_reporter_console.h
+
+#if defined(_MSC_VER)
+#pragma warning(push)
+#pragma warning(disable:4061) // Not all labels are EXPLICITLY handled in switch
+                              // Note that 4062 (not all labels are handled
+                              // and default is missing) is enabled
+#endif
+
+namespace Catch {
+    // Fwd decls
+    struct SummaryColumn;
+    class TablePrinter;
+
+    struct ConsoleReporter : StreamingReporterBase<ConsoleReporter> {
+        std::unique_ptr<TablePrinter> m_tablePrinter;
+
+        ConsoleReporter(ReporterConfig const& config);
+        ~ConsoleReporter() override;
+        static std::string getDescription();
+
+        void noMatchingTestCases(std::string const& spec) override;
+
+        void reportInvalidArguments(std::string const&arg) override;
+
+        void assertionStarting(AssertionInfo const&) override;
+
+        bool assertionEnded(AssertionStats const& _assertionStats) override;
+
+        void sectionStarting(SectionInfo const& _sectionInfo) override;
+        void sectionEnded(SectionStats const& _sectionStats) override;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        void benchmarkPreparing(std::string const& name) override;
+        void benchmarkStarting(BenchmarkInfo const& info) override;
+        void benchmarkEnded(BenchmarkStats<> const& stats) override;
+        void benchmarkFailed(std::string const& error) override;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        void testCaseEnded(TestCaseStats const& _testCaseStats) override;
+        void testGroupEnded(TestGroupStats const& _testGroupStats) override;
+        void testRunEnded(TestRunStats const& _testRunStats) override;
+        void testRunStarting(TestRunInfo const& _testRunInfo) override;
+    private:
+
+        void lazyPrint();
+
+        void lazyPrintWithoutClosingBenchmarkTable();
+        void lazyPrintRunInfo();
+        void lazyPrintGroupInfo();
+        void printTestCaseAndSectionHeader();
+
+        void printClosedHeader(std::string const& _name);
+        void printOpenHeader(std::string const& _name);
+
+        // if string has a : in first line will set indent to follow it on
+        // subsequent lines
+        void printHeaderString(std::string const& _string, std::size_t indent = 0);
+
+        void printTotals(Totals const& totals);
+        void printSummaryRow(std::string const& label, std::vector<SummaryColumn> const& cols, std::size_t row);
+
+        void printTotalsDivider(Totals const& totals);
+        void printSummaryDivider();
+        void printTestFilters();
+
+    private:
+        bool m_headerPrinted = false;
+    };
+
+} // end namespace Catch
+
+#if defined(_MSC_VER)
+#pragma warning(pop)
+#endif
+
+// end catch_reporter_console.h
+// start catch_reporter_junit.h
+
+// start catch_xmlwriter.h
+
+#include <vector>
+
+namespace Catch {
+    enum class XmlFormatting {
+        None = 0x00,
+        Indent = 0x01,
+        Newline = 0x02,
+    };
+
+    XmlFormatting operator | (XmlFormatting lhs, XmlFormatting rhs);
+    XmlFormatting operator & (XmlFormatting lhs, XmlFormatting rhs);
+
+    class XmlEncode {
+    public:
+        enum ForWhat { ForTextNodes, ForAttributes };
+
+        XmlEncode( std::string const& str, ForWhat forWhat = ForTextNodes );
+
+        void encodeTo( std::ostream& os ) const;
+
+        friend std::ostream& operator << ( std::ostream& os, XmlEncode const& xmlEncode );
+
+    private:
+        std::string m_str;
+        ForWhat m_forWhat;
+    };
+
+    class XmlWriter {
+    public:
+
+        class ScopedElement {
+        public:
+            ScopedElement( XmlWriter* writer, XmlFormatting fmt );
+
+            ScopedElement( ScopedElement&& other ) noexcept;
+            ScopedElement& operator=( ScopedElement&& other ) noexcept;
+
+            ~ScopedElement();
+
+            ScopedElement& writeText( std::string const& text, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent );
+
+            template<typename T>
+            ScopedElement& writeAttribute( std::string const& name, T const& attribute ) {
+                m_writer->writeAttribute( name, attribute );
+                return *this;
+            }
+
+        private:
+            mutable XmlWriter* m_writer = nullptr;
+            XmlFormatting m_fmt;
+        };
+
+        XmlWriter( std::ostream& os = Catch::cout() );
+        ~XmlWriter();
+
+        XmlWriter( XmlWriter const& ) = delete;
+        XmlWriter& operator=( XmlWriter const& ) = delete;
+
+        XmlWriter& startElement( std::string const& name, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        ScopedElement scopedElement( std::string const& name, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        XmlWriter& endElement(XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        XmlWriter& writeAttribute( std::string const& name, std::string const& attribute );
+
+        XmlWriter& writeAttribute( std::string const& name, bool attribute );
+
+        template<typename T>
+        XmlWriter& writeAttribute( std::string const& name, T const& attribute ) {
+            ReusableStringStream rss;
+            rss << attribute;
+            return writeAttribute( name, rss.str() );
+        }
+
+        XmlWriter& writeText( std::string const& text, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        XmlWriter& writeComment(std::string const& text, XmlFormatting fmt = XmlFormatting::Newline | XmlFormatting::Indent);
+
+        void writeStylesheetRef( std::string const& url );
+
+        XmlWriter& writeBlankLine();
+
+        void ensureTagClosed();
+
+    private:
+
+        void applyFormatting(XmlFormatting fmt);
+
+        void writeDeclaration();
+
+        void newlineIfNecessary();
+
+        bool m_tagIsOpen = false;
+        bool m_needsNewline = false;
+        std::vector<std::string> m_tags;
+        std::string m_indent;
+        std::ostream& m_os;
+    };
+
+}
+
+// end catch_xmlwriter.h
+namespace Catch {
+
+    class JunitReporter : public CumulativeReporterBase<JunitReporter> {
+    public:
+        JunitReporter(ReporterConfig const& _config);
+
+        ~JunitReporter() override;
+
+        static std::string getDescription();
+
+        void noMatchingTestCases(std::string const& /*spec*/) override;
+
+        void testRunStarting(TestRunInfo const& runInfo) override;
+
+        void testGroupStarting(GroupInfo const& groupInfo) override;
+
+        void testCaseStarting(TestCaseInfo const& testCaseInfo) override;
+        bool assertionEnded(AssertionStats const& assertionStats) override;
+
+        void testCaseEnded(TestCaseStats const& testCaseStats) override;
+
+        void testGroupEnded(TestGroupStats const& testGroupStats) override;
+
+        void testRunEndedCumulative() override;
+
+        void writeGroup(TestGroupNode const& groupNode, double suiteTime);
+
+        void writeTestCase(TestCaseNode const& testCaseNode);
+
+        void writeSection( std::string const& className,
+                           std::string const& rootName,
+                           SectionNode const& sectionNode,
+                           bool testOkToFail );
+
+        void writeAssertions(SectionNode const& sectionNode);
+        void writeAssertion(AssertionStats const& stats);
+
+        XmlWriter xml;
+        Timer suiteTimer;
+        std::string stdOutForSuite;
+        std::string stdErrForSuite;
+        unsigned int unexpectedExceptions = 0;
+        bool m_okToFail = false;
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_junit.h
+// start catch_reporter_xml.h
+
+namespace Catch {
+    class XmlReporter : public StreamingReporterBase<XmlReporter> {
+    public:
+        XmlReporter(ReporterConfig const& _config);
+
+        ~XmlReporter() override;
+
+        static std::string getDescription();
+
+        virtual std::string getStylesheetRef() const;
+
+        void writeSourceInfo(SourceLineInfo const& sourceInfo);
+
+    public: // StreamingReporterBase
+
+        void noMatchingTestCases(std::string const& s) override;
+
+        void testRunStarting(TestRunInfo const& testInfo) override;
+
+        void testGroupStarting(GroupInfo const& groupInfo) override;
+
+        void testCaseStarting(TestCaseInfo const& testInfo) override;
+
+        void sectionStarting(SectionInfo const& sectionInfo) override;
+
+        void assertionStarting(AssertionInfo const&) override;
+
+        bool assertionEnded(AssertionStats const& assertionStats) override;
+
+        void sectionEnded(SectionStats const& sectionStats) override;
+
+        void testCaseEnded(TestCaseStats const& testCaseStats) override;
+
+        void testGroupEnded(TestGroupStats const& testGroupStats) override;
+
+        void testRunEnded(TestRunStats const& testRunStats) override;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        void benchmarkPreparing(std::string const& name) override;
+        void benchmarkStarting(BenchmarkInfo const&) override;
+        void benchmarkEnded(BenchmarkStats<> const&) override;
+        void benchmarkFailed(std::string const&) override;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    private:
+        Timer m_testCaseTimer;
+        XmlWriter m_xml;
+        int m_sectionDepth = 0;
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_xml.h
+
+// end catch_external_interfaces.h
+#endif
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+// start catch_benchmarking_all.hpp
+
+// A proxy header that includes all of the benchmarking headers to allow
+// concise include of the benchmarking features. You should prefer the
+// individual includes in standard use.
+
+// start catch_benchmark.hpp
+
+ // Benchmark
+
+// start catch_chronometer.hpp
+
+// User-facing chronometer
+
+
+// start catch_clock.hpp
+
+// Clocks
+
+
+#include <chrono>
+#include <ratio>
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Clock>
+        using ClockDuration = typename Clock::duration;
+        template <typename Clock>
+        using FloatDuration = std::chrono::duration<double, typename Clock::period>;
+
+        template <typename Clock>
+        using TimePoint = typename Clock::time_point;
+
+        using default_clock = std::chrono::steady_clock;
+
+        template <typename Clock>
+        struct now {
+            TimePoint<Clock> operator()() const {
+                return Clock::now();
+            }
+        };
+
+        using fp_seconds = std::chrono::duration<double, std::ratio<1>>;
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_clock.hpp
+// start catch_optimizer.hpp
+
+ // Hinting the optimizer
+
+
+#if defined(_MSC_VER)
+#   include <atomic> // atomic_thread_fence
+#endif
+
+namespace Catch {
+    namespace Benchmark {
+#if defined(__GNUC__) || defined(__clang__)
+        template <typename T>
+        inline void keep_memory(T* p) {
+            asm volatile("" : : "g"(p) : "memory");
+        }
+        inline void keep_memory() {
+            asm volatile("" : : : "memory");
+        }
+
+        namespace Detail {
+            inline void optimizer_barrier() { keep_memory(); }
+        } // namespace Detail
+#elif defined(_MSC_VER)
+
+#pragma optimize("", off)
+        template <typename T>
+        inline void keep_memory(T* p) {
+            // thanks @milleniumbug
+            *reinterpret_cast<char volatile*>(p) = *reinterpret_cast<char const volatile*>(p);
+        }
+        // TODO equivalent keep_memory()
+#pragma optimize("", on)
+
+        namespace Detail {
+            inline void optimizer_barrier() {
+                std::atomic_thread_fence(std::memory_order_seq_cst);
+            }
+        } // namespace Detail
+
+#endif
+
+        template <typename T>
+        inline void deoptimize_value(T&& x) {
+            keep_memory(&x);
+        }
+
+        template <typename Fn, typename... Args>
+        inline auto invoke_deoptimized(Fn&& fn, Args&&... args) -> typename std::enable_if<!std::is_same<void, decltype(fn(args...))>::value>::type {
+            deoptimize_value(std::forward<Fn>(fn) (std::forward<Args...>(args...)));
+        }
+
+        template <typename Fn, typename... Args>
+        inline auto invoke_deoptimized(Fn&& fn, Args&&... args) -> typename std::enable_if<std::is_same<void, decltype(fn(args...))>::value>::type {
+            std::forward<Fn>(fn) (std::forward<Args...>(args...));
+        }
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_optimizer.hpp
+// start catch_complete_invoke.hpp
+
+// Invoke with a special case for void
+
+
+#include <type_traits>
+#include <utility>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename T>
+            struct CompleteType { using type = T; };
+            template <>
+            struct CompleteType<void> { struct type {}; };
+
+            template <typename T>
+            using CompleteType_t = typename CompleteType<T>::type;
+
+            template <typename Result>
+            struct CompleteInvoker {
+                template <typename Fun, typename... Args>
+                static Result invoke(Fun&& fun, Args&&... args) {
+                    return std::forward<Fun>(fun)(std::forward<Args>(args)...);
+                }
+            };
+            template <>
+            struct CompleteInvoker<void> {
+                template <typename Fun, typename... Args>
+                static CompleteType_t<void> invoke(Fun&& fun, Args&&... args) {
+                    std::forward<Fun>(fun)(std::forward<Args>(args)...);
+                    return {};
+                }
+            };
+
+            // invoke and not return void :(
+            template <typename Fun, typename... Args>
+            CompleteType_t<FunctionReturnType<Fun, Args...>> complete_invoke(Fun&& fun, Args&&... args) {
+                return CompleteInvoker<FunctionReturnType<Fun, Args...>>::invoke(std::forward<Fun>(fun), std::forward<Args>(args)...);
+            }
+
+            const std::string benchmarkErrorMsg = "a benchmark failed to run successfully";
+        } // namespace Detail
+
+        template <typename Fun>
+        Detail::CompleteType_t<FunctionReturnType<Fun>> user_code(Fun&& fun) {
+            CATCH_TRY{
+                return Detail::complete_invoke(std::forward<Fun>(fun));
+            } CATCH_CATCH_ALL{
+                getResultCapture().benchmarkFailed(translateActiveException());
+                CATCH_RUNTIME_ERROR(Detail::benchmarkErrorMsg);
+            }
+        }
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_complete_invoke.hpp
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            struct ChronometerConcept {
+                virtual void start() = 0;
+                virtual void finish() = 0;
+                virtual ~ChronometerConcept() = default;
+            };
+            template <typename Clock>
+            struct ChronometerModel final : public ChronometerConcept {
+                void start() override { started = Clock::now(); }
+                void finish() override { finished = Clock::now(); }
+
+                ClockDuration<Clock> elapsed() const { return finished - started; }
+
+                TimePoint<Clock> started;
+                TimePoint<Clock> finished;
+            };
+        } // namespace Detail
+
+        struct Chronometer {
+        public:
+            template <typename Fun>
+            void measure(Fun&& fun) { measure(std::forward<Fun>(fun), is_callable<Fun(int)>()); }
+
+            int runs() const { return k; }
+
+            Chronometer(Detail::ChronometerConcept& meter, int k)
+                : impl(&meter)
+                , k(k) {}
+
+        private:
+            template <typename Fun>
+            void measure(Fun&& fun, std::false_type) {
+                measure([&fun](int) { return fun(); }, std::true_type());
+            }
+
+            template <typename Fun>
+            void measure(Fun&& fun, std::true_type) {
+                Detail::optimizer_barrier();
+                impl->start();
+                for (int i = 0; i < k; ++i) invoke_deoptimized(fun, i);
+                impl->finish();
+                Detail::optimizer_barrier();
+            }
+
+            Detail::ChronometerConcept* impl;
+            int k;
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_chronometer.hpp
+// start catch_environment.hpp
+
+// Environment information
+
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration>
+        struct EnvironmentEstimate {
+            Duration mean;
+            OutlierClassification outliers;
+
+            template <typename Duration2>
+            operator EnvironmentEstimate<Duration2>() const {
+                return { mean, outliers };
+            }
+        };
+        template <typename Clock>
+        struct Environment {
+            using clock_type = Clock;
+            EnvironmentEstimate<FloatDuration<Clock>> clock_resolution;
+            EnvironmentEstimate<FloatDuration<Clock>> clock_cost;
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_environment.hpp
+// start catch_execution_plan.hpp
+
+ // Execution plan
+
+
+// start catch_benchmark_function.hpp
+
+ // Dumb std::function implementation for consistent call overhead
+
+
+#include <cassert>
+#include <type_traits>
+#include <utility>
+#include <memory>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename T>
+            using Decay = typename std::decay<T>::type;
+            template <typename T, typename U>
+            struct is_related
+                : std::is_same<Decay<T>, Decay<U>> {};
+
+            /// We need to reinvent std::function because every piece of code that might add overhead
+            /// in a measurement context needs to have consistent performance characteristics so that we
+            /// can account for it in the measurement.
+            /// Implementations of std::function with optimizations that aren't always applicable, like
+            /// small buffer optimizations, are not uncommon.
+            /// This is effectively an implementation of std::function without any such optimizations;
+            /// it may be slow, but it is consistently slow.
+            struct BenchmarkFunction {
+            private:
+                struct callable {
+                    virtual void call(Chronometer meter) const = 0;
+                    virtual callable* clone() const = 0;
+                    virtual ~callable() = default;
+                };
+                template <typename Fun>
+                struct model : public callable {
+                    model(Fun&& fun) : fun(std::move(fun)) {}
+                    model(Fun const& fun) : fun(fun) {}
+
+                    model<Fun>* clone() const override { return new model<Fun>(*this); }
+
+                    void call(Chronometer meter) const override {
+                        call(meter, is_callable<Fun(Chronometer)>());
+                    }
+                    void call(Chronometer meter, std::true_type) const {
+                        fun(meter);
+                    }
+                    void call(Chronometer meter, std::false_type) const {
+                        meter.measure(fun);
+                    }
+
+                    Fun fun;
+                };
+
+                struct do_nothing { void operator()() const {} };
+
+                template <typename T>
+                BenchmarkFunction(model<T>* c) : f(c) {}
+
+            public:
+                BenchmarkFunction()
+                    : f(new model<do_nothing>{ {} }) {}
+
+                template <typename Fun,
+                    typename std::enable_if<!is_related<Fun, BenchmarkFunction>::value, int>::type = 0>
+                    BenchmarkFunction(Fun&& fun)
+                    : f(new model<typename std::decay<Fun>::type>(std::forward<Fun>(fun))) {}
+
+                BenchmarkFunction(BenchmarkFunction&& that)
+                    : f(std::move(that.f)) {}
+
+                BenchmarkFunction(BenchmarkFunction const& that)
+                    : f(that.f->clone()) {}
+
+                BenchmarkFunction& operator=(BenchmarkFunction&& that) {
+                    f = std::move(that.f);
+                    return *this;
+                }
+
+                BenchmarkFunction& operator=(BenchmarkFunction const& that) {
+                    f.reset(that.f->clone());
+                    return *this;
+                }
+
+                void operator()(Chronometer meter) const { f->call(meter); }
+
+            private:
+                std::unique_ptr<callable> f;
+            };
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_benchmark_function.hpp
+// start catch_repeat.hpp
+
+// repeat algorithm
+
+
+#include <type_traits>
+#include <utility>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Fun>
+            struct repeater {
+                void operator()(int k) const {
+                    for (int i = 0; i < k; ++i) {
+                        fun();
+                    }
+                }
+                Fun fun;
+            };
+            template <typename Fun>
+            repeater<typename std::decay<Fun>::type> repeat(Fun&& fun) {
+                return { std::forward<Fun>(fun) };
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_repeat.hpp
+// start catch_run_for_at_least.hpp
+
+// Run a function for a minimum amount of time
+
+
+// start catch_measure.hpp
+
+// Measure
+
+
+// start catch_timing.hpp
+
+// Timing
+
+
+#include <tuple>
+#include <type_traits>
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration, typename Result>
+        struct Timing {
+            Duration elapsed;
+            Result result;
+            int iterations;
+        };
+        template <typename Clock, typename Func, typename... Args>
+        using TimingOf = Timing<ClockDuration<Clock>, Detail::CompleteType_t<FunctionReturnType<Func, Args...>>>;
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_timing.hpp
+#include <utility>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Clock, typename Fun, typename... Args>
+            TimingOf<Clock, Fun, Args...> measure(Fun&& fun, Args&&... args) {
+                auto start = Clock::now();
+                auto&& r = Detail::complete_invoke(fun, std::forward<Args>(args)...);
+                auto end = Clock::now();
+                auto delta = end - start;
+                return { delta, std::forward<decltype(r)>(r), 1 };
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_measure.hpp
+#include <utility>
+#include <type_traits>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Clock, typename Fun>
+            TimingOf<Clock, Fun, int> measure_one(Fun&& fun, int iters, std::false_type) {
+                return Detail::measure<Clock>(fun, iters);
+            }
+            template <typename Clock, typename Fun>
+            TimingOf<Clock, Fun, Chronometer> measure_one(Fun&& fun, int iters, std::true_type) {
+                Detail::ChronometerModel<Clock> meter;
+                auto&& result = Detail::complete_invoke(fun, Chronometer(meter, iters));
+
+                return { meter.elapsed(), std::move(result), iters };
+            }
+
+            template <typename Clock, typename Fun>
+            using run_for_at_least_argument_t = typename std::conditional<is_callable<Fun(Chronometer)>::value, Chronometer, int>::type;
+
+            struct optimized_away_error : std::exception {
+                const char* what() const noexcept override {
+                    return "could not measure benchmark, maybe it was optimized away";
+                }
+            };
+
+            template <typename Clock, typename Fun>
+            TimingOf<Clock, Fun, run_for_at_least_argument_t<Clock, Fun>> run_for_at_least(ClockDuration<Clock> how_long, int seed, Fun&& fun) {
+                auto iters = seed;
+                while (iters < (1 << 30)) {
+                    auto&& Timing = measure_one<Clock>(fun, iters, is_callable<Fun(Chronometer)>());
+
+                    if (Timing.elapsed >= how_long) {
+                        return { Timing.elapsed, std::move(Timing.result), iters };
+                    }
+                    iters *= 2;
+                }
+                Catch::throw_exception(optimized_away_error{});
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_run_for_at_least.hpp
+#include <algorithm>
+#include <iterator>
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration>
+        struct ExecutionPlan {
+            int iterations_per_sample;
+            Duration estimated_duration;
+            Detail::BenchmarkFunction benchmark;
+            Duration warmup_time;
+            int warmup_iterations;
+
+            template <typename Duration2>
+            operator ExecutionPlan<Duration2>() const {
+                return { iterations_per_sample, estimated_duration, benchmark, warmup_time, warmup_iterations };
+            }
+
+            template <typename Clock>
+            std::vector<FloatDuration<Clock>> run(const IConfig &cfg, Environment<FloatDuration<Clock>> env) const {
+                // warmup a bit
+                Detail::run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(warmup_time), warmup_iterations, Detail::repeat(now<Clock>{}));
+
+                std::vector<FloatDuration<Clock>> times;
+                times.reserve(cfg.benchmarkSamples());
+                std::generate_n(std::back_inserter(times), cfg.benchmarkSamples(), [this, env] {
+                    Detail::ChronometerModel<Clock> model;
+                    this->benchmark(Chronometer(model, iterations_per_sample));
+                    auto sample_time = model.elapsed() - env.clock_cost.mean;
+                    if (sample_time < FloatDuration<Clock>::zero()) sample_time = FloatDuration<Clock>::zero();
+                    return sample_time / iterations_per_sample;
+                });
+                return times;
+            }
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_execution_plan.hpp
+// start catch_estimate_clock.hpp
+
+ // Environment measurement
+
+
+// start catch_stats.hpp
+
+// Statistical analysis tools
+
+
+#include <algorithm>
+#include <functional>
+#include <vector>
+#include <iterator>
+#include <numeric>
+#include <tuple>
+#include <cmath>
+#include <utility>
+#include <cstddef>
+#include <random>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            using sample = std::vector<double>;
+
+            double weighted_average_quantile(int k, int q, std::vector<double>::iterator first, std::vector<double>::iterator last);
+
+            template <typename Iterator>
+            OutlierClassification classify_outliers(Iterator first, Iterator last) {
+                std::vector<double> copy(first, last);
+
+                auto q1 = weighted_average_quantile(1, 4, copy.begin(), copy.end());
+                auto q3 = weighted_average_quantile(3, 4, copy.begin(), copy.end());
+                auto iqr = q3 - q1;
+                auto los = q1 - (iqr * 3.);
+                auto lom = q1 - (iqr * 1.5);
+                auto him = q3 + (iqr * 1.5);
+                auto his = q3 + (iqr * 3.);
+
+                OutlierClassification o;
+                for (; first != last; ++first) {
+                    auto&& t = *first;
+                    if (t < los) ++o.low_severe;
+                    else if (t < lom) ++o.low_mild;
+                    else if (t > his) ++o.high_severe;
+                    else if (t > him) ++o.high_mild;
+                    ++o.samples_seen;
+                }
+                return o;
+            }
+
+            template <typename Iterator>
+            double mean(Iterator first, Iterator last) {
+                auto count = last - first;
+                double sum = std::accumulate(first, last, 0.);
+                return sum / count;
+            }
+
+            template <typename URng, typename Iterator, typename Estimator>
+            sample resample(URng& rng, int resamples, Iterator first, Iterator last, Estimator& estimator) {
+                auto n = last - first;
+                std::uniform_int_distribution<decltype(n)> dist(0, n - 1);
+
+                sample out;
+                out.reserve(resamples);
+                std::generate_n(std::back_inserter(out), resamples, [n, first, &estimator, &dist, &rng] {
+                    std::vector<double> resampled;
+                    resampled.reserve(n);
+                    std::generate_n(std::back_inserter(resampled), n, [first, &dist, &rng] { return first[dist(rng)]; });
+                    return estimator(resampled.begin(), resampled.end());
+                });
+                std::sort(out.begin(), out.end());
+                return out;
+            }
+
+            template <typename Estimator, typename Iterator>
+            sample jackknife(Estimator&& estimator, Iterator first, Iterator last) {
+                auto n = last - first;
+                auto second = std::next(first);
+                sample results;
+                results.reserve(n);
+
+                for (auto it = first; it != last; ++it) {
+                    std::iter_swap(it, first);
+                    results.push_back(estimator(second, last));
+                }
+
+                return results;
+            }
+
+            inline double normal_cdf(double x) {
+                return std::erfc(-x / std::sqrt(2.0)) / 2.0;
+            }
+
+            double erfc_inv(double x);
+
+            double normal_quantile(double p);
+
+            template <typename Iterator, typename Estimator>
+            Estimate<double> bootstrap(double confidence_level, Iterator first, Iterator last, sample const& resample, Estimator&& estimator) {
+                auto n_samples = last - first;
+
+                double point = estimator(first, last);
+                // Degenerate case with a single sample
+                if (n_samples == 1) return { point, point, point, confidence_level };
+
+                sample jack = jackknife(estimator, first, last);
+                double jack_mean = mean(jack.begin(), jack.end());
+                double sum_squares, sum_cubes;
+                std::tie(sum_squares, sum_cubes) = std::accumulate(jack.begin(), jack.end(), std::make_pair(0., 0.), [jack_mean](std::pair<double, double> sqcb, double x) -> std::pair<double, double> {
+                    auto d = jack_mean - x;
+                    auto d2 = d * d;
+                    auto d3 = d2 * d;
+                    return { sqcb.first + d2, sqcb.second + d3 };
+                });
+
+                double accel = sum_cubes / (6 * std::pow(sum_squares, 1.5));
+                int n = static_cast<int>(resample.size());
+                double prob_n = std::count_if(resample.begin(), resample.end(), [point](double x) { return x < point; }) / (double)n;
+                // degenerate case with uniform samples
+                if (prob_n == 0) return { point, point, point, confidence_level };
+
+                double bias = normal_quantile(prob_n);
+                double z1 = normal_quantile((1. - confidence_level) / 2.);
+
+                auto cumn = [n](double x) -> int {
+                    return std::lround(normal_cdf(x) * n); };
+                auto a = [bias, accel](double b) { return bias + b / (1. - accel * b); };
+                double b1 = bias + z1;
+                double b2 = bias - z1;
+                double a1 = a(b1);
+                double a2 = a(b2);
+                auto lo = (std::max)(cumn(a1), 0);
+                auto hi = (std::min)(cumn(a2), n - 1);
+
+                return { point, resample[lo], resample[hi], confidence_level };
+            }
+
+            double outlier_variance(Estimate<double> mean, Estimate<double> stddev, int n);
+
+            struct bootstrap_analysis {
+                Estimate<double> mean;
+                Estimate<double> standard_deviation;
+                double outlier_variance;
+            };
+
+            bootstrap_analysis analyse_samples(double confidence_level, int n_resamples, std::vector<double>::iterator first, std::vector<double>::iterator last);
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_stats.hpp
+#include <algorithm>
+#include <iterator>
+#include <tuple>
+#include <vector>
+#include <cmath>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Clock>
+            std::vector<double> resolution(int k) {
+                std::vector<TimePoint<Clock>> times;
+                times.reserve(k + 1);
+                std::generate_n(std::back_inserter(times), k + 1, now<Clock>{});
+
+                std::vector<double> deltas;
+                deltas.reserve(k);
+                std::transform(std::next(times.begin()), times.end(), times.begin(),
+                    std::back_inserter(deltas),
+                    [](TimePoint<Clock> a, TimePoint<Clock> b) { return static_cast<double>((a - b).count()); });
+
+                return deltas;
+            }
+
+            const auto warmup_iterations = 10000;
+            const auto warmup_time = std::chrono::milliseconds(100);
+            const auto minimum_ticks = 1000;
+            const auto warmup_seed = 10000;
+            const auto clock_resolution_estimation_time = std::chrono::milliseconds(500);
+            const auto clock_cost_estimation_time_limit = std::chrono::seconds(1);
+            const auto clock_cost_estimation_tick_limit = 100000;
+            const auto clock_cost_estimation_time = std::chrono::milliseconds(10);
+            const auto clock_cost_estimation_iterations = 10000;
+
+            template <typename Clock>
+            int warmup() {
+                return run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(warmup_time), warmup_seed, &resolution<Clock>)
+                    .iterations;
+            }
+            template <typename Clock>
+            EnvironmentEstimate<FloatDuration<Clock>> estimate_clock_resolution(int iterations) {
+                auto r = run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(clock_resolution_estimation_time), iterations, &resolution<Clock>)
+                    .result;
+                return {
+                    FloatDuration<Clock>(mean(r.begin(), r.end())),
+                    classify_outliers(r.begin(), r.end()),
+                };
+            }
+            template <typename Clock>
+            EnvironmentEstimate<FloatDuration<Clock>> estimate_clock_cost(FloatDuration<Clock> resolution) {
+                auto time_limit = (std::min)(
+                    resolution * clock_cost_estimation_tick_limit,
+                    FloatDuration<Clock>(clock_cost_estimation_time_limit));
+                auto time_clock = [](int k) {
+                    return Detail::measure<Clock>([k] {
+                        for (int i = 0; i < k; ++i) {
+                            volatile auto ignored = Clock::now();
+                            (void)ignored;
+                        }
+                    }).elapsed;
+                };
+                time_clock(1);
+                int iters = clock_cost_estimation_iterations;
+                auto&& r = run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(clock_cost_estimation_time), iters, time_clock);
+                std::vector<double> times;
+                int nsamples = static_cast<int>(std::ceil(time_limit / r.elapsed));
+                times.reserve(nsamples);
+                std::generate_n(std::back_inserter(times), nsamples, [time_clock, &r] {
+                    return static_cast<double>((time_clock(r.iterations) / r.iterations).count());
+                });
+                return {
+                    FloatDuration<Clock>(mean(times.begin(), times.end())),
+                    classify_outliers(times.begin(), times.end()),
+                };
+            }
+
+            template <typename Clock>
+            Environment<FloatDuration<Clock>> measure_environment() {
+                static Environment<FloatDuration<Clock>>* env = nullptr;
+                if (env) {
+                    return *env;
+                }
+
+                auto iters = Detail::warmup<Clock>();
+                auto resolution = Detail::estimate_clock_resolution<Clock>(iters);
+                auto cost = Detail::estimate_clock_cost<Clock>(resolution.mean);
+
+                env = new Environment<FloatDuration<Clock>>{ resolution, cost };
+                return *env;
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_estimate_clock.hpp
+// start catch_analyse.hpp
+
+ // Run and analyse one benchmark
+
+
+// start catch_sample_analysis.hpp
+
+// Benchmark results
+
+
+#include <algorithm>
+#include <vector>
+#include <string>
+#include <iterator>
+
+namespace Catch {
+    namespace Benchmark {
+        template <typename Duration>
+        struct SampleAnalysis {
+            std::vector<Duration> samples;
+            Estimate<Duration> mean;
+            Estimate<Duration> standard_deviation;
+            OutlierClassification outliers;
+            double outlier_variance;
+
+            template <typename Duration2>
+            operator SampleAnalysis<Duration2>() const {
+                std::vector<Duration2> samples2;
+                samples2.reserve(samples.size());
+                std::transform(samples.begin(), samples.end(), std::back_inserter(samples2), [](Duration d) { return Duration2(d); });
+                return {
+                    std::move(samples2),
+                    mean,
+                    standard_deviation,
+                    outliers,
+                    outlier_variance,
+                };
+            }
+        };
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_sample_analysis.hpp
+#include <algorithm>
+#include <iterator>
+#include <vector>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename Duration, typename Iterator>
+            SampleAnalysis<Duration> analyse(const IConfig &cfg, Environment<Duration>, Iterator first, Iterator last) {
+                if (!cfg.benchmarkNoAnalysis()) {
+                    std::vector<double> samples;
+                    samples.reserve(last - first);
+                    std::transform(first, last, std::back_inserter(samples), [](Duration d) { return d.count(); });
+
+                    auto analysis = Catch::Benchmark::Detail::analyse_samples(cfg.benchmarkConfidenceInterval(), cfg.benchmarkResamples(), samples.begin(), samples.end());
+                    auto outliers = Catch::Benchmark::Detail::classify_outliers(samples.begin(), samples.end());
+
+                    auto wrap_estimate = [](Estimate<double> e) {
+                        return Estimate<Duration> {
+                            Duration(e.point),
+                                Duration(e.lower_bound),
+                                Duration(e.upper_bound),
+                                e.confidence_interval,
+                        };
+                    };
+                    std::vector<Duration> samples2;
+                    samples2.reserve(samples.size());
+                    std::transform(samples.begin(), samples.end(), std::back_inserter(samples2), [](double d) { return Duration(d); });
+                    return {
+                        std::move(samples2),
+                        wrap_estimate(analysis.mean),
+                        wrap_estimate(analysis.standard_deviation),
+                        outliers,
+                        analysis.outlier_variance,
+                    };
+                } else {
+                    std::vector<Duration> samples;
+                    samples.reserve(last - first);
+
+                    Duration mean = Duration(0);
+                    int i = 0;
+                    for (auto it = first; it < last; ++it, ++i) {
+                        samples.push_back(Duration(*it));
+                        mean += Duration(*it);
+                    }
+                    mean /= i;
+
+                    return {
+                        std::move(samples),
+                        Estimate<Duration>{mean, mean, mean, 0.0},
+                        Estimate<Duration>{Duration(0), Duration(0), Duration(0), 0.0},
+                        OutlierClassification{},
+                        0.0
+                    };
+                }
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+// end catch_analyse.hpp
+#include <algorithm>
+#include <functional>
+#include <string>
+#include <vector>
+#include <cmath>
+
+namespace Catch {
+    namespace Benchmark {
+        struct Benchmark {
+            Benchmark(std::string &&name)
+                : name(std::move(name)) {}
+
+            template <class FUN>
+            Benchmark(std::string &&name, FUN &&func)
+                : fun(std::move(func)), name(std::move(name)) {}
+
+            template <typename Clock>
+            ExecutionPlan<FloatDuration<Clock>> prepare(const IConfig &cfg, Environment<FloatDuration<Clock>> env) const {
+                auto min_time = env.clock_resolution.mean * Detail::minimum_ticks;
+                auto run_time = std::max(min_time, std::chrono::duration_cast<decltype(min_time)>(cfg.benchmarkWarmupTime()));
+                auto&& test = Detail::run_for_at_least<Clock>(std::chrono::duration_cast<ClockDuration<Clock>>(run_time), 1, fun);
+                int new_iters = static_cast<int>(std::ceil(min_time * test.iterations / test.elapsed));
+                return { new_iters, test.elapsed / test.iterations * new_iters * cfg.benchmarkSamples(), fun, std::chrono::duration_cast<FloatDuration<Clock>>(cfg.benchmarkWarmupTime()), Detail::warmup_iterations };
+            }
+
+            template <typename Clock = default_clock>
+            void run() {
+                IConfigPtr cfg = getCurrentContext().getConfig();
+
+                auto env = Detail::measure_environment<Clock>();
+
+                getResultCapture().benchmarkPreparing(name);
+                CATCH_TRY{
+                    auto plan = user_code([&] {
+                        return prepare<Clock>(*cfg, env);
+                    });
+
+                    BenchmarkInfo info {
+                        name,
+                        plan.estimated_duration.count(),
+                        plan.iterations_per_sample,
+                        cfg->benchmarkSamples(),
+                        cfg->benchmarkResamples(),
+                        env.clock_resolution.mean.count(),
+                        env.clock_cost.mean.count()
+                    };
+
+                    getResultCapture().benchmarkStarting(info);
+
+                    auto samples = user_code([&] {
+                        return plan.template run<Clock>(*cfg, env);
+                    });
+
+                    auto analysis = Detail::analyse(*cfg, env, samples.begin(), samples.end());
+                    BenchmarkStats<FloatDuration<Clock>> stats{ info, analysis.samples, analysis.mean, analysis.standard_deviation, analysis.outliers, analysis.outlier_variance };
+                    getResultCapture().benchmarkEnded(stats);
+
+                } CATCH_CATCH_ALL{
+                    if (translateActiveException() != Detail::benchmarkErrorMsg) // benchmark errors have been reported, otherwise rethrow.
+                        std::rethrow_exception(std::current_exception());
+                }
+            }
+
+            // sets lambda to be used in fun *and* executes benchmark!
+            template <typename Fun,
+                typename std::enable_if<!Detail::is_related<Fun, Benchmark>::value, int>::type = 0>
+                Benchmark & operator=(Fun func) {
+                fun = Detail::BenchmarkFunction(func);
+                run();
+                return *this;
+            }
+
+            explicit operator bool() {
+                return true;
+            }
+
+        private:
+            Detail::BenchmarkFunction fun;
+            std::string name;
+        };
+    }
+} // namespace Catch
+
+#define INTERNAL_CATCH_GET_1_ARG(arg1, arg2, ...) arg1
+#define INTERNAL_CATCH_GET_2_ARG(arg1, arg2, ...) arg2
+
+#define INTERNAL_CATCH_BENCHMARK(BenchmarkName, name, benchmarkIndex)\
+    if( Catch::Benchmark::Benchmark BenchmarkName{name} ) \
+        BenchmarkName = [&](int benchmarkIndex)
+
+#define INTERNAL_CATCH_BENCHMARK_ADVANCED(BenchmarkName, name)\
+    if( Catch::Benchmark::Benchmark BenchmarkName{name} ) \
+        BenchmarkName = [&]
+
+// end catch_benchmark.hpp
+// start catch_constructor.hpp
+
+// Constructor and destructor helpers
+
+
+#include <type_traits>
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+            template <typename T, bool Destruct>
+            struct ObjectStorage
+            {
+                using TStorage = typename std::aligned_storage<sizeof(T), std::alignment_of<T>::value>::type;
+
+                ObjectStorage() : data() {}
+
+                ObjectStorage(const ObjectStorage& other)
+                {
+                    new(&data) T(other.stored_object());
+                }
+
+                ObjectStorage(ObjectStorage&& other)
+                {
+                    new(&data) T(std::move(other.stored_object()));
+                }
+
+                ~ObjectStorage() { destruct_on_exit<T>(); }
+
+                template <typename... Args>
+                void construct(Args&&... args)
+                {
+                    new (&data) T(std::forward<Args>(args)...);
+                }
+
+                template <bool AllowManualDestruction = !Destruct>
+                typename std::enable_if<AllowManualDestruction>::type destruct()
+                {
+                    stored_object().~T();
+                }
+
+            private:
+                // If this is a constructor benchmark, destruct the underlying object
+                template <typename U>
+                void destruct_on_exit(typename std::enable_if<Destruct, U>::type* = 0) { destruct<true>(); }
+                // Otherwise, don't
+                template <typename U>
+                void destruct_on_exit(typename std::enable_if<!Destruct, U>::type* = 0) { }
+
+                T& stored_object() {
+                    return *static_cast<T*>(static_cast<void*>(&data));
+                }
+
+                T const& stored_object() const {
+                    return *static_cast<T*>(static_cast<void*>(&data));
+                }
+
+                TStorage data;
+            };
+        }
+
+        template <typename T>
+        using storage_for = Detail::ObjectStorage<T, true>;
+
+        template <typename T>
+        using destructable_object = Detail::ObjectStorage<T, false>;
+    }
+}
+
+// end catch_constructor.hpp
+// end catch_benchmarking_all.hpp
+#endif
+
+#endif // ! CATCH_CONFIG_IMPL_ONLY
+
+#ifdef CATCH_IMPL
+// start catch_impl.hpp
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wweak-vtables"
+#endif
+
+// Keep these here for external reporters
+// start catch_test_case_tracker.h
+
+#include <string>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+namespace TestCaseTracking {
+
+    struct NameAndLocation {
+        std::string name;
+        SourceLineInfo location;
+
+        NameAndLocation( std::string const& _name, SourceLineInfo const& _location );
+        friend bool operator==(NameAndLocation const& lhs, NameAndLocation const& rhs) {
+            return lhs.name == rhs.name
+                && lhs.location == rhs.location;
+        }
+    };
+
+    class ITracker;
+
+    using ITrackerPtr = std::shared_ptr<ITracker>;
+
+    class  ITracker {
+        NameAndLocation m_nameAndLocation;
+
+    public:
+        ITracker(NameAndLocation const& nameAndLoc) :
+            m_nameAndLocation(nameAndLoc)
+        {}
+
+        // static queries
+        NameAndLocation const& nameAndLocation() const {
+            return m_nameAndLocation;
+        }
+
+        virtual ~ITracker();
+
+        // dynamic queries
+        virtual bool isComplete() const = 0; // Successfully completed or failed
+        virtual bool isSuccessfullyCompleted() const = 0;
+        virtual bool isOpen() const = 0; // Started but not complete
+        virtual bool hasChildren() const = 0;
+        virtual bool hasStarted() const = 0;
+
+        virtual ITracker& parent() = 0;
+
+        // actions
+        virtual void close() = 0; // Successfully complete
+        virtual void fail() = 0;
+        virtual void markAsNeedingAnotherRun() = 0;
+
+        virtual void addChild( ITrackerPtr const& child ) = 0;
+        virtual ITrackerPtr findChild( NameAndLocation const& nameAndLocation ) = 0;
+        virtual void openChild() = 0;
+
+        // Debug/ checking
+        virtual bool isSectionTracker() const = 0;
+        virtual bool isGeneratorTracker() const = 0;
+    };
+
+    class TrackerContext {
+
+        enum RunState {
+            NotStarted,
+            Executing,
+            CompletedCycle
+        };
+
+        ITrackerPtr m_rootTracker;
+        ITracker* m_currentTracker = nullptr;
+        RunState m_runState = NotStarted;
+
+    public:
+
+        ITracker& startRun();
+        void endRun();
+
+        void startCycle();
+        void completeCycle();
+
+        bool completedCycle() const;
+        ITracker& currentTracker();
+        void setCurrentTracker( ITracker* tracker );
+    };
+
+    class TrackerBase : public ITracker {
+    protected:
+        enum CycleState {
+            NotStarted,
+            Executing,
+            ExecutingChildren,
+            NeedsAnotherRun,
+            CompletedSuccessfully,
+            Failed
+        };
+
+        using Children = std::vector<ITrackerPtr>;
+        TrackerContext& m_ctx;
+        ITracker* m_parent;
+        Children m_children;
+        CycleState m_runState = NotStarted;
+
+    public:
+        TrackerBase( NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent );
+
+        bool isComplete() const override;
+        bool isSuccessfullyCompleted() const override;
+        bool isOpen() const override;
+        bool hasChildren() const override;
+        bool hasStarted() const override {
+            return m_runState != NotStarted;
+        }
+
+        void addChild( ITrackerPtr const& child ) override;
+
+        ITrackerPtr findChild( NameAndLocation const& nameAndLocation ) override;
+        ITracker& parent() override;
+
+        void openChild() override;
+
+        bool isSectionTracker() const override;
+        bool isGeneratorTracker() const override;
+
+        void open();
+
+        void close() override;
+        void fail() override;
+        void markAsNeedingAnotherRun() override;
+
+    private:
+        void moveToParent();
+        void moveToThis();
+    };
+
+    class SectionTracker : public TrackerBase {
+        std::vector<std::string> m_filters;
+        std::string m_trimmed_name;
+    public:
+        SectionTracker( NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent );
+
+        bool isSectionTracker() const override;
+
+        bool isComplete() const override;
+
+        static SectionTracker& acquire( TrackerContext& ctx, NameAndLocation const& nameAndLocation );
+
+        void tryOpen();
+
+        void addInitialFilters( std::vector<std::string> const& filters );
+        void addNextFilters( std::vector<std::string> const& filters );
+        //! Returns filters active in this tracker
+        std::vector<std::string> const& getFilters() const;
+        //! Returns whitespace-trimmed name of the tracked section
+        std::string const& trimmedName() const;
+    };
+
+} // namespace TestCaseTracking
+
+using TestCaseTracking::ITracker;
+using TestCaseTracking::TrackerContext;
+using TestCaseTracking::SectionTracker;
+
+} // namespace Catch
+
+// end catch_test_case_tracker.h
+
+// start catch_leak_detector.h
+
+namespace Catch {
+
+    struct LeakDetector {
+        LeakDetector();
+        ~LeakDetector();
+    };
+
+}
+// end catch_leak_detector.h
+// Cpp files will be included in the single-header file here
+// start catch_stats.cpp
+
+// Statistical analysis tools
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+
+#include <cassert>
+#include <random>
+
+#if defined(CATCH_CONFIG_USE_ASYNC)
+#include <future>
+#endif
+
+namespace {
+    double erf_inv(double x) {
+        // Code accompanying the article "Approximating the erfinv function" in GPU Computing Gems, Volume 2
+        double w, p;
+
+        w = -log((1.0 - x) * (1.0 + x));
+
+        if (w < 6.250000) {
+            w = w - 3.125000;
+            p = -3.6444120640178196996e-21;
+            p = -1.685059138182016589e-19 + p * w;
+            p = 1.2858480715256400167e-18 + p * w;
+            p = 1.115787767802518096e-17 + p * w;
+            p = -1.333171662854620906e-16 + p * w;
+            p = 2.0972767875968561637e-17 + p * w;
+            p = 6.6376381343583238325e-15 + p * w;
+            p = -4.0545662729752068639e-14 + p * w;
+            p = -8.1519341976054721522e-14 + p * w;
+            p = 2.6335093153082322977e-12 + p * w;
+            p = -1.2975133253453532498e-11 + p * w;
+            p = -5.4154120542946279317e-11 + p * w;
+            p = 1.051212273321532285e-09 + p * w;
+            p = -4.1126339803469836976e-09 + p * w;
+            p = -2.9070369957882005086e-08 + p * w;
+            p = 4.2347877827932403518e-07 + p * w;
+            p = -1.3654692000834678645e-06 + p * w;
+            p = -1.3882523362786468719e-05 + p * w;
+            p = 0.0001867342080340571352 + p * w;
+            p = -0.00074070253416626697512 + p * w;
+            p = -0.0060336708714301490533 + p * w;
+            p = 0.24015818242558961693 + p * w;
+            p = 1.6536545626831027356 + p * w;
+        } else if (w < 16.000000) {
+            w = sqrt(w) - 3.250000;
+            p = 2.2137376921775787049e-09;
+            p = 9.0756561938885390979e-08 + p * w;
+            p = -2.7517406297064545428e-07 + p * w;
+            p = 1.8239629214389227755e-08 + p * w;
+            p = 1.5027403968909827627e-06 + p * w;
+            p = -4.013867526981545969e-06 + p * w;
+            p = 2.9234449089955446044e-06 + p * w;
+            p = 1.2475304481671778723e-05 + p * w;
+            p = -4.7318229009055733981e-05 + p * w;
+            p = 6.8284851459573175448e-05 + p * w;
+            p = 2.4031110387097893999e-05 + p * w;
+            p = -0.0003550375203628474796 + p * w;
+            p = 0.00095328937973738049703 + p * w;
+            p = -0.0016882755560235047313 + p * w;
+            p = 0.0024914420961078508066 + p * w;
+            p = -0.0037512085075692412107 + p * w;
+            p = 0.005370914553590063617 + p * w;
+            p = 1.0052589676941592334 + p * w;
+            p = 3.0838856104922207635 + p * w;
+        } else {
+            w = sqrt(w) - 5.000000;
+            p = -2.7109920616438573243e-11;
+            p = -2.5556418169965252055e-10 + p * w;
+            p = 1.5076572693500548083e-09 + p * w;
+            p = -3.7894654401267369937e-09 + p * w;
+            p = 7.6157012080783393804e-09 + p * w;
+            p = -1.4960026627149240478e-08 + p * w;
+            p = 2.9147953450901080826e-08 + p * w;
+            p = -6.7711997758452339498e-08 + p * w;
+            p = 2.2900482228026654717e-07 + p * w;
+            p = -9.9298272942317002539e-07 + p * w;
+            p = 4.5260625972231537039e-06 + p * w;
+            p = -1.9681778105531670567e-05 + p * w;
+            p = 7.5995277030017761139e-05 + p * w;
+            p = -0.00021503011930044477347 + p * w;
+            p = -0.00013871931833623122026 + p * w;
+            p = 1.0103004648645343977 + p * w;
+            p = 4.8499064014085844221 + p * w;
+        }
+        return p * x;
+    }
+
+    double standard_deviation(std::vector<double>::iterator first, std::vector<double>::iterator last) {
+        auto m = Catch::Benchmark::Detail::mean(first, last);
+        double variance = std::accumulate(first, last, 0., [m](double a, double b) {
+            double diff = b - m;
+            return a + diff * diff;
+            }) / (last - first);
+            return std::sqrt(variance);
+    }
+
+}
+
+namespace Catch {
+    namespace Benchmark {
+        namespace Detail {
+
+            double weighted_average_quantile(int k, int q, std::vector<double>::iterator first, std::vector<double>::iterator last) {
+                auto count = last - first;
+                double idx = (count - 1) * k / static_cast<double>(q);
+                int j = static_cast<int>(idx);
+                double g = idx - j;
+                std::nth_element(first, first + j, last);
+                auto xj = first[j];
+                if (g == 0) return xj;
+
+                auto xj1 = *std::min_element(first + (j + 1), last);
+                return xj + g * (xj1 - xj);
+            }
+
+            double erfc_inv(double x) {
+                return erf_inv(1.0 - x);
+            }
+
+            double normal_quantile(double p) {
+                static const double ROOT_TWO = std::sqrt(2.0);
+
+                double result = 0.0;
+                assert(p >= 0 && p <= 1);
+                if (p < 0 || p > 1) {
+                    return result;
+                }
+
+                result = -erfc_inv(2.0 * p);
+                // result *= normal distribution standard deviation (1.0) * sqrt(2)
+                result *= /*sd * */ ROOT_TWO;
+                // result += normal disttribution mean (0)
+                return result;
+            }
+
+            double outlier_variance(Estimate<double> mean, Estimate<double> stddev, int n) {
+                double sb = stddev.point;
+                double mn = mean.point / n;
+                double mg_min = mn / 2.;
+                double sg = (std::min)(mg_min / 4., sb / std::sqrt(n));
+                double sg2 = sg * sg;
+                double sb2 = sb * sb;
+
+                auto c_max = [n, mn, sb2, sg2](double x) -> double {
+                    double k = mn - x;
+                    double d = k * k;
+                    double nd = n * d;
+                    double k0 = -n * nd;
+                    double k1 = sb2 - n * sg2 + nd;
+                    double det = k1 * k1 - 4 * sg2 * k0;
+                    return (int)(-2. * k0 / (k1 + std::sqrt(det)));
+                };
+
+                auto var_out = [n, sb2, sg2](double c) {
+                    double nc = n - c;
+                    return (nc / n) * (sb2 - nc * sg2);
+                };
+
+                return (std::min)(var_out(1), var_out((std::min)(c_max(0.), c_max(mg_min)))) / sb2;
+            }
+
+            bootstrap_analysis analyse_samples(double confidence_level, int n_resamples, std::vector<double>::iterator first, std::vector<double>::iterator last) {
+                CATCH_INTERNAL_START_WARNINGS_SUPPRESSION
+                CATCH_INTERNAL_SUPPRESS_GLOBALS_WARNINGS
+                static std::random_device entropy;
+                CATCH_INTERNAL_STOP_WARNINGS_SUPPRESSION
+
+                auto n = static_cast<int>(last - first); // seriously, one can't use integral types without hell in C++
+
+                auto mean = &Detail::mean<std::vector<double>::iterator>;
+                auto stddev = &standard_deviation;
+
+#if defined(CATCH_CONFIG_USE_ASYNC)
+                auto Estimate = [=](double(*f)(std::vector<double>::iterator, std::vector<double>::iterator)) {
+                    auto seed = entropy();
+                    return std::async(std::launch::async, [=] {
+                        std::mt19937 rng(seed);
+                        auto resampled = resample(rng, n_resamples, first, last, f);
+                        return bootstrap(confidence_level, first, last, resampled, f);
+                    });
+                };
+
+                auto mean_future = Estimate(mean);
+                auto stddev_future = Estimate(stddev);
+
+                auto mean_estimate = mean_future.get();
+                auto stddev_estimate = stddev_future.get();
+#else
+                auto Estimate = [=](double(*f)(std::vector<double>::iterator, std::vector<double>::iterator)) {
+                    auto seed = entropy();
+                    std::mt19937 rng(seed);
+                    auto resampled = resample(rng, n_resamples, first, last, f);
+                    return bootstrap(confidence_level, first, last, resampled, f);
+                };
+
+                auto mean_estimate = Estimate(mean);
+                auto stddev_estimate = Estimate(stddev);
+#endif // CATCH_USE_ASYNC
+
+                double outlier_variance = Detail::outlier_variance(mean_estimate, stddev_estimate, n);
+
+                return { mean_estimate, stddev_estimate, outlier_variance };
+            }
+        } // namespace Detail
+    } // namespace Benchmark
+} // namespace Catch
+
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+// end catch_stats.cpp
+// start catch_approx.cpp
+
+#include <cmath>
+#include <limits>
+
+namespace {
+
+// Performs equivalent check of std::fabs(lhs - rhs) <= margin
+// But without the subtraction to allow for INFINITY in comparison
+bool marginComparison(double lhs, double rhs, double margin) {
+    return (lhs + margin >= rhs) && (rhs + margin >= lhs);
+}
+
+}
+
+namespace Catch {
+namespace Detail {
+
+    Approx::Approx ( double value )
+    :   m_epsilon( std::numeric_limits<float>::epsilon()*100 ),
+        m_margin( 0.0 ),
+        m_scale( 0.0 ),
+        m_value( value )
+    {}
+
+    Approx Approx::custom() {
+        return Approx( 0 );
+    }
+
+    Approx Approx::operator-() const {
+        auto temp(*this);
+        temp.m_value = -temp.m_value;
+        return temp;
+    }
+
+    std::string Approx::toString() const {
+        ReusableStringStream rss;
+        rss << "Approx( " << ::Catch::Detail::stringify( m_value ) << " )";
+        return rss.str();
+    }
+
+    bool Approx::equalityComparisonImpl(const double other) const {
+        // First try with fixed margin, then compute margin based on epsilon, scale and Approx's value
+        // Thanks to Richard Harris for his help refining the scaled margin value
+        return marginComparison(m_value, other, m_margin)
+            || marginComparison(m_value, other, m_epsilon * (m_scale + std::fabs(std::isinf(m_value)? 0 : m_value)));
+    }
+
+    void Approx::setMargin(double newMargin) {
+        CATCH_ENFORCE(newMargin >= 0,
+            "Invalid Approx::margin: " << newMargin << '.'
+            << " Approx::Margin has to be non-negative.");
+        m_margin = newMargin;
+    }
+
+    void Approx::setEpsilon(double newEpsilon) {
+        CATCH_ENFORCE(newEpsilon >= 0 && newEpsilon <= 1.0,
+            "Invalid Approx::epsilon: " << newEpsilon << '.'
+            << " Approx::epsilon has to be in [0, 1]");
+        m_epsilon = newEpsilon;
+    }
+
+} // end namespace Detail
+
+namespace literals {
+    Detail::Approx operator "" _a(long double val) {
+        return Detail::Approx(val);
+    }
+    Detail::Approx operator "" _a(unsigned long long val) {
+        return Detail::Approx(val);
+    }
+} // end namespace literals
+
+std::string StringMaker<Catch::Detail::Approx>::convert(Catch::Detail::Approx const& value) {
+    return value.toString();
+}
+
+} // end namespace Catch
+// end catch_approx.cpp
+// start catch_assertionhandler.cpp
+
+// start catch_debugger.h
+
+namespace Catch {
+    bool isDebuggerActive();
+}
+
+#ifdef CATCH_PLATFORM_MAC
+
+    #if defined(__i386__) || defined(__x86_64__)
+        #define CATCH_TRAP() __asm__("int $3\n" : : ) /* NOLINT */
+    #elif defined(__aarch64__)
+        #define CATCH_TRAP()  __asm__(".inst 0xd4200000")
+    #endif
+
+#elif defined(CATCH_PLATFORM_IPHONE)
+
+    // use inline assembler
+    #if defined(__i386__) || defined(__x86_64__)
+        #define CATCH_TRAP()  __asm__("int $3")
+    #elif defined(__aarch64__)
+        #define CATCH_TRAP()  __asm__(".inst 0xd4200000")
+    #elif defined(__arm__) && !defined(__thumb__)
+        #define CATCH_TRAP()  __asm__(".inst 0xe7f001f0")
+    #elif defined(__arm__) &&  defined(__thumb__)
+        #define CATCH_TRAP()  __asm__(".inst 0xde01")
+    #endif
+
+#elif defined(CATCH_PLATFORM_LINUX)
+    // If we can use inline assembler, do it because this allows us to break
+    // directly at the location of the failing check instead of breaking inside
+    // raise() called from it, i.e. one stack frame below.
+    #if defined(__GNUC__) && (defined(__i386) || defined(__x86_64))
+        #define CATCH_TRAP() asm volatile ("int $3") /* NOLINT */
+    #else // Fall back to the generic way.
+        #include <signal.h>
+
+        #define CATCH_TRAP() raise(SIGTRAP)
+    #endif
+#elif defined(_MSC_VER)
+    #define CATCH_TRAP() __debugbreak()
+#elif defined(__MINGW32__)
+    extern "C" __declspec(dllimport) void __stdcall DebugBreak();
+    #define CATCH_TRAP() DebugBreak()
+#endif
+
+#ifndef CATCH_BREAK_INTO_DEBUGGER
+    #ifdef CATCH_TRAP
+        #define CATCH_BREAK_INTO_DEBUGGER() []{ if( Catch::isDebuggerActive() ) { CATCH_TRAP(); } }()
+    #else
+        #define CATCH_BREAK_INTO_DEBUGGER() []{}()
+    #endif
+#endif
+
+// end catch_debugger.h
+// start catch_run_context.h
+
+// start catch_fatal_condition.h
+
+#include <cassert>
+
+namespace Catch {
+
+    // Wrapper for platform-specific fatal error (signals/SEH) handlers
+    //
+    // Tries to be cooperative with other handlers, and not step over
+    // other handlers. This means that unknown structured exceptions
+    // are passed on, previous signal handlers are called, and so on.
+    //
+    // Can only be instantiated once, and assumes that once a signal
+    // is caught, the binary will end up terminating. Thus, there
+    class FatalConditionHandler {
+        bool m_started = false;
+
+        // Install/disengage implementation for specific platform.
+        // Should be if-defed to work on current platform, can assume
+        // engage-disengage 1:1 pairing.
+        void engage_platform();
+        void disengage_platform();
+    public:
+        // Should also have platform-specific implementations as needed
+        FatalConditionHandler();
+        ~FatalConditionHandler();
+
+        void engage() {
+            assert(!m_started && "Handler cannot be installed twice.");
+            m_started = true;
+            engage_platform();
+        }
+
+        void disengage() {
+            assert(m_started && "Handler cannot be uninstalled without being installed first");
+            m_started = false;
+            disengage_platform();
+        }
+    };
+
+    //! Simple RAII guard for (dis)engaging the FatalConditionHandler
+    class FatalConditionHandlerGuard {
+        FatalConditionHandler* m_handler;
+    public:
+        FatalConditionHandlerGuard(FatalConditionHandler* handler):
+            m_handler(handler) {
+            m_handler->engage();
+        }
+        ~FatalConditionHandlerGuard() {
+            m_handler->disengage();
+        }
+    };
+
+} // end namespace Catch
+
+// end catch_fatal_condition.h
+#include <string>
+
+namespace Catch {
+
+    struct IMutableContext;
+
+    ///////////////////////////////////////////////////////////////////////////
+
+    class RunContext : public IResultCapture, public IRunner {
+
+    public:
+        RunContext( RunContext const& ) = delete;
+        RunContext& operator =( RunContext const& ) = delete;
+
+        explicit RunContext( IConfigPtr const& _config, IStreamingReporterPtr&& reporter );
+
+        ~RunContext() override;
+
+        void testGroupStarting( std::string const& testSpec, std::size_t groupIndex, std::size_t groupsCount );
+        void testGroupEnded( std::string const& testSpec, Totals const& totals, std::size_t groupIndex, std::size_t groupsCount );
+
+        Totals runTest(TestCase const& testCase);
+
+        IConfigPtr config() const;
+        IStreamingReporter& reporter() const;
+
+    public: // IResultCapture
+
+        // Assertion handlers
+        void handleExpr
+                (   AssertionInfo const& info,
+                    ITransientExpression const& expr,
+                    AssertionReaction& reaction ) override;
+        void handleMessage
+                (   AssertionInfo const& info,
+                    ResultWas::OfType resultType,
+                    StringRef const& message,
+                    AssertionReaction& reaction ) override;
+        void handleUnexpectedExceptionNotThrown
+                (   AssertionInfo const& info,
+                    AssertionReaction& reaction ) override;
+        void handleUnexpectedInflightException
+                (   AssertionInfo const& info,
+                    std::string const& message,
+                    AssertionReaction& reaction ) override;
+        void handleIncomplete
+                (   AssertionInfo const& info ) override;
+        void handleNonExpr
+                (   AssertionInfo const &info,
+                    ResultWas::OfType resultType,
+                    AssertionReaction &reaction ) override;
+
+        bool sectionStarted( SectionInfo const& sectionInfo, Counts& assertions ) override;
+
+        void sectionEnded( SectionEndInfo const& endInfo ) override;
+        void sectionEndedEarly( SectionEndInfo const& endInfo ) override;
+
+        auto acquireGeneratorTracker( StringRef generatorName, SourceLineInfo const& lineInfo ) -> IGeneratorTracker& override;
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        void benchmarkPreparing( std::string const& name ) override;
+        void benchmarkStarting( BenchmarkInfo const& info ) override;
+        void benchmarkEnded( BenchmarkStats<> const& stats ) override;
+        void benchmarkFailed( std::string const& error ) override;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        void pushScopedMessage( MessageInfo const& message ) override;
+        void popScopedMessage( MessageInfo const& message ) override;
+
+        void emplaceUnscopedMessage( MessageBuilder const& builder ) override;
+
+        std::string getCurrentTestName() const override;
+
+        const AssertionResult* getLastResult() const override;
+
+        void exceptionEarlyReported() override;
+
+        void handleFatalErrorCondition( StringRef message ) override;
+
+        bool lastAssertionPassed() override;
+
+        void assertionPassed() override;
+
+    public:
+        // !TBD We need to do this another way!
+        bool aborting() const final;
+
+    private:
+
+        void runCurrentTest( std::string& redirectedCout, std::string& redirectedCerr );
+        void invokeActiveTestCase();
+
+        void resetAssertionInfo();
+        bool testForMissingAssertions( Counts& assertions );
+
+        void assertionEnded( AssertionResult const& result );
+        void reportExpr
+                (   AssertionInfo const &info,
+                    ResultWas::OfType resultType,
+                    ITransientExpression const *expr,
+                    bool negated );
+
+        void populateReaction( AssertionReaction& reaction );
+
+    private:
+
+        void handleUnfinishedSections();
+
+        TestRunInfo m_runInfo;
+        IMutableContext& m_context;
+        TestCase const* m_activeTestCase = nullptr;
+        ITracker* m_testCaseTracker = nullptr;
+        Option<AssertionResult> m_lastResult;
+
+        IConfigPtr m_config;
+        Totals m_totals;
+        IStreamingReporterPtr m_reporter;
+        std::vector<MessageInfo> m_messages;
+        std::vector<ScopedMessage> m_messageScopes; /* Keeps owners of so-called unscoped messages. */
+        AssertionInfo m_lastAssertionInfo;
+        std::vector<SectionEndInfo> m_unfinishedSections;
+        std::vector<ITracker*> m_activeSections;
+        TrackerContext m_trackerContext;
+        FatalConditionHandler m_fatalConditionhandler;
+        bool m_lastAssertionPassed = false;
+        bool m_shouldReportUnexpected = true;
+        bool m_includeSuccessfulResults;
+    };
+
+    void seedRng(IConfig const& config);
+    unsigned int rngSeed();
+} // end namespace Catch
+
+// end catch_run_context.h
+namespace Catch {
+
+    namespace {
+        auto operator <<( std::ostream& os, ITransientExpression const& expr ) -> std::ostream& {
+            expr.streamReconstructedExpression( os );
+            return os;
+        }
+    }
+
+    LazyExpression::LazyExpression( bool isNegated )
+    :   m_isNegated( isNegated )
+    {}
+
+    LazyExpression::LazyExpression( LazyExpression const& other ) : m_isNegated( other.m_isNegated ) {}
+
+    LazyExpression::operator bool() const {
+        return m_transientExpression != nullptr;
+    }
+
+    auto operator << ( std::ostream& os, LazyExpression const& lazyExpr ) -> std::ostream& {
+        if( lazyExpr.m_isNegated )
+            os << "!";
+
+        if( lazyExpr ) {
+            if( lazyExpr.m_isNegated && lazyExpr.m_transientExpression->isBinaryExpression() )
+                os << "(" << *lazyExpr.m_transientExpression << ")";
+            else
+                os << *lazyExpr.m_transientExpression;
+        }
+        else {
+            os << "{** error - unchecked empty expression requested **}";
+        }
+        return os;
+    }
+
+    AssertionHandler::AssertionHandler
+        (   StringRef const& macroName,
+            SourceLineInfo const& lineInfo,
+            StringRef capturedExpression,
+            ResultDisposition::Flags resultDisposition )
+    :   m_assertionInfo{ macroName, lineInfo, capturedExpression, resultDisposition },
+        m_resultCapture( getResultCapture() )
+    {}
+
+    void AssertionHandler::handleExpr( ITransientExpression const& expr ) {
+        m_resultCapture.handleExpr( m_assertionInfo, expr, m_reaction );
+    }
+    void AssertionHandler::handleMessage(ResultWas::OfType resultType, StringRef const& message) {
+        m_resultCapture.handleMessage( m_assertionInfo, resultType, message, m_reaction );
+    }
+
+    auto AssertionHandler::allowThrows() const -> bool {
+        return getCurrentContext().getConfig()->allowThrows();
+    }
+
+    void AssertionHandler::complete() {
+        setCompleted();
+        if( m_reaction.shouldDebugBreak ) {
+
+            // If you find your debugger stopping you here then go one level up on the
+            // call-stack for the code that caused it (typically a failed assertion)
+
+            // (To go back to the test and change execution, jump over the throw, next)
+            CATCH_BREAK_INTO_DEBUGGER();
+        }
+        if (m_reaction.shouldThrow) {
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+            throw Catch::TestFailureException();
+#else
+            CATCH_ERROR( "Test failure requires aborting test!" );
+#endif
+        }
+    }
+    void AssertionHandler::setCompleted() {
+        m_completed = true;
+    }
+
+    void AssertionHandler::handleUnexpectedInflightException() {
+        m_resultCapture.handleUnexpectedInflightException( m_assertionInfo, Catch::translateActiveException(), m_reaction );
+    }
+
+    void AssertionHandler::handleExceptionThrownAsExpected() {
+        m_resultCapture.handleNonExpr(m_assertionInfo, ResultWas::Ok, m_reaction);
+    }
+    void AssertionHandler::handleExceptionNotThrownAsExpected() {
+        m_resultCapture.handleNonExpr(m_assertionInfo, ResultWas::Ok, m_reaction);
+    }
+
+    void AssertionHandler::handleUnexpectedExceptionNotThrown() {
+        m_resultCapture.handleUnexpectedExceptionNotThrown( m_assertionInfo, m_reaction );
+    }
+
+    void AssertionHandler::handleThrowingCallSkipped() {
+        m_resultCapture.handleNonExpr(m_assertionInfo, ResultWas::Ok, m_reaction);
+    }
+
+    // This is the overload that takes a string and infers the Equals matcher from it
+    // The more general overload, that takes any string matcher, is in catch_capture_matchers.cpp
+    void handleExceptionMatchExpr( AssertionHandler& handler, std::string const& str, StringRef const& matcherString  ) {
+        handleExceptionMatchExpr( handler, Matchers::Equals( str ), matcherString );
+    }
+
+} // namespace Catch
+// end catch_assertionhandler.cpp
+// start catch_assertionresult.cpp
+
+namespace Catch {
+    AssertionResultData::AssertionResultData(ResultWas::OfType _resultType, LazyExpression const & _lazyExpression):
+        lazyExpression(_lazyExpression),
+        resultType(_resultType) {}
+
+    std::string AssertionResultData::reconstructExpression() const {
+
+        if( reconstructedExpression.empty() ) {
+            if( lazyExpression ) {
+                ReusableStringStream rss;
+                rss << lazyExpression;
+                reconstructedExpression = rss.str();
+            }
+        }
+        return reconstructedExpression;
+    }
+
+    AssertionResult::AssertionResult( AssertionInfo const& info, AssertionResultData const& data )
+    :   m_info( info ),
+        m_resultData( data )
+    {}
+
+    // Result was a success
+    bool AssertionResult::succeeded() const {
+        return Catch::isOk( m_resultData.resultType );
+    }
+
+    // Result was a success, or failure is suppressed
+    bool AssertionResult::isOk() const {
+        return Catch::isOk( m_resultData.resultType ) || shouldSuppressFailure( m_info.resultDisposition );
+    }
+
+    ResultWas::OfType AssertionResult::getResultType() const {
+        return m_resultData.resultType;
+    }
+
+    bool AssertionResult::hasExpression() const {
+        return !m_info.capturedExpression.empty();
+    }
+
+    bool AssertionResult::hasMessage() const {
+        return !m_resultData.message.empty();
+    }
+
+    std::string AssertionResult::getExpression() const {
+        // Possibly overallocating by 3 characters should be basically free
+        std::string expr; expr.reserve(m_info.capturedExpression.size() + 3);
+        if (isFalseTest(m_info.resultDisposition)) {
+            expr += "!(";
+        }
+        expr += m_info.capturedExpression;
+        if (isFalseTest(m_info.resultDisposition)) {
+            expr += ')';
+        }
+        return expr;
+    }
+
+    std::string AssertionResult::getExpressionInMacro() const {
+        std::string expr;
+        if( m_info.macroName.empty() )
+            expr = static_cast<std::string>(m_info.capturedExpression);
+        else {
+            expr.reserve( m_info.macroName.size() + m_info.capturedExpression.size() + 4 );
+            expr += m_info.macroName;
+            expr += "( ";
+            expr += m_info.capturedExpression;
+            expr += " )";
+        }
+        return expr;
+    }
+
+    bool AssertionResult::hasExpandedExpression() const {
+        return hasExpression() && getExpandedExpression() != getExpression();
+    }
+
+    std::string AssertionResult::getExpandedExpression() const {
+        std::string expr = m_resultData.reconstructExpression();
+        return expr.empty()
+                ? getExpression()
+                : expr;
+    }
+
+    std::string AssertionResult::getMessage() const {
+        return m_resultData.message;
+    }
+    SourceLineInfo AssertionResult::getSourceInfo() const {
+        return m_info.lineInfo;
+    }
+
+    StringRef AssertionResult::getTestMacroName() const {
+        return m_info.macroName;
+    }
+
+} // end namespace Catch
+// end catch_assertionresult.cpp
+// start catch_capture_matchers.cpp
+
+namespace Catch {
+
+    using StringMatcher = Matchers::Impl::MatcherBase<std::string>;
+
+    // This is the general overload that takes a any string matcher
+    // There is another overload, in catch_assertionhandler.h/.cpp, that only takes a string and infers
+    // the Equals matcher (so the header does not mention matchers)
+    void handleExceptionMatchExpr( AssertionHandler& handler, StringMatcher const& matcher, StringRef const& matcherString  ) {
+        std::string exceptionMessage = Catch::translateActiveException();
+        MatchExpr<std::string, StringMatcher const&> expr( exceptionMessage, matcher, matcherString );
+        handler.handleExpr( expr );
+    }
+
+} // namespace Catch
+// end catch_capture_matchers.cpp
+// start catch_commandline.cpp
+
+// start catch_commandline.h
+
+// start catch_clara.h
+
+// Use Catch's value for console width (store Clara's off to the side, if present)
+#ifdef CLARA_CONFIG_CONSOLE_WIDTH
+#define CATCH_TEMP_CLARA_CONFIG_CONSOLE_WIDTH CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH
+#undef CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH
+#endif
+#define CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH CATCH_CONFIG_CONSOLE_WIDTH-1
+
+#ifdef __clang__
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wweak-vtables"
+#pragma clang diagnostic ignored "-Wexit-time-destructors"
+#pragma clang diagnostic ignored "-Wshadow"
+#endif
+
+// start clara.hpp
+// Copyright 2017 Two Blue Cubes Ltd. All rights reserved.
+//
+// Distributed under the Boost Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// See https://github.com/philsquared/Clara for more details
+
+// Clara v1.1.5
+
+
+#ifndef CATCH_CLARA_CONFIG_CONSOLE_WIDTH
+#define CATCH_CLARA_CONFIG_CONSOLE_WIDTH 80
+#endif
+
+#ifndef CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH
+#define CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH CATCH_CLARA_CONFIG_CONSOLE_WIDTH
+#endif
+
+#ifndef CLARA_CONFIG_OPTIONAL_TYPE
+#ifdef __has_include
+#if __has_include(<optional>) && __cplusplus >= 201703L
+#include <optional>
+#define CLARA_CONFIG_OPTIONAL_TYPE std::optional
+#endif
+#endif
+#endif
+
+// ----------- #included from clara_textflow.hpp -----------
+
+// TextFlowCpp
+//
+// A single-header library for wrapping and laying out basic text, by Phil Nash
+//
+// Distributed under the Boost Software License, Version 1.0. (See accompanying
+// file LICENSE.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// This project is hosted at https://github.com/philsquared/textflowcpp
+
+
+#include <cassert>
+#include <ostream>
+#include <sstream>
+#include <vector>
+
+#ifndef CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH
+#define CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH 80
+#endif
+
+namespace Catch {
+namespace clara {
+namespace TextFlow {
+
+inline auto isWhitespace(char c) -> bool {
+	static std::string chars = " \t\n\r";
+	return chars.find(c) != std::string::npos;
+}
+inline auto isBreakableBefore(char c) -> bool {
+	static std::string chars = "[({<|";
+	return chars.find(c) != std::string::npos;
+}
+inline auto isBreakableAfter(char c) -> bool {
+	static std::string chars = "])}>.,:;*+-=&/\\";
+	return chars.find(c) != std::string::npos;
+}
+
+class Columns;
+
+class Column {
+	std::vector<std::string> m_strings;
+	size_t m_width = CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH;
+	size_t m_indent = 0;
+	size_t m_initialIndent = std::string::npos;
+
+public:
+	class iterator {
+		friend Column;
+
+		Column const& m_column;
+		size_t m_stringIndex = 0;
+		size_t m_pos = 0;
+
+		size_t m_len = 0;
+		size_t m_end = 0;
+		bool m_suffix = false;
+
+		iterator(Column const& column, size_t stringIndex)
+			: m_column(column),
+			m_stringIndex(stringIndex) {}
+
+		auto line() const -> std::string const& { return m_column.m_strings[m_stringIndex]; }
+
+		auto isBoundary(size_t at) const -> bool {
+			assert(at > 0);
+			assert(at <= line().size());
+
+			return at == line().size() ||
+				(isWhitespace(line()[at]) && !isWhitespace(line()[at - 1])) ||
+				isBreakableBefore(line()[at]) ||
+				isBreakableAfter(line()[at - 1]);
+		}
+
+		void calcLength() {
+			assert(m_stringIndex < m_column.m_strings.size());
+
+			m_suffix = false;
+			auto width = m_column.m_width - indent();
+			m_end = m_pos;
+			if (line()[m_pos] == '\n') {
+				++m_end;
+			}
+			while (m_end < line().size() && line()[m_end] != '\n')
+				++m_end;
+
+			if (m_end < m_pos + width) {
+				m_len = m_end - m_pos;
+			} else {
+				size_t len = width;
+				while (len > 0 && !isBoundary(m_pos + len))
+					--len;
+				while (len > 0 && isWhitespace(line()[m_pos + len - 1]))
+					--len;
+
+				if (len > 0) {
+					m_len = len;
+				} else {
+					m_suffix = true;
+					m_len = width - 1;
+				}
+			}
+		}
+
+		auto indent() const -> size_t {
+			auto initial = m_pos == 0 && m_stringIndex == 0 ? m_column.m_initialIndent : std::string::npos;
+			return initial == std::string::npos ? m_column.m_indent : initial;
+		}
+
+		auto addIndentAndSuffix(std::string const &plain) const -> std::string {
+			return std::string(indent(), ' ') + (m_suffix ? plain + "-" : plain);
+		}
+
+	public:
+		using difference_type = std::ptrdiff_t;
+		using value_type = std::string;
+		using pointer = value_type * ;
+		using reference = value_type & ;
+		using iterator_category = std::forward_iterator_tag;
+
+		explicit iterator(Column const& column) : m_column(column) {
+			assert(m_column.m_width > m_column.m_indent);
+			assert(m_column.m_initialIndent == std::string::npos || m_column.m_width > m_column.m_initialIndent);
+			calcLength();
+			if (m_len == 0)
+				m_stringIndex++; // Empty string
+		}
+
+		auto operator *() const -> std::string {
+			assert(m_stringIndex < m_column.m_strings.size());
+			assert(m_pos <= m_end);
+			return addIndentAndSuffix(line().substr(m_pos, m_len));
+		}
+
+		auto operator ++() -> iterator& {
+			m_pos += m_len;
+			if (m_pos < line().size() && line()[m_pos] == '\n')
+				m_pos += 1;
+			else
+				while (m_pos < line().size() && isWhitespace(line()[m_pos]))
+					++m_pos;
+
+			if (m_pos == line().size()) {
+				m_pos = 0;
+				++m_stringIndex;
+			}
+			if (m_stringIndex < m_column.m_strings.size())
+				calcLength();
+			return *this;
+		}
+		auto operator ++(int) -> iterator {
+			iterator prev(*this);
+			operator++();
+			return prev;
+		}
+
+		auto operator ==(iterator const& other) const -> bool {
+			return
+				m_pos == other.m_pos &&
+				m_stringIndex == other.m_stringIndex &&
+				&m_column == &other.m_column;
+		}
+		auto operator !=(iterator const& other) const -> bool {
+			return !operator==(other);
+		}
+	};
+	using const_iterator = iterator;
+
+	explicit Column(std::string const& text) { m_strings.push_back(text); }
+
+	auto width(size_t newWidth) -> Column& {
+		assert(newWidth > 0);
+		m_width = newWidth;
+		return *this;
+	}
+	auto indent(size_t newIndent) -> Column& {
+		m_indent = newIndent;
+		return *this;
+	}
+	auto initialIndent(size_t newIndent) -> Column& {
+		m_initialIndent = newIndent;
+		return *this;
+	}
+
+	auto width() const -> size_t { return m_width; }
+	auto begin() const -> iterator { return iterator(*this); }
+	auto end() const -> iterator { return { *this, m_strings.size() }; }
+
+	inline friend std::ostream& operator << (std::ostream& os, Column const& col) {
+		bool first = true;
+		for (auto line : col) {
+			if (first)
+				first = false;
+			else
+				os << "\n";
+			os << line;
+		}
+		return os;
+	}
+
+	auto operator + (Column const& other)->Columns;
+
+	auto toString() const -> std::string {
+		std::ostringstream oss;
+		oss << *this;
+		return oss.str();
+	}
+};
+
+class Spacer : public Column {
+
+public:
+	explicit Spacer(size_t spaceWidth) : Column("") {
+		width(spaceWidth);
+	}
+};
+
+class Columns {
+	std::vector<Column> m_columns;
+
+public:
+
+	class iterator {
+		friend Columns;
+		struct EndTag {};
+
+		std::vector<Column> const& m_columns;
+		std::vector<Column::iterator> m_iterators;
+		size_t m_activeIterators;
+
+		iterator(Columns const& columns, EndTag)
+			: m_columns(columns.m_columns),
+			m_activeIterators(0) {
+			m_iterators.reserve(m_columns.size());
+
+			for (auto const& col : m_columns)
+				m_iterators.push_back(col.end());
+		}
+
+	public:
+		using difference_type = std::ptrdiff_t;
+		using value_type = std::string;
+		using pointer = value_type * ;
+		using reference = value_type & ;
+		using iterator_category = std::forward_iterator_tag;
+
+		explicit iterator(Columns const& columns)
+			: m_columns(columns.m_columns),
+			m_activeIterators(m_columns.size()) {
+			m_iterators.reserve(m_columns.size());
+
+			for (auto const& col : m_columns)
+				m_iterators.push_back(col.begin());
+		}
+
+		auto operator ==(iterator const& other) const -> bool {
+			return m_iterators == other.m_iterators;
+		}
+		auto operator !=(iterator const& other) const -> bool {
+			return m_iterators != other.m_iterators;
+		}
+		auto operator *() const -> std::string {
+			std::string row, padding;
+
+			for (size_t i = 0; i < m_columns.size(); ++i) {
+				auto width = m_columns[i].width();
+				if (m_iterators[i] != m_columns[i].end()) {
+					std::string col = *m_iterators[i];
+					row += padding + col;
+					if (col.size() < width)
+						padding = std::string(width - col.size(), ' ');
+					else
+						padding = "";
+				} else {
+					padding += std::string(width, ' ');
+				}
+			}
+			return row;
+		}
+		auto operator ++() -> iterator& {
+			for (size_t i = 0; i < m_columns.size(); ++i) {
+				if (m_iterators[i] != m_columns[i].end())
+					++m_iterators[i];
+			}
+			return *this;
+		}
+		auto operator ++(int) -> iterator {
+			iterator prev(*this);
+			operator++();
+			return prev;
+		}
+	};
+	using const_iterator = iterator;
+
+	auto begin() const -> iterator { return iterator(*this); }
+	auto end() const -> iterator { return { *this, iterator::EndTag() }; }
+
+	auto operator += (Column const& col) -> Columns& {
+		m_columns.push_back(col);
+		return *this;
+	}
+	auto operator + (Column const& col) -> Columns {
+		Columns combined = *this;
+		combined += col;
+		return combined;
+	}
+
+	inline friend std::ostream& operator << (std::ostream& os, Columns const& cols) {
+
+		bool first = true;
+		for (auto line : cols) {
+			if (first)
+				first = false;
+			else
+				os << "\n";
+			os << line;
+		}
+		return os;
+	}
+
+	auto toString() const -> std::string {
+		std::ostringstream oss;
+		oss << *this;
+		return oss.str();
+	}
+};
+
+inline auto Column::operator + (Column const& other) -> Columns {
+	Columns cols;
+	cols += *this;
+	cols += other;
+	return cols;
+}
+}
+
+}
+}
+
+// ----------- end of #include from clara_textflow.hpp -----------
+// ........... back in clara.hpp
+
+#include <cctype>
+#include <string>
+#include <memory>
+#include <set>
+#include <algorithm>
+
+#if !defined(CATCH_PLATFORM_WINDOWS) && ( defined(WIN32) || defined(__WIN32__) || defined(_WIN32) || defined(_MSC_VER) )
+#define CATCH_PLATFORM_WINDOWS
+#endif
+
+namespace Catch { namespace clara {
+namespace detail {
+
+    // Traits for extracting arg and return type of lambdas (for single argument lambdas)
+    template<typename L>
+    struct UnaryLambdaTraits : UnaryLambdaTraits<decltype( &L::operator() )> {};
+
+    template<typename ClassT, typename ReturnT, typename... Args>
+    struct UnaryLambdaTraits<ReturnT( ClassT::* )( Args... ) const> {
+        static const bool isValid = false;
+    };
+
+    template<typename ClassT, typename ReturnT, typename ArgT>
+    struct UnaryLambdaTraits<ReturnT( ClassT::* )( ArgT ) const> {
+        static const bool isValid = true;
+        using ArgType = typename std::remove_const<typename std::remove_reference<ArgT>::type>::type;
+        using ReturnType = ReturnT;
+    };
+
+    class TokenStream;
+
+    // Transport for raw args (copied from main args, or supplied via init list for testing)
+    class Args {
+        friend TokenStream;
+        std::string m_exeName;
+        std::vector<std::string> m_args;
+
+    public:
+        Args( int argc, char const* const* argv )
+            : m_exeName(argv[0]),
+              m_args(argv + 1, argv + argc) {}
+
+        Args( std::initializer_list<std::string> args )
+        :   m_exeName( *args.begin() ),
+            m_args( args.begin()+1, args.end() )
+        {}
+
+        auto exeName() const -> std::string {
+            return m_exeName;
+        }
+    };
+
+    // Wraps a token coming from a token stream. These may not directly correspond to strings as a single string
+    // may encode an option + its argument if the : or = form is used
+    enum class TokenType {
+        Option, Argument
+    };
+    struct Token {
+        TokenType type;
+        std::string token;
+    };
+
+    inline auto isOptPrefix( char c ) -> bool {
+        return c == '-'
+#ifdef CATCH_PLATFORM_WINDOWS
+            || c == '/'
+#endif
+        ;
+    }
+
+    // Abstracts iterators into args as a stream of tokens, with option arguments uniformly handled
+    class TokenStream {
+        using Iterator = std::vector<std::string>::const_iterator;
+        Iterator it;
+        Iterator itEnd;
+        std::vector<Token> m_tokenBuffer;
+
+        void loadBuffer() {
+            m_tokenBuffer.resize( 0 );
+
+            // Skip any empty strings
+            while( it != itEnd && it->empty() )
+                ++it;
+
+            if( it != itEnd ) {
+                auto const &next = *it;
+                if( isOptPrefix( next[0] ) ) {
+                    auto delimiterPos = next.find_first_of( " :=" );
+                    if( delimiterPos != std::string::npos ) {
+                        m_tokenBuffer.push_back( { TokenType::Option, next.substr( 0, delimiterPos ) } );
+                        m_tokenBuffer.push_back( { TokenType::Argument, next.substr( delimiterPos + 1 ) } );
+                    } else {
+                        if( next[1] != '-' && next.size() > 2 ) {
+                            std::string opt = "- ";
+                            for( size_t i = 1; i < next.size(); ++i ) {
+                                opt[1] = next[i];
+                                m_tokenBuffer.push_back( { TokenType::Option, opt } );
+                            }
+                        } else {
+                            m_tokenBuffer.push_back( { TokenType::Option, next } );
+                        }
+                    }
+                } else {
+                    m_tokenBuffer.push_back( { TokenType::Argument, next } );
+                }
+            }
+        }
+
+    public:
+        explicit TokenStream( Args const &args ) : TokenStream( args.m_args.begin(), args.m_args.end() ) {}
+
+        TokenStream( Iterator it, Iterator itEnd ) : it( it ), itEnd( itEnd ) {
+            loadBuffer();
+        }
+
+        explicit operator bool() const {
+            return !m_tokenBuffer.empty() || it != itEnd;
+        }
+
+        auto count() const -> size_t { return m_tokenBuffer.size() + (itEnd - it); }
+
+        auto operator*() const -> Token {
+            assert( !m_tokenBuffer.empty() );
+            return m_tokenBuffer.front();
+        }
+
+        auto operator->() const -> Token const * {
+            assert( !m_tokenBuffer.empty() );
+            return &m_tokenBuffer.front();
+        }
+
+        auto operator++() -> TokenStream & {
+            if( m_tokenBuffer.size() >= 2 ) {
+                m_tokenBuffer.erase( m_tokenBuffer.begin() );
+            } else {
+                if( it != itEnd )
+                    ++it;
+                loadBuffer();
+            }
+            return *this;
+        }
+    };
+
+    class ResultBase {
+    public:
+        enum Type {
+            Ok, LogicError, RuntimeError
+        };
+
+    protected:
+        ResultBase( Type type ) : m_type( type ) {}
+        virtual ~ResultBase() = default;
+
+        virtual void enforceOk() const = 0;
+
+        Type m_type;
+    };
+
+    template<typename T>
+    class ResultValueBase : public ResultBase {
+    public:
+        auto value() const -> T const & {
+            enforceOk();
+            return m_value;
+        }
+
+    protected:
+        ResultValueBase( Type type ) : ResultBase( type ) {}
+
+        ResultValueBase( ResultValueBase const &other ) : ResultBase( other ) {
+            if( m_type == ResultBase::Ok )
+                new( &m_value ) T( other.m_value );
+        }
+
+        ResultValueBase( Type, T const &value ) : ResultBase( Ok ) {
+            new( &m_value ) T( value );
+        }
+
+        auto operator=( ResultValueBase const &other ) -> ResultValueBase & {
+            if( m_type == ResultBase::Ok )
+                m_value.~T();
+            ResultBase::operator=(other);
+            if( m_type == ResultBase::Ok )
+                new( &m_value ) T( other.m_value );
+            return *this;
+        }
+
+        ~ResultValueBase() override {
+            if( m_type == Ok )
+                m_value.~T();
+        }
+
+        union {
+            T m_value;
+        };
+    };
+
+    template<>
+    class ResultValueBase<void> : public ResultBase {
+    protected:
+        using ResultBase::ResultBase;
+    };
+
+    template<typename T = void>
+    class BasicResult : public ResultValueBase<T> {
+    public:
+        template<typename U>
+        explicit BasicResult( BasicResult<U> const &other )
+        :   ResultValueBase<T>( other.type() ),
+            m_errorMessage( other.errorMessage() )
+        {
+            assert( type() != ResultBase::Ok );
+        }
+
+        template<typename U>
+        static auto ok( U const &value ) -> BasicResult { return { ResultBase::Ok, value }; }
+        static auto ok() -> BasicResult { return { ResultBase::Ok }; }
+        static auto logicError( std::string const &message ) -> BasicResult { return { ResultBase::LogicError, message }; }
+        static auto runtimeError( std::string const &message ) -> BasicResult { return { ResultBase::RuntimeError, message }; }
+
+        explicit operator bool() const { return m_type == ResultBase::Ok; }
+        auto type() const -> ResultBase::Type { return m_type; }
+        auto errorMessage() const -> std::string { return m_errorMessage; }
+
+    protected:
+        void enforceOk() const override {
+
+            // Errors shouldn't reach this point, but if they do
+            // the actual error message will be in m_errorMessage
+            assert( m_type != ResultBase::LogicError );
+            assert( m_type != ResultBase::RuntimeError );
+            if( m_type != ResultBase::Ok )
+                std::abort();
+        }
+
+        std::string m_errorMessage; // Only populated if resultType is an error
+
+        BasicResult( ResultBase::Type type, std::string const &message )
+        :   ResultValueBase<T>(type),
+            m_errorMessage(message)
+        {
+            assert( m_type != ResultBase::Ok );
+        }
+
+        using ResultValueBase<T>::ResultValueBase;
+        using ResultBase::m_type;
+    };
+
+    enum class ParseResultType {
+        Matched, NoMatch, ShortCircuitAll, ShortCircuitSame
+    };
+
+    class ParseState {
+    public:
+
+        ParseState( ParseResultType type, TokenStream const &remainingTokens )
+        : m_type(type),
+          m_remainingTokens( remainingTokens )
+        {}
+
+        auto type() const -> ParseResultType { return m_type; }
+        auto remainingTokens() const -> TokenStream { return m_remainingTokens; }
+
+    private:
+        ParseResultType m_type;
+        TokenStream m_remainingTokens;
+    };
+
+    using Result = BasicResult<void>;
+    using ParserResult = BasicResult<ParseResultType>;
+    using InternalParseResult = BasicResult<ParseState>;
+
+    struct HelpColumns {
+        std::string left;
+        std::string right;
+    };
+
+    template<typename T>
+    inline auto convertInto( std::string const &source, T& target ) -> ParserResult {
+        std::stringstream ss;
+        ss << source;
+        ss >> target;
+        if( ss.fail() )
+            return ParserResult::runtimeError( "Unable to convert '" + source + "' to destination type" );
+        else
+            return ParserResult::ok( ParseResultType::Matched );
+    }
+    inline auto convertInto( std::string const &source, std::string& target ) -> ParserResult {
+        target = source;
+        return ParserResult::ok( ParseResultType::Matched );
+    }
+    inline auto convertInto( std::string const &source, bool &target ) -> ParserResult {
+        std::string srcLC = source;
+        std::transform( srcLC.begin(), srcLC.end(), srcLC.begin(), []( unsigned char c ) { return static_cast<char>( std::tolower(c) ); } );
+        if (srcLC == "y" || srcLC == "1" || srcLC == "true" || srcLC == "yes" || srcLC == "on")
+            target = true;
+        else if (srcLC == "n" || srcLC == "0" || srcLC == "false" || srcLC == "no" || srcLC == "off")
+            target = false;
+        else
+            return ParserResult::runtimeError( "Expected a boolean value but did not recognise: '" + source + "'" );
+        return ParserResult::ok( ParseResultType::Matched );
+    }
+#ifdef CLARA_CONFIG_OPTIONAL_TYPE
+    template<typename T>
+    inline auto convertInto( std::string const &source, CLARA_CONFIG_OPTIONAL_TYPE<T>& target ) -> ParserResult {
+        T temp;
+        auto result = convertInto( source, temp );
+        if( result )
+            target = std::move(temp);
+        return result;
+    }
+#endif // CLARA_CONFIG_OPTIONAL_TYPE
+
+    struct NonCopyable {
+        NonCopyable() = default;
+        NonCopyable( NonCopyable const & ) = delete;
+        NonCopyable( NonCopyable && ) = delete;
+        NonCopyable &operator=( NonCopyable const & ) = delete;
+        NonCopyable &operator=( NonCopyable && ) = delete;
+    };
+
+    struct BoundRef : NonCopyable {
+        virtual ~BoundRef() = default;
+        virtual auto isContainer() const -> bool { return false; }
+        virtual auto isFlag() const -> bool { return false; }
+    };
+    struct BoundValueRefBase : BoundRef {
+        virtual auto setValue( std::string const &arg ) -> ParserResult = 0;
+    };
+    struct BoundFlagRefBase : BoundRef {
+        virtual auto setFlag( bool flag ) -> ParserResult = 0;
+        virtual auto isFlag() const -> bool { return true; }
+    };
+
+    template<typename T>
+    struct BoundValueRef : BoundValueRefBase {
+        T &m_ref;
+
+        explicit BoundValueRef( T &ref ) : m_ref( ref ) {}
+
+        auto setValue( std::string const &arg ) -> ParserResult override {
+            return convertInto( arg, m_ref );
+        }
+    };
+
+    template<typename T>
+    struct BoundValueRef<std::vector<T>> : BoundValueRefBase {
+        std::vector<T> &m_ref;
+
+        explicit BoundValueRef( std::vector<T> &ref ) : m_ref( ref ) {}
+
+        auto isContainer() const -> bool override { return true; }
+
+        auto setValue( std::string const &arg ) -> ParserResult override {
+            T temp;
+            auto result = convertInto( arg, temp );
+            if( result )
+                m_ref.push_back( temp );
+            return result;
+        }
+    };
+
+    struct BoundFlagRef : BoundFlagRefBase {
+        bool &m_ref;
+
+        explicit BoundFlagRef( bool &ref ) : m_ref( ref ) {}
+
+        auto setFlag( bool flag ) -> ParserResult override {
+            m_ref = flag;
+            return ParserResult::ok( ParseResultType::Matched );
+        }
+    };
+
+    template<typename ReturnType>
+    struct LambdaInvoker {
+        static_assert( std::is_same<ReturnType, ParserResult>::value, "Lambda must return void or clara::ParserResult" );
+
+        template<typename L, typename ArgType>
+        static auto invoke( L const &lambda, ArgType const &arg ) -> ParserResult {
+            return lambda( arg );
+        }
+    };
+
+    template<>
+    struct LambdaInvoker<void> {
+        template<typename L, typename ArgType>
+        static auto invoke( L const &lambda, ArgType const &arg ) -> ParserResult {
+            lambda( arg );
+            return ParserResult::ok( ParseResultType::Matched );
+        }
+    };
+
+    template<typename ArgType, typename L>
+    inline auto invokeLambda( L const &lambda, std::string const &arg ) -> ParserResult {
+        ArgType temp{};
+        auto result = convertInto( arg, temp );
+        return !result
+           ? result
+           : LambdaInvoker<typename UnaryLambdaTraits<L>::ReturnType>::invoke( lambda, temp );
+    }
+
+    template<typename L>
+    struct BoundLambda : BoundValueRefBase {
+        L m_lambda;
+
+        static_assert( UnaryLambdaTraits<L>::isValid, "Supplied lambda must take exactly one argument" );
+        explicit BoundLambda( L const &lambda ) : m_lambda( lambda ) {}
+
+        auto setValue( std::string const &arg ) -> ParserResult override {
+            return invokeLambda<typename UnaryLambdaTraits<L>::ArgType>( m_lambda, arg );
+        }
+    };
+
+    template<typename L>
+    struct BoundFlagLambda : BoundFlagRefBase {
+        L m_lambda;
+
+        static_assert( UnaryLambdaTraits<L>::isValid, "Supplied lambda must take exactly one argument" );
+        static_assert( std::is_same<typename UnaryLambdaTraits<L>::ArgType, bool>::value, "flags must be boolean" );
+
+        explicit BoundFlagLambda( L const &lambda ) : m_lambda( lambda ) {}
+
+        auto setFlag( bool flag ) -> ParserResult override {
+            return LambdaInvoker<typename UnaryLambdaTraits<L>::ReturnType>::invoke( m_lambda, flag );
+        }
+    };
+
+    enum class Optionality { Optional, Required };
+
+    struct Parser;
+
+    class ParserBase {
+    public:
+        virtual ~ParserBase() = default;
+        virtual auto validate() const -> Result { return Result::ok(); }
+        virtual auto parse( std::string const& exeName, TokenStream const &tokens) const -> InternalParseResult  = 0;
+        virtual auto cardinality() const -> size_t { return 1; }
+
+        auto parse( Args const &args ) const -> InternalParseResult {
+            return parse( args.exeName(), TokenStream( args ) );
+        }
+    };
+
+    template<typename DerivedT>
+    class ComposableParserImpl : public ParserBase {
+    public:
+        template<typename T>
+        auto operator|( T const &other ) const -> Parser;
+
+		template<typename T>
+        auto operator+( T const &other ) const -> Parser;
+    };
+
+    // Common code and state for Args and Opts
+    template<typename DerivedT>
+    class ParserRefImpl : public ComposableParserImpl<DerivedT> {
+    protected:
+        Optionality m_optionality = Optionality::Optional;
+        std::shared_ptr<BoundRef> m_ref;
+        std::string m_hint;
+        std::string m_description;
+
+        explicit ParserRefImpl( std::shared_ptr<BoundRef> const &ref ) : m_ref( ref ) {}
+
+    public:
+        template<typename T>
+        ParserRefImpl( T &ref, std::string const &hint )
+        :   m_ref( std::make_shared<BoundValueRef<T>>( ref ) ),
+            m_hint( hint )
+        {}
+
+        template<typename LambdaT>
+        ParserRefImpl( LambdaT const &ref, std::string const &hint )
+        :   m_ref( std::make_shared<BoundLambda<LambdaT>>( ref ) ),
+            m_hint(hint)
+        {}
+
+        auto operator()( std::string const &description ) -> DerivedT & {
+            m_description = description;
+            return static_cast<DerivedT &>( *this );
+        }
+
+        auto optional() -> DerivedT & {
+            m_optionality = Optionality::Optional;
+            return static_cast<DerivedT &>( *this );
+        };
+
+        auto required() -> DerivedT & {
+            m_optionality = Optionality::Required;
+            return static_cast<DerivedT &>( *this );
+        };
+
+        auto isOptional() const -> bool {
+            return m_optionality == Optionality::Optional;
+        }
+
+        auto cardinality() const -> size_t override {
+            if( m_ref->isContainer() )
+                return 0;
+            else
+                return 1;
+        }
+
+        auto hint() const -> std::string { return m_hint; }
+    };
+
+    class ExeName : public ComposableParserImpl<ExeName> {
+        std::shared_ptr<std::string> m_name;
+        std::shared_ptr<BoundValueRefBase> m_ref;
+
+        template<typename LambdaT>
+        static auto makeRef(LambdaT const &lambda) -> std::shared_ptr<BoundValueRefBase> {
+            return std::make_shared<BoundLambda<LambdaT>>( lambda) ;
+        }
+
+    public:
+        ExeName() : m_name( std::make_shared<std::string>( "<executable>" ) ) {}
+
+        explicit ExeName( std::string &ref ) : ExeName() {
+            m_ref = std::make_shared<BoundValueRef<std::string>>( ref );
+        }
+
+        template<typename LambdaT>
+        explicit ExeName( LambdaT const& lambda ) : ExeName() {
+            m_ref = std::make_shared<BoundLambda<LambdaT>>( lambda );
+        }
+
+        // The exe name is not parsed out of the normal tokens, but is handled specially
+        auto parse( std::string const&, TokenStream const &tokens ) const -> InternalParseResult override {
+            return InternalParseResult::ok( ParseState( ParseResultType::NoMatch, tokens ) );
+        }
+
+        auto name() const -> std::string { return *m_name; }
+        auto set( std::string const& newName ) -> ParserResult {
+
+            auto lastSlash = newName.find_last_of( "\\/" );
+            auto filename = ( lastSlash == std::string::npos )
+                    ? newName
+                    : newName.substr( lastSlash+1 );
+
+            *m_name = filename;
+            if( m_ref )
+                return m_ref->setValue( filename );
+            else
+                return ParserResult::ok( ParseResultType::Matched );
+        }
+    };
+
+    class Arg : public ParserRefImpl<Arg> {
+    public:
+        using ParserRefImpl::ParserRefImpl;
+
+        auto parse( std::string const &, TokenStream const &tokens ) const -> InternalParseResult override {
+            auto validationResult = validate();
+            if( !validationResult )
+                return InternalParseResult( validationResult );
+
+            auto remainingTokens = tokens;
+            auto const &token = *remainingTokens;
+            if( token.type != TokenType::Argument )
+                return InternalParseResult::ok( ParseState( ParseResultType::NoMatch, remainingTokens ) );
+
+            assert( !m_ref->isFlag() );
+            auto valueRef = static_cast<detail::BoundValueRefBase*>( m_ref.get() );
+
+            auto result = valueRef->setValue( remainingTokens->token );
+            if( !result )
+                return InternalParseResult( result );
+            else
+                return InternalParseResult::ok( ParseState( ParseResultType::Matched, ++remainingTokens ) );
+        }
+    };
+
+    inline auto normaliseOpt( std::string const &optName ) -> std::string {
+#ifdef CATCH_PLATFORM_WINDOWS
+        if( optName[0] == '/' )
+            return "-" + optName.substr( 1 );
+        else
+#endif
+            return optName;
+    }
+
+    class Opt : public ParserRefImpl<Opt> {
+    protected:
+        std::vector<std::string> m_optNames;
+
+    public:
+        template<typename LambdaT>
+        explicit Opt( LambdaT const &ref ) : ParserRefImpl( std::make_shared<BoundFlagLambda<LambdaT>>( ref ) ) {}
+
+        explicit Opt( bool &ref ) : ParserRefImpl( std::make_shared<BoundFlagRef>( ref ) ) {}
+
+        template<typename LambdaT>
+        Opt( LambdaT const &ref, std::string const &hint ) : ParserRefImpl( ref, hint ) {}
+
+        template<typename T>
+        Opt( T &ref, std::string const &hint ) : ParserRefImpl( ref, hint ) {}
+
+        auto operator[]( std::string const &optName ) -> Opt & {
+            m_optNames.push_back( optName );
+            return *this;
+        }
+
+        auto getHelpColumns() const -> std::vector<HelpColumns> {
+            std::ostringstream oss;
+            bool first = true;
+            for( auto const &opt : m_optNames ) {
+                if (first)
+                    first = false;
+                else
+                    oss << ", ";
+                oss << opt;
+            }
+            if( !m_hint.empty() )
+                oss << " <" << m_hint << ">";
+            return { { oss.str(), m_description } };
+        }
+
+        auto isMatch( std::string const &optToken ) const -> bool {
+            auto normalisedToken = normaliseOpt( optToken );
+            for( auto const &name : m_optNames ) {
+                if( normaliseOpt( name ) == normalisedToken )
+                    return true;
+            }
+            return false;
+        }
+
+        using ParserBase::parse;
+
+        auto parse( std::string const&, TokenStream const &tokens ) const -> InternalParseResult override {
+            auto validationResult = validate();
+            if( !validationResult )
+                return InternalParseResult( validationResult );
+
+            auto remainingTokens = tokens;
+            if( remainingTokens && remainingTokens->type == TokenType::Option ) {
+                auto const &token = *remainingTokens;
+                if( isMatch(token.token ) ) {
+                    if( m_ref->isFlag() ) {
+                        auto flagRef = static_cast<detail::BoundFlagRefBase*>( m_ref.get() );
+                        auto result = flagRef->setFlag( true );
+                        if( !result )
+                            return InternalParseResult( result );
+                        if( result.value() == ParseResultType::ShortCircuitAll )
+                            return InternalParseResult::ok( ParseState( result.value(), remainingTokens ) );
+                    } else {
+                        auto valueRef = static_cast<detail::BoundValueRefBase*>( m_ref.get() );
+                        ++remainingTokens;
+                        if( !remainingTokens )
+                            return InternalParseResult::runtimeError( "Expected argument following " + token.token );
+                        auto const &argToken = *remainingTokens;
+                        if( argToken.type != TokenType::Argument )
+                            return InternalParseResult::runtimeError( "Expected argument following " + token.token );
+                        auto result = valueRef->setValue( argToken.token );
+                        if( !result )
+                            return InternalParseResult( result );
+                        if( result.value() == ParseResultType::ShortCircuitAll )
+                            return InternalParseResult::ok( ParseState( result.value(), remainingTokens ) );
+                    }
+                    return InternalParseResult::ok( ParseState( ParseResultType::Matched, ++remainingTokens ) );
+                }
+            }
+            return InternalParseResult::ok( ParseState( ParseResultType::NoMatch, remainingTokens ) );
+        }
+
+        auto validate() const -> Result override {
+            if( m_optNames.empty() )
+                return Result::logicError( "No options supplied to Opt" );
+            for( auto const &name : m_optNames ) {
+                if( name.empty() )
+                    return Result::logicError( "Option name cannot be empty" );
+#ifdef CATCH_PLATFORM_WINDOWS
+                if( name[0] != '-' && name[0] != '/' )
+                    return Result::logicError( "Option name must begin with '-' or '/'" );
+#else
+                if( name[0] != '-' )
+                    return Result::logicError( "Option name must begin with '-'" );
+#endif
+            }
+            return ParserRefImpl::validate();
+        }
+    };
+
+    struct Help : Opt {
+        Help( bool &showHelpFlag )
+        :   Opt([&]( bool flag ) {
+                showHelpFlag = flag;
+                return ParserResult::ok( ParseResultType::ShortCircuitAll );
+            })
+        {
+            static_cast<Opt &>( *this )
+                    ("display usage information")
+                    ["-?"]["-h"]["--help"]
+                    .optional();
+        }
+    };
+
+    struct Parser : ParserBase {
+
+        mutable ExeName m_exeName;
+        std::vector<Opt> m_options;
+        std::vector<Arg> m_args;
+
+        auto operator|=( ExeName const &exeName ) -> Parser & {
+            m_exeName = exeName;
+            return *this;
+        }
+
+        auto operator|=( Arg const &arg ) -> Parser & {
+            m_args.push_back(arg);
+            return *this;
+        }
+
+        auto operator|=( Opt const &opt ) -> Parser & {
+            m_options.push_back(opt);
+            return *this;
+        }
+
+        auto operator|=( Parser const &other ) -> Parser & {
+            m_options.insert(m_options.end(), other.m_options.begin(), other.m_options.end());
+            m_args.insert(m_args.end(), other.m_args.begin(), other.m_args.end());
+            return *this;
+        }
+
+        template<typename T>
+        auto operator|( T const &other ) const -> Parser {
+            return Parser( *this ) |= other;
+        }
+
+        // Forward deprecated interface with '+' instead of '|'
+        template<typename T>
+        auto operator+=( T const &other ) -> Parser & { return operator|=( other ); }
+        template<typename T>
+        auto operator+( T const &other ) const -> Parser { return operator|( other ); }
+
+        auto getHelpColumns() const -> std::vector<HelpColumns> {
+            std::vector<HelpColumns> cols;
+            for (auto const &o : m_options) {
+                auto childCols = o.getHelpColumns();
+                cols.insert( cols.end(), childCols.begin(), childCols.end() );
+            }
+            return cols;
+        }
+
+        void writeToStream( std::ostream &os ) const {
+            if (!m_exeName.name().empty()) {
+                os << "usage:\n" << "  " << m_exeName.name() << " ";
+                bool required = true, first = true;
+                for( auto const &arg : m_args ) {
+                    if (first)
+                        first = false;
+                    else
+                        os << " ";
+                    if( arg.isOptional() && required ) {
+                        os << "[";
+                        required = false;
+                    }
+                    os << "<" << arg.hint() << ">";
+                    if( arg.cardinality() == 0 )
+                        os << " ... ";
+                }
+                if( !required )
+                    os << "]";
+                if( !m_options.empty() )
+                    os << " options";
+                os << "\n\nwhere options are:" << std::endl;
+            }
+
+            auto rows = getHelpColumns();
+            size_t consoleWidth = CATCH_CLARA_CONFIG_CONSOLE_WIDTH;
+            size_t optWidth = 0;
+            for( auto const &cols : rows )
+                optWidth = (std::max)(optWidth, cols.left.size() + 2);
+
+            optWidth = (std::min)(optWidth, consoleWidth/2);
+
+            for( auto const &cols : rows ) {
+                auto row =
+                        TextFlow::Column( cols.left ).width( optWidth ).indent( 2 ) +
+                        TextFlow::Spacer(4) +
+                        TextFlow::Column( cols.right ).width( consoleWidth - 7 - optWidth );
+                os << row << std::endl;
+            }
+        }
+
+        friend auto operator<<( std::ostream &os, Parser const &parser ) -> std::ostream& {
+            parser.writeToStream( os );
+            return os;
+        }
+
+        auto validate() const -> Result override {
+            for( auto const &opt : m_options ) {
+                auto result = opt.validate();
+                if( !result )
+                    return result;
+            }
+            for( auto const &arg : m_args ) {
+                auto result = arg.validate();
+                if( !result )
+                    return result;
+            }
+            return Result::ok();
+        }
+
+        using ParserBase::parse;
+
+        auto parse( std::string const& exeName, TokenStream const &tokens ) const -> InternalParseResult override {
+
+            struct ParserInfo {
+                ParserBase const* parser = nullptr;
+                size_t count = 0;
+            };
+            const size_t totalParsers = m_options.size() + m_args.size();
+            assert( totalParsers < 512 );
+            // ParserInfo parseInfos[totalParsers]; // <-- this is what we really want to do
+            ParserInfo parseInfos[512];
+
+            {
+                size_t i = 0;
+                for (auto const &opt : m_options) parseInfos[i++].parser = &opt;
+                for (auto const &arg : m_args) parseInfos[i++].parser = &arg;
+            }
+
+            m_exeName.set( exeName );
+
+            auto result = InternalParseResult::ok( ParseState( ParseResultType::NoMatch, tokens ) );
+            while( result.value().remainingTokens() ) {
+                bool tokenParsed = false;
+
+                for( size_t i = 0; i < totalParsers; ++i ) {
+                    auto&  parseInfo = parseInfos[i];
+                    if( parseInfo.parser->cardinality() == 0 || parseInfo.count < parseInfo.parser->cardinality() ) {
+                        result = parseInfo.parser->parse(exeName, result.value().remainingTokens());
+                        if (!result)
+                            return result;
+                        if (result.value().type() != ParseResultType::NoMatch) {
+                            tokenParsed = true;
+                            ++parseInfo.count;
+                            break;
+                        }
+                    }
+                }
+
+                if( result.value().type() == ParseResultType::ShortCircuitAll )
+                    return result;
+                if( !tokenParsed )
+                    return InternalParseResult::runtimeError( "Unrecognised token: " + result.value().remainingTokens()->token );
+            }
+            // !TBD Check missing required options
+            return result;
+        }
+    };
+
+    template<typename DerivedT>
+    template<typename T>
+    auto ComposableParserImpl<DerivedT>::operator|( T const &other ) const -> Parser {
+        return Parser() | static_cast<DerivedT const &>( *this ) | other;
+    }
+} // namespace detail
+
+// A Combined parser
+using detail::Parser;
+
+// A parser for options
+using detail::Opt;
+
+// A parser for arguments
+using detail::Arg;
+
+// Wrapper for argc, argv from main()
+using detail::Args;
+
+// Specifies the name of the executable
+using detail::ExeName;
+
+// Convenience wrapper for option parser that specifies the help option
+using detail::Help;
+
+// enum of result types from a parse
+using detail::ParseResultType;
+
+// Result type for parser operation
+using detail::ParserResult;
+
+}} // namespace Catch::clara
+
+// end clara.hpp
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// Restore Clara's value for console width, if present
+#ifdef CATCH_TEMP_CLARA_CONFIG_CONSOLE_WIDTH
+#define CATCH_CLARA_TEXTFLOW_CONFIG_CONSOLE_WIDTH CATCH_TEMP_CLARA_CONFIG_CONSOLE_WIDTH
+#undef CATCH_TEMP_CLARA_CONFIG_CONSOLE_WIDTH
+#endif
+
+// end catch_clara.h
+namespace Catch {
+
+    clara::Parser makeCommandLineParser( ConfigData& config );
+
+} // end namespace Catch
+
+// end catch_commandline.h
+#include <fstream>
+#include <ctime>
+
+namespace Catch {
+
+    clara::Parser makeCommandLineParser( ConfigData& config ) {
+
+        using namespace clara;
+
+        auto const setWarning = [&]( std::string const& warning ) {
+                auto warningSet = [&]() {
+                    if( warning == "NoAssertions" )
+                        return WarnAbout::NoAssertions;
+
+                    if ( warning == "NoTests" )
+                        return WarnAbout::NoTests;
+
+                    return WarnAbout::Nothing;
+                }();
+
+                if (warningSet == WarnAbout::Nothing)
+                    return ParserResult::runtimeError( "Unrecognised warning: '" + warning + "'" );
+                config.warnings = static_cast<WarnAbout::What>( config.warnings | warningSet );
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const loadTestNamesFromFile = [&]( std::string const& filename ) {
+                std::ifstream f( filename.c_str() );
+                if( !f.is_open() )
+                    return ParserResult::runtimeError( "Unable to load input file: '" + filename + "'" );
+
+                std::string line;
+                while( std::getline( f, line ) ) {
+                    line = trim(line);
+                    if( !line.empty() && !startsWith( line, '#' ) ) {
+                        if( !startsWith( line, '"' ) )
+                            line = '"' + line + '"';
+                        config.testsOrTags.push_back( line );
+                        config.testsOrTags.emplace_back( "," );
+                    }
+                }
+                //Remove comma in the end
+                if(!config.testsOrTags.empty())
+                    config.testsOrTags.erase( config.testsOrTags.end()-1 );
+
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setTestOrder = [&]( std::string const& order ) {
+                if( startsWith( "declared", order ) )
+                    config.runOrder = RunTests::InDeclarationOrder;
+                else if( startsWith( "lexical", order ) )
+                    config.runOrder = RunTests::InLexicographicalOrder;
+                else if( startsWith( "random", order ) )
+                    config.runOrder = RunTests::InRandomOrder;
+                else
+                    return clara::ParserResult::runtimeError( "Unrecognised ordering: '" + order + "'" );
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setRngSeed = [&]( std::string const& seed ) {
+                if( seed != "time" )
+                    return clara::detail::convertInto( seed, config.rngSeed );
+                config.rngSeed = static_cast<unsigned int>( std::time(nullptr) );
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setColourUsage = [&]( std::string const& useColour ) {
+                    auto mode = toLower( useColour );
+
+                    if( mode == "yes" )
+                        config.useColour = UseColour::Yes;
+                    else if( mode == "no" )
+                        config.useColour = UseColour::No;
+                    else if( mode == "auto" )
+                        config.useColour = UseColour::Auto;
+                    else
+                        return ParserResult::runtimeError( "colour mode must be one of: auto, yes or no. '" + useColour + "' not recognised" );
+                return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setWaitForKeypress = [&]( std::string const& keypress ) {
+                auto keypressLc = toLower( keypress );
+                if (keypressLc == "never")
+                    config.waitForKeypress = WaitForKeypress::Never;
+                else if( keypressLc == "start" )
+                    config.waitForKeypress = WaitForKeypress::BeforeStart;
+                else if( keypressLc == "exit" )
+                    config.waitForKeypress = WaitForKeypress::BeforeExit;
+                else if( keypressLc == "both" )
+                    config.waitForKeypress = WaitForKeypress::BeforeStartAndExit;
+                else
+                    return ParserResult::runtimeError( "keypress argument must be one of: never, start, exit or both. '" + keypress + "' not recognised" );
+            return ParserResult::ok( ParseResultType::Matched );
+            };
+        auto const setVerbosity = [&]( std::string const& verbosity ) {
+            auto lcVerbosity = toLower( verbosity );
+            if( lcVerbosity == "quiet" )
+                config.verbosity = Verbosity::Quiet;
+            else if( lcVerbosity == "normal" )
+                config.verbosity = Verbosity::Normal;
+            else if( lcVerbosity == "high" )
+                config.verbosity = Verbosity::High;
+            else
+                return ParserResult::runtimeError( "Unrecognised verbosity, '" + verbosity + "'" );
+            return ParserResult::ok( ParseResultType::Matched );
+        };
+        auto const setReporter = [&]( std::string const& reporter ) {
+            IReporterRegistry::FactoryMap const& factories = getRegistryHub().getReporterRegistry().getFactories();
+
+            auto lcReporter = toLower( reporter );
+            auto result = factories.find( lcReporter );
+
+            if( factories.end() != result )
+                config.reporterName = lcReporter;
+            else
+                return ParserResult::runtimeError( "Unrecognized reporter, '" + reporter + "'. Check available with --list-reporters" );
+            return ParserResult::ok( ParseResultType::Matched );
+        };
+
+        auto cli
+            = ExeName( config.processName )
+            | Help( config.showHelp )
+            | Opt( config.listTests )
+                ["-l"]["--list-tests"]
+                ( "list all/matching test cases" )
+            | Opt( config.listTags )
+                ["-t"]["--list-tags"]
+                ( "list all/matching tags" )
+            | Opt( config.showSuccessfulTests )
+                ["-s"]["--success"]
+                ( "include successful tests in output" )
+            | Opt( config.shouldDebugBreak )
+                ["-b"]["--break"]
+                ( "break into debugger on failure" )
+            | Opt( config.noThrow )
+                ["-e"]["--nothrow"]
+                ( "skip exception tests" )
+            | Opt( config.showInvisibles )
+                ["-i"]["--invisibles"]
+                ( "show invisibles (tabs, newlines)" )
+            | Opt( config.outputFilename, "filename" )
+                ["-o"]["--out"]
+                ( "output filename" )
+            | Opt( setReporter, "name" )
+                ["-r"]["--reporter"]
+                ( "reporter to use (defaults to console)" )
+            | Opt( config.name, "name" )
+                ["-n"]["--name"]
+                ( "suite name" )
+            | Opt( [&]( bool ){ config.abortAfter = 1; } )
+                ["-a"]["--abort"]
+                ( "abort at first failure" )
+            | Opt( [&]( int x ){ config.abortAfter = x; }, "no. failures" )
+                ["-x"]["--abortx"]
+                ( "abort after x failures" )
+            | Opt( setWarning, "warning name" )
+                ["-w"]["--warn"]
+                ( "enable warnings" )
+            | Opt( [&]( bool flag ) { config.showDurations = flag ? ShowDurations::Always : ShowDurations::Never; }, "yes|no" )
+                ["-d"]["--durations"]
+                ( "show test durations" )
+            | Opt( config.minDuration, "seconds" )
+                ["-D"]["--min-duration"]
+                ( "show test durations for tests taking at least the given number of seconds" )
+            | Opt( loadTestNamesFromFile, "filename" )
+                ["-f"]["--input-file"]
+                ( "load test names to run from a file" )
+            | Opt( config.filenamesAsTags )
+                ["-#"]["--filenames-as-tags"]
+                ( "adds a tag for the filename" )
+            | Opt( config.sectionsToRun, "section name" )
+                ["-c"]["--section"]
+                ( "specify section to run" )
+            | Opt( setVerbosity, "quiet|normal|high" )
+                ["-v"]["--verbosity"]
+                ( "set output verbosity" )
+            | Opt( config.listTestNamesOnly )
+                ["--list-test-names-only"]
+                ( "list all/matching test cases names only" )
+            | Opt( config.listReporters )
+                ["--list-reporters"]
+                ( "list all reporters" )
+            | Opt( setTestOrder, "decl|lex|rand" )
+                ["--order"]
+                ( "test case order (defaults to decl)" )
+            | Opt( setRngSeed, "'time'|number" )
+                ["--rng-seed"]
+                ( "set a specific seed for random numbers" )
+            | Opt( setColourUsage, "yes|no" )
+                ["--use-colour"]
+                ( "should output be colourised" )
+            | Opt( config.libIdentify )
+                ["--libidentify"]
+                ( "report name and version according to libidentify standard" )
+            | Opt( setWaitForKeypress, "never|start|exit|both" )
+                ["--wait-for-keypress"]
+                ( "waits for a keypress before exiting" )
+            | Opt( config.benchmarkSamples, "samples" )
+                ["--benchmark-samples"]
+                ( "number of samples to collect (default: 100)" )
+            | Opt( config.benchmarkResamples, "resamples" )
+                ["--benchmark-resamples"]
+                ( "number of resamples for the bootstrap (default: 100000)" )
+            | Opt( config.benchmarkConfidenceInterval, "confidence interval" )
+                ["--benchmark-confidence-interval"]
+                ( "confidence interval for the bootstrap (between 0 and 1, default: 0.95)" )
+            | Opt( config.benchmarkNoAnalysis )
+                ["--benchmark-no-analysis"]
+                ( "perform only measurements; do not perform any analysis" )
+            | Opt( config.benchmarkWarmupTime, "benchmarkWarmupTime" )
+                ["--benchmark-warmup-time"]
+                ( "amount of time in milliseconds spent on warming up each test (default: 100)" )
+            | Arg( config.testsOrTags, "test name|pattern|tags" )
+                ( "which test or tests to use" );
+
+        return cli;
+    }
+
+} // end namespace Catch
+// end catch_commandline.cpp
+// start catch_common.cpp
+
+#include <cstring>
+#include <ostream>
+
+namespace Catch {
+
+    bool SourceLineInfo::operator == ( SourceLineInfo const& other ) const noexcept {
+        return line == other.line && (file == other.file || std::strcmp(file, other.file) == 0);
+    }
+    bool SourceLineInfo::operator < ( SourceLineInfo const& other ) const noexcept {
+        // We can assume that the same file will usually have the same pointer.
+        // Thus, if the pointers are the same, there is no point in calling the strcmp
+        return line < other.line || ( line == other.line && file != other.file && (std::strcmp(file, other.file) < 0));
+    }
+
+    std::ostream& operator << ( std::ostream& os, SourceLineInfo const& info ) {
+#ifndef __GNUG__
+        os << info.file << '(' << info.line << ')';
+#else
+        os << info.file << ':' << info.line;
+#endif
+        return os;
+    }
+
+    std::string StreamEndStop::operator+() const {
+        return std::string();
+    }
+
+    NonCopyable::NonCopyable() = default;
+    NonCopyable::~NonCopyable() = default;
+
+}
+// end catch_common.cpp
+// start catch_config.cpp
+
+namespace Catch {
+
+    Config::Config( ConfigData const& data )
+    :   m_data( data ),
+        m_stream( openStream() )
+    {
+        // We need to trim filter specs to avoid trouble with superfluous
+        // whitespace (esp. important for bdd macros, as those are manually
+        // aligned with whitespace).
+
+        for (auto& elem : m_data.testsOrTags) {
+            elem = trim(elem);
+        }
+        for (auto& elem : m_data.sectionsToRun) {
+            elem = trim(elem);
+        }
+
+        TestSpecParser parser(ITagAliasRegistry::get());
+        if (!m_data.testsOrTags.empty()) {
+            m_hasTestFilters = true;
+            for (auto const& testOrTags : m_data.testsOrTags) {
+                parser.parse(testOrTags);
+            }
+        }
+        m_testSpec = parser.testSpec();
+    }
+
+    std::string const& Config::getFilename() const {
+        return m_data.outputFilename ;
+    }
+
+    bool Config::listTests() const          { return m_data.listTests; }
+    bool Config::listTestNamesOnly() const  { return m_data.listTestNamesOnly; }
+    bool Config::listTags() const           { return m_data.listTags; }
+    bool Config::listReporters() const      { return m_data.listReporters; }
+
+    std::string Config::getProcessName() const { return m_data.processName; }
+    std::string const& Config::getReporterName() const { return m_data.reporterName; }
+
+    std::vector<std::string> const& Config::getTestsOrTags() const { return m_data.testsOrTags; }
+    std::vector<std::string> const& Config::getSectionsToRun() const { return m_data.sectionsToRun; }
+
+    TestSpec const& Config::testSpec() const { return m_testSpec; }
+    bool Config::hasTestFilters() const { return m_hasTestFilters; }
+
+    bool Config::showHelp() const { return m_data.showHelp; }
+
+    // IConfig interface
+    bool Config::allowThrows() const                   { return !m_data.noThrow; }
+    std::ostream& Config::stream() const               { return m_stream->stream(); }
+    std::string Config::name() const                   { return m_data.name.empty() ? m_data.processName : m_data.name; }
+    bool Config::includeSuccessfulResults() const      { return m_data.showSuccessfulTests; }
+    bool Config::warnAboutMissingAssertions() const    { return !!(m_data.warnings & WarnAbout::NoAssertions); }
+    bool Config::warnAboutNoTests() const              { return !!(m_data.warnings & WarnAbout::NoTests); }
+    ShowDurations::OrNot Config::showDurations() const { return m_data.showDurations; }
+    double Config::minDuration() const                 { return m_data.minDuration; }
+    RunTests::InWhatOrder Config::runOrder() const     { return m_data.runOrder; }
+    unsigned int Config::rngSeed() const               { return m_data.rngSeed; }
+    UseColour::YesOrNo Config::useColour() const       { return m_data.useColour; }
+    bool Config::shouldDebugBreak() const              { return m_data.shouldDebugBreak; }
+    int Config::abortAfter() const                     { return m_data.abortAfter; }
+    bool Config::showInvisibles() const                { return m_data.showInvisibles; }
+    Verbosity Config::verbosity() const                { return m_data.verbosity; }
+
+    bool Config::benchmarkNoAnalysis() const                      { return m_data.benchmarkNoAnalysis; }
+    int Config::benchmarkSamples() const                          { return m_data.benchmarkSamples; }
+    double Config::benchmarkConfidenceInterval() const            { return m_data.benchmarkConfidenceInterval; }
+    unsigned int Config::benchmarkResamples() const               { return m_data.benchmarkResamples; }
+    std::chrono::milliseconds Config::benchmarkWarmupTime() const { return std::chrono::milliseconds(m_data.benchmarkWarmupTime); }
+
+    IStream const* Config::openStream() {
+        return Catch::makeStream(m_data.outputFilename);
+    }
+
+} // end namespace Catch
+// end catch_config.cpp
+// start catch_console_colour.cpp
+
+#if defined(__clang__)
+#    pragma clang diagnostic push
+#    pragma clang diagnostic ignored "-Wexit-time-destructors"
+#endif
+
+// start catch_errno_guard.h
+
+namespace Catch {
+
+    class ErrnoGuard {
+    public:
+        ErrnoGuard();
+        ~ErrnoGuard();
+    private:
+        int m_oldErrno;
+    };
+
+}
+
+// end catch_errno_guard.h
+// start catch_windows_h_proxy.h
+
+
+#if defined(CATCH_PLATFORM_WINDOWS)
+
+#if !defined(NOMINMAX) && !defined(CATCH_CONFIG_NO_NOMINMAX)
+#  define CATCH_DEFINED_NOMINMAX
+#  define NOMINMAX
+#endif
+#if !defined(WIN32_LEAN_AND_MEAN) && !defined(CATCH_CONFIG_NO_WIN32_LEAN_AND_MEAN)
+#  define CATCH_DEFINED_WIN32_LEAN_AND_MEAN
+#  define WIN32_LEAN_AND_MEAN
+#endif
+
+#ifdef __AFXDLL
+#include <AfxWin.h>
+#else
+#include <windows.h>
+#endif
+
+#ifdef CATCH_DEFINED_NOMINMAX
+#  undef NOMINMAX
+#endif
+#ifdef CATCH_DEFINED_WIN32_LEAN_AND_MEAN
+#  undef WIN32_LEAN_AND_MEAN
+#endif
+
+#endif // defined(CATCH_PLATFORM_WINDOWS)
+
+// end catch_windows_h_proxy.h
+#include <sstream>
+
+namespace Catch {
+    namespace {
+
+        struct IColourImpl {
+            virtual ~IColourImpl() = default;
+            virtual void use( Colour::Code _colourCode ) = 0;
+        };
+
+        struct NoColourImpl : IColourImpl {
+            void use( Colour::Code ) override {}
+
+            static IColourImpl* instance() {
+                static NoColourImpl s_instance;
+                return &s_instance;
+            }
+        };
+
+    } // anon namespace
+} // namespace Catch
+
+#if !defined( CATCH_CONFIG_COLOUR_NONE ) && !defined( CATCH_CONFIG_COLOUR_WINDOWS ) && !defined( CATCH_CONFIG_COLOUR_ANSI )
+#   ifdef CATCH_PLATFORM_WINDOWS
+#       define CATCH_CONFIG_COLOUR_WINDOWS
+#   else
+#       define CATCH_CONFIG_COLOUR_ANSI
+#   endif
+#endif
+
+#if defined ( CATCH_CONFIG_COLOUR_WINDOWS ) /////////////////////////////////////////
+
+namespace Catch {
+namespace {
+
+    class Win32ColourImpl : public IColourImpl {
+    public:
+        Win32ColourImpl() : stdoutHandle( GetStdHandle(STD_OUTPUT_HANDLE) )
+        {
+            CONSOLE_SCREEN_BUFFER_INFO csbiInfo;
+            GetConsoleScreenBufferInfo( stdoutHandle, &csbiInfo );
+            originalForegroundAttributes = csbiInfo.wAttributes & ~( BACKGROUND_GREEN | BACKGROUND_RED | BACKGROUND_BLUE | BACKGROUND_INTENSITY );
+            originalBackgroundAttributes = csbiInfo.wAttributes & ~( FOREGROUND_GREEN | FOREGROUND_RED | FOREGROUND_BLUE | FOREGROUND_INTENSITY );
+        }
+
+        void use( Colour::Code _colourCode ) override {
+            switch( _colourCode ) {
+                case Colour::None:      return setTextAttribute( originalForegroundAttributes );
+                case Colour::White:     return setTextAttribute( FOREGROUND_GREEN | FOREGROUND_RED | FOREGROUND_BLUE );
+                case Colour::Red:       return setTextAttribute( FOREGROUND_RED );
+                case Colour::Green:     return setTextAttribute( FOREGROUND_GREEN );
+                case Colour::Blue:      return setTextAttribute( FOREGROUND_BLUE );
+                case Colour::Cyan:      return setTextAttribute( FOREGROUND_BLUE | FOREGROUND_GREEN );
+                case Colour::Yellow:    return setTextAttribute( FOREGROUND_RED | FOREGROUND_GREEN );
+                case Colour::Grey:      return setTextAttribute( 0 );
+
+                case Colour::LightGrey:     return setTextAttribute( FOREGROUND_INTENSITY );
+                case Colour::BrightRed:     return setTextAttribute( FOREGROUND_INTENSITY | FOREGROUND_RED );
+                case Colour::BrightGreen:   return setTextAttribute( FOREGROUND_INTENSITY | FOREGROUND_GREEN );
+                case Colour::BrightWhite:   return setTextAttribute( FOREGROUND_INTENSITY | FOREGROUND_GREEN | FOREGROUND_RED | FOREGROUND_BLUE );
+                case Colour::BrightYellow:  return setTextAttribute( FOREGROUND_INTENSITY | FOREGROUND_RED | FOREGROUND_GREEN );
+
+                case Colour::Bright: CATCH_INTERNAL_ERROR( "not a colour" );
+
+                default:
+                    CATCH_ERROR( "Unknown colour requested" );
+            }
+        }
+
+    private:
+        void setTextAttribute( WORD _textAttribute ) {
+            SetConsoleTextAttribute( stdoutHandle, _textAttribute | originalBackgroundAttributes );
+        }
+        HANDLE stdoutHandle;
+        WORD originalForegroundAttributes;
+        WORD originalBackgroundAttributes;
+    };
+
+    IColourImpl* platformColourInstance() {
+        static Win32ColourImpl s_instance;
+
+        IConfigPtr config = getCurrentContext().getConfig();
+        UseColour::YesOrNo colourMode = config
+            ? config->useColour()
+            : UseColour::Auto;
+        if( colourMode == UseColour::Auto )
+            colourMode = UseColour::Yes;
+        return colourMode == UseColour::Yes
+            ? &s_instance
+            : NoColourImpl::instance();
+    }
+
+} // end anon namespace
+} // end namespace Catch
+
+#elif defined( CATCH_CONFIG_COLOUR_ANSI ) //////////////////////////////////////
+
+#include <unistd.h>
+
+namespace Catch {
+namespace {
+
+    // use POSIX/ ANSI console terminal codes
+    // Thanks to Adam Strzelecki for original contribution
+    // (http://github.com/nanoant)
+    // https://github.com/philsquared/Catch/pull/131
+    class PosixColourImpl : public IColourImpl {
+    public:
+        void use( Colour::Code _colourCode ) override {
+            switch( _colourCode ) {
+                case Colour::None:
+                case Colour::White:     return setColour( "[0m" );
+                case Colour::Red:       return setColour( "[0;31m" );
+                case Colour::Green:     return setColour( "[0;32m" );
+                case Colour::Blue:      return setColour( "[0;34m" );
+                case Colour::Cyan:      return setColour( "[0;36m" );
+                case Colour::Yellow:    return setColour( "[0;33m" );
+                case Colour::Grey:      return setColour( "[1;30m" );
+
+                case Colour::LightGrey:     return setColour( "[0;37m" );
+                case Colour::BrightRed:     return setColour( "[1;31m" );
+                case Colour::BrightGreen:   return setColour( "[1;32m" );
+                case Colour::BrightWhite:   return setColour( "[1;37m" );
+                case Colour::BrightYellow:  return setColour( "[1;33m" );
+
+                case Colour::Bright: CATCH_INTERNAL_ERROR( "not a colour" );
+                default: CATCH_INTERNAL_ERROR( "Unknown colour requested" );
+            }
+        }
+        static IColourImpl* instance() {
+            static PosixColourImpl s_instance;
+            return &s_instance;
+        }
+
+    private:
+        void setColour( const char* _escapeCode ) {
+            getCurrentContext().getConfig()->stream()
+                << '\033' << _escapeCode;
+        }
+    };
+
+    bool useColourOnPlatform() {
+        return
+#if defined(CATCH_PLATFORM_MAC) || defined(CATCH_PLATFORM_IPHONE)
+            !isDebuggerActive() &&
+#endif
+#if !(defined(__DJGPP__) && defined(__STRICT_ANSI__))
+            isatty(STDOUT_FILENO)
+#else
+            false
+#endif
+            ;
+    }
+    IColourImpl* platformColourInstance() {
+        ErrnoGuard guard;
+        IConfigPtr config = getCurrentContext().getConfig();
+        UseColour::YesOrNo colourMode = config
+            ? config->useColour()
+            : UseColour::Auto;
+        if( colourMode == UseColour::Auto )
+            colourMode = useColourOnPlatform()
+                ? UseColour::Yes
+                : UseColour::No;
+        return colourMode == UseColour::Yes
+            ? PosixColourImpl::instance()
+            : NoColourImpl::instance();
+    }
+
+} // end anon namespace
+} // end namespace Catch
+
+#else  // not Windows or ANSI ///////////////////////////////////////////////
+
+namespace Catch {
+
+    static IColourImpl* platformColourInstance() { return NoColourImpl::instance(); }
+
+} // end namespace Catch
+
+#endif // Windows/ ANSI/ None
+
+namespace Catch {
+
+    Colour::Colour( Code _colourCode ) { use( _colourCode ); }
+    Colour::Colour( Colour&& other ) noexcept {
+        m_moved = other.m_moved;
+        other.m_moved = true;
+    }
+    Colour& Colour::operator=( Colour&& other ) noexcept {
+        m_moved = other.m_moved;
+        other.m_moved  = true;
+        return *this;
+    }
+
+    Colour::~Colour(){ if( !m_moved ) use( None ); }
+
+    void Colour::use( Code _colourCode ) {
+        static IColourImpl* impl = platformColourInstance();
+        // Strictly speaking, this cannot possibly happen.
+        // However, under some conditions it does happen (see #1626),
+        // and this change is small enough that we can let practicality
+        // triumph over purity in this case.
+        if (impl != nullptr) {
+            impl->use( _colourCode );
+        }
+    }
+
+    std::ostream& operator << ( std::ostream& os, Colour const& ) {
+        return os;
+    }
+
+} // end namespace Catch
+
+#if defined(__clang__)
+#    pragma clang diagnostic pop
+#endif
+
+// end catch_console_colour.cpp
+// start catch_context.cpp
+
+namespace Catch {
+
+    class Context : public IMutableContext, NonCopyable {
+
+    public: // IContext
+        IResultCapture* getResultCapture() override {
+            return m_resultCapture;
+        }
+        IRunner* getRunner() override {
+            return m_runner;
+        }
+
+        IConfigPtr const& getConfig() const override {
+            return m_config;
+        }
+
+        ~Context() override;
+
+    public: // IMutableContext
+        void setResultCapture( IResultCapture* resultCapture ) override {
+            m_resultCapture = resultCapture;
+        }
+        void setRunner( IRunner* runner ) override {
+            m_runner = runner;
+        }
+        void setConfig( IConfigPtr const& config ) override {
+            m_config = config;
+        }
+
+        friend IMutableContext& getCurrentMutableContext();
+
+    private:
+        IConfigPtr m_config;
+        IRunner* m_runner = nullptr;
+        IResultCapture* m_resultCapture = nullptr;
+    };
+
+    IMutableContext *IMutableContext::currentContext = nullptr;
+
+    void IMutableContext::createContext()
+    {
+        currentContext = new Context();
+    }
+
+    void cleanUpContext() {
+        delete IMutableContext::currentContext;
+        IMutableContext::currentContext = nullptr;
+    }
+    IContext::~IContext() = default;
+    IMutableContext::~IMutableContext() = default;
+    Context::~Context() = default;
+
+    SimplePcg32& rng() {
+        static SimplePcg32 s_rng;
+        return s_rng;
+    }
+
+}
+// end catch_context.cpp
+// start catch_debug_console.cpp
+
+// start catch_debug_console.h
+
+#include <string>
+
+namespace Catch {
+    void writeToDebugConsole( std::string const& text );
+}
+
+// end catch_debug_console.h
+#if defined(CATCH_CONFIG_ANDROID_LOGWRITE)
+#include <android/log.h>
+
+    namespace Catch {
+        void writeToDebugConsole( std::string const& text ) {
+            __android_log_write( ANDROID_LOG_DEBUG, "Catch", text.c_str() );
+        }
+    }
+
+#elif defined(CATCH_PLATFORM_WINDOWS)
+
+    namespace Catch {
+        void writeToDebugConsole( std::string const& text ) {
+            ::OutputDebugStringA( text.c_str() );
+        }
+    }
+
+#else
+
+    namespace Catch {
+        void writeToDebugConsole( std::string const& text ) {
+            // !TBD: Need a version for Mac/ XCode and other IDEs
+            Catch::cout() << text;
+        }
+    }
+
+#endif // Platform
+// end catch_debug_console.cpp
+// start catch_debugger.cpp
+
+#if defined(CATCH_PLATFORM_MAC) || defined(CATCH_PLATFORM_IPHONE)
+
+#  include <cassert>
+#  include <sys/types.h>
+#  include <unistd.h>
+#  include <cstddef>
+#  include <ostream>
+
+#ifdef __apple_build_version__
+    // These headers will only compile with AppleClang (XCode)
+    // For other compilers (Clang, GCC, ... ) we need to exclude them
+#  include <sys/sysctl.h>
+#endif
+
+    namespace Catch {
+        #ifdef __apple_build_version__
+        // The following function is taken directly from the following technical note:
+        // https://developer.apple.com/library/archive/qa/qa1361/_index.html
+
+        // Returns true if the current process is being debugged (either
+        // running under the debugger or has a debugger attached post facto).
+        bool isDebuggerActive(){
+            int                 mib[4];
+            struct kinfo_proc   info;
+            std::size_t         size;
+
+            // Initialize the flags so that, if sysctl fails for some bizarre
+            // reason, we get a predictable result.
+
+            info.kp_proc.p_flag = 0;
+
+            // Initialize mib, which tells sysctl the info we want, in this case
+            // we're looking for information about a specific process ID.
+
+            mib[0] = CTL_KERN;
+            mib[1] = KERN_PROC;
+            mib[2] = KERN_PROC_PID;
+            mib[3] = getpid();
+
+            // Call sysctl.
+
+            size = sizeof(info);
+            if( sysctl(mib, sizeof(mib) / sizeof(*mib), &info, &size, nullptr, 0) != 0 ) {
+                Catch::cerr() << "\n** Call to sysctl failed - unable to determine if debugger is active **\n" << std::endl;
+                return false;
+            }
+
+            // We're being debugged if the P_TRACED flag is set.
+
+            return ( (info.kp_proc.p_flag & P_TRACED) != 0 );
+        }
+        #else
+        bool isDebuggerActive() {
+            // We need to find another way to determine this for non-appleclang compilers on macOS
+            return false;
+        }
+        #endif
+    } // namespace Catch
+
+#elif defined(CATCH_PLATFORM_LINUX)
+    #include <fstream>
+    #include <string>
+
+    namespace Catch{
+        // The standard POSIX way of detecting a debugger is to attempt to
+        // ptrace() the process, but this needs to be done from a child and not
+        // this process itself to still allow attaching to this process later
+        // if wanted, so is rather heavy. Under Linux we have the PID of the
+        // "debugger" (which doesn't need to be gdb, of course, it could also
+        // be strace, for example) in /proc/$PID/status, so just get it from
+        // there instead.
+        bool isDebuggerActive(){
+            // Libstdc++ has a bug, where std::ifstream sets errno to 0
+            // This way our users can properly assert over errno values
+            ErrnoGuard guard;
+            std::ifstream in("/proc/self/status");
+            for( std::string line; std::getline(in, line); ) {
+                static const int PREFIX_LEN = 11;
+                if( line.compare(0, PREFIX_LEN, "TracerPid:\t") == 0 ) {
+                    // We're traced if the PID is not 0 and no other PID starts
+                    // with 0 digit, so it's enough to check for just a single
+                    // character.
+                    return line.length() > PREFIX_LEN && line[PREFIX_LEN] != '0';
+                }
+            }
+
+            return false;
+        }
+    } // namespace Catch
+#elif defined(_MSC_VER)
+    extern "C" __declspec(dllimport) int __stdcall IsDebuggerPresent();
+    namespace Catch {
+        bool isDebuggerActive() {
+            return IsDebuggerPresent() != 0;
+        }
+    }
+#elif defined(__MINGW32__)
+    extern "C" __declspec(dllimport) int __stdcall IsDebuggerPresent();
+    namespace Catch {
+        bool isDebuggerActive() {
+            return IsDebuggerPresent() != 0;
+        }
+    }
+#else
+    namespace Catch {
+       bool isDebuggerActive() { return false; }
+    }
+#endif // Platform
+// end catch_debugger.cpp
+// start catch_decomposer.cpp
+
+namespace Catch {
+
+    ITransientExpression::~ITransientExpression() = default;
+
+    void formatReconstructedExpression( std::ostream &os, std::string const& lhs, StringRef op, std::string const& rhs ) {
+        if( lhs.size() + rhs.size() < 40 &&
+                lhs.find('\n') == std::string::npos &&
+                rhs.find('\n') == std::string::npos )
+            os << lhs << " " << op << " " << rhs;
+        else
+            os << lhs << "\n" << op << "\n" << rhs;
+    }
+}
+// end catch_decomposer.cpp
+// start catch_enforce.cpp
+
+#include <stdexcept>
+
+namespace Catch {
+#if defined(CATCH_CONFIG_DISABLE_EXCEPTIONS) && !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS_CUSTOM_HANDLER)
+    [[noreturn]]
+    void throw_exception(std::exception const& e) {
+        Catch::cerr() << "Catch will terminate because it needed to throw an exception.\n"
+                      << "The message was: " << e.what() << '\n';
+        std::terminate();
+    }
+#endif
+
+    [[noreturn]]
+    void throw_logic_error(std::string const& msg) {
+        throw_exception(std::logic_error(msg));
+    }
+
+    [[noreturn]]
+    void throw_domain_error(std::string const& msg) {
+        throw_exception(std::domain_error(msg));
+    }
+
+    [[noreturn]]
+    void throw_runtime_error(std::string const& msg) {
+        throw_exception(std::runtime_error(msg));
+    }
+
+} // namespace Catch;
+// end catch_enforce.cpp
+// start catch_enum_values_registry.cpp
+// start catch_enum_values_registry.h
+
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    namespace Detail {
+
+        std::unique_ptr<EnumInfo> makeEnumInfo( StringRef enumName, StringRef allValueNames, std::vector<int> const& values );
+
+        class EnumValuesRegistry : public IMutableEnumValuesRegistry {
+
+            std::vector<std::unique_ptr<EnumInfo>> m_enumInfos;
+
+            EnumInfo const& registerEnum( StringRef enumName, StringRef allEnums, std::vector<int> const& values) override;
+        };
+
+        std::vector<StringRef> parseEnums( StringRef enums );
+
+    } // Detail
+
+} // Catch
+
+// end catch_enum_values_registry.h
+
+#include <map>
+#include <cassert>
+
+namespace Catch {
+
+    IMutableEnumValuesRegistry::~IMutableEnumValuesRegistry() {}
+
+    namespace Detail {
+
+        namespace {
+            // Extracts the actual name part of an enum instance
+            // In other words, it returns the Blue part of Bikeshed::Colour::Blue
+            StringRef extractInstanceName(StringRef enumInstance) {
+                // Find last occurrence of ":"
+                size_t name_start = enumInstance.size();
+                while (name_start > 0 && enumInstance[name_start - 1] != ':') {
+                    --name_start;
+                }
+                return enumInstance.substr(name_start, enumInstance.size() - name_start);
+            }
+        }
+
+        std::vector<StringRef> parseEnums( StringRef enums ) {
+            auto enumValues = splitStringRef( enums, ',' );
+            std::vector<StringRef> parsed;
+            parsed.reserve( enumValues.size() );
+            for( auto const& enumValue : enumValues ) {
+                parsed.push_back(trim(extractInstanceName(enumValue)));
+            }
+            return parsed;
+        }
+
+        EnumInfo::~EnumInfo() {}
+
+        StringRef EnumInfo::lookup( int value ) const {
+            for( auto const& valueToName : m_values ) {
+                if( valueToName.first == value )
+                    return valueToName.second;
+            }
+            return "{** unexpected enum value **}"_sr;
+        }
+
+        std::unique_ptr<EnumInfo> makeEnumInfo( StringRef enumName, StringRef allValueNames, std::vector<int> const& values ) {
+            std::unique_ptr<EnumInfo> enumInfo( new EnumInfo );
+            enumInfo->m_name = enumName;
+            enumInfo->m_values.reserve( values.size() );
+
+            const auto valueNames = Catch::Detail::parseEnums( allValueNames );
+            assert( valueNames.size() == values.size() );
+            std::size_t i = 0;
+            for( auto value : values )
+                enumInfo->m_values.emplace_back(value, valueNames[i++]);
+
+            return enumInfo;
+        }
+
+        EnumInfo const& EnumValuesRegistry::registerEnum( StringRef enumName, StringRef allValueNames, std::vector<int> const& values ) {
+            m_enumInfos.push_back(makeEnumInfo(enumName, allValueNames, values));
+            return *m_enumInfos.back();
+        }
+
+    } // Detail
+} // Catch
+
+// end catch_enum_values_registry.cpp
+// start catch_errno_guard.cpp
+
+#include <cerrno>
+
+namespace Catch {
+        ErrnoGuard::ErrnoGuard():m_oldErrno(errno){}
+        ErrnoGuard::~ErrnoGuard() { errno = m_oldErrno; }
+}
+// end catch_errno_guard.cpp
+// start catch_exception_translator_registry.cpp
+
+// start catch_exception_translator_registry.h
+
+#include <vector>
+#include <string>
+#include <memory>
+
+namespace Catch {
+
+    class ExceptionTranslatorRegistry : public IExceptionTranslatorRegistry {
+    public:
+        ~ExceptionTranslatorRegistry();
+        virtual void registerTranslator( const IExceptionTranslator* translator );
+        std::string translateActiveException() const override;
+        std::string tryTranslators() const;
+
+    private:
+        std::vector<std::unique_ptr<IExceptionTranslator const>> m_translators;
+    };
+}
+
+// end catch_exception_translator_registry.h
+#ifdef __OBJC__
+#import "Foundation/Foundation.h"
+#endif
+
+namespace Catch {
+
+    ExceptionTranslatorRegistry::~ExceptionTranslatorRegistry() {
+    }
+
+    void ExceptionTranslatorRegistry::registerTranslator( const IExceptionTranslator* translator ) {
+        m_translators.push_back( std::unique_ptr<const IExceptionTranslator>( translator ) );
+    }
+
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+    std::string ExceptionTranslatorRegistry::translateActiveException() const {
+        try {
+#ifdef __OBJC__
+            // In Objective-C try objective-c exceptions first
+            @try {
+                return tryTranslators();
+            }
+            @catch (NSException *exception) {
+                return Catch::Detail::stringify( [exception description] );
+            }
+#else
+            // Compiling a mixed mode project with MSVC means that CLR
+            // exceptions will be caught in (...) as well. However, these
+            // do not fill-in std::current_exception and thus lead to crash
+            // when attempting rethrow.
+            // /EHa switch also causes structured exceptions to be caught
+            // here, but they fill-in current_exception properly, so
+            // at worst the output should be a little weird, instead of
+            // causing a crash.
+            if (std::current_exception() == nullptr) {
+                return "Non C++ exception. Possibly a CLR exception.";
+            }
+            return tryTranslators();
+#endif
+        }
+        catch( TestFailureException& ) {
+            std::rethrow_exception(std::current_exception());
+        }
+        catch( std::exception& ex ) {
+            return ex.what();
+        }
+        catch( std::string& msg ) {
+            return msg;
+        }
+        catch( const char* msg ) {
+            return msg;
+        }
+        catch(...) {
+            return "Unknown exception";
+        }
+    }
+
+    std::string ExceptionTranslatorRegistry::tryTranslators() const {
+        if (m_translators.empty()) {
+            std::rethrow_exception(std::current_exception());
+        } else {
+            return m_translators[0]->translate(m_translators.begin() + 1, m_translators.end());
+        }
+    }
+
+#else // ^^ Exceptions are enabled // Exceptions are disabled vv
+    std::string ExceptionTranslatorRegistry::translateActiveException() const {
+        CATCH_INTERNAL_ERROR("Attempted to translate active exception under CATCH_CONFIG_DISABLE_EXCEPTIONS!");
+    }
+
+    std::string ExceptionTranslatorRegistry::tryTranslators() const {
+        CATCH_INTERNAL_ERROR("Attempted to use exception translators under CATCH_CONFIG_DISABLE_EXCEPTIONS!");
+    }
+#endif
+
+}
+// end catch_exception_translator_registry.cpp
+// start catch_fatal_condition.cpp
+
+#include <algorithm>
+
+#if !defined( CATCH_CONFIG_WINDOWS_SEH ) && !defined( CATCH_CONFIG_POSIX_SIGNALS )
+
+namespace Catch {
+
+    // If neither SEH nor signal handling is required, the handler impls
+    // do not have to do anything, and can be empty.
+    void FatalConditionHandler::engage_platform() {}
+    void FatalConditionHandler::disengage_platform() {}
+    FatalConditionHandler::FatalConditionHandler() = default;
+    FatalConditionHandler::~FatalConditionHandler() = default;
+
+} // end namespace Catch
+
+#endif // !CATCH_CONFIG_WINDOWS_SEH && !CATCH_CONFIG_POSIX_SIGNALS
+
+#if defined( CATCH_CONFIG_WINDOWS_SEH ) && defined( CATCH_CONFIG_POSIX_SIGNALS )
+#error "Inconsistent configuration: Windows' SEH handling and POSIX signals cannot be enabled at the same time"
+#endif // CATCH_CONFIG_WINDOWS_SEH && CATCH_CONFIG_POSIX_SIGNALS
+
+#if defined( CATCH_CONFIG_WINDOWS_SEH ) || defined( CATCH_CONFIG_POSIX_SIGNALS )
+
+namespace {
+    //! Signals fatal error message to the run context
+    void reportFatal( char const * const message ) {
+        Catch::getCurrentContext().getResultCapture()->handleFatalErrorCondition( message );
+    }
+
+    //! Minimal size Catch2 needs for its own fatal error handling.
+    //! Picked anecdotally, so it might not be sufficient on all
+    //! platforms, and for all configurations.
+    constexpr std::size_t minStackSizeForErrors = 32 * 1024;
+} // end unnamed namespace
+
+#endif // CATCH_CONFIG_WINDOWS_SEH || CATCH_CONFIG_POSIX_SIGNALS
+
+#if defined( CATCH_CONFIG_WINDOWS_SEH )
+
+namespace Catch {
+
+    struct SignalDefs { DWORD id; const char* name; };
+
+    // There is no 1-1 mapping between signals and windows exceptions.
+    // Windows can easily distinguish between SO and SigSegV,
+    // but SigInt, SigTerm, etc are handled differently.
+    static SignalDefs signalDefs[] = {
+        { static_cast<DWORD>(EXCEPTION_ILLEGAL_INSTRUCTION),  "SIGILL - Illegal instruction signal" },
+        { static_cast<DWORD>(EXCEPTION_STACK_OVERFLOW), "SIGSEGV - Stack overflow" },
+        { static_cast<DWORD>(EXCEPTION_ACCESS_VIOLATION), "SIGSEGV - Segmentation violation signal" },
+        { static_cast<DWORD>(EXCEPTION_INT_DIVIDE_BY_ZERO), "Divide by zero error" },
+    };
+
+    static LONG CALLBACK handleVectoredException(PEXCEPTION_POINTERS ExceptionInfo) {
+        for (auto const& def : signalDefs) {
+            if (ExceptionInfo->ExceptionRecord->ExceptionCode == def.id) {
+                reportFatal(def.name);
+            }
+        }
+        // If its not an exception we care about, pass it along.
+        // This stops us from eating debugger breaks etc.
+        return EXCEPTION_CONTINUE_SEARCH;
+    }
+
+    // Since we do not support multiple instantiations, we put these
+    // into global variables and rely on cleaning them up in outlined
+    // constructors/destructors
+    static PVOID exceptionHandlerHandle = nullptr;
+
+    // For MSVC, we reserve part of the stack memory for handling
+    // memory overflow structured exception.
+    FatalConditionHandler::FatalConditionHandler() {
+        ULONG guaranteeSize = static_cast<ULONG>(minStackSizeForErrors);
+        if (!SetThreadStackGuarantee(&guaranteeSize)) {
+            // We do not want to fully error out, because needing
+            // the stack reserve should be rare enough anyway.
+            Catch::cerr()
+                << "Failed to reserve piece of stack."
+                << " Stack overflows will not be reported successfully.";
+        }
+    }
+
+    // We do not attempt to unset the stack guarantee, because
+    // Windows does not support lowering the stack size guarantee.
+    FatalConditionHandler::~FatalConditionHandler() = default;
+
+    void FatalConditionHandler::engage_platform() {
+        // Register as first handler in current chain
+        exceptionHandlerHandle = AddVectoredExceptionHandler(1, handleVectoredException);
+        if (!exceptionHandlerHandle) {
+            CATCH_RUNTIME_ERROR("Could not register vectored exception handler");
+        }
+    }
+
+    void FatalConditionHandler::disengage_platform() {
+        if (!RemoveVectoredExceptionHandler(exceptionHandlerHandle)) {
+            CATCH_RUNTIME_ERROR("Could not unregister vectored exception handler");
+        }
+        exceptionHandlerHandle = nullptr;
+    }
+
+} // end namespace Catch
+
+#endif // CATCH_CONFIG_WINDOWS_SEH
+
+#if defined( CATCH_CONFIG_POSIX_SIGNALS )
+
+#include <signal.h>
+
+namespace Catch {
+
+    struct SignalDefs {
+        int id;
+        const char* name;
+    };
+
+    static SignalDefs signalDefs[] = {
+        { SIGINT,  "SIGINT - Terminal interrupt signal" },
+        { SIGILL,  "SIGILL - Illegal instruction signal" },
+        { SIGFPE,  "SIGFPE - Floating point error signal" },
+        { SIGSEGV, "SIGSEGV - Segmentation violation signal" },
+        { SIGTERM, "SIGTERM - Termination request signal" },
+        { SIGABRT, "SIGABRT - Abort (abnormal termination) signal" }
+    };
+
+// Older GCCs trigger -Wmissing-field-initializers for T foo = {}
+// which is zero initialization, but not explicit. We want to avoid
+// that.
+#if defined(__GNUC__)
+#    pragma GCC diagnostic push
+#    pragma GCC diagnostic ignored "-Wmissing-field-initializers"
+#endif
+
+    static char* altStackMem = nullptr;
+    static std::size_t altStackSize = 0;
+    static stack_t oldSigStack{};
+    static struct sigaction oldSigActions[sizeof(signalDefs) / sizeof(SignalDefs)]{};
+
+    static void restorePreviousSignalHandlers() {
+        // We set signal handlers back to the previous ones. Hopefully
+        // nobody overwrote them in the meantime, and doesn't expect
+        // their signal handlers to live past ours given that they
+        // installed them after ours..
+        for (std::size_t i = 0; i < sizeof(signalDefs) / sizeof(SignalDefs); ++i) {
+            sigaction(signalDefs[i].id, &oldSigActions[i], nullptr);
+        }
+        // Return the old stack
+        sigaltstack(&oldSigStack, nullptr);
+    }
+
+    static void handleSignal( int sig ) {
+        char const * name = "<unknown signal>";
+        for (auto const& def : signalDefs) {
+            if (sig == def.id) {
+                name = def.name;
+                break;
+            }
+        }
+        // We need to restore previous signal handlers and let them do
+        // their thing, so that the users can have the debugger break
+        // when a signal is raised, and so on.
+        restorePreviousSignalHandlers();
+        reportFatal( name );
+        raise( sig );
+    }
+
+    FatalConditionHandler::FatalConditionHandler() {
+        assert(!altStackMem && "Cannot initialize POSIX signal handler when one already exists");
+        if (altStackSize == 0) {
+            altStackSize = std::max(static_cast<size_t>(SIGSTKSZ), minStackSizeForErrors);
+        }
+        altStackMem = new char[altStackSize]();
+    }
+
+    FatalConditionHandler::~FatalConditionHandler() {
+        delete[] altStackMem;
+        // We signal that another instance can be constructed by zeroing
+        // out the pointer.
+        altStackMem = nullptr;
+    }
+
+    void FatalConditionHandler::engage_platform() {
+        stack_t sigStack;
+        sigStack.ss_sp = altStackMem;
+        sigStack.ss_size = altStackSize;
+        sigStack.ss_flags = 0;
+        sigaltstack(&sigStack, &oldSigStack);
+        struct sigaction sa = { };
+
+        sa.sa_handler = handleSignal;
+        sa.sa_flags = SA_ONSTACK;
+        for (std::size_t i = 0; i < sizeof(signalDefs)/sizeof(SignalDefs); ++i) {
+            sigaction(signalDefs[i].id, &sa, &oldSigActions[i]);
+        }
+    }
+
+#if defined(__GNUC__)
+#    pragma GCC diagnostic pop
+#endif
+
+    void FatalConditionHandler::disengage_platform() {
+        restorePreviousSignalHandlers();
+    }
+
+} // end namespace Catch
+
+#endif // CATCH_CONFIG_POSIX_SIGNALS
+// end catch_fatal_condition.cpp
+// start catch_generators.cpp
+
+#include <limits>
+#include <set>
+
+namespace Catch {
+
+IGeneratorTracker::~IGeneratorTracker() {}
+
+const char* GeneratorException::what() const noexcept {
+    return m_msg;
+}
+
+namespace Generators {
+
+    GeneratorUntypedBase::~GeneratorUntypedBase() {}
+
+    auto acquireGeneratorTracker( StringRef generatorName, SourceLineInfo const& lineInfo ) -> IGeneratorTracker& {
+        return getResultCapture().acquireGeneratorTracker( generatorName, lineInfo );
+    }
+
+} // namespace Generators
+} // namespace Catch
+// end catch_generators.cpp
+// start catch_interfaces_capture.cpp
+
+namespace Catch {
+    IResultCapture::~IResultCapture() = default;
+}
+// end catch_interfaces_capture.cpp
+// start catch_interfaces_config.cpp
+
+namespace Catch {
+    IConfig::~IConfig() = default;
+}
+// end catch_interfaces_config.cpp
+// start catch_interfaces_exception.cpp
+
+namespace Catch {
+    IExceptionTranslator::~IExceptionTranslator() = default;
+    IExceptionTranslatorRegistry::~IExceptionTranslatorRegistry() = default;
+}
+// end catch_interfaces_exception.cpp
+// start catch_interfaces_registry_hub.cpp
+
+namespace Catch {
+    IRegistryHub::~IRegistryHub() = default;
+    IMutableRegistryHub::~IMutableRegistryHub() = default;
+}
+// end catch_interfaces_registry_hub.cpp
+// start catch_interfaces_reporter.cpp
+
+// start catch_reporter_listening.h
+
+namespace Catch {
+
+    class ListeningReporter : public IStreamingReporter {
+        using Reporters = std::vector<IStreamingReporterPtr>;
+        Reporters m_listeners;
+        IStreamingReporterPtr m_reporter = nullptr;
+        ReporterPreferences m_preferences;
+
+    public:
+        ListeningReporter();
+
+        void addListener( IStreamingReporterPtr&& listener );
+        void addReporter( IStreamingReporterPtr&& reporter );
+
+    public: // IStreamingReporter
+
+        ReporterPreferences getPreferences() const override;
+
+        void noMatchingTestCases( std::string const& spec ) override;
+
+        void reportInvalidArguments(std::string const&arg) override;
+
+        static std::set<Verbosity> getSupportedVerbosities();
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+        void benchmarkPreparing(std::string const& name) override;
+        void benchmarkStarting( BenchmarkInfo const& benchmarkInfo ) override;
+        void benchmarkEnded( BenchmarkStats<> const& benchmarkStats ) override;
+        void benchmarkFailed(std::string const&) override;
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+        void testRunStarting( TestRunInfo const& testRunInfo ) override;
+        void testGroupStarting( GroupInfo const& groupInfo ) override;
+        void testCaseStarting( TestCaseInfo const& testInfo ) override;
+        void sectionStarting( SectionInfo const& sectionInfo ) override;
+        void assertionStarting( AssertionInfo const& assertionInfo ) override;
+
+        // The return value indicates if the messages buffer should be cleared:
+        bool assertionEnded( AssertionStats const& assertionStats ) override;
+        void sectionEnded( SectionStats const& sectionStats ) override;
+        void testCaseEnded( TestCaseStats const& testCaseStats ) override;
+        void testGroupEnded( TestGroupStats const& testGroupStats ) override;
+        void testRunEnded( TestRunStats const& testRunStats ) override;
+
+        void skipTest( TestCaseInfo const& testInfo ) override;
+        bool isMulti() const override;
+
+    };
+
+} // end namespace Catch
+
+// end catch_reporter_listening.h
+namespace Catch {
+
+    ReporterConfig::ReporterConfig( IConfigPtr const& _fullConfig )
+    :   m_stream( &_fullConfig->stream() ), m_fullConfig( _fullConfig ) {}
+
+    ReporterConfig::ReporterConfig( IConfigPtr const& _fullConfig, std::ostream& _stream )
+    :   m_stream( &_stream ), m_fullConfig( _fullConfig ) {}
+
+    std::ostream& ReporterConfig::stream() const { return *m_stream; }
+    IConfigPtr ReporterConfig::fullConfig() const { return m_fullConfig; }
+
+    TestRunInfo::TestRunInfo( std::string const& _name ) : name( _name ) {}
+
+    GroupInfo::GroupInfo(  std::string const& _name,
+                           std::size_t _groupIndex,
+                           std::size_t _groupsCount )
+    :   name( _name ),
+        groupIndex( _groupIndex ),
+        groupsCounts( _groupsCount )
+    {}
+
+     AssertionStats::AssertionStats( AssertionResult const& _assertionResult,
+                                     std::vector<MessageInfo> const& _infoMessages,
+                                     Totals const& _totals )
+    :   assertionResult( _assertionResult ),
+        infoMessages( _infoMessages ),
+        totals( _totals )
+    {
+        assertionResult.m_resultData.lazyExpression.m_transientExpression = _assertionResult.m_resultData.lazyExpression.m_transientExpression;
+
+        if( assertionResult.hasMessage() ) {
+            // Copy message into messages list.
+            // !TBD This should have been done earlier, somewhere
+            MessageBuilder builder( assertionResult.getTestMacroName(), assertionResult.getSourceInfo(), assertionResult.getResultType() );
+            builder << assertionResult.getMessage();
+            builder.m_info.message = builder.m_stream.str();
+
+            infoMessages.push_back( builder.m_info );
+        }
+    }
+
+     AssertionStats::~AssertionStats() = default;
+
+    SectionStats::SectionStats(  SectionInfo const& _sectionInfo,
+                                 Counts const& _assertions,
+                                 double _durationInSeconds,
+                                 bool _missingAssertions )
+    :   sectionInfo( _sectionInfo ),
+        assertions( _assertions ),
+        durationInSeconds( _durationInSeconds ),
+        missingAssertions( _missingAssertions )
+    {}
+
+    SectionStats::~SectionStats() = default;
+
+    TestCaseStats::TestCaseStats(  TestCaseInfo const& _testInfo,
+                                   Totals const& _totals,
+                                   std::string const& _stdOut,
+                                   std::string const& _stdErr,
+                                   bool _aborting )
+    : testInfo( _testInfo ),
+        totals( _totals ),
+        stdOut( _stdOut ),
+        stdErr( _stdErr ),
+        aborting( _aborting )
+    {}
+
+    TestCaseStats::~TestCaseStats() = default;
+
+    TestGroupStats::TestGroupStats( GroupInfo const& _groupInfo,
+                                    Totals const& _totals,
+                                    bool _aborting )
+    :   groupInfo( _groupInfo ),
+        totals( _totals ),
+        aborting( _aborting )
+    {}
+
+    TestGroupStats::TestGroupStats( GroupInfo const& _groupInfo )
+    :   groupInfo( _groupInfo ),
+        aborting( false )
+    {}
+
+    TestGroupStats::~TestGroupStats() = default;
+
+    TestRunStats::TestRunStats(   TestRunInfo const& _runInfo,
+                    Totals const& _totals,
+                    bool _aborting )
+    :   runInfo( _runInfo ),
+        totals( _totals ),
+        aborting( _aborting )
+    {}
+
+    TestRunStats::~TestRunStats() = default;
+
+    void IStreamingReporter::fatalErrorEncountered( StringRef ) {}
+    bool IStreamingReporter::isMulti() const { return false; }
+
+    IReporterFactory::~IReporterFactory() = default;
+    IReporterRegistry::~IReporterRegistry() = default;
+
+} // end namespace Catch
+// end catch_interfaces_reporter.cpp
+// start catch_interfaces_runner.cpp
+
+namespace Catch {
+    IRunner::~IRunner() = default;
+}
+// end catch_interfaces_runner.cpp
+// start catch_interfaces_testcase.cpp
+
+namespace Catch {
+    ITestInvoker::~ITestInvoker() = default;
+    ITestCaseRegistry::~ITestCaseRegistry() = default;
+}
+// end catch_interfaces_testcase.cpp
+// start catch_leak_detector.cpp
+
+#ifdef CATCH_CONFIG_WINDOWS_CRTDBG
+#include <crtdbg.h>
+
+namespace Catch {
+
+    LeakDetector::LeakDetector() {
+        int flag = _CrtSetDbgFlag(_CRTDBG_REPORT_FLAG);
+        flag |= _CRTDBG_LEAK_CHECK_DF;
+        flag |= _CRTDBG_ALLOC_MEM_DF;
+        _CrtSetDbgFlag(flag);
+        _CrtSetReportMode(_CRT_WARN, _CRTDBG_MODE_FILE | _CRTDBG_MODE_DEBUG);
+        _CrtSetReportFile(_CRT_WARN, _CRTDBG_FILE_STDERR);
+        // Change this to leaking allocation's number to break there
+        _CrtSetBreakAlloc(-1);
+    }
+}
+
+#else
+
+    Catch::LeakDetector::LeakDetector() {}
+
+#endif
+
+Catch::LeakDetector::~LeakDetector() {
+    Catch::cleanUp();
+}
+// end catch_leak_detector.cpp
+// start catch_list.cpp
+
+// start catch_list.h
+
+#include <set>
+
+namespace Catch {
+
+    std::size_t listTests( Config const& config );
+
+    std::size_t listTestsNamesOnly( Config const& config );
+
+    struct TagInfo {
+        void add( std::string const& spelling );
+        std::string all() const;
+
+        std::set<std::string> spellings;
+        std::size_t count = 0;
+    };
+
+    std::size_t listTags( Config const& config );
+
+    std::size_t listReporters();
+
+    Option<std::size_t> list( std::shared_ptr<Config> const& config );
+
+} // end namespace Catch
+
+// end catch_list.h
+// start catch_text.h
+
+namespace Catch {
+    using namespace clara::TextFlow;
+}
+
+// end catch_text.h
+#include <limits>
+#include <algorithm>
+#include <iomanip>
+
+namespace Catch {
+
+    std::size_t listTests( Config const& config ) {
+        TestSpec const& testSpec = config.testSpec();
+        if( config.hasTestFilters() )
+            Catch::cout() << "Matching test cases:\n";
+        else {
+            Catch::cout() << "All available test cases:\n";
+        }
+
+        auto matchedTestCases = filterTests( getAllTestCasesSorted( config ), testSpec, config );
+        for( auto const& testCaseInfo : matchedTestCases ) {
+            Colour::Code colour = testCaseInfo.isHidden()
+                ? Colour::SecondaryText
+                : Colour::None;
+            Colour colourGuard( colour );
+
+            Catch::cout() << Column( testCaseInfo.name ).initialIndent( 2 ).indent( 4 ) << "\n";
+            if( config.verbosity() >= Verbosity::High ) {
+                Catch::cout() << Column( Catch::Detail::stringify( testCaseInfo.lineInfo ) ).indent(4) << std::endl;
+                std::string description = testCaseInfo.description;
+                if( description.empty() )
+                    description = "(NO DESCRIPTION)";
+                Catch::cout() << Column( description ).indent(4) << std::endl;
+            }
+            if( !testCaseInfo.tags.empty() )
+                Catch::cout() << Column( testCaseInfo.tagsAsString() ).indent( 6 ) << "\n";
+        }
+
+        if( !config.hasTestFilters() )
+            Catch::cout() << pluralise( matchedTestCases.size(), "test case" ) << '\n' << std::endl;
+        else
+            Catch::cout() << pluralise( matchedTestCases.size(), "matching test case" ) << '\n' << std::endl;
+        return matchedTestCases.size();
+    }
+
+    std::size_t listTestsNamesOnly( Config const& config ) {
+        TestSpec const& testSpec = config.testSpec();
+        std::size_t matchedTests = 0;
+        std::vector<TestCase> matchedTestCases = filterTests( getAllTestCasesSorted( config ), testSpec, config );
+        for( auto const& testCaseInfo : matchedTestCases ) {
+            matchedTests++;
+            if( startsWith( testCaseInfo.name, '#' ) )
+               Catch::cout() << '"' << testCaseInfo.name << '"';
+            else
+               Catch::cout() << testCaseInfo.name;
+            if ( config.verbosity() >= Verbosity::High )
+                Catch::cout() << "\t@" << testCaseInfo.lineInfo;
+            Catch::cout() << std::endl;
+        }
+        return matchedTests;
+    }
+
+    void TagInfo::add( std::string const& spelling ) {
+        ++count;
+        spellings.insert( spelling );
+    }
+
+    std::string TagInfo::all() const {
+        size_t size = 0;
+        for (auto const& spelling : spellings) {
+            // Add 2 for the brackes
+            size += spelling.size() + 2;
+        }
+
+        std::string out; out.reserve(size);
+        for (auto const& spelling : spellings) {
+            out += '[';
+            out += spelling;
+            out += ']';
+        }
+        return out;
+    }
+
+    std::size_t listTags( Config const& config ) {
+        TestSpec const& testSpec = config.testSpec();
+        if( config.hasTestFilters() )
+            Catch::cout() << "Tags for matching test cases:\n";
+        else {
+            Catch::cout() << "All available tags:\n";
+        }
+
+        std::map<std::string, TagInfo> tagCounts;
+
+        std::vector<TestCase> matchedTestCases = filterTests( getAllTestCasesSorted( config ), testSpec, config );
+        for( auto const& testCase : matchedTestCases ) {
+            for( auto const& tagName : testCase.getTestCaseInfo().tags ) {
+                std::string lcaseTagName = toLower( tagName );
+                auto countIt = tagCounts.find( lcaseTagName );
+                if( countIt == tagCounts.end() )
+                    countIt = tagCounts.insert( std::make_pair( lcaseTagName, TagInfo() ) ).first;
+                countIt->second.add( tagName );
+            }
+        }
+
+        for( auto const& tagCount : tagCounts ) {
+            ReusableStringStream rss;
+            rss << "  " << std::setw(2) << tagCount.second.count << "  ";
+            auto str = rss.str();
+            auto wrapper = Column( tagCount.second.all() )
+                                                    .initialIndent( 0 )
+                                                    .indent( str.size() )
+                                                    .width( CATCH_CONFIG_CONSOLE_WIDTH-10 );
+            Catch::cout() << str << wrapper << '\n';
+        }
+        Catch::cout() << pluralise( tagCounts.size(), "tag" ) << '\n' << std::endl;
+        return tagCounts.size();
+    }
+
+    std::size_t listReporters() {
+        Catch::cout() << "Available reporters:\n";
+        IReporterRegistry::FactoryMap const& factories = getRegistryHub().getReporterRegistry().getFactories();
+        std::size_t maxNameLen = 0;
+        for( auto const& factoryKvp : factories )
+            maxNameLen = (std::max)( maxNameLen, factoryKvp.first.size() );
+
+        for( auto const& factoryKvp : factories ) {
+            Catch::cout()
+                    << Column( factoryKvp.first + ":" )
+                            .indent(2)
+                            .width( 5+maxNameLen )
+                    +  Column( factoryKvp.second->getDescription() )
+                            .initialIndent(0)
+                            .indent(2)
+                            .width( CATCH_CONFIG_CONSOLE_WIDTH - maxNameLen-8 )
+                    << "\n";
+        }
+        Catch::cout() << std::endl;
+        return factories.size();
+    }
+
+    Option<std::size_t> list( std::shared_ptr<Config> const& config ) {
+        Option<std::size_t> listedCount;
+        getCurrentMutableContext().setConfig( config );
+        if( config->listTests() )
+            listedCount = listedCount.valueOr(0) + listTests( *config );
+        if( config->listTestNamesOnly() )
+            listedCount = listedCount.valueOr(0) + listTestsNamesOnly( *config );
+        if( config->listTags() )
+            listedCount = listedCount.valueOr(0) + listTags( *config );
+        if( config->listReporters() )
+            listedCount = listedCount.valueOr(0) + listReporters();
+        return listedCount;
+    }
+
+} // end namespace Catch
+// end catch_list.cpp
+// start catch_matchers.cpp
+
+namespace Catch {
+namespace Matchers {
+    namespace Impl {
+
+        std::string MatcherUntypedBase::toString() const {
+            if( m_cachedToString.empty() )
+                m_cachedToString = describe();
+            return m_cachedToString;
+        }
+
+        MatcherUntypedBase::~MatcherUntypedBase() = default;
+
+    } // namespace Impl
+} // namespace Matchers
+
+using namespace Matchers;
+using Matchers::Impl::MatcherBase;
+
+} // namespace Catch
+// end catch_matchers.cpp
+// start catch_matchers_exception.cpp
+
+namespace Catch {
+namespace Matchers {
+namespace Exception {
+
+bool ExceptionMessageMatcher::match(std::exception const& ex) const {
+    return ex.what() == m_message;
+}
+
+std::string ExceptionMessageMatcher::describe() const {
+    return "exception message matches \"" + m_message + "\"";
+}
+
+}
+Exception::ExceptionMessageMatcher Message(std::string const& message) {
+    return Exception::ExceptionMessageMatcher(message);
+}
+
+// namespace Exception
+} // namespace Matchers
+} // namespace Catch
+// end catch_matchers_exception.cpp
+// start catch_matchers_floating.cpp
+
+// start catch_polyfills.hpp
+
+namespace Catch {
+    bool isnan(float f);
+    bool isnan(double d);
+}
+
+// end catch_polyfills.hpp
+// start catch_to_string.hpp
+
+#include <string>
+
+namespace Catch {
+    template <typename T>
+    std::string to_string(T const& t) {
+#if defined(CATCH_CONFIG_CPP11_TO_STRING)
+        return std::to_string(t);
+#else
+        ReusableStringStream rss;
+        rss << t;
+        return rss.str();
+#endif
+    }
+} // end namespace Catch
+
+// end catch_to_string.hpp
+#include <algorithm>
+#include <cmath>
+#include <cstdlib>
+#include <cstdint>
+#include <cstring>
+#include <sstream>
+#include <type_traits>
+#include <iomanip>
+#include <limits>
+
+namespace Catch {
+namespace {
+
+    int32_t convert(float f) {
+        static_assert(sizeof(float) == sizeof(int32_t), "Important ULP matcher assumption violated");
+        int32_t i;
+        std::memcpy(&i, &f, sizeof(f));
+        return i;
+    }
+
+    int64_t convert(double d) {
+        static_assert(sizeof(double) == sizeof(int64_t), "Important ULP matcher assumption violated");
+        int64_t i;
+        std::memcpy(&i, &d, sizeof(d));
+        return i;
+    }
+
+    template <typename FP>
+    bool almostEqualUlps(FP lhs, FP rhs, uint64_t maxUlpDiff) {
+        // Comparison with NaN should always be false.
+        // This way we can rule it out before getting into the ugly details
+        if (Catch::isnan(lhs) || Catch::isnan(rhs)) {
+            return false;
+        }
+
+        auto lc = convert(lhs);
+        auto rc = convert(rhs);
+
+        if ((lc < 0) != (rc < 0)) {
+            // Potentially we can have +0 and -0
+            return lhs == rhs;
+        }
+
+        // static cast as a workaround for IBM XLC
+        auto ulpDiff = std::abs(static_cast<FP>(lc - rc));
+        return static_cast<uint64_t>(ulpDiff) <= maxUlpDiff;
+    }
+
+#if defined(CATCH_CONFIG_GLOBAL_NEXTAFTER)
+
+    float nextafter(float x, float y) {
+        return ::nextafterf(x, y);
+    }
+
+    double nextafter(double x, double y) {
+        return ::nextafter(x, y);
+    }
+
+#endif // ^^^ CATCH_CONFIG_GLOBAL_NEXTAFTER ^^^
+
+template <typename FP>
+FP step(FP start, FP direction, uint64_t steps) {
+    for (uint64_t i = 0; i < steps; ++i) {
+#if defined(CATCH_CONFIG_GLOBAL_NEXTAFTER)
+        start = Catch::nextafter(start, direction);
+#else
+        start = std::nextafter(start, direction);
+#endif
+    }
+    return start;
+}
+
+// Performs equivalent check of std::fabs(lhs - rhs) <= margin
+// But without the subtraction to allow for INFINITY in comparison
+bool marginComparison(double lhs, double rhs, double margin) {
+    return (lhs + margin >= rhs) && (rhs + margin >= lhs);
+}
+
+template <typename FloatingPoint>
+void write(std::ostream& out, FloatingPoint num) {
+    out << std::scientific
+        << std::setprecision(std::numeric_limits<FloatingPoint>::max_digits10 - 1)
+        << num;
+}
+
+} // end anonymous namespace
+
+namespace Matchers {
+namespace Floating {
+
+    enum class FloatingPointKind : uint8_t {
+        Float,
+        Double
+    };
+
+    WithinAbsMatcher::WithinAbsMatcher(double target, double margin)
+        :m_target{ target }, m_margin{ margin } {
+        CATCH_ENFORCE(margin >= 0, "Invalid margin: " << margin << '.'
+            << " Margin has to be non-negative.");
+    }
+
+    // Performs equivalent check of std::fabs(lhs - rhs) <= margin
+    // But without the subtraction to allow for INFINITY in comparison
+    bool WithinAbsMatcher::match(double const& matchee) const {
+        return (matchee + m_margin >= m_target) && (m_target + m_margin >= matchee);
+    }
+
+    std::string WithinAbsMatcher::describe() const {
+        return "is within " + ::Catch::Detail::stringify(m_margin) + " of " + ::Catch::Detail::stringify(m_target);
+    }
+
+    WithinUlpsMatcher::WithinUlpsMatcher(double target, uint64_t ulps, FloatingPointKind baseType)
+        :m_target{ target }, m_ulps{ ulps }, m_type{ baseType } {
+        CATCH_ENFORCE(m_type == FloatingPointKind::Double
+                   || m_ulps < (std::numeric_limits<uint32_t>::max)(),
+            "Provided ULP is impossibly large for a float comparison.");
+    }
+
+#if defined(__clang__)
+#pragma clang diagnostic push
+// Clang <3.5 reports on the default branch in the switch below
+#pragma clang diagnostic ignored "-Wunreachable-code"
+#endif
+
+    bool WithinUlpsMatcher::match(double const& matchee) const {
+        switch (m_type) {
+        case FloatingPointKind::Float:
+            return almostEqualUlps<float>(static_cast<float>(matchee), static_cast<float>(m_target), m_ulps);
+        case FloatingPointKind::Double:
+            return almostEqualUlps<double>(matchee, m_target, m_ulps);
+        default:
+            CATCH_INTERNAL_ERROR( "Unknown FloatingPointKind value" );
+        }
+    }
+
+#if defined(__clang__)
+#pragma clang diagnostic pop
+#endif
+
+    std::string WithinUlpsMatcher::describe() const {
+        std::stringstream ret;
+
+        ret << "is within " << m_ulps << " ULPs of ";
+
+        if (m_type == FloatingPointKind::Float) {
+            write(ret, static_cast<float>(m_target));
+            ret << 'f';
+        } else {
+            write(ret, m_target);
+        }
+
+        ret << " ([";
+        if (m_type == FloatingPointKind::Double) {
+            write(ret, step(m_target, static_cast<double>(-INFINITY), m_ulps));
+            ret << ", ";
+            write(ret, step(m_target, static_cast<double>( INFINITY), m_ulps));
+        } else {
+            // We have to cast INFINITY to float because of MinGW, see #1782
+            write(ret, step(static_cast<float>(m_target), static_cast<float>(-INFINITY), m_ulps));
+            ret << ", ";
+            write(ret, step(static_cast<float>(m_target), static_cast<float>( INFINITY), m_ulps));
+        }
+        ret << "])";
+
+        return ret.str();
+    }
+
+    WithinRelMatcher::WithinRelMatcher(double target, double epsilon):
+        m_target(target),
+        m_epsilon(epsilon){
+        CATCH_ENFORCE(m_epsilon >= 0., "Relative comparison with epsilon <  0 does not make sense.");
+        CATCH_ENFORCE(m_epsilon  < 1., "Relative comparison with epsilon >= 1 does not make sense.");
+    }
+
+    bool WithinRelMatcher::match(double const& matchee) const {
+        const auto relMargin = m_epsilon * (std::max)(std::fabs(matchee), std::fabs(m_target));
+        return marginComparison(matchee, m_target,
+                                std::isinf(relMargin)? 0 : relMargin);
+    }
+
+    std::string WithinRelMatcher::describe() const {
+        Catch::ReusableStringStream sstr;
+        sstr << "and " << m_target << " are within " << m_epsilon * 100. << "% of each other";
+        return sstr.str();
+    }
+
+}// namespace Floating
+
+Floating::WithinUlpsMatcher WithinULP(double target, uint64_t maxUlpDiff) {
+    return Floating::WithinUlpsMatcher(target, maxUlpDiff, Floating::FloatingPointKind::Double);
+}
+
+Floating::WithinUlpsMatcher WithinULP(float target, uint64_t maxUlpDiff) {
+    return Floating::WithinUlpsMatcher(target, maxUlpDiff, Floating::FloatingPointKind::Float);
+}
+
+Floating::WithinAbsMatcher WithinAbs(double target, double margin) {
+    return Floating::WithinAbsMatcher(target, margin);
+}
+
+Floating::WithinRelMatcher WithinRel(double target, double eps) {
+    return Floating::WithinRelMatcher(target, eps);
+}
+
+Floating::WithinRelMatcher WithinRel(double target) {
+    return Floating::WithinRelMatcher(target, std::numeric_limits<double>::epsilon() * 100);
+}
+
+Floating::WithinRelMatcher WithinRel(float target, float eps) {
+    return Floating::WithinRelMatcher(target, eps);
+}
+
+Floating::WithinRelMatcher WithinRel(float target) {
+    return Floating::WithinRelMatcher(target, std::numeric_limits<float>::epsilon() * 100);
+}
+
+} // namespace Matchers
+} // namespace Catch
+// end catch_matchers_floating.cpp
+// start catch_matchers_generic.cpp
+
+std::string Catch::Matchers::Generic::Detail::finalizeDescription(const std::string& desc) {
+    if (desc.empty()) {
+        return "matches undescribed predicate";
+    } else {
+        return "matches predicate: \"" + desc + '"';
+    }
+}
+// end catch_matchers_generic.cpp
+// start catch_matchers_string.cpp
+
+#include <regex>
+
+namespace Catch {
+namespace Matchers {
+
+    namespace StdString {
+
+        CasedString::CasedString( std::string const& str, CaseSensitive::Choice caseSensitivity )
+        :   m_caseSensitivity( caseSensitivity ),
+            m_str( adjustString( str ) )
+        {}
+        std::string CasedString::adjustString( std::string const& str ) const {
+            return m_caseSensitivity == CaseSensitive::No
+                   ? toLower( str )
+                   : str;
+        }
+        std::string CasedString::caseSensitivitySuffix() const {
+            return m_caseSensitivity == CaseSensitive::No
+                   ? " (case insensitive)"
+                   : std::string();
+        }
+
+        StringMatcherBase::StringMatcherBase( std::string const& operation, CasedString const& comparator )
+        : m_comparator( comparator ),
+          m_operation( operation ) {
+        }
+
+        std::string StringMatcherBase::describe() const {
+            std::string description;
+            description.reserve(5 + m_operation.size() + m_comparator.m_str.size() +
+                                        m_comparator.caseSensitivitySuffix().size());
+            description += m_operation;
+            description += ": \"";
+            description += m_comparator.m_str;
+            description += "\"";
+            description += m_comparator.caseSensitivitySuffix();
+            return description;
+        }
+
+        EqualsMatcher::EqualsMatcher( CasedString const& comparator ) : StringMatcherBase( "equals", comparator ) {}
+
+        bool EqualsMatcher::match( std::string const& source ) const {
+            return m_comparator.adjustString( source ) == m_comparator.m_str;
+        }
+
+        ContainsMatcher::ContainsMatcher( CasedString const& comparator ) : StringMatcherBase( "contains", comparator ) {}
+
+        bool ContainsMatcher::match( std::string const& source ) const {
+            return contains( m_comparator.adjustString( source ), m_comparator.m_str );
+        }
+
+        StartsWithMatcher::StartsWithMatcher( CasedString const& comparator ) : StringMatcherBase( "starts with", comparator ) {}
+
+        bool StartsWithMatcher::match( std::string const& source ) const {
+            return startsWith( m_comparator.adjustString( source ), m_comparator.m_str );
+        }
+
+        EndsWithMatcher::EndsWithMatcher( CasedString const& comparator ) : StringMatcherBase( "ends with", comparator ) {}
+
+        bool EndsWithMatcher::match( std::string const& source ) const {
+            return endsWith( m_comparator.adjustString( source ), m_comparator.m_str );
+        }
+
+        RegexMatcher::RegexMatcher(std::string regex, CaseSensitive::Choice caseSensitivity): m_regex(std::move(regex)), m_caseSensitivity(caseSensitivity) {}
+
+        bool RegexMatcher::match(std::string const& matchee) const {
+            auto flags = std::regex::ECMAScript; // ECMAScript is the default syntax option anyway
+            if (m_caseSensitivity == CaseSensitive::Choice::No) {
+                flags |= std::regex::icase;
+            }
+            auto reg = std::regex(m_regex, flags);
+            return std::regex_match(matchee, reg);
+        }
+
+        std::string RegexMatcher::describe() const {
+            return "matches " + ::Catch::Detail::stringify(m_regex) + ((m_caseSensitivity == CaseSensitive::Choice::Yes)? " case sensitively" : " case insensitively");
+        }
+
+    } // namespace StdString
+
+    StdString::EqualsMatcher Equals( std::string const& str, CaseSensitive::Choice caseSensitivity ) {
+        return StdString::EqualsMatcher( StdString::CasedString( str, caseSensitivity) );
+    }
+    StdString::ContainsMatcher Contains( std::string const& str, CaseSensitive::Choice caseSensitivity ) {
+        return StdString::ContainsMatcher( StdString::CasedString( str, caseSensitivity) );
+    }
+    StdString::EndsWithMatcher EndsWith( std::string const& str, CaseSensitive::Choice caseSensitivity ) {
+        return StdString::EndsWithMatcher( StdString::CasedString( str, caseSensitivity) );
+    }
+    StdString::StartsWithMatcher StartsWith( std::string const& str, CaseSensitive::Choice caseSensitivity ) {
+        return StdString::StartsWithMatcher( StdString::CasedString( str, caseSensitivity) );
+    }
+
+    StdString::RegexMatcher Matches(std::string const& regex, CaseSensitive::Choice caseSensitivity) {
+        return StdString::RegexMatcher(regex, caseSensitivity);
+    }
+
+} // namespace Matchers
+} // namespace Catch
+// end catch_matchers_string.cpp
+// start catch_message.cpp
+
+// start catch_uncaught_exceptions.h
+
+namespace Catch {
+    bool uncaught_exceptions();
+} // end namespace Catch
+
+// end catch_uncaught_exceptions.h
+#include <cassert>
+#include <stack>
+
+namespace Catch {
+
+    MessageInfo::MessageInfo(   StringRef const& _macroName,
+                                SourceLineInfo const& _lineInfo,
+                                ResultWas::OfType _type )
+    :   macroName( _macroName ),
+        lineInfo( _lineInfo ),
+        type( _type ),
+        sequence( ++globalCount )
+    {}
+
+    bool MessageInfo::operator==( MessageInfo const& other ) const {
+        return sequence == other.sequence;
+    }
+
+    bool MessageInfo::operator<( MessageInfo const& other ) const {
+        return sequence < other.sequence;
+    }
+
+    // This may need protecting if threading support is added
+    unsigned int MessageInfo::globalCount = 0;
+
+    ////////////////////////////////////////////////////////////////////////////
+
+    Catch::MessageBuilder::MessageBuilder( StringRef const& macroName,
+                                           SourceLineInfo const& lineInfo,
+                                           ResultWas::OfType type )
+        :m_info(macroName, lineInfo, type) {}
+
+    ////////////////////////////////////////////////////////////////////////////
+
+    ScopedMessage::ScopedMessage( MessageBuilder const& builder )
+    : m_info( builder.m_info ), m_moved()
+    {
+        m_info.message = builder.m_stream.str();
+        getResultCapture().pushScopedMessage( m_info );
+    }
+
+    ScopedMessage::ScopedMessage( ScopedMessage&& old )
+    : m_info( old.m_info ), m_moved()
+    {
+        old.m_moved = true;
+    }
+
+    ScopedMessage::~ScopedMessage() {
+        if ( !uncaught_exceptions() && !m_moved ){
+            getResultCapture().popScopedMessage(m_info);
+        }
+    }
+
+    Capturer::Capturer( StringRef macroName, SourceLineInfo const& lineInfo, ResultWas::OfType resultType, StringRef names ) {
+        auto trimmed = [&] (size_t start, size_t end) {
+            while (names[start] == ',' || isspace(static_cast<unsigned char>(names[start]))) {
+                ++start;
+            }
+            while (names[end] == ',' || isspace(static_cast<unsigned char>(names[end]))) {
+                --end;
+            }
+            return names.substr(start, end - start + 1);
+        };
+        auto skipq = [&] (size_t start, char quote) {
+            for (auto i = start + 1; i < names.size() ; ++i) {
+                if (names[i] == quote)
+                    return i;
+                if (names[i] == '\\')
+                    ++i;
+            }
+            CATCH_INTERNAL_ERROR("CAPTURE parsing encountered unmatched quote");
+        };
+
+        size_t start = 0;
+        std::stack<char> openings;
+        for (size_t pos = 0; pos < names.size(); ++pos) {
+            char c = names[pos];
+            switch (c) {
+            case '[':
+            case '{':
+            case '(':
+            // It is basically impossible to disambiguate between
+            // comparison and start of template args in this context
+//            case '<':
+                openings.push(c);
+                break;
+            case ']':
+            case '}':
+            case ')':
+//           case '>':
+                openings.pop();
+                break;
+            case '"':
+            case '\'':
+                pos = skipq(pos, c);
+                break;
+            case ',':
+                if (start != pos && openings.empty()) {
+                    m_messages.emplace_back(macroName, lineInfo, resultType);
+                    m_messages.back().message = static_cast<std::string>(trimmed(start, pos));
+                    m_messages.back().message += " := ";
+                    start = pos;
+                }
+            }
+        }
+        assert(openings.empty() && "Mismatched openings");
+        m_messages.emplace_back(macroName, lineInfo, resultType);
+        m_messages.back().message = static_cast<std::string>(trimmed(start, names.size() - 1));
+        m_messages.back().message += " := ";
+    }
+    Capturer::~Capturer() {
+        if ( !uncaught_exceptions() ){
+            assert( m_captured == m_messages.size() );
+            for( size_t i = 0; i < m_captured; ++i  )
+                m_resultCapture.popScopedMessage( m_messages[i] );
+        }
+    }
+
+    void Capturer::captureValue( size_t index, std::string const& value ) {
+        assert( index < m_messages.size() );
+        m_messages[index].message += value;
+        m_resultCapture.pushScopedMessage( m_messages[index] );
+        m_captured++;
+    }
+
+} // end namespace Catch
+// end catch_message.cpp
+// start catch_output_redirect.cpp
+
+// start catch_output_redirect.h
+#ifndef TWOBLUECUBES_CATCH_OUTPUT_REDIRECT_H
+#define TWOBLUECUBES_CATCH_OUTPUT_REDIRECT_H
+
+#include <cstdio>
+#include <iosfwd>
+#include <string>
+
+namespace Catch {
+
+    class RedirectedStream {
+        std::ostream& m_originalStream;
+        std::ostream& m_redirectionStream;
+        std::streambuf* m_prevBuf;
+
+    public:
+        RedirectedStream( std::ostream& originalStream, std::ostream& redirectionStream );
+        ~RedirectedStream();
+    };
+
+    class RedirectedStdOut {
+        ReusableStringStream m_rss;
+        RedirectedStream m_cout;
+    public:
+        RedirectedStdOut();
+        auto str() const -> std::string;
+    };
+
+    // StdErr has two constituent streams in C++, std::cerr and std::clog
+    // This means that we need to redirect 2 streams into 1 to keep proper
+    // order of writes
+    class RedirectedStdErr {
+        ReusableStringStream m_rss;
+        RedirectedStream m_cerr;
+        RedirectedStream m_clog;
+    public:
+        RedirectedStdErr();
+        auto str() const -> std::string;
+    };
+
+    class RedirectedStreams {
+    public:
+        RedirectedStreams(RedirectedStreams const&) = delete;
+        RedirectedStreams& operator=(RedirectedStreams const&) = delete;
+        RedirectedStreams(RedirectedStreams&&) = delete;
+        RedirectedStreams& operator=(RedirectedStreams&&) = delete;
+
+        RedirectedStreams(std::string& redirectedCout, std::string& redirectedCerr);
+        ~RedirectedStreams();
+    private:
+        std::string& m_redirectedCout;
+        std::string& m_redirectedCerr;
+        RedirectedStdOut m_redirectedStdOut;
+        RedirectedStdErr m_redirectedStdErr;
+    };
+
+#if defined(CATCH_CONFIG_NEW_CAPTURE)
+
+    // Windows's implementation of std::tmpfile is terrible (it tries
+    // to create a file inside system folder, thus requiring elevated
+    // privileges for the binary), so we have to use tmpnam(_s) and
+    // create the file ourselves there.
+    class TempFile {
+    public:
+        TempFile(TempFile const&) = delete;
+        TempFile& operator=(TempFile const&) = delete;
+        TempFile(TempFile&&) = delete;
+        TempFile& operator=(TempFile&&) = delete;
+
+        TempFile();
+        ~TempFile();
+
+        std::FILE* getFile();
+        std::string getContents();
+
+    private:
+        std::FILE* m_file = nullptr;
+    #if defined(_MSC_VER)
+        char m_buffer[L_tmpnam] = { 0 };
+    #endif
+    };
+
+    class OutputRedirect {
+    public:
+        OutputRedirect(OutputRedirect const&) = delete;
+        OutputRedirect& operator=(OutputRedirect const&) = delete;
+        OutputRedirect(OutputRedirect&&) = delete;
+        OutputRedirect& operator=(OutputRedirect&&) = delete;
+
+        OutputRedirect(std::string& stdout_dest, std::string& stderr_dest);
+        ~OutputRedirect();
+
+    private:
+        int m_originalStdout = -1;
+        int m_originalStderr = -1;
+        TempFile m_stdoutFile;
+        TempFile m_stderrFile;
+        std::string& m_stdoutDest;
+        std::string& m_stderrDest;
+    };
+
+#endif
+
+} // end namespace Catch
+
+#endif // TWOBLUECUBES_CATCH_OUTPUT_REDIRECT_H
+// end catch_output_redirect.h
+#include <cstdio>
+#include <cstring>
+#include <fstream>
+#include <sstream>
+#include <stdexcept>
+
+#if defined(CATCH_CONFIG_NEW_CAPTURE)
+    #if defined(_MSC_VER)
+    #include <io.h>      //_dup and _dup2
+    #define dup _dup
+    #define dup2 _dup2
+    #define fileno _fileno
+    #else
+    #include <unistd.h>  // dup and dup2
+    #endif
+#endif
+
+namespace Catch {
+
+    RedirectedStream::RedirectedStream( std::ostream& originalStream, std::ostream& redirectionStream )
+    :   m_originalStream( originalStream ),
+        m_redirectionStream( redirectionStream ),
+        m_prevBuf( m_originalStream.rdbuf() )
+    {
+        m_originalStream.rdbuf( m_redirectionStream.rdbuf() );
+    }
+
+    RedirectedStream::~RedirectedStream() {
+        m_originalStream.rdbuf( m_prevBuf );
+    }
+
+    RedirectedStdOut::RedirectedStdOut() : m_cout( Catch::cout(), m_rss.get() ) {}
+    auto RedirectedStdOut::str() const -> std::string { return m_rss.str(); }
+
+    RedirectedStdErr::RedirectedStdErr()
+    :   m_cerr( Catch::cerr(), m_rss.get() ),
+        m_clog( Catch::clog(), m_rss.get() )
+    {}
+    auto RedirectedStdErr::str() const -> std::string { return m_rss.str(); }
+
+    RedirectedStreams::RedirectedStreams(std::string& redirectedCout, std::string& redirectedCerr)
+    :   m_redirectedCout(redirectedCout),
+        m_redirectedCerr(redirectedCerr)
+    {}
+
+    RedirectedStreams::~RedirectedStreams() {
+        m_redirectedCout += m_redirectedStdOut.str();
+        m_redirectedCerr += m_redirectedStdErr.str();
+    }
+
+#if defined(CATCH_CONFIG_NEW_CAPTURE)
+
+#if defined(_MSC_VER)
+    TempFile::TempFile() {
+        if (tmpnam_s(m_buffer)) {
+            CATCH_RUNTIME_ERROR("Could not get a temp filename");
+        }
+        if (fopen_s(&m_file, m_buffer, "w+")) {
+            char buffer[100];
+            if (strerror_s(buffer, errno)) {
+                CATCH_RUNTIME_ERROR("Could not translate errno to a string");
+            }
+            CATCH_RUNTIME_ERROR("Could not open the temp file: '" << m_buffer << "' because: " << buffer);
+        }
+    }
+#else
+    TempFile::TempFile() {
+        m_file = std::tmpfile();
+        if (!m_file) {
+            CATCH_RUNTIME_ERROR("Could not create a temp file.");
+        }
+    }
+
+#endif
+
+    TempFile::~TempFile() {
+         // TBD: What to do about errors here?
+         std::fclose(m_file);
+         // We manually create the file on Windows only, on Linux
+         // it will be autodeleted
+#if defined(_MSC_VER)
+         std::remove(m_buffer);
+#endif
+    }
+
+    FILE* TempFile::getFile() {
+        return m_file;
+    }
+
+    std::string TempFile::getContents() {
+        std::stringstream sstr;
+        char buffer[100] = {};
+        std::rewind(m_file);
+        while (std::fgets(buffer, sizeof(buffer), m_file)) {
+            sstr << buffer;
+        }
+        return sstr.str();
+    }
+
+    OutputRedirect::OutputRedirect(std::string& stdout_dest, std::string& stderr_dest) :
+        m_originalStdout(dup(1)),
+        m_originalStderr(dup(2)),
+        m_stdoutDest(stdout_dest),
+        m_stderrDest(stderr_dest) {
+        dup2(fileno(m_stdoutFile.getFile()), 1);
+        dup2(fileno(m_stderrFile.getFile()), 2);
+    }
+
+    OutputRedirect::~OutputRedirect() {
+        Catch::cout() << std::flush;
+        fflush(stdout);
+        // Since we support overriding these streams, we flush cerr
+        // even though std::cerr is unbuffered
+        Catch::cerr() << std::flush;
+        Catch::clog() << std::flush;
+        fflush(stderr);
+
+        dup2(m_originalStdout, 1);
+        dup2(m_originalStderr, 2);
+
+        m_stdoutDest += m_stdoutFile.getContents();
+        m_stderrDest += m_stderrFile.getContents();
+    }
+
+#endif // CATCH_CONFIG_NEW_CAPTURE
+
+} // namespace Catch
+
+#if defined(CATCH_CONFIG_NEW_CAPTURE)
+    #if defined(_MSC_VER)
+    #undef dup
+    #undef dup2
+    #undef fileno
+    #endif
+#endif
+// end catch_output_redirect.cpp
+// start catch_polyfills.cpp
+
+#include <cmath>
+
+namespace Catch {
+
+#if !defined(CATCH_CONFIG_POLYFILL_ISNAN)
+    bool isnan(float f) {
+        return std::isnan(f);
+    }
+    bool isnan(double d) {
+        return std::isnan(d);
+    }
+#else
+    // For now we only use this for embarcadero
+    bool isnan(float f) {
+        return std::_isnan(f);
+    }
+    bool isnan(double d) {
+        return std::_isnan(d);
+    }
+#endif
+
+} // end namespace Catch
+// end catch_polyfills.cpp
+// start catch_random_number_generator.cpp
+
+namespace Catch {
+
+namespace {
+
+#if defined(_MSC_VER)
+#pragma warning(push)
+#pragma warning(disable:4146) // we negate uint32 during the rotate
+#endif
+        // Safe rotr implementation thanks to John Regehr
+        uint32_t rotate_right(uint32_t val, uint32_t count) {
+            const uint32_t mask = 31;
+            count &= mask;
+            return (val >> count) | (val << (-count & mask));
+        }
+
+#if defined(_MSC_VER)
+#pragma warning(pop)
+#endif
+
+}
+
+    SimplePcg32::SimplePcg32(result_type seed_) {
+        seed(seed_);
+    }
+
+    void SimplePcg32::seed(result_type seed_) {
+        m_state = 0;
+        (*this)();
+        m_state += seed_;
+        (*this)();
+    }
+
+    void SimplePcg32::discard(uint64_t skip) {
+        // We could implement this to run in O(log n) steps, but this
+        // should suffice for our use case.
+        for (uint64_t s = 0; s < skip; ++s) {
+            static_cast<void>((*this)());
+        }
+    }
+
+    SimplePcg32::result_type SimplePcg32::operator()() {
+        // prepare the output value
+        const uint32_t xorshifted = static_cast<uint32_t>(((m_state >> 18u) ^ m_state) >> 27u);
+        const auto output = rotate_right(xorshifted, m_state >> 59u);
+
+        // advance state
+        m_state = m_state * 6364136223846793005ULL + s_inc;
+
+        return output;
+    }
+
+    bool operator==(SimplePcg32 const& lhs, SimplePcg32 const& rhs) {
+        return lhs.m_state == rhs.m_state;
+    }
+
+    bool operator!=(SimplePcg32 const& lhs, SimplePcg32 const& rhs) {
+        return lhs.m_state != rhs.m_state;
+    }
+}
+// end catch_random_number_generator.cpp
+// start catch_registry_hub.cpp
+
+// start catch_test_case_registry_impl.h
+
+#include <vector>
+#include <set>
+#include <algorithm>
+#include <ios>
+
+namespace Catch {
+
+    class TestCase;
+    struct IConfig;
+
+    std::vector<TestCase> sortTests( IConfig const& config, std::vector<TestCase> const& unsortedTestCases );
+
+    bool isThrowSafe( TestCase const& testCase, IConfig const& config );
+    bool matchTest( TestCase const& testCase, TestSpec const& testSpec, IConfig const& config );
+
+    void enforceNoDuplicateTestCases( std::vector<TestCase> const& functions );
+
+    std::vector<TestCase> filterTests( std::vector<TestCase> const& testCases, TestSpec const& testSpec, IConfig const& config );
+    std::vector<TestCase> const& getAllTestCasesSorted( IConfig const& config );
+
+    class TestRegistry : public ITestCaseRegistry {
+    public:
+        virtual ~TestRegistry() = default;
+
+        virtual void registerTest( TestCase const& testCase );
+
+        std::vector<TestCase> const& getAllTests() const override;
+        std::vector<TestCase> const& getAllTestsSorted( IConfig const& config ) const override;
+
+    private:
+        std::vector<TestCase> m_functions;
+        mutable RunTests::InWhatOrder m_currentSortOrder = RunTests::InDeclarationOrder;
+        mutable std::vector<TestCase> m_sortedFunctions;
+        std::size_t m_unnamedCount = 0;
+        std::ios_base::Init m_ostreamInit; // Forces cout/ cerr to be initialised
+    };
+
+    ///////////////////////////////////////////////////////////////////////////
+
+    class TestInvokerAsFunction : public ITestInvoker {
+        void(*m_testAsFunction)();
+    public:
+        TestInvokerAsFunction( void(*testAsFunction)() ) noexcept;
+
+        void invoke() const override;
+    };
+
+    std::string extractClassName( StringRef const& classOrQualifiedMethodName );
+
+    ///////////////////////////////////////////////////////////////////////////
+
+} // end namespace Catch
+
+// end catch_test_case_registry_impl.h
+// start catch_reporter_registry.h
+
+#include <map>
+
+namespace Catch {
+
+    class ReporterRegistry : public IReporterRegistry {
+
+    public:
+
+        ~ReporterRegistry() override;
+
+        IStreamingReporterPtr create( std::string const& name, IConfigPtr const& config ) const override;
+
+        void registerReporter( std::string const& name, IReporterFactoryPtr const& factory );
+        void registerListener( IReporterFactoryPtr const& factory );
+
+        FactoryMap const& getFactories() const override;
+        Listeners const& getListeners() const override;
+
+    private:
+        FactoryMap m_factories;
+        Listeners m_listeners;
+    };
+}
+
+// end catch_reporter_registry.h
+// start catch_tag_alias_registry.h
+
+// start catch_tag_alias.h
+
+#include <string>
+
+namespace Catch {
+
+    struct TagAlias {
+        TagAlias(std::string const& _tag, SourceLineInfo _lineInfo);
+
+        std::string tag;
+        SourceLineInfo lineInfo;
+    };
+
+} // end namespace Catch
+
+// end catch_tag_alias.h
+#include <map>
+
+namespace Catch {
+
+    class TagAliasRegistry : public ITagAliasRegistry {
+    public:
+        ~TagAliasRegistry() override;
+        TagAlias const* find( std::string const& alias ) const override;
+        std::string expandAliases( std::string const& unexpandedTestSpec ) const override;
+        void add( std::string const& alias, std::string const& tag, SourceLineInfo const& lineInfo );
+
+    private:
+        std::map<std::string, TagAlias> m_registry;
+    };
+
+} // end namespace Catch
+
+// end catch_tag_alias_registry.h
+// start catch_startup_exception_registry.h
+
+#include <vector>
+#include <exception>
+
+namespace Catch {
+
+    class StartupExceptionRegistry {
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+    public:
+        void add(std::exception_ptr const& exception) noexcept;
+        std::vector<std::exception_ptr> const& getExceptions() const noexcept;
+    private:
+        std::vector<std::exception_ptr> m_exceptions;
+#endif
+    };
+
+} // end namespace Catch
+
+// end catch_startup_exception_registry.h
+// start catch_singletons.hpp
+
+namespace Catch {
+
+    struct ISingleton {
+        virtual ~ISingleton();
+    };
+
+    void addSingleton( ISingleton* singleton );
+    void cleanupSingletons();
+
+    template<typename SingletonImplT, typename InterfaceT = SingletonImplT, typename MutableInterfaceT = InterfaceT>
+    class Singleton : SingletonImplT, public ISingleton {
+
+        static auto getInternal() -> Singleton* {
+            static Singleton* s_instance = nullptr;
+            if( !s_instance ) {
+                s_instance = new Singleton;
+                addSingleton( s_instance );
+            }
+            return s_instance;
+        }
+
+    public:
+        static auto get() -> InterfaceT const& {
+            return *getInternal();
+        }
+        static auto getMutable() -> MutableInterfaceT& {
+            return *getInternal();
+        }
+    };
+
+} // namespace Catch
+
+// end catch_singletons.hpp
+namespace Catch {
+
+    namespace {
+
+        class RegistryHub : public IRegistryHub, public IMutableRegistryHub,
+                            private NonCopyable {
+
+        public: // IRegistryHub
+            RegistryHub() = default;
+            IReporterRegistry const& getReporterRegistry() const override {
+                return m_reporterRegistry;
+            }
+            ITestCaseRegistry const& getTestCaseRegistry() const override {
+                return m_testCaseRegistry;
+            }
+            IExceptionTranslatorRegistry const& getExceptionTranslatorRegistry() const override {
+                return m_exceptionTranslatorRegistry;
+            }
+            ITagAliasRegistry const& getTagAliasRegistry() const override {
+                return m_tagAliasRegistry;
+            }
+            StartupExceptionRegistry const& getStartupExceptionRegistry() const override {
+                return m_exceptionRegistry;
+            }
+
+        public: // IMutableRegistryHub
+            void registerReporter( std::string const& name, IReporterFactoryPtr const& factory ) override {
+                m_reporterRegistry.registerReporter( name, factory );
+            }
+            void registerListener( IReporterFactoryPtr const& factory ) override {
+                m_reporterRegistry.registerListener( factory );
+            }
+            void registerTest( TestCase const& testInfo ) override {
+                m_testCaseRegistry.registerTest( testInfo );
+            }
+            void registerTranslator( const IExceptionTranslator* translator ) override {
+                m_exceptionTranslatorRegistry.registerTranslator( translator );
+            }
+            void registerTagAlias( std::string const& alias, std::string const& tag, SourceLineInfo const& lineInfo ) override {
+                m_tagAliasRegistry.add( alias, tag, lineInfo );
+            }
+            void registerStartupException() noexcept override {
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+                m_exceptionRegistry.add(std::current_exception());
+#else
+                CATCH_INTERNAL_ERROR("Attempted to register active exception under CATCH_CONFIG_DISABLE_EXCEPTIONS!");
+#endif
+            }
+            IMutableEnumValuesRegistry& getMutableEnumValuesRegistry() override {
+                return m_enumValuesRegistry;
+            }
+
+        private:
+            TestRegistry m_testCaseRegistry;
+            ReporterRegistry m_reporterRegistry;
+            ExceptionTranslatorRegistry m_exceptionTranslatorRegistry;
+            TagAliasRegistry m_tagAliasRegistry;
+            StartupExceptionRegistry m_exceptionRegistry;
+            Detail::EnumValuesRegistry m_enumValuesRegistry;
+        };
+    }
+
+    using RegistryHubSingleton = Singleton<RegistryHub, IRegistryHub, IMutableRegistryHub>;
+
+    IRegistryHub const& getRegistryHub() {
+        return RegistryHubSingleton::get();
+    }
+    IMutableRegistryHub& getMutableRegistryHub() {
+        return RegistryHubSingleton::getMutable();
+    }
+    void cleanUp() {
+        cleanupSingletons();
+        cleanUpContext();
+    }
+    std::string translateActiveException() {
+        return getRegistryHub().getExceptionTranslatorRegistry().translateActiveException();
+    }
+
+} // end namespace Catch
+// end catch_registry_hub.cpp
+// start catch_reporter_registry.cpp
+
+namespace Catch {
+
+    ReporterRegistry::~ReporterRegistry() = default;
+
+    IStreamingReporterPtr ReporterRegistry::create( std::string const& name, IConfigPtr const& config ) const {
+        auto it =  m_factories.find( name );
+        if( it == m_factories.end() )
+            return nullptr;
+        return it->second->create( ReporterConfig( config ) );
+    }
+
+    void ReporterRegistry::registerReporter( std::string const& name, IReporterFactoryPtr const& factory ) {
+        m_factories.emplace(name, factory);
+    }
+    void ReporterRegistry::registerListener( IReporterFactoryPtr const& factory ) {
+        m_listeners.push_back( factory );
+    }
+
+    IReporterRegistry::FactoryMap const& ReporterRegistry::getFactories() const {
+        return m_factories;
+    }
+    IReporterRegistry::Listeners const& ReporterRegistry::getListeners() const {
+        return m_listeners;
+    }
+
+}
+// end catch_reporter_registry.cpp
+// start catch_result_type.cpp
+
+namespace Catch {
+
+    bool isOk( ResultWas::OfType resultType ) {
+        return ( resultType & ResultWas::FailureBit ) == 0;
+    }
+    bool isJustInfo( int flags ) {
+        return flags == ResultWas::Info;
+    }
+
+    ResultDisposition::Flags operator | ( ResultDisposition::Flags lhs, ResultDisposition::Flags rhs ) {
+        return static_cast<ResultDisposition::Flags>( static_cast<int>( lhs ) | static_cast<int>( rhs ) );
+    }
+
+    bool shouldContinueOnFailure( int flags )    { return ( flags & ResultDisposition::ContinueOnFailure ) != 0; }
+    bool shouldSuppressFailure( int flags )      { return ( flags & ResultDisposition::SuppressFail ) != 0; }
+
+} // end namespace Catch
+// end catch_result_type.cpp
+// start catch_run_context.cpp
+
+#include <cassert>
+#include <algorithm>
+#include <sstream>
+
+namespace Catch {
+
+    namespace Generators {
+        struct GeneratorTracker : TestCaseTracking::TrackerBase, IGeneratorTracker {
+            GeneratorBasePtr m_generator;
+
+            GeneratorTracker( TestCaseTracking::NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent )
+            :   TrackerBase( nameAndLocation, ctx, parent )
+            {}
+            ~GeneratorTracker();
+
+            static GeneratorTracker& acquire( TrackerContext& ctx, TestCaseTracking::NameAndLocation const& nameAndLocation ) {
+                std::shared_ptr<GeneratorTracker> tracker;
+
+                ITracker& currentTracker = ctx.currentTracker();
+                // Under specific circumstances, the generator we want
+                // to acquire is also the current tracker. If this is
+                // the case, we have to avoid looking through current
+                // tracker's children, and instead return the current
+                // tracker.
+                // A case where this check is important is e.g.
+                //     for (int i = 0; i < 5; ++i) {
+                //         int n = GENERATE(1, 2);
+                //     }
+                //
+                // without it, the code above creates 5 nested generators.
+                if (currentTracker.nameAndLocation() == nameAndLocation) {
+                    auto thisTracker = currentTracker.parent().findChild(nameAndLocation);
+                    assert(thisTracker);
+                    assert(thisTracker->isGeneratorTracker());
+                    tracker = std::static_pointer_cast<GeneratorTracker>(thisTracker);
+                } else if ( TestCaseTracking::ITrackerPtr childTracker = currentTracker.findChild( nameAndLocation ) ) {
+                    assert( childTracker );
+                    assert( childTracker->isGeneratorTracker() );
+                    tracker = std::static_pointer_cast<GeneratorTracker>( childTracker );
+                } else {
+                    tracker = std::make_shared<GeneratorTracker>( nameAndLocation, ctx, &currentTracker );
+                    currentTracker.addChild( tracker );
+                }
+
+                if( !tracker->isComplete() ) {
+                    tracker->open();
+                }
+
+                return *tracker;
+            }
+
+            // TrackerBase interface
+            bool isGeneratorTracker() const override { return true; }
+            auto hasGenerator() const -> bool override {
+                return !!m_generator;
+            }
+            void close() override {
+                TrackerBase::close();
+                // If a generator has a child (it is followed by a section)
+                // and none of its children have started, then we must wait
+                // until later to start consuming its values.
+                // This catches cases where `GENERATE` is placed between two
+                // `SECTION`s.
+                // **The check for m_children.empty cannot be removed**.
+                // doing so would break `GENERATE` _not_ followed by `SECTION`s.
+                const bool should_wait_for_child = [&]() {
+                    // No children -> nobody to wait for
+                    if ( m_children.empty() ) {
+                        return false;
+                    }
+                    // If at least one child started executing, don't wait
+                    if ( std::find_if(
+                             m_children.begin(),
+                             m_children.end(),
+                             []( TestCaseTracking::ITrackerPtr tracker ) {
+                                 return tracker->hasStarted();
+                             } ) != m_children.end() ) {
+                        return false;
+                    }
+
+                    // No children have started. We need to check if they _can_
+                    // start, and thus we should wait for them, or they cannot
+                    // start (due to filters), and we shouldn't wait for them
+                    auto* parent = m_parent;
+                    // This is safe: there is always at least one section
+                    // tracker in a test case tracking tree
+                    while ( !parent->isSectionTracker() ) {
+                        parent = &( parent->parent() );
+                    }
+                    assert( parent &&
+                            "Missing root (test case) level section" );
+
+                    auto const& parentSection =
+                        static_cast<SectionTracker&>( *parent );
+                    auto const& filters = parentSection.getFilters();
+                    // No filters -> no restrictions on running sections
+                    if ( filters.empty() ) {
+                        return true;
+                    }
+
+                    for ( auto const& child : m_children ) {
+                        if ( child->isSectionTracker() &&
+                             std::find( filters.begin(),
+                                        filters.end(),
+                                        static_cast<SectionTracker&>( *child )
+                                            .trimmedName() ) !=
+                                 filters.end() ) {
+                            return true;
+                        }
+                    }
+                    return false;
+                }();
+
+                // This check is a bit tricky, because m_generator->next()
+                // has a side-effect, where it consumes generator's current
+                // value, but we do not want to invoke the side-effect if
+                // this generator is still waiting for any child to start.
+                if ( should_wait_for_child ||
+                     ( m_runState == CompletedSuccessfully &&
+                       m_generator->next() ) ) {
+                    m_children.clear();
+                    m_runState = Executing;
+                }
+            }
+
+            // IGeneratorTracker interface
+            auto getGenerator() const -> GeneratorBasePtr const& override {
+                return m_generator;
+            }
+            void setGenerator( GeneratorBasePtr&& generator ) override {
+                m_generator = std::move( generator );
+            }
+        };
+        GeneratorTracker::~GeneratorTracker() {}
+    }
+
+    RunContext::RunContext(IConfigPtr const& _config, IStreamingReporterPtr&& reporter)
+    :   m_runInfo(_config->name()),
+        m_context(getCurrentMutableContext()),
+        m_config(_config),
+        m_reporter(std::move(reporter)),
+        m_lastAssertionInfo{ StringRef(), SourceLineInfo("",0), StringRef(), ResultDisposition::Normal },
+        m_includeSuccessfulResults( m_config->includeSuccessfulResults() || m_reporter->getPreferences().shouldReportAllAssertions )
+    {
+        m_context.setRunner(this);
+        m_context.setConfig(m_config);
+        m_context.setResultCapture(this);
+        m_reporter->testRunStarting(m_runInfo);
+    }
+
+    RunContext::~RunContext() {
+        m_reporter->testRunEnded(TestRunStats(m_runInfo, m_totals, aborting()));
+    }
+
+    void RunContext::testGroupStarting(std::string const& testSpec, std::size_t groupIndex, std::size_t groupsCount) {
+        m_reporter->testGroupStarting(GroupInfo(testSpec, groupIndex, groupsCount));
+    }
+
+    void RunContext::testGroupEnded(std::string const& testSpec, Totals const& totals, std::size_t groupIndex, std::size_t groupsCount) {
+        m_reporter->testGroupEnded(TestGroupStats(GroupInfo(testSpec, groupIndex, groupsCount), totals, aborting()));
+    }
+
+    Totals RunContext::runTest(TestCase const& testCase) {
+        Totals prevTotals = m_totals;
+
+        std::string redirectedCout;
+        std::string redirectedCerr;
+
+        auto const& testInfo = testCase.getTestCaseInfo();
+
+        m_reporter->testCaseStarting(testInfo);
+
+        m_activeTestCase = &testCase;
+
+        ITracker& rootTracker = m_trackerContext.startRun();
+        assert(rootTracker.isSectionTracker());
+        static_cast<SectionTracker&>(rootTracker).addInitialFilters(m_config->getSectionsToRun());
+        do {
+            m_trackerContext.startCycle();
+            m_testCaseTracker = &SectionTracker::acquire(m_trackerContext, TestCaseTracking::NameAndLocation(testInfo.name, testInfo.lineInfo));
+            runCurrentTest(redirectedCout, redirectedCerr);
+        } while (!m_testCaseTracker->isSuccessfullyCompleted() && !aborting());
+
+        Totals deltaTotals = m_totals.delta(prevTotals);
+        if (testInfo.expectedToFail() && deltaTotals.testCases.passed > 0) {
+            deltaTotals.assertions.failed++;
+            deltaTotals.testCases.passed--;
+            deltaTotals.testCases.failed++;
+        }
+        m_totals.testCases += deltaTotals.testCases;
+        m_reporter->testCaseEnded(TestCaseStats(testInfo,
+                                  deltaTotals,
+                                  redirectedCout,
+                                  redirectedCerr,
+                                  aborting()));
+
+        m_activeTestCase = nullptr;
+        m_testCaseTracker = nullptr;
+
+        return deltaTotals;
+    }
+
+    IConfigPtr RunContext::config() const {
+        return m_config;
+    }
+
+    IStreamingReporter& RunContext::reporter() const {
+        return *m_reporter;
+    }
+
+    void RunContext::assertionEnded(AssertionResult const & result) {
+        if (result.getResultType() == ResultWas::Ok) {
+            m_totals.assertions.passed++;
+            m_lastAssertionPassed = true;
+        } else if (!result.isOk()) {
+            m_lastAssertionPassed = false;
+            if( m_activeTestCase->getTestCaseInfo().okToFail() )
+                m_totals.assertions.failedButOk++;
+            else
+                m_totals.assertions.failed++;
+        }
+        else {
+            m_lastAssertionPassed = true;
+        }
+
+        // We have no use for the return value (whether messages should be cleared), because messages were made scoped
+        // and should be let to clear themselves out.
+        static_cast<void>(m_reporter->assertionEnded(AssertionStats(result, m_messages, m_totals)));
+
+        if (result.getResultType() != ResultWas::Warning)
+            m_messageScopes.clear();
+
+        // Reset working state
+        resetAssertionInfo();
+        m_lastResult = result;
+    }
+    void RunContext::resetAssertionInfo() {
+        m_lastAssertionInfo.macroName = StringRef();
+        m_lastAssertionInfo.capturedExpression = "{Unknown expression after the reported line}"_sr;
+    }
+
+    bool RunContext::sectionStarted(SectionInfo const & sectionInfo, Counts & assertions) {
+        ITracker& sectionTracker = SectionTracker::acquire(m_trackerContext, TestCaseTracking::NameAndLocation(sectionInfo.name, sectionInfo.lineInfo));
+        if (!sectionTracker.isOpen())
+            return false;
+        m_activeSections.push_back(&sectionTracker);
+
+        m_lastAssertionInfo.lineInfo = sectionInfo.lineInfo;
+
+        m_reporter->sectionStarting(sectionInfo);
+
+        assertions = m_totals.assertions;
+
+        return true;
+    }
+    auto RunContext::acquireGeneratorTracker( StringRef generatorName, SourceLineInfo const& lineInfo ) -> IGeneratorTracker& {
+        using namespace Generators;
+        GeneratorTracker& tracker = GeneratorTracker::acquire(m_trackerContext,
+                                                              TestCaseTracking::NameAndLocation( static_cast<std::string>(generatorName), lineInfo ) );
+        m_lastAssertionInfo.lineInfo = lineInfo;
+        return tracker;
+    }
+
+    bool RunContext::testForMissingAssertions(Counts& assertions) {
+        if (assertions.total() != 0)
+            return false;
+        if (!m_config->warnAboutMissingAssertions())
+            return false;
+        if (m_trackerContext.currentTracker().hasChildren())
+            return false;
+        m_totals.assertions.failed++;
+        assertions.failed++;
+        return true;
+    }
+
+    void RunContext::sectionEnded(SectionEndInfo const & endInfo) {
+        Counts assertions = m_totals.assertions - endInfo.prevAssertions;
+        bool missingAssertions = testForMissingAssertions(assertions);
+
+        if (!m_activeSections.empty()) {
+            m_activeSections.back()->close();
+            m_activeSections.pop_back();
+        }
+
+        m_reporter->sectionEnded(SectionStats(endInfo.sectionInfo, assertions, endInfo.durationInSeconds, missingAssertions));
+        m_messages.clear();
+        m_messageScopes.clear();
+    }
+
+    void RunContext::sectionEndedEarly(SectionEndInfo const & endInfo) {
+        if (m_unfinishedSections.empty())
+            m_activeSections.back()->fail();
+        else
+            m_activeSections.back()->close();
+        m_activeSections.pop_back();
+
+        m_unfinishedSections.push_back(endInfo);
+    }
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    void RunContext::benchmarkPreparing(std::string const& name) {
+        m_reporter->benchmarkPreparing(name);
+    }
+    void RunContext::benchmarkStarting( BenchmarkInfo const& info ) {
+        m_reporter->benchmarkStarting( info );
+    }
+    void RunContext::benchmarkEnded( BenchmarkStats<> const& stats ) {
+        m_reporter->benchmarkEnded( stats );
+    }
+    void RunContext::benchmarkFailed(std::string const & error) {
+        m_reporter->benchmarkFailed(error);
+    }
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    void RunContext::pushScopedMessage(MessageInfo const & message) {
+        m_messages.push_back(message);
+    }
+
+    void RunContext::popScopedMessage(MessageInfo const & message) {
+        m_messages.erase(std::remove(m_messages.begin(), m_messages.end(), message), m_messages.end());
+    }
+
+    void RunContext::emplaceUnscopedMessage( MessageBuilder const& builder ) {
+        m_messageScopes.emplace_back( builder );
+    }
+
+    std::string RunContext::getCurrentTestName() const {
+        return m_activeTestCase
+            ? m_activeTestCase->getTestCaseInfo().name
+            : std::string();
+    }
+
+    const AssertionResult * RunContext::getLastResult() const {
+        return &(*m_lastResult);
+    }
+
+    void RunContext::exceptionEarlyReported() {
+        m_shouldReportUnexpected = false;
+    }
+
+    void RunContext::handleFatalErrorCondition( StringRef message ) {
+        // First notify reporter that bad things happened
+        m_reporter->fatalErrorEncountered(message);
+
+        // Don't rebuild the result -- the stringification itself can cause more fatal errors
+        // Instead, fake a result data.
+        AssertionResultData tempResult( ResultWas::FatalErrorCondition, { false } );
+        tempResult.message = static_cast<std::string>(message);
+        AssertionResult result(m_lastAssertionInfo, tempResult);
+
+        assertionEnded(result);
+
+        handleUnfinishedSections();
+
+        // Recreate section for test case (as we will lose the one that was in scope)
+        auto const& testCaseInfo = m_activeTestCase->getTestCaseInfo();
+        SectionInfo testCaseSection(testCaseInfo.lineInfo, testCaseInfo.name);
+
+        Counts assertions;
+        assertions.failed = 1;
+        SectionStats testCaseSectionStats(testCaseSection, assertions, 0, false);
+        m_reporter->sectionEnded(testCaseSectionStats);
+
+        auto const& testInfo = m_activeTestCase->getTestCaseInfo();
+
+        Totals deltaTotals;
+        deltaTotals.testCases.failed = 1;
+        deltaTotals.assertions.failed = 1;
+        m_reporter->testCaseEnded(TestCaseStats(testInfo,
+                                  deltaTotals,
+                                  std::string(),
+                                  std::string(),
+                                  false));
+        m_totals.testCases.failed++;
+        testGroupEnded(std::string(), m_totals, 1, 1);
+        m_reporter->testRunEnded(TestRunStats(m_runInfo, m_totals, false));
+    }
+
+    bool RunContext::lastAssertionPassed() {
+         return m_lastAssertionPassed;
+    }
+
+    void RunContext::assertionPassed() {
+        m_lastAssertionPassed = true;
+        ++m_totals.assertions.passed;
+        resetAssertionInfo();
+        m_messageScopes.clear();
+    }
+
+    bool RunContext::aborting() const {
+        return m_totals.assertions.failed >= static_cast<std::size_t>(m_config->abortAfter());
+    }
+
+    void RunContext::runCurrentTest(std::string & redirectedCout, std::string & redirectedCerr) {
+        auto const& testCaseInfo = m_activeTestCase->getTestCaseInfo();
+        SectionInfo testCaseSection(testCaseInfo.lineInfo, testCaseInfo.name);
+        m_reporter->sectionStarting(testCaseSection);
+        Counts prevAssertions = m_totals.assertions;
+        double duration = 0;
+        m_shouldReportUnexpected = true;
+        m_lastAssertionInfo = { "TEST_CASE"_sr, testCaseInfo.lineInfo, StringRef(), ResultDisposition::Normal };
+
+        seedRng(*m_config);
+
+        Timer timer;
+        CATCH_TRY {
+            if (m_reporter->getPreferences().shouldRedirectStdOut) {
+#if !defined(CATCH_CONFIG_EXPERIMENTAL_REDIRECT)
+                RedirectedStreams redirectedStreams(redirectedCout, redirectedCerr);
+
+                timer.start();
+                invokeActiveTestCase();
+#else
+                OutputRedirect r(redirectedCout, redirectedCerr);
+                timer.start();
+                invokeActiveTestCase();
+#endif
+            } else {
+                timer.start();
+                invokeActiveTestCase();
+            }
+            duration = timer.getElapsedSeconds();
+        } CATCH_CATCH_ANON (TestFailureException&) {
+            // This just means the test was aborted due to failure
+        } CATCH_CATCH_ALL {
+            // Under CATCH_CONFIG_FAST_COMPILE, unexpected exceptions under REQUIRE assertions
+            // are reported without translation at the point of origin.
+            if( m_shouldReportUnexpected ) {
+                AssertionReaction dummyReaction;
+                handleUnexpectedInflightException( m_lastAssertionInfo, translateActiveException(), dummyReaction );
+            }
+        }
+        Counts assertions = m_totals.assertions - prevAssertions;
+        bool missingAssertions = testForMissingAssertions(assertions);
+
+        m_testCaseTracker->close();
+        handleUnfinishedSections();
+        m_messages.clear();
+        m_messageScopes.clear();
+
+        SectionStats testCaseSectionStats(testCaseSection, assertions, duration, missingAssertions);
+        m_reporter->sectionEnded(testCaseSectionStats);
+    }
+
+    void RunContext::invokeActiveTestCase() {
+        FatalConditionHandlerGuard _(&m_fatalConditionhandler);
+        m_activeTestCase->invoke();
+    }
+
+    void RunContext::handleUnfinishedSections() {
+        // If sections ended prematurely due to an exception we stored their
+        // infos here so we can tear them down outside the unwind process.
+        for (auto it = m_unfinishedSections.rbegin(),
+             itEnd = m_unfinishedSections.rend();
+             it != itEnd;
+             ++it)
+            sectionEnded(*it);
+        m_unfinishedSections.clear();
+    }
+
+    void RunContext::handleExpr(
+        AssertionInfo const& info,
+        ITransientExpression const& expr,
+        AssertionReaction& reaction
+    ) {
+        m_reporter->assertionStarting( info );
+
+        bool negated = isFalseTest( info.resultDisposition );
+        bool result = expr.getResult() != negated;
+
+        if( result ) {
+            if (!m_includeSuccessfulResults) {
+                assertionPassed();
+            }
+            else {
+                reportExpr(info, ResultWas::Ok, &expr, negated);
+            }
+        }
+        else {
+            reportExpr(info, ResultWas::ExpressionFailed, &expr, negated );
+            populateReaction( reaction );
+        }
+    }
+    void RunContext::reportExpr(
+            AssertionInfo const &info,
+            ResultWas::OfType resultType,
+            ITransientExpression const *expr,
+            bool negated ) {
+
+        m_lastAssertionInfo = info;
+        AssertionResultData data( resultType, LazyExpression( negated ) );
+
+        AssertionResult assertionResult{ info, data };
+        assertionResult.m_resultData.lazyExpression.m_transientExpression = expr;
+
+        assertionEnded( assertionResult );
+    }
+
+    void RunContext::handleMessage(
+            AssertionInfo const& info,
+            ResultWas::OfType resultType,
+            StringRef const& message,
+            AssertionReaction& reaction
+    ) {
+        m_reporter->assertionStarting( info );
+
+        m_lastAssertionInfo = info;
+
+        AssertionResultData data( resultType, LazyExpression( false ) );
+        data.message = static_cast<std::string>(message);
+        AssertionResult assertionResult{ m_lastAssertionInfo, data };
+        assertionEnded( assertionResult );
+        if( !assertionResult.isOk() )
+            populateReaction( reaction );
+    }
+    void RunContext::handleUnexpectedExceptionNotThrown(
+            AssertionInfo const& info,
+            AssertionReaction& reaction
+    ) {
+        handleNonExpr(info, Catch::ResultWas::DidntThrowException, reaction);
+    }
+
+    void RunContext::handleUnexpectedInflightException(
+            AssertionInfo const& info,
+            std::string const& message,
+            AssertionReaction& reaction
+    ) {
+        m_lastAssertionInfo = info;
+
+        AssertionResultData data( ResultWas::ThrewException, LazyExpression( false ) );
+        data.message = message;
+        AssertionResult assertionResult{ info, data };
+        assertionEnded( assertionResult );
+        populateReaction( reaction );
+    }
+
+    void RunContext::populateReaction( AssertionReaction& reaction ) {
+        reaction.shouldDebugBreak = m_config->shouldDebugBreak();
+        reaction.shouldThrow = aborting() || (m_lastAssertionInfo.resultDisposition & ResultDisposition::Normal);
+    }
+
+    void RunContext::handleIncomplete(
+            AssertionInfo const& info
+    ) {
+        m_lastAssertionInfo = info;
+
+        AssertionResultData data( ResultWas::ThrewException, LazyExpression( false ) );
+        data.message = "Exception translation was disabled by CATCH_CONFIG_FAST_COMPILE";
+        AssertionResult assertionResult{ info, data };
+        assertionEnded( assertionResult );
+    }
+    void RunContext::handleNonExpr(
+            AssertionInfo const &info,
+            ResultWas::OfType resultType,
+            AssertionReaction &reaction
+    ) {
+        m_lastAssertionInfo = info;
+
+        AssertionResultData data( resultType, LazyExpression( false ) );
+        AssertionResult assertionResult{ info, data };
+        assertionEnded( assertionResult );
+
+        if( !assertionResult.isOk() )
+            populateReaction( reaction );
+    }
+
+    IResultCapture& getResultCapture() {
+        if (auto* capture = getCurrentContext().getResultCapture())
+            return *capture;
+        else
+            CATCH_INTERNAL_ERROR("No result capture instance");
+    }
+
+    void seedRng(IConfig const& config) {
+        if (config.rngSeed() != 0) {
+            std::srand(config.rngSeed());
+            rng().seed(config.rngSeed());
+        }
+    }
+
+    unsigned int rngSeed() {
+        return getCurrentContext().getConfig()->rngSeed();
+    }
+
+}
+// end catch_run_context.cpp
+// start catch_section.cpp
+
+namespace Catch {
+
+    Section::Section( SectionInfo const& info )
+    :   m_info( info ),
+        m_sectionIncluded( getResultCapture().sectionStarted( m_info, m_assertions ) )
+    {
+        m_timer.start();
+    }
+
+    Section::~Section() {
+        if( m_sectionIncluded ) {
+            SectionEndInfo endInfo{ m_info, m_assertions, m_timer.getElapsedSeconds() };
+            if( uncaught_exceptions() )
+                getResultCapture().sectionEndedEarly( endInfo );
+            else
+                getResultCapture().sectionEnded( endInfo );
+        }
+    }
+
+    // This indicates whether the section should be executed or not
+    Section::operator bool() const {
+        return m_sectionIncluded;
+    }
+
+} // end namespace Catch
+// end catch_section.cpp
+// start catch_section_info.cpp
+
+namespace Catch {
+
+    SectionInfo::SectionInfo
+        (   SourceLineInfo const& _lineInfo,
+            std::string const& _name )
+    :   name( _name ),
+        lineInfo( _lineInfo )
+    {}
+
+} // end namespace Catch
+// end catch_section_info.cpp
+// start catch_session.cpp
+
+// start catch_session.h
+
+#include <memory>
+
+namespace Catch {
+
+    class Session : NonCopyable {
+    public:
+
+        Session();
+        ~Session() override;
+
+        void showHelp() const;
+        void libIdentify();
+
+        int applyCommandLine( int argc, char const * const * argv );
+    #if defined(CATCH_CONFIG_WCHAR) && defined(_WIN32) && defined(UNICODE)
+        int applyCommandLine( int argc, wchar_t const * const * argv );
+    #endif
+
+        void useConfigData( ConfigData const& configData );
+
+        template<typename CharT>
+        int run(int argc, CharT const * const argv[]) {
+            if (m_startupExceptions)
+                return 1;
+            int returnCode = applyCommandLine(argc, argv);
+            if (returnCode == 0)
+                returnCode = run();
+            return returnCode;
+        }
+
+        int run();
+
+        clara::Parser const& cli() const;
+        void cli( clara::Parser const& newParser );
+        ConfigData& configData();
+        Config& config();
+    private:
+        int runInternal();
+
+        clara::Parser m_cli;
+        ConfigData m_configData;
+        std::shared_ptr<Config> m_config;
+        bool m_startupExceptions = false;
+    };
+
+} // end namespace Catch
+
+// end catch_session.h
+// start catch_version.h
+
+#include <iosfwd>
+
+namespace Catch {
+
+    // Versioning information
+    struct Version {
+        Version( Version const& ) = delete;
+        Version& operator=( Version const& ) = delete;
+        Version(    unsigned int _majorVersion,
+                    unsigned int _minorVersion,
+                    unsigned int _patchNumber,
+                    char const * const _branchName,
+                    unsigned int _buildNumber );
+
+        unsigned int const majorVersion;
+        unsigned int const minorVersion;
+        unsigned int const patchNumber;
+
+        // buildNumber is only used if branchName is not null
+        char const * const branchName;
+        unsigned int const buildNumber;
+
+        friend std::ostream& operator << ( std::ostream& os, Version const& version );
+    };
+
+    Version const& libraryVersion();
+}
+
+// end catch_version.h
+#include <cstdlib>
+#include <iomanip>
+#include <set>
+#include <iterator>
+
+namespace Catch {
+
+    namespace {
+        const int MaxExitCode = 255;
+
+        IStreamingReporterPtr createReporter(std::string const& reporterName, IConfigPtr const& config) {
+            auto reporter = Catch::getRegistryHub().getReporterRegistry().create(reporterName, config);
+            CATCH_ENFORCE(reporter, "No reporter registered with name: '" << reporterName << "'");
+
+            return reporter;
+        }
+
+        IStreamingReporterPtr makeReporter(std::shared_ptr<Config> const& config) {
+            if (Catch::getRegistryHub().getReporterRegistry().getListeners().empty()) {
+                return createReporter(config->getReporterName(), config);
+            }
+
+            // On older platforms, returning std::unique_ptr<ListeningReporter>
+            // when the return type is std::unique_ptr<IStreamingReporter>
+            // doesn't compile without a std::move call. However, this causes
+            // a warning on newer platforms. Thus, we have to work around
+            // it a bit and downcast the pointer manually.
+            auto ret = std::unique_ptr<IStreamingReporter>(new ListeningReporter);
+            auto& multi = static_cast<ListeningReporter&>(*ret);
+            auto const& listeners = Catch::getRegistryHub().getReporterRegistry().getListeners();
+            for (auto const& listener : listeners) {
+                multi.addListener(listener->create(Catch::ReporterConfig(config)));
+            }
+            multi.addReporter(createReporter(config->getReporterName(), config));
+            return ret;
+        }
+
+        class TestGroup {
+        public:
+            explicit TestGroup(std::shared_ptr<Config> const& config)
+            : m_config{config}
+            , m_context{config, makeReporter(config)}
+            {
+                auto const& allTestCases = getAllTestCasesSorted(*m_config);
+                m_matches = m_config->testSpec().matchesByFilter(allTestCases, *m_config);
+                auto const& invalidArgs = m_config->testSpec().getInvalidArgs();
+
+                if (m_matches.empty() && invalidArgs.empty()) {
+                    for (auto const& test : allTestCases)
+                        if (!test.isHidden())
+                            m_tests.emplace(&test);
+                } else {
+                    for (auto const& match : m_matches)
+                        m_tests.insert(match.tests.begin(), match.tests.end());
+                }
+            }
+
+            Totals execute() {
+                auto const& invalidArgs = m_config->testSpec().getInvalidArgs();
+                Totals totals;
+                m_context.testGroupStarting(m_config->name(), 1, 1);
+                for (auto const& testCase : m_tests) {
+                    if (!m_context.aborting())
+                        totals += m_context.runTest(*testCase);
+                    else
+                        m_context.reporter().skipTest(*testCase);
+                }
+
+                for (auto const& match : m_matches) {
+                    if (match.tests.empty()) {
+                        m_context.reporter().noMatchingTestCases(match.name);
+                        totals.error = -1;
+                    }
+                }
+
+                if (!invalidArgs.empty()) {
+                    for (auto const& invalidArg: invalidArgs)
+                         m_context.reporter().reportInvalidArguments(invalidArg);
+                }
+
+                m_context.testGroupEnded(m_config->name(), totals, 1, 1);
+                return totals;
+            }
+
+        private:
+            using Tests = std::set<TestCase const*>;
+
+            std::shared_ptr<Config> m_config;
+            RunContext m_context;
+            Tests m_tests;
+            TestSpec::Matches m_matches;
+        };
+
+        void applyFilenamesAsTags(Catch::IConfig const& config) {
+            auto& tests = const_cast<std::vector<TestCase>&>(getAllTestCasesSorted(config));
+            for (auto& testCase : tests) {
+                auto tags = testCase.tags;
+
+                std::string filename = testCase.lineInfo.file;
+                auto lastSlash = filename.find_last_of("\\/");
+                if (lastSlash != std::string::npos) {
+                    filename.erase(0, lastSlash);
+                    filename[0] = '#';
+                }
+                else
+                {
+                    filename.insert(0, "#");
+                }
+
+                auto lastDot = filename.find_last_of('.');
+                if (lastDot != std::string::npos) {
+                    filename.erase(lastDot);
+                }
+
+                tags.push_back(std::move(filename));
+                setTags(testCase, tags);
+            }
+        }
+
+    } // anon namespace
+
+    Session::Session() {
+        static bool alreadyInstantiated = false;
+        if( alreadyInstantiated ) {
+            CATCH_TRY { CATCH_INTERNAL_ERROR( "Only one instance of Catch::Session can ever be used" ); }
+            CATCH_CATCH_ALL { getMutableRegistryHub().registerStartupException(); }
+        }
+
+        // There cannot be exceptions at startup in no-exception mode.
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+        const auto& exceptions = getRegistryHub().getStartupExceptionRegistry().getExceptions();
+        if ( !exceptions.empty() ) {
+            config();
+            getCurrentMutableContext().setConfig(m_config);
+
+            m_startupExceptions = true;
+            Colour colourGuard( Colour::Red );
+            Catch::cerr() << "Errors occurred during startup!" << '\n';
+            // iterate over all exceptions and notify user
+            for ( const auto& ex_ptr : exceptions ) {
+                try {
+                    std::rethrow_exception(ex_ptr);
+                } catch ( std::exception const& ex ) {
+                    Catch::cerr() << Column( ex.what() ).indent(2) << '\n';
+                }
+            }
+        }
+#endif
+
+        alreadyInstantiated = true;
+        m_cli = makeCommandLineParser( m_configData );
+    }
+    Session::~Session() {
+        Catch::cleanUp();
+    }
+
+    void Session::showHelp() const {
+        Catch::cout()
+                << "\nCatch v" << libraryVersion() << "\n"
+                << m_cli << std::endl
+                << "For more detailed usage please see the project docs\n" << std::endl;
+    }
+    void Session::libIdentify() {
+        Catch::cout()
+                << std::left << std::setw(16) << "description: " << "A Catch2 test executable\n"
+                << std::left << std::setw(16) << "category: " << "testframework\n"
+                << std::left << std::setw(16) << "framework: " << "Catch Test\n"
+                << std::left << std::setw(16) << "version: " << libraryVersion() << std::endl;
+    }
+
+    int Session::applyCommandLine( int argc, char const * const * argv ) {
+        if( m_startupExceptions )
+            return 1;
+
+        auto result = m_cli.parse( clara::Args( argc, argv ) );
+        if( !result ) {
+            config();
+            getCurrentMutableContext().setConfig(m_config);
+            Catch::cerr()
+                << Colour( Colour::Red )
+                << "\nError(s) in input:\n"
+                << Column( result.errorMessage() ).indent( 2 )
+                << "\n\n";
+            Catch::cerr() << "Run with -? for usage\n" << std::endl;
+            return MaxExitCode;
+        }
+
+        if( m_configData.showHelp )
+            showHelp();
+        if( m_configData.libIdentify )
+            libIdentify();
+        m_config.reset();
+        return 0;
+    }
+
+#if defined(CATCH_CONFIG_WCHAR) && defined(_WIN32) && defined(UNICODE)
+    int Session::applyCommandLine( int argc, wchar_t const * const * argv ) {
+
+        char **utf8Argv = new char *[ argc ];
+
+        for ( int i = 0; i < argc; ++i ) {
+            int bufSize = WideCharToMultiByte( CP_UTF8, 0, argv[i], -1, nullptr, 0, nullptr, nullptr );
+
+            utf8Argv[ i ] = new char[ bufSize ];
+
+            WideCharToMultiByte( CP_UTF8, 0, argv[i], -1, utf8Argv[i], bufSize, nullptr, nullptr );
+        }
+
+        int returnCode = applyCommandLine( argc, utf8Argv );
+
+        for ( int i = 0; i < argc; ++i )
+            delete [] utf8Argv[ i ];
+
+        delete [] utf8Argv;
+
+        return returnCode;
+    }
+#endif
+
+    void Session::useConfigData( ConfigData const& configData ) {
+        m_configData = configData;
+        m_config.reset();
+    }
+
+    int Session::run() {
+        if( ( m_configData.waitForKeypress & WaitForKeypress::BeforeStart ) != 0 ) {
+            Catch::cout() << "...waiting for enter/ return before starting" << std::endl;
+            static_cast<void>(std::getchar());
+        }
+        int exitCode = runInternal();
+        if( ( m_configData.waitForKeypress & WaitForKeypress::BeforeExit ) != 0 ) {
+            Catch::cout() << "...waiting for enter/ return before exiting, with code: " << exitCode << std::endl;
+            static_cast<void>(std::getchar());
+        }
+        return exitCode;
+    }
+
+    clara::Parser const& Session::cli() const {
+        return m_cli;
+    }
+    void Session::cli( clara::Parser const& newParser ) {
+        m_cli = newParser;
+    }
+    ConfigData& Session::configData() {
+        return m_configData;
+    }
+    Config& Session::config() {
+        if( !m_config )
+            m_config = std::make_shared<Config>( m_configData );
+        return *m_config;
+    }
+
+    int Session::runInternal() {
+        if( m_startupExceptions )
+            return 1;
+
+        if (m_configData.showHelp || m_configData.libIdentify) {
+            return 0;
+        }
+
+        CATCH_TRY {
+            config(); // Force config to be constructed
+
+            seedRng( *m_config );
+
+            if( m_configData.filenamesAsTags )
+                applyFilenamesAsTags( *m_config );
+
+            // Handle list request
+            if( Option<std::size_t> listed = list( m_config ) )
+                return static_cast<int>( *listed );
+
+            TestGroup tests { m_config };
+            auto const totals = tests.execute();
+
+            if( m_config->warnAboutNoTests() && totals.error == -1 )
+                return 2;
+
+            // Note that on unices only the lower 8 bits are usually used, clamping
+            // the return value to 255 prevents false negative when some multiple
+            // of 256 tests has failed
+            return (std::min) (MaxExitCode, (std::max) (totals.error, static_cast<int>(totals.assertions.failed)));
+        }
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+        catch( std::exception& ex ) {
+            Catch::cerr() << ex.what() << std::endl;
+            return MaxExitCode;
+        }
+#endif
+    }
+
+} // end namespace Catch
+// end catch_session.cpp
+// start catch_singletons.cpp
+
+#include <vector>
+
+namespace Catch {
+
+    namespace {
+        static auto getSingletons() -> std::vector<ISingleton*>*& {
+            static std::vector<ISingleton*>* g_singletons = nullptr;
+            if( !g_singletons )
+                g_singletons = new std::vector<ISingleton*>();
+            return g_singletons;
+        }
+    }
+
+    ISingleton::~ISingleton() {}
+
+    void addSingleton(ISingleton* singleton ) {
+        getSingletons()->push_back( singleton );
+    }
+    void cleanupSingletons() {
+        auto& singletons = getSingletons();
+        for( auto singleton : *singletons )
+            delete singleton;
+        delete singletons;
+        singletons = nullptr;
+    }
+
+} // namespace Catch
+// end catch_singletons.cpp
+// start catch_startup_exception_registry.cpp
+
+#if !defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+namespace Catch {
+void StartupExceptionRegistry::add( std::exception_ptr const& exception ) noexcept {
+        CATCH_TRY {
+            m_exceptions.push_back(exception);
+        } CATCH_CATCH_ALL {
+            // If we run out of memory during start-up there's really not a lot more we can do about it
+            std::terminate();
+        }
+    }
+
+    std::vector<std::exception_ptr> const& StartupExceptionRegistry::getExceptions() const noexcept {
+        return m_exceptions;
+    }
+
+} // end namespace Catch
+#endif
+// end catch_startup_exception_registry.cpp
+// start catch_stream.cpp
+
+#include <cstdio>
+#include <iostream>
+#include <fstream>
+#include <sstream>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    Catch::IStream::~IStream() = default;
+
+    namespace Detail { namespace {
+        template<typename WriterF, std::size_t bufferSize=256>
+        class StreamBufImpl : public std::streambuf {
+            char data[bufferSize];
+            WriterF m_writer;
+
+        public:
+            StreamBufImpl() {
+                setp( data, data + sizeof(data) );
+            }
+
+            ~StreamBufImpl() noexcept {
+                StreamBufImpl::sync();
+            }
+
+        private:
+            int overflow( int c ) override {
+                sync();
+
+                if( c != EOF ) {
+                    if( pbase() == epptr() )
+                        m_writer( std::string( 1, static_cast<char>( c ) ) );
+                    else
+                        sputc( static_cast<char>( c ) );
+                }
+                return 0;
+            }
+
+            int sync() override {
+                if( pbase() != pptr() ) {
+                    m_writer( std::string( pbase(), static_cast<std::string::size_type>( pptr() - pbase() ) ) );
+                    setp( pbase(), epptr() );
+                }
+                return 0;
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+
+        struct OutputDebugWriter {
+
+            void operator()( std::string const&str ) {
+                writeToDebugConsole( str );
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+
+        class FileStream : public IStream {
+            mutable std::ofstream m_ofs;
+        public:
+            FileStream( StringRef filename ) {
+                m_ofs.open( filename.c_str() );
+                CATCH_ENFORCE( !m_ofs.fail(), "Unable to open file: '" << filename << "'" );
+            }
+            ~FileStream() override = default;
+        public: // IStream
+            std::ostream& stream() const override {
+                return m_ofs;
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+
+        class CoutStream : public IStream {
+            mutable std::ostream m_os;
+        public:
+            // Store the streambuf from cout up-front because
+            // cout may get redirected when running tests
+            CoutStream() : m_os( Catch::cout().rdbuf() ) {}
+            ~CoutStream() override = default;
+
+        public: // IStream
+            std::ostream& stream() const override { return m_os; }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+
+        class DebugOutStream : public IStream {
+            std::unique_ptr<StreamBufImpl<OutputDebugWriter>> m_streamBuf;
+            mutable std::ostream m_os;
+        public:
+            DebugOutStream()
+            :   m_streamBuf( new StreamBufImpl<OutputDebugWriter>() ),
+                m_os( m_streamBuf.get() )
+            {}
+
+            ~DebugOutStream() override = default;
+
+        public: // IStream
+            std::ostream& stream() const override { return m_os; }
+        };
+
+    }} // namespace anon::detail
+
+    ///////////////////////////////////////////////////////////////////////////
+
+    auto makeStream( StringRef const &filename ) -> IStream const* {
+        if( filename.empty() )
+            return new Detail::CoutStream();
+        else if( filename[0] == '%' ) {
+            if( filename == "%debug" )
+                return new Detail::DebugOutStream();
+            else
+                CATCH_ERROR( "Unrecognised stream: '" << filename << "'" );
+        }
+        else
+            return new Detail::FileStream( filename );
+    }
+
+    // This class encapsulates the idea of a pool of ostringstreams that can be reused.
+    struct StringStreams {
+        std::vector<std::unique_ptr<std::ostringstream>> m_streams;
+        std::vector<std::size_t> m_unused;
+        std::ostringstream m_referenceStream; // Used for copy state/ flags from
+
+        auto add() -> std::size_t {
+            if( m_unused.empty() ) {
+                m_streams.push_back( std::unique_ptr<std::ostringstream>( new std::ostringstream ) );
+                return m_streams.size()-1;
+            }
+            else {
+                auto index = m_unused.back();
+                m_unused.pop_back();
+                return index;
+            }
+        }
+
+        void release( std::size_t index ) {
+            m_streams[index]->copyfmt( m_referenceStream ); // Restore initial flags and other state
+            m_unused.push_back(index);
+        }
+    };
+
+    ReusableStringStream::ReusableStringStream()
+    :   m_index( Singleton<StringStreams>::getMutable().add() ),
+        m_oss( Singleton<StringStreams>::getMutable().m_streams[m_index].get() )
+    {}
+
+    ReusableStringStream::~ReusableStringStream() {
+        static_cast<std::ostringstream*>( m_oss )->str("");
+        m_oss->clear();
+        Singleton<StringStreams>::getMutable().release( m_index );
+    }
+
+    auto ReusableStringStream::str() const -> std::string {
+        return static_cast<std::ostringstream*>( m_oss )->str();
+    }
+
+    ///////////////////////////////////////////////////////////////////////////
+
+#ifndef CATCH_CONFIG_NOSTDOUT // If you #define this you must implement these functions
+    std::ostream& cout() { return std::cout; }
+    std::ostream& cerr() { return std::cerr; }
+    std::ostream& clog() { return std::clog; }
+#endif
+}
+// end catch_stream.cpp
+// start catch_string_manip.cpp
+
+#include <algorithm>
+#include <ostream>
+#include <cstring>
+#include <cctype>
+#include <vector>
+
+namespace Catch {
+
+    namespace {
+        char toLowerCh(char c) {
+            return static_cast<char>( std::tolower( static_cast<unsigned char>(c) ) );
+        }
+    }
+
+    bool startsWith( std::string const& s, std::string const& prefix ) {
+        return s.size() >= prefix.size() && std::equal(prefix.begin(), prefix.end(), s.begin());
+    }
+    bool startsWith( std::string const& s, char prefix ) {
+        return !s.empty() && s[0] == prefix;
+    }
+    bool endsWith( std::string const& s, std::string const& suffix ) {
+        return s.size() >= suffix.size() && std::equal(suffix.rbegin(), suffix.rend(), s.rbegin());
+    }
+    bool endsWith( std::string const& s, char suffix ) {
+        return !s.empty() && s[s.size()-1] == suffix;
+    }
+    bool contains( std::string const& s, std::string const& infix ) {
+        return s.find( infix ) != std::string::npos;
+    }
+    void toLowerInPlace( std::string& s ) {
+        std::transform( s.begin(), s.end(), s.begin(), toLowerCh );
+    }
+    std::string toLower( std::string const& s ) {
+        std::string lc = s;
+        toLowerInPlace( lc );
+        return lc;
+    }
+    std::string trim( std::string const& str ) {
+        static char const* whitespaceChars = "\n\r\t ";
+        std::string::size_type start = str.find_first_not_of( whitespaceChars );
+        std::string::size_type end = str.find_last_not_of( whitespaceChars );
+
+        return start != std::string::npos ? str.substr( start, 1+end-start ) : std::string();
+    }
+
+    StringRef trim(StringRef ref) {
+        const auto is_ws = [](char c) {
+            return c == ' ' || c == '\t' || c == '\n' || c == '\r';
+        };
+        size_t real_begin = 0;
+        while (real_begin < ref.size() && is_ws(ref[real_begin])) { ++real_begin; }
+        size_t real_end = ref.size();
+        while (real_end > real_begin && is_ws(ref[real_end - 1])) { --real_end; }
+
+        return ref.substr(real_begin, real_end - real_begin);
+    }
+
+    bool replaceInPlace( std::string& str, std::string const& replaceThis, std::string const& withThis ) {
+        bool replaced = false;
+        std::size_t i = str.find( replaceThis );
+        while( i != std::string::npos ) {
+            replaced = true;
+            str = str.substr( 0, i ) + withThis + str.substr( i+replaceThis.size() );
+            if( i < str.size()-withThis.size() )
+                i = str.find( replaceThis, i+withThis.size() );
+            else
+                i = std::string::npos;
+        }
+        return replaced;
+    }
+
+    std::vector<StringRef> splitStringRef( StringRef str, char delimiter ) {
+        std::vector<StringRef> subStrings;
+        std::size_t start = 0;
+        for(std::size_t pos = 0; pos < str.size(); ++pos ) {
+            if( str[pos] == delimiter ) {
+                if( pos - start > 1 )
+                    subStrings.push_back( str.substr( start, pos-start ) );
+                start = pos+1;
+            }
+        }
+        if( start < str.size() )
+            subStrings.push_back( str.substr( start, str.size()-start ) );
+        return subStrings;
+    }
+
+    pluralise::pluralise( std::size_t count, std::string const& label )
+    :   m_count( count ),
+        m_label( label )
+    {}
+
+    std::ostream& operator << ( std::ostream& os, pluralise const& pluraliser ) {
+        os << pluraliser.m_count << ' ' << pluraliser.m_label;
+        if( pluraliser.m_count != 1 )
+            os << 's';
+        return os;
+    }
+
+}
+// end catch_string_manip.cpp
+// start catch_stringref.cpp
+
+#include <algorithm>
+#include <ostream>
+#include <cstring>
+#include <cstdint>
+
+namespace Catch {
+    StringRef::StringRef( char const* rawChars ) noexcept
+    : StringRef( rawChars, static_cast<StringRef::size_type>(std::strlen(rawChars) ) )
+    {}
+
+    auto StringRef::c_str() const -> char const* {
+        CATCH_ENFORCE(isNullTerminated(), "Called StringRef::c_str() on a non-null-terminated instance");
+        return m_start;
+    }
+    auto StringRef::data() const noexcept -> char const* {
+        return m_start;
+    }
+
+    auto StringRef::substr( size_type start, size_type size ) const noexcept -> StringRef {
+        if (start < m_size) {
+            return StringRef(m_start + start, (std::min)(m_size - start, size));
+        } else {
+            return StringRef();
+        }
+    }
+    auto StringRef::operator == ( StringRef const& other ) const noexcept -> bool {
+        return m_size == other.m_size
+            && (std::memcmp( m_start, other.m_start, m_size ) == 0);
+    }
+
+    auto operator << ( std::ostream& os, StringRef const& str ) -> std::ostream& {
+        return os.write(str.data(), str.size());
+    }
+
+    auto operator+=( std::string& lhs, StringRef const& rhs ) -> std::string& {
+        lhs.append(rhs.data(), rhs.size());
+        return lhs;
+    }
+
+} // namespace Catch
+// end catch_stringref.cpp
+// start catch_tag_alias.cpp
+
+namespace Catch {
+    TagAlias::TagAlias(std::string const & _tag, SourceLineInfo _lineInfo): tag(_tag), lineInfo(_lineInfo) {}
+}
+// end catch_tag_alias.cpp
+// start catch_tag_alias_autoregistrar.cpp
+
+namespace Catch {
+
+    RegistrarForTagAliases::RegistrarForTagAliases(char const* alias, char const* tag, SourceLineInfo const& lineInfo) {
+        CATCH_TRY {
+            getMutableRegistryHub().registerTagAlias(alias, tag, lineInfo);
+        } CATCH_CATCH_ALL {
+            // Do not throw when constructing global objects, instead register the exception to be processed later
+            getMutableRegistryHub().registerStartupException();
+        }
+    }
+
+}
+// end catch_tag_alias_autoregistrar.cpp
+// start catch_tag_alias_registry.cpp
+
+#include <sstream>
+
+namespace Catch {
+
+    TagAliasRegistry::~TagAliasRegistry() {}
+
+    TagAlias const* TagAliasRegistry::find( std::string const& alias ) const {
+        auto it = m_registry.find( alias );
+        if( it != m_registry.end() )
+            return &(it->second);
+        else
+            return nullptr;
+    }
+
+    std::string TagAliasRegistry::expandAliases( std::string const& unexpandedTestSpec ) const {
+        std::string expandedTestSpec = unexpandedTestSpec;
+        for( auto const& registryKvp : m_registry ) {
+            std::size_t pos = expandedTestSpec.find( registryKvp.first );
+            if( pos != std::string::npos ) {
+                expandedTestSpec =  expandedTestSpec.substr( 0, pos ) +
+                                    registryKvp.second.tag +
+                                    expandedTestSpec.substr( pos + registryKvp.first.size() );
+            }
+        }
+        return expandedTestSpec;
+    }
+
+    void TagAliasRegistry::add( std::string const& alias, std::string const& tag, SourceLineInfo const& lineInfo ) {
+        CATCH_ENFORCE( startsWith(alias, "[@") && endsWith(alias, ']'),
+                      "error: tag alias, '" << alias << "' is not of the form [@alias name].\n" << lineInfo );
+
+        CATCH_ENFORCE( m_registry.insert(std::make_pair(alias, TagAlias(tag, lineInfo))).second,
+                      "error: tag alias, '" << alias << "' already registered.\n"
+                      << "\tFirst seen at: " << find(alias)->lineInfo << "\n"
+                      << "\tRedefined at: " << lineInfo );
+    }
+
+    ITagAliasRegistry::~ITagAliasRegistry() {}
+
+    ITagAliasRegistry const& ITagAliasRegistry::get() {
+        return getRegistryHub().getTagAliasRegistry();
+    }
+
+} // end namespace Catch
+// end catch_tag_alias_registry.cpp
+// start catch_test_case_info.cpp
+
+#include <cctype>
+#include <exception>
+#include <algorithm>
+#include <sstream>
+
+namespace Catch {
+
+    namespace {
+        TestCaseInfo::SpecialProperties parseSpecialTag( std::string const& tag ) {
+            if( startsWith( tag, '.' ) ||
+                tag == "!hide" )
+                return TestCaseInfo::IsHidden;
+            else if( tag == "!throws" )
+                return TestCaseInfo::Throws;
+            else if( tag == "!shouldfail" )
+                return TestCaseInfo::ShouldFail;
+            else if( tag == "!mayfail" )
+                return TestCaseInfo::MayFail;
+            else if( tag == "!nonportable" )
+                return TestCaseInfo::NonPortable;
+            else if( tag == "!benchmark" )
+                return static_cast<TestCaseInfo::SpecialProperties>( TestCaseInfo::Benchmark | TestCaseInfo::IsHidden );
+            else
+                return TestCaseInfo::None;
+        }
+        bool isReservedTag( std::string const& tag ) {
+            return parseSpecialTag( tag ) == TestCaseInfo::None && tag.size() > 0 && !std::isalnum( static_cast<unsigned char>(tag[0]) );
+        }
+        void enforceNotReservedTag( std::string const& tag, SourceLineInfo const& _lineInfo ) {
+            CATCH_ENFORCE( !isReservedTag(tag),
+                          "Tag name: [" << tag << "] is not allowed.\n"
+                          << "Tag names starting with non alphanumeric characters are reserved\n"
+                          << _lineInfo );
+        }
+    }
+
+    TestCase makeTestCase(  ITestInvoker* _testCase,
+                            std::string const& _className,
+                            NameAndTags const& nameAndTags,
+                            SourceLineInfo const& _lineInfo )
+    {
+        bool isHidden = false;
+
+        // Parse out tags
+        std::vector<std::string> tags;
+        std::string desc, tag;
+        bool inTag = false;
+        for (char c : nameAndTags.tags) {
+            if( !inTag ) {
+                if( c == '[' )
+                    inTag = true;
+                else
+                    desc += c;
+            }
+            else {
+                if( c == ']' ) {
+                    TestCaseInfo::SpecialProperties prop = parseSpecialTag( tag );
+                    if( ( prop & TestCaseInfo::IsHidden ) != 0 )
+                        isHidden = true;
+                    else if( prop == TestCaseInfo::None )
+                        enforceNotReservedTag( tag, _lineInfo );
+
+                    // Merged hide tags like `[.approvals]` should be added as
+                    // `[.][approvals]`. The `[.]` is added at later point, so
+                    // we only strip the prefix
+                    if (startsWith(tag, '.') && tag.size() > 1) {
+                        tag.erase(0, 1);
+                    }
+                    tags.push_back( tag );
+                    tag.clear();
+                    inTag = false;
+                }
+                else
+                    tag += c;
+            }
+        }
+        if( isHidden ) {
+            // Add all "hidden" tags to make them behave identically
+            tags.insert( tags.end(), { ".", "!hide" } );
+        }
+
+        TestCaseInfo info( static_cast<std::string>(nameAndTags.name), _className, desc, tags, _lineInfo );
+        return TestCase( _testCase, std::move(info) );
+    }
+
+    void setTags( TestCaseInfo& testCaseInfo, std::vector<std::string> tags ) {
+        std::sort(begin(tags), end(tags));
+        tags.erase(std::unique(begin(tags), end(tags)), end(tags));
+        testCaseInfo.lcaseTags.clear();
+
+        for( auto const& tag : tags ) {
+            std::string lcaseTag = toLower( tag );
+            testCaseInfo.properties = static_cast<TestCaseInfo::SpecialProperties>( testCaseInfo.properties | parseSpecialTag( lcaseTag ) );
+            testCaseInfo.lcaseTags.push_back( lcaseTag );
+        }
+        testCaseInfo.tags = std::move(tags);
+    }
+
+    TestCaseInfo::TestCaseInfo( std::string const& _name,
+                                std::string const& _className,
+                                std::string const& _description,
+                                std::vector<std::string> const& _tags,
+                                SourceLineInfo const& _lineInfo )
+    :   name( _name ),
+        className( _className ),
+        description( _description ),
+        lineInfo( _lineInfo ),
+        properties( None )
+    {
+        setTags( *this, _tags );
+    }
+
+    bool TestCaseInfo::isHidden() const {
+        return ( properties & IsHidden ) != 0;
+    }
+    bool TestCaseInfo::throws() const {
+        return ( properties & Throws ) != 0;
+    }
+    bool TestCaseInfo::okToFail() const {
+        return ( properties & (ShouldFail | MayFail ) ) != 0;
+    }
+    bool TestCaseInfo::expectedToFail() const {
+        return ( properties & (ShouldFail ) ) != 0;
+    }
+
+    std::string TestCaseInfo::tagsAsString() const {
+        std::string ret;
+        // '[' and ']' per tag
+        std::size_t full_size = 2 * tags.size();
+        for (const auto& tag : tags) {
+            full_size += tag.size();
+        }
+        ret.reserve(full_size);
+        for (const auto& tag : tags) {
+            ret.push_back('[');
+            ret.append(tag);
+            ret.push_back(']');
+        }
+
+        return ret;
+    }
+
+    TestCase::TestCase( ITestInvoker* testCase, TestCaseInfo&& info ) : TestCaseInfo( std::move(info) ), test( testCase ) {}
+
+    TestCase TestCase::withName( std::string const& _newName ) const {
+        TestCase other( *this );
+        other.name = _newName;
+        return other;
+    }
+
+    void TestCase::invoke() const {
+        test->invoke();
+    }
+
+    bool TestCase::operator == ( TestCase const& other ) const {
+        return  test.get() == other.test.get() &&
+                name == other.name &&
+                className == other.className;
+    }
+
+    bool TestCase::operator < ( TestCase const& other ) const {
+        return name < other.name;
+    }
+
+    TestCaseInfo const& TestCase::getTestCaseInfo() const
+    {
+        return *this;
+    }
+
+} // end namespace Catch
+// end catch_test_case_info.cpp
+// start catch_test_case_registry_impl.cpp
+
+#include <algorithm>
+#include <sstream>
+
+namespace Catch {
+
+    namespace {
+        struct TestHasher {
+            using hash_t = uint64_t;
+
+            explicit TestHasher( hash_t hashSuffix ):
+                m_hashSuffix{ hashSuffix } {}
+
+            uint32_t operator()( TestCase const& t ) const {
+                // FNV-1a hash with multiplication fold.
+                const hash_t prime = 1099511628211u;
+                hash_t hash = 14695981039346656037u;
+                for ( const char c : t.name ) {
+                    hash ^= c;
+                    hash *= prime;
+                }
+                hash ^= m_hashSuffix;
+                hash *= prime;
+                const uint32_t low{ static_cast<uint32_t>( hash ) };
+                const uint32_t high{ static_cast<uint32_t>( hash >> 32 ) };
+                return low * high;
+            }
+
+        private:
+            hash_t m_hashSuffix;
+        };
+    } // end unnamed namespace
+
+    std::vector<TestCase> sortTests( IConfig const& config, std::vector<TestCase> const& unsortedTestCases ) {
+        switch( config.runOrder() ) {
+            case RunTests::InDeclarationOrder:
+                // already in declaration order
+                break;
+
+            case RunTests::InLexicographicalOrder: {
+                std::vector<TestCase> sorted = unsortedTestCases;
+                std::sort( sorted.begin(), sorted.end() );
+                return sorted;
+            }
+
+            case RunTests::InRandomOrder: {
+                seedRng( config );
+                TestHasher h{ config.rngSeed() };
+
+                using hashedTest = std::pair<TestHasher::hash_t, TestCase const*>;
+                std::vector<hashedTest> indexed_tests;
+                indexed_tests.reserve( unsortedTestCases.size() );
+
+                for (auto const& testCase : unsortedTestCases) {
+                    indexed_tests.emplace_back(h(testCase), &testCase);
+                }
+
+                std::sort(indexed_tests.begin(), indexed_tests.end(),
+                          [](hashedTest const& lhs, hashedTest const& rhs) {
+                          if (lhs.first == rhs.first) {
+                              return lhs.second->name < rhs.second->name;
+                          }
+                          return lhs.first < rhs.first;
+                });
+
+                std::vector<TestCase> sorted;
+                sorted.reserve( indexed_tests.size() );
+
+                for (auto const& hashed : indexed_tests) {
+                    sorted.emplace_back(*hashed.second);
+                }
+
+                return sorted;
+            }
+        }
+        return unsortedTestCases;
+    }
+
+    bool isThrowSafe( TestCase const& testCase, IConfig const& config ) {
+        return !testCase.throws() || config.allowThrows();
+    }
+
+    bool matchTest( TestCase const& testCase, TestSpec const& testSpec, IConfig const& config ) {
+        return testSpec.matches( testCase ) && isThrowSafe( testCase, config );
+    }
+
+    void enforceNoDuplicateTestCases( std::vector<TestCase> const& functions ) {
+        std::set<TestCase> seenFunctions;
+        for( auto const& function : functions ) {
+            auto prev = seenFunctions.insert( function );
+            CATCH_ENFORCE( prev.second,
+                    "error: TEST_CASE( \"" << function.name << "\" ) already defined.\n"
+                    << "\tFirst seen at " << prev.first->getTestCaseInfo().lineInfo << "\n"
+                    << "\tRedefined at " << function.getTestCaseInfo().lineInfo );
+        }
+    }
+
+    std::vector<TestCase> filterTests( std::vector<TestCase> const& testCases, TestSpec const& testSpec, IConfig const& config ) {
+        std::vector<TestCase> filtered;
+        filtered.reserve( testCases.size() );
+        for (auto const& testCase : testCases) {
+            if ((!testSpec.hasFilters() && !testCase.isHidden()) ||
+                (testSpec.hasFilters() && matchTest(testCase, testSpec, config))) {
+                filtered.push_back(testCase);
+            }
+        }
+        return filtered;
+    }
+    std::vector<TestCase> const& getAllTestCasesSorted( IConfig const& config ) {
+        return getRegistryHub().getTestCaseRegistry().getAllTestsSorted( config );
+    }
+
+    void TestRegistry::registerTest( TestCase const& testCase ) {
+        std::string name = testCase.getTestCaseInfo().name;
+        if( name.empty() ) {
+            ReusableStringStream rss;
+            rss << "Anonymous test case " << ++m_unnamedCount;
+            return registerTest( testCase.withName( rss.str() ) );
+        }
+        m_functions.push_back( testCase );
+    }
+
+    std::vector<TestCase> const& TestRegistry::getAllTests() const {
+        return m_functions;
+    }
+    std::vector<TestCase> const& TestRegistry::getAllTestsSorted( IConfig const& config ) const {
+        if( m_sortedFunctions.empty() )
+            enforceNoDuplicateTestCases( m_functions );
+
+        if(  m_currentSortOrder != config.runOrder() || m_sortedFunctions.empty() ) {
+            m_sortedFunctions = sortTests( config, m_functions );
+            m_currentSortOrder = config.runOrder();
+        }
+        return m_sortedFunctions;
+    }
+
+    ///////////////////////////////////////////////////////////////////////////
+    TestInvokerAsFunction::TestInvokerAsFunction( void(*testAsFunction)() ) noexcept : m_testAsFunction( testAsFunction ) {}
+
+    void TestInvokerAsFunction::invoke() const {
+        m_testAsFunction();
+    }
+
+    std::string extractClassName( StringRef const& classOrQualifiedMethodName ) {
+        std::string className(classOrQualifiedMethodName);
+        if( startsWith( className, '&' ) )
+        {
+            std::size_t lastColons = className.rfind( "::" );
+            std::size_t penultimateColons = className.rfind( "::", lastColons-1 );
+            if( penultimateColons == std::string::npos )
+                penultimateColons = 1;
+            className = className.substr( penultimateColons, lastColons-penultimateColons );
+        }
+        return className;
+    }
+
+} // end namespace Catch
+// end catch_test_case_registry_impl.cpp
+// start catch_test_case_tracker.cpp
+
+#include <algorithm>
+#include <cassert>
+#include <stdexcept>
+#include <memory>
+#include <sstream>
+
+#if defined(__clang__)
+#    pragma clang diagnostic push
+#    pragma clang diagnostic ignored "-Wexit-time-destructors"
+#endif
+
+namespace Catch {
+namespace TestCaseTracking {
+
+    NameAndLocation::NameAndLocation( std::string const& _name, SourceLineInfo const& _location )
+    :   name( _name ),
+        location( _location )
+    {}
+
+    ITracker::~ITracker() = default;
+
+    ITracker& TrackerContext::startRun() {
+        m_rootTracker = std::make_shared<SectionTracker>( NameAndLocation( "{root}", CATCH_INTERNAL_LINEINFO ), *this, nullptr );
+        m_currentTracker = nullptr;
+        m_runState = Executing;
+        return *m_rootTracker;
+    }
+
+    void TrackerContext::endRun() {
+        m_rootTracker.reset();
+        m_currentTracker = nullptr;
+        m_runState = NotStarted;
+    }
+
+    void TrackerContext::startCycle() {
+        m_currentTracker = m_rootTracker.get();
+        m_runState = Executing;
+    }
+    void TrackerContext::completeCycle() {
+        m_runState = CompletedCycle;
+    }
+
+    bool TrackerContext::completedCycle() const {
+        return m_runState == CompletedCycle;
+    }
+    ITracker& TrackerContext::currentTracker() {
+        return *m_currentTracker;
+    }
+    void TrackerContext::setCurrentTracker( ITracker* tracker ) {
+        m_currentTracker = tracker;
+    }
+
+    TrackerBase::TrackerBase( NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent ):
+        ITracker(nameAndLocation),
+        m_ctx( ctx ),
+        m_parent( parent )
+    {}
+
+    bool TrackerBase::isComplete() const {
+        return m_runState == CompletedSuccessfully || m_runState == Failed;
+    }
+    bool TrackerBase::isSuccessfullyCompleted() const {
+        return m_runState == CompletedSuccessfully;
+    }
+    bool TrackerBase::isOpen() const {
+        return m_runState != NotStarted && !isComplete();
+    }
+    bool TrackerBase::hasChildren() const {
+        return !m_children.empty();
+    }
+
+    void TrackerBase::addChild( ITrackerPtr const& child ) {
+        m_children.push_back( child );
+    }
+
+    ITrackerPtr TrackerBase::findChild( NameAndLocation const& nameAndLocation ) {
+        auto it = std::find_if( m_children.begin(), m_children.end(),
+            [&nameAndLocation]( ITrackerPtr const& tracker ){
+                return
+                    tracker->nameAndLocation().location == nameAndLocation.location &&
+                    tracker->nameAndLocation().name == nameAndLocation.name;
+            } );
+        return( it != m_children.end() )
+            ? *it
+            : nullptr;
+    }
+    ITracker& TrackerBase::parent() {
+        assert( m_parent ); // Should always be non-null except for root
+        return *m_parent;
+    }
+
+    void TrackerBase::openChild() {
+        if( m_runState != ExecutingChildren ) {
+            m_runState = ExecutingChildren;
+            if( m_parent )
+                m_parent->openChild();
+        }
+    }
+
+    bool TrackerBase::isSectionTracker() const { return false; }
+    bool TrackerBase::isGeneratorTracker() const { return false; }
+
+    void TrackerBase::open() {
+        m_runState = Executing;
+        moveToThis();
+        if( m_parent )
+            m_parent->openChild();
+    }
+
+    void TrackerBase::close() {
+
+        // Close any still open children (e.g. generators)
+        while( &m_ctx.currentTracker() != this )
+            m_ctx.currentTracker().close();
+
+        switch( m_runState ) {
+            case NeedsAnotherRun:
+                break;
+
+            case Executing:
+                m_runState = CompletedSuccessfully;
+                break;
+            case ExecutingChildren:
+                if( std::all_of(m_children.begin(), m_children.end(), [](ITrackerPtr const& t){ return t->isComplete(); }) )
+                    m_runState = CompletedSuccessfully;
+                break;
+
+            case NotStarted:
+            case CompletedSuccessfully:
+            case Failed:
+                CATCH_INTERNAL_ERROR( "Illogical state: " << m_runState );
+
+            default:
+                CATCH_INTERNAL_ERROR( "Unknown state: " << m_runState );
+        }
+        moveToParent();
+        m_ctx.completeCycle();
+    }
+    void TrackerBase::fail() {
+        m_runState = Failed;
+        if( m_parent )
+            m_parent->markAsNeedingAnotherRun();
+        moveToParent();
+        m_ctx.completeCycle();
+    }
+    void TrackerBase::markAsNeedingAnotherRun() {
+        m_runState = NeedsAnotherRun;
+    }
+
+    void TrackerBase::moveToParent() {
+        assert( m_parent );
+        m_ctx.setCurrentTracker( m_parent );
+    }
+    void TrackerBase::moveToThis() {
+        m_ctx.setCurrentTracker( this );
+    }
+
+    SectionTracker::SectionTracker( NameAndLocation const& nameAndLocation, TrackerContext& ctx, ITracker* parent )
+    :   TrackerBase( nameAndLocation, ctx, parent ),
+        m_trimmed_name(trim(nameAndLocation.name))
+    {
+        if( parent ) {
+            while( !parent->isSectionTracker() )
+                parent = &parent->parent();
+
+            SectionTracker& parentSection = static_cast<SectionTracker&>( *parent );
+            addNextFilters( parentSection.m_filters );
+        }
+    }
+
+    bool SectionTracker::isComplete() const {
+        bool complete = true;
+
+        if (m_filters.empty()
+            || m_filters[0] == ""
+            || std::find(m_filters.begin(), m_filters.end(), m_trimmed_name) != m_filters.end()) {
+            complete = TrackerBase::isComplete();
+        }
+        return complete;
+    }
+
+    bool SectionTracker::isSectionTracker() const { return true; }
+
+    SectionTracker& SectionTracker::acquire( TrackerContext& ctx, NameAndLocation const& nameAndLocation ) {
+        std::shared_ptr<SectionTracker> section;
+
+        ITracker& currentTracker = ctx.currentTracker();
+        if( ITrackerPtr childTracker = currentTracker.findChild( nameAndLocation ) ) {
+            assert( childTracker );
+            assert( childTracker->isSectionTracker() );
+            section = std::static_pointer_cast<SectionTracker>( childTracker );
+        }
+        else {
+            section = std::make_shared<SectionTracker>( nameAndLocation, ctx, &currentTracker );
+            currentTracker.addChild( section );
+        }
+        if( !ctx.completedCycle() )
+            section->tryOpen();
+        return *section;
+    }
+
+    void SectionTracker::tryOpen() {
+        if( !isComplete() )
+            open();
+    }
+
+    void SectionTracker::addInitialFilters( std::vector<std::string> const& filters ) {
+        if( !filters.empty() ) {
+            m_filters.reserve( m_filters.size() + filters.size() + 2 );
+            m_filters.emplace_back(""); // Root - should never be consulted
+            m_filters.emplace_back(""); // Test Case - not a section filter
+            m_filters.insert( m_filters.end(), filters.begin(), filters.end() );
+        }
+    }
+    void SectionTracker::addNextFilters( std::vector<std::string> const& filters ) {
+        if( filters.size() > 1 )
+            m_filters.insert( m_filters.end(), filters.begin()+1, filters.end() );
+    }
+
+    std::vector<std::string> const& SectionTracker::getFilters() const {
+        return m_filters;
+    }
+
+    std::string const& SectionTracker::trimmedName() const {
+        return m_trimmed_name;
+    }
+
+} // namespace TestCaseTracking
+
+using TestCaseTracking::ITracker;
+using TestCaseTracking::TrackerContext;
+using TestCaseTracking::SectionTracker;
+
+} // namespace Catch
+
+#if defined(__clang__)
+#    pragma clang diagnostic pop
+#endif
+// end catch_test_case_tracker.cpp
+// start catch_test_registry.cpp
+
+namespace Catch {
+
+    auto makeTestInvoker( void(*testAsFunction)() ) noexcept -> ITestInvoker* {
+        return new(std::nothrow) TestInvokerAsFunction( testAsFunction );
+    }
+
+    NameAndTags::NameAndTags( StringRef const& name_ , StringRef const& tags_ ) noexcept : name( name_ ), tags( tags_ ) {}
+
+    AutoReg::AutoReg( ITestInvoker* invoker, SourceLineInfo const& lineInfo, StringRef const& classOrMethod, NameAndTags const& nameAndTags ) noexcept {
+        CATCH_TRY {
+            getMutableRegistryHub()
+                    .registerTest(
+                        makeTestCase(
+                            invoker,
+                            extractClassName( classOrMethod ),
+                            nameAndTags,
+                            lineInfo));
+        } CATCH_CATCH_ALL {
+            // Do not throw when constructing global objects, instead register the exception to be processed later
+            getMutableRegistryHub().registerStartupException();
+        }
+    }
+
+    AutoReg::~AutoReg() = default;
+}
+// end catch_test_registry.cpp
+// start catch_test_spec.cpp
+
+#include <algorithm>
+#include <string>
+#include <vector>
+#include <memory>
+
+namespace Catch {
+
+    TestSpec::Pattern::Pattern( std::string const& name )
+    : m_name( name )
+    {}
+
+    TestSpec::Pattern::~Pattern() = default;
+
+    std::string const& TestSpec::Pattern::name() const {
+        return m_name;
+    }
+
+    TestSpec::NamePattern::NamePattern( std::string const& name, std::string const& filterString )
+    : Pattern( filterString )
+    , m_wildcardPattern( toLower( name ), CaseSensitive::No )
+    {}
+
+    bool TestSpec::NamePattern::matches( TestCaseInfo const& testCase ) const {
+        return m_wildcardPattern.matches( testCase.name );
+    }
+
+    TestSpec::TagPattern::TagPattern( std::string const& tag, std::string const& filterString )
+    : Pattern( filterString )
+    , m_tag( toLower( tag ) )
+    {}
+
+    bool TestSpec::TagPattern::matches( TestCaseInfo const& testCase ) const {
+        return std::find(begin(testCase.lcaseTags),
+                         end(testCase.lcaseTags),
+                         m_tag) != end(testCase.lcaseTags);
+    }
+
+    TestSpec::ExcludedPattern::ExcludedPattern( PatternPtr const& underlyingPattern )
+    : Pattern( underlyingPattern->name() )
+    , m_underlyingPattern( underlyingPattern )
+    {}
+
+    bool TestSpec::ExcludedPattern::matches( TestCaseInfo const& testCase ) const {
+        return !m_underlyingPattern->matches( testCase );
+    }
+
+    bool TestSpec::Filter::matches( TestCaseInfo const& testCase ) const {
+        return std::all_of( m_patterns.begin(), m_patterns.end(), [&]( PatternPtr const& p ){ return p->matches( testCase ); } );
+    }
+
+    std::string TestSpec::Filter::name() const {
+        std::string name;
+        for( auto const& p : m_patterns )
+            name += p->name();
+        return name;
+    }
+
+    bool TestSpec::hasFilters() const {
+        return !m_filters.empty();
+    }
+
+    bool TestSpec::matches( TestCaseInfo const& testCase ) const {
+        return std::any_of( m_filters.begin(), m_filters.end(), [&]( Filter const& f ){ return f.matches( testCase ); } );
+    }
+
+    TestSpec::Matches TestSpec::matchesByFilter( std::vector<TestCase> const& testCases, IConfig const& config ) const
+    {
+        Matches matches( m_filters.size() );
+        std::transform( m_filters.begin(), m_filters.end(), matches.begin(), [&]( Filter const& filter ){
+            std::vector<TestCase const*> currentMatches;
+            for( auto const& test : testCases )
+                if( isThrowSafe( test, config ) && filter.matches( test ) )
+                    currentMatches.emplace_back( &test );
+            return FilterMatch{ filter.name(), currentMatches };
+        } );
+        return matches;
+    }
+
+    const TestSpec::vectorStrings& TestSpec::getInvalidArgs() const{
+        return  (m_invalidArgs);
+    }
+
+}
+// end catch_test_spec.cpp
+// start catch_test_spec_parser.cpp
+
+namespace Catch {
+
+    TestSpecParser::TestSpecParser( ITagAliasRegistry const& tagAliases ) : m_tagAliases( &tagAliases ) {}
+
+    TestSpecParser& TestSpecParser::parse( std::string const& arg ) {
+        m_mode = None;
+        m_exclusion = false;
+        m_arg = m_tagAliases->expandAliases( arg );
+        m_escapeChars.clear();
+        m_substring.reserve(m_arg.size());
+        m_patternName.reserve(m_arg.size());
+        m_realPatternPos = 0;
+
+        for( m_pos = 0; m_pos < m_arg.size(); ++m_pos )
+          //if visitChar fails
+           if( !visitChar( m_arg[m_pos] ) ){
+               m_testSpec.m_invalidArgs.push_back(arg);
+               break;
+           }
+        endMode();
+        return *this;
+    }
+    TestSpec TestSpecParser::testSpec() {
+        addFilter();
+        return m_testSpec;
+    }
+    bool TestSpecParser::visitChar( char c ) {
+        if( (m_mode != EscapedName) && (c == '\\') ) {
+            escape();
+            addCharToPattern(c);
+            return true;
+        }else if((m_mode != EscapedName) && (c == ',') )  {
+            return separate();
+        }
+
+        switch( m_mode ) {
+        case None:
+            if( processNoneChar( c ) )
+                return true;
+            break;
+        case Name:
+            processNameChar( c );
+            break;
+        case EscapedName:
+            endMode();
+            addCharToPattern(c);
+            return true;
+        default:
+        case Tag:
+        case QuotedName:
+            if( processOtherChar( c ) )
+                return true;
+            break;
+        }
+
+        m_substring += c;
+        if( !isControlChar( c ) ) {
+            m_patternName += c;
+            m_realPatternPos++;
+        }
+        return true;
+    }
+    // Two of the processing methods return true to signal the caller to return
+    // without adding the given character to the current pattern strings
+    bool TestSpecParser::processNoneChar( char c ) {
+        switch( c ) {
+        case ' ':
+            return true;
+        case '~':
+            m_exclusion = true;
+            return false;
+        case '[':
+            startNewMode( Tag );
+            return false;
+        case '"':
+            startNewMode( QuotedName );
+            return false;
+        default:
+            startNewMode( Name );
+            return false;
+        }
+    }
+    void TestSpecParser::processNameChar( char c ) {
+        if( c == '[' ) {
+            if( m_substring == "exclude:" )
+                m_exclusion = true;
+            else
+                endMode();
+            startNewMode( Tag );
+        }
+    }
+    bool TestSpecParser::processOtherChar( char c ) {
+        if( !isControlChar( c ) )
+            return false;
+        m_substring += c;
+        endMode();
+        return true;
+    }
+    void TestSpecParser::startNewMode( Mode mode ) {
+        m_mode = mode;
+    }
+    void TestSpecParser::endMode() {
+        switch( m_mode ) {
+        case Name:
+        case QuotedName:
+            return addNamePattern();
+        case Tag:
+            return addTagPattern();
+        case EscapedName:
+            revertBackToLastMode();
+            return;
+        case None:
+        default:
+            return startNewMode( None );
+        }
+    }
+    void TestSpecParser::escape() {
+        saveLastMode();
+        m_mode = EscapedName;
+        m_escapeChars.push_back(m_realPatternPos);
+    }
+    bool TestSpecParser::isControlChar( char c ) const {
+        switch( m_mode ) {
+            default:
+                return false;
+            case None:
+                return c == '~';
+            case Name:
+                return c == '[';
+            case EscapedName:
+                return true;
+            case QuotedName:
+                return c == '"';
+            case Tag:
+                return c == '[' || c == ']';
+        }
+    }
+
+    void TestSpecParser::addFilter() {
+        if( !m_currentFilter.m_patterns.empty() ) {
+            m_testSpec.m_filters.push_back( m_currentFilter );
+            m_currentFilter = TestSpec::Filter();
+        }
+    }
+
+    void TestSpecParser::saveLastMode() {
+      lastMode = m_mode;
+    }
+
+    void TestSpecParser::revertBackToLastMode() {
+      m_mode = lastMode;
+    }
+
+    bool TestSpecParser::separate() {
+      if( (m_mode==QuotedName) || (m_mode==Tag) ){
+         //invalid argument, signal failure to previous scope.
+         m_mode = None;
+         m_pos = m_arg.size();
+         m_substring.clear();
+         m_patternName.clear();
+         m_realPatternPos = 0;
+         return false;
+      }
+      endMode();
+      addFilter();
+      return true; //success
+    }
+
+    std::string TestSpecParser::preprocessPattern() {
+        std::string token = m_patternName;
+        for (std::size_t i = 0; i < m_escapeChars.size(); ++i)
+            token = token.substr(0, m_escapeChars[i] - i) + token.substr(m_escapeChars[i] - i + 1);
+        m_escapeChars.clear();
+        if (startsWith(token, "exclude:")) {
+            m_exclusion = true;
+            token = token.substr(8);
+        }
+
+        m_patternName.clear();
+        m_realPatternPos = 0;
+
+        return token;
+    }
+
+    void TestSpecParser::addNamePattern() {
+        auto token = preprocessPattern();
+
+        if (!token.empty()) {
+            TestSpec::PatternPtr pattern = std::make_shared<TestSpec::NamePattern>(token, m_substring);
+            if (m_exclusion)
+                pattern = std::make_shared<TestSpec::ExcludedPattern>(pattern);
+            m_currentFilter.m_patterns.push_back(pattern);
+        }
+        m_substring.clear();
+        m_exclusion = false;
+        m_mode = None;
+    }
+
+    void TestSpecParser::addTagPattern() {
+        auto token = preprocessPattern();
+
+        if (!token.empty()) {
+            // If the tag pattern is the "hide and tag" shorthand (e.g. [.foo])
+            // we have to create a separate hide tag and shorten the real one
+            if (token.size() > 1 && token[0] == '.') {
+                token.erase(token.begin());
+                TestSpec::PatternPtr pattern = std::make_shared<TestSpec::TagPattern>(".", m_substring);
+                if (m_exclusion) {
+                    pattern = std::make_shared<TestSpec::ExcludedPattern>(pattern);
+                }
+                m_currentFilter.m_patterns.push_back(pattern);
+            }
+
+            TestSpec::PatternPtr pattern = std::make_shared<TestSpec::TagPattern>(token, m_substring);
+
+            if (m_exclusion) {
+                pattern = std::make_shared<TestSpec::ExcludedPattern>(pattern);
+            }
+            m_currentFilter.m_patterns.push_back(pattern);
+        }
+        m_substring.clear();
+        m_exclusion = false;
+        m_mode = None;
+    }
+
+    TestSpec parseTestSpec( std::string const& arg ) {
+        return TestSpecParser( ITagAliasRegistry::get() ).parse( arg ).testSpec();
+    }
+
+} // namespace Catch
+// end catch_test_spec_parser.cpp
+// start catch_timer.cpp
+
+#include <chrono>
+
+static const uint64_t nanosecondsInSecond = 1000000000;
+
+namespace Catch {
+
+    auto getCurrentNanosecondsSinceEpoch() -> uint64_t {
+        return std::chrono::duration_cast<std::chrono::nanoseconds>( std::chrono::high_resolution_clock::now().time_since_epoch() ).count();
+    }
+
+    namespace {
+        auto estimateClockResolution() -> uint64_t {
+            uint64_t sum = 0;
+            static const uint64_t iterations = 1000000;
+
+            auto startTime = getCurrentNanosecondsSinceEpoch();
+
+            for( std::size_t i = 0; i < iterations; ++i ) {
+
+                uint64_t ticks;
+                uint64_t baseTicks = getCurrentNanosecondsSinceEpoch();
+                do {
+                    ticks = getCurrentNanosecondsSinceEpoch();
+                } while( ticks == baseTicks );
+
+                auto delta = ticks - baseTicks;
+                sum += delta;
+
+                // If we have been calibrating for over 3 seconds -- the clock
+                // is terrible and we should move on.
+                // TBD: How to signal that the measured resolution is probably wrong?
+                if (ticks > startTime + 3 * nanosecondsInSecond) {
+                    return sum / ( i + 1u );
+                }
+            }
+
+            // We're just taking the mean, here. To do better we could take the std. dev and exclude outliers
+            // - and potentially do more iterations if there's a high variance.
+            return sum/iterations;
+        }
+    }
+    auto getEstimatedClockResolution() -> uint64_t {
+        static auto s_resolution = estimateClockResolution();
+        return s_resolution;
+    }
+
+    void Timer::start() {
+       m_nanoseconds = getCurrentNanosecondsSinceEpoch();
+    }
+    auto Timer::getElapsedNanoseconds() const -> uint64_t {
+        return getCurrentNanosecondsSinceEpoch() - m_nanoseconds;
+    }
+    auto Timer::getElapsedMicroseconds() const -> uint64_t {
+        return getElapsedNanoseconds()/1000;
+    }
+    auto Timer::getElapsedMilliseconds() const -> unsigned int {
+        return static_cast<unsigned int>(getElapsedMicroseconds()/1000);
+    }
+    auto Timer::getElapsedSeconds() const -> double {
+        return getElapsedMicroseconds()/1000000.0;
+    }
+
+} // namespace Catch
+// end catch_timer.cpp
+// start catch_tostring.cpp
+
+#if defined(__clang__)
+#    pragma clang diagnostic push
+#    pragma clang diagnostic ignored "-Wexit-time-destructors"
+#    pragma clang diagnostic ignored "-Wglobal-constructors"
+#endif
+
+// Enable specific decls locally
+#if !defined(CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER)
+#define CATCH_CONFIG_ENABLE_CHRONO_STRINGMAKER
+#endif
+
+#include <cmath>
+#include <iomanip>
+
+namespace Catch {
+
+namespace Detail {
+
+    const std::string unprintableString = "{?}";
+
+    namespace {
+        const int hexThreshold = 255;
+
+        struct Endianness {
+            enum Arch { Big, Little };
+
+            static Arch which() {
+                int one = 1;
+                // If the lowest byte we read is non-zero, we can assume
+                // that little endian format is used.
+                auto value = *reinterpret_cast<char*>(&one);
+                return value ? Little : Big;
+            }
+        };
+    }
+
+    std::string rawMemoryToString( const void *object, std::size_t size ) {
+        // Reverse order for little endian architectures
+        int i = 0, end = static_cast<int>( size ), inc = 1;
+        if( Endianness::which() == Endianness::Little ) {
+            i = end-1;
+            end = inc = -1;
+        }
+
+        unsigned char const *bytes = static_cast<unsigned char const *>(object);
+        ReusableStringStream rss;
+        rss << "0x" << std::setfill('0') << std::hex;
+        for( ; i != end; i += inc )
+             rss << std::setw(2) << static_cast<unsigned>(bytes[i]);
+       return rss.str();
+    }
+}
+
+template<typename T>
+std::string fpToString( T value, int precision ) {
+    if (Catch::isnan(value)) {
+        return "nan";
+    }
+
+    ReusableStringStream rss;
+    rss << std::setprecision( precision )
+        << std::fixed
+        << value;
+    std::string d = rss.str();
+    std::size_t i = d.find_last_not_of( '0' );
+    if( i != std::string::npos && i != d.size()-1 ) {
+        if( d[i] == '.' )
+            i++;
+        d = d.substr( 0, i+1 );
+    }
+    return d;
+}
+
+//// ======================================================= ////
+//
+//   Out-of-line defs for full specialization of StringMaker
+//
+//// ======================================================= ////
+
+std::string StringMaker<std::string>::convert(const std::string& str) {
+    if (!getCurrentContext().getConfig()->showInvisibles()) {
+        return '"' + str + '"';
+    }
+
+    std::string s("\"");
+    for (char c : str) {
+        switch (c) {
+        case '\n':
+            s.append("\\n");
+            break;
+        case '\t':
+            s.append("\\t");
+            break;
+        default:
+            s.push_back(c);
+            break;
+        }
+    }
+    s.append("\"");
+    return s;
+}
+
+#ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+std::string StringMaker<std::string_view>::convert(std::string_view str) {
+    return ::Catch::Detail::stringify(std::string{ str });
+}
+#endif
+
+std::string StringMaker<char const*>::convert(char const* str) {
+    if (str) {
+        return ::Catch::Detail::stringify(std::string{ str });
+    } else {
+        return{ "{null string}" };
+    }
+}
+std::string StringMaker<char*>::convert(char* str) {
+    if (str) {
+        return ::Catch::Detail::stringify(std::string{ str });
+    } else {
+        return{ "{null string}" };
+    }
+}
+
+#ifdef CATCH_CONFIG_WCHAR
+std::string StringMaker<std::wstring>::convert(const std::wstring& wstr) {
+    std::string s;
+    s.reserve(wstr.size());
+    for (auto c : wstr) {
+        s += (c <= 0xff) ? static_cast<char>(c) : '?';
+    }
+    return ::Catch::Detail::stringify(s);
+}
+
+# ifdef CATCH_CONFIG_CPP17_STRING_VIEW
+std::string StringMaker<std::wstring_view>::convert(std::wstring_view str) {
+    return StringMaker<std::wstring>::convert(std::wstring(str));
+}
+# endif
+
+std::string StringMaker<wchar_t const*>::convert(wchar_t const * str) {
+    if (str) {
+        return ::Catch::Detail::stringify(std::wstring{ str });
+    } else {
+        return{ "{null string}" };
+    }
+}
+std::string StringMaker<wchar_t *>::convert(wchar_t * str) {
+    if (str) {
+        return ::Catch::Detail::stringify(std::wstring{ str });
+    } else {
+        return{ "{null string}" };
+    }
+}
+#endif
+
+#if defined(CATCH_CONFIG_CPP17_BYTE)
+#include <cstddef>
+std::string StringMaker<std::byte>::convert(std::byte value) {
+    return ::Catch::Detail::stringify(std::to_integer<unsigned long long>(value));
+}
+#endif // defined(CATCH_CONFIG_CPP17_BYTE)
+
+std::string StringMaker<int>::convert(int value) {
+    return ::Catch::Detail::stringify(static_cast<long long>(value));
+}
+std::string StringMaker<long>::convert(long value) {
+    return ::Catch::Detail::stringify(static_cast<long long>(value));
+}
+std::string StringMaker<long long>::convert(long long value) {
+    ReusableStringStream rss;
+    rss << value;
+    if (value > Detail::hexThreshold) {
+        rss << " (0x" << std::hex << value << ')';
+    }
+    return rss.str();
+}
+
+std::string StringMaker<unsigned int>::convert(unsigned int value) {
+    return ::Catch::Detail::stringify(static_cast<unsigned long long>(value));
+}
+std::string StringMaker<unsigned long>::convert(unsigned long value) {
+    return ::Catch::Detail::stringify(static_cast<unsigned long long>(value));
+}
+std::string StringMaker<unsigned long long>::convert(unsigned long long value) {
+    ReusableStringStream rss;
+    rss << value;
+    if (value > Detail::hexThreshold) {
+        rss << " (0x" << std::hex << value << ')';
+    }
+    return rss.str();
+}
+
+std::string StringMaker<bool>::convert(bool b) {
+    return b ? "true" : "false";
+}
+
+std::string StringMaker<signed char>::convert(signed char value) {
+    if (value == '\r') {
+        return "'\\r'";
+    } else if (value == '\f') {
+        return "'\\f'";
+    } else if (value == '\n') {
+        return "'\\n'";
+    } else if (value == '\t') {
+        return "'\\t'";
+    } else if ('\0' <= value && value < ' ') {
+        return ::Catch::Detail::stringify(static_cast<unsigned int>(value));
+    } else {
+        char chstr[] = "' '";
+        chstr[1] = value;
+        return chstr;
+    }
+}
+std::string StringMaker<char>::convert(char c) {
+    return ::Catch::Detail::stringify(static_cast<signed char>(c));
+}
+std::string StringMaker<unsigned char>::convert(unsigned char c) {
+    return ::Catch::Detail::stringify(static_cast<char>(c));
+}
+
+std::string StringMaker<std::nullptr_t>::convert(std::nullptr_t) {
+    return "nullptr";
+}
+
+int StringMaker<float>::precision = 5;
+
+std::string StringMaker<float>::convert(float value) {
+    return fpToString(value, precision) + 'f';
+}
+
+int StringMaker<double>::precision = 10;
+
+std::string StringMaker<double>::convert(double value) {
+    return fpToString(value, precision);
+}
+
+std::string ratio_string<std::atto>::symbol() { return "a"; }
+std::string ratio_string<std::femto>::symbol() { return "f"; }
+std::string ratio_string<std::pico>::symbol() { return "p"; }
+std::string ratio_string<std::nano>::symbol() { return "n"; }
+std::string ratio_string<std::micro>::symbol() { return "u"; }
+std::string ratio_string<std::milli>::symbol() { return "m"; }
+
+} // end namespace Catch
+
+#if defined(__clang__)
+#    pragma clang diagnostic pop
+#endif
+
+// end catch_tostring.cpp
+// start catch_totals.cpp
+
+namespace Catch {
+
+    Counts Counts::operator - ( Counts const& other ) const {
+        Counts diff;
+        diff.passed = passed - other.passed;
+        diff.failed = failed - other.failed;
+        diff.failedButOk = failedButOk - other.failedButOk;
+        return diff;
+    }
+
+    Counts& Counts::operator += ( Counts const& other ) {
+        passed += other.passed;
+        failed += other.failed;
+        failedButOk += other.failedButOk;
+        return *this;
+    }
+
+    std::size_t Counts::total() const {
+        return passed + failed + failedButOk;
+    }
+    bool Counts::allPassed() const {
+        return failed == 0 && failedButOk == 0;
+    }
+    bool Counts::allOk() const {
+        return failed == 0;
+    }
+
+    Totals Totals::operator - ( Totals const& other ) const {
+        Totals diff;
+        diff.assertions = assertions - other.assertions;
+        diff.testCases = testCases - other.testCases;
+        return diff;
+    }
+
+    Totals& Totals::operator += ( Totals const& other ) {
+        assertions += other.assertions;
+        testCases += other.testCases;
+        return *this;
+    }
+
+    Totals Totals::delta( Totals const& prevTotals ) const {
+        Totals diff = *this - prevTotals;
+        if( diff.assertions.failed > 0 )
+            ++diff.testCases.failed;
+        else if( diff.assertions.failedButOk > 0 )
+            ++diff.testCases.failedButOk;
+        else
+            ++diff.testCases.passed;
+        return diff;
+    }
+
+}
+// end catch_totals.cpp
+// start catch_uncaught_exceptions.cpp
+
+// start catch_config_uncaught_exceptions.hpp
+
+//              Copyright Catch2 Authors
+// Distributed under the Boost Software License, Version 1.0.
+//   (See accompanying file LICENSE_1_0.txt or copy at
+//        https://www.boost.org/LICENSE_1_0.txt)
+
+// SPDX-License-Identifier: BSL-1.0
+
+#ifndef CATCH_CONFIG_UNCAUGHT_EXCEPTIONS_HPP
+#define CATCH_CONFIG_UNCAUGHT_EXCEPTIONS_HPP
+
+#if defined(_MSC_VER)
+#  if _MSC_VER >= 1900 // Visual Studio 2015 or newer
+#    define CATCH_INTERNAL_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS
+#  endif
+#endif
+
+#include <exception>
+
+#if defined(__cpp_lib_uncaught_exceptions) \
+    && !defined(CATCH_INTERNAL_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS)
+
+#  define CATCH_INTERNAL_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS
+#endif // __cpp_lib_uncaught_exceptions
+
+#if defined(CATCH_INTERNAL_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS) \
+    && !defined(CATCH_CONFIG_NO_CPP17_UNCAUGHT_EXCEPTIONS) \
+    && !defined(CATCH_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS)
+
+#  define CATCH_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS
+#endif
+
+#endif // CATCH_CONFIG_UNCAUGHT_EXCEPTIONS_HPP
+// end catch_config_uncaught_exceptions.hpp
+#include <exception>
+
+namespace Catch {
+    bool uncaught_exceptions() {
+#if defined(CATCH_CONFIG_DISABLE_EXCEPTIONS)
+        return false;
+#elif defined(CATCH_CONFIG_CPP17_UNCAUGHT_EXCEPTIONS)
+        return std::uncaught_exceptions() > 0;
+#else
+        return std::uncaught_exception();
+#endif
+  }
+} // end namespace Catch
+// end catch_uncaught_exceptions.cpp
+// start catch_version.cpp
+
+#include <ostream>
+
+namespace Catch {
+
+    Version::Version
+        (   unsigned int _majorVersion,
+            unsigned int _minorVersion,
+            unsigned int _patchNumber,
+            char const * const _branchName,
+            unsigned int _buildNumber )
+    :   majorVersion( _majorVersion ),
+        minorVersion( _minorVersion ),
+        patchNumber( _patchNumber ),
+        branchName( _branchName ),
+        buildNumber( _buildNumber )
+    {}
+
+    std::ostream& operator << ( std::ostream& os, Version const& version ) {
+        os  << version.majorVersion << '.'
+            << version.minorVersion << '.'
+            << version.patchNumber;
+        // branchName is never null -> 0th char is \0 if it is empty
+        if (version.branchName[0]) {
+            os << '-' << version.branchName
+               << '.' << version.buildNumber;
+        }
+        return os;
+    }
+
+    Version const& libraryVersion() {
+        static Version version( 2, 13, 9, "", 0 );
+        return version;
+    }
+
+}
+// end catch_version.cpp
+// start catch_wildcard_pattern.cpp
+
+namespace Catch {
+
+    WildcardPattern::WildcardPattern( std::string const& pattern,
+                                      CaseSensitive::Choice caseSensitivity )
+    :   m_caseSensitivity( caseSensitivity ),
+        m_pattern( normaliseString( pattern ) )
+    {
+        if( startsWith( m_pattern, '*' ) ) {
+            m_pattern = m_pattern.substr( 1 );
+            m_wildcard = WildcardAtStart;
+        }
+        if( endsWith( m_pattern, '*' ) ) {
+            m_pattern = m_pattern.substr( 0, m_pattern.size()-1 );
+            m_wildcard = static_cast<WildcardPosition>( m_wildcard | WildcardAtEnd );
+        }
+    }
+
+    bool WildcardPattern::matches( std::string const& str ) const {
+        switch( m_wildcard ) {
+            case NoWildcard:
+                return m_pattern == normaliseString( str );
+            case WildcardAtStart:
+                return endsWith( normaliseString( str ), m_pattern );
+            case WildcardAtEnd:
+                return startsWith( normaliseString( str ), m_pattern );
+            case WildcardAtBothEnds:
+                return contains( normaliseString( str ), m_pattern );
+            default:
+                CATCH_INTERNAL_ERROR( "Unknown enum" );
+        }
+    }
+
+    std::string WildcardPattern::normaliseString( std::string const& str ) const {
+        return trim( m_caseSensitivity == CaseSensitive::No ? toLower( str ) : str );
+    }
+}
+// end catch_wildcard_pattern.cpp
+// start catch_xmlwriter.cpp
+
+#include <iomanip>
+#include <type_traits>
+
+namespace Catch {
+
+namespace {
+
+    size_t trailingBytes(unsigned char c) {
+        if ((c & 0xE0) == 0xC0) {
+            return 2;
+        }
+        if ((c & 0xF0) == 0xE0) {
+            return 3;
+        }
+        if ((c & 0xF8) == 0xF0) {
+            return 4;
+        }
+        CATCH_INTERNAL_ERROR("Invalid multibyte utf-8 start byte encountered");
+    }
+
+    uint32_t headerValue(unsigned char c) {
+        if ((c & 0xE0) == 0xC0) {
+            return c & 0x1F;
+        }
+        if ((c & 0xF0) == 0xE0) {
+            return c & 0x0F;
+        }
+        if ((c & 0xF8) == 0xF0) {
+            return c & 0x07;
+        }
+        CATCH_INTERNAL_ERROR("Invalid multibyte utf-8 start byte encountered");
+    }
+
+    void hexEscapeChar(std::ostream& os, unsigned char c) {
+        std::ios_base::fmtflags f(os.flags());
+        os << "\\x"
+            << std::uppercase << std::hex << std::setfill('0') << std::setw(2)
+            << static_cast<int>(c);
+        os.flags(f);
+    }
+
+    bool shouldNewline(XmlFormatting fmt) {
+        return !!(static_cast<std::underlying_type<XmlFormatting>::type>(fmt & XmlFormatting::Newline));
+    }
+
+    bool shouldIndent(XmlFormatting fmt) {
+        return !!(static_cast<std::underlying_type<XmlFormatting>::type>(fmt & XmlFormatting::Indent));
+    }
+
+} // anonymous namespace
+
+    XmlFormatting operator | (XmlFormatting lhs, XmlFormatting rhs) {
+        return static_cast<XmlFormatting>(
+            static_cast<std::underlying_type<XmlFormatting>::type>(lhs) |
+            static_cast<std::underlying_type<XmlFormatting>::type>(rhs)
+        );
+    }
+
+    XmlFormatting operator & (XmlFormatting lhs, XmlFormatting rhs) {
+        return static_cast<XmlFormatting>(
+            static_cast<std::underlying_type<XmlFormatting>::type>(lhs) &
+            static_cast<std::underlying_type<XmlFormatting>::type>(rhs)
+        );
+    }
+
+    XmlEncode::XmlEncode( std::string const& str, ForWhat forWhat )
+    :   m_str( str ),
+        m_forWhat( forWhat )
+    {}
+
+    void XmlEncode::encodeTo( std::ostream& os ) const {
+        // Apostrophe escaping not necessary if we always use " to write attributes
+        // (see: http://www.w3.org/TR/xml/#syntax)
+
+        for( std::size_t idx = 0; idx < m_str.size(); ++ idx ) {
+            unsigned char c = m_str[idx];
+            switch (c) {
+            case '<':   os << "&lt;"; break;
+            case '&':   os << "&amp;"; break;
+
+            case '>':
+                // See: http://www.w3.org/TR/xml/#syntax
+                if (idx > 2 && m_str[idx - 1] == ']' && m_str[idx - 2] == ']')
+                    os << "&gt;";
+                else
+                    os << c;
+                break;
+
+            case '\"':
+                if (m_forWhat == ForAttributes)
+                    os << "&quot;";
+                else
+                    os << c;
+                break;
+
+            default:
+                // Check for control characters and invalid utf-8
+
+                // Escape control characters in standard ascii
+                // see http://stackoverflow.com/questions/404107/why-are-control-characters-illegal-in-xml-1-0
+                if (c < 0x09 || (c > 0x0D && c < 0x20) || c == 0x7F) {
+                    hexEscapeChar(os, c);
+                    break;
+                }
+
+                // Plain ASCII: Write it to stream
+                if (c < 0x7F) {
+                    os << c;
+                    break;
+                }
+
+                // UTF-8 territory
+                // Check if the encoding is valid and if it is not, hex escape bytes.
+                // Important: We do not check the exact decoded values for validity, only the encoding format
+                // First check that this bytes is a valid lead byte:
+                // This means that it is not encoded as 1111 1XXX
+                // Or as 10XX XXXX
+                if (c <  0xC0 ||
+                    c >= 0xF8) {
+                    hexEscapeChar(os, c);
+                    break;
+                }
+
+                auto encBytes = trailingBytes(c);
+                // Are there enough bytes left to avoid accessing out-of-bounds memory?
+                if (idx + encBytes - 1 >= m_str.size()) {
+                    hexEscapeChar(os, c);
+                    break;
+                }
+                // The header is valid, check data
+                // The next encBytes bytes must together be a valid utf-8
+                // This means: bitpattern 10XX XXXX and the extracted value is sane (ish)
+                bool valid = true;
+                uint32_t value = headerValue(c);
+                for (std::size_t n = 1; n < encBytes; ++n) {
+                    unsigned char nc = m_str[idx + n];
+                    valid &= ((nc & 0xC0) == 0x80);
+                    value = (value << 6) | (nc & 0x3F);
+                }
+
+                if (
+                    // Wrong bit pattern of following bytes
+                    (!valid) ||
+                    // Overlong encodings
+                    (value < 0x80) ||
+                    (0x80 <= value && value < 0x800   && encBytes > 2) ||
+                    (0x800 < value && value < 0x10000 && encBytes > 3) ||
+                    // Encoded value out of range
+                    (value >= 0x110000)
+                    ) {
+                    hexEscapeChar(os, c);
+                    break;
+                }
+
+                // If we got here, this is in fact a valid(ish) utf-8 sequence
+                for (std::size_t n = 0; n < encBytes; ++n) {
+                    os << m_str[idx + n];
+                }
+                idx += encBytes - 1;
+                break;
+            }
+        }
+    }
+
+    std::ostream& operator << ( std::ostream& os, XmlEncode const& xmlEncode ) {
+        xmlEncode.encodeTo( os );
+        return os;
+    }
+
+    XmlWriter::ScopedElement::ScopedElement( XmlWriter* writer, XmlFormatting fmt )
+    :   m_writer( writer ),
+        m_fmt(fmt)
+    {}
+
+    XmlWriter::ScopedElement::ScopedElement( ScopedElement&& other ) noexcept
+    :   m_writer( other.m_writer ),
+        m_fmt(other.m_fmt)
+    {
+        other.m_writer = nullptr;
+        other.m_fmt = XmlFormatting::None;
+    }
+    XmlWriter::ScopedElement& XmlWriter::ScopedElement::operator=( ScopedElement&& other ) noexcept {
+        if ( m_writer ) {
+            m_writer->endElement();
+        }
+        m_writer = other.m_writer;
+        other.m_writer = nullptr;
+        m_fmt = other.m_fmt;
+        other.m_fmt = XmlFormatting::None;
+        return *this;
+    }
+
+    XmlWriter::ScopedElement::~ScopedElement() {
+        if (m_writer) {
+            m_writer->endElement(m_fmt);
+        }
+    }
+
+    XmlWriter::ScopedElement& XmlWriter::ScopedElement::writeText( std::string const& text, XmlFormatting fmt ) {
+        m_writer->writeText( text, fmt );
+        return *this;
+    }
+
+    XmlWriter::XmlWriter( std::ostream& os ) : m_os( os )
+    {
+        writeDeclaration();
+    }
+
+    XmlWriter::~XmlWriter() {
+        while (!m_tags.empty()) {
+            endElement();
+        }
+        newlineIfNecessary();
+    }
+
+    XmlWriter& XmlWriter::startElement( std::string const& name, XmlFormatting fmt ) {
+        ensureTagClosed();
+        newlineIfNecessary();
+        if (shouldIndent(fmt)) {
+            m_os << m_indent;
+            m_indent += "  ";
+        }
+        m_os << '<' << name;
+        m_tags.push_back( name );
+        m_tagIsOpen = true;
+        applyFormatting(fmt);
+        return *this;
+    }
+
+    XmlWriter::ScopedElement XmlWriter::scopedElement( std::string const& name, XmlFormatting fmt ) {
+        ScopedElement scoped( this, fmt );
+        startElement( name, fmt );
+        return scoped;
+    }
+
+    XmlWriter& XmlWriter::endElement(XmlFormatting fmt) {
+        m_indent = m_indent.substr(0, m_indent.size() - 2);
+
+        if( m_tagIsOpen ) {
+            m_os << "/>";
+            m_tagIsOpen = false;
+        } else {
+            newlineIfNecessary();
+            if (shouldIndent(fmt)) {
+                m_os << m_indent;
+            }
+            m_os << "</" << m_tags.back() << ">";
+        }
+        m_os << std::flush;
+        applyFormatting(fmt);
+        m_tags.pop_back();
+        return *this;
+    }
+
+    XmlWriter& XmlWriter::writeAttribute( std::string const& name, std::string const& attribute ) {
+        if( !name.empty() && !attribute.empty() )
+            m_os << ' ' << name << "=\"" << XmlEncode( attribute, XmlEncode::ForAttributes ) << '"';
+        return *this;
+    }
+
+    XmlWriter& XmlWriter::writeAttribute( std::string const& name, bool attribute ) {
+        m_os << ' ' << name << "=\"" << ( attribute ? "true" : "false" ) << '"';
+        return *this;
+    }
+
+    XmlWriter& XmlWriter::writeText( std::string const& text, XmlFormatting fmt) {
+        if( !text.empty() ){
+            bool tagWasOpen = m_tagIsOpen;
+            ensureTagClosed();
+            if (tagWasOpen && shouldIndent(fmt)) {
+                m_os << m_indent;
+            }
+            m_os << XmlEncode( text );
+            applyFormatting(fmt);
+        }
+        return *this;
+    }
+
+    XmlWriter& XmlWriter::writeComment( std::string const& text, XmlFormatting fmt) {
+        ensureTagClosed();
+        if (shouldIndent(fmt)) {
+            m_os << m_indent;
+        }
+        m_os << "<!--" << text << "-->";
+        applyFormatting(fmt);
+        return *this;
+    }
+
+    void XmlWriter::writeStylesheetRef( std::string const& url ) {
+        m_os << "<?xml-stylesheet type=\"text/xsl\" href=\"" << url << "\"?>\n";
+    }
+
+    XmlWriter& XmlWriter::writeBlankLine() {
+        ensureTagClosed();
+        m_os << '\n';
+        return *this;
+    }
+
+    void XmlWriter::ensureTagClosed() {
+        if( m_tagIsOpen ) {
+            m_os << '>' << std::flush;
+            newlineIfNecessary();
+            m_tagIsOpen = false;
+        }
+    }
+
+    void XmlWriter::applyFormatting(XmlFormatting fmt) {
+        m_needsNewline = shouldNewline(fmt);
+    }
+
+    void XmlWriter::writeDeclaration() {
+        m_os << "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n";
+    }
+
+    void XmlWriter::newlineIfNecessary() {
+        if( m_needsNewline ) {
+            m_os << std::endl;
+            m_needsNewline = false;
+        }
+    }
+}
+// end catch_xmlwriter.cpp
+// start catch_reporter_bases.cpp
+
+#include <cstring>
+#include <cfloat>
+#include <cstdio>
+#include <cassert>
+#include <memory>
+
+namespace Catch {
+    void prepareExpandedExpression(AssertionResult& result) {
+        result.getExpandedExpression();
+    }
+
+    // Because formatting using c++ streams is stateful, drop down to C is required
+    // Alternatively we could use stringstream, but its performance is... not good.
+    std::string getFormattedDuration( double duration ) {
+        // Max exponent + 1 is required to represent the whole part
+        // + 1 for decimal point
+        // + 3 for the 3 decimal places
+        // + 1 for null terminator
+        const std::size_t maxDoubleSize = DBL_MAX_10_EXP + 1 + 1 + 3 + 1;
+        char buffer[maxDoubleSize];
+
+        // Save previous errno, to prevent sprintf from overwriting it
+        ErrnoGuard guard;
+#ifdef _MSC_VER
+        sprintf_s(buffer, "%.3f", duration);
+#else
+        std::sprintf(buffer, "%.3f", duration);
+#endif
+        return std::string(buffer);
+    }
+
+    bool shouldShowDuration( IConfig const& config, double duration ) {
+        if ( config.showDurations() == ShowDurations::Always ) {
+            return true;
+        }
+        if ( config.showDurations() == ShowDurations::Never ) {
+            return false;
+        }
+        const double min = config.minDuration();
+        return min >= 0 && duration >= min;
+    }
+
+    std::string serializeFilters( std::vector<std::string> const& container ) {
+        ReusableStringStream oss;
+        bool first = true;
+        for (auto&& filter : container)
+        {
+            if (!first)
+                oss << ' ';
+            else
+                first = false;
+
+            oss << filter;
+        }
+        return oss.str();
+    }
+
+    TestEventListenerBase::TestEventListenerBase(ReporterConfig const & _config)
+        :StreamingReporterBase(_config) {}
+
+    std::set<Verbosity> TestEventListenerBase::getSupportedVerbosities() {
+        return { Verbosity::Quiet, Verbosity::Normal, Verbosity::High };
+    }
+
+    void TestEventListenerBase::assertionStarting(AssertionInfo const &) {}
+
+    bool TestEventListenerBase::assertionEnded(AssertionStats const &) {
+        return false;
+    }
+
+} // end namespace Catch
+// end catch_reporter_bases.cpp
+// start catch_reporter_compact.cpp
+
+namespace {
+
+#ifdef CATCH_PLATFORM_MAC
+    const char* failedString() { return "FAILED"; }
+    const char* passedString() { return "PASSED"; }
+#else
+    const char* failedString() { return "failed"; }
+    const char* passedString() { return "passed"; }
+#endif
+
+    // Colour::LightGrey
+    Catch::Colour::Code dimColour() { return Catch::Colour::FileName; }
+
+    std::string bothOrAll( std::size_t count ) {
+        return count == 1 ? std::string() :
+               count == 2 ? "both " : "all " ;
+    }
+
+} // anon namespace
+
+namespace Catch {
+namespace {
+// Colour, message variants:
+// - white: No tests ran.
+// -   red: Failed [both/all] N test cases, failed [both/all] M assertions.
+// - white: Passed [both/all] N test cases (no assertions).
+// -   red: Failed N tests cases, failed M assertions.
+// - green: Passed [both/all] N tests cases with M assertions.
+void printTotals(std::ostream& out, const Totals& totals) {
+    if (totals.testCases.total() == 0) {
+        out << "No tests ran.";
+    } else if (totals.testCases.failed == totals.testCases.total()) {
+        Colour colour(Colour::ResultError);
+        const std::string qualify_assertions_failed =
+            totals.assertions.failed == totals.assertions.total() ?
+            bothOrAll(totals.assertions.failed) : std::string();
+        out <<
+            "Failed " << bothOrAll(totals.testCases.failed)
+            << pluralise(totals.testCases.failed, "test case") << ", "
+            "failed " << qualify_assertions_failed <<
+            pluralise(totals.assertions.failed, "assertion") << '.';
+    } else if (totals.assertions.total() == 0) {
+        out <<
+            "Passed " << bothOrAll(totals.testCases.total())
+            << pluralise(totals.testCases.total(), "test case")
+            << " (no assertions).";
+    } else if (totals.assertions.failed) {
+        Colour colour(Colour::ResultError);
+        out <<
+            "Failed " << pluralise(totals.testCases.failed, "test case") << ", "
+            "failed " << pluralise(totals.assertions.failed, "assertion") << '.';
+    } else {
+        Colour colour(Colour::ResultSuccess);
+        out <<
+            "Passed " << bothOrAll(totals.testCases.passed)
+            << pluralise(totals.testCases.passed, "test case") <<
+            " with " << pluralise(totals.assertions.passed, "assertion") << '.';
+    }
+}
+
+// Implementation of CompactReporter formatting
+class AssertionPrinter {
+public:
+    AssertionPrinter& operator= (AssertionPrinter const&) = delete;
+    AssertionPrinter(AssertionPrinter const&) = delete;
+    AssertionPrinter(std::ostream& _stream, AssertionStats const& _stats, bool _printInfoMessages)
+        : stream(_stream)
+        , result(_stats.assertionResult)
+        , messages(_stats.infoMessages)
+        , itMessage(_stats.infoMessages.begin())
+        , printInfoMessages(_printInfoMessages) {}
+
+    void print() {
+        printSourceInfo();
+
+        itMessage = messages.begin();
+
+        switch (result.getResultType()) {
+        case ResultWas::Ok:
+            printResultType(Colour::ResultSuccess, passedString());
+            printOriginalExpression();
+            printReconstructedExpression();
+            if (!result.hasExpression())
+                printRemainingMessages(Colour::None);
+            else
+                printRemainingMessages();
+            break;
+        case ResultWas::ExpressionFailed:
+            if (result.isOk())
+                printResultType(Colour::ResultSuccess, failedString() + std::string(" - but was ok"));
+            else
+                printResultType(Colour::Error, failedString());
+            printOriginalExpression();
+            printReconstructedExpression();
+            printRemainingMessages();
+            break;
+        case ResultWas::ThrewException:
+            printResultType(Colour::Error, failedString());
+            printIssue("unexpected exception with message:");
+            printMessage();
+            printExpressionWas();
+            printRemainingMessages();
+            break;
+        case ResultWas::FatalErrorCondition:
+            printResultType(Colour::Error, failedString());
+            printIssue("fatal error condition with message:");
+            printMessage();
+            printExpressionWas();
+            printRemainingMessages();
+            break;
+        case ResultWas::DidntThrowException:
+            printResultType(Colour::Error, failedString());
+            printIssue("expected exception, got none");
+            printExpressionWas();
+            printRemainingMessages();
+            break;
+        case ResultWas::Info:
+            printResultType(Colour::None, "info");
+            printMessage();
+            printRemainingMessages();
+            break;
+        case ResultWas::Warning:
+            printResultType(Colour::None, "warning");
+            printMessage();
+            printRemainingMessages();
+            break;
+        case ResultWas::ExplicitFailure:
+            printResultType(Colour::Error, failedString());
+            printIssue("explicitly");
+            printRemainingMessages(Colour::None);
+            break;
+            // These cases are here to prevent compiler warnings
+        case ResultWas::Unknown:
+        case ResultWas::FailureBit:
+        case ResultWas::Exception:
+            printResultType(Colour::Error, "** internal error **");
+            break;
+        }
+    }
+
+private:
+    void printSourceInfo() const {
+        Colour colourGuard(Colour::FileName);
+        stream << result.getSourceInfo() << ':';
+    }
+
+    void printResultType(Colour::Code colour, std::string const& passOrFail) const {
+        if (!passOrFail.empty()) {
+            {
+                Colour colourGuard(colour);
+                stream << ' ' << passOrFail;
+            }
+            stream << ':';
+        }
+    }
+
+    void printIssue(std::string const& issue) const {
+        stream << ' ' << issue;
+    }
+
+    void printExpressionWas() {
+        if (result.hasExpression()) {
+            stream << ';';
+            {
+                Colour colour(dimColour());
+                stream << " expression was:";
+            }
+            printOriginalExpression();
+        }
+    }
+
+    void printOriginalExpression() const {
+        if (result.hasExpression()) {
+            stream << ' ' << result.getExpression();
+        }
+    }
+
+    void printReconstructedExpression() const {
+        if (result.hasExpandedExpression()) {
+            {
+                Colour colour(dimColour());
+                stream << " for: ";
+            }
+            stream << result.getExpandedExpression();
+        }
+    }
+
+    void printMessage() {
+        if (itMessage != messages.end()) {
+            stream << " '" << itMessage->message << '\'';
+            ++itMessage;
+        }
+    }
+
+    void printRemainingMessages(Colour::Code colour = dimColour()) {
+        if (itMessage == messages.end())
+            return;
+
+        const auto itEnd = messages.cend();
+        const auto N = static_cast<std::size_t>(std::distance(itMessage, itEnd));
+
+        {
+            Colour colourGuard(colour);
+            stream << " with " << pluralise(N, "message") << ':';
+        }
+
+        while (itMessage != itEnd) {
+            // If this assertion is a warning ignore any INFO messages
+            if (printInfoMessages || itMessage->type != ResultWas::Info) {
+                printMessage();
+                if (itMessage != itEnd) {
+                    Colour colourGuard(dimColour());
+                    stream << " and";
+                }
+                continue;
+            }
+            ++itMessage;
+        }
+    }
+
+private:
+    std::ostream& stream;
+    AssertionResult const& result;
+    std::vector<MessageInfo> messages;
+    std::vector<MessageInfo>::const_iterator itMessage;
+    bool printInfoMessages;
+};
+
+} // anon namespace
+
+        std::string CompactReporter::getDescription() {
+            return "Reports test results on a single line, suitable for IDEs";
+        }
+
+        void CompactReporter::noMatchingTestCases( std::string const& spec ) {
+            stream << "No test cases matched '" << spec << '\'' << std::endl;
+        }
+
+        void CompactReporter::assertionStarting( AssertionInfo const& ) {}
+
+        bool CompactReporter::assertionEnded( AssertionStats const& _assertionStats ) {
+            AssertionResult const& result = _assertionStats.assertionResult;
+
+            bool printInfoMessages = true;
+
+            // Drop out if result was successful and we're not printing those
+            if( !m_config->includeSuccessfulResults() && result.isOk() ) {
+                if( result.getResultType() != ResultWas::Warning )
+                    return false;
+                printInfoMessages = false;
+            }
+
+            AssertionPrinter printer( stream, _assertionStats, printInfoMessages );
+            printer.print();
+
+            stream << std::endl;
+            return true;
+        }
+
+        void CompactReporter::sectionEnded(SectionStats const& _sectionStats) {
+            double dur = _sectionStats.durationInSeconds;
+            if ( shouldShowDuration( *m_config, dur ) ) {
+                stream << getFormattedDuration( dur ) << " s: " << _sectionStats.sectionInfo.name << std::endl;
+            }
+        }
+
+        void CompactReporter::testRunEnded( TestRunStats const& _testRunStats ) {
+            printTotals( stream, _testRunStats.totals );
+            stream << '\n' << std::endl;
+            StreamingReporterBase::testRunEnded( _testRunStats );
+        }
+
+        CompactReporter::~CompactReporter() {}
+
+    CATCH_REGISTER_REPORTER( "compact", CompactReporter )
+
+} // end namespace Catch
+// end catch_reporter_compact.cpp
+// start catch_reporter_console.cpp
+
+#include <cfloat>
+#include <cstdio>
+
+#if defined(_MSC_VER)
+#pragma warning(push)
+#pragma warning(disable:4061) // Not all labels are EXPLICITLY handled in switch
+ // Note that 4062 (not all labels are handled and default is missing) is enabled
+#endif
+
+#if defined(__clang__)
+#  pragma clang diagnostic push
+// For simplicity, benchmarking-only helpers are always enabled
+#  pragma clang diagnostic ignored "-Wunused-function"
+#endif
+
+namespace Catch {
+
+namespace {
+
+// Formatter impl for ConsoleReporter
+class ConsoleAssertionPrinter {
+public:
+    ConsoleAssertionPrinter& operator= (ConsoleAssertionPrinter const&) = delete;
+    ConsoleAssertionPrinter(ConsoleAssertionPrinter const&) = delete;
+    ConsoleAssertionPrinter(std::ostream& _stream, AssertionStats const& _stats, bool _printInfoMessages)
+        : stream(_stream),
+        stats(_stats),
+        result(_stats.assertionResult),
+        colour(Colour::None),
+        message(result.getMessage()),
+        messages(_stats.infoMessages),
+        printInfoMessages(_printInfoMessages) {
+        switch (result.getResultType()) {
+        case ResultWas::Ok:
+            colour = Colour::Success;
+            passOrFail = "PASSED";
+            //if( result.hasMessage() )
+            if (_stats.infoMessages.size() == 1)
+                messageLabel = "with message";
+            if (_stats.infoMessages.size() > 1)
+                messageLabel = "with messages";
+            break;
+        case ResultWas::ExpressionFailed:
+            if (result.isOk()) {
+                colour = Colour::Success;
+                passOrFail = "FAILED - but was ok";
+            } else {
+                colour = Colour::Error;
+                passOrFail = "FAILED";
+            }
+            if (_stats.infoMessages.size() == 1)
+                messageLabel = "with message";
+            if (_stats.infoMessages.size() > 1)
+                messageLabel = "with messages";
+            break;
+        case ResultWas::ThrewException:
+            colour = Colour::Error;
+            passOrFail = "FAILED";
+            messageLabel = "due to unexpected exception with ";
+            if (_stats.infoMessages.size() == 1)
+                messageLabel += "message";
+            if (_stats.infoMessages.size() > 1)
+                messageLabel += "messages";
+            break;
+        case ResultWas::FatalErrorCondition:
+            colour = Colour::Error;
+            passOrFail = "FAILED";
+            messageLabel = "due to a fatal error condition";
+            break;
+        case ResultWas::DidntThrowException:
+            colour = Colour::Error;
+            passOrFail = "FAILED";
+            messageLabel = "because no exception was thrown where one was expected";
+            break;
+        case ResultWas::Info:
+            messageLabel = "info";
+            break;
+        case ResultWas::Warning:
+            messageLabel = "warning";
+            break;
+        case ResultWas::ExplicitFailure:
+            passOrFail = "FAILED";
+            colour = Colour::Error;
+            if (_stats.infoMessages.size() == 1)
+                messageLabel = "explicitly with message";
+            if (_stats.infoMessages.size() > 1)
+                messageLabel = "explicitly with messages";
+            break;
+            // These cases are here to prevent compiler warnings
+        case ResultWas::Unknown:
+        case ResultWas::FailureBit:
+        case ResultWas::Exception:
+            passOrFail = "** internal error **";
+            colour = Colour::Error;
+            break;
+        }
+    }
+
+    void print() const {
+        printSourceInfo();
+        if (stats.totals.assertions.total() > 0) {
+            printResultType();
+            printOriginalExpression();
+            printReconstructedExpression();
+        } else {
+            stream << '\n';
+        }
+        printMessage();
+    }
+
+private:
+    void printResultType() const {
+        if (!passOrFail.empty()) {
+            Colour colourGuard(colour);
+            stream << passOrFail << ":\n";
+        }
+    }
+    void printOriginalExpression() const {
+        if (result.hasExpression()) {
+            Colour colourGuard(Colour::OriginalExpression);
+            stream << "  ";
+            stream << result.getExpressionInMacro();
+            stream << '\n';
+        }
+    }
+    void printReconstructedExpression() const {
+        if (result.hasExpandedExpression()) {
+            stream << "with expansion:\n";
+            Colour colourGuard(Colour::ReconstructedExpression);
+            stream << Column(result.getExpandedExpression()).indent(2) << '\n';
+        }
+    }
+    void printMessage() const {
+        if (!messageLabel.empty())
+            stream << messageLabel << ':' << '\n';
+        for (auto const& msg : messages) {
+            // If this assertion is a warning ignore any INFO messages
+            if (printInfoMessages || msg.type != ResultWas::Info)
+                stream << Column(msg.message).indent(2) << '\n';
+        }
+    }
+    void printSourceInfo() const {
+        Colour colourGuard(Colour::FileName);
+        stream << result.getSourceInfo() << ": ";
+    }
+
+    std::ostream& stream;
+    AssertionStats const& stats;
+    AssertionResult const& result;
+    Colour::Code colour;
+    std::string passOrFail;
+    std::string messageLabel;
+    std::string message;
+    std::vector<MessageInfo> messages;
+    bool printInfoMessages;
+};
+
+std::size_t makeRatio(std::size_t number, std::size_t total) {
+    std::size_t ratio = total > 0 ? CATCH_CONFIG_CONSOLE_WIDTH * number / total : 0;
+    return (ratio == 0 && number > 0) ? 1 : ratio;
+}
+
+std::size_t& findMax(std::size_t& i, std::size_t& j, std::size_t& k) {
+    if (i > j && i > k)
+        return i;
+    else if (j > k)
+        return j;
+    else
+        return k;
+}
+
+struct ColumnInfo {
+    enum Justification { Left, Right };
+    std::string name;
+    int width;
+    Justification justification;
+};
+struct ColumnBreak {};
+struct RowBreak {};
+
+class Duration {
+    enum class Unit {
+        Auto,
+        Nanoseconds,
+        Microseconds,
+        Milliseconds,
+        Seconds,
+        Minutes
+    };
+    static const uint64_t s_nanosecondsInAMicrosecond = 1000;
+    static const uint64_t s_nanosecondsInAMillisecond = 1000 * s_nanosecondsInAMicrosecond;
+    static const uint64_t s_nanosecondsInASecond = 1000 * s_nanosecondsInAMillisecond;
+    static const uint64_t s_nanosecondsInAMinute = 60 * s_nanosecondsInASecond;
+
+    double m_inNanoseconds;
+    Unit m_units;
+
+public:
+    explicit Duration(double inNanoseconds, Unit units = Unit::Auto)
+        : m_inNanoseconds(inNanoseconds),
+        m_units(units) {
+        if (m_units == Unit::Auto) {
+            if (m_inNanoseconds < s_nanosecondsInAMicrosecond)
+                m_units = Unit::Nanoseconds;
+            else if (m_inNanoseconds < s_nanosecondsInAMillisecond)
+                m_units = Unit::Microseconds;
+            else if (m_inNanoseconds < s_nanosecondsInASecond)
+                m_units = Unit::Milliseconds;
+            else if (m_inNanoseconds < s_nanosecondsInAMinute)
+                m_units = Unit::Seconds;
+            else
+                m_units = Unit::Minutes;
+        }
+
+    }
+
+    auto value() const -> double {
+        switch (m_units) {
+        case Unit::Microseconds:
+            return m_inNanoseconds / static_cast<double>(s_nanosecondsInAMicrosecond);
+        case Unit::Milliseconds:
+            return m_inNanoseconds / static_cast<double>(s_nanosecondsInAMillisecond);
+        case Unit::Seconds:
+            return m_inNanoseconds / static_cast<double>(s_nanosecondsInASecond);
+        case Unit::Minutes:
+            return m_inNanoseconds / static_cast<double>(s_nanosecondsInAMinute);
+        default:
+            return m_inNanoseconds;
+        }
+    }
+    auto unitsAsString() const -> std::string {
+        switch (m_units) {
+        case Unit::Nanoseconds:
+            return "ns";
+        case Unit::Microseconds:
+            return "us";
+        case Unit::Milliseconds:
+            return "ms";
+        case Unit::Seconds:
+            return "s";
+        case Unit::Minutes:
+            return "m";
+        default:
+            return "** internal error **";
+        }
+
+    }
+    friend auto operator << (std::ostream& os, Duration const& duration) -> std::ostream& {
+        return os << duration.value() << ' ' << duration.unitsAsString();
+    }
+};
+} // end anon namespace
+
+class TablePrinter {
+    std::ostream& m_os;
+    std::vector<ColumnInfo> m_columnInfos;
+    std::ostringstream m_oss;
+    int m_currentColumn = -1;
+    bool m_isOpen = false;
+
+public:
+    TablePrinter( std::ostream& os, std::vector<ColumnInfo> columnInfos )
+    :   m_os( os ),
+        m_columnInfos( std::move( columnInfos ) ) {}
+
+    auto columnInfos() const -> std::vector<ColumnInfo> const& {
+        return m_columnInfos;
+    }
+
+    void open() {
+        if (!m_isOpen) {
+            m_isOpen = true;
+            *this << RowBreak();
+
+			Columns headerCols;
+			Spacer spacer(2);
+			for (auto const& info : m_columnInfos) {
+				headerCols += Column(info.name).width(static_cast<std::size_t>(info.width - 2));
+				headerCols += spacer;
+			}
+			m_os << headerCols << '\n';
+
+            m_os << Catch::getLineOfChars<'-'>() << '\n';
+        }
+    }
+    void close() {
+        if (m_isOpen) {
+            *this << RowBreak();
+            m_os << std::endl;
+            m_isOpen = false;
+        }
+    }
+
+    template<typename T>
+    friend TablePrinter& operator << (TablePrinter& tp, T const& value) {
+        tp.m_oss << value;
+        return tp;
+    }
+
+    friend TablePrinter& operator << (TablePrinter& tp, ColumnBreak) {
+        auto colStr = tp.m_oss.str();
+        const auto strSize = colStr.size();
+        tp.m_oss.str("");
+        tp.open();
+        if (tp.m_currentColumn == static_cast<int>(tp.m_columnInfos.size() - 1)) {
+            tp.m_currentColumn = -1;
+            tp.m_os << '\n';
+        }
+        tp.m_currentColumn++;
+
+        auto colInfo = tp.m_columnInfos[tp.m_currentColumn];
+        auto padding = (strSize + 1 < static_cast<std::size_t>(colInfo.width))
+            ? std::string(colInfo.width - (strSize + 1), ' ')
+            : std::string();
+        if (colInfo.justification == ColumnInfo::Left)
+            tp.m_os << colStr << padding << ' ';
+        else
+            tp.m_os << padding << colStr << ' ';
+        return tp;
+    }
+
+    friend TablePrinter& operator << (TablePrinter& tp, RowBreak) {
+        if (tp.m_currentColumn > 0) {
+            tp.m_os << '\n';
+            tp.m_currentColumn = -1;
+        }
+        return tp;
+    }
+};
+
+ConsoleReporter::ConsoleReporter(ReporterConfig const& config)
+    : StreamingReporterBase(config),
+    m_tablePrinter(new TablePrinter(config.stream(),
+        [&config]() -> std::vector<ColumnInfo> {
+        if (config.fullConfig()->benchmarkNoAnalysis())
+        {
+            return{
+                { "benchmark name", CATCH_CONFIG_CONSOLE_WIDTH - 43, ColumnInfo::Left },
+                { "     samples", 14, ColumnInfo::Right },
+                { "  iterations", 14, ColumnInfo::Right },
+                { "        mean", 14, ColumnInfo::Right }
+            };
+        }
+        else
+        {
+            return{
+                { "benchmark name", CATCH_CONFIG_CONSOLE_WIDTH - 43, ColumnInfo::Left },
+                { "samples      mean       std dev", 14, ColumnInfo::Right },
+                { "iterations   low mean   low std dev", 14, ColumnInfo::Right },
+                { "estimated    high mean  high std dev", 14, ColumnInfo::Right }
+            };
+        }
+    }())) {}
+ConsoleReporter::~ConsoleReporter() = default;
+
+std::string ConsoleReporter::getDescription() {
+    return "Reports test results as plain lines of text";
+}
+
+void ConsoleReporter::noMatchingTestCases(std::string const& spec) {
+    stream << "No test cases matched '" << spec << '\'' << std::endl;
+}
+
+void ConsoleReporter::reportInvalidArguments(std::string const&arg){
+    stream << "Invalid Filter: " << arg << std::endl;
+}
+
+void ConsoleReporter::assertionStarting(AssertionInfo const&) {}
+
+bool ConsoleReporter::assertionEnded(AssertionStats const& _assertionStats) {
+    AssertionResult const& result = _assertionStats.assertionResult;
+
+    bool includeResults = m_config->includeSuccessfulResults() || !result.isOk();
+
+    // Drop out if result was successful but we're not printing them.
+    if (!includeResults && result.getResultType() != ResultWas::Warning)
+        return false;
+
+    lazyPrint();
+
+    ConsoleAssertionPrinter printer(stream, _assertionStats, includeResults);
+    printer.print();
+    stream << std::endl;
+    return true;
+}
+
+void ConsoleReporter::sectionStarting(SectionInfo const& _sectionInfo) {
+    m_tablePrinter->close();
+    m_headerPrinted = false;
+    StreamingReporterBase::sectionStarting(_sectionInfo);
+}
+void ConsoleReporter::sectionEnded(SectionStats const& _sectionStats) {
+    m_tablePrinter->close();
+    if (_sectionStats.missingAssertions) {
+        lazyPrint();
+        Colour colour(Colour::ResultError);
+        if (m_sectionStack.size() > 1)
+            stream << "\nNo assertions in section";
+        else
+            stream << "\nNo assertions in test case";
+        stream << " '" << _sectionStats.sectionInfo.name << "'\n" << std::endl;
+    }
+    double dur = _sectionStats.durationInSeconds;
+    if (shouldShowDuration(*m_config, dur)) {
+        stream << getFormattedDuration(dur) << " s: " << _sectionStats.sectionInfo.name << std::endl;
+    }
+    if (m_headerPrinted) {
+        m_headerPrinted = false;
+    }
+    StreamingReporterBase::sectionEnded(_sectionStats);
+}
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+void ConsoleReporter::benchmarkPreparing(std::string const& name) {
+	lazyPrintWithoutClosingBenchmarkTable();
+
+	auto nameCol = Column(name).width(static_cast<std::size_t>(m_tablePrinter->columnInfos()[0].width - 2));
+
+	bool firstLine = true;
+	for (auto line : nameCol) {
+		if (!firstLine)
+			(*m_tablePrinter) << ColumnBreak() << ColumnBreak() << ColumnBreak();
+		else
+			firstLine = false;
+
+		(*m_tablePrinter) << line << ColumnBreak();
+	}
+}
+
+void ConsoleReporter::benchmarkStarting(BenchmarkInfo const& info) {
+    (*m_tablePrinter) << info.samples << ColumnBreak()
+        << info.iterations << ColumnBreak();
+    if (!m_config->benchmarkNoAnalysis())
+        (*m_tablePrinter) << Duration(info.estimatedDuration) << ColumnBreak();
+}
+void ConsoleReporter::benchmarkEnded(BenchmarkStats<> const& stats) {
+    if (m_config->benchmarkNoAnalysis())
+    {
+        (*m_tablePrinter) << Duration(stats.mean.point.count()) << ColumnBreak();
+    }
+    else
+    {
+        (*m_tablePrinter) << ColumnBreak()
+            << Duration(stats.mean.point.count()) << ColumnBreak()
+            << Duration(stats.mean.lower_bound.count()) << ColumnBreak()
+            << Duration(stats.mean.upper_bound.count()) << ColumnBreak() << ColumnBreak()
+            << Duration(stats.standardDeviation.point.count()) << ColumnBreak()
+            << Duration(stats.standardDeviation.lower_bound.count()) << ColumnBreak()
+            << Duration(stats.standardDeviation.upper_bound.count()) << ColumnBreak() << ColumnBreak() << ColumnBreak() << ColumnBreak() << ColumnBreak();
+    }
+}
+
+void ConsoleReporter::benchmarkFailed(std::string const& error) {
+	Colour colour(Colour::Red);
+    (*m_tablePrinter)
+        << "Benchmark failed (" << error << ')'
+        << ColumnBreak() << RowBreak();
+}
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+void ConsoleReporter::testCaseEnded(TestCaseStats const& _testCaseStats) {
+    m_tablePrinter->close();
+    StreamingReporterBase::testCaseEnded(_testCaseStats);
+    m_headerPrinted = false;
+}
+void ConsoleReporter::testGroupEnded(TestGroupStats const& _testGroupStats) {
+    if (currentGroupInfo.used) {
+        printSummaryDivider();
+        stream << "Summary for group '" << _testGroupStats.groupInfo.name << "':\n";
+        printTotals(_testGroupStats.totals);
+        stream << '\n' << std::endl;
+    }
+    StreamingReporterBase::testGroupEnded(_testGroupStats);
+}
+void ConsoleReporter::testRunEnded(TestRunStats const& _testRunStats) {
+    printTotalsDivider(_testRunStats.totals);
+    printTotals(_testRunStats.totals);
+    stream << std::endl;
+    StreamingReporterBase::testRunEnded(_testRunStats);
+}
+void ConsoleReporter::testRunStarting(TestRunInfo const& _testInfo) {
+    StreamingReporterBase::testRunStarting(_testInfo);
+    printTestFilters();
+}
+
+void ConsoleReporter::lazyPrint() {
+
+    m_tablePrinter->close();
+    lazyPrintWithoutClosingBenchmarkTable();
+}
+
+void ConsoleReporter::lazyPrintWithoutClosingBenchmarkTable() {
+
+    if (!currentTestRunInfo.used)
+        lazyPrintRunInfo();
+    if (!currentGroupInfo.used)
+        lazyPrintGroupInfo();
+
+    if (!m_headerPrinted) {
+        printTestCaseAndSectionHeader();
+        m_headerPrinted = true;
+    }
+}
+void ConsoleReporter::lazyPrintRunInfo() {
+    stream << '\n' << getLineOfChars<'~'>() << '\n';
+    Colour colour(Colour::SecondaryText);
+    stream << currentTestRunInfo->name
+        << " is a Catch v" << libraryVersion() << " host application.\n"
+        << "Run with -? for options\n\n";
+
+    if (m_config->rngSeed() != 0)
+        stream << "Randomness seeded to: " << m_config->rngSeed() << "\n\n";
+
+    currentTestRunInfo.used = true;
+}
+void ConsoleReporter::lazyPrintGroupInfo() {
+    if (!currentGroupInfo->name.empty() && currentGroupInfo->groupsCounts > 1) {
+        printClosedHeader("Group: " + currentGroupInfo->name);
+        currentGroupInfo.used = true;
+    }
+}
+void ConsoleReporter::printTestCaseAndSectionHeader() {
+    assert(!m_sectionStack.empty());
+    printOpenHeader(currentTestCaseInfo->name);
+
+    if (m_sectionStack.size() > 1) {
+        Colour colourGuard(Colour::Headers);
+
+        auto
+            it = m_sectionStack.begin() + 1, // Skip first section (test case)
+            itEnd = m_sectionStack.end();
+        for (; it != itEnd; ++it)
+            printHeaderString(it->name, 2);
+    }
+
+    SourceLineInfo lineInfo = m_sectionStack.back().lineInfo;
+
+    stream << getLineOfChars<'-'>() << '\n';
+    Colour colourGuard(Colour::FileName);
+    stream << lineInfo << '\n';
+    stream << getLineOfChars<'.'>() << '\n' << std::endl;
+}
+
+void ConsoleReporter::printClosedHeader(std::string const& _name) {
+    printOpenHeader(_name);
+    stream << getLineOfChars<'.'>() << '\n';
+}
+void ConsoleReporter::printOpenHeader(std::string const& _name) {
+    stream << getLineOfChars<'-'>() << '\n';
+    {
+        Colour colourGuard(Colour::Headers);
+        printHeaderString(_name);
+    }
+}
+
+// if string has a : in first line will set indent to follow it on
+// subsequent lines
+void ConsoleReporter::printHeaderString(std::string const& _string, std::size_t indent) {
+    std::size_t i = _string.find(": ");
+    if (i != std::string::npos)
+        i += 2;
+    else
+        i = 0;
+    stream << Column(_string).indent(indent + i).initialIndent(indent) << '\n';
+}
+
+struct SummaryColumn {
+
+    SummaryColumn( std::string _label, Colour::Code _colour )
+    :   label( std::move( _label ) ),
+        colour( _colour ) {}
+    SummaryColumn addRow( std::size_t count ) {
+        ReusableStringStream rss;
+        rss << count;
+        std::string row = rss.str();
+        for (auto& oldRow : rows) {
+            while (oldRow.size() < row.size())
+                oldRow = ' ' + oldRow;
+            while (oldRow.size() > row.size())
+                row = ' ' + row;
+        }
+        rows.push_back(row);
+        return *this;
+    }
+
+    std::string label;
+    Colour::Code colour;
+    std::vector<std::string> rows;
+
+};
+
+void ConsoleReporter::printTotals( Totals const& totals ) {
+    if (totals.testCases.total() == 0) {
+        stream << Colour(Colour::Warning) << "No tests ran\n";
+    } else if (totals.assertions.total() > 0 && totals.testCases.allPassed()) {
+        stream << Colour(Colour::ResultSuccess) << "All tests passed";
+        stream << " ("
+            << pluralise(totals.assertions.passed, "assertion") << " in "
+            << pluralise(totals.testCases.passed, "test case") << ')'
+            << '\n';
+    } else {
+
+        std::vector<SummaryColumn> columns;
+        columns.push_back(SummaryColumn("", Colour::None)
+                          .addRow(totals.testCases.total())
+                          .addRow(totals.assertions.total()));
+        columns.push_back(SummaryColumn("passed", Colour::Success)
+                          .addRow(totals.testCases.passed)
+                          .addRow(totals.assertions.passed));
+        columns.push_back(SummaryColumn("failed", Colour::ResultError)
+                          .addRow(totals.testCases.failed)
+                          .addRow(totals.assertions.failed));
+        columns.push_back(SummaryColumn("failed as expected", Colour::ResultExpectedFailure)
+                          .addRow(totals.testCases.failedButOk)
+                          .addRow(totals.assertions.failedButOk));
+
+        printSummaryRow("test cases", columns, 0);
+        printSummaryRow("assertions", columns, 1);
+    }
+}
+void ConsoleReporter::printSummaryRow(std::string const& label, std::vector<SummaryColumn> const& cols, std::size_t row) {
+    for (auto col : cols) {
+        std::string value = col.rows[row];
+        if (col.label.empty()) {
+            stream << label << ": ";
+            if (value != "0")
+                stream << value;
+            else
+                stream << Colour(Colour::Warning) << "- none -";
+        } else if (value != "0") {
+            stream << Colour(Colour::LightGrey) << " | ";
+            stream << Colour(col.colour)
+                << value << ' ' << col.label;
+        }
+    }
+    stream << '\n';
+}
+
+void ConsoleReporter::printTotalsDivider(Totals const& totals) {
+    if (totals.testCases.total() > 0) {
+        std::size_t failedRatio = makeRatio(totals.testCases.failed, totals.testCases.total());
+        std::size_t failedButOkRatio = makeRatio(totals.testCases.failedButOk, totals.testCases.total());
+        std::size_t passedRatio = makeRatio(totals.testCases.passed, totals.testCases.total());
+        while (failedRatio + failedButOkRatio + passedRatio < CATCH_CONFIG_CONSOLE_WIDTH - 1)
+            findMax(failedRatio, failedButOkRatio, passedRatio)++;
+        while (failedRatio + failedButOkRatio + passedRatio > CATCH_CONFIG_CONSOLE_WIDTH - 1)
+            findMax(failedRatio, failedButOkRatio, passedRatio)--;
+
+        stream << Colour(Colour::Error) << std::string(failedRatio, '=');
+        stream << Colour(Colour::ResultExpectedFailure) << std::string(failedButOkRatio, '=');
+        if (totals.testCases.allPassed())
+            stream << Colour(Colour::ResultSuccess) << std::string(passedRatio, '=');
+        else
+            stream << Colour(Colour::Success) << std::string(passedRatio, '=');
+    } else {
+        stream << Colour(Colour::Warning) << std::string(CATCH_CONFIG_CONSOLE_WIDTH - 1, '=');
+    }
+    stream << '\n';
+}
+void ConsoleReporter::printSummaryDivider() {
+    stream << getLineOfChars<'-'>() << '\n';
+}
+
+void ConsoleReporter::printTestFilters() {
+    if (m_config->testSpec().hasFilters()) {
+        Colour guard(Colour::BrightYellow);
+        stream << "Filters: " << serializeFilters(m_config->getTestsOrTags()) << '\n';
+    }
+}
+
+CATCH_REGISTER_REPORTER("console", ConsoleReporter)
+
+} // end namespace Catch
+
+#if defined(_MSC_VER)
+#pragma warning(pop)
+#endif
+
+#if defined(__clang__)
+#  pragma clang diagnostic pop
+#endif
+// end catch_reporter_console.cpp
+// start catch_reporter_junit.cpp
+
+#include <cassert>
+#include <sstream>
+#include <ctime>
+#include <algorithm>
+#include <iomanip>
+
+namespace Catch {
+
+    namespace {
+        std::string getCurrentTimestamp() {
+            // Beware, this is not reentrant because of backward compatibility issues
+            // Also, UTC only, again because of backward compatibility (%z is C++11)
+            time_t rawtime;
+            std::time(&rawtime);
+            auto const timeStampSize = sizeof("2017-01-16T17:06:45Z");
+
+#ifdef _MSC_VER
+            std::tm timeInfo = {};
+            gmtime_s(&timeInfo, &rawtime);
+#else
+            std::tm* timeInfo;
+            timeInfo = std::gmtime(&rawtime);
+#endif
+
+            char timeStamp[timeStampSize];
+            const char * const fmt = "%Y-%m-%dT%H:%M:%SZ";
+
+#ifdef _MSC_VER
+            std::strftime(timeStamp, timeStampSize, fmt, &timeInfo);
+#else
+            std::strftime(timeStamp, timeStampSize, fmt, timeInfo);
+#endif
+            return std::string(timeStamp, timeStampSize-1);
+        }
+
+        std::string fileNameTag(const std::vector<std::string> &tags) {
+            auto it = std::find_if(begin(tags),
+                                   end(tags),
+                                   [] (std::string const& tag) {return tag.front() == '#'; });
+            if (it != tags.end())
+                return it->substr(1);
+            return std::string();
+        }
+
+        // Formats the duration in seconds to 3 decimal places.
+        // This is done because some genius defined Maven Surefire schema
+        // in a way that only accepts 3 decimal places, and tools like
+        // Jenkins use that schema for validation JUnit reporter output.
+        std::string formatDuration( double seconds ) {
+            ReusableStringStream rss;
+            rss << std::fixed << std::setprecision( 3 ) << seconds;
+            return rss.str();
+        }
+
+    } // anonymous namespace
+
+    JunitReporter::JunitReporter( ReporterConfig const& _config )
+        :   CumulativeReporterBase( _config ),
+            xml( _config.stream() )
+        {
+            m_reporterPrefs.shouldRedirectStdOut = true;
+            m_reporterPrefs.shouldReportAllAssertions = true;
+        }
+
+    JunitReporter::~JunitReporter() {}
+
+    std::string JunitReporter::getDescription() {
+        return "Reports test results in an XML format that looks like Ant's junitreport target";
+    }
+
+    void JunitReporter::noMatchingTestCases( std::string const& /*spec*/ ) {}
+
+    void JunitReporter::testRunStarting( TestRunInfo const& runInfo )  {
+        CumulativeReporterBase::testRunStarting( runInfo );
+        xml.startElement( "testsuites" );
+    }
+
+    void JunitReporter::testGroupStarting( GroupInfo const& groupInfo ) {
+        suiteTimer.start();
+        stdOutForSuite.clear();
+        stdErrForSuite.clear();
+        unexpectedExceptions = 0;
+        CumulativeReporterBase::testGroupStarting( groupInfo );
+    }
+
+    void JunitReporter::testCaseStarting( TestCaseInfo const& testCaseInfo ) {
+        m_okToFail = testCaseInfo.okToFail();
+    }
+
+    bool JunitReporter::assertionEnded( AssertionStats const& assertionStats ) {
+        if( assertionStats.assertionResult.getResultType() == ResultWas::ThrewException && !m_okToFail )
+            unexpectedExceptions++;
+        return CumulativeReporterBase::assertionEnded( assertionStats );
+    }
+
+    void JunitReporter::testCaseEnded( TestCaseStats const& testCaseStats ) {
+        stdOutForSuite += testCaseStats.stdOut;
+        stdErrForSuite += testCaseStats.stdErr;
+        CumulativeReporterBase::testCaseEnded( testCaseStats );
+    }
+
+    void JunitReporter::testGroupEnded( TestGroupStats const& testGroupStats ) {
+        double suiteTime = suiteTimer.getElapsedSeconds();
+        CumulativeReporterBase::testGroupEnded( testGroupStats );
+        writeGroup( *m_testGroups.back(), suiteTime );
+    }
+
+    void JunitReporter::testRunEndedCumulative() {
+        xml.endElement();
+    }
+
+    void JunitReporter::writeGroup( TestGroupNode const& groupNode, double suiteTime ) {
+        XmlWriter::ScopedElement e = xml.scopedElement( "testsuite" );
+
+        TestGroupStats const& stats = groupNode.value;
+        xml.writeAttribute( "name", stats.groupInfo.name );
+        xml.writeAttribute( "errors", unexpectedExceptions );
+        xml.writeAttribute( "failures", stats.totals.assertions.failed-unexpectedExceptions );
+        xml.writeAttribute( "tests", stats.totals.assertions.total() );
+        xml.writeAttribute( "hostname", "tbd" ); // !TBD
+        if( m_config->showDurations() == ShowDurations::Never )
+            xml.writeAttribute( "time", "" );
+        else
+            xml.writeAttribute( "time", formatDuration( suiteTime ) );
+        xml.writeAttribute( "timestamp", getCurrentTimestamp() );
+
+        // Write properties if there are any
+        if (m_config->hasTestFilters() || m_config->rngSeed() != 0) {
+            auto properties = xml.scopedElement("properties");
+            if (m_config->hasTestFilters()) {
+                xml.scopedElement("property")
+                    .writeAttribute("name", "filters")
+                    .writeAttribute("value", serializeFilters(m_config->getTestsOrTags()));
+            }
+            if (m_config->rngSeed() != 0) {
+                xml.scopedElement("property")
+                    .writeAttribute("name", "random-seed")
+                    .writeAttribute("value", m_config->rngSeed());
+            }
+        }
+
+        // Write test cases
+        for( auto const& child : groupNode.children )
+            writeTestCase( *child );
+
+        xml.scopedElement( "system-out" ).writeText( trim( stdOutForSuite ), XmlFormatting::Newline );
+        xml.scopedElement( "system-err" ).writeText( trim( stdErrForSuite ), XmlFormatting::Newline );
+    }
+
+    void JunitReporter::writeTestCase( TestCaseNode const& testCaseNode ) {
+        TestCaseStats const& stats = testCaseNode.value;
+
+        // All test cases have exactly one section - which represents the
+        // test case itself. That section may have 0-n nested sections
+        assert( testCaseNode.children.size() == 1 );
+        SectionNode const& rootSection = *testCaseNode.children.front();
+
+        std::string className = stats.testInfo.className;
+
+        if( className.empty() ) {
+            className = fileNameTag(stats.testInfo.tags);
+            if ( className.empty() )
+                className = "global";
+        }
+
+        if ( !m_config->name().empty() )
+            className = m_config->name() + "." + className;
+
+        writeSection( className, "", rootSection, stats.testInfo.okToFail() );
+    }
+
+    void JunitReporter::writeSection( std::string const& className,
+                                      std::string const& rootName,
+                                      SectionNode const& sectionNode,
+                                      bool testOkToFail) {
+        std::string name = trim( sectionNode.stats.sectionInfo.name );
+        if( !rootName.empty() )
+            name = rootName + '/' + name;
+
+        if( !sectionNode.assertions.empty() ||
+            !sectionNode.stdOut.empty() ||
+            !sectionNode.stdErr.empty() ) {
+            XmlWriter::ScopedElement e = xml.scopedElement( "testcase" );
+            if( className.empty() ) {
+                xml.writeAttribute( "classname", name );
+                xml.writeAttribute( "name", "root" );
+            }
+            else {
+                xml.writeAttribute( "classname", className );
+                xml.writeAttribute( "name", name );
+            }
+            xml.writeAttribute( "time", formatDuration( sectionNode.stats.durationInSeconds ) );
+            // This is not ideal, but it should be enough to mimic gtest's
+            // junit output.
+            // Ideally the JUnit reporter would also handle `skipTest`
+            // events and write those out appropriately.
+            xml.writeAttribute( "status", "run" );
+
+            if (sectionNode.stats.assertions.failedButOk) {
+                xml.scopedElement("skipped")
+                    .writeAttribute("message", "TEST_CASE tagged with !mayfail");
+            }
+
+            writeAssertions( sectionNode );
+
+            if( !sectionNode.stdOut.empty() )
+                xml.scopedElement( "system-out" ).writeText( trim( sectionNode.stdOut ), XmlFormatting::Newline );
+            if( !sectionNode.stdErr.empty() )
+                xml.scopedElement( "system-err" ).writeText( trim( sectionNode.stdErr ), XmlFormatting::Newline );
+        }
+        for( auto const& childNode : sectionNode.childSections )
+            if( className.empty() )
+                writeSection( name, "", *childNode, testOkToFail );
+            else
+                writeSection( className, name, *childNode, testOkToFail );
+    }
+
+    void JunitReporter::writeAssertions( SectionNode const& sectionNode ) {
+        for( auto const& assertion : sectionNode.assertions )
+            writeAssertion( assertion );
+    }
+
+    void JunitReporter::writeAssertion( AssertionStats const& stats ) {
+        AssertionResult const& result = stats.assertionResult;
+        if( !result.isOk() ) {
+            std::string elementName;
+            switch( result.getResultType() ) {
+                case ResultWas::ThrewException:
+                case ResultWas::FatalErrorCondition:
+                    elementName = "error";
+                    break;
+                case ResultWas::ExplicitFailure:
+                case ResultWas::ExpressionFailed:
+                case ResultWas::DidntThrowException:
+                    elementName = "failure";
+                    break;
+
+                // We should never see these here:
+                case ResultWas::Info:
+                case ResultWas::Warning:
+                case ResultWas::Ok:
+                case ResultWas::Unknown:
+                case ResultWas::FailureBit:
+                case ResultWas::Exception:
+                    elementName = "internalError";
+                    break;
+            }
+
+            XmlWriter::ScopedElement e = xml.scopedElement( elementName );
+
+            xml.writeAttribute( "message", result.getExpression() );
+            xml.writeAttribute( "type", result.getTestMacroName() );
+
+            ReusableStringStream rss;
+            if (stats.totals.assertions.total() > 0) {
+                rss << "FAILED" << ":\n";
+                if (result.hasExpression()) {
+                    rss << "  ";
+                    rss << result.getExpressionInMacro();
+                    rss << '\n';
+                }
+                if (result.hasExpandedExpression()) {
+                    rss << "with expansion:\n";
+                    rss << Column(result.getExpandedExpression()).indent(2) << '\n';
+                }
+            } else {
+                rss << '\n';
+            }
+
+            if( !result.getMessage().empty() )
+                rss << result.getMessage() << '\n';
+            for( auto const& msg : stats.infoMessages )
+                if( msg.type == ResultWas::Info )
+                    rss << msg.message << '\n';
+
+            rss << "at " << result.getSourceInfo();
+            xml.writeText( rss.str(), XmlFormatting::Newline );
+        }
+    }
+
+    CATCH_REGISTER_REPORTER( "junit", JunitReporter )
+
+} // end namespace Catch
+// end catch_reporter_junit.cpp
+// start catch_reporter_listening.cpp
+
+#include <cassert>
+
+namespace Catch {
+
+    ListeningReporter::ListeningReporter() {
+        // We will assume that listeners will always want all assertions
+        m_preferences.shouldReportAllAssertions = true;
+    }
+
+    void ListeningReporter::addListener( IStreamingReporterPtr&& listener ) {
+        m_listeners.push_back( std::move( listener ) );
+    }
+
+    void ListeningReporter::addReporter(IStreamingReporterPtr&& reporter) {
+        assert(!m_reporter && "Listening reporter can wrap only 1 real reporter");
+        m_reporter = std::move( reporter );
+        m_preferences.shouldRedirectStdOut = m_reporter->getPreferences().shouldRedirectStdOut;
+    }
+
+    ReporterPreferences ListeningReporter::getPreferences() const {
+        return m_preferences;
+    }
+
+    std::set<Verbosity> ListeningReporter::getSupportedVerbosities() {
+        return std::set<Verbosity>{ };
+    }
+
+    void ListeningReporter::noMatchingTestCases( std::string const& spec ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->noMatchingTestCases( spec );
+        }
+        m_reporter->noMatchingTestCases( spec );
+    }
+
+    void ListeningReporter::reportInvalidArguments(std::string const&arg){
+        for ( auto const& listener : m_listeners ) {
+            listener->reportInvalidArguments( arg );
+        }
+        m_reporter->reportInvalidArguments( arg );
+    }
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    void ListeningReporter::benchmarkPreparing( std::string const& name ) {
+		for (auto const& listener : m_listeners) {
+			listener->benchmarkPreparing(name);
+		}
+		m_reporter->benchmarkPreparing(name);
+	}
+    void ListeningReporter::benchmarkStarting( BenchmarkInfo const& benchmarkInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->benchmarkStarting( benchmarkInfo );
+        }
+        m_reporter->benchmarkStarting( benchmarkInfo );
+    }
+    void ListeningReporter::benchmarkEnded( BenchmarkStats<> const& benchmarkStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->benchmarkEnded( benchmarkStats );
+        }
+        m_reporter->benchmarkEnded( benchmarkStats );
+    }
+
+	void ListeningReporter::benchmarkFailed( std::string const& error ) {
+		for (auto const& listener : m_listeners) {
+			listener->benchmarkFailed(error);
+		}
+		m_reporter->benchmarkFailed(error);
+	}
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    void ListeningReporter::testRunStarting( TestRunInfo const& testRunInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testRunStarting( testRunInfo );
+        }
+        m_reporter->testRunStarting( testRunInfo );
+    }
+
+    void ListeningReporter::testGroupStarting( GroupInfo const& groupInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testGroupStarting( groupInfo );
+        }
+        m_reporter->testGroupStarting( groupInfo );
+    }
+
+    void ListeningReporter::testCaseStarting( TestCaseInfo const& testInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testCaseStarting( testInfo );
+        }
+        m_reporter->testCaseStarting( testInfo );
+    }
+
+    void ListeningReporter::sectionStarting( SectionInfo const& sectionInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->sectionStarting( sectionInfo );
+        }
+        m_reporter->sectionStarting( sectionInfo );
+    }
+
+    void ListeningReporter::assertionStarting( AssertionInfo const& assertionInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->assertionStarting( assertionInfo );
+        }
+        m_reporter->assertionStarting( assertionInfo );
+    }
+
+    // The return value indicates if the messages buffer should be cleared:
+    bool ListeningReporter::assertionEnded( AssertionStats const& assertionStats ) {
+        for( auto const& listener : m_listeners ) {
+            static_cast<void>( listener->assertionEnded( assertionStats ) );
+        }
+        return m_reporter->assertionEnded( assertionStats );
+    }
+
+    void ListeningReporter::sectionEnded( SectionStats const& sectionStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->sectionEnded( sectionStats );
+        }
+        m_reporter->sectionEnded( sectionStats );
+    }
+
+    void ListeningReporter::testCaseEnded( TestCaseStats const& testCaseStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testCaseEnded( testCaseStats );
+        }
+        m_reporter->testCaseEnded( testCaseStats );
+    }
+
+    void ListeningReporter::testGroupEnded( TestGroupStats const& testGroupStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testGroupEnded( testGroupStats );
+        }
+        m_reporter->testGroupEnded( testGroupStats );
+    }
+
+    void ListeningReporter::testRunEnded( TestRunStats const& testRunStats ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->testRunEnded( testRunStats );
+        }
+        m_reporter->testRunEnded( testRunStats );
+    }
+
+    void ListeningReporter::skipTest( TestCaseInfo const& testInfo ) {
+        for ( auto const& listener : m_listeners ) {
+            listener->skipTest( testInfo );
+        }
+        m_reporter->skipTest( testInfo );
+    }
+
+    bool ListeningReporter::isMulti() const {
+        return true;
+    }
+
+} // end namespace Catch
+// end catch_reporter_listening.cpp
+// start catch_reporter_xml.cpp
+
+#if defined(_MSC_VER)
+#pragma warning(push)
+#pragma warning(disable:4061) // Not all labels are EXPLICITLY handled in switch
+                              // Note that 4062 (not all labels are handled
+                              // and default is missing) is enabled
+#endif
+
+namespace Catch {
+    XmlReporter::XmlReporter( ReporterConfig const& _config )
+    :   StreamingReporterBase( _config ),
+        m_xml(_config.stream())
+    {
+        m_reporterPrefs.shouldRedirectStdOut = true;
+        m_reporterPrefs.shouldReportAllAssertions = true;
+    }
+
+    XmlReporter::~XmlReporter() = default;
+
+    std::string XmlReporter::getDescription() {
+        return "Reports test results as an XML document";
+    }
+
+    std::string XmlReporter::getStylesheetRef() const {
+        return std::string();
+    }
+
+    void XmlReporter::writeSourceInfo( SourceLineInfo const& sourceInfo ) {
+        m_xml
+            .writeAttribute( "filename", sourceInfo.file )
+            .writeAttribute( "line", sourceInfo.line );
+    }
+
+    void XmlReporter::noMatchingTestCases( std::string const& s ) {
+        StreamingReporterBase::noMatchingTestCases( s );
+    }
+
+    void XmlReporter::testRunStarting( TestRunInfo const& testInfo ) {
+        StreamingReporterBase::testRunStarting( testInfo );
+        std::string stylesheetRef = getStylesheetRef();
+        if( !stylesheetRef.empty() )
+            m_xml.writeStylesheetRef( stylesheetRef );
+        m_xml.startElement( "Catch" );
+        if( !m_config->name().empty() )
+            m_xml.writeAttribute( "name", m_config->name() );
+        if (m_config->testSpec().hasFilters())
+            m_xml.writeAttribute( "filters", serializeFilters( m_config->getTestsOrTags() ) );
+        if( m_config->rngSeed() != 0 )
+            m_xml.scopedElement( "Randomness" )
+                .writeAttribute( "seed", m_config->rngSeed() );
+    }
+
+    void XmlReporter::testGroupStarting( GroupInfo const& groupInfo ) {
+        StreamingReporterBase::testGroupStarting( groupInfo );
+        m_xml.startElement( "Group" )
+            .writeAttribute( "name", groupInfo.name );
+    }
+
+    void XmlReporter::testCaseStarting( TestCaseInfo const& testInfo ) {
+        StreamingReporterBase::testCaseStarting(testInfo);
+        m_xml.startElement( "TestCase" )
+            .writeAttribute( "name", trim( testInfo.name ) )
+            .writeAttribute( "description", testInfo.description )
+            .writeAttribute( "tags", testInfo.tagsAsString() );
+
+        writeSourceInfo( testInfo.lineInfo );
+
+        if ( m_config->showDurations() == ShowDurations::Always )
+            m_testCaseTimer.start();
+        m_xml.ensureTagClosed();
+    }
+
+    void XmlReporter::sectionStarting( SectionInfo const& sectionInfo ) {
+        StreamingReporterBase::sectionStarting( sectionInfo );
+        if( m_sectionDepth++ > 0 ) {
+            m_xml.startElement( "Section" )
+                .writeAttribute( "name", trim( sectionInfo.name ) );
+            writeSourceInfo( sectionInfo.lineInfo );
+            m_xml.ensureTagClosed();
+        }
+    }
+
+    void XmlReporter::assertionStarting( AssertionInfo const& ) { }
+
+    bool XmlReporter::assertionEnded( AssertionStats const& assertionStats ) {
+
+        AssertionResult const& result = assertionStats.assertionResult;
+
+        bool includeResults = m_config->includeSuccessfulResults() || !result.isOk();
+
+        if( includeResults || result.getResultType() == ResultWas::Warning ) {
+            // Print any info messages in <Info> tags.
+            for( auto const& msg : assertionStats.infoMessages ) {
+                if( msg.type == ResultWas::Info && includeResults ) {
+                    m_xml.scopedElement( "Info" )
+                            .writeText( msg.message );
+                } else if ( msg.type == ResultWas::Warning ) {
+                    m_xml.scopedElement( "Warning" )
+                            .writeText( msg.message );
+                }
+            }
+        }
+
+        // Drop out if result was successful but we're not printing them.
+        if( !includeResults && result.getResultType() != ResultWas::Warning )
+            return true;
+
+        // Print the expression if there is one.
+        if( result.hasExpression() ) {
+            m_xml.startElement( "Expression" )
+                .writeAttribute( "success", result.succeeded() )
+                .writeAttribute( "type", result.getTestMacroName() );
+
+            writeSourceInfo( result.getSourceInfo() );
+
+            m_xml.scopedElement( "Original" )
+                .writeText( result.getExpression() );
+            m_xml.scopedElement( "Expanded" )
+                .writeText( result.getExpandedExpression() );
+        }
+
+        // And... Print a result applicable to each result type.
+        switch( result.getResultType() ) {
+            case ResultWas::ThrewException:
+                m_xml.startElement( "Exception" );
+                writeSourceInfo( result.getSourceInfo() );
+                m_xml.writeText( result.getMessage() );
+                m_xml.endElement();
+                break;
+            case ResultWas::FatalErrorCondition:
+                m_xml.startElement( "FatalErrorCondition" );
+                writeSourceInfo( result.getSourceInfo() );
+                m_xml.writeText( result.getMessage() );
+                m_xml.endElement();
+                break;
+            case ResultWas::Info:
+                m_xml.scopedElement( "Info" )
+                    .writeText( result.getMessage() );
+                break;
+            case ResultWas::Warning:
+                // Warning will already have been written
+                break;
+            case ResultWas::ExplicitFailure:
+                m_xml.startElement( "Failure" );
+                writeSourceInfo( result.getSourceInfo() );
+                m_xml.writeText( result.getMessage() );
+                m_xml.endElement();
+                break;
+            default:
+                break;
+        }
+
+        if( result.hasExpression() )
+            m_xml.endElement();
+
+        return true;
+    }
+
+    void XmlReporter::sectionEnded( SectionStats const& sectionStats ) {
+        StreamingReporterBase::sectionEnded( sectionStats );
+        if( --m_sectionDepth > 0 ) {
+            XmlWriter::ScopedElement e = m_xml.scopedElement( "OverallResults" );
+            e.writeAttribute( "successes", sectionStats.assertions.passed );
+            e.writeAttribute( "failures", sectionStats.assertions.failed );
+            e.writeAttribute( "expectedFailures", sectionStats.assertions.failedButOk );
+
+            if ( m_config->showDurations() == ShowDurations::Always )
+                e.writeAttribute( "durationInSeconds", sectionStats.durationInSeconds );
+
+            m_xml.endElement();
+        }
+    }
+
+    void XmlReporter::testCaseEnded( TestCaseStats const& testCaseStats ) {
+        StreamingReporterBase::testCaseEnded( testCaseStats );
+        XmlWriter::ScopedElement e = m_xml.scopedElement( "OverallResult" );
+        e.writeAttribute( "success", testCaseStats.totals.assertions.allOk() );
+
+        if ( m_config->showDurations() == ShowDurations::Always )
+            e.writeAttribute( "durationInSeconds", m_testCaseTimer.getElapsedSeconds() );
+
+        if( !testCaseStats.stdOut.empty() )
+            m_xml.scopedElement( "StdOut" ).writeText( trim( testCaseStats.stdOut ), XmlFormatting::Newline );
+        if( !testCaseStats.stdErr.empty() )
+            m_xml.scopedElement( "StdErr" ).writeText( trim( testCaseStats.stdErr ), XmlFormatting::Newline );
+
+        m_xml.endElement();
+    }
+
+    void XmlReporter::testGroupEnded( TestGroupStats const& testGroupStats ) {
+        StreamingReporterBase::testGroupEnded( testGroupStats );
+        // TODO: Check testGroupStats.aborting and act accordingly.
+        m_xml.scopedElement( "OverallResults" )
+            .writeAttribute( "successes", testGroupStats.totals.assertions.passed )
+            .writeAttribute( "failures", testGroupStats.totals.assertions.failed )
+            .writeAttribute( "expectedFailures", testGroupStats.totals.assertions.failedButOk );
+        m_xml.scopedElement( "OverallResultsCases")
+            .writeAttribute( "successes", testGroupStats.totals.testCases.passed )
+            .writeAttribute( "failures", testGroupStats.totals.testCases.failed )
+            .writeAttribute( "expectedFailures", testGroupStats.totals.testCases.failedButOk );
+        m_xml.endElement();
+    }
+
+    void XmlReporter::testRunEnded( TestRunStats const& testRunStats ) {
+        StreamingReporterBase::testRunEnded( testRunStats );
+        m_xml.scopedElement( "OverallResults" )
+            .writeAttribute( "successes", testRunStats.totals.assertions.passed )
+            .writeAttribute( "failures", testRunStats.totals.assertions.failed )
+            .writeAttribute( "expectedFailures", testRunStats.totals.assertions.failedButOk );
+        m_xml.scopedElement( "OverallResultsCases")
+            .writeAttribute( "successes", testRunStats.totals.testCases.passed )
+            .writeAttribute( "failures", testRunStats.totals.testCases.failed )
+            .writeAttribute( "expectedFailures", testRunStats.totals.testCases.failedButOk );
+        m_xml.endElement();
+    }
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+    void XmlReporter::benchmarkPreparing(std::string const& name) {
+        m_xml.startElement("BenchmarkResults")
+            .writeAttribute("name", name);
+    }
+
+    void XmlReporter::benchmarkStarting(BenchmarkInfo const &info) {
+        m_xml.writeAttribute("samples", info.samples)
+            .writeAttribute("resamples", info.resamples)
+            .writeAttribute("iterations", info.iterations)
+            .writeAttribute("clockResolution", info.clockResolution)
+            .writeAttribute("estimatedDuration", info.estimatedDuration)
+            .writeComment("All values in nano seconds");
+    }
+
+    void XmlReporter::benchmarkEnded(BenchmarkStats<> const& benchmarkStats) {
+        m_xml.startElement("mean")
+            .writeAttribute("value", benchmarkStats.mean.point.count())
+            .writeAttribute("lowerBound", benchmarkStats.mean.lower_bound.count())
+            .writeAttribute("upperBound", benchmarkStats.mean.upper_bound.count())
+            .writeAttribute("ci", benchmarkStats.mean.confidence_interval);
+        m_xml.endElement();
+        m_xml.startElement("standardDeviation")
+            .writeAttribute("value", benchmarkStats.standardDeviation.point.count())
+            .writeAttribute("lowerBound", benchmarkStats.standardDeviation.lower_bound.count())
+            .writeAttribute("upperBound", benchmarkStats.standardDeviation.upper_bound.count())
+            .writeAttribute("ci", benchmarkStats.standardDeviation.confidence_interval);
+        m_xml.endElement();
+        m_xml.startElement("outliers")
+            .writeAttribute("variance", benchmarkStats.outlierVariance)
+            .writeAttribute("lowMild", benchmarkStats.outliers.low_mild)
+            .writeAttribute("lowSevere", benchmarkStats.outliers.low_severe)
+            .writeAttribute("highMild", benchmarkStats.outliers.high_mild)
+            .writeAttribute("highSevere", benchmarkStats.outliers.high_severe);
+        m_xml.endElement();
+        m_xml.endElement();
+    }
+
+    void XmlReporter::benchmarkFailed(std::string const &error) {
+        m_xml.scopedElement("failed").
+            writeAttribute("message", error);
+        m_xml.endElement();
+    }
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+    CATCH_REGISTER_REPORTER( "xml", XmlReporter )
+
+} // end namespace Catch
+
+#if defined(_MSC_VER)
+#pragma warning(pop)
+#endif
+// end catch_reporter_xml.cpp
+
+namespace Catch {
+    LeakDetector leakDetector;
+}
+
+#ifdef __clang__
+#pragma clang diagnostic pop
+#endif
+
+// end catch_impl.hpp
+#endif
+
+#ifdef CATCH_CONFIG_MAIN
+// start catch_default_main.hpp
+
+#ifndef __OBJC__
+
+#if defined(CATCH_CONFIG_WCHAR) && defined(CATCH_PLATFORM_WINDOWS) && defined(_UNICODE) && !defined(DO_NOT_USE_WMAIN)
+// Standard C/C++ Win32 Unicode wmain entry point
+extern "C" int wmain (int argc, wchar_t * argv[], wchar_t * []) {
+#else
+// Standard C/C++ main entry point
+int main (int argc, char * argv[]) {
+#endif
+
+    return Catch::Session().run( argc, argv );
+}
+
+#else // __OBJC__
+
+// Objective-C entry point
+int main (int argc, char * const argv[]) {
+#if !CATCH_ARC_ENABLED
+    NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
+#endif
+
+    Catch::registerTestMethods();
+    int result = Catch::Session().run( argc, (char**)argv );
+
+#if !CATCH_ARC_ENABLED
+    [pool drain];
+#endif
+
+    return result;
+}
+
+#endif // __OBJC__
+
+// end catch_default_main.hpp
+#endif
+
+#if !defined(CATCH_CONFIG_IMPL_ONLY)
+
+#ifdef CLARA_CONFIG_MAIN_NOT_DEFINED
+#  undef CLARA_CONFIG_MAIN
+#endif
+
+#if !defined(CATCH_CONFIG_DISABLE)
+//////
+// If this config identifier is defined then all CATCH macros are prefixed with CATCH_
+#ifdef CATCH_CONFIG_PREFIX_ALL
+
+#define CATCH_REQUIRE( ... ) INTERNAL_CATCH_TEST( "CATCH_REQUIRE", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define CATCH_REQUIRE_FALSE( ... ) INTERNAL_CATCH_TEST( "CATCH_REQUIRE_FALSE", Catch::ResultDisposition::Normal | Catch::ResultDisposition::FalseTest, __VA_ARGS__ )
+
+#define CATCH_REQUIRE_THROWS( ... ) INTERNAL_CATCH_THROWS( "CATCH_REQUIRE_THROWS", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define CATCH_REQUIRE_THROWS_AS( expr, exceptionType ) INTERNAL_CATCH_THROWS_AS( "CATCH_REQUIRE_THROWS_AS", exceptionType, Catch::ResultDisposition::Normal, expr )
+#define CATCH_REQUIRE_THROWS_WITH( expr, matcher ) INTERNAL_CATCH_THROWS_STR_MATCHES( "CATCH_REQUIRE_THROWS_WITH", Catch::ResultDisposition::Normal, matcher, expr )
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_REQUIRE_THROWS_MATCHES( expr, exceptionType, matcher ) INTERNAL_CATCH_THROWS_MATCHES( "CATCH_REQUIRE_THROWS_MATCHES", exceptionType, Catch::ResultDisposition::Normal, matcher, expr )
+#endif// CATCH_CONFIG_DISABLE_MATCHERS
+#define CATCH_REQUIRE_NOTHROW( ... ) INTERNAL_CATCH_NO_THROW( "CATCH_REQUIRE_NOTHROW", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+
+#define CATCH_CHECK( ... ) INTERNAL_CATCH_TEST( "CATCH_CHECK", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_CHECK_FALSE( ... ) INTERNAL_CATCH_TEST( "CATCH_CHECK_FALSE", Catch::ResultDisposition::ContinueOnFailure | Catch::ResultDisposition::FalseTest, __VA_ARGS__ )
+#define CATCH_CHECKED_IF( ... ) INTERNAL_CATCH_IF( "CATCH_CHECKED_IF", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_CHECKED_ELSE( ... ) INTERNAL_CATCH_ELSE( "CATCH_CHECKED_ELSE", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_CHECK_NOFAIL( ... ) INTERNAL_CATCH_TEST( "CATCH_CHECK_NOFAIL", Catch::ResultDisposition::ContinueOnFailure | Catch::ResultDisposition::SuppressFail, __VA_ARGS__ )
+
+#define CATCH_CHECK_THROWS( ... )  INTERNAL_CATCH_THROWS( "CATCH_CHECK_THROWS", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_CHECK_THROWS_AS( expr, exceptionType ) INTERNAL_CATCH_THROWS_AS( "CATCH_CHECK_THROWS_AS", exceptionType, Catch::ResultDisposition::ContinueOnFailure, expr )
+#define CATCH_CHECK_THROWS_WITH( expr, matcher ) INTERNAL_CATCH_THROWS_STR_MATCHES( "CATCH_CHECK_THROWS_WITH", Catch::ResultDisposition::ContinueOnFailure, matcher, expr )
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_CHECK_THROWS_MATCHES( expr, exceptionType, matcher ) INTERNAL_CATCH_THROWS_MATCHES( "CATCH_CHECK_THROWS_MATCHES", exceptionType, Catch::ResultDisposition::ContinueOnFailure, matcher, expr )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define CATCH_CHECK_NOTHROW( ... ) INTERNAL_CATCH_NO_THROW( "CATCH_CHECK_NOTHROW", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_CHECK_THAT( arg, matcher ) INTERNAL_CHECK_THAT( "CATCH_CHECK_THAT", matcher, Catch::ResultDisposition::ContinueOnFailure, arg )
+
+#define CATCH_REQUIRE_THAT( arg, matcher ) INTERNAL_CHECK_THAT( "CATCH_REQUIRE_THAT", matcher, Catch::ResultDisposition::Normal, arg )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+#define CATCH_INFO( msg ) INTERNAL_CATCH_INFO( "CATCH_INFO", msg )
+#define CATCH_UNSCOPED_INFO( msg ) INTERNAL_CATCH_UNSCOPED_INFO( "CATCH_UNSCOPED_INFO", msg )
+#define CATCH_WARN( msg ) INTERNAL_CATCH_MSG( "CATCH_WARN", Catch::ResultWas::Warning, Catch::ResultDisposition::ContinueOnFailure, msg )
+#define CATCH_CAPTURE( ... ) INTERNAL_CATCH_CAPTURE( INTERNAL_CATCH_UNIQUE_NAME(capturer), "CATCH_CAPTURE",__VA_ARGS__ )
+
+#define CATCH_TEST_CASE( ... ) INTERNAL_CATCH_TESTCASE( __VA_ARGS__ )
+#define CATCH_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_METHOD_AS_TEST_CASE( method, ... ) INTERNAL_CATCH_METHOD_AS_TEST_CASE( method, __VA_ARGS__ )
+#define CATCH_REGISTER_TEST_CASE( Function, ... ) INTERNAL_CATCH_REGISTER_TESTCASE( Function, __VA_ARGS__ )
+#define CATCH_SECTION( ... ) INTERNAL_CATCH_SECTION( __VA_ARGS__ )
+#define CATCH_DYNAMIC_SECTION( ... ) INTERNAL_CATCH_DYNAMIC_SECTION( __VA_ARGS__ )
+#define CATCH_FAIL( ... ) INTERNAL_CATCH_MSG( "CATCH_FAIL", Catch::ResultWas::ExplicitFailure, Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define CATCH_FAIL_CHECK( ... ) INTERNAL_CATCH_MSG( "CATCH_FAIL_CHECK", Catch::ResultWas::ExplicitFailure, Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CATCH_SUCCEED( ... ) INTERNAL_CATCH_MSG( "CATCH_SUCCEED", Catch::ResultWas::Ok, Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+
+#define CATCH_ANON_TEST_CASE() INTERNAL_CATCH_TESTCASE()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define CATCH_TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG( __VA_ARGS__ )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ )
+#else
+#define CATCH_TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG( __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE( __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ ) )
+#endif
+
+#if !defined(CATCH_CONFIG_RUNTIME_STATIC_REQUIRE)
+#define CATCH_STATIC_REQUIRE( ... )       static_assert(   __VA_ARGS__ ,      #__VA_ARGS__ );     CATCH_SUCCEED( #__VA_ARGS__ )
+#define CATCH_STATIC_REQUIRE_FALSE( ... ) static_assert( !(__VA_ARGS__), "!(" #__VA_ARGS__ ")" ); CATCH_SUCCEED( #__VA_ARGS__ )
+#else
+#define CATCH_STATIC_REQUIRE( ... )       CATCH_REQUIRE( __VA_ARGS__ )
+#define CATCH_STATIC_REQUIRE_FALSE( ... ) CATCH_REQUIRE_FALSE( __VA_ARGS__ )
+#endif
+
+// "BDD-style" convenience wrappers
+#define CATCH_SCENARIO( ... ) CATCH_TEST_CASE( "Scenario: " __VA_ARGS__ )
+#define CATCH_SCENARIO_METHOD( className, ... ) INTERNAL_CATCH_TEST_CASE_METHOD( className, "Scenario: " __VA_ARGS__ )
+#define CATCH_GIVEN( desc )     INTERNAL_CATCH_DYNAMIC_SECTION( "    Given: " << desc )
+#define CATCH_AND_GIVEN( desc ) INTERNAL_CATCH_DYNAMIC_SECTION( "And given: " << desc )
+#define CATCH_WHEN( desc )      INTERNAL_CATCH_DYNAMIC_SECTION( "     When: " << desc )
+#define CATCH_AND_WHEN( desc )  INTERNAL_CATCH_DYNAMIC_SECTION( " And when: " << desc )
+#define CATCH_THEN( desc )      INTERNAL_CATCH_DYNAMIC_SECTION( "     Then: " << desc )
+#define CATCH_AND_THEN( desc )  INTERNAL_CATCH_DYNAMIC_SECTION( "      And: " << desc )
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+#define CATCH_BENCHMARK(...) \
+    INTERNAL_CATCH_BENCHMARK(INTERNAL_CATCH_UNIQUE_NAME(C_A_T_C_H_B_E_N_C_H_), INTERNAL_CATCH_GET_1_ARG(__VA_ARGS__,,), INTERNAL_CATCH_GET_2_ARG(__VA_ARGS__,,))
+#define CATCH_BENCHMARK_ADVANCED(name) \
+    INTERNAL_CATCH_BENCHMARK_ADVANCED(INTERNAL_CATCH_UNIQUE_NAME(C_A_T_C_H_B_E_N_C_H_), name)
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+// If CATCH_CONFIG_PREFIX_ALL is not defined then the CATCH_ prefix is not required
+#else
+
+#define REQUIRE( ... ) INTERNAL_CATCH_TEST( "REQUIRE", Catch::ResultDisposition::Normal, __VA_ARGS__  )
+#define REQUIRE_FALSE( ... ) INTERNAL_CATCH_TEST( "REQUIRE_FALSE", Catch::ResultDisposition::Normal | Catch::ResultDisposition::FalseTest, __VA_ARGS__ )
+
+#define REQUIRE_THROWS( ... ) INTERNAL_CATCH_THROWS( "REQUIRE_THROWS", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define REQUIRE_THROWS_AS( expr, exceptionType ) INTERNAL_CATCH_THROWS_AS( "REQUIRE_THROWS_AS", exceptionType, Catch::ResultDisposition::Normal, expr )
+#define REQUIRE_THROWS_WITH( expr, matcher ) INTERNAL_CATCH_THROWS_STR_MATCHES( "REQUIRE_THROWS_WITH", Catch::ResultDisposition::Normal, matcher, expr )
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define REQUIRE_THROWS_MATCHES( expr, exceptionType, matcher ) INTERNAL_CATCH_THROWS_MATCHES( "REQUIRE_THROWS_MATCHES", exceptionType, Catch::ResultDisposition::Normal, matcher, expr )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define REQUIRE_NOTHROW( ... ) INTERNAL_CATCH_NO_THROW( "REQUIRE_NOTHROW", Catch::ResultDisposition::Normal, __VA_ARGS__ )
+
+#define CHECK( ... ) INTERNAL_CATCH_TEST( "CHECK", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CHECK_FALSE( ... ) INTERNAL_CATCH_TEST( "CHECK_FALSE", Catch::ResultDisposition::ContinueOnFailure | Catch::ResultDisposition::FalseTest, __VA_ARGS__ )
+#define CHECKED_IF( ... ) INTERNAL_CATCH_IF( "CHECKED_IF", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CHECKED_ELSE( ... ) INTERNAL_CATCH_ELSE( "CHECKED_ELSE", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CHECK_NOFAIL( ... ) INTERNAL_CATCH_TEST( "CHECK_NOFAIL", Catch::ResultDisposition::ContinueOnFailure | Catch::ResultDisposition::SuppressFail, __VA_ARGS__ )
+
+#define CHECK_THROWS( ... )  INTERNAL_CATCH_THROWS( "CHECK_THROWS", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define CHECK_THROWS_AS( expr, exceptionType ) INTERNAL_CATCH_THROWS_AS( "CHECK_THROWS_AS", exceptionType, Catch::ResultDisposition::ContinueOnFailure, expr )
+#define CHECK_THROWS_WITH( expr, matcher ) INTERNAL_CATCH_THROWS_STR_MATCHES( "CHECK_THROWS_WITH", Catch::ResultDisposition::ContinueOnFailure, matcher, expr )
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CHECK_THROWS_MATCHES( expr, exceptionType, matcher ) INTERNAL_CATCH_THROWS_MATCHES( "CHECK_THROWS_MATCHES", exceptionType, Catch::ResultDisposition::ContinueOnFailure, matcher, expr )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define CHECK_NOTHROW( ... ) INTERNAL_CATCH_NO_THROW( "CHECK_NOTHROW", Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CHECK_THAT( arg, matcher ) INTERNAL_CHECK_THAT( "CHECK_THAT", matcher, Catch::ResultDisposition::ContinueOnFailure, arg )
+
+#define REQUIRE_THAT( arg, matcher ) INTERNAL_CHECK_THAT( "REQUIRE_THAT", matcher, Catch::ResultDisposition::Normal, arg )
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+#define INFO( msg ) INTERNAL_CATCH_INFO( "INFO", msg )
+#define UNSCOPED_INFO( msg ) INTERNAL_CATCH_UNSCOPED_INFO( "UNSCOPED_INFO", msg )
+#define WARN( msg ) INTERNAL_CATCH_MSG( "WARN", Catch::ResultWas::Warning, Catch::ResultDisposition::ContinueOnFailure, msg )
+#define CAPTURE( ... ) INTERNAL_CATCH_CAPTURE( INTERNAL_CATCH_UNIQUE_NAME(capturer), "CAPTURE",__VA_ARGS__ )
+
+#define TEST_CASE( ... ) INTERNAL_CATCH_TESTCASE( __VA_ARGS__ )
+#define TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define METHOD_AS_TEST_CASE( method, ... ) INTERNAL_CATCH_METHOD_AS_TEST_CASE( method, __VA_ARGS__ )
+#define REGISTER_TEST_CASE( Function, ... ) INTERNAL_CATCH_REGISTER_TESTCASE( Function, __VA_ARGS__ )
+#define SECTION( ... ) INTERNAL_CATCH_SECTION( __VA_ARGS__ )
+#define DYNAMIC_SECTION( ... ) INTERNAL_CATCH_DYNAMIC_SECTION( __VA_ARGS__ )
+#define FAIL( ... ) INTERNAL_CATCH_MSG( "FAIL", Catch::ResultWas::ExplicitFailure, Catch::ResultDisposition::Normal, __VA_ARGS__ )
+#define FAIL_CHECK( ... ) INTERNAL_CATCH_MSG( "FAIL_CHECK", Catch::ResultWas::ExplicitFailure, Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define SUCCEED( ... ) INTERNAL_CATCH_MSG( "SUCCEED", Catch::ResultWas::Ok, Catch::ResultDisposition::ContinueOnFailure, __VA_ARGS__ )
+#define ANON_TEST_CASE() INTERNAL_CATCH_TESTCASE()
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG( __VA_ARGS__ )
+#define TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ )
+#define TEMPLATE_LIST_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE(__VA_ARGS__)
+#define TEMPLATE_LIST_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#else
+#define TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ ) )
+#define TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG( __VA_ARGS__ ) )
+#define TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#define TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE( __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, __VA_ARGS__ ) )
+#define TEMPLATE_LIST_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE( __VA_ARGS__ ) )
+#define TEMPLATE_LIST_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_LIST_TEST_CASE_METHOD( className, __VA_ARGS__ ) )
+#endif
+
+#if !defined(CATCH_CONFIG_RUNTIME_STATIC_REQUIRE)
+#define STATIC_REQUIRE( ... )       static_assert(   __VA_ARGS__,  #__VA_ARGS__ ); SUCCEED( #__VA_ARGS__ )
+#define STATIC_REQUIRE_FALSE( ... ) static_assert( !(__VA_ARGS__), "!(" #__VA_ARGS__ ")" ); SUCCEED( "!(" #__VA_ARGS__ ")" )
+#else
+#define STATIC_REQUIRE( ... )       REQUIRE( __VA_ARGS__ )
+#define STATIC_REQUIRE_FALSE( ... ) REQUIRE_FALSE( __VA_ARGS__ )
+#endif
+
+#endif
+
+#define CATCH_TRANSLATE_EXCEPTION( signature ) INTERNAL_CATCH_TRANSLATE_EXCEPTION( signature )
+
+// "BDD-style" convenience wrappers
+#define SCENARIO( ... ) TEST_CASE( "Scenario: " __VA_ARGS__ )
+#define SCENARIO_METHOD( className, ... ) INTERNAL_CATCH_TEST_CASE_METHOD( className, "Scenario: " __VA_ARGS__ )
+
+#define GIVEN( desc )     INTERNAL_CATCH_DYNAMIC_SECTION( "    Given: " << desc )
+#define AND_GIVEN( desc ) INTERNAL_CATCH_DYNAMIC_SECTION( "And given: " << desc )
+#define WHEN( desc )      INTERNAL_CATCH_DYNAMIC_SECTION( "     When: " << desc )
+#define AND_WHEN( desc )  INTERNAL_CATCH_DYNAMIC_SECTION( " And when: " << desc )
+#define THEN( desc )      INTERNAL_CATCH_DYNAMIC_SECTION( "     Then: " << desc )
+#define AND_THEN( desc )  INTERNAL_CATCH_DYNAMIC_SECTION( "      And: " << desc )
+
+#if defined(CATCH_CONFIG_ENABLE_BENCHMARKING)
+#define BENCHMARK(...) \
+    INTERNAL_CATCH_BENCHMARK(INTERNAL_CATCH_UNIQUE_NAME(C_A_T_C_H_B_E_N_C_H_), INTERNAL_CATCH_GET_1_ARG(__VA_ARGS__,,), INTERNAL_CATCH_GET_2_ARG(__VA_ARGS__,,))
+#define BENCHMARK_ADVANCED(name) \
+    INTERNAL_CATCH_BENCHMARK_ADVANCED(INTERNAL_CATCH_UNIQUE_NAME(C_A_T_C_H_B_E_N_C_H_), name)
+#endif // CATCH_CONFIG_ENABLE_BENCHMARKING
+
+using Catch::Detail::Approx;
+
+#else // CATCH_CONFIG_DISABLE
+
+//////
+// If this config identifier is defined then all CATCH macros are prefixed with CATCH_
+#ifdef CATCH_CONFIG_PREFIX_ALL
+
+#define CATCH_REQUIRE( ... )        (void)(0)
+#define CATCH_REQUIRE_FALSE( ... )  (void)(0)
+
+#define CATCH_REQUIRE_THROWS( ... ) (void)(0)
+#define CATCH_REQUIRE_THROWS_AS( expr, exceptionType ) (void)(0)
+#define CATCH_REQUIRE_THROWS_WITH( expr, matcher )     (void)(0)
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_REQUIRE_THROWS_MATCHES( expr, exceptionType, matcher ) (void)(0)
+#endif// CATCH_CONFIG_DISABLE_MATCHERS
+#define CATCH_REQUIRE_NOTHROW( ... ) (void)(0)
+
+#define CATCH_CHECK( ... )         (void)(0)
+#define CATCH_CHECK_FALSE( ... )   (void)(0)
+#define CATCH_CHECKED_IF( ... )    if (__VA_ARGS__)
+#define CATCH_CHECKED_ELSE( ... )  if (!(__VA_ARGS__))
+#define CATCH_CHECK_NOFAIL( ... )  (void)(0)
+
+#define CATCH_CHECK_THROWS( ... )  (void)(0)
+#define CATCH_CHECK_THROWS_AS( expr, exceptionType ) (void)(0)
+#define CATCH_CHECK_THROWS_WITH( expr, matcher )     (void)(0)
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_CHECK_THROWS_MATCHES( expr, exceptionType, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define CATCH_CHECK_NOTHROW( ... ) (void)(0)
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CATCH_CHECK_THAT( arg, matcher )   (void)(0)
+
+#define CATCH_REQUIRE_THAT( arg, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+#define CATCH_INFO( msg )          (void)(0)
+#define CATCH_UNSCOPED_INFO( msg ) (void)(0)
+#define CATCH_WARN( msg )          (void)(0)
+#define CATCH_CAPTURE( msg )       (void)(0)
+
+#define CATCH_TEST_CASE( ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ))
+#define CATCH_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ))
+#define CATCH_METHOD_AS_TEST_CASE( method, ... )
+#define CATCH_REGISTER_TEST_CASE( Function, ... ) (void)(0)
+#define CATCH_SECTION( ... )
+#define CATCH_DYNAMIC_SECTION( ... )
+#define CATCH_FAIL( ... ) (void)(0)
+#define CATCH_FAIL_CHECK( ... ) (void)(0)
+#define CATCH_SUCCEED( ... ) (void)(0)
+
+#define CATCH_ANON_TEST_CASE() INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ))
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define CATCH_TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(__VA_ARGS__)
+#define CATCH_TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(__VA_ARGS__)
+#define CATCH_TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION(className, __VA_ARGS__)
+#define CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION(className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE( ... ) CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#else
+#define CATCH_TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(__VA_ARGS__) )
+#define CATCH_TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(__VA_ARGS__) )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION(className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION(className, __VA_ARGS__ ) )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE( ... ) CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) CATCH_TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define CATCH_TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) CATCH_TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#endif
+
+// "BDD-style" convenience wrappers
+#define CATCH_SCENARIO( ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ))
+#define CATCH_SCENARIO_METHOD( className, ... ) INTERNAL_CATCH_TESTCASE_METHOD_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ), className )
+#define CATCH_GIVEN( desc )
+#define CATCH_AND_GIVEN( desc )
+#define CATCH_WHEN( desc )
+#define CATCH_AND_WHEN( desc )
+#define CATCH_THEN( desc )
+#define CATCH_AND_THEN( desc )
+
+#define CATCH_STATIC_REQUIRE( ... )       (void)(0)
+#define CATCH_STATIC_REQUIRE_FALSE( ... ) (void)(0)
+
+// If CATCH_CONFIG_PREFIX_ALL is not defined then the CATCH_ prefix is not required
+#else
+
+#define REQUIRE( ... )       (void)(0)
+#define REQUIRE_FALSE( ... ) (void)(0)
+
+#define REQUIRE_THROWS( ... ) (void)(0)
+#define REQUIRE_THROWS_AS( expr, exceptionType ) (void)(0)
+#define REQUIRE_THROWS_WITH( expr, matcher ) (void)(0)
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define REQUIRE_THROWS_MATCHES( expr, exceptionType, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define REQUIRE_NOTHROW( ... ) (void)(0)
+
+#define CHECK( ... ) (void)(0)
+#define CHECK_FALSE( ... ) (void)(0)
+#define CHECKED_IF( ... ) if (__VA_ARGS__)
+#define CHECKED_ELSE( ... ) if (!(__VA_ARGS__))
+#define CHECK_NOFAIL( ... ) (void)(0)
+
+#define CHECK_THROWS( ... )  (void)(0)
+#define CHECK_THROWS_AS( expr, exceptionType ) (void)(0)
+#define CHECK_THROWS_WITH( expr, matcher ) (void)(0)
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CHECK_THROWS_MATCHES( expr, exceptionType, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+#define CHECK_NOTHROW( ... ) (void)(0)
+
+#if !defined(CATCH_CONFIG_DISABLE_MATCHERS)
+#define CHECK_THAT( arg, matcher ) (void)(0)
+
+#define REQUIRE_THAT( arg, matcher ) (void)(0)
+#endif // CATCH_CONFIG_DISABLE_MATCHERS
+
+#define INFO( msg ) (void)(0)
+#define UNSCOPED_INFO( msg ) (void)(0)
+#define WARN( msg ) (void)(0)
+#define CAPTURE( ... ) (void)(0)
+
+#define TEST_CASE( ... )  INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ))
+#define TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ))
+#define METHOD_AS_TEST_CASE( method, ... )
+#define REGISTER_TEST_CASE( Function, ... ) (void)(0)
+#define SECTION( ... )
+#define DYNAMIC_SECTION( ... )
+#define FAIL( ... ) (void)(0)
+#define FAIL_CHECK( ... ) (void)(0)
+#define SUCCEED( ... ) (void)(0)
+#define ANON_TEST_CASE() INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ))
+
+#ifndef CATCH_CONFIG_TRADITIONAL_MSVC_PREPROCESSOR
+#define TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(__VA_ARGS__)
+#define TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(__VA_ARGS__)
+#define TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION(className, __VA_ARGS__)
+#define TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION(className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE( ... ) TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#else
+#define TEMPLATE_TEST_CASE( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_NO_REGISTRATION(__VA_ARGS__) )
+#define TEMPLATE_TEST_CASE_SIG( ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_SIG_NO_REGISTRATION(__VA_ARGS__) )
+#define TEMPLATE_TEST_CASE_METHOD( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_NO_REGISTRATION(className, __VA_ARGS__ ) )
+#define TEMPLATE_TEST_CASE_METHOD_SIG( className, ... ) INTERNAL_CATCH_EXPAND_VARGS( INTERNAL_CATCH_TEMPLATE_TEST_CASE_METHOD_SIG_NO_REGISTRATION(className, __VA_ARGS__ ) )
+#define TEMPLATE_PRODUCT_TEST_CASE( ... ) TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_SIG( ... ) TEMPLATE_TEST_CASE( __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD( className, ... ) TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#define TEMPLATE_PRODUCT_TEST_CASE_METHOD_SIG( className, ... ) TEMPLATE_TEST_CASE_METHOD( className, __VA_ARGS__ )
+#endif
+
+#define STATIC_REQUIRE( ... )       (void)(0)
+#define STATIC_REQUIRE_FALSE( ... ) (void)(0)
+
+#endif
+
+#define CATCH_TRANSLATE_EXCEPTION( signature ) INTERNAL_CATCH_TRANSLATE_EXCEPTION_NO_REG( INTERNAL_CATCH_UNIQUE_NAME( catch_internal_ExceptionTranslator ), signature )
+
+// "BDD-style" convenience wrappers
+#define SCENARIO( ... ) INTERNAL_CATCH_TESTCASE_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ) )
+#define SCENARIO_METHOD( className, ... ) INTERNAL_CATCH_TESTCASE_METHOD_NO_REGISTRATION(INTERNAL_CATCH_UNIQUE_NAME( C_A_T_C_H_T_E_S_T_ ), className )
+
+#define GIVEN( desc )
+#define AND_GIVEN( desc )
+#define WHEN( desc )
+#define AND_WHEN( desc )
+#define THEN( desc )
+#define AND_THEN( desc )
+
+using Catch::Detail::Approx;
+
+#endif
+
+#endif // ! CATCH_CONFIG_IMPL_ONLY
+
+// start catch_reenable_warnings.h
+
+
+#ifdef __clang__
+#    ifdef __ICC // icpc defines the __clang__ macro
+#        pragma warning(pop)
+#    else
+#        pragma clang diagnostic pop
+#    endif
+#elif defined __GNUC__
+#    pragma GCC diagnostic pop
+#endif
+
+// end catch_reenable_warnings.h
+// end catch.hpp
+#endif // TWOBLUECUBES_SINGLE_INCLUDE_CATCH_HPP_INCLUDED
+

ADDED   genfile/test/db/test_fill_SQL.cpp
Index: genfile/test/db/test_fill_SQL.cpp
==================================================================
--- genfile/test/db/test_fill_SQL.cpp
+++ genfile/test/db/test_fill_SQL.cpp
@@ -0,0 +1,25 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include "../test_case.hpp"
+#include "db/fill_SQL.hpp"
+
+TEST_CASE( "test_fill_SQL" ) {
+	std::cerr << "test_fill_SQL()..." ;
+	
+	TEST_ASSERT( db::fill_SQL( "" ) == "" ) ;
+	TEST_ASSERT( db::fill_SQL( "A string" ) == "A string" ) ;
+	TEST_ASSERT( db::fill_SQL( "%s", "hello" ) == "\"hello\"" ) ;
+	TEST_ASSERT( db::fill_SQL( "%s", 5 ) == "5" ) ;
+	TEST_ASSERT( db::fill_SQL( "%s", 5.56 ) == "5.56" ) ;
+
+	TEST_ASSERT( db::fill_SQL( "%s %s", "hello", "goodbye" ) == "\"hello\" \"goodbye\"" ) ;
+	TEST_ASSERT( db::fill_SQL( "%s %s", "hello", 0 ) == "\"hello\" 0" ) ;
+	TEST_ASSERT( db::fill_SQL( "%s %s", 4, 0 ) == "4 0" ) ;
+	TEST_ASSERT( db::fill_SQL( "%s%s", 4, "doof" ) == "4\"doof\"" ) ;
+	std::cerr << "success.\n" ;
+}

ADDED   genfile/test/db/test_get_unique_id.cpp
Index: genfile/test/db/test_get_unique_id.cpp
==================================================================
--- genfile/test/db/test_get_unique_id.cpp
+++ genfile/test/db/test_get_unique_id.cpp
@@ -0,0 +1,70 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <sstream>
+#include "../test_case.hpp"
+#include "sqlite3/sqlite3.h"
+#include "genfile/Error.hpp"
+#include "db/Connection.hpp"
+#include "db/SQLite3Connection.hpp"
+#include "db/SQLite3Statement.hpp"
+#include "db/Connection.hpp"
+#include "db/get_unique_id.hpp"
+
+TEST_CASE( "test_get_unique_id" ) {
+	std::cerr << "test_get_unique_id()\n" ;
+	db::Connection::UniquePtr connection( new db::SQLite3Connection( ":memory:" )) ;
+	typedef db::Connection::StatementPtr StatementPtr ;
+	
+	// Construct a table
+	{
+		StatementPtr statement = connection->get_statement(
+			"CREATE TABLE Fields ( id INT, value INT ) ;"
+		) ;
+		statement->step() ;
+	}
+	
+	{
+		StatementPtr statement = connection->get_statement(
+			"INSERT INTO Fields VALUES( ?1, ?2 ) ;"
+		) ;
+		
+		for( uint64_t i = 0; i < 10; ++i ) {
+			statement->reset() ;
+			statement->bind( 1, i ) ;
+			statement->bind( 2, i*2 ) ;
+			TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
+		}
+
+		// make a duplicate key with value 10
+		statement->reset() ;
+		statement->bind( 1, 99 ) ;
+		statement->bind( 2, 10 ) ;
+		TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
+	}
+	
+	for( std::size_t value = 0; value < 20; ++value ) {
+		try {
+			std::ostringstream ostr ;
+			ostr << "WHERE value == " << value ;
+			int id = db::get_unique_id( connection.get(), "Fields", "id", ostr.str() ) ;
+			std::cerr << "value " << value << " found id " << id << ".\n" ;
+			TEST_ASSERT( value % 2 == 0 ) ;
+			TEST_ASSERT( id == int( value )/2 ) ;
+			TEST_ASSERT( id != 5 ) ;
+		}
+		catch( genfile::KeyNotFoundError const& e ) {
+			TEST_ASSERT( value % 2 == 1 ) ;
+			std::cerr << "value " << value << " found no ids.\n" ;
+		}
+		catch( genfile::DuplicateKeyError const& e ) {
+			TEST_ASSERT( value == 10 ) ;
+			std::cerr << "value " << value << " found duplicate ids.\n" ;
+		}
+	}
+	std::cerr << "success.\n" ;
+}

ADDED   genfile/test/db/test_load_key_value_pairs.cpp
Index: genfile/test/db/test_load_key_value_pairs.cpp
==================================================================
--- genfile/test/db/test_load_key_value_pairs.cpp
+++ genfile/test/db/test_load_key_value_pairs.cpp
@@ -0,0 +1,94 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <sstream>
+#include "../test_case.hpp"
+#include "sqlite3/sqlite3.h"
+#include "db/Connection.hpp"
+#include "db/SQLite3Connection.hpp"
+#include "db/SQLite3Statement.hpp"
+#include "db/Connection.hpp"
+#include "db/load_key_value_pairs.hpp"
+
+TEST_CASE( "test_load_key_value_pairs" ) {
+	std::cerr << "test_load_key_value_pairs()\n" ;
+	db::Connection::UniquePtr connection( new db::SQLite3Connection( ":memory:" )) ;
+	typedef db::Connection::StatementPtr StatementPtr ;
+	
+	// Construct a table
+	{
+		StatementPtr statement = connection->get_statement(
+			"CREATE TABLE KeyValue ( key TEXT, value TEXT ) ;"
+		) ;
+		TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
+	}
+	
+	{
+		StatementPtr statement = connection->get_statement(
+			"INSERT INTO KeyValue VALUES( ?1, ?2 ) ;"
+		) ;
+		
+		for( std::size_t i = 0; i < 10; ++i ) {
+			statement->reset() ;
+			std::string key( i, 'x' ) ;
+			std::string value( i*2, '*' ) ;
+			statement->bind( 1, key ) ;
+			statement->bind( 2, value ) ;
+			TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
+		}
+	}
+	typedef std::map< std::string, std::string > Map ;
+	Map values = db::load_key_value_pairs< std::string, std::string >( connection, "KeyValue", "key", "value" ) ;
+	TEST_ASSERT( values.size() == 10 ) ;
+	for( std::size_t i = 0; i < 10; ++i ) {
+		Map::const_iterator where = values.find( std::string( i, 'x' ) ) ;
+		TEST_ASSERT( where != values.end() ) ;
+		TEST_ASSERT( where->second == std::string( i*2, '*' )) ;
+	}
+
+	std::cerr << "success.\n" ;
+}
+
+TEST_CASE( "test_load_key_value_pairs_duplicates" ) {
+	std::cerr << "test_load_key_value_pairs_duplicates()\n" ;
+	db::Connection::UniquePtr connection( new db::SQLite3Connection( ":memory:" )) ;
+	typedef db::Connection::StatementPtr StatementPtr ;
+	// Construct a table
+	{
+		StatementPtr statement = connection->get_statement(
+			"CREATE TABLE KeyValue ( key TEXT, value TEXT ) ;"
+		) ;
+		TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
+	}
+	
+	{
+		StatementPtr statement = connection->get_statement(
+			"INSERT INTO KeyValue VALUES( ?1, ?2 ) ;"
+		) ;
+		
+		for( std::size_t i = 0; i < 10; ++i ) {
+			statement->reset() ;
+			statement->bind( 1, std::string( i, 'x' ) ) ;
+			statement->bind( 2, std::string( i*2, '*' )) ;
+			TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
+		}
+		
+		statement->reset() ;
+		statement->bind( 1, std::string( 1, 'x' )) ;
+		TEST_ASSERT( statement->step() == db::SQLite3Statement::Error::OK ) ;
+	}
+
+	try {
+		std::map< std::string, std::string > values = db::load_key_value_pairs< std::string, std::string >( connection, "KeyValue", "key", "value" ) ;
+		TEST_ASSERT( 0 ) ;
+	}
+	catch( genfile::DuplicateKeyError const& e ) {
+		// as expected.
+	}
+	std::cerr << "success.\n" ;
+}
+

Index: genfile/test/test_case.cpp
==================================================================
--- genfile/test/test_case.cpp
+++ genfile/test/test_case.cpp
@@ -3,6 +3,7 @@
 // Distributed under the Boost Software License, Version 1.0.
 //    (See accompanying file LICENSE_1_0.txt or copy at
 //          http://www.boost.org/LICENSE_1_0.txt)
 
 #define BOOST_TEST_MODULE genfile
+#define CATCH_CONFIG_MAIN
 #include "test_case.hpp"

Index: genfile/test/test_case.hpp
==================================================================
--- genfile/test/test_case.hpp
+++ genfile/test/test_case.hpp
@@ -11,11 +11,25 @@
 #include <cmath>
 #include <limits>
 #include <iostream>
 #include "config/config.hpp"
 
-#if HAVE_BOOST_UNIT_TEST_FRAMEWORK
+#if 1
+	#include "catch.hpp"
+	// boost -> catch shim
+	// TODO: reduce this legacy usage.
+	#define AUTO_TEST_SUITE( param ) ;
+	#define END_AUTO_TEST_SUITE( param ) ;
+	// Note: # is a 'stringify' operator in C++ macro speak, i.e. produces
+	// a string literal.
+	//#define AUTO_TEST_CASE( param ) TEST_CASE( #param )
+	#define TEST_ASSERT( param ) REQUIRE( (param) )
+	#define REQUIRE_SMALL( param, tolerance ) REQUIRE( abs(param) <= tolerance )
+	#define REQUIRE_CLOSE( a, b, eps ) REQUIRE( ((abs(a-b) <= eps*abs(a)) && (abs(a-b)<=eps*abs(b))) )
+	#define REQUIRE_EQUAL( a, b ) REQUIRE( (a == b) )
+
+#elif HAVE_BOOST_UNIT_TEST_FRAMEWORK
 	#include "boost/test/auto_unit_test.hpp"
 	#include "boost/test/test_tools.hpp"
 	#define AUTO_TEST_CASE( param ) BOOST_AUTO_TEST_CASE(param)
 	#define TEST_ASSERT( param ) BOOST_ASSERT( param )
 	#define AUTO_TEST_MAIN namespace { void test_case_dummy_function_WILL_NOT_BE_CALLED() ; } void test_case_dummy_function_WILL_NOT_BE_CALLED() 

Index: genfile/test/test_cohort_individual_source.cpp
==================================================================
--- genfile/test/test_cohort_individual_source.cpp
+++ genfile/test/test_cohort_individual_source.cpp
@@ -595,8 +595,8 @@
 		}
 		std::cerr << "done\n" ;
 	}
 } ;
 
-AUTO_TEST_CASE( all_tests ) {
+TEST_CASE( "CohortIndividualsource::all_tests" ) {
 	TraditionalStrictCohortIndividualSourceTester tester ;
 }

Index: genfile/test/test_endianness_utils.cpp
==================================================================
--- genfile/test/test_endianness_utils.cpp
+++ genfile/test/test_endianness_utils.cpp
@@ -106,11 +106,11 @@
 		TEST_ASSERT( genfile::read_little_endian_integer( &buffer[0], &buffer[0] + 8, &result ) == ( buffer + sizeof( T ) )) ;
 		TEST_ASSERT( result == *t ) ;
 	}
 }
 
-AUTO_TEST_CASE( test_read_little_endian_integer ) {
+TEST_CASE( "test_read_little_endian_integer" ) {
 	std::cerr << "test_read_little_endian_integer()..." ;
 	
 	uint8_t const raw_data[31] = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0 } ;
 	for( int i = 0; i < ( 31 - 8 ); ++i ) {
 		uint8_t const* data = &raw_data[0] + i ;
@@ -135,11 +135,11 @@
 		read_little_endian_test< uint64_t >( data ) ;
 	}
 	std::cerr << "done.\n" ;
 }
 
-AUTO_TEST_CASE( test_write_and_read_little_endian_integer ) {
+TEST_CASE( "test_write_and_read_little_endian_integer" ) {
 	std::cerr << "test_write_and_read_little_endian_integer()..." ;
 	
 	uint8_t raw_data[265+255] ;
 	for( int i = 0; i < 256; ++i ) {
 		raw_data[i] = uint8_t( i ) ;

Index: genfile/test/test_filter_grammar.cpp
==================================================================
--- genfile/test/test_filter_grammar.cpp
+++ genfile/test/test_filter_grammar.cpp
@@ -11,11 +11,11 @@
 #include "test_case.hpp"
 #include "genfile/impl/filter_grammar.hpp"
 #include <cassert>
 
 #if 0
-AUTO_TEST_CASE( filter_grammar_test1 ) {
+TEST_CASE( filter_grammar_test1 ) {
 	
 	using namespace boost::spirit::qi ;
 	
 	std::vector< std::string > sqls ;
 	sqls.push_back( "A = 1" ) ;

Index: genfile/test/test_genfile_io.cpp
==================================================================
--- genfile/test/test_genfile_io.cpp
+++ genfile/test/test_genfile_io.cpp
@@ -20,12 +20,10 @@
 #include "genfile/bgen/bgen.hpp"
 #include "stdint.h"
 
 // #define DEBUG 1
 
-AUTO_TEST_SUITE( test_genfile_io )
-
 // The following section contains a simple snp block writer.
 namespace data {
 	unsigned int const number_of_samples = 7 ;
 	unsigned int const number_of_snps = 16 ;
 	std::string data =
@@ -228,11 +226,11 @@
 std::vector< SnpData > read_gen_file( std::string filename ) {
 	std::auto_ptr< genfile::SNPDataSource > snp_data_source_ptr( genfile::SNPDataSource::create( filename, genfile::Chromosome( "NA" ) )) ;
 	return read_gen_file( *snp_data_source_ptr ) ;
 }
 
-AUTO_TEST_CASE( test_formats ) {
+TEST_CASE( "test_formats" ) {
 	std::string original = genfile::create_temporary_filename() + std::string( ".gen" );
 	std::string gen = genfile::create_temporary_filename() + std::string( ".gen" );
 	std::string gen2 = genfile::create_temporary_filename() + std::string( ".gen" );
 	std::string bgen_v11 = genfile::create_temporary_filename() + std::string( ".v11.bgen" );
 	std::string bgen_v112 = genfile::create_temporary_filename() + std::string( ".v11.bgen" );
@@ -297,29 +295,27 @@
 #if DEBUG
 		std::cerr << "Testing :" << i << "\n" ;
 #endif
 		TEST_ASSERT( results[i].size() == data::number_of_snps ) ;
 			for( std::size_t j = 0; j < results[i].size(); ++j ) {
-				BOOST_CHECK_EQUAL( results[i][j].snp.number_of_identifiers(), results[0][j].snp.number_of_identifiers() ) ;
-				BOOST_CHECK_EQUAL( results[i][j].snp.get_identifiers_as_string(","), results[0][j].snp.get_identifiers_as_string(",") ) ;
+				REQUIRE_EQUAL( results[i][j].snp.number_of_identifiers(), results[0][j].snp.number_of_identifiers() ) ;
+				REQUIRE_EQUAL( results[i][j].snp.get_identifiers_as_string(","), results[0][j].snp.get_identifiers_as_string(",") ) ;
 				TEST_ASSERT( results[i][j].snp.get_identifiers() == results[0][j].snp.get_identifiers() ) ;
-				BOOST_CHECK_EQUAL( results[i][j].snp.get_primary_id(), results[0][j].snp.get_primary_id() ) ;
-				BOOST_CHECK_EQUAL( results[i][j].snp.get_position(), results[0][j].snp.get_position() ) ;
-				BOOST_CHECK_EQUAL( results[i][j].snp.get_allele(0), results[0][j].snp.get_allele(0) ) ;
-				BOOST_CHECK_EQUAL( results[i][j].snp.get_allele(1), results[0][j].snp.get_allele(1) ) ;
+				REQUIRE_EQUAL( results[i][j].snp.get_primary_id(), results[0][j].snp.get_primary_id() ) ;
+				REQUIRE_EQUAL( results[i][j].snp.get_position(), results[0][j].snp.get_position() ) ;
+				REQUIRE_EQUAL( results[i][j].snp.get_allele(0), results[0][j].snp.get_allele(0) ) ;
+				REQUIRE_EQUAL( results[i][j].snp.get_allele(1), results[0][j].snp.get_allele(1) ) ;
 				if( results[i][j].probabilities != results[0][j].probabilities ) {
 					for( std::size_t k = 0; k < results[i][j].probabilities.size(); ++k ) {
 #if DEBUG
 						std::cerr << results[0][j].probabilities[k] << " : " << results[i][j].probabilities[k] << ".\n" ;
 #endif
 						// BGEN with 16 bits gets accuracy to 1/32768 which is ~4dps of accuracy
-						BOOST_CHECK_SMALL( results[0][j].probabilities[k].AA - results[i][j].probabilities[k].AA, 0.00005 ) ;
-						BOOST_CHECK_SMALL( results[0][j].probabilities[k].AB - results[i][j].probabilities[k].AB, 0.00005 ) ;
-						BOOST_CHECK_SMALL( results[0][j].probabilities[k].BB - results[i][j].probabilities[k].BB, 0.00005 ) ;
+						REQUIRE_SMALL( results[0][j].probabilities[k].AA - results[i][j].probabilities[k].AA, 0.00005 ) ;
+						REQUIRE_SMALL( results[0][j].probabilities[k].AB - results[i][j].probabilities[k].AB, 0.00005 ) ;
+						REQUIRE_SMALL( results[0][j].probabilities[k].BB - results[i][j].probabilities[k].BB, 0.00005 ) ;
 					}
 				}
 			}
 		//TEST_ASSERT( results[i] == results[0] ) ;
 	}
 }
-
-AUTO_TEST_SUITE_END()

Index: genfile/test/test_sample_filtering_snp_data_source.cpp
==================================================================
--- genfile/test/test_sample_filtering_snp_data_source.cpp
+++ genfile/test/test_sample_filtering_snp_data_source.cpp
@@ -23,12 +23,10 @@
 #include "genfile/SampleFilteringSNPDataSource.hpp"
 #include "stdint.h"
 
 #define DEBUG 1
 
-AUTO_TEST_SUITE( test_sample_filtering_snp_data_source )
-
 // The following section contains a simple snp block writer.
 namespace data {
 	namespace {
 		// this data has 1504 samples per row.
 		//unsigned int const number_of_samples = 1504 ;
@@ -113,11 +111,11 @@
 		data.push_back( "SNP1 RS1 1000 a g 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15\n" ) ;
 		return data ;
 	}
 }
 
-AUTO_TEST_CASE( test_sample_filtering_snp_data_source ) {
+TEST_CASE( "test_sample_filtering_snp_data_source" ) {
 	std::vector< std::string > data = construct_data() ;
 	std::string const filename = genfile::create_temporary_filename() + std::string( ".gen" ) ;
 	for( std::size_t data_i = 1; data_i < data.size(); ++data_i ) {
 		std::cerr << "====== Looking at data " << data_i << " ======\n" ;
 		create_file( data[data_i], filename ) ;
@@ -177,7 +175,5 @@
 			}
 		}
 	}
 	std::cout << "==== success ====\n" ;
 }
-
-AUTO_TEST_SUITE_END()

Index: genfile/test/test_slice.cpp
==================================================================
--- genfile/test/test_slice.cpp
+++ genfile/test/test_slice.cpp
@@ -7,13 +7,11 @@
 #include "test_case.hpp"
 #include "genfile/string_utils/slice.hpp"
 
 using namespace genfile::string_utils ;
 
-BOOST_AUTO_TEST_SUITE( test_slice )
-
-AUTO_TEST_CASE( test_constructors ) {
+TEST_CASE( "slice::test_constructors" ) {
 	std::cerr << "test_constructors()..." ;
 
 	{
 		char const* s = "Hello" ;
 		TEST_ASSERT( std::string( slice( s )) == "Hello" ) ;
@@ -111,11 +109,11 @@
 		TEST_ASSERT( slice( s, 5, 5 ).size() == 0 ) ;
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_find ) {
+TEST_CASE( "slice::test_find" ) {
 	std::cerr << "test_find()..." ;
 
 	{
 		std::string const test_string = "Hello, I am a string.$$**88  \t" ;
 		slice s( test_string ) ;
@@ -142,11 +140,11 @@
 		}
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_find_first_of ) {
+TEST_CASE( "test_find_first_of" ) {
 	std::cerr << "test_find_first_of()..." ;
 
 	{
 		std::string test_string = "Hello, I am a string.$$**88  \t" ;
 		slice s( test_string ) ;
@@ -182,11 +180,11 @@
 		}
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_split_slice ) {
+TEST_CASE( "slice::test_split_slice" ) {
 	std::cerr << "test_split_slice()..." ;
 
 	{
 		std::string data = "" ;
 		std::vector< slice > expected ;
@@ -258,7 +256,5 @@
 	}
 
 	std::cerr << "ok.\n" ;
 }
 
-BOOST_AUTO_TEST_SUITE_END()
-

Index: genfile/test/test_snp_data_source_chain.cpp
==================================================================
--- genfile/test/test_snp_data_source_chain.cpp
+++ genfile/test/test_snp_data_source_chain.cpp
@@ -18,12 +18,10 @@
 #include "genfile/FileUtils.hpp"
 #include "genfile/GenFileSNPDataSink.hpp"
 #include "genfile/BGenFileSNPDataSink.hpp"
 #include "stdint.h"
 
-AUTO_TEST_SUITE( test_snp_data_source_chain )
-
 // The following section contains a simple snp block writer.
 namespace data {
 	namespace {
 		// this data has 1504 samples per row.
 		unsigned int const number_of_samples = 7 ;
@@ -176,11 +174,11 @@
 		) ;
 		return read_snp_data( *snp_data_source ) ;
 	}
 }
 
-AUTO_TEST_CASE( test_snp_data_source_chain ) {
+TEST_CASE( "test_snp_data_source_chain" ) {
 	std::string original = genfile::create_temporary_filename() + std::string( ".gen" );
 	std::string gen = genfile::create_temporary_filename() + std::string( ".gen" );
 	std::string gen2 = genfile::create_temporary_filename() + std::string( ".gen" );
 
 	std::vector< genfile::wildcard::FilenameMatch > filenames ;
@@ -208,7 +206,5 @@
 	for( std::size_t i = 0; i < results.size(); ++i ) {
 		TEST_ASSERT( results[i].size() == (2*data::number_of_snps) ) ;
 		TEST_ASSERT( results[i] == results[0] ) ;
 	}
 }
-
-AUTO_TEST_SUITE_END()

Index: genfile/test/test_snp_data_source_rack.cpp
==================================================================
--- genfile/test/test_snp_data_source_rack.cpp
+++ genfile/test/test_snp_data_source_rack.cpp
@@ -19,12 +19,10 @@
 #include "genfile/SNPDataSource.hpp"
 #include "genfile/SNPDataSourceRack.hpp"
 #include "genfile/GenFileSNPDataSource.hpp"
 #include "stdint.h"
 
-AUTO_TEST_SUITE( test_snp_data_source_rack )
-	
 // The following section contains a simple snp block writer.
 namespace data {
 	// this data has 1504 samples per row.
 	unsigned int const number_of_samples = 1504 ;
 }
@@ -160,11 +158,11 @@
 		"SNP5 RS5 5000 a g 1 0 0 1 0 0\n"
 	) ;
 	return data ;
 }
 
-AUTO_TEST_CASE( test_snp_data_source_rack ) {
+TEST_CASE( "test_snp_data_source_rack" ) {
 	std::vector< std::vector< std::string > > data = construct_data() ;
 	genfile::VariantIdentifyingData snp ;
 	for( std::size_t i = 0; i < data.size(); ++i ) {
 		std::cout << "==== Looking at test data " << i << " ====\n" ;
 		std::auto_ptr< genfile::SNPDataSourceRack > rack( new genfile::SNPDataSourceRack() ) ;
@@ -207,8 +205,5 @@
 		
 	}
 	std::cout << "==== success ====\n" ;
 	
 }
-
-AUTO_TEST_SUITE_END()
-

Index: genfile/test/test_snp_identifying_data.cpp
==================================================================
--- genfile/test/test_snp_identifying_data.cpp
+++ genfile/test/test_snp_identifying_data.cpp
@@ -10,17 +10,18 @@
 #include <boost/bind.hpp>
 #include "test_case.hpp"
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/GenomePosition.hpp"
 
-AUTO_TEST_CASE( test_output_streaming ) {
+TEST_CASE( "VariantIdentifyingData::output_streaming" ) {
 	for( char c1 = 33; c1 <= 126; ++c1 ) {
 		std::string rsid = std::string( 1, c1 ) ;
 		genfile::VariantIdentifyingData snp( rsid, genfile::GenomePosition( genfile::Chromosome(), 0 ), "A", "G" ) ;
 		std::ostringstream ostr ;
 		ostr << snp ;
-		BOOST_CHECK_EQUAL( ostr.str(), rsid + " NA 0 A G" ) ;
+		REQUIRE( snp.get_identifiers().size() == 1 ) ;
+		REQUIRE_EQUAL( ostr.str(), rsid + " NA 0 A G" ) ;
 	}
 
 	for( char c1 = 33; c1 <= 126; ++c1 ) {
 		for( char c2 = 33; c2 <= 126; ++c2 ) {
 			std::string rsid = std::string( 1, c1 ) ;
@@ -27,153 +28,124 @@
 			std::string alternate_id = std::string( 1, c2 ) ;
 			genfile::VariantIdentifyingData snp( rsid, genfile::GenomePosition( genfile::Chromosome(), 0 ), "A", "G" ) ;
 			snp.add_identifier( alternate_id ) ;
 			std::ostringstream ostr ;
 			ostr << snp ;
-			if( c1 == c2 ) {
-				BOOST_CHECK_EQUAL( ostr.str(), rsid + " NA 0 A G" ) ;
-			}
-			else {
-				BOOST_CHECK_EQUAL( ostr.str(), rsid + " [" + alternate_id + "] NA 0 A G" ) ;
-			}
-		}
-	}
-}
-
-AUTO_TEST_CASE( test_alternate_ids2 ) {
-	for( std::size_t n = 0; n < 10; ++n ) {
-		for( char c1 = 33; c1 <= 126; ++c1 ) {
-			std::string rsid = std::string( 1, c1 ) ;
-			genfile::VariantIdentifyingData snp( rsid, genfile::GenomePosition( genfile::Chromosome(), 0 ), "A", "G" ) ;
-			snp.add_identifier( rsid ) ; // should be a no-op.
-			for( std::size_t i = 0; i < n; ++i ) {
-				snp.add_identifier( std::string( i + 2, c1 ) ) ;
-			}
-			std::vector< genfile::string_utils::slice > ids = snp.get_identifiers( 1, snp.number_of_identifiers() ) ;
-			BOOST_CHECK_EQUAL( ids.size(), n ) ;
-			for( std::size_t i = 0; i < n; ++i ) {
-				BOOST_CHECK_EQUAL( ids[i], std::string( i + 2, c1 ) ) ;
-			}
-		}
-	}
-}
-
-AUTO_TEST_CASE( test_snp_values ) {
-	genfile::VariantIdentifyingData snp( "RSID_1", genfile::GenomePosition( genfile::Chromosome(), 1000 ), "A", "G" ) ;
-	BOOST_CHECK_EQUAL( snp.get_primary_id(), "RSID_1" ) ;
-	BOOST_CHECK_EQUAL( snp.get_position(), genfile::GenomePosition( genfile::Chromosome(), 1000 ) ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(0), "A" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(1), "G" ) ;
-	BOOST_CHECK( snp.get_identifiers() == std::vector< genfile::string_utils::slice >( 1, "RSID_1" ) ) ;
-}
-
-AUTO_TEST_CASE( test_snp_copying ) {
-	genfile::VariantIdentifyingData snp1( "RSID_1", genfile::GenomePosition( genfile::Chromosome(), 1000 ), "A", "G" ) ;
-	snp1.add_identifier( std::string( "SNP1" ) ) ;
-
-	genfile::VariantIdentifyingData snp2 = snp1 ;
-	BOOST_CHECK_EQUAL( snp1, snp2 ) ;
-
-	genfile::VariantIdentifyingData snp3( "SNP1", "RSID_1", genfile::GenomePosition( genfile::Chromosome(), 1000 ), "A", "G" ) ;
-	genfile::VariantIdentifyingData snp4 = snp3 ;
-	BOOST_CHECK_EQUAL( snp4, snp2 ) ;
-}
-
-AUTO_TEST_CASE( test_alternate_ids_2 ) {
-	std::string rsid ;
-	std::vector< std::string > ids ;
-	void(std::vector<std::string>::*push_back)(std::string const&) = &std::vector<std::string>::push_back;
-	{
-		genfile::VariantIdentifyingData snp( "RSID_1", genfile::GenomePosition( genfile::Chromosome(), 0 ), "A", "G" ) ;
-		ids.clear() ;
-		snp.get_identifiers( boost::bind( push_back, &ids, _1 ) ) ;
-		BOOST_CHECK_EQUAL( ids.size(), 1 ) ;
-		BOOST_CHECK_EQUAL( ids[0], "RSID_1" ) ;
-		snp.add_identifier( std::string( "RSID_1" ) ) ;
-		ids.clear() ;
-		snp.get_identifiers( boost::bind( push_back, &ids, _1 ) ) ;
-		BOOST_CHECK_EQUAL( ids.size(), 1 ) ;
-		BOOST_CHECK_EQUAL( ids[0], "RSID_1" ) ;
-		snp.add_identifier( std::string( "SNPID_1" ) ) ;
-		ids.clear() ;
-		snp.get_identifiers( boost::bind( push_back, &ids, _1 ) ) ;
-		BOOST_CHECK_EQUAL( ids.size(), 2 ) ;
-		BOOST_CHECK_EQUAL( ids[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[1], "SNPID_1" ) ;
-		snp.add_identifier( std::string( "SNPID_1" ) ) ;
-		ids.clear() ;
-		snp.get_identifiers( boost::bind( push_back, &ids, _1 ) ) ;
-		BOOST_CHECK_EQUAL( ids.size(), 2 ) ;
-		BOOST_CHECK_EQUAL( ids[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[1], "SNPID_1" ) ;
-		snp.add_identifier( std::string( "RSID_1" ) ) ;
-		ids.clear() ;
-		snp.get_identifiers( boost::bind( push_back, &ids, _1 ) ) ;
-		BOOST_CHECK_EQUAL( ids.size(), 2 ) ;
-		BOOST_CHECK_EQUAL( ids[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[1], "SNPID_1" ) ;
-		snp.add_identifier( std::string( "AnotherID" ) ) ;
-		ids.clear() ;
-		snp.get_identifiers( boost::bind( push_back, &ids, _1 ) ) ;
-		BOOST_CHECK_EQUAL( ids.size(), 3 ) ;
-		BOOST_CHECK_EQUAL( ids[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[1], "SNPID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[2], "AnotherID" ) ;
-		snp.add_identifier( std::string( "RSID_1" ) ) ;
-		ids.clear() ;
-		snp.get_identifiers( boost::bind( push_back, &ids, _1 ) ) ;
-		BOOST_CHECK_EQUAL( ids.size(), 3 ) ;
-		BOOST_CHECK_EQUAL( ids[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[1], "SNPID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[2], "AnotherID" ) ;
-		snp.add_identifier( std::string( "SNPID_1" ) ) ;
-		ids.clear() ;
-		snp.get_identifiers( boost::bind( push_back, &ids, _1 ) ) ;
-		BOOST_CHECK_EQUAL( ids.size(), 3 ) ;
-		BOOST_CHECK_EQUAL( ids[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[1], "SNPID_1" ) ;
-		BOOST_CHECK_EQUAL( ids[2], "AnotherID" ) ;
-	}
-}
-
-AUTO_TEST_CASE( test_snp_data_setters ) {
-	genfile::GenomePosition pos( genfile::Chromosome( "01" ), 0 ) ;
-	genfile::VariantIdentifyingData snp( "RSID_1", pos, "A", "G" ) ;
-	snp.add_identifier( std::string( "ID" ) ) ;
-	snp.set_primary_id( std::string( "RSID_1_changed" ) ) ;
-	BOOST_CHECK_EQUAL( snp.get_primary_id(), "RSID_1_changed" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(0), "A" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(1), "G" ) ;
-	BOOST_CHECK_EQUAL( snp.get_position(), pos ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 2 ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1_changed" ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "ID" ) ;
-
-	snp.set_allele( 0, std::string( "GA" ) ) ;
-	BOOST_CHECK_EQUAL( snp.get_primary_id(), "RSID_1_changed" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(0), "GA" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(1), "G" ) ;
-	BOOST_CHECK_EQUAL( snp.get_position(), pos ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 2 ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1_changed" ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "ID" ) ;
-
-	snp.set_allele( 1, std::string( "AG" ) ) ;
-	BOOST_CHECK_EQUAL( snp.get_primary_id(), "RSID_1_changed" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(0), "GA" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(1), "AG" ) ;
-	BOOST_CHECK_EQUAL( snp.get_position(), pos ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 2 ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1_changed" ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "ID" ) ;
-
-	pos.position() = 1000 ;
-	snp.set_position( pos ) ;
-	BOOST_CHECK_EQUAL( snp.get_primary_id(), "RSID_1_changed" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(0), "GA" ) ;
-	BOOST_CHECK_EQUAL( snp.get_allele(1), "AG" ) ;
-	BOOST_CHECK_EQUAL( snp.get_position(), pos ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 2 ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1_changed" ) ;
-	BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "ID" ) ;
+			std::cerr << "!!" << snp << ".\n" ;
+			REQUIRE( snp.get_identifiers().size() == 2 ) ;
+			REQUIRE( ostr.str() == (rsid + " [" + alternate_id + "] NA 0 A G") ) ;
+		}
+	}
+}
+
+TEST_CASE( "VariantIdentifyingData::IDs1" ) {
+	std::string rsid = "rs1" ;
+	genfile::VariantIdentifyingData snp( rsid, genfile::GenomePosition( genfile::Chromosome(), 0 ), "A", "G" ) ;
+	REQUIRE( snp.get_identifiers().size() == 1 ) ;
+	REQUIRE( snp.get_identifiers(1).size() == 0 ) ;
+	REQUIRE( snp.get_identifiers()[0] == "rs1" ) ;
+
+	snp.add_identifier( "rs1" ) ;
+	REQUIRE( snp.get_identifiers().size() == 2 ) ;
+	REQUIRE( snp.get_identifiers(1).size() == 1 ) ;
+	REQUIRE( snp.get_identifiers()[0] == "rs1" ) ;
+	REQUIRE( snp.get_identifiers()[1] == "rs1" ) ;
+	REQUIRE( snp.get_identifiers(1)[0] == "rs1" ) ;
+
+	snp.add_identifier( "rs1" ) ;
+	REQUIRE( snp.get_identifiers().size() == 2 ) ;
+	REQUIRE( snp.get_identifiers(1).size() == 1 ) ;
+	REQUIRE( snp.get_identifiers()[0] == "rs1" ) ;
+	REQUIRE( snp.get_identifiers()[1] == "rs1" ) ;
+	REQUIRE( snp.get_identifiers(1)[0] == "rs1" ) ;
+
+	snp.add_identifier( "rs2" ) ;
+	REQUIRE( snp.get_identifiers().size() == 3 ) ;
+	REQUIRE( snp.get_identifiers(1).size() == 2 ) ;
+	REQUIRE( snp.get_identifiers()[0] == "rs1" ) ;
+	REQUIRE( snp.get_identifiers()[1] == "rs1" ) ;
+	REQUIRE( snp.get_identifiers()[2] == "rs2" ) ;
+	REQUIRE( snp.get_identifiers(1)[0] == "rs1" ) ;
+	REQUIRE( snp.get_identifiers(1)[1] == "rs2" ) ;
+	REQUIRE( snp.get_identifiers(2)[0] == "rs2" ) ;
+}
+
+TEST_CASE( "VariantIdentifyingData::alternate_IDs" ) {
+	for( std::size_t n = 0; n < 10; ++n ) {
+		for( char c1 = 33; c1 <= 126; ++c1 ) {
+			std::string rsid = std::string( 1, c1 ) ;
+			genfile::VariantIdentifyingData snp( rsid, genfile::GenomePosition( genfile::Chromosome(), 0 ), "A", "G" ) ;
+			for( std::size_t i = 0; i < n; ++i ) {
+				snp.add_identifier( std::string( i + 2, c1 ) ) ;
+			}
+			std::vector< genfile::string_utils::slice > alternate_ids = snp.get_identifiers(1) ;
+			REQUIRE( alternate_ids.size() == n ) ;
+			for( std::size_t i = 0; i < n; ++i ) {
+				REQUIRE( alternate_ids[i] == std::string( i + 2, c1 ) ) ;
+			}
+		}
+	}
+}
+
+TEST_CASE( "VariantIdentifyingData::snp_values" ) {
+	genfile::VariantIdentifyingData snp( "RSID_1", genfile::GenomePosition( genfile::Chromosome(), 1000 ), "A", "G" ) ;
+	REQUIRE( snp.get_primary_id() == "RSID_1" ) ;
+	REQUIRE( snp.get_position() == genfile::GenomePosition( genfile::Chromosome(), 1000 ) ) ;
+	REQUIRE( snp.get_allele(0) == "A" ) ;
+	REQUIRE( snp.get_allele(1) == "G" ) ;
+	REQUIRE( snp.get_identifiers() == std::vector< genfile::string_utils::slice >( 1, "RSID_1" ) ) ;
+}
+
+TEST_CASE( "VariantIdentifyingData::copying" ) {
+	genfile::VariantIdentifyingData snp1( "RSID_1", genfile::GenomePosition( genfile::Chromosome(), 1000 ), "A", "G" ) ;
+	snp1.add_identifier( std::string( "SNP1" ) ) ;
+
+	genfile::VariantIdentifyingData snp2 = snp1 ;
+	REQUIRE_EQUAL( snp1, snp2 ) ;
+
+	genfile::VariantIdentifyingData snp3( "SNP1", "RSID_1", genfile::GenomePosition( genfile::Chromosome(), 1000 ), "A", "G" ) ;
+	genfile::VariantIdentifyingData snp4 = snp3 ;
+	REQUIRE_EQUAL( snp4, snp2 ) ;
+}
+
+TEST_CASE( "test_snp_data_setters" ) {
+	genfile::GenomePosition pos( genfile::Chromosome( "01" ), 0 ) ;
+	genfile::VariantIdentifyingData snp( "RSID_1", pos, "A", "G" ) ;
+	snp.add_identifier( std::string( "ID" ) ) ;
+	snp.set_primary_id( std::string( "RSID_1_changed" ) ) ;
+	REQUIRE_EQUAL( snp.get_primary_id(), "RSID_1_changed" ) ;
+	REQUIRE_EQUAL( snp.get_allele(0), "A" ) ;
+	REQUIRE_EQUAL( snp.get_allele(1), "G" ) ;
+	REQUIRE_EQUAL( snp.get_position(), pos ) ;
+	REQUIRE_EQUAL( snp.get_identifiers().size(), 2 ) ;
+	REQUIRE_EQUAL( snp.get_identifiers()[0], "RSID_1_changed" ) ;
+	REQUIRE_EQUAL( snp.get_identifiers()[1], "ID" ) ;
+
+	snp.set_allele( 0, std::string( "GA" ) ) ;
+	REQUIRE_EQUAL( snp.get_primary_id(), "RSID_1_changed" ) ;
+	REQUIRE_EQUAL( snp.get_allele(0), "GA" ) ;
+	REQUIRE_EQUAL( snp.get_allele(1), "G" ) ;
+	REQUIRE_EQUAL( snp.get_position(), pos ) ;
+	REQUIRE_EQUAL( snp.get_identifiers().size(), 2 ) ;
+	REQUIRE_EQUAL( snp.get_identifiers()[0], "RSID_1_changed" ) ;
+	REQUIRE_EQUAL( snp.get_identifiers()[1], "ID" ) ;
+
+	snp.set_allele( 1, std::string( "AG" ) ) ;
+	REQUIRE_EQUAL( snp.get_primary_id(), "RSID_1_changed" ) ;
+	REQUIRE_EQUAL( snp.get_allele(0), "GA" ) ;
+	REQUIRE_EQUAL( snp.get_allele(1), "AG" ) ;
+	REQUIRE_EQUAL( snp.get_position(), pos ) ;
+	REQUIRE_EQUAL( snp.get_identifiers().size(), 2 ) ;
+	REQUIRE_EQUAL( snp.get_identifiers()[0], "RSID_1_changed" ) ;
+	REQUIRE_EQUAL( snp.get_identifiers()[1], "ID" ) ;
+
+	pos.position() = 1000 ;
+	snp.set_position( pos ) ;
+	REQUIRE_EQUAL( snp.get_primary_id(), "RSID_1_changed" ) ;
+	REQUIRE_EQUAL( snp.get_allele(0), "GA" ) ;
+	REQUIRE_EQUAL( snp.get_allele(1), "AG" ) ;
+	REQUIRE_EQUAL( snp.get_position(), pos ) ;
+	REQUIRE_EQUAL( snp.get_identifiers().size(), 2 ) ;
+	REQUIRE_EQUAL( snp.get_identifiers()[0], "RSID_1_changed" ) ;
+	REQUIRE_EQUAL( snp.get_identifiers()[1], "ID" ) ;
 }
 

Index: genfile/test/test_strand_aligning_snp_data_source.cpp
==================================================================
--- genfile/test/test_strand_aligning_snp_data_source.cpp
+++ genfile/test/test_strand_aligning_snp_data_source.cpp
@@ -16,12 +16,10 @@
 #include "genfile/SNPDataSink.hpp"
 #include "stdint.h"
 
 // #define DEBUG 1
 
-AUTO_TEST_SUITE( StrandAligningSNPDataSourceTest )
-
 // The following section contains a simple snp block writer.
 namespace data {
 	namespace {
 		unsigned int const number_of_samples = 7 ;
 		unsigned int const number_of_snps = 16 ;
@@ -57,11 +55,11 @@
 			default: assert(0) ; break ;
 		}
 	}
 }
 
-AUTO_TEST_CASE( test_strand_aligning_snp_data_source ) {
+TEST_CASE( "test_strand_aligning_snp_data_source" ) {
 	std::cerr << "test_strand_aligning_snp_data_source()..." ;
 	
 	std::size_t const N = 100 ; // do 100 iterations.
 	std::string const question_mark = "?" ;
 	
@@ -196,7 +194,5 @@
 		}
 	}
 	
 	std::cerr << "ok.\n" ;
 }
-
-AUTO_TEST_SUITE_END()

Index: genfile/test/test_string_utils.cpp
==================================================================
--- genfile/test/test_string_utils.cpp
+++ genfile/test/test_string_utils.cpp
@@ -7,11 +7,11 @@
 #include "test_case.hpp"
 #include "genfile/string_utils/string_utils.hpp"
 
 using namespace genfile::string_utils ;
 
-AUTO_TEST_CASE( test_split ) {
+TEST_CASE( "test_split" ) {
 	std::cerr << "test_split()..." ;
 	std::vector< std::string > expected ;
 	TEST_ASSERT( expected == split( "", "," )) ;
 
 	expected.push_back( "hello" ) ;

Index: genfile/test/test_strtod.cpp
==================================================================
--- genfile/test/test_strtod.cpp
+++ genfile/test/test_strtod.cpp
@@ -4,10 +4,11 @@
 //    (See accompanying file LICENSE_1_0.txt or copy at
 //          http://www.boost.org/LICENSE_1_0.txt)
 
 #include "test_case.hpp"
 #include <string>
+#include <sstream>
 #include <cstdlib>
 #include "genfile/string_utils/slice.hpp"
 #include "genfile/string_utils/strtod.hpp"
 
 namespace {
@@ -36,21 +37,21 @@
 		}
 		
 //		std::cerr << "a = " << a << ", b = " << b << ".\n" ;
 		if( std::abs( a ) != std::numeric_limits< double >::infinity() && ( a == a ) ) {
 			if( a == 0 || b == 0 ) {
-				BOOST_CHECK_SMALL( a - b, 1E-16 ) ;
+				REQUIRE_SMALL( a - b, 1E-16 ) ;
 			} else {
-				BOOST_CHECK_CLOSE( a, b, 1E-12 ) ;
+				REQUIRE_CLOSE( a, b, 1E-12 ) ;
 			}
 		} else {
-			TEST_ASSERT( ((a != a) && (b != b)) || (a == b) ) ;
+			TEST_ASSERT( (((a != a) && (b != b)) || (a == b)) ) ;
 		}
 	}
 }
 
-AUTO_TEST_CASE( test_strtod ) {
+TEST_CASE( "test_strtod" ) {
 	test_it( "0" ) ;
 	test_it( "nan" ) ;
 	test_it( "naN" ) ;
 	test_it( "nAn" ) ;
 	test_it( "nAN" ) ;
@@ -80,11 +81,11 @@
 		test_it( ostr.str() ) ;
 	}
 }
 
 
-AUTO_TEST_CASE( test_strtod_random ) {
+TEST_CASE( "test_strtod_random" ) {
 	assert( sizeof( int ) == 4 ) ;
 	assert( sizeof( double ) == 8 ) ;
 	int D[2] ;
 	for( std::size_t i = 0; i < 1000000; ++i ) {
 		D[0] = rand() ;

Index: genfile/test/test_variant_identifying_data.cpp
==================================================================
--- genfile/test/test_variant_identifying_data.cpp
+++ genfile/test/test_variant_identifying_data.cpp
@@ -8,207 +8,100 @@
 #include <string>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/GenomePosition.hpp"
 #include "test_case.hpp"
 
-BOOST_AUTO_TEST_SUITE( test_variant_identifying_data )
-
-BOOST_AUTO_TEST_CASE( test_constructors ) {
+TEST_CASE( "VariantIdentifyingData::test_constructors" ) {
 	using namespace genfile ;
 	{
 		VariantIdentifyingData data ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 0 ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "(unknown variant)" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 0 ) ;
+		REQUIRE_EQUAL( data.number_of_identifiers(), 1 ) ;
+		REQUIRE_EQUAL( data.get_primary_id(), "(unknown variant)" ) ;
 	}
 
 	{
 		VariantIdentifyingData data( "rs1", GenomePosition( Chromosome( "01" ), 1000 ), "A", "G" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( "," ), "rs1" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 2 ) ;
+		REQUIRE_EQUAL( data.number_of_identifiers(), 1 ) ;
+		REQUIRE_EQUAL( data.get_primary_id(), "rs1" ) ;
+		REQUIRE_EQUAL( data.get_identifiers_as_string( "," ), "rs1" ) ;
 	}
 
 	{
 		VariantIdentifyingData data( "SNP1", "rs1", GenomePosition( Chromosome( "01" ), 1000 ), "A", "G" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( "," ), "rs1,SNP1" ) ;
-	}
-}
-
-BOOST_AUTO_TEST_CASE( test_identifiers ) {
-	using namespace genfile ;
-	{
-		VariantIdentifyingData data( "rs0" ) ;
-		data.set_primary_id( "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 0 ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers().size(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( "," ), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( ",", 1 ), "" ) ;
-
-		data.add_identifier( "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers().size(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( "," ), "rs1" ) ;
-
-		data.add_identifier( "rsx" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( "," ), "rs1,rsx" ) ;
-
-		data.add_identifier( "rsx" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( "," ), "rs1,rsx" ) ;
-
-		data.add_identifier( "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( "," ), "rs1,rsx" ) ;
-
-		data.add_identifier( "rsy" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_identifiers(), 3 ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers().size(), 3 ) ;
-		BOOST_CHECK_EQUAL( data.get_primary_id(), "rs1" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( "," ), "rs1,rsx,rsy" ) ;
-		BOOST_CHECK_EQUAL( data.get_identifiers_as_string( ",", 1 ), "rsx,rsy" ) ;
-	}
-	
-	{
-		genfile::VariantIdentifyingData snp( "RSID_1", genfile::GenomePosition( genfile::Chromosome(), 0 ), "A", "G" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 1 ) ;
-		snp.add_identifier( std::string( "RSID_1" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 1 ) ;
-		snp.add_identifier( std::string( "SNPID_1" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "SNPID_1" ) ;
-		snp.add_identifier( std::string( "SNPID_1" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "SNPID_1" ) ;
-		snp.add_identifier( std::string( "RSID_1" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "SNPID_1" ) ;
-		snp.add_identifier( std::string( "AnotherID" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 3 ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "SNPID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[2], "AnotherID" ) ;
-		snp.add_identifier( std::string( "RSID_1" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 3 ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "SNPID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[2], "AnotherID" ) ;
-		snp.add_identifier( std::string( "SNPID_1" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 3 ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "RSID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "SNPID_1" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[2], "AnotherID" ) ;
-	}
-	
-	{
-		genfile::VariantIdentifyingData snp( "rs1" ) ;
-		snp.set_primary_id( std::string( "rs1_changed" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_primary_id(), "rs1_changed" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 1 ) ;
-	}
-
-	{
-		genfile::GenomePosition pos( genfile::Chromosome( "01" ), 1000 ) ;
-		genfile::VariantIdentifyingData snp( "rs1", pos, "A", "G" ) ;
-		snp.add_identifier( std::string( "ID" ) ) ;
-		snp.set_primary_id( std::string( "rs1_changed" ) ) ;
-		BOOST_CHECK_EQUAL( snp.get_primary_id(), "rs1_changed" ) ;
-		BOOST_CHECK_EQUAL( snp.get_allele(0), "A" ) ;
-		BOOST_CHECK_EQUAL( snp.get_allele(1), "G" ) ;
-		BOOST_CHECK_EQUAL( snp.get_position(), pos ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[0], "rs1_changed" ) ;
-		BOOST_CHECK_EQUAL( snp.get_identifiers()[1], "ID" ) ;
-	}
-}
-
-BOOST_AUTO_TEST_CASE( test_alleles ) {
+		REQUIRE_EQUAL( data.number_of_alleles(), 2 ) ;
+		REQUIRE_EQUAL( data.number_of_identifiers(), 2 ) ;
+		REQUIRE_EQUAL( data.get_primary_id(), "rs1" ) ;
+		REQUIRE_EQUAL( data.get_identifiers_as_string( "," ), "rs1,SNP1" ) ;
+	}
+}
+
+TEST_CASE( "VariantIdentifyingData::test_alleles" ) {
 	using namespace genfile ;
 	using genfile::string_utils::slice ;
 	{
 		VariantIdentifyingData data( "rs0" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 0 ) ;
-		data.add_allele( "A" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_alleles().size(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "A" ) ;
-		data.add_allele( "A" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_alleles().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "A" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(1), "A" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 0 ) ;
+		data.add_allele( "A" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 1 ) ;
+		REQUIRE_EQUAL( data.get_alleles().size(), 1 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "A" ) ;
+		data.add_allele( "A" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 2 ) ;
+		REQUIRE_EQUAL( data.get_alleles().size(), 2 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "A" ) ;
+		REQUIRE_EQUAL( data.get_allele(1), "A" ) ;
 		data.add_allele( "G" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 3 ) ;
-		BOOST_CHECK_EQUAL( data.get_alleles().size(), 3 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "A" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(1), "A" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(2), "G" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 3 ) ;
+		REQUIRE_EQUAL( data.get_alleles().size(), 3 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "A" ) ;
+		REQUIRE_EQUAL( data.get_allele(1), "A" ) ;
+		REQUIRE_EQUAL( data.get_allele(2), "G" ) ;
 		data.add_allele( "CATTAC" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 4 ) ;
-		BOOST_CHECK_EQUAL( data.get_alleles().size(), 4 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "A" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(1), "A" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(2), "G" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(3), "CATTAC" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 4 ) ;
+		REQUIRE_EQUAL( data.get_alleles().size(), 4 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "A" ) ;
+		REQUIRE_EQUAL( data.get_allele(1), "A" ) ;
+		REQUIRE_EQUAL( data.get_allele(2), "G" ) ;
+		REQUIRE_EQUAL( data.get_allele(3), "CATTAC" ) ;
 	}
 
 	{
 		VariantIdentifyingData data( "rs0" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 0 ) ;
-		BOOST_CHECK_EQUAL( data.get_alleles().size(), 0 ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 0 ) ;
+		REQUIRE_EQUAL( data.get_alleles().size(), 0 ) ;
 		data.add_allele( "A" ) ;
 		data.set_allele( 0, "G" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_alleles().size(), 1 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "G" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 1 ) ;
+		REQUIRE_EQUAL( data.get_alleles().size(), 1 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "G" ) ;
 		data.add_allele( "A" ) ;
 		data.set_allele( 0, "C" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_alleles().size(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "C" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 2 ) ;
+		REQUIRE_EQUAL( data.get_alleles().size(), 2 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "C" ) ;
 	}
 
 	{
 		VariantIdentifyingData data( "rs0", genfile::GenomePosition( genfile::Chromosome( "01" ), 1000 ), "A", "G" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 2 ) ;
-		data.set_allele( 0, "CC" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "CC" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(1), "G" ) ;
-		data.set_allele( 1, "GG" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 2 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "CC" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(1), "GG" ) ;
-		data.add_allele( "TT" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 3 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "CC" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(1), "GG" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(2), "TT" ) ;
-		data.set_allele( 0, "TTT" ) ;
-		BOOST_CHECK_EQUAL( data.number_of_alleles(), 3 ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(0), "TTT" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(1), "GG" ) ;
-		BOOST_CHECK_EQUAL( data.get_allele(2), "TT" ) ;
-	}
-}
-
-
-BOOST_AUTO_TEST_SUITE_END()
-
-
+		REQUIRE_EQUAL( data.number_of_alleles(), 2 ) ;
+		data.set_allele( 0, "CC" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 2 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "CC" ) ;
+		REQUIRE_EQUAL( data.get_allele(1), "G" ) ;
+		data.set_allele( 1, "GG" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 2 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "CC" ) ;
+		REQUIRE_EQUAL( data.get_allele(1), "GG" ) ;
+		data.add_allele( "TT" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 3 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "CC" ) ;
+		REQUIRE_EQUAL( data.get_allele(1), "GG" ) ;
+		REQUIRE_EQUAL( data.get_allele(2), "TT" ) ;
+		data.set_allele( 0, "TTT" ) ;
+		REQUIRE_EQUAL( data.number_of_alleles(), 3 ) ;
+		REQUIRE_EQUAL( data.get_allele(0), "TTT" ) ;
+		REQUIRE_EQUAL( data.get_allele(1), "GG" ) ;
+		REQUIRE_EQUAL( data.get_allele(2), "TT" ) ;
+	}
+}

Index: genfile/test/test_vcf_call_reader.cpp
==================================================================
--- genfile/test/test_vcf_call_reader.cpp
+++ genfile/test/test_vcf_call_reader.cpp
@@ -13,12 +13,10 @@
 #include "genfile/Error.hpp"
 #include "genfile/types.hpp"
 #include "genfile/string_utils.hpp"
 #include "test_case.hpp"
 
-BOOST_AUTO_TEST_SUITE( test_vcf_call_reader )
-
 using namespace genfile::vcf ;
 using namespace genfile::string_utils ;
 using namespace genfile ;
 using genfile::ValueType ;
 using genfile::OrderType ;
@@ -92,11 +90,11 @@
 		}
 		TEST_ASSERT( m_indices_of_set_values == expected ) ;
 	}
 
 	void initialise( std::size_t nSamples, std::size_t nAlleles ) {
-		BOOST_CHECK_EQUAL( m_number_of_samples, nSamples ) ;
+		REQUIRE_EQUAL( m_number_of_samples, nSamples ) ;
 	}
 
 	bool set_sample( std::size_t i ) {
 		TEST_ASSERT( i < m_calls.size() ) ;
 		m_sample_i = i ;
@@ -103,37 +101,37 @@
 		m_call_i = 0 ;
 		return true ;
 	}
 
 	void set_number_of_entries( uint32_t ploidy, std::size_t n, OrderType const order_type, ValueType const value_type ) {
-		BOOST_CHECK_EQUAL( m_calls[ m_sample_i ].size(), n ) ;
-		BOOST_CHECK_EQUAL( order_type, m_order_type ) ;
-		BOOST_CHECK_EQUAL( value_type, m_value_type ) ;
+		REQUIRE_EQUAL( m_calls[ m_sample_i ].size(), n ) ;
+		REQUIRE_EQUAL( order_type, m_order_type ) ;
+		REQUIRE_EQUAL( value_type, m_value_type ) ;
 	}
 
 	void set_value( std::size_t, genfile::MissingValue const value ) {
 		m_indices_of_set_values.insert( std::make_pair( m_sample_i, m_call_i )) ;
 		TEST_ASSERT( m_call_i < m_calls[ m_sample_i ].size() ) ;
-		BOOST_CHECK_EQUAL( m_calls[ m_sample_i ][ m_call_i++ ], Entry( value ) ) ;
+		REQUIRE_EQUAL( m_calls[ m_sample_i ][ m_call_i++ ], Entry( value ) ) ;
 	}
 
 	void set_value( std::size_t, std::string& value ) {
 		m_indices_of_set_values.insert( std::make_pair( m_sample_i, m_call_i )) ;
 		TEST_ASSERT( m_call_i < m_calls[ m_sample_i ].size() ) ;
-		BOOST_CHECK_EQUAL( m_calls[ m_sample_i ][ m_call_i++ ], Entry( value ) ) ;
+		REQUIRE_EQUAL( m_calls[ m_sample_i ][ m_call_i++ ], Entry( value ) ) ;
 	}
 
 	void set_value( std::size_t, Integer const value ) {
 		m_indices_of_set_values.insert( std::make_pair( m_sample_i, m_call_i )) ;
 		TEST_ASSERT( m_call_i < m_calls[ m_sample_i ].size() ) ;
-		BOOST_CHECK_EQUAL( m_calls[ m_sample_i ][ m_call_i++ ], Entry( value ) ) ;
+		REQUIRE_EQUAL( m_calls[ m_sample_i ][ m_call_i++ ], Entry( value ) ) ;
 	}
 
 	void set_value( std::size_t, double const value ) {
 		m_indices_of_set_values.insert( std::make_pair( m_sample_i, m_call_i )) ;
 		TEST_ASSERT( m_call_i < m_calls[ m_sample_i ].size() ) ;
-		BOOST_CHECK_EQUAL( m_calls[ m_sample_i ][ m_call_i++ ], Entry( value ) ) ;
+		REQUIRE_EQUAL( m_calls[ m_sample_i ][ m_call_i++ ], Entry( value ) ) ;
 	}
 
 	void finalise() {}
 
 	private:
@@ -159,11 +157,11 @@
 	void set_value( std::size_t, double const value ) {}
 	void finalise() {}
 } ;
 
 
-AUTO_TEST_CASE( test_format ) {
+TEST_CASE( "test_format" ) {
 	std::cerr << "test_format..." ;
 	test_format_types() ;
 	test_malformed_format() ;
 	std::cerr << "ok.\n" ;
 }
@@ -170,19 +168,19 @@
 
 void test_format_types() {
 	boost::ptr_map< std::string, VCFEntryType > types ;
 
 	// Test with no types.  Only empty format is allowed.
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "", "", types ) ) ;
-
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT", "", types ), genfile::BadArgumentError ) ;
-
-	BOOST_CHECK_THROW( CallReader( 1, 2, "HQ", "", types ), genfile::BadArgumentError ) ;
-
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT:HQ", "", types ), genfile::BadArgumentError ) ;
-
-	BOOST_CHECK_THROW( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "", "", types ) ) ;
+
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT", "", types ), genfile::BadArgumentError ) ;
+
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "HQ", "", types ), genfile::BadArgumentError ) ;
+
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT:HQ", "", types ), genfile::BadArgumentError ) ;
+
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
 
 	// Test with GT type only.  Only empty format or GT format allowed.
 	{
 		std::string const GT = "GT" ;
 		VCFEntryType::Spec spec ;
@@ -191,21 +189,21 @@
 		spec[ "Type" ] = "String" ;
 		spec[ "Description" ] = "A test" ;
 		types.insert( GT, VCFEntryType::create( spec )) ;
 	}
 
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "", "", types ) ) ;
-
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT", "", types ) ) ;
-
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT:GT", "", types ), genfile::BadArgumentError ) ;
-
-	BOOST_CHECK_THROW( CallReader( 1, 2, "HQ", "", types ), genfile::BadArgumentError ) ;
-
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT:HQ", "", types ), genfile::BadArgumentError ) ;
-	
-	BOOST_CHECK_THROW( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "", "", types ) ) ;
+
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT", "", types ) ) ;
+
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT:GT", "", types ), genfile::BadArgumentError ) ;
+
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "HQ", "", types ), genfile::BadArgumentError ) ;
+
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT:HQ", "", types ), genfile::BadArgumentError ) ;
+	
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
 
 	// Test with HQ type only.
 
 	types.clear() ;
 	{
@@ -216,16 +214,16 @@
 		spec[ "Type" ] = "String" ;
 		spec[ "Description" ] = "A test, HQ" ;
 		types.insert( ID, VCFEntryType::create( spec )) ;
 	}
 	
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "", "", types ) ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT", "", types ), genfile::BadArgumentError ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT:GT", "", types ), genfile::BadArgumentError ) ;
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "HQ", "", types ) ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT:HQ", "", types ), genfile::BadArgumentError ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "", "", types ) ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT:GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "HQ", "", types ) ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT:HQ", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
 	
 	// Test with GT and HQ type.	
 	{
 		std::string const GT = "GT" ;
 		VCFEntryType::Spec spec ;
@@ -234,21 +232,21 @@
 		spec[ "Type" ] = "String" ;
 		spec[ "Description" ] = "A test" ;
 		types.insert( GT, VCFEntryType::create( spec )) ;
 	}
 	
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "", "", types ) ) ;
-
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT", "", types ) ) ;
-
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT:GT", "", types ), genfile::BadArgumentError ) ;
-
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "HQ", "", types ) ) ;
-
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT:HQ", "", types ) ) ;
-	
-	BOOST_CHECK_THROW( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "", "", types ) ) ;
+
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT", "", types ) ) ;
+
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT:GT", "", types ), genfile::BadArgumentError ) ;
+
+	REQUIRE_NOTHROW( CallReader( 1, 2, "HQ", "", types ) ) ;
+
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT:HQ", "", types ) ) ;
+	
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
 	
 	// Test with three types
 	{
 		std::string const ID = "another_type" ;
 		VCFEntryType::Spec spec ;
@@ -257,25 +255,25 @@
 		spec[ "Type" ] = "String" ;
 		spec[ "Description" ] = "Another test type" ;
 		types.insert( ID, VCFEntryType::create( spec )) ;
 	}
 
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "", "", types ) ) ;
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT", "", types ) ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT:GT", "", types ), genfile::BadArgumentError ) ;
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "HQ", "", types ) ) ;
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT:HQ", "", types ) ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT:another_type", "", types ) ) ;
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT:HQ:another_type", "", types ) ) ;
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT:another_type:HQ", "", types ) ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "another_type:GT:HQ", "", types ), genfile::BadArgumentError ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "another_type:HQ:GT", "", types ), genfile::BadArgumentError ) ;
-	BOOST_CHECK_THROW( CallReader( 1, 2, "GT:another_type:HQ:another_type", "", types ), genfile::BadArgumentError ) ;
-}
-
-AUTO_TEST_CASE( test_setters ) {
+	REQUIRE_NOTHROW( CallReader( 1, 2, "", "", types ) ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT", "", types ) ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT:GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "HQ", "", types ) ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT:HQ", "", types ) ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "HQ:GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT:another_type", "", types ) ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT:HQ:another_type", "", types ) ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT:another_type:HQ", "", types ) ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "another_type:GT:HQ", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "another_type:HQ:GT", "", types ), genfile::BadArgumentError ) ;
+	REQUIRE_THROWS_AS( CallReader( 1, 2, "GT:another_type:HQ:another_type", "", types ), genfile::BadArgumentError ) ;
+}
+
+TEST_CASE( "test_setters" ) {
 	std::cerr << "test_setters()..." ;
 
 	Ignore ignore ;
 
 	using namespace genfile ;
@@ -307,11 +305,11 @@
 		spec[ "Type" ] = "String" ;
 		spec[ "Description" ] = "Another test type" ;
 		types.insert( ID, VCFEntryType::create( spec )) ;
 	}
 	
-	BOOST_CHECK_NO_THROW( CallReader( 1, 2, "GT", "1|1", types ) ) ;
+	REQUIRE_NOTHROW( CallReader( 1, 2, "GT", "1|1", types ) ) ;
 
 	try {
 		std::vector< std::vector< Entry > > expected ;
 		expected.push_back( std::vector< Entry >( 2, Entry( 1 ))) ;
 		GenotypeCallChecker checker( expected, ePerOrderedHaplotype ) ;
@@ -440,11 +438,11 @@
 			}
 		}
 	}
 }
 
-AUTO_TEST_CASE( test_alleles ) {
+TEST_CASE( "test_alleles" ) {
 	std::cerr << "test_alleles..." ;
 	boost::ptr_map< std::string, VCFEntryType > types ;
 	{
 		std::string const GT = "GT" ;
 		VCFEntryType::Spec spec ;
@@ -539,11 +537,11 @@
 		types.insert( AT, VCFEntryType::create( spec )) ;
 	}
 	return types.release() ;
 }
 
-AUTO_TEST_CASE( test_simple_gt_values ) {
+TEST_CASE( "test_simple_gt_values" ) {
 	std::cerr << "test_simple_gt_values..." ;
 	boost::ptr_map< std::string, VCFEntryType > types( make_some_types() ) ;
 
 	Ignore ignore ;
 	
@@ -631,11 +629,11 @@
 	}
 
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_omitted_values ) {
+TEST_CASE( "test_omitted_values" ) {
 	std::cerr << "test_omitted_values..." ;
 	boost::ptr_map< std::string, VCFEntryType > types( make_some_types() ) ;
 	// types:
 	// GT
 	// AT - Number=1, Type=String
@@ -687,11 +685,11 @@
 		TEST_ASSERT(0) ;
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_gt_delimiter ) {
+TEST_CASE( "test_gt_delimiter" ) {
 	std::cerr << "test_gt_delimiter..." ;
 	boost::ptr_map< std::string, VCFEntryType > types( make_some_types() ) ;
 
 	Ignore ignore ;
 
@@ -718,18 +716,18 @@
 			}
 			catch( genfile::MalformedInputError const& ) {
 				TEST_ASSERT( number_of_individuals != 0 ) ;
 			}
 			catch( genfile::BadArgumentError const& ) {
-				BOOST_CHECK_EQUAL( number_of_individuals, 0ul ) ;
+				REQUIRE_EQUAL( number_of_individuals, 0ul ) ;
 			}
 		}
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_complex_gt_values ) {
+TEST_CASE( "test_complex_gt_values" ) {
 	std::cerr << "test_complex_gt_values..." ;
 	boost::ptr_map< std::string, VCFEntryType > types( make_some_types() ) ;
 
 	for( std::size_t number_of_individuals = 0; number_of_individuals < 25; ++number_of_individuals ) {
 		// std::cerr << number_of_individuals << " " ;
@@ -759,19 +757,19 @@
 				}
 				catch( genfile::MalformedInputError const& e ) {
 					TEST_ASSERT(0) ;
 				}
 				catch( genfile::BadArgumentError const& e ) {
-					BOOST_CHECK_EQUAL( number_of_individuals, 0 ) ;
+					REQUIRE_EQUAL( number_of_individuals, 0 ) ;
 				}
 			}
 		}
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_gt_genotype_bounds ) {
+TEST_CASE( "test_gt_genotype_bounds" ) {
 	std::cerr << "test_gt_genotype_bounds..." ;
 	boost::ptr_map< std::string, VCFEntryType > types( make_some_types() ) ;
 
 	for( int n_alleles = 1; n_alleles < 100; ++n_alleles ) {
 		for( int call = 0; call < 110; ++call ) {
@@ -786,11 +784,11 @@
 				expected_set_calls.push_back( std::vector< Entry >( 1, call )) ;
 				checker.reset( new GenotypeCallChecker( expected_set_calls, ePerOrderedHaplotype ) ) ;
 			}
 			
 			if( bad_call ) {
-				BOOST_CHECK_THROW(
+				REQUIRE_THROWS_AS(
 					CallReader(
 						1,
 						n_alleles,
 						"GT",
 						to_string( call ),
@@ -799,11 +797,11 @@
 					.get( "GT", boost::ref( *checker )),
 					genfile::MalformedInputError
 				) ;
 			}
 			else {
-				BOOST_CHECK_NO_THROW(
+				REQUIRE_NOTHROW(
 					CallReader(
 						1,
 						n_alleles,
 						"GT",
 						to_string( call ),
@@ -816,11 +814,11 @@
 	}
 
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_gt_genotype_bounds_2_samples ) {
+TEST_CASE( "test_gt_genotype_bounds_2_samples" ) {
 	std::cerr << "test_gt_genotype_bounds_2_samples..." ;
 	boost::ptr_map< std::string, VCFEntryType > types( make_some_types() ) ;
 
 	std::size_t n_samples = 2 ;
 
@@ -842,11 +840,11 @@
 				checker.reset( new GenotypeCallChecker( expected_set_calls, ePerOrderedHaplotype ) ) ;
 			}
 
 
 			if( bad_call ) {
-				BOOST_CHECK_THROW(
+				REQUIRE_THROWS_AS(
 					CallReader(
 						n_samples,
 						n_alleles,
 						"GT",
 						data,
@@ -855,11 +853,11 @@
 					.get( "GT", boost::ref( *checker )),
 					genfile::MalformedInputError
 				) ;
 			}
 			else {
-				BOOST_CHECK_NO_THROW(
+				REQUIRE_NOTHROW(
 					CallReader(
 						n_samples,
 						n_alleles,
 						"GT",
 						data,
@@ -872,11 +870,11 @@
 	}
 
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_float_fields ) {
+TEST_CASE( "test_float_fields" ) {
 	std::cerr << "test_float_fields..." ;
 	
 	// verify that we can read float fields out of the data correctly.
 
 	boost::ptr_map< std::string, VCFEntryType > types( make_some_types() ) ;
@@ -1067,7 +1065,5 @@
 		}
 	}
 
 	std::cerr << "ok.\n" ;
 }
-
-BOOST_AUTO_TEST_SUITE_END()

Index: genfile/test/test_vcf_format_source.cpp
==================================================================
--- genfile/test/test_vcf_format_source.cpp
+++ genfile/test/test_vcf_format_source.cpp
@@ -162,38 +162,38 @@
 		TEST_ASSERT( my_snps.size() == my_probs.size() ) ;
 		TEST_ASSERT( my_probs.size() == cvcft_probs.size() ) ;
 		
 		for( std::size_t i = 0; i < my_snps.size(); ++i ) {
 			TEST_ASSERT( my_probs[i] == cvcft_probs[i] ) ;
-			BOOST_CHECK_EQUAL( my_snps[i].get_primary_id(), cvcft_snps[i].get_primary_id() ) ;
-			BOOST_CHECK_EQUAL( my_snps[i].get_position(), cvcft_snps[i].get_position() ) ;
-			BOOST_CHECK_EQUAL( my_snps[i].get_allele(0), cvcft_snps[i].get_allele(0) ) ;
-			BOOST_CHECK_EQUAL( my_snps[i].get_allele(1), cvcft_snps[i].get_allele(1) ) ;
-		}
-	}
-}
-
-AUTO_TEST_CASE( test_against_cvcft1 ) {
-	perform_test_against_cvcft( data::metadata4_0 + data::data1, 7, "GL1", 4*3 ) ;
-}
-AUTO_TEST_CASE( test_against_cvcft2 ) {
-	perform_test_against_cvcft( data::metadata4_0 + data::data1, 7, "GL3", 4*3 ) ;
-}
-AUTO_TEST_CASE( test_against_cvcft3 ) {
-	perform_test_against_cvcft( data::metadata4_0 + data::data2, 5, "GL1", 4*3 ) ;
-}
-AUTO_TEST_CASE( test_against_cvcft4 ) {
-	perform_test_against_cvcft( data::metadata4_0 + data::data2, 5, "GL3", 4*3 ) ;
-}
-AUTO_TEST_CASE( test_against_cvcft5 ) {
-	perform_test_against_cvcft( data::metadata4_1 + data::data1, 7, "GL1", 4*3 ) ;
-}
-AUTO_TEST_CASE( test_against_cvcft6 ) {
-	perform_test_against_cvcft( data::metadata4_1 + data::data1, 7, "GL3", 4*3 ) ;
-}
-AUTO_TEST_CASE( test_against_cvcft7 ) {
-	perform_test_against_cvcft( data::metadata4_1 + data::data2, 5, "GL1", 4*3 ) ;
-}
-AUTO_TEST_CASE( test_against_cvcft8 ) {
+			REQUIRE_EQUAL( my_snps[i].get_primary_id(), cvcft_snps[i].get_primary_id() ) ;
+			REQUIRE_EQUAL( my_snps[i].get_position(), cvcft_snps[i].get_position() ) ;
+			REQUIRE_EQUAL( my_snps[i].get_allele(0), cvcft_snps[i].get_allele(0) ) ;
+			REQUIRE_EQUAL( my_snps[i].get_allele(1), cvcft_snps[i].get_allele(1) ) ;
+		}
+	}
+}
+
+TEST_CASE( "test_against_cvcft1" ) {
+	perform_test_against_cvcft( data::metadata4_0 + data::data1, 7, "GL1", 4*3 ) ;
+}
+TEST_CASE( "test_against_cvcft2" ) {
+	perform_test_against_cvcft( data::metadata4_0 + data::data1, 7, "GL3", 4*3 ) ;
+}
+TEST_CASE( "test_against_cvcft3" ) {
+	perform_test_against_cvcft( data::metadata4_0 + data::data2, 5, "GL1", 4*3 ) ;
+}
+TEST_CASE( "test_against_cvcft4" ) {
+	perform_test_against_cvcft( data::metadata4_0 + data::data2, 5, "GL3", 4*3 ) ;
+}
+TEST_CASE( "test_against_cvcft5" ) {
+	perform_test_against_cvcft( data::metadata4_1 + data::data1, 7, "GL1", 4*3 ) ;
+}
+TEST_CASE( "test_against_cvcft6" ) {
+	perform_test_against_cvcft( data::metadata4_1 + data::data1, 7, "GL3", 4*3 ) ;
+}
+TEST_CASE( "test_against_cvcft7" ) {
+	perform_test_against_cvcft( data::metadata4_1 + data::data2, 5, "GL1", 4*3 ) ;
+}
+TEST_CASE( "test_against_cvcft8" ) {
 	perform_test_against_cvcft( data::metadata4_1 + data::data2, 5, "GL3", 4*3 ) ;
 }
 

Index: genfile/test/test_vcf_metadata.cpp
==================================================================
--- genfile/test/test_vcf_metadata.cpp
+++ genfile/test/test_vcf_metadata.cpp
@@ -12,12 +12,10 @@
 #include "genfile/Error.hpp"
 #include "test_case.hpp"
 
 // #define DEBUG 1
 
-BOOST_AUTO_TEST_SUITE( test_vcf_metadata )
-
 namespace data {
 	// This example is from http://www.1000genomes.org/wiki/Analysis/Variant%20Call%20Format/vcf-variant-call-format-version-41
 	std::string const ex1 =
 		"##fileformat=VCFv4.1\n"
 		"##fileDate=20090805\n"
@@ -67,11 +65,11 @@
 		"20\t1110696\trs6040355\tA\tG,T\t67\tPASS\tNS=2;DP=10;AF=0.333,0.667;AA=T;DB\tGT:GQ:DP:HQ\t1|2:21:6:23,27\t2|1:2:0:18,2\t2/2:35:4\n"
 		"20\t1230237\t.\tT\t.\t47\tPASS\tNS=3;DP=13;AA=T\tGT:GQ:DP:HQ\t0|0:54:7:56,60\t0|0:48:4:51,51\t0/0:61:2\n"
 		"20\t1234567\tmicrosat1\tGTC\tG,GTCTC\t50\tPASS\tNS=3;DP=9;AA=G\tGT:GQ:DP\t0/1:35:4\t0/2:17:2\t1/1:40:3\n" ;
 }
 
-AUTO_TEST_CASE( test_spec_example ) {
+TEST_CASE( "test_spec_example" ) {
 	using namespace data ;
 	std::cerr << "test_spec_example()..." ;
 	std::istringstream istr( ex1 + ex2 + ex3 + ex4 + ex5 + ex6 ) ;
 	genfile::vcf::StrictMetadataParser parser( "VCF_4_1_example_file", istr ) ;
 	std::string s ;
@@ -125,11 +123,11 @@
 	where = metadata.equal_range( "FILTER" ).first ;
 	
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_no_fileformat ) {
+TEST_CASE( "test_no_fileformat" ) {
 	using namespace data ;
 	std::cerr << "test_no_fileformat()..." ;
 	std::string content = ex1 + ex2 + ex3 + ex4 + ex5 + ex6 ;
 	// turn it into "gileformat"
 	content[3] = 'g' ;
@@ -142,11 +140,11 @@
 		// ok.
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_malformed_file ) {
+TEST_CASE( "test_malformed_file" ) {
 	using namespace data ;
 	std::cerr << "test_malformed_file()..." ;
 	// ex1 must be present.  Metadata ends with EOF or a a final line not starting with ##.
 	try {
 		std::istringstream istr( ex1 + ex2 + ex3 + ex4 ) ;
@@ -175,11 +173,11 @@
 	}
 	std::cerr << "ok.\n" ;
 }	
 
 void test_info_or_format_field( std::string const& field ) {
-	TEST_ASSERT( field == "INFO" || field == "FORMAT" ) ;
+	REQUIRE( ((field == "INFO") || (field == "FORMAT")) ) ;
 	std::cerr << "test_info_or_format_field(" << field << ")..." ;
 	std::vector< std::string > types ;
 	types.push_back( "Integer" ) ;
 	types.push_back( "Float" ) ;
 	types.push_back( "String" ) ;
@@ -246,11 +244,11 @@
 						&& ( bad_descriptions.count( description_i ) == 0 ) ;
 #if DEBUG
 					std::cerr << "DATA=\"" << istr.str() << "\", this is " << (good ? "good" : "bad") << ".\n" ;
 #endif
 					if( good ) {
-						BOOST_CHECK_NO_THROW( genfile::vcf::StrictMetadataParser( "VCF_4_1_example_file", istr ) ) ;
+						REQUIRE_NOTHROW( genfile::vcf::StrictMetadataParser( "VCF_4_1_example_file", istr ) ) ;
 						std::string s ;
 						istr >> s ;
 						TEST_ASSERT( s == "END" ) ;
 					} else {
 						genfile::vcf::StrictMetadataParser parser( "VCF_4_1_example_file", istr ) ;
@@ -262,16 +260,16 @@
 	}
 
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_info_and_format_fields ) {
+TEST_CASE( "test_info_and_format_fields" ) {
 	test_info_or_format_field( "INFO" ) ;
 	test_info_or_format_field( "FORMAT" ) ;
 }
 
-AUTO_TEST_CASE( test_filter_fields ) {
+TEST_CASE( "test_filter_fields" ) {
 	std::cerr << "test_filter_fields()..." ;
 	std::vector< std::string > IDs ;
 	IDs.push_back( "AnID" ) ;
 	IDs.push_back( "HG" ) ;
 	IDs.push_back( "222 222" ) ;
@@ -316,11 +314,11 @@
 	}
 
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_tab_characters ) {
+TEST_CASE( "test_tab_characters" ) {
 	std::cerr << "test_tab_characters()..." ;
 	// no tab characters are allowed anywhere in the metadata.
 	using namespace data ;
 	std::string base_content = ex1 + ex2 + ex3 + ex4 ;
 	for( std::size_t i = 0; i < base_content.size(); ++i ) {
@@ -336,11 +334,11 @@
 		}
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_v4_0 ) {
+TEST_CASE( "test_v4_0" ) {
 	using namespace data ;
 	std::cerr << "test_v4_0()..." ;
 	{
 		// Correct metadata
 		std::istringstream istr( ex1b + ex2 + ex3 + ex4 + ex5 + ex6 ) ;
@@ -356,11 +354,9 @@
 	}
 
 	{
 		// Incorrect fileformat line
 		std::istringstream istr( ex1c + ex2 + ex3 + ex4 + ex5 + ex6 ) ;
-		BOOST_CHECK_THROW( genfile::vcf::StrictMetadataParser parser( "VCF_4_0_example_file", istr ), genfile::InputError ) ;
+		REQUIRE_THROWS_AS( genfile::vcf::StrictMetadataParser( "VCF_4_0_example_file", istr ), genfile::InputError ) ;
 	}
 	std::cerr << "ok.\n" ;
 }
-
-BOOST_AUTO_TEST_SUITE_END()

Index: genfile/test/test_vcf_types.cpp
==================================================================
--- genfile/test/test_vcf_types.cpp
+++ genfile/test/test_vcf_types.cpp
@@ -10,21 +10,19 @@
 #include "genfile/Error.hpp"
 
 using namespace genfile::vcf ;
 using namespace std ;
 
-BOOST_AUTO_TEST_SUITE( test_vcf_types )
-
-AUTO_TEST_CASE( test_string ) {
+TEST_CASE( "test_string" ) {
 	std::cerr << "test_string()..." ;
 	TEST_ASSERT( StringType().parse( string( "" ) ).as< string >() == "" ) ;
 	TEST_ASSERT( StringType().parse( string( "Hello. there" ) ).as< string >() == "Hello. there" ) ;
 	TEST_ASSERT( StringType().parse( string( "\t\n\rb" ) ).as< string >() == "\t\n\rb" ) ;
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_character ) {
+TEST_CASE( "test_character" ) {
 	std::cerr << "test_character()..." ;
 	try {
 		CharacterType().parse( string( "" ) ) ;
 		TEST_ASSERT(0) ;
 	}
@@ -44,11 +42,11 @@
 		TEST_ASSERT( CharacterType().parse( string( 1, char(c) ) ).as< string >() == string( 1, char(c) ) ) ;
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_integer ) {
+TEST_CASE( "test_integer" ) {
 	std::cerr << "test_integer()..." ;
 	TEST_ASSERT( IntegerType().parse( string( "0" )).as< int >() == 0 ) ;
 	TEST_ASSERT( IntegerType().parse( string( "-0" )).as< int >() == 0 ) ;
 	TEST_ASSERT( IntegerType().parse( string( "1000" )).as< int >() == 1000 ) ;
 	TEST_ASSERT( IntegerType().parse( string( "-10000" )).as< int >() == -10000 ) ;
@@ -77,11 +75,11 @@
 		// ok.
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_float ) {
+TEST_CASE( "test_float" ) {
 	std::cerr << "test_float()..." ;
 	TEST_ASSERT( FloatType().parse( string( "0" )).as< double >() == 0.0 ) ;
 	TEST_ASSERT( FloatType().parse( string( "-0" )).as< double >() == -0.0 ) ;
 	TEST_ASSERT( FloatType().parse( string( "0.0" )).as< double >() == 0.0 ) ;
 	TEST_ASSERT( FloatType().parse( string( "-0.0" )).as< double >() == -0.0 ) ;
@@ -170,11 +168,11 @@
 		return result ;
 	}
 	
 	
 }
-AUTO_TEST_CASE( test_fixed_number_entry_type ) {
+TEST_CASE( "test_fixed_number_entry_type" ) {
 	std::cerr << "test_fixed_number_entry_type()..." ;
 
 	using genfile::BadArgumentError ;
 	using genfile::MissingValue ;
 	
@@ -423,11 +421,11 @@
 	}
 
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_dynamic_number_entry_type ) {
+TEST_CASE( "test_dynamic_number_entry_type" ) {
 	std::cerr << "test_dynamic_number_entry_type()..." ;
 
 	using namespace genfile ;
 
 	// test some simple parseable values
@@ -520,11 +518,11 @@
 		try { parse(  type2, std::string( "1,2," ), n_alleles, ploidy ) ; } catch( BadArgumentError const& ) { TEST_ASSERT(0) ; }
 	}
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_one_per_allele_entry_type ) {
+TEST_CASE( "test_one_per_allele_entry_type" ) {
 	std::cerr << "test_one_per_alternate_allele_entry_type()..." ;
 
 	using namespace genfile ;
 
 	{
@@ -592,11 +590,11 @@
 		}
 		return result ;
 	}
 }
 
-AUTO_TEST_CASE( test_one_per_genotype_entry_type ) {
+TEST_CASE( "test_one_per_genotype_entry_type" ) {
 	std::cerr << "test_one_per_genotype_entry_type()..." ;
 
 	using genfile::BadArgumentError ;
 	using genfile::string_utils::to_string ;
 
@@ -701,11 +699,11 @@
 	}
 
 	std::cerr << "ok.\n" ;
 }
 
-AUTO_TEST_CASE( test_genotype_call_entry_type ) {
+TEST_CASE( "test_genotype_call_entry_type" ) {
 	std::cerr << "test_genotype_call_entry_type()..." ;
 	using namespace genfile ;
 	using genfile::string_utils::to_string ;
 
 	GenotypeCallVCFEntryType type ;
@@ -839,7 +837,5 @@
 		VCFEntryType::create( spec ) ;
 		TEST_ASSERT(0) ;
 	}
 	catch( genfile::BadArgumentError const& ) {}	
 }
-
-BOOST_AUTO_TEST_SUITE_END()

Index: genfile/wscript
==================================================================
--- genfile/wscript
+++ genfile/wscript
@@ -3,34 +3,25 @@
 #import UnitTest
 
 def configure( conf ):
 	pass
 
-def create_tests( bld ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'all_tests',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'genfile boost boost-unit_test_framework',
-		uselib = 'ZLIB',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
-		target = 'genfile',
-		source = bld.glob( 'src/*.cpp' ) + bld.glob( 'src/bgen/*.cpp' ) + bld.glob( 'src/vcf/*.cpp' ) + bld.glob( 'src/string_utils/*.cpp' ),
-		includes='./include',
-		uselib_local = 'boost eigen zstd',
-		uselib = 'ZLIB',
-		export_incdirs = './include'
-	)
-
-	create_tests( bld )
+def build( bld ):
+	bld.stlib(
+		target = 'genfile',
+		source = bld.path.ant_glob( 'src/*.cpp' )
+			+ bld.path.ant_glob( 'src/bgen/*.cpp' )
+			+ bld.path.ant_glob( 'src/vcf/*.cpp' )
+			+ bld.path.ant_glob( 'src/string_utils/*.cpp' )
+			+ bld.path.ant_glob( 'src/db/*.cpp' ),
+		includes='./include',
+		use = 'boost eigen zstd sqlite3 ZLIB',
+		export_includes = './include'
+	)
+	bld.program(
+		target = 'test-genfile',
+		source = bld.path.ant_glob( 'test/*.cpp' ),
+		use = 'genfile boost ZLIB',
+		includes='./include',
+		unit_test = 1,
+		install_path = None
+	)

DELETED include/compute_maximum_likelihood_allele_frequency.hpp
Index: include/compute_maximum_likelihood_allele_frequency.hpp
==================================================================
--- include/compute_maximum_likelihood_allele_frequency.hpp
+++ include/compute_maximum_likelihood_allele_frequency.hpp
@@ -1,14 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef QCTOOL_COMPUTE_MAXIMUM_LIKELIHOOD_ALLELE_FREQUENCY_HPP
-#define QCTOOL_COMPUTE_MAXIMUM_LIKELIHOOD_ALLELE_FREQUENCY_HPP
-
-#include "genfile/SingleSNPGenotypeProbabilities.hpp"
-
-double compute_maximum_likelihood_allele_frequency( genfile::SingleSNPGenotypeProbabilities const& genotypes ) ;
-
-#endif

DELETED include/gamma.hpp
Index: include/gamma.hpp
==================================================================
--- include/gamma.hpp
+++ include/gamma.hpp
@@ -1,26 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef __GTOOL__GAMMA_HPP__
-#define __GTOOL__GAMMA_HPP__
-
-#include <vector>
-#include <cstddef>
-
-namespace impl {
-	extern double const coefficient_array1[] ;
-	extern std::size_t const coefficient_array1_size ;
-	extern double const coefficient_array2[] ;
-	extern std::size_t const coefficient_array2_size ;
-	extern double const pi ;
-	extern double const sqrt_of_2_pi ;
-	extern std::vector< double > log_of_factorial_table ;
-}
-
-double log_of_gamma_function( double x, double const* const coefficient_array = impl::coefficient_array2, std::size_t const number_of_coefficients = impl::coefficient_array2_size ) ;
-double log_of_factorial( unsigned long x ) ;
-
-#endif

DELETED integration/include/integration/ModifiedCholesky.hpp
Index: integration/include/integration/ModifiedCholesky.hpp
==================================================================
--- integration/include/integration/ModifiedCholesky.hpp
+++ integration/include/integration/ModifiedCholesky.hpp
@@ -1,250 +0,0 @@
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef INTEGRATION_MODIFIED_CHOLESKY_HPP
-#define INTEGRATION_MODIFIED_CHOLESKY_HPP
-
-#include <iostream>
-#include <boost/noncopyable.hpp>
-#include <Eigen/Core>
-#include <Eigen/Cholesky>
-#include <Eigen/Eigenvalues>
-
-// #define DEBUG_MODIFIED_CHOLESKY 1
-
-namespace integration {
-	//
-	// Implements the 'MC' algorithm from Gill & Murray, Practical Optimisation.
-	// Also expressed as Algorithm 6.5, "Modified Cholesky algorithm" in
-	// Nocedal & Wright, "Numerical Optimisation".
-	//
-	// I have borrowed a little bit from Eigen's LDLT.h here to get the permutations and types right.
-	//
-	// This algorithm only touches the lower-diagonal of the matrix.
-	// As described in the above references, we use the lower-diagonal of the matrix
-	// to store the non-unity entries of L, and the diagonal to store the entries of D.
-	// The auxiliary variables c_ij are stored in the lower diagonal too until they
-	// are overwritten by entries of L and D.
-	//
-	// At step j the matrix looks like:
-	//
-	//    0 . . j . .
-	// 0  d
-	// .  l d
-	// .  l l d
-	// j  c c c c
-	// .  c c c a c
-	// .  c c c a a c
-	//
-	// Where a refers to an entry of the original matrix (after the possible permutations) and l refers to an entry of
-	// the computed matrix L, d refers to an entry of D, and c to one of the auxiliary c_ijs.
-	//
-	// At the jth step we update this to become
-	// 1: d
-	// .  l d
-	// .  l l d
-	// j: l l l d
-	// .  c c c c c
-	// .  c c c c a c
-	//
-	// i.e. we compute the jth row of L, the jth entry of D, and the c's in
-	// the jth column and on the diagonal below j.
-	template< typename Matrix >
-	struct ModifiedCholesky {
-	public:
-	    enum {
-	      RowsAtCompileTime = Matrix::RowsAtCompileTime,
-	      ColsAtCompileTime = Matrix::ColsAtCompileTime,
-	      Options = Matrix::Options & ~Eigen::RowMajorBit, // these are the options for the TmpMatrixType, we need a ColMajor matrix here!
-	      MaxRowsAtCompileTime = Matrix::MaxRowsAtCompileTime,
-	      MaxColsAtCompileTime = Matrix::MaxColsAtCompileTime,
-	      UpLo = Eigen::Lower
-	    } ;
-	    typedef typename Matrix::Scalar Scalar;
-	    typedef typename Eigen::NumTraits<typename Matrix::Scalar>::Real RealScalar;
-	    typedef typename Matrix::Index Index;
-
-	    typedef Eigen::Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> Transpositions;
-	    typedef Eigen::PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> Permutations;
-	    typedef Eigen::TriangularView< Matrix const, Eigen::UnitLower > const MatrixL ;
-		typedef Eigen::Diagonal< Matrix const > Diagonal ;
-
-	public:
-		ModifiedCholesky() {}
-
-		ModifiedCholesky( ModifiedCholesky const& other ):
-			m_matrix( other.m_matrix ),
-			m_transpositions( other.m_transpositions )
-		{}
-
-		ModifiedCholesky& operator=( ModifiedCholesky const& other ) {
-			m_matrix = other.m_matrix ;
-			m_transpositions = other.m_transpositions ;
-			return *this ;
-		}
-		
-		ModifiedCholesky& compute( Matrix const& matrix ) {
-			m_matrix = matrix ;
-			compute_inplace( m_matrix ) ;
-			return *this ;
-		}
-		
-		MatrixL matrixL() const {
-			return m_matrix ;
-		}
-		
-	    Diagonal vectorD() const {
-			return m_matrix.diagonal();
-		}
-
-		Transpositions const matrixP() const {
-			return m_transpositions ;
-		}
-		
-		Matrix solve( Matrix const& rhs ) const
-	    {
-			Matrix result = rhs ;
-			assert( result.rows() == m_matrix.rows() ) ;
-		    // result = P rhs
-		    result = m_transpositions * result ;
-		    // result = L^-1 (P rhs)
-		    matrixL().solveInPlace( result );
-		    // result = D^-1 (L^-1 P rhs)
-			for( Index i = 0; i < m_matrix.rows(); ++i ) {
-				result.row(i) /= m_matrix(i,i) ;
-			}
-		    // result = L^-T (D^-1 L^-1 P rhs)
-		    matrixL().transpose().solveInPlace( result ) ;
-		    // result = P^-1 L^-T (D^-1 L^-1 P rhs)
-			result = m_transpositions.transpose() * result ;
-			return result ;
-	    }
-		
-	private:
-	    Matrix m_matrix ;
-	    Transpositions m_transpositions;
-		
-	private:
-		
-		void compute_inplace( Matrix& matrix ) {
-			assert( matrix.rows() == matrix.cols() ) ;
-			m_transpositions.resize( matrix.rows() ) ;
-			Index const size = matrix.rows() ;
-			
-#if DEBUG_MODIFIED_CHOLESKY
-			std::cerr << "ModifiedCholesky::compute_inplace(): computing with matrix:\n" << matrix << ".\n" ;
-#endif
-			
-			Scalar biggestOnDiagonal ;
-			RealScalar beta ;
-			RealScalar betaSquared ;
-			RealScalar delta ;
-
-			for( Index j = 0; j < size; ++j ) {
-		        // Find largest diagonal element
-		        Index indexOfBiggestOnDiagonal ;
-		        biggestOnDiagonal = matrix.diagonal().tail( size - j ).cwiseAbs().maxCoeff( &indexOfBiggestOnDiagonal ) ;
-				indexOfBiggestOnDiagonal += j ;
-
-				// Initialise beta and delta if we are starting.
-		        if( j == 0 ) {
-					Scalar biggestOffDiagonal = 0.0 ;
-					for( Index i = 0; i < size; ++i ) {
-						for( Index j = i+1; j < size; ++j ) {
-							biggestOffDiagonal = std::max( biggestOffDiagonal, std::abs( matrix( i, j )) ) ;
-						}
-					}
-					delta = std::numeric_limits< Scalar >::epsilon() * std::max( biggestOnDiagonal + biggestOffDiagonal, Scalar( 1 ) ) ;
-					beta = std::max(
-						std::numeric_limits< Scalar >::epsilon(),
-						std::max( biggestOnDiagonal, biggestOffDiagonal / std::sqrt( ( size * size ) - 1 ) )
-					) ;
-					betaSquared = beta * beta ;
-					
-#if DEBUG_MODIFIED_CHOLESKY
-					std::cerr << "ModifiedCholesky::compute_inplace(): initialised with delta = "
-						<< delta << ", beta^2 = " << betaSquared << ".\n" ;
-#endif
-					
-				}
-				
-#if DEBUG_MODIFIED_CHOLESKY
-				std::cerr << "ModifiedCholesky::compute_inplace(): at iteration "
-					<< j
-						<< ": largest entry on diagonal = " << biggestOnDiagonal
-					<< " at index " << indexOfBiggestOnDiagonal << ".\n" ;
-#endif
-											
-				// Swap rows and columns corresponding to the jth and largest diagonal element.
-		        m_transpositions.coeffRef( j ) = indexOfBiggestOnDiagonal ;
-				Index const tailSize = size - indexOfBiggestOnDiagonal - 1 ;
-		        if( j != indexOfBiggestOnDiagonal ) {
-					// indexOfbiggestOnDiagonal is always >= j by construction
-					// we only touch the lower triangular part of the matrix.
-					matrix.row( j ).head( j ).swap( matrix.row( indexOfBiggestOnDiagonal ).head( j ) ) ;
-					matrix.col( j ).tail( tailSize ).swap( matrix.col( indexOfBiggestOnDiagonal ).tail( tailSize ) ) ;
-					std::swap( matrix.coeffRef(j,j), matrix.coeffRef( indexOfBiggestOnDiagonal, indexOfBiggestOnDiagonal ) );
-					for( int i = j+1; i < indexOfBiggestOnDiagonal; ++i ) {
-						std::swap( matrix.coeffRef( i, j ), matrix.coeffRef( indexOfBiggestOnDiagonal, i ) ) ;
-					}
-				}
-				
-				// We first compute the jth row of L to produce:
-				// 1: d
-				// .  l d
-				// .  l l d
-				// j: l l l c
-				// .  c c c a c
-				// .  c c c a a c
-				//
-				// by formula: l_js = c_js / d_s for s = 0,...,j-1.
-		        matrix.row( j ).head( j ).array() /= matrix.diagonal().head( j ).array() ;
-#if DEBUG_MODIFIED_CHOLESKY
-				std::cerr << "ModifiedCholesky::compute_inplace(): after computing ls, matrix =\n"
-					<< matrix << ".\n" ;
-#endif
-				// We next compute jth column of c_ijs to get:
-				// 1: d
-				// .  l d
-				// .  l l d
-				// j: l l l c
-				// .  c c c c c
-				// .  c c c c a c
-				//
-				// by formula c_ij = a_ij - sum_s l_ks c_is for s=j+1...n
-				for( Index i = j+1; i < size; ++i ) {
-					matrix(i,j) -= ( matrix.row( j ).head( j ) * matrix.row( i ).head( j ).transpose() ) ;
-				}
-				Scalar const theta = ( (j+1) == size ) ? 0.0 : ( matrix.col( j ).tail( tailSize ).maxCoeff() ) ;
-#if DEBUG_MODIFIED_CHOLESKY
-				std::cerr << "ModifiedCholesky::compute_inplace(): after computing cs, matrix =\n"
-					<< matrix << ",\n"
-					<< "theta = " << theta << ".\n" ;
-#endif
-
-				// compute d_jj to produce
-				// 1: d
-				// .  l d
-				// .  l l d
-				// j: l l l d
-				// .  c c c c c
-				// .  c c c c a c
-				double new_dj = std::max( delta, std::abs( matrix(j,j) ) ) ;
-				new_dj = std::max( new_dj, (theta*theta) / betaSquared ) ;
-				matrix(j,j) = new_dj ;
-				//
-				// Finally update the c_ii's
-				matrix.diagonal().tail( tailSize ).array() -= ( matrix.col(j).tail( tailSize ).array().square() ) / matrix(j,j) ;
-				
-#if DEBUG_MODIFIED_CHOLESKY
-				std::cerr << "ModifiedCholesky::compute_inplace(): after iteration " << j << ", matrix is:\n"
-					<< matrix << ".\n" ;
-#endif
-			}
-		}
-	} ;
-}
-
-#endif

DELETED integration/include/integration/ModifiedNewtonRaphson.hpp
Index: integration/include/integration/ModifiedNewtonRaphson.hpp
==================================================================
--- integration/include/integration/ModifiedNewtonRaphson.hpp
+++ integration/include/integration/ModifiedNewtonRaphson.hpp
@@ -1,161 +0,0 @@
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#ifndef CORE_MODIFIED_NEWTON_RAPHSON_HPP
-#define CORE_MODIFIED_NEWTON_RAPHSON_HPP
-
-#include <limits>
-#include <iostream>
-#include <iomanip>
-#include "integration/Error.hpp"
-
-//#define DEBUG_NEWTON_RAPHSON 1
-
-namespace integration {
-	namespace {
-		template< typename Function, typename DirectionPicker, typename StoppingCondition >
-		struct Stepper: public boost::noncopyable {
-			Stepper(
-				DirectionPicker& direction_picker,
-				StoppingCondition& stopping_condition
-			):
-				 m_direction_picker( direction_picker ),
-				 m_stopping_condition( stopping_condition )
-			{
-			}
-
-			bool step( Function& function, typename Function::Vector const& point, typename Function::Vector* result ) {
-				*result = m_direction_picker.compute( function, point ) ;
-				return !m_stopping_condition( function, *result ) ;
-			}
-
-		private:
-			DirectionPicker& m_direction_picker ;
-			StoppingCondition& m_stopping_condition ;
-		} ;
-		
-		template< typename Vector >
-		double oneNorm( Vector const& v ) {
-			return v.array().abs().maxCoeff() ;
-		}
-	}
-	//
-	// The following function represents a generic version of the multidimensional modified Newton-Raphson
-	// algorithm which finds a local maximum of the given function.
-	// It takes an 'function' object which evaluates the function and its first and second derivatives.
-	// A 'direction_picker' object is used to pick an ascent direction at each step.
-	// If an ascent direction (=directional derivative positive) is picked, the algorithm
-	// performs a backward line search to find a step that actually increases the function value.
-	// If a non-ascent direction is picked, the algorithm steps along it unconditionally without line search.
-	// The iteration stops when the stopping condition indicates that the algorithm should stop.
-	//
-	template< typename Function, typename DirectionPicker, typename StoppingCondition >
-	typename Function::Vector find_maximum_by_modified_newton_raphson_with_line_search(
-		Function& function,
-		typename Function::Vector currentPoint,
-		DirectionPicker& direction_picker,
-		StoppingCondition& stopping_condition,
-		double const line_search_tolerance = 0.1
-	)
-	{
-		typedef typename Function::Vector Vector ;
-		typedef typename Function::Matrix Matrix ;
-		
-		Vector first_derivative ;
-		Vector h ;
-		Stepper< Function, DirectionPicker, StoppingCondition > stepper( direction_picker, stopping_condition ) ;
-		for(
-			function.evaluate_at( currentPoint, 1 ) ;
-			stepper.step( function, currentPoint, &h ) ;
-			function.evaluate_at( currentPoint, 1 )
-		) {
-			double const current_function_value = function.get_value_of_function() ;
-			first_derivative = function.get_value_of_first_derivative() ;
-			double directional_derivative = first_derivative.transpose() * h ;
-
-#if DEBUG_NEWTON_RAPHSON
-			std::cerr << "MNR: --------------------------\n" ;
-			std::cerr << "MNR: point is                 : " << currentPoint.transpose() << ".\n" ;
-			std::cerr << "MNR: first derivative is      : " << first_derivative.transpose() << " with 1-norm " << oneNorm( first_derivative ) << ".\n" ;
-			std::cerr << "MNR: line search direction is : " << h.transpose() << ".\n" ;
-			std::cerr << "MNR: current function value is: " << std::setprecision(25) << current_function_value << ".\n" ;
-			std::cerr << "MNR: directional derivative is: " << directional_derivative << ".\n" ;
-			std::cerr << "MNR: machine epsilon is: " << std::numeric_limits< double >::epsilon() << ".\n" ;
-			std::cerr << "MNR: starting line search...\n" ;
-#endif
-
-			double lambda = 1 ;
-			if( directional_derivative > ( 10 * std::numeric_limits< double >::epsilon() ) ) {
-				// Directional derivative is greater than zero by a reasonable amount.
-				// We can hope to improve the function value.
-				//
-				// We conduct a line search starting, trying x + lh with l = 1.
-				// We stop the search when
-				//   f(x+lh) > c * l Df_x(h)
-				// where c is the line search tolerance.
-				//
-				for(
-					function.evaluate_at( currentPoint + lambda * h, 0 ) ;
-					( function.get_value_of_function() - current_function_value ) < ( line_search_tolerance * lambda * directional_derivative ) ;
-					function.evaluate_at( currentPoint + lambda * h, 0 )
-				) {
-	#if DEBUG_NEWTON_RAPHSON
-				std::cerr << "MNR: tried line search with lambda=" << lambda << ": function = " << std::setprecision(25) << function.get_value_of_function() << ".\n" ;
-	#endif
-					lambda = lambda * 0.9 ;
-					if( lambda < std::numeric_limits< double >::epsilon() ) {
-						throw NumericalError(
-							"integration::find_maximum_by_modified_newton_raphson_with_line_search()",
-							"Line search failed."
-						) ;
-					}
-				}
-			} else {
-				// Directional derivative is close to machine epsilon.
-				// We can't reasonably expect to improve the function if the directional derivative
-				// is so small. Instead we aim to not make it worse, and to make the derivative smaller.
-				double const derivativeOneNorm = oneNorm( first_derivative ) ;
-				for(
-					function.evaluate_at( currentPoint + lambda * h, 1 ) ;
-					(( function.get_value_of_function() - current_function_value ) < 0 )
-					|| ( oneNorm( function.get_value_of_first_derivative() ) > derivativeOneNorm ) ;
-					function.evaluate_at( currentPoint + lambda * h, 0 )
-				) {
-	#if DEBUG_NEWTON_RAPHSON
-				std::cerr << "MNR: tried line search with lambda=" << lambda
-					<< ": function = " << std::setprecision(25) << function.get_value_of_function()
-					<< ": derivative = " << function.get_value_of_first_derivative().transpose()
-					<< ": 1-norm = " << oneNorm( function.get_value_of_first_derivative() )
-					<< ".\n" ;
-	#endif
-					lambda = lambda * 0.5 ;
-					if( lambda < std::numeric_limits< double >::epsilon() ) {
-						throw NumericalError(
-							"integration::find_maximum_by_modified_newton_raphson_with_line_search()",
-							"Line search failed."
-						) ;
-					}
-				}
-			}
-#if DEBUG_NEWTON_RAPHSON
-		std::cerr << "MNR: line search complete with lambda = "
-				<< lambda
-				<< " and function value "
-				<< function.get_value_of_function()
-				<< ", improvement = "
-				<< ( function.get_value_of_function() - current_function_value )
-				<< ".\n" ;
-#endif
-			
-			currentPoint += lambda * h ;
-		}
-#if DEBUG_NEWTON_RAPHSON
-		std::cerr << "MNR: point = " << currentPoint << ", function = " << function.get_value_of_function() << ", first derivative = " << function.get_value_of_first_derivative() << ".\n" ;
-#endif
-		return currentPoint ;
-	}
-}
-
-#endif

DELETED integration/test/test_modified_cholesky.cpp
Index: integration/test/test_modified_cholesky.cpp
==================================================================
--- integration/test/test_modified_cholesky.cpp
+++ integration/test/test_modified_cholesky.cpp
@@ -1,82 +0,0 @@
-
-//          Copyright Gavin Band 2008 - 2012.
-// Distributed under the Boost Software License, Version 1.0.
-//    (See accompanying file LICENSE_1_0.txt or copy at
-//          http://www.boost.org/LICENSE_1_0.txt)
-
-#include <iostream>
-#include <boost/bind.hpp>
-#include <boost/noncopyable.hpp>
-#include "test_case.hpp"
-#include <Eigen/Core>
-#include <Eigen/Cholesky>
-#include "integration/ModifiedCholesky.hpp"
-
-AUTO_TEST_CASE( test_modified_cholesky_positive_definite ) {
-	typedef Eigen::VectorXd Vector ;
-	typedef Eigen::MatrixXd Matrix ;
-    integration::ModifiedCholesky< Matrix > comp ;
-	Eigen::LDLT< Matrix > ldlt ;
-	Matrix const identity = Matrix::Identity( 2, 2 ) ;
-
-	
-	{
-		Matrix const identity = Matrix::Identity( 1, 1 ) ;
-		Matrix test( 1, 1 ) ;
-		test << 1 ;
-		comp.compute( test ) ;
-		ldlt.compute( test ) ;
-		BOOST_CHECK_EQUAL( comp.matrixP() * identity, ldlt.transpositionsP() * identity ) ;
-		BOOST_CHECK_EQUAL( comp.vectorD(), ldlt.vectorD() ) ;
-		BOOST_CHECK_EQUAL( comp.matrixL() * identity, ldlt.matrixL() * identity ) ;
-		BOOST_CHECK_EQUAL( comp.solve( identity ) * test, identity ) ;
-	}
-
-	{
-		Matrix test( 2, 2 ) ;
-		test << 1, 0, 0, 1 ;
-		comp.compute( test ) ;
-		ldlt.compute( test ) ;
-		BOOST_CHECK_EQUAL( comp.matrixP() * identity, ldlt.transpositionsP() * identity ) ;
-		BOOST_CHECK_EQUAL( comp.vectorD(), ldlt.vectorD() ) ;
-		BOOST_CHECK_EQUAL( comp.matrixL() * identity, ldlt.matrixL() * identity ) ;
-		BOOST_CHECK_EQUAL( comp.solve( identity ) * test, identity ) ;
-	}
-
-	{
-		// This is a non-positive definite matrix
-		Matrix test( 2, 2 ) ;
-		test << 1, 0.5, 0.5, 1 ;
-		comp.compute( test ) ;
-		ldlt.compute( test ) ;
-		BOOST_CHECK_EQUAL( comp.matrixP() * identity, ldlt.transpositionsP() * identity ) ;
-		BOOST_CHECK_EQUAL( comp.vectorD(), ldlt.vectorD() ) ;
-		BOOST_CHECK_EQUAL( comp.matrixL() * identity, ldlt.matrixL() * identity ) ;
-		BOOST_CHECK_EQUAL( comp.solve( identity ) * test, identity ) ;
-	}
-}
-
-AUTO_TEST_CASE( test_modified_cholesky_nonpositive_definite ) {
-	typedef Eigen::VectorXd Vector ;
-	typedef Eigen::MatrixXd Matrix ;
-    integration::ModifiedCholesky< Matrix > comp ;
-
-	Matrix const identity = Matrix::Identity( 2, 2 ) ;
-
-	{
-		// This is a non-positive definite matrix
-		Matrix test( 2, 2 ) ;
-		test << 1, 2, 2, 1 ;
-		comp.compute( test ) ;
-		BOOST_CHECK_EQUAL( comp.matrixP() * identity, identity ) ;
-		// Diagonal should be at least as large as that of LDLT.
-		for( int j = 0; j < 2; ++j ) {
-			TEST_ASSERT( comp.vectorD()(j) >= std::numeric_limits< double >::epsilon() ) ;
-		}
-
-		std::cerr << "test_modified_cholesky_nonpositive_definite(): reconstructed matrix is:\n"
-			<< comp.solve( identity ).inverse() << ".\n" ;
-	}	
-}
-
-

Index: integration/wscript
==================================================================
--- integration/wscript
+++ integration/wscript
@@ -8,11 +8,11 @@
 def create_test( bld, name ):
 	bld(
 		features = 'cxx cprogram',
 		target = name,
 		source = [  'test/' + name + '.cpp' ],
-		uselib_local = 'integration boost-unit_test_framework',
+		uselib_local = 'integration boost_unit_test_framework',
 		uselib = 'BOOST_UNIT_TEST_FRAMEWORK',
 		includes='./include',
 		unit_test=1,
 		install_path = None
 	)
@@ -35,16 +35,14 @@
 	# libs
 	#---------------------
 	bld(
 		features = 'cxx cstaticlib',
 		target = 'integration',
-		source = bld.glob( 'src/*.cpp' ),
+		source = bld.path.ant_glob 'src/*.cpp' ),
 		includes='./include',
 		uselib_local='fputils eigen boost',
 		uselib = 'BOOST',
-		export_incdirs = './include'
+		export_includes = './include'
 	)
 	
 	create_test( bld, 'test_integrators' )
 	create_test( bld, 'test_newton_raphson' )
-	create_test( bld, 'test_modified_newton_raphson' )
-	create_test( bld, 'test_modified_cholesky' )

ADDED   metro/include/metro/CholeskyStepper.hpp
Index: metro/include/metro/CholeskyStepper.hpp
==================================================================
--- metro/include/metro/CholeskyStepper.hpp
+++ metro/include/metro/CholeskyStepper.hpp
@@ -0,0 +1,42 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_CHOLESKY_STEPPER_HPP
+#define METRO_CHOLESKY_STEPPER_HPP
+
+#include <string>
+#include <vector>
+#include <Eigen/Core>
+#include <Eigen/Cholesky>
+#include "boost/function.hpp"
+#include "metro/ModifiedCholesky.hpp"
+#include "metro/SmoothFunction.hpp"
+#include "metro/fit_model.hpp"
+
+namespace metro {
+	struct CholeskyStepper: public Stepper {
+	public:
+		CholeskyStepper( double tolerance, int max_iterations, Tracer tracer = Tracer()) ;
+
+		bool step( Function& function, Vector* result ) ;
+
+		bool diverged() const ;
+		std::size_t number_of_iterations() const ;
+		void reset() ;
+
+	private:
+		double const m_tolerance ;
+		int const m_max_iterations ;
+		Tracer m_tracer ;
+		int m_iteration ;
+		metro::ModifiedCholesky< Matrix > m_solver ;
+		//Eigen::LDLT< Matrix > m_solver ;
+		//Eigen::ColPivHouseholderQR< Matrix > m_solver ;
+		double m_target_ll ;
+	} ;
+}
+
+#endif

ADDED   metro/include/metro/Error.hpp
Index: metro/include/metro/Error.hpp
==================================================================
--- metro/include/metro/Error.hpp
+++ metro/include/metro/Error.hpp
@@ -0,0 +1,68 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_ERROR_HPP
+#define SNPTEST_ERROR_HPP
+
+#include <exception>
+#include <string>
+
+namespace metro {
+	struct LimitExceededError: public std::exception {
+	public:
+		LimitExceededError( std::string const& source, std::string const& limit, std::string const& reason ):
+			m_source( source ),
+			m_limit( limit ),
+			m_reason( reason )
+		{}
+		~LimitExceededError() throw() {}
+		char const* what() const throw() { return "core::LimitExceededError" ; }
+		std::string const& source() const { return m_source ; }
+		std::string const& limit_description() const { return m_limit ; }
+		std::string const& reason() const { return m_reason ; }
+	private:
+		std::string const m_source ;
+		std::string const m_limit ;
+		std::string const m_reason ;
+	} ;
+
+	struct ModelFitError: public std::exception {
+		ModelFitError( std::string const& caller, std::string const& reason ) ;
+		~ModelFitError() throw() ;
+
+		char const* what() const throw() ;
+		std::string const& get_caller() const ;
+		std::string const& get_reason() const ;
+	private:
+		std::string const m_caller ;
+		std::string const m_reason ;
+	} ;
+	
+	struct NumericalError: public std::exception 
+	{
+		virtual ~NumericalError() throw() {}
+
+		NumericalError( std::string const& source, std::string const& message = "" ):
+			m_source( source ),
+			m_message( message )
+		{}
+		
+		NumericalError( NumericalError const& other ):
+			m_source( other.m_source ),
+			m_message( other.m_message )
+		{}
+
+		const char* what() const throw() { return "integration:NumericalError" ; }
+		virtual std::string format_message() const ;
+		std::string const& source() const { return m_source ; }
+		std::string const& message() const { return m_message ; }
+	private:
+		std::string const m_source ;
+		std::string const m_message ;
+	} ;
+}
+
+#endif

ADDED   metro/include/metro/IndependentParameterDistribution.hpp
Index: metro/include/metro/IndependentParameterDistribution.hpp
==================================================================
--- metro/include/metro/IndependentParameterDistribution.hpp
+++ metro/include/metro/IndependentParameterDistribution.hpp
@@ -0,0 +1,58 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_REGRESSION_INDEPENDENT_INDEPENDENTPARAMETERDISTRIBUTION_HPP
+#define SNPTEST_REGRESSION_INDEPENDENT_INDEPENDENTPARAMETERDISTRIBUTION_HPP
+
+#include <memory>
+#include <unordered_map>
+#include <Eigen/Core>
+#include <boost/ptr_container/ptr_vector.hpp>
+#include <boost/ptr_container/ptr_map.hpp>
+#include "metro/UnivariateLogDensity.hpp"
+#include "metro/SmoothFunction.hpp"
+
+namespace metro {
+	struct IndependentParameterDistribution: public SmoothFunction {
+	public:
+		typedef std::auto_ptr< IndependentParameterDistribution > UniquePtr ;
+		typedef Eigen::VectorXd Point ;
+		typedef Eigen::VectorXd Vector ;
+		typedef Eigen::MatrixXd Matrix ;
+		typedef Eigen::Matrix< int, Eigen::Dynamic, Eigen::Dynamic > IntegerMatrix ;
+
+		static UniquePtr create( std::vector< std::string > const& parameter_names ) ;
+
+	public:
+		IndependentParameterDistribution( std::vector< std::string > const& parameter_names ) ;
+
+		void set_prior( std::string const& name, UnivariateLogDensity::UniquePtr pdf ) ;
+		int number_of_parameters() const ;
+		Vector const& parameters() const { return m_parameters ; }
+
+		void evaluate_at(
+			Point const& parameters,
+			int const numberOfDerivatives = 2
+		) ;
+		void evaluate( int const numberOfDerivatives = 2 ) ;
+		double get_value_of_function() const ;
+		Vector get_value_of_first_derivative() const ;
+		Matrix get_value_of_second_derivative() const ;
+		
+		std::string get_summary() const ;
+		
+	private:
+		std::size_t m_number_of_parameters ;
+		std::vector< std::string > const m_parameter_names ;
+		typedef std::map< std::string, std::size_t > ParameterNameIndices ;
+		ParameterNameIndices m_parameter_name_indices ;
+		Vector m_parameters ;
+		boost::ptr_vector< UnivariateLogDensity > m_densities ;
+	} ;
+}
+
+#endif
+

Index: metro/include/metro/LogLikelihood.hpp
==================================================================
--- metro/include/metro/LogLikelihood.hpp
+++ metro/include/metro/LogLikelihood.hpp
@@ -16,18 +16,19 @@
 	template< typename Scalar, typename Vector, typename Matrix >
 	struct LogLikelihood: public boost::noncopyable {
 		typedef std::auto_ptr< LogLikelihood > UniquePtr ;
 		virtual ~LogLikelihood() {}
 
-		virtual void evaluate_at( Vector const& parameters, DataSubset const& subset ) = 0 ;
+		virtual void evaluate_at( Vector const& parameters, DataSubset const& subset, int numberOfDerivatives = 2 ) = 0 ;
+		virtual void evaluate( int numberOfDerivatives = 2 ) = 0 ;
 		
 		virtual Scalar get_value_of_function() const = 0 ;
 		virtual Vector get_value_of_first_derivative() const = 0 ;
 		virtual Matrix get_value_of_second_derivative() const = 0 ;
 		
 		virtual Vector parameters() const = 0 ;
 
-		virtual std::string get_spec() const = 0 ;
+		virtual std::string get_summary() const = 0 ;
 	} ;
 }
 
 #endif

ADDED   metro/include/metro/ModifiedCholesky.hpp
Index: metro/include/metro/ModifiedCholesky.hpp
==================================================================
--- metro/include/metro/ModifiedCholesky.hpp
+++ metro/include/metro/ModifiedCholesky.hpp
@@ -0,0 +1,302 @@
+//			Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//	  (See accompanying file LICENSE_1_0.txt or copy at
+//			http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef INTEGRATION_MODIFIED_CHOLESKY_HPP
+#define INTEGRATION_MODIFIED_CHOLESKY_HPP
+
+#include <iostream>
+#include <boost/noncopyable.hpp>
+#include <Eigen/Core>
+#include <Eigen/Cholesky>
+#include <Eigen/Eigenvalues>
+
+// #define DEBUG_MODIFIED_CHOLESKY 1
+
+namespace metro {
+	// Utility functions
+	namespace {
+		template< typename Real >
+		Real max( Real const a, Real const b ) {
+			return std::max( a, b ) ;
+		}
+
+		template< typename Real >
+		Real max( Real const a, Real const b, Real const c ) {
+			return std::max( a, std::max( b, c )) ;
+		}
+	}
+
+	//
+	// Implements the 'MC' algorithm from Gill & Murray, Practical Optimisation.
+	// Also expressed as Algorithm 6.5, "Modified Cholesky algorithm" in
+	// Nocedal & Wright, "Numerical Optimisation".
+	// See also Fang & Leary 2006
+	//
+	// I have borrowed a little bit from Eigen's LDLT.h here to get the permutations and types right.
+	//
+	// This algorithm only touches the lower-diagonal of the matrix.
+	// As described in the above references, we use the lower-diagonal of the matrix
+	// to store the non-unity entries of L, and the diagonal to store the entries of D.
+	// The auxiliary variables c_ij are stored in the lower diagonal too until they
+	// are overwritten by entries of L and D.
+	//
+	// At step j the matrix looks like:
+	//
+	//	  0 . . j . .
+	// 0  d
+	// .  l d
+	// .  l l d
+	// j  c c c c
+	// .  c c c a c
+	// .  c c c a a c
+	//
+	// Where a refers to an entry of the original matrix (after the possible permutations) and l refers to an entry of
+	// the computed matrix L, d refers to an entry of D, and c to one of the auxiliary c_ijs.
+	//
+	// At the jth step we update this to become
+	// 1: d
+	// .  l d
+	// .  l l d
+	// j: l l l d
+	// .  c c c c c
+	// .  c c c c a c
+	//
+	// i.e. we compute the jth row of L, the jth entry of D, and the c's in
+	// the jth column and on the diagonal below j.
+	template< typename Matrix >
+	struct ModifiedCholesky {
+	public:
+		enum {
+		  RowsAtCompileTime = Matrix::RowsAtCompileTime,
+		  ColsAtCompileTime = Matrix::ColsAtCompileTime,
+		  Options = Matrix::Options & ~Eigen::RowMajorBit, // these are the options for the TmpMatrixType, we need a ColMajor matrix here!
+		  MaxRowsAtCompileTime = Matrix::MaxRowsAtCompileTime,
+		  MaxColsAtCompileTime = Matrix::MaxColsAtCompileTime,
+		  UpLo = Eigen::Lower
+		} ;
+		typedef typename Matrix::Scalar Scalar;
+		typedef typename Eigen::NumTraits<typename Matrix::Scalar>::Real RealScalar;
+		typedef typename Matrix::Index Index;
+
+		typedef Eigen::Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> Transpositions;
+		typedef Eigen::PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> Permutations;
+		typedef Eigen::TriangularView< Matrix const, Eigen::UnitLower > const MatrixL ;
+		typedef Eigen::Diagonal< Matrix const > Diagonal ;
+
+	public:
+		ModifiedCholesky() {}
+
+		ModifiedCholesky( ModifiedCholesky const& other ):
+			m_matrix( other.m_matrix ),
+			m_transpositions( other.m_transpositions )
+		{}
+
+		ModifiedCholesky& operator=( ModifiedCholesky const& other ) {
+			m_matrix = other.m_matrix ;
+			m_transpositions = other.m_transpositions ;
+			return *this ;
+		}
+		
+		ModifiedCholesky& compute( Matrix const& matrix ) {
+			m_matrix = matrix ;
+			compute_inplace( m_matrix ) ;
+			return *this ;
+		}
+		
+		MatrixL matrixL() const {
+			return m_matrix.template triangularView< Eigen::UnitLower >() ;
+		}
+		
+		Diagonal vectorD() const {
+			return m_matrix.diagonal();
+		}
+
+		Permutations const matrixP() const {
+			return Permutations( m_transpositions ) ;
+		}
+		
+		Matrix solve( Matrix const& rhs ) const
+		{
+			Matrix result = rhs ;
+			assert( result.rows() == m_matrix.rows() ) ;
+			// result = P rhs
+			result = m_transpositions * result ;
+			// result = L^-1 (P rhs)
+			matrixL().solveInPlace( result );
+			// result = D^-1 (L^-1 P rhs)
+			for( Index i = 0; i < m_matrix.rows(); ++i ) {
+				result.row(i) /= m_matrix(i,i) ;
+			}
+			// result = L^-T (D^-1 L^-1 P rhs)
+			matrixL().transpose().solveInPlace( result ) ;
+			// result = P^-1 L^-T (D^-1 L^-1 P rhs)
+			result = m_transpositions.transpose() * result ;
+			return result ;
+		}
+		
+		// "Half" solve the rhs
+		// solve the rhs, i.e compute
+		// S^-1 (rhs)
+		// Where S is the 'square root' of the matrix, given by
+		// S = P^-1 L sqrt(D)
+		// such that
+		// S S^t = P^-1 
+		Matrix halfSolve( Matrix const& rhs ) const
+		{
+			Matrix result = rhs ;
+			assert( result.rows() == m_matrix.rows() ) ;
+			// result = P rhs
+			result = m_transpositions * result ;
+			// result = L^-1 P rhs
+			matrixL().solveInPlace( result );
+			// result = sqrt(D^-1) L^-1 P rhs
+			for( Index i = 0; i < m_matrix.rows(); ++i ) {
+				result.row(i) /= std::sqrt( m_matrix(i,i) ) ;
+			}
+			return result ;
+		}
+
+	private:
+		Matrix m_matrix ;
+		Transpositions m_transpositions;
+		
+	private:
+		
+		void compute_inplace( Matrix& matrix ) {
+			assert( matrix.rows() == matrix.cols() ) ;
+			m_transpositions.resize( matrix.rows() ) ;
+			Index const size = matrix.rows() ;
+			
+#if DEBUG_MODIFIED_CHOLESKY
+			std::cerr << "ModifiedCholesky::compute_inplace(): computing with matrix:\n" << matrix << ".\n" ;
+#endif
+			
+			Scalar biggestOnDiagonal ;
+			RealScalar betaSquared ;
+			RealScalar delta ;
+
+			for( Index j = 0; j < size; ++j ) {
+				// Find largest diagonal element
+				Index indexOfBiggestOnDiagonal ;
+				biggestOnDiagonal = matrix.diagonal().tail( size - j ).cwiseAbs().maxCoeff( &indexOfBiggestOnDiagonal ) ;
+				indexOfBiggestOnDiagonal += j ;
+
+				// Initialise beta and delta if we are starting.
+				if( j == 0 ) {
+					Scalar biggestOffDiagonal = 0.0 ;
+					for( Index i = 0; i < size; ++i ) {
+						for( Index j = i+1; j < size; ++j ) {
+							biggestOffDiagonal = std::max( biggestOffDiagonal, std::abs( matrix( i, j )) ) ;
+						}
+					}
+					// Had this before:
+					//delta = std::numeric_limits< Scalar >::epsilon() * max( biggestOnDiagonal + biggestOffDiagonal, Scalar( 1 ) ) ;
+					// ..but most authors e.g. (Fang & Leary 2006) say:
+					delta = std::numeric_limits< Scalar >::epsilon() ;
+					// Fang & Leary (2006), formula (5).
+					betaSquared = max(
+						std::numeric_limits< Scalar >::epsilon(),
+						biggestOnDiagonal,
+						biggestOffDiagonal / std::sqrt( ( size * size ) - 1 )
+					) ;
+					
+#if DEBUG_MODIFIED_CHOLESKY
+					std::cerr << "ModifiedCholesky::compute_inplace(): initialised with delta = "
+						<< delta << ", beta^2 = " << betaSquared << ".\n" ;
+#endif
+				
+					// Modified cholesky of A is cholesky of A+E for some diagonal matrix E
+					// Bound on elements of E can be computed as in Fang & Leary (2006)
+					//bound = (
+					//	std::pow((biggestOffDiagonal/std::sqrt(betaSquared)) + (size-1)*std::sqrt(betaSquared), 2 )
+					//	+ 2 * ( biggestOnDiagonal + (size-1)*betaSquared )
+					//	+ std::numeric_limits< Scalar >::epsilon()
+					//) ;
+				}
+				
+#if DEBUG_MODIFIED_CHOLESKY
+				std::cerr << "ModifiedCholesky::compute_inplace(): at iteration "
+					<< j
+						<< ": largest entry on diagonal = " << biggestOnDiagonal
+					<< " at index " << indexOfBiggestOnDiagonal << ".\n" ;
+#endif
+											
+				// Swap rows and columns corresponding to the jth and largest diagonal element.
+				m_transpositions.coeffRef( j ) = indexOfBiggestOnDiagonal ;
+				if( j != indexOfBiggestOnDiagonal ) {
+					// indexOfbiggestOnDiagonal is always >= j by construction
+					// we only touch the lower triangular part of the matrix.
+					Index const tailSize = size - indexOfBiggestOnDiagonal - 1 ;
+					matrix.row( j ).head( j ).swap( matrix.row( indexOfBiggestOnDiagonal ).head( j ) ) ;
+					matrix.col( j ).tail( tailSize ).swap( matrix.col( indexOfBiggestOnDiagonal ).tail( tailSize ) ) ;
+					std::swap( matrix.coeffRef(j,j), matrix.coeffRef( indexOfBiggestOnDiagonal, indexOfBiggestOnDiagonal ) );
+					for( int i = j+1; i < indexOfBiggestOnDiagonal; ++i ) {
+						std::swap( matrix.coeffRef( i, j ), matrix.coeffRef( indexOfBiggestOnDiagonal, i ) ) ;
+					}
+				}
+				
+				Index const tailSize = size - j - 1 ;
+				// We first compute the jth row of L to produce:
+				// 1: d
+				// .  l d
+				// .  l l d
+				// j: l l l c
+				// .  c c c a c
+				// .  c c c a a c
+				//
+				// by formula: l_js = c_js / d_s for s = 0,...,j-1.
+				if( j > 0 ) {
+					matrix.row(j).head( j ).array() /= matrix.diagonal().head( j ).array() ;
+				}
+#if DEBUG_MODIFIED_CHOLESKY
+				std::cerr << "ModifiedCholesky::compute_inplace(): after computing ls, matrix =\n"
+					<< matrix << ".\n" ;
+#endif
+				// We next compute jth column of c_ijs to get:
+				// 1: d
+				// .  l d
+				// .  l l d
+				// j: l l l c
+				// .  c c c c c
+				// .  c c c c a c
+				//
+				// by formula c_ij = a_ij - sum_s l_ks c_is for s=j+1...n
+				for( Index i = j+1; i < size; ++i ) {
+					matrix(i,j) -= ( matrix.row( j ).head( j ) * matrix.row( i ).head( j ).transpose() ) ;
+				}
+				Scalar const theta = ( (j+1) == size ) ? 0.0 : ( matrix.col( j ).tail( tailSize ).maxCoeff() ) ;
+#if DEBUG_MODIFIED_CHOLESKY
+				std::cerr << "ModifiedCholesky::compute_inplace(): after computing cs, matrix =\n"
+					<< matrix << ",\n"
+					<< "theta = " << theta << ".\n" ;
+#endif
+
+				// compute d_jj to produce
+				// 1: d
+				// .  l d
+				// .  l l d
+				// j: l l l d
+				// .  c c c c c
+				// .  c c c c a c
+				double new_dj = max(
+					delta,
+					std::abs( matrix(j,j) ),
+					(theta*theta) / betaSquared
+				) ;
+				matrix(j,j) = new_dj ;
+				//
+				// Finally update the c_ii's
+				matrix.diagonal().tail( tailSize ).array() -= ( matrix.col(j).tail( tailSize ).array().square() ) / matrix(j,j) ;
+				
+#if DEBUG_MODIFIED_CHOLESKY
+				std::cerr << "ModifiedCholesky::compute_inplace(): after iteration " << j << ", matrix is:\n"
+					<< matrix << ".\n" ;
+#endif
+			}
+		}
+	} ;
+}
+
+#endif

ADDED   metro/include/metro/ModifiedNewtonRaphson.hpp
Index: metro/include/metro/ModifiedNewtonRaphson.hpp
==================================================================
--- metro/include/metro/ModifiedNewtonRaphson.hpp
+++ metro/include/metro/ModifiedNewtonRaphson.hpp
@@ -0,0 +1,140 @@
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_MODIFIED_NEWTON_RAPHSON_HPP
+#define METRO_MODIFIED_NEWTON_RAPHSON_HPP
+
+#include <limits>
+#include <iostream>
+#include <iomanip>
+#include "Error.hpp"
+
+// #define DEBUG_NEWTON_RAPHSON 1
+
+namespace metro {
+	namespace {
+		// compute the one-norm
+		template< typename Vector >
+		double oneNorm( Vector const& v ) {
+			return v.array().abs().maxCoeff() ;
+		}
+	}
+
+	//
+	// The following function implements the
+	// multidimensional modified Newton-Raphson algorithm.
+	// It finds a local maximum of the given function.
+	// It takes a 'function' object which evaluates the function and its
+	// first and second derivatives.
+
+	// A 'stepper' object is used to tell the algorithm whether to take another
+	// step, and if so in which direction.	This should be callable as
+	//	`stepper.step( function, current_point, &search_direction )`
+	// A false return value indicates the algorithm should stop.	Otherwise, the
+	// function should population the search direction and return true.
+	
+	// If an ascent direction (=directional derivative positive) is picked, the
+	// algorithm performs a backward line search to find a step that actually
+	// increases the function value.
+	// If with nonpositive directional derivative is picked then the algorithm
+	// gamely tries to improve the function or derivative anyway, but will bail
+	// out and return the current value
+	// if it cannot make any improvement.
+	//
+	template< typename Function, typename Stepper >
+	typename Function::Vector find_maximum_by_modified_newton_raphson_with_line_search(
+		Function& function,
+		typename Function::Vector const& startingPoint,
+		Stepper& stepper,
+		double const line_search_tolerance = 0.1
+	)
+	{
+		typedef typename Function::Vector Vector ;
+		typedef typename Function::Matrix Matrix ;
+		double const epsilon = std::numeric_limits< double >::epsilon() ;
+		
+		Vector first_derivative ;
+		Vector h ;
+		for(
+			function.evaluate_at( startingPoint, 1 ) ;
+			stepper.step( function, &h ) ;
+			function.evaluate( 1 )
+		) {
+			double const current_function_value = function.get_value_of_function() ;
+			first_derivative = function.get_value_of_first_derivative() ;
+			double directional_derivative = first_derivative.transpose() * h ;
+
+#if DEBUG_NEWTON_RAPHSON
+			std::cerr << "MNR: --------------------------\n" ;
+			std::cerr << "MNR: point is                 : " << function.parameters().transpose() << ".\n" ;
+			std::cerr << "MNR: first derivative is      : " << first_derivative.transpose() << " with 1-norm " << oneNorm( first_derivative ) << ".\n" ;
+			std::cerr << "MNR: line search direction is : " << h.transpose() << ".\n" ;
+			std::cerr << "MNR: current function value is: " << std::setprecision(25) << current_function_value << ".\n" ;
+			std::cerr << "MNR: current       || df || is: " << std::setprecision(25) << (first_derivative.array().abs().maxCoeff()) << ".\n" ;
+			std::cerr << "MNR: directional derivative is: " << directional_derivative << ".\n" ;
+			std::cerr << "MNR: epsilon is: " << epsilon << ".\n" ;
+			std::cerr << "MNR: starting line search...\n" ;
+#endif
+			// Conduct a line search, starting at x + lh with l = 1.
+			// We stop if either the Armijo condition is satisfied, i.e. stopping the search when
+			//   f(x+lh) > c * l Df_x(h)
+			// where c is the line search tolerance.
+			
+			// OR if the directional derivative is small, we stop if the 
+			// function does not decrease more than a small multiple of epsilon
+			// and the derivative decreases.
+			double lambda = 1 ;
+			// We reckon there's no point trying to use the armijo condition if the directional derivative is smaller than this scale
+			bool const useArmijo = (( directional_derivative / std::abs( current_function_value )) > 10 * epsilon ) ;
+			bool const useDerivative = !useArmijo ;
+			double const derivativeOneNorm = oneNorm( first_derivative ) ;
+			Vector const& currentPoint = function.parameters() ;
+			for(
+				function.evaluate_at( currentPoint + lambda * h, useDerivative ? 1 : 0 ) ;
+				!(
+					(
+						useArmijo
+						&& ( function.get_value_of_function() - current_function_value ) > ( line_search_tolerance * lambda * directional_derivative ))
+					|| 
+					(
+						useDerivative
+						&& (oneNorm( function.get_value_of_first_derivative() ) < derivativeOneNorm)
+						&& (( function.get_value_of_function() - current_function_value ) / std::abs( current_function_value )) > -(epsilon*1E6)
+					)
+				);
+				function.evaluate_at( currentPoint + lambda * h, useDerivative ? 1 : 0 )
+			) {
+#if DEBUG_NEWTON_RAPHSON
+			std::cerr << "MNR: tried line search (" << ( useArmijo ? "armijo" : "derivative" ) << ") with lambda=" << lambda
+				<< ":      f = " << std::setprecision(25) << function.get_value_of_function()
+				<< ";   diff = " << std::setprecision(25) << (function.get_value_of_function() - current_function_value) << "\n"
+				<< "; ||df|| = " << std::setprecision(25) << (function.get_value_of_first_derivative().array().abs().maxCoeff())
+				<< ".\n" ;
+#endif
+				lambda *= 0.875 ; // (1-1/8), exactly representable in float
+				if( (function.get_value_of_function() - current_function_value) == 0 || lambda < 0.05 ) {
+					lambda = 0 ;
+					break ;
+				}
+			}
+#if DEBUG_NEWTON_RAPHSON
+			std::cerr << "MNR: line search complete with lambda = "
+				<< lambda
+				<< " and function value "
+				<< function.get_value_of_function()
+				<< ", improvement = "
+				<< ( function.get_value_of_function() - current_function_value )
+				<< ".\n" ;
+#endif
+		}
+#if DEBUG_NEWTON_RAPHSON
+		std::cerr << "MNR: point = " << currentPoint.transpose() << ", function = " << function.get_value_of_function()
+			<< ",\nfirst derivative = " << function.get_value_of_first_derivative().transpose() << ".\n" ;
+#endif
+		return function.parameters() ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/NewtonRaphson.hpp
Index: metro/include/metro/NewtonRaphson.hpp
==================================================================
--- metro/include/metro/NewtonRaphson.hpp
+++ metro/include/metro/NewtonRaphson.hpp
@@ -0,0 +1,70 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef CORE_NEWTON_RAPHSON_HPP
+#define CORE_NEWTON_RAPHSON_HPP
+
+// #define DEBUG_NEWTON_RAPHSON 1
+
+namespace metro {
+	//
+	// The following function represents a generic version of the multidimensional Newton-Raphson
+	// algorithm.  It takes an "evaluator" object whose job is to evaluate the function
+	// and its derivative simultaneously.  This scheme is useful for functions (such as loglikelihoods)
+	// for which evaluation is computationally expensive and part of the computation can be shared
+	// between the function and the derivative.
+	//
+	// The StoppingCondition is a function or function object
+	// taking the evaluated point and function value as argument and returning true (stop iterating) or false (don't
+	// stop iterating).
+	//
+	// The MatrixSolver is an object which can solve linear equations (i.e. decompose matrices).
+	// This function is suitable for Eigen's solvers which support compute() and solve() methods.
+	// A sensible option is usually Eigen::LDLT since the second derivative will be nonnegative-definite.
+	//
+	template< typename FunctionAndDerivativeEvaluator, typename StoppingCondition, typename MatrixSolver >
+	typename FunctionAndDerivativeEvaluator::Vector find_root_by_newton_raphson(
+		FunctionAndDerivativeEvaluator& evaluator,
+		typename FunctionAndDerivativeEvaluator::Vector point,
+		StoppingCondition& stopping_condition,
+		MatrixSolver& solver
+	)
+	{
+		typedef typename FunctionAndDerivativeEvaluator::Vector Vector ;
+		typedef typename FunctionAndDerivativeEvaluator::Matrix Matrix ;
+		
+		evaluator.evaluate_at( point ) ;
+
+		Matrix derivative_value ;
+
+		Vector function_value = evaluator.get_value_of_function() ;
+#if DEBUG_NEWTON_RAPHSON
+		std::cerr << "NR: point = " << point << ", value = " << function_value << ".\n" ;
+#endif
+		while( !stopping_condition( point, function_value ) ) {
+			// The Newton-Raphson rule comes from the observation that if
+			// f( x + h ) = f( x ) + (D_x f) (h) + higher order terms
+			// and if f( x + h ) = 0
+			// then h must satisfy (D_x f) (h) = -f( x ) + higher order terms.
+			// At each step we solve this and move to the point x + h.
+			// If the function is linear, this will actually get us to the root.
+			derivative_value = evaluator.get_value_of_first_derivative() ;
+#if DEBUG_NEWTON_RAPHSON
+			std::cerr << "NR: derivative_value = " << derivative_value << "\n" ;
+#endif
+			solver.compute( derivative_value ) ;
+			point += solver.solve( -function_value ) ;
+			evaluator.evaluate_at( point ) ;
+#if DEBUG_NEWTON_RAPHSON
+			std::cerr << "NR: point = " << point << ", value = " << function_value << ".\n" ;
+#endif
+			function_value = evaluator.get_value_of_function() ;
+		}
+		return point ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/SampleRange.hpp
Index: metro/include/metro/SampleRange.hpp
==================================================================
--- metro/include/metro/SampleRange.hpp
+++ metro/include/metro/SampleRange.hpp
@@ -0,0 +1,36 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_CASE_CONTROL_SAMPLE_RANGE_HPP
+#define SNPTEST_CASE_CONTROL_SAMPLE_RANGE_HPP
+
+#include <iostream>
+#include <vector>
+
+namespace metro {
+	struct SampleRange {
+		SampleRange() ;
+		SampleRange( SampleRange const& other ) ;
+		SampleRange( int begin, int end ) ;
+		SampleRange& operator=( SampleRange const& other ) ;
+
+		int begin() const { return m_begin ; }
+		int end() const { return m_end ; }
+		int size() const { return m_end - m_begin ; }
+
+		private:
+			int m_begin ;
+			int m_end ;
+	} ;
+	
+	bool operator== ( SampleRange const& left, SampleRange const& right ) ;
+	bool operator< ( SampleRange const& left, SampleRange const& right ) ;
+	
+	std::ostream& operator<<( std::ostream& out, SampleRange const& range ) ;
+	std::ostream& operator<<( std::ostream& out, std::vector< SampleRange > const& range ) ;
+}
+
+#endif

ADDED   metro/include/metro/SampleStratification.hpp
Index: metro/include/metro/SampleStratification.hpp
==================================================================
--- metro/include/metro/SampleStratification.hpp
+++ metro/include/metro/SampleStratification.hpp
@@ -0,0 +1,41 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef CORE_SAMPLESTRATIFICATION_HPP
+#define CORE_SAMPLESTRATIFICATION_HPP
+
+#include <string>
+#include <vector>
+#include <iostream>
+#include <map>
+#include "metro/SampleRange.hpp"
+
+namespace metro {
+	struct SampleStratification {
+		SampleStratification() ;
+		SampleStratification( SampleStratification const& other ) ;
+		SampleStratification& operator=( SampleStratification const& other ) ;
+
+		void add_stratum( std::string const& name ) ;
+		void add_sample( std::string const& strata, int sample_index ) ;
+		void add_sample_range( std::string const& strata, metro::SampleRange const& range ) ;
+
+		std::size_t number_of_strata() const { return m_strata_names.size() ; }
+		std::size_t size() const { return m_strata_names.size() ; }
+		std::string const& stratum_name( std::size_t i ) const ;
+		std::vector< metro::SampleRange > const& stratum( std::size_t i ) const ;
+		std::vector< metro::SampleRange > const& stratum( std::string const& strata_name ) const ;
+
+	private:
+		std::vector< std::string > m_strata_names ;
+		std::map< std::string, std::size_t > m_index_by_strata ;
+		std::vector< std::vector< metro::SampleRange > > m_sample_ranges ;
+	} ;
+
+	std::ostream& operator<<( std::ostream& o, SampleStratification const& stratification ) ;
+}
+
+#endif

ADDED   metro/include/metro/ShotgunStochasticSearch.hpp
Index: metro/include/metro/ShotgunStochasticSearch.hpp
==================================================================
--- metro/include/metro/ShotgunStochasticSearch.hpp
+++ metro/include/metro/ShotgunStochasticSearch.hpp
@@ -0,0 +1,75 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_SHOTGUNSTOCHASTICSEARCH_HPP
+#define METRO_SHOTGUNSTOCHASTICSEARCH_HPP
+
+#include <vector>
+#include <unordered_map>
+#include <boost/function.hpp>
+#include <boost/functional/hash.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/discrete_distribution.hpp>
+
+namespace metro {
+	/*
+	* This class performs a FINEMAP-like 'shotgun stochastic search'.
+	* Given an integer N, starting with the empty state, this class searches by generating
+	* all possible changes to the current state by adding / changing / removing any of the
+	* N possible indicators.  It then computes a likelihood using the user-supplied
+	* likelihood function.  Finally, it updates the current state by moving to one of the new states
+	* uniformly weighted by the likelihood.
+	* See Benner et al, "FINEMAP: Efficient variable selection using summary data from genome-wide association studies",
+	* Bioinformatics (2016) for algorithm details.
+	* This class merely implements the 'search' aspect of this algorithm.  To make efficient use of it,
+	* the user must use a likelihood function that e.g. prohibits too-large numbers of predictor variables.
+	*/
+	struct ShotgunStochasticSearch {
+		typedef std::vector< std::size_t > SelectedStates ;
+		typedef boost::function< double ( SelectedStates const& ) > ComputeLL ;
+		struct StateHash {
+		public:
+			size_t operator()(const SelectedStates &p) const {
+				return boost::hash_value(p);
+			}
+		} ;
+
+		typedef std::unordered_map< SelectedStates, double, StateHash > Store ;
+
+		ShotgunStochasticSearch(
+			std::size_t n,
+			ComputeLL compute_ll,
+			std::uint32_t rng_seed
+		) ;
+
+		/* Compute the next search update with the given likelihood function */
+		SelectedStates const& update() ;
+
+		/* Return our store of states visited so far */ 
+		Store const& visited_states() const ;
+		void visited_states( boost::function< void( SelectedStates const&, double ) > callback ) const ;
+	
+	private:
+		std::size_t const m_N ;
+		ShotgunStochasticSearch::ComputeLL m_compute_ll ;
+		SelectedStates m_current_state ;
+		Store m_lls ;
+		boost::random::mt19937 m_rng;
+	
+	private:
+		/* Generate all states obtained by deleting a member
+		of the current state, and append to the given vector */
+		void generate_deletions( std::vector< SelectedStates >* result ) ;
+
+		/* Generate all states obtained by adding a member or changing a member
+		of the current state, and append to the given vector */
+		void generate_additions_and_changes( std::vector< SelectedStates >* result ) ;
+	} ;
+}
+
+#endif
+
+

ADDED   metro/include/metro/SmoothFunction.hpp
Index: metro/include/metro/SmoothFunction.hpp
==================================================================
--- metro/include/metro/SmoothFunction.hpp
+++ metro/include/metro/SmoothFunction.hpp
@@ -0,0 +1,52 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_LIKELIHOOD_SMOOTH_FUNCTION_HPP
+#define METRO_LIKELIHOOD_SMOOTH_FUNCTION_HPP
+
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include <Eigen/Core>
+#include "metro/DataSubset.hpp"
+
+namespace metro {
+	// This class represents a smooth function, i.e. a function that is
+	// twice differentiable.
+	// SmoothFunctions are intended to be stateful - they are properly thought
+	// of as a function evaluated at a specific point.  This design choice
+	// was made because it is typically the case that a large amount of computation can be
+	// shared between derivatives.
+	
+	// a great deal of comp
+	// The intentino 
+	// This choice means that the accessor functions, named "get_value[...]",
+	// are const and return references, while the 
+	struct SmoothFunction: public boost::noncopyable {
+	public:
+		typedef std::unique_ptr< SmoothFunction > UniquePtr ;
+		typedef double Scalar ;
+		typedef Eigen::VectorXd Vector ;
+		typedef Eigen::MatrixXd Matrix ;
+	public:
+		virtual ~SmoothFunction() {}
+		virtual int number_of_parameters() const = 0 ;
+		virtual Vector const& parameters() const = 0 ;
+
+		// Evaluate the function at a given parameter value
+		virtual void evaluate_at( Vector const& parameters, int const numberOfDerivatives = 2 ) = 0 ;
+		// Re-evaluate the function at a previously set parameter value, previously
+		// set by a call to evaluate_at().
+		// This allows to evaluate a specified number of derivatives.
+		virtual void evaluate( int const numberOfDerivatives = 2 ) = 0 ;
+		
+		virtual Scalar get_value_of_function() const = 0 ;
+		virtual Vector get_value_of_first_derivative() const = 0 ;
+		virtual Matrix get_value_of_second_derivative() const = 0 ;
+		virtual std::string get_summary() const = 0 ;
+	} ;
+}
+
+#endif

ADDED   metro/include/metro/Snptest25StoppingCondition.hpp
Index: metro/include/metro/Snptest25StoppingCondition.hpp
==================================================================
--- metro/include/metro/Snptest25StoppingCondition.hpp
+++ metro/include/metro/Snptest25StoppingCondition.hpp
@@ -0,0 +1,141 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_SNPTEST_STOPPING_CONDITION_HPP
+#define METRO_SNPTEST_STOPPING_CONDITION_HPP
+
+//#include "appcontext/OstreamTee.hpp"
+
+namespace metro {
+	
+	struct Trace {
+	public:
+		int iteration ;
+		int max_iterations ;
+		double tolerance ;
+
+		double ll ;
+		double target_ll ;
+		double ll_difference ;
+		double ll_rel_difference ;
+
+		Eigen::VectorXd parameters ;
+		Eigen::VectorXd difference ;
+		Eigen::VectorXd first_derivative ;
+		Eigen::MatrixXd second_derivative ;
+		bool converged ;
+		bool diverged ;
+		
+		std::ostream& operator<<( std::ostream& out ) {
+			out << "Iteration: " << iteration << "; tolerance = " << tolerance << ":\n"
+				<< "params: " << parameters.transpose() << "\n"
+				<< "difference: " << difference.transpose() << " (rel diff  = " << ( difference.array() / ( parameters.array().abs() + 0.1 ) ).transpose() << ")\n"
+				<< "current ll: " << ll << ", difference: " << ll_difference
+				<< ", rel. diff = " << ll_rel_difference << "\n"
+				<< "target ll: " << target_ll << "\n"
+				<< "first derivative: " << first_derivative.transpose() << "\n"
+				//<< "second derivative:\n" << m_ll.get_value_of_second_derivative() << "\n"
+				<< "converged: " << converged << "\n"
+				<< "diverged: " << diverged << ".\n" ;
+			return out ;
+		}
+	} ;
+	
+	template< typename LogLikelihood >
+	struct Snptest25StoppingCondition {
+		Snptest25StoppingCondition(
+			LogLikelihood const& ll,
+			double tolerance,
+			std::size_t max_iterations,
+			Trace* trace
+		):
+			m_ll( ll ),
+			m_target_ll( -std::numeric_limits< double >::infinity() ),
+			m_one_norm_of_first_derivative( std::numeric_limits< double >::infinity() ),
+			m_current_ll( -std::numeric_limits< double >::infinity() ),
+			m_tolerance( tolerance ),
+			m_iteration( -1 ),
+			m_max_iterations( max_iterations ),
+			m_trace( trace )
+		{}
+
+		void set_target_loglikelihood( double const target ) {
+			m_target_ll = target ;
+		}
+
+		bool operator()(
+			LogLikelihood const& ll,
+			Eigen::VectorXd const& parameters
+		) {
+			return operator()( parameters, ll.get_value_of_first_derivative() ) ;
+		}
+
+		bool operator()(
+			Eigen::VectorXd const& parameters,
+			Eigen::VectorXd const& first_derivative
+		) {
+			++m_iteration ;
+
+			m_one_norm_of_first_derivative = first_derivative.array().abs().maxCoeff() ;
+
+			double const previous_ll = m_current_ll ;
+			m_current_ll = m_ll.get_value_of_function() ;
+
+			if( m_current_ll > m_target_ll ) {
+				m_target_ll = m_current_ll ;
+			}
+
+			// double one_norm = parameters.array().abs().maxCoeff() ; 
+			Eigen::VectorXd difference ;
+			if( m_current_params.size() > 0 ) {
+				difference = ( parameters - m_current_params ).array().abs() ;
+			} else {
+				difference = LogLikelihood::Vector::Constant( parameters.size(), std::numeric_limits< double >::infinity() ) ;
+			}
+
+			//double const param_diff = ( m_current_params.size() == 0 ) ? 10000 : ( parameters - m_current_params ).array().abs().maxCoeff() ;
+			m_current_params = parameters ;
+			bool const converged = (
+				std::abs( m_current_ll - previous_ll ) < m_tolerance        // loglikelihood has not changed much
+				&& ( m_current_ll > ( m_target_ll - m_tolerance ) )         // loglikelihood at least as large as previously seen maximum
+				&& ( m_one_norm_of_first_derivative < m_tolerance )			// derivative close to zero
+			//	&& param_diff < m_tolerance									// parameters have not changed much.
+			) ;
+
+			if( m_trace ) {
+				m_trace->iteration = m_iteration ;
+				m_trace->max_iterations = m_max_iterations ;
+				m_trace->parameters = m_current_params ;
+				m_trace->ll = m_current_ll ;
+				m_trace->target_ll = m_target_ll ;
+				m_trace->ll_difference = std::abs( m_current_ll - previous_ll ) ;
+				m_trace->ll_rel_difference = std::abs( ( m_current_ll - previous_ll ) / m_current_ll ) ;
+				m_trace->first_derivative = first_derivative ;
+				m_trace->second_derivative = m_ll.get_value_of_second_derivative() ;
+				m_trace->converged = converged ;
+				m_trace->diverged = diverged() ;
+			}
+			return diverged() || converged ; 
+		}
+
+		bool diverged() const { return m_iteration >= m_max_iterations || m_current_ll != m_current_ll ; }
+		std::size_t number_of_iterations() const { return m_iteration ; }
+
+		private:
+			LogLikelihood const& m_ll ;
+			double m_target_ll ;
+			double m_one_norm_of_first_derivative ;
+			double m_current_ll ;
+			Eigen::VectorXd m_current_params ;
+			double const m_tolerance ;
+			int m_iteration ;
+			bool m_converged ;
+			std::size_t const m_max_iterations ;
+			Trace* m_trace ;
+	} ;
+}
+
+#endif

ADDED   metro/include/metro/UnivariateLogDensity.hpp
Index: metro/include/metro/UnivariateLogDensity.hpp
==================================================================
--- metro/include/metro/UnivariateLogDensity.hpp
+++ metro/include/metro/UnivariateLogDensity.hpp
@@ -0,0 +1,25 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_DISTRIBUTIONS_UNIVARIATELOGDENSITY_HPP
+#define METRO_DISTRIBUTIONS_UNIVARIATELOGDENSITY_HPP
+
+#include <memory>
+
+namespace metro {
+	struct UnivariateLogDensity {
+		typedef std::unique_ptr< UnivariateLogDensity > UniquePtr ;
+		
+		virtual ~UnivariateLogDensity() ;
+		virtual void evaluate_at( double x ) = 0 ;
+		virtual double get_value_of_function() const = 0 ;
+		virtual double get_value_of_first_derivative() const = 0 ;
+		virtual double get_value_of_second_derivative() const = 0 ;
+		virtual std::string get_summary() const = 0 ;
+	} ;
+}
+
+#endif

ADDED   metro/include/metro/concurrency/threadpool.hpp
Index: metro/include/metro/concurrency/threadpool.hpp
==================================================================
--- metro/include/metro/concurrency/threadpool.hpp
+++ metro/include/metro/concurrency/threadpool.hpp
@@ -0,0 +1,92 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_REGRESSION_CONCURRENCY_THREADPOOL_HPP
+#define METRO_REGRESSION_CONCURRENCY_THREADPOOL_HPP
+
+#include <vector>
+#include <deque>
+#include <thread>
+#include <condition_variable>
+#include <mutex>
+#include <functional>
+
+namespace metro {
+	namespace concurrency {
+		// This threadpool is derived from the implementation
+		// by WhozCraig (https://stackoverflow.com/questions/23896421/efficiently-waiting-for-all-tasks-in-a-threadpool-to-finish)
+		struct threadpool {
+		public:
+			typedef std::unique_ptr< threadpool > UniquePtr ;
+			static UniquePtr create( int number_of_threads = std::thread::hardware_concurrency() ) ;
+			class BatchScheduler ;
+
+		public:
+			threadpool( int number_of_threads = std::thread::hardware_concurrency() ) ;
+			~threadpool() ;
+			
+			template<class Task> void schedule( Task&& task ) {
+				std::unique_lock< std::mutex > lock( m_queue_mutex ) ;
+				m_tasks.emplace_back( std::forward<Task>( task ) );
+				m_task_available.notify_one() ;
+			}
+		
+			void wait() ;
+
+			std::size_t number_of_threads() const { return m_threads.size() ; }
+
+			std::unique_ptr< BatchScheduler > batch_scheduler() { return BatchScheduler::UniquePtr( new BatchScheduler( *this )) ; }
+
+		private:
+			std::vector< std::thread > m_threads ;
+			std::deque< std::function<void()> > m_tasks ;
+			std::mutex m_queue_mutex ;
+			std::condition_variable m_task_available ;
+			std::condition_variable m_task_finished ;
+			unsigned int m_running_tasks ;
+			bool m_stop ;
+
+		public:
+			// class BatchScheduler
+			// This allows multiple jobs to be scheduled without notifying threads
+			// until the scheduler is destructed
+			friend class BatchScheduler ;
+			class BatchScheduler {
+			public:
+				typedef std::unique_ptr< BatchScheduler > UniquePtr ;
+			public:
+				BatchScheduler( threadpool& pool ):
+					m_pool( pool ),
+					m_lock( pool.m_queue_mutex )
+				{
+				}
+
+				~BatchScheduler() {
+					m_lock.unlock() ;
+					m_pool.m_task_available.notify_all() ;
+				}
+				
+				template<class Task>
+				void add( Task&& task ) {
+					m_pool.m_tasks.emplace_back( std::forward<Task>( task ) );
+				}
+				
+			private:
+				threadpool& m_pool ;
+				std::unique_lock< std::mutex > m_lock ;
+
+				// disallow copying
+				BatchScheduler( BatchScheduler const& ) ;
+				BatchScheduler& operator=( BatchScheduler const& ) ;
+			} ;
+		
+		private:
+			void thread_loop() ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/constants.hpp
Index: metro/include/metro/constants.hpp
==================================================================
--- metro/include/metro/constants.hpp
+++ metro/include/metro/constants.hpp
@@ -0,0 +1,16 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_CONSTANTS_HPP
+#define METRO_CONSTANTS_HPP
+
+#include <numeric>
+
+namespace metro {
+	static double const NA = std::numeric_limits< double >::quiet_NaN() ;
+}
+
+#endif

ADDED   metro/include/metro/count_range.hpp
Index: metro/include/metro/count_range.hpp
==================================================================
--- metro/include/metro/count_range.hpp
+++ metro/include/metro/count_range.hpp
@@ -0,0 +1,23 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef CORE_COUNT_RANGES_HPP
+#define CORE_COUNT_RANGES_HPP
+
+#include <vector>
+#include "metro/SampleRange.hpp"
+
+namespace metro {
+	namespace impl {
+		// count the number of samples in a range
+		// each list is assumed to be a sorted list of non-intersecting ranges of integers.
+		int count_range(
+			std::vector< metro::SampleRange > const& range
+		) ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/distributions/Flat.hpp
Index: metro/include/metro/distributions/Flat.hpp
==================================================================
--- metro/include/metro/distributions/Flat.hpp
+++ metro/include/metro/distributions/Flat.hpp
@@ -0,0 +1,46 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_DISTRIBUTIONS_FLAT_HPP
+#define METRO_DISTRIBUTIONS_FLAT_HPP
+
+#include <memory>
+#include "metro/UnivariateLogDensity.hpp"
+
+namespace metro {
+	namespace distributions {
+		struct Flat: public UnivariateLogDensity {
+		public:
+			static UniquePtr create() ;
+			
+		public:
+			Flat() {} ;
+			Flat( Flat const& other ) {}
+			Flat& operator=( Flat const& other ) { return *this ; }
+
+		public:
+			void evaluate_at( double ) {} ;
+
+			double get_value_of_function() const {
+				return 0.0 ;
+			}
+
+			double get_value_of_first_derivative() const {
+				return 0.0 ;
+			}
+
+			double get_value_of_second_derivative() const {
+				return 0.0 ;
+			}
+			
+			std::string get_summary() const ;
+
+		private:
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/distributions/LogF.hpp
Index: metro/include/metro/distributions/LogF.hpp
==================================================================
--- metro/include/metro/distributions/LogF.hpp
+++ metro/include/metro/distributions/LogF.hpp
@@ -0,0 +1,51 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_DISTRIBUTIONS_LOGF_HPP
+#define METRO_DISTRIBUTIONS_LOGF_HPP
+
+#include "metro/UnivariateLogDensity.hpp"
+
+namespace metro {
+	namespace distributions {
+		struct LogF: public UnivariateLogDensity {
+		public:
+			enum Normalisation { ePDF, eZeroAtMean } ;
+			static UniquePtr create( double nu1, double nu2 ) ;
+		public:
+			LogF( double nu1, double nu2 ) ;
+			LogF( LogF const& other ) ;
+			LogF& operator=( LogF const& other ) ;
+
+		public:
+			void evaluate_at( double x ) ;
+
+			double get_value_of_function() const {
+				return m_value_of_function ;
+			}
+
+			double get_value_of_first_derivative() const {
+				return m_value_of_first_derivative ;
+			}
+
+			double get_value_of_second_derivative() const {
+				return m_value_of_second_derivative ;
+			}
+			
+			std::string get_summary() const ;
+				
+		private:
+			double m_alpha ;
+			double m_beta ;
+			double m_constant ;
+			double m_value_of_function ;
+			double m_value_of_first_derivative ;
+			double m_value_of_second_derivative ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/fit_model.hpp
Index: metro/include/metro/fit_model.hpp
==================================================================
--- metro/include/metro/fit_model.hpp
+++ metro/include/metro/fit_model.hpp
@@ -0,0 +1,51 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_REGRESSION_FIT_MODEL_HPP
+#define METRO_REGRESSION_FIT_MODEL_HPP
+
+#include <string>
+#include <vector>
+#include <Eigen/Core>
+#include <Eigen/Cholesky>
+#include "boost/function.hpp"
+#include "metro/ModifiedCholesky.hpp"
+#include "metro/SmoothFunction.hpp"
+
+namespace metro {
+	struct Stepper {
+	public:
+		typedef SmoothFunction Function ;
+		typedef Eigen::VectorXd Vector ;
+		typedef Eigen::MatrixXd Matrix ;
+		typedef boost::function<
+			void(
+				int iteration,
+				double ll,
+				double target_ll,
+				Vector const& point,
+				Vector const& derivative,
+				Vector const& step,
+				bool converged 
+			)
+		> Tracer ;
+	public:
+		virtual ~Stepper() ;
+		virtual bool diverged() const = 0 ;
+		virtual bool step( Function& function, Vector* result ) = 0 ;
+		virtual std::size_t number_of_iterations() const = 0 ;
+	} ;
+
+	std::pair< bool, int > fit_model(
+		metro::SmoothFunction& ll,
+		std::string const& model_name,
+		Eigen::VectorXd const& starting_point,
+		Stepper& stopping_condition,
+		std::vector< std::string >* comments
+	) ;
+}
+
+#endif

ADDED   metro/include/metro/intersect_ranges.hpp
Index: metro/include/metro/intersect_ranges.hpp
==================================================================
--- metro/include/metro/intersect_ranges.hpp
+++ metro/include/metro/intersect_ranges.hpp
@@ -0,0 +1,41 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef CORE_INTERSECT_RANGES_HPP
+#define CORE_INTERSECT_RANGES_HPP
+
+#include <vector>
+#include "metro/SampleRange.hpp"
+
+namespace metro {
+	namespace impl {
+		// intersect two lists of ranges.
+		// each range is assumed to be a sorted list of non-intersecting ranges of integers.
+		// The result is also a sorted list of non-intersecting ranges.
+		std::vector< metro::SampleRange > intersect_ranges(
+			std::vector< metro::SampleRange > const& left,
+			std::vector< metro::SampleRange > const& right
+		) ;
+
+		// intersect two lists of ranges.
+		// each range is assumed to be a sorted list of non-intersecting ranges of integers.
+		// The result is also a sorted list of non-intersecting ranges.
+		std::vector< metro::SampleRange > intersect_ranges(
+			metro::SampleRange const& left,
+			std::vector< metro::SampleRange > const& right
+		) ;
+
+		// intersect two lists of ranges.
+		// each range is assumed to be a sorted list of non-intersecting ranges of integers.
+		// The result is also a sorted list of non-intersecting ranges.
+		std::vector< metro::SampleRange > intersect_ranges(
+			std::vector< metro::SampleRange > const& left,
+			metro::SampleRange const& right
+		) ;
+	}
+}
+
+#endif

Index: metro/include/metro/likelihood/Mixture.hpp
==================================================================
--- metro/include/metro/likelihood/Mixture.hpp
+++ metro/include/metro/likelihood/Mixture.hpp
@@ -50,48 +50,62 @@
 				m_component_names.push_back( name ) ;
 				m_components.push_back( distribution ) ;
 				m_weights.push_back( weight ) ;
 				m_total_weight += weight ;
 			}
+			
+			int number_of_parameters() const {
+				int result = 0 ;
+				for( std::size_t i = 0; i < m_components.size(); ++i ) {
+					result += m_components[i].parameters().size() ;
+				}
+				return result ;
+			}
 			
 			// Evaluate at a given set of parameters expressed as a single vector.
 			// Parameters are taken in order of the components.
-			void evaluate_at( Vector const& parameters ) {
-				evaluate_at( parameters, DataSubset( DataRange( 0, m_data->rows() ))) ;
+			void evaluate_at( Vector const& parameters, int numberOfDerivatives = 2 ) {
+				evaluate_at( parameters, DataSubset( DataRange( 0, m_data->rows() )), numberOfDerivatives ) ;
 			}
 
 			// Evaluate at a given set of parameters expressed as a single vector,
 			// on a given subset of the data. Parameters are taken in order of the components.
 			// Parameters come in the order:
 			// Parameters for first component, (normalised) weight for first component
 			// Parameters for second component, (normalised) weight for second component
 			// ...
 			// Parameters for last component.  No weight is included for last component as weights sum to one.
-			void evaluate_at( Vector const& parameters, DataSubset const& data_subset ) {
+			void evaluate_at( Vector const& parameters, DataSubset const& data_subset, int numberOfDerivatives = 2 ) {
+				m_parameters = parameters ;
+				m_data_subset = data_subset ;
+				evaluate( numberOfDerivatives ) ;
+			}
+			
+			void evaluate( int numberOfDerivatives = 2 ) {
 				{
 					int param_i = 0 ;
 					double total_weight = 0 ;
 					for( std::size_t i = 0; i < m_components.size(); ++i ) {
 						int const componentParameterSize = m_components[i].parameters().size() ;
 						m_components[i].evaluate_at(
-							parameters.segment(
+							m_parameters.segment(
 								param_i,
 								componentParameterSize
 							),
-							data_subset
+							m_data_subset
 						) ;
 						if( i == ( m_components.size() - 1 ) ) {
 							m_weights[i] = 1 - total_weight ;
 							m_total_weight = 1 ;
 						} else {
-							m_weights[i] = parameters( param_i + componentParameterSize ) ;
+							m_weights[i] = m_parameters( param_i + componentParameterSize ) ;
 							total_weight += m_weights[i] ;
 						}
 						param_i += m_components[i].parameters().size() + 1 ;
 					}
 					// sanity check
-					assert((m_components.size() == 0) || (param_i == parameters.size() + 1)) ;
+					assert((m_components.size() == 0) || (param_i == m_parameters.size() + 1)) ;
 				}
 
 				m_component_terms.resize( m_data->rows(), m_components.size() ) ;
 				m_component_terms.setZero() ;
 				for( std::size_t i = 0; i < m_components.size(); ++i ) {
@@ -132,11 +146,11 @@
 			// Parameters for last component.  No weight is included for last component as weights sum to one.
 			Vector parameters() const {
 				return compute_parameters() ;
 			}
 
-			std::string get_spec() const {
+			std::string get_summary() const {
 				return "Mixture" ;
 			}
 
 			Vector get_value_of_first_derivative() const {
 				assert(0) ;
@@ -146,10 +160,12 @@
 				assert(0) ;
 			}
 
 		private:
 			Matrix const* m_data ;
+			Vector m_parameters ;
+			DataSubset m_data_subset ;
 			boost::ptr_vector< Component > m_components ;
 			std::vector< std::string > m_component_names ;
 			std::vector< Scalar > m_weights ;
 			Scalar m_total_weight ;
 			std::vector< Scalar > m_rescaled_weights ;

Index: metro/include/metro/likelihood/Multinomial.hpp
==================================================================
--- metro/include/metro/likelihood/Multinomial.hpp
+++ metro/include/metro/likelihood/Multinomial.hpp
@@ -36,15 +36,19 @@
 				m_counts = other.m_counts ;
 				m_parameters = other.m_parameters ;
 				return *this ;
 			}
 
-			void evaluate_at( Vector const& parameters, DataSubset const& subset = DataRange( 0, 1 ) ) {
+			void evaluate_at( Vector const& parameters, DataSubset const& subset = DataRange( 0, 1 ), int numberOfDerivatives = 2 ) {
 				assert( subset.number_of_subranges() == 1 && subset[0].begin() == 0 && subset[0].end() == 1 ) ;
 				assert( parameters.size() == m_counts.size() ) ;
 				m_parameters = parameters ;
 			}
+
+			void evaluate( int numberOfDerivatives ) {
+				// nothing to do
+			}
 			
 			double get_value_of_function() const {
 				double result = 0.0 ;
 				for( int i = 0; i < m_counts.size(); ++i ) {
 					if( m_counts(i) > 0.0 ) {
@@ -80,14 +84,14 @@
 			}
 
 			Vector parameters() const { return m_parameters ; }
 			Vector const& get_data() const { return m_counts ; }
 			
-			std::string get_spec() const { return "Multinomial" ; }
+			std::string get_summary() const { return "Multinomial" ; }
 		private:
 			Vector m_counts ;
 			Vector m_parameters ;
 		} ;
 	}
 }
 
 #endif

Index: metro/include/metro/likelihood/MultivariateT.hpp
==================================================================
--- metro/include/metro/likelihood/MultivariateT.hpp
+++ metro/include/metro/likelihood/MultivariateT.hpp
@@ -31,27 +31,30 @@
 		public:
 			MultivariateT( double const degrees_of_freedom ):
 				m_pi( 3.141592653589793238462643383279502884 ),
 				m_nu( degrees_of_freedom ),
 				m_data( 0 ),
+				m_p( 0 ),
 				m_kappa( 0 )
 			{
 			}
 			
 			MultivariateT( Matrix const& data, double const degrees_of_freedom ):
 				m_pi( 3.141592653589793238462643383279502884 ),
 				m_nu( degrees_of_freedom ),
 				m_data( 0 ),
+				m_p( 0 ),
 				m_kappa( 0 )
 			{
 				set_data( data ) ;
 			}
 
 			MultivariateT( Matrix const& data, Vector const& weights, double const degrees_of_freedom ):
 				m_pi( 3.141592653589793238462643383279502884 ),
 				m_nu( degrees_of_freedom ),
 				m_data( 0 ),
+				m_p( 0 ),
 				m_kappa( 0 )
 			{
 				set_data( data, weights ) ;
 			}
 
@@ -61,11 +64,11 @@
 			Vector parameters() const { return m_parameters ; }
 			Vector const& mean() const { return m_mean ; }
 			Matrix const& sigma() const { return m_sigma ; }
 			Matrix const& data() const { return m_data ; }
 			
-			std::string get_spec() const { return "MultivariateT" ; }
+			std::string get_summary() const { return "MultivariateT" ; }
 
 
 			// Behaves as if calling set_data() (below) with unit weights.
 			void set_data(
 				Matrix const& data
@@ -94,19 +97,19 @@
 
 			// Evaluate at a given set of parameters, specified as a single vector.
 			// Parameters are taken in order as the p entries of the mean vector,
 			// followed by the p(p+1)/2 entries of the lower triangle of the
 			// variance-covariance matrix taken in column-major order.
-			void evaluate_at( Vector const& parameters ) {
+			void evaluate_at( Vector const& parameters, int numberOfDerivatives = 2 ) {
 				evaluate_at( parameters, DataRange( 0, m_data->rows() )) ;
 			}
 
 			// Evaluate at a given set of parameters on a specified subset of the data.
 			// Parameters are taken in order as the p entries of the mean vector,
 			// followed by the p(p+1)/2 entries of the lower triangle of the
 			// variance-covariance matrix taken in column-major order.
-			void evaluate_at( Vector const& parameters, DataSubset const& data_subset ) {
+			void evaluate_at( Vector const& parameters, DataSubset const& data_subset, int numberOfDerivatives = 2 ) {
 				assert( parameters.size() == m_parameters.size() ) ;
 				assert( m_data ) ;
 				unpack_parameters( parameters, &m_mean, &m_sigma ) ;
 				evaluate_at( m_mean, m_sigma, data_subset ) ;
 			}
@@ -128,14 +131,25 @@
 				assert( sigma.rows() == m_data->cols() ) ;
 
 				m_mean = mean ;
 				m_sigma = sigma ;
 				m_data_subset = data_subset ;
+
+#if DEBUG_MULTIVARIATE_T
+					std::cerr << "metro::likelihood::MultivariateT::evaluate_at():\n"
+						<< " m_data_subset " << m_data_subset << "\n"
+						<< " m_mean " << m_mean.transpose() << "\n"
+						<< " m_sigma = \n" << m_sigma << "\n" 
+						<< " m_log_determinant = " << m_log_determinant << "\n" ;
+#endif				
 
 				// Pack parameters into the parameter vector
 				pack_parameters( mean, m_sigma, &m_parameters ) ;
+				evaluate() ;
+			}
 
+			void evaluate( int const numberOfDerivatives = 2 ) {
 				// We compute up-front some quantities that are useful
 				// when computing the log-likelihood.
 				m_ldlt.compute( m_sigma ) ;
 				m_log_determinant = m_ldlt.vectorD().array().log().sum() ;
 				m_mean_centred_data = m_data->rowwise() - m_mean.transpose() ;
@@ -142,25 +156,22 @@
 				// Z is a vector of the terms ( x_i - mu )^t Sigma^-1 ( x_i - mu ).
 				m_A = m_ldlt.solve( m_mean_centred_data.transpose() ) ;
 				m_Z = (
 					m_mean_centred_data.array() * m_A.transpose().array()
 				).rowwise().sum() ;
-
-#if DEBUG_MULTIVARIATE_T
-					std::cerr << "metro::likelihood::MultivariateT::evaluate_at():\n"
-						<< " m_mean " << m_mean.transpose() << "\n"
-						<< " m_sigma = \n" << m_sigma << "\n" 
-						<< " m_log_determinant = " << m_log_determinant << "\n" ;
-#endif				
 			}
 
 			// Get the value of the log-likelihood for the given data,
 			// and parameters and data subset passed to evaluate_at().
 			// You must call evaluate_at() before using this function.
 			double get_value_of_function() const {
 				Vector terms = Vector::Constant( m_data->rows(), 0 ) ;
 				get_terms_of_function( terms ) ;
+#if DEBUG_MULTIVARIATE_T
+					std::cerr << "metro::likelihood::MultivariateT::get_value_of_function():\n"
+						<< " terms = " << terms << ".\n" ;
+#endif				
 				return terms.sum() ;
 			}
 
 			// Get terms of the log-likelihood corresponding to each
 			// weighted data point.
@@ -188,13 +199,14 @@
 #if DEBUG_MULTIVARIATE_T
 					std::cerr << "metro::likelihood::MultivariateT::get_terms_of_function():\n"
 						<< " Adding " << range << "\n"
 						<< " segmentZ = " << segmentZ.transpose() << "\n"
 						<< " segmentWeights = " << segmentWeights.transpose() << "\n"
-						<< " m_kappa = " << m_kappa << "\n"
+						<< " m_nu = " << m_nu << ", m_p = " << m_p << ", m_kappa = " << m_kappa << "\n"
 						<< " m_log_determinant = " << m_log_determinant << "\n"
-						<< " term = " << (( segmentZ + Vector::Constant( range.size(), m_nu ) ).array().log() )
+						<< " range.size() = " << range.size() << "\n"
+						<< " term = " << ((( segmentZ + Vector::Constant( range.size(), m_nu ) ).array().log() ) )
 						<< " result = " << result << ".\n" ;
 #endif				
 				}
 			}
 
@@ -318,11 +330,11 @@
 				evaluate_at( mean, sigma, data_subset ) ;
 				double loglikelihood = get_value_of_function() ;
 				
 #if DEBUG_MULTIVARIATE_T
 				std::cerr << "metro::likelihood::MultivariateT::estimate_by_em(): start: params = "
-					<< get_parameters().transpose() << ", ll = " << get_value_of_function() << ".\n" ;
+					<< parameters().transpose() << ", ll = " << get_value_of_function() << ".\n" ;
 #endif				
 
 				// If nu = ∞ we are at the MLE already, so bail out...
 				if( m_nu == std::numeric_limits< double >::infinity() ) {
 					// Multivariate normal.  Quit right now.
@@ -351,11 +363,11 @@
 					evaluate_at( mean, sigma, data_subset ) ;
 					loglikelihood = get_value_of_function() ;
 
 #if DEBUG_MULTIVARIATE_T
 					std::cerr << "metro::likelihood::MultivariateT::estimate_by_em(): after iteration "
-						<< iteration << ": params = " << get_parameters().transpose()
+						<< iteration << ": params = " << parameters().transpose()
 						<< ", ll = " << loglikelihood
 						<< ", iterationWeights = " << iterationWeights.head( std::min( iterationWeights.size(), 10l )).transpose() << ".\n" ;
 #endif				
 					++iteration ;
 				}
@@ -381,10 +393,15 @@
 			Vector m_Z ;
 			
 		private:
 			
 			double compute_constant_terms( double const nu, double const p ) const {
+#if DEBUG_MULTIVARIATE_T
+				std::cerr << "metro::likelihood::MultivariateT::compute_constant_terms():\n"
+					<< " nu  = " << nu << "\n"
+					<< " p = " << p << "\n" ;
+#endif
 				return ( nu == std::numeric_limits< double >::infinity() )
 					? (
 						-0.5 * p * std::log( 2 * m_pi )
 					) : (
 						lgamma( ( nu + p ) / 2.0 )

Index: metro/include/metro/likelihood/ProductOfMultinomials.hpp
==================================================================
--- metro/include/metro/likelihood/ProductOfMultinomials.hpp
+++ metro/include/metro/likelihood/ProductOfMultinomials.hpp
@@ -39,17 +39,23 @@
 				for( std::size_t i = 0; i < m_multinomials.size(); ++i ) {
 					m_multinomials[i].evaluate_at( parameters.row( i )) ;
 				}
 			}
 
-			void evaluate_at( Vector const& parameters, DataSubset const& subset = DataRange( 0, 1 ) ) {
+			void evaluate_at( Vector const& parameters, DataSubset const& subset = DataRange( 0, 1 ), int numberOfDerivatives = 2 ) {
 				assert( subset.number_of_subranges() == 1 && subset[0].begin() == 0 && subset[0].end() == 1 ) ;
 				assert( parameters.size() == m_data.rows() * m_data.cols() ) ;
 				for( std::size_t i = 0; i < m_multinomials.size(); ++i ) {
 					m_multinomials[i].evaluate_at( parameters.segment( i * m_data.cols(), m_data.cols() ) ) ;
 				}
 			}
+
+			void evaluate( int numberOfDerivatives = 2 ) {
+				for( std::size_t i = 0; i < m_multinomials.size(); ++i ) {
+					m_multinomials[i].evaluate( numberOfDerivatives ) ;
+				}
+			}
 
 			double get_value_of_function() const {
 				double result = 0 ;
 				for( std::size_t i = 0; i < m_multinomials.size(); ++i ) {
 					result += m_multinomials[i].get_value_of_function() ;
@@ -83,11 +89,11 @@
 					result.segment( m_data.cols() * i, m_data.cols() ) = m_multinomials[i].get_MLE() ;
 				}
 				return result ;
 			}
 
-			std::string get_spec() const { return "ProductOfMultinomials" ; }
+			std::string get_summary() const { return "ProductOfMultinomials" ; }
 			
 			Vector parameters() const {
 				Vector result( m_data.rows() * m_data.cols() ) ;
 				for( std::size_t i = 0; i < m_multinomials.size(); ++i ) {
 					result.segment( m_data.cols() * i, m_data.cols() ) = m_multinomials[i].parameters() ;

Index: metro/include/metro/log_sum_exp.hpp
==================================================================
--- metro/include/metro/log_sum_exp.hpp
+++ metro/include/metro/log_sum_exp.hpp
@@ -5,10 +5,11 @@
 //          http://www.boost.org/LICENSE_1_0.txt)
 
 #ifndef METRO_LOG_SUM_EXP_HPP
 #define METRO_LOG_SUM_EXP_HPP
 
+#include <vector>
 #include <Eigen/Core>
 
 namespace metro {
 	// Compute the log of a sum of exponentials via an algorithm that 
 	template< typename Matrix, typename Nonmissingness >
@@ -38,10 +39,14 @@
 		}
 		Eigen::MatrixXd const exponential = ( data - Eigen::MatrixXd::Constant( data.rows(), data.cols(), max_value ) ).array().exp() ;
 		return max_value + std::log( exponential.array().sum() ) ;
 	}
 
+	// Ditto but assuming all values are present.
+	template<>
+	double log_sum_exp( std::vector< double > const& data ) ;
+
 	void rowwise_log_sum_exp( Eigen::MatrixXd const&, Eigen::VectorXd* result ) ;
 	void rowwise_log_sum_exp( Eigen::MatrixXd const&, Eigen::MatrixXd const& nonmissingness, Eigen::VectorXd* result ) ;
 }
 
 #endif

ADDED   metro/include/metro/maximisation.hpp
Index: metro/include/metro/maximisation.hpp
==================================================================
--- metro/include/metro/maximisation.hpp
+++ metro/include/metro/maximisation.hpp
@@ -0,0 +1,50 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef CORE_MAXIMISATION_HPP
+#define CORE_MAXIMISATION_HPP
+
+#include "metro/NewtonRaphson.hpp"
+
+namespace metro {
+	namespace impl {
+		// This object represents the derivative of a twice-differentiable function.
+		template< typename Function >
+		struct Derivative
+		{
+			typedef typename Function::Vector Vector ;
+			typedef typename Function::Matrix Matrix ;
+
+			Derivative( Function& function ): m_function( function ) {}
+			Derivative( Derivative const& other ): m_function( other.m_function ) {}
+
+			void evaluate_at( Vector const& parameters ) { m_function.evaluate_at( parameters ) ; }
+			Vector get_value_of_function() const { return m_function.get_value_of_first_derivative() ; }
+			Matrix get_value_of_first_derivative() const { return m_function.get_value_of_second_derivative() ; }
+		private:
+			Function& m_function ;
+			Derivative& operator=( Derivative const& other ) ;
+		} ;
+
+		template< typename Function >
+		Derivative< Function > derivative( Function& function ) {
+			return Derivative< Function >( function ) ;
+		}
+	}
+
+	template< typename SmoothFunction, typename Domain, typename StoppingCondition, typename MatrixSolver >
+	Domain maximise_by_newton_raphson(
+		SmoothFunction& f,
+		Domain const& initial_point,
+		StoppingCondition& stopping_condition,
+		MatrixSolver& solver
+	) {
+		impl::Derivative< SmoothFunction > Df = impl::derivative( f ) ;
+		return find_root_by_newton_raphson( Df, initial_point, stopping_condition, solver ) ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/regression/BinomialLogistic.hpp
Index: metro/include/metro/regression/BinomialLogistic.hpp
==================================================================
--- metro/include/metro/regression/BinomialLogistic.hpp
+++ metro/include/metro/regression/BinomialLogistic.hpp
@@ -0,0 +1,137 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_REGRESSION_BINOMIALLOGISTIC_HPP
+#define METRO_REGRESSION_BINOMIALLOGISTIC_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+
+namespace metro {
+	namespace regression {
+		/*
+		* This class implements a log-likelihood for binomial logistic regression, allowing predictors
+		* to take one of a finite set of values with associated probabilities. (A "missing data log-likelihood" ).
+		* The outcome must be a two-column matrix containing positive integers; in the binomial formulation
+		* in terms of 'successes/failures', the 1st column is the number of failure (baseline) outcomes
+		* and the 2nd column the number of successful (non-baseline) outcomes.
+		*/
+		struct BinomialLogistic: public LogLikelihood
+		{
+		public:
+			typedef regression::Design::Point Point ;
+			typedef regression::Design::Vector Vector ;
+			typedef regression::Design::RowVector RowVector ;
+			typedef regression::Design::Matrix Matrix ;
+			typedef Eigen::Block< Matrix > MatrixBlock ;
+			typedef Eigen::Block< Matrix const > ConstMatrixBlock ;
+			typedef boost::function< std::string( std::string const& predictor_name, std::string const& outcome_name ) > GetParameterName ;
+		public:
+			typedef std::auto_ptr< BinomialLogistic > UniquePtr ;
+			static UniquePtr create( Design& ) ;
+			static UniquePtr create( Design::UniquePtr ) ;
+			static UniquePtr create( Design&, std::vector< metro::SampleRange > ) ;
+			static UniquePtr create( Design::UniquePtr, std::vector< metro::SampleRange > ) ;
+			BinomialLogistic( Design& ) ;
+			BinomialLogistic( Design&, std::vector< metro::SampleRange > included_samples ) ;
+			BinomialLogistic( Design::UniquePtr ) ;
+			BinomialLogistic( Design::UniquePtr, std::vector< metro::SampleRange > included_samples ) ;
+			~BinomialLogistic() ;
+			
+			regression::Design& design() const { return *m_design ; }
+			void set_parameter_naming_scheme( GetParameterName ) ;
+			std::string get_parameter_name( std::size_t i ) const ;
+	
+			int number_of_outcomes() const ;
+			int number_of_parameters() const { return m_parameters.size() ; }
+			IntegerMatrix identify_parameters() const ;
+
+			void evaluate_at( Point const& parameters, int const numberOfDerivatives = 2 ) ;
+			void evaluate( int const numberOfDerivatives = 2 ) ;
+
+			Point const& parameters() const ;
+			double get_value_of_function() const ;
+			Vector get_value_of_first_derivative() const ;
+			Matrix get_value_of_second_derivative() const ;
+			
+			std::string get_summary() const ;
+
+		private:
+			regression::Design* m_design ;
+			bool m_design_owned ;
+			GetParameterName m_get_parameter_name ;
+			Point m_parameters ;
+			std::vector< metro::SampleRange > m_included_samples ;
+			std::vector< metro::SampleRange > m_evaluated_samples ;
+			std::vector< metro::SampleRange > m_storage_samples ;
+			int m_number_of_stored_samples ;
+			int m_numberOfDerivativesComputed ;
+			int m_numberOfCDLDerivativesComputed ;
+
+			Matrix m_outcome_probabilities ;
+			
+			// Given outcome, likelihood function is of the form f(x^t theta) where
+			// theta are the parameters (currently we don't handle the case e.g. normal
+			// linear regression where there are additional parameters).  
+			// Therefore derivatives are of the form (Df)|(x^t theta).x^t
+			// And D^2 f(x^t theta) . x^t
+			
+			Matrix m_hx ; // coefficient for each level x in complete data likelihood for each sample.
+			Matrix m_normalisedDhx ; // coefficient of x in 1st derivative of mean function.
+			Matrix m_normalisedDdhx ; // coefficient of x^t ⊗ x in 2nd derivative of mean function.
+			Matrix m_f1 ; // temp storage used in likelihood and derivative computations
+
+			Matrix m_first_derivative_terms ;
+			double m_value_of_function ;
+			Vector m_value_of_first_derivative ;
+			Matrix m_value_of_second_derivative ;
+
+		private:
+			// Evaluate
+			void evaluate_at_impl( Point const& parameters, std::vector< metro::SampleRange > const& included_samples, int const numberOfDerivatives ) ;
+
+			// setup_storage(): this allocates space in:
+			// m_hx, m_normalisedDhx, m_normalisedDdhx,
+			// m_first_derivative_terms,
+			// and defines m_storage_samples and m_number_of_stored_samples
+			// appropriately for the ranges of samples passed in.
+			void setup_storage( std::vector< metro::SampleRange > const& evaluation_samples ) ;
+
+			// Compute complete data likelihood, and its derivatives, for each predictor level
+			// and each sample
+			virtual void compute_complete_data_likelihood_and_derivatives(
+				Point const& parameters,
+				Matrix* fx,
+				Matrix* dfx,
+				Matrix* ddfx,
+				int const numberOfDerivatives
+			) ;
+
+			// Calculate matrix of probabilities of outcome per genotype, given the parameters.
+			void calculate_outcome_probabilities( Vector const& parameters, Matrix const& phenotypes, Matrix* result ) const ;
+			void compute_value_of_loglikelihood(
+				Matrix const& hx,
+				double* result
+			) ;
+			void compute_value_of_first_derivative(
+				Matrix const& normalisedDhx,
+				Matrix* result_terms,
+				Vector* result
+			) ;
+			void compute_value_of_second_derivative(
+				Matrix const& first_derivative_terms,
+				Matrix const& normalisedDdhx,
+				Matrix* result
+			) ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/regression/Design.hpp
Index: metro/include/metro/regression/Design.hpp
==================================================================
--- metro/include/metro/regression/Design.hpp
+++ metro/include/metro/regression/Design.hpp
@@ -0,0 +1,207 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_CASE_CONTROL_REGRESSION_DESIGN_HPP
+#define SNPTEST_CASE_CONTROL_REGRESSION_DESIGN_HPP
+
+#include <vector>
+#include <iostream>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include <boost/function.hpp>
+#include "Eigen/Core"
+#include "metro/SampleRange.hpp"
+
+namespace metro {
+	namespace regression {
+		struct Design: public boost::noncopyable
+		{
+			typedef std::auto_ptr< Design > UniquePtr ;
+		public:
+			typedef Eigen::VectorXd Point ;
+			typedef Eigen::VectorXd Vector ;
+			typedef Eigen::RowVectorXd RowVector ;
+			typedef Eigen::MatrixXd Matrix ;
+			//typedef Eigen::Matrix< char, Eigen::Dynamic, Eigen::Dynamic > NonmissingnessMatrix ;
+			typedef Matrix NonmissingnessMatrix ;
+			typedef Eigen::Block< Matrix > MatrixBlock ;
+			typedef Eigen::Block< Matrix const > ConstMatrixBlock ;
+			typedef std::vector< metro::SampleRange > SampleRanges ;
+			typedef boost::function< std::string const& ( int parameter_i ) > GetPredictorNames ;
+			enum Transform { eIdentity = 0, eMeanCentre = 1 } ;
+
+		public:
+		
+			static UniquePtr create(
+				Matrix const& outcome, SampleRanges const& nonmissing_outcome, std::vector< std::string > const& outcome_names,
+				Matrix const& covariates, SampleRanges const& nonmissing_covariates, std::vector< std::string > const& covariate_names,
+				std::vector< std::string > const& predictor_names,
+				Transform transform = eIdentity,
+				std::vector< int > const& interacting_covariates = std::vector< int >()
+			) ;
+
+			Design(
+				Matrix const& outcome, SampleRanges const& nonmissing_outcome, std::vector< std::string > const& outcome_names,
+				Matrix const& covariates, SampleRanges const& nonmissing_covariates, std::vector< std::string > const& covariate_names,
+				std::vector< std::string > const& predictor_names,
+				Transform transform = eIdentity,
+				std::vector< int > const& interacting_covariates = std::vector< int >()
+			) ;
+
+			static UniquePtr create(
+				Matrix const& outcome, SampleRanges const& nonmissing_outcome, std::vector< std::string > const& outcome_names,
+				std::vector< std::string > const& predictor_names,
+				Transform transform = eIdentity
+			) ;
+
+			Design(
+				Matrix const& outcome, SampleRanges const& nonmissing_outcome, std::vector< std::string > const& outcome_names,
+				std::vector< std::string > const& predictor_names,
+				Transform transform = eIdentity
+			) ;
+		
+			// Design( Design const& other ) ;
+
+			// add a single continuous covariate
+			// missing values are encoded by NaN
+			void add_single_covariate(
+				std::string const& name,
+				boost::function< double( std::size_t ) > const& data
+			) ;
+			// add a single discrete covariate (which expands into multiple columns of zeroes and ones)
+			// levels are specified by non-negative integers, with missing values
+			// encoded by -1.
+			// A seperate function must be supplied to give the names of levels.
+			void add_discrete_covariate(
+				std::string const& name,
+				boost::function< int( std::size_t ) > const& data,
+				boost::function< std::string( int ) > const& levelNames,
+				int numberOfLevels
+			) ;
+
+			int const number_of_predictors() const { return m_predictor_names.size() ; }
+			int const number_of_interaction_terms() const { return number_of_predictors() * m_design_matrix_interaction_columns.size() ; }
+
+			std::string const& get_predictor_name( std::size_t i ) const ;
+			std::vector< std::string > const& design_matrix_column_names() const ;
+			std::string const& get_outcome_name( std::size_t i ) const ;
+
+			Design& set_outcome(
+				Matrix const& outcome,
+				SampleRanges const& nonmissingness,
+				std::vector< std::string > const& names
+			) ;
+
+			// Set predictors with uncertainty
+			// We assume there are K possible combinations of all the predictor values,
+			// and that each sample takes the kth set of predictor values with probability given
+			// by the specified matrix.  Here
+			//
+			// - levels is a K x d matrix  (K levels for d predictors)
+			// - probabilities is N x K    (N samples, probabilities for K levels)
+			//
+			// N = number of samples
+			// K = number of different possible levels of the predictors
+			// and d = number of predictors.
+			Design& set_predictors(
+				Matrix const& levels,
+				Matrix const& probabilities,
+				SampleRanges const& nonmissingness
+			) ;
+
+			// Set predictors without uncertainty
+			// We assume that the nth row of the given matrix
+			// specifies the predictor values for the nth sample.
+			Design& set_predictors(
+				Matrix const& predictors,
+				std::vector< metro::SampleRange > const& nonmissingness
+			) ;
+
+			Matrix const& matrix() const { return m_design_matrix ; }
+			ConstMatrixBlock matrix( metro::SampleRange const& range ) const {
+				return m_design_matrix.block(
+					range.begin(), 0,
+					range.size(), m_design_matrix.cols()
+				) ;
+			}
+			Design& set_predictor_level( int level ) ;
+			Design& set_predictor_level( int level, metro::SampleRange const& ) ;
+			Design& set_predictor_level( int level, std::vector< metro::SampleRange > const& ) ;
+		
+			Matrix const& get_predictor_level_probabilities() const { return m_predictor_level_probabilities ; }
+			int const get_number_of_predictor_levels() const { return m_predictor_level_probabilities.cols() ; }
+			// Matrix const& get_predictor_levels() const { return m_predictor_levels ; }
+		
+			Matrix const& outcome() const { return m_outcome ; }
+
+			SampleRanges const& nonmissing_outcome() const { return m_nonmissing_outcome ; }
+			SampleRanges const& nonmissing_predictor() const { return m_nonmissing_predictors ; }
+			SampleRanges const& nonmissing_covariates() const { return m_nonmissing_covariates ; }
+			SampleRanges const& nonmissing_samples() const { return m_nonmissing_samples ; }
+
+			std::string get_summary() const ;
+		private:
+			// Outcome variables
+			Matrix m_outcome ;
+			std::vector< std::string > m_outcome_names ;
+			SampleRanges m_nonmissing_outcome ;
+
+			// Predictor variables
+			Matrix m_predictor_level_probabilities ;
+			Matrix m_predictor_levels ;
+			std::vector< std::string > const m_predictor_names ;
+			SampleRanges m_nonmissing_predictors ;
+
+			// Covariate variables
+			std::vector< Matrix > m_covariates ;
+			std::vector< std::string > m_covariate_names ;
+			SampleRanges m_nonmissing_covariates ;
+
+			// Interactors
+			std::vector< int > const m_predictor_covariate_interactions ;
+			// Design matrix column transform - e.g. mean centre.
+			Transform const m_transform ;
+
+			// The current design matrix that holds current predictor values and covariates.
+			Matrix m_design_matrix ;
+
+			// SampleRange that tracks samples that have no nonmissing data
+			// in outcome, covariates, or predictors
+			// Invariant: this the intersection of nonmissing samples implied
+			// by m_nonmissing_outcome, m_nonmissing_predictors, and m_nonmissing_covariates.
+			SampleRanges m_nonmissing_samples ;
+			
+			std::vector< int > m_design_matrix_interaction_columns ;
+			std::vector< std::string > m_design_matrix_column_names ;
+
+		private:
+			SampleRanges compute_nonmissing_samples(
+				SampleRanges const& nonmissing_outcome,
+				SampleRanges const& nonmissing_predictors,
+				SampleRanges const& nonmissing_covariates
+			) const ;
+			void recalculate() ; 
+			void calculate_design_matrix(
+				int const,
+				std::vector< Matrix > const& covariates,
+				std::vector< std::string > const& covariate_names,
+				std::vector< std::string > const& predictor_names,
+				std::vector< int > const& interaction_cols,
+				Matrix* result,
+				std::vector< int >* design_matrix_interaction_cols,
+				std::vector< std::string > * design_matrix_column_names
+			) const ;
+			
+			void mean_centre_predictor_levels(
+				Matrix const& probs,
+				Matrix* predictor_levels,
+				SampleRanges const& included_samples
+			) const ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/regression/IndependentLogFWeightedLogLikelihood.hpp
Index: metro/include/metro/regression/IndependentLogFWeightedLogLikelihood.hpp
==================================================================
--- metro/include/metro/regression/IndependentLogFWeightedLogLikelihood.hpp
+++ metro/include/metro/regression/IndependentLogFWeightedLogLikelihood.hpp
@@ -0,0 +1,99 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_REGRESSION_INDEPENDENT_LOGF_WEIGHTED_LOGLIKELIHOOD_HPP
+#define SNPTEST_REGRESSION_INDEPENDENT_LOGF_WEIGHTED_LOGLIKELIHOOD_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "Eigen/Cholesky"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/regression/LogPosteriorDensity.hpp"
+
+namespace metro {
+	namespace regression {
+		// Represents a log-likelihood function weighted by independent
+		// log-F distributions on each of a chosen set of parameters.
+		struct IndependentLogFWeightedLogLikelihood: public LogPosteriorDensity {
+		public:
+			typedef std::auto_ptr< IndependentLogFWeightedLogLikelihood > UniquePtr ;
+			enum Normalisation { ePDF, eZeroAtMean } ;
+			static UniquePtr create(
+				LogLikelihood::UniquePtr ll,
+				std::vector< int > parameter_indices,
+				std::vector< double > nu1,
+				std::vector< double > nu2
+			) ;
+		public:
+			IndependentLogFWeightedLogLikelihood(
+				LogLikelihood::UniquePtr ll,
+				std::vector< int > parameter_indices,
+				std::vector< double > nu1,
+				std::vector< double > nu2
+			) ;
+			
+			regression::Design& design() const { return m_ll->design() ; }
+
+			int number_of_parameters() const ;
+			std::string get_parameter_name( std::size_t i ) const ;
+
+			int number_of_outcomes() const ;
+			// Return a lx2 matrix identifying the l parameters.
+			// The row for each parameter contains the outcome level and design matrix column for that parameter.
+			IntegerMatrix identify_parameters() const ;
+			
+			void evaluate_at( Point const& parameters, int const numberOfDerivatives = 2 ) ;
+			void evaluate( int const numberOfDerivatives = 2 ) ;
+
+			Point const& parameters() const {
+				return m_ll->parameters() ;
+			}
+
+			double get_value_of_function() const {
+				return m_ll->get_value_of_function() + m_value_of_function ;
+			}
+
+			Vector get_value_of_first_derivative() const {
+				return m_ll->get_value_of_first_derivative() + m_value_of_first_derivative ;
+			}
+
+			Matrix get_value_of_second_derivative() const {
+				return m_ll->get_value_of_second_derivative() + m_value_of_second_derivative ;
+			}
+
+			Vector get_prior_mode() const ;
+
+			Matrix get_prior_second_derivative() const {
+				return m_value_of_second_derivative ;
+			}
+
+			Matrix get_loglikelihood_second_derivative() const {
+				return m_ll->get_value_of_second_derivative() ;
+			}
+		
+			std::string get_summary() const ;
+			
+		private:
+			LogLikelihood::UniquePtr m_ll ;
+			std::vector< int > const m_parameter_indices ;
+			std::vector< double > m_alpha ;
+			std::vector< double > m_beta ;
+			Normalisation const m_normalisation ;
+			double m_constant ;
+			double m_value_of_function ;
+			Vector m_value_of_first_derivative ;
+			Matrix m_value_of_second_derivative ;
+
+		private:
+			void evaluate_impl( int const numberOfDerivatives = 2 ) ;
+			
+		} ;
+	}
+}
+#endif

ADDED   metro/include/metro/regression/IndependentNormalWeightedLogLikelihood.hpp
Index: metro/include/metro/regression/IndependentNormalWeightedLogLikelihood.hpp
==================================================================
--- metro/include/metro/regression/IndependentNormalWeightedLogLikelihood.hpp
+++ metro/include/metro/regression/IndependentNormalWeightedLogLikelihood.hpp
@@ -0,0 +1,97 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_REGRESSION_INDEPENDENT_NORMAL_WEIGHTED_LOGLIKELIHOOD_HPP
+#define SNPTEST_REGRESSION_INDEPENDENT_NORMAL_WEIGHTED_LOGLIKELIHOOD_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "Eigen/Cholesky"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/regression/LogPosteriorDensity.hpp"
+
+namespace metro {
+	namespace regression {
+		// Represents a log-likelihood function weighted by independent
+		// normal distributions on each parameter.
+		// by default variance=infinity, i.e. no weighting, and weighting
+		// must be set.
+		struct IndependentNormalWeightedLogLikelihood: public LogPosteriorDensity {
+		public:
+			typedef std::auto_ptr< IndependentNormalWeightedLogLikelihood > UniquePtr ;
+			enum Normalisation { ePDF, eZeroAtMean } ;
+			static UniquePtr create(
+				LogLikelihood::UniquePtr ll,
+				std::vector< int > parameter_indices,
+				std::vector< double > means,
+				std::vector< double > variances
+			) ;
+		public:
+			IndependentNormalWeightedLogLikelihood(
+				LogLikelihood::UniquePtr ll,
+				std::vector< int > parameter_indices,
+				std::vector< double > means,
+				std::vector< double > variances
+			) ;
+			
+			regression::Design& design() const { return m_ll->design() ; }
+
+			int number_of_parameters() const ;
+			std::string get_parameter_name( std::size_t i ) const ;
+
+			int number_of_outcomes() const ;
+			// Return a lx2 matrix identifying the l parameters.
+			// The row for each parameter contains the outcome level and design matrix column for that parameter.
+			IntegerMatrix identify_parameters() const ;
+			
+			void evaluate_at( Point const& parameters, int const numberOfDerivatives = 2 ) ;
+			void evaluate( int const numberOfDerivatives = 2 ) ;
+
+			Point const& parameters() const {
+				return m_ll->parameters() ;
+			}
+
+			double get_value_of_function() const {
+				return m_ll->get_value_of_function() + m_value_of_function ;
+			}
+
+			Vector get_value_of_first_derivative() const {
+				return m_ll->get_value_of_first_derivative() + m_value_of_first_derivative ;
+			}
+
+			Matrix get_value_of_second_derivative() const {
+				return m_ll->get_value_of_second_derivative() + m_value_of_second_derivative ;
+			}
+		
+			Vector get_prior_mode() const ;
+
+			Matrix get_prior_second_derivative() const {
+				return m_value_of_second_derivative ;
+			}
+
+			Matrix get_loglikelihood_second_derivative() const {
+				return m_ll->get_value_of_second_derivative() ;
+			}
+		
+			std::string get_summary() const ;
+			
+		private:
+			LogLikelihood::UniquePtr m_ll ;
+			std::vector< int > const m_parameter_indices ;
+			std::vector< double > const m_means ;
+			std::vector< double > const m_variances ;
+			Normalisation const m_normalisation ;
+			double m_constant ;
+			double m_value_of_function ;
+			Vector m_value_of_first_derivative ;
+			Matrix m_value_of_second_derivative ;
+		} ;
+	}
+}
+#endif

ADDED   metro/include/metro/regression/LogLikelihood.hpp
Index: metro/include/metro/regression/LogLikelihood.hpp
==================================================================
--- metro/include/metro/regression/LogLikelihood.hpp
+++ metro/include/metro/regression/LogLikelihood.hpp
@@ -0,0 +1,56 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_REGRESSION_LOG_LIKELIHOOD_HPP
+#define SNPTEST_REGRESSION_LOG_LIKELIHOOD_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "metro/SmoothFunction.hpp"
+#include "metro/regression/Design.hpp"
+
+namespace metro {
+	namespace regression {
+		/*
+		* Base class for classes implementing regression log-likelihoods
+		*/
+		struct LogLikelihood: public SmoothFunction
+		{
+		public:
+			typedef std::auto_ptr< LogLikelihood > UniquePtr ;
+			typedef regression::Design::Point Point ;
+			typedef regression::Design::Vector Vector ;
+			typedef regression::Design::RowVector RowVector ;
+			typedef regression::Design::Matrix Matrix ;
+			typedef Eigen::Matrix< int, Eigen::Dynamic, Eigen::Dynamic > IntegerMatrix ;
+		public:
+			virtual ~LogLikelihood() ;
+			virtual regression::Design& design() const = 0 ;
+			virtual std::string get_parameter_name( std::size_t i ) const = 0 ;
+			std::vector< std::string > get_parameter_names() const ;
+
+			virtual int number_of_parameters() const = 0 ;
+			virtual int number_of_outcomes() const = 0 ;
+			// Return a lx2 matrix identifying the l parameters.
+			// For each parameter the row contains:
+			// column 0: the index of the outcome column.
+			// column 1: the index of the design matrix column.
+			virtual IntegerMatrix identify_parameters() const = 0 ;
+
+			virtual void evaluate_at( Point const& parameters, int const numberOfDerivatives = 2 ) = 0 ;
+			virtual Point const& parameters() const = 0 ;
+			virtual double get_value_of_function() const = 0 ;
+			virtual Vector get_value_of_first_derivative() const = 0 ;
+			virtual Matrix get_value_of_second_derivative() const = 0 ;
+			
+			virtual std::string get_summary() const = 0 ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/regression/LogPosteriorDensity.hpp
Index: metro/include/metro/regression/LogPosteriorDensity.hpp
==================================================================
--- metro/include/metro/regression/LogPosteriorDensity.hpp
+++ metro/include/metro/regression/LogPosteriorDensity.hpp
@@ -0,0 +1,36 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_REGRESSION_LOG_POSTERIOR_DENSITY_HPP
+#define SNPTEST_REGRESSION_LOG_POSTERIOR_DENSITY_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "metro/regression/Design.hpp"
+
+#include "metro/regression/LogLikelihood.hpp"
+
+namespace metro {
+	namespace regression {
+		/*
+		*
+		* DEPRECATED: use LogUnnormalisedPosterior instead
+		*
+		* Base class for classes implementing regression log posterior densities
+		* These are prior / log-likelihood combinations that can unpack the contribution from likelihood and prior
+		*/
+		struct LogPosteriorDensity: public LogLikelihood
+		{
+			typedef std::auto_ptr< LogPosteriorDensity > UniquePtr ;
+			virtual Vector get_prior_mode() const = 0 ;
+			virtual Matrix get_loglikelihood_second_derivative() const = 0 ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/regression/LogUnnormalisedPosterior.hpp
Index: metro/include/metro/regression/LogUnnormalisedPosterior.hpp
==================================================================
--- metro/include/metro/regression/LogUnnormalisedPosterior.hpp
+++ metro/include/metro/regression/LogUnnormalisedPosterior.hpp
@@ -0,0 +1,64 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_REGRESSION_COMBINED_LOGLIKELIHOOD_PRIOR_HPP
+#define SNPTEST_REGRESSION_COMBINED_LOGLIKELIHOOD_PRIOR_HPP
+
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/SmoothFunction.hpp"
+
+namespace metro {
+	namespace regression {
+		/*
+		* Base class for classes implementing regression log posterior densities
+		* These are prior / log-likelihood combinations that can unpack the contribution from likelihood and prior
+		*/
+		struct LogUnnormalisedPosterior: public SmoothFunction
+		{
+		public:
+			typedef std::auto_ptr< LogUnnormalisedPosterior > UniquePtr ;
+			LogUnnormalisedPosterior( LogLikelihood& loglikelihood, SmoothFunction& posterior ) ;
+
+		public:
+			LogLikelihood const& ll() const ;
+			SmoothFunction const& prior() const ;
+			std::string get_summary() const ;
+			
+		public:
+			int number_of_parameters() const { return m_ll.number_of_parameters() ; }
+			
+			void evaluate_at( Vector const& parameters, int const numberOfDerivatives = 2 ) ;
+			void evaluate( int const numberOfDerivatives = 2 ) ;
+
+			Scalar get_value_of_function() const {
+				return m_ll.get_value_of_function() + m_prior.get_value_of_function() ;
+			}
+		
+			Vector get_value_of_first_derivative() const {
+				return m_ll.get_value_of_first_derivative() + m_prior.get_value_of_first_derivative() ;
+			}
+		
+			Matrix get_value_of_second_derivative() const {
+				return m_ll.get_value_of_second_derivative() + m_prior.get_value_of_second_derivative() ;
+			}
+		
+			Vector const& parameters() const {
+				return m_parameters ;
+			}
+
+			
+		private:
+			LogLikelihood& m_ll ;
+			SmoothFunction& m_prior ;
+			Vector m_parameters ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/regression/Logistic.hpp
Index: metro/include/metro/regression/Logistic.hpp
==================================================================
--- metro/include/metro/regression/Logistic.hpp
+++ metro/include/metro/regression/Logistic.hpp
@@ -0,0 +1,98 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_CASE_CONTROL_ASSOCIATION_LOG_LIKELIHOOD_HPP
+#define SNPTEST_CASE_CONTROL_ASSOCIATION_LOG_LIKELIHOOD_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+
+namespace metro {
+	namespace regression {
+		/*
+		* This class implements a log-likelihood for Bernoulli logistic regression, allowing predictors
+		* to take one of a finite set of values with associated probabilities. (A "missing data log-likelihood" ).
+		* The outcome must be a two-column matrix containing 0s and 1s; a 1 in the 2nd column indicates
+		* a non-baseline outcome and a 1 in the 1st column indicates a baseline outcome.
+		*/
+		struct Logistic: public LogLikelihood
+		{
+		public:
+			typedef regression::Design::Point Point ;
+			typedef regression::Design::Vector Vector ;
+			typedef regression::Design::RowVector RowVector ;
+			typedef regression::Design::Matrix Matrix ;
+			typedef Eigen::Block< Matrix > MatrixBlock ;
+			typedef Eigen::Block< Matrix const > ConstMatrixBlock ;
+			typedef boost::function< std::string( std::string const& predictor_name, std::string const& outcome_name ) > GetParameterName ;
+		public:
+			typedef std::auto_ptr< Logistic > UniquePtr ;
+			static UniquePtr create( Design& ) ;
+			static UniquePtr create( Design::UniquePtr ) ;
+			Logistic( Design& ) ;
+			Logistic( Design::UniquePtr ) ;
+			~Logistic() ;
+			
+			regression::Design& design() const { return *m_design ; }
+			void set_parameter_naming_scheme( GetParameterName ) ;
+			std::string get_parameter_name( std::size_t i ) const ;
+	
+			int number_of_parameters() const ;
+			int number_of_outcomes() const ;
+			IntegerMatrix identify_parameters() const ;
+
+			void evaluate_at( Point const& parameters, int const numberOfDerivatives = 2 ) ;
+			void evaluate( int const numberOfDerivatives = 2 ) ;
+
+			Point const& parameters() const ;
+			double get_value_of_function() const ;
+			Vector get_value_of_first_derivative() const ;
+			Matrix get_value_of_second_derivative() const ;
+			
+			std::string get_summary() const ;
+
+		private:
+			regression::Design* m_design ;
+			bool m_design_owned ;
+			GetParameterName m_get_parameter_name ;
+			Point m_parameters ;
+			std::vector< metro::SampleRange > m_included_samples ;
+			enum State {
+				e_Uncomputed = 0,
+				e_ComputedFunction = 1,
+				e_Computed1stDerivative = 2,
+				e_Computed2ndDerivative = 4
+			} ;
+			uint32_t m_state ;
+			Matrix m_outcome_probabilities ;
+			Matrix m_A ;
+			Matrix m_B ;
+			Vector m_temp ;
+			Matrix m_first_derivative_terms ;
+
+			double m_value_of_function ;
+			Vector m_value_of_first_derivative ;
+			Matrix m_value_of_second_derivative ;
+
+		private:
+			// Evaluate
+			void evaluate_at_impl( Point const& parameters, std::vector< metro::SampleRange > const& included_samples, int const numberOfDerivatives ) ;
+			// Calculate the probability of outcome given the genotype, parameters, and covariates.
+			Vector evaluate_mean_function( Vector const& linear_combinations, Matrix const& outcomes ) const ;
+			// Calculate matrix of probabilities of outcome per genotype, given the parameters.
+			void calculate_outcome_probabilities( Vector const& parameters, Matrix const& phenotypes, Matrix* result ) const ;
+			void compute_value_of_function( Matrix const& V, std::vector< metro::SampleRange > const& included_samples ) ;
+			void compute_value_of_first_derivative( Matrix const& A, std::vector< metro::SampleRange > const& included_samples, Matrix* B ) ;
+			void compute_value_of_second_derivative( Matrix const& B, std::vector< metro::SampleRange > const& included_samples ) ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/regression/MultinomialRegressionLogLikelihood.hpp
Index: metro/include/metro/regression/MultinomialRegressionLogLikelihood.hpp
==================================================================
--- metro/include/metro/regression/MultinomialRegressionLogLikelihood.hpp
+++ metro/include/metro/regression/MultinomialRegressionLogLikelihood.hpp
@@ -0,0 +1,148 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_CASE_CONTROL_MULTINOMIAL_LOG_LIKELIHOOD_HPP
+#define SNPTEST_CASE_CONTROL_MULTINOMIAL_LOG_LIKELIHOOD_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+
+namespace metro {
+	namespace regression {
+		/*
+		* This class implements a log-likelihood for multinomial logistic regression, allowing predictors
+		* to take one of a finite set of values with associated probabilities. (A "missing data log-likelihood" ).
+		* The outcome variables must form a contiguous set of numbers in the range 0,1,...,M
+		* for some positive integer M > 0.
+		*
+		* Notation:
+		* N - number of samples
+		* L - number of predictor levels
+		* M - number of outcome levels not counting the baseline.
+		* 
+		*/
+		struct MultinomialRegressionLogLikelihood: public LogLikelihood
+		{
+		public:
+			typedef regression::Design::Vector Vector ;
+			typedef regression::Design::RowVector RowVector ;
+			typedef regression::Design::Matrix Matrix ;
+			typedef Eigen::Block< Matrix > MatrixBlock ;
+			typedef Eigen::Block< Matrix const > ConstMatrixBlock ;
+			typedef Eigen::PermutationMatrix< Eigen::Dynamic, Eigen::Dynamic > PermutationMatrix ;
+			typedef boost::function< std::string( std::string const& predictor_name, int outcome_level ) > GetParameterName ;
+		public:
+			typedef std::auto_ptr< MultinomialRegressionLogLikelihood > UniquePtr ;
+			static UniquePtr create( regression::Design::UniquePtr ) ;
+			
+		public:
+			MultinomialRegressionLogLikelihood( regression::Design::UniquePtr ) ;
+
+			regression::Design& design() const { return *m_design ; }
+			void set_predictor_levels( Matrix const& levels, Matrix const& probabilities, std::vector< metro::SampleRange > const& included_samples ) ;
+		
+			void set_parameter_naming_scheme( GetParameterName ) ;
+			int number_of_parameters() const ;
+			int number_of_outcomes() const ;
+			std::string get_parameter_name( std::size_t i ) const ;		
+			IntegerMatrix identify_parameters() const ;
+			
+			void evaluate_at( Vector const& parameters, int const numberOfDerivatives = 2 ) ;
+			void evaluate( int const numberOfDerivatives = 2 ) ;
+
+			Vector const& parameters() const ;
+			double get_value_of_function() const ;
+			Vector get_value_of_first_derivative() const ;
+			Matrix get_value_of_second_derivative() const ;
+
+			std::string get_summary() const ;
+
+		private:
+			regression::Design::UniquePtr m_design ;
+			int const m_number_of_samples ;
+			GetParameterName m_get_parameter_name ;
+			Vector m_parameter_vector ;
+			Matrix m_parameter_matrix ;
+			IntegerMatrix m_parameter_identity ;
+			std::size_t m_numberOfDerivativesComputed ;
+
+			// rearranger.  This matrix rearranges columns of an NxLM matrix from L blocks of NxM to M blocks of NxL.
+			PermutationMatrix m_outcome_wise_to_predictor_wise_rearranger ;
+			// Psi matrix, (NxLM).  This represents phenotype data as indicator 1's in each row.
+			Matrix m_psi ;
+			// F matrix (Nx(L(M+1))).  Stores outcome probabilities.
+			Matrix m_F ;
+			// A matrix (NxL).  Stores outcome probabilities times predictor probability, renormalised.
+			Matrix m_A ;
+			// B matrix (Nx(LM)).  Used in the computation of 1st and 2nd derivatives.
+			Matrix m_B ;
+			// C matrix (Nx(LM^2)).  Used in the computation of 2nd derivative.
+			Matrix m_C ;
+			// temp matrix.  Stores the terms that are summed to make the 1st derivative
+			Matrix m_first_derivative_terms ;
+			// temp matrix.  Stores rows of the design matrix tensor squares.
+			mutable Matrix m_design_matrix_tensor_square_rows ;
+
+			double m_value_of_function ;
+			Vector m_value_of_first_derivative ;
+			Matrix m_value_of_second_derivative ;
+
+		private:
+			
+			void compute_psi(
+				Matrix const& outcome,
+				int const number_of_levels,
+				std::vector< metro::SampleRange > const& included_samples,
+				Matrix* result
+			) const ;
+			void compute_rearranger( int const number_of_predictor_levels, PermutationMatrix* result ) const ;
+			IntegerMatrix compute_parameter_identity() const ;
+
+			void evaluate_impl( int const numberOfDerivatives ) ;
+			void compute_F( Matrix const& parameters, Matrix* result ) const ;
+			void rearrange_F( Matrix* result ) const ;
+			void compute_A_and_function_value(
+				Matrix const& F,
+				Matrix const& predictor_probabilities,
+				std::vector< metro::SampleRange > const& included_samples,
+				Matrix* result,
+				double* value_of_function
+			) const ;
+			void compute_B(
+				Matrix const& A,
+				Matrix const& F,
+				Matrix const& psi,
+				Matrix* result
+			) const ;
+			void compute_value_of_first_derivative(
+				Matrix const& B,
+				std::vector< metro::SampleRange > const& included_samples,
+				Vector* result,
+				Matrix* terms
+			) const ;
+			// void compute_C( Matrix const& B, Matrix const& F, Matrix const& Gamma, Matrix* result ) const ;
+			void compute_C(
+				Matrix const& B,
+				Matrix const& F,
+				Matrix const& Gamma,
+				std::vector< metro::SampleRange > const& included_samples,
+				Matrix* result
+			) const ;
+			void compute_value_of_second_derivative(
+				Matrix const& B,
+				Matrix const& C,
+				std::vector< metro::SampleRange > const& included_samples,
+				Matrix* result
+			) const ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/regression/NormalWeightedLogLikelihood.hpp
Index: metro/include/metro/regression/NormalWeightedLogLikelihood.hpp
==================================================================
--- metro/include/metro/regression/NormalWeightedLogLikelihood.hpp
+++ metro/include/metro/regression/NormalWeightedLogLikelihood.hpp
@@ -0,0 +1,92 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef SNPTEST_REGRESSION_NORMAL_WEIGHTED_LOGLIKELIHOOD_HPP
+#define SNPTEST_REGRESSION_NORMAL_WEIGHTED_LOGLIKELIHOOD_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "Eigen/Cholesky"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+
+namespace metro {
+	namespace regression {
+		// Represents a log-likelihood function weighted by independent
+		// normal distributions on each parameter.
+		// by default variance=infinity, i.e. no weighting, and weighting
+		// must be set.
+		struct NormalWeightedLogLikelihood: public LogLikelihood {
+		public:
+			typedef std::auto_ptr< NormalWeightedLogLikelihood > UniquePtr ;
+			enum Normalisation { eNoConstantTerm = 0, eWithConstantTerm = 1 } ;
+			static UniquePtr create(
+				LogLikelihood::UniquePtr ll,
+				Vector const mean,
+				Matrix const covariance,
+				Normalisation normalisation = eWithConstantTerm
+			) ;
+				
+		public:
+			NormalWeightedLogLikelihood(
+				LogLikelihood::UniquePtr ll,
+				Vector const mean,
+				Matrix const covariance,
+				Normalisation normalisation = eWithConstantTerm
+			) ;
+			
+			regression::Design& design() const { return m_ll->design() ; }
+
+			int number_of_parameters() const ;
+			std::string get_parameter_name( std::size_t i ) const ;
+
+			int number_of_outcomes() const ;
+
+			// Return a lx2 matrix identifying the l parameters.
+			// The row for each parameter contains the outcome level and design matrix column for that parameter.
+			IntegerMatrix identify_parameters() const ;
+			
+			void evaluate_at( Point const& parameters, int const numberOfDerivatives = 2 ) ;
+			void evaluate( int const numberOfDerivatives = 2 ) ;
+
+			Point const& parameters() const {
+				return m_ll->parameters() ;
+			}
+
+			double get_value_of_function() const {
+				return m_ll->get_value_of_function() + m_log_density + ( (m_normalisation == eWithConstantTerm) ? m_constant : 0.0 ) ;
+			}
+
+			Vector get_value_of_first_derivative() const {
+				return m_ll->get_value_of_first_derivative() + m_value_of_first_derivative ;
+			}
+
+			Matrix get_value_of_second_derivative() const {
+				return m_ll->get_value_of_second_derivative() + m_value_of_second_derivative ;
+			}
+		
+			std::string get_summary() const ;
+				
+		private:
+			LogLikelihood::UniquePtr m_ll ;
+			Vector const m_mean ;
+			Matrix const m_covariance ;
+			Normalisation const m_normalisation ;
+			Eigen::LDLT< Matrix > m_solver ;
+			Matrix const m_inverse_covariance ;
+			double const m_constant ;
+			double m_log_density ;
+			Vector m_value_of_first_derivative ;
+			Matrix m_value_of_second_derivative ;
+			
+		private:
+			void evaluate_impl( int const numberOfDerivatives = 2 ) ;
+		} ;
+	}
+}
+#endif

ADDED   metro/include/metro/regression/ThreadedLogLikelihood.hpp
Index: metro/include/metro/regression/ThreadedLogLikelihood.hpp
==================================================================
--- metro/include/metro/regression/ThreadedLogLikelihood.hpp
+++ metro/include/metro/regression/ThreadedLogLikelihood.hpp
@@ -0,0 +1,78 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_REGRESSION_THREADED_LOG_LIKELIHOOD_HPP
+#define METRO_REGRESSION_THREADED_LOG_LIKELIHOOD_HPP
+
+#include <vector>
+#include <memory>
+#include <boost/noncopyable.hpp>
+#include <boost/ptr_container/ptr_vector.hpp>
+#include "Eigen/Core"
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/regression/Design.hpp"
+//#include "boost/threadpool.hpp"
+#include "metro/concurrency/threadpool.hpp"
+
+namespace metro {
+	namespace regression {
+		/*
+		* Base class for classes implementing regression log-likelihoods
+		*/
+		struct ThreadedLogLikelihood: public LogLikelihood
+		{
+		public:
+			typedef boost::function< LogLikelihood::UniquePtr ( regression::Design&, std::vector< metro::SampleRange > ) > CreateLL ;
+			//typedef std::auto_ptr< ThreadedLogLikelihood > UniquePtr ;
+
+			static UniquePtr create( Design& design, CreateLL, int number_of_threads ) ;
+			static UniquePtr create( Design::UniquePtr design, CreateLL, int number_of_threads ) ;
+			static UniquePtr create( Design& design, CreateLL, metro::concurrency::threadpool& pool ) ;
+			static UniquePtr create( Design::UniquePtr design, CreateLL, metro::concurrency::threadpool& pool ) ;
+
+		public:
+			~ThreadedLogLikelihood() ;
+			ThreadedLogLikelihood( Design& design, CreateLL, int number_of_threads ) ;
+			ThreadedLogLikelihood( Design::UniquePtr design, CreateLL, int number_of_threads ) ;
+			ThreadedLogLikelihood( Design& design, CreateLL, metro::concurrency::threadpool& pool ) ;
+			ThreadedLogLikelihood( Design::UniquePtr design, CreateLL, metro::concurrency::threadpool& pool ) ;
+
+			regression::Design& design() const { return *m_design ; } ;
+			std::string get_parameter_name( std::size_t i ) const ;
+			std::vector< std::string > get_parameter_names() const ;
+
+			// Return a lx2 matrix identifying the l parameters.
+			// For each parameter the row contains:
+			// column 0: the index of the outcome column.
+			// column 1: the index of the design matrix column.
+			int number_of_parameters() const ;
+			int number_of_outcomes() const ;
+			IntegerMatrix identify_parameters() const ;
+
+			void evaluate_at( Point const& parameters, int const numberOfDerivatives = 2 ) ;
+			void evaluate( int const numberOfDerivatives = 2 ) ;
+
+			Point const& parameters() const ;
+			double get_value_of_function() const ;
+			Vector get_value_of_first_derivative() const ;
+			Matrix get_value_of_second_derivative() const ;
+			
+			std::string get_summary() const ;
+		private:
+			regression::Design* m_design ;
+			bool const m_design_owned ;
+			metro::concurrency::threadpool* m_pool ;
+			bool m_pool_owned ;
+
+			boost::ptr_vector< metro::regression::LogLikelihood > m_lls ;
+
+		private:
+			void create_lls( CreateLL create_ll ) ;
+		} ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/summation.hpp
Index: metro/include/metro/summation.hpp
==================================================================
--- metro/include/metro/summation.hpp
+++ metro/include/metro/summation.hpp
@@ -0,0 +1,33 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef METRO_SUMMATION_HPP
+#define METRO_SUMMATION_HPP
+
+namespace metro {
+	template< typename Vector >
+	double naive_sum( Vector const& data ) {
+		return data.sum() ;
+	}
+
+	template< typename Vector >
+	double neumaier_sum( Vector const& data ) {
+		double sum = 0.0 ;
+		double c = 0.0 ;
+		for( int i = 0; i < data.size(); ++i ) {
+			double t = sum + data[i] ;
+			if( std::abs( sum ) > std::abs( data[i] ) ) {
+				c += (sum - t) + data[i] ;
+			} else {
+				c += (data[i] - t) + sum ;
+			}
+			sum = t ;
+		}
+		return( sum + c ) ;
+	}
+}
+
+#endif

ADDED   metro/include/metro/union_ranges.hpp
Index: metro/include/metro/union_ranges.hpp
==================================================================
--- metro/include/metro/union_ranges.hpp
+++ metro/include/metro/union_ranges.hpp
@@ -0,0 +1,30 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef CORE_UNION_RANGES_HPP
+#define CORE_UNION_RANGES_HPP
+
+#include <vector>
+#include "metro/SampleRange.hpp"
+
+namespace metro {
+	namespace impl {
+		// union two lists of ranges.
+		// each list is assumed to be a sorted list of non-intersecting ranges of integers.
+		// The result is also a sorted list of non-intersecting ranges.
+		std::vector< metro::SampleRange > union_ranges(
+			std::vector< metro::SampleRange > const& left,
+			std::vector< metro::SampleRange > const& right
+		) ;
+
+		std::vector< metro::SampleRange > union_ranges(
+			std::vector< metro::SampleRange > const& left,
+			metro::SampleRange const& right
+		) ;
+	}
+}
+
+#endif

ADDED   metro/src/CholeskyStepper.cpp
Index: metro/src/CholeskyStepper.cpp
==================================================================
--- metro/src/CholeskyStepper.cpp
+++ metro/src/CholeskyStepper.cpp
@@ -0,0 +1,97 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <utility>
+#include <Eigen/Core>
+#include <limits>
+#include <cassert>
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/ModifiedCholesky.hpp"
+#include "metro/ModifiedNewtonRaphson.hpp"
+#include "metro/CholeskyStepper.hpp"
+
+#define DEBUG 1
+
+namespace metro {
+	CholeskyStepper::CholeskyStepper( double tolerance, int max_iterations, Tracer tracer ):
+		m_tolerance( tolerance ),
+		m_max_iterations( max_iterations ),
+		m_tracer( tracer ),
+		m_iteration( -1 ),
+		m_target_ll( -std::numeric_limits< double >::infinity() )
+	{
+		assert( tolerance > 0 ) ;
+	}
+	
+	bool CholeskyStepper::step( Function& function, Vector* result ) {
+		++m_iteration ;
+		//std::cerr << "CholeskyStepper::step(): calling evaluate()...\n" ;
+		function.evaluate( 2 ) ;
+		double const ll = function.get_value_of_function() ;
+		m_solver.compute( -function.get_value_of_second_derivative() ) ;
+
+		// Different possible stopping conditions are possible.
+		// One is to stop when the predicted improvement in function
+		// value is small.  This amount is encoded by the directional derivative.
+		// However, for statistical model fitting we would like a rule that is invariant to
+		// various types of rescaling the function.  For example
+		// - scaling parameters (which scales the derivative)
+		// - multiplying the function by a constant (which is a bit like adding more data)
+		// A rule like directional_derivative < tolerance does not have these properties.
+
+		// Instead, we compute the derivative normalised to 'standard Gaussian' space.
+		// Theory: if the function 2nd derivative H = LLᵗ then Σ=(Lᵗ)⁻¹L⁻¹.
+		// We assume the log-likelihood looks like this:
+		// f(x) = s(Lᵗ(x-x₀)) + O((x-x₀)³)
+		// near the true maximum x₀, where s is the standard multivariate normal
+		// log-density.  Then
+		// f'(x) = -L Lᵗ (x-x₀) + O((x-x₀)²)   (expressed as a column vector).
+		// We put a convergence condition on the corresponding derivative in s-space, given by
+		// z = L⁻¹ f'(x) = -Lᵗ(x-x₀) + O((x-x₀)²)
+		// This has the nice interpretation of being interpretable as a distance
+		// to the maximum in the uncorrelated-variable space that is the domain of s.
+
+		double const derivativeOneNorm = function.get_value_of_first_derivative().array().abs().maxCoeff() ;
+		Vector step = m_solver.solve( function.get_value_of_first_derivative() ) ;
+		//Vector const sqrtStep = m_solver.halfSolve( function.get_value_of_first_derivative() ) ;
+		double directional_derivative = function.get_value_of_first_derivative().transpose() * step ;
+
+		bool converged = (
+			(derivativeOneNorm < m_tolerance)
+			&& ( ll >= ( m_target_ll - m_tolerance ) )
+			//&& (sqrtStep.array().abs().maxCoeff() < m_tolerance )
+			&& (directional_derivative < m_tolerance )
+		) ;
+
+		if( m_tracer ) {
+			m_tracer( m_iteration, ll, m_target_ll, function.parameters(), function.get_value_of_first_derivative(), step, converged ) ;
+		}
+
+		if(
+			converged || (m_iteration) >= m_max_iterations 
+		) {
+			return false ;
+		} else {
+			(*result) = step ;
+			m_target_ll = std::max( m_target_ll, ll ) ;
+			return true ;
+		}
+	}
+	
+	bool CholeskyStepper::diverged() const {
+		return m_iteration >= m_max_iterations || m_target_ll != m_target_ll ;
+	}
+
+	std::size_t CholeskyStepper::number_of_iterations() const {
+		return m_iteration ;
+	}
+
+	void CholeskyStepper::reset() {
+		m_iteration = -1 ;
+		m_target_ll = -std::numeric_limits< double >::infinity() ;
+	}
+}

Index: metro/src/DataSubset.cpp
==================================================================
--- metro/src/DataSubset.cpp
+++ metro/src/DataSubset.cpp
@@ -8,45 +8,10 @@
 #include <algorithm>
 #include "metro/DataRange.hpp"
 #include "metro/DataSubset.hpp"
 
 namespace metro {
-
-#if 0
-	void DataSubset::add( DataRange const& other ) {
-		std::vector< DataRange > newRep ;
-		Rep::const_iterator i = m_rep.begin() ;
-		for(
-			;
-			i != m_rep.end() && i->end() < other.begin();
-			++i
-		) ;
-		std::copy( m_rep.begin(), i, std::back_inserter< newRep >() ) ;
-		int begin = other.begin() ;
-		int end = other.end() ;
-		for(
-			;
-			i != m_rep.end() && i->begin() < other.end();
-			++i
-		) {
-			begin = std::min( begin, i->begin() ) ;
-			end = std::max( end, i->end() ) ;
-		}
-
-
-
-		for( std::size_t i = 0; i < m_rep.size() && ; ++i ) {
-
-			if( m_rep[i].end() < m_rep[i].begin() || m_rep[i].begin() > m_rep[i].end() ) {
-				end = i ;
-			} else {
-				// join
-			}
-		}
-	}
-#endif
-	
 	void DataSubset::add( DataSubset const& other ) {
 		m_rep.insert( m_rep.end(), other.m_rep.begin(), other.m_rep.end() ) ;
 		std::sort( m_rep.begin(), m_rep.end() ) ;
 		// Now join ranges that need to be joined.
 		m_size = 0 ;

ADDED   metro/src/Error.cpp
Index: metro/src/Error.cpp
==================================================================
--- metro/src/Error.cpp
+++ metro/src/Error.cpp
@@ -0,0 +1,33 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include "metro/Error.hpp"
+
+namespace metro {
+	ModelFitError::ModelFitError( std::string const& caller, std::string const& reason ):
+			m_caller( caller ),
+			m_reason( reason )
+	{}
+
+	ModelFitError::~ModelFitError() throw() {}
+
+	char const* ModelFitError::what() const throw() {
+		return "ModelFitError" ;
+	}
+
+	std::string const& ModelFitError::get_caller() const {
+		return m_caller ;
+	}
+	std::string const& ModelFitError::get_reason() const {
+		return m_reason ;
+	}
+	
+	std::string NumericalError::format_message() const {
+		return std::string( what() ) + ": " + m_source + ": " + m_message ;
+	}
+}
+

ADDED   metro/src/IndependentParameterDistribution.cpp
Index: metro/src/IndependentParameterDistribution.cpp
==================================================================
--- metro/src/IndependentParameterDistribution.cpp
+++ metro/src/IndependentParameterDistribution.cpp
@@ -0,0 +1,92 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <exception>
+#include "Eigen/Core"
+#include "metro/distributions/Flat.hpp"
+#include "metro/IndependentParameterDistribution.hpp"
+
+namespace metro {
+	IndependentParameterDistribution::UniquePtr IndependentParameterDistribution::create(
+		std::vector< std::string > const& parameter_names
+	) {
+		return IndependentParameterDistribution::UniquePtr(
+			new IndependentParameterDistribution( parameter_names )
+		) ;
+	}
+	
+	IndependentParameterDistribution::IndependentParameterDistribution(
+		std::vector< std::string > const& parameter_names
+	):
+		m_parameter_names( parameter_names )
+	{
+		for( std::size_t i = 0; i < m_parameter_names.size(); ++i ) {
+			m_parameter_name_indices[ m_parameter_names[i] ] = i ;
+			m_densities.push_back( new metro::distributions::Flat() ) ;
+		}
+	}
+	
+	void IndependentParameterDistribution::set_prior( std::string const& name, UnivariateLogDensity::UniquePtr pdf ) {
+		ParameterNameIndices::const_iterator where = m_parameter_name_indices.find( name ) ;
+		if( where == m_parameter_name_indices.end() ) {
+			throw std::invalid_argument( "Unexpected parameter \"" + name + "\"." ) ;
+		}
+		std::size_t const i = m_parameter_name_indices[name] ;
+		m_densities.replace( i, pdf.release() ) ;
+	}
+	
+	int IndependentParameterDistribution::number_of_parameters() const {
+		return m_parameter_names.size() ;
+	};
+
+	void IndependentParameterDistribution::evaluate_at(
+		Point const& parameters,
+		int const numberOfDerivatives
+	) {
+		m_parameters = parameters ;
+		evaluate() ;
+	}
+
+	void IndependentParameterDistribution::evaluate( int const ) {
+		for( std::size_t i = 0; i < m_densities.size(); ++i ) {
+			m_densities[i].evaluate_at( m_parameters(i) ) ;
+		}
+	}
+	
+	double IndependentParameterDistribution::get_value_of_function() const {
+		double result = 0.0 ;
+		for( std::size_t i = 0; i < m_densities.size(); ++i ) {
+			result += m_densities[i].get_value_of_function() ;
+		}
+		return result ;
+	}
+	
+	IndependentParameterDistribution::Vector IndependentParameterDistribution::get_value_of_first_derivative() const {
+		Vector result = Vector::Zero( m_parameters.size() ) ;
+		for( std::size_t i = 0; i < m_densities.size(); ++i ) {
+			result(i) = m_densities[i].get_value_of_first_derivative() ;
+		}
+		return result ;
+	}
+	
+	IndependentParameterDistribution::Matrix IndependentParameterDistribution::get_value_of_second_derivative() const {
+		Matrix result = Matrix::Zero( m_parameters.size(), m_parameters.size() ) ;
+		for( std::size_t i = 0; i < m_densities.size(); ++i ) {
+			result(i,i) = m_densities[i].get_value_of_second_derivative() ;
+		}
+		return result ;
+	}
+	
+	std::string IndependentParameterDistribution::get_summary() const {
+		std::string result = "per-parameter priors:\n" ;
+		for( std::size_t i = 0; i < m_parameter_names.size(); ++i ) {
+			std::string const& name = m_parameter_names[i] ;
+			ParameterNameIndices::const_iterator where = m_parameter_name_indices.find( name ) ;
+			result += ((i>0) ? "\n        " : "        " ) + name + ": " + m_densities[where->second].get_summary() ;
+		}
+		return result ;
+	}
+}

ADDED   metro/src/SampleRange.cpp
Index: metro/src/SampleRange.cpp
==================================================================
--- metro/src/SampleRange.cpp
+++ metro/src/SampleRange.cpp
@@ -0,0 +1,57 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <cassert>
+#include <iostream>
+#include "metro/SampleRange.hpp"
+
+namespace metro {
+	SampleRange::SampleRange():
+		m_begin( 0 ),
+		m_end( 0 )
+	{}
+
+	SampleRange::SampleRange( SampleRange const& other ):
+		m_begin( other.m_begin ),
+		m_end( other.m_end )
+	{}
+
+	SampleRange::SampleRange( int begin, int end ):
+		m_begin( begin ),
+		m_end( end )
+	{
+		assert( m_end >= m_begin ) ;
+	}
+
+	SampleRange& SampleRange::operator=( SampleRange const& other ) {
+		m_begin = other.m_begin ;
+		m_end = other.m_end ;
+		return *this ;
+	}
+
+	bool operator== ( SampleRange const& left, SampleRange const& right ) {
+		return right.begin() == left.begin() && right.end() == left.end() ;
+	}
+	
+	bool operator< ( SampleRange const& left, SampleRange const& right ) {
+		return
+			( left.begin() < right.begin() )
+			| 
+			( left.begin() == right.begin() && left.end() < right.end() )
+		;
+	}
+	
+	std::ostream& operator<<( std::ostream& out, SampleRange const& range ) {
+		return out << "[" << range.begin() << "-" << range.end() << ")" ;
+	}
+
+	std::ostream& operator<<( std::ostream& out, std::vector< SampleRange > const& ranges ) {
+		for( std::size_t i = 0; i < ranges.size(); ++i ) {
+			out << (i>0?",":"" ) << ranges[i] ;
+		}
+		return out ;
+	}
+}

ADDED   metro/src/SampleStratification.cpp
Index: metro/src/SampleStratification.cpp
==================================================================
--- metro/src/SampleStratification.cpp
+++ metro/src/SampleStratification.cpp
@@ -0,0 +1,83 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <vector>
+#include <map>
+#include <cassert>
+#include <iostream>
+#include <iomanip>
+#include "metro/SampleRange.hpp"
+#include "metro/SampleStratification.hpp"
+#include "metro/union_ranges.hpp"
+#include "genfile/Error.hpp"
+
+namespace metro {
+	SampleStratification::SampleStratification() {}
+	SampleStratification::SampleStratification( SampleStratification const& other ):
+		m_strata_names( other.m_strata_names ),
+		m_index_by_strata( other.m_index_by_strata ),
+		m_sample_ranges( other.m_sample_ranges )
+	{}
+	
+	SampleStratification& SampleStratification::operator=( SampleStratification const& other ) {
+		m_strata_names = other.m_strata_names ;
+		m_index_by_strata = other.m_index_by_strata ;
+		m_sample_ranges = other.m_sample_ranges ;
+		return *this ;
+	}
+
+	void SampleStratification::add_stratum( std::string const& name ) {
+		if( m_index_by_strata.find( name ) != m_index_by_strata.end() ) {
+			throw genfile::BadArgumentError( "core::SampleStratification::add_stratum()", "name=\"" + name + "\" (already in index)" ) ;
+		}
+		m_strata_names.push_back( name ) ;
+		m_sample_ranges.push_back( std::vector< metro::SampleRange >() ) ;
+		m_index_by_strata[ name ] = m_strata_names.size() - 1 ;
+	}
+
+	void SampleStratification::add_sample( std::string const& strata_name, int sample ) {
+		return add_sample_range( strata_name, metro::SampleRange( sample, sample + 1 ) ) ;
+	}
+
+	void SampleStratification::add_sample_range( std::string const& strata_name, metro::SampleRange const& range ) {
+		std::map< std::string, std::size_t >::const_iterator where = m_index_by_strata.find( strata_name ) ;
+		if( where == m_index_by_strata.end() ) {
+			add_stratum( strata_name ) ;
+			where = m_index_by_strata.find( strata_name ) ;
+			assert( where != m_index_by_strata.end() ) ;
+		}
+		std::size_t const stratum_i = where->second ;
+		m_sample_ranges[ stratum_i ] = impl::union_ranges( m_sample_ranges[ stratum_i ], range ) ;
+	}
+	
+	std::string const& SampleStratification::stratum_name( std::size_t i ) const {
+		assert( i < m_strata_names.size() ) ;
+		return m_strata_names[i] ;
+	}
+	
+	std::vector< metro::SampleRange > const& SampleStratification::stratum( std::size_t i ) const {
+		assert( i < m_strata_names.size() ) ;
+		return m_sample_ranges[ i ] ;
+	}
+
+	std::vector< metro::SampleRange > const& SampleStratification::stratum( std::string const& strata_name ) const {
+		std::map< std::string, std::size_t >::const_iterator where = m_index_by_strata.find( strata_name ) ;
+		if( where == m_index_by_strata.end() ) {
+			throw genfile::BadArgumentError( "core::SampleStratification::stratum()", "strata_name=\"" + strata_name + "\"", "no such strata" ) ;
+		}
+		return m_sample_ranges[ where->second ] ;
+	}
+
+
+	std::ostream& operator<<( std::ostream& o, SampleStratification const& stratification ) {
+		for( std::size_t i = 0; i < stratification.size(); ++i ) {
+			o << std::setw(12) << stratification.stratum_name( i ) << ": "
+				<< stratification.stratum(i) << "\n" ;
+		}
+		return o ;
+	}
+}

ADDED   metro/src/ShotgunStochasticSearch.cpp
Index: metro/src/ShotgunStochasticSearch.cpp
==================================================================
--- metro/src/ShotgunStochasticSearch.cpp
+++ metro/src/ShotgunStochasticSearch.cpp
@@ -0,0 +1,160 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include "metro/ShotgunStochasticSearch.hpp"
+
+// #define DEBUG 1
+
+namespace metro {
+#if DEBUG
+	namespace {
+		std::ostream& operator<<( std::ostream& out, std::vector< std::size_t > const& states ) {
+			out << "[" ;
+			for( std::size_t j = 0; j < states.size(); ++j ) {
+				out << ((j>0)?",":"") << states[j] ;
+			}
+			return out << "]" ;
+		}
+	}
+#endif
+	
+	ShotgunStochasticSearch::ShotgunStochasticSearch(
+		std::size_t n,
+		ShotgunStochasticSearch::ComputeLL compute_ll,
+		std::uint32_t rng_seed
+	):
+		m_N(n),
+		m_compute_ll( compute_ll ),
+		m_rng( rng_seed )
+	{
+		assert( m_compute_ll ) ;
+		m_lls.insert( std::make_pair( m_current_state, m_compute_ll( m_current_state ))) ;
+	}
+	
+	ShotgunStochasticSearch::SelectedStates const& ShotgunStochasticSearch::update() {
+		// sample states...
+		std::size_t count = 0 ;
+	
+		std::vector< SelectedStates > new_states ;
+#if DEBUG
+		std::cerr << "Current state: " << m_current_state.size() << "elts: " << m_current_state << ".\n" ;
+#endif
+		generate_deletions( &new_states ) ;
+		generate_additions_and_changes( &new_states ) ;
+#if DEBUG
+		std::cerr << "Generated " << new_states.size() << "new states:\n" ;
+		for( std::size_t i = 0; i < new_states.size(); ++i ) {
+			std::cerr << " -- " << new_states[i] << "\n" ;
+		}
+#endif
+
+		std::vector< double > lls( new_states.size(), 0 ) ;
+		for( std::size_t i = 0; i < new_states.size(); ++i ) {
+			Store::const_iterator where = m_lls.find( new_states[i] ) ;
+			if( where == m_lls.end() ) {
+				lls[i] = m_compute_ll( new_states[i] ) ;
+				m_lls.insert( std::make_pair( new_states[i], lls[i] ) ) ;
+#if DEBUG
+				std::cerr << "INSERTED: " << new_states[i] << ", " << lls[i] << ".\n" ;
+#endif
+			} else {
+				lls[i] = where->second ;
+			}
+		}
+
+		// Values are assumed to be on log scale
+		double const max_ll = *std::max_element( lls.begin(), lls.end() ) ;
+#if DEBUG
+		std::cerr << "ShotgunStochasticSearch::update(): Maximum likelihood is " << max_ll << ".\n" ;
+#endif
+		for( std::size_t i = 0; i < lls.size(); ++i ) {
+			lls[i] = std::exp( lls[i] - max_ll ) ;
+		}
+#if DEBUG
+		for( std::size_t i = 0; i < std::min( lls.size(), 10ul ); ++i ) {
+			std::cerr << "LLs[" << i << "] = " << lls[i] << "\n" ;
+		}
+#endif
+		boost::random::discrete_distribution< std::size_t, double > dist( lls ) ;
+		m_current_state = new_states[ dist(m_rng) ] ;
+		
+		return m_current_state ;
+	}
+
+	ShotgunStochasticSearch::Store const& ShotgunStochasticSearch::visited_states() const {
+		return m_lls ;
+	}
+	
+	void ShotgunStochasticSearch::visited_states( boost::function< void( SelectedStates const&, double ) > callback ) const {
+		Store::const_iterator i = m_lls.begin() ;
+		Store::const_iterator end = m_lls.end() ;
+		for( ; i != end; ++i ) {
+			callback( i->first, i->second ) ;
+		}
+	}
+	
+	
+	void ShotgunStochasticSearch::generate_deletions(
+		std::vector< ShotgunStochasticSearch::SelectedStates >* result
+	) {
+		SelectedStates new_state ;
+		// deletions...
+		for( std::size_t i = 0; i < m_current_state.size(); ++i ) {
+			new_state.resize( m_current_state.size() - 1 ) ;
+			std::copy( m_current_state.begin(), m_current_state.begin() + i, new_state.begin() ) ;
+			std::copy( m_current_state.begin() + i + 1, m_current_state.end(), new_state.begin() + i ) ;
+			result->push_back( new_state ) ;
+		}
+	}
+
+	void ShotgunStochasticSearch::generate_additions_and_changes(
+		std::vector< ShotgunStochasticSearch::SelectedStates >* result
+	) {
+		SelectedStates new_addition_state( m_current_state.size() + 1 ) ;
+		SelectedStates new_change_state( m_current_state.size() ) ;
+		std::size_t begin_addition = 0 ;
+		std::size_t end_addition = 0 ;
+	
+		SelectedStates::const_iterator const begin_i = m_current_state.begin() ;
+		SelectedStates::const_iterator const end_i = m_current_state.end() ;
+		for( std::size_t i = 0; i <= m_current_state.size(); ++i, begin_addition = end_addition + 1 ) {
+			end_addition = (i == m_current_state.size()) ? m_N : m_current_state[i] ;
+			for( std::size_t a = begin_addition; a < end_addition; ++a ) {
+				// In this loop, a will visit everything that can be added
+				// and i will point to the element of current state that follows a.
+
+				// Build the addition states
+				std::copy( begin_i, begin_i + i, new_addition_state.begin() ) ;
+				new_addition_state[i] = a ;
+				std::copy( begin_i + i, end_i, new_addition_state.begin() + i + 1 ) ;
+				result->push_back( new_addition_state ) ;
+			
+				// Build the change states
+				{
+					std::size_t k = 0 ;
+					for( ; k < i; ++k ) {
+						std::copy( begin_i, begin_i + k, new_change_state.begin() ) ;
+						std::copy( begin_i + k + 1, begin_i + i, new_change_state.begin() + k ) ;
+						new_change_state[i-1] = a ;
+						std::copy( begin_i + i, end_i, new_change_state.begin() + i ) ;
+						result->push_back( new_change_state ) ;
+					}
+					for( ; k < m_current_state.size(); ++k ) {
+						std::copy( begin_i, begin_i + i, new_change_state.begin() ) ;
+						new_change_state[i] = a ;
+						std::copy( begin_i + i, begin_i + k, new_change_state.begin() + i + 1 ) ;
+						std::copy( begin_i + k + 1, end_i, new_change_state.begin() + k + 1 ) ;
+						result->push_back( new_change_state ) ;
+					}
+				}
+			}
+		}
+	}
+}
+
+
+

ADDED   metro/src/UnivariateLogDensity.cpp
Index: metro/src/UnivariateLogDensity.cpp
==================================================================
--- metro/src/UnivariateLogDensity.cpp
+++ metro/src/UnivariateLogDensity.cpp
@@ -0,0 +1,13 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include "metro/UnivariateLogDensity.hpp"
+#include <memory>
+
+namespace metro {
+	UnivariateLogDensity::~UnivariateLogDensity() {}
+}
+

ADDED   metro/src/concurrency/threadpool.cpp
Index: metro/src/concurrency/threadpool.cpp
==================================================================
--- metro/src/concurrency/threadpool.cpp
+++ metro/src/concurrency/threadpool.cpp
@@ -0,0 +1,86 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <deque>
+#include <thread>
+#include <condition_variable>
+#include <mutex>
+#include <functional>
+#include "metro/concurrency/threadpool.hpp"
+
+// #define DEBUG 1
+namespace metro {
+	namespace concurrency {
+		threadpool::UniquePtr threadpool::create( int number_of_threads ) {
+			return threadpool::UniquePtr(
+				new threadpool( number_of_threads )
+			) ;
+		}
+
+		threadpool::threadpool( int number_of_threads ):
+			m_running_tasks( 0 ),
+			m_stop( false )
+		{
+			for( int i = 0; i < number_of_threads; ++i ) {
+				m_threads.emplace_back(
+					std::bind( &threadpool::thread_loop, this )
+				) ;
+			}
+		}
+		
+		threadpool::~threadpool() {
+			// set stop-condition
+			std::unique_lock< std::mutex > lock( m_queue_mutex ) ;
+			m_stop = true;
+			m_task_available.notify_all();
+			lock.unlock();
+
+			// all threads terminate, then we're done.
+			for ( auto& thread : m_threads ) {
+				thread.join() ;
+			}
+		}
+		
+		void threadpool::wait()
+		{
+			std::unique_lock< std::mutex > lock( m_queue_mutex );
+			m_task_finished.wait(
+				lock,
+				[this](){ return m_tasks.empty() && (m_running_tasks == 0); }
+			);
+		}
+
+		void threadpool::thread_loop() {
+			while(1) {
+				std::unique_lock<std::mutex> lock( m_queue_mutex ) ;
+				m_task_available.wait(
+					lock,
+					[this](){ return m_stop || !m_tasks.empty(); }
+				) ;
+				if( !m_tasks.empty() ) {
+					++m_running_tasks;
+
+					auto task = m_tasks.front();
+					m_tasks.pop_front();
+
+					{
+						lock.unlock();
+						task();
+					}
+
+					lock.lock();
+					--m_running_tasks;
+					if( m_running_tasks == 0 && m_tasks.size() == 0 ) {
+						lock.unlock() ;
+						m_task_finished.notify_one() ;
+					}
+				} else if( m_stop ) {
+					break;
+				}
+			}
+		}
+	}
+}

ADDED   metro/src/count_range.cpp
Index: metro/src/count_range.cpp
==================================================================
--- metro/src/count_range.cpp
+++ metro/src/count_range.cpp
@@ -0,0 +1,25 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include <algorithm>
+#include "metro/SampleRange.hpp"
+#include "metro/count_range.hpp"
+
+namespace metro {
+	namespace impl {
+		int count_range(
+			std::vector< metro::SampleRange > const& range
+		) {
+			int result = 0 ;
+			for( std::size_t i = 0; i < range.size(); ++i ) {
+				result += range[i].size() ;
+			}
+			return result ;
+		}
+	}
+}
+

ADDED   metro/src/distributions/Flat.cpp
Index: metro/src/distributions/Flat.cpp
==================================================================
--- metro/src/distributions/Flat.cpp
+++ metro/src/distributions/Flat.cpp
@@ -0,0 +1,23 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <memory>
+#include "metro/UnivariateLogDensity.hpp"
+#include "metro/distributions/Flat.hpp"
+
+namespace metro {
+	namespace distributions {
+		Flat::UniquePtr create() {
+			return Flat::UniquePtr( new Flat ) ;
+		}
+		
+		std::string Flat::get_summary() const {
+			return "flat" ;
+		}
+	}
+}
+

ADDED   metro/src/distributions/LogF.cpp
Index: metro/src/distributions/LogF.cpp
==================================================================
--- metro/src/distributions/LogF.cpp
+++ metro/src/distributions/LogF.cpp
@@ -0,0 +1,54 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <cmath>
+#include <cassert>
+#include <boost/format.hpp>
+#include "metro/distributions/LogF.hpp"
+
+namespace metro {
+	namespace distributions {
+		LogF::UniquePtr LogF::create( double nu1, double nu2 ) {
+			return LogF::UniquePtr( new LogF( nu1, nu2 )) ;
+		}
+
+		LogF::LogF( double nu1, double nu2 ):
+			m_alpha( nu1 / 2 ),
+			m_beta( nu2 / 2 ),
+			m_constant(0)
+		{
+			m_constant = -(m_alpha + m_beta) * std::log(0.5) ;
+		}
+		
+		LogF::LogF( LogF const& other ):
+			m_alpha( other.m_alpha ),
+			m_beta( other.m_beta ),
+			m_constant( other.m_constant )
+		{}
+			
+		LogF& LogF::operator=( LogF const& other ) {
+			m_alpha = other.m_alpha ;
+			m_beta = other.m_beta ;
+			m_constant = other.m_constant ;
+			return *this ;
+		}
+		
+
+		void LogF::evaluate_at( double x ) {
+			double const l = 1.0 / (1.0 + std::exp(-x)) ;
+			m_value_of_function = m_constant + ( m_alpha * std::log(l) + m_beta * std::log( 1-l ) );
+			m_value_of_first_derivative = m_alpha - (m_alpha + m_beta) * l ;
+			m_value_of_second_derivative = -(m_alpha + m_beta) * l * (1-l) ;
+		}
+		
+		std::string LogF::get_summary() const {
+			return(
+				boost::format( "logF( %.5d, %.5d )" ) % (m_alpha*2) % (m_beta*2)
+			).str() ;
+		}
+	}
+}

ADDED   metro/src/fit_model.cpp
Index: metro/src/fit_model.cpp
==================================================================
--- metro/src/fit_model.cpp
+++ metro/src/fit_model.cpp
@@ -0,0 +1,74 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <utility>
+#include <Eigen/Core>
+#include <limits>
+#include <cassert>
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/ModifiedCholesky.hpp"
+#include "metro/ModifiedNewtonRaphson.hpp"
+#include "metro/fit_model.hpp"
+
+#define USE_MODIFIED_NR 1
+#define DEBUG 1
+
+namespace metro {
+	Stepper::~Stepper() {}
+
+	std::pair< bool, int > fit_model(
+		metro::SmoothFunction& ll,
+		std::string const& model_name,
+		Eigen::VectorXd const& starting_point,
+		Stepper& stopping_condition,
+		std::vector< std::string >* comments
+	) {
+		typedef metro::regression::Design::Matrix Matrix ;
+		// Fit null model
+		assert( starting_point.size() == ll.number_of_parameters() ) ;
+		ll.evaluate_at( starting_point ) ;
+
+		bool success = true ;
+		int iterations = 0 ;
+		// Compute negative definiteness condition number.
+		Eigen::SelfAdjointEigenSolver< Matrix > eigenSolver( ll.get_value_of_second_derivative() ) ;
+		if( eigenSolver.eigenvalues().maxCoeff() > 0 ) {
+			success = false ;
+			if( comments ) {
+				comments->push_back( model_name + ":not-negative-definite" ) ;
+			}
+		} else {
+#if 1
+			Eigen::VectorXd parameters = metro::find_maximum_by_modified_newton_raphson_with_line_search(
+				ll, starting_point, stopping_condition
+			) ;
+#else
+			metro::Snptest25StoppingCondition< metro::regression::LogLikelihood > stopping_condition(
+				ll,
+				0.01,
+				100,
+				0
+				//&get_ui_context().logger()
+			) ;
+
+			Eigen::ColPivHouseholderQR< Matrix > solver ;
+			Eigen::VectorXd parameters = maximise_by_newton_raphson( ll, starting_point, stopping_condition, solver ) ;
+#endif
+
+			if( stopping_condition.diverged() ) {
+				if( comments ) {
+					comments->push_back( model_name + ":model_fit_error:failed_to_converge_to_mle" ) ;
+				}
+			}
+
+			success = !stopping_condition.diverged() ;
+			iterations = stopping_condition.number_of_iterations() ;
+		}
+
+		return std::make_pair( success, iterations ) ;
+	}
+}

ADDED   metro/src/intersect_ranges.cpp
Index: metro/src/intersect_ranges.cpp
==================================================================
--- metro/src/intersect_ranges.cpp
+++ metro/src/intersect_ranges.cpp
@@ -0,0 +1,55 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include "metro/SampleRange.hpp"
+#include "metro/intersect_ranges.hpp"
+
+namespace metro {
+	namespace impl {
+		std::vector< metro::SampleRange > intersect_ranges(
+			std::vector< metro::SampleRange > const& left,
+			std::vector< metro::SampleRange > const& right
+		) {
+			std::vector< metro::SampleRange > result ;
+			std::size_t i = 0, j = 0 ;
+			while( i < left.size() && j < right.size() ) {
+				int range_start = std::max( left[i].begin(), right[j].begin() ) ;
+				int range_end = std::min( left[i].end(), right[j].end() ) ;
+				if( range_end > range_start ) {
+					result.push_back( metro::SampleRange( range_start, range_end )) ;
+				}
+				if( left[i].end() == range_end ) {
+					++i ;
+				}
+				if( right[j].end() == range_end ) {
+					++j ;
+				}
+			}
+			return result ;
+		}
+		
+		std::vector< metro::SampleRange > intersect_ranges(
+			metro::SampleRange const& left,
+			std::vector< metro::SampleRange > const& right
+		) {
+			return intersect_ranges(
+				std::vector< metro::SampleRange >( 1, left ),
+				right
+			) ;
+		}
+
+		std::vector< metro::SampleRange > intersect_ranges(
+			std::vector< metro::SampleRange > const& left,
+			metro::SampleRange const& right
+		) {
+			return intersect_ranges(
+				left,
+				std::vector< metro::SampleRange >( 1, right )
+			) ;
+		}
+	}
+}

Index: metro/src/log_sum_exp.cpp
==================================================================
--- metro/src/log_sum_exp.cpp
+++ metro/src/log_sum_exp.cpp
@@ -4,14 +4,34 @@
 //    (See accompanying file LICENSE_1_0.txt or copy at
 //          http://www.boost.org/LICENSE_1_0.txt)
 
 #include <math.h>
 #include <cassert>
+#include <vector>
+#include <algorithm>
 #include <Eigen/Core>
 #include "metro/log_sum_exp.hpp"
 
 namespace metro {
+	template<>
+	double log_sum_exp( std::vector< double > const& data ) {
+		if( data.size() == 0 ) {
+			return -std::numeric_limits< double >::infinity() ;
+		}
+		std::vector< double >::const_iterator max_i = std::max_element( data.begin(), data.end() ) ;
+		double const max_value = *max_i ;
+		if( max_value == -std::numeric_limits< double >::infinity() ) {
+			return max_value ;
+		}
+		// exponentiate
+		double result = max_value ;
+		for( std::size_t i = 0; i < data.size(); ++i ) {
+			result += std::exp(data[i] - max_value) ;
+		}
+		return max_value + std::log( result ) ;
+	}
+	
 	void rowwise_log_sum_exp( Eigen::MatrixXd const& data, Eigen::VectorXd* result ) {
 		assert( result ) ;
 		assert( result->size() == data.rows() ) ;
 
 		for( int i = 0; i < result->size(); ++i ) {

ADDED   metro/src/regression/BinomialLogistic.cpp
Index: metro/src/regression/BinomialLogistic.cpp
==================================================================
--- metro/src/regression/BinomialLogistic.cpp
+++ metro/src/regression/BinomialLogistic.cpp
@@ -0,0 +1,660 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <utility>
+#include <algorithm>
+#include <boost/format.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+#include "metro/regression/BinomialLogistic.hpp"
+#include "metro/intersect_ranges.hpp"
+#include "metro/count_range.hpp"
+#include "metro/summation.hpp"
+#include "genfile/string_utils.hpp"
+#include "genfile/Error.hpp"
+
+// #define DEBUG_LOGLIKELIHOOD 1
+
+namespace metro {
+	namespace regression {
+		namespace {
+			std::string standard_parameter_name( std::string const& predictor_name, std::string const& outcome_name ) {
+				return predictor_name + "/" + outcome_name ;
+			}
+		}
+		
+		BinomialLogistic::UniquePtr BinomialLogistic::create(
+			regression::Design& design
+		) {
+			return BinomialLogistic::UniquePtr(
+				new BinomialLogistic( design )
+			) ;
+		}
+
+		BinomialLogistic::UniquePtr BinomialLogistic::create(
+			regression::Design::UniquePtr design
+		) {
+			return BinomialLogistic::UniquePtr(
+				new BinomialLogistic( design )
+			) ;
+		}
+
+		BinomialLogistic::UniquePtr BinomialLogistic::create(
+			regression::Design& design,
+			std::vector< metro::SampleRange > included_samples
+		) {
+			return BinomialLogistic::UniquePtr(
+				new BinomialLogistic( design, included_samples )
+			) ;
+		}
+
+		BinomialLogistic::UniquePtr BinomialLogistic::create(
+			regression::Design::UniquePtr design,
+			std::vector< metro::SampleRange > included_samples
+		) {
+			return BinomialLogistic::UniquePtr(
+				new BinomialLogistic( design, included_samples )
+			) ;
+		}
+
+		namespace {
+			void check_design( regression::Design const& design ) {
+				// Verify design looks sane.
+				BinomialLogistic::Matrix const& outcome = design.outcome() ;
+				// We insist that outcomes are smallish non-negative integers.
+				// Check this by comparing to absolute valued, floored version.
+				if( outcome.rows() > 0 && outcome.cols() > 0
+					&& (outcome.array() - outcome.array().abs().floor()).abs().maxCoeff() != 0 ) {
+					throw genfile::BadArgumentError(
+						"metro::case_control::BinomialLogistic::check_design()",
+						"design",
+						"Outcome does not consist solely of nonnegative integers."
+					) ;
+				}
+			}
+		}
+
+		BinomialLogistic::BinomialLogistic(
+			regression::Design::UniquePtr design
+		):
+			m_design( design.release() ),
+			m_design_owned( true ),
+			m_get_parameter_name( &standard_parameter_name ),
+			m_parameters( Vector::Zero( m_design->matrix().cols() ) ),
+			m_included_samples( 1, SampleRange( 0, m_design->matrix().rows() )),
+			m_numberOfDerivativesComputed( -1 ),
+			m_numberOfCDLDerivativesComputed( -1 )
+		{
+			check_design( *m_design ) ;
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "BinomialLogistic::BinomialLogistic(): created with " << impl::count_range( m_included_samples ) << " samples.\n" ;
+#endif
+			setup_storage( m_included_samples ) ;
+		}
+
+		BinomialLogistic::BinomialLogistic(
+			regression::Design::UniquePtr design,
+			std::vector< metro::SampleRange > included_samples
+		):
+			m_design( design.release() ),
+			m_design_owned( true ),
+			m_get_parameter_name( &standard_parameter_name ),
+			m_parameters( Vector::Zero( m_design->matrix().cols() ) ),
+			m_included_samples( included_samples ),
+			m_numberOfDerivativesComputed( -1 ),
+			m_numberOfCDLDerivativesComputed( -1 )
+		{
+			check_design( *m_design ) ;
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "BinomialLogistic::BinomialLogistic(): created with " << impl::count_range( m_included_samples ) << " samples.\n" ;
+#endif
+			setup_storage( m_included_samples ) ;
+		}
+
+		BinomialLogistic::BinomialLogistic(
+			regression::Design& design
+		):
+			m_design( &design ),
+			m_design_owned( false ),
+			m_get_parameter_name( &standard_parameter_name ),
+			m_parameters( Vector::Zero( m_design->matrix().cols() ) ),
+			m_included_samples( 1, SampleRange( 0, m_design->matrix().rows() )),
+			m_numberOfDerivativesComputed( -1 ),
+			m_numberOfCDLDerivativesComputed( -1 )
+		{
+			assert( m_design != 0 ) ;
+			check_design( *m_design ) ;
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "BinomialLogistic::BinomialLogistic(): created with " << impl::count_range( m_included_samples ) << " samples.\n" ;
+#endif
+			setup_storage( m_included_samples ) ;
+		}
+
+		BinomialLogistic::BinomialLogistic(
+			regression::Design& design,
+			std::vector< metro::SampleRange > included_samples
+		):
+			m_design( &design ),
+			m_design_owned( false ),
+			m_get_parameter_name( &standard_parameter_name ),
+			m_parameters( Vector::Zero( m_design->matrix().cols() ) ),
+			m_included_samples( included_samples ),
+			m_numberOfDerivativesComputed( -1 ),
+			m_numberOfCDLDerivativesComputed( -1 )
+		{
+			assert( m_design != 0 ) ;
+			check_design( *m_design ) ;
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "BinomialLogistic::BinomialLogistic(): created with " << impl::count_range( m_included_samples ) << " samples.\n" ;
+#endif
+			setup_storage( m_included_samples ) ;
+		}
+		
+		BinomialLogistic::~BinomialLogistic() {
+			if( m_design_owned ) {
+				delete m_design ;
+			}
+		}
+
+		std::string BinomialLogistic::get_summary() const {
+			using genfile::string_utils::to_string ;
+			std::string result = "BinomialLogistic( "
+				+ to_string( impl::count_range( m_included_samples ))
+				+ " of "
+				+ to_string( m_design->outcome().rows() )
+				+ " samples ): " ;
+			result += "(" + m_design->get_outcome_name(1) + ") ~ " ;
+			IntegerMatrix const identity = identify_parameters() ;
+			for( int i = 0; i < identity.rows(); ++i ) {
+				result +=
+					((i>0) ? " + " : "")
+					+ get_parameter_name(i) ;
+			}
+			return result ;
+		}
+
+		void BinomialLogistic::set_parameter_naming_scheme( BinomialLogistic::GetParameterName get_parameter_name ) {
+			assert( get_parameter_name ) ;
+			m_get_parameter_name = get_parameter_name ;		
+		}
+	
+		std::string BinomialLogistic::get_parameter_name( std::size_t i ) const {
+			IntegerMatrix const identity = identify_parameters() ;
+			return m_get_parameter_name( m_design->get_predictor_name( identity(i,1) ), m_design->get_outcome_name(identity(i,0)) ) ;
+		}
+	
+		LogLikelihood::IntegerMatrix BinomialLogistic::identify_parameters() const {
+			IntegerMatrix result = IntegerMatrix::Zero( m_design->matrix().cols(), 2 ) ;
+			// Each parameter corresponds to an effect for the non-baseline outcome level
+			// and a column of the design matrix.
+			result.col(0).setConstant( 1.0 ) ;
+			// There is one parameter per design matrix column.
+			for( int i = 0; i < m_design->matrix().cols(); ++i ) {
+				result( i, 1 ) = i ;
+			}
+			return result ;
+		}
+
+		int BinomialLogistic::number_of_outcomes() const {
+			return 2 ;
+		}
+
+		void BinomialLogistic::evaluate_at( Point const& parameters, int const numberOfDerivatives ) {
+			evaluate_at_impl(
+				parameters,
+				metro::impl::intersect_ranges(
+					m_included_samples,
+					m_design->nonmissing_samples()
+				),
+				numberOfDerivatives
+			) ;
+		}
+
+		void BinomialLogistic::evaluate_at_impl(
+			Point const& parameters,
+			std::vector< metro::SampleRange > const& evaluation_samples,
+			int const numberOfDerivatives
+		) {
+			assert( parameters.size() == m_design->matrix().cols() ) ;
+			assert( numberOfDerivatives < 3 ) ;
+
+			if(
+				evaluation_samples != m_evaluated_samples
+				|| m_design->get_number_of_predictor_levels() != m_hx.cols()
+				|| m_design->matrix().cols() != parameters.size()
+			) {
+				m_evaluated_samples = evaluation_samples ;
+				m_numberOfDerivativesComputed = -1 ;
+				m_numberOfCDLDerivativesComputed = -1 ;
+				setup_storage( m_evaluated_samples ) ;
+			}
+
+			if( parameters != m_parameters ) {
+				m_parameters = parameters ;
+				m_numberOfDerivativesComputed = -1 ;
+				m_numberOfCDLDerivativesComputed = -1 ;
+			}
+
+			
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << std::fixed << std::setprecision(4) ;
+			int const N = m_design->outcome().rows() ;
+			std::cerr << "==== BinomialLogistic::evaluate_at() ====\n" ;
+			std::cerr << "  m_numberOfDerivativesComputed: " << m_numberOfDerivativesComputed << ", "
+				<< "Number of samples: " << N << ", "
+				<< "Included samples:" ;
+			for( std::size_t i = 0; i < evaluation_samples.size(); ++i ) {
+				std::cerr << " " << evaluation_samples[i].begin() << "-" << evaluation_samples[i].end() ;
+			}
+			std::cerr << "\n" ;
+			std::cerr << "   Params: " << parameters.transpose() << ".\n" ;
+			std::cerr << "   Phenotypes: " << m_design->outcome().col(1).segment(0, std::min( N, 5 )).transpose() << "...\n";
+			std::cerr << "   Design:\n" << m_design->matrix().block( 0, 0, std::min( N, 5 ), m_design->matrix().cols() ) << "...\n";
+#endif
+			
+			evaluate( numberOfDerivatives ) ;
+		}
+
+		void BinomialLogistic::setup_storage( std::vector< metro::SampleRange > const& evaluation_samples ) {
+			int const R = metro::impl::count_range( evaluation_samples ) ;
+			int const L = m_design->get_number_of_predictor_levels() ;
+			int const D = m_design->matrix().cols() ;
+
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "metro::regression::BinomialLogistic::setup_storage(): Number of evaluated samples is " << R << "\n" ;
+#endif
+
+			// To avoid reallocation we only resize the stored matrices
+			// if we need more rows
+			if( R > m_hx.rows() || L != m_hx.cols() ) {
+				m_hx.resize( R, L ) ;
+				m_normalisedDhx.resize( R, L ) ;
+				m_normalisedDdhx.resize( R, L ) ;
+				m_first_derivative_terms.resize( R, D ) ;
+
+#if DEBUG_LOGLIKELIHOOD
+				std::cerr << "allocated storage: " << m_hx.rows() << " x " << m_hx.cols() << ".\n" ;
+#endif
+			}
+
+			// Since the allocated matrices may be larger than the number of
+			// actual samples analysed, we keep track of this number as well.
+			m_number_of_stored_samples = R ;
+
+			// For each range in the evaluated samples, map to a range
+			// in the stored samples:
+			m_storage_samples.resize( evaluation_samples.size() ) ;
+			int storage_row = 0 ;
+			for( std::size_t i = 0; i < evaluation_samples.size(); ++i ) {
+				int const size = evaluation_samples[i].size() ;
+				m_storage_samples[i] = metro::SampleRange( storage_row, storage_row + size ) ;
+				storage_row += size ;
+			}
+		}
+		
+		void BinomialLogistic::evaluate( int const numberOfDerivatives ) {
+			bool computeFunction = ( m_numberOfDerivativesComputed < 0 ) ;
+			bool compute1stDerivative = ( (numberOfDerivatives > 0) & (m_numberOfDerivativesComputed < 1) ) ;
+			bool compute2ndDerivative = ( (numberOfDerivatives > 1) & (m_numberOfDerivativesComputed < 2) ) ;
+
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "BinomialLogistic::evaluate(): numberOfDerivatives = " << numberOfDerivatives << ".\n" ;
+			std::cerr << "BinomialLogistic::evaluate(): m_numberOfDerivativesComputed = " << m_numberOfDerivativesComputed << ".\n" ;
+			std::cerr << "Computing: "
+				<< (computeFunction ? "function " : "" )
+				<< (compute1stDerivative ? "1st derivative " : "" )
+				<< (compute2ndDerivative ? "2nd derivative " : "" )
+				<< "\n" ;
+			//std::cerr << "  Predictor levels: " << m_design->get_predictor_levels().transpose() << ".\n" ;
+#endif
+
+			if( numberOfDerivatives > m_numberOfCDLDerivativesComputed ) {
+#if DEBUG_LOGLIKELIHOOD
+				std::cerr << "BinomialLogistic::evaluate(): computing CDL\n" ;
+#endif
+				// TODO: compute fx, dfx, ddfx here.
+				compute_complete_data_likelihood_and_derivatives(
+					m_parameters,
+					&m_hx,
+					&m_normalisedDhx,
+					&m_normalisedDdhx,
+					2
+				) ;
+
+				// Convert from complete data likelihood into expected complete data likelihood
+				// and derivatives
+				int const L = m_design->get_number_of_predictor_levels() ;
+				assert( m_hx.rows() >= m_number_of_stored_samples && m_hx.cols() == L ) ;
+				assert( m_normalisedDhx.rows() >= m_number_of_stored_samples && m_normalisedDhx.cols() == L ) ;
+				assert( m_normalisedDdhx.rows() >= m_number_of_stored_samples && m_normalisedDdhx.cols() == L ) ;
+				for( std::size_t i = 0; i < m_evaluated_samples.size(); ++i ) {
+					SampleRange const& range = m_evaluated_samples[i] ;
+					SampleRange const& storage_range = m_storage_samples[i] ;
+					ConstMatrixBlock probabilityBlock = m_design->get_predictor_level_probabilities().block( range.begin(), 0, range.size(), L ) ;
+
+					m_hx.block( storage_range.begin(), 0, storage_range.size(), L ).array() *= probabilityBlock.array() ;
+					m_normalisedDhx.block( storage_range.begin(), 0, storage_range.size(), L ).array() *= probabilityBlock.array() ;
+					m_normalisedDdhx.block( storage_range.begin(), 0, storage_range.size(), L ).array() *= probabilityBlock.array() ;
+				}
+
+				// normalise the derivatives by h, as required in derivative computations
+				typedef Eigen::DiagonalMatrix< double, Eigen::Dynamic > DiagonalMatrix ;
+				DiagonalMatrix one_over_h = (m_hx.rowwise().sum().asDiagonal().inverse()) ;
+				m_normalisedDhx = one_over_h * m_normalisedDhx ;
+				m_normalisedDdhx = one_over_h * m_normalisedDdhx ;
+
+				m_numberOfCDLDerivativesComputed = 2 ;
+			}
+#if DEBUG_LOGLIKELIHOOD
+			else {
+				std::cerr << "BinomialLogistic::evaluate(): skipping CDL computation.\n" ;
+			}
+#endif
+			
+			if( computeFunction ) {
+#if DEBUG_LOGLIKELIHOOD
+				std::cerr << "BinomialLogistic::evaluate(): computing fx\n" ;
+#endif
+				compute_value_of_loglikelihood(
+					m_hx,
+					&m_value_of_function
+				) ;
+				m_numberOfDerivativesComputed = 0 ;
+			}
+
+			if( compute1stDerivative ) {
+#if DEBUG_LOGLIKELIHOOD
+				std::cerr << "BinomialLogistic::evaluate(): computing dfx\n" ;
+#endif
+				compute_value_of_first_derivative(
+					m_normalisedDhx,
+					&m_first_derivative_terms,
+					&m_value_of_first_derivative
+				) ;
+				m_numberOfDerivativesComputed = 1 ;
+			}
+
+			if( compute2ndDerivative ) {
+#if DEBUG_LOGLIKELIHOOD
+				std::cerr << "BinomialLogistic::evaluate(): computing ddfx\n" ;
+#endif
+				compute_value_of_second_derivative(
+					m_first_derivative_terms,
+					m_normalisedDdhx,
+					&m_value_of_second_derivative
+				) ;
+				m_numberOfDerivativesComputed = 2 ;
+			}
+
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "  " << ( computeFunction ? "(computed) " : "(memoized) " ) << "function value = " << m_value_of_function << "\n" ;
+#endif
+
+#if DEBUG_LOGLIKELIHOOD
+			if( m_numberOfDerivativesComputed > 0 ) {
+				std::cerr << "  " << ( compute1stDerivative ? "(computed) " : "(memoized) " ) << "derivative = " << m_value_of_first_derivative.transpose() << "\n" ;
+			} else {
+				std::cerr << "  (1st derivative not computed).\n" ;
+			}
+#endif
+
+#if DEBUG_LOGLIKELIHOOD
+			if( m_numberOfDerivativesComputed > 1 ) {
+				std::cerr << "  " << ( compute2ndDerivative ? "(computed) " : "(memoized) " ) << "2nd derivative = \n"
+					<< m_value_of_second_derivative << ".\n" ;
+			} else {
+				std::cerr << "  (2nd derivative not computed).\n" ;
+			}
+			std::cerr << "====\n" ;
+#endif
+		}
+		
+		void BinomialLogistic::compute_complete_data_likelihood_and_derivatives(
+			Point const& parameters,
+			Matrix* fx,
+			Matrix* dfx,
+			Matrix* ddfx,
+			int const numberOfDerivatives
+		) {
+			int const L = m_design->get_number_of_predictor_levels() ;
+
+			// Outcome data is two columns, conceptually row sum is n
+			// (the number of trials) and 2nd column is k (number of successes / non-baseline outcomes)
+			// The computation requires us to compute f0 and f1, the prob of a single
+			// baseline / non-baseline observation.
+			m_f1.resize( fx->rows(), 1 ) ;
+			Vector linear_combination ;
+			
+			for( int g = 0; g < L; ++g ) {
+				for( std::size_t i = 0; i < m_evaluated_samples.size(); ++i ) {
+					metro::SampleRange const& range = m_evaluated_samples[i] ; 
+					metro::SampleRange const& storage_range = m_storage_samples[i] ; 
+					
+					// Setup relevant matrix nlocks
+					ConstMatrixBlock design_matrix_block
+						= m_design->set_predictor_level( g, range ).matrix( range ) ;
+					
+					MatrixBlock f1 = m_f1.block( storage_range.begin(), 0, storage_range.size(), 1 ) ;
+					
+					ConstMatrixBlock outcome = m_design->outcome().block( range.begin(), 0, range.size(), m_design->outcome().cols() ) ;
+					assert( outcome.cols() == 2 ) ;
+
+					MatrixBlock fxBlock = fx->block( storage_range.begin(), 0, storage_range.size(), L ) ;
+					MatrixBlock dfxBlock = dfx->block( storage_range.begin(), 0, storage_range.size(), L ) ;
+					MatrixBlock ddfxBlock = ddfx->block( storage_range.begin(), 0, storage_range.size(), L ) ;
+
+					auto one = Vector::Ones( range.size() ) ;
+
+#if DEBUG_LOGLIKELIHOOD
+					std::cerr << "design(" << g << ") =\n"
+						<< design_matrix_block.block( 0, 0, std::min( 10, int(design_matrix_block.rows())), design_matrix_block.cols() ) << ".\n" ;
+					std::cerr << "outcome(" << g << ") =\n"
+						<< outcome.block( 0, 0, std::min( 10, int(outcome.rows())), outcome.cols() ) << ".\n" ;
+#endif
+					f1 = (design_matrix_block * parameters).array().exp() ;
+					f1 = f1.array() * ((one + f1).array().inverse()) ;
+				
+				// Likelihood is obtained by raising f1 and f0 to appropriate powers
+				
+#if DEBUG_LOGLIKELIHOOD
+					std::cerr << "(*fx) = \n"
+						<< fx->block( 0, 0, std::min( 10, int(fx->rows())), fx->cols() ) << ".\n" ;
+					std::cerr << "f1 = \n"
+						<< f1.block( 0, 0, std::min( 10, int(f1.rows())), f1.cols() ) << ".\n" ;
+#endif
+					fxBlock.col(g)
+						= f1.array().pow( outcome.col(1).array() )
+						* (one.array() - f1.array() ).pow( outcome.col(0).array() ) ;
+
+#if DEBUG_LOGLIKELIHOOD
+					std::cerr << "Computed f1 and fx, f1 = " << f1.block( 0, 0, std::min( 5, int(f1.rows())), 1 ).transpose() << ", \n"
+						<< "fx(" << g << ") = " << fxBlock.col(g).block(0, 0, std::min( 5, int(f1.rows())), 1 ).transpose() << ".\n" ;
+#endif
+
+					if( numberOfDerivatives > 0 ) {
+						// compute coefficient of x^t in 1st derivative
+						// To share computation with 2nd derivative,
+						// first compute the shared term, we multiple by fx below.
+
+#if DEBUG_LOGLIKELIHOOD
+						std::cerr << "    dfx: " << dfx->rows() << "x" << dfx->cols() << ".\n" ;
+						std::cerr << "outcome: " << outcome.rows() << "x" << outcome.cols() << ".\n" ;
+#endif
+						dfxBlock.col(g)
+							= ( outcome.col(1).array() * ( one - f1 ).array() - outcome.col(0).array() * f1.array() )
+						;
+
+#if DEBUG_LOGLIKELIHOOD
+						std::cerr << "dfx(" << g << ") before fx term = "
+							<< dfxBlock.col(g).segment(0, std::min( 5, int(dfxBlock.rows()) )).transpose() << ".\n" ;
+#endif
+
+						if( numberOfDerivatives > 1 ) {
+							// compute coefficient of x ⊗ x^t in 2nd derivative
+							ddfxBlock.col(g)
+								= dfxBlock.col(g).array().square()
+								- (
+										(outcome.col(0) + outcome.col(1)).array()
+										* (f1.array() * ( one.array() - f1.array() ))
+								).array()
+							;
+							ddfxBlock.col(g).array() *= fxBlock.col(g).array() ;
+
+#if DEBUG_LOGLIKELIHOOD
+							std::cerr << "ddfx(" << g << ") = "
+								<< ddfxBlock.col(g).segment(0, std::min( 5, int(ddfxBlock.rows()) )).transpose() << ".\n" ;
+#endif
+						}
+						dfxBlock.col(g).array() *= fxBlock.col(g).array() ;
+
+#if DEBUG_LOGLIKELIHOOD
+						std::cerr << "dfx(" << g << ") = "
+							<< dfxBlock.col(g).segment(0, std::min( 5, int(dfxBlock.rows()) )).transpose() << ".\n" ;
+#endif
+					}
+				}
+			}
+		}
+
+		void BinomialLogistic::compute_value_of_loglikelihood(
+			Matrix const& hx,
+			double* result
+		) {
+			(*result) = neumaier_sum(
+				hx.block( 0, 0, m_number_of_stored_samples, hx.cols() )
+				.rowwise().sum()
+				.array().log()
+			) ;
+		}
+
+		void BinomialLogistic::compute_value_of_first_derivative(
+			Matrix const& normalisedDhx,
+			Matrix* result_terms,
+			Vector* result
+		) {
+			int const N = m_design->outcome().rows() ;
+			int const D = m_design->matrix().cols() ;
+			int const N_predictor_levels = m_design->get_number_of_predictor_levels() ;
+
+			// Currently we assume
+			// dimension of design matrix = dimension of parameters = dimension of derivative
+			// TODO: More generally we may have more parameters, e.g. multinomial logistic or normal linear model in which case something different must be done.  (Probably, identify_parameters can be used to generalise to this case?)
+			assert( D == m_parameters.size() ) ;
+			assert( result_terms->rows() >= m_number_of_stored_samples && result_terms->cols() == D ) ;
+			result_terms->setZero() ;
+
+			for( int g = 0; g < N_predictor_levels; ++g ) {
+				// At this point we have two sets of indexes - the originals, which index into the
+				// design matrix rows, and the normalisedDhx which only contains evaluated samples.
+				// Keep track of this with a counter.
+				for( std::size_t i = 0; i < m_evaluated_samples.size(); ++i ) {
+					SampleRange const range = m_evaluated_samples[i] ;
+					SampleRange const stored_range = m_storage_samples[i] ;
+
+					ConstMatrixBlock design_matrix_block
+						= m_design->set_predictor_level( g, range ).matrix( range ) ;
+
+					MatrixBlock termsBlock = result_terms->block(
+						stored_range.begin(), 0,
+						stored_range.size(), result_terms->cols()
+					) ;
+					
+					ConstMatrixBlock normalisedDhxBlock = normalisedDhx.block(
+						stored_range.begin(), 0,
+						stored_range.size(), normalisedDhx.cols()
+					) ;
+
+					// Compute the contribution of these samples & this predictor level
+					termsBlock +=
+						normalisedDhxBlock.col(g)
+						.asDiagonal()
+						* design_matrix_block
+					;
+					
+				}
+			}
+
+			MatrixBlock termsBlock = result_terms->block(
+				0, 0,
+				m_number_of_stored_samples, result_terms->cols()
+			) ;
+
+			// Now the rows of terms are the contribution of each sample to the derivative
+			(*result) = termsBlock.colwise().sum() ;
+		}
+		
+		void BinomialLogistic::compute_value_of_second_derivative(
+			Matrix const& firstDerivativeTerms,
+			Matrix const& normalisedDdhx,
+			Matrix* result
+		) {
+			int const D = m_design->matrix().cols() ;
+			int const N_predictor_levels = m_design->get_number_of_predictor_levels() ;
+
+			// Currently we assume
+			// dimension of design matrix = dimension of parameters = dimension of derivative
+			// More generally we may have more parameters, e.g. multinomial logistic or normal linear model
+			// in which case something different must be done.  (Probably, identify_parameters can be
+			// used to generalise to this case?)
+			assert( D == m_parameters.size() ) ;
+
+			result->setZero( D, D ) ;
+
+			for( int g1 = 0; g1 < N_predictor_levels; ++g1 ) {
+				for( std::size_t i = 0; i < m_evaluated_samples.size(); ++i ) {
+					SampleRange const& range = m_evaluated_samples[i] ;
+					SampleRange const& stored_range = m_storage_samples[i] ;
+
+					ConstMatrixBlock design_matrix_block = m_design->set_predictor_level( g1, range ).matrix( range ) ;
+
+					// We are implementing the formula: sum_i (sum_x DD^t h_i)/(sum_x h_i) × x ⊗ x^t
+					// Or, written in the way we compute it here, sum_g ( sum_i Z_i × x_i(g) ⊗ x_i(g)^t )
+					// where Z_i = (DD^t h_i(g)) / h_i and x_i(g)^t is the design matrix row for sample i given predictor level g.
+					// We let matrix multiplication do the sum over i for us, and compute this as
+					// diag(Z) × X(g)^t ⊗ X(g)
+					(*result) += (
+							normalisedDdhx.col(g1).segment( stored_range.begin(), stored_range.size() ).asDiagonal()
+							* design_matrix_block
+						)
+						.transpose()
+						* design_matrix_block
+					;
+				}
+			}
+
+			ConstMatrixBlock firstDerivativeTermsBlock = firstDerivativeTerms.block(
+				0, 0,
+				m_number_of_stored_samples, firstDerivativeTerms.cols()
+			) ;
+
+			(*result) -= ( firstDerivativeTermsBlock.transpose() * firstDerivativeTermsBlock ) ;
+
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "D = " << D << "\n" ;
+			std::cerr << "first_derivative_terms: " << firstDerivativeTermsBlock.rows() << "x" << firstDerivativeTermsBlock.cols() << "\n" ;
+			std::cerr << "result: " << result->rows() << "x" << result->cols() << "\n" ;
+#endif
+		}
+		
+		BinomialLogistic::Point const& BinomialLogistic::parameters() const {
+			return m_parameters ;
+		}
+
+		double BinomialLogistic::get_value_of_function() const {
+			return m_value_of_function ;
+		}
+
+		BinomialLogistic::Vector BinomialLogistic::get_value_of_first_derivative() const {
+			return m_value_of_first_derivative ;
+		}
+
+		BinomialLogistic::Matrix BinomialLogistic::get_value_of_second_derivative() const {
+			return m_value_of_second_derivative ;
+		}
+	}
+}

ADDED   metro/src/regression/Design.cpp
Index: metro/src/regression/Design.cpp
==================================================================
--- metro/src/regression/Design.cpp
+++ metro/src/regression/Design.cpp
@@ -0,0 +1,579 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <sstream>
+#include <vector>
+#include <utility>
+#include <algorithm>
+#include <boost/iterator/counting_iterator.hpp>
+#include <boost/bind.hpp>
+#include "metro/regression/Design.hpp"
+#include "metro/intersect_ranges.hpp"
+
+// #define DEBUG_REGRESSIONDESIGN 1
+
+namespace metro {
+	namespace regression {
+		Design::UniquePtr Design::create(
+			Matrix const& outcome, SampleRanges const& nonmissing_outcome, std::vector< std::string > const& outcome_names,
+			Matrix const& covariates, SampleRanges const& nonmissing_covariate, std::vector< std::string > const& covariate_names,
+			std::vector< std::string > const& predictor_names,
+			Transform transform,
+			std::vector< int > const& interacting_covariates
+		) {
+			return Design::UniquePtr(
+				new Design(
+					outcome, nonmissing_outcome, outcome_names,
+					covariates, nonmissing_covariate, covariate_names,
+					predictor_names,
+					transform,
+					interacting_covariates
+				)
+			) ;
+		}
+
+		Design::UniquePtr Design::create(
+			Matrix const& outcome, SampleRanges const& nonmissing_outcome, std::vector< std::string > const& outcome_names,
+			std::vector< std::string > const& predictor_names,
+			Transform transform
+		) {
+			return Design::UniquePtr(
+				new Design(
+					outcome, nonmissing_outcome, outcome_names,
+					predictor_names,
+					transform
+				)
+			) ;
+		}
+
+		Design::Design(
+			Matrix const& outcome, SampleRanges const& nonmissing_outcome,  std::vector< std::string > const& outcome_names,
+			Matrix const& covariates, SampleRanges const& nonmissing_covariates, std::vector< std::string > const& covariate_names,
+			std::vector< std::string > const& predictor_names,
+			Transform transform,
+			std::vector< int > const& interacting_covariates
+		):
+			// outcome variables
+		 	m_outcome( outcome ),
+			m_outcome_names( outcome_names ),
+		 	m_nonmissing_outcome( nonmissing_outcome ),
+			// predictor variables
+			m_predictor_level_probabilities( Matrix::Zero( outcome.rows(), 0 )),
+			m_predictor_levels( Matrix::Zero( 0, predictor_names.size() )),
+			m_predictor_names( predictor_names ),
+			m_nonmissing_predictors( SampleRanges() ),
+			// covariate variables
+			m_covariates( 1, covariates ),
+			m_covariate_names( covariate_names ),
+			m_nonmissing_covariates( nonmissing_covariates ),
+			// predictor-covariate interactions
+			m_predictor_covariate_interactions( interacting_covariates ),
+			// Design matrix column transform
+			m_transform( transform )
+		{
+			assert( covariates.rows() == m_outcome.rows() ) ;
+			assert( m_outcome_names.size() == std::size_t( m_outcome.cols() )) ;
+			assert( m_covariate_names.size() == std::size_t( m_covariates[0].cols() )) ;
+			recalculate() ;
+		}
+
+		Design::Design(
+			Matrix const& outcome, SampleRanges const& nonmissing_outcome,  std::vector< std::string > const& outcome_names,
+			std::vector< std::string > const& predictor_names,
+			Transform transform
+		):
+			// outcome variables
+		 	m_outcome( outcome ),
+			m_outcome_names( outcome_names ),
+		 	m_nonmissing_outcome( nonmissing_outcome ),
+			// predictor variables
+			m_predictor_level_probabilities( Matrix::Zero( outcome.rows(), 0 )),
+			m_predictor_levels( Matrix::Zero( 0, predictor_names.size() )),
+			m_predictor_names( predictor_names ),
+			m_nonmissing_predictors( SampleRanges() ),
+			// covariate variables
+			m_covariates(),
+			m_covariate_names(),
+			m_nonmissing_covariates( 1, SampleRange( 0, m_outcome.rows() )),
+			// predictor-covariate interactions
+			m_predictor_covariate_interactions(),
+			// Design matrix column transform
+			m_transform( transform )
+		{
+			assert( m_outcome_names.size() == m_outcome.cols() ) ;
+			recalculate() ;
+		}
+		
+		// add a single continuous covariate
+		// missing values are encoded by NaN
+		void Design::add_single_covariate(
+			std::string const& name,
+			boost::function< double( std::size_t ) > const& values
+		) {
+			Vector data = Vector::Constant( m_outcome.rows(), 0 ) ;
+			std::vector< SampleRange > nonmissingness ;
+			int last_nonmissing_sample_i = 0 ;
+			for( int i = 0; i < m_outcome.rows(); ++i ) {
+				double v = values(i) ;
+				if( v == v ) {
+					data(i) = v ;
+				} else {
+					if( i > last_nonmissing_sample_i ) {
+						nonmissingness.push_back( SampleRange( last_nonmissing_sample_i, i )) ;
+					}
+					last_nonmissing_sample_i = i+1 ;
+				}
+			}
+			if( last_nonmissing_sample_i < m_outcome.rows() ) {
+				nonmissingness.push_back( SampleRange( last_nonmissing_sample_i, m_outcome.rows() )) ;
+			}
+
+			// Ok push it.
+			m_covariates.push_back( data ) ;
+			m_covariate_names.push_back( name ) ;
+			m_nonmissing_covariates = impl::intersect_ranges( m_nonmissing_covariates, nonmissingness ) ;
+			
+			recalculate() ;
+		}
+		
+		// add a single discrete covariate (which expands into multiple columns of zeroes and ones)
+		// levels are specified by non-negative integers.
+		// missing values are encoded by -1
+		void Design::add_discrete_covariate(
+			std::string const& name,
+			boost::function< int( std::size_t ) > const& values,
+			boost::function< std::string( int ) > const& levelNames,
+			int numberOfLevels
+		) {
+			// column for level 0 is not provided as will be a linear combination of the others.
+			Matrix data = Matrix::Constant( m_outcome.rows(), numberOfLevels - 1, 0.0 ) ;
+			std::vector< SampleRange > nonmissingness ;
+			int last_nonmissing_sample_i = 0 ;
+			std::vector< std::string > covariateLevelNames ;
+			for( int i = 0; i < m_outcome.rows(); ++i ) {
+				int level = values( i ) ;
+				if( level > 0 ) {
+					data( i, level-1 ) = 1.0 ;
+				} else if( level == -1 ) {
+					if( i > last_nonmissing_sample_i ) {
+						nonmissingness.push_back( SampleRange( last_nonmissing_sample_i, i )) ;
+					}
+					last_nonmissing_sample_i = i+1 ;
+				}
+			}
+			if( last_nonmissing_sample_i < m_outcome.rows() ) {
+				nonmissingness.push_back( SampleRange( last_nonmissing_sample_i, m_outcome.rows() )) ;
+			}
+			m_covariates.push_back( data ) ;
+			for( int i = 1; i < numberOfLevels; ++i ) {
+				m_covariate_names.push_back( name + "=" + levelNames(i) ) ;
+			}
+			m_nonmissing_covariates = impl::intersect_ranges( m_nonmissing_covariates, nonmissingness ) ;
+
+			recalculate() ;
+		}
+
+		std::string const& Design::get_predictor_name( std::size_t i ) const {
+			assert( i < m_design_matrix_column_names.size() ) ;
+			return m_design_matrix_column_names[i] ;
+		}
+
+		std::vector< std::string > const& Design::design_matrix_column_names() const {
+			return m_design_matrix_column_names ;
+		}
+
+		std::string const& Design::get_outcome_name( std::size_t i ) const {
+			assert( i < m_outcome_names.size() ) ;
+			return m_outcome_names[i] ;
+		}
+
+		std::string Design::get_summary() const {
+			std::ostringstream out ;
+
+			int const N = matrix().rows() ;
+			int const D = matrix().cols() ;
+			int const P = number_of_predictors() + number_of_interaction_terms() ;
+
+			// Compute mean predictors
+			Eigen::MatrixXd mean_predictors = Eigen::MatrixXd::Zero( N, P ) ;
+			{
+				for( int level = 0; level < m_predictor_level_probabilities.cols(); ++level ) {
+					mean_predictors += m_predictor_level_probabilities.col(level).asDiagonal() * m_predictor_levels.block( 0, P*level, N, P ) ;
+				}
+			}
+
+			std::vector< std::size_t > widths( D + 1 ) ;
+			widths[0] = std::max( std::size_t( outcome().cols() * 4 - 1 ), 8ul ) ;
+			std::size_t const n_top = 8 ;
+			out << "       " << "   " << std::setw( widths[0] ) << "outcome" << "  " ;
+			for( int j = 0; j < D; ++j ) {
+				std::string const name = m_design_matrix_column_names[j]  ;
+				widths[j+1] = std::max( name.size(), 7ul ) ;
+				out << " " << std::setw( widths[j+1] ) << name ;
+			}
+			out << "\n" ;
+			for( int i = 0; i < N; ++i ) {
+				out << std::setw(7) << i ;
+				out << "   " ;
+				if( outcome().row(i).sum() == outcome().row(i).sum() ) {
+					std::size_t outcomesWidth = 4 * outcome().cols() - 1 ;
+					if( outcomesWidth < widths[0] ) {
+						out << std::string( widths[0] - outcomesWidth, ' ' ) ;
+					}
+					for( int j = 0; j < outcome().cols(); ++j ) {
+						out << ((j>0) ? " " : "" ) << std::setw(3) << outcome()(i,j) ;
+					}
+				} else {
+					out << std::setw(widths[0]) << "NA" ;
+				}
+				out << (( i == n_top ) ? " ~ " : "   " ) ;
+				for( int j = 0; j < D; ++j ) {
+					if( j > 0 ) {
+						out << std::setw(1) << " " ;
+					}
+					out << std::setw( widths[j+1] ) << std::defaultfloat << std::setprecision(3) ;
+					if( j > 0 & j <= P ) {
+						out << mean_predictors(i,j-1) ;
+					} else if( matrix()(i,j) == matrix()(i,j) ){
+						out << matrix()(i,j) ;
+					} else {
+						out << "NA" ;
+					}
+				}
+				out << "\n" ;
+			
+				if( i == n_top && N > 8 ) {
+					for( int i2 = 0; i2 < 3; ++i2 ) {
+						out << std::setw(8) << " " ;
+						out << std::setw(widths[0]) << "." ;
+						out << "  " ;
+						for( int j2 = 0; j2 < D; ++j2 ) {
+							if( j2 > 0 ) {
+								out << std::setw(1) << " " ;
+							}
+							out << std::setw( widths[j2+1] ) << "." ;
+						}
+						out << "\n" ;
+					}
+					i = N - n_top + 1 ;
+				}
+			}
+			return out.str() ;
+		}
+
+		Design::SampleRanges Design::compute_nonmissing_samples(
+			SampleRanges const& nonmissing_outcome,
+			SampleRanges const& nonmissing_predictors,
+			SampleRanges const& nonmissing_covariates
+		) const {
+			SampleRanges result = impl::intersect_ranges( nonmissing_outcome, nonmissing_predictors ) ;
+			return impl::intersect_ranges( result, nonmissing_covariates ) ;
+		}
+
+		void Design::recalculate() {
+			calculate_design_matrix(
+				m_outcome.rows(),
+				m_covariates,
+				m_covariate_names,
+				m_predictor_names,
+				m_predictor_covariate_interactions,
+				&m_design_matrix,
+				&m_design_matrix_interaction_columns,
+				&m_design_matrix_column_names
+			) ;
+			// 
+			m_nonmissing_samples = compute_nonmissing_samples(
+				m_nonmissing_outcome, m_nonmissing_predictors, m_nonmissing_covariates
+			) ;
+			assert( m_design_matrix_column_names.size() == m_design_matrix.cols() ) ;
+		}
+
+		void Design::calculate_design_matrix(
+			int const number_of_samples,
+			std::vector< Matrix > const& covariates,
+			std::vector< std::string > const& covariate_names,
+			std::vector< std::string > const& predictor_names,
+			std::vector< int > const& interacting_covariates,
+			Matrix* result,
+			std::vector< int >* design_matrix_interaction_cols,
+			std::vector< std::string >* design_matrix_column_names
+		) const {
+			assert( result != 0 ) ;
+			assert( design_matrix_interaction_cols != 0 ) ;
+			assert( design_matrix_interaction_cols->size() == 0 ) ;
+			std::size_t const number_of_predictors = predictor_names.size() ;
+			// Compute the number of covariates
+			std::size_t numberOfCovariates = 0 ;
+			for( std::size_t i = 0; i < covariates.size(); ++i ) {
+				numberOfCovariates += covariates[i].cols() ;
+			}
+			
+			// design matrix is layed out as:
+			// baseline column of 1's
+			// columns for predictors with values set later
+			// columns for predictor vs. covariate interactions with values set later
+			// columns for covariates with values set here.
+			std::size_t numberOfDesignMatrixColumns
+				= 1 + number_of_predictors * ( 1 + interacting_covariates.size() ) + numberOfCovariates ;
+
+			result->setZero( number_of_samples, numberOfDesignMatrixColumns ) ;
+			design_matrix_column_names->clear() ;
+
+			// baseline column
+			result->leftCols( 1 ).setOnes() ;
+			design_matrix_column_names->push_back( "baseline" ) ;
+
+			// predict columns
+			design_matrix_column_names->insert(
+				design_matrix_column_names->end(),
+				m_predictor_names.begin(),
+				m_predictor_names.end()
+			) ;
+
+			// predictor-covariate interactions
+			if( interacting_covariates.size() > 0 ) {
+				for( std::size_t i = 0; i < interacting_covariates.size(); ++i ) {
+					design_matrix_interaction_cols->push_back( interacting_covariates[i] + result->cols() - numberOfCovariates ) ;
+					for( std::size_t predictor = 0; predictor < number_of_predictors; ++predictor ) {
+						design_matrix_column_names->push_back( m_predictor_names[predictor] + "x" + covariate_names[interacting_covariates[i]] ) ;
+					}
+				}
+			}
+
+			// covariates
+			if( numberOfCovariates > 0 ) {
+				int col = numberOfDesignMatrixColumns - numberOfCovariates ;
+				for( std::size_t i = 0; i < covariates.size(); ++i ) {
+					result->block(
+						0, col,
+						result->rows(), covariates[i].cols()
+					) = covariates[i] ;
+					col += covariates[i].cols() ;
+				}
+				design_matrix_column_names->insert(
+					design_matrix_column_names->end(),
+					covariate_names.begin(),
+					covariate_names.end()
+				) ;
+			}
+	#if DEBUG_REGRESSIONDESIGN
+			std::cerr << "Design::calculate_design_matrix():"
+				<< "result has " << result->cols() << " columns, and " << design_matrix_column_names->size() << " names.\n" ;
+	#endif
+		
+		
+			assert( design_matrix_column_names->size() == result->cols() ) ;
+		}
+	
+		Design& Design::set_outcome(
+			Matrix const& outcome,
+			SampleRanges const& nonmissingness,
+			std::vector< std::string > const& names
+		) {
+			assert( outcome.rows() == m_design_matrix.rows() ) ;
+			assert( names.size() == outcome.cols() ) ;
+
+			m_outcome = outcome ;
+			m_outcome_names = names ;
+			if( nonmissingness != m_nonmissing_outcome ) {
+				m_nonmissing_outcome = nonmissingness ;
+				m_nonmissing_samples = compute_nonmissing_samples( m_nonmissing_outcome, m_nonmissing_predictors, m_nonmissing_covariates ) ;
+			}
+			return *this ;
+		}
+	
+		Design& Design::set_predictors(
+			Matrix const& levels,
+			Matrix const& probabilities,
+			std::vector< metro::SampleRange > const& nonmissingness
+		) {
+			assert( levels.cols() == number_of_predictors() ) ;
+			assert( probabilities.cols() == levels.rows() ) ;
+			assert( probabilities.rows() == m_design_matrix.rows() ) ;
+
+			// Set probabilities
+			m_predictor_level_probabilities = probabilities ;
+
+			// Set levels
+			{
+				// This is complexified by the need to handle possible interactions between
+				// predictors and covariates.
+				// There is one column per predictor and one column per predictor per interacting covariate.
+				// The levels go in a matrix of dimension N x ((#predictors & interactions) x (#levels)).
+				int const N = probabilities.rows() ;
+				int const number_of_predictors_and_interactions = number_of_predictors() + number_of_interaction_terms() ;
+				m_predictor_levels = Matrix::Zero( N, number_of_predictors_and_interactions * levels.rows() ) ;
+
+				// Lay this out as follows.
+				// For predictor level level_i, we fill in the block of m_predictor_levels with indices
+				// [0,N) x [ level_i*npi,(level_i+1)*npi )
+				// where npi is the total number of predictor and interaction terms.
+				for( int level_i = 0; level_i < levels.rows(); ++level_i ) {
+					m_predictor_levels.block(
+						0, level_i * number_of_predictors_and_interactions,
+						N, number_of_predictors()
+					).rowwise() = levels.row(level_i) ;
+					for( std::size_t i = 0; i < m_design_matrix_interaction_columns.size(); ++i ) {
+						m_predictor_levels.block(
+							0, level_i * number_of_predictors_and_interactions + (i+1) * number_of_predictors(),
+							N, number_of_predictors()
+						) = m_design_matrix.col( m_design_matrix_interaction_columns[i] ) * levels.row(level_i) ;
+					}
+				}
+				
+				// Set nonmissingness if necessary
+				if( nonmissingness != m_nonmissing_predictors ) {
+					m_nonmissing_predictors = nonmissingness ;
+					m_nonmissing_samples = compute_nonmissing_samples( m_nonmissing_outcome, m_nonmissing_predictors, m_nonmissing_covariates ) ;
+				}
+
+#if DEBUG_REGRESSIONDESIGN
+				std::cerr << "Design::set_predictors(): levels is:\n"
+					<< m_predictor_levels.block( 0, 0, 10, m_predictor_levels.cols() ) << "\n" ;
+#endif				
+				if( m_transform == eMeanCentre ) {
+					mean_centre_predictor_levels(
+						m_predictor_level_probabilities,
+						&m_predictor_levels,
+						m_nonmissing_samples
+					) ;
+				}
+#if DEBUG_REGRESSIONDESIGN
+				std::cerr << "Design::set_predictors(): after mean centring, levels is:\n"
+					<< m_predictor_levels.block( 0, 0, 10, m_predictor_levels.cols() ) << "\n" ;
+#endif
+			}
+			
+			return *this ;
+		}
+
+		Design& Design::set_predictors(
+			Matrix const& predictors,
+			std::vector< metro::SampleRange > const& nonmissingness
+		) {
+			int const N = predictors.rows() ;
+			int const D = predictors.cols() ;
+			assert( D == number_of_predictors() ) ;
+			assert( N == m_design_matrix.rows() ) ;
+
+			// Set probabilities
+			m_predictor_level_probabilities = Matrix::Ones( N, 1 ) ;
+
+			// Set levels
+			{
+				// This is complexified by the need to handle possible interactions. 
+				// There is one column per predictor and one column per predictor per interacting covariate.
+				// The levels go in a matrix of dimension N x ((#predictors & interactions) x (#levels)).
+				int const number_of_predictors_and_interactions = number_of_predictors() + number_of_interaction_terms() ;
+				m_predictor_levels = Matrix::Zero( N, number_of_predictors_and_interactions ) ;
+
+				// Lay this out as follows.
+				// For predictor level level_i, we fill in the block of m_predictor_levels with indices
+				// [0,N) x [ level_i*npi,(level_i+1)*npi )
+				// where npi is the total number of predictor and interaction terms.
+				m_predictor_levels.block(
+					0, 0,
+					N, D
+				) = predictors ;
+				for( std::size_t i = 0; i < m_design_matrix_interaction_columns.size(); ++i ) {
+					for( std::size_t d = 0; d < D; ++d ) {
+						m_predictor_levels.col( D * (1+i) + d )
+							= m_design_matrix.col( m_design_matrix_interaction_columns[i] ).array()
+								* predictors.col(d).array() ;
+					}
+				}
+			}
+
+			// Set nonmissingness if necessary
+			if( nonmissingness != m_nonmissing_predictors ) {
+				m_nonmissing_predictors = nonmissingness ;
+				m_nonmissing_samples = compute_nonmissing_samples( m_nonmissing_outcome, m_nonmissing_predictors, m_nonmissing_covariates ) ;
+			}
+
+			if( m_transform == eMeanCentre ) {
+				mean_centre_predictor_levels(
+					m_predictor_level_probabilities,
+					&m_predictor_levels,
+					m_nonmissing_samples
+				) ;
+			}
+			
+			return *this ;
+		}
+
+		void Design::mean_centre_predictor_levels(
+			Matrix const& probs,
+			Matrix* predictor_levels,
+			SampleRanges const& included_samples
+		) const {
+			int const number_of_predictors_and_interactions = number_of_predictors() + number_of_interaction_terms() ;
+
+			// Compute mean of each predictor
+			RowVector means = RowVector::Zero( number_of_predictors_and_interactions ) ;
+			int const number_of_predictor_levels = probs.cols() ;
+			double total = 0 ;
+			for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+				metro::SampleRange const& range = included_samples[i] ;
+				for( int level_i = 0; level_i < number_of_predictor_levels; ++level_i ) {
+					means += (
+						( probs.col( level_i ).segment( range.begin(), range.size() ) ).asDiagonal()
+						* predictor_levels->block(
+							range.begin(), number_of_predictors_and_interactions * level_i,
+							range.size(), number_of_predictors_and_interactions
+						)
+					).colwise().sum() ;
+				}
+				total += probs.block( range.begin(), 0, range.size(), probs.cols() ).sum() ;
+			}
+			means /= total ;
+
+#if DEBUG_REGRESSIONDESIGN
+			std::cerr << "Design::mean_centre_predictor_levels(): nonmissingnes = " << included_samples << ".\n" ;
+			std::cerr << "Design::mean_centre_predictor_levels(): covariate nonmissingness = " << m_nonmissing_covariates << ".\n" ;
+			std::cerr << "Design::mean_centre_predictor_levels(): means = " << means << ".\n" ;
+#endif
+			// Subtract means from the predictor levels
+			for( int level_i = 0; level_i < number_of_predictor_levels; ++level_i ) {
+				predictor_levels->block(
+					0, number_of_predictors_and_interactions * level_i,
+					predictor_levels->rows(), number_of_predictors_and_interactions
+				).rowwise() -= means ;
+			}
+		}
+
+		Design& Design::set_predictor_level( int level ) {
+			if( m_predictor_levels.cols() > 0 ) {
+				set_predictor_level( level, metro::SampleRange( 0, m_design_matrix.rows() )) ;
+			}
+			return *this ;
+		}
+
+		Design& Design::set_predictor_level( int level, metro::SampleRange const& range ) {
+			if( m_predictor_levels.cols() > 0 ) {
+				int const number_of_predictors_and_interactions = ( 1 + m_design_matrix_interaction_columns.size() ) * number_of_predictors() ;
+				m_design_matrix.block(
+					range.begin(), 1,
+					range.size(), number_of_predictors_and_interactions
+				) = m_predictor_levels.block(
+					range.begin(), level * number_of_predictors_and_interactions,
+					range.size(), number_of_predictors_and_interactions
+				) ;
+			}
+			return *this ;
+		}
+
+		Design& Design::set_predictor_level( int level, std::vector< metro::SampleRange > const& ranges ) {
+			if( m_predictor_levels.cols() > 0 ) {
+				for( std::size_t i = 0; i < ranges.size(); ++i ) {
+					set_predictor_level( level, ranges[i] ) ;
+				}
+			}
+			return *this ;
+		}
+	}
+}

ADDED   metro/src/regression/IndependentLogFWeightedLogLikelihood.cpp
Index: metro/src/regression/IndependentLogFWeightedLogLikelihood.cpp
==================================================================
--- metro/src/regression/IndependentLogFWeightedLogLikelihood.cpp
+++ metro/src/regression/IndependentLogFWeightedLogLikelihood.cpp
@@ -0,0 +1,188 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include <memory>
+#include <iostream>
+#include <iomanip>
+#include <boost/noncopyable.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+#include "Eigen/Core"
+#include "Eigen/LU"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/regression/IndependentLogFWeightedLogLikelihood.hpp"
+
+// #define DEBUG_NORMALWEIGHTEDLOGLIKELIHOOD 1
+
+namespace metro {
+	namespace regression {
+		/*
+		logF density
+		this can be computed in R as follows:
+		
+		logistic <- function(x) { exp(x) / (1 + exp(x) )}
+		dlogf <- function( x, nu1 = 1, nu2 = 1, normalisation = "zeroatmean" ) {
+			alpha = nu1/2
+			beta = nu2/2
+			l = logistic((x))
+			constant = 0
+			if( normalisation == "zeroatmean" ) {
+				constant = -(alpha+beta) * log(0.5)
+			} else if( normalisation == "density" ) {
+				constant = -lbeta( alpha, beta )
+			} else {
+				constant = 0
+			}
+			constant + l^alpha * ( 1-l)^ beta
+		}
+		dlogf.v2 <- function( x, nu1 = 1, nu2 = 1 ) {
+			dbeta( logistic(x), shape1 = nu1/2, shape2 = nu2/2 )
+		}
+		*/
+		IndependentLogFWeightedLogLikelihood::UniquePtr IndependentLogFWeightedLogLikelihood::create(
+			LogLikelihood::UniquePtr ll,
+			std::vector< int > parameter_indices,
+			std::vector< double > nu1,
+			std::vector< double > nu2
+		) {
+			return UniquePtr( new IndependentLogFWeightedLogLikelihood( ll, parameter_indices, nu1, nu2 ) ) ;
+		}
+
+		IndependentLogFWeightedLogLikelihood::IndependentLogFWeightedLogLikelihood(
+			LogLikelihood::UniquePtr ll,
+			std::vector< int > parameter_indices,
+			std::vector< double > nu1,
+			std::vector< double > nu2
+		):
+			m_ll( ll ),
+			m_parameter_indices( parameter_indices ),
+			m_alpha( nu1 ),
+			m_beta( nu2 ),
+			m_normalisation( eZeroAtMean )
+		{
+			assert( m_alpha.size() == m_parameter_indices.size() ) ;
+			assert( m_beta.size() == m_parameter_indices.size() ) ;
+			for( std::size_t i = 0; i < m_alpha.size(); ++i ) {
+				m_alpha[i] = m_alpha[i]/2.0 ;
+				m_beta[i] = m_beta[i]/2.0 ;
+			}
+			m_constant = 0.0 ;
+			if( m_normalisation == eZeroAtMean ) {
+				// Normalise so the log-likelihood value at zero is zero.
+				// ll computes as log(0.5)*(alpha+beta) for each parameter.
+				m_constant = 0.0  ;
+				for( std::size_t i = 0; i < m_alpha.size(); ++i ) {
+					m_constant -= (m_alpha[i] + m_beta[i]) * std::log(0.5) ;
+				}
+			} else if( m_normalisation == ePDF ) {
+				assert(0) ; // this might not be correct yet
+				using boost::math::lgamma ;
+				for( std::size_t i = 0; i < m_alpha.size(); ++i ) {
+					m_constant -= lgamma(m_alpha[i]) + lgamma(m_beta[i]) - lgamma(m_alpha[i] + m_beta[i] ) ;
+				}
+			} else {
+				assert(0) ;
+			}
+		}
+
+		std::string IndependentLogFWeightedLogLikelihood::get_parameter_name( std::size_t i ) const {
+			return m_ll->get_parameter_name(i) ;
+		}
+		IndependentLogFWeightedLogLikelihood::IntegerMatrix IndependentLogFWeightedLogLikelihood::identify_parameters() const {
+			return m_ll->identify_parameters() ;
+		}
+		
+		int IndependentLogFWeightedLogLikelihood::number_of_parameters() const {
+			return m_ll->number_of_parameters() ;
+		}
+
+		int IndependentLogFWeightedLogLikelihood::number_of_outcomes() const {
+			return m_ll->number_of_outcomes() ;
+		}
+		
+		void IndependentLogFWeightedLogLikelihood::evaluate_at( Point const& parameters, int const numberOfDerivatives ) {
+			m_ll->evaluate_at( parameters, numberOfDerivatives ) ;
+			evaluate_impl( numberOfDerivatives ) ;
+		}
+
+		void IndependentLogFWeightedLogLikelihood::evaluate( int const numberOfDerivatives ) {
+			m_ll->evaluate( numberOfDerivatives ) ;
+			evaluate_impl( numberOfDerivatives ) ;
+		}
+	
+		void IndependentLogFWeightedLogLikelihood::evaluate_impl( int const numberOfDerivatives ) {
+			Vector const& parameters = m_ll->parameters() ;
+			m_value_of_function = m_constant ;
+			m_value_of_first_derivative.setZero( parameters.size() ) ;
+			m_value_of_second_derivative.setZero( parameters.size(), parameters.size() ) ;
+
+			for( std::size_t i = 0; i < m_parameter_indices.size(); ++i ) {
+				int const& parameter_index = m_parameter_indices[i] ;
+				assert( parameter_index >= 0 && parameter_index < parameters.size() ) ;
+				double const x = parameters( parameter_index ) ;
+				// logistic function evaluated at this value.
+				double const l = 1.0 / (1.0 + std::exp(-x)) ;
+				m_value_of_function += ( m_alpha[i] * std::log(l) + m_beta[i] * std::log( 1-l ) );
+				m_value_of_first_derivative( parameter_index ) = m_alpha[i] - (m_alpha[i] + m_beta[i]) * l ;
+				m_value_of_second_derivative( parameter_index, parameter_index ) = -(m_alpha[i] + m_beta[i]) * l * (1-l) ;
+			}
+		}
+
+		IndependentLogFWeightedLogLikelihood::Vector IndependentLogFWeightedLogLikelihood::get_prior_mode() const {
+			Vector result = Vector::Zero( m_value_of_first_derivative.size() ) ;
+			for( std::size_t i = 0; i < m_parameter_indices.size(); ++i ) {
+				// mode is logit() of mode of beta distribution with shape1=1+alpha, shape2=1+beta
+				// this is given by:
+				double mode = m_alpha[i] / ( m_alpha[i] + m_beta[i] ) ;
+				result[i] = std::log( mode / (1.0 - mode)) ;
+			}
+			return result ;
+		}
+	
+		std::string IndependentLogFWeightedLogLikelihood::get_summary() const {
+			std::ostringstream ostr ;
+			ostr << m_ll->get_summary() << "\n" ;
+			ostr << "  with priors:\n" ;
+			std::size_t max_label_length = 0 ;
+			int const numberOfParameters = m_ll->identify_parameters().rows() ;
+			for( int i = 0; i < numberOfParameters; ++i ) {
+				max_label_length = std::max( max_label_length, m_ll->get_parameter_name(i).size() ) ;
+			}
+
+			for( std::size_t i = 0; i < m_parameter_indices.size(); ++i ) {
+				int const parameter_index = m_parameter_indices[i] ;
+				ostr
+					<< "  "
+					<< std::setw( max_label_length)
+					<< m_ll->get_parameter_name(parameter_index)
+					<< " ~ logF( "
+					<< (m_alpha[i]*2) << ", " << (m_beta[i]*2)
+					<< " ).\n" ;
+			}
+#if 0			
+			
+			ostr
+				<< std::setw(3) << "" << "  "
+				<< std::setw( max_label_length + 2 ) << ""
+				<< ":"
+				<< " " << std::setw(5) << "alpha"
+				<< " " << std::setw(5) << "beta"
+				<< "\n" ;
+			for( std::size_t i = 0; i < m_parameter_indices.size(); ++i ) {
+				int const parameter_index = m_parameter_indices[i] ;
+				ostr << std::setw(3) << parameter_index
+					<< ": " << std::setw( max_label_length + 2 ) << m_ll->get_parameter_name(parameter_index) << ":" ;
+					ostr
+						<< " " << std::setw(5) << m_alpha[i]
+						<< " " << std::setw(5) << m_beta[i]
+						<< "\n" ;
+			}
+#endif
+			return ostr.str() ;
+		}
+	}
+}

ADDED   metro/src/regression/IndependentNormalWeightedLogLikelihood.cpp
Index: metro/src/regression/IndependentNormalWeightedLogLikelihood.cpp
==================================================================
--- metro/src/regression/IndependentNormalWeightedLogLikelihood.cpp
+++ metro/src/regression/IndependentNormalWeightedLogLikelihood.cpp
@@ -0,0 +1,133 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include <memory>
+#include <iostream>
+#include <iomanip>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "Eigen/LU"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/regression/IndependentNormalWeightedLogLikelihood.hpp"
+
+// #define DEBUG_NORMALWEIGHTEDLOGLIKELIHOOD 1
+
+namespace metro {
+	namespace regression {
+		IndependentNormalWeightedLogLikelihood::UniquePtr IndependentNormalWeightedLogLikelihood::create(
+			LogLikelihood::UniquePtr ll,
+			std::vector< int > parameter_indices,
+			std::vector< double > means,
+			std::vector< double > variances
+		) {
+			return UniquePtr( new IndependentNormalWeightedLogLikelihood( ll, parameter_indices, means, variances ) ) ;
+		}
+
+		IndependentNormalWeightedLogLikelihood::IndependentNormalWeightedLogLikelihood(
+			LogLikelihood::UniquePtr ll,
+			std::vector< int > parameter_indices,
+			std::vector< double > means,
+			std::vector< double > variances
+		):
+			m_ll( ll ),
+			m_parameter_indices( parameter_indices ),
+			m_means( means ),
+			m_variances( variances ),
+			m_normalisation( eZeroAtMean ),
+			m_constant( 0.0 ) // ll when at mean
+		{
+			if( m_normalisation == eZeroAtMean ) {
+				m_constant = 0.0 ;
+			} else if( m_normalisation == ePDF ) {
+				assert(0) ; // This may not be correct yet
+				m_constant = 0.0 ;
+				for( std::size_t i = 0; i < m_parameter_indices.size(); ++i ) {
+					m_constant -= std::log( std::sqrt( 2.0 * 3.14159265358979323846 * m_variances[i] )) ;
+				}
+			} else {
+				assert(0) ;
+			}
+		}
+
+		std::string IndependentNormalWeightedLogLikelihood::get_parameter_name( std::size_t i ) const {
+			return m_ll->get_parameter_name(i) ;
+		}
+		IndependentNormalWeightedLogLikelihood::IntegerMatrix IndependentNormalWeightedLogLikelihood::identify_parameters() const {
+			return m_ll->identify_parameters() ;
+		}
+		
+		int IndependentNormalWeightedLogLikelihood::number_of_parameters() const {
+			return m_ll->number_of_parameters() ;
+		}
+
+		int IndependentNormalWeightedLogLikelihood::number_of_outcomes() const {
+			return m_ll->number_of_outcomes() ;
+		}
+		
+		void IndependentNormalWeightedLogLikelihood::evaluate_at( Point const& parameters, int const numberOfDerivatives ) {
+			m_ll->evaluate_at( parameters, numberOfDerivatives ) ;
+			evaluate( numberOfDerivatives ) ;
+		}
+		
+		void IndependentNormalWeightedLogLikelihood::evaluate( int const numberOfDerivatives ) {
+			m_ll->evaluate( numberOfDerivatives ) ;
+			Vector const& parameters = m_ll->parameters() ;
+
+			m_value_of_function = 0.0 ;
+			m_value_of_first_derivative.setZero( parameters.size() ) ;
+			m_value_of_second_derivative.setZero( parameters.size(), parameters.size() ) ;
+			for( std::size_t i = 0; i < m_parameter_indices.size(); ++i ) {
+				int const& parameter_index = m_parameter_indices[i] ;
+				assert( parameter_index >= 0 && parameter_index < parameters.size() ) ;
+				double const centralised = (parameters(parameter_index)-m_means[i]) ;
+
+				m_value_of_function += -0.5 * (centralised * centralised) / m_variances[i] ;
+				m_value_of_first_derivative( parameter_index ) = -centralised / m_variances[i] ;
+				m_value_of_second_derivative( parameter_index, parameter_index )
+					= -1.0 / m_variances[i] ;
+			}
+			m_value_of_function += m_constant ;
+		}
+		
+		IndependentNormalWeightedLogLikelihood::Vector IndependentNormalWeightedLogLikelihood::get_prior_mode() const {
+			Vector result = Vector::Zero( m_value_of_first_derivative.size() ) ;
+			for( std::size_t i = 0; i < m_parameter_indices.size(); ++i ) {
+				result(i) = m_means[i] ;
+			}
+			return result ;
+		}
+	
+		std::string IndependentNormalWeightedLogLikelihood::get_summary() const {
+			std::ostringstream ostr ;
+			ostr << "independently-normal-weighted:" << m_ll->get_summary() << "\n" ;
+			ostr << "independently-normal-weighted: using the following prior parameters:\n" ;
+			std::size_t max_label_length = 0 ;
+			int const numberOfParameters = m_ll->identify_parameters().rows() ;
+			for( int i = 0; i < numberOfParameters; ++i ) {
+				max_label_length = std::max( max_label_length, m_ll->get_parameter_name(i).size() ) ;
+			}
+			ostr
+				<< std::setw(3) << "" << "  "
+				<< std::setw( max_label_length + 2 ) << ""
+				<< ":"
+				<< " " << std::setw(5) << "mean"
+				<< " " << std::setw(8) << "variance"
+				<< "\n" ;
+			for( std::size_t i = 0; i < m_parameter_indices.size(); ++i ) {
+				int const parameter_index = m_parameter_indices[i] ;
+				ostr << std::setw(3) << parameter_index
+					<< ": " << std::setw( max_label_length + 2 ) << m_ll->get_parameter_name(parameter_index) << ":" ;
+					ostr
+						<< " " << std::setw(5) << m_means[i]
+						<< " " << std::setw(8) << m_variances[i]
+						<< "\n" ;
+			}
+			return ostr.str() ;
+		}
+	}
+}

ADDED   metro/src/regression/LogLikelihood.cpp
Index: metro/src/regression/LogLikelihood.cpp
==================================================================
--- metro/src/regression/LogLikelihood.cpp
+++ metro/src/regression/LogLikelihood.cpp
@@ -0,0 +1,23 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include "metro/regression/LogLikelihood.hpp"
+
+namespace metro {
+	namespace regression {
+		LogLikelihood::~LogLikelihood() {}
+		
+		std::vector< std::string > LogLikelihood::get_parameter_names() const {
+			std::size_t const n = identify_parameters().rows() ;
+			std::vector< std::string > result(n, "") ;
+			for( std::size_t i = 0; i < n; ++i ) {
+				result[i] = get_parameter_name(i) ;
+			}
+			return result ;
+		}
+	}
+}
+

ADDED   metro/src/regression/LogUnnormalisedPosterior.cpp
Index: metro/src/regression/LogUnnormalisedPosterior.cpp
==================================================================
--- metro/src/regression/LogUnnormalisedPosterior.cpp
+++ metro/src/regression/LogUnnormalisedPosterior.cpp
@@ -0,0 +1,52 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/SmoothFunction.hpp"
+#include "metro/regression/LogUnnormalisedPosterior.hpp"
+
+namespace metro {
+	namespace regression {
+		LogUnnormalisedPosterior::LogUnnormalisedPosterior( LogLikelihood& loglikelihood, SmoothFunction& posterior ):
+			m_ll( loglikelihood ),
+			m_prior( posterior )
+		{}
+
+		LogLikelihood const& LogUnnormalisedPosterior::ll() const {
+			return m_ll ;
+		}
+
+		SmoothFunction const& LogUnnormalisedPosterior::prior() const {
+			return m_prior ;
+		}
+		
+		std::string LogUnnormalisedPosterior::get_summary() const {
+			std::string result = "LogUnnormalisedPosterior:\n" ;
+			result +=
+				    "  loglikelihood: " + m_ll.get_summary()
+				+ "\n  prior: " + m_prior.get_summary()
+				+ "\n" ;
+			return result ;
+		}
+		
+		void LogUnnormalisedPosterior::evaluate_at(
+			LogUnnormalisedPosterior::Vector const& parameters,
+			int const numberOfDerivatives
+		) {
+			m_parameters = parameters ;
+			evaluate( numberOfDerivatives ) ;
+		}
+
+		void LogUnnormalisedPosterior::evaluate(
+			int const numberOfDerivatives
+		) {
+			m_ll.evaluate_at( m_parameters, numberOfDerivatives ) ;
+			m_prior.evaluate_at( m_parameters, numberOfDerivatives ) ;
+		}
+	}
+}
+

ADDED   metro/src/regression/Logistic.cpp
Index: metro/src/regression/Logistic.cpp
==================================================================
--- metro/src/regression/Logistic.cpp
+++ metro/src/regression/Logistic.cpp
@@ -0,0 +1,352 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <utility>
+#include <algorithm>
+#include <boost/format.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+#include "metro/regression/Logistic.hpp"
+#include "metro/intersect_ranges.hpp"
+#include "metro/summation.hpp"
+#include "genfile/string_utils.hpp"
+#include "genfile/Error.hpp"
+
+// #define DEBUG_LOGLIKELIHOOD 2
+
+namespace metro {
+	namespace regression {
+		
+		namespace {
+			std::string standard_parameter_name( std::string const& predictor_name, std::string const& outcome_name ) {
+				return predictor_name + "/" + outcome_name ;
+			}
+		}
+		
+		Logistic::UniquePtr Logistic::create(
+			regression::Design& design
+		) {
+			return Logistic::UniquePtr(
+				new Logistic( design )
+			) ;
+		}
+
+		Logistic::UniquePtr Logistic::create(
+			regression::Design::UniquePtr design
+		) {
+			return Logistic::UniquePtr(
+				new Logistic( design )
+			) ;
+		}
+
+		namespace {
+			void check_design( regression::Design const& design ) {
+				// Verify design looks sane.
+				// Right now we handle only a bernoulli outcome, i.e.
+				// each sample must have a 1 in column 0 or 1 of the outcome matrix.
+				Logistic::Matrix const& outcome = design.outcome() ;
+				if( outcome.cols() != 2 ) {
+					throw genfile::BadArgumentError(
+						"metro::case_control::Logistic::check_design()",
+						"design",
+						"Expected outcome to have 2 columns (count of fail and success outcomes) with row sums == 1"
+					) ;
+				}
+				regression::Design::SampleRanges const& ranges = design.nonmissing_samples() ;
+				for( std::size_t range_i = 0; range_i < ranges.size(); ++range_i ) {
+					for( int i = ranges[range_i].begin(); i < ranges[range_i].end(); ++i ) {
+						if(
+							(outcome.row(i).sum() == outcome.row(i).sum())
+							&& (
+								( outcome.row(i).sum() != 1.0 )
+								|| ( outcome(i,0) != 1.0 && outcome(i,1) != 1.0 )
+							)
+						) {
+							throw genfile::BadArgumentError(
+								"metro::case_control::Logistic::check_design()",
+								"design",
+								( boost::format( "Outcome (%f for individual %d) has non-missing level other than zero or one." ) % outcome(i) % (i+1) ).str()
+							) ;
+						}
+					}
+				}
+			}
+		}
+
+		Logistic::Logistic(
+			regression::Design::UniquePtr design
+		):
+			m_design( design.release() ),
+			m_design_owned( true ),
+			m_get_parameter_name( &standard_parameter_name ),
+			m_parameters( Vector::Zero( m_design->matrix().cols() ) ),
+			m_state( e_Uncomputed )
+		{
+			check_design( *m_design ) ;
+		}
+
+		Logistic::Logistic(
+			regression::Design& design
+		):
+			m_design( &design ),
+			m_design_owned( false ),
+			m_get_parameter_name( &standard_parameter_name ),
+			m_parameters( Vector::Zero( m_design->matrix().cols() ) ),
+			m_state( e_Uncomputed )
+		{
+			assert( m_design != 0 ) ;
+			check_design( *m_design ) ;
+		}
+		
+		Logistic::~Logistic() {
+			if( m_design_owned ) {
+				delete m_design ;
+			}
+		}
+
+		std::string Logistic::get_summary() const {
+			using genfile::string_utils::to_string ;
+			return "Logistic( "
+				+ to_string( m_design->outcome().rows() )
+				+ " samples )" ;
+		}
+
+		void Logistic::set_parameter_naming_scheme( Logistic::GetParameterName get_parameter_name ) {
+			assert( get_parameter_name ) ;
+			m_get_parameter_name = get_parameter_name ;		
+		}
+	
+		std::string Logistic::get_parameter_name( std::size_t i ) const {
+			IntegerMatrix const identity = identify_parameters() ;
+			return m_get_parameter_name( m_design->get_predictor_name( identity(i,1) ), m_design->get_outcome_name(identity(i,0)) ) ;
+		}
+	
+		int Logistic::number_of_parameters() const {
+			return m_design->matrix().cols() ;
+		}
+
+		LogLikelihood::IntegerMatrix Logistic::identify_parameters() const {
+			IntegerMatrix result = IntegerMatrix::Zero( m_design->matrix().cols(), 2 ) ;
+			// Each parameter corresponds to an effect for the non-baseline outcome level
+			// and a column of the design matrix.
+			result.col(0).setConstant( 1.0 ) ;
+			// There is one parameter per design matrix column.
+			for( int i = 0; i < m_design->matrix().cols(); ++i ) {
+				result( i, 1 ) = i ;
+			}
+			return result ;
+		}
+
+		int Logistic::number_of_outcomes() const {
+			return 2 ;
+		}
+
+		void Logistic::evaluate_at( Point const& parameters, int const numberOfDerivatives ) {
+			evaluate_at_impl( parameters, m_design->nonmissing_samples(), numberOfDerivatives ) ;
+		}
+
+		void Logistic::evaluate_at_impl(
+			Point const& parameters,
+			std::vector< metro::SampleRange > const& included_samples,
+			int const numberOfDerivatives
+		) {
+//			m_state = eUncomputed ;
+			assert( parameters.size() == m_design->matrix().cols() ) ;
+			assert( numberOfDerivatives < 3 ) ;
+
+			m_state = e_Uncomputed ;
+			m_parameters = parameters ;
+			m_included_samples = included_samples ;
+
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << std::fixed << std::setprecision(4) ;
+			int const N = m_design->outcome().rows() ;
+			std::cerr << "==== Logistic::evaluate_at() ====\n" ;
+			std::cerr << "  m_state: " << ( boost::format( "0x%x" ) % m_state ).str() << ", "
+				<< "Number of samples: " << N << ", "
+				<< "Included samples:" ;
+			for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+				std::cerr << " " << included_samples[i].begin() << "-" << included_samples[i].end() ;
+			}
+			std::cerr << "\n" ;
+			std::cerr << "  Params: " << parameters.transpose() << ".\n" ;
+			std::cerr << "  Phenotypes: " << m_design->outcome().col(1).head( std::min( N, 5 ) ).transpose() << "...\n";
+			//std::cerr << "  Predictor levels: " << m_design->get_predictor_levels().transpose() << ".\n" ;
+#endif
+			evaluate( numberOfDerivatives ) ;
+		}
+		
+		void Logistic::evaluate( int const numberOfDerivatives ) {
+			bool computeFunction = ( m_state == e_Uncomputed ) ;
+			bool compute1stDerivative = ( (numberOfDerivatives > 0) & !(m_state & e_Computed1stDerivative )) ;
+			bool compute2ndDerivative = ( (numberOfDerivatives > 1) & !(m_state & e_Computed2ndDerivative )) ;
+
+			// Calculate log-likelihood if needed.
+			if( computeFunction ) {
+	 			calculate_outcome_probabilities( m_parameters, m_design->outcome(), &m_outcome_probabilities ) ;
+				m_A = m_design->get_predictor_level_probabilities().array() * m_outcome_probabilities.array() ;
+				compute_value_of_function( m_A, m_included_samples ) ;
+				m_state |= e_ComputedFunction ;
+				// (m_state | e_ComputedFunction) = 1 implies m_A and m_outcome_probabilities, as well as function value, are computed
+			}
+
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "  " << ( computeFunction ? "(computed) " : "(memoized) " ) << "function value = " << m_value_of_function << "\n" ;
+#endif
+
+			if( compute1stDerivative ) {
+				compute_value_of_first_derivative( m_A, m_included_samples, &m_B ) ;
+				m_state |= e_Computed1stDerivative ;
+				// m_state | e_Computed1stDerivative implies m_B, as well as 1st derivative, are computed
+			}
+#if DEBUG_LOGLIKELIHOOD
+			if( m_state & e_Computed1stDerivative ) {
+				std::cerr << "  " << ( compute1stDerivative ? "(computed) " : "(memoized) " ) << "derivative = " << m_value_of_first_derivative.transpose() << "\n" ;
+			} else {
+				std::cerr << "  (1st derivative not computed).\n" ;
+			}
+#endif
+
+			if( compute2ndDerivative ) {
+				compute_value_of_second_derivative( m_B, m_included_samples ) ;
+				m_state |= e_Computed2ndDerivative ;
+			}
+#if DEBUG_LOGLIKELIHOOD
+			if( m_state & e_Computed2ndDerivative ) {
+				std::cerr << "  " << ( compute2ndDerivative ? "(computed) " : "(memoized) " ) << "2nd derivative = \n"
+					<< m_value_of_second_derivative << ".\n" ;
+			} else {
+				std::cerr << "  (2nd derivative not computed).\n" ;
+			}
+			std::cerr << "====\n" ;
+#endif
+		}
+		
+		Logistic::Point const& Logistic::parameters() const {
+			return m_parameters ;
+		}
+
+		// Calculate P( outcome | genotype, covariates, parameters ).
+		void Logistic::calculate_outcome_probabilities(
+			Vector const& parameters,
+			Matrix const& outcome,
+			Logistic::Matrix* result
+		) const {
+			assert( outcome.cols() == 2 ) ;
+			result->resize( outcome.rows(), m_design->get_number_of_predictor_levels() ) ;
+			Vector linear_combination ;
+			int const number_of_predictor_levels = m_design->get_number_of_predictor_levels() ;
+			for( int g = 0; g < number_of_predictor_levels; ++g ) {
+				Matrix const& design_matrix = m_design->set_predictor_level( g ).matrix() ;
+				result->col( g ) = evaluate_mean_function( design_matrix * parameters, outcome ) ;
+			}
+		}
+		
+		Logistic::Vector Logistic::evaluate_mean_function( Vector const& linear_combinations, Matrix const& outcomes ) const {
+			assert( linear_combinations.size() == outcomes.rows() ) ;
+			// Only the 2nd column of the outcome (i.e. outcome is not baseline) is used in this calculation.
+			Vector exps = linear_combinations.array().exp() ;
+			Vector ones = Vector::Ones( linear_combinations.size() ) ;
+			return ( ones.array() + outcomes.col(1).array() * ( exps.array() - ones.array() ) )  / ( ones + exps ).array() ;
+		}
+
+		void Logistic::compute_value_of_function( Matrix const& V, std::vector< metro::SampleRange > const& included_samples ) {
+			m_value_of_function = 0.0 ;
+			for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+				int const start_row = included_samples[i].begin() ;
+				int const end_row = included_samples[i].end() ;
+				m_value_of_function += neumaier_sum(
+					V.block( start_row, 0, end_row - start_row, V.cols() ).rowwise().sum().array().log()
+				) ;
+			}
+		}
+
+		void Logistic::compute_value_of_first_derivative( Matrix const& A, std::vector< metro::SampleRange > const& included_samples, Matrix* B ) {
+			int const N = m_design->outcome().rows() ;
+			int const D = m_design->matrix().cols() ;
+			int const N_predictor_levels = m_design->get_number_of_predictor_levels() ;
+			// ...and its first derivative...
+			m_value_of_first_derivative = Vector::Zero( D ) ;
+			(*B) = A ;
+			{
+				RowVector ones( RowVector::Ones( N_predictor_levels )) ;
+				for( int i = 0; i < B->rows(); ++i ) {
+					B->row(i) /= B->row(i).sum() ;
+					B->row(i).array() *= ( ones - m_outcome_probabilities.row(i) ).array() ;
+				}
+			}
+
+			{
+				m_first_derivative_terms.setZero( m_design->matrix().rows(), m_design->matrix().cols() ) ;
+				Vector signs = (( m_design->outcome().col(1) * 2.0 ) - Vector::Ones( N ) ) ; // == (-1)^{phenotype + 1}
+				for( int g = 0; g < N_predictor_levels; ++g ) {
+					Matrix const& design_matrix = m_design->set_predictor_level( g ).matrix() ;
+#if DEBUG_LOGLIKELIHOOD
+					std::cerr << "Logistic::compute_value_of_first_derivative(): design_matrix for predictor level " << g << " =\n"
+						<< design_matrix.topRows( std::min( N, 5 ) ) << "\n" ;
+#endif
+					//m_design->matrix().block( 0, 1, m_design->matrix().rows(), predictor_levels.cols() ).rowwise() = predictor_levels.row( g ) ;
+					for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+						int const start_row = included_samples[i].begin() ;
+						int const end_row = included_samples[i].end() ;
+						MatrixBlock block = m_first_derivative_terms.block( start_row, 0, end_row - start_row, m_first_derivative_terms.cols() ) ;
+						// multiply ith row of design matrix by sign times ith entry of column of B.
+						block += (
+								signs.segment( start_row, end_row - start_row ).array()
+								* B->col( g ).segment( start_row, end_row - start_row ).array()
+							).matrix().asDiagonal()
+							* design_matrix.block( start_row, 0, end_row - start_row, design_matrix.cols() )
+						;
+					}
+				}
+				m_value_of_first_derivative = m_first_derivative_terms.colwise().sum() ;
+			}
+		}
+
+		void Logistic::compute_value_of_second_derivative( Matrix const& B, std::vector< metro::SampleRange > const& included_samples ) {
+			int const D = m_design->matrix().cols() ;
+			int const N_predictor_levels = m_design->get_number_of_predictor_levels() ;
+			m_value_of_second_derivative = Matrix::Zero( D, D ) ;
+			// Compute second derivative...
+			for( int row_i = 0; row_i < D; ++row_i ) {
+				MatrixBlock resultRow = m_value_of_second_derivative.block(row_i, 0, 1, D ) ;
+				for( int g1 = 0; g1 < N_predictor_levels; ++g1 ) {
+					Matrix const& design_matrix = m_design->set_predictor_level( g1 ).matrix() ;
+					for( std::size_t sample_i = 0; sample_i < included_samples.size(); ++sample_i ) {
+						int const start_row = included_samples[sample_i].begin() ;
+						int const end_row = included_samples[sample_i].end() ;
+						ConstMatrixBlock design_matrix_block = design_matrix.block( start_row, 0, end_row - start_row, design_matrix.cols() ) ;
+						resultRow += (
+								B.col(g1).segment( start_row, end_row - start_row ).array()
+								* (
+									Vector::Constant( end_row - start_row, 1.0 )
+									- 2.0 * m_outcome_probabilities.col( g1 ).segment( start_row, end_row - start_row )
+								).array()
+								* design_matrix_block.col( row_i ).array()
+							).matrix().transpose()
+							* design_matrix_block
+						;
+					}
+				}
+				resultRow -= ( m_first_derivative_terms.col(row_i).asDiagonal() * m_first_derivative_terms ).colwise().sum() ;
+			}
+		}
+		
+		double Logistic::get_value_of_function() const {
+			return m_value_of_function ;
+		}
+
+		Logistic::Vector Logistic::get_value_of_first_derivative() const {
+			return m_value_of_first_derivative ;
+		}
+
+		Logistic::Matrix Logistic::get_value_of_second_derivative() const {
+			return m_value_of_second_derivative ;
+		}
+	}
+}

ADDED   metro/src/regression/MultinomialRegressionLogLikelihood.cpp
Index: metro/src/regression/MultinomialRegressionLogLikelihood.cpp
==================================================================
--- metro/src/regression/MultinomialRegressionLogLikelihood.cpp
+++ metro/src/regression/MultinomialRegressionLogLikelihood.cpp
@@ -0,0 +1,492 @@
+
+//			Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//	  (See accompanying file LICENSE_1_0.txt or copy at
+//			http://www.boost.org/LICENSE_1_0.txt)
+
+#define EIGEN_RUNTIME_NO_MALLOC
+#include <iostream>
+#include <numeric>
+#include <iomanip>
+#include <vector>
+#include <utility>
+#include <algorithm>
+#include <boost/iterator/counting_iterator.hpp>
+#include "metro/regression/MultinomialRegressionLogLikelihood.hpp"
+#include "metro/intersect_ranges.hpp"
+#include "metro/summation.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/string_utils/string_utils.hpp"
+
+// #define DEBUG_LOGLIKELIHOOD 1
+
+namespace metro {
+	namespace regression {
+		
+		namespace {
+			template< typename T >
+			std::ostream& print_matrix( std::string const& name, T const& matrix, std::ostream& out ) {
+				return out << name << " = (" << matrix.rows() << "x" << matrix.cols() << ")\n"
+					<< matrix << "\n" ;
+			}
+		}
+		
+		MultinomialRegressionLogLikelihood::UniquePtr MultinomialRegressionLogLikelihood::create(
+			regression::Design::UniquePtr design
+		) {
+			return MultinomialRegressionLogLikelihood::UniquePtr(
+				new MultinomialRegressionLogLikelihood( design )
+			) ;
+		}
+		
+		MultinomialRegressionLogLikelihood::MultinomialRegressionLogLikelihood(
+			regression::Design::UniquePtr design
+		):
+			m_design( design ),
+			m_number_of_samples( m_design->outcome().rows() ),
+			m_parameter_vector( Vector::Zero( m_design->matrix().cols() * ( m_design->outcome().cols() - 1 ) )),
+			m_parameter_matrix( Matrix::Zero( m_design->matrix().cols(), m_design->outcome().cols() - 1 ) ),
+			m_parameter_identity( compute_parameter_identity() ),
+			m_numberOfDerivativesComputed( 0 )
+		{
+			assert( m_design.get() != 0 ) ;
+		}
+
+		std::string MultinomialRegressionLogLikelihood::get_summary() const {
+			using genfile::string_utils::to_string ;
+			return "MultinomialRegressionLogLikelihood( " + to_string( m_number_of_samples ) + " samples, " + to_string( m_design->outcome().cols() ) + " outcomes )" ;
+		}
+
+		void MultinomialRegressionLogLikelihood::set_predictor_levels(
+			Matrix const& levels,
+			Matrix const& probabilities,
+			std::vector< metro::SampleRange > const& included_samples
+		) {
+			m_design->set_predictors( levels, probabilities, included_samples ) ;
+
+#if DEBUG_LOGLIKELIHOOD
+			int const print_N = std::min( m_design->outcome().rows(), Vector::Index( 10 ) ) ;
+			int const number_of_outcomes = m_design->outcome().cols() ;
+			std::cerr << "MultinomialRegressionLogLikelihood::number of outcomes = " << number_of_outcomes << "\n" ;
+			std::cerr << "MultinomialRegressionLogLikelihood::set_predictor_levels(): Included samples:" ;
+			for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+				std::cerr << " " << included_samples[i].begin() << "-" << included_samples[i].end() ;
+			}
+			std::cerr << "\n" ;
+			Matrix const& design_matrix = m_design->set_predictor_level(0).matrix() ;
+			std::cerr << "MultinomialRegressionLogLikelihood::design matrix = (" << design_matrix.rows() << "x" << design_matrix.cols() << ")\n"
+				<< design_matrix.block( 0, 0, print_N, design_matrix.cols() ) << "\n" ;
+			std::cerr << "MultinomialRegressionLogLikelihood::predictor levels = (" << levels.rows() << "x" << levels.cols() << ")\n"
+				<< levels << "\n" ;
+#endif
+			compute_psi( m_design->outcome(), levels.rows(), included_samples, &m_psi ) ;
+			compute_rearranger( levels.rows(), &m_outcome_wise_to_predictor_wise_rearranger ) ;
+			m_numberOfDerivativesComputed = 0 ;
+
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "MultinomialRegressionLogLikelihood:" ;
+			std::cerr << "outcome =\n" << m_design->outcome().head( print_N ) << "\n" ;
+			print_matrix( "psi", m_psi.block( 0, 0, print_N, m_psi.cols() ), std::cerr ) ;
+#endif
+		}
+		
+		void MultinomialRegressionLogLikelihood::compute_psi(
+			Matrix const& outcome,
+			int const number_of_predictor_levels,
+			std::vector< metro::SampleRange > const& included_samples,
+			Matrix* result
+		) const {
+			// psi is N x LM, thought of as M blocks of NxL.
+			// For each sample, we put a row of L 1's in the columns corresponding to the outcome for that sample.
+			assert( result != 0 ) ;
+			
+			int const number_of_outcomes = outcome.cols() ;
+			result->setZero( m_number_of_samples, number_of_outcomes * number_of_predictor_levels ) ;
+			for( int i = 0; i < included_samples.size(); ++i ) {
+				int const start_row = included_samples[i].begin() ;
+				int const end_row = included_samples[i].end() ;
+				for( int sample = start_row; sample < end_row; ++sample ) {
+					// look for the 1 identifying the outcome for this sample
+					Matrix::Index outcome_i = 0 ;
+					result->block( sample, outcome_i * number_of_predictor_levels, 1, number_of_predictor_levels ).setConstant( 1.0 ) ;
+				}
+			}
+		}
+		
+		void MultinomialRegressionLogLikelihood::compute_rearranger( int const number_of_predictor_levels, PermutationMatrix* result ) const {
+			// rearranger is MLxML.	 It is a square matrix which when multiplied on the right turns a matrix like
+			// f1(x1) f2(x1) ... fM(x1) f1(x2)...etc (L blocks of NxM)
+			// into
+			// f1(x1) f1(x2) ... f1(xl) f2(x1)...etc (M blocks of NxL).
+			int const number_of_outcomes = m_design->outcome().cols() ;
+			result->setIdentity(
+				number_of_predictor_levels * number_of_outcomes
+			) ;
+			int column = 0 ;
+			for( int j = 0; j < number_of_outcomes; ++j ) {
+				for( int level_i = 0; level_i < number_of_predictor_levels; ++level_i, ++column ) {
+//					result->indices().data()[( level_i * number_of_outcomes + j )] = column ;
+					result->indices().data()[ column ] = ( level_i * number_of_outcomes ) + j ;
+				}
+			}
+#if DEBUG_LOGLIKELIHOOD			
+			std::cerr << "Rearranger2:\n" << result->toDenseMatrix() << "\n" ;
+#endif
+		}
+		
+		MultinomialRegressionLogLikelihood::Vector const& MultinomialRegressionLogLikelihood::parameters() const {
+			return m_parameter_vector ;
+		}
+		
+		void MultinomialRegressionLogLikelihood::evaluate_at(
+			Vector const& parameters,
+			int const numberOfDerivatives
+		) {
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "MultinomialRegressionLogLikelihood::evaluate_at(): parameters = " << parameters.transpose() << "\n" ;
+#endif
+			int const number_of_outcomes = m_design->outcome().cols() ;
+			assert( parameters.size() == m_design->matrix().cols() * ( number_of_outcomes - 1 ) ) ;
+			
+			m_parameter_vector = parameters ;
+			m_numberOfDerivativesComputed = 0 ;
+			m_parameter_matrix.resize( m_design->matrix().cols(), number_of_outcomes - 1 ) ; 
+			for( int i = 0; i < m_parameter_vector.size(); ++i ) {
+				m_parameter_matrix( m_parameter_identity( i, 1 ), m_parameter_identity( i, 0 ) - 1 ) = m_parameter_vector(i) ;
+			}
+			
+			evaluate( numberOfDerivatives ) ;
+		}
+
+		void MultinomialRegressionLogLikelihood::evaluate( int const numberOfDerivatives ) {
+			if( m_numberOfDerivativesComputed <= numberOfDerivatives ) {
+				evaluate_impl( numberOfDerivatives ) ;
+			}
+		}
+		
+		void MultinomialRegressionLogLikelihood::set_parameter_naming_scheme( MultinomialRegressionLogLikelihood::GetParameterName get_parameter_name ) {
+			assert( get_parameter_name ) ;
+			m_get_parameter_name = get_parameter_name ;
+		}
+
+		std::string MultinomialRegressionLogLikelihood::get_parameter_name( std::size_t i ) const {
+			IntegerMatrix const identity = identify_parameters() ;
+			return m_get_parameter_name( m_design->get_predictor_name( identity(i,1)), identity(i,0) ) ;
+		}
+
+		LogLikelihood::IntegerMatrix MultinomialRegressionLogLikelihood::identify_parameters() const {
+			return m_parameter_identity ;
+		}
+
+		int MultinomialRegressionLogLikelihood::number_of_parameters() const {
+			return m_parameter_identity.rows() ;
+		}
+
+		int MultinomialRegressionLogLikelihood::number_of_outcomes() const {
+			return m_design->outcome().cols() ;
+		}
+
+		LogLikelihood::IntegerMatrix MultinomialRegressionLogLikelihood::compute_parameter_identity() const {
+			// each parameter corresponds to a column of the design matrix and a non-baseline phenotype level.
+			IntegerMatrix result = IntegerMatrix::Zero( m_parameter_vector.size(), 2 ) ;
+			int const D = m_design->matrix().cols() ;
+			int const number_of_outcomes = m_design->outcome().cols() ;
+			for( int j = 0; j < D; ++j ) {
+				for( int i = 1; i < number_of_outcomes; ++i ) {
+					result( (i-1)*D + j, 0 ) = i ;
+					result( (i-1)*D + j, 1 ) = j ;
+				}
+			}
+			return result ;
+		}
+
+		void MultinomialRegressionLogLikelihood::evaluate_impl(
+			int const numberOfDerivatives
+		) {
+			std::vector< metro::SampleRange > const& included_samples = m_design->nonmissing_samples() ;
+			int const number_of_outcomes = m_design->outcome().cols() ;
+			assert( numberOfDerivatives < 3 ) ;
+
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "parameters = " << m_parameter_vector.transpose() << ".\n" ;
+			print_matrix( "parameter matrix", m_parameter_matrix, std::cerr ) ;
+#endif
+			compute_F( m_parameter_matrix, &m_F ) ;
+			compute_A_and_function_value( m_F, m_design->get_predictor_level_probabilities(), included_samples, &m_A, &m_value_of_function ) ;
+#if DEBUG_LOGLIKELIHOOD
+			int const print_N = std::min( m_design->outcome().rows(), Vector::Index( 10 ) ) ;
+			print_matrix( "F", m_F.block( 0, 0, print_N, m_F.cols() ), std::cerr ) ;
+			print_matrix( "A", m_A.block( 0, 0, print_N, m_A.cols() ), std::cerr ) ;
+			print_matrix( "psi", m_psi.block( 0, 0, print_N, m_psi.cols() ), std::cerr ) ;
+			std::cerr << "function value = \n" << m_value_of_function << "\n" ;
+#endif
+			++m_numberOfDerivativesComputed ;
+			if( numberOfDerivatives > 0 ) {
+				compute_B( m_A, m_F, m_psi, &m_B ) ;
+				compute_value_of_first_derivative( m_B, included_samples, &m_value_of_first_derivative, &m_first_derivative_terms ) ;
+				++m_numberOfDerivativesComputed ;
+#if DEBUG_LOGLIKELIHOOD
+				print_matrix( "B", m_B.block( 0, 0, print_N, m_B.cols() ), std::cerr ) ;
+				print_matrix( "C", m_C.block( 0, 0, print_N, m_C.cols() ), std::cerr ) ;
+				std::cerr << "derivative = \n" << m_value_of_first_derivative << "\n" ;
+#endif
+				if( numberOfDerivatives > 1 ) {
+					compute_C( m_A, m_F, m_psi, included_samples, &m_C ) ;
+					compute_value_of_second_derivative( m_B, m_C, included_samples, &m_value_of_second_derivative ) ;
+					++m_numberOfDerivativesComputed ;
+#if DEBUG_LOGLIKELIHOOD
+					print_matrix( "C", m_C.block( 0, 0, print_N, m_C.cols() ), std::cerr ) ;
+				
+					std::cerr << "2nd derivative = \n"
+						<< m_value_of_second_derivative << ".\n" ;
+#endif
+				}
+			}
+		}
+		
+		void MultinomialRegressionLogLikelihood::compute_F( Matrix const& parameters, Matrix* result ) const {
+			// F is NxLM, though of as (M+1) blocks of L.
+			// We compute it as L blocks of (M+1), since this leads to simpler code, and then rearrange columns.
+			int const number_of_levels = m_design->get_number_of_predictor_levels() ;
+			int const number_of_outcomes = m_design->outcome().cols() ;
+			result->setZero( m_number_of_samples, number_of_levels *  number_of_outcomes ) ;
+			Vector sums = Vector::Zero( m_number_of_samples ) ;
+			for( int level_i = 0; level_i < number_of_levels; ++level_i ) {
+				Matrix const& design_matrix = m_design->set_predictor_level( level_i ).matrix() ;
+				int const block_first_column = level_i * number_of_outcomes ;
+				MatrixBlock block = result->block( 0, block_first_column, m_number_of_samples, number_of_outcomes ) ;
+				// numerator for baseline outcome is 1
+				block.col(0).setConstant( 1.0 ) ;
+				// compute numerator for non-baseline outcomes
+				MatrixBlock alternative_outcome_block = result->block( 0, block_first_column + 1, m_number_of_samples, number_of_outcomes - 1 ) ;
+				alternative_outcome_block = ( design_matrix * parameters ).array().exp() ;
+				// Normalise all outcome probabilities
+				sums = alternative_outcome_block.rowwise().sum() ;
+				for( int col = 0; col < block.cols(); ++col ) {
+					block.col( col ).array() /= ( Vector::Constant( m_number_of_samples, 1.0 ) + sums ).array() ;
+				}
+			}
+			// We've computed F in the order
+			// f1(x1) f2(x1) ... fM(x1) f1(x2) ...
+			// We now re-arrange so that it comes in the order
+			// f1(x1) f1(x2) ... f1(xl) f2(x1)...
+			// as this fits better with the later computations.
+			// Split into seperate function for profiling.
+			rearrange_F( result ) ;
+		}
+
+		void MultinomialRegressionLogLikelihood::rearrange_F( Matrix* result ) const {
+			// We've computed F in the order
+			// f1(x1) f2(x1) ... fM(x1) f1(x2) ...
+			// We now re-arrange so that it comes in the order
+			// f1(x1) f1(x2) ... f1(xl) f2(x1)...
+			// as this fits better with the later computations.
+			(*result) *= m_outcome_wise_to_predictor_wise_rearranger ;
+		}
+		
+		void MultinomialRegressionLogLikelihood::compute_A_and_function_value(
+			Matrix const& F,
+			Matrix const& predictor_probabilities,
+			std::vector< metro::SampleRange > const& included_samples,
+			Matrix* result,
+			double* value_of_function
+		) const {
+			// A is NxL.
+			int const number_of_predictor_levels = predictor_probabilities.cols() ;
+			*value_of_function = 0.0 ;
+			result->setZero( m_number_of_samples, number_of_predictor_levels ) ;
+			for( std::size_t i = 0; i < included_samples.size(); ++i ) {
+				int const start_row = included_samples[i].begin() ;
+				int const end_row = included_samples[i].end() ;
+				for( int sample = start_row; sample < end_row; ++sample ) {
+					// Look for the 1 indicating which outcome this sample has
+					Matrix::Index outcome_i = 0 ;
+					m_design->outcome().row( sample ).array().maxCoeff( &outcome_i ) ;
+					// Find the F values corresponding to this sample's outcome
+					ConstMatrixBlock block_of_F = F.block( sample, outcome_i * number_of_predictor_levels, 1, number_of_predictor_levels ) ;
+					result->row( sample ) = predictor_probabilities.row( sample ).array() * block_of_F.array() ;
+				}
+				// Compute the log-likelihood for this block of samples as:
+				// the sum over samples of...
+				*value_of_function += neumaier_sum(
+					// the likelihood terms for these samples...
+					result->block( start_row, 0, end_row - start_row, number_of_predictor_levels )
+					 // ...summed over predictor levels...
+						.rowwise().sum()
+					 // ...and logarithm-ed...
+						.array().log()
+				) ;
+				// Now renormalise this block of A.
+				for( int sample = start_row; sample < end_row; ++sample ) {
+					result->row( sample ) /= result->row( sample ).sum() ;
+				}
+			}
+		}
+
+		void MultinomialRegressionLogLikelihood::compute_B( Matrix const& A, Matrix const& F, Matrix const& psi, Matrix* result ) const {
+			// B is NxLM, thought of as M blocks of L.
+			int const number_of_levels = m_design->get_number_of_predictor_levels() ;
+			int const M = m_design->outcome().cols() - 1 ;
+			result->setZero( m_number_of_samples, number_of_levels * M ) ;
+			for( int j = 0; j < M; ++j ) {
+				MatrixBlock block = result->block( 0, j * number_of_levels, m_number_of_samples, number_of_levels ) ;
+				// We use j+1 here to skip the baseline columns in F and psi.
+				ConstMatrixBlock block_of_F = F.block( 0, (j+1) * number_of_levels, m_number_of_samples, number_of_levels ) ;
+				ConstMatrixBlock block_of_psi = psi.block( 0, (j+1) * number_of_levels, m_number_of_samples, number_of_levels ) ;
+				block = A.array() * ( block_of_psi - block_of_F ).array() ;
+			}
+		}
+
+		void MultinomialRegressionLogLikelihood::compute_value_of_first_derivative(
+			Matrix const& B,
+			std::vector< metro::SampleRange > const& included_samples,
+			Vector* result,
+			Matrix* terms
+		) const {
+			int const D = m_design->matrix().cols() ;
+			int const number_of_levels = m_design->get_number_of_predictor_levels() ;
+			int const M = m_design->outcome().cols() - 1 ;
+			result->setZero( D * M ) ;
+			terms->setZero( m_design->matrix().rows(), D*M ) ;
+			for( int level_i = 0; level_i < number_of_levels; ++level_i ) {
+				Matrix const& design_matrix = m_design->set_predictor_level( level_i ).matrix() ;
+				for( int i = 0; i < included_samples.size(); ++i ) {
+					int const start_row = included_samples[i].begin() ;
+					int const end_row = included_samples[i].end() ;
+					for( int j = 0; j < M; ++j ) {
+						MatrixBlock block = terms->block( start_row, j*D, end_row - start_row, D ) ;
+						// multiply each row of the design matrix by the relevant term in the relevant column of B.
+						block += (
+							B.col( j * number_of_levels + level_i ).segment( start_row, end_row - start_row ).asDiagonal()
+							* design_matrix.block( start_row, 0, end_row - start_row, design_matrix.cols() )
+						) ;
+					}
+				}
+			}
+			(*result) = m_first_derivative_terms.colwise().sum() ;
+		}
+
+		void MultinomialRegressionLogLikelihood::compute_C(
+			Matrix const& A,
+			Matrix const& F,
+			Matrix const& psi,
+			std::vector< metro::SampleRange > const& included_samples,
+			Matrix* result
+		) const {
+			// B is NxLM^2, thought of as M blocks of ML, each block is M blocks of L.
+			int const number_of_levels = m_design->get_number_of_predictor_levels() ;
+			int const M = m_design->outcome().cols() - 1 ;
+			int const outer_blocksize = number_of_levels * M ;
+			result->setZero( m_number_of_samples, outer_blocksize * M ) ;
+			for( int j = 0; j < M; ++j ) {
+				ConstMatrixBlock jth_block_of_F = F.block( 0, (j+1) * number_of_levels, m_number_of_samples, number_of_levels ) ;
+				ConstMatrixBlock jth_block_of_psi = psi.block( 0, (j+1) * number_of_levels, m_number_of_samples, number_of_levels ) ;
+				for( int k = 0; k < M; ++k ) {
+					ConstMatrixBlock kth_block_of_F = F.block( 0, (k+1) * number_of_levels, m_number_of_samples, number_of_levels ) ;
+					ConstMatrixBlock kth_block_of_psi = psi.block( 0, (k+1) * number_of_levels, m_number_of_samples, number_of_levels ) ;
+					Matrix Zjk = -kth_block_of_F ;
+					if( j == k ) {
+						Zjk.array() = 1.0 + Zjk.array() ;
+					}
+					result->block( 0, j * outer_blocksize + k * number_of_levels, m_number_of_samples, number_of_levels ).array()
+						= A.array()
+						* (
+							(
+								( jth_block_of_psi - jth_block_of_F ).array()
+								* ( kth_block_of_psi - kth_block_of_F ).array()
+							)
+							- (
+								jth_block_of_F.array() * Zjk.array()
+							)
+						) ;
+				}
+			}
+		}
+
+		void MultinomialRegressionLogLikelihood::compute_value_of_second_derivative(
+			Matrix const& B,
+			Matrix const& C,
+			std::vector< metro::SampleRange > const& included_samples,
+			Matrix* result
+		) const {
+			int const D = m_design->matrix().cols() ;
+			int const number_of_levels = m_design->get_number_of_predictor_levels() ;
+			int const M = m_design->outcome().cols() - 1 ;
+			int const outer_blocksize = M * number_of_levels ;
+			result->setZero( D*M, D*M ) ;
+			m_design_matrix_tensor_square_rows.resize( m_design->matrix().rows(), D ) ;
+#if DEBUG_LOGLIKELIHOOD
+			std::cerr << "MultinomialRegressionLogLikelihood::compute_value_of_second_derivative(): C =\n"
+				<< C.block( 0, 0, std::min( int( C.rows() ), 10 ), C.cols() ) << "\n" ;
+#endif
+			for( int level_i = 0; level_i < number_of_levels; ++level_i ) {
+				Matrix const& design_matrix = m_design->set_predictor_level( level_i ).matrix() ;
+				for( int row_i = 0; row_i < D; ++row_i ) {
+#ifdef EIGEN_RUNTIME_NO_MALLOC
+					Eigen::internal::set_is_malloc_allowed( false ) ;
+#endif
+					m_design_matrix_tensor_square_rows = design_matrix.col( row_i ).asDiagonal() * design_matrix ;
+#ifdef EIGEN_RUNTIME_NO_MALLOC
+					Eigen::internal::set_is_malloc_allowed( true ) ;
+#endif
+					for( int i = 0; i < included_samples.size(); ++i ) {
+						int const start_row = included_samples[i].begin() ;
+						int const end_row = included_samples[i].end() ;
+						MatrixBlock design_matrix_tensor_square_row_block
+							= m_design_matrix_tensor_square_rows.block( start_row, 0, end_row - start_row, design_matrix.cols() ) ;
+						for( int j = 0; j < M; ++j ) {
+							for( int k = j; k < M; ++k ) {
+								MatrixBlock resultRow = result->block( j*D+row_i, k*D, 1, D ) ;
+									resultRow
+										+= (
+											C.block( start_row, j * outer_blocksize + k*number_of_levels + level_i, end_row - start_row, 1 ).transpose()
+											* design_matrix_tensor_square_row_block
+										)
+									;
+							}
+						}
+					}
+				}
+			}
+#ifdef EIGEN_RUNTIME_NO_MALLOC
+			Eigen::internal::set_is_malloc_allowed( false ) ;
+#endif
+			for( int i = 0; i < included_samples.size(); ++i ) {
+				int const start_row = included_samples[i].begin() ;
+				int const end_row = included_samples[i].end() ;
+				for( int row_i = 0; row_i < M*D; ++row_i ) {
+					MatrixBlock resultRow = result->block( row_i, 0, 1, M*D ) ;
+					resultRow.noalias() -= (
+						m_first_derivative_terms.col( row_i ).segment( start_row, end_row - start_row ).asDiagonal()
+							* m_first_derivative_terms.block( start_row, 0, end_row - start_row, M*D )
+						)
+						.colwise().sum() ;
+				}
+			}
+#ifdef EIGEN_RUNTIME_NO_MALLOC
+			Eigen::internal::set_is_malloc_allowed( true ) ;
+#endif
+
+			// fill lower diagonal
+			for( int j = 1; j < M; ++j ) {
+				for( int k = 0; k < j; ++k ) {
+					MatrixBlock target = result->block( j*D, k*D, D, D ) ;
+					MatrixBlock resultBlock = result->block( k*D, j*D, D, D ) ;
+					target.noalias() = resultBlock.transpose() ;
+				}
+			}
+		}
+
+		double MultinomialRegressionLogLikelihood::get_value_of_function() const {
+			return m_value_of_function ;
+		}
+
+		MultinomialRegressionLogLikelihood::Vector MultinomialRegressionLogLikelihood::get_value_of_first_derivative() const {
+			return m_value_of_first_derivative ;
+		}
+
+		MultinomialRegressionLogLikelihood::Matrix MultinomialRegressionLogLikelihood::get_value_of_second_derivative() const {
+			return m_value_of_second_derivative ;
+		}
+	}
+}

ADDED   metro/src/regression/NormalWeightedLogLikelihood.cpp
Index: metro/src/regression/NormalWeightedLogLikelihood.cpp
==================================================================
--- metro/src/regression/NormalWeightedLogLikelihood.cpp
+++ metro/src/regression/NormalWeightedLogLikelihood.cpp
@@ -0,0 +1,120 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include <memory>
+#include <iostream>
+#include <iomanip>
+#include <boost/noncopyable.hpp>
+#include "Eigen/Core"
+#include "Eigen/LU"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/regression/NormalWeightedLogLikelihood.hpp"
+
+// #define DEBUG_NORMALWEIGHTEDLOGLIKELIHOOD 1
+
+namespace metro {
+	namespace regression {
+		namespace impl {
+			double compute_mvn_constant( int const k, double determinant ) {
+				return -0.5 * k * std::log( 2 * 3.141592654 ) - 0.5 * std::log( determinant ) ;
+			}
+		}
+
+		NormalWeightedLogLikelihood::UniquePtr NormalWeightedLogLikelihood::create(
+			LogLikelihood::UniquePtr ll,
+			Vector const mean,
+			Matrix const covariance,
+			Normalisation normalisation
+		) {
+			return UniquePtr( new NormalWeightedLogLikelihood( ll, mean, covariance, normalisation ) ) ;
+		}
+
+		NormalWeightedLogLikelihood::NormalWeightedLogLikelihood(
+			LogLikelihood::UniquePtr ll,
+			Vector const mean,
+			Matrix const covariance,
+			Normalisation normalisation
+		):
+			m_ll( ll ),
+			m_mean( mean ),
+			m_covariance( covariance ),
+			m_normalisation( normalisation ),
+			m_solver( covariance ),
+			m_inverse_covariance( m_solver.solve( Matrix::Identity( mean.size(), mean.size() ))),
+			m_constant( impl::compute_mvn_constant( m_mean.size(), m_covariance.determinant() ))
+		{}
+
+		std::string NormalWeightedLogLikelihood::get_parameter_name( std::size_t i ) const {
+			return m_ll->get_parameter_name(i) ;
+		}
+		NormalWeightedLogLikelihood::IntegerMatrix NormalWeightedLogLikelihood::identify_parameters() const {
+			return m_ll->identify_parameters() ;
+		}
+		
+		int NormalWeightedLogLikelihood::number_of_parameters() const {
+			return m_ll->number_of_parameters() ;
+		}
+
+		int NormalWeightedLogLikelihood::number_of_outcomes() const {
+			return m_ll->number_of_outcomes() ;
+		}
+		
+		void NormalWeightedLogLikelihood::evaluate_at( Point const& parameters, int const numberOfDerivatives ) {
+			m_ll->evaluate_at( parameters, numberOfDerivatives ) ;
+			evaluate_impl( numberOfDerivatives ) ;
+		}
+
+		void NormalWeightedLogLikelihood::evaluate( int const numberOfDerivatives ) {
+			m_ll->evaluate( numberOfDerivatives ) ;
+			evaluate_impl( numberOfDerivatives ) ;
+		}
+
+		void NormalWeightedLogLikelihood::evaluate_impl( int const numberOfDerivatives ) {
+			Vector const& parameters = m_ll->parameters() ;
+			Vector solved = m_solver.solve( parameters - m_mean ) ;
+			m_log_density = -0.5 * ((parameters - m_mean).transpose() * solved)(0) ;
+			m_value_of_first_derivative = -solved ;
+			m_value_of_second_derivative = -m_inverse_covariance ;
+
+#if DEBUG_NORMALWEIGHTEDLOGLIKELIHOOD
+			std::cerr << "NormalWeightedLogLikelihood::evaluate_impl()\:\n" ;
+			std::cerr << "parameters = " << parameters.transpose() << ".\n" ;
+			std::cerr << "constant = " << m_constant << ".\n" ;
+			std::cerr << "solved = \n" << solved << ".\n" ;
+			std::cerr << "log density = " << m_log_density << "\n" ;
+#endif
+		}
+	
+		std::string NormalWeightedLogLikelihood::get_summary() const {
+			std::ostringstream ostr ;
+			ostr << "normal-weighted:" << m_ll->get_summary() << "\n" ;
+			ostr << "normal-weighted: using the following prior covariance:\n" ;
+			std::size_t max_label_length = 0 ;
+			for( int i = 0; i < m_covariance.rows(); ++i ) {
+				max_label_length = std::max( max_label_length, m_ll->get_parameter_name(i).size() ) ;
+			}
+			ostr
+				<< std::setw(3) << "" << "  "
+				<< std::setw( max_label_length + 2 ) << "parameter"
+				<< ":" ;
+			for( int j = 0; j < m_covariance.cols(); ++j ) {
+				ostr << " " << std::setw(5) << (j+1) ;
+			}
+			ostr << "\n" ;
+			for( int i = 0; i < m_covariance.rows(); ++i ) {
+				ostr << std::setw(3) << i+1
+					<< ": " << std::setw( max_label_length + 2 ) << m_ll->get_parameter_name(i) << ":" ;
+				for( int j = 0; j < m_covariance.cols(); ++j ) {
+					ostr << " " << std::setw(5) << std::setprecision(4) << m_covariance(i,j) ;
+				}
+				ostr << "\n" ;
+			}
+			return ostr.str() ;
+		}
+	}
+}

ADDED   metro/src/regression/ThreadedLogLikelihood.cpp
Index: metro/src/regression/ThreadedLogLikelihood.cpp
==================================================================
--- metro/src/regression/ThreadedLogLikelihood.cpp
+++ metro/src/regression/ThreadedLogLikelihood.cpp
@@ -0,0 +1,239 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include <memory>
+#include <exception>
+#include <boost/noncopyable.hpp>
+#include <boost/function.hpp>
+#include "Eigen/Core"
+#include "metro/regression/LogLikelihood.hpp"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/ThreadedLogLikelihood.hpp"
+#include "metro/count_range.hpp"
+#include "metro/intersect_ranges.hpp"
+//#include "boost/threadpool.hpp"
+
+//#define DEBUG 1
+
+namespace metro {
+	namespace regression {
+		ThreadedLogLikelihood::UniquePtr ThreadedLogLikelihood::create( Design& design, CreateLL create_ll, int number_of_threads ) {
+			return ThreadedLogLikelihood::UniquePtr(
+				new ThreadedLogLikelihood( design, create_ll, number_of_threads )
+			) ;
+		}
+
+		ThreadedLogLikelihood::UniquePtr ThreadedLogLikelihood::create( Design::UniquePtr design, CreateLL create_ll, int number_of_threads ) {
+			return ThreadedLogLikelihood::UniquePtr(
+				new ThreadedLogLikelihood( design, create_ll, number_of_threads )
+			) ;
+		}
+
+		ThreadedLogLikelihood::UniquePtr ThreadedLogLikelihood::create( Design& design, CreateLL create_ll, metro::concurrency::threadpool& pool ) {
+			return ThreadedLogLikelihood::UniquePtr(
+				new ThreadedLogLikelihood( design, create_ll, pool )
+			) ;
+		}
+
+		ThreadedLogLikelihood::UniquePtr ThreadedLogLikelihood::create( Design::UniquePtr design, CreateLL create_ll, metro::concurrency::threadpool& pool ) {
+			return ThreadedLogLikelihood::UniquePtr(
+				new ThreadedLogLikelihood( design, create_ll, pool )
+			) ;
+		}
+
+		ThreadedLogLikelihood::~ThreadedLogLikelihood() {
+			if( m_pool_owned ) {
+				delete m_pool ;
+			}
+			if( m_design_owned ) {
+				delete m_design ;
+			}
+		}
+
+		ThreadedLogLikelihood::ThreadedLogLikelihood(
+			Design::UniquePtr design,
+			CreateLL create_ll,
+			int number_of_threads
+		):
+			m_design( design.release() ),
+			m_design_owned( true ),
+			m_pool( new metro::concurrency::threadpool( number_of_threads )),
+			m_pool_owned( true )
+		{
+			create_lls( create_ll ) ;
+		}
+
+		ThreadedLogLikelihood::ThreadedLogLikelihood(
+			Design& design,
+			CreateLL create_ll,
+			int number_of_threads
+		):
+			m_design( &design ),
+			m_design_owned( false ),
+			
+			m_pool( new metro::concurrency::threadpool( number_of_threads )),
+			m_pool_owned( true )
+		{
+			create_lls( create_ll ) ;
+		}
+
+		ThreadedLogLikelihood::ThreadedLogLikelihood(
+			Design::UniquePtr design,
+			CreateLL create_ll,
+			metro::concurrency::threadpool& pool
+		):
+			m_design( design.release() ),
+			m_design_owned( true ),
+			m_pool( &pool ),
+			m_pool_owned( false )
+		{
+			create_lls( create_ll ) ;
+		}
+
+		ThreadedLogLikelihood::ThreadedLogLikelihood(
+			Design& design,
+			CreateLL create_ll,
+			metro::concurrency::threadpool& pool
+		):
+			m_design( &design ),
+			m_design_owned( false ),
+			m_pool( &pool ),
+			m_pool_owned( false )
+		{
+			create_lls( create_ll ) ;
+		}
+		
+		void ThreadedLogLikelihood::create_lls( CreateLL create_ll ) {
+			//int const N = metro::impl::count_range( m_design->nonmissing_samples() ) ;
+			int const N = m_design->outcome().rows() ;
+			std::size_t const threads = m_pool->number_of_threads() ;
+			
+			// aim to submit jobs for some number of the number of threads,
+			// though at least 128 to avoid tiny jobs
+			//int const size = int(std::max( 128ul, (N+4*threads-1) / (4*threads))) ;
+			//int const size = int(std::max( 128ul, (N+2*threads-1) / (2*threads))) ;
+			int const size = int(std::max( 128ul, (N+threads-1) / (threads))) ;
+
+#if DEBUG
+			std::cerr << "ThreadedLogLikelihood::create_lls(): N = " << N << " samples...\n" ;
+#endif
+
+			if( N == 0 ) {
+				// ensure we have at least one ll, even though no samples.
+				m_lls.push_back(
+					create_ll( *m_design, m_design->nonmissing_samples() )
+				) ;
+			} else {
+#if DEBUG
+				std::cerr << "ThreadedLogLikelihood::create_lls(): design nonmissing samples: " << m_design->nonmissing_samples() << ".\n" ;
+#endif
+				for( int i = 0; i < N; i += size ) {
+					//std::vector< metro::SampleRange > ranges = metro::impl::intersect_ranges( m_design->nonmissing_samples(), SampleRange( i, i + size )) ;
+					std::vector< metro::SampleRange > ranges( 1, SampleRange( i, std::min( i + size, N ) )) ;
+#if DEBUG
+					std::cerr << "ThreadedLogLikelihood::create_lls(): creating ll " << m_lls.size() << " with " << metro::impl::count_range( ranges ) << " samples:\n"
+						<< ranges << ".\n" ;
+#endif
+					m_lls.push_back( create_ll( *m_design, ranges )) ;
+				}
+			}
+			
+			// sanity check: do parameter names match?
+			std::vector< std::string > parameter_names = m_lls[0].get_parameter_names() ;
+			for( std::size_t i = 1; i < m_lls.size(); ++i ) {
+				if( m_lls[i].get_parameter_names() != parameter_names ) {
+					throw std::runtime_error( "parameter names do not match" ) ;
+				}
+			}
+		}
+
+		std::string ThreadedLogLikelihood::get_parameter_name( std::size_t i ) const {
+			return m_lls[0].get_parameter_name( i ) ;
+		}
+
+		std::vector< std::string > ThreadedLogLikelihood::get_parameter_names() const {
+			return m_lls[0].get_parameter_names() ;
+		}
+
+		// Return a lx2 matrix identifying the l parameters.
+		// For each parameter the row contains:
+		// column 0: the index of the outcome column.
+		// column 1: the index of the design matrix column.
+		int ThreadedLogLikelihood::number_of_parameters() const {
+			return m_lls[0].number_of_parameters() ;
+		}
+
+		int ThreadedLogLikelihood::number_of_outcomes() const {
+			return m_lls[0].number_of_outcomes() ;
+		}
+
+		ThreadedLogLikelihood::IntegerMatrix ThreadedLogLikelihood::identify_parameters() const {
+			return m_lls[0].identify_parameters() ;
+		}
+
+		void ThreadedLogLikelihood::evaluate_at( Point const& parameters, int const numberOfDerivatives ) {
+			{
+				auto batch = m_pool->batch_scheduler() ;
+				for( std::size_t i = 0; i < m_lls.size(); ++i ) {
+					batch->add(
+						[this,i,parameters,numberOfDerivatives]() {
+							m_lls[i].evaluate_at( parameters, numberOfDerivatives ) ;
+						}
+					) ;
+				}
+			}
+			m_pool->wait() ;
+		}
+
+		void ThreadedLogLikelihood::evaluate( int const numberOfDerivatives ) {
+			{
+				auto batch = m_pool->batch_scheduler() ;
+				for( std::size_t i = 0; i < m_lls.size(); ++i ) {
+					batch->add(
+						[this,i,numberOfDerivatives]() {
+							m_lls[i].evaluate( numberOfDerivatives ) ;
+						}
+					) ;
+				}
+			}
+			m_pool->wait() ;
+		}
+
+		ThreadedLogLikelihood::Point const& ThreadedLogLikelihood::parameters() const {
+			return m_lls[0].parameters() ;
+		}
+		
+		double ThreadedLogLikelihood::get_value_of_function() const {
+			double result = m_lls[0].get_value_of_function() ;
+			for( std::size_t i = 1; i < m_lls.size(); ++i ) {
+				result += m_lls[i].get_value_of_function() ;
+			}
+			return result ;
+		}
+
+		ThreadedLogLikelihood::Vector ThreadedLogLikelihood::get_value_of_first_derivative() const {
+			Vector result = m_lls[0].get_value_of_first_derivative() ;
+			for( std::size_t i = 1; i < m_lls.size(); ++i ) {
+				result += m_lls[i].get_value_of_first_derivative() ;
+			}
+			return result ;
+		}
+
+		ThreadedLogLikelihood::Matrix ThreadedLogLikelihood::get_value_of_second_derivative() const {
+			Matrix result = m_lls[0].get_value_of_second_derivative() ;
+			for( std::size_t i = 1; i < m_lls.size(); ++i ) {
+				result += m_lls[i].get_value_of_second_derivative() ;
+			}
+			return result ;
+		}
+		
+		std::string ThreadedLogLikelihood::get_summary() const {
+			return "ThreadedLogLikelihood:" + m_lls[0].get_summary() ;
+		}
+	}
+}
+

ADDED   metro/src/union_ranges.cpp
Index: metro/src/union_ranges.cpp
==================================================================
--- metro/src/union_ranges.cpp
+++ metro/src/union_ranges.cpp
@@ -0,0 +1,47 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <vector>
+#include <algorithm>
+#include "metro/SampleRange.hpp"
+#include "metro/union_ranges.hpp"
+
+namespace metro {
+	namespace impl {
+		std::vector< metro::SampleRange > union_ranges(
+			std::vector< metro::SampleRange > const& left,
+			std::vector< metro::SampleRange > const& right
+		) {
+			std::vector< metro::SampleRange > tmp ;
+			tmp.reserve( left.size() + right.size() ) ;
+			tmp.insert( tmp.end(), left.begin(), left.end() ) ;
+			tmp.insert( tmp.end(), right.begin(), right.end() ) ;
+			std::sort( tmp.begin(), tmp.end() ) ;
+			
+			std::vector< metro::SampleRange > result ;
+			std::vector< metro::SampleRange >::iterator i = tmp.begin() ;
+			while( i != tmp.end() ) {
+				std::vector< metro::SampleRange >::iterator rightmost_range = i ;
+				std::vector< metro::SampleRange >::iterator j = i ;
+				// walk right through the regions that overlap or abut this one.
+				for( ++j; j != tmp.end() && j->begin() <= rightmost_range->end(); rightmost_range = j++ ) {
+					// nothing to do.
+				}
+				result.push_back( metro::SampleRange( i->begin(), rightmost_range->end() ) ) ;
+				i = j ;
+			}
+			return result ;
+		}
+
+		std::vector< metro::SampleRange > union_ranges(
+			std::vector< metro::SampleRange > const& left,
+			metro::SampleRange const& right
+		) {
+			return union_ranges( left, std::vector< metro::SampleRange >( 1, right ) ) ;
+		}
+	}
+}
+

ADDED   metro/test/test_binomial_logistic_regression.cpp
Index: metro/test/test_binomial_logistic_regression.cpp
==================================================================
--- metro/test/test_binomial_logistic_regression.cpp
+++ metro/test/test_binomial_logistic_regression.cpp
@@ -0,0 +1,555 @@
+#include <vector>
+#include <iostream>
+#include "test_case.hpp"
+#include "metro/SampleRange.hpp"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/BinomialLogistic.hpp"
+
+// #define DEBUG_TESTS 1
+
+namespace {
+	void check_close_or_small(
+	    double expected, double observed, 
+	    double small, double pct_tol
+	) {
+	    if (std::fabs(expected) < small) {
+	        BOOST_CHECK_SMALL(observed, small);
+	    } else {
+	        BOOST_CHECK_CLOSE(expected, observed, pct_tol);
+	    }
+	}
+}
+
+typedef std::vector< std::string > Names ;
+
+BOOST_AUTO_TEST_SUITE( test_binomial_logistic ) ;
+
+namespace {
+	void check_likelihood_etc_for_design1(
+		int trials,
+		int successes,
+		double f0,
+		double f1,
+		double const ll,
+		Eigen::MatrixXd const dll,
+		Eigen::MatrixXd const ddll,
+		int line
+	) {
+#if DEBUG_TESTS
+		std::cerr << "Checking ll on line " << line << "...\n" ;
+		std::cerr << "k = " << successes << ", n = " << trials << "\n"
+			<< "f0 = " << f0 << ", f1 = " << f1 << ".\n" ;
+#endif
+		typedef Eigen::MatrixXd Matrix ;
+		Matrix design_matrix = Matrix::Constant( 1, 2, 1.0 ) ;
+
+		double const expected_l = std::pow( f1, successes ) * std::pow( f0, trials - successes ) ;
+		double const expected_ll = std::log( expected_l ) ;
+		BOOST_CHECK_CLOSE( expected_ll, ll, 0.00001 ) ;
+
+#if DEBUG_TESTS
+		std::cerr << "expected_l = " << expected_l << ", expected_ll = " << expected_ll << ", ll = " << ll << ".\n" ;
+#endif
+		Matrix const expected_dll
+			= design_matrix.row(0)
+			// * expected_l // this gets multiplied by and then divided again
+			* ( successes * f0  - (trials - successes) * f1)
+		;
+		for( int j = 0; j < design_matrix.cols(); ++j ) {
+			check_close_or_small( expected_dll(0,j), dll(j), 0.00001, 0.0001 ) ;
+		}
+
+		double const ddll_first_term
+			= (
+				std::pow( successes * f0  - (trials - successes) * f1, 2 )
+				- trials * f0 * f1
+			) ;
+		double const ddll_second_term
+			= std::pow(
+				( successes * f0  - (trials - successes) * f1 ),
+				2
+			) ;
+			
+		Matrix const expected_ddll
+			= (ddll_first_term - ddll_second_term)
+			* design_matrix.row(0).transpose() * design_matrix.row(0)
+		;
+
+		for( int j = 0; j < design_matrix.cols(); ++j ) {
+			for( int k = 0; k < design_matrix.cols(); ++k ) {
+				check_close_or_small( expected_ddll(j,k), ddll(j,k), 0.00001, 0.0001 ) ;
+			}
+		}
+		
+#if DEBUG_TESTS
+				std::cerr << "test_binomial_logistic_regression_one_sample:\n" ;
+				
+				std::cerr << "expected 2nd derivative = \n"
+					<< expected_ddll << "\n" ;
+				std::cerr << "actual 2nd derivative = \n"
+					<< ddll << "\n" ;
+#endif
+	}
+}
+
+using metro::SampleRange ;
+using namespace metro::regression ;
+using metro::regression::Design ;
+typedef Design::Matrix Matrix ;
+typedef Design::Vector Vector ;
+using std::exp ;
+using std::log ;
+
+// Test that when all samples are missing, the answer is zero.
+AUTO_TEST_CASE( test_binomial_logisticregression_missing_outcome ) {
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+
+	SampleRanges included_samples ;
+	Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+	predictor_levels(0,0) = 1 ;
+	predictor_levels(1,0) = 2 ;
+	int const nOutcomes = 2 ;
+	for( int nSamples = 0; nSamples < 100; ++nSamples ) {
+		SampleRanges const all_samples( SampleRanges( 1, metro::SampleRange( 0, nSamples ))) ;
+
+		for( int nMissing = 0; nMissing < nSamples; ++nMissing ) {
+			Matrix outcome = Matrix::Zero( nSamples, nOutcomes ) ;
+			outcome.col(0).setConstant(1) ;
+			outcome.col(1).setZero() ;
+			SampleRanges nonmissing_samples ;
+			nonmissing_samples.push_back( metro::SampleRange( nMissing, nSamples )) ;
+			Names outcome_names ;
+			for( int j = 0; j < nOutcomes; ++j ) {
+				outcome_names.push_back( "outcome" + std::to_string( j )) ;
+			}
+			BinomialLogistic ll(
+				Design::create(
+					outcome, nonmissing_samples, outcome_names,
+					Names( 1, "predictor" )
+				)
+			) ;
+	
+#if DEBUG_TESTS
+			std::cerr << "DESIGN MATRIX: " << ll.design().matrix().rows() << "x" << ll.design().matrix().cols() << ".\n" ;
+			std::cerr << "nSamples = " << nSamples << ", nMissing = " << nMissing << ", nOutcomes = " << nOutcomes << ".\n" ;
+			std::cerr << "ll =\n" << ll.get_summary() << "\n" ;
+#endif
+		
+			Matrix predictor_probabilities = Matrix::Zero( nSamples, 2 ) ;
+			predictor_probabilities.col(1).setConstant( 1.0 ) ;
+			ll.design().set_predictors( predictor_levels, predictor_probabilities, included_samples ) ;
+			// Now test values.
+			Vector parameters = Vector::Zero( 2 ) ;
+			parameters(0) = 1.0 ;
+			parameters(1) = -1.0 ;
+			ll.evaluate_at( parameters ) ;
+		
+			double const expected_ll = 0.0 ;
+			Vector const expected_dll = Vector::Zero(2) ;
+			Matrix const expected_ddll = Vector::Zero(2,2) ;
+			BOOST_CHECK_EQUAL( ll.get_value_of_function(), expected_ll ) ;
+			BOOST_CHECK_EQUAL( ll.get_value_of_first_derivative(), expected_dll ) ;
+			BOOST_CHECK_EQUAL( ll.get_value_of_second_derivative(), expected_ddll ) ;
+		}
+	}
+}
+
+AUTO_TEST_CASE( test_binomial_logisticregression_zero_samples ) {
+	std::vector< metro::SampleRange > included_samples ;
+	Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+	predictor_levels(0,0) = 1 ;
+	predictor_levels(1,0) = 2 ;
+	int const nOutcomes = 2 ;
+	for( int nSamples = 0; nSamples < 10; ++nSamples ) {
+		Matrix outcome = Matrix::Zero( nSamples, nOutcomes ) ;
+		outcome.col(0).setConstant(1) ;
+		outcome.col(1).setZero() ;
+
+		Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+		Names outcome_names ;
+		for( int j = 0; j < nOutcomes; ++j ) {
+			outcome_names.push_back( "outcome" + std::to_string( j )) ;
+		}
+
+		BinomialLogistic ll(
+			Design::create(
+				outcome, included_samples, outcome_names,
+				covariates, included_samples, Names(),
+				Names( 1, "predictor" )
+			)
+		) ;
+	
+		Matrix predictor_probabilities = Matrix::Zero( nSamples, 2 ) ;
+		ll.design().set_predictors( predictor_levels, predictor_probabilities, included_samples ) ;
+		// Now test values.
+		Vector parameters = Vector::Zero( 2 ) ;
+		ll.evaluate_at( parameters ) ;
+	
+		double const expected_ll = 0.0 ;
+		Vector const expected_dll = Vector::Zero(2) ;
+		Matrix const expected_ddll = Vector::Zero(2,2) ;
+		BOOST_CHECK_EQUAL( ll.get_value_of_function(), expected_ll ) ;
+		BOOST_CHECK_EQUAL( ll.get_value_of_first_derivative(), expected_dll ) ;
+		BOOST_CHECK_EQUAL( ll.get_value_of_second_derivative(), expected_ddll ) ;
+	}
+}
+
+AUTO_TEST_CASE( test_binomial_logistic_regression_one_sample ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	using std::exp ;
+	using std::log ;
+	
+	int const nSamples = 1 ;
+	std::vector< metro::SampleRange > all_samples( 1, metro::SampleRange( 0, 1 ) ) ;
+	Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+	predictor_levels(0,0) = 1 ;
+	predictor_levels(1,0) = 2 ;
+	int const nOutcomes = 2 ;
+	for( int trials = 0; trials < 100; ++trials ) {
+		for( int successes = 0; successes <= trials; ++successes ) {
+			Matrix outcome = Matrix::Zero( nSamples, nOutcomes ) ;
+			outcome(0,0) = trials - successes ;
+			outcome(0,1) = successes ;
+
+			Matrix outcome_nonmissingness = Matrix::Constant( nSamples, nOutcomes, 1.0 ) ;
+			Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+			Matrix covariate_nonmissingness = Matrix::Constant( nSamples, 0, 1.0 ) ;
+			Names outcome_names ;
+			for( int j = 0; j < nOutcomes; ++j ) {
+				outcome_names.push_back( "outcome" + std::to_string( j )) ;
+			}
+
+			BinomialLogistic ll(
+				Design::create(
+					outcome, all_samples, outcome_names,
+					covariates, all_samples, Names(),
+					Names( 1, "predictor" )
+				)
+			) ;
+			
+			// Set up a single predictor, equal to 1 with certainty.
+			Matrix predictor_probabilities = Matrix::Zero( 1, 2 ) ;
+			predictor_probabilities(0, 0) = 1.0 ;
+			ll.design().set_predictors( predictor_levels, predictor_probabilities, all_samples ) ;
+
+			int const nParameters = 2 * ( nOutcomes - 1 ) ;
+			// Now test values.
+			{
+				Vector parameters = Vector::Zero( nParameters ) ;
+				ll.evaluate_at( parameters ) ;
+				// All probs are equal to 1/(M+1).	So outcome probability equals this.
+				Matrix parameter_matrix = parameters ;
+				parameter_matrix.resize( 2, nOutcomes - 1 ) ;
+#if DEBUG_TESTS
+				std::cerr << "parameters = " << parameters.transpose() << ".\n" ;
+				std::cerr << "outcome = " << outcome.transpose() << ".\n" ;
+#endif
+	
+				// params are zero so probs are 1/2
+				double const f0 = 0.5 ;
+				double const f1 = 0.5 ;
+
+#if DEBUG_TESTS
+				std::cerr << "##############\n" ;
+				std::cerr << "(successes, trials) = " << successes << ", " << trials << "\n" ;
+				std::cerr << "parameters = " << parameters.transpose() << ".\n" ;
+				std::cerr << "outcome = " << outcome.transpose() << ".\n" ;
+				std::cerr << "design = " << ll.design().matrix() << ".\n" ;
+#endif
+				check_likelihood_etc_for_design1(
+					trials, successes,
+					f0, f1,
+					ll.get_value_of_function(),
+					ll.get_value_of_first_derivative(),
+					ll.get_value_of_second_derivative(),
+					__LINE__
+				) ;
+			}
+
+			for( int nonzero_i = 0; nonzero_i < nParameters; ++nonzero_i )
+			{
+
+				Vector parameters = Vector::Zero( 2 * ( nOutcomes - 1 ) ) ;
+				parameters( nonzero_i ) = log(2.0) ;
+				ll.evaluate_at( parameters ) ;
+
+				// f_i will equal 1/(M+2), or 2/(M+2) for i=floor(nonzero_i/2).
+				Matrix parameter_matrix = parameters ;
+				parameter_matrix.resize( 2, nParameters ) ;
+
+				// params are zero so probs are 1/2
+				Matrix design_matrix = Matrix::Constant( 1, 2, 1.0 ) ;
+				double const f0 = 1.0 / (1.0 + std::exp( design_matrix.row(0) * parameters )) ;
+				double const f1 = 1 - f0 ;
+
+#if DEBUG_TESTS
+				std::cerr << "##############\n" ;
+				std::cerr << "(successes, trials) = " << successes << ", " << trials << "\n" ;
+				std::cerr << "nonzero = " << nonzero_i << ".\n" ;
+				std::cerr << "parameters = " << parameters.transpose() << ".\n" ;
+				std::cerr << "outcome = " << outcome.transpose() << ".\n" ;
+				std::cerr << "design = " << ll.design().matrix() << ".\n" ;
+#endif
+				check_likelihood_etc_for_design1(
+					trials, successes,
+					f0, f1,
+					ll.get_value_of_function(),
+					ll.get_value_of_first_derivative(),
+					ll.get_value_of_second_derivative(),
+					__LINE__
+				) ;
+			}
+		}
+	}
+}
+
+
+AUTO_TEST_CASE( test_binomial_logisticregression_two_samples ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	using std::exp ;
+	using std::log ;
+	
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+	SampleRanges const all_samples( 1, metro::SampleRange( 0, 2 )) ;
+	
+	{
+		int const nSamples = 2 ;
+		Matrix outcome = Matrix::Zero(nSamples, 2) ;
+		outcome <<
+			1, 0,
+			0, 1 ;
+		Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+
+		BinomialLogistic ll(
+			Design::create(
+				outcome, all_samples, Names({"outcome=0", "outcome=1"}),
+				covariates, all_samples, Names(),
+				Names({"predictor"})
+			)
+		) ;
+		
+		Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+		predictor_levels(0,0) = 0 ;
+		predictor_levels(1,0) = 1 ;
+
+		// Set half the sample to certainly 0, half to certainly 1.
+		Matrix predictor_probabilities = Matrix::Zero( nSamples, 2 ) ;
+		predictor_probabilities( 0, 0 ) = 1.0 ;
+		predictor_probabilities( 1, 1 ) = 1.0 ;
+
+		ll.design().set_predictors( predictor_levels, predictor_probabilities, all_samples ) ;
+		
+		{
+			Vector parameters = Vector::Zero( 2 ) ;
+			ll.evaluate_at( parameters ) ;
+			// all probabilities are one-half.
+			Vector f1( 2 ) ;
+			f1 << 0.5, 0.5 ;
+			Vector F = f1 ; // F=f because probs are 1/2
+
+			double expected_ll = nSamples * std::log( 0.5 ) ;
+			BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+			Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+			design_matrix.col(0).setConstant( 1.0 ) ;
+			design_matrix( 1, 1 ) = 1.0 ;
+			
+			// Compute first derivative
+			Vector B = Vector::Constant( 2, 1.0 ) - F ;
+			B(0) = -B(0) ;
+			Vector const expected_first_derivative = ( B.transpose() * design_matrix ) ;
+			Vector const first_derivative = ll.get_value_of_first_derivative() ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+			
+			// Compute second derivative
+			Vector C = ( Vector::Constant( 2, 1.0 ) - 2.0 * F ).array() * B.array() ;
+			Matrix DD = Matrix::Zero( 2, 2 ) ;
+			for( int i = 0; i < design_matrix.rows(); ++i ) {
+				DD += ( C(i) - B(i) * B(i) ) * design_matrix.row(i).transpose() * design_matrix.row(i) ;
+			}
+			
+			Matrix const& second_derivative = ll.get_value_of_second_derivative() ;
+			BOOST_CHECK_CLOSE( DD(0,0), second_derivative(0,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(0,1), second_derivative(0,1), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,0), second_derivative(1,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,1), second_derivative(1,1), 0.0000001 ) ;
+		}
+
+		{
+			// Set a nonzero predictor effect parameter.
+			Vector parameters = Vector::Zero( 2 ) ;
+			parameters << 0.0, 1.0 ;
+			ll.evaluate_at( parameters ) ;
+			// Now we have exp( x^t theta ) = 1, e for the two samples.  Thus f1 is 1/2, e/1+e
+			Vector f1( 2 ) ;
+			f1 << 0.5, ( std::exp( 1 ) / ( 1.0 + std::exp(1.0) ) ) ;
+			Vector F = f1 ; // f_0 = f_1 for first sample because the first prob is 0.5.
+			double const expected_ll = F.array().log().sum() ;
+			BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+			// f1 = 1/2, e/1+e
+			Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+			design_matrix.col(0).setConstant( 1.0 ) ;
+			design_matrix( 1, 1 ) = 1.0 ;
+			
+			Vector B = F.array() * ( Vector::Constant( 2, 1.0 ) - F ).array() ;
+			for( int i = 0; i < B.size(); ++i ) {
+				B(i) = B(i) / F(i) ;
+			}
+			B(0) = -B(0) ;
+			Vector const expected_first_derivative = ( B.transpose() * design_matrix ) ;
+			Vector const first_derivative = ll.get_value_of_first_derivative() ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+
+			// Compute second derivative
+			Vector C = ( Vector::Constant( 2, 1.0 ) - 2.0 * F ).array() * B.array() ;
+			Matrix DD = Matrix::Zero( 2, 2 ) ;
+			for( int i = 0; i < design_matrix.rows(); ++i ) {
+				DD += ( C(i) - B(i) * B(i) ) * design_matrix.row(i).transpose() * design_matrix.row(i) ;
+			}
+			Matrix const& second_derivative = ll.get_value_of_second_derivative() ;
+			BOOST_CHECK_CLOSE( DD(0,0), second_derivative(0,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(0,1), second_derivative(0,1), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,0), second_derivative(1,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,1), second_derivative(1,1), 0.0000001 ) ;
+		}
+	}
+}
+
+
+AUTO_TEST_CASE( test_binomial_logisticregression_certain_predictors ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+	using std::exp ;
+	using std::log ;
+	
+	std::vector< double > parameter_values ;
+	parameter_values.push_back( -10 ) ;
+	parameter_values.push_back( -3.141592654 ) ;
+	parameter_values.push_back( -1 ) ;
+	parameter_values.push_back( -0.25 ) ;
+	parameter_values.push_back( 0 ) ;
+	parameter_values.push_back( 0.25 ) ;
+	parameter_values.push_back( 0.5 ) ;
+	parameter_values.push_back( 1 ) ;
+	parameter_values.push_back( 3.141592654 ) ;
+	parameter_values.push_back( 10 ) ;
+	
+	for( int nCases = 0; nCases < 50; ++nCases ) {
+		for( int nControls = 0; nControls < 50; ++nControls ) {
+#if DEBUG_TESTS
+			std::cerr << "nCases = " << nCases << ", nControls = " << nControls << ".\n" ;
+#endif
+			int nSamples = nCases + nControls ;
+
+			SampleRanges const all_samples( 1, metro::SampleRange( 0, nSamples )) ;
+
+			// contruct outcome
+			Matrix outcome = Matrix::Zero(nSamples,2) ;
+			{
+				int i = 0 ;
+				for( ; i < nCases; ++i ) {
+					outcome(i,1) = 1 ;
+				}
+				for( ; i < nSamples; ++i ) {
+					outcome(i,0) = 1 ;
+				}
+			}
+
+			Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+
+			BinomialLogistic ll(
+				Design::create(
+					outcome, all_samples, Names({"outcome=0", "outcome=1"}),
+					covariates, all_samples, std::vector< std::string >(),
+					std::vector< std::string >( 1, "predictor" )
+				)
+			) ;
+		
+			// construct a 0/1 predictor.
+			Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+			predictor_levels(0,0) = 0 ;
+			predictor_levels(1,0) = 1 ;
+
+			// Set half the sample to certainly 0, half to certainly 1.
+			Matrix predictor_probabilities = Matrix::Zero( nSamples, 2 ) ;
+			int const nOnes = nSamples / 2 ;
+			for( int i = 0; i < nSamples; ++i ) {
+				if( i < nOnes ) {
+					predictor_probabilities( i, 1 ) = 1 ;
+				} else {
+					predictor_probabilities( i, 0 ) = 1 ;
+				}
+			}
+			
+			ll.design().set_predictors( predictor_levels, predictor_probabilities, all_samples ) ;
+		
+			// Ok we have our likelihood.  Now compute with it.
+			{
+				ll.evaluate_at( Vector::Zero( 2 ) ) ;
+				// all probabilities are one-half.
+				double expected_ll = nSamples * std::log( 0.5 ) ;
+				BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+				Vector one_minus_f1 = ( outcome.col(1).array() - 0.5 ) ;
+				Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+				design_matrix.col(0).setConstant( 1.0 ) ;
+				design_matrix.col(1).segment( 0, nOnes ).setConstant( 1.0 ) ;
+				
+				Vector const expected_first_derivative = ( one_minus_f1.transpose() * design_matrix ) ;
+				Vector const first_derivative = ll.get_value_of_first_derivative() ;
+				BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+				BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+			}
+
+			Vector parameters = Vector::Zero( 2 ) ;
+			for( std::size_t pi0 = 0; pi0 < parameter_values.size(); ++pi0 ) {
+				for( std::size_t pi1 = 0; pi1 < parameter_values.size(); ++pi1 ) {
+					parameters(0) = parameter_values[ pi0 ] ;
+					parameters(1) = parameter_values[ pi1 ] ;
+
+					ll.evaluate_at( parameters ) ;
+
+					Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+					design_matrix.col(0).setConstant( 1.0 ) ;
+					design_matrix.col(1).segment( 0, nOnes ).setConstant( 1.0 ) ;
+
+					Vector F1 = ( design_matrix * parameters ).array().exp() ;
+					Vector ones = Vector::Constant( nSamples, 1.0 ) ;
+					Vector const F0 = ones.array() / ( 1.0 + F1.array() ) ;
+					F1 = F1.array() / ( 1.0 + F1.array() ) ;
+
+					Vector Fpsi = F1 ;
+					Fpsi.segment( nCases, nControls ) = F0.segment( nCases, nControls ) ;
+
+					// all probabilities are one-half.
+					double expected_ll = Fpsi.array().log().sum() ;
+					check_close_or_small( expected_ll, ll.get_value_of_function(), 0.00000000001, 0.0001 ) ;
+
+					Vector outcome_minus_f1 = ( outcome.col(1) - F1 ) ;
+
+					Vector const expected_first_derivative = ( outcome_minus_f1.transpose() * design_matrix ) ;
+					Vector first_derivative = ll.get_value_of_first_derivative() ;
+					check_close_or_small( expected_first_derivative(0), first_derivative(0), 0.00000000001, 0.0001 ) ;
+					check_close_or_small( expected_first_derivative(1), first_derivative(1), 0.00000000001, 0.0001 ) ;
+				}
+			}
+		}
+	}
+}
+
+BOOST_AUTO_TEST_SUITE_END() ;

Index: metro/test/test_case.cpp
==================================================================
--- metro/test/test_case.cpp
+++ metro/test/test_case.cpp
@@ -2,7 +2,7 @@
 //          Copyright Gavin Band 2008 - 2012.
 // Distributed under the Boost Software License, Version 1.0.
 //    (See accompanying file LICENSE_1_0.txt or copy at
 //          http://www.boost.org/LICENSE_1_0.txt)
 
-#define BOOST_TEST_MODULE metro
+#define BOOST_TEST_MODULE genfile
 #include "test_case.hpp"

ADDED   metro/test/test_log_sum_exp.cpp
Index: metro/test/test_log_sum_exp.cpp
==================================================================
--- metro/test/test_log_sum_exp.cpp
+++ metro/test/test_log_sum_exp.cpp
@@ -0,0 +1,90 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <vector>
+#include "test_case.hpp"
+#include "metro/log_sum_exp.hpp"
+
+namespace {
+	template< typename F >
+	bool floats_are_equal_to_within_epsilon( F a, F b, F epsilon ) {
+		if( std::abs( a ) == std::numeric_limits< F >::infinity() || std::abs( b ) == std::numeric_limits< F >::infinity() )  {
+			return a == b ;
+		}
+		else {
+	    	return (std::abs( a - b ) < epsilon ) ;
+		}
+	}
+}
+
+AUTO_TEST_CASE( test_log_sum_exp ) {
+	std::cerr << "test_log_sum_exp...\n" ;
+	
+	std::vector< std::vector< double > > test_data ;
+	std::vector< double > expected_results ;
+	
+	double const infinity = std::numeric_limits< double >::infinity() ;
+	
+	// Empty sum -- result is log( 0 )
+	test_data.push_back( std::vector< double >() ) ;
+	expected_results.push_back( -infinity ) ;
+
+	// Sum of one term -- result is that term.
+	test_data.push_back( std::vector< double >( 1, 0.0 ) ) ;
+	expected_results.push_back( 0.0 ) ;
+
+	test_data.push_back( std::vector< double >( 1, -infinity ) ) ;
+	expected_results.push_back( -infinity ) ;
+
+	// Sum of two terms
+	test_data.push_back( std::vector< double >( 2, 0.0 )) ;
+	expected_results.push_back( std::log( 2.0 )) ;
+
+	// Sum of -infinities
+	test_data.push_back( std::vector< double >( 2, -infinity )) ;
+	expected_results.push_back( -infinity ) ;
+
+	test_data.push_back( std::vector< double >( 3, -infinity )) ;
+	expected_results.push_back( -infinity ) ;
+
+	// adding one or more -infinities to this should make no difference
+	test_data.push_back( std::vector< double >( 3, 0.0 )) ;
+	test_data.back()[0] =-infinity ;
+	expected_results.push_back( std::log( 2.0 )) ;
+
+	test_data.push_back( std::vector< double >( 3, 0.0 )) ;
+	test_data.back()[1] =-infinity ;
+	expected_results.push_back( std::log( 2.0 )) ;
+
+	test_data.push_back( std::vector< double >( 3, 0.0 )) ;
+	test_data.back()[2] =-infinity ;
+	expected_results.push_back( std::log( 2.0 )) ;
+
+	test_data.push_back( std::vector< double >( 4, 0.0 )) ;
+	test_data.back()[0] =-infinity ;
+	test_data.back()[1] =-infinity ;
+	expected_results.push_back( std::log( 2.0 )) ;
+
+	// With different values
+	test_data.push_back( std::vector< double >( 2, 1.0 )) ;
+	expected_results.push_back( std::log( std::exp( 1.0 ) + std::exp( 1.0 ))) ;
+
+	assert( test_data.size() == expected_results.size() ) ;
+
+	for( std::size_t i = 0; i < test_data.size(); ++i ) {
+		/*
+		std::cerr << "test data: " ;
+		for( std::size_t j = 0; j < test_data[i].size(); ++j ) {
+			std::cerr << test_data[i][j] << " " ;
+		}
+		std::cerr << "\n" ;
+		*/
+		double result = metro::log_sum_exp( test_data[i] ) ;
+		TEST_ASSERT( floats_are_equal_to_within_epsilon( result, expected_results[i], 1e-12 )) ;
+	}
+	std::cerr << "success.\n" ;
+}

ADDED   metro/test/test_logistic_regression.cpp
Index: metro/test/test_logistic_regression.cpp
==================================================================
--- metro/test/test_logistic_regression.cpp
+++ metro/test/test_logistic_regression.cpp
@@ -0,0 +1,480 @@
+#include <vector>
+#include <iostream>
+#include "test_case.hpp"
+#include "metro/SampleRange.hpp"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/Logistic.hpp"
+
+// #define DEBUG_TESTS 1
+
+namespace {
+	void check_close_or_small(
+	    double expected, double observed, 
+	    double small, double pct_tol
+	) {
+	    if (std::fabs(expected) < small) {
+	        BOOST_CHECK_SMALL(observed, small);
+	    } else {
+	        BOOST_CHECK_CLOSE(expected, observed, pct_tol);
+	    }
+	}
+}
+
+typedef std::vector< std::string > Names ;
+
+BOOST_AUTO_TEST_SUITE( test_logistic ) ;
+
+AUTO_TEST_CASE( test_logistic_regression_one_sample ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	using std::exp ;
+	using std::log ;
+	
+	int const nSamples = 1 ;
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+	SampleRanges all_samples( 1, metro::SampleRange( 0, 1 ) ) ;
+	Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+	predictor_levels(0,0) = 1 ;
+	predictor_levels(1,0) = 2 ;
+	int const nOutcomes = 2 ;
+	{
+		Matrix outcome = Matrix::Zero(nSamples, nOutcomes) ;
+		Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+		Names outcome_names ;
+		for( int j = 0; j < nOutcomes; ++j ) {
+			outcome_names.push_back( "outcome" + std::to_string( j )) ;
+		}
+//		for( int outcome_i = 0; outcome_i < nOutcomes; ++outcome_i ) {
+		for( int outcome_i = 1; outcome_i < nOutcomes; ++outcome_i ) {
+			// Set the chosen outcome for the single sample
+			outcome.setZero() ;
+			outcome(0,outcome_i) = 1 ;
+			
+			Logistic ll(
+				Design::create(
+					outcome, all_samples, outcome_names,
+					covariates, all_samples, Names(),
+					Names( 1, "predictor" )
+				)
+			) ;
+			
+			// Set up a single predictor, equal to 1 with certainty.
+			Matrix predictor_probabilities = Matrix::Zero( 1, 2 ) ;
+			predictor_probabilities(0, 0) = 1.0 ;
+			ll.design().set_predictors( predictor_levels, predictor_probabilities, all_samples ) ;
+
+			int const nParameters = 2 * ( nOutcomes - 1 ) ;
+			int const M = nOutcomes - 1 ;
+			// Now test values.
+			{
+				Vector parameters = Vector::Zero( nParameters ) ;
+				ll.evaluate_at( parameters ) ;
+				// All probs are equal to 1/(M+1).	So outcome probability equals this.
+				Matrix parameter_matrix = parameters ;
+				parameter_matrix.resize( 2, nOutcomes - 1 ) ;
+#if DEBUG_TESTS
+				std::cerr << "parameters = " << parameters.transpose() << ".\n" ;
+				std::cerr << "outcome = " << outcome.transpose() << ".\n" ;
+#endif
+			
+				double const expected_ll = std::log( 1.0 / double( nOutcomes ) ) ;
+				BOOST_CHECK_CLOSE( expected_ll, ll.get_value_of_function(), 0.00001 ) ;
+				
+				Matrix F = Matrix::Constant( 1, nOutcomes, 1.0 / double( nOutcomes ) ) ;
+				
+				Matrix B = -F.block( 0, 1, 1, M ) ;
+				if( outcome_i > 0 ) {
+					B( 0, outcome_i - 1 ) += 1.0 ;
+				}
+				
+				Matrix design_matrix = Matrix::Constant( 1, 2, 1.0 ) ;
+				Matrix expected_first_derivative = Matrix::Zero( 1, M * 2 ) ;
+				for( int j = 0; j < M ; ++j ) {
+					expected_first_derivative.block( 0, j*2, 1, 2 ) = design_matrix.row(0) * B( 0, j ) ;
+				}
+
+				Vector const first_derivative = ll.get_value_of_first_derivative() ;
+				for( int j = 0; j < M*2; ++j ) {
+					BOOST_CHECK_CLOSE( expected_first_derivative(0,j), first_derivative(j), 0.00001 ) ;
+				}
+
+				Matrix C = Matrix::Zero( M, M ) ;
+				for( int j = 0; j < M ; ++j ) {
+					double Z_ij = ( j == outcome_i - 1 ) ? ( 1 - F(j+1) ) : ( - F(j+1) ) ;
+					for( int k = 0; k < M; ++k ) {
+						double Z_ik = ( k == outcome_i - 1 ) ? ( 1 - F(k+1) ) : ( - F(k+1) ) ;
+						double Z_jk = ( j == k ) ? ( 1 - F(k+1) ) : ( - F(k+1) ) ;
+//						std::cerr << "j:" << j << ", k:" << k << ", Zij:" << Z_ij << ", Z_ik:" << Z_ik << ", Z_jk:" << Z_jk << ".\n" ;
+						C( j, k ) = ( Z_ij * Z_ik ) - ( F( j+1 ) * Z_jk ) ;
+					}
+				}
+
+				Matrix expected_2nd_derivative = Matrix::Zero( M*2, M*2 ) ;
+				for( int j = 0; j < M ; ++j ) {
+					for( int k = 0; k < M ; ++k ) {
+						expected_2nd_derivative.block( j*2, k*2, 2, 2 )
+							= ( C( j, k ) - B( 0, j ) * B( 0, k ) ) * design_matrix.row(0).transpose() * design_matrix.row(0) ;
+					}
+				}
+
+				Matrix const second_derivative = ll.get_value_of_second_derivative() ;
+				for( int j = 0; j < M*2; ++j ) {
+					for( int k = 0; k < M*2; ++k ) {
+						BOOST_CHECK_CLOSE( expected_2nd_derivative(j,k), second_derivative(j,k), 0.00001 ) ;
+					}
+				}
+				
+#if DEBUG_TESTS
+				std::cerr << "test_multinomialregression_one_sample:\n" ;
+				std::cerr << "nOutcomes = " << nOutcomes << "\n" ;
+				std::cerr << "F = " << F << "\n" ;
+				std::cerr << "B = " << B << "\n" ;
+				std::cerr << "C = \n" << C << "\n" ;
+				std::cerr << "expected 2nd derivative = \n"
+					<< expected_2nd_derivative << "\n" ;
+				std::cerr << "actual 2nd derivative = \n"
+					<< second_derivative << "\n" ;
+#endif
+			}
+
+			for( int nonzero_i = 0; nonzero_i < nParameters; ++nonzero_i )
+			{
+
+				Vector parameters = Vector::Zero( 2 * ( nOutcomes - 1 ) ) ;
+				parameters( nonzero_i ) = log(2.0) ;
+#if DEBUG_TESTS
+				std::cerr << "##############\n" ;
+				std::cerr << "nOutcomes = " << nOutcomes << ".\n" ;
+				std::cerr << "parameters = " << parameters.transpose() << ".\n" ;
+				std::cerr << "outcome = " << outcome.transpose() << ".\n" ;
+				std::cerr << "nonzero = " << nonzero_i << ".\n" ;
+#endif
+				ll.evaluate_at( parameters ) ;
+
+				// f_i will equal 1/(M+2), or 2/(M+2) for i=floor(nonzero_i/2).
+				Matrix parameter_matrix = parameters ;
+				parameter_matrix.resize( 2, nParameters ) ;
+			
+				// So if the outcome equals floor(nonzero_i/2) we have
+				int const special_outcome = nonzero_i / 2 ;
+				double expected_ll ;
+				if( outcome_i == 0 ) {
+					expected_ll = std::log( 1.0 / ( M + 2.0 ) ) ;
+				} else if( ( outcome_i - 1 ) == special_outcome ) {
+					expected_ll = std::log( 2.0 / ( M + 2.0 ) ) ;
+				} else {
+					expected_ll = std::log( 1.0 / ( M + 2.0 ) ) ;
+				}
+				BOOST_CHECK_CLOSE( expected_ll, ll.get_value_of_function(), 0.00001 ) ;
+
+				Matrix F = Matrix::Constant( 1, nOutcomes, 1.0 / ( M + 2.0 ) ) ;
+				F( special_outcome + 1 ) = 2.0 / ( M + 2.0 ) ;
+				
+				Matrix B = -F.block( 0, 1, 1, M ) ;
+				if( outcome_i > 0 ) {
+					B( 0, outcome_i - 1 ) += 1.0 ;
+				}
+				Matrix design_matrix = Matrix::Constant( 1, 2, 1.0 ) ;
+				Matrix expected_first_derivative = Matrix::Zero( 1, M * 2 ) ;
+				for( int j = 0; j < M ; ++j ) {
+					expected_first_derivative.block( 0, j*2, 1, 2 ) = design_matrix.row(0) * B( 0, j ) ;
+				}
+
+				Vector const first_derivative = ll.get_value_of_first_derivative() ;
+				for( int j = 0; j < M*2; ++j ) {
+					BOOST_CHECK_CLOSE( expected_first_derivative(0,j), first_derivative(j), 0.00001 ) ;
+				}
+
+				Matrix C = Matrix::Zero( M, M ) ;
+				for( int j = 0; j < M ; ++j ) {
+					double Z_ij = ( j == outcome_i - 1 ) ? ( 1 - F(j+1) ) : ( - F(j+1) ) ;
+					for( int k = 0; k < M; ++k ) {
+						double Z_ik = ( k == outcome_i - 1 ) ? ( 1 - F(k+1) ) : ( - F(k+1) ) ;
+						double Z_jk = ( j == k ) ? ( 1 - F(k+1) ) : ( - F(k+1) ) ;
+						C( j, k ) = ( Z_ij * Z_ik ) - ( F( j+1 ) * Z_jk ) ;
+						//std::cerr << "j:" << j << ", k:" << k << ", Zij:" << Z_ij << ", Z_ik:" << Z_ik << ", Z_jk:" << Z_jk << ".\n" ;
+					}
+				}
+				Matrix expected_2nd_derivative = Matrix::Zero( M*2, M*2 ) ;
+				for( int j = 0; j < M ; ++j ) {
+					for( int k = 0; k < M ; ++k ) {
+						expected_2nd_derivative.block( j*2, k*2, 2, 2 )
+							= ( C( j, k ) - B( 0, j ) * B( 0, k ) ) * design_matrix.row(0).transpose() * design_matrix.row(0) ;
+					}
+				}
+
+				Matrix const second_derivative = ll.get_value_of_second_derivative() ;
+				
+#if DEBUG_TESTS
+				std::cerr << "test_multinomialregression_one_sample:\n" ;
+				std::cerr << "nOutcomes = " << nOutcomes << "\n" ;
+				std::cerr << "F = " << F << "\n" ;
+				std::cerr << "B = " << B << "\n" ;
+				std::cerr << "C = \n" << C << "\n" ;
+				std::cerr << "expected 2nd derivative = \n"
+					<< expected_2nd_derivative << "\n" ;
+				std::cerr << "actual 2nd derivative = \n"
+					<< second_derivative << "\n" ;
+#endif
+				for( int j = 0; j < M*2; ++j ) {
+					for( int k = 0; k < M*2; ++k ) {
+						BOOST_CHECK_CLOSE( expected_2nd_derivative(j,k), second_derivative(j,k), 0.00001 ) ;
+					}
+				}
+			}
+		}
+	}
+}
+
+
+
+AUTO_TEST_CASE( test_logisticregression_two_samples ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+	using std::exp ;
+	using std::log ;
+	
+	SampleRanges all_samples( 1, metro::SampleRange( 0, 2 )) ;
+	
+	{
+		int const nSamples = 2 ;
+		Matrix outcome = Matrix::Zero(nSamples, 2) ;
+		outcome <<
+			1, 0,
+			0, 1 ;
+		Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+
+		Logistic ll(
+			Design::create(
+				outcome, all_samples, Names({"outcome=0", "outcome=1"}),
+				covariates, all_samples, Names(),
+				Names({"predictor"})
+			)
+		) ;
+		
+		Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+		predictor_levels(0,0) = 0 ;
+		predictor_levels(1,0) = 1 ;
+
+		// Set half the sample to certainly 0, half to certainly 1.
+		Matrix predictor_probabilities = Matrix::Zero( nSamples, 2 ) ;
+		predictor_probabilities( 0, 0 ) = 1.0 ;
+		predictor_probabilities( 1, 1 ) = 1.0 ;
+
+		ll.design().set_predictors( predictor_levels, predictor_probabilities, all_samples ) ;
+		
+		{
+			Vector parameters = Vector::Zero( 2 ) ;
+			ll.evaluate_at( parameters ) ;
+			// all probabilities are one-half.
+			Vector f1( 2 ) ;
+			f1 << 0.5, 0.5 ;
+			Vector F = f1 ; // F=f because probs are 1/2
+
+			double expected_ll = nSamples * std::log( 0.5 ) ;
+			BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+			Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+			design_matrix.col(0).setConstant( 1.0 ) ;
+			design_matrix( 1, 1 ) = 1.0 ;
+			
+			// Compute first derivative
+			Vector B = Vector::Constant( 2, 1.0 ) - F ;
+			B(0) = -B(0) ;
+			Vector const expected_first_derivative = ( B.transpose() * design_matrix ) ;
+			Vector const first_derivative = ll.get_value_of_first_derivative() ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+			
+			// Compute second derivative
+			Vector C = ( Vector::Constant( 2, 1.0 ) - 2.0 * F ).array() * B.array() ;
+			Matrix DD = Matrix::Zero( 2, 2 ) ;
+			for( int i = 0; i < design_matrix.rows(); ++i ) {
+				DD += ( C(i) - B(i) * B(i) ) * design_matrix.row(i).transpose() * design_matrix.row(i) ;
+			}
+			
+			Matrix const& second_derivative = ll.get_value_of_second_derivative() ;
+			BOOST_CHECK_CLOSE( DD(0,0), second_derivative(0,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(0,1), second_derivative(0,1), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,0), second_derivative(1,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,1), second_derivative(1,1), 0.0000001 ) ;
+		}
+
+		{
+			// Set a nonzero predictor effect parameter.
+			Vector parameters = Vector::Zero( 2 ) ;
+			parameters << 0.0, 1.0 ;
+			ll.evaluate_at( parameters ) ;
+			// Now we have exp( x^t theta ) = 1, e for the two samples.  Thus f1 is 1/2, e/1+e
+			Vector f1( 2 ) ;
+			f1 << 0.5, ( std::exp( 1 ) / ( 1.0 + std::exp(1.0) ) ) ;
+			Vector F = f1 ; // f_0 = f_1 for first sample because the first prob is 0.5.
+			double const expected_ll = F.array().log().sum() ;
+			BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+			// f1 = 1/2, e/1+e
+			Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+			design_matrix.col(0).setConstant( 1.0 ) ;
+			design_matrix( 1, 1 ) = 1.0 ;
+			
+			Vector B = F.array() * ( Vector::Constant( 2, 1.0 ) - F ).array() ;
+			for( int i = 0; i < B.size(); ++i ) {
+				B(i) = B(i) / F(i) ;
+			}
+			B(0) = -B(0) ;
+			Vector const expected_first_derivative = ( B.transpose() * design_matrix ) ;
+			Vector const first_derivative = ll.get_value_of_first_derivative() ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+
+			// Compute second derivative
+			Vector C = ( Vector::Constant( 2, 1.0 ) - 2.0 * F ).array() * B.array() ;
+			Matrix DD = Matrix::Zero( 2, 2 ) ;
+			for( int i = 0; i < design_matrix.rows(); ++i ) {
+				DD += ( C(i) - B(i) * B(i) ) * design_matrix.row(i).transpose() * design_matrix.row(i) ;
+			}
+			Matrix const& second_derivative = ll.get_value_of_second_derivative() ;
+			BOOST_CHECK_CLOSE( DD(0,0), second_derivative(0,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(0,1), second_derivative(0,1), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,0), second_derivative(1,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,1), second_derivative(1,1), 0.0000001 ) ;
+		}
+	}
+}
+
+
+AUTO_TEST_CASE( test_logisticregression_certain_predictors ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+
+	using std::exp ;
+	using std::log ;
+	
+	std::vector< double > parameter_values ;
+	parameter_values.push_back( -10 ) ;
+	parameter_values.push_back( -3.141592654 ) ;
+	parameter_values.push_back( -1 ) ;
+	parameter_values.push_back( -0.25 ) ;
+	parameter_values.push_back( 0 ) ;
+	parameter_values.push_back( 0.25 ) ;
+	parameter_values.push_back( 0.5 ) ;
+	parameter_values.push_back( 1 ) ;
+	parameter_values.push_back( 3.141592654 ) ;
+	parameter_values.push_back( 10 ) ;
+	
+	for( int nCases = 0; nCases < 50; ++nCases ) {
+		for( int nControls = 0; nControls < 50; ++nControls ) {
+#if DEBUG_TESTS
+			std::cerr << "nCases = " << nCases << ", nControls = " << nControls << ".\n" ;
+#endif
+			int nSamples = nCases + nControls ;
+
+			SampleRanges const all_samples( 1, metro::SampleRange( 0, nSamples )) ;
+			// contruct outcome
+			Matrix outcome = Matrix::Zero(nSamples,2) ;
+			{
+				int i = 0 ;
+				for( ; i < nCases; ++i ) {
+					outcome(i,1) = 1 ;
+				}
+				for( ; i < nSamples; ++i ) {
+					outcome(i,0) = 1 ;
+				}
+			}
+			Matrix outcome_nonmissingness = Matrix::Constant( nSamples, 2, 1.0 ) ;
+
+			Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+			Matrix covariate_nonmissingness = Matrix::Constant( nSamples, 0, 1.0 ) ;
+
+			Logistic ll(
+				Design::create(
+					outcome, all_samples, Names({"outcome=0", "outcome=1"}),
+					covariates, all_samples, std::vector< std::string >(),
+					std::vector< std::string >( 1, "predictor" )
+				)
+			) ;
+		
+			// construct a 0/1 predictor.
+			Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+			predictor_levels(0,0) = 0 ;
+			predictor_levels(1,0) = 1 ;
+
+			// Set half the sample to certainly 0, half to certainly 1.
+			Matrix predictor_probabilities = Matrix::Zero( nSamples, 2 ) ;
+			int const nOnes = nSamples / 2 ;
+			for( int i = 0; i < nSamples; ++i ) {
+				if( i < nOnes ) {
+					predictor_probabilities( i, 1 ) = 1 ;
+				} else {
+					predictor_probabilities( i, 0 ) = 1 ;
+				}
+			}
+			
+			ll.design().set_predictors( predictor_levels, predictor_probabilities, all_samples ) ;
+		
+			// Ok we have our likelihood.  Now compute with it.
+			{
+				ll.evaluate_at( Vector::Zero( 2 ) ) ;
+				// all probabilities are one-half.
+				double expected_ll = nSamples * std::log( 0.5 ) ;
+				BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+				Vector one_minus_f1 = ( outcome.col(1).array() - 0.5 ) ;
+				Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+				design_matrix.col(0).setConstant( 1.0 ) ;
+				design_matrix.col(1).segment( 0, nOnes ).setConstant( 1.0 ) ;
+				
+				Vector const expected_first_derivative = ( one_minus_f1.transpose() * design_matrix ) ;
+				Vector const first_derivative = ll.get_value_of_first_derivative() ;
+				BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+				BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+			}
+
+			Vector parameters = Vector::Zero( 2 ) ;
+			for( std::size_t pi0 = 0; pi0 < parameter_values.size(); ++pi0 ) {
+				for( std::size_t pi1 = 0; pi1 < parameter_values.size(); ++pi1 ) {
+					parameters(0) = parameter_values[ pi0 ] ;
+					parameters(1) = parameter_values[ pi1 ] ;
+
+					ll.evaluate_at( parameters ) ;
+
+					Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+					design_matrix.col(0).setConstant( 1.0 ) ;
+					design_matrix.col(1).segment( 0, nOnes ).setConstant( 1.0 ) ;
+
+					Vector F1 = ( design_matrix * parameters ).array().exp() ;
+					Vector ones = Vector::Constant( nSamples, 1.0 ) ;
+					Vector const F0 = ones.array() / ( 1.0 + F1.array() ) ;
+					F1 = F1.array() / ( 1.0 + F1.array() ) ;
+
+					Vector Fpsi = F1 ;
+					Fpsi.segment( nCases, nControls ) = F0.segment( nCases, nControls ) ;
+
+					// all probabilities are one-half.
+					double expected_ll = Fpsi.array().log().sum() ;
+					check_close_or_small( expected_ll, ll.get_value_of_function(), 0.00000000001, 0.0001 ) ;
+
+					Vector outcome_minus_f1 = ( outcome.col(1) - F1 ) ;
+
+					Vector const expected_first_derivative = ( outcome_minus_f1.transpose() * design_matrix ) ;
+					Vector first_derivative = ll.get_value_of_first_derivative() ;
+					check_close_or_small( expected_first_derivative(0), first_derivative(0), 0.00000000001, 0.0001 ) ;
+					check_close_or_small( expected_first_derivative(1), first_derivative(1), 0.00000000001, 0.0001 ) ;
+				}
+			}
+		}
+	}
+}
+
+BOOST_AUTO_TEST_SUITE_END() ;

Index: metro/test/test_mixture.cpp
==================================================================
--- metro/test/test_mixture.cpp
+++ metro/test/test_mixture.cpp
@@ -11,12 +11,10 @@
 #include "metro/IndependentObservationLogLikelihood.hpp"
 
 typedef Eigen::MatrixXd Matrix ;
 typedef Eigen::VectorXd Vector ;
 
-double const infinity = std::numeric_limits< double >::infinity() ;
-
 // #define DEBUG_MULTIVARIATE_T 1
 
 BOOST_AUTO_TEST_SUITE( test_mixture )
 
 namespace {
@@ -30,17 +28,22 @@
 
 		void set_data( Eigen::MatrixXd const& data ) {
 			m_n = data.rows() ;
 		}
 
-		void evaluate_at( Vector const& parameters ) {
-			evaluate_at( parameters, metro::DataRange( 0, m_n )) ;
+		void evaluate_at( Vector const& parameters, int numberOfDerivatives = 2 ) {
+			evaluate_at( parameters, metro::DataRange( 0, m_n ), numberOfDerivatives ) ;
 		}
 
-		void evaluate_at( Vector const& parameters, metro::DataSubset const& subset ) {
+		void evaluate_at( Vector const& parameters, metro::DataSubset const& subset, int numberOfDerivatives = 2 ) {
 			assert( parameters.size() == 1 ) ;
 			m_parameters = parameters ;
+			evaluate( numberOfDerivatives ) ;
+		}
+
+		void evaluate( int numberOfDerivatives = 2 ) {
+			// nothing to do
 		}
 		
 		double get_value_of_function() const {
 			return m_n * m_parameters(0) ;
 		}
@@ -50,15 +53,17 @@
 		}
 		Eigen::MatrixXd get_value_of_second_derivative() const {
 			assert(0) ;
 		}
 		
+		int number_of_parameters() const { return m_parameters.size() ; }
+
 		Eigen::VectorXd parameters() const {
 			return m_parameters ;
 		}
 
-		std::string get_spec() const {
+		std::string get_summary() const {
 			return "ConstantLogLikelihood" ;
 		}
 
 		virtual void get_terms_of_function( MatrixRef result ) const {
 			assert( result.rows() == m_n ) ;

ADDED   metro/test/test_modified_cholesky.cpp
Index: metro/test/test_modified_cholesky.cpp
==================================================================
--- metro/test/test_modified_cholesky.cpp
+++ metro/test/test_modified_cholesky.cpp
@@ -0,0 +1,215 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <boost/bind.hpp>
+#include <boost/noncopyable.hpp>
+#include "test_case.hpp"
+#include <Eigen/Core>
+#include <Eigen/Cholesky>
+#include "metro/ModifiedCholesky.hpp"
+
+// #define DEBUG 1
+
+AUTO_TEST_CASE( test_modified_cholesky_positive_definite ) {
+	typedef Eigen::VectorXd Vector ;
+	typedef Eigen::MatrixXd Matrix ;
+    metro::ModifiedCholesky< Matrix > comp ;
+	Eigen::LDLT< Matrix > ldlt ;
+	Matrix const identity = Matrix::Identity( 2, 2 ) ;
+
+	
+	{
+		Matrix const identity = Matrix::Identity( 1, 1 ) ;
+		Matrix test( 1, 1 ) ;
+		test << 1 ;
+		comp.compute( test ) ;
+		ldlt.compute( test ) ;
+		BOOST_CHECK_EQUAL( comp.matrixP() * identity, ldlt.transpositionsP() * identity ) ;
+		BOOST_CHECK_EQUAL( comp.vectorD(), ldlt.vectorD() ) ;
+		BOOST_CHECK_EQUAL( comp.matrixL() * identity, ldlt.matrixL() * identity ) ;
+		BOOST_CHECK_EQUAL( comp.solve( identity ) * test, identity ) ;
+	}
+
+	{
+		Matrix test( 2, 2 ) ;
+		test << 1, 0, 0, 1 ;
+		comp.compute( test ) ;
+		ldlt.compute( test ) ;
+		BOOST_CHECK_EQUAL( comp.matrixP() * identity, ldlt.transpositionsP() * identity ) ;
+		BOOST_CHECK_EQUAL( comp.vectorD(), ldlt.vectorD() ) ;
+		BOOST_CHECK_EQUAL( comp.matrixL() * identity, ldlt.matrixL() * identity ) ;
+		BOOST_CHECK_EQUAL( comp.solve( identity ) * test, identity ) ;
+	}
+
+	{
+		Matrix test( 2, 2 ) ;
+		test << 1, 0.5, 0.5, 1 ;
+		comp.compute( test ) ;
+		ldlt.compute( test ) ;
+		BOOST_CHECK_EQUAL( comp.matrixP() * identity, ldlt.transpositionsP() * identity ) ;
+		BOOST_CHECK_EQUAL( comp.vectorD(), ldlt.vectorD() ) ;
+		BOOST_CHECK_EQUAL( comp.matrixL() * identity, ldlt.matrixL() * identity ) ;
+		BOOST_CHECK_EQUAL( comp.solve( identity ) * test, identity ) ;
+	}
+}
+
+AUTO_TEST_CASE( test_modified_cholesky_nonpositive_definite ) {
+	typedef Eigen::VectorXd Vector ;
+	typedef Eigen::MatrixXd Matrix ;
+    metro::ModifiedCholesky< Matrix > comp ;
+	Eigen::LDLT< Matrix > ldlt ;
+
+	Matrix const identity = Matrix::Identity( 2, 2 ) ;
+
+	Matrix test( 2, 2 ) ;
+	test << 1, 2, 2, 1 ;
+
+	{
+		double offs[9] = { 0, 0.5, 0.9, 0.99, 1.0, 1.01, 1.05, 1.1, 2 } ;
+		for( std::size_t i = 0; i < 9; ++i ) {
+			test(0,1) = test(1,0) = offs[i] ;
+			comp.compute( test ) ;
+			BOOST_CHECK_EQUAL( comp.matrixP() * identity, identity ) ;
+			// Diagonal should be strictly positive.
+			for( int j = 0; j < 2; ++j ) {
+				TEST_ASSERT( comp.vectorD()(j) >= std::numeric_limits< double >::epsilon() ) ;
+			}
+
+#if DEBUG
+			std::cerr << "---------\n" ;
+			std::cerr << "test_modified_cholesky_nonpositive_definite(): off-diagonal = " << test(0,1) << ",\n" ;
+			std::cerr << "test_modified_cholesky_nonpositive_definite(): original matrix is:\n"
+				<< test << ".\n" ;
+#endif
+			Matrix reconstructed = comp.matrixL() * Matrix( Vector( comp.vectorD() ).asDiagonal() ) * comp.matrixL().transpose() ;
+#if DEBUG
+			std::cerr << "test_modified_cholesky_nonpositive_definite(): reconstructed matrix is:\n"
+				<< reconstructed << ".\n" ;
+#endif
+			// Modified cholesky is cholesky of a modified matrix with additions of +ve elements
+			// to the diagonal.  Check changes are +ve
+			BOOST_CHECK( (reconstructed.diagonal() - test.diagonal()).minCoeff() >= 0 ) ;
+			// Check that diagonal changes are within error bound
+			// (as in Fang & Leary (2006), formula (3)):
+			double const beta = std::sqrt( std::max( 1.0, offs[i] / std::sqrt( test.rows() * test.rows() - 1 )) ) ;
+			double const errorBound = (
+				std::pow( offs[i] / beta + ( test.rows() - 1.0 ) * beta, 2 )
+					+ 2 * ( test.diagonal().maxCoeff() + ( test.rows() - 1.0 ) * beta*beta )
+					+ std::numeric_limits< double >::epsilon()
+			) ;
+			BOOST_CHECK( (reconstructed.diagonal() - test.diagonal()).maxCoeff() <= errorBound ) ;
+#if DEBUG
+			std::cerr << "test_modified_cholesky_nonpositive_definite(): bound is " << errorBound << ".\n" ;
+#endif			
+			// Check that error is confined to diagonal
+			{
+				Matrix a = reconstructed.triangularView< Eigen::UnitLower >() ;
+				Matrix b = test.triangularView< Eigen::UnitLower >() ;
+				Matrix c = reconstructed.triangularView< Eigen::UnitUpper >() ;
+				Matrix d = test.triangularView< Eigen::UnitUpper >() ;
+				BOOST_CHECK( a == b ) ;
+				BOOST_CHECK( c == d ) ;
+			}
+				
+			if( test(0,1) < 1.0 ) {
+				// Matrix is +ve definite, we should be able to reconstruct original matrix exactly
+				BOOST_CHECK( (reconstructed.diagonal() - test.diagonal()).minCoeff() == 0 ) ;
+				Matrix solved = comp.solve( identity ) ;
+				BOOST_CHECK_EQUAL( solved * test, identity ) ;
+			}
+		}
+	}
+}
+
+
+AUTO_TEST_CASE( test_modified_cholesky_special_test_cases ) {
+	typedef Eigen::VectorXd Vector ;
+	typedef Eigen::MatrixXd Matrix ;
+	Eigen::LDLT< Matrix > ldlt ;
+
+	Matrix const identity = Matrix::Identity( 2, 2 ) ;
+
+	Matrix test( 4, 4 ) ;
+	
+	// This is a problematic 4x4 matrix identified by Schnabel and Eskow.
+	// It is discussed in section 6.2 of Fang & Leary (2006), who list
+	// its smallest eigenvalue as -0.378 and the maximum error / min eigenvalue
+	// as 2.733 for the GMW method.
+	test <<
+		 1890.3, -1705.6, -315.8,  3000.3,
+		-1705.6,  1538.3,  284.9, -2706.6,
+		 -315.8,   284.9,   52.5,  -501.2,
+		 3000.3, -2706.6, -501.2,  4760.8 ;
+
+	{
+		metro::ModifiedCholesky< Matrix > comp ;
+		comp.compute( test ) ;
+		
+		// Check diagonal is strictly positive.
+		for( int j = 0; j < 2; ++j ) {
+			TEST_ASSERT( comp.vectorD()(j) >= std::numeric_limits< double >::epsilon() ) ;
+		}
+
+#if DEBUG
+		std::cerr << "---------\n" ;
+		std::cerr << "test_modified_cholesky_special_test_cases(): off-diagonal = " << test(0,1) << ",\n" ;
+		std::cerr << "test_modified_cholesky_special_test_cases(): original matrix is:\n"
+			<< test << ".\n" ;
+#endif
+		Matrix reconstructed =
+			comp.matrixL()
+			* Matrix( Vector( comp.vectorD() ).asDiagonal() )
+			* comp.matrixL().transpose() ;
+#if DEBUG
+		std::cerr << "test_modified_cholesky_special_test_cases(): reconstructed matrix (1) is:\n"
+			<< reconstructed << ".\n" ;
+#endif
+		reconstructed = comp.matrixP().transpose() * reconstructed ;
+#if DEBUG
+		std::cerr << "test_modified_cholesky_special_test_cases(): reconstructed matrix (2) is:\n"
+			<< reconstructed << ".\n" ;
+#endif
+		reconstructed = reconstructed * comp.matrixP() ;
+#if DEBUG
+		std::cerr << "test_modified_cholesky_special_test_cases(): reconstructed matrix (full) is:\n"
+			<< reconstructed << ".\n" ;
+		std::cerr << "test_modified_cholesky_special_test_cases(): permutation matrix is:\n"
+			<< ( comp.matrixP() * Matrix::Identity( test.rows(), test.rows() ) ) << ".\n" ;
+#endif		
+		// Modified cholesky is cholesky of a modified matrix with additions of +ve elements
+		// to the diagonal.  Check changes are +ve
+		BOOST_CHECK( (reconstructed.diagonal() - test.diagonal()).minCoeff() >= 0 ) ;
+		// Check that diagonal changes are within error bound
+		// (as in Fang & Leary (2006), formula (3)):
+		double const beta = std::sqrt( std::max( 4760.8, 3000.3 / std::sqrt( test.rows() * test.rows() - 1 )) ) ;
+		double const errorBound = (
+			std::pow( 3000.3 / beta + ( test.rows() - 1.0 ) * beta, 2 )
+				+ 2 * ( 4760.8 + ( test.rows() - 1.0 ) * beta*beta )
+				+ std::numeric_limits< double >::epsilon()
+		) ;
+		double const fangLearyR2 = 2.7335 ; // Add 0.0005 for rounding
+		Matrix const E = reconstructed - test ;
+#if DEBUG
+		std::cerr << "test_modified_cholesky_special_test_cases(): bound is " << errorBound << ", predicted r2 is: " << fangLearyR2 << "\n" ;
+		std::cerr << "test_modified_cholesky_special_test_cases(): max error is " << E.maxCoeff() << ".\n" ;
+#endif
+		BOOST_CHECK( E.maxCoeff() <= errorBound ) ;
+		BOOST_CHECK( E.maxCoeff() / 0.3780759 <= fangLearyR2 ) ;
+		
+		// Check that error is confined to diagonal
+		{
+			Matrix a = reconstructed.triangularView< Eigen::UnitLower >() ;
+			Matrix b = test.triangularView< Eigen::UnitLower >() ;
+			Matrix c = reconstructed.triangularView< Eigen::UnitUpper >() ;
+			Matrix d = test.triangularView< Eigen::UnitUpper >() ;
+			BOOST_CHECK( (a - b).array().abs().maxCoeff() < 1E-9 ) ;
+			BOOST_CHECK( (c - d).array().abs().maxCoeff() < 1E-9 ) ;
+		}
+	}
+}
+
+

ADDED   metro/test/test_modified_newton_raphson.cpp
Index: metro/test/test_modified_newton_raphson.cpp
==================================================================
--- metro/test/test_modified_newton_raphson.cpp
+++ metro/test/test_modified_newton_raphson.cpp
@@ -0,0 +1,396 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <boost/bind.hpp>
+#include <boost/noncopyable.hpp>
+#include "test_case.hpp"
+#include <Eigen/Dense>
+#include <Eigen/QR>
+#include "metro/ModifiedNewtonRaphson.hpp"
+#include "metro/ModifiedCholesky.hpp"
+#include "metro/CholeskyStepper.hpp"
+
+BOOST_AUTO_TEST_SUITE( test_modified_newton_raphson ) ;
+
+namespace impl {
+	typedef metro::SmoothFunction FunctionBase ;
+
+	struct Multimodal1d_1: public FunctionBase {
+		// This function f has two local maxima and one local minimum
+		// f(x) = -x^4 + 2x^2
+		// f'(x) = -4x^3 + 4x
+		// f''(x) = -12 x^2 + 4
+		// maxima are at \pm 1
+		// minima is at 0
+		void evaluate_at( Vector const& point, int const number_of_derivatives = 0 ) {
+			assert( point.size() == 1 ) ;
+			m_point = point ;
+		}
+
+		void evaluate( int const number_of_derivatives = 0 ) {}
+		
+		double get_value_of_function() const {
+			assert( m_point.size() == 1 ) ;
+			return -std::pow( m_point(0), 4 ) + 2 * std::pow( m_point(0), 2 ) ;
+		}
+		Eigen::VectorXd get_value_of_first_derivative() const {
+			assert( m_point.size() == 1 ) ;
+			return Eigen::VectorXd::Constant( 1, -4.0 * std::pow( m_point(0), 3 ) + 4 * m_point(0) ) ; 
+		}
+
+		Eigen::MatrixXd get_value_of_second_derivative() const {
+			return Eigen::MatrixXd::Constant(
+				1, 1,
+				-12.0 * std::pow( m_point(0), 2 ) + 4.0
+			) ;
+		}
+		int number_of_parameters() const { return 1 ; }
+		Vector const& parameters() const { return m_point ; }
+		
+		std::string get_summary() const { return "Multimodal1d_1" ; }
+	private:
+		Vector m_point ;
+	} ;
+
+	struct Multimodal2d_1: public FunctionBase {
+		// This function f has four local maxima and one local minimum.
+		// We should walk to one of the maxima depending on where we start.
+		// For appropriately modified NR, we should never walk to the minimum.
+		// f' = -0.1 x^4 - 0.1 y^4 + x^2 + y^2
+		// This has a minimum at (0,0)
+		// And maxima at nonzero solutions of
+		// -0.4 x^3 - 2x = 0 and -0.4 y^3 + 2y = 0
+		// (x,y) = (\pm sqrt(5), \pm sqrt(5))
+		//
+		// First derivative is
+		//
+		// f' = ( -0.4 x^3 + 2x, -0.4 y^3 + 2y )
+		//
+		// Diagonals of second derivative are:
+		// f'' = -1.2 x^2 + 2, -1.2 y^2 + 2
+		//
+		// With zeroes on off-diagonals
+		//
+		void evaluate_at( Vector const& point, int const number_of_derivatives = 0 ) {
+			assert( point.size() == 2 ) ;
+			m_point = point ;
+		}
+
+		void evaluate( int const number_of_derivatives = 0 ) {}
+		
+		double get_value_of_function() const {
+			return -0.1 * ( std::pow( m_point(0), 4 ) + std::pow( m_point(1), 4 ) )
+				+ m_point(0) * m_point(0)
+				+ m_point(1) * m_point(1)
+			;
+		}
+		Eigen::VectorXd get_value_of_first_derivative() const {
+			Eigen::VectorXd result ;
+			result.setZero(2) ;
+			result(0) = -0.4 * std::pow( m_point(0), 3 ) + 2.0 * m_point(0) ;
+			result(1) = -0.4 * std::pow( m_point(1), 3 ) + 2.0 * m_point(1) ;
+			return result ;
+		}
+
+		Eigen::MatrixXd get_value_of_second_derivative() const {
+			Eigen::MatrixXd result ;
+			result.setZero(2,2) ;
+			result(0,0) = -1.2 * std::pow( m_point(0), 2 ) + 2.0 ;
+			result(1,1) = -1.2 * std::pow( m_point(1), 2 ) + 2.0 ;
+			return result ;
+		}
+
+		int number_of_parameters() const { return 2 ; }
+		Vector const& parameters() const { return m_point ; }
+
+		std::string get_summary() const { return "Multimodal2d_1" ; }
+
+	private:
+		Vector m_point ;
+	} ;
+	
+	struct Rosenbrock: public FunctionBase {
+		// Rosenbrock's function
+		// has global minimum at (1,1)
+		// f(x1,x2) = 100*(x2−x1^2)^2+(1−x1)^2
+		// f'(x1,x2) = ( -4 * x1 * (x2−x1^2) -2 * x1,  )
+		// f''(x1,x2) = ( -400*x1-2 
+		void evaluate_at( Vector const& point, int const number_of_derivatives = 0 ) {
+			assert( point.size() == 2 ) ;
+			m_point = point ;
+		}
+		double get_value_of_function() const {
+			Vector const& x = m_point ;
+			Vector x2 = m_point.array().square() ;
+			return 100.0 * (x(1) - x2(0)) * (x(1) - x2(0)) + (1 - x(0)) * (1 - x(0) )  ;
+		}
+
+		Eigen::VectorXd get_value_of_first_derivative() const {
+			assert(0) ;
+		}
+
+		Eigen::MatrixXd get_value_of_second_derivative() const {
+			assert(0) ;
+		}
+
+		int number_of_parameters() const { return 2 ; }
+		Vector const& parameters() const { return m_point ; }
+
+		std::string get_summary() const { return "Rosenbrock" ; }
+
+	private:
+		Vector m_point ;
+	} ;
+	
+
+	// The line search property of modified newton-raphson
+	// should enable it to find a maximum even if we tell it to
+	// jump way past it on each iteration.
+	// This class heads for the maximum but goes 10 times too far.
+	template< typename Function >
+	struct OvershootTarget: public boost::noncopyable {
+		OvershootTarget( FunctionBase::Vector target ):
+			m_target( target )
+		{}
+		
+		bool step( Function& function, FunctionBase::Vector* search_direction ) {
+			// walk toward the target but go ten times too far.
+			FunctionBase::Vector const& v = function.parameters() ;
+			assert( v.size() == m_target.size() ) ;
+			FunctionBase::Vector direction = m_target - v ;
+
+			if( direction.array().abs().maxCoeff() < 1E-3 ) {
+				return false ;
+			} else {
+				(*search_direction) = 10.0 * direction ;
+				return true ;
+			}
+		}
+		
+	private:
+		FunctionBase::Vector m_target ;
+	} ;
+	
+	template< typename Function >
+	struct StoppingCondition {
+		StoppingCondition( double tolerance  = 1E-12 ):
+			m_tolerance( tolerance ),
+			m_iterations(0)
+			{}
+		bool operator()(
+			Function const& function,
+			Eigen::VectorXd const& step
+		) {
+			++m_iterations ;
+			// Stop when all elements of the derivative are close to 0
+			// and the step size is also close to zero.
+			return
+				function.get_value_of_first_derivative().array().abs().maxCoeff() < m_tolerance
+				&& step.array().abs().maxCoeff() < m_tolerance ;
+		}
+		std::size_t iterations() const { return m_iterations ; }
+	private:
+		double m_tolerance ;
+		std::size_t m_iterations ;
+	} ;
+}
+
+AUTO_TEST_CASE( test_newton_direction_1d ) {
+	typedef impl::FunctionBase::Vector Vector ;
+	typedef impl::FunctionBase::Matrix Matrix ;
+	impl::Multimodal1d_1 function ;
+	Eigen::ColPivHouseholderQR< Matrix > solver ;
+	double const one_third = 0.3333333333333333333333333 ;
+	Vector point( 1 ) ;
+	for( point(0) = -10; point(0) < 10; point(0) += 0.01 ) {
+		// Check that the solver always finds an ascent direction
+		function.evaluate_at( point ) ;
+		solver.compute( function.get_value_of_second_derivative() ) ;
+		Vector h = solver.solve( -function.get_value_of_first_derivative() ) ;
+		double directional_derivative = function.get_value_of_first_derivative().transpose() * h ;
+		// f''(x) = -12 x^2 + 4
+		// so 2nd derivative is negative for x < sqtr
+		BOOST_CHECK(
+			( std::abs( point(0) ) > std::sqrt( one_third ) && directional_derivative > 0 )
+				|| 
+			( std::abs( point(0) ) < std::sqrt( one_third ) && directional_derivative < 0 )
+		) ;
+	}
+}
+
+namespace {
+	template< typename Function >
+	struct ModifiedCholeskySolver {
+		typedef impl::FunctionBase::Vector Vector ;
+		typedef impl::FunctionBase::Matrix Matrix ;
+
+		Vector compute( Function& function, Vector const& point ) {
+			function.evaluate_at( point ) ;
+			m_solver.compute( -function.get_value_of_second_derivative() ) ;
+			return m_solver.solve( function.get_value_of_first_derivative() ) ;
+		} ;
+		
+	private:
+		metro::ModifiedCholesky< Matrix > m_solver ;
+	} ;
+}
+
+AUTO_TEST_CASE( test_cholesky_stepper_direction_1d ) {
+	typedef impl::FunctionBase::Vector Vector ;
+	typedef impl::FunctionBase::Matrix Matrix ;
+	impl::Multimodal1d_1 function ;
+	metro::CholeskyStepper stepper( 1E-12, 100 ) ;
+#if 0
+		[]( int iteration,
+			double ll,
+			double target_ll,
+			metro::CholeskyStepper::Vector const& point,
+			metro::CholeskyStepper::Vector const& first_derivative,
+			metro::CholeskyStepper::Vector const& step,
+			bool converged
+		) {
+			std::cerr
+				<< " ITERATION:" << iteration << "\n"
+				<< "        LL:" << ll << "\n"
+				<< "    TARGET:" << target_ll << "\n"
+				<< "     POINT:" << point.transpose() << "\n"
+				<< "DERIVATIVE:" << first_derivative.transpose() << "\n"
+				<< "      STEP:" << step.transpose() << "\n"
+				<< " CONVERGED:" << ( converged ? "yes" : "no" ) << "\n" ;
+		}
+	 ) ;
+#endif
+	Vector point( 1 ) ;
+	// start at -10.005 to avoid meeting maxima or minima
+	for( point(0) = -10.005; point(0) < 10; point(0) += 0.01 ) {
+		stepper.reset() ;
+		// Check that the solver always finds an ascent direction
+		function.evaluate_at( point ) ;
+		Vector h ;
+		BOOST_CHECK( stepper.step( function, &h ) ) ;
+		double directional_derivative = function.get_value_of_first_derivative().transpose() * h ;
+		//std::cerr << "x = " << point(0) << ", function = " << function.get_value_of_function()
+		//	<< ", derivative = " << function.get_value_of_first_derivative().transpose() << ", "
+		//	<< "DD = " << directional_derivative << ".\n" ;
+		BOOST_CHECK_GT( directional_derivative, 0 ) ;
+	}
+}
+
+AUTO_TEST_CASE( test_cholesky_stepper_direction_2d ) {
+	typedef impl::FunctionBase::Vector Vector ;
+	typedef impl::FunctionBase::Matrix Matrix ;
+	impl::Multimodal2d_1 function ;
+	metro::CholeskyStepper stepper( 1E-12, 100 ) ;
+
+	Vector point( 2 ) ;
+	// start at -10.01 so we do not reach 0 (where there is a maximum)
+	for( point(0) = -10.01; point(0) < 10; point(0) += 0.025 ) {
+		for( point(1) = -10.01; point(1) < 10; point(1) += 0.025 ) {
+			stepper.reset() ;
+			function.evaluate_at( point ) ;
+			Vector h ;
+			stepper.step( function, &h ) ;
+			double const directional_derivative = function.get_value_of_first_derivative().transpose() * h ;
+			BOOST_CHECK_GT( directional_derivative, 0 ) ;
+		}
+	}
+}
+
+AUTO_TEST_CASE( test_modified_ewton_raphson_overshoot_1d ) {
+	typedef impl::FunctionBase::Vector Vector ;
+	impl::Multimodal1d_1 function ;
+	
+	// For 1d function 1, maxima are at -1 and 1.
+	Vector target ;
+	target.setZero(1) ;
+	target(0) = -1 ;
+
+	{
+		impl::OvershootTarget< impl::Multimodal1d_1 > overshoot( target ) ;
+		Vector start = Vector::Constant( 1, -0.001 ) ;
+		Vector result = metro::find_maximum_by_modified_newton_raphson_with_line_search(
+			function,
+			start,
+			overshoot
+		) ;
+
+		BOOST_CHECK_CLOSE( result(0), -1, 0.1 ) ;
+	}
+}
+
+AUTO_TEST_CASE( test_newton_raphson_overshoot_2d ) {
+	typedef impl::FunctionBase::Vector Vector ;
+	impl::Multimodal2d_1 function ;
+
+	Vector maximum ;
+	maximum.setZero(2) ;
+	maximum(0) = -sqrt(5) ;
+	maximum(1) = -sqrt(5) ;
+
+	{
+		impl::OvershootTarget< impl::Multimodal2d_1 > overshoot( maximum ) ;
+		Vector start = Vector::Constant(2,-1) ;
+		Vector result = metro::find_maximum_by_modified_newton_raphson_with_line_search(
+			function,
+			start,
+			overshoot
+		) ;
+
+		BOOST_CHECK_CLOSE( result(0), -std::sqrt(5), 0.1 ) ;
+		BOOST_CHECK_CLOSE( result(1), -std::sqrt(5), 0.1 ) ;
+	}
+}
+
+AUTO_TEST_CASE( test_modified_cholesky_newton_raphson_2d ) {
+	typedef impl::FunctionBase::Vector Vector ;
+	impl::Multimodal2d_1 function ;
+
+	{
+		metro::CholeskyStepper solver( 1E-12, 100 ) ;
+		Vector start = Vector::Constant(2,-1) ;
+		Vector result = metro::find_maximum_by_modified_newton_raphson_with_line_search(
+			function,
+			start,
+			solver
+		) ;
+			
+		BOOST_CHECK_CLOSE( result(0), -std::sqrt(5), 0.1 ) ;
+		BOOST_CHECK_CLOSE( result(1), -std::sqrt(5), 0.1 ) ;
+		std::cerr << "test_newton_raphson_overshoot_2d: took " << solver.number_of_iterations() << " iterations.\n" ;
+	}
+	{	
+		metro::CholeskyStepper solver( 1E-12, 100 ) ;
+		Vector start = Vector::Constant(2,-1) ;
+		start(1) = -0.1 ;
+		Vector result = metro::find_maximum_by_modified_newton_raphson_with_line_search(
+			function,
+			start,
+			solver
+		) ;
+			
+		BOOST_CHECK_CLOSE( result(0), -std::sqrt(5), 0.1 ) ;
+		BOOST_CHECK_CLOSE( result(1), -std::sqrt(5), 0.1 ) ;
+		std::cerr << "test_newton_raphson_overshoot_2d: took " << solver.number_of_iterations() << " iterations.\n" ;
+	}
+	{
+		metro::CholeskyStepper solver( 1E-12, 100 ) ;
+		Vector start = Vector::Constant(2,-1) ;
+		start(0) = -100 ;
+		start(1) = -0.1 ;
+		Vector result = metro::find_maximum_by_modified_newton_raphson_with_line_search(
+			function,
+			start,
+			solver
+		) ;
+			
+		BOOST_CHECK_CLOSE( result(0), -std::sqrt(5), 0.1 ) ;
+		BOOST_CHECK_CLOSE( result(1), -std::sqrt(5), 0.1 ) ;
+		std::cerr << "test_newton_raphson_overshoot_2d: took " << solver.number_of_iterations() << " iterations.\n" ;
+	}
+}
+
+BOOST_AUTO_TEST_SUITE_END()

ADDED   metro/test/test_multinomial_regression.cpp
Index: metro/test/test_multinomial_regression.cpp
==================================================================
--- metro/test/test_multinomial_regression.cpp
+++ metro/test/test_multinomial_regression.cpp
@@ -0,0 +1,530 @@
+#include <string>
+#include <vector>
+#include <iostream>
+#include "test_case.hpp"
+#include "metro/SampleRange.hpp"
+#include "metro/regression/Design.hpp"
+#include "metro/regression/Logistic.hpp"
+#include "metro/regression/MultinomialRegressionLogLikelihood.hpp"
+
+// #define DEBUG_TESTS 1
+namespace {
+	inline void check_close_or_small(
+		double expected, double observed, 
+		double small, double pct_tol
+	) {
+		if (std::fabs(expected) < small) {
+			BOOST_CHECK_SMALL(observed, small);
+		} else {
+			BOOST_CHECK_CLOSE(expected, observed, pct_tol);
+		}
+	}
+}
+
+typedef std::vector< std::string > Names ;
+
+BOOST_AUTO_TEST_SUITE( test_multinomial ) ;
+
+AUTO_TEST_CASE( test_multinomialregression_one_sample ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	using std::exp ;
+	using std::log ;
+	
+	int const nSamples = 1 ;
+	std::vector< metro::SampleRange > all_samples( 1, metro::SampleRange( 0, 1 ) ) ;
+	Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+	predictor_levels(0,0) = 1 ;
+	predictor_levels(1,0) = 2 ;
+
+	for( int nOutcomes = 3; nOutcomes < 5; ++nOutcomes ) {
+		Matrix outcome = Matrix::Zero(nSamples, nOutcomes) ;
+		Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+		Names outcome_names ;
+		for( int j = 0; j < nOutcomes; ++j ) {
+			outcome_names.push_back( "outcome" + std::to_string( j )) ;
+		}
+//		for( int outcome_i = 0; outcome_i < nOutcomes; ++outcome_i ) {
+		for( int outcome_i = 1; outcome_i < nOutcomes; ++outcome_i ) {
+			// Set the chosen outcome for the single sample
+			outcome.setZero() ;
+			outcome(0,outcome_i) = 1 ;
+			
+			MultinomialRegressionLogLikelihood ll(
+				Design::create(
+					outcome, all_samples, outcome_names,
+					covariates, all_samples, Names(),
+					Names( 1, "predictor" )
+				)
+			) ;
+			
+			// Set up a single predictor, equal to 1 with certainty.
+			Matrix predictor_probabilities = Matrix::Zero( 1, 2 ) ;
+			predictor_probabilities(0, 0) = 1.0 ;
+			ll.set_predictor_levels( predictor_levels, predictor_probabilities, all_samples ) ;
+
+			int const nParameters = 2 * ( nOutcomes - 1 ) ;
+			int const M = nOutcomes - 1 ;
+			// Now test values.
+			{
+				Vector parameters = Vector::Zero( nParameters ) ;
+				ll.evaluate_at( parameters ) ;
+				// All probs are equal to 1/(M+1).	So outcome probability equals this.
+				Matrix parameter_matrix = parameters ;
+				parameter_matrix.resize( 2, nOutcomes - 1 ) ;
+#if DEBUG_TESTS
+				std::cerr << "parameters = " << parameters.transpose() << ".\n" ;
+				std::cerr << "outcome = " << outcome.transpose() << ".\n" ;
+#endif
+			
+				double const expected_ll = std::log( 1.0 / double( nOutcomes ) ) ;
+				BOOST_CHECK_CLOSE( expected_ll, ll.get_value_of_function(), 0.00001 ) ;
+				
+				Matrix F = Matrix::Constant( 1, nOutcomes, 1.0 / double( nOutcomes ) ) ;
+				
+				Matrix B = -F.block( 0, 1, 1, M ) ;
+				if( outcome_i > 0 ) {
+					B( 0, outcome_i - 1 ) += 1.0 ;
+				}
+				
+				Matrix design_matrix = Matrix::Constant( 1, 2, 1.0 ) ;
+				Matrix expected_first_derivative = Matrix::Zero( 1, M * 2 ) ;
+				for( int j = 0; j < M ; ++j ) {
+					expected_first_derivative.block( 0, j*2, 1, 2 ) = design_matrix.row(0) * B( 0, j ) ;
+				}
+
+				Vector const first_derivative = ll.get_value_of_first_derivative() ;
+				for( int j = 0; j < M*2; ++j ) {
+					BOOST_CHECK_CLOSE( expected_first_derivative(0,j), first_derivative(j), 0.00001 ) ;
+				}
+
+				Matrix C = Matrix::Zero( M, M ) ;
+				for( int j = 0; j < M ; ++j ) {
+					double Z_ij = ( j == outcome_i - 1 ) ? ( 1 - F(j+1) ) : ( - F(j+1) ) ;
+					for( int k = 0; k < M; ++k ) {
+						double Z_ik = ( k == outcome_i - 1 ) ? ( 1 - F(k+1) ) : ( - F(k+1) ) ;
+						double Z_jk = ( j == k ) ? ( 1 - F(k+1) ) : ( - F(k+1) ) ;
+//						std::cerr << "j:" << j << ", k:" << k << ", Zij:" << Z_ij << ", Z_ik:" << Z_ik << ", Z_jk:" << Z_jk << ".\n" ;
+						C( j, k ) = ( Z_ij * Z_ik ) - ( F( j+1 ) * Z_jk ) ;
+					}
+				}
+
+				Matrix expected_2nd_derivative = Matrix::Zero( M*2, M*2 ) ;
+				for( int j = 0; j < M ; ++j ) {
+					for( int k = 0; k < M ; ++k ) {
+						expected_2nd_derivative.block( j*2, k*2, 2, 2 )
+							= ( C( j, k ) - B( 0, j ) * B( 0, k ) ) * design_matrix.row(0).transpose() * design_matrix.row(0) ;
+					}
+				}
+
+				Matrix const second_derivative = ll.get_value_of_second_derivative() ;
+				for( int j = 0; j < M*2; ++j ) {
+					for( int k = 0; k < M*2; ++k ) {
+						BOOST_CHECK_CLOSE( expected_2nd_derivative(j,k), second_derivative(j,k), 0.00001 ) ;
+					}
+				}
+				
+#if DEBUG_TESTS
+				std::cerr << "test_multinomialregression_one_sample:\n" ;
+				std::cerr << "nOutcomes = " << nOutcomes << "\n" ;
+				std::cerr << "F = " << F << "\n" ;
+				std::cerr << "B = " << B << "\n" ;
+				std::cerr << "C = \n" << C << "\n" ;
+				std::cerr << "expected 2nd derivative = \n"
+					<< expected_2nd_derivative << "\n" ;
+				std::cerr << "actual 2nd derivative = \n"
+					<< second_derivative << "\n" ;
+#endif
+			}
+
+			for( int nonzero_i = 0; nonzero_i < nParameters; ++nonzero_i )
+			{
+
+				Vector parameters = Vector::Zero( 2 * ( nOutcomes - 1 ) ) ;
+				parameters( nonzero_i ) = log(2.0) ;
+#if DEBUG_TESTS
+				std::cerr << "##############\n" ;
+				std::cerr << "nOutcomes = " << nOutcomes << ".\n" ;
+				std::cerr << "parameters = " << parameters.transpose() << ".\n" ;
+				std::cerr << "outcome = " << outcome.transpose() << ".\n" ;
+				std::cerr << "nonzero = " << nonzero_i << ".\n" ;
+#endif
+				ll.evaluate_at( parameters ) ;
+
+				// f_i will equal 1/(M+2), or 2/(M+2) for i=floor(nonzero_i/2).
+				Matrix parameter_matrix = parameters ;
+				parameter_matrix.resize( 2, nParameters ) ;
+			
+				// So if the outcome equals floor(nonzero_i/2) we have
+				int const special_outcome = nonzero_i / 2 ;
+				double expected_ll ;
+				if( outcome_i == 0 ) {
+					expected_ll = std::log( 1.0 / ( M + 2.0 ) ) ;
+				} else if( ( outcome_i - 1 ) == special_outcome ) {
+					expected_ll = std::log( 2.0 / ( M + 2.0 ) ) ;
+				} else {
+					expected_ll = std::log( 1.0 / ( M + 2.0 ) ) ;
+				}
+				BOOST_CHECK_CLOSE( expected_ll, ll.get_value_of_function(), 0.00001 ) ;
+
+				Matrix F = Matrix::Constant( 1, nOutcomes, 1.0 / ( M + 2.0 ) ) ;
+				F( special_outcome + 1 ) = 2.0 / ( M + 2.0 ) ;
+				
+				Matrix B = -F.block( 0, 1, 1, M ) ;
+				if( outcome_i > 0 ) {
+					B( 0, outcome_i - 1 ) += 1.0 ;
+				}
+				Matrix design_matrix = Matrix::Constant( 1, 2, 1.0 ) ;
+				Matrix expected_first_derivative = Matrix::Zero( 1, M * 2 ) ;
+				for( int j = 0; j < M ; ++j ) {
+					expected_first_derivative.block( 0, j*2, 1, 2 ) = design_matrix.row(0) * B( 0, j ) ;
+				}
+
+				Vector const first_derivative = ll.get_value_of_first_derivative() ;
+				for( int j = 0; j < M*2; ++j ) {
+					BOOST_CHECK_CLOSE( expected_first_derivative(0,j), first_derivative(j), 0.00001 ) ;
+				}
+
+				Matrix C = Matrix::Zero( M, M ) ;
+				for( int j = 0; j < M ; ++j ) {
+					double Z_ij = ( j == outcome_i - 1 ) ? ( 1 - F(j+1) ) : ( - F(j+1) ) ;
+					for( int k = 0; k < M; ++k ) {
+						double Z_ik = ( k == outcome_i - 1 ) ? ( 1 - F(k+1) ) : ( - F(k+1) ) ;
+						double Z_jk = ( j == k ) ? ( 1 - F(k+1) ) : ( - F(k+1) ) ;
+						C( j, k ) = ( Z_ij * Z_ik ) - ( F( j+1 ) * Z_jk ) ;
+						//std::cerr << "j:" << j << ", k:" << k << ", Zij:" << Z_ij << ", Z_ik:" << Z_ik << ", Z_jk:" << Z_jk << ".\n" ;
+					}
+				}
+				Matrix expected_2nd_derivative = Matrix::Zero( M*2, M*2 ) ;
+				for( int j = 0; j < M ; ++j ) {
+					for( int k = 0; k < M ; ++k ) {
+						expected_2nd_derivative.block( j*2, k*2, 2, 2 )
+							= ( C( j, k ) - B( 0, j ) * B( 0, k ) ) * design_matrix.row(0).transpose() * design_matrix.row(0) ;
+					}
+				}
+
+				Matrix const second_derivative = ll.get_value_of_second_derivative() ;
+				
+#if DEBUG_TESTS
+				std::cerr << "test_multinomialregression_one_sample:\n" ;
+				std::cerr << "nOutcomes = " << nOutcomes << "\n" ;
+				std::cerr << "F = " << F << "\n" ;
+				std::cerr << "B = " << B << "\n" ;
+				std::cerr << "C = \n" << C << "\n" ;
+				std::cerr << "expected 2nd derivative = \n"
+					<< expected_2nd_derivative << "\n" ;
+				std::cerr << "actual 2nd derivative = \n"
+					<< second_derivative << "\n" ;
+#endif
+				for( int j = 0; j < M*2; ++j ) {
+					for( int k = 0; k < M*2; ++k ) {
+						BOOST_CHECK_CLOSE( expected_2nd_derivative(j,k), second_derivative(j,k), 0.00001 ) ;
+					}
+				}
+			}
+		}
+	}
+}
+
+AUTO_TEST_CASE( test_multinomialregression_two_outcomes_two_samples ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	using std::exp ;
+	using std::log ;
+	
+	
+	{
+		int const nSamples = 2 ;
+
+		typedef std::vector< metro::SampleRange > SampleRanges ;
+		SampleRanges const all_samples( 1, metro::SampleRange( 0, nSamples )) ;
+		Matrix outcome = Matrix::Zero(nSamples,2) ;
+		outcome(0,0) = 1 ;
+		outcome(1,1) = 1 ;
+		Matrix outcome_nonmissingness = Matrix::Constant( nSamples, 2, 1.0 ) ;
+		Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+		Matrix covariate_nonmissingness = Matrix::Constant( nSamples, 0, 1.0 ) ;
+		
+		MultinomialRegressionLogLikelihood ll(
+			Design::create(
+				outcome, all_samples, Names({"outcome=0","outcome=1"}),
+				covariates, all_samples, Names(),
+				Names({"predictor"})
+			)
+		) ;
+		
+		Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+		predictor_levels(0,0) = 0 ;
+		predictor_levels(1,0) = 1 ;
+
+		// Set half the sample to certainly 0, half to certainly 1.
+		Matrix predictor_probabilities = Matrix::Zero( nSamples, 2 ) ;
+		predictor_probabilities( 0, 0 ) = 1.0 ;
+		predictor_probabilities( 1, 1 ) = 1.0 ;
+
+		ll.set_predictor_levels( predictor_levels, predictor_probabilities, all_samples ) ;
+		
+		{
+			Vector parameters = Vector::Zero( 2 ) ;
+			ll.evaluate_at( parameters ) ;
+			// all probabilities are one-half.
+			Vector f1( 2 ) ;
+			f1 << 0.5, 0.5 ;
+			Vector F = f1 ; // F=f because probs are 1/2
+
+			double expected_ll = nSamples * std::log( 0.5 ) ;
+			BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+			Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+			design_matrix.col(0).setConstant( 1.0 ) ;
+			design_matrix( 1, 1 ) = 1.0 ;
+			
+			Vector B = F.array() * ( Vector::Constant( 2, 1.0 ) - F ).array() ;
+			for( int i = 0; i < B.size(); ++i ) {
+				B(i) = B(i) / F(i) ;
+			}
+			B(0) = -B(0) ;
+			Vector const expected_first_derivative = ( B.transpose() * design_matrix ) ;
+			Vector const first_derivative = ll.get_value_of_first_derivative() ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+
+			// Compute second derivative
+			Vector C = ( Vector::Constant( 2, 1.0 ) - 2.0 * F ).array() * B.array() ;
+#if DEBUG_TEST
+			std::cerr << "expected C = " << C << ".\n" ;
+#endif
+			Matrix DD = Matrix::Zero( 2, 2 ) ;
+			for( int i = 0; i < design_matrix.rows(); ++i ) {
+				DD += ( C(i) - B(i) * B(i) ) * design_matrix.row(i).transpose() * design_matrix.row(i) ;
+			}
+#if DEBUG_TEST
+			std::cerr << "expected second derivative = " << D << ".\n" ;
+#endif
+			Matrix const& second_derivative = ll.get_value_of_second_derivative() ;
+			BOOST_CHECK_CLOSE( DD(0,0), second_derivative(0,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(0,1), second_derivative(0,1), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,0), second_derivative(1,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,1), second_derivative(1,1), 0.0000001 ) ;
+		}
+
+		{
+			// Set a nonzero predictor effect parameter.
+			Vector parameters = Vector::Zero( 2 ) ;
+			parameters << 0.0, 1.0 ;
+			ll.evaluate_at( parameters ) ;
+			// Now we have exp( x^t theta ) = 1, e for the two samples.	 Thus f1 is 1/2, e/1+e
+			Vector f1( 2 ) ;
+			f1 << 0.5, ( std::exp( 1 ) / ( 1.0 + std::exp(1.0) ) ) ;
+			Vector F = f1 ; // f_0 = f_1 for first sample because the first prob is 0.5.
+			double const expected_ll = F.array().log().sum() ;
+			BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+			// f1 = 1/2, e/1+e
+			Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+			design_matrix.col(0).setConstant( 1.0 ) ;
+			design_matrix( 1, 1 ) = 1.0 ;
+			
+			Vector B = F.array() * ( Vector::Constant( 2, 1.0 ) - F ).array() ;
+			for( int i = 0; i < B.size(); ++i ) {
+				B(i) = B(i) / F(i) ;
+			}
+			B(0) = -B(0) ;
+			Vector const expected_first_derivative = ( B.transpose() * design_matrix ) ;
+			Vector const first_derivative = ll.get_value_of_first_derivative() ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+
+			// Compute second derivative
+			Vector C = ( Vector::Constant( 2, 1.0 ) - 2.0 * F ).array() * B.array() ;
+			
+#if DEBUG_TESTS
+			std::cerr << "test_multinomialregression_two_samples: B = " << B.transpose() << "\n" ;
+			std::cerr << "test_multinomialregression_two_samples: C = " << C.transpose() << "\n" ;
+#endif
+			
+			Matrix DD = Matrix::Zero( 2, 2 ) ;
+			for( int i = 0; i < design_matrix.rows(); ++i ) {
+				DD -= ( B(i) * B(i) ) * design_matrix.row(i).transpose() * design_matrix.row(i) ;
+			}
+#if DEBUG_TESTS
+			std::cerr << "test_multinomialregression_two_samples: after B terms, expected 2nd derivative =\n" << DD << ".\n" ;
+#endif
+			for( int i = 0; i < design_matrix.rows(); ++i ) {
+				DD += C(i) * design_matrix.row(i).transpose() * design_matrix.row(i) ;
+			}
+			Matrix const& second_derivative = ll.get_value_of_second_derivative() ;
+#if DEBUG_TESTS
+			std::cerr << "test_multinomialregression_two_samples: expected 2nd derivative =\n" << DD << ".\n" ;
+#endif
+			BOOST_CHECK_CLOSE( DD(0,0), second_derivative(0,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(0,1), second_derivative(0,1), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,0), second_derivative(1,0), 0.0000001 ) ;
+			BOOST_CHECK_CLOSE( DD(1,1), second_derivative(1,1), 0.0000001 ) ;
+		}
+	}
+}
+
+
+AUTO_TEST_CASE( test_multinomialregression_two_outcomes_certain_predictors ) {
+	using metro::SampleRange ;
+	using namespace metro::regression ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+	using std::exp ;
+	using std::log ;
+	
+	std::vector< double > parameter_values ;
+	parameter_values.push_back( -10 ) ;
+	parameter_values.push_back( -3.141592654 ) ;
+	parameter_values.push_back( -1 ) ;
+	parameter_values.push_back( -0.25 ) ;
+	parameter_values.push_back( 0 ) ;
+	parameter_values.push_back( 0.25 ) ;
+	parameter_values.push_back( 0.5 ) ;
+	parameter_values.push_back( 1 ) ;
+	parameter_values.push_back( 3.141592654 ) ;
+	parameter_values.push_back( 10 ) ;
+	
+	for( int nCases = 0; nCases < 20; ++nCases ) {
+		for( int nControls = 0; nControls < 20; ++nControls ) {
+			int nSamples = nCases + nControls ;
+
+			typedef std::vector< metro::SampleRange > SampleRanges ;
+			SampleRanges const all_samples( 1, metro::SampleRange( 0, nSamples )) ;
+
+			// contruct outcome
+			Matrix outcome = Matrix::Zero(nSamples,2) ;
+			{
+				int i = 0 ;
+				for( ; i < nCases; ++i ) {
+					outcome(i,1) = 1 ;
+				}
+				for( ; i < nSamples; ++i ) {
+					outcome(i,0) = 1 ;
+				}
+			}
+			Matrix covariates = Matrix::Zero( nSamples, 0 ) ;
+
+			MultinomialRegressionLogLikelihood ll(
+				Design::create(
+					outcome, all_samples, Names({"outcome=0", "outcome=1"}),
+					covariates, all_samples, Names(),
+					Names({"predictor"})
+				)
+			) ;
+		
+			// construct a 0/1 predictor.
+			Matrix predictor_levels = Matrix::Zero( 2, 1 ) ;
+			predictor_levels(0,0) = 0 ;
+			predictor_levels(1,0) = 1 ;
+
+			// Set half the sample to certainly 0, half to certainly 1.
+			Matrix predictor_probabilities = Matrix::Zero( nSamples, 2 ) ;
+			int const nOnes = nSamples / 2 ;
+			for( int i = 0; i < nSamples; ++i ) {
+				if( i < nOnes ) {
+					predictor_probabilities( i, 1 ) = 1 ;
+				} else {
+					predictor_probabilities( i, 0 ) = 1 ;
+				}
+			}
+			
+			ll.set_predictor_levels( predictor_levels, predictor_probabilities, all_samples ) ;
+		
+			// Ok we have our likelihood.  Now compute with it.
+			{
+				ll.evaluate_at( Vector::Zero( 2 ) ) ;
+				// all probabilities are one-half.
+				double expected_ll = nSamples * std::log( 0.5 ) ;
+				BOOST_CHECK_CLOSE( ll.get_value_of_function(), expected_ll, 0.0000001 ) ;
+
+#if DEBUG_TESTS
+				std::cerr << "test_multinomialregression_two_outcomes_certain_predictors(): outcome:\n" << outcome << ".\n" ;
+#endif
+				Vector one_minus_f1 = ( outcome.col(1).array() - 0.5 ) ;
+				Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+				design_matrix.col(0).setConstant( 1.0 ) ;
+				design_matrix.col(1).segment( 0, nOnes ).setConstant( 1.0 ) ;
+				
+				Vector const expected_first_derivative = ( one_minus_f1.transpose() * design_matrix ) ;
+				Vector const first_derivative = ll.get_value_of_first_derivative() ;
+				BOOST_CHECK_CLOSE( expected_first_derivative(0), first_derivative(0), 0.0000001 ) ;
+				BOOST_CHECK_CLOSE( expected_first_derivative(1), first_derivative(1), 0.0000001 ) ;
+				
+				Matrix DD = Matrix::Zero( 2, 2 ) ;
+				for( int sample = 0; sample < nSamples; ++sample ) {
+					DD -= 0.25 * design_matrix.row( sample ).transpose() * design_matrix.row( sample ) ;
+				}
+				Matrix const& second_derivative = ll.get_value_of_second_derivative() ;
+				for( int i = 0; i < 2; ++i ) {
+					for( int j = 0; j < 2; ++j ) {
+						BOOST_CHECK_CLOSE( DD(i,j), second_derivative(i,j), 0.000001 ) ;
+					}
+				}
+			}
+
+			Vector parameters = Vector::Zero( 2 ) ;
+			for( std::size_t pi0 = 0; pi0 < parameter_values.size(); ++pi0 ) {
+				for( std::size_t pi1 = 0; pi1 < parameter_values.size(); ++pi1 ) {
+					parameters(0) = parameter_values[ pi0 ] ;
+					parameters(1) = parameter_values[ pi1 ] ;
+
+					ll.evaluate_at( parameters ) ;
+
+					Matrix design_matrix = Matrix::Zero( nSamples, 2 ) ;
+					design_matrix.col(0).setConstant( 1.0 ) ;
+					design_matrix.col(1).segment( 0, nOnes ).setConstant( 1.0 ) ;
+
+					Vector F1 = ( design_matrix * parameters ).array().exp() ;
+					Vector ones = Vector::Constant( nSamples, 1.0 ) ;
+					Vector const F0 = ones.array() / ( 1.0 + F1.array() ) ;
+					F1 = F1.array() / ( 1.0 + F1.array() ) ;
+
+					// Incorporate the phenotype by taking F0 for controls or F1 for cases.
+					Vector Fpsi = F1 ;
+					Fpsi.segment( nCases, nControls ) = F0.segment( nCases, nControls ) ;
+
+#if DEBUG_TESTS > 1
+					std::cerr << "ncontrols = " << nControls << ", nCases = " << nCases << ".\n" ; 
+					std::cerr << "F0 =\n" << F0 << ".\n" ; 
+					std::cerr << "F1 =\n" << F1 << ".\n" ; 
+					std::cerr << "Fpsi =\n" << Fpsi << ".\n" ; 
+#endif
+					
+					double expected_ll = Fpsi.array().log().sum() ;
+					check_close_or_small( expected_ll, ll.get_value_of_function(), 0.00000000001, 0.0001 ) ;
+					Vector outcome_minus_f1 = ( outcome.col(1) - F1 ) ;
+
+					Vector const expected_first_derivative = ( outcome_minus_f1.transpose() * design_matrix ) ;
+					Vector first_derivative = ll.get_value_of_first_derivative() ;
+					check_close_or_small( expected_first_derivative(0), first_derivative(0), 0.00000000001, 0.0001 ) ;
+					check_close_or_small( expected_first_derivative(1), first_derivative(1), 0.00000000001, 0.0001 ) ;
+
+					Vector A = ( 1.0 - Fpsi.array() ) ;
+					Vector B = ( 1.0 - Fpsi.array() ) * ( 1.0 - 2.0 * Fpsi.array() ) ;
+					Matrix DD = Matrix::Zero( 2, 2 ) ;
+					for( int sample = 0; sample < nSamples; ++sample ) {
+						DD += ( B(sample) - A(sample) * A(sample) ) * design_matrix.row( sample ).transpose() * design_matrix.row( sample ) ;
+					}
+					Matrix const& second_derivative = ll.get_value_of_second_derivative() ;
+					
+					for( int i = 0; i < 2; ++i ) {
+						for( int j = 0; j < 2; ++j ) {
+							check_close_or_small( DD(i,j), second_derivative(i,j), 0.00000000001, 0.0001 ) ;
+						}
+					}
+				}
+			}
+		}
+	}
+}
+
+BOOST_AUTO_TEST_SUITE_END() ;

ADDED   metro/test/test_regression_design.cpp
Index: metro/test/test_regression_design.cpp
==================================================================
--- metro/test/test_regression_design.cpp
+++ metro/test/test_regression_design.cpp
@@ -0,0 +1,235 @@
+#include <vector>
+#include <iostream>
+#include <boost/format.hpp>
+#include "test_case.hpp"
+#include "metro/SampleRange.hpp"
+#include "metro/union_ranges.hpp"
+#include "metro/regression/Design.hpp"
+
+#define DEBUG 1
+
+BOOST_AUTO_TEST_SUITE( test_regression_design )
+	
+AUTO_TEST_CASE( test_construction ) {
+	using metro::SampleRange ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+
+	for( int nSamples = 0; nSamples < 100; ++nSamples ) {
+		Vector const outcome_nonmissingness = Vector::Constant( nSamples, 1.0 ) ;
+		Vector outcome = Vector::Zero( nSamples ) ;
+		for( int i = 1; i < nSamples; i += 2 ) {
+			outcome(i) = 1 ;
+		}
+		
+		std::vector< metro::SampleRange > all_samples ;
+		all_samples.push_back( metro::SampleRange( 0, nSamples )) ;
+	
+		for( int nCovariates = 0; nCovariates < 10; ++nCovariates ) {
+			Matrix const covariates = Matrix::Constant( nSamples, nCovariates, 1001.0 ) ;
+			Matrix const covariate_nonmissingness = Matrix::Constant( nSamples, nCovariates, 1.0 ) ;
+			for( int nPredictors = 0; nPredictors < 10; ++nPredictors ) {
+				Matrix predictor_levels = Matrix::Constant( 1, nPredictors, 5.0 ) ;
+				Matrix predictor_probabilities = Matrix::Constant( nSamples, 1, 1.0 ) ;
+			
+				Design design(
+					outcome, all_samples, std::vector< std::string >( 1, "outcome" ),
+					covariates, all_samples, std::vector< std::string >( nCovariates, "cov" ),
+					std::vector< std::string >( nPredictors, "predictor" )
+				) ;
+			
+				design.set_predictors( predictor_levels, predictor_probabilities, all_samples ) ;
+
+				// check the outcome
+				BOOST_CHECK_EQUAL( design.outcome().rows(), nSamples ) ;
+				for( int i = 0; i < nSamples; ++i ) {
+					BOOST_CHECK_EQUAL( design.outcome()(i,0), ( i % 2 ) ) ;
+				}
+
+				Matrix const& matrix = design.set_predictor_level( 0 ).matrix() ;
+				BOOST_CHECK_EQUAL( matrix.rows(), nSamples ) ;
+				BOOST_CHECK_EQUAL( matrix.cols(), nCovariates + nPredictors + 1 ) ;
+
+				if( nSamples > 0 ) {
+					// check the baseline column
+					BOOST_CHECK_EQUAL( matrix.col(0).maxCoeff(), 1.0 ) ;
+					BOOST_CHECK_EQUAL( matrix.col(0).minCoeff(), 1.0 ) ;
+
+					// check the predictor columns
+					for( int i = 0; i < nPredictors; ++i ) {
+						BOOST_CHECK_EQUAL( matrix.col(i+1).maxCoeff(), 5.0 ) ;
+						BOOST_CHECK_EQUAL( matrix.col(i+1).minCoeff(), 5.0 ) ;
+					}
+
+					// check the covariate columns
+					for( int i = 0; i < nCovariates; ++i ) {
+						BOOST_CHECK_EQUAL( matrix.col(i+1+nPredictors).maxCoeff(), 1001.0 ) ;
+						BOOST_CHECK_EQUAL( matrix.col(i+1+nPredictors).minCoeff(), 1001.0 ) ;
+					}
+				}
+			}
+		}
+	}
+}
+
+AUTO_TEST_CASE( test_predictor_levels ) {
+	using metro::SampleRange ;
+	using metro::regression::Design ;
+	typedef Design::Matrix Matrix ;
+	typedef Design::Vector Vector ;
+
+	int nSamples = 10;
+	int nCovariates = 0 ;
+
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+	SampleRanges const all_samples( 1, metro::SampleRange( 0, nSamples )) ;
+	
+	Vector outcome = Vector::Zero( nSamples ) ;
+	for( int i = 0; i < nSamples; i += 2 ) {
+		outcome(i) = 1 ;
+	}
+	
+	Matrix const covariates = Matrix::Constant( nSamples, nCovariates, 1001.0 ) ;
+
+	for( int nPredictors = 0; nPredictors < 10; ++nPredictors ) {
+		Design design(
+			outcome, all_samples, std::vector< std::string >( 1, "outcome" ),
+			covariates, all_samples, std::vector< std::string >( nCovariates, "cov" ),
+			std::vector< std::string >( nPredictors, "predictor" )
+		) ;
+
+		for( int nPredictorLevels = 0; nPredictorLevels < 10; ++nPredictorLevels ) {
+			Matrix predictor_levels = Matrix::Zero( nPredictorLevels, nPredictors ) ;
+			for( int i = 0; i < nPredictorLevels; ++i ) {
+				for( int j = 0; j < nPredictors; ++j ) {
+					predictor_levels( i, j ) = double( (i+1)*(j+1) ) ;
+				}
+			}
+
+			Matrix predictor_probabilities = Matrix::Constant( nSamples, nPredictorLevels, 1 / double( nPredictorLevels ) ) ;
+			design.set_predictors( predictor_levels, predictor_probabilities, all_samples ) ;
+			
+			for( int iLevel = 0; iLevel < nPredictorLevels; ++iLevel ) {
+				Matrix const& matrix = design.set_predictor_level( iLevel ).matrix() ;
+			
+				if( nSamples > 0 ) {
+					for( int j = 0; j < nPredictors; ++j ) {
+							BOOST_CHECK_EQUAL( matrix.col(j+1).maxCoeff(), double((iLevel+1)*(j+1)) ) ;
+							BOOST_CHECK_EQUAL( matrix.col(j+1).minCoeff(), double((iLevel+1)*(j+1)) ) ;
+					}
+				}
+			}
+		}
+	}
+}
+
+AUTO_TEST_CASE( test_names ) {
+	using metro::SampleRange ;
+	using metro::regression::Design ;
+
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+	int const nSamples = 5 ;
+	SampleRanges const all_samples( 1, metro::SampleRange( 0, nSamples )) ;
+
+	for( int numberOfPredictors = 0; numberOfPredictors < 10; ++numberOfPredictors ) {
+		std::vector< std::string > predictor_names( numberOfPredictors ) ;
+		for( int i = 0; i < numberOfPredictors; ++i ) {
+			predictor_names[i] = ( boost::format( "predictor%d" ) % (i+1) ).str() ;
+		}
+		
+		for( int numberOfCovariates = 0; numberOfCovariates < 10; ++numberOfCovariates ) {
+			Eigen::VectorXd outcome = Eigen::VectorXd::Zero( 5 ) ;
+			Eigen::MatrixXd cov = Eigen::MatrixXd::Constant( 5, numberOfCovariates, 2 ) ;
+
+			std::vector< std::string > cov_names( numberOfCovariates ) ;
+			for( int i = 0; i < numberOfCovariates; ++i ) {
+				cov_names[i] = ( boost::format( "cov%d" ) % (i+1)).str() ;
+				cov.col(i).setConstant( i ) ;
+			}
+		
+			Design design(
+				outcome, all_samples, std::vector< std::string >( 1, "outcome" ),
+				cov, all_samples, cov_names,
+				predictor_names
+			) ;
+			std::vector< std::string > names = design.design_matrix_column_names() ;
+			TEST_ASSERT( names.size() == 1 + numberOfPredictors + numberOfCovariates ) ;
+			TEST_ASSERT( names[0] == "baseline" ) ;
+			for( int i = 0; i < numberOfPredictors; ++i ) {
+				TEST_ASSERT( names[1+i] == predictor_names[i] ) ;
+			}
+			for( int i = 0; i < numberOfCovariates; ++i ) {
+				TEST_ASSERT( names[1+numberOfPredictors+i] == cov_names[i] ) ;
+			}
+			
+#if DEBUG
+			std::cerr << design.get_summary() << "\n" ;
+#endif
+			
+		}
+	}
+}
+
+AUTO_TEST_CASE( test_names_interaction ) {
+	using metro::SampleRange ;
+	using metro::regression::Design ;
+
+	typedef std::vector< metro::SampleRange > SampleRanges ;
+	int const nSamples = 5 ;
+	SampleRanges const all_samples( 1, metro::SampleRange( 0, nSamples )) ;
+
+	for( int numberOfPredictors = 0; numberOfPredictors < 10; ++numberOfPredictors ) {
+		std::vector< std::string > predictor_names( numberOfPredictors ) ;
+		for( int i = 0; i < numberOfPredictors; ++i ) {
+			predictor_names[i] = ( boost::format( "predictor%d" ) % (i+1) ).str() ;
+		}
+		
+		for( int numberOfCovariates = 0; numberOfCovariates < 10; ++numberOfCovariates ) {
+			Eigen::VectorXd outcome = Eigen::VectorXd::Zero( 5 ) ;
+			Eigen::MatrixXd cov = Eigen::MatrixXd::Constant( 5, numberOfCovariates, 2 ) ;
+
+			std::vector< std::string > cov_names( numberOfCovariates ) ;
+			for( int i = 0; i < numberOfCovariates; ++i ) {
+				cov_names[i] = ( boost::format( "cov%d" ) % (i+1)).str() ;
+				cov.col(i).setConstant( i ) ;
+			}
+
+			std::vector< int > interactions ;
+			for( int interaction = 0; interaction < numberOfCovariates; interaction +=2 ) {
+				interactions.push_back( interaction ) ;
+			}
+		
+			Design design(
+				outcome, all_samples, std::vector< std::string >( 1, "outcome" ),
+				cov, all_samples, cov_names,
+				predictor_names,
+				Design::eIdentity,
+				interactions
+			) ;
+
+#if DEBUG
+			std::cerr << design.get_summary() << "\n" ;
+#endif
+
+			std::vector< std::string > names = design.design_matrix_column_names() ;
+			BOOST_CHECK_EQUAL( names.size(), 1 + numberOfPredictors * ( 1 + interactions.size() ) + numberOfCovariates ) ;
+			BOOST_CHECK_EQUAL( names[0], "baseline" ) ;
+			for( int i = 0; i < numberOfPredictors; ++i ) {
+				BOOST_CHECK_EQUAL( names[1+i], predictor_names[i] ) ;
+			}
+			for( int j = 0; j < interactions.size(); ++j ) {
+				for( int i = 0; i < numberOfPredictors; ++i ) {
+					BOOST_CHECK_EQUAL( names[1+((j+1)*numberOfPredictors)+i], predictor_names[i] + "x" + cov_names[interactions[j]] ) ;
+				}
+			}
+			for( int i = 0; i < numberOfCovariates; ++i ) {
+				BOOST_CHECK_EQUAL( names[1+(numberOfPredictors*(1+interactions.size()))+i], cov_names[i] ) ;
+			}
+			
+			
+		}
+	}
+}
+
+BOOST_AUTO_TEST_SUITE_END()

Index: metro/wscript
==================================================================
--- metro/wscript
+++ metro/wscript
@@ -1,36 +1,25 @@
-import os.path
-import glob
-#import UnitTest
-
-def configure( conf ):
+def configure( cfg ):
 	pass
 
-def create_tests( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'metro boost boost-unit_test_framework',
-		uselib = 'BOOST_UNIT_TEST_FRAMEWORK',
+def build( bld ):
+	bld.stlib(
+		target = 'metro',
+		source = (
+			bld.path.ant_glob( 'src/*.cpp' ) +
+			bld.path.ant_glob( 'src/regression/*.cpp' ) +
+			bld.path.ant_glob( 'src/distributions/*.cpp') +
+			bld.path.ant_glob( 'src/concurrency/*.cpp')
+		),
+		use = 'eigen boost genfile',
+		includes='./include',
+		export_includes = './include'
+	)
+
+	bld.program(
+		target = 'test_metro',
+		source = bld.path.ant_glob( 'test/*.cpp' ),
+		use = 'boost boost_unit_test_framework metro',
 		includes='./include',
 		unit_test=1,
 		install_path = None
 	)
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld(
-		features = 'cxx cstaticlib',
-		target = 'metro',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib_local='eigen boost',
-		uselib = 'BOOST',
-		export_incdirs = './include'
-	)
-
-	create_tests( bld, 'test_metro' )

Index: qcdb/include/qcdb/DBOutputter.hpp
==================================================================
--- qcdb/include/qcdb/DBOutputter.hpp
+++ qcdb/include/qcdb/DBOutputter.hpp
@@ -16,137 +16,138 @@
 #include <boost/tuple/tuple.hpp>
 #include <boost/unordered_map.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/CohortIndividualSource.hpp"
 #include "genfile/VariantEntry.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "qcdb/StorageOptions.hpp"
 
 namespace qcdb {
 	struct DBOutputter {
+
+	private:
+		typedef StorageOptions Flags ;
+
+	public:
 		typedef std::auto_ptr< DBOutputter > UniquePtr ;
 		typedef boost::shared_ptr< DBOutputter > SharedPtr ;
 		typedef std::map< std::string, std::pair< std::vector< std::string >, std::string > > Metadata ;
 
 		static UniquePtr create(
 			std::string const& filename,
 			std::string const& analysis_name,
 			std::string const& analysis_description,
 			Metadata const& metadata,
-			boost::optional< db::Connection::RowId > analysis_id = boost::optional< db::Connection::RowId >(),
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >(),
 			std::string const& snp_match_fields = "position,alleles"
 		) ;
 		static SharedPtr create_shared(
 			std::string const& filename,
 			std::string const& analysis_name,
 			std::string const& analysis_description,
 			Metadata const& metadata,
-			boost::optional< db::Connection::RowId > analysis_id = boost::optional< db::Connection::RowId >(),
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >(),
 			std::string const& snp_match_fields = "position,alleles"
 		) ;
 
 		DBOutputter(
 			std::string const& filename,
 			std::string const& analysis_name,
 			std::string const& analysis_description,
 			Metadata const& metadata,
-			boost::optional< db::Connection::RowId > analysis_id = boost::optional< db::Connection::RowId >(),
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >(),
 			std::string const& snp_match_fields = "position,alleles"
 		) ;
 		~DBOutputter() ;
+
+		// Specify that variant additional identifiers should not be stored
+		void set_record_nonprimary_identifiers( bool value ) ;
+		// Turn on or off recording of variant identifiers additional to those given
+		// the first time the variant is seen.
+		void set_record_alternative_identifiers( bool value ) ;
+		// Specify whether or not variants should be linked (i.e. all variants will be newly created,
+		// regardless of what is in the Variants table).
+		void set_link_variants( bool value ) ;
 
 		// Create a new variable associated with the current analysis
 		void create_variable( std::string const& table, std::string const& name ) const ;
-#if 0
-		// Create an entity.  Optionally supply a class (which must be the id of another entity.)
-		db::Connection::RowId get_or_create_entity(
-			std::string const& name,
-			std::string const& description,
-			boost::optional< db::Connection::RowId > class_id = boost::optional< db::Connection::RowId >()
-		) const ;
-
-		// Associate some data with an entity.
-		db::Connection::RowId get_or_create_entity_data( db::Connection::RowId const entity_id, db::Connection::RowId const variable_id, genfile::VariantEntry const& value ) const ;
-		// Create a variant
-#endif
-		db::Connection::RowId get_or_create_variant( genfile::VariantIdentifyingData const& snp ) const ;
+
+		// Retrieve, or create a new variant
+		genfile::db::Connection::RowId get_or_create_variant( genfile::VariantIdentifyingData const& snp ) const ;
+
 		// Store some data for a variant.
-		void insert_summary_data( db::Connection::RowId snp_id, db::Connection::RowId variable_id, genfile::VariantEntry const& value ) const ;
+		void insert_summary_data( genfile::db::Connection::RowId snp_id, genfile::db::Connection::RowId variable_id, genfile::VariantEntry const& value ) const ;
+
+		// The db connection
+		genfile::db::Connection& connection() const { return *m_connection ; }
 
-		db::Connection& connection() const { return *m_connection ; }
-		db::Connection::RowId analysis_id() const { return m_analysis_id.get() ; }
+		// The analysis_id for this object
+		genfile::db::Connection::RowId analysis_id() const { return m_analysis_id.get() ; }
 
+		// Finalise the analysis by ensuring any remaining data is written
+		// and the indices are created, if necessary.
 		void finalise( long options = eCreateIndices ) ;
 		
 	private:
-		db::Connection::UniquePtr m_connection ;
+		genfile::db::Connection::UniquePtr m_connection ;
 		std::string const m_analysis_name ;
 		std::string const m_analysis_chunk ;
 		Metadata const m_metadata ;
 		bool const m_create_indices ;
 		bool const m_match_rsid ;
-
-
-		db::Connection::StatementPtr m_insert_variable_statement ;
-
-		db::Connection::StatementPtr m_find_entity_statement ;
-		db::Connection::StatementPtr m_find_entity_data_statement ;
-		db::Connection::StatementPtr m_insert_entity_statement ;
-		db::Connection::StatementPtr m_insert_entity_data_statement ;
-
-		db::Connection::StatementPtr m_insert_analysis_statement ;
-		db::Connection::StatementPtr m_find_analysis_statement ;
-		db::Connection::StatementPtr m_insert_analysis_property_statement ;
-
-		db::Connection::StatementPtr m_insert_entity_relationship_statement ;
-
-		db::Connection::StatementPtr m_find_variant_statement ;
-		db::Connection::StatementPtr m_insert_variant_statement ;
-		db::Connection::StatementPtr m_find_variant_identifier_statement ;
-		db::Connection::StatementPtr m_insert_variant_identifier_statement ;
-
-		boost::optional< db::Connection::RowId > m_analysis_id ;
-		db::Connection::RowId m_is_a ;
-		db::Connection::RowId m_used_by ;
-
-		typedef boost::unordered_map< std::pair< std::string, std::string >, db::Connection::RowId > EntityMap ;
+		uint32_t m_flags ;
+
+		genfile::db::Connection::StatementPtr m_insert_variable_statement ;
+
+		genfile::db::Connection::StatementPtr m_find_entity_statement ;
+		genfile::db::Connection::StatementPtr m_find_entity_data_statement ;
+		genfile::db::Connection::StatementPtr m_insert_entity_statement ;
+		genfile::db::Connection::StatementPtr m_insert_entity_data_statement ;
+
+		genfile::db::Connection::StatementPtr m_insert_analysis_statement ;
+		genfile::db::Connection::StatementPtr m_find_analysis_statement ;
+		genfile::db::Connection::StatementPtr m_insert_analysis_property_statement ;
+
+		genfile::db::Connection::StatementPtr m_insert_entity_relationship_statement ;
+
+		genfile::db::Connection::StatementPtr m_find_variant_statement ;
+		genfile::db::Connection::StatementPtr m_insert_variant_statement ;
+		genfile::db::Connection::StatementPtr m_find_variant_identifier_statement ;
+		genfile::db::Connection::StatementPtr m_insert_variant_identifier_statement ;
+
+		boost::optional< genfile::db::Connection::RowId > m_analysis_id ;
+		genfile::db::Connection::RowId m_is_a ;
+		genfile::db::Connection::RowId m_used_by ;
+
+		typedef boost::unordered_map< std::pair< std::string, std::string >, genfile::db::Connection::RowId > EntityMap ;
 		mutable EntityMap m_entity_map ;
 	private:
 		void construct_statements() ;
 		void store_metadata() ;
 
-#if 0
-		void load_entities() ;
-		void create_entity_relationship( db::Connection::RowId entity1_id, db::Connection::RowId relationship_id, db::Connection::RowId entity2_id ) const ;
-#endif
-		db::Connection::RowId create_analysis(
+		void create_analysis(
+			genfile::db::Connection::RowId id, 
+			std::string const& name,
+			std::string const& description
+		) const ;
+
+		genfile::db::Connection::RowId create_analysis(
 			std::string const& name,
 			std::string const& description
 		) const ;
-		db::Connection::RowId set_analysis_property(
-			db::Connection::RowId const analysis_id,
+
+		genfile::db::Connection::RowId set_analysis_property(
+			genfile::db::Connection::RowId const analysis_id,
 			std::string const& property,
 			genfile::VariantEntry const& value,
 			std::string const& aux
 		) const ;
 
-#if 0
-		db::Connection::RowId get_or_create_entity_internal(
-			std::string const& name,
-			std::string const& description,
-			boost::optional< db::Connection::RowId > class_id = boost::optional< db::Connection::RowId >()
-		) const ;
-		db::Connection::RowId create_entity_internal(
-			std::string const& name,
-			std::string const& description,
-			boost::optional< db::Connection::RowId > class_id = boost::optional< db::Connection::RowId >()
-		) const ;
-#endif
-		void start_analysis( db::Connection::RowId const ) const ;
-		void end_analysis( db::Connection::RowId const ) const ;
-		void add_alternative_variant_identifier( db::Connection::RowId const variant_id, std::string const& identifier, std::string const& rsid ) const ;
-		void add_variant_identifier( db::Connection::RowId const variant_id, std::string const& identifier ) const ;
+		void start_analysis( genfile::db::Connection::RowId const ) const ;
+		void end_analysis( genfile::db::Connection::RowId const ) const ;
+		void add_alternative_variant_identifier( genfile::db::Connection::RowId const variant_id, std::string const& identifier, std::string const& rsid ) const ;
+		void add_variant_identifier( genfile::db::Connection::RowId const variant_id, std::string const& identifier ) const ;
 	} ;
 }
 
 #endif

ADDED   qcdb/include/qcdb/FlatFileMultiVariantOutputter.hpp
Index: qcdb/include/qcdb/FlatFileMultiVariantOutputter.hpp
==================================================================
--- qcdb/include/qcdb/FlatFileMultiVariantOutputter.hpp
+++ qcdb/include/qcdb/FlatFileMultiVariantOutputter.hpp
@@ -0,0 +1,77 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef QCTOOL_QCDB_FLAT_FILE_MULTIVARIANT_OUTPUTTER_HPP
+#define QCTOOL_QCDB_FLAT_FILE_MULTIVARIANT_OUTPUTTER_HPP
+
+#include <string>
+#include <memory>
+#include <map>
+#include <vector>
+#include <utility>
+#include <boost/bimap.hpp>
+#include "genfile/VariantEntry.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "statfile/BuiltInTypeStatSink.hpp"
+#include "qcdb/StorageOptions.hpp"
+#include "qcdb/MultiVariantStorage.hpp"
+
+namespace qcdb {
+	struct FlatFileMultiVariantOutputter: public MultiVariantStorage {
+	public:
+		typedef std::map< std::string, std::pair< std::vector< std::string >, std::string > > Metadata ;
+		typedef std::auto_ptr< FlatFileMultiVariantOutputter > UniquePtr ;
+		static UniquePtr create(
+			std::string const& filename,
+			std::size_t const number_of_key_entries,
+			std::string const& analysis_name,
+			Metadata const& metadata
+		) ;
+
+	public:
+		FlatFileMultiVariantOutputter(
+			std::string const& filename,
+			std::size_t const number_of_key_entries,
+			std::string const& analysis_name,
+			Metadata const& metadata
+		) ;
+		~FlatFileMultiVariantOutputter() ;
+
+		void set_variant_names( std::vector< std::string > const& names ) ;
+		void add_variable( std::string const& ) ;
+
+		void create_new_key( Key const& key ) ;
+		void store_data_for_key(
+			Key const& key,
+			std::string const& value_name,
+			genfile::VariantEntry const& value
+		) ;
+
+		void finalise( long options = eCreateIndices ) ;
+
+		AnalysisId analysis_id() const ;
+
+	private:
+		std::string const m_filename ;
+		std::vector< std::string > m_key_entry_names ;
+		std::string const m_analysis_name ;
+		Metadata const m_metadata ;
+		std::size_t const m_max_keys_per_block ;
+		statfile::BuiltInTypeStatSink::UniquePtr m_sink ;
+		std::vector< Key > m_keys ;
+		typedef boost::bimap< std::string, std::size_t > VariableMap ;
+		VariableMap m_variables ;
+		typedef std::map< std::pair< std::size_t, std::size_t >, genfile::VariantEntry > ValueMap ;
+		ValueMap m_values ;
+	
+	private:
+		void store_block() ;
+		std::string format_metadata() const ;
+		void create_columns() ;
+	} ;
+}
+
+#endif

Index: qcdb/include/qcdb/FlatTableDBOutputter.hpp
==================================================================
--- qcdb/include/qcdb/FlatTableDBOutputter.hpp
+++ qcdb/include/qcdb/FlatTableDBOutputter.hpp
@@ -13,40 +13,51 @@
 #include <boost/tuple/tuple.hpp>
 #include <boost/bimap.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/CohortIndividualSource.hpp"
 #include "genfile/VariantEntry.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "qcdb/DBOutputter.hpp"
 #include "qcdb/Storage.hpp"
 
 namespace qcdb {
 	struct FlatTableDBOutputter: public Storage {
 		typedef std::auto_ptr< FlatTableDBOutputter > UniquePtr ;
 		typedef boost::shared_ptr< FlatTableDBOutputter > SharedPtr ;
 		typedef DBOutputter::Metadata Metadata ;
 		static UniquePtr create(
-			std::string const& filename, std::string const& cohort_name, std::string const& analysis_description, Metadata const& metadata,
-			std::string const& snp_match_fields = "position,alleles"
+			std::string const& filename,
+			std::string const& cohort_name,
+			std::string const& analysis_description,
+			Metadata const& metadata,
+			std::string const& snp_match_fields = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >()
 		 ) ;
 		static SharedPtr create_shared(
-			std::string const& filename, std::string const& cohort_name, std::string const& analysis_description, Metadata const& metadata,
-			std::string const& snp_match_fields = "position,alleles"
+			std::string const& filename,
+			std::string const& cohort_name,
+			std::string const& analysis_description,
+			Metadata const& metadata,
+			std::string const& snp_match_fields = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >()
 		) ;
 
 		FlatTableDBOutputter(
 			std::string const& filename,
 			std::string const& analysis_name,
 			std::string const& analysis_description,
 			Metadata const& metadata,
-			std::string const& snp_match_fields = "position,alleles"
+			std::string const& snp_match_fields = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >()
 		) ;
 
 		~FlatTableDBOutputter() ;
 
 		void set_table_name( std::string const& table_name ) ;
+		void set_link_variants( bool value ) { m_outputter.set_link_variants( value ) ; }
+		void set_record_nonprimary_identifiers( bool value ) { m_outputter.set_record_nonprimary_identifiers( value ) ; }
 		
 		void add_variable(
 			std::string const& 
 		) ;
 		
@@ -63,11 +74,11 @@
 
 	private:
 		DBOutputter m_outputter ;
 		std::string m_table_name ;
 		std::size_t const m_max_snps_per_block ;
-		db::Connection::StatementPtr m_insert_data_sql ;
+		genfile::db::Connection::StatementPtr m_insert_data_sql ;
 		std::vector< genfile::VariantIdentifyingData > m_snps ;
 		typedef boost::bimap< std::string, std::size_t > VariableMap ;
 		VariableMap m_variables ;
 		typedef std::map< std::pair< std::size_t, std::size_t >, genfile::VariantEntry > ValueMap ;
 		ValueMap m_values ;
@@ -77,13 +88,13 @@
 		void store_block() ;
 		void create_schema() ;
 		void store_data_for_variant(
 			std::size_t const,
 			genfile::VariantIdentifyingData const& snp,
-			db::Connection::RowId const,
-			db::Connection::RowId const
+			genfile::db::Connection::RowId const,
+			genfile::db::Connection::RowId const
 		) ;
 		void create_variables() ;
 	} ;
 }
 
 #endif

ADDED   qcdb/include/qcdb/FlatTableMultiVariantDBOutputter.hpp
Index: qcdb/include/qcdb/FlatTableMultiVariantDBOutputter.hpp
==================================================================
--- qcdb/include/qcdb/FlatTableMultiVariantDBOutputter.hpp
+++ qcdb/include/qcdb/FlatTableMultiVariantDBOutputter.hpp
@@ -0,0 +1,95 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef QCTOOL_QCDB_FLAT_TABLE_MULTI_VARIANT_OUTPUTTER_HPP
+#define QCTOOL_QCDB_FLAT_TABLE_MULTI_VARIANT_OUTPUTTER_HPP
+
+#include <string>
+#include <memory>
+#include <boost/shared_ptr.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/bimap.hpp>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/CohortIndividualSource.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+#include "qcdb/MultiVariantStorage.hpp"
+#include "qcdb/DBOutputter.hpp"
+
+namespace qcdb {
+	struct FlatTableMultiVariantDBOutputter: public MultiVariantStorage {
+		typedef std::auto_ptr< FlatTableMultiVariantDBOutputter > UniquePtr ;
+		typedef boost::shared_ptr< FlatTableMultiVariantDBOutputter > SharedPtr ;
+		typedef MultiVariantStorage::Metadata Metadata ;
+		typedef MultiVariantStorage::AnalysisId AnalysisId ;
+		typedef std::vector< genfile::VariantIdentifyingData > Key ;
+			
+		static UniquePtr create(
+			std::string const& filename,
+			std::size_t const number_of_key_fields,
+			std::string const& analysis_name,
+			std::string const& analysis_description,
+			Metadata const& metadata,
+			std::string const& snp_match_fields = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >()
+		) ;
+
+		FlatTableMultiVariantDBOutputter(
+			std::string const& filename,
+			std::size_t number_of_key_fields,
+			std::string const& analysis_name,
+			std::string const& analysis_description,
+			Metadata const& metadata,
+			std::string const& snp_match_fields = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >()
+		) ;
+
+		~FlatTableMultiVariantDBOutputter() ;
+
+		void set_table_name( std::string const& table_name ) ;
+		void set_without_rowid() ;
+
+		void set_variant_names( std::vector< std::string > const& names ) ;
+		void add_variable( std::string const& ) ;
+
+		void create_new_key( Key const& key ) ;
+
+		void store_data_for_key(
+			Key const& key,
+			std::string const& variable,
+			genfile::VariantEntry const& value
+		) ;
+		
+		void finalise( long options = qcdb::eCreateIndices ) ;
+
+		AnalysisId analysis_id() const ;
+
+	private:
+		qcdb::DBOutputter m_outputter ;
+		std::vector< std::string > m_key_entry_names ;
+		std::string m_table_name ;
+		bool m_without_rowid ;
+		std::size_t const m_max_variants_per_block ;
+		genfile::db::Connection::StatementPtr m_insert_data_sql ;
+		std::vector< Key > m_keys ;
+		typedef boost::bimap< std::string, std::size_t > VariableMap ;
+		VariableMap m_variables ;
+		typedef std::map< std::pair< std::size_t, std::size_t >, genfile::VariantEntry > ValueMap ;
+		ValueMap m_values ;
+
+	private:
+		std::string get_table_name() const ;
+		void store_block() ;
+		void create_schema() ;
+		void store_data_for_variants(
+			std::size_t const key_i,
+			genfile::db::Connection::RowId const analysis_id,
+			std::vector< genfile::db::Connection::RowId > const& variant_ids
+		) ;
+	} ;
+}
+#endif

ADDED   qcdb/include/qcdb/MultiFileOutputter.hpp
Index: qcdb/include/qcdb/MultiFileOutputter.hpp
==================================================================
--- qcdb/include/qcdb/MultiFileOutputter.hpp
+++ qcdb/include/qcdb/MultiFileOutputter.hpp
@@ -0,0 +1,70 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef QCTOOL_QCDB_FLAT_FILE_OUTPUTTER_HPP
+#define QCTOOL_QCDB_FLAT_FILE_OUTPUTTER_HPP
+
+#include <string>
+#include <memory>
+#include <map>
+#include <vector>
+#include <utility>
+#include <boost/bimap.hpp>
+#include "genfile/VariantEntry.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "statfile/BuiltInTypeStatSink.hpp"
+#include "qcdb/MultiTableStorage.hpp"
+#include "qcdb/StorageOptions.hpp"
+
+namespace qcdb {
+	struct MultiFileOutputter: public MultiTableStorage {
+		typedef std::map< std::string, std::pair< std::vector< std::string >, std::string > > Metadata ;
+		static UniquePtr create( std::string const& filename, std::string const& analysis_name, Metadata const& metadata ) ;
+		static SharedPtr create_shared( std::string const& filename, std::string const& analysis_name, Metadata const& metadata ) ;
+
+		MultiFileOutputter( std::string const& filename, std::string const& analysis_name, Metadata const& metadata ) ;
+		~MultiFileOutputter() ;
+
+		void add_table( std::string const&, boost::function< bool( std::string const& ) > ) ;
+		void add_meta_table(
+			std::string const& tableName,
+			std::string const& rowName,
+			std::size_t number_of_columns,
+			boost::function< std::string ( std::size_t ) > getColumnName,
+			boost::function< genfile::VariantEntry( std::size_t ) > getColumnValue
+		) ;
+		void add_variable( std::string const& variable, std::string const& type ) ;
+
+		void create_new_variant( genfile::VariantIdentifyingData const& ) ;
+		void store_per_variant_data(
+			genfile::VariantIdentifyingData const& snp,
+			std::string const& value_name,
+			genfile::VariantEntry const& value
+		) ;
+
+		void finalise( long options = eCreateIndices ) ;
+
+		AnalysisId analysis_id() const ;
+	private:
+		std::string const m_filename ;
+		std::string const m_analysis_name ;
+		Metadata const m_metadata ;
+		std::vector< std::string > m_metatables ;
+		std::size_t const m_max_snps_per_block ;
+		statfile::BuiltInTypeStatSink::UniquePtr m_sink ;
+		std::vector< genfile::VariantIdentifyingData > m_snps ;
+		typedef boost::bimap< std::string, std::size_t > VariableMap ;
+		VariableMap m_variables ;
+		typedef std::map< std::pair< std::size_t, std::size_t >, genfile::VariantEntry > ValueMap ;
+		ValueMap m_values ;
+	
+	private:
+		void store_block() ;
+		std::string format_metadata() const ;
+	} ;
+}
+
+#endif

ADDED   qcdb/include/qcdb/MultiTableDBOutputter.hpp
Index: qcdb/include/qcdb/MultiTableDBOutputter.hpp
==================================================================
--- qcdb/include/qcdb/MultiTableDBOutputter.hpp
+++ qcdb/include/qcdb/MultiTableDBOutputter.hpp
@@ -0,0 +1,112 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef QCTOOL_QCDB_MULTI_TABLE_DB_OUTPUTTER_HPP
+#define QCTOOL_QCDB_MULTI_TABLE_DB_OUTPUTTER_HPP
+
+#include <string>
+#include <memory>
+#include <boost/shared_ptr.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/bimap.hpp>
+#include <boost/ptr_container/ptr_vector.hpp>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/CohortIndividualSource.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+#include "qcdb/DBOutputter.hpp"
+#include "qcdb/MultiTableStorage.hpp"
+
+namespace qcdb {
+	struct MultiTableDBOutputter: public MultiTableStorage {
+		typedef std::auto_ptr< MultiTableDBOutputter > UniquePtr ;
+		typedef boost::shared_ptr< MultiTableDBOutputter > SharedPtr ;
+		typedef DBOutputter::Metadata Metadata ;
+		static UniquePtr create(
+			std::string const& filename,
+			std::string const& cohort_name,
+			std::string const& analysis_description,
+			Metadata const& metadata,
+			std::string const& snp_match_fields = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > = boost::optional< genfile::db::Connection::RowId >()
+		 ) ;
+		static SharedPtr create_shared(
+			std::string const& filename,
+			std::string const& cohort_name,
+			std::string const& analysis_description,
+			Metadata const& metadata,
+			std::string const& snp_match_fields = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >()
+		) ;
+
+		MultiTableDBOutputter(
+			std::string const& filename,
+			std::string const& analysis_name,
+			std::string const& analysis_description,
+			Metadata const& metadata,
+			std::string const& snp_match_fields = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > = boost::optional< genfile::db::Connection::RowId >()
+		) ;
+
+		~MultiTableDBOutputter() ;
+
+		void add_table( std::string const&, boost::function< bool( std::string const& ) > ) ;
+		void add_meta_table(
+			std::string const& tableName,
+			std::string const& rowName,
+			std::size_t number_of_columns,
+			boost::function< std::string ( std::size_t ) > getColumnName,
+			boost::function< genfile::VariantEntry( std::size_t ) > getColumnValue
+		) ;
+		void set_record_alternative_identifiers( bool value ) ;
+		void add_variable(
+			std::string const& variable,
+			std::string const& type
+		) ;
+		
+		void create_new_variant( genfile::VariantIdentifyingData const& ) ;
+		void store_per_variant_data(
+			genfile::VariantIdentifyingData const& snp,
+			std::string const& variable,
+			genfile::VariantEntry const& value
+		) ;
+		
+		void finalise( long options = eCreateIndices ) ;
+
+		AnalysisId analysis_id() const ;
+
+	private:
+		DBOutputter m_outputter ;
+		std::vector< std::string > m_table_names ;
+		boost::ptr_vector< genfile::db::SQLStatement > m_insert_data_sql ;
+		typedef boost::function< bool( std::string const& ) > ColumnSelector ;
+		std::vector< ColumnSelector > m_column_selectors ;
+
+		std::size_t const m_max_snps_per_block ;
+		//genfile::db::Connection::StatementPtr m_insert_data_sql ;
+		std::vector< genfile::VariantIdentifyingData > m_snps ;
+		typedef boost::bimap< std::string, std::pair< std::size_t, std::string > > VariableMap ;
+		VariableMap m_variables ;
+		typedef std::map< std::pair< std::size_t, std::size_t >, genfile::VariantEntry > ValueMap ;
+		ValueMap m_values ;
+		std::vector< std::map< std::string, std::size_t > > m_column_maps ;
+		
+	private:
+		std::vector< std::string > const& get_table_names() const ;
+		void store_block() ;
+		void create_schema() ;
+		void store_data_for_variant(
+			std::size_t const,
+			genfile::VariantIdentifyingData const& snp,
+			genfile::db::Connection::RowId const,
+			genfile::db::Connection::RowId const
+		) ;
+		void create_variables() ;
+	} ;
+}
+
+#endif

ADDED   qcdb/include/qcdb/MultiTableStorage.hpp
Index: qcdb/include/qcdb/MultiTableStorage.hpp
==================================================================
--- qcdb/include/qcdb/MultiTableStorage.hpp
+++ qcdb/include/qcdb/MultiTableStorage.hpp
@@ -0,0 +1,52 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef QCTOOL_QCDB_MULTITABLESTORAGE_HPP
+#define QCTOOL_QCDB_MULTITABLESTORAGE_HPP
+
+#include <stdint.h>
+#include <boost/noncopyable.hpp>
+#include <boost/shared_ptr.hpp>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "qcdb/StorageOptions.hpp"
+
+namespace qcdb {
+	struct MultiTableStorage {
+		typedef std::auto_ptr< MultiTableStorage > UniquePtr ;
+		typedef boost::shared_ptr< MultiTableStorage > SharedPtr ;
+		
+		virtual ~MultiTableStorage() {} ;
+
+		virtual void add_table( std::string const&, boost::function< bool( std::string const& ) > ) = 0 ;
+		virtual void add_meta_table(
+			std::string const& tableName,
+			std::string const& rowName,
+			std::size_t number_of_columns,
+			boost::function< std::string ( std::size_t ) > getColumnName,
+			boost::function< genfile::VariantEntry( std::size_t ) > getColumnValue
+		) = 0 ;
+
+		virtual void add_variable(
+			std::string const& variable,
+			std::string const& type
+		) = 0 ;
+
+		virtual void create_new_variant( genfile::VariantIdentifyingData const& ) = 0 ;
+		virtual void store_per_variant_data(
+			genfile::VariantIdentifyingData const& snp,
+			std::string const& variable,
+			genfile::VariantEntry const& value
+		) = 0 ;
+		
+		virtual void finalise( long options = eCreateIndices ) {} ;
+		
+		typedef int64_t AnalysisId ;
+		virtual AnalysisId analysis_id() const = 0 ;
+	} ;
+}
+
+#endif
+

ADDED   qcdb/include/qcdb/MultiVariantStorage.hpp
Index: qcdb/include/qcdb/MultiVariantStorage.hpp
==================================================================
--- qcdb/include/qcdb/MultiVariantStorage.hpp
+++ qcdb/include/qcdb/MultiVariantStorage.hpp
@@ -0,0 +1,61 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef QCTOOL_QCDB_MULTIVARIANT_STORAGE_HPP
+#define QCTOOL_QCDB_MULTIVARIANT_STORAGE_HPP
+
+#include <string>
+#include <memory>
+#include <map>
+#include <stdint.h>
+#include <boost/shared_ptr.hpp>
+#include <boost/shared_ptr.hpp>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "qcdb/StorageOptions.hpp"
+#include "qcdb/Storage.hpp"
+#include "qcdb/DBOutputter.hpp"
+
+namespace qcdb {
+	struct MultiVariantStorage {
+		typedef std::auto_ptr< MultiVariantStorage > UniquePtr ;
+		typedef Storage::Metadata Metadata ;
+		typedef Storage::AnalysisId AnalysisId ;
+		typedef std::vector< genfile::VariantIdentifyingData > Key ;
+		
+		static UniquePtr create(
+			std::string const& filename,
+			std::size_t const number_of_key_fields,
+			std::string const& analysis_name,
+			std::string const& analysis_chunk,
+			Metadata const& metadata,
+			std::string const& compare_by = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >()
+		) ;
+		
+		virtual ~MultiVariantStorage() {} ;
+
+		virtual void set_variant_names( std::vector< std::string > const& names ) = 0 ;
+
+		virtual void add_variable(
+			std::string const& 
+		) = 0 ;
+		virtual void create_new_key(
+			Key const& key
+		) = 0 ;
+		virtual void store_data_for_key(
+			Key const& key,
+			std::string const& variable,
+			genfile::VariantEntry const& value
+		) = 0 ;
+		
+		virtual void finalise( long options = eCreateIndices ) {} ;
+		
+		virtual AnalysisId analysis_id() const = 0 ;
+	} ;
+}
+
+#endif
+

Index: qcdb/include/qcdb/Storage.hpp
==================================================================
--- qcdb/include/qcdb/Storage.hpp
+++ qcdb/include/qcdb/Storage.hpp
@@ -5,20 +5,36 @@
 //          http://www.boost.org/LICENSE_1_0.txt)
 
 #ifndef QCTOOL_QCDB_STORAGE_HPP
 #define QCTOOL_QCDB_STORAGE_HPP
 
+#include <string>
+#include <memory>
+#include <map>
 #include <stdint.h>
-#include <boost/noncopyable.hpp>
+#include <boost/shared_ptr.hpp>
 #include <boost/shared_ptr.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "qcdb/StorageOptions.hpp"
+#include "qcdb/DBOutputter.hpp"
 
 namespace qcdb {
 	struct Storage {
 		typedef std::auto_ptr< Storage > UniquePtr ;
 		typedef boost::shared_ptr< Storage > SharedPtr ;
+		typedef std::map< std::string, std::pair< std::vector< std::string >, std::string > > Metadata ;
+
+		static std::vector< std::string > parse_filespec( std::string spec ) ;
+
+		static UniquePtr create(
+			std::string const& filename,
+			std::string const& analysis_name,
+			std::string const& analysis_chunk,
+			Metadata const& metadata,
+			std::string const& compare_by = "position,alleles",
+			boost::optional< genfile::db::Connection::RowId > analysis_id = boost::optional< genfile::db::Connection::RowId >()
+		) ;
 		
 		virtual ~Storage() {} ;
 
 		virtual void add_variable(
 			std::string const& 

Index: qcdb/include/qcdb/StorageOptions.hpp
==================================================================
--- qcdb/include/qcdb/StorageOptions.hpp
+++ qcdb/include/qcdb/StorageOptions.hpp
@@ -6,10 +6,10 @@
 
 #ifndef QCTOOL_QCDB_STORAGE_OPTIONS_HPP
 #define QCTOOL_QCDB_STORAGE_OPTIONS_HPP
 
 namespace qcdb {
-	enum StorageOptions { eCreateIndices = 1 } ;
+	enum StorageOptions { eCreateIndices = 1, eIncludeAllIdentifiers = 2, eLinkVariants = 4, eAltIdentifiers = 8 } ;
 }
 
 #endif
 

Index: qcdb/src/DBOutputter.cpp
==================================================================
--- qcdb/src/DBOutputter.cpp
+++ qcdb/src/DBOutputter.cpp
@@ -11,12 +11,12 @@
 #include <boost/tuple/tuple.hpp>
 #include <boost/thread/thread.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/Error.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "appcontext/get_current_time_as_string.hpp"
 #include "qcdb/DBOutputter.hpp"
 
 namespace qcdb {
 	namespace impl {
@@ -64,21 +64,21 @@
 	DBOutputter::UniquePtr DBOutputter::create(
 		std::string const& filename,
 		std::string const& analysis_name,
 		std::string const& analysis_description,
 		Metadata const& metadata,
-		boost::optional< db::Connection::RowId > analysis_id,
+		boost::optional< genfile::db::Connection::RowId > analysis_id,
 		std::string const& snp_match_fields
 	) {
 		return UniquePtr( new DBOutputter( filename, analysis_name, analysis_description, metadata, analysis_id, snp_match_fields ) ) ;
 	}
 	DBOutputter::SharedPtr DBOutputter::create_shared(
 		std::string const& filename,
 		std::string const& analysis_name,
 		std::string const& analysis_description,
 		Metadata const& metadata,
-		boost::optional< db::Connection::RowId > analysis_id,
+		boost::optional< genfile::db::Connection::RowId > analysis_id,
 		std::string const& snp_match_fields
 	) {
 		return SharedPtr( new DBOutputter( filename, analysis_name, analysis_description, metadata, analysis_id, snp_match_fields ) ) ;
 	}
 
@@ -87,37 +87,39 @@
 	DBOutputter::DBOutputter(
 		std::string const& filename,
 		std::string const& analysis_name,
 		std::string const& analysis_description,
 		Metadata const& metadata,
-		boost::optional< db::Connection::RowId > analysis_id,
+		boost::optional< genfile::db::Connection::RowId > analysis_id,
 		std::string const& snp_match_fields
 	):
-		m_connection( db::Connection::create( filename )),
+		m_connection( genfile::db::Connection::create( filename )),
 		m_analysis_name( analysis_name ),
 		m_analysis_chunk( analysis_description ),
 		m_metadata( metadata ),
 		m_create_indices( true ),
 		m_match_rsid( impl::get_match_rsid( snp_match_fields )),
+		m_flags( eLinkVariants | eAltIdentifiers ),
 		m_analysis_id( analysis_id )
 	{
 		try {
 			m_connection->run_statement( "PRAGMA journal_mode = OFF" ) ;
 			m_connection->run_statement( "PRAGMA synchronous = OFF" ) ;
 		}
-		catch( db::Error const& ) {
+		catch( genfile::db::Error const& ) {
 			std::cerr << "qcdb::DBOutputter::DBOutputter(): unable to set PRAGMA synchronous=OFF, is another connection using this database?" ;
 		}
 
-		db::Connection::ScopedTransactionPtr transaction = m_connection->open_transaction( 7200 ) ;
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_connection->open_transaction( 7200 ) ;
 
 		m_connection->run_statement(
 			"CREATE TABLE IF NOT EXISTS Variant ( id INTEGER PRIMARY KEY, rsid TEXT, chromosome TEXT, position INTEGER, alleleA TEXT, alleleB TEXT )"
 		) ;
 		m_connection->run_statement(
 			"CREATE INDEX IF NOT EXISTS Variant_position_index ON Variant( chromosome, position )"
 		) ;
+
 		m_connection->run_statement(
 			"CREATE TABLE IF NOT EXISTS VariantIdentifier ( variant_id INTEGER NOT NULL, identifier TEXT, FOREIGN KEY( variant_id ) REFERENCES Variant( id ) ) "
 		) ;
 		m_connection->run_statement(
 			"CREATE INDEX IF NOT EXISTS VariantIdentifierIdentifierIndex ON VariantIdentifier( identifier )"
@@ -182,19 +184,19 @@
 		store_metadata() ;
 	}
 
 	void DBOutputter::finalise( long options ) {
 		if( options & eCreateIndices ) {
-			db::Connection::ScopedTransactionPtr transaction = m_connection->open_transaction( 7200 ) ;
+			genfile::db::Connection::ScopedTransactionPtr transaction = m_connection->open_transaction( 7200 ) ;
 			m_connection->run_statement(
 				"CREATE INDEX IF NOT EXISTS Variant_rsid_index ON Variant( rsid )"
 			) ;
 			m_connection->run_statement(
 				"CREATE INDEX IF NOT EXISTS VariantIdentifierVariantIndex ON VariantIdentifier( variant_id )"
 			) ;
 		}
-		db::Connection::ScopedTransactionPtr transaction = m_connection->open_transaction( 7200 ) ;
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_connection->open_transaction( 7200 ) ;
 		end_analysis( m_analysis_id.get() ) ;
 	}
 
 	void DBOutputter::construct_statements() {
 		m_insert_variable_statement = m_connection->get_statement( "INSERT INTO Variable ( analysis_id, `table`, `name`, `description` ) VALUES( ?, ?, ?, ? )" ) ;
@@ -219,37 +221,56 @@
 	}
 
 	void DBOutputter::store_metadata() {
 		try {
 			if( m_analysis_id ) {
-				m_find_analysis_statement
-					->bind( 1, m_analysis_name )
-					.bind( 2, m_analysis_chunk )
-					.step() ;
-				if( m_find_analysis_statement->empty() ) {
-					throw genfile::BadArgumentError(
-						"qcdb::DBOutputter::store_metadata()",
-						"m_analysis_id=" + genfile::string_utils::to_string( m_analysis_id.get() ),
-						"Could not find an analysis with the given name and chunk."
-					) ;
-				}
-				db::Connection::RowId const id = m_find_analysis_statement->get< db::Connection::RowId >( 0 ) ;
-				if( id != m_analysis_id.get() ) {
-					throw genfile::BadArgumentError(
-						"qcdb::DBOutputter::store_metadata()",
-						"m_analysis_id=" + genfile::string_utils::to_string( m_analysis_id.get() ),
-						"id does not match the analysis with with the given name and chunk."
-					) ;
-				}
-				m_find_analysis_statement->reset() ;
+				genfile::db::Connection::StatementPtr find_analysis_stmt = m_connection->get_statement(
+					"SELECT name, chunk FROM Analysis WHERE id == ?1"
+				) ;
+				find_analysis_stmt
+					->bind( 1, m_analysis_id.get() )
+					.step() ;
+
+				if( find_analysis_stmt->empty() ) {
+					create_analysis(
+						m_analysis_id.get(),
+						m_analysis_name,
+						m_analysis_chunk
+					) ;
+				} else {
+					std::string const existing_analysis_name = find_analysis_stmt->get_column< std::string >(0) ;
+					std::string const existing_analysis_chunk = find_analysis_stmt->get_column< std::string >(1) ;
+					if( existing_analysis_name != m_analysis_name ) {
+						throw genfile::BadArgumentError(
+							"qcdb::DBOutputter::store_metadata()",
+							"m_analysis_id=" + genfile::string_utils::to_string( m_analysis_id.get() ),
+							"Existing analysis has mismatching name (\""
+							+ existing_analysis_name
+							+ "\", exopected \""
+							+ m_analysis_name
+							+ "\")"
+						) ;
+					}
+					if( existing_analysis_chunk != m_analysis_chunk) {
+						throw genfile::BadArgumentError(
+							"qcdb::DBOutputter::store_metadata()",
+							"m_analysis_id=" + genfile::string_utils::to_string( m_analysis_id.get() ),
+							"Existing analysis has mismatching chunk (\""
+							+ existing_analysis_chunk
+							+ "\", exopected \""
+							+ m_analysis_chunk
+							+ "\")"
+						) ;
+					}
+				}
 			} else {
 				m_analysis_id = create_analysis(
 					m_analysis_name,
 					m_analysis_chunk
 				) ;
 			}
-		} catch( db::StatementStepError const& e ) {
+		} catch( genfile::db::StatementStepError const& e ) {
 			throw genfile::BadArgumentError( "qcdb::DBOutputter::store_metadata()", "analysis_name=\"" + m_analysis_name + "\"", "An analysis with name \"" + m_analysis_name + "\" and chunk \"" + m_analysis_chunk + "\" already exists" ) ;
 		}
 
 		start_analysis( m_analysis_id.get() ) ;
 
@@ -270,70 +291,51 @@
 			.bind( 3, name )
 			.step() ;
 		m_insert_variable_statement->reset() ;
 	}
 	
-	void DBOutputter::start_analysis( db::Connection::RowId const analysis_id ) const {
-		db::Connection::StatementPtr stmnt = m_connection->get_statement( "INSERT INTO AnalysisStatus( analysis_id, started, status ) VALUES( ?, ?, ? )" ) ;
+	void DBOutputter::set_record_nonprimary_identifiers( bool value ) {
+		m_flags = ( value ? (m_flags | eAltIdentifiers) : (m_flags & (~eAltIdentifiers))) ;
+	}
+
+	void DBOutputter::set_record_alternative_identifiers( bool value ) {
+		m_flags = ( value ? (m_flags | eIncludeAllIdentifiers) : (m_flags & (~eIncludeAllIdentifiers))) ;
+	}
+
+	void DBOutputter::set_link_variants( bool value ) {
+		m_flags = ( value ? (m_flags | eLinkVariants) : (m_flags & (~eLinkVariants))) ;
+	}
+
+	void DBOutputter::start_analysis( genfile::db::Connection::RowId const analysis_id ) const {
+		genfile::db::Connection::StatementPtr stmnt = m_connection->get_statement( "INSERT INTO AnalysisStatus( analysis_id, started, status ) VALUES( ?, ?, ? )" ) ;
 		stmnt->bind( 1, analysis_id ) ;
 		stmnt->bind( 2, appcontext::get_current_time_as_string() ) ;
 		stmnt->bind( 3, "incomplete" ) ;
 		stmnt->step() ;
 	}
 
-	void DBOutputter::end_analysis( db::Connection::RowId const analysis_id ) const {
-		db::Connection::StatementPtr stmnt = m_connection->get_statement( "UPDATE AnalysisStatus SET completed = ?, status = ? WHERE analysis_id == ?" ) ;
+	void DBOutputter::end_analysis( genfile::db::Connection::RowId const analysis_id ) const {
+		genfile::db::Connection::StatementPtr stmnt = m_connection->get_statement( "UPDATE AnalysisStatus SET completed = ?, status = ? WHERE analysis_id == ?" ) ;
 		stmnt->bind( 1, appcontext::get_current_time_as_string() ) ;
 		stmnt->bind( 2, "success" ) ;
 		stmnt->bind( 3, analysis_id ) ;
 		stmnt->step() ;
 	}
 
-#if 0	
-	db::Connection::RowId DBOutputter::get_or_create_entity_internal( std::string const& name, std::string const& description, boost::optional< db::Connection::RowId > class_id ) const {
-		db::Connection::RowId result ;
-		// Look in our variable cache first
-		EntityMap::const_iterator where = m_entity_map.find( std::make_pair( name, description )) ;
-		if( where != m_entity_map.end() ) {
-			result = where->second ;
-		}
-		else {
-			// try the db nex
-			m_find_entity_statement
-				->bind( 1, name )
-				.bind( 2, description )
-				.step() ;
-			if( m_find_entity_statement->empty() ) {
-				result = create_entity_internal( name, description, class_id ) ;
-			} else {
-				result = m_find_entity_statement->get< db::Connection::RowId >( 0 ) ;
-			}
-			m_find_entity_statement->reset() ;
-		}
-		return result ;
-	}
-	
-	db::Connection::RowId DBOutputter::create_entity_internal( std::string const& name, std::string const& description, boost::optional< db::Connection::RowId > class_id ) const {
-		db::Connection::RowId result ;
-		m_insert_entity_statement
-			->bind( 1, name )
-			.bind( 2, description )
-			.step() ;
-			
-		result = m_connection->get_last_insert_row_id() ;
-		m_entity_map.insert( std::make_pair( std::make_pair( name, description ), result ) ) ;
-		m_insert_entity_statement->reset() ;
-
-		if( class_id ) {
-			create_entity_relationship( result, m_is_a, *class_id ) ;
-		}
-		return result ;
-	}
-
-#endif
-	db::Connection::RowId DBOutputter::create_analysis( std::string const& name, std::string const& description ) const {
-		db::Connection::RowId result ;
+	void DBOutputter::create_analysis( genfile::db::Connection::RowId id, std::string const& name, std::string const& chunk ) const {
+		genfile::db::Connection::StatementPtr insert_analysis_stmt = m_connection->get_statement(
+			"INSERT INTO Analysis( id, name, chunk ) VALUES ( ?, ?, ? )"
+		) ;
+		insert_analysis_stmt
+			->bind( 1, id )
+			.bind( 2, name )
+			.bind( 3, chunk )
+			.step() ;
+	}
+
+	genfile::db::Connection::RowId DBOutputter::create_analysis( std::string const& name, std::string const& description ) const {
+		genfile::db::Connection::RowId result ;
 		m_insert_analysis_statement
 			->bind( 1, name )
 			.bind( 2, description )
 			.step() ;
 			
@@ -341,73 +343,17 @@
 		m_insert_analysis_statement->reset() ;
 
 		return result ;
 	}
 
-#if 0
-	db::Connection::RowId DBOutputter::get_or_create_entity( std::string const& name, std::string const& description, boost::optional< db::Connection::RowId > class_id ) const {
-		db::Connection::RowId result ;
-		EntityMap::const_iterator where = m_entity_map.find( std::make_pair( name, description )) ;
-		if( where != m_entity_map.end() ) {
-			result = where->second ;
-		}
-		else {
-			m_find_entity_statement
-				->bind( 1, name )
-				.bind( 2, description )
-				.step() ;
-			if( m_find_entity_statement->empty() ) {
-				result = create_entity_internal( name, description, class_id ) ;
-				create_entity_relationship( result, m_used_by, m_analysis_id.get() ) ;
-			} else {
-				result = m_find_entity_statement->get< db::Connection::RowId >( 0 ) ;
-			}
-			m_find_entity_statement->reset() ;
-		}
-		return result ;
-	}
-
-	void DBOutputter::create_entity_relationship( db::Connection::RowId entity1_id, db::Connection::RowId relationship_id, db::Connection::RowId entity2_id ) const {
-		m_insert_entity_relationship_statement
-			->bind( 1, entity1_id )
-			.bind( 2, relationship_id )
-			.bind( 3, entity2_id )
-			.step() ;
-			
-		m_insert_entity_relationship_statement->reset() ;
-	}
-
-	db::Connection::RowId DBOutputter::get_or_create_entity_data( db::Connection::RowId const entity_id, db::Connection::RowId const variable_id, genfile::VariantEntry const& value ) const {
-		db::Connection::RowId result ;
-
-		m_find_entity_data_statement
-			->bind( 1, entity_id )
-			.bind( 2, variable_id ).step() ;
-
-		if( m_find_entity_data_statement->empty() ) {
-			m_insert_entity_data_statement
-				->bind( 1, entity_id )
-				.bind( 2, variable_id )
-				.bind( 3, value )
-				.step() ;
-			result = m_connection->get_last_insert_row_id() ;
-			m_insert_entity_data_statement->reset() ;
-		} else {
-			result = m_find_entity_data_statement->get< db::Connection::RowId >( 0 ) ;
-		}
-		m_find_entity_data_statement->reset() ;
-		return result ;
-	}
-#endif
-
-	db::Connection::RowId DBOutputter::set_analysis_property(
-		db::Connection::RowId const analysis_id,
+	genfile::db::Connection::RowId DBOutputter::set_analysis_property(
+		genfile::db::Connection::RowId const analysis_id,
 		std::string const& property,
 		genfile::VariantEntry const& value,
 		std::string const& aux
 	) const {
-		db::Connection::RowId result ;
+		genfile::db::Connection::RowId result ;
 
 		m_insert_analysis_property_statement
 			->bind( 1, analysis_id )
 			.bind( 2, property )
 			.bind( 3, value )
@@ -416,17 +362,21 @@
 		result = m_connection->get_last_insert_row_id() ;
 		m_insert_analysis_property_statement->reset() ;
 		return result ;
 	}
 
-	void DBOutputter::add_alternative_variant_identifier( db::Connection::RowId const variant_id, std::string const& identifier, std::string const& rsid ) const {
+	void DBOutputter::add_alternative_variant_identifier(
+		genfile::db::Connection::RowId const variant_id,
+		std::string const& identifier,
+		std::string const& rsid
+	) const {
 		if( identifier != rsid  && identifier != "---" && identifier != "." ) {
 			add_variant_identifier( variant_id, identifier ) ;
 		}
 	}
 
-	void DBOutputter::add_variant_identifier( db::Connection::RowId const variant_id, std::string const& identifier ) const {
+	void DBOutputter::add_variant_identifier( genfile::db::Connection::RowId const variant_id, std::string const& identifier ) const {
 		m_find_variant_identifier_statement
 			->bind( 1, variant_id )
 			.bind( 2, identifier )
 			.step() ;
 		if( m_find_variant_identifier_statement->empty() ) {
@@ -437,28 +387,32 @@
 			m_insert_variant_identifier_statement->reset() ;
 		}
 		m_find_variant_identifier_statement->reset() ;
 	}
 
-	db::Connection::RowId DBOutputter::get_or_create_variant( genfile::VariantIdentifyingData const& snp ) const {
-		db::Connection::RowId result ;
-		if( snp.get_position().chromosome().is_missing() ) {
-			m_find_variant_statement->bind_NULL( 1 ) ;
-		} else {
-			m_find_variant_statement
-				->bind( 1, std::string( snp.get_position().chromosome() ) ) ;
-		}
-		m_find_variant_statement
-			->bind( 2, snp.get_position().position() )
-			.bind( 3, snp.get_allele(0) )
-			.bind( 4, snp.get_allele(1) ) ;
-		if( m_match_rsid ) {
-			m_find_variant_statement->bind( 5, snp.get_primary_id() ) ;
-		}
-		m_find_variant_statement->step() ;
-
-		if( m_find_variant_statement->empty() ) {
+	genfile::db::Connection::RowId DBOutputter::get_or_create_variant( genfile::VariantIdentifyingData const& snp ) const {
+		genfile::db::Connection::RowId result ;
+		
+		bool createNewVariant = !(m_flags & eLinkVariants) ;
+		if( !createNewVariant ) {
+			if( snp.get_position().chromosome().is_missing() ) {
+				m_find_variant_statement->bind_NULL( 1 ) ;
+			} else {
+				m_find_variant_statement
+					->bind( 1, std::string( snp.get_position().chromosome() ) ) ;
+			}
+			m_find_variant_statement
+				->bind( 2, snp.get_position().position() )
+				.bind( 3, snp.get_allele(0) )
+				.bind( 4, snp.get_allele(1) ) ;
+			if( m_match_rsid ) {
+				m_find_variant_statement->bind( 5, snp.get_primary_id() ) ;
+			}
+			m_find_variant_statement->step() ;
+			createNewVariant = m_find_variant_statement->empty() ;
+		}
+		if( createNewVariant ) {
 			if( snp.get_position().chromosome().is_missing() ) {
 				m_insert_variant_statement
 					->bind_NULL( 2 ) ;
 			} else {
 				m_insert_variant_statement
@@ -473,22 +427,24 @@
 				.step()
 			;
 
 			result = connection().get_last_insert_row_id() ;
 			m_insert_variant_statement->reset() ;
-			snp.get_identifiers(
-				boost::bind(
-					&DBOutputter::add_alternative_variant_identifier,
-					this,
-					result,
-					_1,
-					snp.get_primary_id()
-				),
-				1
-			) ;
+			if( m_flags & eAltIdentifiers ) {
+				snp.get_identifiers(
+					boost::bind(
+						&DBOutputter::add_alternative_variant_identifier,
+						this,
+						result,
+						_1,
+						snp.get_primary_id()
+					),
+					1
+				) ;
+			}
 		} else {
-			result = m_find_variant_statement->get< db::Connection::RowId >( 0 ) ;
+			result = m_find_variant_statement->get< genfile::db::Connection::RowId >( 0 ) ;
 			std::string const rsid = m_find_variant_statement->get< std::string >( 1 ) ;
 			add_alternative_variant_identifier( result, snp.get_primary_id(), rsid ) ;
 			snp.get_identifiers(
 				boost::bind(
 					&DBOutputter::add_alternative_variant_identifier,

ADDED   qcdb/src/FlatFileMultiVariantOutputter.cpp
Index: qcdb/src/FlatFileMultiVariantOutputter.cpp
==================================================================
--- qcdb/src/FlatFileMultiVariantOutputter.cpp
+++ qcdb/src/FlatFileMultiVariantOutputter.cpp
@@ -0,0 +1,216 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <memory>
+#include <boost/bimap.hpp>
+#include <boost/bind.hpp>
+#include <boost/format.hpp>
+#include "genfile/VariantEntry.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/string_utils.hpp"
+#include "statfile/BuiltInTypeStatSink.hpp"
+#include "appcontext/get_current_time_as_string.hpp"
+#include "qcdb/Storage.hpp"
+#include "qcdb/FlatFileMultiVariantOutputter.hpp"
+
+namespace qcdb {
+	namespace {
+		void append_to_string( std::string* target, std::string const& value ) {
+			(*target) += ( target->size() > 0 ? "," : "" ) + value ;
+		}
+
+		std::vector< std::string > generate_key_entry_names( std::size_t n ) {
+			std::vector< std::string > result(n) ;
+			for( std::size_t i = 0; i < n; ++i ) {
+				result[i] = (boost::format( "variant%d" ) % (i+1)).str() ;
+			}
+			return result ;
+		}
+	}
+
+	FlatFileMultiVariantOutputter::UniquePtr FlatFileMultiVariantOutputter::create(
+		std::string const& filename,
+		std::size_t const number_of_key_entries,
+		std::string const& analysis_name,
+		Metadata const& metadata
+	) {
+		return UniquePtr( new FlatFileMultiVariantOutputter( filename, number_of_key_entries, analysis_name, metadata ) ) ;
+	}
+
+	FlatFileMultiVariantOutputter::FlatFileMultiVariantOutputter(
+		std::string const& filename,
+		std::size_t const number_of_key_entries,
+		std::string const& analysis_name,
+		Metadata const& metadata
+	):
+		m_filename( filename ),
+		m_key_entry_names( generate_key_entry_names(number_of_key_entries) ),
+		m_analysis_name( analysis_name ),
+		m_metadata( metadata ),
+		m_max_keys_per_block( 1000 )
+	{
+		m_keys.reserve( 1000 ) ;
+	}
+	
+	FlatFileMultiVariantOutputter::~FlatFileMultiVariantOutputter() {
+	}
+	
+	void FlatFileMultiVariantOutputter::finalise( long ) {
+		store_block() ;
+		m_keys.clear() ;
+		m_values.clear() ;
+		m_sink->write_comment( "Completed successfully at " + appcontext::get_current_time_as_string() ) ;
+	}
+
+	FlatFileMultiVariantOutputter::AnalysisId FlatFileMultiVariantOutputter::analysis_id() const {
+		// A flat file only ever has one analysis.
+		return 0 ;
+	}
+
+	void FlatFileMultiVariantOutputter::set_variant_names( std::vector< std::string > const& names ) {
+		// Ensure we don't change names if we have already written data
+		if( m_sink.get() && names != m_key_entry_names ) {
+			throw genfile::BadArgumentError( "qcdb::FlatFileMultiVariantOutputter::set_variant_names()", "names" ) ;
+		}
+		m_key_entry_names = names ;
+	}
+
+	void FlatFileMultiVariantOutputter::add_variable(
+		std::string const& variable
+	) {
+		VariableMap::left_const_iterator where = m_variables.left.find( variable ) ;
+		if( where == m_variables.left.end() ) {
+			if( m_sink.get() ) {
+				// Uh-oh, have already written a header.
+				throw genfile::BadArgumentError( "qcdb::FlatFileMultiVariantOutputter::add_variable()", "variable=\"" + variable + "\"" ) ;
+			}
+			else {
+				// Still have time to add the variable to our list of variables, retaining the order of addition.
+				where = m_variables.left.insert( VariableMap::left_value_type( variable, m_variables.size() ) ).first ;
+			}
+		}
+	}
+
+	void FlatFileMultiVariantOutputter::create_new_key( MultiVariantStorage::Key const& key ) {
+		if( m_keys.size() == m_max_keys_per_block ) {
+			store_block() ;
+			m_keys.clear() ;
+			m_values.clear() ;
+		}
+		m_keys.push_back( key ) ;
+	}
+
+	void FlatFileMultiVariantOutputter::store_data_for_key(
+		MultiVariantStorage::Key const& key,
+		std::string const& variable,
+		genfile::VariantEntry const& value
+	) {
+		assert( key.size() <= m_key_entry_names.size() ) ;
+		bool const new_key = m_keys.empty() || key != m_keys.back() ;
+		if( new_key ) {
+			// If we have a whole block's worth of data, store it now.
+			if( m_keys.size() == m_max_keys_per_block ) {
+				store_block() ;
+				m_keys.clear() ;
+				m_values.clear() ;
+			}
+			m_keys.push_back( key ) ;
+		}
+
+		VariableMap::left_const_iterator where = m_variables.left.find( variable ) ;
+		if( where == m_variables.left.end() ) {
+			if( m_sink.get() ) {
+				// Uh-oh, have already written a header.
+				throw genfile::BadArgumentError( "qcdb::FlatFileMultiVariantOutputter::store_per_variant_data()", "variable=\"" + variable + "\"" ) ;
+			}
+			else {
+				// Still have time to add the variable to our list of variables, retaining the order of addition.
+				where = m_variables.left.insert( VariableMap::left_value_type( variable, m_variables.size() ) ).first ;
+			}
+		}
+
+		// Store the value of this variable.
+		m_values[ std::make_pair( m_keys.size() - 1, where->second ) ] = value ;
+	}
+	
+	void FlatFileMultiVariantOutputter::store_block() {
+		if( !m_sink.get() ) {
+			m_sink = statfile::BuiltInTypeStatSink::open( m_filename ) ;
+			m_sink->write_metadata( format_metadata() ) ;
+			create_columns() ;
+		}
+		for( std::size_t key_i = 0; key_i < m_keys.size(); ++key_i ) {
+			// output key
+			Key const& key = m_keys[ key_i ] ;
+			for( std::size_t i = 0; i < key.size(); ++i ) {
+				genfile::VariantIdentifyingData const& variant = key[i] ;
+				std::string SNPID ;
+				if( variant.number_of_identifiers() == 1 ) {
+					SNPID = "NA" ;
+				} else {
+					variant.get_identifiers( boost::bind( &append_to_string, &SNPID, _1 ), 1 ) ;
+				}
+				(*m_sink) << SNPID << variant.get_primary_id() << variant.get_position().chromosome()
+				<< variant.get_position().position()
+				<< variant.get_allele(0)
+				<< (( variant.number_of_alleles() < 2 ) ? "." : variant.get_alleles_as_string( ",", 1, variant.number_of_alleles() )) ;
+			}
+			genfile::MissingValue const NA ;
+			for( std::size_t i = key.size(); i < m_key_entry_names.size(); ++i ) {
+				(*m_sink)
+					<< NA << NA << NA
+					<< NA << NA << NA ;
+			}
+
+			// output variables
+			VariableMap::right_const_iterator
+				var_i = m_variables.right.begin(),
+				end_var_i = m_variables.right.end() ;
+			for( ; var_i != end_var_i; ++var_i ) {
+				ValueMap::const_iterator where = m_values.find( std::make_pair( key_i, var_i->first )) ;
+				if( where == m_values.end() ) {
+					(*m_sink) << genfile::MissingValue() ;
+				}
+				else {
+					(*m_sink) << where->second ;
+				}
+			}
+			(*m_sink) << statfile::end_row() ;
+		}
+	}
+	
+	std::string FlatFileMultiVariantOutputter::format_metadata() const {
+		std::ostringstream str ;
+		str << "Analysis: \"" << m_analysis_name << "\"\n"
+			<< " started: " << appcontext::get_current_time_as_string() << "\n" ;
+		str << "\nAnalysis properties:\n" ;
+		for( Metadata::const_iterator i = m_metadata.begin(); i != m_metadata.end(); ++i ) {
+			str << "  "
+				<< i->first
+				<< " "
+				<< genfile::string_utils::join( i->second.first, " " )
+				<< " (" + i->second.second + ")\n" ;
+		}
+		return str.str() ;
+	}
+	
+	void FlatFileMultiVariantOutputter::create_columns() {
+		using genfile::string_utils::to_string ;
+		for( std::size_t i = 0; i < m_key_entry_names.size(); ++i ) {
+			std::string const& stub = m_key_entry_names[i] ;
+			(*m_sink) | (stub+":alternate_ids") | (stub+":rsid") | (stub+":chromosome") | (stub+":position") | (stub+":alleleA") | (stub+":alleleB") ;
+		}
+		VariableMap::right_const_iterator
+			i = m_variables.right.begin(),
+			end_i = m_variables.right.end() ;
+		for( ; i != end_i; ++i ) {
+			(*m_sink).add_column( i->second ) ;
+		}
+		(*m_sink) << statfile::begin_data() ;
+	}
+}

Index: qcdb/src/FlatTableDBOutputter.cpp
==================================================================
--- qcdb/src/FlatTableDBOutputter.cpp
+++ qcdb/src/FlatTableDBOutputter.cpp
@@ -10,41 +10,49 @@
 #include <boost/tuple/tuple.hpp>
 #include <boost/thread/thread.hpp>
 #include "genfile/VariantIdentifyingData.hpp"
 #include "genfile/VariantEntry.hpp"
 #include "genfile/Error.hpp"
-#include "db/Connection.hpp"
-#include "db/SQLStatement.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
 #include "appcontext/get_current_time_as_string.hpp"
 #include "qcdb/FlatTableDBOutputter.hpp"
 
 // #define DEBUG_FLATTABLEDBOUTPUTTER 1
 
 namespace qcdb {
 	FlatTableDBOutputter::UniquePtr FlatTableDBOutputter::create(
-		std::string const& filename, std::string const& analysis_name, std::string const& analysis_description, Metadata const& metadata,
-		std::string const& snp_match_fields
+		std::string const& filename,
+		std::string const& analysis_name,
+		std::string const& analysis_description,
+		Metadata const& metadata,
+		std::string const& snp_match_fields,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
 	) {
-		return UniquePtr( new FlatTableDBOutputter( filename, analysis_name, analysis_description, metadata, snp_match_fields ) ) ;
+		return UniquePtr( new FlatTableDBOutputter( filename, analysis_name, analysis_description, metadata, snp_match_fields, analysis_id ) ) ;
 	}
 
 	FlatTableDBOutputter::SharedPtr FlatTableDBOutputter::create_shared(
-		std::string const& filename, std::string const& analysis_name, std::string const& analysis_description, Metadata const& metadata,
-		std::string const& snp_match_fields
+		std::string const& filename,
+		std::string const& analysis_name,
+		std::string const& analysis_description,
+		Metadata const& metadata,
+		std::string const& snp_match_fields,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
 	) {
-		return SharedPtr( new FlatTableDBOutputter( filename, analysis_name, analysis_description, metadata, snp_match_fields ) ) ;
+		return SharedPtr( new FlatTableDBOutputter( filename, analysis_name, analysis_description, metadata, snp_match_fields, analysis_id ) ) ;
 	}
 
 	FlatTableDBOutputter::FlatTableDBOutputter(
 		std::string const& filename,
 		std::string const& analysis_name,
 		std::string const& analysis_description,
 		Metadata const& metadata,
-		std::string const& snp_match_fields
-		
+		std::string const& snp_match_fields,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
 	):
-		m_outputter( filename, analysis_name, analysis_description, metadata, boost::optional< db::Connection::RowId >(), snp_match_fields ),
+		m_outputter( filename, analysis_name, analysis_description, metadata, analysis_id, snp_match_fields ),
 		m_table_name( "Analysis" + genfile::string_utils::to_string( m_outputter.analysis_id() ) ),
 		m_max_snps_per_block( 1000 )
 	{}
 
 	FlatTableDBOutputter::~FlatTableDBOutputter() {
@@ -65,11 +73,11 @@
 		store_block() ;
 		m_snps.clear() ;
 		m_values.clear() ;
 
 		if( options & eCreateIndices ) {
-			db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
+			genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
 			m_outputter.connection().run_statement( "CREATE INDEX IF NOT EXISTS " + m_table_name + "_index ON " + m_table_name + "( variant_id )" ) ;
 		}
 
 		m_outputter.finalise( options ) ;
 	}
@@ -130,18 +138,18 @@
 		// Store the value of this variable
 		m_values[ std::make_pair( m_snps.size() - 1, where->second ) ] = value ;
 	}
 
 	void FlatTableDBOutputter::store_block() {
-		db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
 
 		if( !m_insert_data_sql.get() ) {
 			create_schema() ;
 			create_variables() ;
 		}
 		for( std::size_t i = 0; i < m_snps.size(); ++i ) {
-			db::Connection::RowId const variant_id = m_outputter.get_or_create_variant( m_snps[i] ) ;
+			genfile::db::Connection::RowId const variant_id = m_outputter.get_or_create_variant( m_snps[i] ) ;
 			store_data_for_variant( i, m_snps[i], m_outputter.analysis_id(), variant_id ) ;
 		}
 	}
 
 	std::string FlatTableDBOutputter::get_table_name() const {
@@ -157,19 +165,19 @@
 		std::ostringstream insert_data_sql_values ;
 		std::string const& table_name = m_table_name ;
 		schema_sql << "CREATE TABLE IF NOT EXISTS "
 			<< table_name
 			<< " ( "
-			"analysis_id INT NOT NULL REFERENCES Entity( id ), "
-			"variant_id INT NOT NULL REFERENCES Variant( id ), "
-			"chromosome TEXT, "
-			"position INTEGER"
+			"`analysis_id` INT NOT NULL REFERENCES Entity( id ), "
+			"`variant_id` INT NOT NULL REFERENCES Variant( id ), "
+			"`chromosome` TEXT, "
+			"`position` INTEGER"
 		;
 		
 		insert_data_sql << "INSERT INTO "
 			<< table_name ;
-		insert_data_sql_columns << "( analysis_id, variant_id, chromosome, position" ;
+		insert_data_sql_columns << "( `analysis_id`, `variant_id`, `chromosome`, `position`" ;
 		insert_data_sql_values << "VALUES( ?1, ?2, ?3, ?4" ;
 		
 		VariableMap::right_const_iterator
 			var_i = m_variables.right.begin(),
 			end_var_i = m_variables.right.end() ;
@@ -177,16 +185,16 @@
 		for( std::size_t bind_i = 5; var_i != end_var_i; ++var_i, ++bind_i ) {
 			schema_sql << ", " ;
 			insert_data_sql_columns << ", " ;
 			insert_data_sql_values << ", " ;
 			schema_sql
-				<< '"'
+				<< '`'
 				<< var_i->second
-				<< '"'
+				<< '`'
 				<< " NULL" ;
 				
-			insert_data_sql_columns << '"' << var_i->second << '"' ;
+			insert_data_sql_columns << '`' << var_i->second << '`' ;
 			insert_data_sql_values << "?" << to_string( bind_i ) ;
 		}
 
 		schema_sql << " ) ; " ;
 
@@ -222,10 +230,13 @@
 #endif
 		
 		m_insert_data_sql = m_outputter.connection().get_statement(
 			insert_data_sql.str()
 		) ;
+#if DEBUG_FLATTABLEDBOUTPUTTER
+		std::cerr << "Schema created.\n" ;
+#endif
 	}
 
 	void FlatTableDBOutputter::create_variables() {
 		VariableMap::right_const_iterator
 			var_i = m_variables.right.begin(),
@@ -236,12 +247,12 @@
 	}
 	
 	void FlatTableDBOutputter::store_data_for_variant(
 		std::size_t const snp_i,
 		genfile::VariantIdentifyingData const& snp,
-		db::Connection::RowId const analysis_id,
-		db::Connection::RowId const variant_id
+		genfile::db::Connection::RowId const analysis_id,
+		genfile::db::Connection::RowId const variant_id
 	) {
 		m_insert_data_sql->bind( 1, analysis_id ) ;
 		m_insert_data_sql->bind( 2, variant_id ) ;
 		m_insert_data_sql->bind( 3, std::string( snp.get_position().chromosome() ) ) ;
 		m_insert_data_sql->bind( 4, snp.get_position().position() ) ;

ADDED   qcdb/src/FlatTableMultiVariantDBOutputter.cpp
Index: qcdb/src/FlatTableMultiVariantDBOutputter.cpp
==================================================================
--- qcdb/src/FlatTableMultiVariantDBOutputter.cpp
+++ qcdb/src/FlatTableMultiVariantDBOutputter.cpp
@@ -0,0 +1,341 @@
+
+//			Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//	  (See accompanying file LICENSE_1_0.txt or copy at
+//			http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <memory>
+#include <boost/shared_ptr.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/thread/thread.hpp>
+#include <boost/format.hpp>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+#include "appcontext/get_current_time_as_string.hpp"
+#include "qcdb/FlatTableMultiVariantDBOutputter.hpp"
+
+// #define DEBUG_FLATTABLEDBOUTPUTTER 1
+
+namespace qcdb {
+	namespace {
+		std::vector< std::string > generate_key_entry_names( std::size_t n ) {
+			std::vector< std::string > result(n) ;
+			for( std::size_t i = 0; i < n; ++i ) {
+				result[i] = (boost::format( "variant%d" ) % (i+1)).str() ;
+			}
+			return result ;
+		}
+	}
+
+	FlatTableMultiVariantDBOutputter::UniquePtr FlatTableMultiVariantDBOutputter::create(
+		std::string const& filename,
+		std::size_t number_of_key_fields,
+		std::string const& analysis_name,
+		std::string const& analysis_description,
+		Metadata const& metadata,
+		std::string const& snp_match_fields,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
+	) {
+		return UniquePtr(
+			new FlatTableMultiVariantDBOutputter( filename, number_of_key_fields, analysis_name, analysis_description, metadata, snp_match_fields, analysis_id )
+		) ;
+	}
+
+	FlatTableMultiVariantDBOutputter::FlatTableMultiVariantDBOutputter(
+		std::string const& filename,
+		std::size_t number_of_key_fields,
+		std::string const& analysis_name,
+		std::string const& analysis_description,
+		Metadata const& metadata,
+		std::string const& snp_match_fields,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
+	):
+		m_outputter( filename, analysis_name, analysis_description, metadata, analysis_id, snp_match_fields ),
+		m_key_entry_names( generate_key_entry_names( number_of_key_fields )),
+		m_table_name( "analysis" + genfile::string_utils::to_string( m_outputter.analysis_id() ) ),
+		m_without_rowid( false ),
+		m_max_variants_per_block( 1000 )
+	{}
+
+	FlatTableMultiVariantDBOutputter::~FlatTableMultiVariantDBOutputter() {
+	}
+	
+	void FlatTableMultiVariantDBOutputter::set_table_name( std::string const& table_name ) {
+		if( table_name.find_first_not_of( "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789_" ) != std::string::npos ) {
+			throw genfile::BadArgumentError( "qcdb::FlatTableMultiVariantDBOutputter::set_table_name()", "table_name=\"" + table_name + "\"" ) ;
+		}
+		m_table_name = table_name ;
+	}
+
+	void FlatTableMultiVariantDBOutputter::set_without_rowid() {
+		m_without_rowid = true ;
+	}
+
+	FlatTableMultiVariantDBOutputter::AnalysisId FlatTableMultiVariantDBOutputter::analysis_id() const {
+		return m_outputter.analysis_id() ;
+	}
+
+	void FlatTableMultiVariantDBOutputter::finalise( long options ) {
+		store_block() ;
+		m_keys.clear() ;
+		m_values.clear() ;
+
+		if( (options & qcdb::eCreateIndices) && (!m_without_rowid) && (m_key_entry_names.size() > 0) ) {
+			genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
+			std::string sql = "CREATE INDEX IF NOT EXISTS " + m_table_name + "_index ON `" + m_table_name + "` (";
+			for( std::size_t i = 0; i < m_key_entry_names.size(); ++i ) {
+				sql += (i>0 ? ", `" : " `" ) + (m_key_entry_names[i] + "_id`" ) ;
+			}
+			sql += ")" ;
+			m_outputter.connection().run_statement( sql ) ;
+		}
+
+		m_outputter.finalise( options ) ;
+	}
+
+	void FlatTableMultiVariantDBOutputter::set_variant_names( std::vector< std::string > const& names ) {
+		// Ensure we don't change names once we have begun writing data
+		if( names != m_key_entry_names && m_insert_data_sql.get() ) {
+			throw genfile::BadArgumentError(
+				"qcdb::FlatTableMultiVariantDBOutputter::set_variant_names()",
+				"names",
+				"Can't change table column names because data has already been written."
+			) ;
+		}
+		m_key_entry_names = names ;
+	}
+
+	void FlatTableMultiVariantDBOutputter::add_variable( std::string const& variable ) {
+		VariableMap::left_const_iterator where = m_variables.left.find( variable ) ;
+		if( where == m_variables.left.end() ) {
+			if( m_insert_data_sql.get() ) {
+				// Uh-oh, table columns are already fixed.
+				// TODO: alter to put this data in SummaryData table?
+				throw genfile::BadArgumentError( "qcdb::FlatTableMultiVariantDBOutputter::add_variable()", "variable=\"" + variable + "\"" ) ;
+			}
+			else {
+				// Still have time to add the variable to our list of variables, retaining the order of addition.
+				m_variables.left.insert( VariableMap::left_value_type( variable, m_variables.size() ) ) ;
+			}
+		}
+	}
+
+	void FlatTableMultiVariantDBOutputter::create_new_key(
+		Key const& key
+	 ) {
+		if( key.size() > m_key_entry_names.size() ) {
+			throw genfile::BadArgumentError(
+				"qcdb::FlatTableMultiVariantDBOutputter::create_new_key()",
+				"key",
+				(
+					boost::format(
+						"number of fields is larger than expected (%d, expected at most %d)"
+					) % key.size() % m_key_entry_names.size()
+				).str()
+			) ;
+		}
+ 		if( m_keys.size() == m_max_variants_per_block ) {
+ 			store_block() ;
+ 			m_keys.clear() ;
+ 			m_values.clear() ;
+ 		}
+		m_keys.push_back( key ) ;
+	}
+
+	void FlatTableMultiVariantDBOutputter::store_data_for_key(
+		Key const& key,
+		std::string const& variable,
+		genfile::VariantEntry const& value
+	) {
+		bool const new_key = m_keys.empty() || key != m_keys.back() ;
+		if( new_key ) {
+			create_new_key( key ) ;
+		}
+
+		VariableMap::left_const_iterator where = m_variables.left.find( variable ) ;
+		if( where == m_variables.left.end() ) {
+			if( m_insert_data_sql.get() ) {
+				// Uh-oh, table columns are already fixed.
+				// TODO: alter to put this data in SummaryData table?
+				throw genfile::BadArgumentError( "qcdb::FlatTableMultiVariantDBOutputter::store_per_variant_pair_data()", "variable=\"" + variable + "\"" ) ;
+			}
+			else {
+				// Still have time to add the variable to our list of variables, retaining the order of addition.
+				where = m_variables.left.insert( VariableMap::left_value_type( variable, m_variables.size() ) ).first ;
+			}
+		}
+
+		// Store the value of this variable
+		m_values[ std::make_pair( m_keys.size() - 1, where->second ) ] = value ;
+	}
+
+	void FlatTableMultiVariantDBOutputter::store_block() {
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
+
+		if( !m_insert_data_sql.get() ) {
+#if DEBUG_FLATTABLEDBOUTPUTTER
+			std::cerr << "FlatTableMultiVariantDBOutputter::store_block(): creating schema...\n" ;
+#endif 
+			create_schema() ;
+#if DEBUG_FLATTABLEDBOUTPUTTER
+			std::cerr << "FlatTableMultiVariantDBOutputter::store_block(): ok.\n" ;
+#endif
+			// create_variables() ;
+		}
+		std::vector< genfile::db::Connection::RowId > variant_ids ;
+		for( std::size_t key_i = 0; key_i < m_keys.size(); ++key_i ) {
+			variant_ids.resize( m_keys[key_i].size() ) ;
+			for( std::size_t i = 0; i < m_keys[key_i].size(); ++i ) {
+				variant_ids[i] = m_outputter.get_or_create_variant( m_keys[key_i][i] ) ;
+			}
+			store_data_for_variants( key_i, m_outputter.analysis_id(), variant_ids ) ;
+		}
+	}
+
+	std::string FlatTableMultiVariantDBOutputter::get_table_name() const {
+		return m_table_name ;
+	}
+
+	void FlatTableMultiVariantDBOutputter::create_schema() {
+		using genfile::string_utils::to_string ;
+		std::ostringstream schema_sql ;
+		std::ostringstream index_sql ;
+		std::ostringstream insert_data_sql ;
+		std::ostringstream insert_data_sql_columns ;
+		std::ostringstream insert_data_sql_values ;
+		std::string const& table_name = m_table_name ;
+
+		schema_sql << "CREATE TABLE IF NOT EXISTS "
+			<< table_name
+			<< " ( "
+			"analysis_id INT NOT NULL REFERENCES Entity( id )"
+				;
+		for( std::size_t i = 0; i < m_key_entry_names.size(); ++i ) {
+			schema_sql
+				<< ", `" << m_key_entry_names[i] << "_id` INT NOT NULL REFERENCES Variant( id )" ;
+		}
+		
+		insert_data_sql << "INSERT INTO "
+			<< table_name ;
+		insert_data_sql_columns << "( analysis_id" ;
+		insert_data_sql_values << "VALUES( ?1" ;
+
+		for( std::size_t i = 0; i < m_key_entry_names.size(); ++i ) {
+			insert_data_sql_columns << ", `" << m_key_entry_names[i] << "_id`" ;
+			insert_data_sql_values << boost::format( ", ?%d") % (i+2) ;
+		}
+		//insert_data_sql_columns << ")" ;
+		//insert_data_sql_values << ")" ;
+
+		VariableMap::right_const_iterator
+			var_i = m_variables.right.begin(),
+			end_var_i = m_variables.right.end() ;
+
+		for( std::size_t bind_i = m_key_entry_names.size()+2; var_i != end_var_i; ++var_i, ++bind_i ) {
+			schema_sql << ", " ;
+			insert_data_sql_columns << ", " ;
+			insert_data_sql_values << ", " ;
+			schema_sql
+				<< '`'
+				<< var_i->second
+				<< '`'
+				<< " NULL" ;
+				
+			insert_data_sql_columns << '`' << var_i->second << '`' ;
+			insert_data_sql_values << "?" << to_string( bind_i ) ;
+		}
+
+		if( m_without_rowid ) {
+			schema_sql << ", PRIMARY KEY( `analysis_id`" ;
+			for( std::size_t i = 0; i < m_key_entry_names.size(); ++i ) {
+				schema_sql  << ", `" << m_key_entry_names[i] << "_id`" ;
+			}
+			schema_sql << " ) ) WITHOUT ROWID ;" ;
+		} else {
+			schema_sql << " ) ; " ;
+		}
+
+		insert_data_sql_columns << ") " ;
+		insert_data_sql_values << ") ; " ;
+
+#if DEBUG_FLATTABLEDBOUTPUTTER
+		std::cerr << "Creating table " << table_name << " using this SQL:\n"
+			<< schema_sql.str()
+			<< "\n" ;
+#endif		
+		m_outputter.connection().run_statement( schema_sql.str() ) ;
+
+		std::ostringstream view_sql ;	
+		view_sql
+			<< "CREATE VIEW IF NOT EXISTS `" << table_name << "View` AS SELECT A.name AS `analysis`, "
+		;
+		for( std::size_t i = 0; i < m_key_entry_names.size(); ++i ) {
+			view_sql << boost::format( " V%d.rsid AS `%s_rsid`, V%d.chromosome AS `%s_chromosome`, V%d.position AS `%s_position`," )
+				% (i+1)
+				% m_key_entry_names[i]
+				% (i+1)
+				% m_key_entry_names[i]
+				% (i+1)
+				% m_key_entry_names[i]
+			;
+		}
+		view_sql  << "T.* FROM `"
+			<< table_name << "` T " ;
+		for( std::size_t i = 0; i < m_key_entry_names.size(); ++i ) {
+			view_sql << (boost::format( "INNER JOIN Variant V%d ON V%d.id = " + m_key_entry_names[i] + "_id " )
+				% (i+1) % (i+1) ) ;
+		}
+		view_sql << "INNER JOIN Analysis A ON A.id = T.analysis_id" ;
+
+#if DEBUG_FLATTABLEDBOUTPUTTER
+		std::cerr << "Creating view using SQL:\n" << view_sql.str() << "\n" ;
+#endif
+		m_outputter.connection().run_statement( view_sql.str() ) ;
+
+		insert_data_sql << " " << insert_data_sql_columns.str() << " " << insert_data_sql_values.str() ;
+#if DEBUG_FLATTABLEDBOUTPUTTER
+		std::cerr << "Inserts will use this SQL:\n"
+			<< insert_data_sql.str()
+			<< "\n" ;
+#endif
+		
+		m_insert_data_sql = m_outputter.connection().get_statement(
+			insert_data_sql.str()
+		) ;
+	}
+
+	void FlatTableMultiVariantDBOutputter::store_data_for_variants(
+		std::size_t const key_i,
+		genfile::db::Connection::RowId const analysis_id,
+		std::vector< genfile::db::Connection::RowId > const& variant_ids
+	) {
+		m_insert_data_sql->bind( 1, analysis_id ) ;
+		std::size_t i = 0 ;
+		for( ; i < variant_ids.size(); ++i ) {
+			m_insert_data_sql->bind( i+2, variant_ids[i] ) ;
+		}
+		
+		VariableMap::right_const_iterator
+			var_i = m_variables.right.begin(),
+			end_var_i = m_variables.right.end() ;
+		
+		for( std::size_t bind_i = i+2; var_i != end_var_i; ++var_i, ++bind_i ) {
+			ValueMap::const_iterator where = m_values.find( std::make_pair( key_i, var_i->first )) ;
+			if( where == m_values.end() ) {
+				m_insert_data_sql->bind( bind_i, genfile::MissingValue() ) ;
+			} else {
+#if DEBUG_FLATTABLEDBOUTPUTTER
+				std::cerr << "FlatTableMultiVariantDBOutputter::store_data_for_variants(): key " << key_i << ", bind( " << bind_i << ", " << where->second << " )\n" ;
+#endif
+				m_insert_data_sql->bind( bind_i, where->second ) ;
+			}
+		}
+		
+		m_insert_data_sql->step() ;
+		m_insert_data_sql->reset() ;
+	}
+}

ADDED   qcdb/src/MultiFileOutputter.cpp
Index: qcdb/src/MultiFileOutputter.cpp
==================================================================
--- qcdb/src/MultiFileOutputter.cpp
+++ qcdb/src/MultiFileOutputter.cpp
@@ -0,0 +1,210 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <memory>
+#include <iostream>
+#include <iomanip>
+#include <boost/bimap.hpp>
+#include <boost/bind.hpp>
+#include "genfile/VariantEntry.hpp"
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/string_utils.hpp"
+#include "statfile/BuiltInTypeStatSink.hpp"
+#include "appcontext/get_current_time_as_string.hpp"
+#include "qcdb/Storage.hpp"
+#include "qcdb/MultiFileOutputter.hpp"
+
+namespace qcdb {
+	namespace {
+		void append_to_string( std::string* target, std::string const& value ) {
+			(*target) += ( target->size() > 0 ? "," : "" ) + value ;
+		}
+	}
+
+	MultiFileOutputter::UniquePtr MultiFileOutputter::create( std::string const& filename, std::string const& analysis_name, Metadata const& metadata ) {
+		return UniquePtr( new MultiFileOutputter( filename, analysis_name, metadata ) ) ;
+	}
+
+	MultiFileOutputter::SharedPtr MultiFileOutputter::create_shared( std::string const& filename, std::string const& analysis_name, Metadata const& metadata ) {
+		return SharedPtr( new MultiFileOutputter( filename, analysis_name, metadata ) ) ;
+	}
+
+	MultiFileOutputter::MultiFileOutputter( std::string const& filename, std::string const& analysis_name, Metadata const& metadata ):
+		m_filename( filename ),
+		m_analysis_name( analysis_name ),
+		m_metadata( metadata ),
+		m_max_snps_per_block( 1000 )
+	{
+		m_snps.reserve( 1000 ) ;
+	}
+	
+	MultiFileOutputter::~MultiFileOutputter() {
+		store_block() ;
+		m_snps.clear() ;
+		m_values.clear() ;
+	}
+	
+	void MultiFileOutputter::finalise( long ) {
+		store_block() ;
+		m_snps.clear() ;
+		m_values.clear() ;
+		m_sink->write_comment( "Completed successfully at " + appcontext::get_current_time_as_string() ) ;
+	}
+
+	MultiFileOutputter::AnalysisId MultiFileOutputter::analysis_id() const {
+		// A flat file only ever has one analysis.
+		return 0 ;
+	}
+
+	void MultiFileOutputter::add_table( std::string const&, boost::function< bool( std::string const& ) > ) {
+		// do nothing, we do not support multiple tables.
+	}
+
+	void MultiFileOutputter::add_meta_table(
+		std::string const& tableName,
+		std::string const& rowName,
+		std::size_t number_of_columns,
+		boost::function< std::string ( std::size_t ) > getColumnName,
+		boost::function< genfile::VariantEntry( std::size_t ) > getColumnValue
+	) {
+		std::string const prefix = "- " + std::string( tableName.size() + 1, ' ' ) ;
+		std::ostringstream str ;
+		str << "- " << tableName << ": " << std::setw( std::max( rowName.size(), std::size_t(10) )) << "name" ;
+		std::vector< std::size_t > column_widths;
+		for( std::size_t i = 0; i < number_of_columns; ++i ) {
+			std::string const& column_name = getColumnName(i) ;
+			column_widths.push_back( std::max( column_name.size(), std::size_t(10) ) ) ;
+			str << " " << std::setw( column_widths[i] ) << column_name ;
+		}
+		str << "\n"
+			<< prefix
+			<< std::setw( std::max( rowName.size(), std::size_t(10) ))
+			<< rowName ;
+		for( std::size_t i = 0; i < number_of_columns; ++i ) {
+			str << " " << std::setw( column_widths[i] ) << getColumnValue(i) ;
+		}
+		str << "\n" ;
+		m_metatables.push_back( str.str() ) ;
+	}
+
+	void MultiFileOutputter::add_variable(
+		std::string const& variable,
+		std::string const& type
+	) {
+		VariableMap::left_const_iterator where = m_variables.left.find( variable ) ;
+		if( where == m_variables.left.end() ) {
+			if( m_sink.get() ) {
+				// Uh-oh, have already written a header.
+				throw genfile::BadArgumentError( "qcdb::MultiFileOutputter::add_variable()", "variable=\"" + variable + "\"" ) ;
+			}
+			else {
+				// Still have time to add the variable to our list of variables, retaining the order of addition.
+				where = m_variables.left.insert( VariableMap::left_value_type( variable, m_variables.size() ) ).first ;
+			}
+		}
+	}
+
+	void MultiFileOutputter::create_new_variant( genfile::VariantIdentifyingData const& snp ) {
+		if( m_snps.size() == m_max_snps_per_block ) {
+			store_block() ;
+			m_snps.clear() ;
+			m_values.clear() ;
+		}
+		m_snps.push_back( snp ) ;
+	}
+
+	void MultiFileOutputter::store_per_variant_data(
+		genfile::VariantIdentifyingData const& snp,
+		std::string const& variable,
+		genfile::VariantEntry const& value
+	) {
+		bool const new_snp = m_snps.empty() || snp != m_snps.back() ;
+		if( new_snp ) {
+			// If we have a whole block's worth of data, store it now.
+			if( m_snps.size() == m_max_snps_per_block ) {
+				store_block() ;
+				m_snps.clear() ;
+				m_values.clear() ;
+			}
+			m_snps.push_back( snp ) ;
+		}
+
+		VariableMap::left_const_iterator where = m_variables.left.find( variable ) ;
+		if( where == m_variables.left.end() ) {
+			if( m_sink.get() ) {
+				// Uh-oh, have already written a header.
+				throw genfile::BadArgumentError( "qcdb::MultiFileOutputter::store_per_variant_data()", "variable=\"" + variable + "\"" ) ;
+			}
+			else {
+				// Still have time to add the variable to our list of variables, retaining the order of addition.
+				where = m_variables.left.insert( VariableMap::left_value_type( variable, m_variables.size() ) ).first ;
+			}
+		}
+
+		// Store the value of this variable.
+		m_values[ std::make_pair( m_snps.size() - 1, where->second ) ] = value ;
+	}
+
+	void MultiFileOutputter::store_block() {
+		if( !m_sink.get() ) {
+			m_sink = statfile::BuiltInTypeStatSink::open( m_filename ) ;
+			m_sink->write_metadata( format_metadata() ) ;
+
+			(*m_sink) | "alternate_ids" | "rsid" | "chromosome" | "position" | "alleleA" | "alleleB" ;
+			VariableMap::right_const_iterator
+				i = m_variables.right.begin(),
+				end_i = m_variables.right.end() ;
+			for( ; i != end_i; ++i ) {
+				(*m_sink).add_column( i->second ) ;
+			}
+			(*m_sink) << statfile::begin_data() ;
+		}
+		for( std::size_t snp_i = 0; snp_i < m_snps.size(); ++snp_i ) {
+			genfile::VariantIdentifyingData const& snp = m_snps[ snp_i ] ;
+			std::string SNPID ;
+			snp.get_identifiers( boost::bind( &append_to_string, &SNPID, _1 ), 1 ) ;
+			(*m_sink) << SNPID << snp.get_primary_id() << snp.get_position().chromosome()
+				<< snp.get_position().position() << snp.get_allele(0) << snp.get_allele(1) ;
+			VariableMap::right_const_iterator
+				var_i = m_variables.right.begin(),
+				end_var_i = m_variables.right.end() ;
+			for( ; var_i != end_var_i; ++var_i ) {
+				ValueMap::const_iterator where = m_values.find( std::make_pair( snp_i, var_i->first )) ;
+				if( where == m_values.end() ) {
+					(*m_sink) << genfile::MissingValue() ;
+				}
+				else {
+					(*m_sink) << where->second ;
+				}
+			}
+			(*m_sink) << statfile::end_row() ;
+		}
+	}
+	
+	std::string MultiFileOutputter::format_metadata() const {
+		std::ostringstream str ;
+		str << "Analysis: \"" << m_analysis_name << "\"\n"
+			<< " started: " << appcontext::get_current_time_as_string() << "\n" ;
+		str << "\nAnalysis properties:\n" ;
+		for( Metadata::const_iterator i = m_metadata.begin(); i != m_metadata.end(); ++i ) {
+			str << "  "
+				<< i->first
+				<< " "
+				<< genfile::string_utils::join( i->second.first, " " )
+				<< " (" + i->second.second + ")\n" ;
+		}
+		if( m_metatables.size() > 0 ) {
+			str << "\nMetadata:\n" ;
+			for( std::size_t i = 0; i < m_metatables.size(); ++i ) {
+				str << m_metatables[i] ;
+			}
+		}
+		
+		return str.str() ;
+	}
+}

ADDED   qcdb/src/MultiTableDBOutputter.cpp
Index: qcdb/src/MultiTableDBOutputter.cpp
==================================================================
--- qcdb/src/MultiTableDBOutputter.cpp
+++ qcdb/src/MultiTableDBOutputter.cpp
@@ -0,0 +1,335 @@
+
+//			Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//	  (See accompanying file LICENSE_1_0.txt or copy at
+//			http://www.boost.org/LICENSE_1_0.txt)
+
+#include <string>
+#include <memory>
+#include <boost/shared_ptr.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/thread/thread.hpp>
+#include <boost/ptr_container/ptr_map.hpp>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "genfile/VariantEntry.hpp"
+#include "genfile/Error.hpp"
+#include "genfile/db/Connection.hpp"
+#include "genfile/db/SQLStatement.hpp"
+#include "appcontext/get_current_time_as_string.hpp"
+#include "qcdb/MultiTableDBOutputter.hpp"
+
+// #define DEBUG_FLATTABLEDBOUTPUTTER 1
+
+namespace qcdb {
+	MultiTableDBOutputter::UniquePtr MultiTableDBOutputter::create(
+		std::string const& filename,
+		std::string const& analysis_name,
+		std::string const& analysis_description,
+		Metadata const& metadata,
+		std::string const& snp_match_fields,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
+	) {
+		return UniquePtr( new MultiTableDBOutputter( filename, analysis_name, analysis_description, metadata, snp_match_fields ) ) ;
+	}
+
+	MultiTableDBOutputter::SharedPtr MultiTableDBOutputter::create_shared(
+		std::string const& filename,
+		std::string const& analysis_name,
+		std::string const& analysis_description,
+		Metadata const& metadata,
+		std::string const& snp_match_fields,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
+	) {
+		return SharedPtr( new MultiTableDBOutputter( filename, analysis_name, analysis_description, metadata, snp_match_fields, analysis_id ) ) ;
+	}
+
+	MultiTableDBOutputter::MultiTableDBOutputter(
+		std::string const& filename,
+		std::string const& analysis_name,
+		std::string const& analysis_description,
+		Metadata const& metadata,
+		std::string const& snp_match_fields,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
+	):
+		m_outputter( filename, analysis_name, analysis_description, metadata, analysis_id, snp_match_fields ),
+		m_max_snps_per_block( 1000 )
+	{}
+
+	MultiTableDBOutputter::~MultiTableDBOutputter() {
+	}
+	
+	void MultiTableDBOutputter::add_table( std::string const& table_name, ColumnSelector selector ) {
+		if( table_name.find_first_not_of( "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789_" ) != std::string::npos ) {
+			throw genfile::BadArgumentError( "qcdb::MultiTableDBOutputter::set_table_name()", "table_name=\"" + table_name + "\"" ) ;
+		}
+		m_table_names.push_back( table_name ) ;
+		m_column_selectors.push_back( selector ) ;
+	}
+
+	void MultiTableDBOutputter::add_meta_table(
+		std::string const& tableName,
+		std::string const& rowName,
+		std::size_t number_of_columns,
+		boost::function< std::string ( std::size_t ) > getColumnName,
+		boost::function< genfile::VariantEntry( std::size_t ) > getColumnValue
+	) {
+		std::ostringstream schema_sql ;
+		std::ostringstream insert_sql ;
+		schema_sql << "CREATE TABLE IF NOT EXISTS `" << tableName << "` ("
+			<< "analysis_id INTEGER NOT NULL, "
+			<< "name TEXT NOT NULL" ;
+		insert_sql << "INSERT INTO `" << tableName << "` VALUES( ?1, ?2" ;
+		for( std::size_t i = 0; i < number_of_columns; ++i ) {
+			schema_sql << ", `" << getColumnName(i) << "`" ;
+			insert_sql << ", ?" << i+3 ;
+		}
+		schema_sql << ");" ;
+		insert_sql << ");" ;
+		
+		m_outputter.connection().run_statement( schema_sql.str() ) ;
+		genfile::db::Connection::StatementPtr stmt = m_outputter.connection().get_statement( insert_sql.str() ) ;
+		stmt->bind( 1, analysis_id() ) ;
+		stmt->bind( 2, rowName ) ;
+		for( std::size_t i = 0; i < number_of_columns; ++i ) {
+			stmt->bind( i+3, getColumnValue(i) ) ;
+		}
+		stmt->step() ;
+	}
+	
+	void MultiTableDBOutputter::set_record_alternative_identifiers( bool value ) {
+		m_outputter.set_record_alternative_identifiers( value ) ;
+	}
+
+	MultiTableDBOutputter::AnalysisId MultiTableDBOutputter::analysis_id() const {
+		return m_outputter.analysis_id() ;
+	}
+
+	void MultiTableDBOutputter::finalise( long options ) {
+		store_block() ;
+		m_snps.clear() ;
+		m_values.clear() ;
+
+		if( options & eCreateIndices ) {
+			genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
+			for( std::size_t i = 0; i < m_table_names.size(); ++i ) {
+				m_outputter.connection().run_statement( "CREATE INDEX IF NOT EXISTS `" + m_table_names[i] + "_index` ON `" + m_table_names[i] + "`( variant_id )" ) ;
+			}
+		}
+
+		m_outputter.finalise( options ) ;
+	}
+
+	void MultiTableDBOutputter::add_variable( std::string const& variable, std::string const& type ) {
+		VariableMap::left_const_iterator where = m_variables.left.find( variable ) ;
+		if( where == m_variables.left.end() ) {
+			if( m_insert_data_sql.size() > 0 ) {
+				// Uh-oh, table columns are already fixed.
+				// TODO: alter to put this data in SummaryData table?
+				throw genfile::BadArgumentError( "qcdb::MultiTableDBOutputter::add_variable()", "variable=\"" + variable + "\"" ) ;
+			}
+			else {
+				// Still have time to add the variable to our list of variables, retaining the order of addition.
+				m_variables.left.insert( VariableMap::left_value_type( variable, std::make_pair( m_variables.size(), type ) ) ) ;
+			}
+		}
+	}
+
+	void MultiTableDBOutputter::create_new_variant( genfile::VariantIdentifyingData const& snp ) {
+		if( m_snps.size() == m_max_snps_per_block ) {
+			store_block() ;
+			m_snps.clear() ;
+			m_values.clear() ;
+		}
+		m_snps.push_back( snp ) ;
+	}
+
+	void MultiTableDBOutputter::store_per_variant_data(
+		genfile::VariantIdentifyingData const& snp,
+		std::string const& variable,
+		genfile::VariantEntry const& value
+	) {
+		bool const new_snp = m_snps.empty() || snp != m_snps.back() ;
+		if( new_snp ) {
+			// If we have a whole block's worth of data, store it now.
+			if( m_snps.size() == m_max_snps_per_block ) {
+				store_block() ;
+				m_snps.clear() ;
+				m_values.clear() ;
+			}
+			m_snps.push_back( snp ) ;
+		}
+
+		VariableMap::left_const_iterator where = m_variables.left.find( variable ) ;
+		if( where == m_variables.left.end() ) {
+			if( m_insert_data_sql.size() > 0 ) {
+				// Uh-oh, table columns are already fixed.
+				// TODO: alter to put this data in SummaryData table?
+				throw genfile::BadArgumentError( "qcdb::MultiTableDBOutputter::store_per_variant_data()", "variable=\"" + variable + "\"" ) ;
+			}
+			else {
+				// Still have time to add the variable to our list of variables, retaining the order of addition.
+				where = m_variables.left.insert( VariableMap::left_value_type( variable, std::make_pair( m_variables.size(), "NULL" ) ) ).first ;
+			}
+		}
+
+		// Store the value of this variable
+		m_values[ std::make_pair( m_snps.size() - 1, where->second.first ) ] = value ;
+	}
+
+	void MultiTableDBOutputter::store_block() {
+		genfile::db::Connection::ScopedTransactionPtr transaction = m_outputter.connection().open_transaction( 7200 ) ;
+
+		if( m_insert_data_sql.empty() ) {
+			create_schema() ;
+			create_variables() ;
+		}
+		for( std::size_t i = 0; i < m_snps.size(); ++i ) {
+			genfile::db::Connection::RowId const variant_id = m_outputter.get_or_create_variant( m_snps[i] ) ;
+			store_data_for_variant( i, m_snps[i], m_outputter.analysis_id(), variant_id ) ;
+		}
+	}
+
+	std::vector< std::string > const& MultiTableDBOutputter::get_table_names() const {
+		return m_table_names ;
+	}
+
+	void MultiTableDBOutputter::create_schema() {
+		using genfile::string_utils::to_string ;
+		assert( m_insert_data_sql.size() == 0 ) ;
+		assert( m_column_maps.size() == 0 ) ;
+		m_column_maps.resize( m_table_names.size() ) ;
+		for( std::size_t table_i = 0; table_i < m_table_names.size(); ++table_i ) {
+			std::string const& table_name = m_table_names[table_i] ;
+
+			std::ostringstream schema_sql ;
+			std::ostringstream index_sql ;
+			std::ostringstream insert_data_sql ;
+			std::ostringstream insert_data_sql_columns ;
+			std::ostringstream insert_data_sql_values ;
+			std::map< std::string, std::size_t > column_map ;
+			
+			schema_sql << "CREATE TABLE IF NOT EXISTS `"
+				<< table_name
+				<< "` ( "
+				"analysis_id INT NOT NULL REFERENCES Entity( id ), "
+				"variant_id INT NOT NULL REFERENCES Variant( id ), "
+				"chromosome TEXT, "
+				"position INTEGER"
+			;
+		
+			insert_data_sql << "INSERT INTO "
+				<< table_name ;
+			insert_data_sql_columns << "( analysis_id, variant_id, chromosome, position" ;
+			insert_data_sql_values << "VALUES( ?1, ?2, ?3, ?4" ;
+		
+			VariableMap::right_const_iterator
+				var_i = m_variables.right.begin(),
+				end_var_i = m_variables.right.end() ;
+
+			for( std::size_t bind_i = 5; var_i != end_var_i; ++var_i ) {
+				std::string const& variable = var_i->second ;
+				if( m_column_selectors[table_i]( variable ) ) {
+					schema_sql << ", " ;
+					insert_data_sql_columns << ", " ;
+					insert_data_sql_values << ", " ;
+					schema_sql
+						<< '`'
+						<< var_i->second
+						<< '`'
+						<< " "
+						<< var_i->first.second ;
+				
+					insert_data_sql_columns << '`' << variable << '`' ;
+					insert_data_sql_values << "?" << to_string( bind_i ) ;
+					column_map[ variable ] = bind_i ;
+					++bind_i ;
+				}
+			}
+
+			schema_sql << " ) ; " ;
+
+			insert_data_sql_columns << ") " ;
+			insert_data_sql_values << ") ; " ;
+
+	#if DEBUG_FLATTABLEDBOUTPUTTER
+			std::cerr << "Creating table " << table_name << " using this SQL:\n"
+				<< schema_sql.str()
+				<< "\n" ;
+	#endif		
+			m_outputter.connection().run_statement( schema_sql.str() ) ;
+
+			std::ostringstream view_sql ;	
+			view_sql
+				<< "CREATE VIEW IF NOT EXISTS \"" << table_name << "View\" AS "
+				<< "SELECT V.rsid, V.alleleA, V.alleleB, A.name AS analysis, T.* FROM \""
+				<< table_name << "\" T "
+				<< "INNER JOIN Variant V ON V.id = T.variant_id "
+				<< "INNER JOIN Analysis A ON A.id = T.analysis_id"
+			;
+
+#if DEBUG_FLATTABLEDBOUTPUTTER
+			std::cerr << "Creating view using SQL:\n" << view_sql.str() << "\n" ;
+#endif
+			m_outputter.connection().run_statement( view_sql.str() ) ;
+
+			insert_data_sql << " " << insert_data_sql_columns.str() << " " << insert_data_sql_values.str() ;
+#if DEBUG_FLATTABLEDBOUTPUTTER
+			std::cerr << "Inserts will use this SQL:\n"
+				<< insert_data_sql.str()
+				<< "\n" ;
+#endif
+			
+			m_insert_data_sql.push_back(
+				m_outputter.connection().get_statement(
+					insert_data_sql.str()
+				)
+			) ;
+			
+			m_column_maps[table_i] = column_map ;
+		}
+	}
+
+	void MultiTableDBOutputter::create_variables() {
+		VariableMap::right_const_iterator
+			var_i = m_variables.right.begin(),
+			end_var_i = m_variables.right.end() ;
+		for( ; var_i != end_var_i; ++var_i ) {
+			m_outputter.create_variable( "", var_i->second ) ;
+		}
+	}
+	
+	void MultiTableDBOutputter::store_data_for_variant(
+		std::size_t const snp_i,
+		genfile::VariantIdentifyingData const& snp,
+		genfile::db::Connection::RowId const analysis_id,
+		genfile::db::Connection::RowId const variant_id
+	) {
+		for( std::size_t i = 0; i < m_table_names.size(); ++i ) {
+			genfile::db::SQLStatement& insert_data_sql = m_insert_data_sql[i] ;
+			insert_data_sql.bind( 1, analysis_id ) ;
+			insert_data_sql.bind( 2, variant_id ) ;
+			insert_data_sql.bind( 3, std::string( snp.get_position().chromosome() ) ) ;
+			insert_data_sql.bind( 4, snp.get_position().position() ) ;
+		
+			VariableMap::right_const_iterator
+				var_i = m_variables.right.begin(),
+				end_var_i = m_variables.right.end() ;
+		
+			for( ; var_i != end_var_i; ++var_i ) {
+				std::string const& variable = var_i->second ;
+				std::map< std::string, std::size_t >::const_iterator column_i = m_column_maps[i].find( variable ) ;
+				if( column_i != m_column_maps[i].end() ) {
+					ValueMap::const_iterator value_i = m_values.find( std::make_pair( snp_i, var_i->first.first )) ;
+					if( value_i == m_values.end() ) {
+						insert_data_sql.bind( column_i->second, genfile::MissingValue() ) ;
+					} else {
+						insert_data_sql.bind( column_i->second, value_i->second ) ;
+					}
+				}
+			}
+		
+			insert_data_sql.step() ;
+			insert_data_sql.reset() ;
+		}
+	}
+}

ADDED   qcdb/src/MultiVariantStorage.cpp
Index: qcdb/src/MultiVariantStorage.cpp
==================================================================
--- qcdb/src/MultiVariantStorage.cpp
+++ qcdb/src/MultiVariantStorage.cpp
@@ -0,0 +1,64 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <stdint.h>
+#include <vector>
+#include <string>
+#include <boost/noncopyable.hpp>
+#include <boost/shared_ptr.hpp>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "qcdb/StorageOptions.hpp"
+#include "qcdb/MultiVariantStorage.hpp"
+#include "qcdb/FlatTableMultiVariantDBOutputter.hpp"
+#include "qcdb/FlatFileMultiVariantOutputter.hpp"
+
+namespace qcdb {
+	MultiVariantStorage::UniquePtr MultiVariantStorage::create(
+		std::string const& filename,
+		std::size_t const number_of_key_fields,
+		std::string const& analysis_name,
+		std::string const& analysis_chunk,
+		Metadata const& metadata,
+		std::string const& compare_by,
+		boost::optional< genfile::db::Connection::RowId > analysis_id	
+	) {
+		MultiVariantStorage::UniquePtr result ;
+		std::vector< std::string > const file_spec = Storage::parse_filespec( filename ) ;
+		if( file_spec[0] == "sqlite" ) {
+			FlatTableMultiVariantDBOutputter::UniquePtr table_storage = FlatTableMultiVariantDBOutputter::create(
+				file_spec[1],
+				number_of_key_fields,
+				analysis_name,
+				analysis_chunk,
+				metadata,
+				compare_by,
+				analysis_id
+			) ;
+			// Set table name, if specified
+			if( file_spec.size() > 2 ) {
+				table_storage->set_table_name( file_spec[2] ) ;
+			}
+			if( file_spec.size() > 3 ) {
+				assert( file_spec[3] == "without rowid" ) ;
+				table_storage->set_without_rowid() ;
+			}
+			result.reset( table_storage.release() ) ;
+		} else if( file_spec[0] == "flat" ){
+			FlatFileMultiVariantOutputter::UniquePtr file_storage = FlatFileMultiVariantOutputter::create(
+				file_spec[1],
+				number_of_key_fields,
+				analysis_name,
+				metadata
+			) ;
+			result.reset( file_storage.release() ) ;
+		} else {
+			assert(0) ;
+		}
+
+		return result ;
+	}
+}
+

ADDED   qcdb/src/Storage.cpp
Index: qcdb/src/Storage.cpp
==================================================================
--- qcdb/src/Storage.cpp
+++ qcdb/src/Storage.cpp
@@ -0,0 +1,100 @@
+
+//          Copyright Gavin Band 2008 - 2012.
+// Distributed under the Boost Software License, Version 1.0.
+//    (See accompanying file LICENSE_1_0.txt or copy at
+//          http://www.boost.org/LICENSE_1_0.txt)
+
+#include <stdint.h>
+#include <vector>
+#include <string>
+#include <boost/noncopyable.hpp>
+#include <boost/shared_ptr.hpp>
+#include "genfile/VariantIdentifyingData.hpp"
+#include "qcdb/StorageOptions.hpp"
+#include "qcdb/Storage.hpp"
+#include "qcdb/FlatTableDBOutputter.hpp"
+#include "qcdb/FlatFileOutputter.hpp"
+
+namespace qcdb {
+	std::vector< std::string > Storage::parse_filespec( std::string spec ) {
+		std::vector< std::string > result(2) ;
+		result[0] = "flat" ;
+	
+		// First get rid of leading sqlite specifier, if any.
+		if( spec.size() >= 9 && spec.substr( 0, 9 ) == "sqlite://" ) {
+			result[0] = "sqlite" ;
+			spec = spec.substr( 9, spec.size() ) ;
+		}
+
+		std::vector< std::string > elts = genfile::string_utils::split( spec, ":" ) ;
+		assert( elts.size() > 0 ) ;
+
+		if( elts[0].size() >= 7 && elts[0].substr( elts[0].size() - 7, 7 ) == ".sqlite" ) {
+			result[0] = "sqlite" ;
+		}
+		result[1] = elts[0] ;
+
+		if( elts.size() > 2 ) {
+			throw genfile::BadArgumentError(
+				"parse_filespec()",
+				"spec=\"" + spec + "\"",
+				"Expected format for filespec is <filename> or sqlite://<filename>[:<tablename>]."
+			) ;
+		}
+		if( elts.size() == 2 ) {
+			if( result[0] != "sqlite" ) {
+				throw genfile::BadArgumentError(
+					"parse_filespec()",
+					"spec=\"" + spec + "\"",
+					"Table spec is not expected unless a sqlite file is specified (i.e. sqlite://<filename>:<tablename>)"
+				) ;
+			}
+			std::vector< std::string > table_elts = genfile::string_utils::split( elts[1], "+" ) ;
+			if( table_elts.size() == 2 ) {
+				result.push_back( table_elts[0] ) ;
+				result.push_back( table_elts[1] ) ;
+			} else {
+				result.push_back( elts[1] ) ;
+			}
+		}
+	
+		return( result ) ;
+	}
+
+	Storage::UniquePtr Storage::create(
+		std::string const& filename,
+		std::string const& analysis_name,
+		std::string const& analysis_chunk,
+		Metadata const& metadata,
+		std::string const& compare_by,
+		boost::optional< genfile::db::Connection::RowId > analysis_id
+	) {
+		Storage::UniquePtr result ;
+		std::vector< std::string > const file_spec = Storage::parse_filespec( filename ) ;
+		if( file_spec[0] == "sqlite" ) {
+			FlatTableDBOutputter::UniquePtr table_storage = FlatTableDBOutputter::create(
+				file_spec[1],
+				analysis_name,
+				analysis_chunk,
+				metadata,
+				compare_by,
+				analysis_id
+			) ;
+			// Set table name, if specified
+			if( file_spec.size() == 3 ) {
+				table_storage->set_table_name( file_spec[2] ) ;
+			}
+			result = table_storage ;
+		} else {
+			assert( file_spec[0] == "flat" ) ;
+			result = FlatFileOutputter::create(
+				file_spec[1],
+				analysis_name,
+				metadata
+			) ;
+		}
+
+		return result ;
+	}
+}
+

Index: qcdb/src/store_samples_in_db.cpp
==================================================================
--- qcdb/src/store_samples_in_db.cpp
+++ qcdb/src/store_samples_in_db.cpp
@@ -35,11 +35,11 @@
 				+ ")."
 			) ;
 		}
 		genfile::CohortIndividualSource::ColumnSpec const spec = sample_data.get_column_spec() ;
 
-		db::Connection::ScopedTransactionPtr transaction = outputter.connection().open_transaction( 2400 ) ;
+		genfile::db::Connection::ScopedTransactionPtr transaction = outputter.connection().open_transaction( 2400 ) ;
 
 		std::string sample_sql = 
 			"CREATE TABLE IF NOT EXISTS Sample ( "
 			"analysis_id INTEGER NOT NULL REFERENCES Analysis( id ), "
 			"index_in_data INTEGER NOT NULL" ;
@@ -61,11 +61,11 @@
 		}
 		insert_sample_sql += " ) ;" ;
 
 		outputter.connection().run_statement( sample_sql ) ;
 	
-		db::Connection::StatementPtr insert_sample_stmnt = outputter.connection().get_statement( insert_sample_sql ) ;
+		genfile::db::Connection::StatementPtr insert_sample_stmnt = outputter.connection().get_statement( insert_sample_sql ) ;
 
 		for( std::size_t sample_i = 0; sample_i < number_of_samples; ++sample_i ) {
 			if( getter(sample_i) != sample_data.get_entry( sample_i, "ID_1" )) {
 				throw genfile::BadArgumentError(
 					"snp_output_component::store_samples_in_db()",

Index: qcdb/wscript
==================================================================
--- qcdb/wscript
+++ qcdb/wscript
@@ -1,46 +1,12 @@
-import os.path
-import glob
-#import UnitTest
-
 def configure( conf ):
 	pass
-
-def create_test( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = [  'test/' + name + '.cpp' ],
-		uselib_local = 'db',
-		uselib = 'BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include',
-		unit_test=1,
-		install_path=None
-	)
-
-def create_benchmark( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = [  'benchmarks/' + name + '.cpp' ],
-		uselib_local = 'db',
-		includes='./include',
-		install_path=None
-	)
-
 
 def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld(
-		features = 'cxx cstaticlib',
+	bld.stlib(
 		target = 'qcdb',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib = 'BOOST_THREAD',
-		uselib_local = 'sqlite3 statfile genfile appcontext db',
-		export_incdirs = './include'
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		use = 'genfile sqlite3 statfile appcontext boost genfile',
+		includes = './include',
+		export_includes = './include'
 	)
 	

Index: release/Release/ReleaseBuilder.py
==================================================================
--- release/Release/ReleaseBuilder.py
+++ release/Release/ReleaseBuilder.py
@@ -7,25 +7,25 @@
 	def build( self ):
 		import os, tempfile, shutil, subprocess
 		tempdir = tempfile.mkdtemp()
 		import platform
 		if platform.system() == 'Darwin':
-			release_stub = '%s_v%s-osx' % ( self.APPNAME, self.VERSION )
+			release_stub = '%s_v%s-osx-%s' % ( self.APPNAME, self.VERSION, platform.machine() )
 		elif platform.system() == 'Linux':
-			distro = platform.linux_distribution()
+			distro = linux_distribution()
 			release_stub = '%s_v%s-%s%s-%s' % ( self.APPNAME, self.VERSION, distro[0], distro[1], platform.machine() )
 		release_dir = os.path.join( tempdir, release_stub )
 		os.mkdir( release_dir )
 		
 		target_executable = "%s/%s" % ( release_dir, self.APPNAME )
 		
 		shutil.copyfile( self.executable, target_executable )
 		shutil.copymode( self.executable, target_executable )
 		shutil.copyfile( "LICENSE_1_0.txt", "%s/LICENSE_1_0.txt" % release_dir )
-		shutil.copyfile( "CHANGELOG.txt", "%s/CHANGELOG.txt" % release_dir )
+		#shutil.copyfile( "CHANGELOG.txt", "%s/CHANGELOG.txt" % release_dir )
 		target_tarball =  '%s/%s.tgz' % ( tempdir, release_stub )
 		process = subprocess.Popen( [ 'tar', '-czf', target_tarball, release_stub ], cwd = tempdir )
 		process.wait()
-		print 'Created %s release tarball in "%s"' % ( self.APPNAME, target_tarball )
-		print "Contents are:"
-		print subprocess.Popen( [ 'tar', '-tzf', target_tarball ], stdout = subprocess.PIPE ).communicate()[0]
+		print(  'Created %s release tarball in "%s"' % ( self.APPNAME, target_tarball ) )
+		print(  "Contents are:" )
+		print(  subprocess.Popen( [ 'tar', '-tzf', target_tarball ], stdout = subprocess.PIPE ).communicate()[0] )
 		return { "release_executable": target_executable, "release_tarball": target_tarball }

Index: release/Release/SingleTest.py
==================================================================
--- release/Release/SingleTest.py
+++ release/Release/SingleTest.py
@@ -25,26 +25,26 @@
 		tmpdir = tempfile.mkdtemp( prefix="qctool-expected" )
 		subprocess.check_call( [ "tar", "-C", tmpdir, "-xzf", self.result_tarball ] )
 		return tmpdir
 
 	def compare( self, expected_dir, output_dir ):
-		print "...and comparing to", expected_dir
+		print(  "...and comparing to", expected_dir )
 
 		# Perform a comparison
 		F = filecmp.dircmp( expected_dir, output_dir )
 		self.directory_comparison = F
 		common_files = F.common_files
 		F = filecmp.cmpfiles( expected_dir, output_dir, common_files, shallow = False )
 		self.file_comparison = { "match": F[0], "mismatch": F[1], "errors": F[2] }
 
 		if len( self.directory_comparison.left_only ) > 0 or len( self.directory_comparison.right_only ) > 0 or len( self.directory_comparison.common_funny ) > 0:
-			print '!! For command', self.command, 'expected result and actual result differ:'
+			print(  '!! For command', self.command, 'expected result and actual result differ:' )
 			F.report()
 			raise Exception( "Expected result differs from actual result" )
 
 		if ( len( self.file_comparison[ "mismatch" ] ) + len( self.file_comparison[ "errors" ] ) ) != 0:
-			print '!! For command', self.command, 'expected result and actual result differ:'
-			print "Mismatches:", " ".join( self.file_comparison[ "mismatch" ] ), "Errors:", " ".join( self.file_comparison[ "errors" ] )
+			print(  '!! For command', self.command, 'expected result and actual result differ:' )
+			print(  "Mismatches:", " ".join( self.file_comparison[ "mismatch" ] ), "Errors:", " ".join( self.file_comparison[ "errors" ] ) )
 			raise Exception( "Expected result differs from actual result" )
 
 	def get_comparison( self ):
 		return { "directory_comparison": self.directory_comparison, "file_comparison": self.file_comparison }

Index: release/Release/TestHarness.py
==================================================================
--- release/Release/TestHarness.py
+++ release/Release/TestHarness.py
@@ -14,11 +14,11 @@
 		for i in range( 0, len( self.tests ) ):
 			if not "result_tarball" in self.tests[i]:
 				self.tests[i][ "result_tarball" ] = os.path.join( self.working_dir, hashlib.md5( self.tests[i][ "command" ] ).hexdigest() + ".tgz" )
 			if not "name" in self.tests[i]:
 				self.tests[i][ "name" ] = self.tests[i][ "command" ]
-		print "Tests are:"
+		print("Tests are:")
 		pprint.pprint( [ test[ "name" ] for test in self.tests ] )
 		
 		if not os.path.exists( qctool_exe ) and os.path.isfile( qctool_exe ):
 			raise Exception( "The qctool executable \"" + qctool_exe + "\" must exist and be an executable." )
 		if not os.path.exists( working_dir ) and os.path.isdir( working_dir ):
@@ -33,38 +33,38 @@
 		for i in range( 0, len( self.tests )):
 			command = self.tests[i][ "command" ]
 			output_dir = tempfile.mkdtemp( prefix="qctool-test-" )
 			command = command.replace( '%INPUT_DIR%', working_dir )
 			command = command.replace( '%OUTPUT_DIR%', output_dir )
-			print "Running command: \"%s\"" % ( os.path.basename( self.qctool_exe ) + " " + command ),
-			print "and comparing to", 
+			print("Running command: \"%s\"" % ( os.path.basename( self.qctool_exe ) + " " + command ))
+			print("and comparing to")
 			
 			test = SingleTest.SingleTest( self.qctool_exe + " " + command, output_dir, os.path.join( self.working_dir, self.tests[i][ "result_tarball" ] ))
 			try:
 				test.run()
 				test_results[ "succeeded" ].append( self.tests[i][ "name" ] )
-			except Exception, e:
-				print "!! Testing of command \"" + self.tests[i][ "name" ] + "\" failed!"
-				print e
+			except Exception as e:
+				print("!! Testing of command \"" + self.tests[i][ "name" ] + "\" failed!")
+				print(e)
 				test_results[ "failed" ].append( { "name": self.tests[i][ "name" ], "comparison": test.get_comparison(), "command": command } )
 		
-		print "---- test summary ----"
-		print "succeeded:     ", len( test_results[ "succeeded" ] )
-		print "failed:        ", len( test_results[ "failed" ] )
+		print("---- test summary ----")
+		print("succeeded:     ", len( test_results[ "succeeded" ] ))
+		print("failed:        ", len( test_results[ "failed" ] ))
 			
 		if len( test_results[ "failed" ] ) > 0:
-			print "Tests failed for the following commands:"
+			print("Tests failed for the following commands:")
 			for i in range( 0, len( test_results[ "failed" ] )):
 				pprint.pprint( test_results[ "failed" ][i] )
-				print "   ( expected", self.tests[i][ "result_tarball" ], ")"
+				print("   ( expected", self.tests[i][ "result_tarball" ], ")")
 			self.m_success = False
 		else:
 			self.m_success = True
 			
 	def setup( self ):
 		working_dir = tempfile.mkdtemp( prefix="qctool-test-" )
-		#print "Extracting", self.setup_tarball, "to", working_dir
+		#print "Extracting", self.setup_tarball, "to", working_dir)
 		subprocess.check_call( [ "tar", "-C", working_dir, "-xzf", self.setup_tarball ] )
 		return working_dir
 
 	def success( self ):
 		return self.m_success

Index: release/test/QctoolRunner.py
==================================================================
--- release/test/QctoolRunner.py
+++ release/test/QctoolRunner.py
@@ -1,18 +1,23 @@
 import os, sys
 import subprocess
 import tempfile
 import json
 from robot.api import logger
-from StringIO import StringIO
+try:
+	# Python 2
+	from StringIO import StringIO
+except ImportError:
+	# Python 3
+	from io import StringIO
 
 class QctoolRunner:
 	def __init__( self, qctool ):
 		self.qctool = qctool
 		self.command = 'snp-stats'
 		self.gdata = [ 'data/test.gen' ]
-		self.sdata = [ 'data/test.sample' ]
+		self.sdata = None
 		self.log = None
 		self.outputFilename = None
 
 	def set_data( self, dataSpec ):
 		spec = json.load( StringIO( dataSpec ))
@@ -22,11 +27,11 @@
 	def run_qctool( self, command, expected, qctool = None ):
 		if qctool is None:
 			qctool = self.qctool
 		filenames = {}
 		temp = open( 'temp', 'a' )
-		print >> temp, command
+		print( command, file = temp )
 		values = json.load( StringIO( command ))
 		gdata = values.get( 'g', self.gdata )
 		sdata = values.get( 's', self.sdata )
 		ogdata = values.get( 'og', None )
 		if ogdata == '<tmp>':
@@ -38,12 +43,13 @@
 			osdata = filenames[ 'os' ]
 		cmd = [ qctool ]
 		logger.debug( gdata, sdata )
 		for i in range( 0, len(gdata) ):
 			cmd += [ "-g", gdata[i] ]
-		for i in range( 0, len(sdata) ):
-			cmd += [ "-s", sdata[i] ]
+		if sdata is not None:
+			for i in range( 0, len(sdata) ):
+				cmd += [ "-s", sdata[i] ]
 		
 		for option in [
 			'vcf-genotype-field',
 			'incl-positions', 'excl-positions',
 			'incl-snpids', 'excl-snpids', 'incl-rsids', 'excl-rsids',
@@ -68,26 +74,32 @@
 					cmd.append( valueList[i] )
 
 		for option in [ 'snp-stats', 'sample-stats' ]:
 			if values.get( option, None ) is not None:
 				cmd.extend( [ '-%s' % option ] )
+
+		for option in [ 'force' ]:
+			if option in values:
+				cmd.extend( [ '-%s' % option ] )
 		
 		if ogdata is not None:
 			cmd.extend( [ '-og', ogdata ])
 		if osdata is not None:
 			cmd.extend( [ '-os', osdata ])
 		
-		print >> temp, ' '.join( cmd )
+		print( ' '.join( cmd ), file = temp )
 		try:
-			subprocess.check_call( cmd, stdout = subprocess.PIPE, stderr = subprocess.PIPE )
+			#subprocess.check_call( cmd, stdout = subprocess.PIPE, stderr = subprocess.PIPE )
+			subprocess.check_call( cmd, stdout = subprocess.DEVNULL, stderr = subprocess.DEVNULL )
 			if expected != 'ok':
 				raise Exception( "Expected failure: %s" % command )
-		except subprocess.CalledProcessError, e:
+		except subprocess.CalledProcessError as e:
+			print( 'ok', file = temp )
 			if expected == 'ok':
 				raise Exception( "Expected success: %s" % command )
 		finally:
 			temp.close()
 		logger.info( "Complete run" )
 		return filenames
 
 	def output_filename( self ):
 		return self.outputFilename

Index: release/test/data/complex.backward.vcf
==================================================================
--- release/test/data/complex.backward.vcf
+++ release/test/data/complex.backward.vcf
@@ -2,14 +2,14 @@
 ##FORMAT=<ID=GT,Type=String,Number=1,Description="Consensus genotype call">
 ##FORMAT=<ID=GP,Type=Float,Number=.,Description="Genotype probabilities">
 ##FORMAT=<ID=HP,Type=Float,Number=.,Description="Haplotype probabilities">
 #CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	sample_3	sample_2	sample_1	sample_0
 01	1	V1	A	G	.	.	.	GT:GP	0/1:0,1,0	0/0:1,0,0	0/0:1,0,0	0:1,0
-01	2	V2,V2.1	A	G	.	.	.	GT:GP	1:0,1	0:1,0	0:1,0	0:1,0
+01	2	V2;V2.1	A	G	.	.	.	GT:GP	1:0,1	0:1,0	0:1,0	0:1,0
 01	3	V3	A	G	.	.	.	GT:HP	0|1:1,0,0,1	0|0:1,0,1,0	1|1:0,1,0,1	0:1,0
 01	4	M4	A	G,T	.	.	.	GT:GP	0/2:0,0,0,1,0,0	0/1:0,1,0,0,0,0	0/0:1,0,0,0,0,0	0:1,0,0
 01	5	M5	A	G	.	.	.	GT:HP	0|1:1,0,0,1	0|0|1:1,0,1,0,0,1	0|0|0:1,0,1,0,1,0	0:1,0
 01	7	M6	A	G,GT,GTT	.	.	.	GT:GP	3:0,0,0,1	2:0,0,1,0	1:0,1,0,0	0:1,0,0,0
 01	7	M7	A	G,GT,GTT,GTTT,GTTTT	.	.	.	GT:GP	5:0,0,0,0,0,1	4:0,0,0,0,1,0	3:0,0,0,1,0,0	0:1,0,0,0,0,0
 01	8	M8	A	G,GT,GTT,GTTT,GTTTT,GTTTTT	.	.	.	GT:GP	5:0,0,0,0,0,1,0	4:0,0,0,0,1,0,0	3:0,0,0,1,0,0,0	0:1,0,0,0,0,0,0
 01	9	M9	A	G,GT,GTT,GTTT,GTTTT,GTTTTT,GTTTTTT	.	.	.	GT:GP	1/5:0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0	4:0,0,0,0,1,0,0,0	6:0,0,0,0,0,0,1,0	0:1,0,0,0,0,0,0,0
 01	10	M10	A	G	.	.	.	GT:GP	0/1/1/1:0,0,0,1,0	0/0/1/1:0,0,1,0,0	0/0/0/1:0,1,0,0,0	0/0/0/0:1,0,0,0,0

Index: release/test/data/complex.reordered.vcf
==================================================================
--- release/test/data/complex.reordered.vcf
+++ release/test/data/complex.reordered.vcf
@@ -2,14 +2,14 @@
 ##FORMAT=<ID=GT,Type=String,Number=1,Description="Consensus genotype call">
 ##FORMAT=<ID=GP,Type=Float,Number=.,Description="Genotype probabilities">
 ##FORMAT=<ID=HP,Type=Float,Number=.,Description="Haplotype probabilities">
 #CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	sample_3	sample_1	sample_0	sample_2
 01	1	V1	A	G	.	.	.	GT:GP	0/1:0,1,0	0/0:1,0,0	0:1,0	0/0:1,0,0
-01	2	V2,V2.1	A	G	.	.	.	GT:GP	1:0,1	0:1,0	0:1,0	0:1,0
+01	2	V2;V2.1	A	G	.	.	.	GT:GP	1:0,1	0:1,0	0:1,0	0:1,0
 01	3	V3	A	G	.	.	.	GT:HP	0|1:1,0,0,1	1|1:0,1,0,1	0:1,0	0|0:1,0,1,0
 01	4	M4	A	G,T	.	.	.	GT:GP	0/2:0,0,0,1,0,0	0/0:1,0,0,0,0,0	0:1,0,0	0/1:0,1,0,0,0,0
 01	5	M5	A	G	.	.	.	GT:HP	0|1:1,0,0,1	0|0|0:1,0,1,0,1,0	0:1,0	0|0|1:1,0,1,0,0,1
 01	7	M6	A	G,GT,GTT	.	.	.	GT:GP	3:0,0,0,1	1:0,1,0,0	0:1,0,0,0	2:0,0,1,0
 01	7	M7	A	G,GT,GTT,GTTT,GTTTT	.	.	.	GT:GP	5:0,0,0,0,0,1	3:0,0,0,1,0,0	0:1,0,0,0,0,0	4:0,0,0,0,1,0
 01	8	M8	A	G,GT,GTT,GTTT,GTTTT,GTTTTT	.	.	.	GT:GP	5:0,0,0,0,0,1,0	3:0,0,0,1,0,0,0	0:1,0,0,0,0,0,0	4:0,0,0,0,1,0,0
 01	9	M9	A	G,GT,GTT,GTTT,GTTTT,GTTTTT,GTTTTTT	.	.	.	GT:GP	1/5:0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0	6:0,0,0,0,0,0,1,0	0:1,0,0,0,0,0,0,0	4:0,0,0,0,1,0,0,0
 01	10	M10	A	G	.	.	.	GT:GP	0/1/1/1:0,0,0,1,0	0/0/0/1:0,1,0,0,0	0/0/0/0:1,0,0,0,0	0/0/1/1:0,0,1,0,0

Index: release/test/data/complex.vcf
==================================================================
--- release/test/data/complex.vcf
+++ release/test/data/complex.vcf
@@ -2,14 +2,14 @@
 ##FORMAT=<ID=GT,Type=String,Number=1,Description="Consensus genotype call">
 ##FORMAT=<ID=GP,Type=Float,Number=.,Description="Genotype probabilities">
 ##FORMAT=<ID=HP,Type=Float,Number=.,Description="Haplotype probabilities">
 #CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	sample_0	sample_1	sample_2	sample_3
 01	1	V1	A	G	.	.	.	GT:GP	0:1,0	0/0:1,0,0	0/0:1,0,0	0/1:0,1,0
-01	2	V2,V2.1	A	G	.	.	.	GT:GP	0:1,0	0:1,0	0:1,0	1:0,1
+01	2	V2;V2.1	A	G	.	.	.	GT:GP	0:1,0	0:1,0	0:1,0	1:0,1
 01	3	V3	A	G	.	.	.	GT:HP	0:1,0	1|1:0,1,0,1	0|0:1,0,1,0	0|1:1,0,0,1
 01	4	M4	A	G,T	.	.	.	GT:GP	0:1,0,0	0/0:1,0,0,0,0,0	0/1:0,1,0,0,0,0	0/2:0,0,0,1,0,0
 01	5	M5	A	G	.	.	.	GT:HP	0:1,0	0|0|0:1,0,1,0,1,0	0|0|1:1,0,1,0,0,1	0|1:1,0,0,1
 01	7	M6	A	G,GT,GTT	.	.	.	GT:GP	0:1,0,0,0	1:0,1,0,0	2:0,0,1,0	3:0,0,0,1
 01	7	M7	A	G,GT,GTT,GTTT,GTTTT	.	.	.	GT:GP	0:1,0,0,0,0,0	3:0,0,0,1,0,0	4:0,0,0,0,1,0	5:0,0,0,0,0,1
 01	8	M8	A	G,GT,GTT,GTTT,GTTTT,GTTTTT	.	.	.	GT:GP	0:1,0,0,0,0,0,0	3:0,0,0,1,0,0,0	4:0,0,0,0,1,0,0	5:0,0,0,0,0,1,0
 01	9	M9	A	G,GT,GTT,GTTT,GTTTT,GTTTTT,GTTTTTT	.	.	.	GT:GP	0:1,0,0,0,0,0,0,0	6:0,0,0,0,0,0,1,0	4:0,0,0,0,1,0,0,0	1/5:0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
 01	10	M10	A	G	.	.	.	GT:GP	0/0/0/0:1,0,0,0,0	0/0/0/1:0,1,0,0,0	0/0/1/1:0,0,1,0,0	0/1/1/1:0,0,0,1,0

ADDED   release/test/data/correlation.sample
Index: release/test/data/correlation.sample
==================================================================
--- release/test/data/correlation.sample
+++ release/test/data/correlation.sample
@@ -0,0 +1,6 @@
+id
+0
+sample_0
+sample_1
+sample_2
+sample_3

ADDED   release/test/data/correlation.vcf
Index: release/test/data/correlation.vcf
==================================================================
--- release/test/data/correlation.vcf
+++ release/test/data/correlation.vcf
@@ -0,0 +1,20 @@
+##fileformat=VCFv4.2
+##FORMAT=<ID=GT,Type=String,Number=1,Description="Threshholded genotype call">
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	sample_1	sample_2	sample_3	sample_4
+1	1	RS1	A	G	.	.	.	GT	0	0	0	0
+1	2	RS2	A	G	.	.	.	GT	0	0	0	1
+1	3	RS3	A	G	.	.	.	GT	0	0	1	0
+1	4	RS4	A	G	.	.	.	GT	0	0	1	1
+1	5	RS5	A	G	.	.	.	GT	0	1	0	0
+1	6	RS6	A	G	.	.	.	GT	0	1	0	1
+1	7	RS7	A	G	.	.	.	GT	0	1	1	0
+1	8	RS8	A	G	.	.	.	GT	0	1	1	1
+1	9	RS9	A	G	.	.	.	GT	1	0	0	0
+1	10	RS10	A	G	.	.	.	GT	1	0	0	1
+1	11	RS11	A	G	.	.	.	GT	1	0	1	0
+1	12	RS12	A	G	.	.	.	GT	1	0	1	1
+1	13	RS13	A	G	.	.	.	GT	1	1	0	0
+1	14	RS14	A	G	.	.	.	GT	1	1	0	1
+1	15	RS15	A	G	.	.	.	GT	1	1	1	0
+1	16	RS16	A	G	.	.	.	GT	1	1	1	1
+1	17	RS17	A	G	.	.	.	GT	1/1	1/1	1/1	1/1

Index: release/test/data/diploid.converted.vcf
==================================================================
--- release/test/data/diploid.converted.vcf
+++ release/test/data/diploid.converted.vcf
@@ -1,12 +1,12 @@
 ##fileformat=VCFv4.2
 ##FORMAT=<ID=GP,Type=Float,Number=G,Description="Genotype call probabilities">
 ##FORMAT=<ID=GT,Type=String,Number=1,Description="Genotype call probabilities, threshholded at 0.90">
 #CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	sample_0	sample_1
-1	1	rs1,SNP1	A	G	.	.	.	GT:GP	./.:0,0,0	./.:0,0,0
-X	1	rs1,SNP1	A	G	.	.	.	GT:GP	./.:0,0,0	.:0,0
-1	1	rs1,SNP1	A	G	.	.	.	GT:GP	0/0:1,0,0	0/0:1,0,0
-X	1	rs1,SNP1	A	G	.	.	.	GT:GP	0/0:1,0,0	0:1,0
-1	1	rs1,SNP1	A	G	.	.	.	GT:GP	0/1:0,1,0	0/1:0,1,0
-X	1	rs1,SNP1	A	G	.	.	.	GT:GP	0/1:0,1,0	1:0,1
-1	1	rs1,SNP1	A	G	.	.	.	GT:GP	1/1:0,0,1	1/1:0,0,1
-X	1	rs1,SNP1	A	G	.	.	.	GT:GP	1/1:0,0,1	1:0,1
+1	1	rs1;SNP1	A	G	.	.	.	GT:GP	./.:0,0,0	./.:0,0,0
+X	1	rs1;SNP1	A	G	.	.	.	GT:GP	./.:0,0,0	.:0,0
+1	1	rs1;SNP1	A	G	.	.	.	GT:GP	0/0:1,0,0	0/0:1,0,0
+X	1	rs1;SNP1	A	G	.	.	.	GT:GP	0/0:1,0,0	0:1,0
+1	1	rs1;SNP1	A	G	.	.	.	GT:GP	0/1:0,1,0	0/1:0,1,0
+X	1	rs1;SNP1	A	G	.	.	.	GT:GP	0/1:0,1,0	1:0,1
+1	1	rs1;SNP1	A	G	.	.	.	GT:GP	1/1:0,0,1	1/1:0,0,1
+X	1	rs1;SNP1	A	G	.	.	.	GT:GP	1/1:0,0,1	1:0,1

Index: release/test/data/diploid.vcf
==================================================================
--- release/test/data/diploid.vcf
+++ release/test/data/diploid.vcf
@@ -1,12 +1,12 @@
 ##fileformat=VCFv4.2
 ##FORMAT=<ID=GP,Type=Float,Number=G,Description="Genotype call probabilities">
 ##FORMAT=<ID=GT,Type=String,Number=1,Description="Genotype call probabilities, threshholded at 0.90">
 #CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	sample_0	sample_1
-1	1	rs1,SNP1	A	G	.	.	.	GT:GP	./.:0,0,0	./.:0,0,0
-X	1	rs1,SNP1	A	G	.	.	.	GT:GP	./.:0,0,0	./.:0,0,0
-1	1	rs1,SNP1	A	G	.	.	.	GT:GP	0/0:1,0,0	0/0:1,0,0
-X	1	rs1,SNP1	A	G	.	.	.	GT:GP	0/0:1,0,0	0/0:1,0,0
-1	1	rs1,SNP1	A	G	.	.	.	GT:GP	0/1:0,1,0	0/1:0,1,0
-X	1	rs1,SNP1	A	G	.	.	.	GT:GP	0/1:0,1,0	1/1:0,0,1
-1	1	rs1,SNP1	A	G	.	.	.	GT:GP	1/1:0,0,1	1/1:0,0,1
-X	1	rs1,SNP1	A	G	.	.	.	GT:GP	1/1:0,0,1	1/1:0,0,1
+1	1	rs1;SNP1	A	G	.	.	.	GT:GP	./.:0,0,0	./.:0,0,0
+X	1	rs1;SNP1	A	G	.	.	.	GT:GP	./.:0,0,0	./.:0,0,0
+1	1	rs1;SNP1	A	G	.	.	.	GT:GP	0/0:1,0,0	0/0:1,0,0
+X	1	rs1;SNP1	A	G	.	.	.	GT:GP	0/0:1,0,0	0/0:1,0,0
+1	1	rs1;SNP1	A	G	.	.	.	GT:GP	0/1:0,1,0	0/1:0,1,0
+X	1	rs1;SNP1	A	G	.	.	.	GT:GP	0/1:0,1,0	1/1:0,0,1
+1	1	rs1;SNP1	A	G	.	.	.	GT:GP	1/1:0,0,1	1/1:0,0,1
+X	1	rs1;SNP1	A	G	.	.	.	GT:GP	1/1:0,0,1	1/1:0,0,1

DELETED release/test/data/excluded_samples.txt
Index: release/test/data/excluded_samples.txt
==================================================================
--- release/test/data/excluded_samples.txt
+++ release/test/data/excluded_samples.txt
@@ -1,21 +0,0 @@
-19
-20
-21
-122
-243
-393
-394
-395
-396
-399
-400
-401
-402
-403
-404
-422
-443
-495
-497
-498
-499

ADDED   release/test/data/finemap.bgen
Index: release/test/data/finemap.bgen
==================================================================
--- release/test/data/finemap.bgen
+++ release/test/data/finemap.bgen
cannot compute difference between binary files

ADDED   release/test/data/finemap.sample
Index: release/test/data/finemap.sample
==================================================================
--- release/test/data/finemap.sample
+++ release/test/data/finemap.sample
@@ -0,0 +1,3438 @@
+ID_1 ID_2 missing bin1 cov1 pheno cov2
+0 0 0 B C B D
+ID1 GID_1 0 1 -0.605428967119456 1 One
+ID2 GID_2 0 0 0.719047788588251 0 Two
+ID3 GID_3 0 0 0.714995926265538 0 Two
+ID4 GID_4 0 0 1.01305945995539 1 One
+ID5 GID_5 0 NA 0.00772581846443526 1 Three
+ID6 GID_6 0 1 -1.1333992004489 0 One
+ID7 GID_7 0 1 0.30634939360127 0 One
+ID8 GID_8 0 0 1.07466115731821 1 Two
+ID9 GID_9 0 1 0.447075121878981 0 One
+ID10 GID_10 0 0 -1.58449283536029 0 One
+ID11 GID_11 0 1 -0.64042015701457 0 One
+ID12 GID_12 0 0 0.104427364163164 1 One
+ID13 GID_13 0 0 0.825645334480735 0 One
+ID14 GID_14 0 0 0.754276956696491 1 One
+ID15 GID_15 0 1 0.655386411861588 1 One
+ID16 GID_16 0 1 1.29558627003139 1 Two
+ID17 GID_17 0 0 -0.664737023425199 1 One
+ID18 GID_18 0 1 -0.295770348976542 1 One
+ID19 GID_19 0 1 0.940419188843138 1 Two
+ID20 GID_20 0 0 0.0648618088541766 1 One
+ID21 GID_21 0 0 0.998013273883472 0 One
+ID22 GID_22 0 1 -0.232419948377096 1 One
+ID23 GID_23 0 0 -0.674858044393886 0 Three
+ID24 GID_24 0 1 1.35841063326069 1 Two
+ID25 GID_25 0 0 -0.476812871329356 1 Two
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+ID30 GID_30 0 0 0.0417156885742874 1 One
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+ID37 GID_37 0 1 0.211742058637266 0 Three
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+ID40 GID_40 0 1 0.187507672401902 1 One
+ID41 GID_41 0 0 -0.020266845306833 0 One
+ID42 GID_42 0 0 0.199864986443873 0 Three
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+ID46 GID_46 0 1 0.277909923682996 0 Two
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+ID48 GID_48 0 0 1.16278195403829 1 One
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+ID88 GID_88 0 1 0.608313519563104 0 One
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ADDED   release/test/data/host-parasite/host.large.vcf
Index: release/test/data/host-parasite/host.large.vcf
==================================================================
--- release/test/data/host-parasite/host.large.vcf
+++ release/test/data/host-parasite/host.large.vcf
cannot compute difference between binary files

ADDED   release/test/data/host-parasite/host.vcf
Index: release/test/data/host-parasite/host.vcf
==================================================================
--- release/test/data/host-parasite/host.vcf
+++ release/test/data/host-parasite/host.vcf
@@ -0,0 +1,103 @@
+##fileformat=VCFv4.2
+##FORMAT=<ID=GT,Type=String,Number=1,Description="Genotype">
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ADDED   release/test/data/host-parasite/host_spec.txt
Index: release/test/data/host-parasite/host_spec.txt
==================================================================
--- release/test/data/host-parasite/host_spec.txt
+++ release/test/data/host-parasite/host_spec.txt
@@ -0,0 +1,101 @@
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ADDED   release/test/data/host-parasite/parasite.large.vcf
Index: release/test/data/host-parasite/parasite.large.vcf
==================================================================
--- release/test/data/host-parasite/parasite.large.vcf
+++ release/test/data/host-parasite/parasite.large.vcf
cannot compute difference between binary files

ADDED   release/test/data/host-parasite/parasite.vcf
Index: release/test/data/host-parasite/parasite.vcf
==================================================================
--- release/test/data/host-parasite/parasite.vcf
+++ release/test/data/host-parasite/parasite.vcf
@@ -0,0 +1,103 @@
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ADDED   release/test/data/host-parasite/samples.large.sample
Index: release/test/data/host-parasite/samples.large.sample
==================================================================
--- release/test/data/host-parasite/samples.large.sample
+++ release/test/data/host-parasite/samples.large.sample
@@ -0,0 +1,10002 @@
+ID cov1 cov2 discrete1 discrete2
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Index: release/test/data/host-parasite/samples.sample
==================================================================
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ADDED   release/test/data/imputed.bgen.bgi
Index: release/test/data/imputed.bgen.bgi
==================================================================
--- release/test/data/imputed.bgen.bgi
+++ release/test/data/imputed.bgen.bgi
cannot compute difference between binary files

ADDED   release/test/data/imputed.vcf
Index: release/test/data/imputed.vcf
==================================================================
--- release/test/data/imputed.vcf
+++ release/test/data/imputed.vcf
@@ -0,0 +1,105 @@
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+##FORMAT=<ID=GP,Type=Float,Number=G,Description="Genotype call probabilities">
+##FORMAT=<ID=HP,Type=Float,Number=.,Description="Haplotype call probabilities">
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+01	50000117	rs139652708,---	C	T	.	.	.	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+01	50000150	rs181929098,---	C	T	.	.	.	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+01	50000584	rs114948258,---	A	G	.	.	.	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+01	50000753	rs58621288,---	G	A	.	.	.	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+01	50002809	rs184223882,---	G	C	.	.	.	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+01	50003214	rs115284317,---	A	G	.	.	.	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+01	50003246	rs11130228,---	C	T	.	.	.	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+01	50003282	rs193180049,---	G	A	.	.	.	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+01	50003574	chr3:50003574:D,---	GAGAA	G	.	.	.	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+01	50004209	kgp5468975,	G	A	.	.	.	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+01	50004618	rs141856763,---	T	C	.	.	.	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+01	50005017	rs17598830,---	T	C	.	.	.	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+01	50005024	chr3:50005024,---	G	C	.	.	.	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+01	50005285	chr3:50005285,---	A	G	.	.	.	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+01	50005491	chr3:50005491,---	C	G	.	.	.	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+01	50005509	chr3:50005509,---	T	C	.	.	.	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+01	50005602	chr3:50005602,---	G	A	.	.	.	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+01	50005855	rs143972186,---	G	A	.	.	.	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+01	50005991	chr3:50005991,---	A	G	.	.	.	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+01	50006003	rs141438866,---	C	T	.	.	.	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+01	50006163	chr3:50006163,---	T	C	.	.	.	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+01	50007389	rs150136291,---	T	C	.	.	.	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+01	50008118	kgp11527019,	T	C	.	.	.	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+01	50008566	rs6446189,---	A	G	.	.	.	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+01	50008623	chr3:50008623:I,---	T	TGGGAGGCAGAGGTTGCG	.	.	.	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+01	50008633	rs148163568,---	A	G	.	.	.	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+01	50008861	rs183936422,---	G	A	.	.	.	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/0:1,0,0	0/0:1,0,0	0/0:1,0,0	0/0:1,0,0	0/0:1,0,0	0/0:1,0,0	0/0:1,0,0	0/0:1,0,0

ADDED   release/test/data/merge1_merged_merge2.gen
Index: release/test/data/merge1_merged_merge2.gen
==================================================================
--- release/test/data/merge1_merged_merge2.gen
+++ release/test/data/merge1_merged_merge2.gen
@@ -0,0 +1,12 @@
+01 SNP1 rs1 100 A G 0.00000 0.00000 1.00000 0.00000 1.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
+01 SNP11 rs11 101 A G 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 1.00000 0.00000 0.00000 0.00000 0.00000 0.00000
+01 SNP3 rs3 102 A G 0.00000 0.00000 1.00000 0.00000 1.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
+01 SNP6 rs6 105 A G 0.00000 0.00000 1.00000 0.00000 1.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
+02 SNP4 rs4 103 A G 0.00000 0.00000 1.00000 0.00000 1.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
+02 SNP7 rs7 106 A G 0.00000 0.00000 1.00000 0.00000 1.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
+03 SNP5 rs5 104 A G 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 0.00000 0.00000
+03 SNP5 rs5 104 A G 0.00000 0.00000 1.00000 0.00000 1.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
+04 SNP2 rs2 101 A G 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 0.00000 0.00000
+04 SNP2 rs2 101 A G 0.00000 0.00000 1.00000 0.00000 1.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
+04 SNP5 rs5 105 A G 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 0.00000 0.00000
+22 SNP22 rs22 1012 T C 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 0.00000 0.00000

ADDED   release/test/data/test.bgen.bgi
Index: release/test/data/test.bgen.bgi
==================================================================
--- release/test/data/test.bgen.bgi
+++ release/test/data/test.bgen.bgi
cannot compute difference between binary files

Index: release/test/data/test.sample-filtered.vcf
==================================================================
--- release/test/data/test.sample-filtered.vcf
+++ release/test/data/test.sample-filtered.vcf
@@ -1,14 +1,15 @@
 ##fileformat=VCFv4.2
-##FORMAT=<ID=GT,Type=String,Number=1,Description="Genotype call probabilities, threshholded at 0.90">
+##FORMAT=<ID=GT,Type=String,Number=1,Description="Threshholded genotype call">
 ##FORMAT=<ID=GP,Type=Float,Number=G,Description="Genotype call probabilities">
+##FORMAT=<ID=HP,Type=Float,Number=.,Description="Haplotype call probabilities">
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-.	2	RSID_2,DELETION_1	A	-	.	.	.	GT:GP	1/1:0.01738,0.0496834,0.932937	0/1:0.0248722,0.932815,0.0423133	1/1:0.0346227,0.0191806,0.946197	1/1:0.0624094,0.0162661,0.921324	./.:0.0890517,0.895216,0.0157321	1/1:0.020325,0.013489,0.966186	1/1:0.0395972,0.0294041,0.930999	1/1:0.044358,0.0343481,0.921294	1/1:0.0204471,0.0430152,0.936538	0/1:0.00341802,0.985199,0.0113832	1/1:0.0433356,0.0240482,0.932616	0/1:0.0309758,0.965118,0.00390631	1/1:0.0354009,0.00350958,0.961089	1/1:0.0550546,0.00799573,0.93695	./.:0.128161,0.0136263,0.858213	1/1:0.0117494,0.0384527,0.949798	1/1:0.0335241,0.0115053,0.954971	1/1:0.00808728,0.0131533,0.978759	1/1:0.00624094,0.0180819,0.975677	1/1:0.0254826,0.00527962,0.969238	1/1:0.0140383,0.00260929,0.983352	1/1:0.0257115,0.00280766,0.971481	0/1:0.0142977,0.948074,0.0376287	1/1:0.0397803,0.020325,0.939895	1/1:0.00469978,0.0087129,0.986587	1/1:0.00622568,0.0043946,0.98938	1/1:0.0304875,0.00329595,0.966217	1/1:0.0222171,0.0297246,0.948058	0/0:0.971069,0.00122072,0.0277104	0/1:0.00669871,0.992905,0.000396735	1/1:0.0358434,0.0184634,0.945693	0/1:0.000122072,0.98262,0.017258	1/1:0.0363317,0.00915541,0.954513	0/1:0.0218204,0.951232,0.0269474	1/1:0.0102693,0.00563058,0.9841	1/1:0.00459297,0.0495766,0.94583	1/1:0.0053254,0.0157015,0.978973	1/1:0.00531014,0.0009308,0.993759	1/1:0.0522011,0.00111391,0.946685	1/1:0.016434,0.00560006,0.977966	1/1:0.0626535,0.00508125,0.932265	0/0:0.966125,0.00132753,0.0325475	1/1:0.0155642,0.00569162,0.978744	1/1:0.0281987,0.00773632,0.964065	./.:0.0508278,0.0542611,0.894911	0/1:0.0184482,0.936538,0.0450141	0/1:0.0361486,0.922301,0.0415503	1/1:0.0427253,0.036408,0.920867	1/1:0.00544747,0.0174258,0.977127	1/1:0.00248722,0.0113222,0.986191	0/1:0.0112154,0.980346,0.00843824	0/1:0.00143435,0.989425,0.00914015	1/1:3.0518e-05,0.0425116,0.957458	0/1:0.0257267,0.950683,0.0235904	1/1:0.0129549,0.0670329,0.920012	1/1:0.000610361,0.0290379,0.970352	0/1:0.0255589,0.970474,0.00396735	0/1:0.0144808,0.967361,0.0181582	1/1:0.0179446,0.0391699,0.942885	0/1:0.013489,0.943526,0.0429847	1/1:0.0774548,0.0114137,0.911131	1/1:0.0176547,0.00340276,0.978943	1/1:0.0100252,0.0271458,0.962829	1/1:0.0130007,0.0141756,0.972824	0/1:0.00733959,0.94374,0.0489204	./.:0.0627604,0.0610361,0.876204	1/1:0.0270085,0.0134585,0.959533	1/1:0.00411994,0.0168002,0.97908	1/1:0.000442512,0.0492256,0.950332	1/1:0.0164492,0.0277562,0.955795	1/1:0.00375372,0.0400702,0.956176	1/1:0.00277714,0.032578,0.964645	1/1:0.0102541,0.00408942,0.985657	0/1:0.00482185,0.990936,0.00424201	0/1:0.0258946,0.956802,0.0173037	./.:0.10454,0.880644,0.0148165	0/1:0.00758373,0.991363,0.00105287	0/1:0.0429236,0.948562,0.00851453	1/1:0.00384527,0.00367742,0.992477	1/1:0.00953689,0.0267948,0.963668	0/1:0.00181582,0.978607,0.0195773	1/1:0.000167849,0.00836194,0.99147	0/1:0.0132906,0.977981,0.00872816	1/1:0.0318761,0.0043946,0.963729	1/1:0.00839246,0.000823987,0.990784	./.:0.1093,0.00549325,0.885206	1/1:0.0087129,0.0323491,0.958938	0/1:0.00701915,0.915908,0.0770733	0/1:0.033875,0.922499,0.0436255	0/1:0.0307927,0.966873,0.00233463	1/1:0.016022,0.0126802,0.971298	1/1:0.0194858,0.0150759,0.965438	1/1:0.0353704,0.0389563,0.925673	0/1:0.00387579,0.985794,0.0103304	./.:0.0982681,0.0382849,0.863447	0/1:0.00225834,0.919478,0.0782635	0/1:0.0084535,0.953399,0.0381476	1/1:0.0272221,0.0196231,0.953155	1/1:0.056733,0.0166018,0.926665	0/1:0.0204166,0.941283,0.0383001	1/1:0.0216831,0.0273442,0.950973	1/1:0.0426032,0.0204623,0.936934	1/1:0.0585031,0.0250248,0.916472	1/1:0.0142519,0.0481727,0.937575	1/1:0.00704967,0.00383001,0.98912	1/1:0.00947585,0.0287327,0.961791	1/1:0.0511177,0.000732433,0.94815	1/1:0.042359,0.0506294,0.907012	1/1:0.0280156,0.0369574,0.935027	1/1:0.0509651,0.011078,0.937957	1/1:0.0256504,0.00415045,0.970199	1/1:0.00701915,0.0359503,0.957031	1/1:0.0230716,0.0121004,0.964828	0/1:0.0615702,0.929992,0.00843824	0/1:0.0289769,0.968536,0.00248722	1/1:0.0202945,0.0614176,0.918288	1/1:0.0619211,0.0218509,0.916228	1/1:0.00706493,0.0120241,0.980911	0/0:0.991852,0.00381476,0.00433356	0/1:0.0620127,0.914351,0.0236362	./.:0.186938,0.0114137,0.801648	1/1:0.00619516,0.0135042,0.980301	0/1:0.00584421,0.956863,0.037293	1/1:0.00593576,0.0612955,0.932769	1/1:0.0269474,0.0389105,0.934142	1/1:0.0356909,0.0327001,0.931609	1/1:0.0561837,0.00373846,0.940078	1/1:0.051194,0.0157321,0.933074	1/1:0.0783246,0.019791,0.901884	1/1:0.00077821,0.0401007,0.959121	1/1:0.0106661,0.0217288,0.967605	0/1:0.0448463,0.914977,0.040177	0/1:0.00030518,0.985061,0.0146334	0/1:0.0392157,0.956313,0.00447089	1/1:0.028397,0.0646983,0.906905	./.:0.0397192,0.895521,0.0647593	1/1:0.0280766,0.0110323,0.960891	0/1:0.024979,0.916808,0.0582132	1/1:0.0502937,0.0427253,0.906981	1/1:0.0395514,0.0561379,0.904311	1/1:0.0103304,0.0181888,0.971481	1/1:0.00764477,0.0403143,0.952041	1/1:0.0191958,0.0253758,0.955428	1/1:0.00872816,0.0280919,0.96318	1/1:0.0502632,0.0229953,0.926741	1/1:0.0083772,7.62951e-05,0.991547	0/1:0.0260777,0.919432,0.05449	0/1:0.00773632,0.99173,0.000534066	1/1:0.0242466,0.0116274,0.964126	1/1:0.0219272,0.0154421,0.962631	1/1:0.0209964,0.0618448,0.917159	1/1:0.03093,0.00195315,0.967117	0/1:0.0209659,0.974426,0.00460822	1/1:0.0294194,0.0594034,0.911177	1/1:0,0.0104067,0.989593	1/1:0.00962844,0.00128176,0.98909	0/1:0.00436408,0.967391,0.0282444	0/1:0.00738537,0.981338,0.0112764	0/1:0.0208133,0.950088,0.029099	1/1:0.0267948,0.0256962,0.947509	1/1:0.0233463,0.00436408,0.97229	1/1:0.0208286,0.0184176,0.960754	0/1:0.0274662,0.93431,0.0382238	0/1:0.0214847,0.960815,0.0177005	0/1:0.0476539,0.939071,0.0132753	0/1:0.0234226,0.967468,0.00910964	0/1:0.0141909,0.951598,0.0342107	0/1:0.00419623,0.970977,0.0248264	0/1:9.15541e-05,0.920333,0.0795758	1/1:0.0109865,0.0149691,0.974044	1/1:0.0613413,0.0350805,0.903578	1/1:0.051667,0.0332952,0.915038	0/1:0.0415656,0.957153,0.00128176	0/1:0.00401312,0.985336,0.0106508	./.:0.0183719,0.14258,0.839048	0/1:0.0472572,0.91751,0.0352331	0/1:0.00512703,0.989593,0.00527962	0/1:0.0491035,0.923003,0.0278935	0/1:0.0242313,0.967636,0.00813306	0/1:0.0787366,0.920516,0.000747692	1/1:0.00521859,0.0133364,0.981445	0/1:0.0143587,0.984543,0.00109865	1/1:0.0172732,0.00381476,0.978912	1/1:0.00321965,0.0263523,0.970428	0/1:0.00369268,0.976303,0.0200046	1/1:9.15541e-05,0.0417945,0.958114	0/1:0.0061799,0.957336,0.0364843	1/1:0.0216678,0.0125124,0.96582	0/1:0.00775158,0.977035,0.0152132	0/1:0.00244144,0.988922,0.00863661	1/1:0.0396735,0.043595,0.916732	0/1:0.0195621,0.960113,0.020325	0/1:0.0713817,0.927718,0.000900282	./.:0.0410315,0.0697642,0.889204	1/1:0.00047303,0.0628214,0.936706	./.:0.103883,0.880873,0.0152438	0/1:0.0398718,0.951812,0.00831617	1/1:0.0253605,0.00296025,0.971679	./.:0.118563,0.848753,0.0326848	1/1:0.0081178,0.0224002,0.969482	1/1:0.018555,0.0335241,0.947921	./.:0.0906538,0.0255131,0.883833	1/1:0.0112459,0.005066,0.983688	1/1:0.0144808,0.0299535,0.955566	1/1:0.0339361,0.00434882,0.961715	1/1:0.0326543,0.0330816,0.934264	1/1:0.0243076,0.00973526,0.965957	0/1:0.00430304,0.973068,0.0226291	1/1:0.0120546,0.0607004,0.927245	0/1:0.0210422,0.938552,0.0404059	1/1:0.0493324,0.029221,0.921447	1/1:0.000656138,0.00218204,0.997162	./.:0.103258,0.0205539,0.876188	0/1:0.037995,0.944259,0.0177462	1/1:0.0672465,0.00733959,0.925414	1/1:0.018967,0.0332647,0.947768	./.:0.0797284,0.898009,0.0222629	1/1:0.0217441,0.0204776,0.957778	1/1:0.00489815,0.022385,0.972717	1/1:0.0415198,0.0458381,0.912642	0/1:0.0105745,0.963699,0.0257267	0/0:0.937316,0.00723278,0.0554513	0/1:0.0315404,0.951812,0.0166476	1/1:0.0389868,0.0166018,0.944411	1/1:0.0034638,0.0493477,0.947189	1/1:0.0233768,0.00468452,0.971939	1/1:0.0436103,0.0396124,0.916777	0/1:0.0205386,0.917876,0.0615854	1/1:0.0468147,0.00898756,0.944198	1/1:0.00564584,0.0172885,0.977066	1/1:0.00151064,0.00062562,0.997864	1/1:0.0466163,0.0382849,0.915099	1/1:0.0277867,0.00753796,0.964675	./.:0.047837,0.111208,0.840955	1/1:0.0529335,0.0445869,0.90248	1/1:0.0281987,0.0180056,0.953796	1/1:0.0139315,0.0069276,0.979141	1/1:0.045243,0.0136263,0.941131	./.:0.102541,0.0259403,0.871519	0/1:0.0446632,0.931563,0.0237736	0/1:0.0442054,0.948333,0.00746166	1/1:0.00399786,0.0289464,0.967056	0/0:0.947982,0.0354162,0.0166018	1/1:0.00653086,0.00578317,0.987686	./.:0.867033,0.0902571,0.04271	1/1:0.0643931,0.0188754,0.916732	1/1:0.000839246,0.00590524,0.993256	1/1:0.0630961,0.0310063,0.905898	0/1:0.0458686,0.949035,0.00509651	0/1:0.0172885,0.959731,0.0229801	1/1:0.007187,0.0334173,0.959396	0/1:0.0166476,0.982376,0.000976577	./.:0.00849928,0.853574,0.137926	1/1:0.00480659,0.0209354,0.974258	1/1:0.00889601,0.012665,0.978439	1/1:0.0367285,0.00135805,0.961913	1/1:0.045716,0.0368658,0.917418	1/1:0.0287327,0.0232853,0.947982	./.:0.00381476,0.222095,0.77409	1/1:0.00280766,0.0105745,0.986618	1/1:0.0326238,0.0386664,0.92871	0/1:0.0466621,0.946868,0.00646983	0/1:0.00527962,0.979141,0.0155795	1/1:0.00265507,0.0386511,0.958694	0/1:0.051545,0.938308,0.0101472	1/1:0.0495918,0.00187686,0.948531	1/1:0.00341802,0.0184482,0.978134	0/1:0.0377661,0.93312,0.0291142	1/1:0.00210575,0.0745403,0.923354	1/1:0.0371862,0.00549325,0.957321	1/1:0.00926223,0.0117189,0.979019	1/1:0.0141451,0.0375525,0.948302	1/1:0.00123598,0.00427253,0.994491	./.:0.00274662,0.0974746,0.899779	0/1:0.000167849,0.947448,0.0523842	./.:0.0343175,0.0812696,0.884413	0/1:0.000640879,0.994598,0.00476081	1/1:0.0564889,0.0069276,0.936584	1/1:0.00259403,0.0374456,0.95996	./.:0.00910964,0.110048,0.880842	1/1:0.0120394,0.00703441,0.980926	1/1:0.0766003,0.00494392,0.918456	1/1:0.000717174,0.000671397,0.998611	1/1:0.0107576,0.00694285,0.9823	./.:0.0809033,0.0269017,0.892195	0/1:0.0148165,0.966217,0.018967	1/1:0.00210575,0.0184329,0.979461	1/1:0.00062562,0.0234226,0.975952	0/1:0.0104982,0.97879,0.0107118	1/1:0.0159457,0.00619516,0.977859	1/1:0.0555581,0.0426642,0.901778	1/1:0.0203708,0.00343328,0.976196	1/1:0.0608072,0.016495,0.922698	0/1:0.0167086,0.980133,0.00315862	1/1:0.0218662,0.00830091,0.969833	./.:0.0666361,0.0836194,0.849744	1/1:0.013489,0.0189517,0.967559	1/1:0.00500496,0.0707103,0.924285	./.:0.110933,0.0216678,0.867399	1/1:0.024567,0.00222782,0.973205	0/0:0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-.	3	RSID_3,SNPID_3	A	G	.	.	.	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+01	2	RSID_2;DELETION_1	A	-	.	.	.	GT:GP	1/1:0.01738,0.0496834,0.932937	0/1:0.0248722,0.932815,0.0423133	1/1:0.0346227,0.0191806,0.946197	1/1:0.0624094,0.0162661,0.921324	./.:0.0890517,0.895216,0.0157321	1/1:0.020325,0.013489,0.966186	1/1:0.0395972,0.0294041,0.930999	1/1:0.044358,0.0343481,0.921294	1/1:0.0204471,0.0430152,0.936538	0/1:0.00341802,0.985199,0.0113832	1/1:0.0433356,0.0240482,0.932616	0/1:0.0309758,0.965118,0.00390631	1/1:0.0354009,0.00350958,0.961089	1/1:0.0550546,0.00799573,0.93695	./.:0.128161,0.0136263,0.858213	1/1:0.0117494,0.0384527,0.949798	1/1:0.0335241,0.0115053,0.954971	1/1:0.00808728,0.0131533,0.978759	1/1:0.00624094,0.0180819,0.975677	1/1:0.0254826,0.00527962,0.969238	1/1:0.0140383,0.00260929,0.983352	1/1:0.0257115,0.00280766,0.971481	0/1:0.0142977,0.948074,0.0376287	1/1:0.0397803,0.020325,0.939895	1/1:0.00469978,0.0087129,0.986587	1/1:0.00622568,0.0043946,0.98938	1/1:0.0304875,0.00329595,0.966217	1/1:0.0222171,0.0297246,0.948058	0/0:0.971069,0.00122072,0.0277104	0/1:0.00669871,0.992905,0.000396735	1/1:0.0358434,0.0184634,0.945693	0/1:0.000122072,0.98262,0.017258	1/1:0.0363317,0.00915541,0.954513	0/1:0.0218204,0.951232,0.0269474	1/1:0.0102693,0.00563058,0.9841	1/1:0.00459297,0.0495766,0.94583	1/1:0.0053254,0.0157015,0.978973	1/1:0.00531014,0.0009308,0.993759	1/1:0.0522011,0.00111391,0.946685	1/1:0.016434,0.00560006,0.977966	1/1:0.0626535,0.00508125,0.932265	0/0:0.966125,0.00132753,0.0325475	1/1:0.0155642,0.00569162,0.978744	1/1:0.0281987,0.00773632,0.964065	./.:0.0508278,0.0542611,0.894911	0/1:0.0184482,0.936538,0.0450141	0/1:0.0361486,0.922301,0.0415503	1/1:0.0427253,0.036408,0.920867	1/1:0.00544747,0.0174258,0.977127	1/1:0.00248722,0.0113222,0.986191	0/1:0.0112154,0.980346,0.00843824	0/1:0.00143435,0.989425,0.00914015	1/1:3.0518e-05,0.0425116,0.957458	0/1:0.0257267,0.950683,0.0235904	1/1:0.0129549,0.0670329,0.920012	1/1:0.000610361,0.0290379,0.970352	0/1:0.0255589,0.970474,0.00396735	0/1:0.0144808,0.967361,0.0181582	1/1:0.0179446,0.0391699,0.942885	0/1:0.013489,0.943526,0.0429847	1/1:0.0774548,0.0114137,0.911131	1/1:0.0176547,0.00340276,0.978943	1/1:0.0100252,0.0271458,0.962829	1/1:0.0130007,0.0141756,0.972824	0/1:0.00733959,0.94374,0.0489204	./.:0.0627604,0.0610361,0.876204	1/1:0.0270085,0.0134585,0.959533	1/1:0.00411994,0.0168002,0.97908	1/1:0.000442512,0.0492256,0.950332	1/1:0.0164492,0.0277562,0.955795	1/1:0.00375372,0.0400702,0.956176	1/1:0.00277714,0.032578,0.964645	1/1:0.0102541,0.00408942,0.985657	0/1:0.00482185,0.990936,0.00424201	0/1:0.0258946,0.956802,0.0173037	./.:0.10454,0.880644,0.0148165	0/1:0.00758373,0.991363,0.00105287	0/1:0.0429236,0.948562,0.00851453	1/1:0.00384527,0.00367742,0.992477	1/1:0.00953689,0.0267948,0.963668	0/1:0.00181582,0.978607,0.0195773	1/1:0.000167849,0.00836194,0.99147	0/1:0.0132906,0.977981,0.00872816	1/1:0.0318761,0.0043946,0.963729	1/1:0.00839246,0.000823987,0.990784	./.:0.1093,0.00549325,0.885206	1/1:0.0087129,0.0323491,0.958938	0/1:0.00701915,0.915908,0.0770733	0/1:0.033875,0.922499,0.0436255	0/1:0.0307927,0.966873,0.00233463	1/1:0.016022,0.0126802,0.971298	1/1:0.0194858,0.0150759,0.965438	1/1:0.0353704,0.0389563,0.925673	0/1:0.00387579,0.985794,0.0103304	./.:0.0982681,0.0382849,0.863447	0/1:0.00225834,0.919478,0.0782635	0/1:0.0084535,0.953399,0.0381476	1/1:0.0272221,0.0196231,0.953155	1/1:0.056733,0.0166018,0.926665	0/1:0.0204166,0.941283,0.0383001	1/1:0.0216831,0.0273442,0.950973	1/1:0.0426032,0.0204623,0.936934	1/1:0.0585031,0.0250248,0.916472	1/1:0.0142519,0.0481727,0.937575	1/1:0.00704967,0.00383001,0.98912	1/1:0.00947585,0.0287327,0.961791	1/1:0.0511177,0.000732433,0.94815	1/1:0.042359,0.0506294,0.907012	1/1:0.0280156,0.0369574,0.935027	1/1:0.0509651,0.011078,0.937957	1/1:0.0256504,0.00415045,0.970199	1/1:0.00701915,0.0359503,0.957031	1/1:0.0230716,0.0121004,0.964828	0/1:0.0615702,0.929992,0.00843824	0/1:0.0289769,0.968536,0.00248722	1/1:0.0202945,0.0614176,0.918288	1/1:0.0619211,0.0218509,0.916228	1/1:0.00706493,0.0120241,0.980911	0/0:0.991852,0.00381476,0.00433356	0/1:0.0620127,0.914351,0.0236362	./.:0.186938,0.0114137,0.801648	1/1:0.00619516,0.0135042,0.980301	0/1:0.00584421,0.956863,0.037293	1/1:0.00593576,0.0612955,0.932769	1/1:0.0269474,0.0389105,0.934142	1/1:0.0356909,0.0327001,0.931609	1/1:0.0561837,0.00373846,0.940078	1/1:0.051194,0.0157321,0.933074	1/1:0.0783246,0.019791,0.901884	1/1:0.00077821,0.0401007,0.959121	1/1:0.0106661,0.0217288,0.967605	0/1:0.0448463,0.914977,0.040177	0/1:0.00030518,0.985061,0.0146334	0/1:0.0392157,0.956313,0.00447089	1/1:0.028397,0.0646983,0.906905	./.:0.0397192,0.895521,0.0647593	1/1:0.0280766,0.0110323,0.960891	0/1:0.024979,0.916808,0.0582132	1/1:0.0502937,0.0427253,0.906981	1/1:0.0395514,0.0561379,0.904311	1/1:0.0103304,0.0181888,0.971481	1/1:0.00764477,0.0403143,0.952041	1/1:0.0191958,0.0253758,0.955428	1/1:0.00872816,0.0280919,0.96318	1/1:0.0502632,0.0229953,0.926741	1/1:0.0083772,7.62951e-05,0.991547	0/1:0.0260777,0.919432,0.05449	0/1:0.00773632,0.99173,0.000534066	1/1:0.0242466,0.0116274,0.964126	1/1:0.0219272,0.0154421,0.962631	1/1:0.0209964,0.0618448,0.917159	1/1:0.03093,0.00195315,0.967117	0/1:0.0209659,0.974426,0.00460822	1/1:0.0294194,0.0594034,0.911177	1/1:0,0.0104067,0.989593	1/1:0.00962844,0.00128176,0.98909	0/1:0.00436408,0.967391,0.0282444	0/1:0.00738537,0.981338,0.0112764	0/1:0.0208133,0.950088,0.029099	1/1:0.0267948,0.0256962,0.947509	1/1:0.0233463,0.00436408,0.97229	1/1:0.0208286,0.0184176,0.960754	0/1:0.0274662,0.93431,0.0382238	0/1:0.0214847,0.960815,0.0177005	0/1:0.0476539,0.939071,0.0132753	0/1:0.0234226,0.967468,0.00910964	0/1:0.0141909,0.951598,0.0342107	0/1:0.00419623,0.970977,0.0248264	0/1:9.15541e-05,0.920333,0.0795758	1/1:0.0109865,0.0149691,0.974044	1/1:0.0613413,0.0350805,0.903578	1/1:0.051667,0.0332952,0.915038	0/1:0.0415656,0.957153,0.00128176	0/1:0.00401312,0.985336,0.0106508	./.:0.0183719,0.14258,0.839048	0/1:0.0472572,0.91751,0.0352331	0/1:0.00512703,0.989593,0.00527962	0/1:0.0491035,0.923003,0.0278935	0/1:0.0242313,0.967636,0.00813306	0/1:0.0787366,0.920516,0.000747692	1/1:0.00521859,0.0133364,0.981445	0/1:0.0143587,0.984543,0.00109865	1/1:0.0172732,0.00381476,0.978912	1/1:0.00321965,0.0263523,0.970428	0/1:0.00369268,0.976303,0.0200046	1/1:9.15541e-05,0.0417945,0.958114	0/1:0.0061799,0.957336,0.0364843	1/1:0.0216678,0.0125124,0.96582	0/1:0.00775158,0.977035,0.0152132	0/1:0.00244144,0.988922,0.00863661	1/1:0.0396735,0.043595,0.916732	0/1:0.0195621,0.960113,0.020325	0/1:0.0713817,0.927718,0.000900282	./.:0.0410315,0.0697642,0.889204	1/1:0.00047303,0.0628214,0.936706	./.:0.103883,0.880873,0.0152438	0/1:0.0398718,0.951812,0.00831617	1/1:0.0253605,0.00296025,0.971679	./.:0.118563,0.848753,0.0326848	1/1:0.0081178,0.0224002,0.969482	1/1:0.018555,0.0335241,0.947921	./.:0.0906538,0.0255131,0.883833	1/1:0.0112459,0.005066,0.983688	1/1:0.0144808,0.0299535,0.955566	1/1:0.0339361,0.00434882,0.961715	1/1:0.0326543,0.0330816,0.934264	1/1:0.0243076,0.00973526,0.965957	0/1:0.00430304,0.973068,0.0226291	1/1:0.0120546,0.0607004,0.927245	0/1:0.0210422,0.938552,0.0404059	1/1:0.0493324,0.029221,0.921447	1/1:0.000656138,0.00218204,0.997162	./.:0.103258,0.0205539,0.876188	0/1:0.037995,0.944259,0.0177462	1/1:0.0672465,0.00733959,0.925414	1/1:0.018967,0.0332647,0.947768	./.:0.0797284,0.898009,0.0222629	1/1:0.0217441,0.0204776,0.957778	1/1:0.00489815,0.022385,0.972717	1/1:0.0415198,0.0458381,0.912642	0/1:0.0105745,0.963699,0.0257267	0/0:0.937316,0.00723278,0.0554513	0/1:0.0315404,0.951812,0.0166476	1/1:0.0389868,0.0166018,0.944411	1/1:0.0034638,0.0493477,0.947189	1/1:0.0233768,0.00468452,0.971939	1/1:0.0436103,0.0396124,0.916777	0/1:0.0205386,0.917876,0.0615854	1/1:0.0468147,0.00898756,0.944198	1/1:0.00564584,0.0172885,0.977066	1/1:0.00151064,0.00062562,0.997864	1/1:0.0466163,0.0382849,0.915099	1/1:0.0277867,0.00753796,0.964675	./.:0.047837,0.111208,0.840955	1/1:0.0529335,0.0445869,0.90248	1/1:0.0281987,0.0180056,0.953796	1/1:0.0139315,0.0069276,0.979141	1/1:0.045243,0.0136263,0.941131	./.:0.102541,0.0259403,0.871519	0/1:0.0446632,0.931563,0.0237736	0/1:0.0442054,0.948333,0.00746166	1/1:0.00399786,0.0289464,0.967056	0/0:0.947982,0.0354162,0.0166018	1/1:0.00653086,0.00578317,0.987686	./.:0.867033,0.0902571,0.04271	1/1:0.0643931,0.0188754,0.916732	1/1:0.000839246,0.00590524,0.993256	1/1:0.0630961,0.0310063,0.905898	0/1:0.0458686,0.949035,0.00509651	0/1:0.0172885,0.959731,0.0229801	1/1:0.007187,0.0334173,0.959396	0/1:0.0166476,0.982376,0.000976577	./.:0.00849928,0.853574,0.137926	1/1:0.00480659,0.0209354,0.974258	1/1:0.00889601,0.012665,0.978439	1/1:0.0367285,0.00135805,0.961913	1/1:0.045716,0.0368658,0.917418	1/1:0.0287327,0.0232853,0.947982	./.:0.00381476,0.222095,0.77409	1/1:0.00280766,0.0105745,0.986618	1/1:0.0326238,0.0386664,0.92871	0/1:0.0466621,0.946868,0.00646983	0/1:0.00527962,0.979141,0.0155795	1/1:0.00265507,0.0386511,0.958694	0/1:0.051545,0.938308,0.0101472	1/1:0.0495918,0.00187686,0.948531	1/1:0.00341802,0.0184482,0.978134	0/1:0.0377661,0.93312,0.0291142	1/1:0.00210575,0.0745403,0.923354	1/1:0.0371862,0.00549325,0.957321	1/1:0.00926223,0.0117189,0.979019	1/1:0.0141451,0.0375525,0.948302	1/1:0.00123598,0.00427253,0.994491	./.:0.00274662,0.0974746,0.899779	0/1:0.000167849,0.947448,0.0523842	./.:0.0343175,0.0812696,0.884413	0/1:0.000640879,0.994598,0.00476081	1/1:0.0564889,0.0069276,0.936584	1/1:0.00259403,0.0374456,0.95996	./.:0.00910964,0.110048,0.880842	1/1:0.0120394,0.00703441,0.980926	1/1:0.0766003,0.00494392,0.918456	1/1:0.000717174,0.000671397,0.998611	1/1:0.0107576,0.00694285,0.9823	./.:0.0809033,0.0269017,0.892195	0/1:0.0148165,0.966217,0.018967	1/1:0.00210575,0.0184329,0.979461	1/1:0.00062562,0.0234226,0.975952	0/1:0.0104982,0.97879,0.0107118	1/1:0.0159457,0.00619516,0.977859	1/1:0.0555581,0.0426642,0.901778	1/1:0.0203708,0.00343328,0.976196	1/1:0.0608072,0.016495,0.922698	0/1:0.0167086,0.980133,0.00315862	1/1:0.0218662,0.00830091,0.969833	./.:0.0666361,0.0836194,0.849744	1/1:0.013489,0.0189517,0.967559	1/1:0.00500496,0.0707103,0.924285	./.:0.110933,0.0216678,0.867399	1/1:0.024567,0.00222782,0.973205	0/0:0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+01	3	RSID_3;SNPID_3	A	G	.	.	.	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Index: release/test/data/test.twice.vcf
==================================================================
--- release/test/data/test.twice.vcf
+++ release/test/data/test.twice.vcf
cannot compute difference between binary files

Index: release/test/data/test.v4.1.vcf
==================================================================
--- release/test/data/test.v4.1.vcf
+++ release/test/data/test.v4.1.vcf
@@ -1,15 +1,15 @@
 ##fileformat=VCFv4.1
 ##FORMAT=<ID=GT,Type=String,Number=1,Description="Genotype call probabilities, threshholded at 0.90">
 ##FORMAT=<ID=GP,Type=Float,Number=G,Description="Genotype call probabilities">
 ##FORMAT=<ID=XY,Type=Float,Number=2,Description="Chip intensities">
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-NA	2	RSID_2,DELETION_1	A	-	.	.	.	GT:GP	1/1:0.0765213,0.00738931,0.916089	1/1:0.0278117,0.00864292,0.963545	1/1:0.0173777,0.0496874,0.932935	0/1:0.0248777,0.932817,0.0423053	1/1:0.0346175,0.0191856,0.946197	1/1:0.0624116,0.0162715,0.921317	./.:0.0890426,0.89522,0.0157372	1/1:0.0203313,0.013491,0.966178	1/1:0.0395959,0.0294134,0.930991	1/1:0.0443588,0.0343402,0.921301	1/1:0.0413977,0.0547565,0.903846	./.:0.0833462,0.0513328,0.865321	1/1:0.0204448,0.0430211,0.936534	0/1:0.00342552,0.985194,0.0113801	0/1:0.00726573,0.991422,0.00131274	1/1:0.00212978,0.0130744,0.984796	1/1:0.0433437,0.0240446,0.932612	0/1:0.030966,0.96512,0.00391444	1/1:0.0354075,0.00350694,0.961086	1/1:0.0308428,0.045246,0.923911	1/1:0.0550592,0.00799191,0.936949	./.:0.128164,0.0136164,0.858219	1/1:0.0117565,0.0384459,0.949798	1/1:0.0335148,0.0115101,0.954975	1/1:0.00809348,0.0131524,0.978754	1/1:0.00623515,0.0180752,0.97569	1/1:0.0146414,0.0125058,0.972853	1/1:0.025476,0.00528723,0.969237	1/1:0.00211196,0.0579454,0.939943	1/1:0.0140452,0.00261017,0.983345	1/1:0.0355083,0.0597193,0.904772	1/1:0.0257136,0.00281197,0.971474	0/1:0.0142856,0.948082,0.0376327	1/1:0.0397819,0.0203298,0.939888	1/1:0.00470346,0.00871748,0.986579	1/1:0.00622709,0.00439993,0.989373	1/1:0.0452334,0.0078768,0.94689	0/1:0.0751067,0.922155,0.002738	1/1:0.0304864,0.00329875,0.966215	1/1:0.022215,0.0297167,0.948068	0/0:0.971078,0.00121635,0.0277058	0/1:0.00669808,0.992912,0.000390372	1/1:0.00366201,0.00229824,0.99404	1/1:0.0358488,0.0184567,0.945695	0/1:0.000127906,0.982611,0.0172609	0/1:0.0269364,0.967933,0.00513028	1/1:0.0363318,0.0091488,0.954519	0/1:0.0218157,0.951233,0.0269512	1/1:0.0102727,0.00562367,0.984104	1/1:0.00458934,0.0495853,0.945825	1/1:0.00532228,0.0157015,0.978976	1/1:0.0053079,0.000927737,0.993764	1/1:0.0264865,0.0254771,0.948036	1/1:0.0522013,0.00111124,0.946687	1/1:0.0164378,0.00560304,0.977959	1/1:0.0626507,0.00508806,0.932261	0/1:0.00161383,0.979377,0.0190092	0/0:0.966122,0.00132746,0.0325505	1/1:0.0155659,0.00569339,0.978741	1/1:0.0202013,0.000290894,0.979508	1/1:0.0281994,0.00773169,0.964069	./.:0.0508201,0.0542616,0.894918	0/1:0.0310162,0.941976,0.0270078	1/1:0.0455028,0.0162002,0.938297	0/1:0.0184549,0.936524,0.045021	0/1:0.0361544,0.922292,0.0415535	1/1:0.0427266,0.036398,0.920875	1/1:0.00544581,0.017418,0.977136	1/1:0.00248236,0.0113308,0.986187	0/1:0.0112173,0.980356,0.00842722	0/1:0.00144022,0.989422,0.00913776	1/1:3.11376e-05,0.0425171,0.957452	1/1:0.0187048,0.0104851,0.97081	1/1:0.00624943,0.035127,0.958624	0/1:0.0257277,0.950684,0.023588	1/1:0.01295,0.0670332,0.920017	1/1:0.0165091,0.0414055,0.942085	1/1:0.000603927,0.0290382,0.970358	0/1:0.0255638,0.970474,0.00396241	0/1:0.0144861,0.967365,0.0181491	1/1:0.00461234,0.0602488,0.935139	1/1:0.0382218,0.00626481,0.955513	1/1:0.0596664,0.0231397,0.917194	1/1:0.0179393,0.0391777,0.942883	0/1:0.0134928,0.943517,0.0429902	1/1:0.0774595,0.0114083,0.911132	1/1:0.0176584,0.00339778,0.978944	1/1:0.0100261,0.0271536,0.96282	1/1:0.0130068,0.0141708,0.972822	0/1:0.00734218,0.943733,0.0489247	./.:0.062756,0.0610352,0.876209	1/1:0.0270041,0.0134642,0.959532	1/1:0.00411924,0.0168011,0.97908	./.:0.0515086,0.887631,0.0608606	0/1:0.0135331,0.978956,0.00751137	1/1:0.0307017,0.000968173,0.96833	1/1:0.0153662,0.0120846,0.972549	1/1:0.00044704,0.0492262,0.950327	./.:0.110592,0.00344009,0.885968	1/1:0.0164569,0.0277545,0.955789	1/1:0.00375503,0.0400653,0.95618	1/1:0.00276732,0.0325795,0.964653	0/1:0.0317738,0.954008,0.0142186	./.:0.0332177,0.0885011,0.878281	./.:0.0779957,0.0638195,0.858185	1/1:0.00664966,0.0874973,0.905853	0/1:0.00581931,0.970621,0.0235596	1/1:0.0102489,0.00409048,0.985661	./.:0.00252458,0.118531,0.878945	0/1:0.00481888,0.990939,0.00424204	1/1:0.0142779,0.014817,0.970905	0/1:0.00742485,0.979232,0.0133436	0/1:0.0259031,0.956843,0.0172542	./.:0.104541,0.880652,0.014807	1/1:0.0694247,0.0148819,0.915693	0/1:0.00757589,0.99137,0.00105374	0/1:0.0429337,0.948554,0.00851256	1/1:0.00232002,0.0135248,0.984155	1/1:0.00385322,0.00367388,0.992473	0/1:0.0191218,0.970571,0.010307	1/1:0.00953562,0.026791,0.963673	0/1:0.0018121,0.978612,0.0195761	1/1:0.00221615,0.000487307,0.997297	1/1:0.000169594,0.00836001,0.99147	0/1:0.0132875,0.977977,0.00873553	1/1:0.0318824,0.0044041,0.963714	1/1:0.00838779,0.000825634,0.990787	./.:0.109297,0.00548867,0.885215	1/1:0.00871124,0.0323483,0.95894	0/1:0.00702381,0.915908,0.0770681	1/1:0.0211908,0.0483898,0.930419	0/1:0.0338834,0.922492,0.0436242	0/1:0.030799,0.966864,0.00233682	1/1:0.0160218,0.0126794,0.971299	1/1:0.00806931,0.00963224,0.982298	1/1:0.0194903,0.0150679,0.965442	1/1:0.035366,0.0389562,0.925678	1/1:0.00267017,0.0382586,0.959071	0/1:0.00388209,0.985784,0.010334	./.:0.0982637,0.0382897,0.863447	0/1:0.0022618,0.919474,0.0782647	1/1:2.49412e-05,0.0167737,0.983201	./.:0.0582512,0.0492292,0.89252	0/1:0.00845342,0.953394,0.0381527	1/1:0.0272179,0.0196223,0.95316	1/1:0.0567382,0.0166038,0.926658	./.:0.12687,0.872336,0.000794047	0/1:0.0204258,0.941278,0.0382964	1/1:0.0232436,0.00367961,0.973077	0/1:0.00880893,0.921912,0.0692794	1/1:0.0216899,0.0273385,0.950972	1/1:0.0426108,0.0204562,0.936933	0/1:0.0104113,0.970103,0.0194862	1/1:0.058506,0.0250296,0.916464	1/1:0.0142527,0.0481697,0.937578	1/1:0.0352332,0.00821716,0.95655	1/1:0.00704378,0.00383585,0.98912	0/1:0.0618883,0.923708,0.0144034	1/1:0.00947037,0.028737,0.961793	0/1:0.0358306,0.959207,0.0049623	1/1:0.0419056,0.00609378,0.952001	1/1:0.0511185,0.00073821,0.948143	1/1:0.0235176,0.0614284,0.915054	1/1:0.0423645,0.050623,0.907012	1/1:0.01013,0.0889667,0.900903	1/1:0.00197436,0.0733078,0.924718	./.:0.0783761,0.0315562,0.890068	1/1:0.0635035,0.0172963,0.9192	1/1:0.0394675,0.00484857,0.955684	1/1:0.0249377,0.021648,0.953414	0/1:0.0118272,0.95642,0.0317532	1/1:0.0132819,0.0262284,0.96049	1/1:0.0203168,0.0178358,0.961847	1/1:0.0280182,0.0369552,0.935027	1/1:0.050963,0.0110882,0.937949	1/1:0.0256438,0.00415634,0.9702	1/1:0.0140764,0.0479012,0.938022	1/1:0.00702359,0.0359428,0.957034	1/1:0.0230789,0.0120966,0.964825	0/1:0.0615742,0.929984,0.0084413	0/1:0.028977,0.968539,0.00248423	1/1:0.0202895,0.0614246,0.918286	1/1:0.0282214,0.0483363,0.923442	1/1:0.0619251,0.0218439,0.916231	1/1:0.00706208,0.0120217,0.980916	0/1:0.00640163,0.961214,0.032384	0/0:0.991858,0.00380923,0.00433243	./.:0.0470269,0.082571,0.870402	0/1:0.0519842,0.944215,0.00380044	0/1:0.0620133,0.914345,0.0236416	./.:0.186934,0.0114153,0.80165	1/1:0.000345943,0.0235675,0.976087	1/1:0.0326442,0.00235391,0.965002	1/1:0.00532184,0.0183645,0.976314	0/1:0.00903543,0.965256,0.0257083	1/1:0.00619173,0.0135111,0.980297	0/1:0.00584457,0.95686,0.0372956	1/1:0.00593699,0.0612912,0.932772	1/1:0.0269436,0.0389198,0.934137	1/1:0.0356937,0.0327066,0.9316	1/1:0.0561839,0.00373752,0.940079	1/1:0.0511941,0.0157286,0.933077	1/1:0.078324,0.0198007,0.901875	1/1:0.000779039,0.0401042,0.959117	1/1:0.0106681,0.0217184,0.967614	0/1:0.0448439,0.914974,0.0401817	0/1:0.00030371,0.985059,0.0146377	0/1:0.039209,0.956317,0.00447422	1/1:0.0284045,0.0646966,0.906899	./.:0.0397172,0.895523,0.0647601	0/0:0.981547,0.00240078,0.0160523	1/1:0.00361121,0.00497761,0.991411	1/1:0.0280749,0.0110312,0.960894	1/1:0.0253983,0.0222725,0.952329	1/1:0.0397773,0.0458102,0.914413	0/1:0.0249766,0.916817,0.0582059	1/1:0.0503006,0.0427178,0.906982	0/1:0.0461137,0.935709,0.0181774	1/1:0.0395516,0.0561328,0.904316	1/1:0.0103299,0.0181879,0.971482	1/1:0.0076416,0.0403221,0.952036	1/1:0.019195,0.0253848,0.95542	1/1:0.00872853,0.0280844,0.963187	1/1:0.0220789,0.0640545,0.913867	1/1:0.0502671,0.0229983,0.926735	1/1:0.00837678,7.85657e-05,0.991545	./.:0.00126481,0.85077,0.147965	0/1:0.0260687,0.919439,0.0544925	0/1:0.00773965,0.991731,0.000528911	1/1:0.0242448,0.011632,0.964123	1/1:0.0448744,0.00833587,0.94679	1/1:0.0195972,0.00775482,0.972648	./.:0.094565,0.0196051,0.88583	1/1:0.0219288,0.0154441,0.962627	0/1:0.0128967,0.980922,0.00618099	1/1:0.0133328,0.0111186,0.975549	1/1:0.0209894,0.0618488,0.917162	1/1:0.0309362,0.00195092,0.967113	0/1:0.0209576,0.97443,0.00461241	1/1:0.0215581,0.0119414,0.9665	1/1:0.0294206,0.0593992,0.91118	1/1:0.0431204,0.0414609,0.915419	1/1:6.64084e-07,0.0104027,0.989597	1/1:0.0264899,0.00513652,0.968374	1/1:0.00962836,0.0012802,0.989091	1/1:0.00262166,0.0280628,0.969316	0/1:0.00436423,0.967383,0.0282524	0/1:0.0166533,0.972714,0.0106325	0/1:0.00737717,0.981342,0.0112812	0/1:0.0208076,0.950085,0.0291073	1/1:0.0173471,0.00669082,0.975962	1/1:0.026793,0.0257043,0.947503	1/1:0.0233496,0.00436309,0.972287	1/1:0.0208317,0.0184149,0.960753	0/1:0.0274726,0.934305,0.0382225	0/1:0.021481,0.960822,0.0176974	0/1:0.0476554,0.939072,0.0132728	0/1:0.0234288,0.967458,0.0091133	0/1:0.0141893,0.951599,0.034212	0/1:0.00419246,0.970974,0.024834	0/1:8.37918e-05,0.920339,0.0795777	1/1:0.0109809,0.0149742,0.974045	1/1:0.0613423,0.0350763,0.903581	1/1:0.0516634,0.0332994,0.915037	0/1:0.0415676,0.957151,0.00128121	0/1:0.0040198,0.985329,0.0106516	./.:0.0183737,0.14258,0.839047	1/1:0.00407833,0.0247806,0.971141	1/1:0.00978301,0.0359626,0.954254	0/1:0.047259,0.917512,0.0352294	0/1:0.0051346,0.989586,0.00527964	0/1:0.0388345,0.952014,0.00915128	0/1:0.0490986,0.923002,0.0278998	0/1:0.0242299,0.967634,0.00813596	0/1:0.0787345,0.920511,0.000754718	1/1:0.00522087,0.0133353,0.981444	0/1:0.00489867,0.978843,0.016258	1/1:0.00542466,0.00122524,0.99335	0/1:0.0143657,0.984541,0.00109371	1/1:0.00252614,0.0177165,0.979757	1/1:0.0730979,0.0046939,0.922208	1/1:0.0172776,0.00380916,0.978913	1/1:0.00321306,0.0263511,0.970436	0/0:0.986966,0.0100988,0.00293523	0/1:0.00127376,0.98952,0.0092064	0/1:0.00369403,0.976305,0.0200013	0/1:0.0418657,0.927221,0.0309128	1/1:8.66898e-05,0.0417915,0.958122	0/1:0.00617715,0.95733,0.0364927	1/1:0.0216624,0.0125235,0.965814	0/1:0.0384431,0.956619,0.00493833	./.:0.091695,0.0296694,0.878636	0/1:0.00775148,0.977032,0.0152162	0/1:0.0345039,0.96546,3.61777e-05	0/1:0.00244344,0.988914,0.00864281	1/1:0.0396826,0.0435855,0.916732	0/1:0.0195579,0.96012,0.0203217	0/1:0.0713879,0.927713,0.000898868	0/1:0.063115,0.929048,0.00783668	./.:0.0410352,0.0697608,0.889204	1/1:0.000479687,0.0628162,0.936704	./.:0.10388,0.880882,0.015238	0/1:0.0398778,0.951817,0.00830562	1/1:0.025359,0.00295701,0.971684	./.:0.118569,0.848748,0.0326829	1/1:0.00435785,0.0230209,0.972621	1/1:0.00811194,0.0224001,0.969488	1/1:0.0185575,0.0335337,0.947909	./.:0.0906568,0.0255168,0.883826	0/1:0.0403838,0.942995,0.0166211	1/1:0.00755941,0.0653485,0.927092	1/1:0.0112374,0.00507048,0.983692	1/1:0.0144833,0.0299461,0.955571	./.:0.0694543,0.0308285,0.899717	1/1:0.0339445,0.00435146,0.961704	1/1:0.0282476,0.0342264,0.937526	1/1:0.0795052,0.0130118,0.907483	1/1:0.0326536,0.0330769,0.93427	1/1:0.0243107,0.00973621,0.965953	0/1:0.00124116,0.98777,0.010989	0/1:0.00548477,0.966598,0.0279173	1/1:0.0314743,0.00316746,0.965358	1/1:0.0237838,0.0281551,0.948061	0/1:0.00429407,0.973073,0.0226329	1/1:0.0120608,0.0606969,0.927242	0/1:0.0210421,0.938546,0.0404122	1/1:0.0701488,0.00185974,0.927991	1/1:0.0493376,0.0292246,0.921438	0/1:0.0499035,0.935747,0.014349	1/1:0.000654433,0.00217569,0.99717	./.:0.103262,0.0205517,0.876186	1/1:0.0224757,0.0591679,0.918356	1/1:0.0214995,0.0314616,0.947039	0/1:0.0379898,0.944268,0.0177421	1/1:0.021328,0.027489,0.951183	1/1:0.06724,0.00734375,0.925416	1/1:0.0189659,0.0332704,0.947764	./.:0.0797317,0.898005,0.0222629	0/1:0.026341,0.969121,0.00453756	1/1:0.0217481,0.0204677,0.957784	1/1:0.00490045,0.0223757,0.972724	1/1:0.0415264,0.0458277,0.912646	./.:0.0511204,0.0537561,0.895123	0/1:0.0105717,0.963693,0.0257349	0/0:0.937322,0.00723122,0.0554466	./.:0.143207,0.0101288,0.846664	0/1:0.0315368,0.951813,0.0166501	1/1:0.038989,0.0165993,0.944412	./.:0.100644,0.183035,0.716321	1/1:0.0823288,0.0128465,0.904825	1/1:0.0034666,0.049338,0.947195	1/1:0.0233664,0.00468681,0.971947	1/1:0.0436117,0.0396148,0.916773	0/1:0.0205411,0.917882,0.0615773	0/1:0.00322377,0.961871,0.0349054	1/1:0.0499616,0.00314309,0.946895	1/1:0.0468127,0.00899458,0.944193	0/1:0.0338638,0.936062,0.0300745	1/1:0.0056396,0.017292,0.977068	1/1:0.00613366,0.0484948,0.945372	1/1:0.00631457,0.0602332,0.933452	./.:0.0691134,0.0618279,0.869059	1/1:0.012638,0.00588526,0.981477	1/1:0.0015112,0.000621104,0.997868	1/1:0.0466233,0.0382781,0.915099	1/1:0.027791,0.00754011,0.964669	1/1:0.00275901,0.00875313,0.988488	./.:0.0478407,0.111212,0.840948	1/1:0.0529263,0.0445907,0.902483	1/1:0.0282028,0.0180073,0.95379	1/1:0.0139361,0.00691779,0.979146	1/1:0.0452405,0.0136163,0.941143	./.:0.102534,0.0259394,0.871527	0/1:0.0446612,0.931562,0.0237766	0/1:0.0442068,0.948338,0.00745547	1/1:0.00399419,0.028948,0.967058	1/1:0.00605696,0.0175714,0.976372	1/1:0.0477588,0.013406,0.938835	0/0:0.947987,0.0354132,0.0165997	1/1:0.00653112,0.00578616,0.987683	./.:0.867035,0.0902634,0.0427012	1/1:0.0643873,0.0188651,0.916748	1/1:0.000842905,0.00590639,0.993251	1/1:0.0630949,0.0309958,0.905909	0/1:0.0458677,0.949031,0.0051017	0/1:0.0172925,0.959727,0.0229802	1/1:0.00718509,0.0334211,0.959394	0/1:0.0166402,0.982376,0.000984025	./.:0.00850386,0.853576,0.13792	0/1:0.0108151,0.983622,0.00556339	1/1:0.00481048,0.0209357,0.974254	1/1:0.0122175,0.0431194,0.944663	1/1:0.0320531,0.0010635,0.966883	1/1:0.00888937,0.0126724,0.978438	1/1:0.0367195,0.0013617,0.961919	1/1:0.0457161,0.0368642,0.91742	1/1:0.0287255,0.0232909,0.947984	./.:0.00381377,0.222103,0.774084	1/1:0.0617475,0.0088487,0.929404	0/0:0.991433,0.00333091,0.00523611	0/1:0.00242355,0.96627,0.0313064	1/1:0.0213438,0.0164512,0.962205	1/1:0.00280492,0.0105787,0.986616	1/1:0.0326335,0.0386607,0.928706	0/1:0.0466641,0.946863,0.00647309	0/1:0.00527895,0.979136,0.0155847	1/1:0.00265403,0.038646,0.9587	1/1:0.0276922,0.00758808,0.96472	0/1:0.0515474,0.938304,0.0101483	1/1:8.05919e-05,0.00504138,0.994878	1/1:0.0495981,0.00187402,0.948528	./.:0.00359426,0.10615,0.890256	1/1:0.00340886,0.0184534,0.978138	0/1:0.0377736,0.933119,0.0291078	1/1:0.052863,0.0199816,0.927155	1/1:0.00211215,0.0745427,0.923345	1/1:0.0371903,0.0054969,0.957313	1/1:0.0317835,0.0178009,0.950416	1/1:0.00925936,0.0117127,0.979028	1/1:0.0141501,0.0375472,0.948303	1/1:0.00122601,0.00427866,0.994495	./.:0.00273981,0.0974786,0.899782	0/1:0.000164116,0.947451,0.0523845	0/1:0.0551723,0.931684,0.0131438	./.:0.10193,0.016837,0.881233	./.:0.0343107,0.0812687,0.884421	0/1:0.020091,0.979088,0.000821213	0/1:0.000642596,0.994601,0.00475618	1/1:0.0644909,0.0289324,0.906577	1/1:0.0044808,0.0043849,0.991134	1/1:0.0564859,0.00692184,0.936592	1/1:0.0193475,0.0685656,0.912087	0/1:0.0364879,0.929134,0.0343783	1/1:0.00259008,0.0374451,0.959965	./.:0.00910023,0.110054,0.880845	1/1:0.0120344,0.00703899,0.980927	1/1:0.0765967,0.004953,0.91845	1/1:0.000718255,0.000674462,0.998607	1/1:0.0105966,0.0460381,0.943365	1/1:0.0107638,0.00694329,0.982293	1/1:0.00319116,0.0566776,0.940131	./.:0.0808961,0.0269019,0.892202	0/1:0.0256116,0.946914,0.0274745	0/1:0.0148058,0.966226,0.0189679	1/1:0.0231881,0.0166036,0.960208	1/1:0.00210352,0.0184419,0.979455	1/1:0.000623254,0.0234305,0.975946	0/1:0.0104944,0.978792,0.0107132	1/1:0.00106302,0.0200414,0.978896	1/1:0.0307733,0.0104072,0.95882	1/1: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-NA	3	RSID_3,SNPID_3	A	G	.	.	.	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-NA	4	RSID_4,SNPID_4	A	G	.	.	.	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-NA	5	RSID_5,SNPID_5	A	G	.	.	.	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-NA	6	RSID_6,SNPID_6	A	G	.	.	.	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-NA	7	RSID_7,SNPID_7	A	G	.	.	.	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-NA	8	RSID_8,SNPID_8	A	G	.	.	.	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-NA	9	RSID_9,SNPID_9	A	G	.	.	.	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-NA	10	RSID_10,SNPID_10	A	G	.	.	.	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+NA	2	RSID_2;DELETION_1	A	-	.	.	.	GT:GP	1/1:0.0765213,0.00738931,0.916089	1/1:0.0278117,0.00864292,0.963545	1/1:0.0173777,0.0496874,0.932935	0/1:0.0248777,0.932817,0.0423053	1/1:0.0346175,0.0191856,0.946197	1/1:0.0624116,0.0162715,0.921317	./.:0.0890426,0.89522,0.0157372	1/1:0.0203313,0.013491,0.966178	1/1:0.0395959,0.0294134,0.930991	1/1:0.0443588,0.0343402,0.921301	1/1:0.0413977,0.0547565,0.903846	./.:0.0833462,0.0513328,0.865321	1/1:0.0204448,0.0430211,0.936534	0/1:0.00342552,0.985194,0.0113801	0/1:0.00726573,0.991422,0.00131274	1/1:0.00212978,0.0130744,0.984796	1/1:0.0433437,0.0240446,0.932612	0/1:0.030966,0.96512,0.00391444	1/1:0.0354075,0.00350694,0.961086	1/1:0.0308428,0.045246,0.923911	1/1:0.0550592,0.00799191,0.936949	./.:0.128164,0.0136164,0.858219	1/1:0.0117565,0.0384459,0.949798	1/1:0.0335148,0.0115101,0.954975	1/1:0.00809348,0.0131524,0.978754	1/1:0.00623515,0.0180752,0.97569	1/1:0.0146414,0.0125058,0.972853	1/1:0.025476,0.00528723,0.969237	1/1:0.00211196,0.0579454,0.939943	1/1:0.0140452,0.00261017,0.983345	1/1:0.0355083,0.0597193,0.904772	1/1:0.0257136,0.00281197,0.971474	0/1:0.0142856,0.948082,0.0376327	1/1:0.0397819,0.0203298,0.939888	1/1:0.00470346,0.00871748,0.986579	1/1:0.00622709,0.00439993,0.989373	1/1:0.0452334,0.0078768,0.94689	0/1:0.0751067,0.922155,0.002738	1/1:0.0304864,0.00329875,0.966215	1/1:0.022215,0.0297167,0.948068	0/0:0.971078,0.00121635,0.0277058	0/1:0.00669808,0.992912,0.000390372	1/1:0.00366201,0.00229824,0.99404	1/1:0.0358488,0.0184567,0.945695	0/1:0.000127906,0.982611,0.0172609	0/1:0.0269364,0.967933,0.00513028	1/1:0.0363318,0.0091488,0.954519	0/1:0.0218157,0.951233,0.0269512	1/1:0.0102727,0.00562367,0.984104	1/1:0.00458934,0.0495853,0.945825	1/1:0.00532228,0.0157015,0.978976	1/1:0.0053079,0.000927737,0.993764	1/1:0.0264865,0.0254771,0.948036	1/1:0.0522013,0.00111124,0.946687	1/1:0.0164378,0.00560304,0.977959	1/1:0.0626507,0.00508806,0.932261	0/1:0.00161383,0.979377,0.0190092	0/0:0.966122,0.00132746,0.0325505	1/1:0.0155659,0.00569339,0.978741	1/1:0.0202013,0.000290894,0.979508	1/1:0.0281994,0.00773169,0.964069	./.:0.0508201,0.0542616,0.894918	0/1:0.0310162,0.941976,0.0270078	1/1:0.0455028,0.0162002,0.938297	0/1:0.0184549,0.936524,0.045021	0/1:0.0361544,0.922292,0.0415535	1/1:0.0427266,0.036398,0.920875	1/1:0.00544581,0.017418,0.977136	1/1:0.00248236,0.0113308,0.986187	0/1:0.0112173,0.980356,0.00842722	0/1:0.00144022,0.989422,0.00913776	1/1:3.11376e-05,0.0425171,0.957452	1/1:0.0187048,0.0104851,0.97081	1/1:0.00624943,0.035127,0.958624	0/1:0.0257277,0.950684,0.023588	1/1:0.01295,0.0670332,0.920017	1/1:0.0165091,0.0414055,0.942085	1/1:0.000603927,0.0290382,0.970358	0/1:0.0255638,0.970474,0.00396241	0/1:0.0144861,0.967365,0.0181491	1/1:0.00461234,0.0602488,0.935139	1/1:0.0382218,0.00626481,0.955513	1/1:0.0596664,0.0231397,0.917194	1/1:0.0179393,0.0391777,0.942883	0/1:0.0134928,0.943517,0.0429902	1/1:0.0774595,0.0114083,0.911132	1/1:0.0176584,0.00339778,0.978944	1/1:0.0100261,0.0271536,0.96282	1/1:0.0130068,0.0141708,0.972822	0/1:0.00734218,0.943733,0.0489247	./.:0.062756,0.0610352,0.876209	1/1:0.0270041,0.0134642,0.959532	1/1:0.00411924,0.0168011,0.97908	./.:0.0515086,0.887631,0.0608606	0/1:0.0135331,0.978956,0.00751137	1/1:0.0307017,0.000968173,0.96833	1/1:0.0153662,0.0120846,0.972549	1/1:0.00044704,0.0492262,0.950327	./.:0.110592,0.00344009,0.885968	1/1:0.0164569,0.0277545,0.955789	1/1:0.00375503,0.0400653,0.95618	1/1:0.00276732,0.0325795,0.964653	0/1:0.0317738,0.954008,0.0142186	./.:0.0332177,0.0885011,0.878281	./.:0.0779957,0.0638195,0.858185	1/1:0.00664966,0.0874973,0.905853	0/1:0.00581931,0.970621,0.0235596	1/1:0.0102489,0.00409048,0.985661	./.:0.00252458,0.118531,0.878945	0/1:0.00481888,0.990939,0.00424204	1/1:0.0142779,0.014817,0.970905	0/1:0.00742485,0.979232,0.0133436	0/1:0.0259031,0.956843,0.0172542	./.:0.104541,0.880652,0.014807	1/1:0.0694247,0.0148819,0.915693	0/1:0.00757589,0.99137,0.00105374	0/1:0.0429337,0.948554,0.00851256	1/1:0.00232002,0.0135248,0.984155	1/1:0.00385322,0.00367388,0.992473	0/1:0.0191218,0.970571,0.010307	1/1:0.00953562,0.026791,0.963673	0/1:0.0018121,0.978612,0.0195761	1/1:0.00221615,0.000487307,0.997297	1/1:0.000169594,0.00836001,0.99147	0/1:0.0132875,0.977977,0.00873553	1/1:0.0318824,0.0044041,0.963714	1/1:0.00838779,0.000825634,0.990787	./.:0.109297,0.00548867,0.885215	1/1:0.00871124,0.0323483,0.95894	0/1:0.00702381,0.915908,0.0770681	1/1:0.0211908,0.0483898,0.930419	0/1:0.0338834,0.922492,0.0436242	0/1:0.030799,0.966864,0.00233682	1/1:0.0160218,0.0126794,0.971299	1/1:0.00806931,0.00963224,0.982298	1/1:0.0194903,0.0150679,0.965442	1/1:0.035366,0.0389562,0.925678	1/1:0.00267017,0.0382586,0.959071	0/1:0.00388209,0.985784,0.010334	./.:0.0982637,0.0382897,0.863447	0/1:0.0022618,0.919474,0.0782647	1/1:2.49412e-05,0.0167737,0.983201	./.:0.0582512,0.0492292,0.89252	0/1:0.00845342,0.953394,0.0381527	1/1:0.0272179,0.0196223,0.95316	1/1:0.0567382,0.0166038,0.926658	./.:0.12687,0.872336,0.000794047	0/1:0.0204258,0.941278,0.0382964	1/1:0.0232436,0.00367961,0.973077	0/1:0.00880893,0.921912,0.0692794	1/1:0.0216899,0.0273385,0.950972	1/1:0.0426108,0.0204562,0.936933	0/1:0.0104113,0.970103,0.0194862	1/1:0.058506,0.0250296,0.916464	1/1:0.0142527,0.0481697,0.937578	1/1:0.0352332,0.00821716,0.95655	1/1:0.00704378,0.00383585,0.98912	0/1:0.0618883,0.923708,0.0144034	1/1:0.00947037,0.028737,0.961793	0/1:0.0358306,0.959207,0.0049623	1/1:0.0419056,0.00609378,0.952001	1/1:0.0511185,0.00073821,0.948143	1/1:0.0235176,0.0614284,0.915054	1/1:0.0423645,0.050623,0.907012	1/1:0.01013,0.0889667,0.900903	1/1:0.00197436,0.0733078,0.924718	./.:0.0783761,0.0315562,0.890068	1/1:0.0635035,0.0172963,0.9192	1/1:0.0394675,0.00484857,0.955684	1/1:0.0249377,0.021648,0.953414	0/1:0.0118272,0.95642,0.0317532	1/1:0.0132819,0.0262284,0.96049	1/1:0.0203168,0.0178358,0.961847	1/1:0.0280182,0.0369552,0.935027	1/1:0.050963,0.0110882,0.937949	1/1:0.0256438,0.00415634,0.9702	1/1:0.0140764,0.0479012,0.938022	1/1:0.00702359,0.0359428,0.957034	1/1:0.0230789,0.0120966,0.964825	0/1:0.0615742,0.929984,0.0084413	0/1:0.028977,0.968539,0.00248423	1/1:0.0202895,0.0614246,0.918286	1/1:0.0282214,0.0483363,0.923442	1/1:0.0619251,0.0218439,0.916231	1/1:0.00706208,0.0120217,0.980916	0/1:0.00640163,0.961214,0.032384	0/0:0.991858,0.00380923,0.00433243	./.:0.0470269,0.082571,0.870402	0/1:0.0519842,0.944215,0.00380044	0/1:0.0620133,0.914345,0.0236416	./.:0.186934,0.0114153,0.80165	1/1:0.000345943,0.0235675,0.976087	1/1:0.0326442,0.00235391,0.965002	1/1:0.00532184,0.0183645,0.976314	0/1:0.00903543,0.965256,0.0257083	1/1:0.00619173,0.0135111,0.980297	0/1:0.00584457,0.95686,0.0372956	1/1:0.00593699,0.0612912,0.932772	1/1:0.0269436,0.0389198,0.934137	1/1:0.0356937,0.0327066,0.9316	1/1:0.0561839,0.00373752,0.940079	1/1:0.0511941,0.0157286,0.933077	1/1:0.078324,0.0198007,0.901875	1/1:0.000779039,0.0401042,0.959117	1/1:0.0106681,0.0217184,0.967614	0/1:0.0448439,0.914974,0.0401817	0/1:0.00030371,0.985059,0.0146377	0/1:0.039209,0.956317,0.00447422	1/1:0.0284045,0.0646966,0.906899	./.:0.0397172,0.895523,0.0647601	0/0:0.981547,0.00240078,0.0160523	1/1:0.00361121,0.00497761,0.991411	1/1:0.0280749,0.0110312,0.960894	1/1:0.0253983,0.0222725,0.952329	1/1:0.0397773,0.0458102,0.914413	0/1:0.0249766,0.916817,0.0582059	1/1:0.0503006,0.0427178,0.906982	0/1:0.0461137,0.935709,0.0181774	1/1:0.0395516,0.0561328,0.904316	1/1:0.0103299,0.0181879,0.971482	1/1:0.0076416,0.0403221,0.952036	1/1:0.019195,0.0253848,0.95542	1/1:0.00872853,0.0280844,0.963187	1/1:0.0220789,0.0640545,0.913867	1/1:0.0502671,0.0229983,0.926735	1/1:0.00837678,7.85657e-05,0.991545	./.:0.00126481,0.85077,0.147965	0/1:0.0260687,0.919439,0.0544925	0/1:0.00773965,0.991731,0.000528911	1/1:0.0242448,0.011632,0.964123	1/1:0.0448744,0.00833587,0.94679	1/1:0.0195972,0.00775482,0.972648	./.:0.094565,0.0196051,0.88583	1/1:0.0219288,0.0154441,0.962627	0/1:0.0128967,0.980922,0.00618099	1/1:0.0133328,0.0111186,0.975549	1/1:0.0209894,0.0618488,0.917162	1/1:0.0309362,0.00195092,0.967113	0/1:0.0209576,0.97443,0.00461241	1/1:0.0215581,0.0119414,0.9665	1/1:0.0294206,0.0593992,0.91118	1/1:0.0431204,0.0414609,0.915419	1/1:6.64084e-07,0.0104027,0.989597	1/1:0.0264899,0.00513652,0.968374	1/1:0.00962836,0.0012802,0.989091	1/1:0.00262166,0.0280628,0.969316	0/1:0.00436423,0.967383,0.0282524	0/1:0.0166533,0.972714,0.0106325	0/1:0.00737717,0.981342,0.0112812	0/1:0.0208076,0.950085,0.0291073	1/1:0.0173471,0.00669082,0.975962	1/1:0.026793,0.0257043,0.947503	1/1:0.0233496,0.00436309,0.972287	1/1:0.0208317,0.0184149,0.960753	0/1:0.0274726,0.934305,0.0382225	0/1:0.021481,0.960822,0.0176974	0/1:0.0476554,0.939072,0.0132728	0/1:0.0234288,0.967458,0.0091133	0/1:0.0141893,0.951599,0.034212	0/1:0.00419246,0.970974,0.024834	0/1:8.37918e-05,0.920339,0.0795777	1/1:0.0109809,0.0149742,0.974045	1/1:0.0613423,0.0350763,0.903581	1/1:0.0516634,0.0332994,0.915037	0/1:0.0415676,0.957151,0.00128121	0/1:0.0040198,0.985329,0.0106516	./.:0.0183737,0.14258,0.839047	1/1:0.00407833,0.0247806,0.971141	1/1:0.00978301,0.0359626,0.954254	0/1:0.047259,0.917512,0.0352294	0/1:0.0051346,0.989586,0.00527964	0/1:0.0388345,0.952014,0.00915128	0/1:0.0490986,0.923002,0.0278998	0/1:0.0242299,0.967634,0.00813596	0/1:0.0787345,0.920511,0.000754718	1/1:0.00522087,0.0133353,0.981444	0/1:0.00489867,0.978843,0.016258	1/1:0.00542466,0.00122524,0.99335	0/1:0.0143657,0.984541,0.00109371	1/1:0.00252614,0.0177165,0.979757	1/1:0.0730979,0.0046939,0.922208	1/1:0.0172776,0.00380916,0.978913	1/1:0.00321306,0.0263511,0.970436	0/0:0.986966,0.0100988,0.00293523	0/1:0.00127376,0.98952,0.0092064	0/1:0.00369403,0.976305,0.0200013	0/1:0.0418657,0.927221,0.0309128	1/1:8.66898e-05,0.0417915,0.958122	0/1:0.00617715,0.95733,0.0364927	1/1:0.0216624,0.0125235,0.965814	0/1:0.0384431,0.956619,0.00493833	./.:0.091695,0.0296694,0.878636	0/1:0.00775148,0.977032,0.0152162	0/1:0.0345039,0.96546,3.61777e-05	0/1:0.00244344,0.988914,0.00864281	1/1:0.0396826,0.0435855,0.916732	0/1:0.0195579,0.96012,0.0203217	0/1:0.0713879,0.927713,0.000898868	0/1:0.063115,0.929048,0.00783668	./.:0.0410352,0.0697608,0.889204	1/1:0.000479687,0.0628162,0.936704	./.:0.10388,0.880882,0.015238	0/1:0.0398778,0.951817,0.00830562	1/1:0.025359,0.00295701,0.971684	./.:0.118569,0.848748,0.0326829	1/1:0.00435785,0.0230209,0.972621	1/1:0.00811194,0.0224001,0.969488	1/1:0.0185575,0.0335337,0.947909	./.:0.0906568,0.0255168,0.883826	0/1:0.0403838,0.942995,0.0166211	1/1:0.00755941,0.0653485,0.927092	1/1:0.0112374,0.00507048,0.983692	1/1:0.0144833,0.0299461,0.955571	./.:0.0694543,0.0308285,0.899717	1/1:0.0339445,0.00435146,0.961704	1/1:0.0282476,0.0342264,0.937526	1/1:0.0795052,0.0130118,0.907483	1/1:0.0326536,0.0330769,0.93427	1/1:0.0243107,0.00973621,0.965953	0/1:0.00124116,0.98777,0.010989	0/1:0.00548477,0.966598,0.0279173	1/1:0.0314743,0.00316746,0.965358	1/1:0.0237838,0.0281551,0.948061	0/1:0.00429407,0.973073,0.0226329	1/1:0.0120608,0.0606969,0.927242	0/1:0.0210421,0.938546,0.0404122	1/1:0.0701488,0.00185974,0.927991	1/1:0.0493376,0.0292246,0.921438	0/1:0.0499035,0.935747,0.014349	1/1:0.000654433,0.00217569,0.99717	./.:0.103262,0.0205517,0.876186	1/1:0.0224757,0.0591679,0.918356	1/1:0.0214995,0.0314616,0.947039	0/1:0.0379898,0.944268,0.0177421	1/1:0.021328,0.027489,0.951183	1/1:0.06724,0.00734375,0.925416	1/1:0.0189659,0.0332704,0.947764	./.:0.0797317,0.898005,0.0222629	0/1:0.026341,0.969121,0.00453756	1/1:0.0217481,0.0204677,0.957784	1/1:0.00490045,0.0223757,0.972724	1/1:0.0415264,0.0458277,0.912646	./.:0.0511204,0.0537561,0.895123	0/1:0.0105717,0.963693,0.0257349	0/0:0.937322,0.00723122,0.0554466	./.:0.143207,0.0101288,0.846664	0/1:0.0315368,0.951813,0.0166501	1/1:0.038989,0.0165993,0.944412	./.:0.100644,0.183035,0.716321	1/1:0.0823288,0.0128465,0.904825	1/1:0.0034666,0.049338,0.947195	1/1:0.0233664,0.00468681,0.971947	1/1:0.0436117,0.0396148,0.916773	0/1:0.0205411,0.917882,0.0615773	0/1:0.00322377,0.961871,0.0349054	1/1:0.0499616,0.00314309,0.946895	1/1:0.0468127,0.00899458,0.944193	0/1:0.0338638,0.936062,0.0300745	1/1:0.0056396,0.017292,0.977068	1/1:0.00613366,0.0484948,0.945372	1/1:0.00631457,0.0602332,0.933452	./.:0.0691134,0.0618279,0.869059	1/1:0.012638,0.00588526,0.981477	1/1:0.0015112,0.000621104,0.997868	1/1:0.0466233,0.0382781,0.915099	1/1:0.027791,0.00754011,0.964669	1/1:0.00275901,0.00875313,0.988488	./.:0.0478407,0.111212,0.840948	1/1:0.0529263,0.0445907,0.902483	1/1:0.0282028,0.0180073,0.95379	1/1:0.0139361,0.00691779,0.979146	1/1:0.0452405,0.0136163,0.941143	./.:0.102534,0.0259394,0.871527	0/1:0.0446612,0.931562,0.0237766	0/1:0.0442068,0.948338,0.00745547	1/1:0.00399419,0.028948,0.967058	1/1:0.00605696,0.0175714,0.976372	1/1:0.0477588,0.013406,0.938835	0/0:0.947987,0.0354132,0.0165997	1/1:0.00653112,0.00578616,0.987683	./.:0.867035,0.0902634,0.0427012	1/1:0.0643873,0.0188651,0.916748	1/1:0.000842905,0.00590639,0.993251	1/1:0.0630949,0.0309958,0.905909	0/1:0.0458677,0.949031,0.0051017	0/1:0.0172925,0.959727,0.0229802	1/1:0.00718509,0.0334211,0.959394	0/1:0.0166402,0.982376,0.000984025	./.:0.00850386,0.853576,0.13792	0/1:0.0108151,0.983622,0.00556339	1/1:0.00481048,0.0209357,0.974254	1/1:0.0122175,0.0431194,0.944663	1/1:0.0320531,0.0010635,0.966883	1/1:0.00888937,0.0126724,0.978438	1/1:0.0367195,0.0013617,0.961919	1/1:0.0457161,0.0368642,0.91742	1/1:0.0287255,0.0232909,0.947984	./.:0.00381377,0.222103,0.774084	1/1:0.0617475,0.0088487,0.929404	0/0:0.991433,0.00333091,0.00523611	0/1:0.00242355,0.96627,0.0313064	1/1:0.0213438,0.0164512,0.962205	1/1:0.00280492,0.0105787,0.986616	1/1:0.0326335,0.0386607,0.928706	0/1:0.0466641,0.946863,0.00647309	0/1:0.00527895,0.979136,0.0155847	1/1:0.00265403,0.038646,0.9587	1/1:0.0276922,0.00758808,0.96472	0/1:0.0515474,0.938304,0.0101483	1/1:8.05919e-05,0.00504138,0.994878	1/1:0.0495981,0.00187402,0.948528	./.:0.00359426,0.10615,0.890256	1/1:0.00340886,0.0184534,0.978138	0/1:0.0377736,0.933119,0.0291078	1/1:0.052863,0.0199816,0.927155	1/1:0.00211215,0.0745427,0.923345	1/1:0.0371903,0.0054969,0.957313	1/1:0.0317835,0.0178009,0.950416	1/1:0.00925936,0.0117127,0.979028	1/1:0.0141501,0.0375472,0.948303	1/1:0.00122601,0.00427866,0.994495	./.:0.00273981,0.0974786,0.899782	0/1:0.000164116,0.947451,0.0523845	0/1:0.0551723,0.931684,0.0131438	./.:0.10193,0.016837,0.881233	./.:0.0343107,0.0812687,0.884421	0/1:0.020091,0.979088,0.000821213	0/1:0.000642596,0.994601,0.00475618	1/1:0.0644909,0.0289324,0.906577	1/1:0.0044808,0.0043849,0.991134	1/1:0.0564859,0.00692184,0.936592	1/1:0.0193475,0.0685656,0.912087	0/1:0.0364879,0.929134,0.0343783	1/1:0.00259008,0.0374451,0.959965	./.:0.00910023,0.110054,0.880845	1/1:0.0120344,0.00703899,0.980927	1/1:0.0765967,0.004953,0.91845	1/1:0.000718255,0.000674462,0.998607	1/1:0.0105966,0.0460381,0.943365	1/1:0.0107638,0.00694329,0.982293	1/1:0.00319116,0.0566776,0.940131	./.:0.0808961,0.0269019,0.892202	0/1:0.0256116,0.946914,0.0274745	0/1:0.0148058,0.966226,0.0189679	1/1:0.0231881,0.0166036,0.960208	1/1:0.00210352,0.0184419,0.979455	1/1:0.000623254,0.0234305,0.975946	0/1:0.0104944,0.978792,0.0107132	1/1:0.00106302,0.0200414,0.978896	1/1:0.0307733,0.0104072,0.95882	1/1: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+NA	3	RSID_3;SNPID_3	A	G	.	.	.	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Index: release/test/data/test.v4.1.vcf.gz
==================================================================
--- release/test/data/test.v4.1.vcf.gz
+++ release/test/data/test.v4.1.vcf.gz
cannot compute difference between binary files

Index: release/test/data/test.v4.2.vcf
==================================================================
--- release/test/data/test.v4.2.vcf
+++ release/test/data/test.v4.2.vcf
@@ -1,15 +1,15 @@
 ##fileformat=VCFv4.2
 ##FORMAT=<ID=GT,Type=String,Number=1,Description="Genotype call probabilities, threshholded at 0.90">
 ##FORMAT=<ID=GP,Type=Float,Number=G,Description="Genotype call probabilities">
 ##FORMAT=<ID=XY,Type=Float,Number=R,Description="Chip intensities">
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-NA	2	RSID_2,DELETION_1	A	-	.	.	.	GT:GP	1/1:0.0765213,0.00738931,0.916089	1/1:0.0278117,0.00864292,0.963545	1/1:0.0173777,0.0496874,0.932935	0/1:0.0248777,0.932817,0.0423053	1/1:0.0346175,0.0191856,0.946197	1/1:0.0624116,0.0162715,0.921317	./.:0.0890426,0.89522,0.0157372	1/1:0.0203313,0.013491,0.966178	1/1:0.0395959,0.0294134,0.930991	1/1:0.0443588,0.0343402,0.921301	1/1:0.0413977,0.0547565,0.903846	./.:0.0833462,0.0513328,0.865321	1/1:0.0204448,0.0430211,0.936534	0/1:0.00342552,0.985194,0.0113801	0/1:0.00726573,0.991422,0.00131274	1/1:0.00212978,0.0130744,0.984796	1/1:0.0433437,0.0240446,0.932612	0/1:0.030966,0.96512,0.00391444	1/1:0.0354075,0.00350694,0.961086	1/1:0.0308428,0.045246,0.923911	1/1:0.0550592,0.00799191,0.936949	./.:0.128164,0.0136164,0.858219	1/1:0.0117565,0.0384459,0.949798	1/1:0.0335148,0.0115101,0.954975	1/1:0.00809348,0.0131524,0.978754	1/1:0.00623515,0.0180752,0.97569	1/1:0.0146414,0.0125058,0.972853	1/1:0.025476,0.00528723,0.969237	1/1:0.00211196,0.0579454,0.939943	1/1:0.0140452,0.00261017,0.983345	1/1:0.0355083,0.0597193,0.904772	1/1:0.0257136,0.00281197,0.971474	0/1:0.0142856,0.948082,0.0376327	1/1:0.0397819,0.0203298,0.939888	1/1:0.00470346,0.00871748,0.986579	1/1:0.00622709,0.00439993,0.989373	1/1:0.0452334,0.0078768,0.94689	0/1:0.0751067,0.922155,0.002738	1/1:0.0304864,0.00329875,0.966215	1/1:0.022215,0.0297167,0.948068	0/0:0.971078,0.00121635,0.0277058	0/1:0.00669808,0.992912,0.000390372	1/1:0.00366201,0.00229824,0.99404	1/1:0.0358488,0.0184567,0.945695	0/1:0.000127906,0.982611,0.0172609	0/1:0.0269364,0.967933,0.00513028	1/1:0.0363318,0.0091488,0.954519	0/1:0.0218157,0.951233,0.0269512	1/1:0.0102727,0.00562367,0.984104	1/1:0.00458934,0.0495853,0.945825	1/1:0.00532228,0.0157015,0.978976	1/1:0.0053079,0.000927737,0.993764	1/1:0.0264865,0.0254771,0.948036	1/1:0.0522013,0.00111124,0.946687	1/1:0.0164378,0.00560304,0.977959	1/1:0.0626507,0.00508806,0.932261	0/1:0.00161383,0.979377,0.0190092	0/0:0.966122,0.00132746,0.0325505	1/1:0.0155659,0.00569339,0.978741	1/1:0.0202013,0.000290894,0.979508	1/1:0.0281994,0.00773169,0.964069	./.:0.0508201,0.0542616,0.894918	0/1:0.0310162,0.941976,0.0270078	1/1:0.0455028,0.0162002,0.938297	0/1:0.0184549,0.936524,0.045021	0/1:0.0361544,0.922292,0.0415535	1/1:0.0427266,0.036398,0.920875	1/1:0.00544581,0.017418,0.977136	1/1:0.00248236,0.0113308,0.986187	0/1:0.0112173,0.980356,0.00842722	0/1:0.00144022,0.989422,0.00913776	1/1:3.11376e-05,0.0425171,0.957452	1/1:0.0187048,0.0104851,0.97081	1/1:0.00624943,0.035127,0.958624	0/1:0.0257277,0.950684,0.023588	1/1:0.01295,0.0670332,0.920017	1/1:0.0165091,0.0414055,0.942085	1/1:0.000603927,0.0290382,0.970358	0/1:0.0255638,0.970474,0.00396241	0/1:0.0144861,0.967365,0.0181491	1/1:0.00461234,0.0602488,0.935139	1/1:0.0382218,0.00626481,0.955513	1/1:0.0596664,0.0231397,0.917194	1/1:0.0179393,0.0391777,0.942883	0/1:0.0134928,0.943517,0.0429902	1/1:0.0774595,0.0114083,0.911132	1/1:0.0176584,0.00339778,0.978944	1/1:0.0100261,0.0271536,0.96282	1/1:0.0130068,0.0141708,0.972822	0/1:0.00734218,0.943733,0.0489247	./.:0.062756,0.0610352,0.876209	1/1:0.0270041,0.0134642,0.959532	1/1:0.00411924,0.0168011,0.97908	./.:0.0515086,0.887631,0.0608606	0/1:0.0135331,0.978956,0.00751137	1/1:0.0307017,0.000968173,0.96833	1/1:0.0153662,0.0120846,0.972549	1/1:0.00044704,0.0492262,0.950327	./.:0.110592,0.00344009,0.885968	1/1:0.0164569,0.0277545,0.955789	1/1:0.00375503,0.0400653,0.95618	1/1:0.00276732,0.0325795,0.964653	0/1:0.0317738,0.954008,0.0142186	./.:0.0332177,0.0885011,0.878281	./.:0.0779957,0.0638195,0.858185	1/1:0.00664966,0.0874973,0.905853	0/1:0.00581931,0.970621,0.0235596	1/1:0.0102489,0.00409048,0.985661	./.:0.00252458,0.118531,0.878945	0/1:0.00481888,0.990939,0.00424204	1/1:0.0142779,0.014817,0.970905	0/1:0.00742485,0.979232,0.0133436	0/1:0.0259031,0.956843,0.0172542	./.:0.104541,0.880652,0.014807	1/1:0.0694247,0.0148819,0.915693	0/1:0.00757589,0.99137,0.00105374	0/1:0.0429337,0.948554,0.00851256	1/1:0.00232002,0.0135248,0.984155	1/1:0.00385322,0.00367388,0.992473	0/1:0.0191218,0.970571,0.010307	1/1:0.00953562,0.026791,0.963673	0/1:0.0018121,0.978612,0.0195761	1/1:0.00221615,0.000487307,0.997297	1/1:0.000169594,0.00836001,0.99147	0/1:0.0132875,0.977977,0.00873553	1/1:0.0318824,0.0044041,0.963714	1/1:0.00838779,0.000825634,0.990787	./.:0.109297,0.00548867,0.885215	1/1:0.00871124,0.0323483,0.95894	0/1:0.00702381,0.915908,0.0770681	1/1:0.0211908,0.0483898,0.930419	0/1:0.0338834,0.922492,0.0436242	0/1:0.030799,0.966864,0.00233682	1/1:0.0160218,0.0126794,0.971299	1/1:0.00806931,0.00963224,0.982298	1/1:0.0194903,0.0150679,0.965442	1/1:0.035366,0.0389562,0.925678	1/1:0.00267017,0.0382586,0.959071	0/1:0.00388209,0.985784,0.010334	./.:0.0982637,0.0382897,0.863447	0/1:0.0022618,0.919474,0.0782647	1/1:2.49412e-05,0.0167737,0.983201	./.:0.0582512,0.0492292,0.89252	0/1:0.00845342,0.953394,0.0381527	1/1:0.0272179,0.0196223,0.95316	1/1:0.0567382,0.0166038,0.926658	./.:0.12687,0.872336,0.000794047	0/1:0.0204258,0.941278,0.0382964	1/1:0.0232436,0.00367961,0.973077	0/1:0.00880893,0.921912,0.0692794	1/1:0.0216899,0.0273385,0.950972	1/1:0.0426108,0.0204562,0.936933	0/1:0.0104113,0.970103,0.0194862	1/1:0.058506,0.0250296,0.916464	1/1:0.0142527,0.0481697,0.937578	1/1:0.0352332,0.00821716,0.95655	1/1:0.00704378,0.00383585,0.98912	0/1:0.0618883,0.923708,0.0144034	1/1:0.00947037,0.028737,0.961793	0/1:0.0358306,0.959207,0.0049623	1/1:0.0419056,0.00609378,0.952001	1/1:0.0511185,0.00073821,0.948143	1/1:0.0235176,0.0614284,0.915054	1/1:0.0423645,0.050623,0.907012	1/1:0.01013,0.0889667,0.900903	1/1:0.00197436,0.0733078,0.924718	./.:0.0783761,0.0315562,0.890068	1/1:0.0635035,0.0172963,0.9192	1/1:0.0394675,0.00484857,0.955684	1/1:0.0249377,0.021648,0.953414	0/1:0.0118272,0.95642,0.0317532	1/1:0.0132819,0.0262284,0.96049	1/1:0.0203168,0.0178358,0.961847	1/1:0.0280182,0.0369552,0.935027	1/1:0.050963,0.0110882,0.937949	1/1:0.0256438,0.00415634,0.9702	1/1:0.0140764,0.0479012,0.938022	1/1:0.00702359,0.0359428,0.957034	1/1:0.0230789,0.0120966,0.964825	0/1:0.0615742,0.929984,0.0084413	0/1:0.028977,0.968539,0.00248423	1/1:0.0202895,0.0614246,0.918286	1/1:0.0282214,0.0483363,0.923442	1/1:0.0619251,0.0218439,0.916231	1/1:0.00706208,0.0120217,0.980916	0/1:0.00640163,0.961214,0.032384	0/0:0.991858,0.00380923,0.00433243	./.:0.0470269,0.082571,0.870402	0/1:0.0519842,0.944215,0.00380044	0/1:0.0620133,0.914345,0.0236416	./.:0.186934,0.0114153,0.80165	1/1:0.000345943,0.0235675,0.976087	1/1:0.0326442,0.00235391,0.965002	1/1:0.00532184,0.0183645,0.976314	0/1:0.00903543,0.965256,0.0257083	1/1:0.00619173,0.0135111,0.980297	0/1:0.00584457,0.95686,0.0372956	1/1:0.00593699,0.0612912,0.932772	1/1:0.0269436,0.0389198,0.934137	1/1:0.0356937,0.0327066,0.9316	1/1:0.0561839,0.00373752,0.940079	1/1:0.0511941,0.0157286,0.933077	1/1:0.078324,0.0198007,0.901875	1/1:0.000779039,0.0401042,0.959117	1/1:0.0106681,0.0217184,0.967614	0/1:0.0448439,0.914974,0.0401817	0/1:0.00030371,0.985059,0.0146377	0/1:0.039209,0.956317,0.00447422	1/1:0.0284045,0.0646966,0.906899	./.:0.0397172,0.895523,0.0647601	0/0:0.981547,0.00240078,0.0160523	1/1:0.00361121,0.00497761,0.991411	1/1:0.0280749,0.0110312,0.960894	1/1:0.0253983,0.0222725,0.952329	1/1:0.0397773,0.0458102,0.914413	0/1:0.0249766,0.916817,0.0582059	1/1:0.0503006,0.0427178,0.906982	0/1:0.0461137,0.935709,0.0181774	1/1:0.0395516,0.0561328,0.904316	1/1:0.0103299,0.0181879,0.971482	1/1:0.0076416,0.0403221,0.952036	1/1:0.019195,0.0253848,0.95542	1/1:0.00872853,0.0280844,0.963187	1/1:0.0220789,0.0640545,0.913867	1/1:0.0502671,0.0229983,0.926735	1/1:0.00837678,7.85657e-05,0.991545	./.:0.00126481,0.85077,0.147965	0/1:0.0260687,0.919439,0.0544925	0/1:0.00773965,0.991731,0.000528911	1/1:0.0242448,0.011632,0.964123	1/1:0.0448744,0.00833587,0.94679	1/1:0.0195972,0.00775482,0.972648	./.:0.094565,0.0196051,0.88583	1/1:0.0219288,0.0154441,0.962627	0/1:0.0128967,0.980922,0.00618099	1/1:0.0133328,0.0111186,0.975549	1/1:0.0209894,0.0618488,0.917162	1/1:0.0309362,0.00195092,0.967113	0/1:0.0209576,0.97443,0.00461241	1/1:0.0215581,0.0119414,0.9665	1/1:0.0294206,0.0593992,0.91118	1/1:0.0431204,0.0414609,0.915419	1/1:6.64084e-07,0.0104027,0.989597	1/1:0.0264899,0.00513652,0.968374	1/1:0.00962836,0.0012802,0.989091	1/1:0.00262166,0.0280628,0.969316	0/1:0.00436423,0.967383,0.0282524	0/1:0.0166533,0.972714,0.0106325	0/1:0.00737717,0.981342,0.0112812	0/1:0.0208076,0.950085,0.0291073	1/1:0.0173471,0.00669082,0.975962	1/1:0.026793,0.0257043,0.947503	1/1:0.0233496,0.00436309,0.972287	1/1:0.0208317,0.0184149,0.960753	0/1:0.0274726,0.934305,0.0382225	0/1:0.021481,0.960822,0.0176974	0/1:0.0476554,0.939072,0.0132728	0/1:0.0234288,0.967458,0.0091133	0/1:0.0141893,0.951599,0.034212	0/1:0.00419246,0.970974,0.024834	0/1:8.37918e-05,0.920339,0.0795777	1/1:0.0109809,0.0149742,0.974045	1/1:0.0613423,0.0350763,0.903581	1/1:0.0516634,0.0332994,0.915037	0/1:0.0415676,0.957151,0.00128121	0/1:0.0040198,0.985329,0.0106516	./.:0.0183737,0.14258,0.839047	1/1:0.00407833,0.0247806,0.971141	1/1:0.00978301,0.0359626,0.954254	0/1:0.047259,0.917512,0.0352294	0/1:0.0051346,0.989586,0.00527964	0/1:0.0388345,0.952014,0.00915128	0/1:0.0490986,0.923002,0.0278998	0/1:0.0242299,0.967634,0.00813596	0/1:0.0787345,0.920511,0.000754718	1/1:0.00522087,0.0133353,0.981444	0/1:0.00489867,0.978843,0.016258	1/1:0.00542466,0.00122524,0.99335	0/1:0.0143657,0.984541,0.00109371	1/1:0.00252614,0.0177165,0.979757	1/1:0.0730979,0.0046939,0.922208	1/1:0.0172776,0.00380916,0.978913	1/1:0.00321306,0.0263511,0.970436	0/0:0.986966,0.0100988,0.00293523	0/1:0.00127376,0.98952,0.0092064	0/1:0.00369403,0.976305,0.0200013	0/1:0.0418657,0.927221,0.0309128	1/1:8.66898e-05,0.0417915,0.958122	0/1:0.00617715,0.95733,0.0364927	1/1:0.0216624,0.0125235,0.965814	0/1:0.0384431,0.956619,0.00493833	./.:0.091695,0.0296694,0.878636	0/1:0.00775148,0.977032,0.0152162	0/1:0.0345039,0.96546,3.61777e-05	0/1:0.00244344,0.988914,0.00864281	1/1:0.0396826,0.0435855,0.916732	0/1:0.0195579,0.96012,0.0203217	0/1:0.0713879,0.927713,0.000898868	0/1:0.063115,0.929048,0.00783668	./.:0.0410352,0.0697608,0.889204	1/1:0.000479687,0.0628162,0.936704	./.:0.10388,0.880882,0.015238	0/1:0.0398778,0.951817,0.00830562	1/1:0.025359,0.00295701,0.971684	./.:0.118569,0.848748,0.0326829	1/1:0.00435785,0.0230209,0.972621	1/1:0.00811194,0.0224001,0.969488	1/1:0.0185575,0.0335337,0.947909	./.:0.0906568,0.0255168,0.883826	0/1:0.0403838,0.942995,0.0166211	1/1:0.00755941,0.0653485,0.927092	1/1:0.0112374,0.00507048,0.983692	1/1:0.0144833,0.0299461,0.955571	./.:0.0694543,0.0308285,0.899717	1/1:0.0339445,0.00435146,0.961704	1/1:0.0282476,0.0342264,0.937526	1/1:0.0795052,0.0130118,0.907483	1/1:0.0326536,0.0330769,0.93427	1/1:0.0243107,0.00973621,0.965953	0/1:0.00124116,0.98777,0.010989	0/1:0.00548477,0.966598,0.0279173	1/1:0.0314743,0.00316746,0.965358	1/1:0.0237838,0.0281551,0.948061	0/1:0.00429407,0.973073,0.0226329	1/1:0.0120608,0.0606969,0.927242	0/1:0.0210421,0.938546,0.0404122	1/1:0.0701488,0.00185974,0.927991	1/1:0.0493376,0.0292246,0.921438	0/1:0.0499035,0.935747,0.014349	1/1:0.000654433,0.00217569,0.99717	./.:0.103262,0.0205517,0.876186	1/1:0.0224757,0.0591679,0.918356	1/1:0.0214995,0.0314616,0.947039	0/1:0.0379898,0.944268,0.0177421	1/1:0.021328,0.027489,0.951183	1/1:0.06724,0.00734375,0.925416	1/1:0.0189659,0.0332704,0.947764	./.:0.0797317,0.898005,0.0222629	0/1:0.026341,0.969121,0.00453756	1/1:0.0217481,0.0204677,0.957784	1/1:0.00490045,0.0223757,0.972724	1/1:0.0415264,0.0458277,0.912646	./.:0.0511204,0.0537561,0.895123	0/1:0.0105717,0.963693,0.0257349	0/0:0.937322,0.00723122,0.0554466	./.:0.143207,0.0101288,0.846664	0/1:0.0315368,0.951813,0.0166501	1/1:0.038989,0.0165993,0.944412	./.:0.100644,0.183035,0.716321	1/1:0.0823288,0.0128465,0.904825	1/1:0.0034666,0.049338,0.947195	1/1:0.0233664,0.00468681,0.971947	1/1:0.0436117,0.0396148,0.916773	0/1:0.0205411,0.917882,0.0615773	0/1:0.00322377,0.961871,0.0349054	1/1:0.0499616,0.00314309,0.946895	1/1:0.0468127,0.00899458,0.944193	0/1:0.0338638,0.936062,0.0300745	1/1:0.0056396,0.017292,0.977068	1/1:0.00613366,0.0484948,0.945372	1/1:0.00631457,0.0602332,0.933452	./.:0.0691134,0.0618279,0.869059	1/1:0.012638,0.00588526,0.981477	1/1:0.0015112,0.000621104,0.997868	1/1:0.0466233,0.0382781,0.915099	1/1:0.027791,0.00754011,0.964669	1/1:0.00275901,0.00875313,0.988488	./.:0.0478407,0.111212,0.840948	1/1:0.0529263,0.0445907,0.902483	1/1:0.0282028,0.0180073,0.95379	1/1:0.0139361,0.00691779,0.979146	1/1:0.0452405,0.0136163,0.941143	./.:0.102534,0.0259394,0.871527	0/1:0.0446612,0.931562,0.0237766	0/1:0.0442068,0.948338,0.00745547	1/1:0.00399419,0.028948,0.967058	1/1:0.00605696,0.0175714,0.976372	1/1:0.0477588,0.013406,0.938835	0/0:0.947987,0.0354132,0.0165997	1/1:0.00653112,0.00578616,0.987683	./.:0.867035,0.0902634,0.0427012	1/1:0.0643873,0.0188651,0.916748	1/1:0.000842905,0.00590639,0.993251	1/1:0.0630949,0.0309958,0.905909	0/1:0.0458677,0.949031,0.0051017	0/1:0.0172925,0.959727,0.0229802	1/1:0.00718509,0.0334211,0.959394	0/1:0.0166402,0.982376,0.000984025	./.:0.00850386,0.853576,0.13792	0/1:0.0108151,0.983622,0.00556339	1/1:0.00481048,0.0209357,0.974254	1/1:0.0122175,0.0431194,0.944663	1/1:0.0320531,0.0010635,0.966883	1/1:0.00888937,0.0126724,0.978438	1/1:0.0367195,0.0013617,0.961919	1/1:0.0457161,0.0368642,0.91742	1/1:0.0287255,0.0232909,0.947984	./.:0.00381377,0.222103,0.774084	1/1:0.0617475,0.0088487,0.929404	0/0:0.991433,0.00333091,0.00523611	0/1:0.00242355,0.96627,0.0313064	1/1:0.0213438,0.0164512,0.962205	1/1:0.00280492,0.0105787,0.986616	1/1:0.0326335,0.0386607,0.928706	0/1:0.0466641,0.946863,0.00647309	0/1:0.00527895,0.979136,0.0155847	1/1:0.00265403,0.038646,0.9587	1/1:0.0276922,0.00758808,0.96472	0/1:0.0515474,0.938304,0.0101483	1/1:8.05919e-05,0.00504138,0.994878	1/1:0.0495981,0.00187402,0.948528	./.:0.00359426,0.10615,0.890256	1/1:0.00340886,0.0184534,0.978138	0/1:0.0377736,0.933119,0.0291078	1/1:0.052863,0.0199816,0.927155	1/1:0.00211215,0.0745427,0.923345	1/1:0.0371903,0.0054969,0.957313	1/1:0.0317835,0.0178009,0.950416	1/1:0.00925936,0.0117127,0.979028	1/1:0.0141501,0.0375472,0.948303	1/1:0.00122601,0.00427866,0.994495	./.:0.00273981,0.0974786,0.899782	0/1:0.000164116,0.947451,0.0523845	0/1:0.0551723,0.931684,0.0131438	./.:0.10193,0.016837,0.881233	./.:0.0343107,0.0812687,0.884421	0/1:0.020091,0.979088,0.000821213	0/1:0.000642596,0.994601,0.00475618	1/1:0.0644909,0.0289324,0.906577	1/1:0.0044808,0.0043849,0.991134	1/1:0.0564859,0.00692184,0.936592	1/1:0.0193475,0.0685656,0.912087	0/1:0.0364879,0.929134,0.0343783	1/1:0.00259008,0.0374451,0.959965	./.:0.00910023,0.110054,0.880845	1/1:0.0120344,0.00703899,0.980927	1/1:0.0765967,0.004953,0.91845	1/1:0.000718255,0.000674462,0.998607	1/1:0.0105966,0.0460381,0.943365	1/1:0.0107638,0.00694329,0.982293	1/1:0.00319116,0.0566776,0.940131	./.:0.0808961,0.0269019,0.892202	0/1:0.0256116,0.946914,0.0274745	0/1:0.0148058,0.966226,0.0189679	1/1:0.0231881,0.0166036,0.960208	1/1:0.00210352,0.0184419,0.979455	1/1:0.000623254,0.0234305,0.975946	0/1:0.0104944,0.978792,0.0107132	1/1:0.00106302,0.0200414,0.978896	1/1:0.0307733,0.0104072,0.95882	1/1: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-NA	3	RSID_3,SNPID_3	A	G	.	.	.	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-NA	4	RSID_4,SNPID_4	A	G	.	.	.	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-NA	5	RSID_5,SNPID_5	A	G	.	.	.	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-NA	6	RSID_6,SNPID_6	A	G	.	.	.	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-NA	7	RSID_7,SNPID_7	A	G	.	.	.	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-NA	8	RSID_8,SNPID_8	A	G	.	.	.	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-NA	9	RSID_9,SNPID_9	A	G	.	.	.	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-NA	10	RSID_10,SNPID_10	A	G	.	.	.	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+NA	2	RSID_2;DELETION_1	A	-	.	.	.	GT:GP	1/1:0.0765213,0.00738931,0.916089	1/1:0.0278117,0.00864292,0.963545	1/1:0.0173777,0.0496874,0.932935	0/1:0.0248777,0.932817,0.0423053	1/1:0.0346175,0.0191856,0.946197	1/1:0.0624116,0.0162715,0.921317	./.:0.0890426,0.89522,0.0157372	1/1:0.0203313,0.013491,0.966178	1/1:0.0395959,0.0294134,0.930991	1/1:0.0443588,0.0343402,0.921301	1/1:0.0413977,0.0547565,0.903846	./.:0.0833462,0.0513328,0.865321	1/1:0.0204448,0.0430211,0.936534	0/1:0.00342552,0.985194,0.0113801	0/1:0.00726573,0.991422,0.00131274	1/1:0.00212978,0.0130744,0.984796	1/1:0.0433437,0.0240446,0.932612	0/1:0.030966,0.96512,0.00391444	1/1:0.0354075,0.00350694,0.961086	1/1:0.0308428,0.045246,0.923911	1/1:0.0550592,0.00799191,0.936949	./.:0.128164,0.0136164,0.858219	1/1:0.0117565,0.0384459,0.949798	1/1:0.0335148,0.0115101,0.954975	1/1:0.00809348,0.0131524,0.978754	1/1:0.00623515,0.0180752,0.97569	1/1:0.0146414,0.0125058,0.972853	1/1:0.025476,0.00528723,0.969237	1/1:0.00211196,0.0579454,0.939943	1/1:0.0140452,0.00261017,0.983345	1/1:0.0355083,0.0597193,0.904772	1/1:0.0257136,0.00281197,0.971474	0/1:0.0142856,0.948082,0.0376327	1/1:0.0397819,0.0203298,0.939888	1/1:0.00470346,0.00871748,0.986579	1/1:0.00622709,0.00439993,0.989373	1/1:0.0452334,0.0078768,0.94689	0/1:0.0751067,0.922155,0.002738	1/1:0.0304864,0.00329875,0.966215	1/1:0.022215,0.0297167,0.948068	0/0:0.971078,0.00121635,0.0277058	0/1:0.00669808,0.992912,0.000390372	1/1:0.00366201,0.00229824,0.99404	1/1:0.0358488,0.0184567,0.945695	0/1:0.000127906,0.982611,0.0172609	0/1:0.0269364,0.967933,0.00513028	1/1:0.0363318,0.0091488,0.954519	0/1:0.0218157,0.951233,0.0269512	1/1:0.0102727,0.00562367,0.984104	1/1:0.00458934,0.0495853,0.945825	1/1:0.00532228,0.0157015,0.978976	1/1:0.0053079,0.000927737,0.993764	1/1:0.0264865,0.0254771,0.948036	1/1:0.0522013,0.00111124,0.946687	1/1:0.0164378,0.00560304,0.977959	1/1:0.0626507,0.00508806,0.932261	0/1:0.00161383,0.979377,0.0190092	0/0:0.966122,0.00132746,0.0325505	1/1:0.0155659,0.00569339,0.978741	1/1:0.0202013,0.000290894,0.979508	1/1:0.0281994,0.00773169,0.964069	./.:0.0508201,0.0542616,0.894918	0/1:0.0310162,0.941976,0.0270078	1/1:0.0455028,0.0162002,0.938297	0/1:0.0184549,0.936524,0.045021	0/1:0.0361544,0.922292,0.0415535	1/1:0.0427266,0.036398,0.920875	1/1:0.00544581,0.017418,0.977136	1/1:0.00248236,0.0113308,0.986187	0/1:0.0112173,0.980356,0.00842722	0/1:0.00144022,0.989422,0.00913776	1/1:3.11376e-05,0.0425171,0.957452	1/1:0.0187048,0.0104851,0.97081	1/1:0.00624943,0.035127,0.958624	0/1:0.0257277,0.950684,0.023588	1/1:0.01295,0.0670332,0.920017	1/1:0.0165091,0.0414055,0.942085	1/1:0.000603927,0.0290382,0.970358	0/1:0.0255638,0.970474,0.00396241	0/1:0.0144861,0.967365,0.0181491	1/1:0.00461234,0.0602488,0.935139	1/1:0.0382218,0.00626481,0.955513	1/1:0.0596664,0.0231397,0.917194	1/1:0.0179393,0.0391777,0.942883	0/1:0.0134928,0.943517,0.0429902	1/1:0.0774595,0.0114083,0.911132	1/1:0.0176584,0.00339778,0.978944	1/1:0.0100261,0.0271536,0.96282	1/1:0.0130068,0.0141708,0.972822	0/1:0.00734218,0.943733,0.0489247	./.:0.062756,0.0610352,0.876209	1/1:0.0270041,0.0134642,0.959532	1/1:0.00411924,0.0168011,0.97908	./.:0.0515086,0.887631,0.0608606	0/1:0.0135331,0.978956,0.00751137	1/1:0.0307017,0.000968173,0.96833	1/1:0.0153662,0.0120846,0.972549	1/1:0.00044704,0.0492262,0.950327	./.:0.110592,0.00344009,0.885968	1/1:0.0164569,0.0277545,0.955789	1/1:0.00375503,0.0400653,0.95618	1/1:0.00276732,0.0325795,0.964653	0/1:0.0317738,0.954008,0.0142186	./.:0.0332177,0.0885011,0.878281	./.:0.0779957,0.0638195,0.858185	1/1:0.00664966,0.0874973,0.905853	0/1:0.00581931,0.970621,0.0235596	1/1:0.0102489,0.00409048,0.985661	./.:0.00252458,0.118531,0.878945	0/1:0.00481888,0.990939,0.00424204	1/1:0.0142779,0.014817,0.970905	0/1:0.00742485,0.979232,0.0133436	0/1:0.0259031,0.956843,0.0172542	./.:0.104541,0.880652,0.014807	1/1:0.0694247,0.0148819,0.915693	0/1:0.00757589,0.99137,0.00105374	0/1:0.0429337,0.948554,0.00851256	1/1:0.00232002,0.0135248,0.984155	1/1:0.00385322,0.00367388,0.992473	0/1:0.0191218,0.970571,0.010307	1/1:0.00953562,0.026791,0.963673	0/1:0.0018121,0.978612,0.0195761	1/1:0.00221615,0.000487307,0.997297	1/1:0.000169594,0.00836001,0.99147	0/1:0.0132875,0.977977,0.00873553	1/1:0.0318824,0.0044041,0.963714	1/1:0.00838779,0.000825634,0.990787	./.:0.109297,0.00548867,0.885215	1/1:0.00871124,0.0323483,0.95894	0/1:0.00702381,0.915908,0.0770681	1/1:0.0211908,0.0483898,0.930419	0/1:0.0338834,0.922492,0.0436242	0/1:0.030799,0.966864,0.00233682	1/1:0.0160218,0.0126794,0.971299	1/1:0.00806931,0.00963224,0.982298	1/1:0.0194903,0.0150679,0.965442	1/1:0.035366,0.0389562,0.925678	1/1:0.00267017,0.0382586,0.959071	0/1:0.00388209,0.985784,0.010334	./.:0.0982637,0.0382897,0.863447	0/1:0.0022618,0.919474,0.0782647	1/1:2.49412e-05,0.0167737,0.983201	./.:0.0582512,0.0492292,0.89252	0/1:0.00845342,0.953394,0.0381527	1/1:0.0272179,0.0196223,0.95316	1/1:0.0567382,0.0166038,0.926658	./.:0.12687,0.872336,0.000794047	0/1:0.0204258,0.941278,0.0382964	1/1:0.0232436,0.00367961,0.973077	0/1:0.00880893,0.921912,0.0692794	1/1:0.0216899,0.0273385,0.950972	1/1:0.0426108,0.0204562,0.936933	0/1:0.0104113,0.970103,0.0194862	1/1:0.058506,0.0250296,0.916464	1/1:0.0142527,0.0481697,0.937578	1/1:0.0352332,0.00821716,0.95655	1/1:0.00704378,0.00383585,0.98912	0/1:0.0618883,0.923708,0.0144034	1/1:0.00947037,0.028737,0.961793	0/1:0.0358306,0.959207,0.0049623	1/1:0.0419056,0.00609378,0.952001	1/1:0.0511185,0.00073821,0.948143	1/1:0.0235176,0.0614284,0.915054	1/1:0.0423645,0.050623,0.907012	1/1:0.01013,0.0889667,0.900903	1/1:0.00197436,0.0733078,0.924718	./.:0.0783761,0.0315562,0.890068	1/1:0.0635035,0.0172963,0.9192	1/1:0.0394675,0.00484857,0.955684	1/1:0.0249377,0.021648,0.953414	0/1:0.0118272,0.95642,0.0317532	1/1:0.0132819,0.0262284,0.96049	1/1:0.0203168,0.0178358,0.961847	1/1:0.0280182,0.0369552,0.935027	1/1:0.050963,0.0110882,0.937949	1/1:0.0256438,0.00415634,0.9702	1/1:0.0140764,0.0479012,0.938022	1/1:0.00702359,0.0359428,0.957034	1/1:0.0230789,0.0120966,0.964825	0/1:0.0615742,0.929984,0.0084413	0/1:0.028977,0.968539,0.00248423	1/1:0.0202895,0.0614246,0.918286	1/1:0.0282214,0.0483363,0.923442	1/1:0.0619251,0.0218439,0.916231	1/1:0.00706208,0.0120217,0.980916	0/1:0.00640163,0.961214,0.032384	0/0:0.991858,0.00380923,0.00433243	./.:0.0470269,0.082571,0.870402	0/1:0.0519842,0.944215,0.00380044	0/1:0.0620133,0.914345,0.0236416	./.:0.186934,0.0114153,0.80165	1/1:0.000345943,0.0235675,0.976087	1/1:0.0326442,0.00235391,0.965002	1/1:0.00532184,0.0183645,0.976314	0/1:0.00903543,0.965256,0.0257083	1/1:0.00619173,0.0135111,0.980297	0/1:0.00584457,0.95686,0.0372956	1/1:0.00593699,0.0612912,0.932772	1/1:0.0269436,0.0389198,0.934137	1/1:0.0356937,0.0327066,0.9316	1/1:0.0561839,0.00373752,0.940079	1/1:0.0511941,0.0157286,0.933077	1/1:0.078324,0.0198007,0.901875	1/1:0.000779039,0.0401042,0.959117	1/1:0.0106681,0.0217184,0.967614	0/1:0.0448439,0.914974,0.0401817	0/1:0.00030371,0.985059,0.0146377	0/1:0.039209,0.956317,0.00447422	1/1:0.0284045,0.0646966,0.906899	./.:0.0397172,0.895523,0.0647601	0/0:0.981547,0.00240078,0.0160523	1/1:0.00361121,0.00497761,0.991411	1/1:0.0280749,0.0110312,0.960894	1/1:0.0253983,0.0222725,0.952329	1/1:0.0397773,0.0458102,0.914413	0/1:0.0249766,0.916817,0.0582059	1/1:0.0503006,0.0427178,0.906982	0/1:0.0461137,0.935709,0.0181774	1/1:0.0395516,0.0561328,0.904316	1/1:0.0103299,0.0181879,0.971482	1/1:0.0076416,0.0403221,0.952036	1/1:0.019195,0.0253848,0.95542	1/1:0.00872853,0.0280844,0.963187	1/1:0.0220789,0.0640545,0.913867	1/1:0.0502671,0.0229983,0.926735	1/1:0.00837678,7.85657e-05,0.991545	./.:0.00126481,0.85077,0.147965	0/1:0.0260687,0.919439,0.0544925	0/1:0.00773965,0.991731,0.000528911	1/1:0.0242448,0.011632,0.964123	1/1:0.0448744,0.00833587,0.94679	1/1:0.0195972,0.00775482,0.972648	./.:0.094565,0.0196051,0.88583	1/1:0.0219288,0.0154441,0.962627	0/1:0.0128967,0.980922,0.00618099	1/1:0.0133328,0.0111186,0.975549	1/1:0.0209894,0.0618488,0.917162	1/1:0.0309362,0.00195092,0.967113	0/1:0.0209576,0.97443,0.00461241	1/1:0.0215581,0.0119414,0.9665	1/1:0.0294206,0.0593992,0.91118	1/1:0.0431204,0.0414609,0.915419	1/1:6.64084e-07,0.0104027,0.989597	1/1:0.0264899,0.00513652,0.968374	1/1:0.00962836,0.0012802,0.989091	1/1:0.00262166,0.0280628,0.969316	0/1:0.00436423,0.967383,0.0282524	0/1:0.0166533,0.972714,0.0106325	0/1:0.00737717,0.981342,0.0112812	0/1:0.0208076,0.950085,0.0291073	1/1:0.0173471,0.00669082,0.975962	1/1:0.026793,0.0257043,0.947503	1/1:0.0233496,0.00436309,0.972287	1/1:0.0208317,0.0184149,0.960753	0/1:0.0274726,0.934305,0.0382225	0/1:0.021481,0.960822,0.0176974	0/1:0.0476554,0.939072,0.0132728	0/1:0.0234288,0.967458,0.0091133	0/1:0.0141893,0.951599,0.034212	0/1:0.00419246,0.970974,0.024834	0/1:8.37918e-05,0.920339,0.0795777	1/1:0.0109809,0.0149742,0.974045	1/1:0.0613423,0.0350763,0.903581	1/1:0.0516634,0.0332994,0.915037	0/1:0.0415676,0.957151,0.00128121	0/1:0.0040198,0.985329,0.0106516	./.:0.0183737,0.14258,0.839047	1/1:0.00407833,0.0247806,0.971141	1/1:0.00978301,0.0359626,0.954254	0/1:0.047259,0.917512,0.0352294	0/1:0.0051346,0.989586,0.00527964	0/1:0.0388345,0.952014,0.00915128	0/1:0.0490986,0.923002,0.0278998	0/1:0.0242299,0.967634,0.00813596	0/1:0.0787345,0.920511,0.000754718	1/1:0.00522087,0.0133353,0.981444	0/1:0.00489867,0.978843,0.016258	1/1:0.00542466,0.00122524,0.99335	0/1:0.0143657,0.984541,0.00109371	1/1:0.00252614,0.0177165,0.979757	1/1:0.0730979,0.0046939,0.922208	1/1:0.0172776,0.00380916,0.978913	1/1:0.00321306,0.0263511,0.970436	0/0:0.986966,0.0100988,0.00293523	0/1:0.00127376,0.98952,0.0092064	0/1:0.00369403,0.976305,0.0200013	0/1:0.0418657,0.927221,0.0309128	1/1:8.66898e-05,0.0417915,0.958122	0/1:0.00617715,0.95733,0.0364927	1/1:0.0216624,0.0125235,0.965814	0/1:0.0384431,0.956619,0.00493833	./.:0.091695,0.0296694,0.878636	0/1:0.00775148,0.977032,0.0152162	0/1:0.0345039,0.96546,3.61777e-05	0/1:0.00244344,0.988914,0.00864281	1/1:0.0396826,0.0435855,0.916732	0/1:0.0195579,0.96012,0.0203217	0/1:0.0713879,0.927713,0.000898868	0/1:0.063115,0.929048,0.00783668	./.:0.0410352,0.0697608,0.889204	1/1:0.000479687,0.0628162,0.936704	./.:0.10388,0.880882,0.015238	0/1:0.0398778,0.951817,0.00830562	1/1:0.025359,0.00295701,0.971684	./.:0.118569,0.848748,0.0326829	1/1:0.00435785,0.0230209,0.972621	1/1:0.00811194,0.0224001,0.969488	1/1:0.0185575,0.0335337,0.947909	./.:0.0906568,0.0255168,0.883826	0/1:0.0403838,0.942995,0.0166211	1/1:0.00755941,0.0653485,0.927092	1/1:0.0112374,0.00507048,0.983692	1/1:0.0144833,0.0299461,0.955571	./.:0.0694543,0.0308285,0.899717	1/1:0.0339445,0.00435146,0.961704	1/1:0.0282476,0.0342264,0.937526	1/1:0.0795052,0.0130118,0.907483	1/1:0.0326536,0.0330769,0.93427	1/1:0.0243107,0.00973621,0.965953	0/1:0.00124116,0.98777,0.010989	0/1:0.00548477,0.966598,0.0279173	1/1:0.0314743,0.00316746,0.965358	1/1:0.0237838,0.0281551,0.948061	0/1:0.00429407,0.973073,0.0226329	1/1:0.0120608,0.0606969,0.927242	0/1:0.0210421,0.938546,0.0404122	1/1:0.0701488,0.00185974,0.927991	1/1:0.0493376,0.0292246,0.921438	0/1:0.0499035,0.935747,0.014349	1/1:0.000654433,0.00217569,0.99717	./.:0.103262,0.0205517,0.876186	1/1:0.0224757,0.0591679,0.918356	1/1:0.0214995,0.0314616,0.947039	0/1:0.0379898,0.944268,0.0177421	1/1:0.021328,0.027489,0.951183	1/1:0.06724,0.00734375,0.925416	1/1:0.0189659,0.0332704,0.947764	./.:0.0797317,0.898005,0.0222629	0/1:0.026341,0.969121,0.00453756	1/1:0.0217481,0.0204677,0.957784	1/1:0.00490045,0.0223757,0.972724	1/1:0.0415264,0.0458277,0.912646	./.:0.0511204,0.0537561,0.895123	0/1:0.0105717,0.963693,0.0257349	0/0:0.937322,0.00723122,0.0554466	./.:0.143207,0.0101288,0.846664	0/1:0.0315368,0.951813,0.0166501	1/1:0.038989,0.0165993,0.944412	./.:0.100644,0.183035,0.716321	1/1:0.0823288,0.0128465,0.904825	1/1:0.0034666,0.049338,0.947195	1/1:0.0233664,0.00468681,0.971947	1/1:0.0436117,0.0396148,0.916773	0/1:0.0205411,0.917882,0.0615773	0/1:0.00322377,0.961871,0.0349054	1/1:0.0499616,0.00314309,0.946895	1/1:0.0468127,0.00899458,0.944193	0/1:0.0338638,0.936062,0.0300745	1/1:0.0056396,0.017292,0.977068	1/1:0.00613366,0.0484948,0.945372	1/1:0.00631457,0.0602332,0.933452	./.:0.0691134,0.0618279,0.869059	1/1:0.012638,0.00588526,0.981477	1/1:0.0015112,0.000621104,0.997868	1/1:0.0466233,0.0382781,0.915099	1/1:0.027791,0.00754011,0.964669	1/1:0.00275901,0.00875313,0.988488	./.:0.0478407,0.111212,0.840948	1/1:0.0529263,0.0445907,0.902483	1/1:0.0282028,0.0180073,0.95379	1/1:0.0139361,0.00691779,0.979146	1/1:0.0452405,0.0136163,0.941143	./.:0.102534,0.0259394,0.871527	0/1:0.0446612,0.931562,0.0237766	0/1:0.0442068,0.948338,0.00745547	1/1:0.00399419,0.028948,0.967058	1/1:0.00605696,0.0175714,0.976372	1/1:0.0477588,0.013406,0.938835	0/0:0.947987,0.0354132,0.0165997	1/1:0.00653112,0.00578616,0.987683	./.:0.867035,0.0902634,0.0427012	1/1:0.0643873,0.0188651,0.916748	1/1:0.000842905,0.00590639,0.993251	1/1:0.0630949,0.0309958,0.905909	0/1:0.0458677,0.949031,0.0051017	0/1:0.0172925,0.959727,0.0229802	1/1:0.00718509,0.0334211,0.959394	0/1:0.0166402,0.982376,0.000984025	./.:0.00850386,0.853576,0.13792	0/1:0.0108151,0.983622,0.00556339	1/1:0.00481048,0.0209357,0.974254	1/1:0.0122175,0.0431194,0.944663	1/1:0.0320531,0.0010635,0.966883	1/1:0.00888937,0.0126724,0.978438	1/1:0.0367195,0.0013617,0.961919	1/1:0.0457161,0.0368642,0.91742	1/1:0.0287255,0.0232909,0.947984	./.:0.00381377,0.222103,0.774084	1/1:0.0617475,0.0088487,0.929404	0/0:0.991433,0.00333091,0.00523611	0/1:0.00242355,0.96627,0.0313064	1/1:0.0213438,0.0164512,0.962205	1/1:0.00280492,0.0105787,0.986616	1/1:0.0326335,0.0386607,0.928706	0/1:0.0466641,0.946863,0.00647309	0/1:0.00527895,0.979136,0.0155847	1/1:0.00265403,0.038646,0.9587	1/1:0.0276922,0.00758808,0.96472	0/1:0.0515474,0.938304,0.0101483	1/1:8.05919e-05,0.00504138,0.994878	1/1:0.0495981,0.00187402,0.948528	./.:0.00359426,0.10615,0.890256	1/1:0.00340886,0.0184534,0.978138	0/1:0.0377736,0.933119,0.0291078	1/1:0.052863,0.0199816,0.927155	1/1:0.00211215,0.0745427,0.923345	1/1:0.0371903,0.0054969,0.957313	1/1:0.0317835,0.0178009,0.950416	1/1:0.00925936,0.0117127,0.979028	1/1:0.0141501,0.0375472,0.948303	1/1:0.00122601,0.00427866,0.994495	./.:0.00273981,0.0974786,0.899782	0/1:0.000164116,0.947451,0.0523845	0/1:0.0551723,0.931684,0.0131438	./.:0.10193,0.016837,0.881233	./.:0.0343107,0.0812687,0.884421	0/1:0.020091,0.979088,0.000821213	0/1:0.000642596,0.994601,0.00475618	1/1:0.0644909,0.0289324,0.906577	1/1:0.0044808,0.0043849,0.991134	1/1:0.0564859,0.00692184,0.936592	1/1:0.0193475,0.0685656,0.912087	0/1:0.0364879,0.929134,0.0343783	1/1:0.00259008,0.0374451,0.959965	./.:0.00910023,0.110054,0.880845	1/1:0.0120344,0.00703899,0.980927	1/1:0.0765967,0.004953,0.91845	1/1:0.000718255,0.000674462,0.998607	1/1:0.0105966,0.0460381,0.943365	1/1:0.0107638,0.00694329,0.982293	1/1:0.00319116,0.0566776,0.940131	./.:0.0808961,0.0269019,0.892202	0/1:0.0256116,0.946914,0.0274745	0/1:0.0148058,0.966226,0.0189679	1/1:0.0231881,0.0166036,0.960208	1/1:0.00210352,0.0184419,0.979455	1/1:0.000623254,0.0234305,0.975946	0/1:0.0104944,0.978792,0.0107132	1/1:0.00106302,0.0200414,0.978896	1/1:0.0307733,0.0104072,0.95882	1/1: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+NA	3	RSID_3;SNPID_3	A	G	.	.	.	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Index: release/test/data/test.vcf
==================================================================
--- release/test/data/test.vcf
+++ release/test/data/test.vcf
@@ -1,15 +1,15 @@
 ##fileformat=VCFv4.2
 ##FORMAT=<ID=GT,Type=String,Number=1,Description="Threshholded genotype call">
 ##FORMAT=<ID=GP,Type=Float,Number=G,Description="Genotype call probabilities">
 ##FORMAT=<ID=HP,Type=Float,Number=.,Description="Haplotype call probabilities">
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.,.,.
-01	2	RSID_2,DELETION_1	A	-	.	.	.	GT:GP	1/1:0.076524,0.00738537,0.916091	1/1:0.0278172,0.00863661,0.963546	1/1:0.01738,0.0496834,0.932937	0/1:0.0248722,0.932815,0.0423133	1/1:0.0346227,0.0191806,0.946197	1/1:0.0624094,0.0162661,0.921324	./.:0.0890517,0.895216,0.0157321	1/1:0.020325,0.013489,0.966186	1/1:0.0395972,0.0294041,0.930999	1/1:0.044358,0.0343481,0.921294	1/1:0.0413977,0.0547494,0.903853	./.:0.0833448,0.0513313,0.865324	1/1:0.0204471,0.0430152,0.936538	0/1:0.00341802,0.985199,0.0113832	0/1:0.00726329,0.991424,0.00131228	1/1:0.00213626,0.0130617,0.984802	1/1:0.0433356,0.0240482,0.932616	0/1:0.0309758,0.965118,0.00390631	1/1:0.0354009,0.00350958,0.961089	1/1:0.0308385,0.045243,0.923919	1/1:0.0550546,0.00799573,0.93695	./.:0.128161,0.0136263,0.858213	1/1:0.0117494,0.0384527,0.949798	1/1:0.0335241,0.0115053,0.954971	1/1:0.00808728,0.0131533,0.978759	1/1:0.00624094,0.0180819,0.975677	1/1:0.0146334,0.0125124,0.972854	1/1:0.0254826,0.00527962,0.969238	1/1:0.00210575,0.0579538,0.93994	1/1:0.0140383,0.00260929,0.983352	1/1:0.0355077,0.0597238,0.904768	1/1:0.0257115,0.00280766,0.971481	0/1:0.0142977,0.948074,0.0376287	1/1:0.0397803,0.020325,0.939895	1/1:0.00469978,0.0087129,0.986587	1/1:0.00622568,0.0043946,0.98938	1/1:0.0452277,0.00787366,0.946899	0/1:0.0751049,0.922164,0.00273136	1/1:0.0304875,0.00329595,0.966217	1/1:0.0222171,0.0297246,0.948058	0/0:0.971069,0.00122072,0.0277104	0/1:0.00669871,0.992905,0.000396735	1/1:0.00366217,0.00230411,0.994034	1/1:0.0358434,0.0184634,0.945693	0/1:0.000122072,0.98262,0.017258	0/1:0.0269322,0.967941,0.00512703	1/1:0.0363317,0.00915541,0.954513	0/1:0.0218204,0.951232,0.0269474	1/1:0.0102693,0.00563058,0.9841	1/1:0.00459297,0.0495766,0.94583	1/1:0.0053254,0.0157015,0.978973	1/1:0.00531014,0.0009308,0.993759	1/1:0.0264897,0.0254826,0.948028	1/1:0.0522011,0.00111391,0.946685	1/1:0.016434,0.00560006,0.977966	1/1:0.0626535,0.00508125,0.932265	0/1:0.00161746,0.97937,0.0190127	0/0:0.966125,0.00132753,0.0325475	1/1:0.0155642,0.00569162,0.978744	1/1:0.0202029,0.000289921,0.979507	1/1:0.0281987,0.00773632,0.964065	./.:0.0508278,0.0542611,0.894911	0/1:0.0310216,0.94197,0.0270085	1/1:0.0455024,0.0162051,0.938293	0/1:0.0184482,0.936538,0.0450141	0/1:0.0361486,0.922301,0.0415503	1/1:0.0427253,0.036408,0.920867	1/1:0.00544747,0.0174258,0.977127	1/1:0.00248722,0.0113222,0.986191	0/1:0.0112154,0.980346,0.00843824	0/1:0.00143435,0.989425,0.00914015	1/1:3.0518e-05,0.0425116,0.957458	1/1:0.0187076,0.0104829,0.970809	1/1:0.0062562,0.0351263,0.958618	0/1:0.0257267,0.950683,0.0235904	1/1:0.0129549,0.0670329,0.920012	1/1:0.0165103,0.041413,0.942077	1/1:0.000610361,0.0290379,0.970352	0/1:0.0255589,0.970474,0.00396735	0/1:0.0144808,0.967361,0.0181582	1/1:0.00460822,0.0602426,0.935149	1/1:0.0382238,0.00627146,0.955505	1/1:0.0596628,0.0231479,0.917189	1/1:0.0179446,0.0391699,0.942885	0/1:0.013489,0.943526,0.0429847	1/1:0.0774548,0.0114137,0.911131	1/1:0.0176547,0.00340276,0.978943	1/1:0.0100252,0.0271458,0.962829	1/1:0.0130007,0.0141756,0.972824	0/1:0.00733959,0.94374,0.0489204	./.:0.0627604,0.0610361,0.876204	1/1:0.0270085,0.0134585,0.959533	1/1:0.00411994,0.0168002,0.97908	./.:0.0515145,0.887633,0.060853	0/1:0.0135348,0.978958,0.00750744	1/1:0.0307012,0.000961318,0.968338	1/1:0.0153658,0.0120851,0.972549	1/1:0.000442512,0.0492256,0.950332	./.:0.110597,0.00343328,0.885969	1/1:0.0164492,0.0277562,0.955795	1/1:0.00375372,0.0400702,0.956176	1/1:0.00277714,0.032578,0.964645	0/1:0.0317693,0.954009,0.0142214	./.:0.0332189,0.0885023,0.878279	./.:0.0780041,0.0638132,0.858183	1/1:0.00665293,0.0874952,0.905852	0/1:0.00581369,0.970626,0.0235599	1/1:0.0102541,0.00408942,0.985657	./.:0.00251774,0.118532,0.87895	0/1:0.00482185,0.990936,0.00424201	1/1:0.0142824,0.0148165,0.970901	0/1:0.00741588,0.979232,0.0133516	0/1:0.0258946,0.956802,0.0173037	./.:0.10454,0.880644,0.0148165	1/1:0.0694285,0.0148775,0.915694	0/1:0.00758373,0.991363,0.00105287	0/1:0.0429236,0.948562,0.00851453	1/1:0.00231937,0.0135195,0.984161	1/1:0.00384527,0.00367742,0.992477	0/1:0.0191196,0.970565,0.0103151	1/1:0.00953689,0.0267948,0.963668	0/1:0.00181582,0.978607,0.0195773	1/1:0.00221256,0.000488289,0.997299	1/1:0.000167849,0.00836194,0.99147	0/1:0.0132906,0.977981,0.00872816	1/1:0.0318761,0.0043946,0.963729	1/1:0.00839246,0.000823987,0.990784	./.:0.1093,0.00549325,0.885206	1/1:0.0087129,0.0323491,0.958938	0/1:0.00701915,0.915908,0.0770733	1/1:0.0211948,0.0483864,0.930419	0/1:0.033875,0.922499,0.0436255	0/1:0.0307927,0.966873,0.00233463	1/1:0.016022,0.0126802,0.971298	1/1:0.00807202,0.00962844,0.9823	1/1:0.0194858,0.0150759,0.965438	1/1:0.0353704,0.0389563,0.925673	1/1:0.00267033,0.0382544,0.959075	0/1:0.00387579,0.985794,0.0103304	./.:0.0982681,0.0382849,0.863447	0/1:0.00225834,0.919478,0.0782635	1/1:3.0518e-05,0.0167697,0.9832	./.:0.0582589,0.0492256,0.892515	0/1:0.0084535,0.953399,0.0381476	1/1:0.0272221,0.0196231,0.953155	1/1:0.056733,0.0166018,0.926665	./.:0.126864,0.872343,0.000793469	0/1:0.0204166,0.941283,0.0383001	1/1:0.0232395,0.00367742,0.973083	0/1:0.00880446,0.92192,0.069276	1/1:0.0216831,0.0273442,0.950973	1/1:0.0426032,0.0204623,0.936934	0/1:0.0104067,0.970108,0.0194858	1/1:0.0585031,0.0250248,0.916472	1/1:0.0142519,0.0481727,0.937575	1/1:0.0352331,0.00822461,0.956542	1/1:0.00704967,0.00383001,0.98912	0/1:0.0618906,0.923705,0.0144045	1/1:0.00947585,0.0287327,0.961791	0/1:0.0358282,0.959213,0.00495918	1/1:0.0419013,0.00610361,0.951995	1/1:0.0511177,0.000732433,0.94815	1/1:0.0235142,0.0614328,0.915053	1/1:0.042359,0.0506294,0.907012	1/1:0.010132,0.0889601,0.900908	1/1:0.00196841,0.0733043,0.924727	./.:0.0783703,0.0315557,0.890074	1/1:0.0634928,0.0173037,0.919203	1/1:0.0394598,0.00485237,0.955688	1/1:0.0249332,0.0216526,0.953414	0/1:0.0118257,0.95642,0.031754	1/1:0.0132753,0.0262303,0.960494	1/1:0.0203098,0.0178378,0.961852	1/1:0.0280156,0.0369574,0.935027	1/1:0.0509651,0.011078,0.937957	1/1:0.0256504,0.00415045,0.970199	1/1:0.0140841,0.0478981,0.938018	1/1:0.00701915,0.0359503,0.957031	1/1:0.0230716,0.0121004,0.964828	0/1:0.0615702,0.929992,0.00843824	0/1:0.0289769,0.968536,0.00248722	1/1:0.0202945,0.0614176,0.918288	1/1:0.0282139,0.0483406,0.923445	1/1:0.0619211,0.0218509,0.916228	1/1:0.00706493,0.0120241,0.980911	0/1:0.00639353,0.961227,0.0323796	0/0:0.991852,0.00381476,0.00433356	./.:0.0470283,0.0825666,0.870405	0/1:0.0519875,0.944213,0.0037995	0/1:0.0620127,0.914351,0.0236362	./.:0.186938,0.0114137,0.801648	1/1:0.000350958,0.0235599,0.976089	1/1:0.032639,0.00234989,0.965011	1/1:0.0053254,0.0183566,0.976318	0/1:0.00903334,0.965255,0.0257115	1/1:0.00619516,0.0135042,0.980301	0/1:0.00584421,0.956863,0.037293	1/1:0.00593576,0.0612955,0.932769	1/1:0.0269474,0.0389105,0.934142	1/1:0.0356909,0.0327001,0.931609	1/1:0.0561837,0.00373846,0.940078	1/1:0.051194,0.0157321,0.933074	1/1:0.0783246,0.019791,0.901884	1/1:0.00077821,0.0401007,0.959121	1/1:0.0106661,0.0217288,0.967605	0/1:0.0448463,0.914977,0.040177	0/1:0.00030518,0.985061,0.0146334	0/1:0.0392157,0.956313,0.00447089	1/1:0.028397,0.0646983,0.906905	./.:0.0397192,0.895521,0.0647593	0/0:0.981552,0.00239567,0.0160525	1/1:0.00361639,0.00497444,0.991409	1/1:0.0280766,0.0110323,0.960891	1/1:0.025391,0.0222782,0.952331	1/1:0.0397803,0.0458076,0.914412	0/1:0.024979,0.916808,0.0582132	1/1:0.0502937,0.0427253,0.906981	0/1:0.0461128,0.935714,0.0181735	1/1:0.0395514,0.0561379,0.904311	1/1:0.0103304,0.0181888,0.971481	1/1:0.00764477,0.0403143,0.952041	1/1:0.0191958,0.0253758,0.955428	1/1:0.00872816,0.0280919,0.96318	1/1:0.0220798,0.0640574,0.913863	1/1:0.0502632,0.0229953,0.926741	1/1:0.0083772,7.62951e-05,0.991547	./.:0.0012665,0.850767,0.147967	0/1:0.0260777,0.919432,0.05449	0/1:0.00773632,0.99173,0.000534066	1/1:0.0242466,0.0116274,0.964126	1/1:0.0448768,0.00833143,0.946792	1/1:0.0195926,0.00775158,0.972656	./.:0.0945602,0.0196078,0.885832	1/1:0.0219272,0.0154421,0.962631	0/1:0.0128939,0.980926,0.0061799	1/1:0.0133211,0.0111238,0.975555	1/1:0.0209964,0.0618448,0.917159	1/1:0.03093,0.00195315,0.967117	0/1:0.0209659,0.974426,0.00460822	1/1:0.021561,0.0119326,0.966506	1/1:0.0294194,0.0594034,0.911177	1/1:0.043122,0.0414588,0.915419	1/1:0,0.0104067,0.989593	1/1:0.0264897,0.00514229,0.968368	1/1:0.00962844,0.00128176,0.98909	1/1:0.00262455,0.0280613,0.969314	0/1:0.00436408,0.967391,0.0282444	0/1:0.0166476,0.972717,0.0106355	0/1:0.00738537,0.981338,0.0112764	0/1:0.0208133,0.950088,0.029099	1/1:0.0173495,0.00668345,0.975967	1/1:0.0267948,0.0256962,0.947509	1/1:0.0233463,0.00436408,0.97229	1/1:0.0208286,0.0184176,0.960754	0/1:0.0274662,0.93431,0.0382238	0/1:0.0214847,0.960815,0.0177005	0/1:0.0476539,0.939071,0.0132753	0/1:0.0234226,0.967468,0.00910964	0/1:0.0141909,0.951598,0.0342107	0/1:0.00419623,0.970977,0.0248264	0/1:9.15541e-05,0.920333,0.0795758	1/1:0.0109865,0.0149691,0.974044	1/1:0.0613413,0.0350805,0.903578	1/1:0.051667,0.0332952,0.915038	0/1:0.0415656,0.957153,0.00128176	0/1:0.00401312,0.985336,0.0106508	./.:0.0183719,0.14258,0.839048	1/1:0.00407416,0.0247807,0.971145	1/1:0.00978103,0.0359655,0.954253	0/1:0.0472572,0.91751,0.0352331	0/1:0.00512703,0.989593,0.00527962	0/1:0.0388342,0.95201,0.00915541	0/1:0.0491035,0.923003,0.0278935	0/1:0.0242313,0.967636,0.00813306	0/1:0.0787366,0.920516,0.000747692	1/1:0.00521859,0.0133364,0.981445	0/1:0.00489815,0.978836,0.0162661	1/1:0.00541695,0.00123598,0.993347	0/1:0.0143587,0.984543,0.00109865	1/1:0.002533,0.0177157,0.979751	1/1:0.073106,0.00468452,0.92221	1/1:0.0172732,0.00381476,0.978912	1/1:0.00321965,0.0263523,0.970428	0/0:0.986954,0.0101015,0.00294499	0/1:0.0012665,0.989532,0.00920119	0/1:0.00369268,0.976303,0.0200046	0/1:0.0418708,0.927214,0.0309148	1/1:9.15541e-05,0.0417945,0.958114	0/1:0.0061799,0.957336,0.0364843	1/1:0.0216678,0.0125124,0.96582	0/1:0.0384375,0.956619,0.00494392	./.:0.0916915,0.0296635,0.878645	0/1:0.00775158,0.977035,0.0152132	0/1:0.0345006,0.965469,3.0518e-05	0/1:0.00244144,0.988922,0.00863661	1/1:0.0396735,0.043595,0.916732	0/1:0.0195621,0.960113,0.020325	0/1:0.0713817,0.927718,0.000900282	0/1:0.0631113,0.929046,0.00784314	./.:0.0410315,0.0697642,0.889204	1/1:0.00047303,0.0628214,0.936706	./.:0.103883,0.880873,0.0152438	0/1:0.0398718,0.951812,0.00831617	1/1:0.0253605,0.00296025,0.971679	./.:0.118563,0.848753,0.0326848	1/1:0.00436408,0.0230259,0.97261	1/1:0.0081178,0.0224002,0.969482	1/1:0.018555,0.0335241,0.947921	./.:0.0906538,0.0255131,0.883833	0/1:0.0403906,0.942992,0.0166171	1/1:0.00755322,0.0653544,0.927092	1/1:0.0112459,0.005066,0.983688	1/1:0.0144808,0.0299535,0.955566	./.:0.0694591,0.0308232,0.899718	1/1:0.0339361,0.00434882,0.961715	1/1:0.0282444,0.034226,0.93753	1/1:0.0794995,0.0130159,0.907485	1/1:0.0326543,0.0330816,0.934264	1/1:0.0243076,0.00973526,0.965957	0/1:0.00123598,0.987778,0.0109865	0/1:0.00547799,0.966598,0.027924	1/1:0.0314794,0.00315862,0.965362	1/1:0.0237888,0.0281529,0.948058	0/1:0.00430304,0.973068,0.0226291	1/1:0.0120546,0.0607004,0.927245	0/1:0.0210422,0.938552,0.0404059	1/1:0.0701457,0.0018616,0.927993	1/1:0.0493324,0.029221,0.921447	0/1:0.0499123,0.935744,0.0143435	1/1:0.000656138,0.00218204,0.997162	./.:0.103258,0.0205539,0.876188	1/1:0.0224765,0.0591745,0.918349	1/1:0.0215,0.0314641,0.947036	0/1:0.037995,0.944259,0.0177462	1/1:0.0213321,0.0274815,0.951186	1/1:0.0672465,0.00733959,0.925414	1/1:0.018967,0.0332647,0.947768	./.:0.0797284,0.898009,0.0222629	0/1:0.0263371,0.969116,0.00454719	1/1:0.0217441,0.0204776,0.957778	1/1:0.00489815,0.022385,0.972717	1/1:0.0415198,0.0458381,0.912642	./.:0.0511177,0.0537575,0.895125	0/1:0.0105745,0.963699,0.0257267	0/0:0.937316,0.00723278,0.0554513	./.:0.143206,0.010132,0.846662	0/1:0.0315404,0.951812,0.0166476	1/1:0.0389868,0.0166018,0.944411	./.:0.100633,0.183047,0.71632	1/1:0.0823377,0.0128481,0.904814	1/1:0.0034638,0.0493477,0.947189	1/1:0.0233768,0.00468452,0.971939	1/1:0.0436103,0.0396124,0.916777	0/1:0.0205386,0.917876,0.0615854	0/1:0.00321965,0.961868,0.0349126	1/1:0.049958,0.00314336,0.946899	1/1:0.0468147,0.00898756,0.944198	0/1:0.0338598,0.936065,0.0300755	1/1:0.00564584,0.0172885,0.977066	1/1:0.00613413,0.0484932,0.945373	1/1:0.00631724,0.0602274,0.933455	./.:0.0691081,0.0618296,0.869062	1/1:0.0126345,0.00588998,0.981476	1/1:0.00151064,0.00062562,0.997864	1/1:0.0466163,0.0382849,0.915099	1/1:0.0277867,0.00753796,0.964675	1/1:0.00276188,0.00874342,0.988495	./.:0.047837,0.111208,0.840955	1/1:0.0529335,0.0445869,0.90248	1/1:0.0281987,0.0180056,0.953796	1/1:0.0139315,0.0069276,0.979141	1/1:0.045243,0.0136263,0.941131	./.:0.102541,0.0259403,0.871519	0/1:0.0446632,0.931563,0.0237736	0/1:0.0442054,0.948333,0.00746166	1/1:0.00399786,0.0289464,0.967056	1/1:0.00605783,0.0175631,0.976379	1/1:0.0477607,0.0133974,0.938842	0/0:0.947982,0.0354162,0.0166018	1/1:0.00653086,0.00578317,0.987686	./.:0.867033,0.0902571,0.04271	1/1:0.0643931,0.0188754,0.916732	1/1:0.000839246,0.00590524,0.993256	1/1:0.0630961,0.0310063,0.905898	0/1:0.0458686,0.949035,0.00509651	0/1:0.0172885,0.959731,0.0229801	1/1:0.007187,0.0334173,0.959396	0/1:0.0166476,0.982376,0.000976577	./.:0.00849928,0.853574,0.137926	0/1:0.0108186,0.983627,0.00555428	1/1:0.00480659,0.0209354,0.974258	1/1:0.0122225,0.043122,0.944656	1/1:0.0320439,0.00106813,0.966888	1/1:0.00889601,0.012665,0.978439	1/1:0.0367285,0.00135805,0.961913	1/1:0.045716,0.0368658,0.917418	1/1:0.0287327,0.0232853,0.947982	./.:0.00381476,0.222095,0.77409	1/1:0.0617533,0.00885023,0.929397	0/0:0.99144,0.00332647,0.00523384	0/1:0.00242618,0.966262,0.0313115	1/1:0.0213474,0.0164492,0.962203	1/1:0.00280766,0.0105745,0.986618	1/1:0.0326238,0.0386664,0.92871	0/1:0.0466621,0.946868,0.00646983	0/1:0.00527962,0.979141,0.0155795	1/1:0.00265507,0.0386511,0.958694	1/1:0.0276951,0.00758373,0.964721	0/1:0.051545,0.938308,0.0101472	1/1:7.62951e-05,0.00503548,0.994888	1/1:0.0495918,0.00187686,0.948531	./.:0.00360113,0.106142,0.890257	1/1:0.00341802,0.0184482,0.978134	0/1:0.0377661,0.93312,0.0291142	1/1:0.0528573,0.0199893,0.927153	1/1:0.00210575,0.0745403,0.923354	1/1:0.0371862,0.00549325,0.957321	1/1:0.0317845,0.017792,0.950423	1/1:0.00926223,0.0117189,0.979019	1/1:0.0141451,0.0375525,0.948302	1/1:0.00123598,0.00427253,0.994491	./.:0.00274662,0.0974746,0.899779	0/1:0.000167849,0.947448,0.0523842	0/1:0.0551766,0.931685,0.013138	./.:0.10193,0.0168307,0.881239	./.:0.0343175,0.0812696,0.884413	0/1:0.0200961,0.97908,0.000823987	0/1:0.000640879,0.994598,0.00476081	1/1:0.0644846,0.0289311,0.906584	1/1:0.00448615,0.00437934,0.991135	1/1:0.0564889,0.0069276,0.936584	1/1:0.0193484,0.068574,0.912078	0/1:0.0364843,0.929137,0.0343786	1/1:0.00259403,0.0374456,0.95996	./.:0.00910964,0.110048,0.880842	1/1:0.0120394,0.00703441,0.980926	1/1:0.0766003,0.00494392,0.918456	1/1:0.000717174,0.000671397,0.998611	1/1:0.010605,0.0460365,0.943359	1/1:0.0107576,0.00694285,0.9823	1/1:0.00318914,0.0566873,0.940124	./.:0.0809033,0.0269017,0.892195	0/1:0.0256199,0.946914,0.0274662	0/1:0.0148165,0.966217,0.018967	1/1:0.0231937,0.0166018,0.960204	1/1:0.00210575,0.0184329,0.979461	1/1:0.00062562,0.0234226,0.975952	0/1:0.0104982,0.97879,0.0107118	1/1:0.00106813,0.0200351,0.978897	1/1:0.0307774,0.0104067,0.958816	1/1:0.003067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-01	3	RSID_3,SNPID_3	A	G	.	.	.	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-01	4	RSID_4,SNPID_4	A	G	.	.	.	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-01	5	RSID_5,SNPID_5	A	G	.	.	.	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-01	6	RSID_6,SNPID_6	A	G	.	.	.	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-01	7	RSID_7,SNPID_7	A	G	.	.	.	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-01	8	RSID_8,SNPID_8	A	G	.	.	.	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-01	9	RSID_9,SNPID_9	A	G	.	.	.	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-01	10	RSID_10,SNPID_10	A	G	.	.	.	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+01	2	RSID_2;DELETION_1	A	-	.	.	.	GT:GP	1/1:0.076524,0.00738537,0.916091	1/1:0.0278172,0.00863661,0.963546	1/1:0.01738,0.0496834,0.932937	0/1:0.0248722,0.932815,0.0423133	1/1:0.0346227,0.0191806,0.946197	1/1:0.0624094,0.0162661,0.921324	./.:0.0890517,0.895216,0.0157321	1/1:0.020325,0.013489,0.966186	1/1:0.0395972,0.0294041,0.930999	1/1:0.044358,0.0343481,0.921294	1/1:0.0413977,0.0547494,0.903853	./.:0.0833448,0.0513313,0.865324	1/1:0.0204471,0.0430152,0.936538	0/1:0.00341802,0.985199,0.0113832	0/1:0.00726329,0.991424,0.00131228	1/1:0.00213626,0.0130617,0.984802	1/1:0.0433356,0.0240482,0.932616	0/1:0.0309758,0.965118,0.00390631	1/1:0.0354009,0.00350958,0.961089	1/1:0.0308385,0.045243,0.923919	1/1:0.0550546,0.00799573,0.93695	./.:0.128161,0.0136263,0.858213	1/1:0.0117494,0.0384527,0.949798	1/1:0.0335241,0.0115053,0.954971	1/1:0.00808728,0.0131533,0.978759	1/1:0.00624094,0.0180819,0.975677	1/1:0.0146334,0.0125124,0.972854	1/1:0.0254826,0.00527962,0.969238	1/1:0.00210575,0.0579538,0.93994	1/1:0.0140383,0.00260929,0.983352	1/1:0.0355077,0.0597238,0.904768	1/1:0.0257115,0.00280766,0.971481	0/1:0.0142977,0.948074,0.0376287	1/1:0.0397803,0.020325,0.939895	1/1:0.00469978,0.0087129,0.986587	1/1:0.00622568,0.0043946,0.98938	1/1:0.0452277,0.00787366,0.946899	0/1:0.0751049,0.922164,0.00273136	1/1:0.0304875,0.00329595,0.966217	1/1:0.0222171,0.0297246,0.948058	0/0:0.971069,0.00122072,0.0277104	0/1:0.00669871,0.992905,0.000396735	1/1:0.00366217,0.00230411,0.994034	1/1:0.0358434,0.0184634,0.945693	0/1:0.000122072,0.98262,0.017258	0/1:0.0269322,0.967941,0.00512703	1/1:0.0363317,0.00915541,0.954513	0/1:0.0218204,0.951232,0.0269474	1/1:0.0102693,0.00563058,0.9841	1/1:0.00459297,0.0495766,0.94583	1/1:0.0053254,0.0157015,0.978973	1/1:0.00531014,0.0009308,0.993759	1/1:0.0264897,0.0254826,0.948028	1/1:0.0522011,0.00111391,0.946685	1/1:0.016434,0.00560006,0.977966	1/1:0.0626535,0.00508125,0.932265	0/1:0.00161746,0.97937,0.0190127	0/0:0.966125,0.00132753,0.0325475	1/1:0.0155642,0.00569162,0.978744	1/1:0.0202029,0.000289921,0.979507	1/1:0.0281987,0.00773632,0.964065	./.:0.0508278,0.0542611,0.894911	0/1:0.0310216,0.94197,0.0270085	1/1:0.0455024,0.0162051,0.938293	0/1:0.0184482,0.936538,0.0450141	0/1:0.0361486,0.922301,0.0415503	1/1:0.0427253,0.036408,0.920867	1/1:0.00544747,0.0174258,0.977127	1/1:0.00248722,0.0113222,0.986191	0/1:0.0112154,0.980346,0.00843824	0/1:0.00143435,0.989425,0.00914015	1/1:3.0518e-05,0.0425116,0.957458	1/1:0.0187076,0.0104829,0.970809	1/1:0.0062562,0.0351263,0.958618	0/1:0.0257267,0.950683,0.0235904	1/1:0.0129549,0.0670329,0.920012	1/1:0.0165103,0.041413,0.942077	1/1:0.000610361,0.0290379,0.970352	0/1:0.0255589,0.970474,0.00396735	0/1:0.0144808,0.967361,0.0181582	1/1:0.00460822,0.0602426,0.935149	1/1:0.0382238,0.00627146,0.955505	1/1:0.0596628,0.0231479,0.917189	1/1:0.0179446,0.0391699,0.942885	0/1:0.013489,0.943526,0.0429847	1/1:0.0774548,0.0114137,0.911131	1/1:0.0176547,0.00340276,0.978943	1/1:0.0100252,0.0271458,0.962829	1/1:0.0130007,0.0141756,0.972824	0/1:0.00733959,0.94374,0.0489204	./.:0.0627604,0.0610361,0.876204	1/1:0.0270085,0.0134585,0.959533	1/1:0.00411994,0.0168002,0.97908	./.:0.0515145,0.887633,0.060853	0/1:0.0135348,0.978958,0.00750744	1/1:0.0307012,0.000961318,0.968338	1/1:0.0153658,0.0120851,0.972549	1/1:0.000442512,0.0492256,0.950332	./.:0.110597,0.00343328,0.885969	1/1:0.0164492,0.0277562,0.955795	1/1:0.00375372,0.0400702,0.956176	1/1:0.00277714,0.032578,0.964645	0/1:0.0317693,0.954009,0.0142214	./.:0.0332189,0.0885023,0.878279	./.:0.0780041,0.0638132,0.858183	1/1:0.00665293,0.0874952,0.905852	0/1:0.00581369,0.970626,0.0235599	1/1:0.0102541,0.00408942,0.985657	./.:0.00251774,0.118532,0.87895	0/1:0.00482185,0.990936,0.00424201	1/1:0.0142824,0.0148165,0.970901	0/1:0.00741588,0.979232,0.0133516	0/1:0.0258946,0.956802,0.0173037	./.:0.10454,0.880644,0.0148165	1/1:0.0694285,0.0148775,0.915694	0/1:0.00758373,0.991363,0.00105287	0/1:0.0429236,0.948562,0.00851453	1/1:0.00231937,0.0135195,0.984161	1/1:0.00384527,0.00367742,0.992477	0/1:0.0191196,0.970565,0.0103151	1/1:0.00953689,0.0267948,0.963668	0/1:0.00181582,0.978607,0.0195773	1/1:0.00221256,0.000488289,0.997299	1/1:0.000167849,0.00836194,0.99147	0/1:0.0132906,0.977981,0.00872816	1/1:0.0318761,0.0043946,0.963729	1/1:0.00839246,0.000823987,0.990784	./.:0.1093,0.00549325,0.885206	1/1:0.0087129,0.0323491,0.958938	0/1:0.00701915,0.915908,0.0770733	1/1:0.0211948,0.0483864,0.930419	0/1:0.033875,0.922499,0.0436255	0/1:0.0307927,0.966873,0.00233463	1/1:0.016022,0.0126802,0.971298	1/1:0.00807202,0.00962844,0.9823	1/1:0.0194858,0.0150759,0.965438	1/1:0.0353704,0.0389563,0.925673	1/1:0.00267033,0.0382544,0.959075	0/1:0.00387579,0.985794,0.0103304	./.:0.0982681,0.0382849,0.863447	0/1:0.00225834,0.919478,0.0782635	1/1:3.0518e-05,0.0167697,0.9832	./.:0.0582589,0.0492256,0.892515	0/1:0.0084535,0.953399,0.0381476	1/1:0.0272221,0.0196231,0.953155	1/1:0.056733,0.0166018,0.926665	./.:0.126864,0.872343,0.000793469	0/1:0.0204166,0.941283,0.0383001	1/1:0.0232395,0.00367742,0.973083	0/1:0.00880446,0.92192,0.069276	1/1:0.0216831,0.0273442,0.950973	1/1:0.0426032,0.0204623,0.936934	0/1:0.0104067,0.970108,0.0194858	1/1:0.0585031,0.0250248,0.916472	1/1:0.0142519,0.0481727,0.937575	1/1:0.0352331,0.00822461,0.956542	1/1:0.00704967,0.00383001,0.98912	0/1:0.0618906,0.923705,0.0144045	1/1:0.00947585,0.0287327,0.961791	0/1:0.0358282,0.959213,0.00495918	1/1:0.0419013,0.00610361,0.951995	1/1:0.0511177,0.000732433,0.94815	1/1:0.0235142,0.0614328,0.915053	1/1:0.042359,0.0506294,0.907012	1/1:0.010132,0.0889601,0.900908	1/1:0.00196841,0.0733043,0.924727	./.:0.0783703,0.0315557,0.890074	1/1:0.0634928,0.0173037,0.919203	1/1:0.0394598,0.00485237,0.955688	1/1:0.0249332,0.0216526,0.953414	0/1:0.0118257,0.95642,0.031754	1/1:0.0132753,0.0262303,0.960494	1/1:0.0203098,0.0178378,0.961852	1/1:0.0280156,0.0369574,0.935027	1/1:0.0509651,0.011078,0.937957	1/1:0.0256504,0.00415045,0.970199	1/1:0.0140841,0.0478981,0.938018	1/1:0.00701915,0.0359503,0.957031	1/1:0.0230716,0.0121004,0.964828	0/1:0.0615702,0.929992,0.00843824	0/1:0.0289769,0.968536,0.00248722	1/1:0.0202945,0.0614176,0.918288	1/1:0.0282139,0.0483406,0.923445	1/1:0.0619211,0.0218509,0.916228	1/1:0.00706493,0.0120241,0.980911	0/1:0.00639353,0.961227,0.0323796	0/0:0.991852,0.00381476,0.00433356	./.:0.0470283,0.0825666,0.870405	0/1:0.0519875,0.944213,0.0037995	0/1:0.0620127,0.914351,0.0236362	./.:0.186938,0.0114137,0.801648	1/1:0.000350958,0.0235599,0.976089	1/1:0.032639,0.00234989,0.965011	1/1:0.0053254,0.0183566,0.976318	0/1:0.00903334,0.965255,0.0257115	1/1:0.00619516,0.0135042,0.980301	0/1:0.00584421,0.956863,0.037293	1/1:0.00593576,0.0612955,0.932769	1/1:0.0269474,0.0389105,0.934142	1/1:0.0356909,0.0327001,0.931609	1/1:0.0561837,0.00373846,0.940078	1/1:0.051194,0.0157321,0.933074	1/1:0.0783246,0.019791,0.901884	1/1:0.00077821,0.0401007,0.959121	1/1:0.0106661,0.0217288,0.967605	0/1:0.0448463,0.914977,0.040177	0/1:0.00030518,0.985061,0.0146334	0/1:0.0392157,0.956313,0.00447089	1/1:0.028397,0.0646983,0.906905	./.:0.0397192,0.895521,0.0647593	0/0:0.981552,0.00239567,0.0160525	1/1:0.00361639,0.00497444,0.991409	1/1:0.0280766,0.0110323,0.960891	1/1:0.025391,0.0222782,0.952331	1/1:0.0397803,0.0458076,0.914412	0/1:0.024979,0.916808,0.0582132	1/1:0.0502937,0.0427253,0.906981	0/1:0.0461128,0.935714,0.0181735	1/1:0.0395514,0.0561379,0.904311	1/1:0.0103304,0.0181888,0.971481	1/1:0.00764477,0.0403143,0.952041	1/1:0.0191958,0.0253758,0.955428	1/1:0.00872816,0.0280919,0.96318	1/1:0.0220798,0.0640574,0.913863	1/1:0.0502632,0.0229953,0.926741	1/1:0.0083772,7.62951e-05,0.991547	./.:0.0012665,0.850767,0.147967	0/1:0.0260777,0.919432,0.05449	0/1:0.00773632,0.99173,0.000534066	1/1:0.0242466,0.0116274,0.964126	1/1:0.0448768,0.00833143,0.946792	1/1:0.0195926,0.00775158,0.972656	./.:0.0945602,0.0196078,0.885832	1/1:0.0219272,0.0154421,0.962631	0/1:0.0128939,0.980926,0.0061799	1/1:0.0133211,0.0111238,0.975555	1/1:0.0209964,0.0618448,0.917159	1/1:0.03093,0.00195315,0.967117	0/1:0.0209659,0.974426,0.00460822	1/1:0.021561,0.0119326,0.966506	1/1:0.0294194,0.0594034,0.911177	1/1:0.043122,0.0414588,0.915419	1/1:0,0.0104067,0.989593	1/1:0.0264897,0.00514229,0.968368	1/1:0.00962844,0.00128176,0.98909	1/1:0.00262455,0.0280613,0.969314	0/1:0.00436408,0.967391,0.0282444	0/1:0.0166476,0.972717,0.0106355	0/1:0.00738537,0.981338,0.0112764	0/1:0.0208133,0.950088,0.029099	1/1:0.0173495,0.00668345,0.975967	1/1:0.0267948,0.0256962,0.947509	1/1:0.0233463,0.00436408,0.97229	1/1:0.0208286,0.0184176,0.960754	0/1:0.0274662,0.93431,0.0382238	0/1:0.0214847,0.960815,0.0177005	0/1:0.0476539,0.939071,0.0132753	0/1:0.0234226,0.967468,0.00910964	0/1:0.0141909,0.951598,0.0342107	0/1:0.00419623,0.970977,0.0248264	0/1:9.15541e-05,0.920333,0.0795758	1/1:0.0109865,0.0149691,0.974044	1/1:0.0613413,0.0350805,0.903578	1/1:0.051667,0.0332952,0.915038	0/1:0.0415656,0.957153,0.00128176	0/1:0.00401312,0.985336,0.0106508	./.:0.0183719,0.14258,0.839048	1/1:0.00407416,0.0247807,0.971145	1/1:0.00978103,0.0359655,0.954253	0/1:0.0472572,0.91751,0.0352331	0/1:0.00512703,0.989593,0.00527962	0/1:0.0388342,0.95201,0.00915541	0/1:0.0491035,0.923003,0.0278935	0/1:0.0242313,0.967636,0.00813306	0/1:0.0787366,0.920516,0.000747692	1/1:0.00521859,0.0133364,0.981445	0/1:0.00489815,0.978836,0.0162661	1/1:0.00541695,0.00123598,0.993347	0/1:0.0143587,0.984543,0.00109865	1/1:0.002533,0.0177157,0.979751	1/1:0.073106,0.00468452,0.92221	1/1:0.0172732,0.00381476,0.978912	1/1:0.00321965,0.0263523,0.970428	0/0:0.986954,0.0101015,0.00294499	0/1:0.0012665,0.989532,0.00920119	0/1:0.00369268,0.976303,0.0200046	0/1:0.0418708,0.927214,0.0309148	1/1:9.15541e-05,0.0417945,0.958114	0/1:0.0061799,0.957336,0.0364843	1/1:0.0216678,0.0125124,0.96582	0/1:0.0384375,0.956619,0.00494392	./.:0.0916915,0.0296635,0.878645	0/1:0.00775158,0.977035,0.0152132	0/1:0.0345006,0.965469,3.0518e-05	0/1:0.00244144,0.988922,0.00863661	1/1:0.0396735,0.043595,0.916732	0/1:0.0195621,0.960113,0.020325	0/1:0.0713817,0.927718,0.000900282	0/1:0.0631113,0.929046,0.00784314	./.:0.0410315,0.0697642,0.889204	1/1:0.00047303,0.0628214,0.936706	./.:0.103883,0.880873,0.0152438	0/1:0.0398718,0.951812,0.00831617	1/1:0.0253605,0.00296025,0.971679	./.:0.118563,0.848753,0.0326848	1/1:0.00436408,0.0230259,0.97261	1/1:0.0081178,0.0224002,0.969482	1/1:0.018555,0.0335241,0.947921	./.:0.0906538,0.0255131,0.883833	0/1:0.0403906,0.942992,0.0166171	1/1:0.00755322,0.0653544,0.927092	1/1:0.0112459,0.005066,0.983688	1/1:0.0144808,0.0299535,0.955566	./.:0.0694591,0.0308232,0.899718	1/1:0.0339361,0.00434882,0.961715	1/1:0.0282444,0.034226,0.93753	1/1:0.0794995,0.0130159,0.907485	1/1:0.0326543,0.0330816,0.934264	1/1:0.0243076,0.00973526,0.965957	0/1:0.00123598,0.987778,0.0109865	0/1:0.00547799,0.966598,0.027924	1/1:0.0314794,0.00315862,0.965362	1/1:0.0237888,0.0281529,0.948058	0/1:0.00430304,0.973068,0.0226291	1/1:0.0120546,0.0607004,0.927245	0/1:0.0210422,0.938552,0.0404059	1/1:0.0701457,0.0018616,0.927993	1/1:0.0493324,0.029221,0.921447	0/1:0.0499123,0.935744,0.0143435	1/1:0.000656138,0.00218204,0.997162	./.:0.103258,0.0205539,0.876188	1/1:0.0224765,0.0591745,0.918349	1/1:0.0215,0.0314641,0.947036	0/1:0.037995,0.944259,0.0177462	1/1:0.0213321,0.0274815,0.951186	1/1:0.0672465,0.00733959,0.925414	1/1:0.018967,0.0332647,0.947768	./.:0.0797284,0.898009,0.0222629	0/1:0.0263371,0.969116,0.00454719	1/1:0.0217441,0.0204776,0.957778	1/1:0.00489815,0.022385,0.972717	1/1:0.0415198,0.0458381,0.912642	./.:0.0511177,0.0537575,0.895125	0/1:0.0105745,0.963699,0.0257267	0/0:0.937316,0.00723278,0.0554513	./.:0.143206,0.010132,0.846662	0/1:0.0315404,0.951812,0.0166476	1/1:0.0389868,0.0166018,0.944411	./.:0.100633,0.183047,0.71632	1/1:0.0823377,0.0128481,0.904814	1/1:0.0034638,0.0493477,0.947189	1/1:0.0233768,0.00468452,0.971939	1/1:0.0436103,0.0396124,0.916777	0/1:0.0205386,0.917876,0.0615854	0/1:0.00321965,0.961868,0.0349126	1/1:0.049958,0.00314336,0.946899	1/1:0.0468147,0.00898756,0.944198	0/1:0.0338598,0.936065,0.0300755	1/1:0.00564584,0.0172885,0.977066	1/1:0.00613413,0.0484932,0.945373	1/1:0.00631724,0.0602274,0.933455	./.:0.0691081,0.0618296,0.869062	1/1:0.0126345,0.00588998,0.981476	1/1:0.00151064,0.00062562,0.997864	1/1:0.0466163,0.0382849,0.915099	1/1:0.0277867,0.00753796,0.964675	1/1:0.00276188,0.00874342,0.988495	./.:0.047837,0.111208,0.840955	1/1:0.0529335,0.0445869,0.90248	1/1:0.0281987,0.0180056,0.953796	1/1:0.0139315,0.0069276,0.979141	1/1:0.045243,0.0136263,0.941131	./.:0.102541,0.0259403,0.871519	0/1:0.0446632,0.931563,0.0237736	0/1:0.0442054,0.948333,0.00746166	1/1:0.00399786,0.0289464,0.967056	1/1:0.00605783,0.0175631,0.976379	1/1:0.0477607,0.0133974,0.938842	0/0:0.947982,0.0354162,0.0166018	1/1:0.00653086,0.00578317,0.987686	./.:0.867033,0.0902571,0.04271	1/1:0.0643931,0.0188754,0.916732	1/1:0.000839246,0.00590524,0.993256	1/1:0.0630961,0.0310063,0.905898	0/1:0.0458686,0.949035,0.00509651	0/1:0.0172885,0.959731,0.0229801	1/1:0.007187,0.0334173,0.959396	0/1:0.0166476,0.982376,0.000976577	./.:0.00849928,0.853574,0.137926	0/1:0.0108186,0.983627,0.00555428	1/1:0.00480659,0.0209354,0.974258	1/1:0.0122225,0.043122,0.944656	1/1:0.0320439,0.00106813,0.966888	1/1:0.00889601,0.012665,0.978439	1/1:0.0367285,0.00135805,0.961913	1/1:0.045716,0.0368658,0.917418	1/1:0.0287327,0.0232853,0.947982	./.:0.00381476,0.222095,0.77409	1/1:0.0617533,0.00885023,0.929397	0/0:0.99144,0.00332647,0.00523384	0/1:0.00242618,0.966262,0.0313115	1/1:0.0213474,0.0164492,0.962203	1/1:0.00280766,0.0105745,0.986618	1/1:0.0326238,0.0386664,0.92871	0/1:0.0466621,0.946868,0.00646983	0/1:0.00527962,0.979141,0.0155795	1/1:0.00265507,0.0386511,0.958694	1/1:0.0276951,0.00758373,0.964721	0/1:0.051545,0.938308,0.0101472	1/1:7.62951e-05,0.00503548,0.994888	1/1:0.0495918,0.00187686,0.948531	./.:0.00360113,0.106142,0.890257	1/1:0.00341802,0.0184482,0.978134	0/1:0.0377661,0.93312,0.0291142	1/1:0.0528573,0.0199893,0.927153	1/1:0.00210575,0.0745403,0.923354	1/1:0.0371862,0.00549325,0.957321	1/1:0.0317845,0.017792,0.950423	1/1:0.00926223,0.0117189,0.979019	1/1:0.0141451,0.0375525,0.948302	1/1:0.00123598,0.00427253,0.994491	./.:0.00274662,0.0974746,0.899779	0/1:0.000167849,0.947448,0.0523842	0/1:0.0551766,0.931685,0.013138	./.:0.10193,0.0168307,0.881239	./.:0.0343175,0.0812696,0.884413	0/1:0.0200961,0.97908,0.000823987	0/1:0.000640879,0.994598,0.00476081	1/1:0.0644846,0.0289311,0.906584	1/1:0.00448615,0.00437934,0.991135	1/1:0.0564889,0.0069276,0.936584	1/1:0.0193484,0.068574,0.912078	0/1:0.0364843,0.929137,0.0343786	1/1:0.00259403,0.0374456,0.95996	./.:0.00910964,0.110048,0.880842	1/1:0.0120394,0.00703441,0.980926	1/1:0.0766003,0.00494392,0.918456	1/1:0.000717174,0.000671397,0.998611	1/1:0.010605,0.0460365,0.943359	1/1:0.0107576,0.00694285,0.9823	1/1:0.00318914,0.0566873,0.940124	./.:0.0809033,0.0269017,0.892195	0/1:0.0256199,0.946914,0.0274662	0/1:0.0148165,0.966217,0.018967	1/1:0.0231937,0.0166018,0.960204	1/1:0.00210575,0.0184329,0.979461	1/1:0.00062562,0.0234226,0.975952	0/1:0.0104982,0.97879,0.0107118	1/1:0.00106813,0.0200351,0.978897	1/1:0.0307774,0.0104067,0.958816	1/1:0.003067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+01	3	RSID_3;SNPID_3	A	G	.	.	.	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+01	4	RSID_4;SNPID_4	A	G	.	.	.	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+01	9	RSID_9;SNPID_9	A	G	.	.	.	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ADDED   release/test/data/test.wrongids.sample
Index: release/test/data/test.wrongids.sample
==================================================================
--- release/test/data/test.wrongids.sample
+++ release/test/data/test.wrongids.sample
@@ -0,0 +1,502 @@
+ID_1 ID_2 missing cov1 cov2 cov3 cov4 pheno1 pheno2 bin1 bin2 sex multi1
+0 0 0 D D C C P P B B D D
+wrong_1 1001 0 NA 2 -1.56166194334463 -1.45448476818552 1.16025452109683 -0.871368351143296 1 0 female case2
+wrong_2 1002 0 0 NA -0.755494485193216 -0.552893803026392 2.70197794763108 1.7386073380311 1 1 female case2
+wrong_3 1003 0 1 5 NA -0.404527517018072 3.73155558962106 0.484628764850888 1 0 female control
+wrong_4 1004 0 1 3 2.72464789596555 NA 3.61252254801485 0.355166555057944 1 0 male control
+wrong_5 1005 0 0 1 -1.57875777581648 -2.3131805646581 NA -1.19036456161967 1 0 female control
+wrong_6 1006 0 1 4 -0.641251718258823 -0.178919881216542 1.70280926902209 NA 1 0 female case1
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+wrong_489 1489 0 0 0 -0.131202295876167 0.928498913998554 1.32722980464452 2.52874627052765 1 1 female case1
+wrong_490 1490 0 1 3 -0.400453625783984 -0.94487105916921 4.25510373367103 -0.455636095121114 1 1 female case1
+wrong_491 1491 0 0 3 -0.0105232012796116 0.513986097596536 2.47335670594744 -2.34967943584297 1 1 male case2
+wrong_492 1492 0 0 2 -1.20258647306953 -2.07138350082307 3.54537672005577 1.14802397452732 1 1 male control
+wrong_493 1493 0 1 2 0.173353514542841 0.412312283559089 4.072021732953 0.359133744918879 1 1 male case1
+wrong_494 1494 0 0 2 0.185446645994745 -1.91345402399295 2.5087137675394 0.291059311897676 1 1 male case2
+wrong_495 1495 0 0 2 0.72631071831223 -1.67079373400935 2.36254173664953 -0.334965765158454 1 1 male control
+wrong_496 1496 0 1 4 0.135862594581834 -0.404761353596607 1.77398179658453 -1.3673062140468 1 1 male control
+wrong_497 1497 0 0 2 1.6288688431865 1.11380245312982 0.891141070588861 -1.91553225140461 1 1 male control
+wrong_498 1498 0 1 3 1.96442539772711 -1.27314952408896 2.89278595757242 -1.5782485654762 1 1 female control
+wrong_499 1499 0 1 3 -0.264129194818256 -0.195125360024932 0.734757977042679 -2.20606029549892 1 0 male control
+wrong_500 1500 0 0 2 -1.02990949104231 2.04609932908729 2.4724546865438 0.242146973221245 1 1 male case1

Index: release/test/info_test.R
==================================================================
--- release/test/info_test.R
+++ release/test/info_test.R
@@ -138,12 +138,12 @@
 		)
 	)
 }
 
 cat( "Comparing frequency...\n" )
-stopifnot( length( which( abs( stats$frequency - qctool.stats$alleleB_frequency ) > 1E-4 )) == 0 )
+stopifnot( length( which( abs( stats$frequency - qctool.stats$alleleB_frequency ) > 1E-5 )) == 0 )
 cat( "Comparing IMPUTE info...\n" )
-stopifnot( length( which( abs( stats$impute_info - qctool.stats$impute_info ) > 1E-4 )) == 0 )
+stopifnot( length( which( abs( (stats$impute_info / qctool.stats$impute_info) - 1 ) > 1E-5 )) == 0 )
 cat( "Comparing QCTOOL info...\n" )
-stopifnot( length( which( abs( stats$info - qctool.stats$info ) > 1E-4 )) == 0 )
+stopifnot( length( which( abs( (stats$info / qctool.stats$info)  - 1 ) > 1E-5 )) == 0 )
 
 cat( "Success.\n" )

Index: release/test/run_tests.sh
==================================================================
--- release/test/run_tests.sh
+++ release/test/run_tests.sh
@@ -1,2 +1,2 @@
 #!/bin/bash
-pybot -d "./output" tests.txt
+python3 -m robot -d "./output" tests.txt

Index: release/test/stats_test.R
==================================================================
--- release/test/stats_test.R
+++ release/test/stats_test.R
@@ -108,10 +108,11 @@
     check.names = F,
     stringsAsFactors = F
 )
 VAR[which(chromosomes != "autosomes"),1] = chromosomes[ which( chromosomes != "autosomes" ) ]
 
+colnames(G) = sprintf( "sample_%d", 1:ncol(G))
 write( '##fileformat=VCFv4.2\n##FORMAT=<ID=GT,Type=String,Number=1,Description="genotype">', file = vcf.filename )
 write.table( cbind( VAR, G ), file = vcf.filename, sep = '\t', col.names = T, row.names = F, quote = F, append = T )
 
 write( 'ID_1 sex\n0 D', file = sample.filename )
 write.table(

Index: release/test/tests.txt
==================================================================
--- release/test/tests.txt
+++ release/test/tests.txt
@@ -1,11 +1,10 @@
 
 *** Variables ***
 ${TMPDIR}	${CURDIR}/tmp
 ${HOME}	%{HOME}
-${QCTOOL}	../../build/release/qctool_v2.0.6
-${INTHINNERATOR}	../../build/release/inthinnerator_v2.0.6
+${QCTOOL}	../../build/release/apps/qctool_v2.2.0-rc1
 
 *** Settings ***
 Library	OperatingSystem
 Library	String
 Library	Process
@@ -23,10 +22,16 @@
 	RunsCommandWithResult	{ "g": ["data/test.gen" ], "s": [ "data/test.sample" ], "og": "<tmp>" }	ok
 	RunsCommandWithResult	{ "g": ["data/test.gen" ], "og": "<tmp>" }	ok
 	RunsCommandWithResult	{ "g": ["data/test.gen" ], "s": [ "data/test.sample" ], "sample-stats": "" }	fail
 	RunsCommandWithResult	{ "g": ["data/test.gen" ], "s": [ "data/test.sample" ], "sample-stats": "", "osample": "<tmp>" }	ok
 
+Rejects mismatching samples
+	RunsCommandWithResult	{ "g": ["data/test.vcf" ] }	ok
+	RunsCommandWithResult	{ "g": ["data/test.vcf" ], "s": [ "data/test.sample" ] }	ok
+	RunsCommandWithResult	{ "g": ["data/test.vcf" ], "s": [ "data/test.wrongids.sample" ] }	fail
+	RunsCommandWithResult	{ "g": ["data/test.vcf" ], "s": [ "data/test.wrongids.sample" ], "force": 1 }	ok
+
 Accepts output formats
 	RunsCommandWithResult	{ "g": ["data/test.gen" ], "og": "<tmp>", "ofiletype": "gen" }	ok
 	RunsCommandWithResult	{ "g": ["data/test.gen" ], "og": "<tmp>", "ofiletype": "vcf" }	ok
 	RunsCommandWithResult	{ "g": ["data/test.gen" ], "og": "<tmp>", "ofiletype": "bgen" }	ok
 	RunsCommandWithResult	{ "g": ["data/test.gen" ], "og": "<tmp>", "ofiletype": "bgen_v1.1" }	ok
@@ -53,27 +58,38 @@
 	RunsCommandWithResult	{ "g": ["data/test.v12.bgen"], "filetype": "bgen", "snp-stats": "", "osnp": "<tmp>" }	ok
 	RunsCommandWithResult	{ "g": ["data/test.bed"], "filetype": "binary_ped", "snp-stats": "", "osnp": "<tmp>" }	ok
 	RunsCommandWithResult	{ "g": ["data/test.shapeit"], "s": [ "data/complex.sample" ], "filetype": "shapeit_haplotypes", "snp-stats": "", "osnp": "<tmp>" }	ok
 
 Filters samples
+	# test -incl-samples, with or without a sample file
 	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples": "data/good_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples": "data/bad_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples-where": "multi1=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples-where": "multi1!=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.v1.1.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples": "data/good_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.vcf" ], "s": [ "data/test.sample" ], "vcf-genotype-field": "GT", "og": "<tmp>", "incl-samples": "data/good_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.thresholded.gen
 	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples": "data/good_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples": "data/bad_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples-where": "multi1=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples-where": "multi1!=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.v1.1.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples": "data/good_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "og": "<tmp>", "incl-samples": "data/good_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.vcf" ], "vcf-genotype-field": "GT", "og": "<tmp>", "incl-samples": "data/good_sample_ids.txt", "ofiletype": "vcf" }	data/test.sample-filtered.vcf
+
+	# test -excl-samples, with or without a sample file
+	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples": "data/bad_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
 	RunsCommandWithOutputGen	{ "g": [ "data/test.v1.1.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples": "data/bad_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.v1.1.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples-where": "multi1=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.v1.1.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples-where": "multi1!=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.vcf" ], "s": [ "data/test.sample" ], "vcf-genotype-field": "GT", "og": "<tmp>", "incl-samples": "data/good_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.thresholded.gen
 	RunsCommandWithOutputGen	{ "g": [ "data/test.vcf" ], "s": [ "data/test.sample" ], "vcf-genotype-field": "GT", "og": "<tmp>", "excl-samples": "data/bad_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.thresholded.gen
-	RunsCommandWithOutputGen	{ "g": [ "data/test.vcf" ], "s": [ "data/test.sample" ], "vcf-genotype-field": "GT", "og": "<tmp>", "excl-samples-where": "multi1=case2", "ofiletype": "gen" }	data/test.sample-filtered.thresholded.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples": "data/bad_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "og": "<tmp>", "excl-samples": "data/bad_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.vcf" ], "vcf-genotype-field": "GT", "og": "<tmp>", "excl-samples": "data/bad_sample_ids.txt", "ofiletype": "gen" }	data/test.sample-filtered.thresholded.gen
+
+	# test -incl-samples-where
+	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples-where": "multi1!=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.v1.1.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples-where": "multi1!=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "incl-samples-where": "multi1!=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
 	RunsCommandWithOutputGen	{ "g": [ "data/test.vcf" ], "s": [ "data/test.sample" ], "vcf-genotype-field": "GT", "og": "<tmp>", "incl-samples-where": "multi1!=case2", "ofiletype": "gen" }	data/test.sample-filtered.thresholded.gen
 
+	# test -excl-samples-where
+	RunsCommandWithOutputGen	{ "g": [ "data/test.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples-where": "multi1=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.v1.1.bgen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples-where": "multi1=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "s": [ "data/test.sample" ], "og": "<tmp>", "excl-samples-where": "multi1=case2", "ofiletype": "gen" }	data/test.sample-filtered.gen
+	RunsCommandWithOutputGen	{ "g": [ "data/test.vcf" ], "s": [ "data/test.sample" ], "vcf-genotype-field": "GT", "og": "<tmp>", "excl-samples-where": "multi1=case2", "ofiletype": "gen" }	data/test.sample-filtered.thresholded.gen
+
 Filters SNPs
 	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "og": "<tmp>", "incl-rsids": "data/good_snp_rsids.txt", "ofiletype": "gen" }	data/test.filtered.gen
 	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "og": "<tmp>", "incl-snpids": "data/good_snp_snpids.txt", "ofiletype": "gen" }	data/test.filtered.gen
 	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "og": "<tmp>", "incl-positions": "data/good_snp_positions.txt", "ofiletype": "gen" }	data/test.filtered.gen
 	RunsCommandWithOutputGen	{ "g": [ "data/test.gen" ], "og": "<tmp>", "assume-chromosome": "1", "incl-positions": "data/good_snp_genomic_positions.txt", "ofiletype": "gen" }	data/test.filtered.gen
@@ -95,22 +111,30 @@
 Reorders Samples
 	RunsCommandWithExactOutput	{ "g": [ "data/complex.vcf" ], "s": [ "data/complex.sample" ], "og": "<tmp>", "reorder": "data/order.txt", "ofiletype": "vcf" }	data/complex.reordered.vcf
 	RunsCommandWithExactOutput	{ "g": [ "data/complex.vcf" ], "s": [ "data/complex.sample" ], "og": "<tmp>", "reorder": "data/order.txt", "ofiletype": "bgen" }	data/complex.reordered.bgen
 	RunsCommandWithExactOutput	{ "g": [ "data/complex.vcf" ], "s": [ "data/complex.sample" ], "og": "<tmp>", "reorder": "backwards", "ofiletype": "vcf" }	data/complex.backward.vcf
 	RunsCommandWithExactOutput	{ "g": [ "data/complex.vcf" ], "s": [ "data/complex.sample" ], "og": "<tmp>", "reorder": "backwards", "ofiletype": "bgen" }	data/complex.backward.bgen
+	# Without a sample file
+	RunsCommandWithExactOutput	{ "g": [ "data/complex.vcf" ], "og": "<tmp>", "reorder": "data/order.txt", "ofiletype": "vcf" }	data/complex.reordered.vcf
+	RunsCommandWithExactOutput	{ "g": [ "data/complex.vcf" ], "og": "<tmp>", "reorder": "data/order.txt", "ofiletype": "bgen" }	data/complex.reordered.bgen
+	RunsCommandWithExactOutput	{ "g": [ "data/complex.vcf" ], "og": "<tmp>", "reorder": "backwards", "ofiletype": "vcf" }	data/complex.backward.vcf
+	RunsCommandWithExactOutput	{ "g": [ "data/complex.vcf" ], "og": "<tmp>", "reorder": "backwards", "ofiletype": "bgen" }	data/complex.backward.bgen
+	# Should fail if no sample IDs in input and a file is given
+	RunsCommandWIthResult	{ "g": [ "data/test.gen" ], "og": "<tmp>", "reorder": "data/order.txt", "ofiletype": "vcf" }	fail
 
 Computes LD
 	RunsCommandWithResult	{ "g": [ "data/test.bgen" ], "s": [ "data/test.sample" ], "compute-ld-with": [ "data/test.bgen", "data/test.sample" ], "old": "<tmp>" }	ok
 	RunsCommandWithResult	{ "g": [ "data/ld_haps.vcf" ], "s": [ "data/ld.sample" ], "compute-ld-with": [ "data/ld_haps.vcf", "data/ld.sample" ], "old": "<tmp>" }	ok
 	RunsCommandWithResult	{ "g": [ "data/ld_genotypes.vcf" ], "s": [ "data/ld.sample" ], "compute-ld-with": [ "data/ld_genotypes.vcf", "data/ld.sample" ], "old": "<tmp>" }	ok
 
 Produces well-formed snp stats output
 	@{commandSpecs}=	Create List	{ "snp-stats": "", "osnp": "<tmp>" }
 	Set data	{ "g": ["data/test.gen"], "s": ["data/test.sample"] }
-	:FOR	${commandSpec}	IN	@{commandSpecs}
-	\	${startChar}=	Get Substring	${commandSpec}	0	1
-	\	Run Keyword If	'${startChar}' != '\#'	ProducesWellFormedSnpStatsOutput	${commandSpec}
+	FOR	${commandSpec}	IN	@{commandSpecs}
+		${startChar}=	Get Substring	${commandSpec}	0	1
+		Run Keyword If	'${startChar}' != '\#'	ProducesWellFormedSnpStatsOutput	${commandSpec}
+	END
 
 Computes correct snp stats
 	CheckRun	Rscript	--vanilla	stats_test.R	--qctool	${QCTOOL}
 	CheckRun	Rscript	--vanilla	info_test.R	--qctool	${QCTOOL}
 
@@ -121,14 +145,14 @@
 	RunsCommandWithExactOutput	 { "g": ["data/merge1.gen"], "s": [ "data/merge1.sample" ], "merge-in": [ "data/merge2.gen", "data/merge1.sample" ], "og": "<tmp>", "ofiletype": "bgen" }	data/merge1_merged_merge2.bgen	
 
 Produces well-formed sample output
 	@{commandSpecs}=	Create List	{ "sample-stats": "", "osample": "<tmp>" }
 	Set data	{ "g": ["data/test.gen"], "s": ["data/test.sample"] }
-	:FOR	${commandSpec}	IN	@{commandSpecs}
-	\	${startChar}=	Get Substring	${commandSpec}	0	1
-	\	Run Keyword If	'${startChar}' != '\#'	ProducesWellFormedSampleStatsOutput	${commandSpec}
-
+	FOR	${commandSpec}	IN	@{commandSpecs}
+		${startChar}=	Get Substring	${commandSpec}	0	1
+		Run Keyword If	'${startChar}' != '\#'	ProducesWellFormedSampleStatsOutput	${commandSpec}
+	END
 Accepts Different VCF fields
 	ProducesWellFormedSnpStatsOutput	{ "g": ["data/test.v4.2.vcf"], "s": ["data/test.sample" ], "snp-stats":"", "vcf-genotype-field": "GT", "osnp": "<tmp>" }
 	ProducesWellFormedSnpStatsOutput	{ "g": ["data/test.v4.2.vcf"], "s": ["data/test.sample" ], "snp-stats":"", "vcf-genotype-field": "GP", "osnp": "<tmp>" }
 
 Accepts Windows line endings
@@ -151,22 +175,24 @@
 
 Roundtrips allele probs formats
 	CheckRun	Rscript	--vanilla	test_allele_probs_format.R	--iterations	10	--qctool	${QCTOOL}
 
 Roundtrips gen files via bgen (v1.2, even bit counts)
-	:FOR	${bits}	IN	2	4	6	8	10	12	14	16	18	20	22	24	26	28	30	32
-	\	CheckRun	Rscript	--vanilla	random_test_bgen.R	--bits	${bits}	--iterations	10	--max_samples	10	--variants	10	--bgen_version	v1.2	--qctool	${QCTOOL}
+	FOR	${bits}	IN	2	4	6	8	10	12	14	16	18	20	22	24	26	28	30	32
+		CheckRun	Rscript	--vanilla	random_test_bgen.R	--bits	${bits}	--iterations	10	--max_samples	10	--variants	10	--bgen_version	v1.2	--qctool	${QCTOOL}
+	END
 
 Roundtrips gen files via bgen (v1.2, odd bit counts)
-	:FOR	${bits}	IN	1	3	5	7	9	11	13	15	17	19	21	23	25	27	29	31
-	\	CheckRun	Rscript	--vanilla	random_test_bgen.R	--bits	${bits}	--iterations	10	--max_samples	10	--variants	10	--bgen_version	v1.2	--qctool	${QCTOOL}
+	FOR	${bits}	IN	1	3	5	7	9	11	13	15	17	19	21	23	25	27	29	31
+		CheckRun	Rscript	--vanilla	random_test_bgen.R	--bits	${bits}	--iterations	10	--max_samples	10	--variants	10	--bgen_version	v1.2	--qctool	${QCTOOL}
+	END
 
 *** Keywords ***
 
 CheckRun
 	[Arguments]	@{command}
-	${result} =	Run Process	@{command}
+	${result} =	Run Process	@{command}	stdout=DEVNULL	stderr=DEVNULL
 	ShouldBeEqualAsIntegers	${result.rc}	0
 
 RunsCommandWithResult
 	[Arguments]	${command}	${expected_result}
 	Run Qctool	${command}	${expected_result}
@@ -185,12 +211,13 @@
 
 RunsCommandWithColumns
 	[Arguments]	${command}	@{columns}
 	${filenames}=	Run Qctool	${command}	ok
 	${filename}=	Get Variable Value	${filenames['osnp']}
-	:FOR	${elt}	IN	@{columns}
-	\	Has Exact Column	${filename}	${elt}
+	FOR	${elt}	IN	@{columns}
+		Has Exact Column	${filename}	${elt}
+	END
 
 ProducesWellFormedSampleStatsOutput
 	[Arguments]	${command}
 	${filenames}=	Run Qctool	${command}	ok
 	${filename}=	Get Variable Value	${filenames['osample']}

Index: src/FileBackupCreator.cpp
==================================================================
--- src/FileBackupCreator.cpp
+++ src/FileBackupCreator.cpp
@@ -6,12 +6,13 @@
 
 #include <vector>
 #include <string>
 #include <cstdio>
 #include "FileBackupCreator.hpp"
-#include "string_utils/string_utils.hpp"
+#include "genfile/string_utils/string_utils.hpp"
 #include <boost/filesystem.hpp>
+
 namespace BFS = boost::filesystem ;
 
 void FileBackupCreator::backup_file_if_necessary( std::string const& filename ) {
 	std::string backup_filename = backup_file_if_necessary_impl( filename ) ;
 	if( backup_filename != "" ) {
@@ -43,11 +44,11 @@
 	filename_stack.push_back( filename ) ;
 
 	// Generate a list of numbered filenames whose numbers we'll increment.
 	// If we hit the limit set by m_max_number_of_backups, we delete the last of these.
 	while( BFS::exists( filename_stack.back() )) {
-		std::string next_backup = filename + ".~" + string_utils::to_string( filename_stack.size() ) ;
+		std::string next_backup = filename + ".~" + genfile::string_utils::to_string( filename_stack.size() ) ;
 		filename_stack.push_back( next_backup ) ;
 		if( filename_stack.size() > m_max_number_of_backups ) {
 			if( BFS::exists( next_backup )) {
 				BFS::remove( next_backup ) ;
 			}

Index: statfile/include/statfile/DelimitedStatSource.hpp
==================================================================
--- statfile/include/statfile/DelimitedStatSource.hpp
+++ statfile/include/statfile/DelimitedStatSource.hpp
@@ -64,10 +64,11 @@
 		template< typename T >
 		void do_read_value( T& value ) {
 			assert( m_have_more_data ) ;
 			std::istringstream istr( m_current_fields[ current_column() ]) ;
 			istr >> value ;
+			istr.peek() ;
 			istr.peek() ;
 			if( !istr.eof() ) {
 				throw genfile::MalformedInputError( get_source_spec(), number_of_rows_read(), current_column() ) ;
 			}
 		}

Index: statfile/include/statfile/SNPDataSourceAdapter.hpp
==================================================================
--- statfile/include/statfile/SNPDataSourceAdapter.hpp
+++ statfile/include/statfile/SNPDataSourceAdapter.hpp
@@ -18,10 +18,11 @@
 		SNPDataSourceAdapter( BuiltInTypeStatSource::UniquePtr source ) ;
 
 		operator bool() const { return *m_source ; }
 		Metadata get_metadata() const { return Metadata() ; }
 		unsigned int number_of_samples() const { return 0 ; }
+		bool has_sample_ids() const { return false ; }
 		OptionalSnpCount total_number_of_snps() const { return m_source->number_of_rows() ; }
 
 		std::string get_source_spec() const ;
 		std::string get_summary( std::string const& prefix = "", std::size_t column_width = 20 ) const ;
 

Index: statfile/wscript
==================================================================
--- statfile/wscript
+++ statfile/wscript
@@ -3,45 +3,22 @@
 #import UnitTest
 
 def configure( conf ):
 	pass
 
-def create_tests( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'statfile boost-unit_test_framework',
-		uselib = 'BOOST_IOSTREAMS ZLIB BOOST_UNIT_TEST_FRAMEWORK',
+def build( bld ):
+	bld.stlib(
+		target = 'statfile',
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		includes='./include ../genfile/include',
+		use = 'genfile BOOST BOOST_IOSTREAMS ZLIB',
+		export_includes = './include'
+	)
+	
+	bld.program(
+		target = 'test_statfile',
+		source = bld.path.ant_glob( 'test/*.cpp' ),
+		use = 'statfile boost_unit_test_framework BOOST_IOSTREAMS ZLIB BOOST_UNIT_TEST_FRAMEWORK',
 		includes='./include',
 		unit_test=1,
 		install_path=None
 	)
-
-def create_benchmark( bld, name ):
-	bld(
-		features = 'cxx cprogram',
-		target = name,
-		source = [  'benchmarks/' + name + '.cpp' ],
-		uselib_local = 'statfile',
-		includes='./include',
-		install_path=None
-	)
-
-
-def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld(
-		features = 'cxx cstaticlib',
-		target = 'statfile',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include ../genfile/include',
-		uselib_local = 'genfile',
-		uselib = 'BOOST BOOST_IOSTREAMS ZLIB',
-		export_incdirs = './include'
-	)
-
-	create_tests( bld, 'test_statfile' )

Index: string_utils/wscript
==================================================================
--- string_utils/wscript
+++ string_utils/wscript
@@ -34,11 +34,11 @@
 	# libs
 	#---------------------
 	bld.new_task_gen(
 		features = 'cxx cstaticlib',
 		target = 'string_utils',
-		source = bld.glob( 'src/*.cpp' ),
+		source = bld.path.ant_glob 'src/*.cpp' ),
 		includes='./include',
 		uselib = 'BOOST',
-		export_incdirs = './include'
+		export_includes = './include'
 	)
 	

ADDED   waf
Index: waf
==================================================================
--- waf
+++ waf
cannot compute difference between binary files

DELETED waf-1.5.18
Index: waf-1.5.18
==================================================================
--- waf-1.5.18
+++ waf-1.5.18
cannot compute difference between binary files

Index: worker/test/test_case.hpp
==================================================================
--- worker/test/test_case.hpp
+++ worker/test/test_case.hpp
@@ -13,14 +13,14 @@
 #include <iostream>
 #include "config/config.hpp"
 
 #if HAVE_BOOST_UNIT_TEST_FRAMEWORK
 	#include "boost/test/unit_test.hpp"
-	#define AUTO_TEST_CASE( param ) BOOST_AUTO_TEST_CASE(param)
+	#define TEST_CASE( param ) BOOST_AUTO_TEST_CASE(param)
 	#define TEST_ASSERT( param ) BOOST_ASSERT( param )
 #else
-	#define AUTO_TEST_CASE( param ) void param()
+	#define TEST_CASE( param ) void param()
 	#define TEST_ASSERT( param ) assert( param )
 #endif	
 
 
 #endif

Index: worker/test/test_workers.cpp
==================================================================
--- worker/test/test_workers.cpp
+++ worker/test/test_workers.cpp
@@ -120,11 +120,11 @@
 		}
 	}
 }
 
 
-AUTO_TEST_CASE( test_synchronous_worker ) {
+TEST_CASE( test_synchronous_worker ) {
 	std::cerr << "Testing synchronous worker...\n" ;
 	try {
 		worker::SynchronousWorker worker ;
 		test_worker( worker ) ;
 		test_worker2( worker ) ;
@@ -133,11 +133,11 @@
 		std::cerr << "!! Error: task " << e.get_task_address() << ": expected " << e.get_expected_value() << ", got: " << e.get_actual_value() << ".\n" ;
 		TEST_ASSERT(0) ;
 	}
 }
 
-AUTO_TEST_CASE( test_queued_multi_threaded_worker ) {
+TEST_CASE( test_queued_multi_threaded_worker ) {
 	std::cerr << "Testing queued multi-threaded worker..." ;
 	for( std::size_t number_of_threads = 1; number_of_threads < 100; ++number_of_threads ) {
 		std::cerr << number_of_threads << " " ;
 		try {
 			{

Index: worker/test/wscript
==================================================================
--- worker/test/wscript
+++ worker/test/wscript
@@ -20,18 +20,18 @@
 			'src/MultiThreadedWorker.cpp',
 			'src/QueuedMultiThreadedWorker.cpp'
 		],
 		includes='./include',
 		uselib = 'BOOST BOOST_THREAD',
-		export_incdirs = './include'	
+		export_includes = './include'	
 	)
 	
 	bld(
 		features = 'cxx cprogram',
 		target = 'test_worker',
-		source = bld.glob( 'test/*.cpp' ),
+		source = bld.path.ant_glob 'test/*.cpp' ),
 		includes='./include',
 		uselib_local = 'worker',
 		uselib = 'BOOST BOOST_UNIT_TEST_FRAMEWORK',
 		unit_test = 1,
 		install_path = None
 	)

Index: worker/wscript
==================================================================
--- worker/wscript
+++ worker/wscript
@@ -1,33 +1,20 @@
-import os.path
-import glob
-#import UnitTest
-
 def configure( conf ):
 	pass
 
 def build( bld ):
-	import Options
-	
-	#---------------------
-	# libs
-	#---------------------
-	bld(
-		features = 'cxx cstaticlib',
-		target = 'worker',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include',
-		uselib_local = 'boost',
-		uselib = 'BOOST BOOST_THREAD BOOST_DATE_TIME PTHREAD',
-		export_incdirs = './include'	
-	)	
-	
-	bld(
-		features = 'cxx cprogram',
-		target = 'test_worker',
-		source = bld.glob( 'test/*.cpp' ),
-		includes='./include',
-		uselib_local = 'worker boost boost-unit_test_framework',
-		uselib = 'BOOST BOOST_THREAD BOOST_DATE_TIME BOOST_UNIT_TEST_FRAMEWORK PTHREAD',
+	bld.stlib(
+		target = 'worker',
+		source = bld.path.ant_glob( 'src/*.cpp' ),
+		includes='./include',
+		use = 'boost pthread',
+		export_includes = './include'	
+	)	
+	
+	bld.program(
+		target = 'test_worker',
+		source = bld.path.ant_glob( 'test/*.cpp' ),
+		includes = './include',
+		use = 'worker boost boost_unit_test_framework rt',
 		unit_test = 1,
 		install_path = None
 	)

Index: wscript
==================================================================
--- wscript
+++ wscript
@@ -1,327 +1,284 @@
 import os.path
 import glob
-#import UnitTest
-import Options
 
 srcdir="."
 APPNAME = "qctool"
-VERSION = "2.0.7"
-
-subdirs = [
-	'genfile', 'statfile', 'string_utils', 'appcontext',
-	'fputils', 'worker', 'integration',
-	'3rd_party', 'components', 'db', 'qcdb', 'metro'
-]
-
-def set_options( opt ):
-	opt.tool_options( 'compiler_cxx' )
-	opt.tool_options( 'compiler_cc' )
-	#opt.tool_options( 'boost' )
-	opt.add_option( "--static", action='store_true', default=False, help='Create statically-linked executables if possible.')
-	opt.add_option( "--all_targets", action='store_true', default=False, help='Create all targets, not just qctool.')
-
+VERSION = "2.2.5"
+
+variants = {
+	"release": {
+		"command": "{command}",
+		"cxxflags": [ '-O3' ],
+		"linkflags": []
+	},
+	"debug": {
+		"command": "{command}_debug",
+		"cxxflags": [ '-g' ],
+		"linkflags": []
+	}
+} ;
+
+subdirs = [
+	'genfile', 'statfile', 'appcontext',
+	'worker', 
+	'3rd_party', 'components', 'qcdb', 'metro',
+	'bingwa',
+	'apps'
+]
+
+def options( opt ):
+	opt.load( 'compiler_cxx' )
+	opt.load( 'compiler_c' )
+	opt.add_option( "--all_targets", action='store_true', default=False, help='Create all targets, not just qctool.')
+	opt.add_option( "--vectorise", action='store_true', default=False, help='Use aggresive vectorisation options for maximum performance.')
+	opt.add_option( '--variant', action='store', default='release', help='set the variant name' )
+	
 #-----------------------------------
 # CONFIGURE
 #-----------------------------------
 
-def configure( conf ):
-	print( "Using prefix\t\t\t\t :", conf.env[ 'PREFIX' ] )
-
-	conf.check_tool( 'compiler_cxx')
-	conf.check_tool( 'compiler_cc')
-
-	cxxflags = conf.env[ 'CXXFLAGS' ] 
-	linkflags = conf.env[ 'LINKFLAGS' ]
-	if conf.check( cxxflags = '-std=c++11' ):
+def configure( cfg ):
+	configure_variant( cfg, 'release' )
+	configure_variant( cfg, 'debug' )
+
+def configure_variant( cfg, variant ):
+	cfg.setenv( variant )
+	cfg.env[ 'VERSION' ] = VERSION ;
+	
+	cfg.load( 'compiler_c' )
+	cfg.load( 'compiler_cxx' )
+
+	print( "Using prefix\t\t\t\t :", cfg.env[ 'PREFIX' ] )
+
+	cxxflags = cfg.env[ 'CXXFLAGS' ] 
+	linkflags = cfg.env[ 'LINKFLAGS' ]
+
+	# We now require C++11.
+	if cfg.check( cxxflags = '-std=c++11' ):
 		cxxflags.append( '-std=c++11' )
 		cxxflags.append( '-Wno-deprecated-declarations' )
 	else:
-		cxxflags.append( '-std=c++98' )
-
-	# Disabling vectorisation checks as not always safe.
-	# Use CXXFLAGS environment variable to turn these on
-	# for flag in [ '-msse2', '-mavx', '-mssse3']:
-	#	if conf.check( cxxflags = flag ):
-	#		cxxflags.append( flag )
-	
-	platform_specific_configure( conf )
-	check_for_3rd_party_components( conf )
-	misc_configure( conf )
-
+		raise( "QCTOOL now requires a C++11-enabled compiler." )
+
+	cxxflags.extend(
+		[
+			"-mavx", "-mssse3", "-msse2", "-msse4.1", "-msse4.2",
+			'-Wall',
+			'-pedantic',
+			'-Wno-long-long', # suppress warnings in Eigen and Boost.
+			# The following are to suppress many warnings in boost
+			'-Wno-unused-local-typedefs',
+			'-Wno-c++11-long-long',
+			'-Wno-keyword-macro',
+			'-Wno-unused-const-variable',
+			'-Wno-deprecated-register',
+			'-Wno-unused-function',
+			'-Wno-redeclared-class-member',
+			'-Wno-int-in-bool-context'
+		]
+	)
+
+	if cfg.options.vectorise:
+		# These are disabled by default as not always safe.
+		for flag in [ '-msse2', '-mavx', '-mssse3']:
+			if cfg.check( cxxflags = flag ):
+				cxxflags.append( flag )
+	
+	cxxflags.extend( variants[ variant ][ "cxxflags" ] )
+	linkflags.extend( variants[ variant ][ "linkflags" ] )
+	
+	configure_blas( cfg )
+	configure_time( cfg )
 	import platform
-	if Options.options.static and platform.system() != "Darwin":
-		conf.env.SHLIB_MARKER='-Wl,-Bstatic'
-	create_variant( conf, 'release' )
-	configure_variant( conf, 'default', cxxflags, linkflags )
-	configure_variant( conf, 'release', cxxflags, linkflags )
-
-def check_for_3rd_party_components( conf ):
-	check_for_zlib( conf )
-	conf.define( 'HAVE_SQLITE3', 1 )
-	conf.define( 'HAVE_EIGEN', 1 )
-	conf.define( 'HAVE_ZSTD', 1 )
-	if conf.check_cxx( lib = 'dl', uselib_store = 'DL' ):
-		conf.define( 'HAVE_DL', 1 )
-	if conf.check_cxx( lib = 'rt', uselib_store = 'RT' ):
-		conf.define( 'HAVE_RT', 1 )
-	if conf.check_cxx( lib = 'm', uselib_store = 'M' ):
-		conf.define( 'HAVE_M', 1 )
-
-	# Remove support for some things
-	conf.define( 'HAVE_BZIP2', 0 )
-	conf.define( 'HAVE_MGL', 0 )
-	conf.define( 'HAVE_CAIRO', 0 )
-
-	if Options.options.static and conf.check_cxx( staticlib = 'pthread', uselib_store = "PTHREAD" ):
-		conf.define( 'HAVE_PTHREAD', 1 )
-	elif conf.check_cxx( lib = 'pthread', uselib_store = "PTHREAD" ):
-		conf.define( 'HAVE_PTHREAD', 1 )
-	if conf.check_cc( lib = 'readline', uselib_store = 'READLINE' ):
-		conf.define( "HAVE_READLINE", 1 )
-	
+	if platform.system() == 'Darwin':
+		configure_darwin( cfg, cxxflags, linkflags )
+	else:
+		configure_linux( cfg, cxxflags, linkflags )
+
+	# Now check for libraries
+	if check_cxx( cfg, lib = 'm', uselib_store = 'M' ):
+		cfg.define( 'HAVE_M', 1 )
+	if check_cxx( cfg, lib='z', uselib_store='ZLIB' ):
+		cfg.define( 'HAVE_ZLIB', 1 )
+	# disable support for some things
+	cfg.define( 'HAVE_BZIP2', 0 )
+	cfg.define( 'HAVE_MGL', 0 )
+	cfg.define( 'HAVE_CAIRO', 0 )
+	# sqlite3, eigen, zstd are part of this repo
+	cfg.define( 'HAVE_SQLITE3', 1 )
+	cfg.define( 'HAVE_EIGEN', 1 )
+	cfg.define( 'HAVE_ZSTD', 1 )
 	# Boost libs are now contained in the repo
-	conf.define( "HAVE_BOOST_IOSTREAMS", 1 )
-	conf.define( "HAVE_BOOST_FILESYSTEM", 1 )
-	conf.define( "HAVE_BOOST_SYSTEM", 1 )
-	conf.define( "HAVE_BOOST_THREAD", 1 )
-	conf.define( "HAVE_BOOST_DATE_TIME", 1 )
-	conf.define( "HAVE_BOOST_UNIT_TEST_FRAMEWORK", 1 )
-	conf.define( "HAVE_BOOST_TIMER", 1 )
-	conf.define( "HAVE_BOOST_REGEX", 1 )
-	conf.define( "HAVE_BOOST_MATH", 1 )
-	conf.define( "HAVE_BOOST_FUNCTION", 1 )
-	conf.define( "HAVE_BOOST_SPIRIT", 1 )
-	conf.define( "BOOST_FILESYSTEM_VERSION", 3 )
-
-def check_for_zlib( conf ):
-	if conf.check_cxx( staticlib='z', uselib_store='ZLIB' ):
-		conf.define( 'HAVE_ZLIB', 1 )
-	elif conf.check_cxx( lib='z', uselib_store='ZLIB' ):
-		conf.define( 'HAVE_ZLIB', 1 )
-
-def platform_specific_configure( conf ):
+	cfg.define( "HAVE_BOOST_IOSTREAMS", 1 )
+	cfg.define( "HAVE_BOOST_FILESYSTEM", 1 )
+	cfg.define( "HAVE_BOOST_SYSTEM", 1 )
+	cfg.define( "HAVE_BOOST_THREAD", 1 )
+	cfg.define( "HAVE_BOOST_DATE_TIME", 1 )
+	cfg.define( "HAVE_BOOST_UNIT_TEST_FRAMEWORK", 1 )
+	cfg.define( "HAVE_BOOST_TIMER", 1 )
+	cfg.define( "HAVE_BOOST_REGEX", 1 )
+	cfg.define( "HAVE_BOOST_MATH", 1 )
+	cfg.define( "HAVE_BOOST_FUNCTION", 1 )
+	cfg.define( "HAVE_BOOST_SPIRIT", 1 )
+	cfg.define( "BOOST_FILESYSTEM_VERSION", 3 )
+	cfg.define( 'EIGEN_NO_DEBUG', 1 )
+
+	cxxflags.append( "-I." )
+	cfg.env[ 'CXXFLAGS' ] = cxxflags
+	cfg.env[ 'LINKFLAGS' ] = linkflags
+	cfg.write_config_header( '%s/config/config.hpp' % variant )
+
+def check_cxx( cfg, **kwargs ):
+	try:
+		cfg.check_cxx( **kwargs )
+		return True
+	except:
+		return False
+		
+
+def configure_blas( cfg ):
 	import platform
 	if platform.system() == 'Darwin':
-		if conf.check_cxx( header_name='mach/mach_time.h', uselib_store = 'MACH_TIME' ):
-			conf.define( 'HAVE_MACH_TIME', 1 )
-		if conf.check_cxx(
+		if check_cxx(
+			cfg,
 			lib = 'cblas',
 			fragment = '#include "cblas.h"\nint main() {}',
-			cxxflags = '-I/System/Library/Frameworks/vecLib.framework/Headers',
+			cxxflags = [ '-I/System/Library/Frameworks/vecLib.framework/Headers', '-I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Headers' ],
 			uselib_store = 'CBLAS'
 		):
-			conf.define( 'HAVE_CBLAS', 1 )
-		if conf.check_cxx(
+			cfg.define( 'HAVE_CBLAS', 1 )
+		if check_cxx(
+			cfg,
 			header_name = 'clapack.h',
 			lib = 'clapack',
-			cxxflags = '-I/System/Library/Frameworks/vecLib.framework/Headers',
+			cxxflags = [ '-I/System/Library/Frameworks/vecLib.framework/Headers', '-I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Headers' ],
 			uselib_store = 'CLAPACK'
 		):
-			conf.define( 'HAVE_CLAPACK', 1 )
-			conf.define( 'HAVE_LAPACK', 1 )
+			cfg.define( 'HAVE_CLAPACK', 1 )
+			cfg.define( 'HAVE_LAPACK', 1 )
 	else:
 		blasCode = """#include "cblas.h"
 int main() {
 	float v[10] ;
 	float result = cblas_snrm2( 1, v, 1 ) ;
 	return int(result) ;
 }
 """
-		if conf.check_cxx( lib = 'cblas', fragment = blasCode, uselib_store = 'CBLAS' ):
-			conf.define( 'HAVE_CBLAS', 1 ) ;
-		elif conf.check_cxx( lib = 'blas', fragment = blasCode, uselib_store = 'CBLAS' ):
-			conf.define( 'HAVE_CBLAS', 1 ) ;
-		elif conf.check_cxx( lib = 'openblas', fragment = blasCode, uselib_store = 'CBLAS' ):
-			conf.define( 'HAVE_CBLAS', 1 ) ;
-		if conf.check_cxx(
+		if check_cxx( cfg, lib = 'cblas', fragment = blasCode, uselib_store = 'CBLAS' ):
+			cfg.define( 'HAVE_CBLAS', 1 ) ;
+		elif check_cxx( cfg, lib = 'blas', fragment = blasCode, uselib_store = 'CBLAS' ):
+			cfg.define( 'HAVE_CBLAS', 1 ) ;
+		elif check_cxx( cfg, lib = 'openblas', fragment = blasCode, uselib_store = 'CBLAS' ):
+			cfg.define( 'HAVE_CBLAS', 1 ) ;
+		if check_cxx(
+			cfg,
 			lib = 'lapack',
 			uselib_store = 'LAPACK'
 		):
-			conf.define( 'HAVE_LAPACK', 1 )
-		if conf.check_cxx( header_name = 'sys/time.h', fragment = '#include "sys/time.h"\nint main(int argc, char** argv ) { struct timeval current_time ; gettimeofday( &current_time, 0 ) ; return 0 ; }' ):
-			conf.define( 'HAVE_GETTIMEOFDAY', 1 )
-			
-def misc_configure( conf ) :
-	conf.define( 'EIGEN_NO_DEBUG', 1 )
-
-def get_cxxflags( variant_name ):
-	cxxflags = [
-		'-Wall',
-		'-pedantic',
-		'-Wno-long-long', # don't warn about the long long thing, it comes up in Eigen and Boost.
-		#'-Wno-redeclared-class-member', # don't warn about class member redeclaration which comes up in Boost
-		'-Wno-unused-local-typedefs' # warns in boost
-	]
-	if variant_name == 'default':
-		cxxflags.extend( [ '-g' ] )
-	elif variant_name == 'release':
-		cxxflags.extend( [ '-O3' ])
-	return cxxflags
-
-def get_ldflags( variant_name ):
-	import platform
-	ldflags = []
-	if variant_name == 'default' and platform.system() == 'Darwin':
-		ldflags.extend( [ '-framework', 'CoreFoundation' ])
-	if Options.options.static and platform.system() != 'Darwin':
-		ldflags.extend( [ '-static', '-static-libgcc' ] )
-	return ldflags
-
-def create_variant( conf, variant_name ):
-	variant = conf.env.copy()
-	conf.set_env_name( variant_name, variant )
-	variant.set_variant( variant_name )
-
-def configure_variant( conf, variant_name, cxxflags = [], linkflags = [] ):
-	cxxflags.extend( get_cxxflags( variant_name ))
-	cxxflags.extend( [ '-I', variant_name ] )
-	linkflags.extend( get_ldflags( variant_name ))
-	
-	conf.setenv( variant_name )
-	conf.env[ 'CXXFLAGS' ] = cxxflags
-	conf.env[ 'LINKFLAGS' ] = linkflags
-	conf.write_config_header( 'config/config.hpp' )
-#	conf.write_config_header( 'config.hpp' )
-#	conf.write_config_header( 'genfile/config.hpp' )
+			cfg.define( 'HAVE_LAPACK', 1 )
+
+def configure_time( cfg ):
+	if check_cxx( cfg, header_name='mach/mach_time.h', uselib_store = 'MACH_TIME' ):
+		cfg.define( 'HAVE_MACH_TIME', 1 )
+	if check_cxx( cfg, header_name = 'sys/time.h', fragment = '#include "sys/time.h"\nint main(int argc, char** argv ) { struct timeval current_time ; gettimeofday( &current_time, 0 ) ; return 0 ; }' ):
+		cfg.define( 'HAVE_GETTIMEOFDAY', 1 )
+
+def configure_darwin( cfg, cxxflags, linkflags ):
+	linkflags.extend( [ '-framework', 'CoreFoundation' ])
+
+def configure_linux( cfg, cxxflags, linkflags ):
+    check_cxx( cfg, lib='rt', uselib_store='rt', msg = 'rt' )
+    check_cxx( cfg, lib='pthread', uselib_store='pthread', msg = 'pthread' )
+    check_cxx( cfg, lib='dl', uselib_store='dl', msg = 'dl' )
+
+# This piece of code comes from
+# https://gitlab.com/ita1024/waf/-/blob/master/demos/variants/wscript
+# It makes the --variant command-line option work.	
+def init(ctx):
+    from waflib.Options import options
+    from waflib.Build import BuildContext, CleanContext, InstallContext, UninstallContext
+    from waflib.Configure import ConfigurationContext
+    for y in (BuildContext, CleanContext, InstallContext, UninstallContext, ConfigurationContext):
+        name = y.__name__.replace('Context','').lower()
+        class tmp(y):
+            cmd = name
+            variant = options.variant
 
 #-----------------------------------
 # BUILD
 #-----------------------------------
 
-def build( bld ):
-	import Options
+def create_app( bld, name, use = '' ):
+	bld.program(
+		target =  '%s_v%s' % ( name, VERSION ),
+		source = 'apps/' + name + '.cpp',
+		includes = './ include',
+		use = use,
+		install_path = os.path.join( bld.env[ 'PREFIX' ], 'bin' )
+	)
 
+def build( bld ):
+	print( "Building %s variant..." % bld.variant )
+	bld.env[ 'VERSION' ] = VERSION
 	bld(
-                rule = """printf '#ifndef QCTOOL_REVISION_HPP\n#define QCTOOL_REVISION_HPP\nnamespace globals {\n\tchar const* qctool_version = \"%%s\" ;\n\tchar const* const qctool_revision = \"%%s\" ;\n}\n#endif\n' `echo """ + VERSION + "` `hg parents --template={node}` > ${TGT}""",
-		#rule = """printf '#ifndef QCTOOL_VERSION_HPP\n#define QCTOOL_VERSION_HPP\nnamespace globals {\n\tchar const* const qctool_revision = \"%%s\" ;\n}\n#endif\n' `hg parents --template={node}` > ${TGT}""",
+		name = 'package_revision',
+		target = "config/package_revision_autogenerated.hpp",
 		always = True,
-		target = "config/qctool_version_autogenerated.hpp",
-		name = "qctool_version_autogenerated",
-		uselib = "",
-		#on_results = True
-		on_results = False
+		on_result = True,
+		rule = compute_revision,
+		ext_out = [ "config/package_revision_autogenerated.hpp" ],
+		export_includes = "./"
+	)
+
+	bld.add_group() # ensure the config above is created first
+	bld.stlib(
+		target = "qctool-lib",
+		source = bld.path.ant_glob( "src/*.cpp" ),
+		includes = "./include",
+		export_includes = "./include",
+		use = "genfile statfile appcontext"
 	)
 	
 	for subdir in subdirs:	
-		bld.add_subdirs( subdir )
-	
-	#---------------------
-	# libs
-	#---------------------
-
-	bld.new_task_gen(
-		features = 'cxx cstaticlib',
-		target = 'gen-tools-lib',
-		source = bld.glob( 'src/*.cpp' ),
-		includes='./include ./genfile/include',
-		uselib_local = 'string_utils statfile appcontext fputils worker genfile integration db',
-		uselib = 'BOOST BOOST_IOSTREAMS ZLIB BOOST_MATH BOOST_FILESYSTEM BOOST_SYSTEM MGL CBLAS CLAPACK MGL'
-	)
-
-	#---------------------
-	# programs
-	#---------------------
-	USELIB = "BOOST BOOST_IOSTREAMS ZLIB BOOST_FILESYSTEM BOOST_SYSTEM BOOST_UNIT_TEST_FRAMEWORK BOOST_THREAD BOOST_TIMER BOOST_CHRONO PTHREAD CBLAS CLAPACK MGL RT"
-	Components = 'SNPSummaryComponent SampleSummaryComponent HaplotypeFrequencyComponent RelatednessComponent SNPOutputComponent'
-	create_app( bld, name='qctool', uselib = USELIB, uselib_local = Components + ' gen-tools-lib qcdb appcontext statfile appcontext string_utils fputils worker genfile metro qctool_version_autogenerated' )
-	create_app( bld, name='inthinnerator', uselib = USELIB, uselib_local = Components + ' qctool_version_autogenerated gen-tools-lib genfile qcdb statfile appcontext db' )
-
-	if Options.options.all_targets:
-		pass
-		#create_app( bld, name='overrep', uselib = 'BOOST_REGEX ' + USELIB, uselib_local = 'qctool_version_autogenerated qcdb appcontext gen-tools-lib genfile statfile' )
-		#create_app( bld, name='gen-grep', uselib = USELIB, uselib_local = 'gen-tools-lib genfile appcontext string_utils' )
-		#create_app( bld, name='inflation', uselib = USELIB, uselib_local = 'qctool_version_autogenerated appcontext genfile' )
-		#create_app( bld, name='selfmap', uselib = USELIB, uselib_local = 'SNPSummaryComponent qctool_version_autogenerated qcdb appcontext genfile' )
-		#create_app( bld, name='checkvcf', uselib = USELIB, uselib_local = 'SNPSummaryComponent qctool_version_autogenerated qcdb appcontext statfile genfile' )
-		#create_app( bld, name='binit', uselib = USELIB, uselib_local = 'qctool_version_autogenerated appcontext genfile' )
-	
-	# Build release variants as well.
-	for obj in [] + bld.all_task_gen:
-	    install_path = obj.install_path
-	    new_obj = obj.clone('release')
-	    new_obj.install_path = install_path
-	    obj.install_path = None
-
-	#---------------------
-	# tests
-	#---------------------
-	# misc tests...
-
-	# create_tests( bld, uselib = USELIB, components = Components )
-
-def create_app( bld, name, uselib = '', uselib_local = '' ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target =  '%s_v%s' % ( name, VERSION ),
-		source = [  'apps/' + name + '.cpp' ],
-		includes='./ ./include ./genfile/include ./statfile/include',
-		uselib_local = uselib_local,
-		uselib = uselib + ' boost',
-		install_path = os.path.join( bld.env[ 'PREFIX' ], 'bin' )
-	)
-
-def create_tests( bld, uselib = '', components = '' ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = 'test_qctool',
-		source = bld.glob( 'test/*.cpp' ),
-		uselib_local = 'gen-tools-lib genfile appcontext string_utils ' + components + ' boost-unit_test_framework',
-		includes='./include ./genfile/include',
-		uselib = uselib + ' BOOST_UNIT_TEST_FRAMEWORK',
-		unit_test=1,
-		install_path=None
-	)
-
-def create_benchmark( bld, name, uselib = '' ):
-	bld.new_task_gen(
-		features = 'cxx cprogram',
-		target = name,
-		source = [  'benchmarks/' + name + '.cpp' ],
-		uselib_local = 'gen-tools-lib string_utils genfile',
-		uselib = uselib + ' BOOST_UNIT_TEST_FRAMEWORK',
-		includes='./include ./genfile/include',
-		install_path=None
-	)
-
-#-----------------------------------
-# CHECK
-#-----------------------------------
-
-def test(context):
-	print( "Performing functional tests..." )
-	import json
-	working_dir = "release/test_data"
-	qctool_executable = "build/release/qctool-%s" % VERSION
-	json = json.loads( open( os.path.join( working_dir, "catalogue.json" ) ).read() )
-	import sys
-	sys.path.append( "release" )
-	import Release.TestHarness
-	harness = Release.TestHarness.TestHarness( qctool_executable, working_dir, json )
-	harness.run()
-
-	# UnitTest module no longer works in waf 1.5.18.  Need to update this.
-	#import UnitTest
-	#ut = UnitTest.unit_test()
-	#ut.change_to_testfile_dir = True
-	#ut.run()
-	#ut.print_results()
+		bld.recurse( subdir )
+	
+def compute_revision(task):
+	import os, sqlite3
+	revision = "unknown"
+	filename = "../.fslckout"
+	if os.path.exists( filename ):
+		db = sqlite3.connect( filename )
+		c = db.cursor()
+		c.execute( "SELECT value FROM vvar WHERE name == 'checkout-hash'" )
+		result = c.fetchone()
+		revision = result[0][0:10]
+	target = open( task.outputs[0].abspath(), "w" )
+	target.write(
+"""
+#ifndef PACKAGE_REVISION_HPP
+#define PACKAGE_REVISION_HPP
+namespace globals {
+char const* const package_version = "%s" ;
+char const* const package_revision = "%s" ;
+}
+#endif
+""" % ( VERSION, revision ) )
+	return 0 # success
+
 
 def release( bld ):
 	import sys
-	import Options
+	from waflib.Options import options
 	sys.path.append( "release" )
 	import Release.TestHarness
 	import Release.ReleaseBuilder
 	
-	if Options.options.all_targets:
-		inthinnerator_executable = "build/release/inthinnerator_v%s" % VERSION
-		builder = Release.ReleaseBuilder.ReleaseBuilder( "inthinnerator", VERSION, inthinnerator_executable )
-		release = builder.build()
-		print( "++ inthinnerator release tarball created in", release[ "release_tarball" ] )
-
-	qctool_executable = "build/release/qctool_v%s" % VERSION
-	builder = Release.ReleaseBuilder.ReleaseBuilder( APPNAME, VERSION, qctool_executable )
-	release = builder.build()
-	print( "++ qctool release tarball created in", release[ "release_tarball" ] )
-
-	print( "++ Release tarball created in", release[ "release_tarball" ] )
+	if options.all_targets:
+		apps = [ 'qctool', 'inthinnerator', 'ldbird', 'hptest' ]
+	else:
+		apps = [ 'qctool' ]
+	for app in apps:
+		executable = "build/release/apps/%s_v%s" % ( app, VERSION )
+		builder = Release.ReleaseBuilder.ReleaseBuilder( app, VERSION, executable )
+		release = builder.build()
+		print( "++ %s release tarball created in", release[ "release_tarball" ] )